[
  {
    "path": ".github/ISSUE_TEMPLATE/bug_report.md",
    "content": "---\nname: Bug report\nabout: Create a report to help us improve\n\n---\n\n**Describe the bug**\nA clear and concise description of what the bug is.\n\n**To Reproduce**\nSteps to reproduce the behavior:\n1. Which git commit version is used?\n2. What are the compilation options (compiler, flags)?\n3. Which application is affected?\n4. What are the actual settings (please provide a minimal example if possible)?\n5. Please provide the error message or describe the crash behavior. \n\n**Expected behavior**\nA clear and concise description of what you expected to happen.\n\n**Additional context**\nAdd any other context about the problem here.\n"
  },
  {
    "path": ".github/ISSUE_TEMPLATE/feature_request.md",
    "content": "---\nname: Feature request\nabout: Suggest an idea for this project\n\n---\n\n**Is your feature request related to a problem? Please describe.**\nA clear and concise description of what the problem is. Ex. I'm always frustrated when [...]\n\n**Describe the solution you'd like**\nA clear and concise description of what you want to happen.\n\n**Describe alternatives you've considered**\nA clear and concise description of any alternative solutions or features you've considered.\n\n**Reference**\nIf you'd like some specific method to be implemented, please point to a useful reference.\n"
  },
  {
    "path": ".github/ISSUE_TEMPLATE/question.md",
    "content": "---\nname: Question\nabout: Ask a general question about the project\n\n---\n\n**The question**\nAsk what you want to know about the code.. e.g. \"Can I do [...] with this software?\" or \"Is [...] supported?\"\n\n**What did you already try?**\nHave you already installed the project and tried something out?\n\n**Background**\nWhat system are you working on?\n"
  },
  {
    "path": ".github/workflows/n2p2-ci.yaml",
    "content": "name: n2p2-ci\non:\n  push:\n  pull_request:\n    branches:\n      - master\n\njobs:\n  build:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v3\n      \n      - name: Install required system packages\n        run: |\n          # Docs\n          # API docs with doxygen (built via makefile, needs cmake),\n          # generating graphs with doxygen requires dot.\n          sudo apt install cmake graphviz\n\n          # Build \n          # MPI\n          sudo apt install openmpi-bin libopenmpi-dev\n          # BLAS\n          sudo apt install libblas3 libblas-dev\n          # OpenBLAS\n          sudo apt install libopenblas0 libopenblas-dev\n          # Eigen library\n          sudo apt install libeigen3-dev\n          # GSL library\n          sudo apt install libgsl-dev libgslcblas0\n\n          # Tests\n          # Boost Test for C++ testing\n          sudo apt install libboost-test-dev libboost-filesystem-dev\n          # Coverage for C++\n          sudo apt install lcov\n      \n      - name: Install required Python packages\n        run: |\n          # Docs\n          pip install sphinx\n          pip install sphinx_rtd_theme\n          pip install breathe\n\n          # pynnp\n          pip install cython==3.0.11\n\n          # python tests\n          pip install pytest #==7.1.3\n          pip install pytest-cov #==4.0.0\n          pip install coverage #==7.6.1\n\n      - name: Build n2p2 libraries and applications\n        run: make MODE=test -j4\n        working-directory: ./src\n      \n      - name: Build documentation\n        run: |\n          # Pre-build doxygen only on 4 cores (-j hangs on Github Actions).\n          cd doc/doxygen/\n          make CORES=4 doxygen\n          cd ../..\n          # Now build the rest of the documentation.\n          make doc\n          # Prevent GitHub Jekyll to interfere with Sphinx theme.\n          touch ../doc/sphinx/html/.nojekyll\n        working-directory: ./src\n      \n      - name: Build LAMMPS with n2p2 support\n        run: make MODE=test lammps-hdnnp\n        working-directory: ./src\n      \n      - name: Run C++ tests and coverage\n        run: |\n          make cpp\n          cd cpp\n          make coverage\n          rm *.gcda *.gcno\n        working-directory: ./test\n      \n      - name: Build pynnp\n        run: make pynnp MODE=test\n        working-directory: ./src\n      \n      - name: Run python tests\n        run: make python\n        working-directory: ./test\n      \n      - name: Upload C++ coverage to Codecov\n        uses: codecov/codecov-action@v2\n        with:\n          files: test/cpp/tests.info\n          flags: cpp\n          verbose: true\n      \n      - name: Upload Python coverage to Codecov\n        uses: codecov/codecov-action@v2\n        with:\n          directory: test/python\n          flags: python\n          verbose: true\n\n      - name: Deploy Github pages\n        if: ${{ github.ref == 'refs/heads/master' }}\n        uses: JamesIves/github-pages-deploy-action@v4.3.3\n        with:\n          branch: gh-pages\n          folder: doc/sphinx/html\n"
  },
  {
    "path": ".gitignore",
    "content": "*.o\ncompile_commands.json\n.clangd\n.idea/\nsrc/interface/stable_29Sep2021.tar.gz\n"
  },
  {
    "path": "AUTHORS.rst",
    "content": "Authors\n=======\n\nThis software was originally created by `Andreas Singraber\n<andreas.singraber@gmx.at>`_ during his PhD programme at the University of\nVienna. Code development started in 2015 and the first release to the public\nwas in 2018.\n\nContributions are much appreciated and will be recorded here:\n\n* CabanaMD interface (`libnnpif/CabanaMD`): Saaketh Desai and Sam Reeve\n* Polynomial symmetry functions (`libnnp/Sym(Fnc/Grp)(Base)Comp...`): Martin P.\n  Bircher and Andreas Singraber\n* 4G-HDNNP training/prediction implementation in n2p2: Philipp Misof\n* 4G-HDNNP prediction implementation in LAMMPS+n2p2: Emir Kocer\n"
  },
  {
    "path": "CHANGELOG.rst",
    "content": "Changelog\n=========\n\nAll notable changes to this project will be documented in this file.\n\nVersion 3.0.0 - 2024-1?-??\n--------------------------\n\nNew features\n^^^^^^^^^^^^\n\n* 4G-HDNNPs training/prediction in n2p2 (Philipp Misof).\n* 4G-HDNNPs prediction in LAMMPS+n2p2 (Emir Kocer).\n\nVersion 2.3.0 - 2024-11-23\n--------------------------\n\nNew features\n^^^^^^^^^^^^\n\n* Allow manual definition of train/test set (add ``set=train/test`` after ``begin`` in\n  input.data).\n* Additional symmetry function log output, extra column ``spread``.\n* Structure ``remap()`` function is now available in pynnp.\n\nMaintenance\n^^^^^^^^^^^\n\n* Fixed CI: Cython updated to version 3.0+, added ``__rmul__`` to ``Vec3D`` in\n  pynnp.\n\nImportant changes\n^^^^^^^^^^^^^^^^^\n\n* Synchronized LAMMPS developer build with LAMMPS-distributed source: Finally\n  switched to pair style ``hdnnp`` everywhere.\n\nDocumentation\n^^^^^^^^^^^^^\n\n* Removed old ``nnp`` pair style description page.\n* Updated LAMMPS interface build instructions page.\n* Added train/test set split documentation.\n\nVersion 2.2.0 - 2022-05-23\n--------------------------\n\nNew features\n^^^^^^^^^^^^\n\n* Normalization procedure on-the-fly via nnp-train, keyword ``normalize_data_set``.\n* New normalization scheme based on force predictions.\n* New keyword ``force_energy_ratio`` for nnp-train.\n* Additional neighbor statistics output from nnp-scaling.\n* New tool nnp-checkdw (for testing purposes).\n\nImportant changes\n^^^^^^^^^^^^^^^^^\n\n* New CI via Github Actions.\n* Use self-compiled doxygen for API docs, use version 1.9.4.\n\nBugfixes\n^^^^^^^^\n\n* Fixed missing atomic energy offsets for LAMMPS interface.\n* Fixed NaNs from nnp-dist when running mixed data sets.\n* Fixed bugs in pynnp examples.\n\nVersion 2.1.4 - 2021-05-11\n--------------------------\n\nNew features\n^^^^^^^^^^^^\n\n* Changed build behavior for LAMMPS interface to conform with PR (lammps/lammps#2626)\n\n\nVersion 2.1.3 - 2021-04-26\n--------------------------\n\nBugfixes\n^^^^^^^^\n\n* Fixed bug in nnp-scaling which could cause segfaults (MPI only).\n\n\nVersion 2.1.2 - 2021-04-12\n--------------------------\n\nNew features\n^^^^^^^^^^^^\n\n* New tool to check numeric vs. analytic forces\n\nBugfixes\n^^^^^^^^\n\n* Fixed critical bug for large cutoff values (large compared to lattice vectors)\n\n\nVersion 2.1.1 - 2021-01-15\n--------------------------\n\nNew features\n^^^^^^^^^^^^\n\n* Now compatible with latest LAMMPS stable release 29Oct2020\n* Improved EW warnings in LAMMPS\n* Citation header in screen output\n* Restructured training to prepare for multi-network HDNNPs (e.g. 4G-HDNNP)\n* New training \"properties\" can be added more easily now\n\nBugfixes\n^^^^^^^^\n\n* Fixed bugs in makefiles\n* Fixed bug when creating scaling data\n\n\nVersion 2.1.0 - 2020-12-21\n--------------------------\n\nNew features\n^^^^^^^^^^^^\n\n* Polynomial symmetry functions (Martin P. Bircher and Andreas Singraber)\n* Better symmetry function cache mechanism\n\nImportant changes\n^^^^^^^^^^^^^^^^^\n\n* Documentation updates (API docs in Sphinx via Breathe)\n\n\nVersion 2.0.3 - 2020-11-30\n--------------------------\n\nNew features\n^^^^^^^^^^^^\n\n* Tool nnp-scaling puts out rejected configurations into a separate file.\n\n\nVersion 2.0.2 - 2020-11-25\n--------------------------\n\nBugfixes\n^^^^^^^^\n\n* Bugfix in CabanaMD interface: SF group initialization\n\n\nVersion 2.0.1 - 2020-10-05\n--------------------------\n\nBugfixes\n^^^^^^^^\n\n* Fix bug in makefile which sometimes causes a failed build due to parallel execution\n\n\nVersion 2.0.0 - 2020-10-05\n--------------------------\n\nNew features\n^^^^^^^^^^^^\n\n* Training library (Multi-stream Kalman filter training).\n* Tools for HDNNP data set handling, etc.\n* Python interface (basic functionality).\n* Sphinx documentation (+ Doxygen API reference).\n* CabanaMD interface (by Saaketh Desai and Sam Reeve)\n\nImportant changes\n^^^^^^^^^^^^^^^^^\n\n* License change from MPL 2.0 to GPL v3 or later.\n\n\nVersion 1.0.0 - 2018-08-13\n--------------------------\n\nNew features\n^^^^^^^^^^^^\n\n* Core library (NN, symmetry functions, ...).\n* LAMMPS interface.\n* Documentation (in parts) via doxygen.\n"
  },
  {
    "path": "LICENSE",
    "content": "                    GNU GENERAL PUBLIC LICENSE\n                       Version 3, 29 June 2007\n\n Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>\n Everyone is permitted to copy and distribute verbatim copies\n of this license document, but changing it is not allowed.\n\n                            Preamble\n\n  The GNU General Public License is a free, copyleft license for\nsoftware and other kinds of works.\n\n  The licenses for most software and other practical works are designed\nto take away your freedom to share and change the works.  By contrast,\nthe GNU General Public License is intended to guarantee your freedom to\nshare and change all versions of a program--to make sure it remains free\nsoftware for all its users.  We, the Free Software Foundation, use the\nGNU General Public License for most of our software; it applies also to\nany other work released this way by its authors.  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  },
  {
    "path": "README.md",
    "content": "n2p2 - A neural network potential package\n=========================================\n\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1344446.svg)](https://doi.org/10.5281/zenodo.1344446)\n[![GitHub release](https://img.shields.io/github/release/CompPhysVienna/n2p2.svg)](https://GitHub.com/CompPhysVienna/n2p2/releases/)\n[![Build Status](https://app.travis-ci.com/CompPhysVienna/n2p2.svg?branch=master)](https://app.travis-ci.com/CompPhysVienna/n2p2)\n[![Coverage](https://codecov.io/gh/CompPhysVienna/n2p2/branch/master/graph/badge.svg)](https://codecov.io/gh/CompPhysVienna/n2p2)\n[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)\n\nThis repository provides ready-to-use software for high-dimensional neural\nnetwork potentials in computational physics and chemistry.\n\n# [Documentation](http://compphysvienna.github.io/n2p2)\n\nThis package uses automatic documentation generation via\n[Sphinx](http://www.sphinx-doc.org),\n[Breathe](https://breathe.readthedocs.io/en/latest/#) and\n[doxygen](http://www.doxygen.nl/). An online version of the documentation which\nis automatically updated with the master branch of the repository can be found\n[__here__](http://compphysvienna.github.io/n2p2).\n\n# Authors\n\nSee [AUTHORS.rst](https://github.com/CompPhysVienna/n2p2/blob/master/AUTHORS.rst) for a list of contributions.\n\n# License\n\nThis software is licensed under the [GNU General Public License version 3 or any later version (GPL-3.0-or-later)](https://www.gnu.org/licenses/gpl.txt).\n"
  },
  {
    "path": "bin/.gitignore",
    "content": ""
  },
  {
    "path": "doc/.gitignore",
    "content": ""
  },
  {
    "path": "doc/doxygen/.gitignore",
    "content": ""
  },
  {
    "path": "examples/coarse-graining/README.md",
    "content": "Descriptor analysis/Coarse-graining\n===================================\n\nPlease have a look at the online documentation:\n\nhttps://compphysvienna.github.io/n2p2/misc/cg_descriptor_analysis.html\n"
  },
  {
    "path": "examples/coarse-graining/step-0_cg-data-set/input.data",
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6.7497471886841078E-03   1.0666150827331258E-03\natom   3.5358980099999982E+01   3.7663172299999992E+01   3.1091568599999992E+01  H   0.0000000000000000E+00   0.0000000000000000E+00  -1.0323550464067858E-02  -9.6460217422694866E-03  -1.8848351317658947E-02\natom   3.6343155899999992E+01   3.8583406799999992E+01   3.3461821699999987E+01  H   0.0000000000000000E+00   0.0000000000000000E+00   9.4847816470513494E-03  -2.9566630345860480E-03   1.4341422257178363E-02\nenergy  -2.7564827043397370E+04\ncharge   0.0000000000000000E+00\nend\n"
  },
  {
    "path": "examples/coarse-graining/step-0_cg-data-set/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=../../../\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# GENERAL SETTINGS\n###############################################################################\n# Default compiler, may be overridden by master makefile or command line.\nCOMP=gnu\n\n# Default build mode, may be overridden by master makefile or command line.\n# Possible modes are \"static\", \"shared\" and \"test\".\nMODE=static\n\n# Include global (project-wide) settings.\ninclude $(PROJECT_DIR)/src/makefile.$(COMP)\n\n\n###############################################################################\n# PROJECT COMPILER AND FLAGS\n###############################################################################\n# Include directories and linking flags are target specific (see below).\nCC=$(PROJECT_CC)\nMPICC=$(PROJECT_MPICC)\nCFLAGS=$(PROJECT_CFLAGS)\nOPTIONS+=$(PROJECT_OPTIONS)\nDEBUG=$(PROJECT_DEBUG)\nifeq ($(MODE), test)\n\tDEBUG+= $(PROJECT_TEST)\nendif\n\n\n###############################################################################\n# APPLICATION TYPES\n###############################################################################\n# Applications which require only libnnp:\nAPP_CORE=nnp-cgdata\n\n# Targets for cleaning.\nCLEAN_APP=$(patsubst %, clean-%, $(APP_CORE))\n\n\n###############################################################################\n# RULES\n###############################################################################\n.PHONY: all $(CLEAN_APP) list-core\n\nall: $(APP_CORE)\n\n# Applications which require only libnnp:\n$(APP_CORE): INCLUDES=-I./ -I$(PROJECT_INCLUDE)/\nifeq ($(MODE), shared)\n$(APP_CORE): LDFLAGS=-L$(PROJECT_LIB) -lnnp\nelse\n$(APP_CORE): LDFLAGS=$(PROJECT_LIB)/libnnp.a\nendif\n$(APP_CORE):\n\t$(CC) $(CFLAGS) $(DEBUG) $(INCLUDES) $(OPTIONS) -o $@.o -c $@.cpp\n\t$(CC) $(CFLAGS) $(DEBUG) $(OPTIONS) -o $@ $@.o $(LDFLAGS)\n\t#cp $@ $(PROJECT_BIN)/\n\n# Clean everything.\nclean: $(CLEAN_APP)\n\n# Clean rules for all applications.\n$(CLEAN_APP): EXE=$(patsubst clean-%,%,$@)\n$(CLEAN_APP):\n\t$(RM) $(EXE).gcno $(EXE).gcda $(EXE).o $(EXE)\n\t#$(RM) $(PROJECT_BIN)/$(EXE)\n\nlist-core:\n\t@echo $(APP_CORE)\n"
  },
  {
    "path": "examples/coarse-graining/step-0_cg-data-set/nnp-cgdata.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"ElementMap.h\"\n#include \"Log.h\"\n#include \"Structure.h\"\n#include \"utility.h\"\n#include <algorithm>\n#include <cmath>\n#include <cstdlib>\n#include <stdexcept>\n#include <iostream>\n#include <fstream>\n#include <map>\n#include <string>\n#include <utility>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\ndouble const massH = 1.00784;\ndouble const massO = 15.99903;\ndouble const massCG = massO + 2.0 * massH;\nstring const elements = \"H O\";\nstring const elementCG = \"Cm\";\n\nint main(int argc, char* argv[])\n{\n    if (argc < 2)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <rcut>\\n\"\n             << \"       <rcut> .... Cutoff radius.\\n\";\n        return 1;\n    }\n\n    double const cutoffRadius = atof(argv[1]);\n\n    ofstream logFile;\n    logFile.open(\"nnp-cgdata.log\");\n    Log log;\n    log.registerStreamPointer(&logFile);\n\n    log << \"\\n\";\n    log << \"*** NNP-CGDATA **************************\"\n           \"**************************************\\n\";\n    log << strpr(\"Cutoff radius: %f\\n\", cutoffRadius);\n    log << \"\\n\";\n\n\n    ifstream inputFile;\n    inputFile.open(\"input.data\");\n    ElementMap elementMap;\n    elementMap.registerElements(elements);\n    Structure structure;\n    structure.setElementMap(elementMap);\n\n    ofstream outputFile;\n    outputFile.open(\"output.data\");\n    ElementMap elementMapCG;\n    elementMapCG.registerElements(elementCG);\n    Structure structureCG;\n    structureCG.setElementMap(elementMapCG);\n\n    size_t countStructures = 0;\n    while (inputFile.peek() != EOF)\n    {\n        structure.readFromFile(inputFile);\n        structure.calculateNeighborList(cutoffRadius);\n        // Copy structure properties.\n        structureCG.comment = structure.comment;\n        structureCG.isPeriodic = structure.isPeriodic;\n        structureCG.isTriclinic = structure.isTriclinic;\n        structureCG.volume = structure.volume;\n        for (size_t i = 0; i < 3; ++i)\n        {\n            for (size_t j = 0; j < 3; ++j)\n            {\n                structureCG.box[i][j] = structure.box[i][j];\n                structureCG.invbox[i][j] = structure.invbox[i][j];\n            }\n        }\n        // Set atom tag to zero (used here for duplicate hydrogen usage check.\n        for (vector<Atom>::iterator it = structure.atoms.begin();\n             it != structure.atoms.end(); ++it)\n        {\n            it->tag = 0;\n        }\n        // Main loop over atoms.\n        for (vector<Atom>::iterator it = structure.atoms.begin();\n             it != structure.atoms.end(); ++it)\n        {\n            if (elementMap[it->element] == \"O\")\n            {\n                vector<Atom::Neighbor const*> hn;\n                sort(it->neighbors.begin(), it->neighbors.end());\n                for (size_t i = 0; i < it->numNeighbors; ++i)\n                {\n                    Atom::Neighbor& n = it->neighbors.at(i);\n                    if (elementMap[n.element] == \"H\")\n                    {\n                        hn.push_back(&n);\n                    }\n                }\n                if (hn.size() != 2)\n                {\n                    throw runtime_error(strpr(\"ERROR: Could not find two \"\n                                              \"hydrogen neighbors (structure \"\n                                              \"%zu, atom %zu, #Hs = %zu!\",\n                                              countStructures,\n                                              it->index,\n                                              hn.size()));\n                }\n                vector<Atom*> ha;\n                // Check if a hydrogen atom is already part of a molecule.\n                for (size_t i = 0; i < hn.size(); ++i)\n                {\n                    ha.push_back(&structure.atoms.at(hn[i]->index));\n                    if (ha.back()->tag > 0)\n                    {\n                        throw runtime_error(strpr(\"ERROR: Hydrogen atom %zu (\"\n                                                  \"structure %zu) is already \"\n                                                  \"part of another \"\n                                                  \"molecule!\\n\",\n                                                  ha.back()->index,\n                                                  countStructures));\n                    }\n                }\n                Atom atomCG;\n                atomCG.r = it->r\n                         - 2.0 * massH * (hn[0]->dr + hn[1]->dr) / massCG;\n                if (structureCG.isPeriodic) structureCG.remap(atomCG);\n                atomCG.fRef = it->fRef + ha[0]->fRef + ha[1]->fRef;\n                structureCG.addAtom(atomCG, elementCG);\n                // Increment hydrogen counter.\n                ha[0]->tag++;\n                ha[1]->tag++;\n            }\n        }\n        structureCG.numElementsPresent = 1;\n        structureCG.writeToFile(&outputFile, true);\n        countStructures++;\n        log << strpr(\"Configuration %7zu: %7zu atoms\\n\",\n                     countStructures,\n                     structure.numAtoms);\n        structure.reset();\n        structureCG.reset();\n    }\n    outputFile.close();\n\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n    logFile.close();\n\n    return 0;\n}\n"
  },
  {
    "path": "examples/coarse-graining/step-1_scaling-data/input.data",
    "content": "begin\ncomment \nlattice   4.3300044700000001E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   0.0000000000000000E+00   4.4998692699999999E+01   0.0000000000000000E+00\nlattice   0.0000000000000000E+00   0.0000000000000000E+00   4.2425182200000002E+01\natom   3.4520548506176327E+00   6.4953514118403612E+00   1.0185182686319557E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   1.0757494795234478E-03  -8.1136616458475051E-03  -1.4615725023380752E-03\natom   2.5244848806974898E+00   4.1049989663337605E+01   2.3671232117177180E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   7.8654455038887697E-03  -3.5238397933609351E-04   1.7812039370898401E-03\natom   1.1193191940536424E+01   2.7602227605023493E+00   4.2026705264867523E+00 Cm   0.0000000000000000E+00   0.0000000000000000E+00   4.5113998872697101E-03  -2.8575636893147715E-03   1.5433486128823251E-03\natom   6.1611344861343795E+00   2.7979335921346209E+01   8.6080961359906443E+00 Cm   0.0000000000000000E+00   0.0000000000000000E+00   2.5141930638709030E-03  -2.4247325846724795E-03  -2.4260317837500505E-03\natom   9.2612516412625734E+00   3.6831779356645747E+01   4.0140462420995561E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -1.8288569349835838E-04   3.1800875767620234E-03  -3.9738787279870683E-03\natom   2.5078374725268734E+01   2.8099107890323836E+01   3.2028300217395000E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   9.3753735708852759E-04   5.1812216314924883E-03  -1.6752923204681469E-03\natom   6.0676087984174352E+00   8.2555283618554114E+00   3.0344963904657021E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   2.3460836626651507E-03  -2.0717851064912494E-03   2.1622773455346519E-03\natom   3.9378247047059958E+01   1.6159376309253158E+01   2.8883885932931133E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   1.4807625589110130E-03   1.0510196837180954E-03  -2.2688299284999835E-03\natom   2.5431038097983471E+01   3.3847209831745992E+01   2.6872823226477252E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -4.5331475985143678E-04   5.5461229298504671E-04  -3.2828491323306334E-03\natom   2.6811903826404354E+01   3.4099972399661141E+01   6.8568519227169000E+00 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -2.3264563652022341E-03  -1.4800360276007573E-03  -3.6468510555376387E-03\natom   1.0383511154382173E+01   4.3095472353816113E+01   2.1481808887456136E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   8.4985105331515740E-04  -5.1818010891796148E-04   2.6421593294193562E-03\natom   2.8940680431670827E+01   9.8645794129669504E+00   4.2113693583241371E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -2.2940354609011435E-03   4.1282679021848075E-03   8.8954225871923712E-04\natom   8.5901007894028343E+00   8.4593046218744181E+00   2.4857996569843692E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -1.1164309883313420E-03   3.8604783493594429E-03   3.4957067287302614E-03\natom   1.0251931463511372E+01   2.3538569943121420E+01   2.4125965085051039E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   4.7260530357863539E-04  -2.7794200150293227E-03   3.8139188353849170E-03\natom   2.8013043068393820E+01   5.7936600168418897E+00   1.9131127336453538E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   9.5755210468463081E-03  -7.3320445368892789E-04  -1.1228115497918093E-03\natom   3.1137825366430086E+01   4.8232236184361108E+00   1.4268097871086068E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -1.4315713392876930E-03  -8.8673480927059338E-04   1.1715662890165790E-02\natom   3.5655028868785990E+01   3.0228110443926756E+01   1.5208012552052947E+00 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -3.4153215204603413E-03   9.5025969540961418E-04   4.9010545858741202E-03\natom   1.7308789171861605E+01   5.2772047583981516E+00   1.9593275989124830E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -3.4477451600576367E-05   4.2020403887937478E-03  -1.6106751123870153E-03\natom   1.1645664198552014E+01   2.1320303196251714E+01   3.3030544549476835E+00 Cm   0.0000000000000000E+00   0.0000000000000000E+00   3.0101757854560963E-04   2.5247272566340400E-03  -3.0738600717560610E-03\natom   1.8508068192862275E+01   1.8113706604397013E+01   2.1400739541504802E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -5.5916279544094647E-03   1.7742118978310885E-03  -2.4300731865005503E-03\natom   3.2341493018274662E+01   3.2648540187571037E+01   2.3705917210289307E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -3.1127886967975658E-03   2.7974216215357456E-03   2.3105939157955289E-03\natom   8.3846035592660719E+00   1.6300398129061247E+01   1.4146025857839284E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   1.5125827850675233E-03   7.6422065019416509E-03   3.3923432753534336E-04\natom   3.0041637132016209E+01   1.9131729480474839E+01   2.6196710381320759E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   7.5817250786499365E-04  -1.3020321509108410E-03   3.9519846984783086E-03\natom   1.7496751784572268E+01   1.0590926702532816E+01   2.0581003054538868E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -1.4381986657681957E-03  -6.7720911366835656E-03  -2.1037303458585430E-03\natom   3.3253151413863705E+01   9.9228671671566087E+00   1.3421426311186798E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00   2.7371466478916368E-03   2.2895405495067874E-04  -5.1239322444934978E-03\natom   2.1235764562144261E+01   4.1374550846445970E+01   1.7263174567209514E+00 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -1.2013708863028126E-03  -4.2436862039089644E-03   3.2638396211977228E-03\natom   1.8647384499852002E+01   2.8518108589667932E+01   3.6029083221144489E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -8.9384420466756750E-03  -3.3854471339787480E-03  -5.0187327643043921E-03\natom   6.9839929448412681E+00   3.8259348213616185E+01   3.0438790787703429E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -4.7313728413396830E-04  -5.3241992801866880E-03  -8.8013586294104652E-04\natom   8.4027063998429323E+00   8.5421344780326045E+00   3.3109095931757864E+00 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -4.4424850938734085E-03   2.1114987057037210E-03  -1.0498072228437331E-03\natom   1.5047539882219247E+01   4.4605811783796788E+01   3.4948433729879525E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -2.8682838517773285E-04   1.6695875156056534E-03   1.2249703495777562E-03\natom   3.1676694781584537E+01   3.2906392915417615E+00   5.8334853634531925E+00 Cm   0.0000000000000000E+00   0.0000000000000000E+00   2.3249009431830711E-03   2.2219489866644199E-03  -1.8913229017591851E-03\natom   4.2218062851914006E+01   1.8007092456553394E+01   2.0341663376279218E+01 Cm   0.0000000000000000E+00   0.0000000000000000E+00  -2.7975319945331770E-03  -8.9824575445565658E-04   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  },
  {
    "path": "examples/coarse-graining/step-1_scaling-data/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              1              # Number of elements.\nelements                        Cm             # Specification of elements.\n#atom_energy                     Cm 0.0         # Free atom reference energy (Cm).\ncutoff_type                     2 0.0          # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Radial symmetry functions for element Cm \nsymfunction_short Cm 2 Cm 0.001 0.0 12.00\nsymfunction_short Cm 2 Cm 0.01  0.0 12.00\nsymfunction_short Cm 2 Cm 0.03  0.0 12.00\nsymfunction_short Cm 2 Cm 0.06  0.0 12.00\nsymfunction_short Cm 2 Cm 0.15  4.0 12.00\nsymfunction_short Cm 2 Cm 0.30  4.0 12.00\nsymfunction_short Cm 2 Cm 0.60  4.0 12.00\nsymfunction_short Cm 2 Cm 1.50  4.0 12.00\n\n# Narrow angular symmetry functions for element Cm \nsymfunction_short Cm 3 Cm Cm 0.03  1.0 1.0   12.00000\nsymfunction_short Cm 3 Cm Cm 0.03 -1.0 1.0   12.00000\nsymfunction_short Cm 3 Cm Cm 0.001  1.0 4.0  12.00000\nsymfunction_short Cm 3 Cm Cm 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/coarse-graining/step-2_atomic-env/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   5.4005112633370322E-01   1.1646552925931319E+00   8.2490782007633423E-01   7.9817654662490939E-02\n         1          2   3.4373468726633372E-01   8.0681438592811827E-01   5.5798559011744298E-01   5.9568139789567480E-02\n         1          3   1.2808001450972825E-01   3.8331566178726878E-01   2.5508609184409264E-01   3.3725528344431994E-02\n         1          4   3.5450524530118190E-02   1.6101900383754972E-01   9.0353431023550299E-02   1.6253990236946941E-02\n         1          5   1.5922524741267469E-01   6.3650151424113222E-01   3.9284024555249086E-01   6.2311715965030781E-02\n         1          6   6.9182724190482311E-02   4.9907577110453788E-01   2.5656248194768250E-01   5.8050583260227856E-02\n         1          7   1.3111816333175368E-02   3.5326071390845604E-01   1.3438901095741926E-01   4.7168634985871240E-02\n         1          8   8.3967906351164291E-05   1.5238467200459038E-01   2.9470932682113090E-02   1.9958488467972508E-02\n         1          9   4.4627186630085814E-05   1.6487896139005657E-03   4.5921752298186608E-04   1.9397882891657528E-04\n         1         10   2.2716563112859496E-03   1.4275091803946810E-02   6.5507183293825252E-03   1.5890603352436709E-03\n         1         11   1.4019799526838609E-05   4.6790951535725060E-04   1.1974526385996796E-04   5.4218593772106395E-05\n         1         12   5.8216458222489737E-05   1.0712137652324029E-03   3.3713182826035880E-04   1.3892832303346564E-04\n"
  },
  {
    "path": "examples/coarse-graining/step-3_cluster-analysis/analyze-descriptors.ipynb",
    "content": "{\n \"cells\": [\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"This notebook requires some packages which may not be installed by default:\\n\",\n    \"\\n\",\n    \"* numpy\\n\",\n    \"* scipy\\n\",\n    \"* scikit-learn\\n\",\n    \"* seaborn\\n\",\n    \"* hdbscan (can be ommitted if only the k-means algorithm is used)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 1,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"%matplotlib nbagg\\n\",\n    \"import matplotlib\\n\",\n    \"from matplotlib.lines import Line2D\\n\",\n    \"import numpy as np\\n\",\n    \"import pickle\\n\",\n    \"import scipy.stats as stats\\n\",\n    \"import matplotlib.pyplot as plt\\n\",\n    \"import seaborn as sns              # conda install seaborn\\n\",\n    \"from sklearn.cluster import KMeans # conda install scikit-learn\\n\",\n    \"from sklearn.manifold import TSNE\\n\",\n    \"from hdbscan import HDBSCAN        # conda install -c conda-forge hdbscan\\n\",\n    \"\\n\",\n    \"matplotlib.rcParams.update({'font.size': 12})\\n\",\n    \"plt.rc('text', usetex=True)\\n\",\n    \"plt.rc('font', family='serif')\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"## Atomic environment descriptor analysis (H<sub>2</sub>O center of mass)\\n\",\n    \"\\n\",\n    \"### Introduction\\n\",\n    \"\\n\",\n    \"The overall goal of this analysis is to show qualitatively whether there is a correlation between the raw atomic environment descriptors (and their derivatives) and the atomic forces. If no or very little correlation can be found we can assume that the descriptors do not encode enough information to construct a (free) energy landscape. On the other hand, if \\\"similar\\\" descriptors correspond to \\\"similar\\\" forces there is a good chance that a machine learning algorithm is capable of detecting this link and a machine learning potential can be fitted.\\n\",\n    \"\\n\",\n    \"**NOTE:** If you just stumbled over this notebook without any context, please have a look at additional information in the [online documentation](https://compphysvienna.github.io/n2p2/misc/cg_descriptor_analysis.html).\\n\",\n    \"\\n\",\n    \"### Method\\n\",\n    \"\\n\",\n    \"In order to find a possible correlation between descriptors and forces the following approach is used: First, a clustering algorithm (k-means or HDBSCAN) searches for groups in the high-dimensional descriptor space of all atoms. Then, for every detected cluster the statistical distribution of the corresponding atomic forces is compared to the statistics of all remaining atomic forces. A hypothesis test (Welch's t-test) is applied to decide whether the link between descriptors and forces is statistically significant. The percentage of clusters which show a clear link is then an indicator for a good descriptor-force correlation. See the explanations below for further details on the individual steps.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 2,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"# Some global variables needed throughout the script:\\n\",\n    \"extract_element = \\\"Cm\\\"      # Determines which atoms to use for analysis in multicomponent systems.\\n\",\n    \"extract_component = 0       # Which force component to analyze (0 = x, 1 = y, 2 = z)\\n\",\n    \"extract_descriptor = \\\"dGdx\\\" # Which descriptor set to use (\\\"G\\\" ... symmetry functions, \\\"dGd(x,y,z)\\\" ... SF derivatives)\\n\",\n    \"pvalue_max = 0.002699796063 # Max p-value allowed for statistical test (3 sigma, for 5 sigma => 5.73303143e-07)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"First, a simple function to read in the atomic forces from an _n2p2_ / _RuNNer_ data set file (\\\"`input.data`\\\"). Only atoms of a specific element are considered (argument `element`). Note, that the whole analysis can only be performed for a single element at a time because it makes no sense to search for similarities in the environments of different species. The functions returns a 2-dimensional `numpy` array. The first index is a running atom number, the second index denotes the x,y and z-component (0, 1, 2). Note, that the returned array is unaware of the original arrangement of atoms in different structures.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 3,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"def read_forces(file_name=\\\"input.data\\\", element=\\\"H\\\"):\\n\",\n    \"    data = []\\n\",\n    \"    f = open(file_name, \\\"r\\\")\\n\",\n    \"    for line in f:\\n\",\n    \"        if line.split()[0] == \\\"begin\\\":\\n\",\n    \"            natoms = 0\\n\",\n    \"        elif line.split()[0] == \\\"atom\\\":\\n\",\n    \"            natoms += 1\\n\",\n    \"            if line.split()[4] == element:\\n\",\n    \"                data.append(np.array([float(number) for number in line.split()[7:10]]))\\n\",\n    \"        else:\\n\",\n    \"            pass\\n\",\n    \"    f.close()\\n\",\n    \"    return np.array(data)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"Now, let's read in a file and extract all atoms of the given element (see `extract_element` global variable above). The shape of the returned array should show a $N_\\\\text{atoms} \\\\times 3$ matrix.\\n\",\n    \"\\n\",\n    \"**WARNING:** Be careful when using huge data sets ($N_\\\\text{atoms} \\\\gg 10^4$) because the clustering algorithms below may become very slow (especially HDBSCAN).\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 4,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"(6840, 3)\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"forces = read_forces(\\\"input.data\\\", extract_element)\\n\",\n    \"print(np.shape(forces))\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"Next, we have a look at the force distributions in the data set. If the data set is taken from an MD simulation we expect a Gaussian-like distribution around zero.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 5,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"<f_x> :  8.62E-19 +/- 4.38E-03\\n\",\n      \"<f_y> : -1.30E-18 +/- 4.23E-03\\n\",\n      \"<f_z> : -1.03E-19 +/- 4.29E-03\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"application/javascript\": [\n       \"/* Put everything inside the global mpl namespace */\\n\",\n       \"window.mpl = {};\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.get_websocket_type = function() {\\n\",\n       \"    if (typeof(WebSocket) !== 'undefined') {\\n\",\n       \"        return WebSocket;\\n\",\n       \"    } else if (typeof(MozWebSocket) !== 'undefined') {\\n\",\n       \"        return MozWebSocket;\\n\",\n       \"    } else {\\n\",\n       \"        alert('Your browser does not have WebSocket support. 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' +\\n\",\n       \"        'text-align: center; padding: 3px;\\\"/>');\\n\",\n       \"    titlebar.append(titletext)\\n\",\n       \"    this.root.append(titlebar);\\n\",\n       \"    this.header = titletext[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_canvas = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var canvas_div = $('<div/>');\\n\",\n       \"\\n\",\n       \"    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\\n\",\n       \"\\n\",\n       \"    function canvas_keyboard_event(event) {\\n\",\n       \"        return fig.key_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    canvas_div.keydown('key_press', canvas_keyboard_event);\\n\",\n       \"    canvas_div.keyup('key_release', canvas_keyboard_event);\\n\",\n       \"    this.canvas_div = canvas_div\\n\",\n       \"    this._canvas_extra_style(canvas_div)\\n\",\n       \"    this.root.append(canvas_div);\\n\",\n       \"\\n\",\n       \"    var canvas = $('<canvas/>');\\n\",\n       \"    canvas.addClass('mpl-canvas');\\n\",\n       \"    canvas.attr('style', \\\"left: 0; top: 0; z-index: 0; outline: 0\\\")\\n\",\n       \"\\n\",\n       \"    this.canvas = canvas[0];\\n\",\n       \"    this.context = canvas[0].getContext(\\\"2d\\\");\\n\",\n       \"\\n\",\n       \"    var backingStore = this.context.backingStorePixelRatio ||\\n\",\n       \"\\tthis.context.webkitBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.mozBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.msBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.oBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.backingStorePixelRatio || 1;\\n\",\n       \"\\n\",\n       \"    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\\n\",\n       \"\\n\",\n       \"    var rubberband = $('<canvas/>');\\n\",\n       \"    rubberband.attr('style', \\\"position: absolute; left: 0; top: 0; z-index: 1;\\\")\\n\",\n       \"\\n\",\n       \"    var pass_mouse_events = true;\\n\",\n       \"\\n\",\n       \"    canvas_div.resizable({\\n\",\n       \"        start: function(event, ui) {\\n\",\n       \"            pass_mouse_events = false;\\n\",\n       \"        },\\n\",\n       \"        resize: function(event, ui) {\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"        stop: function(event, ui) {\\n\",\n       \"            pass_mouse_events = true;\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function mouse_event_fn(event) {\\n\",\n       \"        if (pass_mouse_events)\\n\",\n       \"            return fig.mouse_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    rubberband.mousedown('button_press', mouse_event_fn);\\n\",\n       \"    rubberband.mouseup('button_release', mouse_event_fn);\\n\",\n       \"    // Throttle sequential mouse events to 1 every 20ms.\\n\",\n       \"    rubberband.mousemove('motion_notify', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    rubberband.mouseenter('figure_enter', mouse_event_fn);\\n\",\n       \"    rubberband.mouseleave('figure_leave', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    canvas_div.on(\\\"wheel\\\", function (event) {\\n\",\n       \"        event = event.originalEvent;\\n\",\n       \"        event['data'] = 'scroll'\\n\",\n       \"        if (event.deltaY < 0) {\\n\",\n       \"            event.step = 1;\\n\",\n       \"        } else {\\n\",\n       \"            event.step = -1;\\n\",\n       \"        }\\n\",\n       \"        mouse_event_fn(event);\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    canvas_div.append(canvas);\\n\",\n       \"    canvas_div.append(rubberband);\\n\",\n       \"\\n\",\n       \"    this.rubberband = rubberband;\\n\",\n       \"    this.rubberband_canvas = rubberband[0];\\n\",\n       \"    this.rubberband_context = rubberband[0].getContext(\\\"2d\\\");\\n\",\n       \"    this.rubberband_context.strokeStyle = \\\"#000000\\\";\\n\",\n       \"\\n\",\n       \"    this._resize_canvas = function(width, height) {\\n\",\n       \"        // Keep the size of the canvas, canvas container, and rubber band\\n\",\n       \"        // canvas in synch.\\n\",\n       \"        canvas_div.css('width', width)\\n\",\n       \"        canvas_div.css('height', height)\\n\",\n       \"\\n\",\n       \"        canvas.attr('width', width * mpl.ratio);\\n\",\n       \"        canvas.attr('height', height * mpl.ratio);\\n\",\n       \"        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\\n\",\n       \"\\n\",\n       \"        rubberband.attr('width', width);\\n\",\n       \"        rubberband.attr('height', height);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Set the figure to an initial 600x600px, this will subsequently be updated\\n\",\n       \"    // upon first draw.\\n\",\n       \"    this._resize_canvas(600, 600);\\n\",\n       \"\\n\",\n       \"    // Disable right mouse context menu.\\n\",\n       \"    $(this.rubberband_canvas).bind(\\\"contextmenu\\\",function(e){\\n\",\n       \"        return false;\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function set_focus () {\\n\",\n       \"        canvas.focus();\\n\",\n       \"        canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    window.setTimeout(set_focus, 100);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>');\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items) {\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) {\\n\",\n       \"            // put a spacer in here.\\n\",\n       \"            continue;\\n\",\n       \"        }\\n\",\n       \"        var button = $('<button/>');\\n\",\n       \"        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\\n\",\n       \"                        'ui-button-icon-only');\\n\",\n       \"        button.attr('role', 'button');\\n\",\n       \"        button.attr('aria-disabled', 'false');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"\\n\",\n       \"        var icon_img = $('<span/>');\\n\",\n       \"        icon_img.addClass('ui-button-icon-primary ui-icon');\\n\",\n       \"        icon_img.addClass(image);\\n\",\n       \"        icon_img.addClass('ui-corner-all');\\n\",\n       \"\\n\",\n       \"        var tooltip_span = $('<span/>');\\n\",\n       \"        tooltip_span.addClass('ui-button-text');\\n\",\n       \"        tooltip_span.html(tooltip);\\n\",\n       \"\\n\",\n       \"        button.append(icon_img);\\n\",\n       \"        button.append(tooltip_span);\\n\",\n       \"\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fmt_picker_span = $('<span/>');\\n\",\n       \"\\n\",\n       \"    var fmt_picker = $('<select/>');\\n\",\n       \"    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\\n\",\n       \"    fmt_picker_span.append(fmt_picker);\\n\",\n       \"    nav_element.append(fmt_picker_span);\\n\",\n       \"    this.format_dropdown = fmt_picker[0];\\n\",\n       \"\\n\",\n       \"    for (var ind in mpl.extensions) {\\n\",\n       \"        var fmt = mpl.extensions[ind];\\n\",\n       \"        var option = $(\\n\",\n       \"            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\\n\",\n       \"        fmt_picker.append(option);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add hover states to the ui-buttons\\n\",\n       \"    $( \\\".ui-button\\\" ).hover(\\n\",\n       \"        function() { $(this).addClass(\\\"ui-state-hover\\\");},\\n\",\n       \"        function() { $(this).removeClass(\\\"ui-state-hover\\\");}\\n\",\n       \"    );\\n\",\n       \"\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\\n\",\n       \"    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\\n\",\n       \"    // which will in turn request a refresh of the image.\\n\",\n       \"    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_message = function(type, properties) {\\n\",\n       \"    properties['type'] = type;\\n\",\n       \"    properties['figure_id'] = this.id;\\n\",\n       \"    this.ws.send(JSON.stringify(properties));\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_draw_message = function() {\\n\",\n       \"    if (!this.waiting) {\\n\",\n       \"        this.waiting = true;\\n\",\n       \"        this.ws.send(JSON.stringify({type: \\\"draw\\\", figure_id: this.id}));\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    var format_dropdown = fig.format_dropdown;\\n\",\n       \"    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\\n\",\n       \"    fig.ondownload(fig, format);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_resize = function(fig, msg) {\\n\",\n       \"    var size = msg['size'];\\n\",\n       \"    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\\n\",\n       \"        fig._resize_canvas(size[0], size[1]);\\n\",\n       \"        fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\\n\",\n       \"    var x0 = msg['x0'] / mpl.ratio;\\n\",\n       \"    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\\n\",\n       \"    var x1 = msg['x1'] / mpl.ratio;\\n\",\n       \"    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\\n\",\n       \"    x0 = Math.floor(x0) + 0.5;\\n\",\n       \"    y0 = Math.floor(y0) + 0.5;\\n\",\n       \"    x1 = Math.floor(x1) + 0.5;\\n\",\n       \"    y1 = Math.floor(y1) + 0.5;\\n\",\n       \"    var min_x = Math.min(x0, x1);\\n\",\n       \"    var min_y = Math.min(y0, y1);\\n\",\n       \"    var width = Math.abs(x1 - x0);\\n\",\n       \"    var height = Math.abs(y1 - y0);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.clearRect(\\n\",\n       \"        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\\n\",\n       \"    // Updates the figure title.\\n\",\n       \"    fig.header.textContent = msg['label'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_cursor = function(fig, msg) {\\n\",\n       \"    var cursor = msg['cursor'];\\n\",\n       \"    switch(cursor)\\n\",\n       \"    {\\n\",\n       \"    case 0:\\n\",\n       \"        cursor = 'pointer';\\n\",\n       \"        break;\\n\",\n       \"    case 1:\\n\",\n       \"        cursor = 'default';\\n\",\n       \"        break;\\n\",\n       \"    case 2:\\n\",\n       \"        cursor = 'crosshair';\\n\",\n       \"        break;\\n\",\n       \"    case 3:\\n\",\n       \"        cursor = 'move';\\n\",\n       \"        break;\\n\",\n       \"    }\\n\",\n       \"    fig.rubberband_canvas.style.cursor = cursor;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_message = function(fig, msg) {\\n\",\n       \"    fig.message.textContent = msg['message'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_draw = function(fig, msg) {\\n\",\n       \"    // Request the server to send over a new figure.\\n\",\n       \"    fig.send_draw_message();\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\\n\",\n       \"    fig.image_mode = msg['mode'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Called whenever the canvas gets updated.\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// A function to construct a web socket function for onmessage handling.\\n\",\n       \"// Called in the figure constructor.\\n\",\n       \"mpl.figure.prototype._make_on_message_function = function(fig) {\\n\",\n       \"    return function socket_on_message(evt) {\\n\",\n       \"        if (evt.data instanceof Blob) {\\n\",\n       \"            /* FIXME: We get \\\"Resource interpreted as Image but\\n\",\n       \"             * transferred with MIME type text/plain:\\\" errors on\\n\",\n       \"             * Chrome.  But how to set the MIME type?  It doesn't seem\\n\",\n       \"             * to be part of the websocket stream */\\n\",\n       \"            evt.data.type = \\\"image/png\\\";\\n\",\n       \"\\n\",\n       \"            /* Free the memory for the previous frames */\\n\",\n       \"            if (fig.imageObj.src) {\\n\",\n       \"                (window.URL || window.webkitURL).revokeObjectURL(\\n\",\n       \"                    fig.imageObj.src);\\n\",\n       \"            }\\n\",\n       \"\\n\",\n       \"            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\\n\",\n       \"                evt.data);\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \\\"data:image/png;base64\\\") {\\n\",\n       \"            fig.imageObj.src = evt.data;\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        var msg = JSON.parse(evt.data);\\n\",\n       \"        var msg_type = msg['type'];\\n\",\n       \"\\n\",\n       \"        // Call the  \\\"handle_{type}\\\" callback, which takes\\n\",\n       \"        // the figure and JSON message as its only arguments.\\n\",\n       \"        try {\\n\",\n       \"            var callback = fig[\\\"handle_\\\" + msg_type];\\n\",\n       \"        } catch (e) {\\n\",\n       \"            console.log(\\\"No handler for the '\\\" + msg_type + \\\"' message type: \\\", msg);\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        if (callback) {\\n\",\n       \"            try {\\n\",\n       \"                // console.log(\\\"Handling '\\\" + msg_type + \\\"' message: \\\", msg);\\n\",\n       \"                callback(fig, msg);\\n\",\n       \"            } catch (e) {\\n\",\n       \"                console.log(\\\"Exception inside the 'handler_\\\" + msg_type + \\\"' callback:\\\", e, e.stack, msg);\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\\n\",\n       \"mpl.findpos = function(e) {\\n\",\n       \"    //this section is from http://www.quirksmode.org/js/events_properties.html\\n\",\n       \"    var targ;\\n\",\n       \"    if (!e)\\n\",\n       \"        e = window.event;\\n\",\n       \"    if (e.target)\\n\",\n       \"        targ = e.target;\\n\",\n       \"    else if (e.srcElement)\\n\",\n       \"        targ = e.srcElement;\\n\",\n       \"    if (targ.nodeType == 3) // defeat Safari bug\\n\",\n       \"        targ = targ.parentNode;\\n\",\n       \"\\n\",\n       \"    // jQuery normalizes the pageX and pageY\\n\",\n       \"    // pageX,Y are the mouse positions relative to the document\\n\",\n       \"    // offset() returns the position of the element relative to the document\\n\",\n       \"    var x = e.pageX - $(targ).offset().left;\\n\",\n       \"    var y = e.pageY - $(targ).offset().top;\\n\",\n       \"\\n\",\n       \"    return {\\\"x\\\": x, \\\"y\\\": y};\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"/*\\n\",\n       \" * return a copy of an object with only non-object keys\\n\",\n       \" * we need this to avoid circular references\\n\",\n       \" * http://stackoverflow.com/a/24161582/3208463\\n\",\n       \" */\\n\",\n       \"function simpleKeys (original) {\\n\",\n       \"  return Object.keys(original).reduce(function (obj, key) {\\n\",\n       \"    if (typeof original[key] !== 'object')\\n\",\n       \"        obj[key] = original[key]\\n\",\n       \"    return obj;\\n\",\n       \"  }, {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.mouse_event = function(event, name) {\\n\",\n       \"    var canvas_pos = mpl.findpos(event)\\n\",\n       \"\\n\",\n       \"    if (name === 'button_press')\\n\",\n       \"    {\\n\",\n       \"        this.canvas.focus();\\n\",\n       \"        this.canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var x = canvas_pos.x * mpl.ratio;\\n\",\n       \"    var y = canvas_pos.y * mpl.ratio;\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {x: x, y: y, button: event.button,\\n\",\n       \"                             step: event.step,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"\\n\",\n       \"    /* This prevents the web browser from automatically changing to\\n\",\n       \"     * the text insertion cursor when the button is pressed.  We want\\n\",\n       \"     * to control all of the cursor setting manually through the\\n\",\n       \"     * 'cursor' event from matplotlib */\\n\",\n       \"    event.preventDefault();\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    // Handle any extra behaviour associated with a key event\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.key_event = function(event, name) {\\n\",\n       \"\\n\",\n       \"    // Prevent repeat events\\n\",\n       \"    if (name == 'key_press')\\n\",\n       \"    {\\n\",\n       \"        if (event.which === this._key)\\n\",\n       \"            return;\\n\",\n       \"        else\\n\",\n       \"            this._key = event.which;\\n\",\n       \"    }\\n\",\n       \"    if (name == 'key_release')\\n\",\n       \"        this._key = null;\\n\",\n       \"\\n\",\n       \"    var value = '';\\n\",\n       \"    if (event.ctrlKey && event.which != 17)\\n\",\n       \"        value += \\\"ctrl+\\\";\\n\",\n       \"    if (event.altKey && event.which != 18)\\n\",\n       \"        value += \\\"alt+\\\";\\n\",\n       \"    if (event.shiftKey && event.which != 16)\\n\",\n       \"        value += \\\"shift+\\\";\\n\",\n       \"\\n\",\n       \"    value += 'k';\\n\",\n       \"    value += event.which.toString();\\n\",\n       \"\\n\",\n       \"    this._key_event_extra(event, name);\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {key: value,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onclick = function(name) {\\n\",\n       \"    if (name == 'download') {\\n\",\n       \"        this.handle_save(this, null);\\n\",\n       \"    } else {\\n\",\n       \"        this.send_message(\\\"toolbar_button\\\", {name: name});\\n\",\n       \"    }\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\\n\",\n       \"    this.message.textContent = tooltip;\\n\",\n       \"};\\n\",\n       \"mpl.toolbar_items = [[\\\"Home\\\", \\\"Reset original view\\\", \\\"fa fa-home icon-home\\\", \\\"home\\\"], [\\\"Back\\\", \\\"Back to previous view\\\", \\\"fa fa-arrow-left icon-arrow-left\\\", \\\"back\\\"], [\\\"Forward\\\", \\\"Forward to next view\\\", \\\"fa fa-arrow-right icon-arrow-right\\\", \\\"forward\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Pan\\\", \\\"Pan axes with left mouse, zoom with right\\\", \\\"fa fa-arrows icon-move\\\", \\\"pan\\\"], [\\\"Zoom\\\", \\\"Zoom to rectangle\\\", \\\"fa fa-square-o icon-check-empty\\\", \\\"zoom\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Download\\\", \\\"Download plot\\\", \\\"fa fa-floppy-o icon-save\\\", \\\"download\\\"]];\\n\",\n       \"\\n\",\n       \"mpl.extensions = [\\\"eps\\\", \\\"jpeg\\\", \\\"pdf\\\", \\\"png\\\", \\\"ps\\\", \\\"raw\\\", \\\"svg\\\", \\\"tif\\\"];\\n\",\n       \"\\n\",\n       \"mpl.default_extension = \\\"png\\\";var comm_websocket_adapter = function(comm) {\\n\",\n       \"    // Create a \\\"websocket\\\"-like object which calls the given IPython comm\\n\",\n       \"    // object with the appropriate methods. Currently this is a non binary\\n\",\n       \"    // socket, so there is still some room for performance tuning.\\n\",\n       \"    var ws = {};\\n\",\n       \"\\n\",\n       \"    ws.close = function() {\\n\",\n       \"        comm.close()\\n\",\n       \"    };\\n\",\n       \"    ws.send = function(m) {\\n\",\n       \"        //console.log('sending', m);\\n\",\n       \"        comm.send(m);\\n\",\n       \"    };\\n\",\n       \"    // Register the callback with on_msg.\\n\",\n       \"    comm.on_msg(function(msg) {\\n\",\n       \"        //console.log('receiving', msg['content']['data'], msg);\\n\",\n       \"        // Pass the mpl event to the overridden (by mpl) onmessage function.\\n\",\n       \"        ws.onmessage(msg['content']['data'])\\n\",\n       \"    });\\n\",\n       \"    return ws;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.mpl_figure_comm = function(comm, msg) {\\n\",\n       \"    // This is the function which gets called when the mpl process\\n\",\n       \"    // starts-up an IPython Comm through the \\\"matplotlib\\\" channel.\\n\",\n       \"\\n\",\n       \"    var id = msg.content.data.id;\\n\",\n       \"    // Get hold of the div created by the display call when the Comm\\n\",\n       \"    // socket was opened in Python.\\n\",\n       \"    var element = $(\\\"#\\\" + id);\\n\",\n       \"    var ws_proxy = comm_websocket_adapter(comm)\\n\",\n       \"\\n\",\n       \"    function ondownload(figure, format) {\\n\",\n       \"        window.open(figure.imageObj.src);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fig = new mpl.figure(id, ws_proxy,\\n\",\n       \"                           ondownload,\\n\",\n       \"                           element.get(0));\\n\",\n       \"\\n\",\n       \"    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\\n\",\n       \"    // web socket which is closed, not our websocket->open comm proxy.\\n\",\n       \"    ws_proxy.onopen();\\n\",\n       \"\\n\",\n       \"    fig.parent_element = element.get(0);\\n\",\n       \"    fig.cell_info = mpl.find_output_cell(\\\"<div id='\\\" + id + \\\"'></div>\\\");\\n\",\n       \"    if (!fig.cell_info) {\\n\",\n       \"        console.error(\\\"Failed to find cell for figure\\\", id, fig);\\n\",\n       \"        return;\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var output_index = fig.cell_info[2]\\n\",\n       \"    var cell = fig.cell_info[0];\\n\",\n       \"\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_close = function(fig, msg) {\\n\",\n       \"    var width = fig.canvas.width/mpl.ratio\\n\",\n       \"    fig.root.unbind('remove')\\n\",\n       \"\\n\",\n       \"    // Update the output cell to use the data from the current canvas.\\n\",\n       \"    fig.push_to_output();\\n\",\n       \"    var dataURL = fig.canvas.toDataURL();\\n\",\n       \"    // Re-enable the keyboard manager in IPython - without this line, in FF,\\n\",\n       \"    // the notebook keyboard shortcuts fail.\\n\",\n       \"    IPython.keyboard_manager.enable()\\n\",\n       \"    $(fig.parent_element).html('<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">');\\n\",\n       \"    fig.close_ws(fig, msg);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.close_ws = function(fig, msg){\\n\",\n       \"    fig.send_message('closing', msg);\\n\",\n       \"    // fig.ws.close()\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.push_to_output = function(remove_interactive) {\\n\",\n       \"    // Turn the data on the canvas into data in the output cell.\\n\",\n       \"    var width = this.canvas.width/mpl.ratio\\n\",\n       \"    var dataURL = this.canvas.toDataURL();\\n\",\n       \"    this.cell_info[1]['text/html'] = '<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">';\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Tell IPython that the notebook contents must change.\\n\",\n       \"    IPython.notebook.set_dirty(true);\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"    var fig = this;\\n\",\n       \"    // Wait a second, then push the new image to the DOM so\\n\",\n       \"    // that it is saved nicely (might be nice to debounce this).\\n\",\n       \"    setTimeout(function () { fig.push_to_output() }, 1000);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>');\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items){\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) { continue; };\\n\",\n       \"\\n\",\n       \"        var button = $('<button class=\\\"btn btn-default\\\" href=\\\"#\\\" title=\\\"' + name + '\\\"><i class=\\\"fa ' + image + ' fa-lg\\\"></i></button>');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add the status bar.\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\" style=\\\"text-align:right; float: right;\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"\\n\",\n       \"    // Add the close button to the window.\\n\",\n       \"    var buttongrp = $('<div class=\\\"btn-group inline pull-right\\\"></div>');\\n\",\n       \"    var button = $('<button class=\\\"btn btn-mini btn-primary\\\" href=\\\"#\\\" title=\\\"Stop Interaction\\\"><i class=\\\"fa fa-power-off icon-remove icon-large\\\"></i></button>');\\n\",\n       \"    button.click(function (evt) { fig.handle_close(fig, {}); } );\\n\",\n       \"    button.mouseover('Stop Interaction', toolbar_mouse_event);\\n\",\n       \"    buttongrp.append(button);\\n\",\n       \"    var titlebar = this.root.find($('.ui-dialog-titlebar'));\\n\",\n       \"    titlebar.prepend(buttongrp);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(el){\\n\",\n       \"    var fig = this\\n\",\n       \"    el.on(\\\"remove\\\", function(){\\n\",\n       \"\\tfig.close_ws(fig, {});\\n\",\n       \"    });\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(el){\\n\",\n       \"    // this is important to make the div 'focusable\\n\",\n       \"    el.attr('tabindex', 0)\\n\",\n       \"    // reach out to IPython and tell the keyboard manager to turn it's self\\n\",\n       \"    // off when our div gets focus\\n\",\n       \"\\n\",\n       \"    // location in version 3\\n\",\n       \"    if (IPython.notebook.keyboard_manager) {\\n\",\n       \"        IPython.notebook.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"    else {\\n\",\n       \"        // location in version 2\\n\",\n       \"        IPython.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    var manager = IPython.notebook.keyboard_manager;\\n\",\n       \"    if (!manager)\\n\",\n       \"        manager = IPython.keyboard_manager;\\n\",\n       \"\\n\",\n       \"    // Check for shift+enter\\n\",\n       \"    if (event.shiftKey && event.which == 13) {\\n\",\n       \"        this.canvas_div.blur();\\n\",\n       \"        event.shiftKey = false;\\n\",\n       \"        // Send a \\\"J\\\" for go to next cell\\n\",\n       \"        event.which = 74;\\n\",\n       \"        event.keyCode = 74;\\n\",\n       \"        manager.command_mode();\\n\",\n       \"        manager.handle_keydown(event);\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    fig.ondownload(fig, null);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.find_output_cell = function(html_output) {\\n\",\n       \"    // Return the cell and output element which can be found *uniquely* in the notebook.\\n\",\n       \"    // Note - this is a bit hacky, but it is done because the \\\"notebook_saving.Notebook\\\"\\n\",\n       \"    // IPython event is triggered only after the cells have been serialised, which for\\n\",\n       \"    // our purposes (turning an active figure into a static one), is too late.\\n\",\n       \"    var cells = IPython.notebook.get_cells();\\n\",\n       \"    var ncells = cells.length;\\n\",\n       \"    for (var i=0; i<ncells; i++) {\\n\",\n       \"        var cell = cells[i];\\n\",\n       \"        if (cell.cell_type === 'code'){\\n\",\n       \"            for (var j=0; j<cell.output_area.outputs.length; j++) {\\n\",\n       \"                var data = cell.output_area.outputs[j];\\n\",\n       \"                if (data.data) {\\n\",\n       \"                    // IPython >= 3 moved mimebundle to data attribute of output\\n\",\n       \"                    data = data.data;\\n\",\n       \"                }\\n\",\n       \"                if (data['text/html'] == html_output) {\\n\",\n       \"                    return [cell, data, j];\\n\",\n       \"                }\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// Register the function which deals with the matplotlib target/channel.\\n\",\n       \"// The kernel may be null if the page has been refreshed.\\n\",\n       \"if (IPython.notebook.kernel != null) {\\n\",\n       \"    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\\n\",\n       \"}\\n\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.Javascript object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"text/html\": [\n       \"<img src=\\\"data:image/png;base64,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\\\" width=\\\"800\\\">\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.HTML object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"print(\\\"<f_x> : {0:9.2E} +/- {1:8.2E}\\\".format(np.mean(forces.T[0]), np.std(forces.T[0], ddof=1)))\\n\",\n    \"print(\\\"<f_y> : {0:9.2E} +/- {1:8.2E}\\\".format(np.mean(forces.T[1]), np.std(forces.T[1], ddof=1)))\\n\",\n    \"print(\\\"<f_z> : {0:9.2E} +/- {1:8.2E}\\\".format(np.mean(forces.T[2]), np.std(forces.T[2], ddof=1)))\\n\",\n    \"\\n\",\n    \"fig, ax = plt.subplots()\\n\",\n    \"fig.set_size_inches(8, 6)\\n\",\n    \"ax.hist(forces.T[0], bins='auto', density=1, alpha=0.5, label=r'$f_x$')\\n\",\n    \"ax.hist(forces.T[1], bins='auto', density=1, alpha=0.5, label=r'$f_y$')\\n\",\n    \"ax.hist(forces.T[2], bins='auto', density=1, alpha=0.5, label=r'$f_z$')\\n\",\n    \"ax.legend(loc='best')\\n\",\n    \"ax.set_xlabel(r'$f$')\\n\",\n    \"ax.set_ylabel(r'$p(f)$')\\n\",\n    \"fig.savefig(f\\\"force_histogram_{extract_element}.pdf\\\")\\n\",\n    \"fig.savefig(f\\\"force_histogram_{extract_element}.png\\\", dpi=300)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"Up until now we have just prepared the atomic forces and we still need to get meaningful atomic environment descriptors. For this purpose we use the _n2p2_ tool `nnp-atomenv` which is described in the [online documentation](https://compphysvienna.github.io/n2p2/tools/nnp-atomenv.html). With a given data set in \\\"`input.data`\\\" and symmetry function definitions (and scaling information) in \\\"`input.nn`\\\" and \\\"`scaling.data`\\\" the tool will provide the files \\\"`atomic-env.G`\\\" and \\\"`atomic-env.dGd?`\\\" (where `?` is all of `x`, `y` and `z`) which contain the desired descriptors and their derivatives.\\n\",\n    \"\\n\",\n    \"**WARNING:** Do not run the `nnp-atomenv` tool on large data sets as it will create HUGE files!\\n\",\n    \"\\n\",\n    \"Once the files have been created we can use this helper function to read in the symmetry function files. Again, only atoms of a specified element are extracted.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 6,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"def read_sf_data(file_name=\\\"atomic-env.G\\\", element=\\\"H\\\"):\\n\",\n    \"    sf = []\\n\",\n    \"    f = open(file_name, \\\"r\\\")\\n\",\n    \"    for line in f:\\n\",\n    \"        if line.split()[0] == element:\\n\",\n    \"            sf.append(np.array([float(number) for number in line.split()[1:]]))\\n\",\n    \"    f.close()    \\n\",\n    \"    return np.array(sf)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"When applying the above function to an actual data set we end up with a large numpy array with dimensions $N_\\\\text{atoms} \\\\times N_d$, where $N_d$ is the total number of atomic environment descriptors per atom (depends on the symmetry function setup and neighbor cutoffs picked by `nnp-atomenv`).\\n\",\n    \"\\n\",\n    \"**CHECK:** The number of atoms here and above (when reading in the forces) must match!\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 7,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"(6840, 60)\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"sf = read_sf_data(\\\"atomic-env.\\\" + extract_descriptor, extract_element)\\n\",\n    \"print(np.shape(sf))\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"**OPTIONAL:** The next two code cells can be excluded from execution, the visualization is not required for the analysis.\\n\",\n    \"\\n\",\n    \"We can visualize the distribution of data points in the high-dimensional symmetry function space making use of a dimensionality-reduction algorithm (t-SNE). First, we need to prepare the projection which takes some time, especially for larger data sets. To limit the computational effort the data set is automatically sparsified if the number of points exceeds the given threshold in `vis_typ_points`.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 8,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"NOTE: Using only every 2th point for t-SNE visualization!\\n\",\n      \"\\n\",\n      \"CPU times: user 23.2 s, sys: 33.2 ms, total: 23.2 s\\n\",\n      \"Wall time: 23.2 s\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Typical number of data points for t-SNE visualization.\\n\",\n    \"vis_typ_points = 2500\\n\",\n    \"\\n\",\n    \"# Automatic sparsification\\n\",\n    \"vis_sp = 1\\n\",\n    \"if len(sf) > vis_typ_points:\\n\",\n    \"    vis_sp = int(len(sf)/float(vis_typ_points))\\n\",\n    \"\\n\",\n    \"if vis_sp > 1:\\n\",\n    \"    print(\\\"NOTE: Using only every {0:d}th point for t-SNE visualization!\\\\n\\\".format(vis_sp))\\n\",\n    \"\\n\",\n    \"%time projection = TSNE().fit_transform(sf[::vis_sp])\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"Next, here are the data points arranged in 2 dimensions:\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 9,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"application/javascript\": [\n       \"/* Put everything inside the global mpl namespace */\\n\",\n       \"window.mpl = {};\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.get_websocket_type = function() {\\n\",\n       \"    if (typeof(WebSocket) !== 'undefined') {\\n\",\n       \"        return WebSocket;\\n\",\n       \"    } else if (typeof(MozWebSocket) !== 'undefined') {\\n\",\n       \"        return MozWebSocket;\\n\",\n       \"    } else {\\n\",\n       \"        alert('Your browser does not have WebSocket support. ' +\\n\",\n       \"              'Please try Chrome, Safari or Firefox ≥ 6. ' +\\n\",\n       \"              'Firefox 4 and 5 are also supported but you ' +\\n\",\n       \"              'have to enable WebSockets in about:config.');\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\\n\",\n       \"    this.id = figure_id;\\n\",\n       \"\\n\",\n       \"    this.ws = websocket;\\n\",\n       \"\\n\",\n       \"    this.supports_binary = (this.ws.binaryType != undefined);\\n\",\n       \"\\n\",\n       \"    if (!this.supports_binary) {\\n\",\n       \"        var warnings = document.getElementById(\\\"mpl-warnings\\\");\\n\",\n       \"        if (warnings) {\\n\",\n       \"            warnings.style.display = 'block';\\n\",\n       \"            warnings.textContent = (\\n\",\n       \"                \\\"This browser does not support binary websocket messages. \\\" +\\n\",\n       \"                    \\\"Performance may be slow.\\\");\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.imageObj = new Image();\\n\",\n       \"\\n\",\n       \"    this.context = undefined;\\n\",\n       \"    this.message = undefined;\\n\",\n       \"    this.canvas = undefined;\\n\",\n       \"    this.rubberband_canvas = undefined;\\n\",\n       \"    this.rubberband_context = undefined;\\n\",\n       \"    this.format_dropdown = undefined;\\n\",\n       \"\\n\",\n       \"    this.image_mode = 'full';\\n\",\n       \"\\n\",\n       \"    this.root = $('<div/>');\\n\",\n       \"    this._root_extra_style(this.root)\\n\",\n       \"    this.root.attr('style', 'display: inline-block');\\n\",\n       \"\\n\",\n       \"    $(parent_element).append(this.root);\\n\",\n       \"\\n\",\n       \"    this._init_header(this);\\n\",\n       \"    this._init_canvas(this);\\n\",\n       \"    this._init_toolbar(this);\\n\",\n       \"\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    this.waiting = false;\\n\",\n       \"\\n\",\n       \"    this.ws.onopen =  function () {\\n\",\n       \"            fig.send_message(\\\"supports_binary\\\", {value: fig.supports_binary});\\n\",\n       \"            fig.send_message(\\\"send_image_mode\\\", {});\\n\",\n       \"            if (mpl.ratio != 1) {\\n\",\n       \"                fig.send_message(\\\"set_dpi_ratio\\\", {'dpi_ratio': mpl.ratio});\\n\",\n       \"            }\\n\",\n       \"            fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"    this.imageObj.onload = function() {\\n\",\n       \"            if (fig.image_mode == 'full') {\\n\",\n       \"                // Full images could contain transparency (where diff images\\n\",\n       \"                // almost always do), so we need to clear the canvas so that\\n\",\n       \"                // there is no ghosting.\\n\",\n       \"                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\\n\",\n       \"            }\\n\",\n       \"            fig.context.drawImage(fig.imageObj, 0, 0);\\n\",\n       \"        };\\n\",\n       \"\\n\",\n       \"    this.imageObj.onunload = function() {\\n\",\n       \"        fig.ws.close();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.ws.onmessage = this._make_on_message_function(this);\\n\",\n       \"\\n\",\n       \"    this.ondownload = ondownload;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_header = function() {\\n\",\n       \"    var titlebar = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\\n\",\n       \"        'ui-helper-clearfix\\\"/>');\\n\",\n       \"    var titletext = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-title\\\" style=\\\"width: 100%; ' +\\n\",\n       \"        'text-align: center; padding: 3px;\\\"/>');\\n\",\n       \"    titlebar.append(titletext)\\n\",\n       \"    this.root.append(titlebar);\\n\",\n       \"    this.header = titletext[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_canvas = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var canvas_div = $('<div/>');\\n\",\n       \"\\n\",\n       \"    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\\n\",\n       \"\\n\",\n       \"    function canvas_keyboard_event(event) {\\n\",\n       \"        return fig.key_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    canvas_div.keydown('key_press', canvas_keyboard_event);\\n\",\n       \"    canvas_div.keyup('key_release', canvas_keyboard_event);\\n\",\n       \"    this.canvas_div = canvas_div\\n\",\n       \"    this._canvas_extra_style(canvas_div)\\n\",\n       \"    this.root.append(canvas_div);\\n\",\n       \"\\n\",\n       \"    var canvas = $('<canvas/>');\\n\",\n       \"    canvas.addClass('mpl-canvas');\\n\",\n       \"    canvas.attr('style', \\\"left: 0; top: 0; z-index: 0; outline: 0\\\")\\n\",\n       \"\\n\",\n       \"    this.canvas = canvas[0];\\n\",\n       \"    this.context = canvas[0].getContext(\\\"2d\\\");\\n\",\n       \"\\n\",\n       \"    var backingStore = this.context.backingStorePixelRatio ||\\n\",\n       \"\\tthis.context.webkitBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.mozBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.msBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.oBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.backingStorePixelRatio || 1;\\n\",\n       \"\\n\",\n       \"    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\\n\",\n       \"\\n\",\n       \"    var rubberband = $('<canvas/>');\\n\",\n       \"    rubberband.attr('style', \\\"position: absolute; left: 0; top: 0; z-index: 1;\\\")\\n\",\n       \"\\n\",\n       \"    var pass_mouse_events = true;\\n\",\n       \"\\n\",\n       \"    canvas_div.resizable({\\n\",\n       \"        start: function(event, ui) {\\n\",\n       \"            pass_mouse_events = false;\\n\",\n       \"        },\\n\",\n       \"        resize: function(event, ui) {\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"        stop: function(event, ui) {\\n\",\n       \"            pass_mouse_events = true;\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function mouse_event_fn(event) {\\n\",\n       \"        if (pass_mouse_events)\\n\",\n       \"            return fig.mouse_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    rubberband.mousedown('button_press', mouse_event_fn);\\n\",\n       \"    rubberband.mouseup('button_release', mouse_event_fn);\\n\",\n       \"    // Throttle sequential mouse events to 1 every 20ms.\\n\",\n       \"    rubberband.mousemove('motion_notify', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    rubberband.mouseenter('figure_enter', mouse_event_fn);\\n\",\n       \"    rubberband.mouseleave('figure_leave', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    canvas_div.on(\\\"wheel\\\", function (event) {\\n\",\n       \"        event = event.originalEvent;\\n\",\n       \"        event['data'] = 'scroll'\\n\",\n       \"        if (event.deltaY < 0) {\\n\",\n       \"            event.step = 1;\\n\",\n       \"        } else {\\n\",\n       \"            event.step = -1;\\n\",\n       \"        }\\n\",\n       \"        mouse_event_fn(event);\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    canvas_div.append(canvas);\\n\",\n       \"    canvas_div.append(rubberband);\\n\",\n       \"\\n\",\n       \"    this.rubberband = rubberband;\\n\",\n       \"    this.rubberband_canvas = rubberband[0];\\n\",\n       \"    this.rubberband_context = rubberband[0].getContext(\\\"2d\\\");\\n\",\n       \"    this.rubberband_context.strokeStyle = \\\"#000000\\\";\\n\",\n       \"\\n\",\n       \"    this._resize_canvas = function(width, height) {\\n\",\n       \"        // Keep the size of the canvas, canvas container, and rubber band\\n\",\n       \"        // canvas in synch.\\n\",\n       \"        canvas_div.css('width', width)\\n\",\n       \"        canvas_div.css('height', height)\\n\",\n       \"\\n\",\n       \"        canvas.attr('width', width * mpl.ratio);\\n\",\n       \"        canvas.attr('height', height * mpl.ratio);\\n\",\n       \"        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\\n\",\n       \"\\n\",\n       \"        rubberband.attr('width', width);\\n\",\n       \"        rubberband.attr('height', height);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Set the figure to an initial 600x600px, this will subsequently be updated\\n\",\n       \"    // upon first draw.\\n\",\n       \"    this._resize_canvas(600, 600);\\n\",\n       \"\\n\",\n       \"    // Disable right mouse context menu.\\n\",\n       \"    $(this.rubberband_canvas).bind(\\\"contextmenu\\\",function(e){\\n\",\n       \"        return false;\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function set_focus () {\\n\",\n       \"        canvas.focus();\\n\",\n       \"        canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    window.setTimeout(set_focus, 100);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>');\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items) {\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) {\\n\",\n       \"            // put a spacer in here.\\n\",\n       \"            continue;\\n\",\n       \"        }\\n\",\n       \"        var button = $('<button/>');\\n\",\n       \"        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\\n\",\n       \"                        'ui-button-icon-only');\\n\",\n       \"        button.attr('role', 'button');\\n\",\n       \"        button.attr('aria-disabled', 'false');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"\\n\",\n       \"        var icon_img = $('<span/>');\\n\",\n       \"        icon_img.addClass('ui-button-icon-primary ui-icon');\\n\",\n       \"        icon_img.addClass(image);\\n\",\n       \"        icon_img.addClass('ui-corner-all');\\n\",\n       \"\\n\",\n       \"        var tooltip_span = $('<span/>');\\n\",\n       \"        tooltip_span.addClass('ui-button-text');\\n\",\n       \"        tooltip_span.html(tooltip);\\n\",\n       \"\\n\",\n       \"        button.append(icon_img);\\n\",\n       \"        button.append(tooltip_span);\\n\",\n       \"\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fmt_picker_span = $('<span/>');\\n\",\n       \"\\n\",\n       \"    var fmt_picker = $('<select/>');\\n\",\n       \"    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\\n\",\n       \"    fmt_picker_span.append(fmt_picker);\\n\",\n       \"    nav_element.append(fmt_picker_span);\\n\",\n       \"    this.format_dropdown = fmt_picker[0];\\n\",\n       \"\\n\",\n       \"    for (var ind in mpl.extensions) {\\n\",\n       \"        var fmt = mpl.extensions[ind];\\n\",\n       \"        var option = $(\\n\",\n       \"            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\\n\",\n       \"        fmt_picker.append(option);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add hover states to the ui-buttons\\n\",\n       \"    $( \\\".ui-button\\\" ).hover(\\n\",\n       \"        function() { $(this).addClass(\\\"ui-state-hover\\\");},\\n\",\n       \"        function() { $(this).removeClass(\\\"ui-state-hover\\\");}\\n\",\n       \"    );\\n\",\n       \"\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\\n\",\n       \"    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\\n\",\n       \"    // which will in turn request a refresh of the image.\\n\",\n       \"    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_message = function(type, properties) {\\n\",\n       \"    properties['type'] = type;\\n\",\n       \"    properties['figure_id'] = this.id;\\n\",\n       \"    this.ws.send(JSON.stringify(properties));\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_draw_message = function() {\\n\",\n       \"    if (!this.waiting) {\\n\",\n       \"        this.waiting = true;\\n\",\n       \"        this.ws.send(JSON.stringify({type: \\\"draw\\\", figure_id: this.id}));\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    var format_dropdown = fig.format_dropdown;\\n\",\n       \"    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\\n\",\n       \"    fig.ondownload(fig, format);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_resize = function(fig, msg) {\\n\",\n       \"    var size = msg['size'];\\n\",\n       \"    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\\n\",\n       \"        fig._resize_canvas(size[0], size[1]);\\n\",\n       \"        fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\\n\",\n       \"    var x0 = msg['x0'] / mpl.ratio;\\n\",\n       \"    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\\n\",\n       \"    var x1 = msg['x1'] / mpl.ratio;\\n\",\n       \"    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\\n\",\n       \"    x0 = Math.floor(x0) + 0.5;\\n\",\n       \"    y0 = Math.floor(y0) + 0.5;\\n\",\n       \"    x1 = Math.floor(x1) + 0.5;\\n\",\n       \"    y1 = Math.floor(y1) + 0.5;\\n\",\n       \"    var min_x = Math.min(x0, x1);\\n\",\n       \"    var min_y = Math.min(y0, y1);\\n\",\n       \"    var width = Math.abs(x1 - x0);\\n\",\n       \"    var height = Math.abs(y1 - y0);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.clearRect(\\n\",\n       \"        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\\n\",\n       \"    // Updates the figure title.\\n\",\n       \"    fig.header.textContent = msg['label'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_cursor = function(fig, msg) {\\n\",\n       \"    var cursor = msg['cursor'];\\n\",\n       \"    switch(cursor)\\n\",\n       \"    {\\n\",\n       \"    case 0:\\n\",\n       \"        cursor = 'pointer';\\n\",\n       \"        break;\\n\",\n       \"    case 1:\\n\",\n       \"        cursor = 'default';\\n\",\n       \"        break;\\n\",\n       \"    case 2:\\n\",\n       \"        cursor = 'crosshair';\\n\",\n       \"        break;\\n\",\n       \"    case 3:\\n\",\n       \"        cursor = 'move';\\n\",\n       \"        break;\\n\",\n       \"    }\\n\",\n       \"    fig.rubberband_canvas.style.cursor = cursor;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_message = function(fig, msg) {\\n\",\n       \"    fig.message.textContent = msg['message'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_draw = function(fig, msg) {\\n\",\n       \"    // Request the server to send over a new figure.\\n\",\n       \"    fig.send_draw_message();\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\\n\",\n       \"    fig.image_mode = msg['mode'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Called whenever the canvas gets updated.\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// A function to construct a web socket function for onmessage handling.\\n\",\n       \"// Called in the figure constructor.\\n\",\n       \"mpl.figure.prototype._make_on_message_function = function(fig) {\\n\",\n       \"    return function socket_on_message(evt) {\\n\",\n       \"        if (evt.data instanceof Blob) {\\n\",\n       \"            /* FIXME: We get \\\"Resource interpreted as Image but\\n\",\n       \"             * transferred with MIME type text/plain:\\\" errors on\\n\",\n       \"             * Chrome.  But how to set the MIME type?  It doesn't seem\\n\",\n       \"             * to be part of the websocket stream */\\n\",\n       \"            evt.data.type = \\\"image/png\\\";\\n\",\n       \"\\n\",\n       \"            /* Free the memory for the previous frames */\\n\",\n       \"            if (fig.imageObj.src) {\\n\",\n       \"                (window.URL || window.webkitURL).revokeObjectURL(\\n\",\n       \"                    fig.imageObj.src);\\n\",\n       \"            }\\n\",\n       \"\\n\",\n       \"            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\\n\",\n       \"                evt.data);\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \\\"data:image/png;base64\\\") {\\n\",\n       \"            fig.imageObj.src = evt.data;\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        var msg = JSON.parse(evt.data);\\n\",\n       \"        var msg_type = msg['type'];\\n\",\n       \"\\n\",\n       \"        // Call the  \\\"handle_{type}\\\" callback, which takes\\n\",\n       \"        // the figure and JSON message as its only arguments.\\n\",\n       \"        try {\\n\",\n       \"            var callback = fig[\\\"handle_\\\" + msg_type];\\n\",\n       \"        } catch (e) {\\n\",\n       \"            console.log(\\\"No handler for the '\\\" + msg_type + \\\"' message type: \\\", msg);\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        if (callback) {\\n\",\n       \"            try {\\n\",\n       \"                // console.log(\\\"Handling '\\\" + msg_type + \\\"' message: \\\", msg);\\n\",\n       \"                callback(fig, msg);\\n\",\n       \"            } catch (e) {\\n\",\n       \"                console.log(\\\"Exception inside the 'handler_\\\" + msg_type + \\\"' callback:\\\", e, e.stack, msg);\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\\n\",\n       \"mpl.findpos = function(e) {\\n\",\n       \"    //this section is from http://www.quirksmode.org/js/events_properties.html\\n\",\n       \"    var targ;\\n\",\n       \"    if (!e)\\n\",\n       \"        e = window.event;\\n\",\n       \"    if (e.target)\\n\",\n       \"        targ = e.target;\\n\",\n       \"    else if (e.srcElement)\\n\",\n       \"        targ = e.srcElement;\\n\",\n       \"    if (targ.nodeType == 3) // defeat Safari bug\\n\",\n       \"        targ = targ.parentNode;\\n\",\n       \"\\n\",\n       \"    // jQuery normalizes the pageX and pageY\\n\",\n       \"    // pageX,Y are the mouse positions relative to the document\\n\",\n       \"    // offset() returns the position of the element relative to the document\\n\",\n       \"    var x = e.pageX - $(targ).offset().left;\\n\",\n       \"    var y = e.pageY - $(targ).offset().top;\\n\",\n       \"\\n\",\n       \"    return {\\\"x\\\": x, \\\"y\\\": y};\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"/*\\n\",\n       \" * return a copy of an object with only non-object keys\\n\",\n       \" * we need this to avoid circular references\\n\",\n       \" * http://stackoverflow.com/a/24161582/3208463\\n\",\n       \" */\\n\",\n       \"function simpleKeys (original) {\\n\",\n       \"  return Object.keys(original).reduce(function (obj, key) {\\n\",\n       \"    if (typeof original[key] !== 'object')\\n\",\n       \"        obj[key] = original[key]\\n\",\n       \"    return obj;\\n\",\n       \"  }, {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.mouse_event = function(event, name) {\\n\",\n       \"    var canvas_pos = mpl.findpos(event)\\n\",\n       \"\\n\",\n       \"    if (name === 'button_press')\\n\",\n       \"    {\\n\",\n       \"        this.canvas.focus();\\n\",\n       \"        this.canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var x = canvas_pos.x * mpl.ratio;\\n\",\n       \"    var y = canvas_pos.y * mpl.ratio;\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {x: x, y: y, button: event.button,\\n\",\n       \"                             step: event.step,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"\\n\",\n       \"    /* This prevents the web browser from automatically changing to\\n\",\n       \"     * the text insertion cursor when the button is pressed.  We want\\n\",\n       \"     * to control all of the cursor setting manually through the\\n\",\n       \"     * 'cursor' event from matplotlib */\\n\",\n       \"    event.preventDefault();\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    // Handle any extra behaviour associated with a key event\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.key_event = function(event, name) {\\n\",\n       \"\\n\",\n       \"    // Prevent repeat events\\n\",\n       \"    if (name == 'key_press')\\n\",\n       \"    {\\n\",\n       \"        if (event.which === this._key)\\n\",\n       \"            return;\\n\",\n       \"        else\\n\",\n       \"            this._key = event.which;\\n\",\n       \"    }\\n\",\n       \"    if (name == 'key_release')\\n\",\n       \"        this._key = null;\\n\",\n       \"\\n\",\n       \"    var value = '';\\n\",\n       \"    if (event.ctrlKey && event.which != 17)\\n\",\n       \"        value += \\\"ctrl+\\\";\\n\",\n       \"    if (event.altKey && event.which != 18)\\n\",\n       \"        value += \\\"alt+\\\";\\n\",\n       \"    if (event.shiftKey && event.which != 16)\\n\",\n       \"        value += \\\"shift+\\\";\\n\",\n       \"\\n\",\n       \"    value += 'k';\\n\",\n       \"    value += event.which.toString();\\n\",\n       \"\\n\",\n       \"    this._key_event_extra(event, name);\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {key: value,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onclick = function(name) {\\n\",\n       \"    if (name == 'download') {\\n\",\n       \"        this.handle_save(this, null);\\n\",\n       \"    } else {\\n\",\n       \"        this.send_message(\\\"toolbar_button\\\", {name: name});\\n\",\n       \"    }\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\\n\",\n       \"    this.message.textContent = tooltip;\\n\",\n       \"};\\n\",\n       \"mpl.toolbar_items = [[\\\"Home\\\", \\\"Reset original view\\\", \\\"fa fa-home icon-home\\\", \\\"home\\\"], [\\\"Back\\\", \\\"Back to previous view\\\", \\\"fa fa-arrow-left icon-arrow-left\\\", \\\"back\\\"], [\\\"Forward\\\", \\\"Forward to next view\\\", \\\"fa fa-arrow-right icon-arrow-right\\\", \\\"forward\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Pan\\\", \\\"Pan axes with left mouse, zoom with right\\\", \\\"fa fa-arrows icon-move\\\", \\\"pan\\\"], [\\\"Zoom\\\", \\\"Zoom to rectangle\\\", \\\"fa fa-square-o icon-check-empty\\\", \\\"zoom\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Download\\\", \\\"Download plot\\\", \\\"fa fa-floppy-o icon-save\\\", \\\"download\\\"]];\\n\",\n       \"\\n\",\n       \"mpl.extensions = [\\\"eps\\\", \\\"jpeg\\\", \\\"pdf\\\", \\\"png\\\", \\\"ps\\\", \\\"raw\\\", \\\"svg\\\", \\\"tif\\\"];\\n\",\n       \"\\n\",\n       \"mpl.default_extension = \\\"png\\\";var comm_websocket_adapter = function(comm) {\\n\",\n       \"    // Create a \\\"websocket\\\"-like object which calls the given IPython comm\\n\",\n       \"    // object with the appropriate methods. Currently this is a non binary\\n\",\n       \"    // socket, so there is still some room for performance tuning.\\n\",\n       \"    var ws = {};\\n\",\n       \"\\n\",\n       \"    ws.close = function() {\\n\",\n       \"        comm.close()\\n\",\n       \"    };\\n\",\n       \"    ws.send = function(m) {\\n\",\n       \"        //console.log('sending', m);\\n\",\n       \"        comm.send(m);\\n\",\n       \"    };\\n\",\n       \"    // Register the callback with on_msg.\\n\",\n       \"    comm.on_msg(function(msg) {\\n\",\n       \"        //console.log('receiving', msg['content']['data'], msg);\\n\",\n       \"        // Pass the mpl event to the overridden (by mpl) onmessage function.\\n\",\n       \"        ws.onmessage(msg['content']['data'])\\n\",\n       \"    });\\n\",\n       \"    return ws;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.mpl_figure_comm = function(comm, msg) {\\n\",\n       \"    // This is the function which gets called when the mpl process\\n\",\n       \"    // starts-up an IPython Comm through the \\\"matplotlib\\\" channel.\\n\",\n       \"\\n\",\n       \"    var id = msg.content.data.id;\\n\",\n       \"    // Get hold of the div created by the display call when the Comm\\n\",\n       \"    // socket was opened in Python.\\n\",\n       \"    var element = $(\\\"#\\\" + id);\\n\",\n       \"    var ws_proxy = comm_websocket_adapter(comm)\\n\",\n       \"\\n\",\n       \"    function ondownload(figure, format) {\\n\",\n       \"        window.open(figure.imageObj.src);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fig = new mpl.figure(id, ws_proxy,\\n\",\n       \"                           ondownload,\\n\",\n       \"                           element.get(0));\\n\",\n       \"\\n\",\n       \"    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\\n\",\n       \"    // web socket which is closed, not our websocket->open comm proxy.\\n\",\n       \"    ws_proxy.onopen();\\n\",\n       \"\\n\",\n       \"    fig.parent_element = element.get(0);\\n\",\n       \"    fig.cell_info = mpl.find_output_cell(\\\"<div id='\\\" + id + \\\"'></div>\\\");\\n\",\n       \"    if (!fig.cell_info) {\\n\",\n       \"        console.error(\\\"Failed to find cell for figure\\\", id, fig);\\n\",\n       \"        return;\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var output_index = fig.cell_info[2]\\n\",\n       \"    var cell = fig.cell_info[0];\\n\",\n       \"\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_close = function(fig, msg) {\\n\",\n       \"    var width = fig.canvas.width/mpl.ratio\\n\",\n       \"    fig.root.unbind('remove')\\n\",\n       \"\\n\",\n       \"    // Update the output cell to use the data from the current canvas.\\n\",\n       \"    fig.push_to_output();\\n\",\n       \"    var dataURL = fig.canvas.toDataURL();\\n\",\n       \"    // Re-enable the keyboard manager in IPython - without this line, in FF,\\n\",\n       \"    // the notebook keyboard shortcuts fail.\\n\",\n       \"    IPython.keyboard_manager.enable()\\n\",\n       \"    $(fig.parent_element).html('<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">');\\n\",\n       \"    fig.close_ws(fig, msg);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.close_ws = function(fig, msg){\\n\",\n       \"    fig.send_message('closing', msg);\\n\",\n       \"    // fig.ws.close()\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.push_to_output = function(remove_interactive) {\\n\",\n       \"    // Turn the data on the canvas into data in the output cell.\\n\",\n       \"    var width = this.canvas.width/mpl.ratio\\n\",\n       \"    var dataURL = this.canvas.toDataURL();\\n\",\n       \"    this.cell_info[1]['text/html'] = '<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">';\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Tell IPython that the notebook contents must change.\\n\",\n       \"    IPython.notebook.set_dirty(true);\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"    var fig = this;\\n\",\n       \"    // Wait a second, then push the new image to the DOM so\\n\",\n       \"    // that it is saved nicely (might be nice to debounce this).\\n\",\n       \"    setTimeout(function () { fig.push_to_output() }, 1000);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>');\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items){\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) { continue; };\\n\",\n       \"\\n\",\n       \"        var button = $('<button class=\\\"btn btn-default\\\" href=\\\"#\\\" title=\\\"' + name + '\\\"><i class=\\\"fa ' + image + ' fa-lg\\\"></i></button>');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add the status bar.\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\" style=\\\"text-align:right; float: right;\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"\\n\",\n       \"    // Add the close button to the window.\\n\",\n       \"    var buttongrp = $('<div class=\\\"btn-group inline pull-right\\\"></div>');\\n\",\n       \"    var button = $('<button class=\\\"btn btn-mini btn-primary\\\" href=\\\"#\\\" title=\\\"Stop Interaction\\\"><i class=\\\"fa fa-power-off icon-remove icon-large\\\"></i></button>');\\n\",\n       \"    button.click(function (evt) { fig.handle_close(fig, {}); } );\\n\",\n       \"    button.mouseover('Stop Interaction', toolbar_mouse_event);\\n\",\n       \"    buttongrp.append(button);\\n\",\n       \"    var titlebar = this.root.find($('.ui-dialog-titlebar'));\\n\",\n       \"    titlebar.prepend(buttongrp);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(el){\\n\",\n       \"    var fig = this\\n\",\n       \"    el.on(\\\"remove\\\", function(){\\n\",\n       \"\\tfig.close_ws(fig, {});\\n\",\n       \"    });\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(el){\\n\",\n       \"    // this is important to make the div 'focusable\\n\",\n       \"    el.attr('tabindex', 0)\\n\",\n       \"    // reach out to IPython and tell the keyboard manager to turn it's self\\n\",\n       \"    // off when our div gets focus\\n\",\n       \"\\n\",\n       \"    // location in version 3\\n\",\n       \"    if (IPython.notebook.keyboard_manager) {\\n\",\n       \"        IPython.notebook.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"    else {\\n\",\n       \"        // location in version 2\\n\",\n       \"        IPython.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    var manager = IPython.notebook.keyboard_manager;\\n\",\n       \"    if (!manager)\\n\",\n       \"        manager = IPython.keyboard_manager;\\n\",\n       \"\\n\",\n       \"    // Check for shift+enter\\n\",\n       \"    if (event.shiftKey && event.which == 13) {\\n\",\n       \"        this.canvas_div.blur();\\n\",\n       \"        event.shiftKey = false;\\n\",\n       \"        // Send a \\\"J\\\" for go to next cell\\n\",\n       \"        event.which = 74;\\n\",\n       \"        event.keyCode = 74;\\n\",\n       \"        manager.command_mode();\\n\",\n       \"        manager.handle_keydown(event);\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    fig.ondownload(fig, null);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.find_output_cell = function(html_output) {\\n\",\n       \"    // Return the cell and output element which can be found *uniquely* in the notebook.\\n\",\n       \"    // Note - this is a bit hacky, but it is done because the \\\"notebook_saving.Notebook\\\"\\n\",\n       \"    // IPython event is triggered only after the cells have been serialised, which for\\n\",\n       \"    // our purposes (turning an active figure into a static one), is too late.\\n\",\n       \"    var cells = IPython.notebook.get_cells();\\n\",\n       \"    var ncells = cells.length;\\n\",\n       \"    for (var i=0; i<ncells; i++) {\\n\",\n       \"        var cell = cells[i];\\n\",\n       \"        if (cell.cell_type === 'code'){\\n\",\n       \"            for (var j=0; j<cell.output_area.outputs.length; j++) {\\n\",\n       \"                var data = cell.output_area.outputs[j];\\n\",\n       \"                if (data.data) {\\n\",\n       \"                    // IPython >= 3 moved mimebundle to data attribute of output\\n\",\n       \"                    data = data.data;\\n\",\n       \"                }\\n\",\n       \"                if (data['text/html'] == html_output) {\\n\",\n       \"                    return [cell, data, j];\\n\",\n       \"                }\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// Register the function which deals with the matplotlib target/channel.\\n\",\n       \"// The kernel may be null if the page has been refreshed.\\n\",\n       \"if (IPython.notebook.kernel != null) {\\n\",\n       \"    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\\n\",\n       \"}\\n\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.Javascript object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"text/html\": [\n       \"<img 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width=\\\"800\\\">\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.HTML object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"text/plain\": [\n       \"<matplotlib.collections.PathCollection at 0x7fba11552190>\"\n      ]\n     },\n     \"execution_count\": 9,\n     \"metadata\": {},\n     \"output_type\": \"execute_result\"\n    }\n   ],\n   \"source\": [\n    \"fig, ax = plt.subplots()\\n\",\n    \"fig.set_size_inches(8, 6)\\n\",\n    \"ax.scatter(*projection.T, s=10, linewidth=0, alpha=0.25)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"Next we set up a clustering algorithm. There are of course many algorithms available, see the documentation of _scikit-learn_. \\\"k-means\\\" is a simple and fast choice but requires the user to specify beforehand how many clusters should be found. A more sophisticated and modern algorithm is \\\"HDBSCAN\\\" (requires an extra package) which allows tuning via two parameters (`min_cluster_size` and `min_samples`, see their doc page). With HDBSCAN it is not guarantueed that always clusters are found.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 10,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"#clustering = HDBSCAN(min_cluster_size=50, min_samples=1)\\n\",\n    \"#clustering = HDBSCAN()\\n\",\n    \"clustering = KMeans(n_clusters=10)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"Finally, we can perform the cluster analysis:\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 11,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"CPU times: user 768 ms, sys: 3.99 ms, total: 772 ms\\n\",\n      \"Wall time: 773 ms\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"text/plain\": [\n       \"KMeans(n_clusters=10)\"\n      ]\n     },\n     \"execution_count\": 11,\n     \"metadata\": {},\n     \"output_type\": \"execute_result\"\n    }\n   ],\n   \"source\": [\n    \"%time clustering.fit(sf)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"Most clustering algorithms provide the output in the `labels_` variable which we can use to build a list of clusters and the corresponding atom indices:\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 12,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"Number of clusters: 10\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"cluster_indices_dict = {}\\n\",\n    \"for i,l in enumerate(clustering.labels_):\\n\",\n    \"    try:\\n\",\n    \"        cluster_indices_dict[l].extend([i])\\n\",\n    \"    except KeyError:\\n\",\n    \"        cluster_indices_dict[l] = [i]\\n\",\n    \"\\n\",\n    \"cluster_indices = []\\n\",\n    \"for i in sorted(cluster_indices_dict.keys()):\\n\",\n    \"    cluster_indices.append([i, cluster_indices_dict[i]])\\n\",\n    \"    \\n\",\n    \"num_clusters = len(cluster_indices)\\n\",\n    \"# HDBScan may not always assign a cluster label (label = -1 in this case).\\n\",\n    \"# Remove this list of indices from the beginning of the array.\\n\",\n    \"if cluster_indices[0][0] == -1:\\n\",\n    \"    num_clusters -= 1\\n\",\n    \"    cluster_indices = cluster_indices[1:]\\n\",\n    \"\\n\",\n    \"if num_clusters == 0:\\n\",\n    \"    print(\\\"WARNING: No clusters found!\\\")\\n\",\n    \"elif cluster_indices[-1][0] + 1 != num_clusters:\\n\",\n    \"    print(\\\"WARNING: Some cluster indices were not found!\\\")\\n\",\n    \"print(\\\"Number of clusters: {0:d}\\\".format(num_clusters))\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 13,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"# Preview color palette\\n\",\n    \"#sns.palplot(sns.color_palette(\\\"hls\\\", num_clusters))\\n\",\n    \"# Spectral, rainbow, hls, hsv, gist_rainbow\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"**OPTIONAL:** Now that we have found some symmetry function clusters we can reuse the t-SNE visualization to check how the clusters look like:\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 14,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"NOTE: Using only every 2th point for t-SNE visualization!\\n\",\n      \"\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"application/javascript\": [\n       \"/* Put everything inside the global mpl namespace */\\n\",\n       \"window.mpl = {};\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.get_websocket_type = function() {\\n\",\n       \"    if (typeof(WebSocket) !== 'undefined') {\\n\",\n       \"        return WebSocket;\\n\",\n       \"    } else if (typeof(MozWebSocket) !== 'undefined') {\\n\",\n       \"        return MozWebSocket;\\n\",\n       \"    } else {\\n\",\n       \"        alert('Your browser does not have WebSocket support. ' +\\n\",\n       \"              'Please try Chrome, Safari or Firefox ≥ 6. ' +\\n\",\n       \"              'Firefox 4 and 5 are also supported but you ' +\\n\",\n       \"              'have to enable WebSockets in about:config.');\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\\n\",\n       \"    this.id = figure_id;\\n\",\n       \"\\n\",\n       \"    this.ws = websocket;\\n\",\n       \"\\n\",\n       \"    this.supports_binary = (this.ws.binaryType != undefined);\\n\",\n       \"\\n\",\n       \"    if (!this.supports_binary) {\\n\",\n       \"        var warnings = document.getElementById(\\\"mpl-warnings\\\");\\n\",\n       \"        if (warnings) {\\n\",\n       \"            warnings.style.display = 'block';\\n\",\n       \"            warnings.textContent = (\\n\",\n       \"                \\\"This browser does not support binary websocket messages. \\\" +\\n\",\n       \"                    \\\"Performance may be slow.\\\");\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.imageObj = new Image();\\n\",\n       \"\\n\",\n       \"    this.context = undefined;\\n\",\n       \"    this.message = undefined;\\n\",\n       \"    this.canvas = undefined;\\n\",\n       \"    this.rubberband_canvas = undefined;\\n\",\n       \"    this.rubberband_context = undefined;\\n\",\n       \"    this.format_dropdown = undefined;\\n\",\n       \"\\n\",\n       \"    this.image_mode = 'full';\\n\",\n       \"\\n\",\n       \"    this.root = $('<div/>');\\n\",\n       \"    this._root_extra_style(this.root)\\n\",\n       \"    this.root.attr('style', 'display: inline-block');\\n\",\n       \"\\n\",\n       \"    $(parent_element).append(this.root);\\n\",\n       \"\\n\",\n       \"    this._init_header(this);\\n\",\n       \"    this._init_canvas(this);\\n\",\n       \"    this._init_toolbar(this);\\n\",\n       \"\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    this.waiting = false;\\n\",\n       \"\\n\",\n       \"    this.ws.onopen =  function () {\\n\",\n       \"            fig.send_message(\\\"supports_binary\\\", {value: fig.supports_binary});\\n\",\n       \"            fig.send_message(\\\"send_image_mode\\\", {});\\n\",\n       \"            if (mpl.ratio != 1) {\\n\",\n       \"                fig.send_message(\\\"set_dpi_ratio\\\", {'dpi_ratio': mpl.ratio});\\n\",\n       \"            }\\n\",\n       \"            fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"    this.imageObj.onload = function() {\\n\",\n       \"            if (fig.image_mode == 'full') {\\n\",\n       \"                // Full images could contain transparency (where diff images\\n\",\n       \"                // almost always do), so we need to clear the canvas so that\\n\",\n       \"                // there is no ghosting.\\n\",\n       \"                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\\n\",\n       \"            }\\n\",\n       \"            fig.context.drawImage(fig.imageObj, 0, 0);\\n\",\n       \"        };\\n\",\n       \"\\n\",\n       \"    this.imageObj.onunload = function() {\\n\",\n       \"        fig.ws.close();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.ws.onmessage = this._make_on_message_function(this);\\n\",\n       \"\\n\",\n       \"    this.ondownload = ondownload;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_header = function() {\\n\",\n       \"    var titlebar = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\\n\",\n       \"        'ui-helper-clearfix\\\"/>');\\n\",\n       \"    var titletext = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-title\\\" style=\\\"width: 100%; ' +\\n\",\n       \"        'text-align: center; padding: 3px;\\\"/>');\\n\",\n       \"    titlebar.append(titletext)\\n\",\n       \"    this.root.append(titlebar);\\n\",\n       \"    this.header = titletext[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_canvas = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var canvas_div = $('<div/>');\\n\",\n       \"\\n\",\n       \"    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\\n\",\n       \"\\n\",\n       \"    function canvas_keyboard_event(event) {\\n\",\n       \"        return fig.key_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    canvas_div.keydown('key_press', canvas_keyboard_event);\\n\",\n       \"    canvas_div.keyup('key_release', canvas_keyboard_event);\\n\",\n       \"    this.canvas_div = canvas_div\\n\",\n       \"    this._canvas_extra_style(canvas_div)\\n\",\n       \"    this.root.append(canvas_div);\\n\",\n       \"\\n\",\n       \"    var canvas = $('<canvas/>');\\n\",\n       \"    canvas.addClass('mpl-canvas');\\n\",\n       \"    canvas.attr('style', \\\"left: 0; top: 0; z-index: 0; outline: 0\\\")\\n\",\n       \"\\n\",\n       \"    this.canvas = canvas[0];\\n\",\n       \"    this.context = canvas[0].getContext(\\\"2d\\\");\\n\",\n       \"\\n\",\n       \"    var backingStore = this.context.backingStorePixelRatio ||\\n\",\n       \"\\tthis.context.webkitBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.mozBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.msBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.oBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.backingStorePixelRatio || 1;\\n\",\n       \"\\n\",\n       \"    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\\n\",\n       \"\\n\",\n       \"    var rubberband = $('<canvas/>');\\n\",\n       \"    rubberband.attr('style', \\\"position: absolute; left: 0; top: 0; z-index: 1;\\\")\\n\",\n       \"\\n\",\n       \"    var pass_mouse_events = true;\\n\",\n       \"\\n\",\n       \"    canvas_div.resizable({\\n\",\n       \"        start: function(event, ui) {\\n\",\n       \"            pass_mouse_events = false;\\n\",\n       \"        },\\n\",\n       \"        resize: function(event, ui) {\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"        stop: function(event, ui) {\\n\",\n       \"            pass_mouse_events = true;\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function mouse_event_fn(event) {\\n\",\n       \"        if (pass_mouse_events)\\n\",\n       \"            return fig.mouse_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    rubberband.mousedown('button_press', mouse_event_fn);\\n\",\n       \"    rubberband.mouseup('button_release', mouse_event_fn);\\n\",\n       \"    // Throttle sequential mouse events to 1 every 20ms.\\n\",\n       \"    rubberband.mousemove('motion_notify', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    rubberband.mouseenter('figure_enter', mouse_event_fn);\\n\",\n       \"    rubberband.mouseleave('figure_leave', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    canvas_div.on(\\\"wheel\\\", function (event) {\\n\",\n       \"        event = event.originalEvent;\\n\",\n       \"        event['data'] = 'scroll'\\n\",\n       \"        if (event.deltaY < 0) {\\n\",\n       \"            event.step = 1;\\n\",\n       \"        } else {\\n\",\n       \"            event.step = -1;\\n\",\n       \"        }\\n\",\n       \"        mouse_event_fn(event);\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    canvas_div.append(canvas);\\n\",\n       \"    canvas_div.append(rubberband);\\n\",\n       \"\\n\",\n       \"    this.rubberband = rubberband;\\n\",\n       \"    this.rubberband_canvas = rubberband[0];\\n\",\n       \"    this.rubberband_context = rubberband[0].getContext(\\\"2d\\\");\\n\",\n       \"    this.rubberband_context.strokeStyle = \\\"#000000\\\";\\n\",\n       \"\\n\",\n       \"    this._resize_canvas = function(width, height) {\\n\",\n       \"        // Keep the size of the canvas, canvas container, and rubber band\\n\",\n       \"        // canvas in synch.\\n\",\n       \"        canvas_div.css('width', width)\\n\",\n       \"        canvas_div.css('height', height)\\n\",\n       \"\\n\",\n       \"        canvas.attr('width', width * mpl.ratio);\\n\",\n       \"        canvas.attr('height', height * mpl.ratio);\\n\",\n       \"        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\\n\",\n       \"\\n\",\n       \"        rubberband.attr('width', width);\\n\",\n       \"        rubberband.attr('height', height);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Set the figure to an initial 600x600px, this will subsequently be updated\\n\",\n       \"    // upon first draw.\\n\",\n       \"    this._resize_canvas(600, 600);\\n\",\n       \"\\n\",\n       \"    // Disable right mouse context menu.\\n\",\n       \"    $(this.rubberband_canvas).bind(\\\"contextmenu\\\",function(e){\\n\",\n       \"        return false;\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function set_focus () {\\n\",\n       \"        canvas.focus();\\n\",\n       \"        canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    window.setTimeout(set_focus, 100);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>');\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items) {\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) {\\n\",\n       \"            // put a spacer in here.\\n\",\n       \"            continue;\\n\",\n       \"        }\\n\",\n       \"        var button = $('<button/>');\\n\",\n       \"        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\\n\",\n       \"                        'ui-button-icon-only');\\n\",\n       \"        button.attr('role', 'button');\\n\",\n       \"        button.attr('aria-disabled', 'false');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"\\n\",\n       \"        var icon_img = $('<span/>');\\n\",\n       \"        icon_img.addClass('ui-button-icon-primary ui-icon');\\n\",\n       \"        icon_img.addClass(image);\\n\",\n       \"        icon_img.addClass('ui-corner-all');\\n\",\n       \"\\n\",\n       \"        var tooltip_span = $('<span/>');\\n\",\n       \"        tooltip_span.addClass('ui-button-text');\\n\",\n       \"        tooltip_span.html(tooltip);\\n\",\n       \"\\n\",\n       \"        button.append(icon_img);\\n\",\n       \"        button.append(tooltip_span);\\n\",\n       \"\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fmt_picker_span = $('<span/>');\\n\",\n       \"\\n\",\n       \"    var fmt_picker = $('<select/>');\\n\",\n       \"    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\\n\",\n       \"    fmt_picker_span.append(fmt_picker);\\n\",\n       \"    nav_element.append(fmt_picker_span);\\n\",\n       \"    this.format_dropdown = fmt_picker[0];\\n\",\n       \"\\n\",\n       \"    for (var ind in mpl.extensions) {\\n\",\n       \"        var fmt = mpl.extensions[ind];\\n\",\n       \"        var option = $(\\n\",\n       \"            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\\n\",\n       \"        fmt_picker.append(option);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add hover states to the ui-buttons\\n\",\n       \"    $( \\\".ui-button\\\" ).hover(\\n\",\n       \"        function() { $(this).addClass(\\\"ui-state-hover\\\");},\\n\",\n       \"        function() { $(this).removeClass(\\\"ui-state-hover\\\");}\\n\",\n       \"    );\\n\",\n       \"\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\\n\",\n       \"    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\\n\",\n       \"    // which will in turn request a refresh of the image.\\n\",\n       \"    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_message = function(type, properties) {\\n\",\n       \"    properties['type'] = type;\\n\",\n       \"    properties['figure_id'] = this.id;\\n\",\n       \"    this.ws.send(JSON.stringify(properties));\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_draw_message = function() {\\n\",\n       \"    if (!this.waiting) {\\n\",\n       \"        this.waiting = true;\\n\",\n       \"        this.ws.send(JSON.stringify({type: \\\"draw\\\", figure_id: this.id}));\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    var format_dropdown = fig.format_dropdown;\\n\",\n       \"    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\\n\",\n       \"    fig.ondownload(fig, format);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_resize = function(fig, msg) {\\n\",\n       \"    var size = msg['size'];\\n\",\n       \"    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\\n\",\n       \"        fig._resize_canvas(size[0], size[1]);\\n\",\n       \"        fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\\n\",\n       \"    var x0 = msg['x0'] / mpl.ratio;\\n\",\n       \"    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\\n\",\n       \"    var x1 = msg['x1'] / mpl.ratio;\\n\",\n       \"    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\\n\",\n       \"    x0 = Math.floor(x0) + 0.5;\\n\",\n       \"    y0 = Math.floor(y0) + 0.5;\\n\",\n       \"    x1 = Math.floor(x1) + 0.5;\\n\",\n       \"    y1 = Math.floor(y1) + 0.5;\\n\",\n       \"    var min_x = Math.min(x0, x1);\\n\",\n       \"    var min_y = Math.min(y0, y1);\\n\",\n       \"    var width = Math.abs(x1 - x0);\\n\",\n       \"    var height = Math.abs(y1 - y0);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.clearRect(\\n\",\n       \"        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\\n\",\n       \"    // Updates the figure title.\\n\",\n       \"    fig.header.textContent = msg['label'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_cursor = function(fig, msg) {\\n\",\n       \"    var cursor = msg['cursor'];\\n\",\n       \"    switch(cursor)\\n\",\n       \"    {\\n\",\n       \"    case 0:\\n\",\n       \"        cursor = 'pointer';\\n\",\n       \"        break;\\n\",\n       \"    case 1:\\n\",\n       \"        cursor = 'default';\\n\",\n       \"        break;\\n\",\n       \"    case 2:\\n\",\n       \"        cursor = 'crosshair';\\n\",\n       \"        break;\\n\",\n       \"    case 3:\\n\",\n       \"        cursor = 'move';\\n\",\n       \"        break;\\n\",\n       \"    }\\n\",\n       \"    fig.rubberband_canvas.style.cursor = cursor;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_message = function(fig, msg) {\\n\",\n       \"    fig.message.textContent = msg['message'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_draw = function(fig, msg) {\\n\",\n       \"    // Request the server to send over a new figure.\\n\",\n       \"    fig.send_draw_message();\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\\n\",\n       \"    fig.image_mode = msg['mode'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Called whenever the canvas gets updated.\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// A function to construct a web socket function for onmessage handling.\\n\",\n       \"// Called in the figure constructor.\\n\",\n       \"mpl.figure.prototype._make_on_message_function = function(fig) {\\n\",\n       \"    return function socket_on_message(evt) {\\n\",\n       \"        if (evt.data instanceof Blob) {\\n\",\n       \"            /* FIXME: We get \\\"Resource interpreted as Image but\\n\",\n       \"             * transferred with MIME type text/plain:\\\" errors on\\n\",\n       \"             * Chrome.  But how to set the MIME type?  It doesn't seem\\n\",\n       \"             * to be part of the websocket stream */\\n\",\n       \"            evt.data.type = \\\"image/png\\\";\\n\",\n       \"\\n\",\n       \"            /* Free the memory for the previous frames */\\n\",\n       \"            if (fig.imageObj.src) {\\n\",\n       \"                (window.URL || window.webkitURL).revokeObjectURL(\\n\",\n       \"                    fig.imageObj.src);\\n\",\n       \"            }\\n\",\n       \"\\n\",\n       \"            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\\n\",\n       \"                evt.data);\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \\\"data:image/png;base64\\\") {\\n\",\n       \"            fig.imageObj.src = evt.data;\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        var msg = JSON.parse(evt.data);\\n\",\n       \"        var msg_type = msg['type'];\\n\",\n       \"\\n\",\n       \"        // Call the  \\\"handle_{type}\\\" callback, which takes\\n\",\n       \"        // the figure and JSON message as its only arguments.\\n\",\n       \"        try {\\n\",\n       \"            var callback = fig[\\\"handle_\\\" + msg_type];\\n\",\n       \"        } catch (e) {\\n\",\n       \"            console.log(\\\"No handler for the '\\\" + msg_type + \\\"' message type: \\\", msg);\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        if (callback) {\\n\",\n       \"            try {\\n\",\n       \"                // console.log(\\\"Handling '\\\" + msg_type + \\\"' message: \\\", msg);\\n\",\n       \"                callback(fig, msg);\\n\",\n       \"            } catch (e) {\\n\",\n       \"                console.log(\\\"Exception inside the 'handler_\\\" + msg_type + \\\"' callback:\\\", e, e.stack, msg);\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\\n\",\n       \"mpl.findpos = function(e) {\\n\",\n       \"    //this section is from http://www.quirksmode.org/js/events_properties.html\\n\",\n       \"    var targ;\\n\",\n       \"    if (!e)\\n\",\n       \"        e = window.event;\\n\",\n       \"    if (e.target)\\n\",\n       \"        targ = e.target;\\n\",\n       \"    else if (e.srcElement)\\n\",\n       \"        targ = e.srcElement;\\n\",\n       \"    if (targ.nodeType == 3) // defeat Safari bug\\n\",\n       \"        targ = targ.parentNode;\\n\",\n       \"\\n\",\n       \"    // jQuery normalizes the pageX and pageY\\n\",\n       \"    // pageX,Y are the mouse positions relative to the document\\n\",\n       \"    // offset() returns the position of the element relative to the document\\n\",\n       \"    var x = e.pageX - $(targ).offset().left;\\n\",\n       \"    var y = e.pageY - $(targ).offset().top;\\n\",\n       \"\\n\",\n       \"    return {\\\"x\\\": x, \\\"y\\\": y};\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"/*\\n\",\n       \" * return a copy of an object with only non-object keys\\n\",\n       \" * we need this to avoid circular references\\n\",\n       \" * http://stackoverflow.com/a/24161582/3208463\\n\",\n       \" */\\n\",\n       \"function simpleKeys (original) {\\n\",\n       \"  return Object.keys(original).reduce(function (obj, key) {\\n\",\n       \"    if (typeof original[key] !== 'object')\\n\",\n       \"        obj[key] = original[key]\\n\",\n       \"    return obj;\\n\",\n       \"  }, {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.mouse_event = function(event, name) {\\n\",\n       \"    var canvas_pos = mpl.findpos(event)\\n\",\n       \"\\n\",\n       \"    if (name === 'button_press')\\n\",\n       \"    {\\n\",\n       \"        this.canvas.focus();\\n\",\n       \"        this.canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var x = canvas_pos.x * mpl.ratio;\\n\",\n       \"    var y = canvas_pos.y * mpl.ratio;\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {x: x, y: y, button: event.button,\\n\",\n       \"                             step: event.step,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"\\n\",\n       \"    /* This prevents the web browser from automatically changing to\\n\",\n       \"     * the text insertion cursor when the button is pressed.  We want\\n\",\n       \"     * to control all of the cursor setting manually through the\\n\",\n       \"     * 'cursor' event from matplotlib */\\n\",\n       \"    event.preventDefault();\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    // Handle any extra behaviour associated with a key event\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.key_event = function(event, name) {\\n\",\n       \"\\n\",\n       \"    // Prevent repeat events\\n\",\n       \"    if (name == 'key_press')\\n\",\n       \"    {\\n\",\n       \"        if (event.which === this._key)\\n\",\n       \"            return;\\n\",\n       \"        else\\n\",\n       \"            this._key = event.which;\\n\",\n       \"    }\\n\",\n       \"    if (name == 'key_release')\\n\",\n       \"        this._key = null;\\n\",\n       \"\\n\",\n       \"    var value = '';\\n\",\n       \"    if (event.ctrlKey && event.which != 17)\\n\",\n       \"        value += \\\"ctrl+\\\";\\n\",\n       \"    if (event.altKey && event.which != 18)\\n\",\n       \"        value += \\\"alt+\\\";\\n\",\n       \"    if (event.shiftKey && event.which != 16)\\n\",\n       \"        value += \\\"shift+\\\";\\n\",\n       \"\\n\",\n       \"    value += 'k';\\n\",\n       \"    value += event.which.toString();\\n\",\n       \"\\n\",\n       \"    this._key_event_extra(event, name);\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {key: value,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onclick = function(name) {\\n\",\n       \"    if (name == 'download') {\\n\",\n       \"        this.handle_save(this, null);\\n\",\n       \"    } else {\\n\",\n       \"        this.send_message(\\\"toolbar_button\\\", {name: name});\\n\",\n       \"    }\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\\n\",\n       \"    this.message.textContent = tooltip;\\n\",\n       \"};\\n\",\n       \"mpl.toolbar_items = [[\\\"Home\\\", \\\"Reset original view\\\", \\\"fa fa-home icon-home\\\", \\\"home\\\"], [\\\"Back\\\", \\\"Back to previous view\\\", \\\"fa fa-arrow-left icon-arrow-left\\\", \\\"back\\\"], [\\\"Forward\\\", \\\"Forward to next view\\\", \\\"fa fa-arrow-right icon-arrow-right\\\", \\\"forward\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Pan\\\", \\\"Pan axes with left mouse, zoom with right\\\", \\\"fa fa-arrows icon-move\\\", \\\"pan\\\"], [\\\"Zoom\\\", \\\"Zoom to rectangle\\\", \\\"fa fa-square-o icon-check-empty\\\", \\\"zoom\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Download\\\", \\\"Download plot\\\", \\\"fa fa-floppy-o icon-save\\\", \\\"download\\\"]];\\n\",\n       \"\\n\",\n       \"mpl.extensions = [\\\"eps\\\", \\\"jpeg\\\", \\\"pdf\\\", \\\"png\\\", \\\"ps\\\", \\\"raw\\\", \\\"svg\\\", \\\"tif\\\"];\\n\",\n       \"\\n\",\n       \"mpl.default_extension = \\\"png\\\";var comm_websocket_adapter = function(comm) {\\n\",\n       \"    // Create a \\\"websocket\\\"-like object which calls the given IPython comm\\n\",\n       \"    // object with the appropriate methods. Currently this is a non binary\\n\",\n       \"    // socket, so there is still some room for performance tuning.\\n\",\n       \"    var ws = {};\\n\",\n       \"\\n\",\n       \"    ws.close = function() {\\n\",\n       \"        comm.close()\\n\",\n       \"    };\\n\",\n       \"    ws.send = function(m) {\\n\",\n       \"        //console.log('sending', m);\\n\",\n       \"        comm.send(m);\\n\",\n       \"    };\\n\",\n       \"    // Register the callback with on_msg.\\n\",\n       \"    comm.on_msg(function(msg) {\\n\",\n       \"        //console.log('receiving', msg['content']['data'], msg);\\n\",\n       \"        // Pass the mpl event to the overridden (by mpl) onmessage function.\\n\",\n       \"        ws.onmessage(msg['content']['data'])\\n\",\n       \"    });\\n\",\n       \"    return ws;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.mpl_figure_comm = function(comm, msg) {\\n\",\n       \"    // This is the function which gets called when the mpl process\\n\",\n       \"    // starts-up an IPython Comm through the \\\"matplotlib\\\" channel.\\n\",\n       \"\\n\",\n       \"    var id = msg.content.data.id;\\n\",\n       \"    // Get hold of the div created by the display call when the Comm\\n\",\n       \"    // socket was opened in Python.\\n\",\n       \"    var element = $(\\\"#\\\" + id);\\n\",\n       \"    var ws_proxy = comm_websocket_adapter(comm)\\n\",\n       \"\\n\",\n       \"    function ondownload(figure, format) {\\n\",\n       \"        window.open(figure.imageObj.src);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fig = new mpl.figure(id, ws_proxy,\\n\",\n       \"                           ondownload,\\n\",\n       \"                           element.get(0));\\n\",\n       \"\\n\",\n       \"    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\\n\",\n       \"    // web socket which is closed, not our websocket->open comm proxy.\\n\",\n       \"    ws_proxy.onopen();\\n\",\n       \"\\n\",\n       \"    fig.parent_element = element.get(0);\\n\",\n       \"    fig.cell_info = mpl.find_output_cell(\\\"<div id='\\\" + id + \\\"'></div>\\\");\\n\",\n       \"    if (!fig.cell_info) {\\n\",\n       \"        console.error(\\\"Failed to find cell for figure\\\", id, fig);\\n\",\n       \"        return;\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var output_index = fig.cell_info[2]\\n\",\n       \"    var cell = fig.cell_info[0];\\n\",\n       \"\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_close = function(fig, msg) {\\n\",\n       \"    var width = fig.canvas.width/mpl.ratio\\n\",\n       \"    fig.root.unbind('remove')\\n\",\n       \"\\n\",\n       \"    // Update the output cell to use the data from the current canvas.\\n\",\n       \"    fig.push_to_output();\\n\",\n       \"    var dataURL = fig.canvas.toDataURL();\\n\",\n       \"    // Re-enable the keyboard manager in IPython - without this line, in FF,\\n\",\n       \"    // the notebook keyboard shortcuts fail.\\n\",\n       \"    IPython.keyboard_manager.enable()\\n\",\n       \"    $(fig.parent_element).html('<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">');\\n\",\n       \"    fig.close_ws(fig, msg);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.close_ws = function(fig, msg){\\n\",\n       \"    fig.send_message('closing', msg);\\n\",\n       \"    // fig.ws.close()\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.push_to_output = function(remove_interactive) {\\n\",\n       \"    // Turn the data on the canvas into data in the output cell.\\n\",\n       \"    var width = this.canvas.width/mpl.ratio\\n\",\n       \"    var dataURL = this.canvas.toDataURL();\\n\",\n       \"    this.cell_info[1]['text/html'] = '<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">';\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Tell IPython that the notebook contents must change.\\n\",\n       \"    IPython.notebook.set_dirty(true);\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"    var fig = this;\\n\",\n       \"    // Wait a second, then push the new image to the DOM so\\n\",\n       \"    // that it is saved nicely (might be nice to debounce this).\\n\",\n       \"    setTimeout(function () { fig.push_to_output() }, 1000);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>');\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items){\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) { continue; };\\n\",\n       \"\\n\",\n       \"        var button = $('<button class=\\\"btn btn-default\\\" href=\\\"#\\\" title=\\\"' + name + '\\\"><i class=\\\"fa ' + image + ' fa-lg\\\"></i></button>');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add the status bar.\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\" style=\\\"text-align:right; float: right;\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"\\n\",\n       \"    // Add the close button to the window.\\n\",\n       \"    var buttongrp = $('<div class=\\\"btn-group inline pull-right\\\"></div>');\\n\",\n       \"    var button = $('<button class=\\\"btn btn-mini btn-primary\\\" href=\\\"#\\\" title=\\\"Stop Interaction\\\"><i class=\\\"fa fa-power-off icon-remove icon-large\\\"></i></button>');\\n\",\n       \"    button.click(function (evt) { fig.handle_close(fig, {}); } );\\n\",\n       \"    button.mouseover('Stop Interaction', toolbar_mouse_event);\\n\",\n       \"    buttongrp.append(button);\\n\",\n       \"    var titlebar = this.root.find($('.ui-dialog-titlebar'));\\n\",\n       \"    titlebar.prepend(buttongrp);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(el){\\n\",\n       \"    var fig = this\\n\",\n       \"    el.on(\\\"remove\\\", function(){\\n\",\n       \"\\tfig.close_ws(fig, {});\\n\",\n       \"    });\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(el){\\n\",\n       \"    // this is important to make the div 'focusable\\n\",\n       \"    el.attr('tabindex', 0)\\n\",\n       \"    // reach out to IPython and tell the keyboard manager to turn it's self\\n\",\n       \"    // off when our div gets focus\\n\",\n       \"\\n\",\n       \"    // location in version 3\\n\",\n       \"    if (IPython.notebook.keyboard_manager) {\\n\",\n       \"        IPython.notebook.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"    else {\\n\",\n       \"        // location in version 2\\n\",\n       \"        IPython.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    var manager = IPython.notebook.keyboard_manager;\\n\",\n       \"    if (!manager)\\n\",\n       \"        manager = IPython.keyboard_manager;\\n\",\n       \"\\n\",\n       \"    // Check for shift+enter\\n\",\n       \"    if (event.shiftKey && event.which == 13) {\\n\",\n       \"        this.canvas_div.blur();\\n\",\n       \"        event.shiftKey = false;\\n\",\n       \"        // Send a \\\"J\\\" for go to next cell\\n\",\n       \"        event.which = 74;\\n\",\n       \"        event.keyCode = 74;\\n\",\n       \"        manager.command_mode();\\n\",\n       \"        manager.handle_keydown(event);\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    fig.ondownload(fig, null);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.find_output_cell = function(html_output) {\\n\",\n       \"    // Return the cell and output element which can be found *uniquely* in the notebook.\\n\",\n       \"    // Note - this is a bit hacky, but it is done because the \\\"notebook_saving.Notebook\\\"\\n\",\n       \"    // IPython event is triggered only after the cells have been serialised, which for\\n\",\n       \"    // our purposes (turning an active figure into a static one), is too late.\\n\",\n       \"    var cells = IPython.notebook.get_cells();\\n\",\n       \"    var ncells = cells.length;\\n\",\n       \"    for (var i=0; i<ncells; i++) {\\n\",\n       \"        var cell = cells[i];\\n\",\n       \"        if (cell.cell_type === 'code'){\\n\",\n       \"            for (var j=0; j<cell.output_area.outputs.length; j++) {\\n\",\n       \"                var data = cell.output_area.outputs[j];\\n\",\n       \"                if (data.data) {\\n\",\n       \"                    // IPython >= 3 moved mimebundle to data attribute of output\\n\",\n       \"                    data = data.data;\\n\",\n       \"                }\\n\",\n       \"                if (data['text/html'] == html_output) {\\n\",\n       \"                    return [cell, data, j];\\n\",\n       \"                }\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// Register the function which deals with the matplotlib target/channel.\\n\",\n       \"// The kernel may be null if the page has been refreshed.\\n\",\n       \"if (IPython.notebook.kernel != null) {\\n\",\n       \"    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\\n\",\n       \"}\\n\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.Javascript object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"text/html\": [\n       \"<img src=\\\"data:image/png;base64,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\\\" width=\\\"800\\\">\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.HTML object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"if vis_sp > 1:\\n\",\n    \"    print(\\\"NOTE: Using only every {0:d}th point for t-SNE visualization!\\\\n\\\".format(vis_sp))\\n\",\n    \"\\n\",\n    \"color_palette = sns.color_palette(\\\"gist_rainbow\\\", num_clusters)\\n\",\n    \"cluster_colors = [color_palette[x] if x >= 0\\n\",\n    \"                  else (0.5, 0.5, 0.5)\\n\",\n    \"                  for x in clustering.labels_[::vis_sp]]\\n\",\n    \"# Only HDBSCAN provides probabilities_ information.\\n\",\n    \"try:\\n\",\n    \"    cluster_member_colors = [sns.desaturate(x, p) for x, p in\\n\",\n    \"                             zip(cluster_colors, clustering.probabilities_[::vis_sp])]\\n\",\n    \"except AttributeError:\\n\",\n    \"    cluster_member_colors = cluster_colors\\n\",\n    \"\\n\",\n    \"fig, ax = plt.subplots()\\n\",\n    \"fig.set_size_inches(8, 6)\\n\",\n    \"scatter = ax.scatter(*projection.T, s=20, linewidth=0, c=cluster_member_colors, alpha=0.25)\\n\",\n    \"legend_elements = [Line2D([0], [0], marker='o', color=\\\"white\\\", markerfacecolor=color_palette[i], label='{0:d}'.format(i), markersize=12) for i in range(len(color_palette))]\\n\",\n    \"ax.legend(handles=legend_elements, loc='best', title=\\\"Index\\\")\\n\",\n    \"fig.savefig(f\\\"tsne_visualization_{extract_element}.pdf\\\")\\n\",\n    \"fig.savefig(f\\\"tsne_visualization_{extract_element}.png\\\", dpi=300)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"Now comes the actual analysis... we loop over all clusters and for each one we perform a statistical test. First, the forces belonging to a cluster are grouped (`f_clust`) and excluded from the remaining set (`f_excl`). These two sets are then compared with Welch's t-test (`stats.ttest_ind(equal_var=False)`), where the null hypothesis is that they have an equal mean value. Here, there are two possible outcomes:\\n\",\n    \"\\n\",\n    \"  1. The null hypothesis is **accepted** (technically \\\"failed to reject\\\", p-value > `pvalue_max`):  \\n\",\n    \"  \\n\",\n    \"  We cannot distinguish the distributions (well, at least the mean is the same). Hence, the atom indices obtained from clustering their symmetry function vectors are not distinguishable from a randomly picked subset of indices. In other words, similar symmetry functions do not correspond to similar atomic forces (only exception: forces close to the overall mean force, usually zero)\\n\",\n    \"  \\n\",\n    \"  \\n\",\n    \"  2. The null hypothesis is **rejected** (p-value < `pvalue_max`):\\n\",\n    \"  \\n\",\n    \"  The distribution of forces is different for the two subsets. Therefore we can argue that the symmetry function clusters correspond to similar atomic environments and hence similar forces different from the overall mean.\\n\",\n    \"\\n\",\n    \"Of course we hope for many occurences of case (2)... hence, we count their percentage with respect to all tests.\\n\",\n    \"\\n\",\n    \"In order to visualize the results we can plot histograms for each cluster. The grey histogram is the distribution of forces in the \\\"remaining\\\" set. A green histogram of the cluster forces is plotted if the null hypothesis is \\\"successfully\\\" rejected (case (2)), a red one otherwise.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 15,\n   \"metadata\": {\n    \"scrolled\": false\n   },\n   \"outputs\": [\n    {\n     \"data\": {\n      \"application/javascript\": [\n       \"/* Put everything inside the global mpl namespace */\\n\",\n       \"window.mpl = {};\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.get_websocket_type = function() {\\n\",\n       \"    if (typeof(WebSocket) !== 'undefined') {\\n\",\n       \"        return WebSocket;\\n\",\n       \"    } else if (typeof(MozWebSocket) !== 'undefined') {\\n\",\n       \"        return MozWebSocket;\\n\",\n       \"    } else {\\n\",\n       \"        alert('Your browser does not have WebSocket support. ' +\\n\",\n       \"              'Please try Chrome, Safari or Firefox ≥ 6. ' +\\n\",\n       \"              'Firefox 4 and 5 are also supported but you ' +\\n\",\n       \"              'have to enable WebSockets in about:config.');\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\\n\",\n       \"    this.id = figure_id;\\n\",\n       \"\\n\",\n       \"    this.ws = websocket;\\n\",\n       \"\\n\",\n       \"    this.supports_binary = (this.ws.binaryType != undefined);\\n\",\n       \"\\n\",\n       \"    if (!this.supports_binary) {\\n\",\n       \"        var warnings = document.getElementById(\\\"mpl-warnings\\\");\\n\",\n       \"        if (warnings) {\\n\",\n       \"            warnings.style.display = 'block';\\n\",\n       \"            warnings.textContent = (\\n\",\n       \"                \\\"This browser does not support binary websocket messages. \\\" +\\n\",\n       \"                    \\\"Performance may be slow.\\\");\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.imageObj = new Image();\\n\",\n       \"\\n\",\n       \"    this.context = undefined;\\n\",\n       \"    this.message = undefined;\\n\",\n       \"    this.canvas = undefined;\\n\",\n       \"    this.rubberband_canvas = undefined;\\n\",\n       \"    this.rubberband_context = undefined;\\n\",\n       \"    this.format_dropdown = undefined;\\n\",\n       \"\\n\",\n       \"    this.image_mode = 'full';\\n\",\n       \"\\n\",\n       \"    this.root = $('<div/>');\\n\",\n       \"    this._root_extra_style(this.root)\\n\",\n       \"    this.root.attr('style', 'display: inline-block');\\n\",\n       \"\\n\",\n       \"    $(parent_element).append(this.root);\\n\",\n       \"\\n\",\n       \"    this._init_header(this);\\n\",\n       \"    this._init_canvas(this);\\n\",\n       \"    this._init_toolbar(this);\\n\",\n       \"\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    this.waiting = false;\\n\",\n       \"\\n\",\n       \"    this.ws.onopen =  function () {\\n\",\n       \"            fig.send_message(\\\"supports_binary\\\", {value: fig.supports_binary});\\n\",\n       \"            fig.send_message(\\\"send_image_mode\\\", {});\\n\",\n       \"            if (mpl.ratio != 1) {\\n\",\n       \"                fig.send_message(\\\"set_dpi_ratio\\\", {'dpi_ratio': mpl.ratio});\\n\",\n       \"            }\\n\",\n       \"            fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"    this.imageObj.onload = function() {\\n\",\n       \"            if (fig.image_mode == 'full') {\\n\",\n       \"                // Full images could contain transparency (where diff images\\n\",\n       \"                // almost always do), so we need to clear the canvas so that\\n\",\n       \"                // there is no ghosting.\\n\",\n       \"                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\\n\",\n       \"            }\\n\",\n       \"            fig.context.drawImage(fig.imageObj, 0, 0);\\n\",\n       \"        };\\n\",\n       \"\\n\",\n       \"    this.imageObj.onunload = function() {\\n\",\n       \"        fig.ws.close();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.ws.onmessage = this._make_on_message_function(this);\\n\",\n       \"\\n\",\n       \"    this.ondownload = ondownload;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_header = function() {\\n\",\n       \"    var titlebar = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\\n\",\n       \"        'ui-helper-clearfix\\\"/>');\\n\",\n       \"    var titletext = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-title\\\" style=\\\"width: 100%; ' +\\n\",\n       \"        'text-align: center; padding: 3px;\\\"/>');\\n\",\n       \"    titlebar.append(titletext)\\n\",\n       \"    this.root.append(titlebar);\\n\",\n       \"    this.header = titletext[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_canvas = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var canvas_div = $('<div/>');\\n\",\n       \"\\n\",\n       \"    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\\n\",\n       \"\\n\",\n       \"    function canvas_keyboard_event(event) {\\n\",\n       \"        return fig.key_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    canvas_div.keydown('key_press', canvas_keyboard_event);\\n\",\n       \"    canvas_div.keyup('key_release', canvas_keyboard_event);\\n\",\n       \"    this.canvas_div = canvas_div\\n\",\n       \"    this._canvas_extra_style(canvas_div)\\n\",\n       \"    this.root.append(canvas_div);\\n\",\n       \"\\n\",\n       \"    var canvas = $('<canvas/>');\\n\",\n       \"    canvas.addClass('mpl-canvas');\\n\",\n       \"    canvas.attr('style', \\\"left: 0; top: 0; z-index: 0; outline: 0\\\")\\n\",\n       \"\\n\",\n       \"    this.canvas = canvas[0];\\n\",\n       \"    this.context = canvas[0].getContext(\\\"2d\\\");\\n\",\n       \"\\n\",\n       \"    var backingStore = this.context.backingStorePixelRatio ||\\n\",\n       \"\\tthis.context.webkitBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.mozBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.msBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.oBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.backingStorePixelRatio || 1;\\n\",\n       \"\\n\",\n       \"    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\\n\",\n       \"\\n\",\n       \"    var rubberband = $('<canvas/>');\\n\",\n       \"    rubberband.attr('style', \\\"position: absolute; left: 0; top: 0; z-index: 1;\\\")\\n\",\n       \"\\n\",\n       \"    var pass_mouse_events = true;\\n\",\n       \"\\n\",\n       \"    canvas_div.resizable({\\n\",\n       \"        start: function(event, ui) {\\n\",\n       \"            pass_mouse_events = false;\\n\",\n       \"        },\\n\",\n       \"        resize: function(event, ui) {\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"        stop: function(event, ui) {\\n\",\n       \"            pass_mouse_events = true;\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function mouse_event_fn(event) {\\n\",\n       \"        if (pass_mouse_events)\\n\",\n       \"            return fig.mouse_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    rubberband.mousedown('button_press', mouse_event_fn);\\n\",\n       \"    rubberband.mouseup('button_release', mouse_event_fn);\\n\",\n       \"    // Throttle sequential mouse events to 1 every 20ms.\\n\",\n       \"    rubberband.mousemove('motion_notify', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    rubberband.mouseenter('figure_enter', mouse_event_fn);\\n\",\n       \"    rubberband.mouseleave('figure_leave', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    canvas_div.on(\\\"wheel\\\", function (event) {\\n\",\n       \"        event = event.originalEvent;\\n\",\n       \"        event['data'] = 'scroll'\\n\",\n       \"        if (event.deltaY < 0) {\\n\",\n       \"            event.step = 1;\\n\",\n       \"        } else {\\n\",\n       \"            event.step = -1;\\n\",\n       \"        }\\n\",\n       \"        mouse_event_fn(event);\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    canvas_div.append(canvas);\\n\",\n       \"    canvas_div.append(rubberband);\\n\",\n       \"\\n\",\n       \"    this.rubberband = rubberband;\\n\",\n       \"    this.rubberband_canvas = rubberband[0];\\n\",\n       \"    this.rubberband_context = rubberband[0].getContext(\\\"2d\\\");\\n\",\n       \"    this.rubberband_context.strokeStyle = \\\"#000000\\\";\\n\",\n       \"\\n\",\n       \"    this._resize_canvas = function(width, height) {\\n\",\n       \"        // Keep the size of the canvas, canvas container, and rubber band\\n\",\n       \"        // canvas in synch.\\n\",\n       \"        canvas_div.css('width', width)\\n\",\n       \"        canvas_div.css('height', height)\\n\",\n       \"\\n\",\n       \"        canvas.attr('width', width * mpl.ratio);\\n\",\n       \"        canvas.attr('height', height * mpl.ratio);\\n\",\n       \"        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\\n\",\n       \"\\n\",\n       \"        rubberband.attr('width', width);\\n\",\n       \"        rubberband.attr('height', height);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Set the figure to an initial 600x600px, this will subsequently be updated\\n\",\n       \"    // upon first draw.\\n\",\n       \"    this._resize_canvas(600, 600);\\n\",\n       \"\\n\",\n       \"    // Disable right mouse context menu.\\n\",\n       \"    $(this.rubberband_canvas).bind(\\\"contextmenu\\\",function(e){\\n\",\n       \"        return false;\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function set_focus () {\\n\",\n       \"        canvas.focus();\\n\",\n       \"        canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    window.setTimeout(set_focus, 100);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>');\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items) {\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) {\\n\",\n       \"            // put a spacer in here.\\n\",\n       \"            continue;\\n\",\n       \"        }\\n\",\n       \"        var button = $('<button/>');\\n\",\n       \"        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\\n\",\n       \"                        'ui-button-icon-only');\\n\",\n       \"        button.attr('role', 'button');\\n\",\n       \"        button.attr('aria-disabled', 'false');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"\\n\",\n       \"        var icon_img = $('<span/>');\\n\",\n       \"        icon_img.addClass('ui-button-icon-primary ui-icon');\\n\",\n       \"        icon_img.addClass(image);\\n\",\n       \"        icon_img.addClass('ui-corner-all');\\n\",\n       \"\\n\",\n       \"        var tooltip_span = $('<span/>');\\n\",\n       \"        tooltip_span.addClass('ui-button-text');\\n\",\n       \"        tooltip_span.html(tooltip);\\n\",\n       \"\\n\",\n       \"        button.append(icon_img);\\n\",\n       \"        button.append(tooltip_span);\\n\",\n       \"\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fmt_picker_span = $('<span/>');\\n\",\n       \"\\n\",\n       \"    var fmt_picker = $('<select/>');\\n\",\n       \"    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\\n\",\n       \"    fmt_picker_span.append(fmt_picker);\\n\",\n       \"    nav_element.append(fmt_picker_span);\\n\",\n       \"    this.format_dropdown = fmt_picker[0];\\n\",\n       \"\\n\",\n       \"    for (var ind in mpl.extensions) {\\n\",\n       \"        var fmt = mpl.extensions[ind];\\n\",\n       \"        var option = $(\\n\",\n       \"            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\\n\",\n       \"        fmt_picker.append(option);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add hover states to the ui-buttons\\n\",\n       \"    $( \\\".ui-button\\\" ).hover(\\n\",\n       \"        function() { $(this).addClass(\\\"ui-state-hover\\\");},\\n\",\n       \"        function() { $(this).removeClass(\\\"ui-state-hover\\\");}\\n\",\n       \"    );\\n\",\n       \"\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\\n\",\n       \"    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\\n\",\n       \"    // which will in turn request a refresh of the image.\\n\",\n       \"    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_message = function(type, properties) {\\n\",\n       \"    properties['type'] = type;\\n\",\n       \"    properties['figure_id'] = this.id;\\n\",\n       \"    this.ws.send(JSON.stringify(properties));\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_draw_message = function() {\\n\",\n       \"    if (!this.waiting) {\\n\",\n       \"        this.waiting = true;\\n\",\n       \"        this.ws.send(JSON.stringify({type: \\\"draw\\\", figure_id: this.id}));\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    var format_dropdown = fig.format_dropdown;\\n\",\n       \"    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\\n\",\n       \"    fig.ondownload(fig, format);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_resize = function(fig, msg) {\\n\",\n       \"    var size = msg['size'];\\n\",\n       \"    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\\n\",\n       \"        fig._resize_canvas(size[0], size[1]);\\n\",\n       \"        fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\\n\",\n       \"    var x0 = msg['x0'] / mpl.ratio;\\n\",\n       \"    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\\n\",\n       \"    var x1 = msg['x1'] / mpl.ratio;\\n\",\n       \"    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\\n\",\n       \"    x0 = Math.floor(x0) + 0.5;\\n\",\n       \"    y0 = Math.floor(y0) + 0.5;\\n\",\n       \"    x1 = Math.floor(x1) + 0.5;\\n\",\n       \"    y1 = Math.floor(y1) + 0.5;\\n\",\n       \"    var min_x = Math.min(x0, x1);\\n\",\n       \"    var min_y = Math.min(y0, y1);\\n\",\n       \"    var width = Math.abs(x1 - x0);\\n\",\n       \"    var height = Math.abs(y1 - y0);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.clearRect(\\n\",\n       \"        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\\n\",\n       \"    // Updates the figure title.\\n\",\n       \"    fig.header.textContent = msg['label'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_cursor = function(fig, msg) {\\n\",\n       \"    var cursor = msg['cursor'];\\n\",\n       \"    switch(cursor)\\n\",\n       \"    {\\n\",\n       \"    case 0:\\n\",\n       \"        cursor = 'pointer';\\n\",\n       \"        break;\\n\",\n       \"    case 1:\\n\",\n       \"        cursor = 'default';\\n\",\n       \"        break;\\n\",\n       \"    case 2:\\n\",\n       \"        cursor = 'crosshair';\\n\",\n       \"        break;\\n\",\n       \"    case 3:\\n\",\n       \"        cursor = 'move';\\n\",\n       \"        break;\\n\",\n       \"    }\\n\",\n       \"    fig.rubberband_canvas.style.cursor = cursor;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_message = function(fig, msg) {\\n\",\n       \"    fig.message.textContent = msg['message'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_draw = function(fig, msg) {\\n\",\n       \"    // Request the server to send over a new figure.\\n\",\n       \"    fig.send_draw_message();\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\\n\",\n       \"    fig.image_mode = msg['mode'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Called whenever the canvas gets updated.\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// A function to construct a web socket function for onmessage handling.\\n\",\n       \"// Called in the figure constructor.\\n\",\n       \"mpl.figure.prototype._make_on_message_function = function(fig) {\\n\",\n       \"    return function socket_on_message(evt) {\\n\",\n       \"        if (evt.data instanceof Blob) {\\n\",\n       \"            /* FIXME: We get \\\"Resource interpreted as Image but\\n\",\n       \"             * transferred with MIME type text/plain:\\\" errors on\\n\",\n       \"             * Chrome.  But how to set the MIME type?  It doesn't seem\\n\",\n       \"             * to be part of the websocket stream */\\n\",\n       \"            evt.data.type = \\\"image/png\\\";\\n\",\n       \"\\n\",\n       \"            /* Free the memory for the previous frames */\\n\",\n       \"            if (fig.imageObj.src) {\\n\",\n       \"                (window.URL || window.webkitURL).revokeObjectURL(\\n\",\n       \"                    fig.imageObj.src);\\n\",\n       \"            }\\n\",\n       \"\\n\",\n       \"            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\\n\",\n       \"                evt.data);\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \\\"data:image/png;base64\\\") {\\n\",\n       \"            fig.imageObj.src = evt.data;\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        var msg = JSON.parse(evt.data);\\n\",\n       \"        var msg_type = msg['type'];\\n\",\n       \"\\n\",\n       \"        // Call the  \\\"handle_{type}\\\" callback, which takes\\n\",\n       \"        // the figure and JSON message as its only arguments.\\n\",\n       \"        try {\\n\",\n       \"            var callback = fig[\\\"handle_\\\" + msg_type];\\n\",\n       \"        } catch (e) {\\n\",\n       \"            console.log(\\\"No handler for the '\\\" + msg_type + \\\"' message type: \\\", msg);\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        if (callback) {\\n\",\n       \"            try {\\n\",\n       \"                // console.log(\\\"Handling '\\\" + msg_type + \\\"' message: \\\", msg);\\n\",\n       \"                callback(fig, msg);\\n\",\n       \"            } catch (e) {\\n\",\n       \"                console.log(\\\"Exception inside the 'handler_\\\" + msg_type + \\\"' callback:\\\", e, e.stack, msg);\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\\n\",\n       \"mpl.findpos = function(e) {\\n\",\n       \"    //this section is from http://www.quirksmode.org/js/events_properties.html\\n\",\n       \"    var targ;\\n\",\n       \"    if (!e)\\n\",\n       \"        e = window.event;\\n\",\n       \"    if (e.target)\\n\",\n       \"        targ = e.target;\\n\",\n       \"    else if (e.srcElement)\\n\",\n       \"        targ = e.srcElement;\\n\",\n       \"    if (targ.nodeType == 3) // defeat Safari bug\\n\",\n       \"        targ = targ.parentNode;\\n\",\n       \"\\n\",\n       \"    // jQuery normalizes the pageX and pageY\\n\",\n       \"    // pageX,Y are the mouse positions relative to the document\\n\",\n       \"    // offset() returns the position of the element relative to the document\\n\",\n       \"    var x = e.pageX - $(targ).offset().left;\\n\",\n       \"    var y = e.pageY - $(targ).offset().top;\\n\",\n       \"\\n\",\n       \"    return {\\\"x\\\": x, \\\"y\\\": y};\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"/*\\n\",\n       \" * return a copy of an object with only non-object keys\\n\",\n       \" * we need this to avoid circular references\\n\",\n       \" * http://stackoverflow.com/a/24161582/3208463\\n\",\n       \" */\\n\",\n       \"function simpleKeys (original) {\\n\",\n       \"  return Object.keys(original).reduce(function (obj, key) {\\n\",\n       \"    if (typeof original[key] !== 'object')\\n\",\n       \"        obj[key] = original[key]\\n\",\n       \"    return obj;\\n\",\n       \"  }, {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.mouse_event = function(event, name) {\\n\",\n       \"    var canvas_pos = mpl.findpos(event)\\n\",\n       \"\\n\",\n       \"    if (name === 'button_press')\\n\",\n       \"    {\\n\",\n       \"        this.canvas.focus();\\n\",\n       \"        this.canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var x = canvas_pos.x * mpl.ratio;\\n\",\n       \"    var y = canvas_pos.y * mpl.ratio;\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {x: x, y: y, button: event.button,\\n\",\n       \"                             step: event.step,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"\\n\",\n       \"    /* This prevents the web browser from automatically changing to\\n\",\n       \"     * the text insertion cursor when the button is pressed.  We want\\n\",\n       \"     * to control all of the cursor setting manually through the\\n\",\n       \"     * 'cursor' event from matplotlib */\\n\",\n       \"    event.preventDefault();\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    // Handle any extra behaviour associated with a key event\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.key_event = function(event, name) {\\n\",\n       \"\\n\",\n       \"    // Prevent repeat events\\n\",\n       \"    if (name == 'key_press')\\n\",\n       \"    {\\n\",\n       \"        if (event.which === this._key)\\n\",\n       \"            return;\\n\",\n       \"        else\\n\",\n       \"            this._key = event.which;\\n\",\n       \"    }\\n\",\n       \"    if (name == 'key_release')\\n\",\n       \"        this._key = null;\\n\",\n       \"\\n\",\n       \"    var value = '';\\n\",\n       \"    if (event.ctrlKey && event.which != 17)\\n\",\n       \"        value += \\\"ctrl+\\\";\\n\",\n       \"    if (event.altKey && event.which != 18)\\n\",\n       \"        value += \\\"alt+\\\";\\n\",\n       \"    if (event.shiftKey && event.which != 16)\\n\",\n       \"        value += \\\"shift+\\\";\\n\",\n       \"\\n\",\n       \"    value += 'k';\\n\",\n       \"    value += event.which.toString();\\n\",\n       \"\\n\",\n       \"    this._key_event_extra(event, name);\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {key: value,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onclick = function(name) {\\n\",\n       \"    if (name == 'download') {\\n\",\n       \"        this.handle_save(this, null);\\n\",\n       \"    } else {\\n\",\n       \"        this.send_message(\\\"toolbar_button\\\", {name: name});\\n\",\n       \"    }\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\\n\",\n       \"    this.message.textContent = tooltip;\\n\",\n       \"};\\n\",\n       \"mpl.toolbar_items = [[\\\"Home\\\", \\\"Reset original view\\\", \\\"fa fa-home icon-home\\\", \\\"home\\\"], [\\\"Back\\\", \\\"Back to previous view\\\", \\\"fa fa-arrow-left icon-arrow-left\\\", \\\"back\\\"], [\\\"Forward\\\", \\\"Forward to next view\\\", \\\"fa fa-arrow-right icon-arrow-right\\\", \\\"forward\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Pan\\\", \\\"Pan axes with left mouse, zoom with right\\\", \\\"fa fa-arrows icon-move\\\", \\\"pan\\\"], [\\\"Zoom\\\", \\\"Zoom to rectangle\\\", \\\"fa fa-square-o icon-check-empty\\\", \\\"zoom\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Download\\\", \\\"Download plot\\\", \\\"fa fa-floppy-o icon-save\\\", \\\"download\\\"]];\\n\",\n       \"\\n\",\n       \"mpl.extensions = [\\\"eps\\\", \\\"jpeg\\\", \\\"pdf\\\", \\\"png\\\", \\\"ps\\\", \\\"raw\\\", \\\"svg\\\", \\\"tif\\\"];\\n\",\n       \"\\n\",\n       \"mpl.default_extension = \\\"png\\\";var comm_websocket_adapter = function(comm) {\\n\",\n       \"    // Create a \\\"websocket\\\"-like object which calls the given IPython comm\\n\",\n       \"    // object with the appropriate methods. Currently this is a non binary\\n\",\n       \"    // socket, so there is still some room for performance tuning.\\n\",\n       \"    var ws = {};\\n\",\n       \"\\n\",\n       \"    ws.close = function() {\\n\",\n       \"        comm.close()\\n\",\n       \"    };\\n\",\n       \"    ws.send = function(m) {\\n\",\n       \"        //console.log('sending', m);\\n\",\n       \"        comm.send(m);\\n\",\n       \"    };\\n\",\n       \"    // Register the callback with on_msg.\\n\",\n       \"    comm.on_msg(function(msg) {\\n\",\n       \"        //console.log('receiving', msg['content']['data'], msg);\\n\",\n       \"        // Pass the mpl event to the overridden (by mpl) onmessage function.\\n\",\n       \"        ws.onmessage(msg['content']['data'])\\n\",\n       \"    });\\n\",\n       \"    return ws;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.mpl_figure_comm = function(comm, msg) {\\n\",\n       \"    // This is the function which gets called when the mpl process\\n\",\n       \"    // starts-up an IPython Comm through the \\\"matplotlib\\\" channel.\\n\",\n       \"\\n\",\n       \"    var id = msg.content.data.id;\\n\",\n       \"    // Get hold of the div created by the display call when the Comm\\n\",\n       \"    // socket was opened in Python.\\n\",\n       \"    var element = $(\\\"#\\\" + id);\\n\",\n       \"    var ws_proxy = comm_websocket_adapter(comm)\\n\",\n       \"\\n\",\n       \"    function ondownload(figure, format) {\\n\",\n       \"        window.open(figure.imageObj.src);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fig = new mpl.figure(id, ws_proxy,\\n\",\n       \"                           ondownload,\\n\",\n       \"                           element.get(0));\\n\",\n       \"\\n\",\n       \"    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\\n\",\n       \"    // web socket which is closed, not our websocket->open comm proxy.\\n\",\n       \"    ws_proxy.onopen();\\n\",\n       \"\\n\",\n       \"    fig.parent_element = element.get(0);\\n\",\n       \"    fig.cell_info = mpl.find_output_cell(\\\"<div id='\\\" + id + \\\"'></div>\\\");\\n\",\n       \"    if (!fig.cell_info) {\\n\",\n       \"        console.error(\\\"Failed to find cell for figure\\\", id, fig);\\n\",\n       \"        return;\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var output_index = fig.cell_info[2]\\n\",\n       \"    var cell = fig.cell_info[0];\\n\",\n       \"\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_close = function(fig, msg) {\\n\",\n       \"    var width = fig.canvas.width/mpl.ratio\\n\",\n       \"    fig.root.unbind('remove')\\n\",\n       \"\\n\",\n       \"    // Update the output cell to use the data from the current canvas.\\n\",\n       \"    fig.push_to_output();\\n\",\n       \"    var dataURL = fig.canvas.toDataURL();\\n\",\n       \"    // Re-enable the keyboard manager in IPython - without this line, in FF,\\n\",\n       \"    // the notebook keyboard shortcuts fail.\\n\",\n       \"    IPython.keyboard_manager.enable()\\n\",\n       \"    $(fig.parent_element).html('<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">');\\n\",\n       \"    fig.close_ws(fig, msg);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.close_ws = function(fig, msg){\\n\",\n       \"    fig.send_message('closing', msg);\\n\",\n       \"    // fig.ws.close()\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.push_to_output = function(remove_interactive) {\\n\",\n       \"    // Turn the data on the canvas into data in the output cell.\\n\",\n       \"    var width = this.canvas.width/mpl.ratio\\n\",\n       \"    var dataURL = this.canvas.toDataURL();\\n\",\n       \"    this.cell_info[1]['text/html'] = '<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">';\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Tell IPython that the notebook contents must change.\\n\",\n       \"    IPython.notebook.set_dirty(true);\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"    var fig = this;\\n\",\n       \"    // Wait a second, then push the new image to the DOM so\\n\",\n       \"    // that it is saved nicely (might be nice to debounce this).\\n\",\n       \"    setTimeout(function () { fig.push_to_output() }, 1000);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>');\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items){\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) { continue; };\\n\",\n       \"\\n\",\n       \"        var button = $('<button class=\\\"btn btn-default\\\" href=\\\"#\\\" title=\\\"' + name + '\\\"><i class=\\\"fa ' + image + ' fa-lg\\\"></i></button>');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add the status bar.\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\" style=\\\"text-align:right; float: right;\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"\\n\",\n       \"    // Add the close button to the window.\\n\",\n       \"    var buttongrp = $('<div class=\\\"btn-group inline pull-right\\\"></div>');\\n\",\n       \"    var button = $('<button class=\\\"btn btn-mini btn-primary\\\" href=\\\"#\\\" title=\\\"Stop Interaction\\\"><i class=\\\"fa fa-power-off icon-remove icon-large\\\"></i></button>');\\n\",\n       \"    button.click(function (evt) { fig.handle_close(fig, {}); } );\\n\",\n       \"    button.mouseover('Stop Interaction', toolbar_mouse_event);\\n\",\n       \"    buttongrp.append(button);\\n\",\n       \"    var titlebar = this.root.find($('.ui-dialog-titlebar'));\\n\",\n       \"    titlebar.prepend(buttongrp);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(el){\\n\",\n       \"    var fig = this\\n\",\n       \"    el.on(\\\"remove\\\", function(){\\n\",\n       \"\\tfig.close_ws(fig, {});\\n\",\n       \"    });\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(el){\\n\",\n       \"    // this is important to make the div 'focusable\\n\",\n       \"    el.attr('tabindex', 0)\\n\",\n       \"    // reach out to IPython and tell the keyboard manager to turn it's self\\n\",\n       \"    // off when our div gets focus\\n\",\n       \"\\n\",\n       \"    // location in version 3\\n\",\n       \"    if (IPython.notebook.keyboard_manager) {\\n\",\n       \"        IPython.notebook.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"    else {\\n\",\n       \"        // location in version 2\\n\",\n       \"        IPython.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    var manager = IPython.notebook.keyboard_manager;\\n\",\n       \"    if (!manager)\\n\",\n       \"        manager = IPython.keyboard_manager;\\n\",\n       \"\\n\",\n       \"    // Check for shift+enter\\n\",\n       \"    if (event.shiftKey && event.which == 13) {\\n\",\n       \"        this.canvas_div.blur();\\n\",\n       \"        event.shiftKey = false;\\n\",\n       \"        // Send a \\\"J\\\" for go to next cell\\n\",\n       \"        event.which = 74;\\n\",\n       \"        event.keyCode = 74;\\n\",\n       \"        manager.command_mode();\\n\",\n       \"        manager.handle_keydown(event);\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    fig.ondownload(fig, null);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.find_output_cell = function(html_output) {\\n\",\n       \"    // Return the cell and output element which can be found *uniquely* in the notebook.\\n\",\n       \"    // Note - this is a bit hacky, but it is done because the \\\"notebook_saving.Notebook\\\"\\n\",\n       \"    // IPython event is triggered only after the cells have been serialised, which for\\n\",\n       \"    // our purposes (turning an active figure into a static one), is too late.\\n\",\n       \"    var cells = IPython.notebook.get_cells();\\n\",\n       \"    var ncells = cells.length;\\n\",\n       \"    for (var i=0; i<ncells; i++) {\\n\",\n       \"        var cell = cells[i];\\n\",\n       \"        if (cell.cell_type === 'code'){\\n\",\n       \"            for (var j=0; j<cell.output_area.outputs.length; j++) {\\n\",\n       \"                var data = cell.output_area.outputs[j];\\n\",\n       \"                if (data.data) {\\n\",\n       \"                    // IPython >= 3 moved mimebundle to data attribute of output\\n\",\n       \"                    data = data.data;\\n\",\n       \"                }\\n\",\n       \"                if (data['text/html'] == html_output) {\\n\",\n       \"                    return [cell, data, j];\\n\",\n       \"                }\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// Register the function which deals with the matplotlib target/channel.\\n\",\n       \"// The kernel may be null if the page has been refreshed.\\n\",\n       \"if (IPython.notebook.kernel != null) {\\n\",\n       \"    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\\n\",\n       \"}\\n\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.Javascript object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"text/html\": [\n       \"<img src=\\\"data:image/png;base64,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\\\" width=\\\"800\\\">\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.HTML object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"Cluster    0 (size   721): rejected p = 2.07E-22\\n\",\n      \"Cluster    1 (size   534): rejected p = 1.37E-36\\n\",\n      \"Cluster    2 (size   796): rejected p = 4.13E-05\\n\",\n      \"Cluster    3 (size   810): rejected p = 5.45E-20\\n\",\n      \"Cluster    4 (size   583): rejected p = 2.49E-134\\n\",\n      \"Cluster    5 (size   734): rejected p = 1.24E-03\\n\",\n      \"Cluster    6 (size   761): rejected p = 1.19E-32\\n\",\n      \"Cluster    7 (size   626): rejected p = 2.95E-15\\n\",\n      \"Cluster    8 (size   673): rejected p = 7.67E-60\\n\",\n      \"Cluster    9 (size   602): rejected p = 1.04E-140\\n\",\n      \"-----------------------------------\\n\",\n      \"Number of clusters with statistically differing mean force: 10 (100.00 %)\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Setup for array of histograms.\\n\",\n    \"ncols = 3\\n\",\n    \"nrows = int(np.ceil(num_clusters / float(ncols)))\\n\",\n    \"fig, axs = plt.subplots(nrows=nrows, ncols=ncols, sharex=\\\"col\\\", sharey=\\\"row\\\")\\n\",\n    \"fig.set_size_inches(8, 2.5*nrows)\\n\",\n    \"\\n\",\n    \"count_rejected = 0\\n\",\n    \"for i in range(num_clusters):\\n\",\n    \"    a = extract_component\\n\",\n    \"    indices = np.array(cluster_indices[i][1])\\n\",\n    \"    f_all = forces.T[a]\\n\",\n    \"    f_excl = forces.T[a][~np.isin(range(len(forces.T[a])), indices)]\\n\",\n    \"    f_clust = forces.T[a][indices]\\n\",\n    \"    if len(forces.T[a]) != len(f_excl) + len(f_clust):\\n\",\n    \"        print(\\\"WARNING: Something went wrong.\\\")\\n\",\n    \"    if len(f_clust) > 1:\\n\",\n    \"        ttest = stats.ttest_ind(f_excl, f_clust, equal_var=False)\\n\",\n    \"    ax = fig.axes[i]\\n\",\n    \"    ax.hist(f_excl,  bins='auto', density=1, color=\\\"grey\\\", alpha=0.5)\\n\",\n    \"    if len(f_clust) <= 1 or ttest.pvalue > pvalue_max:\\n\",\n    \"        color = \\\"red\\\"\\n\",\n    \"        print(\\\"Cluster {0:4d} (size {1:5d}): ACCEPTED p = {2:.2E}\\\".format(i, len(f_clust), ttest.pvalue))\\n\",\n    \"    else:\\n\",\n    \"        color = \\\"green\\\"\\n\",\n    \"        print(\\\"Cluster {0:4d} (size {1:5d}): rejected p = {2:.2E}\\\".format(i, len(f_clust), ttest.pvalue))\\n\",\n    \"        count_rejected += 1\\n\",\n    \"    ax.hist(f_clust, bins='auto', density=1, color=color, alpha=0.5, label=\\\"{0:d}\\\".format(i))\\n\",\n    \"    ax.legend(loc=\\\"upper right\\\")\\n\",\n    \"print(\\\"-----------------------------------\\\")\\n\",\n    \"print(\\\"Number of clusters with statistically differing mean force: {0:d} ({1:.2f} %)\\\".format(count_rejected, count_rejected * 100.0 / num_clusters))\\n\",\n    \"fig.savefig(f\\\"cluster_histograms_{extract_element}.pdf\\\")\\n\",\n    \"fig.savefig(f\\\"cluster_histograms_{extract_element}.png\\\", dpi=300)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"The above calculation will give us a good impression of the atomic environment descriptor quality. Still, one could argue that the result could look different if other cluster search parameters were chosen. Luckily, with k-means we can easily repeat the calculation for many desired number of clusters.\\n\",\n    \"\\n\",\n    \"**WARNING:** This may take a while...\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 16,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"Cluster size     3: Number of clusters with statistically differing mean force: 3 (100.00 %)\\n\",\n      \"Cluster size     5: Number of clusters with statistically differing mean force: 5 (100.00 %)\\n\",\n      \"Cluster size    10: Number of clusters with statistically differing mean force: 10 (100.00 %)\\n\",\n      \"Cluster size    20: Number of clusters with statistically differing mean force: 17 (85.00 %)\\n\",\n      \"Cluster size    50: Number of clusters with statistically differing mean force: 36 (72.00 %)\\n\",\n      \"Cluster size   100: Number of clusters with statistically differing mean force: 65 (65.00 %)\\n\",\n      \"Cluster size   150: Number of clusters with statistically differing mean force: 86 (57.33 %)\\n\",\n      \"Cluster size   200: Number of clusters with statistically differing mean force: 96 (48.00 %)\\n\",\n      \"CPU times: user 17.5 s, sys: 3.84 ms, total: 17.5 s\\n\",\n      \"Wall time: 17.5 s\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"%%time \\n\",\n    \"cluster_numbers = [3, 5,10, 20, 50, 100, 150, 200]\\n\",\n    \"cluster_results = []\\n\",\n    \"for n_clusters in cluster_numbers:\\n\",\n    \"    clustering = KMeans(n_clusters=n_clusters)\\n\",\n    \"    clustering.fit(sf)\\n\",\n    \"    cluster_indices_dict = {}\\n\",\n    \"    for i,l in enumerate(clustering.labels_):\\n\",\n    \"        try:\\n\",\n    \"            cluster_indices_dict[l].extend([i])\\n\",\n    \"        except KeyError:\\n\",\n    \"            cluster_indices_dict[l] = [i]\\n\",\n    \"\\n\",\n    \"    cluster_indices = []\\n\",\n    \"    for i in sorted(cluster_indices_dict.keys()):\\n\",\n    \"        cluster_indices.append([i, cluster_indices_dict[i]])\\n\",\n    \"\\n\",\n    \"    num_clusters = len(cluster_indices)\\n\",\n    \"    # HDBScan may not always assign a cluster label (label = -1 in this case).\\n\",\n    \"    # Remove this list of indices from the beginning of the array.\\n\",\n    \"    if cluster_indices[0][0] == -1:\\n\",\n    \"        num_clusters -= 1\\n\",\n    \"        cluster_indices = cluster_indices[1:]\\n\",\n    \"\\n\",\n    \"    if num_clusters == 0:\\n\",\n    \"        print(\\\"WARNING: No clusters found!\\\")\\n\",\n    \"    elif cluster_indices[-1][0] + 1 != num_clusters:\\n\",\n    \"        print(\\\"WARNING: Some cluster indices were not found!\\\")\\n\",\n    \"\\n\",\n    \"    count_rejected = 0\\n\",\n    \"    for i in range(num_clusters):\\n\",\n    \"        a = extract_component\\n\",\n    \"        indices = np.array(cluster_indices[i][1])\\n\",\n    \"        f_all = forces.T[a]\\n\",\n    \"        f_excl = forces.T[a][~np.isin(range(len(forces.T[a])), indices)]\\n\",\n    \"        f_clust = forces.T[a][indices]\\n\",\n    \"        if len(forces.T[a]) != len(f_excl) + len(f_clust):\\n\",\n    \"            print(\\\"WARNING: Something went wrong.\\\")\\n\",\n    \"        if len(f_clust) > 1:\\n\",\n    \"            ttest = stats.ttest_ind(f_excl, f_clust, equal_var=False)\\n\",\n    \"        if len(f_clust) <= 1 or ttest.pvalue > pvalue_max:\\n\",\n    \"            pass\\n\",\n    \"        else:\\n\",\n    \"            count_rejected += 1\\n\",\n    \"    cluster_results.append(count_rejected * 100.0 / num_clusters)\\n\",\n    \"    print(\\\"Cluster size {0:5d}: Number of clusters with statistically differing mean force: {1:d} ({2:.2f} %)\\\".format(n_clusters, count_rejected, count_rejected * 100.0 / num_clusters))\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"Finally, we can plot the results to check if we find a consistent picture across many possible cluster numbers.\\n\",\n    \"\\n\",\n    \"**Note:** In the limit of cluster number $ = N_\\\\text{atoms}$ the ratio should drop to zero because with a single sample point the null hypothesis should not be rejected.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 17,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"f = open(f\\\"cluster_data_{extract_element}.pkl\\\", \\\"wb\\\")\\n\",\n    \"pickle.dump(extract_element, f)\\n\",\n    \"pickle.dump(cluster_numbers, f)\\n\",\n    \"pickle.dump(cluster_results, f)\\n\",\n    \"f.close()\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 18,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"application/javascript\": [\n       \"/* Put everything inside the global mpl namespace */\\n\",\n       \"window.mpl = {};\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.get_websocket_type = function() {\\n\",\n       \"    if (typeof(WebSocket) !== 'undefined') {\\n\",\n       \"        return WebSocket;\\n\",\n       \"    } else if (typeof(MozWebSocket) !== 'undefined') {\\n\",\n       \"        return MozWebSocket;\\n\",\n       \"    } else {\\n\",\n       \"        alert('Your browser does not have WebSocket support. ' +\\n\",\n       \"              'Please try Chrome, Safari or Firefox ≥ 6. ' +\\n\",\n       \"              'Firefox 4 and 5 are also supported but you ' +\\n\",\n       \"              'have to enable WebSockets in about:config.');\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\\n\",\n       \"    this.id = figure_id;\\n\",\n       \"\\n\",\n       \"    this.ws = websocket;\\n\",\n       \"\\n\",\n       \"    this.supports_binary = (this.ws.binaryType != undefined);\\n\",\n       \"\\n\",\n       \"    if (!this.supports_binary) {\\n\",\n       \"        var warnings = document.getElementById(\\\"mpl-warnings\\\");\\n\",\n       \"        if (warnings) {\\n\",\n       \"            warnings.style.display = 'block';\\n\",\n       \"            warnings.textContent = (\\n\",\n       \"                \\\"This browser does not support binary websocket messages. \\\" +\\n\",\n       \"                    \\\"Performance may be slow.\\\");\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.imageObj = new Image();\\n\",\n       \"\\n\",\n       \"    this.context = undefined;\\n\",\n       \"    this.message = undefined;\\n\",\n       \"    this.canvas = undefined;\\n\",\n       \"    this.rubberband_canvas = undefined;\\n\",\n       \"    this.rubberband_context = undefined;\\n\",\n       \"    this.format_dropdown = undefined;\\n\",\n       \"\\n\",\n       \"    this.image_mode = 'full';\\n\",\n       \"\\n\",\n       \"    this.root = $('<div/>');\\n\",\n       \"    this._root_extra_style(this.root)\\n\",\n       \"    this.root.attr('style', 'display: inline-block');\\n\",\n       \"\\n\",\n       \"    $(parent_element).append(this.root);\\n\",\n       \"\\n\",\n       \"    this._init_header(this);\\n\",\n       \"    this._init_canvas(this);\\n\",\n       \"    this._init_toolbar(this);\\n\",\n       \"\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    this.waiting = false;\\n\",\n       \"\\n\",\n       \"    this.ws.onopen =  function () {\\n\",\n       \"            fig.send_message(\\\"supports_binary\\\", {value: fig.supports_binary});\\n\",\n       \"            fig.send_message(\\\"send_image_mode\\\", {});\\n\",\n       \"            if (mpl.ratio != 1) {\\n\",\n       \"                fig.send_message(\\\"set_dpi_ratio\\\", {'dpi_ratio': mpl.ratio});\\n\",\n       \"            }\\n\",\n       \"            fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"    this.imageObj.onload = function() {\\n\",\n       \"            if (fig.image_mode == 'full') {\\n\",\n       \"                // Full images could contain transparency (where diff images\\n\",\n       \"                // almost always do), so we need to clear the canvas so that\\n\",\n       \"                // there is no ghosting.\\n\",\n       \"                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\\n\",\n       \"            }\\n\",\n       \"            fig.context.drawImage(fig.imageObj, 0, 0);\\n\",\n       \"        };\\n\",\n       \"\\n\",\n       \"    this.imageObj.onunload = function() {\\n\",\n       \"        fig.ws.close();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.ws.onmessage = this._make_on_message_function(this);\\n\",\n       \"\\n\",\n       \"    this.ondownload = ondownload;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_header = function() {\\n\",\n       \"    var titlebar = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\\n\",\n       \"        'ui-helper-clearfix\\\"/>');\\n\",\n       \"    var titletext = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-title\\\" style=\\\"width: 100%; ' +\\n\",\n       \"        'text-align: center; padding: 3px;\\\"/>');\\n\",\n       \"    titlebar.append(titletext)\\n\",\n       \"    this.root.append(titlebar);\\n\",\n       \"    this.header = titletext[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_canvas = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var canvas_div = $('<div/>');\\n\",\n       \"\\n\",\n       \"    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\\n\",\n       \"\\n\",\n       \"    function canvas_keyboard_event(event) {\\n\",\n       \"        return fig.key_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    canvas_div.keydown('key_press', canvas_keyboard_event);\\n\",\n       \"    canvas_div.keyup('key_release', canvas_keyboard_event);\\n\",\n       \"    this.canvas_div = canvas_div\\n\",\n       \"    this._canvas_extra_style(canvas_div)\\n\",\n       \"    this.root.append(canvas_div);\\n\",\n       \"\\n\",\n       \"    var canvas = $('<canvas/>');\\n\",\n       \"    canvas.addClass('mpl-canvas');\\n\",\n       \"    canvas.attr('style', \\\"left: 0; top: 0; z-index: 0; outline: 0\\\")\\n\",\n       \"\\n\",\n       \"    this.canvas = canvas[0];\\n\",\n       \"    this.context = canvas[0].getContext(\\\"2d\\\");\\n\",\n       \"\\n\",\n       \"    var backingStore = this.context.backingStorePixelRatio ||\\n\",\n       \"\\tthis.context.webkitBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.mozBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.msBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.oBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.backingStorePixelRatio || 1;\\n\",\n       \"\\n\",\n       \"    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\\n\",\n       \"\\n\",\n       \"    var rubberband = $('<canvas/>');\\n\",\n       \"    rubberband.attr('style', \\\"position: absolute; left: 0; top: 0; z-index: 1;\\\")\\n\",\n       \"\\n\",\n       \"    var pass_mouse_events = true;\\n\",\n       \"\\n\",\n       \"    canvas_div.resizable({\\n\",\n       \"        start: function(event, ui) {\\n\",\n       \"            pass_mouse_events = false;\\n\",\n       \"        },\\n\",\n       \"        resize: function(event, ui) {\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"        stop: function(event, ui) {\\n\",\n       \"            pass_mouse_events = true;\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function mouse_event_fn(event) {\\n\",\n       \"        if (pass_mouse_events)\\n\",\n       \"            return fig.mouse_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    rubberband.mousedown('button_press', mouse_event_fn);\\n\",\n       \"    rubberband.mouseup('button_release', mouse_event_fn);\\n\",\n       \"    // Throttle sequential mouse events to 1 every 20ms.\\n\",\n       \"    rubberband.mousemove('motion_notify', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    rubberband.mouseenter('figure_enter', mouse_event_fn);\\n\",\n       \"    rubberband.mouseleave('figure_leave', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    canvas_div.on(\\\"wheel\\\", function (event) {\\n\",\n       \"        event = event.originalEvent;\\n\",\n       \"        event['data'] = 'scroll'\\n\",\n       \"        if (event.deltaY < 0) {\\n\",\n       \"            event.step = 1;\\n\",\n       \"        } else {\\n\",\n       \"            event.step = -1;\\n\",\n       \"        }\\n\",\n       \"        mouse_event_fn(event);\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    canvas_div.append(canvas);\\n\",\n       \"    canvas_div.append(rubberband);\\n\",\n       \"\\n\",\n       \"    this.rubberband = rubberband;\\n\",\n       \"    this.rubberband_canvas = rubberband[0];\\n\",\n       \"    this.rubberband_context = rubberband[0].getContext(\\\"2d\\\");\\n\",\n       \"    this.rubberband_context.strokeStyle = \\\"#000000\\\";\\n\",\n       \"\\n\",\n       \"    this._resize_canvas = function(width, height) {\\n\",\n       \"        // Keep the size of the canvas, canvas container, and rubber band\\n\",\n       \"        // canvas in synch.\\n\",\n       \"        canvas_div.css('width', width)\\n\",\n       \"        canvas_div.css('height', height)\\n\",\n       \"\\n\",\n       \"        canvas.attr('width', width * mpl.ratio);\\n\",\n       \"        canvas.attr('height', height * mpl.ratio);\\n\",\n       \"        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\\n\",\n       \"\\n\",\n       \"        rubberband.attr('width', width);\\n\",\n       \"        rubberband.attr('height', height);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Set the figure to an initial 600x600px, this will subsequently be updated\\n\",\n       \"    // upon first draw.\\n\",\n       \"    this._resize_canvas(600, 600);\\n\",\n       \"\\n\",\n       \"    // Disable right mouse context menu.\\n\",\n       \"    $(this.rubberband_canvas).bind(\\\"contextmenu\\\",function(e){\\n\",\n       \"        return false;\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function set_focus () {\\n\",\n       \"        canvas.focus();\\n\",\n       \"        canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    window.setTimeout(set_focus, 100);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>');\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items) {\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) {\\n\",\n       \"            // put a spacer in here.\\n\",\n       \"            continue;\\n\",\n       \"        }\\n\",\n       \"        var button = $('<button/>');\\n\",\n       \"        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\\n\",\n       \"                        'ui-button-icon-only');\\n\",\n       \"        button.attr('role', 'button');\\n\",\n       \"        button.attr('aria-disabled', 'false');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"\\n\",\n       \"        var icon_img = $('<span/>');\\n\",\n       \"        icon_img.addClass('ui-button-icon-primary ui-icon');\\n\",\n       \"        icon_img.addClass(image);\\n\",\n       \"        icon_img.addClass('ui-corner-all');\\n\",\n       \"\\n\",\n       \"        var tooltip_span = $('<span/>');\\n\",\n       \"        tooltip_span.addClass('ui-button-text');\\n\",\n       \"        tooltip_span.html(tooltip);\\n\",\n       \"\\n\",\n       \"        button.append(icon_img);\\n\",\n       \"        button.append(tooltip_span);\\n\",\n       \"\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fmt_picker_span = $('<span/>');\\n\",\n       \"\\n\",\n       \"    var fmt_picker = $('<select/>');\\n\",\n       \"    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\\n\",\n       \"    fmt_picker_span.append(fmt_picker);\\n\",\n       \"    nav_element.append(fmt_picker_span);\\n\",\n       \"    this.format_dropdown = fmt_picker[0];\\n\",\n       \"\\n\",\n       \"    for (var ind in mpl.extensions) {\\n\",\n       \"        var fmt = mpl.extensions[ind];\\n\",\n       \"        var option = $(\\n\",\n       \"            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\\n\",\n       \"        fmt_picker.append(option);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add hover states to the ui-buttons\\n\",\n       \"    $( \\\".ui-button\\\" ).hover(\\n\",\n       \"        function() { $(this).addClass(\\\"ui-state-hover\\\");},\\n\",\n       \"        function() { $(this).removeClass(\\\"ui-state-hover\\\");}\\n\",\n       \"    );\\n\",\n       \"\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\\n\",\n       \"    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\\n\",\n       \"    // which will in turn request a refresh of the image.\\n\",\n       \"    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_message = function(type, properties) {\\n\",\n       \"    properties['type'] = type;\\n\",\n       \"    properties['figure_id'] = this.id;\\n\",\n       \"    this.ws.send(JSON.stringify(properties));\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_draw_message = function() {\\n\",\n       \"    if (!this.waiting) {\\n\",\n       \"        this.waiting = true;\\n\",\n       \"        this.ws.send(JSON.stringify({type: \\\"draw\\\", figure_id: this.id}));\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    var format_dropdown = fig.format_dropdown;\\n\",\n       \"    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\\n\",\n       \"    fig.ondownload(fig, format);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_resize = function(fig, msg) {\\n\",\n       \"    var size = msg['size'];\\n\",\n       \"    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\\n\",\n       \"        fig._resize_canvas(size[0], size[1]);\\n\",\n       \"        fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\\n\",\n       \"    var x0 = msg['x0'] / mpl.ratio;\\n\",\n       \"    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\\n\",\n       \"    var x1 = msg['x1'] / mpl.ratio;\\n\",\n       \"    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\\n\",\n       \"    x0 = Math.floor(x0) + 0.5;\\n\",\n       \"    y0 = Math.floor(y0) + 0.5;\\n\",\n       \"    x1 = Math.floor(x1) + 0.5;\\n\",\n       \"    y1 = Math.floor(y1) + 0.5;\\n\",\n       \"    var min_x = Math.min(x0, x1);\\n\",\n       \"    var min_y = Math.min(y0, y1);\\n\",\n       \"    var width = Math.abs(x1 - x0);\\n\",\n       \"    var height = Math.abs(y1 - y0);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.clearRect(\\n\",\n       \"        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\\n\",\n       \"    // Updates the figure title.\\n\",\n       \"    fig.header.textContent = msg['label'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_cursor = function(fig, msg) {\\n\",\n       \"    var cursor = msg['cursor'];\\n\",\n       \"    switch(cursor)\\n\",\n       \"    {\\n\",\n       \"    case 0:\\n\",\n       \"        cursor = 'pointer';\\n\",\n       \"        break;\\n\",\n       \"    case 1:\\n\",\n       \"        cursor = 'default';\\n\",\n       \"        break;\\n\",\n       \"    case 2:\\n\",\n       \"        cursor = 'crosshair';\\n\",\n       \"        break;\\n\",\n       \"    case 3:\\n\",\n       \"        cursor = 'move';\\n\",\n       \"        break;\\n\",\n       \"    }\\n\",\n       \"    fig.rubberband_canvas.style.cursor = cursor;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_message = function(fig, msg) {\\n\",\n       \"    fig.message.textContent = msg['message'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_draw = function(fig, msg) {\\n\",\n       \"    // Request the server to send over a new figure.\\n\",\n       \"    fig.send_draw_message();\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\\n\",\n       \"    fig.image_mode = msg['mode'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Called whenever the canvas gets updated.\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// A function to construct a web socket function for onmessage handling.\\n\",\n       \"// Called in the figure constructor.\\n\",\n       \"mpl.figure.prototype._make_on_message_function = function(fig) {\\n\",\n       \"    return function socket_on_message(evt) {\\n\",\n       \"        if (evt.data instanceof Blob) {\\n\",\n       \"            /* FIXME: We get \\\"Resource interpreted as Image but\\n\",\n       \"             * transferred with MIME type text/plain:\\\" errors on\\n\",\n       \"             * Chrome.  But how to set the MIME type?  It doesn't seem\\n\",\n       \"             * to be part of the websocket stream */\\n\",\n       \"            evt.data.type = \\\"image/png\\\";\\n\",\n       \"\\n\",\n       \"            /* Free the memory for the previous frames */\\n\",\n       \"            if (fig.imageObj.src) {\\n\",\n       \"                (window.URL || window.webkitURL).revokeObjectURL(\\n\",\n       \"                    fig.imageObj.src);\\n\",\n       \"            }\\n\",\n       \"\\n\",\n       \"            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\\n\",\n       \"                evt.data);\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \\\"data:image/png;base64\\\") {\\n\",\n       \"            fig.imageObj.src = evt.data;\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        var msg = JSON.parse(evt.data);\\n\",\n       \"        var msg_type = msg['type'];\\n\",\n       \"\\n\",\n       \"        // Call the  \\\"handle_{type}\\\" callback, which takes\\n\",\n       \"        // the figure and JSON message as its only arguments.\\n\",\n       \"        try {\\n\",\n       \"            var callback = fig[\\\"handle_\\\" + msg_type];\\n\",\n       \"        } catch (e) {\\n\",\n       \"            console.log(\\\"No handler for the '\\\" + msg_type + \\\"' message type: \\\", msg);\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        if (callback) {\\n\",\n       \"            try {\\n\",\n       \"                // console.log(\\\"Handling '\\\" + msg_type + \\\"' message: \\\", msg);\\n\",\n       \"                callback(fig, msg);\\n\",\n       \"            } catch (e) {\\n\",\n       \"                console.log(\\\"Exception inside the 'handler_\\\" + msg_type + \\\"' callback:\\\", e, e.stack, msg);\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\\n\",\n       \"mpl.findpos = function(e) {\\n\",\n       \"    //this section is from http://www.quirksmode.org/js/events_properties.html\\n\",\n       \"    var targ;\\n\",\n       \"    if (!e)\\n\",\n       \"        e = window.event;\\n\",\n       \"    if (e.target)\\n\",\n       \"        targ = e.target;\\n\",\n       \"    else if (e.srcElement)\\n\",\n       \"        targ = e.srcElement;\\n\",\n       \"    if (targ.nodeType == 3) // defeat Safari bug\\n\",\n       \"        targ = targ.parentNode;\\n\",\n       \"\\n\",\n       \"    // jQuery normalizes the pageX and pageY\\n\",\n       \"    // pageX,Y are the mouse positions relative to the document\\n\",\n       \"    // offset() returns the position of the element relative to the document\\n\",\n       \"    var x = e.pageX - $(targ).offset().left;\\n\",\n       \"    var y = e.pageY - $(targ).offset().top;\\n\",\n       \"\\n\",\n       \"    return {\\\"x\\\": x, \\\"y\\\": y};\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"/*\\n\",\n       \" * return a copy of an object with only non-object keys\\n\",\n       \" * we need this to avoid circular references\\n\",\n       \" * http://stackoverflow.com/a/24161582/3208463\\n\",\n       \" */\\n\",\n       \"function simpleKeys (original) {\\n\",\n       \"  return Object.keys(original).reduce(function (obj, key) {\\n\",\n       \"    if (typeof original[key] !== 'object')\\n\",\n       \"        obj[key] = original[key]\\n\",\n       \"    return obj;\\n\",\n       \"  }, {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.mouse_event = function(event, name) {\\n\",\n       \"    var canvas_pos = mpl.findpos(event)\\n\",\n       \"\\n\",\n       \"    if (name === 'button_press')\\n\",\n       \"    {\\n\",\n       \"        this.canvas.focus();\\n\",\n       \"        this.canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var x = canvas_pos.x * mpl.ratio;\\n\",\n       \"    var y = canvas_pos.y * mpl.ratio;\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {x: x, y: y, button: event.button,\\n\",\n       \"                             step: event.step,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"\\n\",\n       \"    /* This prevents the web browser from automatically changing to\\n\",\n       \"     * the text insertion cursor when the button is pressed.  We want\\n\",\n       \"     * to control all of the cursor setting manually through the\\n\",\n       \"     * 'cursor' event from matplotlib */\\n\",\n       \"    event.preventDefault();\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    // Handle any extra behaviour associated with a key event\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.key_event = function(event, name) {\\n\",\n       \"\\n\",\n       \"    // Prevent repeat events\\n\",\n       \"    if (name == 'key_press')\\n\",\n       \"    {\\n\",\n       \"        if (event.which === this._key)\\n\",\n       \"            return;\\n\",\n       \"        else\\n\",\n       \"            this._key = event.which;\\n\",\n       \"    }\\n\",\n       \"    if (name == 'key_release')\\n\",\n       \"        this._key = null;\\n\",\n       \"\\n\",\n       \"    var value = '';\\n\",\n       \"    if (event.ctrlKey && event.which != 17)\\n\",\n       \"        value += \\\"ctrl+\\\";\\n\",\n       \"    if (event.altKey && event.which != 18)\\n\",\n       \"        value += \\\"alt+\\\";\\n\",\n       \"    if (event.shiftKey && event.which != 16)\\n\",\n       \"        value += \\\"shift+\\\";\\n\",\n       \"\\n\",\n       \"    value += 'k';\\n\",\n       \"    value += event.which.toString();\\n\",\n       \"\\n\",\n       \"    this._key_event_extra(event, name);\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {key: value,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onclick = function(name) {\\n\",\n       \"    if (name == 'download') {\\n\",\n       \"        this.handle_save(this, null);\\n\",\n       \"    } else {\\n\",\n       \"        this.send_message(\\\"toolbar_button\\\", {name: name});\\n\",\n       \"    }\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\\n\",\n       \"    this.message.textContent = tooltip;\\n\",\n       \"};\\n\",\n       \"mpl.toolbar_items = [[\\\"Home\\\", \\\"Reset original view\\\", \\\"fa fa-home icon-home\\\", \\\"home\\\"], [\\\"Back\\\", \\\"Back to previous view\\\", \\\"fa fa-arrow-left icon-arrow-left\\\", \\\"back\\\"], [\\\"Forward\\\", \\\"Forward to next view\\\", \\\"fa fa-arrow-right icon-arrow-right\\\", \\\"forward\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Pan\\\", \\\"Pan axes with left mouse, zoom with right\\\", \\\"fa fa-arrows icon-move\\\", \\\"pan\\\"], [\\\"Zoom\\\", \\\"Zoom to rectangle\\\", \\\"fa fa-square-o icon-check-empty\\\", \\\"zoom\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Download\\\", \\\"Download plot\\\", \\\"fa fa-floppy-o icon-save\\\", \\\"download\\\"]];\\n\",\n       \"\\n\",\n       \"mpl.extensions = [\\\"eps\\\", \\\"jpeg\\\", \\\"pdf\\\", \\\"png\\\", \\\"ps\\\", \\\"raw\\\", \\\"svg\\\", \\\"tif\\\"];\\n\",\n       \"\\n\",\n       \"mpl.default_extension = \\\"png\\\";var comm_websocket_adapter = function(comm) {\\n\",\n       \"    // Create a \\\"websocket\\\"-like object which calls the given IPython comm\\n\",\n       \"    // object with the appropriate methods. Currently this is a non binary\\n\",\n       \"    // socket, so there is still some room for performance tuning.\\n\",\n       \"    var ws = {};\\n\",\n       \"\\n\",\n       \"    ws.close = function() {\\n\",\n       \"        comm.close()\\n\",\n       \"    };\\n\",\n       \"    ws.send = function(m) {\\n\",\n       \"        //console.log('sending', m);\\n\",\n       \"        comm.send(m);\\n\",\n       \"    };\\n\",\n       \"    // Register the callback with on_msg.\\n\",\n       \"    comm.on_msg(function(msg) {\\n\",\n       \"        //console.log('receiving', msg['content']['data'], msg);\\n\",\n       \"        // Pass the mpl event to the overridden (by mpl) onmessage function.\\n\",\n       \"        ws.onmessage(msg['content']['data'])\\n\",\n       \"    });\\n\",\n       \"    return ws;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.mpl_figure_comm = function(comm, msg) {\\n\",\n       \"    // This is the function which gets called when the mpl process\\n\",\n       \"    // starts-up an IPython Comm through the \\\"matplotlib\\\" channel.\\n\",\n       \"\\n\",\n       \"    var id = msg.content.data.id;\\n\",\n       \"    // Get hold of the div created by the display call when the Comm\\n\",\n       \"    // socket was opened in Python.\\n\",\n       \"    var element = $(\\\"#\\\" + id);\\n\",\n       \"    var ws_proxy = comm_websocket_adapter(comm)\\n\",\n       \"\\n\",\n       \"    function ondownload(figure, format) {\\n\",\n       \"        window.open(figure.imageObj.src);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fig = new mpl.figure(id, ws_proxy,\\n\",\n       \"                           ondownload,\\n\",\n       \"                           element.get(0));\\n\",\n       \"\\n\",\n       \"    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\\n\",\n       \"    // web socket which is closed, not our websocket->open comm proxy.\\n\",\n       \"    ws_proxy.onopen();\\n\",\n       \"\\n\",\n       \"    fig.parent_element = element.get(0);\\n\",\n       \"    fig.cell_info = mpl.find_output_cell(\\\"<div id='\\\" + id + \\\"'></div>\\\");\\n\",\n       \"    if (!fig.cell_info) {\\n\",\n       \"        console.error(\\\"Failed to find cell for figure\\\", id, fig);\\n\",\n       \"        return;\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var output_index = fig.cell_info[2]\\n\",\n       \"    var cell = fig.cell_info[0];\\n\",\n       \"\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_close = function(fig, msg) {\\n\",\n       \"    var width = fig.canvas.width/mpl.ratio\\n\",\n       \"    fig.root.unbind('remove')\\n\",\n       \"\\n\",\n       \"    // Update the output cell to use the data from the current canvas.\\n\",\n       \"    fig.push_to_output();\\n\",\n       \"    var dataURL = fig.canvas.toDataURL();\\n\",\n       \"    // Re-enable the keyboard manager in IPython - without this line, in FF,\\n\",\n       \"    // the notebook keyboard shortcuts fail.\\n\",\n       \"    IPython.keyboard_manager.enable()\\n\",\n       \"    $(fig.parent_element).html('<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">');\\n\",\n       \"    fig.close_ws(fig, msg);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.close_ws = function(fig, msg){\\n\",\n       \"    fig.send_message('closing', msg);\\n\",\n       \"    // fig.ws.close()\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.push_to_output = function(remove_interactive) {\\n\",\n       \"    // Turn the data on the canvas into data in the output cell.\\n\",\n       \"    var width = this.canvas.width/mpl.ratio\\n\",\n       \"    var dataURL = this.canvas.toDataURL();\\n\",\n       \"    this.cell_info[1]['text/html'] = '<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">';\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Tell IPython that the notebook contents must change.\\n\",\n       \"    IPython.notebook.set_dirty(true);\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"    var fig = this;\\n\",\n       \"    // Wait a second, then push the new image to the DOM so\\n\",\n       \"    // that it is saved nicely (might be nice to debounce this).\\n\",\n       \"    setTimeout(function () { fig.push_to_output() }, 1000);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>');\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items){\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) { continue; };\\n\",\n       \"\\n\",\n       \"        var button = $('<button class=\\\"btn btn-default\\\" href=\\\"#\\\" title=\\\"' + name + '\\\"><i class=\\\"fa ' + image + ' fa-lg\\\"></i></button>');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add the status bar.\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\" style=\\\"text-align:right; float: right;\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"\\n\",\n       \"    // Add the close button to the window.\\n\",\n       \"    var buttongrp = $('<div class=\\\"btn-group inline pull-right\\\"></div>');\\n\",\n       \"    var button = $('<button class=\\\"btn btn-mini btn-primary\\\" href=\\\"#\\\" title=\\\"Stop Interaction\\\"><i class=\\\"fa fa-power-off icon-remove icon-large\\\"></i></button>');\\n\",\n       \"    button.click(function (evt) { fig.handle_close(fig, {}); } );\\n\",\n       \"    button.mouseover('Stop Interaction', toolbar_mouse_event);\\n\",\n       \"    buttongrp.append(button);\\n\",\n       \"    var titlebar = this.root.find($('.ui-dialog-titlebar'));\\n\",\n       \"    titlebar.prepend(buttongrp);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(el){\\n\",\n       \"    var fig = this\\n\",\n       \"    el.on(\\\"remove\\\", function(){\\n\",\n       \"\\tfig.close_ws(fig, {});\\n\",\n       \"    });\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(el){\\n\",\n       \"    // this is important to make the div 'focusable\\n\",\n       \"    el.attr('tabindex', 0)\\n\",\n       \"    // reach out to IPython and tell the keyboard manager to turn it's self\\n\",\n       \"    // off when our div gets focus\\n\",\n       \"\\n\",\n       \"    // location in version 3\\n\",\n       \"    if (IPython.notebook.keyboard_manager) {\\n\",\n       \"        IPython.notebook.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"    else {\\n\",\n       \"        // location in version 2\\n\",\n       \"        IPython.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    var manager = IPython.notebook.keyboard_manager;\\n\",\n       \"    if (!manager)\\n\",\n       \"        manager = IPython.keyboard_manager;\\n\",\n       \"\\n\",\n       \"    // Check for shift+enter\\n\",\n       \"    if (event.shiftKey && event.which == 13) {\\n\",\n       \"        this.canvas_div.blur();\\n\",\n       \"        event.shiftKey = false;\\n\",\n       \"        // Send a \\\"J\\\" for go to next cell\\n\",\n       \"        event.which = 74;\\n\",\n       \"        event.keyCode = 74;\\n\",\n       \"        manager.command_mode();\\n\",\n       \"        manager.handle_keydown(event);\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    fig.ondownload(fig, null);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.find_output_cell = function(html_output) {\\n\",\n       \"    // Return the cell and output element which can be found *uniquely* in the notebook.\\n\",\n       \"    // Note - this is a bit hacky, but it is done because the \\\"notebook_saving.Notebook\\\"\\n\",\n       \"    // IPython event is triggered only after the cells have been serialised, which for\\n\",\n       \"    // our purposes (turning an active figure into a static one), is too late.\\n\",\n       \"    var cells = IPython.notebook.get_cells();\\n\",\n       \"    var ncells = cells.length;\\n\",\n       \"    for (var i=0; i<ncells; i++) {\\n\",\n       \"        var cell = cells[i];\\n\",\n       \"        if (cell.cell_type === 'code'){\\n\",\n       \"            for (var j=0; j<cell.output_area.outputs.length; j++) {\\n\",\n       \"                var data = cell.output_area.outputs[j];\\n\",\n       \"                if (data.data) {\\n\",\n       \"                    // IPython >= 3 moved mimebundle to data attribute of output\\n\",\n       \"                    data = data.data;\\n\",\n       \"                }\\n\",\n       \"                if (data['text/html'] == html_output) {\\n\",\n       \"                    return [cell, data, j];\\n\",\n       \"                }\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// Register the function which deals with the matplotlib target/channel.\\n\",\n       \"// The kernel may be null if the page has been refreshed.\\n\",\n       \"if (IPython.notebook.kernel != null) {\\n\",\n       \"    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\\n\",\n       \"}\\n\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.Javascript object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"text/html\": [\n       \"<img src=\\\"data:image/png;base64,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\\\" 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  },
  {
    "path": "examples/coarse-graining/step-3_cluster-analysis/atomic-env.dGdx",
    "content": "Cm  -2.58219032E-02  -4.06287260E-02  -7.50249397E-02  -1.19040543E-01  -7.32798855E-02  -1.31422937E-01  -2.15281855E-01  -3.15612884E-01  -8.23123490E-02  -2.72606064E-02  -4.33969036E-02  -3.05741912E-02  -6.17681744E-02  -8.18827416E-02  -1.25432785E-01  -1.66106881E-01  -1.30227953E-01  -1.74945884E-01  -2.39781617E-01  -3.24552238E-01  -2.04933641E-01  -3.92484921E-02  -1.04264928E-01  -5.38691619E-02   4.92056970E-02   6.20911421E-02   8.54415890E-02   9.65515057E-02   9.61626738E-02   1.09164731E-01   1.01906461E-01   4.08100840E-02   1.35705173E-01   1.40650386E-02   5.04308374E-02   2.35361409E-02  -3.92627381E-02  -4.95173652E-02  -6.80589471E-02  -7.67753990E-02  -7.66248713E-02  -8.67927992E-02  -8.06333804E-02  -3.18125143E-02  -4.49095742E-02  -3.75190457E-02  -2.21906120E-02  -3.50065681E-02  -4.64870913E-03  -5.41792910E-03  -6.29044804E-03  -5.54573224E-03  -6.82519352E-03  -5.31839788E-03  -2.25423799E-03  -8.05816650E-05  -5.21460888E-03  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8.13507523E-02   5.34085673E-02   7.23644949E-03   6.38487334E-02   3.42200564E-02   4.64244070E-02   4.88362629E-02\nCm  -3.47480641E-02  -4.70657209E-02  -8.08598521E-02  -1.18780085E-01  -9.21312954E-02  -1.42335100E-01  -1.84360457E-01  -1.70932931E-01  -5.74542018E-02  -3.65016058E-02  -3.28701234E-02  -4.51825648E-02  -4.96754644E-02  -6.49460654E-02  -9.65156207E-02  -1.22181219E-01  -1.03680212E-01  -1.33807323E-01  -1.66491789E-01  -1.64668542E-01  -1.00983432E-01  -2.15620222E-02  -4.85775671E-02  -2.57363384E-02  -3.01791721E-02  -3.74246012E-02  -4.96037637E-02  -5.30516136E-02  -5.61680359E-02  -5.92400218E-02  -4.72132622E-02  -1.15972132E-02  -2.00703548E-02  -1.86785627E-02  -3.56126143E-02  -2.57602174E-02   2.07363411E-02   2.54925105E-02   3.31652185E-02   3.45160119E-02   3.75406221E-02   3.80876095E-02   2.79569381E-02   5.33199919E-03   2.66800423E-02   4.55789503E-03   9.15984446E-03   4.36462623E-03   3.65875533E-02   3.80802311E-02   3.48291927E-02   2.17530353E-02   2.94752246E-02   1.18405232E-02   1.30754345E-03   8.06793486E-07   1.32108752E-02   1.43138990E-02   8.88422686E-03   8.47883777E-03\nCm   6.46790357E-02   7.63867258E-02   8.96770264E-02   8.78444894E-02   8.70270615E-02   8.60070546E-02   8.74765721E-02   7.15961902E-02   4.09497069E-02   5.05634309E-02   1.06429745E-01   9.97720191E-02   6.85586713E-02   8.81532598E-02   1.26338767E-01   1.51581586E-01   1.39619615E-01   1.70337990E-01   1.86364941E-01   1.22539350E-01   6.53742868E-02   5.32478158E-02   6.96382999E-02   7.63130433E-02   2.81631168E-03   3.58225925E-03   5.01504325E-03   5.81260287E-03   5.60980418E-03   6.57254033E-03   6.57346371E-03   3.26248478E-03  -2.86967538E-03   4.18618624E-03   5.78055682E-03   2.95176542E-03  -7.07871779E-02  -8.95024758E-02  -1.23692698E-01  -1.40664162E-01  -1.39029153E-01  -1.59099537E-01  -1.51137369E-01  -6.38994809E-02  -1.17736787E-01  -1.75545394E-02  -1.61635659E-02  -1.37256428E-02   2.94559926E-02   3.64039771E-02   4.79005369E-02   5.06856280E-02   5.42454668E-02   5.63596832E-02   4.35059163E-02   9.68628835E-03   4.42709232E-02   5.42639893E-02   4.69120325E-02   7.18080887E-02\nCm   1.18728387E-03   6.43742964E-03   1.67174509E-02   1.85050292E-02   2.90936533E-02   2.11720756E-02  -5.98656538E-03  -2.06701587E-02   6.95451095E-03  -3.13812473E-02   1.66222427E-02  -2.32711481E-02   2.56638321E-02   3.29179486E-02   4.69268573E-02   5.58627244E-02   5.20234705E-02   6.29059613E-02   6.74661669E-02   4.16657595E-02   3.21809587E-02   1.47012625E-02   2.37290542E-02   2.73125547E-02  -6.90706454E-02  -8.80561008E-02  -1.23884796E-01  -1.44633310E-01  -1.38275696E-01  -1.63431376E-01  -1.66636558E-01  -8.78364030E-02  -1.74389210E-01  -2.24140762E-02  -1.28487582E-01  -5.86553644E-02   4.91021307E-02   6.12869687E-02   8.23725566E-02   8.99187909E-02   9.31656333E-02   1.01061457E-01   8.55285935E-02   2.52818816E-02   1.07510706E-01   3.30508921E-02   5.92584141E-02   3.72495281E-02   1.53549904E-02   1.78297247E-02   2.05392956E-02   1.79024793E-02   2.21717064E-02   1.69402273E-02   6.89560999E-03   2.18034391E-04   1.13936390E-02   1.56539708E-02   1.23300843E-02   2.11864831E-02\nCm  -1.80061707E-02  -1.09836881E-02  -6.00943379E-03  -2.28248006E-02   1.32994094E-02  -2.82714397E-02  -1.08461304E-01  -1.41207902E-01  -1.85828888E-02  -3.00816348E-02   4.56030961E-02   6.16476800E-02  -5.48243729E-02  -7.11445647E-02  -1.04019963E-01  -1.28544013E-01  -1.13347614E-01  -1.42783808E-01  -1.67965930E-01  -1.38889310E-01  -1.31374269E-01  -2.88282963E-02  -7.95222197E-02  -4.05077765E-02  -3.99351779E-02  -5.10927431E-02  -7.24347925E-02  -8.55275687E-02  -8.05446767E-02  -9.64785353E-02  -1.01322627E-01  -5.85862503E-02  -1.22404391E-01  -1.61578833E-02  -3.79321989E-02  -2.23999711E-02   5.37918454E-02   6.81459828E-02   9.45737021E-02   1.08215524E-01   1.06148602E-01   1.22415532E-01   1.18267308E-01   5.26955535E-02   7.20072488E-02   3.09633917E-02   8.58287933E-02   7.75487551E-02   2.75729230E-02   3.33701434E-02   4.19823824E-02   4.16022781E-02   4.72502467E-02   4.45543370E-02   2.80376508E-02   3.33736790E-03   2.68349502E-02   1.87725890E-02   2.48555384E-02   2.40800341E-02\nCm   9.73203020E-03   1.04876412E-02   1.73727636E-02   3.57572887E-02   1.08346937E-02   4.18358938E-02   9.41974324E-02   1.24771531E-01   2.64340638E-02   1.28319117E-02   2.56615793E-02  -1.18219286E-02   2.07260868E-02   2.70717415E-02   4.01477822E-02   5.06681563E-02   4.32127873E-02   5.56033607E-02   6.87038442E-02   6.64474249E-02   1.78702163E-02   2.88247708E-02   5.16609774E-02   5.30735610E-02   6.79962764E-02   8.79557879E-02   1.27707895E-01   1.56200815E-01   1.39901498E-01   1.74328045E-01   2.00048067E-01   1.52903099E-01   1.59343242E-01   5.50035220E-02   7.31057945E-02   6.67402011E-02  -4.02979563E-02  -5.17693320E-02  -7.40512420E-02  -8.85939883E-02  -8.19315183E-02  -9.96364498E-02  -1.08228235E-01  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8.87918119E-02   6.98984881E-02   1.65300688E-02   5.97732914E-02   3.10028528E-02   3.44007313E-02   2.62283908E-02   3.34249241E-02   3.96094105E-02   4.76436634E-02   4.42201667E-02   5.27276915E-02   4.47990781E-02   2.26977268E-02   1.39524839E-03   2.92314357E-02   2.02694673E-02   6.50890443E-02   4.47961442E-02\nCm   4.01030374E-02   4.38347928E-02   4.80801529E-02   4.40700685E-02   4.67091286E-02   3.89756919E-02   2.84717627E-02   5.75426779E-02   6.45490320E-03   5.61679862E-02   7.98260573E-02   7.99666800E-02   4.00990471E-02   5.29789468E-02   8.05604067E-02   1.05520525E-01   8.44167615E-02   1.12377277E-01   1.50599306E-01   1.89357850E-01   1.07863732E-01   2.19442133E-02   7.98626927E-02   6.12635258E-02  -6.51016186E-02  -8.45944627E-02  -1.24046488E-01  -1.53955660E-01  -1.34850417E-01  -1.70631861E-01  -2.02796157E-01  -1.73251549E-01  -6.69950589E-02  -1.78240910E-02  -3.72610668E-02  -2.33910745E-02   1.42801088E-02   1.85485851E-02   2.71757254E-02   3.36853791E-02   2.95634049E-02   3.73589584E-02   4.42679597E-02   3.74590300E-02   2.06445582E-02   1.49696346E-02   1.62407931E-02   1.61220033E-02   3.41184620E-03   4.16292186E-03   5.32920019E-03   5.41689280E-03   6.02040500E-03   5.89977107E-03   4.02494702E-03   6.13363012E-04   6.45176377E-03   1.49484807E-02   5.85501901E-03   1.24866050E-02\nCm   2.00356926E-02   3.54637157E-02   7.09112006E-02   9.26638815E-02   1.03801384E-01   1.18449183E-01   7.31778395E-02  -1.42249935E-02   5.40416306E-02   3.82145530E-02   1.52121320E-01   1.69407895E-01  -2.15198139E-02  -2.77597330E-02  -4.00640606E-02  -4.85687816E-02  -4.40757956E-02  -5.43947238E-02  -6.10713350E-02  -4.35646854E-02  -3.34759008E-02   2.17280365E-02  -2.05588272E-02   1.51364982E-02   1.09487912E-02   1.38536236E-02   1.91759231E-02   2.18575705E-02   2.15423332E-02   2.47241683E-02   2.36364782E-02   1.01925711E-02   1.40387866E-02   3.15829028E-02   2.92270844E-02   3.90580270E-02   6.57520088E-02   8.04486063E-02   1.03598223E-01   1.06218133E-01   1.17139826E-01   1.16276748E-01   8.15005598E-02   1.34926076E-02   9.56898834E-02   6.77412357E-02   1.36520752E-01   1.24438699E-01   3.19513990E-02   3.90033406E-02   4.99804577E-02   5.08772829E-02   5.64723189E-02   5.54616256E-02   3.80110977E-02   5.87450701E-03   1.97841388E-02   6.15977754E-02   9.81078154E-02   1.17605583E-01\nCm   9.38702112E-03   1.75635783E-02   3.82099593E-02   5.19395045E-02   5.68224360E-02   6.50943163E-02   4.60266013E-02  -1.42461630E-03   3.06513533E-02   3.60286493E-02   1.22338764E-01   1.45335002E-01   5.03846066E-02   6.64876203E-02   1.00833584E-01   1.31554270E-01   1.05996464E-01   1.40627769E-01   1.86905830E-01   2.28752494E-01   1.36270126E-01   4.97231083E-02   1.71108026E-01   1.29363089E-01  -7.18557406E-02  -9.45146577E-02  -1.42326543E-01  -1.83743900E-01  -1.50827100E-01  -1.98254380E-01  -2.57640325E-01  -2.93128331E-01  -1.34005218E-01  -3.32419065E-02  -9.21498278E-02  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1.72646771E-01   1.86600127E-01   1.18075068E-01   8.94975575E-02   4.52993744E-02   1.06665865E-01   8.50365230E-02  -4.43244100E-02  -5.54352691E-02  -7.48314536E-02  -8.22085479E-02  -8.45840479E-02  -9.25418999E-02  -7.97715448E-02  -2.49580051E-02  -1.11607923E-01  -9.73690630E-03  -3.49863973E-02  -1.65771417E-02   2.12591476E-02   2.51360021E-02   3.00900585E-02   2.77338658E-02   3.32224497E-02   2.79041930E-02   1.38055629E-02   7.89418200E-04   3.56464457E-02   2.40846671E-02   2.91603038E-02   2.91946085E-02   1.17968163E-02   1.37384058E-02   1.59252213E-02   1.40070614E-02   1.72612528E-02   1.33964834E-02   5.63139971E-03   1.96313516E-04   7.35919539E-03   1.94139614E-02   1.30135705E-02   1.91448940E-02\nCm  -1.94383496E-02  -2.15001746E-02  -2.85625767E-02  -4.12903810E-02  -2.84721800E-02  -4.91183296E-02  -6.14297426E-02  -9.53375588E-02  -4.77944819E-02  -2.69176230E-02  -4.95219501E-03   2.61098328E-02  -4.05547053E-02  -5.40915692E-02  -8.39846934E-02  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1.70234636E-02   3.85682670E-03   2.07307038E-05   1.48039862E-02   2.36440577E-02   1.84924965E-02   1.74777518E-02\nCm   2.78108397E-02   3.50315185E-02   5.45879647E-02   6.34756451E-02   7.81910517E-02   8.13888754E-02   3.41029550E-02  -4.57964770E-02   5.23356242E-02   5.29396633E-04   6.14648196E-02   2.85728764E-02  -1.20088452E-02  -1.58840012E-02  -2.42131725E-02  -3.18319662E-02  -2.52955220E-02  -3.37784242E-02  -4.56134161E-02  -5.87989890E-02  -5.28147887E-02   2.24544077E-02   6.23981185E-03   2.55302020E-02  -3.31791545E-02  -4.16080902E-02  -5.64928283E-02  -6.25926122E-02  -6.37898963E-02  -7.05856820E-02  -6.23449481E-02  -2.10313918E-02  -5.81957400E-02  -8.10601867E-03  -3.61676638E-02  -1.52839691E-02   5.05606221E-02   6.32555741E-02   8.54486173E-02   9.39702430E-02   9.65739720E-02   1.05807218E-01   9.14798580E-02   2.88873274E-02   9.88635878E-02   4.29060206E-02   4.37906507E-02   4.19986032E-02   5.52331476E-02   6.64938844E-02   8.27168673E-02   8.06300302E-02   9.27908572E-02   8.52908938E-02   5.08854074E-02   5.14663811E-03   8.17067302E-02   5.01235385E-02   3.44617606E-02   4.43807201E-02\nCm  -1.44219295E-02  -2.91969414E-02  -6.65643993E-02  -1.07140940E-01  -7.36692532E-02  -1.13426523E-01  -1.76835081E-01  -2.81693051E-01  -4.83057177E-02  -1.16950677E-02  -3.25454728E-02  -2.87680101E-02  -7.31567074E-02  -9.66211394E-02  -1.46811070E-01  -1.92079457E-01  -1.53980562E-01  -2.04783805E-01  -2.73785966E-01  -3.41596155E-01  -1.96122040E-01  -2.64771270E-02  -1.25900414E-01  -5.44764390E-02   3.63357765E-02   4.66231134E-02   6.65161826E-02   7.92730905E-02   7.37075366E-02   8.92430419E-02   9.59931592E-02   5.98311753E-02   5.23507843E-02   1.01956919E-02   6.25539839E-02   3.50859882E-02   8.48894898E-03   9.82084168E-03   1.12252459E-02   9.67376820E-03   1.20528901E-02   9.02872718E-03   3.52902925E-03   9.86665774E-05   1.26071852E-02  -1.99244614E-02   1.37779808E-03  -1.24922594E-02  -1.35956822E-02  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1.02140073E-01   1.29356027E-01   1.35416687E-01   6.73167118E-02   3.02010643E-02   2.36267561E-02   2.09458047E-02  -5.90384652E-02  -7.69176945E-02  -1.13437167E-01  -1.41987009E-01  -1.22716357E-01  -1.56620594E-01  -1.89881299E-01  -1.72827186E-01  -1.83185110E-01  -4.55955070E-02  -1.64133375E-01  -1.01387833E-01  -3.81219680E-02  -4.89354993E-02  -6.98786522E-02  -8.33921479E-02  -7.73927504E-02  -9.38485055E-02  -1.01292489E-01  -6.38155772E-02  -8.45433119E-02  -4.09684398E-02  -7.30061355E-02  -6.61386439E-02\nCm  -5.14958368E-02  -7.01127703E-02  -1.00261909E-01  -1.09164929E-01  -1.11510842E-01  -1.05871919E-01  -1.00750232E-01  -1.14941977E-01  -5.91252421E-02  -6.11643470E-02  -1.51648501E-01  -1.61016332E-01  -7.36187786E-02  -9.67207159E-02  -1.45277144E-01  -1.86843380E-01  -1.54381360E-01  -2.02229169E-01  -2.60648719E-01  -2.88749405E-01  -1.80418838E-01  -6.08424077E-02  -2.44847550E-01  -1.66298381E-01   5.02140668E-02   6.57459844E-02   9.80158335E-02   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1.94939749E-02   8.98457597E-03   3.04512299E-02   4.16202037E-02   4.15090593E-02   1.07259535E-02   3.72283011E-03   3.13841315E-02  -7.23004069E-03   3.10907257E-03   4.23136185E-03   6.86991908E-03   9.92389564E-03   6.46247750E-03   9.16387561E-03   1.46033385E-02   3.31479933E-02   2.47860244E-02   6.68313535E-03  -1.74753323E-02  -1.04020250E-02  -2.35510727E-03  -3.01835989E-03  -4.29535359E-03  -5.10007933E-03  -4.76655406E-03  -5.74653554E-03  -6.12242561E-03  -3.70327531E-03  -1.69438988E-02   2.05132967E-02   1.31567002E-02   3.34479101E-02   4.57243268E-02   5.69699674E-02   7.62792061E-02   8.28031327E-02   8.63119140E-02   9.29188376E-02   7.73692450E-02   2.17506067E-02   7.12994127E-02   3.59042060E-02   6.69971570E-02   7.26831710E-02  -2.94559926E-02  -3.64039771E-02  -4.79005369E-02  -5.06856280E-02  -5.42454668E-02  -5.63596832E-02  -4.35059163E-02  -9.68628835E-03  -3.99326904E-02  -9.17092172E-03  -3.80619732E-02  -2.36107255E-02\nCm   4.25295260E-02   6.70668023E-02   1.10628677E-01   1.42146365E-01   1.17422486E-01   1.44511992E-01   1.87438742E-01   2.76016518E-01   1.32260253E-01   5.95372269E-02   2.80677620E-01   3.02582116E-01   4.26802929E-03   5.73482691E-03   9.05028949E-03   1.25290109E-02   8.98870739E-03   1.24671601E-02   1.85761449E-02   3.32598837E-02   1.19045684E-02   5.73473206E-02   2.35955836E-02   7.91866525E-02   4.14743880E-02   5.51185734E-02   8.49009833E-02   1.13359295E-01   8.75011254E-02   1.18315990E-01   1.64844326E-01   2.35518749E-01   1.09216553E-01   5.70151908E-02   2.09705437E-01   2.00681657E-01   4.00749344E-02   5.10006904E-02   7.14799978E-02   8.29857471E-02   7.99186661E-02   9.38233097E-02   9.42539274E-02   4.74318271E-02   4.64903936E-02   8.01181591E-02   9.82742130E-02   1.53753892E-01  -6.11427352E-02  -7.68349864E-02  -1.04789359E-01  -1.16869440E-01  -1.18212406E-01  -1.31939425E-01  -1.18725360E-01  -4.24269064E-02  -1.31157059E-01  -3.96926825E-02  -5.29052723E-02  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1.03035032E-02   1.09548242E-02   1.14873951E-02   9.04330744E-03   2.13878753E-03   1.49144796E-02   4.76156127E-03   8.79737617E-04   5.11017504E-03\nCm   6.13813730E-02   8.14419349E-02   1.26752550E-01   1.71866205E-01   1.33335050E-01   1.86280512E-01   2.55249866E-01   3.20899573E-01   1.09829883E-01   6.63048452E-02   2.97186290E-02   4.63550095E-02   5.27445842E-02   6.97261413E-02   1.06159518E-01   1.39310763E-01   1.11071394E-01   1.48094174E-01   1.99235303E-01   2.53704585E-01   1.75895494E-01   2.45999306E-02   8.78058521E-02   3.44263061E-02   1.52117708E-02   2.00564692E-02   3.03607183E-02   3.95014084E-02   3.19846480E-02   4.23330138E-02   5.59367144E-02   6.71725928E-02   4.86588558E-02   6.48102484E-03  -7.85840456E-04  -1.10650796E-02   4.82202455E-03   5.49305028E-03   6.07642576E-03   4.99382013E-03   6.36386888E-03   4.38069404E-03   1.44015563E-03   2.38396405E-05  -5.08443877E-04   2.13204079E-02   9.59884357E-03   1.61016832E-02  -2.96866427E-02  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6.32752406E-02   1.50731099E-01   8.84602541E-02   7.38392965E-02   1.01218537E-01   1.66995326E-01   2.47130028E-01   1.51411850E-01   2.16459640E-01   3.56012873E-01   9.10736383E-01   4.52111084E-01   7.43392186E-02   1.86890752E-01   1.28507394E-01  -6.08726425E-02  -7.74736919E-02  -1.08598832E-01  -1.26106101E-01  -1.21412084E-01  -1.42572503E-01  -1.43307636E-01  -7.22443757E-02  -1.13146026E-01  -2.50432060E-02  -1.14580145E-01  -6.03030372E-02  -5.90428624E-03  -7.51318031E-03  -1.05276395E-02  -1.22180185E-02  -1.17716747E-02  -1.38140189E-02  -1.38647277E-02  -6.95730903E-03  -2.54954171E-02   3.97020492E-02   4.34147466E-03   3.62990087E-02   3.10248364E-02   3.78654212E-02   4.85034842E-02   4.93458441E-02   5.48000368E-02   5.37738553E-02   3.67889831E-02   5.65479201E-03   3.86105701E-02   4.89598437E-02   4.53839883E-02   5.57243967E-02\nCm   1.50891993E-02   2.20602566E-02   2.86998876E-02   2.91618170E-02   2.24971466E-02   2.69527262E-02   4.67332471E-02   3.65335747E-02   7.17869231E-03   3.12523184E-04   1.12379519E-02   9.90305560E-03   6.70491298E-02   8.48485875E-02   1.17477492E-01   1.33959236E-01   1.31962858E-01   1.51529432E-01   1.45020596E-01   6.27476363E-02   6.50936881E-02   2.01396506E-02   3.70101945E-02   2.18316931E-02  -5.49812953E-02  -6.85027330E-02  -9.17182573E-02  -9.95585026E-02  -1.03781907E-01  -1.11719775E-01  -9.30126415E-02  -2.61386106E-02  -1.24695498E-01  -8.46907466E-03  -2.80019263E-02  -9.52731591E-03  -2.08326941E-02  -2.36011895E-02  -2.58048593E-02  -2.08518565E-02  -2.67609012E-02  -1.78627478E-02  -5.51454865E-03  -7.54750270E-05  -1.03487452E-02  -5.40528864E-03  -1.40934475E-02  -9.60686110E-03   1.19362906E-02   1.19501793E-02   1.00759368E-02   5.59903249E-03   7.56468174E-03   2.36538553E-03   1.57893727E-04   2.14578518E-08   2.46043462E-03   5.23881221E-03   6.72710124E-03   4.85164294E-03\nCm   2.96097144E-02   2.71379166E-02   1.62587464E-02  -2.56203685E-03   5.81962625E-03  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1.01788954E-02   1.96508042E-02   1.06136036E-03  -1.16074047E-02  -1.68543084E-02   1.85787285E-03   1.93073349E-03   2.94331777E-02   2.73645475E-02  -1.11291867E-03  -1.44787498E-03  -2.12863403E-03  -2.65204756E-03  -2.30900345E-03  -2.93318189E-03  -3.51780142E-03  -3.09321217E-03  -9.50736741E-04   2.80326777E-03   1.84008843E-03   6.86970413E-04  -3.16938151E-02  -4.10973268E-02  -5.99891067E-02  -7.39516567E-02  -6.54535464E-02  -8.22417959E-02  -9.61833684E-02  -7.80727036E-02  -8.42876722E-02   1.89529000E-03  -4.56010122E-02  -8.06090062E-03   6.33203269E-02   8.17041994E-02   1.17992512E-01   1.43171390E-01   1.29752530E-01   1.60291366E-01   1.80376183E-01   1.29597520E-01   7.80629841E-02   2.79442436E-02   6.05907549E-02   4.44427314E-02  -3.29976376E-02  -4.25402224E-02  -6.13161610E-02  -7.41896224E-02  -6.75148056E-02  -8.31454872E-02  -9.29074711E-02  -6.52860014E-02  -6.44544079E-02  -1.14180313E-02  -1.35082589E-02  -7.02391468E-03\nCm   5.37585410E-02   6.73675641E-02   1.11211478E-01   1.60471667E-01   1.29981275E-01   1.86514307E-01   2.27951993E-01   2.59220860E-01   1.11354064E-01   2.71299713E-02   1.76618573E-01   4.99566982E-02   5.96969033E-02   7.86659401E-02   1.18937564E-01   1.54468188E-01   1.25473933E-01   1.65808403E-01   2.18255453E-01   2.58861197E-01   1.99173973E-01   7.89236274E-02   8.74757619E-02   1.20330892E-01   3.04410341E-02   3.94032339E-02   5.72957990E-02   7.02313725E-02   6.26984128E-02   7.83084506E-02   9.03372151E-02   7.02106236E-02   7.17848329E-02   6.69387492E-02   3.67929124E-02   8.36739037E-02  -1.81228030E-02  -2.34382032E-02  -3.40175418E-02  -4.15824571E-02  -3.72764938E-02  -4.64197672E-02  -5.31913096E-02  -4.04697614E-02  -3.49730733E-02   2.30982792E-02  -1.89549932E-02   1.66911991E-02  -3.80306824E-02  -4.81985207E-02  -6.69489126E-02  -7.67046251E-02  -7.51192699E-02  -8.67699170E-02  -8.41233865E-02  -3.78926652E-02  -5.75434543E-02  -1.13597940E-02  -6.91694057E-02  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5.07448455E-03   2.47685672E-02   5.32684146E-03\nCm   1.42652267E-02   1.12128866E-02   1.83030455E-02   4.80584186E-02   4.44290457E-03   4.93566200E-02   1.41306563E-01   2.58679716E-01   4.90529026E-02   6.39001453E-03   1.23972755E-02  -5.56338519E-02   2.48591366E-02   3.29029100E-02   5.02298138E-02   6.61787696E-02   5.23793658E-02   7.00717187E-02   9.50472085E-02   1.24331710E-01   9.12176571E-02   5.07763187E-02   5.37710363E-02   8.54149209E-02   4.97030309E-02   6.56140986E-02   9.95949278E-02   1.30105415E-01   1.04587151E-01   1.38911833E-01   1.85124804E-01   2.28576799E-01   1.04674244E-01   3.41859165E-02   6.83748933E-02   8.12961968E-02  -3.67080859E-02  -4.79438440E-02  -7.10914897E-02  -8.97018356E-02  -7.65288324E-02  -9.84523564E-02  -1.21590887E-01  -1.17419793E-01  -6.15304250E-02  -3.42573960E-02  -1.10237643E-01  -1.15075493E-01   1.21295547E-02   1.57023472E-02   2.28380105E-02   2.80039080E-02   2.49870693E-02   3.12197359E-02   3.60458884E-02   2.80904700E-02   3.50109193E-02   1.22245804E-02   7.29854668E-04   4.69552260E-03\nCm  -6.80873872E-02  -6.93088125E-02  -5.30800606E-02  -1.56751842E-02  -3.54185013E-02   5.71136151E-03   3.57308322E-02   6.02208540E-02   1.51753132E-02  -6.53199995E-02  -8.07355893E-02  -8.26373502E-02   2.66135611E-02   3.47943339E-02   5.17060734E-02   6.54532189E-02   5.55457800E-02   7.16833449E-02   8.91849904E-02   8.81826471E-02   6.88369015E-02  -1.71033203E-02   3.67041685E-02  -1.64396916E-02  -1.77339275E-02  -2.29105552E-02  -3.31738777E-02  -4.04108985E-02  -3.64131726E-02  -4.51756020E-02  -5.13287757E-02  -3.80197193E-02  -3.10520823E-02  -2.70333662E-02  -3.93693849E-02  -2.84068021E-02   4.63219073E-02   5.87554901E-02   8.17600768E-02   9.39229988E-02   9.16770406E-02   1.06244781E-01   1.03748036E-01   4.77911974E-02   9.73222059E-02   1.46138540E-02   4.04906335E-02   1.79504798E-02  -5.42870288E-02  -6.82224152E-02  -9.30511171E-02  -1.03790779E-01  -1.04968543E-01  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1.99321537E-02   2.38598974E-02   2.00761707E-02   9.96935781E-03   5.76489055E-04   1.10217135E-02   2.37505504E-02   1.44880990E-02   2.47737409E-02\nCm  -4.80905146E-03   3.09627379E-03   2.18002237E-02   4.40034660E-02   3.10919819E-02   6.24761706E-02   7.86857669E-02   4.87291589E-02   3.62462880E-02  -2.56326595E-02   2.87888126E-02  -6.24271339E-02  -5.96969033E-02  -7.86659401E-02  -1.18937564E-01  -1.54468188E-01  -1.25473933E-01  -1.65808403E-01  -2.18255453E-01  -2.58861197E-01  -9.67305692E-02  -2.91678641E-02  -1.82305145E-01  -1.07137426E-01   7.28048466E-02   9.57521094E-02   1.44153918E-01   1.86033926E-01   1.52805598E-01   2.00787743E-01   2.60722825E-01   2.95864183E-01   1.75226319E-01   6.30855833E-02   1.31703171E-01   1.15232905E-01  -1.28748430E-02  -1.64100306E-02  -2.30756970E-02  -2.69209922E-02  -2.57620557E-02  -3.04224298E-02  -3.09598749E-02  -1.62222478E-02  -1.29998519E-02   1.50447519E-03  -3.35341261E-02  -1.23917723E-02   3.35265002E-02   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9.16102190E-03   5.09667821E-03  -1.95251014E-03   5.31606366E-03  -3.69626164E-03   6.32638989E-02   7.88942803E-02   1.05839153E-01   1.15218013E-01   1.19734380E-01   1.29398939E-01   1.08639925E-01   3.13317065E-02   1.07959311E-01   2.92362477E-02   5.63466802E-02   3.57248351E-02\nCm   2.10646339E-02   2.83890426E-02   3.90921465E-02   5.30612944E-02   2.32283878E-02   3.56689023E-02   9.55274088E-02   2.89583325E-01   4.45217813E-02   3.66235204E-02   4.36835839E-02   5.32984074E-02   7.61949431E-02   1.01397914E-01   1.56649932E-01   2.10083213E-01   1.60786329E-01   2.18148482E-01   3.06572979E-01   4.50732844E-01   2.10861094E-01   5.06351616E-02   1.15987009E-01   7.14642522E-02   2.09163713E-04   2.71875725E-04   3.98937371E-04   4.95618835E-04   4.33441926E-04   5.49012464E-04   6.54037131E-04   5.62946944E-04   2.54138190E-03   1.87986049E-03  -4.21938624E-03  -1.15459909E-03  -7.23662671E-02  -9.36058369E-02  -1.35902987E-01  -1.66208890E-01  -1.48885893E-01  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1.51943255E-01   2.03825466E-01   2.56328912E-01   1.19029030E-01   1.28950081E-02   7.43850783E-02   5.04959431E-02   4.26810646E-02   5.67113242E-02   8.73174591E-02   1.16512425E-01   9.00434682E-02   1.21694026E-01   1.69340498E-01   2.40951273E-01   1.17493152E-01   4.10355796E-02   1.46773129E-01   9.57243185E-02  -1.22091151E-02  -1.52350333E-02  -2.04655884E-02  -2.23228356E-02  -2.31487197E-02  -2.50837785E-02  -2.11799284E-02  -6.21659663E-03  -1.48618130E-02   1.36982933E-02  -2.30176660E-02  -3.30725055E-03   5.15972329E-02   6.43147504E-02   8.61925490E-02   9.36905193E-02   9.75196080E-02   1.05177434E-01   8.79213430E-02   2.50187191E-02   6.86190784E-02   3.92794493E-02   3.03246445E-02   3.25739346E-02  -3.46482985E-02  -4.17466892E-02  -5.20234226E-02  -5.08413657E-02  -5.83917304E-02  -5.38880666E-02  -3.24205936E-02  -3.36399192E-03  -3.89553552E-02  -1.35424046E-02  -6.51147196E-02  -4.48176368E-02\nCm  -3.30510512E-02  -3.68123241E-02  -3.87637927E-02  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3.31997711E-02   2.12019239E-02   3.03685144E-02   3.20437318E-02   4.08217194E-02  -6.00659046E-02  -7.65760306E-02  -1.07733065E-01  -1.25775426E-01  -1.20248028E-01  -1.42122657E-01  -1.44906825E-01  -7.63772388E-02  -8.63111566E-02  -1.92238808E-02  -6.85927898E-02  -3.45851696E-02   1.91599416E-02   2.40923841E-02   3.29020501E-02   3.67676983E-02   3.71050167E-02   4.15206933E-02   3.75711878E-02   1.36601477E-02   2.36332302E-02   4.91513201E-03   2.48690758E-02   1.22505322E-02\nCm  -2.81304127E-02  -3.40451608E-02  -5.10046427E-02  -8.51394051E-02  -2.22005177E-02  -5.28907590E-02  -1.82597297E-01  -5.57111027E-01  -8.70240643E-02  -3.43652198E-02  -5.11546198E-02  -4.13011726E-02  -3.70668447E-02  -5.01017093E-02  -8.01115127E-02  -1.13104633E-01  -7.77170860E-02  -1.09022840E-01  -1.67849887E-01  -3.36668719E-01  -7.26849396E-02  -3.77171813E-02  -1.15977923E-01  -7.11563649E-02  -5.46539010E-02  -7.25600074E-02  -1.11516936E-01  -1.48401633E-01  -1.15280384E-01  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3.46496049E-03   3.14328039E-03   3.88023994E-03   4.35920747E-03   3.11567158E-03  -1.54036251E-02  -1.06652326E-02   2.64994448E-02   5.45810760E-03   4.13460999E-02   5.27265271E-02   7.42277361E-02   8.67415062E-02   8.28256675E-02   9.80043313E-02   1.00175777E-01   5.32170571E-02   9.47276922E-02   8.66343180E-03   2.57265295E-02   1.03973174E-02  -4.08631052E-02  -5.00015896E-02  -6.44035115E-02  -6.60526730E-02  -7.28239324E-02  -7.23204257E-02  -5.07395977E-02  -8.42489650E-03  -6.57570021E-02  -1.69395388E-02  -2.46438347E-02  -1.41263117E-02  -5.07015856E-02  -6.12463947E-02  -7.67442934E-02  -7.56050327E-02  -8.62796004E-02  -8.06246716E-02  -4.97864283E-02  -5.59364116E-03  -6.33207575E-02  -3.03357313E-02  -3.59521945E-02  -3.26599558E-02\nCm   1.69577745E-02   3.48638619E-02   7.78814971E-02   1.19756242E-01   9.69105552E-02   1.46401832E-01   1.87246019E-01   1.25749430E-01   4.73026067E-02   4.33902245E-02   1.18148468E-01   1.57807303E-01   4.01967853E-02   5.15540001E-02   7.34791105E-02   8.74451791E-02   8.14688021E-02   9.84773285E-02   1.05536195E-01   6.50221632E-02   4.84298743E-02   4.88166740E-02   1.07771086E-01   9.58130421E-02   4.47535107E-02   5.71865615E-02   8.08573342E-02   9.50963669E-02   9.00336146E-02   1.07346400E-01   1.11584773E-01   6.24784066E-02   6.12706515E-02   4.90788711E-02   9.67409799E-02   8.80044726E-02  -4.31556475E-02  -5.11029515E-02  -6.13723391E-02  -5.68326350E-02  -6.78697299E-02  -5.74483301E-02  -2.88814792E-02  -1.73393576E-03  -4.04312716E-02  -1.96119191E-02  -2.98651559E-02  -2.02078269E-02  -4.78709612E-02  -5.29516865E-02  -5.50464177E-02  -4.13486541E-02  -5.44148484E-02  -3.16743899E-02  -7.40083206E-03  -4.36588465E-05  -2.08328812E-02  -3.03032285E-02  -3.42691164E-02  -2.94232061E-02\nCm   2.70390593E-02   3.06907784E-02   2.65609316E-02   2.77584404E-03   2.91638047E-02  -2.08287223E-03  -4.84471256E-02  -1.48397753E-01   6.73711294E-04  -1.74271884E-03   3.28280789E-02   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1.19392046E-01   2.57597476E-01   5.20030127E-01   7.06927274E-02  -9.14804508E-03   2.00097725E-01   1.08608940E-01   4.12884864E-02   5.55457368E-02   8.78946668E-02   1.22170365E-01   8.68947019E-02   1.20820119E-01   1.81275675E-01   3.32390546E-01   7.75275685E-02   6.90808695E-02   1.00897730E-01   1.38003223E-01   6.98480135E-02   9.13859577E-02   1.36022565E-01   1.72598121E-01   1.45896676E-01   1.88716432E-01   2.36061324E-01   2.37481692E-01   1.07567777E-01   9.57301803E-02   1.16069311E-01   1.80481957E-01  -6.33396953E-02  -7.95040014E-02  -1.08160166E-01  -1.20188963E-01  -1.22081566E-01  -1.35607568E-01  -1.20772334E-01  -4.17997911E-02  -9.46275940E-02  -4.34629428E-02  -3.91581834E-02  -4.11690446E-02  -7.17034873E-03  -8.94486481E-03  -1.20083738E-02  -1.30861684E-02  -1.35837634E-02  -1.47010522E-02  -1.23802030E-02  -3.60411685E-03  -1.49284001E-02   1.81012007E-02  -6.49359141E-03   2.22108540E-02\nCm  -2.39862512E-02  -4.89489293E-02  -9.53174671E-02  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2.50903637E-02   3.98663354E-02   2.45039629E-02  -4.47058785E-02  -5.54330612E-02  -7.34561750E-02  -7.85359716E-02  -8.31776371E-02  -8.76863788E-02  -6.98158519E-02  -1.70973626E-02  -5.41802643E-02  -5.91396441E-02  -7.90711077E-02  -8.51205723E-02\nCm   4.68261070E-02   6.15757154E-02   8.18437107E-02   9.62403213E-02   7.07428042E-02   9.09240762E-02   1.48494264E-01   2.14111443E-01   5.96334107E-02   7.68587212E-02   1.22601126E-01   1.22706830E-01   1.70504288E-02   2.27094110E-02   3.51492625E-02   4.72697568E-02   3.59823394E-02   4.89217738E-02   6.91221866E-02   1.03457105E-01   3.36005248E-02   4.58442582E-02   4.64765338E-02   7.25074280E-02  -1.24236052E-02  -1.63193661E-02  -2.45028420E-02  -3.14957898E-02  -2.60489440E-02  -3.41047945E-02  -4.39028947E-02  -4.84432131E-02  -5.41167540E-02   5.32270018E-03  -1.08628642E-02   1.18566993E-03   6.58605688E-02   8.56997744E-02   1.26048667E-01   1.57144034E-01   1.36678768E-01   1.73739738E-01   2.08682768E-01   1.84379429E-01   1.37112336E-01   5.63489311E-02   1.61730773E-01   1.24537808E-01  -4.91021307E-02  -6.12869687E-02  -8.23725566E-02  -8.99187909E-02  -9.31656333E-02  -1.01061457E-01  -8.55285935E-02  -2.52818816E-02  -5.88165487E-02  -1.71307864E-02  -3.45410152E-02  -2.32081469E-02\nCm  -6.79258694E-03  -6.22737152E-03  -1.46650468E-02  -4.07985592E-02  -7.97192906E-03  -5.21906399E-02  -1.18106162E-01  -1.50293390E-01  -3.46388635E-02  -2.10351186E-02  -4.79844012E-02  -9.34393707E-04  -6.92028526E-03  -9.25253415E-03  -1.44424799E-02  -1.96690832E-02  -1.46005703E-02  -2.00327407E-02  -2.89857883E-02  -4.69779874E-02  -2.63273110E-02  -4.70989012E-02  -4.10511152E-02  -8.92490454E-02  -2.09163713E-04  -2.71875725E-04  -3.98937371E-04  -4.95618835E-04  -4.33441926E-04  -5.49012464E-04  -6.54037131E-04  -5.62946944E-04  -9.17172506E-04  -4.76411245E-03   1.37775115E-03  -4.65137618E-03  -6.33476472E-02  -8.17249579E-02  -1.17977029E-01  -1.43071127E-01  -1.29769540E-01  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1.67102792E-01   1.33186287E-01   1.77607268E-01   2.39028692E-01   3.04746251E-01   2.27873065E-01   5.42158512E-02   1.53978090E-01   8.38473558E-02   4.17645047E-02   5.37351893E-02   7.71178425E-02   9.27144572E-02   8.51516934E-02   1.04123639E-01   1.14505095E-01   7.65126159E-02   1.01715112E-01   3.81946578E-02   1.00945411E-01   8.16492821E-02  -5.48289307E-02  -6.91477050E-02  -9.50355649E-02  -1.07199960E-01  -1.06998124E-01  -1.21186367E-01  -1.12565704E-01  -4.43858444E-02  -1.06814594E-01  -7.40262347E-02  -1.04707233E-01  -1.38058160E-01\nCm   4.30910318E-02   4.87066083E-02   7.09046626E-02   1.07042824E-01   6.16403273E-02   1.04063359E-01   1.89877796E-01   3.74611880E-01   1.26116302E-01   4.66597530E-02   4.20074874E-02   4.85751553E-02   5.11004478E-02   6.82264377E-02   1.06167573E-01   1.43923567E-01   1.07834615E-01   1.47473711E-01   2.11559626E-01   3.33139440E-01   1.64869506E-01   4.09618756E-02   1.23095798E-01   7.27020365E-02   1.52970707E-02   2.02090787E-02   3.07253478E-02   4.02356418E-02   3.22022449E-02   4.28597814E-02   5.74094799E-02   7.20701866E-02   3.58234278E-02   3.63811694E-03   1.15713735E-02  -5.47903135E-03  -5.67894973E-02  -7.15622325E-02  -9.81821947E-02  -1.10464929E-01  -1.10594363E-01  -1.24846994E-01  -1.15139241E-01  -4.44037799E-02  -7.79594246E-02  -2.04089693E-02  -5.48859470E-02  -4.05210485E-02   1.78281741E-02   2.24607944E-02   3.08009037E-02   3.46294546E-02   3.46992663E-02   3.91351717E-02   3.60204821E-02   1.38060306E-02   3.80792154E-02   2.57660441E-02   4.47701532E-04   1.16018926E-02\nCm   5.01835415E-03  -1.11432064E-02  -4.66091119E-02  -7.62615586E-02  -7.51401273E-02  -1.07277793E-01  -8.74836131E-02  -2.43735686E-03  -4.67239193E-02   2.36370019E-02  -7.55089081E-02  -1.04935590E-02   5.93260653E-02   7.67719874E-02   1.11568883E-01   1.36640943E-01   1.22141418E-01   1.52412238E-01   1.75460155E-01   1.35477175E-01   1.55238947E-01   1.67994997E-02   1.01872655E-01   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2.19009598E-02   2.79942844E-02   2.83920197E-02   3.16169475E-02   3.08811068E-02   2.09217396E-02   3.12109405E-03   1.95135477E-02   2.08735435E-02   3.58478263E-03   8.55641784E-03\nCm   3.25778922E-02   3.57749983E-02   4.72154098E-02   7.58457415E-02   2.06911710E-02   5.51764527E-02   1.73143415E-01   4.32825441E-01   7.81799185E-02   6.90112605E-02   8.40985293E-02   1.24766310E-01   1.19275103E-02   1.61218853E-02   2.57784160E-02   3.63947473E-02   2.50081502E-02   3.50817276E-02   5.40106969E-02   1.08329009E-01   4.13943730E-02   1.64790737E-02   2.21453460E-02   1.07779163E-02   5.17812955E-02   6.91550660E-02   1.07679860E-01   1.46109766E-01   1.09268051E-01   1.49533531E-01   2.14889319E-01   3.40368799E-01   2.13516282E-01   4.06052729E-02   2.27280950E-01   1.44934335E-01   2.17651966E-02   2.71065983E-02   3.62605854E-02   3.93086385E-02   4.10335884E-02   4.40930761E-02   3.65694905E-02   1.01561151E-02   1.10105531E-02   5.29651056E-02   5.45333027E-02   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1.00799632E-02   2.81272538E-02   1.46356566E-02  -6.39105862E-02  -8.03813505E-02  -1.09826550E-01  -1.22816802E-01  -1.23841739E-01  -1.38706921E-01  -1.25762592E-01  -4.60072787E-02  -7.69676770E-02  -3.69223317E-02  -1.27458389E-01  -1.24104579E-01\nCm  -1.58332265E-03  -3.63302224E-03  -9.65458569E-03  -2.13009188E-02  -8.03721616E-03  -2.42921579E-02  -4.72219769E-02  -8.77384404E-02  -5.77086365E-02  -2.16338799E-02   6.72936913E-02   4.99995628E-02  -4.26802929E-03  -5.73482691E-03  -9.05028949E-03  -1.25290109E-02  -8.98870739E-03  -1.24671601E-02  -1.85761449E-02  -3.32598837E-02  -3.14292795E-02   1.75078905E-02   3.07356474E-02   5.27447654E-02  -3.88862884E-02  -5.08120280E-02  -7.54198144E-02  -9.53043555E-02  -8.11118744E-02  -1.04499144E-01  -1.29495568E-01  -1.26414171E-01  -8.11121310E-02  -2.94950328E-02  -5.83420034E-02  -3.68452762E-02   3.10620226E-02   4.01902934E-02   5.83872998E-02   7.14734214E-02   6.39357730E-02   7.97397310E-02   9.16894341E-02   7.05308184E-02   4.80052566E-02   1.84564985E-02   6.89508119E-02   5.34696735E-02   2.96826005E-02   3.54780956E-02   4.34621615E-02   4.14285320E-02   4.84881095E-02   4.30177257E-02   2.38402138E-02   1.92561112E-03   1.97278175E-02   5.12289493E-02   7.44957951E-02   1.07660030E-01\nCm  -7.23162466E-02  -8.44613233E-02  -1.02862556E-01  -1.12937598E-01  -1.01312506E-01  -1.24490254E-01  -1.42665975E-01  -8.96190759E-02  -5.68441379E-02  -1.05747029E-01  -1.62922321E-01  -1.70815509E-01  -3.10620226E-02  -4.01902934E-02  -5.83872998E-02  -7.14734214E-02  -6.39357730E-02  -7.97397310E-02  -9.16894341E-02  -7.05308184E-02  -8.12693595E-02  -4.68753257E-02  -7.51036311E-02  -9.34128512E-02  -6.77339108E-02  -8.44133289E-02  -1.13083602E-01  -1.22850054E-01  -1.27949990E-01  -1.37889164E-01  -1.15072746E-01  -3.25755989E-02  -1.14138023E-01  -9.48590133E-02  -1.63767071E-01  -1.90016211E-01   4.74114509E-02   5.87493593E-02   7.77413305E-02   8.29463446E-02   8.80338952E-02   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5.82633263E-02   5.53777340E-02   5.56162583E-02   5.51526852E-02   7.27581040E-02   1.10271890E-01   1.43729837E-01   1.16006265E-01   1.53779902E-01   2.03972191E-01   2.47997273E-01   1.97823921E-01   4.66167172E-02   1.20474968E-01   6.93153863E-02   2.41504185E-02   3.16915756E-02   4.74790967E-02   6.08305329E-02   5.05922344E-02   6.60394562E-02   8.44054015E-02   9.10055074E-02   3.66001806E-02   2.39621729E-02   5.91566641E-02   4.02789026E-02   1.22821735E-02   1.57111925E-02   2.22662048E-02   2.62774053E-02   2.47636472E-02   2.96447853E-02   3.10918625E-02   1.79030485E-02   1.54773602E-02   1.50780314E-02   1.17368971E-02   1.07181995E-02  -6.46378554E-02  -8.06841861E-02  -1.08461419E-01  -1.18426672E-01  -1.22670219E-01  -1.33110625E-01  -1.12731871E-01  -3.33961588E-02  -5.05467542E-02  -3.24116626E-02  -8.59943828E-02  -5.84797199E-02\nCm  -8.32253047E-04   1.95275264E-02   6.36908481E-02   9.79717613E-02   9.03050742E-02   1.16762014E-01   1.26260143E-01   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6.54039944E-02   5.40885854E-02   5.49046490E-02   3.73401452E-02   6.20532695E-02   1.11299650E-01   1.44131487E-01   5.01983770E-03   6.72457443E-03   1.05413378E-02   1.44477395E-02   1.05857461E-02   1.45874013E-02   2.13532502E-02   3.59911474E-02  -1.59011581E-02   1.66153760E-02   5.14504418E-02   3.77560062E-02   2.49149670E-02   3.16315387E-02   4.41035158E-02   5.08124500E-02   4.94154968E-02   5.74740446E-02   5.65669374E-02   2.67043166E-02   1.44903847E-02   4.01174489E-02   5.69099994E-02   6.08018857E-02  -2.14788227E-02  -2.66095053E-02  -3.51953051E-02  -3.75262840E-02  -3.98554743E-02  -4.18552941E-02  -3.30545575E-02  -7.89413701E-03  -4.16506723E-02  -7.37491256E-03  -1.54375049E-02  -1.17131734E-02  -1.45162514E-02  -1.65895853E-02  -1.84767788E-02  -1.53354290E-02  -1.94578124E-02  -1.36348522E-02  -4.64863617E-03  -8.59129160E-05  -1.97115631E-02   1.16696676E-03  -8.55251761E-03  -4.00385877E-03\nCm  -2.05738523E-02  -3.32683310E-02  -6.36027635E-02  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3.64538792E-02\nCm   3.92060677E-02   4.33185439E-02   3.96547549E-02   1.72213926E-02   4.37648495E-02   2.04635700E-02  -1.92991983E-02  -1.70844692E-01  -1.81053243E-02   3.00067426E-02   8.71277087E-02   5.81803930E-02  -3.69397906E-02  -5.00592666E-02  -8.05044900E-02  -1.14641768E-01  -7.72339869E-02  -1.08820103E-01  -1.69804404E-01  -3.57198914E-01  -1.17703345E-01   1.20300346E-02  -7.33237693E-02  -1.18203007E-02   6.25779980E-02   8.20349908E-02   1.22628711E-01   1.56595217E-01   1.30969440E-01   1.70432887E-01   2.16246540E-01   2.27733673E-01   1.57140547E-01   4.04463225E-02   1.21280475E-01   9.18201052E-02  -2.00050653E-02  -2.56995496E-02  -3.67600942E-02  -4.39780235E-02  -4.06724625E-02  -4.94598947E-02  -5.37208690E-02  -3.45227304E-02  -6.61073456E-02   1.05493332E-02  -6.70231795E-03   1.41751327E-02  -1.19881508E-02  -1.50049419E-02  -2.02890578E-02  -2.23442515E-02  -2.29270006E-02  -2.51668127E-02  -2.18480981E-02  -6.98688502E-03  -3.31600201E-02  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1.31332885E-01   1.09650751E-01   1.42827702E-01   1.81634126E-01   1.92691175E-01   1.50296519E-01   3.16512994E-02   1.66505468E-01   7.28811524E-02   1.77221538E-02   2.28910470E-02   3.31321087E-02   4.03356829E-02   3.63777834E-02   4.51022027E-02   5.11695528E-02   3.77247964E-02   2.16419699E-02   4.85307842E-03   5.50490173E-02   1.53758058E-02  -5.39123064E-02  -6.67638467E-02  -8.82303657E-02  -9.39560758E-02  -9.99147460E-02  -1.04743997E-01  -8.24113127E-02  -1.94564558E-02  -7.87475349E-02  -1.13794509E-02  -3.38915898E-02  -2.78814575E-02   1.39690726E-02   1.56791944E-02   1.68101073E-02   1.32031414E-02   1.71283884E-02   1.08480652E-02   3.00899955E-03   2.97973482E-05   7.83663346E-03   6.74190152E-03   1.23156653E-02   7.57147134E-03\nCm  -9.15881676E-03  -1.44253824E-02  -2.69251801E-02  -3.66528679E-02  -3.58261616E-02  -4.72089398E-02  -4.62868281E-02   5.52801474E-03  -2.38418281E-02  -2.81106662E-02  -4.25717398E-02  -3.90242192E-02   7.58727897E-03   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9.58930592E-02   1.07911072E-02   1.43305944E-02   2.20381913E-02   2.93544037E-02   2.27630491E-02   3.07214244E-02   4.25991543E-02   5.99109213E-02   2.75168644E-02   1.80932942E-02   2.23487614E-02   2.18774503E-02   5.44905175E-02   7.18398064E-02   1.08731635E-01   1.41435096E-01   1.14567855E-01   1.51605028E-01   2.00226147E-01   2.40066265E-01   1.52109697E-01   3.36396717E-02   1.60174469E-01   7.75152790E-02   2.92515667E-03   3.72058354E-03   5.20832001E-03   6.03598101E-03   5.82617848E-03   6.82517406E-03   6.82421270E-03   3.38396234E-03   1.47769056E-02   1.10794508E-03  -5.96361133E-03  -3.36936158E-04  -6.31933304E-02  -7.52666052E-02  -9.15165085E-02  -8.62870960E-02  -1.01783275E-01  -8.87261172E-02  -4.74086895E-02  -3.42622058E-03  -9.16580233E-02  -2.70762864E-02  -3.31932412E-02  -2.14406242E-02\nCm   4.82580150E-02   4.46266299E-02   3.87659774E-02   3.65446567E-02   2.24547820E-02   2.51857027E-02   5.51786917E-02   1.38020136E-01   5.62253647E-02   6.51327900E-02   1.23997106E-02   3.97045065E-02   5.08820914E-04   6.79095460E-04   1.05587571E-03   1.42961777E-03   1.07377268E-03   1.46718846E-03   2.09991798E-03   3.28125661E-03  -5.46821344E-03  -7.99403893E-03   5.05897083E-03  -1.04401991E-02   7.27693901E-02   9.66303348E-02   1.48577043E-01   1.97851588E-01   1.53498840E-01   2.07123711E-01   2.87059571E-01   4.03050069E-01   2.00111348E-01   3.72646803E-02   9.67259237E-02   4.84854127E-02  -5.27445842E-02  -6.97261413E-02  -1.06159518E-01  -1.39310763E-01  -1.11071394E-01  -1.48094174E-01  -1.99235303E-01  -2.53704585E-01  -8.58462022E-02  -2.14257913E-02  -2.85128643E-02  -2.78902071E-02  -1.63354773E-02  -2.06497492E-02  -2.85241906E-02  -3.24147813E-02  -3.20658597E-02  -3.66619257E-02  -3.47590290E-02  -1.46066043E-02  -4.10867493E-02   6.77474461E-03  -1.78149231E-02  -6.02860877E-04\nCm  -4.60490068E-03  -1.04199485E-02  -3.28859546E-02  -6.14604886E-02  -5.26687261E-02  -9.36704937E-02  -8.77576334E-02  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6.20630026E-02   8.83276941E-02   1.04888610E-01   9.80127086E-02   1.18180432E-01   1.25950585E-01   7.62593696E-02   5.15734250E-02   3.70250006E-02   6.27269662E-02   4.88179926E-02  -3.26476668E-02  -4.18254044E-02  -5.94695316E-02  -7.05214823E-02  -6.60246375E-02  -7.94824207E-02  -8.44056823E-02  -5.05345906E-02  -4.65947024E-02   4.46570634E-03  -2.40925782E-02  -1.90918537E-03  -5.17673043E-02  -6.26969540E-02  -7.90004847E-02  -7.84629189E-02  -8.89489074E-02  -8.41663315E-02  -5.33523434E-02  -6.49357800E-03  -6.76886551E-02  -2.53981697E-02  -6.59958342E-02  -4.11007811E-02\nCm   5.06865395E-02   7.79040501E-02   1.28363648E-01   1.59316136E-01   1.43287375E-01   1.57261795E-01   1.86226667E-01   2.78606499E-01   1.43119082E-01   5.19643509E-02   2.81083149E-01   2.69210398E-01   8.35943468E-03   1.11344898E-02   1.72357805E-02   2.31831832E-02   1.76413692E-02   2.39883949E-02   3.39047717E-02   5.08023926E-02  -6.73820451E-03   5.67538010E-02   8.41776024E-02   1.05352552E-01   6.98952024E-02   9.19543568E-02   1.38531970E-01   1.78961928E-01   1.46734754E-01   1.92988591E-01   2.51151487E-01   2.87055103E-01   8.43373911E-02   9.13725737E-02   2.54737049E-01   2.19332798E-01   1.60262176E-02   2.10769969E-02   3.17295674E-02   4.09445566E-02   3.36358061E-02   4.41946172E-02   5.73770603E-02   6.50751977E-02   3.60187595E-02   5.42290702E-02   2.05075837E-02   5.11493102E-02  -5.77298589E-02  -7.45918387E-02  -1.08039518E-01  -1.31667355E-01  -1.18563878E-01  -1.47165818E-01  -1.67393190E-01  -1.24418199E-01  -1.07991289E-01  -1.66771707E-02  -9.67818595E-02  -4.46418646E-02\nCm   2.85922378E-02   2.66982785E-02   2.53641322E-02   2.02670877E-02   3.00976685E-02   2.06482615E-02  -4.44883640E-03  -1.85252076E-02   1.00002474E-02   5.92511937E-02   4.24933600E-02   6.91174156E-02  -1.26941406E-02  -1.63716955E-02  -2.36181353E-02  -2.86134652E-02  -2.59906735E-02  -3.20530731E-02  -3.59304860E-02  -2.55030024E-02  -3.40355117E-02  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2.32667131E-03\nCm   5.69714067E-02   7.36084778E-02   8.03725528E-02   5.34069511E-02   7.67828658E-02   3.76188906E-02  -4.48649716E-03  -4.36717297E-02   4.52728192E-02   4.11441547E-02   6.74583591E-02   8.01350615E-02  -5.42333671E-03  -7.03585696E-03  -1.02810132E-02  -1.26938155E-02  -1.12081759E-02  -1.41060855E-02  -1.65593695E-02  -1.36024550E-02  -1.50940968E-02   1.96489761E-02  -1.33205621E-02  -3.84445660E-03  -4.97761698E-02  -6.41338350E-02  -9.23244920E-02  -1.11501131E-01  -1.01742148E-01  -1.25040396E-01  -1.39077417E-01  -9.63164968E-02  -1.25202768E-01  -1.06412196E-02  -3.46166203E-02  -1.52437867E-02   5.69942252E-02   7.24675464E-02   1.01369539E-01   1.17349804E-01   1.13430193E-01   1.32702881E-01   1.32296703E-01   6.50068633E-02   3.22860147E-02   4.23417496E-02   9.10736922E-02   7.30494429E-02   3.02123702E-02   3.57971405E-02   4.30445366E-02   3.99331624E-02   4.76305388E-02   4.04378217E-02   2.04560622E-02   1.25148463E-03   3.42967802E-02   3.72829340E-02   3.83235143E-02   3.54896137E-02\nCm   6.79789433E-03  -4.45657235E-03  -3.02829425E-02  -5.85309635E-02  -3.24577850E-02  -5.98639782E-02  -1.20762865E-01  -1.79417142E-01  -1.38195720E-02  -3.33325527E-03  -4.10700201E-02  -5.67342605E-02  -3.51600768E-02  -4.64566692E-02  -7.06528945E-02  -9.25634997E-02  -7.40218601E-02  -9.85575934E-02  -1.32139108E-01  -1.66392767E-01  -3.96185463E-02  -1.52437377E-02  -8.38940508E-02  -5.52021475E-02  -3.71205130E-03  -4.86972294E-03  -7.29089889E-03  -9.33215731E-03  -7.77419897E-03  -1.01388085E-02  -1.29309595E-02  -1.38468859E-02  -3.68672487E-02  -2.77522412E-03   1.06904225E-02   5.19917123E-03   5.54596915E-02   6.44476336E-02   7.43630769E-02   6.49703815E-02   8.03604020E-02   6.16520745E-02   2.53086734E-02   8.21007069E-04   5.32745803E-02   1.48485514E-02   2.06224537E-02   1.02823461E-02   2.78163967E-03   3.06707235E-03   3.16704530E-03   2.35596477E-03   3.10886324E-03   1.77618170E-03   3.99585977E-04   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1.10736304E-01   1.39632469E-01   1.44137783E-01   1.04627974E-01   2.52240211E-02   3.89465033E-02   2.97356288E-02   3.70664647E-02   4.73240262E-02   6.67903684E-02   7.83409407E-02   7.44373555E-02   8.84691361E-02   9.13169415E-02   5.00156727E-02   6.87700159E-02   1.80065393E-02   4.07197158E-02   2.71587262E-02  -4.88073429E-02  -6.11630813E-02  -8.29165034E-02  -9.16633244E-02  -9.36540989E-02  -1.03324148E-01  -9.06793440E-02  -2.99901944E-02  -8.00974281E-02  -1.77926062E-02  -3.61124201E-02  -2.29815191E-02\nCm   9.27553373E-03   4.27833320E-03   6.79675578E-03   3.37320826E-02  -4.46471514E-03   4.69823036E-02   1.14912546E-01   1.82269885E-01   3.07511345E-02   4.10858289E-02  -6.11170679E-03  -1.23141310E-02   6.36759099E-02   8.38849082E-02   1.26747556E-01   1.64455623E-01   1.33810338E-01   1.76677126E-01   2.32093158E-01   2.73474694E-01   1.62058333E-01   3.38226047E-02   1.07273855E-01   5.40229664E-02  -2.55869706E-02  -3.32641444E-02  -4.88281803E-02  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8.28506637E-02   1.14241277E-01   1.29484544E-01   1.28497445E-01   1.46430183E-01   1.37834523E-01   5.66407984E-02   7.09570250E-02   7.85817777E-02   1.34913705E-01   1.41255799E-01  -7.10555828E-03  -8.71069564E-03  -1.12641004E-02  -1.16195812E-02  -1.27429700E-02  -1.27630126E-02  -9.11657171E-03  -1.59934062E-03  -6.51944097E-03   8.63539585E-03  -1.60204055E-02  -6.87841360E-03  -2.42838462E-02  -2.87106565E-02  -3.43650826E-02  -3.16685564E-02  -3.79401922E-02  -3.18574336E-02  -1.57519290E-02  -8.99064692E-04  -3.22147816E-02  -1.44668534E-03  -1.13047623E-02  -8.03170470E-03\nCm   1.53204614E-02   1.49664807E-02   1.42627489E-02   9.69678285E-03   2.33473468E-02   3.25193938E-02   3.23728157E-03  -1.84984905E-01   2.35484810E-02   1.58423637E-02   1.77239537E-02  -2.06168732E-02  -6.93483003E-02  -9.26503323E-02  -1.44381083E-01  -1.96146925E-01  -1.46330724E-01  -2.00426167E-01  -2.88677579E-01  -4.60728468E-01  -1.48647872E-01  -4.06910455E-02  -2.57359150E-01  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1.94484494E-02   1.47479712E-02   3.33729571E-02   1.23072524E-02   1.59070545E-02   2.30558293E-02   2.81267263E-02   2.52893124E-02   3.14246263E-02   3.58332296E-02   2.68449722E-02   3.09756927E-02   3.00439600E-03   1.17017867E-02  -1.40580062E-03  -3.75049958E-02  -4.73914894E-02  -6.54076073E-02  -7.42356947E-02  -7.35487488E-02  -8.39573045E-02  -7.93251526E-02  -3.29785210E-02  -7.82802387E-02  -1.18053414E-02  -4.11797704E-02  -1.86089850E-02   1.82615093E-02   2.28521462E-02   3.08856646E-02   3.39915318E-02   3.49040116E-02   3.82797640E-02   3.31682416E-02   1.05443417E-02   1.77324981E-02   1.39762351E-02   5.20172490E-02   4.25409944E-02   2.81148109E-02   3.22077099E-02   3.60545358E-02   3.01462316E-02   3.81214156E-02   2.70690483E-02   9.48208635E-03   1.90206321E-04   1.75894181E-02   8.83011526E-03   1.92329339E-02   1.31485638E-02\nCm   2.72402893E-02   4.30052464E-02   8.32416084E-02   1.22251536E-01   9.50675705E-02   1.29795748E-01   1.78686311E-01   2.59812597E-01   1.18817181E-01   2.68245693E-02   2.16030552E-01   2.02148477E-01   6.62360648E-02   8.78488983E-02   1.34717949E-01   1.78690856E-01   1.39670497E-01   1.87874838E-01   2.58340068E-01   3.53430559E-01   1.66922290E-01   9.13685658E-02   3.08610086E-01   2.82517486E-01  -2.19739989E-02  -2.89515018E-02  -4.37566079E-02  -5.67971181E-02  -4.61807178E-02  -6.09964465E-02  -8.01967907E-02  -9.47577645E-02  -4.43402251E-02   1.80026039E-02  -6.12312693E-02  -7.03506413E-03  -7.78974932E-04  -1.02053228E-03  -1.52342315E-03  -1.94141281E-03  -1.62931550E-03  -2.11617551E-03  -2.67280667E-03  -2.77378698E-03  -9.25126707E-03  -5.47021278E-03  -8.96174977E-03  -3.15390644E-02   3.92975578E-02   4.83659148E-02   6.30764514E-02   6.58799396E-02   7.14098248E-02   7.28244781E-02   5.40400567E-02   1.06572901E-02   3.76696517E-02   8.43527372E-02   1.28654165E-01   1.91615829E-01\nCm   5.47975870E-02   6.21770602E-02   5.51382309E-02   2.22117862E-02   4.08971876E-02  -1.38401437E-02  -4.55465996E-02   6.36189564E-02  -1.91594082E-02   7.34252668E-02   8.63412868E-02   1.11681478E-01   2.15170563E-02   2.88313422E-02   4.52201207E-02   6.20280697E-02   4.53711163E-02   6.25563009E-02   9.17047793E-02   1.55337102E-01   6.58062748E-02   3.05493626E-02   7.21531427E-02   6.96938513E-02   3.68972829E-04   4.86139667E-04   7.34757198E-04   9.53765736E-04   7.75441785E-04   1.02425119E-03   1.34676367E-03   1.59167589E-03  -6.06553556E-03   1.34923685E-02   5.32630200E-03   8.66751435E-03  -6.73498081E-02  -8.60606636E-02  -1.21683942E-01  -1.43114097E-01  -1.35493032E-01  -1.61549353E-01  -1.67932507E-01  -9.40367605E-02  -1.46981348E-01  -3.13878231E-02  -4.15514750E-02  -3.23148428E-02   5.83776231E-02   6.73905629E-02   7.66741795E-02   6.56372032E-02   8.20599301E-02   6.07548708E-02   2.31834945E-02   6.02669716E-04   3.54123844E-02   7.47350594E-02   7.70966471E-02   1.05884016E-01\nCm   3.00668819E-03   9.15459075E-03   1.70448064E-02   1.72081207E-02   2.38795274E-02   1.66003134E-02   8.53344623E-04  -6.93317744E-04   2.29858927E-03  -1.37099888E-02   1.33527182E-02   1.41165324E-02  -1.92214199E-02  -2.27915758E-02  -2.74496259E-02  -2.55246732E-02  -3.03973710E-02  -2.59056248E-02  -1.32085719E-02  -8.27727054E-04  -8.02999639E-03   1.47263012E-03  -2.03149287E-02  -1.12092114E-02  -3.91424714E-03  -4.63158919E-03  -5.55343805E-03  -5.13068805E-03  -6.13653290E-03  -5.17436064E-03  -2.58076580E-03  -1.51240486E-04  -1.10510329E-03  -6.52416250E-03  -9.43926981E-03  -6.01154577E-03   4.04467496E-02   4.62570132E-02   5.15977389E-02   4.29200919E-02   5.44032516E-02   3.82743115E-02   1.31556475E-02   2.49189421E-04   2.42480018E-02   2.71048864E-02   6.46643725E-02   5.83976231E-02   6.63579690E-03   7.53555964E-03   8.28074842E-03   6.74031566E-03   8.62459886E-03   5.83411990E-03   1.85076474E-03   2.75027874E-05   9.40442920E-03  -6.29025331E-04   4.75406219E-03   3.53864491E-03\nCm   4.02505935E-02   3.10638388E-02  -3.36730605E-03  -6.79898130E-02   7.46599542E-03  -5.14366410E-02  -1.64659985E-01  -5.90801696E-01  -9.56603428E-02   1.66498011E-02  -6.09065376E-03   2.84615793E-02  -7.02898814E-02  -9.60750497E-02  -1.57488804E-01  -2.30805743E-01  -1.45007475E-01  -2.06713071E-01  -3.35897083E-01  -8.20048612E-01  -2.82707676E-01  -2.68095015E-02  -2.06497214E-01  -8.23200524E-02   2.53414702E-02   3.41079601E-02   5.40274998E-02   7.52120354E-02   5.33171524E-02   7.42020291E-02   1.11623426E-01   2.06533455E-01   5.39014507E-02   1.54747678E-02   1.10942544E-01   6.59550625E-02  -2.87432248E-03  -3.70493349E-03  -5.33825450E-03  -6.45559835E-03  -5.87932025E-03  -7.23622473E-03  -8.07513551E-03  -5.65077583E-03  -8.34449774E-03  -6.32390185E-03   1.41467006E-02  -1.23600578E-03   3.00169582E-02   3.79941894E-02   5.26309337E-02   6.00583975E-02   5.91106287E-02   6.79368366E-02   6.51475647E-02   2.83622886E-02   4.66489044E-02  -6.88637876E-03   5.51123885E-02   1.68416191E-02\nCm  -2.72596881E-02  -3.84789420E-02  -6.45983277E-02  -9.45668969E-02  -5.96460890E-02  -8.24697856E-02  -1.42508698E-01  -3.47417184E-01  -5.92387620E-02  -2.19837702E-02  -8.37287826E-02  -8.45360613E-02  -4.20543159E-02  -5.69805881E-02  -9.16007074E-02  -1.30369522E-01  -8.79451054E-02  -1.23877559E-01  -1.93133074E-01  -4.05020585E-01  -1.50704729E-01  -4.57876420E-02  -1.36740726E-01  -1.16763262E-01   1.07370792E-02   1.42362336E-02   2.18168701E-02   2.89091237E-02   2.26387891E-02   3.04275888E-02   4.17557477E-02   5.67479566E-02   3.63791833E-02   1.25922479E-02   1.89651607E-02   2.14847125E-02   5.12484914E-02   6.05931957E-02   7.25328178E-02   6.68495424E-02   8.00820240E-02   6.72564597E-02   3.32688901E-02   1.90128405E-03   4.73605304E-02   3.59382192E-02   7.29705731E-02   7.11825911E-02  -4.92522699E-02  -5.76301132E-02  -6.74767573E-02  -6.02206556E-02  -7.35947699E-02  -5.85598249E-02  -2.59131940E-02  -1.05565133E-03  -1.99123363E-02  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7.73003812E-02   2.09131340E-01   2.40415245E-01   1.73370561E-02   2.24802883E-02   3.28120543E-02   4.04453482E-02   3.58026779E-02   4.49813615E-02   5.25948491E-02   4.26614192E-02   1.97181545E-02   6.69418765E-03   5.77026055E-03  -4.68639978E-03   5.08759919E-02   6.56058404E-02   9.46155480E-02   1.14575671E-01   1.04141318E-01   1.28369230E-01   1.43737771E-01   1.01665490E-01   9.87787248E-02   8.47774737E-02   1.77484626E-01   2.21882313E-01\nCm   2.74611131E-02   1.88418237E-02  -7.32291189E-03  -4.13546782E-02  -2.16329677E-02  -6.18902010E-02  -9.39650441E-02  -8.56522778E-02  -4.17438882E-02   5.73934156E-02  -7.65463689E-03   6.64511974E-02  -7.29892225E-02  -9.44593350E-02  -1.37292893E-01  -1.68181722E-01  -1.50286983E-01  -1.87576089E-01  -2.16053800E-01  -1.67095396E-01  -1.30650328E-01  -6.89564737E-02  -1.29488654E-01  -1.41913299E-01   5.81832666E-02   7.45153846E-02   1.05875765E-01   1.25422474E-01   1.17590850E-01   1.41390315E-01   1.49749706E-01   8.89124193E-02   1.23211912E-01   4.72926448E-02   2.14842681E-01   1.54321248E-01   1.85183841E-02   2.30339137E-02   3.07291113E-02   3.31799669E-02   3.47823328E-02   3.71724701E-02   3.04724707E-02   8.16402448E-03   1.63194006E-02   3.04388585E-02   4.25702512E-02   4.94218304E-02  -4.23177194E-02  -5.24517343E-02  -6.94482732E-02  -7.41612808E-02  -7.86415216E-02  -8.27646459E-02  -6.56608726E-02  -1.59029628E-02  -7.33864301E-02  -6.86006061E-02  -1.14534321E-01  -1.61799965E-01\nCm  -5.56584581E-03   1.09492412E-02   5.18472471E-02   1.07488939E-01   5.42269033E-02   1.25675402E-01   2.23002752E-01   3.33440859E-01   1.05950655E-01  -1.33340268E-02   5.42133125E-02   2.03329183E-02   4.89549872E-02   6.49738046E-02   9.97896694E-02   1.32660715E-01   1.03251284E-01   1.39136767E-01   1.92188815E-01   2.66876170E-01   5.82483662E-02   2.66587398E-02   4.76832933E-02   4.07934794E-02   3.74408380E-02   4.86876483E-02   7.15097326E-02   8.89648173E-02   7.76330843E-02   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3.60958596E-02   4.98427076E-02   3.59019232E-02   2.66479567E-02   3.02276613E-02   3.31390253E-02   2.68827855E-02   3.44462892E-02   2.31571228E-02   7.25372438E-03   1.03741468E-04   1.26397036E-02   4.12109487E-02   4.17701349E-02   5.70129470E-02\nCm   5.69152280E-02   5.86030029E-02   5.65981156E-02   5.16044071E-02   4.63803944E-02   4.97875553E-02   5.60514766E-02   6.43813251E-02   5.63686835E-02   3.90533535E-02   3.84571994E-02   4.50158154E-03   4.29422987E-02   5.68630482E-02   8.68938139E-02   1.14653666E-01   9.04987544E-02   1.21214638E-01   1.64916678E-01   2.17877604E-01   6.64391152E-02   3.64004350E-02   4.08483570E-02   3.69446832E-02  -6.20510089E-02  -8.11646403E-02  -1.20743525E-01  -1.53088021E-01  -1.29576500E-01  -1.67477569E-01  -2.09115840E-01  -2.09157232E-01  -1.84892115E-01  -1.05975149E-02  -8.98926173E-02  -3.21611412E-02  -4.63470799E-03  -5.97014863E-03  -8.58996250E-03  -1.03662893E-02  -9.46936841E-03  -1.16279830E-02  -1.29088235E-02  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3.05919348E-02  -9.40983822E-03   2.45745479E-02   4.01959096E-02   5.08519187E-02   7.03631646E-02   8.01609929E-02   7.90557676E-02   9.06726468E-02   8.65592563E-02   3.71598969E-02   5.48374850E-02   2.29408280E-02   8.02539168E-02   6.78145691E-02  -2.11697008E-02  -2.55354561E-02  -3.18980291E-02  -3.12827384E-02  -3.58289870E-02  -3.32466685E-02  -2.02315063E-02  -2.17360113E-03  -1.28549505E-02  -5.85423950E-03  -1.97999561E-02  -9.61182118E-03   4.03119818E-02   4.63134072E-02   5.21614298E-02   4.40002863E-02   5.54097608E-02   3.99693682E-02   1.44594725E-02   3.19779468E-04   2.76659646E-02   2.53673601E-02   3.09409042E-02   3.22624242E-02\nCm  -8.05444532E-03  -7.03170647E-03  -2.54984678E-02  -7.59307551E-02  -1.37938798E-02  -8.53014123E-02  -2.08487619E-01  -3.69221952E-01  -5.82101968E-02  -3.92361165E-02  -4.28855516E-02  -8.53082153E-03  -2.70536654E-02  -3.60765138E-02  -5.59882848E-02  -7.55957138E-02  -5.70940098E-02  -7.78550481E-02  -1.10845632E-01  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9.83705167E-02   1.52049907E-01   2.04068133E-01   1.55953617E-01   2.11712836E-01   2.97965086E-01   4.40215063E-01   2.67370003E-01   5.07604658E-02   1.53719875E-01   1.12142650E-01  -3.76280038E-02  -4.83101525E-02  -6.90127287E-02  -8.24064480E-02  -7.64161633E-02  -9.27253782E-02  -1.00227789E-01  -6.34377473E-02  -8.02213475E-02  -4.75576230E-02  -8.16985969E-02  -9.49051227E-02   4.62082888E-03   5.88375116E-03   8.25586957E-03   9.60104511E-03   9.22590049E-03   1.08532998E-02   1.09524090E-02   5.58980446E-03   2.82392852E-03   3.61100948E-02   1.20058503E-02   5.04307350E-02  -6.63543845E-02  -8.36777129E-02  -1.14989499E-01  -1.29681614E-01  -1.29468807E-01  -1.46598594E-01  -1.36093391E-01  -5.35691420E-02  -1.51430999E-01  -6.39460318E-02  -7.18244780E-02  -9.70505868E-02\nCm   3.10998206E-03  -1.93400539E-03  -2.16924777E-02  -5.16134485E-02  -3.43046636E-02  -7.99605413E-02  -9.93064325E-02  -4.62047365E-02  -3.24034013E-02   1.44558966E-02  -5.33136178E-03   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5.41954581E-02   6.36682440E-02   5.24229128E-02   5.36599318E-02   9.55208929E-03   2.85871774E-02   1.49186767E-02  -6.71393951E-03  -8.54015682E-03  -1.19566561E-02  -1.38593969E-02  -1.33743192E-02  -1.56712690E-02  -1.56771923E-02  -7.78653520E-03  -1.74060922E-02  -6.26628818E-03  -4.68343959E-04  -2.56267962E-03\nCm  -2.19011393E-03   7.60252312E-04   2.25056114E-03  -6.22523907E-03   1.54831364E-02   1.21501740E-02  -2.09159211E-02  -2.13313310E-01  -8.24243228E-05   1.46755234E-02   1.15409765E-02   1.46740567E-02  -3.13843267E-02  -4.27037782E-02  -6.92985807E-02  -1.00030932E-01  -6.52572883E-02  -9.25076319E-02  -1.47264008E-01  -3.32993800E-01  -9.67491428E-02  -1.44438226E-02  -5.78131369E-02  -3.00284410E-02   2.41835194E-02   3.17418935E-02   4.75770311E-02   6.09989115E-02   5.06714472E-02   6.61859568E-02   8.47238383E-02   9.18066620E-02   7.77406258E-02   2.10652364E-02   3.40291145E-02   2.49939611E-02   6.39489131E-02   8.17438964E-02   1.15669030E-01   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1.25586374E-02   2.15935991E-02   3.33660099E-03   5.68078309E-02   7.32108680E-02   1.05444987E-01   1.27442496E-01   1.16162260E-01   1.42881205E-01   1.59218499E-01   1.10917090E-01   8.15286970E-02   2.86594369E-02   4.81977204E-02   2.87836090E-02  -6.49191187E-02  -8.11754030E-02  -1.09528174E-01  -1.20245817E-01  -1.23811437E-01  -1.35339347E-01  -1.16440242E-01  -3.62157996E-02  -8.82598781E-02  -4.37576485E-02  -9.15635878E-02  -7.55795631E-02  -1.86590553E-02  -2.24801800E-02  -2.80099704E-02  -2.73676509E-02  -3.14372921E-02  -2.90028414E-02  -1.74367123E-02  -1.80538432E-03  -3.05819577E-02  -3.67131504E-02  -3.22053361E-02  -4.48446245E-02\nCm  -2.54651038E-04   5.74880644E-03   2.37462997E-02   4.63707196E-02   3.03405484E-02   5.95182640E-02   8.75311193E-02   8.21375845E-02   4.93223083E-02   1.20585761E-02   1.34337046E-03  -1.69355241E-02   6.91157448E-02   8.93078739E-02   1.29368568E-01   1.57686584E-01   1.41959570E-01   1.76236346E-01   2.00539137E-01   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5.16249652E-02   1.05056174E-01   7.70593598E-02   1.21529343E-01   1.50618732E-01\nCm   5.43407783E-03  -8.50780075E-03  -4.48483647E-02  -8.63370553E-02  -6.20079801E-02  -1.09271875E-01  -1.46930872E-01  -1.51891768E-01  -8.96773338E-02   1.55660097E-02  -6.08131314E-02  -8.54045721E-03  -7.30166507E-02  -9.55759880E-02  -1.42403393E-01  -1.80966439E-01  -1.52589080E-01  -1.97656899E-01  -2.48082477E-01  -2.52301208E-01  -1.61479600E-01  -6.27303905E-02  -1.04761762E-01  -9.71568194E-02   5.79035346E-02   7.55237619E-02   1.11654311E-01   1.40263029E-01   1.20523911E-01   1.54379223E-01   1.88741315E-01   1.76457166E-01   1.96547498E-01   2.92386752E-02   1.06845268E-01   6.53130753E-02  -2.91128822E-02  -3.78315985E-02  -5.54803699E-02  -6.88672735E-02  -6.03076498E-02  -7.63210503E-02  -9.07384597E-02  -7.76029085E-02  -6.66527902E-02  -5.68517807E-02  -2.59939922E-02  -6.56692029E-02   1.09896724E-03   1.40474649E-03   1.98765186E-03   2.34019552E-03   2.21241065E-03   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3.47308319E-02   4.06421267E-02   3.60705138E-02   2.00057673E-02   1.61975860E-03   3.04879883E-02   9.16492114E-03   8.02039580E-03   4.91838031E-03\nCm  -1.09700221E-02  -2.29527497E-02  -6.37940293E-02  -1.12907399E-01  -8.59962995E-02  -1.38217538E-01  -1.76087541E-01  -2.05468360E-01  -8.79630077E-02  -9.62184231E-04  -6.36800479E-02  -3.09473902E-02  -5.30120565E-02  -6.97067777E-02  -1.04896541E-01  -1.35282569E-01  -1.11245919E-01  -1.46091349E-01  -1.89429944E-01  -2.13974704E-01  -1.73192457E-01  -3.17013402E-02  -9.70565476E-02  -5.91875327E-02  -6.19975331E-03  -8.08332600E-03  -1.19406173E-02  -1.49819460E-02  -1.28986629E-02  -1.65020461E-02  -2.01187418E-02  -1.86418861E-02  -3.73319956E-02  -9.96297924E-03   1.83974108E-02   7.09355463E-03   4.44959376E-02   5.61996142E-02   7.74878017E-02   8.78189886E-02   8.71591688E-02   9.93113094E-02   9.34579683E-02   3.83748478E-02   9.09081559E-02  -8.61613080E-04   3.82069537E-02   1.00500957E-02  -4.54383478E-02  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4.13773365E-02   1.39262922E-02   1.77425927E-02   2.49264450E-02   2.90404893E-02   2.78399464E-02   3.28224022E-02   3.32818762E-02   1.72433271E-02   2.72403965E-02   3.48612265E-02   2.94673820E-02   3.02057875E-02   4.93295252E-02   6.24366202E-02   8.64817158E-02   9.86732885E-02   9.71319447E-02   1.11616901E-01   1.06995643E-01   4.65287803E-02   9.88152639E-02   3.98650204E-02   4.19803198E-02   3.26275673E-02  -4.34942203E-02  -5.22005763E-02  -6.45108543E-02  -6.22832058E-02  -7.22075784E-02  -6.53774863E-02  -3.77976428E-02  -3.47325790E-03  -8.27949073E-02  -1.33526420E-03  -1.58081203E-02  -4.45873527E-03\nCm  -8.76844929E-03  -1.88554329E-02  -3.41284952E-02  -4.15459187E-02  -3.63599300E-02  -4.16149188E-02  -5.64287939E-02  -5.17953972E-02  -2.90595816E-02  -2.13280180E-02  -6.39853553E-02  -6.78441655E-02  -1.93109275E-02  -2.50535790E-02  -3.66120438E-02  -4.52097855E-02  -3.99112255E-02  -5.02367021E-02  -5.89906518E-02  -4.85012542E-02  -4.62112420E-02  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9.32546484E-02   5.77731099E-02   7.69725554E-02   1.19221211E-01   1.60501373E-01   1.21923250E-01   1.65898069E-01   2.34875388E-01   3.53926759E-01   1.63709149E-01   4.64329265E-02   1.25833779E-01   7.09156131E-02  -3.01242866E-02  -3.93240344E-02  -5.82426775E-02  -7.33637908E-02  -6.27646525E-02  -8.06098149E-02  -9.91658716E-02  -9.45710361E-02  -5.88818067E-02   9.13912875E-03  -9.63692412E-03   5.24691111E-03   4.39290713E-02   5.68965585E-02   8.28410841E-02   1.01740878E-01   9.05632732E-02   1.13343845E-01   1.31368806E-01   1.03628794E-01   1.37479881E-01   4.43379850E-02   7.40747455E-02   5.13750569E-02  -4.51716422E-02  -5.79149275E-02  -8.24849303E-02  -9.80569070E-02  -9.14916267E-02  -1.10455725E-01  -1.18046746E-01  -7.21021962E-02  -9.89486322E-02  -1.58411454E-02  -6.02270397E-02  -2.45942359E-02\nCm   7.64378141E-02   8.15447224E-02   6.99921398E-02   3.97991541E-02   4.46133643E-02   1.27886582E-02   1.56287418E-02   6.05969784E-02   2.57739353E-02   1.09765345E-01   6.49668779E-02   1.34295497E-01   6.05648114E-02   7.95557835E-02   1.19447104E-01   1.53531628E-01   1.26986988E-01   1.66253916E-01   2.14002765E-01   2.36081281E-01   1.24032414E-01   2.25203982E-02   2.30680405E-01   1.02391508E-01  -5.35165409E-02  -6.97245535E-02  -1.02832180E-01  -1.28719191E-01  -1.11240677E-01  -1.41981285E-01  -1.72152476E-01  -1.56746929E-01  -1.19372258E-01  -1.75143101E-04  -1.04800495E-01  -3.62450536E-02  -8.68698946E-03  -1.12135722E-02  -1.62080566E-02  -1.96919948E-02  -1.78128578E-02  -2.20361791E-02  -2.48759929E-02  -1.80526224E-02  -3.77273655E-02   5.10967969E-03   3.49920964E-03   1.95312003E-03  -1.17521233E-03  -1.47096318E-03  -1.98900815E-03  -2.19053937E-03  -2.24760873E-03  -2.46726488E-03  -2.14205934E-03  -6.85164951E-04  -6.10627843E-03   6.80137394E-03   1.14310467E-02   6.32179807E-03\nCm   8.75782695E-03   1.71005139E-02   3.22485799E-02   4.31918105E-02   3.70672842E-02   4.62119382E-02   5.89399380E-02   6.27316562E-02   6.52249341E-02   1.22975775E-02   2.73061958E-02   3.20146442E-02   9.13562585E-03   1.19282430E-02   1.76754764E-02   2.22804958E-02   1.90392170E-02   2.44697379E-02   3.01523530E-02   2.89077255E-02   9.54264865E-03   1.21421618E-02   2.88188862E-02   1.80808967E-02  -3.47997499E-02  -4.52218684E-02  -6.63192269E-02  -8.23232140E-02  -7.20887193E-02  -9.12323422E-02  -1.08472071E-01  -9.27843356E-02  -9.77587701E-02  -2.26379170E-04  -7.39394949E-02  -2.50810443E-02   5.54672431E-02   7.20188776E-02   1.05425967E-01   1.30515346E-01   1.14768006E-01   1.44842585E-01   1.71117213E-01   1.43428748E-01   1.76278324E-01   2.07088400E-02   9.89521158E-02   4.99360074E-02  -1.60091415E-02  -2.03350060E-02  -2.83834142E-02  -3.27529084E-02  -3.17885051E-02  -3.70445029E-02  -3.66156481E-02  -1.75169410E-02  -1.87459238E-02   7.48265313E-03  -1.04568322E-02   3.63671211E-03\nCm  -2.19851988E-02  -3.02807069E-02  -3.43070626E-02  -2.16457710E-02  -3.62932135E-02  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1.28261346E-01   9.95223633E-02   2.54300904E-02   3.57640161E-02   2.85765734E-02  -6.54766397E-02  -8.54181528E-02  -1.26336261E-01  -1.58807600E-01  -1.36319172E-01  -1.74721103E-01  -2.13923466E-01  -2.00937355E-01  -1.00133141E-01  -3.12453229E-02  -7.10679985E-02  -6.02274658E-02   4.24987099E-02   5.41834720E-02   7.62394603E-02   8.90246613E-02   8.50907862E-02   1.00593077E-01   1.02615892E-01   5.41726984E-02   6.90990272E-02   2.07509355E-02   4.85961562E-02   2.95501252E-02   3.90881867E-03   4.93129761E-03   6.78247534E-03   7.65887925E-03   7.63461537E-03   8.65892131E-03   8.06708005E-03   3.21063540E-03   5.33808344E-03   1.74687057E-02   8.45366375E-03   1.96813475E-02\nCm  -7.63792254E-02  -1.09085012E-01  -1.74866575E-01  -2.35659324E-01  -1.80298438E-01  -2.44015349E-01  -3.36730299E-01  -5.13495508E-01  -1.46167479E-01  -8.91363288E-02  -1.74681869E-01  -1.49442032E-01  -5.86926914E-02  -7.88919382E-02  -1.24600278E-01  -1.72698274E-01  -1.23585860E-01  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1.53279626E-01   7.28228619E-02   6.41514904E-02   7.70055461E-02   1.00918389E-01   1.58689574E-02   2.11631984E-02   3.28495780E-02   4.43652546E-02   3.34897634E-02   4.56763247E-02   6.50635947E-02   1.00058875E-01   6.88173162E-02   2.24494854E-02   3.52716144E-02   2.22571195E-02   6.62156317E-02   8.55176249E-02   1.23743267E-01   1.50587277E-01   1.35891144E-01   1.68408584E-01   1.90876027E-01   1.40287226E-01   1.07121312E-01   4.17262727E-02   1.26390048E-01   7.82173744E-02  -4.89805797E-02  -6.29686174E-02  -9.02106986E-02  -1.08174567E-01  -9.97168852E-02  -1.21579539E-01  -1.32831387E-01  -8.69530440E-02  -1.06446194E-01  -7.27135441E-03  -3.14797929E-02  -1.09146384E-02  -1.69398731E-02  -1.94117944E-02  -2.17441684E-02  -1.81977503E-02  -2.30020916E-02  -1.63602534E-02  -5.75031377E-03  -1.16537357E-04  -1.48059740E-02   1.01233481E-02  -5.99448555E-03   3.19833477E-03\nCm  -5.89253853E-02  -6.71907890E-02  -9.95406449E-02  -1.38447831E-01  -1.16305380E-01  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1.57910794E-01   1.49392315E-01   1.66596538E-01   1.82437758E-01   1.22167792E-01   9.17537315E-02   9.13465223E-02   9.26359297E-02   9.33857923E-02   6.66275009E-02   8.56879660E-02   1.22861018E-01   1.47507245E-01   1.35738464E-01   1.65727071E-01   1.81625071E-01   1.20055899E-01   1.95663093E-01   4.95175738E-02   1.30198644E-01   8.06321958E-02   1.17521233E-03   1.47096318E-03   1.98900815E-03   2.19053937E-03   2.24760873E-03   2.46726488E-03   2.14205934E-03   6.85164951E-04   2.53947126E-03   2.50912320E-02   3.03354761E-03   1.35939120E-02   2.33262964E-02   2.90326242E-02   3.87847951E-02   4.19620944E-02   4.38955423E-02   4.70410878E-02   3.87896264E-02   1.05823364E-02   2.17192037E-02   3.86881461E-02   8.71010633E-03   2.74864090E-02  -2.59061753E-02  -3.20661687E-02  -4.23324763E-02  -4.50112227E-02  -4.79393950E-02  -5.01493470E-02  -3.92782035E-02  -9.14453621E-03  -5.12076834E-02   1.19736792E-02  -2.26114940E-02  -1.76770182E-03\nCm   2.77281788E-02   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1.81997796E-01   1.05269408E-01   6.11009531E-02   6.02539840E-02   7.81762462E-02  -1.94837645E-02  -2.59139887E-02  -3.99856570E-02  -5.35271091E-02  -4.11116449E-02  -5.57010703E-02  -7.80013844E-02  -1.13336062E-01  -7.43027838E-02   2.04069551E-02  -3.73502794E-02   7.06808263E-03   5.91121699E-02   7.80563977E-02   1.18551138E-01   1.55005177E-01   1.24405615E-01   1.65359392E-01   2.20777825E-01   2.74243085E-01   1.92440489E-01   3.64729148E-02   1.89499262E-01   7.91413498E-02   2.02316181E-02   2.56716831E-02   3.57516924E-02   4.11189197E-02   4.00759355E-02   4.65121239E-02   4.55647596E-02   2.11996597E-02   1.29273564E-02   1.31987819E-02   3.05222344E-02   1.63251771E-02  -1.71685047E-02  -1.96396695E-02  -2.19187273E-02  -1.82463497E-02  -2.31201117E-02  -1.62879427E-02  -5.61416843E-03  -1.07245455E-04  -9.08568967E-03  -6.47904769E-03  -1.73689244E-02  -1.46929064E-02\nCm   3.97347026E-02   4.83714251E-02   5.89102150E-02   6.08770633E-02   5.50614648E-02   6.39393844E-02   8.51218395E-02   2.29558407E-02   4.90086353E-02   7.46180134E-02   6.73668502E-02   1.00786716E-01  -1.50442902E-02  -2.01389363E-02  -3.15197387E-02  -4.30986931E-02  -3.17318560E-02  -4.36578597E-02  -6.36348819E-02  -1.05719854E-01  -6.48361189E-02   5.46991639E-04  -1.35099363E-02  -4.41723323E-04   5.78459965E-02   7.45407750E-02   1.07335345E-01   1.29682418E-01   1.18262933E-01   1.45409526E-01   1.61896605E-01   1.12477268E-01   1.30134593E-01   4.43160760E-02   1.18749111E-01   7.37449348E-02   3.13353084E-02   3.96836678E-02   5.50334367E-02   6.29045079E-02   6.17847943E-02   7.11582019E-02   6.85471419E-02   3.02667553E-02   6.77237437E-02   2.99280756E-02   5.97050049E-02   4.00094687E-02  -6.52073282E-02  -7.98662966E-02  -1.03080684E-01  -1.06036917E-01  -1.16588324E-01  -1.16293509E-01  -8.23521482E-02  -1.40688162E-02  -9.93629651E-02  -3.43165954E-02  -3.90665991E-02  -3.56128741E-02\nCm   1.94831580E-02   2.14968004E-02   1.67886779E-02   5.42280182E-03   3.47360052E-03  -1.77645855E-02  -1.20645721E-02   1.12733870E-01  -7.70181217E-03   1.21988708E-02   5.71895943E-02   6.82676179E-02   2.21306100E-02   2.97837105E-02   4.71685672E-02   6.56443936E-02   4.65643637E-02   6.47927040E-02   9.74202232E-02   1.79943998E-01   6.11068670E-02   2.14900438E-02   6.45339276E-02   4.70513043E-02  -6.20098597E-02  -7.88431910E-02  -1.10282876E-01  -1.27659604E-01  -1.23406377E-01  -1.44362158E-01  -1.43894158E-01  -7.06654775E-02  -1.18526001E-01  -1.66425242E-02  -5.41369148E-02  -2.38556560E-02   3.27548862E-02   3.95124191E-02   4.93645246E-02   4.84222607E-02   5.54502976E-02   5.14702369E-02   3.13419359E-02   3.37412848E-03   2.87620471E-02   2.67739632E-02   4.86320243E-02   4.63646496E-02   1.45789322E-02   1.66733222E-02   1.85986080E-02   1.54709854E-02   1.96100527E-02   1.37966890E-02   4.74250171E-03   8.98481147E-05   3.75082491E-03   4.88028511E-02   4.01117627E-02   8.57033956E-02\nCm   3.14024504E-02   5.76749380E-02   1.20100743E-01   1.89135927E-01   1.31904670E-01   2.01870594E-01   2.99919906E-01   4.95126148E-01   1.57188416E-01   1.50563061E-02   1.41532857E-01   4.41749959E-02   6.94545435E-02   9.26858303E-02   1.44071516E-01   1.94989159E-01   1.46572255E-01   2.00216164E-01   2.86342659E-01   4.46293970E-01   1.41843284E-01   6.63753929E-02   7.59286409E-02   9.08455399E-02   3.38219213E-02   4.43712509E-02   6.64365642E-02   8.50453723E-02   7.08356697E-02   9.23895489E-02   1.17858435E-01   1.26294681E-01   1.09262244E-01   5.94797302E-02   4.98583368E-02   6.66488298E-02  -4.42665533E-02  -5.69447295E-02  -8.16939379E-02  -9.81626907E-02  -9.02252754E-02  -1.10260475E-01  -1.21088240E-01  -8.05641843E-02  -1.08051354E-01   3.74545943E-03  -5.89181677E-02  -1.62197583E-02   1.28537689E-02   1.57806397E-02   2.04709632E-02   2.12147002E-02   2.31660231E-02   2.33594432E-02   1.69247814E-02   3.10168439E-03   3.87005357E-02   4.85538857E-02   1.37337031E-02   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5.55592204E-02   3.66940606E-02   5.06332025E-03   3.22671217E-02   2.74408919E-02   6.02577140E-02   4.61295772E-02  -4.61626592E-03  -5.59325253E-03  -7.05404366E-03  -7.01524737E-03  -7.94414457E-03  -7.53214295E-03  -4.79470935E-03  -5.91129018E-04  -1.42002143E-02   2.26473042E-02   2.21704734E-02   5.16166320E-02   4.61932269E-02   5.53130405E-02   6.80243432E-02   6.52093902E-02   7.60046209E-02   6.80421141E-02   3.84238935E-02   3.28649386E-03   6.36395033E-02   3.73386696E-02   1.32315710E-01   8.84056545E-02\nCm  -4.44757758E-02  -4.04185211E-02  -2.47443388E-02  -6.79864267E-04  -1.21096287E-02   1.40853872E-02   3.24311587E-02   2.96781205E-02   6.79378620E-03  -4.92917846E-02  -7.28266930E-03  -1.05577962E-02  -9.24983509E-03  -1.23580954E-02  -1.92587881E-02  -2.61650276E-02  -1.95178864E-02  -2.67341607E-02  -3.85091873E-02  -6.14791520E-02  -4.35163384E-03  -3.28841730E-02  -7.07938941E-02  -7.47963366E-02   5.01902228E-02   6.50695682E-02   9.49428108E-02   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1.24931731E-02   1.51608203E-02   1.87275178E-02   2.46152766E-02   2.60054850E-02   2.78755126E-02   2.88973441E-02   2.22012856E-02   4.87139850E-03   1.06813167E-02   1.12384271E-02   7.36483546E-02   5.05539599E-02  -6.08857080E-02  -7.11176708E-02  -8.29595193E-02  -7.36391238E-02  -9.02768244E-02  -7.11743914E-02  -3.09028282E-02  -1.18840427E-03  -6.06003453E-02  -3.51148445E-02  -5.56459823E-02  -4.48872017E-02\nCm  -9.44587244E-03  -7.56009104E-03  -2.21830712E-02  -7.16074267E-02   2.06870135E-03  -6.46958537E-02  -2.10786576E-01  -4.97357109E-01  -8.56798441E-02  -2.36636850E-02  -1.35633931E-02   4.24661943E-03  -6.22626951E-02  -8.32787408E-02  -1.30103544E-01  -1.77414684E-01  -1.31352777E-01  -1.80383575E-01  -2.61619284E-01  -4.27406857E-01  -2.21953441E-01  -5.14871426E-02  -2.27217148E-01  -1.07967335E-01  -2.00252982E-02  -2.66832890E-02  -4.13397190E-02  -5.56746548E-02  -4.22611675E-02  -5.75199957E-02  -8.14950435E-02  -1.23100673E-01  -4.61541123E-02  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1.19410213E-03   6.98650591E-03   9.26906660E-03   1.42239398E-02   1.88858096E-02   1.47336819E-02   1.98347494E-02   2.73294335E-02   3.76395359E-02   2.19760420E-02  -2.43623861E-03   2.18781166E-03  -2.11157202E-03   5.95332577E-02   7.64431411E-02   1.09229850E-01   1.30478417E-01   1.20929275E-01   1.46802334E-01   1.58833802E-01   1.00837934E-01   1.30149187E-01   3.03494392E-02   8.17205366E-02   4.66493529E-02  -4.72416597E-02  -6.02815819E-02  -8.49757497E-02  -9.94948895E-02  -9.47596444E-02  -1.12385695E-01  -1.15465527E-01  -6.23295304E-02  -1.20070586E-01  -9.60122323E-03  -6.60553040E-02  -2.48837073E-02   9.88062342E-03   1.22186900E-02   1.60984916E-02   1.70672391E-02   1.82309832E-02   1.89930262E-02   1.47461414E-02   3.34187830E-03   2.26228566E-02   1.66444962E-02   2.01802221E-03   7.95232329E-03\nCm   1.27753652E-02   7.12883336E-03   1.86652143E-03   1.03828387E-03   2.54270677E-03   2.67205652E-03  -3.26582388E-03  -5.19550815E-03  -1.44368136E-02   1.35739200E-02   4.97108753E-02   3.66617300E-02   9.50685709E-03   1.24527645E-02   1.85821899E-02   2.36675281E-02   1.98812996E-02   2.58085158E-02   3.25566548E-02   3.36520257E-02   1.79076830E-03   2.92092399E-02   4.58384285E-02   4.71787239E-02  -2.29569143E-02  -2.96230774E-02  -4.27832496E-02  -5.19188551E-02  -4.70448688E-02  -5.81247041E-02  -6.54262857E-02  -4.70496475E-02  -5.80499420E-02   1.22394675E-02  -1.79701936E-02   2.07702338E-02  -4.05266479E-02  -5.16051741E-02  -7.24170858E-02  -8.42276318E-02  -8.09225750E-02  -9.52121851E-02  -9.61156341E-02  -4.91089661E-02  -1.43652634E-02  -2.79086279E-02  -3.40572588E-02  -3.25873520E-02   5.62627122E-02   7.13427436E-02   9.92100220E-02   1.13858003E-01   1.11270972E-01   1.28796987E-01   1.25439306E-01   5.73109847E-02   9.55200518E-02   2.50322252E-02   4.94111298E-02   5.12517204E-02\nCm  -6.20560018E-02  -7.09924394E-02  -8.86675985E-02  -1.06511878E-01  -8.55417657E-02  -1.15603964E-01  -1.54356157E-01  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1.52721556E-01   2.33451610E-01   2.38115626E-01   9.32285551E-02   1.81059048E-02   1.68078850E-01   1.12019803E-01  -1.33343875E-02  -1.78455075E-02  -2.79147980E-02  -3.81379117E-02  -2.81271399E-02  -3.86765720E-02  -5.62893588E-02  -9.30415271E-02  -2.75467006E-02   8.54554382E-03  -2.19325823E-02   6.39731304E-03   6.67904714E-02   8.81979787E-02   1.33962518E-01   1.75171960E-01   1.40567429E-01   1.86856634E-01   2.49528705E-01   3.10155397E-01   1.38323676E-01   7.74301229E-02   1.50651093E-01   1.49404351E-01   2.28613482E-02   2.88019494E-02   3.94970000E-02   4.44070583E-02   4.44958909E-02   5.01850312E-02   4.61925979E-02   1.77068397E-02   2.08933765E-02   5.22443449E-02   5.87224561E-02   9.40830419E-02   4.36279700E-02   5.32560396E-02   6.82417304E-02   6.94621908E-02   7.71050142E-02   7.57184997E-02   5.18848703E-02   8.01418790E-03   6.02900876E-02   9.59443972E-02   1.24112053E-01   1.96186346E-01\nCm   1.87746373E-03   3.17630868E-03   2.36870877E-02   7.10812891E-02   2.15697125E-02   9.82003289E-02   1.92722646E-01   2.06603596E-01   4.27559824E-02  -3.43490003E-02   9.41567265E-03  -3.33415776E-02   6.09596920E-02   7.96523156E-02   1.18218629E-01   1.49371117E-01   1.27149485E-01   1.63793856E-01   2.02924160E-01   1.97940583E-01   1.11750170E-01   2.70031491E-02   9.21220400E-02   5.38350793E-02   4.26385279E-03   5.50551189E-03   7.96245873E-03   9.68264400E-03   8.74717638E-03   1.08316148E-02   1.22544355E-02   8.95515484E-03   2.19901487E-02   1.99151781E-02  -4.96235235E-03   9.22275279E-03  -1.64577036E-02  -1.86857678E-02  -2.05255272E-02  -1.66977382E-02  -2.13707143E-02  -1.44412401E-02  -4.57151039E-03  -6.74994747E-05  -1.50345580E-02  -2.22752884E-02  -1.14711682E-02  -1.73939506E-02  -5.64679646E-02  -6.40415516E-02  -7.01820275E-02  -5.69000382E-02  -7.29259760E-02  -4.89746500E-02  -1.53081662E-02  -2.17529402E-04  -4.69396271E-02  -3.86434080E-02  -7.89766425E-02  -6.45444722E-02\nCm   1.08381008E-03  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1.17293368E-02   1.95853268E-02   2.95132321E-02   1.72185915E-02   2.47059625E-02   4.14579830E-02   1.15075398E-01   4.75364424E-02   3.40926263E-03   1.99678820E-02  -1.66058350E-03   5.43778391E-02   7.28018284E-02   1.13975333E-01   1.55910470E-01   1.14691273E-01   1.57841584E-01   2.30243235E-01   3.83506360E-01   1.37378559E-01   5.11386197E-02   1.90498996E-01   1.20448290E-01  -4.21608237E-02  -5.42763714E-02  -7.79920178E-02  -9.39388115E-02  -8.60488076E-02  -1.05438030E-01  -1.16489289E-01  -7.89832540E-02  -8.25240960E-02  -5.90456651E-02  -1.11836960E-01  -1.28763388E-01  -6.54436592E-02  -8.00499827E-02  -1.03026045E-01  -1.05543299E-01  -1.16483802E-01  -1.15482985E-01  -8.07340699E-02  -1.32596534E-02  -8.70893475E-02  -8.10908744E-02  -9.07739933E-02  -1.18776110E-01\nCm   1.42402080E-02   1.40630621E-02   1.08148138E-02   1.59686848E-03   1.51177930E-02   7.20188019E-03  -2.80103839E-02  -8.88703607E-02   3.10235700E-03   1.76591915E-02   1.56509628E-02   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5.79297430E-02   8.98259950E-02   1.23595794E-01   1.06674188E-01   5.61051110E-02   6.08277611E-02   5.41298052E-02   1.46213016E-02   1.95795416E-02   3.06678464E-02   4.19821350E-02   3.08366182E-02   4.24592139E-02   6.20172310E-02   1.03763034E-01   5.78370211E-02   1.57225849E-02   2.16528570E-02   1.06902092E-04  -2.22225851E-02  -2.96235802E-02  -4.59375410E-02  -6.19522641E-02  -4.68986351E-02  -6.38971092E-02  -9.07695813E-02  -1.38322542E-01  -6.07917015E-02   1.67336536E-02  -7.15024261E-02  -8.38430277E-03   6.83258859E-02   8.92497630E-02   1.32373928E-01   1.67089878E-01   1.42464373E-01   1.83344296E-01   2.26629584E-01   2.19460155E-01   1.66317525E-01   6.26583260E-02   2.16099272E-01   1.49872167E-01  -3.16618804E-02  -4.07081431E-02  -5.83326118E-02  -6.99714122E-02  -6.44708051E-02  -7.86348282E-02  -8.59832474E-02  -5.64321445E-02  -6.76486781E-02  -1.53188262E-02  -7.78208498E-02  -6.97803308E-02\nCm   2.40201924E-02   2.88097843E-02   4.34032085E-02   5.81194838E-02   5.21993893E-02   7.34679727E-02   7.69046366E-02   3.00343307E-02   3.59941217E-02   4.44645013E-02   9.57452849E-02   5.16938125E-02  -3.51563828E-03  -4.59175049E-03  -6.80878400E-03  -8.59137992E-03  -7.32944237E-03  -9.42934212E-03  -1.16460419E-02  -1.12483605E-02   3.16119878E-03   6.51475087E-03  -1.91875434E-02  -1.55259829E-03  -4.17987683E-02  -5.43157381E-02  -7.96515936E-02  -9.88654423E-02  -8.65845953E-02  -1.09569180E-01  -1.30250653E-01  -1.11349869E-01  -6.84148290E-02  -1.56086255E-02  -8.82528327E-02  -5.28158683E-02   4.55547382E-02   5.90335890E-02   8.60524001E-02   1.05866422E-01   9.39906815E-02   1.17847029E-01   1.37154777E-01   1.09622520E-01   1.21248236E-01   5.25040801E-02   1.17077752E-01   1.04767214E-01   6.47708321E-02   8.23112020E-02   1.15005489E-01   1.32907884E-01   1.28749965E-01   1.50311645E-01   1.49166837E-01   7.22568029E-02   1.22074337E-01   7.71249724E-02   9.57549462E-02   1.14697114E-01\nCm  -3.97605719E-02  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1.16692723E-01   9.53629160E-02   2.53053644E-02   9.28795288E-02   1.95296298E-02   6.09863128E-02   3.51483124E-02\nCm  -3.41239729E-02  -3.65267300E-02  -3.65841169E-02  -3.75022018E-02  -1.59049580E-02  -1.66750317E-02  -7.05222900E-02  -2.11586071E-01   6.56860739E-03  -4.19288730E-02  -7.88741265E-02  -1.04208890E-01  -6.67904714E-02  -8.81979787E-02  -1.33962518E-01  -1.75171960E-01  -1.40567429E-01  -1.86856634E-01  -2.49528705E-01  -3.10155397E-01  -1.46936160E-01  -2.84385510E-02  -1.81166962E-01  -1.02444686E-01   4.51716422E-02   5.79149275E-02   8.24849303E-02   9.80569070E-02   9.14916267E-02   1.10455725E-01   1.18046746E-01   7.21021962E-02   1.30054605E-01   9.38193938E-03   4.18346803E-02   1.41043720E-02   1.31041367E-02   1.67804602E-02   2.38364148E-02   2.82261881E-02   2.64776414E-02   3.18222690E-02   3.36701831E-02   1.99290770E-02   1.97312835E-02  -8.72157735E-03   2.63861907E-02   3.95683591E-03   2.23810351E-02   2.76166184E-02   3.62153497E-02   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3.23403464E-02   1.03545576E-01   7.13065234E-02  -5.75984373E-02  -7.28445199E-02  -1.00724277E-01  -1.14632928E-01  -1.13193541E-01  -1.29660533E-01  -1.23433290E-01  -5.25318444E-02  -1.08722158E-01  -3.18884325E-02  -5.69082350E-02  -5.03864068E-02  -1.88954897E-04  -2.20038360E-04  -2.55024062E-04  -2.24257144E-04  -2.76391932E-04  -2.14426177E-04  -9.00662140E-05  -3.13227482E-06  -2.65921453E-03   3.24481755E-03   5.79001549E-03  -8.06749928E-04\nCm   1.18836093E-02   1.01652693E-02   6.31333636E-03   8.82762430E-03  -7.83176808E-03   1.01936373E-03   4.70047695E-02   8.92200493E-02  -6.40234872E-03   1.47779133E-02  -5.41053130E-03  -3.46483552E-03  -8.73125971E-03  -1.14461792E-02  -1.71106713E-02  -2.18511038E-02  -1.82738943E-02  -2.37811743E-02  -3.01768216E-02  -3.17903023E-02  -1.95910655E-02  -8.34591525E-03  -1.42536095E-02  -2.15277004E-03   5.60611674E-02   7.31657165E-02   1.08313320E-01   1.36336621E-01   1.16774574E-01   1.49870582E-01   1.84068748E-01   1.74623245E-01   1.51180348E-01   1.97144721E-02   7.22782143E-02   2.60964915E-02  -2.62009346E-02  -3.37755830E-02  -4.86755735E-02  -5.88816986E-02  -5.36018355E-02  -6.59948789E-02  -7.37014917E-02  -5.16975514E-02  -4.43616515E-02  -8.00524927E-03  -3.13430832E-02  -9.12295125E-03  -5.21573566E-02  -6.16554634E-02  -7.37730371E-02  -6.79505340E-02  -8.14338522E-02  -6.83218101E-02  -3.37244128E-02  -1.91495059E-03  -3.66346499E-02  -3.23213842E-02  -4.88498481E-02  -3.86426762E-02\nCm   1.51939484E-02   2.95193406E-02   6.29175981E-02   1.06206114E-01   5.84881981E-02   1.04782206E-01   1.91742978E-01   3.89859815E-01   4.98726508E-02   2.58447718E-02   7.94673939E-02   6.19495299E-02   4.97502424E-02   6.67814726E-02   1.05158160E-01   1.45100705E-01   1.04828729E-01   1.45093720E-01   2.14952002E-01   3.77377065E-01   1.19912555E-01   2.98796007E-02   9.24764376E-02   6.73732228E-02   2.62009346E-02   3.37755830E-02   4.86755735E-02   5.88816986E-02   5.36018355E-02   6.59948789E-02   7.37014917E-02   5.16975514E-02   5.80704825E-02   3.73955427E-02   3.24388267E-02   5.00643969E-02  -4.93310649E-02  -6.21930497E-02  -8.54149613E-02  -9.62448115E-02  -9.61861791E-02  -1.08791386E-01  -1.00752130E-01  -3.93623396E-02  -1.30190913E-01  -6.00384578E-03  -3.94009948E-02  -1.55439785E-02   1.59470875E-02   1.83810773E-02   2.08456645E-02   1.77614036E-02   2.22577747E-02   1.63432585E-02   6.13155455E-03   1.51408955E-04   3.88222161E-03   6.41483274E-03   1.11896085E-02   6.62430797E-03\nCm  -1.57247368E-02  -4.58811547E-03   2.78616138E-02   7.97155963E-02   2.17574998E-02   7.85244718E-02   1.93910812E-01   4.14189301E-01   6.37855480E-02  -4.61028003E-03   4.98388838E-02   2.39181192E-02   2.19976327E-02   2.96634569E-02   4.71846366E-02   6.60992001E-02   4.62182900E-02   6.45582872E-02   9.81413981E-02   1.88314332E-01   5.90948741E-02   3.04227110E-02   6.70958087E-02   5.54895989E-02   6.80661762E-02   8.94960229E-02   1.34656923E-01   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4.82275589E-01   1.11895906E-01   6.81364636E-02   1.56178688E-01   1.60204092E-01   5.51635589E-02   7.39727739E-02   1.16220913E-01   1.59828600E-01   1.16285564E-01   1.60602487E-01   2.36519520E-01   4.06929746E-01   1.44280063E-01   5.34973156E-02   2.12988965E-01   1.36603193E-01   4.24567767E-02   5.50696995E-02   8.04353863E-02   9.92499891E-02   8.77186170E-02   1.10326078E-01   1.29319069E-01   1.05721431E-01   7.35967754E-02   5.23965577E-02   6.81440532E-02   7.41233041E-02  -3.07658193E-02  -3.87886286E-02  -5.32755527E-02  -6.00368054E-02  -5.99926357E-02  -6.78639377E-02  -6.28676697E-02  -2.45840294E-02  -5.26356642E-02   7.81743494E-03  -5.25017614E-02  -2.56874056E-02  -2.09636698E-02  -2.58115208E-02  -3.36907863E-02  -3.52320865E-02  -3.81437570E-02  -3.89692936E-02  -2.90276077E-02  -5.79175980E-03  -3.58072177E-02   1.82618670E-02  -1.24146829E-02   9.17717529E-03\nCm   9.48605026E-03   2.62260999E-02   6.98073603E-02   1.09172413E-01   9.82054082E-02   1.39615706E-01   1.46690076E-01   7.23284737E-02   5.59450141E-02  -1.51427554E-02   1.52589480E-01   1.27790899E-01   3.21509556E-02   4.11164371E-02   5.82383666E-02   6.86730907E-02   6.47893602E-02   7.74849564E-02   8.10931506E-02   4.63815833E-02   2.58290560E-02   5.42224437E-02   9.42529571E-02   1.15073545E-01   2.37023758E-02   3.00092822E-02   4.15933605E-02   4.75025028E-02   4.67051315E-02   5.37346882E-02   5.16452140E-02   2.26427639E-02   4.40335053E-02   3.76853415E-02   6.47520151E-02   6.18352497E-02   4.67565409E-02   5.67436305E-02   7.18107098E-02   7.17765590E-02   8.09389459E-02   7.73339894E-02   5.00279379E-02   6.47932578E-03   5.69068891E-02   7.82103601E-02   6.71111411E-02   1.08438826E-01  -3.86053281E-02  -4.63164298E-02  -5.71952594E-02  -5.51585987E-02  -6.40017686E-02  -5.78455734E-02  -3.33203153E-02  -3.02767523E-03  -4.91848550E-02  -2.32682371E-02  -3.44573405E-02  -2.30050986E-02\nCm   4.10007637E-02   5.70450528E-02   8.69262627E-02   9.91924077E-02   1.08309487E-01   1.14148664E-01   8.55496702E-02   1.20736148E-02   1.17061862E-01   2.70207664E-02   1.96939721E-01   1.71084538E-01  -6.41599703E-02  -8.59463733E-02  -1.34720160E-01  -1.84628227E-01  -1.35300594E-01  -1.86436218E-01  -2.72864206E-01  -4.59665512E-01  -1.83730532E-01  -9.75945481E-03  -1.54980472E-01  -5.33310264E-02   1.73317522E-02   2.31218616E-02   3.59166646E-02   4.85616509E-02   3.65764014E-02   4.99267322E-02   7.12686138E-02   1.10378520E-01   4.23938226E-02   3.89926516E-02   2.87857402E-02   3.25461652E-02   5.34499738E-02   7.12643174E-02   1.10555961E-01   1.49190014E-01   1.12800997E-01   1.53755734E-01   2.18676327E-01   3.34549711E-01   1.48236199E-01   5.38257164E-02   1.66390644E-01   1.41708363E-01   1.61401895E-02   2.06940464E-02   2.94751388E-02   3.50427607E-02   3.26924742E-02   3.94729312E-02   4.21953694E-02   2.57912274E-02   1.30564243E-02   5.66429162E-02   7.61318857E-02   1.07849149E-01\nCm  -3.06734100E-02  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3.20218610E-03   3.74184874E-02   2.72649609E-02\nCm   3.04478003E-02   3.76537247E-02   5.47091563E-02   7.83201226E-02   4.20217673E-02   6.72491392E-02   1.46993444E-01   3.08813331E-01   3.60450334E-02   9.78901586E-03   8.25777696E-02   4.07661939E-02   7.65283326E-02   1.00988339E-01   1.53161261E-01   1.99833561E-01   1.60997610E-01   2.13607353E-01   2.83928860E-01   3.47606562E-01   1.33839914E-01   6.12491196E-02   1.04346765E-01   1.09428853E-01   2.26262149E-02   2.92970910E-02   4.26304793E-02   5.23093558E-02   4.66257492E-02   5.82984974E-02   6.74228935E-02   5.28205580E-02   4.00329879E-02   6.30255301E-02   5.28784396E-02   9.09606377E-02  -6.29112853E-02  -7.99119061E-02  -1.11544007E-01  -1.28721982E-01  -1.24924022E-01  -1.45588027E-01  -1.43921505E-01  -6.88803226E-02  -1.06894539E-01  -3.74103167E-02  -8.82913114E-02  -6.39359505E-02  -3.25003373E-02  -4.08502601E-02  -5.57382061E-02  -6.22057686E-02  -6.28713699E-02  -7.02340816E-02  -6.33206414E-02  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1.15848684E-02   9.23588022E-03   1.23148202E-02   1.65687937E-02   2.11040443E-02   1.20658904E-02   3.80226284E-03  -4.67606156E-04   7.30678716E-04  -6.71742003E-03  -8.85684745E-03  -1.34072899E-02  -1.74440726E-02  -1.41242560E-02  -1.86942800E-02  -2.47024469E-02  -2.96673621E-02  -3.23796466E-03  -3.36397964E-02  -2.35877083E-02  -4.27632751E-02  -6.25191708E-02  -8.20361416E-02  -1.22886585E-01  -1.57411167E-01  -1.30962759E-01  -1.70917185E-01  -2.18352523E-01  -2.35087253E-01  -1.71500949E-01  -3.55354383E-02  -7.27243318E-02  -5.60725323E-02   5.09360986E-02   6.66545251E-02   9.92504960E-02   1.26012085E-01   1.06414185E-01   1.37723345E-01   1.72502725E-01   1.74277793E-01   1.55193127E-01   1.37724503E-02   1.37276035E-01   4.69241715E-02\nCm   5.35664288E-02   6.35041557E-02   7.65478479E-02   8.35853839E-02   5.46698104E-02   3.71792576E-02   8.32219178E-02   4.51337286E-01   4.70078247E-02   1.02527942E-01   1.34719749E-01   2.12838599E-01   6.23084268E-02   8.45365051E-02   1.36303700E-01   1.94859725E-01   1.30086764E-01   1.83627929E-01   2.88229330E-01   6.19252698E-01   9.59697269E-02   5.37352985E-02   2.97436457E-01   1.82901218E-01  -3.95248720E-02  -5.11815545E-02  -7.44861174E-02  -9.14181284E-02  -8.14575169E-02  -1.01874756E-01  -1.17883576E-01  -9.25121869E-02  -4.45035739E-02  -3.34882141E-02  -5.23952913E-02  -4.94862907E-02  -5.30580182E-02  -6.81119376E-02  -9.72735342E-02  -1.16104902E-01  -1.07726034E-01  -1.30657237E-01  -1.41083052E-01  -8.90073869E-02  -6.51354247E-02  -3.18647043E-02  -9.13986211E-02  -6.77504051E-02   3.10852265E-02   3.86586021E-02   5.15552041E-02   5.56377817E-02   5.83570647E-02   6.23220288E-02   5.10100642E-02   1.36013118E-02   4.28415135E-02   5.58696793E-02   7.81787747E-02   7.14071756E-02\nCm  -2.11478166E-02  -2.60977510E-02  -2.36081528E-02  -5.59981449E-03  -1.65362458E-02   1.89794034E-02   3.32941534E-02  -4.26590489E-02  -8.62356908E-03  -1.83859672E-02  -1.28516369E-02  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5.59482041E-02   8.30815059E-02   1.06316046E-01   4.56355516E-02   5.93520116E-02   8.71987246E-02   1.08530869E-01   9.46419650E-02   1.20102784E-01   1.43700539E-01   1.25408006E-01   5.41772696E-02   3.62524502E-02   8.11377098E-02   6.28910487E-02  -2.20500138E-02  -2.79383718E-02  -3.87863571E-02  -4.44033421E-02  -4.35281518E-02  -5.02300232E-02  -4.85940627E-02  -2.17437200E-02  -3.38157972E-02   5.13514101E-03  -3.70228287E-02  -1.44058279E-02   4.90417544E-02   5.98126975E-02   7.65013276E-02   7.76586184E-02   8.64105045E-02   8.45139443E-02   5.74210614E-02   8.64113715E-03   4.01968421E-02   4.19260843E-02   7.14382007E-02   6.04712475E-02   4.68933505E-02   4.80565641E-02   4.25495577E-02   2.53630753E-02   3.43887615E-02   1.25155644E-02   1.13313613E-03   3.84800547E-07   5.42917779E-03   8.48994384E-02   5.49354476E-02   1.11565152E-01\nCm   2.89792452E-02   3.28373940E-02   3.69037873E-02   3.92999969E-02   3.14341114E-02   4.05352147E-02   5.29758550E-02   6.26138048E-02   2.17578938E-02   4.17554075E-02   2.13164388E-02   2.63356997E-02   2.27054472E-02   3.00645726E-02   4.59377938E-02   6.06044214E-02   4.78496984E-02   6.40823233E-02   8.71596063E-02   1.15034620E-01   5.11536911E-02   1.11821290E-02   2.53132810E-02   1.24354493E-02  -5.06982423E-02  -6.52591300E-02  -9.37486091E-02  -1.12872648E-01  -1.03450667E-01  -1.26705361E-01  -1.39847630E-01  -9.45265892E-02  -8.09681837E-02  -2.16319409E-02  -3.23235782E-02  -2.21111243E-02   5.51412043E-02   6.94512516E-02   9.51856957E-02   1.06927927E-01   1.07249161E-01   1.20829664E-01   1.10954089E-01   4.22203527E-02   1.29830879E-01   3.19686602E-02   7.48811560E-02   5.10897061E-02  -4.59144217E-03  -5.38147406E-03  -6.32345100E-03  -5.67278289E-03  -6.91137607E-03  -5.54802368E-03  -2.49995056E-03  -1.07605133E-04   1.95942339E-03   2.84400296E-03  -1.34957033E-02  -6.44758435E-03\nCm   3.40853124E-02   6.70174704E-02   1.18392990E-01   1.31432701E-01   1.52255967E-01   1.41265921E-01   8.68693173E-02   2.05201162E-02   6.60018030E-02   3.89512025E-02   1.88039036E-01   2.19006643E-01   5.22143313E-03   6.81422811E-03   1.00867311E-02   1.26946620E-02   1.08756203E-02   1.39560682E-02   1.71351954E-02   1.62394224E-02  -9.98539433E-03   4.88177393E-02   7.54014249E-02   1.19415734E-01  -3.06864595E-02  -3.82614420E-02  -5.13098608E-02  -5.58262085E-02  -5.80486133E-02  -6.26876593E-02  -5.25474858E-02  -1.50806615E-02  -6.37604374E-02  -4.52529707E-03  -4.03541396E-02  -1.71276257E-02   5.95270048E-02   7.32717197E-02   9.55802648E-02   9.98634182E-02   1.08209455E-01   1.10408896E-01   8.20175753E-02   1.62279710E-02   7.27523728E-02   6.54418172E-02   7.98116519E-02   8.56235014E-02   5.05629781E-02   6.03851138E-02   7.38433465E-02   7.02066037E-02   8.23241545E-02   7.27344918E-02   3.99636823E-02   3.14438273E-03   2.86197101E-02   7.81328237E-02   1.59772244E-01   1.90102445E-01\nCm   9.50220255E-02   1.16620136E-01   1.60938974E-01   1.99553054E-01   1.55037495E-01   1.81286219E-01   2.49637819E-01   5.42962006E-01   1.41768691E-01   7.63749609E-02   1.73094191E-01   1.74460242E-01   7.50116715E-02   1.01292015E-01   1.61616228E-01   2.27443410E-01   1.57418530E-01   2.20447355E-01   3.37647947E-01   6.65071331E-01   2.03163472E-01   5.61880586E-02   2.69667776E-01   1.72094489E-01  -3.05960653E-02  -4.03400876E-02  -6.10642234E-02  -7.94467509E-02  -6.43317150E-02  -8.51437791E-02  -1.12498533E-01  -1.35071750E-01  -1.07275747E-01   2.38532765E-02  -5.43006617E-02   3.64028296E-03   5.59057719E-03   7.23672216E-03   1.05235101E-02   1.29006064E-02   1.15152575E-02   1.43836643E-02   1.65969132E-02   1.29086053E-02   3.23976129E-02   2.37517670E-02  -1.35266156E-02   1.08387015E-03   4.19032014E-02   4.66119742E-02   4.90341956E-02   3.74696054E-02   4.90574732E-02   2.95051591E-02   7.36744431E-03   5.31112957E-05   2.11037206E-02   1.00991635E-01   6.91322403E-02   1.68678962E-01\nCm   2.98475804E-02   2.70337679E-02   2.65949301E-02   3.33795040E-02   2.11882649E-02   3.77941106E-02   6.22615304E-02   6.25276748E-02   3.03168266E-02   2.94972859E-02   1.42604625E-03   7.06777314E-03   4.41659537E-02   5.66123671E-02   8.05891532E-02   9.57320374E-02   8.94140543E-02   1.07855181E-01   1.15047925E-01   6.98512710E-02   3.96559176E-02   2.95896694E-02   6.36285473E-02   4.68959721E-02   2.72005454E-02   3.45121015E-02   4.80561510E-02   5.52584684E-02   5.38717008E-02   6.25065689E-02   6.11971678E-02   2.84203703E-02   4.40697727E-02   5.25836253E-03   4.59063316E-02   1.77229176E-02  -1.06365681E-02  -1.34756761E-02  -1.87040295E-02  -2.14059520E-02  -2.09922843E-02  -2.42148543E-02  -2.34060561E-02  -1.04451953E-02  -1.30064189E-02  -1.61558155E-03  -4.45436096E-03   4.31328619E-03  -5.67964032E-02  -7.06670424E-02  -9.43369178E-02  -1.01958158E-01  -1.06774445E-01  -1.14261375E-01  -9.39295608E-02  -2.53834221E-02  -9.04195003E-02  -3.07383214E-02  -1.10307963E-01  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4.70039228E-02   2.01622477E-02   2.20982201E-02   2.25319211E-02   1.64582710E-02   2.18204826E-02   1.20335876E-02   2.51987869E-03   1.06806489E-05   3.77296826E-03   4.05682484E-02   2.09457145E-02   3.28895076E-02\nCm  -1.21267003E-02  -3.80482477E-03   8.42970402E-03   5.52045623E-03   2.48981705E-02   4.24520841E-03  -3.47764770E-02  -6.87598673E-02   6.95934662E-03  -2.94769070E-02   2.22175876E-02   1.15165112E-02  -5.51984439E-02  -7.21122703E-02  -1.06988395E-01  -1.35107729E-01  -1.15110862E-01  -1.48206892E-01  -1.83385175E-01  -1.78169778E-01  -8.27082263E-02  -2.37960944E-02  -1.09972187E-01  -6.18272313E-02   1.82940686E-02   2.37618534E-02   3.48121223E-02   4.31480270E-02   3.78721773E-02   4.78552696E-02   5.66961680E-02   4.79507676E-02   2.72851890E-02   4.34388297E-03   1.59993870E-02   5.20914625E-03   5.26976759E-02   6.77094358E-02   9.68850845E-02   1.15970419E-01   1.07173351E-01   1.30407138E-01   1.41832940E-01   9.15338354E-02   4.90302211E-02   3.81135625E-02   7.44626832E-02   6.93294293E-02  -2.31080342E-02  -2.94771398E-02  -4.15239656E-02  -4.85698762E-02  -4.63199388E-02  -5.48699400E-02  -5.62244257E-02  -3.01001061E-02  -5.08891411E-02  -4.17706989E-03  -2.27422918E-02  -6.84239176E-03\nCm   1.66638510E-02   2.59743977E-02   5.65981738E-02   9.48846748E-02   6.83808166E-02   1.15033748E-01   1.55338564E-01   1.75790329E-01   7.17189628E-02   1.08768476E-02   2.57270600E-02   1.68641650E-02   2.03787241E-02   2.72469057E-02   4.25310381E-02   5.79241740E-02   4.29954150E-02   5.89930322E-02   8.53624230E-02   1.38371809E-01   5.44876796E-02   1.94430428E-02   5.30274180E-02   3.05455190E-02   2.04594780E-02   2.61298830E-02   3.69043813E-02   4.33318667E-02   4.11153641E-02   4.89263723E-02   5.06398659E-02   2.79750454E-02   4.40158359E-02   1.31722014E-02   2.28804243E-02   1.36937040E-02   9.53002244E-03   1.20764067E-02   1.67697678E-02   1.92055925E-02   1.88182110E-02   2.17257903E-02   2.10397825E-02   9.44451300E-03   2.46518689E-02  -9.93681527E-04  -1.24312560E-02  -1.48908988E-02  -2.70884204E-02  -2.83326095E-02  -2.61826698E-02  -1.65973812E-02  -2.24728868E-02  -9.31207521E-03  -1.09461868E-03  -8.15047072E-07  -1.27412853E-02  -1.16666074E-02  -2.64495834E-02  -2.60029772E-02\nCm   1.52141454E-02   2.86933421E-02   6.14640324E-02   8.92404885E-02   8.70059675E-02   1.19385995E-01   1.00162561E-01   2.32678228E-02   4.08658895E-02   3.10518259E-02   6.66364978E-02   7.50845266E-02   1.63401303E-02   2.06929691E-02   2.86955717E-02   3.27971817E-02   3.22164589E-02   3.71004638E-02   3.57315979E-02   1.57668492E-02   4.68605889E-02   2.40820704E-02   4.33672911E-02   3.76626215E-02   2.68767882E-02   3.28524987E-02   4.22188423E-02   4.31561258E-02   4.77235624E-02   4.71609936E-02   3.27467654E-02   5.26735930E-03   3.28753836E-02   1.61533098E-02   1.00558621E-02   7.95724616E-03   5.77885638E-02   6.81752817E-02   8.12270542E-02   7.43532926E-02   8.94650844E-02   7.42905570E-02   3.58980600E-02   1.91058931E-03   3.22603273E-02   5.70850081E-02   8.07698813E-02   9.53325640E-02   2.59520633E-02   3.02323647E-02   3.50666588E-02   3.08711475E-02   3.80238630E-02   2.95568242E-02   1.24648728E-02   4.38816575E-04   1.01108254E-02   3.65002447E-02   3.89538610E-02   5.72684619E-02\nCm   1.72687020E-04  -7.38324181E-03  -3.06072257E-02  -6.31152528E-02  -3.33071646E-02  -7.48369267E-02  -1.33342034E-01  -1.68758474E-01  -4.81851521E-02   5.10390816E-03  -9.23932096E-03  -5.52534389E-03  -2.07190933E-02  -2.76267681E-02  -4.28663536E-02  -5.78612881E-02  -4.37256036E-02  -5.96125740E-02  -8.48252836E-02  -1.29989592E-01  -8.10987216E-02  -1.07745891E-02  -1.93162584E-02  -5.58968133E-03  -1.80728886E-02  -2.32626904E-02  -3.34155600E-02  -4.02273388E-02  -3.68756166E-02  -4.51589372E-02  -4.98281952E-02  -3.36487327E-02  -2.99634403E-02  -1.12210368E-02  -2.19332335E-02  -1.30073000E-02  -2.59387512E-02  -3.19185252E-02  -4.16101191E-02  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1.82343420E-02  -5.51750005E-03   2.11937929E-02\nCm   2.89247164E-02   4.42769662E-02   7.78188500E-02   1.28658946E-01   4.99093150E-02   9.85721456E-02   2.35219491E-01   6.86980861E-01   1.11295956E-01   6.65660886E-02   1.24343655E-01   1.37810721E-01   7.77760321E-02   1.05575536E-01   1.70418147E-01   2.44041861E-01   1.62272352E-01   2.29239013E-01   3.60730086E-01   7.82082775E-01   1.72313639E-01   6.24583976E-02   2.63029065E-01   1.68630732E-01  -4.77072091E-02  -6.15344296E-02  -8.87902555E-02  -1.07604589E-01  -9.76951653E-02  -1.20525694E-01  -1.35213972E-01  -9.62165290E-02  -1.12869139E-01  -2.25427693E-02  -5.80741044E-02  -4.11236835E-02  -7.52796552E-03  -9.70066650E-03  -1.39687555E-02  -1.68774497E-02  -1.53907158E-02  -1.89240872E-02  -2.10710725E-02  -1.46419266E-02  -1.01448040E-02  -2.88263450E-03  -1.91091082E-02  -2.22247184E-02   2.36209453E-02   2.96649264E-02   4.04039295E-02   4.49736710E-02   4.55930421E-02   5.07574524E-02   4.54225008E-02   1.59566700E-02   3.60447472E-02   6.91574563E-02   4.79168577E-02   1.04177373E-01\nCm   2.89635861E-02   1.81180531E-02  -1.80286225E-02  -6.51296920E-02  -3.41542755E-02  -7.83453352E-02  -1.35149888E-01  -2.24633595E-01  -6.47825673E-02   3.74268816E-02  -3.04117906E-02   4.81904652E-03  -7.09977642E-02  -9.34476843E-02  -1.40922944E-01  -1.82322019E-01  -1.49101216E-01  -1.96362932E-01  -2.56364556E-01  -2.96077928E-01  -1.90954867E-01  -4.03178720E-02  -1.13052275E-01  -6.39448448E-02   2.40548069E-03   3.12005941E-03   4.55708448E-03   5.62283398E-03   4.96980965E-03   6.25043630E-03   7.32585800E-03   5.98747827E-03  -1.49075212E-02  -1.68225921E-03   2.43457025E-02   1.27330993E-02  -5.59057719E-03  -7.23672216E-03  -1.05235101E-02  -1.29006064E-02  -1.15152575E-02  -1.43836643E-02  -1.65969132E-02  -1.29086053E-02  -1.96086423E-02  -2.71608797E-02   5.34299936E-03  -2.05541095E-02   5.02592416E-02   6.43996941E-02   9.16033379E-02   1.08691012E-01   1.01678167E-01   1.22486438E-01   1.30270367E-01   7.83653422E-02   9.00824803E-02   1.92773989E-02   6.05323041E-02   2.92912191E-02\nCm   1.86676858E-02   2.36819571E-02   1.96471480E-02  -4.61044028E-04   1.75899109E-02  -6.09301361E-03  -3.90203517E-02  -9.98514560E-02  -4.80568757E-03   9.21456935E-03  -7.11918719E-03  -1.32602327E-02  -5.00770086E-02  -6.59824469E-02  -9.97383966E-02  -1.29490016E-01  -1.05246899E-01  -1.39038038E-01  -1.82886117E-01  -2.16406748E-01  -1.46968703E-01   3.95579539E-04  -1.29592532E-01  -5.53762468E-02   4.25436024E-02   5.53401137E-02   8.13345764E-02   1.01287524E-01   8.82496862E-02   1.12053279E-01   1.34241979E-01   1.17634310E-01   9.94092069E-02   1.21728065E-02   6.15927942E-02   2.99240706E-02  -1.22785040E-02  -1.56828774E-02  -2.21537439E-02  -2.60193178E-02  -2.46793346E-02  -2.93773989E-02  -3.04281032E-02  -1.68472722E-02  -3.83418491E-02   4.22243569E-04  -8.60432306E-03   2.24770968E-03   1.87295429E-02   2.36425048E-02   3.25582619E-02   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1.28500238E-01   1.34369926E-01   7.66493905E-02   8.53601879E-02   3.29150717E-02   9.15035829E-02   5.19364688E-02\nCm   3.30902434E-02   3.18565746E-02   2.55559769E-02   1.85305197E-02   1.32096251E-02   1.53400531E-02   4.58013349E-02   1.96087950E-02   1.30724847E-02   4.29664645E-02   3.48118979E-02   5.23584369E-02  -2.94965256E-02  -4.01680110E-02  -6.53027345E-02  -9.45219609E-02  -6.12530443E-02  -8.69277661E-02  -1.38916676E-01  -3.18610809E-01  -1.13713649E-01   1.04972295E-02  -3.97910182E-02   5.99298895E-03   7.22556688E-02   9.57247559E-02   1.46432847E-01   1.93515359E-01   1.52304020E-01   2.04258214E-01   2.78784961E-01   3.72176066E-01   1.68237553E-01   3.12027901E-02   1.36096739E-01   6.31766924E-02  -3.95412146E-03  -5.05753638E-03  -7.16603253E-03  -8.45418155E-03  -7.97072332E-03  -9.53813799E-03  -9.99515853E-03  -5.73988660E-03  -1.55924975E-02  -8.18801901E-03   1.87068198E-03  -4.93341439E-03  -4.49238015E-02  -5.63246067E-02  -7.64395537E-02  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3.41187823E-02   7.59245300E-02   5.81607158E-02  -4.21711172E-02  -4.69967723E-02  -4.96321695E-02  -3.81410288E-02  -4.98473460E-02  -3.03021749E-02  -7.73253674E-03  -5.95201760E-05  -3.15663176E-02  -3.53777602E-02  -4.78827958E-02  -4.43768110E-02\nCm   2.69663299E-03   9.08817568E-03   3.07038284E-02   5.58593927E-02   3.78402413E-02   5.48868488E-02   8.68341342E-02   1.92548859E-01   4.26739445E-02   1.83823682E-02   7.29451064E-02   7.98682658E-02   1.73855806E-02   2.32461214E-02   3.62899052E-02   4.94321113E-02   3.66800816E-02   5.03335096E-02   7.28536671E-02   1.18212616E-01   6.68864778E-02   1.14057688E-02   1.03658217E-02   5.58758797E-04   5.18835068E-02   6.83728471E-02   1.03385225E-01   1.34289377E-01   1.09054668E-01   1.44129497E-01   1.89778060E-01   2.25312385E-01   1.20343689E-01   5.26665224E-02   1.36497602E-01   9.87455365E-02  -7.16458118E-02  -9.27334497E-02  -1.34824530E-01  -1.65230762E-01  -1.47552367E-01  -1.84249462E-01  -2.12449046E-01  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1.44003299E-01   1.65361091E-01   1.26661675E-01   1.28034248E-01   2.96245376E-02   1.09281683E-01   5.58003438E-02  -2.07917563E-02  -2.56784153E-02  -3.37380555E-02  -3.56227412E-02  -3.82063536E-02  -3.95741420E-02  -3.03507461E-02  -6.62370390E-03  -2.77312335E-02  -9.60775456E-04  -7.02399468E-03  -6.64145821E-03\nCm   7.54684043E-03  -2.31528185E-03  -3.52498030E-02  -7.45910868E-02  -5.55782593E-02  -9.49623900E-02  -1.15576695E-01  -1.51173621E-01  -7.31458411E-02   6.33631712E-02  -6.83794108E-02   3.16933370E-02  -1.73855806E-02  -2.32461214E-02  -3.62899052E-02  -4.94321113E-02  -3.66800816E-02  -5.03335096E-02  -7.28536671E-02  -1.18212616E-01  -5.74004907E-02  -4.73474032E-02  -5.52181549E-02  -8.14403727E-02  -6.00923072E-02  -7.84526625E-02  -1.16223681E-01  -1.46449773E-01  -1.25219655E-01  -1.60877818E-01  -1.98071752E-01  -1.89384856E-01  -6.77514571E-02  -4.43488442E-02  -1.85422984E-02  -3.61624574E-02   6.11118142E-02   7.93917792E-02   1.16359198E-01   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5.11903525E-02   2.96342773E-02   2.73403635E-03   3.35745265E-02   1.94723390E-02   6.94112450E-02   5.22232632E-02   5.11560492E-02   6.04047500E-02   7.21061351E-02   6.61874577E-02   7.94979198E-02   6.63188930E-02   3.23526879E-02   1.77247424E-03   4.44842268E-02   1.65528783E-02   1.54218335E-02   8.73643435E-03  -2.66525311E-02  -3.05646830E-02  -3.42915502E-02  -2.87648985E-02  -3.63199578E-02  -2.59391838E-02  -9.19427193E-03  -1.91148852E-04  -1.97362696E-02  -5.84419431E-02  -5.61741635E-02  -1.24502199E-01\nCm  -2.78403141E-02  -3.58308598E-02  -5.40000625E-02  -7.15500444E-02  -5.30812129E-02  -7.05381751E-02  -1.05652403E-01  -1.77474339E-01  -5.37830479E-02  -4.92722990E-03  -7.40104016E-02  -1.54115784E-02  -7.32546119E-02  -9.67541737E-02  -1.47025629E-01  -1.92384337E-01  -1.54189938E-01  -2.05084251E-01  -2.74259604E-01  -3.42480236E-01  -2.36256629E-01  -5.38819953E-02  -1.12747248E-01  -8.45053459E-02   3.99821669E-02   5.21546441E-02   7.71240501E-02   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2.57071129E-02   2.18399549E-02   3.30489425E-02   3.56435433E-02   4.61115391E-02   6.69684869E-02   8.19398290E-02   7.33493533E-02   9.14347905E-02   1.05018459E-01   8.04957274E-02   6.05944809E-02   2.82500048E-02   5.21993887E-02   4.14479567E-02   2.07917563E-02   2.56784153E-02   3.37380555E-02   3.56227412E-02   3.82063536E-02   3.95741420E-02   3.03507461E-02   6.62370390E-03   3.87990859E-02   3.50061211E-02   4.94432980E-02   4.59607827E-02  -6.17887776E-02  -7.34543132E-02  -8.89530814E-02  -8.33783183E-02  -9.87561773E-02  -8.52690923E-02  -4.46681040E-02  -3.03927270E-03  -8.01051207E-02  -2.21113490E-02  -2.29491902E-02  -1.98428410E-02\nCm  -2.45618424E-02  -2.66983663E-02  -3.90876657E-02  -5.58557582E-02  -4.65487080E-02  -6.83834393E-02  -7.72668789E-02  -7.33904065E-02  -3.80829388E-02  -3.49866835E-02  -2.23755058E-02  -1.97534269E-02  -3.50067901E-02  -4.55885615E-02  -6.71701025E-02  -8.39582657E-02  -7.27246324E-02  -9.26871319E-02  -1.12006402E-01  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2.17752294E-03   1.56621298E-03   2.80667423E-04  -4.56099228E-04   7.68589921E-03   6.57609557E-03   9.70150621E-03\nCm   8.40436741E-03   1.13873331E-02   1.11549978E-02  -1.48379894E-03   1.87851775E-02  -2.90322084E-03  -5.31593066E-02  -7.48157058E-02   1.50764309E-02  -1.25039930E-02   3.48580456E-03  -3.21874103E-02   2.79056645E-02   3.64878785E-02   5.42365874E-02   6.86824775E-02   5.82499611E-02   7.52006170E-02   9.36411828E-02   9.28434665E-02   9.83337218E-02   1.41974053E-02   5.73790322E-02   2.03133397E-02  -6.72416621E-02  -8.73167198E-02  -1.27851493E-01  -1.58335524E-01  -1.39152909E-01  -1.75683874E-01  -2.07733357E-01  -1.74601049E-01  -1.76417019E-01  -1.62341125E-02  -1.59474808E-01  -5.57130770E-02   2.03018046E-02   2.47702956E-02   3.17079901E-02   3.22269008E-02   3.58201976E-02   3.50978208E-02   2.39378266E-02   3.64479628E-03   1.16482473E-02   2.24961446E-02   2.25601633E-02   2.02857752E-02   4.36380604E-02   5.23156643E-02   6.45016833E-02   6.20617980E-02   7.21365913E-02   6.49604535E-02   3.71355164E-02   3.29709105E-03   5.42643781E-02   1.88493127E-02   3.12489884E-02   1.68784252E-02\nCm   1.88410086E-02   4.89146404E-02   1.26171639E-01   2.08539156E-01   1.65720311E-01   2.66294449E-01   3.26412700E-01   2.37628462E-01   7.44155253E-02   4.54705728E-03   2.74463979E-01   2.49397631E-01   5.93708920E-02   7.66948530E-02   1.11030977E-01   1.35214795E-01   1.21889078E-01   1.51174244E-01   1.71646437E-01   1.26862884E-01   7.65652173E-02   9.42362565E-02   2.33950228E-01   2.92640523E-01   6.70583092E-02   8.61441492E-02   1.23211174E-01   1.47390548E-01   1.36329541E-01   1.65766921E-01   1.80006185E-01   1.15593711E-01   1.13769135E-01   9.00953300E-02   1.79924461E-01   2.36379556E-01  -1.89932006E-02  -2.33718416E-02  -3.04685142E-02  -3.18045357E-02  -3.44930390E-02  -3.51473832E-02  -2.60359884E-02  -5.10715904E-03  -2.85270490E-02   3.54231215E-03  -1.61600123E-02  -5.57902707E-04   1.05055810E-03   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1.15636013E-01   3.96179354E-02   5.15047868E-02   7.56028211E-02   9.39749720E-02   8.21171979E-02   1.04069192E-01   1.24133127E-01   1.07272518E-01   5.34073479E-02   8.96381752E-02   9.75202960E-02   1.89284943E-01\nCm   4.06572777E-02   5.71050752E-02   9.89870833E-02   1.50568820E-01   9.19409709E-02   1.38618864E-01   2.43944497E-01   5.42313209E-01   9.32664367E-02   3.67755905E-02   2.58583852E-01   1.59373228E-01   5.62848638E-02   7.60523835E-02   1.21515596E-01   1.71369403E-01   1.18049288E-01   1.65503156E-01   2.54352374E-01   5.06986327E-01   1.35737664E-01   8.88536789E-02   1.79822871E-01   1.96500448E-01  -4.63632101E-03  -6.20127765E-03  -9.68811617E-03  -1.32112688E-02  -9.78102859E-03  -1.34321504E-02  -1.94817087E-02  -3.18293834E-02  -1.19451064E-02   4.32611171E-02  -7.28944747E-03   5.74933634E-02   5.84137313E-02   7.61656394E-02   1.12527286E-01   1.41218387E-01   1.21540220E-01   1.55526560E-01   1.89705591E-01   1.76054967E-01   1.21233028E-01   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3.40380678E-02   3.52371207E-02   4.00379290E-02   6.64084197E-02   8.63358693E-02   1.26738515E-01   1.57551557E-01   1.37651907E-01   1.74466125E-01   2.08147243E-01   1.79999293E-01   1.60539942E-01   5.37917627E-02   6.49296660E-02   5.63993720E-02   1.75143928E-02   2.19114358E-02   2.95974414E-02   3.25466168E-02   3.34512949E-02   3.66457140E-02   3.16764701E-02   9.99585786E-03   2.52867241E-02   3.86157104E-02   2.54404002E-02   3.58728886E-02\nCm   1.13545811E-02   1.60098043E-02   1.83916042E-02   1.12124674E-02   1.46519567E-02  -4.97115548E-03  -1.12455933E-03   4.92574378E-02   1.75371620E-02   2.74430266E-02   2.59953115E-02   7.47753396E-02   1.00369169E-02   1.32011386E-02   1.98764967E-02   2.56554898E-02   2.10667423E-02   2.76861626E-02   3.59638767E-02   4.08605250E-02   9.64632819E-03   2.04962320E-02   7.10009124E-02   6.27531907E-02   4.87624109E-02   6.25873898E-02   8.93522128E-02   1.06594641E-01   9.89738694E-02   1.19970902E-01   1.29372597E-01   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4.78391642E-02   1.23266966E-01   7.68293322E-02  -2.36310443E-02  -3.00012606E-02  -4.18297259E-02  -4.81915706E-02  -4.68681547E-02  -5.45096121E-02  -5.36456774E-02  -2.53199207E-02  -4.14953650E-02  -8.76942454E-03  -2.17557589E-02  -1.20793169E-02  -3.44551814E-02  -4.17772477E-02  -5.27690843E-02  -5.25965352E-02  -5.94499745E-02  -5.65601573E-02  -3.62634399E-02  -4.56994213E-03  -1.84470869E-02  -2.58560776E-02  -1.17771076E-02  -1.63291642E-02\nCm   7.99783584E-03   1.66982610E-02   3.18417602E-02   4.80114676E-02   2.36412223E-02   4.26775961E-02   1.07553644E-01   1.53724572E-01   4.85207596E-02   1.47001698E-02   2.17121280E-02   2.67284300E-02   2.90830524E-02   3.81402081E-02   5.70608271E-02   7.29560788E-02   6.08898691E-02   7.93288545E-02   1.00929587E-01   1.07234545E-01   5.13288806E-02   2.71133169E-02   4.27781089E-02   3.53447249E-02   1.63986090E-02   2.13434844E-02   3.14087599E-02   3.91873971E-02   3.40423191E-02   4.33069649E-02   5.21113077E-02   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9.37669668E-02   3.94185017E-02   6.60799240E-02   1.53726518E-01   5.54723407E-01   1.02614172E-01   2.37473593E-02   9.58109417E-02   3.64877483E-02   7.87982545E-02   1.06722661E-01   1.71410315E-01   2.43627888E-01   1.64862486E-01   2.32067098E-01   3.61055886E-01   7.51585074E-01   3.89981573E-01   6.28744748E-02   1.37085020E-01   1.14049180E-01  -3.17370596E-02  -4.17575733E-02  -6.29228569E-02  -8.13131668E-02  -6.66324548E-02  -8.76620939E-02  -1.14162145E-01  -1.30780643E-01  -8.93357422E-02  -9.98651415E-03  -5.18659768E-02  -2.41920280E-02  -3.97479190E-02  -5.12012745E-02  -7.36706893E-02  -8.89074933E-02  -8.12118468E-02  -9.97276539E-02  -1.10720179E-01  -7.62367354E-02  -7.80785797E-02  -9.06000934E-03  -4.53561970E-02  -2.74117293E-02   4.20758090E-03   5.41120537E-03   7.75850323E-03   9.31455067E-03   8.57182255E-03   1.04651759E-02   1.14680712E-02   7.57838970E-03   1.57234683E-02   1.09709146E-03  -5.80926680E-03  -1.01022599E-02\nCm   5.54076919E-02   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3.53498344E-02\nCm   2.07582120E-03   8.41874280E-03   2.89533156E-02   5.26574243E-02   3.27672097E-02   3.47040368E-02   6.17713856E-02   3.12477095E-01   2.85264299E-03  -3.95767274E-03   1.21189127E-01   1.11833174E-01   6.93823333E-02   9.30450302E-02   1.46204254E-01   2.01099768E-01   1.46255675E-01   2.02019073E-01   2.97613056E-01   5.12621791E-01   1.74391841E-01   5.69323749E-02   2.43889987E-01   1.77679296E-01  -7.01060056E-02  -9.11039371E-02  -1.33613052E-01  -1.65867965E-01  -1.45231080E-01  -1.83811509E-01  -2.18582085E-01  -1.87069413E-01  -1.04730325E-01  -5.09363181E-02  -1.26759749E-01  -8.60737290E-02  -3.14634136E-03  -3.99011405E-03  -5.55008690E-03  -6.37188409E-03  -6.22423166E-03  -7.20788481E-03  -7.02699047E-03  -3.22050390E-03  -4.87373557E-03   1.93782924E-02  -5.51249457E-03   1.39407045E-02  -1.78992233E-02  -2.24018707E-02  -3.02860698E-02  -3.33461455E-02  -3.42247176E-02  -3.75565661E-02  -3.25822504E-02  -1.03980942E-02  -2.68101228E-02   7.32483394E-03  -6.78825540E-03   1.38852419E-02\nCm   2.46763239E-02   4.16547058E-02   8.23279050E-02   1.26452300E-01   8.84684733E-02   1.27227625E-01   1.82253364E-01   3.56284870E-01   9.81791515E-02   1.43842314E-02   1.74904918E-01   1.27959775E-01   2.64263666E-02   3.61163113E-02   5.91870358E-02   8.67060005E-02   5.45300588E-02   7.77243069E-02   1.26232255E-01   3.07572814E-01   4.53491035E-02   5.11371898E-02   5.88739832E-02   6.89891524E-02   5.56697115E-02   7.11886414E-02   1.00818387E-01   1.18856183E-01   1.12167638E-01   1.34112583E-01   1.40277657E-01   8.00891387E-02   7.17997893E-02   7.86436730E-02   1.44104254E-01   1.37996594E-01  -2.29053296E-02  -2.88053751E-02  -3.93484370E-02  -4.39879541E-02  -4.43721776E-02  -4.96768951E-02  -4.49989700E-02  -1.64142779E-02  -6.26479666E-02  -1.22243955E-03  -2.60411820E-02  -4.78996332E-03  -5.63407101E-02  -6.97232185E-02  -9.20054800E-02  -9.77646656E-02  -1.04192105E-01  -1.08896788E-01  -8.51269067E-02  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9.08048691E-02   5.32462875E-02   5.10860421E-03   5.53951173E-02   2.03441660E-02   4.71387763E-02   3.64983203E-02\nCm  -1.81106181E-02  -1.11737445E-02  -5.89602629E-03  -1.73082155E-02   1.01536197E-02  -1.06818559E-02  -6.82732573E-02  -1.86266631E-01  -4.11077300E-03   1.01074963E-02   6.60372875E-03   3.40685961E-02  -2.22344348E-02  -2.93477351E-02  -4.45318171E-02  -5.81452388E-02  -4.67824385E-02  -6.21096817E-02  -8.26864843E-02  -1.01750083E-01  -7.68856437E-02  -1.57165317E-02  -2.63806594E-02  -1.18252976E-02  -3.74269778E-02  -4.92314114E-02  -7.41433878E-02  -9.57334954E-02  -7.85630151E-02  -1.03280806E-01  -1.34261068E-01  -1.52913409E-01  -5.99527583E-02  -6.00830966E-03  -2.92962684E-02  -1.38775025E-02   6.80904867E-02   8.63169976E-02   1.19962199E-01   1.37553982E-01   1.34575370E-01   1.55603393E-01   1.51188484E-01   6.85679468E-02   1.29359985E-01   2.46665396E-02   8.52037934E-02   4.51621028E-02  -5.12405842E-03  -6.04641042E-03  -7.20743721E-03  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2.29080718E-02   3.79871992E-02   5.66476529E-02   3.40086046E-02   4.87074049E-02   8.08241500E-02   2.14203826E-01   5.88521665E-02   7.87128564E-04   6.99690551E-02   7.62972465E-03   5.78351927E-02   7.80764100E-02   1.24499158E-01   1.75049414E-01   1.21401840E-01   1.69925337E-01   2.59883153E-01   5.09266960E-01   1.66960645E-01   4.58104874E-02   1.25658608E-01   8.18961188E-02  -4.93369465E-02  -6.36047059E-02  -9.16778902E-02  -1.10925924E-01  -1.00945873E-01  -1.24316419E-01  -1.38912409E-01  -9.76140533E-02  -4.09121071E-02  -3.93286582E-02  -9.40817259E-02  -8.72310856E-02   1.61629536E-03   1.99601714E-03   2.62206958E-03   2.76787326E-03   2.96933056E-03   3.07457343E-03   2.35627099E-03   5.13074687E-04   1.71899886E-03   1.66569649E-02   3.12544024E-03   1.13597295E-02\nCm   6.67880646E-03   3.15439342E-02   8.50210797E-02   1.33739973E-01   1.06287374E-01   1.56437747E-01   2.02684764E-01   2.05032523E-01   1.00440175E-01   3.94887092E-02   1.92601006E-01   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2.74771622E-02   2.24085887E-02   2.21502857E-02  -5.66516343E-02  -7.42719533E-02  -1.11043778E-01  -1.41838407E-01  -1.18575259E-01  -1.54341861E-01  -1.95943617E-01  -2.06737623E-01  -1.07859020E-01  -2.81352952E-02  -4.01671699E-02  -3.33392880E-02   3.48596983E-02   4.47915842E-02   6.40968721E-02   7.67318019E-02   7.09001336E-02   8.62812064E-02   9.38672645E-02   6.06321622E-02   7.56030777E-02   2.60449190E-02   5.64936412E-02   4.77876441E-02   2.36310443E-02   3.00012606E-02   4.18297259E-02   4.81915706E-02   4.68681547E-02   5.45096121E-02   5.36456774E-02   2.53199207E-02   4.95695606E-02   3.02376125E-02   3.46002612E-02   4.44698186E-02   5.06812501E-02   5.72176616E-02   6.21033320E-02   4.96533732E-02   6.39915712E-02   4.18886028E-02   1.24272408E-02   1.50803155E-04   4.15224265E-02   3.28092031E-02   2.16431390E-02   2.07027719E-02\nCm  -3.46793778E-02  -3.88350948E-02  -3.40343585E-02  -1.39963548E-02  -2.49333138E-02   8.44670047E-04   1.67342138E-02   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1.35226793E-01   1.44054919E-01   8.71018034E-02   8.62015086E-02   1.01143449E-01   1.75950277E-01   2.68995900E-01\nCm   4.81421602E-02   4.78662757E-02   4.77467881E-02   4.60854113E-02   4.28829929E-02   5.04643527E-02   5.81583195E-02   7.74201264E-03   4.16197690E-02   4.28572509E-02   2.80905687E-02   2.77901987E-02  -1.79718117E-02  -2.35862991E-02  -3.53447625E-02  -4.53004507E-02  -3.76526038E-02  -4.91655926E-02  -6.28893033E-02  -6.79828225E-02  -4.77499886E-02   5.94517340E-03  -1.66489735E-02  -4.35749337E-03   6.88240287E-02   8.76320110E-02   1.22954928E-01   1.42976367E-01   1.37405159E-01   1.61625907E-01   1.63064557E-01   8.31642367E-02   1.42217253E-01   4.17715356E-02   8.20493926E-02   5.51137318E-02  -2.84005137E-02  -3.49251484E-02  -4.54663986E-02  -4.73632122E-02  -5.14671213E-02  -5.22889272E-02  -3.84927894E-02  -7.40729274E-03  -3.38946633E-02  -3.90710198E-03  -1.46723399E-02  -6.74560523E-03  -1.86107455E-02  -2.08111304E-02  -2.21366875E-02  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3.04162624E-02   3.61334940E-02   3.29353383E-02   3.97363826E-02   3.27633091E-02   1.56013574E-02   7.94179802E-04   2.32523104E-02   4.61372577E-02   3.19953108E-02   6.59654717E-02\nCm   2.47563030E-02   1.32456296E-02   2.18748795E-02   7.52255193E-02   1.95935959E-02   1.22690214E-01   2.14628824E-01   1.67338401E-01   6.34424002E-02   3.62888872E-02   2.51697741E-03  -2.09953852E-02   2.40699086E-02   3.10900856E-02   4.49988784E-02   5.47818419E-02   4.94073327E-02   6.12557804E-02   6.94940613E-02   5.12296151E-02   8.88582048E-02   1.75843829E-03   2.16635033E-02  -1.83339258E-03   5.58877515E-02   7.20250499E-02   1.03736847E-01   1.25377622E-01   1.14280664E-01   1.40566335E-01   1.56637738E-01   1.09116594E-01   1.36942919E-01   3.51199795E-02   6.52981921E-02   5.28528183E-02   7.49548687E-03   9.50722695E-03   1.32290726E-02   1.51961857E-02   1.48338945E-02   1.71897954E-02   1.67831731E-02   7.72729483E-03   1.14924680E-02   2.31284630E-02   2.24668733E-02   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5.59385865E-02   1.18701644E-01   9.78227057E-02   4.10994808E-02   4.94553176E-02   6.14592665E-02   5.98206417E-02   6.89218859E-02   6.32053052E-02   3.75280872E-02   3.74037774E-03   3.83672974E-02   4.56101672E-02   4.87392558E-02   6.75290034E-02\nCm   3.02238082E-02   4.58915500E-02   7.42331871E-02   8.99346884E-02   8.77412491E-02   1.00356345E-01   9.96602179E-02   6.11233604E-02   7.29485478E-02   3.51562052E-02   5.22116339E-02   5.77227761E-02   3.21818843E-02   4.18267487E-02   6.13618009E-02   7.62092179E-02   6.66805664E-02   8.44332397E-02   1.00512017E-01   8.63134456E-02   7.56430565E-02   3.27360988E-02   9.05429907E-02   4.62612325E-02  -2.94441859E-02  -3.81866471E-02  -5.57608085E-02  -6.87763936E-02  -6.08226835E-02  -7.64664623E-02  -8.95449702E-02  -7.29838527E-02  -6.61714776E-02  -5.05803687E-03  -3.58424869E-02  -1.38459176E-02   3.48585213E-02   4.45223989E-02   6.28893041E-02   7.38569603E-02   7.00607095E-02   8.33900219E-02   8.63547782E-02   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1.01545636E-01   1.66467520E-01   3.00089443E-02   8.16238823E-02   3.90166181E-02   4.09602510E-02   5.14306075E-02   7.00187938E-02   7.78886336E-02   7.90187751E-02   8.78963358E-02   7.85169275E-02   2.74298262E-02   7.37606506E-02   2.34522337E-02   4.32805438E-02   2.81867627E-02  -5.06812501E-02  -5.72176616E-02  -6.21033320E-02  -4.96533732E-02  -6.39915712E-02  -4.18886028E-02  -1.24272408E-02  -1.50803155E-04  -4.71563290E-02  -2.25369339E-02  -2.36744343E-02  -1.76797662E-02\nCm   3.28212562E-03   1.43227710E-02   2.38394549E-02   1.79668927E-02   2.71218982E-02   1.04594664E-02  -7.97607004E-03   6.88492941E-03   1.26964090E-02   2.98512254E-02   5.53357800E-02   1.05281352E-01   2.54736447E-02   3.35285643E-02   5.05624506E-02   6.54162315E-02   5.34967745E-02   7.04540424E-02   9.19823230E-02   1.06231271E-01   7.51426735E-02   1.49801492E-02   1.01985408E-01   6.61119259E-02  -1.42387283E-02  -1.85344696E-02  -2.72819885E-02  -3.40514123E-02  -2.95630570E-02  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1.80354302E-01   2.10719271E-01   1.53745196E-01   8.28287633E-02   1.00643232E-01   1.57939964E-01   1.32058035E-01   4.97578774E-02   6.38810557E-02   9.12485610E-02   1.08944078E-01   1.01042407E-01   1.22590028E-01   1.32466578E-01   8.37589206E-02   1.59095946E-01   6.51080569E-02   9.18897991E-02   8.38931499E-02   5.54047275E-02   7.09717213E-02   1.00886361E-01   1.19591729E-01   1.12021811E-01   1.34798344E-01   1.43013758E-01   8.53723193E-02   1.04743813E-01   6.97037149E-02   7.26979946E-02   9.66039207E-02  -1.83572844E-02  -2.28578542E-02  -3.05641018E-02  -3.31127670E-02  -3.45886737E-02  -3.71361129E-02  -3.07437693E-02  -8.49054481E-03  -1.56837856E-02   1.95348847E-02  -6.62308552E-03   7.53030464E-03  -4.33592695E-02  -5.28397738E-02  -6.74669619E-02  -6.83159702E-02  -7.61827066E-02  -7.42313023E-02  -5.00382119E-02  -7.35029693E-03  -2.71152418E-02  -6.66027880E-03  -1.03461741E-02  -6.48678731E-03\nCm  -1.75454801E-02  -2.60234076E-02  -3.78924829E-02  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1.12412125E-03   9.88930636E-04   1.24770405E-03   1.47302932E-03   1.23199214E-03  -3.65960746E-03   9.74955801E-03   7.99618354E-03   6.98833741E-03   1.71471396E-02   2.11264311E-02   2.76147807E-02   2.89383363E-02   3.12669730E-02   3.20394597E-02   2.40174768E-02   4.88635001E-03   2.28376944E-02   3.88699329E-02   3.90529612E-02   6.68390444E-02\nCm   1.91808524E-02   2.08593707E-02   4.05117614E-02   9.08609169E-02   1.76144189E-02   8.03619395E-02   2.29046681E-01   5.21085644E-01   3.06303025E-02   1.87839568E-02   5.49392814E-02   2.88586806E-02   7.27432151E-02   9.74807940E-02   1.52927045E-01   2.09839764E-01   1.53381823E-01   2.11525717E-01   3.10276055E-01   5.26656356E-01   2.36808606E-01   4.69037558E-02   1.35489241E-01   9.09655261E-02   1.65307371E-02   2.08684753E-02   2.87427234E-02   3.25238756E-02   3.23405730E-02   3.67763296E-02   3.44592526E-02   1.39603483E-02   9.30844975E-03   4.38869886E-02   4.75511017E-02   6.60868325E-02  -3.64622673E-02  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1.34836245E-01   1.07364230E-01   1.43237139E-01   1.92985280E-01   2.46933347E-01   9.02796093E-02   1.38316913E-02   1.08182793E-01   6.14873076E-02   6.66631142E-04   8.78030288E-04   1.32611016E-03   1.71954246E-03   1.40068489E-03   1.84836216E-03   2.42481962E-03   2.84459171E-03  -4.62317708E-03  -1.22637276E-02   1.48134120E-02   4.83087886E-03  -4.12714525E-02  -5.43068442E-02  -8.18478158E-02  -1.05797983E-01  -8.66555817E-02  -1.14032411E-01  -1.48591112E-01  -1.70544597E-01  -1.25314174E-01  -2.18599817E-02  -5.22370231E-02  -3.11325417E-02  -4.55594043E-02  -5.51394831E-02  -6.93732043E-02  -6.87497422E-02  -7.80789574E-02  -7.36317180E-02  -4.63458399E-02  -5.52027923E-03  -6.37707421E-02  -3.80677639E-02  -4.89545602E-02  -5.19642546E-02\nCm   4.57462173E-02   5.18245352E-02   6.32910677E-02   6.30523335E-02   7.14943161E-02   6.53139660E-02   4.39552897E-02   1.23959722E-02   5.88841369E-02   3.96103585E-02   3.60909808E-02   2.93300671E-02   6.81466295E-03   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1.09870616E-01   1.13924095E-01   6.77751109E-02   1.85927479E-01   1.70876752E-01   4.77535537E-02   6.15148033E-02   8.85136058E-02   1.06826239E-01   9.75717301E-02   1.19824919E-01   1.33051237E-01   9.16531560E-02   1.18746937E-01   6.86386123E-02   8.71616746E-02   1.23362318E-01  -1.98226420E-02  -2.51867043E-02  -3.51787472E-02  -4.06341098E-02  -3.93885468E-02  -4.59562161E-02  -4.55437675E-02  -2.19674767E-02  -4.34757802E-02  -3.92471779E-04  -4.63184145E-02  -2.04618451E-02\nCm  -2.83405978E-02  -3.77558983E-02  -7.14507307E-02  -1.30141579E-01  -5.88280960E-02  -1.30446654E-01  -2.49308153E-01  -5.34551307E-01  -1.07156965E-01  -5.96844006E-02  -1.10351647E-01  -7.45932139E-02  -5.44893214E-02  -7.38545655E-02  -1.18817820E-01  -1.69300108E-01  -1.13902873E-01  -1.60530625E-01  -2.50716917E-01  -5.29082111E-01  -1.30454484E-01  -5.30740474E-02  -1.35755808E-01  -9.70789868E-02  -4.15164238E-02  -5.18961290E-02  -6.99748432E-02  -7.67456619E-02  -7.91082178E-02  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1.29698954E-01   1.29255114E-01   1.46636637E-01   1.36694656E-01   5.45032489E-02   1.72572825E-01   4.75293943E-02   8.36445819E-02   5.30857367E-02\nCm   3.88035435E-02   5.17390436E-02   6.69513225E-02   5.63419349E-02   7.95188633E-02   5.29126727E-02   1.85947960E-03  -4.26575290E-02   4.80536469E-02   1.40921170E-02   5.70310175E-02   3.58433903E-02   2.15302570E-02   2.83497114E-02   4.27903836E-02   5.54337887E-02   4.52287759E-02   5.96351217E-02   7.80777210E-02   9.10024285E-02   6.05348879E-02   2.74441245E-02   2.95744868E-02   2.50807350E-02  -3.46920306E-02  -4.55986700E-02  -6.85565664E-02  -8.82981705E-02  -7.27771821E-02  -9.54577999E-02  -1.23418344E-01  -1.38111741E-01  -1.05906896E-01  -1.97324868E-03  -5.99949383E-02  -1.73435765E-02  -1.51196551E-02  -1.85039192E-02  -2.38417455E-02  -2.44644937E-02  -2.69601490E-02  -2.67935221E-02  -1.88274529E-02  -3.14109005E-03  -2.75572581E-02   7.02645537E-03  -6.34239620E-03   7.50140896E-04   6.26282662E-02   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7.47229273E-02   3.49839121E-02   4.39742919E-02   6.00078010E-02   6.69822738E-02   6.76855405E-02   7.56289409E-02   6.82174239E-02   2.45589765E-02   4.80805190E-02   5.22195107E-02   5.37669665E-02   6.60964277E-02\nCm  -7.63127718E-02  -1.03396011E-01  -1.51401056E-01  -1.90876131E-01  -1.49028902E-01  -1.85334951E-01  -2.48935662E-01  -4.57920615E-01  -1.64675002E-01  -1.18632964E-01  -1.70981242E-01  -1.65915596E-01  -7.07382062E-02  -9.52726162E-02  -1.51136491E-01  -2.10864023E-01  -1.48761877E-01  -2.07305313E-01  -3.13020610E-01  -5.86697165E-01  -2.36682742E-01  -6.19654015E-02  -1.92865870E-01  -1.25760817E-01   2.36398212E-02   3.14403073E-02   4.85082272E-02   6.49267022E-02   4.98807999E-02   6.75748070E-02   9.46026115E-02   1.37331306E-01   9.21536161E-02  -3.99254906E-02   3.71293426E-02  -1.54672642E-02  -1.13789345E-02  -1.43216207E-02  -1.95978457E-02  -2.19651864E-02  -2.20904415E-02  -2.48142665E-02  -2.26409016E-02  -8.44615665E-03  -1.59267080E-02  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2.59775066E-01   1.09886451E-01   4.40842120E-02   1.24150535E-01   8.55642413E-02  -7.08777200E-02  -9.14487897E-02  -1.32043284E-01  -1.60181421E-01  -1.45220057E-01  -1.79351459E-01  -2.01702827E-01  -1.44644631E-01  -1.01663977E-01  -3.56386453E-02  -1.28776817E-01  -7.25051586E-02   6.13918307E-03   7.79355291E-03   1.08645695E-02   1.25140460E-02   1.21739650E-02   1.41547844E-02   1.39217298E-02   6.55804050E-03   1.11076161E-02   2.23578830E-02   1.80069108E-02   3.69558820E-02   1.34694733E-02   1.67433832E-02   2.23069823E-02   2.40386079E-02   2.52518677E-02   2.69138162E-02   2.19350930E-02   5.77246317E-03   2.40942103E-02   3.33625934E-02   1.83108541E-02   2.79615916E-02\nCm  -4.59898304E-03  -1.55883024E-02  -4.13773748E-02  -7.74426331E-02  -3.69433505E-02  -9.04536225E-02  -1.74278380E-01  -2.13396844E-01  -8.51691936E-02  -2.77228633E-02  -2.29111185E-02  -4.04210647E-02   9.29915006E-03   1.25039407E-02   1.97640614E-02   2.74257134E-02   1.95766898E-02   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1.19679426E-02   5.88403934E-03   2.35130569E-02   2.18401129E-02   3.03565881E-02\nCm   9.58935013E-03   1.16496904E-02   1.91314820E-02   3.23190054E-02   1.90523412E-02   3.97504599E-02   6.41661350E-02   6.91625974E-02   8.69290885E-03   2.29084860E-02   2.97957347E-02   2.13754010E-02  -1.86448976E-02  -2.42836952E-02  -3.57887434E-02  -4.47506271E-02  -3.87395513E-02  -4.93922398E-02  -5.97402576E-02  -5.39667211E-02  -5.23468683E-02  -4.53303932E-03  -2.10348833E-02  -5.99997220E-03   7.08777200E-02   9.14487897E-02   1.32043284E-01   1.60181421E-01   1.45220057E-01   1.79351459E-01   2.01702827E-01   1.44644631E-01   1.69511603E-01   5.39293339E-02   8.59758259E-02   6.94433687E-02  -2.39874205E-02  -3.00660228E-02  -4.07772220E-02  -4.51077698E-02  -4.60540408E-02  -5.08525103E-02  -4.47110524E-02  -1.48712779E-02  -3.62812828E-02  -2.32240762E-02  -2.95312556E-02  -3.51802765E-02  -4.64824859E-02  -5.65365974E-02  -7.18896037E-02  -7.23561684E-02  -8.11117952E-02  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5.78463042E-02   6.87536809E-02   5.88744485E-02   3.03166384E-02   1.95782316E-03   4.70856265E-02   7.42867092E-02   9.55604923E-02   1.28545280E-01\nCm   3.13881163E-02   3.09329150E-02   2.64479911E-02   2.14427755E-02   1.63594684E-02   1.84910517E-02   3.07072508E-02   3.31854987E-02   1.64856744E-02   2.13364437E-02   1.16162999E-03  -2.57728808E-03  -9.05431801E-03  -1.16262114E-02  -1.66130292E-02  -1.98453009E-02  -1.83922281E-02  -2.23279551E-02  -2.41595138E-02  -1.53412657E-02  -3.01759821E-02  -1.57008067E-03  -4.78649266E-03  -1.57103194E-03   6.42431193E-02   8.20824250E-02   1.16033076E-01   1.36423127E-01   1.29215325E-01   1.54004642E-01   1.59952240E-01   8.93275451E-02   1.30767508E-01   3.23330716E-02   5.60379652E-02   3.55735571E-02   1.50251243E-02   1.91415951E-02   2.68890094E-02   3.13220189E-02   3.00333505E-02   3.54016272E-02   3.58821829E-02   1.85662497E-02   3.48706341E-02  -2.89715204E-03   1.41496480E-02  -2.89536428E-03  -6.61821848E-02  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1.05617885E-01   2.26874356E-01   2.32687316E-01   2.34410498E-03   3.04554154E-03   4.46447652E-03   5.53834046E-03   4.85457013E-03   6.13974981E-03   7.28906810E-03   6.20537403E-03   8.23122244E-04   1.84358670E-02   6.37082590E-03   1.48154884E-02\nCm   3.61155945E-02   4.31716077E-02   6.74588554E-02   1.10413826E-01   5.42833968E-02   1.16437897E-01   2.19584984E-01   3.76962242E-01   1.00248086E-01   4.66919403E-02  -8.67753627E-03   1.29746999E-02   4.92780938E-02   6.61094651E-02   1.03967107E-01   1.43183709E-01   1.03860423E-01   1.43577042E-01   2.11989597E-01   3.67925785E-01   1.40864940E-01   1.79888693E-02   1.28444700E-01   4.27823096E-02   1.82863528E-03   2.38459642E-03   3.52378047E-03   4.42367588E-03   3.80526885E-03   4.87090937E-03   5.94581588E-03   5.53121897E-03   2.23798583E-02   3.52010962E-03  -1.36250231E-02  -1.04919007E-02   1.14143017E-02   1.40984122E-02   1.85274668E-02   1.95686581E-02   2.09813319E-02   2.17422528E-02   1.66908136E-02   3.65330030E-03   1.43030283E-02  -1.08922520E-02   1.64654267E-02  -8.46541447E-03  -2.53183006E-02  -2.84849213E-02  -3.06920149E-02  -2.42808349E-02  -3.14173059E-02  -2.01666865E-02  -5.74879463E-03  -6.18314525E-05  -1.91702600E-02  -1.64140850E-02  -2.57347218E-02  -2.77401053E-02\nCm  -7.83441816E-02  -9.14879154E-02  -1.18400581E-01  -1.50802845E-01  -9.80402859E-02  -1.40011767E-01  -2.53382004E-01  -4.34751062E-01  -1.61633398E-01  -8.22866685E-02  -1.28774811E-01  -1.16221331E-01  -9.55775637E-03  -1.27346894E-02  -1.97267231E-02  -2.65615349E-02  -2.01705409E-02  -2.74490087E-02  -3.88743330E-02  -5.86415667E-02   3.37579070E-03  -4.25338623E-02  -6.82838176E-02  -7.37356686E-02  -7.02623666E-02  -9.32602233E-02  -1.43256640E-01  -1.90492231E-01  -1.48193819E-01  -1.99737901E-01  -2.76030939E-01  -3.83915552E-01  -1.71313378E-01  -6.72844121E-02  -1.37285769E-01  -9.48495573E-02   5.04909440E-02   6.11726466E-02   7.71378002E-02   7.66971123E-02   8.68681056E-02   8.23358972E-02   5.23762694E-02   6.44380574E-03   7.09617161E-02   3.35001662E-02   7.69962650E-02   6.40325597E-02   1.45998420E-02   1.76487374E-02   2.21479614E-02   2.18672382E-02   2.49102677E-02   2.33568943E-02   1.45259613E-02   1.66785313E-03   2.01470494E-02  -1.08795086E-02   2.59894780E-02   1.19887476E-02\nCm  -8.24940367E-03  -1.01167024E-02  -1.40500305E-02  -9.56839621E-03  -2.59453087E-02  -1.31380471E-02   3.15263682E-02   5.35828080E-02  -4.84084164E-03   6.47784591E-03  -2.19336620E-02   9.90459196E-03   4.94700578E-02   6.36059755E-02   9.11489614E-02   1.09344238E-01   1.00736963E-01   1.22879678E-01   1.34390069E-01   8.82586900E-02   1.02614996E-01   1.50473744E-02   8.06478396E-02   3.67089553E-02  -5.35195569E-02  -6.76637624E-02  -9.34944178E-02  -1.06293854E-01  -1.05092849E-01  -1.20223328E-01  -1.14122319E-01  -4.81390977E-02  -6.42698534E-02  -2.52772662E-02  -3.51660033E-02  -2.60937750E-02   2.39874205E-02   3.00660228E-02   4.07772220E-02   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1.90094810E-01   6.68640475E-02   1.86818249E-02   2.64958612E-02   1.74522790E-02   2.53319704E-02   3.36668841E-02   5.18624219E-02   6.92547430E-02   5.34448307E-02   7.22730130E-02   1.00718624E-01   1.44013202E-01   3.02963154E-02   2.84392046E-02   5.53367924E-02   4.02778398E-02   1.34651295E-02   1.76860803E-02   2.65502808E-02   3.41187303E-02   2.82308189E-02   3.69526742E-02   4.75420515E-02   5.23629432E-02   2.08225255E-02   4.19366662E-02   5.07872673E-02   6.16672519E-02  -6.61655943E-02  -8.34789665E-02  -1.14833070E-01  -1.29698954E-01  -1.29255114E-01  -1.46636637E-01  -1.36694656E-01  -5.45032489E-02  -1.90489237E-01  -2.92780215E-02  -1.09309897E-01  -4.84432984E-02\nCm   3.06149284E-02   3.63938921E-02   5.77951550E-02   8.97259443E-02   5.34224333E-02   8.81873320E-02   1.55374392E-01   3.10929348E-01   9.15543818E-02   6.91077119E-02   8.42902175E-02   8.32609493E-02   7.70121585E-02   1.02254344E-01   1.57190779E-01   2.09255319E-01   1.62444586E-01   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1.23206379E-01   1.10384807E-01   1.37516851E-01   1.57724689E-01   1.20357927E-01   6.85225738E-02   4.92379712E-03   6.50998924E-02   2.54873594E-02  -6.93033491E-02  -8.80661819E-02  -1.23031347E-01  -1.42157532E-01  -1.37741834E-01  -1.60774043E-01  -1.59472644E-01  -7.71329078E-02  -1.49992390E-01  -3.07447154E-02  -1.60606945E-01  -8.70785469E-02   2.67924907E-02   3.09677141E-02   3.53273450E-02   3.03587391E-02   3.78802228E-02   2.82356900E-02   1.09248987E-02   2.96187073E-04   2.64768843E-02   3.70398539E-03   1.82617771E-02   6.94917832E-03  -3.59091557E-02  -3.62643409E-02  -3.11374612E-02  -1.77597031E-02  -2.40407816E-02  -7.95700873E-03  -5.95330318E-04  -1.13975783E-07  -5.12682922E-03  -5.25152475E-02  -1.86060219E-02  -4.26431977E-02\nCm  -2.89062747E-02  -3.01573785E-02  -3.27051745E-02  -2.58383185E-02  -4.01659041E-02  -2.36882332E-02   1.36413188E-02   1.08635636E-02   1.14293075E-02  -1.89541550E-02  -6.48726285E-02  -4.03501974E-02   1.91120402E-02   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1.57333505E-01   6.91020679E-02   8.36409589E-02   6.41484296E-02   9.83106912E-02   1.93816390E-02   2.51143475E-02   3.66025389E-02   4.50190443E-02   3.99843643E-02   5.01196241E-02   5.82954621E-02   4.65031156E-02   5.63478539E-02   2.02014828E-02   1.00303300E-02   7.00989323E-03   4.92692087E-02   6.37554008E-02   9.26451779E-02   1.13451339E-01   1.01430410E-01   1.26552477E-01   1.45648337E-01   1.12357268E-01   1.07252089E-01   2.62315907E-02   1.34469877E-01   7.15047386E-02  -1.55008806E-03  -1.90030357E-03  -2.45749317E-03  -2.53526773E-03  -2.78015688E-03  -2.78488235E-03  -1.98976265E-03  -3.49354761E-04  -4.91130727E-03   5.16149534E-03  -4.31538740E-04   9.79978919E-04  -5.17768879E-02  -6.06525814E-02  -7.11860638E-02  -6.37528413E-02  -7.77512350E-02  -6.22344706E-02  -2.78771377E-02  -1.17849468E-03  -5.29838967E-02  -7.16915508E-03  -1.50249538E-02  -8.04962568E-03\nCm  -5.50960519E-02  -5.05193257E-02  -1.76415876E-02   4.45065797E-02  -6.07525613E-03   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9.13708474E-02   1.23941978E-01   1.41110565E-01   1.46669914E-01   1.64085026E-01   1.32315512E-01   4.12939742E-02   1.58085296E-01   1.11563923E-01   2.28721397E-01   2.30493348E-01  -4.63565445E-03  -6.05471667E-03  -8.97850501E-03  -1.13298837E-02  -9.66468464E-03  -1.24344206E-02  -1.53598358E-02  -1.48423485E-02  -1.12378229E-02   2.59687008E-02   1.39233964E-02   2.86847085E-02  -2.42283949E-02  -3.15365746E-02  -4.64161147E-02  -5.79250337E-02  -5.03011533E-02  -6.40058466E-02  -7.70605669E-02  -6.86002506E-02  -3.76518700E-02   3.29064940E-03  -5.90528699E-02  -2.89675434E-02   2.11055144E-03   2.73710783E-03   3.99645196E-03   4.92871128E-03   4.35951768E-03   5.48011766E-03   6.41558952E-03   5.22432394E-03   3.79484299E-03   4.09165769E-02   1.78713194E-02   3.85637935E-02   6.77877297E-02   8.70954864E-02   1.24616284E-01   1.49149882E-01   1.37854792E-01   1.67721473E-01   1.82371740E-01   1.17605061E-01   1.14539542E-01   9.62722345E-02   1.58190312E-01   1.76924099E-01\nCm  -9.59455021E-02  -1.12649422E-01  -1.36049627E-01  -1.38115642E-01  -1.34400771E-01  -1.33764578E-01  -1.39101550E-01  -1.46966597E-01  -1.25265664E-01  -1.44805205E-01  -1.44413749E-01  -1.77129185E-01  -5.69842566E-02  -7.52879916E-02  -1.14484701E-01  -1.49957373E-01  -1.19963840E-01  -1.59699843E-01  -2.14022545E-01  -2.69125214E-01  -2.33266295E-01  -4.33829971E-02  -1.67138151E-01  -8.53754288E-02   5.21900870E-02   6.81270069E-02   1.00897578E-01   1.27083396E-01   1.08736339E-01   1.39641886E-01   1.71757548E-01   1.63709675E-01   1.29217671E-01  -7.60088980E-03   6.42061295E-02   1.37972682E-02  -2.64123616E-02  -3.35309402E-02  -4.67468275E-02  -5.38493701E-02  -5.23793652E-02  -6.09094466E-02  -5.99226714E-02  -2.82510979E-02  -7.06580761E-02  -3.78713821E-02  -6.95756106E-02  -5.05848039E-02  -1.74946838E-02  -2.20311166E-02  -3.01835144E-02  -3.38888264E-02  -3.40120994E-02  -3.82924297E-02  -3.51101278E-02  -1.32982395E-02  -3.71007909E-02  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-3.84102543E-03  -1.09202405E-02  -1.82899459E-02  -5.70766494E-02  -4.38795409E-02\nCm  -1.32203771E-02  -1.12812478E-02  -8.18710669E-03   1.78192317E-04  -2.55007144E-02  -4.77514679E-02  -2.64334722E-02   3.80688640E-01  -7.68964517E-03  -2.09931496E-02  -2.31083568E-02   3.87605983E-02   6.59729686E-02   9.01416478E-02   1.47642345E-01   2.16110425E-01   1.36197716E-01   1.94076577E-01   3.14864243E-01   7.64083050E-01   2.37424225E-01   2.06395702E-02   2.06191676E-01   9.10645151E-02  -6.38186867E-02  -8.39094247E-02  -1.26245207E-01  -1.62769789E-01  -1.33914407E-01  -1.75815635E-01  -2.27833405E-01  -2.56847974E-01  -2.01896678E-01  -6.11183227E-02  -9.62447209E-02  -9.66614640E-02  -4.45526810E-02  -5.80814690E-02  -8.57750564E-02  -1.07580771E-01  -9.26788026E-02  -1.18524050E-01  -1.44371471E-01  -1.33392202E-01  -1.10090541E-01  -4.36404468E-02  -1.08184966E-01  -1.02909216E-01   1.58671262E-02   1.97239898E-02   2.62785100E-02   2.83192333E-02   2.97476612E-02   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2.99198390E-02   3.70330142E-02   2.40236104E-02   2.83625150E-02   2.21100448E-02  -7.08585550E-02  -9.07706327E-02  -1.29039903E-01  -1.52981621E-01  -1.43277152E-01  -1.72429980E-01  -1.82989377E-01  -1.09330432E-01  -9.01549319E-02  -2.84598858E-02  -6.23269958E-02  -4.18951594E-02   5.77985013E-02   7.39176733E-02   1.04704157E-01   1.23473475E-01   1.16478861E-01   1.39315261E-01   1.45830871E-01   8.34591584E-02   1.61783457E-01   6.65565750E-02   1.32565056E-01   1.26648451E-01\nCm   5.84952320E-02   4.80217216E-02   5.85164587E-03  -4.35193917E-02  -3.72162544E-02  -8.25284770E-02  -7.12454535E-02  -1.08341445E-02  -3.71856675E-02   8.19404884E-02  -2.32833318E-02   4.08856175E-02   3.99367896E-03   5.12157872E-03   7.29823599E-03   8.68282011E-03   8.09272805E-03   9.77893899E-03   1.04719271E-02   6.43649587E-03  -8.81945808E-03   6.90240330E-03   2.54398468E-02   1.47053722E-02   3.58007172E-03   4.52248594E-03   6.23783313E-03   7.07325106E-03   7.01560788E-03   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1.15057847E-01   9.61377407E-02   7.73434085E-02   7.89978928E-02   1.21267069E-01  -7.75381053E-04  -9.87644750E-04  -1.38687176E-03  -1.61463301E-03  -1.54930665E-03  -1.82503483E-03  -1.84713052E-03  -9.51431539E-04  -3.05858926E-03   8.01079063E-03   2.21389416E-03   1.68111347E-02\nCm   1.01982114E-01   1.22053196E-01   1.52513139E-01   1.52684950E-01   1.66942960E-01   1.59262322E-01   1.17451894E-01   5.09140056E-02   8.34720904E-02   1.24087931E-01   2.60441090E-01   2.56034245E-01   3.55450120E-02   4.60133800E-02   6.69185989E-02   8.20467504E-02   7.32195486E-02   9.14728429E-02   1.05586313E-01   8.22165146E-02   9.46842295E-02   5.22494838E-02   9.19198627E-02   8.93227981E-02  -3.79025082E-02  -4.86649476E-02  -6.95268852E-02  -8.30332922E-02  -7.69807129E-02  -9.34269389E-02  -1.01026032E-01  -6.40224561E-02  -7.44642192E-02   2.20473087E-02  -5.16532201E-02  -4.92014574E-03   2.47188288E-02   3.13390902E-02   4.35651774E-02   4.99715494E-02   4.88677272E-02   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3.22696679E-02   3.30948568E-02   3.71933154E-02   3.66727583E-02   4.95623845E-02\nCm  -1.48711982E-02  -9.92834247E-03  -6.27724642E-03  -2.60365798E-02   2.67565465E-02   3.60406241E-03  -1.00999087E-01  -4.25427685E-01   4.30591122E-03  -4.88370035E-02   8.75062363E-03  -3.79126039E-02  -5.12885343E-02  -6.93644943E-02  -1.11054021E-01  -1.57090848E-01  -1.07473277E-01  -1.50916991E-01  -2.33056312E-01  -4.72488583E-01  -2.01098913E-01  -8.47571251E-03  -1.21632736E-01  -3.38441062E-02   2.30673564E-02   2.94803949E-02   4.16972380E-02   4.90648914E-02   4.64213605E-02   5.53807188E-02   5.76430921E-02   3.24086354E-02   3.20902832E-02   2.77572404E-02   4.62539071E-02   3.54623543E-02  -6.06178267E-03  -7.56588290E-03  -1.01684704E-02  -1.10993246E-02  -1.15008829E-02  -1.24745387E-02  -1.05553350E-02  -3.11837589E-03  -4.89593429E-03  -8.00429664E-03  -1.26656729E-02  -1.19184653E-02   5.95833506E-02   7.34825834E-02   9.62523728E-02   1.01176186E-01   1.08991631E-01   1.12177127E-01   8.48785035E-02   1.77706191E-02   5.95257730E-02   2.94796276E-02   2.09781909E-02   2.31134137E-02\nCm   1.00115181E-01   1.21707474E-01   1.57833513E-01   1.84680211E-01   1.44314465E-01   1.56650352E-01   2.02496667E-01   5.10686953E-01   1.73428681E-01   1.34265997E-01   1.79584472E-01   2.10887999E-01   4.47891043E-02   6.14666958E-02   1.01669880E-01   1.51037147E-01   9.16028954E-02   1.31082251E-01   2.16571913E-01   5.64048182E-01   1.06469344E-01   5.99479103E-02   1.95095672E-01   1.24384527E-01  -8.52629123E-03  -1.12799075E-02  -1.72023415E-02  -2.26298839E-02  -1.79615241E-02  -2.39980112E-02  -3.24497583E-02  -4.20143174E-02  -2.33114024E-02   2.85414619E-02  -1.64104857E-02   6.46040719E-03  -2.93162275E-02  -3.71463436E-02  -5.15736679E-02  -5.90493062E-02  -5.78771409E-02  -6.67978685E-02  -6.46425825E-02  -2.89529923E-02  -4.88687014E-02   4.15576142E-03  -9.99925265E-03  -2.53267198E-03   5.70831994E-02   7.04501500E-02   9.24235761E-02   9.73725420E-02   1.04660969E-01   1.08069753E-01   8.23348666E-02   1.76062476E-02   1.06108537E-01   7.63794439E-02   1.01530584E-01   1.09252678E-01\nCm   2.41661057E-02   4.51772469E-02   9.06394561E-02   1.43334972E-01   7.60929577E-02   1.05779816E-01   2.04009214E-01   6.79190070E-01   1.26662974E-01   3.06307535E-02   8.75990653E-02   7.67917537E-02   5.88601627E-02   8.07492838E-02   1.33461069E-01   1.98033548E-01   1.20478378E-01   1.72354017E-01   2.84372771E-01   7.36633404E-01   2.03221537E-01   3.31709089E-02   1.52149575E-01   7.08009815E-02   2.96994314E-02   3.90796518E-02   5.88976900E-02   7.61309413E-02   6.23581471E-02   8.20575172E-02   1.06921991E-01   1.22704580E-01   2.50996677E-02   3.67011627E-02   5.87937556E-02   5.23820589E-02  -5.66177333E-02  -7.39364248E-02  -1.09597600E-01  -1.38221002E-01  -1.18016114E-01  -1.51752654E-01  -1.87210302E-01  -1.80147501E-01  -1.36551221E-01  -4.99696607E-03  -9.74721523E-02  -3.89302665E-02  -1.25741916E-02  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1.04680584E-02   4.24099883E-02   1.41980631E-01   1.71650735E-02   7.27360244E-03  -1.54857468E-02  -3.30407805E-02   5.19871806E-02   6.89572239E-02   1.05769519E-01   1.40337519E-01   1.09627488E-01   1.47500276E-01   2.02950451E-01   2.78230558E-01   1.24794177E-01   6.70069848E-03   5.60278323E-02   2.27043953E-02  -4.22553739E-02  -5.51607304E-02  -8.17011239E-02  -1.02917762E-01  -8.80416533E-02  -1.13079133E-01  -1.39125556E-01  -1.32728218E-01  -6.20934443E-02   2.24872657E-04  -7.66185017E-02  -3.24414600E-02   5.16869580E-03   6.51322014E-03   8.93598231E-03   1.00538079E-02   1.00656814E-02   1.13627620E-02   1.04789968E-02   4.04098179E-03   1.01272002E-02   1.93751047E-03  -3.41674204E-03  -4.98548082E-03  -3.25289460E-02  -3.99336058E-02  -5.17961380E-02  -5.36680454E-02  -5.86145595E-02  -5.90880489E-02  -4.27871544E-02  -7.82763529E-03  -4.90601246E-02  -1.00824347E-02  -1.79980190E-02  -1.07755305E-02\nCm  -7.31392959E-03  -9.19531533E-03  -1.35951832E-02  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5.91280680E-02   4.50931254E-02   5.87620862E-02   8.67031574E-02   1.08601830E-01   9.37557067E-02   1.19743925E-01   1.45413375E-01   1.33053060E-01   1.32140879E-01   3.14410810E-02   5.04802292E-02   3.54308462E-02  -2.37459167E-02  -3.03944749E-02  -4.31340799E-02  -5.10064754E-02  -4.79379160E-02  -5.75209548E-02  -6.06420583E-02  -3.54898410E-02  -5.90901825E-02   4.18218812E-03  -3.65969389E-02  -9.72766276E-03   2.36050025E-02   2.88257882E-02   3.69686160E-02   3.76767864E-02   4.17758345E-02   4.11009346E-02   2.82740860E-02   4.41986575E-03   3.98418916E-02   3.39766559E-02   5.61288340E-02   6.83426248E-02  -4.34149103E-02  -5.27797017E-02  -6.70423763E-02  -6.73744972E-02  -7.56263269E-02  -7.28544965E-02  -4.79495460E-02  -6.54635440E-03  -6.16233563E-02  -1.58694488E-02  -4.00062696E-02  -2.27045028E-02\nCm   2.86841469E-02   3.34561907E-02   4.07034269E-02   4.36377749E-02   3.56985291E-02   3.29344776E-02   5.37300890E-02   1.22467953E-01   3.19740638E-02   4.01773390E-02   5.40382537E-02   6.33324789E-02   7.29955062E-02   9.65821712E-02   1.47333225E-01   1.93899417E-01   1.53781684E-01   2.05535817E-01   2.78160941E-01   3.61161639E-01   1.73026478E-01   3.36894871E-02   1.35082174E-01   7.07641435E-02  -4.62035148E-02  -6.09391795E-02  -9.23157888E-02  -1.20241616E-01  -9.71697994E-02  -1.28731833E-01  -1.70496933E-01  -2.06303606E-01  -1.26212605E-01  -3.27069131E-03  -5.80863188E-02  -1.67599823E-02  -1.91069409E-02  -2.45277998E-02  -3.50283509E-02  -4.18080836E-02  -3.87928535E-02  -4.70486431E-02  -5.07983436E-02  -3.20389615E-02  -5.27437645E-02   8.04681914E-04  -2.82901088E-02  -3.81893316E-03  -4.82501722E-03  -5.78027362E-03  -7.11561205E-03  -6.83094325E-03  -7.95331030E-03  -7.13635974E-03  -4.04912943E-03  -3.51380203E-04  -1.13633776E-02   1.95145008E-03   3.17347806E-03   4.14143336E-03\nCm  -1.27949776E-02  -9.36818661E-03   1.33271835E-02   4.57936081E-02   3.16061064E-02   7.18861847E-02   9.59417420E-02   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2.31647468E-01   9.45366268E-02   4.63587306E-02   6.74453728E-02   7.10056615E-02  -2.42006099E-02  -3.20965593E-02  -4.92182842E-02  -6.52787531E-02  -5.10309228E-02  -6.86391786E-02  -9.43695601E-02  -1.29043411E-01  -6.84817743E-02  -1.29400340E-02  -1.42922331E-02  -1.01209468E-02  -5.47530606E-02  -7.16193972E-02  -1.06545939E-01  -1.35091490E-01  -1.14337929E-01  -1.47786214E-01  -1.84542000E-01  -1.84620838E-01  -1.09537031E-01  -2.74632473E-02  -1.04504221E-01  -5.93934904E-02   6.08952881E-02   7.84680991E-02   1.12984212E-01   1.36496124E-01   1.24491457E-01   1.53053822E-01   1.70372661E-01   1.18289392E-01   1.33477042E-01   6.53408816E-02   1.16793177E-01   1.04250143E-01\nCm   4.17120297E-04  -1.75363071E-03  -2.12449933E-02  -6.25094254E-02  -2.09637202E-02  -8.32981840E-02  -1.62397843E-01  -1.86099969E-01  -8.01412215E-02   5.65488282E-03   4.80440379E-03   1.13292987E-01  -2.87206103E-02  -3.83322110E-02  -5.96012521E-02  -8.07005996E-02  -6.06095057E-02  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1.35091490E-01   1.14337929E-01   1.47786214E-01   1.84542000E-01   1.84620838E-01   1.63828349E-01   3.42516424E-02   1.16483911E-01   5.63581944E-02  -5.15978734E-02  -6.71671727E-02  -9.88754485E-02  -1.23424167E-01  -1.07134941E-01  -1.36360422E-01  -1.64273671E-01  -1.46525420E-01  -1.00325550E-01   6.22418348E-04  -6.00822946E-02  -2.12837449E-02   3.16914322E-02   4.11530303E-02   6.02576718E-02   7.46256401E-02   6.55838794E-02   8.28018392E-02   9.79088242E-02   8.22974393E-02   7.33183266E-02   3.79111225E-02   4.36425860E-02   4.31890993E-02  -1.00116033E-02  -1.28531606E-02  -1.83592669E-02  -2.19189798E-02  -2.03300292E-02  -2.46646590E-02  -2.66498166E-02  -1.68468311E-02  -2.19617352E-02   2.36366241E-02   1.02395562E-03   2.15905334E-02\nCm   6.51668222E-02   8.65255629E-02   1.11862324E-01   1.04920147E-01   1.17214900E-01   8.94945160E-02   6.31269732E-02   1.02390160E-01   8.82517593E-02   1.19825393E-01   1.37615586E-01   1.95793448E-01   3.85530658E-02   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1.11520535E-02   1.79676729E-03   3.45597757E-06   1.01010807E-02   2.70321485E-02   2.30429654E-02   2.67388784E-02\nCm   5.73944688E-03   1.22215507E-02   4.45428912E-02   9.69265014E-02   5.22297054E-02   1.20385383E-01   2.06395848E-01   2.41232535E-01   5.83135831E-02   8.25610166E-03   4.80675831E-02  -4.81437664E-04   2.69478741E-02   3.56938989E-02   5.45790919E-02   7.20829430E-02   5.67978434E-02   7.61339815E-02   1.03780990E-01   1.37971401E-01   1.05705912E-01   4.07718918E-02   4.83351648E-02   5.12663207E-02   6.09841685E-02   7.84597411E-02   1.12588982E-01   1.35337758E-01   1.24326529E-01   1.51999449E-01   1.67087042E-01   1.11506682E-01   1.41781337E-01   4.14092386E-02   3.83070110E-02   4.73148706E-02  -6.36828943E-02  -7.72457608E-02  -9.76495807E-02  -9.74468807E-02  -1.10034141E-01  -1.04876938E-01  -6.74995149E-02  -8.60646327E-03  -6.13732111E-02  -2.14681335E-02  -4.85635375E-02  -3.25530973E-02   5.78574909E-03   6.91146533E-03   8.45654644E-03   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1.54607867E-01   2.83447360E-01   4.30390732E-01   1.25914482E-01   4.79870846E-02   1.74542523E-01   6.51582795E-02   6.75887442E-03   9.03975195E-03   1.41207686E-02   1.92521587E-02   1.42590598E-02   1.95791470E-02   2.83870764E-02   4.63234458E-02   2.00273110E-02   7.25252844E-02   2.12683778E-02   1.01810591E-01   5.57060894E-02   7.38117741E-02   1.12952269E-01   1.49349124E-01   1.17427212E-01   1.57552466E-01   2.15270024E-01   2.88404369E-01   1.36105456E-01   7.01499161E-02   8.30805236E-02   1.31429236E-01   5.20473359E-02   6.73139713E-02   9.77013819E-02   1.19435350E-01   1.07058349E-01   1.33326116E-01   1.52796635E-01   1.16304439E-01   1.39823150E-01   6.63160395E-02   6.08376752E-02   7.21201560E-02  -2.66869920E-02  -3.27942828E-02  -4.26263741E-02  -4.43042403E-02  -4.82465836E-02  -4.88563787E-02  -3.57172190E-02  -6.72833859E-03  -2.50682440E-02  -1.95463669E-02  -3.13002674E-02  -4.13243012E-02\nCm  -2.81418701E-02  -3.86528540E-02  -5.28184327E-02  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2.26318192E-02   3.08752302E-02   1.59782601E-02   7.28246113E-02   9.67739275E-02   1.49035603E-01   1.98934761E-01   1.53640034E-01   2.07700678E-01   2.89217441E-01   4.12447488E-01   2.19040137E-01   3.07382503E-02   1.11990270E-01   4.92126447E-02  -2.58147542E-02  -3.41839647E-02  -5.22398837E-02  -6.89338612E-02  -5.44037993E-02  -7.28731357E-02  -9.91609957E-02  -1.31068575E-01  -6.13325737E-02   1.00063919E-02  -4.83213535E-02  -7.18222922E-03   8.79240708E-03   1.03150014E-02   1.21448419E-02   1.09269357E-02   1.32894613E-02   1.07206353E-02   4.88003864E-03   2.16629042E-04   1.10088386E-02   1.18506297E-02  -2.48721051E-03   2.95423555E-03  -3.35547819E-02  -3.83572332E-02  -4.27439500E-02  -3.55048285E-02  -4.50330046E-02  -3.16012572E-02  -1.08054072E-02  -2.01461923E-04  -1.28231852E-02  -2.32024207E-02  -1.63072126E-02  -1.57977517E-02\nCm   9.66023770E-03   1.15201029E-02   2.23685499E-02   3.21270620E-02   4.14317985E-02   5.85131927E-02   2.77767187E-02  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2.75233535E-02   7.52085087E-02   3.12068328E-02   3.97917341E-02   3.62904462E-02  -5.84119386E-02  -7.07075406E-02  -8.89947819E-02  -8.82453296E-02  -1.00173083E-01  -9.45502933E-02  -5.96218724E-02  -7.14152948E-03  -7.89302576E-02  -6.34898483E-02  -3.41312498E-02  -6.26256602E-02\nCm   8.75150354E-03   1.90028799E-02   4.12992053E-02   6.29716303E-02   4.83097469E-02   8.02758141E-02   1.06639098E-01   5.09780746E-02   3.41601632E-02   7.00212810E-03   2.82088145E-02   3.12317821E-02  -8.00422145E-03  -1.01057267E-02  -1.39223495E-02  -1.57596091E-02  -1.56639047E-02  -1.78206018E-02  -1.67146803E-02  -6.79281102E-03  -1.71758860E-02   9.73435928E-03  -1.79309139E-03   4.91987118E-03   7.06333577E-02   8.91302446E-02   1.22649814E-01   1.38598892E-01   1.38039535E-01   1.56705160E-01   1.46288889E-01   5.85873742E-02   9.66118295E-02   3.49299837E-02   7.12620079E-02   4.74426909E-02  -6.00569476E-03  -7.16626724E-03  -8.74765079E-03  -8.29500879E-03  -9.74512013E-03  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4.25662644E-03   6.44893376E-03   3.32624627E-03\nCm   1.17502036E-02   1.77254166E-02   1.84134391E-02   1.95947863E-03   2.37057781E-02  -6.79636068E-03  -5.46406472E-02  -5.69375821E-02  -9.58782529E-03   2.28556476E-02   3.36012829E-02   5.15878110E-02   1.29294397E-02   1.69658429E-02   2.54145729E-02   3.25556180E-02   2.70843042E-02   3.53481584E-02   4.51612419E-02   4.86320458E-02   2.84600432E-02   2.42686956E-03   1.04151942E-02   2.70464130E-03  -7.01546782E-02  -9.04026450E-02  -1.30178261E-01  -1.57285733E-01  -1.43429600E-01  -1.76358685E-01  -1.96369000E-01  -1.36457781E-01  -1.65980114E-01  -3.54496057E-02  -3.96519835E-02  -3.58161873E-02   2.31434863E-02   2.94634854E-02   4.13258315E-02   4.80314041E-02   4.61894232E-02   5.42989343E-02   5.47103603E-02   2.77885445E-02   6.52173219E-02   1.82005018E-02   3.03705494E-02   2.39884107E-02   6.96758025E-04   8.54731193E-04   1.10688054E-03   1.14422883E-03   1.25239610E-03   1.25825220E-03   9.04651564E-04   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9.68799228E-02   7.35087280E-03   9.89515446E-03   1.56788387E-02   2.18365545E-02   1.54644525E-02   2.15278928E-02   3.24098036E-02   6.01268397E-02  -5.63253238E-03   2.64634028E-02   4.57552950E-02   3.70839000E-02   1.23621458E-02   1.65971009E-02   2.61451220E-02   3.60971953E-02   2.60460929E-02   3.60640360E-02   5.34832018E-02   9.42297918E-02   6.13259763E-02   2.22869287E-02   2.08238964E-02   4.16254675E-02   4.53280363E-02   5.98827278E-02   9.10424708E-02   1.19219286E-01   9.54207539E-02   1.26997958E-01   1.70100709E-01   2.13500503E-01   1.27368807E-01   2.76302191E-02   1.12192787E-01   8.74450640E-02  -5.37179185E-02  -6.93480512E-02  -1.00255682E-01  -1.21842133E-01  -1.10166860E-01  -1.36331144E-01  -1.54013578E-01  -1.12028634E-01  -1.18785438E-01  -1.42839829E-02  -6.86632095E-02  -5.32378303E-02\nCm  -4.22034623E-02  -4.61069198E-02  -3.82050837E-02   3.03952702E-03  -4.94184282E-02   1.27510218E-02   1.19886140E-01   2.44101738E-01   1.58552604E-02  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1.07248479E-03   7.00765464E-04   9.35754047E-05  -2.15228374E-03  -6.98622820E-03   2.97688322E-04  -2.57834743E-03\nCm   2.04866336E-02   3.03060574E-02   5.80770960E-02   8.57468458E-02   6.93019501E-02   9.48751318E-02   1.25698768E-01   1.49272704E-01   3.47041001E-02   1.04701471E-02   9.64141491E-02   9.04091017E-02   5.80295614E-02   7.55715853E-02   1.11350190E-01   1.39186349E-01   1.20555147E-01   1.53653344E-01   1.85698294E-01   1.67330160E-01   1.16555608E-01   5.71256165E-02   1.41880175E-01   1.20463845E-01  -1.20866062E-02  -1.52679172E-02  -2.10578771E-02  -2.38763498E-02  -2.36838803E-02  -2.70016270E-02  -2.54421828E-02  -1.04877770E-02  -5.51772785E-03   4.95319401E-03  -9.47788635E-03   6.26481052E-03  -5.82099038E-02  -7.08276798E-02  -9.01351167E-02  -9.08284004E-02  -1.01714724E-01  -9.83901683E-02  -6.53167299E-02  -9.15582161E-03  -9.38021850E-02  -3.80339001E-02  -8.42702399E-02  -6.71892336E-02   3.34802137E-02   3.97287408E-02   4.79252437E-02   4.46687374E-02   5.31120887E-02   4.54376538E-02   2.33520111E-02   1.49914237E-03   3.11466145E-02   3.98494707E-02   5.24419473E-02   5.55629742E-02\nCm   2.21179567E-02   3.48509695E-02   4.70603092E-02   3.00499169E-02   6.33453942E-02   1.93450720E-02  -5.59711954E-02  -5.72635735E-02  -6.15468868E-03   1.97195006E-02   1.17690254E-01   1.05435650E-01   3.74359450E-02   4.94112118E-02   7.49713766E-02   9.78815423E-02   7.87659596E-02   1.04563936E-01   1.39179865E-01   1.71164443E-01   1.08430052E-01   5.27977135E-02   1.04413653E-01   1.02994215E-01  -6.82258298E-02  -8.91186506E-02  -1.32178119E-01  -1.66840200E-01  -1.42254996E-01  -1.83072144E-01  -2.26285394E-01  -2.19102701E-01  -1.62251155E-01  -2.84435657E-02  -9.35331619E-02  -4.34270957E-02  -1.22934307E-02  -1.55890613E-02  -2.16802357E-02  -2.48844697E-02  -2.43151045E-02  -2.81494431E-02  -2.74252425E-02  -1.25438344E-02  -1.94903481E-02   1.28611631E-02  -1.54426192E-02   1.59692238E-03   6.13335170E-02   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1.07330358E-01   9.38984463E-02   1.18907532E-01   1.41578917E-01   1.21654602E-01   1.15030269E-01   1.82918931E-02   4.79991590E-02   2.58721221E-02  -2.84348143E-02  -3.66588534E-02  -5.28419962E-02  -6.39417564E-02  -5.81817190E-02  -7.16584051E-02  -8.00887234E-02  -5.63160132E-02  -8.37617738E-02  -4.11504479E-02  -4.05565814E-02  -6.24401682E-02  -5.36014028E-02  -6.84248329E-02  -9.65405245E-02  -1.13183664E-01  -1.07610057E-01  -1.27824935E-01  -1.31779753E-01  -7.19045527E-02  -1.18925408E-01  -3.63334327E-02  -5.32790019E-02  -6.70807349E-02\nCm   4.55541979E-02   6.13924973E-02   9.25487122E-02   1.14777283E-01   9.95644792E-02   1.22378017E-01   1.55437605E-01   1.41731120E-01   9.36908967E-02   2.60552109E-02   4.33027657E-02   4.51200625E-02   3.31670037E-02   4.32931171E-02   6.41120328E-02   8.07397212E-02   6.90988971E-02   8.87263816E-02   1.09097414E-01   1.03879523E-01   9.63758035E-02   1.50869754E-02   3.53994548E-02   1.52241887E-02   4.28492318E-02   5.44132585E-02   7.59062298E-02   8.75181217E-02   8.50317491E-02   9.89891032E-02   9.76224433E-02   4.63750383E-02   7.27296092E-02   2.68372271E-02   3.02941899E-02   1.83151784E-02   3.58144991E-03   4.48844722E-03   6.08581738E-03   6.72942669E-03   6.87371341E-03   7.58586196E-03   6.66207705E-03   2.20802008E-03   2.54496367E-03   2.26817507E-02   1.28199650E-02   2.35314403E-02  -4.46173904E-02  -5.47732489E-02  -7.10425204E-02  -7.36077592E-02  -8.03943723E-02  -8.10402209E-02  -5.86778060E-02  -1.07316565E-02  -8.75012661E-02  -2.71236637E-03  -2.29078921E-02  -1.12434100E-02\nCm  -4.92334755E-03  -4.72574132E-03   8.92871411E-03   4.11624578E-02   7.81665643E-03   4.80626150E-02   1.11665557E-01   2.10489423E-01  -8.26925357E-04  -1.15974601E-02   5.01849920E-02   5.85667032E-03   4.06823623E-02   5.39203770E-02   8.25646323E-02   1.09271354E-01   8.57664236E-02   1.15160276E-01   1.57645156E-01   2.12516475E-01   1.15289511E-01   4.18960990E-02   6.95534880E-02   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9.91939268E-02   7.03183821E-02   9.22370884E-02   1.38059182E-01   1.76641394E-01   1.47251976E-01   1.91968785E-01   2.44619057E-01   2.61200074E-01   2.38622266E-01   6.50134816E-02   1.28560405E-01   1.05111061E-01  -3.47140320E-02  -4.50865544E-02  -6.60444330E-02  -8.18420198E-02  -7.18581040E-02  -9.07803774E-02  -1.07498312E-01  -9.07741405E-02  -8.94906027E-02   5.72819774E-03  -3.64390361E-02  -1.61232266E-02  -1.37910886E-02  -1.76122350E-02  -2.48711855E-02  -2.91971047E-02  -2.77109516E-02  -3.29676817E-02  -3.41045637E-02  -1.88098465E-02  -3.24136725E-02   2.22237840E-02  -1.50460129E-02   5.52799875E-03   3.73954299E-02   4.74072900E-02   6.58914898E-02   7.55633538E-02   7.39157985E-02   8.54784644E-02   8.30807751E-02   3.77182786E-02   6.12475692E-02   5.67262605E-02   5.67301899E-02   7.64442967E-02\nCm   5.53552181E-02   6.80192374E-02   7.43732369E-02   5.22221341E-02   7.22482940E-02   3.40984235E-02   5.14088766E-03  -1.71766554E-02   3.11101267E-02   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2.73264562E-02   3.90727717E-02   1.80095992E-01   3.33190849E-02   3.65039955E-02   3.81413728E-02   3.37675885E-02   3.66009792E-02   4.92304550E-02   7.78694800E-02   1.08169258E-01   7.70382912E-02   1.07075631E-01   1.60485079E-01   2.93206580E-01   1.25807526E-01   3.45947173E-02   6.31312715E-02   4.38141618E-02  -2.53320452E-03  -3.31126459E-03  -4.91867470E-03  -6.22260801E-03  -5.28601718E-03  -6.81772116E-03  -8.47054387E-03  -8.33823220E-03  -1.62635861E-02   1.71570563E-02   9.19517742E-03   1.87663752E-02  -6.44236324E-02  -8.28255077E-02  -1.18669330E-01  -1.42319824E-01  -1.31166929E-01  -1.59949727E-01  -1.74813377E-01  -1.14560182E-01  -9.28876810E-02  -3.45666501E-02  -8.05549784E-02  -6.14983222E-02   5.28083799E-02   6.44754233E-02   8.26537598E-02   8.41850239E-02   9.33953803E-02   9.18020752E-02   6.30302368E-02   9.79478613E-03   4.88407710E-02   4.51523886E-02   6.56088021E-02   5.97020169E-02\nCm   2.03932472E-03   1.19758538E-03  -1.95895040E-02  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1.24557979E-02   1.45067327E-03   1.05051143E-06   9.13090648E-03   3.62992148E-02   8.79886740E-03   2.32053922E-02\nCm  -2.92456705E-02  -3.21229915E-02  -3.57248991E-02  -3.14445137E-02  -4.56973869E-02  -4.88122564E-02  -1.27609301E-02   1.29123024E-01  -4.27040236E-02  -5.36015919E-02  -3.68478125E-02  -1.91997821E-02   8.80953785E-03   1.16934023E-02   1.79634670E-02   2.38890439E-02   1.85807924E-02   2.50455853E-02   3.46194711E-02   4.81838786E-02   1.81661446E-02  -2.42664917E-02   7.18108266E-03  -1.70770792E-02   4.44105659E-02   5.88933748E-02   9.02859421E-02   1.19700334E-01   9.36433082E-02   1.25915332E-01   1.72980116E-01   2.35924581E-01   8.07659053E-02   1.49892335E-02   6.68582077E-02   3.52459850E-02  -7.13929303E-02  -9.22414449E-02  -1.33590050E-01  -1.62781691E-01  -1.46613705E-01  -1.81953262E-01  -2.06887230E-01  -1.53597254E-01  -1.93470688E-01  -4.37259326E-02  -1.00366770E-01  -5.99698611E-02  -1.57990928E-02  -1.89980881E-02  -2.35747167E-02  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2.25065696E-03   2.76361613E-03   2.64331560E-03   3.08602021E-03   2.75285063E-03   1.54303198E-03   1.29019929E-04   6.05741318E-03  -3.43852860E-03  -5.63731474E-03  -5.94338895E-03\nCm   1.65524560E-02   1.89576326E-02   1.40163477E-02  -5.07460812E-03   2.06629427E-02   3.18928264E-03  -4.83020523E-02  -1.69948726E-01  -1.49854038E-02  -6.96980156E-04   2.14186912E-02  -1.55625293E-02  -3.73538430E-02  -5.08266657E-02  -8.24813952E-02  -1.19062637E-01  -7.76688950E-02  -1.10103112E-01  -1.75279916E-01  -3.96388662E-01  -1.37253786E-01  -1.03246656E-02  -1.12042352E-01  -4.52655206E-02   5.59085661E-02   7.48963678E-02   1.17410716E-01   1.60929584E-01   1.17898373E-01   1.62472668E-01   2.37853547E-01   4.01040185E-01   1.29504745E-01   3.62501320E-02   1.06941955E-01   6.61681809E-02  -4.62270875E-02  -6.07442154E-02  -9.12750887E-02  -1.17458487E-01  -9.69544515E-02  -1.27071024E-01  -1.63986336E-01  -1.82410026E-01  -1.75496075E-01  -1.34450442E-02  -9.11149232E-02  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4.62693219E-02   1.18788387E-01   6.61097225E-02  -3.22094793E-02  -4.12533998E-02  -5.86234625E-02  -6.94609002E-02  -6.51051419E-02  -7.83007471E-02  -8.29744865E-02  -4.93480231E-02  -4.62574586E-02  -2.53774985E-02  -6.31744204E-02  -5.37643937E-02  -1.59723337E-02  -2.00407272E-02  -2.72414426E-02  -3.02340227E-02  -3.07530371E-02  -3.41053917E-02  -3.02690902E-02  -1.03643008E-02  -8.92469673E-03  -2.99244289E-02  -5.07104629E-02  -5.78615036E-02   2.94918385E-02   3.56688754E-02   4.48109220E-02   4.43135557E-02   5.04147517E-02   4.73873518E-02   2.96227548E-02   3.45510529E-03   2.54235569E-02   3.12821290E-02   9.65631073E-02   8.38921830E-02\nCm   5.83721609E-02   8.69263108E-02   1.34566346E-01   1.62961326E-01   1.39381307E-01   1.51995927E-01   1.91700333E-01   3.58682828E-01   1.69094028E-01   5.99423218E-02   2.55928168E-01   1.87019271E-01   3.10596255E-02   4.15876637E-02   6.51236840E-02   8.91171791E-02   6.55074954E-02   9.01755941E-02   1.31625943E-01   2.19734261E-01   6.32226492E-02   6.87511114E-02   1.29729117E-01   1.26285702E-01   6.33088234E-02   8.40505161E-02   1.29176606E-01   1.71902299E-01   1.33536039E-01   1.80091984E-01   2.49264190E-01   3.48451903E-01   2.03049270E-01   8.05877653E-02   1.22671869E-01   1.19145084E-01  -2.35750803E-02  -3.11137416E-02  -4.71997511E-02  -6.16059090E-02  -4.95998657E-02  -6.58291306E-02  -8.75698820E-02  -1.07485945E-01  -5.87872701E-02   4.37021209E-02  -2.47206792E-02   2.94134196E-02  -3.85295795E-02  -5.00672899E-02  -7.34205561E-02  -9.11297165E-02  -7.98119869E-02  -1.00996888E-01  -1.20055287E-01  -1.02620279E-01  -1.33468286E-01   4.93453827E-03  -3.56277308E-02  -3.68400224E-03\nCm   4.08389090E-02   3.97587145E-02   4.64959282E-02   7.24063294E-02   2.56692802E-02   7.05125565E-02   1.76366254E-01   2.76783861E-01   6.81428017E-02   7.67359002E-02   1.82118355E-02   6.06244279E-02   5.40293585E-02   7.10105817E-02   1.06747098E-01   1.37456056E-01   1.13336903E-01   1.48628213E-01   1.92071573E-01   2.14608204E-01   1.74572326E-01   3.43526160E-02   1.32760960E-01   6.40954679E-02   1.85420289E-02   2.43447382E-02   3.65143694E-02   4.68624736E-02   3.88615489E-02   5.08072477E-02   6.51816247E-02   7.11362841E-02   6.51062787E-02   5.09803269E-03   2.65361316E-02   1.25511683E-03  -6.04258644E-02  -7.31862849E-02  -9.22246616E-02  -9.16076002E-02  -1.03840451E-01  -9.82744456E-02  -6.23182571E-02  -7.59335418E-03  -8.02134606E-02  -3.38930655E-02  -6.14228705E-02  -4.18001781E-02   1.26954434E-02   1.52844378E-02   1.90153290E-02   1.85382132E-02   2.13318434E-02   1.96119957E-02   1.17061058E-02   1.18564159E-03   1.13992148E-02   1.47319552E-02   2.17575105E-02   1.76167550E-02\nCm   2.75744186E-02   2.49659934E-02   3.22609639E-02   5.41482761E-02   3.26920920E-02   7.68577334E-02   1.07563005E-01   5.68448589E-02   6.28481533E-02   2.07735973E-02   7.97483473E-02  -2.36308291E-02   6.63695286E-03   9.06697585E-03   1.48457146E-02   2.17192597E-02   1.37055998E-02   1.95266554E-02   3.16585318E-02   7.66334307E-02   2.83707278E-02   4.92081628E-02   2.56530213E-02   6.73066445E-02  -4.02660529E-02  -5.32345186E-02  -8.10656232E-02  -1.06409787E-01  -8.47972541E-02  -1.13088356E-01  -1.52227448E-01  -1.94205606E-01  -1.32324385E-01  -3.39947621E-02  -1.15969896E-01  -8.29267666E-02   2.10097870E-02   2.76394445E-02   4.16360173E-02   5.37803510E-02   4.41056202E-02   5.80018794E-02   7.54613916E-02   8.61710080E-02   3.00987656E-02   4.34312214E-02   7.99945421E-02   8.77499361E-02   6.87307476E-02   8.76486515E-02   1.23390385E-01   1.44191826E-01   1.37683057E-01   1.62914269E-01   1.66522462E-01   8.84604654E-02   1.47985863E-01   8.10888628E-02   6.63388468E-02   9.31346187E-02\nCm  -1.95406716E-02  -1.87297442E-02  -1.49364321E-02  -5.92162605E-03  -1.79450808E-02  -1.16482693E-02   2.21173870E-02   7.80680904E-02   1.58842463E-03  -7.28882382E-03  -1.99440773E-02  -4.99045853E-03  -7.78058270E-03  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1.27100595E-01   3.37935670E-04   4.58817424E-04   7.40950068E-04   1.06177459E-03   7.04879107E-04   9.96076499E-04   1.56900162E-03   3.41405368E-03  -1.91926934E-02   2.27619861E-02   1.64333758E-02   2.03951841E-02   6.12757205E-02   8.09226361E-02   1.22935368E-01   1.60797865E-01   1.28967352E-01   1.71477873E-01   2.29126638E-01   2.85343465E-01   1.43981762E-01   4.77274390E-02   1.97610115E-01   1.10504154E-01   4.43937186E-03   5.68713791E-03   8.08563182E-03   9.58717088E-03   8.97726757E-03   1.08056505E-02   1.14715413E-02   6.86170162E-03   9.29640563E-03   3.69636455E-03  -5.69104915E-04  -3.28217680E-03  -6.00791609E-02  -7.33581577E-02  -9.40562976E-02  -9.58217268E-02  -1.06282558E-01  -1.04506604E-01  -7.18067872E-02  -1.11842804E-02  -1.17945839E-01  -3.07158783E-02  -6.15631582E-02  -3.94924094E-02\nCm   1.62088415E-02   2.56818548E-02   4.61111241E-02   5.81584976E-02   7.16925271E-02   9.72266917E-02   5.92585565E-02  -1.81511395E-01   4.81569315E-02   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1.89839489E-01   2.20094015E-01   1.73780136E-01   1.68847724E-01   3.45500023E-02   1.63126070E-01   9.42456330E-02  -1.57552550E-02  -1.97639042E-02  -2.68521275E-02  -2.97807113E-02  -3.03165250E-02  -3.35897553E-02  -2.97511894E-02  -1.01233606E-02  -3.03546471E-02  -1.72767241E-02  -1.19141771E-02  -1.40535815E-02  -4.77489662E-02  -5.48183135E-02  -6.16467188E-02  -5.18872742E-02  -6.54104610E-02  -4.69989954E-02  -1.68668438E-02  -3.64076654E-04  -2.57307242E-02  -4.65959923E-02  -3.74089430E-02  -3.93136372E-02\nCm   1.03660583E-02   8.02154774E-03  -9.77558488E-04  -1.58254233E-02   6.30905286E-04  -1.39933573E-02  -4.85785719E-02  -1.22340278E-01  -8.85980908E-03   2.04574444E-02  -6.59613717E-03   2.31216575E-03  -5.44104551E-02  -7.11985247E-02  -1.06008472E-01  -1.34576880E-01  -1.13668509E-01  -1.47095943E-01  -1.84194777E-01  -1.85936407E-01  -9.01686751E-02  -3.77300746E-02  -1.41353780E-01  -8.61656171E-02   3.26275983E-03   4.21944122E-03   6.12308456E-03   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1.11816680E-01   1.00500418E-01   1.24915033E-01   1.42524177E-01   1.06974818E-01   5.84873489E-02   2.48908325E-02   1.24413790E-01   7.05882686E-02  -3.55023608E-02  -4.21797112E-02  -5.10141798E-02  -4.77279372E-02  -5.66033007E-02  -4.87246052E-02  -2.53639542E-02  -1.69300136E-03  -3.32072104E-02  -1.74717710E-02  -1.63551562E-02  -1.27830395E-02  -3.84625323E-02  -4.55881659E-02  -5.48583237E-02  -5.09477656E-02  -6.07245724E-02  -5.16456940E-02  -2.62214546E-02  -1.62215576E-03  -2.86023639E-02  -3.28053260E-02  -5.96387103E-02  -5.40784870E-02\nCm   7.12801238E-02   6.83550187E-02   5.62933422E-02   2.86576202E-02   5.89771050E-02   3.27350592E-02  -3.89519212E-02  -1.62568274E-01   9.53602237E-03   4.98408812E-02   7.51631817E-02   5.89393190E-02  -6.54137060E-02  -8.57740996E-02  -1.28289025E-01  -1.63957918E-01  -1.36937213E-01  -1.78335950E-01  -2.26686726E-01  -2.40133749E-01  -1.39999938E-01  -1.86973174E-02  -7.10715569E-02  -3.32147012E-02   3.41720890E-02   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5.92654952E-02   7.63256181E-02   1.04245109E-01   1.70589539E-01   2.49363161E-01   1.57690121E-01   2.24601012E-01   3.63746587E-01   8.76850517E-01   2.94416675E-01   4.59451127E-02   2.08599824E-01   1.10355488E-01  -4.20259697E-02  -5.61296223E-02  -8.74085530E-02  -1.18624740E-01  -8.86819581E-02  -1.21376656E-01  -1.74483582E-01  -2.76674877E-01  -7.76777705E-02  -3.32778091E-02  -6.74937446E-02  -5.08463510E-02  -4.91584755E-03  -6.44340156E-03  -9.62887643E-03  -1.22903766E-02  -1.02869937E-02  -1.33809575E-02  -1.69607708E-02  -1.78039102E-02  -1.46449314E-02   5.96863024E-03  -7.80641459E-03   1.11748513E-02  -5.10173293E-02  -6.28285299E-02  -8.20452850E-02  -8.58563597E-02  -9.28916786E-02  -9.49938289E-02  -7.09042577E-02  -1.42363848E-02  -6.48039977E-02  -4.66683424E-02  -4.50019321E-02  -4.42333886E-02\nCm   1.47564823E-02   1.91265685E-02   1.45918294E-02  -1.08407343E-02   1.56191003E-02  -2.82194715E-02  -7.52813406E-02  -8.35075539E-02  -3.84794407E-02   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2.64527341E-02   2.34218523E-02   2.94216534E-02   3.43886210E-02   2.78605559E-02   2.36730110E-02   9.87112586E-03   2.41639009E-02   1.36194035E-02   6.04394997E-02   7.65506682E-02   1.06187265E-01   1.21419218E-01   1.19203590E-01   1.37351134E-01   1.32443981E-01   5.86629827E-02   9.90331095E-02   2.78972088E-02   1.83459711E-02   1.90286624E-02  -4.68572803E-02  -5.82887840E-02  -7.77786253E-02  -8.40083815E-02  -8.80362443E-02  -9.41264682E-02  -7.72322474E-02  -2.07505995E-02  -7.26939718E-02  -1.31029232E-02  -3.23541996E-02  -1.67474062E-02\nCm   1.38513887E-02   2.01371592E-02   3.49668515E-02   3.89301381E-02   5.21599809E-02   4.22721735E-02   1.04524240E-02  -1.14199083E-02   2.37358669E-02  -1.83569515E-02   1.12082359E-01   6.36170494E-02  -5.14731627E-02  -6.79890396E-02  -1.03326892E-01  -1.35227820E-01  -1.08346487E-01  -1.44130522E-01  -1.92816516E-01  -2.41065987E-01  -1.07411752E-01  -3.15848869E-02  -1.12325282E-01  -6.24746188E-02   6.98006547E-02   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1.02618855E-01   1.22845963E-01   1.06852490E-01   7.81780522E-02  -4.25896209E-02   7.10325113E-02   3.59865738E-02   2.63173028E-01   2.17174287E-01  -6.15709446E-02  -8.29178502E-02  -1.31509364E-01  -1.83421936E-01  -1.29491956E-01  -1.80418054E-01  -2.72275999E-01  -5.09382614E-01  -1.61827064E-01  -1.43376463E-02  -1.23032190E-01  -4.68487979E-02   2.26118447E-02   3.02609393E-02   4.73333461E-02   6.46634089E-02   4.76969812E-02   6.55831237E-02   9.54363396E-02   1.57678698E-01   3.09917012E-02   7.05591690E-02   1.53009501E-01   1.61502727E-01   6.99688384E-02   9.23249359E-02   1.39997675E-01   1.82611240E-01   1.47190849E-01   1.95245068E-01   2.59379620E-01   3.16986270E-01   1.40461601E-01   8.90070140E-02   1.57685659E-01   1.53946912E-01  -3.74670343E-03  -4.83815347E-03  -6.99849729E-03  -8.51262317E-03  -7.68728129E-03  -9.52181491E-03  -1.07794127E-02  -7.89304508E-03  -1.99763066E-02   3.31973902E-02   1.36187535E-02   3.44930943E-02\nCm   3.17991887E-02   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4.17880505E-01   1.13752030E-01   6.19553032E-02   4.39245122E-02   7.18774107E-02   6.01095732E-02   8.02975222E-02   1.25097715E-01   1.69882005E-01   1.26838338E-01   1.73678817E-01   2.49967022E-01   3.97952316E-01   1.74043212E-01   4.71506783E-02   1.21368290E-01   7.21592968E-02   1.12313177E-02   1.43853968E-02   2.04440188E-02   2.42260975E-02   2.27034745E-02   2.73085630E-02   2.89468860E-02   1.72312590E-02   1.07421474E-02   9.71640092E-03   4.19202856E-02   2.21225794E-02   1.16272841E-02   1.46486885E-02   2.00882389E-02   2.25855711E-02   2.26306706E-02   2.55242747E-02   2.34939085E-02   9.00607039E-03   1.76310994E-02   2.61930519E-03   6.05617921E-03  -2.18799069E-03  -4.63534678E-02  -5.59678001E-02  -7.00600372E-02  -6.89195246E-02  -7.87424027E-02  -7.34156497E-02  -4.51215892E-02  -4.99706540E-03  -2.01677783E-02  -3.44680452E-02  -3.06468346E-02  -4.00929216E-02\nCm  -5.58905585E-02  -7.22856019E-02  -9.00394020E-02  -7.76151926E-02  -1.02302205E-01  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1.58528349E-02   3.75865711E-02   1.41488135E-02   7.16154715E-03   9.84915414E-03  -3.47390752E-02  -4.32991936E-02  -5.80216796E-02  -6.30586752E-02  -6.56474428E-02  -7.07866343E-02  -5.91445836E-02  -1.68052036E-02  -5.88740729E-02  -1.38707534E-02  -4.63220344E-02  -3.75592541E-02\nCm   1.08467665E-02   1.62720187E-02   3.51107895E-02   6.08844384E-02   3.79386422E-02   6.53413100E-02   1.05255018E-01   1.80167344E-01   5.15004459E-02   4.22578738E-02   6.18005528E-02   1.00001709E-01   2.95915478E-02   3.97609382E-02   6.27465684E-02   8.68622624E-02   6.23217522E-02   8.64374079E-02   1.28785492E-01   2.30543998E-01   9.84521778E-02   2.07786495E-02   9.47359808E-02   6.99105711E-02  -7.59200269E-03  -1.01580243E-02  -1.58813617E-02  -2.16805907E-02  -1.60152710E-02  -2.20102306E-02  -3.19877103E-02  -5.26189088E-02  -3.00383672E-02  -5.74867541E-03  -1.64377378E-02  -1.17454311E-02   4.37088959E-02   5.23276807E-02   6.43252674E-02   6.16247492E-02   7.18599032E-02   6.42673962E-02   3.62169815E-02   3.07818004E-03   5.64812304E-02   4.18161187E-02   5.79079480E-02   5.74458070E-02  -5.53177400E-02  -6.41270617E-02  -7.36137589E-02  -6.38373083E-02  -7.92766252E-02  -6.00372807E-02  -2.39982519E-02  -7.18111396E-04  -4.57193500E-02  -4.30649702E-02  -2.43695082E-02  -3.48489916E-02\nCm  -3.21329648E-02  -1.44438761E-02   4.29703623E-02   1.13241435E-01   8.14338599E-02   1.66832864E-01   2.07669363E-01   1.12438543E-01   7.74084253E-02  -7.27597164E-02   6.29890745E-02  -1.14547534E-02   2.30154833E-02   2.96832302E-02   4.28217728E-02   5.18790200E-02   4.71232826E-02   5.81152582E-02   6.51462194E-02   4.62418500E-02   3.73595338E-02   3.04674896E-02   1.42670907E-02   2.51006065E-02   6.63392133E-02   8.39628042E-02   1.16288738E-01   1.32666921E-01   1.30613201E-01   1.50069315E-01   1.43810481E-01   6.24767533E-02   1.34406037E-01   6.39808200E-02   6.83283851E-02   8.32461439E-02   3.03101891E-02   3.70246351E-02   4.75127671E-02   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9.88898602E-02   5.62774555E-02   7.46333552E-02   1.14426609E-01   1.51726818E-01   1.18667235E-01   1.59580945E-01   2.19290357E-01   2.99360611E-01   1.20542570E-01   5.07404801E-02   9.29377612E-02   6.58654793E-02  -5.28304754E-02  -6.85786296E-02  -1.00336828E-01  -1.24117905E-01  -1.09274474E-01  -1.37797599E-01  -1.62491338E-01  -1.35394830E-01  -7.21703119E-02  -2.25116919E-02  -3.79613595E-02  -3.21440823E-02   3.77659395E-02   4.84946322E-02   6.92991544E-02   8.27888228E-02   7.67183930E-02   9.31437676E-02   1.00804931E-01   6.40521459E-02   6.80697391E-02   3.80590065E-02   5.91303287E-02   5.01924442E-02  -4.88004911E-02  -6.18234937E-02  -8.58016486E-02  -9.81821211E-02  -9.63019929E-02  -1.11065571E-01  -1.07313790E-01  -4.78314822E-02  -7.43429518E-02  -2.91757441E-02  -4.01838881E-02  -3.47915688E-02\nCm  -1.61617966E-02  -1.91276170E-02  -2.96922074E-02  -4.60472934E-02  -2.59505019E-02  -4.47449626E-02  -8.40018703E-02  -1.64805285E-01  -1.42333184E-02  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3.83296376E-02   4.36181831E-02   4.09789614E-02   2.55906806E-02   2.97554729E-03   2.48663513E-02   1.48465896E-02   1.47161841E-02   1.23755262E-02\nCm  -3.11739439E-02  -2.71024269E-02  -1.90221410E-02  -8.58228934E-03  -1.87927550E-02  -1.74487102E-02   1.82704135E-03   1.13533851E-01  -2.20420666E-03  -3.41382607E-02  -4.88674421E-02  -5.31222775E-03   6.90226103E-02   9.17444680E-02   1.41367544E-01   1.88853544E-01   1.45625815E-01   1.96991508E-01   2.74746959E-01   3.93903389E-01   2.26885645E-01   2.52104911E-02   2.17899402E-01   9.63472209E-02  -6.98006547E-02  -9.16060477E-02  -1.37272078E-01  -1.75933676E-01  -1.46237816E-01  -1.90948416E-01  -2.44235069E-01  -2.63969948E-01  -2.38206990E-01  -4.25068333E-02  -1.81075509E-01  -1.16010317E-01  -1.27990494E-02  -1.63273574E-02  -2.30018984E-02  -2.69080611E-02  -2.56576371E-02  -3.03978890E-02  -3.11578156E-02  -1.66965202E-02  -1.96088666E-02  -2.81218056E-02  -2.00610238E-02  -2.63209328E-02   6.68779986E-04   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4.36963439E-01   2.74620521E-01   4.30890607E-02   1.47275512E-01   8.73471715E-02  -2.32136827E-02  -3.01140183E-02  -4.39978583E-02  -5.43131273E-02  -4.79705733E-02  -6.03614727E-02  -7.08269732E-02  -5.80954461E-02  -2.62496300E-02   1.75064822E-02  -4.13920117E-02   7.06916689E-04  -1.59888042E-03  -2.07380798E-03  -3.02882655E-03  -3.73693400E-03  -3.30325059E-03  -4.15416456E-03  -4.86818248E-03  -3.97691141E-03   7.94328857E-03  -2.37503106E-03  -2.77914626E-02  -2.37492355E-02  -3.83607538E-03  -4.84571105E-03  -6.68315316E-03  -7.57737434E-03  -7.51662781E-03  -8.56919086E-03  -8.07346727E-03  -3.32699357E-03  -8.33090548E-03   2.03268268E-02  -2.63952285E-03   1.49938951E-02\nCm  -9.38508095E-04   8.70387989E-03   3.09770958E-02   6.41814696E-02   2.23545957E-02   6.71589202E-02   1.58643487E-01   2.49780841E-01   2.86045671E-02  -9.53505414E-04   3.30732600E-02  -3.90153738E-03   6.54137060E-02   8.57740996E-02   1.28289025E-01   1.63957918E-01   1.36937213E-01   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6.99956555E-03   7.79014957E-03   5.40550453E-03   1.76475432E-02   4.10421044E-03  -2.21917241E-02  -1.55856280E-02  -3.31198962E-02  -4.08627834E-02  -5.35722602E-02  -5.63859215E-02  -6.06644179E-02  -6.25533157E-02  -4.75171989E-02  -1.00693665E-02  -3.24553720E-02   3.70024713E-03  -3.42231234E-02  -1.66717786E-02\nCm  -1.21658102E-02  -9.00911051E-03  -6.60750892E-03  -1.61869651E-02   8.81312585E-03  -5.67381285E-03  -6.33748376E-02  -1.79905845E-01  -5.79122769E-03  -1.37397805E-02   7.89540836E-03   1.28482941E-02  -7.29167179E-02  -9.59581319E-02  -1.44658334E-01  -1.87057817E-01  -1.53112867E-01  -2.01552748E-01  -2.62846805E-01  -3.02468595E-01  -2.23509028E-01  -2.19246798E-02  -7.60403209E-02  -2.58541589E-02   3.21558359E-02   4.18556006E-02   6.16050538E-02   7.68823121E-02   6.67602848E-02   8.49518054E-02   1.02285623E-01   9.10755746E-02   9.07549874E-02   1.53874056E-02   5.44951553E-02   2.09777487E-02   1.66788815E-02   2.10910511E-02   2.91552664E-02   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3.25255682E-02   7.73520163E-03   2.36277359E-02\nCm   2.43450000E-02   3.13769419E-02   5.54148593E-02   8.53557626E-02   6.87356624E-02   1.17208914E-01   1.32232473E-01   5.21738587E-02   6.59955795E-02   1.98848757E-02   8.42728500E-02   6.93277024E-02   4.26772978E-03   5.54258158E-03   8.11788484E-03   1.00576520E-02   8.83344189E-03   1.11572435E-02   1.32057022E-02   1.11344801E-02   4.72360449E-04   1.32518004E-03   1.97548673E-02   6.65312908E-03   1.33322512E-02   1.70844144E-02   2.43046784E-02   2.88445727E-02   2.69756509E-02   3.25041157E-02   3.45885394E-02   2.08425975E-02   3.66041564E-02   2.28820778E-02   2.31216920E-02   2.61078660E-02   5.15908319E-02   6.38563927E-02   8.42956936E-02   8.96220798E-02   9.54606956E-02   9.98491958E-02   7.81841494E-02   1.81879418E-02   5.67218022E-02   5.52028946E-02   1.19550545E-01   1.25210925E-01   6.08276798E-02   7.22255655E-02   8.72432527E-02   8.14737724E-02   9.67456794E-02   8.30307326E-02   4.29551816E-02   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3.47565274E-02   6.07926394E-02   8.05829585E-02   1.23419605E-01   1.63397343E-01   1.28167573E-01   1.72140871E-01   2.35810072E-01   3.18612013E-01   1.71666606E-01   4.06663609E-02   4.23657689E-02   3.90812348E-02   3.23374127E-02   4.21347933E-02   6.21536711E-02   7.78221850E-02   6.72246377E-02   8.58259333E-02   1.04132187E-01   9.50119499E-02   8.45201590E-02   3.64151349E-02   4.64690617E-02   3.35471611E-02  -4.83102329E-02  -5.82125350E-02  -7.25559302E-02  -7.09262896E-02  -8.14423030E-02  -7.51921349E-02  -4.52771099E-02  -4.71049273E-03  -7.41978161E-02  -1.00640287E-02  -2.26918038E-02  -1.18416457E-02  -1.50830497E-02  -1.55205307E-02  -1.38602689E-02  -8.36426093E-03  -1.13415713E-02  -4.23740357E-03  -4.04422546E-04  -1.60932035E-07  -6.36153772E-03  -3.56931614E-03  -9.11469219E-03  -6.29996346E-03\nCm  -1.99109939E-02  -4.07043760E-02  -1.00397373E-01  -1.73465249E-01  -1.20512653E-01  -2.16051278E-01  -3.18280922E-01  -2.57953541E-01  -8.72738699E-02   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4.96782590E-02\nCm   3.03835937E-02   3.30385193E-02   1.11226355E-02  -4.78735466E-02   7.80599146E-03  -7.75578202E-02  -1.72878451E-01  -2.62321021E-01  -5.40803120E-02   5.09054046E-02   4.56266267E-02   8.93216823E-02  -7.07711384E-02  -9.34795638E-02  -1.42068074E-01  -1.85933282E-01  -1.48967494E-01  -1.98170693E-01  -2.65121118E-01  -3.31505156E-01  -9.44529492E-02  -2.63246721E-02  -4.42697859E-02  -3.11923296E-02   3.21450130E-02   4.15964293E-02   6.04455286E-02   7.40209018E-02   6.61771176E-02   8.25684120E-02   9.50291924E-02   7.33126165E-02   4.81018175E-02   2.14180434E-02   7.57417691E-02   5.93899619E-02  -5.88097083E-03  -7.39363044E-03  -1.00933471E-02  -1.12728872E-02  -1.13837153E-02  -1.27291379E-02  -1.15001644E-02  -4.16083997E-03  -1.41219290E-02  -7.04590110E-04   9.08246634E-03   7.11122070E-03   3.57547161E-02   3.94630313E-02   4.08352793E-02   3.04699539E-02   4.01737589E-02   2.30872896E-02   5.25604825E-03   2.86676877E-05   1.68020417E-02   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1.65983260E-01   2.31257721E-01   3.30409342E-01   1.67576099E-01   4.11262022E-02   1.65303317E-01   9.86748363E-02   1.93734655E-02   2.52165285E-02   3.71119387E-02   4.63097852E-02   4.02202823E-02   5.11738373E-02   6.15985877E-02   5.47996803E-02   5.37696261E-02   3.04551447E-02   3.79946175E-02   4.32207664E-02  -5.51134746E-02  -6.88891785E-02  -9.28776100E-02  -1.01848355E-01  -1.05002033E-01  -1.14601110E-01  -9.82707531E-02  -3.02523084E-02  -1.04963768E-01  -4.61019637E-02  -7.71660711E-02  -6.27896218E-02  -5.22905709E-02  -6.41044059E-02  -8.28996466E-02  -8.55219415E-02  -9.37840886E-02  -9.39413913E-02  -6.71167462E-02  -1.17823892E-02  -6.58084132E-02  -5.32170780E-02  -1.07984359E-01  -9.10804166E-02\nCm  -3.38959490E-02  -3.33302004E-02  -3.46938889E-02  -3.99988681E-02  -2.32903989E-02  -2.21434875E-02  -5.04454997E-02  -2.26086106E-01  -2.87371242E-02  -2.30661626E-02  -1.80044143E-02  -1.08156904E-02  -5.92030473E-02  -7.91637092E-02  -1.23596813E-01  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7.18677613E-02  -3.28115262E-02  -4.36335262E-02  -6.73041416E-02  -9.00513219E-02  -6.92322210E-02  -9.37641884E-02  -1.31172545E-01  -1.89965144E-01  -7.63392647E-02  -6.11640317E-03  -1.06677793E-01  -4.44800300E-02   5.04609603E-02   6.70712203E-02   1.03344855E-01   1.38050728E-01   1.06463578E-01   1.44009239E-01   2.00828530E-01   2.87816446E-01   1.60829717E-01   4.25550406E-02   2.03625602E-01   9.47807498E-02   5.22905709E-02   6.41044059E-02   8.28996466E-02   8.55219415E-02   9.37840886E-02   9.39413913E-02   6.71167462E-02   1.17823892E-02   8.02450839E-02   6.15982976E-02   8.30916215E-02   8.17253441E-02   2.18943687E-02   2.63416787E-02   3.27248575E-02   3.18373648E-02   3.66945765E-02   3.36262017E-02   1.99348312E-02   1.97757359E-03   2.83216613E-02   4.26283665E-02   2.16302260E-02   3.83563419E-02\nCm   6.76353704E-02   8.71487270E-02   1.19031599E-01   1.39825957E-01   1.17638508E-01   1.44537401E-01   1.92508125E-01   1.96566077E-01   5.44632147E-02   5.28619014E-02   4.25305397E-02   4.73178251E-02   6.37509554E-02   8.31866888E-02   1.23099740E-01   1.54858297E-01   1.32764001E-01   1.70293767E-01   2.08872112E-01   1.97306245E-01   1.39435518E-01   2.90845222E-02   3.84394068E-02   2.09724674E-02   2.19238595E-02   2.58073299E-02   3.06039860E-02   2.78234611E-02   3.36232564E-02   2.76037119E-02   1.30280052E-02   6.45492319E-04   1.03307363E-02   2.70083083E-02   2.75056702E-02   2.50030663E-02  -6.06012283E-02  -7.10040322E-02  -8.33712149E-02  -7.47124864E-02  -9.10833251E-02  -7.29835041E-02  -3.27637880E-02  -1.39432813E-03  -7.10188930E-02  -3.29333538E-03  -1.86337990E-02  -5.77761874E-03   2.79463671E-02   3.02521440E-02   3.00506124E-02   2.11381937E-02   2.82563644E-02   1.44697982E-02   2.60782132E-03   7.03105010E-06   1.15056486E-02   2.84331126E-02   1.18364016E-02   1.54764141E-02\nCm  -1.90442498E-02  -1.50307185E-02  -6.44268503E-03   1.06987260E-02  -1.24145301E-02   1.15941962E-02   6.48995665E-02   1.12993444E-01  -5.08175599E-03   2.28141476E-02   3.32684260E-03   2.94114276E-02  -1.80971337E-02  -2.38288028E-02  -3.59653618E-02  -4.65897141E-02  -3.80163432E-02  -5.01230361E-02  -6.56165744E-02  -7.64506142E-02  -4.36146327E-02  -2.84528109E-02  -1.91434165E-02  -2.66115081E-02   4.91199118E-02   6.45220613E-02   9.68747288E-02   1.24517487E-01   1.02990178E-01   1.34836132E-01   1.73559578E-01   1.91458186E-01   1.12422956E-01   2.00714548E-02   4.80799360E-02   3.16700889E-02   2.32194783E-02   2.89712844E-02   3.89093599E-02   4.24268264E-02   4.40117406E-02   4.76701731E-02   4.02138624E-02   1.17695916E-02   5.08858383E-02   2.41159350E-02   3.42897663E-02   2.99425534E-02  -6.64690994E-02  -8.13438132E-02  -1.04800226E-01  -1.07524349E-01  -1.18506355E-01  -1.17752496E-01  -8.27113917E-02  -1.37829950E-02  -4.44468031E-02  -4.21404797E-02  -1.89930776E-02  -3.45861952E-02\nCm  -7.09641806E-02  -8.93968533E-02  -1.01684715E-01  -8.10488499E-02  -9.85102449E-02  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1.00905130E-01   4.63451399E-02   1.12852445E-01   2.17855326E-01   3.18323888E-01   9.36775826E-02   6.81267562E-02   2.61078120E-02   2.74425122E-02   5.30544149E-02   7.04619271E-02   1.08378399E-01   1.44395591E-01   1.11916516E-01   1.51075707E-01   2.09594677E-01   2.95278455E-01   1.60643605E-01   2.49824402E-02   7.85990758E-02   3.17446936E-02   5.49626322E-03   7.15681428E-03   1.05421181E-02   1.31719314E-02   1.14164449E-02   1.45445982E-02   1.75605601E-02   1.57737646E-02   1.80097852E-03   2.59605129E-02   2.76098519E-02   2.99501165E-02   1.35574278E-02   1.70147977E-02   2.31402628E-02   2.57018546E-02   2.61203935E-02   2.89967496E-02   2.57906843E-02   8.89006310E-03   2.41427675E-02   5.32755772E-03   7.76897590E-03  -7.35617613E-04  -5.29383756E-02  -6.23393647E-02  -7.39859961E-02  -6.73434083E-02  -8.13210193E-02  -6.68941497E-02  -3.17007086E-02  -1.59023814E-03  -2.97225004E-02  -2.32648320E-02  -3.67423535E-02  -2.83980243E-02\nCm   9.08736550E-03   1.47710894E-02   2.38885122E-02   3.16700523E-02   2.36114501E-02   3.45158808E-02   5.18211705E-02   5.90486973E-02   3.16079069E-02   2.64917999E-02   3.99540608E-02   4.68202429E-02  -3.27864823E-02  -4.40868795E-02  -6.96887586E-02  -9.67120246E-02  -6.90215082E-02  -9.58766023E-02  -1.43462376E-01  -2.60619261E-01  -5.92505936E-02  -3.10711110E-02  -4.68007111E-02  -4.97922771E-02   5.67335566E-02   7.55489831E-02   1.16884950E-01   1.57093017E-01   1.19726105E-01   1.62704665E-01   2.29613186E-01   3.42306115E-01   1.11999690E-01   5.29855805E-02   8.43281990E-02   8.08562284E-02  -6.50162111E-02  -8.35481304E-02  -1.19582844E-01  -1.43199948E-01  -1.32258557E-01  -1.61007494E-01  -1.75302005E-01  -1.13515204E-01  -1.41881468E-01  -4.77509392E-02  -6.39389450E-02  -5.78668261E-02   5.24544282E-02   6.73924598E-02   9.64177578E-02   1.15386711E-01   1.06665549E-01   1.29758287E-01   1.41051902E-01   9.08770520E-02   8.85760618E-02   5.78644702E-02   9.48562530E-02   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6.02759434E-02   9.48728854E-02   1.05930608E-01  -6.22661186E-02  -7.77699334E-02  -1.04677805E-01  -1.14510397E-01  -1.18370683E-01  -1.28771348E-01  -1.09651755E-01  -3.30339964E-02  -8.87823710E-02  -2.94029040E-02  -4.54354388E-02  -3.22786758E-02\nCm   7.10502562E-02   7.62841271E-02   8.73709138E-02   9.18776230E-02   8.85370537E-02   9.73484339E-02   9.68005475E-02   7.98508873E-02   5.08273635E-02   5.22918775E-02   7.03226297E-02   6.28821050E-02   6.84643564E-02   8.83501530E-02   1.27616738E-01   1.54896934E-01   1.40316043E-01   1.73399369E-01   1.95274793E-01   1.40638562E-01   1.35391706E-01   3.65532225E-02   7.61600600E-02   6.46393287E-02  -4.85192160E-02  -6.18535647E-02  -8.70143506E-02  -1.01576544E-01  -9.71255875E-02  -1.14779959E-01  -1.16997025E-01  -6.16147904E-02  -9.86842176E-02   3.29591747E-04  -1.98584938E-02  -4.00301456E-03   2.85849790E-05   3.59835120E-05   4.92585515E-05   5.52390509E-05   5.55183698E-05   6.24082039E-05   5.70296287E-05   2.13763119E-05  -3.69647633E-03   1.44760096E-02   3.67119666E-03   5.50043019E-03   3.40969135E-02   3.99700810E-02   4.69820562E-02   4.21680501E-02   5.13601867E-02   4.12624653E-02   1.86242796E-02   8.05752261E-04   2.67878220E-02   5.05505372E-02   3.00269316E-02   6.20971232E-02\nCm   3.07766982E-02   4.26494030E-02   5.91616787E-02   6.01137157E-02   6.85074657E-02   6.51858413E-02   4.06706290E-02  -8.94108859E-04   3.69652029E-02   1.82653410E-02   7.53525514E-02   5.06171961E-02   5.33385286E-02   7.09048974E-02   1.09282026E-01   1.46041785E-01   1.12537294E-01   1.52273414E-01   2.12525102E-01   3.05395631E-01   1.98889061E-01   4.17658276E-02   1.04426953E-01   6.29536767E-02  -6.07926394E-02  -8.05829585E-02  -1.23419605E-01  -1.63397343E-01  -1.28167573E-01  -1.72140871E-01  -2.35810072E-01  -3.18612013E-01  -1.02044705E-01  -6.15476272E-03  -4.60166090E-02  -1.40398403E-02   5.22192251E-02   6.40911982E-02   8.30886625E-02   8.60289936E-02   9.40220091E-02   9.46812716E-02   6.84080472E-02   1.24292868E-02   3.01647601E-02   5.06882894E-02   3.46386780E-02   5.04384952E-02  -2.00401938E-02  -2.28891654E-02  -2.54615699E-02  -2.10949502E-02  -2.67870315E-02  -1.87104225E-02  -6.33726156E-03  -1.14811856E-04  -1.65101615E-02  -8.47557629E-04  -1.45209173E-02  -6.28545764E-03\nCm   1.81589363E-02   1.86263588E-02   3.06962493E-02   4.94290027E-02   4.64940938E-02   8.73331216E-02   7.92996994E-02  -9.49770204E-02   4.58308804E-02  -7.01306442E-03   8.85779742E-02   1.66256193E-02   1.53443535E-02   2.06308679E-02   3.26039289E-02   4.52310586E-02   3.23046349E-02   4.48642471E-02   6.70912843E-02   1.21630538E-01   7.48658534E-02   3.96675465E-02   4.53175387E-02   7.40591398E-02  -4.36022566E-02  -5.85635156E-02  -9.23385340E-02  -1.27661447E-01  -9.18479701E-02  -1.27285100E-01  -1.89217034E-01  -3.36111947E-01  -1.25023903E-01  -7.98605465E-03  -9.28741851E-02  -4.05073569E-02   5.12886578E-02   6.58640934E-02   9.41362187E-02   1.12488832E-01   1.04204080E-01   1.26550187E-01   1.37046335E-01   8.72547283E-02   6.68164949E-02   5.12413347E-02   1.09596905E-01   1.25427109E-01   2.99766277E-02   3.80614367E-02   5.30798531E-02   6.11732531E-02   5.94680646E-02   6.91923817E-02   6.81573374E-02   3.22599778E-02   5.55620019E-02   2.51102876E-02   4.34571575E-02   2.93403881E-02\nCm  -1.70114416E-02  -1.45299957E-02  -1.26915420E-02  -1.80038496E-02  -4.57645085E-03  -2.21173895E-02  -5.66109741E-02  -2.72182144E-02  -4.12028889E-03  -2.79194915E-02   1.81658338E-02   2.74291400E-02   7.88172850E-03   1.03557649E-02   1.55569769E-02   2.00125522E-02   1.65292370E-02   2.16565979E-02   2.79263051E-02   3.09857741E-02   3.84005182E-02   2.35945511E-02  -5.31298469E-03   6.93019221E-03  -4.24350644E-02  -5.38208709E-02  -7.48799278E-02  -8.59965525E-02  -8.39680348E-02  -9.72789115E-02  -9.49247965E-02  -4.36292896E-02  -1.03822504E-01  -4.01336178E-02  -1.08544851E-01  -7.74910063E-02  -1.97517746E-02  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2.48345079E-02  -3.59631823E-02  -3.67506409E-02   7.37659077E-05   5.80221055E-02   1.37514435E-01   2.21205916E-01   6.14986582E-03   7.97843417E-03   1.16584294E-02   1.43946611E-02   1.27097301E-02   1.59960685E-02   1.87785824E-02   1.54267788E-02  -3.45194378E-03   2.99955061E-03   1.67466773E-02   7.45743377E-03  -7.16163173E-02  -9.06537246E-02  -1.25591303E-01  -1.43339487E-01  -1.41048018E-01  -1.62143271E-01  -1.55558193E-01  -6.78205792E-02  -1.36756485E-01  -4.32919462E-02  -5.61440113E-02  -4.83230592E-02  -1.00313288E-02  -1.25580832E-02  -1.69874859E-02  -1.87195193E-02  -1.91948252E-02  -2.10869530E-02  -1.83378800E-02  -5.89573100E-03  -1.14274860E-02  -2.34219039E-03  -9.18798520E-03  -7.01512502E-03   2.10914953E-02   2.63615825E-02   3.55360263E-02   3.89600853E-02   4.01758285E-02   4.38361582E-02   3.75666824E-02   1.15429807E-02   1.44959791E-02   5.49890377E-02   8.57337391E-02   1.04020824E-01\nCm   1.98093001E-03   1.19453373E-03  -1.00328471E-02  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8.54069566E-02   8.86229814E-02   9.59551082E-02   8.08838688E-02   2.36163372E-02   7.15965684E-02   3.48747280E-02   2.61045071E-02   3.21434358E-02\nCm  -1.89485475E-02  -2.01428994E-02  -1.73177732E-03   4.08453575E-02   4.98818035E-03   6.33313933E-02   1.34046980E-01   1.43241401E-01   4.05610320E-02  -3.06168414E-02  -8.17576110E-03  -2.16671748E-02   3.80518673E-02   4.92766331E-02   7.17217474E-02   8.80397500E-02   7.84278906E-02   9.81027632E-02   1.13563706E-01   8.92337156E-02   8.49130656E-02   2.34913758E-02   6.42762757E-02   4.09905285E-02   4.34637167E-02   5.57973842E-02   7.96924776E-02   9.51306508E-02   8.82520001E-02   1.07051120E-01   1.15625311E-01   7.30099798E-02   6.99908069E-02   2.45891253E-02   5.75806619E-02   3.93188166E-02  -4.29079857E-02  -5.32167232E-02  -7.05561295E-02  -7.54932408E-02  -7.98921883E-02  -8.43129545E-02  -6.72830296E-02  -1.65930865E-02  -5.98539477E-02  -2.63793753E-02  -6.22989564E-02  -4.61462136E-02  -2.87341010E-02  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1.63227665E-01   2.22746083E-01   2.97199284E-01   1.06015338E-01   2.52783735E-02   6.29814776E-02   3.77319303E-02  -5.05543782E-02  -6.68142715E-02  -1.01671028E-01  -1.33313144E-01  -1.06445694E-01  -1.41830070E-01  -1.90489282E-01  -2.41245603E-01  -1.61918575E-01  -5.46186189E-03  -8.65640364E-02  -2.83236813E-02  -1.36253113E-02  -1.77984571E-02  -2.64002822E-02  -3.33274395E-02  -2.84107988E-02  -3.65669855E-02  -4.52108435E-02  -4.38142744E-02  -3.09680753E-02   1.77138658E-03  -2.40675313E-02  -2.44619525E-03   2.78573654E-02   3.45109761E-02   4.56441981E-02   4.86639875E-02   5.16879509E-02   5.42764580E-02   4.28555252E-02   1.02286085E-02   4.17356306E-02   2.15988475E-02   1.99592070E-02   1.72122255E-02\nCm   5.26606083E-02   6.76144460E-02   9.81978623E-02   1.33601867E-01   8.15001508E-02   1.20915243E-01   2.20789986E-01   4.54677951E-01   1.07366007E-01   5.83005722E-02   1.41801074E-01   1.09280434E-01   7.84268000E-02   1.05185778E-01   1.65321911E-01   2.27478941E-01   1.65313778E-01   2.28398158E-01   3.36694080E-01   5.81224681E-01   1.41424963E-01   5.84178952E-02   1.84336313E-01   1.30467165E-01  -8.51381619E-03  -1.13952406E-02  -1.78289121E-02  -2.43663362E-02  -1.79583137E-02  -2.46993477E-02  -3.59686908E-02  -5.95738920E-02  -5.15936452E-02   4.57155157E-02  -5.51627138E-04   6.15342629E-02  -2.22435173E-02  -2.90016465E-02  -4.28417290E-02  -5.37551116E-02  -4.62783682E-02  -5.92082757E-02  -7.21891006E-02  -6.69028107E-02  -3.59505746E-02   1.54442043E-03  -3.48255589E-02  -1.82349355E-02  -3.35841539E-02  -3.76667982E-02  -4.03185162E-02  -3.15934512E-02  -4.10200037E-02  -2.58664934E-02  -7.11134449E-03  -6.85578789E-05  -2.12979280E-02  -1.57742566E-02  -2.00437949E-02  -1.90301358E-02\nCm   1.18906361E-02   2.05631302E-02   4.41168931E-02   7.48380780E-02   4.17484388E-02   7.58170058E-02   1.46786613E-01   2.43067570E-01   7.63801796E-02   3.74515693E-02   4.56357304E-02   5.37823326E-02   1.56092604E-02   2.05949993E-02   3.12238975E-02   4.07174078E-02   3.28350079E-02   4.35449730E-02   5.78168279E-02   7.05307829E-02   5.27338805E-02   2.96560776E-02   1.89176045E-02   2.44939774E-02   4.33052193E-02   5.68140090E-02   8.50720144E-02   1.08910188E-01   9.06994785E-02   1.18307211E-01   1.50950157E-01   1.61856626E-01   1.03885534E-01   3.14128968E-02   1.20050752E-01   6.57963383E-02   1.79588913E-02   2.34202167E-02   3.46127670E-02   4.34597287E-02   3.73737288E-02   4.78483343E-02   5.84311251E-02   5.44272224E-02   6.67442916E-02   3.29531700E-03  -6.01297851E-05  -2.21931416E-03  -6.11870103E-02  -7.69437120E-02  -1.05093854E-01  -1.17465534E-01  -1.18514767E-01  -1.32654216E-01  -1.20105677E-01  -4.37467118E-02  -6.97717608E-02  -2.23132741E-02  -4.73272147E-02  -3.18056102E-02\nCm  -7.82595470E-02  -1.02440406E-01  -1.61945612E-01  -2.42525424E-01  -1.32817943E-01  -2.07466355E-01  -3.97594748E-01  -1.00192187E+00  -2.14478280E-01  -1.19411759E-01  -1.89608740E-01  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5.42101207E-03   5.97745457E-03   4.02790267E-03   7.52035171E-03   1.24685282E-02   4.64181067E-03   6.41803057E-03  -4.11388268E-02  -5.01980210E-02  -6.42696227E-02  -6.53393667E-02  -7.26070339E-02  -7.11719661E-02  -4.85834141E-02  -7.41691902E-03  -4.15749986E-02  -3.29066381E-02  -6.09573804E-02  -5.13304268E-02\nCm   3.74559583E-02   5.16934352E-02   6.40102671E-02   5.63359977E-02   5.84643150E-02   4.26320967E-02   4.70549746E-02   6.71753594E-02   5.27138153E-02   5.60765141E-02   6.35330221E-02   1.03574542E-01   5.05543782E-02   6.68142715E-02   1.01671028E-01   1.33313144E-01   1.06445694E-01   1.41830070E-01   1.90489282E-01   2.41245603E-01   1.19486093E-01   3.29052073E-02   1.11542789E-01   5.72682807E-02  -2.66630693E-02  -3.52075083E-02  -5.34710069E-02  -6.99097588E-02  -5.61137827E-02  -7.45830975E-02  -9.95687295E-02  -1.23640163E-01  -7.52754369E-02   6.61981846E-03  -2.01526329E-02   2.29170357E-03  -4.33052193E-02  -5.68140090E-02  -8.50720144E-02  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9.80390687E-02   1.24972579E-01   3.37396812E-02   1.36776712E-01   8.30396883E-02   3.63252371E-02   4.58940882E-02   6.33211491E-02   7.18345614E-02   7.12095577E-02   8.12397297E-02   7.66602874E-02   3.17453640E-02   4.42287590E-02   3.30599075E-02   5.28076196E-02   4.43992347E-02  -5.80666879E-02  -7.32124276E-02  -1.00566977E-01  -1.13348086E-01  -1.13243233E-01  -1.28127410E-01  -1.18747021E-01  -4.64991937E-02  -1.18206106E-01  -5.46795918E-02  -5.87926399E-02  -7.11448658E-02\nCm   6.51510058E-02   7.48953360E-02   8.71445470E-02   7.71863614E-02   9.94843741E-02   8.07376657E-02   2.51697355E-02  -4.67227725E-02   7.17444347E-02   4.46199698E-02   6.33026464E-02   5.38178636E-02  -2.81195815E-02  -3.64403319E-02  -5.31206254E-02  -6.53557282E-02  -5.80192196E-02  -7.27498868E-02  -8.46808800E-02  -6.77121876E-02  -6.16788905E-02  -2.25534463E-03  -5.60016482E-02  -2.30699606E-02  -9.41137661E-03  -1.20558510E-02  -1.71379329E-02  -2.03164099E-02  -1.90292307E-02  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1.00793511E-01   2.31292724E-02   1.40008299E-03   4.27564188E-02   1.13836915E-02  -7.19572653E-04  -9.27321260E-04  -1.33553419E-03  -1.61400747E-03  -1.47133299E-03  -1.80958606E-03  -2.01606042E-03  -1.40349758E-03   6.10917115E-03   2.88648173E-02  -5.53206315E-03   1.86764818E-02   6.93262611E-02   8.89543665E-02   1.26910951E-01   1.51253733E-01   1.40630767E-01   1.70275659E-01   1.83164060E-01   1.14181542E-01   1.40085986E-01   3.67771933E-02   8.24531143E-02   5.29369407E-02  -6.09841836E-02  -7.45574680E-02  -9.58531800E-02  -9.80397466E-02  -1.08357455E-01  -1.07174972E-01  -7.45570014E-02  -1.20612914E-02  -1.17149102E-01  -1.77276414E-02  -6.13217796E-02  -2.42474832E-02   2.23825793E-02   2.53419934E-02   2.76734495E-02   2.23211735E-02   2.86675302E-02   1.90717474E-02   5.84789419E-03   7.84085904E-05   1.50910140E-02   1.77256030E-02   1.54899328E-02   1.29660413E-02\nCm  -1.32093597E-02  -2.70641246E-02  -4.30398060E-02  -3.83780709E-02  -5.35869807E-02  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1.77678534E-02   1.96267276E-02   2.52341287E-02   5.76295761E-02   7.49528935E-02   1.10125200E-01   1.37077074E-01   1.19519949E-01   1.51685958E-01   1.81523531E-01   1.58511838E-01   1.28499712E-01   5.25192282E-02   1.58248902E-01   1.12985390E-01   3.06394830E-02   3.96740758E-02   5.77338297E-02   7.08485039E-02   6.31415215E-02   7.89569370E-02   9.13355645E-02   7.16062810E-02   1.15610844E-01   5.06011825E-02   5.46023168E-02   6.62223524E-02  -4.42177513E-02  -5.59491160E-02  -7.74434601E-02  -8.82730910E-02  -8.70004840E-02  -9.98500031E-02  -9.54560865E-02  -4.11611400E-02  -9.08831473E-02  -1.50283243E-02  -5.47422862E-02  -3.19782019E-02\nCm  -5.67042402E-02  -6.24809467E-02  -6.58889665E-02  -4.74344433E-02  -7.02579073E-02  -3.53457394E-02   9.73825271E-03   2.50554885E-02  -8.58344347E-03  -9.56311325E-02  -1.42907484E-01  -2.00574820E-01  -2.34313958E-02  -3.07495847E-02  -4.60729277E-02  -5.90386111E-02  -4.90882053E-02  -6.40859341E-02  -8.19381727E-02  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1.07275884E-01   1.69808532E-01   2.36146031E-01   1.67778982E-01   2.33353962E-01   3.50418546E-01   6.44430366E-01   2.52688155E-01   7.02322169E-02   2.71760542E-01   1.78468642E-01  -6.31740922E-03  -8.31720877E-03  -1.25499483E-02  -1.62507140E-02  -1.32696761E-02  -1.74892632E-02  -2.28755703E-02  -2.65778860E-02   3.76897884E-03   1.96177313E-02  -4.09547156E-02  -1.95990787E-02  -2.45382385E-02  -3.16986340E-02  -4.58910835E-02  -5.58885550E-02  -5.03781270E-02  -6.24842793E-02  -7.09517955E-02  -5.24536638E-02  -7.02098311E-02  -1.06504653E-03  -4.74000766E-02  -1.54550470E-02  -1.05289439E-02  -1.25374156E-02  -1.52361551E-02  -1.43544670E-02  -1.69415397E-02  -1.47497866E-02  -7.86081352E-03  -5.63637694E-04  -1.12160551E-03  -2.29065383E-02  -3.76725202E-02  -4.89947527E-02\nCm  -8.38674460E-03  -4.39449561E-03   1.64143835E-02   5.08621468E-02   2.76509210E-02   8.28728165E-02   1.15000111E-01   5.17169073E-02   4.53015048E-02  -6.71488104E-03   9.87475644E-03  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2.11760370E-02   1.57957435E-02   3.66234851E-02   2.54993537E-02   3.36182478E-02   5.08826263E-02   6.61875435E-02   5.36132487E-02   7.09459703E-02   9.37014964E-02   1.12355574E-01   6.45593582E-02   2.45692183E-02   7.82324978E-02   7.23415428E-02   8.88683182E-03   1.14284010E-02   1.63839803E-02   1.96666133E-02   1.81027918E-02   2.20971351E-02   2.42043730E-02   1.59733136E-02   2.26561392E-02  -1.10616389E-02   4.89756753E-03  -1.03716120E-02  -6.87839458E-02  -8.68459574E-02  -1.19653373E-01  -1.35457327E-01  -1.34618056E-01  -1.53173070E-01  -1.43708186E-01  -5.84542604E-02  -6.95689128E-02  -4.50513999E-02  -1.07984276E-01  -7.90731123E-02   2.80411272E-04   3.53026650E-04   4.83376489E-04   5.42246811E-04   5.44772374E-04   6.12646526E-04   5.60376655E-04   2.10662547E-04   4.17695633E-04   7.32204701E-03  -2.38639919E-04   3.24207417E-03\nCm   1.43842030E-02   1.28051473E-02   1.60873335E-02   2.99546306E-02   1.53129830E-02   3.82349120E-02   5.46280096E-02   1.01269054E-01   1.58317824E-02   6.08035432E-03   3.66029963E-02  -1.39327517E-02   1.18213847E-02   1.57527647E-02   2.44088177E-02   3.28797788E-02   2.49477651E-02   3.39607606E-02   4.81355959E-02   7.28088318E-02   5.08235637E-02   2.20245825E-02   1.98619651E-02   2.08113163E-02   1.85675644E-02   2.44830095E-02   3.70680194E-02   4.82407864E-02   3.90426784E-02   5.16865077E-02   6.83341210E-02   8.22095005E-02   4.61011061E-02   1.38520709E-02   2.39540633E-02   1.33781863E-02  -6.91713285E-02  -8.80035217E-02  -1.23261906E-01  -1.42967029E-01  -1.37851779E-01  -1.61649951E-01  -1.61981906E-01  -8.08743059E-02  -1.31055347E-01  -4.20013171E-02  -1.28459454E-01  -6.87023601E-02   6.00361820E-02   7.47138169E-02   9.97844727E-02   1.07917686E-01   1.12935841E-01   1.20965374E-01   9.96351786E-02   2.70880657E-02   1.00411949E-01   5.35628347E-02   8.83087154E-02   7.68677243E-02\nCm  -1.54366292E-02  -1.23586935E-02   1.62036925E-03   2.83665258E-02  -3.55551430E-03   2.08396209E-02   8.80704905E-02   2.50453075E-01   4.25143425E-02  -1.44327814E-02  -1.77690215E-02  -3.31685125E-02   7.64001625E-02   1.01295810E-01   1.55225481E-01   2.05668169E-01   1.61085849E-01   2.16491445E-01   2.97038000E-01   4.03451297E-01   2.25993897E-01   3.39129897E-02   1.17173895E-01   5.17778391E-02  -1.59861409E-02  -2.10959764E-02  -3.19957808E-02  -4.17479417E-02  -3.36314085E-02  -4.46232886E-02  -5.93202580E-02  -7.26504344E-02  -1.52484003E-02  -8.20613956E-03  -6.62742297E-02  -3.79101652E-02  -2.03152920E-02  -2.62560987E-02  -3.80517256E-02  -4.64134211E-02  -4.17411211E-02  -5.18588070E-02  -5.91110889E-02  -4.42293191E-02  -3.76655159E-02  -7.66386422E-03  -3.18566422E-02  -1.72044960E-02  -4.23428352E-02  -5.34652866E-02  -7.36734100E-02  -8.34222254E-02  -8.28838621E-02  -9.43339163E-02  -8.85574555E-02  -3.60879054E-02  -6.74476511E-02  -2.06757587E-02  -4.54991863E-02  -2.25486361E-02\nCm   5.65370724E-02   5.91201232E-02   6.13679849E-02   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3.64153343E-02   1.25718899E-01   1.03035955E-01  -5.07775442E-02  -6.39807238E-02  -8.77637533E-02  -9.87154457E-02  -9.88639115E-02  -1.11564574E-01  -1.02809244E-01  -3.95526639E-02  -8.56046987E-02  -4.16334274E-02  -6.20059417E-02  -4.45565468E-02\nCm   2.57636768E-02   3.94995585E-02   6.01810719E-02   6.81402152E-02   5.96813385E-02   4.64321411E-02   6.01256842E-02   2.41098589E-01   6.74466222E-02   2.58885664E-02   1.36395019E-01   1.17763567E-01   1.07950987E-02   1.44379545E-02   2.25528116E-02   3.07476293E-02   2.27742344E-02   3.12708465E-02   4.53364874E-02   7.39716235E-02   4.38416195E-02   3.15077358E-02   3.46419339E-02   4.77338964E-02   7.00494448E-02   9.31556828E-02   1.43699260E-01   1.92281785E-01   1.47804683E-01   2.00190785E-01   2.80103898E-01   4.05862795E-01   1.50909164E-01   9.11981883E-02   1.68524158E-01   1.60125070E-01  -1.62115882E-02  -2.11838819E-02  -3.14446084E-02  -3.97379691E-02  -3.38161859E-02  -4.35696640E-02  -5.40007312E-02  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8.38995976E-02   6.17599037E-02   1.18827339E-02   4.10653936E-02   5.85445391E-02   1.09952302E-01   1.37866231E-01  -2.12883512E-02  -2.55482403E-02  -3.15693497E-02  -3.04738073E-02  -3.53343369E-02  -3.19830950E-02  -1.84800514E-02  -1.69512369E-03  -3.07343120E-02   1.37114033E-02  -2.24302735E-02   9.57147569E-03\nCm   1.76842489E-02   4.35103518E-03  -1.35509334E-02  -1.05443098E-02  -3.30295186E-02  -7.30026602E-03   4.36985101E-02   4.88666574E-02   2.91543768E-02   3.67407686E-02  -6.32729258E-02  -3.41143594E-02  -5.13154948E-02  -6.69694935E-02  -9.91320678E-02  -1.24764165E-01  -1.06884483E-01  -1.37160365E-01  -1.68409308E-01  -1.59618911E-01  -1.34979695E-01  -4.73619488E-02  -7.99216112E-02  -7.49985294E-02   6.98163616E-02   9.08104198E-02   1.33447772E-01   1.66151378E-01   1.44810372E-01   1.83832093E-01   2.20129400E-01   1.92603489E-01   2.06127415E-01   3.28638174E-02   7.46903095E-02   3.57688188E-02   1.64102672E-02   2.09019244E-02   2.93487405E-02   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2.41881021E-02   1.92427411E-02   4.70049351E-03   2.38814296E-02   1.34609898E-02   1.28747399E-02   1.13784367E-02   6.43342485E-03   7.54374922E-03   8.87257914E-03   7.97053788E-03   9.70284671E-03   7.80695215E-03   3.53470587E-03   1.54371591E-04   4.64761683E-03   2.28010716E-02   7.29297216E-03   2.33334941E-02\nCm   3.84109799E-02   4.98764293E-02   7.43483921E-02   8.96637864E-02   8.96857563E-02   1.06261777E-01   9.65783626E-02   2.63628913E-02   8.37987644E-02   3.42141562E-02   5.73981142E-02   3.74237363E-02  -9.01818925E-03  -1.18352923E-02  -1.77347924E-02  -2.27288066E-02  -1.88936142E-02  -2.46692740E-02  -3.15509585E-02  -3.40913037E-02  -3.55972124E-02   2.45347504E-02   1.33293656E-02   2.30326840E-02   1.42700050E-02   1.82844902E-02   2.60070162E-02   3.08562836E-02   2.88680770E-02   3.47731768E-02   3.69765858E-02   2.22315265E-02   1.73012225E-02   2.02151742E-02   7.79096194E-03   1.75180219E-02   6.53723889E-02   8.22819090E-02   1.12606232E-01   1.26226511E-01   1.26925219E-01   1.42601694E-01   1.30163585E-01   4.86171939E-02   1.22792254E-01   4.80595156E-02   5.49808836E-02   4.56086756E-02  -2.45260039E-02  -3.04799180E-02  -4.05867684E-02  -4.37038987E-02  -4.59465453E-02  -4.89187519E-02  -3.97794846E-02  -1.03958252E-02  -3.02693289E-02  -2.43207637E-03  -2.79712738E-02  -1.81827762E-02\nCm   6.13178906E-02   4.55893783E-02   1.22674505E-02  -1.74608867E-02  -1.60740111E-02  -4.25778041E-02  -3.74323376E-02   4.43329884E-02  -2.48593139E-02   4.56274873E-02   7.03381630E-03  -1.13636603E-03   2.09555035E-02   2.76968752E-02   4.21509588E-02   5.52784236E-02   4.41244128E-02   5.88004175E-02   7.90010841E-02   1.00164407E-01   6.11838021E-02   4.00055460E-03   4.13574877E-02   1.19661468E-02   9.41137661E-03   1.20558510E-02   1.71379329E-02   2.03164099E-02   1.90292307E-02   2.28995088E-02   2.42979991E-02   1.45100872E-02   6.30017197E-03   1.52132225E-02   2.38866815E-02   2.21986282E-02  -6.47137157E-02  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2.59526892E-03   3.70622153E-03   4.42337847E-03   4.10459656E-03   4.97789258E-03   5.37406042E-03   3.38835328E-03  -1.73169998E-03   1.47546809E-02   3.57701035E-03   9.08833048E-03  -5.05601925E-02  -6.46384185E-02  -9.14917807E-02  -1.07773904E-01  -1.01819673E-01  -1.21624904E-01  -1.26949216E-01  -7.20046035E-02  -1.30925964E-01  -1.31947566E-02  -1.09659852E-01  -4.70170762E-02  -3.00886409E-02  -3.65625207E-02  -4.63983794E-02  -4.65630516E-02  -5.23284385E-02  -5.03038614E-02  -3.29609856E-02  -4.43928457E-03  -4.90850878E-02  -6.64110385E-03  -2.17194703E-02  -1.12815503E-02\nCm  -4.83641995E-02  -5.51040340E-02  -6.44029076E-02  -5.43451898E-02  -8.03838262E-02  -5.78069203E-02   1.09555905E-02   5.67960303E-02  -4.43614813E-02  -7.71328999E-02  -5.71755666E-02  -8.88427603E-02   1.29798332E-02   1.68873963E-02   2.48307117E-02   3.09423425E-02   2.69317543E-02   3.42187498E-02   4.10575365E-02   3.61540648E-02   1.55928988E-02   1.77256414E-03   2.82575509E-02   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1.34353821E-02  -4.90961502E-03  -6.63067316E-03  -1.05830016E-02  -1.49007855E-02  -1.03018777E-02  -1.44304849E-02  -2.21198779E-02  -4.36904801E-02  -5.55619276E-03   1.85803065E-03  -4.25511295E-03   3.14114230E-03   5.91668989E-02   7.85275692E-02   1.20607361E-01   1.60338227E-01   1.24789451E-01   1.68162631E-01   2.32289027E-01   3.22591755E-01   1.45305338E-01   4.14512573E-02   6.51082696E-02   5.76073223E-02   1.95120146E-02   2.57488371E-02   3.90525711E-02   5.09554215E-02   4.10490619E-02   5.44651096E-02   7.24029890E-02   8.86708317E-02   9.06487030E-03   4.96119249E-02   7.02416155E-02   7.55575954E-02  -5.19024291E-02  -6.41198193E-02  -8.42981085E-02  -8.90894094E-02  -9.54634880E-02  -9.90107586E-02  -7.61462347E-02  -1.67608071E-02  -5.13840808E-02  -3.13990735E-02  -9.34802819E-02  -6.30662598E-02\nCm   1.13927871E-02   2.08850071E-02   2.76619833E-02   1.22478617E-02   4.29131423E-02   1.08202528E-02  -6.36492613E-02  -1.01968568E-01  -1.65132876E-02   5.33955822E-03   6.61948442E-02   4.36141535E-02   1.51122756E-03   2.02341081E-03   3.16830781E-03   4.33514220E-03   3.18734223E-03   4.38727926E-03   6.40270329E-03   1.06815498E-02   5.15199627E-03   2.34089221E-02   1.35626000E-02   3.76700295E-02  -1.78306337E-03  -2.34172940E-03  -3.51449070E-03  -4.51460878E-03  -3.73796981E-03  -4.89109231E-03  -6.28744834E-03  -6.90631756E-03   2.10288858E-02  -5.03815381E-03  -3.53214125E-02  -2.66771044E-02  -3.67458964E-02  -4.78973249E-02  -7.07132694E-02  -8.86495208E-02  -7.64257647E-02  -9.76941032E-02  -1.18873349E-01  -1.09463213E-01  -6.62712465E-02  -4.86285141E-04  -2.95526621E-02  -3.53245300E-03   5.98484563E-02   7.14282622E-02   8.72277581E-02   8.27659027E-02   9.71912586E-02   8.55937280E-02   4.67156995E-02   3.60151342E-03   5.90274505E-02   6.03249347E-02   7.56591136E-02   9.07023925E-02\nCm   2.17595075E-03   8.79352066E-03   3.10766365E-02   5.95874097E-02   3.90070565E-02   7.16210672E-02   1.12843090E-01   1.16928600E-01   3.78866779E-02   6.47114610E-03   3.44367843E-02   1.53653571E-02   4.90961502E-03   6.63067316E-03   1.05830016E-02   1.49007855E-02   1.03018777E-02   1.44304849E-02   2.21198779E-02   4.36904801E-02   2.37798498E-02   2.15908908E-03   1.79911939E-02   9.84608458E-03   5.07412571E-02   6.47666671E-02   9.13576956E-02   1.07070146E-01   1.01844544E-01   1.20926504E-01   1.24554374E-01   6.77686884E-02   6.50332582E-02   2.85970002E-02   2.21086252E-02   2.74727075E-02   2.36679897E-02   2.98703757E-02   4.11169331E-02   4.64854315E-02   4.62718402E-02   5.25600516E-02   4.91300047E-02   1.97554789E-02   3.77626192E-02   3.08677965E-02   1.33401498E-02   2.99968485E-02  -6.54769061E-02  -8.02153904E-02  -1.03583546E-01  -1.06632949E-01  -1.17164190E-01  -1.16994882E-01  -8.30387291E-02  -1.42860537E-02  -7.11944806E-02  -2.16293097E-02  -3.06724042E-02  -1.80568575E-02\nCm   3.50374166E-02   4.78759621E-02   7.80520985E-02   1.13055473E-01   7.78120105E-02   1.20680848E-01   1.78872226E-01   2.89828680E-01   1.08685962E-01   5.15019480E-02   7.12419804E-02   4.55912044E-02   5.00745057E-02   6.66857854E-02   1.03186965E-01   1.38712289E-01   1.05673822E-01   1.43630775E-01   2.02778303E-01   3.02711330E-01   1.34500963E-01   5.12558012E-02   1.13859965E-01   9.03995385E-02   1.84036196E-02   2.37241165E-02   3.41900595E-02   4.13591354E-02   3.76502088E-02   4.63554227E-02   5.17693139E-02   3.63148680E-02   2.55066187E-02   4.40340451E-03   5.72308593E-02   1.16263598E-02  -4.92856432E-02  -6.25811389E-02  -8.72835875E-02  -1.00607443E-01  -9.77843102E-02  -1.13795301E-01  -1.12138681E-01  -5.31444421E-02  -8.70823599E-02  -3.38724638E-02  -1.37673836E-01  -1.04276819E-01   5.08376783E-02   6.10032630E-02   7.53611709E-02   7.27190491E-02   8.43412333E-02   7.62973701E-02   4.40315077E-02   4.02391995E-03   4.89990287E-02   8.20607939E-02   9.95624338E-02   1.27653041E-01\nCm   3.06863812E-02   4.63614962E-02   8.40170967E-02   1.39795072E-01   6.67498602E-02   1.39890928E-01   2.82505124E-01   5.07978299E-01   1.71730707E-01   8.00436867E-02   8.89782280E-02   8.36978439E-02   4.08933941E-02   5.51550520E-02   8.77718791E-02   1.23037438E-01   8.59056168E-02   1.20038905E-01   1.82681509E-01   3.51859594E-01   1.01029415E-01   5.38313960E-02   1.50124104E-01   1.03895099E-01   1.52576868E-02   1.99989107E-02   2.98860572E-02   3.81470509E-02   3.19285788E-02   4.15318144E-02   5.26435847E-02   5.52630801E-02   3.18599179E-02   3.60622706E-02   3.40534544E-02   3.71501448E-02   3.34410127E-02   4.37393141E-02   6.50598902E-02   8.24723187E-02   6.98279992E-02   9.02361728E-02   1.12622351E-01   1.12489622E-01   9.85188851E-02   3.13517916E-02   6.48443100E-02   4.60650398E-02  -4.10667618E-02  -5.05876033E-02  -6.60976899E-02  -6.92252461E-02  -7.48379874E-02  -7.66226474E-02  -5.73360502E-02  -1.16015150E-02  -5.41367565E-02  -2.93757801E-02  -9.83252514E-02  -8.42885864E-02\nCm   2.58478517E-02   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8.75991060E-02   1.14416123E-01   1.32326950E-01   6.83540424E-02   5.37334971E-02   6.52440065E-02   5.86554276E-02   3.59406829E-02   4.62666877E-02   6.64760390E-02   8.00565892E-02   7.33477875E-02   8.98605882E-02   9.92430799E-02   6.72128561E-02   8.28394479E-02   6.04980531E-02   4.21267109E-02   7.64042557E-02  -6.79324481E-02  -8.51348515E-02  -1.15428974E-01  -1.27629614E-01  -1.30373767E-01  -1.43871207E-01  -1.26332281E-01  -4.18512937E-02  -1.13033882E-01  -2.25158179E-02  -4.24471446E-02  -2.65539753E-02\nCm   5.51108050E-02   7.60819425E-02   1.22022355E-01   1.77058267E-01   1.07100398E-01   1.65707551E-01   2.95550312E-01   6.11018744E-01   1.62517602E-01   1.17237864E-01   2.19522100E-01   1.95340769E-01   2.02871818E-02   2.74123438E-02   4.37998424E-02   6.17709917E-02   4.25491004E-02   5.96539294E-02   9.16823686E-02   1.82770826E-01   3.85754181E-02   7.07678767E-02   7.17995258E-02   1.06327151E-01   7.56760722E-02   1.01044322E-01   1.57255901E-01   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3.43943309E-04   1.43396290E-02   2.09939581E-02   2.80896032E-02   2.62410929E-02   3.28315641E-02   3.60351712E-02   3.68524859E-02   2.70351638E-02   3.58050155E-02   1.99123356E-02   4.24131680E-03   1.89243335E-05   1.62443181E-02   4.52462016E-02   2.99307533E-02   5.52021952E-02\nCm   3.97105380E-02   4.54057120E-02   4.99810454E-02   5.13314459E-02   3.72875788E-02   4.34943047E-02   7.42789391E-02   1.32365996E-01   3.73561655E-02   4.87487632E-02   2.60493861E-02   3.99974601E-02   5.84833710E-02   7.71083593E-02   1.16720370E-01   1.51854903E-01   1.22967549E-01   1.62746653E-01   2.15025940E-01   2.58142347E-01   1.30119556E-01   1.46020102E-02   7.95169808E-02   3.25994967E-02  -4.33860406E-02  -5.65193076E-02  -8.33353330E-02  -1.04274730E-01  -9.01698640E-02  -1.15044028E-01  -1.39368354E-01  -1.26540760E-01  -8.25799935E-02   7.13521137E-03  -3.12519070E-02  -6.73562022E-03   1.47054842E-02   1.79472949E-02   2.29879369E-02   2.33848734E-02   2.59718636E-02   2.54817881E-02   1.74278125E-02   2.67628549E-03   1.82843032E-02   3.98060390E-03   1.22309982E-02   4.30069822E-03  -2.03953495E-02  -2.45564335E-02  -3.05554813E-02  -2.97957628E-02  -3.42796080E-02  -3.15273776E-02  -1.88325578E-02  -1.91187692E-03  -1.67350394E-02  -2.60455620E-04  -6.74865115E-03  -2.26448984E-03\nCm  -1.75318947E-03   9.07453027E-03   3.43199784E-02   6.18822551E-02   4.23277047E-02   6.92325194E-02   1.04838027E-01   1.58375649E-01   4.18609374E-02  -3.37545256E-03   5.08436070E-02   2.70052490E-02   2.36705036E-02   3.11026074E-02   4.67307078E-02   6.01274070E-02   4.96435442E-02   6.50556425E-02   8.39287625E-02   9.32641109E-02   6.78883596E-02   2.09971513E-02   2.13560430E-02   1.78786248E-02   3.21744087E-02   4.18951196E-02   6.17124738E-02   7.71074952E-02   6.68305069E-02   8.51427500E-02   1.02799052E-01   9.23424549E-02   6.90457085E-02   3.54996853E-02   4.38566378E-02   5.52467781E-02   4.99019450E-03   6.28136641E-03   8.59744995E-03   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4.27818987E-03   7.92578315E-02   2.95412233E-02  -6.84571104E-02  -8.94381237E-02  -1.32708190E-01  -1.67614552E-01  -1.42768558E-01  -1.83845633E-01  -2.27567245E-01  -2.21357446E-01  -1.77499647E-01  -2.84831603E-02  -1.71993137E-01  -1.12281987E-01  -3.53752173E-02  -4.05595824E-02  -4.54858489E-02  -3.81315630E-02  -4.81606484E-02  -3.43578320E-02  -1.21509287E-02  -2.50902210E-04  -1.40128163E-02  -7.09010525E-02  -6.41524204E-02  -1.35627765E-01  -4.11609162E-03  -4.67352376E-03  -5.13411136E-03  -4.17717699E-03  -5.34591131E-03  -3.61331791E-03  -1.14436201E-03  -1.69205796E-05  -4.93167037E-03  -7.39788227E-04   5.40382792E-04   6.76181281E-04\nCm   2.54997824E-02   2.29327898E-02   6.08045068E-03  -2.28034427E-02  -7.26348334E-04  -3.38089514E-02  -7.97161137E-02  -1.04128613E-01  -1.66646957E-02   1.15686107E-02  -3.02215780E-02  -1.65888982E-02  -6.22275545E-02  -8.06621750E-02  -1.17651713E-01  -1.44872123E-01  -1.28444662E-01  -1.61198874E-01  -1.88016348E-01  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1.48720189E-01   1.41674308E-01   5.14023529E-02   5.73733154E-02   1.69394058E-03   9.91410352E-02   7.16203156E-02  -2.89550949E-03  -3.76299280E-03  -5.51953878E-03  -6.85333213E-03  -5.99881924E-03  -7.59393013E-03  -9.03462727E-03  -7.74355701E-03   1.78649433E-02   1.07153946E-02  -2.48259658E-02   2.08304997E-03   2.01258577E-02   2.58720598E-02   3.70607006E-02   4.44329395E-02   4.09690253E-02   4.99415598E-02   5.45395005E-02   3.56528111E-02   2.82682178E-02   3.09998432E-02   6.13530005E-02   6.89008097E-02   5.71930464E-02   7.09996261E-02   9.43209062E-02   1.01216155E-01   1.06791704E-01   1.13159740E-01   9.10885441E-02   2.30711139E-02   1.31482613E-01   5.44390367E-02   6.77623682E-02   7.72645742E-02   4.13339162E-02   4.81036085E-02   5.56787244E-02   4.88680121E-02   6.02927216E-02   4.66216109E-02   1.94505223E-02   6.62688829E-04   4.92888719E-02   6.82190747E-02   9.97066815E-02   1.34719856E-01\nCm   2.71223593E-02   2.66544420E-02   2.74593469E-02   3.48258863E-02   1.97569918E-02   3.97168304E-02   6.65319156E-02   8.12942385E-02   8.55474919E-03   5.90235614E-02   4.96899393E-02   6.21299004E-02   3.93395903E-02   5.13288042E-02   7.59427442E-02   9.55097724E-02   8.19183005E-02   1.05047336E-01   1.28765768E-01   1.21397290E-01   9.65654810E-02   2.00334477E-02   1.19950035E-01   6.96612925E-02  -2.01258577E-02  -2.58720598E-02  -3.70607006E-02  -4.44329395E-02  -4.09690253E-02  -4.99415598E-02  -5.45395005E-02  -3.56528111E-02  -3.30881616E-02  -1.61480137E-03  -1.40991675E-02   2.30121403E-03  -5.23896233E-03  -6.62775572E-03  -9.17054831E-03  -1.04471896E-02  -1.03035424E-02  -1.18171369E-02  -1.12800851E-02  -4.84125496E-03  -2.63652965E-03   4.00782990E-03  -1.56750047E-02  -2.18028262E-03   1.76859958E-02   2.08082953E-02   2.46493661E-02   2.23749214E-02   2.70652737E-02   2.21618001E-02   1.04033362E-02   5.07068542E-04   2.03855652E-02   2.65463124E-02   2.74485792E-02   4.07695539E-02\nCm   2.25628622E-02   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1.14085360E-01   3.33793898E-01   3.41782005E-01   5.87399621E-02   7.69416515E-02   1.14812853E-01   1.46232324E-01   1.22840196E-01   1.59461481E-01   2.01152544E-01   2.07909544E-01   1.42425435E-01   9.48740776E-02   2.81274244E-01   2.72830369E-01   5.19075130E-02   6.66099183E-02   9.50507843E-02   1.13315188E-01   1.05314436E-01   1.27556758E-01   1.37312833E-01   8.57969534E-02   7.66301787E-02   1.14819907E-01   2.18548162E-01   2.60956861E-01   3.54590189E-03   4.44395423E-03   6.02565801E-03   6.66317797E-03   6.80572996E-03   7.51124246E-03   6.59731495E-03   2.18734606E-03  -2.22602574E-03   4.77555496E-02   2.06931622E-02   5.32150847E-02  -2.53716247E-02  -3.10488711E-02  -4.00007467E-02  -4.10383757E-02  -4.52319681E-02  -4.49407914E-02  -3.15620975E-02  -5.25689561E-03  -2.16384534E-02  -1.34478220E-02  -6.67006224E-02  -7.70351560E-02\nCm   9.29340110E-03   3.01676709E-03  -1.51924882E-02  -3.66344084E-02  -2.12468797E-02  -4.19388220E-02  -7.77339221E-02  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7.21766803E-02   7.86650670E-02   9.12195579E-02\nCm   2.40113257E-02   3.38529628E-02   4.67727670E-02   5.05342470E-02   4.68102588E-02   4.89297611E-02   6.07812241E-02   5.54696865E-02   1.04394670E-02   1.98624580E-02   5.90194536E-02   5.36633137E-02   2.31055726E-02   2.99352644E-02   4.36145006E-02   5.36175104E-02   4.76560640E-02   5.97055580E-02   6.93645001E-02   5.51296183E-02   5.62460800E-02   3.36192868E-02   2.11151498E-02   3.26241801E-02  -4.62771823E-02  -5.75194361E-02  -7.66153443E-02  -8.25358786E-02  -8.67311711E-02  -9.23978381E-02  -7.52331650E-02  -1.97399792E-02  -7.63410748E-02  -1.17431432E-02  -2.73609391E-02  -1.42178444E-02   6.72016436E-02   8.32786862E-02   1.10218852E-01   1.17627382E-01   1.24810682E-01   1.31243136E-01   1.03933291E-01   2.50330209E-02   6.07336936E-02   4.41970280E-02   7.84500581E-02   6.99614598E-02  -3.60487993E-02  -4.37412373E-02  -5.53355154E-02  -5.52795897E-02  -6.23642085E-02  -5.95379847E-02  -3.84498130E-02  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8.34932505E-02   7.66425981E-03   9.68565058E-03   1.33708459E-02   1.51807670E-02   1.50339728E-02   1.71690835E-02   1.62372811E-02   6.77047801E-03   2.99804911E-02  -1.51897572E-02  -8.95241090E-03  -2.27784911E-02\nCm   3.37937860E-02   3.30570582E-02   1.57453864E-02  -2.54063769E-02   9.32911390E-03  -5.41256293E-02  -1.17555925E-01  -9.40081913E-02  -3.90718617E-02   2.52323304E-02   3.39959773E-02   3.95643487E-02  -3.73572357E-02  -4.83771558E-02  -7.04127585E-02  -8.64332927E-02  -7.69963491E-02  -9.63125113E-02  -1.11492404E-01  -8.76088940E-02  -8.33808987E-02  -9.76165445E-03  -4.31974632E-02  -1.74641923E-02   2.34138018E-02   3.01684054E-02   4.34324127E-02   5.24594097E-02   4.78604813E-02   5.88272633E-02   6.54488966E-02   4.53645468E-02   6.71799915E-02   2.13501419E-02   2.74821522E-02   2.93053663E-02  -4.66447940E-02  -5.93239827E-02  -8.30312595E-02  -9.62013023E-02  -9.28879603E-02  -1.08781387E-01  -1.08691931E-01  -5.37831641E-02  -1.04041925E-01  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9.92005362E-03   7.14026968E-02   4.19859025E-02   5.46703260E-02   5.65237447E-02  -1.72809842E-02  -1.92651918E-02  -2.03605364E-02  -1.56632570E-02  -2.04636109E-02  -1.24649526E-02  -3.19389776E-03  -2.48911576E-05  -1.10531865E-02  -1.21427368E-02  -2.86418724E-03  -6.74708323E-03\nCm  -1.45250539E-02  -1.60461283E-02  -1.74693986E-02  -2.34767960E-02  -2.55812332E-03  -4.33818291E-03  -4.98204846E-02  -2.10817463E-01  -1.55714775E-02  -1.19374140E-02  -1.08167326E-02  -3.44774130E-02  -2.75131340E-02  -3.70736440E-02  -5.88754240E-02  -8.22747974E-02  -5.78395386E-02  -8.06774826E-02  -1.22148232E-01  -2.31093653E-01  -1.04488733E-01  -1.11315691E-02  -2.45590402E-02  -8.43943517E-03  -1.58216213E-02  -2.02755121E-02  -2.88478965E-02  -3.42425338E-02  -3.20160071E-02  -3.85854052E-02  -4.10786467E-02  -2.47891012E-02  -3.06449309E-02  -1.12895834E-02  -4.20944531E-02  -2.27518245E-02  -1.42464058E-02  -1.80920758E-02  -2.52410449E-02  -2.91069026E-02  -2.82743587E-02  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2.06771609E-02   7.34747110E-02   2.97589673E-01   1.22998588E-02   3.45084160E-02   3.55468177E-02   4.17302508E-02   4.61460552E-02   6.20719895E-02   9.81913431E-02   1.36419278E-01   9.71261900E-02   1.35008303E-01   2.02403226E-01   3.70122092E-01   1.90054559E-01   1.32764655E-02   9.63766259E-02   3.88775849E-02  -6.09526927E-03  -8.01389753E-03  -1.20565125E-02  -1.55432430E-02  -1.27897690E-02  -1.67902669E-02  -2.17536894E-02  -2.45085699E-02  -1.47273392E-02   1.94361511E-02  -3.89421369E-03   1.48416309E-02  -6.15275758E-02  -7.75706965E-02  -1.06537833E-01  -1.20051592E-01  -1.19971661E-01  -1.35702246E-01  -1.25691035E-01  -4.91257904E-02  -1.31255222E-01  -1.40070501E-02  -3.62626277E-02  -1.40827885E-02   2.77718668E-02   3.28782484E-02   3.94650345E-02   3.65185178E-02   4.36321562E-02   3.68870038E-02   1.84973417E-02   1.10194115E-03   2.70518113E-02   7.91475268E-03   3.96016281E-03   2.91066967E-03\nCm   1.91579070E-02   2.42541336E-02   4.33088690E-02   7.63853890E-02   3.61266938E-02   8.44362986E-02   1.63374270E-01   2.39799291E-01   5.23558447E-02   8.66854716E-03   6.51027856E-02   1.37369601E-02   5.53285756E-02   7.38398688E-02   1.14793957E-01   1.55398143E-01   1.16761226E-01   1.59519668E-01   2.28233436E-01   3.56213481E-01   1.60121968E-01   3.59329509E-02   1.22133886E-01   8.22298059E-02  -4.05811366E-02  -5.37100096E-02  -8.19869335E-02  -1.08005397E-01  -8.55048727E-02  -1.14373853E-01  -1.55098619E-01  -2.02708605E-01  -8.17885555E-02  -3.64533334E-03  -1.07444595E-01  -4.80227401E-02   4.85301448E-02   6.24910192E-02   8.98428254E-02   1.08296086E-01   9.90907403E-02   1.21522854E-01   1.34519098E-01   9.17637196E-02   7.98435480E-02   4.89995882E-02   8.56339872E-02   7.13158670E-02  -3.35864067E-02  -4.08891939E-02  -5.20967269E-02  -5.25877627E-02  -5.88032067E-02  -5.70287185E-02  -3.80651472E-02  -5.42533594E-03  -5.51795066E-02  -1.46460254E-02  -2.06197486E-02  -1.12706391E-02\nCm   5.18172513E-02   6.23144306E-02   7.33120318E-02   7.07144088E-02   6.16159887E-02   5.38472513E-02   8.93156447E-02   1.33500663E-01   4.45541617E-02   8.42419665E-02   7.79854703E-02   1.24312453E-01   3.68470861E-02   4.79311279E-02   7.04485077E-02   8.77365712E-02   7.64352463E-02   9.70585252E-02   1.16295657E-01   1.01957581E-01   1.03937422E-01   2.14454540E-02   1.03182644E-01   5.48622175E-02   4.08967375E-02   5.27554246E-02   7.61395776E-02   9.23034892E-02   8.37631847E-02   1.03375049E-01   1.16067268E-01   8.28035976E-02   5.99994113E-02   4.42984174E-02   7.30266357E-02   5.91289042E-02  -1.52847715E-02  -1.93483813E-02  -2.68067714E-02  -3.05977145E-02  -3.01053062E-02  -3.46116915E-02  -3.32139951E-02  -1.44915308E-02  -4.86868273E-02   3.78620198E-03   3.72072739E-03   9.48152515E-03  -5.93689069E-02  -7.44117334E-02  -1.00916319E-01  -1.11625466E-01  -1.13976576E-01  -1.25839830E-01  -1.10619035E-01  -3.67690560E-02  -9.98714977E-02  -1.89657808E-02  -6.59665666E-02  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-4.76998037E-02  -1.12679179E-01  -3.57011250E-02  -7.81662248E-02  -6.04038044E-02\nCm   5.06257140E-02   4.71215280E-02   3.96301877E-02   3.46076384E-02   1.69553205E-02   3.26714674E-03   4.34597765E-02   2.51642506E-01   1.29069716E-02   4.11000888E-02   4.61828990E-02   6.18183657E-02   4.29054440E-02   5.76519179E-02   9.09859989E-02   1.25966994E-01   9.03603166E-02   1.25333002E-01   1.86767757E-01   3.34528311E-01   1.74305255E-01   2.05978284E-02   1.17186089E-01   6.42145395E-02  -5.79400364E-03  -7.62020899E-03  -1.14721578E-02  -1.48050884E-02  -1.21606778E-02  -1.59792315E-02  -2.07490473E-02  -2.35457671E-02  -2.42369169E-02   2.70555091E-02   2.55530330E-03   2.93457477E-02   1.07259116E-03   1.39648466E-03   2.05652848E-03   2.56858552E-03   2.22757757E-03   2.83687395E-03   3.42214155E-03   3.06539966E-03  -4.61779632E-04  -1.47786694E-02   2.20257758E-03  -1.59017126E-02  -5.59484473E-02  -7.10995208E-02  -9.93400789E-02  -1.14803208E-01  -1.11212545E-01  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6.04548147E-02   4.81156696E-02   5.92527395E-02   7.73692022E-02   8.09529576E-02   8.75970181E-02   8.95632625E-02   6.68254162E-02   1.34017588E-02   3.08920516E-02   4.39502181E-02   7.39985309E-02   7.18113913E-02\nCm  -1.99393405E-02  -2.54506936E-02  -2.11242005E-02   1.16503932E-02  -3.03558704E-02   2.41006736E-02   1.16302056E-01   1.54793373E-01   4.75383938E-02  -1.03652049E-02  -6.11655740E-02  -4.92032183E-02   3.18548910E-02   4.13972805E-02   6.07174517E-02   7.53826766E-02   6.59932361E-02   8.35330162E-02   9.93584853E-02   8.50995117E-02   8.73981470E-02  -3.22601132E-04   3.11731119E-02   3.87071851E-03   2.14937053E-02   2.77911979E-02   4.03145667E-02   4.92422857E-02   4.41933151E-02   5.49881240E-02   6.28925377E-02   4.75700801E-02   3.27281967E-02  -3.88935654E-03   1.97894982E-02  -6.23329842E-03   1.99980196E-02   2.57049879E-02   3.68128791E-02   4.41207830E-02   4.07007985E-02   4.95955253E-02   5.41149982E-02   3.52796231E-02   3.61258956E-02   1.08436896E-02   1.80105982E-02   9.12497196E-03  -5.68989757E-02  -6.96154526E-02  -8.96440919E-02  -9.19056155E-02  -1.01361154E-01  -1.00605446E-01  -7.05031275E-02  -1.16653011E-02  -8.44953352E-02  -4.33965080E-02  -7.51494475E-02  -6.57838906E-02\nCm  -1.79660343E-02  -2.45475491E-02  -2.09851356E-02   3.54877762E-03  -1.78401265E-02   2.25547303E-02   5.89185270E-02   4.81929386E-02   1.99278899E-02  -3.51793547E-02  -4.36046209E-02  -9.37831914E-02   7.10247310E-03   9.43585471E-03   1.45235996E-02   1.93704386E-02   1.49835026E-02   2.02427536E-02   2.81419527E-02   3.99187530E-02   3.28751618E-02  -1.14965775E-02  -2.12903588E-02  -5.61224399E-02  -2.40782046E-03  -3.19401576E-03  -4.89984692E-03  -6.50267567E-03  -5.07757515E-03  -6.83292898E-03  -9.40583714E-03  -1.29136546E-02   9.60274924E-03  -2.32694012E-03  -1.65485194E-02  -7.58411869E-03   3.99463081E-02   4.99977038E-02   6.76018959E-02   7.44449571E-02   7.63919152E-02   8.38478002E-02   7.27776747E-02   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6.27192539E-02   8.81094355E-02   1.02644101E-01   9.84102277E-02   1.16012215E-01   1.17613283E-01   6.08982468E-02   7.68729277E-02   7.46928740E-02   8.45293516E-02   1.19801346E-01  -3.13512302E-02  -3.78511131E-02  -4.73742761E-02  -4.65923861E-02  -5.32428401E-02  -4.96234432E-02  -3.04761630E-02  -3.36749106E-03  -2.79800818E-02  -1.00660639E-02  -4.37513025E-02  -2.90038509E-02  -3.64025452E-02  -4.35572513E-02  -5.34827866E-02  -5.11521246E-02  -5.97213147E-02  -5.32695071E-02  -2.98537641E-02  -2.49495056E-03  -4.41768313E-02  -1.36302015E-02  -3.23888168E-02  -2.26212884E-02\nCm   3.51763816E-02   4.66550851E-02   7.87581545E-02   1.20627770E-01   7.87693459E-02   1.31046678E-01   2.07861498E-01   3.10746890E-01   1.12135959E-01   4.33377700E-02   1.06208180E-01   3.28790780E-02   5.02317140E-02   6.64955234E-02   1.01546470E-01   1.33856027E-01   1.05847531E-01   1.41658275E-01   1.92344985E-01   2.52448879E-01   1.33680129E-01   8.16707080E-02   1.20784273E-01   1.20801633E-01   5.40153705E-02   7.06613227E-02   1.05142919E-01   1.33354471E-01   1.12809099E-01   1.45854174E-01   1.82258711E-01   1.82752281E-01   9.26015056E-02   7.77473794E-02   1.31944110E-01   1.31375350E-01  -6.27711349E-02  -8.09988519E-02  -1.16984219E-01  -1.41966458E-01  -1.28635985E-01  -1.58934715E-01  -1.78907230E-01  -1.28673056E-01  -9.93724695E-02  -4.34671411E-02  -1.82219693E-01  -1.34625107E-01   2.62762410E-02   3.22261984E-02   4.17121270E-02   4.30879248E-02   4.71933366E-02   4.73631404E-02   3.39758330E-02   6.03889812E-03   2.51499688E-02   3.86258831E-02   6.04914589E-02   4.95031598E-02\nCm   1.22615488E-02   2.00481405E-02   2.01716919E-02  -1.03834782E-02   3.37149997E-02  -2.44438202E-02  -1.14843153E-01  -1.62235755E-01  -2.67721139E-02  -5.78679468E-04   5.53240898E-02   8.20655957E-02  -5.40153705E-02  -7.06613227E-02  -1.05142919E-01  -1.33354471E-01  -1.12809099E-01  -1.45854174E-01  -1.82258711E-01  -1.82752281E-01  -1.36869361E-01  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1.03853330E-01   9.51853511E-02   1.16581013E-01   1.28670501E-01   8.69660344E-02   9.03200805E-02   3.26834070E-02   6.52810472E-02   4.30415202E-02  -1.23151458E-02  -1.55489196E-02  -2.14225686E-02  -2.42517560E-02  -2.41018911E-02  -2.74234893E-02  -2.57279676E-02  -1.04638004E-02  -1.62829318E-02  -1.92531816E-03  -3.46535133E-02  -1.84135130E-02\nCm  -5.40376890E-02  -5.59270657E-02  -4.23813575E-02   3.44698565E-03  -3.80710505E-02   3.84503170E-02   1.11831132E-01   8.65445332E-02   3.49497825E-02  -3.23635283E-02  -5.89266114E-02  -6.18525888E-02  -4.40604347E-03  -5.73048647E-03  -8.41955664E-03  -1.04801255E-02  -9.13783677E-03  -1.15970494E-02  -1.38781971E-02  -1.21186830E-02  -1.50158655E-02  -2.30044790E-02  -1.69334222E-02  -2.43689502E-02   5.11508165E-02   6.55824313E-02   9.34101246E-02   1.11053052E-01   1.03606769E-01   1.25092977E-01   1.33715948E-01   8.17227389E-02   1.35982979E-01   1.39836176E-02   6.63989422E-02   2.84951386E-02   2.82537927E-02   3.59211017E-02   5.02374379E-02   5.81400762E-02   5.62191659E-02   6.57478594E-02   6.54954493E-02   3.21043081E-02   7.06963617E-02   9.28685877E-03   3.29643035E-02   1.48877664E-02  -3.21891437E-02  -4.00836903E-02  -5.36057119E-02  -5.80889422E-02  -6.06634301E-02  -6.51514872E-02  -5.39726035E-02  -1.49362409E-02  -6.42658544E-02  -1.90938257E-02  -3.39137159E-02  -2.15200676E-02\nCm   2.21802812E-03  -2.70430276E-03  -2.42689197E-02  -4.99882422E-02  -4.65996158E-02  -7.24111932E-02  -6.48671035E-02  -2.24217777E-02  -7.34356768E-02   1.09211706E-02  -4.73553476E-02  -8.54433866E-03   2.06855439E-02   2.73536316E-02   4.16738953E-02   5.47412736E-02   4.35668424E-02   5.81365680E-02   7.83713674E-02   1.00460732E-01   5.66340618E-02  -8.56324882E-04   7.69897953E-02   1.97564456E-02  -1.49786471E-02  -1.97837879E-02  -3.00633546E-02  -3.93387925E-02  -3.15278845E-02  -4.19350352E-02  -5.60816780E-02  -7.00393061E-02  -4.21053520E-02  -2.46697440E-02  -1.65812477E-02  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1.36910679E-02   1.03915673E-03   9.19999992E-03  -6.98770962E-03  -8.65817456E-03  -1.14555036E-02  -1.22199685E-02  -1.29722051E-02  -1.36321207E-02  -1.07809155E-02  -2.58589359E-03  -5.86723398E-03   5.39573140E-03  -1.20463226E-02   8.52513157E-03  -2.78914746E-02  -3.39047270E-02  -4.30584907E-02  -4.32595824E-02  -4.85696186E-02  -4.67694776E-02  -3.07539902E-02  -4.18722016E-03  -5.39613505E-02   4.50711955E-03  -4.50279631E-02  -1.72900415E-02\nCm  -1.49146362E-03  -7.37505153E-04   8.55657405E-03   2.31414085E-02   1.45775353E-02   2.78090943E-02   3.92741628E-02   7.39378708E-02  -7.46583779E-03   5.28764459E-03   1.08961463E-01   9.93928572E-02   2.71792107E-02   3.62402401E-02   5.62297655E-02   7.58963776E-02   5.73590531E-02   7.81972934E-02   1.11262094E-01   1.70460541E-01   5.89819124E-02   4.64835444E-02   7.58539268E-02   8.56370754E-02   5.62987023E-02   7.46141488E-02   1.14237771E-01   1.51162374E-01   1.18686402E-01   1.59339267E-01   2.18043085E-01   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1.57319296E-02   1.64598523E-02   9.40594683E-03   8.84940783E-05   3.01596342E-02   1.14272619E-02   2.29367287E-02  -2.76257450E-02  -3.47270184E-02  -4.73942833E-02  -5.29116164E-02  -5.34567576E-02  -5.97433737E-02  -5.39141016E-02  -1.94380870E-02  -6.47383966E-02  -7.53620330E-03  -4.00028950E-02  -1.58428473E-02   1.42369649E-02   1.77374471E-02   2.37463929E-02   2.57726773E-02   2.68700050E-02   2.89196727E-02   2.40673435E-02   6.75494995E-03   1.71366276E-02   1.64489682E-02   2.79487434E-02   2.19960011E-02\nCm   4.12212508E-02   5.24758506E-02   7.86499059E-02   1.06227271E-01   7.41189558E-02   8.28837555E-02   1.24314685E-01   4.35747157E-01   7.78194627E-02   7.68196151E-02   8.43367319E-02   9.58678317E-02   5.24048470E-02   7.11058314E-02   1.14669834E-01   1.63977617E-01   1.09398417E-01   1.54444651E-01   2.42523212E-01   5.21835857E-01   2.34136857E-01   3.06202927E-02   1.80659963E-01   8.05584396E-02  -4.22391007E-02  -5.41393680E-02  -7.70590886E-02  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2.92640636E-02   4.51291715E-02   6.03612932E-02   4.64365959E-02   6.28746889E-02   8.79009547E-02   1.27019234E-01   3.99256094E-02   3.74044376E-02   6.84111183E-02   6.02885722E-02  -2.66126689E-02  -3.52331468E-02  -5.38183657E-02  -7.09679537E-02  -5.60804854E-02  -7.50764971E-02  -1.02015813E-01  -1.34222223E-01  -6.74360560E-02  -3.98362293E-03  -7.80972906E-02  -4.37995851E-02   4.63357016E-02   6.00602819E-02   8.75955025E-02   1.07849528E-01   9.56369746E-02   1.20010444E-01   1.39936871E-01   1.12518669E-01   1.15460041E-01   4.28467115E-02   1.53334738E-01   9.73242331E-02   4.05771788E-02   4.39625883E-02   4.37482152E-02   3.08531799E-02   4.12221678E-02   2.12182167E-02   3.86402064E-03   1.07495333E-05   1.02621436E-02   7.32451231E-02   7.05759664E-02   1.04580572E-01\nCm   3.52533896E-02   4.70772156E-02   7.30528281E-02   9.91237599E-02   7.20014896E-02   9.51487944E-02   1.41807314E-01   2.81964971E-01   8.21448692E-02   4.45424742E-02   2.57211184E-01   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6.74585825E-02   6.63742443E-02   6.98318815E-02   2.17649009E-02   1.04225646E-02   6.21544829E-02   3.73221586E-02   3.12232402E-02   4.04868982E-02   5.90973280E-02   7.28509550E-02   6.44811709E-02   8.10184285E-02   9.47483740E-02   7.68969801E-02   7.52415745E-02   3.98550546E-02   5.70444663E-02   5.32038131E-02  -1.45257839E-02  -1.79028051E-02  -2.34181126E-02  -2.45666319E-02  -2.65161454E-02  -2.72127214E-02  -2.04652526E-02  -4.20517871E-03  -2.26317211E-02   1.34552642E-02  -8.42950270E-03   1.33838946E-02  -2.37530767E-02  -2.87840175E-02  -3.63118945E-02  -3.61272190E-02  -4.08967342E-02  -3.88004516E-02  -2.47320352E-02  -3.06161660E-03  -2.19512765E-02  -1.36092427E-02  -4.64041733E-02  -3.05569913E-02   3.98170220E-02   4.52148989E-02   4.96838518E-02   4.04386239E-02   5.17448720E-02   3.49985390E-02   1.10998180E-02   1.64819596E-04   2.68867191E-02   4.88756217E-02   4.81949590E-02   6.33549314E-02\nCm   6.42238119E-02   8.67704427E-02   1.36057035E-01   1.80302364E-01   1.43690254E-01   1.84626321E-01   2.49933864E-01   3.78816944E-01   1.06557706E-01   6.99010728E-02   1.66629868E-01   1.52830862E-01   6.95769680E-02   9.24299632E-02   1.42249987E-01   1.89687028E-01   1.46779018E-01   1.98270373E-01   2.75540008E-01   3.90378350E-01   1.62261947E-01   6.95428292E-02   1.97373483E-01   1.39385206E-01  -3.05540113E-02  -3.80537085E-02  -5.09086853E-02  -5.51945972E-02  -5.76093731E-02  -6.19147942E-02  -5.13680996E-02  -1.42812638E-02  -7.20963025E-02   9.49367097E-03  -5.09093195E-02  -1.12055320E-02  -2.58300447E-02  -3.16749259E-02  -4.09873848E-02  -4.23223559E-02  -4.63720165E-02  -4.65116554E-02  -3.33238650E-02  -5.90063431E-03  -3.70626028E-02   1.06510390E-02  -3.73033210E-02  -6.21517292E-03   3.92444373E-02   4.80506065E-02   6.19725207E-02   6.36825465E-02   7.00871110E-02   6.98013615E-02   4.92675477E-02   8.33263850E-03   6.44245410E-02   6.85268004E-02   3.43694064E-02   6.30846121E-02\nCm   4.14171816E-02   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1.18777962E-02   4.26590762E-02   3.09772604E-02   8.23873918E-03   9.90693839E-03   1.22935721E-02   1.19402740E-02   1.37796684E-02   1.25944556E-02   7.42587141E-03   7.24512178E-04   1.32134150E-02  -1.17790701E-02   6.04812213E-03   1.04400081E-04\nCm  -2.52612388E-02  -2.64225455E-02  -3.82543529E-02  -5.98406268E-02  -3.66480691E-02  -6.59998947E-02  -9.79801699E-02  -1.68172852E-01  -3.96117795E-02   5.28231291E-03  -9.83401311E-02  -2.10236627E-02  -3.60979769E-02  -4.86940610E-02  -7.75141924E-02  -1.08708980E-01  -7.58230685E-02  -1.05978065E-01  -1.61406673E-01  -3.11713641E-01  -9.67234785E-02  -3.03223669E-02  -7.13761106E-02  -7.56283932E-02  -7.07222797E-03  -9.50120570E-03  -1.49887396E-02  -2.07389404E-02  -1.48957815E-02  -2.06532276E-02  -3.07447692E-02  -5.48719370E-02  -4.67387742E-03  -2.86740054E-02  -2.63866036E-02  -4.40349911E-02   6.68712148E-02   8.83007457E-02   1.34105770E-01   1.75334321E-01   1.40733868E-01   1.87055085E-01   2.49719312E-01   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1.02402939E-01   1.29767944E-01   1.36114493E-01   1.01869058E-01   9.14969558E-02   1.42047311E-01   1.96457112E-01   3.29847928E-02   4.03961534E-02   5.21274157E-02   5.36065548E-02   5.89567129E-02   5.87821262E-02   4.15879534E-02   7.08487717E-03   3.32838057E-02   8.15590139E-02   6.94266481E-02   1.40436424E-01  -6.02984910E-02  -7.07187976E-02  -8.32098448E-02  -7.47945791E-02  -9.10179016E-02  -7.33069266E-02  -3.32594571E-02  -1.46169792E-03  -4.95310187E-02  -3.45642573E-02  -5.66530619E-02  -4.71981360E-02\nCm  -1.03010069E-02  -2.66313447E-03  -2.94405026E-04  -1.89316693E-02   1.39501036E-02  -1.17353522E-02  -7.43515931E-02  -2.32771121E-01  -3.65610286E-02  -6.39503905E-03   1.31060583E-02   3.35873589E-02  -7.89421839E-02  -1.05630960E-01  -1.65171125E-01  -2.25534850E-01  -1.66525225E-01  -2.28894982E-01  -3.32790396E-01  -5.48179987E-01  -2.68467951E-01  -5.12586631E-02  -1.45308387E-01  -9.01215641E-02   2.76553127E-02   3.68729468E-02   5.72042239E-02   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6.00626946E-02   4.94119339E-02   6.48747743E-02   8.40753894E-02   9.48057779E-02   6.91117484E-02   2.19609075E-02   2.97974853E-02   1.44546689E-02   6.41382160E-02   8.31813636E-02   1.21461164E-01   1.49809276E-01   1.32488678E-01   1.66561526E-01   1.95039763E-01   1.58942404E-01   1.96274122E-01   4.06381152E-02   1.44922226E-01   6.90050649E-02  -3.64147810E-02  -4.68750141E-02  -6.73438976E-02  -8.10907441E-02  -7.43097052E-02  -9.10252904E-02  -1.00495221E-01  -6.79880264E-02  -7.14012598E-02   2.02618634E-03  -2.89756470E-02  -6.24084454E-03  -2.10374879E-02  -2.67569375E-02  -3.74525198E-02  -4.33979721E-02  -4.18971843E-02  -4.90726665E-02  -4.90471104E-02  -2.42924535E-02  -3.94098105E-02  -2.64415128E-03  -4.40744578E-02  -2.34197971E-02\nCm   1.38978859E-02   1.44578409E-02   6.15511384E-03  -1.25490962E-02  -8.58676201E-04  -2.48348768E-02  -4.24604392E-02  -4.54936442E-02   8.98149191E-03   2.65239359E-02  -1.39176794E-02   2.27929099E-02  -2.85782439E-02  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1.70909230E-02   3.53572917E-02   9.81556473E-02   1.06509165E-02   1.52196422E-02   5.88568187E-02   1.08716987E-01  -5.14252470E-02  -6.82159999E-02  -1.04646551E-01  -1.38875102E-01  -1.08444542E-01  -1.45931871E-01  -2.00872466E-01  -2.75743507E-01  -9.14633711E-02  -4.63581937E-02  -7.70676760E-02  -7.72047159E-02   7.36063246E-02   9.75628885E-02   1.49408657E-01   1.97770918E-01   1.55179493E-01   2.08391528E-01   2.85370100E-01   3.85136951E-01   1.96964011E-01   5.23023657E-02   2.17235466E-01   1.61551265E-01  -1.99823165E-02  -2.47603992E-02  -3.27634125E-02  -3.49549741E-02  -3.71011660E-02  -3.89965968E-02  -3.08538600E-02  -7.41056277E-03  -4.12965723E-02  -1.81876812E-02  -1.93157512E-02  -2.74748015E-02  -4.58978145E-02  -5.53751077E-02  -6.92045753E-02  -6.79152986E-02  -7.77436676E-02  -7.22158264E-02  -4.40412809E-02  -4.76326411E-03  -6.05804205E-02  -4.37268437E-02  -4.31991021E-02  -4.90254535E-02\nCm  -8.43597465E-03  -1.88386395E-02  -3.22429148E-02  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4.08725036E-02   4.21484717E-02   4.59877948E-02   3.94092479E-02   1.21078648E-02   4.45756401E-02   2.23529956E-02   4.53761423E-02   3.85471701E-02\nCm   3.63491611E-02   3.65080297E-02   3.11017100E-02   1.94216976E-02   2.65289229E-02   1.98264998E-02   3.61155750E-03  -4.31537017E-02  -5.10967815E-03   1.40819060E-02   5.70180299E-02   3.74053501E-02  -6.50677999E-02  -8.48244732E-02  -1.25263810E-01  -1.57098178E-01  -1.35351163E-01  -1.73085251E-01  -2.10799664E-01  -1.94675449E-01  -2.13128926E-01  -1.21265849E-02  -6.71927179E-02  -2.03462399E-02   6.90997387E-02   8.92509501E-02   1.29172076E-01   1.57241847E-01   1.41832320E-01   1.75829774E-01   1.99437101E-01   1.46927852E-01   1.18143566E-01   3.12008645E-02   7.78774078E-02   6.39447801E-02   8.58231173E-03   1.07214092E-02   1.44372126E-02   1.58033983E-02   1.63247528E-02   1.77743859E-02   1.51632063E-02   4.59417965E-03   1.88791754E-02   3.10723376E-02   2.72055602E-02   5.07992340E-02  -4.10815182E-03  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1.31718430E-01   1.05617942E-01   1.40448546E-01   1.87719801E-01   2.33997596E-01   1.15736450E-01   5.76666157E-02   1.57031612E-01   1.15042719E-01   3.98160379E-02   4.98718295E-02   6.75400439E-02   7.45523905E-02   7.63007190E-02   8.40108752E-02   7.34130378E-02   2.39587036E-02   6.20358680E-02   6.28255012E-02   7.46036375E-02   9.76593738E-02   2.16788128E-02   2.71369869E-02   3.67015100E-02   4.04321640E-02   4.14718340E-02   4.55427929E-02   3.95734454E-02   1.26913204E-02   2.78238692E-02   3.27092496E-02   2.31990053E-02   3.61949619E-02\nCm  -3.03294883E-02  -4.34494362E-02  -5.83343317E-02  -4.87784419E-02  -6.82083947E-02  -4.19791668E-02  -4.18052090E-03   2.73621188E-02  -2.23023833E-02  -2.14820273E-02  -7.94755122E-02  -7.88565730E-02   5.41685135E-02   7.00875239E-02   1.01822335E-01   1.24645557E-01   1.11497417E-01   1.39060487E-01   1.59906705E-01   1.23022507E-01   1.55771256E-01   1.42991170E-02   7.06622595E-02   2.54701809E-02  -1.69829556E-02  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1.17301558E-02   3.45763154E-02   2.10996976E-02   1.29950443E-02   1.64627212E-02   2.28471406E-02   2.61427445E-02   2.56434060E-02   2.95731874E-02   2.85710840E-02   1.27302581E-02   3.42159690E-02   2.62795489E-02   1.05101989E-02   2.01938136E-02\nCm   2.96296198E-02   3.89521516E-02   4.95633399E-02   3.90250778E-02   6.59365484E-02   5.77290320E-02   2.48158244E-03  -2.18075690E-01   2.74807915E-02   6.10414387E-02   1.30374316E-01   2.04707750E-01  -5.99584803E-02  -7.98159580E-02  -1.23393052E-01  -1.65652738E-01  -1.26528218E-01  -1.71802328E-01  -2.41923263E-01  -3.58049238E-01  -9.27199517E-02  -4.63081854E-02  -4.69462535E-02  -5.84929281E-02   2.48175507E-02   3.22557319E-02   4.73219397E-02   5.87745326E-02   5.14226034E-02   6.51157314E-02   7.75231090E-02   6.65918736E-02   4.64428130E-02   2.35342830E-02   5.94837945E-02   4.06801324E-02   5.60296808E-02   7.07934520E-02   9.76883237E-02   1.10843935E-01   1.09853579E-01   1.25357854E-01   1.18355007E-01   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4.64933382E-02   2.10962974E-02   9.27441432E-04   4.05597032E-02   1.62052738E-02   3.40043942E-02   2.16592521E-02  -1.90162402E-02  -2.10886356E-02  -2.20420378E-02  -1.66873099E-02  -2.19102824E-02  -1.29462527E-02  -3.11835756E-03  -2.01645340E-05  -6.08131853E-03   6.24611926E-03  -2.27664150E-02  -8.03810572E-03  -2.40548903E-02  -2.50595401E-02  -2.29648448E-02  -1.43832671E-02  -1.94869309E-02  -7.87421720E-03  -8.79886421E-04  -5.62568197E-07  -2.84624129E-03  -1.50026059E-02  -1.63130886E-02  -1.68611574E-02\nCm   7.62052772E-03   1.41390949E-02   4.47082796E-02   9.98889621E-02   3.66413541E-02   8.46026255E-02   1.87886556E-01   5.82521305E-01   5.24334198E-02   1.48506260E-04   6.83123006E-02   5.40230845E-02   7.90396583E-02   1.06644891E-01   1.69852137E-01   2.38392819E-01   1.65988777E-01   2.32104227E-01   3.53951033E-01   6.86611164E-01   2.54827694E-01   4.34337614E-02   2.21996626E-01   1.28732782E-01  -4.26687913E-02  -5.48987834E-02  -7.87881371E-02  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4.12493961E-03   4.40466914E-03   4.59103424E-03   3.56818784E-03   8.11247385E-04  -6.25660088E-03   9.32501577E-03   1.99017422E-02   1.79848399E-02\nCm  -2.46645292E-02  -2.68155167E-02  -1.20187576E-02   3.06801639E-02  -1.50320049E-02   3.71457938E-02   1.26296695E-01   2.75933256E-01   4.80406324E-03  -2.87123838E-02   2.02810170E-02  -1.51656981E-03   4.16674448E-02   5.55195213E-02   8.60099120E-02   1.15824569E-01   8.79344408E-02   1.19676328E-01   1.69530589E-01   2.55938498E-01   1.54811637E-01   3.05272287E-02   1.14656552E-01   6.18238334E-02   4.44958561E-02   5.73882396E-02   8.27947980E-02   1.00315853E-01   9.11078897E-02   1.12370910E-01   1.25994213E-01   8.94962349E-02   9.31754431E-02   3.64661271E-02   6.95044639E-02   6.33588627E-02  -5.73595103E-02  -7.29064594E-02  -1.01906288E-01  -1.17839640E-01  -1.14066456E-01  -1.33265857E-01  -1.32461823E-01  -6.44845745E-02  -1.19672337E-01  -4.01386766E-02  -6.89587924E-02  -4.62499193E-02  -2.41265231E-02  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2.02805941E-02   4.85575113E-02   5.63259110E-02   7.38785580E-02   9.38325854E-02  -3.41719719E-02  -3.82028890E-02  -4.06153270E-02  -3.15145712E-02  -4.10564707E-02  -2.54166325E-02  -6.73040724E-03  -5.79339351E-05  -2.39230854E-02  -2.14769855E-02  -4.12199179E-02  -4.43300564E-02\nCm  -5.65406584E-02  -5.82457490E-02  -6.26827346E-02  -6.69659193E-02  -5.38802941E-02  -6.59145152E-02  -9.67497559E-02  -1.07259891E-01  -7.74170760E-02  -6.34689781E-02  -6.20691461E-02  -8.24218852E-02   7.07222797E-03   9.50120570E-03   1.49887396E-02   2.07389404E-02   1.48957815E-02   2.06532276E-02   3.07447692E-02   5.48719370E-02   3.55928364E-02  -6.22616311E-03   9.41414481E-03   4.01139889E-03  -7.27627491E-02  -9.48867723E-02  -1.40222847E-01  -1.76044155E-01  -1.51418180E-01  -1.93834421E-01  -2.36645270E-01  -2.20250350E-01  -1.90108418E-01  -5.94858931E-02  -1.35681162E-01  -1.09359559E-01   4.37179498E-02   5.57944504E-02   7.86786011E-02   9.21703552E-02   8.77224584E-02   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1.34146745E-01   1.09897128E-01   2.93845851E-02   8.60569835E-02   3.76240633E-02   9.06866597E-02   6.48117303E-02   3.07477406E-03   3.71790822E-03   4.66847482E-03   4.61327454E-03   5.25157705E-03   4.93064407E-03   3.07496517E-03   3.56073708E-04   1.28683544E-03  -5.80033477E-03   1.03841499E-02   1.13155193E-04\nCm   3.14629297E-02   3.79643505E-02   3.22749377E-02  -1.56542677E-03   3.77438524E-02  -5.30323754E-03  -7.27205992E-02  -2.39491507E-01  -3.35051367E-02   6.17926634E-02   9.86136123E-02   1.33278670E-01   1.08735403E-04   1.48664526E-04   2.43843560E-04   3.57690050E-04   2.24200001E-04   3.19698856E-04   5.20104946E-04   1.27548548E-03  -1.67431642E-02   2.26834574E-02   3.24939562E-02   4.54272157E-02  -4.88354556E-02  -6.54114017E-02  -1.02508232E-01  -1.40434976E-01  -1.02987626E-01  -1.41878238E-01  -2.07521465E-01  -3.48856812E-01  -1.39068163E-01  -3.05637377E-02  -1.13721195E-01  -6.50650033E-02   5.56353978E-02   7.18434956E-02   1.03926311E-01   1.26416333E-01   1.14152253E-01   1.41400901E-01   1.60093776E-01   1.17266010E-01   1.22359033E-01   3.82127956E-02   1.49707163E-01   1.02808446E-01  -1.97128039E-02  -2.45516467E-02  -3.28460374E-02  -3.56121847E-02  -3.71692263E-02  -3.99484347E-02  -3.31459780E-02  -9.21727855E-03  -4.51087740E-02   6.74945199E-03  -1.75225431E-02   9.42384490E-03\nCm  -3.46485252E-02  -4.64396500E-02  -5.43810355E-02  -3.89570948E-02  -6.00357315E-02  -3.52230507E-02   7.58657363E-03   5.85279833E-02  -5.75887180E-02  -6.65954349E-02  -5.32982925E-02  -8.94123624E-02   4.80839367E-03   6.58649078E-03   1.08489045E-02   1.60152493E-02   9.87580638E-03   1.41090983E-02   2.31360952E-02   5.84980177E-02   2.34957455E-02  -1.17157148E-02   3.11070447E-02   1.15368275E-02   3.24261992E-03   3.84666718E-03   4.63736918E-03   4.31831435E-03   5.13774599E-03   4.38879516E-03   2.24857802E-03   1.42998527E-04   8.89164002E-03  -1.22952789E-02  -6.91472539E-03  -1.29235244E-02   5.10934251E-02   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1.04647246E-01   8.00504388E-02   1.08630931E-01   1.52741490E-01   2.24946409E-01   1.10524607E-01   8.41014024E-03   5.26769905E-02   1.65496837E-02   3.28172204E-02   4.30034906E-02   6.42263259E-02   8.19087329E-02   6.86563048E-02   8.92336540E-02   1.12890618E-01   1.17776478E-01   6.27000792E-02   1.22747940E-02   5.03044468E-02   2.78779541E-02  -7.33513148E-02  -9.49483424E-02  -1.38068170E-01  -1.69248381E-01  -1.51083123E-01  -1.88708771E-01  -2.17723297E-01  -1.69283433E-01  -1.36059158E-01  -4.28858658E-02  -1.20677381E-01  -6.78811848E-02  -6.75753079E-03  -8.69777456E-03  -1.24931037E-02  -1.50384686E-02  -1.37872542E-02  -1.68825618E-02  -1.86239272E-02  -1.25676615E-02  -1.63070924E-03  -1.31851672E-02  -2.14882691E-02  -1.59313789E-02\nCm   5.67625913E-02   7.51489706E-02   1.12804858E-01   1.37375077E-01   1.29106532E-01   1.46412768E-01   1.48233047E-01   1.83369909E-01   7.95252796E-02   1.05684226E-01   2.70925612E-01   2.90610469E-01   6.26431725E-02   8.23991403E-02   1.24089209E-01   1.60212937E-01   1.31492333E-01   1.72852934E-01   2.24670908E-01   2.55768309E-01   2.52976747E-01   8.62518212E-02   2.56221691E-01   2.07339818E-01   1.95543293E-02   2.53666625E-02   3.70609788E-02   4.57484555E-02   4.04080211E-02   5.08438198E-02   5.96546376E-02   4.89196598E-02   4.12507449E-02   4.38115131E-02   6.83666501E-02   6.11096849E-02  -7.16393683E-02  -9.21764654E-02  -1.32297830E-01  -1.59074048E-01  -1.46072405E-01  -1.78642469E-01  -1.96515113E-01  -1.31441256E-01  -1.11338233E-01  -2.98306832E-02  -1.08379572E-01  -5.74590768E-02   1.97128039E-02   2.45516467E-02   3.28460374E-02   3.56121847E-02   3.71692263E-02   3.99484347E-02   3.31459780E-02   9.21727855E-03   3.86066856E-02   7.12990445E-02   7.48591187E-02   1.14870088E-01\nCm   4.46098059E-02   5.24158164E-02   5.50748366E-02   3.53704204E-02   5.52381363E-02   2.33256352E-02  -1.13090684E-02  -4.35010539E-02   2.15497924E-02   6.50872262E-02   9.46238918E-02   1.25170332E-01  -6.37985378E-02  -8.32871550E-02  -1.23372407E-01  -1.55432763E-01  -1.32935008E-01  -1.70763386E-01  -2.10165682E-01  -2.00712557E-01  -1.67967623E-01  -4.43659151E-02  -9.29191968E-02  -6.84685712E-02   4.86476817E-02   6.30058865E-02   9.17293413E-02   1.12644431E-01   1.00285770E-01   1.25497192E-01   1.45415844E-01   1.14612075E-01   1.34401772E-01   5.81144571E-02   1.24898767E-01   1.08941045E-01   3.35549975E-02   4.30567900E-02   6.14335887E-02   7.32252264E-02   6.80719896E-02   8.24319076E-02   8.86962165E-02   5.53406339E-02   4.86181299E-02   3.36245092E-02   9.45388580E-02   5.51039846E-02  -6.27039707E-03  -7.91230925E-03  -1.08875427E-02  -1.23026993E-02  -1.22538030E-02  -1.39098429E-02  -1.29833995E-02  -5.19743518E-03  -1.92882535E-02   6.77351818E-03   2.64569976E-03   1.19112167E-02\nCm  -3.18652711E-02  -2.44062488E-02  -3.60490509E-03   2.47798980E-02  -2.75887269E-03   2.04740983E-02   8.91028714E-02   1.87154322E-01   2.75063491E-02  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1.37405776E-01   7.16790223E-02  -1.19067127E-02   6.85318337E-02   2.61789678E-02   4.93401145E-02   6.50653097E-02   9.85304793E-02   1.28266772E-01   1.03755305E-01   1.37391565E-01   1.81757722E-01   2.19110563E-01   1.09151985E-01   4.07949763E-02   6.01430479E-02   5.46324614E-02  -3.26333959E-02  -4.26164532E-02  -6.31741894E-02  -7.96786544E-02  -6.80238953E-02  -8.74752455E-02  -1.07930860E-01  -1.03910331E-01  -7.05517049E-02  -5.83375531E-03  -6.55202331E-02  -3.28373272E-02   4.37750022E-02   5.69363491E-02   8.36628215E-02   1.04154163E-01   9.07921999E-02   1.15244656E-01   1.37963288E-01   1.20610908E-01   1.10785212E-01   3.87699444E-02   7.25968958E-02   6.04814975E-02  -4.08312310E-02  -5.29149126E-02  -7.71410155E-02  -9.49171964E-02  -8.42507436E-02  -1.05651428E-01  -1.23004914E-01  -9.84242775E-02  -1.24339231E-01  -4.03511350E-03  -5.85599302E-02  -1.61488435E-02\nCm  -9.53943599E-04  -1.25298326E-04  -3.57318353E-03  -1.74163456E-02  -2.10972420E-03  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2.67262902E-01   8.64734045E-02   4.93882468E-02   2.09446742E-01   1.51671116E-01   4.57449687E-02   5.90578502E-02   8.53874653E-02   1.03787326E-01   9.38225382E-02   1.16123070E-01   1.31230413E-01   9.55619170E-02   2.94657391E-02   5.55687183E-02   8.91038720E-02   9.90259821E-02  -2.68485223E-02  -3.45730964E-02  -4.97084059E-02  -5.99235107E-02  -5.48230180E-02  -6.72403805E-02  -7.44477104E-02  -5.08204361E-02  -8.45649096E-02   6.36478019E-03  -5.41530213E-02  -1.01716166E-02  -4.66963564E-02  -5.77966750E-02  -7.62918457E-02  -8.11054486E-02  -8.63967989E-02  -9.03575744E-02  -7.07336172E-02  -1.64415773E-02  -1.06095509E-01  -2.14423258E-02  -3.75782057E-02  -2.06711329E-02\nCm  -4.75075937E-02  -4.49889863E-02  -2.20169220E-02   2.77966173E-02  -1.98672989E-02   4.18436684E-02   1.37745684E-01   2.43709386E-01   2.32810966E-02  -2.35630514E-02  -2.76077624E-02  -1.68107649E-02   1.78735521E-02   2.37754537E-02   3.66963760E-02   4.91448571E-02   3.77147172E-02   5.11153773E-02   7.16394760E-02   1.04380384E-01   8.90222259E-02  -3.79321049E-04   1.78285723E-02   4.73034242E-03   4.38200267E-02   5.73708015E-02   8.55188977E-02   1.08751657E-01   9.15942056E-02   1.18724041E-01   1.49240809E-01   1.52527127E-01   2.08046344E-01   6.79343559E-03   7.13320998E-02   1.50285925E-02  -3.37729364E-03  -4.15583367E-03  -5.41757365E-03  -5.65490767E-03  -6.13315962E-03  -6.24915287E-03  -4.62860422E-03  -9.07601369E-04  -1.02066417E-02  -9.57409795E-03   3.91961526E-04  -3.11894782E-03  -6.47024207E-02  -7.90365447E-02  -1.01428213E-01  -1.03468258E-01  -1.14628912E-01  -1.12934560E-01  -7.79182544E-02  -1.22904315E-02  -1.23304206E-01  -3.54162254E-02  -7.39206168E-02  -4.55589322E-02\nCm   2.61220987E-02   3.64802907E-02   6.12570404E-02   8.65742214E-02   7.23297110E-02   1.13465153E-01   1.27315546E-01   5.07809910E-02   3.08970494E-02   6.41668559E-03   2.55062057E-02   7.24567915E-03   2.21305680E-02   2.82309257E-02   3.97704698E-02   4.65223344E-02   4.43628506E-02   5.25563043E-02   5.38643179E-02   2.88544265E-02   5.11634340E-02   1.55237127E-02   1.10926133E-02   1.71428270E-02   4.38251305E-02   5.46258199E-02   7.32043403E-02   7.95670046E-02   8.28249657E-02   8.93205516E-02   7.46511415E-02   2.12294969E-02   5.26979382E-02   3.56524861E-02   2.94170564E-02   3.56761422E-02   2.34390989E-02   2.77589004E-02   3.33458443E-02   3.08909316E-02   3.68807926E-02   3.12371845E-02   1.57243722E-02   9.47738569E-04   1.01148116E-02   1.54177838E-02   1.40732469E-02   1.44592481E-02  -4.13974690E-02  -4.73009713E-02  -5.26600592E-02  -4.36808277E-02  -5.54377802E-02  -3.88055798E-02  -1.32011645E-02  -2.42352929E-04  -4.22843152E-02  -2.12966259E-02  -3.32488420E-02  -2.91825072E-02\nCm  -4.59064304E-02  -5.98473794E-02  -9.01217538E-02  -1.30331749E-01  -7.57026226E-02  -1.31477318E-01  -2.48875686E-01  -3.73226193E-01  -7.17931597E-02  -9.11098086E-02  -7.45756378E-02  -1.07618280E-01  -6.95092358E-02  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1.73189306E-01   3.52998393E-02   4.66750907E-02   7.10978010E-02   9.33664401E-02   7.43437360E-02   9.91836580E-02   1.33631231E-01   1.70986268E-01   9.54322214E-02   3.17598623E-02   9.31628796E-02   4.93913746E-02   5.09989554E-02   6.51344994E-02   9.19954705E-02   1.08023411E-01   1.02490903E-01   1.21969199E-01   1.26257495E-01   6.97774780E-02   1.00401290E-01   5.28155422E-02   2.08296492E-01   1.58446985E-01  -1.63206747E-02  -2.00695885E-02  -2.61255640E-02  -2.72131955E-02  -2.95735321E-02  -3.00420745E-02  -2.21099215E-02  -4.25130573E-03  -2.56921790E-02   3.10805726E-02  -1.20024118E-02   3.21158867E-02   1.24723150E-03   1.45348301E-03   1.68724230E-03   1.48709058E-03   1.83045684E-03   1.42568522E-03   6.03709129E-04   2.15181778E-05   3.72979296E-03   2.42405387E-02   5.25809997E-03   3.44806584E-02\nCm   3.02318512E-02   3.03750936E-02   3.10411316E-02   3.85174428E-02   2.16139986E-02   4.53734288E-02   7.80922149E-02   7.04061963E-02   5.47511283E-02   4.84273321E-02  -2.32683775E-02  -1.73280859E-02   2.45881984E-02   3.18140989E-02   4.62189470E-02   5.65784396E-02   5.06108014E-02   6.31217637E-02   7.25830426E-02   5.58381821E-02   5.33986890E-02   1.01283515E-02   4.07215740E-02   1.45570203E-02   4.25243440E-02   5.38489739E-02   7.46638093E-02   8.53187391E-02   8.38288989E-02   9.65130787E-02   9.29011528E-02   4.09234791E-02   8.00315664E-02   3.40132256E-02   5.80379800E-02   4.20283072E-02  -1.28659719E-02  -1.61815883E-02  -2.21087751E-02  -2.47230824E-02  -2.49302383E-02  -2.79216621E-02  -2.53139236E-02  -9.25817936E-03  -2.37297179E-02  -7.13645404E-03  -8.07353063E-03  -8.57320699E-03  -4.42046994E-02  -5.50631316E-02  -7.36873243E-02  -7.99279062E-02  -8.33835793E-02  -8.96719001E-02  -7.44976828E-02  -2.07982983E-02  -6.16896850E-02  -3.10969818E-02  -1.12515749E-01  -8.49620250E-02\nCm  -1.34036605E-02  -7.11114001E-03   1.92119546E-02   4.40401733E-02   5.25535487E-02   7.39827346E-02   3.57893535E-02  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3.04138141E-02   3.70570850E-02   3.42705554E-02   1.70588931E-02   4.35111799E-02   3.77361361E-02   7.25545046E-02  -3.95578760E-02  -5.05473727E-02  -7.14695930E-02  -8.40546636E-02  -7.95807332E-02  -9.48824786E-02  -9.86263665E-02  -5.52185970E-02  -8.36279490E-02  -4.45168865E-02  -1.41626174E-01  -1.30389923E-01   8.96936229E-03   1.06621294E-02   1.29102231E-02   1.20989414E-02   1.43321951E-02   1.23712114E-02   6.47669005E-03   4.39864201E-04   7.23021743E-03   3.24874081E-02   8.88202162E-03   3.07607052E-02\nCm   3.72275036E-02   3.47358126E-02   1.48593586E-02  -2.68243748E-02   5.84212378E-03  -5.84597695E-02  -1.14959232E-01  -7.62913301E-02  -1.72629601E-02   6.50216739E-02   4.59184489E-03   7.38241074E-02  -3.63082840E-02  -4.66002385E-02  -6.65219320E-02  -7.93475063E-02  -7.36892906E-02  -8.93078086E-02  -9.62717296E-02  -6.04156999E-02  -8.77609069E-02  -3.11982556E-02  -8.39567186E-02  -6.05283987E-02  -2.75555346E-02  -3.45738785E-02  -4.69950531E-02  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5.06253369E-03   5.31945262E-02   3.80264070E-02   4.55075749E-02   5.75026730E-02   7.93598892E-02   9.00665797E-02   8.92386000E-02   1.01861070E-01   9.62277593E-02   3.99883317E-02   6.24196887E-02   2.05103389E-02   5.16452495E-02   2.66728993E-02  -3.21764257E-02  -4.00689338E-02  -5.35890845E-02  -5.80758640E-02  -6.06442775E-02  -6.51384950E-02  -5.39752683E-02  -1.49484467E-02  -4.58666954E-02  -2.57622361E-02  -5.05941320E-02  -3.35790217E-02  -5.80392419E-02  -7.00276918E-02  -8.75274913E-02  -8.59125785E-02  -9.83310835E-02  -9.13653791E-02  -5.57528484E-02  -6.04086497E-03  -5.11560763E-02  -3.24963878E-02  -3.96297341E-02  -2.97072779E-02\nCm   1.03766346E-02   2.04682705E-02   3.95204456E-02   4.63608652E-02   5.36806974E-02   5.47492241E-02   4.10263240E-02  -3.50558637E-02   5.27425002E-02   1.27215794E-02   6.49253125E-02   8.50465892E-02  -2.71792735E-02  -3.57727605E-02  -5.39442735E-02  -6.97866987E-02  -5.70778282E-02  -7.51655526E-02  -9.81188692E-02  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1.10248643E-02   1.79239582E-02   4.86062947E-02   7.61894193E-02   8.70321687E-02\nCm   1.13767234E-02   2.55451967E-02   4.23348564E-02   2.66571657E-02   7.34343190E-02   5.94637097E-02  -2.19575828E-03  -3.69025274E-01   3.13869981E-02  -9.82159082E-03   1.10542390E-01   1.03298911E-01  -3.55876742E-02  -4.90555929E-02  -8.19504307E-02  -1.23579770E-01  -7.19554462E-02  -1.03254752E-01  -1.73392558E-01  -4.82767394E-01  -1.68082129E-01  -1.37541118E-02  -7.91685288E-02  -4.00136804E-02   5.12954236E-02   6.58564836E-02   9.40748358E-02   1.12326456E-01   1.04169076E-01   1.26393735E-01   1.36601523E-01   8.64227355E-02   1.02875703E-01   6.89807271E-02   1.30293709E-01   1.20596708E-01   5.61805562E-02   7.09009145E-02   9.75894142E-02   1.10320441E-01   1.09826551E-01   1.24735970E-01   1.16563888E-01   4.68312971E-02   4.39303356E-02   7.29188190E-02   8.53286740E-02   1.10649061E-01  -5.82623269E-02  -7.20347811E-02  -9.48677188E-02  -1.00513983E-01  -1.07434377E-01  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8.04388850E-02   7.33764184E-02   9.54479591E-02   1.40285017E-01   1.74705297E-01   1.52209310E-01   1.93271096E-01   2.31560062E-01   2.02961827E-01   1.41777766E-01   5.57056438E-02   1.55699368E-01   1.18275759E-01  -2.93176943E-02  -3.77813986E-02  -5.44110200E-02  -6.57527348E-02  -5.99450505E-02  -7.37217333E-02  -8.21223057E-02  -5.71457761E-02  -4.55239739E-02   6.10604871E-03  -8.62382314E-02  -3.05668536E-02  -2.16667637E-02  -2.75182843E-02  -3.84004105E-02  -4.42960785E-02  -4.30113863E-02  -5.01009578E-02  -4.94732103E-02  -2.35969466E-02  -3.03274136E-02  -2.32604881E-03  -1.57192564E-02  -1.30035305E-03  -1.58666470E-02  -2.00509502E-02  -2.76787259E-02  -3.14233907E-02  -3.11219604E-02  -3.55389867E-02  -3.36042737E-02  -1.40043228E-02  -3.36701668E-02   5.91010226E-03  -7.89451671E-03   2.65272103E-03\nCm   9.58110206E-03   5.91969554E-03  -3.01777586E-04   1.09489870E-02  -2.89748848E-02  -4.59845129E-03   9.52922053E-02   2.29552447E-01   3.02063516E-02   3.73408342E-02  -5.10043326E-02  -1.90666763E-02   5.03758091E-02   6.64251217E-02   1.00569884E-01   1.30883365E-01   1.05927080E-01   1.40231603E-01   1.85399905E-01   2.23051051E-01   1.20349039E-01   2.21300677E-02   1.08625700E-01   5.17096919E-02   6.86616412E-03   8.99553724E-03   1.34289488E-02   1.71147542E-02   1.43616860E-02   1.86544094E-02   2.35649901E-02   2.44679557E-02   1.24339531E-02  -7.08985387E-03   1.31740943E-02  -2.32960647E-03  -3.97045938E-02  -4.90175841E-02  -6.43498880E-02  -6.78631010E-02  -7.28713237E-02  -7.53514080E-02  -5.75806203E-02  -1.24271651E-02  -7.23088005E-02  -4.20122766E-02  -9.08717232E-02  -9.72178198E-02  -6.45137451E-02  -7.75429255E-02  -9.61342300E-02  -9.32452477E-02  -1.07721857E-01  -9.82472909E-02  -5.76717500E-02  -5.55119688E-03  -6.16742882E-02  -6.12064519E-02  -8.45890155E-02  -1.04507965E-01\nCm   3.14411893E-02   4.30941141E-02   6.50224857E-02   6.42640626E-02   9.09184411E-02   7.57137315E-02   2.08945297E-02  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1.06862696E-01   9.90855094E-02   3.98539165E-02   6.05849824E-02   6.60045559E-02   1.73016899E-01   1.77600527E-01  -4.71826011E-02  -6.24456277E-02  -9.53163932E-02  -1.25554688E-01  -9.94131345E-02  -1.32968951E-01  -1.80284618E-01  -2.35496524E-01  -1.18980689E-01  -7.02374358E-03  -2.56254138E-02  -7.28699360E-03   7.29040164E-02   9.55862474E-02   1.42933413E-01   1.82614692E-01   1.52603003E-01   1.98677459E-01   2.52361525E-01   2.66712374E-01   9.17698518E-02   7.41087170E-02   1.40568787E-01   1.27390118E-01   1.67259737E-02   2.09067792E-02   2.81872401E-02   3.09103176E-02   3.18667980E-02   3.47808495E-02   2.98262385E-02   9.18339582E-03   5.96517493E-03   5.00504328E-02   5.29306300E-02   7.97451507E-02  -4.39524912E-03  -5.31327701E-03  -6.66824220E-03  -6.58436009E-03  -7.50004580E-03  -7.03340287E-03  -4.37553244E-03  -5.02872833E-04  -3.40524418E-03   9.32839097E-03  -9.77500726E-03  -7.00631603E-03\nCm   2.42086977E-02   9.48741331E-03  -2.82482180E-02  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5.07269477E-02   1.02862065E-01   7.43294798E-02   1.63511291E-02   2.12535875E-02   3.11865568E-02   3.87446581E-02   3.38838603E-02   4.29185979E-02   5.11291826E-02   4.40092383E-02   4.72019767E-02   2.66109250E-02   9.49314662E-03   2.62388992E-02  -1.75303635E-02  -2.25932767E-02  -3.25443125E-02  -3.93396640E-02  -3.58495924E-02  -4.41030418E-02  -4.91648010E-02  -3.42915319E-02  -2.20033584E-02   6.45508154E-04  -4.07646463E-02  -1.69397493E-02  -4.89816203E-02  -5.96071903E-02  -7.58781321E-02  -7.64944319E-02  -8.56311510E-02  -8.28856594E-02  -5.50984403E-02  -7.75548780E-03  -5.22073662E-02  -3.68745903E-02  -5.41903857E-02  -4.70427967E-02\nCm  -8.71820424E-03   8.18920504E-04   3.05204426E-02   6.75042522E-02   4.16804073E-02   8.14883582E-02   1.34985843E-01   1.51726588E-01   4.28558282E-02   1.18382192E-02   1.24611126E-03   3.39526611E-02   3.49048086E-03   4.65656279E-03   7.23333187E-03   9.77992281E-03   7.36620450E-03   1.00548510E-02   1.43529125E-02   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1.98468323E-01   2.55440905E-01   2.81693424E-01   1.31936756E-01   3.88095768E-02   1.10224534E-01   7.27739009E-02  -1.39951204E-02  -1.82016655E-02  -2.67418187E-02  -3.32844718E-02  -2.90241985E-02  -3.68330171E-02  -4.40717657E-02  -3.84666278E-02  -2.06058990E-02  -2.80211865E-02  -6.64800307E-02  -9.22433430E-02  -1.91743093E-02  -2.35447302E-02  -3.05547354E-02  -3.16830952E-02  -3.45785949E-02  -3.48965894E-02  -2.53287545E-02  -4.66715202E-03  -3.06240604E-02  -8.34732261E-04  -1.65435867E-02  -6.09565910E-03  -5.60015366E-02  -6.69489111E-02  -8.20495431E-02  -7.82580707E-02  -9.15528437E-02  -8.13032682E-02  -4.51493746E-02  -3.66939933E-03  -7.31935723E-02  -5.05941935E-02  -9.73661009E-02  -1.15843732E-01\nCm   4.64738409E-03   1.90253725E-02   5.54793200E-02   9.39794697E-02   7.17247208E-02   1.12356710E-01   1.47682577E-01   1.66874664E-01   1.84358896E-02  -1.22074388E-02   1.26787051E-01   6.61896244E-02   3.78992295E-03   4.98797896E-03   7.52095326E-03   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6.87326340E-02   3.02595937E-01   1.91112224E-01   5.29411266E-02   7.30388521E-02   1.22250992E-01   1.84889102E-01   1.06779201E-01   1.53280966E-01   2.58144305E-01   7.27687149E-01   1.56960611E-01   1.02548068E-01   1.59208468E-01   1.85369799E-01   6.24463879E-02   8.29285428E-02   1.27530045E-01   1.69865416E-01   1.31725967E-01   1.77778191E-01   2.46506549E-01   3.46658307E-01   1.48754445E-01   1.01941339E-01   1.79151675E-01   2.11501908E-01  -4.76200422E-02  -5.70267453E-02  -7.01454964E-02  -6.72618180E-02  -7.83803531E-02  -7.02006197E-02  -3.96800328E-02  -3.40365662E-03  -5.23353759E-02  -2.49832456E-02  -6.27259556E-02  -4.37729204E-02  -1.70259414E-02  -1.88563833E-02  -1.96537586E-02  -1.48191243E-02  -1.94806290E-02  -1.14219965E-02  -2.70835918E-03  -1.67028245E-05  -2.69025256E-03  -3.54123797E-03  -1.11891359E-02  -6.64101590E-03\nCm   1.20341644E-02   6.28793664E-03   6.52370170E-03   1.79356689E-02   1.27323469E-02   3.99724312E-02   4.09205509E-02  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6.95348167E-02   1.09323011E-01   3.11800261E-01   1.23478144E-01   5.14131380E-02   1.03707632E-01   1.07696224E-01   2.98994303E-02   4.01735009E-02   6.33937022E-02   8.77499800E-02   6.29711125E-02   8.73329853E-02   1.30098897E-01   2.32766813E-01   5.89558835E-02   1.86413884E-02   6.41969561E-02   3.24639884E-02   1.96213699E-02   2.63451968E-02   4.15082546E-02   5.73229772E-02   4.13391851E-02   5.72485578E-02   8.49382193E-02   1.49879349E-01   5.21277141E-02   4.94199870E-02   7.65151280E-02   7.49341807E-02   2.65922190E-02   3.43428141E-02   4.96903236E-02   6.04636253E-02   5.45710617E-02   6.76218914E-02   7.66241118E-02   5.62713931E-02   6.02927093E-02   3.88616981E-02   1.78435885E-02   2.77744323E-02  -6.65864998E-02  -8.57630357E-02  -1.23367366E-01  -1.48824970E-01  -1.36018748E-01  -1.66958450E-01  -1.85182416E-01  -1.27120016E-01  -1.14061806E-01  -2.46295164E-02  -7.19964257E-02  -4.35476141E-02\nCm   4.95992420E-02   6.86435633E-02   8.06072749E-02   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7.86718941E-02\nCm   2.53250167E-02   2.72119271E-02   3.40792443E-02   3.96013370E-02   3.95902299E-02   4.94150810E-02   4.22316508E-02   1.95907092E-03   6.12087891E-03   4.60907484E-02   6.88956727E-02   1.00007618E-01  -2.63499046E-03  -3.46212177E-03  -5.20104966E-03  -6.69077834E-03  -5.52602121E-03  -7.24031762E-03  -9.33682320E-03  -1.03611286E-02   6.77104637E-03  -4.35083669E-03  -2.39188603E-02  -2.45452124E-02   3.31289902E-02   4.06444501E-02   5.26465459E-02   5.44408107E-02   5.95690590E-02   5.98763069E-02   4.30931589E-02   7.73683276E-03   2.88490674E-02   5.50597190E-02   1.20928156E-01   1.43320982E-01   3.09227553E-02   3.78753961E-02   4.88873308E-02   5.02936639E-02   5.52938942E-02   5.51610108E-02   3.90721088E-02   6.68040238E-03   3.57989340E-02   3.26229251E-02   7.85791432E-02   8.32161086E-02  -2.37665698E-02  -2.81076072E-02  -3.36649790E-02  -3.10525358E-02  -3.71793119E-02  -3.12670612E-02  -1.55097485E-02  -8.93929940E-04  -1.41118027E-02  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6.79363940E-02   3.86875587E-02   3.39481432E-03   4.87166808E-02   1.97123752E-02   1.96694773E-02   1.41532993E-02\nCm  -4.27137565E-02  -4.44336960E-02  -3.89528461E-02  -1.77559672E-02  -3.37833925E-02  -2.42741157E-03   2.19330291E-02   3.06921348E-02  -2.53467113E-02  -6.66164770E-02   3.55587145E-03  -2.27207755E-03   6.72887342E-02   8.63120487E-02   1.23054854E-01   1.46506326E-01   1.36412632E-01   1.64972818E-01   1.76991465E-01   1.09421614E-01   1.22362063E-01   5.95977299E-02   1.75742157E-01   1.54303080E-01  -5.40131540E-02  -6.88871240E-02  -9.69996373E-02  -1.13388989E-01  -1.08224220E-01  -1.28106744E-01  -1.31056460E-01  -6.98071754E-02  -1.40182267E-01  -7.04920107E-02  -1.41705106E-01  -1.27321930E-01   2.62423424E-02   3.27866721E-02   4.41601228E-02   4.83555504E-02   4.99320237E-02   5.43910715E-02   4.64466305E-02   1.41156200E-02   4.12081440E-02   4.30649376E-02   6.83917706E-02   8.24896818E-02  -4.90256344E-02  -6.11229692E-02  -8.19543993E-02  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1.56452445E-02   1.16237480E-01   2.24225163E-02   7.47384391E-02   4.00233053E-02  -3.75706628E-02  -4.55103440E-02  -5.73645751E-02  -5.70030445E-02  -6.45940708E-02  -6.11683877E-02  -3.88370846E-02  -4.75040305E-03  -3.15463495E-02  -9.92491750E-03  -9.19449667E-03  -5.84934705E-03  -4.58408950E-02  -5.11263486E-02  -5.40822738E-02  -4.16598814E-02  -5.44043206E-02  -3.32214769E-02  -8.55538316E-03  -6.76982743E-05  -4.70618756E-02  -1.41854403E-02  -1.56866004E-02  -8.48216925E-03\nCm   7.84955604E-03   1.29650040E-02   9.25075385E-03  -1.96281424E-02   1.77897186E-02  -3.27230074E-02  -1.08894184E-01  -1.46574410E-01  -2.97017095E-02  -2.90383902E-02   3.67844483E-02   3.40919573E-02  -4.54818570E-02  -5.98418174E-02  -9.01723994E-02  -1.16525142E-01  -9.54895396E-02  -1.25624994E-01  -1.63595916E-01  -1.87391051E-01  -1.37143166E-01  -3.91842405E-03  -9.27735677E-02  -3.15879981E-02   3.45932106E-02   4.48667360E-02   6.55222934E-02   8.08293496E-02   7.14642166E-02   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3.46212177E-03   5.20104966E-03   6.69077834E-03   5.52602121E-03   7.24031762E-03   9.33682320E-03   1.03611286E-02   5.51553804E-03  -1.53193098E-02   3.44581858E-03  -2.07650058E-02  -6.79180237E-02  -8.89150333E-02  -1.32521070E-01  -1.68487467E-01  -1.41955308E-01  -1.83965144E-01  -2.31142592E-01  -2.35875218E-01  -1.73289332E-01  -4.34502822E-02  -8.01089452E-02  -5.79887654E-02   2.54484330E-02   3.31370085E-02   4.88114262E-02   6.09878294E-02   5.28596699E-02   6.73434543E-02   8.13078082E-02   7.30348226E-02   5.35607950E-02   1.53184640E-02   5.35469885E-02   3.33278667E-02   4.51550266E-02   5.73645637E-02   8.00933776E-02   9.24649394E-02   8.96910369E-02   1.04578386E-01   1.03492633E-01   4.96977007E-02   8.72680068E-02   4.64426816E-02   5.71825517E-02   5.48400653E-02\nCm   5.61710371E-02   7.34589415E-02   9.88605906E-02   1.08293980E-01   1.02321749E-01   1.16959574E-01   1.27909489E-01   6.78738644E-02   1.27899496E-01   8.68781516E-02   5.71395446E-02   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2.11764017E-02   5.87546586E-02   3.58192722E-02   5.10049755E-02   4.07389283E-02   2.08848691E-02   2.58025673E-02   3.39269985E-02   3.58622195E-02   3.84207283E-02   3.98592465E-02   3.06723109E-02   6.76341377E-03   3.38971852E-02   4.39032033E-03   6.03912561E-02   3.99514936E-02\nCm  -4.63461102E-03   6.22623272E-04  -5.85696699E-03  -4.52999976E-02   8.32923509E-03  -6.36038206E-02  -1.74296428E-01  -2.17244501E-01  -4.36941770E-02  -1.23124317E-02   2.30747802E-02   4.20937450E-02  -3.22357488E-02  -4.22199218E-02  -6.29855841E-02  -8.01932631E-02  -6.74056703E-02  -8.74709429E-02  -1.10251457E-01  -1.13660671E-01  -9.83855443E-02  -1.32130336E-02  -2.37152873E-02  -1.10380651E-02  -5.56175506E-02  -7.18065954E-02  -1.03829396E-01  -1.26220213E-01  -1.14079074E-01  -1.41215023E-01  -1.59639631E-01  -1.16371179E-01  -1.27876870E-01  -2.52825730E-02  -1.08786282E-01  -5.10887077E-02   6.29641712E-02   7.69216827E-02   9.87374844E-02   1.00758164E-01   1.11592029E-01   1.09998920E-01   7.59747294E-02   1.20235323E-02   8.28167027E-02   4.49482253E-02   1.05853597E-01   7.72137541E-02   1.34881856E-02   1.59619664E-02   1.91437467E-02   1.76928899E-02   2.11564081E-02   1.78499321E-02   8.91391271E-03   5.24360500E-04   1.21318175E-02   1.11320615E-02   2.41325838E-02   2.20548718E-02\nCm   6.68050292E-03   1.90854051E-02   4.16034627E-02   6.45313494E-02   3.70274124E-02   6.71014097E-02   1.36310182E-01   1.48749655E-01   1.76778668E-02  -2.15701219E-02   3.82037348E-02  -2.58421160E-02   1.82470689E-02   2.35762232E-02   3.41463661E-02   4.16110639E-02   3.74739253E-02   4.65103970E-02   5.28937698E-02   3.92924596E-02   2.34775575E-02   3.61613439E-02   4.51621799E-02   8.19766659E-02   6.32078184E-02   8.14579713E-02   1.17320545E-01   1.41790708E-01   1.29246772E-01   1.58969419E-01   1.77131413E-01   1.23363210E-01   8.51471597E-02   4.35076841E-02   1.11204836E-01   1.11723124E-01  -5.38915087E-02  -6.61221197E-02  -8.56617402E-02  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1.85555368E-01   2.82631389E-01   5.46007809E-01   1.67280661E-01   4.26668795E-02   1.34718818E-01   1.06700505E-01  -5.46461336E-02  -7.16793199E-02  -1.07287371E-01  -1.37267713E-01  -1.14432554E-01  -1.49180545E-01  -1.90088353E-01  -2.02948483E-01  -9.24879898E-02  -6.83472343E-02  -1.23379281E-01  -1.22794462E-01  -5.01319827E-02  -6.54915992E-02  -9.71600515E-02  -1.22685621E-01  -1.04542105E-01  -1.34588111E-01  -1.66500990E-01  -1.61663535E-01  -1.15732737E-01  -6.79915551E-02  -6.69335071E-02  -9.36255770E-02   4.68905163E-02   6.08120901E-02   8.87957332E-02   1.09516536E-01   9.68591536E-02   1.21764948E-01   1.42573239E-01   1.16158424E-01   1.51352719E-01   5.36128653E-02   7.01662516E-02   7.31796606E-02\nCm   2.96270387E-02   3.23808344E-02   2.71661187E-02   4.42814127E-03   2.86177229E-02  -3.02995619E-03  -4.63747077E-02  -1.02701381E-01  -1.32481537E-02   3.62102714E-02   4.05293973E-02   4.26574058E-02  -5.75058047E-02  -7.77014484E-02  -1.24148055E-01  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1.21536764E-01   1.38370425E-01   1.03149993E-01   2.12837417E-02   8.19687814E-02   6.81973497E-02   1.08159493E-01  -6.28149547E-02  -7.45329951E-02  -8.98963376E-02  -8.37693384E-02  -9.96185108E-02  -8.51932046E-02  -4.37508947E-02  -2.80228487E-03  -4.47123758E-02  -1.54743188E-02  -2.84825358E-02  -1.81276755E-02\nCm   8.78134209E-03   8.69761703E-03  -4.88224407E-04  -1.72124128E-02  -7.08958293E-03  -2.28275952E-02  -3.90413831E-02  -7.52962344E-02  -1.97471863E-02   2.55076678E-02  -1.66719370E-02   1.76557431E-02   9.77684063E-03   1.31368176E-02   2.07314403E-02   2.86998434E-02   2.05906035E-02   2.85585865E-02   4.25517435E-02   7.61828373E-02   2.47000433E-02   1.12479715E-02   5.53389151E-03   7.94743732E-03   3.31108629E-02   4.43148898E-02   6.93276953E-02   9.47340440E-02   6.98420543E-02   9.60487874E-02   1.39833276E-01   2.31384836E-01   1.01599241E-01   2.26554640E-03   5.53380306E-02   1.43702919E-02  -6.62777258E-02  -8.84999885E-02  -1.37748654E-01  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2.02654552E-01   1.15462452E-01   3.40197852E-02   1.17655990E-01   8.18042788E-02   2.77396950E-02   3.62220363E-02   5.36833419E-02   6.76861828E-02   5.78163308E-02   7.43250757E-02   9.16371369E-02   8.80128750E-02   6.78305264E-02  -1.68909086E-03   2.36388511E-02   1.61999445E-03  -5.26003431E-02  -6.83504907E-02  -1.00228333E-01  -1.24397336E-01  -1.08956490E-01  -1.37870256E-01  -1.63867325E-01  -1.40016869E-01  -1.17320933E-01  -4.64665047E-02  -1.44508184E-01  -1.03117268E-01  -5.79470877E-02  -7.29427885E-02  -9.98454493E-02  -1.11955531E-01  -1.12536013E-01  -1.26483926E-01  -1.15547827E-01  -4.32696547E-02  -9.27277162E-02  -6.46352831E-02  -9.16802016E-02  -9.36925470E-02\nCm   3.70986925E-04  -6.76547464E-03  -1.63652901E-02  -2.17482846E-02  -1.37186032E-02  -1.49404318E-02  -3.41654761E-02  -9.15002504E-02  -2.64518409E-02   2.34825051E-02  -1.42005076E-02  -2.38178774E-03  -5.10821068E-02  -6.72392197E-02  -1.01414836E-01  -1.31237044E-01  -1.07282192E-01  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5.58962568E-02   8.82294378E-02   1.22180060E-01   8.75987766E-02   1.21520896E-01   1.81162766E-01   3.24953993E-01   1.06060361E-01   5.05224248E-02   1.02011904E-01   1.26357923E-01  -7.63099106E-02  -1.00726801E-01  -1.52853387E-01  -1.99604186E-01  -1.60563539E-01  -2.13190158E-01  -2.83889389E-01  -3.49620945E-01  -1.58616963E-01  -5.42253538E-02  -1.26706732E-01  -7.61254332E-02   4.72837222E-03   6.21282127E-03   9.33400345E-03   1.20087771E-02   9.91646351E-03   1.29940085E-02   1.67603573E-02   1.86127232E-02   1.02976208E-02   4.03460342E-03   1.77765275E-02   1.02189540E-02   8.17137991E-03   1.05796246E-02   1.53916040E-02   1.88808538E-02   1.68364736E-02   2.10452299E-02   2.43225898E-02   1.90140326E-02   2.72044147E-02   1.62734460E-02   1.83262730E-02   2.97630673E-02\nCm  -4.93101081E-03  -5.83172749E-03  -1.01962492E-02  -2.28162637E-02  -8.58170032E-03  -3.98403170E-02  -6.34455079E-02  -4.58265769E-03  -5.00246626E-03  -1.31722297E-02  -2.22303370E-02  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1.55502604E-01   6.92169413E-02   3.58871583E-03   4.22578526E-02   4.56680817E-02   6.01872174E-03   7.82804499E-03   1.15017744E-02   1.43173466E-02   1.24826665E-02   1.58428134E-02   1.89612033E-02   1.65630872E-02   6.96886447E-03   8.95983724E-03  -3.78897603E-03   1.76738389E-03   6.47876771E-02   8.41782261E-02   1.23409645E-01   1.53116620E-01   1.34181831E-01   1.69730395E-01   2.01573186E-01   1.71795432E-01   1.19977545E-01   3.02139961E-02   1.26670398E-01   6.43972347E-02  -2.05339452E-02  -2.61770678E-02  -3.68249393E-02  -4.29869924E-02  -4.11042914E-02  -4.85747488E-02  -4.95107427E-02  -2.60703879E-02  -3.31273428E-02   5.16049673E-04  -4.33909211E-02  -1.79386324E-02  -2.66596698E-02  -3.27673251E-02  -4.26097739E-02  -4.43150536E-02  -4.82294520E-02  -4.88839274E-02  -3.58068431E-02  -6.78555786E-03  -4.03974893E-02   5.01311074E-03  -1.32304807E-02  -6.45905062E-04\nCm   1.91441268E-03  -1.33418576E-02  -4.56674662E-02  -8.66424368E-02  -4.06438008E-02  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2.71854572E-02   1.19976300E-02   4.84804019E-04   1.44723462E-02   3.61303634E-02   3.49464740E-02   4.08925868E-02\nCm   4.72134521E-02   6.49440993E-02   8.10977754E-02   5.62449511E-02   1.04872422E-01   5.63250330E-02  -5.96649734E-02  -1.60967434E-01   2.96342349E-02   7.80770786E-03   1.31797188E-01   1.02851422E-01  -6.83274410E-02  -8.89679136E-02  -1.31042170E-01  -1.63714651E-01  -1.41919002E-01  -1.80786468E-01  -2.18221385E-01  -1.95865795E-01  -1.99926263E-01  -1.87899775E-02  -1.36149992E-01  -6.60782429E-02   3.27327556E-02   4.11933404E-02   5.63564641E-02   6.31428431E-02   6.35279381E-02   7.13300548E-02   6.50212379E-02   2.41852584E-02   4.60791532E-02   6.59054253E-02   7.44752298E-02   1.02720408E-01   3.20503503E-02   3.94512168E-02   5.14640002E-02   5.37722578E-02   5.82641203E-02   5.94516446E-02   4.41689580E-02   8.74237240E-03   4.48691973E-02   3.73018508E-02   3.89137384E-02   5.13976110E-02   5.96180351E-02   6.98342143E-02   8.19531428E-02   7.33837526E-02   8.95054334E-02   7.16232303E-02   3.20645751E-02   1.35319127E-03   2.98084586E-02   9.38194333E-02   1.26236302E-01   1.65700070E-01\nCm  -6.48458559E-02  -8.00035360E-02  -1.00015958E-01  -1.09441006E-01  -8.51257314E-02  -9.12318002E-02  -1.47742481E-01  -2.83366827E-01  -9.13356731E-02  -7.82834433E-02  -8.79249105E-02  -1.04822829E-01  -2.87114038E-02  -3.81704212E-02  -5.88412021E-02  -7.86560631E-02  -6.05782038E-02  -8.19857867E-02  -1.14489301E-01  -1.64821132E-01  -5.41785171E-02  -2.31886929E-02  -6.51812182E-02  -4.09752792E-02  -2.97577415E-02  -3.93784823E-02  -6.00883594E-02  -7.91144915E-02  -6.26952623E-02  -8.38253785E-02  -1.13546642E-01  -1.47862407E-01  -6.99815036E-02  -3.63152537E-02  -6.45333980E-02  -4.62191096E-02   6.90488550E-02   8.61667379E-02   1.15763594E-01   1.26291097E-01   1.30938782E-01   1.41917723E-01   1.19891267E-01   3.52446412E-02   7.97450256E-02   1.57417706E-02   3.04464111E-02   1.45660362E-02  -3.27059783E-02  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1.14931914E-02   4.86347336E-02   6.10766788E-02   8.31799841E-02   9.25761975E-02   9.38646062E-02   1.04479736E-01   9.34652001E-02   3.27979156E-02   1.42011836E-01   3.48639248E-02   6.96997233E-02   4.77557921E-02\nCm   4.43037883E-02   6.57457903E-02   9.84710932E-02   1.19756488E-01   8.54755754E-02   7.42668667E-02   1.21267342E-01   5.19886861E-01   4.53752560E-02   1.07540916E-01   2.18525721E-01   3.43796617E-01   6.20286302E-02   8.45749915E-02   1.37878773E-01   2.00405204E-01   1.28543415E-01   1.82716486E-01   2.93675966E-01   6.88055062E-01   1.54945198E-01   5.23039525E-02   4.13393241E-01   2.52633453E-01  -5.09507147E-02  -6.65818586E-02  -9.88445086E-02  -1.24938136E-01  -1.06286461E-01  -1.36967709E-01  -1.69833149E-01  -1.66112880E-01  -1.38400165E-01  -1.68473481E-02  -8.64334352E-02  -4.38687195E-02  -8.32579696E-03  -1.02283847E-02  -1.32872766E-02  -1.37986001E-02  -1.50384630E-02  -1.52098221E-02  -1.10905174E-02  -2.07261111E-03  -1.18638061E-02   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1.16717725E-01   1.01822436E-01   1.29180889E-01   1.54468328E-01   1.34544232E-01   1.16171309E-01   4.60085989E-02   1.07235352E-01   7.67776368E-02   4.10047200E-02   5.26434199E-02   7.51965726E-02   8.97791866E-02   8.32675332E-02   1.01024610E-01   1.09163737E-01   6.90245030E-02   5.91744704E-02   3.79685177E-02   9.39410325E-02   7.61664105E-02  -2.65217674E-02  -3.30209389E-02  -4.41447906E-02  -4.78120032E-02  -4.99585481E-02  -5.36166184E-02  -4.43496611E-02  -1.22159753E-02  -3.07524692E-02   3.67521845E-03  -2.16625172E-02  -1.13713047E-02\nCm   3.75667701E-02   5.50561477E-02   8.81761312E-02   1.07373819E-01   9.70828888E-02   9.79942819E-02   1.13249277E-01   2.40426382E-01   9.26265035E-02   2.24183889E-02   1.66928278E-01   1.41076812E-01   5.48640039E-02   7.28510375E-02   1.12005071E-01   1.49132221E-01   1.15728367E-01   1.56142802E-01   2.16349963E-01   3.03521375E-01   1.88249778E-01   5.87915725E-02   1.85480851E-01   1.71332432E-01   9.12391123E-03   1.20928766E-02   1.85171752E-02   2.45071572E-02   1.92350285E-02   2.58275397E-02   3.53568012E-02   4.76677190E-02   4.02434597E-02   2.09926069E-02   1.09399282E-02   9.88525483E-03  -4.08734551E-02  -5.28765083E-02  -7.67905355E-02  -9.39525758E-02  -8.41095282E-02  -1.04841965E-01  -1.20401517E-01  -9.22481299E-02  -9.91978070E-02  -8.20485476E-03  -6.66419011E-02  -2.38471133E-02  -2.94655571E-02  -3.70450711E-02  -5.05735129E-02  -5.64866012E-02  -5.70385349E-02  -6.37841036E-02  -5.76342277E-02  -2.08618367E-02  -4.46733344E-02   1.16182397E-02  -4.87585442E-02  -7.86717318E-03\nCm  -7.49713731E-03  -1.09440518E-02  -3.71234232E-03   2.21496517E-02  -4.13961343E-03   3.15924155E-02   7.19368877E-02   1.51342029E-01   5.16183463E-02  -6.93749592E-03  -4.06007412E-02  -8.43452333E-02   7.59782689E-02   1.02044285E-01   1.60880271E-01   2.22390992E-01   1.60051406E-01   2.21782950E-01   3.29611153E-01   5.84996286E-01   3.34662419E-01   3.78723119E-02   1.38949334E-01   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4.78134130E-01   9.47313621E-02   6.43744267E-02   2.05660620E-01   1.55045933E-01   3.93949108E-02   5.27022403E-02   8.23695163E-02   1.12393016E-01   8.31061250E-02   1.14176997E-01   1.65787352E-01   2.71899744E-01   9.89071439E-02   5.21989125E-02   5.90392809E-02   5.72977417E-02  -5.61199211E-03  -7.16625997E-03  -1.01178227E-02  -1.18741179E-02  -1.12741791E-02  -1.34081619E-02  -1.38597590E-02  -7.62556160E-03  -1.62862527E-02   2.22606992E-02  -8.22389295E-03   9.13278282E-03  -5.89074504E-02  -6.99236291E-02  -8.44064106E-02  -7.87480698E-02  -9.35709109E-02  -8.01787094E-02  -4.13436045E-02  -2.68109180E-03  -4.47552631E-02  -2.92808936E-02  -7.58470183E-02  -5.24137203E-02\nCm  -5.37429158E-03  -7.03380147E-04   1.38857972E-02   2.91878076E-02   2.59976062E-02   4.14553268E-02   4.20094077E-02   1.23110586E-02   4.53283818E-02  -3.12355806E-02  -1.44728314E-02  -5.11877976E-02   1.48350360E-02   1.96611309E-02   3.01016726E-02   3.98304387E-02   3.12744829E-02   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1.35956808E-02\nCm   7.11194301E-03   3.18264798E-02   6.89229800E-02   7.71853941E-02   9.36886949E-02   8.31303719E-02   4.56946527E-02  -1.55634534E-02   5.92965073E-02  -7.51577627E-03   3.58520147E-02   2.21245584E-02  -1.28118071E-02  -1.68831473E-02  -2.55272140E-02  -3.31550544E-02  -2.69288382E-02  -3.55871984E-02  -4.68498735E-02  -5.55894530E-02  -2.90330849E-02   1.77694481E-02  -1.07641082E-02   6.24411993E-03   1.01770057E-02   1.32578525E-02   1.95487669E-02   2.44618766E-02   2.11514156E-02   2.69875013E-02   3.26971915E-02   2.96981165E-02   2.23323158E-02   1.49636140E-02   5.72629021E-03   1.15781068E-02   4.59911982E-02   5.63777635E-02   7.28962910E-02   7.51851324E-02   8.24659123E-02   8.25768303E-02   5.89560136E-02   1.03275716E-02   3.94352524E-02   1.95563341E-02   2.27342534E-02   1.58743019E-02   4.25339684E-02   4.35502650E-02   3.84877886E-02   2.28805210E-02   3.10215919E-02   1.12256593E-02   1.00472352E-03   3.29594367E-07   5.05183442E-03   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2.22630936E-01   1.22627652E-01   2.05064383E-02   5.19239730E-02   4.01151090E-02   8.65941916E-03   1.11949800E-02   1.62347093E-02   1.98208970E-02   1.78006349E-02   2.21378478E-02   2.52920159E-02   1.90630678E-02   2.06898122E-02   1.47076519E-02   1.06953495E-02   2.84584936E-02  -6.81376126E-02  -8.73257429E-02  -1.24268042E-01  -1.47544027E-01  -1.37902142E-01  -1.66247194E-01  -1.77105103E-01  -1.07094197E-01  -1.34803140E-01  -4.33812484E-02  -7.76962724E-02  -4.96619150E-02   3.36332114E-02   4.15985966E-02   5.48263783E-02   5.81551159E-02   6.20889312E-02   6.47305449E-02   5.03331784E-02   1.14603945E-02   2.54771602E-02   6.29193442E-03   2.27107231E-02   1.10537352E-02\nCm  -8.50878192E-03   4.98315298E-03   3.34221004E-02   6.65291779E-02   3.67149890E-02   7.82813850E-02   1.35682433E-01   1.73480445E-01   6.49023942E-02  -2.17218919E-03   2.89460685E-02   2.19354366E-02   2.87114038E-02   3.81704212E-02   5.88412021E-02   7.86560631E-02   6.05782038E-02   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7.90016920E-02   1.17913945E-01   1.50233243E-01   1.26129053E-01   1.63783614E-01   2.06762083E-01   2.14231588E-01   1.15148623E-01   3.18312740E-02   8.17515038E-02   4.34127940E-02   7.07936688E-03   9.12396268E-03   1.31425936E-02   1.58868988E-02   1.44773502E-02   1.78105024E-02   1.98549205E-02   1.38490642E-02   1.48044016E-02   1.97684870E-02   1.94489969E-02   2.48499091E-02   2.05628344E-02   2.63282193E-02   3.73882512E-02   4.42552107E-02   4.15374618E-02   4.98976932E-02   5.27381673E-02   3.11095434E-02   4.24392316E-02   2.23834402E-02   2.89275026E-02   3.13592344E-02  -4.22196088E-02  -5.25431096E-02  -7.01790174E-02  -7.59067096E-02  -7.94279852E-02  -8.50867863E-02  -7.01036261E-02  -1.90764077E-02  -7.32926108E-02  -9.39036882E-03  -4.33265035E-02  -2.53652780E-02\nCm   7.09055889E-05   5.07862586E-03   3.14833826E-03  -9.89276691E-03  -2.24710622E-03  -2.43136277E-02  -2.96615576E-02  -1.06583725E-02  -2.48682042E-03   8.00181921E-03   5.19563407E-03   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1.55473320E-01   1.41231306E-01   1.74165433E-01   1.95212514E-01   1.38511315E-01   1.13521125E-01   3.25631831E-02   7.75410454E-02   4.63771753E-02  -1.51326589E-02  -1.90167148E-02  -2.59362266E-02  -2.89274316E-02  -2.92583392E-02  -3.26577603E-02  -2.93906869E-02  -1.05069397E-02  -4.48790274E-02   8.53176219E-03   4.25774795E-04   4.71943023E-03   8.84410547E-03   1.07058456E-02   1.34749168E-02   1.33617236E-02   1.51675077E-02   1.43166104E-02   9.02843603E-03   1.08165452E-03   9.92165209E-03   1.15785195E-02   7.92974497E-03   6.40451602E-03\nCm   7.89110624E-03   8.80117575E-03   1.86644491E-02   4.24748148E-02   9.66556348E-03   4.13067907E-02   1.11442422E-01   2.15285154E-01   4.02453536E-02   1.74880688E-02   2.01977543E-02   1.78804454E-02   2.97577415E-02   3.93784823E-02   6.00883594E-02   7.91144915E-02   6.26952623E-02   8.38253785E-02   1.13546642E-01   1.47862407E-01   8.57656417E-02  -9.03564858E-04   2.14554658E-02   1.54546961E-03   3.16393252E-02   4.12093115E-02   6.07373996E-02   7.59542461E-02   6.57413817E-02   8.38274740E-02   1.01413395E-01   9.16801184E-02   5.94646535E-02   1.78303268E-02   6.09135947E-02   3.30334944E-02   1.61498840E-02   2.09916928E-02   3.08012688E-02   3.82641639E-02   3.34661482E-02   4.23874280E-02   5.04906923E-02   4.34440372E-02   3.96744548E-02   3.33577331E-02   2.90623724E-02   4.00620744E-02  -6.60895365E-02  -8.38105419E-02  -1.16569222E-01  -1.33816281E-01  -1.30731647E-01  -1.51373393E-01  -1.47534827E-01  -6.75594577E-02  -7.65270576E-02  -3.42262747E-02  -5.14179194E-02  -4.05269723E-02\nCm   5.65188796E-02   6.01644253E-02   6.78248802E-02   7.19691806E-02   6.83268738E-02   8.13431308E-02   8.29186228E-02   3.31569104E-02   3.97413695E-02   6.00083567E-02   2.04097639E-02   2.98596726E-02   6.98332487E-02   8.76280978E-02   1.19134525E-01   1.32256647E-01   1.34486780E-01   1.49198586E-01   1.32514888E-01   4.54786086E-02   1.59934512E-01   2.62099377E-02   7.07873944E-02   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2.73642175E-02   2.84543481E-02   3.53709237E-02   4.22196088E-02   5.25431096E-02   7.01790174E-02   7.59067096E-02   7.94279852E-02   8.50867863E-02   7.01036261E-02   1.90764077E-02   6.15213730E-02   5.72385899E-02   7.38252422E-02   7.26447032E-02\nCm   1.86696520E-02   3.44382279E-02   6.46294155E-02   9.10885522E-02   6.74973438E-02   9.19258996E-02   1.35694785E-01   2.24205909E-01   8.72878828E-02   3.43275323E-02   7.67772500E-02   6.32665477E-02   7.27919655E-02   9.64218942E-02   1.47454450E-01   1.94777308E-01   1.53426254E-01   2.05687168E-01   2.80477223E-01   3.73306076E-01   2.43428739E-01   4.45665427E-02   1.42164248E-01   7.40683118E-02  -1.45796113E-02  -1.91909703E-02  -2.89447273E-02  -3.74554533E-02  -3.06198211E-02  -4.03329276E-02  -5.26802606E-02  -6.09271663E-02  -5.33252563E-02   2.33087077E-02  -1.99639998E-02   1.42704687E-02  -4.18175550E-02  -5.43198558E-02  -7.95928501E-02  -9.86736261E-02  -8.65785916E-02  -1.09425790E-01  -1.29709770E-01  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1.48551058E-02   1.25733373E-02   3.71792015E-03   1.53834973E-02   5.88855534E-03   2.92714203E-03   1.06625223E-03  -3.86314021E-02  -4.18148788E-02  -4.15281836E-02  -2.92034909E-02  -3.90397168E-02  -1.99806325E-02  -3.59692816E-03  -9.66471167E-06  -2.89275376E-02  -2.24568948E-02  -2.74789694E-02  -2.31584609E-02\nCm   1.66995419E-02   2.52659269E-02   6.23497865E-02   1.21250983E-01   6.37031001E-02   1.38578639E-01   2.50166046E-01   3.61843929E-01   6.85097004E-02  -6.64207433E-03   4.14150723E-02  -6.54538715E-04   7.12799979E-02   9.43728434E-02   1.44165725E-01   1.90128501E-01   1.50209664E-01   2.01110237E-01   2.73342324E-01   3.59933265E-01   1.56257038E-01   4.06277449E-02   1.42356752E-01   9.21753430E-02   7.53324151E-03   9.49823123E-03   1.30472806E-02   1.47057984E-02   1.46917997E-02   1.66233047E-02   1.54072569E-02   6.03438066E-03   1.62102830E-02   4.29496746E-02   2.53180137E-02   4.28436022E-02  -2.28337305E-02  -2.78405794E-02  -3.55864185E-02  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1.30438695E-01   1.34049662E-01   7.24229437E-02   1.30913545E-01   2.87048015E-02   1.46774764E-01   7.77180005E-02  -4.20786103E-02  -5.32837763E-02  -7.38778614E-02  -8.44168009E-02  -8.29473651E-02  -9.54927446E-02  -9.19076295E-02  -4.04702414E-02  -8.07256943E-02  -4.03769933E-03  -5.19210050E-02  -1.83419773E-02  -1.75658640E-02  -2.21311301E-02  -3.03512144E-02  -3.41278121E-02  -3.41919430E-02  -3.85687288E-02  -3.55105660E-02  -1.36242053E-02  -2.50490272E-02   2.51516535E-02  -4.49221101E-03   2.65908754E-02\nCm   8.38941663E-03   2.14174398E-02   7.36240876E-02   1.54662197E-01   8.25623551E-02   1.85892189E-01   3.14877059E-01   4.33493362E-01   1.22560472E-01   1.95471528E-02   9.53908137E-02   2.99877632E-02   4.13800414E-02   5.55308864E-02   8.73902208E-02   1.20476593E-01   8.72025373E-02   1.20628370E-01   1.78427174E-01   3.11581056E-01   1.40548173E-01   5.28500929E-02   7.28794735E-02   8.01131558E-02   2.06752921E-02   2.70555972E-02   4.02868646E-02   5.11502632E-02   4.31943636E-02   5.59036030E-02   7.00227573E-02   7.07490586E-02   4.25847459E-02   3.22608220E-02   8.76710372E-03   3.22088238E-02   4.41986256E-02   5.62681527E-02   7.89218045E-02   9.17267645E-02   8.82103027E-02   1.03696120E-01   1.04478880E-01   5.30623456E-02   7.13241292E-02   4.01980143E-02   3.46866028E-02   4.77930861E-02  -4.34358417E-02  -5.14884335E-02  -6.19727147E-02  -5.75743911E-02  -6.86073435E-02  -5.83821937E-02  -2.96756472E-02  -1.84224944E-03  -3.07503207E-02  -1.73803564E-02  -2.30433689E-02  -1.88167824E-02\nCm  -2.52607746E-02  -2.94090115E-02  -4.72333044E-02  -7.02602539E-02  -5.57307608E-02  -8.76876087E-02  -1.07049375E-01  -8.65720972E-02  -2.70058148E-02  -2.87001250E-02  -3.31672927E-02  -5.15559583E-02  -2.63835928E-02  -3.43192874E-02  -5.04394386E-02  -6.28125294E-02  -5.47281665E-02  -6.94892312E-02  -8.32473122E-02  -7.29425008E-02  -6.34818551E-02  -1.78796079E-02  -6.67237146E-02  -4.25350885E-02  -6.60139585E-03  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5.20817025E-02   1.16350802E-01   1.05278336E-01   6.70192881E-02   8.82498946E-02   1.33212349E-01   1.72592342E-01   1.40791441E-01   1.85655055E-01   2.43128641E-01   2.83596230E-01   1.20620258E-01   5.45902729E-02   1.56847246E-01   1.33535237E-01   1.07805027E-02   1.36133710E-02   1.87620135E-02   2.12500813E-02   2.11064882E-02   2.40300029E-02   2.25743534E-02   9.21927655E-03   1.71366007E-02   1.31336047E-02   1.22002773E-02   8.30238488E-03   2.86927808E-02   3.59196288E-02   4.85875879E-02   5.35393294E-02   5.49012828E-02   6.03098419E-02   5.24411169E-02   1.68539250E-02   7.14832227E-02   6.44348141E-02   5.25760626E-02   1.00530289E-01  -3.47480972E-02  -4.01052840E-02  -4.56118434E-02  -3.90234789E-02  -4.88016797E-02  -3.60944502E-02  -1.37444456E-02  -3.55031601E-04  -2.91484671E-02  -2.70424988E-02  -3.78714632E-02  -3.81780559E-02\nCm   3.89951037E-02   3.56480619E-02   3.15427911E-02   4.74567246E-02  -5.43582565E-03   1.27245562E-02   1.06597194E-01   4.59416296E-01   9.63872512E-02   7.43338776E-02  -4.99969261E-02  -4.18455332E-02   7.07468114E-02   9.59726093E-02   1.54697675E-01   2.21058832E-01   1.47729171E-01   2.08488956E-01   3.27037137E-01   7.00972812E-01   3.67276663E-01   2.61201150E-02   2.01045939E-01   7.56519600E-02  -3.44832231E-02  -4.55693958E-02  -6.93270076E-02  -9.08722532E-02  -7.26028436E-02  -9.67095767E-02  -1.29797531E-01  -1.64005297E-01  -1.11534062E-01  -2.19989360E-03  -1.65229741E-01  -9.90511754E-02  -1.63702374E-02  -2.16212558E-02  -3.28537511E-02  -4.29865853E-02  -3.44564989E-02  -4.58271596E-02  -6.12763040E-02  -7.64840216E-02  -5.18957493E-02  -1.84393479E-02  -2.12312766E-02  -3.16488892E-02   5.13615941E-03   6.37158490E-03   8.45175077E-03   9.04964720E-03   9.56990067E-03   1.01095446E-02   8.08477387E-03   2.00695867E-03   4.06472139E-03   1.48881569E-02   1.35916228E-02   1.25181182E-02\nCm   5.51197201E-02   6.58785796E-02   6.90116986E-02   3.60862502E-02   8.15751284E-02   3.39485918E-02  -6.03777363E-02  -2.13269373E-01   1.34700818E-02   7.34461925E-02   1.13276789E-01   1.30295339E-01  -2.61835852E-02  -3.49268497E-02  -5.42403429E-02  -7.33087020E-02  -5.52573097E-02  -7.54053786E-02  -1.07561352E-01  -1.66188912E-01  -9.89136114E-02   2.48880224E-04  -3.73290726E-02  -7.03563744E-03  -5.41282100E-02  -7.00233135E-02  -1.01690952E-01  -1.24415793E-01  -1.11384223E-01  -1.38837021E-01  -1.59434801E-01  -1.22137401E-01  -1.09061909E-01  -2.07133052E-02  -1.20258607E-01  -6.47930036E-02   6.37906185E-02   8.08502613E-02   1.12316951E-01   1.28707217E-01   1.26018284E-01   1.45596281E-01   1.41225768E-01   6.37125621E-02   1.32732934E-01   7.54409272E-02   1.38940488E-01   1.23087938E-01   4.29010498E-02   5.27457337E-02   6.86342753E-02   7.14497910E-02   7.76901390E-02   7.88542420E-02   5.79302017E-02   1.10778096E-02   4.73104974E-02   6.64711068E-02   1.08146165E-01   1.01679337E-01\nCm   4.28087601E-02   4.03593266E-02   3.75927852E-02   3.79500798E-02   2.84413598E-02   3.85529423E-02   6.00307239E-02   5.38578384E-02   4.24085335E-02   4.93658892E-02   1.86139697E-02   2.35875186E-02  -2.35209880E-03  -3.08491166E-03  -4.61630122E-03  -5.90419391E-03  -4.92494984E-03  -6.41832163E-03  -8.17194733E-03  -8.70287067E-03   1.81379888E-03   4.86069469E-03  -1.55323259E-03  -5.06601534E-04   6.81376126E-02   8.73257429E-02   1.24268042E-01   1.47544027E-01   1.37902142E-01   1.66247194E-01   1.77105103E-01   1.07094197E-01   1.60437758E-01   3.15134006E-02   9.09907650E-02   4.50622075E-02  -2.63914889E-02  -3.36898626E-02  -4.75324603E-02  -5.57259181E-02  -5.29829153E-02  -6.29346876E-02  -6.48790415E-02  -3.53959376E-02  -5.62882431E-02   4.34757094E-03  -1.09211674E-02   3.45364378E-03  -3.09698339E-02  -3.81854190E-02  -4.99929045E-02  -5.25120021E-02  -5.66085759E-02  -5.82023622E-02  -4.39414374E-02  -9.13755070E-03  -5.01460099E-02  -1.58417983E-02  -4.79748572E-02  -3.05619658E-02\nCm  -7.04178586E-02  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7.51842938E-03\nCm   2.69810039E-02   2.78704391E-02   2.99709327E-02   3.34176379E-02   2.89866363E-02   3.44266214E-02   3.49308003E-02   6.90816022E-02   2.41067305E-02   8.05311072E-02   5.92056517E-02   1.37144618E-01   4.51495565E-02   5.97085755E-02   9.09835709E-02   1.19544212E-01   9.50954500E-02   1.26925629E-01   1.71196343E-01   2.19841237E-01   1.03338933E-01   1.76512673E-02   1.99872933E-01   1.00995301E-01  -6.12253711E-02  -7.97156960E-02  -1.17399218E-01  -1.46641965E-01  -1.27157958E-01  -1.61951440E-01  -1.95398655E-01  -1.75130627E-01  -1.38311552E-01  -2.13432585E-02  -1.11879285E-01  -5.79682861E-02   1.38845229E-02   1.76904183E-02   2.48563106E-02   2.89642139E-02   2.77600227E-02   3.27355566E-02   3.32103121E-02   1.72329782E-02   1.58319107E-02   6.75815572E-03   3.16131444E-02   1.40197870E-02   1.27012591E-02   1.58837956E-02   2.14375679E-02   2.35448300E-02   2.42321435E-02   2.65027423E-02   2.28284318E-02   7.12583205E-03   1.59463663E-02   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2.06388325E-03  -8.52551942E-03   5.22880025E-03   1.64957968E-02   9.86225993E-03\nCm  -7.32790705E-04  -8.06523185E-03  -2.47354488E-02  -3.23920132E-02  -4.75602133E-02  -6.02338648E-02  -3.30254176E-02   1.75920079E-01  -4.27691097E-02   5.47582579E-02  -4.21280879E-02   2.67086779E-02   4.20566976E-02   5.67343375E-02   9.03213479E-02   1.26687357E-01   8.83362716E-02   1.23477185E-01   1.88099936E-01   3.63545652E-01   1.58325791E-01   1.60846227E-02   1.48796589E-01   5.40143514E-02  -4.02813588E-02  -5.27796943E-02  -7.88116958E-02  -1.00480285E-01  -8.42644532E-02  -1.09489625E-01  -1.38426469E-01  -1.44114993E-01  -1.02240859E-01  -4.46466563E-02  -5.75538756E-02  -4.87510642E-02  -6.22273761E-02  -7.84291037E-02  -1.07646136E-01  -1.21183504E-01  -1.21241649E-01  -1.36969076E-01  -1.26524230E-01  -4.90411309E-02  -7.90594708E-02  -5.93166993E-02  -6.81422001E-02  -8.03556913E-02   5.08856892E-02   6.14664198E-02   7.70136582E-02   7.58612881E-02   8.65804168E-02   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1.64231490E-01   2.26419282E-01   3.12435983E-01   1.52739337E-01   3.17442879E-02   1.22272844E-01   6.03909136E-02  -4.72837222E-03  -6.21282127E-03  -9.33400345E-03  -1.20087771E-02  -9.91646351E-03  -1.29940085E-02  -1.67603573E-02  -1.86127232E-02  -8.02012342E-05   4.16778867E-03  -1.73481471E-02  -2.44500453E-03   1.30830703E-02   1.69486851E-02   2.46886148E-02   3.03419607E-02   2.69805265E-02   3.37917621E-02   3.92303916E-02   3.11089461E-02   3.78129252E-02   9.46356355E-03   5.06751559E-02   2.75207571E-02  -7.00239270E-02  -9.03607914E-02  -1.30514974E-01  -1.58403927E-01  -1.43507213E-01  -1.77329737E-01  -1.99667402E-01  -1.43725771E-01  -1.54959774E-01  -4.55848894E-02  -1.07888670E-01  -8.30765815E-02\nCm  -2.06308634E-03  -4.54869042E-03  -1.14050636E-02  -2.02373203E-02  -1.13455404E-02  -2.08575981E-02  -3.91933028E-02  -6.58363030E-02  -2.26756020E-02  -1.34709530E-02  -1.13228735E-02  -2.08097019E-02  -6.70863671E-02  -8.79518219E-02  -1.31495293E-01  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3.09788737E-02   3.80943574E-02   2.97595090E-02   1.26796060E-02   4.60471805E-04   2.62746054E-02   3.14910028E-02   2.12639287E-02   3.55022212E-02\nCm   6.23702142E-02   6.47579966E-02   4.86383778E-02   4.68906647E-03   3.47903902E-02  -2.39080154E-02  -6.41811691E-02  -1.06453046E-01   3.45857992E-02   9.73869037E-02   9.68132936E-03   9.19931359E-02  -6.22479150E-02  -8.20085454E-02  -1.23928443E-01  -1.60828685E-01  -1.30814889E-01  -1.72751363E-01  -2.27029116E-01  -2.67864147E-01  -1.13519862E-01  -4.83281901E-02  -1.14361764E-01  -1.12187880E-01   7.11182090E-02   9.25809105E-02   1.36297016E-01   1.70156171E-01   1.47672659E-01   1.87978179E-01   2.26518158E-01   2.02217052E-01   1.74137192E-01   5.37022775E-02   2.02927313E-01   1.20750201E-01  -1.34575594E-02  -1.75134474E-02  -2.57656831E-02  -3.21341137E-02  -2.79324543E-02  -3.55201299E-02  -4.27020352E-02  -3.78361214E-02  -4.15277957E-02  -6.21113055E-03  -1.52249309E-02  -1.58588187E-02  -2.63983972E-02  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1.75500611E-01   1.53798643E-01   1.94543518E-01   2.31039436E-01   1.96903267E-01   1.40545981E-01   9.58520439E-02   1.88367013E-01   2.22696023E-01   4.17138499E-03   5.35749209E-03   7.65925347E-03   9.15612299E-03   8.47705774E-03   1.02995712E-02   1.11650811E-02   7.13116743E-03  -1.17688028E-02   5.11973249E-02   4.26461795E-02   6.46663060E-02\nCm   1.37683100E-02   1.12712052E-02   5.27201653E-03  -1.65738195E-02   2.88608847E-02   1.44745288E-02  -6.37499781E-02  -4.15317454E-01   2.39902310E-02  -6.09760932E-03  -1.76693579E-02  -3.12985508E-02  -5.07719069E-02  -6.89723443E-02  -1.11524545E-01  -1.60115740E-01  -1.05819951E-01  -1.49662419E-01  -2.36401374E-01  -5.19591777E-01  -1.81246325E-01  -1.47363804E-02  -1.73514410E-01  -7.60617405E-02  -9.17095477E-03  -1.19775795E-02  -1.77589628E-02  -2.24051374E-02  -1.91187263E-02  -2.45927733E-02  -3.03640551E-02  -2.92959288E-02  -8.53223974E-03  -2.05083589E-02  -3.27129094E-02  -3.63614853E-02   6.51301341E-02   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5.34338153E-03   3.86372015E-03   1.13282477E-02   2.59795740E-02   2.92846415E-02   3.16809701E-02   2.52096813E-02   3.25483714E-02   2.11196548E-02   6.15444169E-03   7.07481224E-05   6.84475611E-03   3.20751784E-02   3.94086886E-02   4.64290054E-02\nCm  -7.19944532E-04   4.80437427E-03   1.72613157E-02   2.97744690E-02   2.61066997E-02   4.30968337E-02   4.13760366E-02   8.35242982E-03   2.19818825E-02  -7.18760572E-03   3.49915013E-02   7.00987803E-04   1.08334125E-03   1.45292072E-03   2.28339058E-03   3.14151066E-03   2.28357997E-03   3.15475454E-03   4.64959565E-03   8.02059291E-03   1.66994295E-02   2.28748561E-03  -1.46788671E-02  -8.15132931E-03  -7.18142572E-02  -9.23871929E-02  -1.32555752E-01  -1.59305140E-01  -1.46387980E-01  -1.78928976E-01  -1.96585013E-01  -1.30972808E-01  -2.10241649E-01  -3.86339928E-02  -5.31173280E-02  -3.68351105E-02   2.70975524E-02   3.47937649E-02   4.97150563E-02   5.93828747E-02   5.50411700E-02   6.68131276E-02   7.22787459E-02   4.58668979E-02   6.82450236E-02   3.70523951E-02   2.14317659E-02   4.14887323E-02   6.67713820E-02   8.51377412E-02   1.19818294E-01   1.39953376E-01   1.33716534E-01   1.58134209E-01   1.61441293E-01   8.54378409E-02   1.40642234E-01   5.54422436E-02   5.62141390E-02   6.37747123E-02\nCm   5.34842011E-02   6.44297856E-02   8.89936257E-02   1.07555098E-01   9.94233472E-02   1.24261936E-01   1.30026950E-01   8.19640394E-02   6.25551073E-02   4.15044290E-02   8.18056007E-02   6.54485666E-02  -3.46861896E-02  -4.50063766E-02  -6.57868159E-02  -8.12664006E-02  -7.17005032E-02  -9.02857001E-02  -1.06113855E-01  -8.74951085E-02  -8.18906804E-02  -3.65577918E-03  -3.09489260E-02  -1.23813381E-02   7.24388379E-02   9.35765884E-02   1.35472724E-01   1.64984002E-01   1.48719446E-01   1.84455465E-01   2.09446384E-01   1.54828047E-01   1.08760468E-01   4.60715216E-02   1.02908314E-01   8.03843336E-02   7.07740316E-03   9.13029118E-03   1.31794715E-02   1.59811904E-02   1.44975044E-02   1.78965469E-02   2.01057099E-02   1.43703508E-02   2.96276968E-02   2.98843672E-02   1.28991769E-02   2.04546477E-02   1.30626843E-02   1.52642961E-02   1.78218303E-02   1.58400623E-02   1.94043845E-02   1.53323123E-02   6.68742374E-03   2.60750250E-04   9.92187777E-03   3.22611387E-02   1.05000337E-02   3.39674639E-02\nCm   9.68969858E-02   1.08811013E-01   1.27038880E-01   1.35432174E-01   1.15116757E-01   1.24661120E-01   1.66959105E-01   2.59472019E-01   6.14907281E-02   1.36127104E-01   2.64624061E-01   2.55747152E-01   7.58653991E-02   1.00189393E-01   1.52202114E-01   1.99073014E-01   1.59673587E-01   2.12300668E-01   2.83657546E-01   3.53188625E-01   2.03803596E-01   9.47321177E-02   2.75204717E-01   2.49355360E-01  -3.82210913E-02  -4.95801604E-02  -7.24315208E-02  -8.93998994E-02  -7.89778028E-02  -9.93626742E-02  -1.16549233E-01  -9.54922120E-02  -7.57647828E-02  -1.19996536E-04  -1.31828966E-02  -2.25271492E-03   3.61721475E-02   4.64611624E-02   6.64339147E-02   7.94374948E-02   7.35197502E-02   8.93518297E-02   9.69229646E-02   6.20307874E-02   7.53903424E-02   8.10454338E-02   1.00629406E-01   1.54698133E-01  -4.63054546E-02  -5.91453000E-02  -8.35523191E-02  -9.81368644E-02  -9.30757368E-02  -1.10801539E-01  -1.14781638E-01  -6.35815090E-02  -8.11300175E-02  -1.65960099E-02  -6.82263293E-02  -4.13952277E-02\nCm   1.53407741E-02   3.11534670E-02   6.14611385E-02   8.38017042E-02   7.37182998E-02   9.31250573E-02   1.10782526E-01   1.04790683E-01   3.80341485E-02   1.80026401E-02   7.04748841E-02   5.77100079E-02   3.07913818E-02   4.01777964E-02   5.94520929E-02   7.47844836E-02   6.41225391E-02   8.22425524E-02   1.00856162E-01   9.52182518E-02   8.99346779E-02   2.58993592E-02   4.65617055E-02   3.30556511E-02   3.27696516E-02   4.09294255E-02   5.50917929E-02   6.02683793E-02   6.22981711E-02   6.77745985E-02   5.77163482E-02   1.73921860E-02   4.05188210E-02   3.06027640E-02   3.84389662E-02   4.01841972E-02  -2.34408437E-02  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2.54414406E-02   6.46762281E-02   8.22649010E-02   1.15164442E-01   1.33473173E-01   1.28824144E-01   1.50923910E-01   1.50926195E-01   7.48770952E-02   1.53328516E-01   6.31187684E-02   9.43541164E-02   8.44378497E-02   3.63643222E-02   4.61057512E-02   6.40993780E-02   7.35367247E-02   7.18984757E-02   8.31856129E-02   8.09373843E-02   3.68658105E-02   7.28022600E-02   3.48363011E-02   3.70099801E-02   4.38005354E-02\nCm  -2.06534991E-02  -1.95206351E-02  -1.83906031E-02  -1.85272963E-02  -1.18189931E-02  -1.50019030E-02  -3.41017950E-02  -4.52063896E-02   1.81231177E-03  -3.98351963E-02  -2.00945921E-03  -2.86764850E-02  -6.22961134E-02  -7.98097554E-02  -1.13481634E-01  -1.34578278E-01  -1.25987873E-01  -1.51677023E-01  -1.61093578E-01  -9.64887598E-02  -1.69136751E-01  -9.87043294E-03  -1.00335047E-01  -3.02558799E-02   4.80189884E-02   6.08876246E-02   8.46654904E-02   9.71566926E-02   9.49605566E-02   1.09904474E-01   1.07011452E-01   4.88520102E-02   8.67572074E-02   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5.48128282E-02   5.51696964E-02   7.39016873E-02   1.15834548E-01   1.58734684E-01   1.16342720E-01   1.60305532E-01   2.34588878E-01   3.95010306E-01   1.12306502E-01   4.29911069E-02   1.00611952E-01   9.60632363E-02  -2.09000460E-03  -2.71720043E-03  -3.98889657E-03  -4.95892140E-03  -4.33226388E-03  -5.49116660E-03  -6.55197414E-03  -5.66793855E-03   9.75656169E-03   4.28550044E-02  -1.11886658E-02   5.34237419E-02  -3.94662006E-02  -5.03248643E-02  -7.08335295E-02  -8.27523953E-02  -7.90451466E-02  -9.35003608E-02  -9.55029697E-02  -5.06202049E-02  -7.16400968E-02  -6.17869400E-03  -6.24968252E-02  -3.69546641E-02   4.08224494E-02   5.17110745E-02   7.17511358E-02   8.20772858E-02   8.05383549E-02   9.28472865E-02   8.96307931E-02   3.98389499E-02   7.19234781E-02   3.44531418E-02   8.43925348E-02   5.25302849E-02\nCm  -6.46971452E-03  -1.91282156E-02  -6.07717845E-02  -1.16839420E-01  -8.11090992E-02  -1.58454189E-01  -2.13938334E-01  -1.50962041E-01  -7.24404339E-02  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2.01885042E-01   2.66019113E-01   3.16575513E-01   9.81430850E-02   4.87193615E-02   1.00500322E-01   7.33007617E-02\nCm   5.06788800E-03  -8.13578589E-03  -4.82516150E-02  -8.72250378E-02  -8.56314971E-02  -1.23448845E-01  -9.90320868E-02  -2.60429176E-02  -3.78171159E-02  -7.05927123E-03  -6.55878423E-02  -9.18114612E-02  -1.31581099E-02  -1.67950022E-02  -2.36900233E-02  -2.77636598E-02  -2.64096140E-02  -3.13567827E-02  -3.22951577E-02  -1.75674506E-02  -3.10052923E-02  -9.28354358E-03  -2.63814558E-02  -1.94635519E-02  -6.11029705E-02  -7.41433008E-02  -9.38004154E-02  -9.37119025E-02  -1.05716032E-01  -1.00935505E-01  -6.51984195E-02  -8.40561312E-03  -7.06037973E-02  -3.88850307E-02  -9.59354419E-02  -7.94748570E-02  -2.81362947E-02  -3.18827901E-02  -3.48768612E-02  -2.82026442E-02  -3.61843624E-02  -2.41843721E-02  -7.48603872E-03  -1.03285648E-04  -1.03420207E-02  -5.10133109E-02  -7.64731162E-02  -1.01160419E-01   8.00264117E-04   8.92573634E-04   9.44266029E-04   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6.52454492E-02   5.53476006E-02   7.99780238E-02  -4.27941221E-02  -5.26449545E-02  -6.85888062E-02  -7.15332064E-02  -7.76455172E-02  -7.90177324E-02  -5.83760652E-02  -1.13565132E-02  -6.29204652E-02  -1.40441400E-02  -1.18678412E-02  -7.24522141E-03\nCm   6.00222085E-03   1.67319795E-02   2.39437081E-02   7.30974118E-03   3.76356411E-02   1.98643859E-02  -1.84456986E-02  -2.52967594E-01  -1.00456489E-03   2.02733679E-02   6.64569249E-02   8.54602127E-02  -6.82041256E-02  -9.22210198E-02  -1.47574150E-01  -2.08594171E-01  -1.42951966E-01  -2.00658764E-01  -3.09504456E-01  -6.24862545E-01  -2.60476260E-01  -3.49483649E-02  -6.94390791E-02  -3.58208812E-02   3.16040265E-02   4.20537526E-02   6.49556260E-02   8.70853335E-02   6.66900079E-02   9.04612905E-02   1.27053330E-01   1.86428992E-01   1.36848610E-01   2.82528266E-02   8.40429715E-02   4.14406005E-02   6.07222907E-02   7.93083662E-02   1.17598886E-01   1.48383666E-01   1.26593440E-01   1.62858872E-01   2.01133517E-01   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1.62868433E-01   1.93328421E-01   1.64510153E-01   1.52152931E-01   2.72247071E-02   1.71337826E-01   9.06026054E-02   4.25365836E-03   4.84001760E-03   5.34101909E-03   4.37397602E-03   5.58242313E-03   3.81825943E-03   1.23895408E-03   1.97137656E-05   4.58551694E-03   3.37814928E-02   8.87508508E-03   5.22558630E-02  -5.49862901E-02  -6.16576953E-02  -6.59690226E-02  -5.16598569E-02  -6.70888190E-02  -4.22541960E-02  -1.15883360E-02  -1.10895842E-04  -3.86218173E-02  -5.83391352E-02  -7.45548853E-02  -6.94280497E-02\nCm   8.84613154E-03   1.62924443E-02   1.00388596E-02  -2.70866331E-02   1.19906209E-02  -3.92262841E-02  -9.75414556E-02  -2.43060658E-01  -1.97153680E-02   1.10218473E-02  -8.12037878E-03   7.08784286E-03  -3.49187372E-02  -4.68770312E-02  -7.38307367E-02  -1.01905688E-01  -7.35740466E-02  -1.01854197E-01  -1.50976223E-01  -2.65552639E-01  -1.15660272E-01  -2.41632244E-02  -9.30335486E-02  -6.20499157E-02  -2.61023383E-02  -3.42052016E-02  -5.10887382E-02  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3.04679046E-02   4.66733485E-02   6.18097450E-02   4.84565103E-02   6.50969888E-02   8.92269701E-02   1.20792737E-01   3.67049305E-02   7.88030447E-03   4.60586288E-02   2.00069302E-02   2.34965548E-02   2.99205834E-02   4.19900735E-02   4.88430288E-02   4.69204959E-02   5.52123943E-02   5.57507448E-02   2.85081489E-02   5.17741685E-02   1.92805177E-02   5.07909038E-02   3.18428701E-02   3.88011836E-02   4.79076885E-02   6.29080824E-02   6.63661539E-02   7.12389439E-02   7.37007087E-02   5.63796442E-02   1.22081474E-02   8.55027462E-02   2.32454479E-02   4.45661964E-02   2.21411508E-02  -6.11699800E-02  -7.49175521E-02  -9.66830678E-02  -9.94401128E-02  -1.09350927E-01  -1.09049076E-01  -7.71842534E-02  -1.31661577E-02  -1.11325504E-01  -1.75882308E-02  -3.68211624E-02  -2.70233088E-02\nCm  -2.34679464E-02  -2.53192703E-02  -2.17413129E-02  -2.80602118E-03  -3.19288262E-02  -1.77709502E-02   4.38640128E-02   2.44275568E-01  -8.93389553E-04  -2.79405888E-02  -4.47882358E-02  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5.28617222E-01   7.96411297E-02   4.90379782E-02   1.75398691E-01   2.49334275E-01   7.84750979E-02   1.06545005E-01   1.72056788E-01   2.46546989E-01   1.63688705E-01   2.31307521E-01   3.64332188E-01   7.92614055E-01   2.38122034E-01   8.05455800E-02   4.00731649E-01   3.14494363E-01  -4.63271009E-02  -6.11350669E-02  -9.27218051E-02  -1.20982307E-01  -9.74621760E-02  -1.29315497E-01  -1.71904420E-01  -2.10526115E-01  -1.27891724E-01  -3.78223626E-02  -6.16566698E-02  -5.88762202E-02  -3.37830915E-02  -4.34432949E-02  -6.22764485E-02  -7.47455725E-02  -6.88129654E-02  -8.39858525E-02  -9.19690461E-02  -6.06398189E-02  -5.11384921E-02  -2.71304517E-02  -1.71301772E-01  -1.32423346E-01   1.70095669E-03   2.10994698E-03   2.79836799E-03   2.99566432E-03   3.16860701E-03   3.34624663E-03   2.67428352E-03   6.62513528E-04  -2.73571715E-03   1.07012454E-02   1.93851143E-02   1.73920205E-02\nCm  -5.82688950E-03  -4.59142093E-03  -6.13296997E-03  -8.77114901E-04  -2.47145770E-02  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1.80772795E-02   1.56583519E-02   3.73550427E-02   8.14580968E-03   1.06455049E-02   1.58059449E-02   1.99824290E-02   1.69938297E-02   2.19035435E-02   2.71714448E-02   2.66143364E-02  -7.84988175E-05   1.10395915E-02   3.63784102E-02   3.30418849E-02   4.63054546E-02   5.91453000E-02   8.35523191E-02   9.81368644E-02   9.30757368E-02   1.10801539E-01   1.14781638E-01   6.35815090E-02   1.19541381E-01   3.84349296E-02   8.95333036E-02   6.93584122E-02   2.77703271E-03   3.53546399E-03   4.95913243E-03   5.76423286E-03   5.54264562E-03   6.51635432E-03   6.56702035E-03   3.33757653E-03   3.92094395E-03  -8.51184773E-04   3.36931401E-05   4.08464342E-03   5.91188158E-03   7.09605083E-03   8.77152240E-03   8.47149582E-03   9.81884681E-03   8.89484227E-03   5.14823700E-03   4.74685930E-04  -4.01143547E-03  -6.23030312E-03   1.39850870E-02   6.28163631E-03\nCm   2.49662835E-03   1.40506591E-02   4.28271491E-02   8.07113206E-02   4.20952188E-02   8.37151441E-02   1.62457629E-01   2.83302687E-01   6.98888191E-02   1.15841974E-02   3.76910385E-02   4.33984984E-02   5.85727081E-02   7.72761198E-02   1.17140235E-01   1.52722547E-01   1.23206031E-01   1.63361520E-01   2.16802206E-01   2.64076259E-01   1.20636104E-01   3.30296673E-02   1.93756865E-01   9.60282626E-02   1.42364494E-02   1.86598923E-02   2.78836174E-02   3.55883932E-02   2.97908398E-02   3.87483290E-02   4.91070612E-02   5.15224706E-02   4.23859438E-02   2.36437170E-02   2.04048193E-02   1.19364070E-02  -6.07867516E-02  -7.59285497E-02  -1.02217664E-01  -1.11848639E-01  -1.15585858E-01  -1.25786488E-01  -1.07191703E-01  -3.23689482E-02  -1.11516519E-01  -2.50339975E-02  -1.20087224E-01  -6.84180646E-02   1.51887512E-02   1.72953142E-02   1.91155574E-02   1.56901316E-02   2.00055295E-02   1.37399147E-02   4.49606663E-03   7.33867372E-05   2.04747131E-02   1.19445409E-02   6.64981250E-03   5.68535903E-03\nCm  -1.07442865E-02  -9.21637183E-03   1.59404618E-02   6.79265566E-02   2.04601054E-02   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1.35245767E-02   1.44028166E-02   1.12027571E-02   1.45826864E-02   9.06896697E-03   2.42391441E-03   2.14585662E-05   4.40378008E-03   3.68413228E-02   2.73520010E-02   4.81544197E-02\nCm   2.21240985E-02   1.89165701E-02   2.33658126E-02   3.97429649E-02   2.41713496E-02   5.88989635E-02   8.06703598E-02   3.65072930E-02   2.36508497E-02   3.27235153E-02   1.31752590E-02   6.39475630E-03   1.45311451E-02   1.84940071E-02   2.59238761E-02   3.01028738E-02   2.89826141E-02   3.40335987E-02   3.42084697E-02   1.72442399E-02   1.54078049E-02   1.69914417E-02   3.59664162E-02   3.58944941E-02  -2.27455734E-02  -2.86061730E-02  -3.90813448E-02  -4.36976183E-02  -4.40696272E-02  -4.93502849E-02  -4.47268458E-02  -1.63418709E-02  -3.02026654E-02  -2.08843985E-02  -5.29345242E-02  -4.38794384E-02   5.22132541E-02   6.55925573E-02   8.93943915E-02   9.95977729E-02   1.00861260E-01   1.12423011E-01   1.00871818E-01   3.57258369E-02   1.27876061E-01   3.03561133E-02   8.58743301E-02   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9.63524516E-02   8.91465842E-02   3.47244111E-02   5.36043949E-02   3.84932787E-02   5.89278121E-02   4.86091073E-02  -4.65917223E-02  -5.75570735E-02  -7.56646053E-02  -7.99567099E-02  -8.56863891E-02  -8.88569742E-02  -6.83154135E-02  -1.50223609E-02  -1.05192975E-01  -3.35746453E-02  -4.65346712E-02  -4.60118579E-02\nCm   9.10879642E-02   1.10571595E-01   1.41602655E-01   1.48660089E-01   1.54209220E-01   1.58896354E-01   1.37933333E-01   6.62497712E-02   1.31170423E-01   1.16421893E-01   2.85447193E-01   2.82177194E-01   2.27358785E-02   2.95134629E-02   4.31818021E-02   5.34180702E-02   4.70274972E-02   5.93046385E-02   6.99373303E-02   5.82883863E-02   5.36534953E-02   5.64712742E-02   4.86656832E-02   5.32484654E-02  -8.45164711E-03  -1.08645916E-02  -1.55627426E-02  -1.86579082E-02  -1.72041881E-02  -2.09712438E-02  -2.29000462E-02  -1.49659032E-02  -7.43152511E-03   3.20144603E-02   5.96379442E-03   4.31690971E-02  -3.61721475E-02  -4.64611624E-02  -6.64339147E-02  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5.29756319E-01   1.89624417E-01   4.91605140E-02   2.02681432E-01   1.06697591E-01  -1.42364494E-02  -1.86598923E-02  -2.78836174E-02  -3.55883932E-02  -2.97908398E-02  -3.87483290E-02  -4.91070612E-02  -5.15224706E-02  -4.43377166E-02  -2.41869281E-02  -5.50961050E-03  -2.64313559E-02  -7.47595680E-02  -9.77127290E-02  -1.45117447E-01  -1.83534146E-01  -1.55984625E-01  -2.01126497E-01  -2.49719647E-01  -2.45295741E-01  -1.71560411E-01  -6.69276406E-02  -2.18567010E-01  -1.78125953E-01  -3.13558714E-02  -3.81354949E-02  -4.84844048E-02  -4.87886045E-02  -5.47024660E-02  -5.28022198E-02  -3.48970474E-02  -4.82543726E-03  -3.69107075E-02  -7.15282783E-02  -7.30759373E-02  -1.39496889E-01\nCm   2.62463075E-02   3.82112885E-02   5.16810771E-02   4.60072871E-02   6.28970798E-02   5.14602314E-02   1.25030038E-02  -7.00668824E-02   3.20938440E-02   3.77940587E-02   1.02040920E-01   8.82204527E-02   4.75495753E-02   6.36216428E-02   9.94706952E-02   1.35798860E-01   1.00305166E-01   1.37856001E-01   2.00362501E-01   3.29673311E-01   9.44246225E-02   5.30545193E-02   1.29986521E-01   1.11543421E-01  -4.11115754E-02  -5.49799765E-02  -8.58646472E-02  -1.17030264E-01  -8.67339990E-02  -1.19068579E-01  -1.72532704E-01  -2.80996209E-01  -5.86615797E-02  -1.96754808E-02  -7.87689139E-02  -5.03840972E-02  -2.51872182E-02  -3.34529083E-02  -5.14597378E-02  -6.85719500E-02  -5.31321837E-02  -7.17317318E-02  -9.95477005E-02  -1.40386860E-01  -1.07587597E-01  -6.89942511E-03  -3.39026541E-02  -1.29861161E-02   5.80896715E-02   7.19976931E-02   9.53194796E-02   1.01774968E-01   1.07937740E-01   1.13576202E-01   9.00701900E-02   2.17888882E-02   1.38977318E-01   8.17726084E-02   7.84138877E-02   1.00515140E-01\nCm   1.38813165E-02   9.57174298E-03  -8.30144836E-03  -3.86091656E-02  -1.39854933E-02  -6.22031706E-02  -1.08154377E-01  -5.65912963E-02  -1.29231456E-02   7.70947729E-02  -9.14047434E-03   7.63627860E-02  -5.35045948E-02  -6.75299380E-02  -9.29677636E-02  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8.51034517E-02   8.96783075E-02   9.51860790E-02   7.68963133E-02   1.96932513E-02   5.40731279E-02   7.89822884E-02   9.77948044E-02   1.52763589E-01  -1.80701696E-02  -2.14803910E-02  -2.60091887E-02  -2.43743419E-02  -2.88737662E-02  -2.49224470E-02  -1.30468637E-02  -8.85919370E-04  -2.05551453E-02   1.55488362E-02  -1.75753613E-02   3.43373060E-03\nCm  -5.75457358E-02  -4.65148219E-02  -1.74069679E-02   2.28262563E-02  -2.19087104E-03   4.71454828E-02   9.12924321E-02   7.67980580E-02   2.60691790E-02  -3.77431303E-02  -2.47592110E-02  -4.15779162E-02   2.90514291E-02   3.81043707E-02   5.70256421E-02   7.29460743E-02   6.08320529E-02   7.92890118E-02   1.00986084E-01   1.07662389E-01   9.91801167E-02  -7.67811573E-03   2.54140380E-02  -5.98917023E-03  -1.80485058E-02  -2.36215019E-02  -3.51841131E-02  -4.46918047E-02  -3.77120403E-02  -4.88293582E-02  -6.12242574E-02  -6.20623389E-02  -6.73415341E-02  -3.63697623E-03  -2.71635807E-02  -1.47480474E-02   3.97945318E-02   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4.50521412E-02   5.94279613E-02   1.80060544E-01   7.33062794E-02   9.25955914E-03   4.50852106E-02   3.10777513E-02   7.10421251E-02   9.44743743E-02   1.45728582E-01   1.94987514E-01   1.49898894E-01   2.03019496E-01   2.84034198E-01   4.11425217E-01   1.69058803E-01   4.80936073E-02   6.82836317E-02   6.14830558E-02  -4.53872264E-02  -5.93198568E-02  -8.80905826E-02  -1.11395787E-01  -9.46953917E-02  -1.22084388E-01  -1.51534618E-01  -1.48705478E-01  -1.55858713E-01  -1.79247611E-02  -8.18369775E-02  -4.44206244E-02  -3.40992860E-02  -4.44003393E-02  -6.53988276E-02  -8.17062581E-02  -7.08262456E-02  -9.02253457E-02  -1.08913242E-01  -9.77705681E-02  -9.46609877E-02  -1.38570527E-02  -3.99467466E-02  -2.93711179E-02   1.00859170E-02   1.29074821E-02   1.83102821E-02   2.16394160E-02   2.03537778E-02   2.44059536E-02   2.56912845E-02   1.49642152E-02   1.31433191E-02   2.68351685E-02   3.85816729E-02   4.33780221E-02\nCm   3.77231737E-02   4.25226430E-02   4.67997973E-02   5.41428388E-02   2.18066068E-02   1.63211788E-02   6.90255252E-02   3.99694432E-01   2.66814154E-02   4.17411700E-02   9.00725532E-02   9.42752750E-02   6.87540139E-02   9.30069529E-02   1.48982525E-01   2.10904525E-01   1.44037091E-01   2.02341604E-01   3.12848880E-01   6.36978914E-01   2.35363966E-01   5.35324562E-02   1.92056045E-01   1.20081341E-01   7.67061769E-03   1.02377814E-02   1.59187539E-02   2.15549938E-02   1.61873970E-02   2.21194037E-02   3.16628159E-02   4.94979523E-02  -7.04193250E-03   4.00220519E-02   3.78748051E-02   5.93090486E-02  -7.18556964E-02  -9.43431042E-02  -1.41504834E-01  -1.81608539E-01  -1.50600018E-01  -1.96894639E-01  -2.52604612E-01  -2.75697408E-01  -2.32018939E-01  -4.21741870E-02  -1.28401864E-01  -6.82010189E-02  -1.12230936E-02  -1.42207665E-02  -1.97442303E-02  -2.26065724E-02  -2.21573274E-02  -2.55730504E-02  -2.47491137E-02  -1.10866373E-02  -2.01378383E-02  -2.23346619E-02  -6.99380796E-03  -2.05298828E-02\nCm   4.14115288E-02   5.10161026E-02   6.60371211E-02   6.04640720E-02   8.10589141E-02   5.97532248E-02   1.07528847E-02  -2.09825881E-02   3.50061761E-02   4.82868243E-02   4.75685620E-02   3.96552654E-02  -1.04949925E-02  -1.35810330E-02  -1.97359859E-02  -2.41699346E-02  -2.16067408E-02  -2.69602305E-02  -3.10335157E-02  -2.39527942E-02  -2.19068004E-02   5.16082429E-03  -1.70255398E-02  -2.55152771E-03   4.77435259E-02   5.75918731E-02   7.19481224E-02   7.05693123E-02   8.08167726E-02   7.50069349E-02   4.56627140E-02   4.91205961E-03   5.81056840E-02   4.62100531E-02   3.93972012E-02   4.55387448E-02  -5.14586495E-02  -6.15515937E-02  -7.55227548E-02  -7.21552951E-02  -8.43085014E-02  -7.50735718E-02  -4.19259016E-02  -3.46654656E-03  -5.37433081E-02  -2.38139806E-02  -5.82730243E-02  -4.16320269E-02   5.53069587E-02   6.48915654E-02   7.64206297E-02   6.87800105E-02   8.36341425E-02   6.75059276E-02   3.07645135E-02   1.37049827E-03   7.18324867E-02   5.27841245E-02   5.15241406E-02   5.26520315E-02\nCm  -3.03297000E-02  -3.79176468E-02  -4.44918601E-02  -3.97806406E-02  -4.13562161E-02  -3.23953229E-02  -3.22670256E-02  -4.59303847E-02  -4.32602014E-02  -5.38928987E-02  -2.94554532E-02  -5.65652306E-02  -2.34748999E-02  -3.08468174E-02  -4.63504335E-02  -5.96458388E-02  -4.92349482E-02  -6.45278185E-02  -8.32713283E-02  -9.26180702E-02  -4.20602935E-02  -7.69730296E-03  -6.98795519E-02  -2.38943832E-02   3.26312057E-02   4.19787862E-02   6.02292226E-02   7.23809949E-02   6.65150603E-02   8.12979596E-02   8.93129358E-02   5.94887545E-02   4.48496172E-02  -5.40753474E-03   2.24283717E-02   3.24371761E-03  -5.64130191E-02  -7.04421936E-02  -9.47647515E-02  -1.03586019E-01  -1.07168597E-01  -1.16463411E-01  -9.89495596E-02  -2.96044739E-02  -9.83681153E-02  -3.30579762E-02  -4.19444637E-02  -2.75230938E-02   3.66911444E-02   4.56765390E-02   6.10470864E-02   6.60920005E-02   6.90885689E-02   7.41068257E-02   6.12267301E-02   1.68039720E-02   4.76089925E-02   1.76339301E-02   2.50567503E-02   2.12331480E-02\nCm   2.13993358E-02   3.29078061E-02   5.53678455E-02   7.12557137E-02   6.25372635E-02   7.67256076E-02   8.85175035E-02   1.07584143E-01   4.85982546E-02   3.11667910E-02   7.29238732E-02   9.89939753E-02   3.80150109E-02   4.99247226E-02   7.49239765E-02   9.62383272E-02   7.96922392E-02   1.04269697E-01   1.34017008E-01   1.47135142E-01   6.28394730E-02   2.73233931E-02   4.04588018E-02   3.16875948E-02  -3.32851234E-02  -4.24505867E-02  -5.97729860E-02  -6.98698488E-02  -6.66905593E-02  -7.89392298E-02  -8.07490425E-02  -4.29979645E-02  -6.75879263E-02  -5.19906704E-03  -2.42973678E-02  -8.13362551E-03   4.50203153E-02   5.38759855E-02   6.61717135E-02   6.33143579E-02   7.38984258E-02   6.59587015E-02   3.70160826E-02   3.10653190E-03   7.34966558E-02   3.96656527E-02   1.24603832E-01   1.03650751E-01   3.21612173E-02   3.77377509E-02   4.44501127E-02   4.00159207E-02   4.86506571E-02   3.92852911E-02   1.79190642E-02   8.00367488E-04   1.72629119E-02   5.11034209E-02   8.47343813E-02   1.07989885E-01\nCm   2.98859801E-02   3.91155353E-02   4.92356880E-02   4.52345841E-02   5.51884200E-02   4.57688146E-02   2.34143797E-02  -6.77199227E-03   3.48369329E-02   3.57300499E-02   1.00687665E-01   9.50425141E-02  -4.41744478E-02  -5.89227021E-02  -9.14964629E-02  -1.23644763E-01  -9.32250129E-02  -1.27203802E-01  -1.81399921E-01  -2.80021974E-01  -8.97437209E-02  -1.12959462E-02  -6.39444863E-02  -2.92491937E-02   5.96766296E-02   7.89414888E-02   1.20362177E-01   1.58285105E-01   1.25709083E-01   1.67910529E-01   2.26890378E-01   2.93106896E-01   1.35007745E-01   5.65946905E-02   1.80427042E-01   1.41922380E-01  -3.29226699E-03  -4.27168054E-03  -6.24357993E-03  -7.71190338E-03  -6.80519798E-03  -8.56823552E-03  -1.00678984E-02  -8.29496993E-03  -2.11594291E-03   8.48602133E-03  -1.62591654E-02  -1.41926024E-02  -2.42156773E-02  -3.02622791E-02  -4.07823128E-02  -4.46926611E-02  -4.61090875E-02  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-2.57117358E-02  -3.22687170E-02  -3.18629471E-02  -3.62939830E-02  -3.40360656E-02  -2.11744109E-02  -2.43365311E-03  -2.32298637E-02  -1.19574864E-02  -2.90015191E-03  -4.34680255E-03\nCm   8.23557709E-02   1.08927112E-01   1.43085605E-01   1.45975077E-01   1.52603885E-01   1.50088997E-01   1.33900100E-01   6.39443436E-02   8.64890921E-02   1.46059348E-01   2.13667911E-01   2.63474322E-01  -4.10019268E-02  -5.38965344E-02  -8.10461485E-02  -1.04410910E-01  -8.60196522E-02  -1.12853389E-01  -1.45990319E-01  -1.63664666E-01  -1.00856585E-01  -5.83297073E-03  -3.00353439E-02  -1.40699287E-02   4.71512499E-02   6.18672341E-02   9.26629930E-02   1.18674608E-01   9.87655586E-02   1.28875270E-01   1.64576005E-01   1.76958423E-01   1.13253396E-01   7.29501534E-02   2.08224311E-01   1.61110013E-01   6.40320667E-02   8.10300462E-02   1.12188894E-01   1.27925946E-01   1.26022772E-01   1.44704734E-01   1.38481002E-01   5.99072537E-02   9.76816161E-02   7.98417314E-02   1.32441033E-01   1.42902800E-01  -1.30092875E-02  -1.63576935E-02  -2.23371887E-02  -2.49584731E-02  -2.51910867E-02  -2.81843889E-02  -2.54945346E-02  -9.25927436E-03  -1.63969480E-02   1.75620747E-02  -1.95943420E-04   1.07473746E-02\nCm   9.25690283E-03   4.38004125E-03   6.26978966E-03   3.14569966E-02  -1.08654384E-02   2.97957833E-02   1.16228071E-01   2.57251622E-01   4.75254237E-02   4.95788908E-02  -8.37465931E-03   9.67517209E-03   5.92862780E-03   7.98628134E-03   1.26740356E-02   1.76929835E-02   1.24662949E-02   1.73781926E-02   2.62658814E-02   4.93973151E-02   1.81116479E-02  -9.73304804E-04  -6.41775336E-04  -3.57783014E-03   7.18556964E-02   9.43431042E-02   1.41504834E-01   1.81608539E-01   1.50600018E-01   1.96894639E-01   2.52604612E-01   2.75697408E-01   2.54403838E-01   5.05290972E-02   1.28420244E-01   7.02419415E-02  -2.34965548E-02  -2.99205834E-02  -4.19900735E-02  -4.88430288E-02  -4.69204959E-02  -5.52123943E-02  -5.57507448E-02  -2.85081489E-02  -4.16651142E-02  -2.53158839E-02  -2.31434546E-02  -2.66266646E-02  -5.97776622E-02  -7.51647680E-02  -1.02644459E-01  -1.14695578E-01  -1.15757837E-01  -1.29521038E-01  -1.17176287E-01  -4.25753740E-02  -6.50871709E-02  -4.96003441E-02  -6.14031946E-02  -6.23506362E-02\nCm   2.27781856E-02   3.70481260E-02   7.51563976E-02   1.20492882E-01   7.94959900E-02   1.31582680E-01   2.19153726E-01   2.76955450E-01   7.48530833E-02   4.54713659E-03   1.56020972E-01   1.07799469E-01   5.34674073E-03   7.12108890E-03   1.10211654E-02   1.48200986E-02   1.12834636E-02   1.53399023E-02   2.16697501E-02   3.24128585E-02   7.13307330E-03   3.01905285E-02   1.93664295E-02   6.15203190E-02   3.69934165E-02   4.86007060E-02   7.29948897E-02   9.38709999E-02   7.75746691E-02   1.01608721E-01   1.30933952E-01   1.44952364E-01   5.05437431E-02   4.80074710E-02   1.13004352E-01   9.05843938E-02   5.52974932E-02   7.14272055E-02   1.03387200E-01   1.25874052E-01   1.13511558E-01   1.40745064E-01   1.59705009E-01   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7.11723772E-02   7.08033690E-02   8.04759329E-02   7.53269347E-02   3.04181837E-02   7.65738384E-02   1.88945649E-02   5.31883743E-02   3.20731449E-02\nCm  -5.73944609E-03   9.89447180E-03   4.49310677E-02   8.46482339E-02   4.99887451E-02   9.02174102E-02   1.56812966E-01   2.68767901E-01   1.00972936E-01  -5.64734944E-03   1.83400003E-02  -3.76410178E-02   6.89185771E-02   9.10717195E-02   1.38539253E-01   1.81569283E-01   1.45101700E-01   1.93258275E-01   2.59305505E-01   3.27340965E-01   1.85197654E-01   4.97451258E-02   1.26439100E-01   7.89099886E-02   3.37761537E-03   4.35689336E-03   6.28774338E-03   7.62192795E-03   6.91758906E-03   8.53642524E-03   9.58245772E-03   6.83159802E-03   2.63873826E-02   5.91609182E-03  -1.59113744E-02  -7.75709876E-03  -4.92492190E-02  -6.29290029E-02  -8.89698776E-02  -1.04625708E-01  -9.90706339E-02  -1.18105440E-01  -1.22732414E-01  -6.86567635E-02  -9.92166237E-02  -3.04660396E-02  -1.43050047E-01  -1.04744197E-01   1.27716577E-02   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6.97103112E-04   1.14489347E-02  -9.68446771E-04  -1.04457005E-02   1.02918674E-03  -7.26668416E-02  -9.28117937E-02  -1.31097836E-01  -1.53957729E-01  -1.46048185E-01  -1.73830299E-01  -1.80001077E-01  -9.95817059E-02  -1.43541907E-01  -6.20827895E-02  -1.28722885E-01  -1.01118013E-01  -6.15942085E-03  -7.83872692E-03  -1.09864971E-02  -1.27551609E-02  -1.22834592E-02  -1.44209062E-02  -1.44877786E-02  -7.29182641E-03  -1.93741535E-02  -3.38065490E-03   4.94066905E-03   9.42372771E-03\nCm  -1.21452221E-02  -1.79999034E-02  -1.68480231E-02   4.55700609E-03  -2.48931553E-02   1.35682454E-02   7.88770236E-02   1.02248185E-01   8.00991045E-03  -1.87120397E-02  -3.58577669E-02  -9.92910670E-02  -2.93724913E-02  -3.93648332E-02  -6.17681109E-02  -8.47819188E-02  -6.19309718E-02  -8.54253978E-02  -1.25376248E-01  -2.13215734E-01  -2.92326668E-02  -3.41459160E-02  -1.27452719E-01  -1.20145337E-01   6.63089073E-02   8.77856130E-02   1.34084049E-01   1.76795517E-01   1.39730221E-01   1.87047333E-01   2.54119529E-01   3.34150826E-01   1.03982277E-01   4.23172381E-02   1.26540060E-01   1.04052209E-01  -1.80031762E-02  -2.30389182E-02  -3.26803732E-02  -3.86184958E-02  -3.63288872E-02  -4.35565737E-02  -4.58389473E-02  -2.66784607E-02  -8.29014031E-03  -2.95187862E-04  -3.19536270E-02  -1.85631537E-03   6.98198815E-03   8.88663535E-03   1.24584735E-02   1.44696865E-02   1.39276268E-02   1.63588148E-02   1.64515650E-02   8.30681212E-03   1.89521987E-02   1.33858976E-02   4.31269692E-04   1.22032846E-02\nCm   3.60055723E-02   3.15213684E-02   5.92826180E-03  -4.73802590E-02   1.54451922E-02  -3.73538383E-02  -1.60955170E-01  -4.72419191E-01  -6.10989807E-02   4.41081796E-02   1.41473477E-02   3.57190977E-02  -3.85070253E-02  -5.15911717E-02  -8.08983025E-02  -1.10928300E-01  -8.11992727E-02  -1.11928683E-01  -1.63978084E-01  -2.77160775E-01  -1.56909225E-01  -2.81655399E-02  -6.01106776E-02  -3.94118711E-02  -5.25820795E-02  -6.99704386E-02  -1.08083280E-01  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1.04119394E-01   4.35189036E-03   5.76723698E-03   8.82843993E-03   1.16791235E-02   9.17420893E-03   1.23141083E-02   1.68424159E-02   2.26401160E-02   9.62477866E-03   1.88933173E-02   1.39601280E-02   1.56883089E-02   8.17775155E-03   1.06302071E-02   1.56001110E-02   1.93841728E-02   1.69477047E-02   2.14704225E-02   2.55882954E-02   2.20536824E-02   7.43682196E-03   4.31483308E-02   1.43684827E-02   4.06379307E-02   5.94619538E-02   7.44066640E-02   1.00555021E-01   1.10652622E-01   1.13639272E-01   1.24608542E-01   1.07929652E-01   3.42722362E-02   9.61964462E-02   5.61019500E-02   1.02836181E-01   8.45026744E-02  -3.30108667E-02  -3.96529339E-02  -4.90943992E-02  -4.75264818E-02  -5.49870526E-02  -4.99972677E-02  -2.91618984E-02  -2.75283138E-03  -5.02583804E-02  -7.28666651E-03  -3.04651639E-02  -1.49493038E-02\nCm  -1.53073911E-02  -1.79384473E-02  -1.66760245E-02  -1.11624793E-02  -9.61907179E-03  -7.15509286E-03  -1.34582079E-02  -1.19535840E-02   8.45138371E-04  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3.75668857E-02   9.09062737E-02   6.08348341E-02   3.71652053E-02   4.73506923E-02   6.65253810E-02   7.75098956E-02   7.42997621E-02   8.76033832E-02   8.88439148E-02   4.60529718E-02   8.70490028E-02   3.77044316E-02   7.10001571E-02   4.16907193E-02  -4.11993060E-02  -4.43393894E-02  -4.35072960E-02  -3.00675240E-02  -4.03203570E-02  -1.99323978E-02  -3.34514334E-03  -7.27559077E-06  -1.80388377E-02  -1.76628248E-02  -2.62306626E-02  -2.06519933E-02  -1.22604840E-02  -1.30347467E-02  -1.24658790E-02  -8.30208894E-03  -1.11921622E-02  -5.13426644E-03  -7.40894003E-04  -1.02261123E-06  -3.68868634E-03  -2.99746616E-03  -4.18212637E-03  -3.73500847E-03\nCm   1.06426085E-02   7.64436560E-03   5.65619830E-04  -4.53364370E-03  -7.40470913E-03  -8.80955495E-03  -5.25466421E-04   1.36684590E-02  -1.17511410E-02   2.93261720E-02   1.83205777E-02   4.63943851E-02   5.11506220E-02   6.64504358E-02   9.73902580E-02   1.20779679E-01   1.05917633E-01   1.33916309E-01   1.58871180E-01   1.34944766E-01   1.04682388E-01   1.78341328E-02   1.05538787E-01   5.32982511E-02  -5.10661389E-02  -6.61413592E-02  -9.63044155E-02  -1.18281164E-01  -1.05279170E-01  -1.31767752E-01  -1.52739371E-01  -1.20528542E-01  -5.09052113E-02  -1.55603390E-02  -3.10318622E-02  -1.99336507E-02  -1.60096276E-02  -1.90870841E-02  -2.32566319E-02  -2.19947631E-02  -2.58888192E-02  -2.26793863E-02  -1.22429617E-02  -9.12834607E-04  -1.68441747E-02  -5.08368833E-03  -1.04539285E-02  -3.97016154E-03   4.04173904E-02   4.60924460E-02   5.11062914E-02   4.21427541E-02   5.36258081E-02   3.71401702E-02   1.23629391E-02   2.12513652E-04   2.41263439E-02   2.59393348E-02   2.10009687E-02   2.29503560E-02\nCm   6.34157416E-02   7.00576585E-02   8.47680410E-02   9.34314281E-02   8.79067038E-02   1.03911529E-01   1.10611056E-01   5.62512502E-02   4.96841976E-02   1.20594860E-01   1.12340111E-01   1.64188777E-01   3.32127029E-02   4.25054732E-02   6.03017283E-02   7.12732521E-02   6.70290632E-02   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8.17222432E-02   1.30697139E-01   1.84576546E-01   1.26744659E-01   1.77826639E-01   2.73904715E-01   5.50277850E-01   1.78398730E-01   1.94736915E-02   1.42664094E-01   6.69977810E-02  -2.98035723E-02  -3.91907776E-02  -5.89798023E-02  -7.60734988E-02  -6.25446088E-02  -8.21438348E-02  -1.06538420E-01  -1.20438913E-01  -3.04100491E-02  -2.43529209E-03  -7.21465813E-02  -2.71643869E-02   1.54493235E-02   1.95596804E-02   2.71084979E-02   3.09571935E-02   3.04406953E-02   3.50186362E-02   3.36492481E-02   1.47423282E-02   3.83934936E-02  -1.05160860E-03   1.30077674E-02   3.26944386E-04  -5.88653476E-02  -7.33145011E-02  -9.80816644E-02  -1.06340081E-01  -1.10991264E-01  -1.19287845E-01  -9.89710855E-02  -2.75183133E-02  -6.09372955E-02  -5.14916284E-02  -1.03003931E-01  -8.16987055E-02\nCm  -6.43606433E-02  -6.69974872E-02  -6.85787291E-02  -6.76582053E-02  -5.45265356E-02  -6.08853676E-02  -9.05835425E-02  -1.28688816E-01  -5.86403286E-02  -8.45589099E-02  -6.02953707E-02  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1.71575370E-01   1.43486279E-01   1.86729889E-01   2.36950193E-01   2.49624942E-01   1.70514561E-01   7.18154166E-02   1.74685085E-01   1.31189523E-01  -4.10301714E-02  -5.23830843E-02  -7.39257159E-02  -8.67021120E-02  -8.23921992E-02  -9.79126004E-02  -1.01039509E-01  -5.52982571E-02  -5.62433331E-02  -2.34175823E-02  -5.92402192E-02  -4.01916384E-02  -2.37223624E-02  -3.01954145E-02  -4.23371998E-02  -4.91807867E-02  -4.73272372E-02  -5.56008580E-02  -5.59431885E-02  -2.82898755E-02  -6.28582511E-02  -4.19820639E-03  -3.41581813E-02  -1.36608578E-02  -8.79672641E-03  -1.02075076E-02  -1.17417216E-02  -1.02128314E-02  -1.26626269E-02  -9.63959274E-03  -3.89453911E-03  -1.20374402E-04  -4.86054702E-03  -3.58732655E-04  -7.17833127E-03  -1.93392105E-03\nCm   1.95038547E-02   6.05382926E-02   1.39159667E-01   2.00597956E-01   1.63936275E-01   2.06533421E-01   2.64584922E-01   4.43540284E-01   1.35477431E-01  -6.18970472E-03   3.77955092E-01   2.71914887E-01   5.10727889E-02   6.79207703E-02   1.04777057E-01   1.40209439E-01   1.07764161E-01   1.45965874E-01   2.04258485E-01   2.96086227E-01   1.52548495E-01   1.05518001E-01   2.06429696E-01   2.30949140E-01   3.89476861E-02   5.17533510E-02   7.96927361E-02   1.06356202E-01   8.21680877E-02   1.11064962E-01   1.54601106E-01   2.20220186E-01   4.84072375E-02   7.94365261E-02   8.47858771E-02   1.35421630E-01   1.50793657E-02   1.96213781E-02   2.88583272E-02   3.59754076E-02   3.12930874E-02   3.97759976E-02   4.77693955E-02   4.21879436E-02   2.81846255E-02   7.43143574E-02   3.57327316E-02   8.97133118E-02  -6.48502783E-02  -8.33980748E-02  -1.19564507E-01  -1.43526009E-01  -1.32105473E-01  -1.61261855E-01  -1.76658815E-01  -1.16622039E-01  -2.13658085E-01  -1.87855389E-02  -6.77141642E-02  -2.69055504E-02\nCm  -1.19652331E-02  -1.29558925E-02  -9.85860874E-03  -1.92182560E-03  -4.78538872E-03   5.68067604E-03   6.49460856E-03  -2.14934219E-03  -5.90234948E-03  -2.31300967E-03  -5.32323117E-03   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7.16795611E-02   5.92303413E-02   7.75847408E-02   9.99879895E-02   1.10734561E-01   1.13850358E-01   1.08714739E-02   4.46184873E-02   1.60235819E-02   1.60336534E-02   2.10073653E-02   3.13648840E-02   3.99813238E-02   3.35389555E-02   4.35718214E-02   5.50656525E-02   5.72559073E-02   4.89455272E-02   4.70692803E-02   1.55758129E-02   6.20860844E-02  -5.62095927E-02  -6.92858834E-02  -9.06543901E-02  -9.51367796E-02  -1.02648387E-01  -1.05402611E-01  -7.93597094E-02  -1.63649473E-02  -8.61496408E-02  -3.51091941E-02  -4.59389290E-02  -3.98367046E-02\nCm   2.04796104E-02   1.54429814E-02  -1.43425008E-03  -2.21558502E-02  -1.11373688E-02  -2.58129519E-02  -4.51041032E-02  -1.02574268E-01  -2.44967415E-02   3.55889661E-02   2.12124155E-04   1.94424067E-02  -6.04111048E-02  -7.88175160E-02  -1.16598399E-01  -1.46612896E-01  -1.25787562E-01  -1.61272708E-01  -1.97600367E-01  -1.86034483E-01  -1.21911112E-01  -1.99119126E-02  -4.83323829E-02  -2.23569558E-02   5.30539032E-02   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5.38858850E-02   1.44323267E-01   1.07230957E-01   2.98402309E-02   3.77548588E-02   5.22526637E-02   5.95483477E-02   5.87035123E-02   6.73576859E-02   6.43602076E-02   2.77077130E-02   3.75142911E-02   5.56388008E-02   3.29736538E-02   6.49752809E-02\nCm   1.82542429E-03  -8.07789009E-03  -3.21783234E-02  -6.14720151E-02  -3.96036964E-02  -7.50882421E-02  -9.88237641E-02  -1.63185819E-01  -3.64002209E-02  -1.95916953E-02  -1.29273929E-01  -1.72816508E-01  -5.91439362E-02  -7.89923976E-02  -1.23012328E-01  -1.66944557E-01  -1.24803761E-01  -1.70816252E-01  -2.45557306E-01  -3.89387797E-01  -1.63787114E-01  -6.51505144E-02  -2.20137933E-01  -2.01351083E-01   5.92652792E-02   7.78836635E-02   1.17051251E-01   1.50671275E-01   1.24309079E-01   1.62964530E-01   2.10436355E-01   2.34543570E-01   1.18346203E-01   4.45405664E-02   1.02983303E-01   9.36213065E-02   2.06734898E-02   2.59251935E-02   3.51988423E-02   3.89982104E-02   3.97455729E-02   4.39780240E-02   3.88402550E-02   1.30987642E-02   4.38124599E-02   4.73881088E-02   4.08628124E-02   6.93886128E-02  -6.36332789E-02  -7.84411881E-02  -1.02646234E-01  -1.07741456E-01  -1.16227410E-01  -1.19377555E-01  -8.99321160E-02  -1.85770744E-02  -7.52244412E-02  -1.11341813E-01  -1.99670564E-01  -2.86228757E-01\nCm  -4.37614550E-02  -4.25442632E-02  -4.17027946E-02  -4.18181857E-02  -2.78727493E-02  -2.12611920E-02  -5.85034785E-02  -1.87000449E-01  -5.69570941E-02  -7.47936650E-02  -4.71910644E-02  -8.18140535E-02  -4.97140454E-02  -6.60257674E-02  -1.01555786E-01  -1.35307025E-01  -1.04870195E-01  -1.41565049E-01  -1.96404088E-01  -2.76714126E-01  -2.05330333E-01  -4.62076001E-02  -1.27968427E-01  -8.16206945E-02   4.97809231E-02   6.43182986E-02   9.31502680E-02   1.13505744E-01   1.02231203E-01   1.26873588E-01   1.44261576E-01   1.07107078E-01   1.29576461E-01   4.02575432E-02   9.23439000E-02   6.61457826E-02   1.29834447E-03   1.65480543E-03   2.32685739E-03   2.71439274E-03   2.59780042E-03   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8.54577184E-02   7.42674482E-02   9.44550697E-02   1.13590237E-01   1.00751315E-01   9.22009157E-02   4.89815941E-02   4.97019898E-02   6.47947034E-02  -2.24521890E-02  -2.92045365E-02  -4.29194976E-02  -5.34428607E-02  -4.65713379E-02  -5.91266955E-02  -7.08174148E-02  -6.20074519E-02  -3.71687298E-02  -1.77498846E-02  -6.74317362E-02  -7.17447667E-02\nCm   6.57265657E-03   1.36111116E-02   3.76900232E-02   8.63929537E-02   1.45293192E-02   5.92388010E-02   1.83222659E-01   6.23207752E-01   9.62272395E-02   9.79743291E-03   2.75881883E-02  -1.26470111E-02   6.85214771E-02   9.29717808E-02   1.49925110E-01   2.14377226E-01   1.43046866E-01   2.01941574E-01   3.17073272E-01   6.81981901E-01   1.37201043E-01   4.05034610E-02   6.94274909E-02   5.13457324E-02   1.40030149E-02   1.84283977E-02   2.77826781E-02   3.59288592E-02   2.94045602E-02   3.87101432E-02   5.04915023E-02   5.81371400E-02   5.23362179E-02   2.29191655E-02   1.16876205E-02   1.92295436E-02  -1.92068142E-02  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3.26243165E-03   3.69697869E-02   1.03339517E-02   2.91287399E-02   1.69411799E-02   2.32887766E-02   2.79306832E-02   3.44651642E-02   3.32015138E-02   3.85562942E-02   3.47872451E-02   1.99659816E-02   1.79435389E-03   2.36574651E-02   1.68687747E-02   2.99542500E-02   2.57178915E-02   1.27389351E-02   1.42414562E-02   1.51404163E-02   1.17474694E-02   1.53045148E-02   9.47387980E-03   2.50838423E-03   2.15830663E-05   1.44965332E-03   9.67842239E-03   9.83973411E-03   1.00254447E-02\nCm  -2.88553769E-03  -1.23044823E-02  -4.46477987E-02  -8.42543806E-02  -6.30648871E-02  -1.08991065E-01  -1.39581685E-01  -1.26328461E-01  -5.87184249E-02   1.59811321E-02  -2.63277745E-02   3.42897740E-03   3.02184218E-02   3.94419863E-02   5.84014424E-02   7.35340413E-02   6.29515852E-02   8.08177695E-02   9.93295642E-02   9.44465288E-02   7.66057803E-02  -2.49957333E-03   6.11280299E-02   8.53735500E-03  -7.28646010E-02  -9.50209476E-02  -1.40425496E-01  -1.76306694E-01  -1.51632758E-01  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6.86122401E-02   7.13527608E-02   7.70426095E-02   6.45581337E-02   1.85078835E-02   5.55666327E-02   1.06695381E-02   6.25524286E-02   3.81690226E-02   1.09172230E-02   1.23933068E-02   1.36091038E-02   1.10659450E-02   1.41655874E-02   9.56416977E-03   3.02232794E-03   4.43895413E-05   6.32653298E-03   2.23415597E-02   1.69662097E-02   3.68993676E-02  -1.27389351E-02  -1.42414562E-02  -1.51404163E-02  -1.17474694E-02  -1.53045148E-02  -9.47387980E-03  -2.50838423E-03  -2.15830663E-05  -3.01006787E-03   6.98296966E-05  -1.00260620E-02  -5.94162672E-03\nCm   2.33947591E-02   1.87273429E-02   2.02504057E-02   3.19410085E-02   2.04686045E-02   4.20421194E-02   6.12651187E-02   4.78417620E-02   2.40543682E-02   5.04522213E-03  -1.76112992E-05  -1.51922888E-02   3.77987280E-02   4.84760491E-02   6.90849067E-02   8.22030478E-02   7.66013586E-02   9.25772444E-02   9.91739001E-02   6.10263251E-02   6.96707878E-02   1.31252649E-02   4.07353338E-02   2.11045085E-02  -2.33403615E-02  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1.33733583E-01   7.26408038E-02   9.70653623E-02   1.51316879E-01   2.05682339E-01   1.53274442E-01   2.10018193E-01   3.02802260E-01   4.84932177E-01   2.82381134E-01   4.63035130E-02   1.89790546E-01   1.13128527E-01  -6.78880729E-03  -8.90595155E-03  -1.33336680E-02  -1.70663036E-02  -1.42177870E-02  -1.85418431E-02  -2.36467850E-02  -2.53171060E-02  -2.47585253E-02   3.32142211E-02   1.00039841E-02   4.53779288E-02  -4.66074490E-02  -5.79829860E-02  -7.73848728E-02  -8.36057407E-02  -8.75892434E-02  -9.36834218E-02  -7.69298998E-02  -2.07201307E-02  -8.43807025E-02  -1.47507132E-02  -4.29316111E-02  -2.22424674E-02  -1.32073624E-02  -1.64207916E-02  -2.18864439E-02  -2.36000443E-02  -2.47750552E-02  -2.64281908E-02  -2.15786289E-02  -5.71067632E-03  -3.10028871E-02   2.49340967E-03  -3.53805932E-03   6.79559093E-03\nCm  -7.53795894E-03  -1.26264865E-02  -4.04927128E-02  -9.74326168E-02  -2.58185588E-02  -1.01444008E-01  -2.44125303E-01  -4.62177364E-01  -8.75866331E-02   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1.70091461E-01   4.13934653E-02   9.13190164E-02   3.60147482E-02   7.13439481E-02   3.65271332E-02   4.85624973E-02   7.48658851E-02   1.00086820E-01   7.70690070E-02   1.04312076E-01   1.45694745E-01   2.09877876E-01   9.97980436E-02   1.29936171E-02   7.39688212E-02   3.06325355E-02  -3.06282007E-02  -4.01903511E-02  -6.02059197E-02  -7.71253577E-02  -6.41598908E-02  -8.37387581E-02  -1.06993745E-01  -1.15244656E-01  -1.00013610E-01   3.34736662E-03  -1.97581751E-02   1.48220718E-04   2.93225308E-02   3.81058211E-02   5.58882336E-02   6.93840512E-02   6.07458686E-02   7.68875858E-02   9.14447345E-02   7.82960385E-02   7.72029020E-02   5.25246004E-03   6.54609173E-02   2.94258726E-02  -4.15118982E-02  -4.96796432E-02  -6.10234149E-02  -5.83963819E-02  -6.81514312E-02  -6.08424937E-02  -3.41604143E-02  -2.87085517E-03  -3.96270985E-02  -1.34978165E-02  -3.78308896E-02  -2.76156194E-02\nCm   4.14460958E-02   4.40689392E-02   6.15863858E-02   1.10010224E-01   2.89087843E-02   9.77015298E-02   2.67600149E-01   5.56222344E-01   1.45722162E-01   9.73854699E-02   6.94495994E-02   9.57009415E-02   3.97098746E-02   5.33145191E-02   8.39891050E-02   1.15966932E-01   8.36648706E-02   1.15849183E-01   1.71824831E-01   3.02849659E-01   1.10264890E-01   3.94688612E-02   9.50624338E-02   7.09193122E-02   4.82043497E-02   6.39827827E-02   9.82852859E-02   1.30695773E-01   1.01670372E-01   1.37035522E-01   1.89387560E-01   2.63450300E-01   1.36936791E-01   4.68815365E-02   1.79937784E-01   9.57643366E-02  -1.33084996E-04  -1.72476847E-04  -2.51462431E-04  -3.09445727E-04  -2.74621500E-04  -3.44421918E-04  -4.01109183E-04  -3.21246201E-04  -3.40105449E-03   1.76077097E-02  -9.80596060E-04   1.49630113E-02  -4.26550075E-02  -5.18252734E-02  -6.57469749E-02  -6.59509103E-02  -7.41450283E-02  -7.12282282E-02  -4.66053353E-02  -6.24979799E-03  -3.99901291E-02  -3.89584080E-02  -4.41795614E-02  -5.03288208E-02\nCm   4.91331051E-02   4.99400259E-02   3.56017973E-02  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2.77520286E-02   4.98608708E-02   8.40708373E-02   4.38073889E-02   7.95351013E-02   1.45814402E-01   3.54917497E-01   5.86743045E-02   1.23530680E-02   6.12335811E-02   2.08874117E-02   7.14960508E-02   9.58258159E-02   1.50387224E-01   2.06470580E-01   1.50743134E-01   2.07964100E-01   3.05359135E-01   5.20084794E-01   1.80129403E-01   4.34800226E-02   1.30685317E-01   8.58665244E-02  -5.82120903E-02  -7.58686658E-02  -1.11978897E-01  -1.40326576E-01  -1.21053755E-01  -1.54680452E-01  -1.88041479E-01  -1.72649977E-01  -1.58258483E-01  -1.82213388E-02  -1.01092276E-01  -4.15493027E-02   1.32073624E-02   1.64207916E-02   2.18864439E-02   2.36000443E-02   2.47750552E-02   2.64281908E-02   2.15786289E-02   5.71067632E-03   2.85104785E-02   3.90075497E-02   1.97871605E-02   4.45341755E-02   7.98516303E-03   9.78793384E-03   1.26541558E-02   1.30490414E-02   1.43151541E-02   1.43304853E-02   1.02253930E-02   1.78805536E-03   1.90519636E-02   9.31438259E-03  -6.68919149E-03  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4.54587466E-03   3.95665271E-02  -1.53797284E-03   2.91264807E-02   1.52427837E-02\nCm  -2.63030934E-02  -3.61405327E-02  -2.51673668E-02   5.50730037E-02  -8.41822654E-02  -8.56873490E-04   2.34653424E-01   1.00758216E+00   2.64742620E-02  -2.29751729E-02  -1.73430159E-01  -2.33963307E-01   8.08314046E-02   1.11124184E-01   1.84529770E-01   2.75759180E-01   1.64610302E-01   2.35858377E-01   3.92301436E-01   1.04967692E+00   4.08974351E-01   1.89536426E-02   1.66043375E-01   5.33173557E-02  -3.54585590E-02  -4.49596529E-02  -6.25129162E-02  -7.17283808E-02  -7.01161217E-02  -8.11398498E-02  -7.89818056E-02  -3.60246080E-02  -7.77251752E-02  -7.24064894E-02  -1.38269162E-01  -1.57935306E-01  -3.88333278E-02  -4.69287844E-02  -5.88545577E-02  -5.80540460E-02  -6.61831512E-02  -6.19661238E-02  -3.84209062E-02  -4.37077773E-03  -1.65762531E-02  -6.48261376E-02  -8.90044143E-02  -1.17638691E-01  -6.11814460E-02  -7.19150263E-02  -8.50205105E-02  -7.69521969E-02  -9.32503811E-02  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  },
  {
    "path": "examples/configuration-sets/input.data.Anisole",
    "content": "begin\ncomment       frame number       26\nlattice   26.9097   0.0000   0.0000\nlattice    0.0000  26.9097   0.0000\nlattice    0.0000   0.0000  26.9097\natom       0.86777766879146       4.73017440716062      23.07803416989450     C  0.00  0.00       0.01525757175204       0.02812286837187       0.00767676377891\natom       0.92344556769964       7.39422086244662      23.16431125871410     C  0.00  0.00       0.03014815390882      -0.04195881041955      -0.00042456790795\natom       0.94210594503600      20.61150684046838       6.09307292350435     C  0.00  0.00      -0.00704064954080      -0.01080150602966       0.01332323186951\natom       1.18009523263683      13.93158928309510       5.06653539712602     C  0.00  0.00       0.04997677384680       0.01353658518627       0.04138015061819\natom       1.33693232804421      18.20765303990029       5.14033073491527     C  0.00  0.00      -0.01933852067018      -0.00592515572910       0.04267725720051\natom       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  },
  {
    "path": "examples/configuration-sets/input.data.Cu2S_PBE",
    "content": "begin\ncomment source_file_name=OUTCAR_4_1\nlattice 15.415349658 0.000000000 0.000000000\nlattice 0.000000000 12.016005204 0.000000000\nlattice -6.055885795 0.000000000 12.226281044\natom 9.66279 1.04561 10.73808 S 0.0 0.0 0.107416 0.024235 -0.891279\natom -3.16184 6.79866 8.04560 S 0.0 0.0 0.066538 0.139566 0.120509\natom -0.30404 11.04333 1.97659 S 0.0 0.0 -0.953672 -0.464533 -1.796811\natom 12.83426 5.06839 4.33902 S 0.0 0.0 0.393296 -0.326470 -0.518344\natom 12.39515 0.83117 4.16637 S 0.0 0.0 -0.063080 -0.611946 0.506821\natom -0.04295 7.13059 1.93130 S 0.0 0.0 -0.643788 -0.077636 0.315228\natom -3.25380 10.86483 8.16358 S 0.0 0.0 0.302005 0.898190 -0.193786\natom 9.41762 5.14521 10.58660 S 0.0 0.0 -0.644394 -0.340890 -0.050007\natom 9.00831 1.11279 6.18474 S 0.0 0.0 0.511148 0.550276 -0.454197\natom 3.34802 6.99932 0.09625 S 0.0 0.0 0.108918 0.284724 0.514152\natom 0.30069 11.03010 5.97943 S 0.0 0.0 0.216866 -0.247468 0.308978\natom 12.12524 5.04060 0.14613 S 0.0 0.0 0.501229 -0.426423 -0.428415\natom 6.18973 0.76543 12.21862 S 0.0 0.0 0.711680 -0.222174 -0.534560\natom 0.27700 6.96838 5.89276 S 0.0 0.0 0.301012 0.404099 0.020448\natom -2.83579 11.33619 12.07566 S 0.0 0.0 -0.366454 -1.013699 0.180780\natom 9.11071 5.30752 5.88412 S 0.0 0.0 0.521382 -0.161316 1.257161\natom 3.29671 1.11468 7.49721 S 0.0 0.0 0.423783 0.469883 0.109794\natom 3.12703 6.91177 10.90503 S 0.0 0.0 -0.330671 0.236197 -0.223073\natom 6.12068 10.97358 4.59954 S 0.0 0.0 0.157883 -0.563474 0.377419\natom 6.40437 4.95096 1.33698 S 0.0 0.0 -0.271097 0.026027 -0.062192\natom 6.26122 0.72292 1.03040 S 0.0 0.0 0.479811 0.556269 0.374940\natom 6.11755 6.85613 4.84907 S 0.0 0.0 -0.163743 0.501150 0.586061\natom 3.26768 11.19922 10.85073 S 0.0 0.0 -0.977102 0.340434 0.160795\natom 3.52987 5.32717 7.24188 S 0.0 0.0 -0.660281 -0.466761 -0.537193\natom -0.16538 0.79379 9.67493 S 0.0 0.0 0.082621 0.738076 -0.305641\natom 6.38897 6.71555 8.70905 S 0.0 0.0 0.714567 0.858927 -0.006896\natom 9.21963 11.13097 2.41939 S 0.0 0.0 0.578520 0.128482 0.160710\natom 2.69797 5.15168 3.47535 S 0.0 0.0 0.444296 -0.868870 -0.367079\natom 2.57642 0.90122 3.58188 S 0.0 0.0 0.258623 0.391067 -0.413657\natom 9.93715 6.97306 2.74299 S 0.0 0.0 0.641907 0.681899 -0.621142\natom 6.98678 11.02130 8.74051 S 0.0 0.0 -0.283456 -0.455182 0.418023\natom -0.27493 5.08709 9.39966 S 0.0 0.0 -0.364478 0.475103 0.470787\natom 6.51424 2.93256 8.87090 S 0.0 0.0 0.248611 -0.532822 0.261379\natom -0.07028 9.08780 9.47600 S 0.0 0.0 0.334238 -1.001614 -0.353571\natom 3.02649 8.97677 3.38093 S 0.0 0.0 0.257971 0.378857 -0.128484\natom 9.22001 3.23692 3.10270 S 0.0 0.0 0.394135 -0.561144 -0.530672\natom 5.74428 2.95266 4.87537 S 0.0 0.0 0.504185 -0.767518 0.098132\natom 6.59397 8.58770 1.02620 S 0.0 0.0 -0.052306 0.889508 0.134244\natom 3.55928 9.31404 7.15633 S 0.0 0.0 0.007547 0.236500 0.509320\natom 2.96180 3.18689 11.02470 S 0.0 0.0 0.388499 0.335359 -0.153235\natom 0.00319 2.81986 5.84202 S 0.0 0.0 0.197651 -0.410017 -0.474082\natom 12.07390 8.62516 0.18008 S 0.0 0.0 0.955619 0.478197 -0.371759\natom 9.29009 9.21675 6.39687 S 0.0 0.0 -0.053343 -0.438911 -0.538072\natom -2.79943 3.30466 11.86546 S 0.0 0.0 0.397348 0.490476 0.572317\natom 0.22927 2.73487 1.72492 S 0.0 0.0 -0.311377 0.041312 -0.093182\natom 12.80848 9.20714 4.54446 S 0.0 0.0 -1.078226 -0.482916 -0.754490\natom 9.57560 8.83412 10.64965 S 0.0 0.0 -0.180223 0.207007 -0.965804\natom -3.02133 3.13287 7.77891 S 0.0 0.0 -0.431739 0.229304 -0.188167\natom 11.52491 2.71697 3.53948 Cu 0.0 0.0 -0.524195 0.593531 -0.018888\natom 0.94130 9.18527 2.48932 Cu 0.0 0.0 0.344344 -0.016827 -0.038025\natom -2.17737 8.90566 8.67171 Cu 0.0 0.0 -0.080113 -0.460384 -0.097485\natom 8.60937 2.99411 9.87382 Cu 0.0 0.0 0.242483 0.166370 -0.096114\natom 5.78704 0.81660 8.10398 Cu 0.0 0.0 -0.650869 0.037090 0.138420\natom 1.13645 6.89390 9.81986 Cu 0.0 0.0 -0.922068 -0.415802 0.004088\natom 3.98661 11.22749 4.05170 Cu 0.0 0.0 -0.169993 0.048173 -0.094445\natom 8.48776 5.35715 2.31898 Cu 0.0 0.0 -0.235778 -0.425782 -0.273045\natom 8.46457 1.29601 1.87017 Cu 0.0 0.0 -0.176692 0.115597 0.370769\natom 4.03103 6.96064 3.88549 Cu 0.0 0.0 0.138133 0.336666 0.141528\natom 0.94448 10.87127 10.21508 Cu 0.0 0.0 0.488695 0.336434 0.182050\natom 5.52896 4.74049 8.15135 Cu 0.0 0.0 -0.555966 -0.104080 -0.202623\natom 5.25495 2.85580 0.88760 Cu 0.0 0.0 -0.236780 0.111323 0.058556\natom 7.20832 9.00509 5.25253 Cu 0.0 0.0 -0.093050 -0.067663 0.112018\natom 4.02963 9.12378 11.29065 Cu 0.0 0.0 0.214455 -0.397161 -0.297440\natom 2.00869 2.95149 6.95641 Cu 0.0 0.0 0.242228 0.086186 0.256424\natom -3.59727 1.31298 11.56779 Cu 0.0 0.0 -0.234649 0.051811 -0.011230\natom 10.17489 7.11535 7.19747 Cu 0.0 0.0 -0.205621 -0.373986 -0.133792\natom 13.14051 10.69193 0.61472 Cu 0.0 0.0 -0.227511 0.015227 -0.013204\natom -0.15851 4.93004 5.03782 Cu 0.0 0.0 -0.407379 -0.188360 -0.079197\natom -1.03043 0.75778 5.49457 Cu 0.0 0.0 -0.614057 0.276670 -0.421905\natom 13.29870 6.86184 0.95026 Cu 0.0 0.0 0.173253 -0.290646 0.319586\natom 9.90736 11.28706 7.03112 Cu 0.0 0.0 0.528504 -0.034630 0.164799\natom -4.08827 5.25818 11.63154 Cu 0.0 0.0 0.507294 -0.050859 0.108014\natom 14.22568 1.81408 0.08656 Cu 0.0 0.0 0.571499 0.026055 -0.038863\natom -1.97034 7.15598 6.03887 Cu 0.0 0.0 -0.449980 0.314388 0.305998\natom -5.20546 10.47006 12.19513 Cu 0.0 0.0 0.395519 -0.013242 0.783300\natom 11.23565 4.47173 5.73470 Cu 0.0 0.0 -0.177903 -0.216022 0.218810\natom 11.50533 1.75385 6.16054 Cu 0.0 0.0 -0.082071 0.040075 -0.078104\natom 1.05145 7.68106 0.13325 Cu 0.0 0.0 0.678999 0.031254 -0.143904\natom -1.99506 10.44925 6.34486 Cu 0.0 0.0 0.240461 0.040601 0.140157\natom 14.46480 4.42495 0.30428 Cu 0.0 0.0 -0.397487 -0.006486 -0.227579\natom 9.50706 3.23697 7.16092 Cu 0.0 0.0 0.420873 -0.228470 -0.137433\natom 3.09422 9.25746 0.87162 Cu 0.0 0.0 0.083127 -0.013205 -0.008907\natom 0.08332 8.97416 7.15956 Cu 0.0 0.0 0.004363 -0.110554 -0.102250\natom 12.23272 2.72008 1.12254 Cu 0.0 0.0 -0.249257 0.710722 -0.108280\natom 1.15816 2.14568 11.54656 Cu 0.0 0.0 -0.411213 -0.684450 0.384207\natom 5.27209 7.82267 6.86516 Cu 0.0 0.0 0.125328 -0.256841 -0.003757\natom 8.17277 10.18657 0.27762 Cu 0.0 0.0 -0.368442 -0.181728 0.621258\natom 3.91864 4.11751 5.06655 Cu 0.0 0.0 -0.432305 0.483675 0.538896\natom 4.00310 1.50710 5.38681 Cu 0.0 0.0 -0.237210 -0.113493 -0.033558\natom 8.72038 7.58568 0.75111 Cu 0.0 0.0 -0.048667 0.004667 0.557755\natom 5.69466 10.30930 6.99982 Cu 0.0 0.0 0.082381 0.291179 -0.205718\natom 0.73141 4.83540 11.36935 Cu 0.0 0.0 -0.060464 -0.428701 -0.029908\natom -1.02582 2.77460 10.47989 Cu 0.0 0.0 -0.129362 0.072520 -0.184218\natom 7.80433 8.30190 7.77366 Cu 0.0 0.0 -0.615739 0.187191 -0.342683\natom 10.52153 9.29163 1.56932 Cu 0.0 0.0 -0.404426 0.511279 0.817259\natom 1.76042 2.96828 4.38708 Cu 0.0 0.0 0.093553 0.136826 -0.191640\natom 8.37753 0.81962 8.31150 Cu 0.0 0.0 0.131603 0.121433 0.418584\natom 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4.59107 9.25548 Cu 0.0 0.0 0.004397 0.377740 -0.175196\natom 0.44256 0.79397 7.51533 Cu 0.0 0.0 0.392843 -0.098361 0.143483\natom 5.25134 6.41678 10.66453 Cu 0.0 0.0 0.475273 -0.138365 -0.079004\natom 8.24962 11.81450 4.48984 Cu 0.0 0.0 0.215133 -0.064211 -0.350886\natom 4.18342 5.45581 1.75203 Cu 0.0 0.0 -0.080309 -0.016133 -0.219496\natom 4.01003 0.66675 1.73762 Cu 0.0 0.0 0.028881 -0.323578 0.033634\natom 8.34839 6.92699 4.24743 Cu 0.0 0.0 -0.310258 0.036970 0.397137\natom 5.48094 11.18523 10.58182 Cu 0.0 0.0 0.514304 0.188252 -0.630833\natom 1.07131 5.38871 7.37534 Cu 0.0 0.0 0.320279 0.188182 0.416405\natom 4.21301 2.62568 9.10014 Cu 0.0 0.0 -0.197230 -0.370539 -0.076098\natom 2.86651 8.26904 9.12445 Cu 0.0 0.0 0.813195 0.821609 -0.598471\natom 5.34637 9.52143 2.76224 Cu 0.0 0.0 0.183371 -0.205205 0.073164\natom 6.83808 3.46300 3.01720 Cu 0.0 0.0 0.096663 -0.107759 -0.264892\natom -1.22919 1.20692 2.84928 Cu 0.0 0.0 0.111910 0.175226 -0.288781\natom 12.57696 7.12242 3.51550 Cu 0.0 0.0 -0.080300 0.482168 0.355862\natom 9.16529 10.95579 10.07757 Cu 0.0 0.0 -0.015034 0.485749 -0.534452\natom 10.74902 4.75363 8.87895 Cu 0.0 0.0 0.538526 -0.144405 -0.516937\natom 4.19619 1.36541 11.49226 Cu 0.0 0.0 -0.380785 -0.030453 -0.004198\natom 2.45878 7.37775 6.65467 Cu 0.0 0.0 0.066074 -0.078546 0.088615\natom 5.31896 10.66606 0.43882 Cu 0.0 0.0 0.385710 -0.001102 -0.031416\natom 6.91402 4.80767 5.46184 Cu 0.0 0.0 0.125936 0.245444 -0.030834\natom 7.15034 2.69321 6.67590 Cu 0.0 0.0 -0.238705 -0.448773 0.259050\natom -0.81738 8.39491 11.50197 Cu 0.0 0.0 -0.436133 -0.344043 -0.296601\natom 2.10487 9.67028 5.38794 Cu 0.0 0.0 -0.077371 0.125704 -0.228517\natom 9.68527 3.42373 0.94518 Cu 0.0 0.0 0.175207 -0.068417 -0.088789\natom 2.62334 2.67217 1.88371 Cu 0.0 0.0 -0.048296 0.199486 -0.370291\natom 10.41720 8.36449 4.55256 Cu 0.0 0.0 0.315948 0.348300 0.091776\natom 7.21584 9.43029 10.57027 Cu 0.0 0.0 0.126790 -0.352963 0.043304\natom -0.52072 3.61443 7.80169 Cu 0.0 0.0 -0.368694 -0.497919 0.257311\natom -2.05660 1.09117 8.12167 Cu 0.0 0.0 -0.050113 -0.337128 0.262282\natom 8.62319 6.99659 9.55662 Cu 0.0 0.0 -0.012621 0.030326 0.525793\natom 11.01715 10.84050 3.79143 Cu 0.0 0.0 0.398331 -0.525816 0.304382\natom 0.75801 4.98978 2.17022 Cu 0.0 0.0 -0.010398 -0.002406 0.096091\nenergy -567.404752\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_124\nlattice 15.500587762 0.000000000 0.000000000\nlattice 0.000000000 12.082446869 0.000000000\nlattice -6.089371395 0.000000000 12.293885415\natom 9.50410 0.76802 10.45161 S 0.0 0.0 0.640875 0.266748 -0.858945\natom -3.15994 7.08941 7.80010 S 0.0 0.0 -0.365604 0.003541 0.417022\natom -0.48097 10.88463 1.58416 S 0.0 0.0 0.136805 0.509213 0.137938\natom 12.70994 4.97717 4.24055 S 0.0 0.0 0.201329 0.059868 0.266074\natom 12.64729 1.13865 4.14005 S 0.0 0.0 -0.875522 0.232730 0.574094\natom 0.25057 6.85877 1.67778 S 0.0 0.0 -0.662225 0.558296 -0.255495\natom -3.09982 11.31509 8.18143 S 0.0 0.0 -0.483827 -0.076863 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9.14403 8.20163 Cu 0.0 0.0 -0.736542 -0.170504 -0.135000\natom 8.78257 2.91894 9.94865 Cu 0.0 0.0 0.074663 0.111987 -0.087260\natom 5.44081 0.91688 8.74315 Cu 0.0 0.0 -0.180289 0.645887 -0.366148\natom 0.77289 7.30984 9.98548 Cu 0.0 0.0 -0.277405 -0.881330 0.335080\natom 3.85512 10.95899 3.91346 Cu 0.0 0.0 0.260423 0.320780 -0.193056\natom 8.53235 5.11107 2.48624 Cu 0.0 0.0 -0.058014 -0.089280 -0.050176\natom 8.43690 0.63670 1.96905 Cu 0.0 0.0 0.099391 0.927992 0.179655\natom 3.99811 6.95598 3.90500 Cu 0.0 0.0 -0.352701 -0.011541 0.050527\natom 1.18262 10.61798 10.28166 Cu 0.0 0.0 -1.094495 -0.340401 -0.726245\natom 5.10052 4.88890 8.30125 Cu 0.0 0.0 0.018158 0.149382 -0.187026\natom 5.10993 2.61008 0.77614 Cu 0.0 0.0 -0.275247 0.260318 -0.417356\natom 7.25024 8.89725 5.25590 Cu 0.0 0.0 0.639651 0.022245 0.247963\natom 4.08558 8.88878 11.36107 Cu 0.0 0.0 0.524273 0.774990 0.801272\natom 2.21835 3.02757 6.84923 Cu 0.0 0.0 -0.169081 0.275750 0.105148\natom -3.87773 0.67325 11.41533 Cu 0.0 0.0 0.251774 0.280134 0.178852\natom 9.32650 7.13585 7.16763 Cu 0.0 0.0 0.548313 -0.054311 -0.557519\natom 12.78822 11.27114 0.55769 Cu 0.0 0.0 0.294325 -0.384911 -0.009479\natom -0.88291 4.97952 5.49548 Cu 0.0 0.0 0.564377 0.282694 -0.115547\natom -0.94004 0.86817 5.17878 Cu 0.0 0.0 0.531793 -0.105153 0.480341\natom 13.50445 7.21972 0.82994 Cu 0.0 0.0 0.202768 -0.216719 0.219452\natom 10.42550 11.49942 6.83806 Cu 0.0 0.0 0.645052 -0.311437 0.297678\natom -4.02735 4.98160 11.70489 Cu 0.0 0.0 -0.046036 -0.144755 -0.350289\natom 8.20421 1.34114 12.16595 Cu 0.0 0.0 -0.136416 0.398756 0.126365\natom -1.77903 7.86620 5.88147 Cu 0.0 0.0 0.105846 -0.233096 0.554421\natom 1.66504 10.96535 0.86414 Cu 0.0 0.0 -0.184789 0.089984 -0.093283\natom 11.43269 4.94510 6.15516 Cu 0.0 0.0 0.189353 -0.287190 0.179424\natom 11.54652 1.99240 6.03084 Cu 0.0 0.0 -0.256757 -0.069354 0.081431\natom 1.32088 8.42018 0.03724 Cu 0.0 0.0 0.539276 -0.848730 0.280594\natom -2.06691 10.78843 6.10765 Cu 0.0 0.0 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0.191471 0.144924\natom 7.53328 8.64255 7.81010 Cu 0.0 0.0 -0.410488 -0.373785 0.688861\natom 10.55700 9.25204 1.89577 Cu 0.0 0.0 0.008971 -0.108409 0.159629\natom 1.92211 3.05547 4.24761 Cu 0.0 0.0 0.075546 0.396327 -0.235163\natom 8.65383 0.55413 8.23760 Cu 0.0 0.0 0.005452 0.005784 0.424360\natom -2.55086 6.53265 10.09238 Cu 0.0 0.0 -0.262719 0.202456 -0.932792\natom 0.90508 11.74169 3.78313 Cu 0.0 0.0 -0.150431 -0.455428 0.140236\natom 11.78802 5.54212 2.32963 Cu 0.0 0.0 -0.124617 0.257916 -0.409950\natom 11.61932 0.94869 2.18215 Cu 0.0 0.0 -0.353023 -0.227486 -0.564353\natom 1.05562 6.53028 3.96023 Cu 0.0 0.0 0.168913 -0.084876 0.016187\natom -1.76094 11.00618 9.97517 Cu 0.0 0.0 0.098497 0.074319 0.555086\natom 7.69498 4.65712 7.98759 Cu 0.0 0.0 -0.445991 -0.271844 0.809157\natom -4.24716 2.00227 9.25078 Cu 0.0 0.0 -0.534140 -0.083126 0.310756\natom 10.82742 8.28566 8.92735 Cu 0.0 0.0 0.289489 -0.198715 -0.063571\natom 13.45709 9.48564 2.56436 Cu 0.0 0.0 -0.094304 -0.251934 0.167616\natom -1.13919 3.60534 3.37464 Cu 0.0 0.0 -0.081470 -0.216910 -0.268008\natom 5.81252 0.87416 3.69546 Cu 0.0 0.0 0.239683 -0.389727 -0.441421\natom 6.27049 6.44284 2.73448 Cu 0.0 0.0 0.593297 -0.267458 -0.209278\natom 3.31810 11.57108 8.96326 Cu 0.0 0.0 -0.094871 0.025466 -0.063309\natom 2.93597 5.49182 9.37236 Cu 0.0 0.0 -0.352565 0.166649 0.402671\natom 1.19319 0.86485 7.88775 Cu 0.0 0.0 0.112395 -0.280213 0.120366\natom 5.26044 6.78722 10.70638 Cu 0.0 0.0 0.200201 -0.557848 -0.024562\natom 8.36755 11.16562 4.67475 Cu 0.0 0.0 0.099281 0.195008 -0.022501\natom 4.26368 5.66242 1.58437 Cu 0.0 0.0 -0.713695 -0.342037 -0.255913\natom 3.94831 0.44729 1.60572 Cu 0.0 0.0 -0.373471 0.103052 0.100319\natom 8.51632 6.74447 4.54446 Cu 0.0 0.0 -0.287029 -0.070477 0.054991\natom 5.26048 11.15558 10.54689 Cu 0.0 0.0 0.010288 0.017542 0.174574\natom 0.80269 5.77855 7.91179 Cu 0.0 0.0 0.151297 -0.299896 -0.394095\natom 3.54421 2.88108 9.06926 Cu 0.0 0.0 0.134787 -0.405971 -0.278721\natom 2.79386 8.35830 9.40614 Cu 0.0 0.0 0.421860 0.208443 -0.662631\natom 5.51876 8.95312 3.28504 Cu 0.0 0.0 -0.516486 0.374121 0.944122\natom 6.47196 3.62579 3.03481 Cu 0.0 0.0 0.034735 -0.775339 0.537677\natom 14.15939 0.56032 2.61849 Cu 0.0 0.0 0.357476 0.155425 -0.251905\natom -1.33103 6.95771 3.30479 Cu 0.0 0.0 -0.441228 -0.034632 0.201249\natom 10.69010 10.74585 9.61767 Cu 0.0 0.0 0.383109 0.887366 -0.524036\natom -4.26198 4.65909 9.05469 Cu 0.0 0.0 -0.351208 0.015277 0.243678\natom 3.51669 1.28051 11.64637 Cu 0.0 0.0 0.130873 -0.302352 -0.216671\natom 2.38974 7.46529 6.99156 Cu 0.0 0.0 0.230953 0.041896 -0.041359\natom 5.56353 10.80506 0.96796 Cu 0.0 0.0 0.626194 -0.006385 0.114088\natom 7.22734 4.74326 5.10303 Cu 0.0 0.0 -0.291754 0.209924 0.300175\natom 7.57996 2.33894 6.91905 Cu 0.0 0.0 -0.505569 0.292717 0.181547\natom -0.98774 8.57345 11.79519 Cu 0.0 0.0 0.415435 -0.079250 -0.345337\natom 0.87942 9.02397 5.07166 Cu 0.0 0.0 0.193953 0.478963 -0.291218\natom 10.35506 3.85100 0.71450 Cu 0.0 0.0 -0.005244 -0.092026 0.344046\natom 2.08530 2.27155 1.67193 Cu 0.0 0.0 0.297269 0.059745 -0.607520\natom 10.11475 8.59559 4.45899 Cu 0.0 0.0 0.065398 0.290857 0.624966\natom 7.31810 9.47289 10.77761 Cu 0.0 0.0 0.095057 0.223664 -0.700720\natom -0.61214 3.59627 7.63285 Cu 0.0 0.0 -0.066518 0.184155 0.474062\natom -1.78829 1.25111 7.75054 Cu 0.0 0.0 0.004942 -0.258494 0.392792\natom 8.71311 7.23083 9.84811 Cu 0.0 0.0 -0.373314 -0.092349 -0.144806\natom 11.63479 11.13932 4.32592 Cu 0.0 0.0 0.193398 -0.054525 -0.140596\natom 0.85282 4.69732 2.08289 Cu 0.0 0.0 -0.006659 -0.137894 -0.260756\nenergy -565.024216\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_156\nlattice 15.476500743 0.000000000 0.000000000\nlattice 0.000000000 12.063671443 0.000000000\nlattice -6.079908863 0.000000000 12.274781426\natom 9.46546 0.80147 10.59117 S 0.0 0.0 0.567680 0.746124 -0.093120\natom -3.68163 7.22230 8.34836 S 0.0 0.0 0.387695 -0.000600 -0.616679\natom -0.52248 10.99513 1.81375 S 0.0 0.0 0.529956 0.600806 0.268886\natom 12.59401 5.04757 4.12770 S 0.0 0.0 -0.893270 -0.177804 -0.208977\natom 12.90765 0.87444 4.38374 S 0.0 0.0 0.038247 -0.271884 -0.005272\natom -0.45034 7.05854 1.72671 S 0.0 0.0 0.119406 -0.479405 -0.111679\natom -3.18674 11.07152 7.99360 S 0.0 0.0 1.118232 -0.052893 -0.826535\natom 9.44056 5.00424 10.01691 S 0.0 0.0 -0.320228 0.045556 1.555971\natom 8.97165 1.08320 6.29060 S 0.0 0.0 0.273196 0.445005 -0.512019\natom -2.79343 6.69069 12.21453 S 0.0 0.0 -0.301627 1.249701 -0.133407\natom 0.44323 10.94663 6.41511 S 0.0 0.0 -0.101366 -0.267548 -0.323962\natom 12.03816 4.73106 0.09168 S 0.0 0.0 -0.474474 1.187613 -0.299392\natom 12.21250 0.97729 0.03720 S 0.0 0.0 0.187815 -0.130197 -0.977853\natom 0.15367 6.84387 6.04010 S 0.0 0.0 0.361664 -0.444143 -0.353284\natom -2.90699 11.26923 12.17921 S 0.0 0.0 0.543831 0.646016 -0.394893\natom 9.36361 5.07040 6.19915 S 0.0 0.0 0.069293 0.756133 -0.092190\natom 3.53000 1.21954 7.39901 S 0.0 0.0 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4.71253 S 0.0 0.0 -0.975836 0.509250 0.700128\natom 9.61046 9.29715 10.54329 S 0.0 0.0 -0.689819 -0.038470 0.279675\natom -3.32385 2.82722 7.63729 S 0.0 0.0 -0.481512 -0.403178 -0.397401\natom 11.85911 2.73356 3.92196 Cu 0.0 0.0 -0.479321 0.767893 -0.562323\natom 0.47693 9.02830 2.23133 Cu 0.0 0.0 0.605631 -0.267566 -0.103670\natom -2.19514 9.06196 8.75963 Cu 0.0 0.0 -0.120668 -0.075990 -0.026226\natom 8.61715 2.90429 9.93588 Cu 0.0 0.0 -0.652625 -0.157447 0.123248\natom 5.71077 1.15189 8.57530 Cu 0.0 0.0 -0.306528 -0.389515 -0.056375\natom 1.26479 6.55483 9.74342 Cu 0.0 0.0 0.008496 0.424139 -0.022828\natom 3.52146 11.10608 3.67750 Cu 0.0 0.0 0.020809 -0.597194 0.023990\natom 8.41537 4.98142 2.27163 Cu 0.0 0.0 0.235358 0.181826 0.048358\natom 8.47714 1.62571 1.63661 Cu 0.0 0.0 0.043483 -0.054413 0.120383\natom 4.23686 6.67208 3.77629 Cu 0.0 0.0 -0.192383 0.291531 -0.159868\natom 1.25660 10.66737 10.34630 Cu 0.0 0.0 -0.166772 -0.029497 -0.384436\natom 5.78458 4.84978 7.88012 Cu 0.0 0.0 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0.157264 0.197031\natom 1.02280 10.58200 0.06181 Cu 0.0 0.0 -0.218236 -0.187763 0.031161\natom 11.66814 4.65161 6.11953 Cu 0.0 0.0 -0.070981 -0.144674 0.268308\natom 11.17925 1.32646 5.84452 Cu 0.0 0.0 0.023128 -0.035360 0.242812\natom -4.61050 7.95128 11.73329 Cu 0.0 0.0 0.329658 -0.333983 0.292666\natom -1.78278 10.52749 5.82970 Cu 0.0 0.0 0.034615 -0.364520 0.129266\natom 9.00914 5.78702 12.09242 Cu 0.0 0.0 0.994671 -0.386441 -0.075135\natom 7.80736 2.39500 4.07240 Cu 0.0 0.0 0.441504 0.017547 -0.066392\natom 3.16731 9.66801 1.33663 Cu 0.0 0.0 -0.274231 -0.649275 1.020066\natom -0.04408 8.60360 7.36891 Cu 0.0 0.0 0.180492 0.364851 0.169512\natom 13.36768 3.03761 0.20609 Cu 0.0 0.0 0.978545 -0.227040 0.222372\natom 1.44044 1.67482 11.32771 Cu 0.0 0.0 -1.101495 -0.309701 0.206537\natom 5.63563 7.79884 6.93017 Cu 0.0 0.0 -0.324695 0.238419 -0.473087\natom 8.51250 10.83254 1.12027 Cu 0.0 0.0 0.488465 -0.159050 -0.471260\natom 3.85876 4.58544 5.21483 Cu 0.0 0.0 0.259699 -0.580176 -0.504002\natom 3.39975 1.76570 5.21088 Cu 0.0 0.0 0.372620 0.050830 0.105994\natom 8.50288 7.67680 0.77178 Cu 0.0 0.0 -0.034512 0.180881 -0.277722\natom 5.95585 10.44534 6.85060 Cu 0.0 0.0 -0.098091 0.113787 0.635195\natom 1.06569 4.44498 11.00679 Cu 0.0 0.0 -0.459896 -0.095633 0.239578\natom -0.92630 2.83989 10.40390 Cu 0.0 0.0 0.027126 -0.201139 -1.262686\natom 7.82589 8.89581 7.99861 Cu 0.0 0.0 -0.456813 -0.163378 0.435444\natom 10.74970 9.49448 1.89715 Cu 0.0 0.0 -0.433436 0.141223 0.371875\natom 1.52592 3.52200 4.56827 Cu 0.0 0.0 -0.045412 0.251593 -0.299799\natom 8.40968 0.71057 8.37641 Cu 0.0 0.0 0.636335 -0.600660 1.020686\natom -2.31332 6.41934 10.00683 Cu 0.0 0.0 0.079240 0.163677 -0.160208\natom 0.62963 10.68788 4.08853 Cu 0.0 0.0 -0.364721 0.569182 0.036294\natom 11.44204 5.26910 2.22302 Cu 0.0 0.0 -0.212612 0.269129 -0.552828\natom 10.56674 0.15792 1.57028 Cu 0.0 0.0 0.026637 -0.359762 0.478559\natom 1.45183 7.10351 4.02133 Cu 0.0 0.0 -0.837559 -0.613186 0.649713\natom -1.23030 10.76433 10.69782 Cu 0.0 0.0 -0.228945 0.181178 -0.141454\natom 8.19768 5.49842 8.15275 Cu 0.0 0.0 -0.067737 0.013079 -0.565414\natom 10.75518 2.03047 9.08778 Cu 0.0 0.0 -0.127089 -0.626709 0.675419\natom 10.53941 9.26580 8.47578 Cu 0.0 0.0 -0.011505 -1.144278 -0.194608\natom 13.67048 9.86424 3.27436 Cu 0.0 0.0 0.310611 0.109719 -0.309471\natom 13.87761 3.86356 2.79151 Cu 0.0 0.0 0.075938 -0.485094 -0.088543\natom 5.79025 0.85484 3.65459 Cu 0.0 0.0 0.006360 0.221598 -0.284394\natom 6.71967 7.06096 2.56724 Cu 0.0 0.0 -0.065842 -0.127556 -0.207352\natom 3.43429 11.02735 8.59249 Cu 0.0 0.0 0.069115 0.305329 0.241524\natom 3.12381 4.49821 9.26633 Cu 0.0 0.0 -0.106447 0.431844 -0.214806\natom 1.42765 0.47369 8.00013 Cu 0.0 0.0 -0.565141 -0.228125 -0.260050\natom 5.32980 6.85063 10.76243 Cu 0.0 0.0 0.217987 -0.176717 -0.224907\natom 7.82504 11.81171 4.96800 Cu 0.0 0.0 -0.410194 -0.162350 -0.300873\natom 4.06569 5.08945 1.23542 Cu 0.0 0.0 0.226147 -0.558748 0.635810\natom 3.82072 0.69367 1.61273 Cu 0.0 0.0 0.352183 -0.330605 -0.433545\natom 8.42771 6.69296 4.47460 Cu 0.0 0.0 0.689370 -0.431659 -0.180798\natom 5.46930 11.27210 10.45754 Cu 0.0 0.0 -0.131870 0.167259 -0.200839\natom 1.02843 5.27934 7.63758 Cu 0.0 0.0 -0.362658 0.007936 -0.282589\natom 2.81917 2.00618 9.27301 Cu 0.0 0.0 0.318462 0.074140 0.001576\natom 2.64013 8.64133 9.20612 Cu 0.0 0.0 0.128971 -0.137565 0.331888\natom 6.04710 9.36861 3.07892 Cu 0.0 0.0 -0.667901 0.845714 0.059480\natom 6.00274 4.27888 2.85114 Cu 0.0 0.0 -0.037020 0.057974 -0.353457\natom 12.92783 1.12272 2.04760 Cu 0.0 0.0 0.401960 0.151104 1.434726\natom 13.37407 7.13313 3.29031 Cu 0.0 0.0 0.324719 -0.201409 -0.364960\natom -4.65025 11.33050 9.53169 Cu 0.0 0.0 -0.565266 1.138113 1.042211\natom 11.04888 4.60936 8.68318 Cu 0.0 0.0 0.940677 -0.174636 -0.571331\natom 4.02365 1.31607 11.56031 Cu 0.0 0.0 -0.376401 -0.380534 -0.131713\natom 2.46413 7.30893 6.98392 Cu 0.0 0.0 -0.328069 -0.319872 0.014500\natom 6.16733 10.98807 0.73595 Cu 0.0 0.0 -0.576462 -0.180970 -0.049483\natom 7.32782 4.31071 5.82521 Cu 0.0 0.0 -0.522107 0.353251 -0.959985\natom 7.66354 2.73122 7.50603 Cu 0.0 0.0 -0.166669 0.192502 0.201686\natom -1.43250 8.41399 11.77217 Cu 0.0 0.0 0.347823 0.068297 -0.186494\natom 2.11419 9.49110 5.62346 Cu 0.0 0.0 -0.042565 0.158531 -0.223262\natom 11.03887 2.73447 1.15455 Cu 0.0 0.0 -0.117768 0.166711 0.190583\natom 2.43931 2.81590 1.89111 Cu 0.0 0.0 0.006521 0.227399 -0.415608\natom 10.21714 8.56313 4.34968 Cu 0.0 0.0 0.258534 0.100881 -0.558522\natom 7.09611 9.38395 10.57802 Cu 0.0 0.0 0.393663 0.075645 0.014443\natom -1.59050 4.06116 7.81026 Cu 0.0 0.0 0.776427 0.169641 0.044501\natom -2.15370 1.08495 8.85227 Cu 0.0 0.0 -0.251265 -0.119388 -0.127210\natom 8.67455 7.22254 10.03372 Cu 0.0 0.0 -0.079222 0.387976 -0.021438\natom 11.53372 11.21480 3.96977 Cu 0.0 0.0 -0.374950 -0.033082 -0.260344\natom 0.47515 5.15818 2.57476 Cu 0.0 0.0 0.420379 -0.030283 -0.128469\nenergy -564.447991\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_176\nlattice 15.463955202 0.000000000 0.000000000\nlattice 0.000000000 12.053892406 0.000000000\nlattice -6.074980375 0.000000000 12.264831259\natom 9.66285 1.13396 10.35953 S 0.0 0.0 0.059331 0.466949 -0.252002\natom -3.34021 7.01825 7.89525 S 0.0 0.0 0.013108 -0.377592 0.106189\natom -0.33307 11.13913 1.83530 S 0.0 0.0 0.190905 0.101275 0.012557\natom 12.84785 5.15702 4.46957 S 0.0 0.0 0.781157 -0.254804 -0.012527\natom 12.44940 1.02530 4.51863 S 0.0 0.0 -0.678636 0.645963 -0.073725\natom -0.40165 6.94989 1.45069 S 0.0 0.0 -0.414465 -0.480092 0.533069\natom -3.18688 11.35965 7.96824 S 0.0 0.0 -0.109083 -1.189397 -0.178564\natom 9.42211 5.27973 10.76485 S 0.0 0.0 0.605880 -0.929977 0.707081\natom 8.86475 1.11073 6.19884 S 0.0 0.0 -0.300114 0.358714 0.564408\natom -2.63355 7.01827 12.08403 S 0.0 0.0 -0.156676 0.110675 0.236263\natom 0.31827 11.07834 6.16183 S 0.0 0.0 0.650049 0.304402 -0.264113\natom 12.06705 4.59763 0.13430 S 0.0 0.0 0.561013 1.611998 0.192934\natom 6.16555 1.02111 12.25565 S 0.0 0.0 0.995092 -0.381545 -0.518864\natom 0.19593 6.71797 6.06409 S 0.0 0.0 -0.359264 0.580047 0.566627\natom 3.43019 11.17345 0.23481 S 0.0 0.0 0.111344 -0.466229 -0.294129\natom 9.19687 5.06887 5.95682 S 0.0 0.0 -0.620737 0.947887 0.781180\natom 3.47484 0.85546 7.27266 S 0.0 0.0 0.282027 0.027802 -0.173750\natom 2.87215 7.11764 10.74581 S 0.0 0.0 0.539568 -1.150546 0.227819\natom 6.06409 11.04047 4.64475 S 0.0 0.0 -0.287356 -0.462820 0.112927\natom 6.18876 4.82254 1.18148 S 0.0 0.0 -0.059584 0.123912 0.094320\natom 6.55072 0.49489 1.19980 S 0.0 0.0 0.005871 -0.638718 -0.327630\natom 6.08033 6.79862 4.87843 S 0.0 0.0 0.180856 0.427868 -0.190605\natom 3.22039 11.23071 11.07410 S 0.0 0.0 -0.157242 -0.068576 0.934038\natom 3.38936 5.31636 7.20173 S 0.0 0.0 0.286741 0.030167 -0.971897\natom -0.10619 0.74172 9.60268 S 0.0 0.0 -0.277689 -0.109803 0.195716\natom 6.52269 7.06115 8.74997 S 0.0 0.0 -0.115919 -0.523606 -0.077707\natom 9.76285 11.50326 2.87422 S 0.0 0.0 0.148664 -1.106461 0.225512\natom 2.61930 5.37388 3.32079 S 0.0 0.0 -0.508848 -1.036656 0.856369\natom 2.73655 0.92354 3.30746 S 0.0 0.0 -0.894922 0.076449 0.068578\natom 9.76599 7.09293 2.72245 S 0.0 0.0 -0.014380 -0.058741 -0.874402\natom 6.88827 10.87958 8.72096 S 0.0 0.0 -0.163790 0.360632 0.662780\natom -0.44794 4.85966 9.48466 S 0.0 0.0 -0.327609 0.405723 -0.339171\natom 6.74921 2.95722 9.19704 S 0.0 0.0 -1.072889 0.340169 -0.543980\natom 0.17096 8.82187 9.39851 S 0.0 0.0 -0.817903 1.399087 0.133936\natom 2.66455 8.90768 3.47826 S 0.0 0.0 0.495606 -0.094124 -0.862506\natom 9.11265 3.07417 2.86015 S 0.0 0.0 0.691561 0.179568 -1.819007\natom 5.74333 2.70158 5.06719 S 0.0 0.0 0.296495 -0.198774 0.111479\natom 6.39559 8.68544 0.97086 S 0.0 0.0 -1.158082 -0.396519 0.340664\natom 3.57873 9.52282 7.21048 S 0.0 0.0 0.230978 -0.617377 -0.746252\natom 2.70265 3.05351 10.82441 S 0.0 0.0 0.338469 0.594265 0.832617\natom 0.28441 2.65122 6.05477 S 0.0 0.0 0.185371 -0.392556 -0.207226\natom 12.07641 8.95908 0.14265 S 0.0 0.0 0.441586 -0.584793 0.196521\natom 9.22628 9.55966 6.46445 S 0.0 0.0 1.188211 -0.824610 0.517735\natom -2.91541 3.20849 11.88179 S 0.0 0.0 -0.324162 -0.287234 0.678644\natom -0.17466 2.74423 1.66850 S 0.0 0.0 -0.372012 0.572366 0.638305\natom 12.50872 8.96375 4.69524 S 0.0 0.0 1.048691 -0.373282 -0.185449\natom 9.63818 9.19569 10.62692 S 0.0 0.0 -0.332292 0.705799 -0.043748\natom -3.39740 3.10418 7.82119 S 0.0 0.0 -0.394274 0.204585 0.179593\natom 11.41337 2.93384 3.62262 Cu 0.0 0.0 -0.137120 -0.022584 -0.215086\natom 0.42729 8.98124 2.15855 Cu 0.0 0.0 0.280879 -0.322722 0.213868\natom -2.31587 9.10396 8.70111 Cu 0.0 0.0 0.410500 0.664991 -0.503630\natom 8.78767 3.43602 9.81686 Cu 0.0 0.0 0.475583 -0.513672 0.132257\natom 5.64818 1.02099 8.42292 Cu 0.0 0.0 -0.271670 -0.353939 0.232634\natom 0.84887 6.77692 9.62394 Cu 0.0 0.0 0.162007 -0.779704 0.161309\natom 3.93285 11.07174 4.04964 Cu 0.0 0.0 -0.368359 0.036225 -0.417675\natom 8.35331 5.25069 1.96185 Cu 0.0 0.0 -0.065740 -0.009721 0.471231\natom 8.61374 1.01281 1.84285 Cu 0.0 0.0 -0.075207 0.691007 0.244132\natom 3.98819 7.01520 4.08453 Cu 0.0 0.0 -0.005850 0.302379 -0.054429\natom 1.28650 10.86603 10.04236 Cu 0.0 0.0 -0.899301 -0.330313 -0.052247\natom 5.43481 4.88855 8.22503 Cu 0.0 0.0 0.047879 -0.095438 0.143025\natom 5.86648 2.54337 1.03205 Cu 0.0 0.0 -0.107581 0.836877 0.033215\natom 7.60617 9.12707 5.16278 Cu 0.0 0.0 -0.956506 -0.017016 -0.779352\natom 3.93909 8.94321 11.32906 Cu 0.0 0.0 0.417107 0.741236 0.347355\natom 2.39416 3.13520 6.97198 Cu 0.0 0.0 0.075592 -0.228780 -0.268870\natom -3.99849 0.73352 11.73475 Cu 0.0 0.0 0.130375 0.156715 -0.307785\natom 9.94564 7.32136 7.13838 Cu 0.0 0.0 -0.285083 0.184109 -0.001821\natom 13.17042 11.01284 0.57219 Cu 0.0 0.0 -0.304780 -0.047407 0.150029\natom -0.19229 4.68561 5.39542 Cu 0.0 0.0 0.034591 0.064932 0.202602\natom -1.07098 0.75128 5.41659 Cu 0.0 0.0 0.863294 0.247785 0.073945\natom 12.70449 6.72841 0.74030 Cu 0.0 0.0 0.134503 0.200290 -0.306322\natom 10.22460 11.57781 6.93779 Cu 0.0 0.0 0.435221 -0.220918 0.333122\natom -3.96122 5.23996 11.42410 Cu 0.0 0.0 0.441758 -0.037326 0.080004\natom 8.49195 1.50407 12.19042 Cu 0.0 0.0 -0.396014 -0.048724 0.028348\natom -1.90345 7.56003 6.24977 Cu 0.0 0.0 0.085702 0.293137 -0.167176\natom 1.23781 10.44263 0.16434 Cu 0.0 0.0 0.045933 -0.139459 -0.185520\natom 11.28175 4.29287 5.74789 Cu 0.0 0.0 0.051435 0.385378 0.458159\natom 11.00768 1.94337 6.22241 Cu 0.0 0.0 -0.176789 -0.526081 -0.026952\natom -5.05782 7.70470 12.16961 Cu 0.0 0.0 0.658849 0.119553 -0.125727\natom -1.80937 10.54787 6.21179 Cu 0.0 0.0 -0.659471 -0.678440 0.104255\natom 14.24151 4.22680 0.16549 Cu 0.0 0.0 0.465856 -0.238533 0.168964\natom 8.75302 2.99896 4.95124 Cu 0.0 0.0 0.249160 0.210750 0.947661\natom 3.28638 8.79262 1.24186 Cu 0.0 0.0 -0.346733 0.387165 -0.154626\natom 0.24706 8.92765 7.14449 Cu 0.0 0.0 -0.338020 0.180951 -0.109421\natom 5.10189 3.75629 10.61762 Cu 0.0 0.0 -0.473425 -0.110636 -0.590338\natom 1.05952 1.47514 11.44673 Cu 0.0 0.0 0.195146 -0.113334 -0.029193\natom 5.10503 7.84909 6.58179 Cu 0.0 0.0 -0.060244 0.529389 0.274714\natom 8.69693 9.23535 2.74652 Cu 0.0 0.0 0.198904 0.042220 0.139482\natom 4.18862 4.32075 5.08468 Cu 0.0 0.0 -0.687486 0.252557 0.046419\natom 3.56995 1.66576 5.17934 Cu 0.0 0.0 0.350572 0.113282 0.055055\natom 8.38102 7.55761 0.67249 Cu 0.0 0.0 0.221268 -0.096170 0.196745\natom 5.88457 10.48193 6.82940 Cu 0.0 0.0 -0.527455 -0.073681 -0.327656\natom 0.68402 4.12479 11.24727 Cu 0.0 0.0 0.274571 0.302013 0.432248\natom -1.12364 2.61442 10.69119 Cu 0.0 0.0 -0.406000 -0.415393 -0.376120\natom 7.54822 8.75270 7.69958 Cu 0.0 0.0 0.122682 -0.295042 0.353740\natom 10.67731 10.00740 1.48796 Cu 0.0 0.0 0.004412 0.290884 -0.025178\natom 1.83663 3.28932 4.22959 Cu 0.0 0.0 -0.080904 0.356566 -0.023366\natom 8.33507 0.56145 8.60945 Cu 0.0 0.0 0.114603 -0.021616 -0.355167\natom -2.04215 6.77389 9.82833 Cu 0.0 0.0 -0.007534 -0.717134 0.011035\natom 1.04834 11.37616 3.74608 Cu 0.0 0.0 -0.288259 0.230254 0.065589\natom 11.58793 5.79437 2.84809 Cu 0.0 0.0 -0.244081 -0.079537 -0.320782\natom 11.64504 0.70716 2.02330 Cu 0.0 0.0 -0.989841 -0.364179 0.552394\natom 1.11142 7.40922 4.23882 Cu 0.0 0.0 0.371931 0.133288 -0.489418\natom -1.88783 11.40659 10.34487 Cu 0.0 0.0 -0.096300 -0.299633 0.370507\natom 7.92534 5.01851 7.96233 Cu 0.0 0.0 0.356730 0.125769 -0.314713\natom -4.13829 2.80083 9.99982 Cu 0.0 0.0 0.131330 -0.067725 -0.257719\natom -4.32990 7.99757 9.60330 Cu 0.0 0.0 -0.389135 -0.044329 -0.182795\natom -1.56293 10.02503 3.28950 Cu 0.0 0.0 -0.163143 -0.170593 -0.024373\natom -1.30134 3.47561 3.73172 Cu 0.0 0.0 -0.100760 0.130375 -0.806868\natom 6.17439 1.10633 3.40005 Cu 0.0 0.0 0.336882 0.359130 0.398025\natom 6.37044 7.00825 2.48371 Cu 0.0 0.0 0.015742 -0.275627 0.324090\natom 3.44024 11.20972 8.87800 Cu 0.0 0.0 0.400193 -0.136619 -0.546082\natom 2.97105 4.56706 9.15608 Cu 0.0 0.0 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0.285689\natom 10.67763 11.28842 9.58969 Cu 0.0 0.0 -0.021239 -0.492052 0.293759\natom 10.65236 5.18394 8.51971 Cu 0.0 0.0 0.006797 -0.195878 0.204414\natom 4.18590 1.38357 11.39813 Cu 0.0 0.0 -0.375486 -0.017114 0.060248\natom 2.27516 7.42030 6.67243 Cu 0.0 0.0 0.523978 0.082577 0.237924\natom 7.84663 10.07741 0.39405 Cu 0.0 0.0 1.164994 1.031202 -0.529445\natom 6.81010 4.81633 5.60962 Cu 0.0 0.0 0.055794 -0.470187 0.015497\natom 7.14424 2.58987 7.06385 Cu 0.0 0.0 0.121366 0.070144 -0.525206\natom -1.45274 8.82216 11.02617 Cu 0.0 0.0 0.165812 0.240095 0.481689\natom 2.10769 9.84569 5.36999 Cu 0.0 0.0 -0.159444 -0.140440 0.752452\natom 10.47994 3.75604 1.23239 Cu 0.0 0.0 -0.380032 -0.307886 0.942959\natom 2.04626 2.36807 1.60570 Cu 0.0 0.0 0.448066 0.067754 -0.297946\natom 10.35379 8.55398 4.73610 Cu 0.0 0.0 -0.846167 -0.056089 -0.118372\natom 6.98392 9.10700 10.37288 Cu 0.0 0.0 0.323577 0.072657 -0.086433\natom -1.21280 3.26685 7.73503 Cu 0.0 0.0 0.632881 0.536764 -0.025554\natom 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-0.000427\natom 15.05717 4.96662 0.22650 Cu 0.0 0.0 -0.379133 -0.304059 0.136958\natom 9.28967 2.88898 5.08692 Cu 0.0 0.0 0.117682 0.616494 -0.306475\natom 3.16447 9.17559 1.14169 Cu 0.0 0.0 0.030456 0.037399 -0.640928\natom 0.37739 8.70188 7.70190 Cu 0.0 0.0 -0.001689 -0.201921 -0.548107\natom 5.28792 3.60439 10.55368 Cu 0.0 0.0 0.457627 -0.225015 0.531135\natom 1.03295 1.75095 11.62696 Cu 0.0 0.0 -0.173491 0.095705 -0.022558\natom 4.60570 7.55834 6.86272 Cu 0.0 0.0 0.674104 0.042332 -0.067677\natom 8.25251 10.54132 0.76591 Cu 0.0 0.0 0.114499 -0.291107 0.149544\natom 4.46596 4.18082 5.48738 Cu 0.0 0.0 -0.557451 -0.253554 0.050618\natom 3.58863 1.51455 5.07176 Cu 0.0 0.0 0.718783 0.669856 0.870525\natom 8.40039 7.59253 0.80712 Cu 0.0 0.0 0.343056 -0.036320 -0.525589\natom 5.48965 10.34826 6.97892 Cu 0.0 0.0 0.024921 -0.042790 0.317892\natom 0.80000 4.87994 11.68969 Cu 0.0 0.0 0.246354 -0.347015 0.236503\natom -1.18845 2.71278 10.31996 Cu 0.0 0.0 -0.104547 0.273178 0.306075\natom 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3.84134 Cu 0.0 0.0 -0.210706 0.227822 -0.550197\natom 5.58912 1.00407 3.49382 Cu 0.0 0.0 0.373138 0.265093 0.159110\natom 6.57741 7.14653 2.56683 Cu 0.0 0.0 -0.417628 -0.291723 0.407608\natom 3.58870 10.89339 8.71247 Cu 0.0 0.0 -0.305316 0.000667 0.350551\natom 3.42368 4.98435 9.96699 Cu 0.0 0.0 -0.255185 1.082788 -0.716166\natom 1.28762 0.71788 7.99947 Cu 0.0 0.0 0.405352 -0.190991 -0.277226\natom 5.85996 6.34795 10.61468 Cu 0.0 0.0 -0.073768 -0.028163 -0.035427\natom 8.15201 11.55962 4.48578 Cu 0.0 0.0 -0.644758 -0.427102 -0.395821\natom 3.57494 4.73989 1.23786 Cu 0.0 0.0 -0.051561 0.396326 0.465236\natom 3.80726 0.43646 1.82202 Cu 0.0 0.0 -0.125559 0.146887 -0.029206\natom 8.40548 6.57428 4.21744 Cu 0.0 0.0 0.033844 0.295766 0.253862\natom 5.44343 11.21633 10.68925 Cu 0.0 0.0 0.092219 0.324847 -0.419697\natom 1.28907 5.09385 8.21174 Cu 0.0 0.0 0.381162 0.156476 0.140724\natom 3.34804 2.44109 9.26473 Cu 0.0 0.0 -0.277518 -0.018140 -0.412823\natom 2.59851 8.50015 8.96715 Cu 0.0 0.0 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Cu 0.0 0.0 -0.639656 -0.502632 0.278945\natom 11.25623 4.59140 6.17465 Cu 0.0 0.0 -0.167411 -0.323254 -0.088040\natom 10.74056 2.00309 7.23737 Cu 0.0 0.0 0.280785 0.289572 -0.082256\natom -5.03746 8.11584 12.01208 Cu 0.0 0.0 0.382434 -0.449550 0.445620\natom -1.94857 10.87638 5.61594 Cu 0.0 0.0 -0.285999 -0.126621 0.554910\natom 14.45612 4.56956 0.00791 Cu 0.0 0.0 -0.114656 -0.112373 0.378247\natom 9.32861 2.94473 5.03697 Cu 0.0 0.0 0.104405 -0.208697 0.101586\natom 3.08177 8.78775 1.26265 Cu 0.0 0.0 0.100098 -0.033736 -0.066842\natom 1.26045 9.79223 7.72958 Cu 0.0 0.0 -0.106339 -0.101528 0.011347\natom 6.12331 2.90073 11.91474 Cu 0.0 0.0 0.156307 -1.352597 -0.162173\natom 1.12871 1.68462 11.50637 Cu 0.0 0.0 0.069475 0.126589 -0.086201\natom 5.05905 7.48840 7.06112 Cu 0.0 0.0 0.463196 -0.016689 0.081990\natom 8.40755 10.03140 0.85379 Cu 0.0 0.0 -0.103302 0.414453 0.198273\natom 4.19600 4.03461 5.11551 Cu 0.0 0.0 -0.219619 0.038422 -0.014174\natom 3.56644 1.49862 5.41080 Cu 0.0 0.0 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0.166547 0.114091\natom 8.15390 0.99127 2.14780 Cu 0.0 0.0 0.958431 0.061715 0.550308\natom 3.91171 7.05858 3.94693 Cu 0.0 0.0 -0.593287 0.563440 -0.613666\natom 0.84233 10.68690 10.18157 Cu 0.0 0.0 -0.773124 -0.301789 -0.002082\natom 5.26278 5.03082 8.28175 Cu 0.0 0.0 -0.024658 -0.048603 -0.221183\natom 5.33385 2.97441 0.32510 Cu 0.0 0.0 -0.155059 -0.606661 0.350608\natom 7.13637 8.74433 5.23109 Cu 0.0 0.0 0.107513 -0.007236 -0.941867\natom 3.93104 9.28260 11.30744 Cu 0.0 0.0 -0.054279 -0.082426 0.425705\natom 2.29236 3.05478 6.94063 Cu 0.0 0.0 -0.355398 -0.670930 0.250804\natom -3.96522 1.12788 11.00629 Cu 0.0 0.0 0.143495 -0.065307 0.184808\natom 10.09341 6.98320 7.41685 Cu 0.0 0.0 0.067943 0.412064 -0.481542\natom 12.67090 11.08148 1.08576 Cu 0.0 0.0 0.318328 -0.218203 0.548704\natom -0.89798 4.49077 5.28438 Cu 0.0 0.0 0.084834 0.085855 -0.071555\natom -0.90652 0.60283 5.76942 Cu 0.0 0.0 0.174943 0.118883 0.025746\natom 13.18747 7.17871 0.89452 Cu 0.0 0.0 0.030141 0.238899 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0.080560\natom 1.53664 1.72721 10.84714 Cu 0.0 0.0 0.078035 0.319768 0.369381\natom 5.22050 7.88927 6.76847 Cu 0.0 0.0 0.157444 -0.671022 0.412933\natom 7.93323 10.54466 0.49770 Cu 0.0 0.0 -0.244667 -0.368220 0.493466\natom 3.97707 4.00516 5.37104 Cu 0.0 0.0 0.487677 0.064783 -0.114850\natom 4.14569 1.27047 5.44463 Cu 0.0 0.0 -0.229985 0.329857 0.509785\natom 8.60070 7.74534 1.20477 Cu 0.0 0.0 -0.222494 0.078646 -0.059131\natom 5.46247 10.32666 6.77296 Cu 0.0 0.0 0.389763 0.678031 -0.028391\natom 0.77818 4.14352 11.07585 Cu 0.0 0.0 0.710249 0.091945 0.042840\natom -2.03971 3.57901 10.07552 Cu 0.0 0.0 0.056195 0.174251 -0.306246\natom 7.52477 8.84811 7.52561 Cu 0.0 0.0 0.373785 0.022630 1.049059\natom 11.79066 8.56243 2.69914 Cu 0.0 0.0 -0.657496 -0.036112 -1.212240\natom 1.59296 3.78609 4.53421 Cu 0.0 0.0 -0.286303 -0.685100 0.139181\natom 8.25121 0.15969 8.21043 Cu 0.0 0.0 0.160832 0.013432 0.192410\natom -1.93085 6.46651 10.05052 Cu 0.0 0.0 -0.138020 0.117795 0.259108\natom 0.97360 11.41610 4.28596 Cu 0.0 0.0 -0.014056 0.185524 -0.862979\natom 11.52553 5.30790 2.37743 Cu 0.0 0.0 0.256471 -0.144463 -0.603064\natom 10.80790 1.09153 1.89892 Cu 0.0 0.0 -0.019321 -0.076711 -0.383196\natom 1.68183 6.23307 4.42374 Cu 0.0 0.0 -0.243586 -0.011855 -0.120223\natom -1.87128 11.76502 10.68888 Cu 0.0 0.0 0.640043 0.083334 -0.446739\natom 8.13397 5.56651 7.93130 Cu 0.0 0.0 -0.423619 -0.428718 0.100977\natom 10.70794 2.25357 8.76261 Cu 0.0 0.0 -0.106956 -0.013716 0.335948\natom -4.41206 8.17752 9.67390 Cu 0.0 0.0 0.276208 -0.387555 -0.430613\natom 13.70504 10.01305 3.31585 Cu 0.0 0.0 0.414771 -0.249604 0.255288\natom 13.73304 3.64037 2.85404 Cu 0.0 0.0 0.522658 0.415626 0.040275\natom 5.76760 1.00746 3.47078 Cu 0.0 0.0 0.333859 0.012078 -0.235374\natom 6.42130 7.39571 2.73410 Cu 0.0 0.0 -0.101190 -0.329321 0.487881\natom 2.99229 10.70748 8.85769 Cu 0.0 0.0 0.419757 -0.095925 -0.435644\natom 2.73717 4.95425 9.59201 Cu 0.0 0.0 0.270206 0.564614 -0.638823\natom 1.04479 0.70311 7.56489 Cu 0.0 0.0 0.014249 -0.174170 0.522684\natom 5.18317 6.36625 10.81283 Cu 0.0 0.0 -0.214810 0.260237 -0.537882\natom 8.69784 11.48037 4.50091 Cu 0.0 0.0 -0.193064 0.047017 0.095723\natom 4.58416 5.89450 1.63141 Cu 0.0 0.0 0.216909 -0.279348 -0.126868\natom 3.94569 0.45096 1.80470 Cu 0.0 0.0 -0.175552 0.322117 0.465767\natom 8.59222 6.62006 4.36053 Cu 0.0 0.0 -0.611487 -0.169427 0.672643\natom 5.64553 11.26185 10.87209 Cu 0.0 0.0 -0.033775 -0.032469 -0.404609\natom -0.13634 6.06048 7.39439 Cu 0.0 0.0 0.064881 -0.903679 0.515902\natom 4.10068 2.75920 9.20853 Cu 0.0 0.0 0.036713 -0.301824 -0.543378\natom 3.48420 8.04223 9.23234 Cu 0.0 0.0 0.009075 0.452588 -0.974432\natom 7.14713 9.74242 2.84920 Cu 0.0 0.0 -0.155895 0.318316 -0.030286\natom 6.28278 3.48344 2.53849 Cu 0.0 0.0 0.043173 -0.336382 1.182775\natom 13.43777 1.25970 2.26051 Cu 0.0 0.0 0.139460 -0.110830 0.013725\natom -1.24232 7.32609 3.51738 Cu 0.0 0.0 -0.581870 0.403351 0.776642\natom -4.16418 10.72484 9.71795 Cu 0.0 0.0 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0.647005\natom 8.59603 7.42789 9.53548 Cu 0.0 0.0 0.020664 -0.039652 0.515946\natom 11.47735 11.01270 3.98370 Cu 0.0 0.0 0.149182 0.373105 0.088168\natom 0.76510 5.08065 2.09778 Cu 0.0 0.0 0.194502 -0.574828 0.146530\nenergy -564.634729\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_244\nlattice 15.460130590 0.000000000 0.000000000\nlattice 0.000000000 12.050911186 0.000000000\nlattice -6.073477885 0.000000000 12.261797868\natom 9.64730 1.07210 10.29220 S 0.0 0.0 -0.303783 0.377034 -1.261417\natom -3.46410 6.99556 7.96533 S 0.0 0.0 -0.737118 0.114454 -0.618454\natom -0.32875 11.07441 1.78785 S 0.0 0.0 -0.146763 -0.332146 0.493005\natom 12.93460 4.71315 3.91933 S 0.0 0.0 0.082427 0.456456 0.115908\natom 12.40424 0.86664 4.74317 S 0.0 0.0 0.701237 -0.129904 -0.730142\natom -0.19854 6.90001 1.77518 S 0.0 0.0 -0.241392 0.247904 0.273040\natom -2.92590 11.06031 8.00658 S 0.0 0.0 -0.614617 0.688615 -0.436951\natom 9.50389 5.27072 10.51943 S 0.0 0.0 0.733981 0.320167 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8.93106 3.20666 9.82593 Cu 0.0 0.0 0.404059 -0.185715 0.193175\natom 5.12718 1.79422 8.76416 Cu 0.0 0.0 -0.422465 0.093702 -0.268297\natom 1.30696 6.26391 10.18407 Cu 0.0 0.0 -0.167872 0.343777 -0.233509\natom 4.03629 11.51454 3.75582 Cu 0.0 0.0 -0.137338 -0.040704 0.250584\natom 9.18086 4.76922 2.37441 Cu 0.0 0.0 -0.067050 1.103550 -0.022953\natom 8.29622 0.98682 2.26938 Cu 0.0 0.0 0.505105 -0.168897 0.305891\natom 3.88133 6.99392 3.85049 Cu 0.0 0.0 0.288115 0.215939 0.328325\natom 0.86706 10.47234 9.90275 Cu 0.0 0.0 -0.186088 0.318505 0.289278\natom 5.46284 4.97312 7.94552 Cu 0.0 0.0 0.306231 -0.160823 0.165998\natom 5.38224 2.99876 0.85174 Cu 0.0 0.0 -0.493339 -0.304152 0.675844\natom 7.21309 9.02643 5.13983 Cu 0.0 0.0 -0.119787 -0.262287 0.078496\natom 3.74731 9.23009 11.19808 Cu 0.0 0.0 0.323234 0.842037 -0.043862\natom 2.29510 3.27554 7.11924 Cu 0.0 0.0 -0.301989 0.637721 0.344864\natom -4.06216 0.44209 11.30966 Cu 0.0 0.0 0.765533 -0.227914 0.278824\natom 10.34169 6.83885 6.30428 Cu 0.0 0.0 -0.322831 0.139102 0.206135\natom 8.02163 10.08801 12.23225 Cu 0.0 0.0 -0.222858 0.131274 0.256342\natom -0.56212 5.14775 5.32292 Cu 0.0 0.0 -0.076425 -0.606583 0.030943\natom -0.80989 0.93651 5.32614 Cu 0.0 0.0 -0.238610 0.307378 0.097839\natom 13.22050 6.98149 0.64487 Cu 0.0 0.0 0.169634 -0.132976 -0.014427\natom 10.68960 10.99004 6.55602 Cu 0.0 0.0 -0.031273 -0.115594 0.335940\natom -3.98489 5.49480 11.84622 Cu 0.0 0.0 -0.086968 -0.378460 -0.357526\natom 8.50023 0.72367 12.08366 Cu 0.0 0.0 -0.557422 0.104888 0.767138\natom -2.28814 7.03102 6.10286 Cu 0.0 0.0 0.247534 0.091236 -0.365017\natom 1.18362 10.23521 0.06025 Cu 0.0 0.0 -0.211480 0.405759 0.032660\natom 12.41333 4.38140 6.00365 Cu 0.0 0.0 -0.256548 -0.029173 0.576026\natom 11.51756 1.83507 6.64050 Cu 0.0 0.0 -0.221897 -0.172319 -0.401036\natom -4.27596 7.93845 11.17010 Cu 0.0 0.0 -0.066611 0.205050 0.002508\natom -2.00185 10.57175 5.51422 Cu 0.0 0.0 0.265903 -0.184834 0.472879\natom 14.56384 4.46179 0.08498 Cu 0.0 0.0 -0.076981 -0.184061 0.460070\natom 9.29155 2.94824 6.05561 Cu 0.0 0.0 0.356971 -0.083707 -0.140828\natom 2.79320 8.86419 1.18304 Cu 0.0 0.0 0.402123 0.043113 0.408780\natom 0.71620 9.62470 7.49043 Cu 0.0 0.0 -0.026539 -0.009460 -0.138752\natom 6.67586 3.02149 11.33699 Cu 0.0 0.0 -0.187888 -0.450268 -0.364371\natom 1.35323 2.05907 12.05236 Cu 0.0 0.0 -0.289119 -0.302741 -0.339240\natom 4.97791 7.50315 6.52953 Cu 0.0 0.0 0.236291 -0.531066 -0.158393\natom 8.66633 10.67540 0.88180 Cu 0.0 0.0 -0.009262 -0.265512 0.181465\natom 3.88832 4.68600 5.21390 Cu 0.0 0.0 0.190584 -0.315626 0.305439\natom 3.59371 1.95851 5.58261 Cu 0.0 0.0 0.415568 -0.230631 -1.048671\natom 8.69567 7.62597 0.52674 Cu 0.0 0.0 -0.222160 -0.053461 0.049758\natom 5.55294 9.85689 6.89807 Cu 0.0 0.0 0.412270 0.909727 0.119868\natom 0.54967 4.55307 11.71433 Cu 0.0 0.0 0.104313 0.066133 -0.114549\natom -1.42787 2.58175 10.69710 Cu 0.0 0.0 0.124508 -0.017162 0.078447\natom 7.63841 8.49022 7.73689 Cu 0.0 0.0 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-0.206668 -0.161333\natom 5.76208 1.51146 3.30331 Cu 0.0 0.0 -0.162984 -0.911707 -0.535959\natom 6.19559 7.03121 2.48106 Cu 0.0 0.0 -0.110884 0.557633 -0.458419\natom 4.18661 11.38083 9.40044 Cu 0.0 0.0 0.448134 -0.026982 -0.394941\natom 3.26999 4.67781 9.52538 Cu 0.0 0.0 -0.012990 0.162557 -0.163104\natom 0.66417 0.74542 7.76543 Cu 0.0 0.0 0.303785 -0.122071 -0.628350\natom 5.59656 6.47554 10.80731 Cu 0.0 0.0 -0.179429 0.017325 0.173138\natom 7.71285 0.34387 4.91439 Cu 0.0 0.0 -0.164157 0.070422 -0.188627\natom 4.21367 5.37222 1.39589 Cu 0.0 0.0 -0.428677 0.059481 0.126895\natom 3.90154 0.70692 1.51783 Cu 0.0 0.0 0.030748 0.122797 0.044549\natom 8.45738 6.46255 4.36958 Cu 0.0 0.0 0.386327 0.093554 -0.442003\natom 6.11205 0.37183 10.53471 Cu 0.0 0.0 0.478328 -0.061979 0.572865\natom -0.05709 6.10731 7.78044 Cu 0.0 0.0 0.219605 0.212783 -0.312550\natom 2.61689 2.28186 9.55132 Cu 0.0 0.0 -0.021512 -0.042919 -0.526703\natom 2.23260 8.30133 9.01334 Cu 0.0 0.0 0.198318 0.325063 -0.124887\natom 5.86688 9.56649 3.14262 Cu 0.0 0.0 -0.065061 0.131836 -0.551547\natom 7.25690 3.36116 3.14582 Cu 0.0 0.0 -0.011123 0.449408 0.143481\natom 13.94918 0.75037 2.82362 Cu 0.0 0.0 -0.191972 0.112782 0.135722\natom 13.52029 7.17132 3.33495 Cu 0.0 0.0 0.396371 -0.196837 -0.389273\natom -4.60781 10.42544 9.41729 Cu 0.0 0.0 0.379390 0.534571 -0.131199\natom 10.95215 4.93405 8.71385 Cu 0.0 0.0 0.046524 -0.177882 0.268881\natom 3.70882 1.18234 11.44669 Cu 0.0 0.0 0.478668 -0.145618 0.317542\natom 2.19800 7.16113 6.60811 Cu 0.0 0.0 -0.049952 0.386545 0.019818\natom 5.46788 10.89348 0.69516 Cu 0.0 0.0 0.595939 -0.967020 0.053046\natom 6.75504 4.92581 5.44408 Cu 0.0 0.0 -0.471192 -0.558760 0.004329\natom 6.94719 2.59723 6.99465 Cu 0.0 0.0 -0.363036 -0.065506 -0.441084\natom -0.53772 8.58625 11.57564 Cu 0.0 0.0 -0.154595 0.005370 -0.389952\natom 2.35242 9.91666 5.38753 Cu 0.0 0.0 -0.228784 -0.075660 0.021979\natom 10.53701 3.13823 0.79965 Cu 0.0 0.0 0.142064 0.159419 0.102862\natom 1.83115 2.12383 1.32680 Cu 0.0 0.0 -0.000513 0.388412 -0.178296\natom 9.86276 8.58750 4.23015 Cu 0.0 0.0 0.165429 -0.374009 -0.582075\natom 6.25401 9.81429 10.35848 Cu 0.0 0.0 -0.003169 0.438295 -0.463030\natom -0.40899 3.57584 8.13020 Cu 0.0 0.0 -0.226630 0.007697 -0.035426\natom -2.25922 1.24340 8.59967 Cu 0.0 0.0 0.330032 -0.533475 0.117152\natom 8.29838 7.22805 10.20971 Cu 0.0 0.0 -0.136638 0.131888 -0.118130\natom 11.70801 10.87039 3.90521 Cu 0.0 0.0 -0.649110 0.460998 -0.133177\natom 0.41048 4.73426 2.30406 Cu 0.0 0.0 0.156004 0.016041 -0.078820\nenergy -565.036508\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_261\nlattice 15.415026976 0.000000000 0.000000000\nlattice 0.000000000 12.015753678 0.000000000\nlattice -6.055759030 0.000000000 12.226025117\natom 9.33391 0.91596 10.48946 S 0.0 0.0 0.786740 0.127686 -0.436092\natom -3.43521 6.99419 7.88172 S 0.0 0.0 0.345123 -0.297495 1.207748\natom -0.16959 10.98461 1.99420 S 0.0 0.0 0.436167 -0.190197 0.450593\natom 12.53471 5.04393 4.21097 S 0.0 0.0 0.357452 0.645377 -0.200419\natom 12.58297 0.96977 4.35115 S 0.0 0.0 0.075600 -0.644780 -0.230116\natom -0.00529 7.03627 1.73847 S 0.0 0.0 0.033074 0.895063 -0.127887\natom -3.12188 10.91845 7.72695 S 0.0 0.0 -0.393429 0.172242 0.835254\natom 9.52759 4.99760 10.43209 S 0.0 0.0 -0.000484 0.419755 0.236766\natom 8.84010 0.91341 6.02534 S 0.0 0.0 -0.258047 -0.162491 0.414270\natom -2.71569 6.92760 11.83271 S 0.0 0.0 -0.225165 0.110639 -0.001515\natom 0.26310 10.74251 5.86527 S 0.0 0.0 -0.291403 0.246144 -0.106097\natom 12.16049 5.18375 0.25903 S 0.0 0.0 -0.306233 0.189129 0.277409\natom 5.90335 0.80202 12.19479 S 0.0 0.0 0.682301 0.575851 -0.057515\natom 0.25690 7.15092 6.01075 S 0.0 0.0 -0.173297 -0.244374 0.963441\natom -2.72436 10.97968 12.22256 S 0.0 0.0 -0.098899 0.462324 -0.316690\natom 8.97928 4.87721 6.07816 S 0.0 0.0 -0.606398 -0.521561 -0.860132\natom 3.14328 1.06997 7.40557 S 0.0 0.0 0.386891 -0.150164 -0.289766\natom 2.84899 6.80084 10.98649 S 0.0 0.0 0.268124 0.824389 1.741362\natom 5.91565 10.92115 4.94652 S 0.0 0.0 0.816206 -0.069857 -0.458061\natom 6.19505 4.97784 1.19607 S 0.0 0.0 0.020261 0.232791 -0.436911\natom 6.51300 1.22938 1.43819 S 0.0 0.0 -0.034982 -0.914875 -0.946866\natom 6.07306 6.94380 4.93668 S 0.0 0.0 -1.069947 -0.817955 -0.382670\natom 3.08405 10.84138 10.97219 S 0.0 0.0 0.582596 -0.294231 -0.234379\natom 3.34583 5.01451 7.17457 S 0.0 0.0 0.433933 -0.515564 -0.059070\natom -0.10769 0.53439 9.55190 S 0.0 0.0 -0.246487 0.575358 -0.641655\natom 6.46784 6.93696 8.86987 S 0.0 0.0 0.195445 -0.871740 -0.723818\natom 9.71726 11.16132 2.44952 S 0.0 0.0 -0.350855 -0.023043 0.716478\natom 2.74777 4.92832 3.37943 S 0.0 0.0 -1.240342 0.662845 0.569114\natom 2.86321 1.09691 3.37519 S 0.0 0.0 0.168622 -0.323482 0.654758\natom 9.54365 7.17388 2.63388 S 0.0 0.0 -0.312841 0.398204 -0.329716\natom 6.68798 10.98009 8.90353 S 0.0 0.0 -0.149860 0.287866 -0.563104\natom -0.34160 4.88543 9.68239 S 0.0 0.0 -0.117975 -0.374465 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10.55069 S 0.0 0.0 0.073929 -0.154241 0.018321\natom -3.38107 2.91741 7.55176 S 0.0 0.0 0.715325 0.928195 -0.216603\natom 11.71801 2.98914 3.89390 Cu 0.0 0.0 -0.467988 -0.665921 -0.676485\natom 0.99904 9.01667 2.40789 Cu 0.0 0.0 -0.279413 0.098695 0.211728\natom -2.45788 8.89150 8.68152 Cu 0.0 0.0 0.460491 0.312367 0.059293\natom 8.65654 3.07551 9.75934 Cu 0.0 0.0 -0.419582 -0.382171 0.055251\natom 5.56828 0.93060 7.75629 Cu 0.0 0.0 -0.487518 -0.636133 0.688723\natom 0.75015 7.02990 10.06052 Cu 0.0 0.0 0.496763 -0.785950 0.118159\natom 3.90282 11.00621 3.48431 Cu 0.0 0.0 -0.488871 0.504442 0.314079\natom 8.29519 5.46566 1.61428 Cu 0.0 0.0 0.357376 -0.010017 0.440791\natom 9.15076 1.34525 2.56253 Cu 0.0 0.0 -0.093506 -0.615875 0.049226\natom 4.17865 6.69824 3.69420 Cu 0.0 0.0 -0.163601 0.398007 0.556611\natom 1.01648 10.72034 10.10046 Cu 0.0 0.0 -0.078193 -0.522280 0.140449\natom 5.62156 4.68027 8.04338 Cu 0.0 0.0 -0.708620 0.555179 -0.066652\natom 5.19654 2.96726 0.75982 Cu 0.0 0.0 -0.019284 -0.140251 -0.110442\natom 7.23117 8.62874 5.41001 Cu 0.0 0.0 0.315338 1.232601 0.237574\natom 3.86144 8.78725 11.67080 Cu 0.0 0.0 0.515774 0.072994 0.340351\natom 2.06236 3.09246 6.83012 Cu 0.0 0.0 -0.018984 0.241250 0.130947\natom -3.74653 0.94360 11.05878 Cu 0.0 0.0 -0.410483 -0.136584 0.270231\natom 9.99908 6.51694 6.93065 Cu 0.0 0.0 0.396143 0.816893 0.282226\natom 13.42126 11.12701 0.81370 Cu 0.0 0.0 -0.471867 -0.300103 -0.378838\natom -0.77879 5.21618 5.30510 Cu 0.0 0.0 0.225993 -0.053244 0.006220\natom -0.92197 0.96681 5.73762 Cu 0.0 0.0 0.110018 -0.314645 -0.221574\natom 13.47620 6.96931 0.70467 Cu 0.0 0.0 -0.433818 0.483797 -0.128972\natom 10.22948 11.13227 6.67148 Cu 0.0 0.0 -0.031991 0.204574 0.154043\natom -3.81283 5.00544 11.66820 Cu 0.0 0.0 -0.212745 -0.429051 -0.290690\natom 14.11855 1.59548 0.23698 Cu 0.0 0.0 0.058571 0.354736 0.036190\natom -2.81698 6.65728 5.86158 Cu 0.0 0.0 0.151068 -0.030905 -0.552647\natom 1.09440 10.63092 0.05018 Cu 0.0 0.0 -0.043658 -0.279292 0.073343\natom 11.14045 4.35279 5.88169 Cu 0.0 0.0 0.102749 0.020270 0.421236\natom 10.95004 1.69746 5.93561 Cu 0.0 0.0 0.175632 -0.356166 0.288761\natom -5.02025 7.67893 11.79654 Cu 0.0 0.0 0.578382 -0.307209 0.397629\natom 1.14801 9.41001 7.73385 Cu 0.0 0.0 -0.776125 -0.047744 0.495185\natom 14.20494 4.34744 0.29158 Cu 0.0 0.0 0.610102 -0.542936 -0.047785\natom 9.09479 2.66833 4.59776 Cu 0.0 0.0 -0.028794 0.584770 0.097207\natom 3.10805 8.38728 1.23799 Cu 0.0 0.0 0.185960 -0.174943 -0.752289\natom -2.03864 10.60918 5.84110 Cu 0.0 0.0 0.352905 -0.142834 -0.394039\natom 6.13297 3.15308 11.32270 Cu 0.0 0.0 0.423521 -0.263698 -0.096399\natom 1.15384 1.61366 11.16064 Cu 0.0 0.0 0.095285 -0.078379 0.099962\natom 4.96658 7.98829 7.80702 Cu 0.0 0.0 -0.555634 0.199894 -0.454383\natom 8.23677 11.92333 0.44464 Cu 0.0 0.0 0.125107 0.109684 0.376365\natom 3.79810 3.68907 4.75234 Cu 0.0 0.0 0.013001 -0.421798 0.541088\natom 4.64971 0.71725 5.33548 Cu 0.0 0.0 -0.495544 0.364019 0.141225\natom 8.48774 9.23201 2.05606 Cu 0.0 0.0 0.470603 0.254027 0.207617\natom 5.39323 10.31506 7.02597 Cu 0.0 0.0 0.128387 0.525209 0.325742\natom 1.27201 4.13500 11.12724 Cu 0.0 0.0 0.100106 0.027229 0.148301\natom -1.08356 2.34871 10.36440 Cu 0.0 0.0 -0.115961 0.201545 -0.039684\natom 7.41684 9.00449 7.99731 Cu 0.0 0.0 -0.346857 -0.262197 0.497363\natom 11.91265 8.39927 2.42959 Cu 0.0 0.0 -0.131640 -0.321162 0.508974\natom 1.18746 1.93982 4.73443 Cu 0.0 0.0 0.316395 0.106054 -0.281281\natom 8.46428 0.58439 8.38410 Cu 0.0 0.0 -0.201599 -0.093222 -0.211731\natom -2.28228 6.03105 9.60677 Cu 0.0 0.0 -0.147047 0.154758 0.109189\natom 1.21645 11.58938 3.94392 Cu 0.0 0.0 0.036200 -0.091983 -0.032970\natom 11.10207 5.65120 2.47741 Cu 0.0 0.0 0.624661 -0.133601 -0.503282\natom 11.98936 0.59789 2.16769 Cu 0.0 0.0 -0.295112 0.256572 0.643703\natom 1.00043 6.73888 4.04158 Cu 0.0 0.0 0.529960 -0.354381 -0.658114\natom -2.12839 11.43922 9.97281 Cu 0.0 0.0 0.000413 -0.492403 0.310696\natom 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5.21104 Cu 0.0 0.0 0.245095 -0.446805 0.418171\natom 4.46850 9.26065 11.12519 Cu 0.0 0.0 0.306807 -0.334017 0.208098\natom 2.26961 3.05527 6.77589 Cu 0.0 0.0 -0.353764 0.114041 -0.013309\natom -3.90401 1.03284 11.46200 Cu 0.0 0.0 0.001015 0.337714 -0.325268\natom 10.04011 7.25985 6.84980 Cu 0.0 0.0 0.244773 -0.320630 0.146804\natom 13.21623 11.02955 0.89163 Cu 0.0 0.0 0.112597 -0.567873 -0.018682\natom -0.51286 4.85669 5.10751 Cu 0.0 0.0 0.253876 -1.088299 -0.207555\natom -1.04706 0.72587 5.52506 Cu 0.0 0.0 -0.099741 -0.138001 -0.186971\natom 13.36150 6.86658 0.76794 Cu 0.0 0.0 -0.569603 0.126375 -0.339053\natom 10.12348 11.14436 6.92507 Cu 0.0 0.0 0.593908 0.253869 -0.057492\natom -3.89692 5.17103 11.34088 Cu 0.0 0.0 0.395195 0.075991 0.300955\natom 7.87836 1.23229 12.01207 Cu 0.0 0.0 0.600315 0.231568 -0.311218\natom -2.28976 7.34384 6.19682 Cu 0.0 0.0 -0.380809 -0.111907 0.356839\natom 0.90592 10.61238 0.07715 Cu 0.0 0.0 -0.021947 -0.526168 -0.337515\natom 11.21629 4.63957 6.08514 Cu 0.0 0.0 0.631695 -0.363444 -0.142808\natom 11.47399 1.84913 6.17495 Cu 0.0 0.0 -0.256208 0.011497 0.228798\natom -4.72531 7.79138 12.13660 Cu 0.0 0.0 -0.093923 -0.235496 -0.291658\natom -1.97425 10.19444 5.89992 Cu 0.0 0.0 0.234500 0.468924 -0.024111\natom 14.39111 4.08618 0.16464 Cu 0.0 0.0 -0.556085 0.585623 -0.525095\natom 9.22431 3.12924 5.09010 Cu 0.0 0.0 -0.022337 -0.006849 0.451603\natom 3.15359 9.23676 0.94540 Cu 0.0 0.0 0.062331 -1.208447 0.413546\natom -0.14476 8.70876 6.83661 Cu 0.0 0.0 0.152332 1.033735 -0.156566\natom 4.89805 3.75290 10.52765 Cu 0.0 0.0 0.148448 -0.525528 -1.048912\natom 1.18373 1.85350 11.20431 Cu 0.0 0.0 -0.813557 -0.325455 -0.019585\natom 4.99915 8.31554 8.33002 Cu 0.0 0.0 -0.257787 -0.231200 -0.043920\natom 8.01583 10.44061 0.99761 Cu 0.0 0.0 -0.396911 -0.277273 -0.135587\natom 4.05055 4.30653 4.67827 Cu 0.0 0.0 0.299631 -0.319010 0.353422\natom 3.83077 1.60663 5.02926 Cu 0.0 0.0 0.612574 0.439723 0.812241\natom 8.32052 7.15493 0.99878 Cu 0.0 0.0 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0.348682 -0.815617\natom -4.45212 1.94910 9.00188 Cu 0.0 0.0 0.146912 0.374676 -0.046818\natom 10.66299 8.41691 9.11260 Cu 0.0 0.0 -0.313353 0.113297 0.242159\natom -1.56062 9.96863 3.30079 Cu 0.0 0.0 -0.278408 -0.485308 0.103815\natom 13.73967 3.97375 2.71086 Cu 0.0 0.0 0.336940 -0.819309 -0.583271\natom 5.92778 1.35655 3.15688 Cu 0.0 0.0 0.070707 -0.219348 -0.260031\natom 6.54915 7.05855 2.75279 Cu 0.0 0.0 -0.088029 -0.071413 0.494950\natom 3.01547 11.62749 9.14424 Cu 0.0 0.0 -0.024791 0.003903 -0.523111\natom 3.35876 6.03323 9.07133 Cu 0.0 0.0 -0.095102 -0.063640 0.046690\natom 0.93017 0.74594 7.66931 Cu 0.0 0.0 -0.694347 -0.219155 0.041993\natom 5.26306 6.14718 10.73979 Cu 0.0 0.0 -0.103324 1.119268 -0.267892\natom 8.20036 11.21140 4.38288 Cu 0.0 0.0 0.004602 0.466955 0.202930\natom 4.49282 6.02257 1.56161 Cu 0.0 0.0 -0.009942 -0.094018 -0.233662\natom 3.75924 1.04894 1.35025 Cu 0.0 0.0 -0.166689 -0.284036 0.339482\natom 8.66395 6.58551 4.76169 Cu 0.0 0.0 -0.422704 0.486288 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7.41944 2.56304 6.88725 Cu 0.0 0.0 -0.173495 -0.220622 -0.396372\natom -1.11496 8.70006 10.97901 Cu 0.0 0.0 0.102019 -0.002106 -0.016884\natom 1.74272 9.08392 5.17534 Cu 0.0 0.0 -0.004178 0.261880 0.287603\natom 10.86803 3.04810 0.69753 Cu 0.0 0.0 -0.676314 -0.224309 0.821829\natom 2.88786 2.96233 2.73772 Cu 0.0 0.0 0.025540 0.290891 0.102734\natom 10.04071 8.64572 4.36542 Cu 0.0 0.0 0.141534 0.472423 0.775006\natom 7.12007 9.67126 10.55086 Cu 0.0 0.0 -0.606393 0.168277 -0.325061\natom -0.54230 3.53038 7.90963 Cu 0.0 0.0 -0.366325 -0.039287 0.385268\natom -2.07071 1.06297 8.26581 Cu 0.0 0.0 -0.204938 -0.059626 -0.004073\natom 8.54843 7.25768 10.34880 Cu 0.0 0.0 0.167314 0.204633 0.055703\natom 10.86934 11.02063 4.48999 Cu 0.0 0.0 0.847499 0.482703 0.037180\natom 0.69627 4.52606 2.42298 Cu 0.0 0.0 0.670820 0.765650 0.036433\nenergy -565.065780\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_33\nlattice 15.435177690 0.000000000 0.000000000\nlattice 0.000000000 12.031460820 0.000000000\nlattice -6.063675193 0.000000000 12.242007129\natom 9.65782 1.18202 10.27504 S 0.0 0.0 0.285181 -0.931064 -0.295809\natom -3.00257 7.12970 7.86560 S 0.0 0.0 -0.448164 -0.023945 -0.215172\natom -0.15780 11.06610 1.83396 S 0.0 0.0 -0.218794 0.072166 -0.012565\natom 12.59337 5.17117 4.03079 S 0.0 0.0 0.237190 -0.267151 0.050005\natom 12.89964 0.92876 4.54449 S 0.0 0.0 0.433577 0.463749 -0.287981\natom 0.05333 6.85151 1.51964 S 0.0 0.0 -0.132438 0.598876 0.074034\natom -3.20349 11.14002 7.49952 S 0.0 0.0 0.647545 -0.084959 0.394377\natom 9.45521 5.04327 10.41663 S 0.0 0.0 0.444666 0.541643 -0.036629\natom 9.10717 0.79608 6.24383 S 0.0 0.0 -0.208903 0.875131 -0.163135\natom -2.72448 7.13282 11.91110 S 0.0 0.0 -0.390073 0.651253 1.359356\natom 0.16389 10.90629 6.06716 S 0.0 0.0 -1.015894 -0.299023 -0.369495\natom 5.95258 4.95754 12.16634 S 0.0 0.0 0.201297 -0.030857 -0.751876\natom 12.09801 0.51942 0.17225 S 0.0 0.0 0.633923 0.392681 -0.475602\natom 0.37633 6.84818 6.24529 S 0.0 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0.740625 0.004409 0.136783\natom -3.04027 3.15796 12.00428 S 0.0 0.0 -0.027101 -0.979495 0.529354\natom -0.20545 2.79264 1.63317 S 0.0 0.0 0.819069 -0.715685 -0.714571\natom 12.38739 8.56259 4.14965 S 0.0 0.0 -0.311704 0.628863 0.276147\natom 9.48956 9.43813 10.26445 S 0.0 0.0 0.147783 -0.002337 0.005063\natom -3.19859 3.30868 7.73838 S 0.0 0.0 -0.127702 -0.465654 0.062915\natom 11.68424 2.77964 3.71134 Cu 0.0 0.0 0.250086 -0.248113 0.078845\natom 0.88023 9.06278 2.14244 Cu 0.0 0.0 -0.395778 -0.334036 0.009925\natom -2.10948 9.40264 8.62341 Cu 0.0 0.0 -0.976151 0.352945 -0.373781\natom 8.53873 3.08322 9.92044 Cu 0.0 0.0 -1.036412 0.201948 -0.331137\natom 5.27467 0.64485 8.26120 Cu 0.0 0.0 0.023755 0.480977 -0.296181\natom 0.85845 6.96864 9.86806 Cu 0.0 0.0 -0.362467 -0.223358 -0.238101\natom 3.69632 10.66923 3.40648 Cu 0.0 0.0 0.167067 0.258891 0.302006\natom 8.39836 5.03179 2.44298 Cu 0.0 0.0 -0.235975 -0.283906 -0.288519\natom 8.18977 1.08439 2.25277 Cu 0.0 0.0 1.281028 0.284735 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11.42114 5.38310 1.94298 Cu 0.0 0.0 0.075951 0.425932 1.041462\natom 10.70567 1.00731 1.84688 Cu 0.0 0.0 0.223407 0.460631 0.647478\natom 1.90497 6.05672 4.77712 Cu 0.0 0.0 -0.259846 0.014966 -0.403398\natom -1.65585 11.68537 10.50567 Cu 0.0 0.0 0.268929 -0.707850 0.123446\natom 7.82215 5.48886 7.69180 Cu 0.0 0.0 0.380108 -0.177917 -0.130356\natom -4.42527 2.91274 9.64339 Cu 0.0 0.0 0.418973 0.370299 -0.445789\natom -4.19924 8.09144 9.57067 Cu 0.0 0.0 -0.260352 0.155246 -0.281942\natom -1.54616 9.88953 3.13799 Cu 0.0 0.0 0.349213 -0.120284 0.223816\natom 13.83430 3.84871 2.76269 Cu 0.0 0.0 -0.691911 0.450026 0.830477\natom 6.00171 1.13082 3.73239 Cu 0.0 0.0 0.098110 -0.566170 0.492193\natom 6.36143 6.95491 2.47509 Cu 0.0 0.0 -0.083912 0.125975 0.453908\natom 3.32728 11.29262 8.98225 Cu 0.0 0.0 -0.620479 -0.387307 -0.143286\natom 3.21657 5.03458 9.89750 Cu 0.0 0.0 -0.274916 -0.619830 -0.546933\natom 0.82229 0.13098 7.69079 Cu 0.0 0.0 0.438388 0.346984 0.670891\natom 5.09347 6.53680 10.60139 Cu 0.0 0.0 0.337538 -0.049954 0.164278\natom 8.21358 11.66913 4.51337 Cu 0.0 0.0 -0.343163 -0.056985 -0.025961\natom 3.93413 6.02726 1.59945 Cu 0.0 0.0 0.489399 0.526914 -0.814016\natom 3.94376 0.70044 1.63113 Cu 0.0 0.0 -0.123210 -0.302805 0.182278\natom 8.75881 7.34042 4.59194 Cu 0.0 0.0 0.209668 -0.195761 -0.054017\natom 5.20963 11.49503 10.49665 Cu 0.0 0.0 0.128236 -0.088421 0.002172\natom 0.79096 5.24340 7.74830 Cu 0.0 0.0 -0.269998 -0.047888 0.903317\natom 4.01411 2.54816 9.34197 Cu 0.0 0.0 0.007589 0.071441 -0.217994\natom 2.93521 8.60930 9.25798 Cu 0.0 0.0 0.151766 0.215699 -0.252560\natom 6.29266 9.50900 2.96155 Cu 0.0 0.0 -0.310873 0.377971 0.158102\natom 6.62111 3.10464 2.68527 Cu 0.0 0.0 0.171896 0.983184 0.487710\natom 13.39829 1.22636 2.24611 Cu 0.0 0.0 0.050971 0.059745 0.260887\natom 13.86998 7.31557 3.08116 Cu 0.0 0.0 0.471160 -0.357974 -0.191337\natom -4.30255 11.00313 9.50116 Cu 0.0 0.0 -0.049573 -0.211658 0.053019\natom -4.30044 5.52854 8.80646 Cu 0.0 0.0 -0.280231 -0.412144 0.319339\natom 3.87850 1.30338 11.77458 Cu 0.0 0.0 -0.122584 0.207500 -0.306725\natom 2.73962 7.03541 7.04746 Cu 0.0 0.0 -0.552699 0.409602 -0.014414\natom 6.13873 10.96173 0.60062 Cu 0.0 0.0 -0.045089 -0.488069 0.055684\natom 7.23101 4.76673 4.90486 Cu 0.0 0.0 -0.696646 -0.216287 -0.180897\natom 7.33346 2.34509 6.64273 Cu 0.0 0.0 -0.131107 -0.109486 0.021014\natom -1.80964 9.24479 11.34020 Cu 0.0 0.0 0.321823 -0.193257 -0.315113\natom 1.76250 9.49303 5.52213 Cu 0.0 0.0 0.791381 -0.238453 -0.149389\natom 10.27426 3.55203 0.72125 Cu 0.0 0.0 -0.567562 -0.049506 0.084905\natom 2.25862 2.50203 2.05134 Cu 0.0 0.0 -0.168929 0.509180 -0.358181\natom 9.94430 9.81195 4.60197 Cu 0.0 0.0 -0.080221 -0.228557 -0.113512\natom 6.83850 9.70781 10.36143 Cu 0.0 0.0 0.268182 -0.728823 0.571879\natom -0.85354 3.15716 7.94805 Cu 0.0 0.0 -0.574809 0.080394 0.905543\natom -2.39335 1.05511 8.41489 Cu 0.0 0.0 -0.116089 0.236136 0.043041\natom 8.70780 7.16242 9.61005 Cu 0.0 0.0 0.049346 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0.324178\natom 5.88982 0.73452 8.63276 Cu 0.0 0.0 -0.622485 -0.563224 -0.142045\natom 0.79752 6.86381 9.84725 Cu 0.0 0.0 0.682134 1.102318 0.258538\natom 4.15518 11.26781 4.05532 Cu 0.0 0.0 -0.382752 -0.335446 -0.523601\natom 8.43879 5.18875 2.01899 Cu 0.0 0.0 -0.521069 0.080386 0.227965\natom 8.23032 1.51809 2.02800 Cu 0.0 0.0 0.274933 -0.217530 0.080775\natom 4.09179 7.31485 3.81976 Cu 0.0 0.0 -0.350764 0.394703 -0.175752\natom 1.07376 10.90111 9.98153 Cu 0.0 0.0 -0.398227 -0.048638 0.093686\natom 5.46699 4.73378 8.28133 Cu 0.0 0.0 -0.087166 0.211269 -0.358015\natom 5.16720 2.84364 1.19692 Cu 0.0 0.0 0.046259 0.201715 -0.356204\natom 7.16256 9.03567 5.16722 Cu 0.0 0.0 -0.218735 -0.396738 -0.260383\natom 3.73656 9.21724 11.57400 Cu 0.0 0.0 0.334667 0.231045 0.028330\natom 2.33159 3.06921 6.86393 Cu 0.0 0.0 -0.133697 -0.171327 0.450428\natom -3.81102 0.80098 11.52015 Cu 0.0 0.0 0.173927 0.663246 0.047117\natom 10.05517 6.74784 6.76599 Cu 0.0 0.0 0.235281 0.287885 0.196644\natom 13.08403 11.03620 1.03971 Cu 0.0 0.0 -1.762495 -0.456507 -0.716181\natom -0.63174 5.30808 5.10175 Cu 0.0 0.0 0.241826 -0.041153 0.295433\natom -0.64372 1.03701 5.29732 Cu 0.0 0.0 -0.257431 0.740593 0.440301\natom 13.51339 7.39384 1.00709 Cu 0.0 0.0 0.370298 -0.324317 -0.371142\natom 9.83696 11.03363 6.64159 Cu 0.0 0.0 0.439562 0.005226 0.322419\natom -3.97699 4.81529 11.90457 Cu 0.0 0.0 -0.165398 0.076871 -0.316354\natom 15.10523 0.97018 0.45335 Cu 0.0 0.0 0.108855 0.349277 -0.195362\natom -1.87717 7.59875 5.94873 Cu 0.0 0.0 0.139248 -0.584412 0.412171\natom 0.81659 10.83165 0.01596 Cu 0.0 0.0 0.517358 -0.674483 -0.194676\natom 11.26107 4.24369 6.09709 Cu 0.0 0.0 -0.162982 0.508744 0.077368\natom 11.60629 1.86990 6.11246 Cu 0.0 0.0 -0.307392 -0.501398 0.118571\natom -4.97881 7.54115 12.09636 Cu 0.0 0.0 -0.056304 -0.017572 -0.326777\natom -1.92231 10.89385 5.82448 Cu 0.0 0.0 0.073982 -0.083700 0.204187\natom 14.72874 4.60296 0.15773 Cu 0.0 0.0 -0.332554 0.302974 -0.483146\natom 9.29036 2.46552 4.42771 Cu 0.0 0.0 -0.188209 -0.209773 0.685848\natom 2.84329 9.02647 0.89470 Cu 0.0 0.0 0.371717 0.515513 -0.026191\natom -0.34393 9.17943 7.03999 Cu 0.0 0.0 0.471892 0.582224 -0.019573\natom 5.33064 3.56966 10.70737 Cu 0.0 0.0 -0.399926 0.130172 0.596025\natom 1.05972 2.11438 10.15431 Cu 0.0 0.0 -0.718098 -0.330092 -0.354223\natom 5.10288 8.07193 6.44549 Cu 0.0 0.0 0.132556 -0.656152 -0.222280\natom 8.23428 10.62487 1.00344 Cu 0.0 0.0 -0.383120 -0.348728 0.290531\natom 4.26793 4.03251 5.37922 Cu 0.0 0.0 0.173414 0.401816 0.140236\natom 3.88090 1.48691 5.09628 Cu 0.0 0.0 0.446610 0.451931 1.046696\natom 8.68604 7.43322 0.82228 Cu 0.0 0.0 -0.057976 0.051102 0.148079\natom 5.80908 10.29903 7.15036 Cu 0.0 0.0 0.017333 0.468693 0.113093\natom 0.58906 4.28541 11.67626 Cu 0.0 0.0 0.123722 0.167641 -0.252301\natom -2.22381 3.92945 10.06964 Cu 0.0 0.0 -0.176000 -0.517677 -0.037408\natom 8.52022 8.06816 8.42355 Cu 0.0 0.0 -0.539787 -0.009521 0.329340\natom 9.41015 9.06777 2.70081 Cu 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7.78762 S 0.0 0.0 0.307424 0.468046 -0.003713\natom 11.73155 2.72999 3.65429 Cu 0.0 0.0 -0.205403 0.640337 -0.151061\natom 0.66613 8.60344 2.43088 Cu 0.0 0.0 0.355992 -0.185770 -0.193305\natom -2.29146 9.07539 8.56173 Cu 0.0 0.0 -0.042250 -0.301201 0.203443\natom 8.80854 2.86845 9.60856 Cu 0.0 0.0 -0.320755 -0.172987 0.168747\natom 5.30302 0.86141 8.63190 Cu 0.0 0.0 -0.108091 0.111894 -0.000144\natom 0.76235 6.97487 10.00323 Cu 0.0 0.0 0.193386 0.458556 0.543800\natom 3.73917 11.16368 3.99209 Cu 0.0 0.0 0.098091 -0.299638 -0.050441\natom 8.67336 4.89055 2.05390 Cu 0.0 0.0 -0.160631 -0.313052 -0.310123\natom 8.64053 1.22491 1.89864 Cu 0.0 0.0 -0.531404 -0.329692 0.082656\natom 3.87060 7.15001 3.98688 Cu 0.0 0.0 0.343764 -0.245635 0.192519\natom 0.86747 10.99916 10.12815 Cu 0.0 0.0 0.553844 0.504072 -0.015565\natom 5.37338 4.54608 7.96600 Cu 0.0 0.0 -0.790988 0.612881 0.188971\natom 5.30235 2.96679 0.74196 Cu 0.0 0.0 -0.279765 0.053589 0.061152\natom 7.17235 8.95634 5.48649 Cu 0.0 0.0 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0.052221 -0.147774\natom -2.92174 3.34768 11.88610 S 0.0 0.0 0.050199 0.007954 0.053206\natom -0.01405 3.10105 1.74874 S 0.0 0.0 -1.256553 -0.991026 -0.911636\natom 12.54325 8.73734 4.60141 S 0.0 0.0 -0.668099 0.095902 0.446299\natom 9.62451 9.13033 10.77019 S 0.0 0.0 -0.951899 -0.199389 -1.096222\natom -3.10511 3.22896 7.68996 S 0.0 0.0 -0.191980 0.090752 0.181160\natom 11.71159 3.05493 3.42301 Cu 0.0 0.0 -0.614346 -0.362901 0.023987\natom 0.79889 9.09650 2.66785 Cu 0.0 0.0 0.238005 -0.467958 0.174566\natom -2.08133 8.83859 8.65215 Cu 0.0 0.0 -0.179033 0.047382 0.078499\natom 8.38345 2.76307 9.68602 Cu 0.0 0.0 0.229534 0.245422 0.262122\natom 5.54077 0.71040 7.81966 Cu 0.0 0.0 -0.543723 0.104156 0.062864\natom 0.99210 6.95531 9.77437 Cu 0.0 0.0 -0.602864 0.096841 -0.245447\natom 4.20764 11.27650 3.97750 Cu 0.0 0.0 -0.278442 -0.155795 -0.117456\natom 8.13159 5.19745 2.25772 Cu 0.0 0.0 0.413031 0.147334 -0.261297\natom 8.36442 1.04172 2.16453 Cu 0.0 0.0 0.107403 0.359153 0.029200\natom 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5.16669 11.07826 Cu 0.0 0.0 0.068204 0.464504 0.580785\natom 14.40140 1.55724 0.07078 Cu 0.0 0.0 -0.175878 0.077724 -0.485831\natom 12.39439 6.48209 5.81842 Cu 0.0 0.0 -0.038046 -0.033224 -0.289350\natom 1.04454 10.25970 0.33599 Cu 0.0 0.0 0.362430 0.420358 0.063403\natom 11.23577 4.09764 5.81212 Cu 0.0 0.0 0.196093 0.306465 0.077735\natom 11.34717 1.45856 5.99899 Cu 0.0 0.0 -0.229240 0.458238 0.843086\natom -4.88353 7.68744 12.16439 Cu 0.0 0.0 0.051403 -0.373407 0.449964\natom -2.41629 11.10057 5.98287 Cu 0.0 0.0 -0.056673 -0.124752 -0.355872\natom 14.06539 4.26781 0.26329 Cu 0.0 0.0 0.564317 -0.090832 -0.077447\natom 9.07661 3.06429 4.99900 Cu 0.0 0.0 0.095513 -0.073796 -0.030946\natom 3.26713 9.15368 1.12967 Cu 0.0 0.0 -0.131499 -0.290807 -0.245339\natom -0.75901 9.07992 5.52474 Cu 0.0 0.0 0.102919 0.030057 0.034120\natom 6.22595 3.07567 11.14685 Cu 0.0 0.0 -0.035081 -0.198247 0.345145\natom 1.04384 1.46412 11.32789 Cu 0.0 0.0 0.052973 0.431111 0.163237\natom 5.40090 7.63747 6.67094 Cu 0.0 0.0 -0.331470 0.252398 0.495228\natom 8.19074 10.20427 0.59092 Cu 0.0 0.0 0.040328 -0.185457 0.244075\natom 4.33223 4.14579 5.18777 Cu 0.0 0.0 0.336363 -0.551805 0.367652\natom 3.73865 1.60189 5.41475 Cu 0.0 0.0 -0.207445 -0.174537 -0.155598\natom 8.32237 7.46590 0.77550 Cu 0.0 0.0 0.261253 0.027276 0.048673\natom 5.56080 10.18706 6.52803 Cu 0.0 0.0 -0.120393 0.271156 0.429619\natom 0.90273 4.27241 11.65507 Cu 0.0 0.0 -0.421922 0.020559 0.088453\natom -1.32779 2.49177 10.47752 Cu 0.0 0.0 -0.066978 -0.009727 -0.291503\natom 7.50996 9.04857 7.85521 Cu 0.0 0.0 -0.114700 -0.644251 -0.023218\natom 10.73365 9.18162 1.73432 Cu 0.0 0.0 -0.426919 -0.210149 0.411827\natom 1.68706 3.88963 4.75733 Cu 0.0 0.0 0.421421 0.255337 -0.128322\natom 8.90235 0.55317 8.27384 Cu 0.0 0.0 -0.356851 0.199562 0.968593\natom -1.91232 6.50406 9.88035 Cu 0.0 0.0 -0.013697 -0.067394 0.369268\natom 0.70885 11.72524 3.95941 Cu 0.0 0.0 0.192362 0.149447 -0.950886\natom 11.46683 5.56791 2.08637 Cu 0.0 0.0 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3.44327 10.24238 1.77073 Cu 0.0 0.0 -0.350057 -0.176774 -0.256603\natom -0.03280 8.81250 7.12799 Cu 0.0 0.0 -0.041940 0.420079 0.097492\natom 6.46455 3.37543 11.06979 Cu 0.0 0.0 -0.353013 0.286262 -0.382891\natom 0.93281 1.43790 11.35287 Cu 0.0 0.0 0.307421 0.333833 0.134033\natom 4.98237 7.67647 6.73481 Cu 0.0 0.0 0.646501 -0.510815 -0.073037\natom 8.22109 9.63094 1.66601 Cu 0.0 0.0 -1.147843 -1.102191 -0.619118\natom 4.02130 4.00831 5.51665 Cu 0.0 0.0 0.173977 -0.433642 -0.819676\natom 3.01648 1.21991 5.37519 Cu 0.0 0.0 0.204883 0.430032 -0.046187\natom 8.71496 7.24901 0.41989 Cu 0.0 0.0 0.028850 -0.022814 0.239184\natom 5.53143 10.22296 6.96858 Cu 0.0 0.0 0.160567 0.179981 0.538441\natom 0.85345 4.32598 11.49647 Cu 0.0 0.0 -0.538446 0.337959 0.345063\natom -1.29048 2.61315 10.23283 Cu 0.0 0.0 -0.299114 0.570145 0.723668\natom 7.69541 8.57343 7.82927 Cu 0.0 0.0 -0.729899 -0.109052 0.363813\natom 10.64911 10.02171 1.08460 Cu 0.0 0.0 0.128979 0.109735 0.435639\natom 1.47720 3.44615 4.36867 Cu 0.0 0.0 -0.114276 -0.230592 0.287064\natom 8.72304 0.21063 8.19764 Cu 0.0 0.0 -0.192633 0.367962 0.438521\natom -2.16120 6.36592 10.10799 Cu 0.0 0.0 -0.494501 0.210617 0.060073\natom 0.56732 11.61300 3.93830 Cu 0.0 0.0 0.010921 -0.343774 0.100572\natom 11.35659 5.51648 2.20087 Cu 0.0 0.0 0.498229 -0.120575 -0.029479\natom 11.56200 0.72730 2.10855 Cu 0.0 0.0 0.008456 0.072176 -0.164480\natom 1.10430 6.29081 4.35545 Cu 0.0 0.0 0.618673 -0.113613 -0.754336\natom -1.03856 0.07794 10.94100 Cu 0.0 0.0 -0.051909 -0.302481 -0.497623\natom 8.10432 6.04634 7.98365 Cu 0.0 0.0 -0.110391 -0.390517 -0.309706\natom -3.96247 2.24019 9.62523 Cu 0.0 0.0 -0.592591 0.331202 -0.089427\natom 10.22205 8.85141 8.38912 Cu 0.0 0.0 0.293962 -0.253980 0.213099\natom 13.56027 9.84290 2.83780 Cu 0.0 0.0 -0.052248 -0.059945 0.126373\natom -1.18772 3.59737 3.31697 Cu 0.0 0.0 -0.126922 0.126883 0.083608\natom 6.09030 0.88726 3.61543 Cu 0.0 0.0 0.705088 0.195842 0.805285\natom 6.59092 6.83284 2.81258 Cu 0.0 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0.353789\natom 2.70683 9.04991 3.55321 S 0.0 0.0 0.537298 0.158861 0.561862\natom 9.30615 3.09449 2.59476 S 0.0 0.0 -0.196051 -0.356101 1.123435\natom 6.02460 2.61054 5.10729 S 0.0 0.0 0.578382 -0.199064 -0.567365\natom 6.48266 8.86413 0.92686 S 0.0 0.0 0.091800 -0.139599 0.160166\natom 3.44944 9.08993 7.09874 S 0.0 0.0 0.974626 -0.680965 0.431179\natom 2.89860 3.23245 10.84667 S 0.0 0.0 -0.051320 0.073445 0.969085\natom 0.34061 2.85112 5.67753 S 0.0 0.0 -0.739912 -0.095006 0.953045\natom 12.04718 8.60085 0.18208 S 0.0 0.0 1.585812 0.272001 1.273766\natom 9.34669 9.34914 6.36354 S 0.0 0.0 -1.005174 -0.136858 0.137180\natom -2.89263 3.05685 12.10173 S 0.0 0.0 0.160634 0.532234 -0.702486\natom -0.09105 3.01999 1.66882 S 0.0 0.0 0.456189 -0.317115 0.005520\natom 12.20418 9.29411 4.83927 S 0.0 0.0 1.091587 -0.709974 0.718821\natom 9.35341 9.09981 10.67217 S 0.0 0.0 -0.334153 -0.312737 -0.207610\natom -3.12568 3.38817 7.71964 S 0.0 0.0 0.319589 -0.641005 1.014040\natom 11.66666 3.29114 3.26623 Cu 0.0 0.0 -0.331580 -0.186834 0.243762\natom 0.64245 8.84056 2.54336 Cu 0.0 0.0 -0.324729 0.763125 -0.372292\natom -2.32332 9.00304 9.07330 Cu 0.0 0.0 0.094923 0.166559 -0.262267\natom 8.32954 2.70576 9.43005 Cu 0.0 0.0 0.064536 0.213399 0.577320\natom 5.55597 0.75237 8.02568 Cu 0.0 0.0 -0.708120 -0.266832 0.333225\natom 1.08180 6.69107 9.73028 Cu 0.0 0.0 -0.303017 0.478637 0.216091\natom 4.01222 10.99930 4.02960 Cu 0.0 0.0 -1.245291 0.054410 -0.818701\natom 8.35845 5.15286 2.36047 Cu 0.0 0.0 -0.118441 -0.057232 -0.735131\natom 8.41490 1.12824 1.86743 Cu 0.0 0.0 0.320209 -0.150756 0.090996\natom 4.16893 7.21379 3.73240 Cu 0.0 0.0 -0.534435 0.086894 -0.088972\natom 0.76182 10.90972 9.94147 Cu 0.0 0.0 0.091647 -0.588284 0.343511\natom 5.54852 4.89654 7.98309 Cu 0.0 0.0 0.111048 0.557234 -0.010039\natom 5.33459 3.13848 0.73696 Cu 0.0 0.0 -0.464573 -0.242602 -0.139119\natom 7.31805 8.81667 5.30938 Cu 0.0 0.0 0.071239 0.170203 0.009755\natom 4.29466 8.66726 11.25985 Cu 0.0 0.0 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0.329849\natom 1.15159 4.66099 11.37756 Cu 0.0 0.0 -0.336283 -0.209514 -0.185101\natom -1.55569 2.58815 10.33805 Cu 0.0 0.0 0.018895 -0.182426 0.088816\natom 7.72449 8.71925 7.96406 Cu 0.0 0.0 -0.132685 0.009046 -0.283066\natom 10.48229 9.25727 1.60632 Cu 0.0 0.0 -0.021676 0.223088 0.482373\natom 2.04179 3.21034 4.34011 Cu 0.0 0.0 0.557433 -0.411878 -0.252549\natom 8.44392 0.41332 8.47139 Cu 0.0 0.0 0.165632 -0.254377 -0.139415\natom -2.31493 6.23191 9.85245 Cu 0.0 0.0 0.502422 0.314304 -0.743111\natom 0.50399 11.69005 4.13484 Cu 0.0 0.0 0.092619 -0.279971 -0.397506\natom 11.34738 5.55045 2.17023 Cu 0.0 0.0 0.716229 -0.469512 -0.506610\natom 10.95567 1.18490 2.02043 Cu 0.0 0.0 -0.014750 -0.331213 -0.138469\natom 2.21720 5.62898 5.08263 Cu 0.0 0.0 -0.332510 0.399610 0.045123\natom -1.83721 11.60535 10.30407 Cu 0.0 0.0 0.362648 0.046791 0.578956\natom 8.42975 4.76827 8.05356 Cu 0.0 0.0 -0.424215 0.401851 0.322087\natom -4.21196 2.16155 9.43808 Cu 0.0 0.0 0.584340 0.810775 -0.646786\natom 10.30143 8.64350 8.49723 Cu 0.0 0.0 0.083810 -0.131603 0.334935\natom -1.72938 10.29452 3.65016 Cu 0.0 0.0 1.515674 -0.190272 -0.779449\natom -1.20943 4.09990 3.12087 Cu 0.0 0.0 -1.157590 -0.021959 -0.036250\natom 6.03292 0.69436 3.48553 Cu 0.0 0.0 0.074178 0.275570 -0.141869\natom 6.47805 7.11514 2.48784 Cu 0.0 0.0 -0.059485 0.222165 -0.060826\natom 3.72981 10.53068 8.97299 Cu 0.0 0.0 -0.077474 -0.112193 -0.507353\natom 2.88978 5.00932 9.10674 Cu 0.0 0.0 0.008224 -0.355010 0.440848\natom 0.23300 1.13948 7.48811 Cu 0.0 0.0 0.054018 0.722375 0.248494\natom 5.27272 6.61739 10.35420 Cu 0.0 0.0 0.313267 -0.599971 -0.290047\natom 8.20480 11.26250 4.34608 Cu 0.0 0.0 -0.243905 0.093448 0.199879\natom 4.22879 5.97189 1.29570 Cu 0.0 0.0 0.087090 -0.189640 0.436014\natom 4.00347 0.35536 1.65123 Cu 0.0 0.0 -0.107968 -0.053414 0.246173\natom 8.43919 6.42307 4.39054 Cu 0.0 0.0 -0.130801 1.110111 -0.172923\natom 5.97020 11.97330 10.78348 Cu 0.0 0.0 0.477561 -0.741416 -0.712938\natom 0.67815 5.42894 7.57952 Cu 0.0 0.0 0.753475 0.611000 -0.355301\natom 3.52075 1.97610 9.25572 Cu 0.0 0.0 0.112054 -0.426083 -0.762882\natom 3.26902 8.05342 9.03638 Cu 0.0 0.0 -0.157608 -0.565383 0.382513\natom 6.24172 9.98896 2.84463 Cu 0.0 0.0 0.003933 -0.138988 0.313051\natom 6.43948 3.61142 3.09045 Cu 0.0 0.0 -0.060870 -0.031435 0.141111\natom 13.69400 1.53934 2.62912 Cu 0.0 0.0 0.335950 0.186153 0.053134\natom 0.10282 6.95017 3.92907 Cu 0.0 0.0 -0.087201 -0.379768 0.513462\natom 10.27674 10.90234 9.71186 Cu 0.0 0.0 -0.130954 0.044084 0.051030\natom 10.78148 5.62170 8.62304 Cu 0.0 0.0 0.225660 0.075907 0.231229\natom 4.08450 0.96778 11.65065 Cu 0.0 0.0 -0.942692 0.584827 0.378703\natom 1.56751 8.44109 5.49639 Cu 0.0 0.0 0.776519 0.455451 -0.498322\natom 5.86360 11.00627 0.29875 Cu 0.0 0.0 -0.174387 0.309697 0.215419\natom 6.84270 4.79087 5.65818 Cu 0.0 0.0 -0.019140 -0.147352 -0.202036\natom 7.41095 2.15234 7.06265 Cu 0.0 0.0 -0.138064 0.659121 -0.120287\natom -1.56302 8.97419 11.56691 Cu 0.0 0.0 0.361844 0.152706 -0.183741\natom 2.20625 10.78629 6.56346 Cu 0.0 0.0 -0.261686 0.468924 0.098358\natom 10.28961 3.38087 0.70884 Cu 0.0 0.0 0.421617 0.194674 -0.807809\natom 2.22367 2.29936 1.67960 Cu 0.0 0.0 -0.265866 -0.257214 0.654316\natom 10.12344 8.73026 4.22911 Cu 0.0 0.0 -0.471823 -0.443444 -0.098388\natom 7.02590 9.64543 10.80660 Cu 0.0 0.0 0.328841 0.093988 -0.529030\natom -0.68291 3.58552 7.68339 Cu 0.0 0.0 -0.634678 -1.092178 -0.209949\natom -2.35594 1.09296 8.02549 Cu 0.0 0.0 0.171107 0.496459 -0.079950\natom 8.94965 6.92338 10.11464 Cu 0.0 0.0 -0.154993 0.167321 -0.101779\natom 11.47675 11.01482 3.68364 Cu 0.0 0.0 -1.272556 0.754215 -0.569692\natom 1.03833 4.85681 2.68082 Cu 0.0 0.0 0.647871 0.231656 -0.088701\nenergy -565.510497\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_52\nlattice 15.452772050 0.000000000 0.000000000\nlattice 0.000000000 12.045175328 0.000000000\nlattice -6.070587099 0.000000000 12.255961635\natom 9.68829 0.88849 10.39469 S 0.0 0.0 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-0.315783 -0.830057\natom -0.27492 2.93000 1.65662 S 0.0 0.0 1.317144 -0.472014 -1.478939\natom 12.70682 8.83360 4.38230 S 0.0 0.0 -0.314408 0.423262 0.566147\natom 9.55891 8.83086 10.81540 S 0.0 0.0 -0.632277 -0.260585 -0.656271\natom -3.13973 3.21023 7.57021 S 0.0 0.0 0.035096 -0.125648 0.261547\natom 11.67545 2.89950 3.60542 Cu 0.0 0.0 0.304505 -0.063909 0.234011\natom 1.05856 8.88570 2.64150 Cu 0.0 0.0 0.080229 -0.118842 -0.092864\natom -2.03469 9.25706 8.62281 Cu 0.0 0.0 -0.862891 0.167669 -0.411915\natom 8.48896 2.80002 9.97195 Cu 0.0 0.0 0.354960 0.225683 -0.303977\natom 5.45597 1.28499 8.47908 Cu 0.0 0.0 0.410477 0.205054 -0.304789\natom 1.05344 7.23415 10.04549 Cu 0.0 0.0 -0.163714 -0.542530 -0.155902\natom 4.27941 11.21374 3.88343 Cu 0.0 0.0 -0.222332 0.285825 -0.273272\natom 8.59142 5.23398 2.42178 Cu 0.0 0.0 -0.271659 -0.215243 -0.287463\natom 8.41791 1.16182 2.20372 Cu 0.0 0.0 -0.394520 -0.568841 -0.253266\natom 4.38860 7.53723 4.27049 Cu 0.0 0.0 -0.180703 0.028054 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0.507960\natom 8.34727 1.45761 12.13804 Cu 0.0 0.0 -0.243015 -0.063355 0.384000\natom -1.91304 7.87559 6.27224 Cu 0.0 0.0 0.182465 -0.125591 -0.042310\natom 1.22350 10.01820 0.09676 Cu 0.0 0.0 0.329541 0.496820 0.527121\natom 11.03890 4.23073 6.01320 Cu 0.0 0.0 0.292541 0.331663 -0.043652\natom 11.16626 1.63740 5.92045 Cu 0.0 0.0 0.082946 -0.262730 0.096357\natom 1.35930 7.49830 0.32093 Cu 0.0 0.0 0.515749 -0.127466 -0.306337\natom -0.85889 10.05124 5.32919 Cu 0.0 0.0 -1.065336 -0.557422 -0.438531\natom 14.30901 4.24465 0.08140 Cu 0.0 0.0 -0.109927 0.237845 -0.214746\natom 9.13306 2.95525 5.08939 Cu 0.0 0.0 -0.026585 0.633991 -0.361295\natom 3.35563 8.63970 1.52747 Cu 0.0 0.0 0.084884 -0.344084 -0.620736\natom 0.05199 10.35869 7.80543 Cu 0.0 0.0 0.069402 -0.307704 0.363921\natom 6.24559 2.85868 11.46795 Cu 0.0 0.0 -0.045526 0.210162 -0.045442\natom -0.90545 3.86279 7.69139 Cu 0.0 0.0 0.435370 0.040458 0.173097\natom 5.54793 7.73506 7.04433 Cu 0.0 0.0 -0.163665 -0.165320 -0.216939\natom 8.07550 10.08907 0.73957 Cu 0.0 0.0 0.274589 0.224532 -0.123789\natom 3.86209 3.99357 5.47504 Cu 0.0 0.0 0.713637 -0.120590 -0.371456\natom 3.71869 1.30131 5.20309 Cu 0.0 0.0 0.295541 0.532457 0.277208\natom 8.40070 7.55699 1.22324 Cu 0.0 0.0 0.918084 -0.017097 -0.172116\natom 5.46091 10.31389 6.88238 Cu 0.0 0.0 0.636379 0.305708 -0.274427\natom 7.51135 4.14117 0.07082 Cu 0.0 0.0 -0.806049 0.048342 0.411963\natom -0.51039 2.11068 12.19002 Cu 0.0 0.0 -0.204222 0.342347 -0.129231\natom 7.64971 8.80134 8.07465 Cu 0.0 0.0 0.024751 0.202055 -0.029493\natom 10.63996 9.17796 1.90314 Cu 0.0 0.0 -0.099927 -0.100229 -0.384760\natom 1.91044 3.03927 4.31101 Cu 0.0 0.0 -0.164463 -0.083120 -0.642104\natom 8.54230 0.59236 8.32153 Cu 0.0 0.0 0.100847 0.345645 -0.240471\natom -1.94652 6.36568 9.71590 Cu 0.0 0.0 -0.478626 0.132312 -0.016137\natom 0.70683 11.56552 3.80038 Cu 0.0 0.0 0.008461 -0.141396 -0.923532\natom 11.99474 5.27822 2.27860 Cu 0.0 0.0 -0.046479 -0.015532 -0.072183\natom 10.62870 0.31821 1.25739 Cu 0.0 0.0 -0.076343 -0.123905 0.577853\natom 1.70035 6.52242 4.52969 Cu 0.0 0.0 -0.279728 -0.075011 -0.557715\natom -3.24874 11.45552 9.69927 Cu 0.0 0.0 0.144854 -0.195696 0.557575\natom 7.73758 4.97325 7.80800 Cu 0.0 0.0 -0.044919 0.103196 0.649776\natom 10.96720 1.77377 8.69401 Cu 0.0 0.0 -0.300278 -0.312687 0.318857\natom 10.82361 8.87007 8.96418 Cu 0.0 0.0 0.231775 -0.245660 0.012344\natom 14.05468 9.39456 2.79846 Cu 0.0 0.0 0.039430 0.506389 -0.355454\natom -0.99274 3.66799 3.45835 Cu 0.0 0.0 -1.391409 -0.130586 1.244523\natom 5.85981 0.99793 3.45645 Cu 0.0 0.0 0.350906 -0.124246 -0.365691\natom 6.48697 6.99586 2.70234 Cu 0.0 0.0 -0.115451 -0.567635 0.286672\natom 2.93836 10.45460 9.06873 Cu 0.0 0.0 -0.020449 -0.147844 -0.074972\natom 2.87856 5.04724 9.79968 Cu 0.0 0.0 0.021081 0.802603 -0.883295\natom 1.29372 0.50868 8.19919 Cu 0.0 0.0 0.102742 0.247199 0.257831\natom 5.13997 6.95690 10.71659 Cu 0.0 0.0 0.318380 -0.429011 0.569694\natom 9.21189 11.04964 4.94144 Cu 0.0 0.0 -0.226220 0.047172 -0.338081\natom 4.17990 5.48315 1.65625 Cu 0.0 0.0 -0.061149 0.024759 0.018456\natom 4.10194 0.86935 1.46185 Cu 0.0 0.0 -0.325118 -0.356689 0.351853\natom 8.58370 6.73929 4.48938 Cu 0.0 0.0 -0.183253 0.073806 -0.336752\natom 5.26307 11.59673 10.20705 Cu 0.0 0.0 0.019433 -0.355420 0.226874\natom 1.13195 5.80679 7.86158 Cu 0.0 0.0 -0.111944 0.087901 -0.238204\natom 3.31937 2.27542 9.37690 Cu 0.0 0.0 -0.379342 0.001606 -0.305208\natom 3.34483 7.75485 9.18163 Cu 0.0 0.0 0.229823 0.791373 -1.131988\natom 6.39482 9.67667 3.15210 Cu 0.0 0.0 -0.094336 -0.795504 -1.057292\natom 7.22236 3.07618 3.37057 Cu 0.0 0.0 -0.235709 0.757783 -0.201253\natom 13.81610 1.37747 2.41015 Cu 0.0 0.0 -0.421134 -0.441437 0.596880\natom 13.61863 6.95911 3.36775 Cu 0.0 0.0 0.023890 -0.090556 0.088628\natom 9.66897 10.87854 9.80118 Cu 0.0 0.0 -0.033376 -0.779259 -0.024728\natom 10.82688 4.33130 8.82018 Cu 0.0 0.0 0.025061 0.077835 -0.093269\natom 0.52093 2.93256 9.86635 Cu 0.0 0.0 -0.188157 0.007009 0.046775\natom 3.05650 7.20429 6.37008 Cu 0.0 0.0 0.120817 0.632245 0.914727\natom 5.20021 10.41570 0.87518 Cu 0.0 0.0 -0.188866 0.673383 -0.290560\natom 6.42686 4.58096 5.63885 Cu 0.0 0.0 -0.033889 0.762947 -0.354041\natom 7.36790 2.66841 6.96813 Cu 0.0 0.0 -0.012373 -0.662690 0.449303\natom -1.75746 8.94560 11.22149 Cu 0.0 0.0 -0.054235 0.048564 0.114417\natom 1.59161 9.16276 5.19623 Cu 0.0 0.0 0.020031 -0.301564 0.165598\natom 10.50996 3.65139 0.92879 Cu 0.0 0.0 0.046307 0.222299 -0.224030\natom 2.01792 2.44696 1.65061 Cu 0.0 0.0 -0.342256 0.024552 0.104635\natom 10.30682 8.44864 4.52417 Cu 0.0 0.0 0.305590 0.465815 -0.017841\natom 7.37748 10.13132 10.55358 Cu 0.0 0.0 -0.193255 -0.757234 0.590322\natom -2.71285 3.62703 10.24934 Cu 0.0 0.0 0.527769 -0.745936 -0.242669\natom -2.00328 1.53124 8.67936 Cu 0.0 0.0 -0.218742 -0.112512 -0.294307\natom 8.67784 6.86853 9.57287 Cu 0.0 0.0 0.367175 0.005611 0.281933\natom 11.50050 10.89754 3.55966 Cu 0.0 0.0 0.489069 -0.022825 0.280065\natom 0.89763 4.90137 2.64962 Cu 0.0 0.0 -0.158200 0.447650 -0.491001\nenergy -565.862799\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_84\nlattice 15.394732161 0.000000000 0.000000000\nlattice 0.000000000 11.999934213 0.000000000\nlattice -6.047786257 0.000000000 12.209928816\natom 9.61168 1.01608 10.42083 S 0.0 0.0 -1.191961 0.326660 -1.181596\natom -3.21463 7.13012 7.92824 S 0.0 0.0 0.049036 -0.759072 0.181961\natom -0.42418 11.01723 1.89660 S 0.0 0.0 0.333188 0.647869 -0.641060\natom 12.57968 4.81260 4.21805 S 0.0 0.0 -0.689337 0.705370 -0.234277\natom 12.37573 0.60830 4.48839 S 0.0 0.0 0.095115 0.347347 -0.081025\natom -0.23392 7.11563 2.18372 S 0.0 0.0 0.321971 -0.092889 -0.125810\natom -3.13570 10.97664 7.97003 S 0.0 0.0 -0.416872 0.419920 0.025070\natom 9.30709 5.19093 10.26152 S 0.0 0.0 -0.754127 -0.201431 -0.317495\natom 9.13516 1.37154 6.38042 S 0.0 0.0 -1.096006 -0.210231 0.119114\natom -2.70337 6.66340 12.17485 S 0.0 0.0 -0.157448 -0.296626 -0.315583\natom 0.52081 11.02950 6.12582 S 0.0 0.0 -0.366875 -0.419006 -0.118833\natom 5.95478 5.06273 12.20984 S 0.0 0.0 0.189358 -0.399059 0.431364\natom 12.27007 0.80807 0.08879 S 0.0 0.0 -0.045453 0.689615 -0.894263\natom 0.44020 7.23695 5.65654 S 0.0 0.0 -0.120498 -0.316167 -0.057735\natom -2.82652 11.02867 12.15304 S 0.0 0.0 0.059436 -0.688768 0.520918\natom 9.11293 5.20079 6.11113 S 0.0 0.0 -0.017723 -0.154378 -0.108366\natom 3.38699 1.08368 7.37498 S 0.0 0.0 0.973286 0.097585 0.088526\natom 2.92580 7.06587 10.95448 S 0.0 0.0 0.563369 0.009440 -0.487694\natom 6.34495 11.21156 4.60274 S 0.0 0.0 -0.026626 -0.041480 -0.333513\natom 6.42843 4.98838 1.35546 S 0.0 0.0 0.034401 -0.204238 0.527625\natom 6.50804 1.36580 1.36949 S 0.0 0.0 0.393739 0.075181 -0.528536\natom 6.08187 6.89875 4.87840 S 0.0 0.0 0.357849 0.233861 0.053863\natom 2.93210 11.31408 11.23341 S 0.0 0.0 0.558437 0.132660 -0.653574\natom 3.13237 5.27444 7.57536 S 0.0 0.0 0.451955 -0.465550 0.444521\natom -0.25369 1.08496 9.38773 S 0.0 0.0 0.075403 -0.259372 -0.621188\natom 6.34054 6.96441 8.61398 S 0.0 0.0 0.402595 -0.723001 0.756399\natom 9.44702 11.07522 2.60649 S 0.0 0.0 0.124143 -0.220298 0.690966\natom 2.72174 5.30293 3.64982 S 0.0 0.0 0.266566 0.028388 -0.153975\natom 2.60106 0.99820 3.39868 S 0.0 0.0 0.133698 0.036970 0.506408\natom 9.67221 7.04953 2.66653 S 0.0 0.0 0.663083 0.216520 -0.406805\natom 6.55951 10.81941 8.71656 S 0.0 0.0 0.888808 -0.578877 0.126432\natom -0.43056 5.03803 9.41733 S 0.0 0.0 -0.875998 0.186108 0.476104\natom 6.23491 2.85458 9.12792 S 0.0 0.0 -0.171363 -0.175101 -0.393890\natom 0.26889 9.09982 9.39944 S 0.0 0.0 -0.960259 -0.011127 0.730988\natom 3.33550 9.12756 3.25851 S 0.0 0.0 -0.476551 0.507590 0.573442\natom 9.77520 2.96453 2.59647 S 0.0 0.0 -0.566787 -0.098178 0.053217\natom 5.79508 2.94445 5.16220 S 0.0 0.0 -0.192775 0.225588 -0.442090\natom 6.39349 8.80687 0.95628 S 0.0 0.0 0.536297 0.033054 0.478046\natom 3.57897 9.37915 7.30478 S 0.0 0.0 -0.089353 -0.299949 -0.470851\natom 2.54131 2.93520 10.85817 S 0.0 0.0 0.548588 0.635996 0.557775\natom 0.11490 2.58780 5.99619 S 0.0 0.0 -0.279109 0.432643 0.237834\natom 12.07420 8.66439 0.11760 S 0.0 0.0 0.137315 0.465733 -0.244200\natom 9.11578 9.42753 6.08890 S 0.0 0.0 0.085813 -0.380959 0.423167\natom -3.06738 3.08427 11.82586 S 0.0 0.0 -0.476050 0.444938 -0.035933\natom -0.16711 2.91929 1.70250 S 0.0 0.0 0.112141 -0.369133 0.403277\natom 12.70125 8.95407 4.51622 S 0.0 0.0 -0.614318 -0.276546 0.371311\natom 9.74225 8.92619 10.84282 S 0.0 0.0 -1.202930 0.042308 0.276779\natom -3.20438 3.20878 7.65061 S 0.0 0.0 -0.289725 0.255052 -0.043827\natom 11.61231 2.69652 3.80240 Cu 0.0 0.0 0.391770 -0.054206 -0.012242\natom 1.41467 9.00327 2.21273 Cu 0.0 0.0 -0.693663 -0.090294 0.140010\natom -2.02004 9.24063 8.95087 Cu 0.0 0.0 -0.002940 0.062471 -0.095837\natom 8.47278 3.04012 9.76366 Cu 0.0 0.0 0.100954 0.077138 -0.004811\natom 5.55379 0.69555 8.27037 Cu 0.0 0.0 -0.295086 0.648668 0.173849\natom 0.98887 6.80797 9.65854 Cu 0.0 0.0 0.315449 0.420092 0.858395\natom 3.98611 11.29356 4.10338 Cu 0.0 0.0 -0.059508 -0.194572 -0.276054\natom 8.64481 4.91039 2.26137 Cu 0.0 0.0 -0.328978 0.165652 0.435556\natom 8.75433 1.02416 1.86991 Cu 0.0 0.0 -0.162032 0.422745 0.038880\natom 4.00536 7.36720 4.38927 Cu 0.0 0.0 -0.419183 -0.459053 -0.186304\natom 0.88893 11.18860 10.19854 Cu 0.0 0.0 0.031607 0.013853 -0.013245\natom 5.40073 4.66855 8.09789 Cu 0.0 0.0 -0.310233 0.364814 0.004740\natom 4.87332 3.39932 0.69978 Cu 0.0 0.0 0.290394 -0.353057 0.154532\natom 7.09795 8.93120 5.14333 Cu 0.0 0.0 -0.138698 0.057681 -0.002073\natom 3.70509 9.16447 11.39834 Cu 0.0 0.0 0.437228 0.207239 0.318415\natom 2.14836 3.16801 6.88630 Cu 0.0 0.0 0.123592 0.057810 0.339965\natom -4.01817 0.82592 11.54874 Cu 0.0 0.0 1.075584 0.120868 0.176741\natom 9.89746 7.31258 6.48309 Cu 0.0 0.0 -0.066838 0.070502 0.539386\natom 12.83146 10.85639 0.92260 Cu 0.0 0.0 -0.084247 -1.064775 -0.010222\natom -0.85835 5.29316 5.27531 Cu 0.0 0.0 0.266740 0.088528 0.150937\natom -0.96231 0.67333 5.44880 Cu 0.0 0.0 -0.125972 -0.190869 -0.229224\natom 13.27310 6.79948 0.98173 Cu 0.0 0.0 0.313132 0.102051 -0.307492\natom 10.35055 11.21868 6.73618 Cu 0.0 0.0 -0.021537 0.094407 0.324178\natom -4.07327 5.24861 11.02907 Cu 0.0 0.0 0.502192 -0.418966 0.619331\natom 14.59142 1.31024 0.24868 Cu 0.0 0.0 -0.068794 0.045746 -0.445258\natom -1.74385 7.33635 6.30245 Cu 0.0 0.0 -0.103437 0.578930 -0.038327\natom -3.35489 8.70890 11.45086 Cu 0.0 0.0 -0.023471 0.541481 -0.089149\natom 11.31328 4.92819 6.00106 Cu 0.0 0.0 0.124277 -0.354520 0.331290\natom 11.25926 1.71899 6.14910 Cu 0.0 0.0 0.576058 0.153646 0.284591\natom 0.98756 7.18957 0.34767 Cu 0.0 0.0 0.148718 -0.153860 -0.137073\natom -1.89896 10.08005 6.27442 Cu 0.0 0.0 0.269953 0.252167 0.119336\natom 14.82866 4.39039 0.09180 Cu 0.0 0.0 -0.340573 0.056927 -0.147375\natom 8.87065 3.15774 4.77775 Cu 0.0 0.0 0.162618 -0.061351 -0.073613\natom 4.26291 8.24195 1.31598 Cu 0.0 0.0 -0.565867 -0.359922 0.446488\natom 0.22021 8.94420 7.17875 Cu 0.0 0.0 -0.009841 -0.048517 -0.177917\natom 6.40085 2.98501 11.36531 Cu 0.0 0.0 -0.043523 0.040280 0.578155\natom 0.68234 1.70256 11.28986 Cu 0.0 0.0 -0.186826 -0.000683 0.598754\natom 5.26580 7.81845 6.92142 Cu 0.0 0.0 -0.445676 0.563885 -0.652128\natom 7.95813 10.36362 0.83491 Cu 0.0 0.0 0.260321 0.279152 0.286081\natom 4.02707 4.53549 5.72216 Cu 0.0 0.0 0.303080 -0.344855 -0.551618\natom 4.88474 0.93701 5.70079 Cu 0.0 0.0 0.230608 -0.147864 0.000888\natom 8.40394 7.67556 0.92211 Cu 0.0 0.0 0.254484 -0.067652 -0.202682\natom 5.45731 10.49026 6.43732 Cu 0.0 0.0 -0.319092 -0.150872 0.710175\natom 1.92198 5.32701 11.97658 Cu 0.0 0.0 -0.166622 -0.121822 -0.420830\natom -1.69666 2.70600 10.16369 Cu 0.0 0.0 0.358334 -0.239200 -0.109338\natom 7.73517 8.65378 7.88721 Cu 0.0 0.0 0.014459 0.573296 -0.606470\natom 10.68735 9.34588 1.74641 Cu 0.0 0.0 -0.439726 -0.201238 -0.448797\natom 3.64684 3.23269 3.42151 Cu 0.0 0.0 -0.105829 0.453683 0.248434\natom 8.16102 0.46510 8.73219 Cu 0.0 0.0 0.192188 -0.096106 -0.270723\natom -1.85848 6.99743 9.97666 Cu 0.0 0.0 -0.218796 -0.500547 0.105423\natom 0.44296 10.99190 3.89648 Cu 0.0 0.0 0.053204 -0.031752 0.450723\natom 11.40933 5.64462 2.13470 Cu 0.0 0.0 -0.351827 -0.331935 0.076030\natom 11.37718 0.81774 2.06734 Cu 0.0 0.0 -0.611435 -0.193327 0.366000\natom 1.24707 3.95096 4.76029 Cu 0.0 0.0 0.324235 0.241591 -0.679982\natom -1.73266 11.65475 10.37157 Cu 0.0 0.0 0.212860 0.380882 -0.393675\natom 7.92981 5.30116 8.00521 Cu 0.0 0.0 -0.074729 0.092064 0.136868\natom -4.37850 2.67262 9.46103 Cu 0.0 0.0 0.057103 -0.274483 0.202197\natom 10.74864 8.24225 9.06354 Cu 0.0 0.0 -0.023471 -0.253329 -0.343244\natom -1.34377 9.25254 2.80510 Cu 0.0 0.0 0.066385 -0.309898 -0.212381\natom -1.25306 3.50180 3.61142 Cu 0.0 0.0 0.828273 -0.763521 -0.530900\natom 4.64858 1.24230 2.50442 Cu 0.0 0.0 -0.291803 0.025681 0.328332\natom 6.53044 7.12313 2.58618 Cu 0.0 0.0 -0.404324 -0.176835 0.114015\natom 3.42063 11.23257 8.81961 Cu 0.0 0.0 -0.139718 -0.054750 0.343706\natom 1.61485 4.27536 9.16077 Cu 0.0 0.0 0.642162 0.094405 0.089876\natom 1.26903 0.78491 7.43404 Cu 0.0 0.0 -1.098981 -0.221546 0.289553\natom 5.44186 6.51461 10.64828 Cu 0.0 0.0 -0.234590 0.410853 -0.301251\natom 8.72291 11.76178 4.86728 Cu 0.0 0.0 -0.175245 -0.098272 -0.519528\natom 4.27688 5.51884 1.91924 Cu 0.0 0.0 -0.221023 0.180796 0.180334\natom 1.77230 11.62345 1.70957 Cu 0.0 0.0 0.079069 -0.087724 -0.045952\natom 8.38154 6.62650 4.33873 Cu 0.0 0.0 -0.248326 -0.078102 0.530087\natom 5.44621 11.15069 10.67735 Cu 0.0 0.0 -0.260829 0.197381 0.016748\natom 0.25174 6.00863 7.54331 Cu 0.0 0.0 -0.473189 -0.146569 -0.892481\natom 3.67802 2.75104 8.87314 Cu 0.0 0.0 0.089110 -0.140927 0.371747\natom 2.51073 8.84239 9.22448 Cu 0.0 0.0 0.304691 -0.146943 -0.082301\natom 5.64252 9.90858 2.81814 Cu 0.0 0.0 0.513423 -0.142304 0.173443\natom 6.39122 3.17193 2.99785 Cu 0.0 0.0 -0.031973 0.226428 -0.106016\natom 13.78888 1.08302 2.77159 Cu 0.0 0.0 0.380818 -0.054563 -0.043082\natom 13.12264 6.93811 3.58588 Cu 0.0 0.0 0.102637 -0.131678 0.110528\natom -4.66009 10.58928 9.71670 Cu 0.0 0.0 0.270843 0.740876 -0.231055\natom 10.75300 5.17700 8.48767 Cu 0.0 0.0 0.320537 0.022315 -0.106267\natom 4.11156 1.42512 11.60725 Cu 0.0 0.0 -0.071191 -0.081941 -0.092444\natom 2.32526 7.33053 7.02235 Cu 0.0 0.0 0.427606 0.281319 -0.144109\natom 5.26791 11.54654 0.92695 Cu 0.0 0.0 0.083201 -0.202086 -0.734203\natom 6.67048 4.91449 5.73851 Cu 0.0 0.0 0.114596 -0.072935 -0.046294\natom 7.31983 2.84405 7.11799 Cu 0.0 0.0 0.238880 -0.435311 -0.009822\natom -0.99607 9.51313 11.51918 Cu 0.0 0.0 0.286827 0.011185 -0.967809\natom 2.19299 9.57686 5.32161 Cu 0.0 0.0 0.241050 0.033235 0.022089\natom 9.93250 3.87375 0.41602 Cu 0.0 0.0 0.481727 -0.314361 -0.455733\natom 2.25099 2.16311 1.55201 Cu 0.0 0.0 -0.161767 0.376937 -0.281467\natom 10.36062 8.54543 4.32968 Cu 0.0 0.0 0.069128 -0.029650 -0.123427\natom 7.34497 9.46663 10.56599 Cu 0.0 0.0 0.041764 -0.020438 0.077561\natom -0.98405 3.73778 7.63702 Cu 0.0 0.0 0.162342 -0.121758 -0.145897\natom -2.40276 1.09063 8.20590 Cu 0.0 0.0 -0.080006 0.099818 0.070596\natom 8.38212 7.22719 9.70741 Cu 0.0 0.0 0.218579 0.053630 0.432589\natom 11.63611 10.66180 3.47400 Cu 0.0 0.0 -0.056787 0.347671 0.309465\natom 0.79475 4.80215 2.38119 Cu 0.0 0.0 0.125964 0.706002 0.158111\nenergy -566.729768\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/configuration-sets/input.data.DMABN",
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    "path": "examples/configuration-sets/input.data.Ethylbenzene",
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  },
  {
    "path": "examples/configuration-sets/input.data.H2O_RPBE-D3",
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0.002321756\natom    19.791306123    0.403381099   16.673060243   H    0.135466030    0.000000000    0.007300874   -0.001511841   -0.002631261\natom     4.387622667    5.349905608    5.734684236   O   -0.244070880    0.000000000    0.006036707   -0.002395292   -0.007121226\natom     5.561779896    4.386347101    4.687272878   H    0.132242000    0.000000000   -0.001600843   -0.006100575    0.002766324\natom     4.544428424    7.058727042    5.033047544   H    0.105441580    0.000000000   -0.007509432    0.001400767    0.002801820\natom    12.207452327   13.810638028    0.785451749   O   -0.299231180    0.000000000    0.008830351    0.043755567   -0.020647161\natom    12.237085134   12.043310650    0.901348698   H    0.099587150    0.000000000   -0.001848726   -0.040808947    0.003856916\natom    12.980288259   14.130026437   23.097774469   H    0.108720700    0.000000000   -0.009686812   -0.004306622    0.018477729\natom    10.994413967   10.449928852   16.407704794   O   -0.251217290    0.000000000   -0.006370888    0.056247648   -0.031058801\natom     9.763067934   11.451480318   17.376546978   H    0.148892550    0.000000000    0.006833630   -0.021155921   -0.000205670\natom    11.408230138    8.937399018   17.185444568   H    0.136118080    0.000000000    0.001795583   -0.041155529    0.024493603\natom    14.170564858   13.888046911   19.492670694   O   -0.251800560    0.000000000    0.004239013    0.073946008    0.020920695\natom    13.165891564   15.350565123   18.663849714   H    0.126872490    0.000000000    0.018369262   -0.030052313    0.013865349\natom    13.813117350   12.390153011   18.673207641   H    0.120968470    0.000000000   -0.021834018   -0.040411280   -0.032788753\natom     3.697932828   21.117508886   15.038060989   O   -0.265370070    0.000000000   -0.002942453   -0.001427849    0.018483596\natom     3.095574827   20.348189736   13.502982934   H    0.107759500    0.000000000   -0.002732177   -0.006999465   -0.011219806\natom     4.779540683   22.476902813   14.527774261   H    0.138662860    0.000000000    0.004746171    0.007331837   -0.004406990\natom     3.457032335   12.750752584   23.404722805   O   -0.228693350    0.000000000    0.123278715   -0.099684528   -0.046435375\natom     2.211953656   13.787133606   23.479659925   H    0.114599780    0.000000000   -0.126789826    0.100662559    0.021674136\natom     4.049690368   11.984079051    0.898181516   H    0.116759010    0.000000000   -0.001963257   -0.003975942    0.026550270\natom    16.315367070   14.145497631    4.688686394   O   -0.257095370    0.000000000    0.019415748    0.011961034    0.015573235\natom    16.879503455   12.564315909    3.976306604   H    0.112639780    0.000000000    0.007203556   -0.010557103   -0.005524374\natom    14.604502841   14.302482912    4.175823968   H    0.123197200    0.000000000   -0.022297483    0.002539158   -0.013545090\natom     4.398802291   10.339742657    3.897875380   O   -0.202867670    0.000000000   -0.007595701    0.000169458   -0.002835816\natom     6.013579577   10.506359876    4.753392532   H    0.145063750    0.000000000   -0.001970558    0.010961620    0.007571230\natom     3.118151394   11.375205272    4.806584564   H    0.128255580    0.000000000    0.012295645   -0.006476487    0.003924093\natom    10.594691379    0.663929082   12.934001289   O   -0.229582380    0.000000000   -0.005718461   -0.009204961    0.016130566\natom     9.810114574    2.351203851   12.631886873   H    0.130965550    0.000000000    0.002048060   -0.018347172    0.012319236\natom    10.477305325    0.034272087   14.740476249   H    0.133202620    0.000000000   -0.006074826    0.025088333   -0.020766319\natom    12.271704930    7.075965131    7.185826293   O   -0.214138270    0.000000000    0.014703364   -0.037033285   -0.040099260\natom    13.568972196    5.966432781    6.289377656   H    0.162923180    0.000000000   -0.028438357    0.015427135    0.020083631\natom    13.309686551    7.858690004    8.414967015   H    0.125455030    0.000000000    0.011234519    0.017085563    0.021636987\natom     0.372695714   13.548797472    5.926536868   O   -0.268084480    0.000000000    0.007614420   -0.073404173   -0.063264501\natom     0.382902129   14.703288314    7.165780070   H    0.127809330    0.000000000   -0.000950585    0.059556028    0.068283917\natom     0.966755925   14.552265121    4.457181624   H    0.107279650    0.000000000   -0.012777661    0.009268460   -0.000933885\natom    17.466446954   19.223044463   17.927731175   O   -0.219763310    0.000000000   -0.035165353   -0.017553463   -0.018934327\natom    18.940386676   18.203939325   17.931045756   H    0.127674450    0.000000000    0.032197931   -0.004780277    0.005456355\natom    16.507728038   18.239067458   16.615179798   H    0.142510840    0.000000000   -0.002326973    0.017481994    0.012448661\natom    14.013464304   16.394244270   13.426133411   O   -0.284574960    0.000000000    0.035938662    0.007538260   -0.048171816\natom    12.330477326   16.976378414   13.002709868   H    0.105804360    0.000000000   -0.008450623    0.005466588    0.004089666\natom    15.005799572   16.925270751   11.745075844   H    0.106969100    0.000000000   -0.019060852   -0.013019411    0.044592581\natom     7.862480796    4.636206789   22.996949981   O   -0.255211000    0.000000000    0.026019058    0.004901961   -0.000568282\natom     6.607577427    4.184068847   21.690317228   H    0.104519940    0.000000000    0.008125767   -0.006959821   -0.003212454\natom     9.649892191    4.419026148   22.306113077   H    0.118804020    0.000000000   -0.031718409   -0.002728319    0.010893469\natom     3.798515431    8.049864223   11.577092353   O   -0.233009840    0.000000000   -0.021582397   -0.005949985   -0.012554795\natom     4.831649902    9.433934203   11.065106760   H    0.130163010    0.000000000    0.017887414    0.015747756   -0.003688555\natom     2.260784199    8.320520355   10.505921459   H    0.115764620    0.000000000    0.007732114   -0.009542268    0.015826322\natom    12.995256786    2.891686525   22.201032925   O   -0.255490060    0.000000000   -0.004915353    0.019472311   -0.001635838\natom    14.491852443    4.010641052   22.317041368   H    0.117038160    0.000000000   -0.003270477   -0.018395304   -0.003528621\natom    13.429871291    1.114213203   22.359666047   H    0.108781130    0.000000000    0.011282327   -0.001145895    0.002319521\natom     2.512601644   20.398749379   20.640606073   O   -0.224422270    0.000000000   -0.021598908    0.009665119    0.051877148\natom     1.537532810   21.905054452   21.392409345   H    0.148959210    0.000000000    0.024157839   -0.031036950   -0.030643998\natom     2.900545564   20.619692466   18.913945617   H    0.123358800    0.000000000    0.000772829    0.021377620   -0.029067107\natom     5.744871754   16.617566523   20.785400726   O   -0.265656930    0.000000000   -0.032497393    0.020526624    0.019299565\natom     4.262486843   18.003063247   20.988257237   H    0.099385010    0.000000000    0.038336244   -0.026808230    0.000017966\natom     5.294918335   15.358585124   22.119375937   H    0.098640670    0.000000000    0.006613032    0.008209277   -0.013429656\natom    17.847113537    1.659677197    7.261604340   O   -0.214984170    0.000000000    0.006018312   -0.022409254    0.003621639\natom    18.987064820    0.224034680    6.782637945   H    0.134801280    0.000000000   -0.013345731    0.012413327    0.012346459\natom    17.213508902    1.225867715    9.010954747   H    0.120488240    0.000000000   -0.000443941    0.002779306   -0.013526258\natom     0.223231546    4.153421256    1.485365010   O   -0.284149710    0.000000000   -0.016138645    0.008676852    0.024731263\natom    22.710372900    4.079060503    2.742248813   H    0.105341390    0.000000000    0.039423346    0.012173922   -0.023123038\natom     1.652651192    5.001182969    2.395013389   H    0.117989360    0.000000000   -0.023819333   -0.014915583   -0.003918404\natom    18.029065889    5.395499049   22.331535573   O   -0.232616100    0.000000000   -0.022435825   -0.041986031    0.019777229\natom    18.450206642    6.009076358   20.698998634   H    0.117402890    0.000000000    0.010969888    0.018577415   -0.028888712\natom    18.471749528    6.543217109   23.632648433   H    0.122965160    0.000000000    0.008555544    0.023492454    0.010076612\natom     9.730995489   -0.013755322   18.655527357   O   -0.260468440    0.000000000    0.033447936   -0.047525024   -0.017241120\natom    10.958809623    1.192342071   19.181358978   H    0.127148600    0.000000000    0.001410520    0.021472916    0.006833322\natom     8.059414903    0.566851923   18.625879432   H    0.119766210    0.000000000   -0.033795515    0.025211959    0.007633086\natom     5.720611440   23.314163314    9.722983047   O   -0.231630130    0.000000000    0.008590611   -0.010936445   -0.025443175\natom     6.834575199    0.786704638    9.364550991   H    0.130111070    0.000000000   -0.010659177   -0.018642575    0.001906309\natom     6.037573440   21.935577321    8.393439246   H    0.130229060    0.000000000   -0.004288229    0.030206013    0.023949980\natom     9.845218141   19.848952241    1.377688373   O   -0.231982490    0.000000000    0.047210910    0.050634028    0.057109462\natom     8.964032828   21.443191975    1.821177035   H    0.130585310    0.000000000   -0.001359815   -0.006723989   -0.005653620\natom     8.864534929   18.936979498    0.325325931   H    0.140456380    0.000000000   -0.053312141   -0.042279623   -0.051814244\natom    21.486183262    2.087957338   12.058619328   O   -0.245742770    0.000000000   -0.018336922    0.012948985   -0.040170727\natom    20.067351756    2.869512469   10.984447548   H    0.132828300    0.000000000    0.028333925   -0.013530492    0.030219120\natom    22.734213694    1.753487019   10.673217090   H    0.099760430    0.000000000   -0.005192035    0.002432708    0.011480438\natom    -0.218456207   22.514791837    3.828822870   O   -0.233891290    0.000000000    0.001999487    0.001056955    0.002002219\natom    22.977963895   23.403316849    2.478210504   H    0.123135500    0.000000000   -0.006368839    0.004516237   -0.013166446\natom     0.169763614   -0.170292738    5.058420906   H    0.104258450    0.000000000    0.006641123   -0.000339229    0.001710832\natom    22.768355390   15.179884991   22.329029795   O   -0.238086150    0.000000000   -0.046086010   -0.025235881    0.005743850\natom    21.434125066   15.631748923   -0.333185305   H    0.126220700    0.000000000    0.031123799   -0.009001222   -0.035124767\natom    21.989842718   13.702640137   21.289668674   H    0.119659510    0.000000000    0.013004599    0.035317132    0.026225131\natom    12.222509671    8.189955346    1.618074860   O   -0.247919730    0.000000000   -0.001797123    0.017574523   -0.067071366\natom    12.278849988    7.760085945    3.281828197   H    0.111233780    0.000000000   -0.004235384   -0.012471568    0.070548691\natom    13.880380289    7.710926590    1.035681823   H    0.141482170    0.000000000    0.006536703    0.000642119   -0.006764662\natom    13.661907075   10.667631057   11.112100488   O   -0.216001700    0.000000000   -0.037279496   -0.013776615    0.034916697\natom    14.124858034   12.345145386   11.672595370   H    0.133272180    0.000000000    0.003591734    0.013021971    0.000895419\natom    12.435880622   10.173618657   12.581225186   H    0.147421220    0.000000000    0.029632111    0.008032176   -0.031477484\natom    17.486330661   17.032057327    9.295375649   O   -0.235087510    0.000000000   -0.006875504   -0.012809861   -0.043019615\natom    16.911783770   16.107704983    7.688512539   H    0.110665490    0.000000000    0.006713966    0.011433370    0.028267991\natom    18.328113278   18.516190235    8.528021815   H    0.118898150    0.000000000   -0.000175840   -0.004542786    0.012591957\natom     4.935770073   18.663509563    6.368200054   O   -0.194094220    0.000000000    0.031139053   -0.066276697    0.021098669\natom     6.518835853   17.598527525    5.812888693   H    0.156894820    0.000000000   -0.042755679    0.033516151    0.011475343\natom     4.178872098   17.417123193    7.699892475   H    0.137280880    0.000000000    0.015711127    0.037753788   -0.030393813\natom    21.151675148   20.879473220    7.686178727   O   -0.248140030    0.000000000   -0.009994913   -0.003084252    0.015181890\natom    21.725161902   21.081677775    5.962589077   H    0.096696550    0.000000000    0.004375907    0.001697312   -0.018251199\natom    22.673568579   21.355735416    8.583993635   H    0.139564520    0.000000000   -0.002909430   -0.001404868    0.006677838\natom    19.507253717   12.301401988   18.501302967   O   -0.199717660    0.000000000   -0.028410932   -0.035128726    0.043667183\natom    19.776549245   13.758948329   17.594513745   H    0.142371980    0.000000000    0.012693146    0.047711282   -0.031771675\natom    17.867647309   12.681150163   19.378767407   H    0.141514070    0.000000000    0.014688099   -0.002133776   -0.011109509\natom    23.134797998   17.370023640   17.326635511   O   -0.251377170    0.000000000   -0.000268730   -0.000574628   -0.003573364\natom    23.309537263   17.766571487   19.122904057   H    0.118237060    0.000000000    0.005638293   -0.001455468   -0.001185792\natom     0.463480083   18.316502796   16.477809882   H    0.138644360    0.000000000   -0.009964426   -0.001923402    0.004419419\natom     7.198349513    9.467121587   20.207068712   O   -0.243428280    0.000000000    0.009787410   -0.009154114    0.016239349\natom     7.841261053    8.491977165   21.715395794   H    0.127971510    0.000000000   -0.015877818    0.012471507   -0.019846659\natom     5.641732350   10.325405299   20.696485297   H    0.130413120    0.000000000    0.003877775    0.000013170    0.004937889\nenergy   -4900.14395256\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/configuration-sets/input.data.LJ",
    "content": "begin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.38564065E+01  -1.38564065E+01  -1.38564065E+01\natom   5.77350269E-01   5.77350269E-01   5.77350269E-01 Ne   0.00000000E+00   0.00000000E+00   1.38564065E+01   1.38564065E+01   1.38564065E+01\nenergy   0.00000000E+00\ncomment r =   1.00000000E+00, E =   0.00000000E+00, dEdr =  -2.40000000E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.14260918E+01  -1.14260918E+01  -1.14260918E+01\natom   5.83123772E-01   5.83123772E-01   5.83123772E-01 Ne   0.00000000E+00   0.00000000E+00   1.14260918E+01   1.14260918E+01   1.14260918E+01\nenergy  -2.18384040E-01\ncomment r =   1.01000000E+00, E =  -2.18384040E-01, dEdr =  -1.97905715E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -9.36007007E+00  -9.36007007E+00  -9.36007007E+00\natom   5.88897275E-01   5.88897275E-01   5.88897275E-01 Ne   0.00000000E+00   0.00000000E+00   9.36007007E+00   9.36007007E+00   9.36007007E+00\nenergy  -3.97912826E-01\ncomment r =   1.02000000E+00, E =  -3.97912826E-01, dEdr =  -1.62121169E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -7.60455062E+00  -7.60455062E+00  -7.60455062E+00\natom   5.94670777E-01   5.94670777E-01   5.94670777E-01 Ne   0.00000000E+00   0.00000000E+00   7.60455062E+00   7.60455062E+00   7.60455062E+00\nenergy  -5.44417506E-01\ncomment r =   1.03000000E+00, E =  -5.44417506E-01, dEdr =  -1.31714680E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -6.11386720E+00  -6.11386720E+00  -6.11386720E+00\natom   6.00444280E-01   6.00444280E-01   6.00444280E-01 Ne   0.00000000E+00   0.00000000E+00   6.11386720E+00   6.11386720E+00   6.11386720E+00\nenergy  -6.62869905E-01\ncomment r =   1.04000000E+00, E =  -6.62869905E-01, dEdr =  -1.05895286E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -4.84920700E+00  -4.84920700E+00  -4.84920700E+00\natom   6.06217783E-01   6.06217783E-01   6.06217783E-01 Ne   0.00000000E+00   0.00000000E+00   4.84920700E+00   4.84920700E+00   4.84920700E+00\nenergy  -7.57511914E-01\ncomment r =   1.05000000E+00, E =  -7.57511914E-01, dEdr =  -8.39907291E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -3.77754643E+00  -3.77754643E+00  -3.77754643E+00\natom   6.11991285E-01   6.11991285E-01   6.11991285E-01 Ne   0.00000000E+00   0.00000000E+00   3.77754643E+00   3.77754643E+00   3.77754643E+00\nenergy  -8.31964707E-01\ncomment r =   1.06000000E+00, E =  -8.31964707E-01, dEdr =  -6.54290234E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -2.87075857E+00  -2.87075857E+00  -2.87075857E+00\natom   6.17764788E-01   6.17764788E-01   6.17764788E-01 Ne   0.00000000E+00   0.00000000E+00   2.87075857E+00   2.87075857E+00   2.87075857E+00\nenergy  -8.89321058E-01\ncomment r =   1.07000000E+00, E =  -8.89321058E-01, dEdr =  -4.97229969E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -2.10486372E+00  -2.10486372E+00  -2.10486372E+00\natom   6.23538291E-01   6.23538291E-01   6.23538291E-01 Ne   0.00000000E+00   0.00000000E+00   2.10486372E+00   2.10486372E+00   2.10486372E+00\nenergy  -9.32223473E-01\ncomment r =   1.08000000E+00, E =  -9.32223473E-01, dEdr =  -3.64573090E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.45939898E+00  -1.45939898E+00  -1.45939898E+00\natom   6.29311793E-01   6.29311793E-01   6.29311793E-01 Ne   0.00000000E+00   0.00000000E+00   1.45939898E+00   1.45939898E+00   1.45939898E+00\nenergy  -9.62930407E-01\ncomment r =   1.09000000E+00, E =  -9.62930407E-01, dEdr =  -2.52775317E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -9.16887301E-01  -9.16887301E-01  -9.16887301E-01\natom   6.35085296E-01   6.35085296E-01   6.35085296E-01 Ne   0.00000000E+00   0.00000000E+00   9.16887301E-01   9.16887301E-01   9.16887301E-01\nenergy  -9.83372449E-01\ncomment r =   1.10000000E+00, E =  -9.83372449E-01, dEdr =  -1.58809539E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -4.62389671E-01  -4.62389671E-01  -4.62389671E-01\natom   6.40858799E-01   6.40858799E-01   6.40858799E-01 Ne   0.00000000E+00   0.00000000E+00   4.62389671E-01   4.62389671E-01   4.62389671E-01\nenergy  -9.95200050E-01\ncomment r =   1.11000000E+00, E =  -9.95200050E-01, dEdr =  -8.00882403E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -8.31268676E-02  -8.31268676E-02  -8.31268676E-02\natom   6.46632301E-01   6.46632301E-01   6.46632301E-01 Ne   0.00000000E+00   0.00000000E+00   8.31268676E-02   8.31268676E-02   8.31268676E-02\nenergy  -9.99824113E-01\ncomment r =   1.12000000E+00, E =  -9.99824113E-01, dEdr =  -1.43979958E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.31840388E-01   2.31840388E-01   2.31840388E-01\natom   6.52405804E-01   6.52405804E-01   6.52405804E-01 Ne   0.00000000E+00   0.00000000E+00  -2.31840388E-01  -2.31840388E-01  -2.31840388E-01\nenergy  -9.98450559E-01\ncomment r =   1.13000000E+00, E =  -9.98450559E-01, dEdr =   4.01559331E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.91882287E-01   4.91882287E-01   4.91882287E-01\natom   6.58179307E-01   6.58179307E-01   6.58179307E-01 Ne   0.00000000E+00   0.00000000E+00  -4.91882287E-01  -4.91882287E-01  -4.91882287E-01\nenergy  -9.92109781E-01\ncomment r =   1.14000000E+00, E =  -9.92109781E-01, dEdr =   8.51965112E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.05029571E-01   7.05029571E-01   7.05029571E-01\natom   6.63952810E-01   6.63952810E-01   6.63952810E-01 Ne   0.00000000E+00   0.00000000E+00  -7.05029571E-01  -7.05029571E-01  -7.05029571E-01\nenergy  -9.81681783E-01\ncomment r =   1.15000000E+00, E =  -9.81681783E-01, dEdr =   1.22114704E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.78168464E-01   8.78168464E-01   8.78168464E-01\natom   6.69726312E-01   6.69726312E-01   6.69726312E-01 Ne   0.00000000E+00   0.00000000E+00  -8.78168464E-01  -8.78168464E-01  -8.78168464E-01\nenergy  -9.67917641E-01\ncomment r =   1.16000000E+00, E =  -9.67917641E-01, dEdr =   1.52103240E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.01720634E+00   1.01720634E+00   1.01720634E+00\natom   6.75499815E-01   6.75499815E-01   6.75499815E-01 Ne   0.00000000E+00   0.00000000E+00  -1.01720634E+00  -1.01720634E+00  -1.01720634E+00\nenergy  -9.51457857E-01\ncomment r =   1.17000000E+00, E =  -9.51457857E-01, dEdr =   1.76185306E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.12721266E+00   1.12721266E+00   1.12721266E+00\natom   6.81273318E-01   6.81273318E-01   6.81273318E-01 Ne   0.00000000E+00   0.00000000E+00  -1.12721266E+00  -1.12721266E+00  -1.12721266E+00\nenergy  -9.32848056E-01\ncomment r =   1.18000000E+00, E =  -9.32848056E-01, dEdr =   1.95238960E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.21253907E+00   1.21253907E+00   1.21253907E+00\natom   6.87046820E-01   6.87046820E-01   6.87046820E-01 Ne   0.00000000E+00   0.00000000E+00  -1.21253907E+00  -1.21253907E+00  -1.21253907E+00\nenergy  -9.12552436E-01\ncomment r =   1.19000000E+00, E =  -9.12552436E-01, dEdr =   2.10017928E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.27692175E+00   1.27692175E+00   1.27692175E+00\natom   6.92820323E-01   6.92820323E-01   6.92820323E-01 Ne   0.00000000E+00   0.00000000E+00  -1.27692175E+00  -1.27692175E+00  -1.27692175E+00\nenergy  -8.90965288E-01\ncomment r =   1.20000000E+00, E =  -8.90965288E-01, dEdr =   2.21169334E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.32356877E+00   1.32356877E+00   1.32356877E+00\natom   6.98593826E-01   6.98593826E-01   6.98593826E-01 Ne   0.00000000E+00   0.00000000E+00  -1.32356877E+00  -1.32356877E+00  -1.32356877E+00\nenergy  -8.68420879E-01\ncomment r =   1.21000000E+00, E =  -8.68420879E-01, dEdr =   2.29248836E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.35523484E+00   1.35523484E+00   1.35523484E+00\natom   7.04367328E-01   7.04367328E-01   7.04367328E-01 Ne   0.00000000E+00   0.00000000E+00  -1.35523484E+00  -1.35523484E+00  -1.35523484E+00\nenergy  -8.45201938E-01\ncomment r =   1.22000000E+00, E =  -8.45201938E-01, dEdr =   2.34733561E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.37428509E+00   1.37428509E+00   1.37428509E+00\natom   7.10140831E-01   7.10140831E-01   7.10140831E-01 Ne   0.00000000E+00   0.00000000E+00  -1.37428509E+00  -1.37428509E+00  -1.37428509E+00\nenergy  -8.21546940E-01\ncomment r =   1.23000000E+00, E =  -8.21546940E-01, dEdr =   2.38033160E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38274975E+00   1.38274975E+00   1.38274975E+00\natom   7.15914334E-01   7.15914334E-01   7.15914334E-01 Ne   0.00000000E+00   0.00000000E+00  -1.38274975E+00  -1.38274975E+00  -1.38274975E+00\nenergy  -7.97656367E-01\ncomment r =   1.24000000E+00, E =  -7.97656367E-01, dEdr =   2.39499283E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38237105E+00   1.38237105E+00   1.38237105E+00\natom   7.21687836E-01   7.21687836E-01   7.21687836E-01 Ne   0.00000000E+00   0.00000000E+00  -1.38237105E+00  -1.38237105E+00  -1.38237105E+00\nenergy  -7.73698093E-01\ncomment r =   1.25000000E+00, E =  -7.73698093E-01, dEdr =   2.39433689E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.37464330E+00   1.37464330E+00   1.37464330E+00\natom   7.27461339E-01   7.27461339E-01   7.27461339E-01 Ne   0.00000000E+00   0.00000000E+00  -1.37464330E+00  -1.37464330E+00  -1.37464330E+00\nenergy  -7.49812018E-01\ncomment r =   1.26000000E+00, E =  -7.49812018E-01, dEdr =   2.38095204E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.36084745E+00   1.36084745E+00   1.36084745E+00\natom   7.33234842E-01   7.33234842E-01   7.33234842E-01 Ne   0.00000000E+00   0.00000000E+00  -1.36084745E+00  -1.36084745E+00  -1.36084745E+00\nenergy  -7.26114051E-01\ncomment r =   1.27000000E+00, E =  -7.26114051E-01, dEdr =   2.35705692E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.34208064E+00   1.34208064E+00   1.34208064E+00\natom   7.39008345E-01   7.39008345E-01   7.39008345E-01 Ne   0.00000000E+00   0.00000000E+00  -1.34208064E+00  -1.34208064E+00  -1.34208064E+00\nenergy  -7.02699549E-01\ncomment r =   1.28000000E+00, E =  -7.02699549E-01, dEdr =   2.32455185E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.31928169E+00   1.31928169E+00   1.31928169E+00\natom   7.44781847E-01   7.44781847E-01   7.44781847E-01 Ne   0.00000000E+00   0.00000000E+00  -1.31928169E+00  -1.31928169E+00  -1.31928169E+00\nenergy  -6.79646267E-01\ncomment r =   1.29000000E+00, E =  -6.79646267E-01, dEdr =   2.28506292E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.29325302E+00   1.29325302E+00   1.29325302E+00\natom   7.50555350E-01   7.50555350E-01   7.50555350E-01 Ne   0.00000000E+00   0.00000000E+00  -1.29325302E+00  -1.29325302E+00  -1.29325302E+00\nenergy  -6.57016914E-01\ncomment r =   1.30000000E+00, E =  -6.57016914E-01, dEdr =   2.23997993E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.26467942E+00   1.26467942E+00   1.26467942E+00\natom   7.56328853E-01   7.56328853E-01   7.56328853E-01 Ne   0.00000000E+00   0.00000000E+00  -1.26467942E+00  -1.26467942E+00  -1.26467942E+00\nenergy  -6.34861342E-01\ncomment r =   1.31000000E+00, E =  -6.34861342E-01, dEdr =   2.19048901E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.23414440E+00   1.23414440E+00   1.23414440E+00\natom   7.62102355E-01   7.62102355E-01   7.62102355E-01 Ne   0.00000000E+00   0.00000000E+00  -1.23414440E+00  -1.23414440E+00  -1.23414440E+00\nenergy  -6.13218442E-01\ncomment r =   1.32000000E+00, E =  -6.13218442E-01, dEdr =   2.13760080E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.20214407E+00   1.20214407E+00   1.20214407E+00\natom   7.67875858E-01   7.67875858E-01   7.67875858E-01 Ne   0.00000000E+00   0.00000000E+00  -1.20214407E+00  -1.20214407E+00  -1.20214407E+00\nenergy  -5.92117772E-01\ncomment r =   1.33000000E+00, E =  -5.92117772E-01, dEdr =   2.08217461E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.16909931E+00   1.16909931E+00   1.16909931E+00\natom   7.73649361E-01   7.73649361E-01   7.73649361E-01 Ne   0.00000000E+00   0.00000000E+00  -1.16909931E+00  -1.16909931E+00  -1.16909931E+00\nenergy  -5.71580967E-01\ncomment r =   1.34000000E+00, E =  -5.71580967E-01, dEdr =   2.02493940E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.13536610E+00   1.13536610E+00   1.13536610E+00\natom   7.79422863E-01   7.79422863E-01   7.79422863E-01 Ne   0.00000000E+00   0.00000000E+00  -1.13536610E+00  -1.13536610E+00  -1.13536610E+00\nenergy  -5.51622948E-01\ncomment r =   1.35000000E+00, E =  -5.51622948E-01, dEdr =   1.96651177E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.10124456E+00   1.10124456E+00   1.10124456E+00\natom   7.85196366E-01   7.85196366E-01   7.85196366E-01 Ne   0.00000000E+00   0.00000000E+00  -1.10124456E+00  -1.10124456E+00  -1.10124456E+00\nenergy  -5.32252964E-01\ncomment r =   1.36000000E+00, E =  -5.32252964E-01, dEdr =   1.90741154E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.06698669E+00   1.06698669E+00   1.06698669E+00\natom   7.90969869E-01   7.90969869E-01   7.90969869E-01 Ne   0.00000000E+00   0.00000000E+00  -1.06698669E+00  -1.06698669E+00  -1.06698669E+00\nenergy  -5.13475496E-01\ncomment r =   1.37000000E+00, E =  -5.13475496E-01, dEdr =   1.84807516E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.03280308E+00   1.03280308E+00   1.03280308E+00\natom   7.96743371E-01   7.96743371E-01   7.96743371E-01 Ne   0.00000000E+00   0.00000000E+00  -1.03280308E+00  -1.03280308E+00  -1.03280308E+00\nenergy  -4.95291026E-01\ncomment r =   1.38000000E+00, E =  -4.95291026E-01, dEdr =   1.78886740E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.98868680E-01   9.98868680E-01   9.98868680E-01\natom   8.02516874E-01   8.02516874E-01   8.02516874E-01 Ne   0.00000000E+00   0.00000000E+00  -9.98868680E-01  -9.98868680E-01  -9.98868680E-01\nenergy  -4.77696704E-01\ncomment r =   1.39000000E+00, E =  -4.77696704E-01, dEdr =   1.73009130E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.65327860E-01   9.65327860E-01   9.65327860E-01\natom   8.08290377E-01   8.08290377E-01   8.08290377E-01 Ne   0.00000000E+00   0.00000000E+00  -9.65327860E-01  -9.65327860E-01  -9.65327860E-01\nenergy  -4.60686922E-01\ncomment r =   1.40000000E+00, E =  -4.60686922E-01, dEdr =   1.67199690E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.32298690E-01   9.32298690E-01   9.32298690E-01\natom   8.14063880E-01   8.14063880E-01   8.14063880E-01 Ne   0.00000000E+00   0.00000000E+00  -9.32298690E-01  -9.32298690E-01  -9.32298690E-01\nenergy  -4.44253807E-01\ncomment r =   1.41000000E+00, E =  -4.44253807E-01, dEdr =   1.61478870E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.99876705E-01   8.99876705E-01   8.99876705E-01\natom   8.19837382E-01   8.19837382E-01   8.19837382E-01 Ne   0.00000000E+00   0.00000000E+00  -8.99876705E-01  -8.99876705E-01  -8.99876705E-01\nenergy  -4.28387639E-01\ncomment r =   1.42000000E+00, E =  -4.28387639E-01, dEdr =   1.55863217E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.68138141E-01   8.68138141E-01   8.68138141E-01\natom   8.25610885E-01   8.25610885E-01   8.25610885E-01 Ne   0.00000000E+00   0.00000000E+00  -8.68138141E-01  -8.68138141E-01  -8.68138141E-01\nenergy  -4.13077215E-01\ncomment r =   1.43000000E+00, E =  -4.13077215E-01, dEdr =   1.50365937E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.37142729E-01   8.37142729E-01   8.37142729E-01\natom   8.31384388E-01   8.31384388E-01   8.31384388E-01 Ne   0.00000000E+00   0.00000000E+00  -8.37142729E-01  -8.37142729E-01  -8.37142729E-01\nenergy  -3.98310158E-01\ncomment r =   1.44000000E+00, E =  -3.98310158E-01, dEdr =   1.44997374E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.06936119E-01   8.06936119E-01   8.06936119E-01\natom   8.37157890E-01   8.37157890E-01   8.37157890E-01 Ne   0.00000000E+00   0.00000000E+00  -8.06936119E-01  -8.06936119E-01  -8.06936119E-01\nenergy  -3.84073184E-01\ncomment r =   1.45000000E+00, E =  -3.84073184E-01, dEdr =   1.39765436E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.77551972E-01   7.77551972E-01   7.77551972E-01\natom   8.42931393E-01   8.42931393E-01   8.42931393E-01 Ne   0.00000000E+00   0.00000000E+00  -7.77551972E-01  -7.77551972E-01  -7.77551972E-01\nenergy  -3.70352321E-01\ncomment r =   1.46000000E+00, E =  -3.70352321E-01, dEdr =   1.34675952E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.49013769E-01   7.49013769E-01   7.49013769E-01\natom   8.48704896E-01   8.48704896E-01   8.48704896E-01 Ne   0.00000000E+00   0.00000000E+00  -7.49013769E-01  -7.49013769E-01  -7.49013769E-01\nenergy  -3.57133107E-01\ncomment r =   1.47000000E+00, E =  -3.57133107E-01, dEdr =   1.29732990E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.21336370E-01   7.21336370E-01   7.21336370E-01\natom   8.54478398E-01   8.54478398E-01   8.54478398E-01 Ne   0.00000000E+00   0.00000000E+00  -7.21336370E-01  -7.21336370E-01  -7.21336370E-01\nenergy  -3.44400751E-01\ncomment r =   1.48000000E+00, E =  -3.44400751E-01, dEdr =   1.24939124E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.94527370E-01   6.94527370E-01   6.94527370E-01\natom   8.60251901E-01   8.60251901E-01   8.60251901E-01 Ne   0.00000000E+00   0.00000000E+00  -6.94527370E-01  -6.94527370E-01  -6.94527370E-01\nenergy  -3.32140268E-01\ncomment r =   1.49000000E+00, E =  -3.32140268E-01, dEdr =   1.20295669E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.68588257E-01   6.68588257E-01   6.68588257E-01\natom   8.66025404E-01   8.66025404E-01   8.66025404E-01 Ne   0.00000000E+00   0.00000000E+00  -6.68588257E-01  -6.68588257E-01  -6.68588257E-01\nenergy  -3.20336594E-01\ncomment r =   1.50000000E+00, E =  -3.20336594E-01, dEdr =   1.15802883E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.43515424E-01   6.43515424E-01   6.43515424E-01\natom   8.71798906E-01   8.71798906E-01   8.71798906E-01 Ne   0.00000000E+00   0.00000000E+00  -6.43515424E-01  -6.43515424E-01  -6.43515424E-01\nenergy  -3.08974689E-01\ncomment r =   1.51000000E+00, E =  -3.08974689E-01, dEdr =   1.11460141E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.19301030E-01   6.19301030E-01   6.19301030E-01\natom   8.77572409E-01   8.77572409E-01   8.77572409E-01 Ne   0.00000000E+00   0.00000000E+00  -6.19301030E-01  -6.19301030E-01  -6.19301030E-01\nenergy  -2.98039609E-01\ncomment r =   1.52000000E+00, E =  -2.98039609E-01, dEdr =   1.07266085E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.95933747E-01   5.95933747E-01   5.95933747E-01\natom   8.83345912E-01   8.83345912E-01   8.83345912E-01 Ne   0.00000000E+00   0.00000000E+00  -5.95933747E-01  -5.95933747E-01  -5.95933747E-01\nenergy  -2.87516580E-01\ncomment r =   1.53000000E+00, E =  -2.87516580E-01, dEdr =   1.03218753E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.73399404E-01   5.73399404E-01   5.73399404E-01\natom   8.89119415E-01   8.89119415E-01   8.89119415E-01 Ne   0.00000000E+00   0.00000000E+00  -5.73399404E-01  -5.73399404E-01  -5.73399404E-01\nenergy  -2.77391049E-01\ncomment r =   1.54000000E+00, E =  -2.77391049E-01, dEdr =   9.93156900E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.51681534E-01   5.51681534E-01   5.51681534E-01\natom   8.94892917E-01   8.94892917E-01   8.94892917E-01 Ne   0.00000000E+00   0.00000000E+00  -5.51681534E-01  -5.51681534E-01  -5.51681534E-01\nenergy  -2.67648728E-01\ncomment r =   1.55000000E+00, E =  -2.67648728E-01, dEdr =   9.55540446E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.30761850E-01   5.30761850E-01   5.30761850E-01\natom   9.00666420E-01   9.00666420E-01   9.00666420E-01 Ne   0.00000000E+00   0.00000000E+00  -5.30761850E-01  -5.30761850E-01  -5.30761850E-01\nenergy  -2.58275632E-01\ncomment r =   1.56000000E+00, E =  -2.58275632E-01, dEdr =   9.19306492E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.10620650E-01   5.10620650E-01   5.10620650E-01\natom   9.06439923E-01   9.06439923E-01   9.06439923E-01 Ne   0.00000000E+00   0.00000000E+00  -5.10620650E-01  -5.10620650E-01  -5.10620650E-01\nenergy  -2.49258104E-01\ncomment r =   1.57000000E+00, E =  -2.49258104E-01, dEdr =   8.84420909E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.91237157E-01   4.91237157E-01   4.91237157E-01\natom   9.12213425E-01   9.12213425E-01   9.12213425E-01 Ne   0.00000000E+00   0.00000000E+00  -4.91237157E-01  -4.91237157E-01  -4.91237157E-01\nenergy  -2.40582839E-01\ncomment r =   1.58000000E+00, E =  -2.40582839E-01, dEdr =   8.50847714E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.72589820E-01   4.72589820E-01   4.72589820E-01\natom   9.17986928E-01   9.17986928E-01   9.17986928E-01 Ne   0.00000000E+00   0.00000000E+00  -4.72589820E-01  -4.72589820E-01  -4.72589820E-01\nenergy  -2.32236899E-01\ncomment r =   1.59000000E+00, E =  -2.32236899E-01, dEdr =   8.18549579E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.54656560E-01   4.54656560E-01   4.54656560E-01\natom   9.23760431E-01   9.23760431E-01   9.23760431E-01 Ne   0.00000000E+00   0.00000000E+00  -4.54656560E-01  -4.54656560E-01  -4.54656560E-01\nenergy  -2.24207724E-01\ncomment r =   1.60000000E+00, E =  -2.24207724E-01, dEdr =   7.87488261E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.37414983E-01   4.37414983E-01   4.37414983E-01\natom   9.29533933E-01   9.29533933E-01   9.29533933E-01 Ne   0.00000000E+00   0.00000000E+00  -4.37414983E-01  -4.37414983E-01  -4.37414983E-01\nenergy  -2.16483140E-01\ncomment r =   1.61000000E+00, E =  -2.16483140E-01, dEdr =   7.57624975E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.20842560E-01   4.20842560E-01   4.20842560E-01\natom   9.35307436E-01   9.35307436E-01   9.35307436E-01 Ne   0.00000000E+00   0.00000000E+00  -4.20842560E-01  -4.20842560E-01  -4.20842560E-01\nenergy  -2.09051362E-01\ncomment r =   1.62000000E+00, E =  -2.09051362E-01, dEdr =   7.28920696E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.04916775E-01   4.04916775E-01   4.04916775E-01\natom   9.41080939E-01   9.41080939E-01   9.41080939E-01 Ne   0.00000000E+00   0.00000000E+00  -4.04916775E-01  -4.04916775E-01  -4.04916775E-01\nenergy  -2.01900993E-01\ncomment r =   1.63000000E+00, E =  -2.01900993E-01, dEdr =   7.01336426E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.89615248E-01   3.89615248E-01   3.89615248E-01\natom   9.46854441E-01   9.46854441E-01   9.46854441E-01 Ne   0.00000000E+00   0.00000000E+00  -3.89615248E-01  -3.89615248E-01  -3.89615248E-01\nenergy  -1.95021029E-01\ncomment r =   1.64000000E+00, E =  -1.95021029E-01, dEdr =   6.74833406E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.74915846E-01   3.74915846E-01   3.74915846E-01\natom   9.52627944E-01   9.52627944E-01   9.52627944E-01 Ne   0.00000000E+00   0.00000000E+00  -3.74915846E-01  -3.74915846E-01  -3.74915846E-01\nenergy  -1.88400849E-01\ncomment r =   1.65000000E+00, E =  -1.88400849E-01, dEdr =   6.49373295E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.60796761E-01   3.60796761E-01   3.60796761E-01\natom   9.58401447E-01   9.58401447E-01   9.58401447E-01 Ne   0.00000000E+00   0.00000000E+00  -3.60796761E-01  -3.60796761E-01  -3.60796761E-01\nenergy  -1.82030213E-01\ncomment r =   1.66000000E+00, E =  -1.82030213E-01, dEdr =   6.24918320E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.47236580E-01   3.47236580E-01   3.47236580E-01\natom   9.64174950E-01   9.64174950E-01   9.64174950E-01 Ne   0.00000000E+00   0.00000000E+00  -3.47236580E-01  -3.47236580E-01  -3.47236580E-01\nenergy  -1.75899255E-01\ncomment r =   1.67000000E+00, E =  -1.75899255E-01, dEdr =   6.01431398E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.34214345E-01   3.34214345E-01   3.34214345E-01\natom   9.69948452E-01   9.69948452E-01   9.69948452E-01 Ne   0.00000000E+00   0.00000000E+00  -3.34214345E-01  -3.34214345E-01  -3.34214345E-01\nenergy  -1.69998479E-01\ncomment r =   1.68000000E+00, E =  -1.69998479E-01, dEdr =   5.78876226E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.21709594E-01   3.21709594E-01   3.21709594E-01\natom   9.75721955E-01   9.75721955E-01   9.75721955E-01 Ne   0.00000000E+00   0.00000000E+00  -3.21709594E-01  -3.21709594E-01  -3.21709594E-01\nenergy  -1.64318743E-01\ncomment r =   1.69000000E+00, E =  -1.64318743E-01, dEdr =   5.57217362E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.09702395E-01   3.09702395E-01   3.09702395E-01\natom   9.81495458E-01   9.81495458E-01   9.81495458E-01 Ne   0.00000000E+00   0.00000000E+00  -3.09702395E-01  -3.09702395E-01  -3.09702395E-01\nenergy  -1.58851259E-01\ncomment r =   1.70000000E+00, E =  -1.58851259E-01, dEdr =   5.36420284E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.98173372E-01   2.98173372E-01   2.98173372E-01\natom   9.87268960E-01   9.87268960E-01   9.87268960E-01 Ne   0.00000000E+00   0.00000000E+00  -2.98173372E-01  -2.98173372E-01  -2.98173372E-01\nenergy  -1.53587577E-01\ncomment r =   1.71000000E+00, E =  -1.53587577E-01, dEdr =   5.16451429E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.87103720E-01   2.87103720E-01   2.87103720E-01\natom   9.93042463E-01   9.93042463E-01   9.93042463E-01 Ne   0.00000000E+00   0.00000000E+00  -2.87103720E-01  -2.87103720E-01  -2.87103720E-01\nenergy  -1.48519579E-01\ncomment r =   1.72000000E+00, E =  -1.48519579E-01, dEdr =   4.97278230E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.76475222E-01   2.76475222E-01   2.76475222E-01\natom   9.98815966E-01   9.98815966E-01   9.98815966E-01 Ne   0.00000000E+00   0.00000000E+00  -2.76475222E-01  -2.76475222E-01  -2.76475222E-01\nenergy  -1.43639466E-01\ncomment r =   1.73000000E+00, E =  -1.43639466E-01, dEdr =   4.78869131E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.66270250E-01   2.66270250E-01   2.66270250E-01\natom   1.00458947E+00   1.00458947E+00   1.00458947E+00 Ne   0.00000000E+00   0.00000000E+00  -2.66270250E-01  -2.66270250E-01  -2.66270250E-01\nenergy  -1.38939751E-01\ncomment r =   1.74000000E+00, E =  -1.38939751E-01, dEdr =   4.61193602E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.56471773E-01   2.56471773E-01   2.56471773E-01\natom   1.01036297E+00   1.01036297E+00   1.01036297E+00 Ne   0.00000000E+00   0.00000000E+00  -2.56471773E-01  -2.56471773E-01  -2.56471773E-01\nenergy  -1.34413247E-01\ncomment r =   1.75000000E+00, E =  -1.34413247E-01, dEdr =   4.44222142E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.47063348E-01   2.47063348E-01   2.47063348E-01\natom   1.01613647E+00   1.01613647E+00   1.01613647E+00 Ne   0.00000000E+00   0.00000000E+00  -2.47063348E-01  -2.47063348E-01  -2.47063348E-01\nenergy  -1.30053056E-01\ncomment r =   1.76000000E+00, E =  -1.30053056E-01, dEdr =   4.27926272E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.38029122E-01   2.38029122E-01   2.38029122E-01\natom   1.02190998E+00   1.02190998E+00   1.02190998E+00 Ne   0.00000000E+00   0.00000000E+00  -2.38029122E-01  -2.38029122E-01  -2.38029122E-01\nenergy  -1.25852561E-01\ncomment r =   1.77000000E+00, E =  -1.25852561E-01, dEdr =   4.12278533E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.29353819E-01   2.29353819E-01   2.29353819E-01\natom   1.02768348E+00   1.02768348E+00   1.02768348E+00 Ne   0.00000000E+00   0.00000000E+00  -2.29353819E-01  -2.29353819E-01  -2.29353819E-01\nenergy  -1.21805413E-01\ncomment r =   1.78000000E+00, E =  -1.21805413E-01, dEdr =   3.97252467E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.21022735E-01   2.21022735E-01   2.21022735E-01\natom   1.03345698E+00   1.03345698E+00   1.03345698E+00 Ne   0.00000000E+00   0.00000000E+00  -2.21022735E-01  -2.21022735E-01  -2.21022735E-01\nenergy  -1.17905524E-01\ncomment r =   1.79000000E+00, E =  -1.17905524E-01, dEdr =   3.82822607E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.13021724E-01   2.13021724E-01   2.13021724E-01\natom   1.03923048E+00   1.03923048E+00   1.03923048E+00 Ne   0.00000000E+00   0.00000000E+00  -2.13021724E-01  -2.13021724E-01  -2.13021724E-01\nenergy  -1.14147056E-01\ncomment r =   1.80000000E+00, E =  -1.14147056E-01, dEdr =   3.68964449E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.05337187E-01   2.05337187E-01   2.05337187E-01\natom   1.04500399E+00   1.04500399E+00   1.04500399E+00 Ne   0.00000000E+00   0.00000000E+00  -2.05337187E-01  -2.05337187E-01  -2.05337187E-01\nenergy  -1.10524408E-01\ncomment r =   1.81000000E+00, E =  -1.10524408E-01, dEdr =   3.55654440E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.97956057E-01   1.97956057E-01   1.97956057E-01\natom   1.05077749E+00   1.05077749E+00   1.05077749E+00 Ne   0.00000000E+00   0.00000000E+00  -1.97956057E-01  -1.97956057E-01  -1.97956057E-01\nenergy  -1.07032215E-01\ncomment r =   1.82000000E+00, E =  -1.07032215E-01, dEdr =   3.42869948E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.90865785E-01   1.90865785E-01   1.90865785E-01\natom   1.05655099E+00   1.05655099E+00   1.05655099E+00 Ne   0.00000000E+00   0.00000000E+00  -1.90865785E-01  -1.90865785E-01  -1.90865785E-01\nenergy  -1.03665330E-01\ncomment r =   1.83000000E+00, E =  -1.03665330E-01, dEdr =   3.30589238E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.84054328E-01   1.84054328E-01   1.84054328E-01\natom   1.06232450E+00   1.06232450E+00   1.06232450E+00 Ne   0.00000000E+00   0.00000000E+00  -1.84054328E-01  -1.84054328E-01  -1.84054328E-01\nenergy  -1.00418821E-01\ncomment r =   1.84000000E+00, E =  -1.00418821E-01, dEdr =   3.18791447E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.77510126E-01   1.77510126E-01   1.77510126E-01\natom   1.06809800E+00   1.06809800E+00   1.06809800E+00 Ne   0.00000000E+00   0.00000000E+00  -1.77510126E-01  -1.77510126E-01  -1.77510126E-01\nenergy  -9.72879584E-02\ncomment r =   1.85000000E+00, E =  -9.72879584E-02, dEdr =   3.07456558E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.71222096E-01   1.71222096E-01   1.71222096E-01\natom   1.07387150E+00   1.07387150E+00   1.07387150E+00 Ne   0.00000000E+00   0.00000000E+00  -1.71222096E-01  -1.71222096E-01  -1.71222096E-01\nenergy  -9.42682107E-02\ncomment r =   1.86000000E+00, E =  -9.42682107E-02, dEdr =   2.96565370E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.65179609E-01   1.65179609E-01   1.65179609E-01\natom   1.07964500E+00   1.07964500E+00   1.07964500E+00 Ne   0.00000000E+00   0.00000000E+00  -1.65179609E-01  -1.65179609E-01  -1.65179609E-01\nenergy  -9.13552334E-02\ncomment r =   1.87000000E+00, E =  -9.13552334E-02, dEdr =   2.86099475E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.59372475E-01   1.59372475E-01   1.59372475E-01\natom   1.08541851E+00   1.08541851E+00   1.08541851E+00 Ne   0.00000000E+00   0.00000000E+00  -1.59372475E-01  -1.59372475E-01  -1.59372475E-01\nenergy  -8.85448625E-02\ncomment r =   1.88000000E+00, E =  -8.85448625E-02, dEdr =   2.76041225E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.53790932E-01   1.53790932E-01   1.53790932E-01\natom   1.09119201E+00   1.09119201E+00   1.09119201E+00 Ne   0.00000000E+00   0.00000000E+00  -1.53790932E-01  -1.53790932E-01  -1.53790932E-01\nenergy  -8.58331065E-02\ncomment r =   1.89000000E+00, E =  -8.58331065E-02, dEdr =   2.66373709E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.48425625E-01   1.48425625E-01   1.48425625E-01\natom   1.09696551E+00   1.09696551E+00   1.09696551E+00 Ne   0.00000000E+00   0.00000000E+00  -1.48425625E-01  -1.48425625E-01  -1.48425625E-01\nenergy  -8.32161399E-02\ncomment r =   1.90000000E+00, E =  -8.32161399E-02, dEdr =   2.57080724E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.43267593E-01   1.43267593E-01   1.43267593E-01\natom   1.10273901E+00   1.10273901E+00   1.10273901E+00 Ne   0.00000000E+00   0.00000000E+00  -1.43267593E-01  -1.43267593E-01  -1.43267593E-01\nenergy  -8.06902954E-02\ncomment r =   1.91000000E+00, E =  -8.06902954E-02, dEdr =   2.48146751E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38308255E-01   1.38308255E-01   1.38308255E-01\natom   1.10851252E+00   1.10851252E+00   1.10851252E+00 Ne   0.00000000E+00   0.00000000E+00  -1.38308255E-01  -1.38308255E-01  -1.38308255E-01\nenergy  -7.82520578E-02\ncomment r =   1.92000000E+00, E =  -7.82520578E-02, dEdr =   2.39556925E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.33539391E-01   1.33539391E-01   1.33539391E-01\natom   1.11428602E+00   1.11428602E+00   1.11428602E+00 Ne   0.00000000E+00   0.00000000E+00  -1.33539391E-01  -1.33539391E-01  -1.33539391E-01\nenergy  -7.58980573E-02\ncomment r =   1.93000000E+00, E =  -7.58980573E-02, dEdr =   2.31297011E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.28953134E-01   1.28953134E-01   1.28953134E-01\natom   1.12005952E+00   1.12005952E+00   1.12005952E+00 Ne   0.00000000E+00   0.00000000E+00  -1.28953134E-01  -1.28953134E-01  -1.28953134E-01\nenergy  -7.36250634E-02\ncomment r =   1.94000000E+00, E =  -7.36250634E-02, dEdr =   2.23353381E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.24541951E-01   1.24541951E-01   1.24541951E-01\natom   1.12583302E+00   1.12583302E+00   1.12583302E+00 Ne   0.00000000E+00   0.00000000E+00  -1.24541951E-01  -1.24541951E-01  -1.24541951E-01\nenergy  -7.14299790E-02\ncomment r =   1.95000000E+00, E =  -7.14299790E-02, dEdr =   2.15712986E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.20298629E-01   1.20298629E-01   1.20298629E-01\natom   1.13160653E+00   1.13160653E+00   1.13160653E+00 Ne   0.00000000E+00   0.00000000E+00  -1.20298629E-01  -1.20298629E-01  -1.20298629E-01\nenergy  -6.93098346E-02\ncomment r =   1.96000000E+00, E =  -6.93098346E-02, dEdr =   2.08363337E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.16216266E-01   1.16216266E-01   1.16216266E-01\natom   1.13738003E+00   1.13738003E+00   1.13738003E+00 Ne   0.00000000E+00   0.00000000E+00  -1.16216266E-01  -1.16216266E-01  -1.16216266E-01\nenergy  -6.72617830E-02\ncomment r =   1.97000000E+00, E =  -6.72617830E-02, dEdr =   2.01292477E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.12288255E-01   1.12288255E-01   1.12288255E-01\natom   1.14315353E+00   1.14315353E+00   1.14315353E+00 Ne   0.00000000E+00   0.00000000E+00  -1.12288255E-01  -1.12288255E-01  -1.12288255E-01\nenergy  -6.52830939E-02\ncomment r =   1.98000000E+00, E =  -6.52830939E-02, dEdr =   1.94488962E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.08508271E-01   1.08508271E-01   1.08508271E-01\natom   1.14892704E+00   1.14892704E+00   1.14892704E+00 Ne   0.00000000E+00   0.00000000E+00  -1.08508271E-01  -1.08508271E-01  -1.08508271E-01\nenergy  -6.33711491E-02\ncomment r =   1.99000000E+00, E =  -6.33711491E-02, dEdr =   1.87941839E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.04870264E-01   1.04870264E-01   1.04870264E-01\natom   1.15470054E+00   1.15470054E+00   1.15470054E+00 Ne   0.00000000E+00   0.00000000E+00  -1.04870264E-01  -1.04870264E-01  -1.04870264E-01\nenergy  -6.15234375E-02\ncomment r =   2.00000000E+00, E =  -6.15234375E-02, dEdr =   1.81640625E-01\nend\n"
  },
  {
    "path": "examples/configuration-single/input.data.Anisole",
    "content": "begin\ncomment       frame number       26\nlattice   26.9097   0.0000   0.0000\nlattice    0.0000  26.9097   0.0000\nlattice    0.0000   0.0000  26.9097\natom       0.86777766879146       4.73017440716062      23.07803416989450     C  0.00  0.00       0.01525757175204       0.02812286837187       0.00767676377891\natom       0.92344556769964       7.39422086244662      23.16431125871410     C  0.00  0.00       0.03014815390882      -0.04195881041955      -0.00042456790795\natom       0.94210594503600      20.61150684046838       6.09307292350435     C  0.00  0.00      -0.00704064954080      -0.01080150602966       0.01332323186951\natom       1.18009523263683      13.93158928309510       5.06653539712602     C  0.00  0.00       0.04997677384680       0.01353658518627       0.04138015061819\natom       1.33693232804421      18.20765303990029       5.14033073491527     C  0.00  0.00      -0.01933852067018      -0.00592515572910       0.04267725720051\natom       1.38956443208569      23.20454531249680      23.41927705598249     C  0.00  0.00       0.03151728064164       0.01400490172248       0.01255850923611\natom       1.82181636962522       3.55683451694793       4.19715836971545     C  0.00  0.00       0.00951179232419      -0.01518136609870       0.00003013287281\natom       1.93010598026109      22.61858655660978       4.86532132363768     C  0.00  0.00      -0.01064809968863       0.03874445962677       0.00957790938166\natom      19.18562156059880       5.08133191767783      15.46062504461108     C  0.00  0.00       0.00686545475555      -0.00031286254394      -0.00141992125559\natom      19.35681466944991      12.08394712779837      18.83717197075168     C  0.00  0.00      -0.02045424485601      -0.00063633174477      -0.05051339851463\natom      19.84793876029054       4.48762733650928      19.95694863487657     C  0.00  0.00      -0.03665277286706       0.03791783805779      -0.01596994932413\natom      19.84897929895120      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     -0.00622133402966       0.00258252883965\natom      13.56036646870816       5.61765557979666       3.29556790030826     H  0.00  0.00      -0.00311810424462      -0.01215047882269      -0.01395473625950\natom      13.60219985312595      14.83770943186823      20.75100986674471     H  0.00  0.00      -0.00923474910949      -0.00608238683212       0.00496040377586\natom      13.66606791430935      16.59191719298875      24.06827119382295     H  0.00  0.00       0.00628151430032      -0.00117256008886      -0.01020557221268\natom      14.01098253772640       1.21945248298170      15.47217588232092     H  0.00  0.00      -0.00243325109130       0.00283157055164      -0.00077285288182\natom      13.78291894239097      11.74323480186236      11.17551651217406     H  0.00  0.00       0.00807014326230       0.00404950832336      -0.00067866208846\natom      14.04781121823483       6.00570182540271       0.02701695410012     H  0.00  0.00      -0.00059984647113      -0.00781475401433      -0.00289340341183\natom      14.10536735561700      10.92732466952432      18.61768132401458     H  0.00  0.00       0.00274197217616       0.00404691461410      -0.00305345077743\natom      14.12243536357763      17.49495910072382       8.50911740636720     H  0.00  0.00       0.00963260394582       0.00785450446139      -0.01133649657111\natom      14.41725760252159       2.17847561272686       6.98198335029839     H  0.00  0.00       0.02147723382730      -0.00177181942864      -0.01273088343706\natom      14.73615441561018       3.05144857018187       1.52722283822307     H  0.00  0.00      -0.00146052554942      -0.01089916511199      -0.00663693077820\natom      15.23602799838478      -0.05130236463687      24.65338334413847     H  0.00  0.00      -0.00242975724945       0.00312981735145      -0.00478411226734\natom      15.45602174193877       5.06313374917128      21.14568432891446     H  0.00  0.00      -0.01263666651945       0.01423852012403       0.01753511920221\natom      15.60443650047727      -0.02386596902469       9.24710229675185     H  0.00  0.00       0.01134275898103       0.01816703324056      -0.00767777340283\natom      15.57721751114974       9.57543186422626       5.23933449716621     H  0.00  0.00       0.00624564825530      -0.00566848960734       0.00001440493889\natom      15.81474348283718      24.78363321751743       5.34954011930717     H  0.00  0.00       0.00040303349044       0.00529491463504      -0.00030418216736\natom      15.85042637471030       6.69550868314797      24.17715887447349     H  0.00  0.00       0.01113745427154      -0.00969184807853       0.00774798479530\natom      16.58176924976132      10.41310876413758      12.93142038506577     H  0.00  0.00       0.01392628592271      -0.00583129654889      -0.00427760047623\natom      16.67240519833128       6.47146025612988      18.25513898865395     H  0.00  0.00       0.00171583012982      -0.00044537934721      -0.00284019368261\natom      16.93222024989329       8.06810545013082      21.33361715085772     H  0.00  0.00      -0.00407220942928       0.00216452866788       0.00737222382900\natom      16.94342905073737      15.17316658154625      17.47335900105367     H  0.00  0.00       0.00546120940450      -0.01109815541517      -0.01311580620804\natom      17.08903032723207      11.42727863210189       9.73830939166701     H  0.00  0.00       0.00156970400515      -0.00447341517029      -0.00061331630192\natom      17.13045045783256      18.85454043706166      13.91607951533275     H  0.00  0.00       0.00100586090669      -0.02089684377865      -0.00532076800367\natom      17.29293296936279      17.72272146099177      21.10561926864150     H  0.00  0.00       0.00888893701414      -0.00405641301131      -0.00244185023976\natom      17.69895793055693      15.65865159161054       6.13057094516978     H  0.00  0.00      -0.00629666188696       0.02077891040454      -0.00894935266232\natom      17.92987938521209       2.09154857687027       7.85843944009235     H  0.00  0.00      -0.00587028854997       0.00516571950856      -0.00550929662939\natom      18.06844560772488       5.69423714900442      13.78424595656472     H  0.00  0.00       0.00567737911350      -0.00179985798174       0.01917963985382\natom      18.31263915021914       0.39295739984359      16.94871258583458     H  0.00  0.00      -0.01019325522844       0.00330500703603       0.01519698121501\natom      18.63873474875025      14.63766031714465      -0.09789294062495     H  0.00  0.00       0.00290368643868       0.00927415617764      -0.00170272766280\natom      18.83856940296016       0.01436579960824      21.79619246127434     H  0.00  0.00      -0.00219157053993      -0.00270965406836      -0.00259809832966\nenergy    -967.50349042280641\ncharge       0\nend\n"
  },
  {
    "path": "examples/configuration-single/input.data.Cu2S_144_low-chalcocite",
    "content": "begin\ncomment source_file_name=OUTCAR_0_1\nlattice 15.246000000 0.000000000 0.000000000\nlattice 0.000000000 11.884000000 0.000000000\nlattice -5.989357159 0.000000000 12.091965796\natom 9.55381 0.98518 10.18385 S 0.0 0.0 -0.125331 0.028415 0.031193\natom -3.29184 6.92718 7.95410 S 0.0 0.0 0.125331 0.028415 -0.031193\natom -0.29717 10.89882 1.90811 S 0.0 0.0 0.125331 -0.028415 -0.031193\natom 12.54849 4.95682 4.13787 S 0.0 0.0 -0.125331 -0.028415 0.031193\natom 12.27754 0.91269 4.18624 S 0.0 0.0 -0.126394 -0.041931 0.027223\natom -0.02622 6.85469 1.85974 S 0.0 0.0 0.126394 -0.041931 -0.027223\natom -3.02090 10.97131 7.90573 S 0.0 0.0 0.126394 0.041931 -0.027223\natom 9.28287 5.02931 10.23222 S 0.0 0.0 -0.126394 0.041931 0.027223\natom 9.06992 0.97924 6.12821 S 0.0 0.0 -0.013446 -0.068418 -0.051411\natom -2.80795 6.92124 12.00974 S 0.0 0.0 0.013446 -0.068418 0.051411\natom 0.18673 10.90476 5.96376 S 0.0 0.0 0.013446 0.068418 0.051411\natom 12.06460 4.96276 0.08223 S 0.0 0.0 -0.013446 0.068418 -0.051411\natom 12.03432 0.97092 0.07255 S 0.0 0.0 0.063364 0.002358 -0.040486\natom 0.21700 6.91292 5.97343 S 0.0 0.0 -0.063364 0.002358 0.040486\natom -2.77768 10.91308 12.01941 S 0.0 0.0 -0.063364 -0.002358 0.040486\natom 9.03964 4.97108 6.11853 S 0.0 0.0 0.063364 -0.002358 -0.040486\natom 3.17371 1.04936 7.41600 S 0.0 0.0 -0.099435 -0.033364 0.051184\natom 3.08826 6.99136 10.72195 S 0.0 0.0 0.099435 -0.033364 -0.051184\natom 6.08294 10.83464 4.67596 S 0.0 0.0 0.099435 0.033364 -0.051184\natom 6.16838 4.89264 1.37002 S 0.0 0.0 -0.099435 0.033364 0.051184\natom 6.20214 0.86278 1.15720 S 0.0 0.0 0.136972 -0.061507 -0.119929\natom 6.04918 6.80478 4.88878 S 0.0 0.0 -0.136972 -0.061507 0.119929\natom 3.05450 11.02122 10.93476 S 0.0 0.0 -0.136972 0.061507 0.119929\natom 3.20746 5.07922 7.20318 S 0.0 0.0 0.136972 0.061507 -0.119929\natom -0.14015 0.92814 9.51396 S 0.0 0.0 0.207624 -0.187454 0.034062\natom 6.40212 6.87014 8.62399 S 0.0 0.0 -0.207624 -0.187454 -0.034062\natom 9.39679 10.95586 2.57801 S 0.0 0.0 -0.207624 0.187454 -0.034062\natom 2.85453 5.01386 3.46798 S 0.0 0.0 0.207624 0.187454 0.034062\natom 2.61609 0.98875 3.46918 S 0.0 0.0 -0.379594 -0.045519 -0.051010\natom 9.63523 6.93075 2.57680 S 0.0 0.0 0.379594 -0.045519 0.051010\natom 6.64055 10.89525 8.62278 S 0.0 0.0 0.379594 0.045519 0.051010\natom -0.37859 4.95325 9.51517 S 0.0 0.0 -0.379594 0.045519 -0.051010\natom 6.28690 2.94842 8.73040 S 0.0 0.0 -0.101684 -0.045832 0.134656\natom -0.02494 8.89042 9.40755 S 0.0 0.0 0.101684 -0.045832 -0.134656\natom 2.96974 8.93558 3.36157 S 0.0 0.0 0.101684 0.045832 -0.134656\natom 9.28158 2.99358 2.68442 S 0.0 0.0 -0.101684 0.045832 0.134656\natom 5.85752 2.65845 5.03872 S 0.0 0.0 -0.067582 -0.177681 0.103192\natom 6.39380 8.60045 1.00726 S 0.0 0.0 0.067582 -0.177681 -0.103192\natom 3.39912 9.22555 7.05324 S 0.0 0.0 0.067582 0.177681 -0.103192\natom 2.86284 3.28355 11.08471 S 0.0 0.0 -0.067582 0.177681 0.103192\natom 0.14893 2.83315 5.76303 S 0.0 0.0 -0.063213 -0.002445 -0.183871\natom 12.10239 8.77515 0.28295 S 0.0 0.0 0.063213 -0.002445 0.183871\natom 9.10771 9.05085 6.32893 S 0.0 0.0 0.063213 0.002445 0.183871\natom -2.84574 3.10885 11.80901 S 0.0 0.0 -0.063213 0.002445 -0.183871\natom -0.06140 2.76184 1.61065 S 0.0 0.0 0.033374 -0.217794 -0.226789\natom 12.31272 8.70384 4.43533 S 0.0 0.0 -0.033374 -0.217794 0.226789\natom 9.31804 9.12216 10.48132 S 0.0 0.0 -0.033374 0.217794 0.226789\natom -3.05608 3.18016 7.65663 S 0.0 0.0 0.033374 0.217794 -0.226789\natom 11.42708 2.96625 3.53932 Cu 0.0 0.0 -0.056517 -0.018383 -0.066026\natom 0.82424 8.90825 2.50666 Cu 0.0 0.0 0.056517 -0.018383 0.066026\natom -2.17044 8.91775 8.55265 Cu 0.0 0.0 0.056517 0.018383 0.066026\natom 8.43240 2.97575 9.58530 Cu 0.0 0.0 -0.056517 0.018383 -0.066026\natom 5.35651 0.87942 8.18021 Cu 0.0 0.0 -0.068978 -0.042620 0.067357\natom 0.90546 6.82142 9.95773 Cu 0.0 0.0 0.068978 -0.042620 -0.067357\natom 3.90014 11.00458 3.91175 Cu 0.0 0.0 0.068978 0.042620 -0.067357\natom 8.35119 5.06258 2.13423 Cu 0.0 0.0 -0.068978 0.042620 0.067357\natom 8.29869 1.08857 2.02782 Cu 0.0 0.0 -0.013003 -0.079744 -0.061412\natom 3.95263 7.03057 4.01816 Cu 0.0 0.0 0.013003 -0.079744 0.061412\natom 0.95795 10.79543 10.06414 Cu 0.0 0.0 0.013003 0.079744 0.061412\natom 5.30402 4.85343 8.07381 Cu 0.0 0.0 -0.013003 0.079744 -0.061412\natom 5.09343 2.85216 0.88392 Cu 0.0 0.0 -0.071088 -0.013473 -0.002685\natom 7.15789 8.79416 5.16206 Cu 0.0 0.0 0.071088 -0.013473 0.002685\natom 4.16322 9.03184 11.20804 Cu 0.0 0.0 0.071088 0.013473 0.002685\natom 2.09875 3.08984 6.92991 Cu 0.0 0.0 -0.071088 0.013473 -0.002685\natom -3.71515 1.00895 11.42812 Cu 0.0 0.0 0.067641 0.039805 0.039650\natom 9.97712 6.95095 6.70983 Cu 0.0 0.0 -0.067641 0.039805 -0.039650\natom 12.97179 10.87505 0.66385 Cu 0.0 0.0 -0.067641 -0.039805 -0.039650\natom -0.72047 4.93305 5.38213 Cu 0.0 0.0 0.067641 -0.039805 0.039650\natom -1.02899 0.93052 5.35553 Cu 0.0 0.0 0.007293 -0.021110 -0.015108\natom 13.28031 6.87252 0.69045 Cu 0.0 0.0 -0.007293 -0.021110 0.015108\natom 10.28563 10.95348 6.73643 Cu 0.0 0.0 -0.007293 0.021110 0.015108\natom -4.02367 5.01148 11.40151 Cu 0.0 0.0 0.007293 0.021110 -0.015108\natom 8.30415 1.46530 11.99886 Cu 0.0 0.0 -0.140674 0.136237 -0.040072\natom -2.04218 7.40730 6.13909 Cu 0.0 0.0 0.140674 0.136237 0.040072\natom 0.95249 10.41870 0.09311 Cu 0.0 0.0 0.140674 -0.136237 0.040072\natom 11.29883 4.47670 5.95287 Cu 0.0 0.0 -0.140674 -0.136237 -0.040072\natom 11.29861 1.67802 6.16569 Cu 0.0 0.0 0.015271 0.116590 -0.074616\natom -5.03665 7.62002 11.97226 Cu 0.0 0.0 -0.015271 0.116590 0.074616\natom -2.04197 10.20598 5.92627 Cu 0.0 0.0 -0.015271 -0.116590 0.074616\natom 14.29329 4.26398 0.11971 Cu 0.0 0.0 0.015271 -0.116590 -0.074616\natom 9.14880 2.97575 4.96859 Cu 0.0 0.0 0.164959 0.084500 0.087098\natom 3.10252 8.91775 1.07739 Cu 0.0 0.0 -0.164959 0.084500 -0.087098\natom 0.10784 8.90825 7.12338 Cu 0.0 0.0 -0.164959 -0.084500 -0.087098\natom 6.15412 2.96625 11.01457 Cu 0.0 0.0 0.164959 -0.084500 0.087098\natom 1.15360 1.75527 11.30357 Cu 0.0 0.0 -0.063629 0.156987 0.058610\natom 5.10836 7.69727 6.83438 Cu 0.0 0.0 0.063629 0.156987 -0.058610\natom 8.10304 10.12873 0.78840 Cu 0.0 0.0 0.063629 -0.156987 -0.058610\natom 4.14828 4.18673 5.25759 Cu 0.0 0.0 -0.063629 -0.156987 0.058610\natom 3.85752 1.46054 5.30595 Cu 0.0 0.0 0.025586 0.159786 -0.058692\natom 8.39380 7.40254 0.74003 Cu 0.0 0.0 -0.025586 0.159786 0.058692\natom 5.39912 10.42346 6.78601 Cu 0.0 0.0 -0.025586 -0.159786 0.058692\natom 0.86284 4.48146 11.35194 Cu 0.0 0.0 0.025586 -0.159786 -0.058692\natom -1.16473 2.80106 10.28664 Cu 0.0 0.0 0.114949 0.029868 0.062123\natom 7.42669 8.74306 7.85131 Cu 0.0 0.0 -0.114949 0.029868 -0.062123\natom 10.42137 9.08294 1.80533 Cu 0.0 0.0 -0.114949 -0.029868 -0.062123\natom 1.82995 3.14094 4.24065 Cu 0.0 0.0 0.114949 -0.029868 0.062123\natom 8.42471 0.42545 8.25881 Cu 0.0 0.0 -0.006801 -0.023883 -0.023161\natom -2.16275 6.36745 9.87914 Cu 0.0 0.0 0.006801 -0.023883 0.023161\natom 0.83193 11.45855 3.83315 Cu 0.0 0.0 0.006801 0.023883 0.023161\natom 11.41939 5.51655 2.21283 Cu 0.0 0.0 -0.006801 0.023883 -0.023161\natom 10.93680 0.74156 2.02057 Cu 0.0 0.0 -0.002607 0.001704 -0.015858\natom 1.31453 6.68356 4.02542 Cu 0.0 0.0 0.002607 0.001704 0.015858\natom -1.68015 11.14244 10.07140 Cu 0.0 0.0 0.002607 -0.001704 0.015858\natom 7.94212 5.20044 8.06655 Cu 0.0 0.0 -0.002607 -0.001704 -0.015858\natom -4.22706 2.43028 9.33742 Cu 0.0 0.0 -0.057628 -0.032284 0.078709\natom 10.48903 8.37228 8.80053 Cu 0.0 0.0 0.057628 -0.032284 -0.078709\natom 13.48370 9.45372 2.75455 Cu 0.0 0.0 0.057628 0.032284 -0.078709\natom -1.23238 3.51172 3.29143 Cu 0.0 0.0 -0.057628 0.032284 0.078709\natom 5.96526 0.94478 3.42686 Cu 0.0 0.0 -0.017114 0.034111 0.052038\natom 6.28607 6.88678 2.61912 Cu 0.0 0.0 0.017114 0.034111 -0.052038\natom 3.29139 10.93922 8.66510 Cu 0.0 0.0 0.017114 -0.034111 -0.052038\natom 2.97058 4.99722 9.47285 Cu 0.0 0.0 -0.017114 -0.034111 0.052038\natom 0.87597 0.51577 7.53329 Cu 0.0 0.0 -0.012110 -0.004506 0.081390\natom 5.38599 6.45777 10.60465 Cu 0.0 0.0 0.012110 -0.004506 -0.081390\natom 8.38067 11.36823 4.55867 Cu 0.0 0.0 0.012110 0.004506 -0.081390\natom 3.87065 5.42623 1.48731 Cu 0.0 0.0 -0.012110 0.004506 0.081390\natom 3.84806 0.51220 1.61911 Cu 0.0 0.0 0.106207 0.025692 0.047083\natom 8.40327 6.45420 4.42687 Cu 0.0 0.0 -0.106207 0.025692 -0.047083\natom 5.40859 11.37180 10.47285 Cu 0.0 0.0 -0.106207 -0.025692 -0.047083\natom 0.85338 5.42980 7.66510 Cu 0.0 0.0 0.106207 -0.025692 0.047083\natom 3.47571 2.47425 9.12097 Cu 0.0 0.0 0.013369 -0.021692 -0.063355\natom 2.78626 8.41625 9.01698 Cu 0.0 0.0 -0.013369 -0.021692 0.063355\natom 5.78094 9.40975 2.97100 Cu 0.0 0.0 -0.013369 0.021692 0.063355\natom 6.47038 3.46775 3.07499 Cu 0.0 0.0 0.013369 0.021692 -0.063355\natom 13.93651 1.01727 2.61912 Cu 0.0 0.0 0.070095 0.058281 0.058871\natom -1.68519 6.95927 3.42686 Cu 0.0 0.0 -0.070095 0.058281 -0.058871\natom -4.67987 10.86673 9.47285 Cu 0.0 0.0 -0.070095 -0.058281 -0.058871\natom 10.94183 4.92473 8.66510 Cu 0.0 0.0 0.070095 -0.058281 0.058871\natom 3.78523 1.22643 11.52485 Cu 0.0 0.0 -0.055512 0.072701 0.045980\natom 2.47674 7.16843 6.61310 Cu 0.0 0.0 0.055512 0.072701 -0.045980\natom 5.47141 10.65757 0.56711 Cu 0.0 0.0 0.055512 -0.072701 -0.045980\natom 6.77991 4.71557 5.47887 Cu 0.0 0.0 -0.055512 -0.072701 0.045980\natom 7.33923 2.31025 6.84284 Cu 0.0 0.0 0.008001 0.031273 -0.008244\natom -1.07727 8.25225 11.29511 Cu 0.0 0.0 -0.008001 0.031273 0.008244\natom 1.91741 9.57375 5.24912 Cu 0.0 0.0 -0.008001 -0.031273 0.008244\natom 10.33391 3.63175 0.79686 Cu 0.0 0.0 0.008001 -0.031273 -0.008244\natom 2.25458 2.45880 1.69046 Cu 0.0 0.0 0.009284 0.010061 0.048810\natom 9.99674 8.40080 4.35553 Cu 0.0 0.0 -0.009284 0.010061 -0.048810\natom 7.00207 9.42520 10.40151 Cu 0.0 0.0 -0.009284 -0.010061 -0.048810\natom -0.74010 3.48320 7.73644 Cu 0.0 0.0 0.009284 -0.010061 0.048810\natom -2.07320 1.14799 8.21165 Cu 0.0 0.0 0.008891 0.031001 0.014345\natom 8.33516 7.08999 9.92629 Cu 0.0 0.0 -0.008891 0.031001 -0.014345\natom 11.32984 10.73601 3.88031 Cu 0.0 0.0 -0.008891 -0.031001 -0.014345\natom 0.92148 4.79401 2.16567 Cu 0.0 0.0 0.008891 -0.031001 0.014345\nenergy -573.700369\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/configuration-single/input.data.DMABN",
    "content": "begin\ncomment       frame number       51\natom      19.83251167146305      16.41913713228821      14.16783556224251     C  0.00  0.00       0.00570937805307       0.08432160529386      -0.03802980568277\natom      19.94312355646866      11.69393878949732      14.17410262328673     C  0.00  0.00      -0.07435648445475       0.02184249364754       0.00881332970143\natom      15.84154197252689      14.18721189705679      14.24155885726955     C  0.00  0.00       0.02998903171000       0.01161345609006      -0.01614157184062\natom      14.46771974192691      16.52911346925335      14.15446414798641     C  0.00  0.00       0.02825211245628      -0.00679186972071       0.01067765902089\natom      11.90001209045941      16.50440326164718      14.10001557121353     C  0.00  0.00       0.00762251101379      -0.04054091659537       0.01107218637850\natom      10.52693843736862      14.19175453817904      14.24867638671206     C  0.00  0.00       0.04489483017033      -0.00970003430984      -0.02024170809199\natom      11.88525530053014      11.87627801089468      14.03804339218586     C  0.00  0.00       0.01050492288895      -0.03025563548793       0.04062107513648\natom      14.55399939930356      11.88307666854348      14.16029752399963     C  0.00  0.00      -0.00430630286069      -0.01331581049870      -0.00376499999923\natom       7.94035181627116      14.20878640658312      14.21053262433509     C  0.00  0.00      -0.07441555771308      -0.00325503384669       0.00082781395929\natom      18.51576746385395      14.23362538195587      14.14454518191298     N  0.00  0.00      -0.03910867744178      -0.07459503409686       0.00679871752372\natom       5.70790049494324      14.17883214623779      14.18710950383843     N  0.00  0.00       0.04080327791136       0.00177504000833       0.00118773139851\natom      21.79028529767151      16.11497933011361      14.26552105714931     H  0.00  0.00       0.02518293764933      -0.00361728537155       0.00618743342718\natom      19.61077628263096      17.86917886537563      12.41697223367492     H  0.00  0.00      -0.00091709441398      -0.03521300054738       0.01742148802879\natom      19.21953158661805      17.71831608185630      15.59063976560335     H  0.00  0.00       0.00199657064710       0.00520019321164       0.02297470209990\natom      21.82497590676626      12.12531471861068      14.29058750869887     H  0.00  0.00       0.04538124820076       0.00616351842390      -0.00154483025617\natom      19.32669969441613      10.57749722415571      15.86241146777433     H  0.00  0.00       0.00591786395647       0.00729899135856      -0.01249697562980\natom      19.35969488797767      10.76021845677893      12.44205910126362     H  0.00  0.00       0.00829470188437      -0.00858990474455      -0.00147517152114\natom      15.56901622106281      18.30123521694460      14.42236692729784     H  0.00  0.00      -0.01360814881885      -0.01287249963721      -0.00929548183066\natom      10.91615035702339      18.17723906171991      14.17763298181264     H  0.00  0.00      -0.02115105437214       0.03530021184193       0.00007051927839\natom      11.03999403230822       9.89099801104345      14.54005436633091     H  0.00  0.00       0.00478517659222       0.04200087762286      -0.02092001237780\natom      15.70700931574327      10.08078663320902      14.18667669126373     H  0.00  0.00      -0.02236155378428       0.02151554633149      -0.00040927268169\nenergy     -76.86434126036589\ncharge       0\nend\n"
  },
  {
    "path": "examples/configuration-single/input.data.Ethylbenzene",
    "content": "begin\ncomment       frame number       51\nlattice   28.0069   0.0000   0.0000\nlattice    0.0000  28.0069   0.0000\nlattice    0.0000   0.0000  28.0069\natom       0.56526262299801      13.31517334680679       6.34522126057460     C  0.00  0.00      -0.03113424307455      -0.01537473276533      -0.00015747921029\natom       0.90032952776671      14.97008713320335       8.34814801930335     C  0.00  0.00      -0.00918702883818      -0.00621123467824       0.00569078114988\natom       1.22144598563829      22.64678760266016       4.42245898770571     C  0.00  0.00      -0.00640475619597       0.00398620895847       0.00850240190023\natom       1.06572501490317      14.18328710792346       3.92303174139759     C  0.00  0.00      -0.00334927089300      -0.00621053489691      -0.00707908580865\natom       1.62275720525955      21.37062188986548      17.55963435321880     C  0.00  0.00      -0.00479777831613      -0.01234629445177      -0.01383075643633\natom       1.67366171913499       8.54531739390388      22.53841032174025     C  0.00  0.00       0.03024889501062      -0.00416721250475      -0.01310658559641\natom       1.57960136982838       9.08630561150544      11.63757358555911     C  0.00  0.00       0.00885756614318      -0.01535898558112       0.01669466739678\natom       1.63309820104926       5.08902942212961      17.44145754223917     C  0.00  0.00       0.00318055010079       0.01347561878931       0.01519802190954\natom       1.60174664167610      13.54360133892586      15.98380463708957     C  0.00  0.00      -0.00914277689309      -0.00170769481885      -0.02660005239701\natom       1.77508606568939      17.37866243386567       7.84907198266061     C  0.00  0.00       0.00578322021348       0.02128793139007       0.01941973080386\natom      19.42017503029161       1.84646074163295      13.03284311649700     C  0.00  0.00       0.01496461886347       0.00759956901463       0.02436126347362\natom      19.98920982307874      10.07167913088219      20.37562704854361     C  0.00  0.00      -0.00454856413741       0.03094354715905      -0.06047735409984\natom      19.88050961896570       9.42323669072232      17.76602680405809     C  0.00  0.00      -0.00393495444235      -0.00815061193791       0.00862027080651\natom      20.32836026642741      12.56485006093525      21.00610457525624     C  0.00  0.00      -0.00833704700464      -0.00083921744336      -0.04110955866970\natom       2.04706619055359       4.89158108004898       2.06036182657225     C  0.00  0.00      -0.01662741018271       0.00818053485893       0.00378802667561\natom      20.19957603885057      11.10564526227436      15.77573862409358     C  0.00  0.00       0.01223748995540       0.00549500550399       0.02554327662469\natom      20.49549529567459      14.31191216707652      19.02566996711138     C  0.00  0.00       0.01146820995559       0.02489913778494       0.00171862924228\natom      20.59733903109143      13.63009591547120      16.42572519641251     C  0.00  0.00      -0.00926093855168       0.00165723624677       0.02021657587443\natom      20.75827949925510       2.28798263181872       3.10599451219084     C  0.00  0.00       0.00634967573579       0.02372679561522      -0.02353951792925\natom      20.87493849885538       1.18413668648834      23.00240055095743     C  0.00  0.00      -0.03167266336860       0.00841213897080       0.02028357808554\natom      21.05605175511753      15.51055897252136      14.42327650834872     C  0.00  0.00      -0.02492143128553       0.02449392954586      -0.01040836807155\natom       2.09589778195885      16.53692074122318       3.46040399095607     C  0.00  0.00      -0.03479375606366       0.01434664228727       0.02765182461407\natom      21.10788097034883      16.27212456961610       2.14013214980539     C  0.00  0.00       0.01789891290779      -0.00132139005110       0.04424729285422\natom      21.56208976987802       6.93830684758924       3.69752198938163     C  0.00  0.00       0.01190847181747      -0.00251621453919      -0.00743722503517\natom      21.79162413090577       4.47997729171169       4.62773289817370     C  0.00  0.00      -0.01161946725410       0.00690421952786       0.01533707188642\natom      22.37147250522815       9.06519531018642       5.03653857918100     C  0.00  0.00      -0.00959004801381      -0.02158297332834       0.00415667163388\natom      21.99024724602286      18.54068040466066       3.66228471707080     C  0.00  0.00       0.00637562882358       0.00562766580030       0.00031699823548\natom       2.07845902589428       8.18291624574512       9.21113091919115     C  0.00  0.00       0.04243780665518       0.04266981302250       0.02456611036710\natom       2.06772823560957       4.93377590878455      14.88921190162479     C  0.00  0.00       0.02793092128793       0.01798557539395       0.01079257455876\natom      22.52007313862244      20.78295180307453       2.37009325182745     C  0.00  0.00      -0.00622074103648       0.00546722692857      -0.03818909078255\natom      22.60417310262147      18.52966939056008       6.24586959096211     C  0.00  0.00       0.01519242748229       0.02153696228349      -0.01426571122083\natom      22.78108107796566       4.14500168473142       7.07959557786557     C  0.00  0.00       0.00146453060873       0.00393117466517      -0.02151235386404\natom      22.88060674484136       1.36715380361950       1.34196273054029     C  0.00  0.00      -0.01335137583922       0.01268993180563       0.00614549093632\natom      23.39906841916602       8.65455073811154       7.37971566407711     C  0.00  0.00       0.00532687209478      -0.02671960290704      -0.00324999410307\natom      23.28654805499568      23.04697583038289       3.43567426847633     C  0.00  0.00      -0.02370347899049      -0.00722062769825       0.01401692700955\natom      23.30770405709121      14.69991553748173       1.31234942980960     C  0.00  0.00       0.02988886561591       0.00739620546839       0.00973104755390\natom      23.62595792713298      20.72359991940420       7.36533333788752     C  0.00  0.00      -0.01494553750117      -0.00436941457723      -0.01159860633750\natom      23.74919548111163       6.21793952686716       8.36146836213127     C  0.00  0.00      -0.01452196881092       0.00574999631110      -0.00661268971557\natom      23.69539966201250       1.80332988174515      22.58079619886890     C  0.00  0.00      -0.00143222453887      -0.01701969562929       0.03914787389846\natom      23.74011159054143      16.01032658012861      13.94950307715662     C  0.00  0.00       0.02671363629700       0.01167469583817       0.00710334458671\natom      23.69263037177299      23.01492847615055       6.02819725607590     C  0.00  0.00       0.03090908136976       0.00766343819721       0.00024104051061\natom      23.93729685619517       3.49264335463377      20.41033270701973     C  0.00  0.00       0.00919514494476       0.01709432063394      -0.02579032628563\natom      24.09293624876284       6.11980551889360      20.84728213934916     C  0.00  0.00      -0.00997591661876      -0.00482128222309       0.01042457630781\natom      24.00778229306282       2.57052805836606      17.87986297682389     C  0.00  0.00      -0.00455418111259       0.02127733780004       0.01408291231464\natom      24.36851301843411       7.77414790111594      18.85669000114838     C  0.00  0.00       0.00728215431556      -0.01112273924305      -0.02897229585797\natom       2.40133730236385      18.27619010773118       5.46848410196132     C  0.00  0.00      -0.02387232872724      -0.02665865511050       0.00071933460532\natom      24.30262341809173       4.22886811652232      15.85071692999344     C  0.00  0.00       0.00484431503534       0.02460890060767       0.05091345002168\natom      24.57486502131593       6.80640747477542      16.36314469082321     C  0.00  0.00      -0.01106774001053      -0.00809060833390       0.01481757318097\natom       2.55552089910938      20.99178673481072      15.15244931201936     C  0.00  0.00      -0.01196261031803      -0.00927319366083      -0.00912422098771\natom       2.71032952672826      20.26364681415319      19.63255479434139     C  0.00  0.00      -0.01124250141944      -0.01381761320272       0.02292766011508\natom       2.91227106866145       2.45113971135536       1.97703613252853     C  0.00  0.00       0.02596275148344      -0.00735802028859      -0.01715280381037\natom       2.94567450107410       6.04261680483679      21.82943821979898     C  0.00  0.00       0.00080183056371      -0.00695773174189       0.02238614071066\natom       3.03909829140582      11.10690421862281      15.79816268176167     C  0.00  0.00      -0.01923826194167      -0.02644234121965       0.01715115797532\natom       3.30317050863200       0.42348132048328      15.78986021939246     C  0.00  0.00       0.01843501212655      -0.01694049181028      -0.00272985204716\natom       3.35596878919189      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0.0000000000000000E+00 \natom   3.5691481140492854E+01   4.7402963911951463E+00   2.8731679608676199E+01  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.4321996612052693E+01   4.1176883222215315E+00   3.1401673661709321E+01  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.5398907894673455E+00   3.6593444496626631E+01   2.6212485701040521E+01  O   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.2832901528495384E+00   3.8271710275166313E+01   2.5880460819507562E+01  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.9603443041051376E+00   3.6967043353081195E+01   2.7111995340253323E+01  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3329690406923969E+01   2.7628961667849993E+01   1.2098952694655752E+01  O   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4472577874780081E+01   2.6346971459358471E+01   1.1391099079831529E+01  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1736840249586850E+01   2.6907464230346957E+01   1.2589242139810713E+01  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\n"
  },
  {
    "path": "examples/input.nn.recommended",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type (optional argument: shift parameter alpha).\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              15 15          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nnormalize_data_set              force          # Normalize data set prior to training (ref = via ref. data, force = via force prediction, stats-only = use existing).\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    1.0            # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\n#short_force_fraction            0.02315        # Fraction of force updates per epoch (not necessary if force_energy_ratio given).\nforce_energy_ratio              3.0            # Specifies ratio between force and energy updates (ratio = updates_force / updates_energy).\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Weighted radial symmetry function (type 12):\n#symfunction_short <element-central> 12 <eta> <rshift> <rcutoff>\n\n# Weighted narrow Angular symmetry function (type 13):\n#symfunction_short <element-central> 13 <eta> <rshift> <lambda> <zeta> <rcutoff>\n\n# Radial symmetry function with compact support (type 20):\n#symfunction_short <element-central> 20 <element-neighbor> <rlow> <rcutoff> <subtype>\n\n# Narrow angular symmetry function with compact support (type 21):\n#symfunction_short <element-central> 21 <element-neighbor1> <element-neighbor2> <rlow> <rcutoff> <left> <right> <subtype>\n\n# Wide angular symmetry function with compact support (type 22):\n#symfunction_short <element-central> 22 <element-neighbor1> <element-neighbor2> <rlow> <rcutoff> <left> <right> <subtype>\n\n# Weighted radial symmetry function with compact support (type 23):\n#symfunction_short <element-central> 23 <rlow> <rcutoff> <subtype>\n\n# Weighted narrow angular symmetry function with compact support (type 24):\n#symfunction_short <element-central> 24 <rlow> <rcutoff> <left> <right> <subtype>\n\n# Weighted wide angular symmetry function with compact support (type 24):\n#symfunction_short <element-central> 25 <rlow> <rcutoff> <left> <right> <subtype>\n\n##############################\n# EXAMPLE SYMMETRY FUNCTIONS #\n##############################\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/AlAuMgO.data",
    "content": "MgO with Al/Au, first structure from input.data (wrapped into box)\n\n110 atoms\n\n4 atom types\n\n0.0 1.7097166001000002E+01 xlo xhi\n0.0 1.7097166001000002E+01 ylo yhi\n0.0 5.0000000000999997E+01 zlo zhi\n\nAtoms\n\n1 2 0.0   1.7077390207502003E+01   1.7033133769712002E+01   2.0026111118999999E+01\n2 1 0.0   2.8784590472999998E+00   2.8904829958000002E+00   2.0053576907000000E+01\n3 1 0.0   7.2652159692999999E-02   1.7080954778737002E+01   2.4043132172000000E+01\n4 2 0.0   2.8780260733000000E+00   2.8998185634999998E+00   2.4032640394000001E+01\n5 2 0.0   1.7040370588769001E+01   1.7074725410399001E+01   2.8111288945999998E+01\n6 1 0.0   2.8421666140000004E+00   2.8834652149000006E+00   2.8032859288999997E+01\n7 1 0.0   6.5214500558000016E-02   1.7058420249857001E+01   3.2113867333000002E+01\n8 2 0.0   2.8332198764000003E+00   2.7977822229000000E+00   3.2113907679000000E+01\n9 3 0.0   1.9864553928000000E-02   1.0486013922000000E-02   3.6088078099000001E+01\n10 1 0.0  2.7981764574999999E+00   2.8796998035999999E+00   3.6124511960000000E+01\n11 1 0.0  1.7088713823570803E+01   1.7074561363286001E+01   4.0153894391000001E+01\n12 2 0.0  2.8234702698000000E+00   2.8619477365999999E+00   4.0124676317000002E+01\n13 2 0.0  1.7084046370454001E+01   5.6888413584000004E+00   2.0013899747000000E+01\n14 1 0.0  2.8848335277000001E+00   8.5308909416999992E+00   1.9989943256000000E+01\n15 1 0.0  1.8241298201000001E-02   5.6837552365000006E+00   2.4026099825999999E+01\n16 2 0.0  2.9361062157000006E+00   8.4795591997000006E+00   2.4082757439000002E+01\n17 2 0.0  1.6188356579000002E-02   5.6698041264999999E+00   2.8051270020000000E+01\n18 1 0.0  2.8977599905000000E+00   8.5660735577999993E+00   2.8036115495000001E+01\n19 1 0.0  9.8433937020000009E-04   5.6927154290000006E+00   3.2118501962000003E+01\n20 2 0.0  2.8073628502000005E+00   8.5498039808000019E+00   3.2128399704000003E+01\n21 2 0.0  1.7046169666499001E+01   5.7492786883000013E+00   3.6121753734000002E+01\n22 1 0.0  2.9059518581000003E+00   8.5723518133999992E+00   3.6118083753999997E+01\n23 1 0.0  5.2199900982999997E-04   5.6455106974000007E+00   4.0180597257999999E+01\n24 2 0.0  2.8610732470000007E+00   8.5614353198999993E+00   4.0139419523999997E+01\n25 2 0.0  1.7057826762513002E+01   1.1415957378000000E+01   1.9959977720000001E+01\n26 1 0.0  2.9183726113000006E+00   1.4291678041999999E+01   1.9988445497000001E+01\n27 1 0.0  1.7075894413793002E+01   1.1421205582000002E+01   2.4027048543999999E+01\n28 2 0.0  2.9026486927000001E+00   1.4185336528000002E+01   2.4050086987000000E+01\n29 2 0.0  1.7045656265742000E+01   1.1382810885000000E+01   2.8094293014999998E+01\n30 1 0.0  2.9119668371000000E+00   1.4181088046000001E+01   2.8044752600999999E+01\n31 1 0.0  1.0413278368000002E-02   1.1323763827000002E+01   3.2100372837999998E+01\n32 2 0.0  2.7888050607000006E+00   1.4200832470000002E+01   3.2081624640000001E+01\n33 2 0.0  1.7091929343518501E+01   1.1380297133999999E+01   3.6148026784000002E+01\n34 1 0.0  2.8964801357000005E+00   1.4225437477000002E+01   3.6102833042000000E+01\n35 1 0.0  1.7049035190295999E+01   1.1455866520000002E+01   4.0155035312999999E+01\n36 2 0.0  2.8743271236000005E+00   1.4294384262000001E+01   4.0132651035999999E+01\n37 2 0.0  5.7360837333000001E+00   1.7083132839117003E+01   2.0040227467000001E+01\n38 1 0.0  8.5193853072000003E+00   2.8764031199000000E+00   1.9994398985000000E+01\n39 1 0.0  5.6375475999000004E+00   1.7056498228451002E+01   2.4029267612000002E+01\n40 2 0.0  8.5444746323000018E+00   2.8328648157999998E+00   2.4073209125999998E+01\n41 2 0.0  5.6374929679000001E+00   8.9788629595000009E-03   2.8040190972000001E+01\n42 1 0.0  8.5205746819000012E+00   2.8135749087000006E+00   2.8097702553000001E+01\n43 1 0.0  5.7090540565000003E+00   1.6821528168000002E-02   3.2068389906000000E+01\n44 2 0.0  8.5099907611999992E+00   2.8387661466000003E+00   3.2089405585999998E+01\n45 2 0.0  5.7491607504999998E+00   2.6551802873000005E-02   3.6161801185000002E+01\n46 1 0.0  8.5696933089999998E+00   2.8243981820000004E+00   3.6095548903999997E+01\n47 1 0.0  5.6004605746999996E+00   1.7058153326061003E+01   4.0102869652999999E+01\n48 2 0.0  8.5839177868000025E+00   2.8525893410000003E+00   4.0129186941000000E+01\n49 2 0.0  5.6735244868000008E+00   5.6849201959000011E+00   1.9979804725000001E+01\n50 1 0.0  8.5832999976000011E+00   8.5656793231999995E+00   1.9987182838999999E+01\n51 1 0.0  5.7075209596000001E+00   5.6897493150000011E+00   2.4036549652000001E+01\n52 2 0.0  8.6020291474000015E+00   8.5486919148999991E+00   2.3965788408999998E+01\n53 2 0.0  5.7493104546000007E+00   5.6905967816000000E+00   2.8035716479000001E+01\n54 1 0.0  8.5305642648000024E+00   8.5336383575999992E+00   2.8041326564999999E+01\n55 1 0.0  5.6467260935000008E+00   5.6755829275000007E+00   3.2090861072000003E+01\n56 2 0.0  8.5337005863000002E+00   8.5466174492999993E+00   3.2081751156999999E+01\n57 3 0.0  5.6610188848999998E+00   5.6993559449999998E+00   3.6064080941000000E+01\n58 1 0.0  8.5010303797999995E+00   8.5362875267000007E+00   3.6131963186999997E+01\n59 1 0.0  5.6984002350000003E+00   5.7462274801000000E+00   4.0178786901000002E+01\n60 2 0.0  8.5592887233999999E+00   8.5947597306000016E+00   4.0146193152000002E+01\n61 2 0.0  5.6032739042000008E+00   1.1399683984000001E+01   1.9913916443000002E+01\n62 1 0.0  8.5029228270000008E+00   1.4343324046000001E+01   2.0023014406000001E+01\n63 1 0.0  5.6720512753000012E+00   1.1358988262000000E+01   2.4060251955999998E+01\n64 2 0.0  8.5254411798000014E+00   1.4231011829000000E+01   2.4012346344000001E+01\n65 2 0.0  5.7426630599999999E+00   1.1378874679999999E+01   2.8023933603000000E+01\n66 1 0.0  8.6362523685000010E+00   1.4255022857000000E+01   2.8036097202000001E+01\n67 1 0.0  5.7117658322000002E+00   1.1454697101000001E+01   3.2073160784000002E+01\n68 2 0.0  8.5246584174999995E+00   1.4270581047000002E+01   3.2102696917000003E+01\n69 2 0.0  5.7186666391000012E+00   1.1422359334999999E+01   3.6101213659999999E+01\n70 1 0.0  8.5627598477000006E+00   1.4273198941000002E+01   3.6166519037999997E+01\n71 1 0.0  5.7264381750000002E+00   1.1398781375000002E+01   4.0260042284000001E+01\n72 2 0.0  8.5102664156000021E+00   1.4232221424000002E+01   4.0091178051000000E+01\n73 2 0.0  1.1401532344000001E+01   4.5076087540000004E-02   2.0029059109999999E+01\n74 1 0.0  1.4239757122000000E+01   2.8608573080000004E+00   1.9951038843999999E+01\n75 1 0.0  1.1393443466000003E+01   1.7096738299317003E+01   2.4001081706000001E+01\n76 2 0.0  1.4231685554000000E+01   2.8864018680000005E+00   2.4021645382999999E+01\n77 2 0.0  1.1402686003000001E+01   3.9371628390000003E-02   2.8113584924999998E+01\n78 1 0.0  1.4244927525000000E+01   2.8375641675000005E+00   2.8036863637000000E+01\n79 1 0.0  1.1395989211000002E+01   4.7920427509000009E-03   3.2086785538000001E+01\n80 2 0.0  1.4238799238000002E+01   2.8820363931000004E+00   3.2090336899999997E+01\n81 2 0.0  1.1420507253000000E+01   1.8697459156999999E-02   3.6120652571999997E+01\n82 1 0.0  1.4268517750000003E+01   2.8561106375000000E+00   3.6168027133000002E+01\n83 1 0.0  1.1414591957000003E+01   1.7014573542456002E+01   4.0173253651000003E+01\n84 2 0.0  1.4256298422000002E+01   2.8717039193999998E+00   4.0140854601000001E+01\n85 2 0.0  1.1393721861000001E+01   5.7236951243999998E+00   2.0010035087999999E+01\n86 1 0.0  1.4257639788000002E+01   8.4981605285000015E+00   1.9925047364000001E+01\n87 1 0.0  1.1373306754000000E+01   5.7232945403000013E+00   2.3983895820000001E+01\n88 2 0.0  1.4251016393000000E+01   8.5961130012000027E+00   2.4011062539000001E+01\n89 2 0.0  1.1392303111000002E+01   5.6922237034000007E+00   2.8086502354999997E+01\n90 1 0.0  1.4307995467000000E+01   8.5052796176999994E+00   2.8127594521999999E+01\n91 1 0.0  1.1467787838000001E+01   5.7303018143000006E+00   3.2140124452000002E+01\n92 2 0.0  1.4223684114000001E+01   8.5394621151999992E+00   3.2083417384999997E+01\n93 2 0.0  1.1398360231000000E+01   5.6984501048000000E+00   3.6109137658999998E+01\n94 1 0.0  1.4243599161000002E+01   8.4926708933999997E+00   3.6111924268000003E+01\n95 1 0.0  1.1387116342000001E+01   5.7224672938000012E+00   4.0150551843000002E+01\n96 2 0.0  1.4251826367000001E+01   8.5541300360000001E+00   4.0169736718999999E+01\n97 2 0.0  1.1397087406000001E+01   1.1432029951000001E+01   1.9991521328999998E+01\n98 1 0.0  1.4222100486000002E+01   1.4237423386000001E+01   1.9890837445999999E+01\n99 1 0.0  1.1397172084999999E+01   1.1362254483999999E+01   2.4106729256000001E+01\n100 2 0.0 1.4223050564000001E+01   1.4272733426000002E+01   2.4026767277000001E+01\n101 2 0.0 1.1412415162000000E+01   1.1398466358000000E+01   2.8036581274000000E+01\n102 1 0.0 1.4265352610000001E+01   1.4216093689000001E+01   2.8052093902999996E+01\n103 1 0.0 1.1401696598999999E+01   1.1369599225000000E+01   3.2083243398000000E+01\n104 2 0.0 1.4233083328000001E+01   1.4215807831000001E+01   3.2083725031999997E+01\n105 3 0.0 1.1446195847000000E+01   1.1455486685000000E+01   3.6062830566000002E+01\n106 1 0.0 1.4275939497000001E+01   1.4231407235000002E+01   3.6076973256999999E+01\n107 1 0.0 1.1412436308000000E+01   1.1399368513000002E+01   4.0122450030000003E+01\n108 2 0.0 1.4206953179000001E+01   1.4201432515000002E+01   4.0151366428999999E+01\n109 4 0.0 2.7674441650000001E+00   3.2676547854000000E+00   1.5266538963000000E+01\n110 4 0.0 2.7884963172999999E+00   3.1844017731000003E+00   1.0716139441999999E+01\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/AlAuMgO.data-n2p2",
    "content": "MgO with Al/Au, first structure from input.data (wrapped into box)\n\n110 atoms\n\n4 atom types\n\n#0.0 1.7097166001000002E+01 xlo xhi\n#0.0 1.7097166001000002E+01 ylo yhi\n#0.0 5.0000000000999997E+01 zlo zhi\n-1.0 1.6097166001000002E+01 xlo xhi\n-1.0 1.6097166001000002E+01 ylo yhi\n-1.0 4.0000000000999997E+01 zlo zhi\n\nAtoms\n\n1 2 0.0 -1.9775793498e-02 -6.4032231288e-02  2.0026111119e+01 \n2 1 0.0  2.8784590473e+00  2.8904829958e+00  2.0053576907e+01 \n3 1 0.0  7.2652159693e-02 -1.6211222263e-02  2.4043132172e+01\n4 2 0.0  2.8780260733e+00  2.8998185635e+00  2.4032640394e+01 \n5 2 0.0 -5.6795412231e-02 -2.2440590601e-02  2.8111288946e+01 \n6 1 0.0  2.8421666140e+00  2.8834652149e+00  2.8032859289e+01 \n7 1 0.0  6.5214500558e-02 -3.8745751143e-02  3.2113867333e+01 \n8 2 0.0  2.8332198764e+00  2.7977822229e+00  3.2113907679e+01 \n9 3 0.0  1.9864553928e-02  1.0486013922e-02  3.6088078099e+01 \n10 1 0.0  2.7981764575e+00  2.8796998036e+00  3.6124511960e+01 \n11 1 0.0 -8.4521774292e-03 -2.2604637714e-02  4.0153894391e+01\n12 2 0.0  2.8234702698e+00  2.8619477366e+00  4.0124676317e+01 \n13 2 0.0 -1.3119630546e-02  5.6888413584e+00  2.0013899747e+01\n14 1 0.0  2.8848335277e+00  8.5308909417e+00  1.9989943256e+01 \n15 1 0.0  1.8241298201e-02  5.6837552365e+00  2.4026099826e+01 \n16 2 0.0  2.9361062157e+00  8.4795591997e+00  2.4082757439e+01 \n17 2 0.0  1.6188356579e-02  5.6698041265e+00  2.8051270020e+01 \n18 1 0.0  2.8977599905e+00  8.5660735578e+00  2.8036115495e+01 \n19 1 0.0  9.8433937020e-04  5.6927154290e+00  3.2118501962e+01 \n20 2 0.0  2.8073628502e+00  8.5498039808e+00  3.2128399704e+01 \n21 2 0.0 -5.0996334501e-02  5.7492786883e+00  3.6121753734e+01 \n22 1 0.0  2.9059518581e+00  8.5723518134e+00  3.6118083754e+01 \n23 1 0.0  5.2199900983e-04  5.6455106974e+00  4.0180597258e+01 \n24 2 0.0  2.8610732470e+00  8.5614353199e+00  4.0139419524e+01 \n25 2 0.0 -3.9339238487e-02  1.1415957378e+01  1.9959977720e+01 \n26 1 0.0  2.9183726113e+00  1.4291678042e+01  1.9988445497e+01   \n27 1 0.0 -2.1271587207e-02  1.1421205582e+01  2.4027048544e+01 \n28 2 0.0  2.9026486927e+00  1.4185336528e+01  2.4050086987e+01 \n29 2 0.0 -5.1509735258e-02  1.1382810885e+01  2.8094293015e+01 \n30 1 0.0  2.9119668371e+00  1.4181088046e+01  2.8044752601e+01 \n31 1 0.0  1.0413278368e-02  1.1323763827e+01  3.2100372838e+01 \n32 2 0.0  2.7888050607e+00  1.4200832470e+01  3.2081624640e+01 \n33 2 0.0 -5.2366574815e-03  1.1380297134e+01  3.6148026784e+01 \n34 1 0.0  2.8964801357e+00  1.4225437477e+01  3.6102833042e+01 \n35 1 0.0 -4.8130810704e-02  1.1455866520e+01  4.0155035313e+01 \n36 2 0.0  2.8743271236e+00  1.4294384262e+01  4.0132651036e+01 \n37 2 0.0  5.7360837333e+00 -1.4033161883e-02  2.0040227467e+01 \n38 1 0.0  8.5193853072e+00  2.8764031199e+00  1.9994398985e+01 \n39 1 0.0  5.6375475999e+00 -4.0667772549e-02  2.4029267612e+01 \n40 2 0.0  8.5444746323e+00  2.8328648158e+00  2.4073209126e+01 \n41 2 0.0  5.6374929679e+00  8.9788629595e-03  2.8040190972e+01 \n42 1 0.0  8.5205746819e+00  2.8135749087e+00  2.8097702553e+01 \n43 1 0.0  5.7090540565e+00  1.6821528168e-02  3.2068389906e+01 \n44 2 0.0  8.5099907612e+00  2.8387661466e+00  3.2089405586e+01 \n45 2 0.0  5.7491607505e+00  2.6551802873e-02  3.6161801185e+01 \n46 1 0.0  8.5696933090e+00  2.8243981820e+00  3.6095548904e+01 \n47 1 0.0  5.6004605747e+00 -3.9012674939e-02  4.0102869653e+01 \n48 2 0.0  8.5839177868e+00  2.8525893410e+00  4.0129186941e+01 \n49 2 0.0  5.6735244868e+00  5.6849201959e+00  1.9979804725e+01 \n50 1 0.0  8.5832999976e+00  8.5656793232e+00  1.9987182839e+01 \n51 1 0.0  5.7075209596e+00  5.6897493150e+00  2.4036549652e+01 \n52 2 0.0  8.6020291474e+00  8.5486919149e+00  2.3965788409e+01 \n53 2 0.0  5.7493104546e+00  5.6905967816e+00  2.8035716479e+01 \n54 1 0.0  8.5305642648e+00  8.5336383576e+00  2.8041326565e+01 \n55 1 0.0  5.6467260935e+00  5.6755829275e+00  3.2090861072e+01 \n56 2 0.0  8.5337005863e+00  8.5466174493e+00  3.2081751157e+01 \n57 3 0.0  5.6610188849e+00  5.6993559450e+00  3.6064080941e+01 \n58 1 0.0  8.5010303798e+00  8.5362875267e+00  3.6131963187e+01 \n59 1 0.0  5.6984002350e+00  5.7462274801e+00  4.0178786901e+01 \n60 2 0.0  8.5592887234e+00  8.5947597306e+00  4.0146193152e+01 \n61 2 0.0  5.6032739042e+00  1.1399683984e+01  1.9913916443e+01 \n62 1 0.0  8.5029228270e+00  1.4343324046e+01  2.0023014406e+01 \n63 1 0.0  5.6720512753e+00  1.1358988262e+01  2.4060251956e+01 \n64 2 0.0  8.5254411798e+00  1.4231011829e+01  2.4012346344e+01 \n65 2 0.0  5.7426630600e+00  1.1378874680e+01  2.8023933603e+01 \n66 1 0.0  8.6362523685e+00  1.4255022857e+01  2.8036097202e+01 \n67 1 0.0  5.7117658322e+00  1.1454697101e+01  3.2073160784e+01 \n68 2 0.0  8.5246584175e+00  1.4270581047e+01  3.2102696917e+01 \n69 2 0.0  5.7186666391e+00  1.1422359335e+01  3.6101213660e+01 \n70 1 0.0  8.5627598477e+00  1.4273198941e+01  3.6166519038e+01 \n71 1 0.0  5.7264381750e+00  1.1398781375e+01  4.0260042284e+01 \n72 2 0.0  8.5102664156e+00  1.4232221424e+01  4.0091178051e+01 \n73 2 0.0  1.1401532344e+01  4.5076087540e-02  2.0029059110e+01 \n74 1 0.0  1.4239757122e+01  2.8608573080e+00  1.9951038844e+01 \n75 1 0.0  1.1393443466e+01 -4.2770168300e-04  2.4001081706e+01 \n76 2 0.0  1.4231685554e+01  2.8864018680e+00  2.4021645383e+01 \n77 2 0.0  1.1402686003e+01  3.9371628390e-02  2.8113584925e+01 \n78 1 0.0  1.4244927525e+01  2.8375641675e+00  2.8036863637e+01 \n79 1 0.0  1.1395989211e+01  4.7920427509e-03  3.2086785538e+01 \n80 2 0.0  1.4238799238e+01  2.8820363931e+00  3.2090336900e+01 \n81 2 0.0  1.1420507253e+01  1.8697459157e-02  3.6120652572e+01 \n82 1 0.0  1.4268517750e+01  2.8561106375e+00  3.6168027133e+01 \n83 1 0.0  1.1414591957e+01 -8.2592458544e-02  4.0173253651e+01 \n84 2 0.0  1.4256298422e+01  2.8717039194e+00  4.0140854601e+01 \n85 2 0.0  1.1393721861e+01  5.7236951244e+00  2.0010035088e+01 \n86 1 0.0  1.4257639788e+01  8.4981605285e+00  1.9925047364e+01 \n87 1 0.0  1.1373306754e+01  5.7232945403e+00  2.3983895820e+01 \n88 2 0.0  1.4251016393e+01  8.5961130012e+00  2.4011062539e+01 \n89 2 0.0  1.1392303111e+01  5.6922237034e+00  2.8086502355e+01 \n90 1 0.0  1.4307995467e+01  8.5052796177e+00  2.8127594522e+01 \n91 1 0.0  1.1467787838e+01  5.7303018143e+00  3.2140124452e+01 \n92 2 0.0  1.4223684114e+01  8.5394621152e+00  3.2083417385e+01 \n93 2 0.0  1.1398360231e+01  5.6984501048e+00  3.6109137659e+01 \n94 1 0.0  1.4243599161e+01  8.4926708934e+00  3.6111924268e+01 \n95 1 0.0  1.1387116342e+01  5.7224672938e+00  4.0150551843e+01 \n96 2 0.0  1.4251826367e+01  8.5541300360e+00  4.0169736719e+01 \n97 2 0.0  1.1397087406e+01  1.1432029951e+01  1.9991521329e+01 \n98 1 0.0  1.4222100486e+01  1.4237423386e+01  1.9890837446e+01 \n99 1 0.0  1.1397172085e+01  1.1362254484e+01  2.4106729256e+01 \n100 2 0.0  1.4223050564e+01  1.4272733426e+01  2.4026767277e+01\n101 2 0.0  1.1412415162e+01  1.1398466358e+01  2.8036581274e+01 \n102 1 0.0  1.4265352610e+01  1.4216093689e+01  2.8052093903e+01 \n103 1 0.0  1.1401696599e+01  1.1369599225e+01  3.2083243398e+01 \n104 2 0.0  1.4233083328e+01  1.4215807831e+01  3.2083725032e+01 \n105 3 0.0  1.1446195847e+01  1.1455486685e+01  3.6062830566e+01 \n106 1 0.0  1.4275939497e+01  1.4231407235e+01  3.6076973257e+01 \n107 1 0.0  1.1412436308e+01  1.1399368513e+01  4.0122450030e+01 \n108 2 0.0  1.4206953179e+01  1.4201432515e+01  4.0151366429e+01 \n109 4 0.0  2.7674441650e+00  3.2676547854e+00  1.5266538963e+01 \n110 4 0.0  2.7884963173e+00  3.1844017731e+00  1.0716139442e+01 \n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/hdnnp-data/hardness.008.data",
    "content": "     12.9752105872\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/hdnnp-data/hardness.012.data",
    "content": "     14.5786310784\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/hdnnp-data/hardness.013.data",
    "content": "      1.4392244883\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/hdnnp-data/hardness.079.data",
    "content": "      0.0175182304\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/hdnnp-data/input.nn",
    "content": "## #############################################################\n### This is the input file for RuNNer \n### #############################################################\n### General remarks: \n### - commands can be switched off by using the # character at the BEGINNING of the line\n### - the input file can be structured by blank lines and comment lines\n### - the order of the keywords is arbitrary\n### - if keywords are missing, default values will be used and written to runner.out\n### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message \n\n### THIS INPUT.NN IS AN EXAMPLE, IT IS NOT A REALISTIC CASE\n### It contains only a subset of all keywords\n\n########################################################################################################################\n### general keywords\n########################################################################################################################\n\nnnp_generation 4\nuse_electrostatics\nuse_short_nn\nuse_short_forces                    \nprecondition_weights            \n#regularize_fit_param 1.e-4\nrunner_mode 2\nepochs 100\n#epochs 25\n\nnumber_of_elements 4\nelements Al O Mg Au\n\ninitial_hardness        O        1.0\ninitial_hardness       Mg        1.0\ninitial_hardness       Al        1.0\ninitial_hardness       Au        1.0\n\nfixed_gausswidth Mg 4.289\nfixed_gausswidth  O 2.872\nfixed_gausswidth Al 3.477\nfixed_gausswidth Au 3.288\n\nscreen_electrostatics 3.2 8.0\n\nparallel_mode 1\nrandom_seed 12346\nrandom_number_type 5\n\nremove_atom_energies                     \natom_energy     O    -75.29000258799172\natom_energy    Mg   -200.61689378490792\natom_energy    Au -19684.765036573383\natom_energy    Al   -243.09681374120558\n\nenergy_threshold 100.0d0\nbond_threshold 0.4d0\newald_prec 1.e-6\n#\n\n########################################################################################################################\n### NN structure of the short-range NN  \n########################################################################################################################\nglobal_hidden_layers_short 2              \nglobal_nodes_short 15 15\nglobal_activation_short t t l            \nglobal_hidden_layers_electrostatic 2              \nglobal_nodes_electrostatic 15 15\nglobal_activation_electrostatic t t l            \n\n########################################################################################################################\n### symmetry function generation ( mode 1): \n########################################################################################################################\ntest_fraction 0.1      \n\n########################################################################################################################\n### symmetry function definitions (all modes): \n########################################################################################################################\ncutoff_type 2\n\nsymfunction Mg  2  Mg    0.000000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.001000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.002000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.003000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.004000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.005000      0.000000      8.000000\n\n\nsymfunction O  2 Mg     0.000000      0.000000      8.000000\nsymfunction O  2 Mg     0.004000      0.000000      8.000000\nsymfunction O  2 Mg     0.007000      0.000000      8.000000\nsymfunction O  2 Mg     0.010000      0.000000      8.000000\nsymfunction O  2 Mg     0.014000      0.000000      8.000000\nsymfunction O  2 Mg     0.018000      0.000000      8.000000\n\nsymfunction Mg 2  O    0.000000      0.000000      8.000000\nsymfunction Mg 2  O    0.004000      0.000000      8.000000\nsymfunction Mg 2  O    0.007000      0.000000      8.000000\nsymfunction Mg 2  O    0.010000      0.000000      8.000000\nsymfunction Mg 2  O    0.014000      0.000000      8.000000\nsymfunction Mg 2  O    0.018000      0.000000      8.000000\n\nsymfunction O  2  O    0.000000      0.000000      8.000000\nsymfunction O  2  O    0.001000      0.000000      8.000000\nsymfunction O  2  O    0.002000      0.000000      8.000000\nsymfunction O  2  O    0.003000      0.000000      8.000000\nsymfunction O  2  O    0.004000      0.000000      8.000000\nsymfunction O  2  O    0.005000      0.000000      8.000000\n\nsymfunction Mg  2  Au    0.000000      0.000000      8.000000\nsymfunction Mg  2  Au    0.001000      0.000000      8.000000\nsymfunction Mg  2  Au    0.002000      0.000000      8.000000\nsymfunction Mg  2  Au    0.003000      0.000000      8.000000\nsymfunction Mg  2  Au    0.004000      0.000000      8.000000\nsymfunction Mg  2  Au    0.005000      0.000000      8.000000\n\nsymfunction Au  2  Mg    0.000000      0.000000      8.000000\nsymfunction Au  2  Mg    0.001000      0.000000      8.000000\nsymfunction Au  2  Mg    0.002000      0.000000      8.000000\nsymfunction Au  2  Mg    0.003000      0.000000      8.000000\nsymfunction Au  2  Mg    0.004000      0.000000      8.000000\nsymfunction Au  2  Mg    0.005000      0.000000      8.000000\n\n\nsymfunction Au  2 O     0.000000      0.000000      8.000000\nsymfunction Au  2 O     0.004000      0.000000      8.000000\nsymfunction Au  2 O     0.008000      0.000000      8.000000\nsymfunction Au  2 O     0.013000      0.000000      8.000000\nsymfunction Au  2 O     0.018000      0.000000      8.000000\nsymfunction Au  2 O     0.024000      0.000000      8.000000\n\nsymfunction O  2 Au     0.000000      0.000000      8.000000\nsymfunction O  2 Au     0.004000      0.000000      8.000000\nsymfunction O  2 Au     0.008000      0.000000      8.000000\nsymfunction O  2 Au     0.013000      0.000000      8.000000\nsymfunction O  2 Au     0.018000      0.000000      8.000000\nsymfunction O  2 Au     0.024000      0.000000      8.000000\n\nsymfunction Au  2 Au     0.000000      0.000000      8.000000\nsymfunction Au  2 Au     0.004000      0.000000      8.000000\nsymfunction Au  2 Au     0.008000      0.000000      8.000000\nsymfunction Au  2 Au     0.012000      0.000000      8.000000\nsymfunction Au  2 Au     0.017000      0.000000      8.000000\nsymfunction Au  2 Au     0.022000      0.000000      8.000000\n\n\nsymfunction O  2  Al    0.000000      0.000000      8.000000\nsymfunction O  2  Al    0.003000      0.000000      8.000000\nsymfunction O  2  Al    0.005000      0.000000      8.000000\nsymfunction O  2  Al    0.008000      0.000000      8.000000\nsymfunction O  2  Al    0.011000      0.000000      8.000000\nsymfunction O  2  Al    0.014000      0.000000      8.000000\n\nsymfunction Al  2  O    0.000000      0.000000      8.000000\nsymfunction Al  2  O    0.003000      0.000000      8.000000\nsymfunction Al  2  O    0.005000      0.000000      8.000000\nsymfunction Al  2  O    0.008000      0.000000      8.000000\nsymfunction Al  2  O    0.011000      0.000000      8.000000\nsymfunction Al  2  O    0.014000      0.000000      8.000000\n\nsymfunction Al  2  Mg    0.000000      0.000000      8.000000\nsymfunction Al  2  Mg    0.001000      0.000000      8.000000\nsymfunction Al  2  Mg    0.002000      0.000000      8.000000\nsymfunction Al  2  Mg    0.003000      0.000000      8.000000\nsymfunction Al  2  Mg    0.004000      0.000000      8.000000\nsymfunction Al  2  Mg    0.005000      0.000000      8.000000\n\nsymfunction Mg  2  Al    0.000000      0.000000      8.000000\nsymfunction Mg  2  Al    0.001000      0.000000      8.000000\nsymfunction Mg  2  Al    0.002000      0.000000      8.000000\nsymfunction Mg  2  Al    0.003000      0.000000      8.000000\nsymfunction Mg  2  Al    0.004000      0.000000      8.000000\nsymfunction Mg  2  Al    0.005000      0.000000      8.000000\n\n#symfunction Al  2  Al    0.000000      0.000000      8.000000\n#symfunction Al  2  Al    0.001000      0.000000      8.000000\n#symfunction Al  2  Al    0.002000      0.000000      8.000000\n#symfunction Al  2  Al    0.003000      0.000000      8.000000\n#symfunction Al  2  Al    0.004000      0.000000      8.000000\n#symfunction Al  2  Al    0.005000      0.000000      8.000000\n\n\nsymfunction Mg 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction Mg 3 Mg Mg 0.0  1.0 2.0  8.0\nsymfunction Mg 3 Mg Mg 0.0  1.0 4.0  8.0\n#symfunction Mg 3 Mg Mg 0.0  1.0 8.0  8.0\nsymfunction Mg 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 4.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 8.0  8.0\nsymfunction Mg 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction Mg 3 Mg  O 0.0 -1.0 2.0  8.0\n#symfunction Mg 3 Mg  O 0.0 -1.0 4.0  8.0\n#symfunction Mg 3 Mg  O 0.0 -1.0 8.0  8.0\n\n#symfunction Mg 3 Mg Al 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Mg Al 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Mg Al 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Al 0.0 -1.0 2.0  8.0\n\n#symfunction Mg 3 Mg Au 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Mg Au 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Mg Au 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3  O  O 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O  O 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O  O 0.0  1.0 4.0  8.0\n#symfunction Mg 3  O  O 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 1.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 2.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 4.0  8.0\n#symfunction Mg 3  O  O 0.0 -1.0 8.0  8.0\n\nsymfunction Mg 3  O Al 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 4.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O Al 0.0 -1.0 1.0  8.0\n#symfunction Mg 3  O Al 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3  O Au 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 4.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O Au 0.0 -1.0 1.0  8.0\nsymfunction Mg 3  O Au 0.0 -1.0 2.0  8.0\n\n#symfunction Mg 3 Al Al 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Al Al 0.0  1.0 2.0  8.0\n\n#symfunction Mg 3 Au Au 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Au Au 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Au Au 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Au Au 0.0 -1.0 2.0  8.0\n\n\n\nsymfunction  O 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Mg 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Mg 0.0  1.0 4.0  8.0\n#symfunction  O 3 Mg Mg 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 2.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg Mg 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 4.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg  O 0.0 -1.0 2.0  8.0\n#symfunction  O 3 Mg  O 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg  O 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg Al 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Al 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Al 0.0  1.0 4.0  8.0\n#symfunction  O 3 Mg Al 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 2.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg Al 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg Au 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Au 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Au 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction  O 3  O  O 0.0  1.0 1.0  8.0\nsymfunction  O 3  O  O 0.0  1.0 2.0  8.0\nsymfunction  O 3  O  O 0.0 -1.0 1.0  8.0\n\nsymfunction  O 3  O Al 0.0  1.0 1.0  8.0\nsymfunction  O 3  O Al 0.0  1.0 2.0  8.0\nsymfunction  O 3  O Al 0.0 -1.0 1.0  8.0\nsymfunction  O 3  O Al 0.0 -1.0 2.0  8.0\n\n#symfunction  O 3  O Au 0.0  1.0 1.0  8.0\n\n\n\n\nsymfunction Al 3 Mg Mg 0.0  1.0 1.0  8.0\n#symfunction Al 3 Mg Mg 0.0  1.0 2.0  8.0\n#symfunction Al 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Al 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Al 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Al 3 Mg  O 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg  O 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3 Mg Al 0.0  1.0 1.0  8.0\n#symfunction Al 3 Mg Al 0.0  1.0 2.0  8.0\n#symfunction Al 3 Mg Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg Al 0.0 -1.0 2.0  8.0\n\nsymfunction Al 3  O  O 0.0  1.0 1.0  8.0\nsymfunction Al 3  O  O 0.0  1.0 2.0  8.0\nsymfunction Al 3  O  O 0.0 -1.0 1.0  8.0\nsymfunction Al 3  O  O 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3  O Al 0.0  1.0 1.0  8.0\n#symfunction Al 3  O Al 0.0  1.0 2.0  8.0\n#symfunction Al 3  O Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3  O Al 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3 Al Al 0.0  1.0 1.0  8.0\n#symfunction Al 3 Al Al 0.0  1.0 2.0  8.0\n#symfunction Al 3 Al Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Al Al 0.0 -1.0 2.0  8.0\n\n\n\nsymfunction Au 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction Au 3 Mg Mg 0.0  1.0 2.0  8.0\n#symfunction Au 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Au 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Au 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Au 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction Au 3 Mg  O 0.0 -1.0 2.0  8.0\n\n#symfunction Au 3 Mg Au 0.0  1.0 1.0  8.0\n#symfunction Au 3 Mg Au 0.0  1.0 2.0  8.0\n#symfunction Au 3 Mg Au 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction Au 3  O  O 0.0  1.0 1.0  8.0\n#symfunction Au 3  O  O 0.0  1.0 2.0  8.0\n#symfunction Au 3  O  O 0.0 -1.0 1.0  8.0\n#symfunction Au 3  O  O 0.0 -1.0 2.0  8.0\n\n#symfunction Au 3  O Au 0.0  1.0 1.0  8.0\n#symfunction Au 3  O Au 0.0  1.0 2.0  8.0\nsymfunction Au 3  O Au 0.0  1.0 -1.0  8.0\nsymfunction Au 3  O Au 0.0  1.0 -2.0  8.0\n\n#symfunction Au 3 Au Au 0.0  1.0 1.0  8.0\n#symfunction Au 3 Au Au 0.0  1.0 2.0  8.0\n#symfunction Au 3 Au Au 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Au Au 0.0 -1.0 2.0  8.0\n\n\n\n\n########################################################################################################################\n### fitting (mode 2):general inputs for short range AND short part:\n########################################################################################################################\npoints_in_memory 1000\nmix_all_points                       \nscale_symmetry_functions             \ncenter_symmetry_functions             \nfitting_unit  eV                      \n########################################################################################################################\n### fitting options ( mode 2): short range part only:\n########################################################################################################################\noptmode_short_energy 1                 \noptmode_short_force 1                   \nshort_energy_error_threshold 0.8\t \nshort_force_error_threshold 0.8\t\t \nkalman_lambda_short 0.98000                \nkalman_lambda_charge 0.98000                \nkalman_nue_short 0.99870                   \nkalman_nue_charge 0.99870                   \n#use_old_weights_short               \n#force_update_scaling -1.0d0          \n#short_energy_group 1         \n#short_energy_fraction 1.00           \n#short_force_group 1                  \nshort_force_fraction 0.025\nweights_min -1.0                 \nweights_max 1.0                  \nrepeated_energy_update\nnguyen_widrow_weights_short\n\n\n########################################################################################################################\n### output options for mode 2 (fitting):  \n########################################################################################################################\n#write_trainpoints              \n#write_trainforces      \n########################################################################################################################\n### output options for mode 3 (prediction):  \n########################################################################################################################\ncalculate_forces     \n#calculate_stress       \n\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/hdnnp-data/scaling.data",
    "content": "   1    1        0.157132975       0.280279850       0.234169887\n   1    2        0.379295480       0.622179554       0.545652438\n   1    3        0.000000000       0.205184943       0.016565410\n   1    4        0.000000000       0.167300348       0.001157152\n   1    5        0.151966913       0.271484679       0.226693585\n   1    6        0.146970813       0.262965553       0.219456059\n   1    7        0.142139079       0.254713806       0.212449681\n   1    8        0.000000000       0.195870161       0.015737764\n   1    9        0.137466301       0.246721045       0.205667064\n   1   10        0.353782761       0.582354440       0.509841176\n   1   11        0.000000000       0.161223776       0.001045601\n   1   12        0.132947244       0.238979140       0.199101062\n   1   13        0.000000000       0.189896965       0.015211084\n   1   14        0.335850555       0.554313578       0.484647540\n   1   15        0.000000000       0.181277733       0.014456530\n   1   16        0.000000000       0.155367918       0.000947149\n   1   17        0.318878593       0.527730187       0.460782520\n   1   18        0.000000000       0.173050590       0.013742142\n   1   19        0.000000000       0.148346286       0.000839806\n   1   20        0.297643309       0.494532513       0.430890275\n   1   21        0.000000000       0.165197661       0.013065428\n   1   22        0.277886581       0.463747515       0.403042058\n   1   23        0.000000000       0.141641990       0.000747240\n   1   24        0.000000000       0.133995570       0.000652336\n   1   25        0.000045839       0.000152977       0.000106156\n   1   26        0.000680557       0.001734569       0.001348253\n   1   27        0.000000000       0.000580779       0.000043631\n   1   28        0.000687759       0.003088959       0.002094644\n   1   29        0.000000000       0.001975434       0.000139623\n   1   30        0.000000000       0.002858460       0.000006888\n   1   31        0.000141138       0.000459099       0.000318440\n   1   32        0.003883787       0.009565828       0.007507740\n   1   33        0.000000000       0.003170549       0.000242247\n   1   34        0.000723568       0.003193167       0.002190205\n   1   35        0.000000000       0.002015297       0.000146458\n   1   36        0.000000000       0.002849448       0.000008773\n   1   37        0.000108434       0.000298716       0.000226841\n   1   38        0.000000000       0.000100115       0.000007401\n   1   39        0.000337708       0.001533218       0.001037438\n   1   40        0.000000000       0.000985795       0.000069101\n   1   41        0.000000000       0.001452136       0.000003254\n   1   42        0.000106418       0.000344381       0.000238835\n   1   43        0.003311665       0.008129974       0.006386328\n   1   44        0.000000000       0.002695024       0.000206016\n   1   45        0.000376278       0.001638804       0.001133000\n   1   46        0.000000000       0.001025445       0.000075936\n   1   47        0.000000000       0.001443125       0.000005139\n   1   48        0.000083248       0.000381693       0.000258183\n   1   49        0.000000000       0.000247525       0.000017187\n   1   50        0.002416132       0.005909800       0.004645819\n   1   51        0.000108377       0.000463908       0.000321719\n   1   52        0.000000000       0.000274278       0.000021729\n   1   53        0.001290479       0.003153152       0.002478974\n   2    1        0.465366967       0.622899345       0.561220975\n   2    2        0.119958755       0.278325877       0.225814452\n   2    3        0.000000000       0.052290984       0.007517999\n   2    4        0.000000000       0.082321041       0.001283464\n   2    5        0.116028951       0.269574643       0.218604882\n   2    6        0.000000000       0.050704245       0.007277988\n   2    7        0.000000000       0.080774026       0.001244257\n   2    8        0.112227916       0.261098625       0.211625571\n   2    9        0.000000000       0.049165662       0.007045642\n   2   10        0.000000000       0.079257371       0.001206277\n   2   11        0.108551431       0.252889168       0.204869161\n   2   12        0.000000000       0.047673774       0.006820716\n   2   13        0.000000000       0.077770417       0.001169485\n   2   14        0.434143302       0.583124772       0.524387947\n   2   15        0.104995412       0.244937885       0.198328532\n   2   16        0.000000000       0.046227162       0.006602973\n   2   17        0.000000000       0.076312525       0.001133843\n   2   18        0.101555912       0.237236656       0.191996789\n   2   19        0.000000000       0.044824453       0.006392183\n   2   20        0.000000000       0.074883070       0.001099315\n   2   21        0.412169183       0.555114045       0.498475487\n   2   22        0.391351992       0.528554985       0.473929551\n   2   23        0.365280511       0.495248302       0.443184422\n   2   24        0.341001583       0.464173404       0.414541640\n   2   25        0.001304697       0.003073521       0.002226260\n   2   26        0.000658301       0.001747757       0.001341772\n   2   27        0.000000000       0.000344142       0.000044915\n   2   28        0.000000000       0.000536511       0.000003397\n   2   29        0.000015937       0.000150219       0.000098274\n   2   30        0.001379442       0.003196463       0.002328076\n   2   31        0.003777691       0.009615500       0.007472434\n   2   32        0.000000000       0.001853922       0.000249329\n   2   33        0.000000000       0.001669339       0.000012712\n   2   34        0.000048632       0.000451042       0.000294796\n   2   35        0.000640789       0.001524318       0.001102595\n   2   36        0.000104063       0.000302504       0.000225688\n   2   37        0.000000000       0.000263424       0.000001016\n   2   38        0.000709709       0.001647260       0.001204412\n   2   39        0.003223454       0.008170246       0.006356350\n   2   40        0.000000000       0.001575067       0.000212033\n   2   41        0.000000000       0.001450386       0.000010331\n   2   42        0.000036630       0.000338360       0.000221102\n   2   43        0.000156394       0.000379666       0.000274392\n   2   44        0.000197865       0.000461980       0.000342083\n   2   45        0.002354467       0.005937258       0.004624037\n   2   46        0.000000000       0.001144834       0.000154222\n   2   47        0.000000000       0.001123811       0.000007188\n   2   48        0.000020441       0.000190427       0.000124392\n   2   49        0.001262549       0.003166018       0.002467335\n   2   50        0.000000000       0.000611201       0.000082309\n   2   51        0.000000000       0.000698347       0.000003778\n   3    1        0.577136243       0.616694005       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  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/hdnnp-data/weights.008.data",
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  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/hdnnp-data/weightse.012.data",
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  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/hdnnp-data/weightse.013.data",
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  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/hdnnp-data/weightse.079.data",
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-0.2023173027\n     -0.0346307314\n      0.1454586515\n      0.0499358161\n     -0.3025620612\n     -0.0615975991\n     -0.1344299547\n     -0.2200005758\n      0.0613286471\n     -0.0095641876\n      0.1077087090\n      0.0238586352\n      0.0900418907\n      0.1739544847\n     -0.0403015175\n      0.0633257879\n      0.0598231882\n     -0.0043880669\n      0.4304185740\n     -0.2331181875\n      0.1449090428\n     -0.2454187095\n     -0.1682876393\n      0.1509626947\n     -0.3338329016\n      0.1650067521\n      0.1653432182\n     -0.3073306576\n      0.3124937274\n     -0.1521119233\n      0.0447478080\n     -0.1095822516\n     -0.0238035401\n     -0.0025984171\n     -0.1025755475\n     -0.0615939344\n     -0.1482717020\n     -0.0578191435\n      0.0915471638\n     -0.0423972689\n      0.0441757511\n      0.1113012611\n     -0.1172166503\n      0.2325309272\n     -0.0895939091\n      0.1005929196\n     -0.1384167043\n      0.2122254593\n      0.0714664070\n     -0.2705822901\n      0.0118268280\n     -0.2193245726\n      0.2431070294\n      0.1141446596\n     -0.1867606865\n      0.1935099930\n      0.2209813140\n     -0.2529433949\n      0.1440143975\n     -0.0722829562\n     -0.0598002212\n      0.0208649888\n      0.0577711911\n      0.0328625300\n     -0.4509728043\n     -0.1559953040\n     -0.1223170768\n     -0.2639953341\n      0.0548075896\n      0.0576850840\n      0.0786432581\n     -0.0760044592\n      0.2492190636\n      0.0083271687\n      0.0283693425\n      0.0978297844\n     -0.1222856258\n     -0.0651284791\n     -0.0178319910\n     -0.0658492086\n     -0.0677102135\n     -0.1473605241\n     -0.0197504678\n      0.0986096003\n     -0.0466665163\n      0.0264603481\n      0.1290190457\n     -0.1591221726\n      0.2329792336\n     -0.0948194226\n      0.1127973166\n     -0.2122030043\n     -0.0036133367\n      0.2592597572\n     -0.2275641658\n     -0.0352099798\n     -0.0510248230\n      0.2101184628\n      0.0068438583\n     -0.1914768435\n      0.1580744693\n      0.3367138970\n     -0.2758308964\n      0.1194249955\n     -0.1189355850\n     -0.0268126611\n      0.9203075660\n      0.7456691833\n      0.2222706793\n     -0.1988471649\n      0.3739655052\n     -0.3294855879\n      0.5728060471\n      0.0393707195\n      0.6439223591\n      0.5441672350\n     -0.0135455178\n      0.6243344121\n     -0.1346168015\n      0.4979660549\n     -0.7870518947\n     -0.5332850238\n     -0.3587958597\n     -0.1479196713\n     -0.6215149074\n     -0.7771744116\n     -0.5163484113\n     -0.1940326928\n      0.3175103040\n      0.4954133086\n     -0.2761520547\n      0.3831963000\n      0.4605532208\n      0.3860955709\n      0.0378062514\n     -0.1707804695\n     -0.0435508038\n     -0.0810929828\n     -0.4526255338\n      0.2463436433\n     -0.3273868010\n      0.3637041064\n      0.0724031602\n     -0.1624640494\n      0.1892663892\n     -0.1521606342\n      0.2815898854\n      0.1367806931\n     -0.2829098452\n     -0.0888158292\n     -0.4768318121\n     -0.0812336748\n      0.0034283591\n      1.0013113650\n      0.4150497899\n     -0.1063706595\n      0.2857364395\n      0.0628422180\n     -0.5849189818\n      0.3915753066\n     -0.3741713347\n     -0.1918341851\n     -0.1663933130\n      0.2835631780\n     -0.2939765787\n     -0.2276334491\n      0.1039590962\n     -0.3242652545\n      0.0186193017\n     -0.1433616691\n     -0.1613015297\n      0.0605507977\n     -0.3616662631\n      0.0177685095\n     -0.7604765543\n      0.0476406693\n      0.3468828079\n      0.2581321661\n     -0.1937871932\n      0.2621700413\n      0.4630765087\n      0.8510017645\n      0.3689454032\n     -0.4602175172\n     -0.0066761804\n      0.7722044785\n     -0.0305925950\n     -0.7111077469\n     -0.2776830879\n     -0.5123830560\n      1.0439249658\n      0.2048119234\n     -0.2821199655\n      0.2264540283\n     -0.3373758126\n     -0.3064677507\n      0.7312395462\n     -0.0528935699\n      0.6398342791\n      0.3253160435\n     -0.3344819542\n     -0.2014156839\n     -0.7466067836\n      0.0710261411\n     -1.2018333087\n      0.6152880326\n      0.3473916962\n      0.5407951540\n      0.0516084216\n      0.1278888061\n      0.6017158483\n     -0.1417335912\n      0.2143850072\n     -0.1118223674\n     -0.4201007154\n     -0.4666319341\n      0.5337375625\n      0.3218953867\n      0.0944373628\n     -0.9002175948\n      0.2591672154\n     -0.3000104463\n      0.4861039688\n      0.0952490403\n     -0.3920374309\n      0.0247337474\n     -0.5106625667\n     -0.1015746734\n      0.4126996028\n      0.1906749269\n      0.7667360527\n     -0.2519091950\n     -0.2538368872\n     -0.3091588395\n      0.1743960227\n     -0.0738386990\n      0.0954615004\n     -0.6309371822\n      0.2845880292\n     -0.0026901912\n     -0.1206545296\n      0.0758079075\n      0.0010136892\n      0.1490356550\n      0.0021429510\n      0.1603305471\n     -0.2690907146\n      0.0072183932\n      0.2317995676\n      0.3841513421\n     -0.1435027077\n      0.1843797288\n      0.8279229355\n      0.1612532146\n      0.1261892740\n      0.0960014594\n     -0.2441902221\n     -0.0871481995\n      0.5670319559\n      0.1439771996\n      0.0873918284\n      0.5928485078\n      0.5222145033\n     -0.2947982040\n      0.1572202719\n      0.1069671383\n     -0.7922665695\n     -0.1772334153\n     -0.3776175949\n      0.2032090117\n     -0.1847832635\n     -0.1930693654\n     -0.2188837767\n      0.3509390016\n     -0.2170035072\n     -0.4627849794\n      0.4561667716\n     -0.3401245781\n     -0.0231144919\n      0.1302318702\n     -0.4121202672\n     -0.5001609206\n      0.0843134021\n     -0.0926861702\n      0.3255728108\n     -0.1711697918\n     -0.8780680929\n     -0.3413916248\n      0.3916863656\n     -0.6500525270\n     -0.4044179063\n      0.2977145371\n     -0.3145119048\n      0.5759574510\n      0.8617288100\n     -0.4371884938\n      0.3023348726\n     -0.3238457119\n      0.2568039620\n      0.0640803265\n      0.6770661325\n     -0.2782708301\n     -0.2097110502\n     -0.1415992491\n     -0.0746808521\n      0.4398888003\n     -0.4949939471\n     -0.2431396059\n     -0.4795168393\n     -0.0108472702\n      0.5038791106\n      0.5240696579\n     -0.9252031009\n      0.3309561660\n      0.1440836156\n     -0.3944453019\n      0.2948833127\n      0.0129818495\n      0.4223860733\n      0.0957712177\n      0.5006578292\n     -0.2747709559\n     -0.5699756136\n     -0.7476578080\n      0.3753346881\n      0.4670965348\n      0.3435678002\n      0.0800265005\n     -0.0211998040\n      0.0347383614\n      0.2070381583\n      0.0176409642\n     -0.0088772683\n     -0.6111740774\n     -0.0290809661\n     -0.3306605622\n      0.4799933221\n      0.1060321019\n     -0.1373112089\n     -0.5419840819\n     -0.3688590619\n     -0.1731587211\n     -0.6552664178\n      0.1983996951\n     -0.1075821292\n     -0.0350305109\n     -0.0159929994\n     -0.1398821349\n      0.0720797163\n      0.0554322662\n      0.2405258084\n     -0.2998280663\n      0.2220944588\n     -0.2774169468\n      0.4108718462\n      0.0168266678\n      0.1893295294\n      0.2570022134\n     -0.4562349824\n      0.0733776332\n     -0.5885666954\n     -0.0412252054\n      0.0377403884\n     -1.0664772437\n     -0.1060277409\n     -0.2698892553\n      0.2826469476\n     -0.2529006758\n     -0.6399482527\n      1.3647214921\n     -0.2285785734\n      0.1962570917\n      0.2684972608\n     -0.1470008551\n     -0.0341685014\n      0.2593568604\n      0.2522317733\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/input.data",
    "content": "MgO with Al/Au, first structure from input.data (wrapped into box)\n\n110 atoms\n\n4 atom types\n\n0.0 1.7097166001000002E+01 xlo xhi\n0.0 1.7097166001000002E+01 ylo yhi\n0.0 5.0000000000999997E+01 zlo zhi\n\nAtoms\n\n1   2 0.0 -1.9775793498e-02 -6.4032231288e-02  2.0026111119e+01\n2   1 0.0  2.8784590473e+00  2.8904829958e+00  2.0053576907e+01\n3   1 0.0  7.2652159693e-02 -1.6211222263e-02  2.4043132172e+01\n4   2 0.0  2.8780260733e+00  2.8998185635e+00  2.4032640394e+01\n5   2 0.0 -5.6795412231e-02 -2.2440590601e-02  2.8111288946e+01\n6   1 0.0  2.8421666140e+00  2.8834652149e+00  2.8032859289e+01\n7   1 0.0  6.5214500558e-02 -3.8745751143e-02  3.2113867333e+01\n8   2 0.0  2.8332198764e+00  2.7977822229e+00  3.2113907679e+01\n9   3 0.0  1.9864553928e-02  1.0486013922e-02  3.6088078099e+01\n10  1 0.0  2.7981764575e+00  2.8796998036e+00  3.6124511960e+01\n11  1 0.0 -8.4521774292e-03 -2.2604637714e-02  4.0153894391e+01\n12  2 0.0  2.8234702698e+00  2.8619477366e+00  4.0124676317e+01\n13  2 0.0 -1.3119630546e-02  5.6888413584e+00  2.0013899747e+01\n14  1 0.0  2.8848335277e+00  8.5308909417e+00  1.9989943256e+01\n15  1 0.0  1.8241298201e-02  5.6837552365e+00  2.4026099826e+01\n16  2 0.0  2.9361062157e+00  8.4795591997e+00  2.4082757439e+01\n17  2 0.0  1.6188356579e-02  5.6698041265e+00  2.8051270020e+01\n18  1 0.0  2.8977599905e+00  8.5660735578e+00  2.8036115495e+01\n19  1 0.0  9.8433937020e-04  5.6927154290e+00  3.2118501962e+01\n20  2 0.0  2.8073628502e+00  8.5498039808e+00  3.2128399704e+01\n21  2 0.0 -5.0996334501e-02  5.7492786883e+00  3.6121753734e+01\n22  1 0.0  2.9059518581e+00  8.5723518134e+00  3.6118083754e+01\n23  1 0.0  5.2199900983e-04  5.6455106974e+00  4.0180597258e+01\n24  2 0.0  2.8610732470e+00  8.5614353199e+00  4.0139419524e+01\n25  2 0.0 -3.9339238487e-02  1.1415957378e+01  1.9959977720e+01\n26  1 0.0  2.9183726113e+00  1.4291678042e+01  1.9988445497e+01\n27  1 0.0 -2.1271587207e-02  1.1421205582e+01  2.4027048544e+01\n28  2 0.0  2.9026486927e+00  1.4185336528e+01  2.4050086987e+01\n29  2 0.0 -5.1509735258e-02  1.1382810885e+01  2.8094293015e+01\n30  1 0.0  2.9119668371e+00  1.4181088046e+01  2.8044752601e+01\n31  1 0.0  1.0413278368e-02  1.1323763827e+01  3.2100372838e+01\n32  2 0.0  2.7888050607e+00  1.4200832470e+01  3.2081624640e+01\n33  2 0.0 -5.2366574815e-03  1.1380297134e+01  3.6148026784e+01\n34  1 0.0  2.8964801357e+00  1.4225437477e+01  3.6102833042e+01\n35  1 0.0 -4.8130810704e-02  1.1455866520e+01  4.0155035313e+01\n36  2 0.0  2.8743271236e+00  1.4294384262e+01  4.0132651036e+01\n37  2 0.0  5.7360837333e+00 -1.4033161883e-02  2.0040227467e+01\n38  1 0.0  8.5193853072e+00  2.8764031199e+00  1.9994398985e+01\n39  1 0.0  5.6375475999e+00 -4.0667772549e-02  2.4029267612e+01\n40  2 0.0  8.5444746323e+00  2.8328648158e+00  2.4073209126e+01\n41  2 0.0  5.6374929679e+00  8.9788629595e-03  2.8040190972e+01\n42  1 0.0  8.5205746819e+00  2.8135749087e+00  2.8097702553e+01\n43  1 0.0  5.7090540565e+00  1.6821528168e-02  3.2068389906e+01\n44  2 0.0  8.5099907612e+00  2.8387661466e+00  3.2089405586e+01\n45  2 0.0  5.7491607505e+00  2.6551802873e-02  3.6161801185e+01\n46  1 0.0  8.5696933090e+00  2.8243981820e+00  3.6095548904e+01\n47  1 0.0  5.6004605747e+00 -3.9012674939e-02  4.0102869653e+01\n48  2 0.0  8.5839177868e+00  2.8525893410e+00  4.0129186941e+01\n49  2 0.0  5.6735244868e+00  5.6849201959e+00  1.9979804725e+01\n50  1 0.0  8.5832999976e+00  8.5656793232e+00  1.9987182839e+01\n51  1 0.0  5.7075209596e+00  5.6897493150e+00  2.4036549652e+01\n52  2 0.0  8.6020291474e+00  8.5486919149e+00  2.3965788409e+01\n53  2 0.0  5.7493104546e+00  5.6905967816e+00  2.8035716479e+01\n54  1 0.0  8.5305642648e+00  8.5336383576e+00  2.8041326565e+01\n55  1 0.0  5.6467260935e+00  5.6755829275e+00  3.2090861072e+01\n56  2 0.0  8.5337005863e+00  8.5466174493e+00  3.2081751157e+01\n57  3 0.0  5.6610188849e+00  5.6993559450e+00  3.6064080941e+01\n58  1 0.0  8.5010303798e+00  8.5362875267e+00  3.6131963187e+01\n59  1 0.0  5.6984002350e+00  5.7462274801e+00  4.0178786901e+01\n60  2 0.0  8.5592887234e+00  8.5947597306e+00  4.0146193152e+01\n61  2 0.0  5.6032739042e+00  1.1399683984e+01  1.9913916443e+01\n62  1 0.0  8.5029228270e+00  1.4343324046e+01  2.0023014406e+01\n63  1 0.0  5.6720512753e+00  1.1358988262e+01  2.4060251956e+01\n64  2 0.0  8.5254411798e+00  1.4231011829e+01  2.4012346344e+01\n65  2 0.0  5.7426630600e+00  1.1378874680e+01  2.8023933603e+01\n66  1 0.0  8.6362523685e+00  1.4255022857e+01  2.8036097202e+01\n67  1 0.0  5.7117658322e+00  1.1454697101e+01  3.2073160784e+01\n68  2 0.0  8.5246584175e+00  1.4270581047e+01  3.2102696917e+01\n69  2 0.0  5.7186666391e+00  1.1422359335e+01  3.6101213660e+01\n70  1 0.0  8.5627598477e+00  1.4273198941e+01  3.6166519038e+01\n71  1 0.0  5.7264381750e+00  1.1398781375e+01  4.0260042284e+01\n72  2 0.0  8.5102664156e+00  1.4232221424e+01  4.0091178051e+01\n73  2 0.0  1.1401532344e+01  4.5076087540e-02  2.0029059110e+01\n74  1 0.0  1.4239757122e+01  2.8608573080e+00  1.9951038844e+01\n75  1 0.0  1.1393443466e+01 -4.2770168300e-04  2.4001081706e+01\n76  2 0.0  1.4231685554e+01  2.8864018680e+00  2.4021645383e+01\n77  2 0.0  1.1402686003e+01  3.9371628390e-02  2.8113584925e+01\n78  1 0.0  1.4244927525e+01  2.8375641675e+00  2.8036863637e+01\n79  1 0.0  1.1395989211e+01  4.7920427509e-03  3.2086785538e+01\n80  2 0.0  1.4238799238e+01  2.8820363931e+00  3.2090336900e+01\n81  2 0.0  1.1420507253e+01  1.8697459157e-02  3.6120652572e+01\n82  1 0.0  1.4268517750e+01  2.8561106375e+00  3.6168027133e+01\n83  1 0.0  1.1414591957e+01 -8.2592458544e-02  4.0173253651e+01\n84  2 0.0  1.4256298422e+01  2.8717039194e+00  4.0140854601e+01\n85  2 0.0  1.1393721861e+01  5.7236951244e+00  2.0010035088e+01\n86  1 0.0  1.4257639788e+01  8.4981605285e+00  1.9925047364e+01\n87  1 0.0  1.1373306754e+01  5.7232945403e+00  2.3983895820e+01\n88  2 0.0  1.4251016393e+01  8.5961130012e+00  2.4011062539e+01\n89  2 0.0  1.1392303111e+01  5.6922237034e+00  2.8086502355e+01\n90  1 0.0  1.4307995467e+01  8.5052796177e+00  2.8127594522e+01\n91  1 0.0  1.1467787838e+01  5.7303018143e+00  3.2140124452e+01\n92  2 0.0  1.4223684114e+01  8.5394621152e+00  3.2083417385e+01\n93  2 0.0  1.1398360231e+01  5.6984501048e+00  3.6109137659e+01\n94  1 0.0  1.4243599161e+01  8.4926708934e+00  3.6111924268e+01\n95  1 0.0  1.1387116342e+01  5.7224672938e+00  4.0150551843e+01\n96  2 0.0  1.4251826367e+01  8.5541300360e+00  4.0169736719e+01\n97  2 0.0  1.1397087406e+01  1.1432029951e+01  1.9991521329e+01\n98  1 0.0  1.4222100486e+01  1.4237423386e+01  1.9890837446e+01\n99  1 0.0  1.1397172085e+01  1.1362254484e+01  2.4106729256e+01\n100 2 0.0  1.4223050564e+01  1.4272733426e+01  2.4026767277e+01\n101 2 0.0  1.1412415162e+01  1.1398466358e+01  2.8036581274e+01\n102 1 0.0  1.4265352610e+01  1.4216093689e+01  2.8052093903e+01\n103 1 0.0  1.1401696599e+01  1.1369599225e+01  3.2083243398e+01\n104 2 0.0  1.4233083328e+01  1.4215807831e+01  3.2083725032e+01\n105 3 0.0  1.1446195847e+01  1.1455486685e+01  3.6062830566e+01\n106 1 0.0  1.4275939497e+01  1.4231407235e+01  3.6076973257e+01\n107 1 0.0  1.1412436308e+01  1.1399368513e+01  4.0122450030e+01\n108 2 0.0  1.4206953179e+01  1.4201432515e+01  4.0151366429e+01\n109 4 0.0  2.7674441650e+00  3.2676547854e+00  1.5266538963e+01\n110 4 0.0  2.7884963173e+00  3.1844017731e+00  1.0716139442e+01\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/input.data.q",
    "content": "MgO with Al/Au, first structure from input.data (wrapped into box)\n\n110 atoms\n\n4 atom types\n\n0.0 1.7097166001000002E+01 xlo xhi\n0.0 1.7097166001000002E+01 ylo yhi\n0.0 5.0000000000999997E+01 zlo zhi\n\nAtoms\n\n1   2  3.8291924061925653E-01 -1.9775793498e-02 -6.4032231288e-02  2.0026111119e+01\n2   1 -3.4428156299665341E-01  2.8784590473e+00  2.8904829958e+00  2.0053576907e+01\n3   1 -3.5086580292126851E-01  7.2652159693e-02 -1.6211222263e-02  2.4043132172e+01\n4   2  3.2433687005490347E-01  2.8780260733e+00  2.8998185635e+00  2.4032640394e+01\n5   2  3.3204727049820898E-01 -5.6795412231e-02 -2.2440590601e-02  2.8111288946e+01\n6   1 -3.4688163791959031E-01  2.8421666140e+00  2.8834652149e+00  2.8032859289e+01\n7   1 -3.0572472683900559E-01  6.5214500558e-02 -3.8745751143e-02  3.2113867333e+01\n8   2  3.2528985564654112E-01  2.8332198764e+00  2.7977822229e+00  3.2113907679e+01\n9   3  4.0611938023445521E-01  1.9864553928e-02  1.0486013922e-02  3.6088078099e+01\n10  1 -2.8630283769104226E-01  2.7981764575e+00  2.8796998036e+00  3.6124511960e+01\n11  1 -3.5957655071713124E-01 -8.4521774292e-03 -2.2604637714e-02  4.0153894391e+01\n12  2  3.7753609731287419E-01  2.8234702698e+00  2.8619477366e+00  4.0124676317e+01\n13  2  3.5591802844379500E-01 -1.3119630546e-02  5.6888413584e+00  2.0013899747e+01\n14  1 -4.0169249064342727E-01  2.8848335277e+00  8.5308909417e+00  1.9989943256e+01\n15  1 -3.4691547806469936E-01  1.8241298201e-02  5.6837552365e+00  2.4026099826e+01\n16  2  3.2914052387976833E-01  2.9361062157e+00  8.4795591997e+00  2.4082757439e+01\n17  2  3.2730311340688478E-01  1.6188356579e-02  5.6698041265e+00  2.8051270020e+01\n18  1 -3.5093513486162087E-01  2.8977599905e+00  8.5660735578e+00  2.8036115495e+01\n19  1 -3.4459782389606863E-01  9.8433937020e-04  5.6927154290e+00  3.2118501962e+01\n20  2  3.3395169100324523E-01  2.8073628502e+00  8.5498039808e+00  3.2128399704e+01\n21  2  3.2474904180868053E-01 -5.0996334501e-02  5.7492786883e+00  3.6121753734e+01\n22  1 -3.0989233562802238E-01  2.9059518581e+00  8.5723518134e+00  3.6118083754e+01\n23  1 -3.9852445333057718E-01  5.2199900983e-04  5.6455106974e+00  4.0180597258e+01\n24  2  3.9163043876072223E-01  2.8610732470e+00  8.5614353199e+00  4.0139419524e+01\n25  2  4.1777879320476413E-01 -3.9339238487e-02  1.1415957378e+01  1.9959977720e+01\n26  1 -4.0097762724649699E-01  2.9183726113e+00  1.4291678042e+01  1.9988445497e+01\n27  1 -3.4828423145469906E-01 -2.1271587207e-02  1.1421205582e+01  2.4027048544e+01\n28  2  3.2454737976948755E-01  2.9026486927e+00  1.4185336528e+01  2.4050086987e+01\n29  2  3.2875417706283000E-01 -5.1509735258e-02  1.1382810885e+01  2.8094293015e+01\n30  1 -3.4883507746559250E-01  2.9119668371e+00  1.4181088046e+01  2.8044752601e+01\n31  1 -3.4040606525743328E-01  1.0413278368e-02  1.1323763827e+01  3.2100372838e+01\n32  2  3.3235814987891393E-01  2.7888050607e+00  1.4200832470e+01  3.2081624640e+01\n33  2  3.2842388397732730E-01 -5.2366574815e-03  1.1380297134e+01  3.6148026784e+01\n34  1 -3.1247489207792084E-01  2.8964801357e+00  1.4225437477e+01  3.6102833042e+01\n35  1 -3.9718514714947045E-01 -4.8130810704e-02  1.1455866520e+01  4.0155035313e+01\n36  2  3.8725258795124762E-01  2.8743271236e+00  1.4294384262e+01  4.0132651036e+01\n37  2  3.7342003398233831E-01  5.7360837333e+00 -1.4033161883e-02  2.0040227467e+01\n38  1 -4.0112209845641089E-01  8.5193853072e+00  2.8764031199e+00  1.9994398985e+01\n39  1 -3.4610575012682820E-01  5.6375475999e+00 -4.0667772549e-02  2.4029267612e+01\n40  2  3.3444687859953010E-01  8.5444746323e+00  2.8328648158e+00  2.4073209126e+01\n41  2  3.2977286773217079E-01  5.6374929679e+00  8.9788629595e-03  2.8040190972e+01\n42  1 -3.4517785256341482E-01  8.5205746819e+00  2.8135749087e+00  2.8097702553e+01\n43  1 -3.4554638801648696E-01  5.7090540565e+00  1.6821528168e-02  3.2068389906e+01\n44  2  3.3382590130835504E-01  8.5099907612e+00  2.8387661466e+00  3.2089405586e+01\n45  2  3.2671030857881539E-01  5.7491607505e+00  2.6551802873e-02  3.6161801185e+01\n46  1 -3.1121445409967080E-01  8.5696933090e+00  2.8243981820e+00  3.6095548904e+01\n47  1 -3.9549490315911745E-01  5.6004605747e+00 -3.9012674939e-02  4.0102869653e+01\n48  2  3.9618401154005384E-01  8.5839177868e+00  2.8525893410e+00  4.0129186941e+01\n49  2  3.6065557836492707E-01  5.6735244868e+00  5.6849201959e+00  1.9979804725e+01\n50  1 -4.0283363399652794E-01  8.5832999976e+00  8.5656793232e+00  1.9987182839e+01\n51  1 -3.4540454100172940E-01  5.7075209596e+00  5.6897493150e+00  2.4036549652e+01\n52  2  3.2682977765946147E-01  8.6020291474e+00  8.5486919149e+00  2.3965788409e+01\n53  2  3.2614167936219646E-01  5.7493104546e+00  5.6905967816e+00  2.8035716479e+01\n54  1 -3.4704518542992951E-01  8.5305642648e+00  8.5336383576e+00  2.8041326565e+01\n55  1 -3.0651620021158088E-01  5.6467260935e+00  5.6755829275e+00  3.2090861072e+01\n56  2  3.3142205106456285E-01  8.5337005863e+00  8.5466174493e+00  3.2081751157e+01\n57  3  4.0981307620742680E-01  5.6610188849e+00  5.6993559450e+00  3.6064080941e+01\n58  1 -2.9091958147245911E-01  8.5010303798e+00  8.5362875267e+00  3.6131963187e+01\n59  1 -3.6216384625985165E-01  5.6984002350e+00  5.7462274801e+00  4.0178786901e+01\n60  2  3.7810321218398363E-01  8.5592887234e+00  8.5947597306e+00  4.0146193152e+01\n61  2  4.1791251306477228E-01  5.6032739042e+00  1.1399683984e+01  1.9913916443e+01\n62  1 -4.0228298247337763E-01  8.5029228270e+00  1.4343324046e+01  2.0023014406e+01\n63  1 -3.4712093400918431E-01  5.6720512753e+00  1.1358988262e+01  2.4060251956e+01\n64  2  3.3249607431034101E-01  8.5254411798e+00  1.4231011829e+01  2.4012346344e+01\n65  2  3.2413149036707861E-01  5.7426630600e+00  1.1378874680e+01  2.8023933603e+01\n66  1 -3.4992251769580884E-01  8.6362523685e+00  1.4255022857e+01  2.8036097202e+01\n67  1 -3.4540108561664140E-01  5.7117658322e+00  1.1454697101e+01  3.2073160784e+01\n68  2  3.3480445647613249E-01  8.5246584175e+00  1.4270581047e+01  3.2102696917e+01\n69  2  3.2813653471690885E-01  5.7186666391e+00  1.1422359335e+01  3.6101213660e+01\n70  1 -3.1044009306062004E-01  8.5627598477e+00  1.4273198941e+01  3.6166519038e+01\n71  1 -4.0152383538759395E-01  5.7264381750e+00  1.1398781375e+01  4.0260042284e+01\n72  2  3.8461825101443542E-01  8.5102664156e+00  1.4232221424e+01  4.0091178051e+01\n73  2  4.0434089461753853E-01  1.1401532344e+01  4.5076087540e-02  2.0029059110e+01\n74  1 -4.0269081201368068E-01  1.4239757122e+01  2.8608573080e+00  1.9951038844e+01\n75  1 -3.4644736886291427E-01  1.1393443466e+01 -4.2770168300e-04  2.4001081706e+01\n76  2  3.3391498829207378E-01  1.4231685554e+01  2.8864018680e+00  2.4021645383e+01\n77  2  3.2637464521159698E-01  1.1402686003e+01  3.9371628390e-02  2.8113584925e+01\n78  1 -3.4526722283733730E-01  1.4244927525e+01  2.8375641675e+00  2.8036863637e+01\n79  1 -3.4317538266324116E-01  1.1395989211e+01  4.7920427509e-03  3.2086785538e+01\n80  2  3.3859570914612275E-01  1.4238799238e+01  2.8820363931e+00  3.2090336900e+01\n81  2  3.2717406973233076E-01  1.1420507253e+01  1.8697459157e-02  3.6120652572e+01\n82  1 -3.1199799110455384E-01  1.4268517750e+01  2.8561106375e+00  3.6168027133e+01\n83  1 -3.9787972466062677E-01  1.1414591957e+01 -8.2592458544e-02  4.0173253651e+01\n84  2  3.8944129327761023E-01  1.4256298422e+01  2.8717039194e+00  4.0140854601e+01\n85  2  4.0293056065045130E-01  1.1393721861e+01  5.7236951244e+00  2.0010035088e+01\n86  1 -4.0308428555845843E-01  1.4257639788e+01  8.4981605285e+00  1.9925047364e+01\n87  1 -3.4610510814460854E-01  1.1373306754e+01  5.7232945403e+00  2.3983895820e+01\n88  2  3.3563369794527187E-01  1.4251016393e+01  8.5961130012e+00  2.4011062539e+01\n89  2  3.3577567445494227E-01  1.1392303111e+01  5.6922237034e+00  2.8086502355e+01\n90  1 -3.4632024265923089E-01  1.4307995467e+01  8.5052796177e+00  2.8127594522e+01\n91  1 -3.4272129620502212E-01  1.1467787838e+01  5.7303018143e+00  3.2140124452e+01\n92  2  3.2658585338481128E-01  1.4223684114e+01  8.5394621152e+00  3.2083417385e+01\n93  2  3.2446795575973625E-01  1.1398360231e+01  5.6984501048e+00  3.6109137659e+01\n94  1 -3.1027087421689914E-01  1.4243599161e+01  8.4926708934e+00  3.6111924268e+01\n95  1 -4.0224397193198974E-01  1.1387116342e+01  5.7224672938e+00  4.0150551843e+01\n96  2  3.9141809039880648E-01  1.4251826367e+01  8.5541300360e+00  4.0169736719e+01\n97  2  4.1163259599154606E-01  1.1397087406e+01  1.1432029951e+01  1.9991521329e+01\n98  1 -3.9861261294319328E-01  1.4222100486e+01  1.4237423386e+01  1.9890837446e+01\n99  1 -3.4426097778309650E-01  1.1397172085e+01  1.1362254484e+01  2.4106729256e+01\n100 2  3.3507591789797203E-01  1.4223050564e+01  1.4272733426e+01  2.4026767277e+01\n101 2  3.2599946771409777E-01  1.1412415162e+01  1.1398466358e+01  2.8036581274e+01\n102 1 -3.4707768329649691E-01  1.4265352610e+01  1.4216093689e+01  2.8052093903e+01\n103 1 -3.0688777105113402E-01  1.1401696599e+01  1.1369599225e+01  3.2083243398e+01\n104 2  3.3018690623164043E-01  1.4233083328e+01  1.4215807831e+01  3.2083725032e+01\n105 3  4.0123726733194143E-01  1.1446195847e+01  1.1455486685e+01  3.6062830566e+01\n106 1 -2.8677889278053709E-01  1.4275939497e+01  1.4231407235e+01  3.6076973257e+01\n107 1 -3.5646759316313670E-01  1.1412436308e+01  1.1399368513e+01  4.0122450030e+01\n108 2  3.7555739662669552E-01  1.4206953179e+01  1.4201432515e+01  4.0151366429e+01\n109 4  3.6996649330713637E-02  2.7674441650e+00  3.2676547854e+00  1.5266538963e+01\n110 4 -1.4394128296917899E-01  2.7884963173e+00  3.1844017731e+00  1.0716139442e+01\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/md-external.lmp",
    "content": "###############################################################################\n# MD simulation for MgO with Al/Au\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"AlAuMgO.data\"\n# Timesteps\nvariable numSteps        equal  5\nvariable dt              equal  0.0005\n# NN\nvariable nnpCutoff       equal  8.01\nvariable nnpDir          string \"nnp-data\"\n# Masses\nvariable mass_O          equal  15.9994\nvariable mass_Mg         equal  24.305\nvariable mass_Al         equal  26.981539\nvariable mass_Au         equal  196.96657\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary p p p\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_O}\nmass 2 ${mass_Mg}\nmass 3 ${mass_Al}\nmass 4 ${mass_Au}\ntimestep ${dt}\nthermo 1\n\n###############################################################################\n# NN\n###############################################################################\npair_style nnp/external \"O Mg Al Au\" dir ${nnpDir} command \"RuNNer-gaussian.x\" cflength 1.0 cfenergy 1.0\n#pair_style nnp/external \"O Mg Al Au\" dir ${nnpDir} command \"nnp-predict 0\" cflength 1.0 cfenergy 1.0\npair_coeff * * ${nnpCutoff}\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\n#dump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/md.lmp",
    "content": "###############################################################################\n# MD simulation for MgO with Al/Au\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"input.data\"\n# Timesteps\nvariable numSteps        equal  0\nvariable dt              equal  0.0005\n# NN\n#variable hdnnpCutoff     equal  8.01\nvariable hdnnpCutoff     equal  8.00000001\nvariable hdnnpDir        string \"hdnnp-data\"\n# Masses\nvariable mass_O          equal  15.9994\nvariable mass_Mg         equal  24.305\nvariable mass_Al         equal  26.981539\nvariable mass_Au         equal  196.96657\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary p p p\natom_style charge\natom_modify map yes\nread_data ${cfgFile}\nmass 1 ${mass_O}\nmass 2 ${mass_Mg}\nmass 3 ${mass_Al}\nmass 4 ${mass_Au}\ntimestep ${dt}\nvelocity all create 300.0 12345\nthermo 1\n\nneighbor 0.0 bin\nneigh_modify delay 10 # Seems this was the default previously (29Oct2020).\n\n###############################################################################\n# NN\n###############################################################################\npair_style hdnnp/4g dir ${hdnnpDir} showew yes showewsum 10 resetew no maxew 1000000 cflength 1.0 cfenergy 1.0 emap \"1:O,2:Mg,3:Al,4:Au\"\npair_coeff * * ${hdnnpCutoff}\nkspace_style hdnnp ewald 1.0e-6\nfix 1 all hdnnp 1 1.0e-7 1.0e-1 1.0e-1 100 nnp nnp 1\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\n#dump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/nnp-predict/hardness.008.data",
    "content": "     12.9752105872\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/nnp-predict/hardness.012.data",
    "content": "     14.5786310784\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/nnp-predict/hardness.013.data",
    "content": "      1.4392244883\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/nnp-predict/hardness.079.data",
    "content": "      0.0175182304\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/nnp-predict/input.data",
    "content": "begin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -1.9775793498e-02 -6.4032231288e-02  2.0026111119e+01 Mg  3.8788494400e-01 0.0  4.0412140453e-03  7.0265869263e-03 -8.4677419696e-03\natom  2.8784590473e+00  2.8904829958e+00  2.0053576907e+01 O  -3.5909487600e-01 0.0 -3.5357067955e-03 -4.5792491166e-03  9.7973038610e-04\natom  7.2652159693e-02 -1.6211222263e-02  2.4043132172e+01 O  -3.4594157600e-01 0.0 -9.9524052388e-03  8.2613919709e-04  9.0438549577e-03\natom  2.8780260733e+00  2.8998185635e+00  2.4032640394e+01 Mg  3.2864151400e-01 0.0 -4.1635240288e-03 -8.3031064753e-03 -7.5802494690e-03\natom -5.6795412231e-02 -2.2440590601e-02  2.8111288946e+01 Mg  3.4539947400e-01 0.0  8.7251795163e-03 -6.4186986345e-05 -2.4363991342e-02\natom  2.8421666140e+00  2.8834652149e+00  2.8032859289e+01 O  -3.4176807600e-01 0.0 -4.0428635156e-04 -4.3146904728e-03  1.5444027344e-02\natom  6.5214500558e-02 -3.8745751143e-02  3.2113867333e+01 O  -3.0785905600e-01 0.0 -8.7729091934e-03  1.9519751482e-03  1.9968874099e-02\natom  2.8332198764e+00  2.7977822229e+00  3.2113907679e+01 Mg  3.3011505400e-01 0.0  2.2963600668e-03  5.3318657122e-03 -1.5343107719e-02\natom  1.9864553928e-02  1.0486013922e-02  3.6088078099e+01 Al  3.9917245400e-01 0.0  6.7803750166e-05 -7.0094514898e-04  1.5053560097e-02\natom  2.7981764575e+00  2.8796998036e+00  3.6124511960e+01 O  -2.8949547600e-01 0.0  3.6273019714e-03 -2.8183589325e-03 -7.9325270091e-03\natom -8.4521774292e-03 -2.2604637714e-02  4.0153894391e+01 O  -3.6598870600e-01 0.0 -5.8418150328e-04  2.0246535621e-03 -2.5173725174e-02\natom  2.8234702698e+00  2.8619477366e+00  4.0124676317e+01 Mg  3.7450518400e-01 0.0  1.3973418832e-03  7.8928841829e-05  1.5591933809e-02\natom -1.3119630546e-02  5.6888413584e+00  2.0013899747e+01 Mg  3.5809711400e-01 0.0  1.0417032765e-03  1.3876195467e-03 -1.2083096942e-02\natom  2.8848335277e+00  8.5308909417e+00  1.9989943256e+01 O  -3.9844002600e-01 0.0 -3.7448860438e-03  5.0357737828e-03  5.7879501668e-03\natom  1.8241298201e-02  5.6837552365e+00  2.4026099826e+01 O  -3.4215310600e-01 0.0 -2.8868044844e-03  2.3195077530e-03  1.1176398239e-02\natom  2.9361062157e+00  8.4795591997e+00  2.4082757439e+01 Mg  3.2952672400e-01 0.0 -7.9282995215e-03  7.7984136030e-03 -1.5464891041e-02\natom  1.6188356579e-02  5.6698041265e+00  2.8051270020e+01 Mg  3.3684778400e-01 0.0  2.2916383144e-03  4.1861975500e-03 -8.6622492722e-03\natom  2.8977599905e+00  8.5660735578e+00  2.8036115495e+01 O  -3.4409367600e-01 0.0 -3.3334995364e-03 -5.1017646429e-03  1.4470957486e-02\natom  9.8433937020e-04  5.6927154290e+00  3.2118501962e+01 O  -3.4614451600e-01 0.0  9.1005095975e-04 -4.0730943899e-03  4.9154030300e-03\natom  2.8073628502e+00  8.5498039808e+00  3.2128399704e+01 Mg  3.3498536400e-01 0.0  1.6059193804e-03  2.0542016438e-03 -1.6551022033e-02\natom -5.0996334501e-02  5.7492786883e+00  3.6121753734e+01 Mg  3.1982162400e-01 0.0  2.0618641544e-03 -3.0958082828e-03  5.5585234542e-03\natom  2.9059518581e+00  8.5723518134e+00  3.6118083754e+01 O  -3.1404623600e-01 0.0  6.9455266915e-03 -1.4599515105e-02 -4.8605312468e-03\natom  5.2199900983e-04  5.6455106974e+00  4.0180597258e+01 O  -4.0522186600e-01 0.0  7.6228232308e-04  7.0096828995e-03 -8.2712198059e-03\natom  2.8610732470e+00  8.5614353199e+00  4.0139419524e+01 Mg  3.8989854400e-01 0.0 -1.8149964341e-03  3.0632250705e-03  1.2872167566e-02\natom -3.9339238487e-02  1.1415957378e+01  1.9959977720e+01 Mg  4.3559881400e-01 0.0  5.0407268883e-03 -4.9856774589e-03  7.3154652172e-04\natom  2.9183726113e+00  1.4291678042e+01  1.9988445497e+01 O  -3.9816017600e-01 0.0 -9.0864151516e-03 -6.5665931399e-03  2.3483399976e-03\natom -2.1271587207e-02  1.1421205582e+01  2.4027048544e+01 O  -3.4569412600e-01 0.0 -1.6480077969e-03 -2.5662981317e-03  8.0363346320e-03\natom  2.9026486927e+00  1.4185336528e+01  2.4050086987e+01 Mg  3.2444578400e-01 0.0 -6.8689188539e-03  3.2051673130e-03 -1.0907852568e-02\natom -5.1509735258e-02  1.1382810885e+01  2.8094293015e+01 Mg  3.3699468400e-01 0.0  1.0337570946e-02 -2.4454976218e-03 -1.5847585775e-02\natom  2.9119668371e+00  1.4181088046e+01  2.8044752601e+01 O  -3.4257456600e-01 0.0 -8.2941301304e-03  6.6795718730e-03  1.4777589094e-02\natom  1.0413278368e-02  1.1323763827e+01  3.2100372838e+01 O  -3.4337754600e-01 0.0 -4.7694216653e-03  8.0178829511e-03  7.6432220993e-03\natom  2.7888050607e+00  1.4200832470e+01  3.2081624640e+01 Mg  3.3130130400e-01 0.0  1.3617006170e-02 -3.0759183427e-03 -9.3055525579e-03\natom -5.2366574815e-03  1.1380297134e+01  3.6148026784e+01 Mg  3.2297365400e-01 0.0  4.1066729168e-03  2.2768915629e-05  3.9804170447e-03\natom  2.8964801357e+00  1.4225437477e+01  3.6102833042e+01 O  -3.1847690600e-01 0.0 -1.5460639298e-02  1.3193699226e-02 -5.8103963873e-03\natom -4.8130810704e-02  1.1455866520e+01  4.0155035313e+01 O  -4.0505696600e-01 0.0  3.7970831683e-03 -6.3408931789e-03 -7.8798399309e-03\natom  2.8743271236e+00  1.4294384262e+01  4.0132651036e+01 Mg  3.8473278400e-01 0.0 -2.4948861758e-03 -7.5442135624e-03  1.0956968603e-02\natom  5.7360837333e+00 -1.4033161883e-02  2.0040227467e+01 Mg  3.7834282400e-01 0.0 -3.1145522209e-03  4.7039978880e-03 -9.5377403839e-03\natom  8.5193853072e+00  2.8764031199e+00  1.9994398985e+01 O  -3.9950044600e-01 0.0  4.0226856182e-03 -1.0833243234e-03  7.0920793159e-03\natom  5.6375475999e+00 -4.0667772549e-02  2.4029267612e+01 O  -3.4229819600e-01 0.0  8.2987266746e-03  5.1601950377e-03  1.3653884031e-02\natom  8.5444746323e+00  2.8328648158e+00  2.4073209126e+01 Mg  3.3553648400e-01 0.0 -1.1939707021e-03  3.5132870514e-04 -1.7099589602e-02\natom  5.6374929679e+00  8.9788629595e-03  2.8040190972e+01 Mg  3.3864572400e-01 0.0  3.1101976032e-03 -4.7262982395e-03 -8.3170798198e-03\natom  8.5205746819e+00  2.8135749087e+00  2.8097702553e+01 O  -3.3886362600e-01 0.0  3.7845103628e-03  5.8571539814e-03  6.9679588563e-03\natom  5.7090540565e+00  1.6821528168e-02  3.2068389906e+01 O  -3.4666686600e-01 0.0 -3.1239594304e-03  4.1799787804e-04  9.7581195600e-03\natom  8.5099907612e+00  2.8387661466e+00  3.2089405586e+01 Mg  3.3338522400e-01 0.0  4.5954450282e-03 -3.2823725103e-03 -7.8829159998e-03\natom  5.7491607505e+00  2.6551802873e-02  3.6161801185e+01 Mg  3.2062906400e-01 0.0 -4.1993310165e-03 -4.5241656508e-03 -9.8132859281e-04\natom  8.5696933090e+00  2.8243981820e+00  3.6095548904e+01 O  -3.1752737600e-01 0.0 -1.1989515676e-02  1.2992190124e-02 -4.1340044842e-03\natom  5.6004605747e+00 -3.9012674939e-02  4.0102869653e+01 O  -4.0424763600e-01 0.0  9.1904512527e-03  8.0531063374e-03 -4.3266832980e-03\natom  8.5839177868e+00  2.8525893410e+00  4.0129186941e+01 Mg  3.9453091400e-01 0.0 -8.9551899583e-04 -1.2966259170e-03  1.1905612997e-02\natom  5.6735244868e+00  5.6849201959e+00  1.9979804725e+01 Mg  3.6383293400e-01 0.0  4.5971562540e-03  2.1902624151e-03 -9.8381440608e-03\natom  8.5832999976e+00  8.5656793232e+00  1.9987182839e+01 O  -3.9964279600e-01 0.0 -1.8118615688e-03  4.3394088546e-03  1.8180132199e-03\natom  5.7075209596e+00  5.6897493150e+00  2.4036549652e+01 O  -3.4040861600e-01 0.0  3.2875388794e-03 -1.8092081345e-03  1.0919704276e-02\natom  8.6020291474e+00  8.5486919149e+00  2.3965788409e+01 Mg  3.2910246400e-01 0.0 -6.5282823297e-03 -1.9398922850e-05 -7.6593529797e-03\natom  5.7493104546e+00  5.6905967816e+00  2.8035716479e+01 Mg  3.3820629400e-01 0.0 -6.9332970705e-03  2.1950535253e-03 -1.1109486024e-02\natom  8.5305642648e+00  8.5336383576e+00  2.8041326565e+01 O  -3.4017292600e-01 0.0  6.2200847315e-03 -2.1695478471e-03  1.4204631174e-02\natom  5.6467260935e+00  5.6755829275e+00  3.2090861072e+01 O  -3.0795973600e-01 0.0  5.3782896637e-03  2.2777776459e-03  2.4895982323e-02\natom  8.5337005863e+00  8.5466174493e+00  3.2081751157e+01 Mg  3.3673371400e-01 0.0 -9.4849000381e-04  1.9614202195e-03 -1.0185315242e-02\natom  5.6610188849e+00  5.6993559450e+00  3.6064080941e+01 Al  3.9695487400e-01 0.0  2.0843440953e-03  5.4869365378e-03  1.3686507699e-02\natom  8.5010303798e+00  8.5362875267e+00  3.6131963187e+01 O  -2.9557145600e-01 0.0  3.0568550055e-04 -1.8106929285e-03 -1.0374877539e-02\natom  5.6984002350e+00  5.7462274801e+00  4.0178786901e+01 O  -3.6865153600e-01 0.0 -1.4045906970e-04 -5.9452336267e-03 -2.4798495009e-02\natom  8.5592887234e+00  8.5947597306e+00  4.0146193152e+01 Mg  3.7318686400e-01 0.0 -1.1433119464e-03 -3.5399292035e-03  1.3056911106e-02\natom  5.6032739042e+00  1.1399683984e+01  1.9913916443e+01 Mg  4.3835344400e-01 0.0  6.6418467348e-03 -1.1775122828e-03  3.1477360114e-03\natom  8.5029228270e+00  1.4343324046e+01  2.0023014406e+01 O  -3.9907663600e-01 0.0  7.2713665230e-03 -1.1173914494e-02  1.7166732560e-03\natom  5.6720512753e+00  1.1358988262e+01  2.4060251956e+01 O  -3.4351320600e-01 0.0  7.0636885577e-03  1.6039809108e-03  4.6649418728e-03\natom  8.5254411798e+00  1.4231011829e+01  2.4012346344e+01 Mg  3.3264691400e-01 0.0 -1.3993287519e-04  1.1852947065e-03 -7.4662349067e-03\natom  5.7426630600e+00  1.1378874680e+01  2.8023933603e+01 Mg  3.3174515400e-01 0.0 -3.6900886505e-03  1.8336596819e-03 -5.5396560217e-03\natom  8.6362523685e+00  1.4255022857e+01  2.8036097202e+01 O  -3.4397266600e-01 0.0 -5.0705193303e-03 -7.5718061593e-04  1.1779551880e-02\natom  5.7117658322e+00  1.1454697101e+01  3.2073160784e+01 O  -3.4651384600e-01 0.0  2.1618711944e-03 -7.4378623137e-03  8.9025832048e-03\natom  8.5246584175e+00  1.4270581047e+01  3.2102696917e+01 Mg  3.3500711400e-01 0.0 -3.8221904068e-03  2.1794735203e-03 -1.2919341424e-02\natom  5.7186666391e+00  1.1422359335e+01  3.6101213660e+01 Mg  3.2162119400e-01 0.0 -2.1102349976e-03  6.9409950913e-04  6.0550268388e-03\natom  8.5627598477e+00  1.4273198941e+01  3.6166519038e+01 O  -3.1534753600e-01 0.0  1.2512748219e-02 -1.2697967497e-02 -1.3121498323e-02\natom  5.7264381750e+00  1.1398781375e+01  4.0260042284e+01 O  -4.0657984600e-01 0.0 -1.9984775388e-03  6.5175188640e-04 -1.2874514248e-02\natom  8.5102664156e+00  1.4232221424e+01  4.0091178051e+01 Mg  3.8243331400e-01 0.0  2.3236357718e-04  3.0747797589e-03  1.6241732204e-02\natom  1.1401532344e+01  4.5076087540e-02  2.0029059110e+01 Mg  4.2144506400e-01 0.0 -2.6338069933e-03  1.8692072892e-03 -7.1830928865e-03\natom  1.4239757122e+01  2.8608573080e+00  1.9951038844e+01 O  -3.9885712600e-01 0.0 -6.7963033186e-04 -3.3978674162e-03  1.0028046590e-02\natom  1.1393443466e+01 -4.2770168300e-04  2.4001081706e+01 O  -3.4229476600e-01 0.0  2.0189146226e-03  9.1299232460e-04  1.4398345789e-02\natom  1.4231685554e+01  2.8864018680e+00  2.4021645383e+01 Mg  3.3282959400e-01 0.0  3.8787517487e-03 -2.8789314967e-03 -1.2767519873e-02\natom  1.1402686003e+01  3.9371628390e-02  2.8113584925e+01 Mg  3.3652098400e-01 0.0 -3.2700826696e-03 -6.2824640544e-03 -1.5263318317e-02\natom  1.4244927525e+01  2.8375641675e+00  2.8036863637e+01 O  -3.3851908600e-01 0.0 -1.3208680593e-03 -5.9644746145e-04  1.4148312919e-02\natom  1.1395989211e+01  4.7920427509e-03  3.2086785538e+01 O  -3.4427758600e-01 0.0  4.7319631798e-03 -7.9854064381e-04  8.2523928680e-03\natom  1.4238799238e+01  2.8820363931e+00  3.2090336900e+01 Mg  3.3852211400e-01 0.0 -1.2291432619e-03  1.8897942996e-03 -5.9334117928e-03\natom  1.1420507253e+01  1.8697459157e-02  3.6120652572e+01 Mg  3.2123483400e-01 0.0 -1.2722942429e-03  7.4047551684e-04  5.9269917397e-03\natom  1.4268517750e+01  2.8561106375e+00  3.6168027133e+01 O  -3.1630029600e-01 0.0  9.9977910458e-03 -1.4624310110e-02 -1.2145468097e-02\natom  1.1414591957e+01 -8.2592458544e-02  4.0173253651e+01 O  -4.0620398600e-01 0.0 -2.6302655582e-03  6.6918761996e-03 -8.7626692688e-03\natom  1.4256298422e+01  2.8717039194e+00  4.0140854601e+01 Mg  3.8601067400e-01 0.0 -2.8596898963e-03 -1.4777345476e-03  1.2289643997e-02\natom  1.1393721861e+01  5.7236951244e+00  2.0010035088e+01 Mg  4.2033274400e-01 0.0 -8.1139904315e-04 -3.0861963554e-03 -7.3630749684e-03\natom  1.4257639788e+01  8.4981605285e+00  1.9925047364e+01 O  -3.9897923600e-01 0.0 -1.7423814112e-03  8.5171378710e-03  8.0062458716e-03\natom  1.1373306754e+01  5.7232945403e+00  2.3983895820e+01 O  -3.4182347600e-01 0.0  4.0244773526e-03 -2.4137289154e-03  1.8159649360e-02\natom  1.4251016393e+01  8.5961130012e+00  2.4011062539e+01 Mg  3.3498552400e-01 0.0  4.4389163746e-03 -4.4172058062e-03 -9.4928399393e-03\natom  1.1392303111e+01  5.6922237034e+00  2.8086502355e+01 Mg  3.4501975400e-01 0.0  1.8134973837e-03  2.6779993312e-03 -1.2349980602e-02\natom  1.4307995467e+01  8.5052796177e+00  2.8127594522e+01 O  -3.4156871600e-01 0.0 -7.9013844901e-03  2.5678006408e-03  3.0349451961e-03\natom  1.1467787838e+01  5.7303018143e+00  3.2140124452e+01 O  -3.4440377600e-01 0.0 -1.1083574237e-02 -3.6233205620e-03  5.7329971301e-04\natom  1.4223684114e+01  8.5394621152e+00  3.2083417385e+01 Mg  3.2495508400e-01 0.0  7.0578324494e-03 -4.2671290167e-03 -7.2611099535e-03\natom  1.1398360231e+01  5.6984501048e+00  3.6109137659e+01 Mg  3.1960005400e-01 0.0 -6.5266005394e-05  4.8167648923e-04  7.8354922050e-03\natom  1.4243599161e+01  8.4926708934e+00  3.6111924268e+01 O  -3.1767765600e-01 0.0 -9.4029885467e-03  1.7964035274e-02 -4.5031305790e-03\natom  1.1387116342e+01  5.7224672938e+00  4.0150551843e+01 O  -4.0551030600e-01 0.0  2.9192985592e-04 -2.0199560577e-03 -6.7187072234e-03\natom  1.4251826367e+01  8.5541300360e+00  4.0169736719e+01 Mg  3.8899702400e-01 0.0  1.3419741060e-03 -3.7739771689e-03  9.1943222875e-03\natom  1.1397087406e+01  1.1432029951e+01  1.9991521329e+01 Mg  4.3234339400e-01 0.0 -2.9331678203e-03 -2.3537332479e-03 -3.5884246025e-03\natom  1.4222100486e+01  1.4237423386e+01  1.9890837446e+01 O  -3.9647633600e-01 0.0  1.2213495570e-04 -8.6001771121e-04  9.1625308313e-03\natom  1.1397172085e+01  1.1362254484e+01  2.4106729256e+01 O  -3.4142175600e-01 0.0  2.0876450668e-03  4.4046296191e-03  2.7239861311e-04\natom  1.4223050564e+01  1.4272733426e+01  2.4026767277e+01 Mg  3.3476471400e-01 0.0  5.0484460649e-03 -9.0630921718e-04 -9.3487312430e-03\natom  1.1412415162e+01  1.1398466358e+01  2.8036581274e+01 Mg  3.3912875400e-01 0.0 -2.3330411841e-03 -2.8659618461e-04 -1.1392465406e-02\natom  1.4265352610e+01  1.4216093689e+01  2.8052093903e+01 O  -3.3926433600e-01 0.0 -6.8569593497e-04  3.6447957468e-03  1.5464750274e-02\natom  1.1401696599e+01  1.1369599225e+01  3.2083243398e+01 O  -3.0799256600e-01 0.0 -1.8796304720e-04  3.6748951931e-03  2.3090729543e-02\natom  1.4233083328e+01  1.4215807831e+01  3.2083725032e+01 Mg  3.3553753400e-01 0.0  6.4488285943e-04  1.0481239340e-03 -1.1624902137e-02\natom  1.1446195847e+01  1.1455486685e+01  3.6062830566e+01 Al  3.9603740400e-01 0.0 -3.7845126362e-03 -5.5501858565e-03  1.3573459514e-02\natom  1.4275939497e+01  1.4231407235e+01  3.6076973257e+01 O  -2.8918410600e-01 0.0 -2.8119721838e-03  5.1917246104e-04 -6.1571751814e-03\natom  1.1412436308e+01  1.1399368513e+01  4.0122450030e+01 O  -3.6358139600e-01 0.0 -8.7882158509e-04 -9.1956096436e-04 -2.2866358560e-02\natom  1.4206953179e+01  1.4201432515e+01  4.0151366429e+01 Mg  3.7335335400e-01 0.0  3.7450445387e-03  5.1525057893e-03  1.4302349011e-02\natom  2.7674441650e+00  3.2676547854e+00  1.5266538963e+01 Au -1.8129486000e-02 0.0  4.7752095368e-04 -2.2142671411e-03  5.1007575752e-02\natom  2.7884963173e+00  3.1844017731e+00  1.0716139442e+01 Au -2.1088749600e-01 0.0 -3.8108279331e-05  1.9467681277e-04 -4.1132711694e-02\nenergy -5.4395981012e+04\ncharge  0.0000000000e+00\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/nnp-predict/input.data-2",
    "content": "begin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -1.9775793498e-02 -6.4032231288e-02  2.0026111119e+01 Mg  3.8788494400e-01 0.0  4.0412140453e-03  7.0265869263e-03 -8.4677419696e-03\natom  2.8784590473e+00  2.8904829958e+00  2.0053576907e+01 O  -3.5909487600e-01 0.0 -3.5357067955e-03 -4.5792491166e-03  9.7973038610e-04\natom  7.2652159693e-02 -1.6211222263e-02  2.4043132172e+01 O  -3.4594157600e-01 0.0 -9.9524052388e-03  8.2613919709e-04  9.0438549577e-03\natom  2.8780260733e+00  2.8998185635e+00  2.4032640394e+01 Mg  3.2864151400e-01 0.0 -4.1635240288e-03 -8.3031064753e-03 -7.5802494690e-03\natom -5.6795412231e-02 -2.2440590601e-02  2.8111288946e+01 Mg  3.4539947400e-01 0.0  8.7251795163e-03 -6.4186986345e-05 -2.4363991342e-02\natom  2.8421666140e+00  2.8834652149e+00  2.8032859289e+01 O  -3.4176807600e-01 0.0 -4.0428635156e-04 -4.3146904728e-03  1.5444027344e-02\natom  6.5214500558e-02 -3.8745751143e-02  3.2113867333e+01 O  -3.0785905600e-01 0.0 -8.7729091934e-03  1.9519751482e-03  1.9968874099e-02\natom  2.8332198764e+00  2.7977822229e+00  3.2113907679e+01 Mg  3.3011505400e-01 0.0  2.2963600668e-03  5.3318657122e-03 -1.5343107719e-02\natom  1.9864553928e-02  1.0486013922e-02  3.6088078099e+01 Al  3.9917245400e-01 0.0  6.7803750166e-05 -7.0094514898e-04  1.5053560097e-02\natom  2.7981764575e+00  2.8796998036e+00  3.6124511960e+01 O  -2.8949547600e-01 0.0  3.6273019714e-03 -2.8183589325e-03 -7.9325270091e-03\natom -8.4521774292e-03 -2.2604637714e-02  4.0153894391e+01 O  -3.6598870600e-01 0.0 -5.8418150328e-04  2.0246535621e-03 -2.5173725174e-02\natom  2.8234702698e+00  2.8619477366e+00  4.0124676317e+01 Mg  3.7450518400e-01 0.0  1.3973418832e-03  7.8928841829e-05  1.5591933809e-02\natom -1.3119630546e-02  5.6888413584e+00  2.0013899747e+01 Mg  3.5809711400e-01 0.0  1.0417032765e-03  1.3876195467e-03 -1.2083096942e-02\natom  2.8848335277e+00  8.5308909417e+00  1.9989943256e+01 O  -3.9844002600e-01 0.0 -3.7448860438e-03  5.0357737828e-03  5.7879501668e-03\natom  1.8241298201e-02  5.6837552365e+00  2.4026099826e+01 O  -3.4215310600e-01 0.0 -2.8868044844e-03  2.3195077530e-03  1.1176398239e-02\natom  2.9361062157e+00  8.4795591997e+00  2.4082757439e+01 Mg  3.2952672400e-01 0.0 -7.9282995215e-03  7.7984136030e-03 -1.5464891041e-02\natom  1.6188356579e-02  5.6698041265e+00  2.8051270020e+01 Mg  3.3684778400e-01 0.0  2.2916383144e-03  4.1861975500e-03 -8.6622492722e-03\natom  2.8977599905e+00  8.5660735578e+00  2.8036115495e+01 O  -3.4409367600e-01 0.0 -3.3334995364e-03 -5.1017646429e-03  1.4470957486e-02\natom  9.8433937020e-04  5.6927154290e+00  3.2118501962e+01 O  -3.4614451600e-01 0.0  9.1005095975e-04 -4.0730943899e-03  4.9154030300e-03\natom  2.8073628502e+00  8.5498039808e+00  3.2128399704e+01 Mg  3.3498536400e-01 0.0  1.6059193804e-03  2.0542016438e-03 -1.6551022033e-02\natom -5.0996334501e-02  5.7492786883e+00  3.6121753734e+01 Mg  3.1982162400e-01 0.0  2.0618641544e-03 -3.0958082828e-03  5.5585234542e-03\natom  2.9059518581e+00  8.5723518134e+00  3.6118083754e+01 O  -3.1404623600e-01 0.0  6.9455266915e-03 -1.4599515105e-02 -4.8605312468e-03\natom  5.2199900983e-04  5.6455106974e+00  4.0180597258e+01 O  -4.0522186600e-01 0.0  7.6228232308e-04  7.0096828995e-03 -8.2712198059e-03\natom  2.8610732470e+00  8.5614353199e+00  4.0139419524e+01 Mg  3.8989854400e-01 0.0 -1.8149964341e-03  3.0632250705e-03  1.2872167566e-02\natom -3.9339238487e-02  1.1415957378e+01  1.9959977720e+01 Mg  4.3559881400e-01 0.0  5.0407268883e-03 -4.9856774589e-03  7.3154652172e-04\natom  2.9183726113e+00  1.4291678042e+01  1.9988445497e+01 O  -3.9816017600e-01 0.0 -9.0864151516e-03 -6.5665931399e-03  2.3483399976e-03\natom -2.1271587207e-02  1.1421205582e+01  2.4027048544e+01 O  -3.4569412600e-01 0.0 -1.6480077969e-03 -2.5662981317e-03  8.0363346320e-03\natom  2.9026486927e+00  1.4185336528e+01  2.4050086987e+01 Mg  3.2444578400e-01 0.0 -6.8689188539e-03  3.2051673130e-03 -1.0907852568e-02\natom -5.1509735258e-02  1.1382810885e+01  2.8094293015e+01 Mg  3.3699468400e-01 0.0  1.0337570946e-02 -2.4454976218e-03 -1.5847585775e-02\natom  2.9119668371e+00  1.4181088046e+01  2.8044752601e+01 O  -3.4257456600e-01 0.0 -8.2941301304e-03  6.6795718730e-03  1.4777589094e-02\natom  1.0413278368e-02  1.1323763827e+01  3.2100372838e+01 O  -3.4337754600e-01 0.0 -4.7694216653e-03  8.0178829511e-03  7.6432220993e-03\natom  2.7888050607e+00  1.4200832470e+01  3.2081624640e+01 Mg  3.3130130400e-01 0.0  1.3617006170e-02 -3.0759183427e-03 -9.3055525579e-03\natom -5.2366574815e-03  1.1380297134e+01  3.6148026784e+01 Mg  3.2297365400e-01 0.0  4.1066729168e-03  2.2768915629e-05  3.9804170447e-03\natom  2.8964801357e+00  1.4225437477e+01  3.6102833042e+01 O  -3.1847690600e-01 0.0 -1.5460639298e-02  1.3193699226e-02 -5.8103963873e-03\natom -4.8130810704e-02  1.1455866520e+01  4.0155035313e+01 O  -4.0505696600e-01 0.0  3.7970831683e-03 -6.3408931789e-03 -7.8798399309e-03\natom  2.8743271236e+00  1.4294384262e+01  4.0132651036e+01 Mg  3.8473278400e-01 0.0 -2.4948861758e-03 -7.5442135624e-03  1.0956968603e-02\natom  5.7360837333e+00 -1.4033161883e-02  2.0040227467e+01 Mg  3.7834282400e-01 0.0 -3.1145522209e-03  4.7039978880e-03 -9.5377403839e-03\natom  8.5193853072e+00  2.8764031199e+00  1.9994398985e+01 O  -3.9950044600e-01 0.0  4.0226856182e-03 -1.0833243234e-03  7.0920793159e-03\natom  5.6375475999e+00 -4.0667772549e-02  2.4029267612e+01 O  -3.4229819600e-01 0.0  8.2987266746e-03  5.1601950377e-03  1.3653884031e-02\natom  8.5444746323e+00  2.8328648158e+00  2.4073209126e+01 Mg  3.3553648400e-01 0.0 -1.1939707021e-03  3.5132870514e-04 -1.7099589602e-02\natom  5.6374929679e+00  8.9788629595e-03  2.8040190972e+01 Mg  3.3864572400e-01 0.0  3.1101976032e-03 -4.7262982395e-03 -8.3170798198e-03\natom  8.5205746819e+00  2.8135749087e+00  2.8097702553e+01 O  -3.3886362600e-01 0.0  3.7845103628e-03  5.8571539814e-03  6.9679588563e-03\natom  5.7090540565e+00  1.6821528168e-02  3.2068389906e+01 O  -3.4666686600e-01 0.0 -3.1239594304e-03  4.1799787804e-04  9.7581195600e-03\natom  8.5099907612e+00  2.8387661466e+00  3.2089405586e+01 Mg  3.3338522400e-01 0.0  4.5954450282e-03 -3.2823725103e-03 -7.8829159998e-03\natom  5.7491607505e+00  2.6551802873e-02  3.6161801185e+01 Mg  3.2062906400e-01 0.0 -4.1993310165e-03 -4.5241656508e-03 -9.8132859281e-04\natom  8.5696933090e+00  2.8243981820e+00  3.6095548904e+01 O  -3.1752737600e-01 0.0 -1.1989515676e-02  1.2992190124e-02 -4.1340044842e-03\natom  5.6004605747e+00 -3.9012674939e-02  4.0102869653e+01 O  -4.0424763600e-01 0.0  9.1904512527e-03  8.0531063374e-03 -4.3266832980e-03\natom  8.5839177868e+00  2.8525893410e+00  4.0129186941e+01 Mg  3.9453091400e-01 0.0 -8.9551899583e-04 -1.2966259170e-03  1.1905612997e-02\natom  5.6735244868e+00  5.6849201959e+00  1.9979804725e+01 Mg  3.6383293400e-01 0.0  4.5971562540e-03  2.1902624151e-03 -9.8381440608e-03\natom  8.5832999976e+00  8.5656793232e+00  1.9987182839e+01 O  -3.9964279600e-01 0.0 -1.8118615688e-03  4.3394088546e-03  1.8180132199e-03\natom  5.7075209596e+00  5.6897493150e+00  2.4036549652e+01 O  -3.4040861600e-01 0.0  3.2875388794e-03 -1.8092081345e-03  1.0919704276e-02\natom  8.6020291474e+00  8.5486919149e+00  2.3965788409e+01 Mg  3.2910246400e-01 0.0 -6.5282823297e-03 -1.9398922850e-05 -7.6593529797e-03\natom  5.7493104546e+00  5.6905967816e+00  2.8035716479e+01 Mg  3.3820629400e-01 0.0 -6.9332970705e-03  2.1950535253e-03 -1.1109486024e-02\natom  8.5305642648e+00  8.5336383576e+00  2.8041326565e+01 O  -3.4017292600e-01 0.0  6.2200847315e-03 -2.1695478471e-03  1.4204631174e-02\natom  5.6467260935e+00  5.6755829275e+00  3.2090861072e+01 O  -3.0795973600e-01 0.0  5.3782896637e-03  2.2777776459e-03  2.4895982323e-02\natom  8.5337005863e+00  8.5466174493e+00  3.2081751157e+01 Mg  3.3673371400e-01 0.0 -9.4849000381e-04  1.9614202195e-03 -1.0185315242e-02\natom  5.6610188849e+00  5.6993559450e+00  3.6064080941e+01 Al  3.9695487400e-01 0.0  2.0843440953e-03  5.4869365378e-03  1.3686507699e-02\natom  8.5010303798e+00  8.5362875267e+00  3.6131963187e+01 O  -2.9557145600e-01 0.0  3.0568550055e-04 -1.8106929285e-03 -1.0374877539e-02\natom  5.6984002350e+00  5.7462274801e+00  4.0178786901e+01 O  -3.6865153600e-01 0.0 -1.4045906970e-04 -5.9452336267e-03 -2.4798495009e-02\natom  8.5592887234e+00  8.5947597306e+00  4.0146193152e+01 Mg  3.7318686400e-01 0.0 -1.1433119464e-03 -3.5399292035e-03  1.3056911106e-02\natom  5.6032739042e+00  1.1399683984e+01  1.9913916443e+01 Mg  4.3835344400e-01 0.0  6.6418467348e-03 -1.1775122828e-03  3.1477360114e-03\natom  8.5029228270e+00  1.4343324046e+01  2.0023014406e+01 O  -3.9907663600e-01 0.0  7.2713665230e-03 -1.1173914494e-02  1.7166732560e-03\natom  5.6720512753e+00  1.1358988262e+01  2.4060251956e+01 O  -3.4351320600e-01 0.0  7.0636885577e-03  1.6039809108e-03  4.6649418728e-03\natom  8.5254411798e+00  1.4231011829e+01  2.4012346344e+01 Mg  3.3264691400e-01 0.0 -1.3993287519e-04  1.1852947065e-03 -7.4662349067e-03\natom  5.7426630600e+00  1.1378874680e+01  2.8023933603e+01 Mg  3.3174515400e-01 0.0 -3.6900886505e-03  1.8336596819e-03 -5.5396560217e-03\natom  8.6362523685e+00  1.4255022857e+01  2.8036097202e+01 O  -3.4397266600e-01 0.0 -5.0705193303e-03 -7.5718061593e-04  1.1779551880e-02\natom  5.7117658322e+00  1.1454697101e+01  3.2073160784e+01 O  -3.4651384600e-01 0.0  2.1618711944e-03 -7.4378623137e-03  8.9025832048e-03\natom  8.5246584175e+00  1.4270581047e+01  3.2102696917e+01 Mg  3.3500711400e-01 0.0 -3.8221904068e-03  2.1794735203e-03 -1.2919341424e-02\natom  5.7186666391e+00  1.1422359335e+01  3.6101213660e+01 Mg  3.2162119400e-01 0.0 -2.1102349976e-03  6.9409950913e-04  6.0550268388e-03\natom  8.5627598477e+00  1.4273198941e+01  3.6166519038e+01 O  -3.1534753600e-01 0.0  1.2512748219e-02 -1.2697967497e-02 -1.3121498323e-02\natom  5.7264381750e+00  1.1398781375e+01  4.0260042284e+01 O  -4.0657984600e-01 0.0 -1.9984775388e-03  6.5175188640e-04 -1.2874514248e-02\natom  8.5102664156e+00  1.4232221424e+01  4.0091178051e+01 Mg  3.8243331400e-01 0.0  2.3236357718e-04  3.0747797589e-03  1.6241732204e-02\natom  1.1401532344e+01  4.5076087540e-02  2.0029059110e+01 Mg  4.2144506400e-01 0.0 -2.6338069933e-03  1.8692072892e-03 -7.1830928865e-03\natom  1.4239757122e+01  2.8608573080e+00  1.9951038844e+01 O  -3.9885712600e-01 0.0 -6.7963033186e-04 -3.3978674162e-03  1.0028046590e-02\natom  1.1393443466e+01 -4.2770168300e-04  2.4001081706e+01 O  -3.4229476600e-01 0.0  2.0189146226e-03  9.1299232460e-04  1.4398345789e-02\natom  1.4231685554e+01  2.8864018680e+00  2.4021645383e+01 Mg  3.3282959400e-01 0.0  3.8787517487e-03 -2.8789314967e-03 -1.2767519873e-02\natom  1.1402686003e+01  3.9371628390e-02  2.8113584925e+01 Mg  3.3652098400e-01 0.0 -3.2700826696e-03 -6.2824640544e-03 -1.5263318317e-02\natom  1.4244927525e+01  2.8375641675e+00  2.8036863637e+01 O  -3.3851908600e-01 0.0 -1.3208680593e-03 -5.9644746145e-04  1.4148312919e-02\natom  1.1395989211e+01  4.7920427509e-03  3.2086785538e+01 O  -3.4427758600e-01 0.0  4.7319631798e-03 -7.9854064381e-04  8.2523928680e-03\natom  1.4238799238e+01  2.8820363931e+00  3.2090336900e+01 Mg  3.3852211400e-01 0.0 -1.2291432619e-03  1.8897942996e-03 -5.9334117928e-03\natom  1.1420507253e+01  1.8697459157e-02  3.6120652572e+01 Mg  3.2123483400e-01 0.0 -1.2722942429e-03  7.4047551684e-04  5.9269917397e-03\natom  1.4268517750e+01  2.8561106375e+00  3.6168027133e+01 O  -3.1630029600e-01 0.0  9.9977910458e-03 -1.4624310110e-02 -1.2145468097e-02\natom  1.1414591957e+01 -8.2592458544e-02  4.0173253651e+01 O  -4.0620398600e-01 0.0 -2.6302655582e-03  6.6918761996e-03 -8.7626692688e-03\natom  1.4256298422e+01  2.8717039194e+00  4.0140854601e+01 Mg  3.8601067400e-01 0.0 -2.8596898963e-03 -1.4777345476e-03  1.2289643997e-02\natom  1.1393721861e+01  5.7236951244e+00  2.0010035088e+01 Mg  4.2033274400e-01 0.0 -8.1139904315e-04 -3.0861963554e-03 -7.3630749684e-03\natom  1.4257639788e+01  8.4981605285e+00  1.9925047364e+01 O  -3.9897923600e-01 0.0 -1.7423814112e-03  8.5171378710e-03  8.0062458716e-03\natom  1.1373306754e+01  5.7232945403e+00  2.3983895820e+01 O  -3.4182347600e-01 0.0  4.0244773526e-03 -2.4137289154e-03  1.8159649360e-02\natom  1.4251016393e+01  8.5961130012e+00  2.4011062539e+01 Mg  3.3498552400e-01 0.0  4.4389163746e-03 -4.4172058062e-03 -9.4928399393e-03\natom  1.1392303111e+01  5.6922237034e+00  2.8086502355e+01 Mg  3.4501975400e-01 0.0  1.8134973837e-03  2.6779993312e-03 -1.2349980602e-02\natom  1.4307995467e+01  8.5052796177e+00  2.8127594522e+01 O  -3.4156871600e-01 0.0 -7.9013844901e-03  2.5678006408e-03  3.0349451961e-03\natom  1.1467787838e+01  5.7303018143e+00  3.2140124452e+01 O  -3.4440377600e-01 0.0 -1.1083574237e-02 -3.6233205620e-03  5.7329971301e-04\natom  1.4223684114e+01  8.5394621152e+00  3.2083417385e+01 Mg  3.2495508400e-01 0.0  7.0578324494e-03 -4.2671290167e-03 -7.2611099535e-03\natom  1.1398360231e+01  5.6984501048e+00  3.6109137659e+01 Mg  3.1960005400e-01 0.0 -6.5266005394e-05  4.8167648923e-04  7.8354922050e-03\natom  1.4243599161e+01  8.4926708934e+00  3.6111924268e+01 O  -3.1767765600e-01 0.0 -9.4029885467e-03  1.7964035274e-02 -4.5031305790e-03\natom  1.1387116342e+01  5.7224672938e+00  4.0150551843e+01 O  -4.0551030600e-01 0.0  2.9192985592e-04 -2.0199560577e-03 -6.7187072234e-03\natom  1.4251826367e+01  8.5541300360e+00  4.0169736719e+01 Mg  3.8899702400e-01 0.0  1.3419741060e-03 -3.7739771689e-03  9.1943222875e-03\natom  1.1397087406e+01  1.1432029951e+01  1.9991521329e+01 Mg  4.3234339400e-01 0.0 -2.9331678203e-03 -2.3537332479e-03 -3.5884246025e-03\natom  1.4222100486e+01  1.4237423386e+01  1.9890837446e+01 O  -3.9647633600e-01 0.0  1.2213495570e-04 -8.6001771121e-04  9.1625308313e-03\natom  1.1397172085e+01  1.1362254484e+01  2.4106729256e+01 O  -3.4142175600e-01 0.0  2.0876450668e-03  4.4046296191e-03  2.7239861311e-04\natom  1.4223050564e+01  1.4272733426e+01  2.4026767277e+01 Mg  3.3476471400e-01 0.0  5.0484460649e-03 -9.0630921718e-04 -9.3487312430e-03\natom  1.1412415162e+01  1.1398466358e+01  2.8036581274e+01 Mg  3.3912875400e-01 0.0 -2.3330411841e-03 -2.8659618461e-04 -1.1392465406e-02\natom  1.4265352610e+01  1.4216093689e+01  2.8052093903e+01 O  -3.3926433600e-01 0.0 -6.8569593497e-04  3.6447957468e-03  1.5464750274e-02\natom  1.1401696599e+01  1.1369599225e+01  3.2083243398e+01 O  -3.0799256600e-01 0.0 -1.8796304720e-04  3.6748951931e-03  2.3090729543e-02\natom  1.4233083328e+01  1.4215807831e+01  3.2083725032e+01 Mg  3.3553753400e-01 0.0  6.4488285943e-04  1.0481239340e-03 -1.1624902137e-02\natom  1.1446195847e+01  1.1455486685e+01  3.6062830566e+01 Al  3.9603740400e-01 0.0 -3.7845126362e-03 -5.5501858565e-03  1.3573459514e-02\natom  1.4275939497e+01  1.4231407235e+01  3.6076973257e+01 O  -2.8918410600e-01 0.0 -2.8119721838e-03  5.1917246104e-04 -6.1571751814e-03\natom  1.1412436308e+01  1.1399368513e+01  4.0122450030e+01 O  -3.6358139600e-01 0.0 -8.7882158509e-04 -9.1956096436e-04 -2.2866358560e-02\natom  1.4206953179e+01  1.4201432515e+01  4.0151366429e+01 Mg  3.7335335400e-01 0.0  3.7450445387e-03  5.1525057893e-03  1.4302349011e-02\natom  2.7674441650e+00  3.2676547854e+00  1.5266538963e+01 Au -1.8129486000e-02 0.0  4.7752095368e-04 -2.2142671411e-03  5.1007575752e-02\natom  2.7884963173e+00  3.1844017731e+00  1.0716139442e+01 Au -2.1088749600e-01 0.0 -3.8108279331e-05  1.9467681277e-04 -4.1132711694e-02\nenergy -5.4395981012e+04\ncharge  0.0000000000e+00\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/nnp-predict/input.nn",
    "content": "## #############################################################\n### This is the input file for RuNNer \n### #############################################################\n### General remarks: \n### - commands can be switched off by using the # character at the BEGINNING of the line\n### - the input file can be structured by blank lines and comment lines\n### - the order of the keywords is arbitrary\n### - if keywords are missing, default values will be used and written to runner.out\n### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message \n\n### THIS INPUT.NN IS AN EXAMPLE, IT IS NOT A REALISTIC CASE\n### It contains only a subset of all keywords\n\n########################################################################################################################\n### general keywords\n########################################################################################################################\n\nnnp_generation 4\nuse_electrostatics\nuse_short_nn\nuse_short_forces                    \nprecondition_weights            \n#regularize_fit_param 1.e-4\nrunner_mode 2\nepochs 100\n#epochs 25\n\nnumber_of_elements 4\nelements Al O Mg Au\n\ninitial_hardness        O        1.0\ninitial_hardness       Mg        1.0\ninitial_hardness       Al        1.0\ninitial_hardness       Au        1.0\n\nfixed_gausswidth Mg 4.289\nfixed_gausswidth  O 2.872\nfixed_gausswidth Al 3.477\nfixed_gausswidth Au 3.288\n\nscreen_electrostatics 3.2 8.0\n\nparallel_mode 1\nrandom_seed 12346\nrandom_number_type 5\n\nremove_atom_energies                     \natom_energy     O    -75.29000258799172\natom_energy    Mg   -200.61689378490792\natom_energy    Au -19684.765036573383\natom_energy    Al   -243.09681374120558\n\nenergy_threshold 100.0d0\nbond_threshold 0.4d0\newald_prec 1.e-6\n#\n\n########################################################################################################################\n### NN structure of the short-range NN  \n########################################################################################################################\nglobal_hidden_layers_short 2              \nglobal_nodes_short 15 15\nglobal_activation_short t t l            \nglobal_hidden_layers_electrostatic 2              \nglobal_nodes_electrostatic 15 15\nglobal_activation_electrostatic t t l            \n\n########################################################################################################################\n### symmetry function generation ( mode 1): \n########################################################################################################################\ntest_fraction 0.1      \n\n########################################################################################################################\n### symmetry function definitions (all modes): \n########################################################################################################################\ncutoff_type 2\n\nsymfunction Mg  2  Mg    0.000000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.001000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.002000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.003000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.004000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.005000      0.000000      8.000000\n\n\nsymfunction O  2 Mg     0.000000      0.000000      8.000000\nsymfunction O  2 Mg     0.004000      0.000000      8.000000\nsymfunction O  2 Mg     0.007000      0.000000      8.000000\nsymfunction O  2 Mg     0.010000      0.000000      8.000000\nsymfunction O  2 Mg     0.014000      0.000000      8.000000\nsymfunction O  2 Mg     0.018000      0.000000      8.000000\n\nsymfunction Mg 2  O    0.000000      0.000000      8.000000\nsymfunction Mg 2  O    0.004000      0.000000      8.000000\nsymfunction Mg 2  O    0.007000      0.000000      8.000000\nsymfunction Mg 2  O    0.010000      0.000000      8.000000\nsymfunction Mg 2  O    0.014000      0.000000      8.000000\nsymfunction Mg 2  O    0.018000      0.000000      8.000000\n\nsymfunction O  2  O    0.000000      0.000000      8.000000\nsymfunction O  2  O    0.001000      0.000000      8.000000\nsymfunction O  2  O    0.002000      0.000000      8.000000\nsymfunction O  2  O    0.003000      0.000000      8.000000\nsymfunction O  2  O    0.004000      0.000000      8.000000\nsymfunction O  2  O    0.005000      0.000000      8.000000\n\nsymfunction Mg  2  Au    0.000000      0.000000      8.000000\nsymfunction Mg  2  Au    0.001000      0.000000      8.000000\nsymfunction Mg  2  Au    0.002000      0.000000      8.000000\nsymfunction Mg  2  Au    0.003000      0.000000      8.000000\nsymfunction Mg  2  Au    0.004000      0.000000      8.000000\nsymfunction Mg  2  Au    0.005000      0.000000      8.000000\n\nsymfunction Au  2  Mg    0.000000      0.000000      8.000000\nsymfunction Au  2  Mg    0.001000      0.000000      8.000000\nsymfunction Au  2  Mg    0.002000      0.000000      8.000000\nsymfunction Au  2  Mg    0.003000      0.000000      8.000000\nsymfunction Au  2  Mg    0.004000      0.000000      8.000000\nsymfunction Au  2  Mg    0.005000      0.000000      8.000000\n\n\nsymfunction Au  2 O     0.000000      0.000000      8.000000\nsymfunction Au  2 O     0.004000      0.000000      8.000000\nsymfunction Au  2 O     0.008000      0.000000      8.000000\nsymfunction Au  2 O     0.013000      0.000000      8.000000\nsymfunction Au  2 O     0.018000      0.000000      8.000000\nsymfunction Au  2 O     0.024000      0.000000      8.000000\n\nsymfunction O  2 Au     0.000000      0.000000      8.000000\nsymfunction O  2 Au     0.004000      0.000000      8.000000\nsymfunction O  2 Au     0.008000      0.000000      8.000000\nsymfunction O  2 Au     0.013000      0.000000      8.000000\nsymfunction O  2 Au     0.018000      0.000000      8.000000\nsymfunction O  2 Au     0.024000      0.000000      8.000000\n\nsymfunction Au  2 Au     0.000000      0.000000      8.000000\nsymfunction Au  2 Au     0.004000      0.000000      8.000000\nsymfunction Au  2 Au     0.008000      0.000000      8.000000\nsymfunction Au  2 Au     0.012000      0.000000      8.000000\nsymfunction Au  2 Au     0.017000      0.000000      8.000000\nsymfunction Au  2 Au     0.022000      0.000000      8.000000\n\n\nsymfunction O  2  Al    0.000000      0.000000      8.000000\nsymfunction O  2  Al    0.003000      0.000000      8.000000\nsymfunction O  2  Al    0.005000      0.000000      8.000000\nsymfunction O  2  Al    0.008000      0.000000      8.000000\nsymfunction O  2  Al    0.011000      0.000000      8.000000\nsymfunction O  2  Al    0.014000      0.000000      8.000000\n\nsymfunction Al  2  O    0.000000      0.000000      8.000000\nsymfunction Al  2  O    0.003000      0.000000      8.000000\nsymfunction Al  2  O    0.005000      0.000000      8.000000\nsymfunction Al  2  O    0.008000      0.000000      8.000000\nsymfunction Al  2  O    0.011000      0.000000      8.000000\nsymfunction Al  2  O    0.014000      0.000000      8.000000\n\nsymfunction Al  2  Mg    0.000000      0.000000      8.000000\nsymfunction Al  2  Mg    0.001000      0.000000      8.000000\nsymfunction Al  2  Mg    0.002000      0.000000      8.000000\nsymfunction Al  2  Mg    0.003000      0.000000      8.000000\nsymfunction Al  2  Mg    0.004000      0.000000      8.000000\nsymfunction Al  2  Mg    0.005000      0.000000      8.000000\n\nsymfunction Mg  2  Al    0.000000      0.000000      8.000000\nsymfunction Mg  2  Al    0.001000      0.000000      8.000000\nsymfunction Mg  2  Al    0.002000      0.000000      8.000000\nsymfunction Mg  2  Al    0.003000      0.000000      8.000000\nsymfunction Mg  2  Al    0.004000      0.000000      8.000000\nsymfunction Mg  2  Al    0.005000      0.000000      8.000000\n\n#symfunction Al  2  Al    0.000000      0.000000      8.000000\n#symfunction Al  2  Al    0.001000      0.000000      8.000000\n#symfunction Al  2  Al    0.002000      0.000000      8.000000\n#symfunction Al  2  Al    0.003000      0.000000      8.000000\n#symfunction Al  2  Al    0.004000      0.000000      8.000000\n#symfunction Al  2  Al    0.005000      0.000000      8.000000\n\n\nsymfunction Mg 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction Mg 3 Mg Mg 0.0  1.0 2.0  8.0\nsymfunction Mg 3 Mg Mg 0.0  1.0 4.0  8.0\n#symfunction Mg 3 Mg Mg 0.0  1.0 8.0  8.0\nsymfunction Mg 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 4.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 8.0  8.0\nsymfunction Mg 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction Mg 3 Mg  O 0.0 -1.0 2.0  8.0\n#symfunction Mg 3 Mg  O 0.0 -1.0 4.0  8.0\n#symfunction Mg 3 Mg  O 0.0 -1.0 8.0  8.0\n\n#symfunction Mg 3 Mg Al 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Mg Al 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Mg Al 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Al 0.0 -1.0 2.0  8.0\n\n#symfunction Mg 3 Mg Au 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Mg Au 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Mg Au 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3  O  O 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O  O 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O  O 0.0  1.0 4.0  8.0\n#symfunction Mg 3  O  O 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 1.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 2.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 4.0  8.0\n#symfunction Mg 3  O  O 0.0 -1.0 8.0  8.0\n\nsymfunction Mg 3  O Al 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 4.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O Al 0.0 -1.0 1.0  8.0\n#symfunction Mg 3  O Al 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3  O Au 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 4.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O Au 0.0 -1.0 1.0  8.0\nsymfunction Mg 3  O Au 0.0 -1.0 2.0  8.0\n\n#symfunction Mg 3 Al Al 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Al Al 0.0  1.0 2.0  8.0\n\n#symfunction Mg 3 Au Au 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Au Au 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Au Au 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Au Au 0.0 -1.0 2.0  8.0\n\n\n\nsymfunction  O 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Mg 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Mg 0.0  1.0 4.0  8.0\n#symfunction  O 3 Mg Mg 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 2.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg Mg 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 4.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg  O 0.0 -1.0 2.0  8.0\n#symfunction  O 3 Mg  O 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg  O 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg Al 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Al 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Al 0.0  1.0 4.0  8.0\n#symfunction  O 3 Mg Al 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 2.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg Al 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg Au 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Au 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Au 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction  O 3  O  O 0.0  1.0 1.0  8.0\nsymfunction  O 3  O  O 0.0  1.0 2.0  8.0\nsymfunction  O 3  O  O 0.0 -1.0 1.0  8.0\n\nsymfunction  O 3  O Al 0.0  1.0 1.0  8.0\nsymfunction  O 3  O Al 0.0  1.0 2.0  8.0\nsymfunction  O 3  O Al 0.0 -1.0 1.0  8.0\nsymfunction  O 3  O Al 0.0 -1.0 2.0  8.0\n\n#symfunction  O 3  O Au 0.0  1.0 1.0  8.0\n\n\n\n\nsymfunction Al 3 Mg Mg 0.0  1.0 1.0  8.0\n#symfunction Al 3 Mg Mg 0.0  1.0 2.0  8.0\n#symfunction Al 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Al 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Al 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Al 3 Mg  O 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg  O 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3 Mg Al 0.0  1.0 1.0  8.0\n#symfunction Al 3 Mg Al 0.0  1.0 2.0  8.0\n#symfunction Al 3 Mg Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg Al 0.0 -1.0 2.0  8.0\n\nsymfunction Al 3  O  O 0.0  1.0 1.0  8.0\nsymfunction Al 3  O  O 0.0  1.0 2.0  8.0\nsymfunction Al 3  O  O 0.0 -1.0 1.0  8.0\nsymfunction Al 3  O  O 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3  O Al 0.0  1.0 1.0  8.0\n#symfunction Al 3  O Al 0.0  1.0 2.0  8.0\n#symfunction Al 3  O Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3  O Al 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3 Al Al 0.0  1.0 1.0  8.0\n#symfunction Al 3 Al Al 0.0  1.0 2.0  8.0\n#symfunction Al 3 Al Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Al Al 0.0 -1.0 2.0  8.0\n\n\n\nsymfunction Au 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction Au 3 Mg Mg 0.0  1.0 2.0  8.0\n#symfunction Au 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Au 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Au 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Au 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction Au 3 Mg  O 0.0 -1.0 2.0  8.0\n\n#symfunction Au 3 Mg Au 0.0  1.0 1.0  8.0\n#symfunction Au 3 Mg Au 0.0  1.0 2.0  8.0\n#symfunction Au 3 Mg Au 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction Au 3  O  O 0.0  1.0 1.0  8.0\n#symfunction Au 3  O  O 0.0  1.0 2.0  8.0\n#symfunction Au 3  O  O 0.0 -1.0 1.0  8.0\n#symfunction Au 3  O  O 0.0 -1.0 2.0  8.0\n\n#symfunction Au 3  O Au 0.0  1.0 1.0  8.0\n#symfunction Au 3  O Au 0.0  1.0 2.0  8.0\nsymfunction Au 3  O Au 0.0  1.0 -1.0  8.0\nsymfunction Au 3  O Au 0.0  1.0 -2.0  8.0\n\n#symfunction Au 3 Au Au 0.0  1.0 1.0  8.0\n#symfunction Au 3 Au Au 0.0  1.0 2.0  8.0\n#symfunction Au 3 Au Au 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Au Au 0.0 -1.0 2.0  8.0\n\n\n\n\n########################################################################################################################\n### fitting (mode 2):general inputs for short range AND short part:\n########################################################################################################################\npoints_in_memory 1000\nmix_all_points                       \nscale_symmetry_functions             \ncenter_symmetry_functions             \nfitting_unit  eV                      \n########################################################################################################################\n### fitting options ( mode 2): short range part only:\n########################################################################################################################\noptmode_short_energy 1                 \noptmode_short_force 1                   \nshort_energy_error_threshold 0.8\t \nshort_force_error_threshold 0.8\t\t \nkalman_lambda_short 0.98000                \nkalman_lambda_charge 0.98000                \nkalman_nue_short 0.99870                   \nkalman_nue_charge 0.99870                   \n#use_old_weights_short               \n#force_update_scaling -1.0d0          \n#short_energy_group 1         \n#short_energy_fraction 1.00           \n#short_force_group 1                  \nshort_force_fraction 0.025\nweights_min -1.0                 \nweights_max 1.0                  \nrepeated_energy_update\nnguyen_widrow_weights_short\n\n\n########################################################################################################################\n### output options for mode 2 (fitting):  \n########################################################################################################################\n#write_trainpoints              \n#write_trainforces      \n########################################################################################################################\n### output options for mode 3 (prediction):  \n########################################################################################################################\ncalculate_forces     \n#calculate_stress       \n\n"
  },
  {
    "path": "examples/interface-LAMMPS/AlAuMgO_4G/nnp-predict/scaling.data",
    "content": "   1    1        0.157132975       0.280279850       0.234169887\n   1    2        0.379295480       0.622179554       0.545652438\n   1    3        0.000000000       0.205184943       0.016565410\n   1    4        0.000000000       0.167300348       0.001157152\n   1    5        0.151966913       0.271484679       0.226693585\n   1    6        0.146970813       0.262965553       0.219456059\n   1    7        0.142139079       0.254713806       0.212449681\n   1    8        0.000000000       0.195870161       0.015737764\n   1    9        0.137466301       0.246721045       0.205667064\n   1   10        0.353782761       0.582354440       0.509841176\n   1   11        0.000000000       0.161223776       0.001045601\n   1   12        0.132947244       0.238979140       0.199101062\n   1   13        0.000000000       0.189896965       0.015211084\n   1   14        0.335850555       0.554313578       0.484647540\n   1   15        0.000000000       0.181277733       0.014456530\n   1   16        0.000000000       0.155367918       0.000947149\n   1   17        0.318878593       0.527730187       0.460782520\n   1   18        0.000000000       0.173050590       0.013742142\n   1   19        0.000000000       0.148346286       0.000839806\n   1   20        0.297643309       0.494532513       0.430890275\n   1   21        0.000000000       0.165197661       0.013065428\n   1   22        0.277886581       0.463747515       0.403042058\n   1   23        0.000000000       0.141641990       0.000747240\n   1   24        0.000000000       0.133995570       0.000652336\n   1   25        0.000045839       0.000152977       0.000106156\n   1   26        0.000680557       0.001734569       0.001348253\n   1   27        0.000000000       0.000580779       0.000043631\n   1   28        0.000687759       0.003088959       0.002094644\n   1   29        0.000000000       0.001975434       0.000139623\n   1   30        0.000000000       0.002858460       0.000006888\n   1   31        0.000141138       0.000459099       0.000318440\n   1   32        0.003883787       0.009565828       0.007507740\n   1   33        0.000000000       0.003170549       0.000242247\n   1   34        0.000723568       0.003193167       0.002190205\n   1   35        0.000000000       0.002015297       0.000146458\n   1   36        0.000000000       0.002849448       0.000008773\n   1   37        0.000108434       0.000298716       0.000226841\n   1   38        0.000000000       0.000100115       0.000007401\n   1   39        0.000337708       0.001533218       0.001037438\n   1   40        0.000000000       0.000985795       0.000069101\n   1   41        0.000000000       0.001452136       0.000003254\n   1   42        0.000106418       0.000344381       0.000238835\n   1   43        0.003311665       0.008129974       0.006386328\n   1   44        0.000000000       0.002695024       0.000206016\n   1   45        0.000376278       0.001638804       0.001133000\n   1   46        0.000000000       0.001025445       0.000075936\n   1   47        0.000000000       0.001443125       0.000005139\n   1   48        0.000083248       0.000381693       0.000258183\n   1   49        0.000000000       0.000247525       0.000017187\n   1   50        0.002416132       0.005909800       0.004645819\n   1   51        0.000108377       0.000463908       0.000321719\n   1   52        0.000000000       0.000274278       0.000021729\n   1   53        0.001290479       0.003153152       0.002478974\n   2    1        0.465366967       0.622899345       0.561220975\n   2    2        0.119958755       0.278325877       0.225814452\n   2    3        0.000000000       0.052290984       0.007517999\n   2    4        0.000000000       0.082321041       0.001283464\n   2    5        0.116028951       0.269574643       0.218604882\n   2    6        0.000000000       0.050704245       0.007277988\n   2    7        0.000000000       0.080774026       0.001244257\n   2    8        0.112227916       0.261098625       0.211625571\n   2    9        0.000000000       0.049165662       0.007045642\n   2   10        0.000000000       0.079257371       0.001206277\n   2   11        0.108551431       0.252889168       0.204869161\n   2   12        0.000000000       0.047673774       0.006820716\n   2   13        0.000000000       0.077770417       0.001169485\n   2   14        0.434143302       0.583124772       0.524387947\n   2   15        0.104995412       0.244937885       0.198328532\n   2   16        0.000000000       0.046227162       0.006602973\n   2   17        0.000000000       0.076312525       0.001133843\n   2   18        0.101555912       0.237236656       0.191996789\n   2   19        0.000000000       0.044824453       0.006392183\n   2   20        0.000000000       0.074883070       0.001099315\n   2   21        0.412169183       0.555114045       0.498475487\n   2   22        0.391351992       0.528554985       0.473929551\n   2   23        0.365280511       0.495248302       0.443184422\n   2   24        0.341001583       0.464173404       0.414541640\n   2   25        0.001304697       0.003073521       0.002226260\n   2   26        0.000658301       0.001747757       0.001341772\n   2   27        0.000000000       0.000344142       0.000044915\n   2   28        0.000000000       0.000536511       0.000003397\n   2   29        0.000015937       0.000150219       0.000098274\n   2   30        0.001379442       0.003196463       0.002328076\n   2   31        0.003777691       0.009615500       0.007472434\n   2   32        0.000000000       0.001853922       0.000249329\n   2   33        0.000000000       0.001669339       0.000012712\n   2   34        0.000048632       0.000451042       0.000294796\n   2   35        0.000640789       0.001524318       0.001102595\n   2   36        0.000104063       0.000302504       0.000225688\n   2   37        0.000000000       0.000263424       0.000001016\n   2   38        0.000709709       0.001647260       0.001204412\n   2   39        0.003223454       0.008170246       0.006356350\n   2   40        0.000000000       0.001575067       0.000212033\n   2   41        0.000000000       0.001450386       0.000010331\n   2   42        0.000036630       0.000338360       0.000221102\n   2   43        0.000156394       0.000379666       0.000274392\n   2   44        0.000197865       0.000461980       0.000342083\n   2   45        0.002354467       0.005937258       0.004624037\n   2   46        0.000000000       0.001144834       0.000154222\n   2   47        0.000000000       0.001123811       0.000007188\n   2   48        0.000020441       0.000190427       0.000124392\n   2   49        0.001262549       0.003166018       0.002467335\n   2   50        0.000000000       0.000611201       0.000082309\n   2   51        0.000000000       0.000698347       0.000003778\n   3    1        0.577136243       0.616694005       0.597156670\n   3    2        0.250892044       0.277137801       0.263493918\n   3    3        0.242773609       0.268416021       0.255081906\n   3    4        0.234917966       0.259968821       0.246938538\n   3    5        0.547624822       0.586625275       0.567321361\n   3    6        0.227316605       0.251787552       0.239055233\n   3    7        0.219961293       0.243863841       0.231423681\n   3    8        0.528861449       0.567471623       0.548335377\n   3    9        0.212844062       0.236189575       0.224035841\n   3   10        0.502003814       0.540003438       0.521134901\n   3   11        0.476603541       0.513965831       0.495382352\n   3   12        0.452569426       0.489271173       0.470987896\n   3   13        0.002144387       0.002924649       0.002514975\n   3   14        0.001446412       0.001705750       0.001573953\n   3   15        0.002255498       0.003054915       0.002637746\n   3   16        0.008084071       0.009374504       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-0.2023173027\n     -0.0346307314\n      0.1454586515\n      0.0499358161\n     -0.3025620612\n     -0.0615975991\n     -0.1344299547\n     -0.2200005758\n      0.0613286471\n     -0.0095641876\n      0.1077087090\n      0.0238586352\n      0.0900418907\n      0.1739544847\n     -0.0403015175\n      0.0633257879\n      0.0598231882\n     -0.0043880669\n      0.4304185740\n     -0.2331181875\n      0.1449090428\n     -0.2454187095\n     -0.1682876393\n      0.1509626947\n     -0.3338329016\n      0.1650067521\n      0.1653432182\n     -0.3073306576\n      0.3124937274\n     -0.1521119233\n      0.0447478080\n     -0.1095822516\n     -0.0238035401\n     -0.0025984171\n     -0.1025755475\n     -0.0615939344\n     -0.1482717020\n     -0.0578191435\n      0.0915471638\n     -0.0423972689\n      0.0441757511\n      0.1113012611\n     -0.1172166503\n      0.2325309272\n     -0.0895939091\n      0.1005929196\n     -0.1384167043\n      0.2122254593\n      0.0714664070\n     -0.2705822901\n      0.0118268280\n     -0.2193245726\n      0.2431070294\n      0.1141446596\n     -0.1867606865\n      0.1935099930\n      0.2209813140\n     -0.2529433949\n      0.1440143975\n     -0.0722829562\n     -0.0598002212\n      0.0208649888\n      0.0577711911\n      0.0328625300\n     -0.4509728043\n     -0.1559953040\n     -0.1223170768\n     -0.2639953341\n      0.0548075896\n      0.0576850840\n      0.0786432581\n     -0.0760044592\n      0.2492190636\n      0.0083271687\n      0.0283693425\n      0.0978297844\n     -0.1222856258\n     -0.0651284791\n     -0.0178319910\n     -0.0658492086\n     -0.0677102135\n     -0.1473605241\n     -0.0197504678\n      0.0986096003\n     -0.0466665163\n      0.0264603481\n      0.1290190457\n     -0.1591221726\n      0.2329792336\n     -0.0948194226\n      0.1127973166\n     -0.2122030043\n     -0.0036133367\n      0.2592597572\n     -0.2275641658\n     -0.0352099798\n     -0.0510248230\n      0.2101184628\n      0.0068438583\n     -0.1914768435\n      0.1580744693\n      0.3367138970\n     -0.2758308964\n      0.1194249955\n     -0.1189355850\n     -0.0268126611\n      0.9203075660\n      0.7456691833\n      0.2222706793\n     -0.1988471649\n      0.3739655052\n     -0.3294855879\n      0.5728060471\n      0.0393707195\n      0.6439223591\n      0.5441672350\n     -0.0135455178\n      0.6243344121\n     -0.1346168015\n      0.4979660549\n     -0.7870518947\n     -0.5332850238\n     -0.3587958597\n     -0.1479196713\n     -0.6215149074\n     -0.7771744116\n     -0.5163484113\n     -0.1940326928\n      0.3175103040\n      0.4954133086\n     -0.2761520547\n      0.3831963000\n      0.4605532208\n      0.3860955709\n      0.0378062514\n     -0.1707804695\n     -0.0435508038\n     -0.0810929828\n     -0.4526255338\n      0.2463436433\n     -0.3273868010\n      0.3637041064\n      0.0724031602\n     -0.1624640494\n      0.1892663892\n     -0.1521606342\n      0.2815898854\n      0.1367806931\n     -0.2829098452\n     -0.0888158292\n     -0.4768318121\n     -0.0812336748\n      0.0034283591\n      1.0013113650\n      0.4150497899\n     -0.1063706595\n      0.2857364395\n      0.0628422180\n     -0.5849189818\n      0.3915753066\n     -0.3741713347\n     -0.1918341851\n     -0.1663933130\n      0.2835631780\n     -0.2939765787\n     -0.2276334491\n      0.1039590962\n     -0.3242652545\n      0.0186193017\n     -0.1433616691\n     -0.1613015297\n      0.0605507977\n     -0.3616662631\n      0.0177685095\n     -0.7604765543\n      0.0476406693\n      0.3468828079\n      0.2581321661\n     -0.1937871932\n      0.2621700413\n      0.4630765087\n      0.8510017645\n      0.3689454032\n     -0.4602175172\n     -0.0066761804\n      0.7722044785\n     -0.0305925950\n     -0.7111077469\n     -0.2776830879\n     -0.5123830560\n      1.0439249658\n      0.2048119234\n     -0.2821199655\n      0.2264540283\n     -0.3373758126\n     -0.3064677507\n      0.7312395462\n     -0.0528935699\n      0.6398342791\n      0.3253160435\n     -0.3344819542\n     -0.2014156839\n     -0.7466067836\n      0.0710261411\n     -1.2018333087\n      0.6152880326\n      0.3473916962\n      0.5407951540\n      0.0516084216\n      0.1278888061\n      0.6017158483\n     -0.1417335912\n      0.2143850072\n     -0.1118223674\n     -0.4201007154\n     -0.4666319341\n      0.5337375625\n      0.3218953867\n      0.0944373628\n     -0.9002175948\n      0.2591672154\n     -0.3000104463\n      0.4861039688\n      0.0952490403\n     -0.3920374309\n      0.0247337474\n     -0.5106625667\n     -0.1015746734\n      0.4126996028\n      0.1906749269\n      0.7667360527\n     -0.2519091950\n     -0.2538368872\n     -0.3091588395\n      0.1743960227\n     -0.0738386990\n      0.0954615004\n     -0.6309371822\n      0.2845880292\n     -0.0026901912\n     -0.1206545296\n      0.0758079075\n      0.0010136892\n      0.1490356550\n      0.0021429510\n      0.1603305471\n     -0.2690907146\n      0.0072183932\n      0.2317995676\n      0.3841513421\n     -0.1435027077\n      0.1843797288\n      0.8279229355\n      0.1612532146\n      0.1261892740\n      0.0960014594\n     -0.2441902221\n     -0.0871481995\n      0.5670319559\n      0.1439771996\n      0.0873918284\n      0.5928485078\n      0.5222145033\n     -0.2947982040\n      0.1572202719\n      0.1069671383\n     -0.7922665695\n     -0.1772334153\n     -0.3776175949\n      0.2032090117\n     -0.1847832635\n     -0.1930693654\n     -0.2188837767\n      0.3509390016\n     -0.2170035072\n     -0.4627849794\n      0.4561667716\n     -0.3401245781\n     -0.0231144919\n      0.1302318702\n     -0.4121202672\n     -0.5001609206\n      0.0843134021\n     -0.0926861702\n      0.3255728108\n     -0.1711697918\n     -0.8780680929\n     -0.3413916248\n      0.3916863656\n     -0.6500525270\n     -0.4044179063\n      0.2977145371\n     -0.3145119048\n      0.5759574510\n      0.8617288100\n     -0.4371884938\n      0.3023348726\n     -0.3238457119\n      0.2568039620\n      0.0640803265\n      0.6770661325\n     -0.2782708301\n     -0.2097110502\n     -0.1415992491\n     -0.0746808521\n      0.4398888003\n     -0.4949939471\n     -0.2431396059\n     -0.4795168393\n     -0.0108472702\n      0.5038791106\n      0.5240696579\n     -0.9252031009\n      0.3309561660\n      0.1440836156\n     -0.3944453019\n      0.2948833127\n      0.0129818495\n      0.4223860733\n      0.0957712177\n      0.5006578292\n     -0.2747709559\n     -0.5699756136\n     -0.7476578080\n      0.3753346881\n      0.4670965348\n      0.3435678002\n      0.0800265005\n     -0.0211998040\n      0.0347383614\n      0.2070381583\n      0.0176409642\n     -0.0088772683\n     -0.6111740774\n     -0.0290809661\n     -0.3306605622\n      0.4799933221\n      0.1060321019\n     -0.1373112089\n     -0.5419840819\n     -0.3688590619\n     -0.1731587211\n     -0.6552664178\n      0.1983996951\n     -0.1075821292\n     -0.0350305109\n     -0.0159929994\n     -0.1398821349\n      0.0720797163\n      0.0554322662\n      0.2405258084\n     -0.2998280663\n      0.2220944588\n     -0.2774169468\n      0.4108718462\n      0.0168266678\n      0.1893295294\n      0.2570022134\n     -0.4562349824\n      0.0733776332\n     -0.5885666954\n     -0.0412252054\n      0.0377403884\n     -1.0664772437\n     -0.1060277409\n     -0.2698892553\n      0.2826469476\n     -0.2529006758\n     -0.6399482527\n      1.3647214921\n     -0.2285785734\n      0.1962570917\n      0.2684972608\n     -0.1470008551\n     -0.0341685014\n      0.2593568604\n      0.2522317733\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE/cu2s_144_low-chalcocite_Evans-1979_PBE.data",
    "content": "Generated by sg2cfg\n\n144 atoms\n2 atom types\n\n  0.0000000000000000E+00   1.5246000000000000E+01 xlo xhi\n  0.0000000000000000E+00   1.1884000000000000E+01 ylo yhi\n  0.0000000000000000E+00   1.2091965796411374E+01 zlo zhi\n  0.0000000000000000E+00  -5.9893571590294590E+00   0.0000000000000000E+00 xy xz yz\n\nAtoms\n\n1 1   9.5538084006653907E+00   9.8518360000000005E-01   1.0183853593737659E+01\n2 1  -3.2918441392095787E+00   6.9271836000000002E+00   7.9540951008794023E+00\n3 1  -2.9716555969484926E-01   1.0898816400000001E+01   1.9081122026737154E+00\n4 1   1.2548486980180119E+01   4.9568164000000001E+00   4.1378706955319728E+00\n5 1   1.2277544351544003E+01   9.1269119999999992E-01   4.1862385587176183E+00\n6 1  -2.6222931058731080E-02   6.8546911999999995E+00   1.8597443394880693E+00\n7 1  -3.0209015105734602E+00   1.0971308800000001E+01   7.9057272376937560E+00\n8 1   9.2828657720292718E+00   5.0293088000000008E+00   1.0232221456923305E+01\n9 1   9.0699177918038707E+00   9.7924160000000005E-01   6.1282082656212848E+00\n10 1  -2.8079535303480587E+00   6.9212416000000001E+00   1.2009740428995777E+01\n11 1   1.8672504916667076E-01   1.0904758400000000E+01   5.9637575307900894E+00\n12 1   1.2064596371318601E+01   4.9627584000000002E+00   8.2225367415599035E-02\n13 1   1.2034322057045824E+01   9.7092279999999997E-01   7.2551794778468251E-02\n14 1   2.1699936343944826E-01   6.9129228000000005E+00   5.9734311034272185E+00\n15 1  -2.7776792160752812E+00   1.0913077200000000E+01   1.2019414001632907E+01\n16 1   9.0396434775310937E+00   4.9710771999999999E+00   6.1185346929841558E+00\n17 1   3.1737058543672330E+00   1.0493572000000000E+00   7.4160026229390956E+00\n18 1   3.0882584070885768E+00   6.9913572000000004E+00   1.0721946071677966E+01\n19 1   6.0829369866033067E+00   1.0834642799999999E+01   4.6759631734722786E+00\n20 1   6.1683844338819629E+00   4.8926428000000000E+00   1.3700197247334083E+00\n21 1   6.2021409198808808E+00   8.6277839999999995E-01   1.1572011267165685E+00\n22 1   6.0491805006043897E+00   6.8047784000000000E+00   4.8887817714891186E+00\n23 1   3.0545019210896607E+00   1.1021221600000001E+01   1.0934764669694806E+01\n24 1   3.2074623403661517E+00   5.0792216000000003E+00   7.2031840249222556E+00\n25 1  -1.4015081272437779E-01   9.2814040000000009E-01   9.5139586886164693E+00\n26 1   6.4021150741801902E+00   6.8701404000000013E+00   8.6239900060005912E+00\n27 1   9.3967936536949193E+00   1.0955859600000000E+01   2.5780071077949045E+00\n28 1   2.8545277667903521E+00   5.0138596000000000E+00   3.4679757904107813E+00\n29 1   2.6160912310744484E+00   9.8874879999999998E-01   3.4691849869904230E+00\n30 1   9.6352301894108230E+00   6.9307487999999999E+00   2.5767979112152641E+00\n31 1   6.6405516098960931E+00   1.0895251200000001E+01   8.6227808094209522E+00\n32 1  -3.7858734844028064E-01   4.9532512000000004E+00   9.5151678851961101E+00\n33 1   6.2869001311807295E+00   2.9484203999999998E+00   8.7303993050090121E+00\n34 1  -2.4935869724918902E-02   8.8904204000000000E+00   9.4075493896080502E+00\n35 1   2.9697427097898110E+00   8.9355796000000005E+00   3.3615664914023622E+00\n36 1   9.2815787106954595E+00   2.9935796000000003E+00   2.6844164068033249E+00\n37 1   5.8575182718324248E+00   2.6584508000000002E+00   5.0387221473646200E+00\n38 1   6.3938031486528448E+00   8.6004508000000008E+00   1.0072607508410674E+00\n39 1   3.3991245691381162E+00   9.2255491999999997E+00   7.0532436490467534E+00\n40 1   2.8628396923176949E+00   3.2835491999999999E+00   1.1084705045570308E+01\n41 1   1.4893437800655995E-01   2.8331455999999999E+00   5.7630308985696610E+00\n42 1   1.2102387042478711E+01   8.7751456000000001E+00   2.8295199963602585E-01\n43 1   9.1077084629639806E+00   9.0508544000000004E+00   6.3289348978417133E+00\n44 1  -2.8457442015081695E+00   3.1088544000000002E+00   1.1809013796775348E+01\n45 1  -6.1400573582723883E-02   2.7618415999999999E+00   1.6106498440819952E+00\n46 1   1.2312721994067994E+01   8.7038415999999987E+00   4.4353330541236922E+00\n47 1   9.3180434145532658E+00   9.1221584000000018E+00   1.0481315952329380E+01\n48 1  -3.0560791530974529E+00   3.1801584000000003E+00   7.6566327422876821E+00\n49 2   1.1427082159552079E+01   2.9662463999999997E+00   3.5393183886096096E+00\n50 2   8.2423926093319233E-01   8.9082464000000012E+00   2.5066645095960776E+00\n51 2  -2.1704393185815376E+00   8.9177535999999993E+00   8.5526474078017660E+00\n52 2   8.4324035800373487E+00   2.9757536000000004E+00   9.5853012868152963E+00\n53 2   5.3565064819165702E+00   8.7941599999999998E-01   8.1802148612722938E+00\n54 2   9.0545777953924045E-01   6.8214159999999993E+00   9.9577338333447667E+00\n55 2   3.9001363590539699E+00   1.1004584000000001E+01   3.9117509351390796E+00\n56 2   8.3511850614313001E+00   5.0625840000000002E+00   2.1342319630666062E+00\n57 2   8.2986940044307591E+00   1.0885743999999999E+00   2.0278226640581871E+00\n58 2   3.9526274160545114E+00   7.0305744000000008E+00   4.0181602341475005E+00\n59 2   9.5794883653978147E-01   1.0795425600000000E+01   1.0064143132353188E+01\n60 2   5.3040154249160301E+00   4.8534255999999996E+00   8.0738055622638747E+00\n61 2   5.0934267916749469E+00   2.8521600000000000E+00   8.8392269971767146E-01\n62 2   7.1578946288103236E+00   8.7941599999999998E+00   5.1620601984880157E+00\n63 2   4.1632160492955945E+00   9.0318400000000008E+00   1.1208043096693704E+01\n64 2   2.0987482121602175E+00   3.0898400000000001E+00   6.9299055979233577E+00\n65 2  -3.7151518509987418E+00   1.0089516000000001E+00   1.1428116874188390E+01\n66 2   9.9771161124545564E+00   6.9509515999999998E+00   6.7098318204286711E+00\n67 2   1.2971794691969285E+01   1.0875048400000001E+01   6.6384892222298386E-01\n68 2  -7.2047327148401274E-01   4.9330484000000006E+00   5.3821339759827032E+00\n69 2  -1.0289872857341475E+00   9.3051719999999993E-01   5.3555316512305975E+00\n70 2   1.3280308706219419E+01   6.8725172000000008E+00   6.9045124697508931E-01\n71 2   1.0285630126704689E+01   1.0953482800000000E+01   6.7364341451807759E+00\n72 2  -4.0236658652488773E+00   5.0114828000000005E+00   1.1401514549436286E+01\n73 2   8.3041478910950666E+00   1.4652972000000002E+00   1.1998857659779006E+01\n74 2  -2.0421836296392564E+00   7.4072971999999995E+00   6.1390910348380556E+00\n75 2   9.5249494987547301E-01   1.0418702800000000E+01   9.3108136632368069E-02\n76 2   1.1298826470609797E+01   4.4767028000000000E+00   5.9528747615733186E+00\n77 2   1.1298611184610881E+01   1.6780207999999999E+00   6.1656933595901604E+00\n78 2  -5.0366469231550672E+00   7.6200207999999998E+00   1.1972255335026901E+01\n79 2  -2.0419683436403382E+00   1.0205979200000000E+01   5.9262724368212139E+00\n80 2   1.4293289764125610E+01   4.2639792000000005E+00   1.1971046138447285E-01\n81 2   9.1488021433547946E+00   2.9757536000000004E+00   4.9685887457454339E+00\n82 2   3.1025192771304759E+00   8.9177535999999993E+00   1.0773941524602535E+00\n83 2   1.0784069761574688E-01   8.9082464000000012E+00   7.1233770506659404E+00\n84 2   6.1541235638400646E+00   2.9662463999999997E+00   1.1014571643951122E+01\n85 2   1.1536023277392626E+00   1.7552668000000000E+00   1.1303569626485352E+01\n86 2   5.1083619337165480E+00   7.6972667999999995E+00   6.8343790681317094E+00\n87 2   8.1030405132312779E+00   1.0128733200000001E+01   7.8839616992602202E-01\n88 2   4.1482809072539908E+00   4.1867331999999999E+00   5.2575867282796667E+00\n89 2   3.8575184786178740E+00   1.4605436000000001E+00   5.3059545914653112E+00\n90 2   8.3938029418673974E+00   7.4025436000000004E+00   7.4002830674037579E-01\n91 2   5.3991243623526675E+00   1.0423456400000001E+01   6.7860112049460621E+00\n92 2   8.6283989910314407E-01   4.4814563999999999E+00   1.1351937489670998E+01\n93 2  -1.1647273351863610E+00   2.8010587999999998E+00   1.0286635303007156E+01\n94 2   7.4266915966421729E+00   8.7430588000000000E+00   7.8513133916099056E+00\n95 2   1.0421370176156902E+01   9.0829412000000005E+00   1.8053304934042180E+00\n96 2   1.8299512443283681E+00   3.1409411999999999E+00   4.2406524048014687E+00\n97 2   8.4247104603828795E+00   4.2544719999999997E-01   8.2588126389489691E+00\n98 2  -2.1627461989270667E+00   6.3674472000000009E+00   9.8791360556680914E+00\n99 2   8.3193238058766239E-01   1.1458552800000000E+01   3.8331531574624051E+00\n100 2   1.1419389039897609E+01   5.5165528000000004E+00   2.2128297407432820E+00\n101 2   1.0936796418726178E+01   7.4156159999999993E-01   2.0205674845803405E+00\n102 2   1.3145250017590928E+00   6.6835616000000000E+00   4.0254154136253462E+00\n103 2  -1.6801535777556365E+00   1.1142438400000000E+01   1.0071398311831034E+01\n104 2   7.9421178392114484E+00   5.2004384000000003E+00   8.0665503827860281E+00\n105 2  -4.2270609982025480E+00   2.4302779999999999E+00   9.3374159879888623E+00\n106 2   1.0489025259658359E+01   8.3722779999999997E+00   8.8005327066281982E+00\n107 2   1.3483703839173089E+01   9.4537220000000008E+00   2.7545498084225111E+00\n108 2  -1.2323824186878187E+00   3.5117219999999998E+00   3.2914330897831761E+00\n109 2   5.9652557811310523E+00   9.4477800000000001E-01   3.4268631067029833E+00\n110 2   6.2860656393542182E+00   6.8867780000000005E+00   2.6191197915027038E+00\n111 2   3.2913870598394892E+00   1.0939222000000001E+01   8.6651026897083909E+00\n112 2   2.9705772016163232E+00   4.9972219999999998E+00   9.4728460049086696E+00\n113 2   8.7597168992464747E-01   5.1576560000000005E-01   7.5332946911642864E+00\n114 2   5.3859925715311645E+00   6.4577656000000001E+00   1.0604654003452776E+01\n115 2   8.3806711510458936E+00   1.1368234400000000E+01   4.5586711052470879E+00\n116 2   3.8706502694393770E+00   5.4262344000000002E+00   1.4873117929585991E+00\n117 2   3.8480550764059558E+00   5.1220040000000000E-01   1.6191142201394828E+00\n118 2   8.4032663440793165E+00   6.4542004000000004E+00   4.4268686780662039E+00\n119 2   5.4085877645645866E+00   1.1371799599999999E+01   1.0472851576271891E+01\n120 2   8.5337649689122586E-01   5.4297995999999999E+00   7.6650971183451704E+00\n121 2   3.4757056949440797E+00   2.4742487999999998E+00   9.1209698002330999E+00\n122 2   2.7862585665117328E+00   8.4162488000000000E+00   9.0169788943839624E+00\n123 2   5.7809371460264618E+00   9.4097512000000005E+00   2.9709959961782748E+00\n124 2   6.4703842744588087E+00   3.4677512000000004E+00   3.0749869020274123E+00\n125 2   1.3936508439354220E+01   1.0172703999999999E+00   2.6191197915027034E+00\n126 2  -1.6851870188689482E+00   6.9592704000000003E+00   3.4268631067029833E+00\n127 2  -4.6798655983836772E+00   1.0866729599999999E+01   9.4728460049086696E+00\n128 2   1.0941829859839491E+01   4.9247296000000000E+00   8.6651026897083909E+00\n129 2   3.7852278917290239E+00   1.2264288000000001E+00   1.1524852600559679E+01\n130 2   2.4767363697267886E+00   7.1684288000000000E+00   6.6130960940573811E+00\n131 2   5.4714149492415176E+00   1.0657571200000001E+01   5.6711319585169406E-01\n132 2   6.7799064712437520E+00   4.7155712000000003E+00   5.4788697023539941E+00\n133 2   7.3392329837052301E+00   2.3102496000000001E+00   6.8428434441891959E+00\n134 2  -1.0772687222494177E+00   8.2522496000000007E+00   1.1295105250427865E+01\n135 2   1.9174098572653118E+00   9.5737503999999998E+00   5.2491223522221784E+00\n136 2   1.0333911563219958E+01   3.6317504000000000E+00   7.9686054598351042E-01\n137 2   2.2545766691676814E+00   2.4587995999999999E+00   1.6904568183383102E+00\n138 2   9.9967447513175891E+00   8.4007995999999991E+00   4.3555260798673769E+00\n139 2   7.0020661718028601E+00   9.4252004000000014E+00   1.0401508978073064E+01\n140 2  -7.4010191034704809E-01   3.4832004000000003E+00   7.7364397165439973E+00\n141 2  -2.0731956466969059E+00   1.1479944000000002E+00   8.2116539723429653E+00\n142 2   8.3351599081527183E+00   7.0899944000000001E+00   9.9262947222740969E+00\n143 2   1.1329838487667448E+01   1.0736005600000000E+01   3.8803118240684094E+00\n144 2   9.2148293281782356E-01   4.7940056000000002E+00   2.1656710741372778E+00\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE/hdnnp-data/input.nn",
    "content": "###############################################################################\n# HDNNP for copper sulfide Cu2S\n###############################################################################\n# Length unit     : Angstrom\n# Energy unit     : eV\n# Reference method: PBE\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.8640662064628053E+00\nconv_energy   7.3890846653659121E+00\nconv_length   6.1376931796181502E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type.\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          40             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   2              # Training parallelization used (0 = Serial, 1-4 = MSEKF implementations (4-fastest)).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2 10 1 15 2    # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 3\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.02315        # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               1              # Write energy comparison.\nwrite_trainforces               5              # Write force comparison.\nwrite_weights_epoch             1              # Write weights.\nwrite_neuronstats               5              # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE/hdnnp-data/nnp-train.log.0000",
    "content": "\n*** SETUP: MPI ****************************************************************\n\nNumber of processors: 16\nProcess 1 of 16 (rank 0): n51-048.vsc3plus.xcat\nProcess 2 of 16 (rank 1): n51-048.vsc3plus.xcat\nProcess 3 of 16 (rank 2): n51-048.vsc3plus.xcat\nProcess 4 of 16 (rank 3): n51-048.vsc3plus.xcat\nProcess 5 of 16 (rank 4): n51-048.vsc3plus.xcat\nProcess 6 of 16 (rank 5): n51-048.vsc3plus.xcat\nProcess 7 of 16 (rank 6): n51-048.vsc3plus.xcat\nProcess 8 of 16 (rank 7): n51-048.vsc3plus.xcat\nProcess 9 of 16 (rank 8): n51-048.vsc3plus.xcat\nProcess 10 of 16 (rank 9): n51-048.vsc3plus.xcat\nProcess 11 of 16 (rank 10): n51-048.vsc3plus.xcat\nProcess 12 of 16 (rank 11): n51-048.vsc3plus.xcat\nProcess 13 of 16 (rank 12): n51-048.vsc3plus.xcat\nProcess 14 of 16 (rank 13): n51-048.vsc3plus.xcat\nProcess 15 of 16 (rank 14): n51-048.vsc3plus.xcat\nProcess 16 of 16 (rank 15): n51-048.vsc3plus.xcat\n*******************************************************************************\n\n*******************************************************************************\n\n   NNP LIBRARY v0.1.0\n   ------------------\n\nGit branch  : master\nGit revision: 7f7427e (7f7427e692ba496c08cde43f02c65ec58de915fa)\n\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 321 lines.\nFound 182 lines with keywords.\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is used.\nMean energy per atom     :  -3.8640662064628053E+00\nConversion factor energy :   7.3890846653659121E+00\nConversion factor length :   6.1376931796181502E+00\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  S ( 16)\nElement  1: Cu ( 29)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:   0.00000000E+00\nElement  1:   0.00000000E+00\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_POLY2 (6)\nx := (r - rc * alpha) / (rc - rc * alpha)\nf(x) = ((15 - 6x)x - 10)x^3 + 1\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  S :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  S  2  S    5.309E-02 9.207E+00         3.683E+01  6 0.00   105\n   2  S  2 Cu    5.309E-02 9.207E+00         3.683E+01  6 0.00   115\n   3  S  2  S    5.309E-02 1.228E+01         3.683E+01  6 0.00   106\n   4  S  2 Cu    5.309E-02 1.228E+01         3.683E+01  6 0.00   116\n   5  S  2  S    5.309E-02 1.534E+01         3.683E+01  6 0.00   107\n   6  S  2 Cu    5.309E-02 1.534E+01         3.683E+01  6 0.00   117\n   7  S  2 Cu    5.309E-02 1.841E+01         3.683E+01  6 0.00   118\n   8  S  3  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   163\n   9  S  3  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   176\n  10  S  3 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   189\n  11  S  3  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   164\n  12  S  3  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   177\n  13  S  3 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   190\n  14  S  3  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   165\n  15  S  3  S Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   178\n  16  S  3 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   191\n  17  S  3  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   166\n  18  S  3  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   179\n  19  S  3 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   192\n  20  S  3  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   159\n  21  S  3  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   172\n  22  S  3 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   185\n  23  S  3  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   160\n  24  S  3  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   173\n  25  S  3 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   186\n  26  S  3  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   161\n  27  S  3  S Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   174\n  28  S  3 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   187\n  29  S  3  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   162\n  30  S  3  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   175\n  31  S  3 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   188\n  32  S  3  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   155\n  33  S  3  S Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   168\n  34  S  3  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   156\n  35  S  3  S Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   169\n  36  S  3 Cu Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   182\n  37  S  3  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   158\n  38  S  3  S Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   171\n  39  S  9  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   251\n  40  S  9  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   264\n  41  S  9 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   277\n  42  S  9  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   252\n  43  S  9  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   265\n  44  S  9 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   278\n  45  S  9  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   253\n  46  S  9  S Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   266\n  47  S  9 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   279\n  48  S  9  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   254\n  49  S  9  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   267\n  50  S  9 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   280\n  51  S  9  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   247\n  52  S  9  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   260\n  53  S  9 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   273\n  54  S  9  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   248\n  55  S  9  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   261\n  56  S  9 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   274\n  57  S  9  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   249\n  58  S  9  S Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   262\n  59  S  9 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   275\n  60  S  9  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   250\n  61  S  9  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   263\n  62  S  9 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   276\n  63  S  9  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   243\n  64  S  9  S Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   256\n  65  S  9 Cu Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   269\n  66  S  9  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   244\n  67  S  9  S Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   257\n  68  S  9 Cu Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   270\n  69  S  9  S Cu 5.898E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   258\n  70  S  9  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   246\n  71  S  9  S Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   259\n  72  S  9 Cu Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   272\n-------------------------------------------------------------------------------\nShort range atomic symmetry functions element Cu :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1 Cu  2  S    5.309E-02 9.207E+00         3.683E+01  6 0.00   126\n   2 Cu  2  S    5.309E-02 1.228E+01         3.683E+01  6 0.00   127\n   3 Cu  2 Cu    5.309E-02 1.228E+01         3.683E+01  6 0.00   137\n   4 Cu  2  S    5.309E-02 1.534E+01         3.683E+01  6 0.00   128\n   5 Cu  2 Cu    5.309E-02 1.534E+01         3.683E+01  6 0.00   138\n   6 Cu  2  S    5.309E-02 1.841E+01         3.683E+01  6 0.00   129\n   7 Cu  2 Cu    5.309E-02 1.841E+01         3.683E+01  6 0.00   139\n   8 Cu  2  S    5.309E-02 2.455E+01         3.683E+01  6 0.00   131\n   9 Cu  2  S    5.309E-02 3.069E+01         3.683E+01  6 0.00   133\n  10 Cu  3  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   203\n  11 Cu  3  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   216\n  12 Cu  3 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   229\n  13 Cu  3  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   204\n  14 Cu  3  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   217\n  15 Cu  3 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   230\n  16 Cu  3  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   205\n  17 Cu  3 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   231\n  18 Cu  3  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   206\n  19 Cu  3  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   219\n  20 Cu  3 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   232\n  21 Cu  3  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   199\n  22 Cu  3  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   212\n  23 Cu  3 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   225\n  24 Cu  3  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   200\n  25 Cu  3  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   213\n  26 Cu  3 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   226\n  27 Cu  3  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   201\n  28 Cu  3 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   227\n  29 Cu  3  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   202\n  30 Cu  3  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   215\n  31 Cu  3 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   228\n  32 Cu  3  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   195\n  33 Cu  3  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   196\n  34 Cu  3  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   198\n  35 Cu  9  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   291\n  36 Cu  9  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   304\n  37 Cu  9 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   317\n  38 Cu  9  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   292\n  39 Cu  9  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   305\n  40 Cu  9 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   318\n  41 Cu  9  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   293\n  42 Cu  9  S Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   306\n  43 Cu  9 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   319\n  44 Cu  9  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   294\n  45 Cu  9  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   307\n  46 Cu  9 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   320\n  47 Cu  9  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   287\n  48 Cu  9  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   300\n  49 Cu  9 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   313\n  50 Cu  9  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   288\n  51 Cu  9  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   301\n  52 Cu  9 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   314\n  53 Cu  9  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   289\n  54 Cu  9  S Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   302\n  55 Cu  9 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   315\n  56 Cu  9  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   290\n  57 Cu  9  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   303\n  58 Cu  9 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   316\n  59 Cu  9  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   283\n  60 Cu  9  S Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   296\n  61 Cu  9 Cu Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   309\n  62 Cu  9  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   284\n  63 Cu  9  S Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   297\n  64 Cu  9 Cu Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   310\n  65 Cu  9  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   286\n  66 Cu  9  S Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   299\n-------------------------------------------------------------------------------\nMinimum cutoff radius for element  S: 36.826159\nMinimum cutoff radius for element Cu: 36.826159\nMaximum cutoff radius (global)      : 36.826159\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function group index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  S :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  S  2  S            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 9.207E+00                 -  -    -   104    1    1  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   105    2    3  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   106    3    5  \n   2  S  2 Cu            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 9.207E+00                 -  -    -   114    1    2  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   115    2    4  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   116    3    6  \n   -  -  -  -    5.309E-02 1.841E+01                 -  -    -   117    4    7  \n   3  S  3  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   162    1    8 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   163    2   11 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   164    3   14 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   165    4   17 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   158    5   20 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   159    6   23 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   160    7   26 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   161    8   29 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   154    9   32 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   155   10   34 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   157   11   37 0\n   4  S  3  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   175    1    9 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   176    2   12 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   177    3   15 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   178    4   18 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   171    5   21 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   172    6   24 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   173    7   27 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   174    8   30 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   167    9   33 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   168   10   35 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   170   11   38 0\n   5  S  3 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   188    1   10 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   189    2   13 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   190    3   16 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   191    4   19 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   184    5   22 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   185    6   25 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   186    7   28 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   187    8   31 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   181    9   36 1\n   6  S  9  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   250    1   39 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   251    2   42 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   252    3   45 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   253    4   48 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   246    5   51 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   247    6   54 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   248    7   57 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   249    8   60 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   242    9   63 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   243   10   66 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   245   11   70 0\n   7  S  9  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   263    1   40 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   264    2   43 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   265    3   46 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   266    4   49 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   259    5   52 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   260    6   55 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   261    7   58 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   262    8   61 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   255    9   64 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   256   10   67 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  6.0         -  -    -   257   11   69 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   258   12   71 0\n   8  S  9 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   276    1   41 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   277    2   44 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   278    3   47 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   279    4   50 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   272    5   53 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   273    6   56 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   274    7   59 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   275    8   62 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   268    9   65 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   269   10   68 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   271   11   72 0\n-------------------------------------------------------------------------------\nShort range atomic symmetry function groups element Cu :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1 Cu  2  S            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 9.207E+00                 -  -    -   125    1    1  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   126    2    2  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   127    3    4  \n   -  -  -  -    5.309E-02 1.841E+01                 -  -    -   128    4    6  \n   -  -  -  -    5.309E-02 2.455E+01                 -  -    -   130    5    8  \n   -  -  -  -    5.309E-02 3.069E+01                 -  -    -   132    6    9  \n   2 Cu  2 Cu            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   136    1    3  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   137    2    5  \n   -  -  -  -    5.309E-02 1.841E+01                 -  -    -   138    3    7  \n   3 Cu  3  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   202    1   10 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   203    2   13 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   204    3   16 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   205    4   18 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   198    5   21 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   199    6   24 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   200    7   27 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   201    8   29 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   194    9   32 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   195   10   33 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   197   11   34 0\n   4 Cu  3  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   215    1   11 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   216    2   14 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   218    3   19 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   211    4   22 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   212    5   25 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   214    6   30 0\n   5 Cu  3 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   228    1   12 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   229    2   15 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   230    3   17 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   231    4   20 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   224    5   23 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   225    6   26 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   226    7   28 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   227    8   31 0\n   6 Cu  9  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   290    1   35 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   291    2   38 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   292    3   41 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   293    4   44 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   286    5   47 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   287    6   50 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   288    7   53 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   289    8   56 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   282    9   59 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   283   10   62 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   285   11   65 0\n   7 Cu  9  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   303    1   36 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   304    2   39 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   305    3   42 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   306    4   45 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   299    5   48 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   300    6   51 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   301    7   54 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   302    8   57 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   295    9   60 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   296   10   63 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   298   11   66 0\n   8 Cu  9 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   316    1   37 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   317    2   40 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   318    3   43 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   319    4   46 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   312    5   49 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   313    6   52 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   314    7   55 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   315    8   58 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   308    9   61 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   309   10   64 0\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic short range NN for element  S :\nNumber of weights    :   2450\nNumber of biases     :     51\nNumber of connections:   2501\nArchitecture       72   25   25    1\n-------------------------------------------------------------------------------\n   1   G   p   p   l\n   2   G   p   p    \n   3   G   p   p    \n   4   G   p   p    \n   5   G   p   p    \n   6   G   p   p    \n   7   G   p   p    \n   8   G   p   p    \n   9   G   p   p    \n  10   G   p   p    \n  11   G   p   p    \n  12   G   p   p    \n  13   G   p   p    \n  14   G   p   p    \n  15   G   p   p    \n  16   G   p   p    \n  17   G   p   p    \n  18   G   p   p    \n  19   G   p   p    \n  20   G   p   p    \n  21   G   p   p    \n  22   G   p   p    \n  23   G   p   p    \n  24   G   p   p    \n  25   G   p   p    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n  37   G            \n  38   G            \n  39   G            \n  40   G            \n  41   G            \n  42   G            \n  43   G            \n  44   G            \n  45   G            \n  46   G            \n  47   G            \n  48   G            \n  49   G            \n  50   G            \n  51   G            \n  52   G            \n  53   G            \n  54   G            \n  55   G            \n  56   G            \n  57   G            \n  58   G            \n  59   G            \n  60   G            \n  61   G            \n  62   G            \n  63   G            \n  64   G            \n  65   G            \n  66   G            \n  67   G            \n  68   G            \n  69   G            \n  70   G            \n  71   G            \n  72   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element Cu :\nNumber of weights    :   2300\nNumber of biases     :     51\nNumber of connections:   2351\nArchitecture       66   25   25    1\n-------------------------------------------------------------------------------\n   1   G   p   p   l\n   2   G   p   p    \n   3   G   p   p    \n   4   G   p   p    \n   5   G   p   p    \n   6   G   p   p    \n   7   G   p   p    \n   8   G   p   p    \n   9   G   p   p    \n  10   G   p   p    \n  11   G   p   p    \n  12   G   p   p    \n  13   G   p   p    \n  14   G   p   p    \n  15   G   p   p    \n  16   G   p   p    \n  17   G   p   p    \n  18   G   p   p    \n  19   G   p   p    \n  20   G   p   p    \n  21   G   p   p    \n  22   G   p   p    \n  23   G   p   p    \n  24   G   p   p    \n  25   G   p   p    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n  37   G            \n  38   G            \n  39   G            \n  40   G            \n  41   G            \n  42   G            \n  43   G            \n  44   G            \n  45   G            \n  46   G            \n  47   G            \n  48   G            \n  49   G            \n  50   G            \n  51   G            \n  52   G            \n  53   G            \n  54   G            \n  55   G            \n  56   G            \n  57   G            \n  58   G            \n  59   G            \n  60   G            \n  61   G            \n  62   G            \n  63   G            \n  64   G            \n  65   G            \n  66   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALESIGMA (4)\nGs = Smin + (Smax - Smin) * (G - Gmean) / Gsigma\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  S :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  9.17E-08  7.06E-01  2.24E-02  9.64E-02  1.04E+01  0.00  1.00 4\n   2  2.64E-01  2.47E+00  1.04E+00  1.94E-01  5.15E+00  0.00  1.00 4\n   3  1.55E-05  1.42E+00  5.53E-02  2.15E-01  4.65E+00  0.00  1.00 4\n   4  1.41E+00  4.74E+00  3.10E+00  3.59E-01  2.79E+00  0.00  1.00 4\n   5  9.80E-04  1.95E+00  1.14E-01  2.29E-01  4.37E+00  0.00  1.00 4\n   6  2.22E+00  6.07E+00  3.88E+00  3.93E-01  2.54E+00  0.00  1.00 4\n   7  1.03E+00  5.14E+00  2.58E+00  4.38E-01  2.28E+00  0.00  1.00 4\n   8  4.85E-03  3.91E-01  4.76E-02  2.78E-02  3.60E+01  0.00  1.00 4\n   9  9.32E-02  2.83E+00  6.02E-01  3.19E-01  3.13E+00  0.00  1.00 4\n  10  6.72E-01  4.49E+00  2.20E+00  4.15E-01  2.41E+00  0.00  1.00 4\n  11  2.21E-02  8.66E-01  1.41E-01  7.58E-02  1.32E+01  0.00  1.00 4\n  12  8.42E-01  7.07E+00  2.90E+00  7.31E-01  1.37E+00  0.00  1.00 4\n  13  1.45E+00  9.65E+00  4.37E+00  8.38E-01  1.19E+00  0.00  1.00 4\n  14  2.43E-06  5.30E-02  2.81E-04  1.65E-03  6.05E+02  0.00  1.00 4\n  15  4.38E-04  3.34E-01  1.51E-02  3.64E-02  2.75E+01  0.00  1.00 4\n  16  1.87E-02  5.31E-01  1.93E-01  5.38E-02  1.86E+01  0.00  1.00 4\n  17  5.64E-03  2.71E-01  3.62E-02  2.22E-02  4.50E+01  0.00  1.00 4\n  18  5.82E-01  3.04E+00  1.54E+00  2.90E-01  3.45E+00  0.00  1.00 4\n  19  3.55E-01  2.89E+00  1.25E+00  2.61E-01  3.84E+00  0.00  1.00 4\n  20  1.31E-03  2.10E-01  1.65E-02  1.62E-02  6.18E+01  0.00  1.00 4\n  21  3.36E-02  1.60E+00  2.67E-01  1.92E-01  5.22E+00  0.00  1.00 4\n  22  3.53E-01  2.60E+00  1.20E+00  2.39E-01  4.19E+00  0.00  1.00 4\n  23  5.63E-03  4.83E-01  4.87E-02  4.56E-02  2.19E+01  0.00  1.00 4\n  24  3.56E-01  3.94E+00  1.35E+00  4.31E-01  2.32E+00  0.00  1.00 4\n  25  7.14E-01  5.41E+00  2.34E+00  4.75E-01  2.11E+00  0.00  1.00 4\n  26  6.03E-07  2.43E-02  1.04E-04  6.95E-04  1.44E+03  0.00  1.00 4\n  27  1.42E-04  1.88E-01  6.73E-03  1.89E-02  5.30E+01  0.00  1.00 4\n  28  7.67E-03  2.89E-01  9.68E-02  2.86E-02  3.50E+01  0.00  1.00 4\n  29  1.46E-03  1.28E-01  1.25E-02  1.22E-02  8.20E+01  0.00  1.00 4\n  30  2.43E-01  1.58E+00  7.31E-01  1.60E-01  6.24E+00  0.00  1.00 4\n  31  1.57E-01  1.50E+00  6.22E-01  1.39E-01  7.21E+00  0.00  1.00 4\n  32  8.03E-08  9.10E-03  1.18E-04  7.29E-04  1.37E+03  0.00  1.00 4\n  33  3.84E-05  4.69E-02  2.29E-03  6.35E-03  1.57E+02  0.00  1.00 4\n  34  2.51E-07  2.66E-02  3.52E-04  2.18E-03  4.59E+02  0.00  1.00 4\n  35  7.82E-04  1.21E-01  1.02E-02  1.56E-02  6.43E+01  0.00  1.00 4\n  36  6.08E-03  1.52E-01  4.53E-02  1.44E-02  6.93E+01  0.00  1.00 4\n  37  6.52E-08  6.90E-03  8.45E-05  5.18E-04  1.93E+03  0.00  1.00 4\n  38  5.10E-04  3.38E-02  5.05E-03  4.24E-03  2.36E+02  0.00  1.00 4\n  39  3.01E-01  3.92E+00  1.62E+00  3.61E-01  2.77E+00  0.00  1.00 4\n  40  2.92E+00  2.10E+01  1.07E+01  1.84E+00  5.42E-01  0.00  1.00 4\n  41  5.83E+00  3.32E+01  1.69E+01  2.84E+00  3.52E-01  0.00  1.00 4\n  42  2.90E-01  3.42E+00  1.35E+00  2.98E-01  3.35E+00  0.00  1.00 4\n  43  3.32E+00  2.00E+01  1.05E+01  1.84E+00  5.45E-01  0.00  1.00 4\n  44  5.60E+00  2.95E+01  1.47E+01  2.43E+00  4.11E-01  0.00  1.00 4\n  45  7.32E-02  1.42E+00  4.62E-01  1.06E-01  9.43E+00  0.00  1.00 4\n  46  7.44E-01  6.16E+00  3.09E+00  5.27E-01  1.90E+00  0.00  1.00 4\n  47  1.03E+00  9.55E+00  4.66E+00  8.82E-01  1.13E+00  0.00  1.00 4\n  48  5.34E-02  6.08E-01  2.01E-01  4.75E-02  2.11E+01  0.00  1.00 4\n  49  1.10E+00  5.34E+00  2.92E+00  4.91E-01  2.04E+00  0.00  1.00 4\n  50  9.37E-01  6.05E+00  2.81E+00  5.09E-01  1.97E+00  0.00  1.00 4\n  51  1.14E-01  2.31E+00  7.57E-01  2.08E-01  4.80E+00  0.00  1.00 4\n  52  1.43E+00  1.33E+01  5.88E+00  1.22E+00  8.22E-01  0.00  1.00 4\n  53  3.55E+00  2.13E+01  1.09E+01  1.88E+00  5.32E-01  0.00  1.00 4\n  54  1.10E-01  2.08E+00  6.31E-01  1.75E-01  5.70E+00  0.00  1.00 4\n  55  1.65E+00  1.24E+01  5.77E+00  1.19E+00  8.38E-01  0.00  1.00 4\n  56  3.33E+00  1.87E+01  9.22E+00  1.58E+00  6.34E-01  0.00  1.00 4\n  57  2.75E-02  9.17E-01  2.15E-01  6.17E-02  1.62E+01  0.00  1.00 4\n  58  3.62E-01  3.89E+00  1.71E+00  3.48E-01  2.87E+00  0.00  1.00 4\n  59  5.66E-01  6.16E+00  2.96E+00  5.90E-01  1.69E+00  0.00  1.00 4\n  60  2.02E-02  3.35E-01  9.30E-02  2.76E-02  3.62E+01  0.00  1.00 4\n  61  5.54E-01  3.19E+00  1.59E+00  3.05E-01  3.28E+00  0.00  1.00 4\n  62  5.38E-01  3.63E+00  1.66E+00  3.14E-01  3.19E+00  0.00  1.00 4\n  63  9.67E-05  1.49E-01  4.32E-03  8.27E-03  1.21E+02  0.00  1.00 4\n  64  1.20E-02  1.13E+00  1.28E-01  1.34E-01  7.47E+00  0.00  1.00 4\n  65  2.08E-01  1.86E+00  8.23E-01  1.78E-01  5.60E+00  0.00  1.00 4\n  66  8.79E-05  1.26E-01  4.40E-03  1.18E-02  8.46E+01  0.00  1.00 4\n  67  1.34E-02  8.78E-01  1.18E-01  1.13E-01  8.81E+00  0.00  1.00 4\n  68  1.77E-01  1.43E+00  6.21E-01  1.29E-01  7.73E+00  0.00  1.00 4\n  69  2.86E-03  3.73E-01  3.77E-02  3.72E-02  2.69E+01  0.00  1.00 4\n  70  1.59E-05  2.60E-02  7.25E-04  2.49E-03  4.02E+02  0.00  1.00 4\n  71  4.72E-03  1.60E-01  2.88E-02  1.94E-02  5.15E+01  0.00  1.00 4\n  72  1.53E-02  1.93E-01  6.97E-02  1.78E-02  5.62E+01  0.00  1.00 4\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element Cu :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  2.47E-02  1.51E+00  5.19E-01  1.23E-01  8.13E+00  0.00  1.00 4\n   2  2.50E-01  2.69E+00  1.55E+00  2.29E-01  4.37E+00  0.00  1.00 4\n   3  1.86E-03  3.82E+00  1.12E+00  3.99E-01  2.50E+00  0.00  1.00 4\n   4  6.93E-01  3.94E+00  1.94E+00  2.80E-01  3.57E+00  0.00  1.00 4\n   5  5.22E-02  5.98E+00  2.79E+00  6.88E-01  1.45E+00  0.00  1.00 4\n   6  3.47E-01  2.81E+00  1.29E+00  2.50E-01  3.99E+00  0.00  1.00 4\n   7  5.67E-01  6.01E+00  3.40E+00  5.38E-01  1.86E+00  0.00  1.00 4\n   8  8.22E-02  2.16E+00  9.59E-01  2.21E-01  4.53E+00  0.00  1.00 4\n   9  9.75E-02  8.05E-01  3.96E-01  7.28E-02  1.37E+01  0.00  1.00 4\n  10  7.56E-02  1.22E+00  4.24E-01  1.10E-01  9.07E+00  0.00  1.00 4\n  11  3.86E-01  3.42E+00  1.54E+00  2.98E-01  3.35E+00  0.00  1.00 4\n  12  1.27E-01  3.34E+00  9.07E-01  3.08E-01  3.25E+00  0.00  1.00 4\n  13  3.58E-02  2.31E+00  4.52E-01  2.05E-01  4.87E+00  0.00  1.00 4\n  14  1.74E+00  9.19E+00  5.03E+00  7.70E-01  1.30E+00  0.00  1.00 4\n  15  5.61E-01  6.92E+00  2.56E+00  7.04E-01  1.42E+00  0.00  1.00 4\n  16  2.73E-03  2.67E-01  6.84E-02  1.84E-02  5.43E+01  0.00  1.00 4\n  17  1.50E-04  2.89E-01  3.24E-02  2.15E-02  4.66E+01  0.00  1.00 4\n  18  9.70E-03  7.00E-01  7.45E-02  9.21E-02  1.09E+01  0.00  1.00 4\n  19  7.56E-01  3.87E+00  2.13E+00  2.95E-01  3.39E+00  0.00  1.00 4\n  20  2.30E-01  2.24E+00  8.48E-01  2.20E-01  4.54E+00  0.00  1.00 4\n  21  3.17E-02  6.93E-01  2.02E-01  6.20E-02  1.61E+01  0.00  1.00 4\n  22  1.63E-01  1.90E+00  8.13E-01  1.70E-01  5.88E+00  0.00  1.00 4\n  23  4.36E-02  1.85E+00  4.34E-01  1.65E-01  6.07E+00  0.00  1.00 4\n  24  1.18E-02  1.33E+00  2.02E-01  1.24E-01  8.08E+00  0.00  1.00 4\n  25  9.56E-01  5.16E+00  2.73E+00  4.50E-01  2.22E+00  0.00  1.00 4\n  26  2.13E-01  3.76E+00  1.23E+00  3.89E-01  2.57E+00  0.00  1.00 4\n  27  1.08E-03  1.62E-01  3.44E-02  1.03E-02  9.67E+01  0.00  1.00 4\n  28  4.15E-05  1.36E-01  1.35E-02  9.43E-03  1.06E+02  0.00  1.00 4\n  29  2.98E-03  3.97E-01  3.29E-02  5.36E-02  1.87E+01  0.00  1.00 4\n  30  4.09E-01  2.15E+00  1.13E+00  1.66E-01  6.04E+00  0.00  1.00 4\n  31  8.77E-02  1.12E+00  3.97E-01  1.16E-01  8.62E+00  0.00  1.00 4\n  32  2.00E-05  1.76E-02  1.42E-03  1.36E-03  7.35E+02  0.00  1.00 4\n  33  5.27E-06  4.46E-02  1.71E-03  4.26E-03  2.35E+02  0.00  1.00 4\n  34  8.83E-07  1.21E-02  4.19E-04  1.52E-03  6.60E+02  0.00  1.00 4\n  35  1.27E+00  8.93E+00  4.26E+00  5.94E-01  1.68E+00  0.00  1.00 4\n  36  4.30E+00  2.47E+01  1.43E+01  1.97E+00  5.08E-01  0.00  1.00 4\n  37  2.97E+00  2.58E+01  1.18E+01  2.36E+00  4.23E-01  0.00  1.00 4\n  38  4.87E-01  6.92E+00  2.94E+00  5.04E-01  1.98E+00  0.00  1.00 4\n  39  4.73E+00  2.48E+01  1.42E+01  1.97E+00  5.07E-01  0.00  1.00 4\n  40  2.79E+00  2.29E+01  1.03E+01  2.05E+00  4.87E-01  0.00  1.00 4\n  41  5.20E-01  3.06E+00  1.19E+00  2.26E-01  4.43E+00  0.00  1.00 4\n  42  1.07E+00  7.23E+00  3.99E+00  5.81E-01  1.72E+00  0.00  1.00 4\n  43  8.46E-01  7.53E+00  3.40E+00  7.11E-01  1.41E+00  0.00  1.00 4\n  44  7.08E-02  1.30E+00  3.18E-01  1.36E-01  7.34E+00  0.00  1.00 4\n  45  1.37E+00  6.40E+00  3.75E+00  5.02E-01  1.99E+00  0.00  1.00 4\n  46  6.40E-01  4.72E+00  1.99E+00  4.28E-01  2.34E+00  0.00  1.00 4\n  47  8.65E-01  6.12E+00  2.74E+00  4.06E-01  2.47E+00  0.00  1.00 4\n  48  2.53E+00  1.58E+01  8.79E+00  1.28E+00  7.81E-01  0.00  1.00 4\n  49  1.57E+00  1.61E+01  6.94E+00  1.58E+00  6.35E-01  0.00  1.00 4\n  50  2.45E-01  4.57E+00  1.78E+00  3.33E-01  3.00E+00  0.00  1.00 4\n  51  2.84E+00  1.57E+01  8.71E+00  1.28E+00  7.82E-01  0.00  1.00 4\n  52  1.48E+00  1.41E+01  5.96E+00  1.34E+00  7.46E-01  0.00  1.00 4\n  53  2.95E-01  2.16E+00  7.69E-01  1.64E-01  6.08E+00  0.00  1.00 4\n  54  6.12E-01  4.74E+00  2.44E+00  3.84E-01  2.61E+00  0.00  1.00 4\n  55  4.30E-01  4.73E+00  2.01E+00  4.76E-01  2.10E+00  0.00  1.00 4\n  56  3.34E-02  8.33E-01  1.73E-01  8.80E-02  1.14E+01  0.00  1.00 4\n  57  8.27E-01  3.95E+00  2.25E+00  3.13E-01  3.20E+00  0.00  1.00 4\n  58  3.12E-01  2.77E+00  1.11E+00  2.63E-01  3.80E+00  0.00  1.00 4\n  59  2.66E-02  5.68E-01  2.09E-01  4.91E-02  2.04E+01  0.00  1.00 4\n  60  7.25E-02  1.10E+00  4.58E-01  1.03E-01  9.67E+00  0.00  1.00 4\n  61  5.93E-03  1.25E+00  2.45E-01  1.10E-01  9.09E+00  0.00  1.00 4\n  62  3.60E-03  3.91E-01  8.91E-02  3.19E-02  3.14E+01  0.00  1.00 4\n  63  7.25E-02  1.09E+00  4.46E-01  1.02E-01  9.84E+00  0.00  1.00 4\n  64  5.47E-03  9.86E-01  1.95E-01  8.68E-02  1.15E+01  0.00  1.00 4\n  65  1.74E-04  5.69E-02  3.93E-03  6.00E-03  1.67E+02  0.00  1.00 4\n  66  2.10E-02  2.27E-01  9.55E-02  2.06E-02  4.86E+01  0.00  1.00 4\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 0\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** SETUP: RANDOM NUMBER GENERATOR ********************************************\n\nRandom number generator seed: 3\nSeed for rank 0: 3\nSeed for rank 1: 2365658986\nSeed for rank 2: 303761048\nSeed for rank 3: 3041471737\nSeed for rank 4: 3607553667\nSeed for rank 5: 1249426360\nSeed for rank 6: 521102280\nSeed for rank 7: 2193987840\nSeed for rank 8: 2445173525\nSeed for rank 9: 3835177981\nSeed for rank 10: 1877166739\nSeed for rank 11: 3849549514\nSeed for rank 12: 80522091\nSeed for rank 13: 539384825\nSeed for rank 14: 174507689\nSeed for rank 15: 890101386\nSeed for global RNG: 1064672149\n*******************************************************************************\n\n*** STRUCTURE DISTRIBUTION ****************************************************\n\nReading configurations from data file: input.data.\nTotal number of structures: 3965\nNumber of structures per processor: 247 (3) or 248 (13)\nDistributed 3965 structures, 118368544 bytes (112.89 MiB) transferred.\nNumber of local structures: 247\n*******************************************************************************\n\n*** DEFINE TRAINING/TEST SETS *************************************************\n\nDesired test set ratio      : 0.100000\nTotal number of energies    : 3965\nNumber of training energies : 3578\nNumber of test     energies : 387\nNumber of training forces   : 1545696\nNumber of test     forces   : 167184\nActual test set fraction    : 0.097604\n*******************************************************************************\n\n*** WRITE TRAINING/TEST SETS **************************************************\n\nWriting training/test set to files:\n - train.data\n - test.data\n*******************************************************************************\n\n*** WEIGHT INITIALIZATION *****************************************************\n\nInitial weights selected randomly in interval [-1.000000, 1.000000).\nWeights modified accoring to Glorot Bengio scheme.\nBiases set to zero.\n*******************************************************************************\n\n*** SETUP: TRAINING ***********************************************************\n\nForces will be used for training.\nForce update weight:   1.00E+01\nWeight update via Kalman filter selected: updaterType::UT_KALMANFILTER (1)\nMulti-stream Kalman filter training with non-blocking communication selected: ParallelMode::PM_MSEKFNB (2)\nNumber of streams       : 16\nStream of this processor: 0\nCombined updater for all elements selected: UpdateStrategy::US_COMBINED (0)\nNumber of weight updaters    : 1\nTotal fit parameters         : 4852\nSelection mode starting with epoch 0:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 0.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\nSelection mode starting with epoch 10:\nUpdate candidates selected according to error: SelectionMode::SM_SORT (1)\nSelection mode starting with epoch 15:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 0.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\n-------------------------------------------------------------------------------\nSymmetry function memory is reused (HIGH MEMORY USAGE!).\nTraining will be stopped after 40 epochs.\nEnergy comparison will be written every 1 epochs.\nForce comparison will be written every 5 epochs.\nWeights will be written every 1 epochs.\nNeuron statistics will be written every 5 epochs.\nTraining log with update information will be written to: train-log.out.\n-------------------------------------------------------------------------------\nFraction of energies used per epoch:    1.0000\nFraction of forces used per epoch  :    0.0232\nProjected energy updates per epoch :     224 (  9.1%)\nProjected forces updates per epoch :    2236 ( 90.9%)\nTotal projected updates per epoch  :    2460\nMulti-stream training uses 16 energies/forces per weight update.\nqtau is divided by number of projected updates per epoch.\netatau is divided by number of projected updates per epoch.\n-------------------------------------------------------------------------------\nCombined weight updater:\n-------------------------------------------------------------------------------\nKalmanType::KT_STANDARD (0)\nsizeState       = 4852\nsizeObservation = 16\nepsilon         =   1.0000E-02\nq0              =   1.0000E-02\nqtau            =   9.3575E-04\nqmin            =   1.0000E-06\neta0            =   1.0000E-02\netatau          =   9.3575E-04\netamax          =   1.0000E+00\nKalmanParallel::KP_NBCOMM (1)\nOpenMP threads used: 1\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** CALCULATE NEIGHBOR LISTS **************************************************\n\nCalculating neighbor lists for all structures.\nCutoff radius for neighbor lists: 36.826159\n*******************************************************************************\n\n*** TRAINING LOOP *************************************************************\n\nThe training loop output covers different RMSEs, update and\ntiming information. The following quantities are organized\naccording to the matrix scheme below:\n-------------------------------------------------------------------\nep ............ Epoch.\nEtrain_phys ... RMSE of training energies per atom (p. u.).\nEtest_phys .... RMSE of test     energies per atom (p. u.).\nEtrain_int .... RMSE of training energies per atom (i. u.).\nEtest_int ..... RMSE of test     energies per atom (i. u.).\nFtrain_phys ... RMSE of training forces (p. u.).\nFtest_phys .... RMSE of test     forces (p. u.).\nFtrain_int .... RMSE of training forces (i. u.).\nFtest_int ..... RMSE of test     forces (i. u.).\nE_count ....... Number of energy updates.\nF_count ....... Number of force  updates.\ncount ......... Total number of updates.\nt_train ....... Time for training (seconds).\nt_rmse ........ Time for RMSE calculation (seconds).\nt_epoch ....... Total time for this epoch (seconds).\nt_tot ......... Total time for all epochs (seconds).\nAbbreviations:\n  p. u. = physical units.\n  i. u. = internal units.\nNote: RMSEs in internal units (columns 5 + 6) are only present \n      if data set normalization is used.\n-------------------------------------------------------------------\n     1    2             3             4             5             6\nenergy   ep   Etrain_phys    Etest_phys    Etrain_int     Etest_int\nforces   ep   Ftrain_phys    Ftest_phys    Ftrain_int     Ftest_int\nupdate   ep       E_count       F_count         count\ntiming   ep       t_train        t_rmse       t_epoch         t_tot\n-------------------------------------------------------------------\nENERGY    0   1.91455E+00   1.85460E+00   1.41468E+01   1.37038E+01\nFORCES    0   3.95765E+00   3.81821E+00   4.76457E+00   4.59669E+00\nTIMING    0          0.00         36.72         36.84         36.84\n------\nENERGY    1   4.89186E-03   4.44070E-03   3.61464E-02   3.28127E-02\nFORCES    1   9.00338E-02   7.98956E-02   1.08390E-01   9.61853E-02\nUPDATE    1           223          2198          2421\nTIMING    1        591.73          2.88        594.74        631.57\n------\nENERGY    2   8.14646E-03   7.83106E-03   6.01949E-02   5.78643E-02\nFORCES    2   8.33764E-02   7.53830E-02   1.00376E-01   9.07526E-02\nUPDATE    2           223          2205          2428\nTIMING    2        581.29          2.88        584.28       1215.86\n------\nENERGY    3   1.46929E-03   1.41092E-03   1.08567E-02   1.04254E-02\nFORCES    3   7.14048E-02   6.44540E-02   8.59633E-02   7.75953E-02\nUPDATE    3           223          2304          2527\nTIMING    3        606.13          2.87        609.11       1824.97\n------\nENERGY    4   1.19764E-03   1.16880E-03   8.84947E-03   8.63635E-03\nFORCES    4   6.50925E-02   5.92062E-02   7.83639E-02   7.12775E-02\nUPDATE    4           223          2263          2486\nTIMING    4        594.00          2.86        596.98       2421.95\n------\nENERGY    5   3.46244E-03   3.20340E-03   2.55843E-02   2.36702E-02\nFORCES    5   6.32945E-02   5.82054E-02   7.61994E-02   7.00727E-02\nUPDATE    5           223          2168          2391\nTIMING    5        569.04          3.66        572.82       2994.77\n------\nENERGY    6   1.35889E-03   1.30765E-03   1.00410E-02   9.66235E-03\nFORCES    6   6.01682E-02   5.59752E-02   7.24357E-02   6.73878E-02\nUPDATE    6           223          2222          2445\nTIMING    6        582.19          2.88        585.18       3579.95\n------\nENERGY    7   1.10132E-03   1.06999E-03   8.13778E-03   7.90622E-03\nFORCES    7   6.09336E-02   5.61479E-02   7.33572E-02   6.75957E-02\nUPDATE    7           223          2220          2443\nTIMING    7        580.57          2.88        583.56       4163.52\n------\nENERGY    8   1.32085E-03   1.32122E-03   9.75985E-03   9.76257E-03\nFORCES    8   6.04221E-02   5.57148E-02   7.27413E-02   6.70743E-02\nUPDATE    8           223          2177          2400\nTIMING    8        570.35          2.87        573.33       4736.85\n------\nENERGY    9   1.21040E-03   1.20911E-03   8.94372E-03   8.93418E-03\nFORCES    9   6.07639E-02   5.61795E-02   7.31529E-02   6.76337E-02\nUPDATE    9           223          2219          2442\nTIMING    9        580.68          2.86        583.68       5320.52\n------\nINFO   Switching selection mode to SM_SORT (1).\nENERGY   10   1.58579E-03   1.73841E-03   1.17175E-02   1.28453E-02\nFORCES   10   6.52223E-02   6.36152E-02   7.85202E-02   7.65855E-02\nUPDATE   10           223          2275          2498\nTIMING   10        540.55          3.95        544.63       5865.15\n------\nENERGY   11   1.71933E-03   1.52765E-03   1.27043E-02   1.12880E-02\nFORCES   11   6.73072E-02   6.52751E-02   8.10303E-02   7.85838E-02\nUPDATE   11           223          2227          2450\nTIMING   11        530.01          3.05        533.20       6398.36\n------\nENERGY   12   1.91272E-03   2.18165E-03   1.41332E-02   1.61204E-02\nFORCES   12   7.01522E-02   6.84824E-02   8.44553E-02   8.24450E-02\nUPDATE   12           223          2267          2490\nTIMING   12        539.23          3.06        542.42       6940.78\n------\nENERGY   13   2.44192E-03   2.27489E-03   1.80435E-02   1.68094E-02\nFORCES   13   6.86417E-02   6.70474E-02   8.26368E-02   8.07175E-02\nUPDATE   13           223          2294          2517\nTIMING   13        545.08          3.01        548.22       7489.00\n------\nENERGY   14   2.26249E-03   2.34073E-03   1.67177E-02   1.72959E-02\nFORCES   14   6.90512E-02   6.75645E-02   8.31298E-02   8.13399E-02\nUPDATE   14           223          2288          2511\nTIMING   14        543.79          3.02        546.93       8035.93\n------\nINFO   Switching selection mode to SM_THRESHOLD (2).\nENERGY   15   1.06025E-03   1.07406E-03   7.83427E-03   7.93633E-03\nFORCES   15   5.73058E-02   5.50161E-02   6.89896E-02   6.62331E-02\nUPDATE   15           223          2238          2461\nTIMING   15        587.56          3.80        591.48       8627.41\n------\nENERGY   16   1.37488E-03   1.35568E-03   1.01591E-02   1.00172E-02\nFORCES   16   5.58823E-02   5.42190E-02   6.72759E-02   6.52735E-02\nUPDATE   16           223          2143          2366\nTIMING   16        560.83          2.88        563.83       9191.23\n------\nENERGY   17   1.27424E-03   1.31414E-03   9.41548E-03   9.71029E-03\nFORCES   17   5.58550E-02   5.41179E-02   6.72430E-02   6.51518E-02\nUPDATE   17           223          2203          2426\nTIMING   17        575.49          2.91        578.52       9769.76\n------\nENERGY   18   1.28910E-03   1.30698E-03   9.52530E-03   9.65742E-03\nFORCES   18   5.56228E-02   5.38312E-02   6.69636E-02   6.48066E-02\nUPDATE   18           223          2200          2423\nTIMING   18        574.57          2.86        577.55      10347.30\n------\nENERGY   19   1.12363E-03   1.14564E-03   8.30256E-03   8.46527E-03\nFORCES   19   5.62287E-02   5.43167E-02   6.76930E-02   6.53912E-02\nUPDATE   19           223          2220          2443\nTIMING   19        578.92          2.92        581.96      10929.26\n------\nENERGY   20   1.47923E-03   1.47152E-03   1.09301E-02   1.08732E-02\nFORCES   20   5.54920E-02   5.36308E-02   6.68061E-02   6.45654E-02\nUPDATE   20           223          2273          2496\nTIMING   20        591.90          3.68        595.70      11524.96\n------\nENERGY   21   1.11350E-03   1.16066E-03   8.22774E-03   8.57618E-03\nFORCES   21   5.66581E-02   5.41310E-02   6.82100E-02   6.51675E-02\nUPDATE   21           223          2273          2496\nTIMING   21        592.28          2.89        595.29      12120.25\n------\nENERGY   22   1.12267E-03   1.14775E-03   8.29551E-03   8.48081E-03\nFORCES   22   5.58592E-02   5.37209E-02   6.72481E-02   6.46739E-02\nUPDATE   22           223          2249          2472\nTIMING   22        586.16          2.92        589.20      12709.45\n------\nENERGY   23   1.26418E-03   1.27163E-03   9.34117E-03   9.39615E-03\nFORCES   23   5.56921E-02   5.34196E-02   6.70469E-02   6.43111E-02\nUPDATE   23           223          2228          2451\nTIMING   23        581.39          2.87        584.38      13293.83\n------\nENERGY   24   1.25106E-03   1.25941E-03   9.24418E-03   9.30589E-03\nFORCES   24   5.54962E-02   5.34614E-02   6.68111E-02   6.43615E-02\nUPDATE   24           223          2237          2460\nTIMING   24        583.31          2.99        586.42      13880.25\n------\nENERGY   25   1.31547E-03   1.31167E-03   9.72012E-03   9.69202E-03\nFORCES   25   5.55124E-02   5.35109E-02   6.68307E-02   6.44210E-02\nUPDATE   25           223          2204          2427\nTIMING   25        574.94          3.69        578.74      14458.99\n------\nENERGY   26   1.05830E-03   1.07179E-03   7.81984E-03   7.91958E-03\nFORCES   26   5.53964E-02   5.33895E-02   6.66909E-02   6.42749E-02\nUPDATE   26           223          2235          2458\nTIMING   26        583.34          2.92        586.38      15045.38\n------\nENERGY   27   1.06478E-03   1.07289E-03   7.86772E-03   7.92768E-03\nFORCES   27   5.57830E-02   5.35759E-02   6.71564E-02   6.44993E-02\nUPDATE   27           223          2185          2408\nTIMING   27        571.02          2.91        574.05      15619.42\n------\nENERGY   28   1.11424E-03   1.15456E-03   8.23318E-03   8.53116E-03\nFORCES   28   5.61240E-02   5.38066E-02   6.75669E-02   6.47770E-02\nUPDATE   28           223          2226          2449\nTIMING   28        580.99          2.92        584.02      16203.45\n------\nENERGY   29   1.19805E-03   1.25617E-03   8.85250E-03   9.28192E-03\nFORCES   29   5.56368E-02   5.33399E-02   6.69803E-02   6.42151E-02\nUPDATE   29           223          2177          2400\nTIMING   29        569.07          2.93        572.12      16775.57\n------\nENERGY   30   1.32401E-03   1.23619E-03   9.78320E-03   9.13429E-03\nFORCES   30   5.51757E-02   5.33361E-02   6.64253E-02   6.42106E-02\nUPDATE   30           223          2250          2473\nTIMING   30        586.74          3.70        590.56      17366.13\n------\nENERGY   31   1.21832E-03   1.31752E-03   9.00229E-03   9.73525E-03\nFORCES   31   5.54089E-02   5.34993E-02   6.67060E-02   6.44070E-02\nUPDATE   31           223          2223          2446\nTIMING   31        579.31          2.92        582.35      17948.48\n------\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE/hdnnp-data/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   9.1739161189824411E-08   7.0593095050533450E-01   2.2372649929284196E-02   9.6379208796011293E-02\n         1          2   2.6433999906765265E-01   2.4749666370750676E+00   1.0378805142792313E+00   1.9413782463770093E-01\n         1          3   1.5504686427401054E-05   1.4168627312588329E+00   5.5254915214857578E-02   2.1495058826125538E-01\n         1          4   1.4086411910634238E+00   4.7388215758712082E+00   3.1031877925923803E+00   3.5864448236496921E-01\n         1          5   9.8043626772015909E-04   1.9535901883323099E+00   1.1429456309160095E-01   2.2901461288065855E-01\n         1          6   2.2158364445227399E+00   6.0748308460582043E+00   3.8835182764170546E+00   3.9299243538518969E-01\n         1          7   1.0255080523534783E+00   5.1401074554660049E+00   2.5810215644603796E+00   4.3835591238870431E-01\n         1          8   4.8489829707261999E-03   3.9129781874325281E-01   4.7557455423079396E-02   2.7778419734655713E-02\n         1          9   9.3223803365223998E-02   2.8346930075434797E+00   6.0185719975366336E-01   3.1949957606875956E-01\n         1         10   6.7206749586119430E-01   4.4876923880381465E+00   2.1991872165248538E+00   4.1504796440380803E-01\n         1         11   2.2128378766968923E-02   8.6593017344520318E-01   1.4060436434125115E-01   7.5838421599526348E-02\n         1         12   8.4205124330445313E-01   7.0656885702864862E+00   2.9013712601439368E+00   7.3052821449417049E-01\n         1         13   1.4518778507164800E+00   9.6462711741708382E+00   4.3715329035264965E+00   8.3811671947643118E-01\n         1         14   2.4300884834352513E-06   5.3039215356450418E-02   2.8067394350178213E-04   1.6541693025921896E-03\n         1         15   4.3805855934107564E-04   3.3431366727997386E-01   1.5056637491023487E-02   3.6381498406602590E-02\n         1         16   1.8742403996648012E-02   5.3094282134884740E-01   1.9287359264197504E-01   5.3785992354357007E-02\n         1         17   5.6391705067135155E-03   2.7103176024192799E-01   3.6199336036120536E-02   2.2235092628611220E-02\n         1         18   5.8157340520125522E-01   3.0394483797974066E+00   1.5432926655352674E+00   2.9013849228704902E-01\n         1         19   3.5474335876025032E-01   2.8914948266501281E+00   1.2453633098426364E+00   2.6070492382053573E-01\n         1         20   1.3050150224953865E-03   2.0977615521049353E-01   1.6466279986318652E-02   1.6175233794254219E-02\n         1         21   3.3625763520090814E-02   1.6019727512861448E+00   2.6707302954572526E-01   1.9158906783856428E-01\n         1         22   3.5314748293148263E-01   2.5968432133168928E+00   1.2041087980295160E+00   2.3880745648555143E-01\n         1         23   5.6279184570511148E-03   4.8263719913200909E-01   4.8674878532957294E-02   4.5579012837321450E-02\n         1         24   3.5640890668898983E-01   3.9354254479681789E+00   1.3506519169134916E+00   4.3100694380807969E-01\n         1         25   7.1435545388184229E-01   5.4083380133399706E+00   2.3405335217844168E+00   4.7481787957091687E-01\n         1         26   6.0302894280955782E-07   2.4282702757490063E-02   1.0392381208153868E-04   6.9514343858439293E-04\n         1         27   1.4152015883516988E-04   1.8793440136817721E-01   6.7319944252965166E-03   1.8860146728064606E-02\n         1         28   7.6669273315039489E-03   2.8853650966579203E-01   9.6832241039761832E-02   2.8591400835791262E-02\n         1         29   1.4586287100215936E-03   1.2827520308122028E-01   1.2535333774723276E-02   1.2196652689168296E-02\n         1         30   2.4306078779227119E-01   1.5771292876622454E+00   7.3118666045976355E-01   1.6033491927751306E-01\n         1         31   1.5700215118676836E-01   1.4950427209078341E+00   6.2168623298528469E-01   1.3878720233016123E-01\n         1         32   8.0322135442977674E-08   9.1020506427165644E-03   1.1758299063219979E-04   7.2850621729108440E-04\n         1         33   3.8387499554503460E-05   4.6879099417593433E-02   2.2899299020297070E-03   6.3507919696978174E-03\n         1         34   2.5111603817039843E-07   2.6638155845094137E-02   3.5204871838944324E-04   2.1803344919789219E-03\n         1         35   7.8176366916082938E-04   1.2144199943350505E-01   1.0237823308897595E-02   1.5551953673898984E-02\n         1         36   6.0784771853405629E-03   1.5177813800129991E-01   4.5342256644197804E-02   1.4422755174681633E-02\n         1         37   6.5208235096380454E-08   6.8957085587219831E-03   8.4477914517405974E-05   5.1826403434160535E-04\n         1         38   5.1003186367566016E-04   3.3817704100212627E-02   5.0495259674331701E-03   4.2413701977289924E-03\n         1         39   3.0092380409832575E-01   3.9241027015819827E+00   1.6245850308330121E+00   3.6115017167195557E-01\n         1         40   2.9205060411645536E+00   2.0972699454192377E+01   1.0685030237788666E+01   1.8434608066664662E+00\n         1         41   5.8304225749625562E+00   3.3157582599900756E+01   1.6937338463410185E+01   2.8416990087236536E+00\n         1         42   2.8963706388516774E-01   3.4220973094358569E+00   1.3527222233246401E+00   2.9841578592458634E-01\n         1         43   3.3240856510350132E+00   1.9977206504626281E+01   1.0533032366441756E+01   1.8362183066460305E+00\n         1         44   5.5968160844972745E+00   2.9479500954936675E+01   1.4663357897716818E+01   2.4340402007751933E+00\n         1         45   7.3194532436105672E-02   1.4240027432637063E+00   4.6184059564430718E-01   1.0603619804309938E-01\n         1         46   7.4351404260172327E-01   6.1601360099088307E+00   3.0926623459215312E+00   5.2746971733324144E-01\n         1         47   1.0304047665725904E+00   9.5490875529313932E+00   4.6615470051220029E+00   8.8228607777747381E-01\n         1         48   5.3439780036913555E-02   6.0792049084128386E-01   2.0133541277710790E-01   4.7497199912796259E-02\n         1         49   1.0984946263275692E+00   5.3381605458179147E+00   2.9222626179881503E+00   4.9078113758325748E-01\n         1         50   9.3741001607568142E-01   6.0472356274080674E+00   2.8114797251218855E+00   5.0873676433244819E-01\n         1         51   1.1424085007079182E-01   2.3139492223359586E+00   7.5719953168832033E-01   2.0833570661709583E-01\n         1         52   1.4315113742496002E+00   1.3300925195398728E+01   5.8838374866614309E+00   1.2171600869775945E+00\n         1         53   3.5503714858105737E+00   2.1312715022502385E+01   1.0871674742056101E+01   1.8799426423890726E+00\n         1         54   1.0963309213378970E-01   2.0788696656585590E+00   6.3126459151902947E-01   1.7541529953806104E-01\n         1         55   1.6510272306266744E+00   1.2357046870783602E+01   5.7724472752012481E+00   1.1927743223366301E+00\n         1         56   3.3307522004182251E+00   1.8663597697385917E+01   9.2207406968320633E+00   1.5761279490996694E+00\n         1         57   2.7455727216146104E-02   9.1674320906634155E-01   2.1461170716720621E-01   6.1714021121502906E-02\n         1         58   3.6192386693953038E-01   3.8875893126984216E+00   1.7092032560335464E+00   3.4843371038350474E-01\n         1         59   5.6557210052590146E-01   6.1563972117346957E+00   2.9617726398537609E+00   5.9044611830216798E-01\n         1         60   2.0196364035104716E-02   3.3469617649847838E-01   9.3035775655912298E-02   2.7640180745065839E-02\n         1         61   5.5357670454431462E-01   3.1907980705952856E+00   1.5901399654465433E+00   3.0513520444755149E-01\n         1         62   5.3781344801473907E-01   3.6339755326587713E+00   1.6575261374157455E+00   3.1383714619102349E-01\n         1         63   9.6664268597268675E-05   1.4867672619417913E-01   4.3177785208556420E-03   8.2707901241799234E-03\n         1         64   1.2006437712525238E-02   1.1332481089585240E+00   1.2838035367153358E-01   1.3388538744183132E-01\n         1         65   2.0772479772511018E-01   1.8626169502984133E+00   8.2255201121385824E-01   1.7849382645365078E-01\n         1         66   8.7907438908811975E-05   1.2622839046469150E-01   4.4000149614673457E-03   1.1827043706432264E-02\n         1         67   1.3369106385547676E-02   8.7813896596785235E-01   1.1827747851010054E-01   1.1347348778532439E-01\n         1         68   1.7657303404092337E-01   1.4295433698727396E+00   6.2121356605669209E-01   1.2933064669650537E-01\n         1         69   2.8597998667575309E-03   3.7304172172637867E-01   3.7665097851475426E-02   3.7208167402427196E-02\n         1         70   1.5902143209986809E-05   2.6009225424800504E-02   7.2450937404019229E-04   2.4859888979869879E-03\n         1         71   4.7171431923273572E-03   1.6025670770457742E-01   2.8821358718588475E-02   1.9416774232856850E-02\n         1         72   1.5331295649388408E-02   1.9310943777686740E-01   6.9677412943044442E-02   1.7784064753732315E-02\n         2          1   2.4721472942648627E-02   1.5073065774351924E+00   5.1894025713961534E-01   1.2292746613848948E-01\n         2          2   2.4966843476303169E-01   2.6917832996745195E+00   1.5515938962961904E+00   2.2894178892035891E-01\n         2          3   1.8582961795319244E-03   3.8171243121869747E+00   1.1221679663414206E+00   3.9926224172528085E-01\n         2          4   6.9308990079045429E-01   3.9421018903882858E+00   1.9417591382085293E+00   2.7982355416028953E-01\n         2          5   5.2213352864915873E-02   5.9786240694290029E+00   2.7894744649522680E+00   6.8818475947171043E-01\n         2          6   3.4706330958249576E-01   2.8061894414477742E+00   1.2905107822301898E+00   2.5049917129048904E-01\n         2          7   5.6650782795607790E-01   6.0129804050995874E+00   3.4024808580901604E+00   5.3817898895468230E-01\n         2          8   8.2160472578002200E-02   2.1591157175155038E+00   9.5893716661004147E-01   2.2068746057755104E-01\n         2          9   9.7533565633843480E-02   8.0520717520847240E-01   3.9574121682754421E-01   7.2843087896835634E-02\n         2         10   7.5624736998622447E-02   1.2151161903363619E+00   4.2414909548153323E-01   1.1030205700397629E-01\n         2         11   3.8590027688988915E-01   3.4170303616374733E+00   1.5389187655267780E+00   2.9839201545750010E-01\n         2         12   1.2653139464575366E-01   3.3448693047411142E+00   9.0701446886275106E-01   3.0808232807716252E-01\n         2         13   3.5754079396564345E-02   2.3051636092543291E+00   4.5165801949286744E-01   2.0529180913687342E-01\n         2         14   1.7360244301899754E+00   9.1860981352526956E+00   5.0318013545245659E+00   7.7006828863188448E-01\n         2         15   5.6096556948092302E-01   6.9184291400548386E+00   2.5593433032311834E+00   7.0382259666666958E-01\n         2         16   2.7321455653550736E-03   2.6718628880300366E-01   6.8392239083035003E-02   1.8417271845608391E-02\n         2         17   1.4998879259624551E-04   2.8869834404308442E-01   3.2421219256901605E-02   2.1462316150937667E-02\n         2         18   9.6976148378458242E-03   6.9986551977156553E-01   7.4501947267367571E-02   9.2109247490457000E-02\n         2         19   7.5554776729931772E-01   3.8650650491408283E+00   2.1261658860729638E+00   2.9459249679651817E-01\n         2         20   2.2984860438624041E-01   2.2399640197541903E+00   8.4832685420611464E-01   2.2013029667841760E-01\n         2         21   3.1742242534198488E-02   6.9305314098138393E-01   2.0239450285654340E-01   6.2019223320811959E-02\n         2         22   1.6267388613945685E-01   1.8982342788109985E+00   8.1342448996901984E-01   1.7017885772188068E-01\n         2         23   4.3623299253776143E-02   1.8524213261728384E+00   4.3372964228967342E-01   1.6475284995752615E-01\n         2         24   1.1782155855406862E-02   1.3256780035707432E+00   2.0203673375826020E-01   1.2375770385162231E-01\n         2         25   9.5572013219445029E-01   5.1585503300832807E+00   2.7312178298449119E+00   4.5027566865612645E-01\n         2         26   2.1346552007948805E-01   3.7560054368796258E+00   1.2309867059977997E+00   3.8895981570570448E-01\n         2         27   1.0778454975081308E-03   1.6230009416534466E-01   3.4353839552470775E-02   1.0338804556484340E-02\n         2         28   4.1455680376600344E-05   1.3561930079689324E-01   1.3464607540962245E-02   9.4307016558753589E-03\n         2         29   2.9811923400491925E-03   3.9674788724187127E-01   3.2946560522656709E-02   5.3575100644579036E-02\n         2         30   4.0860996892032608E-01   2.1541090596644543E+00   1.1291055145629398E+00   1.6554701558125592E-01\n         2         31   8.7689965003411183E-02   1.1196100344004409E+00   3.9704096379805787E-01   1.1606734505235136E-01\n         2         32   2.0029888316796539E-05   1.7556653440553127E-02   1.4233102888664287E-03   1.3598121443903737E-03\n         2         33   5.2716716179610746E-06   4.4644993845652417E-02   1.7086280138653978E-03   4.2643079956046579E-03\n         2         34   8.8339290835669212E-07   1.2139204575362132E-02   4.1922038284938451E-04   1.5155281653507265E-03\n         2         35   1.2653672947005059E+00   8.9337925904902882E+00   4.2637335795708999E+00   5.9362291906692699E-01\n         2         36   4.3025897744283652E+00   2.4744209023066571E+01   1.4272525712868205E+01   1.9700222663219151E+00\n         2         37   2.9677470818795189E+00   2.5847640450705327E+01   1.1788593731598802E+01   2.3639335745006553E+00\n         2         38   4.8673248345854536E-01   6.9220258514917292E+00   2.9410791137038919E+00   5.0416378898015868E-01\n         2         39   4.7312413761643519E+00   2.4784350068345699E+01   1.4182436900763136E+01   1.9734981280505293E+00\n         2         40   2.7914940844674572E+00   2.2909604188642842E+01   1.0258913931047273E+01   2.0538117984713926E+00\n         2         41   5.1976352609600407E-01   3.0581982698648895E+00   1.1910833091075925E+00   2.2566892125976182E-01\n         2         42   1.0695804209866875E+00   7.2313250376604037E+00   3.9928775708897235E+00   5.8095727320582324E-01\n         2         43   8.4628209088378592E-01   7.5313801441068913E+00   3.3982729265620653E+00   7.1123273080942895E-01\n         2         44   7.0763463381880415E-02   1.2969398476188700E+00   3.1793764328087359E-01   1.3617384576811825E-01\n         2         45   1.3721123798749537E+00   6.3973513973729199E+00   3.7457022157866304E+00   5.0158792550110110E-01\n         2         46   6.3964342968618404E-01   4.7161013997028380E+00   1.9947659320351354E+00   4.2776493844298569E-01\n         2         47   8.6532747970285151E-01   6.1240088873304499E+00   2.7402018484921369E+00   4.0552538612845523E-01\n         2         48   2.5315105294788682E+00   1.5776758660822487E+01   8.7867531123795093E+00   1.2800885070636867E+00\n         2         49   1.5679508239487920E+00   1.6123025100421103E+01   6.9389600266532643E+00   1.5752331036924878E+00\n         2         50   2.4475421880204548E-01   4.5715135037651979E+00   1.7778621079614614E+00   3.3311384228682872E-01\n         2         51   2.8365798870360606E+00   1.5735394223700631E+01   8.7129345829426814E+00   1.2788947945672131E+00\n         2         52   1.4825266957775993E+00   1.4111085036729261E+01   5.9550381055833128E+00   1.3412575984240060E+00\n         2         53   2.9486345514961088E-01   2.1632897998459173E+00   7.6894782290828789E-01   1.6439255789853263E-01\n         2         54   6.1183454216254696E-01   4.7418024842673727E+00   2.4364672738977449E+00   3.8379810845509604E-01\n         2         55   4.2978046698724798E-01   4.7295979558909700E+00   2.0069121315341767E+00   4.7649159304923261E-01\n         2         56   3.3379248097225291E-02   8.3272635081969881E-01   1.7274845946125020E-01   8.7956031429209408E-02\n         2         57   8.2656009161897048E-01   3.9467471262168639E+00   2.2459243943426777E+00   3.1269124051179731E-01\n         2         58   3.1171589063801924E-01   2.7714452296122714E+00   1.1129251102859337E+00   2.6297335909685149E-01\n         2         59   2.6592109568248031E-02   5.6825603390221913E-01   2.0877471778793405E-01   4.9135988886466996E-02\n         2         60   7.2485536842319745E-02   1.1034806181844534E+00   4.5818934497666303E-01   1.0344323974312900E-01\n         2         61   5.9263838221524185E-03   1.2515028539804678E+00   2.4502825958578195E-01   1.1006546541667923E-01\n         2         62   3.5994334696395447E-03   3.9125406849266531E-01   8.9107610428087070E-02   3.1854933024728180E-02\n         2         63   7.2533340578499653E-02   1.0927078443379801E+00   4.4612155612487853E-01   1.0164232620041405E-01\n         2         64   5.4706332551405917E-03   9.8645463183530846E-01   1.9457952454956559E-01   8.6829363320211461E-02\n         2         65   1.7435002600794914E-04   5.6940854477051987E-02   3.9265019004702875E-03   5.9979210203388224E-03\n         2         66   2.1035187678847361E-02   2.2735828246294021E-01   9.5459655622289877E-02   2.0577872261152416E-02\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE/hdnnp-data/weights.016.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -3.5529535307974660E+00 a         1     0     1     1     1\n  7.2419212968357530E-02 a         2     0     1     1     2\n  6.6238167719007179E-01 a         3     0     1     1     3\n  1.3187085002852068E+00 a         4     0     1     1     4\n  8.0230438760649514E-01 a         5     0     1     1     5\n  8.3955862269426929E-01 a         6     0     1     1     6\n  6.0886672237242623E-01 a         7     0     1     1     7\n  1.8038521037244075E+00 a         8     0     1     1     8\n -9.4212226737513360E-01 a         9     0     1     1     9\n -5.1556581063883433E-01 a        10     0     1     1    10\n -1.1787308470438386E-01 a        11     0     1     1    11\n  2.7402309255936421E+00 a        12     0     1     1    12\n -1.4988157706430596E+00 a        13     0     1     1    13\n -1.4218948987030877E+00 a        14     0     1     1    14\n -3.1471248905197000E+00 a        15     0     1     1    15\n -2.7242744362012289E-01 a        16     0     1     1    16\n -1.4939110915197420E+00 a        17     0     1     1    17\n -4.5760625854044340E-01 a        18     0     1     1    18\n  1.8320965746572428E+00 a        19     0     1     1    19\n  1.4829292005742705E+00 a        20     0     1     1    20\n -4.7531481220841671E+00 a        21     0     1     1    21\n  6.9284365000837844E-01 a        22     0     1     1    22\n -1.4360334184866708E+00 a        23     0     1     1    23\n -6.9988606086712224E-01 a        24     0     1     1    24\n -2.6821117310359570E+00 a        25     0     1     1    25\n  1.2328185292695659E+00 a        26     0     2     1     1\n  6.8539081540980901E-02 a        27     0     2     1     2\n  1.1312525424757594E-01 a        28     0     2     1     3\n  3.3791299053992763E-01 a        29     0     2     1     4\n  1.3203780104475105E+00 a        30     0     2     1     5\n -1.4531712477250573E+00 a        31     0     2     1     6\n  2.4379072742488564E-01 a        32     0     2     1     7\n  7.2963026955779986E-01 a        33     0     2     1     8\n -1.2591734762557112E+00 a        34     0     2     1     9\n -4.7096176379988147E-01 a        35     0     2     1    10\n  1.1052943930835461E-01 a        36     0     2     1    11\n  1.2282514057948777E+00 a        37     0     2     1    12\n -5.8437787869506075E-01 a        38     0     2     1    13\n  1.4166787422902487E+00 a        39     0     2     1    14\n -1.6938650584717402E-01 a        40     0     2     1    15\n  2.3030826774815769E+00 a        41     0     2     1    16\n -1.4473769335578126E+00 a        42     0     2     1    17\n  4.0195075881174241E-01 a        43     0     2     1    18\n  1.1043558865793792E+00 a        44     0     2     1    19\n -3.4549061205961434E-01 a        45     0     2     1    20\n  8.1879232157423720E-01 a        46     0     2     1    21\n -2.7007345535606064E-01 a        47     0     2     1    22\n -8.2869143511169474E-01 a        48     0     2     1    23\n -2.9469119089022022E-01 a        49     0     2     1    24\n -5.7206441642229700E-01 a        50     0     2     1    25\n  7.7333844542414798E-01 a        51     0     3     1     1\n -2.8005034461966472E+00 a        52     0     3     1     2\n -2.0054154055351620E-01 a        53     0     3     1     3\n -2.3648818664674390E-01 a        54     0     3     1     4\n -6.4064022093719220E-01 a        55     0     3     1     5\n  6.9876341352721461E-01 a        56     0     3     1     6\n  1.2138517429043079E+00 a        57     0     3     1     7\n -1.0872828987358620E+00 a        58     0     3     1     8\n  2.4009903950784475E+00 a        59     0     3     1     9\n -7.1414550990900871E-01 a        60     0     3     1    10\n  4.8262298434516965E-01 a        61     0     3     1    11\n  1.2017235942575036E-01 a        62     0     3     1    12\n -5.0067742187524500E-01 a        63     0     3     1    13\n  1.6682617398315705E-01 a        64     0     3     1    14\n -1.9521789463955752E+00 a        65     0     3     1    15\n  1.3587159322569415E+00 a        66     0     3     1    16\n  1.9824040428450457E-01 a        67     0     3     1    17\n  5.0478176436946609E-01 a        68     0     3     1    18\n  1.7968971934667841E+00 a        69     0     3     1    19\n -2.6819167691107553E+00 a        70     0     3     1    20\n  3.1361294632323173E+00 a        71     0     3     1    21\n -7.2813429885436576E-01 a        72     0     3     1    22\n  7.9662962027149486E-01 a        73     0     3     1    23\n  5.3906067437318705E-01 a        74     0     3     1    24\n  1.8219650246428634E+00 a        75     0     3     1    25\n  5.8927722128305347E-02 a        76     0     4     1     1\n  3.4478358925805858E-01 a        77     0     4     1     2\n  2.1711984340886667E-01 a        78     0     4     1     3\n -7.5943721634464512E-01 a        79     0     4     1     4\n 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-2.9263488552138478E-01 a      1941     1     5     2    16\n  7.4326458357632263E-01 a      1942     1     5     2    17\n  4.2013924569516037E-01 a      1943     1     5     2    18\n -5.8280302654581832E-02 a      1944     1     5     2    19\n -3.2612804852919446E-02 a      1945     1     5     2    20\n  3.0897375192782450E-01 a      1946     1     5     2    21\n -3.4554814584389509E-01 a      1947     1     5     2    22\n  5.6462638020854716E-01 a      1948     1     5     2    23\n -2.2840636874785014E-01 a      1949     1     5     2    24\n -4.9669234553755076E-01 a      1950     1     5     2    25\n  1.1758939649783381E-01 a      1951     1     6     2     1\n  8.6738679928268236E-01 a      1952     1     6     2     2\n -8.2268243221940873E-01 a      1953     1     6     2     3\n -1.7656641024661676E-01 a      1954     1     6     2     4\n -7.3983486152494982E-01 a      1955     1     6     2     5\n  5.9385478664743296E-01 a      1956     1     6     2     6\n -4.2593570872866021E-01 a      1957     1     6     2     7\n -1.9801025124105215E-01 a      1958     1     6     2     8\n -4.6730416799726238E-01 a      1959     1     6     2     9\n  1.8116336463074925E-01 a      1960     1     6     2    10\n -7.5935659696139179E-01 a      1961     1     6     2    11\n -2.7885626460361607E-01 a      1962     1     6     2    12\n  2.2498372487170440E-01 a      1963     1     6     2    13\n -2.6922194278960770E-01 a      1964     1     6     2    14\n  8.2356834198746176E-02 a      1965     1     6     2    15\n -1.9959174200148408E+00 a      1966     1     6     2    16\n -9.1441649022992150E-02 a      1967     1     6     2    17\n -3.2893725936322316E-01 a      1968     1     6     2    18\n  8.4708812890909327E-02 a      1969     1     6     2    19\n -9.8738542155083330E-03 a      1970     1     6     2    20\n -1.5706979176219785E-01 a      1971     1     6     2    21\n -3.3385820430832114E-01 a      1972     1     6     2    22\n -8.1658461786034431E-01 a      1973     1     6     2    23\n  4.2826805041754107E-01 a      1974     1     6     2    24\n  6.7595378736221203E-03 a      1975     1     6     2    25\n -1.4858293771378450E-01 a      1976     1     7     2     1\n -4.8665064878920916E-01 a      1977     1     7     2     2\n  9.3147532658334302E-03 a      1978     1     7     2     3\n  2.2071434698840436E-01 a      1979     1     7     2     4\n -3.1521981986003578E+00 a      1980     1     7     2     5\n  1.4896102615333093E-01 a      1981     1     7     2     6\n  2.0639082326871608E-01 a      1982     1     7     2     7\n  1.4764434422173356E+00 a      1983     1     7     2     8\n -8.5415180586937678E-01 a      1984     1     7     2     9\n  2.0056826451387089E+00 a      1985     1     7     2    10\n -1.6035541337428121E+00 a      1986     1     7     2    11\n -1.0126746741541708E-01 a      1987     1     7     2    12\n  1.0176837892450277E+00 a      1988     1     7     2    13\n  5.8650237148957363E-01 a      1989     1     7     2    14\n  6.8764775335937489E-01 a      1990     1     7     2    15\n -1.6327881928548789E+00 a      1991     1     7     2    16\n -2.6588597247788198E-01 a      1992     1     7     2    17\n  1.9718370666773979E-01 a      1993     1     7     2    18\n  4.3601566297954825E-01 a      1994     1     7     2    19\n -2.7082844396133726E-01 a      1995     1     7     2    20\n  3.2206390922604272E-01 a      1996     1     7     2    21\n  5.0949702830703934E-03 a      1997     1     7     2    22\n -1.3049790188741632E+00 a      1998     1     7     2    23\n  4.2026808266723220E-01 a      1999     1     7     2    24\n -6.3063301866048659E-03 a      2000     1     7     2    25\n -2.6986778384233595E-01 a      2001     1     8     2     1\n  1.0472413049447822E+00 a      2002     1     8     2     2\n  2.1270075261563209E-01 a      2003     1     8     2     3\n  1.0059956884525167E-02 a      2004     1     8     2     4\n -5.6674331507128162E-01 a      2005     1     8     2     5\n -4.1069951508364727E-01 a      2006     1     8     2     6\n -5.7946760577066525E-01 a      2007     1     8     2     7\n -6.9320514952269952E-01 a      2008     1     8     2     8\n -2.6235771311219197E-01 a      2009     1     8     2     9\n -4.9114985182179943E-01 a      2010     1     8     2    10\n -6.4751077129371837E-01 a      2011     1     8     2    11\n  1.6623516048991380E-01 a      2012     1     8     2    12\n -1.3252784721447061E-01 a      2013     1     8     2    13\n  6.3617130518492077E-02 a      2014     1     8     2    14\n -7.9749770183388205E-02 a      2015     1     8     2    15\n  2.6810344620231513E-01 a      2016     1     8     2    16\n -1.0886590179511721E-01 a      2017     1     8     2    17\n -8.5635070249057671E-02 a      2018     1     8     2    18\n -8.5883419432118385E-02 a      2019     1     8     2    19\n  1.4001812857233212E-01 a      2020     1     8     2    20\n  2.4652559241660935E-01 a      2021     1     8     2    21\n -1.1705271450291483E-02 a      2022     1     8     2    22\n  5.1059887324814701E-01 a      2023     1     8     2    23\n -9.2777234250212143E-02 a      2024     1     8     2    24\n -6.6631934340703591E-01 a      2025     1     8     2    25\n  4.4575672600804567E-01 a      2026     1     9     2     1\n -6.7107163032432227E-01 a      2027     1     9     2     2\n -3.0179267369944862E-01 a      2028     1     9     2     3\n -1.3598496288690123E+00 a      2029     1     9     2     4\n -1.4940270248112404E+00 a      2030     1     9     2     5\n -2.2080339138801010E-02 a      2031     1     9     2     6\n -5.7301816910865744E-01 a      2032     1     9     2     7\n -1.0063124051587569E-01 a      2033     1     9     2     8\n -2.3012172042264027E+00 a      2034     1     9     2     9\n  1.0885556179246252E+00 a      2035     1     9     2    10\n -1.1526492907689538E+00 a      2036     1     9     2    11\n  3.9520279659304998E-02 a      2037     1     9     2    12\n  2.7509795088948047E-01 a      2038     1     9     2    13\n -3.2176987618681385E-01 a      2039     1     9     2    14\n  1.2152345255401775E+00 a      2040     1     9     2    15\n  6.7561788359563746E-01 a      2041     1     9     2    16\n  1.2756402711221351E-01 a      2042     1     9     2    17\n  4.2778010903937930E-02 a      2043     1     9     2    18\n  2.2524717454514478E-01 a      2044     1     9     2    19\n -5.9203499543104976E-01 a      2045     1     9     2    20\n  1.9472787318819443E-01 a      2046     1     9     2    21\n  2.6372584248809827E-01 a      2047     1     9     2    22\n -1.2605296128570485E+00 a      2048     1     9     2    23\n -4.2493619774884570E-02 a      2049     1     9     2    24\n -3.2689975704292223E-01 a      2050     1     9     2    25\n -5.0316442252296556E-01 a      2051     1    10     2     1\n -1.2776598471010672E+00 a      2052     1    10     2     2\n  3.2727687173561748E-01 a      2053     1    10     2     3\n -5.2750979806146270E-01 a      2054     1    10     2     4\n -5.2100917223171461E-01 a      2055     1    10     2     5\n  1.0271103871270988E+00 a      2056     1    10     2     6\n -1.3174585043808176E+00 a      2057     1    10     2     7\n  1.7860344423744762E-01 a      2058     1    10     2     8\n -3.1935218220133910E-01 a      2059     1    10     2     9\n  4.0624355231658738E-01 a      2060     1    10     2    10\n -8.4263015301232114E-01 a      2061     1    10     2    11\n -4.1311568727252523E-01 a      2062     1    10     2    12\n -2.0250507836832625E+00 a      2063     1    10     2    13\n -4.9669616476317113E-01 a      2064     1    10     2    14\n  1.4542353491363211E+00 a      2065     1    10     2    15\n -1.0829455537390682E-01 a      2066     1    10     2    16\n  3.0637661429549540E-01 a      2067     1    10     2    17\n  3.9830418172493465E-01 a      2068     1    10     2    18\n -1.6636558535137880E+00 a      2069     1    10     2    19\n  7.0498166711701593E-01 a      2070     1    10     2    20\n -3.8215339196853010E-01 a      2071     1    10     2    21\n -2.9475963780786207E-01 a      2072     1    10     2    22\n  1.2815404826499932E+00 a      2073     1    10     2    23\n  3.7464874577430729E-01 a      2074     1    10     2    24\n  6.7369985980501002E-01 a      2075     1    10     2    25\n  1.4787802212199200E-01 a      2076     1    11     2     1\n  2.3652422194864106E-01 a      2077     1    11     2     2\n -2.9319277439498237E-01 a      2078     1    11     2     3\n  8.1893235515044593E-01 a      2079     1    11     2     4\n -5.4251461750474061E-01 a      2080     1    11     2     5\n -7.9432325051447306E-01 a      2081     1    11     2     6\n  5.6741940214747433E-01 a      2082     1    11     2     7\n -1.9883538594217587E-01 a      2083     1    11     2     8\n  2.4059652163192724E-01 a      2084     1    11     2     9\n  9.0487535694630072E-01 a      2085     1    11     2    10\n  2.1500450010677571E-01 a      2086     1    11     2    11\n -8.8392848708160249E-02 a      2087     1    11     2    12\n  4.8911199216330936E-01 a      2088     1    11     2    13\n  3.8501747509679890E-01 a      2089     1    11     2    14\n  2.0880386832367939E-01 a      2090     1    11     2    15\n -1.2898150999726214E+00 a      2091     1    11     2    16\n -6.7684897098766336E-02 a      2092     1    11     2    17\n -1.3226797298228404E-01 a      2093     1    11     2    18\n -7.0860409533946489E-01 a      2094     1    11     2    19\n  2.0428970671759283E-01 a      2095     1    11     2    20\n  6.1788460934391509E-01 a      2096     1    11     2    21\n -1.5387742244322317E-02 a      2097     1    11     2    22\n -2.9187261106596285E-01 a      2098     1    11     2    23\n -2.7435985561202314E-01 a      2099     1    11     2    24\n -2.9893757922781268E-02 a      2100     1    11     2    25\n  1.4366492019663546E-01 a      2101     1    12     2     1\n -8.3708506447152686E-01 a      2102     1    12     2     2\n  8.4900741982625050E-01 a      2103     1    12     2     3\n -3.1763858239521897E-01 a      2104     1    12     2     4\n -8.5836557564984983E-02 a      2105     1    12     2     5\n  4.8971995238975233E-02 a      2106     1    12     2     6\n -8.6345064469884769E-01 a      2107     1    12     2     7\n -1.8877691890216164E+00 a      2108     1    12     2     8\n  4.7870208924774238E-01 a      2109     1    12     2     9\n -2.6803285718567860E-01 a      2110     1    12     2    10\n -8.3576740507701341E-01 a      2111     1    12     2    11\n -2.0233607775747742E-01 a      2112     1    12     2    12\n -2.0851336604971404E+00 a      2113     1    12     2    13\n  5.5710849793933925E-02 a      2114     1    12     2    14\n -2.5441709390192631E+00 a      2115     1    12     2    15\n  1.1056110845657674E+00 a      2116     1    12     2    16\n  4.1604534414542688E-01 a      2117     1    12     2    17\n -2.4025453894460813E-01 a      2118     1    12     2    18\n -4.8834369066457661E-01 a      2119     1    12     2    19\n  1.2885571052723108E-01 a      2120     1    12     2    20\n -5.4132000309146744E-01 a      2121     1    12     2    21\n -1.7269282812154974E-01 a      2122     1    12     2    22\n -5.8064851629878863E-03 a      2123     1    12     2    23\n -1.4394463497698487E-01 a      2124     1    12     2    24\n -4.2487948203957382E-01 a      2125     1    12     2    25\n  5.8675042735952393E-02 a      2126     1    13     2     1\n  1.7863972211172008E-01 a      2127     1    13     2     2\n  4.5741880103604365E-01 a      2128     1    13     2     3\n  9.1416506499137384E-01 a      2129     1    13     2     4\n -7.3674367315233913E-01 a      2130     1    13     2     5\n -3.0779431852369288E-01 a      2131     1    13     2     6\n -3.2999352842234286E-01 a      2132     1    13     2     7\n -5.4956662968530401E-01 a      2133     1    13     2     8\n -8.2136164243233878E-01 a      2134     1    13     2     9\n  1.2183161209162805E+00 a      2135     1    13     2    10\n -1.2314580021681576E-04 a      2136     1    13     2    11\n -1.0026980899080576E-01 a      2137     1    13     2    12\n -7.5923362473088618E-01 a      2138     1    13     2    13\n  8.7341315448514784E-02 a      2139     1    13     2    14\n  2.5889498070253123E+00 a      2140     1    13     2    15\n  3.2846563407201890E-01 a      2141     1    13     2    16\n  2.4140079639811293E-01 a      2142     1    13     2    17\n  6.6559640464078706E-01 a      2143     1    13     2    18\n -6.0228182791517193E-01 a      2144     1    13     2    19\n  5.0959148190761594E-01 a      2145     1    13     2    20\n -1.8343764259383200E-01 a      2146     1    13     2    21\n -2.0541935684248189E-01 a      2147     1    13     2    22\n  5.2020354314273987E-01 a      2148     1    13     2    23\n  2.8411193388383044E-01 a      2149     1    13     2    24\n  1.5031583886753237E+00 a      2150     1    13     2    25\n -1.5611135743074465E+00 a      2151     1    14     2     1\n -3.2360297425207724E-01 a      2152     1    14     2     2\n -2.8070095488766600E-01 a      2153     1    14     2     3\n -4.2682370987576490E-01 a      2154     1    14     2     4\n -8.0124669652434721E-01 a      2155     1    14     2     5\n  6.0916260028745439E-01 a      2156     1    14     2     6\n -1.3043834885545900E+00 a      2157     1    14     2     7\n -1.1114567839213945E+00 a      2158     1    14     2     8\n -7.6508338871898718E-01 a      2159     1    14     2     9\n  1.7394319780653198E+00 a      2160     1    14     2    10\n  6.1580012015667462E-01 a      2161     1    14     2    11\n -2.1501534971396988E-01 a      2162     1    14     2    12\n  8.1316399521310057E-01 a      2163     1    14     2    13\n -1.2944835426827954E+00 a      2164     1    14     2    14\n  3.6338934043065596E-02 a      2165     1    14     2    15\n -9.7464822438627852E-01 a      2166     1    14     2    16\n -2.4145501724766127E-01 a      2167     1    14     2    17\n -8.8876835360975071E-03 a      2168     1    14     2    18\n -5.8076528324547438E-01 a      2169     1    14     2    19\n -2.0411437917641737E+00 a      2170     1    14     2    20\n -4.2526015090964880E-01 a      2171     1    14     2    21\n  5.9996421373152897E-01 a      2172     1    14     2    22\n -3.6675255943507928E-02 a      2173     1    14     2    23\n  1.3185398858057240E-01 a      2174     1    14     2    24\n -2.0032286135136248E+00 a      2175     1    14     2    25\n  5.1591662327951759E-01 a      2176     1    15     2     1\n -2.5446052702797714E-03 a      2177     1    15     2     2\n -8.1769338860501051E-01 a      2178     1    15     2     3\n -6.8480492422848949E-01 a      2179     1    15     2     4\n  1.6061689254540090E+00 a      2180     1    15     2     5\n -3.6828605283363745E+00 a      2181     1    15     2     6\n -2.6949729107316758E+00 a      2182     1    15     2     7\n -8.7436479908358988E-01 a      2183     1    15     2     8\n -7.2537234627087488E-01 a      2184     1    15     2     9\n  1.7554101736285144E+00 a      2185     1    15     2    10\n -1.5729036376143151E+00 a      2186     1    15     2    11\n -4.7196403406815074E-01 a      2187     1    15     2    12\n  2.4686309706562368E+00 a      2188     1    15     2    13\n -8.1429048034865914E-01 a      2189     1    15     2    14\n  1.2457943097534157E+00 a      2190     1    15     2    15\n -1.8238343315299035E+00 a      2191     1    15     2    16\n -9.1710155695980261E-02 a      2192     1    15     2    17\n -1.7104412957602122E+00 a      2193     1    15     2    18\n  2.7030869802557012E-01 a      2194     1    15     2    19\n -1.7298684033912173E+00 a      2195     1    15     2    20\n -3.1058841915893948E-01 a      2196     1    15     2    21\n  1.8274844624858664E+00 a      2197     1    15     2    22\n -1.3513314668634027E+00 a      2198     1    15     2    23\n -1.1539080164302253E+00 a      2199     1    15     2    24\n  3.7623134982371026E-01 a      2200     1    15     2    25\n  3.8564708777748902E-01 a      2201     1    16     2     1\n -3.7485013341251339E-01 a      2202     1    16     2     2\n  3.0694902381634054E-01 a      2203     1    16     2     3\n -6.3820812530951954E-01 a      2204     1    16     2     4\n  6.1596951581411624E-02 a      2205     1    16     2     5\n  3.1823666483179947E-01 a      2206     1    16     2     6\n -1.7451214484287221E+00 a      2207     1    16     2     7\n  6.6928800449640258E-01 a      2208     1    16     2     8\n -1.1768614713311631E+00 a      2209     1    16     2     9\n -1.2657577834196381E+00 a      2210     1    16     2    10\n -3.0160201061177228E-01 a      2211     1    16     2    11\n -5.3877877406889563E-01 a      2212     1    16     2    12\n -8.6493612190989910E-01 a      2213     1    16     2    13\n -8.8460225776662071E-01 a      2214     1    16     2    14\n  1.9057948312439157E+00 a      2215     1    16     2    15\n -2.7200418390588271E-01 a      2216     1    16     2    16\n  1.9952889394862189E-01 a      2217     1    16     2    17\n  7.9321718120701656E-02 a      2218     1    16     2    18\n -7.5240700188026213E-02 a      2219     1    16     2    19\n  3.5188674964451849E-01 a      2220     1    16     2    20\n  4.4883278162576262E-01 a      2221     1    16     2    21\n  2.4951384292998435E-01 a      2222     1    16     2    22\n  1.6851679055279442E-01 a      2223     1    16     2    23\n -4.8371544786080266E-02 a      2224     1    16     2    24\n  8.1495784381186021E-01 a      2225     1    16     2    25\n -7.7932092504504180E-01 a      2226     1    17     2     1\n  8.4308356300312914E-01 a      2227     1    17     2     2\n  6.2801495977484001E-01 a      2228     1    17     2     3\n -1.6671863188240814E-02 a      2229     1    17     2     4\n  4.9617622666448757E-01 a      2230     1    17     2     5\n  2.8578791610744131E-01 a      2231     1    17     2     6\n  5.0261300134126208E-01 a      2232     1    17     2     7\n  4.2973672296612153E-01 a      2233     1    17     2     8\n  2.0605776991439645E-02 a      2234     1    17     2     9\n  3.1505912130803543E-01 a      2235     1    17     2    10\n -4.8141644197770223E-01 a      2236     1    17     2    11\n  6.5147019223382929E-01 a      2237     1    17     2    12\n  1.3223922139341173E-02 a      2238     1    17     2    13\n  1.3552951191767832E+00 a      2239     1    17     2    14\n -2.7683725661405684E-01 a      2240     1    17     2    15\n -1.4553982661789062E+00 a      2241     1    17     2    16\n  1.3934738472514663E-01 a      2242     1    17     2    17\n  6.5662014192387624E-02 a      2243     1    17     2    18\n  3.9097955051468730E-01 a      2244     1    17     2    19\n -1.5329149954135943E+00 a      2245     1    17     2    20\n -4.9182889227766408E-01 a      2246     1    17     2    21\n -8.4101247787721850E-02 a      2247     1    17     2    22\n  1.1079957740309260E-01 a      2248     1    17     2    23\n  1.2653734338244162E+00 a      2249     1    17     2    24\n  5.1889782109670390E-01 a      2250     1    17     2    25\n -3.5701303156391490E-01 a      2251     1    18     2     1\n -2.3369886700637788E-01 a      2252     1    18     2     2\n  1.8192889993017079E-02 a      2253     1    18     2     3\n -1.9089403601514085E-01 a      2254     1    18     2     4\n -2.2245213004847283E-01 a      2255     1    18     2     5\n -4.1704360216982245E-01 a      2256     1    18     2     6\n -5.9376327509449600E-01 a      2257     1    18     2     7\n  4.7700366121749904E-01 a      2258     1    18     2     8\n -2.4234013871626243E+00 a      2259     1    18     2     9\n -3.4319600817672740E+00 a      2260     1    18     2    10\n  1.4602063702387118E+00 a      2261     1    18     2    11\n -4.8017949262669966E-02 a      2262     1    18     2    12\n -2.5388955532842389E-01 a      2263     1    18     2    13\n -4.4955574787101665E-01 a      2264     1    18     2    14\n -5.9686971656068388E-01 a      2265     1    18     2    15\n  1.5329181413373798E+00 a      2266     1    18     2    16\n -1.7745540088419492E-01 a      2267     1    18     2    17\n -6.8356066126928808E-02 a      2268     1    18     2    18\n -5.7868883010994010E-01 a      2269     1    18     2    19\n -2.4958945618463482E-01 a      2270     1    18     2    20\n -8.8915588088891362E-01 a      2271     1    18     2    21\n  4.6796145878627105E-01 a      2272     1    18     2    22\n  3.7239838802427244E-01 a      2273     1    18     2    23\n  5.8825012698306467E-01 a      2274     1    18     2    24\n -2.5213870537746796E-01 a      2275     1    18     2    25\n -4.0945577957805229E-01 a      2276     1    19     2     1\n -6.3926426566269479E-01 a      2277     1    19     2     2\n -2.4803832950792159E-03 a      2278     1    19     2     3\n -9.5504254863097604E-01 a      2279     1    19     2     4\n  2.4385416954208063E-02 a      2280     1    19     2     5\n  1.8105456314263782E-01 a      2281     1    19     2     6\n -1.3959803913453275E+00 a      2282     1    19     2     7\n -1.4647235163838312E+00 a      2283     1    19     2     8\n -8.0598524282205181E-02 a      2284     1    19     2     9\n -6.8890711362406043E-01 a      2285     1    19     2    10\n  7.4049128505740025E-01 a      2286     1    19     2    11\n -1.8107652733146301E-01 a      2287     1    19     2    12\n  1.1180459617056233E-01 a      2288     1    19     2    13\n -9.7523288912192785E-01 a      2289     1    19     2    14\n  5.4031707452495070E-01 a      2290     1    19     2    15\n -8.6865875639635415E-01 a      2291     1    19     2    16\n -1.1736299949303194E-03 a      2292     1    19     2    17\n -2.1796832363882152E-01 a      2293     1    19     2    18\n -2.0197745129587785E-01 a      2294     1    19     2    19\n -2.0649260039989298E-01 a      2295     1    19     2    20\n -2.5945409305212930E-01 a      2296     1    19     2    21\n -5.3195384264402990E-01 a      2297     1    19     2    22\n  6.1477888542849975E-02 a      2298     1    19     2    23\n -6.9385778198627257E-01 a      2299     1    19     2    24\n  3.3845607119781312E-01 a      2300     1    19     2    25\n  4.0809678373584041E-02 a      2301     1    20     2     1\n  3.2924070883990825E-01 a      2302     1    20     2     2\n -3.9610966191553226E-01 a      2303     1    20     2     3\n -2.0132651897409879E+00 a      2304     1    20     2     4\n  2.4484241841952716E+00 a      2305     1    20     2     5\n  5.3570194814429040E-01 a      2306     1    20     2     6\n  3.9782963410556638E-01 a      2307     1    20     2     7\n  4.9250587897907255E-01 a      2308     1    20     2     8\n -9.0581905870919688E-01 a      2309     1    20     2     9\n  9.6720818758476146E-01 a      2310     1    20     2    10\n -2.4290730668752603E+00 a      2311     1    20     2    11\n  8.5170505147369346E-01 a      2312     1    20     2    12\n -2.1483680686887496E-01 a      2313     1    20     2    13\n  1.0883989821232398E+00 a      2314     1    20     2    14\n -4.2448276419305673E+00 a      2315     1    20     2    15\n  1.3220278308357323E+00 a      2316     1    20     2    16\n  2.0515176886377723E-01 a      2317     1    20     2    17\n  4.3773484307033583E-01 a      2318     1    20     2    18\n -1.3786340518033451E+00 a      2319     1    20     2    19\n -2.2372534223710475E-01 a      2320     1    20     2    20\n -2.7758118237942005E-02 a      2321     1    20     2    21\n -3.6463714150317883E-01 a      2322     1    20     2    22\n -1.4652346461706460E+00 a      2323     1    20     2    23\n -1.9948609569365011E-01 a      2324     1    20     2    24\n -1.2992922004186624E+00 a      2325     1    20     2    25\n -5.4234465116761910E-01 a      2326     1    21     2     1\n -1.1703464645203435E-01 a      2327     1    21     2     2\n  2.7846604110004280E-01 a      2328     1    21     2     3\n  4.2152065037688702E-01 a      2329     1    21     2     4\n -3.1812648076931704E-01 a      2330     1    21     2     5\n  2.5354733798445972E-01 a      2331     1    21     2     6\n  5.0508300555905372E-01 a      2332     1    21     2     7\n -1.8871360552404024E+00 a      2333     1    21     2     8\n -1.8179368004635235E+00 a      2334     1    21     2     9\n -9.1331416740862581E-01 a      2335     1    21     2    10\n  1.0900023434903663E+00 a      2336     1    21     2    11\n  8.9874047451855385E-02 a      2337     1    21     2    12\n -1.2847531299662041E+00 a      2338     1    21     2    13\n -7.4525540480534103E-01 a      2339     1    21     2    14\n  1.0535696198186528E+00 a      2340     1    21     2    15\n  7.8428574671901730E-01 a      2341     1    21     2    16\n  1.3814042929844125E-01 a      2342     1    21     2    17\n  6.9643061019999272E-02 a      2343     1    21     2    18\n  8.0359279616965651E-01 a      2344     1    21     2    19\n -5.6529681854842539E-01 a      2345     1    21     2    20\n -2.3488037904274034E-02 a      2346     1    21     2    21\n  2.1341829380240665E-01 a      2347     1    21     2    22\n -1.4102093313296238E-01 a      2348     1    21     2    23\n -1.6582794027459599E-01 a      2349     1    21     2    24\n -2.1114013691856662E-01 a      2350     1    21     2    25\n  2.4212589160209405E-01 a      2351     1    22     2     1\n  3.9327330796009152E-01 a      2352     1    22     2     2\n -3.6566016634832049E-01 a      2353     1    22     2     3\n  1.0287117668616212E+00 a      2354     1    22     2     4\n  1.6899708282115562E+00 a      2355     1    22     2     5\n  4.3429485581693034E-01 a      2356     1    22     2     6\n  1.7977381066015556E+00 a      2357     1    22     2     7\n  2.9196281691007775E-01 a      2358     1    22     2     8\n  8.9048235778413076E-01 a      2359     1    22     2     9\n -2.7029855626099626E+00 a      2360     1    22     2    10\n -9.9842398461553661E-01 a      2361     1    22     2    11\n  1.3261280174131618E-01 a      2362     1    22     2    12\n  7.8677628275123768E-01 a      2363     1    22     2    13\n -1.6176772224659823E+00 a      2364     1    22     2    14\n -2.9218429770545273E+00 a      2365     1    22     2    15\n -1.0470075932239322E+00 a      2366     1    22     2    16\n -6.2813242798639934E-01 a      2367     1    22     2    17\n -1.1926621420051280E+00 a      2368     1    22     2    18\n  5.6467524440711148E-01 a      2369     1    22     2    19\n  7.0550764585496206E-01 a      2370     1    22     2    20\n  6.7061497370680800E-01 a      2371     1    22     2    21\n  3.2149813491975643E-01 a      2372     1    22     2    22\n -6.5948083157745863E-01 a      2373     1    22     2    23\n  1.4878019494104766E-01 a      2374     1    22     2    24\n -1.4238392562512412E+00 a      2375     1    22     2    25\n -2.9244659427496789E+00 a      2376     1    23     2     1\n  1.1485640801249154E-01 a      2377     1    23     2     2\n  1.1880136805560255E-01 a      2378     1    23     2     3\n  1.9995339152108655E+00 a      2379     1    23     2     4\n -8.8052571584319517E-01 a      2380     1    23     2     5\n -7.6723479106454269E+00 a      2381     1    23     2     6\n -1.6775055426770660E-01 a      2382     1    23     2     7\n  1.1568877491878693E+00 a      2383     1    23     2     8\n -3.6248359285478049E-01 a      2384     1    23     2     9\n -1.0171667144821397E+00 a      2385     1    23     2    10\n -9.7885097010848721E-01 a      2386     1    23     2    11\n  1.7525905926099136E-01 a      2387     1    23     2    12\n  1.6667129102202356E+00 a      2388     1    23     2    13\n -6.3496168416867071E-01 a      2389     1    23     2    14\n -3.9752798317985540E+00 a      2390     1    23     2    15\n -3.0889419514464751E+00 a      2391     1    23     2    16\n -1.6580901185939814E-01 a      2392     1    23     2    17\n -3.0257630892267329E-01 a      2393     1    23     2    18\n  1.1693501120123342E+00 a      2394     1    23     2    19\n -4.4706334843197343E-01 a      2395     1    23     2    20\n  6.3453286866045877E-01 a      2396     1    23     2    21\n  1.9358044980890732E+00 a      2397     1    23     2    22\n  3.1113852281756920E+00 a      2398     1    23     2    23\n -1.9662951755400133E+00 a      2399     1    23     2    24\n -7.5262034829552482E-01 a      2400     1    23     2    25\n -1.0570204013747100E+00 a      2401     1    24     2     1\n  2.0242154350721828E-01 a      2402     1    24     2     2\n -6.1919254330906649E-02 a      2403     1    24     2     3\n -9.3075303350374716E-01 a      2404     1    24     2     4\n -9.4855833806427159E-01 a      2405     1    24     2     5\n  1.2813916759344554E-01 a      2406     1    24     2     6\n -2.0331973717312746E+00 a      2407     1    24     2     7\n  3.0837174823873076E-01 a      2408     1    24     2     8\n  3.7215037809188369E-02 a      2409     1    24     2     9\n  3.9279821894082573E-01 a      2410     1    24     2    10\n  1.1362819017641221E-01 a      2411     1    24     2    11\n -1.3856723422770947E-01 a      2412     1    24     2    12\n -9.0761795928204336E-01 a      2413     1    24     2    13\n -1.9312687936000594E+00 a      2414     1    24     2    14\n  2.4072402343893264E+00 a      2415     1    24     2    15\n -1.3575532169402038E+00 a      2416     1    24     2    16\n -5.0043337242109498E-01 a      2417     1    24     2    17\n  6.6622788206750017E-01 a      2418     1    24     2    18\n -2.7744853244980633E-01 a      2419     1    24     2    19\n -3.3208589628698015E-01 a      2420     1    24     2    20\n -6.5082760242357884E-01 a      2421     1    24     2    21\n -7.4238152455462947E-01 a      2422     1    24     2    22\n  3.5709111009352618E-01 a      2423     1    24     2    23\n  6.1990222796862571E-01 a      2424     1    24     2    24\n  1.1667603307669538E+00 a      2425     1    24     2    25\n  3.4874499133420743E-02 a      2426     1    25     2     1\n  4.6834087122092077E-01 a      2427     1    25     2     2\n -2.4278656264438364E-01 a      2428     1    25     2     3\n -4.7923572182631186E-01 a      2429     1    25     2     4\n  9.1932774354097346E-01 a      2430     1    25     2     5\n  6.9805008912145541E-03 a      2431     1    25     2     6\n -4.0244240337174698E-02 a      2432     1    25     2     7\n  2.3085018839417204E-01 a      2433     1    25     2     8\n  4.1477758640374958E-02 a      2434     1    25     2     9\n -2.9907893871952584E-01 a      2435     1    25     2    10\n  9.9861813798121868E-01 a      2436     1    25     2    11\n  6.1719473832720140E-01 a      2437     1    25     2    12\n  7.7349291753880958E-02 a      2438     1    25     2    13\n  1.9789467747705813E-01 a      2439     1    25     2    14\n -1.6963001394405985E+00 a      2440     1    25     2    15\n  1.6964283624354803E+00 a      2441     1    25     2    16\n -1.2412318165627852E-02 a      2442     1    25     2    17\n -3.0090042509304782E+00 a      2443     1    25     2    18\n -5.2854050109483008E-01 a      2444     1    25     2    19\n -4.0883552444931642E-01 a      2445     1    25     2    20\n -6.7332635048994605E-01 a      2446     1    25     2    21\n -1.9391822634747917E-02 a      2447     1    25     2    22\n  3.7493997817479574E-01 a      2448     1    25     2    23\n -3.1982153221239995E-01 a      2449     1    25     2    24\n -6.5908145380152439E-02 a      2450     1    25     2    25\n  3.6520581763320918E+00 b      2451     2     1\n  8.0350355841113590E+00 b      2452     2     2\n  1.0328413848960700E+00 b      2453     2     3\n  7.2118044450618859E+00 b      2454     2     4\n  1.6897857032469032E+00 b      2455     2     5\n -5.3128298088875221E+00 b      2456     2     6\n  1.1119283095513778E+01 b      2457     2     7\n  5.6335078037870667E-01 b      2458     2     8\n  3.1863573747908753E+00 b      2459     2     9\n -1.5027072914328254E+01 b      2460     2    10\n  4.2491825701309507E+00 b      2461     2    11\n  1.1953389718194374E+00 b      2462     2    12\n -3.7826613521070804E+00 b      2463     2    13\n  2.5804189796272916E+00 b      2464     2    14\n -1.8825899893966049E+01 b      2465     2    15\n  5.0689924546781171E+00 b      2466     2    16\n -4.2675620759638759E+00 b      2467     2    17\n -2.2492760679197388E+00 b      2468     2    18\n  3.5306849260434596E+00 b      2469     2    19\n -4.5612849025174862E+00 b      2470     2    20\n  2.5261284082068989E+00 b      2471     2    21\n  4.9997935137889167E+00 b      2472     2    22\n -1.0317047947417777E+01 b      2473     2    23\n -8.8894968314347089E+00 b      2474     2    24\n -2.4854869056932949E+00 b      2475     2    25\n  7.7377789653328519E-02 a      2476     2     1     3     1\n  3.8948596770158572E-01 a      2477     2     2     3     1\n  1.7977756447195445E-01 a      2478     2     3     3     1\n  6.2246542349685442E-02 a      2479     2     4     3     1\n -1.1775426437182669E-02 a      2480     2     5     3     1\n  7.4084231368981346E-02 a      2481     2     6     3     1\n -2.6739218038996107E-02 a      2482     2     7     3     1\n -1.4199418404546765E-01 a      2483     2     8     3     1\n -1.3644380226489719E-01 a      2484     2     9     3     1\n  4.2740071857011105E-02 a      2485     2    10     3     1\n -8.4658663941687990E-03 a      2486     2    11     3     1\n  1.8776930772068579E-01 a      2487     2    12     3     1\n -6.7008756457919524E-02 a      2488     2    13     3     1\n  4.7698142607044192E-02 a      2489     2    14     3     1\n -1.3372183470389412E-01 a      2490     2    15     3     1\n  4.0870498106272558E-02 a      2491     2    16     3     1\n  1.7572570907757842E-01 a      2492     2    17     3     1\n -1.6327794687227459E-01 a      2493     2    18     3     1\n -5.9707729641314558E-02 a      2494     2    19     3     1\n  1.0563906282310645E-01 a      2495     2    20     3     1\n  6.6231803238242182E-02 a      2496     2    21     3     1\n -2.7962585890502650E-01 a      2497     2    22     3     1\n  1.6032832788645526E-01 a      2498     2    23     3     1\n -1.0623041830538342E-01 a      2499     2    24     3     1\n  1.0896429147371821E-01 a      2500     2    25     3     1\n -1.3407810853851474E+00 b      2501     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE/hdnnp-data/weights.029.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -6.2446602207005186E-01 a         1     0     1     1     1\n  7.9109168478070069E-01 a         2     0     1     1     2\n  5.0258947941284748E-01 a         3     0     1     1     3\n  5.5154910097820120E-01 a         4     0     1     1     4\n  1.4505158314343458E+00 a         5     0     1     1     5\n -3.6571470924977034E-01 a         6     0     1     1     6\n  4.7092493582249750E-01 a         7     0     1     1     7\n  1.7219501990786370E+00 a         8     0     1     1     8\n -1.3599868727171069E-01 a         9     0     1     1     9\n  5.5171059902123576E-01 a        10     0     1     1    10\n -1.3239450297968971E+00 a        11     0     1     1    11\n  7.9289101991721189E-01 a        12     0     1     1    12\n -2.4436241907430895E-01 a        13     0     1     1    13\n  1.2669669007011655E+00 a        14     0     1     1    14\n -1.0859472353178850E+00 a        15     0     1     1    15\n  5.7149297331656246E-01 a        16     0     1     1    16\n  1.1787879403665555E+00 a        17     0     1     1    17\n  5.1959050316647970E-01 a        18     0     1     1    18\n -5.2070371830737283E-01 a        19     0     1     1    19\n -8.6539404799579653E-02 a        20     0     1     1    20\n -1.1403926908826987E+00 a        21     0     1     1    21\n  7.2846619332612425E-02 a        22     0     1     1    22\n -6.0675985144277489E-01 a        23     0     1     1    23\n  1.6628179166765720E+00 a        24     0     1     1    24\n  1.0538483108672489E+00 a        25     0     1     1    25\n -7.0622748176492056E-01 a        26     0     2     1     1\n  1.0910592071347260E+00 a        27     0     2     1     2\n  2.4631386883986663E+00 a        28     0     2     1     3\n  1.1474600047546029E+00 a        29     0     2     1     4\n -2.7984407189871603E+00 a        30     0     2     1     5\n  1.0533577807665364E-02 a        31     0     2     1     6\n -5.0292118189174440E-01 a        32     0     2     1     7\n -2.2761190415250261E+00 a        33     0     2     1     8\n -1.2187992237701142E+00 a        34     0     2     1     9\n  3.3724765156968588E-02 a        35     0     2     1    10\n -3.9421452238268578E-01 a        36     0     2     1    11\n  8.4824888999103987E-01 a        37     0     2     1    12\n -1.2466531728713620E-01 a        38     0     2     1    13\n  1.2079681252116843E+00 a        39     0     2     1    14\n -9.0112129189102541E-01 a        40     0     2     1    15\n  1.6824118679571578E+00 a        41     0     2     1    16\n  3.3935207339432649E-01 a        42     0     2     1    17\n -6.0996462596068590E-01 a        43     0     2     1    18\n  2.0533210855615880E-01 a        44     0     2     1    19\n -8.8645148744139757E-01 a        45     0     2     1    20\n -8.5393507862220064E-01 a        46     0     2     1    21\n -8.5526839185724302E-01 a        47     0     2     1    22\n  1.2489032362439190E+00 a        48     0     2     1    23\n  1.0938354906306260E+00 a        49     0     2     1    24\n -2.6473483803801245E-01 a        50     0     2     1    25\n -8.5878129366894407E-01 a        51     0     3     1     1\n  1.0564533358250394E+00 a        52     0     3     1     2\n  5.6697850343574663E-01 a        53     0     3     1     3\n  2.1086070474971215E+00 a        54     0     3     1     4\n  3.8166154557138393E-01 a        55     0     3     1     5\n -1.4247279770394652E-01 a        56     0     3     1     6\n -5.9572071020060458E-01 a        57     0     3     1     7\n -1.0694188993944764E-01 a        58     0     3     1     8\n  1.5066623963754497E+00 a        59     0     3     1     9\n  1.8089065761782133E-01 a        60     0     3     1    10\n -2.7214036058537823E+00 a        61     0     3     1    11\n  5.9806847727363321E-01 a        62     0     3     1    12\n -6.1642316248623163E-01 a        63     0     3     1    13\n  1.3696608481313977E+00 a        64     0     3     1    14\n -1.7104667782680838E+00 a        65     0     3     1    15\n  3.4174228333518369E-01 a        66     0     3     1    16\n  2.1950204328903058E+00 a        67     0     3     1    17\n  1.4819471011296372E+00 a        68     0     3     1    18\n  8.6419598086195182E-01 a        69     0     3     1    19\n -1.9807673916649222E+00 a        70     0     3     1    20\n -8.1754981466548049E-01 a        71     0     3     1    21\n  8.5183964054601424E-01 a        72     0     3     1    22\n -1.1265351050299546E+00 a        73     0     3     1    23\n  3.1023051337695745E-01 a        74     0     3     1    24\n  2.7440424392777945E+00 a        75     0     3     1    25\n  2.2960298979188901E-01 a        76     0     4     1     1\n  4.7699142503296446E-02 a        77     0     4     1     2\n  6.0155337022245625E-01 a        78     0     4     1     3\n -1.9439503692815557E-01 a        79     0     4     1     4\n -2.8605530154913746E-02 a        80     0     4     1     5\n  5.5983316423300188E-03 a        81     0     4     1     6\n  9.7519204826929984E-01 a        82     0     4     1     7\n  2.9668852740436547E-01 a        83     0     4     1     8\n  4.8725450035125151E-01 a        84     0     4     1     9\n  2.1326287630079049E-01 a        85     0     4     1    10\n -7.3554692603307470E-01 a        86     0     4     1    11\n  5.3315910230702435E-01 a        87     0     4     1    12\n -5.0172823432095809E-02 a        88     0     4     1    13\n  1.0865253078708168E+00 a        89     0     4     1    14\n -1.0261853156045440E+00 a        90     0     4     1    15\n  2.6512919821052433E-01 a        91     0     4     1    16\n  1.0812812614858249E+00 a        92     0     4     1    17\n  5.1028631925899315E-01 a        93     0     4     1    18\n -2.2599179332603903E-01 a        94     0     4     1    19\n  7.5088913825415021E-02 a        95     0     4     1    20\n -1.2364446472765618E+00 a        96     0     4     1    21\n  7.5326701143038222E-01 a        97     0     4     1    22\n -2.6515244091963569E-01 a        98     0     4     1    23\n  1.6838686308480304E+00 a        99     0     4     1    24\n  4.4492731774876376E-01 a       100     0     4     1    25\n -6.6099920232044096E-01 a       101     0     5     1     1\n  1.0089031054636115E-01 a       102     0     5     1     2\n  6.6342762904664385E-02 a       103     0     5     1     3\n  4.5542810443153381E-01 a       104     0     5     1     4\n -1.6657987380644132E-01 a       105     0     5     1     5\n -8.7555923451999446E-02 a       106     0     5     1     6\n -5.0759948537866628E-01 a       107     0     5     1     7\n  1.6763463093097672E-01 a       108     0     5     1     8\n -5.0802820857751363E-01 a       109     0     5     1     9\n  6.5721089961406787E-01 a       110     0     5     1    10\n -1.7250321983253045E+00 a       111     0     5     1    11\n  3.6248667744583185E-01 a       112     0     5     1    12\n -1.4187643709855371E-01 a       113     0     5     1    13\n  1.8277813268335372E-01 a       114     0     5     1    14\n -2.8759067553024059E-01 a       115     0     5     1    15\n  1.6396175797308257E-01 a       116     0     5     1    16\n  4.8459268505242964E-01 a       117     0     5     1    17\n  1.1485781012576022E+00 a       118     0     5     1    18\n  5.1100172835951252E-01 a       119     0     5     1    19\n -9.6969998866484486E-01 a       120     0     5     1    20\n  2.9282365167621466E-01 a       121     0     5     1    21\n  1.9454366730362621E-01 a       122     0     5     1    22\n  3.3723039867517968E-01 a       123     0     5     1    23\n -1.9892929243485494E-01 a       124     0     5     1    24\n -7.1822973746603158E-01 a       125     0     5     1    25\n -6.8064782973022775E-01 a       126     0     6     1     1\n  1.8829906173635458E-01 a       127     0     6     1     2\n  8.1479476506818194E-01 a       128     0     6     1     3\n  8.8277352960690048E-01 a       129     0     6     1     4\n -1.1427613588950543E+00 a       130     0     6     1     5\n  3.0159781113246154E-01 a       131     0     6     1     6\n -6.6588549790596940E-01 a       132     0     6     1     7\n -3.5003459927148434E-01 a       133     0     6     1     8\n -1.5345874997486508E+00 a       134     0     6     1     9\n -2.4240783711001435E-01 a       135     0     6     1    10\n  6.3947769766304896E-01 a       136     0     6     1    11\n  4.1352767758563735E-01 a       137     0     6     1    12\n -1.9019289044167662E-01 a       138     0     6     1    13\n  6.5802349593562548E-01 a       139     0     6     1    14\n -2.8846900299080136E-01 a       140     0     6     1    15\n  1.8044674812699533E+00 a       141     0     6     1    16\n -5.9916590668694536E-01 a       142     0     6     1    17\n  1.0233762388247421E-01 a       143     0     6     1    18\n -1.8293705219837877E-01 a       144     0     6     1    19\n -4.7618220713345544E-01 a       145     0     6     1    20\n -6.7585128250473714E-01 a       146     0     6     1    21\n -6.6619987727158803E-01 a       147     0     6     1    22\n  1.3937539584448881E+00 a       148     0     6     1    23\n  1.1804472226031208E+00 a       149     0     6     1    24\n -1.0475143437784208E-01 a       150     0     6     1    25\n -5.0310349062450688E-01 a       151     0     7     1     1\n  3.0549253527946091E-01 a       152     0     7     1     2\n  2.1639018141171862E-03 a       153     0     7     1     3\n  9.6581676298511743E-01 a       154     0     7     1     4\n  7.7874943618349207E-02 a       155     0     7     1     5\n  8.3859302793542922E-02 a       156     0     7     1     6\n  1.7299832669890869E-03 a       157     0     7     1     7\n  2.9262810015651336E-01 a       158     0     7     1     8\n  1.7542214681324636E-01 a       159     0     7     1     9\n -2.8526127268586043E-01 a       160     0     7     1    10\n -5.4990409523663197E-01 a       161     0     7     1    11\n  1.3450068091702161E-01 a       162     0     7     1    12\n -1.4756996153937790E-01 a       163     0     7     1    13\n  2.9311237452477523E-01 a       164     0     7     1    14\n -7.2084298548573761E-02 a       165     0     7     1    15\n -8.5149614730888945E-02 a       166     0     7     1    16\n  9.2949085965140277E-01 a       167     0     7     1    17\n -2.8847043946794215E-01 a       168     0     7     1    18\n  4.1186911885861338E-01 a       169     0     7     1    19\n -5.4169485090346026E-01 a       170     0     7     1    20\n -3.5243695639465118E-02 a       171     0     7     1    21\n  3.1341789027127781E-02 a       172     0     7     1    22\n -2.8786714994989410E-01 a       173     0     7     1    23\n  2.7315793972504460E-01 a       174     0     7     1    24\n  1.1716570530670567E+00 a       175     0     7     1    25\n -5.1036135947851669E-01 a       176     0     8     1     1\n -1.3740271110517560E-01 a       177     0     8     1     2\n  4.8958222402524031E-02 a       178     0     8     1     3\n  3.3177672494990651E-01 a       179     0     8     1     4\n -2.3856000868246988E-01 a       180     0     8     1     5\n  4.1214983538548872E-01 a       181     0     8     1     6\n -9.8286694614992598E-01 a       182     0     8     1     7\n -5.4107034590118536E-02 a       183     0     8     1     8\n -1.4324705358476875E-01 a       184     0     8     1     9\n -3.0823277006517974E-01 a       185     0     8     1    10\n  1.1094081849455624E+00 a       186     0     8     1    11\n  1.5831813220006527E-01 a       187     0     8     1    12\n -7.8050742477211929E-02 a       188     0     8     1    13\n  1.4147217795488959E-01 a       189     0     8     1    14\n -3.6482920722359169E-01 a       190     0     8     1    15\n  2.0010515781611065E+00 a       191     0     8     1    16\n -3.7164167894211825E-01 a       192     0     8     1    17\n -1.3125516149697244E-02 a       193     0     8     1    18\n -4.1954663172842910E-02 a       194     0     8     1    19\n -1.0331434570137119E-01 a       195     0     8     1    20\n -1.8011393958889632E-01 a       196     0     8     1    21\n  1.3088400236386397E-01 a       197     0     8     1    22\n  1.1923413887217991E+00 a       198     0     8     1    23\n  3.7781840918971593E-01 a       199     0     8     1    24\n -1.9294958159048309E-01 a       200     0     8     1    25\n -3.3392447645114481E-01 a       201     0     9     1     1\n  1.7014988701747677E-01 a       202     0     9     1     2\n -2.7070863493070599E-02 a       203     0     9     1     3\n  7.4604630341273778E-02 a       204     0     9     1     4\n -1.5102715752534066E-02 a       205     0     9     1     5\n  1.5720699324567589E-01 a       206     0     9     1     6\n -6.1974554587877762E-01 a       207     0     9     1     7\n  5.4891362413614087E-03 a       208     0     9     1     8\n  2.0919388011889421E-02 a       209     0     9     1     9\n -9.6391241772834951E-02 a       210     0     9     1    10\n  7.7306858668673450E-01 a       211     0     9     1    11\n  3.1255109436960182E-01 a       212     0     9     1    12\n  7.7005492614491439E-02 a       213     0     9     1    13\n -2.4607006332823117E-02 a       214     0     9     1    14\n -1.0454167793466912E-01 a       215     0     9     1    15\n  5.7967244318170463E-01 a       216     0     9     1    16\n -1.2093767067885464E-01 a       217     0     9     1    17\n -2.2544971455810286E-01 a       218     0     9     1    18\n  2.1029853185087000E-01 a       219     0     9     1    19\n -1.9601661095545145E-01 a       220     0     9     1    20\n -5.1292763498012379E-02 a       221     0     9     1    21\n  1.4590455721615306E-01 a       222     0     9     1    22\n  4.6964108851222075E-01 a       223     0     9     1    23\n  5.7481385069930169E-02 a       224     0     9     1    24\n -2.0098849633862609E-01 a       225     0     9     1    25\n  4.8244923506134771E+00 a       226     0    10     1     1\n  3.5108916592109578E+00 a       227     0    10     1     2\n  7.5139348670019617E+00 a       228     0    10     1     3\n -3.5578918915946471E+00 a       229     0    10     1     4\n  2.8386058903754559E+00 a       230     0    10     1     5\n  4.4207199746823003E+00 a       231     0    10     1     6\n -3.3412935119326561E+00 a       232     0    10     1     7\n -9.0971866563833217E+00 a       233     0    10     1     8\n -4.5268654758530369E+00 a       234     0    10     1     9\n -5.5872647360635401E+00 a       235     0    10     1    10\n -2.0635169275427789E+00 a       236     0    10     1    11\n -1.5340623877597045E+01 a       237     0    10     1    12\n -8.3715082878395020E+00 a       238     0    10     1    13\n -6.4817382472795639E+00 a       239     0    10     1    14\n -5.0809375777610395E+00 a       240     0    10     1    15\n -6.4689687360330987E+00 a       241     0    10     1    16\n  2.1416014963815999E+00 a       242     0    10     1    17\n  6.8940758724466367E+00 a       243     0    10     1    18\n -4.3648169145202758E+00 a       244     0    10     1    19\n  9.0382653292775696E+00 a       245     0    10     1    20\n -9.9166110945066848E+00 a       246     0    10     1    21\n -1.2044366652841560E+01 a       247     0    10     1    22\n  2.2720545079306909E+01 a       248     0    10     1    23\n -3.7379508213234649E+00 a       249     0    10     1    24\n -4.5209017693635660E+00 a       250     0    10     1    25\n  7.5183832154301431E+00 a       251     0    11     1     1\n -2.3203106234194992E+00 a       252     0    11     1     2\n  1.4841440810090241E+00 a       253     0    11     1     3\n  9.6482513939399706E-01 a       254     0    11     1     4\n -8.4297506087479601E-01 a       255     0    11     1     5\n -4.6990364184782007E-01 a       256     0    11     1     6\n -1.0961424660272627E+00 a       257     0    11     1     7\n -2.7374480650608306E+00 a       258     0    11     1     8\n  3.1380660893974572E+00 a       259     0    11     1     9\n  1.4968023108710922E+00 a       260     0    11     1    10\n  4.8431460218952400E-02 a       261     0    11     1    11\n -1.1491977088084576E+01 a       262     0    11     1    12\n -8.0416563043774918E+00 a       263     0    11     1    13\n -2.5360493765208667E+00 a       264     0    11     1    14\n  7.9109477782628268E-01 a       265     0    11     1    15\n -7.2962300446546091E-01 a       266     0    11     1    16\n -1.2513868916478101E+00 a       267     0    11     1    17\n -2.7011654742543052E+00 a       268     0    11     1    18\n  2.4531950654664225E+00 a       269     0    11     1    19\n -1.0070370759062769E+01 a       270     0    11     1    20\n  7.9155519637009908E+00 a       271     0    11     1    21\n 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1.6244338649202151E-02 a      1893     1     9     2    18\n  2.8159940956926782E-02 a      1894     1     9     2    19\n -7.3760105274932919E-01 a      1895     1     9     2    20\n  1.0604614152784235E-01 a      1896     1     9     2    21\n  1.3087759494518761E-01 a      1897     1     9     2    22\n  2.9873262087000452E-01 a      1898     1     9     2    23\n -7.5121649539691160E-01 a      1899     1     9     2    24\n -5.3923107796072600E-01 a      1900     1     9     2    25\n -9.4224670371027917E-03 a      1901     1    10     2     1\n  1.7582720220947401E-01 a      1902     1    10     2     2\n -4.3499560356818456E-02 a      1903     1    10     2     3\n  2.7310295785198496E-01 a      1904     1    10     2     4\n -1.4711568084768856E+00 a      1905     1    10     2     5\n -4.4204405689495387E-02 a      1906     1    10     2     6\n  6.0834648389602855E-02 a      1907     1    10     2     7\n -2.4139577578874571E+00 a      1908     1    10     2     8\n -3.2330445150185877E-01 a      1909     1    10     2     9\n -6.8558897710748834E-01 a      1910     1    10     2    10\n -2.6306695094273136E-01 a      1911     1    10     2    11\n -2.9406094777407277E+00 a      1912     1    10     2    12\n -1.0262257550335584E-01 a      1913     1    10     2    13\n -4.4889806212745592E-01 a      1914     1    10     2    14\n  1.2729127190479747E-01 a      1915     1    10     2    15\n -5.4339870455363115E-01 a      1916     1    10     2    16\n -4.3051833335864892E-01 a      1917     1    10     2    17\n  2.2774840440979685E-01 a      1918     1    10     2    18\n -4.6577095617807179E-01 a      1919     1    10     2    19\n  6.7677527850068725E-02 a      1920     1    10     2    20\n -5.4331229454547138E-02 a      1921     1    10     2    21\n -7.2517226150440761E-01 a      1922     1    10     2    22\n -1.1034679805264240E+00 a      1923     1    10     2    23\n -2.0195864669569050E+00 a      1924     1    10     2    24\n  3.4421830988038693E-01 a      1925     1    10     2    25\n  6.4169421416549660E-02 a      1926     1    11     2     1\n -1.5453028953359832E-01 a      1927     1    11     2     2\n -3.3937811286737152E-01 a      1928     1    11     2     3\n -2.7264685928399618E-02 a      1929     1    11     2     4\n -1.3046027284183024E+00 a      1930     1    11     2     5\n -2.7987570911040532E-01 a      1931     1    11     2     6\n -7.1818879614311160E-01 a      1932     1    11     2     7\n -1.1206386399096295E+00 a      1933     1    11     2     8\n  5.8589221854259044E-01 a      1934     1    11     2     9\n -3.7755430943908636E-01 a      1935     1    11     2    10\n -2.4227661602201420E-01 a      1936     1    11     2    11\n -6.6802170984862275E-01 a      1937     1    11     2    12\n -1.0335031399378087E+00 a      1938     1    11     2    13\n  2.7352884921752563E-01 a      1939     1    11     2    14\n -7.7644903482906286E-02 a      1940     1    11     2    15\n -1.2483161225817251E-01 a      1941     1    11     2    16\n -1.0076823380037454E-01 a      1942     1    11     2    17\n  1.8474479042673506E-02 a      1943     1    11     2    18\n  1.5921923675493641E-01 a      1944     1    11     2    19\n -8.6092467903913172E-01 a      1945     1    11     2    20\n  3.1597658763496336E-02 a      1946     1    11     2    21\n  1.2582027961569384E-01 a      1947     1    11     2    22\n  4.1552569278194468E-01 a      1948     1    11     2    23\n -1.8547083512843898E-01 a      1949     1    11     2    24\n -3.1841028886761663E-01 a      1950     1    11     2    25\n  1.8006197092716905E-01 a      1951     1    12     2     1\n -5.4024199178819454E-01 a      1952     1    12     2     2\n  3.3523776691134710E-01 a      1953     1    12     2     3\n  2.7560028312601675E-01 a      1954     1    12     2     4\n  8.6177633437044554E-01 a      1955     1    12     2     5\n  1.0087407297301751E+00 a      1956     1    12     2     6\n -1.2380927066334282E-01 a      1957     1    12     2     7\n -1.5229780941544174E-01 a      1958     1    12     2     8\n  2.9946743134146903E-01 a      1959     1    12     2     9\n  1.9819105447401073E+00 a      1960     1    12     2    10\n -8.0628486303151947E-01 a      1961     1    12     2    11\n -9.3151349622473523E-01 a      1962     1    12     2    12\n  1.5051328872455074E+00 a      1963     1    12     2    13\n -8.9627139441554438E-01 a      1964     1    12     2    14\n -3.1439437993199801E-02 a      1965     1    12     2    15\n  1.3701630178002484E+00 a      1966     1    12     2    16\n -2.9138443586057278E-01 a      1967     1    12     2    17\n -3.9087530619619010E-01 a      1968     1    12     2    18\n -2.2753042561066517E-01 a      1969     1    12     2    19\n -8.0931038915796594E-01 a      1970     1    12     2    20\n  1.2030804656668543E+00 a      1971     1    12     2    21\n -1.3389862350446610E-01 a      1972     1    12     2    22\n  4.8419262676478225E-01 a      1973     1    12     2    23\n  1.2108153439974718E+00 a      1974     1    12     2    24\n -1.9519966513619349E+00 a      1975     1    12     2    25\n -1.5047045953264607E-01 a      1976     1    13     2     1\n -6.5196314968694580E-01 a      1977     1    13     2     2\n -1.9444580576963033E-01 a      1978     1    13     2     3\n -3.0635873068371338E-03 a      1979     1    13     2     4\n  1.4891889558793558E+00 a      1980     1    13     2     5\n -2.7617795790820687E-01 a      1981     1    13     2     6\n  1.3155600760922213E+00 a      1982     1    13     2     7\n  1.6548881500952060E+00 a      1983     1    13     2     8\n  1.2939743974749243E+00 a      1984     1    13     2     9\n -8.8087806931438950E-01 a      1985     1    13     2    10\n -7.3026619095577089E-02 a      1986     1    13     2    11\n -6.7521271933403364E+00 a      1987     1    13     2    12\n  3.4361606414546986E-01 a      1988     1    13     2    13\n  8.7558578977526269E-01 a      1989     1    13     2    14\n -2.2881702674887253E-01 a      1990     1    13     2    15\n -6.2816527553206336E-01 a      1991     1    13     2    16\n -8.9317308141201190E-01 a      1992     1    13     2    17\n  9.7069680211539489E-01 a      1993     1    13     2    18\n -5.6927576536010438E-01 a      1994     1    13     2    19\n  8.2910381395357602E-01 a      1995     1    13     2    20\n -3.8934674186907103E-01 a      1996     1    13     2    21\n -1.0181364553104701E+00 a      1997     1    13     2    22\n -9.1002882788836370E-01 a      1998     1    13     2    23\n  2.1075571090156360E+00 a      1999     1    13     2    24\n  2.3017239447035212E-01 a      2000     1    13     2    25\n -3.5483123954045620E-01 a      2001     1    14     2     1\n -9.6047986054177317E-02 a      2002     1    14     2     2\n  3.3071183118138114E-01 a      2003     1    14     2     3\n  1.7705379181791761E-01 a      2004     1    14     2     4\n -1.2043718203406772E+00 a      2005     1    14     2     5\n -5.7806038919408154E-01 a      2006     1    14     2     6\n  6.5633162044623850E-01 a      2007     1    14     2     7\n -1.3450535190144031E-01 a      2008     1    14     2     8\n -1.2862521179205477E-01 a      2009     1    14     2     9\n -1.5177254021629161E-01 a      2010     1    14     2    10\n -2.9016357432381029E-01 a      2011     1    14     2    11\n  1.2793982277409728E+00 a      2012     1    14     2    12\n -3.7109006944139383E-01 a      2013     1    14     2    13\n -4.5064222698368622E-01 a      2014     1    14     2    14\n  3.9087439217392134E-02 a      2015     1    14     2    15\n -1.7890737007331405E+00 a      2016     1    14     2    16\n -3.5761366598992050E-01 a      2017     1    14     2    17\n  3.8280249413524364E-01 a      2018     1    14     2    18\n -3.4580266787944813E-01 a      2019     1    14     2    19\n -2.3102511719307051E-01 a      2020     1    14     2    20\n  6.1712210683785684E-02 a      2021     1    14     2    21\n -3.3548067811281668E-01 a      2022     1    14     2    22\n -7.9862203729164616E-01 a      2023     1    14     2    23\n -5.1952466530501407E-01 a      2024     1    14     2    24\n  2.5810393446929092E-01 a      2025     1    14     2    25\n -4.3558412131876484E-01 a      2026     1    15     2     1\n  1.1902629233075568E-01 a      2027     1    15     2     2\n  1.1747512026211912E-01 a      2028     1    15     2     3\n  1.5495247101048408E-02 a      2029     1    15     2     4\n -1.2065420500806932E+00 a      2030     1    15     2     5\n  3.3479165215501783E-01 a      2031     1    15     2     6\n  2.8245317600466197E-01 a      2032     1    15     2     7\n  6.6749992551384099E-02 a      2033     1    15     2     8\n -3.1396609925815760E-01 a      2034     1    15     2     9\n  3.0054714990159620E-01 a      2035     1    15     2    10\n  6.0483428643207637E-01 a      2036     1    15     2    11\n -1.2454958402656351E+00 a      2037     1    15     2    12\n  6.3389744137669779E-01 a      2038     1    15     2    13\n -5.9521423079842484E-01 a      2039     1    15     2    14\n  1.2019169256706089E-01 a      2040     1    15     2    15\n -1.1987245524864630E-01 a      2041     1    15     2    16\n -5.6896152994198784E-02 a      2042     1    15     2    17\n  2.8941200439853954E-01 a      2043     1    15     2    18\n  1.6309209946798925E-01 a      2044     1    15     2    19\n  8.7949523201494928E-01 a      2045     1    15     2    20\n  6.4769343609644300E-02 a      2046     1    15     2    21\n  4.8521193987474981E-01 a      2047     1    15     2    22\n  4.9988972941182691E-01 a      2048     1    15     2    23\n -2.3016622688408100E-01 a      2049     1    15     2    24\n -5.4074197586570194E-01 a      2050     1    15     2    25\n -4.8573302372386212E-01 a      2051     1    16     2     1\n -1.2895431219807293E-01 a      2052     1    16     2     2\n -3.6183115010678968E-01 a      2053     1    16     2     3\n -1.9197089311858578E-01 a      2054     1    16     2     4\n  1.6791441443786570E+00 a      2055     1    16     2     5\n  1.4524232953370153E+00 a      2056     1    16     2     6\n  8.1332800345877809E-01 a      2057     1    16     2     7\n -6.8993826377906453E-01 a      2058     1    16     2     8\n -6.4581623589215043E-01 a      2059     1    16     2     9\n -1.9086496482644792E+00 a      2060     1    16     2    10\n -7.6174424886678238E-01 a      2061     1    16     2    11\n -6.6106476479584952E-01 a      2062     1    16     2    12\n -6.5143307233530923E-01 a      2063     1    16     2    13\n  6.3145424574265796E-01 a      2064     1    16     2    14\n -2.3081494763260896E-01 a      2065     1    16     2    15\n  1.1456064040705682E-01 a      2066     1    16     2    16\n  1.6252315194690317E-01 a      2067     1    16     2    17\n -1.2291397585047813E-01 a      2068     1    16     2    18\n -6.7674808608296347E-02 a      2069     1    16     2    19\n  5.4942310825997287E-01 a      2070     1    16     2    20\n -1.0797615834794017E-01 a      2071     1    16     2    21\n  2.4950326732348715E-01 a      2072     1    16     2    22\n -7.9414639176233692E-01 a      2073     1    16     2    23\n  2.0544441738751792E-01 a      2074     1    16     2    24\n  1.8992443483722937E-01 a      2075     1    16     2    25\n -4.6582766497660771E-01 a      2076     1    17     2     1\n  2.9539156697999569E-01 a      2077     1    17     2     2\n -2.2097168205408066E-01 a      2078     1    17     2     3\n -1.4860622629638501E-01 a      2079     1    17     2     4\n -3.2498215361218613E-01 a      2080     1    17     2     5\n  3.4427076522021333E-01 a      2081     1    17     2     6\n  8.6586127926198697E-01 a      2082     1    17     2     7\n -1.1418000025514305E-01 a      2083     1    17     2     8\n -6.0056682073398004E-01 a      2084     1    17     2     9\n  2.0450736509644665E-01 a      2085     1    17     2    10\n -1.8519278941182027E-01 a      2086     1    17     2    11\n -1.4644629512368172E+00 a      2087     1    17     2    12\n -2.9378404760799470E-01 a      2088     1    17     2    13\n  5.5384788915605931E-01 a      2089     1    17     2    14\n -1.5004256050064771E-01 a      2090     1    17     2    15\n  3.2806846888851510E-01 a      2091     1    17     2    16\n  2.7598536643862270E-01 a      2092     1    17     2    17\n  4.1850888007058207E-01 a      2093     1    17     2    18\n -5.5362304975505497E-02 a      2094     1    17     2    19\n  2.6951266238898874E-01 a      2095     1    17     2    20\n -2.4264170360616094E-02 a      2096     1    17     2    21\n -1.8676465863061775E-01 a      2097     1    17     2    22\n -3.8787011654837039E-01 a      2098     1    17     2    23\n  3.4485637458118229E-01 a      2099     1    17     2    24\n -3.0786400824237545E-02 a      2100     1    17     2    25\n -1.4217762050351745E-01 a      2101     1    18     2     1\n -7.0998782591968046E-01 a      2102     1    18     2     2\n -9.6362930548428383E-01 a      2103     1    18     2     3\n  7.5180370041830813E-02 a      2104     1    18     2     4\n  9.3452511163166374E-01 a      2105     1    18     2     5\n  7.5072353982545093E-01 a      2106     1    18     2     6\n -1.4600462437868158E+00 a      2107     1    18     2     7\n -1.0484471284226574E-01 a      2108     1    18     2     8\n -1.5226425654047304E+00 a      2109     1    18     2     9\n -8.8296305768438263E-02 a      2110     1    18     2    10\n -3.6274389516383643E-01 a      2111     1    18     2    11\n  8.8349447132068071E-01 a      2112     1    18     2    12\n  3.6371290147774743E-01 a      2113     1    18     2    13\n -4.7916817706816656E-01 a      2114     1    18     2    14\n  1.3662341082955812E-01 a      2115     1    18     2    15\n  1.3172314297178116E+00 a      2116     1    18     2    16\n  3.4403068584860565E-02 a      2117     1    18     2    17\n  3.6061432566306936E-02 a      2118     1    18     2    18\n  4.5896212647717503E-02 a      2119     1    18     2    19\n -1.8589693017644275E+00 a      2120     1    18     2    20\n  1.5237137982152765E-01 a      2121     1    18     2    21\n -3.8234921593024973E-01 a      2122     1    18     2    22\n  3.5542438141750315E-02 a      2123     1    18     2    23\n -3.9944133636062124E-01 a      2124     1    18     2    24\n -6.5550378551330324E-01 a      2125     1    18     2    25\n  1.2816550559385723E-01 a      2126     1    19     2     1\n  3.5486759391369166E-02 a      2127     1    19     2     2\n  4.6182319454349319E-01 a      2128     1    19     2     3\n -5.5122652267036590E-03 a      2129     1    19     2     4\n -3.5080949888496260E+00 a      2130     1    19     2     5\n  7.1486948663206473E-01 a      2131     1    19     2     6\n -2.1201853030552007E+00 a      2132     1    19     2     7\n  7.2604028903282403E-01 a      2133     1    19     2     8\n  5.1081128242304719E-01 a      2134     1    19     2     9\n -4.9137504534121196E-01 a      2135     1    19     2    10\n -1.0472694822448174E+00 a      2136     1    19     2    11\n -1.3523763718593251E+00 a      2137     1    19     2    12\n  2.3568530190159431E-01 a      2138     1    19     2    13\n  5.9584736557607831E-01 a      2139     1    19     2    14\n -3.0079808992756946E-02 a      2140     1    19     2    15\n -1.5268283743999284E-01 a      2141     1    19     2    16\n  9.6122412178057212E-02 a      2142     1    19     2    17\n -1.0684936989401796E-01 a      2143     1    19     2    18\n -5.7716017213991798E-02 a      2144     1    19     2    19\n -2.1338482417439314E-01 a      2145     1    19     2    20\n -3.2012152562395965E-02 a      2146     1    19     2    21\n  6.6195535336631889E-02 a      2147     1    19     2    22\n -4.0717271079249823E-01 a      2148     1    19     2    23\n  4.3854075768154355E-01 a      2149     1    19     2    24\n  5.4824793644114189E-01 a      2150     1    19     2    25\n -1.6683810612646832E-01 a      2151     1    20     2     1\n  2.3322749612412674E-01 a      2152     1    20     2     2\n -4.4183715955442193E-01 a      2153     1    20     2     3\n -7.2076827728753526E-02 a      2154     1    20     2     4\n -5.9352383243727491E-01 a      2155     1    20     2     5\n -3.9339117998165263E-01 a      2156     1    20     2     6\n -5.4931274369409873E-02 a      2157     1    20     2     7\n -4.5548835587531822E-01 a      2158     1    20     2     8\n -6.5732706177413358E-01 a      2159     1    20     2     9\n -1.1236237633542311E-01 a      2160     1    20     2    10\n  1.1351566319349074E-02 a      2161     1    20     2    11\n -1.2386831457708261E+00 a      2162     1    20     2    12\n  4.5243628166561789E-01 a      2163     1    20     2    13\n -5.8831183211013338E-01 a      2164     1    20     2    14\n -8.3869411335455488E-02 a      2165     1    20     2    15\n -7.0984549162019170E-02 a      2166     1    20     2    16\n  3.3054811913793787E-02 a      2167     1    20     2    17\n  1.9644857020909354E-01 a      2168     1    20     2    18\n  1.5161782757226400E-01 a      2169     1    20     2    19\n -2.3505702805909551E-01 a      2170     1    20     2    20\n -1.7918789556131143E-01 a      2171     1    20     2    21\n  3.4990356667744421E-01 a      2172     1    20     2    22\n  6.4840494486623490E-01 a      2173     1    20     2    23\n -1.4478590661265617E-01 a      2174     1    20     2    24\n  2.1297816904812697E-01 a      2175     1    20     2    25\n  3.4493308448955345E-01 a      2176     1    21     2     1\n  3.5266855354427494E-02 a      2177     1    21     2     2\n -2.7754410875303576E-01 a      2178     1    21     2     3\n  4.6768620046741878E-02 a      2179     1    21     2     4\n -1.5769313809619548E-01 a      2180     1    21     2     5\n  1.3497835265205210E-01 a      2181     1    21     2     6\n -3.7341652004504744E-01 a      2182     1    21     2     7\n -3.0627556863254835E-01 a      2183     1    21     2     8\n -2.2925939617710103E-01 a      2184     1    21     2     9\n -3.8592084381092573E-01 a      2185     1    21     2    10\n  4.1234641447800625E-02 a      2186     1    21     2    11\n -9.5022250284578980E-01 a      2187     1    21     2    12\n -1.1125930303081784E+00 a      2188     1    21     2    13\n -5.3122650273704952E-01 a      2189     1    21     2    14\n  2.3060682491837362E-02 a      2190     1    21     2    15\n -1.5104224681786016E+00 a      2191     1    21     2    16\n  1.4753038731650985E-03 a      2192     1    21     2    17\n  1.5143866707297242E-02 a      2193     1    21     2    18\n  8.6090707736472302E-02 a      2194     1    21     2    19\n -6.2430761394861624E-02 a      2195     1    21     2    20\n -6.1308060604509992E-03 a      2196     1    21     2    21\n -1.4270727537208755E-01 a      2197     1    21     2    22\n  4.1134552752308873E-01 a      2198     1    21     2    23\n -6.8567787253466550E-01 a      2199     1    21     2    24\n -6.7206916205524492E-01 a      2200     1    21     2    25\n -1.5391019835641329E+00 a      2201     1    22     2     1\n  1.7206752534353434E-01 a      2202     1    22     2     2\n  6.7593465480848644E-02 a      2203     1    22     2     3\n -8.5997555363846803E-02 a      2204     1    22     2     4\n -9.6065684505879689E-01 a      2205     1    22     2     5\n  1.1113173657279094E+00 a      2206     1    22     2     6\n -3.0842014372062625E+00 a      2207     1    22     2     7\n -1.4384158041499902E+00 a      2208     1    22     2     8\n  1.1309101459634252E+00 a      2209     1    22     2     9\n  1.5105165505154550E-01 a      2210     1    22     2    10\n  3.0645396828385907E-01 a      2211     1    22     2    11\n  6.4601478772770526E-01 a      2212     1    22     2    12\n  4.8724111088572403E-01 a      2213     1    22     2    13\n -4.6620160034283531E-01 a      2214     1    22     2    14\n -4.8803479432276621E-02 a      2215     1    22     2    15\n -9.0430630054920480E-01 a      2216     1    22     2    16\n -6.9889480249312042E-01 a      2217     1    22     2    17\n -1.4468447857571731E+00 a      2218     1    22     2    18\n  2.3039464990726008E-01 a      2219     1    22     2    19\n  5.4576177723516872E-01 a      2220     1    22     2    20\n -7.8015018576137352E-02 a      2221     1    22     2    21\n -1.6133123661713483E-01 a      2222     1    22     2    22\n -1.8319296597374665E-01 a      2223     1    22     2    23\n  2.7253642896910552E-01 a      2224     1    22     2    24\n -1.1584411372851944E+00 a      2225     1    22     2    25\n -5.5424557394569851E-01 a      2226     1    23     2     1\n  7.0029876501251875E-01 a      2227     1    23     2     2\n  8.6637467798596698E-02 a      2228     1    23     2     3\n -7.8591217867498966E-02 a      2229     1    23     2     4\n -3.8578050693417802E+00 a      2230     1    23     2     5\n -1.5514902939375283E-02 a      2231     1    23     2     6\n  5.3013810166945474E-01 a      2232     1    23     2     7\n -6.0550270203294210E-01 a      2233     1    23     2     8\n  4.3671597358238062E-01 a      2234     1    23     2     9\n -3.5715147706396755E-01 a      2235     1    23     2    10\n  1.0882856270043771E-01 a      2236     1    23     2    11\n  1.7281037261210461E+00 a      2237     1    23     2    12\n -5.7515626421966193E-01 a      2238     1    23     2    13\n -1.3375042180867350E-01 a      2239     1    23     2    14\n -6.5503722712337037E-02 a      2240     1    23     2    15\n -2.2025191432304744E-02 a      2241     1    23     2    16\n -8.2655071054651752E-02 a      2242     1    23     2    17\n -2.1027511956094072E-01 a      2243     1    23     2    18\n  2.8902376330777999E-02 a      2244     1    23     2    19\n  1.3213999048426042E-01 a      2245     1    23     2    20\n -1.1460728829522189E-01 a      2246     1    23     2    21\n -5.8828720552246631E-02 a      2247     1    23     2    22\n -6.0152091553027887E-01 a      2248     1    23     2    23\n -7.1147789709956066E-01 a      2249     1    23     2    24\n  5.2100860083053230E-02 a      2250     1    23     2    25\n -1.4344935215141292E+00 a      2251     1    24     2     1\n  9.2746205501548851E-01 a      2252     1    24     2     2\n -7.7216665110619850E-02 a      2253     1    24     2     3\n -2.8798885399279067E-01 a      2254     1    24     2     4\n  3.7454428387915351E+00 a      2255     1    24     2     5\n -1.5625207926251825E+00 a      2256     1    24     2     6\n  3.6660395247444808E+00 a      2257     1    24     2     7\n  2.0253108718040456E+00 a      2258     1    24     2     8\n  1.6318897346220811E+00 a      2259     1    24     2     9\n  2.4800845209015692E+00 a      2260     1    24     2    10\n  1.4907673234653401E-01 a      2261     1    24     2    11\n -4.8613830479267428E-01 a      2262     1    24     2    12\n -6.2019617622102718E-01 a      2263     1    24     2    13\n  2.5952895630277122E+00 a      2264     1    24     2    14\n -4.5829312494493707E-01 a      2265     1    24     2    15\n -2.3487736500391203E+00 a      2266     1    24     2    16\n -3.0197296181118466E-01 a      2267     1    24     2    17\n -2.3095098659235344E-01 a      2268     1    24     2    18\n -3.3608639629945564E-01 a      2269     1    24     2    19\n  6.8582631891122880E-01 a      2270     1    24     2    20\n -5.0043316001326121E-01 a      2271     1    24     2    21\n  1.0373154633440593E-01 a      2272     1    24     2    22\n -1.6204291412423728E+00 a      2273     1    24     2    23\n  1.5638127191591980E+00 a      2274     1    24     2    24\n -2.3309635202853114E+00 a      2275     1    24     2    25\n  2.4489203274966312E-01 a      2276     1    25     2     1\n -2.1518661593071592E-01 a      2277     1    25     2     2\n -5.5802781061846052E-02 a      2278     1    25     2     3\n  4.8845808066633911E-02 a      2279     1    25     2     4\n -1.7557830120404228E-01 a      2280     1    25     2     5\n  2.7192371503339396E-01 a      2281     1    25     2     6\n  5.1576877441197089E-01 a      2282     1    25     2     7\n -2.5099882589234657E-01 a      2283     1    25     2     8\n  3.9307512202972061E-01 a      2284     1    25     2     9\n -1.1210987406922690E+00 a      2285     1    25     2    10\n -1.0439036996834390E-01 a      2286     1    25     2    11\n -4.6783720798261658E-01 a      2287     1    25     2    12\n -3.4722854444840895E-01 a      2288     1    25     2    13\n  3.6029120328851533E-01 a      2289     1    25     2    14\n -2.8984025140998956E-02 a      2290     1    25     2    15\n -2.4076394027143521E-02 a      2291     1    25     2    16\n -3.5643134150827477E-01 a      2292     1    25     2    17\n -8.0475176631190595E-02 a      2293     1    25     2    18\n -4.1056819128214495E-01 a      2294     1    25     2    19\n  7.9766759746990878E-02 a      2295     1    25     2    20\n -6.3351379628206916E-02 a      2296     1    25     2    21\n -6.6416236384591232E-01 a      2297     1    25     2    22\n  9.9799168900512741E-02 a      2298     1    25     2    23\n  3.6809534821907935E-01 a      2299     1    25     2    24\n  4.4938760583598990E-02 a      2300     1    25     2    25\n  1.2254169285344445E+00 b      2301     2     1\n -1.2971586668099495E+00 b      2302     2     2\n  1.5496818967172494E+00 b      2303     2     3\n -5.1016745940541508E+00 b      2304     2     4\n  1.0570990409883480E+01 b      2305     2     5\n -4.5156912340057982E+00 b      2306     2     6\n -5.3447216226080076E+00 b      2307     2     7\n  4.9121474463955411E-01 b      2308     2     8\n  1.8948035234025085E+00 b      2309     2     9\n  8.0589028128011697E-01 b      2310     2    10\n -1.7792287088770824E+00 b      2311     2    11\n  1.4582711867438684E+01 b      2312     2    12\n -1.7367556115635654E+00 b      2313     2    13\n -1.9740162795480241E+00 b      2314     2    14\n -2.4240966432157127E+00 b      2315     2    15\n -2.8599154334878940E+00 b      2316     2    16\n  4.0042881027206061E+00 b      2317     2    17\n -4.2248506318729575E+00 b      2318     2    18\n  4.0200826303003624E-02 b      2319     2    19\n -1.2474151269634015E+00 b      2320     2    20\n -9.2525707564953397E+00 b      2321     2    21\n  3.6900482337635778E+00 b      2322     2    22\n  1.2241959433351147E+01 b      2323     2    23\n -3.6270070547836308E+00 b      2324     2    24\n -9.9424710717210443E-02 b      2325     2    25\n -1.7929412362301902E-01 a      2326     2     1     3     1\n -7.9318720367251710E-02 a      2327     2     2     3     1\n -1.2245497150588677E-01 a      2328     2     3     3     1\n  2.6686957929803099E+00 a      2329     2     4     3     1\n  2.2208281256188907E-02 a      2330     2     5     3     1\n -1.3827880546853433E-01 a      2331     2     6     3     1\n  5.8883707570105491E-02 a      2332     2     7     3     1\n -1.8503473008958521E-01 a      2333     2     8     3     1\n  7.9941146090854662E-02 a      2334     2     9     3     1\n  6.0980780074337042E-02 a      2335     2    10     3     1\n  4.2898647862968903E-01 a      2336     2    11     3     1\n -1.6418700509588654E-02 a      2337     2    12     3     1\n  9.2626066276151567E-02 a      2338     2    13     3     1\n  1.6213121749951970E-01 a      2339     2    14     3     1\n  5.0025887501899446E-01 a      2340     2    15     3     1\n -9.3228633980085102E-02 a      2341     2    16     3     1\n -4.2506309509736678E-01 a      2342     2    17     3     1\n -2.8020236882301058E-01 a      2343     2    18     3     1\n  1.3369952476903810E+00 a      2344     2    19     3     1\n  7.6998543117290666E-02 a      2345     2    20     3     1\n  5.8165502415695283E+00 a      2346     2    21     3     1\n  4.9617644425128343E-01 a      2347     2    22     3     1\n  3.8051021746990116E-01 a      2348     2    23     3     1\n  1.1951241138280733E-01 a      2349     2    24     3     1\n  1.3087209279691459E-01 a      2350     2    25     3     1\n -2.6815621704168309E+00 b      2351     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE/md.lmp",
    "content": "###############################################################################\n# MD simulation for HDNNP copper sulfide\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"cu2s_144_low-chalcocite_Evans-1979_PBE.data\"\n# Timesteps\nvariable numSteps        equal  100\nvariable dt              equal  0.001\n# NN\nvariable hdnnpCutoff     equal  6.01\nvariable hdnnpDir        string \"hdnnp-data\"\n# Masses\nvariable mass_S          equal  32.065                                                  # mass for element 1 (S)  (g/mol)\nvariable mass_Cu         equal  63.546                                                  # mass for element 2 (Cu) (g/mol)\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary p p p\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_S}\nmass 2 ${mass_Cu}\ntimestep ${dt}\nthermo 10\n\n###############################################################################\n# HDNNP\n###############################################################################\npair_style hdnnp ${hdnnpCutoff} dir ${hdnnpDir} showew no showewsum 100 resetew no maxew 100 cflength 1.0 cfenergy 1.0\npair_coeff * * S Cu\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\ndump 1 all atom 10 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE_external/cu2s_144_low-chalcocite_Evans-1979_PBE.data",
    "content": "Generated by sg2cfg\n\n144 atoms\n2 atom types\n\n  0.0000000000000000E+00   1.5246000000000000E+01 xlo xhi\n  0.0000000000000000E+00   1.1884000000000000E+01 ylo yhi\n  0.0000000000000000E+00   1.2091965796411374E+01 zlo zhi\n  0.0000000000000000E+00  -5.9893571590294590E+00   0.0000000000000000E+00 xy xz yz\n\nAtoms\n\n1 1   9.5538084006653907E+00   9.8518360000000005E-01   1.0183853593737659E+01\n2 1  -3.2918441392095787E+00   6.9271836000000002E+00   7.9540951008794023E+00\n3 1  -2.9716555969484926E-01   1.0898816400000001E+01   1.9081122026737154E+00\n4 1   1.2548486980180119E+01   4.9568164000000001E+00   4.1378706955319728E+00\n5 1   1.2277544351544003E+01   9.1269119999999992E-01   4.1862385587176183E+00\n6 1  -2.6222931058731080E-02   6.8546911999999995E+00   1.8597443394880693E+00\n7 1  -3.0209015105734602E+00   1.0971308800000001E+01   7.9057272376937560E+00\n8 1   9.2828657720292718E+00   5.0293088000000008E+00   1.0232221456923305E+01\n9 1   9.0699177918038707E+00   9.7924160000000005E-01   6.1282082656212848E+00\n10 1  -2.8079535303480587E+00   6.9212416000000001E+00   1.2009740428995777E+01\n11 1   1.8672504916667076E-01   1.0904758400000000E+01   5.9637575307900894E+00\n12 1   1.2064596371318601E+01   4.9627584000000002E+00   8.2225367415599035E-02\n13 1   1.2034322057045824E+01   9.7092279999999997E-01   7.2551794778468251E-02\n14 1   2.1699936343944826E-01   6.9129228000000005E+00   5.9734311034272185E+00\n15 1  -2.7776792160752812E+00   1.0913077200000000E+01   1.2019414001632907E+01\n16 1   9.0396434775310937E+00   4.9710771999999999E+00   6.1185346929841558E+00\n17 1   3.1737058543672330E+00   1.0493572000000000E+00   7.4160026229390956E+00\n18 1   3.0882584070885768E+00   6.9913572000000004E+00   1.0721946071677966E+01\n19 1   6.0829369866033067E+00   1.0834642799999999E+01   4.6759631734722786E+00\n20 1   6.1683844338819629E+00   4.8926428000000000E+00   1.3700197247334083E+00\n21 1   6.2021409198808808E+00   8.6277839999999995E-01   1.1572011267165685E+00\n22 1   6.0491805006043897E+00   6.8047784000000000E+00   4.8887817714891186E+00\n23 1   3.0545019210896607E+00   1.1021221600000001E+01   1.0934764669694806E+01\n24 1   3.2074623403661517E+00   5.0792216000000003E+00   7.2031840249222556E+00\n25 1  -1.4015081272437779E-01   9.2814040000000009E-01   9.5139586886164693E+00\n26 1   6.4021150741801902E+00   6.8701404000000013E+00   8.6239900060005912E+00\n27 1   9.3967936536949193E+00   1.0955859600000000E+01   2.5780071077949045E+00\n28 1   2.8545277667903521E+00   5.0138596000000000E+00   3.4679757904107813E+00\n29 1   2.6160912310744484E+00   9.8874879999999998E-01   3.4691849869904230E+00\n30 1   9.6352301894108230E+00   6.9307487999999999E+00   2.5767979112152641E+00\n31 1   6.6405516098960931E+00   1.0895251200000001E+01   8.6227808094209522E+00\n32 1  -3.7858734844028064E-01   4.9532512000000004E+00   9.5151678851961101E+00\n33 1   6.2869001311807295E+00   2.9484203999999998E+00   8.7303993050090121E+00\n34 1  -2.4935869724918902E-02   8.8904204000000000E+00   9.4075493896080502E+00\n35 1   2.9697427097898110E+00   8.9355796000000005E+00   3.3615664914023622E+00\n36 1   9.2815787106954595E+00   2.9935796000000003E+00   2.6844164068033249E+00\n37 1   5.8575182718324248E+00   2.6584508000000002E+00   5.0387221473646200E+00\n38 1   6.3938031486528448E+00   8.6004508000000008E+00   1.0072607508410674E+00\n39 1   3.3991245691381162E+00   9.2255491999999997E+00   7.0532436490467534E+00\n40 1   2.8628396923176949E+00   3.2835491999999999E+00   1.1084705045570308E+01\n41 1   1.4893437800655995E-01   2.8331455999999999E+00   5.7630308985696610E+00\n42 1   1.2102387042478711E+01   8.7751456000000001E+00   2.8295199963602585E-01\n43 1   9.1077084629639806E+00   9.0508544000000004E+00   6.3289348978417133E+00\n44 1  -2.8457442015081695E+00   3.1088544000000002E+00   1.1809013796775348E+01\n45 1  -6.1400573582723883E-02   2.7618415999999999E+00   1.6106498440819952E+00\n46 1   1.2312721994067994E+01   8.7038415999999987E+00   4.4353330541236922E+00\n47 1   9.3180434145532658E+00   9.1221584000000018E+00   1.0481315952329380E+01\n48 1  -3.0560791530974529E+00   3.1801584000000003E+00   7.6566327422876821E+00\n49 2   1.1427082159552079E+01   2.9662463999999997E+00   3.5393183886096096E+00\n50 2   8.2423926093319233E-01   8.9082464000000012E+00   2.5066645095960776E+00\n51 2  -2.1704393185815376E+00   8.9177535999999993E+00   8.5526474078017660E+00\n52 2   8.4324035800373487E+00   2.9757536000000004E+00   9.5853012868152963E+00\n53 2   5.3565064819165702E+00   8.7941599999999998E-01   8.1802148612722938E+00\n54 2   9.0545777953924045E-01   6.8214159999999993E+00   9.9577338333447667E+00\n55 2   3.9001363590539699E+00   1.1004584000000001E+01   3.9117509351390796E+00\n56 2   8.3511850614313001E+00   5.0625840000000002E+00   2.1342319630666062E+00\n57 2   8.2986940044307591E+00   1.0885743999999999E+00   2.0278226640581871E+00\n58 2   3.9526274160545114E+00   7.0305744000000008E+00   4.0181602341475005E+00\n59 2   9.5794883653978147E-01   1.0795425600000000E+01   1.0064143132353188E+01\n60 2   5.3040154249160301E+00   4.8534255999999996E+00   8.0738055622638747E+00\n61 2   5.0934267916749469E+00   2.8521600000000000E+00   8.8392269971767146E-01\n62 2   7.1578946288103236E+00   8.7941599999999998E+00   5.1620601984880157E+00\n63 2   4.1632160492955945E+00   9.0318400000000008E+00   1.1208043096693704E+01\n64 2   2.0987482121602175E+00   3.0898400000000001E+00   6.9299055979233577E+00\n65 2  -3.7151518509987418E+00   1.0089516000000001E+00   1.1428116874188390E+01\n66 2   9.9771161124545564E+00   6.9509515999999998E+00   6.7098318204286711E+00\n67 2   1.2971794691969285E+01   1.0875048400000001E+01   6.6384892222298386E-01\n68 2  -7.2047327148401274E-01   4.9330484000000006E+00   5.3821339759827032E+00\n69 2  -1.0289872857341475E+00   9.3051719999999993E-01   5.3555316512305975E+00\n70 2   1.3280308706219419E+01   6.8725172000000008E+00   6.9045124697508931E-01\n71 2   1.0285630126704689E+01   1.0953482800000000E+01   6.7364341451807759E+00\n72 2  -4.0236658652488773E+00   5.0114828000000005E+00   1.1401514549436286E+01\n73 2   8.3041478910950666E+00   1.4652972000000002E+00   1.1998857659779006E+01\n74 2  -2.0421836296392564E+00   7.4072971999999995E+00   6.1390910348380556E+00\n75 2   9.5249494987547301E-01   1.0418702800000000E+01   9.3108136632368069E-02\n76 2   1.1298826470609797E+01   4.4767028000000000E+00   5.9528747615733186E+00\n77 2   1.1298611184610881E+01   1.6780207999999999E+00   6.1656933595901604E+00\n78 2  -5.0366469231550672E+00   7.6200207999999998E+00   1.1972255335026901E+01\n79 2  -2.0419683436403382E+00   1.0205979200000000E+01   5.9262724368212139E+00\n80 2   1.4293289764125610E+01   4.2639792000000005E+00   1.1971046138447285E-01\n81 2   9.1488021433547946E+00   2.9757536000000004E+00   4.9685887457454339E+00\n82 2   3.1025192771304759E+00   8.9177535999999993E+00   1.0773941524602535E+00\n83 2   1.0784069761574688E-01   8.9082464000000012E+00   7.1233770506659404E+00\n84 2   6.1541235638400646E+00   2.9662463999999997E+00   1.1014571643951122E+01\n85 2   1.1536023277392626E+00   1.7552668000000000E+00   1.1303569626485352E+01\n86 2   5.1083619337165480E+00   7.6972667999999995E+00   6.8343790681317094E+00\n87 2   8.1030405132312779E+00   1.0128733200000001E+01   7.8839616992602202E-01\n88 2   4.1482809072539908E+00   4.1867331999999999E+00   5.2575867282796667E+00\n89 2   3.8575184786178740E+00   1.4605436000000001E+00   5.3059545914653112E+00\n90 2   8.3938029418673974E+00   7.4025436000000004E+00   7.4002830674037579E-01\n91 2   5.3991243623526675E+00   1.0423456400000001E+01   6.7860112049460621E+00\n92 2   8.6283989910314407E-01   4.4814563999999999E+00   1.1351937489670998E+01\n93 2  -1.1647273351863610E+00   2.8010587999999998E+00   1.0286635303007156E+01\n94 2   7.4266915966421729E+00   8.7430588000000000E+00   7.8513133916099056E+00\n95 2   1.0421370176156902E+01   9.0829412000000005E+00   1.8053304934042180E+00\n96 2   1.8299512443283681E+00   3.1409411999999999E+00   4.2406524048014687E+00\n97 2   8.4247104603828795E+00   4.2544719999999997E-01   8.2588126389489691E+00\n98 2  -2.1627461989270667E+00   6.3674472000000009E+00   9.8791360556680914E+00\n99 2   8.3193238058766239E-01   1.1458552800000000E+01   3.8331531574624051E+00\n100 2   1.1419389039897609E+01   5.5165528000000004E+00   2.2128297407432820E+00\n101 2   1.0936796418726178E+01   7.4156159999999993E-01   2.0205674845803405E+00\n102 2   1.3145250017590928E+00   6.6835616000000000E+00   4.0254154136253462E+00\n103 2  -1.6801535777556365E+00   1.1142438400000000E+01   1.0071398311831034E+01\n104 2   7.9421178392114484E+00   5.2004384000000003E+00   8.0665503827860281E+00\n105 2  -4.2270609982025480E+00   2.4302779999999999E+00   9.3374159879888623E+00\n106 2   1.0489025259658359E+01   8.3722779999999997E+00   8.8005327066281982E+00\n107 2   1.3483703839173089E+01   9.4537220000000008E+00   2.7545498084225111E+00\n108 2  -1.2323824186878187E+00   3.5117219999999998E+00   3.2914330897831761E+00\n109 2   5.9652557811310523E+00   9.4477800000000001E-01   3.4268631067029833E+00\n110 2   6.2860656393542182E+00   6.8867780000000005E+00   2.6191197915027038E+00\n111 2   3.2913870598394892E+00   1.0939222000000001E+01   8.6651026897083909E+00\n112 2   2.9705772016163232E+00   4.9972219999999998E+00   9.4728460049086696E+00\n113 2   8.7597168992464747E-01   5.1576560000000005E-01   7.5332946911642864E+00\n114 2   5.3859925715311645E+00   6.4577656000000001E+00   1.0604654003452776E+01\n115 2   8.3806711510458936E+00   1.1368234400000000E+01   4.5586711052470879E+00\n116 2   3.8706502694393770E+00   5.4262344000000002E+00   1.4873117929585991E+00\n117 2   3.8480550764059558E+00   5.1220040000000000E-01   1.6191142201394828E+00\n118 2   8.4032663440793165E+00   6.4542004000000004E+00   4.4268686780662039E+00\n119 2   5.4085877645645866E+00   1.1371799599999999E+01   1.0472851576271891E+01\n120 2   8.5337649689122586E-01   5.4297995999999999E+00   7.6650971183451704E+00\n121 2   3.4757056949440797E+00   2.4742487999999998E+00   9.1209698002330999E+00\n122 2   2.7862585665117328E+00   8.4162488000000000E+00   9.0169788943839624E+00\n123 2   5.7809371460264618E+00   9.4097512000000005E+00   2.9709959961782748E+00\n124 2   6.4703842744588087E+00   3.4677512000000004E+00   3.0749869020274123E+00\n125 2   1.3936508439354220E+01   1.0172703999999999E+00   2.6191197915027034E+00\n126 2  -1.6851870188689482E+00   6.9592704000000003E+00   3.4268631067029833E+00\n127 2  -4.6798655983836772E+00   1.0866729599999999E+01   9.4728460049086696E+00\n128 2   1.0941829859839491E+01   4.9247296000000000E+00   8.6651026897083909E+00\n129 2   3.7852278917290239E+00   1.2264288000000001E+00   1.1524852600559679E+01\n130 2   2.4767363697267886E+00   7.1684288000000000E+00   6.6130960940573811E+00\n131 2   5.4714149492415176E+00   1.0657571200000001E+01   5.6711319585169406E-01\n132 2   6.7799064712437520E+00   4.7155712000000003E+00   5.4788697023539941E+00\n133 2   7.3392329837052301E+00   2.3102496000000001E+00   6.8428434441891959E+00\n134 2  -1.0772687222494177E+00   8.2522496000000007E+00   1.1295105250427865E+01\n135 2   1.9174098572653118E+00   9.5737503999999998E+00   5.2491223522221784E+00\n136 2   1.0333911563219958E+01   3.6317504000000000E+00   7.9686054598351042E-01\n137 2   2.2545766691676814E+00   2.4587995999999999E+00   1.6904568183383102E+00\n138 2   9.9967447513175891E+00   8.4007995999999991E+00   4.3555260798673769E+00\n139 2   7.0020661718028601E+00   9.4252004000000014E+00   1.0401508978073064E+01\n140 2  -7.4010191034704809E-01   3.4832004000000003E+00   7.7364397165439973E+00\n141 2  -2.0731956466969059E+00   1.1479944000000002E+00   8.2116539723429653E+00\n142 2   8.3351599081527183E+00   7.0899944000000001E+00   9.9262947222740969E+00\n143 2   1.1329838487667448E+01   1.0736005600000000E+01   3.8803118240684094E+00\n144 2   9.2148293281782356E-01   4.7940056000000002E+00   2.1656710741372778E+00\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE_external/hdnnp-data/input.nn",
    "content": "###############################################################################\n# HDNNP for copper sulfide Cu2S\n###############################################################################\n# Length unit     : Angstrom\n# Energy unit     : eV\n# Reference method: PBE\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.8640662064628053E+00\nconv_energy   7.3890846653659121E+00\nconv_length   6.1376931796181502E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type.\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          40             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   2              # Training parallelization used (0 = Serial, 1-4 = MSEKF implementations (4-fastest)).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2 10 1 15 2    # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 3\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.02315        # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               1              # Write energy comparison.\nwrite_trainforces               5              # Write force comparison.\nwrite_weights_epoch             1              # Write weights.\nwrite_neuronstats               5              # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE_external/hdnnp-data/nnp-train.log.0000",
    "content": "\n*** SETUP: MPI ****************************************************************\n\nNumber of processors: 16\nProcess 1 of 16 (rank 0): n51-048.vsc3plus.xcat\nProcess 2 of 16 (rank 1): n51-048.vsc3plus.xcat\nProcess 3 of 16 (rank 2): n51-048.vsc3plus.xcat\nProcess 4 of 16 (rank 3): n51-048.vsc3plus.xcat\nProcess 5 of 16 (rank 4): n51-048.vsc3plus.xcat\nProcess 6 of 16 (rank 5): n51-048.vsc3plus.xcat\nProcess 7 of 16 (rank 6): n51-048.vsc3plus.xcat\nProcess 8 of 16 (rank 7): n51-048.vsc3plus.xcat\nProcess 9 of 16 (rank 8): n51-048.vsc3plus.xcat\nProcess 10 of 16 (rank 9): n51-048.vsc3plus.xcat\nProcess 11 of 16 (rank 10): n51-048.vsc3plus.xcat\nProcess 12 of 16 (rank 11): n51-048.vsc3plus.xcat\nProcess 13 of 16 (rank 12): n51-048.vsc3plus.xcat\nProcess 14 of 16 (rank 13): n51-048.vsc3plus.xcat\nProcess 15 of 16 (rank 14): n51-048.vsc3plus.xcat\nProcess 16 of 16 (rank 15): n51-048.vsc3plus.xcat\n*******************************************************************************\n\n*******************************************************************************\n\n   NNP LIBRARY v0.1.0\n   ------------------\n\nGit branch  : master\nGit revision: 7f7427e (7f7427e692ba496c08cde43f02c65ec58de915fa)\n\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 321 lines.\nFound 182 lines with keywords.\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is used.\nMean energy per atom     :  -3.8640662064628053E+00\nConversion factor energy :   7.3890846653659121E+00\nConversion factor length :   6.1376931796181502E+00\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  S ( 16)\nElement  1: Cu ( 29)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:   0.00000000E+00\nElement  1:   0.00000000E+00\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_POLY2 (6)\nx := (r - rc * alpha) / (rc - rc * alpha)\nf(x) = ((15 - 6x)x - 10)x^3 + 1\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  S :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  S  2  S    5.309E-02 9.207E+00         3.683E+01  6 0.00   105\n   2  S  2 Cu    5.309E-02 9.207E+00         3.683E+01  6 0.00   115\n   3  S  2  S    5.309E-02 1.228E+01         3.683E+01  6 0.00   106\n   4  S  2 Cu    5.309E-02 1.228E+01         3.683E+01  6 0.00   116\n   5  S  2  S    5.309E-02 1.534E+01         3.683E+01  6 0.00   107\n   6  S  2 Cu    5.309E-02 1.534E+01         3.683E+01  6 0.00   117\n   7  S  2 Cu    5.309E-02 1.841E+01         3.683E+01  6 0.00   118\n   8  S  3  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   163\n   9  S  3  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   176\n  10  S  3 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   189\n  11  S  3  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   164\n  12  S  3  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   177\n  13  S  3 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   190\n  14  S  3  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   165\n  15  S  3  S Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   178\n  16  S  3 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   191\n  17  S  3  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   166\n  18  S  3  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   179\n  19  S  3 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   192\n  20  S  3  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   159\n  21  S  3  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   172\n  22  S  3 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   185\n  23  S  3  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   160\n  24  S  3  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   173\n  25  S  3 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   186\n  26  S  3  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   161\n  27  S  3  S Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   174\n  28  S  3 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   187\n  29  S  3  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   162\n  30  S  3  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   175\n  31  S  3 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   188\n  32  S  3  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   155\n  33  S  3  S Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   168\n  34  S  3  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   156\n  35  S  3  S Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   169\n  36  S  3 Cu Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   182\n  37  S  3  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   158\n  38  S  3  S Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   171\n  39  S  9  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   251\n  40  S  9  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   264\n  41  S  9 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   277\n  42  S  9  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   252\n  43  S  9  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   265\n  44  S  9 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   278\n  45  S  9  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   253\n  46  S  9  S Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   266\n  47  S  9 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   279\n  48  S  9  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   254\n  49  S  9  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   267\n  50  S  9 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   280\n  51  S  9  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   247\n  52  S  9  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   260\n  53  S  9 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   273\n  54  S  9  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   248\n  55  S  9  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   261\n  56  S  9 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   274\n  57  S  9  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   249\n  58  S  9  S Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   262\n  59  S  9 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   275\n  60  S  9  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   250\n  61  S  9  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   263\n  62  S  9 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   276\n  63  S  9  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   243\n  64  S  9  S Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   256\n  65  S  9 Cu Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   269\n  66  S  9  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   244\n  67  S  9  S Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   257\n  68  S  9 Cu Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   270\n  69  S  9  S Cu 5.898E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   258\n  70  S  9  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   246\n  71  S  9  S Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   259\n  72  S  9 Cu Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   272\n-------------------------------------------------------------------------------\nShort range atomic symmetry functions element Cu :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1 Cu  2  S    5.309E-02 9.207E+00         3.683E+01  6 0.00   126\n   2 Cu  2  S    5.309E-02 1.228E+01         3.683E+01  6 0.00   127\n   3 Cu  2 Cu    5.309E-02 1.228E+01         3.683E+01  6 0.00   137\n   4 Cu  2  S    5.309E-02 1.534E+01         3.683E+01  6 0.00   128\n   5 Cu  2 Cu    5.309E-02 1.534E+01         3.683E+01  6 0.00   138\n   6 Cu  2  S    5.309E-02 1.841E+01         3.683E+01  6 0.00   129\n   7 Cu  2 Cu    5.309E-02 1.841E+01         3.683E+01  6 0.00   139\n   8 Cu  2  S    5.309E-02 2.455E+01         3.683E+01  6 0.00   131\n   9 Cu  2  S    5.309E-02 3.069E+01         3.683E+01  6 0.00   133\n  10 Cu  3  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   203\n  11 Cu  3  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   216\n  12 Cu  3 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   229\n  13 Cu  3  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   204\n  14 Cu  3  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   217\n  15 Cu  3 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   230\n  16 Cu  3  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   205\n  17 Cu  3 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   231\n  18 Cu  3  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   206\n  19 Cu  3  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   219\n  20 Cu  3 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   232\n  21 Cu  3  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   199\n  22 Cu  3  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   212\n  23 Cu  3 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   225\n  24 Cu  3  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   200\n  25 Cu  3  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   213\n  26 Cu  3 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   226\n  27 Cu  3  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   201\n  28 Cu  3 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   227\n  29 Cu  3  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   202\n  30 Cu  3  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   215\n  31 Cu  3 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   228\n  32 Cu  3  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   195\n  33 Cu  3  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   196\n  34 Cu  3  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   198\n  35 Cu  9  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   291\n  36 Cu  9  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   304\n  37 Cu  9 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   317\n  38 Cu  9  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   292\n  39 Cu  9  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   305\n  40 Cu  9 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   318\n  41 Cu  9  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   293\n  42 Cu  9  S Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   306\n  43 Cu  9 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   319\n  44 Cu  9  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   294\n  45 Cu  9  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   307\n  46 Cu  9 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   320\n  47 Cu  9  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   287\n  48 Cu  9  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   300\n  49 Cu  9 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   313\n  50 Cu  9  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   288\n  51 Cu  9  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   301\n  52 Cu  9 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   314\n  53 Cu  9  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   289\n  54 Cu  9  S Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   302\n  55 Cu  9 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   315\n  56 Cu  9  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   290\n  57 Cu  9  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   303\n  58 Cu  9 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   316\n  59 Cu  9  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   283\n  60 Cu  9  S Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   296\n  61 Cu  9 Cu Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   309\n  62 Cu  9  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   284\n  63 Cu  9  S Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   297\n  64 Cu  9 Cu Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   310\n  65 Cu  9  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   286\n  66 Cu  9  S Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   299\n-------------------------------------------------------------------------------\nMinimum cutoff radius for element  S: 36.826159\nMinimum cutoff radius for element Cu: 36.826159\nMaximum cutoff radius (global)      : 36.826159\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function group index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  S :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  S  2  S            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 9.207E+00                 -  -    -   104    1    1  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   105    2    3  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   106    3    5  \n   2  S  2 Cu            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 9.207E+00                 -  -    -   114    1    2  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   115    2    4  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   116    3    6  \n   -  -  -  -    5.309E-02 1.841E+01                 -  -    -   117    4    7  \n   3  S  3  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   162    1    8 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   163    2   11 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   164    3   14 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   165    4   17 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   158    5   20 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   159    6   23 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   160    7   26 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   161    8   29 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   154    9   32 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   155   10   34 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   157   11   37 0\n   4  S  3  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   175    1    9 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   176    2   12 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   177    3   15 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   178    4   18 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   171    5   21 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   172    6   24 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   173    7   27 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   174    8   30 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   167    9   33 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   168   10   35 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   170   11   38 0\n   5  S  3 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   188    1   10 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   189    2   13 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   190    3   16 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   191    4   19 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   184    5   22 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   185    6   25 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   186    7   28 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   187    8   31 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   181    9   36 1\n   6  S  9  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   250    1   39 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   251    2   42 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   252    3   45 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   253    4   48 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   246    5   51 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   247    6   54 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   248    7   57 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   249    8   60 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   242    9   63 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   243   10   66 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   245   11   70 0\n   7  S  9  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   263    1   40 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   264    2   43 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   265    3   46 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   266    4   49 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   259    5   52 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   260    6   55 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   261    7   58 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   262    8   61 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   255    9   64 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   256   10   67 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  6.0         -  -    -   257   11   69 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   258   12   71 0\n   8  S  9 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   276    1   41 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   277    2   44 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   278    3   47 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   279    4   50 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   272    5   53 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   273    6   56 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   274    7   59 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   275    8   62 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   268    9   65 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   269   10   68 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   271   11   72 0\n-------------------------------------------------------------------------------\nShort range atomic symmetry function groups element Cu :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1 Cu  2  S            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 9.207E+00                 -  -    -   125    1    1  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   126    2    2  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   127    3    4  \n   -  -  -  -    5.309E-02 1.841E+01                 -  -    -   128    4    6  \n   -  -  -  -    5.309E-02 2.455E+01                 -  -    -   130    5    8  \n   -  -  -  -    5.309E-02 3.069E+01                 -  -    -   132    6    9  \n   2 Cu  2 Cu            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   136    1    3  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   137    2    5  \n   -  -  -  -    5.309E-02 1.841E+01                 -  -    -   138    3    7  \n   3 Cu  3  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   202    1   10 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   203    2   13 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   204    3   16 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   205    4   18 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   198    5   21 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   199    6   24 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   200    7   27 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   201    8   29 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   194    9   32 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   195   10   33 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   197   11   34 0\n   4 Cu  3  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   215    1   11 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   216    2   14 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   218    3   19 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   211    4   22 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   212    5   25 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   214    6   30 0\n   5 Cu  3 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   228    1   12 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   229    2   15 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   230    3   17 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   231    4   20 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   224    5   23 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   225    6   26 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   226    7   28 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   227    8   31 0\n   6 Cu  9  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   290    1   35 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   291    2   38 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   292    3   41 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   293    4   44 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   286    5   47 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   287    6   50 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   288    7   53 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   289    8   56 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   282    9   59 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   283   10   62 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   285   11   65 0\n   7 Cu  9  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   303    1   36 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   304    2   39 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   305    3   42 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   306    4   45 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   299    5   48 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   300    6   51 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   301    7   54 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   302    8   57 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   295    9   60 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   296   10   63 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   298   11   66 0\n   8 Cu  9 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   316    1   37 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   317    2   40 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   318    3   43 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   319    4   46 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   312    5   49 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   313    6   52 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   314    7   55 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   315    8   58 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   308    9   61 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   309   10   64 0\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic short range NN for element  S :\nNumber of weights    :   2450\nNumber of biases     :     51\nNumber of connections:   2501\nArchitecture       72   25   25    1\n-------------------------------------------------------------------------------\n   1   G   p   p   l\n   2   G   p   p    \n   3   G   p   p    \n   4   G   p   p    \n   5   G   p   p    \n   6   G   p   p    \n   7   G   p   p    \n   8   G   p   p    \n   9   G   p   p    \n  10   G   p   p    \n  11   G   p   p    \n  12   G   p   p    \n  13   G   p   p    \n  14   G   p   p    \n  15   G   p   p    \n  16   G   p   p    \n  17   G   p   p    \n  18   G   p   p    \n  19   G   p   p    \n  20   G   p   p    \n  21   G   p   p    \n  22   G   p   p    \n  23   G   p   p    \n  24   G   p   p    \n  25   G   p   p    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n  37   G            \n  38   G            \n  39   G            \n  40   G            \n  41   G            \n  42   G            \n  43   G            \n  44   G            \n  45   G            \n  46   G            \n  47   G            \n  48   G            \n  49   G            \n  50   G            \n  51   G            \n  52   G            \n  53   G            \n  54   G            \n  55   G            \n  56   G            \n  57   G            \n  58   G            \n  59   G            \n  60   G            \n  61   G            \n  62   G            \n  63   G            \n  64   G            \n  65   G            \n  66   G            \n  67   G            \n  68   G            \n  69   G            \n  70   G            \n  71   G            \n  72   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element Cu :\nNumber of weights    :   2300\nNumber of biases     :     51\nNumber of connections:   2351\nArchitecture       66   25   25    1\n-------------------------------------------------------------------------------\n   1   G   p   p   l\n   2   G   p   p    \n   3   G   p   p    \n   4   G   p   p    \n   5   G   p   p    \n   6   G   p   p    \n   7   G   p   p    \n   8   G   p   p    \n   9   G   p   p    \n  10   G   p   p    \n  11   G   p   p    \n  12   G   p   p    \n  13   G   p   p    \n  14   G   p   p    \n  15   G   p   p    \n  16   G   p   p    \n  17   G   p   p    \n  18   G   p   p    \n  19   G   p   p    \n  20   G   p   p    \n  21   G   p   p    \n  22   G   p   p    \n  23   G   p   p    \n  24   G   p   p    \n  25   G   p   p    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n  37   G            \n  38   G            \n  39   G            \n  40   G            \n  41   G            \n  42   G            \n  43   G            \n  44   G            \n  45   G            \n  46   G            \n  47   G            \n  48   G            \n  49   G            \n  50   G            \n  51   G            \n  52   G            \n  53   G            \n  54   G            \n  55   G            \n  56   G            \n  57   G            \n  58   G            \n  59   G            \n  60   G            \n  61   G            \n  62   G            \n  63   G            \n  64   G            \n  65   G            \n  66   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALESIGMA (4)\nGs = Smin + (Smax - Smin) * (G - Gmean) / Gsigma\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  S :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  9.17E-08  7.06E-01  2.24E-02  9.64E-02  1.04E+01  0.00  1.00 4\n   2  2.64E-01  2.47E+00  1.04E+00  1.94E-01  5.15E+00  0.00  1.00 4\n   3  1.55E-05  1.42E+00  5.53E-02  2.15E-01  4.65E+00  0.00  1.00 4\n   4  1.41E+00  4.74E+00  3.10E+00  3.59E-01  2.79E+00  0.00  1.00 4\n   5  9.80E-04  1.95E+00  1.14E-01  2.29E-01  4.37E+00  0.00  1.00 4\n   6  2.22E+00  6.07E+00  3.88E+00  3.93E-01  2.54E+00  0.00  1.00 4\n   7  1.03E+00  5.14E+00  2.58E+00  4.38E-01  2.28E+00  0.00  1.00 4\n   8  4.85E-03  3.91E-01  4.76E-02  2.78E-02  3.60E+01  0.00  1.00 4\n   9  9.32E-02  2.83E+00  6.02E-01  3.19E-01  3.13E+00  0.00  1.00 4\n  10  6.72E-01  4.49E+00  2.20E+00  4.15E-01  2.41E+00  0.00  1.00 4\n  11  2.21E-02  8.66E-01  1.41E-01  7.58E-02  1.32E+01  0.00  1.00 4\n  12  8.42E-01  7.07E+00  2.90E+00  7.31E-01  1.37E+00  0.00  1.00 4\n  13  1.45E+00  9.65E+00  4.37E+00  8.38E-01  1.19E+00  0.00  1.00 4\n  14  2.43E-06  5.30E-02  2.81E-04  1.65E-03  6.05E+02  0.00  1.00 4\n  15  4.38E-04  3.34E-01  1.51E-02  3.64E-02  2.75E+01  0.00  1.00 4\n  16  1.87E-02  5.31E-01  1.93E-01  5.38E-02  1.86E+01  0.00  1.00 4\n  17  5.64E-03  2.71E-01  3.62E-02  2.22E-02  4.50E+01  0.00  1.00 4\n  18  5.82E-01  3.04E+00  1.54E+00  2.90E-01  3.45E+00  0.00  1.00 4\n  19  3.55E-01  2.89E+00  1.25E+00  2.61E-01  3.84E+00  0.00  1.00 4\n  20  1.31E-03  2.10E-01  1.65E-02  1.62E-02  6.18E+01  0.00  1.00 4\n  21  3.36E-02  1.60E+00  2.67E-01  1.92E-01  5.22E+00  0.00  1.00 4\n  22  3.53E-01  2.60E+00  1.20E+00  2.39E-01  4.19E+00  0.00  1.00 4\n  23  5.63E-03  4.83E-01  4.87E-02  4.56E-02  2.19E+01  0.00  1.00 4\n  24  3.56E-01  3.94E+00  1.35E+00  4.31E-01  2.32E+00  0.00  1.00 4\n  25  7.14E-01  5.41E+00  2.34E+00  4.75E-01  2.11E+00  0.00  1.00 4\n  26  6.03E-07  2.43E-02  1.04E-04  6.95E-04  1.44E+03  0.00  1.00 4\n  27  1.42E-04  1.88E-01  6.73E-03  1.89E-02  5.30E+01  0.00  1.00 4\n  28  7.67E-03  2.89E-01  9.68E-02  2.86E-02  3.50E+01  0.00  1.00 4\n  29  1.46E-03  1.28E-01  1.25E-02  1.22E-02  8.20E+01  0.00  1.00 4\n  30  2.43E-01  1.58E+00  7.31E-01  1.60E-01  6.24E+00  0.00  1.00 4\n  31  1.57E-01  1.50E+00  6.22E-01  1.39E-01  7.21E+00  0.00  1.00 4\n  32  8.03E-08  9.10E-03  1.18E-04  7.29E-04  1.37E+03  0.00  1.00 4\n  33  3.84E-05  4.69E-02  2.29E-03  6.35E-03  1.57E+02  0.00  1.00 4\n  34  2.51E-07  2.66E-02  3.52E-04  2.18E-03  4.59E+02  0.00  1.00 4\n  35  7.82E-04  1.21E-01  1.02E-02  1.56E-02  6.43E+01  0.00  1.00 4\n  36  6.08E-03  1.52E-01  4.53E-02  1.44E-02  6.93E+01  0.00  1.00 4\n  37  6.52E-08  6.90E-03  8.45E-05  5.18E-04  1.93E+03  0.00  1.00 4\n  38  5.10E-04  3.38E-02  5.05E-03  4.24E-03  2.36E+02  0.00  1.00 4\n  39  3.01E-01  3.92E+00  1.62E+00  3.61E-01  2.77E+00  0.00  1.00 4\n  40  2.92E+00  2.10E+01  1.07E+01  1.84E+00  5.42E-01  0.00  1.00 4\n  41  5.83E+00  3.32E+01  1.69E+01  2.84E+00  3.52E-01  0.00  1.00 4\n  42  2.90E-01  3.42E+00  1.35E+00  2.98E-01  3.35E+00  0.00  1.00 4\n  43  3.32E+00  2.00E+01  1.05E+01  1.84E+00  5.45E-01  0.00  1.00 4\n  44  5.60E+00  2.95E+01  1.47E+01  2.43E+00  4.11E-01  0.00  1.00 4\n  45  7.32E-02  1.42E+00  4.62E-01  1.06E-01  9.43E+00  0.00  1.00 4\n  46  7.44E-01  6.16E+00  3.09E+00  5.27E-01  1.90E+00  0.00  1.00 4\n  47  1.03E+00  9.55E+00  4.66E+00  8.82E-01  1.13E+00  0.00  1.00 4\n  48  5.34E-02  6.08E-01  2.01E-01  4.75E-02  2.11E+01  0.00  1.00 4\n  49  1.10E+00  5.34E+00  2.92E+00  4.91E-01  2.04E+00  0.00  1.00 4\n  50  9.37E-01  6.05E+00  2.81E+00  5.09E-01  1.97E+00  0.00  1.00 4\n  51  1.14E-01  2.31E+00  7.57E-01  2.08E-01  4.80E+00  0.00  1.00 4\n  52  1.43E+00  1.33E+01  5.88E+00  1.22E+00  8.22E-01  0.00  1.00 4\n  53  3.55E+00  2.13E+01  1.09E+01  1.88E+00  5.32E-01  0.00  1.00 4\n  54  1.10E-01  2.08E+00  6.31E-01  1.75E-01  5.70E+00  0.00  1.00 4\n  55  1.65E+00  1.24E+01  5.77E+00  1.19E+00  8.38E-01  0.00  1.00 4\n  56  3.33E+00  1.87E+01  9.22E+00  1.58E+00  6.34E-01  0.00  1.00 4\n  57  2.75E-02  9.17E-01  2.15E-01  6.17E-02  1.62E+01  0.00  1.00 4\n  58  3.62E-01  3.89E+00  1.71E+00  3.48E-01  2.87E+00  0.00  1.00 4\n  59  5.66E-01  6.16E+00  2.96E+00  5.90E-01  1.69E+00  0.00  1.00 4\n  60  2.02E-02  3.35E-01  9.30E-02  2.76E-02  3.62E+01  0.00  1.00 4\n  61  5.54E-01  3.19E+00  1.59E+00  3.05E-01  3.28E+00  0.00  1.00 4\n  62  5.38E-01  3.63E+00  1.66E+00  3.14E-01  3.19E+00  0.00  1.00 4\n  63  9.67E-05  1.49E-01  4.32E-03  8.27E-03  1.21E+02  0.00  1.00 4\n  64  1.20E-02  1.13E+00  1.28E-01  1.34E-01  7.47E+00  0.00  1.00 4\n  65  2.08E-01  1.86E+00  8.23E-01  1.78E-01  5.60E+00  0.00  1.00 4\n  66  8.79E-05  1.26E-01  4.40E-03  1.18E-02  8.46E+01  0.00  1.00 4\n  67  1.34E-02  8.78E-01  1.18E-01  1.13E-01  8.81E+00  0.00  1.00 4\n  68  1.77E-01  1.43E+00  6.21E-01  1.29E-01  7.73E+00  0.00  1.00 4\n  69  2.86E-03  3.73E-01  3.77E-02  3.72E-02  2.69E+01  0.00  1.00 4\n  70  1.59E-05  2.60E-02  7.25E-04  2.49E-03  4.02E+02  0.00  1.00 4\n  71  4.72E-03  1.60E-01  2.88E-02  1.94E-02  5.15E+01  0.00  1.00 4\n  72  1.53E-02  1.93E-01  6.97E-02  1.78E-02  5.62E+01  0.00  1.00 4\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element Cu :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  2.47E-02  1.51E+00  5.19E-01  1.23E-01  8.13E+00  0.00  1.00 4\n   2  2.50E-01  2.69E+00  1.55E+00  2.29E-01  4.37E+00  0.00  1.00 4\n   3  1.86E-03  3.82E+00  1.12E+00  3.99E-01  2.50E+00  0.00  1.00 4\n   4  6.93E-01  3.94E+00  1.94E+00  2.80E-01  3.57E+00  0.00  1.00 4\n   5  5.22E-02  5.98E+00  2.79E+00  6.88E-01  1.45E+00  0.00  1.00 4\n   6  3.47E-01  2.81E+00  1.29E+00  2.50E-01  3.99E+00  0.00  1.00 4\n   7  5.67E-01  6.01E+00  3.40E+00  5.38E-01  1.86E+00  0.00  1.00 4\n   8  8.22E-02  2.16E+00  9.59E-01  2.21E-01  4.53E+00  0.00  1.00 4\n   9  9.75E-02  8.05E-01  3.96E-01  7.28E-02  1.37E+01  0.00  1.00 4\n  10  7.56E-02  1.22E+00  4.24E-01  1.10E-01  9.07E+00  0.00  1.00 4\n  11  3.86E-01  3.42E+00  1.54E+00  2.98E-01  3.35E+00  0.00  1.00 4\n  12  1.27E-01  3.34E+00  9.07E-01  3.08E-01  3.25E+00  0.00  1.00 4\n  13  3.58E-02  2.31E+00  4.52E-01  2.05E-01  4.87E+00  0.00  1.00 4\n  14  1.74E+00  9.19E+00  5.03E+00  7.70E-01  1.30E+00  0.00  1.00 4\n  15  5.61E-01  6.92E+00  2.56E+00  7.04E-01  1.42E+00  0.00  1.00 4\n  16  2.73E-03  2.67E-01  6.84E-02  1.84E-02  5.43E+01  0.00  1.00 4\n  17  1.50E-04  2.89E-01  3.24E-02  2.15E-02  4.66E+01  0.00  1.00 4\n  18  9.70E-03  7.00E-01  7.45E-02  9.21E-02  1.09E+01  0.00  1.00 4\n  19  7.56E-01  3.87E+00  2.13E+00  2.95E-01  3.39E+00  0.00  1.00 4\n  20  2.30E-01  2.24E+00  8.48E-01  2.20E-01  4.54E+00  0.00  1.00 4\n  21  3.17E-02  6.93E-01  2.02E-01  6.20E-02  1.61E+01  0.00  1.00 4\n  22  1.63E-01  1.90E+00  8.13E-01  1.70E-01  5.88E+00  0.00  1.00 4\n  23  4.36E-02  1.85E+00  4.34E-01  1.65E-01  6.07E+00  0.00  1.00 4\n  24  1.18E-02  1.33E+00  2.02E-01  1.24E-01  8.08E+00  0.00  1.00 4\n  25  9.56E-01  5.16E+00  2.73E+00  4.50E-01  2.22E+00  0.00  1.00 4\n  26  2.13E-01  3.76E+00  1.23E+00  3.89E-01  2.57E+00  0.00  1.00 4\n  27  1.08E-03  1.62E-01  3.44E-02  1.03E-02  9.67E+01  0.00  1.00 4\n  28  4.15E-05  1.36E-01  1.35E-02  9.43E-03  1.06E+02  0.00  1.00 4\n  29  2.98E-03  3.97E-01  3.29E-02  5.36E-02  1.87E+01  0.00  1.00 4\n  30  4.09E-01  2.15E+00  1.13E+00  1.66E-01  6.04E+00  0.00  1.00 4\n  31  8.77E-02  1.12E+00  3.97E-01  1.16E-01  8.62E+00  0.00  1.00 4\n  32  2.00E-05  1.76E-02  1.42E-03  1.36E-03  7.35E+02  0.00  1.00 4\n  33  5.27E-06  4.46E-02  1.71E-03  4.26E-03  2.35E+02  0.00  1.00 4\n  34  8.83E-07  1.21E-02  4.19E-04  1.52E-03  6.60E+02  0.00  1.00 4\n  35  1.27E+00  8.93E+00  4.26E+00  5.94E-01  1.68E+00  0.00  1.00 4\n  36  4.30E+00  2.47E+01  1.43E+01  1.97E+00  5.08E-01  0.00  1.00 4\n  37  2.97E+00  2.58E+01  1.18E+01  2.36E+00  4.23E-01  0.00  1.00 4\n  38  4.87E-01  6.92E+00  2.94E+00  5.04E-01  1.98E+00  0.00  1.00 4\n  39  4.73E+00  2.48E+01  1.42E+01  1.97E+00  5.07E-01  0.00  1.00 4\n  40  2.79E+00  2.29E+01  1.03E+01  2.05E+00  4.87E-01  0.00  1.00 4\n  41  5.20E-01  3.06E+00  1.19E+00  2.26E-01  4.43E+00  0.00  1.00 4\n  42  1.07E+00  7.23E+00  3.99E+00  5.81E-01  1.72E+00  0.00  1.00 4\n  43  8.46E-01  7.53E+00  3.40E+00  7.11E-01  1.41E+00  0.00  1.00 4\n  44  7.08E-02  1.30E+00  3.18E-01  1.36E-01  7.34E+00  0.00  1.00 4\n  45  1.37E+00  6.40E+00  3.75E+00  5.02E-01  1.99E+00  0.00  1.00 4\n  46  6.40E-01  4.72E+00  1.99E+00  4.28E-01  2.34E+00  0.00  1.00 4\n  47  8.65E-01  6.12E+00  2.74E+00  4.06E-01  2.47E+00  0.00  1.00 4\n  48  2.53E+00  1.58E+01  8.79E+00  1.28E+00  7.81E-01  0.00  1.00 4\n  49  1.57E+00  1.61E+01  6.94E+00  1.58E+00  6.35E-01  0.00  1.00 4\n  50  2.45E-01  4.57E+00  1.78E+00  3.33E-01  3.00E+00  0.00  1.00 4\n  51  2.84E+00  1.57E+01  8.71E+00  1.28E+00  7.82E-01  0.00  1.00 4\n  52  1.48E+00  1.41E+01  5.96E+00  1.34E+00  7.46E-01  0.00  1.00 4\n  53  2.95E-01  2.16E+00  7.69E-01  1.64E-01  6.08E+00  0.00  1.00 4\n  54  6.12E-01  4.74E+00  2.44E+00  3.84E-01  2.61E+00  0.00  1.00 4\n  55  4.30E-01  4.73E+00  2.01E+00  4.76E-01  2.10E+00  0.00  1.00 4\n  56  3.34E-02  8.33E-01  1.73E-01  8.80E-02  1.14E+01  0.00  1.00 4\n  57  8.27E-01  3.95E+00  2.25E+00  3.13E-01  3.20E+00  0.00  1.00 4\n  58  3.12E-01  2.77E+00  1.11E+00  2.63E-01  3.80E+00  0.00  1.00 4\n  59  2.66E-02  5.68E-01  2.09E-01  4.91E-02  2.04E+01  0.00  1.00 4\n  60  7.25E-02  1.10E+00  4.58E-01  1.03E-01  9.67E+00  0.00  1.00 4\n  61  5.93E-03  1.25E+00  2.45E-01  1.10E-01  9.09E+00  0.00  1.00 4\n  62  3.60E-03  3.91E-01  8.91E-02  3.19E-02  3.14E+01  0.00  1.00 4\n  63  7.25E-02  1.09E+00  4.46E-01  1.02E-01  9.84E+00  0.00  1.00 4\n  64  5.47E-03  9.86E-01  1.95E-01  8.68E-02  1.15E+01  0.00  1.00 4\n  65  1.74E-04  5.69E-02  3.93E-03  6.00E-03  1.67E+02  0.00  1.00 4\n  66  2.10E-02  2.27E-01  9.55E-02  2.06E-02  4.86E+01  0.00  1.00 4\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 0\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** SETUP: RANDOM NUMBER GENERATOR ********************************************\n\nRandom number generator seed: 3\nSeed for rank 0: 3\nSeed for rank 1: 2365658986\nSeed for rank 2: 303761048\nSeed for rank 3: 3041471737\nSeed for rank 4: 3607553667\nSeed for rank 5: 1249426360\nSeed for rank 6: 521102280\nSeed for rank 7: 2193987840\nSeed for rank 8: 2445173525\nSeed for rank 9: 3835177981\nSeed for rank 10: 1877166739\nSeed for rank 11: 3849549514\nSeed for rank 12: 80522091\nSeed for rank 13: 539384825\nSeed for rank 14: 174507689\nSeed for rank 15: 890101386\nSeed for global RNG: 1064672149\n*******************************************************************************\n\n*** STRUCTURE DISTRIBUTION ****************************************************\n\nReading configurations from data file: input.data.\nTotal number of structures: 3965\nNumber of structures per processor: 247 (3) or 248 (13)\nDistributed 3965 structures, 118368544 bytes (112.89 MiB) transferred.\nNumber of local structures: 247\n*******************************************************************************\n\n*** DEFINE TRAINING/TEST SETS *************************************************\n\nDesired test set ratio      : 0.100000\nTotal number of energies    : 3965\nNumber of training energies : 3578\nNumber of test     energies : 387\nNumber of training forces   : 1545696\nNumber of test     forces   : 167184\nActual test set fraction    : 0.097604\n*******************************************************************************\n\n*** WRITE TRAINING/TEST SETS **************************************************\n\nWriting training/test set to files:\n - train.data\n - test.data\n*******************************************************************************\n\n*** WEIGHT INITIALIZATION *****************************************************\n\nInitial weights selected randomly in interval [-1.000000, 1.000000).\nWeights modified accoring to Glorot Bengio scheme.\nBiases set to zero.\n*******************************************************************************\n\n*** SETUP: TRAINING ***********************************************************\n\nForces will be used for training.\nForce update weight:   1.00E+01\nWeight update via Kalman filter selected: updaterType::UT_KALMANFILTER (1)\nMulti-stream Kalman filter training with non-blocking communication selected: ParallelMode::PM_MSEKFNB (2)\nNumber of streams       : 16\nStream of this processor: 0\nCombined updater for all elements selected: UpdateStrategy::US_COMBINED (0)\nNumber of weight updaters    : 1\nTotal fit parameters         : 4852\nSelection mode starting with epoch 0:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 0.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\nSelection mode starting with epoch 10:\nUpdate candidates selected according to error: SelectionMode::SM_SORT (1)\nSelection mode starting with epoch 15:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 0.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\n-------------------------------------------------------------------------------\nSymmetry function memory is reused (HIGH MEMORY USAGE!).\nTraining will be stopped after 40 epochs.\nEnergy comparison will be written every 1 epochs.\nForce comparison will be written every 5 epochs.\nWeights will be written every 1 epochs.\nNeuron statistics will be written every 5 epochs.\nTraining log with update information will be written to: train-log.out.\n-------------------------------------------------------------------------------\nFraction of energies used per epoch:    1.0000\nFraction of forces used per epoch  :    0.0232\nProjected energy updates per epoch :     224 (  9.1%)\nProjected forces updates per epoch :    2236 ( 90.9%)\nTotal projected updates per epoch  :    2460\nMulti-stream training uses 16 energies/forces per weight update.\nqtau is divided by number of projected updates per epoch.\netatau is divided by number of projected updates per epoch.\n-------------------------------------------------------------------------------\nCombined weight updater:\n-------------------------------------------------------------------------------\nKalmanType::KT_STANDARD (0)\nsizeState       = 4852\nsizeObservation = 16\nepsilon         =   1.0000E-02\nq0              =   1.0000E-02\nqtau            =   9.3575E-04\nqmin            =   1.0000E-06\neta0            =   1.0000E-02\netatau          =   9.3575E-04\netamax          =   1.0000E+00\nKalmanParallel::KP_NBCOMM (1)\nOpenMP threads used: 1\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** CALCULATE NEIGHBOR LISTS **************************************************\n\nCalculating neighbor lists for all structures.\nCutoff radius for neighbor lists: 36.826159\n*******************************************************************************\n\n*** TRAINING LOOP *************************************************************\n\nThe training loop output covers different RMSEs, update and\ntiming information. The following quantities are organized\naccording to the matrix scheme below:\n-------------------------------------------------------------------\nep ............ Epoch.\nEtrain_phys ... RMSE of training energies per atom (p. u.).\nEtest_phys .... RMSE of test     energies per atom (p. u.).\nEtrain_int .... RMSE of training energies per atom (i. u.).\nEtest_int ..... RMSE of test     energies per atom (i. u.).\nFtrain_phys ... RMSE of training forces (p. u.).\nFtest_phys .... RMSE of test     forces (p. u.).\nFtrain_int .... RMSE of training forces (i. u.).\nFtest_int ..... RMSE of test     forces (i. u.).\nE_count ....... Number of energy updates.\nF_count ....... Number of force  updates.\ncount ......... Total number of updates.\nt_train ....... Time for training (seconds).\nt_rmse ........ Time for RMSE calculation (seconds).\nt_epoch ....... Total time for this epoch (seconds).\nt_tot ......... Total time for all epochs (seconds).\nAbbreviations:\n  p. u. = physical units.\n  i. u. = internal units.\nNote: RMSEs in internal units (columns 5 + 6) are only present \n      if data set normalization is used.\n-------------------------------------------------------------------\n     1    2             3             4             5             6\nenergy   ep   Etrain_phys    Etest_phys    Etrain_int     Etest_int\nforces   ep   Ftrain_phys    Ftest_phys    Ftrain_int     Ftest_int\nupdate   ep       E_count       F_count         count\ntiming   ep       t_train        t_rmse       t_epoch         t_tot\n-------------------------------------------------------------------\nENERGY    0   1.91455E+00   1.85460E+00   1.41468E+01   1.37038E+01\nFORCES    0   3.95765E+00   3.81821E+00   4.76457E+00   4.59669E+00\nTIMING    0          0.00         36.72         36.84         36.84\n------\nENERGY    1   4.89186E-03   4.44070E-03   3.61464E-02   3.28127E-02\nFORCES    1   9.00338E-02   7.98956E-02   1.08390E-01   9.61853E-02\nUPDATE    1           223          2198          2421\nTIMING    1        591.73          2.88        594.74        631.57\n------\nENERGY    2   8.14646E-03   7.83106E-03   6.01949E-02   5.78643E-02\nFORCES    2   8.33764E-02   7.53830E-02   1.00376E-01   9.07526E-02\nUPDATE    2           223          2205          2428\nTIMING    2        581.29          2.88        584.28       1215.86\n------\nENERGY    3   1.46929E-03   1.41092E-03   1.08567E-02   1.04254E-02\nFORCES    3   7.14048E-02   6.44540E-02   8.59633E-02   7.75953E-02\nUPDATE    3           223          2304          2527\nTIMING    3        606.13          2.87        609.11       1824.97\n------\nENERGY    4   1.19764E-03   1.16880E-03   8.84947E-03   8.63635E-03\nFORCES    4   6.50925E-02   5.92062E-02   7.83639E-02   7.12775E-02\nUPDATE    4           223          2263          2486\nTIMING    4        594.00          2.86        596.98       2421.95\n------\nENERGY    5   3.46244E-03   3.20340E-03   2.55843E-02   2.36702E-02\nFORCES    5   6.32945E-02   5.82054E-02   7.61994E-02   7.00727E-02\nUPDATE    5           223          2168          2391\nTIMING    5        569.04          3.66        572.82       2994.77\n------\nENERGY    6   1.35889E-03   1.30765E-03   1.00410E-02   9.66235E-03\nFORCES    6   6.01682E-02   5.59752E-02   7.24357E-02   6.73878E-02\nUPDATE    6           223          2222          2445\nTIMING    6        582.19          2.88        585.18       3579.95\n------\nENERGY    7   1.10132E-03   1.06999E-03   8.13778E-03   7.90622E-03\nFORCES    7   6.09336E-02   5.61479E-02   7.33572E-02   6.75957E-02\nUPDATE    7           223          2220          2443\nTIMING    7        580.57          2.88        583.56       4163.52\n------\nENERGY    8   1.32085E-03   1.32122E-03   9.75985E-03   9.76257E-03\nFORCES    8   6.04221E-02   5.57148E-02   7.27413E-02   6.70743E-02\nUPDATE    8           223          2177          2400\nTIMING    8        570.35          2.87        573.33       4736.85\n------\nENERGY    9   1.21040E-03   1.20911E-03   8.94372E-03   8.93418E-03\nFORCES    9   6.07639E-02   5.61795E-02   7.31529E-02   6.76337E-02\nUPDATE    9           223          2219          2442\nTIMING    9        580.68          2.86        583.68       5320.52\n------\nINFO   Switching selection mode to SM_SORT (1).\nENERGY   10   1.58579E-03   1.73841E-03   1.17175E-02   1.28453E-02\nFORCES   10   6.52223E-02   6.36152E-02   7.85202E-02   7.65855E-02\nUPDATE   10           223          2275          2498\nTIMING   10        540.55          3.95        544.63       5865.15\n------\nENERGY   11   1.71933E-03   1.52765E-03   1.27043E-02   1.12880E-02\nFORCES   11   6.73072E-02   6.52751E-02   8.10303E-02   7.85838E-02\nUPDATE   11           223          2227          2450\nTIMING   11        530.01          3.05        533.20       6398.36\n------\nENERGY   12   1.91272E-03   2.18165E-03   1.41332E-02   1.61204E-02\nFORCES   12   7.01522E-02   6.84824E-02   8.44553E-02   8.24450E-02\nUPDATE   12           223          2267          2490\nTIMING   12        539.23          3.06        542.42       6940.78\n------\nENERGY   13   2.44192E-03   2.27489E-03   1.80435E-02   1.68094E-02\nFORCES   13   6.86417E-02   6.70474E-02   8.26368E-02   8.07175E-02\nUPDATE   13           223          2294          2517\nTIMING   13        545.08          3.01        548.22       7489.00\n------\nENERGY   14   2.26249E-03   2.34073E-03   1.67177E-02   1.72959E-02\nFORCES   14   6.90512E-02   6.75645E-02   8.31298E-02   8.13399E-02\nUPDATE   14           223          2288          2511\nTIMING   14        543.79          3.02        546.93       8035.93\n------\nINFO   Switching selection mode to SM_THRESHOLD (2).\nENERGY   15   1.06025E-03   1.07406E-03   7.83427E-03   7.93633E-03\nFORCES   15   5.73058E-02   5.50161E-02   6.89896E-02   6.62331E-02\nUPDATE   15           223          2238          2461\nTIMING   15        587.56          3.80        591.48       8627.41\n------\nENERGY   16   1.37488E-03   1.35568E-03   1.01591E-02   1.00172E-02\nFORCES   16   5.58823E-02   5.42190E-02   6.72759E-02   6.52735E-02\nUPDATE   16           223          2143          2366\nTIMING   16        560.83          2.88        563.83       9191.23\n------\nENERGY   17   1.27424E-03   1.31414E-03   9.41548E-03   9.71029E-03\nFORCES   17   5.58550E-02   5.41179E-02   6.72430E-02   6.51518E-02\nUPDATE   17           223          2203          2426\nTIMING   17        575.49          2.91        578.52       9769.76\n------\nENERGY   18   1.28910E-03   1.30698E-03   9.52530E-03   9.65742E-03\nFORCES   18   5.56228E-02   5.38312E-02   6.69636E-02   6.48066E-02\nUPDATE   18           223          2200          2423\nTIMING   18        574.57          2.86        577.55      10347.30\n------\nENERGY   19   1.12363E-03   1.14564E-03   8.30256E-03   8.46527E-03\nFORCES   19   5.62287E-02   5.43167E-02   6.76930E-02   6.53912E-02\nUPDATE   19           223          2220          2443\nTIMING   19        578.92          2.92        581.96      10929.26\n------\nENERGY   20   1.47923E-03   1.47152E-03   1.09301E-02   1.08732E-02\nFORCES   20   5.54920E-02   5.36308E-02   6.68061E-02   6.45654E-02\nUPDATE   20           223          2273          2496\nTIMING   20        591.90          3.68        595.70      11524.96\n------\nENERGY   21   1.11350E-03   1.16066E-03   8.22774E-03   8.57618E-03\nFORCES   21   5.66581E-02   5.41310E-02   6.82100E-02   6.51675E-02\nUPDATE   21           223          2273          2496\nTIMING   21        592.28          2.89        595.29      12120.25\n------\nENERGY   22   1.12267E-03   1.14775E-03   8.29551E-03   8.48081E-03\nFORCES   22   5.58592E-02   5.37209E-02   6.72481E-02   6.46739E-02\nUPDATE   22           223          2249          2472\nTIMING   22        586.16          2.92        589.20      12709.45\n------\nENERGY   23   1.26418E-03   1.27163E-03   9.34117E-03   9.39615E-03\nFORCES   23   5.56921E-02   5.34196E-02   6.70469E-02   6.43111E-02\nUPDATE   23           223          2228          2451\nTIMING   23        581.39          2.87        584.38      13293.83\n------\nENERGY   24   1.25106E-03   1.25941E-03   9.24418E-03   9.30589E-03\nFORCES   24   5.54962E-02   5.34614E-02   6.68111E-02   6.43615E-02\nUPDATE   24           223          2237          2460\nTIMING   24        583.31          2.99        586.42      13880.25\n------\nENERGY   25   1.31547E-03   1.31167E-03   9.72012E-03   9.69202E-03\nFORCES   25   5.55124E-02   5.35109E-02   6.68307E-02   6.44210E-02\nUPDATE   25           223          2204          2427\nTIMING   25        574.94          3.69        578.74      14458.99\n------\nENERGY   26   1.05830E-03   1.07179E-03   7.81984E-03   7.91958E-03\nFORCES   26   5.53964E-02   5.33895E-02   6.66909E-02   6.42749E-02\nUPDATE   26           223          2235          2458\nTIMING   26        583.34          2.92        586.38      15045.38\n------\nENERGY   27   1.06478E-03   1.07289E-03   7.86772E-03   7.92768E-03\nFORCES   27   5.57830E-02   5.35759E-02   6.71564E-02   6.44993E-02\nUPDATE   27           223          2185          2408\nTIMING   27        571.02          2.91        574.05      15619.42\n------\nENERGY   28   1.11424E-03   1.15456E-03   8.23318E-03   8.53116E-03\nFORCES   28   5.61240E-02   5.38066E-02   6.75669E-02   6.47770E-02\nUPDATE   28           223          2226          2449\nTIMING   28        580.99          2.92        584.02      16203.45\n------\nENERGY   29   1.19805E-03   1.25617E-03   8.85250E-03   9.28192E-03\nFORCES   29   5.56368E-02   5.33399E-02   6.69803E-02   6.42151E-02\nUPDATE   29           223          2177          2400\nTIMING   29        569.07          2.93        572.12      16775.57\n------\nENERGY   30   1.32401E-03   1.23619E-03   9.78320E-03   9.13429E-03\nFORCES   30   5.51757E-02   5.33361E-02   6.64253E-02   6.42106E-02\nUPDATE   30           223          2250          2473\nTIMING   30        586.74          3.70        590.56      17366.13\n------\nENERGY   31   1.21832E-03   1.31752E-03   9.00229E-03   9.73525E-03\nFORCES   31   5.54089E-02   5.34993E-02   6.67060E-02   6.44070E-02\nUPDATE   31           223          2223          2446\nTIMING   31        579.31          2.92        582.35      17948.48\n------\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE_external/hdnnp-data/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   9.1739161189824411E-08   7.0593095050533450E-01   2.2372649929284196E-02   9.6379208796011293E-02\n         1          2   2.6433999906765265E-01   2.4749666370750676E+00   1.0378805142792313E+00   1.9413782463770093E-01\n         1          3   1.5504686427401054E-05   1.4168627312588329E+00   5.5254915214857578E-02   2.1495058826125538E-01\n         1          4   1.4086411910634238E+00   4.7388215758712082E+00   3.1031877925923803E+00   3.5864448236496921E-01\n         1          5   9.8043626772015909E-04   1.9535901883323099E+00   1.1429456309160095E-01   2.2901461288065855E-01\n         1          6   2.2158364445227399E+00   6.0748308460582043E+00   3.8835182764170546E+00   3.9299243538518969E-01\n         1          7   1.0255080523534783E+00   5.1401074554660049E+00   2.5810215644603796E+00   4.3835591238870431E-01\n         1          8   4.8489829707261999E-03   3.9129781874325281E-01   4.7557455423079396E-02   2.7778419734655713E-02\n         1          9   9.3223803365223998E-02   2.8346930075434797E+00   6.0185719975366336E-01   3.1949957606875956E-01\n         1         10   6.7206749586119430E-01   4.4876923880381465E+00   2.1991872165248538E+00   4.1504796440380803E-01\n         1         11   2.2128378766968923E-02   8.6593017344520318E-01   1.4060436434125115E-01   7.5838421599526348E-02\n         1         12   8.4205124330445313E-01   7.0656885702864862E+00   2.9013712601439368E+00   7.3052821449417049E-01\n         1         13   1.4518778507164800E+00   9.6462711741708382E+00   4.3715329035264965E+00   8.3811671947643118E-01\n         1         14   2.4300884834352513E-06   5.3039215356450418E-02   2.8067394350178213E-04   1.6541693025921896E-03\n         1         15   4.3805855934107564E-04   3.3431366727997386E-01   1.5056637491023487E-02   3.6381498406602590E-02\n         1         16   1.8742403996648012E-02   5.3094282134884740E-01   1.9287359264197504E-01   5.3785992354357007E-02\n         1         17   5.6391705067135155E-03   2.7103176024192799E-01   3.6199336036120536E-02   2.2235092628611220E-02\n         1         18   5.8157340520125522E-01   3.0394483797974066E+00   1.5432926655352674E+00   2.9013849228704902E-01\n         1         19   3.5474335876025032E-01   2.8914948266501281E+00   1.2453633098426364E+00   2.6070492382053573E-01\n         1         20   1.3050150224953865E-03   2.0977615521049353E-01   1.6466279986318652E-02   1.6175233794254219E-02\n         1         21   3.3625763520090814E-02   1.6019727512861448E+00   2.6707302954572526E-01   1.9158906783856428E-01\n         1         22   3.5314748293148263E-01   2.5968432133168928E+00   1.2041087980295160E+00   2.3880745648555143E-01\n         1         23   5.6279184570511148E-03   4.8263719913200909E-01   4.8674878532957294E-02   4.5579012837321450E-02\n         1         24   3.5640890668898983E-01   3.9354254479681789E+00   1.3506519169134916E+00   4.3100694380807969E-01\n         1         25   7.1435545388184229E-01   5.4083380133399706E+00   2.3405335217844168E+00   4.7481787957091687E-01\n         1         26   6.0302894280955782E-07   2.4282702757490063E-02   1.0392381208153868E-04   6.9514343858439293E-04\n         1         27   1.4152015883516988E-04   1.8793440136817721E-01   6.7319944252965166E-03   1.8860146728064606E-02\n         1         28   7.6669273315039489E-03   2.8853650966579203E-01   9.6832241039761832E-02   2.8591400835791262E-02\n         1         29   1.4586287100215936E-03   1.2827520308122028E-01   1.2535333774723276E-02   1.2196652689168296E-02\n         1         30   2.4306078779227119E-01   1.5771292876622454E+00   7.3118666045976355E-01   1.6033491927751306E-01\n         1         31   1.5700215118676836E-01   1.4950427209078341E+00   6.2168623298528469E-01   1.3878720233016123E-01\n         1         32   8.0322135442977674E-08   9.1020506427165644E-03   1.1758299063219979E-04   7.2850621729108440E-04\n         1         33   3.8387499554503460E-05   4.6879099417593433E-02   2.2899299020297070E-03   6.3507919696978174E-03\n         1         34   2.5111603817039843E-07   2.6638155845094137E-02   3.5204871838944324E-04   2.1803344919789219E-03\n         1         35   7.8176366916082938E-04   1.2144199943350505E-01   1.0237823308897595E-02   1.5551953673898984E-02\n         1         36   6.0784771853405629E-03   1.5177813800129991E-01   4.5342256644197804E-02   1.4422755174681633E-02\n         1         37   6.5208235096380454E-08   6.8957085587219831E-03   8.4477914517405974E-05   5.1826403434160535E-04\n         1         38   5.1003186367566016E-04   3.3817704100212627E-02   5.0495259674331701E-03   4.2413701977289924E-03\n         1         39   3.0092380409832575E-01   3.9241027015819827E+00   1.6245850308330121E+00   3.6115017167195557E-01\n         1         40   2.9205060411645536E+00   2.0972699454192377E+01   1.0685030237788666E+01   1.8434608066664662E+00\n         1         41   5.8304225749625562E+00   3.3157582599900756E+01   1.6937338463410185E+01   2.8416990087236536E+00\n         1         42   2.8963706388516774E-01   3.4220973094358569E+00   1.3527222233246401E+00   2.9841578592458634E-01\n         1         43   3.3240856510350132E+00   1.9977206504626281E+01   1.0533032366441756E+01   1.8362183066460305E+00\n         1         44   5.5968160844972745E+00   2.9479500954936675E+01   1.4663357897716818E+01   2.4340402007751933E+00\n         1         45   7.3194532436105672E-02   1.4240027432637063E+00   4.6184059564430718E-01   1.0603619804309938E-01\n         1         46   7.4351404260172327E-01   6.1601360099088307E+00   3.0926623459215312E+00   5.2746971733324144E-01\n         1         47   1.0304047665725904E+00   9.5490875529313932E+00   4.6615470051220029E+00   8.8228607777747381E-01\n         1         48   5.3439780036913555E-02   6.0792049084128386E-01   2.0133541277710790E-01   4.7497199912796259E-02\n         1         49   1.0984946263275692E+00   5.3381605458179147E+00   2.9222626179881503E+00   4.9078113758325748E-01\n         1         50   9.3741001607568142E-01   6.0472356274080674E+00   2.8114797251218855E+00   5.0873676433244819E-01\n         1         51   1.1424085007079182E-01   2.3139492223359586E+00   7.5719953168832033E-01   2.0833570661709583E-01\n         1         52   1.4315113742496002E+00   1.3300925195398728E+01   5.8838374866614309E+00   1.2171600869775945E+00\n         1         53   3.5503714858105737E+00   2.1312715022502385E+01   1.0871674742056101E+01   1.8799426423890726E+00\n         1         54   1.0963309213378970E-01   2.0788696656585590E+00   6.3126459151902947E-01   1.7541529953806104E-01\n         1         55   1.6510272306266744E+00   1.2357046870783602E+01   5.7724472752012481E+00   1.1927743223366301E+00\n         1         56   3.3307522004182251E+00   1.8663597697385917E+01   9.2207406968320633E+00   1.5761279490996694E+00\n         1         57   2.7455727216146104E-02   9.1674320906634155E-01   2.1461170716720621E-01   6.1714021121502906E-02\n         1         58   3.6192386693953038E-01   3.8875893126984216E+00   1.7092032560335464E+00   3.4843371038350474E-01\n         1         59   5.6557210052590146E-01   6.1563972117346957E+00   2.9617726398537609E+00   5.9044611830216798E-01\n         1         60   2.0196364035104716E-02   3.3469617649847838E-01   9.3035775655912298E-02   2.7640180745065839E-02\n         1         61   5.5357670454431462E-01   3.1907980705952856E+00   1.5901399654465433E+00   3.0513520444755149E-01\n         1         62   5.3781344801473907E-01   3.6339755326587713E+00   1.6575261374157455E+00   3.1383714619102349E-01\n         1         63   9.6664268597268675E-05   1.4867672619417913E-01   4.3177785208556420E-03   8.2707901241799234E-03\n         1         64   1.2006437712525238E-02   1.1332481089585240E+00   1.2838035367153358E-01   1.3388538744183132E-01\n         1         65   2.0772479772511018E-01   1.8626169502984133E+00   8.2255201121385824E-01   1.7849382645365078E-01\n         1         66   8.7907438908811975E-05   1.2622839046469150E-01   4.4000149614673457E-03   1.1827043706432264E-02\n         1         67   1.3369106385547676E-02   8.7813896596785235E-01   1.1827747851010054E-01   1.1347348778532439E-01\n         1         68   1.7657303404092337E-01   1.4295433698727396E+00   6.2121356605669209E-01   1.2933064669650537E-01\n         1         69   2.8597998667575309E-03   3.7304172172637867E-01   3.7665097851475426E-02   3.7208167402427196E-02\n         1         70   1.5902143209986809E-05   2.6009225424800504E-02   7.2450937404019229E-04   2.4859888979869879E-03\n         1         71   4.7171431923273572E-03   1.6025670770457742E-01   2.8821358718588475E-02   1.9416774232856850E-02\n         1         72   1.5331295649388408E-02   1.9310943777686740E-01   6.9677412943044442E-02   1.7784064753732315E-02\n         2          1   2.4721472942648627E-02   1.5073065774351924E+00   5.1894025713961534E-01   1.2292746613848948E-01\n         2          2   2.4966843476303169E-01   2.6917832996745195E+00   1.5515938962961904E+00   2.2894178892035891E-01\n         2          3   1.8582961795319244E-03   3.8171243121869747E+00   1.1221679663414206E+00   3.9926224172528085E-01\n         2          4   6.9308990079045429E-01   3.9421018903882858E+00   1.9417591382085293E+00   2.7982355416028953E-01\n         2          5   5.2213352864915873E-02   5.9786240694290029E+00   2.7894744649522680E+00   6.8818475947171043E-01\n         2          6   3.4706330958249576E-01   2.8061894414477742E+00   1.2905107822301898E+00   2.5049917129048904E-01\n         2          7   5.6650782795607790E-01   6.0129804050995874E+00   3.4024808580901604E+00   5.3817898895468230E-01\n         2          8   8.2160472578002200E-02   2.1591157175155038E+00   9.5893716661004147E-01   2.2068746057755104E-01\n         2          9   9.7533565633843480E-02   8.0520717520847240E-01   3.9574121682754421E-01   7.2843087896835634E-02\n         2         10   7.5624736998622447E-02   1.2151161903363619E+00   4.2414909548153323E-01   1.1030205700397629E-01\n         2         11   3.8590027688988915E-01   3.4170303616374733E+00   1.5389187655267780E+00   2.9839201545750010E-01\n         2         12   1.2653139464575366E-01   3.3448693047411142E+00   9.0701446886275106E-01   3.0808232807716252E-01\n         2         13   3.5754079396564345E-02   2.3051636092543291E+00   4.5165801949286744E-01   2.0529180913687342E-01\n         2         14   1.7360244301899754E+00   9.1860981352526956E+00   5.0318013545245659E+00   7.7006828863188448E-01\n         2         15   5.6096556948092302E-01   6.9184291400548386E+00   2.5593433032311834E+00   7.0382259666666958E-01\n         2         16   2.7321455653550736E-03   2.6718628880300366E-01   6.8392239083035003E-02   1.8417271845608391E-02\n         2         17   1.4998879259624551E-04   2.8869834404308442E-01   3.2421219256901605E-02   2.1462316150937667E-02\n         2         18   9.6976148378458242E-03   6.9986551977156553E-01   7.4501947267367571E-02   9.2109247490457000E-02\n         2         19   7.5554776729931772E-01   3.8650650491408283E+00   2.1261658860729638E+00   2.9459249679651817E-01\n         2         20   2.2984860438624041E-01   2.2399640197541903E+00   8.4832685420611464E-01   2.2013029667841760E-01\n         2         21   3.1742242534198488E-02   6.9305314098138393E-01   2.0239450285654340E-01   6.2019223320811959E-02\n         2         22   1.6267388613945685E-01   1.8982342788109985E+00   8.1342448996901984E-01   1.7017885772188068E-01\n         2         23   4.3623299253776143E-02   1.8524213261728384E+00   4.3372964228967342E-01   1.6475284995752615E-01\n         2         24   1.1782155855406862E-02   1.3256780035707432E+00   2.0203673375826020E-01   1.2375770385162231E-01\n         2         25   9.5572013219445029E-01   5.1585503300832807E+00   2.7312178298449119E+00   4.5027566865612645E-01\n         2         26   2.1346552007948805E-01   3.7560054368796258E+00   1.2309867059977997E+00   3.8895981570570448E-01\n         2         27   1.0778454975081308E-03   1.6230009416534466E-01   3.4353839552470775E-02   1.0338804556484340E-02\n         2         28   4.1455680376600344E-05   1.3561930079689324E-01   1.3464607540962245E-02   9.4307016558753589E-03\n         2         29   2.9811923400491925E-03   3.9674788724187127E-01   3.2946560522656709E-02   5.3575100644579036E-02\n         2         30   4.0860996892032608E-01   2.1541090596644543E+00   1.1291055145629398E+00   1.6554701558125592E-01\n         2         31   8.7689965003411183E-02   1.1196100344004409E+00   3.9704096379805787E-01   1.1606734505235136E-01\n         2         32   2.0029888316796539E-05   1.7556653440553127E-02   1.4233102888664287E-03   1.3598121443903737E-03\n         2         33   5.2716716179610746E-06   4.4644993845652417E-02   1.7086280138653978E-03   4.2643079956046579E-03\n         2         34   8.8339290835669212E-07   1.2139204575362132E-02   4.1922038284938451E-04   1.5155281653507265E-03\n         2         35   1.2653672947005059E+00   8.9337925904902882E+00   4.2637335795708999E+00   5.9362291906692699E-01\n         2         36   4.3025897744283652E+00   2.4744209023066571E+01   1.4272525712868205E+01   1.9700222663219151E+00\n         2         37   2.9677470818795189E+00   2.5847640450705327E+01   1.1788593731598802E+01   2.3639335745006553E+00\n         2         38   4.8673248345854536E-01   6.9220258514917292E+00   2.9410791137038919E+00   5.0416378898015868E-01\n         2         39   4.7312413761643519E+00   2.4784350068345699E+01   1.4182436900763136E+01   1.9734981280505293E+00\n         2         40   2.7914940844674572E+00   2.2909604188642842E+01   1.0258913931047273E+01   2.0538117984713926E+00\n         2         41   5.1976352609600407E-01   3.0581982698648895E+00   1.1910833091075925E+00   2.2566892125976182E-01\n         2         42   1.0695804209866875E+00   7.2313250376604037E+00   3.9928775708897235E+00   5.8095727320582324E-01\n         2         43   8.4628209088378592E-01   7.5313801441068913E+00   3.3982729265620653E+00   7.1123273080942895E-01\n         2         44   7.0763463381880415E-02   1.2969398476188700E+00   3.1793764328087359E-01   1.3617384576811825E-01\n         2         45   1.3721123798749537E+00   6.3973513973729199E+00   3.7457022157866304E+00   5.0158792550110110E-01\n         2         46   6.3964342968618404E-01   4.7161013997028380E+00   1.9947659320351354E+00   4.2776493844298569E-01\n         2         47   8.6532747970285151E-01   6.1240088873304499E+00   2.7402018484921369E+00   4.0552538612845523E-01\n         2         48   2.5315105294788682E+00   1.5776758660822487E+01   8.7867531123795093E+00   1.2800885070636867E+00\n         2         49   1.5679508239487920E+00   1.6123025100421103E+01   6.9389600266532643E+00   1.5752331036924878E+00\n         2         50   2.4475421880204548E-01   4.5715135037651979E+00   1.7778621079614614E+00   3.3311384228682872E-01\n         2         51   2.8365798870360606E+00   1.5735394223700631E+01   8.7129345829426814E+00   1.2788947945672131E+00\n         2         52   1.4825266957775993E+00   1.4111085036729261E+01   5.9550381055833128E+00   1.3412575984240060E+00\n         2         53   2.9486345514961088E-01   2.1632897998459173E+00   7.6894782290828789E-01   1.6439255789853263E-01\n         2         54   6.1183454216254696E-01   4.7418024842673727E+00   2.4364672738977449E+00   3.8379810845509604E-01\n         2         55   4.2978046698724798E-01   4.7295979558909700E+00   2.0069121315341767E+00   4.7649159304923261E-01\n         2         56   3.3379248097225291E-02   8.3272635081969881E-01   1.7274845946125020E-01   8.7956031429209408E-02\n         2         57   8.2656009161897048E-01   3.9467471262168639E+00   2.2459243943426777E+00   3.1269124051179731E-01\n         2         58   3.1171589063801924E-01   2.7714452296122714E+00   1.1129251102859337E+00   2.6297335909685149E-01\n         2         59   2.6592109568248031E-02   5.6825603390221913E-01   2.0877471778793405E-01   4.9135988886466996E-02\n         2         60   7.2485536842319745E-02   1.1034806181844534E+00   4.5818934497666303E-01   1.0344323974312900E-01\n         2         61   5.9263838221524185E-03   1.2515028539804678E+00   2.4502825958578195E-01   1.1006546541667923E-01\n         2         62   3.5994334696395447E-03   3.9125406849266531E-01   8.9107610428087070E-02   3.1854933024728180E-02\n         2         63   7.2533340578499653E-02   1.0927078443379801E+00   4.4612155612487853E-01   1.0164232620041405E-01\n         2         64   5.4706332551405917E-03   9.8645463183530846E-01   1.9457952454956559E-01   8.6829363320211461E-02\n         2         65   1.7435002600794914E-04   5.6940854477051987E-02   3.9265019004702875E-03   5.9979210203388224E-03\n         2         66   2.1035187678847361E-02   2.2735828246294021E-01   9.5459655622289877E-02   2.0577872261152416E-02\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE_external/hdnnp-data/weights.016.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -3.5529535307974660E+00 a         1     0     1     1     1\n  7.2419212968357530E-02 a         2     0     1     1     2\n  6.6238167719007179E-01 a         3     0     1     1     3\n  1.3187085002852068E+00 a         4     0     1     1     4\n  8.0230438760649514E-01 a         5     0     1     1     5\n  8.3955862269426929E-01 a         6     0     1     1     6\n  6.0886672237242623E-01 a         7     0     1     1     7\n  1.8038521037244075E+00 a         8     0     1     1     8\n -9.4212226737513360E-01 a         9     0     1     1     9\n -5.1556581063883433E-01 a        10     0     1     1    10\n -1.1787308470438386E-01 a        11     0     1     1    11\n  2.7402309255936421E+00 a        12     0     1     1    12\n -1.4988157706430596E+00 a        13     0     1     1    13\n -1.4218948987030877E+00 a        14     0     1     1    14\n -3.1471248905197000E+00 a        15     0     1     1    15\n -2.7242744362012289E-01 a        16     0     1     1    16\n -1.4939110915197420E+00 a        17     0     1     1    17\n -4.5760625854044340E-01 a        18     0     1     1    18\n  1.8320965746572428E+00 a        19     0     1     1    19\n  1.4829292005742705E+00 a        20     0     1     1    20\n -4.7531481220841671E+00 a        21     0     1     1    21\n  6.9284365000837844E-01 a        22     0     1     1    22\n -1.4360334184866708E+00 a        23     0     1     1    23\n -6.9988606086712224E-01 a        24     0     1     1    24\n -2.6821117310359570E+00 a        25     0     1     1    25\n  1.2328185292695659E+00 a        26     0     2     1     1\n  6.8539081540980901E-02 a        27     0     2     1     2\n  1.1312525424757594E-01 a        28     0     2     1     3\n  3.3791299053992763E-01 a        29     0     2     1     4\n  1.3203780104475105E+00 a        30     0     2     1     5\n -1.4531712477250573E+00 a        31     0     2     1     6\n  2.4379072742488564E-01 a        32     0     2     1     7\n  7.2963026955779986E-01 a        33     0     2     1     8\n -1.2591734762557112E+00 a        34     0     2     1     9\n -4.7096176379988147E-01 a        35     0     2     1    10\n  1.1052943930835461E-01 a        36     0     2     1    11\n  1.2282514057948777E+00 a        37     0     2     1    12\n -5.8437787869506075E-01 a        38     0     2     1    13\n  1.4166787422902487E+00 a        39     0     2     1    14\n -1.6938650584717402E-01 a        40     0     2     1    15\n  2.3030826774815769E+00 a        41     0     2     1    16\n -1.4473769335578126E+00 a        42     0     2     1    17\n  4.0195075881174241E-01 a        43     0     2     1    18\n  1.1043558865793792E+00 a        44     0     2     1    19\n -3.4549061205961434E-01 a        45     0     2     1    20\n  8.1879232157423720E-01 a        46     0     2     1    21\n -2.7007345535606064E-01 a        47     0     2     1    22\n -8.2869143511169474E-01 a        48     0     2     1    23\n -2.9469119089022022E-01 a        49     0     2     1    24\n -5.7206441642229700E-01 a        50     0     2     1    25\n  7.7333844542414798E-01 a        51     0     3     1     1\n -2.8005034461966472E+00 a        52     0     3     1     2\n -2.0054154055351620E-01 a        53     0     3     1     3\n -2.3648818664674390E-01 a        54     0     3     1     4\n -6.4064022093719220E-01 a        55     0     3     1     5\n  6.9876341352721461E-01 a        56     0     3     1     6\n  1.2138517429043079E+00 a        57     0     3     1     7\n -1.0872828987358620E+00 a        58     0     3     1     8\n  2.4009903950784475E+00 a        59     0     3     1     9\n -7.1414550990900871E-01 a        60     0     3     1    10\n  4.8262298434516965E-01 a        61     0     3     1    11\n  1.2017235942575036E-01 a        62     0     3     1    12\n -5.0067742187524500E-01 a        63     0     3     1    13\n  1.6682617398315705E-01 a        64     0     3     1    14\n -1.9521789463955752E+00 a        65     0     3     1    15\n  1.3587159322569415E+00 a        66     0     3     1    16\n  1.9824040428450457E-01 a        67     0     3     1    17\n  5.0478176436946609E-01 a        68     0     3     1    18\n  1.7968971934667841E+00 a        69     0     3     1    19\n -2.6819167691107553E+00 a        70     0     3     1    20\n  3.1361294632323173E+00 a        71     0     3     1    21\n -7.2813429885436576E-01 a        72     0     3     1    22\n  7.9662962027149486E-01 a        73     0     3     1    23\n  5.3906067437318705E-01 a        74     0     3     1    24\n  1.8219650246428634E+00 a        75     0     3     1    25\n  5.8927722128305347E-02 a        76     0     4     1     1\n  3.4478358925805858E-01 a        77     0     4     1     2\n  2.1711984340886667E-01 a        78     0     4     1     3\n -7.5943721634464512E-01 a        79     0     4     1     4\n 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-2.9263488552138478E-01 a      1941     1     5     2    16\n  7.4326458357632263E-01 a      1942     1     5     2    17\n  4.2013924569516037E-01 a      1943     1     5     2    18\n -5.8280302654581832E-02 a      1944     1     5     2    19\n -3.2612804852919446E-02 a      1945     1     5     2    20\n  3.0897375192782450E-01 a      1946     1     5     2    21\n -3.4554814584389509E-01 a      1947     1     5     2    22\n  5.6462638020854716E-01 a      1948     1     5     2    23\n -2.2840636874785014E-01 a      1949     1     5     2    24\n -4.9669234553755076E-01 a      1950     1     5     2    25\n  1.1758939649783381E-01 a      1951     1     6     2     1\n  8.6738679928268236E-01 a      1952     1     6     2     2\n -8.2268243221940873E-01 a      1953     1     6     2     3\n -1.7656641024661676E-01 a      1954     1     6     2     4\n -7.3983486152494982E-01 a      1955     1     6     2     5\n  5.9385478664743296E-01 a      1956     1     6     2     6\n -4.2593570872866021E-01 a      1957     1     6     2     7\n -1.9801025124105215E-01 a      1958     1     6     2     8\n -4.6730416799726238E-01 a      1959     1     6     2     9\n  1.8116336463074925E-01 a      1960     1     6     2    10\n -7.5935659696139179E-01 a      1961     1     6     2    11\n -2.7885626460361607E-01 a      1962     1     6     2    12\n  2.2498372487170440E-01 a      1963     1     6     2    13\n -2.6922194278960770E-01 a      1964     1     6     2    14\n  8.2356834198746176E-02 a      1965     1     6     2    15\n -1.9959174200148408E+00 a      1966     1     6     2    16\n -9.1441649022992150E-02 a      1967     1     6     2    17\n -3.2893725936322316E-01 a      1968     1     6     2    18\n  8.4708812890909327E-02 a      1969     1     6     2    19\n -9.8738542155083330E-03 a      1970     1     6     2    20\n -1.5706979176219785E-01 a      1971     1     6     2    21\n -3.3385820430832114E-01 a      1972     1     6     2    22\n -8.1658461786034431E-01 a      1973     1     6     2    23\n  4.2826805041754107E-01 a      1974     1     6     2    24\n  6.7595378736221203E-03 a      1975     1     6     2    25\n -1.4858293771378450E-01 a      1976     1     7     2     1\n -4.8665064878920916E-01 a      1977     1     7     2     2\n  9.3147532658334302E-03 a      1978     1     7     2     3\n  2.2071434698840436E-01 a      1979     1     7     2     4\n -3.1521981986003578E+00 a      1980     1     7     2     5\n  1.4896102615333093E-01 a      1981     1     7     2     6\n  2.0639082326871608E-01 a      1982     1     7     2     7\n  1.4764434422173356E+00 a      1983     1     7     2     8\n -8.5415180586937678E-01 a      1984     1     7     2     9\n  2.0056826451387089E+00 a      1985     1     7     2    10\n -1.6035541337428121E+00 a      1986     1     7     2    11\n -1.0126746741541708E-01 a      1987     1     7     2    12\n  1.0176837892450277E+00 a      1988     1     7     2    13\n  5.8650237148957363E-01 a      1989     1     7     2    14\n  6.8764775335937489E-01 a      1990     1     7     2    15\n -1.6327881928548789E+00 a      1991     1     7     2    16\n -2.6588597247788198E-01 a      1992     1     7     2    17\n  1.9718370666773979E-01 a      1993     1     7     2    18\n  4.3601566297954825E-01 a      1994     1     7     2    19\n -2.7082844396133726E-01 a      1995     1     7     2    20\n  3.2206390922604272E-01 a      1996     1     7     2    21\n  5.0949702830703934E-03 a      1997     1     7     2    22\n -1.3049790188741632E+00 a      1998     1     7     2    23\n  4.2026808266723220E-01 a      1999     1     7     2    24\n -6.3063301866048659E-03 a      2000     1     7     2    25\n -2.6986778384233595E-01 a      2001     1     8     2     1\n  1.0472413049447822E+00 a      2002     1     8     2     2\n  2.1270075261563209E-01 a      2003     1     8     2     3\n  1.0059956884525167E-02 a      2004     1     8     2     4\n -5.6674331507128162E-01 a      2005     1     8     2     5\n -4.1069951508364727E-01 a      2006     1     8     2     6\n -5.7946760577066525E-01 a      2007     1     8     2     7\n -6.9320514952269952E-01 a      2008     1     8     2     8\n -2.6235771311219197E-01 a      2009     1     8     2     9\n -4.9114985182179943E-01 a      2010     1     8     2    10\n -6.4751077129371837E-01 a      2011     1     8     2    11\n  1.6623516048991380E-01 a      2012     1     8     2    12\n -1.3252784721447061E-01 a      2013     1     8     2    13\n  6.3617130518492077E-02 a      2014     1     8     2    14\n -7.9749770183388205E-02 a      2015     1     8     2    15\n  2.6810344620231513E-01 a      2016     1     8     2    16\n -1.0886590179511721E-01 a      2017     1     8     2    17\n -8.5635070249057671E-02 a      2018     1     8     2    18\n -8.5883419432118385E-02 a      2019     1     8     2    19\n  1.4001812857233212E-01 a      2020     1     8     2    20\n  2.4652559241660935E-01 a      2021     1     8     2    21\n -1.1705271450291483E-02 a      2022     1     8     2    22\n  5.1059887324814701E-01 a      2023     1     8     2    23\n -9.2777234250212143E-02 a      2024     1     8     2    24\n -6.6631934340703591E-01 a      2025     1     8     2    25\n  4.4575672600804567E-01 a      2026     1     9     2     1\n -6.7107163032432227E-01 a      2027     1     9     2     2\n -3.0179267369944862E-01 a      2028     1     9     2     3\n -1.3598496288690123E+00 a      2029     1     9     2     4\n -1.4940270248112404E+00 a      2030     1     9     2     5\n -2.2080339138801010E-02 a      2031     1     9     2     6\n -5.7301816910865744E-01 a      2032     1     9     2     7\n -1.0063124051587569E-01 a      2033     1     9     2     8\n -2.3012172042264027E+00 a      2034     1     9     2     9\n  1.0885556179246252E+00 a      2035     1     9     2    10\n -1.1526492907689538E+00 a      2036     1     9     2    11\n  3.9520279659304998E-02 a      2037     1     9     2    12\n  2.7509795088948047E-01 a      2038     1     9     2    13\n -3.2176987618681385E-01 a      2039     1     9     2    14\n  1.2152345255401775E+00 a      2040     1     9     2    15\n  6.7561788359563746E-01 a      2041     1     9     2    16\n  1.2756402711221351E-01 a      2042     1     9     2    17\n  4.2778010903937930E-02 a      2043     1     9     2    18\n  2.2524717454514478E-01 a      2044     1     9     2    19\n -5.9203499543104976E-01 a      2045     1     9     2    20\n  1.9472787318819443E-01 a      2046     1     9     2    21\n  2.6372584248809827E-01 a      2047     1     9     2    22\n -1.2605296128570485E+00 a      2048     1     9     2    23\n -4.2493619774884570E-02 a      2049     1     9     2    24\n -3.2689975704292223E-01 a      2050     1     9     2    25\n -5.0316442252296556E-01 a      2051     1    10     2     1\n -1.2776598471010672E+00 a      2052     1    10     2     2\n  3.2727687173561748E-01 a      2053     1    10     2     3\n -5.2750979806146270E-01 a      2054     1    10     2     4\n -5.2100917223171461E-01 a      2055     1    10     2     5\n  1.0271103871270988E+00 a      2056     1    10     2     6\n -1.3174585043808176E+00 a      2057     1    10     2     7\n  1.7860344423744762E-01 a      2058     1    10     2     8\n -3.1935218220133910E-01 a      2059     1    10     2     9\n  4.0624355231658738E-01 a      2060     1    10     2    10\n -8.4263015301232114E-01 a      2061     1    10     2    11\n -4.1311568727252523E-01 a      2062     1    10     2    12\n -2.0250507836832625E+00 a      2063     1    10     2    13\n -4.9669616476317113E-01 a      2064     1    10     2    14\n  1.4542353491363211E+00 a      2065     1    10     2    15\n -1.0829455537390682E-01 a      2066     1    10     2    16\n  3.0637661429549540E-01 a      2067     1    10     2    17\n  3.9830418172493465E-01 a      2068     1    10     2    18\n -1.6636558535137880E+00 a      2069     1    10     2    19\n  7.0498166711701593E-01 a      2070     1    10     2    20\n -3.8215339196853010E-01 a      2071     1    10     2    21\n -2.9475963780786207E-01 a      2072     1    10     2    22\n  1.2815404826499932E+00 a      2073     1    10     2    23\n  3.7464874577430729E-01 a      2074     1    10     2    24\n  6.7369985980501002E-01 a      2075     1    10     2    25\n  1.4787802212199200E-01 a      2076     1    11     2     1\n  2.3652422194864106E-01 a      2077     1    11     2     2\n -2.9319277439498237E-01 a      2078     1    11     2     3\n  8.1893235515044593E-01 a      2079     1    11     2     4\n -5.4251461750474061E-01 a      2080     1    11     2     5\n -7.9432325051447306E-01 a      2081     1    11     2     6\n  5.6741940214747433E-01 a      2082     1    11     2     7\n -1.9883538594217587E-01 a      2083     1    11     2     8\n  2.4059652163192724E-01 a      2084     1    11     2     9\n  9.0487535694630072E-01 a      2085     1    11     2    10\n  2.1500450010677571E-01 a      2086     1    11     2    11\n -8.8392848708160249E-02 a      2087     1    11     2    12\n  4.8911199216330936E-01 a      2088     1    11     2    13\n  3.8501747509679890E-01 a      2089     1    11     2    14\n  2.0880386832367939E-01 a      2090     1    11     2    15\n -1.2898150999726214E+00 a      2091     1    11     2    16\n -6.7684897098766336E-02 a      2092     1    11     2    17\n -1.3226797298228404E-01 a      2093     1    11     2    18\n -7.0860409533946489E-01 a      2094     1    11     2    19\n  2.0428970671759283E-01 a      2095     1    11     2    20\n  6.1788460934391509E-01 a      2096     1    11     2    21\n -1.5387742244322317E-02 a      2097     1    11     2    22\n -2.9187261106596285E-01 a      2098     1    11     2    23\n -2.7435985561202314E-01 a      2099     1    11     2    24\n -2.9893757922781268E-02 a      2100     1    11     2    25\n  1.4366492019663546E-01 a      2101     1    12     2     1\n -8.3708506447152686E-01 a      2102     1    12     2     2\n  8.4900741982625050E-01 a      2103     1    12     2     3\n -3.1763858239521897E-01 a      2104     1    12     2     4\n -8.5836557564984983E-02 a      2105     1    12     2     5\n  4.8971995238975233E-02 a      2106     1    12     2     6\n -8.6345064469884769E-01 a      2107     1    12     2     7\n -1.8877691890216164E+00 a      2108     1    12     2     8\n  4.7870208924774238E-01 a      2109     1    12     2     9\n -2.6803285718567860E-01 a      2110     1    12     2    10\n -8.3576740507701341E-01 a      2111     1    12     2    11\n -2.0233607775747742E-01 a      2112     1    12     2    12\n -2.0851336604971404E+00 a      2113     1    12     2    13\n  5.5710849793933925E-02 a      2114     1    12     2    14\n -2.5441709390192631E+00 a      2115     1    12     2    15\n  1.1056110845657674E+00 a      2116     1    12     2    16\n  4.1604534414542688E-01 a      2117     1    12     2    17\n -2.4025453894460813E-01 a      2118     1    12     2    18\n -4.8834369066457661E-01 a      2119     1    12     2    19\n  1.2885571052723108E-01 a      2120     1    12     2    20\n -5.4132000309146744E-01 a      2121     1    12     2    21\n -1.7269282812154974E-01 a      2122     1    12     2    22\n -5.8064851629878863E-03 a      2123     1    12     2    23\n -1.4394463497698487E-01 a      2124     1    12     2    24\n -4.2487948203957382E-01 a      2125     1    12     2    25\n  5.8675042735952393E-02 a      2126     1    13     2     1\n  1.7863972211172008E-01 a      2127     1    13     2     2\n  4.5741880103604365E-01 a      2128     1    13     2     3\n  9.1416506499137384E-01 a      2129     1    13     2     4\n -7.3674367315233913E-01 a      2130     1    13     2     5\n -3.0779431852369288E-01 a      2131     1    13     2     6\n -3.2999352842234286E-01 a      2132     1    13     2     7\n -5.4956662968530401E-01 a      2133     1    13     2     8\n -8.2136164243233878E-01 a      2134     1    13     2     9\n  1.2183161209162805E+00 a      2135     1    13     2    10\n -1.2314580021681576E-04 a      2136     1    13     2    11\n -1.0026980899080576E-01 a      2137     1    13     2    12\n -7.5923362473088618E-01 a      2138     1    13     2    13\n  8.7341315448514784E-02 a      2139     1    13     2    14\n  2.5889498070253123E+00 a      2140     1    13     2    15\n  3.2846563407201890E-01 a      2141     1    13     2    16\n  2.4140079639811293E-01 a      2142     1    13     2    17\n  6.6559640464078706E-01 a      2143     1    13     2    18\n -6.0228182791517193E-01 a      2144     1    13     2    19\n  5.0959148190761594E-01 a      2145     1    13     2    20\n -1.8343764259383200E-01 a      2146     1    13     2    21\n -2.0541935684248189E-01 a      2147     1    13     2    22\n  5.2020354314273987E-01 a      2148     1    13     2    23\n  2.8411193388383044E-01 a      2149     1    13     2    24\n  1.5031583886753237E+00 a      2150     1    13     2    25\n -1.5611135743074465E+00 a      2151     1    14     2     1\n -3.2360297425207724E-01 a      2152     1    14     2     2\n -2.8070095488766600E-01 a      2153     1    14     2     3\n -4.2682370987576490E-01 a      2154     1    14     2     4\n -8.0124669652434721E-01 a      2155     1    14     2     5\n  6.0916260028745439E-01 a      2156     1    14     2     6\n -1.3043834885545900E+00 a      2157     1    14     2     7\n -1.1114567839213945E+00 a      2158     1    14     2     8\n -7.6508338871898718E-01 a      2159     1    14     2     9\n  1.7394319780653198E+00 a      2160     1    14     2    10\n  6.1580012015667462E-01 a      2161     1    14     2    11\n -2.1501534971396988E-01 a      2162     1    14     2    12\n  8.1316399521310057E-01 a      2163     1    14     2    13\n -1.2944835426827954E+00 a      2164     1    14     2    14\n  3.6338934043065596E-02 a      2165     1    14     2    15\n -9.7464822438627852E-01 a      2166     1    14     2    16\n -2.4145501724766127E-01 a      2167     1    14     2    17\n -8.8876835360975071E-03 a      2168     1    14     2    18\n -5.8076528324547438E-01 a      2169     1    14     2    19\n -2.0411437917641737E+00 a      2170     1    14     2    20\n -4.2526015090964880E-01 a      2171     1    14     2    21\n  5.9996421373152897E-01 a      2172     1    14     2    22\n -3.6675255943507928E-02 a      2173     1    14     2    23\n  1.3185398858057240E-01 a      2174     1    14     2    24\n -2.0032286135136248E+00 a      2175     1    14     2    25\n  5.1591662327951759E-01 a      2176     1    15     2     1\n -2.5446052702797714E-03 a      2177     1    15     2     2\n -8.1769338860501051E-01 a      2178     1    15     2     3\n -6.8480492422848949E-01 a      2179     1    15     2     4\n  1.6061689254540090E+00 a      2180     1    15     2     5\n -3.6828605283363745E+00 a      2181     1    15     2     6\n -2.6949729107316758E+00 a      2182     1    15     2     7\n -8.7436479908358988E-01 a      2183     1    15     2     8\n -7.2537234627087488E-01 a      2184     1    15     2     9\n  1.7554101736285144E+00 a      2185     1    15     2    10\n -1.5729036376143151E+00 a      2186     1    15     2    11\n -4.7196403406815074E-01 a      2187     1    15     2    12\n  2.4686309706562368E+00 a      2188     1    15     2    13\n -8.1429048034865914E-01 a      2189     1    15     2    14\n  1.2457943097534157E+00 a      2190     1    15     2    15\n -1.8238343315299035E+00 a      2191     1    15     2    16\n -9.1710155695980261E-02 a      2192     1    15     2    17\n -1.7104412957602122E+00 a      2193     1    15     2    18\n  2.7030869802557012E-01 a      2194     1    15     2    19\n -1.7298684033912173E+00 a      2195     1    15     2    20\n -3.1058841915893948E-01 a      2196     1    15     2    21\n  1.8274844624858664E+00 a      2197     1    15     2    22\n -1.3513314668634027E+00 a      2198     1    15     2    23\n -1.1539080164302253E+00 a      2199     1    15     2    24\n  3.7623134982371026E-01 a      2200     1    15     2    25\n  3.8564708777748902E-01 a      2201     1    16     2     1\n -3.7485013341251339E-01 a      2202     1    16     2     2\n  3.0694902381634054E-01 a      2203     1    16     2     3\n -6.3820812530951954E-01 a      2204     1    16     2     4\n  6.1596951581411624E-02 a      2205     1    16     2     5\n  3.1823666483179947E-01 a      2206     1    16     2     6\n -1.7451214484287221E+00 a      2207     1    16     2     7\n  6.6928800449640258E-01 a      2208     1    16     2     8\n -1.1768614713311631E+00 a      2209     1    16     2     9\n -1.2657577834196381E+00 a      2210     1    16     2    10\n -3.0160201061177228E-01 a      2211     1    16     2    11\n -5.3877877406889563E-01 a      2212     1    16     2    12\n -8.6493612190989910E-01 a      2213     1    16     2    13\n -8.8460225776662071E-01 a      2214     1    16     2    14\n  1.9057948312439157E+00 a      2215     1    16     2    15\n -2.7200418390588271E-01 a      2216     1    16     2    16\n  1.9952889394862189E-01 a      2217     1    16     2    17\n  7.9321718120701656E-02 a      2218     1    16     2    18\n -7.5240700188026213E-02 a      2219     1    16     2    19\n  3.5188674964451849E-01 a      2220     1    16     2    20\n  4.4883278162576262E-01 a      2221     1    16     2    21\n  2.4951384292998435E-01 a      2222     1    16     2    22\n  1.6851679055279442E-01 a      2223     1    16     2    23\n -4.8371544786080266E-02 a      2224     1    16     2    24\n  8.1495784381186021E-01 a      2225     1    16     2    25\n -7.7932092504504180E-01 a      2226     1    17     2     1\n  8.4308356300312914E-01 a      2227     1    17     2     2\n  6.2801495977484001E-01 a      2228     1    17     2     3\n -1.6671863188240814E-02 a      2229     1    17     2     4\n  4.9617622666448757E-01 a      2230     1    17     2     5\n  2.8578791610744131E-01 a      2231     1    17     2     6\n  5.0261300134126208E-01 a      2232     1    17     2     7\n  4.2973672296612153E-01 a      2233     1    17     2     8\n  2.0605776991439645E-02 a      2234     1    17     2     9\n  3.1505912130803543E-01 a      2235     1    17     2    10\n -4.8141644197770223E-01 a      2236     1    17     2    11\n  6.5147019223382929E-01 a      2237     1    17     2    12\n  1.3223922139341173E-02 a      2238     1    17     2    13\n  1.3552951191767832E+00 a      2239     1    17     2    14\n -2.7683725661405684E-01 a      2240     1    17     2    15\n -1.4553982661789062E+00 a      2241     1    17     2    16\n  1.3934738472514663E-01 a      2242     1    17     2    17\n  6.5662014192387624E-02 a      2243     1    17     2    18\n  3.9097955051468730E-01 a      2244     1    17     2    19\n -1.5329149954135943E+00 a      2245     1    17     2    20\n -4.9182889227766408E-01 a      2246     1    17     2    21\n -8.4101247787721850E-02 a      2247     1    17     2    22\n  1.1079957740309260E-01 a      2248     1    17     2    23\n  1.2653734338244162E+00 a      2249     1    17     2    24\n  5.1889782109670390E-01 a      2250     1    17     2    25\n -3.5701303156391490E-01 a      2251     1    18     2     1\n -2.3369886700637788E-01 a      2252     1    18     2     2\n  1.8192889993017079E-02 a      2253     1    18     2     3\n -1.9089403601514085E-01 a      2254     1    18     2     4\n -2.2245213004847283E-01 a      2255     1    18     2     5\n -4.1704360216982245E-01 a      2256     1    18     2     6\n -5.9376327509449600E-01 a      2257     1    18     2     7\n  4.7700366121749904E-01 a      2258     1    18     2     8\n -2.4234013871626243E+00 a      2259     1    18     2     9\n -3.4319600817672740E+00 a      2260     1    18     2    10\n  1.4602063702387118E+00 a      2261     1    18     2    11\n -4.8017949262669966E-02 a      2262     1    18     2    12\n -2.5388955532842389E-01 a      2263     1    18     2    13\n -4.4955574787101665E-01 a      2264     1    18     2    14\n -5.9686971656068388E-01 a      2265     1    18     2    15\n  1.5329181413373798E+00 a      2266     1    18     2    16\n -1.7745540088419492E-01 a      2267     1    18     2    17\n -6.8356066126928808E-02 a      2268     1    18     2    18\n -5.7868883010994010E-01 a      2269     1    18     2    19\n -2.4958945618463482E-01 a      2270     1    18     2    20\n -8.8915588088891362E-01 a      2271     1    18     2    21\n  4.6796145878627105E-01 a      2272     1    18     2    22\n  3.7239838802427244E-01 a      2273     1    18     2    23\n  5.8825012698306467E-01 a      2274     1    18     2    24\n -2.5213870537746796E-01 a      2275     1    18     2    25\n -4.0945577957805229E-01 a      2276     1    19     2     1\n -6.3926426566269479E-01 a      2277     1    19     2     2\n -2.4803832950792159E-03 a      2278     1    19     2     3\n -9.5504254863097604E-01 a      2279     1    19     2     4\n  2.4385416954208063E-02 a      2280     1    19     2     5\n  1.8105456314263782E-01 a      2281     1    19     2     6\n -1.3959803913453275E+00 a      2282     1    19     2     7\n -1.4647235163838312E+00 a      2283     1    19     2     8\n -8.0598524282205181E-02 a      2284     1    19     2     9\n -6.8890711362406043E-01 a      2285     1    19     2    10\n  7.4049128505740025E-01 a      2286     1    19     2    11\n -1.8107652733146301E-01 a      2287     1    19     2    12\n  1.1180459617056233E-01 a      2288     1    19     2    13\n -9.7523288912192785E-01 a      2289     1    19     2    14\n  5.4031707452495070E-01 a      2290     1    19     2    15\n -8.6865875639635415E-01 a      2291     1    19     2    16\n -1.1736299949303194E-03 a      2292     1    19     2    17\n -2.1796832363882152E-01 a      2293     1    19     2    18\n -2.0197745129587785E-01 a      2294     1    19     2    19\n -2.0649260039989298E-01 a      2295     1    19     2    20\n -2.5945409305212930E-01 a      2296     1    19     2    21\n -5.3195384264402990E-01 a      2297     1    19     2    22\n  6.1477888542849975E-02 a      2298     1    19     2    23\n -6.9385778198627257E-01 a      2299     1    19     2    24\n  3.3845607119781312E-01 a      2300     1    19     2    25\n  4.0809678373584041E-02 a      2301     1    20     2     1\n  3.2924070883990825E-01 a      2302     1    20     2     2\n -3.9610966191553226E-01 a      2303     1    20     2     3\n -2.0132651897409879E+00 a      2304     1    20     2     4\n  2.4484241841952716E+00 a      2305     1    20     2     5\n  5.3570194814429040E-01 a      2306     1    20     2     6\n  3.9782963410556638E-01 a      2307     1    20     2     7\n  4.9250587897907255E-01 a      2308     1    20     2     8\n -9.0581905870919688E-01 a      2309     1    20     2     9\n  9.6720818758476146E-01 a      2310     1    20     2    10\n -2.4290730668752603E+00 a      2311     1    20     2    11\n  8.5170505147369346E-01 a      2312     1    20     2    12\n -2.1483680686887496E-01 a      2313     1    20     2    13\n  1.0883989821232398E+00 a      2314     1    20     2    14\n -4.2448276419305673E+00 a      2315     1    20     2    15\n  1.3220278308357323E+00 a      2316     1    20     2    16\n  2.0515176886377723E-01 a      2317     1    20     2    17\n  4.3773484307033583E-01 a      2318     1    20     2    18\n -1.3786340518033451E+00 a      2319     1    20     2    19\n -2.2372534223710475E-01 a      2320     1    20     2    20\n -2.7758118237942005E-02 a      2321     1    20     2    21\n -3.6463714150317883E-01 a      2322     1    20     2    22\n -1.4652346461706460E+00 a      2323     1    20     2    23\n -1.9948609569365011E-01 a      2324     1    20     2    24\n -1.2992922004186624E+00 a      2325     1    20     2    25\n -5.4234465116761910E-01 a      2326     1    21     2     1\n -1.1703464645203435E-01 a      2327     1    21     2     2\n  2.7846604110004280E-01 a      2328     1    21     2     3\n  4.2152065037688702E-01 a      2329     1    21     2     4\n -3.1812648076931704E-01 a      2330     1    21     2     5\n  2.5354733798445972E-01 a      2331     1    21     2     6\n  5.0508300555905372E-01 a      2332     1    21     2     7\n -1.8871360552404024E+00 a      2333     1    21     2     8\n -1.8179368004635235E+00 a      2334     1    21     2     9\n -9.1331416740862581E-01 a      2335     1    21     2    10\n  1.0900023434903663E+00 a      2336     1    21     2    11\n  8.9874047451855385E-02 a      2337     1    21     2    12\n -1.2847531299662041E+00 a      2338     1    21     2    13\n -7.4525540480534103E-01 a      2339     1    21     2    14\n  1.0535696198186528E+00 a      2340     1    21     2    15\n  7.8428574671901730E-01 a      2341     1    21     2    16\n  1.3814042929844125E-01 a      2342     1    21     2    17\n  6.9643061019999272E-02 a      2343     1    21     2    18\n  8.0359279616965651E-01 a      2344     1    21     2    19\n -5.6529681854842539E-01 a      2345     1    21     2    20\n -2.3488037904274034E-02 a      2346     1    21     2    21\n  2.1341829380240665E-01 a      2347     1    21     2    22\n -1.4102093313296238E-01 a      2348     1    21     2    23\n -1.6582794027459599E-01 a      2349     1    21     2    24\n -2.1114013691856662E-01 a      2350     1    21     2    25\n  2.4212589160209405E-01 a      2351     1    22     2     1\n  3.9327330796009152E-01 a      2352     1    22     2     2\n -3.6566016634832049E-01 a      2353     1    22     2     3\n  1.0287117668616212E+00 a      2354     1    22     2     4\n  1.6899708282115562E+00 a      2355     1    22     2     5\n  4.3429485581693034E-01 a      2356     1    22     2     6\n  1.7977381066015556E+00 a      2357     1    22     2     7\n  2.9196281691007775E-01 a      2358     1    22     2     8\n  8.9048235778413076E-01 a      2359     1    22     2     9\n -2.7029855626099626E+00 a      2360     1    22     2    10\n -9.9842398461553661E-01 a      2361     1    22     2    11\n  1.3261280174131618E-01 a      2362     1    22     2    12\n  7.8677628275123768E-01 a      2363     1    22     2    13\n -1.6176772224659823E+00 a      2364     1    22     2    14\n -2.9218429770545273E+00 a      2365     1    22     2    15\n -1.0470075932239322E+00 a      2366     1    22     2    16\n -6.2813242798639934E-01 a      2367     1    22     2    17\n -1.1926621420051280E+00 a      2368     1    22     2    18\n  5.6467524440711148E-01 a      2369     1    22     2    19\n  7.0550764585496206E-01 a      2370     1    22     2    20\n  6.7061497370680800E-01 a      2371     1    22     2    21\n  3.2149813491975643E-01 a      2372     1    22     2    22\n -6.5948083157745863E-01 a      2373     1    22     2    23\n  1.4878019494104766E-01 a      2374     1    22     2    24\n -1.4238392562512412E+00 a      2375     1    22     2    25\n -2.9244659427496789E+00 a      2376     1    23     2     1\n  1.1485640801249154E-01 a      2377     1    23     2     2\n  1.1880136805560255E-01 a      2378     1    23     2     3\n  1.9995339152108655E+00 a      2379     1    23     2     4\n -8.8052571584319517E-01 a      2380     1    23     2     5\n -7.6723479106454269E+00 a      2381     1    23     2     6\n -1.6775055426770660E-01 a      2382     1    23     2     7\n  1.1568877491878693E+00 a      2383     1    23     2     8\n -3.6248359285478049E-01 a      2384     1    23     2     9\n -1.0171667144821397E+00 a      2385     1    23     2    10\n -9.7885097010848721E-01 a      2386     1    23     2    11\n  1.7525905926099136E-01 a      2387     1    23     2    12\n  1.6667129102202356E+00 a      2388     1    23     2    13\n -6.3496168416867071E-01 a      2389     1    23     2    14\n -3.9752798317985540E+00 a      2390     1    23     2    15\n -3.0889419514464751E+00 a      2391     1    23     2    16\n -1.6580901185939814E-01 a      2392     1    23     2    17\n -3.0257630892267329E-01 a      2393     1    23     2    18\n  1.1693501120123342E+00 a      2394     1    23     2    19\n -4.4706334843197343E-01 a      2395     1    23     2    20\n  6.3453286866045877E-01 a      2396     1    23     2    21\n  1.9358044980890732E+00 a      2397     1    23     2    22\n  3.1113852281756920E+00 a      2398     1    23     2    23\n -1.9662951755400133E+00 a      2399     1    23     2    24\n -7.5262034829552482E-01 a      2400     1    23     2    25\n -1.0570204013747100E+00 a      2401     1    24     2     1\n  2.0242154350721828E-01 a      2402     1    24     2     2\n -6.1919254330906649E-02 a      2403     1    24     2     3\n -9.3075303350374716E-01 a      2404     1    24     2     4\n -9.4855833806427159E-01 a      2405     1    24     2     5\n  1.2813916759344554E-01 a      2406     1    24     2     6\n -2.0331973717312746E+00 a      2407     1    24     2     7\n  3.0837174823873076E-01 a      2408     1    24     2     8\n  3.7215037809188369E-02 a      2409     1    24     2     9\n  3.9279821894082573E-01 a      2410     1    24     2    10\n  1.1362819017641221E-01 a      2411     1    24     2    11\n -1.3856723422770947E-01 a      2412     1    24     2    12\n -9.0761795928204336E-01 a      2413     1    24     2    13\n -1.9312687936000594E+00 a      2414     1    24     2    14\n  2.4072402343893264E+00 a      2415     1    24     2    15\n -1.3575532169402038E+00 a      2416     1    24     2    16\n -5.0043337242109498E-01 a      2417     1    24     2    17\n  6.6622788206750017E-01 a      2418     1    24     2    18\n -2.7744853244980633E-01 a      2419     1    24     2    19\n -3.3208589628698015E-01 a      2420     1    24     2    20\n -6.5082760242357884E-01 a      2421     1    24     2    21\n -7.4238152455462947E-01 a      2422     1    24     2    22\n  3.5709111009352618E-01 a      2423     1    24     2    23\n  6.1990222796862571E-01 a      2424     1    24     2    24\n  1.1667603307669538E+00 a      2425     1    24     2    25\n  3.4874499133420743E-02 a      2426     1    25     2     1\n  4.6834087122092077E-01 a      2427     1    25     2     2\n -2.4278656264438364E-01 a      2428     1    25     2     3\n -4.7923572182631186E-01 a      2429     1    25     2     4\n  9.1932774354097346E-01 a      2430     1    25     2     5\n  6.9805008912145541E-03 a      2431     1    25     2     6\n -4.0244240337174698E-02 a      2432     1    25     2     7\n  2.3085018839417204E-01 a      2433     1    25     2     8\n  4.1477758640374958E-02 a      2434     1    25     2     9\n -2.9907893871952584E-01 a      2435     1    25     2    10\n  9.9861813798121868E-01 a      2436     1    25     2    11\n  6.1719473832720140E-01 a      2437     1    25     2    12\n  7.7349291753880958E-02 a      2438     1    25     2    13\n  1.9789467747705813E-01 a      2439     1    25     2    14\n -1.6963001394405985E+00 a      2440     1    25     2    15\n  1.6964283624354803E+00 a      2441     1    25     2    16\n -1.2412318165627852E-02 a      2442     1    25     2    17\n -3.0090042509304782E+00 a      2443     1    25     2    18\n -5.2854050109483008E-01 a      2444     1    25     2    19\n -4.0883552444931642E-01 a      2445     1    25     2    20\n -6.7332635048994605E-01 a      2446     1    25     2    21\n -1.9391822634747917E-02 a      2447     1    25     2    22\n  3.7493997817479574E-01 a      2448     1    25     2    23\n -3.1982153221239995E-01 a      2449     1    25     2    24\n -6.5908145380152439E-02 a      2450     1    25     2    25\n  3.6520581763320918E+00 b      2451     2     1\n  8.0350355841113590E+00 b      2452     2     2\n  1.0328413848960700E+00 b      2453     2     3\n  7.2118044450618859E+00 b      2454     2     4\n  1.6897857032469032E+00 b      2455     2     5\n -5.3128298088875221E+00 b      2456     2     6\n  1.1119283095513778E+01 b      2457     2     7\n  5.6335078037870667E-01 b      2458     2     8\n  3.1863573747908753E+00 b      2459     2     9\n -1.5027072914328254E+01 b      2460     2    10\n  4.2491825701309507E+00 b      2461     2    11\n  1.1953389718194374E+00 b      2462     2    12\n -3.7826613521070804E+00 b      2463     2    13\n  2.5804189796272916E+00 b      2464     2    14\n -1.8825899893966049E+01 b      2465     2    15\n  5.0689924546781171E+00 b      2466     2    16\n -4.2675620759638759E+00 b      2467     2    17\n -2.2492760679197388E+00 b      2468     2    18\n  3.5306849260434596E+00 b      2469     2    19\n -4.5612849025174862E+00 b      2470     2    20\n  2.5261284082068989E+00 b      2471     2    21\n  4.9997935137889167E+00 b      2472     2    22\n -1.0317047947417777E+01 b      2473     2    23\n -8.8894968314347089E+00 b      2474     2    24\n -2.4854869056932949E+00 b      2475     2    25\n  7.7377789653328519E-02 a      2476     2     1     3     1\n  3.8948596770158572E-01 a      2477     2     2     3     1\n  1.7977756447195445E-01 a      2478     2     3     3     1\n  6.2246542349685442E-02 a      2479     2     4     3     1\n -1.1775426437182669E-02 a      2480     2     5     3     1\n  7.4084231368981346E-02 a      2481     2     6     3     1\n -2.6739218038996107E-02 a      2482     2     7     3     1\n -1.4199418404546765E-01 a      2483     2     8     3     1\n -1.3644380226489719E-01 a      2484     2     9     3     1\n  4.2740071857011105E-02 a      2485     2    10     3     1\n -8.4658663941687990E-03 a      2486     2    11     3     1\n  1.8776930772068579E-01 a      2487     2    12     3     1\n -6.7008756457919524E-02 a      2488     2    13     3     1\n  4.7698142607044192E-02 a      2489     2    14     3     1\n -1.3372183470389412E-01 a      2490     2    15     3     1\n  4.0870498106272558E-02 a      2491     2    16     3     1\n  1.7572570907757842E-01 a      2492     2    17     3     1\n -1.6327794687227459E-01 a      2493     2    18     3     1\n -5.9707729641314558E-02 a      2494     2    19     3     1\n  1.0563906282310645E-01 a      2495     2    20     3     1\n  6.6231803238242182E-02 a      2496     2    21     3     1\n -2.7962585890502650E-01 a      2497     2    22     3     1\n  1.6032832788645526E-01 a      2498     2    23     3     1\n -1.0623041830538342E-01 a      2499     2    24     3     1\n  1.0896429147371821E-01 a      2500     2    25     3     1\n -1.3407810853851474E+00 b      2501     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE_external/hdnnp-data/weights.029.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -6.2446602207005186E-01 a         1     0     1     1     1\n  7.9109168478070069E-01 a         2     0     1     1     2\n  5.0258947941284748E-01 a         3     0     1     1     3\n  5.5154910097820120E-01 a         4     0     1     1     4\n  1.4505158314343458E+00 a         5     0     1     1     5\n -3.6571470924977034E-01 a         6     0     1     1     6\n  4.7092493582249750E-01 a         7     0     1     1     7\n  1.7219501990786370E+00 a         8     0     1     1     8\n -1.3599868727171069E-01 a         9     0     1     1     9\n  5.5171059902123576E-01 a        10     0     1     1    10\n -1.3239450297968971E+00 a        11     0     1     1    11\n  7.9289101991721189E-01 a        12     0     1     1    12\n -2.4436241907430895E-01 a        13     0     1     1    13\n  1.2669669007011655E+00 a        14     0     1     1    14\n -1.0859472353178850E+00 a        15     0     1     1    15\n  5.7149297331656246E-01 a        16     0     1     1    16\n  1.1787879403665555E+00 a        17     0     1     1    17\n  5.1959050316647970E-01 a        18     0     1     1    18\n -5.2070371830737283E-01 a        19     0     1     1    19\n -8.6539404799579653E-02 a        20     0     1     1    20\n -1.1403926908826987E+00 a        21     0     1     1    21\n  7.2846619332612425E-02 a        22     0     1     1    22\n -6.0675985144277489E-01 a        23     0     1     1    23\n  1.6628179166765720E+00 a        24     0     1     1    24\n  1.0538483108672489E+00 a        25     0     1     1    25\n -7.0622748176492056E-01 a        26     0     2     1     1\n  1.0910592071347260E+00 a        27     0     2     1     2\n  2.4631386883986663E+00 a        28     0     2     1     3\n  1.1474600047546029E+00 a        29     0     2     1     4\n -2.7984407189871603E+00 a        30     0     2     1     5\n  1.0533577807665364E-02 a        31     0     2     1     6\n -5.0292118189174440E-01 a        32     0     2     1     7\n -2.2761190415250261E+00 a        33     0     2     1     8\n -1.2187992237701142E+00 a        34     0     2     1     9\n  3.3724765156968588E-02 a        35     0     2     1    10\n -3.9421452238268578E-01 a        36     0     2     1    11\n  8.4824888999103987E-01 a        37     0     2     1    12\n -1.2466531728713620E-01 a        38     0     2     1    13\n  1.2079681252116843E+00 a        39     0     2     1    14\n -9.0112129189102541E-01 a        40     0     2     1    15\n  1.6824118679571578E+00 a        41     0     2     1    16\n  3.3935207339432649E-01 a        42     0     2     1    17\n -6.0996462596068590E-01 a        43     0     2     1    18\n  2.0533210855615880E-01 a        44     0     2     1    19\n -8.8645148744139757E-01 a        45     0     2     1    20\n -8.5393507862220064E-01 a        46     0     2     1    21\n -8.5526839185724302E-01 a        47     0     2     1    22\n  1.2489032362439190E+00 a        48     0     2     1    23\n  1.0938354906306260E+00 a        49     0     2     1    24\n -2.6473483803801245E-01 a        50     0     2     1    25\n -8.5878129366894407E-01 a        51     0     3     1     1\n  1.0564533358250394E+00 a        52     0     3     1     2\n  5.6697850343574663E-01 a        53     0     3     1     3\n  2.1086070474971215E+00 a        54     0     3     1     4\n  3.8166154557138393E-01 a        55     0     3     1     5\n -1.4247279770394652E-01 a        56     0     3     1     6\n -5.9572071020060458E-01 a        57     0     3     1     7\n -1.0694188993944764E-01 a        58     0     3     1     8\n  1.5066623963754497E+00 a        59     0     3     1     9\n  1.8089065761782133E-01 a        60     0     3     1    10\n -2.7214036058537823E+00 a        61     0     3     1    11\n  5.9806847727363321E-01 a        62     0     3     1    12\n -6.1642316248623163E-01 a        63     0     3     1    13\n  1.3696608481313977E+00 a        64     0     3     1    14\n -1.7104667782680838E+00 a        65     0     3     1    15\n  3.4174228333518369E-01 a        66     0     3     1    16\n  2.1950204328903058E+00 a        67     0     3     1    17\n  1.4819471011296372E+00 a        68     0     3     1    18\n  8.6419598086195182E-01 a        69     0     3     1    19\n -1.9807673916649222E+00 a        70     0     3     1    20\n -8.1754981466548049E-01 a        71     0     3     1    21\n  8.5183964054601424E-01 a        72     0     3     1    22\n -1.1265351050299546E+00 a        73     0     3     1    23\n  3.1023051337695745E-01 a        74     0     3     1    24\n  2.7440424392777945E+00 a        75     0     3     1    25\n  2.2960298979188901E-01 a        76     0     4     1     1\n  4.7699142503296446E-02 a        77     0     4     1     2\n  6.0155337022245625E-01 a        78     0     4     1     3\n -1.9439503692815557E-01 a        79     0     4     1     4\n -2.8605530154913746E-02 a        80     0     4     1     5\n  5.5983316423300188E-03 a        81     0     4     1     6\n  9.7519204826929984E-01 a        82     0     4     1     7\n  2.9668852740436547E-01 a        83     0     4     1     8\n  4.8725450035125151E-01 a        84     0     4     1     9\n  2.1326287630079049E-01 a        85     0     4     1    10\n -7.3554692603307470E-01 a        86     0     4     1    11\n  5.3315910230702435E-01 a        87     0     4     1    12\n -5.0172823432095809E-02 a        88     0     4     1    13\n  1.0865253078708168E+00 a        89     0     4     1    14\n -1.0261853156045440E+00 a        90     0     4     1    15\n  2.6512919821052433E-01 a        91     0     4     1    16\n  1.0812812614858249E+00 a        92     0     4     1    17\n  5.1028631925899315E-01 a        93     0     4     1    18\n -2.2599179332603903E-01 a        94     0     4     1    19\n  7.5088913825415021E-02 a        95     0     4     1    20\n -1.2364446472765618E+00 a        96     0     4     1    21\n  7.5326701143038222E-01 a        97     0     4     1    22\n -2.6515244091963569E-01 a        98     0     4     1    23\n  1.6838686308480304E+00 a        99     0     4     1    24\n  4.4492731774876376E-01 a       100     0     4     1    25\n -6.6099920232044096E-01 a       101     0     5     1     1\n  1.0089031054636115E-01 a       102     0     5     1     2\n  6.6342762904664385E-02 a       103     0     5     1     3\n  4.5542810443153381E-01 a       104     0     5     1     4\n -1.6657987380644132E-01 a       105     0     5     1     5\n -8.7555923451999446E-02 a       106     0     5     1     6\n -5.0759948537866628E-01 a       107     0     5     1     7\n  1.6763463093097672E-01 a       108     0     5     1     8\n -5.0802820857751363E-01 a       109     0     5     1     9\n  6.5721089961406787E-01 a       110     0     5     1    10\n -1.7250321983253045E+00 a       111     0     5     1    11\n  3.6248667744583185E-01 a       112     0     5     1    12\n -1.4187643709855371E-01 a       113     0     5     1    13\n  1.8277813268335372E-01 a       114     0     5     1    14\n -2.8759067553024059E-01 a       115     0     5     1    15\n  1.6396175797308257E-01 a       116     0     5     1    16\n  4.8459268505242964E-01 a       117     0     5     1    17\n  1.1485781012576022E+00 a       118     0     5     1    18\n  5.1100172835951252E-01 a       119     0     5     1    19\n -9.6969998866484486E-01 a       120     0     5     1    20\n  2.9282365167621466E-01 a       121     0     5     1    21\n  1.9454366730362621E-01 a       122     0     5     1    22\n  3.3723039867517968E-01 a       123     0     5     1    23\n -1.9892929243485494E-01 a       124     0     5     1    24\n -7.1822973746603158E-01 a       125     0     5     1    25\n -6.8064782973022775E-01 a       126     0     6     1     1\n  1.8829906173635458E-01 a       127     0     6     1     2\n  8.1479476506818194E-01 a       128     0     6     1     3\n  8.8277352960690048E-01 a       129     0     6     1     4\n -1.1427613588950543E+00 a       130     0     6     1     5\n  3.0159781113246154E-01 a       131     0     6     1     6\n -6.6588549790596940E-01 a       132     0     6     1     7\n -3.5003459927148434E-01 a       133     0     6     1     8\n -1.5345874997486508E+00 a       134     0     6     1     9\n -2.4240783711001435E-01 a       135     0     6     1    10\n  6.3947769766304896E-01 a       136     0     6     1    11\n  4.1352767758563735E-01 a       137     0     6     1    12\n -1.9019289044167662E-01 a       138     0     6     1    13\n  6.5802349593562548E-01 a       139     0     6     1    14\n -2.8846900299080136E-01 a       140     0     6     1    15\n  1.8044674812699533E+00 a       141     0     6     1    16\n -5.9916590668694536E-01 a       142     0     6     1    17\n  1.0233762388247421E-01 a       143     0     6     1    18\n -1.8293705219837877E-01 a       144     0     6     1    19\n -4.7618220713345544E-01 a       145     0     6     1    20\n -6.7585128250473714E-01 a       146     0     6     1    21\n -6.6619987727158803E-01 a       147     0     6     1    22\n  1.3937539584448881E+00 a       148     0     6     1    23\n  1.1804472226031208E+00 a       149     0     6     1    24\n -1.0475143437784208E-01 a       150     0     6     1    25\n -5.0310349062450688E-01 a       151     0     7     1     1\n  3.0549253527946091E-01 a       152     0     7     1     2\n  2.1639018141171862E-03 a       153     0     7     1     3\n  9.6581676298511743E-01 a       154     0     7     1     4\n  7.7874943618349207E-02 a       155     0     7     1     5\n  8.3859302793542922E-02 a       156     0     7     1     6\n  1.7299832669890869E-03 a       157     0     7     1     7\n  2.9262810015651336E-01 a       158     0     7     1     8\n  1.7542214681324636E-01 a       159     0     7     1     9\n -2.8526127268586043E-01 a       160     0     7     1    10\n -5.4990409523663197E-01 a       161     0     7     1    11\n  1.3450068091702161E-01 a       162     0     7     1    12\n -1.4756996153937790E-01 a       163     0     7     1    13\n  2.9311237452477523E-01 a       164     0     7     1    14\n -7.2084298548573761E-02 a       165     0     7     1    15\n -8.5149614730888945E-02 a       166     0     7     1    16\n  9.2949085965140277E-01 a       167     0     7     1    17\n -2.8847043946794215E-01 a       168     0     7     1    18\n  4.1186911885861338E-01 a       169     0     7     1    19\n -5.4169485090346026E-01 a       170     0     7     1    20\n -3.5243695639465118E-02 a       171     0     7     1    21\n  3.1341789027127781E-02 a       172     0     7     1    22\n -2.8786714994989410E-01 a       173     0     7     1    23\n  2.7315793972504460E-01 a       174     0     7     1    24\n  1.1716570530670567E+00 a       175     0     7     1    25\n -5.1036135947851669E-01 a       176     0     8     1     1\n -1.3740271110517560E-01 a       177     0     8     1     2\n  4.8958222402524031E-02 a       178     0     8     1     3\n  3.3177672494990651E-01 a       179     0     8     1     4\n -2.3856000868246988E-01 a       180     0     8     1     5\n  4.1214983538548872E-01 a       181     0     8     1     6\n -9.8286694614992598E-01 a       182     0     8     1     7\n -5.4107034590118536E-02 a       183     0     8     1     8\n -1.4324705358476875E-01 a       184     0     8     1     9\n -3.0823277006517974E-01 a       185     0     8     1    10\n  1.1094081849455624E+00 a       186     0     8     1    11\n  1.5831813220006527E-01 a       187     0     8     1    12\n -7.8050742477211929E-02 a       188     0     8     1    13\n  1.4147217795488959E-01 a       189     0     8     1    14\n -3.6482920722359169E-01 a       190     0     8     1    15\n  2.0010515781611065E+00 a       191     0     8     1    16\n -3.7164167894211825E-01 a       192     0     8     1    17\n -1.3125516149697244E-02 a       193     0     8     1    18\n -4.1954663172842910E-02 a       194     0     8     1    19\n -1.0331434570137119E-01 a       195     0     8     1    20\n -1.8011393958889632E-01 a       196     0     8     1    21\n  1.3088400236386397E-01 a       197     0     8     1    22\n  1.1923413887217991E+00 a       198     0     8     1    23\n  3.7781840918971593E-01 a       199     0     8     1    24\n -1.9294958159048309E-01 a       200     0     8     1    25\n -3.3392447645114481E-01 a       201     0     9     1     1\n  1.7014988701747677E-01 a       202     0     9     1     2\n -2.7070863493070599E-02 a       203     0     9     1     3\n  7.4604630341273778E-02 a       204     0     9     1     4\n -1.5102715752534066E-02 a       205     0     9     1     5\n  1.5720699324567589E-01 a       206     0     9     1     6\n -6.1974554587877762E-01 a       207     0     9     1     7\n  5.4891362413614087E-03 a       208     0     9     1     8\n  2.0919388011889421E-02 a       209     0     9     1     9\n -9.6391241772834951E-02 a       210     0     9     1    10\n  7.7306858668673450E-01 a       211     0     9     1    11\n  3.1255109436960182E-01 a       212     0     9     1    12\n  7.7005492614491439E-02 a       213     0     9     1    13\n -2.4607006332823117E-02 a       214     0     9     1    14\n -1.0454167793466912E-01 a       215     0     9     1    15\n  5.7967244318170463E-01 a       216     0     9     1    16\n -1.2093767067885464E-01 a       217     0     9     1    17\n -2.2544971455810286E-01 a       218     0     9     1    18\n  2.1029853185087000E-01 a       219     0     9     1    19\n -1.9601661095545145E-01 a       220     0     9     1    20\n -5.1292763498012379E-02 a       221     0     9     1    21\n  1.4590455721615306E-01 a       222     0     9     1    22\n  4.6964108851222075E-01 a       223     0     9     1    23\n  5.7481385069930169E-02 a       224     0     9     1    24\n -2.0098849633862609E-01 a       225     0     9     1    25\n  4.8244923506134771E+00 a       226     0    10     1     1\n  3.5108916592109578E+00 a       227     0    10     1     2\n  7.5139348670019617E+00 a       228     0    10     1     3\n -3.5578918915946471E+00 a       229     0    10     1     4\n  2.8386058903754559E+00 a       230     0    10     1     5\n  4.4207199746823003E+00 a       231     0    10     1     6\n -3.3412935119326561E+00 a       232     0    10     1     7\n -9.0971866563833217E+00 a       233     0    10     1     8\n -4.5268654758530369E+00 a       234     0    10     1     9\n -5.5872647360635401E+00 a       235     0    10     1    10\n -2.0635169275427789E+00 a       236     0    10     1    11\n -1.5340623877597045E+01 a       237     0    10     1    12\n -8.3715082878395020E+00 a       238     0    10     1    13\n -6.4817382472795639E+00 a       239     0    10     1    14\n -5.0809375777610395E+00 a       240     0    10     1    15\n -6.4689687360330987E+00 a       241     0    10     1    16\n  2.1416014963815999E+00 a       242     0    10     1    17\n  6.8940758724466367E+00 a       243     0    10     1    18\n -4.3648169145202758E+00 a       244     0    10     1    19\n  9.0382653292775696E+00 a       245     0    10     1    20\n -9.9166110945066848E+00 a       246     0    10     1    21\n -1.2044366652841560E+01 a       247     0    10     1    22\n  2.2720545079306909E+01 a       248     0    10     1    23\n -3.7379508213234649E+00 a       249     0    10     1    24\n -4.5209017693635660E+00 a       250     0    10     1    25\n  7.5183832154301431E+00 a       251     0    11     1     1\n -2.3203106234194992E+00 a       252     0    11     1     2\n  1.4841440810090241E+00 a       253     0    11     1     3\n  9.6482513939399706E-01 a       254     0    11     1     4\n -8.4297506087479601E-01 a       255     0    11     1     5\n -4.6990364184782007E-01 a       256     0    11     1     6\n -1.0961424660272627E+00 a       257     0    11     1     7\n -2.7374480650608306E+00 a       258     0    11     1     8\n  3.1380660893974572E+00 a       259     0    11     1     9\n  1.4968023108710922E+00 a       260     0    11     1    10\n  4.8431460218952400E-02 a       261     0    11     1    11\n -1.1491977088084576E+01 a       262     0    11     1    12\n -8.0416563043774918E+00 a       263     0    11     1    13\n -2.5360493765208667E+00 a       264     0    11     1    14\n  7.9109477782628268E-01 a       265     0    11     1    15\n -7.2962300446546091E-01 a       266     0    11     1    16\n -1.2513868916478101E+00 a       267     0    11     1    17\n -2.7011654742543052E+00 a       268     0    11     1    18\n  2.4531950654664225E+00 a       269     0    11     1    19\n -1.0070370759062769E+01 a       270     0    11     1    20\n  7.9155519637009908E+00 a       271     0    11     1    21\n 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1.6244338649202151E-02 a      1893     1     9     2    18\n  2.8159940956926782E-02 a      1894     1     9     2    19\n -7.3760105274932919E-01 a      1895     1     9     2    20\n  1.0604614152784235E-01 a      1896     1     9     2    21\n  1.3087759494518761E-01 a      1897     1     9     2    22\n  2.9873262087000452E-01 a      1898     1     9     2    23\n -7.5121649539691160E-01 a      1899     1     9     2    24\n -5.3923107796072600E-01 a      1900     1     9     2    25\n -9.4224670371027917E-03 a      1901     1    10     2     1\n  1.7582720220947401E-01 a      1902     1    10     2     2\n -4.3499560356818456E-02 a      1903     1    10     2     3\n  2.7310295785198496E-01 a      1904     1    10     2     4\n -1.4711568084768856E+00 a      1905     1    10     2     5\n -4.4204405689495387E-02 a      1906     1    10     2     6\n  6.0834648389602855E-02 a      1907     1    10     2     7\n -2.4139577578874571E+00 a      1908     1    10     2     8\n -3.2330445150185877E-01 a      1909     1    10     2     9\n -6.8558897710748834E-01 a      1910     1    10     2    10\n -2.6306695094273136E-01 a      1911     1    10     2    11\n -2.9406094777407277E+00 a      1912     1    10     2    12\n -1.0262257550335584E-01 a      1913     1    10     2    13\n -4.4889806212745592E-01 a      1914     1    10     2    14\n  1.2729127190479747E-01 a      1915     1    10     2    15\n -5.4339870455363115E-01 a      1916     1    10     2    16\n -4.3051833335864892E-01 a      1917     1    10     2    17\n  2.2774840440979685E-01 a      1918     1    10     2    18\n -4.6577095617807179E-01 a      1919     1    10     2    19\n  6.7677527850068725E-02 a      1920     1    10     2    20\n -5.4331229454547138E-02 a      1921     1    10     2    21\n -7.2517226150440761E-01 a      1922     1    10     2    22\n -1.1034679805264240E+00 a      1923     1    10     2    23\n -2.0195864669569050E+00 a      1924     1    10     2    24\n  3.4421830988038693E-01 a      1925     1    10     2    25\n  6.4169421416549660E-02 a      1926     1    11     2     1\n -1.5453028953359832E-01 a      1927     1    11     2     2\n -3.3937811286737152E-01 a      1928     1    11     2     3\n -2.7264685928399618E-02 a      1929     1    11     2     4\n -1.3046027284183024E+00 a      1930     1    11     2     5\n -2.7987570911040532E-01 a      1931     1    11     2     6\n -7.1818879614311160E-01 a      1932     1    11     2     7\n -1.1206386399096295E+00 a      1933     1    11     2     8\n  5.8589221854259044E-01 a      1934     1    11     2     9\n -3.7755430943908636E-01 a      1935     1    11     2    10\n -2.4227661602201420E-01 a      1936     1    11     2    11\n -6.6802170984862275E-01 a      1937     1    11     2    12\n -1.0335031399378087E+00 a      1938     1    11     2    13\n  2.7352884921752563E-01 a      1939     1    11     2    14\n -7.7644903482906286E-02 a      1940     1    11     2    15\n -1.2483161225817251E-01 a      1941     1    11     2    16\n -1.0076823380037454E-01 a      1942     1    11     2    17\n  1.8474479042673506E-02 a      1943     1    11     2    18\n  1.5921923675493641E-01 a      1944     1    11     2    19\n -8.6092467903913172E-01 a      1945     1    11     2    20\n  3.1597658763496336E-02 a      1946     1    11     2    21\n  1.2582027961569384E-01 a      1947     1    11     2    22\n  4.1552569278194468E-01 a      1948     1    11     2    23\n -1.8547083512843898E-01 a      1949     1    11     2    24\n -3.1841028886761663E-01 a      1950     1    11     2    25\n  1.8006197092716905E-01 a      1951     1    12     2     1\n -5.4024199178819454E-01 a      1952     1    12     2     2\n  3.3523776691134710E-01 a      1953     1    12     2     3\n  2.7560028312601675E-01 a      1954     1    12     2     4\n  8.6177633437044554E-01 a      1955     1    12     2     5\n  1.0087407297301751E+00 a      1956     1    12     2     6\n -1.2380927066334282E-01 a      1957     1    12     2     7\n -1.5229780941544174E-01 a      1958     1    12     2     8\n  2.9946743134146903E-01 a      1959     1    12     2     9\n  1.9819105447401073E+00 a      1960     1    12     2    10\n -8.0628486303151947E-01 a      1961     1    12     2    11\n -9.3151349622473523E-01 a      1962     1    12     2    12\n  1.5051328872455074E+00 a      1963     1    12     2    13\n -8.9627139441554438E-01 a      1964     1    12     2    14\n -3.1439437993199801E-02 a      1965     1    12     2    15\n  1.3701630178002484E+00 a      1966     1    12     2    16\n -2.9138443586057278E-01 a      1967     1    12     2    17\n -3.9087530619619010E-01 a      1968     1    12     2    18\n -2.2753042561066517E-01 a      1969     1    12     2    19\n -8.0931038915796594E-01 a      1970     1    12     2    20\n  1.2030804656668543E+00 a      1971     1    12     2    21\n -1.3389862350446610E-01 a      1972     1    12     2    22\n  4.8419262676478225E-01 a      1973     1    12     2    23\n  1.2108153439974718E+00 a      1974     1    12     2    24\n -1.9519966513619349E+00 a      1975     1    12     2    25\n -1.5047045953264607E-01 a      1976     1    13     2     1\n -6.5196314968694580E-01 a      1977     1    13     2     2\n -1.9444580576963033E-01 a      1978     1    13     2     3\n -3.0635873068371338E-03 a      1979     1    13     2     4\n  1.4891889558793558E+00 a      1980     1    13     2     5\n -2.7617795790820687E-01 a      1981     1    13     2     6\n  1.3155600760922213E+00 a      1982     1    13     2     7\n  1.6548881500952060E+00 a      1983     1    13     2     8\n  1.2939743974749243E+00 a      1984     1    13     2     9\n -8.8087806931438950E-01 a      1985     1    13     2    10\n -7.3026619095577089E-02 a      1986     1    13     2    11\n -6.7521271933403364E+00 a      1987     1    13     2    12\n  3.4361606414546986E-01 a      1988     1    13     2    13\n  8.7558578977526269E-01 a      1989     1    13     2    14\n -2.2881702674887253E-01 a      1990     1    13     2    15\n -6.2816527553206336E-01 a      1991     1    13     2    16\n -8.9317308141201190E-01 a      1992     1    13     2    17\n  9.7069680211539489E-01 a      1993     1    13     2    18\n -5.6927576536010438E-01 a      1994     1    13     2    19\n  8.2910381395357602E-01 a      1995     1    13     2    20\n -3.8934674186907103E-01 a      1996     1    13     2    21\n -1.0181364553104701E+00 a      1997     1    13     2    22\n -9.1002882788836370E-01 a      1998     1    13     2    23\n  2.1075571090156360E+00 a      1999     1    13     2    24\n  2.3017239447035212E-01 a      2000     1    13     2    25\n -3.5483123954045620E-01 a      2001     1    14     2     1\n -9.6047986054177317E-02 a      2002     1    14     2     2\n  3.3071183118138114E-01 a      2003     1    14     2     3\n  1.7705379181791761E-01 a      2004     1    14     2     4\n -1.2043718203406772E+00 a      2005     1    14     2     5\n -5.7806038919408154E-01 a      2006     1    14     2     6\n  6.5633162044623850E-01 a      2007     1    14     2     7\n -1.3450535190144031E-01 a      2008     1    14     2     8\n -1.2862521179205477E-01 a      2009     1    14     2     9\n -1.5177254021629161E-01 a      2010     1    14     2    10\n -2.9016357432381029E-01 a      2011     1    14     2    11\n  1.2793982277409728E+00 a      2012     1    14     2    12\n -3.7109006944139383E-01 a      2013     1    14     2    13\n -4.5064222698368622E-01 a      2014     1    14     2    14\n  3.9087439217392134E-02 a      2015     1    14     2    15\n -1.7890737007331405E+00 a      2016     1    14     2    16\n -3.5761366598992050E-01 a      2017     1    14     2    17\n  3.8280249413524364E-01 a      2018     1    14     2    18\n -3.4580266787944813E-01 a      2019     1    14     2    19\n -2.3102511719307051E-01 a      2020     1    14     2    20\n  6.1712210683785684E-02 a      2021     1    14     2    21\n -3.3548067811281668E-01 a      2022     1    14     2    22\n -7.9862203729164616E-01 a      2023     1    14     2    23\n -5.1952466530501407E-01 a      2024     1    14     2    24\n  2.5810393446929092E-01 a      2025     1    14     2    25\n -4.3558412131876484E-01 a      2026     1    15     2     1\n  1.1902629233075568E-01 a      2027     1    15     2     2\n  1.1747512026211912E-01 a      2028     1    15     2     3\n  1.5495247101048408E-02 a      2029     1    15     2     4\n -1.2065420500806932E+00 a      2030     1    15     2     5\n  3.3479165215501783E-01 a      2031     1    15     2     6\n  2.8245317600466197E-01 a      2032     1    15     2     7\n  6.6749992551384099E-02 a      2033     1    15     2     8\n -3.1396609925815760E-01 a      2034     1    15     2     9\n  3.0054714990159620E-01 a      2035     1    15     2    10\n  6.0483428643207637E-01 a      2036     1    15     2    11\n -1.2454958402656351E+00 a      2037     1    15     2    12\n  6.3389744137669779E-01 a      2038     1    15     2    13\n -5.9521423079842484E-01 a      2039     1    15     2    14\n  1.2019169256706089E-01 a      2040     1    15     2    15\n -1.1987245524864630E-01 a      2041     1    15     2    16\n -5.6896152994198784E-02 a      2042     1    15     2    17\n  2.8941200439853954E-01 a      2043     1    15     2    18\n  1.6309209946798925E-01 a      2044     1    15     2    19\n  8.7949523201494928E-01 a      2045     1    15     2    20\n  6.4769343609644300E-02 a      2046     1    15     2    21\n  4.8521193987474981E-01 a      2047     1    15     2    22\n  4.9988972941182691E-01 a      2048     1    15     2    23\n -2.3016622688408100E-01 a      2049     1    15     2    24\n -5.4074197586570194E-01 a      2050     1    15     2    25\n -4.8573302372386212E-01 a      2051     1    16     2     1\n -1.2895431219807293E-01 a      2052     1    16     2     2\n -3.6183115010678968E-01 a      2053     1    16     2     3\n -1.9197089311858578E-01 a      2054     1    16     2     4\n  1.6791441443786570E+00 a      2055     1    16     2     5\n  1.4524232953370153E+00 a      2056     1    16     2     6\n  8.1332800345877809E-01 a      2057     1    16     2     7\n -6.8993826377906453E-01 a      2058     1    16     2     8\n -6.4581623589215043E-01 a      2059     1    16     2     9\n -1.9086496482644792E+00 a      2060     1    16     2    10\n -7.6174424886678238E-01 a      2061     1    16     2    11\n -6.6106476479584952E-01 a      2062     1    16     2    12\n -6.5143307233530923E-01 a      2063     1    16     2    13\n  6.3145424574265796E-01 a      2064     1    16     2    14\n -2.3081494763260896E-01 a      2065     1    16     2    15\n  1.1456064040705682E-01 a      2066     1    16     2    16\n  1.6252315194690317E-01 a      2067     1    16     2    17\n -1.2291397585047813E-01 a      2068     1    16     2    18\n -6.7674808608296347E-02 a      2069     1    16     2    19\n  5.4942310825997287E-01 a      2070     1    16     2    20\n -1.0797615834794017E-01 a      2071     1    16     2    21\n  2.4950326732348715E-01 a      2072     1    16     2    22\n -7.9414639176233692E-01 a      2073     1    16     2    23\n  2.0544441738751792E-01 a      2074     1    16     2    24\n  1.8992443483722937E-01 a      2075     1    16     2    25\n -4.6582766497660771E-01 a      2076     1    17     2     1\n  2.9539156697999569E-01 a      2077     1    17     2     2\n -2.2097168205408066E-01 a      2078     1    17     2     3\n -1.4860622629638501E-01 a      2079     1    17     2     4\n -3.2498215361218613E-01 a      2080     1    17     2     5\n  3.4427076522021333E-01 a      2081     1    17     2     6\n  8.6586127926198697E-01 a      2082     1    17     2     7\n -1.1418000025514305E-01 a      2083     1    17     2     8\n -6.0056682073398004E-01 a      2084     1    17     2     9\n  2.0450736509644665E-01 a      2085     1    17     2    10\n -1.8519278941182027E-01 a      2086     1    17     2    11\n -1.4644629512368172E+00 a      2087     1    17     2    12\n -2.9378404760799470E-01 a      2088     1    17     2    13\n  5.5384788915605931E-01 a      2089     1    17     2    14\n -1.5004256050064771E-01 a      2090     1    17     2    15\n  3.2806846888851510E-01 a      2091     1    17     2    16\n  2.7598536643862270E-01 a      2092     1    17     2    17\n  4.1850888007058207E-01 a      2093     1    17     2    18\n -5.5362304975505497E-02 a      2094     1    17     2    19\n  2.6951266238898874E-01 a      2095     1    17     2    20\n -2.4264170360616094E-02 a      2096     1    17     2    21\n -1.8676465863061775E-01 a      2097     1    17     2    22\n -3.8787011654837039E-01 a      2098     1    17     2    23\n  3.4485637458118229E-01 a      2099     1    17     2    24\n -3.0786400824237545E-02 a      2100     1    17     2    25\n -1.4217762050351745E-01 a      2101     1    18     2     1\n -7.0998782591968046E-01 a      2102     1    18     2     2\n -9.6362930548428383E-01 a      2103     1    18     2     3\n  7.5180370041830813E-02 a      2104     1    18     2     4\n  9.3452511163166374E-01 a      2105     1    18     2     5\n  7.5072353982545093E-01 a      2106     1    18     2     6\n -1.4600462437868158E+00 a      2107     1    18     2     7\n -1.0484471284226574E-01 a      2108     1    18     2     8\n -1.5226425654047304E+00 a      2109     1    18     2     9\n -8.8296305768438263E-02 a      2110     1    18     2    10\n -3.6274389516383643E-01 a      2111     1    18     2    11\n  8.8349447132068071E-01 a      2112     1    18     2    12\n  3.6371290147774743E-01 a      2113     1    18     2    13\n -4.7916817706816656E-01 a      2114     1    18     2    14\n  1.3662341082955812E-01 a      2115     1    18     2    15\n  1.3172314297178116E+00 a      2116     1    18     2    16\n  3.4403068584860565E-02 a      2117     1    18     2    17\n  3.6061432566306936E-02 a      2118     1    18     2    18\n  4.5896212647717503E-02 a      2119     1    18     2    19\n -1.8589693017644275E+00 a      2120     1    18     2    20\n  1.5237137982152765E-01 a      2121     1    18     2    21\n -3.8234921593024973E-01 a      2122     1    18     2    22\n  3.5542438141750315E-02 a      2123     1    18     2    23\n -3.9944133636062124E-01 a      2124     1    18     2    24\n -6.5550378551330324E-01 a      2125     1    18     2    25\n  1.2816550559385723E-01 a      2126     1    19     2     1\n  3.5486759391369166E-02 a      2127     1    19     2     2\n  4.6182319454349319E-01 a      2128     1    19     2     3\n -5.5122652267036590E-03 a      2129     1    19     2     4\n -3.5080949888496260E+00 a      2130     1    19     2     5\n  7.1486948663206473E-01 a      2131     1    19     2     6\n -2.1201853030552007E+00 a      2132     1    19     2     7\n  7.2604028903282403E-01 a      2133     1    19     2     8\n  5.1081128242304719E-01 a      2134     1    19     2     9\n -4.9137504534121196E-01 a      2135     1    19     2    10\n -1.0472694822448174E+00 a      2136     1    19     2    11\n -1.3523763718593251E+00 a      2137     1    19     2    12\n  2.3568530190159431E-01 a      2138     1    19     2    13\n  5.9584736557607831E-01 a      2139     1    19     2    14\n -3.0079808992756946E-02 a      2140     1    19     2    15\n -1.5268283743999284E-01 a      2141     1    19     2    16\n  9.6122412178057212E-02 a      2142     1    19     2    17\n -1.0684936989401796E-01 a      2143     1    19     2    18\n -5.7716017213991798E-02 a      2144     1    19     2    19\n -2.1338482417439314E-01 a      2145     1    19     2    20\n -3.2012152562395965E-02 a      2146     1    19     2    21\n  6.6195535336631889E-02 a      2147     1    19     2    22\n -4.0717271079249823E-01 a      2148     1    19     2    23\n  4.3854075768154355E-01 a      2149     1    19     2    24\n  5.4824793644114189E-01 a      2150     1    19     2    25\n -1.6683810612646832E-01 a      2151     1    20     2     1\n  2.3322749612412674E-01 a      2152     1    20     2     2\n -4.4183715955442193E-01 a      2153     1    20     2     3\n -7.2076827728753526E-02 a      2154     1    20     2     4\n -5.9352383243727491E-01 a      2155     1    20     2     5\n -3.9339117998165263E-01 a      2156     1    20     2     6\n -5.4931274369409873E-02 a      2157     1    20     2     7\n -4.5548835587531822E-01 a      2158     1    20     2     8\n -6.5732706177413358E-01 a      2159     1    20     2     9\n -1.1236237633542311E-01 a      2160     1    20     2    10\n  1.1351566319349074E-02 a      2161     1    20     2    11\n -1.2386831457708261E+00 a      2162     1    20     2    12\n  4.5243628166561789E-01 a      2163     1    20     2    13\n -5.8831183211013338E-01 a      2164     1    20     2    14\n -8.3869411335455488E-02 a      2165     1    20     2    15\n -7.0984549162019170E-02 a      2166     1    20     2    16\n  3.3054811913793787E-02 a      2167     1    20     2    17\n  1.9644857020909354E-01 a      2168     1    20     2    18\n  1.5161782757226400E-01 a      2169     1    20     2    19\n -2.3505702805909551E-01 a      2170     1    20     2    20\n -1.7918789556131143E-01 a      2171     1    20     2    21\n  3.4990356667744421E-01 a      2172     1    20     2    22\n  6.4840494486623490E-01 a      2173     1    20     2    23\n -1.4478590661265617E-01 a      2174     1    20     2    24\n  2.1297816904812697E-01 a      2175     1    20     2    25\n  3.4493308448955345E-01 a      2176     1    21     2     1\n  3.5266855354427494E-02 a      2177     1    21     2     2\n -2.7754410875303576E-01 a      2178     1    21     2     3\n  4.6768620046741878E-02 a      2179     1    21     2     4\n -1.5769313809619548E-01 a      2180     1    21     2     5\n  1.3497835265205210E-01 a      2181     1    21     2     6\n -3.7341652004504744E-01 a      2182     1    21     2     7\n -3.0627556863254835E-01 a      2183     1    21     2     8\n -2.2925939617710103E-01 a      2184     1    21     2     9\n -3.8592084381092573E-01 a      2185     1    21     2    10\n  4.1234641447800625E-02 a      2186     1    21     2    11\n -9.5022250284578980E-01 a      2187     1    21     2    12\n -1.1125930303081784E+00 a      2188     1    21     2    13\n -5.3122650273704952E-01 a      2189     1    21     2    14\n  2.3060682491837362E-02 a      2190     1    21     2    15\n -1.5104224681786016E+00 a      2191     1    21     2    16\n  1.4753038731650985E-03 a      2192     1    21     2    17\n  1.5143866707297242E-02 a      2193     1    21     2    18\n  8.6090707736472302E-02 a      2194     1    21     2    19\n -6.2430761394861624E-02 a      2195     1    21     2    20\n -6.1308060604509992E-03 a      2196     1    21     2    21\n -1.4270727537208755E-01 a      2197     1    21     2    22\n  4.1134552752308873E-01 a      2198     1    21     2    23\n -6.8567787253466550E-01 a      2199     1    21     2    24\n -6.7206916205524492E-01 a      2200     1    21     2    25\n -1.5391019835641329E+00 a      2201     1    22     2     1\n  1.7206752534353434E-01 a      2202     1    22     2     2\n  6.7593465480848644E-02 a      2203     1    22     2     3\n -8.5997555363846803E-02 a      2204     1    22     2     4\n -9.6065684505879689E-01 a      2205     1    22     2     5\n  1.1113173657279094E+00 a      2206     1    22     2     6\n -3.0842014372062625E+00 a      2207     1    22     2     7\n -1.4384158041499902E+00 a      2208     1    22     2     8\n  1.1309101459634252E+00 a      2209     1    22     2     9\n  1.5105165505154550E-01 a      2210     1    22     2    10\n  3.0645396828385907E-01 a      2211     1    22     2    11\n  6.4601478772770526E-01 a      2212     1    22     2    12\n  4.8724111088572403E-01 a      2213     1    22     2    13\n -4.6620160034283531E-01 a      2214     1    22     2    14\n -4.8803479432276621E-02 a      2215     1    22     2    15\n -9.0430630054920480E-01 a      2216     1    22     2    16\n -6.9889480249312042E-01 a      2217     1    22     2    17\n -1.4468447857571731E+00 a      2218     1    22     2    18\n  2.3039464990726008E-01 a      2219     1    22     2    19\n  5.4576177723516872E-01 a      2220     1    22     2    20\n -7.8015018576137352E-02 a      2221     1    22     2    21\n -1.6133123661713483E-01 a      2222     1    22     2    22\n -1.8319296597374665E-01 a      2223     1    22     2    23\n  2.7253642896910552E-01 a      2224     1    22     2    24\n -1.1584411372851944E+00 a      2225     1    22     2    25\n -5.5424557394569851E-01 a      2226     1    23     2     1\n  7.0029876501251875E-01 a      2227     1    23     2     2\n  8.6637467798596698E-02 a      2228     1    23     2     3\n -7.8591217867498966E-02 a      2229     1    23     2     4\n -3.8578050693417802E+00 a      2230     1    23     2     5\n -1.5514902939375283E-02 a      2231     1    23     2     6\n  5.3013810166945474E-01 a      2232     1    23     2     7\n -6.0550270203294210E-01 a      2233     1    23     2     8\n  4.3671597358238062E-01 a      2234     1    23     2     9\n -3.5715147706396755E-01 a      2235     1    23     2    10\n  1.0882856270043771E-01 a      2236     1    23     2    11\n  1.7281037261210461E+00 a      2237     1    23     2    12\n -5.7515626421966193E-01 a      2238     1    23     2    13\n -1.3375042180867350E-01 a      2239     1    23     2    14\n -6.5503722712337037E-02 a      2240     1    23     2    15\n -2.2025191432304744E-02 a      2241     1    23     2    16\n -8.2655071054651752E-02 a      2242     1    23     2    17\n -2.1027511956094072E-01 a      2243     1    23     2    18\n  2.8902376330777999E-02 a      2244     1    23     2    19\n  1.3213999048426042E-01 a      2245     1    23     2    20\n -1.1460728829522189E-01 a      2246     1    23     2    21\n -5.8828720552246631E-02 a      2247     1    23     2    22\n -6.0152091553027887E-01 a      2248     1    23     2    23\n -7.1147789709956066E-01 a      2249     1    23     2    24\n  5.2100860083053230E-02 a      2250     1    23     2    25\n -1.4344935215141292E+00 a      2251     1    24     2     1\n  9.2746205501548851E-01 a      2252     1    24     2     2\n -7.7216665110619850E-02 a      2253     1    24     2     3\n -2.8798885399279067E-01 a      2254     1    24     2     4\n  3.7454428387915351E+00 a      2255     1    24     2     5\n -1.5625207926251825E+00 a      2256     1    24     2     6\n  3.6660395247444808E+00 a      2257     1    24     2     7\n  2.0253108718040456E+00 a      2258     1    24     2     8\n  1.6318897346220811E+00 a      2259     1    24     2     9\n  2.4800845209015692E+00 a      2260     1    24     2    10\n  1.4907673234653401E-01 a      2261     1    24     2    11\n -4.8613830479267428E-01 a      2262     1    24     2    12\n -6.2019617622102718E-01 a      2263     1    24     2    13\n  2.5952895630277122E+00 a      2264     1    24     2    14\n -4.5829312494493707E-01 a      2265     1    24     2    15\n -2.3487736500391203E+00 a      2266     1    24     2    16\n -3.0197296181118466E-01 a      2267     1    24     2    17\n -2.3095098659235344E-01 a      2268     1    24     2    18\n -3.3608639629945564E-01 a      2269     1    24     2    19\n  6.8582631891122880E-01 a      2270     1    24     2    20\n -5.0043316001326121E-01 a      2271     1    24     2    21\n  1.0373154633440593E-01 a      2272     1    24     2    22\n -1.6204291412423728E+00 a      2273     1    24     2    23\n  1.5638127191591980E+00 a      2274     1    24     2    24\n -2.3309635202853114E+00 a      2275     1    24     2    25\n  2.4489203274966312E-01 a      2276     1    25     2     1\n -2.1518661593071592E-01 a      2277     1    25     2     2\n -5.5802781061846052E-02 a      2278     1    25     2     3\n  4.8845808066633911E-02 a      2279     1    25     2     4\n -1.7557830120404228E-01 a      2280     1    25     2     5\n  2.7192371503339396E-01 a      2281     1    25     2     6\n  5.1576877441197089E-01 a      2282     1    25     2     7\n -2.5099882589234657E-01 a      2283     1    25     2     8\n  3.9307512202972061E-01 a      2284     1    25     2     9\n -1.1210987406922690E+00 a      2285     1    25     2    10\n -1.0439036996834390E-01 a      2286     1    25     2    11\n -4.6783720798261658E-01 a      2287     1    25     2    12\n -3.4722854444840895E-01 a      2288     1    25     2    13\n  3.6029120328851533E-01 a      2289     1    25     2    14\n -2.8984025140998956E-02 a      2290     1    25     2    15\n -2.4076394027143521E-02 a      2291     1    25     2    16\n -3.5643134150827477E-01 a      2292     1    25     2    17\n -8.0475176631190595E-02 a      2293     1    25     2    18\n -4.1056819128214495E-01 a      2294     1    25     2    19\n  7.9766759746990878E-02 a      2295     1    25     2    20\n -6.3351379628206916E-02 a      2296     1    25     2    21\n -6.6416236384591232E-01 a      2297     1    25     2    22\n  9.9799168900512741E-02 a      2298     1    25     2    23\n  3.6809534821907935E-01 a      2299     1    25     2    24\n  4.4938760583598990E-02 a      2300     1    25     2    25\n  1.2254169285344445E+00 b      2301     2     1\n -1.2971586668099495E+00 b      2302     2     2\n  1.5496818967172494E+00 b      2303     2     3\n -5.1016745940541508E+00 b      2304     2     4\n  1.0570990409883480E+01 b      2305     2     5\n -4.5156912340057982E+00 b      2306     2     6\n -5.3447216226080076E+00 b      2307     2     7\n  4.9121474463955411E-01 b      2308     2     8\n  1.8948035234025085E+00 b      2309     2     9\n  8.0589028128011697E-01 b      2310     2    10\n -1.7792287088770824E+00 b      2311     2    11\n  1.4582711867438684E+01 b      2312     2    12\n -1.7367556115635654E+00 b      2313     2    13\n -1.9740162795480241E+00 b      2314     2    14\n -2.4240966432157127E+00 b      2315     2    15\n -2.8599154334878940E+00 b      2316     2    16\n  4.0042881027206061E+00 b      2317     2    17\n -4.2248506318729575E+00 b      2318     2    18\n  4.0200826303003624E-02 b      2319     2    19\n -1.2474151269634015E+00 b      2320     2    20\n -9.2525707564953397E+00 b      2321     2    21\n  3.6900482337635778E+00 b      2322     2    22\n  1.2241959433351147E+01 b      2323     2    23\n -3.6270070547836308E+00 b      2324     2    24\n -9.9424710717210443E-02 b      2325     2    25\n -1.7929412362301902E-01 a      2326     2     1     3     1\n -7.9318720367251710E-02 a      2327     2     2     3     1\n -1.2245497150588677E-01 a      2328     2     3     3     1\n  2.6686957929803099E+00 a      2329     2     4     3     1\n  2.2208281256188907E-02 a      2330     2     5     3     1\n -1.3827880546853433E-01 a      2331     2     6     3     1\n  5.8883707570105491E-02 a      2332     2     7     3     1\n -1.8503473008958521E-01 a      2333     2     8     3     1\n  7.9941146090854662E-02 a      2334     2     9     3     1\n  6.0980780074337042E-02 a      2335     2    10     3     1\n  4.2898647862968903E-01 a      2336     2    11     3     1\n -1.6418700509588654E-02 a      2337     2    12     3     1\n  9.2626066276151567E-02 a      2338     2    13     3     1\n  1.6213121749951970E-01 a      2339     2    14     3     1\n  5.0025887501899446E-01 a      2340     2    15     3     1\n -9.3228633980085102E-02 a      2341     2    16     3     1\n -4.2506309509736678E-01 a      2342     2    17     3     1\n -2.8020236882301058E-01 a      2343     2    18     3     1\n  1.3369952476903810E+00 a      2344     2    19     3     1\n  7.6998543117290666E-02 a      2345     2    20     3     1\n  5.8165502415695283E+00 a      2346     2    21     3     1\n  4.9617644425128343E-01 a      2347     2    22     3     1\n  3.8051021746990116E-01 a      2348     2    23     3     1\n  1.1951241138280733E-01 a      2349     2    24     3     1\n  1.3087209279691459E-01 a      2350     2    25     3     1\n -2.6815621704168309E+00 b      2351     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/Cu2S_PBE_external/md.lmp",
    "content": "###############################################################################\n# MD simulation for NN copper sulfide\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"cu2s_144_low-chalcocite_Evans-1979_PBE.data\"\n# Timesteps\nvariable numSteps        equal  100\nvariable dt              equal  0.001\n# NN\nvariable hdnnpCutoff     equal  6.01\nvariable hdnnpDir        string \"hdnnp-data\"\n# Masses\nvariable mass_S          equal  32.065                                                  # mass for element 1 (S)  (g/mol)\nvariable mass_Cu         equal  63.546                                                  # mass for element 2 (Cu) (g/mol)\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary p p p\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_S}\nmass 2 ${mass_Cu}\ntimestep ${dt}\nthermo 10\n\n###############################################################################\n# NN\n###############################################################################\npair_style hdnnp/external \"S Cu\" dir ${hdnnpDir} cflength 1.0 cfenergy 1.0\npair_coeff * * ${hdnnpCutoff}\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\ndump 1 all atom 10 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/correct-input-data/input.data-h2o-192",
    "content": "begin\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\nlattice   2.3488727120000000E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   0.0000000000000000E+00   2.3488727120000000E+01   0.0000000000000000E+00\nlattice   0.0000000000000000E+00   0.0000000000000000E+00   2.3488727120000000E+01\natom   2.0304918120000000E+01   1.2036463120000002E+01   1.9531799999999999E-01  O  -1.9879263175625675E-01   0.0000000000000000E+00  -6.8284873995153164E-02   1.5787274386548209E+00   6.4505071874474607E-01\natom   1.9700255120000001E+01   1.0286042000000000E+01   5.7179300000000000E-01  H   1.0201390041329145E-01   0.0000000000000000E+00  -7.0328871677551885E-01  -2.0069697316267390E+00  -1.2542986145350115E+00\natom   2.1009248119999999E+01   1.2811504120000000E+01   1.7683070000000001E+00  H   1.1414068043640804E-01   0.0000000000000000E+00   9.8942502341395033E-01  -1.7146032835883098E+00  -3.9278105791948277E+00\natom   1.8042954119999997E+01   2.2429598120000001E+01   2.3451588120000000E+01  O  -2.0911191113438887E-01   0.0000000000000000E+00  -1.2143984940007395E+00   7.9058512573662709E-01  -9.7143080942182902E-01\natom   1.7360224120000002E+01   2.0772076120000001E+01   2.2853624119999999E+01  H   1.2957589415459830E-01   0.0000000000000000E+00  -1.5848519803826953E+00  -2.2342148090456218E+00   4.9496382307307757E-01\natom   1.9389503120000001E+01   2.3021133119999998E+01   2.2265014120000000E+01  H   1.5514246013031521E-01   0.0000000000000000E+00   1.6398874061501056E+00   1.7091336313622123E+00  -1.1145031748157310E+00\natom   1.9462741120000000E+01   2.0739459999999998E+00   1.0249672000000000E+01  O  -2.4484970763208769E-01   0.0000000000000000E+00   9.4305945523707968E-01   1.1936042346493123E+00   1.0266301185118702E+00\natom   1.8372006119999998E+01   7.7177700000000005E-01   9.4215920000000004E+00  H   1.2705239467014318E-01   0.0000000000000000E+00  -9.8535753349065469E-01  -2.7121561171308075E+00   7.9200464867444098E-01\natom   1.9313683120000000E+01   3.7084700000000002E+00   9.3130959999999998E+00  H   1.0665589300684451E-01   0.0000000000000000E+00   4.5637964573337714E-01  -1.8173488616107927E+00   4.8649392828231802E-01\natom   2.1432401120000002E+01   1.7878873120000002E+01   1.8130218119999999E+01  O  -3.0900693721588052E-01   0.0000000000000000E+00  -1.3170903976451349E+00   2.9619635578321875E+00  -3.0412342709621085E+00\natom   2.2548154120000000E+01   1.6763768120000002E+01   1.9170746120000000E+01  H   9.3483567904267428E-02   0.0000000000000000E+00   1.4737045447503363E+00  -2.8526161025625858E+00   3.6218955369736796E+00\natom   1.9686842120000001E+01   1.7875235119999999E+01   1.8854149119999999E+01  H   1.4492626406377870E-01   0.0000000000000000E+00   1.2140010502313068E+00  -1.0313956758266110E+00   6.3141591698450350E-01\natom   1.4613290120000000E+01   3.4009399999999999E+00   1.5759029119999999E+01  O  -2.7139230220147459E-01   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0.0000000000000000E+00   1.0802286819668062E-01   2.6593741230106605E+00  -6.7844334932672030E+00\natom   2.0523758120000000E+01   4.7030409999999998E+00   4.7202679999999999E+00  O  -2.0517705839608336E-01   0.0000000000000000E+00  -1.5589473558354145E+00   1.3148311171978464E+00  -2.9609279115179761E+00\natom   1.9085319120000001E+01   5.5130340000000002E+00   5.6399759999999999E+00  H   1.0550886501042894E-01   0.0000000000000000E+00   6.9666450544438896E-01  -4.6634307130037501E-02  -6.7827603196095612E-02\natom   2.0045470120000001E+01   4.4380839999999999E+00   2.9113709999999999E+00  H   1.0945746395538625E-01   0.0000000000000000E+00   1.2420242495646279E+00  -9.3185034931585242E-01   7.3825244395909440E-01\natom   7.9902610000000003E+00   7.5561780000000001E+00   6.3158400000000003E-01  O  -2.1073468347786953E-01   0.0000000000000000E+00  -1.8383572080730319E+00   5.2109189523326261E-03   3.0672464485758080E+00\natom   9.0505160000000000E+00   8.3789909999999992E+00   1.9619610000000001E+00  H   1.3529723421269738E-01   0.0000000000000000E+00   3.3262746311299052E-02   9.8260470416338475E-01   1.6386998456814159E+00\natom   9.1063620000000007E+00   6.8865740000000004E+00   2.2750269119999999E+01  H   1.3565850805070764E-01   0.0000000000000000E+00   1.0156530137755859E+00  -2.5231334615549379E+00  -3.3976868639675009E+00\natom   2.2708452120000000E+01   1.4205266120000001E+01   4.5547690000000003E+00  O  -2.2070130524189713E-01   0.0000000000000000E+00   1.7473880169140554E+00  -1.0362358359886974E+00  -2.9121509328320703E+00\natom   2.1735787119999998E+01   1.3652712120000000E+01   6.0778169999999996E+00  H   1.2043467445457638E-01   0.0000000000000000E+00  -1.6165928575232158E+00  -4.6030882388702743E-01   2.2412086388775703E+00\natom   2.2624765119999999E+01   1.2858916120000002E+01   3.2313639999999997E+00  H   1.3640932968234940E-01   0.0000000000000000E+00   5.5276141591112868E-02   4.2951999735715676E+00   2.2700694752167325E+00\natom   1.1141560999999999E+01   1.3267886120000002E+01   8.1445310000000006E+00  O  -2.3585776472999037E-01   0.0000000000000000E+00   2.7379762077417800E+00   1.1601447212459137E+00   3.4286755225109591E+00\natom   1.0275976999999999E+01   1.1713756999999999E+01   7.5067670000000000E+00  H   8.0630712341651853E-02   0.0000000000000000E+00   1.1432678968092641E-01   8.1506401083501701E-01   9.0920001945895168E-02\natom   1.1960026120000000E+01   1.2895835119999999E+01   9.8067200000000003E+00  H   1.1747429965144887E-01   0.0000000000000000E+00  -1.7349390131081026E+00   6.8288269181711891E-01  -3.3523925285403715E+00\natom   8.0348579999999998E+00   2.2918185120000000E+01   1.7478927120000002E+01  O  -2.5894551747423700E-01   0.0000000000000000E+00  -6.9633077944477692E-02  -1.9712207883323756E+00   9.8287825424521325E-01\natom   7.7329729999999994E+00   2.1370580120000000E+01   1.8520488120000003E+01  H   1.2920903841339917E-01   0.0000000000000000E+00   7.0444865246529764E-01   1.5331453421641299E+00  -5.5987562915846467E-01\natom   9.2023119999999992E+00   5.9294100000000005E-01   1.8403277119999998E+01  H   1.2650866550346915E-01   0.0000000000000000E+00   1.2610657253135440E+00   1.2121320776759203E+00   1.2541260239455236E+00\natom   1.5187141119999998E+01   2.2712399120000001E+01   1.8823129120000001E+01  O  -2.2311876148056808E-01   0.0000000000000000E+00  -2.4044052128774176E+00  -2.1380073131587358E+00   3.6660927404486054E-01\natom   1.3608780120000000E+01   2.1792696119999999E+01   1.8339410120000000E+01  H   1.1349258021931473E-01   0.0000000000000000E+00   1.6316326911508778E+00  -2.4131855289480049E+00  -1.1034354330076201E+00\natom   1.6110679120000000E+01   2.1726610120000000E+01   2.0144632120000001E+01  H   1.0766455078797760E-01   0.0000000000000000E+00  -6.7369632370877341E-01   9.9080912321162984E-01  -9.3712852971545824E-01\natom   6.5985909999999999E+00   7.1627219999999996E+00   6.7163719999999998E+00  O  -2.1024610067255159E-01   0.0000000000000000E+00  -1.9907653094061089E+00  -5.5205217159790134E+00   1.8707812417637832E+00\natom   5.8164559999999996E+00   5.9575180000000003E+00   7.9438969999999998E+00  H   1.2512962864008512E-01   0.0000000000000000E+00   5.7389738420156231E+00   4.4879271464980857E+00   4.3104750725949742E-01\natom   5.2527549999999996E+00   8.2507500000000000E+00   5.9574350000000003E+00  H   1.0724365658640164E-01   0.0000000000000000E+00  -1.9752148737998791E+00   2.6913978163177279E+00  -1.3351631705518119E+00\natom   6.2141280000000005E+00   1.6936289120000001E+01   1.1911167120000002E+01  O  -2.4271289094993506E-01   0.0000000000000000E+00   8.0314593776971244E-01  -2.2417893969675401E-01   4.5874131486567427E+00\natom   6.3734469999999996E+00   1.5483409119999997E+01   1.3109008120000002E+01  H   1.0147909824707625E-01   0.0000000000000000E+00  -8.2915142531454733E-01   1.8591871680460814E+00  -6.7773788200862439E-01\natom   6.2152149999999997E+00   1.6291240120000001E+01   1.0134869999999999E+01  H   1.1506523691615815E-01   0.0000000000000000E+00  -2.2418599813751486E-01  -1.6334337242613681E+00  -2.7790279801440483E+00\natom   1.8920193120000000E+01   1.8192229120000000E+01   6.5713679999999997E+00  O  -2.3576177873984405E-01   0.0000000000000000E+00  -1.3234987489714813E+00  -4.0523221847365143E+00  -1.6407039521625968E-01\natom   1.8550553120000000E+01   1.6994950119999999E+01   5.1568189999999996E+00  H   1.2499399695919702E-01   0.0000000000000000E+00  -8.4263812076402600E-01   2.2598414693979727E+00   3.4297989593930627E+00\natom   2.0155638119999999E+01   1.9496784120000001E+01   5.9858079999999996E+00  H   1.2349782973025965E-01   0.0000000000000000E+00   2.1397726167904514E+00   1.5967344199549043E+00  -5.1206794934515620E-01\nenergy  -4.8942642280032924E+03\ncharge  -1.3877787807814457E-17\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/correct-input-data/input.data-h2o-36",
    "content": "begin\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\nlattice   1.3443888628000000E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   0.0000000000000000E+00   1.3443888628000000E+01   0.0000000000000000E+00\nlattice   0.0000000000000000E+00   0.0000000000000000E+00   1.3443888628000000E+01\natom   1.0281570000000000E+00   6.8756146279999992E+00   8.4965726279999991E+00  O  -2.8256347534442394E-01   0.0000000000000000E+00  -2.9283692352115263E+00  -2.1942965040430695E-01  -7.8128583031086121E-02\natom   2.0441220000000002E+00   6.7232386279999998E+00   1.0082655627999999E+01  H   1.2277837277223855E-01   0.0000000000000000E+00   1.9482823532380507E+00   3.1792184330776235E-01   2.2469585801699852E+00\natom   2.0479959999999999E+00   7.7664106280000009E+00   7.1784396279999996E+00  H   1.2747526484297358E-01   0.0000000000000000E+00   8.9380603941331793E-01   2.7100055065674783E-01  -2.0117787682273802E-01\natom   1.1192644628000000E+01   5.0014000000000003E+00   2.3129659999999999E+00  O  -2.0320633594884582E-01   0.0000000000000000E+00   2.8271820248615240E+00   3.8199554621973880E-01   3.5845413797895835E+00\natom   1.0184262628000001E+01   4.6480459999999999E+00   7.5432200000000005E-01  H   1.5077528010356028E-01   0.0000000000000000E+00  -1.1936480532254552E+00  -2.3140105928612867E-01  -2.3175789249624752E+00\natom   1.2084808628000001E+01   6.6565360000000000E+00   2.1242049999999999E+00  H   1.0545961981723478E-01   0.0000000000000000E+00  -3.4603179700863103E+00  -1.3868476023525984E+00  -1.0545047365673061E+00\natom   7.9033536279999996E+00   3.0212699999999999E+00   6.9125696280000009E+00  O  -2.3518637803977813E-01   0.0000000000000000E+00   4.2372154470977669E-01   1.8073177424203288E-01   3.0951853714291844E-01\natom   8.8537476279999989E+00   1.9672839999999998E+00   5.6648090000000000E+00  H   1.1004800576876206E-01   0.0000000000000000E+00   7.7840436378832478E-02   5.2958376699306908E-01  -2.2524862715071485E+00\natom   7.7022636279999999E+00   2.0587849999999999E+00   8.5263396280000006E+00  H   1.2457842239861067E-01   0.0000000000000000E+00  -2.3265786214644388E-01   2.0210037813235607E-01   2.1477750389810897E+00\natom   7.8743726279999988E+00   1.0387881627999999E+01   1.1051255628000000E+01  O  -2.2058240732065956E-01   0.0000000000000000E+00  -3.4565727104575689E-01   2.5528939648646114E+00  -3.8700539207258222E+00\natom   9.2086816279999990E+00   9.1761326279999995E+00   1.1619012628000000E+01  H   1.2797577200732241E-01   0.0000000000000000E+00   1.5078420052350747E-01  -2.1634546570493454E+00   1.1018383816958270E+00\natom   8.1086836279999996E+00   1.0767815628000001E+01   9.2150046279999991E+00  H   1.1917909653994410E-01   0.0000000000000000E+00  -1.8331532626603048E-01  -1.1747870971878707E+00   6.7991269031499835E+00\natom   3.8907250000000002E+00   8.2707826279999992E+00   1.8582870000000000E+00  O  -2.6183165626861749E-01   0.0000000000000000E+00   7.0244269367983858E-01  -1.1111776866062637E+00   1.6022264684182443E+00\natom   3.6563539999999999E+00   7.5442296280000001E+00   1.2963000000000000E-01  H   1.2478853272527493E-01   0.0000000000000000E+00  -9.2733544280998526E-01   1.2708147351939285E+00  -2.1037967614413642E+00\natom   4.0430140000000003E+00   6.8683186279999999E+00   3.1156519999999999E+00  H   9.9154652510639180E-02   0.0000000000000000E+00   1.8655372292621097E-01   1.3721069236350780E+00  -8.0692036225339978E-02\natom   4.7885530000000003E+00   1.2039224627999999E+01   6.5503749999999998E+00  O  -2.7263628991795935E-01   0.0000000000000000E+00  -1.1292771081345108E+00  -9.0760280713822394E-01  -1.5762793800709740E-01\natom   4.6924869999999999E+00   1.1124599999999998E-01   5.4261629999999998E+00  H   1.1434733344402727E-01   0.0000000000000000E+00  -9.8293571178456843E-02   1.0082309420963453E+00  -5.8307946025373902E-01\natom   5.5979869999999998E+00   1.2520381627999999E+01   8.1887696280000011E+00  H   1.1263403257973484E-01   0.0000000000000000E+00  -5.8627648478079153E-01   3.6509413794346102E-01  -1.1572643025824929E-01\natom   4.8991110000000004E+00   3.3909980000000002E+00   1.3105727628000000E+01  O  -2.7372231339107428E-01   0.0000000000000000E+00   1.0579372843395085E+00   1.1643437983388070E+00   1.2704653330434790E+00\natom   4.0105050000000002E+00   2.4129309999999999E+00   1.1754866627999998E+01  H   1.3658196132808181E-01   0.0000000000000000E+00  -2.7108633263781412E+00  -1.3756498865725824E+00  -1.9441844331785387E+00\natom   3.6245479999999999E+00   4.2738459999999998E+00   7.4217699999999998E-01  H   9.0172983387061936E-02   0.0000000000000000E+00  -4.0507125991796944E-01  -1.6796036702909269E+00  -1.4731090864111782E-01\natom   1.1298731628000001E+01   1.2691991628000000E+01   4.4432619999999998E+00  O  -2.5637106920821656E-01   0.0000000000000000E+00  -2.8283675022934567E+00   1.2289852492197650E+00   4.1542682352061577E-01\natom   1.1360284628000000E+01   1.3169730628000000E+01   6.2705669999999998E+00  H   1.1847178479117913E-01   0.0000000000000000E+00   1.1556735718984914E+00  -7.1030210772562219E-01   1.8949900190596836E+00\natom   1.2995212628000001E+01   1.2061610628000000E+01   3.8995389999999999E+00  H   1.3767024849619425E-01   0.0000000000000000E+00   2.6903838305192367E+00  -9.4978647053313636E-01  -1.3294639818356677E+00\natom   1.2764696627999999E+01   1.5378200000000000E-01   1.0125363628000001E+01  O  -2.2955663167309948E-01   0.0000000000000000E+00  -1.6237528514361890E+00  -1.7798214425490955E+00  -1.0320891233855798E+00\natom   1.1249884628000000E+01   1.2710340000000000E+00   9.9575596280000003E+00  H   1.3433991100513273E-01   0.0000000000000000E+00   5.0306812661490385E-01   6.4606072642904910E-02   1.2035900324044681E-01\natom   8.4522900000000001E-01   1.2098420000000001E+00   1.0488610628000000E+01  H   1.3761295680984548E-01   0.0000000000000000E+00   2.3015420911979811E+00   1.6439986297320848E+00   8.3471087553758916E-01\natom   8.8003156279999999E+00   8.1706076280000008E+00   6.1612819999999999E+00  O  -2.3412971681479525E-01   0.0000000000000000E+00   4.7823813809165792E+00   4.5453029913715861E+00  -3.2129178691353069E+00\natom   7.4882556279999992E+00   6.9694036280000002E+00   6.7989826280000001E+00  H   1.1415705913922836E-01   0.0000000000000000E+00  -5.1160186352989925E+00  -5.4134409660054734E+00   1.5484060579498757E+00\natom   8.7161336279999979E+00   9.7785886279999996E+00   7.1504036279999994E+00  H   1.1034962117814637E-01   0.0000000000000000E+00   1.2454296150285611E+00  -3.2682486247550602E-01  -2.3874749634340637E+00\natom   3.1354829999999998E+00   3.7303289999999998E+00   4.8504040000000002E+00  O  -2.2006091505768430E-01   0.0000000000000000E+00  -1.2832754207323978E+00  -1.4767181813664836E+00  -1.6544059920266059E+00\natom   2.5813579999999998E+00   2.1819250000000001E+00   3.9195639999999994E+00  H   1.3641844939732595E-01   0.0000000000000000E+00  -1.8176714669371274E+00  -3.7272692203761654E-01  -2.5341845334408836E-01\natom   4.8735999999999997E+00   4.2146619999999997E+00   4.2887670000000000E+00  H   1.1534057032122745E-01   0.0000000000000000E+00   2.8905795806354817E+00   1.2490296651432349E+00   4.4489626141762684E-01\natom   1.2696753628000000E+01   9.5005796279999988E+00   1.3316218628000000E+01  O  -2.0590918634609703E-01   0.0000000000000000E+00   3.6313703894020638E-01  -2.9210646513595001E-01   7.7685508623495614E-01\natom   1.2096099628000001E+01   8.3233416279999997E+00   1.2230289999999999E+00  H   1.0721155781927215E-01   0.0000000000000000E+00   2.1821057837216054E+00  -8.1494640847712330E-01   1.1342821157055141E-02\natom   1.1423969628000000E+01   1.0874955628000000E+01   1.3066854628000000E+01  H   1.1823488614823414E-01   0.0000000000000000E+00   4.8731746833591910E-01   4.0378869734607514E+00  -3.3331890572564116E-01\nenergy  -9.1689613647168449E+02\ncharge   1.2212453270876722E-15\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/correct-input-data/input.data-h2o-768",
    "content": "begin\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\nlattice   3.7285997399999999E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   0.0000000000000000E+00   3.7285997399999999E+01   0.0000000000000000E+00\nlattice   0.0000000000000000E+00   0.0000000000000000E+00   3.7285997399999999E+01\natom   1.5393882899999998E+01   1.5450053199999997E+01   1.7958337699999998E+01  O  -2.4222446839019240E-01   0.0000000000000000E+00   2.5194620416878477E+00  -2.7841022844887866E+00   3.1373061741649120E+00\natom   1.6432138200000001E+01   1.3949797700000000E+01   1.8450596200000000E+01  H   1.1386982862045239E-01   0.0000000000000000E+00  -1.9441343743148316E+00   5.6476874344034984E+00  -3.8727363556617772E-01\natom   1.4070126000000000E+01   1.4920389399999999E+01   1.6718101000000001E+01  H   1.2418670170342477E-01   0.0000000000000000E+00  -2.9206537098779428E+00   8.7253250356032741E-01  -1.8899052829142506E+00\natom   3.6059676629999998E+01   3.2862872289999999E+01   2.4082668000000002E+01  O  -2.5015097410068982E-01   0.0000000000000000E+00   1.1035581541852670E-01   4.0384347155401450E+00  -1.8911558759887759E+00\natom   3.4902844879999996E+01   3.1394445479999998E+01   2.3806029100000000E+01  H   1.2159813276226661E-01   0.0000000000000000E+00  -1.5974023319356156E+00  -4.0680132143421899E+00   5.4469839242707652E-01\natom   9.0164502999999979E-02   3.2396508670000003E+01   2.5355632900000000E+01  H   1.4148988835321463E-01   0.0000000000000000E+00   2.1023623505852425E+00  -1.7905690317635359E+00   2.5883923469775314E+00\natom   2.7548937800000002E+00   1.8038048199999999E+01   2.3447117099999999E+00  O  -1.8820599335966476E-01   0.0000000000000000E+00   8.5978555199458329E-01  -2.9311392719122429E+00  -2.7157286309182860E+00\natom   3.3076178899999999E+00   1.7995947000000001E+01   4.1513068999999998E+00  H   1.1764632210040805E-01   0.0000000000000000E+00   4.2455225941780850E-01   3.6128032553800399E-01   3.0332506951007288E+00\natom   3.2489022099999998E+00   1.6422952200000001E+01   1.4970769500000001E+00  H   9.4849123473162933E-02   0.0000000000000000E+00  -1.6052306939944729E+00   3.5583316951324466E+00   1.5468061586508721E+00\natom   5.7654864000000003E+00   1.3165752199999998E+01   1.7214741799999999E+01  O  -2.5025289652527360E-01   0.0000000000000000E+00  -2.7869004299296024E-01  -5.2942145434031207E-01  -1.4529540175624620E+00\natom   5.8948910699999999E+00   1.4685190299999999E+01   1.8330819699999999E+01  H   1.4720762296202070E-01   0.0000000000000000E+00   2.9646176474973374E-01   9.1380527487176189E-01   5.2160211007622281E-01\natom   6.5253755099999990E+00   1.1673921099999999E+01   1.8091142000000001E+01  H   1.1844706167061329E-01   0.0000000000000000E+00   3.6044768133295257E-01  -4.5014250215810014E-01   2.7952837632748544E+00\natom   1.0226527000000001E+01   1.5583800399999999E+01   2.3403521199999999E+00  O  -2.7528041849725271E-01   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5.4891139500000001E+00   1.7054487299999998E+01   3.6114646879999995E+01  H   9.9968044666886705E-02   0.0000000000000000E+00  -7.4560890964251147E-01  -6.0764570622940184E-01   1.6028439848141727E+00\natom   1.5736061299999998E+01   1.6917107999999999E+01   2.5814042599999997E+01  O  -2.6881762867803888E-01   0.0000000000000000E+00   7.2729870519897122E-01   4.9528894260777019E+00   1.1249143376875610E+00\natom   1.4389247800000000E+01   1.8126464700000000E+01   2.5271258499999998E+01  H   9.5776167632687453E-02   0.0000000000000000E+00   3.6189054074796707E+00  -2.2509280080199074E+00   2.0886086864426223E-01\natom   1.5272307399999999E+01   1.5169634799999999E+01   2.5264194699999997E+01  H   1.0452042010693514E-01   0.0000000000000000E+00  -2.1144459772374433E+00  -4.6845596271218488E+00  -1.3430308753641464E+00\natom   1.3330349200000001E+01   2.4112708999999999E+01   1.4581799599999998E+01  O  -2.5359811161022361E-01   0.0000000000000000E+00   1.6113206520608905E-01   3.4328750381500589E-01  -6.1054749989318169E-01\natom   1.1859452599999999E+01   2.2936551000000001E+01   1.4737288099999999E+01  H   1.2852879827876618E-01   0.0000000000000000E+00  -2.4821970108548541E+00  -1.4428368225771537E-01   1.0212747010535397E+00\natom   1.4559504600000000E+01   2.3421258200000000E+01   1.3323967599999998E+01  H   1.1462655666206358E-01   0.0000000000000000E+00   1.6156811808978746E+00  -1.9593571952120883E-01  -1.5429213968341886E+00\natom   1.6811751999999998E+01   3.2846505370000003E+01   3.3477515160000003E+01  O  -2.3134831152147839E-01   0.0000000000000000E+00  -2.1302443852143149E+00  -1.1532204159955672E+00  -8.1253058455947103E-01\natom   1.5276109500000000E+01   3.1805283280000001E+01   3.3118737429999996E+01  H   1.1386972524432752E-01   0.0000000000000000E+00   1.6445506708938509E+00   1.8934108038664230E+00   5.9005934261031145E-01\natom   1.7406322200000002E+01   3.2505927589999999E+01   3.5238639759999998E+01  H   1.4600820449540156E-01   0.0000000000000000E+00   1.0755793768262040E-01  -5.3609412943368184E-01   1.9457307407046585E+00\natom   3.4173869789999998E+01   1.4727548499999997E+01   1.0948336199999998E+01  O  -2.1754576427972272E-01   0.0000000000000000E+00   3.1024111646012984E+00  -2.7304447665858717E-01  -1.7441805603529561E+00\natom   3.4386435640000002E+01   1.5189639400000001E+01   1.2768322000000000E+01  H   1.0404455414268970E-01   0.0000000000000000E+00   4.8783654931351672E-02   1.2972582428269730E-01   1.8358683440582046E+00\natom   3.5864003050000001E+01   1.4347016199999999E+01   1.0193543699999998E+01  H   1.3269534874087749E-01   0.0000000000000000E+00  -5.0989712166453689E+00   3.6824917988155565E+00   1.4431120796009471E+00\natom   1.9449666099999998E+01   1.2475650699999999E+01   9.1481169700000002E+00  O  -2.7632964244840885E-01   0.0000000000000000E+00  -7.2239790834372031E-01   2.4052973580561221E+00  -6.8195575504399941E-01\natom   1.8820321199999999E+01   1.1317042600000001E+01   1.0501860100000000E+01  H   1.0574197876578205E-01   0.0000000000000000E+00  -2.9511256107373496E-01  -1.5718613309177005E+00   2.1816296396226118E+00\natom   2.0106631300000000E+01   1.1454363299999999E+01   7.7002088000000004E+00  H   1.2683558571572007E-01   0.0000000000000000E+00   1.4520664029738251E-01  -6.9940652090589550E-01  -1.5061827660254516E+00\natom   8.2073376000000007E+00   1.4634995399999999E+01   1.2639499399999998E+01  O  -2.1294272030520670E-01   0.0000000000000000E+00  -4.4583096877615352E-01  -1.1738129662848132E-01  -1.1312467033452656E-01\natom   6.8198307500000004E+00   1.3380232299999998E+01   1.2372182499999999E+01  H   1.3514344049128185E-01   0.0000000000000000E+00  -4.7562913268923335E-01  -1.4837820669554187E+00  -8.4616373853582139E-01\natom   7.6068449899999990E+00   1.6000468000000001E+01   1.3799653299999999E+01  H   1.4287184779336368E-01   0.0000000000000000E+00  -4.4039195097694056E-03   1.7433165412650540E+00   1.6252095105174222E+00\natom   3.1514131279999997E+01   5.2310812999999996E+00   2.4170037600000001E+01  O  -2.2105358092623129E-01   0.0000000000000000E+00   6.5961556379040553E-01   8.7041887511788063E-01   6.9922323016970234E-01\natom   3.1328329629999999E+01   6.3917302999999990E+00   2.2690363099999999E+01  H   1.4521970263915279E-01   0.0000000000000000E+00   2.5781981423503861E+00   2.2091762461910043E+00  -4.5206575609761037E+00\natom   3.0095814340000000E+01   5.5256102299999990E+00   2.5383583800000000E+01  H   1.5535657750356807E-01   0.0000000000000000E+00  -1.9979064773832835E+00  -1.1014409127190916E+00   4.6683092763028462E+00\natom   2.1045373500000000E+01   6.7201269099999994E+00   2.2663952300000002E+01  O  -2.6823101055687082E-01   0.0000000000000000E+00  -3.0078693983593472E+00   5.5475720387444327E-01  -1.1654038499249422E+00\natom   2.0707046399999999E+01   8.4575751299999986E+00   2.3325672099999998E+01  H   1.4263435551532594E-01   0.0000000000000000E+00  -9.4052651326742132E-01   1.3777930066097186E+00  -1.0252891977490097E-01\natom   2.2588421900000000E+01   6.0176514599999988E+00   2.3498576300000000E+01  H   1.1615735243889569E-01   0.0000000000000000E+00   5.5009693954329180E+00  -2.3221153519020858E+00   2.4197767702972111E+00\natom   1.6224377900000000E+01   2.7617608590000003E+01   2.4078059000000000E+01  O  -2.5716176545236769E-01   0.0000000000000000E+00  -1.7228075201222854E+00  -6.3960400055189592E-01   8.8359823051672670E-01\natom   1.7181870000000000E+01   2.9147517640000000E+01   2.4638103900000001E+01  H   8.8973500045188642E-02   0.0000000000000000E+00  -3.5922723205630691E-01  -2.6563911376160049E-01   4.8381182729724104E-01\natom   1.5096253000000001E+01   2.7033509400000000E+01   2.5477068599999999E+01  H   1.1324483723146468E-01   0.0000000000000000E+00   1.4388698386598961E+00   3.0830162167108210E-01  -1.1079678457450335E+00\natom   2.6142269200000001E+01   1.3988620199999998E+01   2.7082302100000003E+01  O  -2.9234001731100151E-01   0.0000000000000000E+00  -1.4387067545343117E+00  -8.7536511059844924E-01   1.0417663200481471E-01\natom   2.7833084620000001E+01   1.3317820400000000E+01   2.7594391419999997E+01  H   9.7549446922953378E-02   0.0000000000000000E+00   9.0638673648725820E-01   2.0002066308699242E+00   5.6320741970346855E-01\natom   2.6158963000000000E+01   1.5875989899999999E+01   2.7175136800000001E+01  H   1.1038465598549677E-01   0.0000000000000000E+00   2.1287941773411525E+00  -7.4853093546181815E-01   8.5904546234955759E-01\natom   1.7088755599999999E+01   4.9249229899999998E+00   9.9384250000000005E+00  O  -2.2254772137821102E-01   0.0000000000000000E+00   2.7234579886859032E+00   1.1123431005783422E+00  -3.6427670490390279E-01\natom   1.6003119300000002E+01   6.4596451699999990E+00   1.0130999400000000E+01  H   1.3951249307736638E-01   0.0000000000000000E+00  -2.7843834066702540E+00   1.7093274356539359E+00   1.9601074764968929E+00\natom   1.8390567200000000E+01   5.2375743999999989E+00   8.6047829100000008E+00  H   1.1787089547126460E-01   0.0000000000000000E+00  -1.6439806994437192E+00  -1.9217812745301261E+00   1.0022560311492315E+00\natom   2.2608893299999998E+01   1.9812954599999994E+01   3.0760706920000001E+01  O  -2.0785292933782398E-01   0.0000000000000000E+00  -6.3100232260122517E+00  -1.8373948048743525E+00  -2.6357075665943115E+00\natom   2.3050427800000001E+01   1.8041523399999999E+01   3.1249010269999999E+01  H   1.0799817903206925E-01   0.0000000000000000E+00  -1.8188106035223401E+00   4.0792855099130138E-02  -2.0960679239592999E+00\natom   2.3787558900000001E+01   2.1015260800000004E+01   3.1618772979999999E+01  H   1.2190939804854146E-01   0.0000000000000000E+00   4.5394979735280101E+00   5.9758394240880888E+00   3.5246506204954526E+00\natom   2.3350691999999999E+01   4.4624937799999997E-01   1.5904014499999999E+01  O  -2.1830698191927736E-01   0.0000000000000000E+00  -1.0620546978537548E+00  -8.0687512588135490E-01  -6.3027063631504465E-01\natom   2.2344174800000001E+01   1.2297978599999999E+00   1.7298303600000001E+01  H   1.0563199523805547E-01   0.0000000000000000E+00   1.4245889308744419E-01  -1.2184712523394872E+00  -1.0213222350652240E+00\natom   2.2198541100000003E+01   3.7266295115299997E+01   1.4480461099999998E+01  H   1.1428316557799945E-01   0.0000000000000000E+00   5.7907507818492965E-01   2.3525954958812707E+00   1.8882862816322574E+00\natom   1.5676134299999998E+01   3.2015545549999999E+01   2.8432874240000000E+01  O  -1.6104264320473546E-01   0.0000000000000000E+00   5.6123266577871356E-01  -9.8555083130296040E-01   3.3043291977293094E+00\natom   1.7541683299999999E+01   3.1761966980000000E+01   2.8595634459999999E+01  H   1.1757409012443597E-01   0.0000000000000000E+00  -2.1874155348597917E+00  -1.9126326472659514E+00  -1.3328219513586022E+00\natom   1.5315366700000000E+01   3.3080508270000003E+01   2.6914071100000001E+01  H   1.1664185450491404E-01   0.0000000000000000E+00   5.8476765828212951E-01   1.0734082191020842E+00  -6.3427891792473901E-01\nenergy  -1.9539578322273323E+04\ncharge   3.0392355299113660E-15\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/correct-input-data/water.data-h2o-192",
    "content": "Generated by RuNNerUC, original comment lines: 12.4297\n\n192 atoms\n2 atom types\n\n0.0 1.2429699051257149E+01 xlo xhi\n0.0 1.2429699051257149E+01 ylo yhi\n0.0 1.2429699051257149E+01 zlo zhi\n\nMasses\n\n1 1.0079\n2 15.9994\n\nAtoms\n\n    1  2 0.0  1.0744899891877074E+01   6.3694219554267484E+00   1.0335783403206583E-01\n    2  1 0.0  1.0424926013384917E+01   5.4431389932461860E+00   3.0257982364501490E-01\n    3  1 0.0  1.1117615275220160E+01   6.7795559883681369E+00   9.3574776223256562E-01\n    4  2 0.0  9.5479200963717545E+00   1.1869232123475031E+01   1.2410045938906434E+01\n    5  1 0.0  9.1866349407347325E+00   1.0992109258298765E+01   1.2093617018534783E+01\n    6  1 0.0  1.0260483137453706E+01   1.2182258963572501E+01   1.1782138021772507E+01\n    7  2 0.0  1.0299239017858175E+01   1.0974849550961345E+00   5.4238928181688957E+00\n    8  1 0.0  9.7220469152206022E+00   4.0840679853247364E-01   4.9856917552598290E+00\n    9  1 0.0  1.0220360921496592E+01   1.9624378028286960E+00   4.9282781448340458E+00\n   10  2 0.0  1.1341538198576794E+01   9.4610921708051663E+00   9.5940982163042445E+00\n   11  1 0.0  1.1931969256619469E+01   8.8710040195936699E+00   1.0144721918828937E+01\n   12  1 0.0  1.0417828159485779E+01   9.4591670241202266E+00   9.9771860021133740E+00\n   13  2 0.0  7.7330200743678903E+00   1.7996999358636376E+00   8.3393190401880659E+00\n   14  1 0.0  7.1623130384218818E+00   1.4988457590959130E+00   9.1033741987314070E+00\n   15  1 0.0  8.6138138418403098E+00   1.3275510966675668E+00   8.3750691940476099E+00\n   16  2 0.0  8.3147260585949407E+00   4.7601040404048964E+00   8.8451632381426322E+00\n   17  1 0.0  7.8160289280199136E+00   5.1501579149882204E+00   8.0711103345969466E+00\n   18  1 0.0  9.2975510128374310E+00   4.8090449945435614E+00   8.6672311059866409E+00\n   19  2 0.0  9.9745268866400920E+00   6.9952581437889503E+00   8.6555823280934217E+00\n   20  1 0.0  9.4666818696597534E+00   7.3904011155875144E+00   7.8901052703905341E+00\n   21  1 0.0  1.0928144963207549E+01   7.2931219401507992E+00   8.6121083036969477E+00\n   22  2 0.0  3.3039168436269821E+00   6.2627112546009025E+00   4.8761822361776250E+00\n   23  1 0.0  2.7080050972346910E+00   6.5297060276754619E+00   5.6335480656268784E+00\n   24  1 0.0  4.0550817745456964E+00   5.7020860393321433E+00   5.2247438550107352E+00\n   25  2 0.0  6.1744708915632565E+00   4.4795078255373326E+00   3.3895731708537022E+00\n   26  1 0.0  7.0324180257322428E+00   4.9686617743322135E+00   3.5468017738998801E+00\n   27  1 0.0  5.5527659896687016E+00   5.0581588697390529E+00   2.8617019715905792E+00\n   28  2 0.0  9.9713422981986497E+00   5.7982687595926130E+00   2.8705810359739128E+00\n   29  1 0.0  1.0644035011674788E+01   5.7083890690639452E+00   2.1361391632018183E+00\n   30  1 0.0  9.1815252056083558E+00   6.3136122811202720E+00   2.5379391842847463E+00\n   31  2 0.0  7.9074199486563836E+00   2.7049898455000085E+00   1.3284999114026117E+00\n   32  1 0.0  7.8907852631036022E+00   1.9932121033956418E+00   6.2629286829323783E-01\n   33  1 0.0  8.4426340108662323E+00   2.3882211933604269E+00   2.1115731696463311E+00\n   34  2 0.0  1.3418801571224162E+00   9.9557712588351848E+00   2.9249407647287846E+00\n   35  1 0.0  2.1025131266576516E+00   9.5593302153438913E+00   3.4390147266317150E+00\n   36  1 0.0  1.4205730414609843E+00   1.0952662272459845E+01   2.9289090646161808E+00\n   37  2 0.0  4.3623792130055055E+00   1.4786999827639788E+00   1.5750160556810182E+00\n   38  1 0.0  4.3997968042493909E+00   6.4915014864211018E-01   2.1321920304027664E+00\n   39  1 0.0  3.4193700811163383E+00   1.8085768835381373E+00   1.5312620965411885E+00\n   40  2 0.0  4.1955280515978908E+00   5.7850779593134920E+00   1.0676260845324963E+01\n   41  1 0.0  4.4994747399727553E+00   5.1180040494384169E+00   9.9960929745999429E+00\n   42  1 0.0  3.9810149573648315E+00   5.3143822407322743E+00   1.1532082211145681E+01\n   43  2 0.0  6.3169381598764121E+00   9.7072003194557315E+00   1.5890090886083976E+00\n   44  1 0.0  6.5244841069808608E+00   1.0323524018315888E+01   8.2935774279514163E-01\n   45  1 0.0  7.0412399389770455E+00   9.7688992069168670E+00   2.2757260564672235E+00\n   46  2 0.0  4.4202547951344080E+00   9.8640050515578075E+00   3.9758528336948022E+00\n   47  1 0.0  3.5374242245860312E+00   9.8276209434023460E+00   3.5075728090709082E+00\n   48  1 0.0  4.6923809996008963E+00   1.0818162888878053E+01   4.1004698329057261E+00\n   49  2 0.0  2.2511907551898358E+00   8.6356021842277819E+00   9.5606790880486461E+00\n   50  1 0.0  2.6219730541898554E+00   8.7035252540166397E+00   8.6344459320269618E+00\n   51  1 0.0  2.7464598758074605E+00   7.9296893131264845E+00   1.0067032883655109E+01\n   52  2 0.0  2.1072280955864016E+00   1.0943558307762848E+01   8.0616269498413740E+00\n   53  1 0.0  1.3196271971457811E+00   1.0513609234244909E+01   8.5030200096728006E+00\n   54  1 0.0  2.9119489350801029E+00   1.0360777035447896E+01   8.1747211153347301E+00\n   55  2 0.0  6.3310513160301465E+00   6.6563529506586292E+00   7.5238415520736035E-01\n   56  1 0.0  6.4426262137575714E+00   7.2575358312259253E+00   1.2390799234651935E+01\n   57  1 0.0  6.2298191868450843E+00   7.2092870408761280E+00   1.5794368020817793E+00\n   58  2 0.0  1.7418328205700728E+00   1.2077780861389801E+01   1.2193210285904767E+01\n   59  1 0.0  1.0143390445470797E+00   1.2187109867542602E-01   1.1696946841312158E+01\n   60  1 0.0  1.4864450203892530E+00   1.1119936246457140E+01   1.2324773794333169E+01\n   61  2 0.0  9.2462351113865058E+00   7.0347051296278700E+00   5.4606388835350508E+00\n   62  1 0.0  1.0086851099294909E+01   7.4968091270500326E+00   5.1781058800839590E+00\n   63  1 0.0  8.4578340970064616E+00   7.5055320841568252E+00   5.0647270172523706E+00\n   64  2 0.0  7.5698398152564312E+00   9.1968898658604612E+00   5.1579960878022106E+00\n   65  1 0.0  6.7572173016837063E+00   9.7266438776318331E+00   4.9150878737321335E+00\n   66  1 0.0  7.8542662147599422E+00   9.4303612627693258E+00   6.0878308239057235E+00\n   67  2 0.0  5.0927130831071290E+00   6.8577980137249650E+00   7.5227128805888945E+00\n   68  1 0.0  6.0694149278687481E+00   7.0040890530463020E+00   7.3657012401982493E+00\n   69  1 0.0  4.5844971129035557E+00   7.0791512525565690E+00   6.6904150292226943E+00\n   70  2 0.0  2.1559684915630015E-01   2.6227879870911206E+00   6.3700379176975730E+00\n   71  1 0.0  1.1925900123213875E+01   2.8184359138370909E+00   5.7035222262763225E+00\n   72  1 0.0  5.2950794436936632E-01   1.6803720628528103E+00   6.2546629984350934E+00\n   73  2 0.0  5.1264661221813634E+00   3.3202049181081206E+00   9.0991661815685099E+00\n   74  1 0.0  5.6921131656586041E+00   2.6222810353252686E+00   9.5384218946543449E+00\n   75  1 0.0  5.7112381591551227E+00   3.9497342342092421E+00   8.5875650647614297E+00\n   76  2 0.0  7.0154383166394458E+00   1.2375728796927818E+01   2.4476260976222237E+00\n   77  1 0.0  6.4664878724483925E+00   3.0473410406128248E-01   1.6926521491559063E+00\n   78  1 0.0  6.7510582081526493E+00   4.0146293520104087E-01   3.2977349954759543E+00\n   79  2 0.0  6.1595851366849450E+00   1.2483078680320403E+00   1.1350344236505338E+01\n   80  1 0.0  6.1850269185206885E+00   2.0072310660062436E+00   1.0699660003135456E+01\n   81  1 0.0  5.4135759793097575E+00   1.3916921369464590E+00   1.2000660162538026E+01\n   82  2 0.0  1.7257331331752008E+00   5.4722728444664286E+00   1.1799978173006510E+01\n   83  1 0.0  8.5727184054952910E-01   5.4051128482123945E+00   1.2291165220636886E+01\n   84  1 0.0  2.4346041048726512E+00   5.8074880849210855E+00   1.2420569156876931E+01\n   85  2 0.0  8.2803321224198079E-01   2.8292221328802700E+00   3.7398932455510363E+00\n   86  1 0.0  8.6962124906695371E-01   2.6657010836464634E+00   4.7255561771633241E+00\n   87  1 0.0  1.7525301378422047E+00   2.8084180601008195E+00   3.3592719547112568E+00\n   88  2 0.0  7.0040832320970070E+00   1.9276639809190452E+00   5.0007172129212147E+00\n   89  1 0.0  7.4146099145271878E+00   2.8394638285757847E+00   4.9913222007594822E+00\n   90  1 0.0  6.3091301501633126E+00   1.8823981624942052E+00   5.7183460674212254E+00\n   91  2 0.0  1.9022438953488554E+00   5.8668458924113152E+00   2.4574042340829929E+00\n   92  1 0.0  1.8618951915464563E+00   6.3527639860767886E+00   3.3304979439928717E+00\n   93  1 0.0  2.8491678802273479E+00   5.8341221030078358E+00   2.1376150384366430E+00\n   94  2 0.0  6.1333691685930001E+00   1.0165149217435854E+01   8.0447139170768622E+00\n   95  1 0.0  6.5862703086814198E+00   1.0401943847214813E+01   8.9042749782308572E+00\n   96  1 0.0  6.6925169210953097E+00   9.5039290658424669E+00   7.5445303277228417E+00\n   97  2 0.0  2.3713848912911644E+00   6.0703092373513057E+00   7.6474119022671552E+00\n   98  1 0.0  2.6483879929122396E+00   5.3263231244446487E+00   8.2554862576222305E+00\n   99  1 0.0  2.9540777910122791E+00   6.8669263205735582E+00   7.8084479353293110E+00\n  100  2 0.0  9.1033731403769913E+00   9.2763500571515198E+00   9.1300690086958836E-01\n  101  1 0.0  8.2315431056412809E+00   9.3703028246548890E+00   4.3229174102047430E-01\n  102  1 0.0  8.9400918084186838E+00   9.2607901305094344E+00   1.8994641274720061E+00\n  103  2 0.0  1.0254602920311587E+01   3.6983179089790696E+00   1.2290831309818250E+01\n  104  1 0.0  1.0862791048766516E+01   2.9749157311330801E+00   1.1964034220398224E+01\n  105  1 0.0  1.0335027272476740E+01   3.7778389556491190E+00   8.5471485627750654E-01\n  106  2 0.0  1.1539618223773553E+01   1.0649182318382978E+01   5.7221688435762532E+00\n  107  1 0.0  1.2277761161942694E+01   1.0530492103908529E+01   5.0580477425252441E+00\n  108  1 0.0  1.0706704939313733E+01   1.0217910831020712E+01   5.3753820851008340E+00\n  109  2 0.0  1.0273467029444257E+01   3.8613949785348498E+00   5.4715272337794918E+00\n  110  1 0.0  9.4998321758933759E+00   4.0376078139400535E+00   6.0801619877984896E+00\n  111  1 0.0  9.9804552589081901E+00   3.2652329313228834E+00   4.7240411428150626E+00\n  112  2 0.0  3.5204371070123144E+00   2.0026108197978347E+00   5.7750077170335681E+00\n  113  1 0.0  4.5174159640536038E+00   1.9256621035388584E+00   5.7855949654463075E+00\n  114  1 0.0  3.2547001881626305E+00   2.8211511220944896E+00   5.2657191046281335E+00\n  115  2 0.0  4.2890627691064553E+00   1.0089963190458770E+01   1.1781280225517344E+01\n  116  1 0.0  4.8642889784140264E+00   1.0609319928435292E+01   1.1149311931661723E+01\n  117  1 0.0  3.6976728419617695E+00   1.0718260052841030E+01   1.2286750824362628E+01\n  118  2 0.0  8.2676689118176760E-01   2.4146689410697446E+00   7.8011780353361049E-01\n  119  1 0.0  8.5811905326052026E-02   2.7702881963341395E+00   1.3497860646191093E+00\n  120  1 0.0  4.4082789857262644E-01   1.9041420539961538E+00   1.1735033778223677E-02\n  121  2 0.0  7.6364875044712621E-01   8.5295360212420306E+00   5.3737702113233965E+00\n  122  1 0.0  3.4102825209128107E-02   7.8520849463060358E+00   5.2798428443260397E+00\n  123  1 0.0  5.2088500175500141E-01   9.1836572605818603E+00   6.0901427991301578E+00\n  124  2 0.0  1.6826078365592045E+00   2.1838302007737362E+00   1.0241303109527491E+01\n  125  1 0.0  1.1042039181139063E+00   1.6141677606375324E+00   9.6574068608339871E+00\n  126  1 0.0  1.1133650339494316E+00   2.8423171520846315E+00   1.0733600900118750E+01\n  127  2 0.0  1.0563847201721886E+01   4.7661086141910392E-01   9.0686681115044596E+00\n  128  1 0.0  9.8395491268617139E+00   1.2229346209949393E+01   8.9378539180034569E+00\n  129  1 0.0  1.0176080960211401E+01   1.3961647427136645E+00   9.0049662883087151E+00\n  130  2 0.0  6.9783149479235496E+00   4.9597170919750120E+00   6.0323137845956136E+00\n  131  1 0.0  7.0499501958308315E+00   4.4456251380469878E+00   5.1775761736981361E+00\n  132  1 0.0  6.3205450317303251E+00   5.7044011896198299E+00   5.9192481946715239E+00\n  133  2 0.0  9.7896799958991387E+00   1.2351027863184134E+01   2.7611080301191038E+00\n  134  1 0.0  9.8284030673166765E+00   2.7022010816106129E-01   1.8247448347929203E+00\n  135  1 0.0  9.2366649415687228E+00   5.3622426150109492E-01   3.3233159509175620E+00\n  136  2 0.0  1.4822560536058647E+00   1.2062943790814680E+01   4.6677769052863889E+00\n  137  1 0.0  1.8378620794400438E+00   2.2903001259696609E-01   3.9476482176528855E+00\n  138  1 0.0  2.0249712027478184E+00   1.2184147067852837E+01   5.4989020999583023E+00\n  139  2 0.0  1.1690770284933215E+01   4.3884692369218010E+00   9.2861689402573528E+00\n  140  1 0.0  1.1846754792361944E+01   3.5481919224269087E+00   8.7669349713932263E+00\n  141  1 0.0  1.2215482825438123E+01   4.3568752408587113E+00   1.0136860991394975E+01\n  142  2 0.0  8.7146961848904816E+00   1.1414830829501456E+01   7.0995330419235447E+00\n  143  1 0.0  9.2149088789909772E+00   1.1888057073494263E+01   7.8246841504440052E+00\n  144  1 0.0  9.3471322713985163E+00   1.1166119128984510E+01   6.3659352067991897E+00\n  145  2 0.0  4.0021513534312914E-01   8.3396122043616376E+00   1.1717893262760727E+01\n  146  1 0.0  6.4505008362976912E-01   8.2365972771607545E+00   2.5226988806766631E-01\n  147  1 0.0  8.6894813565759677E-01   7.6401701121672714E+00   1.1178382810794139E+01\n  148  2 0.0  6.8004082162735706E+00   8.4555131257694800E+00   1.0768745146074428E+01\n  149  1 0.0  7.4826959708962972E+00   8.0475201438141433E+00   1.0162094277410525E+01\n  150  1 0.0  7.0163998316274974E+00   9.4214160512349139E+00   1.0911497048224554E+01\n  151  2 0.0  4.0938990395063666E+00   7.7811879006047677E+00   2.0295967407283140E+00\n  152  1 0.0  3.4036667474507185E+00   8.0650359094192670E+00   2.6951857793560170E+00\n  153  1 0.0  4.1592598332511139E+00   6.7833538931943593E+00   2.0221348129096479E+00\n  154  2 0.0  5.4355109037840155E+00   1.2294726054073649E+01   5.9793860093672517E+00\n  155  1 0.0  5.1793880764604312E+00   1.1329402048474440E+01   5.9288760448050466E+00\n  156  1 0.0  5.8738379108687324E+00   1.3881111947757685E-01   5.1232841796259674E+00\n  157  2 0.0  1.2159078885126375E+01   5.8163772036713830E+00   4.9016017925706068E+00\n  158  1 0.0  3.9434073915030532E-01   6.5632939634606089E+00   4.9024897519266606E+00\n  159  1 0.0  1.1571608044388686E+01   5.8921797220965013E+00   5.7072889096472368E+00\n  160  2 0.0  1.1901221944090162E+01   1.1318394104180854E+01   1.4298791518516700E+00\n  161  1 0.0  1.1232291151390063E+01   1.1823696953851005E+01   8.8471814565150197E-01\n  162  1 0.0  1.1710919236328403E+01   1.0338701879013355E+01   1.3667250270668430E+00\n  163  2 0.0  6.7938390104058364E+00   4.2525500708892991E+00   1.1078510137858006E+01\n  164  1 0.0  6.3562422678690078E+00   4.8239349828395417E+00   1.1772793281445590E+01\n  165  1 0.0  6.7980750739607911E+00   4.7360561113366435E+00   1.0203179066710105E+01\n  166  2 0.0  1.0860705032210157E+01   2.4887421083771128E+00   2.4978582441499060E+00\n  167  1 0.0  1.0099515897428670E+01   2.9173719431139786E+00   2.9845467563298547E+00\n  168  1 0.0  1.0607605923456594E+01   2.3485329027143780E+00   1.5406311790196989E+00\n  169  2 0.0  4.2282640120771688E+00   3.9985571818303853E+00   3.3421985812525357E-01\n  170  1 0.0  4.7893267933961869E+00   4.4339710683816813E+00   1.0382250453894979E+00\n  171  1 0.0  4.8188792237884437E+00   3.6442180062336282E+00   1.2038923908138484E+01\n  172  2 0.0  1.2016795304805875E+01   7.5171030730003787E+00   2.4102799453015007E+00\n  173  1 0.0  1.1502083155189354E+01   7.2247040896718877E+00   3.2162422345266091E+00\n  174  1 0.0  1.1972510051748595E+01   6.8046453381829437E+00   1.7099641815357129E+00\n  175  2 0.0  5.8958601495824112E+00   7.0210629411898040E+00   4.3099001800500485E+00\n  176  1 0.0  5.4378128246414859E+00   6.1986532316424974E+00   3.9724100067755597E+00\n  177  1 0.0  6.3289732371319198E+00   6.8241820315477622E+00   5.1894927152589148E+00\n  178  2 0.0  4.2518637280497265E+00   1.2127781228300110E+01   9.2494498629288380E+00\n  179  1 0.0  4.0921130664272942E+00   1.1308823934363067E+01   9.8006202055100271E+00\n  180  1 0.0  4.8696537769549542E+00   3.1377086325278342E-01   9.7385948157111706E+00\n  181  2 0.0  8.0366889447082315E+00   1.2018883967248273E+01   9.9607709251021692E+00\n  182  1 0.0  7.2014562765430581E+00   1.1532198100954368E+01   9.7047978549286231E+00\n  183  1 0.0  8.5254042055971730E+00   1.1497226895945904E+01   1.0660080193817173E+01\n  184  2 0.0  3.4918239661653474E+00   3.7903492340379619E+00   3.5541509869731112E+00\n  185  1 0.0  3.0779359501060504E+00   3.1525827455075563E+00   4.2037292399769894E+00\n  186  1 0.0  2.7796382284331398E+00   4.3661088539718165E+00   3.1525388237992411E+00\n  187  2 0.0  3.2883749090099905E+00   8.9622982008009640E+00   6.3031181678962502E+00\n  188  1 0.0  3.3726828927091610E+00   8.1934672179498786E+00   6.9369883246396320E+00\n  189  1 0.0  3.2889501246357531E+00   8.6209529715617226E+00   5.3631422162655928E+00\n  190  2 0.0  1.0012134981679077E+01   9.6269130241876084E+00   3.4774181750152491E+00\n  191  1 0.0  9.8165299182870047E+00   8.9933402650354672E+00   2.7288710837475487E+00\n  192  1 0.0  1.0665904318175178E+01   1.0317253797571022E+01   3.1675531687392451E+00\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/correct-input-data/water.data-h2o-36",
    "content": "Generated by RuNNerUC, original comment lines: 7.1142\n\n36 atoms\n2 atom types\n\n0.0 7.1141994570823028E+00 xlo xhi\n0.0 7.1141994570823028E+00 ylo yhi\n0.0 7.1141994570823028E+00 zlo zhi\n\nMasses\n\n1 1.0079\n2 15.9994\n\nAtoms\n\n    1  2 0.0  5.4407725127692641E-01   3.6384185563505054E+00   4.4961925860710092E+00\n    2  1 0.0  1.0817027740264313E+00   3.5577846500107415E+00   5.3355115606411010E+00\n    3  1 0.0  1.0837528065326016E+00   4.1098074970750078E+00   3.7986666445490349E+00\n    4  2 0.0  5.9228924412533273E+00   2.6466268911619726E+00   1.2239688914990485E+00\n    5  1 0.0  5.3892796692767426E+00   2.4596400077893872E+00   3.9917001035611654E-01\n    6  1 0.0  6.3950052963992130E+00   3.5224871395184847E+00   1.1240808724238647E+00\n    7  2 0.0  4.1822746115542317E+00   1.5987872250691670E+00   3.6579743000948359E+00\n    8  1 0.0  4.6852014555577082E+00   1.0410418556709500E+00   2.9976878139513659E+00\n    9  1 0.0  4.0758623666740457E+00   1.0894620994363380E+00   4.5119446040398223E+00\n   10  2 0.0  4.1669385268713892E+00   5.4970302033175118E+00   5.8480726049046048E+00\n   11  1 0.0  4.8730244389199040E+00   4.8558002499567277E+00   6.1485166693356534E+00\n   12  1 0.0  4.2909305677989407E+00   5.6980826168950580E+00   4.8763704264099701E+00\n   13  2 0.0  2.0588829949846374E+00   4.3767096641380583E+00   9.8336312746365173E-01\n   14  1 0.0  1.9348592034245695E+00   3.9922343756879437E+00   6.8597241552630556E-02\n   15  1 0.0  2.1394708629072521E+00   3.6345576794364582E+00   1.6487320283725717E+00\n   16  2 0.0  2.5339931098401118E+00   6.3708832825217518E+00   3.4663091578748157E+00\n   17  1 0.0  2.4831571721174011E+00   5.8868847749471091E-02   2.8714017898244730E+00\n   18  1 0.0  2.9623271345173623E+00   6.6255006006868298E+00   4.3333102537280004E+00\n   19  2 0.0  2.5924978836700570E+00   1.7944388560555977E+00   6.9352523630401910E+00\n   20  1 0.0  2.1222678410324201E+00   1.2768680911581454E+00   6.2204075098346969E+00\n   21  1 0.0  1.9180281931273930E+00   2.2616218963260346E+00   3.9274315315749969E-01\n   22  2 0.0  5.9790312637835585E+00   6.7163127014570758E+00   2.3512729823005811E+00\n   23  1 0.0  6.0116037085053753E+00   6.9691212919231109E+00   3.3182411414869546E+00\n   24  1 0.0  6.8767703438302163E+00   6.3827294435137851E+00   2.0635471629013606E+00\n   25  2 0.0  6.7547865304093548E+00   8.1377929495075468E-02   5.3581116608665873E+00\n   26  1 0.0  5.9531825446743918E+00   6.7260222417346471E-01   5.2693136085523262E+00\n   27  1 0.0  4.4727592285958784E-01   6.4022081242395790E-01   5.5503336943639905E+00\n   28  2 0.0  4.6569264589470469E+00   4.3236993372651531E+00   3.2604100102435756E+00\n   29  1 0.0  3.9626142106129842E+00   3.6880495575692027E+00   3.5978666484999993E+00\n   30  1 0.0  4.6123792631715030E+00   5.1746062343494730E+00   3.7838306323283333E+00\n   31  2 0.0  1.6592261415965956E+00   1.9740050874317887E+00   2.5667232493700953E+00\n   32  1 0.0  1.3659958208733727E+00   1.1546249809050639E+00   2.0741439365038556E+00\n   33  1 0.0  2.5789980439011053E+00   2.2303030724114246E+00   2.2695177494557641E+00\n   34  2 0.0  6.7188326433244958E+00   5.0274902077599082E+00   7.0466394028585562E+00\n   35  1 0.0  6.4009802362616730E+00   4.4045226890456011E+00   6.4719907227395035E-01\n   36  1 0.0  6.0453043590359563E+00   5.7547786630259594E+00   6.9146816574097389E+00\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/correct-input-data/water.data-h2o-768",
    "content": "LAMMPS data file via BUILD_WATER.f\n\n768 atoms\n2 atom types\n\n0.0 1.9730900024520210E+01 xlo xhi\n0.0 1.9730900024520210E+01 ylo yhi\n0.0 1.9730900024520210E+01 zlo zhi\n\nMasses\n\n1 1.00794\n2 15.9994\n\nAtoms # atomic\n\n 1  2 0.0   8.1460919827525178E+00   8.1758160253135266E+00   9.5031430154332455E+00\n 2  1 0.0   8.6955130242351917E+00   7.3819150076157536E+00   9.7636349943797534E+00\n 3  1 0.0   7.4455900015270196E+00   7.8955300141256535E+00   8.8468380205066310E+00\n 4  2 0.0   1.9081959022586261E+01   1.7390283025459993E+01   1.2743999028217281E+01\n 5  1 0.0   1.8469790026285231E+01   1.6613225025090259E+01   1.2597608027321238E+01\n 6  1 0.0   4.7713000013607045E-02   1.7143494026829284E+01   1.3417623040662859E+01\n 7  2 0.0   1.4578270005284231E+00   9.5453239953204712E+00   1.2407679977023176E+00\n 8  1 0.0   1.7503160021918707E+00   9.5230449998251743E+00   2.1967769974419649E+00\n 9  1 0.0   1.7192450025475987E+00   8.6906520023968632E+00   7.9221900148133473E-01\n10  2 0.0   3.0509639994538791E+00   6.9670159984993987E+00   9.1096490127344438E+00\n11  1 0.0   3.1194420015060924E+00   7.7710680109191319E+00   9.7002520004522008E+00\n12  1 0.0   3.4530799975398421E+00   6.1775729812778719E+00   9.5734200241991818E+00\n13  2 0.0   5.4116450116755255E+00   8.2465919952694637E+00   1.2384610020354163E+00\n14  1 0.0   5.0424200018238752E+00   8.8395509857554124E+00   5.2286899982484059E-01\n15  1 0.0   4.7488510023953667E+00   7.5286940012411527E+00   1.4513599999467606E+00\n16  2 0.0   1.9418453024528127E+01   4.5553910011525884E+00   1.4962582026690171E+01\n17  1 0.0   5.5593800168460061E-01   4.2738010020707904E+00   1.5370767025887424E+01\n18  1 0.0   1.9593978024284855E+01   5.1927780008313809E+00   1.4212297027509257E+01\n19  2 0.0   1.6984057024413712E+01   1.5683270017590771E+00   1.5315294024704617E+01\n20  1 0.0   1.7836559025649731E+01   2.0908909981286574E+00   1.5302340025934580E+01\n21  1 0.0   1.7028189022459603E+01   8.4149799931263358E-01   1.4629895025601563E+01\n22  2 0.0   7.8306660119443521E+00   1.0865953030757600E+01   1.8904324023432906E+01\n23  1 0.0   7.8293959866436786E+00   1.0132421025277999E+01   1.9583977024313501E+01\n24  1 0.0   8.6912639958386269E+00   1.1371999003981815E+01   1.8961678022046140E+01\n25  2 0.0   5.8593060167898212E+00   1.9381903024609539E+01   3.6136759985859466E+00\n26  1 0.0   5.9037310255478932E+00   1.8410199026274483E+01   3.3816890019567394E+00\n27  1 0.0   6.2447090058043573E+00   1.9038600025439625E-01   2.8649889981560612E+00\n28  2 0.0   2.1654499977394817E-01   3.0436229992109256E+00   7.8344979957828098E+00\n29  1 0.0   1.0627739994388672E+00   2.5667640013069306E+00   7.5967990021543290E+00\n30  1 0.0   1.9414746024408686E+01   3.2108189989465337E+00   7.0048730184973182E+00\n31  2 0.0   7.3171990162997025E+00   2.1325060018241815E+00   1.2272106998720552E+01\n32  1 0.0   8.2686779998367825E+00   2.4389769977784370E+00   1.2244462040494465E+01\n33  1 0.0   6.9083219908996547E+00   2.3932219973584101E+00   1.3146662031492017E+01\n34  2 0.0   1.5241831025177639E+01   9.7374560157746917E+00   1.4352403043616311E+01\n35  1 0.0   1.5815054023578458E+01   8.9751689970384909E+00   1.4051849016161313E+01\n36  1 0.0   1.5814948024091803E+01   1.0438168027434287E+01   1.4777376025711911E+01\n37  2 0.0   1.8128910023188944E+01   1.0674546035996904E+01   5.9860240082721052E+00\n38  1 0.0   1.8667682024236225E+01   1.1459164015430289E+01   5.6792660130587569E+00\n39  1 0.0   1.8616045023346889E+01   1.0202502026805860E+01   6.7207840223820190E+00\n40  2 0.0   1.4091887040024533E+01   2.9921530013568534E+00   3.5472750012022267E+00\n41  1 0.0   1.4687056022703272E+01   2.9583969988902510E+00   2.7443829981414964E+00\n42  1 0.0   1.3708108042945513E+01   2.0842919995840785E+00   3.7160969984549705E+00\n43  2 0.0   1.9178652023137222E+01   1.5423094026230849E+01   6.5152500070247221E-01\n44  1 0.0   1.9162169026231293E+01   1.4461355026883293E+01   3.7805399978326421E-01\n45  1 0.0   1.8408723024037130E+01   1.5609309025268088E+01   1.2618799986994602E+00\n46  2 0.0   1.5660177025837868E+01   1.7838811023929338E+01   8.3398340248639453E+00\n47  1 0.0   1.5324259022174857E+01   1.7022542024296868E+01   8.8097959863276980E+00\n48  1 0.0   1.6113707024245688E+01   1.8439549025217357E+01   8.9981830196765529E+00\n49  2 0.0   3.6651939981046122E+00   1.2389583016089833E+01   1.2791353032825032E+01\n50  1 0.0   4.3094529988499088E+00   1.1680068035729500E+01   1.3076869008201081E+01\n51  1 0.0   3.7345759988740737E+00   1.2524616021968789E+01   1.1802944041924086E+01\n52  2 0.0   2.3746640013656060E+00   1.2881341045928304E+01   1.6795682024554580E+01\n53  1 0.0   3.1804640025243764E+00   1.2307247011258564E+01   1.6650414022363567E+01\n54  1 0.0   1.7668319985885310E+00   1.2808868004664344E+01   1.6004931024151208E+01\n55  2 0.0   1.5178441024943846E+01   1.3269077018502456E+01   1.3613634035891661E+01\n56  1 0.0   1.6066594022814058E+01   1.3446721013668357E+01   1.3189809024373567E+01\n57  1 0.0   1.5275625022567821E+01   1.2550959045508524E+01   1.4302736005429706E+01\n58  2 0.0   1.7609510024975616E+01   1.8037095025772931E+01   2.4147480001447121E+00\n59  1 0.0   1.7693234024582676E+01   1.7045953025093286E+01   2.3116539979935449E+00\n60  1 0.0   1.8318731026229475E+01   1.8489534024821527E+01   1.8740970019568539E+00\n61  2 0.0   1.9887040004212828E+00   1.0374653003793187E+01   8.5708219931327818E+00\n62  1 0.0   1.2309939994073196E+00   1.0968046025425638E+01   8.8424119823337826E+00\n63  1 0.0   1.6588500024367128E+00   9.4354199746292462E+00   8.4753149792499922E+00\n64  2 0.0   1.6321601027075559E+01   6.4365160056170447E+00   1.5078583026091705E+01\n65  1 0.0   1.6718825025289398E+01   5.9592570079528304E+00   1.5862443022675018E+01\n66  1 0.0   1.6704718023466604E+01   7.3583890060283554E+00   1.5020505023096964E+01\n67  2 0.0   1.3331365038949945E+01   5.6409989865596035E+00   1.2033834006573889E+01\n68  1 0.0   1.3827003048999694E+01   4.7991049986499927E+00   1.1820392019928784E+01\n69  1 0.0   1.2877054022608162E+01   5.9784659818723540E+00   1.1209384011964595E+01\n70  2 0.0   1.2476569006888637E+01   1.6430214024714470E+01   1.6475888023979177E+01\n71  1 0.0   1.1928773015695896E+01   1.7265733025375454E+01   1.6433129023826982E+01\n72  1 0.0   1.3222097036345753E+01   1.6553598025154010E+01   1.7130841024055506E+01\n73  2 0.0   6.7434600066192185E-01   1.6741651025973475E+01   5.9661710256896967E+00\n74  1 0.0   1.2602059995177308E+00   1.7482797023634408E+01   6.2939969943564300E+00\n75  1 0.0   9.1963999959349021E-02   1.7079360024607269E+01   5.2267219987931144E+00\n76  2 0.0   1.0100926038270643E+01   4.8717150015590871E+00   6.9899569946826743E+00\n77  1 0.0   1.0134996001575114E+01   5.0321890007997458E+00   7.9764079769940297E+00\n78  1 0.0   1.0953056022637229E+01   4.4410000022411715E+00   6.6927020166993376E+00\n79  2 0.0   8.8150690255406534E+00   4.8098419989209988E+00   1.2718895020193797E+01\n80  1 0.0   9.4898680230602359E+00   5.0239249990859847E+00   1.2012627018267798E+01\n81  1 0.0   8.6898919980898501E+00   5.6049859903805421E+00   1.3312255021168431E+01\n82  2 0.0   1.1494103998983444E+01   2.8632860000632996E+00   9.3592409995379207E+00\n83  1 0.0   1.1469448045302494E+01   2.0783999976655241E+00   9.9784350084953228E+00\n84  1 0.0   1.1950614011215627E+01   3.6298630002202401E+00   9.8108579747106521E+00\n85  2 0.0   1.7287996023843736E+01   1.1850434045074449E+01   1.7165347024088103E+01\n86  1 0.0   1.8031198023129758E+01   1.2497252003922759E+01   1.6994243024208018E+01\n87  1 0.0   1.7460907026305161E+01   1.1003458035048876E+01   1.6662621024002384E+01\n88  2 0.0   7.8430599771827414E-01   1.8869380002257645E+00   1.8186069025292575E+01\n89  1 0.0   3.7061400000976902E-01   1.1669469992101704E+00   1.8743269024659593E+01\n90  1 0.0   1.5241159975559397E+00   1.4992430018428753E+00   1.7636183022255551E+01\n91  2 0.0   1.4608192023622525E+01   1.0134352998348927E+01   9.8051189949655129E+00\n92  1 0.0   1.5076166025066678E+01   9.4004950197088153E+00   9.3126590115598145E+00\n93  1 0.0   1.5264086022486529E+01   1.0617810036986755E+01   1.0384880041280024E+01\n94  2 0.0   3.6469960013668281E+00   5.3758099777917199E+00   1.1385365014834704E+01\n95  1 0.0   3.7404070025357905E+00   6.1152270159260400E+00   1.2052101045062079E+01\n96  1 0.0   2.7363780022124908E+00   4.9699450026042422E+00   1.1463135014121452E+01\n97  2 0.0   1.5204934022596271E+01   1.4927292024164149E+01   1.8203838023359104E+01\n98  1 0.0   1.6166471024419756E+01   1.4975024025343785E+01   1.8474335023494575E+01\n99  1 0.0   1.4735130025821062E+01   1.4243600029025327E+01   1.8762273027079136E+01\n100  2 0.0  1.1842423042984128E+01   9.6295500094700293E-01   1.2824437033154414E+01\n101  1 0.0  1.2060909040946296E+01   1.0579439979685081E+00   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1.5498200025738668E-01\n700  2 0.0  6.1989420036452385E+00   1.8140466025733950E+01   1.3326869043550118E+01\n701  1 0.0  6.3715199737221946E+00   1.7552823022483206E+01   1.4117370044764828E+01\n702  1 0.0  5.5129449813787330E+00   1.7713584026274731E+01   1.2737649007549354E+01\n703  2 0.0  1.5368275024576622E+01   9.9085500142055292E+00   4.2213119994167227E+00\n704  1 0.0  1.5880660022166364E+01   1.0706073038225382E+01   3.9028500013766645E+00\n705  1 0.0  1.4693089023889060E+01   1.0195718027909150E+01   4.9007659995037782E+00\n706  2 0.0  1.6824454024399575E+01   1.5284496022290496E+01   1.2700499021219864E+01\n707  1 0.0  1.7021973026503304E+01   1.4339260028039128E+01   1.2440660999467763E+01\n708  1 0.0  1.7023784024372571E+01   1.5411675022373380E+01   1.3672144048575969E+01\n709  2 0.0  1.8087632025998726E+01   9.4512899991155805E+00   6.6629999879102053E-01\n710  1 0.0  1.7825590023506926E+01   9.1560119742659047E+00   1.5850739998826140E+00\n711  1 0.0  1.8933688024404717E+01   8.9912349758451722E+00   3.9696799974316360E-01\n712  2 0.0  1.4615773026896672E+01   2.5593989975857943E+00   6.3031100079836921E-01\n713  1 0.0  1.4673730022939123E+01   1.7622510014536856E+00   2.9314000022807960E-02\n714  1 0.0  1.5396599022996799E+01   3.1610889992556492E+00   4.6214299989914387E-01\n715  2 0.0  9.6963240238681010E+00   6.3508109940871318E+00   1.7120637026944330E+01\n716  1 0.0  9.4808959822413481E+00   7.1185929889575785E+00   1.7724047023878889E+01\n717  1 0.0  1.0589887049055260E+01   5.9746650078183228E+00   1.7365866027039367E+01\n718  2 0.0  1.3868327026397569E+01   1.6092359026088822E+01   5.9487319907798231E+00\n719  1 0.0  1.3751504013703714E+01   1.7024861026994632E+01   6.2904809822292362E+00\n720  1 0.0  1.2981525033816267E+01   1.5630577022414558E+01   5.9302979968823131E+00\n721  2 0.0  1.1359190005058706E+00   1.2558577027686010E+01   7.1101410234993176E+00\n722  1 0.0  3.5555899997235835E-01   1.3145807039876059E+01   6.8952040054044383E+00\n723  1 0.0  1.8162910013391120E+00   1.2628075034683143E+01   6.3805759949640883E+00\n724  2 0.0  3.5445290001230596E+00   8.5273250024454565E+00   1.8525293026523997E+01\n725  1 0.0  3.7665219983245608E+00   9.0847430228224244E+00   1.7725290024099518E+01\n726  1 0.0  2.9047139978250716E+00   9.0248459837566148E+00   1.9111048026038070E+01\n727  2 0.0  8.3271649933125165E+00   8.9521479892612721E+00   1.3660203006110430E+01\n728  1 0.0  7.6144619848588890E+00   9.5921119919858899E+00   1.3372974031192378E+01\n729  1 0.0  8.0817569990266680E+00   8.0274249991575282E+00   1.3369236029226171E+01\n730  2 0.0  7.0541169795056353E+00   1.2759896040741253E+01   7.7163560088964864E+00\n731  1 0.0  6.2757520225578372E+00   1.2137500033412250E+01   7.7986369792980614E+00\n732  1 0.0  7.7045580030304386E+00   1.2393996036503349E+01   7.0507399822311427E+00\n733  2 0.0  8.8963959952705380E+00   1.7381622024420789E+01   1.7715538023701086E+01\n734  1 0.0  8.0837689836915398E+00   1.6830631025287371E+01   1.7525681026026820E+01\n735  1 0.0  9.2110289940315955E+00   1.7201396025484438E+01   1.8647485023550498E+01\n736  2 0.0  1.8084033023009905E+01   7.7934830049570438E+00   5.7936099892834161E+00\n737  1 0.0  1.8196518026159566E+01   8.0380109775449693E+00   6.7567049946445028E+00\n738  1 0.0  1.8978413023722357E+01   7.5921139846555858E+00   5.3941910010506460E+00\n739  2 0.0  1.0292320015272002E+01   6.6018300130690770E+00   4.8409750022588041E+00\n740  1 0.0  9.9592850378345581E+00   5.9887210128335280E+00   5.5573450129725597E+00\n741  1 0.0  1.0639971025964531E+01   6.0613879975444451E+00   4.0747749985288246E+00\n742  2 0.0  4.3431360013205831E+00   7.7445060138504740E+00   6.6885350107701065E+00\n743  1 0.0  3.6088989995048033E+00   7.0805139791206457E+00   6.5470769998127638E+00\n744  1 0.0  4.0253689981674574E+00   8.4670829927573532E+00   7.3024620131347318E+00\n745  2 0.0  1.6676560022644992E+01   2.7681690003668029E+00   1.2790233029263002E+01\n746  1 0.0  1.6578238024142120E+01   3.3823579983674126E+00   1.2007223007695710E+01\n747  1 0.0  1.5926019023405868E+01   2.9240269974002655E+00   1.3432414019903108E+01\n748  2 0.0  1.1136732002968680E+01   3.5561379997655074E+00   1.1993247014274450E+01\n749  1 0.0  1.0957697012592215E+01   4.4755559989364393E+00   1.2343414050923052E+01\n750  1 0.0  1.1953278048036951E+01   3.1844040020146558E+00   1.2434911012836686E+01\n751  2 0.0  8.5855710086203878E+00   1.4614609022249748E+01   1.2741560050462779E+01\n752  1 0.0  9.0922540053683285E+00   1.5424202022762016E+01   1.3037923047343277E+01\n753  1 0.0  7.9885930230704600E+00   1.4305517043331857E+01   1.3481884045414944E+01\n754  2 0.0  1.3833893042091290E+01   7.4024589897971689E+00   1.4331337028118599E+01\n755  1 0.0  1.4728634026328368E+01   7.0474870240943526E+00   1.4602323025037228E+01\n756  1 0.0  1.3842727020576451E+01   8.4012120192657793E+00   1.4380463035527114E+01\n757  2 0.0  9.0429799870945615E+00   2.6061570004870283E+00   5.2591879995194200E+00\n758  1 0.0  8.4684860002905502E+00   3.4182969996973940E+00   5.3610939829619317E+00\n759  1 0.0  9.7318690157238645E+00   2.7716050009000539E+00   4.5534550010431021E+00\n760  2 0.0  1.1964111046345371E+01   1.0484564009623561E+01   1.6277865022918416E+01\n761  1 0.0  1.2197761040562144E+01   9.5471629919558474E+00   1.6536264026628274E+01\n762  1 0.0  1.2587834018442697E+01   1.1120797048438851E+01   1.6731934025355613E+01\n763  2 0.0  1.2356654011764853E+01   2.3614500019576593E-01   8.4160419988663016E+00\n764  1 0.0  1.1824028049446891E+01   6.5078099871424921E-01   9.1538680128052050E+00\n765  1 0.0  1.1746962014600767E+01   1.9720474024499346E+01   7.6627299843413574E+00\n766  2 0.0  8.2954529907319063E+00   1.6941897026402810E+01   1.5046029023195610E+01\n767  1 0.0  9.2826590030845129E+00   1.6807709026565885E+01   1.5132158022088607E+01\n768  1 0.0  8.1045429992055418E+00   1.7505451025850366E+01   1.4242313017136258E+01\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/hdnnp-data/hardness.001.data",
    "content": "     12.5140142151\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/hdnnp-data/hardness.008.data",
    "content": "      9.0176209746\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/hdnnp-data/input.nn",
    "content": "## #############################################################\n### This is the input file for RuNNer \n### #############################################################\n### General remarks: \n### - commands can be switched off by using the # character at the BEGINNING of the line\n### - the input file can be structured by blank lines and comment lines\n### - the order of the keywords is arbitrary\n### - if keywords are missing, default values will be used and written to runner.out\n### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message \n\n### THIS INPUT.NN IS AN EXAMPLE, IT IS NOT A REALISTIC CASE\n### It contains only a subset of all keywords\n\n########################################################################################################################\n### general keywords\n########################################################################################################################\nuse_electrostatics\nuse_short_nn\nnnp_gen 4 # nnp_type_gen --> nnp_gen \nrunner_mode 3\nparallel_mode 1                         \nnumber_of_elements 2                  \nelements  H O                          \nrandom_seed 10                         \nrandom_number_type 5                      \nremove_atom_energies                     \natom_energy H -0.458907306351869\natom_energy O -74.94518524\ninitial_hardness H 10.0 ## fixed_atomhardness--> initial_hardness \ninitial_hardness O 10.0 \nfixed_gausswidth H 0.585815056466\nfixed_gausswidth O 1.379499971678\nenergy_threshold 100.0d0              \nbond_threshold 0.4d0                 \newald_prec 1.0e-4 # for optimal combination of ewald parameters\nscreen_electrostatics 4.8 8.0\n########################################################################################################################\n### NN structure of the electrostatic-range NN  \n########################################################################################################################\nglobal_hidden_layers_electrostatic 2              \nglobal_nodes_electrostatic 15 15                 \nglobal_activation_electrostatic t t l            \nglobal_hidden_layers_short 2              \nglobal_nodes_short 15 15                 \nglobal_activation_short t t l            \n## element_hidden_layers_electrostatic needs to take care !!! should check the output  \n########################################################################################################################\n### symmetry function generation ( mode 1): \n########################################################################################################################\ntest_fraction 0.1      \n\n########################################################################################################################\n### symmetry function definitions (all modes): \n########################################################################################################################\ncutoff_type 2\n\n\n# radial H H\nsymfunction H 2 H 0.001 0.0 8.00\nsymfunction H 2 H 0.01  0.0 8.00\nsymfunction H 2 H 0.03  0.0 8.00\nsymfunction H 2 H 0.06  0.0 8.00\nsymfunction H 2 H 0.15  1.9 8.00\nsymfunction H 2 H 0.30  1.9 8.00\nsymfunction H 2 H 0.60  1.9 8.00\nsymfunction H 2 H 1.50  1.9 8.00\n\n# radial H O / O H\nsymfunction H 2 O 0.001 0.0 8.00\nsymfunction H 2 O 0.01  0.0 8.00\nsymfunction H 2 O 0.03  0.0 8.00\nsymfunction H 2 O 0.06  0.0 8.00\nsymfunction H 2 O 0.15  0.9 8.00\nsymfunction H 2 O 0.30  0.9 8.00\nsymfunction H 2 O 0.60  0.9 8.00\nsymfunction H 2 O 1.50  0.9 8.00\n\nsymfunction O 2 H 0.001 0.0 8.00\nsymfunction O 2 H 0.01  0.0 8.00\nsymfunction O 2 H 0.03  0.0 8.00\nsymfunction O 2 H 0.06  0.0 8.00\nsymfunction O 2 H 0.15  0.9 8.00\nsymfunction O 2 H 0.30  0.9 8.00\nsymfunction O 2 H 0.60  0.9 8.00\nsymfunction O 2 H 1.50  0.9 8.00\n\n# radial O O\nsymfunction O 2 O 0.001 0.0 8.00\nsymfunction O 2 O 0.01  0.0 8.00\nsymfunction O 2 O 0.03  0.0 8.00\nsymfunction O 2 O 0.06  0.0 8.00\nsymfunction O 2 O 0.15  4.0 8.00\nsymfunction O 2 O 0.30  4.0 8.00\nsymfunction O 2 O 0.60  4.0 8.00\nsymfunction O 2 O 1.50  4.0 8.00\n\n# angular\nsymfunction H 3 O H 0.2  1.0 1.0  8.00000\n\nsymfunction O 3 H H 0.07  1.0 1.0  8.00000\nsymfunction H 3 O H 0.07  1.0 1.0  8.00000\nsymfunction O 3 H H 0.07 -1.0 1.0  8.00000\nsymfunction H 3 O H 0.07 -1.0 1.0  8.00000\n\nsymfunction O 3 H H 0.03  1.0 1.0  8.00000\nsymfunction H 3 O H 0.03  1.0 1.0  8.00000\nsymfunction O 3 H H 0.03 -1.0 1.0  8.00000\nsymfunction H 3 O H 0.03 -1.0 1.0  8.00000\n\nsymfunction O 3 H H 0.01  1.0 4.0  8.00000\nsymfunction H 3 O H 0.01  1.0 4.0  8.00000\nsymfunction O 3 H H 0.01 -1.0 4.0  8.00000\nsymfunction H 3 O H 0.01 -1.0 4.0  8.00000\n\nsymfunction O 3 O H 0.03  1.0 1.0   8.00000\nsymfunction O 3 O H 0.03 -1.0 1.0   8.00000\nsymfunction O 3 O H 0.001  1.0 4.0  8.00000\nsymfunction O 3 O H 0.001 -1.0 4.0  8.00000\n\nsymfunction H 3 O O 0.03  1.0 1.0   8.00000\nsymfunction H 3 O O 0.03 -1.0 1.0   8.00000\nsymfunction H 3 O O 0.001  1.0 4.0  8.00000\nsymfunction H 3 O O 0.001 -1.0 4.0  8.00000\n\n#symfunction O 3 O O 0.03  1.0 1.0   8.00000\n#symfunction O 3 O O 0.03 -1.0 1.0   8.00000\n#symfunction O 3 O O 0.001  1.0 4.0  8.00000\n#symfunction O 3 O O 0.001 -1.0 4.0  8.00000\n\n########################################################################################################################\n### fitting (mode 2):general inputs for electrostatic range AND electrostatic part:\n########################################################################################################################\nepochs 30                        \npoints_in_memory 500                \nmix_all_points                       \nscale_symmetry_functions             \ncenter_symmetry_functions             \nfitting_unit  eV                      \n########################################################################################################################\n### fitting options ( mode 2): electrostatic range part only:\n########################################################################################################################\noptmode_short_energy 1                 \noptmode_short_force 1                   \nshort_energy_error_threshold 0.8\t \nshort_force_error_threshold 0.8\t\t \nkalman_lambda_charge 0.98000                \nkalman_nue_charge 0.99870                   \nkalman_lambda_short 0.98000                \nkalman_nue_short 0.99870                   \n#use_old_weights_electrostatic               \n#force_update_scaling -1.0d0          \n#electrostatic_energy_group 1         \n#electrostatic_energy_fraction 1.00           \n#electrostatic_force_group 1                 \n\n#short_force_fraction 0.025            \n#use_short_forces                    \nweights_min -1.0                 \nweights_max 1.0                  \n#precondition_weights            \n#repeated_energy_update          \n#nguyen_widrow_weights_short     \nregularize_fit_param 0.00001 ## 4G cases L2 regularization \n########################################################################################################################\n### output options for mode 2 (fitting):  \n########################################################################################################################\n#write_trainpoints              \n#write_trainforces      \nwrite_traincharges\n########################################################################################################################\n### output options for mode 3 (prediction):  \n########################################################################################################################\ncalculate_forces     \n#calculate_stress       \n\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/hdnnp-data/scaling.data",
    "content": "   1    1        0.332976205       0.801624245       0.529022897\n   1    2        0.302337347       0.559557103       0.444982986\n   1    3        0.279156661       0.689216779       0.447398011\n   1    4        0.281666680       0.500530512       0.405813837\n   1    5        0.184597589       0.500915675       0.315606906\n   1    6        0.246938750       0.411905369       0.340350304\n   1    7        0.108144137       0.321581311       0.196758358\n   1    8        0.206524003       0.332910999       0.275222988\n   1    9        0.192266492       0.337437016       0.268862686\n   1   10        0.137888800       0.438702601       0.258407517\n   1   11        0.123155815       0.264414914       0.211036382\n   1   12        0.079044824       0.323909809       0.164714948\n   1   13        0.060252990       0.223808509       0.148947959\n   1   14        0.027902463       0.204282365       0.091898588\n   1   15        0.008301924       0.147213416       0.061276132\n   1   16        0.002347157       0.105178649       0.028579526\n   1   17        0.000003005       0.005579422       0.001547947\n   1   18        0.000019930       0.000524387       0.000216322\n   1   19        0.000014927       0.003701946       0.000686603\n   1   20        0.014211691       0.033835238       0.022236736\n   1   21        0.000923120       0.006114561       0.002645102\n   1   22        0.000007167       0.002120404       0.000529206\n   1   23        0.011944886       0.029242703       0.018758239\n   1   24        0.000007559       0.000378023       0.000104479\n   1   25        0.000324117       0.002415409       0.001014563\n   1   26        0.004378590       0.013887358       0.008122121\n   1   27        0.000247127       0.002444197       0.000854440\n   2    1        0.693621490       1.096065781       0.889965972\n   2    2        0.054518807       0.204722516       0.128280243\n   2    3        0.640580762       0.993246230       0.811627675\n   2    4        0.038923431       0.158395358       0.097711184\n   2    5        0.551807090       0.820610595       0.680700608\n   2    6        0.018487600       0.093003263       0.053784777\n   2    7        0.456675414       0.666767988       0.550445975\n   2    8        0.006106326       0.042261243       0.022350937\n   2    9        0.436638353       0.665201432       0.537725373\n   2   10        0.029120590       0.167003997       0.094121049\n   2   11        0.321348553       0.514230878       0.422072764\n   2   12        0.015448674       0.137320836       0.069828762\n   2   13        0.196593790       0.408515108       0.297895918\n   2   14        0.004538808       0.100407427       0.041347516\n   2   15        0.049968528       0.246264120       0.122552265\n   2   16        0.000129041       0.042031039       0.011393965\n   2   17        0.000009812       0.000447566       0.000169694\n   2   18        0.001933554       0.017758036       0.008603827\n   2   19        0.002325650       0.010442752       0.005875043\n   2   20        0.000956077       0.010566084       0.003169792\n   2   21        0.007035328       0.022388524       0.012854532\n   2   22        0.000018894       0.000470842       0.000153842\n   2   23        0.004523457       0.015610385       0.008548809\n   2   24        0.000379375       0.005673761       0.002380896\n   2   25        0.002690099       0.009402971       0.005666492\n   2   26        0.001503235       0.006697403       0.003470192\n       -0.2343807221       -0.2306674948\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/hdnnp-data/weights.001.data",
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0.5942708655\n     -0.3151702181\n      0.6692082089\n     -0.3454416214\n      0.3452339579\n      0.6332216728\n     -0.9700023198\n     -0.4055381926\n     -0.0355149584\n      0.3993968037\n      0.8704729420\n      0.7604167805\n     -0.9467715231\n     -0.0538438193\n     -0.3568811236\n      0.8729153053\n      0.6064032025\n     -0.9018643963\n      0.6096202633\n     -0.1629901482\n     -0.2102066800\n      0.0418629788\n      0.9461284119\n      0.4613308589\n      0.1256943942\n      0.8828697808\n     -0.2766490154\n      0.7811020735\n     -0.1545083060\n      0.8004130438\n      0.3679158189\n     -0.0265489216\n     -0.7118616309\n     -0.1264359181\n     -0.9277114325\n     -0.9355174106\n     -0.4718635331\n      0.5817545548\n     -0.6982732602\n     -0.1671310049\n      0.1898598368\n      0.7099377849\n     -0.4315402269\n     -0.5776648746\n     -0.3974497971\n     -0.0331213292\n      0.0646055872\n      0.4276625592\n      0.1290703082\n      0.2219742921\n      0.2753971848\n     -0.7072481023\n      0.8105753204\n      0.2247370729\n      0.7730055000\n     -0.6209426987\n     -0.5411414259\n     -0.7731702568\n     -0.6559320148\n     -0.0755143701\n     -0.4271403361\n      0.3461391136\n      0.3417807216\n      0.0184106155\n      0.5513405590\n     -0.9229149080\n      0.3778375365\n     -0.5859511746\n     -0.5101791615\n     -0.1856282699\n      0.9710670331\n      0.5635923003\n     -0.1112938287\n     -0.3242495229\n      0.8414739826\n      0.3827220295\n      0.3038715732\n     -0.4112382338\n     -0.0920345335\n     -0.8762491125\n     -0.0290280828\n     -0.1545475389\n      0.5126446354\n     -0.0427995278\n      0.2226437635\n     -0.2097325805\n     -0.8791256965\n      0.5245989490\n     -0.2850807242\n      0.2915403972\n      0.0388828733\n      0.4712610496\n     -0.4763792207\n     -0.6202220605\n      0.7065563132\n      0.4389203799\n     -0.6202401377\n      0.4799276035\n     -0.3919167546\n      0.7818915886\n     -0.4150139967\n     -0.5392546384\n      0.1999568255\n     -0.4016607533\n     -0.2214671535\n      0.0185862788\n     -0.3383099818\n      0.2341326634\n     -0.4936292943\n      0.3704642374\n     -0.1905999828\n     -0.6392079429\n      0.5426081711\n      0.0577432910\n     -0.7137274551\n     -0.6305892988\n     -0.2896260228\n      0.2198150488\n     -0.2953854579\n     -0.3291196787\n     -0.3184137743\n     -0.5783357391\n     -0.3965853066\n      0.2753442744\n     -0.1381662878\n     -0.2153889807\n      0.8826328638\n     -0.5031027535\n     -0.0169396930\n      0.5905112079\n      0.8329543750\n      0.5040034097\n     -0.4057313868\n     -0.9032904717\n     -0.0420881092\n     -0.5384331098\n      0.7157622261\n      0.7444845842\n      0.3982970713\n      0.3807439306\n     -0.7093090571\n     -0.9186332195\n      0.1758165519\n     -0.2936914364\n      0.0916198723\n      0.5356016954\n     -0.3221428577\n     -0.0415891409\n      0.0620953366\n      0.4467405457\n      0.1981172492\n      0.5285643340\n      0.1085165576\n     -0.1184786705\n      0.6077267684\n     -0.1420929770\n      0.5731801739\n      0.6227406456\n      0.9620074715\n      0.8490074878\n      0.9362903172\n     -0.5057953427\n      0.7232282422\n      0.6995187786\n      0.5711734509\n      0.8734445410\n     -0.2051459396\n      0.6597777224\n     -0.8903637293\n      0.6837552666\n      0.3306572551\n      0.0570701747\n     -0.1489858225\n      0.0359842033\n      0.4906376652\n     -0.3606952376\n      0.3330177582\n      0.1465340738\n     -0.6217662946\n     -0.5705314998\n      0.4410674000\n      0.1219662330\n      0.1473201459\n     -0.2329137189\n      0.4086990983\n     -0.3294037942\n     -0.3072180886\n     -0.5955341346\n     -0.8755348844\n      0.1293538474\n     -0.8731595053\n      0.0908548875\n     -0.8553159417\n     -0.9554948917\n      0.5162502107\n      0.6595608439\n      0.6658005530\n      0.8071896899\n     -0.5075111258\n     -0.3702491150\n     -0.8165489848\n     -0.3544039739\n      0.0640174136\n     -0.8874649470\n      0.3488438078\n     -0.6485081734\n     -0.8894295941\n      0.6620174977\n      0.1436414822\n      0.5153693607\n     -0.5055985622\n      0.3475276708\n      0.5959987026\n     -0.1391022732\n      0.1675133773\n      0.8193941177\n      0.4471004159\n     -0.5270840497\n      0.4290683737\n     -0.8979001370\n      0.7832581113\n      0.6417166144\n     -0.1368274109\n     -0.3522653815\n      1.0441250654\n     -0.2395379537\n      0.8580799449\n     -0.0389485442\n      0.6100646644\n      0.4963950500\n      0.3918289484\n     -0.3973449051\n      0.4852352488\n      0.8959630161\n      0.0037728442\n     -0.5389766063\n      0.3209411781\n     -0.4118207699\n      0.3170692058\n     -0.6112952942\n     -0.1783209683\n     -0.3613652756\n     -0.4437654874\n     -0.8162848193\n      0.5383884320\n      0.6206342410\n      0.7399253915\n      0.2576662702\n     -0.6991193103\n      0.6458670116\n      0.6359505144\n     -0.8614888917\n     -0.4364971410\n      0.3140537477\n     -0.7007379188\n      0.5574459567\n      0.0968387286\n     -0.8535521100\n      0.8683360982\n     -0.8004420276\n      0.8172673232\n      1.0194018870\n     -0.7115632942\n     -0.0332603046\n     -0.7047725535\n      0.8689103772\n     -0.2153443938\n     -0.1033774054\n      0.6260273257\n     -0.8350477063\n     -0.0386191740\n     -0.6929678282\n     -0.7384682172\n      0.6416105171\n      0.7622353252\n     -0.3876754987\n     -0.0976554640\n      0.4329428562\n     -0.3921009642\n     -0.1309682176\n     -0.2247897804\n     -0.0168939603\n      0.0183562826\n      0.6505278435\n      0.3453244872\n      0.4130576111\n     -0.1728616074\n      0.8693078578\n     -0.6829366270\n     -0.2191063461\n     -0.2831385089\n      0.2284952515\n     -0.0279698201\n      0.6989477888\n     -0.6133666784\n     -0.4987286386\n     -0.1452792866\n      0.0712386228\n      0.6156780866\n     -0.0400875824\n     -0.7615680754\n      0.1290922112\n     -0.6658924258\n     -0.8345649568\n     -0.5443670820\n      0.4816110824\n     -0.3449383811\n      0.2886147595\n     -0.4378887623\n     -0.9371529312\n      0.1045406164\n      0.3932260783\n      0.2752084607\n      0.1814527216\n     -0.1775405112\n      1.0685752108\n      0.5990474503\n      0.6021958194\n      0.0551747631\n      0.1055465704\n     -0.6053510840\n     -0.6506144476\n     -0.0741603451\n      0.0090392873\n      0.2045025063\n     -0.4781022051\n     -0.2293780166\n     -0.9960570834\n     -0.5201790586\n      1.0164998384\n      0.7288111916\n      0.1417528795\n      0.1071142373\n      0.7881410576\n     -0.4822513208\n     -0.7156728419\n     -0.3935481577\n     -0.7733693160\n      0.5246759825\n      0.3407302981\n      0.4548641558\n     -0.2068535967\n     -0.1649316036\n     -0.6315615834\n      0.9700455187\n     -0.5779436236\n     -0.4218804285\n     -0.9606854545\n     -0.0983985000\n     -0.7261310067\n     -0.3436863506\n     -0.6817386964\n     -0.6446186946\n      0.4362963755\n      0.1893713211\n      0.9115416413\n     -0.5887616141\n     -0.2896035883\n     -0.5783337128\n      0.1599300242\n      0.0087457405\n      0.1721412119\n     -0.4867249018\n      0.7378585555\n     -0.7026878933\n     -0.1655095163\n      0.2094691226\n      0.6002739629\n     -0.5171355385\n     -0.0173132561\n     -0.2380956229\n      0.6635455096\n     -0.2501503261\n      0.6133652264\n      0.5780862620\n      0.6577902668\n      0.2769433310\n     -0.9776496994\n      0.8134599042\n     -0.0190719027\n     -0.7318424178\n     -0.4826918411\n      0.3888605289\n     -0.6819514697\n      0.9505006296\n     -0.1485141208\n      0.0939239244\n     -0.1520702891\n      0.7338668220\n     -0.6425614935\n      0.3192698130\n      0.9165973613\n     -0.9669436343\n     -0.4954173590\n      0.4112375957\n      0.5458122867\n     -0.8229239184\n     -0.5429910248\n      0.9275309325\n      0.7127841454\n     -0.2567688469\n     -0.1854437513\n      0.7619540377\n      0.6155455350\n     -0.8155913346\n     -0.1551608561\n     -0.4265190006\n     -0.9237142868\n      0.6865251218\n     -0.7229777878\n      0.4915316231\n     -0.2854209783\n     -0.8598012727\n      0.7645933695\n     -0.5502033158\n      0.4798885599\n     -0.3823706115\n      1.0391022343\n     -1.0530272356\n     -0.4066625689\n     -0.1466145889\n      0.4000785355\n      0.8121005453\n     -0.3908539269\n     -0.4503908647\n      0.1629499183\n     -0.0915027514\n      0.8615411937\n      0.7777514854\n     -0.0702736026\n      0.0317188077\n      0.0321728247\n      0.2638355092\n      0.9873595251\n      0.1372122762\n      0.9002071334\n      0.9683609528\n     -0.1434027270\n      0.0115974373\n      0.7104187075\n      0.9803357208\n     -0.8746257674\n     -0.1268704133\n      0.0259584427\n     -0.9617033357\n      0.5290441297\n     -1.1523602359\n      0.2565233342\n     -0.5561208083\n      0.2822574217\n      0.9562597424\n     -0.1492012448\n     -0.1082100677\n     -0.3810973294\n     -0.3577272526\n      0.0341348973\n      0.5814419788\n     -0.2362748063\n      0.2740130803\n      0.2005358826\n     -0.1874268796\n      0.7040305804\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/md.lmp",
    "content": "###############################################################################\n# MD simulation for carbon chain\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"water.data\"\n# Timesteps\nvariable numSteps        equal  10\nvariable dt              equal  0.0005\n# NN\n#variable hdnnpCutoff     equal  4.238709440998 #8.01\nvariable hdnnpCutoff     equal  4.23341767420363 #8.00000001\nvariable hdnnpDir        string \"hdnnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_O          equal  15.9994\n\n# Conversions\nvariable c1\t\t\t\t equal \t1.8897261328\nvariable c2\t\t\t\t equal  0.0367493254\n#variable c1\t\t\t\t equal  1.0\n#variable c2\t\t\t\t equal  1.0\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary p p p\natom_style charge\natom_modify map yes\nread_data ${cfgFile}\nmass 1 ${mass_H}\nmass 2 ${mass_O}\ntimestep ${dt}\nthermo 1\n\nneighbor 0.0 bin\nneigh_modify delay 10 # Seems this was the default previously (29Oct2020).\n\n###############################################################################\n# NN\n###############################################################################\npair_style hdnnp/4g dir ${hdnnpDir} showew no showewsum 10 resetew no maxew 1000000 cflength ${c1} cfenergy ${c2} emap \"1:H,2:O\"\npair_coeff * * ${hdnnpCutoff}\nkspace_style hdnnp ewald 1.0e-6\n#fix 1 all hdnnp 1 1.0e-5 1.0e-4 1.0e-2 100 nnp\nfix 1 all hdnnp 1 1.0e-7 1.0e-1 1.0e-1 100 nnp nnp 1 # No clue whether this is the right flag at the end.\n\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\n#dump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/hardness.001.data",
    "content": "     12.5140142151\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/hardness.008.data",
    "content": "      9.0176209746\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/input.data",
    "content": "begin\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\nlattice   1.3443888628000000E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   0.0000000000000000E+00   1.3443888628000000E+01   0.0000000000000000E+00\nlattice   0.0000000000000000E+00   0.0000000000000000E+00   1.3443888628000000E+01\natom   1.0281570000000000E+00   6.8756146279999992E+00   8.4965726279999991E+00  O  -2.8256347534442394E-01   0.0000000000000000E+00  -2.9283692352115263E+00  -2.1942965040430695E-01  -7.8128583031086121E-02\natom   2.0441220000000002E+00   6.7232386279999998E+00   1.0082655627999999E+01  H   1.2277837277223855E-01   0.0000000000000000E+00   1.9482823532380507E+00   3.1792184330776235E-01   2.2469585801699852E+00\natom   2.0479959999999999E+00   7.7664106280000009E+00   7.1784396279999996E+00  H   1.2747526484297358E-01   0.0000000000000000E+00   8.9380603941331793E-01   2.7100055065674783E-01  -2.0117787682273802E-01\natom   1.1192644628000000E+01   5.0014000000000003E+00   2.3129659999999999E+00  O  -2.0320633594884582E-01   0.0000000000000000E+00   2.8271820248615240E+00   3.8199554621973880E-01   3.5845413797895835E+00\natom   1.0184262628000001E+01   4.6480459999999999E+00   7.5432200000000005E-01  H   1.5077528010356028E-01   0.0000000000000000E+00  -1.1936480532254552E+00  -2.3140105928612867E-01  -2.3175789249624752E+00\natom   1.2084808628000001E+01   6.6565360000000000E+00   2.1242049999999999E+00  H   1.0545961981723478E-01   0.0000000000000000E+00  -3.4603179700863103E+00  -1.3868476023525984E+00  -1.0545047365673061E+00\natom   7.9033536279999996E+00   3.0212699999999999E+00   6.9125696280000009E+00  O  -2.3518637803977813E-01   0.0000000000000000E+00   4.2372154470977669E-01   1.8073177424203288E-01   3.0951853714291844E-01\natom   8.8537476279999989E+00   1.9672839999999998E+00   5.6648090000000000E+00  H   1.1004800576876206E-01   0.0000000000000000E+00   7.7840436378832478E-02   5.2958376699306908E-01  -2.2524862715071485E+00\natom   7.7022636279999999E+00   2.0587849999999999E+00   8.5263396280000006E+00  H   1.2457842239861067E-01   0.0000000000000000E+00  -2.3265786214644388E-01   2.0210037813235607E-01   2.1477750389810897E+00\natom   7.8743726279999988E+00   1.0387881627999999E+01   1.1051255628000000E+01  O  -2.2058240732065956E-01   0.0000000000000000E+00  -3.4565727104575689E-01   2.5528939648646114E+00  -3.8700539207258222E+00\natom   9.2086816279999990E+00   9.1761326279999995E+00   1.1619012628000000E+01  H   1.2797577200732241E-01   0.0000000000000000E+00   1.5078420052350747E-01  -2.1634546570493454E+00   1.1018383816958270E+00\natom   8.1086836279999996E+00   1.0767815628000001E+01   9.2150046279999991E+00  H   1.1917909653994410E-01   0.0000000000000000E+00  -1.8331532626603048E-01  -1.1747870971878707E+00   6.7991269031499835E+00\natom   3.8907250000000002E+00   8.2707826279999992E+00   1.8582870000000000E+00  O  -2.6183165626861749E-01   0.0000000000000000E+00   7.0244269367983858E-01  -1.1111776866062637E+00   1.6022264684182443E+00\natom   3.6563539999999999E+00   7.5442296280000001E+00   1.2963000000000000E-01  H   1.2478853272527493E-01   0.0000000000000000E+00  -9.2733544280998526E-01   1.2708147351939285E+00  -2.1037967614413642E+00\natom   4.0430140000000003E+00   6.8683186279999999E+00   3.1156519999999999E+00  H   9.9154652510639180E-02   0.0000000000000000E+00   1.8655372292621097E-01   1.3721069236350780E+00  -8.0692036225339978E-02\natom   4.7885530000000003E+00   1.2039224627999999E+01   6.5503749999999998E+00  O  -2.7263628991795935E-01   0.0000000000000000E+00  -1.1292771081345108E+00  -9.0760280713822394E-01  -1.5762793800709740E-01\natom   4.6924869999999999E+00   1.1124599999999998E-01   5.4261629999999998E+00  H   1.1434733344402727E-01   0.0000000000000000E+00  -9.8293571178456843E-02   1.0082309420963453E+00  -5.8307946025373902E-01\natom   5.5979869999999998E+00   1.2520381627999999E+01   8.1887696280000011E+00  H   1.1263403257973484E-01   0.0000000000000000E+00  -5.8627648478079153E-01   3.6509413794346102E-01  -1.1572643025824929E-01\natom   4.8991110000000004E+00   3.3909980000000002E+00   1.3105727628000000E+01  O  -2.7372231339107428E-01   0.0000000000000000E+00   1.0579372843395085E+00   1.1643437983388070E+00   1.2704653330434790E+00\natom   4.0105050000000002E+00   2.4129309999999999E+00   1.1754866627999998E+01  H   1.3658196132808181E-01   0.0000000000000000E+00  -2.7108633263781412E+00  -1.3756498865725824E+00  -1.9441844331785387E+00\natom   3.6245479999999999E+00   4.2738459999999998E+00   7.4217699999999998E-01  H   9.0172983387061936E-02   0.0000000000000000E+00  -4.0507125991796944E-01  -1.6796036702909269E+00  -1.4731090864111782E-01\natom   1.1298731628000001E+01   1.2691991628000000E+01   4.4432619999999998E+00  O  -2.5637106920821656E-01   0.0000000000000000E+00  -2.8283675022934567E+00   1.2289852492197650E+00   4.1542682352061577E-01\natom   1.1360284628000000E+01   1.3169730628000000E+01   6.2705669999999998E+00  H   1.1847178479117913E-01   0.0000000000000000E+00   1.1556735718984914E+00  -7.1030210772562219E-01   1.8949900190596836E+00\natom   1.2995212628000001E+01   1.2061610628000000E+01   3.8995389999999999E+00  H   1.3767024849619425E-01   0.0000000000000000E+00   2.6903838305192367E+00  -9.4978647053313636E-01  -1.3294639818356677E+00\natom   1.2764696627999999E+01   1.5378200000000000E-01   1.0125363628000001E+01  O  -2.2955663167309948E-01   0.0000000000000000E+00  -1.6237528514361890E+00  -1.7798214425490955E+00  -1.0320891233855798E+00\natom   1.1249884628000000E+01   1.2710340000000000E+00   9.9575596280000003E+00  H   1.3433991100513273E-01   0.0000000000000000E+00   5.0306812661490385E-01   6.4606072642904910E-02   1.2035900324044681E-01\natom   8.4522900000000001E-01   1.2098420000000001E+00   1.0488610628000000E+01  H   1.3761295680984548E-01   0.0000000000000000E+00   2.3015420911979811E+00   1.6439986297320848E+00   8.3471087553758916E-01\natom   8.8003156279999999E+00   8.1706076280000008E+00   6.1612819999999999E+00  O  -2.3412971681479525E-01   0.0000000000000000E+00   4.7823813809165792E+00   4.5453029913715861E+00  -3.2129178691353069E+00\natom   7.4882556279999992E+00   6.9694036280000002E+00   6.7989826280000001E+00  H   1.1415705913922836E-01   0.0000000000000000E+00  -5.1160186352989925E+00  -5.4134409660054734E+00   1.5484060579498757E+00\natom   8.7161336279999979E+00   9.7785886279999996E+00   7.1504036279999994E+00  H   1.1034962117814637E-01   0.0000000000000000E+00   1.2454296150285611E+00  -3.2682486247550602E-01  -2.3874749634340637E+00\natom   3.1354829999999998E+00   3.7303289999999998E+00   4.8504040000000002E+00  O  -2.2006091505768430E-01   0.0000000000000000E+00  -1.2832754207323978E+00  -1.4767181813664836E+00  -1.6544059920266059E+00\natom   2.5813579999999998E+00   2.1819250000000001E+00   3.9195639999999994E+00  H   1.3641844939732595E-01   0.0000000000000000E+00  -1.8176714669371274E+00  -3.7272692203761654E-01  -2.5341845334408836E-01\natom   4.8735999999999997E+00   4.2146619999999997E+00   4.2887670000000000E+00  H   1.1534057032122745E-01   0.0000000000000000E+00   2.8905795806354817E+00   1.2490296651432349E+00   4.4489626141762684E-01\natom   1.2696753628000000E+01   9.5005796279999988E+00   1.3316218628000000E+01  O  -2.0590918634609703E-01   0.0000000000000000E+00   3.6313703894020638E-01  -2.9210646513595001E-01   7.7685508623495614E-01\natom   1.2096099628000001E+01   8.3233416279999997E+00   1.2230289999999999E+00  H   1.0721155781927215E-01   0.0000000000000000E+00   2.1821057837216054E+00  -8.1494640847712330E-01   1.1342821157055141E-02\natom   1.1423969628000000E+01   1.0874955628000000E+01   1.3066854628000000E+01  H   1.1823488614823414E-01   0.0000000000000000E+00   4.8731746833591910E-01   4.0378869734607514E+00  -3.3331890572564116E-01\nenergy  -9.1689613647168449E+02\ncharge   1.2212453270876722E-15\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/input.nn",
    "content": "## #############################################################\n### This is the input file for RuNNer \n### #############################################################\n### General remarks: \n### - commands can be switched off by using the # character at the BEGINNING of the line\n### - the input file can be structured by blank lines and comment lines\n### - the order of the keywords is arbitrary\n### - if keywords are missing, default values will be used and written to runner.out\n### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message \n\n### THIS INPUT.NN IS AN EXAMPLE, IT IS NOT A REALISTIC CASE\n### It contains only a subset of all keywords\n\n########################################################################################################################\n### general keywords\n########################################################################################################################\nuse_electrostatics\nuse_short_nn\nnnp_gen 4 # nnp_type_gen --> nnp_gen \nrunner_mode 3\nparallel_mode 1                         \nnumber_of_elements 2                  \nelements  H O                          \nrandom_seed 10                         \nrandom_number_type 5                      \nremove_atom_energies                     \natom_energy H -0.458907306351869\natom_energy O -74.94518524\ninitial_hardness H 10.0 ## fixed_atomhardness--> initial_hardness \ninitial_hardness O 10.0 \nfixed_gausswidth H 0.585815056466\nfixed_gausswidth O 1.379499971678\nenergy_threshold 100.0d0              \nbond_threshold 0.4d0                 \newald_prec 1.0e-4 # for optimal combination of ewald parameters\nscreen_electrostatics 4.8 8.0\n########################################################################################################################\n### NN structure of the electrostatic-range NN  \n########################################################################################################################\nglobal_hidden_layers_electrostatic 2              \nglobal_nodes_electrostatic 15 15                 \nglobal_activation_electrostatic t t l            \nglobal_hidden_layers_short 2              \nglobal_nodes_short 15 15                 \nglobal_activation_short t t l            \n## element_hidden_layers_electrostatic needs to take care !!! should check the output  \n########################################################################################################################\n### symmetry function generation ( mode 1): \n########################################################################################################################\ntest_fraction 0.1      \n\n########################################################################################################################\n### symmetry function definitions (all modes): \n########################################################################################################################\ncutoff_type 2\n\n\n# radial H H\nsymfunction H 2 H 0.001 0.0 8.00\nsymfunction H 2 H 0.01  0.0 8.00\nsymfunction H 2 H 0.03  0.0 8.00\nsymfunction H 2 H 0.06  0.0 8.00\nsymfunction H 2 H 0.15  1.9 8.00\nsymfunction H 2 H 0.30  1.9 8.00\nsymfunction H 2 H 0.60  1.9 8.00\nsymfunction H 2 H 1.50  1.9 8.00\n\n# radial H O / O H\nsymfunction H 2 O 0.001 0.0 8.00\nsymfunction H 2 O 0.01  0.0 8.00\nsymfunction H 2 O 0.03  0.0 8.00\nsymfunction H 2 O 0.06  0.0 8.00\nsymfunction H 2 O 0.15  0.9 8.00\nsymfunction H 2 O 0.30  0.9 8.00\nsymfunction H 2 O 0.60  0.9 8.00\nsymfunction H 2 O 1.50  0.9 8.00\n\nsymfunction O 2 H 0.001 0.0 8.00\nsymfunction O 2 H 0.01  0.0 8.00\nsymfunction O 2 H 0.03  0.0 8.00\nsymfunction O 2 H 0.06  0.0 8.00\nsymfunction O 2 H 0.15  0.9 8.00\nsymfunction O 2 H 0.30  0.9 8.00\nsymfunction O 2 H 0.60  0.9 8.00\nsymfunction O 2 H 1.50  0.9 8.00\n\n# radial O O\nsymfunction O 2 O 0.001 0.0 8.00\nsymfunction O 2 O 0.01  0.0 8.00\nsymfunction O 2 O 0.03  0.0 8.00\nsymfunction O 2 O 0.06  0.0 8.00\nsymfunction O 2 O 0.15  4.0 8.00\nsymfunction O 2 O 0.30  4.0 8.00\nsymfunction O 2 O 0.60  4.0 8.00\nsymfunction O 2 O 1.50  4.0 8.00\n\n# angular\nsymfunction H 3 O H 0.2  1.0 1.0  8.00000\n\nsymfunction O 3 H H 0.07  1.0 1.0  8.00000\nsymfunction H 3 O H 0.07  1.0 1.0  8.00000\nsymfunction O 3 H H 0.07 -1.0 1.0  8.00000\nsymfunction H 3 O H 0.07 -1.0 1.0  8.00000\n\nsymfunction O 3 H H 0.03  1.0 1.0  8.00000\nsymfunction H 3 O H 0.03  1.0 1.0  8.00000\nsymfunction O 3 H H 0.03 -1.0 1.0  8.00000\nsymfunction H 3 O H 0.03 -1.0 1.0  8.00000\n\nsymfunction O 3 H H 0.01  1.0 4.0  8.00000\nsymfunction H 3 O H 0.01  1.0 4.0  8.00000\nsymfunction O 3 H H 0.01 -1.0 4.0  8.00000\nsymfunction H 3 O H 0.01 -1.0 4.0  8.00000\n\nsymfunction O 3 O H 0.03  1.0 1.0   8.00000\nsymfunction O 3 O H 0.03 -1.0 1.0   8.00000\nsymfunction O 3 O H 0.001  1.0 4.0  8.00000\nsymfunction O 3 O H 0.001 -1.0 4.0  8.00000\n\nsymfunction H 3 O O 0.03  1.0 1.0   8.00000\nsymfunction H 3 O O 0.03 -1.0 1.0   8.00000\nsymfunction H 3 O O 0.001  1.0 4.0  8.00000\nsymfunction H 3 O O 0.001 -1.0 4.0  8.00000\n\n#symfunction O 3 O O 0.03  1.0 1.0   8.00000\n#symfunction O 3 O O 0.03 -1.0 1.0   8.00000\n#symfunction O 3 O O 0.001  1.0 4.0  8.00000\n#symfunction O 3 O O 0.001 -1.0 4.0  8.00000\n\n########################################################################################################################\n### fitting (mode 2):general inputs for electrostatic range AND electrostatic part:\n########################################################################################################################\nepochs 30                        \npoints_in_memory 500                \nmix_all_points                       \nscale_symmetry_functions             \ncenter_symmetry_functions             \nfitting_unit  eV                      \n########################################################################################################################\n### fitting options ( mode 2): electrostatic range part only:\n########################################################################################################################\noptmode_short_energy 1                 \noptmode_short_force 1                   \nshort_energy_error_threshold 0.8\t \nshort_force_error_threshold 0.8\t\t \nkalman_lambda_charge 0.98000                \nkalman_nue_charge 0.99870                   \nkalman_lambda_short 0.98000                \nkalman_nue_short 0.99870                   \n#use_old_weights_electrostatic               \n#force_update_scaling -1.0d0          \n#electrostatic_energy_group 1         \n#electrostatic_energy_fraction 1.00           \n#electrostatic_force_group 1                 \n\n#short_force_fraction 0.025            \n#use_short_forces                    \nweights_min -1.0                 \nweights_max 1.0                  \n#precondition_weights            \n#repeated_energy_update          \n#nguyen_widrow_weights_short     \nregularize_fit_param 0.00001 ## 4G cases L2 regularization \n########################################################################################################################\n### output options for mode 2 (fitting):  \n########################################################################################################################\n#write_trainpoints              \n#write_trainforces      \nwrite_traincharges\n########################################################################################################################\n### output options for mode 3 (prediction):  \n########################################################################################################################\ncalculate_forces     \n#calculate_stress       \n\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/other-input-data/input.data-1np",
    "content": "begin\ncomment 7.1142\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\nlattice 50.0\t0.00\t0.00\nlattice 0.00    50.0    0.00\nlattice 0.00    0.00\t50.0\natom     1.028157    -6.568274    -4.947316  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.044122    -6.720650    -3.361233  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.047996    -5.677478    -6.265449  H      0.000000     0.000000    99.999999    99.999999    99.999999\nenergy  99.999999\ncharge  0.0\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/other-input-data/input.data-1p",
    "content": "begin\ncomment 7.1142\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\ncomment lattice 13.443888628\t0.0000000000\t0.0000000000\ncomment lattice 0.0000000000    13.443888628    0.0000000000\ncomment lattice 0.0000000000    0.0000000000\t13.443888628\natom     1.028157    -6.568274    -4.947316  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.044122    -6.720650    -3.361233  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.047996    -5.677478    -6.265449  H      0.000000     0.000000    99.999999    99.999999    99.999999\nenergy  99.999999\ncharge  0.0\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/other-input-data/input.data-36-angs",
    "content": "begin\natom  0.544077    -3.475781    -2.618007 O  0.0 0.0 0.0 0.0 0.0\natom  1.081703    -3.556415    -1.778688 H  0.0 0.0 0.0 0.0 0.0\natom  1.083753    -3.004392    -3.315533 H  0.0 0.0 0.0 0.0 0.0\natom -1.191307     2.646627     1.223969 O  0.0 0.0 0.0 0.0 0.0\natom -1.724920     2.459640     0.399170 H  0.0 0.0 0.0 0.0 0.0\natom -0.719194     3.522487     1.124081 H  0.0 0.0 0.0 0.0 0.0\natom -2.931925     1.598787    -3.456225 O  0.0 0.0 0.0 0.0 0.0\natom -2.428998     1.041042     2.997688 H  0.0 0.0 0.0 0.0 0.0\natom -3.038337     1.089462    -2.602255 H  0.0 0.0 0.0 0.0 0.0\natom -2.947261    -1.617169    -1.266127 O  0.0 0.0 0.0 0.0 0.0\natom -2.241175    -2.258399    -0.965683 H  0.0 0.0 0.0 0.0 0.0\natom -2.823269    -1.416117    -2.237829 H  0.0 0.0 0.0 0.0 0.0\natom  2.058883    -2.737490     0.983363 O  0.0 0.0 0.0 0.0 0.0\natom  1.934859    -3.121965     0.068597 H  0.0 0.0 0.0 0.0 0.0\natom  2.139471    -3.479642     1.648732 H  0.0 0.0 0.0 0.0 0.0\natom  2.533993    -0.743316     3.466309 O  0.0 0.0 0.0 0.0 0.0\natom  2.483157     0.058869     2.871402 H  0.0 0.0 0.0 0.0 0.0\natom  2.962327    -0.488699    -2.780889 H  0.0 0.0 0.0 0.0 0.0\natom  2.592498     1.794439    -0.178947 O  0.0 0.0 0.0 0.0 0.0\natom  2.122268     1.276868    -0.893792 H  0.0 0.0 0.0 0.0 0.0\natom  1.918028     2.261622     0.392743 H  0.0 0.0 0.0 0.0 0.0\natom -1.135168    -0.397887     2.351273 O  0.0 0.0 0.0 0.0 0.0\natom -1.102596    -0.145078     3.318241 H  0.0 0.0 0.0 0.0 0.0\natom -0.237429    -0.731470     2.063547 H  0.0 0.0 0.0 0.0 0.0\natom -0.359413     0.081378    -1.756088 O  0.0 0.0 0.0 0.0 0.0\natom -1.161017     0.672602    -1.844886 H  0.0 0.0 0.0 0.0 0.0\natom  0.447276     0.640221    -1.563866 H  0.0 0.0 0.0 0.0 0.0\natom -2.457273    -2.790500     3.260410 O  0.0 0.0 0.0 0.0 0.0\natom -3.151585    -3.426150    -3.516333 H  0.0 0.0 0.0 0.0 0.0\natom -2.501820    -1.939593    -3.330369 H  0.0 0.0 0.0 0.0 0.0\natom  1.659226     1.974005     2.566723 O  0.0 0.0 0.0 0.0 0.0\natom  1.365996     1.154625     2.074144 H  0.0 0.0 0.0 0.0 0.0\natom  2.578998     2.230303     2.269518 H  0.0 0.0 0.0 0.0 0.0\natom -0.395367    -2.086709    -0.067560 O  0.0 0.0 0.0 0.0 0.0\natom -0.713219    -2.709677     0.647199 H  0.0 0.0 0.0 0.0 0.0\natom -1.068895    -1.359421    -0.199518 H  0.0 0.0 0.0 0.0 0.0\nenergy 0.0\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/other-input-data/input.data-36p",
    "content": "begin\ncomment 7.1142\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\nlattice 13.443888628\t0.0000000000\t0.0000000000\nlattice 0.0000000000    13.443888628    0.0000000000\nlattice 0.0000000000    0.0000000000\t13.443888628\natom     1.028157    -6.568274    -4.947316  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.044122    -6.720650    -3.361233  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.047996    -5.677478    -6.265449  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.251244     5.001400     2.312966  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -3.259626     4.648046     0.754322  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -1.359080     6.656536     2.124205  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.540535     3.021270    -6.531319  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.590141     1.967284     5.664809  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.741625     2.058785    -4.917549  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.569516    -3.056007    -2.392633  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.235207    -4.267756    -1.824876  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.335205    -2.676073    -4.228884  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.890725    -5.173106     1.858287  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.656354    -5.899659     0.129630  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.043014    -6.575570     3.115652  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.788553    -1.404664     6.550375  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.692487     0.111246     5.426163  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     5.597987    -0.923507    -5.255119  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.899111     3.390998    -0.338161  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.010505     2.412931    -1.689022  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.624548     4.273846     0.742177  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.145157    -0.751897     4.443262  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.083604    -0.274158     6.270567  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -0.448676    -1.382278     3.899539  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -0.679192     0.153782    -3.318525  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.194004     1.271034    -3.486329  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     0.845229     1.209842    -2.955278  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.643573    -5.273281     6.161282  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.955633    -6.474485    -6.644906  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.727755    -3.665300    -6.293485  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.135483     3.730329     4.850404  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.581358     2.181925     3.919564  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.873600     4.214662     4.288767  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -0.747135    -3.943309    -0.127670  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -1.347789    -5.120547     1.223029  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.019919    -2.568933    -0.377034  H      0.000000     0.000000    99.999999    99.999999    99.999999\nenergy  99.999999\ncharge  0.0\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/other-input-data/input.data-36s",
    "content": "begin\ncomment 7.1142\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\ncomment lattice 13.443888628\t0.0000000000\t0.0000000000\ncomment lattice 0.0000000000    13.443888628    0.0000000000\ncomment lattice 0.0000000000    0.0000000000\t13.443888628\natom     1.028157    -6.568274    -4.947316  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.044122    -6.720650    -3.361233  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.047996    -5.677478    -6.265449  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.251244     5.001400     2.312966  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -3.259626     4.648046     0.754322  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -1.359080     6.656536     2.124205  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.540535     3.021270    -6.531319  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.590141     1.967284     5.664809  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.741625     2.058785    -4.917549  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.569516    -3.056007    -2.392633  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.235207    -4.267756    -1.824876  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.335205    -2.676073    -4.228884  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.890725    -5.173106     1.858287  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.656354    -5.899659     0.129630  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.043014    -6.575570     3.115652  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.788553    -1.404664     6.550375  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.692487     0.111246     5.426163  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     5.597987    -0.923507    -5.255119  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.899111     3.390998    -0.338161  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.010505     2.412931    -1.689022  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.624548     4.273846     0.742177  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.145157    -0.751897     4.443262  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.083604    -0.274158     6.270567  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -0.448676    -1.382278     3.899539  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -0.679192     0.153782    -3.318525  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.194004     1.271034    -3.486329  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     0.845229     1.209842    -2.955278  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.643573    -5.273281     6.161282  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.955633    -6.474485    -6.644906  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.727755    -3.665300    -6.293485  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.135483     3.730329     4.850404  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.581358     2.181925     3.919564  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.873600     4.214662     4.288767  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -0.747135    -3.943309    -0.127670  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -1.347789    -5.120547     1.223029  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.019919    -2.568933    -0.377034  H      0.000000     0.000000    99.999999    99.999999    99.999999\nenergy  99.999999\ncharge  0.0\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/other-input-data/input.data-angs-p",
    "content": "begin\nlattice 7.1142 0.0000 0.0000\nlattice 0.0000 7.1142 0.0000\nlattice 0.0000 0.0000 7.1142\natom  0.544077    -3.475781    -2.618007 O  0.0 0.0 0.0 0.0 0.0\natom  1.081703    -3.556415    -1.778688 H  0.0 0.0 0.0 0.0 0.0\natom  1.083753    -3.004392    -3.315533 H  0.0 0.0 0.0 0.0 0.0\natom -1.191307     2.646627     1.223969 O  0.0 0.0 0.0 0.0 0.0\natom -1.724920     2.459640     0.399170 H  0.0 0.0 0.0 0.0 0.0\natom -0.719194     3.522487     1.124081 H  0.0 0.0 0.0 0.0 0.0\natom -2.931925     1.598787    -3.456225 O  0.0 0.0 0.0 0.0 0.0\natom -2.428998     1.041042     2.997688 H  0.0 0.0 0.0 0.0 0.0\natom -3.038337     1.089462    -2.602255 H  0.0 0.0 0.0 0.0 0.0\natom -2.947261    -1.617169    -1.266127 O  0.0 0.0 0.0 0.0 0.0\natom -2.241175    -2.258399    -0.965683 H  0.0 0.0 0.0 0.0 0.0\natom -2.823269    -1.416117    -2.237829 H  0.0 0.0 0.0 0.0 0.0\natom  2.058883    -2.737490     0.983363 O  0.0 0.0 0.0 0.0 0.0\natom  1.934859    -3.121965     0.068597 H  0.0 0.0 0.0 0.0 0.0\natom  2.139471    -3.479642     1.648732 H  0.0 0.0 0.0 0.0 0.0\natom  2.533993    -0.743316     3.466309 O  0.0 0.0 0.0 0.0 0.0\natom  2.483157     0.058869     2.871402 H  0.0 0.0 0.0 0.0 0.0\natom  2.962327    -0.488699    -2.780889 H  0.0 0.0 0.0 0.0 0.0\natom  2.592498     1.794439    -0.178947 O  0.0 0.0 0.0 0.0 0.0\natom  2.122268     1.276868    -0.893792 H  0.0 0.0 0.0 0.0 0.0\natom  1.918028     2.261622     0.392743 H  0.0 0.0 0.0 0.0 0.0\natom -1.135168    -0.397887     2.351273 O  0.0 0.0 0.0 0.0 0.0\natom -1.102596    -0.145078     3.318241 H  0.0 0.0 0.0 0.0 0.0\natom -0.237429    -0.731470     2.063547 H  0.0 0.0 0.0 0.0 0.0\natom -0.359413     0.081378    -1.756088 O  0.0 0.0 0.0 0.0 0.0\natom -1.161017     0.672602    -1.844886 H  0.0 0.0 0.0 0.0 0.0\natom  0.447276     0.640221    -1.563866 H  0.0 0.0 0.0 0.0 0.0\natom -2.457273    -2.790500     3.260410 O  0.0 0.0 0.0 0.0 0.0\natom -3.151585    -3.426150    -3.516333 H  0.0 0.0 0.0 0.0 0.0\natom -2.501820    -1.939593    -3.330369 H  0.0 0.0 0.0 0.0 0.0\natom  1.659226     1.974005     2.566723 O  0.0 0.0 0.0 0.0 0.0\natom  1.365996     1.154625     2.074144 H  0.0 0.0 0.0 0.0 0.0\natom  2.578998     2.230303     2.269518 H  0.0 0.0 0.0 0.0 0.0\natom -0.395367    -2.086709    -0.067560 O  0.0 0.0 0.0 0.0 0.0\natom -0.713219    -2.709677     0.647199 H  0.0 0.0 0.0 0.0 0.0\natom -1.068895    -1.359421    -0.199518 H  0.0 0.0 0.0 0.0 0.0\nenergy 0.0\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/other-input-data/input.data-h2o-192-neg",
    "content": "begin\ncomment 12.4297\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\nlattice 23.48872712 0.0 0.0\nlattice 0.0 23.48872712 0.0\nlattice 0.0 0.0 23.48872712\natom    -3.183809   -11.452264     0.195318  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -3.788472    10.286042     0.571793  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.479479   -10.677223     1.768307  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.445773    -1.059129    -0.037139  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -6.128503    -2.716651    -0.635103  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.099224    -0.467594    -1.223713  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.025986     2.073946    10.249672  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.116721     0.771777     9.421592  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.175044     3.708470     9.313096  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.056326    -5.609854    -5.358509  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -0.940573    -6.724959    -4.317981  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -3.801885    -5.613492    -4.634578  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -8.875437     3.400940    -7.729698  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -9.953917     2.832408    -6.285843  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -7.210978     2.508708    -7.662140  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -7.776172     8.995293    -6.773791  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -8.718573     9.732388    -8.236539  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.918902     9.087778    -7.110034  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.639603   -10.269605    -7.132047  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.599291    -9.522893    -8.578589  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.837526    -9.706724    -7.214201  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     6.243498   -11.653918     9.214649  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     5.117388   -11.149371    10.645863  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     7.662994    10.775381     9.873335  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    11.668059     8.465043     6.405365  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   -10.199383     9.389410     6.702484  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    10.493207     9.558535     5.407833  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.645621    10.957140     5.424612  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -3.374416    10.787292     4.036718  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -6.138159   -11.557729     4.796010  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -8.545869     5.111690     2.510501  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -8.577304     3.766625     1.183522  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -7.534461     4.513084     3.990295  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.535786    -4.675046     5.527337  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.973174    -5.424211     6.498796  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.684494    -2.791195     5.534836  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     8.243702     2.794338     2.976349  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     8.314411     1.226716     4.029259  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     6.461673     3.417715     2.893666  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     7.928399    10.932213    -3.313518  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     8.502775     9.671626    -4.598849  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     7.523028    10.042727    -1.696250  H      0.000000     0.000000    99.999999    99.999999    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  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/other-input-data/input.data-h2o-36-neg",
    "content": "begin\ncomment 7.1142\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\nlattice 13.443888628\t0.0000000000\t0.0000000000\nlattice 0.0000000000    13.443888628    0.0000000000\nlattice 0.0000000000    0.0000000000\t13.443888628\natom     1.028157    -6.568274    -4.947316  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.044122    -6.720650    -3.361233  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.047996    -5.677478    -6.265449  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.251244     5.001400     2.312966  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -3.259626     4.648046     0.754322  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -1.359080     6.656536     2.124205  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.540535     3.021270    -6.531319  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.590141     1.967284     5.664809  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.741625     2.058785    -4.917549  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.569516    -3.056007    -2.392633  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.235207    -4.267756    -1.824876  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.335205    -2.676073    -4.228884  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.890725    -5.173106     1.858287  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.656354    -5.899659     0.129630  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.043014    -6.575570     3.115652  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.788553    -1.404664     6.550375  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.692487     0.111246     5.426163  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     5.597987    -0.923507    -5.255119  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.899111     3.390998    -0.338161  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.010505     2.412931    -1.689022  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.624548     4.273846     0.742177  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.145157    -0.751897     4.443262  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.083604    -0.274158     6.270567  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -0.448676    -1.382278     3.899539  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -0.679192     0.153782    -3.318525  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.194004     1.271034    -3.486329  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     0.845229     1.209842    -2.955278  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.643573    -5.273281     6.161282  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -5.955633    -6.474485    -6.644906  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -4.727755    -3.665300    -6.293485  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     3.135483     3.730329     4.850404  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom     2.581358     2.181925     3.919564  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom     4.873600     4.214662     4.288767  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -0.747135    -3.943309    -0.127670  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -1.347789    -5.120547     1.223029  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom    -2.019919    -2.568933    -0.377034  H      0.000000     0.000000    99.999999    99.999999    99.999999\nenergy  99.999999\ncharge  0.0\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/other-input-data/input.data-h2o-768-neg",
    "content": "begin\ncomment 19.7309\ncomment Values for ['energy', 'charge', 'force of atom'] were set to default values\nlattice 3.72859974E+01   0.00000000E+00   0.00000000E+00\nlattice 0.00000000E+00   3.72859974E+01   0.00000000E+00\nlattice 0.00000000E+00   0.00000000E+00   3.72859974E+01\natom   1.53938829E+01   1.54500532E+01   1.79583377E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.64321382E+01   1.39497977E+01   1.84505962E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.40701260E+01   1.49203894E+01   1.67181010E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.22632077E+00  -4.42312511E+00  -1.32033294E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -2.38315252E+00  -5.89155192E+00  -1.34799683E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   9.01645030E-02  -4.88948873E+00  -1.19303645E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   2.75489378E+00   1.80380482E+01   2.34471171E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   3.30761789E+00   1.79959470E+01   4.15130690E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   3.24890221E+00   1.64229522E+01   1.49707695E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   5.76548640E+00   1.31657522E+01   1.72147418E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   5.89489107E+00   1.46851903E+01   1.83308197E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   6.52537551E+00   1.16739211E+01   1.80911420E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.02265270E+01   1.55838004E+01   2.34035212E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   9.52879285E+00   1.67043305E+01   9.88079213E-01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   8.97402784E+00   1.42271698E+01   2.74267292E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -5.90439261E-01   8.60844142E+00  -9.01081513E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.05057057E+00   8.07631344E+00  -8.23945727E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -2.58745082E-01   9.81292829E+00  -1.04286483E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -5.19078100E+00   2.96370852E+00  -8.34428605E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -3.57978569E+00   3.95121136E+00  -8.36876556E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -5.10738361E+00   1.59020076E+00  -9.63950245E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.47978142E+01  -1.67523220E+01  -1.56200227E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.47954142E+01  -1.81384966E+01  -2.77644233E-01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.64241087E+01  -1.57960337E+01  -1.45361892E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.10724837E+01  -6.59508751E-01   6.82885797E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.11564348E+01  -2.49576319E+00   6.39046608E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.18007898E+01   3.59777400E-01   5.41404458E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   4.09210745E-01   5.75161392E+00   1.48050556E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   2.00835180E+00   4.85048101E+00   1.43558696E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -5.97444476E-01   6.06756857E+00   1.32372916E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.38275022E+01   4.02985232E+00  -1.40950761E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.56255369E+01   4.60899857E+00  -1.41473175E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.30548366E+01   4.52253415E+00  -1.24424066E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -8.48311100E+00   1.84011251E+01  -1.01638863E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -7.39987652E+00   1.69606114E+01  -1.07318511E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -7.40007683E+00  -1.75607185E+01  -9.36080375E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -3.02732237E+00  -1.71140288E+01   1.13119460E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -2.00919084E+00  -1.56313157E+01   1.07322574E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -2.10677063E+00  -1.80060627E+01   1.27004412E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.06561902E+01   5.65434972E+00   6.70337827E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -9.53148382E+00   5.59056012E+00   5.18613227E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.13814274E+01   3.93874106E+00   7.02240561E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.04359748E+00  -8.14057357E+00   1.23120382E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.07474583E+00  -9.95799689E+00   7.14418523E-01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -2.49855243E+00  -7.78867822E+00   2.38460761E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -7.69255163E+00  -3.57553003E+00   1.57600023E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -8.32734466E+00  -5.11805489E+00   1.66481017E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -6.83550414E+00  -2.44029973E+00   1.70041016E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   6.92621288E+00  -1.38730786E+01  -1.31138433E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   8.14368595E+00  -1.52138676E+01  -1.25742963E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   7.05732586E+00  -1.36179032E+01  -1.49816656E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   4.48746462E+00  -1.29437906E+01  -5.54675816E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   6.01020594E+00  -1.40286711E+01  -5.82127490E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   3.33882860E+00  -1.30807448E+01  -7.04106099E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -8.60290074E+00  -1.22110758E+01  -1.15599574E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -6.92453481E+00  -1.18753773E+01  -1.23608706E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -8.41924960E+00  -1.35681221E+01  -1.02577434E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -4.00884612E+00  -3.20082757E+00   4.56321240E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -3.85063069E+00  -5.07381451E+00   4.36839297E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -2.66861266E+00  -2.34584177E+00   3.54153008E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   3.75810592E+00  -1.76807445E+01   1.61965063E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   2.32624153E+00  -1.65593942E+01   1.67097370E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   3.13477220E+00   1.78303597E+01   1.60160242E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -6.44264141E+00   1.21632525E+01  -8.79160501E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -5.69199684E+00   1.12613637E+01  -7.31032429E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -5.71865521E+00   1.39053400E+01  -8.90135653E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.20933685E+01   1.06599432E+01  -1.45453468E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.11567484E+01   9.06899413E+00  -1.49486937E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.29518919E+01   1.12976634E+01  -1.61033315E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.37086989E+01  -6.23739259E+00  -6.15108124E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.47438833E+01  -4.65849050E+00  -6.23188404E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.22998551E+01  -6.00423062E+00  -4.91339944E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.27432926E+00  -5.64886195E+00   1.12744293E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   2.38144421E+00  -4.24829899E+00   1.18939306E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.73786774E-01  -5.01068443E+00   9.87707315E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.81980135E+01   9.20620715E+00   1.32091044E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.81336306E+01   9.50945906E+00   1.50732266E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.65877212E+01   8.39227376E+00   1.26473739E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.66580663E+01   9.08928412E+00  -1.32507691E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.79332516E+01   9.49384236E+00  -1.45854222E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.64215160E+01   1.05918885E+01  -1.21294812E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.55652887E+01   5.41082638E+00   1.76864023E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.56118817E+01   3.92760679E+00  -1.84294880E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.47026098E+01   6.85944697E+00   1.85398347E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -4.61641953E+00  -1.48919225E+01  -4.84819255E+00  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O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   7.11769505E+00   1.71676763E+01  -3.79005363E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   5.48911395E+00   1.70544873E+01  -1.17135052E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.57360613E+01   1.69171080E+01  -1.14719548E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.43892478E+01   1.81264647E+01  -1.20147389E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.52723074E+01   1.51696348E+01  -1.20218027E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.33303492E+01  -1.31732884E+01   1.45817996E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.18594526E+01  -1.43494464E+01   1.47372881E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.45595046E+01  -1.38647392E+01   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1.13170426E+01   1.05018601E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.71793661E+01   1.14543633E+01   7.70020880E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   8.20733760E+00   1.46349954E+01   1.26394994E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   6.81983075E+00   1.33802323E+01   1.23721825E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   7.60684499E+00   1.60004680E+01   1.37996533E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -5.77186612E+00   5.23108130E+00  -1.31159598E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -5.95766777E+00   6.39173030E+00  -1.45956343E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -7.19018306E+00   5.52561023E+00  -1.19024136E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  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99.999999\natom  -1.11270344E+01   1.58759899E+01  -1.01108606E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.70887556E+01   4.92492299E+00   9.93842500E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.60031193E+01   6.45964517E+00   1.01309994E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.83905672E+01   5.23757440E+00   8.60478291E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.46771041E+01  -1.74730428E+01  -6.52529048E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.42355696E+01   1.80415234E+01  -6.03698713E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.34984385E+01  -1.62707366E+01  -5.66722442E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.39353054E+01   4.46249378E-01   1.59040145E+01  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.49418226E+01   1.22979786E+00   1.72983036E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom  -1.50874563E+01  -1.97022847E-02   1.44804611E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.56761343E+01  -5.27045185E+00  -8.85312316E+00  O      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.75416833E+01  -5.52403042E+00  -8.69036294E+00  H      0.000000     0.000000    99.999999    99.999999    99.999999\natom   1.53153667E+01  -4.20548913E+00  -1.03719263E+01  H      0.000000     0.000000    99.999999    99.999999    99.999999\nenergy  99.999999\ncharge  0.0\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/nnp-predict/scaling.data",
    "content": "   1    1        0.332976205       0.801624245       0.529022897\n   1    2        0.302337347       0.559557103       0.444982986\n   1    3        0.279156661       0.689216779       0.447398011\n   1    4        0.281666680       0.500530512       0.405813837\n   1    5        0.184597589       0.500915675       0.315606906\n   1    6        0.246938750       0.411905369       0.340350304\n   1    7        0.108144137       0.321581311       0.196758358\n   1    8        0.206524003       0.332910999       0.275222988\n   1    9        0.192266492       0.337437016       0.268862686\n   1   10        0.137888800       0.438702601       0.258407517\n   1   11        0.123155815       0.264414914       0.211036382\n   1   12        0.079044824       0.323909809       0.164714948\n   1   13        0.060252990       0.223808509       0.148947959\n   1   14        0.027902463       0.204282365       0.091898588\n   1   15        0.008301924       0.147213416       0.061276132\n   1   16        0.002347157       0.105178649       0.028579526\n   1   17        0.000003005       0.005579422       0.001547947\n   1   18        0.000019930       0.000524387       0.000216322\n   1   19        0.000014927       0.003701946       0.000686603\n   1   20        0.014211691       0.033835238       0.022236736\n   1   21        0.000923120       0.006114561       0.002645102\n   1   22        0.000007167       0.002120404       0.000529206\n   1   23        0.011944886       0.029242703       0.018758239\n   1   24        0.000007559       0.000378023       0.000104479\n   1   25        0.000324117       0.002415409       0.001014563\n   1   26        0.004378590       0.013887358       0.008122121\n   1   27        0.000247127       0.002444197       0.000854440\n   2    1        0.693621490       1.096065781       0.889965972\n   2    2        0.054518807       0.204722516       0.128280243\n   2    3        0.640580762       0.993246230       0.811627675\n   2    4        0.038923431       0.158395358       0.097711184\n   2    5        0.551807090       0.820610595       0.680700608\n   2    6        0.018487600       0.093003263       0.053784777\n   2    7        0.456675414       0.666767988       0.550445975\n   2    8        0.006106326       0.042261243       0.022350937\n   2    9        0.436638353       0.665201432       0.537725373\n   2   10        0.029120590       0.167003997       0.094121049\n   2   11        0.321348553       0.514230878       0.422072764\n   2   12        0.015448674       0.137320836       0.069828762\n   2   13        0.196593790       0.408515108       0.297895918\n   2   14        0.004538808       0.100407427       0.041347516\n   2   15        0.049968528       0.246264120       0.122552265\n   2   16        0.000129041       0.042031039       0.011393965\n   2   17        0.000009812       0.000447566       0.000169694\n   2   18        0.001933554       0.017758036       0.008603827\n   2   19        0.002325650       0.010442752       0.005875043\n   2   20        0.000956077       0.010566084       0.003169792\n   2   21        0.007035328       0.022388524       0.012854532\n   2   22        0.000018894       0.000470842       0.000153842\n   2   23        0.004523457       0.015610385       0.008548809\n   2   24        0.000379375       0.005673761       0.002380896\n   2   25        0.002690099       0.009402971       0.005666492\n   2   26        0.001503235       0.006697403       0.003470192\n       -0.2343807221       -0.2306674948\n"
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0.9562597424\n     -0.1492012448\n     -0.1082100677\n     -0.3810973294\n     -0.3577272526\n      0.0341348973\n      0.5814419788\n     -0.2362748063\n      0.2740130803\n      0.2005358826\n     -0.1874268796\n      0.7040305804\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/water.data",
    "content": "Generated by RuNNerUC, original comment lines: 7.1142\n\n36 atoms\n2 atom types\n\n0.0 7.1141994570823028E+00 xlo xhi\n0.0 7.1141994570823028E+00 ylo yhi\n0.0 7.1141994570823028E+00 zlo zhi\n\nMasses\n\n1 1.0079\n2 15.9994\n\nAtoms\n\n    1  2 0.0  5.4407725127692641E-01   3.6384185563505054E+00   4.4961925860710092E+00\n    2  1 0.0  1.0817027740264313E+00   3.5577846500107415E+00   5.3355115606411010E+00\n    3  1 0.0  1.0837528065326016E+00   4.1098074970750078E+00   3.7986666445490349E+00\n    4  2 0.0  5.9228924412533273E+00   2.6466268911619726E+00   1.2239688914990485E+00\n    5  1 0.0  5.3892796692767426E+00   2.4596400077893872E+00   3.9917001035611654E-01\n    6  1 0.0  6.3950052963992130E+00   3.5224871395184847E+00   1.1240808724238647E+00\n    7  2 0.0  4.1822746115542317E+00   1.5987872250691670E+00   3.6579743000948359E+00\n    8  1 0.0  4.6852014555577082E+00   1.0410418556709500E+00   2.9976878139513659E+00\n    9  1 0.0  4.0758623666740457E+00   1.0894620994363380E+00   4.5119446040398223E+00\n   10  2 0.0  4.1669385268713892E+00   5.4970302033175118E+00   5.8480726049046048E+00\n   11  1 0.0  4.8730244389199040E+00   4.8558002499567277E+00   6.1485166693356534E+00\n   12  1 0.0  4.2909305677989407E+00   5.6980826168950580E+00   4.8763704264099701E+00\n   13  2 0.0  2.0588829949846374E+00   4.3767096641380583E+00   9.8336312746365173E-01\n   14  1 0.0  1.9348592034245695E+00   3.9922343756879437E+00   6.8597241552630556E-02\n   15  1 0.0  2.1394708629072521E+00   3.6345576794364582E+00   1.6487320283725717E+00\n   16  2 0.0  2.5339931098401118E+00   6.3708832825217518E+00   3.4663091578748157E+00\n   17  1 0.0  2.4831571721174011E+00   5.8868847749471091E-02   2.8714017898244730E+00\n   18  1 0.0  2.9623271345173623E+00   6.6255006006868298E+00   4.3333102537280004E+00\n   19  2 0.0  2.5924978836700570E+00   1.7944388560555977E+00   6.9352523630401910E+00\n   20  1 0.0  2.1222678410324201E+00   1.2768680911581454E+00   6.2204075098346969E+00\n   21  1 0.0  1.9180281931273930E+00   2.2616218963260346E+00   3.9274315315749969E-01\n   22  2 0.0  5.9790312637835585E+00   6.7163127014570758E+00   2.3512729823005811E+00\n   23  1 0.0  6.0116037085053753E+00   6.9691212919231109E+00   3.3182411414869546E+00\n   24  1 0.0  6.8767703438302163E+00   6.3827294435137851E+00   2.0635471629013606E+00\n   25  2 0.0  6.7547865304093548E+00   8.1377929495075468E-02   5.3581116608665873E+00\n   26  1 0.0  5.9531825446743918E+00   6.7260222417346471E-01   5.2693136085523262E+00\n   27  1 0.0  4.4727592285958784E-01   6.4022081242395790E-01   5.5503336943639905E+00\n   28  2 0.0  4.6569264589470469E+00   4.3236993372651531E+00   3.2604100102435756E+00\n   29  1 0.0  3.9626142106129842E+00   3.6880495575692027E+00   3.5978666484999993E+00\n   30  1 0.0  4.6123792631715030E+00   5.1746062343494730E+00   3.7838306323283333E+00\n   31  2 0.0  1.6592261415965956E+00   1.9740050874317887E+00   2.5667232493700953E+00\n   32  1 0.0  1.3659958208733727E+00   1.1546249809050639E+00   2.0741439365038556E+00\n   33  1 0.0  2.5789980439011053E+00   2.2303030724114246E+00   2.2695177494557641E+00\n   34  2 0.0  6.7188326433244958E+00   5.0274902077599082E+00   7.0466394028585562E+00\n   35  1 0.0  6.4009802362616730E+00   4.4045226890456011E+00   6.4719907227395035E-01\n   36  1 0.0  6.0453043590359563E+00   5.7547786630259594E+00   6.9146816574097389E+00\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_4G/water.data.q",
    "content": "Generated by RuNNerUC, original comment lines: 7.1142\n\n36 atoms\n2 atom types\n\n0.0 7.1141994570823028E+00 xlo xhi\n0.0 7.1141994570823028E+00 ylo yhi\n0.0 7.1141994570823028E+00 zlo zhi\n\nMasses\n\n1 1.0079\n2 15.9994\n\nAtoms\n\n    1  2 -2.8256347534442394E-01  5.4407725127692641E-01   3.6384185563505054E+00   4.4961925860710092E+00\n    2  1  1.2277837277223856E-01  1.0817027740264313E+00   3.5577846500107415E+00   5.3355115606411010E+00\n    3  1  1.2747526484297361E-01  1.0837528065326016E+00   4.1098074970750078E+00   3.7986666445490349E+00\n    4  2 -2.0320633594884582E-01  5.9228924412533273E+00   2.6466268911619726E+00   1.2239688914990485E+00\n    5  1  1.5077528010356031E-01  5.3892796692767426E+00   2.4596400077893872E+00   3.9917001035611654E-01\n    6  1  1.0545961981723477E-01  6.3950052963992130E+00   3.5224871395184847E+00   1.1240808724238647E+00\n    7  2 -2.3518637803977813E-01  4.1822746115542317E+00   1.5987872250691670E+00   3.6579743000948359E+00\n    8  1  1.1004800576876206E-01  4.6852014555577082E+00   1.0410418556709500E+00   2.9976878139513659E+00\n    9  1  1.2457842239861068E-01  4.0758623666740457E+00   1.0894620994363380E+00   4.5119446040398223E+00\n   10  2 -2.2058240732065956E-01  4.1669385268713892E+00   5.4970302033175118E+00   5.8480726049046048E+00\n   11  1  1.2797577200732246E-01  4.8730244389199040E+00   4.8558002499567277E+00   6.1485166693356534E+00\n   12  1  1.1917909653994410E-01  4.2909305677989407E+00   5.6980826168950580E+00   4.8763704264099701E+00\n   13  2 -2.6183165626861749E-01  2.0588829949846374E+00   4.3767096641380583E+00   9.8336312746365173E-01\n   14  1  1.2478853272527497E-01  1.9348592034245695E+00   3.9922343756879437E+00   6.8597241552630556E-02\n   15  1  9.9154652510639193E-02  2.1394708629072521E+00   3.6345576794364582E+00   1.6487320283725717E+00\n   16  2 -2.7263628991795930E-01  2.5339931098401118E+00   6.3708832825217518E+00   3.4663091578748157E+00\n   17  1  1.1434733344402730E-01  2.4831571721174011E+00   5.8868847749471091E-02   2.8714017898244730E+00\n   18  1  1.1263403257973484E-01  2.9623271345173623E+00   6.6255006006868298E+00   4.3333102537280004E+00\n   19  2 -2.7372231339107417E-01  2.5924978836700570E+00   1.7944388560555977E+00   6.9352523630401910E+00\n   20  1  1.3658196132808181E-01  2.1222678410324201E+00   1.2768680911581454E+00   6.2204075098346969E+00\n   21  1  9.0172983387062006E-02  1.9180281931273930E+00   2.2616218963260346E+00   3.9274315315749969E-01\n   22  2 -2.5637106920821656E-01  5.9790312637835585E+00   6.7163127014570758E+00   2.3512729823005811E+00\n   23  1  1.1847178479117916E-01  6.0116037085053753E+00   6.9691212919231109E+00   3.3182411414869546E+00\n   24  1  1.3767024849619425E-01  6.8767703438302163E+00   6.3827294435137851E+00   2.0635471629013606E+00\n   25  2 -2.2955663167309948E-01  6.7547865304093548E+00   8.1377929495075468E-02   5.3581116608665873E+00\n   26  1  1.3433991100513271E-01  5.9531825446743918E+00   6.7260222417346471E-01   5.2693136085523262E+00\n   27  1  1.3761295680984550E-01  4.4727592285958784E-01   6.4022081242395790E-01   5.5503336943639905E+00\n   28  2 -2.3412971681479519E-01  4.6569264589470469E+00   4.3236993372651531E+00   3.2604100102435756E+00\n   29  1  1.1415705913922840E-01  3.9626142106129842E+00   3.6880495575692027E+00   3.5978666484999993E+00\n   30  1  1.1034962117814638E-01  4.6123792631715030E+00   5.1746062343494730E+00   3.7838306323283333E+00\n   31  2 -2.2006091505768430E-01  1.6592261415965956E+00   1.9740050874317887E+00   2.5667232493700953E+00\n   32  1  1.3641844939732600E-01  1.3659958208733727E+00   1.1546249809050639E+00   2.0741439365038556E+00\n   33  1  1.1534057032122748E-01  2.5789980439011053E+00   2.2303030724114246E+00   2.2695177494557641E+00\n   34  2 -2.0590918634609698E-01  6.7188326433244958E+00   5.0274902077599082E+00   7.0466394028585562E+00\n   35  1  1.0721155781927211E-01  6.4009802362616730E+00   4.4045226890456011E+00   6.4719907227395035E-01\n   36  1  1.1823488614823419E-01  6.0453043590359563E+00   5.7547786630259594E+00   6.9146816574097389E+00\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3/h2o_8640_liquid_NpT_RPBE-D3.data",
    "content": "LAMMPS data file via write_data, version 11 Aug 2017, timestep = 4000000\n\n8640 atoms\n2 atom types\n\n-3.2819324253026849e-01 4.5250693242527888e+01 xlo xhi\n-3.4106819274526146e-01 4.7025868192729938e+01 ylo yhi\n-3.2156223769001357e-01 4.4336422237685404e+01 zlo zhi\n0.0000000000000000e+00 0.0000000000000000e+00 0.0000000000000000e+00 xy xz yz\n\nMasses\n\n1 1.00794\n2 15.9994\n\nAtoms # atomic\n\n3791 1 1.6008666373327329e+00 -4.9126005439609932e-02 2.5055609599106323e+00 -2 0 2\n8571 1 1.9526752437770063e+00 8.0292814103758570e-01 2.4000828179486722e-01 0 3 0\n3790 2 1.1178391832328887e+00 1.5515453925548139e-01 3.3841161516446476e+00 -2 0 2\n8570 1 3.3204838069660298e+00 1.2797530996917250e-01 4.8199032657161134e-01 0 3 0\n3643 2 2.3226130647484529e+00 2.9114842240804601e+00 2.9779959101728890e+00 1 0 0\n8569 2 2.7196266572829577e+00 8.2992287659823982e-01 8.3148665117339071e-01 0 3 0\n3792 1 1.1279293032586206e+00 1.1286834145070108e+00 3.4879293545790904e+00 -2 0 2\n3644 1 2.5829235677481077e+00 2.6596195935451457e+00 2.0450920325305986e+00 1 0 0\n2839 2 1.1732257634842524e-01 1.8891526949140256e+00 -1.6627610215656008e-02 1 0 2\n1277 1 4.4430810556611080e+00 3.2355357958943554e+00 4.1337751747822509e+00 3 -3 1\n2841 1 -1.6216128249735967e-01 2.2070409723013085e+00 8.9311784996396582e-01 1 0 2\n3888 1 8.1972737457188072e-01 3.0840146587628579e+00 6.5837350094436413e+00 -1 0 1\n1844 1 -2.4701800857062756e-01 3.0493236212766410e+00 8.9427805291639118e+00 2 0 0\n2359 2 3.3387991665555545e+00 2.0160126155632812e+00 9.4365037141395423e+00 0 0 -2\n6535 2 9.8469083060522933e-01 -5.4845309086806460e-02 7.4918810751485179e+00 1 -1 1\n2875 2 5.1162855595342878e+00 1.1248525090341861e+00 6.8999885543230892e+00 0 2 0\n2360 1 3.4358229798221638e+00 1.5481424646636084e+00 8.5516514625290885e+00 0 0 -2\n1845 1 3.4263625931358077e-01 2.7517154882724273e+00 1.0358938962036662e+01 2 0 0\n2361 1 4.2438257264102521e+00 2.3384150687752761e+00 9.4325204152901598e+00 0 0 -2\n3887 1 1.8733756587121786e-01 1.7039526123530035e+00 6.9490012096920148e+00 -1 0 1\n3886 2 -2.2642640722228047e-02 2.6948254664417335e+00 6.7398388397755005e+00 -1 0 1\n1843 2 -2.9047839515697721e-01 3.3700749370637855e+00 9.8692555174822800e+00 2 0 0\n4389 1 4.7639686566741855e+00 -2.7906450625957407e-01 5.6006777021312395e+00 -3 1 0\n2709 1 3.1108338452562854e+00 1.8689110501446335e+00 1.4805959512348442e+01 -2 1 3\n7006 2 1.6383988883290872e+00 1.5424466467358098e+00 1.1444818116848193e+01 2 -2 0\n7007 1 1.8914485385893385e+00 1.6977448505166683e+00 1.2392447819900616e+01 2 -2 0\n3899 1 5.2639786340544725e-02 6.3430149349255127e-01 1.1719254324870558e+01 0 -2 2\n2707 2 3.0873742486936480e+00 2.3802379409893732e+00 1.3986838460750901e+01 -2 1 3\n2708 1 4.0346043834463812e+00 2.3796534944978829e+00 1.3606725156144611e+01 -2 1 3\n3808 2 5.3296333632344224e+00 2.4560808224817801e+00 1.2287336027283192e+01 2 3 0\n6451 2 4.9154845037098616e+00 1.4970470223624543e+00 1.6238289976369714e+01 1 1 0\n7008 1 2.5054048881573547e+00 1.5232177896054353e+00 1.0953460658566042e+01 2 -2 0\n3407 1 5.2137179415743207e+00 5.9038368386366336e-01 1.9538050860339649e+01 -2 1 -1\n322 2 3.9895926496811827e+00 3.1261732062082155e+00 1.8437581340760687e+01 0 -1 -1\n4537 2 2.4289327430533172e+00 1.8710574065218011e+00 2.0544201250879034e+01 2 -2 -1\n5172 1 2.2046383303072261e+00 3.9257437304131471e-01 1.7563979438759517e+01 3 1 -1\n4711 2 1.2460552496590069e+00 2.1358019733097233e+00 1.7280768673627971e+01 -2 -1 -1\n4539 1 2.9857347081934509e+00 2.2955045893908173e+00 1.9883283195177786e+01 2 -2 -1\n324 1 4.2282578573994360e+00 2.4812117569753624e+00 1.7701211381453366e+01 0 -1 -1\n4538 1 3.0319229603134783e+00 1.6562014178028117e+00 2.1330716875076678e+01 2 -2 -1\n4712 1 1.7124855911992705e+00 2.7415633786048605e+00 1.7862547963603824e+01 -2 -1 -1\n5014 2 -2.7916797577052715e-01 2.0702634957322390e+00 2.1924699322071312e+01 -1 2 0\n4713 1 9.8427145526707593e-01 2.6873358690926055e+00 1.6544803892136233e+01 -2 -1 -1\n5016 1 6.6020340586231074e-01 2.1606983187092510e+00 2.1696363616860538e+01 -1 2 0\n3406 2 4.8208239916240201e+00 -2.7964396274810310e-01 1.9567220324511261e+01 -2 1 -1\n323 1 4.7938855543796670e+00 3.4099110855474586e+00 1.8876315444667064e+01 0 -1 -1\n5171 1 3.4242879637416337e+00 -3.3502703667111128e-01 1.8187199506349575e+01 3 1 -1\n8041 2 4.3953348165969617e+00 2.6075598282097454e+00 2.7052110102272493e+01 0 1 -1\n769 2 4.2999262450635394e+00 2.2887091685681620e+00 2.2714583868049207e+01 1 1 0\n5856 1 1.1847191929965426e+00 5.3107193452776358e-01 2.4431977562515858e+01 -1 0 1\n4682 1 1.1014036126174629e+00 2.6340144445163096e+00 2.5832753471745146e+01 1 -1 1\n7432 2 5.0737537910626731e+00 6.3304750136240329e-01 2.5058709565263811e+01 3 2 0\n4681 2 1.5310002784347216e+00 3.4453791156182043e+00 2.6166283009198786e+01 1 -1 1\n8042 1 3.4226844550396009e+00 2.8444732778271269e+00 2.6987685885883383e+01 0 1 -1\n5854 2 4.5631628667812107e-01 1.1175356042994167e+00 2.4512706259402126e+01 -1 0 1\n8043 1 4.5667610216212688e+00 2.0369809666608338e+00 2.6258476702470301e+01 0 1 -1\n770 1 4.4867225229743886e+00 1.7001179180779373e+00 2.3487616837382109e+01 1 1 0\n7433 1 4.3550963204287125e+00 -4.0284105821217220e-02 2.5049858918126588e+01 3 2 0\n5855 1 2.7320563053961677e-01 1.2783757153034183e+00 2.3608761583608970e+01 -1 0 1\n771 1 5.1169641079654253e+00 2.8805163707631065e+00 2.2494465544866063e+01 1 1 0\n4258 2 2.9512144543512142e-01 2.7207784469021656e+00 3.1459993924772697e+01 -1 1 1\n4260 1 1.1443937247853619e-01 3.5038750888393193e+00 3.0846296268864727e+01 -1 1 1\n2598 1 3.2851294384109431e+00 1.7207121607714106e+00 3.1238553224172772e+01 -2 0 -2\n2596 2 3.7684486805898292e+00 2.1731835524801189e+00 3.0521075205477199e+01 -2 0 -2\n4259 1 1.2451019167501187e+00 2.6155255554574062e+00 3.1325979247351864e+01 -1 1 1\n2597 1 4.0417564658435063e+00 2.9993812437509622e+00 3.0910637266560439e+01 -2 0 -2\n2243 1 4.1002103718421443e+00 -1.8360780409336269e-01 2.8622511966180287e+01 0 4 -2\n978 1 2.9285679459181888e+00 4.6377264688469055e-01 3.3171443993181768e+01 0 -3 -1\n1833 1 4.8378738032169490e+00 1.5496875005857130e-01 3.1366490346868325e+01 -1 2 0\n471 1 7.1125277661877506e-01 -2.7004573629379797e-01 2.8048232327443554e+01 0 1 0\n5588 1 1.3181595283051406e+00 8.9324970422624705e-01 3.6900691971555361e+01 -2 0 1\n977 1 1.9865656709599468e+00 1.5506264148298978e+00 3.3770789742757856e+01 0 -3 -1\n713 1 -2.8904494494047933e-01 2.9875763409414771e+00 3.4907855472815598e+01 0 0 1\n712 2 -1.8751669511623006e-01 2.1795814814171908e+00 3.4296310864957235e+01 0 0 1\n3975 1 5.0064100801497400e+00 1.7016114424078732e+00 3.4342424421098045e+01 -3 2 2\n976 2 2.9304607653931978e+00 1.3885091099769031e+00 3.3460408921647598e+01 0 -3 -1\n6072 1 2.6343754770741112e+00 2.6694833220259033e+00 3.6470970815752139e+01 2 3 2\n6070 2 2.4527840898462605e+00 3.5292414958607452e+00 3.6836652823018298e+01 2 3 2\n714 1 -1.4823292912900454e-01 2.4341607366338600e+00 3.3364854002756744e+01 0 0 1\n6071 1 2.4017306881653711e+00 3.3124060291800705e+00 3.7766031715914039e+01 2 3 2\n6686 1 5.3634818670010551e+00 2.0508424896631468e+00 3.8356515765733093e+01 2 1 -2\n5589 1 4.6906635580204925e-01 -1.1331155234501808e-01 3.7690356589726264e+01 -2 0 1\n5587 2 1.0420553720874854e+00 -3.8134823413191243e-02 3.6872035008503815e+01 -2 0 1\n5985 1 3.3350262313680847e+00 3.2232429855423144e+00 4.1831712134148390e+01 -1 0 2\n2789 1 3.1158918349706282e+00 2.2998295542188318e-01 4.0051518236481300e+01 -1 3 -2\n5426 1 1.3063479898763004e+00 2.0364643731412584e+00 4.0069198371299137e+01 -1 -1 2\n5425 2 2.0355659439336966e+00 1.8829159800688875e+00 3.9437162833538636e+01 -1 -1 2\n5984 1 4.2746108244027301e+00 2.3096433946449304e+00 4.2472782757396132e+01 -1 0 2\n2840 1 -5.8393034094813057e-02 2.6502142659700292e+00 4.4093478253240008e+01 1 0 1\n5983 2 4.0213718828374967e+00 2.6149838878941822e+00 4.1583640560400511e+01 -1 0 2\n2790 1 4.3341008382863908e+00 2.2613312243174111e-01 4.0923651895643701e+01 -1 3 -2\n5427 1 2.7783500628023972e+00 2.2049568241697970e+00 3.9962527688957294e+01 -1 -1 2\n2788 2 3.8965985578825784e+00 -2.9149056393465628e-01 4.0219028056195896e+01 -1 3 -2\n4141 2 1.1787537732153082e+00 3.5751936062339920e+00 4.2329910033563237e+01 -2 -2 0\n7422 1 5.3123610843935465e+00 5.7359083977286307e+00 2.8203632785239729e-01 2 2 0\n7167 1 1.4481346932905341e+00 5.4790388332984383e+00 5.9184230952981420e-01 3 1 2\n7997 1 2.4281198459056528e+00 5.5780228570547754e+00 4.7309348765483215e+00 1 2 -2\n7147 2 -1.3692789843251357e-01 5.5071185305951005e+00 2.1983503246977203e+00 0 -2 1\n1278 1 4.2039224454867208e+00 4.5886617314095135e+00 3.6263325758777696e+00 3 -3 1\n1276 2 4.7011096755242168e+00 4.1601233557022743e+00 4.3477643809239126e+00 3 -3 1\n7996 2 1.8486654765938528e+00 5.9639341649265747e+00 4.0670930324576577e+00 1 2 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  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3/hdnnp-data/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   4              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 2\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               25             # Write energy comparison.\nwrite_trainforces               25             # Write force comparison.\nwrite_weights_epoch                            # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3/hdnnp-data/nnp-train.log.0000",
    "content": "\n*** SETUP: MPI ****************************************************************\n\nNumber of processors: 16\nProcess 1 of 16 (rank 0): n18-040\nProcess 2 of 16 (rank 1): n18-040\nProcess 3 of 16 (rank 2): n18-040\nProcess 4 of 16 (rank 3): n18-040\nProcess 5 of 16 (rank 4): n18-040\nProcess 6 of 16 (rank 5): n18-040\nProcess 7 of 16 (rank 6): n18-040\nProcess 8 of 16 (rank 7): n18-040\nProcess 9 of 16 (rank 8): n18-040\nProcess 10 of 16 (rank 9): n18-040\nProcess 11 of 16 (rank 10): n18-040\nProcess 12 of 16 (rank 11): n18-040\nProcess 13 of 16 (rank 12): n18-040\nProcess 14 of 16 (rank 13): n18-040\nProcess 15 of 16 (rank 14): n18-040\nProcess 16 of 16 (rank 15): n18-040\n*******************************************************************************\n\n*******************************************************************************\n\n   NNP LIBRARY v0.1.0\n   ------------------\n\nGit branch  : master\nGit revision: d2f83cd (d2f83cde386d59595aea395bfe3755dccebc195a)\n\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 167 lines.\nFound 102 lines with keywords.\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is used.\nMean energy per atom     :  -2.5521343547039809E+01\nConversion factor energy :   2.4265748255366972E+02\nConversion factor length :   5.8038448995319847E+00\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  H (  1)\nElement  1:  O (  8)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:   0.00000000E+00\nElement  1:   0.00000000E+00\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_TANHU (2)\nf(r) = tanh^3(1 - r/rc)\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  H  2  H    2.969E-05 0.000E+00         6.965E+01  2 0.00    98\n   2  H  2  O    2.969E-05 0.000E+00         6.965E+01  2 0.00   108\n   3  H  2  H    2.969E-04 0.000E+00         6.965E+01  2 0.00    99\n   4  H  2  O    2.969E-04 0.000E+00         6.965E+01  2 0.00   109\n   5  H  2  H    8.906E-04 0.000E+00         6.965E+01  2 0.00   100\n   6  H  2  O    8.906E-04 0.000E+00         6.965E+01  2 0.00   110\n   7  H  2  H    1.781E-03 0.000E+00         6.965E+01  2 0.00   101\n   8  H  2  O    1.781E-03 0.000E+00         6.965E+01  2 0.00   111\n   9  H  2  O    4.453E-03 5.223E+00         6.965E+01  2 0.00   112\n  10  H  2  H    4.453E-03 1.103E+01         6.965E+01  2 0.00   102\n  11  H  2  O    8.906E-03 5.223E+00         6.965E+01  2 0.00   113\n  12  H  2  H    8.906E-03 1.103E+01         6.965E+01  2 0.00   103\n  13  H  2  O    1.781E-02 5.223E+00         6.965E+01  2 0.00   114\n  14  H  2  H    1.781E-02 1.103E+01         6.965E+01  2 0.00   104\n  15  H  2  O    4.453E-02 5.223E+00         6.965E+01  2 0.00   115\n  16  H  2  H    4.453E-02 1.103E+01         6.965E+01  2 0.00   105\n  17  H  3  O  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   162\n  18  H  3  O  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   161\n  19  H  3  H  O 2.969E-04 0.000E+00 -1  4.0 6.965E+01  2 0.00   152\n  20  H  3  H  O 2.969E-04 0.000E+00  1  4.0 6.965E+01  2 0.00   150\n  21  H  3  H  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   147\n  22  H  3  O  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   160\n  23  H  3  H  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   145\n  24  H  3  O  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   159\n  25  H  3  H  O 2.078E-03 0.000E+00 -1  1.0 6.965E+01  2 0.00   142\n  26  H  3  H  O 2.078E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   140\n  27  H  3  H  O 5.937E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   137\n-------------------------------------------------------------------------------\nShort range atomic symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  O  2  H    2.969E-05 0.000E+00         6.965E+01  2 0.00   117\n   2  O  2  O    2.969E-05 0.000E+00         6.965E+01  2 0.00   127\n   3  O  2  H    2.969E-04 0.000E+00         6.965E+01  2 0.00   118\n   4  O  2  O    2.969E-04 0.000E+00         6.965E+01  2 0.00   128\n   5  O  2  H    8.906E-04 0.000E+00         6.965E+01  2 0.00   119\n   6  O  2  O    8.906E-04 0.000E+00         6.965E+01  2 0.00   129\n   7  O  2  H    1.781E-03 0.000E+00         6.965E+01  2 0.00   120\n   8  O  2  O    1.781E-03 0.000E+00         6.965E+01  2 0.00   130\n   9  O  2  H    4.453E-03 5.223E+00         6.965E+01  2 0.00   121\n  10  O  2  O    4.453E-03 2.322E+01         6.965E+01  2 0.00   131\n  11  O  2  H    8.906E-03 5.223E+00         6.965E+01  2 0.00   122\n  12  O  2  O    8.906E-03 2.322E+01         6.965E+01  2 0.00   132\n  13  O  2  H    1.781E-02 5.223E+00         6.965E+01  2 0.00   123\n  14  O  2  O    1.781E-02 2.322E+01         6.965E+01  2 0.00   133\n  15  O  2  H    4.453E-02 5.223E+00         6.965E+01  2 0.00   124\n  16  O  2  O    4.453E-02 2.322E+01         6.965E+01  2 0.00   134\n  17  O  3  H  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   157\n  18  O  3  O  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   167\n  19  O  3  H  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   156\n  20  O  3  O  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   166\n  21  O  3  H  H 2.969E-04 0.000E+00 -1  4.0 6.965E+01  2 0.00   151\n  22  O  3  H  H 2.969E-04 0.000E+00  1  4.0 6.965E+01  2 0.00   149\n  23  O  3  H  H 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   146\n  24  O  3  H  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   155\n  25  O  3  O  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   165\n  26  O  3  H  H 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   144\n  27  O  3  H  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   154\n  28  O  3  O  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   164\n  29  O  3  H  H 2.078E-03 0.000E+00 -1  1.0 6.965E+01  2 0.00   141\n  30  O  3  H  H 2.078E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   139\n-------------------------------------------------------------------------------\nMinimum cutoff radius for element  H: 69.646139\nMinimum cutoff radius for element  O: 69.646139\nMaximum cutoff radius (global)      : 69.646139\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function group index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  H  2  H            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -    97    1    1  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -    98    2    3  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -    99    3    5  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   100    4    7  \n   -  -  -  -    4.453E-03 1.103E+01                 -  -    -   101    5   10  \n   -  -  -  -    8.906E-03 1.103E+01                 -  -    -   102    6   12  \n   -  -  -  -    1.781E-02 1.103E+01                 -  -    -   103    7   14  \n   -  -  -  -    4.453E-02 1.103E+01                 -  -    -   104    8   16  \n   2  H  2  O            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   107    1    2  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   108    2    4  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   109    3    6  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   110    4    8  \n   -  -  -  -    4.453E-03 5.223E+00                 -  -    -   111    5    9  \n   -  -  -  -    8.906E-03 5.223E+00                 -  -    -   112    6   11  \n   -  -  -  -    1.781E-02 5.223E+00                 -  -    -   113    7   13  \n   -  -  -  -    4.453E-02 5.223E+00                 -  -    -   114    8   15  \n   3  H  3  H  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-04 0.000E+00 -1  4.0         -  -    -   151    1   19 1\n   -  -  -  -  - 2.969E-04 0.000E+00  1  4.0         -  -    -   149    2   20 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   146    3   21 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   144    4   23 0\n   -  -  -  -  - 2.078E-03 0.000E+00 -1  1.0         -  -    -   141    5   25 1\n   -  -  -  -  - 2.078E-03 0.000E+00  1  1.0         -  -    -   139    6   26 0\n   -  -  -  -  - 5.937E-03 0.000E+00  1  1.0         -  -    -   136    7   27 1\n   4  H  3  O  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   161    1   17 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   160    2   18 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   159    3   22 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   158    4   24 0\n-------------------------------------------------------------------------------\nShort range atomic symmetry function groups element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  O  2  H            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   116    1    1  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   117    2    3  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   118    3    5  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   119    4    7  \n   -  -  -  -    4.453E-03 5.223E+00                 -  -    -   120    5    9  \n   -  -  -  -    8.906E-03 5.223E+00                 -  -    -   121    6   11  \n   -  -  -  -    1.781E-02 5.223E+00                 -  -    -   122    7   13  \n   -  -  -  -    4.453E-02 5.223E+00                 -  -    -   123    8   15  \n   2  O  2  O            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   126    1    2  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   127    2    4  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   128    3    6  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   129    4    8  \n   -  -  -  -    4.453E-03 2.322E+01                 -  -    -   130    5   10  \n   -  -  -  -    8.906E-03 2.322E+01                 -  -    -   131    6   12  \n   -  -  -  -    1.781E-02 2.322E+01                 -  -    -   132    7   14  \n   -  -  -  -    4.453E-02 2.322E+01                 -  -    -   133    8   16  \n   3  O  3  H  H         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-04 0.000E+00 -1  4.0         -  -    -   150    1   21 1\n   -  -  -  -  - 2.969E-04 0.000E+00  1  4.0         -  -    -   148    2   22 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   145    3   23 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   143    4   26 0\n   -  -  -  -  - 2.078E-03 0.000E+00 -1  1.0         -  -    -   140    5   29 1\n   -  -  -  -  - 2.078E-03 0.000E+00  1  1.0         -  -    -   138    6   30 0\n   4  O  3  H  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   156    1   17 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   155    2   19 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   154    3   24 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   153    4   27 0\n   5  O  3  O  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   166    1   18 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   165    2   20 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   164    3   25 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   163    4   28 0\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic short range NN for element  H :\nNumber of weights    :   1325\nNumber of biases     :     51\nNumber of connections:   1376\nArchitecture       27   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  O :\nNumber of weights    :   1400\nNumber of biases     :     51\nNumber of connections:   1451\nArchitecture       30   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALECENTER (3)\nGs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  1.09E+00  9.62E+00  2.27E+00  6.79E-01  1.17E-01  0.00  1.00 3\n   2  7.33E-01  5.00E+00  1.33E+00  3.39E-01  2.34E-01  0.00  1.00 3\n   3  7.60E-01  7.14E+00  1.65E+00  5.08E-01  1.57E-01  0.00  1.00 3\n   4  5.48E-01  3.77E+00  1.02E+00  2.54E-01  3.11E-01  0.00  1.00 3\n   5  4.01E-01  4.15E+00  9.09E-01  2.98E-01  2.67E-01  0.00  1.00 3\n   6  3.62E-01  2.27E+00  6.49E-01  1.48E-01  5.25E-01  0.00  1.00 3\n   7  1.89E-01  2.23E+00  4.57E-01  1.60E-01  4.90E-01  0.00  1.00 3\n   8  2.67E-01  1.32E+00  4.24E-01  8.05E-02  9.49E-01  0.00  1.00 3\n   9  2.45E-01  9.48E-01  3.62E-01  5.30E-02  1.42E+00  0.00  1.00 3\n  10  2.22E-01  2.76E+00  5.39E-01  2.01E-01  3.94E-01  0.00  1.00 3\n  11  1.47E-01  5.56E-01  2.68E-01  2.62E-02  2.45E+00  0.00  1.00 3\n  12  9.91E-02  1.73E+00  2.96E-01  1.16E-01  6.14E-01  0.00  1.00 3\n  13  6.51E-02  3.45E-01  1.85E-01  1.97E-02  3.57E+00  0.00  1.00 3\n  14  3.17E-02  9.13E-01  1.50E-01  5.35E-02  1.13E+00  0.00  1.00 3\n  15  2.92E-03  2.65E-01  7.65E-02  1.88E-02  3.82E+00  0.00  1.00 3\n  16  3.21E-04  2.87E-01  4.58E-02  2.33E-02  3.49E+00  0.00  1.00 3\n  17  2.47E-04  1.38E-01  1.77E-02  9.75E-03  7.23E+00  0.00  1.00 3\n  18  5.10E-03  5.83E-01  2.39E-02  3.78E-02  1.73E+00  0.00  1.00 3\n  19  3.23E-04  2.16E-01  1.71E-02  1.40E-02  4.63E+00  0.00  1.00 3\n  20  4.96E-02  1.69E+00  1.45E-01  1.10E-01  6.11E-01  0.00  1.00 3\n  21  3.41E-03  3.16E-01  1.84E-02  2.01E-02  3.20E+00  0.00  1.00 3\n  22  1.31E-04  1.03E-01  6.37E-03  6.61E-03  9.76E+00  0.00  1.00 3\n  23  3.38E-02  9.16E-01  8.13E-02  5.79E-02  1.13E+00  0.00  1.00 3\n  24  4.17E-04  1.58E-01  4.66E-03  9.86E-03  6.35E+00  0.00  1.00 3\n  25  7.35E-04  5.92E-02  3.70E-03  3.31E-03  1.71E+01  0.00  1.00 3\n  26  8.98E-03  1.94E-01  2.41E-02  1.10E-02  5.40E+00  0.00  1.00 3\n  27  2.12E-04  8.78E-03  2.06E-03  5.88E-04  1.17E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  1.51E+00  1.00E+01  2.65E+00  6.78E-01  1.18E-01  0.00  1.00 3\n   2  4.44E-01  4.62E+00  9.66E-01  3.37E-01  2.39E-01  0.00  1.00 3\n   3  1.19E+00  7.53E+00  2.03E+00  5.06E-01  1.58E-01  0.00  1.00 3\n   4  2.76E-01  3.39E+00  6.59E-01  2.50E-01  3.21E-01  0.00  1.00 3\n   5  8.06E-01  4.54E+00  1.30E+00  2.94E-01  2.68E-01  0.00  1.00 3\n   6  1.05E-01  1.89E+00  3.07E-01  1.42E-01  5.60E-01  0.00  1.00 3\n   7  5.69E-01  2.62E+00  8.48E-01  1.57E-01  4.89E-01  0.00  1.00 3\n   8  2.33E-02  9.36E-01  1.11E-01  6.98E-02  1.10E+00  0.00  1.00 3\n   9  5.14E-01  1.85E+00  7.25E-01  9.80E-02  7.46E-01  0.00  1.00 3\n  10  1.11E-01  2.91E+00  4.75E-01  2.34E-01  3.57E-01  0.00  1.00 3\n  11  3.53E-01  1.07E+00  5.35E-01  4.52E-02  1.39E+00  0.00  1.00 3\n  12  3.04E-02  2.53E+00  3.17E-01  2.10E-01  4.00E-01  0.00  1.00 3\n  13  1.60E-01  6.63E-01  3.70E-01  3.08E-02  1.99E+00  0.00  1.00 3\n  14  2.78E-03  2.30E+00  1.77E-01  1.86E-01  4.35E-01  0.00  1.00 3\n  15  9.56E-03  3.91E-01  1.53E-01  2.79E-02  2.62E+00  0.00  1.00 3\n  16  3.75E-06  2.04E+00  5.41E-02  1.43E-01  4.91E-01  0.00  1.00 3\n  17  2.47E-03  3.43E-01  1.67E-02  2.19E-02  2.93E+00  0.00  1.00 3\n  18  1.74E-05  5.63E-02  9.55E-04  3.36E-03  1.78E+01  0.00  1.00 3\n  19  5.48E-02  3.02E+00  2.04E-01  2.01E-01  3.37E-01  0.00  1.00 3\n  20  1.38E-03  4.99E-01  1.28E-02  3.18E-02  2.01E+00  0.00  1.00 3\n  21  6.69E-03  2.67E-01  3.09E-02  1.71E-02  3.84E+00  0.00  1.00 3\n  22  1.70E-02  1.42E+00  7.63E-02  9.29E-02  7.14E-01  0.00  1.00 3\n  23  1.98E-02  4.08E-01  4.88E-02  2.55E-02  2.58E+00  0.00  1.00 3\n  24  5.28E-04  2.33E-01  7.21E-03  1.45E-02  4.30E+00  0.00  1.00 3\n  25  1.11E-05  3.53E-02  4.25E-04  2.05E-03  2.83E+01  0.00  1.00 3\n  26  1.60E-02  8.22E-01  5.08E-02  5.28E-02  1.24E+00  0.00  1.00 3\n  27  3.99E-03  7.86E-01  3.69E-02  5.05E-02  1.28E+00  0.00  1.00 3\n  28  4.05E-05  9.84E-02  1.21E-03  5.79E-03  1.02E+01  0.00  1.00 3\n  29  6.04E-03  9.93E-02  1.62E-02  5.52E-03  1.07E+01  0.00  1.00 3\n  30  2.96E-03  1.55E-01  1.16E-02  8.94E-03  6.59E+00  0.00  1.00 3\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 0\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** SETUP: RANDOM NUMBER GENERATOR ********************************************\n\nRandom number generator seed: 2\nSeed for rank 0: 2\nSeed for rank 1: 1872583848\nSeed for rank 2: 794921487\nSeed for rank 3: 111352301\nSeed for rank 4: 4000937544\nSeed for rank 5: 2360782358\nSeed for rank 6: 4070471979\nSeed for rank 7: 1869695442\nSeed for rank 8: 2081981515\nSeed for rank 9: 1805465960\nSeed for rank 10: 1376693511\nSeed for rank 11: 1418777250\nSeed for rank 12: 663257521\nSeed for rank 13: 878959199\nSeed for rank 14: 3001592395\nSeed for rank 15: 2659748565\nSeed for global RNG: 515183663\n*******************************************************************************\n\n*** STRUCTURE DISTRIBUTION ****************************************************\n\nReading configurations from data file: input.data.\nTotal number of structures: 7241\nNumber of structures per processor: 452 (7) or 453 (9)\nDistributed 7241 structures, 123519504 bytes (117.80 MiB) transferred.\nNumber of local structures: 452\n*******************************************************************************\n\n*** DEFINE TRAINING/TEST SETS *************************************************\n\nDesired test set ratio      : 0.100000\nTotal number of energies    : 7241\nNumber of training energies : 6533\nNumber of test     energies : 708\nNumber of training forces   : 1596654\nNumber of test     forces   : 169290\nActual test set fraction    : 0.097777\n*******************************************************************************\n\n*** WRITE TRAINING/TEST SETS **************************************************\n\nWriting training/test set to files:\n - train.data\n - test.data\n*******************************************************************************\n\n*** WEIGHT INITIALIZATION *****************************************************\n\nInitial weights selected randomly in interval [-1.000000, 1.000000).\nWeights modified accoring to Glorot Bengio scheme.\nBiases set to zero.\n*******************************************************************************\n\n*** SETUP: TRAINING ***********************************************************\n\nForces will be used for training.\nForce update weight:   1.00E+01\nWeight update via Kalman filter selected: updaterType::UT_KALMANFILTER (1)\nMulti-stream Kalman filter training, update on rank 0, partial X calculation selected: ParallelMode::PM_MSEKFR0PX (4)\nNumber of streams       : 16\nStream of this processor: 0\nCombined updater for all elements selected: UpdateStrategy::US_COMBINED (0)\nNumber of weight updaters    : 1\nTotal fit parameters         : 2827\nSelection mode starting with epoch 0:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 1.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\n-------------------------------------------------------------------------------\nSymmetry function memory is reused (HIGH MEMORY USAGE!).\nTraining will be stopped after 25 epochs.\nEnergy comparison will be written every 25 epochs.\nForce comparison will be written every 25 epochs.\nWeights will be written every 1 epochs.\nNeuron statistics will be written every 5 epochs.\nUp to epoch 10 neuron statistics will be written every epoch.\nTraining log with update information will be written to: train-log.out.\n-------------------------------------------------------------------------------\nFraction of energies used per epoch:    1.0000\nFraction of forces used per epoch  :    0.0410\nProjected energy updates per epoch :     408 (  9.1%)\nProjected forces updates per epoch :    4091 ( 90.9%)\nTotal projected updates per epoch  :    4500\nMulti-stream training uses 16 energies/forces per weight update.\nqtau is divided by number of projected updates per epoch.\netatau is divided by number of projected updates per epoch.\n-------------------------------------------------------------------------------\nCombined weight updater:\n-------------------------------------------------------------------------------\nKalmanType::KT_STANDARD (0)\nsizeState       = 2827\nsizeObservation = 16\nepsilon         =   1.0000E-02\nq0              =   1.0000E-02\nqtau            =   5.1159E-04\nqmin            =   1.0000E-06\neta0            =   1.0000E-02\netatau          =   5.1159E-04\netamax          =   1.0000E+00\nKalmanParallel::KP_PRECALCX (2)\nOpenMP threads used: 1\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** CALCULATE NEIGHBOR LISTS **************************************************\n\nCalculating neighbor lists for all structures.\nCutoff radius for neighbor lists: 69.646139\n*******************************************************************************\n\n*** TRAINING LOOP *************************************************************\n\nThe training loop output covers different RMSEs, update and\ntiming information. The following quantities are organized\naccording to the matrix scheme below:\n-------------------------------------------------------------------\nep ............ Epoch.\nEtrain_phys ... RMSE of training energies per atom (p. u.).\nEtest_phys .... RMSE of test     energies per atom (p. u.).\nEtrain_int .... RMSE of training energies per atom (i. u.).\nEtest_int ..... RMSE of test     energies per atom (i. u.).\nFtrain_phys ... RMSE of training forces (p. u.).\nFtest_phys .... RMSE of test     forces (p. u.).\nFtrain_int .... RMSE of training forces (i. u.).\nFtest_int ..... RMSE of test     forces (i. u.).\nE_count ....... Number of energy updates.\nF_count ....... Number of force  updates.\ncount ......... Total number of updates.\nt_train ....... Time for training (seconds).\nt_rmse ........ Time for RMSE calculation (seconds).\nt_epoch ....... Total time for this epoch (seconds).\nt_tot ......... Total time for all epochs (seconds).\nAbbreviations:\n  p. u. = physical units.\n  i. u. = internal units.\nNote: RMSEs in internal units (columns 5 + 6) are only present \n      if data set normalization is used.\n-------------------------------------------------------------------\n     1    2             3             4             5             6\nenergy   ep   Etrain_phys    Etest_phys    Etrain_int     Etest_int\nforces   ep   Ftrain_phys    Ftest_phys    Ftrain_int     Ftest_int\nupdate   ep       E_count       F_count         count\ntiming   ep       t_train        t_rmse       t_epoch         t_tot\n-------------------------------------------------------------------\nENERGY    0   3.72115E-03   3.81895E-03   9.02965E-01   9.26696E-01\nFORCES    0   2.34072E-02   2.29953E-02   9.78649E-01   9.61428E-01\nTIMING    0          0.00         30.72         30.75         30.75\n------\nENERGY    1   5.27269E-05   5.44783E-05   1.27946E-02   1.32196E-02\nFORCES    1   9.78255E-04   9.47430E-04   4.09006E-02   3.96118E-02\nUPDATE    1           408          4076          4484\nTIMING    1        547.67          2.61        550.32        581.07\n------\nENERGY    2   9.56678E-05   8.86669E-05   2.32145E-02   2.15157E-02\nFORCES    2   8.94076E-04   8.74898E-04   3.73811E-02   3.65793E-02\nUPDATE    2           408          4082          4490\nTIMING    2        525.97          2.71        528.71       1109.78\n------\nENERGY    3   3.38638E-05   3.30619E-05   8.21730E-03   8.02272E-03\nFORCES    3   7.89628E-04   7.69554E-04   3.30142E-02   3.21749E-02\nUPDATE    3           408          3997          4405\nTIMING    3        517.62          2.69        520.35       1630.13\n------\nENERGY    4   2.69193E-05   2.55573E-05   6.53218E-03   6.20168E-03\nFORCES    4   7.54758E-04   7.38703E-04   3.15563E-02   3.08850E-02\nUPDATE    4           408          4143          4551\nTIMING    4        530.61          2.66        533.30       2163.43\n------\nENERGY    5   3.67487E-05   3.57290E-05   8.91736E-03   8.66991E-03\nFORCES    5   7.34764E-04   7.34122E-04   3.07203E-02   3.06935E-02\nUPDATE    5           408          3987          4395\nTIMING    5        508.88          2.63        511.54       2674.97\n------\nENERGY    6   3.05092E-05   3.02791E-05   7.40328E-03   7.34745E-03\nFORCES    6   7.24954E-04   7.21860E-04   3.03102E-02   3.01808E-02\nUPDATE    6           408          4077          4485\nTIMING    6        520.66          2.68        523.37       3198.34\n------\nENERGY    7   4.44131E-05   4.29940E-05   1.07772E-02   1.04328E-02\nFORCES    7   7.19542E-04   7.18822E-04   3.00839E-02   3.00538E-02\nUPDATE    7           408          4151          4559\nTIMING    7        529.47          2.71        532.21       3730.55\n------\nENERGY    8   3.55360E-05   3.40692E-05   8.62307E-03   8.26716E-03\nFORCES    8   7.22773E-04   7.20229E-04   3.02190E-02   3.01126E-02\nUPDATE    8           408          4151          4559\nTIMING    8        527.71          2.63        530.38       4260.93\n------\nENERGY    9   2.65646E-05   2.57801E-05   6.44610E-03   6.25574E-03\nFORCES    9   7.14881E-04   7.12744E-04   2.98890E-02   2.97997E-02\nUPDATE    9           408          4051          4459\nTIMING    9        515.96          2.67        518.66       4779.59\n------\nENERGY   10   2.74199E-05   2.62896E-05   6.65364E-03   6.37936E-03\nFORCES   10   7.14391E-04   7.12126E-04   2.98685E-02   2.97738E-02\nUPDATE   10           408          4054          4462\nTIMING   10        519.13          2.76        521.92       5301.51\n------\nENERGY   11   2.74124E-05   2.69574E-05   6.65184E-03   6.54141E-03\nFORCES   11   7.15474E-04   7.13003E-04   2.99138E-02   2.98105E-02\nUPDATE   11           408          3931          4339\nTIMING   11        501.49          2.65        504.17       5805.68\n------\nENERGY   12   2.87293E-05   2.82820E-05   6.97137E-03   6.86285E-03\nFORCES   12   7.14605E-04   7.12197E-04   2.98775E-02   2.97768E-02\nUPDATE   12           408          4122          4530\nTIMING   12        526.86          2.66        529.54       6335.22\n------\nENERGY   13   2.50400E-05   2.41467E-05   6.07614E-03   5.85937E-03\nFORCES   13   7.12309E-04   7.11631E-04   2.97815E-02   2.97531E-02\nUPDATE   13           408          4009          4417\nTIMING   13        511.79          2.72        514.54       6849.76\n------\nENERGY   14   3.27553E-05   3.21490E-05   7.94833E-03   7.80119E-03\nFORCES   14   7.11961E-04   7.10919E-04   2.97669E-02   2.97234E-02\nUPDATE   14           408          4132          4540\nTIMING   14        526.43          2.68        529.14       7378.90\n------\nENERGY   15   3.24771E-05   3.11575E-05   7.88081E-03   7.56061E-03\nFORCES   15   7.07100E-04   7.05472E-04   2.95637E-02   2.94956E-02\nUPDATE   15           408          4053          4461\nTIMING   15        515.38          2.65        518.06       7896.96\n------\nENERGY   16   3.12976E-05   3.18343E-05   7.59461E-03   7.72483E-03\nFORCES   16   7.10094E-04   7.07533E-04   2.96889E-02   2.95818E-02\nUPDATE   16           408          4104          4512\nTIMING   16        523.43          2.71        526.17       8423.13\n------\nENERGY   17   2.70985E-05   2.73839E-05   6.57565E-03   6.64491E-03\nFORCES   17   7.07123E-04   7.06332E-04   2.95647E-02   2.95316E-02\nUPDATE   17           408          4021          4429\nTIMING   17        513.31          2.67        516.01       8939.14\n------\nENERGY   18   3.09332E-05   2.91548E-05   7.50617E-03   7.07463E-03\nFORCES   18   7.05834E-04   7.04317E-04   2.95108E-02   2.94473E-02\nUPDATE   18           408          4079          4487\nTIMING   18        521.91          2.66        524.60       9463.74\n------\nENERGY   19   3.26598E-05   3.28139E-05   7.92515E-03   7.96254E-03\nFORCES   19   7.05070E-04   7.01846E-04   2.94788E-02   2.93440E-02\nUPDATE   19           408          4033          4441\nTIMING   19        514.32          2.69        517.05       9980.78\n------\nENERGY   20   2.60466E-05   2.47333E-05   6.32039E-03   6.00173E-03\nFORCES   20   7.06028E-04   7.04603E-04   2.95189E-02   2.94593E-02\nUPDATE   20           408          4026          4434\nTIMING   20        568.05          2.67        570.75      10551.53\n------\nENERGY   21   2.80412E-05   2.81732E-05   6.80440E-03   6.83644E-03\nFORCES   21   7.11965E-04   7.11953E-04   2.97671E-02   2.97666E-02\nUPDATE   21           408          4012          4420\nTIMING   21        518.97          2.80        521.80      11073.33\n------\nENERGY   22   2.64661E-05   2.60412E-05   6.42221E-03   6.31908E-03\nFORCES   22   7.14539E-04   7.13341E-04   2.98747E-02   2.98246E-02\nUPDATE   22           408          4038          4446\nTIMING   22        520.31          2.72        523.07      11596.40\n------\nENERGY   23   3.66545E-05   3.65880E-05   8.89450E-03   8.87835E-03\nFORCES   23   7.05732E-04   7.05303E-04   2.95065E-02   2.94886E-02\nUPDATE   23           408          4078          4486\nTIMING   23        526.46          3.31        529.80      12126.21\n------\nENERGY   24   3.00251E-05   2.86382E-05   7.28581E-03   6.94926E-03\nFORCES   24   7.05073E-04   7.02898E-04   2.94790E-02   2.93880E-02\nUPDATE   24           408          3989          4397\nTIMING   24        515.17          2.68        517.87      12644.08\n------\nENERGY   25   3.24461E-05   3.15622E-05   7.87329E-03   7.65879E-03\nFORCES   25   7.06710E-04   7.05342E-04   2.95474E-02   2.94902E-02\nUPDATE   25           408          4053          4461\nTIMING   25        523.39          3.60        527.02      13171.10\n*******************************************************************************\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3/hdnnp-data/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3/hdnnp-data/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.2539155865352127E+00 a         1     0     1     1     1\n  2.2490365890661286E+00 a         2     0     1     1     2\n  4.9361851928374572E+00 a         3     0     1     1     3\n -2.3971991574908125E+00 a         4     0     1     1     4\n -1.8596992303156465E+00 a         5     0     1     1     5\n  3.8287764168815897E+00 a         6     0     1     1     6\n  7.4523181738636106E+00 a         7     0     1     1     7\n  6.0971861116881998E+00 a         8     0     1     1     8\n -8.7239359226117639E+00 a         9     0     1     1     9\n -1.8255232070184267E+01 a        10     0     1     1    10\n -7.8065643887610179E+00 a        11     0     1     1    11\n  1.4247237398130265E+01 a        12     0     1     1    12\n -3.2217879518334338E+00 a        13     0     1     1    13\n -5.7395252086520712E+00 a        14     0     1     1    14\n  2.0353040522911576E+00 a        15     0     1     1    15\n  7.7520578160630560E+00 a        16     0     1     1    16\n  2.9357257867412252E+00 a        17     0     1     1    17\n -2.9719860930100790E+00 a        18     0     1     1    18\n  8.9245382590288980E+00 a        19     0     1     1    19\n  6.6848134049442169E+00 a        20     0     1     1    20\n -2.2992719903495891E+00 a        21     0     1     1    21\n -1.4401533482181721E+01 a        22     0     1     1    22\n -2.0574070545285186E+00 a        23     0     1     1    23\n -6.3544667277888678E+00 a        24     0     1     1    24\n  3.9668360525851707E+00 a        25     0     1     1    25\n  1.0930597297534963E+01 a        26     0     2     1     1\n  3.0058866618169424E+00 a        27     0     2     1     2\n -4.9950943102999927E+00 a        28     0     2     1     3\n -1.9930957240687266E+00 a        29     0     2     1     4\n  1.6790893133342006E+00 a        30     0     2     1     5\n -4.5254006136507128E+00 a        31     0     2     1     6\n -9.6165021729265252E+00 a        32     0     2     1     7\n -8.7465722730176285E+00 a        33     0     2     1     8\n  1.5506950040431201E+01 a        34     0     2     1     9\n  2.1903342918227118E+01 a        35     0     2     1    10\n -1.0685216745153280E+01 a        36     0     2     1    11\n -2.5859690636594280E+01 a        37     0     2     1    12\n -3.2423603491405122E+00 a        38     0     2     1    13\n  5.3753900550878555E+00 a        39     0     2     1    14\n -3.0291935617567991E+00 a        40     0     2     1    15\n -1.3534893178408465E+01 a        41     0     2     1    16\n -5.7625138055631471E+00 a        42     0     2     1    17\n  1.0216765318459601E+01 a        43     0     2     1    18\n -1.4416012930050949E+01 a        44     0     2     1    19\n -4.7226757471872144E-01 a        45     0     2     1    20\n  7.8981385188798026E+00 a        46     0     2     1    21\n  1.2202710023744410E+00 a        47     0     2     1    22\n  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7.2770779951192111E-01 a      1141     1    18     2    16\n  1.7348650121938709E+00 a      1142     1    18     2    17\n  7.2380729647406006E-01 a      1143     1    18     2    18\n -2.1671682060080908E+00 a      1144     1    18     2    19\n -1.8448084445689281E-01 a      1145     1    18     2    20\n  1.3024719111160912E+00 a      1146     1    18     2    21\n -1.2909789979215052E+00 a      1147     1    18     2    22\n -2.0330008356136617E+00 a      1148     1    18     2    23\n -3.5287322032224533E-01 a      1149     1    18     2    24\n -4.4414575257293076E-01 a      1150     1    18     2    25\n -2.7258373164925753E-02 a      1151     1    19     2     1\n  1.7786409180863971E+00 a      1152     1    19     2     2\n -6.2433485311638581E-01 a      1153     1    19     2     3\n -7.0729056795105427E-01 a      1154     1    19     2     4\n  5.1264534381277294E-01 a      1155     1    19     2     5\n -8.6616294143739847E-01 a      1156     1    19     2     6\n  8.0698814912956451E-01 a      1157     1    19     2     7\n -1.8175081356783283E+00 a      1158     1    19     2     8\n -3.2026939775244762E-01 a      1159     1    19     2     9\n -6.7288331966478787E-01 a      1160     1    19     2    10\n  1.7148578091095124E-01 a      1161     1    19     2    11\n  3.2140265958315151E-01 a      1162     1    19     2    12\n -8.1210044120660096E-01 a      1163     1    19     2    13\n -7.6231158138043847E-02 a      1164     1    19     2    14\n -1.5851767882039058E+00 a      1165     1    19     2    15\n  1.2557130027742122E-01 a      1166     1    19     2    16\n  4.8654065981248962E-01 a      1167     1    19     2    17\n  9.1550158332637088E-01 a      1168     1    19     2    18\n  1.7945138007319117E+00 a      1169     1    19     2    19\n -6.2793744117252037E-01 a      1170     1    19     2    20\n  4.9770901971481168E-01 a      1171     1    19     2    21\n  7.9199978603495880E-01 a      1172     1    19     2    22\n  1.3566279316779111E+00 a      1173     1    19     2    23\n -6.4989908124401896E-01 a      1174     1    19     2    24\n -1.2130061691278531E+00 a      1175     1    19     2    25\n  2.1718589739533791E+00 a      1176     1    20     2     1\n  2.9938291414473661E-01 a      1177     1    20     2     2\n  9.2914772861453521E-01 a      1178     1    20     2     3\n  1.7565171250248528E+00 a      1179     1    20     2     4\n -1.7171376009305626E+00 a      1180     1    20     2     5\n  2.8704512164424800E+00 a      1181     1    20     2     6\n -4.0609063853165461E-01 a      1182     1    20     2     7\n -8.8956304852711987E-01 a      1183     1    20     2     8\n  1.5588822278177381E+00 a      1184     1    20     2     9\n -5.3859945323628011E-01 a      1185     1    20     2    10\n -8.9087250387841876E-01 a      1186     1    20     2    11\n -8.9835382331213787E-01 a      1187     1    20     2    12\n -1.1369908152037626E-01 a      1188     1    20     2    13\n -5.7966570046060373E-01 a      1189     1    20     2    14\n  1.1066980646243854E+00 a      1190     1    20     2    15\n  3.1244375834572546E-01 a      1191     1    20     2    16\n  2.1974097139332476E+00 a      1192     1    20     2    17\n -7.6349397720541767E-01 a      1193     1    20     2    18\n -3.6503418073743810E-01 a      1194     1    20     2    19\n -6.0642338824938813E-01 a      1195     1    20     2    20\n  2.2802643907348267E-02 a      1196     1    20     2    21\n  8.3743733952396715E-01 a      1197     1    20     2    22\n -3.9872923910188316E+00 a      1198     1    20     2    23\n -3.3066587159099775E-01 a      1199     1    20     2    24\n -3.3827603813335005E-01 a      1200     1    20     2    25\n  2.0707890624068246E+00 a      1201     1    21     2     1\n  8.1792094222389677E-01 a      1202     1    21     2     2\n  1.0420587694448914E-01 a      1203     1    21     2     3\n  3.8654442605274053E-01 a      1204     1    21     2     4\n -1.0273245523110555E+00 a      1205     1    21     2     5\n  4.8026156110006928E-02 a      1206     1    21     2     6\n -1.2317220364565722E+00 a      1207     1    21     2     7\n -9.2171220979112878E-01 a      1208     1    21     2     8\n -8.3293051813215280E-01 a      1209     1    21     2     9\n  3.7826002267822101E-01 a      1210     1    21     2    10\n -1.2566916573054130E+00 a      1211     1    21     2    11\n -1.4542331491456711E-01 a      1212     1    21     2    12\n -1.0890378021893508E+00 a      1213     1    21     2    13\n -5.8298836953764355E-01 a      1214     1    21     2    14\n -1.9020824106971643E+00 a      1215     1    21     2    15\n  4.4353810152599149E-01 a      1216     1    21     2    16\n -2.9928311527046703E-01 a      1217     1    21     2    17\n -7.7527928990984052E-01 a      1218     1    21     2    18\n  2.6159175407438195E-01 a      1219     1    21     2    19\n -2.6604337400489050E-02 a      1220     1    21     2    20\n -4.6552795168897604E-01 a      1221     1    21     2    21\n  1.1611386377657384E+00 a      1222     1    21     2    22\n -1.2972265245341139E+00 a      1223     1    21     2    23\n  1.8117173751313085E+00 a      1224     1    21     2    24\n  1.0433495561237927E+00 a      1225     1    21     2    25\n  1.5410314634266913E+00 a      1226     1    22     2     1\n  6.6201420998527072E-01 a      1227     1    22     2     2\n  1.1189293597068475E+00 a      1228     1    22     2     3\n -1.1536147566508355E+00 a      1229     1    22     2     4\n -8.4859080711662893E-01 a      1230     1    22     2     5\n  3.7903158089014494E-01 a      1231     1    22     2     6\n -2.6461659405296234E+00 a      1232     1    22     2     7\n  2.2472472042954434E+00 a      1233     1    22     2     8\n -9.2281733258289744E-01 a      1234     1    22     2     9\n  8.7312141982063785E-01 a      1235     1    22     2    10\n -4.3593190134289528E-01 a      1236     1    22     2    11\n  5.1912574126564559E-01 a      1237     1    22     2    12\n -5.9029854481930821E-01 a      1238     1    22     2    13\n -7.2255183403800793E-01 a      1239     1    22     2    14\n  4.1024670935059383E-02 a      1240     1    22     2    15\n  2.0425371936604741E-01 a      1241     1    22     2    16\n -1.0394832812330597E+00 a      1242     1    22     2    17\n  4.7202219372950349E-01 a      1243     1    22     2    18\n -1.9958648332222221E-03 a      1244     1    22     2    19\n -1.4664186611455649E-02 a      1245     1    22     2    20\n  1.0689476163444707E+00 a      1246     1    22     2    21\n  8.4484833020425232E-01 a      1247     1    22     2    22\n -1.4147373614558330E+00 a      1248     1    22     2    23\n  1.9187324467269602E+00 a      1249     1    22     2    24\n  1.5330124676330812E+00 a      1250     1    22     2    25\n  2.3019050197742894E+00 a      1251     1    23     2     1\n -1.3828322911066271E-01 a      1252     1    23     2     2\n -2.3555430378419923E-01 a      1253     1    23     2     3\n -1.3434989779696097E-01 a      1254     1    23     2     4\n  3.7852663531566189E-01 a      1255     1    23     2     5\n  9.8266847359694973E-02 a      1256     1    23     2     6\n  3.2721968443206462E-01 a      1257     1    23     2     7\n -3.7061171550241617E-01 a      1258     1    23     2     8\n  2.2862436245090851E+00 a      1259     1    23     2     9\n  1.7674065728047832E+00 a      1260     1    23     2    10\n -5.2627257197444939E-02 a      1261     1    23     2    11\n  9.4094481148145870E-01 a      1262     1    23     2    12\n  1.0616552648143298E+00 a      1263     1    23     2    13\n -1.6065739188681796E-01 a      1264     1    23     2    14\n  1.6833160475834315E+00 a      1265     1    23     2    15\n -5.5679530352182072E-01 a      1266     1    23     2    16\n  4.2170082515325280E-01 a      1267     1    23     2    17\n  1.8142946234467967E+00 a      1268     1    23     2    18\n -6.0004075552166369E-01 a      1269     1    23     2    19\n  8.6767695096505049E-01 a      1270     1    23     2    20\n  1.7471709925670367E-01 a      1271     1    23     2    21\n  6.3494817986861019E-01 a      1272     1    23     2    22\n  7.9839233743975266E-02 a      1273     1    23     2    23\n -8.7497499907984810E-01 a      1274     1    23     2    24\n -2.1279336414401262E-01 a      1275     1    23     2    25\n -1.0628518357816100E+01 a      1276     1    24     2     1\n -3.4149879843865938E-01 a      1277     1    24     2     2\n -4.0534872173827868E-01 a      1278     1    24     2     3\n  1.0980204380257913E-01 a      1279     1    24     2     4\n  1.8376924276804879E-01 a      1280     1    24     2     5\n  8.5047887536146360E-01 a      1281     1    24     2     6\n  4.3913590571042438E-01 a      1282     1    24     2     7\n  2.7167430357232609E+00 a      1283     1    24     2     8\n  2.9682659556600960E-01 a      1284     1    24     2     9\n -1.6032245851281013E+00 a      1285     1    24     2    10\n -6.7567048640865046E-01 a      1286     1    24     2    11\n -1.5253382251900995E+00 a      1287     1    24     2    12\n -6.7540631566041298E-01 a      1288     1    24     2    13\n -1.4565321192168545E+00 a      1289     1    24     2    14\n -1.3315414628143039E+00 a      1290     1    24     2    15\n  1.2552098425264056E+00 a      1291     1    24     2    16\n -1.1701558601459501E+00 a      1292     1    24     2    17\n  2.1967564647703792E+00 a      1293     1    24     2    18\n  3.6767594091430167E-01 a      1294     1    24     2    19\n  1.4791781996464841E+00 a      1295     1    24     2    20\n -2.4597335939693896E+00 a      1296     1    24     2    21\n  1.8222789722776007E+00 a      1297     1    24     2    22\n -2.4818384588216302E+00 a      1298     1    24     2    23\n -1.3359962912345340E+00 a      1299     1    24     2    24\n -1.6060924344568878E-02 a      1300     1    24     2    25\n -1.1558703878945702E+00 a      1301     1    25     2     1\n  5.5859771317693908E-02 a      1302     1    25     2     2\n -1.9275021348316721E+00 a      1303     1    25     2     3\n  4.2881321046205173E-01 a      1304     1    25     2     4\n  6.6308764508018558E-01 a      1305     1    25     2     5\n -2.5357661809360188E-01 a      1306     1    25     2     6\n  7.7965409617466697E-01 a      1307     1    25     2     7\n -1.9470416731652336E+00 a      1308     1    25     2     8\n  2.0923659915641873E-01 a      1309     1    25     2     9\n  8.9211452410465542E-01 a      1310     1    25     2    10\n -1.9807939822570442E-01 a      1311     1    25     2    11\n -5.0922943173038127E-01 a      1312     1    25     2    12\n  1.3378430979044107E+00 a      1313     1    25     2    13\n -6.8964614083753073E-01 a      1314     1    25     2    14\n  7.6939619343191556E-01 a      1315     1    25     2    15\n -1.5783243312480257E+00 a      1316     1    25     2    16\n  2.3586020281744577E+00 a      1317     1    25     2    17\n -5.1641666185758928E-01 a      1318     1    25     2    18\n  1.0291540870545792E+00 a      1319     1    25     2    19\n  1.5269830348487650E+00 a      1320     1    25     2    20\n -2.8987700591417855E+00 a      1321     1    25     2    21\n  9.0207337792476916E-01 a      1322     1    25     2    22\n  1.9890049402284911E+00 a      1323     1    25     2    23\n  3.9387622927433424E-01 a      1324     1    25     2    24\n  9.9397126232482103E-01 a      1325     1    25     2    25\n  2.5306467041996967E+00 b      1326     2     1\n  3.1633393474977245E+00 b      1327     2     2\n -1.1644295509710691E+00 b      1328     2     3\n -5.7686722641223600E+00 b      1329     2     4\n  2.0065022303893989E+00 b      1330     2     5\n -5.9106057000795840E+00 b      1331     2     6\n -1.1326093285804056E+01 b      1332     2     7\n -3.9025063397327071E+00 b      1333     2     8\n  4.4520505166676267E+00 b      1334     2     9\n -1.7352681951318241E+00 b      1335     2    10\n -2.1518912430432668E+00 b      1336     2    11\n  5.0463376560082969E+00 b      1337     2    12\n -2.2614514173852837E-01 b      1338     2    13\n -4.1454590614747211E+00 b      1339     2    14\n  1.6688417293495756E+00 b      1340     2    15\n -5.8649976938793378E+00 b      1341     2    16\n -3.8350084459541849E+00 b      1342     2    17\n  1.3730477223722950E+00 b      1343     2    18\n  1.8506935712854127E+00 b      1344     2    19\n  5.7362757779153428E+00 b      1345     2    20\n  7.2901484895568780E+00 b      1346     2    21\n  3.9773783666446022E-01 b      1347     2    22\n -6.1298011242151409E+00 b      1348     2    23\n  9.9698755072742991E+00 b      1349     2    24\n  1.1801564149295556E+00 b      1350     2    25\n  1.2704098997067026E+01 a      1351     2     1     3     1\n  1.5947733940307620E+00 a      1352     2     2     3     1\n -1.6022927057878529E+00 a      1353     2     3     3     1\n -1.5507258540777733E+00 a      1354     2     4     3     1\n  1.8696884022727636E+00 a      1355     2     5     3     1\n -8.2051908880071633E-01 a      1356     2     6     3     1\n  9.4325719092522542E-01 a      1357     2     7     3     1\n  2.4098435369626174E+00 a      1358     2     8     3     1\n  1.4100759633042474E+00 a      1359     2     9     3     1\n -1.4613034838529613E+00 a      1360     2    10     3     1\n  1.0296574685193380E+00 a      1361     2    11     3     1\n  1.2413851904356363E+00 a      1362     2    12     3     1\n -6.3168181712211169E-01 a      1363     2    13     3     1\n  7.6424175125347729E+00 a      1364     2    14     3     1\n -1.3477038299214714E+00 a      1365     2    15     3     1\n -1.6064659765754943E+00 a      1366     2    16     3     1\n -8.9624380518145874E-01 a      1367     2    17     3     1\n -1.0509865792522375E+00 a      1368     2    18     3     1\n  8.1847872933853638E-01 a      1369     2    19     3     1\n  1.2845504810303034E+00 a      1370     2    20     3     1\n -5.1879822944368881E-01 a      1371     2    21     3     1\n -7.2018714033119180E-01 a      1372     2    22     3     1\n  5.9870832883780798E+00 a      1373     2    23     3     1\n -6.0589155387470683E-01 a      1374     2    24     3     1\n  5.0177609140285355E+00 a      1375     2    25     3     1\n  9.7386086372975722E+00 b      1376     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3/hdnnp-data/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -4.2252995889643252E-01 a         1     0     1     1     1\n -6.0555645962054347E+00 a         2     0     1     1     2\n  1.4040722027928377E+01 a         3     0     1     1     3\n -2.7041370011942618E+00 a         4     0     1     1     4\n -3.8202743208058858E+00 a         5     0     1     1     5\n -3.3612643261393358E+00 a         6     0     1     1     6\n -2.0418101025905258E+00 a         7     0     1     1     7\n  7.5707237340996727E+00 a         8     0     1     1     8\n -5.8098755815926548E+00 a         9     0     1     1     9\n -6.0966886893925210E-01 a        10     0     1     1    10\n  5.8061564015115206E+00 a        11     0     1     1    11\n -1.5509339733099867E+00 a        12     0     1     1    12\n  1.9747395485200818E+00 a        13     0     1     1    13\n  4.5260782279680539E-01 a        14     0     1     1    14\n  9.9210415760283279E+00 a        15     0     1     1    15\n -6.5078831481547121E+00 a        16     0     1     1    16\n -3.4768832871318085E+00 a        17     0     1     1    17\n -1.9463994340943838E+00 a        18     0     1     1    18\n -3.4186058699290269E+00 a        19     0     1     1    19\n  1.2263643166698479E+00 a        20     0     1     1    20\n -5.9171161834436594E+00 a        21     0     1     1    21\n  1.8436267358458363E+00 a        22     0     1     1    22\n -2.3139530616378448E+00 a        23     0     1     1    23\n -1.7228542411478951E+01 a        24     0     1     1    24\n  2.2888610253215895E+00 a        25     0     1     1    25\n  8.0819405565169262E+00 a        26     0     2     1     1\n  8.0066409422078735E+00 a        27     0     2     1     2\n -2.8439251469462398E+01 a        28     0     2     1     3\n -1.1146087290797917E+01 a        29     0     2     1     4\n -7.5292172093563314E+00 a        30     0     2     1     5\n -4.0783685663337641E+00 a        31     0     2     1     6\n 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1.1965703107989687E+00 a      1365     1    24     2    15\n -4.8078015734066326E-01 a      1366     1    24     2    16\n  2.8731897539798784E-01 a      1367     1    24     2    17\n  2.8943049077679879E+00 a      1368     1    24     2    18\n  4.4309374097560666E-01 a      1369     1    24     2    19\n -5.2571668466848664E-01 a      1370     1    24     2    20\n  2.6293009755349539E+00 a      1371     1    24     2    21\n  1.1166360248787797E+00 a      1372     1    24     2    22\n  1.4367909042068954E+00 a      1373     1    24     2    23\n  1.2263949730702137E+00 a      1374     1    24     2    24\n -1.5658327417588482E+00 a      1375     1    24     2    25\n -3.0524380712257440E+00 a      1376     1    25     2     1\n -1.6248402538917406E-01 a      1377     1    25     2     2\n  5.3725239557723847E-01 a      1378     1    25     2     3\n -3.1435543583372311E-01 a      1379     1    25     2     4\n  8.0294309812719877E-01 a      1380     1    25     2     5\n -3.3745709161028831E-01 a      1381     1    25     2     6\n  2.9618139473335392E-01 a      1382     1    25     2     7\n -1.3606606680314999E+00 a      1383     1    25     2     8\n  2.9886863438452965E-01 a      1384     1    25     2     9\n  3.4365095196288835E+00 a      1385     1    25     2    10\n  2.8778063903425566E-01 a      1386     1    25     2    11\n -5.2312889094867954E-01 a      1387     1    25     2    12\n  4.5730896273705224E-01 a      1388     1    25     2    13\n -8.8949447500584955E-01 a      1389     1    25     2    14\n -8.1389897744929640E-01 a      1390     1    25     2    15\n -4.0077086298379117E-01 a      1391     1    25     2    16\n  7.2544627916775950E-01 a      1392     1    25     2    17\n -9.8029709488119798E-01 a      1393     1    25     2    18\n  8.5017837869712165E-01 a      1394     1    25     2    19\n -2.9795775527520296E-01 a      1395     1    25     2    20\n  1.1940911570260535E+00 a      1396     1    25     2    21\n -4.1259772504588357E-02 a      1397     1    25     2    22\n  1.0619824936744515E+00 a      1398     1    25     2    23\n -6.5325825341918264E-01 a      1399     1    25     2    24\n  3.7575240210802421E+00 a      1400     1    25     2    25\n -1.0787018434494783E+01 b      1401     2     1\n -8.4067078142086771E-01 b      1402     2     2\n  9.3201271110229211E-01 b      1403     2     3\n -1.8318272256547821E+00 b      1404     2     4\n -2.1732436845179119E+00 b      1405     2     5\n -2.6390929073478930E+00 b      1406     2     6\n  3.7489748853957300E-01 b      1407     2     7\n -2.3789675524866163E+00 b      1408     2     8\n  2.7252644932624959E+00 b      1409     2     9\n  2.5100559841854970E+00 b      1410     2    10\n -2.4897033671113025E-01 b      1411     2    11\n  2.6913296692082476E+00 b      1412     2    12\n  5.8162695990329221E+00 b      1413     2    13\n -1.5170700889568940E+00 b      1414     2    14\n  4.2121259244130220E+00 b      1415     2    15\n  2.2987725066596130E+00 b      1416     2    16\n -7.1493650128731911E-01 b      1417     2    17\n -3.9961443472349811E-01 b      1418     2    18\n  7.8083705485664430E+00 b      1419     2    19\n -4.0462773256448170E-01 b      1420     2    20\n -1.4333029489891109E+00 b      1421     2    21\n -4.9517224038431467E+00 b      1422     2    22\n  1.0702867307710989E+01 b      1423     2    23\n -9.7535853921453985E-01 b      1424     2    24\n  5.3161969295054172E+00 b      1425     2    25\n -5.1941647295982207E-01 a      1426     2     1     3     1\n -7.7346657642095373E-01 a      1427     2     2     3     1\n  1.4003893583106508E+00 a      1428     2     3     3     1\n  8.9188080044914464E-01 a      1429     2     4     3     1\n -2.0147808233792022E+00 a      1430     2     5     3     1\n -1.8131831735812174E+00 a      1431     2     6     3     1\n  3.3217884596641700E+00 a      1432     2     7     3     1\n -1.2675289031787327E+00 a      1433     2     8     3     1\n -1.2791140359120716E+00 a      1434     2     9     3     1\n  1.9731828075446340E+00 a      1435     2    10     3     1\n -2.3928332883234411E+00 a      1436     2    11     3     1\n -1.1755085043375486E+00 a      1437     2    12     3     1\n  2.6525670286472951E+00 a      1438     2    13     3     1\n -2.4861988521743901E+00 a      1439     2    14     3     1\n  1.2534500349238071E+00 a      1440     2    15     3     1\n  2.8804282010183990E+00 a      1441     2    16     3     1\n -2.0327745898215275E+00 a      1442     2    17     3     1\n -1.1760164122204946E+00 a      1443     2    18     3     1\n -9.9841804355412322E-01 a      1444     2    19     3     1\n -1.8663330516323837E+00 a      1445     2    20     3     1\n  6.3266049836286531E-01 a      1446     2    21     3     1\n  1.2025500357718348E+00 a      1447     2    22     3     1\n  1.1367820678861495E-01 a      1448     2    23     3     1\n -2.6481374255863193E+00 a      1449     2    24     3     1\n  5.2166795947347921E-01 a      1450     2    25     3     1\n  4.8693043186011655E+00 b      1451     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3/md.lmp",
    "content": "###############################################################################\n# MD simulation for HDNNP water\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"h2o_8640_liquid_NpT_RPBE-D3.data\"\n# Timesteps\nvariable numSteps        equal  5\nvariable dt              equal  0.0005\n# NN\nvariable hdnnpCutoff     equal  6.36\nvariable hdnnpDir        string \"hdnnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_O          equal  15.9994\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary p p p\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_H}\nmass 2 ${mass_O}\ntimestep ${dt}\nthermo 1\n\n###############################################################################\n# HDNNP\n###############################################################################\n#pair_style hdnnp/4g emap \"1:H,2:O\" dir ${hdnnpDir} showew no showewsum 5 resetew no maxew 100 cflength 1.8897261328 cfenergy 0.0367493254\npair_style hdnnp ${hdnnpCutoff} dir ${hdnnpDir} showew no showewsum 5 resetew no maxew 100 cflength 1.8897261328 cfenergy 0.0367493254\npair_coeff * * H O\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\ndump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol/hdnnp-data/input.nn",
    "content": "## #############################################################\n### This is the input file for RuNNer (version 0_44 and upwards)\n### #############################################################\n### General remarks: \n### - commands can be switched off by using the # character at the BEGINNING of the line\n### - the input file can be structured by blank lines and comment lines\n### - the order of the keywords is arbitrary\n### - if keywords are missing, default values will be used and written to runner.out\n### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message \n\n\n########################################################################################################################\n### general keywords\n########################################################################################################################\nnn_type_short 1                           # 1=Behler-Parrinello, 2=Pair NN\nrunner_mode 3                             # 1=calculate symmetry functions, 2=fitting mode, 3=predicition mode (mode)\n#debug_mode                               # debugging mode                                       (ldebug)\nparallel_mode 1                           # parallelization mode                                 (not fully implemented yet)\n#detailed_timing                          # enable detailed timing                               (lfinetime)(not fully implemented)\nnumber_of_elements 2                      # number of elements                                   (nelem)                       MODE1+2+3+4\nelements O H                              # specification of elements                            (element)                     MODE1+2+3+4\nrandom_seed 10                         # seed for initial random weight parameters and train/test splitting (iseed)         MODE1+2\nrandom_number_type 5                      # 1=ran0, 2=ran1, 3=ran2, 4=ran3\nremove_atom_energies                      # remove atomic energies before fitting                (lremoveatomenergies)         MODE1+2+3+4\natom_energy O -74.94518524                # free atom reference energy (atomic zora)\natom_energy H  -0.45890771                # free atom reference energy (atomic zora)\nenergy_threshold 100.0d0                  # energythreshold for fitting data in Ha per atom      (fitethres)                   MODE1\nbond_threshold 0.4d0                      # threshold for the shortest bond in structure         (rmin)                        MODE1+2+3\n\n########################################################################################################################\n### NN structure of the short-range NN  \n########################################################################################################################\nuse_short_nn                              # use NN for short range interactions                  (lshort) \n#global_output_nodes_short 1               # number of output nodes                               (nodes_short(num_layersshort))\nglobal_hidden_layers_short 2              # number of hidden layers                              (num_layersshort-1)\nglobal_nodes_short 25 25                  # number of nodes in hidden layers                     (nodes_short)\nglobal_activation_short t t l             # activation functions                                 (actfunc_short)\n\n#element_hidden_layers_short H 0         # set number of hidden layers for element \n#element_hidden_layers_short Zn 1         # set number of hidden layers for element \n#element_hidden_layers_short O 2          # set number of hidden layers for element\n#element_nodes_short O 1 9                # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_short O 2 8                # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_short Zn 1 7               # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_short Zn 2 6               # set number of nodes in hidden layer (order: element layer nodes)\n#element_activation_short Zn 1 1 s        # set activation function for node (order: element layer node function)\n\n########################################################################################################################\n### NN structure of the electrostatic NN  \n########################################################################################################################\n#use_electrostatic_nn                      # use NN for electrostatic interactions                (lewald)                             \n#global_output_nodes_electrostatic 1       # number of output nodes                               (nodes_ewald(num_layersewald))\n#global_hidden_layers_electrostatic 2      # number of hidden layers                              (num_layersewald-1)\n#global_nodes_electrostatic 60 60          # number of nodes in hidden layers                     (nodes_ewald)\n#global_activation_electrostatic t t l     # activation functions                                 (actfunc_ewald)\n#ewald_alpha 0.2                           # alpha for Ewald summation (ewaldalpha)! recommended (alpha 0.2/kmax 10) or (alpha 0.5/kmax >20 )\n#ewald_kmax 10                             # parameter Kmax for Ewald summation                   (ewaldkmax)\n#ewald_cutoff 19.0                         # Ewald cutoff                                         (ewaldcutoff)\n\n#element_nodes_electrostatic O 1 5        # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_electrostatic O 2 4        # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_electrostatic Zn 1 3        # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_electrostatic Zn 2 2        # set number of nodes in hidden layer (order: element layer nodes)\n#element_activation_electrostatic Zn 1 1 s # set activation function for node (order: element layer node function)\n\n########################################################################################################################\n### symmetry function generation ( mode 1): \n########################################################################################################################\n#use_atom_energies                        # use atomic energies for fitting (not implemented)    (luseatomenergies)                     MODE1+2+3+4\nuse_atom_charges                          # use atomic charges for fitting(set always true!)     (luseatomcharges)                      MODE1+2+3+4\ntest_fraction 0.1                         # threshold for splitting between fitting and test set (splitthres)                           MODE1\n#CAUTION: don't forget use_short_forces below (if you want to generate the training files for the forces)\n\n########################################################################################################################\n### symmetry function definitions (all modes): \n########################################################################################################################\n# INFO: not yet implemented in this file\n# INFO: symfunction format: reference atom, type, neighbor element 1 (and neighbor element 2), symfunction parameters \n#\n# GLOBAL SYMMETRY FUNCTIONS FOR SHORT RANGE NN\n# SAMPLE TYPE 1: global_symfunction_short 1 2.0                           ! type funccutoff \n# SAMPLE TYPE 2: global_symfunction_short 2 7.14214 0.0 11.338            ! type eta rshift funccutoff\n# SAMPLE TYPE 3: global_symfunction_short 3 0.03571 -1.0 16.0  7.55891    ! type eta lambda zeta funccutoff\n# SAMPLE TYPE 4: global_symfunction_short 4 7.14214 11.338                ! type eta funccutoff\n# SAMPLE TYPE 5: global_symfunction_short O 5 1.000                       ! central_atom type eta                         ! CARTESIAN COORDINATES \n# SAMPLE TYPE 6: global_symfunction_short O 6 11.338                      ! central_atom type funccutoff                  ! BOND LENGTH\n#\n# ELEMENT-SPECIFIC SYMMETRY FUNCTIONS FOR SHORT RANGE NN\n# SAMPLE TYPE 1: element_symfunction_short O 1 2.0                        ! central_atom type funccutoff \n# SAMPLE TYPE 2: element_symfunction_short O 2 7.14214 0.0 11.338         ! central_atom type eta rshift funccutoff\n# SAMPLE TYPE 3: element_symfunction_short O 3 0.03571 -1.0 16.0  7.55891 ! central_atom type eta lambda zeta funccutoff\n# SAMPLE TYPE 4: element_symfunction_short O 4 7.14214 11.338             ! central_atom type eta funccutoff\n# SAMPLE TYPE 5: element_symfunction_short O 5 1.000                      ! central_atom type eta                         ! CARTESIAN COORDINATES \n# SAMPLE TYPE 6: element_symfunction_short O 6 11.338                     ! central_atom type funccutoff                  ! BOND LENGTH\n#\n# CUSTOMIZED SYMMETRY FUNCTIONS FOR SHORT RANGE NN\n# SAMPLE TYPE 1: symfunction_short O 1  O 2.0                             ! central_atom type neighbor_atom funccutoff \n# SAMPLE TYPE 2: symfunction_short O 2  O 7.14214 0.0 11.338              ! central_atom type neighbor_atom eta rshift funccutoff\n# SAMPLE TYPE 3: symfunction_short O 3 Zn Zn 0.03571 -1.0 16.0  7.55891   ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n# SAMPLE TYPE 4: symfunction_short O 4  O 7.14214 11.338                  ! central_atom type neighbor_atom eta funccutoff\n# SAMPLE TYPE 5: symfunction_short O 5 1.000                              ! central_atom type eta                         ! CARTESIAN COORDIATES \n# SAMPLE TYPE 6: symfunction_short O 6  O 11.338                          ! central_atom type neighbor_atom funccutoff    ! BOND LENGTH\n\ncutoff_type 2\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.01  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.03  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.06  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.15  1.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.30  1.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.60  1.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 1.50  1.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\n#\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.01  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.03  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.06  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.15  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.30  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.60  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 1.50  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\n#\nsymfunction_short O 2 H 0.001 0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.01  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.03  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.06  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.15  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.30  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.60  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 1.50  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\n#\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.01  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.03  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.06  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.15  4.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.30  4.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.60  4.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 1.50  4.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\n#\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\n\n#\n# SYMMETRY FUNCTIONS FOR ELECTROSTATIC NN HAVE THE SAME FORMAT, BUT REPLACE \"short\" by \"electrostatic\"\n\n########################################################################################################################\n### fitting (mode 2):general inputs for short range AND electrostatic part:\n########################################################################################################################\nepochs 100                             # number of epochs                                     (nepochs)                              MODE2\npoints_in_memory 500                      # max number of structures in memory                   (nblock)                               MODE2\nmix_all_points                          # training with random order of points                 (lrandomtrain)                         MODE2\n#save_kalman_matrices                      # save Kalman filter matrices                          (lsavekalman)                          MODE2\n#read_kalman_matrices                      # restart using old Kalman filter matrices             (lrestkalman)                          MODE2\nscale_symmetry_functions                  # scale symmetry functions                             (lscalesym)                            MODE2+3+4\ncenter_symmetry_functions                 # remove center of mass of structure function values   (lcentersym)                           MODE2+3+4\n#fix_weights                               # fix some weights                                     (lfixweights)                          MODE2\n#growth_mode 11 6                          # growth mode                                          (lgrowth,ngrowth,growthstep)           MODE2\n#use_damping 0.00001d0                     # use weight decay                                     (ldampw,dampw)                         MODE2\n#pdate_single_element 8                  # do weight update just for one element                (lupdatebyelement,elemupdate)          MODE2\nfitting_unit  eV                           # unit for error output in mode 2 (eV or Ha)\n#joint_energy_force_update                  # for each atom do one update for energy and averaged forces together (not yet working well) \n\n########################################################################################################################\n### fitting options ( mode 2): short range part only:\n########################################################################################################################\noptmode_short_energy 1                     # optimization mode short range energies(optmodee, 1=Kalman filter, 2=conjugate gradient, 3=steepest descent) \noptmode_short_force 1                      # optimization mode short range forces  (optmodef, 1=Kalman filter, 2=conjugate gradient, 3=steepest descent) \nshort_energy_error_threshold 0.8\t   # threshold of adaptive Kalman filter short E          (kalmanthreshold)                      MODE2\nshort_force_error_threshold 0.8\t\t   # threshold of adaptive Kalman filter short F          (kalmanthresholdf)                     MODE2\nkalman_lambda_short 0.98000                # Kalman parameter short E/F                           (kalmanlambda)                         MODE2\nkalman_nue_short 0.99870                   # Kalman parameter short E/F                           (kalmannue)                            MODE2\n#steepest_descent_step_energy_short 0.01d0 # step size for steepest descent energy                (steepeststepe)                        MODE2\n#steepest_descent_step_force_short 0.01d0  # step size for steepest descent force                 (steepeststepf)                        MODE2\n#use_old_weights_short                     # restart fitting with old weight parameters for short (luseoldweightsshort)                  MODE2\n#update_worst_short_energies 0.1d0         # percentage of the worst energies used for update     (worste)                               MODE2\n#update_worst_short_forces 0.1d0           # percentage of the worst forces used for update       (worstf)                               MODE2\nforce_update_scaling -1.0d0               # scaling factor for the force update (negative value means automatic scaling) (scalefactorf) MODE2\n#short_energy_group 1                      # group energies for update                            (nenergygroup)                         MODE2\n#short_energy_fraction 1.00                # percentage of energies used for fitting 100%=1.0     (energyrnd)                            MODE2\nshort_force_group 1                       # group forces for update                              (nforcegroup)                          MODE2\nshort_force_fraction 0.05                  # percentage of forces used for fitting 100%=1.0       (forcernd)                             MODE2 \nuse_short_forces                           # use forces for fitting                               (luseforces)                           MODE2\n#weight_constraint H all fixed             # \"all\" switch\n#weight_constraint O interlayer 1 2 free   # \"interlayer\" layer1 layer2 switch\n#weight_constraint Zn bias 1 2 free        # \"bias layer\" node switch\n#weight_constraint Zn weight 1 3 2 3 free  # \"weight\" layer1 node1 layer2 node2 switch\n#weight_constraint Zn node 1 1 free        # \"node\" layer node switch\nweights_min -1.0                          # minimum value for initial random short range weights\nweights_max 1.0                           # maximum value for initial random short range weights\nprecondition_weights                      # precondition initial weights (lprecond)\n#normalize_nodes                           # normalize input of nodes\nrepeated_energy_update                       # calculate error of\nnguyen_widrow_weights_short              # initialize short\n\n\n########################################################################################################################\n### fitting ( mode 2): electrostatic part only:\n########################################################################################################################\n#optmode_charge 1                          # optimization mode atomic charges      (optmodeq, 1=Kalman filter, 2=conjugate gradient, 3=steepest descent)\n#charge_error_threshold 1.0          # threshold of adaptive Kalman filter charge           (kalmanthresholde)                     MODE2\n#kalman_lambda_charge 0.98000              # Kalman parameter charge                              (kalmanlambdae)                        MODE2\n#kalman_nue_charge 0.99870                 # Kalman parameter charge                              (kalmannuee)                           MODE2\n#steepest_descent_step_charge 0.01d0       # step size for steepest descent charge                (steepeststepq)                        MODE2\n#use_old_weights_charge                    # restart fitting with old weight parameters for charge(luseoldweightscharge)                 MODE2\n#update_worst_charges 0.1d0                # percentage of the worst charges used for update      (worstq)                               MODE2\n#charge_group 20                            # group charges for update                             (nchargegroup)                         MODE2\n#charge_fraction 1.00                      # percentage of charges used for fitting 100%=1.0      (chargernd)                            MODE2\n#weighte_constraint O all fixed              # \"all\" switch\n#weighte_constraint O interlayer 1 2 free    # \"interlayer\" layer1 layer2 switch\n#weighte_constraint Zn bias 1 2 free          # \"bias layer\" node switch\n#weighte_constraint Zn weight 1 3 2 3 free    # \"weight\" layer1 node1 layer2 node2 switch\n#weighte_constraint Zn node 2 1 free          # \"node\" layer node switch\n#precondition_weights                      # precondition initial weights (lprecond)\n#nguyen_widrow_weights_ewald              # initialize short\n#weightse_min -1.0                          # minimum value for initial random charge weights\n#weightse_max 1.0                           # maximum value for initial random charge weights\n\n########################################################################################################################\n### options for charge constraint in mode 2 (not tested! not parallel!)\n########################################################################################################################\n#use_charge_constraint                     # use total charge constraint                          (lchargeconstraint)                    MODE2\n#total_charge_error_threshold 0.0000001    # threshold of adaptive Kalman filter charge constraint(kalmanthresholdc)                     MODE2\n#kalman_lambda_charge_constraint 0.98000   # Kalman parameter charge constraint                   (kalmanlambdac)                        MODE2\n#kalman_nue_charge_constraint 0.99870      # Kalman parameter charge constraint                   (kalmannuec)                           MODE2\n\n########################################################################################################################\n### output options for mode 2 (fitting):  \n########################################################################################################################\n#write_weights_epoch 1                     # write set of weight parameters every ith epoch       (iwriteweight)                         MODE2\n#write_temporary_weights                   # write temporary weights each data block              (lwritetmpweights)                     MODE2\n#write_trainpoints                         # write trainpoints.out and testpoints.out files       (lwritetrainpoints)                    MODE2\n#write_traincharges                        # write traincharges.out and testcharges.out files     (lwritetraincharges)                   MODE2\n#write_trainforces                         # write trainforces.out and testforces.out files       (lwritetrainforces)                    MODE2\n\n########################################################################################################################\n### output options for mode 3 (prediction):  \n########################################################################################################################\ncalculate_forces                          # calculate forces                                     (ldoforces)                            MODE3\n#calculate_stress                          # calculate stress                                     (ldostress)(not fully implemented)     MODE3\n#write_pdb                                 # write predicted structure in pdb format              (lwritepdb)                            MODE3\n#write_xyz                                 # write predicted structure in xyz format              (lwritexyz)                            MODE3\n#write_pov                                 # write predicted structure in pov format              (lwritepov)                            MODE3\n#write_pwscf                               # write predicted structure in pwscf format            (lwritepw)                             MODE3\n\n########################################################################################################################\n### output options for debug.out file  \n########################################################################################################################\n#print_all_short_weights\n#print_all_electrostatic_weights\n\n########################################################################################################################\n### options for mode 4 (not yet working)\n########################################################################################################################\n#symfunction_check_threshold 0.001d0       # threshold for symmetry function check                (symthres)                             MODE4\n#charge_check_threshold 0.0002d0           # threshold for atomic charge check                    (chargethres)                          MODE4\n#force_check_threshold 0.0003d0            # threshold for atomic force check                     (forcethres)                           MODE4\n#energy_check_threshold 0.0004d0           # threshold for atomic energy check                    (energythres)(not yet implemented)     MODE4\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol/hdnnp-data/scaling.data",
    "content": "   1    1        1.088201664       9.616641912       2.270109565\n   1    2        0.732744389       5.002855932       1.327702465\n   1    3        0.760107838       7.142794297       1.647742147\n   1    4        0.548422859       3.766177117       1.016703770\n   1    5        0.400806651       4.146983240       0.909602933\n   1    6        0.362093522       2.267823940       0.649481595\n   1    7        0.189191039       2.229265268       0.457092189\n   1    8        0.267041787       1.320874236       0.424021804\n   1    9        0.245130998       0.947511607       0.362454975\n   1   10        0.222489101       2.759621601       0.539082969\n   1   11        0.147436017       0.555992707       0.267708440\n   1   12        0.099110926       1.726540533       0.295581816\n   1   13        0.065093699       0.345217577       0.185155535\n   1   14        0.031653527       0.912931701       0.150225678\n   1   15        0.002920282       0.264539818       0.076473362\n   1   16        0.000321454       0.286964256       0.045764109\n   1   17        0.000246938       0.138487311       0.017696446\n   1   18        0.005099284       0.583191737       0.023872131\n   1   19        0.000322830       0.216139623       0.017077760\n   1   20        0.049647513       1.685161743       0.145479047\n   1   21        0.003407347       0.316370718       0.018433754\n   1   22        0.000131214       0.102583489       0.006372278\n   1   23        0.033813163       0.916185609       0.081291971\n   1   24        0.000417085       0.157859670       0.004669432\n   1   25        0.000735289       0.059225627       0.003705331\n   1   26        0.008982833       0.194260856       0.024091451\n   1   27        0.000212280       0.008777781       0.002053455\n   2    1        1.517044076      10.005711989       2.655404931\n   2    2        0.446766389       4.619540936       0.966350390\n   2    3        1.193931096       7.532354409       2.033407541\n   2    4        0.275760365       3.386213103       0.659640224\n   2    5        0.821855400       4.535648125       1.298963189\n   2    6        0.105170538       1.890987754       0.306914986\n   2    7        0.569491417       2.615432862       0.848043608\n   2    8        0.025104990       0.936410342       0.111481479\n   2    9        0.513541617       1.854534178       0.724909950\n   2   10        0.118789489       2.912145690       0.475036427\n   2   11        0.352693173       1.062836509       0.535416881\n   2   12        0.030424314       2.527764277       0.316746678\n   2   13        0.159800227       0.631218183       0.370311070\n   2   14        0.002786809       2.303005782       0.177515943\n   2   15        0.009564104       0.390852331       0.152946724\n   2   16        0.000003880       2.036706882       0.054190131\n   2   17        0.002472623       0.343354006       0.016697369\n   2   18        0.000022353       0.056319317       0.000955763\n   2   19        0.054785372       3.018259758       0.204054793\n   2   20        0.001379524       0.498788004       0.012802849\n   2   21        0.006685277       0.267395828       0.030865481\n   2   22        0.017021399       1.416779651       0.076329790\n   2   23        0.019759832       0.407563783       0.048851573\n   2   24        0.000592976       0.233240507       0.007212399\n   2   25        0.000011145       0.035285773       0.000426102\n   2   26        0.017309321       0.822454100       0.050874152\n   2   27        0.004098051       0.785570314       0.036954443\n   2   28        0.000040524       0.098448069       0.001213796\n   2   29        0.006037465       0.098674752       0.016153531\n   2   30        0.002959549       0.154785376       0.011643250\n       -0.2378336387       -0.1948975729\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol/hdnnp-data/weights.001.data",
    "content": "     -0.7927042964 a         1     0     1     1     1\n     -0.1198851087 a         2     0     1     1     2\n      0.0543859814 a         3     0     1     1     3\n     -0.3213507434 a         4     0     1     1     4\n      0.9947283385 a         5     0     1     1     5\n     -0.0507052725 a         6     0     1     1     6\n      0.4930137902 a         7     0     1     1     7\n      0.2457216581 a         8     0     1     1     8\n      0.0396945776 a         9     0     1     1     9\n     -0.3667600593 a        10     0     1     1    10\n      0.9819342066 a        11     0     1     1    11\n     -2.5033297964 a        12     0     1     1    12\n      0.3533671770 a        13     0     1     1    13\n      0.8870651689 a        14     0     1     1    14\n      0.1737131510 a        15     0     1     1    15\n      0.1049435511 a        16     0     1     1    16\n      0.5760697997 a        17     0     1     1    17\n     -0.2746380133 a        18   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  36     0     2     1    11\n      2.3893080188 a        37     0     2     1    12\n      0.4220726777 a        38     0     2     1    13\n     -0.3084783109 a        39     0     2     1    14\n     -0.5397392775 a        40     0     2     1    15\n     -0.0861465591 a        41     0     2     1    16\n     -0.7317585970 a        42     0     2     1    17\n      0.9087828216 a        43     0     2     1    18\n      0.0865205926 a        44     0     2     1    19\n      1.0878175778 a        45     0     2     1    20\n      0.1834980475 a        46     0     2     1    21\n      0.1189143167 a        47     0     2     1    22\n     -0.9158509039 a        48     0     2     1    23\n     -0.3101482477 a        49     0     2     1    24\n     -0.0137187960 a        50     0     2     1    25\n      1.1182741670 a        51     0     3     1     1\n     -0.4888691766 a        52     0     3     1     2\n     -0.1086332442 a        53     0     3     1     3\n     -0.5134586014 a        54     0     3     1     4\n     -0.0057520752 a        55     0     3     1     5\n      0.3066541236 a        56     0     3     1     6\n     -0.0484807758 a        57     0     3     1     7\n      0.2401205472 a        58     0     3     1     8\n     -0.4227675745 a        59     0     3     1     9\n      1.3328495997 a        60     0     3     1    10\n     -0.5334636802 a        61     0     3     1    11\n     -0.5992628199 a        62     0     3     1    12\n      0.8085682112 a        63     0     3     1    13\n      0.6180749319 a        64     0     3     1    14\n      0.8070953921 a        65     0     3     1    15\n     -0.5343615213 a        66     0     3     1    16\n      0.7746093862 a        67     0     3     1    17\n      0.2386220441 a        68     0     3     1    18\n      0.1311285270 a        69     0     3     1    19\n     -0.5274542195 a        70     0     3     1    20\n      0.0941941293 a        71     0     3     1    21\n     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14\n      0.3957786185 a        90     0     4     1    15\n     -0.2757012873 a        91     0     4     1    16\n     -1.1671968770 a        92     0     4     1    17\n      0.4498673301 a        93     0     4     1    18\n      0.3219881887 a        94     0     4     1    19\n      1.1560311040 a        95     0     4     1    20\n      1.0517279568 a        96     0     4     1    21\n      1.5859444628 a        97     0     4     1    22\n      0.6165257833 a        98     0     4     1    23\n      0.9164424251 a        99     0     4     1    24\n     -0.1549103257 a       100     0     4     1    25\n      0.8878136706 a       101     0     5     1     1\n      0.6683308831 a       102     0     5     1     2\n      0.2636251772 a       103     0     5     1     3\n      1.3024585424 a       104     0     5     1     4\n      0.8710929943 a       105     0     5     1     5\n      0.3952247481 a       106     0     5     1     6\n      0.1457163533 a       107     0     5   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   5     1    25\n     -0.3028891873 a       126     0     6     1     1\n     -0.8329314284 a       127     0     6     1     2\n      0.8506980855 a       128     0     6     1     3\n     -1.6895212572 a       129     0     6     1     4\n     -1.4546910921 a       130     0     6     1     5\n     -1.0894395769 a       131     0     6     1     6\n     -0.6978770245 a       132     0     6     1     7\n     -0.3523398542 a       133     0     6     1     8\n     -0.1313112867 a       134     0     6     1     9\n      1.5117762774 a       135     0     6     1    10\n      0.0267964310 a       136     0     6     1    11\n      1.4263493593 a       137     0     6     1    12\n      1.2091063301 a       138     0     6     1    13\n      0.0348753715 a       139     0     6     1    14\n      0.3699989564 a       140     0     6     1    15\n     -0.0069224822 a       141     0     6     1    16\n      1.6788783580 a       142     0     6     1    17\n     -0.5572515265 a       143     0     6     1    18\n      0.7130554672 a       144     0     6     1    19\n      0.0229312689 a       145     0     6     1    20\n     -0.7751561912 a       146     0     6     1    21\n      0.5640449208 a       147     0     6     1    22\n      0.2943062733 a       148     0     6     1    23\n     -0.5124900099 a       149     0     6     1    24\n     -0.5888956181 a       150     0     6     1    25\n     -0.4897411297 a       151     0     7     1     1\n      0.1655134237 a       152     0     7     1     2\n      0.5755404586 a       153     0     7     1     3\n     -0.3279181156 a       154     0     7     1     4\n     -0.3664511641 a       155     0     7     1     5\n      0.0389093563 a       156     0     7     1     6\n      0.2228809011 a       157     0     7     1     7\n     -0.0976622814 a       158     0     7     1     8\n      0.8774557366 a       159     0     7     1     9\n     -0.3252636084 a       160     0     7     1    10\n     -0.2534172404 a    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1.5421154504 a       179     0     8     1     4\n      1.4099032448 a       180     0     8     1     5\n     -0.7264449033 a       181     0     8     1     6\n      0.4691643687 a       182     0     8     1     7\n     -0.4840883213 a       183     0     8     1     8\n     -0.5423218633 a       184     0     8     1     9\n     -0.1180396293 a       185     0     8     1    10\n      1.2161661752 a       186     0     8     1    11\n      0.1583151175 a       187     0     8     1    12\n      0.0493063615 a       188     0     8     1    13\n     -1.0670567955 a       189     0     8     1    14\n     -1.8917611535 a       190     0     8     1    15\n      1.2372326769 a       191     0     8     1    16\n      0.0716974137 a       192     0     8     1    17\n      0.2629331870 a       193     0     8     1    18\n     -0.0425632922 a       194     0     8     1    19\n     -0.5293580787 a       195     0     8     1    20\n      0.2732681603 a       196     0     8     1    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3\n     -0.5877754957 a       304     0    13     1     4\n      0.7131031711 a       305     0    13     1     5\n     -0.0876124563 a       306     0    13     1     6\n     -0.5361043818 a       307     0    13     1     7\n      0.4402045517 a       308     0    13     1     8\n     -0.1816561289 a       309     0    13     1     9\n      0.0221635205 a       310     0    13     1    10\n     -0.3525013857 a       311     0    13     1    11\n     -0.1201611864 a       312     0    13     1    12\n      0.4566999491 a       313     0    13     1    13\n     -0.2408349282 a       314     0    13     1    14\n     -0.7548810952 a       315     0    13     1    15\n      0.9575973316 a       316     0    13     1    16\n     -0.1469151538 a       317     0    13     1    17\n     -0.5720421187 a       318     0    13     1    18\n      0.2022969539 a       319     0    13     1    19\n     -0.5086027171 a       320     0    13     1    20\n     -0.0232005197 a       321     0    13    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10\n      0.2133805441 a       411     0    17     1    11\n      1.5071209918 a       412     0    17     1    12\n      0.4900472948 a       413     0    17     1    13\n      0.1625163678 a       414     0    17     1    14\n      0.1453448982 a       415     0    17     1    15\n     -0.7755564559 a       416     0    17     1    16\n     -0.8366412481 a       417     0    17     1    17\n      1.0543696826 a       418     0    17     1    18\n      0.2920363042 a       419     0    17     1    19\n      0.2781414582 a       420     0    17     1    20\n     -0.4543622719 a       421     0    17     1    21\n     -0.6145329733 a       422     0    17     1    22\n      0.1255424116 a       423     0    17     1    23\n      0.0310109269 a       424     0    17     1    24\n     -0.2846477163 a       425     0    17     1    25\n     -0.3854747312 a       426     0    18     1     1\n      0.0870068451 a       427     0    18     1     2\n     -0.0889898301 a       428     0    18   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0.5230697331 a       500     0    20     1    25\n      0.5158802542 a       501     0    21     1     1\n      0.9473184967 a       502     0    21     1     2\n      0.1351680221 a       503     0    21     1     3\n      0.9225937969 a       504     0    21     1     4\n      0.8246581647 a       505     0    21     1     5\n      0.5654030831 a       506     0    21     1     6\n     -1.4221104561 a       507     0    21     1     7\n     -0.8452399497 a       508     0    21     1     8\n     -0.0400058657 a       509     0    21     1     9\n     -0.6492811242 a       510     0    21     1    10\n      0.7293860605 a       511     0    21     1    11\n      0.6886017793 a       512     0    21     1    12\n     -0.0289279562 a       513     0    21     1    13\n     -0.6517433614 a       514     0    21     1    14\n      1.0281504327 a       515     0    21     1    15\n      0.7233169020 a       516     0    21     1    16\n     -1.5386100966 a       517     0    21     1    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22\n     -0.1837362420 a       773     1     3     2    23\n     -0.0793250995 a       774     1     3     2    24\n      0.3557317192 a       775     1     3     2    25\n      0.3711258010 a       776     1     4     2     1\n     -0.9655094619 a       777     1     4     2     2\n     -0.2108388755 a       778     1     4     2     3\n      0.0552788822 a       779     1     4     2     4\n     -0.0214891552 a       780     1     4     2     5\n      0.3389395553 a       781     1     4     2     6\n     -0.8905061606 a       782     1     4     2     7\n     -0.4336203334 a       783     1     4     2     8\n      0.1511191358 a       784     1     4     2     9\n     -0.4072275488 a       785     1     4     2    10\n     -0.1531892564 a       786     1     4     2    11\n      0.5528230933 a       787     1     4     2    12\n     -0.0136787803 a       788     1     4     2    13\n      0.6250714091 a       789     1     4     2    14\n      0.5047873465 a       790     1     4   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4\n      0.4661943881 a       880     1     8     2     5\n      0.5930919644 a       881     1     8     2     6\n      0.6222017702 a       882     1     8     2     7\n      0.5366666154 a       883     1     8     2     8\n     -0.9569363458 a       884     1     8     2     9\n     -0.2476196981 a       885     1     8     2    10\n      0.2661967732 a       886     1     8     2    11\n     -0.1431840923 a       887     1     8     2    12\n      0.3074401466 a       888     1     8     2    13\n      0.0697948912 a       889     1     8     2    14\n      0.1174940380 a       890     1     8     2    15\n     -0.3814567990 a       891     1     8     2    16\n     -0.0580013031 a       892     1     8     2    17\n     -0.4233214680 a       893     1     8     2    18\n     -0.7184726593 a       894     1     8     2    19\n     -0.6174438367 a       895     1     8     2    20\n      0.1045705160 a       896     1     8     2    21\n     -0.9040333955 a       897     1     8     2    22\n     -0.1889575997 a       898     1     8     2    23\n     -0.6421070264 a       899     1     8     2    24\n      0.0536162439 a       900     1     8     2    25\n      0.6591748608 a       901     1     9     2     1\n     -0.5599899623 a       902     1     9     2     2\n     -0.7565812741 a       903     1     9     2     3\n     -0.3451495701 a       904     1     9     2     4\n      0.2619505414 a       905     1     9     2     5\n      0.0473457026 a       906     1     9     2     6\n     -0.1643215786 a       907     1     9     2     7\n     -0.3780998812 a       908     1     9     2     8\n     -0.6702783807 a       909     1     9     2     9\n      0.0369976854 a       910     1     9     2    10\n      0.0167359085 a       911     1     9     2    11\n     -0.5398455835 a       912     1     9     2    12\n     -0.2453761193 a       913     1     9     2    13\n      0.1804898550 a       914     1     9     2    14\n     -0.2416108348 a       915     1   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   1    10     2     8\n     -0.1760006093 a       934     1    10     2     9\n     -0.3230880365 a       935     1    10     2    10\n     -0.4851780473 a       936     1    10     2    11\n     -0.0058269713 a       937     1    10     2    12\n      0.1166814547 a       938     1    10     2    13\n      0.3454250707 a       939     1    10     2    14\n      0.1645989847 a       940     1    10     2    15\n     -0.1484306340 a       941     1    10     2    16\n      0.0529273030 a       942     1    10     2    17\n      0.4423031519 a       943     1    10     2    18\n     -0.4847660242 a       944     1    10     2    19\n      0.6818632386 a       945     1    10     2    20\n      0.1015173575 a       946     1    10     2    21\n      0.2774474407 a       947     1    10     2    22\n      1.1348861126 a       948     1    10     2    23\n     -0.8335332525 a       949     1    10     2    24\n     -0.1332202090 a       950     1    10     2    25\n      0.0801984566 a       951     1    11     2     1\n     -0.3228878137 a       952     1    11     2     2\n     -0.1693614645 a       953     1    11     2     3\n      0.3725228802 a       954     1    11     2     4\n     -0.0445533902 a       955     1    11     2     5\n      0.4861759195 a       956     1    11     2     6\n      0.7900266525 a       957     1    11     2     7\n      0.0759923271 a       958     1    11     2     8\n     -0.0404313323 a       959     1    11     2     9\n     -0.3148097795 a       960     1    11     2    10\n     -0.3644949138 a       961     1    11     2    11\n      0.8054303656 a       962     1    11     2    12\n     -0.0108671994 a       963     1    11     2    13\n     -0.1169143755 a       964     1    11     2    14\n      0.3788326165 a       965     1    11     2    15\n     -0.5658553019 a       966     1    11     2    16\n      0.3059616400 a       967     1    11     2    17\n     -0.3176649217 a       968     1    11     2    18\n     -0.2778649945 a       969     1    11     2    19\n      0.7039206920 a       970     1    11     2    20\n      1.0909542445 a       971     1    11     2    21\n      0.3255016232 a       972     1    11     2    22\n      0.9696536131 a       973     1    11     2    23\n     -0.0631143210 a       974     1    11     2    24\n     -0.0903252819 a       975     1    11     2    25\n     -0.4317353115 a       976     1    12     2     1\n     -0.1033292612 a       977     1    12     2     2\n      0.7076354512 a       978     1    12     2     3\n     -0.4515761478 a       979     1    12     2     4\n      0.1575430804 a       980     1    12     2     5\n      0.0806955529 a       981     1    12     2     6\n      0.7784035988 a       982     1    12     2     7\n     -0.0661548504 a       983     1    12     2     8\n      0.1105768113 a       984     1    12     2     9\n      0.5293655079 a       985     1    12     2    10\n     -0.6135924350 a       986     1    12     2    11\n     -1.3016283024 a       987     1    12     2    12\n      0.0960549277 a       988     1    12     2    13\n      0.0908668132 a       989     1    12     2    14\n      0.7708530863 a       990     1    12     2    15\n     -0.0508620412 a       991     1    12     2    16\n     -0.6686270366 a       992     1    12     2    17\n     -0.3065474627 a       993     1    12     2    18\n      0.5171179238 a       994     1    12     2    19\n     -0.7411792894 a       995     1    12     2    20\n      0.9787388893 a       996     1    12     2    21\n      0.1161451158 a       997     1    12     2    22\n      0.4154997271 a       998     1    12     2    23\n      0.1316038634 a       999     1    12     2    24\n     -0.9659837213 a      1000     1    12     2    25\n      0.0171075897 a      1001     1    13     2     1\n     -0.4168701878 a      1002     1    13     2     2\n      0.6242696104 a      1003     1    13     2     3\n     -0.8076143507 a      1004     1    13     2     4\n     -0.3254994109 a      1005     1    13     2     5\n     -0.1675340375 a      1006     1    13     2     6\n      0.0065918669 a      1007     1    13     2     7\n     -0.0475603898 a      1008     1    13     2     8\n     -0.6383433558 a      1009     1    13     2     9\n     -0.1113436214 a      1010     1    13     2    10\n      0.5479730050 a      1011     1    13     2    11\n     -0.3051368270 a      1012     1    13     2    12\n      0.0992574333 a      1013     1    13     2    13\n      0.1650402180 a      1014     1    13     2    14\n      0.6561600670 a      1015     1    13     2    15\n     -0.3578145667 a      1016     1    13     2    16\n     -1.4141336289 a      1017     1    13     2    17\n      0.3299122773 a      1018     1    13     2    18\n      1.3365952072 a      1019     1    13     2    19\n     -0.5125722699 a      1020     1    13     2    20\n      0.2137876087 a      1021     1    13     2    21\n     -0.4282606253 a      1022     1  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    1    14     2    15\n      0.5542548783 a      1041     1    14     2    16\n      0.3912643133 a      1042     1    14     2    17\n      0.7670803223 a      1043     1    14     2    18\n     -0.0457746751 a      1044     1    14     2    19\n      0.2506962819 a      1045     1    14     2    20\n     -0.2674431129 a      1046     1    14     2    21\n      0.5117627223 a      1047     1    14     2    22\n     -0.3002284257 a      1048     1    14     2    23\n     -0.0086690560 a      1049     1    14     2    24\n      0.7459057535 a      1050     1    14     2    25\n      0.8371466976 a      1051     1    15     2     1\n      1.5674021096 a      1052     1    15     2     2\n      0.2557427846 a      1053     1    15     2     3\n      1.4829361085 a      1054     1    15     2     4\n      0.1444695628 a      1055     1    15     2     5\n     -0.0782513640 a      1056     1    15     2     6\n     -0.5129214416 a      1057     1    15     2     7\n      0.2970221657 a      1058     1    15     2     8\n     -0.0474002938 a      1059     1    15     2     9\n      0.6106742624 a      1060     1    15     2    10\n      0.2175685149 a      1061     1    15     2    11\n     -1.0231819125 a      1062     1    15     2    12\n     -1.1346553680 a      1063     1    15     2    13\n     -1.3248890856 a      1064     1    15     2    14\n     -0.3352895715 a      1065     1    15     2    15\n     -0.2080889924 a      1066     1    15     2    16\n     -0.2903220167 a      1067     1    15     2    17\n      0.2978982413 a      1068     1    15     2    18\n     -0.2508691077 a      1069     1    15     2    19\n      0.1707126281 a      1070     1    15     2    20\n     -0.4311867886 a      1071     1    15     2    21\n      0.1964524577 a      1072     1    15     2    22\n      0.5100944582 a      1073     1    15     2    23\n     -0.0624844283 a      1074     1    15     2    24\n      0.1517147856 a      1075     1    15     2    25\n      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18\n     -0.3092507416 a      1094     1    16     2    19\n     -0.6692428706 a      1095     1    16     2    20\n     -0.4587126123 a      1096     1    16     2    21\n     -0.3103848106 a      1097     1    16     2    22\n      0.3692718422 a      1098     1    16     2    23\n      0.3203906544 a      1099     1    16     2    24\n     -0.1771469861 a      1100     1    16     2    25\n     -0.3137509547 a      1101     1    17     2     1\n      0.3245885547 a      1102     1    17     2     2\n      0.7603576131 a      1103     1    17     2     3\n      0.2744152432 a      1104     1    17     2     4\n      0.7366883885 a      1105     1    17     2     5\n     -0.0226266806 a      1106     1    17     2     6\n     -0.2782025698 a      1107     1    17     2     7\n     -0.3300147038 a      1108     1    17     2     8\n     -0.7754807753 a      1109     1    17     2     9\n     -0.8785115890 a      1110     1    17     2    10\n     -0.2840265820 a      1111     1    17     2    11\n     -0.3870319235 a      1112     1    17     2    12\n      0.1810602319 a      1113     1    17     2    13\n     -0.3918417572 a      1114     1    17     2    14\n      0.8016114122 a      1115     1    17     2    15\n     -0.1955388929 a      1116     1    17     2    16\n     -0.0978992837 a      1117     1    17     2    17\n      0.2513560279 a      1118     1    17     2    18\n      0.0970983145 a      1119     1    17     2    19\n      0.5211675939 a      1120     1    17     2    20\n      0.2758279000 a      1121     1    17     2    21\n     -0.3466235778 a      1122     1    17     2    22\n      0.4064956338 a      1123     1    17     2    23\n     -0.3786977664 a      1124     1    17     2    24\n     -0.3508320527 a      1125     1    17     2    25\n      0.5745554031 a      1126     1    18     2     1\n     -0.0398630401 a      1127     1    18     2     2\n      0.1690116957 a      1128     1    18     2     3\n     -0.1148091651 a      1129     1  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    1    18     2    22\n      0.3218681670 a      1148     1    18     2    23\n      0.4261292864 a      1149     1    18     2    24\n     -0.1862489169 a      1150     1    18     2    25\n     -0.9834227109 a      1151     1    19     2     1\n     -0.0911827078 a      1152     1    19     2     2\n     -0.2005261461 a      1153     1    19     2     3\n      0.6900915994 a      1154     1    19     2     4\n     -0.4950527151 a      1155     1    19     2     5\n      0.4037905710 a      1156     1    19     2     6\n      0.5485415449 a      1157     1    19     2     7\n      0.3974062148 a      1158     1    19     2     8\n     -0.1323415107 a      1159     1    19     2     9\n      0.2374162689 a      1160     1    19     2    10\n     -0.8819445396 a      1161     1    19     2    11\n      0.3740653957 a      1162     1    19     2    12\n     -0.3785612222 a      1163     1    19     2    13\n      0.3817377412 a      1164     1    19     2    14\n     -0.0665657326 a    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  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol/hdnnp-data/weights.008.data",
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2    15\n      0.0818677963 a       791     1     1     2    16\n      0.3463472901 a       792     1     1     2    17\n     -0.1143486219 a       793     1     1     2    18\n      0.5608060859 a       794     1     1     2    19\n     -0.0570421536 a       795     1     1     2    20\n      0.1101573409 a       796     1     1     2    21\n     -0.0701072786 a       797     1     1     2    22\n     -0.1151364284 a       798     1     1     2    23\n     -0.2832969063 a       799     1     1     2    24\n     -0.5830216098 a       800     1     1     2    25\n     -0.6055106341 a       801     1     2     2     1\n     -0.3480469251 a       802     1     2     2     2\n     -0.8645770732 a       803     1     2     2     3\n     -0.4280622087 a       804     1     2     2     4\n     -0.2573231463 a       805     1     2     2     5\n     -0.1270521658 a       806     1     2     2     6\n      0.9192449617 a       807     1     2     2     7\n      0.0901967077 a       808     1    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 844     1     3     2    19\n     -0.8517225378 a       845     1     3     2    20\n      0.2963139332 a       846     1     3     2    21\n      0.5367036969 a       847     1     3     2    22\n     -0.3765919028 a       848     1     3     2    23\n      0.8513339921 a       849     1     3     2    24\n     -0.0623150367 a       850     1     3     2    25\n     -0.0116049652 a       851     1     4     2     1\n     -0.3958941814 a       852     1     4     2     2\n      0.0742089967 a       853     1     4     2     3\n      0.1437570964 a       854     1     4     2     4\n     -0.2623030486 a       855     1     4     2     5\n     -0.0629453369 a       856     1     4     2     6\n     -0.8432788718 a       857     1     4     2     7\n      0.2478908992 a       858     1     4     2     8\n      0.2380497838 a       859     1     4     2     9\n     -0.3326149583 a       860     1     4     2    10\n      0.2691157789 a       861     1     4     2    11\n     -0.8732341015 a       862     1     4     2    12\n      0.1561987845 a       863     1     4     2    13\n     -0.3753879181 a       864     1     4     2    14\n      0.0571191647 a       865     1     4     2    15\n     -0.2306561796 a       866     1     4     2    16\n      0.2725988162 a       867     1     4     2    17\n      0.0131588168 a       868     1     4     2    18\n      0.7601524464 a       869     1     4     2    19\n     -0.1359801512 a       870     1     4     2    20\n      0.0400202993 a       871     1     4     2    21\n     -0.0244063213 a       872     1     4     2    22\n     -0.0568819011 a       873     1     4     2    23\n      0.4487169103 a       874     1     4     2    24\n      0.1382261735 a       875     1     4     2    25\n      0.0948329845 a       876     1     5     2     1\n      0.3819188665 a       877     1     5     2     2\n     -0.4317862032 a       878     1     5     2     3\n      0.0755118412 a       879     1     5     2     4\n      0.3782702495 a       880     1     5     2     5\n     -0.2645732239 a       881     1     5     2     6\n      0.1649598771 a       882     1     5     2     7\n      0.6682449771 a       883     1     5     2     8\n      0.1191065058 a       884     1     5     2     9\n     -0.4552288816 a       885     1     5     2    10\n     -0.0701411455 a       886     1     5     2    11\n     -0.7559323555 a       887     1     5     2    12\n      0.4181185871 a       888     1     5     2    13\n      0.4499083913 a       889     1     5     2    14\n      0.4729532074 a       890     1     5     2    15\n     -0.2427233162 a       891     1     5     2    16\n      0.5016641720 a       892     1     5     2    17\n     -0.0335177127 a       893     1     5     2    18\n      0.4201751203 a       894     1     5     2    19\n     -0.3814306110 a       895     1     5     2    20\n      0.1449541382 a       896     1     5     2    21\n      0.6835751445 a       897     1     5     2    22\n      0.3904538714 a       898     1     5     2    23\n     -0.9227804204 a       899     1     5     2    24\n     -0.9869046908 a       900     1     5     2    25\n      0.1567152529 a       901     1     6     2     1\n      0.2150776523 a       902     1     6     2     2\n     -0.8424725533 a       903     1     6     2     3\n      0.9274198940 a       904     1     6     2     4\n     -0.5690051726 a       905     1     6     2     5\n     -0.4377792528 a       906     1     6     2     6\n     -2.0686731226 a       907     1     6     2     7\n     -0.3038058638 a       908     1     6     2     8\n     -0.7003254212 a       909     1     6     2     9\n      3.1518004986 a       910     1     6     2    10\n     -0.0108938240 a       911     1     6     2    11\n      0.8066121843 a       912     1     6     2    12\n      0.1577601200 a       913     1     6     2    13\n      1.2787533204 a       914     1     6     2    14\n      0.6315518297 a       915     1     6     2    15\n      0.0504928855 a       916     1     6     2    16\n     -0.4717855098 a       917     1     6     2    17\n      0.1698523602 a       918     1     6     2    18\n     -0.0575604095 a       919     1     6     2    19\n      0.2454046888 a       920     1     6     2    20\n      0.1336077723 a       921     1     6     2    21\n     -1.6277418023 a       922     1     6     2    22\n      0.1889171438 a       923     1     6     2    23\n     -0.1919104426 a       924     1     6     2    24\n      0.1956427067 a       925     1     6     2    25\n     -0.4066042353 a       926     1     7     2     1\n      0.4904305308 a       927     1     7     2     2\n     -1.0419607279 a       928     1     7     2     3\n      0.1654227099 a       929     1     7     2     4\n     -0.3895869516 a       930     1     7     2     5\n      0.4078517609 a       931     1     7     2     6\n      0.4905798204 a       932     1     7     2     7\n     -0.1280324003 a       933     1     7     2     8\n     -0.7358799539 a       934     1     7     2     9\n      1.2300743717 a       935     1     7     2    10\n      0.4321154680 a       936     1     7     2    11\n      0.7229744297 a       937     1     7     2    12\n     -0.0654358393 a       938     1     7     2    13\n     -0.3869277794 a       939     1     7     2    14\n      0.3342091387 a       940     1     7     2    15\n      0.0558127506 a       941     1     7     2    16\n      0.0378866552 a       942     1     7     2    17\n      0.2132571031 a       943     1     7     2    18\n      0.4587754864 a       944     1     7     2    19\n      0.3389875703 a       945     1     7     2    20\n      0.3074769055 a       946     1     7     2    21\n     -0.3295011902 a       947     1     7     2    22\n      0.2498017688 a       948     1     7     2    23\n      0.2955746811 a       949     1     7     2    24\n     -0.0255450441 a       950     1     7     2    25\n     -0.6518894057 a       951     1     8     2     1\n      0.4986985044 a       952     1     8     2     2\n      0.3284453189 a       953     1     8     2     3\n     -0.0795662024 a       954     1     8     2     4\n      0.1265126741 a       955     1     8     2     5\n     -0.5846865216 a       956     1     8     2     6\n     -0.8955943736 a       957     1     8     2     7\n      0.0633253554 a       958     1     8     2     8\n     -0.4792549946 a       959     1     8     2     9\n      0.5464099287 a       960     1     8     2    10\n     -0.5478594746 a       961     1     8     2    11\n     -0.0935759895 a       962     1     8     2    12\n     -0.3142838172 a       963     1     8     2    13\n      0.6591951288 a       964     1     8     2    14\n      0.3546627997 a       965     1     8     2    15\n     -0.2612495440 a       966     1     8     2    16\n     -0.1453285476 a       967     1     8     2    17\n     -0.3363708270 a       968     1     8     2    18\n     -0.6247359374 a       969     1     8     2    19\n      0.0841924429 a       970     1     8     2    20\n      0.0123505754 a       971     1     8     2    21\n     -0.1092431414 a       972     1     8     2    22\n     -0.4593069632 a       973     1     8     2    23\n      0.4994599558 a       974     1     8     2    24\n      0.3604137014 a       975     1     8     2    25\n     -1.0048754953 a       976     1     9     2     1\n      0.1216057484 a       977     1     9     2     2\n      0.8387739165 a       978     1     9     2     3\n     -0.0118531741 a       979     1     9     2     4\n     -0.1870581944 a       980     1     9     2     5\n     -0.4484327002 a       981     1     9     2     6\n      0.4030071582 a       982     1     9     2     7\n     -0.1538907972 a       983     1     9     2     8\n      0.2602421536 a       984     1     9     2     9\n     -0.2854946701 a       985     1     9     2    10\n      0.0443161767 a       986     1     9     2    11\n      0.3228759644 a       987     1     9     2    12\n     -0.3097281238 a       988     1     9     2    13\n      0.8894289310 a       989     1     9     2    14\n     -0.6798932862 a       990     1     9     2    15\n     -0.4085513130 a       991     1     9     2    16\n     -0.1491152436 a       992     1     9     2    17\n      0.2051522069 a       993     1     9     2    18\n      0.4743677518 a       994     1     9     2    19\n     -0.6913763647 a       995     1     9     2    20\n     -0.2381306302 a       996     1     9     2    21\n     -0.1476013731 a       997     1     9     2    22\n      0.7857587901 a       998     1     9     2    23\n      0.8049835307 a       999     1     9     2    24\n      0.2462326028 a      1000     1     9     2    25\n      0.8253545875 a      1001     1    10     2     1\n     -0.2086307080 a      1002     1    10     2     2\n     -0.6230027155 a      1003     1    10     2     3\n     -0.2565399917 a      1004     1    10     2     4\n      0.5450747484 a      1005     1    10     2     5\n      0.5632929179 a      1006     1    10     2     6\n      1.1125553431 a      1007     1    10     2     7\n     -0.2158849119 a      1008     1    10     2     8\n     -0.2791921186 a      1009     1    10     2     9\n     -0.1693316747 a      1010     1    10     2    10\n     -1.0159113920 a      1011     1    10     2    11\n     -0.2560345579 a      1012     1    10     2    12\n      0.1436833491 a      1013     1    10     2    13\n     -0.1097112294 a      1014     1    10     2    14\n     -0.3599845631 a      1015     1    10     2    15\n      0.1070535383 a      1016     1    10     2    16\n      0.4406999761 a      1017     1    10     2    17\n      0.3472842131 a      1018     1    10     2    18\n      0.3492759989 a      1019     1    10     2    19\n     -0.2124660256 a      1020     1    10     2    20\n      0.1786875024 a      1021     1    10     2    21\n      0.1578213029 a      1022     1    10     2    22\n      0.3709067718 a      1023     1    10     2    23\n     -0.8904005638 a      1024     1    10     2    24\n      0.8659766335 a      1025     1    10     2    25\n     -0.4327388700 a      1026     1    11     2     1\n      0.5197366094 a      1027     1    11     2     2\n     -0.6177011474 a      1028     1    11     2     3\n      0.3573134796 a      1029     1    11     2     4\n      0.1281530873 a      1030     1    11     2     5\n      1.1521851558 a      1031     1    11     2     6\n     -0.5681160794 a      1032     1    11     2     7\n      0.5683807357 a      1033     1    11     2     8\n      0.0569848793 a      1034     1    11     2     9\n      0.2630145730 a      1035     1    11     2    10\n      0.0095664834 a      1036     1    11     2    11\n      0.4159466278 a      1037     1    11     2    12\n     -0.4973540366 a      1038     1    11     2    13\n      0.1202631402 a      1039     1    11     2    14\n      0.6970074376 a      1040     1    11     2    15\n     -0.3111604386 a      1041     1    11     2    16\n      0.0047989685 a      1042     1    11     2    17\n     -1.0728858489 a      1043     1    11     2    18\n      0.2984821711 a      1044     1    11     2    19\n     -0.6471394643 a      1045     1    11     2    20\n      0.4600869514 a      1046     1    11     2    21\n     -0.3166444044 a      1047     1    11     2    22\n      0.6723644598 a      1048     1    11     2    23\n     -0.2853508368 a      1049     1    11     2    24\n     -0.0831987984 a      1050     1    11     2    25\n     -0.5519259551 a      1051     1    12     2     1\n      0.2036523622 a      1052     1    12     2     2\n      0.7685193985 a      1053     1    12     2     3\n     -0.0071316570 a      1054     1    12     2     4\n      0.3818327586 a      1055     1    12     2     5\n     -0.2272331510 a      1056     1    12     2     6\n      0.5560531802 a      1057     1    12     2     7\n      0.0335751891 a      1058     1    12     2     8\n      0.3610766879 a      1059     1    12     2     9\n      0.0645044592 a      1060     1    12     2    10\n     -0.6976978286 a      1061     1    12     2    11\n     -0.1237042791 a      1062     1    12     2    12\n     -0.6598766004 a      1063     1    12     2    13\n     -0.7596937065 a      1064     1    12     2    14\n     -0.7183164033 a      1065     1    12     2    15\n      0.3451415928 a      1066     1    12     2    16\n      0.3208762044 a      1067     1    12     2    17\n      0.1065806352 a      1068     1    12     2    18\n      0.8188754954 a      1069     1    12     2    19\n      0.4461747140 a      1070     1    12     2    20\n     -0.1428090118 a      1071     1    12     2    21\n      0.0783171166 a      1072     1    12     2    22\n     -0.3749129281 a      1073     1    12     2    23\n     -0.1949811868 a      1074     1    12     2    24\n     -0.4124115984 a      1075     1    12     2    25\n      0.4915911361 a      1076     1    13     2     1\n      0.5124119574 a      1077     1    13     2     2\n      0.1664274921 a      1078     1    13     2     3\n      0.3052981160 a      1079     1    13     2     4\n     -0.3236543541 a      1080     1    13     2     5\n      0.1039547847 a      1081     1    13     2     6\n     -0.1873248728 a      1082     1    13     2     7\n     -0.4199592488 a      1083     1    13     2     8\n     -0.1043316283 a      1084     1    13     2     9\n     -0.2774033849 a      1085     1    13     2    10\n      0.1558407396 a      1086     1    13     2    11\n     -0.8168807040 a      1087     1    13     2    12\n      0.5394635220 a      1088     1    13     2    13\n      0.1835581053 a      1089     1    13     2    14\n      0.0257013583 a      1090     1    13     2    15\n      0.5674313377 a      1091     1    13     2    16\n     -0.0889116651 a      1092     1    13     2    17\n     -0.0863660941 a      1093     1    13     2    18\n     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11\n     -0.1586351924 a      1112     1    14     2    12\n      0.2709459319 a      1113     1    14     2    13\n     -0.1936530770 a      1114     1    14     2    14\n     -0.8559107865 a      1115     1    14     2    15\n      0.3796776651 a      1116     1    14     2    16\n     -0.0967032987 a      1117     1    14     2    17\n     -0.2301580450 a      1118     1    14     2    18\n     -0.1080631818 a      1119     1    14     2    19\n      0.1626167612 a      1120     1    14     2    20\n      0.4562394027 a      1121     1    14     2    21\n     -0.6172136633 a      1122     1    14     2    22\n     -0.7061698916 a      1123     1    14     2    23\n      0.4782222367 a      1124     1    14     2    24\n     -0.6791540503 a      1125     1    14     2    25\n      0.1912169741 a      1126     1    15     2     1\n     -0.5651416511 a      1127     1    15     2     2\n      0.1052028126 a      1128     1    15     2     3\n      0.2993357782 a      1129     1    15     2     4\n     -0.3527546304 a      1130     1    15     2     5\n      0.0209791425 a      1131     1    15     2     6\n     -0.0927915629 a      1132     1    15     2     7\n      0.5777850320 a      1133     1    15     2     8\n      0.2492356282 a      1134     1    15     2     9\n     -0.2690263928 a      1135     1    15     2    10\n     -0.1681129944 a      1136     1    15     2    11\n      1.2249560054 a      1137     1    15     2    12\n     -0.2225554132 a      1138     1    15     2    13\n     -0.3414359163 a      1139     1    15     2    14\n      0.2956835194 a      1140     1    15     2    15\n     -0.3950006073 a      1141     1    15     2    16\n     -0.0565837995 a      1142     1    15     2    17\n      0.0496653406 a      1143     1    15     2    18\n      0.0544155173 a      1144     1    15     2    19\n      0.1472879499 a      1145     1    15     2    20\n      0.1827329427 a      1146     1    15     2    21\n      0.2300600514 a      1147     1  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    1    16     2    15\n      0.7534670130 a      1166     1    16     2    16\n     -0.3238064160 a      1167     1    16     2    17\n     -0.3601236845 a      1168     1    16     2    18\n      0.3151437122 a      1169     1    16     2    19\n     -0.0774472631 a      1170     1    16     2    20\n     -0.0735883133 a      1171     1    16     2    21\n     -0.7327417789 a      1172     1    16     2    22\n      0.2933211285 a      1173     1    16     2    23\n      0.0914558550 a      1174     1    16     2    24\n     -0.1656335267 a      1175     1    16     2    25\n     -0.8203657793 a      1176     1    17     2     1\n      0.2266896721 a      1177     1    17     2     2\n      0.4659978357 a      1178     1    17     2     3\n      0.3704152294 a      1179     1    17     2     4\n      0.4757034735 a      1180     1    17     2     5\n     -0.5066679894 a      1181     1    17     2     6\n      0.2694221564 a      1182     1    17     2     7\n      0.4578639279 a      1183     1    17     2     8\n      0.0067540494 a      1184     1    17     2     9\n     -0.3476218299 a      1185     1    17     2    10\n      0.1070395211 a      1186     1    17     2    11\n      0.2030131378 a      1187     1    17     2    12\n      0.6520560652 a      1188     1    17     2    13\n      0.1165191765 a      1189     1    17     2    14\n      0.4086082641 a      1190     1    17     2    15\n      0.2948992876 a      1191     1    17     2    16\n      0.2642198352 a      1192     1    17     2    17\n      0.4957462589 a      1193     1    17     2    18\n      0.0803337306 a      1194     1    17     2    19\n     -0.1887960839 a      1195     1    17     2    20\n     -0.1172641133 a      1196     1    17     2    21\n     -0.4243613643 a      1197     1    17     2    22\n     -0.6537059534 a      1198     1    17     2    23\n     -1.2842818114 a      1199     1    17     2    24\n     -0.0760485591 a      1200     1    17     2    25\n      0.4879320739 a      1201     1    18     2     1\n      0.4935359650 a      1202     1    18     2     2\n     -0.8202648604 a      1203     1    18     2     3\n     -0.5842327388 a      1204     1    18     2     4\n      0.2324224476 a      1205     1    18     2     5\n     -0.3342898408 a      1206     1    18     2     6\n      1.3847773826 a      1207     1    18     2     7\n      0.7200289595 a      1208     1    18     2     8\n      1.0423383297 a      1209     1    18     2     9\n     -0.7928797812 a      1210     1    18     2    10\n      0.4136427225 a      1211     1    18     2    11\n      0.0920764365 a      1212     1    18     2    12\n     -0.6981882796 a      1213     1    18     2    13\n     -0.1179783159 a      1214     1    18     2    14\n     -0.0006437393 a      1215     1    18     2    15\n     -0.5944717759 a      1216     1    18     2    16\n      0.4139379479 a      1217     1    18     2    17\n      0.1456704184 a      1218     1    18     2    18\n      0.0862537469 a      1219     1    18     2    19\n     -0.2672688246 a      1220     1    18     2    20\n     -0.2188372451 a      1221     1    18     2    21\n     -0.6312176121 a      1222     1    18     2    22\n     -0.1634984338 a      1223     1    18     2    23\n     -0.5236720704 a      1224     1    18     2    24\n     -0.5603589741 a      1225     1    18     2    25\n     -0.4814334632 a      1226     1    19     2     1\n     -0.0729144131 a      1227     1    19     2     2\n      0.7283035961 a      1228     1    19     2     3\n      0.6987892572 a      1229     1    19     2     4\n     -0.3854897686 a      1230     1    19     2     5\n      0.5203943389 a      1231     1    19     2     6\n      0.4909956861 a      1232     1    19     2     7\n      0.0976435278 a      1233     1    19     2     8\n      0.3263473112 a      1234     1    19     2     9\n     -0.7450407258 a      1235     1    19     2    10\n     -0.8229663200 a      1236     1    19     2    11\n     -0.6627172276 a      1237     1    19     2    12\n      0.7796855695 a      1238     1    19     2    13\n     -0.6231975657 a      1239     1    19     2    14\n      1.1141361959 a      1240     1    19     2    15\n     -0.3130099968 a      1241     1    19     2    16\n      0.5031213334 a      1242     1    19     2    17\n      0.2991024116 a      1243     1    19     2    18\n      0.2673772106 a      1244     1    19     2    19\n     -0.2494117076 a      1245     1    19     2    20\n     -0.5197855310 a      1246     1    19     2    21\n     -0.4797645309 a      1247     1    19     2    22\n      0.5022958375 a      1248     1    19     2    23\n     -0.0415718029 a      1249     1    19     2    24\n     -0.6883174625 a      1250     1    19     2    25\n     -0.5467977740 a      1251     1    20     2     1\n      0.3997174507 a      1252     1    20     2     2\n     -1.3478223509 a      1253     1    20     2     3\n     -0.1840651843 a      1254     1    20     2     4\n      0.3844689418 a      1255     1    20     2     5\n      0.3892947460 a      1256     1    20     2     6\n      0.5185024631 a      1257     1    20     2     7\n      0.6757740665 a      1258     1    20     2     8\n     -0.3237646202 a      1259     1    20     2     9\n     -0.1866587599 a      1260     1    20     2    10\n     -0.2285220156 a      1261     1    20     2    11\n      0.1293114102 a      1262     1    20     2    12\n     -0.4880760868 a      1263     1    20     2    13\n     -1.0072669054 a      1264     1    20     2    14\n      0.9286583633 a      1265     1    20     2    15\n     -0.2439320506 a      1266     1    20     2    16\n      0.3278167035 a      1267     1    20     2    17\n     -0.7720705458 a      1268     1    20     2    18\n      0.6680396977 a      1269     1    20     2    19\n      0.4304666100 a      1270     1    20     2    20\n      0.6694906840 a      1271     1    20     2    21\n      0.2387326095 a      1272     1    20     2    22\n      0.6261663306 a      1273     1    20     2    23\n     -0.4476644527 a      1274     1    20     2    24\n      0.0311718262 a      1275     1    20     2    25\n      0.7449554248 a      1276     1    21     2     1\n      0.5197356231 a      1277     1    21     2     2\n     -0.1559938950 a      1278     1    21     2     3\n     -0.6040448583 a      1279     1    21     2     4\n     -0.3217581587 a      1280     1    21     2     5\n      0.2703860499 a      1281     1    21     2     6\n     -0.2207025250 a      1282     1    21     2     7\n     -0.2952675348 a      1283     1    21     2     8\n     -0.4413004391 a      1284     1    21     2     9\n      0.5293946518 a      1285     1    21     2    10\n      0.7288283594 a      1286     1    21     2    11\n     -0.0138952814 a      1287     1    21     2    12\n      0.4255265968 a      1288     1    21     2    13\n      0.2137567986 a      1289     1    21     2    14\n      0.4305055748 a      1290     1    21     2    15\n     -0.0164938189 a      1291     1    21     2    16\n      0.0542231986 a      1292     1    21     2    17\n     -0.4549651237 a      1293     1    21     2    18\n     -0.9455580850 a      1294     1    21     2    19\n     -0.0825588007 a      1295     1    21     2    20\n     -0.1969562218 a      1296     1    21     2    21\n     -0.7110726076 a      1297     1    21     2    22\n      0.3306366927 a      1298     1    21     2    23\n     -1.2881833359 a      1299     1    21     2    24\n     -0.4663332524 a      1300     1    21     2    25\n      0.7205879410 a      1301     1    22     2     1\n     -0.3626082087 a      1302     1    22     2     2\n      0.1661907876 a      1303     1    22     2     3\n     -0.2395062939 a      1304     1    22     2     4\n     -0.3968335376 a      1305     1    22     2     5\n      0.0893874175 a      1306     1    22     2     6\n      0.1011569648 a      1307     1    22     2     7\n     -0.1291163654 a      1308     1    22     2     8\n     -0.4148799030 a      1309     1    22     2     9\n     -0.3969554545 a      1310     1    22     2    10\n      0.1002934132 a      1311     1    22     2    11\n     -0.5139344230 a      1312     1    22     2    12\n     -0.2427965921 a      1313     1    22     2    13\n      0.7723988146 a      1314     1    22     2    14\n     -0.9431548929 a      1315     1    22     2    15\n      0.0276233590 a      1316     1    22     2    16\n     -0.5070566190 a      1317     1    22     2    17\n     -0.7254907095 a      1318     1    22     2    18\n      0.0746703133 a      1319     1    22     2    19\n     -0.1270249948 a      1320     1    22     2    20\n     -0.3968966152 a      1321     1    22     2    21\n      0.3846697275 a      1322     1    22     2    22\n      0.4361181716 a      1323     1    22     2    23\n     -0.2851459447 a      1324     1    22     2    24\n     -0.7077908948 a      1325     1    22     2    25\n     -0.3409236443 a      1326     1    23     2     1\n     -0.1198377385 a      1327     1    23     2     2\n     -0.3598078150 a      1328     1    23     2     3\n      0.3200824247 a      1329     1    23     2     4\n      0.4829035341 a      1330     1    23     2     5\n     -0.6011363962 a      1331     1    23     2     6\n     -1.0848545894 a      1332     1    23     2     7\n     -0.3741601801 a      1333     1    23     2     8\n      0.7781267608 a      1334     1    23     2     9\n      0.0243013976 a      1335     1    23     2    10\n     -0.1210792009 a      1336     1    23     2    11\n     -0.3629840971 a      1337     1    23     2    12\n     -0.7036853247 a      1338     1    23     2    13\n      0.1490468608 a      1339     1    23     2    14\n      1.0704229680 a      1340     1    23     2    15\n     -0.5397046980 a      1341     1    23     2    16\n      0.7668251746 a      1342     1    23     2    17\n     -0.0508418490 a      1343     1    23     2    18\n      0.2758083032 a      1344     1    23     2    19\n      0.3306812174 a      1345     1    23     2    20\n      0.0071493281 a      1346     1    23     2    21\n      0.2964062551 a      1347     1    23     2    22\n     -0.6024351255 a      1348     1    23     2    23\n     -1.2517953336 a      1349     1    23     2    24\n     -0.1264785194 a      1350     1    23     2    25\n     -0.1435971932 a      1351     1    24     2     1\n      0.1092566501 a      1352     1    24     2     2\n      0.6876235645 a      1353     1    24     2     3\n     -0.6474366853 a      1354     1    24     2     4\n      0.2911945762 a      1355     1    24     2     5\n     -0.2236085897 a      1356     1    24     2     6\n      0.9660014634 a      1357     1    24     2     7\n     -0.0103120199 a      1358     1    24     2     8\n      0.6553430759 a      1359     1    24     2     9\n     -1.2057731715 a      1360     1    24     2    10\n     -0.1080931244 a      1361     1    24     2    11\n     -0.5622975704 a      1362     1    24     2    12\n      0.0120591416 a      1363     1    24     2    13\n      1.1487553111 a      1364     1    24     2    14\n     -0.5177106230 a      1365     1    24     2    15\n     -0.3899576917 a      1366     1    24     2    16\n      0.7904796538 a      1367     1    24     2    17\n     -0.2587389367 a      1368     1    24     2    18\n     -0.4151583040 a      1369     1    24     2    19\n      0.4005401371 a      1370     1    24     2    20\n     -0.5009971248 a      1371     1    24     2    21\n      1.2969824334 a      1372     1    24     2    22\n      0.2828177948 a      1373     1    24     2    23\n      0.0226170407 a      1374     1    24     2    24\n     -0.2939570886 a      1375     1    24     2    25\n     -0.0364501947 a      1376     1    25     2     1\n     -0.3124746469 a      1377     1    25     2     2\n     -0.0911001383 a      1378     1    25     2     3\n      0.6461314621 a      1379     1    25     2     4\n      0.0158891035 a      1380     1    25     2     5\n     -0.5845752231 a      1381     1    25     2     6\n     -0.1428298207 a      1382     1    25     2     7\n      0.2628229342 a      1383     1    25     2     8\n      0.3612990703 a      1384     1    25     2     9\n     -0.3340586442 a      1385     1    25     2    10\n     -0.4929352502 a      1386     1    25     2    11\n     -0.4006983336 a      1387     1    25     2    12\n      0.2213390092 a      1388     1    25     2    13\n      0.7860476727 a      1389     1    25     2    14\n     -0.0578154170 a      1390     1    25     2    15\n     -0.1019399485 a      1391     1    25     2    16\n      0.4659758451 a      1392     1    25     2    17\n     -0.8611122072 a      1393     1    25     2    18\n     -0.4946250532 a      1394     1    25     2    19\n     -0.9314498370 a      1395     1    25     2    20\n      0.3973951766 a      1396     1    25     2    21\n      0.1515791739 a      1397     1    25     2    22\n     -0.1968296890 a      1398     1    25     2    23\n     -1.0363869373 a      1399     1    25     2    24\n     -0.6468229951 a      1400     1    25     2    25\n     -0.1763092635 b      1401     2     1\n     -0.7621524272 b      1402     2     2\n      0.5675964973 b      1403     2     3\n      0.2812523188 b      1404     2     4\n     -1.2731906777 b      1405     2     5\n     -0.5120072557 b      1406     2     6\n     -0.6016927187 b      1407     2     7\n     -0.5413525588 b      1408     2     8\n     -0.4388952877 b      1409     2     9\n      0.4691197676 b      1410     2    10\n      1.4293780428 b      1411     2    11\n      0.7949634944 b      1412     2    12\n     -0.1510003557 b      1413     2    13\n     -0.5634345945 b      1414     2    14\n     -1.4000068197 b      1415     2    15\n      1.3740227580 b      1416     2    16\n      0.2090192782 b      1417     2    17\n      1.0257980357 b      1418     2    18\n      1.0321238670 b      1419     2    19\n      0.9867896198 b      1420     2    20\n     -0.4739147575 b      1421     2    21\n     -1.5305053560 b      1422     2    22\n     -1.3077137778 b      1423     2    23\n      0.7106828608 b      1424     2    24\n      0.2155175549 b      1425     2    25\n      0.0807595152 a      1426     2     1     3     1\n     -0.0159833111 a      1427     2     2     3     1\n      0.1306787658 a      1428     2     3     3     1\n      0.1374835598 a      1429     2     4     3     1\n     -0.0013415305 a      1430     2     5     3     1\n     -0.0736957587 a      1431     2     6     3     1\n      0.0681119159 a      1432     2     7     3     1\n     -0.0093324867 a      1433     2     8     3     1\n     -0.0240015765 a      1434     2     9     3     1\n     -0.0752336026 a      1435     2    10     3     1\n     -0.0692611141 a      1436     2    11     3     1\n     -0.0808010387 a      1437     2    12     3     1\n     -0.1740393457 a      1438     2    13     3     1\n      0.0639676031 a      1439     2    14     3     1\n      0.1589784658 a      1440     2    15     3     1\n      0.0432355392 a      1441     2    16     3     1\n      0.0070135735 a      1442     2    17     3     1\n      0.0131666890 a      1443     2    18     3     1\n      0.0573691989 a      1444     2    19     3     1\n      0.0451232415 a      1445     2    20     3     1\n     -0.1403703320 a      1446     2    21     3     1\n      0.1825203948 a      1447     2    22     3     1\n      0.0232415967 a      1448     2    23     3     1\n      0.1600700404 a      1449     2    24     3     1\n      0.0644496051 a      1450     2    25     3     1\n     -0.2938446474 b      1451     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol/iceIh_128.data",
    "content": "Generated by ./convert_pgxyzinfo_lammpsdata.sh from iceIh_Cmc21.xyz, comment: \n\n384 atoms\n\n2 atom types\n\n  0.0000000000000000E+00   1.7969000000000001E+01 xlo xhi\n  0.0000000000000000E+00   1.5561600000000000E+01 ylo yhi\n  0.0000000000000000E+00   1.4671620000000001E+01 zlo zhi\n  0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 xy xz yz\n\nAtoms\n\n1 2    7.7574078122432866E-01   2.1919704683420500E+00   3.9845996089839000E+00\n2 1    0.0000000000000000E+00   1.7442755219935400E+00   3.6679050000000002E+00\n3 1    7.7574078122432866E-01   2.1919704683420500E+00   4.9345996089839002E+00\n4 2    7.7574078122432866E-01   4.7860884683420490E+00   3.1669460898389978E-01\n5 1    1.5514815624486591E+00   5.2337834146905600E+00   0.0000000000000000E+00\n6 1    0.0000000000000000E+00   5.2337834146905600E+00   0.0000000000000000E+00\n7 2    3.0218657812243297E+00   6.0823704683420496E+00   3.9845996089839000E+00\n8 1    2.2461249999999993E+00   5.6346755219935396E+00   3.6679050000000002E+00\n9 1    3.0218657812243297E+00   6.9780589366841044E+00   3.6679891737814803E+00\n10 2    3.0218657812243297E+00   8.9568846834204940E-01   3.1669460898389978E-01\n11 1    3.7976065624486592E+00   1.3433834146905594E+00   0.0000000000000000E+00\n12 1    3.0218657812243297E+00   8.9568846834204940E-01   1.2666946089839000E+00\n13 2    3.0218657812243297E+00   6.0823704683420496E+00   6.7355286089839002E+00\n14 1    2.2461249999999993E+00   5.6346755219935396E+00   7.0522232179678008E+00\n15 1    3.0218657812243297E+00   6.0823704683420496E+00   5.7855286089839000E+00\n16 2    3.0218657812243297E+00   8.9568846834204940E-01   3.0676236089839000E+00\n17 1    2.2461249999999993E+00   1.3433834146905594E+00   3.3843182179678002E+00\n18 1    3.0218657812243297E+00   0.0000000000000000E+00   3.3842340441863201E+00\n19 2    5.2679907812243290E+00   4.7860884683420490E+00   3.0676236089839000E+00\n20 1    4.4922499999999994E+00   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  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol/md.lmp",
    "content": "###############################################################################\n# MD simulation for NN water\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"iceIh_128.data\"\n# Timesteps\nvariable numSteps        equal  5\nvariable dt              equal  0.0005\n# NN\nvariable hdnnpCutoff     equal  6.36\nvariable hdnnpDir        string \"hdnnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_O          equal  15.9994\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary p p p\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_H}\nmass 2 ${mass_O}\ntimestep ${dt}\nthermo 1\n\n###############################################################################\n# NN\n###############################################################################\npair_style hdnnp ${hdnnpCutoff} dir ${hdnnpDir} showew no showewsum 10 resetew no maxew 100 cflength 1.8897261328 cfenergy 0.0367493254\npair_coeff * * H O\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\ndump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_develop/hdnnp-data/hardness.001.data",
    "content": "13.0342\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_develop/hdnnp-data/hardness.008.data",
    "content": "12.5756\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_develop/hdnnp-data/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.3367692947173474E-01\nconv_energy   2.4265748255367663E+02\nconv_length   5.7816872518854572E+00\n###############################################################################\n\n################################################################\n### This is the input file for n2p2 (modified by me)\n#################################################################\n#\n### It contains only a subset of all keywords\n\n################################################################################\n### general keywords\n################################################################################\n\nnnp_generation 4\nuse_short_forces\n\nnumber_of_elements 2\nelements H O\n\n#initial_hardness        H        10.0\n#initial_hardness        O        10.0\n\nfixed_gausswidth  H 0.585815056466\nfixed_gausswidth  O 1.379499971678\n\nscreen_electrostatics 4.8 8.0\n\nrandom_seed 12346\n\n#remove_atom_energies\natom_energy     H    -0.458907306351869\natom_energy     O    -74.94518524\n\newald_truncation_error_method 1                 # 0 RuNNer method (default),\n                                                # 1 method optimized for n2p2 (recommended)\n#ewald_prec 1.e-2\newald_prec 1.e-5 0.36                            # method 0 requires one\n                                                # dimensionless parameter which controls\n                                                # the electrostatic energy\n                                                # error,\n                                                # method 1 requires two\n                                                # arguments: first the precision\n                                                # of the electrostatic forces in\n                                                # the same unit as the training\n                                                # data, second an estimate for\n                                                # the maximum expected charge.\n\n################################################################################\n### NN structure of the short-range NN\n################################################################################\nglobal_hidden_layers_short 2\nglobal_nodes_short 15 15\nglobal_activation_short t t l\n\n################################################################################\n### NN structure of the electrostatic NN\n################################################################################\nglobal_hidden_layers_electrostatic 2\nglobal_nodes_electrostatic 15 15\nglobal_activation_electrostatic t t l\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (General)\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          20              # Number of training epochs.\nupdater_type                    1               # Weight update method\n                                                # (0 = Gradient Descent,\n                                                # 1 = Kalman filter).\nparallel_mode                   1               # Training parallelization used\n                                                # (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1               # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0               # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  0               # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                        # Keep symmetry function results in memory.\nrmse_threshold_trials           3               # Maximum number of RMSE threshold trials.\nmain_error_metric               RMSEpa          # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\ntest_fraction                   0.1             # Fraction of structures kept for testing.\nweights_min                     -1.0            # Minimum value for initial random weights.\nweights_max                     1.0             # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\nwrite_weights_epoch             2               # Write weights every this many epochs.\nscale_symmetry_functions\ncenter_symmetry_functions\n#write_neuronstats               1              # Write neuron statistics every this many epochs.\n#write_trainlog                                 # Write training log file.\n\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (charges, stage 1)\n################################################################################\ntask_batch_size_charge          1\n#nguyen_widrow_weights_charge                   # Initialize neural network weights according to Nguyen-Widrow scheme.\ncharge_fraction                 1.000\nwrite_traincharges              4               # Write charge comparison. Can produce large files.\n#use_old_weights_charge                         # Restart fitting with old weight parameters.\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (short-range, stage 2)\n################################################################################\ntask_batch_size_energy          1               # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1               # Number of force update candidates prepared per task for each update (0 = Entire training set).\nforce_weight                    10.0            # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000           # Fraction of energy updates per epoch.\nshort_force_fraction            0.025           # Fraction of force updates per epoch.\n#short_energy_error_threshold    0.80           # RMSE threshold for energy update candidates.\n#short_force_error_threshold     0.80           # RMSE threshold for force update candidates.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\n#repeated_energy_update\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               5               # Write energy comparison every this many epochs.\nwrite_trainforces               5               # Write force comparison every this many epochs.\n\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# These two parameters are only used if \"updater_type\" is \"1\".\n#kalman_lambda_short 0.98000\n#kalman_nue_short 0.99870\n\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon, covariance matrix initialization (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0, initial process noise (\"large\").\nkalman_qtau                     2.302 #2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin, final process noise (typ. 1.0E-6).\nkalman_eta                      0.01          # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   1.609          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   0.1            # Standard Kalman filter parameter etamax (1.0+).\n\n\n################################################################################\n### symmetry function definitions (all modes):\n################################################################################\ncutoff_type 2\n\n# radial H H\nsymfunction H 2 H 0.001 0.0 8.00\nsymfunction H 2 H 0.01  0.0 8.00\nsymfunction H 2 H 0.03  0.0 8.00\nsymfunction H 2 H 0.06  0.0 8.00\nsymfunction H 2 H 0.15  1.9 8.00\nsymfunction H 2 H 0.30  1.9 8.00\nsymfunction H 2 H 0.60  1.9 8.00\nsymfunction H 2 H 1.50  1.9 8.00\n\n# radial H O / O H\nsymfunction H 2 O 0.001 0.0 8.00\nsymfunction H 2 O 0.01  0.0 8.00\nsymfunction H 2 O 0.03  0.0 8.00\nsymfunction H 2 O 0.06  0.0 8.00\nsymfunction H 2 O 0.15  0.9 8.00\nsymfunction H 2 O 0.30  0.9 8.00\nsymfunction H 2 O 0.60  0.9 8.00\nsymfunction H 2 O 1.50  0.9 8.00\n\nsymfunction O 2 H 0.001 0.0 8.00\nsymfunction O 2 H 0.01  0.0 8.00\nsymfunction O 2 H 0.03  0.0 8.00\nsymfunction O 2 H 0.06  0.0 8.00\nsymfunction O 2 H 0.15  0.9 8.00\nsymfunction O 2 H 0.30  0.9 8.00\nsymfunction O 2 H 0.60  0.9 8.00\nsymfunction O 2 H 1.50  0.9 8.00\n\n# radial O O\nsymfunction O 2 O 0.001 0.0 8.00\nsymfunction O 2 O 0.01  0.0 8.00\nsymfunction O 2 O 0.03  0.0 8.00\nsymfunction O 2 O 0.06  0.0 8.00\nsymfunction O 2 O 0.15  4.0 8.00\nsymfunction O 2 O 0.30  4.0 8.00\nsymfunction O 2 O 0.60  4.0 8.00\nsymfunction O 2 O 1.50  4.0 8.00\n\n# angular\nsymfunction H 3 O H 0.2  1.0 1.0  8.00000\n\nsymfunction O 3 H H 0.07  1.0 1.0  8.00000\nsymfunction H 3 O H 0.07  1.0 1.0  8.00000\nsymfunction O 3 H H 0.07 -1.0 1.0  8.00000\nsymfunction H 3 O H 0.07 -1.0 1.0  8.00000\n\nsymfunction O 3 H H 0.03  1.0 1.0  8.00000\nsymfunction H 3 O H 0.03  1.0 1.0  8.00000\nsymfunction O 3 H H 0.03 -1.0 1.0  8.00000\nsymfunction H 3 O H 0.03 -1.0 1.0  8.00000\n\nsymfunction O 3 H H 0.01  1.0 4.0  8.00000\nsymfunction H 3 O H 0.01  1.0 4.0  8.00000\nsymfunction O 3 H H 0.01 -1.0 4.0  8.00000\nsymfunction H 3 O H 0.01 -1.0 4.0  8.00000\n\nsymfunction O 3 O H 0.03  1.0 1.0   8.00000\nsymfunction O 3 O H 0.03 -1.0 1.0   8.00000\nsymfunction O 3 O H 0.001  1.0 4.0  8.00000\nsymfunction O 3 O H 0.001 -1.0 4.0  8.00000\n\nsymfunction H 3 O O 0.03  1.0 1.0   8.00000\nsymfunction H 3 O O 0.03 -1.0 1.0   8.00000\nsymfunction H 3 O O 0.001  1.0 4.0  8.00000\nsymfunction H 3 O O 0.001 -1.0 4.0  8.00000\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_develop/hdnnp-data/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   2.0811328411603291E-01   2.6502965458022318E+00   5.4820779183620016E-01   1.9438655003491395E-01\n         1          2   2.6433635267579064E-01   1.5146690311845015E+00   4.5479260296306578E-01   9.7280960332528199E-02\n         1          3   1.7997590388914353E-01   2.2758763028581233E+00   4.6383027387611486E-01   1.6637393633826927E-01\n         1          4   2.5164230865801712E-01   1.3306586507044289E+00   4.1434387767152581E-01   8.3423919577292033E-02\n         1          5   1.3281966828124936E-01   1.6627981343419305E+00   3.2752602910447615E-01   1.2003375173852063E-01\n         1          6   2.2597288579037783E-01   1.0274360903839950E+00   3.4684254930103392E-01   6.1168891244830069E-02\n         1          7   8.2149386182782322E-02   1.0931441839643286E+00   2.0448958208237744E-01   7.6327545904223026E-02\n         1          8   1.8494239959516390E-01   7.4164165589182818E-01   2.7989660958600449E-01   4.1113013365414681E-02\n         1          9   1.6751248687704154E-01   6.3451358309364347E-01   2.7282862040313216E-01   3.2782751043787056E-02\n         1         10   9.9814913304491840E-02   1.4923368301275222E+00   2.6862939200493952E-01   1.0428094014194154E-01\n         1         11   1.0849664749548267E-01   4.2492696326932716E-01   2.1395460812841474E-01   1.9759157190422972E-02\n         1         12   4.9512429901861006E-02   1.0351911873358328E+00   1.7159090193442056E-01   6.5760700745434983E-02\n         1         13   4.5851290715271713E-02   2.8078525482049599E-01   1.5136333258526743E-01   1.7712883560853453E-02\n         1         14   1.5572680775701220E-02   5.6549997368551852E-01   9.6280906120558410E-02   3.3622821342384389E-02\n         1         15   2.0558245629162986E-03   2.3344123028135391E-01   6.2957467617677315E-02   1.6232452259873492E-02\n         1         16   1.4251786751748164E-04   2.2677621553134111E-01   3.0805306618705043E-02   1.6825464758098242E-02\n         1         17   8.7677506694763963E-09   1.8133523252440008E-02   1.6904054131874958E-03   1.4498718100987250E-03\n         1         18   1.1825047322002258E-06   2.2644297834218174E-02   3.4901866652083455E-04   1.2372085569777791E-03\n         1         19   1.2121533479425855E-06   1.7252396095482177E-02   7.5204485043056993E-04   1.0233732774886429E-03\n         1         20   9.3893909497466312E-03   1.8871833869180935E-01   2.3601290358002125E-02   1.1268011187407586E-02\n         1         21   5.0912749619490293E-04   4.7735409785710552E-02   2.9207054104726160E-03   2.6361672763745348E-03\n         1         22   3.5709418954137420E-07   1.7920245508055817E-02   6.2824806746419914E-04   9.9517810480315790E-04\n         1         23   7.3548336492137998E-03   1.5864992809160433E-01   1.9965515177632759E-02   8.9059457363348318E-03\n         1         24   4.0555469146903359E-07   1.6584613512818498E-02   1.9113049770027145E-04   8.6857315901075756E-04\n         1         25   1.7120177596911926E-04   1.3255281248816040E-02   1.0979500456395565E-03   6.6475873777848023E-04\n         1         26   2.4322401900543343E-03   5.1545511160465539E-02   8.5844169964596640E-03   2.6804579087894337E-03\n         1         27   4.7105173128093422E-05   5.0076469955970607E-03   9.1132439628238899E-04   2.9969891087298559E-04\n         2          1   5.6622988327342849E-01   3.0147634063327788E+00   9.0958520592614012E-01   1.9095186874369857E-01\n         2          2   1.3218655928873254E-02   1.1635302009851911E+00   1.3801198173921958E-01   9.1411833493487485E-02\n         2          3   5.3975003894284335E-01   2.6399559955371741E+00   8.2868775534309214E-01   1.6288172484062952E-01\n         2          4   8.7272333712139164E-03   9.7788447046439819E-01   1.0582206167666698E-01   7.5702626572108633E-02\n         2          5   4.7776492746364946E-01   2.0231917173164033E+00   6.9368509860206673E-01   1.1755794249914943E-01\n         2          6   3.4776242312125867E-03   6.7234361665195730E-01   5.9193112360643070E-02   5.0095702059349122E-02\n         2          7   3.9068291166034574E-01   1.4497982392307129E+00   5.5979321917201608E-01   7.6739868380187357E-02\n         2          8   8.7990047184996001E-04   3.8972735375533091E-01   2.5299574150808492E-02   2.7307035754050888E-02\n         2          9   3.7766156969729747E-01   1.2292345546905405E+00   5.4565724080627731E-01   5.8371007436868252E-02\n         2         10   4.3415602012824173E-03   1.1225891847759155E+00   1.0363127377056386E-01   8.7758953907225212E-02\n         2         11   2.6442344770784837E-01   8.2111699815680450E-01   4.2790921625683404E-01   3.3342299973635116E-02\n         2         12   1.3935375828897189E-03   1.0857170141924004E+00   7.8864434998351773E-02   8.3250529422228450E-02\n         2         13   1.1448482726683375E-01   5.3607470039908600E-01   3.0272666517053037E-01   2.7157317425580321E-02\n         2         14   1.5068679194630010E-04   1.0375459330533015E+00   4.9493713937866293E-02   7.5807310920218529E-02\n         2         15   6.8556300948793419E-03   3.3798603795908300E-01   1.2591493523535371E-01   2.4074409175343241E-02\n         2         16   2.2805731083975582E-07   9.4421042507398634E-01   1.7791151625124037E-02   6.1266323775209533E-02\n         2         17   2.7212699981397850E-07   1.1324028652035913E-02   2.3221011453718719E-04   5.8780718631226301E-04\n         2         18   1.9589943115997871E-04   2.1807749964542619E-01   1.0098166205242015E-02   1.3777410653208302E-02\n         2         19   1.0742817109419558E-03   3.1848369378060223E-02   5.9810023462588593E-03   2.0652541092962017E-03\n         2         20   3.4051730284575339E-04   1.1585003644294592E-01   3.7566613479653871E-03   7.0348789275473346E-03\n         2         21   5.0259564912627230E-03   8.1604220512722495E-02   1.3514844421438774E-02   4.5277209011638838E-03\n         2         22   5.6558642152248699E-07   2.2509783821801910E-02   2.7677535090990459E-04   1.2203932554202270E-03\n         2         23   2.1708348421484859E-03   1.2529174851847125E-01   9.3713761666662631E-03   7.1747015213576024E-03\n         2         24   2.0702350340735524E-05   1.0355923302213448E-01   3.0007389097479781E-03   6.0036304299016640E-03\n         2         25   1.6923574905950110E-03   3.1357384977899992E-02   5.9452133141760198E-03   1.5431153498629406E-03\n         2         26   7.2436096051361868E-04   3.5916824163405081E-02   3.7371537279232152E-03   1.8987944013853955E-03\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_develop/hdnnp-data/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -1.4516098909915223E+00 a         1     0     1     1     1\n -4.3915659497784354E+00 a         2     0     1     1     2\n -2.8662447788755396E+00 a         3     0     1     1     3\n -1.0410785447374080E+00 a         4     0     1     1     4\n  8.6140755481261273E+00 a         5     0     1     1     5\n  9.7972176093654850E-01 a         6     0     1     1     6\n -3.0000066703403316E+00 a         7     0     1     1     7\n -2.6974382167781106E+00 a         8     0     1     1     8\n -4.7446318300438994E+00 a         9     0     1     1     9\n  5.0263233312458321E-03 a        10     0     1     1    10\n  2.3272900870535320E+00 a        11     0     1     1    11\n -1.7559406347268283E+00 a        12     0     1     1    12\n  3.7083731742671664E+00 a        13     0     1     1    13\n -2.4342590856552064E+00 a        14     0     1     1    14\n  4.7010081584351244E+00 a        15     0     1     1    15\n  1.2344067585100691E+00 a        16     0     2     1     1\n -7.2379705006653019E+00 a        17     0     2     1     2\n -2.5652882510167268E-02 a        18     0     2     1     3\n -2.2072005816756204E-01 a        19     0     2     1     4\n -6.0379896013924688E+00 a        20     0     2     1     5\n  1.1938634998442006E+00 a        21     0     2     1     6\n  8.3147371304878810E+00 a        22     0     2     1     7\n -3.7554352336807062E+00 a        23     0     2     1     8\n  2.1504571324538486E+00 a        24     0     2     1     9\n -5.9340099392532490E+00 a        25     0     2     1    10\n  4.4172763816674223E+00 a        26     0     2     1    11\n  9.3775896805280503E+00 a        27     0     2     1    12\n -1.5221559579193118E+00 a        28     0     2     1    13\n -4.3268916568715748E-01 a        29     0     2     1    14\n -4.9045463553428820E-01 a        30     0     2     1    15\n -2.3975435839140544E-01 a        31     0     3     1     1\n  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1.8848739097832090E+00 a       563     1     9     2     8\n -1.0255947028457026E+00 a       564     1     9     2     9\n -9.3778044668765326E-01 a       565     1     9     2    10\n  4.2567424637104126E-02 a       566     1     9     2    11\n  4.8235517344715673E-01 a       567     1     9     2    12\n  6.8367635590886078E-01 a       568     1     9     2    13\n  6.6659560559796616E-01 a       569     1     9     2    14\n -2.0099389283070939E+00 a       570     1     9     2    15\n  1.3152584327223553E+00 a       571     1    10     2     1\n -9.7418522247564510E-01 a       572     1    10     2     2\n -2.4088283239822674E+00 a       573     1    10     2     3\n  1.3588280278444673E+00 a       574     1    10     2     4\n -1.0268662256590455E+00 a       575     1    10     2     5\n -1.5533070863586642E+00 a       576     1    10     2     6\n -1.7053589856414169E+00 a       577     1    10     2     7\n -2.5106404673059357E+00 a       578     1    10     2     8\n  5.3597428665539493E-01 a       579     1    10     2     9\n  1.9810737146159789E+00 a       580     1    10     2    10\n  2.4942944419775235E+00 a       581     1    10     2    11\n -2.0220305163366251E-01 a       582     1    10     2    12\n  1.0966260336430664E+00 a       583     1    10     2    13\n -9.9865005835752008E-01 a       584     1    10     2    14\n  5.5194601874881566E-01 a       585     1    10     2    15\n  8.4006781705269040E-01 a       586     1    11     2     1\n  6.2066729352953243E-01 a       587     1    11     2     2\n  8.0432947644550645E-01 a       588     1    11     2     3\n -5.1799017042100381E-01 a       589     1    11     2     4\n -1.0630012165487022E+00 a       590     1    11     2     5\n  1.5130614341658133E+00 a       591     1    11     2     6\n -6.1473182635982038E-01 a       592     1    11     2     7\n -2.7405724547587462E-01 a       593     1    11     2     8\n -1.2800380117140682E+00 a       594     1    11     2     9\n  5.3809013413341378E-01 a       595     1    11     2    10\n  5.4877936534749683E-01 a       596     1    11     2    11\n -1.3539151645603287E+00 a       597     1    11     2    12\n -1.3713033636628183E-01 a       598     1    11     2    13\n -1.6135771655545332E+00 a       599     1    11     2    14\n -1.1285432212435138E+00 a       600     1    11     2    15\n  1.4052413915962835E-02 a       601     1    12     2     1\n -1.7443625928559863E+00 a       602     1    12     2     2\n -2.0033756082785503E+00 a       603     1    12     2     3\n -1.3881845900345777E+00 a       604     1    12     2     4\n -1.1272646968294637E+00 a       605     1    12     2     5\n -4.7626339729445683E-01 a       606     1    12     2     6\n -5.2041323747039037E-01 a       607     1    12     2     7\n -1.2301874297861546E+00 a       608     1    12     2     8\n -3.7726300799000917E-01 a       609     1    12     2     9\n  1.4054990452727345E+00 a       610     1    12     2    10\n  1.1240582571752584E+00 a       611     1    12     2    11\n -1.3778868152506147E+00 a       612     1    12     2    12\n -1.5842674314283259E-01 a       613     1    12     2    13\n -2.0146095914080617E+00 a       614     1    12     2    14\n  7.7054169453964005E-01 a       615     1    12     2    15\n  1.5927712872721738E+00 a       616     1    13     2     1\n  5.0375728684154875E-01 a       617     1    13     2     2\n -7.6921224117895914E-01 a       618     1    13     2     3\n -3.0199856013515776E+00 a       619     1    13     2     4\n -3.7487627757252695E-01 a       620     1    13     2     5\n -2.8170575777935647E-01 a       621     1    13     2     6\n -5.8585207044898990E-01 a       622     1    13     2     7\n -1.0743693648368418E+00 a       623     1    13     2     8\n  1.3553923914186670E+00 a       624     1    13     2     9\n -1.2583595141121922E+00 a       625     1    13     2    10\n -5.1254794038116869E-01 a       626     1    13     2    11\n -1.3922027707265838E-01 a       627     1    13     2    12\n  1.1779900156090011E+00 a       628     1    13     2    13\n -7.7135713375556014E-01 a       629     1    13     2    14\n  6.3639609911518180E-01 a       630     1    13     2    15\n  4.7604729417697946E+00 a       631     1    14     2     1\n  4.6793081405761043E+00 a       632     1    14     2     2\n  3.3948441436184225E+00 a       633     1    14     2     3\n -3.1278862924891961E+00 a       634     1    14     2     4\n -2.5451861077698306E+00 a       635     1    14     2     5\n  2.9007493089381455E+00 a       636     1    14     2     6\n  1.8535204667202563E+00 a       637     1    14     2     7\n  3.6240309978609702E+00 a       638     1    14     2     8\n  2.1060616972749191E+00 a       639     1    14     2     9\n -2.8865672968583538E+00 a       640     1    14     2    10\n  1.9408484391579959E+00 a       641     1    14     2    11\n  4.2008426960272721E-01 a       642     1    14     2    12\n -2.7439711971860936E-01 a       643     1    14     2    13\n  1.4129046735985789E+00 a       644     1    14     2    14\n  2.6049592328294384E+00 a       645     1    14     2    15\n  6.0350643116147262E-01 a       646     1    15     2     1\n -1.4898366577149469E+00 a       647     1    15     2     2\n  1.0892479813832015E-01 a       648     1    15     2     3\n  7.9970284092818333E-01 a       649     1    15     2     4\n  5.9590325551598011E-01 a       650     1    15     2     5\n -2.1637940006662877E+00 a       651     1    15     2     6\n  7.5955020785500293E-01 a       652     1    15     2     7\n -1.5181143736166489E+00 a       653     1    15     2     8\n  4.8273529527988113E-01 a       654     1    15     2     9\n  2.1363324484178441E+00 a       655     1    15     2    10\n -2.0377432263730544E+00 a       656     1    15     2    11\n -6.0027424840474608E-01 a       657     1    15     2    12\n  1.0600232985952251E+00 a       658     1    15     2    13\n -1.2912224826762091E+00 a       659     1    15     2    14\n  3.6212898504794011E-01 a       660     1    15     2    15\n  1.8559630989489921E+00 b       661     2     1\n -1.5251146011022561E+00 b       662     2     2\n  1.9544202034490237E+00 b       663     2     3\n -1.6653905632026074E+00 b       664     2     4\n -1.0761970018183560E+00 b       665     2     5\n -7.5913047088594787E-01 b       666     2     6\n  8.6757213066618377E-01 b       667     2     7\n  1.2824164531790896E+00 b       668     2     8\n  3.7831098859633636E+00 b       669     2     9\n -2.4255228475055652E+00 b       670     2    10\n -3.0656556981500911E+00 b       671     2    11\n  9.7964586452250613E-01 b       672     2    12\n -1.8257989293154795E+00 b       673     2    13\n  1.7484987918856354E+00 b       674     2    14\n  8.6942928812341413E-01 b       675     2    15\n  1.6982840359681100E+00 a       676     2     1     3     1\n -3.2829655779919680E+00 a       677     2     2     3     1\n -6.2540306116676909E+00 a       678     2     3     3     1\n  1.3541434315983958E+00 a       679     2     4     3     1\n  5.1207889610517201E+00 a       680     2     5     3     1\n -9.1056666111458839E-01 a       681     2     6     3     1\n -2.6371851290658412E+00 a       682     2     7     3     1\n  1.0429931103544281E+00 a       683     2     8     3     1\n  4.7085170902527729E+00 a       684     2     9     3     1\n -1.1540375915055721E+00 a       685     2    10     3     1\n  2.3833051577718360E+00 a       686     2    11     3     1\n  5.0571111551685970E+00 a       687     2    12     3     1\n  2.7451995728299692E+00 a       688     2    13     3     1\n  3.8842127104832600E+00 a       689     2    14     3     1\n  7.3466255552346258E+00 a       690     2    15     3     1\n  4.3718268945892147E+00 b       691     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_develop/hdnnp-data/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  6.5087058178326573E-01 a         1     0     1     1     1\n  3.0373179569952495E+00 a         2     0     1     1     2\n -3.6132730859803659E+00 a         3     0     1     1     3\n -2.2456606938102852E+00 a         4     0     1     1     4\n -2.7341725911215984E+00 a         5     0     1     1     5\n  2.9652859486644556E+00 a         6     0     1     1     6\n -1.4213535338879309E-02 a         7     0     1     1     7\n  4.8787512111159853E-01 a         8     0     1     1     8\n  5.3632972434975477E+00 a         9     0     1     1     9\n -1.1231461720038960E+00 a        10     0     1     1    10\n  6.6266460888869112E+00 a        11     0     1     1    11\n  2.1229557616550605E+00 a        12     0     1     1    12\n -1.7523713762768549E+00 a        13     0     1     1    13\n -2.2957220655274448E+00 a        14     0     1     1    14\n  3.1983745807552699E+00 a        15     0     1     1    15\n -3.5352902775394568E-01 a        16     0     2     1     1\n -2.4936440361762613E+00 a        17     0     2     1     2\n  5.4386128105043303E+00 a        18     0     2     1     3\n  1.7369619860174434E+00 a        19     0     2     1     4\n  4.8165986422292804E+00 a        20     0     2     1     5\n  3.5945419605163692E-01 a        21     0     2     1     6\n -1.4284083712837476E+00 a        22     0     2     1     7\n -2.2660484983366627E+00 a        23     0     2     1     8\n -4.9705533904972414E+00 a        24     0     2     1     9\n -3.1034389102110604E+00 a        25     0     2     1    10\n -4.8995247072445478E+00 a        26     0     2     1    11\n  7.9108802511685705E-01 a        27     0     2     1    12\n  1.4367071661583730E+00 a        28     0     2     1    13\n -1.8157217634188061E+00 a        29     0     2     1    14\n -4.8697745566741242E+00 a        30     0     2     1    15\n  7.8859835835177483E-01 a        31     0     3     1     1\n -1.4085821926014190E+00 a        32     0     3     1     2\n  8.5005598876555943E-01 a        33     0     3     1     3\n  3.0514944182867865E+00 a        34     0     3     1     4\n  1.1090158020851475E+00 a        35     0     3     1     5\n -4.0697102766142619E+00 a        36     0     3     1     6\n  1.1150052689944840E+00 a        37     0     3     1     7\n  9.2095984766708416E-01 a        38     0     3     1     8\n -8.4371541526910292E+00 a        39     0     3     1     9\n  2.5650033092899389E+00 a        40     0     3     1    10\n -2.4192966146384784E+00 a        41     0     3     1    11\n -1.8276621685660919E+00 a        42     0     3     1    12\n  2.0936810180175329E+00 a        43     0     3     1    13\n  2.4079187895993313E+00 a        44     0     3     1    14\n -3.6989909796566636E+00 a        45     0     3     1    15\n  2.9518098446976515E-01 a        46     0     4     1     1\n -5.2048087846331292E-01 a        47     0     4     1     2\n  6.0774447655771424E-01 a        48     0     4     1     3\n -1.6771151940996403E+00 a        49     0     4     1     4\n  9.1729118542874277E-01 a        50     0     4     1     5\n  9.8768939347078588E-01 a        51     0     4     1     6\n -1.3323778151894126E+00 a        52     0     4     1     7\n -4.8500722437593879E-01 a        53     0     4     1     8\n  2.0744585582871680E+00 a        54     0     4     1     9\n -1.6115280480263883E+00 a        55     0     4     1    10\n -5.3503664894535263E-01 a        56     0     4     1    11\n  1.6891506359801034E+00 a        57     0     4     1    12\n -9.4651370538626628E-02 a        58     0     4     1    13\n -1.4744146967056186E+00 a        59     0     4     1    14\n  8.2355762048641068E-01 a        60     0     4     1    15\n -7.2374145175818894E-01 a        61     0     5     1     1\n -3.6410046718751992E+00 a        62     0     5     1     2\n  2.8805968640993092E+00 a        63     0     5     1     3\n  4.6486083494060743E-01 a        64     0     5     1     4\n  2.9419017048240130E+00 a        65     0     5     1     5\n  2.4272469221076223E-01 a        66     0     5     1     6\n -2.3751598905011684E+00 a        67     0     5     1     7\n -3.1283639370512706E+00 a        68     0     5     1     8\n  3.6573279474985023E+00 a        69     0     5     1     9\n  3.5406444902342922E+00 a        70     0     5     1    10\n -7.8412287204160491E-01 a        71     0     5     1    11\n -3.6108246457869198E-01 a        72     0     5     1    12\n -4.5495857193018030E-01 a        73     0     5     1    13\n -1.4734744941192557E-01 a        74     0     5     1    14\n  7.9331734034549550E-01 a        75     0     5     1    15\n  4.7334011821470473E-01 a        76     0     6     1     1\n  2.9473713198189999E-01 a        77     0     6     1     2\n -2.7722222671610024E+00 a        78     0     6     1     3\n -3.3868864542165369E+00 a        79     0     6     1     4\n -2.7305895872494172E+00 a        80     0     6     1     5\n -2.8037046336718074E-01 a        81     0     6     1     6\n -5.7915685590862609E-01 a        82     0     6     1     7\n  4.1920164922224812E-01 a        83     0     6     1     8\n  3.3762033945129413E+00 a        84     0     6     1     9\n -6.5295223774783440E-01 a        85     0     6     1    10\n  2.1354167158716528E+00 a        86     0     6     1    11\n  2.1665072927691433E+00 a        87     0     6     1    12\n -4.1087807992273323E-01 a        88     0     6     1    13\n  1.1352153171654955E+00 a        89     0     6     1    14\n  3.8543983008561242E+00 a        90     0     6     1    15\n -2.6558109684114353E+00 a        91     0     7     1     1\n  1.2819953567671030E+00 a        92     0     7     1     2\n -4.4208731357864250E+00 a        93     0     7     1     3\n -9.6583253108521483E-01 a        94     0     7     1     4\n -4.4526691497952759E+00 a        95     0     7     1     5\n  5.0200348158316643E+00 a        96     0     7     1     6\n -1.8211438960833282E-01 a        97     0     7     1     7\n  4.4676564166426695E+00 a        98     0     7     1     8\n  2.1542552546620173E+00 a        99     0     7     1     9\n -1.8843340574782459E+00 a       100     0     7     1    10\n  2.6836995872288698E+00 a       101     0     7     1    11\n -5.4208527350760416E-01 a       102     0     7     1    12\n -2.9843697253844796E+00 a       103     0     7     1    13\n -6.1922714878314418E+00 a       104     0     7     1    14\n  6.9347577850234003E+00 a       105     0     7     1    15\n  2.1548137734001060E+00 a       106     0     8     1     1\n -1.8167638241118513E+00 a       107     0     8     1     2\n  1.5620528578319168E-01 a       108     0     8     1     3\n -1.0294790758422099E+00 a       109     0     8     1     4\n -1.3699003104058278E+00 a       110     0     8     1     5\n -2.5163165357229649E+00 a       111     0     8     1     6\n -6.9980253260796754E-01 a       112     0     8     1     7\n  7.9951181929358051E-01 a       113     0     8     1     8\n  6.9645389789437806E-01 a       114     0     8     1     9\n -1.8783857374014634E-01 a       115     0     8     1    10\n  3.5248039878464765E+00 a       116     0     8     1    11\n  3.6400739182965176E+00 a       117     0     8     1    12\n -1.2823656295489265E+00 a       118     0     8     1    13\n  5.1281695333399782E+00 a       119     0     8     1    14\n  7.7342280955130778E-04 a       120     0     8     1    15\n -3.6225466468491669E+00 a       121     0     9     1     1\n  4.1491588877594765E+00 a       122     0     9     1     2\n  1.4920809910871493E+00 a       123     0     9     1     3\n -2.7894319999227069E+00 a       124     0     9     1     4\n  4.2267412729476357E+00 a       125     0     9     1     5\n -5.1496860090449248E-01 a       126     0     9     1     6\n  1.0101832196888145E+00 a       127     0     9     1     7\n -9.1676996401829536E-01 a       128     0     9     1     8\n -4.9784687987666807E+00 a       129     0     9     1     9\n -1.0331674116014107E+00 a       130     0     9     1    10\n -9.4313487539762597E-01 a       131     0     9     1    11\n  7.4224791954287073E-01 a       132     0     9     1    12\n  1.2826037538154549E+00 a       133     0     9     1    13\n -1.4868711188109953E+00 a       134     0     9     1    14\n -8.0013299592331446E+00 a       135     0     9     1    15\n -1.4580453352931515E+00 a       136     0    10     1     1\n  1.9657010967405255E+00 a       137     0    10     1     2\n -7.2085889014814946E+00 a       138     0    10     1     3\n  1.5191861918416030E-01 a       139     0    10     1     4\n -4.4149309555100809E+00 a       140     0    10     1     5\n -1.5143801050497223E+00 a       141     0    10     1     6\n  3.9825301054107229E+00 a       142     0    10     1     7\n  2.5989373394598672E+00 a       143     0    10     1     8\n -1.5129039471866623E+00 a       144     0    10     1     9\n  1.8663937881673003E+00 a       145     0    10     1    10\n -1.6379507683513626E+00 a       146     0    10     1    11\n -3.5341403615062745E+00 a       147     0    10     1    12\n  2.4266627335718982E-01 a       148     0    10     1    13\n -8.5133028981710518E-02 a       149     0    10     1    14\n  6.2705223914057484E+00 a       150     0    10     1    15\n  9.0107097262362212E-01 a       151     0    11     1     1\n -7.1422314904671402E-01 a       152     0    11     1     2\n -4.1116648743238828E+00 a       153     0    11     1     3\n  3.3274585590105310E-01 a       154     0    11     1     4\n -5.8892545493023913E+00 a       155     0    11     1     5\n  6.2076720575704236E-01 a       156     0    11     1     6\n  1.0571870511128816E+00 a       157     0    11     1     7\n  3.6680919713593543E+00 a       158     0    11     1     8\n -1.2393884383654330E+00 a       159     0    11     1     9\n 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  418     1    13\n  3.9717272109430179E-01 b       419     1    14\n -1.1306425849619857E+00 b       420     1    15\n -3.7328877194675633E-02 a       421     1     1     2     1\n -1.4158397402432676E+00 a       422     1     1     2     2\n -1.8086435048246935E-01 a       423     1     1     2     3\n -4.4032904127145933E-01 a       424     1     1     2     4\n  2.8545547847500989E+00 a       425     1     1     2     5\n -1.9026299214968803E-01 a       426     1     1     2     6\n -4.7177407212682299E-01 a       427     1     1     2     7\n  1.1189107179458697E+00 a       428     1     1     2     8\n  2.4123475681086623E-01 a       429     1     1     2     9\n  4.5375238549301605E-01 a       430     1     1     2    10\n  3.4219622544599461E-02 a       431     1     1     2    11\n  1.2966300493475166E-01 a       432     1     1     2    12\n -3.4636727425986347E-01 a       433     1     1     2    13\n  4.5791855751445315E-02 a       434     1     1     2    14\n  4.4316471336803298E-01 a       435     1     1     2    15\n  6.4304745296461152E-01 a       436     1     2     2     1\n -2.7350262467521297E-01 a       437     1     2     2     2\n -5.3710812413869680E-01 a       438     1     2     2     3\n -1.0334587659948440E-01 a       439     1     2     2     4\n -1.0433267897662146E+00 a       440     1     2     2     5\n  4.2693997789910987E-01 a       441     1     2     2     6\n -1.2311949003970377E+00 a       442     1     2     2     7\n  1.5303142279853786E-02 a       443     1     2     2     8\n  6.7389152662860344E-02 a       444     1     2     2     9\n  1.1999187511754403E+00 a       445     1     2     2    10\n -8.2767877510973165E-01 a       446     1     2     2    11\n -2.8260511139375133E+00 a       447     1     2     2    12\n -4.6775586505004346E-01 a       448     1     2     2    13\n -3.0462069830640082E-01 a       449     1     2     2    14\n -2.1450157804375549E+00 a       450     1     2     2    15\n  3.6025618195738179E-01 a       451     1     3     2     1\n -1.5954806258840024E-01 a       452     1     3     2     2\n  6.9428867166111918E-01 a       453     1     3     2     3\n  1.6664052485364849E+00 a       454     1     3     2     4\n  1.4140928544109488E+00 a       455     1     3     2     5\n  1.1233155046744747E+00 a       456     1     3     2     6\n  7.6714490216627340E-01 a       457     1     3     2     7\n  1.7845064799815974E-01 a       458     1     3     2     8\n -5.4256851932690739E-02 a       459     1     3     2     9\n  1.0774844294901027E+00 a       460     1     3     2    10\n  1.0969848829939437E+00 a       461     1     3     2    11\n  9.9253395802091837E-01 a       462     1     3     2    12\n -2.0564855430674118E+00 a       463     1     3     2    13\n -1.5895484916211691E-01 a       464     1     3     2    14\n  7.4416719427234734E-01 a       465     1     3     2    15\n -1.2621695929422168E+00 a       466     1     4     2     1\n  1.2774092905605599E+00 a       467     1     4     2     2\n  3.0310775866425343E-01 a       468     1     4     2     3\n -5.0830897157009580E-01 a       469     1     4     2     4\n  1.2471522451227866E+00 a       470     1     4     2     5\n -7.6441384643553811E-01 a       471     1     4     2     6\n -2.4480684885139228E-01 a       472     1     4     2     7\n  1.8185728490466651E+00 a       473     1     4     2     8\n -8.0429993802366195E-01 a       474     1     4     2     9\n -1.1494823198559472E+00 a       475     1     4     2    10\n -9.5460328573065478E-01 a       476     1     4     2    11\n -4.5534062434671718E-01 a       477     1     4     2    12\n  5.1530632775821517E-01 a       478     1     4     2    13\n -3.2804543257268864E-01 a       479     1     4     2    14\n  4.3755548199612104E-01 a       480     1     4     2    15\n  9.1216937433892964E-01 a       481     1     5     2     1\n -9.2987707747766962E-02 a       482     1     5     2     2\n  1.0548645981011171E+00 a       483     1     5     2     3\n  2.1127367446155327E+00 a       484     1     5     2     4\n  7.6210219732364437E-01 a       485     1     5     2     5\n -1.1055538828506959E+00 a       486     1     5     2     6\n  1.9318062930173350E+00 a       487     1     5     2     7\n -6.2898105849048358E-01 a       488     1     5     2     8\n -5.0832031155747491E-02 a       489     1     5     2     9\n  2.3062738553770565E-01 a       490     1     5     2    10\n  3.0164949686184722E-01 a       491     1     5     2    11\n  1.1101730714008793E+00 a       492     1     5     2    12\n -1.4101913957835168E+00 a       493     1     5     2    13\n -1.1712412183012204E+00 a       494     1     5     2    14\n -7.7480854130163215E-02 a       495     1     5     2    15\n  1.5808695011471069E-01 a       496     1     6     2     1\n -2.0207426857684276E+00 a       497     1     6     2     2\n -1.1884566972450408E-01 a       498     1     6     2     3\n  8.0774951253617422E-01 a       499     1     6     2     4\n -2.9282520012991786E-01 a       500     1     6     2     5\n -1.6156813987928962E+00 a       501     1     6     2     6\n  1.3188720315773528E+00 a       502     1     6     2     7\n -1.0026459724217616E+00 a       503     1     6     2     8\n -1.1068423640490670E+00 a       504     1     6     2     9\n  7.9119835592299947E-01 a       505     1     6     2    10\n  2.3303948692350609E+00 a       506     1     6     2    11\n -5.9322188587371993E-01 a       507     1     6     2    12\n -7.6318207109200265E-01 a       508     1     6     2    13\n -2.9263740878858002E-01 a       509     1     6     2    14\n -7.1725313726808215E-01 a       510     1     6     2    15\n  1.2001474726660191E+00 a       511     1     7     2     1\n  5.3387548191070011E-01 a       512     1     7     2     2\n  1.9154072812061729E+00 a       513     1     7     2     3\n -1.4536846896256372E-01 a       514     1     7     2     4\n  7.2361663394440257E-01 a       515     1     7     2     5\n  2.9592170719971800E-01 a       516     1     7     2     6\n -1.9839667620589366E-01 a       517     1     7     2     7\n  1.4761324533019915E+00 a       518     1     7     2     8\n -1.7329930562769677E-01 a       519     1     7     2     9\n -8.1308267819227592E-02 a       520     1     7     2    10\n  7.0690998179482889E-01 a       521     1     7     2    11\n  1.2800774862866200E+00 a       522     1     7     2    12\n  2.2141061873048535E+00 a       523     1     7     2    13\n -5.7577464363333408E-01 a       524     1     7     2    14\n -1.6494442022030403E-01 a       525     1     7     2    15\n  2.3660576092423229E+00 a       526     1     8     2     1\n -1.7835840067819762E+00 a       527     1     8     2     2\n -1.2380935761570890E+00 a       528     1     8     2     3\n -1.0475743381828218E+00 a       529     1     8     2     4\n  2.1328327943522747E+00 a       530     1     8     2     5\n  2.9225480683394482E+00 a       531     1     8     2     6\n  1.1839487364446408E+00 a       532     1     8     2     7\n -3.8595095579081729E-03 a       533     1     8     2     8\n  1.4941139356516566E+00 a       534     1     8     2     9\n -1.5871629368971751E+00 a       535     1     8     2    10\n -1.1806258322074961E+00 a       536     1     8     2    11\n  4.1985440903383087E-01 a       537     1     8     2    12\n  7.5236543730978900E-01 a       538     1     8     2    13\n -1.2310329419891299E+00 a       539     1     8     2    14\n -1.6798394363945528E+00 a       540     1     8     2    15\n -1.9741049943047091E+00 a       541     1     9     2     1\n -3.5312446637901531E+00 a       542     1     9     2     2\n -6.6209759267578772E-01 a       543     1     9     2     3\n  1.1888839625134326E+00 a       544     1     9     2     4\n -8.5478043558468220E-01 a       545     1     9     2     5\n -2.8846115498776204E+00 a       546     1     9     2     6\n  2.0751699596692408E+00 a       547     1     9     2     7\n -5.3969899178807024E-01 a       548     1     9     2     8\n -2.0777875602380811E+00 a       549     1     9     2     9\n  1.4945239157119494E+00 a       550     1     9     2    10\n  1.2660747925252551E+00 a       551     1     9     2    11\n  4.1829737571051254E-02 a       552     1     9     2    12\n -2.0901099363856401E+00 a       553     1     9     2    13\n  3.0543126439328789E+00 a       554     1     9     2    14\n  5.9545430641834061E-02 a       555     1     9     2    15\n  4.9074752159054096E-02 a       556     1    10     2     1\n  1.0361685034859938E+00 a       557     1    10     2     2\n  5.5880815284886687E-01 a       558     1    10     2     3\n  2.1411367067278788E+00 a       559     1    10     2     4\n  1.3797090891711710E+00 a       560     1    10     2     5\n -1.9429754047068961E+00 a       561     1    10     2     6\n -7.7245052813659587E-01 a       562     1    10     2     7\n -1.3709094524616579E+00 a       563     1    10     2     8\n  3.5431408353138666E-01 a       564     1    10     2     9\n  1.7162735653281780E+00 a       565     1    10     2    10\n -9.8468501480590132E-01 a       566     1    10     2    11\n  3.4172638233100625E+00 a       567     1    10     2    12\n  8.7735390554317494E-01 a       568     1    10     2    13\n  4.3446643765443843E-01 a       569     1    10     2    14\n  1.0236908795022091E+00 a       570     1    10     2    15\n -1.5542743726097472E+00 a       571     1    11     2     1\n -2.5343074093855456E-01 a       572     1    11     2     2\n  1.5760461763855993E+00 a       573     1    11     2     3\n  1.1234633900341131E+00 a       574     1    11     2     4\n -4.0561929896608967E-01 a       575     1    11     2     5\n -6.4195451369707571E-02 a       576     1    11     2     6\n  7.6789645263945139E-01 a       577     1    11     2     7\n  9.2678661205446955E-01 a       578     1    11     2     8\n -1.3502633647894097E-01 a       579     1    11     2     9\n  5.7053537422278677E-01 a       580     1    11     2    10\n  7.4353182930669148E-01 a       581     1    11     2    11\n  2.5937750173283352E+00 a       582     1    11     2    12\n -1.5627310648834443E+00 a       583     1    11     2    13\n -3.3524845571249146E-01 a       584     1    11     2    14\n  1.7067699828491517E-01 a       585     1    11     2    15\n -2.3437037863727969E-01 a       586     1    12     2     1\n -1.2207661544976496E+00 a       587     1    12     2     2\n -1.1883239204769573E+00 a       588     1    12     2     3\n -1.4005388531091778E-01 a       589     1    12     2     4\n -1.1251680309191512E+00 a       590     1    12     2     5\n  1.2276219371160790E+00 a       591     1    12     2     6\n  1.4064076990802858E+00 a       592     1    12     2     7\n  6.0891084222362424E-01 a       593     1    12     2     8\n -8.1118051993315965E-01 a       594     1    12     2     9\n -4.5076965043766637E-01 a       595     1    12     2    10\n  2.1432803014636858E-02 a       596     1    12     2    11\n -2.9816322312156873E+00 a       597     1    12     2    12\n -9.1620105186998169E-01 a       598     1    12     2    13\n  1.0856154951338997E+00 a       599     1    12     2    14\n -1.6867149461945197E+00 a       600     1    12     2    15\n  2.4421852657526338E-01 a       601     1    13     2     1\n  4.9651086984463383E-01 a       602     1    13     2     2\n  1.6240112737942176E+00 a       603     1    13     2     3\n  4.4644979305360855E-01 a       604     1    13     2     4\n  1.8529821922359253E+00 a       605     1    13     2     5\n -7.1935201531738513E-01 a       606     1    13     2     6\n -6.5264138334675825E-01 a       607     1    13     2     7\n  1.8348084811680696E+00 a       608     1    13     2     8\n  8.0283242916775785E-02 a       609     1    13     2     9\n -6.6652817435759848E-01 a       610     1    13     2    10\n -1.4832977312663509E+00 a       611     1    13     2    11\n -5.0092250531182034E-03 a       612     1    13     2    12\n  4.5839673266933667E-01 a       613     1    13     2    13\n  1.5207709743456568E+00 a       614     1    13     2    14\n -2.0200042550870714E-01 a       615     1    13     2    15\n -6.3124190881445352E-01 a       616     1    14     2     1\n -2.1951775803253018E-01 a       617     1    14     2     2\n -1.3414671881955751E+00 a       618     1    14     2     3\n  6.9841301205136053E-01 a       619     1    14     2     4\n  6.0822236865978008E-01 a       620     1    14     2     5\n  1.8776814967141049E+00 a       621     1    14     2     6\n  2.9483317487658062E-01 a       622     1    14     2     7\n  2.0888755897408200E+00 a       623     1    14     2     8\n  4.3714360613381203E-01 a       624     1    14     2     9\n -5.4234179150886919E-01 a       625     1    14     2    10\n  1.6140630687643307E+00 a       626     1    14     2    11\n  1.0902541241398622E+00 a       627     1    14     2    12\n -3.0112191182137760E-01 a       628     1    14     2    13\n -5.3156395216958330E-01 a       629     1    14     2    14\n  1.8424571097163966E-01 a       630     1    14     2    15\n -2.1542726670633744E-01 a       631     1    15     2     1\n -1.8063104624308559E+00 a       632     1    15     2     2\n  3.4233937417881044E-01 a       633     1    15     2     3\n  8.3822503589263075E-02 a       634     1    15     2     4\n  3.1785962435438458E-01 a       635     1    15     2     5\n  6.7564366698966216E-01 a       636     1    15     2     6\n  5.9730756378952832E-01 a       637     1    15     2     7\n -1.4786370301621621E-01 a       638     1    15     2     8\n -2.8264592760453416E-01 a       639     1    15     2     9\n  1.0598175032810422E+00 a       640     1    15     2    10\n -2.4100928614248948E-01 a       641     1    15     2    11\n  1.4185398035741263E+00 a       642     1    15     2    12\n  3.9793152116425395E-02 a       643     1    15     2    13\n  4.6185257177966468E-03 a       644     1    15     2    14\n -2.1257207159859899E+00 a       645     1    15     2    15\n -1.4314767080455246E+00 b       646     2     1\n -2.2095572513425386E+00 b       647     2     2\n -3.5653510873522647E+00 b       648     2     3\n -1.4343005552702830E+00 b       649     2     4\n  2.3811827107710117E+00 b       650     2     5\n  1.2874574832224628E-01 b       651     2     6\n -2.3463213671637946E+00 b       652     2     7\n  1.0063310172995978E+00 b       653     2     8\n  1.2952639565345434E+00 b       654     2     9\n -1.0160121759395997E+00 b       655     2    10\n -4.0779730338621514E+00 b       656     2    11\n -4.2277434250257730E+00 b       657     2    12\n  3.0920135209688953E+00 b       658     2    13\n  2.7543193262323804E+00 b       659     2    14\n -2.3525174683336756E+00 b       660     2    15\n  2.6293217819861781E+00 a       661     2     1     3     1\n  4.0867868409862007E+00 a       662     2     2     3     1\n -3.0068760794365907E+00 a       663     2     3     3     1\n -3.8801899652224670E+00 a       664     2     4     3     1\n  2.1584001317194224E+00 a       665     2     5     3     1\n  1.1343219574753758E+00 a       666     2     6     3     1\n -3.1471828236536630E+00 a       667     2     7     3     1\n  1.8797692842927036E+00 a       668     2     8     3     1\n  3.2876320189693216E+00 a       669     2     9     3     1\n -3.9208639132674534E+00 a       670     2    10     3     1\n -2.8677726196476385E+00 a       671     2    11     3     1\n -4.2697917917386183E+00 a       672     2    12     3     1\n  3.4452360380667448E+00 a       673     2    13     3     1\n -2.6134944860112732E+00 a       674     2    14     3     1\n  3.4189601281690716E+00 a       675     2    15     3     1\n  2.1859134472586370E+00 b       676     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_develop/hdnnp-data/weightse.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  5.3201815249319195E-01 a         1     0     1     1     1\n  9.1949997434726871E-02 a         2     0     1     1     2\n -3.9259151253982832E-01 a         3     0     1     1     3\n -4.2316281757438023E-01 a         4     0     1     1     4\n -1.4058239976277095E-01 a         5     0     1     1     5\n  8.1938308896857583E-03 a         6     0     1     1     6\n  4.6855767123270070E-01 a         7     0     1     1     7\n -2.0751456685886785E-01 a         8     0     1     1     8\n  2.6198097982900281E-01 a         9     0     1     1     9\n -7.5989646265032340E-01 a        10     0     1     1    10\n  1.9650615083918799E-01 a        11     0     1     1    11\n -8.7169031136439964E-02 a        12     0     1     1    12\n  4.2242267840758102E-02 a        13     0     1     1    13\n -5.7446637921793164E-01 a        14     0     1     1    14\n  1.2051740955821162E-02 a        15     0     1     1    15\n  1.6389096514425661E-01 a        16     0     2     1     1\n  3.0169595846845715E-01 a        17     0     2     1     2\n  2.5081964684644009E-01 a        18     0     2     1     3\n -7.2001312493847813E-03 a        19     0     2     1     4\n  9.9866950891054768E-02 a        20     0     2     1     5\n  2.2463499968652004E-01 a        21     0     2     1     6\n  4.3791989301539924E-01 a        22     0     2     1     7\n  1.2088515973801436E-01 a        23     0     2     1     8\n -2.9221810419522537E-01 a        24     0     2     1     9\n -6.2582102839685483E-01 a        25     0     2     1    10\n -4.3294558236205311E-01 a        26     0     2     1    11\n -6.9810188216782354E-01 a        27     0     2     1    12\n -6.9632739986717629E-01 a        28     0     2     1    13\n  1.8228857487781652E-01 a        29     0     2     1    14\n -2.4050398553703647E-01 a        30     0     2     1    15\n  3.0726992270702647E-01 a        31     0     3     1     1\n  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1.0432995170143324E+00 a       547     1     9     2     7\n -1.0139790098454039E-01 a       548     1     9     2     8\n  9.0623015053470746E-01 a       549     1     9     2     9\n  3.7991630610564722E-02 a       550     1     9     2    10\n -4.6926431734843044E-01 a       551     1     9     2    11\n  1.8787872755265370E-01 a       552     1     9     2    12\n  3.7374076802318695E-01 a       553     1     9     2    13\n -2.4228714976059126E-01 a       554     1     9     2    14\n  7.6200580304322107E-01 a       555     1     9     2    15\n  1.7981819349888164E+00 a       556     1    10     2     1\n  1.4665804205770824E-01 a       557     1    10     2     2\n  9.0905996631491748E-01 a       558     1    10     2     3\n  2.6431179986033815E-01 a       559     1    10     2     4\n -2.3232395993629898E-01 a       560     1    10     2     5\n -1.1825718523215936E+00 a       561     1    10     2     6\n -2.3858866274451902E-02 a       562     1    10     2     7\n -2.1620580297874593E-02 a       563     1    10     2     8\n -5.7550543096973938E-01 a       564     1    10     2     9\n -4.7910558701559219E-01 a       565     1    10     2    10\n  3.8382752573733742E-01 a       566     1    10     2    11\n -2.3762056705567230E-02 a       567     1    10     2    12\n -2.1040612541712433E-01 a       568     1    10     2    13\n  3.4239220695798117E-01 a       569     1    10     2    14\n -2.1429884947635072E-01 a       570     1    10     2    15\n -1.3895010748024339E-01 a       571     1    11     2     1\n -4.8486260564133320E-02 a       572     1    11     2     2\n -5.1652993104385647E-01 a       573     1    11     2     3\n  7.1062194273845136E-02 a       574     1    11     2     4\n  3.1401050715994916E-01 a       575     1    11     2     5\n  2.2567444934459455E-01 a       576     1    11     2     6\n -7.1970892735980363E-01 a       577     1    11     2     7\n -1.6962330723500851E-01 a       578     1    11     2     8\n  2.8871202853817896E-01 a       579     1    11     2     9\n  1.9688528341328923E-01 a       580     1    11     2    10\n  1.5130834192341686E-01 a       581     1    11     2    11\n  3.1208081927500975E-01 a       582     1    11     2    12\n  2.1666394361228342E-01 a       583     1    11     2    13\n  9.6000758693955524E-02 a       584     1    11     2    14\n  4.0731400088406061E-01 a       585     1    11     2    15\n  5.5381305362117672E-01 a       586     1    12     2     1\n -7.9704916045535049E-02 a       587     1    12     2     2\n -2.4906127594166771E-02 a       588     1    12     2     3\n -5.4614067060148141E-01 a       589     1    12     2     4\n  1.3922302207259705E+00 a       590     1    12     2     5\n -2.9093368873168873E-01 a       591     1    12     2     6\n  1.0829296246845839E-01 a       592     1    12     2     7\n  1.2034544245600124E-03 a       593     1    12     2     8\n -4.0632806587770859E-01 a       594     1    12     2     9\n  3.1497878157248410E-01 a       595     1    12     2    10\n -5.5924135049943435E-01 a       596     1    12     2    11\n -1.3008730014510528E-01 a       597     1    12     2    12\n -2.8558817883814991E-01 a       598     1    12     2    13\n -4.6290325620412437E-02 a       599     1    12     2    14\n -3.1984779708870048E-01 a       600     1    12     2    15\n  1.5294887124471066E+00 a       601     1    13     2     1\n  1.2694494111113727E-01 a       602     1    13     2     2\n  6.7247933055491205E-02 a       603     1    13     2     3\n -2.5150654663660033E-01 a       604     1    13     2     4\n -9.7517320215330594E-01 a       605     1    13     2     5\n -3.7506445843466085E-01 a       606     1    13     2     6\n  4.3810227131070084E-01 a       607     1    13     2     7\n -4.3807252580898154E-01 a       608     1    13     2     8\n -5.1961464494473319E-01 a       609     1    13     2     9\n -8.3266551995970661E-02 a       610     1    13     2    10\n  8.0667307447147396E-02 a       611     1    13     2    11\n -2.7745263854075064E-01 a       612     1    13     2    12\n -3.2322626148572245E-02 a       613     1    13     2    13\n  2.9069751170109687E-01 a       614     1    13     2    14\n  1.3670019998932353E-01 a       615     1    13     2    15\n  3.3589506751048803E-01 a       616     1    14     2     1\n -3.2464820195812066E-01 a       617     1    14     2     2\n  4.9908716986762652E-01 a       618     1    14     2     3\n  3.3466424181570487E-01 a       619     1    14     2     4\n -9.6072942093854596E-01 a       620     1    14     2     5\n  3.1229915259755086E-02 a       621     1    14     2     6\n -4.3711334671187446E-01 a       622     1    14     2     7\n -1.1699473662928556E-01 a       623     1    14     2     8\n -1.1134244032182465E+00 a       624     1    14     2     9\n  2.9989850679877032E-02 a       625     1    14     2    10\n -1.6134890542974747E-01 a       626     1    14     2    11\n  4.2336374028068065E-02 a       627     1    14     2    12\n -2.1687695529852113E-01 a       628     1    14     2    13\n  3.9239770750945667E-02 a       629     1    14     2    14\n -7.3196601073814593E-01 a       630     1    14     2    15\n -4.5271601505879307E-03 a       631     1    15     2     1\n  1.3881388690414706E-01 a       632     1    15     2     2\n -2.3375805252445656E-01 a       633     1    15     2     3\n  1.3996622058371466E-01 a       634     1    15     2     4\n -2.3708068467511018E-01 a       635     1    15     2     5\n -5.8100330460808182E-02 a       636     1    15     2     6\n  5.4065992074137670E-01 a       637     1    15     2     7\n -3.1777395865095093E-01 a       638     1    15     2     8\n -5.3620435518351950E-01 a       639     1    15     2     9\n  5.2199894070266162E-01 a       640     1    15     2    10\n  1.1359895538378711E-01 a       641     1    15     2    11\n  1.7069994461531324E-01 a       642     1    15     2    12\n -2.3525514774954286E-02 a       643     1    15     2    13\n -2.7988407524404352E-01 a       644     1    15     2    14\n -3.1215454303026663E-01 a       645     1    15     2    15\n  1.4652351228694052E-01 b       646     2     1\n -9.6577032071490904E-02 b       647     2     2\n  8.2376024587410071E-02 b       648     2     3\n  1.4510708144492740E-01 b       649     2     4\n -3.9049127867874889E-01 b       650     2     5\n  1.4201292385772604E-01 b       651     2     6\n -2.4583252620937265E-01 b       652     2     7\n  9.3556211862906052E-02 b       653     2     8\n -1.4924904487212751E-01 b       654     2     9\n -2.1614934239174724E-01 b       655     2    10\n  2.1352692475253698E-01 b       656     2    11\n  2.4491312690854122E-03 b       657     2    12\n -2.6565725052780298E-01 b       658     2    13\n -1.1276763202700255E-01 b       659     2    14\n  5.1621249347429277E-03 b       660     2    15\n -2.4162668450663314E+00 a       661     2     1     3     1\n  2.5487933392218282E-01 a       662     2     2     3     1\n -1.3995010614126584E+00 a       663     2     3     3     1\n -9.7078732127554523E-01 a       664     2     4     3     1\n  2.5073762873877969E+00 a       665     2     5     3     1\n  1.2980830473822387E+00 a       666     2     6     3     1\n  1.7932624525556753E+00 a       667     2     7     3     1\n -3.6241282564997351E-01 a       668     2     8     3     1\n  1.4746873739677677E+00 a       669     2     9     3     1\n  8.2877439550304144E-01 a       670     2    10     3     1\n -8.9454959613248719E-01 a       671     2    11     3     1\n -5.7584664908246222E-02 a       672     2    12     3     1\n  6.4222398050106677E-01 a       673     2    13     3     1\n -3.4647782228631116E-02 a       674     2    14     3     1\n  1.2657344986613126E+00 a       675     2    15     3     1\n -5.2796413368386985E-01 b       676     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_develop/hdnnp-data/weightse.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -2.5631224527208313E-01 a         1     0     1     1     1\n -8.0448320240673932E-01 a         2     0     1     1     2\n  8.3550493540857684E-01 a         3     0     1     1     3\n  5.8570801951208229E-02 a         4     0     1     1     4\n -3.1379245718367704E-01 a         5     0     1     1     5\n -1.8703973113879591E-01 a         6     0     1     1     6\n -5.7953676181459128E-02 a         7     0     1     1     7\n -1.2683318062705329E-01 a         8     0     1     1     8\n  9.0256292793796100E-02 a         9     0     1     1     9\n  2.7632599596725194E-02 a        10     0     1     1    10\n  5.3446812970980961E-01 a        11     0     1     1    11\n  5.1683206849276679E-02 a        12     0     1     1    12\n -4.2092159339042735E-02 a        13     0     1     1    13\n -3.0750990041803000E-01 a        14     0     1     1    14\n  5.6386945392164922E-01 a        15     0     1     1    15\n  3.6164534229941420E-01 a        16     0     2     1     1\n -1.8388422644393318E-01 a        17     0     2     1     2\n  9.0136721049944768E-01 a        18     0     2     1     3\n  5.8990375432744924E-01 a        19     0     2     1     4\n  2.3680107572015385E-02 a        20     0     2     1     5\n -4.4854327163580571E-01 a        21     0     2     1     6\n -2.7176977447164824E-02 a        22     0     2     1     7\n -1.3625943877080113E-01 a        23     0     2     1     8\n  1.6974173611630478E-01 a        24     0     2     1     9\n  1.9340768718970747E-01 a        25     0     2     1    10\n -1.3902776402605749E-01 a        26     0     2     1    11\n  2.5327249313832101E-01 a        27     0     2     1    12\n  2.2244186212406888E-01 a        28     0     2     1    13\n  4.4119976375294495E-01 a        29     0     2     1    14\n  2.1825715288986700E-01 a        30     0     2     1    15\n -3.2673732903830710E-01 a        31     0     3     1     1\n -5.0393854486486667E-01 a        32     0     3     1     2\n  1.0605147172342941E-01 a        33     0     3     1     3\n -2.1828563842184479E-01 a        34     0     3     1     4\n -3.8831897021582079E-01 a        35     0     3     1     5\n  9.8768646610608773E-02 a        36     0     3     1     6\n -1.5389597442482683E-01 a        37     0     3     1     7\n -1.1182605242548900E-01 a        38     0     3     1     8\n -1.4950407488235035E-01 a        39     0     3     1     9\n  1.4938748566844037E-01 a        40     0     3     1    10\n  2.2031091763159996E-01 a        41     0     3     1    11\n  2.4864776564200741E-01 a        42     0     3     1    12\n  1.0369306817733541E-01 a        43     0     3     1    13\n -6.7761129460234729E-02 a        44     0     3     1    14\n  2.0792043055358592E-01 a        45     0     3     1    15\n  2.8113394087620119E-01 a        46     0     4     1     1\n -1.8254703020324389E-02 a        47     0     4     1     2\n  7.3941237951308758E-01 a        48     0     4     1     3\n -1.3357600737228681E-01 a        49     0     4     1     4\n -5.7786853241055564E-02 a        50     0     4     1     5\n -2.6921283361745463E-01 a        51     0     4     1     6\n -2.1135503071647352E-01 a        52     0     4     1     7\n -9.6760156288648799E-02 a        53     0     4     1     8\n -9.4129369555837478E-02 a        54     0     4     1     9\n -4.7534121556506770E-02 a        55     0     4     1    10\n -4.1599801218544419E-01 a        56     0     4     1    11\n  7.3948864409019641E-02 a        57     0     4     1    12\n -4.7332048264678150E-01 a        58     0     4     1    13\n  5.4318386104504512E-01 a        59     0     4     1    14\n  1.9019467892899283E-01 a        60     0     4     1    15\n  1.0959195740243370E-01 a        61     0     5     1     1\n -8.2526237629110755E-01 a        62     0     5     1     2\n  3.4216664521574008E-01 a        63     0     5     1     3\n  3.1563504325259145E-01 a        64     0     5     1     4\n -1.1593165248094202E-01 a        65     0     5     1     5\n -3.1270466393123347E-01 a        66     0     5     1     6\n -1.6248420184562690E-01 a        67     0     5     1     7\n  3.5984448336046576E-01 a        68     0     5     1     8\n  8.7315417888880295E-02 a        69     0     5     1     9\n  6.2770697604659220E-01 a        70     0     5     1    10\n  3.0202211676583751E-01 a        71     0     5     1    11\n  2.7370690560417671E-01 a        72     0     5     1    12\n  7.0535654120878075E-02 a        73     0     5     1    13\n  3.5801511433004515E-02 a        74     0     5     1    14\n -2.9551248060022539E-01 a        75     0     5     1    15\n -2.9162135820318719E-01 a        76     0     6     1     1\n -3.4431210951329833E-01 a        77     0     6     1     2\n  3.0962129524391929E-01 a        78     0     6     1     3\n  2.3637686698818694E-01 a        79     0     6     1     4\n  3.7285698567923847E-01 a        80     0     6     1     5\n  2.6553011970269497E-01 a        81     0     6     1     6\n -2.6935826608875879E-01 a        82     0     6     1     7\n  1.2129886794275684E-01 a        83     0     6     1     8\n -9.2089388150925627E-02 a        84     0     6     1     9\n -3.1615060611380325E-01 a        85     0     6     1    10\n -1.6102687777385896E-01 a        86     0     6     1    11\n  3.7371872998129205E-02 a        87     0     6     1    12\n -4.1629482389055389E-01 a        88     0     6     1    13\n -2.2513881890279086E-01 a        89     0     6     1    14\n  2.3681272779664898E-02 a        90     0     6     1    15\n -4.1117208021801321E-01 a        91     0     7     1     1\n -8.0671472609837747E-01 a        92     0     7     1     2\n  2.3095635389379490E-01 a        93     0     7     1     3\n -2.8988205023099317E-01 a        94     0     7     1     4\n -3.5717425155316646E-01 a        95     0     7     1     5\n -1.4764471132531282E-01 a        96     0     7     1     6\n -3.0541937631208127E-01 a        97     0     7     1     7\n -2.5070316540345766E-01 a        98     0     7     1     8\n -6.9367518432231456E-01 a        99     0     7     1     9\n  8.1256810540164773E-02 a       100     0     7     1    10\n -2.3338001934742220E-01 a       101     0     7     1    11\n  1.9250043569145320E-01 a       102     0     7     1    12\n  5.5817852600700224E-01 a       103     0     7     1    13\n  2.6132383992892766E-01 a       104     0     7     1    14\n -2.3765294209931331E-01 a       105     0     7     1    15\n -1.6788883499995105E-01 a       106     0     8     1     1\n -6.0842729437581733E-01 a       107     0     8     1     2\n -6.1482226326399866E-02 a       108     0     8     1     3\n  3.1981078483811581E-01 a       109     0     8     1     4\n -1.3003036771791909E-02 a       110     0     8     1     5\n  1.8522372096075373E-01 a       111     0     8     1     6\n -2.9187417494870971E-01 a       112     0     8     1     7\n  3.0610846327712199E-01 a       113     0     8     1     8\n  4.3938517931933069E-01 a       114     0     8     1     9\n  1.5655783695745634E-01 a       115     0     8     1    10\n -2.6903566819045760E-01 a       116     0     8     1    11\n -1.9605587599409782E-01 a       117     0     8     1    12\n -5.3507527095750573E-01 a       118     0     8     1    13\n  2.0634348079978507E-01 a       119     0     8     1    14\n  2.3568300931111322E-01 a       120     0     8     1    15\n -2.6122731864372162E-01 a       121     0     9     1     1\n -4.9822559852530851E-01 a       122     0     9     1     2\n -4.4230757722044257E-03 a       123     0     9     1     3\n -9.5880161100123040E-02 a       124     0     9     1     4\n  2.6438841336871205E-01 a       125     0     9     1     5\n  2.9613790903471976E-01 a       126     0     9     1     6\n  3.5410009888287068E-02 a       127     0     9     1     7\n  2.2693734284745262E-01 a       128     0     9     1     8\n -5.5610615716073641E-01 a       129     0     9     1     9\n  9.3302234024595906E-02 a       130     0     9     1    10\n -6.5628593555647499E-02 a       131     0     9     1    11\n -3.7345028664766261E-01 a       132     0     9     1    12\n -3.5451436430642824E-01 a       133     0     9     1    13\n -4.5811406879685573E-02 a       134     0     9     1    14\n -4.8491379455213604E-02 a       135     0     9     1    15\n  1.9016739599690216E-01 a       136     0    10     1     1\n -8.7792789803220278E-02 a       137     0    10     1     2\n  5.5242963598115646E-01 a       138     0    10     1     3\n  1.9084540241075790E-01 a       139     0    10     1     4\n  1.2675174688949861E-01 a       140     0    10     1     5\n  3.2439443116690420E-02 a       141     0    10     1     6\n  4.4181561054424535E-02 a       142     0    10     1     7\n -3.2588393741350430E-01 a       143     0    10     1     8\n  1.8855998444621133E-01 a       144     0    10     1     9\n -1.5518203847728804E-01 a       145     0    10     1    10\n -1.5016410461728696E-01 a       146     0    10     1    11\n  1.7628406765011595E-01 a       147     0    10     1    12\n -4.7982829335437394E-01 a       148     0    10     1    13\n -5.6418235192735244E-01 a       149     0    10     1    14\n -3.1448266210847992E-01 a       150     0    10     1    15\n -4.2244976375582100E-01 a       151     0    11     1     1\n  3.3756640754985506E-01 a       152     0    11     1     2\n -3.6455569831181783E-02 a       153     0    11     1     3\n  2.1748446440227404E-01 a       154     0    11     1     4\n  2.8871265590230749E-01 a       155     0    11     1     5\n  8.6392862050570299E-02 a       156     0    11     1     6\n -8.7417834548437601E-02 a       157     0    11     1     7\n  1.4108660883700302E-01 a       158     0    11     1     8\n -1.1755386327347347E-01 a       159     0    11     1     9\n  2.8755427109180998E-02 a       160     0    11     1    10\n -3.1638494361555836E-01 a       161     0    11     1    11\n  2.3051182088286484E-01 a       162     0    11     1    12\n  3.6862468834448311E-02 a       163     0    11     1    13\n  5.6122941841994137E-02 a       164     0    11     1    14\n  3.9980538442576996E-01 a       165     0    11     1    15\n -1.5808312579508527E-01 a       166     0    12     1     1\n -5.1722589306442668E-01 a       167     0    12     1     2\n -3.1549683616603597E-01 a       168     0    12     1     3\n -1.4978407257902004E-01 a       169     0    12     1     4\n -8.0944171661912145E-02 a       170     0    12     1     5\n -1.5491462313734516E-01 a       171     0    12     1     6\n  1.6756538700485709E-02 a       172     0    12     1     7\n  2.2078955339445816E-01 a       173     0    12     1     8\n  4.7041637979743955E-01 a       174     0    12     1     9\n  2.6471410510692778E-01 a       175     0    12     1    10\n 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4.8855318123668140E-01 a       451     1     4     2     1\n -3.9753681565162591E-01 a       452     1     4     2     2\n -1.7791083255354809E-02 a       453     1     4     2     3\n  1.3168575122684029E-01 a       454     1     4     2     4\n -1.7564156037125878E-01 a       455     1     4     2     5\n  7.5989340916749012E-02 a       456     1     4     2     6\n  5.6830345651909608E-01 a       457     1     4     2     7\n -2.6245403917606430E-01 a       458     1     4     2     8\n  5.4041616163295420E-02 a       459     1     4     2     9\n -5.5641165416699410E-02 a       460     1     4     2    10\n  5.2902035911061784E-01 a       461     1     4     2    11\n  4.4417871757467853E-01 a       462     1     4     2    12\n  1.7478493763360886E-01 a       463     1     4     2    13\n -5.0762531071368966E-01 a       464     1     4     2    14\n -1.9057023282832394E-01 a       465     1     4     2    15\n -1.6848910320947585E-01 a       466     1     5     2     1\n -2.5228491003632846E-02 a       467     1     5     2     2\n  3.0514999779401825E-01 a       468     1     5     2     3\n  3.9977724038972862E-01 a       469     1     5     2     4\n  3.3146281416556495E-01 a       470     1     5     2     5\n  3.2928474551055570E-01 a       471     1     5     2     6\n  4.0616586645683350E-02 a       472     1     5     2     7\n  1.2465033915585050E-01 a       473     1     5     2     8\n -2.9858688963426983E-01 a       474     1     5     2     9\n -2.2926389238807819E-02 a       475     1     5     2    10\n -4.0740739502440632E-01 a       476     1     5     2    11\n -3.9662826109221316E-01 a       477     1     5     2    12\n  5.9081340717012223E-02 a       478     1     5     2    13\n -9.6006000337559932E-02 a       479     1     5     2    14\n  7.2852886836106440E-02 a       480     1     5     2    15\n  5.2679627563481124E-01 a       481     1     6     2     1\n  4.1861898132760328E-01 a       482     1     6     2     2\n -2.5972265923234700E-01 a       483     1     6     2     3\n  1.5489832085671879E-01 a       484     1     6     2     4\n  3.0017172905041389E-01 a       485     1     6     2     5\n -3.2156189866678958E-01 a       486     1     6     2     6\n -3.9534898603753715E-01 a       487     1     6     2     7\n -2.7785990307446874E-02 a       488     1     6     2     8\n -2.1961534980259309E-01 a       489     1     6     2     9\n -4.1331463250154576E-01 a       490     1     6     2    10\n -5.0131604326567381E-01 a       491     1     6     2    11\n -5.5007166518486017E-01 a       492     1     6     2    12\n  3.9806013853853173E-01 a       493     1     6     2    13\n  2.4901999900123267E-01 a       494     1     6     2    14\n  1.5141546107976358E-03 a       495     1     6     2    15\n  3.5937371279231178E-01 a       496     1     7     2     1\n  3.8814610523012638E-01 a       497     1     7     2     2\n  1.5213928241109426E-01 a       498     1     7     2     3\n  1.0691648882790723E-01 a       499     1     7     2     4\n  1.0516261205494996E-01 a       500     1     7     2     5\n -3.0169968940306274E-01 a       501     1     7     2     6\n -3.9973241426629343E-02 a       502     1     7     2     7\n  1.2316916680991677E-01 a       503     1     7     2     8\n -1.8249605125124413E-01 a       504     1     7     2     9\n  4.1625662813982961E-01 a       505     1     7     2    10\n -6.1927730984724783E-01 a       506     1     7     2    11\n -3.9710705544546443E-01 a       507     1     7     2    12\n  2.3227857001736893E-01 a       508     1     7     2    13\n -2.4715799417965406E-01 a       509     1     7     2    14\n  7.3039411164989065E-01 a       510     1     7     2    15\n  2.8176137046653216E-01 a       511     1     8     2     1\n -2.6589677398137623E-01 a       512     1     8     2     2\n -2.2896860245051665E-01 a       513     1     8     2     3\n -3.5020711789191095E-01 a       514     1     8     2     4\n  9.9270481858335768E-03 a       515     1     8     2     5\n -1.2079871690244605E-01 a       516     1     8     2     6\n -1.5284860981810200E-01 a       517     1     8     2     7\n -4.0438375159674084E-01 a       518     1     8     2     8\n -3.7534959556968422E-01 a       519     1     8     2     9\n  1.4737424930726584E-01 a       520     1     8     2    10\n  5.5989962242560520E-01 a       521     1     8     2    11\n -1.7135946442561660E-02 a       522     1     8     2    12\n  2.5701746474937948E-02 a       523     1     8     2    13\n  1.8458885030601516E-01 a       524     1     8     2    14\n  3.6863392838041037E-01 a       525     1     8     2    15\n  7.5000494054341571E-01 a       526     1     9     2     1\n -2.2991444283415660E-01 a       527     1     9     2     2\n -8.3205287130462338E-02 a       528     1     9     2     3\n  7.0347542397560237E-01 a       529     1     9     2     4\n -3.7485725160936778E-01 a       530     1     9     2     5\n  2.2400939954238794E-01 a       531     1     9     2     6\n  1.2946816922203580E-01 a       532     1     9     2     7\n  8.0592988506832788E-02 a       533     1     9     2     8\n  3.2078819612234166E-01 a       534     1     9     2     9\n -3.9006586316075542E-01 a       535     1     9     2    10\n  2.2139938281143110E-02 a       536     1     9     2    11\n -1.0093904185146083E+00 a       537     1     9     2    12\n  3.4602055179087110E-01 a       538     1     9     2    13\n  9.1851582323216521E-03 a       539     1     9     2    14\n  1.5026469116177527E-01 a       540     1     9     2    15\n  6.4303198161200847E-01 a       541     1    10     2     1\n -6.3051118633927505E-01 a       542     1    10     2     2\n -6.8004700120774519E-01 a       543     1    10     2     3\n  2.4507092776723863E-01 a       544     1    10     2     4\n  1.1973635115004680E-01 a       545     1    10     2     5\n  6.4968030775506347E-01 a       546     1    10     2     6\n  8.6312924653120227E-01 a       547     1    10     2     7\n  5.9544625693896025E-01 a       548     1    10     2     8\n  7.6728284263885516E-01 a       549     1    10     2     9\n -5.3689735237359060E-01 a       550     1    10     2    10\n  1.2160225690505191E+00 a       551     1    10     2    11\n -9.3106443067395595E-01 a       552     1    10     2    12\n  2.6942866760679207E-01 a       553     1    10     2    13\n -4.1144063365978834E-01 a       554     1    10     2    14\n  4.0976720101470417E-02 a       555     1    10     2    15\n -2.3287993483195885E-01 a       556     1    11     2     1\n -2.0285531198237033E-01 a       557     1    11     2     2\n  6.0559492023610184E-01 a       558     1    11     2     3\n  4.3808911389546623E-02 a       559     1    11     2     4\n  2.5133854030812075E-01 a       560     1    11     2     5\n -4.8110238753646600E-01 a       561     1    11     2     6\n -5.7753147921058001E-01 a       562     1    11     2     7\n -6.7062106434086588E-01 a       563     1    11     2     8\n -8.3206605996018179E-01 a       564     1    11     2     9\n  5.1569637468051510E-01 a       565     1    11     2    10\n  1.2458279763614601E-01 a       566     1    11     2    11\n  4.3954553219958659E-01 a       567     1    11     2    12\n -4.4181364821800850E-01 a       568     1    11     2    13\n  5.3589531314508021E-01 a       569     1    11     2    14\n -2.1273220578724700E-01 a       570     1    11     2    15\n  6.2823844447659638E-01 a       571     1    12     2     1\n -1.4004623735516147E-01 a       572     1    12     2     2\n -1.7363743658317166E-01 a       573     1    12     2     3\n  2.4975299928336750E-01 a       574     1    12     2     4\n  3.1858848743841883E-01 a       575     1    12     2     5\n  1.9564304171328506E-01 a       576     1    12     2     6\n  7.8978155960462659E-01 a       577     1    12     2     7\n  3.8975971596722542E-01 a       578     1    12     2     8\n  1.3011228632838398E-01 a       579     1    12     2     9\n -3.8175333446985465E-01 a       580     1    12     2    10\n  1.0259021037031602E+00 a       581     1    12     2    11\n  2.0761163277819891E-01 a       582     1    12     2    12\n -2.5030653339977205E-01 a       583     1    12     2    13\n -2.8522367516218039E-01 a       584     1    12     2    14\n  3.4564652699058056E-02 a       585     1    12     2    15\n  9.9769207641657046E-02 a       586     1    13     2     1\n -1.7429359955152260E-01 a       587     1    13     2     2\n -5.2284656341984659E-01 a       588     1    13     2     3\n -8.8117831873367969E-02 a       589     1    13     2     4\n -1.7077974318355890E-01 a       590     1    13     2     5\n  1.9743249735614019E-01 a       591     1    13     2     6\n  1.0326294180263389E+00 a       592     1    13     2     7\n  3.2127542428012074E-01 a       593     1    13     2     8\n  6.7003512833250156E-01 a       594     1    13     2     9\n  1.1551584699872490E-01 a       595     1    13     2    10\n  7.1501459689124369E-01 a       596     1    13     2    11\n -6.1937983375803141E-01 a       597     1    13     2    12\n  3.3244902669807508E-01 a       598     1    13     2    13\n  1.0879806593972921E-01 a       599     1    13     2    14\n  1.1109299522419723E-01 a       600     1    13     2    15\n  5.0442700792115813E-01 a       601     1    14     2     1\n -6.7492052728658292E-01 a       602     1    14     2     2\n -6.1017518981120566E-01 a       603     1    14     2     3\n  9.5324676966055999E-01 a       604     1    14     2     4\n -8.3582888008778417E-02 a       605     1    14     2     5\n  9.0069399076941448E-01 a       606     1    14     2     6\n  3.1638877099177526E-01 a       607     1    14     2     7\n  1.5198195279090371E-01 a       608     1    14     2     8\n  7.8030347825819868E-01 a       609     1    14     2     9\n -6.7772460251796507E-01 a       610     1    14     2    10\n  8.3839686096731381E-01 a       611     1    14     2    11\n -6.0730236678937910E-01 a       612     1    14     2    12\n -1.6696104273048409E-01 a       613     1    14     2    13\n -2.0650639860347164E-01 a       614     1    14     2    14\n  4.0424927410365558E-01 a       615     1    14     2    15\n -5.8444139438332088E-01 a       616     1    15     2     1\n  3.7301500890833061E-01 a       617     1    15     2     2\n -9.7011895988837360E-02 a       618     1    15     2     3\n  1.2138605987418914E-01 a       619     1    15     2     4\n -1.3650063888418543E-01 a       620     1    15     2     5\n  2.0366144273098505E-01 a       621     1    15     2     6\n  4.8961409428980462E-01 a       622     1    15     2     7\n -5.2725160863673837E-01 a       623     1    15     2     8\n  1.1346370993521047E-01 a       624     1    15     2     9\n  1.3052696917325579E-01 a       625     1    15     2    10\n -5.2177834720508642E-01 a       626     1    15     2    11\n  3.1664875491531186E-01 a       627     1    15     2    12\n  4.4585727437598094E-01 a       628     1    15     2    13\n  1.4162282897467895E-01 a       629     1    15     2    14\n -6.6183854621321070E-01 a       630     1    15     2    15\n -1.3865724818450345E-01 b       631     2     1\n -1.2153105131829747E-01 b       632     2     2\n  2.7613358823419426E-01 b       633     2     3\n -1.5928982005096509E-01 b       634     2     4\n  9.2202110337080895E-02 b       635     2     5\n -5.7403027370522934E-02 b       636     2     6\n  4.3813625844945317E-02 b       637     2     7\n -1.6392304476941888E-01 b       638     2     8\n  4.7567404672600733E-03 b       639     2     9\n  1.4905536369220515E-01 b       640     2    10\n  1.4033718055254318E-01 b       641     2    11\n  7.5798579839132726E-02 b       642     2    12\n  3.4467320439565970E-02 b       643     2    13\n  1.0645023964972909E-01 b       644     2    14\n -1.6880567709133684E-01 b       645     2    15\n -1.7064693108490390E+00 a       646     2     1     3     1\n  7.7382270023563093E-01 a       647     2     2     3     1\n  1.3433741296611872E+00 a       648     2     3     3     1\n -1.2805957157015400E+00 a       649     2     4     3     1\n  1.3310870197186372E-01 a       650     2     5     3     1\n -1.1109685166686216E+00 a       651     2     6     3     1\n -1.7589605295110935E+00 a       652     2     7     3     1\n -9.0055329744436596E-01 a       653     2     8     3     1\n -1.5080432199854541E+00 a       654     2     9     3     1\n  8.0201729919523168E-01 a       655     2    10     3     1\n -1.8018187579582887E+00 a       656     2    11     3     1\n  1.7045814569414630E+00 a       657     2    12     3     1\n -1.2496126396839006E-02 a       658     2    13     3     1\n  8.3924354137061097E-01 a       659     2    14     3     1\n -1.5185303030453736E+00 a       660     2    15     3     1\n  5.2796413368385731E-01 b       661     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_develop/iceIh_128.data",
    "content": "Generated by ./convert_pgxyzinfo_lammpsdata.sh from iceIh_Cmc21.xyz, comment:\n\n384 atoms\n\n2 atom types\n\n  0.0000000000000000E+00   1.7969000000000001E+01 xlo xhi\n  0.0000000000000000E+00   1.5561600000000000E+01 ylo yhi\n  0.0000000000000000E+00   1.4671620000000001E+01 zlo zhi\n  0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 xy xz yz\n\nAtoms\n\n1 2    7.7574078122432866E-01   2.1919704683420500E+00   3.9845996089839000E+00\n2 1    0.0000000000000000E+00   1.7442755219935400E+00   3.6679050000000002E+00\n3 1    7.7574078122432866E-01   2.1919704683420500E+00   4.9345996089839002E+00\n4 2    7.7574078122432866E-01   4.7860884683420490E+00   3.1669460898389978E-01\n5 1    1.5514815624486591E+00   5.2337834146905600E+00   0.0000000000000000E+00\n6 1    0.0000000000000000E+00   5.2337834146905600E+00   0.0000000000000000E+00\n7 2    3.0218657812243297E+00   6.0823704683420496E+00   3.9845996089839000E+00\n8 1    2.2461249999999993E+00   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1.3415475521993539E+01   3.6679050000000002E+00\n345 1   1.6498615781224331E+01   1.4758858936684099E+01   3.6679891737814803E+00\n346 2   1.6498615781224331E+01   8.6764884683420505E+00   3.1669460898389978E-01\n347 1   1.7274356562448659E+01   9.1241834146905596E+00   0.0000000000000000E+00\n348 1   1.6498615781224331E+01   8.6764884683420505E+00   1.2666946089839000E+00\n349 2   1.6498615781224331E+01   1.3863170468342050E+01   6.7355286089839002E+00\n350 1   1.7274356562448659E+01   1.3415475521993539E+01   7.0522232179678008E+00\n351 1   1.6498615781224331E+01   1.3863170468342050E+01   5.7855286089839000E+00\n352 2   1.6498615781224331E+01   8.6764884683420505E+00   3.0676236089839000E+00\n353 1   1.5722874999999998E+01   9.1241834146905596E+00   3.3843182179678002E+00\n354 1   1.6498615781224331E+01   7.7807999999999948E+00   3.3842340441863201E+00\n355 2   1.8744740781224330E+01   1.2566888468342050E+01   3.0676236089839000E+00\n356 1   1.8744740781224330E+01   1.2566888468342050E+01   2.1176236089838998E+00\n357 1   1.8744740781224330E+01   1.1671199999999990E+01   3.3842340441863201E+00\n358 2   1.4252490781224330E+01   9.9727704683420502E+00   6.7355286089839002E+00\n359 1   1.3476749999999999E+01   9.5250755219935392E+00   7.0522232179678008E+00\n360 1   1.4252490781224330E+01   1.0868458936684110E+01   7.0521390441863172E+00\n361 2   1.4252490781224330E+01   9.9727704683420502E+00   1.1320409608983901E+01\n362 1   1.4252490781224330E+01   9.9727704683420502E+00   1.2270409608983901E+01\n363 1   1.4252490781224330E+01   1.0868458936684110E+01   1.1003799173781481E+01\n364 2   1.4252490781224330E+01   1.2566888468342050E+01   7.6525046089839002E+00\n365 1   1.5028231562448660E+01   1.3014583414690559E+01   7.3358099999999995E+00\n366 1   1.4252490781224330E+01   1.2566888468342050E+01   8.6025046089838995E+00\n367 2   1.6498615781224331E+01   1.3863170468342050E+01   1.1320409608983901E+01\n368 1   1.6498615781224331E+01   1.3863170468342050E+01   1.2270409608983901E+01\n369 1   1.6498615781224331E+01   1.4758858936684099E+01   1.1003799173781481E+01\n370 2   1.6498615781224331E+01   8.6764884683420505E+00   7.6525046089839002E+00\n371 1   1.5722874999999998E+01   9.1241834146905596E+00   7.3358099999999995E+00\n372 1   1.6498615781224331E+01   8.6764884683420505E+00   8.6025046089838995E+00\n373 2   1.6498615781224331E+01   1.3863170468342050E+01   1.4071338608983901E+01\n374 1   1.5722874999999998E+01   1.3415475521993539E+01   1.4388033217967800E+01\n375 1   1.7274356562448659E+01   1.3415475521993539E+01   1.4388033217967800E+01\n376 2   1.6498615781224331E+01   8.6764884683420505E+00   1.0403433608983899E+01\n377 1   1.5722874999999998E+01   9.1241834146905596E+00   1.0720128217967801E+01\n378 1   1.7274356562448659E+01   9.1241834146905596E+00   1.0720128217967801E+01\n379 2   1.8744740781224330E+01   1.2566888468342050E+01   1.0403433608983899E+01\n380 1   1.7969000000000001E+01   1.3014583414690559E+01   1.0720128217967801E+01\n381 1   1.8744740781224330E+01   1.2566888468342050E+01   9.4534336089839002E+00\n382 2   1.4252490781224330E+01   9.9727704683420502E+00   1.4071338608983901E+01\n383 1   1.5028231562448660E+01   9.5250755219935392E+00   1.4388033217967800E+01\n384 1   1.3476749999999999E+01   9.5250755219935392E+00   1.4388033217967800E+01\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_develop/md.lmp",
    "content": "###############################################################################\n# MD simulation for NN water\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"iceIh_128.data\"\n# Timesteps\nvariable numSteps        equal  10\nvariable dt              equal  0.0005\n# NN\nvariable hdnnpCutoff     equal  14.22\nvariable hdnnpDir        string \"hdnnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_O          equal  15.9994\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\n\n# Needed for hdnnp/develop\natom_modify map yes\n\nboundary p p p\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_H}\nmass 2 ${mass_O}\n\ntimestep ${dt}\nthermo 1\n###############################################################################\n# NN\n###############################################################################\n#pair_style hdnnp/develop dir ${hdnnpDir} showew no showewsum 10 resetew no maxew 1000 cflength 1.8897261328 cfenergy 0.0367493254 emap \"1:H,2:O\"\n#pair_coeff * * ${hdnnpCutoff}\npair_style hdnnp/develop ${hdnnpCutoff} dir ${hdnnpDir} showew no showewsum 10 resetew no maxew 1000 cflength 1.8897261328 cfenergy 0.0367493254\npair_coeff * * H O\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\ndump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_external/hdnnp-data/input.nn",
    "content": "## #############################################################\n### This is the input file for RuNNer (version 0_44 and upwards)\n### #############################################################\n### General remarks: \n### - commands can be switched off by using the # character at the BEGINNING of the line\n### - the input file can be structured by blank lines and comment lines\n### - the order of the keywords is arbitrary\n### - if keywords are missing, default values will be used and written to runner.out\n### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message \n\n\n########################################################################################################################\n### general keywords\n########################################################################################################################\nnn_type_short 1                           # 1=Behler-Parrinello, 2=Pair NN\nrunner_mode 3                             # 1=calculate symmetry functions, 2=fitting mode, 3=predicition mode (mode)\n#debug_mode                               # debugging mode                                       (ldebug)\nparallel_mode 1                           # parallelization mode                                 (not fully implemented yet)\n#detailed_timing                          # enable detailed timing                               (lfinetime)(not fully implemented)\nnumber_of_elements 2                      # number of elements                                   (nelem)                       MODE1+2+3+4\nelements O H                              # specification of elements                            (element)                     MODE1+2+3+4\nrandom_seed 10                         # seed for initial random weight parameters and train/test splitting (iseed)         MODE1+2\nrandom_number_type 5                      # 1=ran0, 2=ran1, 3=ran2, 4=ran3\nremove_atom_energies                      # remove atomic energies before fitting                (lremoveatomenergies)         MODE1+2+3+4\natom_energy O -74.94518524                # free atom reference energy (atomic zora)\natom_energy H  -0.45890771                # free atom reference energy (atomic zora)\nenergy_threshold 100.0d0                  # energythreshold for fitting data in Ha per atom      (fitethres)                   MODE1\nbond_threshold 0.4d0                      # threshold for the shortest bond in structure         (rmin)                        MODE1+2+3\n\n########################################################################################################################\n### NN structure of the short-range NN  \n########################################################################################################################\nuse_short_nn                              # use NN for short range interactions                  (lshort) \n#global_output_nodes_short 1               # number of output nodes                               (nodes_short(num_layersshort))\nglobal_hidden_layers_short 2              # number of hidden layers                              (num_layersshort-1)\nglobal_nodes_short 25 25                  # number of nodes in hidden layers                     (nodes_short)\nglobal_activation_short t t l             # activation functions                                 (actfunc_short)\n\n#element_hidden_layers_short H 0         # set number of hidden layers for element \n#element_hidden_layers_short Zn 1         # set number of hidden layers for element \n#element_hidden_layers_short O 2          # set number of hidden layers for element\n#element_nodes_short O 1 9                # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_short O 2 8                # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_short Zn 1 7               # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_short Zn 2 6               # set number of nodes in hidden layer (order: element layer nodes)\n#element_activation_short Zn 1 1 s        # set activation function for node (order: element layer node function)\n\n########################################################################################################################\n### NN structure of the electrostatic NN  \n########################################################################################################################\n#use_electrostatic_nn                      # use NN for electrostatic interactions                (lewald)                             \n#global_output_nodes_electrostatic 1       # number of output nodes                               (nodes_ewald(num_layersewald))\n#global_hidden_layers_electrostatic 2      # number of hidden layers                              (num_layersewald-1)\n#global_nodes_electrostatic 60 60          # number of nodes in hidden layers                     (nodes_ewald)\n#global_activation_electrostatic t t l     # activation functions                                 (actfunc_ewald)\n#ewald_alpha 0.2                           # alpha for Ewald summation (ewaldalpha)! recommended (alpha 0.2/kmax 10) or (alpha 0.5/kmax >20 )\n#ewald_kmax 10                             # parameter Kmax for Ewald summation                   (ewaldkmax)\n#ewald_cutoff 19.0                         # Ewald cutoff                                         (ewaldcutoff)\n\n#element_nodes_electrostatic O 1 5        # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_electrostatic O 2 4        # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_electrostatic Zn 1 3        # set number of nodes in hidden layer (order: element layer nodes)\n#element_nodes_electrostatic Zn 2 2        # set number of nodes in hidden layer (order: element layer nodes)\n#element_activation_electrostatic Zn 1 1 s # set activation function for node (order: element layer node function)\n\n########################################################################################################################\n### symmetry function generation ( mode 1): \n########################################################################################################################\n#use_atom_energies                        # use atomic energies for fitting (not implemented)    (luseatomenergies)                     MODE1+2+3+4\nuse_atom_charges                          # use atomic charges for fitting(set always true!)     (luseatomcharges)                      MODE1+2+3+4\ntest_fraction 0.1                         # threshold for splitting between fitting and test set (splitthres)                           MODE1\n#CAUTION: don't forget use_short_forces below (if you want to generate the training files for the forces)\n\n########################################################################################################################\n### symmetry function definitions (all modes): \n########################################################################################################################\n# INFO: not yet implemented in this file\n# INFO: symfunction format: reference atom, type, neighbor element 1 (and neighbor element 2), symfunction parameters \n#\n# GLOBAL SYMMETRY FUNCTIONS FOR SHORT RANGE NN\n# SAMPLE TYPE 1: global_symfunction_short 1 2.0                           ! type funccutoff \n# SAMPLE TYPE 2: global_symfunction_short 2 7.14214 0.0 11.338            ! type eta rshift funccutoff\n# SAMPLE TYPE 3: global_symfunction_short 3 0.03571 -1.0 16.0  7.55891    ! type eta lambda zeta funccutoff\n# SAMPLE TYPE 4: global_symfunction_short 4 7.14214 11.338                ! type eta funccutoff\n# SAMPLE TYPE 5: global_symfunction_short O 5 1.000                       ! central_atom type eta                         ! CARTESIAN COORDINATES \n# SAMPLE TYPE 6: global_symfunction_short O 6 11.338                      ! central_atom type funccutoff                  ! BOND LENGTH\n#\n# ELEMENT-SPECIFIC SYMMETRY FUNCTIONS FOR SHORT RANGE NN\n# SAMPLE TYPE 1: element_symfunction_short O 1 2.0                        ! central_atom type funccutoff \n# SAMPLE TYPE 2: element_symfunction_short O 2 7.14214 0.0 11.338         ! central_atom type eta rshift funccutoff\n# SAMPLE TYPE 3: element_symfunction_short O 3 0.03571 -1.0 16.0  7.55891 ! central_atom type eta lambda zeta funccutoff\n# SAMPLE TYPE 4: element_symfunction_short O 4 7.14214 11.338             ! central_atom type eta funccutoff\n# SAMPLE TYPE 5: element_symfunction_short O 5 1.000                      ! central_atom type eta                         ! CARTESIAN COORDINATES \n# SAMPLE TYPE 6: element_symfunction_short O 6 11.338                     ! central_atom type funccutoff                  ! BOND LENGTH\n#\n# CUSTOMIZED SYMMETRY FUNCTIONS FOR SHORT RANGE NN\n# SAMPLE TYPE 1: symfunction_short O 1  O 2.0                             ! central_atom type neighbor_atom funccutoff \n# SAMPLE TYPE 2: symfunction_short O 2  O 7.14214 0.0 11.338              ! central_atom type neighbor_atom eta rshift funccutoff\n# SAMPLE TYPE 3: symfunction_short O 3 Zn Zn 0.03571 -1.0 16.0  7.55891   ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n# SAMPLE TYPE 4: symfunction_short O 4  O 7.14214 11.338                  ! central_atom type neighbor_atom eta funccutoff\n# SAMPLE TYPE 5: symfunction_short O 5 1.000                              ! central_atom type eta                         ! CARTESIAN COORDIATES \n# SAMPLE TYPE 6: symfunction_short O 6  O 11.338                          ! central_atom type neighbor_atom funccutoff    ! BOND LENGTH\n\ncutoff_type 2\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.01  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.03  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.06  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.15  1.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.30  1.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 0.60  1.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 H 1.50  1.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\n#\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.01  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.03  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.06  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.15  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.30  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 0.60  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short H 2 O 1.50  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\n#\nsymfunction_short O 2 H 0.001 0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.01  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.03  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.06  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.15  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.30  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 0.60  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 H 1.50  0.9 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\n#\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.01  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.03  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.06  0.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.15  4.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.30  4.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 0.60  4.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\nsymfunction_short O 2 O 1.50  4.0 12.00           \t    ! central_atom type neighbor_atom eta rshift funccutoff\n#\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\n\n#\n# SYMMETRY FUNCTIONS FOR ELECTROSTATIC NN HAVE THE SAME FORMAT, BUT REPLACE \"short\" by \"electrostatic\"\n\n########################################################################################################################\n### fitting (mode 2):general inputs for short range AND electrostatic part:\n########################################################################################################################\nepochs 100                             # number of epochs                                     (nepochs)                              MODE2\npoints_in_memory 500                      # max number of structures in memory                   (nblock)                               MODE2\nmix_all_points                          # training with random order of points                 (lrandomtrain)                         MODE2\n#save_kalman_matrices                      # save Kalman filter matrices                          (lsavekalman)                          MODE2\n#read_kalman_matrices                      # restart using old Kalman filter matrices             (lrestkalman)                          MODE2\nscale_symmetry_functions                  # scale symmetry functions                             (lscalesym)                            MODE2+3+4\ncenter_symmetry_functions                 # remove center of mass of structure function values   (lcentersym)                           MODE2+3+4\n#fix_weights                               # fix some weights                                     (lfixweights)                          MODE2\n#growth_mode 11 6                          # growth mode                                          (lgrowth,ngrowth,growthstep)           MODE2\n#use_damping 0.00001d0                     # use weight decay                                     (ldampw,dampw)                         MODE2\n#pdate_single_element 8                  # do weight update just for one element                (lupdatebyelement,elemupdate)          MODE2\nfitting_unit  eV                           # unit for error output in mode 2 (eV or Ha)\n#joint_energy_force_update                  # for each atom do one update for energy and averaged forces together (not yet working well) \n\n########################################################################################################################\n### fitting options ( mode 2): short range part only:\n########################################################################################################################\noptmode_short_energy 1                     # optimization mode short range energies(optmodee, 1=Kalman filter, 2=conjugate gradient, 3=steepest descent) \noptmode_short_force 1                      # optimization mode short range forces  (optmodef, 1=Kalman filter, 2=conjugate gradient, 3=steepest descent) \nshort_energy_error_threshold 0.8\t   # threshold of adaptive Kalman filter short E          (kalmanthreshold)                      MODE2\nshort_force_error_threshold 0.8\t\t   # threshold of adaptive Kalman filter short F          (kalmanthresholdf)                     MODE2\nkalman_lambda_short 0.98000                # Kalman parameter short E/F                           (kalmanlambda)                         MODE2\nkalman_nue_short 0.99870                   # Kalman parameter short E/F                           (kalmannue)                            MODE2\n#steepest_descent_step_energy_short 0.01d0 # step size for steepest descent energy                (steepeststepe)                        MODE2\n#steepest_descent_step_force_short 0.01d0  # step size for steepest descent force                 (steepeststepf)                        MODE2\n#use_old_weights_short                     # restart fitting with old weight parameters for short (luseoldweightsshort)                  MODE2\n#update_worst_short_energies 0.1d0         # percentage of the worst energies used for update     (worste)                               MODE2\n#update_worst_short_forces 0.1d0           # percentage of the worst forces used for update       (worstf)                               MODE2\nforce_update_scaling -1.0d0               # scaling factor for the force update (negative value means automatic scaling) (scalefactorf) MODE2\n#short_energy_group 1                      # group energies for update                            (nenergygroup)                         MODE2\n#short_energy_fraction 1.00                # percentage of energies used for fitting 100%=1.0     (energyrnd)                            MODE2\nshort_force_group 1                       # group forces for update                              (nforcegroup)                          MODE2\nshort_force_fraction 0.05                  # percentage of forces used for fitting 100%=1.0       (forcernd)                             MODE2 \nuse_short_forces                           # use forces for fitting                               (luseforces)                           MODE2\n#weight_constraint H all fixed             # \"all\" switch\n#weight_constraint O interlayer 1 2 free   # \"interlayer\" layer1 layer2 switch\n#weight_constraint Zn bias 1 2 free        # \"bias layer\" node switch\n#weight_constraint Zn weight 1 3 2 3 free  # \"weight\" layer1 node1 layer2 node2 switch\n#weight_constraint Zn node 1 1 free        # \"node\" layer node switch\nweights_min -1.0                          # minimum value for initial random short range weights\nweights_max 1.0                           # maximum value for initial random short range weights\nprecondition_weights                      # precondition initial weights (lprecond)\n#normalize_nodes                           # normalize input of nodes\nrepeated_energy_update                       # calculate error of\nnguyen_widrow_weights_short              # initialize short\n\n\n########################################################################################################################\n### fitting ( mode 2): electrostatic part only:\n########################################################################################################################\n#optmode_charge 1                          # optimization mode atomic charges      (optmodeq, 1=Kalman filter, 2=conjugate gradient, 3=steepest descent)\n#charge_error_threshold 1.0          # threshold of adaptive Kalman filter charge           (kalmanthresholde)                     MODE2\n#kalman_lambda_charge 0.98000              # Kalman parameter charge                              (kalmanlambdae)                        MODE2\n#kalman_nue_charge 0.99870                 # Kalman parameter charge                              (kalmannuee)                           MODE2\n#steepest_descent_step_charge 0.01d0       # step size for steepest descent charge                (steepeststepq)                        MODE2\n#use_old_weights_charge                    # restart fitting with old weight parameters for charge(luseoldweightscharge)                 MODE2\n#update_worst_charges 0.1d0                # percentage of the worst charges used for update      (worstq)                               MODE2\n#charge_group 20                            # group charges for update                             (nchargegroup)                         MODE2\n#charge_fraction 1.00                      # percentage of charges used for fitting 100%=1.0      (chargernd)                            MODE2\n#weighte_constraint O all fixed              # \"all\" switch\n#weighte_constraint O interlayer 1 2 free    # \"interlayer\" layer1 layer2 switch\n#weighte_constraint Zn bias 1 2 free          # \"bias layer\" node switch\n#weighte_constraint Zn weight 1 3 2 3 free    # \"weight\" layer1 node1 layer2 node2 switch\n#weighte_constraint Zn node 2 1 free          # \"node\" layer node switch\n#precondition_weights                      # precondition initial weights (lprecond)\n#nguyen_widrow_weights_ewald              # initialize short\n#weightse_min -1.0                          # minimum value for initial random charge weights\n#weightse_max 1.0                           # maximum value for initial random charge weights\n\n########################################################################################################################\n### options for charge constraint in mode 2 (not tested! not parallel!)\n########################################################################################################################\n#use_charge_constraint                     # use total charge constraint                          (lchargeconstraint)                    MODE2\n#total_charge_error_threshold 0.0000001    # threshold of adaptive Kalman filter charge constraint(kalmanthresholdc)                     MODE2\n#kalman_lambda_charge_constraint 0.98000   # Kalman parameter charge constraint                   (kalmanlambdac)                        MODE2\n#kalman_nue_charge_constraint 0.99870      # Kalman parameter charge constraint                   (kalmannuec)                           MODE2\n\n########################################################################################################################\n### output options for mode 2 (fitting):  \n########################################################################################################################\n#write_weights_epoch 1                     # write set of weight parameters every ith epoch       (iwriteweight)                         MODE2\n#write_temporary_weights                   # write temporary weights each data block              (lwritetmpweights)                     MODE2\n#write_trainpoints                         # write trainpoints.out and testpoints.out files       (lwritetrainpoints)                    MODE2\n#write_traincharges                        # write traincharges.out and testcharges.out files     (lwritetraincharges)                   MODE2\n#write_trainforces                         # write trainforces.out and testforces.out files       (lwritetrainforces)                    MODE2\n\n########################################################################################################################\n### output options for mode 3 (prediction):  \n########################################################################################################################\ncalculate_forces                          # calculate forces                                     (ldoforces)                            MODE3\n#calculate_stress                          # calculate stress                                     (ldostress)(not fully implemented)     MODE3\n#write_pdb                                 # write predicted structure in pdb format              (lwritepdb)                            MODE3\n#write_xyz                                 # write predicted structure in xyz format              (lwritexyz)                            MODE3\n#write_pov                                 # write predicted structure in pov format              (lwritepov)                            MODE3\n#write_pwscf                               # write predicted structure in pwscf format            (lwritepw)                             MODE3\n\n########################################################################################################################\n### output options for debug.out file  \n########################################################################################################################\n#print_all_short_weights\n#print_all_electrostatic_weights\n\n########################################################################################################################\n### options for mode 4 (not yet working)\n########################################################################################################################\n#symfunction_check_threshold 0.001d0       # threshold for symmetry function check                (symthres)                             MODE4\n#charge_check_threshold 0.0002d0           # threshold for atomic charge check                    (chargethres)                          MODE4\n#force_check_threshold 0.0003d0            # threshold for atomic force check                     (forcethres)                           MODE4\n#energy_check_threshold 0.0004d0           # threshold for atomic energy check                    (energythres)(not yet implemented)     MODE4\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_external/hdnnp-data/scaling.data",
    "content": "   1    1        1.088201664       9.616641912       2.270109565\n   1    2        0.732744389       5.002855932       1.327702465\n   1    3        0.760107838       7.142794297       1.647742147\n   1    4        0.548422859       3.766177117       1.016703770\n   1    5        0.400806651       4.146983240       0.909602933\n   1    6        0.362093522       2.267823940       0.649481595\n   1    7        0.189191039       2.229265268       0.457092189\n   1    8        0.267041787       1.320874236       0.424021804\n   1    9        0.245130998       0.947511607       0.362454975\n   1   10        0.222489101       2.759621601       0.539082969\n   1   11        0.147436017       0.555992707       0.267708440\n   1   12        0.099110926       1.726540533       0.295581816\n   1   13        0.065093699       0.345217577       0.185155535\n   1   14        0.031653527       0.912931701       0.150225678\n   1   15        0.002920282       0.264539818       0.076473362\n   1   16        0.000321454       0.286964256       0.045764109\n   1   17        0.000246938       0.138487311       0.017696446\n   1   18        0.005099284       0.583191737       0.023872131\n   1   19        0.000322830       0.216139623       0.017077760\n   1   20        0.049647513       1.685161743       0.145479047\n   1   21        0.003407347       0.316370718       0.018433754\n   1   22        0.000131214       0.102583489       0.006372278\n   1   23        0.033813163       0.916185609       0.081291971\n   1   24        0.000417085       0.157859670       0.004669432\n   1   25        0.000735289       0.059225627       0.003705331\n   1   26        0.008982833       0.194260856       0.024091451\n   1   27        0.000212280       0.008777781       0.002053455\n   2    1        1.517044076      10.005711989       2.655404931\n   2    2        0.446766389       4.619540936       0.966350390\n   2    3        1.193931096       7.532354409       2.033407541\n   2    4        0.275760365       3.386213103       0.659640224\n   2    5        0.821855400       4.535648125       1.298963189\n   2    6        0.105170538       1.890987754       0.306914986\n   2    7        0.569491417       2.615432862       0.848043608\n   2    8        0.025104990       0.936410342       0.111481479\n   2    9        0.513541617       1.854534178       0.724909950\n   2   10        0.118789489       2.912145690       0.475036427\n   2   11        0.352693173       1.062836509       0.535416881\n   2   12        0.030424314       2.527764277       0.316746678\n   2   13        0.159800227       0.631218183       0.370311070\n   2   14        0.002786809       2.303005782       0.177515943\n   2   15        0.009564104       0.390852331       0.152946724\n   2   16        0.000003880       2.036706882       0.054190131\n   2   17        0.002472623       0.343354006       0.016697369\n   2   18        0.000022353       0.056319317       0.000955763\n   2   19        0.054785372       3.018259758       0.204054793\n   2   20        0.001379524       0.498788004       0.012802849\n   2   21        0.006685277       0.267395828       0.030865481\n   2   22        0.017021399       1.416779651       0.076329790\n   2   23        0.019759832       0.407563783       0.048851573\n   2   24        0.000592976       0.233240507       0.007212399\n   2   25        0.000011145       0.035285773       0.000426102\n   2   26        0.017309321       0.822454100       0.050874152\n   2   27        0.004098051       0.785570314       0.036954443\n   2   28        0.000040524       0.098448069       0.001213796\n   2   29        0.006037465       0.098674752       0.016153531\n   2   30        0.002959549       0.154785376       0.011643250\n       -0.2378336387       -0.1948975729\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_external/hdnnp-data/weights.001.data",
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a        54     0     3     1     4\n     -0.0057520752 a        55     0     3     1     5\n      0.3066541236 a        56     0     3     1     6\n     -0.0484807758 a        57     0     3     1     7\n      0.2401205472 a        58     0     3     1     8\n     -0.4227675745 a        59     0     3     1     9\n      1.3328495997 a        60     0     3     1    10\n     -0.5334636802 a        61     0     3     1    11\n     -0.5992628199 a        62     0     3     1    12\n      0.8085682112 a        63     0     3     1    13\n      0.6180749319 a        64     0     3     1    14\n      0.8070953921 a        65     0     3     1    15\n     -0.5343615213 a        66     0     3     1    16\n      0.7746093862 a        67     0     3     1    17\n      0.2386220441 a        68     0     3     1    18\n      0.1311285270 a        69     0     3     1    19\n     -0.5274542195 a        70     0     3     1    20\n      0.0941941293 a        71     0     3     1    21\n     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14\n      0.3957786185 a        90     0     4     1    15\n     -0.2757012873 a        91     0     4     1    16\n     -1.1671968770 a        92     0     4     1    17\n      0.4498673301 a        93     0     4     1    18\n      0.3219881887 a        94     0     4     1    19\n      1.1560311040 a        95     0     4     1    20\n      1.0517279568 a        96     0     4     1    21\n      1.5859444628 a        97     0     4     1    22\n      0.6165257833 a        98     0     4     1    23\n      0.9164424251 a        99     0     4     1    24\n     -0.1549103257 a       100     0     4     1    25\n      0.8878136706 a       101     0     5     1     1\n      0.6683308831 a       102     0     5     1     2\n      0.2636251772 a       103     0     5     1     3\n      1.3024585424 a       104     0     5     1     4\n      0.8710929943 a       105     0     5     1     5\n      0.3952247481 a       106     0     5     1     6\n      0.1457163533 a       107     0     5   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1.5421154504 a       179     0     8     1     4\n      1.4099032448 a       180     0     8     1     5\n     -0.7264449033 a       181     0     8     1     6\n      0.4691643687 a       182     0     8     1     7\n     -0.4840883213 a       183     0     8     1     8\n     -0.5423218633 a       184     0     8     1     9\n     -0.1180396293 a       185     0     8     1    10\n      1.2161661752 a       186     0     8     1    11\n      0.1583151175 a       187     0     8     1    12\n      0.0493063615 a       188     0     8     1    13\n     -1.0670567955 a       189     0     8     1    14\n     -1.8917611535 a       190     0     8     1    15\n      1.2372326769 a       191     0     8     1    16\n      0.0716974137 a       192     0     8     1    17\n      0.2629331870 a       193     0     8     1    18\n     -0.0425632922 a       194     0     8     1    19\n     -0.5293580787 a       195     0     8     1    20\n      0.2732681603 a       196     0     8     1    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3\n     -0.5877754957 a       304     0    13     1     4\n      0.7131031711 a       305     0    13     1     5\n     -0.0876124563 a       306     0    13     1     6\n     -0.5361043818 a       307     0    13     1     7\n      0.4402045517 a       308     0    13     1     8\n     -0.1816561289 a       309     0    13     1     9\n      0.0221635205 a       310     0    13     1    10\n     -0.3525013857 a       311     0    13     1    11\n     -0.1201611864 a       312     0    13     1    12\n      0.4566999491 a       313     0    13     1    13\n     -0.2408349282 a       314     0    13     1    14\n     -0.7548810952 a       315     0    13     1    15\n      0.9575973316 a       316     0    13     1    16\n     -0.1469151538 a       317     0    13     1    17\n     -0.5720421187 a       318     0    13     1    18\n      0.2022969539 a       319     0    13     1    19\n     -0.5086027171 a       320     0    13     1    20\n     -0.0232005197 a       321     0    13    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 14     1    14\n      0.2692705344 a       340     0    14     1    15\n      0.1627085938 a       341     0    14     1    16\n      0.8786022206 a       342     0    14     1    17\n      0.0164511620 a       343     0    14     1    18\n      0.3017961109 a       344     0    14     1    19\n      1.9192553195 a       345     0    14     1    20\n      0.2357337426 a       346     0    14     1    21\n     -1.2230192155 a       347     0    14     1    22\n     -0.7760583854 a       348     0    14     1    23\n     -0.9719718561 a       349     0    14     1    24\n      0.4901846322 a       350     0    14     1    25\n      0.7986447982 a       351     0    15     1     1\n     -0.5778194791 a       352     0    15     1     2\n      0.4902847759 a       353     0    15     1     3\n      0.4497028504 a       354     0    15     1     4\n      0.4232120769 a       355     0    15     1     5\n      0.3199478766 a       356     0    15     1     6\n     -0.0204728649 a       357  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10\n      0.2133805441 a       411     0    17     1    11\n      1.5071209918 a       412     0    17     1    12\n      0.4900472948 a       413     0    17     1    13\n      0.1625163678 a       414     0    17     1    14\n      0.1453448982 a       415     0    17     1    15\n     -0.7755564559 a       416     0    17     1    16\n     -0.8366412481 a       417     0    17     1    17\n      1.0543696826 a       418     0    17     1    18\n      0.2920363042 a       419     0    17     1    19\n      0.2781414582 a       420     0    17     1    20\n     -0.4543622719 a       421     0    17     1    21\n     -0.6145329733 a       422     0    17     1    22\n      0.1255424116 a       423     0    17     1    23\n      0.0310109269 a       424     0    17     1    24\n     -0.2846477163 a       425     0    17     1    25\n     -0.3854747312 a       426     0    18     1     1\n      0.0870068451 a       427     0    18     1     2\n     -0.0889898301 a       428     0    18   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0.5230697331 a       500     0    20     1    25\n      0.5158802542 a       501     0    21     1     1\n      0.9473184967 a       502     0    21     1     2\n      0.1351680221 a       503     0    21     1     3\n      0.9225937969 a       504     0    21     1     4\n      0.8246581647 a       505     0    21     1     5\n      0.5654030831 a       506     0    21     1     6\n     -1.4221104561 a       507     0    21     1     7\n     -0.8452399497 a       508     0    21     1     8\n     -0.0400058657 a       509     0    21     1     9\n     -0.6492811242 a       510     0    21     1    10\n      0.7293860605 a       511     0    21     1    11\n      0.6886017793 a       512     0    21     1    12\n     -0.0289279562 a       513     0    21     1    13\n     -0.6517433614 a       514     0    21     1    14\n      1.0281504327 a       515     0    21     1    15\n      0.7233169020 a       516     0    21     1    16\n     -1.5386100966 a       517     0    21     1    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24\n     -0.4448243105 a       625     0    25     1    25\n      0.2744485215 a       626     0    26     1     1\n     -0.8513896798 a       627     0    26     1     2\n      0.1640210684 a       628     0    26     1     3\n      0.1345189667 a       629     0    26     1     4\n      0.6285565186 a       630     0    26     1     5\n      0.0456189212 a       631     0    26     1     6\n      0.4014092888 a       632     0    26     1     7\n     -0.1629949863 a       633     0    26     1     8\n      0.3995526084 a       634     0    26     1     9\n      0.0403671042 a       635     0    26     1    10\n     -1.5428738555 a       636     0    26     1    11\n      0.3538432273 a       637     0    26     1    12\n     -0.0887796318 a       638     0    26     1    13\n      0.7421204021 a       639     0    26     1    14\n      0.7929835437 a       640     0    26     1    15\n      0.6039578388 a       641     0    26     1    16\n     -2.1189003495 a       642     0    26   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22\n     -0.1837362420 a       773     1     3     2    23\n     -0.0793250995 a       774     1     3     2    24\n      0.3557317192 a       775     1     3     2    25\n      0.3711258010 a       776     1     4     2     1\n     -0.9655094619 a       777     1     4     2     2\n     -0.2108388755 a       778     1     4     2     3\n      0.0552788822 a       779     1     4     2     4\n     -0.0214891552 a       780     1     4     2     5\n      0.3389395553 a       781     1     4     2     6\n     -0.8905061606 a       782     1     4     2     7\n     -0.4336203334 a       783     1     4     2     8\n      0.1511191358 a       784     1     4     2     9\n     -0.4072275488 a       785     1     4     2    10\n     -0.1531892564 a       786     1     4     2    11\n      0.5528230933 a       787     1     4     2    12\n     -0.0136787803 a       788     1     4     2    13\n      0.6250714091 a       789     1     4     2    14\n      0.5047873465 a       790     1     4   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0.1861094485 a       862     1     7     2    12\n     -0.0221707845 a       863     1     7     2    13\n     -0.0357880573 a       864     1     7     2    14\n     -0.8377531200 a       865     1     7     2    15\n     -0.0609889730 a       866     1     7     2    16\n      0.1834895576 a       867     1     7     2    17\n     -0.2332994835 a       868     1     7     2    18\n      0.2150454282 a       869     1     7     2    19\n     -0.5970324314 a       870     1     7     2    20\n      0.1215000649 a       871     1     7     2    21\n     -0.2049832941 a       872     1     7     2    22\n     -0.2032397356 a       873     1     7     2    23\n      0.9035182640 a       874     1     7     2    24\n     -0.1710711465 a       875     1     7     2    25\n     -0.6593603401 a       876     1     8     2     1\n      0.4782153076 a       877     1     8     2     2\n     -0.8486803989 a       878     1     8     2     3\n      0.2336199023 a       879     1     8     2     4\n      0.4661943881 a       880     1     8     2     5\n      0.5930919644 a       881     1     8     2     6\n      0.6222017702 a       882     1     8     2     7\n      0.5366666154 a       883     1     8     2     8\n     -0.9569363458 a       884     1     8     2     9\n     -0.2476196981 a       885     1     8     2    10\n      0.2661967732 a       886     1     8     2    11\n     -0.1431840923 a       887     1     8     2    12\n      0.3074401466 a       888     1     8     2    13\n      0.0697948912 a       889     1     8     2    14\n      0.1174940380 a       890     1     8     2    15\n     -0.3814567990 a       891     1     8     2    16\n     -0.0580013031 a       892     1     8     2    17\n     -0.4233214680 a       893     1     8     2    18\n     -0.7184726593 a       894     1     8     2    19\n     -0.6174438367 a       895     1     8     2    20\n      0.1045705160 a       896     1     8     2    21\n     -0.9040333955 a       897     1     8     2    22\n     -0.1889575997 a       898     1     8     2    23\n     -0.6421070264 a       899     1     8     2    24\n      0.0536162439 a       900     1     8     2    25\n      0.6591748608 a       901     1     9     2     1\n     -0.5599899623 a       902     1     9     2     2\n     -0.7565812741 a       903     1     9     2     3\n     -0.3451495701 a       904     1     9     2     4\n      0.2619505414 a       905     1     9     2     5\n      0.0473457026 a       906     1     9     2     6\n     -0.1643215786 a       907     1     9     2     7\n     -0.3780998812 a       908     1     9     2     8\n     -0.6702783807 a       909     1     9     2     9\n      0.0369976854 a       910     1     9     2    10\n      0.0167359085 a       911     1     9     2    11\n     -0.5398455835 a       912     1     9     2    12\n     -0.2453761193 a       913     1     9     2    13\n      0.1804898550 a       914     1     9     2    14\n     -0.2416108348 a       915     1   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   1    10     2     8\n     -0.1760006093 a       934     1    10     2     9\n     -0.3230880365 a       935     1    10     2    10\n     -0.4851780473 a       936     1    10     2    11\n     -0.0058269713 a       937     1    10     2    12\n      0.1166814547 a       938     1    10     2    13\n      0.3454250707 a       939     1    10     2    14\n      0.1645989847 a       940     1    10     2    15\n     -0.1484306340 a       941     1    10     2    16\n      0.0529273030 a       942     1    10     2    17\n      0.4423031519 a       943     1    10     2    18\n     -0.4847660242 a       944     1    10     2    19\n      0.6818632386 a       945     1    10     2    20\n      0.1015173575 a       946     1    10     2    21\n      0.2774474407 a       947     1    10     2    22\n      1.1348861126 a       948     1    10     2    23\n     -0.8335332525 a       949     1    10     2    24\n     -0.1332202090 a       950     1    10     2    25\n      0.0801984566 a       951     1    11     2     1\n     -0.3228878137 a       952     1    11     2     2\n     -0.1693614645 a       953     1    11     2     3\n      0.3725228802 a       954     1    11     2     4\n     -0.0445533902 a       955     1    11     2     5\n      0.4861759195 a       956     1    11     2     6\n      0.7900266525 a       957     1    11     2     7\n      0.0759923271 a       958     1    11     2     8\n     -0.0404313323 a       959     1    11     2     9\n     -0.3148097795 a       960     1    11     2    10\n     -0.3644949138 a       961     1    11     2    11\n      0.8054303656 a       962     1    11     2    12\n     -0.0108671994 a       963     1    11     2    13\n     -0.1169143755 a       964     1    11     2    14\n      0.3788326165 a       965     1    11     2    15\n     -0.5658553019 a       966     1    11     2    16\n      0.3059616400 a       967     1    11     2    17\n     -0.3176649217 a       968     1    11     2    18\n     -0.2778649945 a       969     1    11     2    19\n      0.7039206920 a       970     1    11     2    20\n      1.0909542445 a       971     1    11     2    21\n      0.3255016232 a       972     1    11     2    22\n      0.9696536131 a       973     1    11     2    23\n     -0.0631143210 a       974     1    11     2    24\n     -0.0903252819 a       975     1    11     2    25\n     -0.4317353115 a       976     1    12     2     1\n     -0.1033292612 a       977     1    12     2     2\n      0.7076354512 a       978     1    12     2     3\n     -0.4515761478 a       979     1    12     2     4\n      0.1575430804 a       980     1    12     2     5\n      0.0806955529 a       981     1    12     2     6\n      0.7784035988 a       982     1    12     2     7\n     -0.0661548504 a       983     1    12     2     8\n      0.1105768113 a       984     1    12     2     9\n      0.5293655079 a       985     1    12     2    10\n     -0.6135924350 a       986     1    12     2    11\n     -1.3016283024 a       987     1    12     2    12\n      0.0960549277 a       988     1    12     2    13\n      0.0908668132 a       989     1    12     2    14\n      0.7708530863 a       990     1    12     2    15\n     -0.0508620412 a       991     1    12     2    16\n     -0.6686270366 a       992     1    12     2    17\n     -0.3065474627 a       993     1    12     2    18\n      0.5171179238 a       994     1    12     2    19\n     -0.7411792894 a       995     1    12     2    20\n      0.9787388893 a       996     1    12     2    21\n      0.1161451158 a       997     1    12     2    22\n      0.4154997271 a       998     1    12     2    23\n      0.1316038634 a       999     1    12     2    24\n     -0.9659837213 a      1000     1    12     2    25\n      0.0171075897 a      1001     1    13     2     1\n     -0.4168701878 a      1002     1    13     2     2\n      0.6242696104 a      1003     1    13     2     3\n     -0.8076143507 a      1004     1    13     2     4\n     -0.3254994109 a      1005     1    13     2     5\n     -0.1675340375 a      1006     1    13     2     6\n      0.0065918669 a      1007     1    13     2     7\n     -0.0475603898 a      1008     1    13     2     8\n     -0.6383433558 a      1009     1    13     2     9\n     -0.1113436214 a      1010     1    13     2    10\n      0.5479730050 a      1011     1    13     2    11\n     -0.3051368270 a      1012     1    13     2    12\n      0.0992574333 a      1013     1    13     2    13\n      0.1650402180 a      1014     1    13     2    14\n      0.6561600670 a      1015     1    13     2    15\n     -0.3578145667 a      1016     1    13     2    16\n     -1.4141336289 a      1017     1    13     2    17\n      0.3299122773 a      1018     1    13     2    18\n      1.3365952072 a      1019     1    13     2    19\n     -0.5125722699 a      1020     1    13     2    20\n      0.2137876087 a      1021     1    13     2    21\n     -0.4282606253 a      1022     1  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    1    14     2    15\n      0.5542548783 a      1041     1    14     2    16\n      0.3912643133 a      1042     1    14     2    17\n      0.7670803223 a      1043     1    14     2    18\n     -0.0457746751 a      1044     1    14     2    19\n      0.2506962819 a      1045     1    14     2    20\n     -0.2674431129 a      1046     1    14     2    21\n      0.5117627223 a      1047     1    14     2    22\n     -0.3002284257 a      1048     1    14     2    23\n     -0.0086690560 a      1049     1    14     2    24\n      0.7459057535 a      1050     1    14     2    25\n      0.8371466976 a      1051     1    15     2     1\n      1.5674021096 a      1052     1    15     2     2\n      0.2557427846 a      1053     1    15     2     3\n      1.4829361085 a      1054     1    15     2     4\n      0.1444695628 a      1055     1    15     2     5\n     -0.0782513640 a      1056     1    15     2     6\n     -0.5129214416 a      1057     1    15     2     7\n      0.2970221657 a      1058     1    15     2     8\n     -0.0474002938 a      1059     1    15     2     9\n      0.6106742624 a      1060     1    15     2    10\n      0.2175685149 a      1061     1    15     2    11\n     -1.0231819125 a      1062     1    15     2    12\n     -1.1346553680 a      1063     1    15     2    13\n     -1.3248890856 a      1064     1    15     2    14\n     -0.3352895715 a      1065     1    15     2    15\n     -0.2080889924 a      1066     1    15     2    16\n     -0.2903220167 a      1067     1    15     2    17\n      0.2978982413 a      1068     1    15     2    18\n     -0.2508691077 a      1069     1    15     2    19\n      0.1707126281 a      1070     1    15     2    20\n     -0.4311867886 a      1071     1    15     2    21\n      0.1964524577 a      1072     1    15     2    22\n      0.5100944582 a      1073     1    15     2    23\n     -0.0624844283 a      1074     1    15     2    24\n      0.1517147856 a      1075     1    15     2    25\n      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18\n     -0.3092507416 a      1094     1    16     2    19\n     -0.6692428706 a      1095     1    16     2    20\n     -0.4587126123 a      1096     1    16     2    21\n     -0.3103848106 a      1097     1    16     2    22\n      0.3692718422 a      1098     1    16     2    23\n      0.3203906544 a      1099     1    16     2    24\n     -0.1771469861 a      1100     1    16     2    25\n     -0.3137509547 a      1101     1    17     2     1\n      0.3245885547 a      1102     1    17     2     2\n      0.7603576131 a      1103     1    17     2     3\n      0.2744152432 a      1104     1    17     2     4\n      0.7366883885 a      1105     1    17     2     5\n     -0.0226266806 a      1106     1    17     2     6\n     -0.2782025698 a      1107     1    17     2     7\n     -0.3300147038 a      1108     1    17     2     8\n     -0.7754807753 a      1109     1    17     2     9\n     -0.8785115890 a      1110     1    17     2    10\n     -0.2840265820 a      1111     1    17   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    1    18     2    22\n      0.3218681670 a      1148     1    18     2    23\n      0.4261292864 a      1149     1    18     2    24\n     -0.1862489169 a      1150     1    18     2    25\n     -0.9834227109 a      1151     1    19     2     1\n     -0.0911827078 a      1152     1    19     2     2\n     -0.2005261461 a      1153     1    19     2     3\n      0.6900915994 a      1154     1    19     2     4\n     -0.4950527151 a      1155     1    19     2     5\n      0.4037905710 a      1156     1    19     2     6\n      0.5485415449 a      1157     1    19     2     7\n      0.3974062148 a      1158     1    19     2     8\n     -0.1323415107 a      1159     1    19     2     9\n      0.2374162689 a      1160     1    19     2    10\n     -0.8819445396 a      1161     1    19     2    11\n      0.3740653957 a      1162     1    19     2    12\n     -0.3785612222 a      1163     1    19     2    13\n      0.3817377412 a      1164     1    19     2    14\n     -0.0665657326 a    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  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_external/hdnnp-data/weights.008.data",
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0.3054075378 a       500     0    20     1    25\n     -1.1435921258 a       501     0    21     1     1\n     -0.5998808148 a       502     0    21     1     2\n      0.9242796121 a       503     0    21     1     3\n      0.0463785957 a       504     0    21     1     4\n      0.3014189009 a       505     0    21     1     5\n     -0.7652887802 a       506     0    21     1     6\n     -2.0403308872 a       507     0    21     1     7\n      0.5096039981 a       508     0    21     1     8\n      0.2699604442 a       509     0    21     1     9\n     -0.2807822090 a       510     0    21     1    10\n     -0.1784854860 a       511     0    21     1    11\n      0.5029684300 a       512     0    21     1    12\n     -0.3700564148 a       513     0    21     1    13\n      0.3349805793 a       514     0    21     1    14\n     -0.2380831148 a       515     0    21     1    15\n     -0.4546820650 a       516     0    21     1    16\n      0.7827236389 a       517     0    21     1    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6\n     -1.5064513922 a       732     0    30     1     7\n      0.2333195769 a       733     0    30     1     8\n      0.4895038745 a       734     0    30     1     9\n      0.5326030289 a       735     0    30     1    10\n      0.1563484830 a       736     0    30     1    11\n      0.8222201126 a       737     0    30     1    12\n     -0.4317201721 a       738     0    30     1    13\n     -0.4453659375 a       739     0    30     1    14\n      0.5968980299 a       740     0    30     1    15\n      0.0206583414 a       741     0    30     1    16\n      0.0735504595 a       742     0    30     1    17\n     -0.1767603051 a       743     0    30     1    18\n      0.0898845855 a       744     0    30     1    19\n     -0.0146136029 a       745     0    30     1    20\n     -0.8969201781 a       746     0    30     1    21\n      0.6323118608 a       747     0    30     1    22\n     -0.3424867687 a       748     0    30     1    23\n     -0.7736150480 a       749     0    30    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2    15\n      0.0818677963 a       791     1     1     2    16\n      0.3463472901 a       792     1     1     2    17\n     -0.1143486219 a       793     1     1     2    18\n      0.5608060859 a       794     1     1     2    19\n     -0.0570421536 a       795     1     1     2    20\n      0.1101573409 a       796     1     1     2    21\n     -0.0701072786 a       797     1     1     2    22\n     -0.1151364284 a       798     1     1     2    23\n     -0.2832969063 a       799     1     1     2    24\n     -0.5830216098 a       800     1     1     2    25\n     -0.6055106341 a       801     1     2     2     1\n     -0.3480469251 a       802     1     2     2     2\n     -0.8645770732 a       803     1     2     2     3\n     -0.4280622087 a       804     1     2     2     4\n     -0.2573231463 a       805     1     2     2     5\n     -0.1270521658 a       806     1     2     2     6\n      0.9192449617 a       807     1     2     2     7\n      0.0901967077 a       808     1    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  1     3     2     1\n     -0.5424094449 a       827     1     3     2     2\n      0.5550098654 a       828     1     3     2     3\n      0.4747289246 a       829     1     3     2     4\n      0.5345386810 a       830     1     3     2     5\n      0.2343293037 a       831     1     3     2     6\n      0.1484295689 a       832     1     3     2     7\n      0.3383141334 a       833     1     3     2     8\n     -0.6063074708 a       834     1     3     2     9\n     -0.0952737547 a       835     1     3     2    10\n     -0.2866843878 a       836     1     3     2    11\n      0.6361234033 a       837     1     3     2    12\n     -0.4150011094 a       838     1     3     2    13\n      0.4334272684 a       839     1     3     2    14\n      0.4746931275 a       840     1     3     2    15\n      0.2114024596 a       841     1     3     2    16\n      0.3935253378 a       842     1     3     2    17\n     -0.5023354182 a       843     1     3     2    18\n      0.2721234725 a       844     1     3     2    19\n     -0.8517225378 a       845     1     3     2    20\n      0.2963139332 a       846     1     3     2    21\n      0.5367036969 a       847     1     3     2    22\n     -0.3765919028 a       848     1     3     2    23\n      0.8513339921 a       849     1     3     2    24\n     -0.0623150367 a       850     1     3     2    25\n     -0.0116049652 a       851     1     4     2     1\n     -0.3958941814 a       852     1     4     2     2\n      0.0742089967 a       853     1     4     2     3\n      0.1437570964 a       854     1     4     2     4\n     -0.2623030486 a       855     1     4     2     5\n     -0.0629453369 a       856     1     4     2     6\n     -0.8432788718 a       857     1     4     2     7\n      0.2478908992 a       858     1     4     2     8\n      0.2380497838 a       859     1     4     2     9\n     -0.3326149583 a       860     1     4     2    10\n      0.2691157789 a       861     1     4     2    11\n     -0.8732341015 a       862     1     4     2    12\n      0.1561987845 a       863     1     4     2    13\n     -0.3753879181 a       864     1     4     2    14\n      0.0571191647 a       865     1     4     2    15\n     -0.2306561796 a       866     1     4     2    16\n      0.2725988162 a       867     1     4     2    17\n      0.0131588168 a       868     1     4     2    18\n      0.7601524464 a       869     1     4     2    19\n     -0.1359801512 a       870     1     4     2    20\n      0.0400202993 a       871     1     4     2    21\n     -0.0244063213 a       872     1     4     2    22\n     -0.0568819011 a       873     1     4     2    23\n      0.4487169103 a       874     1     4     2    24\n      0.1382261735 a       875     1     4     2    25\n      0.0948329845 a       876     1     5     2     1\n      0.3819188665 a       877     1     5     2     2\n     -0.4317862032 a       878     1     5     2     3\n      0.0755118412 a       879     1     5     2     4\n      0.3782702495 a       880     1     5     2     5\n     -0.2645732239 a       881     1     5     2     6\n      0.1649598771 a       882     1     5     2     7\n      0.6682449771 a       883     1     5     2     8\n      0.1191065058 a       884     1     5     2     9\n     -0.4552288816 a       885     1     5     2    10\n     -0.0701411455 a       886     1     5     2    11\n     -0.7559323555 a       887     1     5     2    12\n      0.4181185871 a       888     1     5     2    13\n      0.4499083913 a       889     1     5     2    14\n      0.4729532074 a       890     1     5     2    15\n     -0.2427233162 a       891     1     5     2    16\n      0.5016641720 a       892     1     5     2    17\n     -0.0335177127 a       893     1     5     2    18\n      0.4201751203 a       894     1     5     2    19\n     -0.3814306110 a       895     1     5     2    20\n      0.1449541382 a       896     1     5     2    21\n      0.6835751445 a       897     1     5     2    22\n      0.3904538714 a       898     1     5     2    23\n     -0.9227804204 a       899     1     5     2    24\n     -0.9869046908 a       900     1     5     2    25\n      0.1567152529 a       901     1     6     2     1\n      0.2150776523 a       902     1     6     2     2\n     -0.8424725533 a       903     1     6     2     3\n      0.9274198940 a       904     1     6     2     4\n     -0.5690051726 a       905     1     6     2     5\n     -0.4377792528 a       906     1     6     2     6\n     -2.0686731226 a       907     1     6     2     7\n     -0.3038058638 a       908     1     6     2     8\n     -0.7003254212 a       909     1     6     2     9\n      3.1518004986 a       910     1     6     2    10\n     -0.0108938240 a       911     1     6     2    11\n      0.8066121843 a       912     1     6     2    12\n      0.1577601200 a       913     1     6     2    13\n      1.2787533204 a       914     1     6     2    14\n      0.6315518297 a       915     1     6     2    15\n      0.0504928855 a       916     1     6     2    16\n     -0.4717855098 a       917     1     6     2    17\n      0.1698523602 a       918     1     6     2    18\n     -0.0575604095 a       919     1     6     2    19\n      0.2454046888 a       920     1     6     2    20\n      0.1336077723 a       921     1     6     2    21\n     -1.6277418023 a       922     1     6     2    22\n      0.1889171438 a       923     1     6     2    23\n     -0.1919104426 a       924     1     6     2    24\n      0.1956427067 a       925     1     6     2    25\n     -0.4066042353 a       926     1     7     2     1\n      0.4904305308 a       927     1     7     2     2\n     -1.0419607279 a       928     1     7     2     3\n      0.1654227099 a       929     1     7     2     4\n     -0.3895869516 a       930     1     7     2     5\n      0.4078517609 a       931     1     7     2     6\n      0.4905798204 a       932     1     7     2     7\n     -0.1280324003 a       933     1     7     2     8\n     -0.7358799539 a       934     1     7     2     9\n      1.2300743717 a       935     1     7     2    10\n      0.4321154680 a       936     1     7     2    11\n      0.7229744297 a       937     1     7     2    12\n     -0.0654358393 a       938     1     7     2    13\n     -0.3869277794 a       939     1     7     2    14\n      0.3342091387 a       940     1     7     2    15\n      0.0558127506 a       941     1     7     2    16\n      0.0378866552 a       942     1     7     2    17\n      0.2132571031 a       943     1     7     2    18\n      0.4587754864 a       944     1     7     2    19\n      0.3389875703 a       945     1     7     2    20\n      0.3074769055 a       946     1     7     2    21\n     -0.3295011902 a       947     1     7     2    22\n      0.2498017688 a       948     1     7     2    23\n      0.2955746811 a       949     1     7     2    24\n     -0.0255450441 a       950     1     7     2    25\n     -0.6518894057 a       951     1     8     2     1\n      0.4986985044 a       952     1     8     2     2\n      0.3284453189 a       953     1     8     2     3\n     -0.0795662024 a       954     1     8     2     4\n      0.1265126741 a       955     1     8     2     5\n     -0.5846865216 a       956     1     8     2     6\n     -0.8955943736 a       957     1     8     2     7\n      0.0633253554 a       958     1     8     2     8\n     -0.4792549946 a       959     1     8     2     9\n      0.5464099287 a       960     1     8     2    10\n     -0.5478594746 a       961     1     8     2    11\n     -0.0935759895 a       962     1     8     2    12\n     -0.3142838172 a       963     1     8     2    13\n      0.6591951288 a       964     1     8     2    14\n      0.3546627997 a       965     1     8     2    15\n     -0.2612495440 a       966     1     8     2    16\n     -0.1453285476 a       967     1     8     2    17\n     -0.3363708270 a       968     1     8     2    18\n     -0.6247359374 a       969     1     8     2    19\n      0.0841924429 a       970     1     8     2    20\n      0.0123505754 a       971     1     8     2    21\n     -0.1092431414 a       972     1     8     2    22\n     -0.4593069632 a       973     1     8     2    23\n      0.4994599558 a       974     1     8     2    24\n      0.3604137014 a       975     1     8     2    25\n     -1.0048754953 a       976     1     9     2     1\n      0.1216057484 a       977     1     9     2     2\n      0.8387739165 a       978     1     9     2     3\n     -0.0118531741 a       979     1     9     2     4\n     -0.1870581944 a       980     1     9     2     5\n     -0.4484327002 a       981     1     9     2     6\n      0.4030071582 a       982     1     9     2     7\n     -0.1538907972 a       983     1     9     2     8\n      0.2602421536 a       984     1     9     2     9\n     -0.2854946701 a       985     1     9     2    10\n      0.0443161767 a       986     1     9     2    11\n      0.3228759644 a       987     1     9     2    12\n     -0.3097281238 a       988     1     9     2    13\n      0.8894289310 a       989     1     9     2    14\n     -0.6798932862 a       990     1     9     2    15\n     -0.4085513130 a       991     1     9     2    16\n     -0.1491152436 a       992     1     9     2    17\n      0.2051522069 a       993     1     9     2    18\n      0.4743677518 a       994     1     9     2    19\n     -0.6913763647 a       995     1     9     2    20\n     -0.2381306302 a       996     1     9     2    21\n     -0.1476013731 a       997     1     9     2    22\n      0.7857587901 a       998     1     9     2    23\n      0.8049835307 a       999     1     9     2    24\n      0.2462326028 a      1000     1     9     2    25\n      0.8253545875 a      1001     1    10     2     1\n     -0.2086307080 a      1002     1    10     2     2\n     -0.6230027155 a      1003     1    10     2     3\n     -0.2565399917 a      1004     1    10     2     4\n      0.5450747484 a      1005     1    10     2     5\n      0.5632929179 a      1006     1    10     2     6\n      1.1125553431 a      1007     1    10     2     7\n     -0.2158849119 a      1008     1    10     2     8\n     -0.2791921186 a      1009     1    10     2     9\n     -0.1693316747 a      1010     1    10     2    10\n     -1.0159113920 a      1011     1    10     2    11\n     -0.2560345579 a      1012     1    10     2    12\n      0.1436833491 a      1013     1    10     2    13\n     -0.1097112294 a      1014     1    10     2    14\n     -0.3599845631 a      1015     1    10     2    15\n      0.1070535383 a      1016     1    10     2    16\n      0.4406999761 a      1017     1    10     2    17\n      0.3472842131 a      1018     1    10     2    18\n      0.3492759989 a      1019     1    10     2    19\n     -0.2124660256 a      1020     1    10     2    20\n      0.1786875024 a      1021     1    10     2    21\n      0.1578213029 a      1022     1    10     2    22\n      0.3709067718 a      1023     1    10     2    23\n     -0.8904005638 a      1024     1    10     2    24\n      0.8659766335 a      1025     1    10     2    25\n     -0.4327388700 a      1026     1    11     2     1\n      0.5197366094 a      1027     1    11     2     2\n     -0.6177011474 a      1028     1    11     2     3\n      0.3573134796 a      1029     1    11     2     4\n      0.1281530873 a      1030     1    11     2     5\n      1.1521851558 a      1031     1    11     2     6\n     -0.5681160794 a      1032     1    11     2     7\n      0.5683807357 a      1033     1    11     2     8\n      0.0569848793 a      1034     1    11     2     9\n      0.2630145730 a      1035     1    11     2    10\n      0.0095664834 a      1036     1    11     2    11\n      0.4159466278 a      1037     1    11     2    12\n     -0.4973540366 a      1038     1    11     2    13\n      0.1202631402 a      1039     1    11     2    14\n      0.6970074376 a      1040     1    11     2    15\n     -0.3111604386 a      1041     1    11     2    16\n      0.0047989685 a      1042     1    11     2    17\n     -1.0728858489 a      1043     1    11     2    18\n      0.2984821711 a      1044     1    11     2    19\n     -0.6471394643 a      1045     1    11     2    20\n      0.4600869514 a      1046     1    11     2    21\n     -0.3166444044 a      1047     1    11     2    22\n      0.6723644598 a      1048     1    11     2    23\n     -0.2853508368 a      1049     1    11     2    24\n     -0.0831987984 a      1050     1    11     2    25\n     -0.5519259551 a      1051     1    12     2     1\n      0.2036523622 a      1052     1    12     2     2\n      0.7685193985 a      1053     1    12     2     3\n     -0.0071316570 a      1054     1    12     2     4\n      0.3818327586 a      1055     1    12     2     5\n     -0.2272331510 a      1056     1    12     2     6\n      0.5560531802 a      1057     1    12     2     7\n      0.0335751891 a      1058     1    12     2     8\n      0.3610766879 a      1059     1    12     2     9\n      0.0645044592 a      1060     1    12     2    10\n     -0.6976978286 a      1061     1    12     2    11\n     -0.1237042791 a      1062     1    12     2    12\n     -0.6598766004 a      1063     1    12     2    13\n     -0.7596937065 a      1064     1    12     2    14\n     -0.7183164033 a      1065     1    12     2    15\n      0.3451415928 a      1066     1    12     2    16\n      0.3208762044 a      1067     1    12     2    17\n      0.1065806352 a      1068     1    12     2    18\n      0.8188754954 a      1069     1    12     2    19\n      0.4461747140 a      1070     1    12     2    20\n     -0.1428090118 a      1071     1    12     2    21\n      0.0783171166 a      1072     1    12     2    22\n     -0.3749129281 a      1073     1    12     2    23\n     -0.1949811868 a      1074     1    12     2    24\n     -0.4124115984 a      1075     1    12     2    25\n      0.4915911361 a      1076     1    13     2     1\n      0.5124119574 a      1077     1    13     2     2\n      0.1664274921 a      1078     1    13     2     3\n      0.3052981160 a      1079     1    13     2     4\n     -0.3236543541 a      1080     1    13     2     5\n      0.1039547847 a      1081     1    13     2     6\n     -0.1873248728 a      1082     1    13     2     7\n     -0.4199592488 a      1083     1    13     2     8\n     -0.1043316283 a      1084     1    13     2     9\n     -0.2774033849 a      1085     1    13     2    10\n      0.1558407396 a      1086     1    13     2    11\n     -0.8168807040 a      1087     1    13     2    12\n      0.5394635220 a      1088     1    13     2    13\n      0.1835581053 a      1089     1    13     2    14\n      0.0257013583 a      1090     1    13     2    15\n      0.5674313377 a      1091     1    13     2    16\n     -0.0889116651 a      1092     1    13     2    17\n     -0.0863660941 a      1093     1    13     2    18\n     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11\n     -0.1586351924 a      1112     1    14     2    12\n      0.2709459319 a      1113     1    14     2    13\n     -0.1936530770 a      1114     1    14     2    14\n     -0.8559107865 a      1115     1    14     2    15\n      0.3796776651 a      1116     1    14     2    16\n     -0.0967032987 a      1117     1    14     2    17\n     -0.2301580450 a      1118     1    14     2    18\n     -0.1080631818 a      1119     1    14     2    19\n      0.1626167612 a      1120     1    14     2    20\n      0.4562394027 a      1121     1    14     2    21\n     -0.6172136633 a      1122     1    14     2    22\n     -0.7061698916 a      1123     1    14     2    23\n      0.4782222367 a      1124     1    14     2    24\n     -0.6791540503 a      1125     1    14     2    25\n      0.1912169741 a      1126     1    15     2     1\n     -0.5651416511 a      1127     1    15     2     2\n      0.1052028126 a      1128     1    15     2     3\n      0.2993357782 a      1129     1    15     2     4\n     -0.3527546304 a      1130     1    15     2     5\n      0.0209791425 a      1131     1    15     2     6\n     -0.0927915629 a      1132     1    15     2     7\n      0.5777850320 a      1133     1    15     2     8\n      0.2492356282 a      1134     1    15     2     9\n     -0.2690263928 a      1135     1    15     2    10\n     -0.1681129944 a      1136     1    15     2    11\n      1.2249560054 a      1137     1    15     2    12\n     -0.2225554132 a      1138     1    15     2    13\n     -0.3414359163 a      1139     1    15     2    14\n      0.2956835194 a      1140     1    15     2    15\n     -0.3950006073 a      1141     1    15     2    16\n     -0.0565837995 a      1142     1    15     2    17\n      0.0496653406 a      1143     1    15     2    18\n      0.0544155173 a      1144     1    15     2    19\n      0.1472879499 a      1145     1    15     2    20\n      0.1827329427 a      1146     1    15     2    21\n      0.2300600514 a      1147     1  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    1    16     2    15\n      0.7534670130 a      1166     1    16     2    16\n     -0.3238064160 a      1167     1    16     2    17\n     -0.3601236845 a      1168     1    16     2    18\n      0.3151437122 a      1169     1    16     2    19\n     -0.0774472631 a      1170     1    16     2    20\n     -0.0735883133 a      1171     1    16     2    21\n     -0.7327417789 a      1172     1    16     2    22\n      0.2933211285 a      1173     1    16     2    23\n      0.0914558550 a      1174     1    16     2    24\n     -0.1656335267 a      1175     1    16     2    25\n     -0.8203657793 a      1176     1    17     2     1\n      0.2266896721 a      1177     1    17     2     2\n      0.4659978357 a      1178     1    17     2     3\n      0.3704152294 a      1179     1    17     2     4\n      0.4757034735 a      1180     1    17     2     5\n     -0.5066679894 a      1181     1    17     2     6\n      0.2694221564 a      1182     1    17     2     7\n      0.4578639279 a      1183     1    17     2     8\n      0.0067540494 a      1184     1    17     2     9\n     -0.3476218299 a      1185     1    17     2    10\n      0.1070395211 a      1186     1    17     2    11\n      0.2030131378 a      1187     1    17     2    12\n      0.6520560652 a      1188     1    17     2    13\n      0.1165191765 a      1189     1    17     2    14\n      0.4086082641 a      1190     1    17     2    15\n      0.2948992876 a      1191     1    17     2    16\n      0.2642198352 a      1192     1    17     2    17\n      0.4957462589 a      1193     1    17     2    18\n      0.0803337306 a      1194     1    17     2    19\n     -0.1887960839 a      1195     1    17     2    20\n     -0.1172641133 a      1196     1    17     2    21\n     -0.4243613643 a      1197     1    17     2    22\n     -0.6537059534 a      1198     1    17     2    23\n     -1.2842818114 a      1199     1    17     2    24\n     -0.0760485591 a      1200     1    17     2    25\n      0.4879320739 a      1201     1    18     2     1\n      0.4935359650 a      1202     1    18     2     2\n     -0.8202648604 a      1203     1    18     2     3\n     -0.5842327388 a      1204     1    18     2     4\n      0.2324224476 a      1205     1    18     2     5\n     -0.3342898408 a      1206     1    18     2     6\n      1.3847773826 a      1207     1    18     2     7\n      0.7200289595 a      1208     1    18     2     8\n      1.0423383297 a      1209     1    18     2     9\n     -0.7928797812 a      1210     1    18     2    10\n      0.4136427225 a      1211     1    18     2    11\n      0.0920764365 a      1212     1    18     2    12\n     -0.6981882796 a      1213     1    18     2    13\n     -0.1179783159 a      1214     1    18     2    14\n     -0.0006437393 a      1215     1    18     2    15\n     -0.5944717759 a      1216     1    18     2    16\n      0.4139379479 a      1217     1    18     2    17\n      0.1456704184 a      1218     1    18     2    18\n      0.0862537469 a      1219     1    18     2    19\n     -0.2672688246 a      1220     1    18     2    20\n     -0.2188372451 a      1221     1    18     2    21\n     -0.6312176121 a      1222     1    18     2    22\n     -0.1634984338 a      1223     1    18     2    23\n     -0.5236720704 a      1224     1    18     2    24\n     -0.5603589741 a      1225     1    18     2    25\n     -0.4814334632 a      1226     1    19     2     1\n     -0.0729144131 a      1227     1    19     2     2\n      0.7283035961 a      1228     1    19     2     3\n      0.6987892572 a      1229     1    19     2     4\n     -0.3854897686 a      1230     1    19     2     5\n      0.5203943389 a      1231     1    19     2     6\n      0.4909956861 a      1232     1    19     2     7\n      0.0976435278 a      1233     1    19     2     8\n      0.3263473112 a      1234     1    19     2     9\n     -0.7450407258 a      1235     1    19     2    10\n     -0.8229663200 a      1236     1    19     2    11\n     -0.6627172276 a      1237     1    19     2    12\n      0.7796855695 a      1238     1    19     2    13\n     -0.6231975657 a      1239     1    19     2    14\n      1.1141361959 a      1240     1    19     2    15\n     -0.3130099968 a      1241     1    19     2    16\n      0.5031213334 a      1242     1    19     2    17\n      0.2991024116 a      1243     1    19     2    18\n      0.2673772106 a      1244     1    19     2    19\n     -0.2494117076 a      1245     1    19     2    20\n     -0.5197855310 a      1246     1    19     2    21\n     -0.4797645309 a      1247     1    19     2    22\n      0.5022958375 a      1248     1    19     2    23\n     -0.0415718029 a      1249     1    19     2    24\n     -0.6883174625 a      1250     1    19     2    25\n     -0.5467977740 a      1251     1    20     2     1\n      0.3997174507 a      1252     1    20     2     2\n     -1.3478223509 a      1253     1    20     2     3\n     -0.1840651843 a      1254     1    20     2     4\n      0.3844689418 a      1255     1    20     2     5\n      0.3892947460 a      1256     1    20     2     6\n      0.5185024631 a      1257     1    20     2     7\n      0.6757740665 a      1258     1    20     2     8\n     -0.3237646202 a      1259     1    20     2     9\n     -0.1866587599 a      1260     1    20     2    10\n     -0.2285220156 a      1261     1    20     2    11\n      0.1293114102 a      1262     1    20     2    12\n     -0.4880760868 a      1263     1    20     2    13\n     -1.0072669054 a      1264     1    20     2    14\n      0.9286583633 a      1265     1    20     2    15\n     -0.2439320506 a      1266     1    20     2    16\n      0.3278167035 a      1267     1    20     2    17\n     -0.7720705458 a      1268     1    20     2    18\n      0.6680396977 a      1269     1    20     2    19\n      0.4304666100 a      1270     1    20     2    20\n      0.6694906840 a      1271     1    20     2    21\n      0.2387326095 a      1272     1    20     2    22\n      0.6261663306 a      1273     1    20     2    23\n     -0.4476644527 a      1274     1    20     2    24\n      0.0311718262 a      1275     1    20     2    25\n      0.7449554248 a      1276     1    21     2     1\n      0.5197356231 a      1277     1    21     2     2\n     -0.1559938950 a      1278     1    21     2     3\n     -0.6040448583 a      1279     1    21     2     4\n     -0.3217581587 a      1280     1    21     2     5\n      0.2703860499 a      1281     1    21     2     6\n     -0.2207025250 a      1282     1    21     2     7\n     -0.2952675348 a      1283     1    21     2     8\n     -0.4413004391 a      1284     1    21     2     9\n      0.5293946518 a      1285     1    21     2    10\n      0.7288283594 a      1286     1    21     2    11\n     -0.0138952814 a      1287     1    21     2    12\n      0.4255265968 a      1288     1    21     2    13\n      0.2137567986 a      1289     1    21     2    14\n      0.4305055748 a      1290     1    21     2    15\n     -0.0164938189 a      1291     1    21     2    16\n      0.0542231986 a      1292     1    21     2    17\n     -0.4549651237 a      1293     1    21     2    18\n     -0.9455580850 a      1294     1    21     2    19\n     -0.0825588007 a      1295     1    21     2    20\n     -0.1969562218 a      1296     1    21     2    21\n     -0.7110726076 a      1297     1    21     2    22\n      0.3306366927 a      1298     1    21     2    23\n     -1.2881833359 a      1299     1    21     2    24\n     -0.4663332524 a      1300     1    21     2    25\n      0.7205879410 a      1301     1    22     2     1\n     -0.3626082087 a      1302     1    22     2     2\n      0.1661907876 a      1303     1    22     2     3\n     -0.2395062939 a      1304     1    22     2     4\n     -0.3968335376 a      1305     1    22     2     5\n      0.0893874175 a      1306     1    22     2     6\n      0.1011569648 a      1307     1    22     2     7\n     -0.1291163654 a      1308     1    22     2     8\n     -0.4148799030 a      1309     1    22     2     9\n     -0.3969554545 a      1310     1    22     2    10\n      0.1002934132 a      1311     1    22     2    11\n     -0.5139344230 a      1312     1    22     2    12\n     -0.2427965921 a      1313     1    22     2    13\n      0.7723988146 a      1314     1    22     2    14\n     -0.9431548929 a      1315     1    22     2    15\n      0.0276233590 a      1316     1    22     2    16\n     -0.5070566190 a      1317     1    22     2    17\n     -0.7254907095 a      1318     1    22     2    18\n      0.0746703133 a      1319     1    22     2    19\n     -0.1270249948 a      1320     1    22     2    20\n     -0.3968966152 a      1321     1    22     2    21\n      0.3846697275 a      1322     1    22     2    22\n      0.4361181716 a      1323     1    22     2    23\n     -0.2851459447 a      1324     1    22     2    24\n     -0.7077908948 a      1325     1    22     2    25\n     -0.3409236443 a      1326     1    23     2     1\n     -0.1198377385 a      1327     1    23     2     2\n     -0.3598078150 a      1328     1    23     2     3\n      0.3200824247 a      1329     1    23     2     4\n      0.4829035341 a      1330     1    23     2     5\n     -0.6011363962 a      1331     1    23     2     6\n     -1.0848545894 a      1332     1    23     2     7\n     -0.3741601801 a      1333     1    23     2     8\n      0.7781267608 a      1334     1    23     2     9\n      0.0243013976 a      1335     1    23     2    10\n     -0.1210792009 a      1336     1    23     2    11\n     -0.3629840971 a      1337     1    23     2    12\n     -0.7036853247 a      1338     1    23     2    13\n      0.1490468608 a      1339     1    23     2    14\n      1.0704229680 a      1340     1    23     2    15\n     -0.5397046980 a      1341     1    23     2    16\n      0.7668251746 a      1342     1    23     2    17\n     -0.0508418490 a      1343     1    23     2    18\n      0.2758083032 a      1344     1    23     2    19\n      0.3306812174 a      1345     1    23     2    20\n      0.0071493281 a      1346     1    23     2    21\n      0.2964062551 a      1347     1    23     2    22\n     -0.6024351255 a      1348     1    23     2    23\n     -1.2517953336 a      1349     1    23     2    24\n     -0.1264785194 a      1350     1    23     2    25\n     -0.1435971932 a      1351     1    24     2     1\n      0.1092566501 a      1352     1    24     2     2\n      0.6876235645 a      1353     1    24     2     3\n     -0.6474366853 a      1354     1    24     2     4\n      0.2911945762 a      1355     1    24     2     5\n     -0.2236085897 a      1356     1    24     2     6\n      0.9660014634 a      1357     1    24     2     7\n     -0.0103120199 a      1358     1    24     2     8\n      0.6553430759 a      1359     1    24     2     9\n     -1.2057731715 a      1360     1    24     2    10\n     -0.1080931244 a      1361     1    24     2    11\n     -0.5622975704 a      1362     1    24     2    12\n      0.0120591416 a      1363     1    24     2    13\n      1.1487553111 a      1364     1    24     2    14\n     -0.5177106230 a      1365     1    24     2    15\n     -0.3899576917 a      1366     1    24     2    16\n      0.7904796538 a      1367     1    24     2    17\n     -0.2587389367 a      1368     1    24     2    18\n     -0.4151583040 a      1369     1    24     2    19\n      0.4005401371 a      1370     1    24     2    20\n     -0.5009971248 a      1371     1    24     2    21\n      1.2969824334 a      1372     1    24     2    22\n      0.2828177948 a      1373     1    24     2    23\n      0.0226170407 a      1374     1    24     2    24\n     -0.2939570886 a      1375     1    24     2    25\n     -0.0364501947 a      1376     1    25     2     1\n     -0.3124746469 a      1377     1    25     2     2\n     -0.0911001383 a      1378     1    25     2     3\n      0.6461314621 a      1379     1    25     2     4\n      0.0158891035 a      1380     1    25     2     5\n     -0.5845752231 a      1381     1    25     2     6\n     -0.1428298207 a      1382     1    25     2     7\n      0.2628229342 a      1383     1    25     2     8\n      0.3612990703 a      1384     1    25     2     9\n     -0.3340586442 a      1385     1    25     2    10\n     -0.4929352502 a      1386     1    25     2    11\n     -0.4006983336 a      1387     1    25     2    12\n      0.2213390092 a      1388     1    25     2    13\n      0.7860476727 a      1389     1    25     2    14\n     -0.0578154170 a      1390     1    25     2    15\n     -0.1019399485 a      1391     1    25     2    16\n      0.4659758451 a      1392     1    25     2    17\n     -0.8611122072 a      1393     1    25     2    18\n     -0.4946250532 a      1394     1    25     2    19\n     -0.9314498370 a      1395     1    25     2    20\n      0.3973951766 a      1396     1    25     2    21\n      0.1515791739 a      1397     1    25     2    22\n     -0.1968296890 a      1398     1    25     2    23\n     -1.0363869373 a      1399     1    25     2    24\n     -0.6468229951 a      1400     1    25     2    25\n     -0.1763092635 b      1401     2     1\n     -0.7621524272 b      1402     2     2\n      0.5675964973 b      1403     2     3\n      0.2812523188 b      1404     2     4\n     -1.2731906777 b      1405     2     5\n     -0.5120072557 b      1406     2     6\n     -0.6016927187 b      1407     2     7\n     -0.5413525588 b      1408     2     8\n     -0.4388952877 b      1409     2     9\n      0.4691197676 b      1410     2    10\n      1.4293780428 b      1411     2    11\n      0.7949634944 b      1412     2    12\n     -0.1510003557 b      1413     2    13\n     -0.5634345945 b      1414     2    14\n     -1.4000068197 b      1415     2    15\n      1.3740227580 b      1416     2    16\n      0.2090192782 b      1417     2    17\n      1.0257980357 b      1418     2    18\n      1.0321238670 b      1419     2    19\n      0.9867896198 b      1420     2    20\n     -0.4739147575 b      1421     2    21\n     -1.5305053560 b      1422     2    22\n     -1.3077137778 b      1423     2    23\n      0.7106828608 b      1424     2    24\n      0.2155175549 b      1425     2    25\n      0.0807595152 a      1426     2     1     3     1\n     -0.0159833111 a      1427     2     2     3     1\n      0.1306787658 a      1428     2     3     3     1\n      0.1374835598 a      1429     2     4     3     1\n     -0.0013415305 a      1430     2     5     3     1\n     -0.0736957587 a      1431     2     6     3     1\n      0.0681119159 a      1432     2     7     3     1\n     -0.0093324867 a      1433     2     8     3     1\n     -0.0240015765 a      1434     2     9     3     1\n     -0.0752336026 a      1435     2    10     3     1\n     -0.0692611141 a      1436     2    11     3     1\n     -0.0808010387 a      1437     2    12     3     1\n     -0.1740393457 a      1438     2    13     3     1\n      0.0639676031 a      1439     2    14     3     1\n      0.1589784658 a      1440     2    15     3     1\n      0.0432355392 a      1441     2    16     3     1\n      0.0070135735 a      1442     2    17     3     1\n      0.0131666890 a      1443     2    18     3     1\n      0.0573691989 a      1444     2    19     3     1\n      0.0451232415 a      1445     2    20     3     1\n     -0.1403703320 a      1446     2    21     3     1\n      0.1825203948 a      1447     2    22     3     1\n      0.0232415967 a      1448     2    23     3     1\n      0.1600700404 a      1449     2    24     3     1\n      0.0644496051 a      1450     2    25     3     1\n     -0.2938446474 b      1451     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_external/iceIh_128.data",
    "content": "Generated by ./convert_pgxyzinfo_lammpsdata.sh from iceIh_Cmc21.xyz, comment: \n\n384 atoms\n\n2 atom types\n\n  0.0000000000000000E+00   1.7969000000000001E+01 xlo xhi\n  0.0000000000000000E+00   1.5561600000000000E+01 ylo yhi\n  0.0000000000000000E+00   1.4671620000000001E+01 zlo zhi\n  0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 xy xz yz\n\nAtoms\n\n1 2    7.7574078122432866E-01   2.1919704683420500E+00   3.9845996089839000E+00\n2 1    0.0000000000000000E+00   1.7442755219935400E+00   3.6679050000000002E+00\n3 1    7.7574078122432866E-01   2.1919704683420500E+00   4.9345996089839002E+00\n4 2    7.7574078122432866E-01   4.7860884683420490E+00   3.1669460898389978E-01\n5 1    1.5514815624486591E+00   5.2337834146905600E+00   0.0000000000000000E+00\n6 1    0.0000000000000000E+00   5.2337834146905600E+00   0.0000000000000000E+00\n7 2    3.0218657812243297E+00   6.0823704683420496E+00   3.9845996089839000E+00\n8 1    2.2461249999999993E+00   5.6346755219935396E+00   3.6679050000000002E+00\n9 1    3.0218657812243297E+00   6.9780589366841044E+00   3.6679891737814803E+00\n10 2    3.0218657812243297E+00   8.9568846834204940E-01   3.1669460898389978E-01\n11 1    3.7976065624486592E+00   1.3433834146905594E+00   0.0000000000000000E+00\n12 1    3.0218657812243297E+00   8.9568846834204940E-01   1.2666946089839000E+00\n13 2    3.0218657812243297E+00   6.0823704683420496E+00   6.7355286089839002E+00\n14 1    2.2461249999999993E+00   5.6346755219935396E+00   7.0522232179678008E+00\n15 1    3.0218657812243297E+00   6.0823704683420496E+00   5.7855286089839000E+00\n16 2    3.0218657812243297E+00   8.9568846834204940E-01   3.0676236089839000E+00\n17 1    2.2461249999999993E+00   1.3433834146905594E+00   3.3843182179678002E+00\n18 1    3.0218657812243297E+00   0.0000000000000000E+00   3.3842340441863201E+00\n19 2    5.2679907812243290E+00   4.7860884683420490E+00   3.0676236089839000E+00\n20 1    4.4922499999999994E+00   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  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_128mol_external/md.lmp",
    "content": "###############################################################################\n# MD simulation for NN water\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"iceIh_128.data\"\n# Timesteps\nvariable numSteps        equal  5\nvariable dt              equal  0.0005\n# NN\nvariable hdnnpCutoff     equal  6.36\nvariable hdnnpDir        string \"hdnnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_O          equal  15.9994\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary p p p\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_H}\nmass 2 ${mass_O}\ntimestep ${dt}\nthermo 1\n\n###############################################################################\n# NN\n###############################################################################\npair_style hdnnp/external \"H O\" dir ${hdnnpDir} command \"./nnp-predict 0\" cflength 1.8897261328 cfenergy 0.0367493254\n#pair_style hdnnp/external \"H O\" dir ${hdnnpDir} command \"RuNNer.serial.x\" cflength 1.8897261328 cfenergy 0.0367493254\npair_coeff * * ${hdnnpCutoff}\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\ndump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_external/h2o_8640_liquid_NpT_RPBE-D3.data",
    "content": "LAMMPS data file via write_data, version 11 Aug 2017, timestep = 4000000\n\n8640 atoms\n2 atom types\n\n-3.2819324253026849e-01 4.5250693242527888e+01 xlo xhi\n-3.4106819274526146e-01 4.7025868192729938e+01 ylo yhi\n-3.2156223769001357e-01 4.4336422237685404e+01 zlo zhi\n0.0000000000000000e+00 0.0000000000000000e+00 0.0000000000000000e+00 xy xz yz\n\nMasses\n\n1 1.00794\n2 15.9994\n\nAtoms # atomic\n\n3791 1 1.6008666373327329e+00 -4.9126005439609932e-02 2.5055609599106323e+00 -2 0 2\n8571 1 1.9526752437770063e+00 8.0292814103758570e-01 2.4000828179486722e-01 0 3 0\n3790 2 1.1178391832328887e+00 1.5515453925548139e-01 3.3841161516446476e+00 -2 0 2\n8570 1 3.3204838069660298e+00 1.2797530996917250e-01 4.8199032657161134e-01 0 3 0\n3643 2 2.3226130647484529e+00 2.9114842240804601e+00 2.9779959101728890e+00 1 0 0\n8569 2 2.7196266572829577e+00 8.2992287659823982e-01 8.3148665117339071e-01 0 3 0\n3792 1 1.1279293032586206e+00 1.1286834145070108e+00 3.4879293545790904e+00 -2 0 2\n3644 1 2.5829235677481077e+00 2.6596195935451457e+00 2.0450920325305986e+00 1 0 0\n2839 2 1.1732257634842524e-01 1.8891526949140256e+00 -1.6627610215656008e-02 1 0 2\n1277 1 4.4430810556611080e+00 3.2355357958943554e+00 4.1337751747822509e+00 3 -3 1\n2841 1 -1.6216128249735967e-01 2.2070409723013085e+00 8.9311784996396582e-01 1 0 2\n3888 1 8.1972737457188072e-01 3.0840146587628579e+00 6.5837350094436413e+00 -1 0 1\n1844 1 -2.4701800857062756e-01 3.0493236212766410e+00 8.9427805291639118e+00 2 0 0\n2359 2 3.3387991665555545e+00 2.0160126155632812e+00 9.4365037141395423e+00 0 0 -2\n6535 2 9.8469083060522933e-01 -5.4845309086806460e-02 7.4918810751485179e+00 1 -1 1\n2875 2 5.1162855595342878e+00 1.1248525090341861e+00 6.8999885543230892e+00 0 2 0\n2360 1 3.4358229798221638e+00 1.5481424646636084e+00 8.5516514625290885e+00 0 0 -2\n1845 1 3.4263625931358077e-01 2.7517154882724273e+00 1.0358938962036662e+01 2 0 0\n2361 1 4.2438257264102521e+00 2.3384150687752761e+00 9.4325204152901598e+00 0 0 -2\n3887 1 1.8733756587121786e-01 1.7039526123530035e+00 6.9490012096920148e+00 -1 0 1\n3886 2 -2.2642640722228047e-02 2.6948254664417335e+00 6.7398388397755005e+00 -1 0 1\n1843 2 -2.9047839515697721e-01 3.3700749370637855e+00 9.8692555174822800e+00 2 0 0\n4389 1 4.7639686566741855e+00 -2.7906450625957407e-01 5.6006777021312395e+00 -3 1 0\n2709 1 3.1108338452562854e+00 1.8689110501446335e+00 1.4805959512348442e+01 -2 1 3\n7006 2 1.6383988883290872e+00 1.5424466467358098e+00 1.1444818116848193e+01 2 -2 0\n7007 1 1.8914485385893385e+00 1.6977448505166683e+00 1.2392447819900616e+01 2 -2 0\n3899 1 5.2639786340544725e-02 6.3430149349255127e-01 1.1719254324870558e+01 0 -2 2\n2707 2 3.0873742486936480e+00 2.3802379409893732e+00 1.3986838460750901e+01 -2 1 3\n2708 1 4.0346043834463812e+00 2.3796534944978829e+00 1.3606725156144611e+01 -2 1 3\n3808 2 5.3296333632344224e+00 2.4560808224817801e+00 1.2287336027283192e+01 2 3 0\n6451 2 4.9154845037098616e+00 1.4970470223624543e+00 1.6238289976369714e+01 1 1 0\n7008 1 2.5054048881573547e+00 1.5232177896054353e+00 1.0953460658566042e+01 2 -2 0\n3407 1 5.2137179415743207e+00 5.9038368386366336e-01 1.9538050860339649e+01 -2 1 -1\n322 2 3.9895926496811827e+00 3.1261732062082155e+00 1.8437581340760687e+01 0 -1 -1\n4537 2 2.4289327430533172e+00 1.8710574065218011e+00 2.0544201250879034e+01 2 -2 -1\n5172 1 2.2046383303072261e+00 3.9257437304131471e-01 1.7563979438759517e+01 3 1 -1\n4711 2 1.2460552496590069e+00 2.1358019733097233e+00 1.7280768673627971e+01 -2 -1 -1\n4539 1 2.9857347081934509e+00 2.2955045893908173e+00 1.9883283195177786e+01 2 -2 -1\n324 1 4.2282578573994360e+00 2.4812117569753624e+00 1.7701211381453366e+01 0 -1 -1\n4538 1 3.0319229603134783e+00 1.6562014178028117e+00 2.1330716875076678e+01 2 -2 -1\n4712 1 1.7124855911992705e+00 2.7415633786048605e+00 1.7862547963603824e+01 -2 -1 -1\n5014 2 -2.7916797577052715e-01 2.0702634957322390e+00 2.1924699322071312e+01 -1 2 0\n4713 1 9.8427145526707593e-01 2.6873358690926055e+00 1.6544803892136233e+01 -2 -1 -1\n5016 1 6.6020340586231074e-01 2.1606983187092510e+00 2.1696363616860538e+01 -1 2 0\n3406 2 4.8208239916240201e+00 -2.7964396274810310e-01 1.9567220324511261e+01 -2 1 -1\n323 1 4.7938855543796670e+00 3.4099110855474586e+00 1.8876315444667064e+01 0 -1 -1\n5171 1 3.4242879637416337e+00 -3.3502703667111128e-01 1.8187199506349575e+01 3 1 -1\n8041 2 4.3953348165969617e+00 2.6075598282097454e+00 2.7052110102272493e+01 0 1 -1\n769 2 4.2999262450635394e+00 2.2887091685681620e+00 2.2714583868049207e+01 1 1 0\n5856 1 1.1847191929965426e+00 5.3107193452776358e-01 2.4431977562515858e+01 -1 0 1\n4682 1 1.1014036126174629e+00 2.6340144445163096e+00 2.5832753471745146e+01 1 -1 1\n7432 2 5.0737537910626731e+00 6.3304750136240329e-01 2.5058709565263811e+01 3 2 0\n4681 2 1.5310002784347216e+00 3.4453791156182043e+00 2.6166283009198786e+01 1 -1 1\n8042 1 3.4226844550396009e+00 2.8444732778271269e+00 2.6987685885883383e+01 0 1 -1\n5854 2 4.5631628667812107e-01 1.1175356042994167e+00 2.4512706259402126e+01 -1 0 1\n8043 1 4.5667610216212688e+00 2.0369809666608338e+00 2.6258476702470301e+01 0 1 -1\n770 1 4.4867225229743886e+00 1.7001179180779373e+00 2.3487616837382109e+01 1 1 0\n7433 1 4.3550963204287125e+00 -4.0284105821217220e-02 2.5049858918126588e+01 3 2 0\n5855 1 2.7320563053961677e-01 1.2783757153034183e+00 2.3608761583608970e+01 -1 0 1\n771 1 5.1169641079654253e+00 2.8805163707631065e+00 2.2494465544866063e+01 1 1 0\n4258 2 2.9512144543512142e-01 2.7207784469021656e+00 3.1459993924772697e+01 -1 1 1\n4260 1 1.1443937247853619e-01 3.5038750888393193e+00 3.0846296268864727e+01 -1 1 1\n2598 1 3.2851294384109431e+00 1.7207121607714106e+00 3.1238553224172772e+01 -2 0 -2\n2596 2 3.7684486805898292e+00 2.1731835524801189e+00 3.0521075205477199e+01 -2 0 -2\n4259 1 1.2451019167501187e+00 2.6155255554574062e+00 3.1325979247351864e+01 -1 1 1\n2597 1 4.0417564658435063e+00 2.9993812437509622e+00 3.0910637266560439e+01 -2 0 -2\n2243 1 4.1002103718421443e+00 -1.8360780409336269e-01 2.8622511966180287e+01 0 4 -2\n978 1 2.9285679459181888e+00 4.6377264688469055e-01 3.3171443993181768e+01 0 -3 -1\n1833 1 4.8378738032169490e+00 1.5496875005857130e-01 3.1366490346868325e+01 -1 2 0\n471 1 7.1125277661877506e-01 -2.7004573629379797e-01 2.8048232327443554e+01 0 1 0\n5588 1 1.3181595283051406e+00 8.9324970422624705e-01 3.6900691971555361e+01 -2 0 1\n977 1 1.9865656709599468e+00 1.5506264148298978e+00 3.3770789742757856e+01 0 -3 -1\n713 1 -2.8904494494047933e-01 2.9875763409414771e+00 3.4907855472815598e+01 0 0 1\n712 2 -1.8751669511623006e-01 2.1795814814171908e+00 3.4296310864957235e+01 0 0 1\n3975 1 5.0064100801497400e+00 1.7016114424078732e+00 3.4342424421098045e+01 -3 2 2\n976 2 2.9304607653931978e+00 1.3885091099769031e+00 3.3460408921647598e+01 0 -3 -1\n6072 1 2.6343754770741112e+00 2.6694833220259033e+00 3.6470970815752139e+01 2 3 2\n6070 2 2.4527840898462605e+00 3.5292414958607452e+00 3.6836652823018298e+01 2 3 2\n714 1 -1.4823292912900454e-01 2.4341607366338600e+00 3.3364854002756744e+01 0 0 1\n6071 1 2.4017306881653711e+00 3.3124060291800705e+00 3.7766031715914039e+01 2 3 2\n6686 1 5.3634818670010551e+00 2.0508424896631468e+00 3.8356515765733093e+01 2 1 -2\n5589 1 4.6906635580204925e-01 -1.1331155234501808e-01 3.7690356589726264e+01 -2 0 1\n5587 2 1.0420553720874854e+00 -3.8134823413191243e-02 3.6872035008503815e+01 -2 0 1\n5985 1 3.3350262313680847e+00 3.2232429855423144e+00 4.1831712134148390e+01 -1 0 2\n2789 1 3.1158918349706282e+00 2.2998295542188318e-01 4.0051518236481300e+01 -1 3 -2\n5426 1 1.3063479898763004e+00 2.0364643731412584e+00 4.0069198371299137e+01 -1 -1 2\n5425 2 2.0355659439336966e+00 1.8829159800688875e+00 3.9437162833538636e+01 -1 -1 2\n5984 1 4.2746108244027301e+00 2.3096433946449304e+00 4.2472782757396132e+01 -1 0 2\n2840 1 -5.8393034094813057e-02 2.6502142659700292e+00 4.4093478253240008e+01 1 0 1\n5983 2 4.0213718828374967e+00 2.6149838878941822e+00 4.1583640560400511e+01 -1 0 2\n2790 1 4.3341008382863908e+00 2.2613312243174111e-01 4.0923651895643701e+01 -1 3 -2\n5427 1 2.7783500628023972e+00 2.2049568241697970e+00 3.9962527688957294e+01 -1 -1 2\n2788 2 3.8965985578825784e+00 -2.9149056393465628e-01 4.0219028056195896e+01 -1 3 -2\n4141 2 1.1787537732153082e+00 3.5751936062339920e+00 4.2329910033563237e+01 -2 -2 0\n7422 1 5.3123610843935465e+00 5.7359083977286307e+00 2.8203632785239729e-01 2 2 0\n7167 1 1.4481346932905341e+00 5.4790388332984383e+00 5.9184230952981420e-01 3 1 2\n7997 1 2.4281198459056528e+00 5.5780228570547754e+00 4.7309348765483215e+00 1 2 -2\n7147 2 -1.3692789843251357e-01 5.5071185305951005e+00 2.1983503246977203e+00 0 -2 1\n1278 1 4.2039224454867208e+00 4.5886617314095135e+00 3.6263325758777696e+00 3 -3 1\n1276 2 4.7011096755242168e+00 4.1601233557022743e+00 4.3477643809239126e+00 3 -3 1\n7996 2 1.8486654765938528e+00 5.9639341649265747e+00 4.0670930324576577e+00 1 2 -2\n7149 1 2.6567372813194745e-01 5.6518616514656301e+00 3.0493467237593306e+00 0 -2 1\n7420 2 4.7106018663659528e+00 4.9869145012938461e+00 -5.9247414218552563e-02 2 2 0\n6515 1 4.8567552370989882e+00 7.1751669742712147e+00 4.8805009435628905e+00 -3 1 1\n7998 1 2.0069973419605511e+00 6.8830220559169808e+00 4.2300493216608839e+00 1 2 -2\n7165 2 1.9464165341529398e+00 5.3887850454309936e+00 -3.0117106265923704e-01 3 1 2\n3645 1 1.8822471884797465e+00 3.7567515913681007e+00 2.9256697801331621e+00 1 0 0\n7421 1 3.7781535267590360e+00 5.3308042346394240e+00 -1.0291990882541688e-01 2 2 0\n2113 2 5.1690733222699237e+00 4.7150742499139104e+00 1.0176684613466115e+01 -1 0 2\n1623 1 2.0627839590875663e+00 5.5300863606380810e+00 1.0287075684645242e+01 1 -1 1\n1010 1 3.9816334724528601e-01 4.6859453178531973e+00 9.4243755684286548e+00 -1 -1 1\n6191 1 3.5658456414174480e+00 4.2049252644672883e+00 6.3244935903808592e+00 2 -1 0\n6190 2 2.7216481476357544e+00 4.5571336281716093e+00 6.5373791958150962e+00 2 -1 0\n1009 2 8.8606061509133016e-01 5.3923525516468054e+00 8.9582184301426810e+00 -1 -1 1\n1011 1 2.9025955616340371e-01 6.1549484584659515e+00 8.6955816402696477e+00 -1 -1 1\n6192 1 2.8241095964753109e+00 4.8957589683567484e+00 7.4144241150507604e+00 2 -1 0\n4036 2 5.2585779671053867e+00 6.4329320615611794e+00 6.7130986942678179e+00 -1 1 1\n2115 1 4.2278242599765896e+00 4.5678276902453394e+00 1.0471497594873162e+01 -1 0 2\n7094 1 5.8530957177006437e-01 4.4248331636285325e+00 1.3782793434903569e+01 0 0 3\n8094 1 3.1362751782501772e+00 7.3337702561614995e+00 1.1283686830358693e+01 -2 1 -1\n7093 2 1.4853532298473255e+00 4.7033029000025266e+00 1.3892210282919711e+01 0 0 3\n1985 1 2.0644116875316763e+00 6.3736097443269903e+00 1.4897908157560135e+01 0 0 -2\n1622 1 1.9175300833885034e+00 5.3496746218869662e+00 1.1870586887945061e+01 1 -1 1\n1984 2 2.1740121073406136e+00 7.2122387925503499e+00 1.5442377405819865e+01 0 0 -2\n8219 1 4.2712225918579838e+00 5.8478189823884286e+00 1.6084445563584755e+01 2 0 2\n1621 2 2.5530228860024189e+00 5.5420672156638737e+00 1.1150402849964541e+01 1 -1 1\n8218 2 5.1614440984343037e+00 5.9221491553116579e+00 1.5687143088563772e+01 2 0 2\n7095 1 2.0439992954655697e+00 3.9050420564402355e+00 1.3908318677001546e+01 0 0 3\n8220 1 4.9904650541488165e+00 6.2008006098877866e+00 1.4765426168122907e+01 2 0 2\n5697 1 5.2681049848665413e+00 7.3163074696241157e+00 1.2071635442224604e+01 0 2 -1\n2025 1 2.5219377494625612e+00 6.4522028134249938e+00 1.7121842011173346e+01 1 -1 1\n2023 2 2.5526715169916430e+00 6.0471441519466458e+00 1.8041805256173202e+01 1 -1 1\n309 1 5.2453499572306606e-01 6.0230244613992383e+00 2.0606252954271742e+01 1 -1 -3\n308 1 1.2179107361657431e+00 6.7238711891904845e+00 1.9423355482153639e+01 1 -1 -3\n2024 1 2.9599409663454015e+00 5.1266010969700275e+00 1.8062464022951918e+01 1 -1 1\n307 2 4.0248487577156566e-01 6.7668879709162333e+00 1.9916973620905893e+01 1 -1 -3\n7436 1 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-1.2911634979688955e+00 5.3139980884098712e+00\n660 1.4998889609830046e+01 2.6760371449264770e+01 -1.4789632659213684e+01\n8230 -1.5769133516474156e+00 4.0007477486976377e+00 5.2723771453642883e+00\n994 2.8549212751988956e-01 -2.3203789729971049e+00 -2.3403484847890561e+00\n8231 -2.4984008995105242e+01 2.6226172308583113e+01 1.8936050093936775e+01\n2435 5.9869851453289824e+00 6.3223575806554306e+00 -2.7291119662086981e+01\n996 1.0391501271044133e+01 3.1789802234130047e+00 -1.6301596194326418e+01\n3202 -7.4171937537142030e-01 3.7379768760696712e+00 -3.6542260727760261e+00\n3203 1.6666003039969588e+01 -4.9050932380231904e+00 -3.9490508813551446e+00\n5960 -2.1655662762986363e+01 -6.2841532556022202e+00 3.5108302167167153e+01\n2434 -9.6925242827011604e-01 -6.9344339593953865e+00 -1.0237397144271567e+00\n3204 -1.3539258732643109e+01 1.2338363138943496e+00 3.3462339202850808e+00\n3343 4.9308894972482458e+00 -2.2622827808921713e+00 -1.1912436855300712e+00\n2436 1.0165629396603288e+01 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-1.3468374082438466e+01 1.0346131812057989e+01\n2594 -2.2215150822769370e+01 1.0518792533104007e+01 5.8442877872170795e+00\n3144 -1.5386782657126608e+00 -1.7169344920249856e+01 2.1428691907132958e+01\n2460 4.4942972575817839e+00 -1.7726623411487012e+01 -6.5743237947869382e+00\n2595 8.6391889932173189e+00 4.3412474053325454e+00 2.0512456481595001e+00\n3142 -7.3701429171087895e-01 -1.7973607901749822e+00 -4.8371332839338317e+00\n1099 1.2048373112367278e+01 -2.3675588348594641e+00 -6.5220622944145867e-01\n2459 -7.1977142831786649e+00 1.9281281838095250e+01 1.1919490901361351e+01\n5471 5.8914307374317589e+00 3.1155920380752040e+01 -4.5778552875678614e+01\n2941 1.5969070404545087e+00 1.3496343091536629e+00 1.1355192591231256e-01\n1541 1.3555144213963910e+01 3.8015333300020639e+00 -6.2769522154189721e+00\n4105 2.5606459934936749e+00 -2.8496782697361717e-01 -1.6552978388968853e+00\n2458 1.0260971529328804e+01 -1.3967793756089069e+00 4.1797618444894119e-01\n2943 -2.8707615700707674e+01 -4.3180558540335428e+00 1.7869478115460879e+00\n4107 -1.8241790111449980e+01 1.7783081457866751e-01 3.6516912610007019e+01\n1540 -9.5105320070828048e-01 -4.0246028219765346e+00 -4.8159147337083814e+00\n1542 -1.5082737251076750e+01 1.1822780976631284e+01 -3.3707642782777874e+00\n8158 -1.2751510990972694e+00 -3.6093915113924226e+00 2.2157489325750159e+00\n230 7.2562875022918645e+00 -1.4003758300775143e+01 -8.8456223383618706e+00\n2326 -4.8361012774731318e+00 -5.7410731482919672e+00 5.6350446642657488e+00\n2942 -2.6506568550595990e+01 2.0940933468912210e+01 -9.4849065083639363e+00\n231 4.8241390523418798e-01 -1.6392005520588860e+01 1.1739318764082240e+01\n229 3.0383092780758583e+00 -2.1600285884611292e+00 7.3710358187464953e-01\n1906 -2.3791914635994744e+00 -1.4211140260110242e+00 1.6119991099314763e+00\n2328 8.0317021072148691e+00 1.6724430880173010e+01 6.7616965353329828e-01\n1174 -2.7417555160979852e+00 -1.5533076694719148e+00 8.0248718046867640e-01\n8418 1.2507511290887110e+00 1.2730631058857201e+01 -1.8421338850367253e+01\n42 1.2833558299765579e+01 2.8308499869102590e+00 -1.1105376010136319e+00\n1175 9.9729476654088032e+00 -1.6414974817949130e+01 1.4733063532859397e+01\n40 -3.3246589564363918e+00 4.9381906299813245e+00 -1.4344391847731515e+00\n1090 1.5549570012575129e+00 2.0030643455822821e+00 3.2828134181945630e+00\n41 -2.0001664616824705e+01 -9.6366480445892968e+00 1.1954867506525023e+01\n8416 3.4511779790378472e+00 3.4113364686793948e+00 -1.0969336380768896e+01\n6510 -1.6181620613363986e+01 -3.9065334237403615e+00 -1.7035566633664956e+01\n1176 -2.2982661884702011e+01 -4.1148773537296597e+00 -4.2904360554952659e+00\n8417 4.4361843685475195e+00 -1.9944626449585424e+01 1.4429443748666580e+01\n6336 -2.1343340696952073e+00 -1.6436604886133562e+01 -4.0538315382288816e+00\n2340 1.3349437231078479e+01 -1.1011261982736437e+01 1.1380104288476335e+01\n3814 1.7945048552674903e+00 2.6652359468567792e+00 5.6413435616775862e+00\n6508 -6.6132651117699215e-01 1.6629693349945400e+00 -9.8578517240304127e+00\n3816 1.5478476789990740e+01 9.9349241951421075e+00 6.9021168783561015e-01\n3815 -7.0666136971748394e-02 -3.3666793004227005e+00 3.2495970269962591e+01\n6509 -1.7543167463859458e+01 -2.0875781947548241e+01 -4.8788468477258267e+00\n1376 -8.7518925604285940e+00 -5.3903239317123415e+00 2.0064267857030327e+01\n3354 -1.8741875609946650e+01 8.0940968827329540e-01 1.8374867324244839e+01\n1377 1.8132517509739785e+01 -7.6642722411899857e+00 1.4097050724081306e+01\n1967 -2.7067398467756213e+01 -2.0937328596156856e+01 2.2305508156004766e-01\n8050 -3.9389956142620646e+00 -4.2334437438134600e+00 4.5373671530645368e+00\n2339 -1.0267320339677667e+01 -2.9195803039353500e+01 -1.0736714745698983e+01\n8051 -2.3292625532693840e+01 2.3134253516459818e+01 -7.4979213706770373e+00\n4994 -3.0555513720856795e+00 1.0591599740119905e+01 -2.4557378531767291e+01\n5895 -2.4734274696786905e+01 1.9452871780736164e+01 2.2757306095450733e+01\n2047 -9.7900128526341473e-02 5.4955160713166009e+00 2.8305512242278614e+00\n4995 5.1367167566142955e+00 -1.1045698272223804e+01 -1.9066014213115444e+01\n4993 -5.2928950321616020e-01 -2.0301647743036080e+00 3.8201390499855750e+00\n2048 -1.8239567115424071e+00 9.3413208951515703e+00 1.6661016163917179e+01\n5893 4.0950289937103834e-01 4.9985273975607702e+00 -1.1272392419690933e+00\n5894 1.3945583302387059e+01 1.5343435001253338e+01 3.6400034285235141e+00\n3352 1.8436557062773280e+00 9.8100220259307003e-01 6.8687483212176836e+00\n281 -3.4422791243100384e+00 9.6216308639370194e+00 4.1226930665091919e+00\n8385 6.5501879633626832e+00 -2.8815895204292752e+00 -3.8112147213496691e+01\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_external/hdnnp-data/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   4              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 2\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               25             # Write energy comparison.\nwrite_trainforces               25             # Write force comparison.\nwrite_weights_epoch                            # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_external/hdnnp-data/nnp-train.log.0000",
    "content": "\n*** SETUP: MPI ****************************************************************\n\nNumber of processors: 16\nProcess 1 of 16 (rank 0): n18-040\nProcess 2 of 16 (rank 1): n18-040\nProcess 3 of 16 (rank 2): n18-040\nProcess 4 of 16 (rank 3): n18-040\nProcess 5 of 16 (rank 4): n18-040\nProcess 6 of 16 (rank 5): n18-040\nProcess 7 of 16 (rank 6): n18-040\nProcess 8 of 16 (rank 7): n18-040\nProcess 9 of 16 (rank 8): n18-040\nProcess 10 of 16 (rank 9): n18-040\nProcess 11 of 16 (rank 10): n18-040\nProcess 12 of 16 (rank 11): n18-040\nProcess 13 of 16 (rank 12): n18-040\nProcess 14 of 16 (rank 13): n18-040\nProcess 15 of 16 (rank 14): n18-040\nProcess 16 of 16 (rank 15): n18-040\n*******************************************************************************\n\n*******************************************************************************\n\n   NNP LIBRARY v0.1.0\n   ------------------\n\nGit branch  : master\nGit revision: d2f83cd (d2f83cde386d59595aea395bfe3755dccebc195a)\n\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 167 lines.\nFound 102 lines with keywords.\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is used.\nMean energy per atom     :  -2.5521343547039809E+01\nConversion factor energy :   2.4265748255366972E+02\nConversion factor length :   5.8038448995319847E+00\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  H (  1)\nElement  1:  O (  8)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:   0.00000000E+00\nElement  1:   0.00000000E+00\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_TANHU (2)\nf(r) = tanh^3(1 - r/rc)\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  H  2  H    2.969E-05 0.000E+00         6.965E+01  2 0.00    98\n   2  H  2  O    2.969E-05 0.000E+00         6.965E+01  2 0.00   108\n   3  H  2  H    2.969E-04 0.000E+00         6.965E+01  2 0.00    99\n   4  H  2  O    2.969E-04 0.000E+00         6.965E+01  2 0.00   109\n   5  H  2  H    8.906E-04 0.000E+00         6.965E+01  2 0.00   100\n   6  H  2  O    8.906E-04 0.000E+00         6.965E+01  2 0.00   110\n   7  H  2  H    1.781E-03 0.000E+00         6.965E+01  2 0.00   101\n   8  H  2  O    1.781E-03 0.000E+00         6.965E+01  2 0.00   111\n   9  H  2  O    4.453E-03 5.223E+00         6.965E+01  2 0.00   112\n  10  H  2  H    4.453E-03 1.103E+01         6.965E+01  2 0.00   102\n  11  H  2  O    8.906E-03 5.223E+00         6.965E+01  2 0.00   113\n  12  H  2  H    8.906E-03 1.103E+01         6.965E+01  2 0.00   103\n  13  H  2  O    1.781E-02 5.223E+00         6.965E+01  2 0.00   114\n  14  H  2  H    1.781E-02 1.103E+01         6.965E+01  2 0.00   104\n  15  H  2  O    4.453E-02 5.223E+00         6.965E+01  2 0.00   115\n  16  H  2  H    4.453E-02 1.103E+01         6.965E+01  2 0.00   105\n  17  H  3  O  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   162\n  18  H  3  O  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   161\n  19  H  3  H  O 2.969E-04 0.000E+00 -1  4.0 6.965E+01  2 0.00   152\n  20  H  3  H  O 2.969E-04 0.000E+00  1  4.0 6.965E+01  2 0.00   150\n  21  H  3  H  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   147\n  22  H  3  O  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   160\n  23  H  3  H  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   145\n  24  H  3  O  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   159\n  25  H  3  H  O 2.078E-03 0.000E+00 -1  1.0 6.965E+01  2 0.00   142\n  26  H  3  H  O 2.078E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   140\n  27  H  3  H  O 5.937E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   137\n-------------------------------------------------------------------------------\nShort range atomic symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  O  2  H    2.969E-05 0.000E+00         6.965E+01  2 0.00   117\n   2  O  2  O    2.969E-05 0.000E+00         6.965E+01  2 0.00   127\n   3  O  2  H    2.969E-04 0.000E+00         6.965E+01  2 0.00   118\n   4  O  2  O    2.969E-04 0.000E+00         6.965E+01  2 0.00   128\n   5  O  2  H    8.906E-04 0.000E+00         6.965E+01  2 0.00   119\n   6  O  2  O    8.906E-04 0.000E+00         6.965E+01  2 0.00   129\n   7  O  2  H    1.781E-03 0.000E+00         6.965E+01  2 0.00   120\n   8  O  2  O    1.781E-03 0.000E+00         6.965E+01  2 0.00   130\n   9  O  2  H    4.453E-03 5.223E+00         6.965E+01  2 0.00   121\n  10  O  2  O    4.453E-03 2.322E+01         6.965E+01  2 0.00   131\n  11  O  2  H    8.906E-03 5.223E+00         6.965E+01  2 0.00   122\n  12  O  2  O    8.906E-03 2.322E+01         6.965E+01  2 0.00   132\n  13  O  2  H    1.781E-02 5.223E+00         6.965E+01  2 0.00   123\n  14  O  2  O    1.781E-02 2.322E+01         6.965E+01  2 0.00   133\n  15  O  2  H    4.453E-02 5.223E+00         6.965E+01  2 0.00   124\n  16  O  2  O    4.453E-02 2.322E+01         6.965E+01  2 0.00   134\n  17  O  3  H  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   157\n  18  O  3  O  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   167\n  19  O  3  H  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   156\n  20  O  3  O  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   166\n  21  O  3  H  H 2.969E-04 0.000E+00 -1  4.0 6.965E+01  2 0.00   151\n  22  O  3  H  H 2.969E-04 0.000E+00  1  4.0 6.965E+01  2 0.00   149\n  23  O  3  H  H 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   146\n  24  O  3  H  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   155\n  25  O  3  O  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   165\n  26  O  3  H  H 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   144\n  27  O  3  H  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   154\n  28  O  3  O  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   164\n  29  O  3  H  H 2.078E-03 0.000E+00 -1  1.0 6.965E+01  2 0.00   141\n  30  O  3  H  H 2.078E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   139\n-------------------------------------------------------------------------------\nMinimum cutoff radius for element  H: 69.646139\nMinimum cutoff radius for element  O: 69.646139\nMaximum cutoff radius (global)      : 69.646139\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function group index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  H  2  H            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -    97    1    1  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -    98    2    3  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -    99    3    5  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   100    4    7  \n   -  -  -  -    4.453E-03 1.103E+01                 -  -    -   101    5   10  \n   -  -  -  -    8.906E-03 1.103E+01                 -  -    -   102    6   12  \n   -  -  -  -    1.781E-02 1.103E+01                 -  -    -   103    7   14  \n   -  -  -  -    4.453E-02 1.103E+01                 -  -    -   104    8   16  \n   2  H  2  O            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   107    1    2  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   108    2    4  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   109    3    6  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   110    4    8  \n   -  -  -  -    4.453E-03 5.223E+00                 -  -    -   111    5    9  \n   -  -  -  -    8.906E-03 5.223E+00                 -  -    -   112    6   11  \n   -  -  -  -    1.781E-02 5.223E+00                 -  -    -   113    7   13  \n   -  -  -  -    4.453E-02 5.223E+00                 -  -    -   114    8   15  \n   3  H  3  H  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-04 0.000E+00 -1  4.0         -  -    -   151    1   19 1\n   -  -  -  -  - 2.969E-04 0.000E+00  1  4.0         -  -    -   149    2   20 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   146    3   21 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   144    4   23 0\n   -  -  -  -  - 2.078E-03 0.000E+00 -1  1.0         -  -    -   141    5   25 1\n   -  -  -  -  - 2.078E-03 0.000E+00  1  1.0         -  -    -   139    6   26 0\n   -  -  -  -  - 5.937E-03 0.000E+00  1  1.0         -  -    -   136    7   27 1\n   4  H  3  O  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   161    1   17 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   160    2   18 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   159    3   22 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   158    4   24 0\n-------------------------------------------------------------------------------\nShort range atomic symmetry function groups element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  O  2  H            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   116    1    1  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   117    2    3  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   118    3    5  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   119    4    7  \n   -  -  -  -    4.453E-03 5.223E+00                 -  -    -   120    5    9  \n   -  -  -  -    8.906E-03 5.223E+00                 -  -    -   121    6   11  \n   -  -  -  -    1.781E-02 5.223E+00                 -  -    -   122    7   13  \n   -  -  -  -    4.453E-02 5.223E+00                 -  -    -   123    8   15  \n   2  O  2  O            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   126    1    2  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   127    2    4  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   128    3    6  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   129    4    8  \n   -  -  -  -    4.453E-03 2.322E+01                 -  -    -   130    5   10  \n   -  -  -  -    8.906E-03 2.322E+01                 -  -    -   131    6   12  \n   -  -  -  -    1.781E-02 2.322E+01                 -  -    -   132    7   14  \n   -  -  -  -    4.453E-02 2.322E+01                 -  -    -   133    8   16  \n   3  O  3  H  H         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-04 0.000E+00 -1  4.0         -  -    -   150    1   21 1\n   -  -  -  -  - 2.969E-04 0.000E+00  1  4.0         -  -    -   148    2   22 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   145    3   23 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   143    4   26 0\n   -  -  -  -  - 2.078E-03 0.000E+00 -1  1.0         -  -    -   140    5   29 1\n   -  -  -  -  - 2.078E-03 0.000E+00  1  1.0         -  -    -   138    6   30 0\n   4  O  3  H  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   156    1   17 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   155    2   19 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   154    3   24 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   153    4   27 0\n   5  O  3  O  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   166    1   18 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   165    2   20 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   164    3   25 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   163    4   28 0\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic short range NN for element  H :\nNumber of weights    :   1325\nNumber of biases     :     51\nNumber of connections:   1376\nArchitecture       27   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  O :\nNumber of weights    :   1400\nNumber of biases     :     51\nNumber of connections:   1451\nArchitecture       30   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALECENTER (3)\nGs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  1.09E+00  9.62E+00  2.27E+00  6.79E-01  1.17E-01  0.00  1.00 3\n   2  7.33E-01  5.00E+00  1.33E+00  3.39E-01  2.34E-01  0.00  1.00 3\n   3  7.60E-01  7.14E+00  1.65E+00  5.08E-01  1.57E-01  0.00  1.00 3\n   4  5.48E-01  3.77E+00  1.02E+00  2.54E-01  3.11E-01  0.00  1.00 3\n   5  4.01E-01  4.15E+00  9.09E-01  2.98E-01  2.67E-01  0.00  1.00 3\n   6  3.62E-01  2.27E+00  6.49E-01  1.48E-01  5.25E-01  0.00  1.00 3\n   7  1.89E-01  2.23E+00  4.57E-01  1.60E-01  4.90E-01  0.00  1.00 3\n   8  2.67E-01  1.32E+00  4.24E-01  8.05E-02  9.49E-01  0.00  1.00 3\n   9  2.45E-01  9.48E-01  3.62E-01  5.30E-02  1.42E+00  0.00  1.00 3\n  10  2.22E-01  2.76E+00  5.39E-01  2.01E-01  3.94E-01  0.00  1.00 3\n  11  1.47E-01  5.56E-01  2.68E-01  2.62E-02  2.45E+00  0.00  1.00 3\n  12  9.91E-02  1.73E+00  2.96E-01  1.16E-01  6.14E-01  0.00  1.00 3\n  13  6.51E-02  3.45E-01  1.85E-01  1.97E-02  3.57E+00  0.00  1.00 3\n  14  3.17E-02  9.13E-01  1.50E-01  5.35E-02  1.13E+00  0.00  1.00 3\n  15  2.92E-03  2.65E-01  7.65E-02  1.88E-02  3.82E+00  0.00  1.00 3\n  16  3.21E-04  2.87E-01  4.58E-02  2.33E-02  3.49E+00  0.00  1.00 3\n  17  2.47E-04  1.38E-01  1.77E-02  9.75E-03  7.23E+00  0.00  1.00 3\n  18  5.10E-03  5.83E-01  2.39E-02  3.78E-02  1.73E+00  0.00  1.00 3\n  19  3.23E-04  2.16E-01  1.71E-02  1.40E-02  4.63E+00  0.00  1.00 3\n  20  4.96E-02  1.69E+00  1.45E-01  1.10E-01  6.11E-01  0.00  1.00 3\n  21  3.41E-03  3.16E-01  1.84E-02  2.01E-02  3.20E+00  0.00  1.00 3\n  22  1.31E-04  1.03E-01  6.37E-03  6.61E-03  9.76E+00  0.00  1.00 3\n  23  3.38E-02  9.16E-01  8.13E-02  5.79E-02  1.13E+00  0.00  1.00 3\n  24  4.17E-04  1.58E-01  4.66E-03  9.86E-03  6.35E+00  0.00  1.00 3\n  25  7.35E-04  5.92E-02  3.70E-03  3.31E-03  1.71E+01  0.00  1.00 3\n  26  8.98E-03  1.94E-01  2.41E-02  1.10E-02  5.40E+00  0.00  1.00 3\n  27  2.12E-04  8.78E-03  2.06E-03  5.88E-04  1.17E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  1.51E+00  1.00E+01  2.65E+00  6.78E-01  1.18E-01  0.00  1.00 3\n   2  4.44E-01  4.62E+00  9.66E-01  3.37E-01  2.39E-01  0.00  1.00 3\n   3  1.19E+00  7.53E+00  2.03E+00  5.06E-01  1.58E-01  0.00  1.00 3\n   4  2.76E-01  3.39E+00  6.59E-01  2.50E-01  3.21E-01  0.00  1.00 3\n   5  8.06E-01  4.54E+00  1.30E+00  2.94E-01  2.68E-01  0.00  1.00 3\n   6  1.05E-01  1.89E+00  3.07E-01  1.42E-01  5.60E-01  0.00  1.00 3\n   7  5.69E-01  2.62E+00  8.48E-01  1.57E-01  4.89E-01  0.00  1.00 3\n   8  2.33E-02  9.36E-01  1.11E-01  6.98E-02  1.10E+00  0.00  1.00 3\n   9  5.14E-01  1.85E+00  7.25E-01  9.80E-02  7.46E-01  0.00  1.00 3\n  10  1.11E-01  2.91E+00  4.75E-01  2.34E-01  3.57E-01  0.00  1.00 3\n  11  3.53E-01  1.07E+00  5.35E-01  4.52E-02  1.39E+00  0.00  1.00 3\n  12  3.04E-02  2.53E+00  3.17E-01  2.10E-01  4.00E-01  0.00  1.00 3\n  13  1.60E-01  6.63E-01  3.70E-01  3.08E-02  1.99E+00  0.00  1.00 3\n  14  2.78E-03  2.30E+00  1.77E-01  1.86E-01  4.35E-01  0.00  1.00 3\n  15  9.56E-03  3.91E-01  1.53E-01  2.79E-02  2.62E+00  0.00  1.00 3\n  16  3.75E-06  2.04E+00  5.41E-02  1.43E-01  4.91E-01  0.00  1.00 3\n  17  2.47E-03  3.43E-01  1.67E-02  2.19E-02  2.93E+00  0.00  1.00 3\n  18  1.74E-05  5.63E-02  9.55E-04  3.36E-03  1.78E+01  0.00  1.00 3\n  19  5.48E-02  3.02E+00  2.04E-01  2.01E-01  3.37E-01  0.00  1.00 3\n  20  1.38E-03  4.99E-01  1.28E-02  3.18E-02  2.01E+00  0.00  1.00 3\n  21  6.69E-03  2.67E-01  3.09E-02  1.71E-02  3.84E+00  0.00  1.00 3\n  22  1.70E-02  1.42E+00  7.63E-02  9.29E-02  7.14E-01  0.00  1.00 3\n  23  1.98E-02  4.08E-01  4.88E-02  2.55E-02  2.58E+00  0.00  1.00 3\n  24  5.28E-04  2.33E-01  7.21E-03  1.45E-02  4.30E+00  0.00  1.00 3\n  25  1.11E-05  3.53E-02  4.25E-04  2.05E-03  2.83E+01  0.00  1.00 3\n  26  1.60E-02  8.22E-01  5.08E-02  5.28E-02  1.24E+00  0.00  1.00 3\n  27  3.99E-03  7.86E-01  3.69E-02  5.05E-02  1.28E+00  0.00  1.00 3\n  28  4.05E-05  9.84E-02  1.21E-03  5.79E-03  1.02E+01  0.00  1.00 3\n  29  6.04E-03  9.93E-02  1.62E-02  5.52E-03  1.07E+01  0.00  1.00 3\n  30  2.96E-03  1.55E-01  1.16E-02  8.94E-03  6.59E+00  0.00  1.00 3\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 0\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** SETUP: RANDOM NUMBER GENERATOR ********************************************\n\nRandom number generator seed: 2\nSeed for rank 0: 2\nSeed for rank 1: 1872583848\nSeed for rank 2: 794921487\nSeed for rank 3: 111352301\nSeed for rank 4: 4000937544\nSeed for rank 5: 2360782358\nSeed for rank 6: 4070471979\nSeed for rank 7: 1869695442\nSeed for rank 8: 2081981515\nSeed for rank 9: 1805465960\nSeed for rank 10: 1376693511\nSeed for rank 11: 1418777250\nSeed for rank 12: 663257521\nSeed for rank 13: 878959199\nSeed for rank 14: 3001592395\nSeed for rank 15: 2659748565\nSeed for global RNG: 515183663\n*******************************************************************************\n\n*** STRUCTURE DISTRIBUTION ****************************************************\n\nReading configurations from data file: input.data.\nTotal number of structures: 7241\nNumber of structures per processor: 452 (7) or 453 (9)\nDistributed 7241 structures, 123519504 bytes (117.80 MiB) transferred.\nNumber of local structures: 452\n*******************************************************************************\n\n*** DEFINE TRAINING/TEST SETS *************************************************\n\nDesired test set ratio      : 0.100000\nTotal number of energies    : 7241\nNumber of training energies : 6533\nNumber of test     energies : 708\nNumber of training forces   : 1596654\nNumber of test     forces   : 169290\nActual test set fraction    : 0.097777\n*******************************************************************************\n\n*** WRITE TRAINING/TEST SETS **************************************************\n\nWriting training/test set to files:\n - train.data\n - test.data\n*******************************************************************************\n\n*** WEIGHT INITIALIZATION *****************************************************\n\nInitial weights selected randomly in interval [-1.000000, 1.000000).\nWeights modified accoring to Glorot Bengio scheme.\nBiases set to zero.\n*******************************************************************************\n\n*** SETUP: TRAINING ***********************************************************\n\nForces will be used for training.\nForce update weight:   1.00E+01\nWeight update via Kalman filter selected: updaterType::UT_KALMANFILTER (1)\nMulti-stream Kalman filter training, update on rank 0, partial X calculation selected: ParallelMode::PM_MSEKFR0PX (4)\nNumber of streams       : 16\nStream of this processor: 0\nCombined updater for all elements selected: UpdateStrategy::US_COMBINED (0)\nNumber of weight updaters    : 1\nTotal fit parameters         : 2827\nSelection mode starting with epoch 0:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 1.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\n-------------------------------------------------------------------------------\nSymmetry function memory is reused (HIGH MEMORY USAGE!).\nTraining will be stopped after 25 epochs.\nEnergy comparison will be written every 25 epochs.\nForce comparison will be written every 25 epochs.\nWeights will be written every 1 epochs.\nNeuron statistics will be written every 5 epochs.\nUp to epoch 10 neuron statistics will be written every epoch.\nTraining log with update information will be written to: train-log.out.\n-------------------------------------------------------------------------------\nFraction of energies used per epoch:    1.0000\nFraction of forces used per epoch  :    0.0410\nProjected energy updates per epoch :     408 (  9.1%)\nProjected forces updates per epoch :    4091 ( 90.9%)\nTotal projected updates per epoch  :    4500\nMulti-stream training uses 16 energies/forces per weight update.\nqtau is divided by number of projected updates per epoch.\netatau is divided by number of projected updates per epoch.\n-------------------------------------------------------------------------------\nCombined weight updater:\n-------------------------------------------------------------------------------\nKalmanType::KT_STANDARD (0)\nsizeState       = 2827\nsizeObservation = 16\nepsilon         =   1.0000E-02\nq0              =   1.0000E-02\nqtau            =   5.1159E-04\nqmin            =   1.0000E-06\neta0            =   1.0000E-02\netatau          =   5.1159E-04\netamax          =   1.0000E+00\nKalmanParallel::KP_PRECALCX (2)\nOpenMP threads used: 1\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** CALCULATE NEIGHBOR LISTS **************************************************\n\nCalculating neighbor lists for all structures.\nCutoff radius for neighbor lists: 69.646139\n*******************************************************************************\n\n*** TRAINING LOOP *************************************************************\n\nThe training loop output covers different RMSEs, update and\ntiming information. The following quantities are organized\naccording to the matrix scheme below:\n-------------------------------------------------------------------\nep ............ Epoch.\nEtrain_phys ... RMSE of training energies per atom (p. u.).\nEtest_phys .... RMSE of test     energies per atom (p. u.).\nEtrain_int .... RMSE of training energies per atom (i. u.).\nEtest_int ..... RMSE of test     energies per atom (i. u.).\nFtrain_phys ... RMSE of training forces (p. u.).\nFtest_phys .... RMSE of test     forces (p. u.).\nFtrain_int .... RMSE of training forces (i. u.).\nFtest_int ..... RMSE of test     forces (i. u.).\nE_count ....... Number of energy updates.\nF_count ....... Number of force  updates.\ncount ......... Total number of updates.\nt_train ....... Time for training (seconds).\nt_rmse ........ Time for RMSE calculation (seconds).\nt_epoch ....... Total time for this epoch (seconds).\nt_tot ......... Total time for all epochs (seconds).\nAbbreviations:\n  p. u. = physical units.\n  i. u. = internal units.\nNote: RMSEs in internal units (columns 5 + 6) are only present \n      if data set normalization is used.\n-------------------------------------------------------------------\n     1    2             3             4             5             6\nenergy   ep   Etrain_phys    Etest_phys    Etrain_int     Etest_int\nforces   ep   Ftrain_phys    Ftest_phys    Ftrain_int     Ftest_int\nupdate   ep       E_count       F_count         count\ntiming   ep       t_train        t_rmse       t_epoch         t_tot\n-------------------------------------------------------------------\nENERGY    0   3.72115E-03   3.81895E-03   9.02965E-01   9.26696E-01\nFORCES    0   2.34072E-02   2.29953E-02   9.78649E-01   9.61428E-01\nTIMING    0          0.00         30.72         30.75         30.75\n------\nENERGY    1   5.27269E-05   5.44783E-05   1.27946E-02   1.32196E-02\nFORCES    1   9.78255E-04   9.47430E-04   4.09006E-02   3.96118E-02\nUPDATE    1           408          4076          4484\nTIMING    1        547.67          2.61        550.32        581.07\n------\nENERGY    2   9.56678E-05   8.86669E-05   2.32145E-02   2.15157E-02\nFORCES    2   8.94076E-04   8.74898E-04   3.73811E-02   3.65793E-02\nUPDATE    2           408          4082          4490\nTIMING    2        525.97          2.71        528.71       1109.78\n------\nENERGY    3   3.38638E-05   3.30619E-05   8.21730E-03   8.02272E-03\nFORCES    3   7.89628E-04   7.69554E-04   3.30142E-02   3.21749E-02\nUPDATE    3           408          3997          4405\nTIMING    3        517.62          2.69        520.35       1630.13\n------\nENERGY    4   2.69193E-05   2.55573E-05   6.53218E-03   6.20168E-03\nFORCES    4   7.54758E-04   7.38703E-04   3.15563E-02   3.08850E-02\nUPDATE    4           408          4143          4551\nTIMING    4        530.61          2.66        533.30       2163.43\n------\nENERGY    5   3.67487E-05   3.57290E-05   8.91736E-03   8.66991E-03\nFORCES    5   7.34764E-04   7.34122E-04   3.07203E-02   3.06935E-02\nUPDATE    5           408          3987          4395\nTIMING    5        508.88          2.63        511.54       2674.97\n------\nENERGY    6   3.05092E-05   3.02791E-05   7.40328E-03   7.34745E-03\nFORCES    6   7.24954E-04   7.21860E-04   3.03102E-02   3.01808E-02\nUPDATE    6           408          4077          4485\nTIMING    6        520.66          2.68        523.37       3198.34\n------\nENERGY    7   4.44131E-05   4.29940E-05   1.07772E-02   1.04328E-02\nFORCES    7   7.19542E-04   7.18822E-04   3.00839E-02   3.00538E-02\nUPDATE    7           408          4151          4559\nTIMING    7        529.47          2.71        532.21       3730.55\n------\nENERGY    8   3.55360E-05   3.40692E-05   8.62307E-03   8.26716E-03\nFORCES    8   7.22773E-04   7.20229E-04   3.02190E-02   3.01126E-02\nUPDATE    8           408          4151          4559\nTIMING    8        527.71          2.63        530.38       4260.93\n------\nENERGY    9   2.65646E-05   2.57801E-05   6.44610E-03   6.25574E-03\nFORCES    9   7.14881E-04   7.12744E-04   2.98890E-02   2.97997E-02\nUPDATE    9           408          4051          4459\nTIMING    9        515.96          2.67        518.66       4779.59\n------\nENERGY   10   2.74199E-05   2.62896E-05   6.65364E-03   6.37936E-03\nFORCES   10   7.14391E-04   7.12126E-04   2.98685E-02   2.97738E-02\nUPDATE   10           408          4054          4462\nTIMING   10        519.13          2.76        521.92       5301.51\n------\nENERGY   11   2.74124E-05   2.69574E-05   6.65184E-03   6.54141E-03\nFORCES   11   7.15474E-04   7.13003E-04   2.99138E-02   2.98105E-02\nUPDATE   11           408          3931          4339\nTIMING   11        501.49          2.65        504.17       5805.68\n------\nENERGY   12   2.87293E-05   2.82820E-05   6.97137E-03   6.86285E-03\nFORCES   12   7.14605E-04   7.12197E-04   2.98775E-02   2.97768E-02\nUPDATE   12           408          4122          4530\nTIMING   12        526.86          2.66        529.54       6335.22\n------\nENERGY   13   2.50400E-05   2.41467E-05   6.07614E-03   5.85937E-03\nFORCES   13   7.12309E-04   7.11631E-04   2.97815E-02   2.97531E-02\nUPDATE   13           408          4009          4417\nTIMING   13        511.79          2.72        514.54       6849.76\n------\nENERGY   14   3.27553E-05   3.21490E-05   7.94833E-03   7.80119E-03\nFORCES   14   7.11961E-04   7.10919E-04   2.97669E-02   2.97234E-02\nUPDATE   14           408          4132          4540\nTIMING   14        526.43          2.68        529.14       7378.90\n------\nENERGY   15   3.24771E-05   3.11575E-05   7.88081E-03   7.56061E-03\nFORCES   15   7.07100E-04   7.05472E-04   2.95637E-02   2.94956E-02\nUPDATE   15           408          4053          4461\nTIMING   15        515.38          2.65        518.06       7896.96\n------\nENERGY   16   3.12976E-05   3.18343E-05   7.59461E-03   7.72483E-03\nFORCES   16   7.10094E-04   7.07533E-04   2.96889E-02   2.95818E-02\nUPDATE   16           408          4104          4512\nTIMING   16        523.43          2.71        526.17       8423.13\n------\nENERGY   17   2.70985E-05   2.73839E-05   6.57565E-03   6.64491E-03\nFORCES   17   7.07123E-04   7.06332E-04   2.95647E-02   2.95316E-02\nUPDATE   17           408          4021          4429\nTIMING   17        513.31          2.67        516.01       8939.14\n------\nENERGY   18   3.09332E-05   2.91548E-05   7.50617E-03   7.07463E-03\nFORCES   18   7.05834E-04   7.04317E-04   2.95108E-02   2.94473E-02\nUPDATE   18           408          4079          4487\nTIMING   18        521.91          2.66        524.60       9463.74\n------\nENERGY   19   3.26598E-05   3.28139E-05   7.92515E-03   7.96254E-03\nFORCES   19   7.05070E-04   7.01846E-04   2.94788E-02   2.93440E-02\nUPDATE   19           408          4033          4441\nTIMING   19        514.32          2.69        517.05       9980.78\n------\nENERGY   20   2.60466E-05   2.47333E-05   6.32039E-03   6.00173E-03\nFORCES   20   7.06028E-04   7.04603E-04   2.95189E-02   2.94593E-02\nUPDATE   20           408          4026          4434\nTIMING   20        568.05          2.67        570.75      10551.53\n------\nENERGY   21   2.80412E-05   2.81732E-05   6.80440E-03   6.83644E-03\nFORCES   21   7.11965E-04   7.11953E-04   2.97671E-02   2.97666E-02\nUPDATE   21           408          4012          4420\nTIMING   21        518.97          2.80        521.80      11073.33\n------\nENERGY   22   2.64661E-05   2.60412E-05   6.42221E-03   6.31908E-03\nFORCES   22   7.14539E-04   7.13341E-04   2.98747E-02   2.98246E-02\nUPDATE   22           408          4038          4446\nTIMING   22        520.31          2.72        523.07      11596.40\n------\nENERGY   23   3.66545E-05   3.65880E-05   8.89450E-03   8.87835E-03\nFORCES   23   7.05732E-04   7.05303E-04   2.95065E-02   2.94886E-02\nUPDATE   23           408          4078          4486\nTIMING   23        526.46          3.31        529.80      12126.21\n------\nENERGY   24   3.00251E-05   2.86382E-05   7.28581E-03   6.94926E-03\nFORCES   24   7.05073E-04   7.02898E-04   2.94790E-02   2.93880E-02\nUPDATE   24           408          3989          4397\nTIMING   24        515.17          2.68        517.87      12644.08\n------\nENERGY   25   3.24461E-05   3.15622E-05   7.87329E-03   7.65879E-03\nFORCES   25   7.06710E-04   7.05342E-04   2.95474E-02   2.94902E-02\nUPDATE   25           408          4053          4461\nTIMING   25        523.39          3.60        527.02      13171.10\n*******************************************************************************\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_external/hdnnp-data/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_external/hdnnp-data/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.2539155865352127E+00 a         1     0     1     1     1\n  2.2490365890661286E+00 a         2     0     1     1     2\n  4.9361851928374572E+00 a         3     0     1     1     3\n -2.3971991574908125E+00 a         4     0     1     1     4\n -1.8596992303156465E+00 a         5     0     1     1     5\n  3.8287764168815897E+00 a         6     0     1     1     6\n  7.4523181738636106E+00 a         7     0     1     1     7\n  6.0971861116881998E+00 a         8     0     1     1     8\n -8.7239359226117639E+00 a         9     0     1     1     9\n -1.8255232070184267E+01 a        10     0     1     1    10\n -7.8065643887610179E+00 a        11     0     1     1    11\n  1.4247237398130265E+01 a        12     0     1     1    12\n -3.2217879518334338E+00 a        13     0     1     1    13\n -5.7395252086520712E+00 a        14     0     1     1    14\n  2.0353040522911576E+00 a        15     0     1     1    15\n  7.7520578160630560E+00 a        16     0     1     1    16\n  2.9357257867412252E+00 a        17     0     1     1    17\n -2.9719860930100790E+00 a        18     0     1     1    18\n  8.9245382590288980E+00 a        19     0     1     1    19\n  6.6848134049442169E+00 a        20     0     1     1    20\n -2.2992719903495891E+00 a        21     0     1     1    21\n -1.4401533482181721E+01 a        22     0     1     1    22\n -2.0574070545285186E+00 a        23     0     1     1    23\n -6.3544667277888678E+00 a        24     0     1     1    24\n  3.9668360525851707E+00 a        25     0     1     1    25\n  1.0930597297534963E+01 a        26     0     2     1     1\n  3.0058866618169424E+00 a        27     0     2     1     2\n -4.9950943102999927E+00 a        28     0     2     1     3\n -1.9930957240687266E+00 a        29     0     2     1     4\n  1.6790893133342006E+00 a        30     0     2     1     5\n -4.5254006136507128E+00 a        31     0     2     1     6\n -9.6165021729265252E+00 a        32     0     2     1     7\n -8.7465722730176285E+00 a        33     0     2     1     8\n  1.5506950040431201E+01 a        34     0     2     1     9\n  2.1903342918227118E+01 a        35     0     2     1    10\n -1.0685216745153280E+01 a        36     0     2     1    11\n -2.5859690636594280E+01 a        37     0     2     1    12\n -3.2423603491405122E+00 a        38     0     2     1    13\n  5.3753900550878555E+00 a        39     0     2     1    14\n -3.0291935617567991E+00 a        40     0     2     1    15\n -1.3534893178408465E+01 a        41     0     2     1    16\n -5.7625138055631471E+00 a        42     0     2     1    17\n  1.0216765318459601E+01 a        43     0     2     1    18\n -1.4416012930050949E+01 a        44     0     2     1    19\n -4.7226757471872144E-01 a        45     0     2     1    20\n  7.8981385188798026E+00 a        46     0     2     1    21\n  1.2202710023744410E+00 a        47     0     2     1    22\n  8.0560891210932120E+00 a        48     0     2     1    23\n  4.5972445013263297E-01 a        49     0     2     1    24\n  1.3374237019728858E+01 a        50     0     2     1    25\n -1.0644910441621166E+01 a        51     0     3     1     1\n -5.6098794516515920E+00 a        52     0     3     1     2\n -1.0236653403367724E+01 a        53     0     3     1     3\n  1.3552139405799508E+00 a        54     0     3     1     4\n  1.3201025058567883E+00 a        55     0     3     1     5\n  1.6531266759009673E+00 a        56     0     3     1     6\n -1.0303768926395865E+01 a        57     0     3     1     7\n  1.9927521303470008E-01 a        58     0     3     1     8\n  8.1216226663758366E+00 a        59     0     3     1     9\n  2.1349555016157687E+01 a        60     0     3     1    10\n  1.0105416692705148E+01 a        61     0     3     1    11\n -1.1444993918278378E+01 a        62     0     3     1    12\n  2.9861675555209538E-01 a        63     0     3     1    13\n  9.3552992513120543E+00 a        64     0     3     1    14\n -2.2844869025933630E+00 a        65     0     3     1    15\n -3.8047300595857316E+00 a        66     0     3     1    16\n -3.0512161452147448E+00 a        67     0     3     1    17\n  2.7887340590896472E+00 a        68     0     3     1    18\n -1.5988439945122812E+01 a        69     0     3     1    19\n -1.6917164763280326E+01 a        70     0     3     1    20\n  3.2170907488709326E+00 a        71     0     3     1    21\n  2.1641888770160929E+01 a        72     0     3     1    22\n  3.2604671723420497E+00 a        73     0     3     1    23\n  1.5230689068493776E+01 a        74     0     3     1    24\n -1.4713830039823366E+01 a        75     0     3     1    25\n -2.3544214523969775E+00 a        76     0     4     1     1\n -5.8299691629399382E+00 a        77     0     4     1     2\n  1.7168784391956539E+01 a        78     0     4     1     3\n  1.0050003860864617E+01 a        79     0     4     1     4\n  3.5168903759752812E+00 a        80     0     4     1     5\n -4.4828111046589010E+00 a        81     0     4     1     6\n  1.8299193380051442E+01 a        82     0     4     1     7\n  6.9717289110204188E+00 a        83     0     4     1     8\n -2.0364082994445859E+01 a        84     0     4     1     9\n -3.5062338388300589E+01 a        85     0     4     1    10\n  1.8010375764887119E+01 a        86     0     4     1    11\n  4.2133659287179640E+01 a        87     0     4     1    12\n  1.1988736553417061E+01 a        88     0     4     1    13\n -1.2351529706885179E+01 a        89     0     4     1    14\n  5.4139212296285057E+00 a        90     0     4     1    15\n  1.6705967069968899E+01 a        91     0     4     1    16\n  8.3219076874511639E+00 a        92     0     4     1    17\n -1.8555777504879448E+01 a        93     0     4     1    18\n  3.1433889377775369E+01 a        94     0     4     1    19\n  6.7043459658252780E-01 a        95     0     4     1    20\n -1.3837570456349678E+01 a        96     0     4     1    21\n  5.0298368971353791E-01 a        97     0     4     1    22\n -2.2656240789613065E+01 a        98     0     4     1    23\n -2.4243684644962626E+00 a        99     0     4     1    24\n -2.8280330035212309E+01 a       100     0     4     1    25\n  4.2306100814115322E+00 a       101     0     5     1     1\n  9.9770374716830084E+00 a       102     0     5     1     2\n  2.0487048112933808E+00 a       103     0     5     1     3\n -1.3702212470739978E+00 a       104     0     5     1     4\n  2.8131124422603837E+00 a       105     0     5     1     5\n  3.2845640151619522E-03 a       106     0     5     1     6\n  2.4065616021196026E+00 a       107     0     5     1     7\n -1.0461000723401572E+01 a       108     0     5     1     8\n -1.0180720750329515E+01 a       109     0     5     1     9\n -8.8668996772076660E+00 a       110     0     5     1    10\n  6.5256092481271502E+00 a       111     0     5     1    11\n -6.9831054240027211E+00 a       112     0     5     1    12\n  4.0892074148312876E+00 a       113     0     5     1    13\n -5.1951354450201128E+00 a       114     0     5     1    14\n  1.6657989141753051E+00 a       115     0     5     1    15\n -7.3542511663155619E+00 a       116     0     5     1    16\n  5.1573102842565115E+00 a       117     0     5     1    17\n  3.4929930175122172E+00 a       118     0     5     1    18\n  2.5382184218789963E+00 a       119     0     5     1    19\n  2.0045179007481050E+01 a       120     0     5     1    20\n -1.6165269676512768E+00 a       121     0     5     1    21\n  2.4869117790922393E+00 a       122     0     5     1    22\n  6.0131560843540068E+00 a       123     0     5     1    23\n -1.2231651850388728E+01 a       124     0     5     1    24\n  3.5372450187997345E+01 a       125     0     5     1    25\n -1.0433252604911765E+01 a       126     0     6     1     1\n -2.3715834640656657E+00 a       127     0     6     1     2\n -1.8239608965373137E+01 a       128     0     6     1     3\n -3.6510816169583777E+00 a       129     0     6     1     4\n -1.7632327653119535E+01 a       130     0     6     1     5\n  1.0040509177650593E+01 a       131     0     6     1     6\n -1.5407385349225459E+01 a       132     0     6     1     7\n -7.0553605774310779E-01 a       133     0     6     1     8\n  1.3204892207903583E+01 a       134     0     6     1     9\n  2.9596389655595953E+01 a       135     0     6     1    10\n -2.0620173259628203E+01 a       136     0     6     1    11\n -3.0803380363815094E+01 a       137     0     6     1    12\n -1.4917676387082279E+01 a       138     0     6     1    13\n  9.6935054799166185E+00 a       139     0     6     1    14\n  4.6937319413252743E+00 a       140     0     6     1    15\n -5.0263591258131060E+00 a       141     0     6     1    16\n -9.7243575590712439E+00 a       142     0     6     1    17\n  1.5625340951727363E+01 a       143     0     6     1    18\n -2.8266776356585389E+01 a       144     0     6     1    19\n  2.5386057418612946E+00 a       145     0     6     1    20\n  1.6302330128073283E+01 a       146     0     6     1    21\n -8.5166226512297030E+00 a       147     0     6     1    22\n  2.5040570504752605E+01 a       148     0     6     1    23\n -8.5008658358878897E-01 a       149     0     6     1    24\n  2.0458930574550632E+01 a       150     0     6     1    25\n  7.8529627796707677E+00 a       151     0     7     1     1\n -4.5279242985866821E+00 a       152     0     7     1     2\n  4.7942839133231594E+00 a       153     0     7     1     3\n -6.2431002330064649E+00 a       154     0     7     1     4\n  4.3358077462982054E+00 a       155     0     7     1     5\n -6.8037589596444281E+00 a       156     0     7     1     6\n  1.8980667946224101E+00 a       157     0     7     1     7\n  1.9802532239433695E+01 a       158     0     7     1     8\n  8.4826746941006572E+00 a       159     0     7     1     9\n  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-4.6552795168897604E-01 a      1221     1    21     2    21\n  1.1611386377657384E+00 a      1222     1    21     2    22\n -1.2972265245341139E+00 a      1223     1    21     2    23\n  1.8117173751313085E+00 a      1224     1    21     2    24\n  1.0433495561237927E+00 a      1225     1    21     2    25\n  1.5410314634266913E+00 a      1226     1    22     2     1\n  6.6201420998527072E-01 a      1227     1    22     2     2\n  1.1189293597068475E+00 a      1228     1    22     2     3\n -1.1536147566508355E+00 a      1229     1    22     2     4\n -8.4859080711662893E-01 a      1230     1    22     2     5\n  3.7903158089014494E-01 a      1231     1    22     2     6\n -2.6461659405296234E+00 a      1232     1    22     2     7\n  2.2472472042954434E+00 a      1233     1    22     2     8\n -9.2281733258289744E-01 a      1234     1    22     2     9\n  8.7312141982063785E-01 a      1235     1    22     2    10\n -4.3593190134289528E-01 a      1236     1    22     2    11\n  5.1912574126564559E-01 a      1237     1    22     2    12\n -5.9029854481930821E-01 a      1238     1    22     2    13\n -7.2255183403800793E-01 a      1239     1    22     2    14\n  4.1024670935059383E-02 a      1240     1    22     2    15\n  2.0425371936604741E-01 a      1241     1    22     2    16\n -1.0394832812330597E+00 a      1242     1    22     2    17\n  4.7202219372950349E-01 a      1243     1    22     2    18\n -1.9958648332222221E-03 a      1244     1    22     2    19\n -1.4664186611455649E-02 a      1245     1    22     2    20\n  1.0689476163444707E+00 a      1246     1    22     2    21\n  8.4484833020425232E-01 a      1247     1    22     2    22\n -1.4147373614558330E+00 a      1248     1    22     2    23\n  1.9187324467269602E+00 a      1249     1    22     2    24\n  1.5330124676330812E+00 a      1250     1    22     2    25\n  2.3019050197742894E+00 a      1251     1    23     2     1\n -1.3828322911066271E-01 a      1252     1    23     2     2\n -2.3555430378419923E-01 a      1253     1    23     2     3\n -1.3434989779696097E-01 a      1254     1    23     2     4\n  3.7852663531566189E-01 a      1255     1    23     2     5\n  9.8266847359694973E-02 a      1256     1    23     2     6\n  3.2721968443206462E-01 a      1257     1    23     2     7\n -3.7061171550241617E-01 a      1258     1    23     2     8\n  2.2862436245090851E+00 a      1259     1    23     2     9\n  1.7674065728047832E+00 a      1260     1    23     2    10\n -5.2627257197444939E-02 a      1261     1    23     2    11\n  9.4094481148145870E-01 a      1262     1    23     2    12\n  1.0616552648143298E+00 a      1263     1    23     2    13\n -1.6065739188681796E-01 a      1264     1    23     2    14\n  1.6833160475834315E+00 a      1265     1    23     2    15\n -5.5679530352182072E-01 a      1266     1    23     2    16\n  4.2170082515325280E-01 a      1267     1    23     2    17\n  1.8142946234467967E+00 a      1268     1    23     2    18\n -6.0004075552166369E-01 a      1269     1    23     2    19\n  8.6767695096505049E-01 a      1270     1    23     2    20\n  1.7471709925670367E-01 a      1271     1    23     2    21\n  6.3494817986861019E-01 a      1272     1    23     2    22\n  7.9839233743975266E-02 a      1273     1    23     2    23\n -8.7497499907984810E-01 a      1274     1    23     2    24\n -2.1279336414401262E-01 a      1275     1    23     2    25\n -1.0628518357816100E+01 a      1276     1    24     2     1\n -3.4149879843865938E-01 a      1277     1    24     2     2\n -4.0534872173827868E-01 a      1278     1    24     2     3\n  1.0980204380257913E-01 a      1279     1    24     2     4\n  1.8376924276804879E-01 a      1280     1    24     2     5\n  8.5047887536146360E-01 a      1281     1    24     2     6\n  4.3913590571042438E-01 a      1282     1    24     2     7\n  2.7167430357232609E+00 a      1283     1    24     2     8\n  2.9682659556600960E-01 a      1284     1    24     2     9\n -1.6032245851281013E+00 a      1285     1    24     2    10\n -6.7567048640865046E-01 a      1286     1    24     2    11\n -1.5253382251900995E+00 a      1287     1    24     2    12\n -6.7540631566041298E-01 a      1288     1    24     2    13\n -1.4565321192168545E+00 a      1289     1    24     2    14\n -1.3315414628143039E+00 a      1290     1    24     2    15\n  1.2552098425264056E+00 a      1291     1    24     2    16\n -1.1701558601459501E+00 a      1292     1    24     2    17\n  2.1967564647703792E+00 a      1293     1    24     2    18\n  3.6767594091430167E-01 a      1294     1    24     2    19\n  1.4791781996464841E+00 a      1295     1    24     2    20\n -2.4597335939693896E+00 a      1296     1    24     2    21\n  1.8222789722776007E+00 a      1297     1    24     2    22\n -2.4818384588216302E+00 a      1298     1    24     2    23\n -1.3359962912345340E+00 a      1299     1    24     2    24\n -1.6060924344568878E-02 a      1300     1    24     2    25\n -1.1558703878945702E+00 a      1301     1    25     2     1\n  5.5859771317693908E-02 a      1302     1    25     2     2\n -1.9275021348316721E+00 a      1303     1    25     2     3\n  4.2881321046205173E-01 a      1304     1    25     2     4\n  6.6308764508018558E-01 a      1305     1    25     2     5\n -2.5357661809360188E-01 a      1306     1    25     2     6\n  7.7965409617466697E-01 a      1307     1    25     2     7\n -1.9470416731652336E+00 a      1308     1    25     2     8\n  2.0923659915641873E-01 a      1309     1    25     2     9\n  8.9211452410465542E-01 a      1310     1    25     2    10\n -1.9807939822570442E-01 a      1311     1    25     2    11\n -5.0922943173038127E-01 a      1312     1    25     2    12\n  1.3378430979044107E+00 a      1313     1    25     2    13\n -6.8964614083753073E-01 a      1314     1    25     2    14\n  7.6939619343191556E-01 a      1315     1    25     2    15\n -1.5783243312480257E+00 a      1316     1    25     2    16\n  2.3586020281744577E+00 a      1317     1    25     2    17\n -5.1641666185758928E-01 a      1318     1    25     2    18\n  1.0291540870545792E+00 a      1319     1    25     2    19\n  1.5269830348487650E+00 a      1320     1    25     2    20\n -2.8987700591417855E+00 a      1321     1    25     2    21\n  9.0207337792476916E-01 a      1322     1    25     2    22\n  1.9890049402284911E+00 a      1323     1    25     2    23\n  3.9387622927433424E-01 a      1324     1    25     2    24\n  9.9397126232482103E-01 a      1325     1    25     2    25\n  2.5306467041996967E+00 b      1326     2     1\n  3.1633393474977245E+00 b      1327     2     2\n -1.1644295509710691E+00 b      1328     2     3\n -5.7686722641223600E+00 b      1329     2     4\n  2.0065022303893989E+00 b      1330     2     5\n -5.9106057000795840E+00 b      1331     2     6\n -1.1326093285804056E+01 b      1332     2     7\n -3.9025063397327071E+00 b      1333     2     8\n  4.4520505166676267E+00 b      1334     2     9\n -1.7352681951318241E+00 b      1335     2    10\n -2.1518912430432668E+00 b      1336     2    11\n  5.0463376560082969E+00 b      1337     2    12\n -2.2614514173852837E-01 b      1338     2    13\n -4.1454590614747211E+00 b      1339     2    14\n  1.6688417293495756E+00 b      1340     2    15\n -5.8649976938793378E+00 b      1341     2    16\n -3.8350084459541849E+00 b      1342     2    17\n  1.3730477223722950E+00 b      1343     2    18\n  1.8506935712854127E+00 b      1344     2    19\n  5.7362757779153428E+00 b      1345     2    20\n  7.2901484895568780E+00 b      1346     2    21\n  3.9773783666446022E-01 b      1347     2    22\n -6.1298011242151409E+00 b      1348     2    23\n  9.9698755072742991E+00 b      1349     2    24\n  1.1801564149295556E+00 b      1350     2    25\n  1.2704098997067026E+01 a      1351     2     1     3     1\n  1.5947733940307620E+00 a      1352     2     2     3     1\n -1.6022927057878529E+00 a      1353     2     3     3     1\n -1.5507258540777733E+00 a      1354     2     4     3     1\n  1.8696884022727636E+00 a      1355     2     5     3     1\n -8.2051908880071633E-01 a      1356     2     6     3     1\n  9.4325719092522542E-01 a      1357     2     7     3     1\n  2.4098435369626174E+00 a      1358     2     8     3     1\n  1.4100759633042474E+00 a      1359     2     9     3     1\n -1.4613034838529613E+00 a      1360     2    10     3     1\n  1.0296574685193380E+00 a      1361     2    11     3     1\n  1.2413851904356363E+00 a      1362     2    12     3     1\n -6.3168181712211169E-01 a      1363     2    13     3     1\n  7.6424175125347729E+00 a      1364     2    14     3     1\n -1.3477038299214714E+00 a      1365     2    15     3     1\n -1.6064659765754943E+00 a      1366     2    16     3     1\n -8.9624380518145874E-01 a      1367     2    17     3     1\n -1.0509865792522375E+00 a      1368     2    18     3     1\n  8.1847872933853638E-01 a      1369     2    19     3     1\n  1.2845504810303034E+00 a      1370     2    20     3     1\n -5.1879822944368881E-01 a      1371     2    21     3     1\n -7.2018714033119180E-01 a      1372     2    22     3     1\n  5.9870832883780798E+00 a      1373     2    23     3     1\n -6.0589155387470683E-01 a      1374     2    24     3     1\n  5.0177609140285355E+00 a      1375     2    25     3     1\n  9.7386086372975722E+00 b      1376     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_external/hdnnp-data/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -4.2252995889643252E-01 a         1     0     1     1     1\n -6.0555645962054347E+00 a         2     0     1     1     2\n  1.4040722027928377E+01 a         3     0     1     1     3\n -2.7041370011942618E+00 a         4     0     1     1     4\n -3.8202743208058858E+00 a         5     0     1     1     5\n -3.3612643261393358E+00 a         6     0     1     1     6\n -2.0418101025905258E+00 a         7     0     1     1     7\n  7.5707237340996727E+00 a         8     0     1     1     8\n -5.8098755815926548E+00 a         9     0     1     1     9\n -6.0966886893925210E-01 a        10     0     1     1    10\n  5.8061564015115206E+00 a        11     0     1     1    11\n -1.5509339733099867E+00 a        12     0     1     1    12\n  1.9747395485200818E+00 a        13     0     1     1    13\n  4.5260782279680539E-01 a        14     0     1     1    14\n  9.9210415760283279E+00 a        15     0     1     1    15\n -6.5078831481547121E+00 a        16     0     1     1    16\n -3.4768832871318085E+00 a        17     0     1     1    17\n -1.9463994340943838E+00 a        18     0     1     1    18\n -3.4186058699290269E+00 a        19     0     1     1    19\n  1.2263643166698479E+00 a        20     0     1     1    20\n -5.9171161834436594E+00 a        21     0     1     1    21\n  1.8436267358458363E+00 a        22     0     1     1    22\n -2.3139530616378448E+00 a        23     0     1     1    23\n -1.7228542411478951E+01 a        24     0     1     1    24\n  2.2888610253215895E+00 a        25     0     1     1    25\n  8.0819405565169262E+00 a        26     0     2     1     1\n  8.0066409422078735E+00 a        27     0     2     1     2\n -2.8439251469462398E+01 a        28     0     2     1     3\n -1.1146087290797917E+01 a        29     0     2     1     4\n -7.5292172093563314E+00 a        30     0     2     1     5\n -4.0783685663337641E+00 a        31     0     2     1     6\n -4.4130406528599337E+00 a        32     0     2     1     7\n  1.0563249167508673E+01 a        33     0     2     1     8\n  1.0933105521974941E+01 a        34     0     2     1     9\n -1.1646509907117448E+01 a        35     0     2     1    10\n -7.5007478428041727E+00 a        36     0     2     1    11\n  7.7790182254249176E+00 a        37     0     2     1    12\n  1.1567034492555623E+01 a        38     0     2     1    13\n -4.2051741520233508E+00 a        39     0     2     1    14\n  3.1165306119132130E+00 a        40     0     2     1    15\n  1.6385645103485370E+01 a        41     0     2     1    16\n  2.6440539124381655E+00 a        42     0     2     1    17\n -3.9524518111687827E+00 a        43     0     2     1    18\n -8.7912410635652076E+00 a        44     0     2     1    19\n  4.3903318583813933E+00 a        45     0     2     1    20\n  3.3748047065442632E-01 a        46     0     2     1    21\n -6.6858946327311741E-01 a        47     0     2     1    22\n  5.4447187026310928E+00 a        48     0     2     1    23\n  1.9966018946508100E+01 a        49     0     2     1    24\n -1.7414420670154115E+01 a        50     0     2     1    25\n -3.9418657694849879E-01 a        51     0     3     1     1\n  9.1804829174186846E+00 a        52     0     3     1     2\n -1.0485089041850278E+01 a        53     0     3     1     3\n  8.9380499555048889E+00 a        54     0     3     1     4\n  1.0758607876097068E+01 a        55     0     3     1     5\n  7.2881492125393788E+00 a        56     0     3     1     6\n  8.2627077997774609E+00 a        57     0     3     1     7\n -1.2523613158520124E+01 a        58     0     3     1     8\n  4.5963999046141870E+00 a        59     0     3     1     9\n  8.2776469521184293E+00 a        60     0     3     1    10\n -2.1354371687617113E+00 a        61     0     3     1    11\n -9.0381751821938234E+00 a        62     0     3     1    12\n -1.2209592338152297E+00 a        63     0     3     1    13\n  4.7653671372245672E+00 a        64     0     3     1    14\n -1.7909124818088952E+01 a        65     0     3     1    15\n  3.2182917515973237E+00 a        66     0     3     1    16\n -2.3712750109800793E+00 a        67     0     3     1    17\n  4.6394007836500366E+00 a        68     0     3     1    18\n  2.3761984937954490E+00 a        69     0     3     1    19\n -1.0484832585147684E+01 a        70     0     3     1    20\n  1.2317970755621140E+01 a        71     0     3     1    21\n -1.5014054499447769E+00 a        72     0     3     1    22\n -1.1215435083480425E+00 a        73     0     3     1    23\n  8.9428653321614355E+00 a        74     0     3     1    24\n  1.2636165742848842E+00 a        75     0     3     1    25\n -1.3406492086741725E+01 a        76     0     4     1     1\n -1.0241053204283523E+01 a        77     0     4     1     2\n  4.3016369326050899E+01 a        78     0     4     1     3\n  2.0170433813810671E+01 a        79     0     4     1     4\n  1.3209328101408278E+01 a        80     0     4     1     5\n  1.2456789467161695E+01 a        81     0     4     1     6\n  4.3498515722861573E+00 a        82     0     4     1     7\n -2.1948185511490657E+01 a        83     0     4     1     8\n -1.5329558038416376E+01 a        84     0     4     1     9\n  1.4173337432869845E+01 a        85     0     4     1    10\n  5.6040631650516088E+00 a        86     0     4     1    11\n -9.7646834958548663E+00 a        87     0     4     1    12\n -1.3810669587629080E+01 a        88     0     4     1    13\n -1.5274915717855073E+00 a        89     0     4     1    14\n -1.3662043326477198E+01 a        90     0     4     1    15\n -2.5095635769057225E+01 a        91     0     4     1    16\n  5.4033548590960638E+00 a        92     0     4     1    17\n  1.1047593171711565E+01 a        93     0     4     1    18\n  1.9404912122904062E+01 a        94     0     4     1    19\n  2.4043652449872512E+00 a        95     0     4     1    20\n -3.3818087825635010E+00 a        96     0     4     1    21\n -4.9505657938825802E+00 a        97     0     4     1    22\n  6.2159614529590854E+00 a        98     0     4     1    23\n -1.9315299866781363E+01 a        99     0     4     1    24\n  2.4149549923763363E+01 a       100     0     4     1    25\n  2.2633190213689671E+00 a       101     0     5     1     1\n -1.1275056403465689E+01 a       102     0     5     1     2\n  1.2588751117785917E+00 a       103     0     5     1     3\n -1.7399288116611554E+01 a       104     0     5     1     4\n -1.8915392010979964E+01 a       105     0     5     1     5\n -6.5088880348621911E+00 a       106     0     5     1     6\n -8.7022768117985532E+00 a       107     0     5     1     7\n  9.5716939158219958E+00 a       108     0     5     1     8\n  6.7173652175539926E+00 a       109     0     5     1     9\n -1.0675975211687946E+01 a       110     0     5     1    10\n -9.8676303718126039E+00 a       111     0     5     1    11\n  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1.5566506128138184E+00 a      1237     1    19     2    12\n -9.4986537106149321E-02 a      1238     1    19     2    13\n -2.3530503270088396E-01 a      1239     1    19     2    14\n  3.6439425212581661E-01 a      1240     1    19     2    15\n  1.2871636736138770E+00 a      1241     1    19     2    16\n -8.4712787652121069E-01 a      1242     1    19     2    17\n -1.0234220464653516E+00 a      1243     1    19     2    18\n -1.3802013894870373E+00 a      1244     1    19     2    19\n  4.6238544527464259E-01 a      1245     1    19     2    20\n -3.1736140472371468E+00 a      1246     1    19     2    21\n  1.7897235482645921E+00 a      1247     1    19     2    22\n -1.2075712900497950E+00 a      1248     1    19     2    23\n -3.1032297572767770E-01 a      1249     1    19     2    24\n  2.1706205401676661E+00 a      1250     1    19     2    25\n  6.9973782486580109E+00 a      1251     1    20     2     1\n  2.9325190821916197E-01 a      1252     1    20     2     2\n -1.2648655109330131E+00 a      1253     1    20     2     3\n -4.3905910522706337E-01 a      1254     1    20     2     4\n  4.2887555555714030E-01 a      1255     1    20     2     5\n  1.3300944280643934E+00 a      1256     1    20     2     6\n  1.0988390404457922E+00 a      1257     1    20     2     7\n  2.3801051936039075E+00 a      1258     1    20     2     8\n  1.1789379212300943E-01 a      1259     1    20     2     9\n  3.9144297908957699E+00 a      1260     1    20     2    10\n  5.5000952527940228E-01 a      1261     1    20     2    11\n  2.4087943927489916E-01 a      1262     1    20     2    12\n -3.7997171313505251E-01 a      1263     1    20     2    13\n -5.4744714104500347E-01 a      1264     1    20     2    14\n  8.9095280999944937E-01 a      1265     1    20     2    15\n -8.7130940035564164E-01 a      1266     1    20     2    16\n  3.7900358553306007E-01 a      1267     1    20     2    17\n  2.1342515402584987E+00 a      1268     1    20     2    18\n  1.2475880574414706E+00 a      1269     1    20     2    19\n  7.8956439485340524E-01 a      1270     1    20     2    20\n  4.6968348528891219E+00 a      1271     1    20     2    21\n  2.4464240930319816E+00 a      1272     1    20     2    22\n -5.7785142905302376E+00 a      1273     1    20     2    23\n -2.3074149497856417E-01 a      1274     1    20     2    24\n -2.6800082940155296E+00 a      1275     1    20     2    25\n -3.2729577955630704E+00 a      1276     1    21     2     1\n -1.2928637501931926E+00 a      1277     1    21     2     2\n -2.2664219916515152E-01 a      1278     1    21     2     3\n  6.8197406796553048E-02 a      1279     1    21     2     4\n  2.2800043902454539E-01 a      1280     1    21     2     5\n -1.4547709606717896E+00 a      1281     1    21     2     6\n -8.9797316703694119E-02 a      1282     1    21     2     7\n -7.9615421262219899E-01 a      1283     1    21     2     8\n -2.5074736863647562E-01 a      1284     1    21     2     9\n -3.2383137185187805E-01 a      1285     1    21     2    10\n -7.7486670060442631E-01 a      1286     1    21     2    11\n -1.7378145875987788E-01 a      1287     1    21     2    12\n  1.7001762592878558E+00 a      1288     1    21     2    13\n -1.7033999809142997E+00 a      1289     1    21     2    14\n  3.7961258225336264E-01 a      1290     1    21     2    15\n  6.0929689839357426E-01 a      1291     1    21     2    16\n -1.9171250145280534E+00 a      1292     1    21     2    17\n -1.6594854242769004E+00 a      1293     1    21     2    18\n -2.8219229087100910E+00 a      1294     1    21     2    19\n -4.3902463688638738E-01 a      1295     1    21     2    20\n -1.1744026035352828E+00 a      1296     1    21     2    21\n  3.9648025457334164E+00 a      1297     1    21     2    22\n -1.3587513635268793E+00 a      1298     1    21     2    23\n  3.9463311556495906E-02 a      1299     1    21     2    24\n -4.6280624473662763E-01 a      1300     1    21     2    25\n  8.3725910272757709E+00 a      1301     1    22     2     1\n  1.2030400911595496E+00 a      1302     1    22     2     2\n  5.2723639396495003E-01 a      1303     1    22     2     3\n  2.4863416823271995E+00 a      1304     1    22     2     4\n  5.0656775645932173E-01 a      1305     1    22     2     5\n  7.8889662692367113E-01 a      1306     1    22     2     6\n  2.7467021112668549E-01 a      1307     1    22     2     7\n  3.5551997281423904E+00 a      1308     1    22     2     8\n -6.9074567194666425E-01 a      1309     1    22     2     9\n  9.2831069742658789E-01 a      1310     1    22     2    10\n -2.7305664188353734E-01 a      1311     1    22     2    11\n -1.6732686793215996E+00 a      1312     1    22     2    12\n -1.2508123463191103E+00 a      1313     1    22     2    13\n  1.4253551144285490E+00 a      1314     1    22     2    14\n -1.2730453204508483E+00 a      1315     1    22     2    15\n -5.6234386233504563E-01 a      1316     1    22     2    16\n  4.7348930208036427E-01 a      1317     1    22     2    17\n  1.4228359329011722E+00 a      1318     1    22     2    18\n -3.0896237212805277E-02 a      1319     1    22     2    19\n -7.7625773033108136E-01 a      1320     1    22     2    20\n  5.1571228251110171E-02 a      1321     1    22     2    21\n -1.5781774955827834E+00 a      1322     1    22     2    22\n -1.7313703986673430E+00 a      1323     1    22     2    23\n -1.3316987118953665E+00 a      1324     1    22     2    24\n -7.0760527312605037E-01 a      1325     1    22     2    25\n -8.1466385165616928E-01 a      1326     1    23     2     1\n  6.8912340727205368E-01 a      1327     1    23     2     2\n  8.4582890184800619E-01 a      1328     1    23     2     3\n  3.8163700575566650E-01 a      1329     1    23     2     4\n -6.6556600373886232E-01 a      1330     1    23     2     5\n -1.3399458536680564E+00 a      1331     1    23     2     6\n -1.7425009694107033E-01 a      1332     1    23     2     7\n -2.6104662248332646E+00 a      1333     1    23     2     8\n -1.9788280313555501E-01 a      1334     1    23     2     9\n -4.6341960827595043E+00 a      1335     1    23     2    10\n -4.1560774205921192E-01 a      1336     1    23     2    11\n -1.3453315295733928E-01 a      1337     1    23     2    12\n  5.9251987079212687E-01 a      1338     1    23     2    13\n  1.3014540212114664E-01 a      1339     1    23     2    14\n  2.4962768316839337E-01 a      1340     1    23     2    15\n  3.3868458734074913E-01 a      1341     1    23     2    16\n -2.1103970517135956E-01 a      1342     1    23     2    17\n -2.7311756320323316E-01 a      1343     1    23     2    18\n  7.7825779463422798E-02 a      1344     1    23     2    19\n -1.5510879185574573E+00 a      1345     1    23     2    20\n -3.3731285186903501E+00 a      1346     1    23     2    21\n  1.5012690395440691E+00 a      1347     1    23     2    22\n -1.4938786629136067E+00 a      1348     1    23     2    23\n  1.5155834326942672E-01 a      1349     1    23     2    24\n  2.2135367884980521E+00 a      1350     1    23     2    25\n  7.6092107307961931E-01 a      1351     1    24     2     1\n  2.5019321183393825E-02 a      1352     1    24     2     2\n  2.4714648764760871E-01 a      1353     1    24     2     3\n -4.2700090187223255E-01 a      1354     1    24     2     4\n  1.9684439924637190E-01 a      1355     1    24     2     5\n -1.6150658390090172E-01 a      1356     1    24     2     6\n -8.4941771549071021E-01 a      1357     1    24     2     7\n  3.2616941337700417E-01 a      1358     1    24     2     8\n -6.0235251095177200E-01 a      1359     1    24     2     9\n  2.0073315297316108E+00 a      1360     1    24     2    10\n  6.8678637919958119E-01 a      1361     1    24     2    11\n -1.4709309602563259E+00 a      1362     1    24     2    12\n -7.3119546383323997E-01 a      1363     1    24     2    13\n  5.9624465461749732E-01 a      1364     1    24     2    14\n  1.1965703107989687E+00 a      1365     1    24     2    15\n -4.8078015734066326E-01 a      1366     1    24     2    16\n  2.8731897539798784E-01 a      1367     1    24     2    17\n  2.8943049077679879E+00 a      1368     1    24     2    18\n  4.4309374097560666E-01 a      1369     1    24     2    19\n -5.2571668466848664E-01 a      1370     1    24     2    20\n  2.6293009755349539E+00 a      1371     1    24     2    21\n  1.1166360248787797E+00 a      1372     1    24     2    22\n  1.4367909042068954E+00 a      1373     1    24     2    23\n  1.2263949730702137E+00 a      1374     1    24     2    24\n -1.5658327417588482E+00 a      1375     1    24     2    25\n -3.0524380712257440E+00 a      1376     1    25     2     1\n -1.6248402538917406E-01 a      1377     1    25     2     2\n  5.3725239557723847E-01 a      1378     1    25     2     3\n -3.1435543583372311E-01 a      1379     1    25     2     4\n  8.0294309812719877E-01 a      1380     1    25     2     5\n -3.3745709161028831E-01 a      1381     1    25     2     6\n  2.9618139473335392E-01 a      1382     1    25     2     7\n -1.3606606680314999E+00 a      1383     1    25     2     8\n  2.9886863438452965E-01 a      1384     1    25     2     9\n  3.4365095196288835E+00 a      1385     1    25     2    10\n  2.8778063903425566E-01 a      1386     1    25     2    11\n -5.2312889094867954E-01 a      1387     1    25     2    12\n  4.5730896273705224E-01 a      1388     1    25     2    13\n -8.8949447500584955E-01 a      1389     1    25     2    14\n -8.1389897744929640E-01 a      1390     1    25     2    15\n -4.0077086298379117E-01 a      1391     1    25     2    16\n  7.2544627916775950E-01 a      1392     1    25     2    17\n -9.8029709488119798E-01 a      1393     1    25     2    18\n  8.5017837869712165E-01 a      1394     1    25     2    19\n -2.9795775527520296E-01 a      1395     1    25     2    20\n  1.1940911570260535E+00 a      1396     1    25     2    21\n -4.1259772504588357E-02 a      1397     1    25     2    22\n  1.0619824936744515E+00 a      1398     1    25     2    23\n -6.5325825341918264E-01 a      1399     1    25     2    24\n  3.7575240210802421E+00 a      1400     1    25     2    25\n -1.0787018434494783E+01 b      1401     2     1\n -8.4067078142086771E-01 b      1402     2     2\n  9.3201271110229211E-01 b      1403     2     3\n -1.8318272256547821E+00 b      1404     2     4\n -2.1732436845179119E+00 b      1405     2     5\n -2.6390929073478930E+00 b      1406     2     6\n  3.7489748853957300E-01 b      1407     2     7\n -2.3789675524866163E+00 b      1408     2     8\n  2.7252644932624959E+00 b      1409     2     9\n  2.5100559841854970E+00 b      1410     2    10\n -2.4897033671113025E-01 b      1411     2    11\n  2.6913296692082476E+00 b      1412     2    12\n  5.8162695990329221E+00 b      1413     2    13\n -1.5170700889568940E+00 b      1414     2    14\n  4.2121259244130220E+00 b      1415     2    15\n  2.2987725066596130E+00 b      1416     2    16\n -7.1493650128731911E-01 b      1417     2    17\n -3.9961443472349811E-01 b      1418     2    18\n  7.8083705485664430E+00 b      1419     2    19\n -4.0462773256448170E-01 b      1420     2    20\n -1.4333029489891109E+00 b      1421     2    21\n -4.9517224038431467E+00 b      1422     2    22\n  1.0702867307710989E+01 b      1423     2    23\n -9.7535853921453985E-01 b      1424     2    24\n  5.3161969295054172E+00 b      1425     2    25\n -5.1941647295982207E-01 a      1426     2     1     3     1\n -7.7346657642095373E-01 a      1427     2     2     3     1\n  1.4003893583106508E+00 a      1428     2     3     3     1\n  8.9188080044914464E-01 a      1429     2     4     3     1\n -2.0147808233792022E+00 a      1430     2     5     3     1\n -1.8131831735812174E+00 a      1431     2     6     3     1\n  3.3217884596641700E+00 a      1432     2     7     3     1\n -1.2675289031787327E+00 a      1433     2     8     3     1\n -1.2791140359120716E+00 a      1434     2     9     3     1\n  1.9731828075446340E+00 a      1435     2    10     3     1\n -2.3928332883234411E+00 a      1436     2    11     3     1\n -1.1755085043375486E+00 a      1437     2    12     3     1\n  2.6525670286472951E+00 a      1438     2    13     3     1\n -2.4861988521743901E+00 a      1439     2    14     3     1\n  1.2534500349238071E+00 a      1440     2    15     3     1\n  2.8804282010183990E+00 a      1441     2    16     3     1\n -2.0327745898215275E+00 a      1442     2    17     3     1\n -1.1760164122204946E+00 a      1443     2    18     3     1\n -9.9841804355412322E-01 a      1444     2    19     3     1\n -1.8663330516323837E+00 a      1445     2    20     3     1\n  6.3266049836286531E-01 a      1446     2    21     3     1\n  1.2025500357718348E+00 a      1447     2    22     3     1\n  1.1367820678861495E-01 a      1448     2    23     3     1\n -2.6481374255863193E+00 a      1449     2    24     3     1\n  5.2166795947347921E-01 a      1450     2    25     3     1\n  4.8693043186011655E+00 b      1451     3     1\n"
  },
  {
    "path": "examples/interface-LAMMPS/H2O_RPBE-D3_external/md.lmp",
    "content": "###############################################################################\n# MD simulation for NN water\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"h2o_8640_liquid_NpT_RPBE-D3.data\"\n# Timesteps\nvariable numSteps        equal  5\nvariable dt              equal  0.0005\n# NN\nvariable hdnnpCutoff     equal  6.36\nvariable hdnnpDir        string \"hdnnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_O          equal  15.9994\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary p p p\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_H}\nmass 2 ${mass_O}\ntimestep ${dt}\nthermo 1\n\n###############################################################################\n# NN\n###############################################################################\npair_style hdnnp/external \"H O\" dir ${hdnnpDir} cflength 1.8897261328 cfenergy 0.0367493254\npair_coeff * * ${hdnnpCutoff}\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\ndump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/carbon-chain.data",
    "content": "Carbon chain, first structure from input.data\n\n12 atoms\n\n2 atom types\n\n  -12.94 12.67 xlo xhi\n   -0.36  1.20 ylo yhi\n   -0.67  1.17 zlo zhi\n\nAtoms\n\n1  2  1.17284095486 -0.172504222684   -0.667448516865\n2  2 -1.1595434822  -0.350641000445   -0.467598107194\n3  2  3.72594054969 -0.0837975179097  -0.229777168673\n4  2 -3.69146983116 -0.334172643167   -0.21088223315\n5  2  6.07758586771 -0.166745226042   -0.145024035228\n6  2 -6.06809789367 -0.00253733508489 -0.0705357610724\n7  2  8.59164353464 -0.0806915075831   0.402236831619\n8  2 -8.60892564573  0.117192245354    0.0982851777904\n9  2  10.8705405815  0.51581338865     0.435826522093\n10 2 -10.8879581104  0.411807821319    0.694948565342\n11 1  12.661965991   1.19502446714     1.1691448209\n12 1 -12.9307322131  0.525058551796    0.728011456903\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/log.lammps",
    "content": "LAMMPS (29 Oct 2020)\n###############################################################################\n# MD simulation for carbon chain\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"carbon-chain.data\"\n# Timesteps\nvariable numSteps        equal  5\nvariable dt              equal  0.0005\n# NN\nvariable nnpCutoff       equal  8.01\nvariable nnpDir          string \"nnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_C          equal  12.0107\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary s s s\natom_style atomic\nread_data ${cfgFile}\nread_data carbon-chain.data\nReading data file ...\n  orthogonal box = (-12.940000 -0.36 -0.67) to (12.670000 1.2000000 1.1700000)\n  1 by 1 by 1 MPI processor grid\n  reading atoms ...\n  12 atoms\n  read_data CPU = 0.000 seconds\nmass 1 ${mass_H}\nmass 1 1.00794\nmass 2 ${mass_C}\nmass 2 12.0107\ntimestep ${dt}\ntimestep 0.0005\nthermo 1\n\n###############################################################################\n# NN\n###############################################################################\npair_style nnp dir ${nnpDir} showew no showewsum 10 resetew no maxew 100 cflength 1.0 cfenergy 1.0 emap \"1:H,2:C\"\npair_style nnp dir nnp-data showew no showewsum 10 resetew no maxew 100 cflength 1.0 cfenergy 1.0 emap \"1:H,2:C\"\npair_coeff * * ${nnpCutoff}\npair_coeff * * 8.01\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\n#dump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\nrun 5\n\n*******************************************************************************\n\nWELCOME TO n²p², A SOFTWARE PACKAGE FOR NEURAL NETWORK POTENTIALS!\n------------------------------------------------------------------\n\nn²p² version      : v2.1.1-43-g417919d\n------------------------------------------------------------\nGit branch        : 4G-HDNNP-prediction\nGit revision      : 417919d7ff1bc727b4f9032afc6a574811f7a75b\nCompile date/time : Feb 27 2021 23:33:56\n------------------------------------------------------------\n\nPlease cite the following papers when publishing results obtained with n²p²:\n-------------------------------------------------------------------------------\n * General citation for n²p² and the LAMMPS interface:\n\n Singraber, A.; Behler, J.; Dellago, C.\n Library-Based LAMMPS Implementation of High-Dimensional\n Neural Network Potentials.\n J. Chem. Theory Comput. 2019 15 (3), 1827–1840.\n https://doi.org/10.1021/acs.jctc.8b00770\n-------------------------------------------------------------------------------\n * Additionally, if you use the NNP training features of n²p²:\n\n Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C.\n Parallel Multistream Training of High-Dimensional Neural\n Network Potentials.\n J. Chem. Theory Comput. 2019, 15 (5), 3075–3092.\n https://doi.org/10.1021/acs.jctc.8b01092\n-------------------------------------------------------------------------------\n * Additionally, if polynomial symmetry functions are used:\n\n Bircher, M. P.; Singraber, A.; Dellago, C.\n Improved Description of Atomic Environments Using Low-Cost\n Polynomial Functions with Compact Support.\n arXiv:2010.14414 [cond-mat, physics:physics] 2020.\n https://arxiv.org/abs/2010.14414\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: nnp-data/input.nn\nRead 185 lines.\nWARNING: Unknown keyword \"bond_threshold\" at line 34.\nWARNING: Unknown keyword \"calculate_forces\" at line 183.\nWARNING: Unknown keyword \"energy_threshold\" at line 33.\nWARNING: Unknown keyword \"fitting_unit\" at line 148.\nWARNING: Unknown keyword \"initial_hardness\" at line 29.\nWARNING: Unknown keyword \"initial_hardness\" at line 30.\nWARNING: Unknown keyword \"kalman_lambda_charge\" at line 156.\nWARNING: Unknown keyword \"kalman_nue_charge\" at line 157.\nWARNING: Unknown keyword \"mix_all_points\" at line 145.\nWARNING: Unknown keyword \"optmode_short_energy\" at line 152.\nWARNING: Unknown keyword \"optmode_short_force\" at line 153.\nWARNING: Unknown keyword \"points_in_memory\" at line 144.\nWARNING: Unknown keyword \"random_number_type\" at line 25.\nWARNING: Unknown keyword \"regularize_fit_param\" at line 173.\nWARNING: Unknown keyword \"remove_atom_energies\" at line 26.\nWARNING: Unknown keyword \"runner_mode\" at line 20.\nWARNING: Unknown keyword \"use_electrostatics\" at line 17.\nWARNING: Unknown keyword \"use_short_nn\" at line 18.\nWARNING: 18 problems detected (0 critical).\nFound 113 lines with keywords.\nThis settings file defines a NNP with electrostatics and\nnon-local charge transfer (4G-HDNNP).\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is not used.\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  H (  1)\nElement  1:  C (  6)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:  -4.58907306E-01\nElement  1:  -3.77481119E+01\nEnergy offsets are automatically subtracted from reference energies.\n*******************************************************************************\n\n*** SETUP: ELECTROSTATICS *****************************************************\n\nAtomic hardness file name format: nnp-data/hardness.%03zu.data\nAtomic hardness for element  H from file nnp-data/hardness.001.data:   8.89533120E-03\nAtomic hardness for element  C from file nnp-data/hardness.006.data:   6.61189426E-02\n\nGaussian width of charge distribution per element:\nElement  0:   5.85815056E-01\nElement  1:   1.37949997E+00\n\nEwald precision:   1.00000000E-06\n\nScreening function information:\nInner radius :   4.80000000E+00\nOuter radius :   8.00000000E+00\nTransition region functional form:\nx     := (r - inner) / (outer - inner)\nfs(x) := 1 - f(x)\nCoreFunction::Type::COS (0):\nf(x) := 1/2 * (cos(pi*x) + 1)\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_TANHU (2)\nf(r) = tanh^3(1 - r/rc)\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\ntp ..... Symmetry function type.\nsbtp ... Symmetry function subtype (e.g. cutoff type).\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs/rl... Shift distance of Gaussian or left cutoff radius for polynomial.\nangl.... Left cutoff angle for polynomial.\nangr.... Right cutoff angle for polynomial.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius / right cutoff radius for polynomial.\na ...... Free parameter alpha (e.g. cutoff alpha).\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  H :\n-------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln\n-------------------------------------------------------------------------------------------------\n   1  H  2  ct2  H    0.000E+00  0.000E+00  8.000E+00                       0.00    59\n   2  H  2  ct2  C    0.000E+00  0.000E+00  8.000E+00                       0.00    74\n   3  H  2  ct2  H    6.000E-03  0.000E+00  8.000E+00                       0.00    60\n   4  H  2  ct2  H    1.100E-02  0.000E+00  8.000E+00                       0.00    61\n   5  H  2  ct2  C    1.300E-02  0.000E+00  8.000E+00                       0.00    75\n   6  H  2  ct2  H    1.800E-02  0.000E+00  8.000E+00                       0.00    62\n   7  H  2  ct2  H    2.600E-02  0.000E+00  8.000E+00                       0.00    63\n   8  H  2  ct2  C    2.900E-02  0.000E+00  8.000E+00                       0.00    76\n   9  H  2  ct2  H    3.500E-02  0.000E+00  8.000E+00                       0.00    64\n  10  H  2  ct2  C    5.400E-02  0.000E+00  8.000E+00                       0.00    77\n  11  H  2  ct2  C    9.300E-02  0.000E+00  8.000E+00                       0.00    78\n  12  H  2  ct2  C    1.610E-01  0.000E+00  8.000E+00                       0.00    79\n  13  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   134\n  14  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   125\n  15  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   130\n  16  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   121\n  17  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   135\n  18  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   126\n  19  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   131\n  20  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   122\n  21  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   132\n  22  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   123\n  23  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   133\n  24  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   124\n-------------------------------------------------------------------------------------------------\nShort range atomic symmetry functions element  C :\n-------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln\n-------------------------------------------------------------------------------------------------\n   1  C  2  ct2  H    0.000E+00  0.000E+00  8.000E+00                       0.00    67\n   2  C  2  ct2  C    0.000E+00  0.000E+00  8.000E+00                       0.00    82\n   3  C  2  ct2  C    1.000E-02  0.000E+00  8.000E+00                       0.00    83\n   4  C  2  ct2  H    1.300E-02  0.000E+00  8.000E+00                       0.00    68\n   5  C  2  ct2  C    2.300E-02  0.000E+00  8.000E+00                       0.00    84\n   6  C  2  ct2  H    2.900E-02  0.000E+00  8.000E+00                       0.00    69\n   7  C  2  ct2  C    4.100E-02  0.000E+00  8.000E+00                       0.00    85\n   8  C  2  ct2  H    5.400E-02  0.000E+00  8.000E+00                       0.00    70\n   9  C  2  ct2  C    6.500E-02  0.000E+00  8.000E+00                       0.00    86\n  10  C  2  ct2  H    9.300E-02  0.000E+00  8.000E+00                       0.00    71\n  11  C  2  ct2  C    1.030E-01  0.000E+00  8.000E+00                       0.00    87\n  12  C  2  ct2  H    1.610E-01  0.000E+00  8.000E+00                       0.00    72\n  13  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   106\n  14  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   115\n  15  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00    97\n  16  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   102\n  17  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   111\n  18  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00    93\n  19  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   107\n  20  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   116\n  21  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00    98\n  22  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   103\n  23  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   112\n  24  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00    94\n  25  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  4.0 0.00   108\n  26  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  4.0 0.00   117\n  27  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  4.0 0.00    99\n  28  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   104\n  29  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   113\n  30  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00    95\n  31  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  8.0 0.00   109\n  32  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  8.0 0.00   118\n  33  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  8.0 0.00   100\n  34  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   105\n  35  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   114\n  36  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00    96\n-------------------------------------------------------------------------------------------------\nMinimum cutoff radius for element  H: 8.000000\nMinimum cutoff radius for element  C: 8.000000\nMaximum cutoff radius (global)      : 8.000000\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION MEMORY *******************************************\n\nSymmetry function derivatives memory table for element  H :\n-------------------------------------------------------------------------------\nRelevant symmetry functions for neighbors with element:\n-  H:   12 of   24 ( 50.0 %)\n-  C:   18 of   24 ( 75.0 %)\n-------------------------------------------------------------------------------\nSymmetry function derivatives memory table for element  C :\n-------------------------------------------------------------------------------\nRelevant symmetry functions for neighbors with element:\n-  H:   22 of   36 ( 61.1 %)\n-  C:   22 of   36 ( 61.1 %)\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION CACHE ********************************************\n\nElement  H: in total 4 caches, used 15.00 times on average.\nElement  C: in total 4 caches, used 22.00 times on average.\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\ntp ..... Symmetry function type.\nsbtp ... Symmetry function subtype (e.g. cutoff type).\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs/rl... Shift distance of Gaussian or left cutoff radius for polynomial.\nangl.... Left cutoff angle for polynomial.\nangr.... Right cutoff angle for polynomial.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius / right cutoff radius for polynomial.\na ...... Free parameter alpha (e.g. cutoff alpha).\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  H :\n----------------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln   mi  sfi e\n----------------------------------------------------------------------------------------------------------\n   1  H  2  ct2  H            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    59    1    1  \n   -  -  -    -  -    6.000E-03  0.000E+00          -                          -    60    2    3  \n   -  -  -    -  -    1.100E-02  0.000E+00          -                          -    61    3    4  \n   -  -  -    -  -    1.800E-02  0.000E+00          -                          -    62    4    6  \n   -  -  -    -  -    2.600E-02  0.000E+00          -                          -    63    5    7  \n   -  -  -    -  -    3.500E-02  0.000E+00          -                          -    64    6    9  \n   2  H  2  ct2  C            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    74    1    2  \n   -  -  -    -  -    1.300E-02  0.000E+00          -                          -    75    2    5  \n   -  -  -    -  -    2.900E-02  0.000E+00          -                          -    76    3    8  \n   -  -  -    -  -    5.400E-02  0.000E+00          -                          -    77    4   10  \n   -  -  -    -  -    9.300E-02  0.000E+00          -                          -    78    5   11  \n   -  -  -    -  -    1.610E-01  0.000E+00          -                          -    79    6   12  \n   3  H  3  ct2  H  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   134    1   13 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   130    2   15 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   135    3   17 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   131    4   19 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   132    5   21 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   133    6   23 0\n   4  H  3  ct2  C  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   125    1   14 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   121    2   16 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   126    3   18 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   122    4   20 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   123    5   22 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   124    6   24 0\n----------------------------------------------------------------------------------------------------------\nShort range atomic symmetry function groups element  C :\n----------------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln   mi  sfi e\n----------------------------------------------------------------------------------------------------------\n   1  C  2  ct2  H            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    67    1    1  \n   -  -  -    -  -    1.300E-02  0.000E+00          -                          -    68    2    4  \n   -  -  -    -  -    2.900E-02  0.000E+00          -                          -    69    3    6  \n   -  -  -    -  -    5.400E-02  0.000E+00          -                          -    70    4    8  \n   -  -  -    -  -    9.300E-02  0.000E+00          -                          -    71    5   10  \n   -  -  -    -  -    1.610E-01  0.000E+00          -                          -    72    6   12  \n   2  C  2  ct2  C            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    82    1    2  \n   -  -  -    -  -    1.000E-02  0.000E+00          -                          -    83    2    3  \n   -  -  -    -  -    2.300E-02  0.000E+00          -                          -    84    3    5  \n   -  -  -    -  -    4.100E-02  0.000E+00          -                          -    85    4    7  \n   -  -  -    -  -    6.500E-02  0.000E+00          -                          -    86    5    9  \n   -  -  -    -  -    1.030E-01  0.000E+00          -                          -    87    6   11  \n   3  C  3  ct2  H  H         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   106    1   13 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   102    2   16 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   107    3   19 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   103    4   22 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  4.0    -   108    5   25 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   104    6   28 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  8.0    -   109    7   31 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   105    8   34 0\n   4  C  3  ct2  H  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   115    1   14 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   111    2   17 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   116    3   20 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   112    4   23 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  4.0    -   117    5   26 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   113    6   29 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  8.0    -   118    7   32 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   114    8   35 0\n   5  C  3  ct2  C  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -    97    1   15 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -    93    2   18 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -    98    3   21 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -    94    4   24 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  4.0    -    99    5   27 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -    95    6   30 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  8.0    -   100    7   33 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -    96    8   36 0\n----------------------------------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic electronegativity NN for element  H :\nNumber of weights    :    600\nNumber of biases     :     31\nNumber of connections:    631\nArchitecture       24   15   15    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n-------------------------------------------------------------------------------\nAtomic electronegativity NN for element  C :\nNumber of weights    :    780\nNumber of biases     :     31\nNumber of connections:    811\nArchitecture       36   15   15    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n  25   G            \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  H :\nNumber of weights    :    360\nNumber of biases     :     21\nNumber of connections:    381\nArchitecture       25   10   10    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G            \n  12   G            \n  13   G            \n  14   G            \n  15   G            \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n  25   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  C :\nNumber of weights    :    480\nNumber of biases     :     21\nNumber of connections:    501\nArchitecture       37   10   10    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G            \n  12   G            \n  13   G            \n  14   G            \n  15   G            \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n  25   G            \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n  37   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALECENTER (3)\nGs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\nWARNING: Keyword \"scale_min_short\" not found.\n         Default value for Smin = 0.0.\nWARNING: Keyword \"scale_max_short\" not found.\n         Default value for Smax = 1.0.\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: nnp-data/scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  0.00E+00  1.68E-01  5.14E-02  0.00E+00  5.94E+00  0.00  1.00 3\n   2  3.04E-01  4.17E-01  3.46E-01  0.00E+00  8.85E+00  0.00  1.00 3\n   3  0.00E+00  1.59E-01  4.77E-02  0.00E+00  6.27E+00  0.00  1.00 3\n   4  0.00E+00  1.52E-01  4.48E-02  0.00E+00  6.56E+00  0.00  1.00 3\n   5  2.70E-01  3.77E-01  3.12E-01  0.00E+00  9.35E+00  0.00  1.00 3\n   6  0.00E+00  1.43E-01  4.10E-02  0.00E+00  7.00E+00  0.00  1.00 3\n   7  0.00E+00  1.33E-01  3.71E-02  0.00E+00  7.53E+00  0.00  1.00 3\n   8  2.36E-01  3.37E-01  2.78E-01  0.00E+00  9.97E+00  0.00  1.00 3\n   9  0.00E+00  1.22E-01  3.31E-02  0.00E+00  8.18E+00  0.00  1.00 3\n  10  1.94E-01  2.86E-01  2.36E-01  0.00E+00  1.09E+01  0.00  1.00 3\n  11  1.46E-01  2.31E-01  1.88E-01  0.00E+00  1.18E+01  0.00  1.00 3\n  12  9.43E-02  1.67E-01  1.33E-01  0.00E+00  1.37E+01  0.00  1.00 3\n  13  0.00E+00  3.94E-03  7.66E-04  0.00E+00  2.54E+02  0.00  1.00 3\n  14  0.00E+00  2.18E-03  3.95E-04  0.00E+00  4.59E+02  0.00  1.00 3\n  15  0.00E+00  2.26E-02  6.69E-03  0.00E+00  4.42E+01  0.00  1.00 3\n  16  6.80E-03  1.48E-02  9.85E-03  0.00E+00  1.25E+02  0.00  1.00 3\n  17  0.00E+00  7.54E-04  1.18E-04  0.00E+00  1.33E+03  0.00  1.00 3\n  18  0.00E+00  3.07E-04  3.12E-05  0.00E+00  3.26E+03  0.00  1.00 3\n  19  0.00E+00  2.02E-02  6.04E-03  0.00E+00  4.96E+01  0.00  1.00 3\n  20  6.45E-03  1.30E-02  9.49E-03  0.00E+00  1.53E+02  0.00  1.00 3\n  21  0.00E+00  1.67E-02  5.00E-03  0.00E+00  5.97E+01  0.00  1.00 3\n  22  5.80E-03  1.11E-02  8.84E-03  0.00E+00  1.88E+02  0.00  1.00 3\n  23  0.00E+00  1.27E-02  3.57E-03  0.00E+00  7.90E+01  0.00  1.00 3\n  24  4.42E-03  1.10E-02  7.82E-03  0.00E+00  1.51E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element  C :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  0.00E+00  5.28E-01  8.65E-02  0.00E+00  1.89E+00  0.00  1.00 3\n   2  2.44E-01  5.76E-01  4.78E-01  0.00E+00  3.00E+00  0.00  1.00 3\n   3  2.20E-01  5.27E-01  4.38E-01  0.00E+00  3.26E+00  0.00  1.00 3\n   4  0.00E+00  5.04E-01  7.81E-02  0.00E+00  1.99E+00  0.00  1.00 3\n   5  1.95E-01  4.73E-01  3.93E-01  0.00E+00  3.59E+00  0.00  1.00 3\n   6  0.00E+00  4.75E-01  6.95E-02  0.00E+00  2.11E+00  0.00  1.00 3\n   7  1.66E-01  4.12E-01  3.41E-01  0.00E+00  4.07E+00  0.00  1.00 3\n   8  0.00E+00  4.33E-01  5.90E-02  0.00E+00  2.31E+00  0.00  1.00 3\n   9  1.36E-01  3.48E-01  2.86E-01  0.00E+00  4.72E+00  0.00  1.00 3\n  10  0.00E+00  3.76E-01  4.70E-02  0.00E+00  2.66E+00  0.00  1.00 3\n  11  1.02E-01  2.73E-01  2.22E-01  0.00E+00  5.83E+00  0.00  1.00 3\n  12  0.00E+00  2.93E-01  3.33E-02  0.00E+00  3.41E+00  0.00  1.00 3\n  13  0.00E+00  1.53E-02  6.08E-04  0.00E+00  6.55E+01  0.00  1.00 3\n  14  0.00E+00  2.04E-02  2.32E-03  0.00E+00  4.91E+01  0.00  1.00 3\n  15  0.00E+00  6.66E-03  3.99E-03  0.00E+00  1.50E+02  0.00  1.00 3\n  16  0.00E+00  9.28E-03  3.24E-04  0.00E+00  1.08E+02  0.00  1.00 3\n  17  0.00E+00  2.50E-02  2.80E-03  0.00E+00  4.00E+01  0.00  1.00 3\n  18  3.52E-03  1.25E-02  8.03E-03  0.00E+00  1.11E+02  0.00  1.00 3\n  19  0.00E+00  1.19E-02  4.30E-04  0.00E+00  8.39E+01  0.00  1.00 3\n  20  0.00E+00  1.56E-02  2.02E-03  0.00E+00  6.43E+01  0.00  1.00 3\n  21  0.00E+00  6.52E-03  3.94E-03  0.00E+00  1.53E+02  0.00  1.00 3\n  22  0.00E+00  3.82E-03  1.46E-04  0.00E+00  2.62E+02  0.00  1.00 3\n  23  0.00E+00  2.34E-02  2.50E-03  0.00E+00  4.27E+01  0.00  1.00 3\n  24  3.51E-03  1.24E-02  7.98E-03  0.00E+00  1.12E+02  0.00  1.00 3\n  25  0.00E+00  8.68E-03  2.29E-04  0.00E+00  1.15E+02  0.00  1.00 3\n  26  0.00E+00  1.07E-02  1.70E-03  0.00E+00  9.33E+01  0.00  1.00 3\n  27  0.00E+00  6.38E-03  3.88E-03  0.00E+00  1.57E+02  0.00  1.00 3\n  28  0.00E+00  1.76E-03  6.00E-05  0.00E+00  5.69E+02  0.00  1.00 3\n  29  0.00E+00  2.11E-02  2.32E-03  0.00E+00  4.74E+01  0.00  1.00 3\n  30  3.50E-03  1.23E-02  7.95E-03  0.00E+00  1.13E+02  0.00  1.00 3\n  31  0.00E+00  4.70E-03  6.92E-05  0.00E+00  2.13E+02  0.00  1.00 3\n  32  0.00E+00  1.07E-02  1.36E-03  0.00E+00  9.34E+01  0.00  1.00 3\n  33  0.00E+00  6.34E-03  3.76E-03  0.00E+00  1.58E+02  0.00  1.00 3\n  34  0.00E+00  9.43E-04  2.30E-05  0.00E+00  1.06E+03  0.00  1.00 3\n  35  0.00E+00  1.71E-02  2.11E-03  0.00E+00  5.84E+01  0.00  1.00 3\n  36  3.48E-03  1.22E-02  7.88E-03  0.00E+00  1.15E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 1\nWrite extrapolation warnings immediately to stderr: 0\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORK WEIGHTS *********************************************\n\nElectronegativity weight file name format: nnp-data/weightse.%03zu.data\nSetting weights for element  H from file: nnp-data/weightse.001.data\nSetting weights for element  C from file: nnp-data/weightse.006.data\nShort range weight file name format: nnp-data/weights.%03zu.data\nSetting weights for element  H from file: nnp-data/weights.001.data\nSetting weights for element  C from file: nnp-data/weights.006.data\n*******************************************************************************\n\n*** SETUP: LAMMPS INTERFACE ***************************************************\n\nIndividual extrapolation warnings will not be shown.\nExtrapolation warning summary will be shown every 10 timesteps.\nThe simulation will be stopped when 100 extrapolation warnings are exceeded.\nExtrapolation warnings are accumulated over all time steps.\n-------------------------------------------------------------------------------\nCAUTION: If the LAMMPS unit system differs from the one used\n         during NN training, appropriate conversion factors\n         must be provided (see keywords cflength and cfenergy).\n\nLength unit conversion factor:   1.0000000000000000E+00\nEnergy unit conversion factor:   1.0000000000000000E+00\n\nChecking consistency of cutoff radii (in LAMMPS units):\nLAMMPS Cutoff (via pair_coeff)  :   8.010E+00\nMaximum symmetry function cutoff:   8.000E+00\nCutoff radii are consistent.\n-------------------------------------------------------------------------------\nElement mapping string from LAMMPS to n2p2: \"1:H,2:C\"\n\nCAUTION: Please ensure that this mapping between LAMMPS\n         atom types and NNP elements is consistent:\n\n---------------------------\nLAMMPS type  |  NNP element\n---------------------------\n          1 <->  H (  1)\n          2 <->  C (  6)\n---------------------------\n\nNNP setup for LAMMPS completed.\n*******************************************************************************\nNeighbor list info ...\n  update every 1 steps, delay 10 steps, check yes\n  max neighbors/atom: 2000, page size: 100000\n  master list distance cutoff = 10.01\n  ghost atom cutoff = 10.01\n  binsize = 5.005, bins = 6 1 1\n  1 neighbor lists, perpetual/occasional/extra = 1 0 0\n  (1) pair nnp, perpetual\n      attributes: full, newton on\n      pair build: full/bin/atomonly\n      stencil: full/bin/3d\n      bin: standard\nWARNING: Proc sub-domain size < neighbor skin, could lead to lost atoms (../domain.cpp:963)\nAtom     0 ( C) chi:  -1.46678106E-01\nAtom     1 ( C) chi:  -1.62293124E-01\nAtom     2 ( H) chi:  -2.28364821E-01\nAtom     3 ( C) chi:  -1.49337351E-01\nAtom     4 ( C) chi:  -1.48569008E-01\nAtom     5 ( C) chi:  -1.50037876E-01\nAtom     6 ( C) chi:  -1.49461645E-01\nAtom     7 ( C) chi:  -1.49033407E-01\nAtom     8 ( C) chi:  -1.48516909E-01\nAtom     9 ( C) chi:  -1.46830562E-01\nAtom    10 ( C) chi:  -1.60724572E-01\nAtom    11 ( H) chi:  -2.25977980E-01\nSolve relative error:             -NAN\nAtom     0 ( C) q:             -NAN\nAtom     1 ( C) q:             -NAN\nAtom     2 ( H) q:             -NAN\nAtom     3 ( C) q:             -NAN\nAtom     4 ( C) q:             -NAN\nAtom     5 ( C) q:             -NAN\nAtom     6 ( C) q:             -NAN\nAtom     7 ( C) q:             -NAN\nAtom     8 ( C) q:             -NAN\nAtom     9 ( C) q:             -NAN\nAtom    10 ( C) q:             -NAN\nAtom    11 ( H) q:             -NAN\nTotal charge:             -NAN (ref:   0.00000000E+00)\nElectrostatic energy:             -NAN\nAtom     0 ( C) energy:             -NAN\nAtom     1 ( C) energy:             -NAN\nAtom     2 ( H) energy:             -NAN\nAtom     3 ( C) energy:             -NAN\nAtom     4 ( C) energy:             -NAN\nAtom     5 ( C) energy:             -NAN\nAtom     6 ( C) energy:             -NAN\nAtom     7 ( C) energy:             -NAN\nAtom     8 ( C) energy:             -NAN\nAtom     9 ( C) energy:             -NAN\nAtom    10 ( C) energy:             -NAN\nAtom    11 ( H) energy:             -NAN\n### NNP EW SUMMARY ### TS:          0 EW          0 EWPERSTEP  0.000E+00\nPer MPI rank memory allocation (min/avg/max) = 3.063 | 3.063 | 3.063 Mbytes\nStep Temp E_pair E_mol TotEng Press Volume \n       0            0         -nan            0         -nan            0    72.695271 \nAtom     0 ( C) chi:  -1.46678106E-01\nAtom     1 ( C) chi:  -1.62293124E-01\nAtom     2 ( H) chi:  -2.28364821E-01\nAtom     3 ( C) chi:  -1.49337351E-01\nAtom     4 ( C) chi:  -1.48569008E-01\nAtom     5 ( C) chi:  -1.50037876E-01\nAtom     6 ( C) chi:  -1.49461645E-01\nAtom     7 ( C) chi:  -1.49033407E-01\nAtom     8 ( C) chi:  -1.48516909E-01\nAtom     9 ( C) chi:  -1.46830562E-01\nAtom    10 ( C) chi:  -1.60724572E-01\nAtom    11 ( H) chi:  -2.25977980E-01\nSolve relative error:             -NAN\nAtom     0 ( C) q:             -NAN\nAtom     1 ( C) q:             -NAN\nAtom     2 ( H) q:             -NAN\nAtom     3 ( C) q:             -NAN\nAtom     4 ( C) q:             -NAN\nAtom     5 ( C) q:             -NAN\nAtom     6 ( C) q:             -NAN\nAtom     7 ( C) q:             -NAN\nAtom     8 ( C) q:             -NAN\nAtom     9 ( C) q:             -NAN\nAtom    10 ( C) q:             -NAN\nAtom    11 ( H) q:             -NAN\nTotal charge:             -NAN (ref:   0.00000000E+00)\nElectrostatic energy:             -NAN\nAtom     0 ( C) energy:             -NAN\nAtom     1 ( C) energy:             -NAN\nAtom     2 ( H) energy:             -NAN\nAtom     3 ( C) energy:             -NAN\nAtom     4 ( C) energy:             -NAN\nAtom     5 ( C) energy:             -NAN\nAtom     6 ( C) energy:             -NAN\nAtom     7 ( C) energy:             -NAN\nAtom     8 ( C) energy:             -NAN\nAtom     9 ( C) energy:             -NAN\nAtom    10 ( C) energy:             -NAN\nAtom    11 ( H) energy:             -NAN\n       1            0         -nan            0         -nan            0    72.695271 \nAtom     0 ( C) chi:  -1.46678106E-01\nAtom     1 ( C) chi:  -1.62293124E-01\nAtom     2 ( H) chi:  -2.28364821E-01\nAtom     3 ( C) chi:  -1.49337351E-01\nAtom     4 ( C) chi:  -1.48569008E-01\nAtom     5 ( C) chi:  -1.50037876E-01\nAtom     6 ( C) chi:  -1.49461645E-01\nAtom     7 ( C) chi:  -1.49033407E-01\nAtom     8 ( C) chi:  -1.48516909E-01\nAtom     9 ( C) chi:  -1.46830562E-01\nAtom    10 ( C) chi:  -1.60724572E-01\nAtom    11 ( H) chi:  -2.25977980E-01\nSolve relative error:             -NAN\nAtom     0 ( C) q:             -NAN\nAtom     1 ( C) q:             -NAN\nAtom     2 ( H) q:             -NAN\nAtom     3 ( C) q:             -NAN\nAtom     4 ( C) q:             -NAN\nAtom     5 ( C) q:             -NAN\nAtom     6 ( C) q:             -NAN\nAtom     7 ( C) q:             -NAN\nAtom     8 ( C) q:             -NAN\nAtom     9 ( C) q:             -NAN\nAtom    10 ( C) q:             -NAN\nAtom    11 ( H) q:             -NAN\nTotal charge:             -NAN (ref:   0.00000000E+00)\nElectrostatic energy:             -NAN\nAtom     0 ( C) energy:             -NAN\nAtom     1 ( C) energy:             -NAN\nAtom     2 ( H) energy:             -NAN\nAtom     3 ( C) energy:             -NAN\nAtom     4 ( C) energy:             -NAN\nAtom     5 ( C) energy:             -NAN\nAtom     6 ( C) energy:             -NAN\nAtom     7 ( C) energy:             -NAN\nAtom     8 ( C) energy:             -NAN\nAtom     9 ( C) energy:             -NAN\nAtom    10 ( C) energy:             -NAN\nAtom    11 ( H) energy:             -NAN\n       2            0         -nan            0         -nan            0    72.695271 \nAtom     0 ( C) chi:  -1.46678106E-01\nAtom     1 ( C) chi:  -1.62293124E-01\nAtom     2 ( H) chi:  -2.28364821E-01\nAtom     3 ( C) chi:  -1.49337351E-01\nAtom     4 ( C) chi:  -1.48569008E-01\nAtom     5 ( C) chi:  -1.50037876E-01\nAtom     6 ( C) chi:  -1.49461645E-01\nAtom     7 ( C) chi:  -1.49033407E-01\nAtom     8 ( C) chi:  -1.48516909E-01\nAtom     9 ( C) chi:  -1.46830562E-01\nAtom    10 ( C) chi:  -1.60724572E-01\nAtom    11 ( H) chi:  -2.25977980E-01\nSolve relative error:             -NAN\nAtom     0 ( C) q:             -NAN\nAtom     1 ( C) q:             -NAN\nAtom     2 ( H) q:             -NAN\nAtom     3 ( C) q:             -NAN\nAtom     4 ( C) q:             -NAN\nAtom     5 ( C) q:             -NAN\nAtom     6 ( C) q:             -NAN\nAtom     7 ( C) q:             -NAN\nAtom     8 ( C) q:             -NAN\nAtom     9 ( C) q:             -NAN\nAtom    10 ( C) q:             -NAN\nAtom    11 ( H) q:             -NAN\nTotal charge:             -NAN (ref:   0.00000000E+00)\nElectrostatic energy:             -NAN\nAtom     0 ( C) energy:             -NAN\nAtom     1 ( C) energy:             -NAN\nAtom     2 ( H) energy:             -NAN\nAtom     3 ( C) energy:             -NAN\nAtom     4 ( C) energy:             -NAN\nAtom     5 ( C) energy:             -NAN\nAtom     6 ( C) energy:             -NAN\nAtom     7 ( C) energy:             -NAN\nAtom     8 ( C) energy:             -NAN\nAtom     9 ( C) energy:             -NAN\nAtom    10 ( C) energy:             -NAN\nAtom    11 ( H) energy:             -NAN\n       3            0         -nan            0         -nan            0    72.695271 \nAtom     0 ( C) chi:  -1.46678106E-01\nAtom     1 ( C) chi:  -1.62293124E-01\nAtom     2 ( H) chi:  -2.28364821E-01\nAtom     3 ( C) chi:  -1.49337351E-01\nAtom     4 ( C) chi:  -1.48569008E-01\nAtom     5 ( C) chi:  -1.50037876E-01\nAtom     6 ( C) chi:  -1.49461645E-01\nAtom     7 ( C) chi:  -1.49033407E-01\nAtom     8 ( C) chi:  -1.48516909E-01\nAtom     9 ( C) chi:  -1.46830562E-01\nAtom    10 ( C) chi:  -1.60724572E-01\nAtom    11 ( H) chi:  -2.25977980E-01\nSolve relative error:             -NAN\nAtom     0 ( C) q:             -NAN\nAtom     1 ( C) q:             -NAN\nAtom     2 ( H) q:             -NAN\nAtom     3 ( C) q:             -NAN\nAtom     4 ( C) q:             -NAN\nAtom     5 ( C) q:             -NAN\nAtom     6 ( C) q:             -NAN\nAtom     7 ( C) q:             -NAN\nAtom     8 ( C) q:             -NAN\nAtom     9 ( C) q:             -NAN\nAtom    10 ( C) q:             -NAN\nAtom    11 ( H) q:             -NAN\nTotal charge:             -NAN (ref:   0.00000000E+00)\nElectrostatic energy:             -NAN\nAtom     0 ( C) energy:             -NAN\nAtom     1 ( C) energy:             -NAN\nAtom     2 ( H) energy:             -NAN\nAtom     3 ( C) energy:             -NAN\nAtom     4 ( C) energy:             -NAN\nAtom     5 ( C) energy:             -NAN\nAtom     6 ( C) energy:             -NAN\nAtom     7 ( C) energy:             -NAN\nAtom     8 ( C) energy:             -NAN\nAtom     9 ( C) energy:             -NAN\nAtom    10 ( C) energy:             -NAN\nAtom    11 ( H) energy:             -NAN\n       4            0         -nan            0         -nan            0    72.695271 \nAtom     0 ( C) chi:  -1.46678106E-01\nAtom     1 ( C) chi:  -1.62293124E-01\nAtom     2 ( H) chi:  -2.28364821E-01\nAtom     3 ( C) chi:  -1.49337351E-01\nAtom     4 ( C) chi:  -1.48569008E-01\nAtom     5 ( C) chi:  -1.50037876E-01\nAtom     6 ( C) chi:  -1.49461645E-01\nAtom     7 ( C) chi:  -1.49033407E-01\nAtom     8 ( C) chi:  -1.48516909E-01\nAtom     9 ( C) chi:  -1.46830562E-01\nAtom    10 ( C) chi:  -1.60724572E-01\nAtom    11 ( H) chi:  -2.25977980E-01\nSolve relative error:             -NAN\nAtom     0 ( C) q:             -NAN\nAtom     1 ( C) q:             -NAN\nAtom     2 ( H) q:             -NAN\nAtom     3 ( C) q:             -NAN\nAtom     4 ( C) q:             -NAN\nAtom     5 ( C) q:             -NAN\nAtom     6 ( C) q:             -NAN\nAtom     7 ( C) q:             -NAN\nAtom     8 ( C) q:             -NAN\nAtom     9 ( C) q:             -NAN\nAtom    10 ( C) q:             -NAN\nAtom    11 ( H) q:             -NAN\nTotal charge:             -NAN (ref:   0.00000000E+00)\nElectrostatic energy:             -NAN\nAtom     0 ( C) energy:             -NAN\nAtom     1 ( C) energy:             -NAN\nAtom     2 ( H) energy:             -NAN\nAtom     3 ( C) energy:             -NAN\nAtom     4 ( C) energy:             -NAN\nAtom     5 ( C) energy:             -NAN\nAtom     6 ( C) energy:             -NAN\nAtom     7 ( C) energy:             -NAN\nAtom     8 ( C) energy:             -NAN\nAtom     9 ( C) energy:             -NAN\nAtom    10 ( C) energy:             -NAN\nAtom    11 ( H) energy:             -NAN\n       5            0         -nan            0         -nan            0    72.695271 \nLoop time of 0.00210395 on 1 procs for 5 steps with 12 atoms\n\nPerformance: 102.664 ns/day, 0.234 hours/ns, 2376.482 timesteps/s\n29.9% CPU use with 1 MPI tasks x no OpenMP threads\n\nMPI task timing breakdown:\nSection |  min time  |  avg time  |  max time  |%varavg| %total\n---------------------------------------------------------------\nPair    | 0.0019988  | 0.0019988  | 0.0019988  |   0.0 | 95.00\nNeigh   | 0          | 0          | 0          |   0.0 |  0.00\nComm    | 4.048e-06  | 4.048e-06  | 4.048e-06  |   0.0 |  0.19\nOutput  | 7.6602e-05 | 7.6602e-05 | 7.6602e-05 |   0.0 |  3.64\nModify  | 6.668e-06  | 6.668e-06  | 6.668e-06  |   0.0 |  0.32\nOther   |            | 1.783e-05  |            |       |  0.85\n\nNlocal:        12.0000 ave          12 max          12 min\nHistogram: 1 0 0 0 0 0 0 0 0 0\nNghost:        0.00000 ave           0 max           0 min\nHistogram: 1 0 0 0 0 0 0 0 0 0\nNeighs:        0.00000 ave           0 max           0 min\nHistogram: 1 0 0 0 0 0 0 0 0 0\nFullNghs:      76.0000 ave          76 max          76 min\nHistogram: 1 0 0 0 0 0 0 0 0 0\n\nTotal # of neighbors = 76\nAve neighs/atom = 6.3333333\nNeighbor list builds = 0\nDangerous builds = 0\nTotal wall time: 0:00:00\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/md-external.lmp",
    "content": "###############################################################################\n# MD simulation for carbon chain\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"carbon-chain.data\"\n# Timesteps\nvariable numSteps        equal  5\nvariable dt              equal  0.0005\n# NN\nvariable nnpCutoff       equal  8.01\nvariable nnpDir          string \"nnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_C          equal  12.0107\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary s s s\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_H}\nmass 2 ${mass_C}\ntimestep ${dt}\nthermo 1\n\n###############################################################################\n# NN\n###############################################################################\npair_style nnp/external \"H C\" dir ${nnpDir} command \"RuNNer-gaussian.x\" cflength 1.0 cfenergy 1.0\n#pair_style nnp/external \"H C\" dir ${nnpDir} command \"nnp-predict 0\" cflength 1.0 cfenergy 1.0\npair_coeff * * ${nnpCutoff}\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\n#dump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/md.lmp",
    "content": "###############################################################################\n# MD simulation for carbon chain\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"carbon-chain.data\"\n# Timesteps\nvariable numSteps        equal  5\nvariable dt              equal  0.0005\n# NN\nvariable nnpCutoff       equal  8.01\nvariable nnpDir          string \"nnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_C          equal  12.0107\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary s s s\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_H}\nmass 2 ${mass_C}\ntimestep ${dt}\nthermo 1\n\n###############################################################################\n# NN\n###############################################################################\npair_style nnp dir ${nnpDir} showew no showewsum 10 resetew no maxew 100 cflength 1.0 cfenergy 1.0 emap \"1:H,2:C\"\npair_coeff * * ${nnpCutoff}\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\n#dump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/nnp-data/hardness.001.data",
    "content": "      0.0088953312\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/nnp-data/hardness.006.data",
    "content": "      0.0661189426\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/nnp-data/input.nn",
    "content": "## #############################################################\n### This is the input file for RuNNer \n### #############################################################\n### General remarks: \n### - commands can be switched off by using the # character at the BEGINNING of the line\n### - the input file can be structured by blank lines and comment lines\n### - the order of the keywords is arbitrary\n### - if keywords are missing, default values will be used and written to runner.out\n### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message \n\n### THIS INPUT.NN IS AN EXAMPLE, IT IS NOT A REALISTIC CASE\n### It contains only a subset of all keywords\n\n########################################################################################################################\n### general keywords\n########################################################################################################################\nuse_electrostatics\nuse_short_nn\nnnp_gen 4 # nnp_type_gen --> nnp_gen \nrunner_mode 3\nparallel_mode 1                         \nnumber_of_elements 2                  \nelements  C H                          \nrandom_seed 10                         \nrandom_number_type 5                      \nremove_atom_energies                     \natom_energy H -0.458907306351869\natom_energy C -37.748111931202914\ninitial_hardness H 10.0 ## fixed_atomhardness--> initial_hardness \ninitial_hardness C 10.0 \nfixed_gausswidth H 0.585815056466\nfixed_gausswidth C 1.379499971678\nenergy_threshold 100.0d0              \nbond_threshold 0.4d0                 \newald_prec 1.0e-6 # for optimal combination of ewald parameters\nscreen_electrostatics 4.8 8.0\n########################################################################################################################\n### NN structure of the electrostatic-range NN  \n########################################################################################################################\nglobal_hidden_layers_electrostatic 2              \nglobal_nodes_electrostatic 15 15                 \nglobal_activation_electrostatic t t l            \nglobal_hidden_layers_short 2              \nglobal_nodes_short 10 10                 \nglobal_activation_short t t l            \n## element_hidden_layers_electrostatic needs to take care !!! should check the output  \n########################################################################################################################\n### symmetry function generation ( mode 1): \n########################################################################################################################\ntest_fraction 0.1      \n\n########################################################################################################################\n### symmetry function definitions (all modes): \n########################################################################################################################\ncutoff_type 2\n\n\n# radial H H\nsymfunction H  2  H 0.000000      0.000000      8.000000  \nsymfunction H  2  H 0.006000      0.000000      8.000000  \nsymfunction H  2  H 0.011000      0.000000      8.000000  \nsymfunction H  2  H 0.018000      0.000000      8.000000  \nsymfunction H  2  H 0.026000      0.000000      8.000000  \nsymfunction H  2  H 0.035000      0.000000      8.000000  \n\n#radial C H\nsymfunction C  2  H 0.000000      0.000000      8.000000  \nsymfunction C  2  H 0.013000      0.000000      8.000000  \nsymfunction C  2  H 0.029000      0.000000      8.000000  \nsymfunction C  2  H 0.054000      0.000000      8.000000  \nsymfunction C  2  H 0.093000      0.000000      8.000000  \nsymfunction C  2  H 0.161000      0.000000      8.000000  \n\nsymfunction H  2  C 0.000000      0.000000      8.000000  \nsymfunction H  2  C 0.013000      0.000000      8.000000  \nsymfunction H  2  C 0.029000      0.000000      8.000000  \nsymfunction H  2  C 0.054000      0.000000      8.000000  \nsymfunction H  2  C 0.093000      0.000000      8.000000  \nsymfunction H  2  C 0.161000      0.000000      8.000000  \n\n# radial C C \nsymfunction C  2  C 0.000000      0.000000      8.000000\nsymfunction C  2  C 0.010000      0.000000      8.000000\nsymfunction C  2  C 0.023000      0.000000      8.000000\nsymfunction C  2  C 0.041000      0.000000      8.000000\nsymfunction C  2  C 0.065000      0.000000      8.000000\nsymfunction C  2  C 0.103000      0.000000      8.000000\n\n\n#\n# angular\n\nsymfunction C 3 C C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction C 3 H H 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction C 3 C H 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\n\nsymfunction H 3 C C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 C C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 C C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction H 3 H C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 H C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 H C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\n\n########################################################################################################################\n### fitting (mode 2):general inputs for electrostatic range AND electrostatic part:\n########################################################################################################################\nepochs 10                          \npoints_in_memory 500                \nmix_all_points                       \nscale_symmetry_functions             \ncenter_symmetry_functions             \nfitting_unit  eV                      \n########################################################################################################################\n### fitting options ( mode 2): electrostatic range part only:\n########################################################################################################################\noptmode_short_energy 1                 \noptmode_short_force 1                   \nshort_energy_error_threshold 0.8\t \nshort_force_error_threshold 0.8\t\t \nkalman_lambda_charge 0.98000                \nkalman_nue_charge 0.99870                   \nkalman_lambda_short 0.98000                \nkalman_nue_short 0.99870                   \n#use_old_weights_electrostatic               \n#force_update_scaling -1.0d0          \n#electrostatic_energy_group 1         \n#electrostatic_energy_fraction 1.00           \n#electrostatic_force_group 1                 \n\nshort_force_fraction 0.025            \nuse_short_forces                    \nweights_min -1.0                 \nweights_max 1.0                  \nprecondition_weights            \nrepeated_energy_update          \nnguyen_widrow_weights_short     \nregularize_fit_param 0.00001 ## 4G cases L2 regularization \n########################################################################################################################\n### output options for mode 2 (fitting):  \n########################################################################################################################\nwrite_trainpoints              \nwrite_trainforces      \n#write_traincharges\n########################################################################################################################\n### output options for mode 3 (prediction):  \n########################################################################################################################\ncalculate_forces     \n#calculate_stress       \n\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/nnp-data/scaling.data",
    "content": "   1    1        0.000000000       0.168474325       0.051436597\n   1    2        0.304058579       0.417104776       0.345915594\n   1    3        0.000000000       0.159465228       0.047693255\n   1    4        0.000000000       0.152326768       0.044784312\n   1    5        0.270367239       0.377289298       0.312242885\n   1    6        0.000000000       0.142866546       0.041009575\n   1    7        0.000000000       0.132772126       0.037086368\n   1    8        0.236241291       0.336573119       0.278003131\n   1    9        0.000000000       0.122265892       0.033122717\n   1   10        0.194043783       0.286076543       0.235857711\n   1   11        0.146413959       0.230979612       0.188000406\n   1   12        0.094328785       0.167444236       0.133300930\n   1   13        0.000000000       0.003940598       0.000766277\n   1   14        0.000000000       0.002179848       0.000395242\n   1   15        0.000000000       0.022615147       0.006688070\n   1   16        0.006799063       0.014786064       0.009854503\n   1   17        0.000000000       0.000754211       0.000118471\n   1   18        0.000000000       0.000307111       0.000031177\n   1   19        0.000000000       0.020171446       0.006040265\n   1   20        0.006447566       0.012997039       0.009490438\n   1   21        0.000000000       0.016749223       0.005002441\n   1   22        0.005799086       0.011113091       0.008844953\n   1   23        0.000000000       0.012662314       0.003565243\n   1   24        0.004417978       0.011019545       0.007821957\n   2    1        0.000000000       0.528085920       0.086499956\n   2    2        0.243551003       0.576397651       0.478191952\n   2    3        0.220486953       0.527469369       0.437635603\n   2    4        0.000000000       0.503534550       0.078079729\n   2    5        0.195097154       0.473305655       0.392510705\n   2    6        0.000000000       0.474879557       0.069517706\n   2    7        0.166254512       0.411783730       0.340934855\n   2    8        0.000000000       0.433337270       0.058978785\n   2    9        0.136220939       0.347964660       0.286400724\n   2   10        0.000000000       0.375671652       0.047011546\n   2   11        0.101581283       0.273092311       0.221977741\n   2   12        0.000000000       0.292877983       0.033333347\n   2   13        0.000000000       0.015267809       0.000607918\n   2   14        0.000000000       0.020367325       0.002323101\n   2   15        0.000000000       0.006658033       0.003990472\n   2   16        0.000000000       0.009284484       0.000324103\n   2   17        0.000000000       0.024985840       0.002803020\n   2   18        0.003522361       0.012523471       0.008029970\n   2   19        0.000000000       0.011921850       0.000429967\n   2   20        0.000000000       0.015558424       0.002023934\n   2   21        0.000000000       0.006518589       0.003941639\n   2   22        0.000000000       0.003823383       0.000146152\n   2   23        0.000000000       0.023446294       0.002503853\n   2   24        0.003512986       0.012433317       0.007981137\n   2   25        0.000000000       0.008678726       0.000229107\n   2   26        0.000000000       0.010714201       0.001695750\n   2   27        0.000000000       0.006384431       0.003878387\n   2   28        0.000000000       0.001758371       0.000060041\n   2   29        0.000000000       0.021095757       0.002319082\n   2   30        0.003504699       0.012339772       0.007947861\n   2   31        0.000000000       0.004699984       0.000069193\n   2   32        0.000000000       0.010701233       0.001357400\n   2   33        0.000000000       0.006338867       0.003757820\n   2   34        0.000000000       0.000942648       0.000023014\n   2   35        0.000000000       0.017137757       0.002111679\n   2   36        0.003476868       0.012155470       0.007883155\n       -0.2691374625       -0.2381480047\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/nnp-data/weights.001.data",
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  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/nnp-data/weights.006.data",
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  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/lammps-nnp/nnp-data/weightse.006.data",
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0.9514517105\n     -0.5609427673\n     -0.2681244852\n     -0.2380255405\n     -0.6299317154\n     -0.0444312503\n      0.6723833199\n     -0.1755227672\n      0.0214165418\n     -0.5909926702\n      0.1439287461\n     -0.4741347554\n     -0.7723338598\n     -0.2175892032\n     -0.1319381853\n      0.8237379200\n     -0.6223845297\n      0.0655192356\n      0.0791274955\n      0.0241765665\n     -0.2064087004\n     -0.3940068910\n     -0.5444628729\n     -0.1359227526\n      0.3800822323\n      0.5993674359\n     -0.7269496390\n      0.8367187022\n      0.1374179268\n      0.7344415866\n     -0.2551345486\n     -0.1743276516\n      0.9910772307\n      0.3316258177\n      1.2238138235\n     -0.4179177766\n     -0.2008342288\n      0.6387734163\n     -0.1928348474\n      0.6881137644\n     -0.7000929936\n      0.0735157620\n     -0.3324781162\n      0.0420307653\n      0.9959977273\n     -0.7450342041\n     -0.8529960883\n      0.2969544922\n     -0.0602600691\n      0.2766838148\n     -0.1003145324\n      0.1700644349\n     -0.0641415901\n     -0.9352716760\n     -0.6402313900\n     -0.4651572692\n      0.7722681957\n      1.0887719406\n     -0.4964838793\n      0.7038089902\n     -0.7986021023\n      0.5782880196\n     -0.6165892783\n     -1.0079411424\n     -0.9160050730\n      0.7999285374\n      0.1367149508\n     -0.0647141492\n      0.7688656893\n      0.2878636341\n     -0.3722237651\n      0.1111473417\n      0.3828950059\n     -0.4378732916\n     -0.1316414863\n     -0.1096866025\n     -0.3705437296\n     -0.4851148132\n      0.6206502475\n      0.7147946611\n     -0.0178212911\n      0.3792484954\n     -0.2507005539\n      1.0659073038\n     -0.2027245679\n      0.2017199777\n      0.3003215698\n     -0.8389435343\n     -0.6369460665\n     -0.0933321836\n      0.5776260865\n     -0.5767028069\n     -0.4353569523\n     -0.7078700015\n     -0.4528725887\n      0.4402600593\n      0.0847773972\n      0.2788315779\n      0.2652386196\n     -0.5934642654\n      0.0606796684\n     -0.0240946437\n     -0.5221134615\n     -0.2158837878\n     -0.1666201799\n      0.2831691942\n      0.1548712159\n      0.4069982742\n      0.0614233895\n      0.0076948724\n      0.1343740575\n     -0.1587786167\n     -0.2949905912\n      0.0568310441\n      0.2915891973\n      0.2089325098\n      0.0021438982\n      0.1311775629\n     -0.6705841369\n      0.7347319618\n     -0.1484791977\n     -0.2162294124\n      0.8309982253\n     -0.0401276045\n      0.8479086493\n     -0.2065159209\n      0.9296989088\n     -0.0481041026\n      0.5809043146\n      0.4089903880\n      0.2223221997\n      0.1160041545\n     -0.4602602639\n     -0.1334080950\n     -0.0435590321\n      1.0788682386\n      0.1605417540\n      0.4218863145\n     -0.3317259475\n      0.4283293595\n      0.0611642978\n      0.9183707139\n     -0.2723340672\n     -1.0920471036\n     -0.3713786255\n     -0.2472463119\n     -0.4721194768\n      1.4978735406\n      0.3286069439\n      0.0938603768\n      0.1690412455\n     -0.5012145404\n      0.6166936354\n     -0.8298359733\n     -0.6693731422\n      0.5221510234\n      0.4215053294\n      0.0656388111\n      0.4861742881\n     -0.0081073075\n     -0.4925803428\n     -0.6600221667\n      0.1272019508\n     -0.0090456956\n     -1.3715130022\n      0.3109905053\n      0.4535667158\n     -1.6915038027\n      0.8338429940\n      2.2347737978\n      0.0804225592\n     -0.0308499916\n     -0.1486614136\n      0.9753636261\n      0.3032806837\n      0.0604180499\n     -0.2851974368\n     -0.1318419288\n     -0.1369773622\n     -1.0050621724\n      0.4592854729\n     -0.5367611149\n     -0.7810309148\n     -0.9202002259\n      0.0669989367\n      1.7276884639\n     -0.9999769999\n      1.0285707457\n      1.1542196303\n     -0.6086259937\n     -0.0759605467\n     -0.9023685322\n     -0.1508870075\n      0.6164065665\n      0.3333376818\n     -0.7858766466\n      0.4294231053\n     -0.4407090829\n      0.7736383708\n     -0.2359834008\n     -0.0202907128\n     -0.2180730486\n     -0.6840055578\n     -0.8463543049\n     -0.1538054213\n      0.8565837683\n     -0.2703235873\n     -0.0508505534\n      0.0559036001\n     -1.2569307297\n      0.0145876741\n      0.3387996939\n      0.3199708674\n     -0.2029252897\n     -0.0472493730\n     -0.6309356950\n      0.8896411965\n     -2.0955514047\n      0.4279469201\n      0.0266378958\n      1.4070332400\n     -0.0294007300\n      0.3407484478\n     -0.8172902279\n      1.6487546807\n     -0.0623547386\n      0.3883346270\n      0.0784087968\n      0.5987994829\n     -2.0482785708\n     -0.0878347656\n     -1.5024420974\n      2.8311533001\n     -1.9208463310\n     -0.9728285530\n     -0.4000267303\n      0.0916188942\n      0.0652916261\n     -0.2063674689\n     -0.4998824884\n      0.5934900052\n     -0.3538291998\n     -0.2192364250\n      0.7330223549\n     -0.0143295732\n     -1.0152116046\n      0.4316079184\n     -2.2107091847\n     -2.7316551236\n     -0.6181078170\n     -2.3335805886\n     -0.2451520870\n     -0.3100282558\n      0.0797196058\n     -0.5008548511\n     -0.8840659238\n     -0.1130072915\n      0.2551511750\n     -0.3179275739\n      1.0384571273\n      0.6575601296\n      1.6034851298\n     -2.3886312909\n     -0.9339623524\n     -1.2643663283\n     -0.0148557048\n      0.1206068884\n      0.0133351930\n     -0.3060192388\n      1.2442941197\n      1.2913622498\n      0.4127824106\n     -0.0259057296\n     -0.6683841364\n     -0.7607917591\n     -1.5364039498\n     -2.0420547619\n      1.0021196401\n      0.6885654807\n      0.8722571125\n     -1.8557931911\n     -0.1943362643\n     -0.0334702134\n     -0.1250534993\n      0.7684573398\n     -0.6287528033\n     -0.1237433239\n      0.3552105233\n     -0.1326254090\n     -1.1625292734\n     -0.3730818618\n     -0.1193215635\n      5.2965831132\n     -0.4618024048\n     -0.0004434927\n      4.2724404576\n     -0.2706485705\n     -0.2992525783\n      0.4444540238\n      1.1950931653\n      0.2349044910\n     -0.1070516985\n      0.4369045762\n     -0.0444983410\n      0.2153442351\n     -1.1251010384\n     -1.4979626726\n     -0.5551913574\n     -2.0694528611\n      0.2606234991\n     -2.2022190083\n     -0.1144456894\n     -0.1258836280\n     -0.3684364718\n     -0.2583360506\n     -0.4544922852\n     -0.2618750396\n      0.2359057839\n      0.1613573769\n      0.9904412492\n     -0.1016524499\n     -1.0657100465\n      0.8605886894\n      0.1413029799\n     -0.1893761626\n     -3.7391061335\n      0.0036828432\n      0.3886376713\n     -0.6562280624\n      0.1083763220\n     -0.0391240429\n      0.2267509693\n     -0.2058136409\n     -0.1430979256\n      0.7009168993\n      0.4931955095\n      0.7863721995\n      0.2472528221\n     -1.2495204718\n      0.6875830102\n      1.9466142831\n      0.1023390652\n     -0.2558956548\n      0.2852365762\n      0.0029291118\n      0.9868865541\n      0.0403577509\n     -0.1047418136\n     -0.3488408483\n     -0.9674470264\n      0.1494635568\n      0.2065713356\n      2.3167621560\n     -0.4749087023\n      1.3388042843\n      2.6993169368\n      0.0429258126\n      0.0103415735\n      0.2764993198\n      0.6813767545\n     -0.4331521111\n      0.2551211682\n     -0.2364161739\n     -0.3079983949\n      0.6467916994\n     -1.5260399719\n      0.6265168530\n     -0.8105200453\n     -0.3736370520\n      0.3084884217\n     -0.2992212659\n     -0.0273815678\n      0.1049134175\n      0.2536801614\n     -1.1511637867\n     -0.9000689224\n      0.1443339389\n      0.0620394402\n      1.9992994309\n      0.7843928157\n      1.4391271323\n     -0.3321939402\n     -2.4382905743\n     -1.6734428117\n     -0.9249641999\n     -1.3018867082\n      0.0152212636\n      0.3104785525\n     -0.2492140028\n     -0.8955123746\n      0.9869474327\n      0.0822669444\n     -0.1830559445\n     -1.1230333927\n     -0.1385515232\n     -0.3696105195\n      0.1082286260\n      0.1748680549\n     -1.2177151081\n      0.1079492551\n     -0.2859594318\n     -0.3121904922\n      0.1034155480\n      0.1806808724\n     -0.2580117886\n      0.3535325828\n      0.0229540981\n      0.3238516401\n     -0.7821787424\n     -0.5357628124\n      1.2345527437\n      1.8953010665\n      0.3961253271\n     -0.4570288514\n      0.4972780485\n      1.5141288000\n      0.1366535654\n     -0.0558186183\n      0.5826411377\n     -0.1801513810\n      0.4953259346\n     -0.0545313333\n     -0.1340448904\n     -0.1234905918\n     -1.2417564423\n     -0.8220806959\n      0.1234736475\n     -0.3094409144\n      0.3831220587\n     -0.1464400551\n     -0.2343229869\n      0.0007787294\n     -0.4790095880\n      0.6993700632\n     -0.1998249300\n      0.2858428262\n     -0.2110018462\n      0.1624702703\n      0.6789582127\n     -0.4868270904\n     -0.2768406958\n     -0.7069002115\n     -0.6879166506\n     -2.0867370236\n     -0.7994656137\n      0.1719842944\n     -0.0000752220\n     -0.0003613176\n     -0.0029232214\n      0.0445647221\n      0.0222816566\n     -0.0003398342\n      0.0003305899\n     -0.0272082042\n     -0.0176071818\n      0.0295840498\n      0.0939072748\n     -0.0735707973\n      0.0340777246\n     -0.0573394490\n     -0.1135653336\n     -0.1319696539\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/nnp-predict/hardness.001.data",
    "content": "      0.0088953312\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/nnp-predict/hardness.006.data",
    "content": "      0.0661189426\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/nnp-predict/input.data",
    "content": "begin\natom 1.17284095486 -0.172504222684 -0.667448516865 C -0.00802366916667 0.0 0.0347925826351 -0.00110373556182 0.0172205087376\natom -1.1595434822 -0.350641000445 -0.467598107194 C -0.00855427916667 0.0 -0.0190916650141 0.00319122911054 0.00166842074686\natom 3.72594054969 -0.0837975179097 -0.229777168673 C -0.00986190916667 0.0 -0.0218470438236 -0.00628540399811 -0.0170756379211\natom -3.69146983116 -0.334172643167 -0.21088223315 C -0.0100583891667 0.0 -0.0301687534058 0.0106478678179 -0.00452518599678\natom 6.07758586771 -0.166745226042 -0.145024035228 C -0.00672012916667 0.0 0.00266924762633 -0.00156314063781 0.0115961079544\natom -6.06809789367 -0.00253733508489 -0.0705357610724 C -0.00417966916667 0.0 0.0380293993069 -0.012272279507 -0.00385017456324\natom 8.59164353464 -0.0806915075831 0.402236831619 C -0.0283825591667 0.0 0.0114358510185 0.0168883247486 -0.0145042007862\natom -8.60892564573 0.117192245354 0.0982851777904 C -0.0314335491667 0.0 -0.0313212312302 0.00897304604753 0.0196935694367\natom 10.8705405815 0.51581338865 0.435826522093 C -0.0539909791667 0.0 -0.0207616703214 -0.00491358425534 0.014173822701\natom -10.8879581104 0.411807821319 0.694948565342 C -0.0495567391667 0.0 0.0330796233985 -0.00720705271362 -0.0192967826535\natom 12.661965991 1.19502446714 1.1691448209 H 0.104980830833 0.0 -0.00448104672571 -0.00638001418343 -0.00747636563225\natom -12.9307322131 0.525058551796 0.728011456903 H 0.105781040833 0.0 0.00766470653545 2.474313253e-05 0.00237591797661\nenergy -381.611525444\ncharge  -0.0\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/nnp-predict/input.nn",
    "content": "## #############################################################\n### This is the input file for RuNNer \n### #############################################################\n### General remarks: \n### - commands can be switched off by using the # character at the BEGINNING of the line\n### - the input file can be structured by blank lines and comment lines\n### - the order of the keywords is arbitrary\n### - if keywords are missing, default values will be used and written to runner.out\n### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message \n\n### THIS INPUT.NN IS AN EXAMPLE, IT IS NOT A REALISTIC CASE\n### It contains only a subset of all keywords\n\n########################################################################################################################\n### general keywords\n########################################################################################################################\nuse_electrostatics\nuse_short_nn\nnnp_gen 4 # nnp_type_gen --> nnp_gen \nrunner_mode 3\nparallel_mode 1                         \nnumber_of_elements 2                  \nelements  C H                          \nrandom_seed 10                         \nrandom_number_type 5                      \nremove_atom_energies                     \natom_energy H -0.458907306351869\natom_energy C -37.748111931202914\ninitial_hardness H 10.0 ## fixed_atomhardness--> initial_hardness \ninitial_hardness C 10.0 \nfixed_gausswidth H 0.585815056466\nfixed_gausswidth C 1.379499971678\nenergy_threshold 100.0d0              \nbond_threshold 0.4d0                 \newald_prec 1.0e-6 # for optimal combination of ewald parameters\nscreen_electrostatics 4.8 8.0\n########################################################################################################################\n### NN structure of the electrostatic-range NN  \n########################################################################################################################\nglobal_hidden_layers_electrostatic 2              \nglobal_nodes_electrostatic 15 15                 \nglobal_activation_electrostatic t t l            \nglobal_hidden_layers_short 2              \nglobal_nodes_short 10 10                 \nglobal_activation_short t t l            \n## element_hidden_layers_electrostatic needs to take care !!! should check the output  \n########################################################################################################################\n### symmetry function generation ( mode 1): \n########################################################################################################################\ntest_fraction 0.1      \n\n########################################################################################################################\n### symmetry function definitions (all modes): \n########################################################################################################################\ncutoff_type 2\n\n\n# radial H H\nsymfunction H  2  H 0.000000      0.000000      8.000000  \nsymfunction H  2  H 0.006000      0.000000      8.000000  \nsymfunction H  2  H 0.011000      0.000000      8.000000  \nsymfunction H  2  H 0.018000      0.000000      8.000000  \nsymfunction H  2  H 0.026000      0.000000      8.000000  \nsymfunction H  2  H 0.035000      0.000000      8.000000  \n\n#radial C H\nsymfunction C  2  H 0.000000      0.000000      8.000000  \nsymfunction C  2  H 0.013000      0.000000      8.000000  \nsymfunction C  2  H 0.029000      0.000000      8.000000  \nsymfunction C  2  H 0.054000      0.000000      8.000000  \nsymfunction C  2  H 0.093000      0.000000      8.000000  \nsymfunction C  2  H 0.161000      0.000000      8.000000  \n\nsymfunction H  2  C 0.000000      0.000000      8.000000  \nsymfunction H  2  C 0.013000      0.000000      8.000000  \nsymfunction H  2  C 0.029000      0.000000      8.000000  \nsymfunction H  2  C 0.054000      0.000000      8.000000  \nsymfunction H  2  C 0.093000      0.000000      8.000000  \nsymfunction H  2  C 0.161000      0.000000      8.000000  \n\n# radial C C \nsymfunction C  2  C 0.000000      0.000000      8.000000\nsymfunction C  2  C 0.010000      0.000000      8.000000\nsymfunction C  2  C 0.023000      0.000000      8.000000\nsymfunction C  2  C 0.041000      0.000000      8.000000\nsymfunction C  2  C 0.065000      0.000000      8.000000\nsymfunction C  2  C 0.103000      0.000000      8.000000\n\n\n#\n# angular\n\nsymfunction C 3 C C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction C 3 H H 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction C 3 C H 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\n\nsymfunction H 3 C C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 C C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 C C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction H 3 H C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 H C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 H C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\n\n########################################################################################################################\n### fitting (mode 2):general inputs for electrostatic range AND electrostatic part:\n########################################################################################################################\nepochs 10                          \npoints_in_memory 500                \nmix_all_points                       \nscale_symmetry_functions             \ncenter_symmetry_functions             \nfitting_unit  eV                      \n########################################################################################################################\n### fitting options ( mode 2): electrostatic range part only:\n########################################################################################################################\noptmode_short_energy 1                 \noptmode_short_force 1                   \nshort_energy_error_threshold 0.8\t \nshort_force_error_threshold 0.8\t\t \nkalman_lambda_charge 0.98000                \nkalman_nue_charge 0.99870                   \nkalman_lambda_short 0.98000                \nkalman_nue_short 0.99870                   \n#use_old_weights_electrostatic               \n#force_update_scaling -1.0d0          \n#electrostatic_energy_group 1         \n#electrostatic_energy_fraction 1.00           \n#electrostatic_force_group 1                 \n\nshort_force_fraction 0.025            \nuse_short_forces                    \nweights_min -1.0                 \nweights_max 1.0                  \nprecondition_weights            \nrepeated_energy_update          \nnguyen_widrow_weights_short     \nregularize_fit_param 0.00001 ## 4G cases L2 regularization \n########################################################################################################################\n### output options for mode 2 (fitting):  \n########################################################################################################################\nwrite_trainpoints              \nwrite_trainforces      \n#write_traincharges\n########################################################################################################################\n### output options for mode 3 (prediction):  \n########################################################################################################################\ncalculate_forces     \n#calculate_stress       \n\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/nnp-predict/scaling.data",
    "content": "   1    1        0.000000000       0.168474325       0.051436597\n   1    2        0.304058579       0.417104776       0.345915594\n   1    3        0.000000000       0.159465228       0.047693255\n   1    4        0.000000000       0.152326768       0.044784312\n   1    5        0.270367239       0.377289298       0.312242885\n   1    6        0.000000000       0.142866546       0.041009575\n   1    7        0.000000000       0.132772126       0.037086368\n   1    8        0.236241291       0.336573119       0.278003131\n   1    9        0.000000000       0.122265892       0.033122717\n   1   10        0.194043783       0.286076543       0.235857711\n   1   11        0.146413959       0.230979612       0.188000406\n   1   12        0.094328785       0.167444236       0.133300930\n   1   13        0.000000000       0.003940598       0.000766277\n   1   14        0.000000000       0.002179848       0.000395242\n   1   15        0.000000000       0.022615147       0.006688070\n   1   16        0.006799063       0.014786064       0.009854503\n   1   17        0.000000000       0.000754211       0.000118471\n   1   18        0.000000000       0.000307111       0.000031177\n   1   19        0.000000000       0.020171446       0.006040265\n   1   20        0.006447566       0.012997039       0.009490438\n   1   21        0.000000000       0.016749223       0.005002441\n   1   22        0.005799086       0.011113091       0.008844953\n   1   23        0.000000000       0.012662314       0.003565243\n   1   24        0.004417978       0.011019545       0.007821957\n   2    1        0.000000000       0.528085920       0.086499956\n   2    2        0.243551003       0.576397651       0.478191952\n   2    3        0.220486953       0.527469369       0.437635603\n   2    4        0.000000000       0.503534550       0.078079729\n   2    5        0.195097154       0.473305655       0.392510705\n   2    6        0.000000000       0.474879557       0.069517706\n   2    7        0.166254512       0.411783730       0.340934855\n   2    8        0.000000000       0.433337270       0.058978785\n   2    9        0.136220939       0.347964660       0.286400724\n   2   10        0.000000000       0.375671652       0.047011546\n   2   11        0.101581283       0.273092311       0.221977741\n   2   12        0.000000000       0.292877983       0.033333347\n   2   13        0.000000000       0.015267809       0.000607918\n   2   14        0.000000000       0.020367325       0.002323101\n   2   15        0.000000000       0.006658033       0.003990472\n   2   16        0.000000000       0.009284484       0.000324103\n   2   17        0.000000000       0.024985840       0.002803020\n   2   18        0.003522361       0.012523471       0.008029970\n   2   19        0.000000000       0.011921850       0.000429967\n   2   20        0.000000000       0.015558424       0.002023934\n   2   21        0.000000000       0.006518589       0.003941639\n   2   22        0.000000000       0.003823383       0.000146152\n   2   23        0.000000000       0.023446294       0.002503853\n   2   24        0.003512986       0.012433317       0.007981137\n   2   25        0.000000000       0.008678726       0.000229107\n   2   26        0.000000000       0.010714201       0.001695750\n   2   27        0.000000000       0.006384431       0.003878387\n   2   28        0.000000000       0.001758371       0.000060041\n   2   29        0.000000000       0.021095757       0.002319082\n   2   30        0.003504699       0.012339772       0.007947861\n   2   31        0.000000000       0.004699984       0.000069193\n   2   32        0.000000000       0.010701233       0.001357400\n   2   33        0.000000000       0.006338867       0.003757820\n   2   34        0.000000000       0.000942648       0.000023014\n   2   35        0.000000000       0.017137757       0.002111679\n   2   36        0.003476868       0.012155470       0.007883155\n       -0.2691374625       -0.2381480047\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/nnp-predict/weights.001.data",
    "content": "     -1.4888017024\n     -1.0017511436\n     -1.1705029344\n      0.6414103790\n      0.2140403300\n     -0.1026432602\n     -0.0174383388\n      0.3331085986\n      0.3793430722\n     -0.3303750465\n      1.4789792152\n     -0.8809387034\n     -0.7433616539\n      1.9484973301\n      0.3899739566\n     -1.5454192398\n     -0.9055489974\n     -0.8277917923\n     -0.5777927282\n     -0.5223132192\n     -0.8810762974\n     -0.1101163560\n     -0.1533430498\n     -0.2377377963\n      0.2138962565\n     -0.0132007576\n      0.4904505541\n     -0.0335941714\n     -0.3806985032\n     -0.5236784919\n     -0.6209355724\n     -0.1368801342\n     -0.0088625262\n     -0.3759965136\n     -0.0733722403\n     -0.0012326042\n     -0.1624516438\n     -0.0273982461\n      0.3317405833\n      0.2815090995\n      0.1875439696\n      0.6260027685\n      0.5215529418\n     -0.5322396567\n      0.3446091767\n      0.0347493778\n     -0.4563104126\n      0.1104412679\n     -0.1347965805\n     -0.5622254472\n      0.3871238242\n      0.3362064347\n      0.1822209069\n     -0.3223321905\n      0.0701017737\n      0.3762275128\n      0.3961039164\n      0.4778753236\n     -0.5685960130\n      0.4814378311\n      0.1993690095\n     -0.1235293614\n      0.2910057032\n     -0.9505893382\n      0.2692414487\n      0.6278566042\n      0.1037176712\n      0.4841582715\n     -0.1892464641\n      0.9434407586\n     -0.6178794870\n      0.9091361754\n      1.1933435533\n     -1.4155870671\n     -0.1189239170\n      0.7269244449\n      0.2703700120\n     -0.1793085568\n      0.1248321810\n      0.2106361067\n      0.8806724501\n      0.4276010456\n      0.4776106525\n      0.0506541684\n     -0.1786751640\n     -0.0763037363\n     -0.3420462616\n     -0.1143970958\n      0.3704849225\n      1.5066744083\n     -0.2367170132\n     -0.1457966423\n     -0.0308319311\n     -0.2730000774\n      0.6488153491\n      0.8879587482\n      0.2063419313\n      0.0122982782\n      0.4502714143\n      0.1871250710\n     -0.2165619759\n     -0.0435890354\n     -0.5560803877\n      1.4521312199\n      0.2342364551\n      0.7601873569\n     -0.1991963220\n      0.2642172811\n      0.1158846780\n      1.1960869146\n     -1.0889586625\n     -0.8817908502\n      0.3506735846\n     -0.8351667224\n     -0.9248840778\n     -0.5400175749\n      0.4998695561\n     -0.3882540978\n     -0.3622393196\n     -0.6569324324\n      0.0363303904\n      0.5447484487\n     -0.7338996921\n     -0.0781323293\n      0.2238236356\n     -0.9167299330\n      0.4580166800\n      0.0143999708\n      0.5247884201\n     -1.0815517756\n      0.0402330966\n      0.1056890409\n     -0.0094211343\n     -0.0013035368\n      0.4797689057\n      0.5187854610\n      0.5723168941\n     -0.1819713182\n      0.4015321816\n     -0.1681640071\n      0.5301870488\n      0.0931431814\n      0.0290987728\n      0.4205243136\n      0.4264724644\n     -0.6957253717\n      0.1909090918\n      0.3581991152\n     -0.1416601912\n     -0.1123970840\n     -0.1314235841\n      0.1688318613\n     -0.1379177947\n      0.3532596357\n     -0.6704295045\n     -0.2946578835\n     -0.1720089868\n     -0.1537416401\n     -0.2688881698\n     -0.3799738100\n     -0.7106331481\n      0.4367219986\n      0.5855889382\n     -0.3899779563\n     -0.2792952026\n     -1.5245808139\n     -0.5513806266\n      0.8692974234\n     -0.2741632804\n     -0.6062190375\n     -0.3604725451\n      0.3259486516\n      0.3363966232\n     -0.0442549617\n     -0.0188410038\n      0.6462078306\n     -0.1180726862\n      0.3669540581\n      0.3128139913\n      0.0581398132\n      0.1778325171\n      0.0148846415\n     -0.4429995921\n      0.2390172381\n     -0.1331025880\n     -0.6024920452\n      0.5117700657\n     -0.2691642687\n     -0.2315779607\n     -0.3163003641\n     -0.0127591756\n     -0.4391654338\n     -0.3925018208\n     -0.4744533821\n     -0.2107614189\n      0.0018311472\n      0.0994113312\n     -0.3325323373\n     -0.0877343069\n     -0.0968864505\n      0.6322296571\n     -0.6009314321\n      0.5239541145\n      0.4070156005\n     -0.2424100255\n      0.1701964662\n     -0.1891924004\n     -0.1725962288\n     -0.7454897924\n     -0.5669621459\n      0.1908183223\n      0.1942187055\n      0.0604871372\n     -0.2492556116\n     -0.0385591976\n     -0.4468781371\n     -0.5177978893\n     -0.4064720805\n     -0.1066245329\n     -0.0948811797\n      0.1951580772\n     -0.4209040086\n      0.3766356111\n     -0.3915380758\n     -0.0757449805\n      0.1359964622\n     -0.3250915212\n      0.0933939924\n      1.1579791964\n      0.0838738469\n      0.2034585376\n     -0.1635881649\n     -0.1456949933\n     -0.3592021673\n      0.2137216945\n      0.8663164242\n     -0.5406019849\n      0.5695388479\n     -0.5641558406\n     -0.5315446888\n      0.1534782506\n      0.1169388218\n      0.5654266064\n      1.0147237347\n      1.3732022653\n      0.6500158986\n      1.1632835797\n     -0.5884712191\n      0.2854592057\n     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  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain/nnp-predict/weightse.006.data",
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0.0214767984\n     -1.2604674016\n      0.5117483036\n      0.0880440127\n      0.4217428286\n     -0.8853368328\n     -0.6115408946\n      0.9172122162\n     -0.4760333806\n      0.5499250085\n     -0.2704654038\n      0.2449174326\n     -0.1050311993\n     -0.1485510317\n      1.0146321724\n     -1.6743211709\n      0.2380767417\n     -0.1328144437\n      0.3638814031\n     -0.1239239708\n     -0.9601038260\n     -0.1806512904\n     -0.2575698971\n     -1.2162814460\n     -0.1610690177\n     -0.7615870513\n     -0.4591059211\n     -0.4612198156\n     -0.1540382710\n      0.3441983173\n      0.6391384300\n     -0.7455779825\n     -0.4627302238\n      0.1314744334\n     -0.7014068370\n     -0.2033579104\n      0.1212232083\n     -0.6067023954\n      0.5069908346\n     -0.1774228426\n      0.5536857046\n      0.7152596430\n     -0.2418226948\n     -0.0352134388\n      0.6312171276\n     -0.0538997573\n     -1.8036093239\n     -0.1168802607\n      0.7909203414\n     -0.2117160212\n     -0.4390582068\n      0.4336737889\n      0.0565324994\n      0.8931585316\n      0.0435124833\n      0.3879218289\n      0.6662162305\n     -0.6033649501\n     -0.6728141812\n      0.2764534423\n      0.8692009451\n     -0.3103588626\n     -0.3246343119\n      0.0805694796\n     -0.7924980381\n     -0.4734892016\n      0.7774455099\n     -0.3552006863\n     -0.1311372105\n     -0.4510464545\n      0.0872751413\n     -1.0068512474\n     -0.9366882501\n     -0.1412700750\n     -0.0692648205\n      1.2727720375\n     -1.2412274225\n     -0.1330418616\n      0.2253218249\n     -0.1290402095\n     -0.4364647730\n     -0.4358748116\n     -0.7905074940\n     -0.1598844773\n      0.2305348727\n      0.9211109539\n     -0.5239096769\n      0.1874155714\n      0.9697008034\n      0.7611261866\n     -0.0697588311\n     -0.5518943437\n      0.5789207512\n      0.0244157208\n      0.9491052451\n     -0.7439931541\n     -0.6774484135\n      0.8670996480\n     -0.4929419890\n      0.5412678292\n     -0.5268373832\n      0.0840376342\n     -0.2607310769\n     -0.1247074014\n      0.9302104239\n     -1.6082907232\n     -0.0934733327\n     -0.0544075839\n     -0.0659296363\n      0.1060982776\n     -0.3862593619\n     -0.3381255597\n     -0.0133900094\n     -1.0318316002\n     -0.3504094283\n     -0.7014289303\n      0.3079766203\n     -0.0389294618\n     -0.3651490085\n      0.6087736787\n     -0.0317926478\n     -0.0373969409\n     -0.6111852963\n     -0.2307355678\n     -1.0033829768\n      0.2033559075\n      0.3339897170\n     -0.4331902160\n      0.9350283302\n     -0.0916543374\n      0.1739349306\n      0.4961860405\n      0.1048187453\n     -0.4115258728\n      0.3354771239\n     -0.1223458088\n     -1.1934187986\n     -0.1850137586\n      0.7827224665\n      0.0378443840\n     -0.1925403772\n      0.5438516370\n     -0.1610405300\n      1.0382208971\n     -0.0721478188\n      0.2986940144\n      0.5508842218\n     -0.7215798344\n     -0.6587087954\n      0.2018763434\n      0.9514517105\n     -0.5609427673\n     -0.2681244852\n     -0.2380255405\n     -0.6299317154\n     -0.0444312503\n      0.6723833199\n     -0.1755227672\n      0.0214165418\n     -0.5909926702\n      0.1439287461\n     -0.4741347554\n     -0.7723338598\n     -0.2175892032\n     -0.1319381853\n      0.8237379200\n     -0.6223845297\n      0.0655192356\n      0.0791274955\n      0.0241765665\n     -0.2064087004\n     -0.3940068910\n     -0.5444628729\n     -0.1359227526\n      0.3800822323\n      0.5993674359\n     -0.7269496390\n      0.8367187022\n      0.1374179268\n      0.7344415866\n     -0.2551345486\n     -0.1743276516\n      0.9910772307\n      0.3316258177\n      1.2238138235\n     -0.4179177766\n     -0.2008342288\n      0.6387734163\n     -0.1928348474\n      0.6881137644\n     -0.7000929936\n      0.0735157620\n     -0.3324781162\n      0.0420307653\n      0.9959977273\n     -0.7450342041\n     -0.8529960883\n      0.2969544922\n     -0.0602600691\n      0.2766838148\n     -0.1003145324\n      0.1700644349\n     -0.0641415901\n     -0.9352716760\n     -0.6402313900\n     -0.4651572692\n      0.7722681957\n      1.0887719406\n     -0.4964838793\n      0.7038089902\n     -0.7986021023\n      0.5782880196\n     -0.6165892783\n     -1.0079411424\n     -0.9160050730\n      0.7999285374\n      0.1367149508\n     -0.0647141492\n      0.7688656893\n      0.2878636341\n     -0.3722237651\n      0.1111473417\n      0.3828950059\n     -0.4378732916\n     -0.1316414863\n     -0.1096866025\n     -0.3705437296\n     -0.4851148132\n      0.6206502475\n      0.7147946611\n     -0.0178212911\n      0.3792484954\n     -0.2507005539\n      1.0659073038\n     -0.2027245679\n      0.2017199777\n      0.3003215698\n     -0.8389435343\n     -0.6369460665\n     -0.0933321836\n      0.5776260865\n     -0.5767028069\n     -0.4353569523\n     -0.7078700015\n     -0.4528725887\n      0.4402600593\n      0.0847773972\n      0.2788315779\n      0.2652386196\n     -0.5934642654\n      0.0606796684\n     -0.0240946437\n     -0.5221134615\n     -0.2158837878\n     -0.1666201799\n      0.2831691942\n      0.1548712159\n      0.4069982742\n      0.0614233895\n      0.0076948724\n      0.1343740575\n     -0.1587786167\n     -0.2949905912\n      0.0568310441\n      0.2915891973\n      0.2089325098\n      0.0021438982\n      0.1311775629\n     -0.6705841369\n      0.7347319618\n     -0.1484791977\n     -0.2162294124\n      0.8309982253\n     -0.0401276045\n      0.8479086493\n     -0.2065159209\n      0.9296989088\n     -0.0481041026\n      0.5809043146\n      0.4089903880\n      0.2223221997\n      0.1160041545\n     -0.4602602639\n     -0.1334080950\n     -0.0435590321\n      1.0788682386\n      0.1605417540\n      0.4218863145\n     -0.3317259475\n      0.4283293595\n      0.0611642978\n      0.9183707139\n     -0.2723340672\n     -1.0920471036\n     -0.3713786255\n     -0.2472463119\n     -0.4721194768\n      1.4978735406\n      0.3286069439\n      0.0938603768\n      0.1690412455\n     -0.5012145404\n      0.6166936354\n     -0.8298359733\n     -0.6693731422\n      0.5221510234\n      0.4215053294\n      0.0656388111\n      0.4861742881\n     -0.0081073075\n     -0.4925803428\n     -0.6600221667\n      0.1272019508\n     -0.0090456956\n     -1.3715130022\n      0.3109905053\n      0.4535667158\n     -1.6915038027\n      0.8338429940\n      2.2347737978\n      0.0804225592\n     -0.0308499916\n     -0.1486614136\n      0.9753636261\n      0.3032806837\n      0.0604180499\n     -0.2851974368\n     -0.1318419288\n     -0.1369773622\n     -1.0050621724\n      0.4592854729\n     -0.5367611149\n     -0.7810309148\n     -0.9202002259\n      0.0669989367\n      1.7276884639\n     -0.9999769999\n      1.0285707457\n      1.1542196303\n     -0.6086259937\n     -0.0759605467\n     -0.9023685322\n     -0.1508870075\n      0.6164065665\n      0.3333376818\n     -0.7858766466\n      0.4294231053\n     -0.4407090829\n      0.7736383708\n     -0.2359834008\n     -0.0202907128\n     -0.2180730486\n     -0.6840055578\n     -0.8463543049\n     -0.1538054213\n      0.8565837683\n     -0.2703235873\n     -0.0508505534\n      0.0559036001\n     -1.2569307297\n      0.0145876741\n      0.3387996939\n      0.3199708674\n     -0.2029252897\n     -0.0472493730\n     -0.6309356950\n      0.8896411965\n     -2.0955514047\n      0.4279469201\n      0.0266378958\n      1.4070332400\n     -0.0294007300\n      0.3407484478\n     -0.8172902279\n      1.6487546807\n     -0.0623547386\n      0.3883346270\n      0.0784087968\n      0.5987994829\n     -2.0482785708\n     -0.0878347656\n     -1.5024420974\n      2.8311533001\n     -1.9208463310\n     -0.9728285530\n     -0.4000267303\n      0.0916188942\n      0.0652916261\n     -0.2063674689\n     -0.4998824884\n      0.5934900052\n     -0.3538291998\n     -0.2192364250\n      0.7330223549\n     -0.0143295732\n     -1.0152116046\n      0.4316079184\n     -2.2107091847\n     -2.7316551236\n     -0.6181078170\n     -2.3335805886\n     -0.2451520870\n     -0.3100282558\n      0.0797196058\n     -0.5008548511\n     -0.8840659238\n     -0.1130072915\n      0.2551511750\n     -0.3179275739\n      1.0384571273\n      0.6575601296\n      1.6034851298\n     -2.3886312909\n     -0.9339623524\n     -1.2643663283\n     -0.0148557048\n      0.1206068884\n      0.0133351930\n     -0.3060192388\n      1.2442941197\n      1.2913622498\n      0.4127824106\n     -0.0259057296\n     -0.6683841364\n     -0.7607917591\n     -1.5364039498\n     -2.0420547619\n      1.0021196401\n      0.6885654807\n      0.8722571125\n     -1.8557931911\n     -0.1943362643\n     -0.0334702134\n     -0.1250534993\n      0.7684573398\n     -0.6287528033\n     -0.1237433239\n      0.3552105233\n     -0.1326254090\n     -1.1625292734\n     -0.3730818618\n     -0.1193215635\n      5.2965831132\n     -0.4618024048\n     -0.0004434927\n      4.2724404576\n     -0.2706485705\n     -0.2992525783\n      0.4444540238\n      1.1950931653\n      0.2349044910\n     -0.1070516985\n      0.4369045762\n     -0.0444983410\n      0.2153442351\n     -1.1251010384\n     -1.4979626726\n     -0.5551913574\n     -2.0694528611\n      0.2606234991\n     -2.2022190083\n     -0.1144456894\n     -0.1258836280\n     -0.3684364718\n     -0.2583360506\n     -0.4544922852\n     -0.2618750396\n      0.2359057839\n      0.1613573769\n      0.9904412492\n     -0.1016524499\n     -1.0657100465\n      0.8605886894\n      0.1413029799\n     -0.1893761626\n     -3.7391061335\n      0.0036828432\n      0.3886376713\n     -0.6562280624\n      0.1083763220\n     -0.0391240429\n      0.2267509693\n     -0.2058136409\n     -0.1430979256\n      0.7009168993\n      0.4931955095\n      0.7863721995\n      0.2472528221\n     -1.2495204718\n      0.6875830102\n      1.9466142831\n      0.1023390652\n     -0.2558956548\n      0.2852365762\n      0.0029291118\n      0.9868865541\n      0.0403577509\n     -0.1047418136\n     -0.3488408483\n     -0.9674470264\n      0.1494635568\n      0.2065713356\n      2.3167621560\n     -0.4749087023\n      1.3388042843\n      2.6993169368\n      0.0429258126\n      0.0103415735\n      0.2764993198\n      0.6813767545\n     -0.4331521111\n      0.2551211682\n     -0.2364161739\n     -0.3079983949\n      0.6467916994\n     -1.5260399719\n      0.6265168530\n     -0.8105200453\n     -0.3736370520\n      0.3084884217\n     -0.2992212659\n     -0.0273815678\n      0.1049134175\n      0.2536801614\n     -1.1511637867\n     -0.9000689224\n      0.1443339389\n      0.0620394402\n      1.9992994309\n      0.7843928157\n      1.4391271323\n     -0.3321939402\n     -2.4382905743\n     -1.6734428117\n     -0.9249641999\n     -1.3018867082\n      0.0152212636\n      0.3104785525\n     -0.2492140028\n     -0.8955123746\n      0.9869474327\n      0.0822669444\n     -0.1830559445\n     -1.1230333927\n     -0.1385515232\n     -0.3696105195\n      0.1082286260\n      0.1748680549\n     -1.2177151081\n      0.1079492551\n     -0.2859594318\n     -0.3121904922\n      0.1034155480\n      0.1806808724\n     -0.2580117886\n      0.3535325828\n      0.0229540981\n      0.3238516401\n     -0.7821787424\n     -0.5357628124\n      1.2345527437\n      1.8953010665\n      0.3961253271\n     -0.4570288514\n      0.4972780485\n      1.5141288000\n      0.1366535654\n     -0.0558186183\n      0.5826411377\n     -0.1801513810\n      0.4953259346\n     -0.0545313333\n     -0.1340448904\n     -0.1234905918\n     -1.2417564423\n     -0.8220806959\n      0.1234736475\n     -0.3094409144\n      0.3831220587\n     -0.1464400551\n     -0.2343229869\n      0.0007787294\n     -0.4790095880\n      0.6993700632\n     -0.1998249300\n      0.2858428262\n     -0.2110018462\n      0.1624702703\n      0.6789582127\n     -0.4868270904\n     -0.2768406958\n     -0.7069002115\n     -0.6879166506\n     -2.0867370236\n     -0.7994656137\n      0.1719842944\n     -0.0000752220\n     -0.0003613176\n     -0.0029232214\n      0.0445647221\n      0.0222816566\n     -0.0003398342\n      0.0003305899\n     -0.0272082042\n     -0.0176071818\n      0.0295840498\n      0.0939072748\n     -0.0735707973\n      0.0340777246\n     -0.0573394490\n     -0.1135653336\n     -0.1319696539\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/carbon-chain.data",
    "content": "Carbon chain, first structure from input.data\n\n12 atoms\n\n2 atom types\n\n  -12.94 12.67 xlo xhi\n   -0.36  1.20 ylo yhi\n   -0.67  1.17 zlo zhi\n\nAtoms\n\n1  2  0.0  1.17284095486 -0.172504222684   -0.667448516865\n2  2  0.0 -1.1595434822  -0.350641000445   -0.467598107194\n3  2  0.0  3.72594054969 -0.0837975179097  -0.229777168673\n4  2  0.0 -3.69146983116 -0.334172643167   -0.21088223315\n5  2  0.0  6.07758586771 -0.166745226042   -0.145024035228\n6  2  0.0 -6.06809789367 -0.00253733508489 -0.0705357610724\n7  2  0.0  8.59164353464 -0.0806915075831   0.402236831619\n8  2  0.0 -8.60892564573  0.117192245354    0.0982851777904\n9  2  0.0  10.8705405815  0.51581338865     0.435826522093\n10 2  0.0 -10.8879581104  0.411807821319    0.694948565342\n11 1  0.0  12.661965991   1.19502446714     1.1691448209\n12 1  0.0 -12.9307322131  0.525058551796    0.728011456903\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/carbon-chain.data-eg",
    "content": "Carbon chain, first structure from input.data\n\n12 atoms\n\n2 atom types\n\n  -12.94 12.67 xlo xhi\n   -0.36  1.20 ylo yhi\n   -0.67  1.17 zlo zhi\n\nAtoms\n\n1  2  -2.36E-03   1.1729073318400078 -1.7250595988097372E-01 -6.6741810230359422E-01\n2  2  -8.49E-03  -1.1595817453608341 -3.5063784106789647E-01 -4.6759951235815161E-01\n3  2  -1.05E-02   3.7259094240411681 -8.3808446129817402E-02 -2.2980808620118351E-01\n4  2  -7.14E-03  -3.6915315204094927 -3.3414993292840278E-01 -2.1088572536199013E-01\n5  2   8.15E-04   6.0775914248949645 -1.6674672212588620E-01 -1.4499820679122288E-01\n6  2   8.35E-04  -6.0680299107700124 -2.5620260955245030E-03 -7.0543207699589230E-02\n7  2  -2.85E-02   8.5916667587931013 -8.0658783933167305E-02  4.0220650606187225E-01\n8  2  -3.24E-02  -8.6089840636623833  0.11721101618520001    9.8323591084281514E-02\n9  2  -6.05E-02  10.870494591100982  5.1580223738887498E-01  4.3585444122535055E-01\n10 2  -5.61E-02 -10.887890663537627  4.1179249277052421E-01  6.9490967680382398E-01\n11 1   1.01E-01  12.661796981509699  1.1948282077976258      1.1689054257962741\n12 1   1.02E-01 -12.930485451086453  5.2506382642642058E-01  7.2809053422821779E-01\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/carbon-chain.data-mod",
    "content": "Carbon chain, first structure from input.data\n\n12 atoms\n\n2 atom types\n\n  -12.94 12.67 xlo xhi\n   -0.36  1.20 ylo yhi\n   -0.67  1.17 zlo zhi\n\nAtoms\n\n1  2  -2.35997196E-03   1.172907331840007 -1.7250595988097372E-01 -6.6741810230359422E-01\n2  2  -8.49071586E-03  -1.159581745360834 -3.5063784106789647E-01 -4.6759951235815161E-01\n3  2  -1.05341133E-02   3.725909424041168 -8.3808446129817402E-02 -2.2980808620118351E-01\n4  2  -7.15563490E-03  -3.691531520409492 -3.3414993292840278E-01 -2.1088572536199013E-01\n5  2   8.14623403E-04   6.077591424894964 -1.6674672212588620E-01 -1.4499820679122288E-01\n6  2   8.34327483E-04  -6.068029910770012 -2.5620260955245030E-03 -7.0543207699589230E-02\n7  2  -2.83459938E-02   8.591666758793101 -8.0658783933167305E-02  4.0220650606187225E-01\n8  2  -3.24586443E-02  -8.608984063662383  0.11721101618520001     9.8323591084281514E-02\n9  2  -6.06473430E-02  10.870494591100982  5.1580223738887498E-01  4.3585444122535055E-01\n10 2  -5.61417786E-02 -10.887890663537627  4.1179249277052421E-01  6.9490967680382398E-01\n11 1   1.01543794E-01  12.661796981509699  1.1948282077976258      1.1689054257962741\n12 1   1.02941451E-01 -12.930485451086453  5.2506382642642058E-01  7.2809053422821779E-01\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/carbon-chain.data-n2p2",
    "content": "Carbon chain, first structure from input.data\n\n12 atoms\n\n2 atom types\n\n  -12.94 12.67 xlo xhi\n   -0.36  1.20 ylo yhi\n   -0.67  1.17 zlo zhi\n\nAtoms\n\n1  2  0.0   1.1729073318400078  -0.17250595988097372  -0.66741810230359422 \n2  2  0.0  -1.1595817453608341  -0.35063784106789647  -0.46759951235815161\n3  2  0.0   3.7259094240411681  -0.083808446129817402  -0.22980808620118351\n4  2  0.0  -3.6915315204094927  -0.33414993292840278  -0.21088572536199013\n5  2  0.0   6.0775914248949645  -0.16674672212588620  -0.14499820679122288\n6  2  0.0  -6.0680299107700124  -0.0025620260955245030  -0.070543207699589230 \n7  2  0.0   8.5916667587931013  -0.080658783933167305   0.40220650606187225\n8  2  0.0  -8.6089840636623833   0.11721101618520001   0.098323591084281514\n9  2  0.0   10.870494591100982   0.51580223738887498   0.43585444122535055\n10 2  0.0  -10.887890663537627   0.41179249277052421   0.69490967680382398\n11 1  0.0   12.661796981509699   1.1948282077976258   1.168905425796274     \n12 1  0.0  -12.930485451086453   0.52506382642642058   0.72809053422821779  \n  \n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/carbon-chain.data-org",
    "content": "Carbon chain, first structure from input.data\n\n12 atoms\n\n2 atom types\n\n  -12.94 12.67 xlo xhi\n   -0.36  1.20 ylo yhi\n   -0.67  1.17 zlo zhi\n\nAtoms\n\n1  2  -2.35997196E-03  1.17284095486 -0.172504222684   -0.667448516865\n2  2  -8.49071586E-03 -1.1595434822  -0.350641000445   -0.467598107194\n3  2  -1.05341133E-02  3.72594054969 -0.0837975179097  -0.229777168673\n4  2  -7.15563490E-03 -3.69146983116 -0.334172643167   -0.21088223315\n5  2  8.14623403E-04  6.07758586771 -0.166745226042   -0.145024035228\n6  2  8.34327483E-04 -6.06809789367 -0.00253733508489 -0.0705357610724\n7  2  -2.83459938E-02  8.59164353464 -0.0806915075831   0.402236831619\n8  2  -3.24586443E-02 -8.60892564573  0.117192245354    0.0982851777904\n9  2  -6.06473430E-02  10.8705405815  0.51581338865     0.435826522093\n10 2  -5.61417786E-02 -10.8879581104  0.411807821319    0.694948565342\n11 1  1.01543794E-01  12.661965991   1.19502446714     1.1691448209\n12 1  1.02941451E-01 -12.9307322131  0.525058551796    0.728011456903\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/carbon-chain.data-q0",
    "content": "Carbon chain, first structure from input.data\n\n12 atoms\n\n2 atom types\n\n  -12.94 12.67 xlo xhi\n   -0.36  1.20 ylo yhi\n   -0.67  1.17 zlo zhi\n\nAtoms\n\n1  2  0.0  1.17284095486 -0.172504222684   -0.667448516865\n2  2  0.0 -1.1595434822  -0.350641000445   -0.467598107194\n3  2  0.0  3.72594054969 -0.0837975179097  -0.229777168673\n4  2  0.0 -3.69146983116 -0.334172643167   -0.21088223315\n5  2  0.0  6.07758586771 -0.166745226042   -0.145024035228\n6  2  0.0 -6.06809789367 -0.00253733508489 -0.0705357610724\n7  2  0.0  8.59164353464 -0.0806915075831   0.402236831619\n8  2  0.0 -8.60892564573  0.117192245354    0.0982851777904\n9  2  0.0  10.8705405815  0.51581338865     0.435826522093\n10 2  0.0 -10.8879581104  0.411807821319    0.694948565342\n11 1  0.0  12.661965991   1.19502446714     1.1691448209\n12 1  0.0 -12.9307322131  0.525058551796    0.728011456903\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/carbon-chain.data-sameq",
    "content": "Carbon chain, first structure from input.data\n\n12 atoms\n\n2 atom types\n\n  -12.94 12.67 xlo xhi\n   -0.36  1.20 ylo yhi\n   -0.67  1.17 zlo zhi\n\nAtoms\n\n1  2  -2.3599719595358937E-03   1.1729073318400078 -1.7250595988097372E-01 -6.6741810230359422E-01\n2  2  -8.4907158646713859E-03  -1.1595817453608341 -3.5063784106789647E-01 -4.6759951235815161E-01\n3  2  -1.0534113290044665E-02   3.7259094240411681 -8.3808446129817402E-02 -2.2980808620118351E-01\n4  2  -7.1556348953342435E-03  -3.6915315204094927 -3.3414993292840278E-01 -2.1088572536199013E-01\n5  2   8.1462340324302566E-04   6.0775914248949645 -1.6674672212588620E-01 -1.4499820679122288E-01\n6  2   8.3432748292313285E-04  -6.0680299107700124 -2.5620260955245030E-03 -7.0543207699589230E-02\n7  2  -2.8345993789409479E-02   8.5916667587931013 -8.0658783933167305E-02  4.0220650606187225E-01\n8  2  -3.2458644274754651E-02  -8.6089840636623833  0.11721101618520001    9.8323591084281514E-02\n9  2  -6.0647343034107404E-02  10.870494591100982  5.1580223738887498E-01  4.3585444122535055E-01\n10 2  -5.6141778584216068E-02 -10.887890663537627  4.1179249277052421E-01  6.9490967680382398E-01\n11 1   1.0154379417885089E-01  12.661796981509699  1.1948282077976258      1.1689054257962741\n12 1   1.0294145062705674E-01 -12.930485451086453  5.2506382642642058E-01  7.2809053422821779E-01\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/carbond-chain.data",
    "content": "Carbon chain, first structure from input.data\n\n12 atoms\n\n2 atom types\n\n  -12.94 12.67 xlo xhi\n   -0.36  1.20 ylo yhi\n   -0.67  1.17 zlo zhi\n\nAtoms\n\n1  2  -2.35997196E-03   1.172907331840007 -1.7250595988097372E-01 -6.6741810230359422E-01\n2  2  -8.49071586E-03  -1.159581745360834 -3.5063784106789647E-01 -4.6759951235815161E-01\n3  2  -1.05341133E-02   3.725909424041168 -8.3808446129817402E-02 -2.2980808620118351E-01\n4  2  -7.15563490E-03  -3.691531520409492 -3.3414993292840278E-01 -2.1088572536199013E-01\n5  2   8.14623403E-04   6.077591424894964 -1.6674672212588620E-01 -1.4499820679122288E-01\n6  2   8.34327483E-04  -6.068029910770012 -2.5620260955245030E-03 -7.0543207699589230E-02\n7  2  -2.83459938E-02   8.591666758793101 -8.0658783933167305E-02  4.0220650606187225E-01\n8  2  -3.24586443E-02  -8.608984063662383  0.11721101618520001     9.8323591084281514E-02\n9  2  -6.06473430E-02  10.870494591100982  5.1580223738887498E-01  4.3585444122535055E-01\n10 2  -5.61417786E-02 -10.887890663537627  4.1179249277052421E-01  6.9490967680382398E-01\n11 1   1.01543794E-01  12.661796981509699  1.1948282077976258      1.1689054257962741\n12 1   1.02941451E-01 -12.930485451086453  5.2506382642642058E-01  7.2809053422821779E-01\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/debug.out",
    "content": " 00000000000000000000\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/energy.out",
    "content": "################################################################################\n# Energy comparison.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    conf     Configuration index (starting with 1).\n# 2    natoms   Number of atoms in configuration.\n# 3    Eref     Reference potential energy.\n# 4    Ennp     Potential energy predicted by NNP.\n# 5    Ediff    Difference in energy per atom between reference and NNP prediction.\n# 6    E_offset Sum of atomic offset energies (included in column Ennp).\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#     conf     natoms                     Eref                     Ennp                    Ediff                 E_offset\n#########################################################################################################################\n         1         12   0.0000000000000000E+00  -3.8161081273904063E+02   3.1800901061586718E+01  -3.7839893392473289E+02\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/external.out",
    "content": " -------------------------------------------------------------\n ---------------------- Welcome to the -----------------------\n     RuNNer Neural Network Energy Representation - RuNNer     \n ----------  (c) 2008-2020 Prof. Dr. Joerg Behler   ----------\n ----------  Georg-August-Universitaet Goettingen   ----------\n ----------           Theoretische Chemie           ----------\n ----------              Tammannstr. 6              ----------\n ----------        37077 Goettingen, Germany        ----------\n -------------------------------------------------------------\n -------------------------------------------------------------\n  This program is free software: you can redistribute it and/or modify it\n  under the terms of the GNU General Public License as published by the \n  Free Software Foundation, either version 3 of the License, or \n  (at your option) any later version.\n    \n  This program is distributed in the hope that it will be useful, but \n  WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY\n  or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License \n  for more details.\n      \n  You should have received a copy of the GNU General Public License along\n  with this program. If not, see http://www.gnu.org/licenses. \n -------------------------------------------------------------\n -------------------------------------------------------------\n When using RuNNer, please cite the following papers:\n J. Behler, Angew. Chem. Int. Ed. 56, 12828 (2017).\n J. Behler, Int. J. Quant. Chem. 115, 1032 (2015).\n -------------------------------------------------------------\n Whenever using high-dimensional NNPs irrespective of the Code please cite:\n J. Behler and M. Parrinello, Phys. Rev. Lett. 98, 146401 (2007).\n -------------------------------------------------------------\n The reference for the atom-centered symmetry functions is:\n J. Behler, J. Chem. Phys. 134, 074106 (2011).\n -------------------------------------------------------------\n For high-dimensional NNs including electrostatics:\n N. Artrith, T. Morawietz, and J. Behler, Phys. Rev. B 83, 153101 (2011).\n -------------------------------------------------------------\n -------------------------------------------------------------\n RuNNer has been written by Joerg Behler\n  \n *** with contributions from some friends ***\n  \n Tobias Morawietz - Nguyen Widrow weights and electrostatic screening\n Jovan Jose Kochumannil Varghese - Pair symmetry functions and pair NNPs\n Michael Gastegger and Philipp Marquetand - element decoupled Kalman filter\n Andreas Singraber - more efficient symmetry function type 3 implementation\n Sinja Klees and Mariana Rossi - some infrastructure for i-Pi compatibility\n Emir Kocer - Symmetry function groups\n Fenfei Wei and Emir Kocer - Hessian, frequencies and normal modes\n Alexander Knoll - vdW corrections long ranged\n -------------------------------------------------------------\n -------------------------------------------------------------\n General job information:\n -------------------------------------------------------------\n Executing host    : Emir-MacBook-Pro.loc\n User name         : emirkocer           \n Starting date     :  8. 2.2021\n Starting time     : 10 h 29 min \n Working directory :                                                             \n -------------------------------------------------------------\n -------------------------------------------------------------\n Serial run requested\n -------------------------------------------------------------\n Reading control parameters from input.nn\n =============================================================\n -------------------------------------------------------------\n ### WARNING ### use_atom_charges is switched on for electrostatic NN\n WARNING: reducing points_in_memory to max_num_atoms           12\n =============================================================\n General input parameters:\n -------------------------------------------------------------\n Short range NN is on\n Electrostatic NN is off\n vdW corrections switched off\n -------------------------------------------------------------\n RuNNer nn_type_short                                   3\n RuNNer is started in mode for prediction (3)\n debugging mode is                                       F\n parallelization mode                                     1\n enable detailed time measurement                        F\n using symmetry function groups                          F\n silent mode                                             F\n NN force check                                          F\n number of elements                                       2\n elements (sorted):\n  1 H \n  6 C \n seed for random number generator                        10\n random number generator type                             5\n remove free atom reference energies                     T\n remove vdw dispersion energy and forces             F\n shortest allowed bond in structure                   0.400\n Cutoff_type for symmetry function is                     2\n Cutoff_alpha for inner cutoff radius is              0.000\n -------------------------------------------------------------\n Short range NN specifications:\n -------------------------------------------------------------\n global hidden layers short range NN                      2\n global nodes hidden layers short NN                10   10\n global activation functions short                      ttl\n -------------------------------------------------------------\n Electrostatic specifications:\n -------------------------------------------------------------\n electrostatic_type (nn_type_elec)                        0\n Ewald alpha                                          0.000\n Ewald cutoff                                         0.000\n Ewald kmax                                               0\n Screening electrostatics                                  4.800000      8.000000\n -------------------------------------------------------------\n Parameters for symmetry function generation: short range part:\n -------------------------------------------------------------\n using forces for fitting                                T\n using atomic energies for fitting                       F\n -------------------------------------------------------------\n Options for prediction mode:\n -------------------------------------------------------------\n rescale symmetry functions                              T\n remove CMS from symmetry functions                      T\n rescale atomic charges                                  F\n remove CMS from atomic charges                          F\n Reading formatted files \n calculation of analytic forces                          T\n calculation of analytic Hessian                         F\n calculation of analytic stress                          F\n write symmetry functions                                F\n prepare md                                              F\n =============================================================\n Element pairs:   3    , shortest distance (Bohr)\n pair    2 H  C       2.046\n pair    3 C  C       2.348\n =============================================================\n => short range NN weights type 3                 H        381\n => short range NN weights type 3                 C        501\n => electrostatic NN weights                      H        631\n => electrostatic NN weights                      C        811\n -------------------------------------------------------------\n -------------------------------------------------------------\n Atomic reference energies read from input.nn:\n H         -0.45890731\n C        -37.74811193\n -------------------------------------------------------------\n -------------------------------------------------\n Atomic short range NN for element: H \n architecture       25   10   10    1\n -------------------------------------------------\n   1   G  t  t  l\n   2   G  t  t   \n   3   G  t  t   \n   4   G  t  t   \n   5   G  t  t   \n   6   G  t  t   \n   7   G  t  t   \n   8   G  t  t   \n   9   G  t  t   \n  10   G  t  t   \n  11   G\n  12   G\n  13   G\n  14   G\n  15   G\n  16   G\n  17   G\n  18   G\n  19   G\n  20   G\n  21   G\n  22   G\n  23   G\n  24   G\n  25   G\n -------------------------------------------------\n Atomic short range NN for element: C \n architecture       37   10   10    1\n -------------------------------------------------\n   1   G  t  t  l\n   2   G  t  t   \n   3   G  t  t   \n   4   G  t  t   \n   5   G  t  t   \n   6   G  t  t   \n   7   G  t  t   \n   8   G  t  t   \n   9   G  t  t   \n  10   G  t  t   \n  11   G\n  12   G\n  13   G\n  14   G\n  15   G\n  16   G\n  17   G\n  18   G\n  19   G\n  20   G\n  21   G\n  22   G\n  23   G\n  24   G\n  25   G\n  26   G\n  27   G\n  28   G\n  29   G\n  30   G\n  31   G\n  32   G\n  33   G\n  34   G\n  35   G\n  36   G\n  37   G\n ---------------------------------------------------\n Electrostatic NN for element: H \n architecture       24   15   15    1\n ---------------------------------------------------\n   1   G  t  t  l\n   2   G  t  t   \n   3   G  t  t   \n   4   G  t  t   \n   5   G  t  t   \n   6   G  t  t   \n   7   G  t  t   \n   8   G  t  t   \n   9   G  t  t   \n  10   G  t  t   \n  11   G  t  t   \n  12   G  t  t   \n  13   G  t  t   \n  14   G  t  t   \n  15   G  t  t   \n  16   G\n  17   G\n  18   G\n  19   G\n  20   G\n  21   G\n  22   G\n  23   G\n  24   G\n ---------------------------------------------------\n Electrostatic NN for element: C \n architecture       36   15   15    1\n ---------------------------------------------------\n   1   G  t  t  l\n   2   G  t  t   \n   3   G  t  t   \n   4   G  t  t   \n   5   G  t  t   \n   6   G  t  t   \n   7   G  t  t   \n   8   G  t  t   \n   9   G  t  t   \n  10   G  t  t   \n  11   G  t  t   \n  12   G  t  t   \n  13   G  t  t   \n  14   G  t  t   \n  15   G  t  t   \n  16   G\n  17   G\n  18   G\n  19   G\n  20   G\n  21   G\n  22   G\n  23   G\n  24   G\n  25   G\n  26   G\n  27   G\n  28   G\n  29   G\n  30   G\n  31   G\n  32   G\n  33   G\n  34   G\n  35   G\n  36   G\n -------------------------------------------------------------\n -------------------------------------------------------------\n  short range atomic symmetry functions element H  :\n -------------------------------------------------------------\n    1 H   2  H               0.000   0.000   8.000\n    2 H   2  C               0.000   0.000   8.000\n    3 H   2  H               0.006   0.000   8.000\n    4 H   2  H               0.011   0.000   8.000\n    5 H   2  C               0.013   0.000   8.000\n    6 H   2  H               0.018   0.000   8.000\n    7 H   2  H               0.026   0.000   8.000\n    8 H   2  C               0.029   0.000   8.000\n    9 H   2  H               0.035   0.000   8.000\n   10 H   2  C               0.054   0.000   8.000\n   11 H   2  C               0.093   0.000   8.000\n   12 H   2  C               0.161   0.000   8.000\n   13 H   3  H  C    0.000  -1.000   1.000   8.000\n   14 H   3  C  C    0.000  -1.000   1.000   8.000\n   15 H   3  H  C    0.000   1.000   1.000   8.000\n   16 H   3  C  C    0.000   1.000   1.000   8.000\n   17 H   3  H  C    0.000  -1.000   2.000   8.000\n   18 H   3  C  C    0.000  -1.000   2.000   8.000\n   19 H   3  H  C    0.000   1.000   2.000   8.000\n   20 H   3  C  C    0.000   1.000   2.000   8.000\n   21 H   3  H  C    0.000   1.000   4.000   8.000\n   22 H   3  C  C    0.000   1.000   4.000   8.000\n   23 H   3  H  C    0.000   1.000   8.000   8.000\n   24 H   3  C  C    0.000   1.000   8.000   8.000\n -------------------------------------------------------------\n  short range atomic symmetry functions element C  :\n -------------------------------------------------------------\n    1 C   2  H               0.000   0.000   8.000\n    2 C   2  C               0.000   0.000   8.000\n    3 C   2  C               0.010   0.000   8.000\n    4 C   2  H               0.013   0.000   8.000\n    5 C   2  C               0.023   0.000   8.000\n    6 C   2  H               0.029   0.000   8.000\n    7 C   2  C               0.041   0.000   8.000\n    8 C   2  H               0.054   0.000   8.000\n    9 C   2  C               0.065   0.000   8.000\n   10 C   2  H               0.093   0.000   8.000\n   11 C   2  C               0.103   0.000   8.000\n   12 C   2  H               0.161   0.000   8.000\n   13 C   3  H  H    0.000  -1.000   1.000   8.000\n   14 C   3  H  C    0.000  -1.000   1.000   8.000\n   15 C   3  C  C    0.000  -1.000   1.000   8.000\n   16 C   3  H  H    0.000   1.000   1.000   8.000\n   17 C   3  H  C    0.000   1.000   1.000   8.000\n   18 C   3  C  C    0.000   1.000   1.000   8.000\n   19 C   3  H  H    0.000  -1.000   2.000   8.000\n   20 C   3  H  C    0.000  -1.000   2.000   8.000\n   21 C   3  C  C    0.000  -1.000   2.000   8.000\n   22 C   3  H  H    0.000   1.000   2.000   8.000\n   23 C   3  H  C    0.000   1.000   2.000   8.000\n   24 C   3  C  C    0.000   1.000   2.000   8.000\n   25 C   3  H  H    0.000  -1.000   4.000   8.000\n   26 C   3  H  C    0.000  -1.000   4.000   8.000\n   27 C   3  C  C    0.000  -1.000   4.000   8.000\n   28 C   3  H  H    0.000   1.000   4.000   8.000\n   29 C   3  H  C    0.000   1.000   4.000   8.000\n   30 C   3  C  C    0.000   1.000   4.000   8.000\n   31 C   3  H  H    0.000  -1.000   8.000   8.000\n   32 C   3  H  C    0.000  -1.000   8.000   8.000\n   33 C   3  C  C    0.000  -1.000   8.000   8.000\n   34 C   3  H  H    0.000   1.000   8.000   8.000\n   35 C   3  H  C    0.000   1.000   8.000   8.000\n   36 C   3  C  C    0.000   1.000   8.000   8.000\n -------------------------------------------------------------\n Prediction Mode for all configurations\n NNconfiguration:         1    Number of atoms:        12\n -------------------------------------------------------------\n begin\n atom     -8.608984064     0.117211016     0.098323591 C       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom    -10.887890664     0.411792493     0.694909677 C       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom    -12.930485451     0.525063826     0.728090534 H       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom     -3.691531520    -0.334149933    -0.210885725 C       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom     -6.068029911    -0.002562026    -0.070543208 C       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom      1.172907332    -0.172505960    -0.667418102 C       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom     -1.159581745    -0.350637841    -0.467599512 C       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom      3.725909424    -0.083808446    -0.229808086 C       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom      6.077591425    -0.166746722    -0.144998207 C       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom      8.591666759    -0.080658784     0.402206506 C       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom     10.870494591     0.515802237     0.435854441 C       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n atom     12.661796982     1.194828208     1.168905426 H       0.000000000     0.000000000     0.000000000     0.000000000     0.000000000\n energy         0.00000000\n charge         0.00000000\n end\n -------------------------------------------------------------\n =============================================================\n Short range symmetry function values for element H \n Training set:  min           max       average         range \n   1     0.00000000    0.16847433    0.05143660    0.16847433\n   2     0.30405858    0.41710478    0.34591559    0.11304620\n   3     0.00000000    0.15946523    0.04769325    0.15946523\n   4     0.00000000    0.15232677    0.04478431    0.15232677\n   5     0.27036724    0.37728930    0.31224289    0.10692206\n   6     0.00000000    0.14286655    0.04100957    0.14286655\n   7     0.00000000    0.13277213    0.03708637    0.13277213\n   8     0.23624129    0.33657312    0.27800313    0.10033183\n   9     0.00000000    0.12226589    0.03312272    0.12226589\n  10     0.19404378    0.28607654    0.23585771    0.09203276\n  11     0.14641396    0.23097961    0.18800041    0.08456565\n  12     0.09432878    0.16744424    0.13330093    0.07311545\n  13     0.00000000    0.00394060    0.00076628    0.00394060\n  14     0.00000000    0.00217985    0.00039524    0.00217985\n  15     0.00000000    0.02261515    0.00668807    0.02261515\n  16     0.00679906    0.01478606    0.00985450    0.00798700\n  17     0.00000000    0.00075421    0.00011847    0.00075421\n  18     0.00000000    0.00030711    0.00003118    0.00030711\n  19     0.00000000    0.02017145    0.00604027    0.02017145\n  20     0.00644757    0.01299704    0.00949044    0.00654947\n  21     0.00000000    0.01674922    0.00500244    0.01674922\n  22     0.00579909    0.01111309    0.00884495    0.00531401\n  23     0.00000000    0.01266231    0.00356524    0.01266231\n  24     0.00441798    0.01101955    0.00782196    0.00660157\n =============================================================\n Short range symmetry function values for element C \n Training set:  min           max       average         range \n   1     0.00000000    0.52808592    0.08649996    0.52808592\n   2     0.24355100    0.57639765    0.47819195    0.33284665\n   3     0.22048695    0.52746937    0.43763560    0.30698242\n   4     0.00000000    0.50353455    0.07807973    0.50353455\n   5     0.19509715    0.47330565    0.39251071    0.27820850\n   6     0.00000000    0.47487956    0.06951771    0.47487956\n   7     0.16625451    0.41178373    0.34093485    0.24552922\n   8     0.00000000    0.43333727    0.05897878    0.43333727\n   9     0.13622094    0.34796466    0.28640072    0.21174372\n  10     0.00000000    0.37567165    0.04701155    0.37567165\n  11     0.10158128    0.27309231    0.22197774    0.17151103\n  12     0.00000000    0.29287798    0.03333335    0.29287798\n  13     0.00000000    0.01526781    0.00060792    0.01526781\n  14     0.00000000    0.02036732    0.00232310    0.02036732\n  15     0.00000000    0.00665803    0.00399047    0.00665803\n  16     0.00000000    0.00928448    0.00032410    0.00928448\n  17     0.00000000    0.02498584    0.00280302    0.02498584\n  18     0.00352236    0.01252347    0.00802997    0.00900111\n  19     0.00000000    0.01192185    0.00042997    0.01192185\n  20     0.00000000    0.01555842    0.00202393    0.01555842\n  21     0.00000000    0.00651859    0.00394164    0.00651859\n  22     0.00000000    0.00382338    0.00014615    0.00382338\n  23     0.00000000    0.02344629    0.00250385    0.02344629\n  24     0.00351299    0.01243332    0.00798114    0.00892033\n  25     0.00000000    0.00867873    0.00022911    0.00867873\n  26     0.00000000    0.01071420    0.00169575    0.01071420\n  27     0.00000000    0.00638443    0.00387839    0.00638443\n  28     0.00000000    0.00175837    0.00006004    0.00175837\n  29     0.00000000    0.02109576    0.00231908    0.02109576\n  30     0.00350470    0.01233977    0.00794786    0.00883507\n  31     0.00000000    0.00469998    0.00006919    0.00469998\n  32     0.00000000    0.01070123    0.00135740    0.01070123\n  33     0.00000000    0.00633887    0.00375782    0.00633887\n  34     0.00000000    0.00094265    0.00002301    0.00094265\n  35     0.00000000    0.01713776    0.00211168    0.01713776\n  36     0.00347687    0.01215547    0.00788315    0.00867860\n -------------------------------------------------------------\n eshortmin from scaling.data:        -0.2691374625\n eshortmax from scaling.data:        -0.2381480047\n -------------------------------------------------------------\n -------------------------------------------------------------\n NN sum of free atom energies,short range and electrostatic energy for configuration         1\n NN sum of free atom energies         0.00000000 Ha\n NN short range energy             -381.61079700 Ha\n NN electrostatic energy             -0.00001574 Ha\n NN vdw dispersion energy             0.00000000 Ha\n NNenergy                          -381.61081274 Ha\n -------------------------------------------------------------\n NN atomenergies with configuration            1\nNNatomenergy      1 C      -37.952909\nNNatomenergy      2 C      -37.919421\nNNatomenergy      3 H       -0.880328\nNNatomenergy      4 C      -38.022413\nNNatomenergy      5 C      -38.018132\nNNatomenergy      6 C      -38.020613\nNNatomenergy      7 C      -38.009915\nNNatomenergy      8 C      -38.018981\nNNatomenergy      9 C      -38.012933\nNNatomenergy     10 C      -37.952059\nNNatomenergy     11 C      -37.922947\nNNatomenergy     12 H       -0.880147\n -------------------------------------------------------------\n NNcharges for configuration            1\n NNcharge      1   -0.03245864\n NNcharge      2   -0.05614178\n NNcharge      3    0.10294145\n NNcharge      4   -0.00715563\n NNcharge      5    0.00083433\n NNcharge      6   -0.00235997\n NNcharge      7   -0.00849072\n NNcharge      8   -0.01053411\n NNcharge      9    0.00081462\n NNcharge     10   -0.02834599\n NNcharge     11   -0.06064734\n NNcharge     12    0.10154379\n -------------------------------------------------------------\n NN forces for the configuration            1\n NNforces      1     -0.03084848      0.00994372      0.02035300 Ha/Bohr\n NNforces      2      0.03575321     -0.00812376     -0.02060840 Ha/Bohr\n NNforces      3      0.00817873      0.00018015      0.00264405 Ha/Bohr\n NNforces      4     -0.03267242      0.01204150     -0.00185729 Ha/Bohr\n NNforces      5      0.03596400     -0.01308899     -0.00394444 Ha/Bohr\n NNforces      6      0.03510320     -0.00092789      0.01613691 Ha/Bohr\n NNforces      7     -0.02021497      0.00168076     -0.00075111 Ha/Bohr\n NNforces      8     -0.01645840     -0.00579815     -0.01639606 Ha/Bohr\n NNforces      9      0.00292959     -0.00079391      0.01370348 Ha/Bohr\n NNforces     10      0.01224082      0.01734497     -0.01609327 Ha/Bohr\n NNforces     11     -0.02441314     -0.00593162      0.01477905 Ha/Bohr\n NNforces     12     -0.00556215     -0.00652678     -0.00796590 Ha/Bohr\n -------------------------------------------------------------\n -------------------------------------------------------------\n  extrapolation warnings for configuration         1\n           extrapolation warnings (energy)         0\nextrapolation warnings (symmetry functions         0\n -------------------------------------------------------------\n Total runtime (s)  :          0.014\n Total runtime (min):          0.000\n Total runtime (h)  :          0.000\n Normal termination of RuNNer\n -------------------------------------------------------------\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/hardness.001.data",
    "content": "      0.0088953312\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/hardness.006.data",
    "content": "      0.0661189426\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/input.data",
    "content": "begin\ncomment \natom  -8.6089840636623833E+00   1.1721101618520001E-01   9.8323591084281514E-02  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom  -1.0887890663537627E+01   4.1179249277052421E-01   6.9490967680382398E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom  -1.2930485451086453E+01   5.2506382642642058E-01   7.2809053422821779E-01  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom  -3.6915315204094927E+00  -3.3414993292840278E-01  -2.1088572536199013E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom  -6.0680299107700124E+00  -2.5620260955245030E-03  -7.0543207699589230E-02  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   1.1729073318400078E+00  -1.7250595988097372E-01  -6.6741810230359422E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom  -1.1595817453608341E+00  -3.5063784106789647E-01  -4.6759951235815161E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   3.7259094240411681E+00  -8.3808446129817402E-02  -2.2980808620118351E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   6.0775914248949645E+00  -1.6674672212588620E-01  -1.4499820679122288E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   8.5916667587931013E+00  -8.0658783933167305E-02   4.0220650606187225E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   1.0870494591100982E+01   5.1580223738887498E-01   4.3585444122535055E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   1.2661796981509699E+01   1.1948282077976258E+00   1.1689054257962741E+00  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/input.data-org",
    "content": "begin\ncomment \natom  -8.6089840636623833E+00   1.1721101618520001E-01   9.8323591084281514E-02  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom  -1.0887890663537627E+01   4.1179249277052421E-01   6.9490967680382398E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom  -1.2930485451086453E+01   5.2506382642642058E-01   7.2809053422821779E-01  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom  -3.6915315204094927E+00  -3.3414993292840278E-01  -2.1088572536199013E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom  -6.0680299107700124E+00  -2.5620260955245030E-03  -7.0543207699589230E-02  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   1.1729073318400078E+00  -1.7250595988097372E-01  -6.6741810230359422E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom  -1.1595817453608341E+00  -3.5063784106789647E-01  -4.6759951235815161E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   3.7259094240411681E+00  -8.3808446129817402E-02  -2.2980808620118351E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   6.0775914248949645E+00  -1.6674672212588620E-01  -1.4499820679122288E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   8.5916667587931013E+00  -8.0658783933167305E-02   4.0220650606187225E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   1.0870494591100982E+01   5.1580223738887498E-01   4.3585444122535055E-01  C   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\natom   1.2661796981509699E+01   1.1948282077976258E+00   1.1689054257962741E+00  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00\nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/input.nn",
    "content": "## #############################################################\n### This is the input file for RuNNer \n### #############################################################\n### General remarks: \n### - commands can be switched off by using the # character at the BEGINNING of the line\n### - the input file can be structured by blank lines and comment lines\n### - the order of the keywords is arbitrary\n### - if keywords are missing, default values will be used and written to runner.out\n### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message \n\n### THIS INPUT.NN IS AN EXAMPLE, IT IS NOT A REALISTIC CASE\n### It contains only a subset of all keywords\n\n########################################################################################################################\n### general keywords\n########################################################################################################################\nuse_electrostatics\nuse_short_nn\nnnp_gen 4 # nnp_type_gen --> nnp_gen \nrunner_mode 3\nparallel_mode 1                         \nnumber_of_elements 2                  \nelements  C H                          \nrandom_seed 10                         \nrandom_number_type 5                      \nremove_atom_energies                     \natom_energy H -0.458907306351869\natom_energy C -37.748111931202914\ninitial_hardness H 10.0 ## fixed_atomhardness--> initial_hardness \ninitial_hardness C 10.0 \nfixed_gausswidth H 0.585815056466\nfixed_gausswidth C 1.379499971678\nenergy_threshold 100.0d0              \nbond_threshold 0.4d0                 \newald_prec 1.0e-6 # for optimal combination of ewald parameters\nscreen_electrostatics 4.8 8.0\n########################################################################################################################\n### NN structure of the electrostatic-range NN  \n########################################################################################################################\nglobal_hidden_layers_electrostatic 2              \nglobal_nodes_electrostatic 15 15                 \nglobal_activation_electrostatic t t l            \nglobal_hidden_layers_short 2              \nglobal_nodes_short 10 10                 \nglobal_activation_short t t l            \n## element_hidden_layers_electrostatic needs to take care !!! should check the output  \n########################################################################################################################\n### symmetry function generation ( mode 1): \n########################################################################################################################\ntest_fraction 0.1      \n\n########################################################################################################################\n### symmetry function definitions (all modes): \n########################################################################################################################\ncutoff_type 2\n\n\n# radial H H\nsymfunction H  2  H 0.000000      0.000000      8.000000  \nsymfunction H  2  H 0.006000      0.000000      8.000000  \nsymfunction H  2  H 0.011000      0.000000      8.000000  \nsymfunction H  2  H 0.018000      0.000000      8.000000  \nsymfunction H  2  H 0.026000      0.000000      8.000000  \nsymfunction H  2  H 0.035000      0.000000      8.000000  \n\n#radial C H\nsymfunction C  2  H 0.000000      0.000000      8.000000  \nsymfunction C  2  H 0.013000      0.000000      8.000000  \nsymfunction C  2  H 0.029000      0.000000      8.000000  \nsymfunction C  2  H 0.054000      0.000000      8.000000  \nsymfunction C  2  H 0.093000      0.000000      8.000000  \nsymfunction C  2  H 0.161000      0.000000      8.000000  \n\nsymfunction H  2  C 0.000000      0.000000      8.000000  \nsymfunction H  2  C 0.013000      0.000000      8.000000  \nsymfunction H  2  C 0.029000      0.000000      8.000000  \nsymfunction H  2  C 0.054000      0.000000      8.000000  \nsymfunction H  2  C 0.093000      0.000000      8.000000  \nsymfunction H  2  C 0.161000      0.000000      8.000000  \n\n# radial C C \nsymfunction C  2  C 0.000000      0.000000      8.000000\nsymfunction C  2  C 0.010000      0.000000      8.000000\nsymfunction C  2  C 0.023000      0.000000      8.000000\nsymfunction C  2  C 0.041000      0.000000      8.000000\nsymfunction C  2  C 0.065000      0.000000      8.000000\nsymfunction C  2  C 0.103000      0.000000      8.000000\n\n\n#\n# angular\n\nsymfunction C 3 C C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction C 3 H H 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction C 3 C H 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\n\nsymfunction H 3 C C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 C C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 C C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction H 3 H C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 H C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 H C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\n\n########################################################################################################################\n### fitting (mode 2):general inputs for electrostatic range AND electrostatic part:\n########################################################################################################################\nepochs 10                          \npoints_in_memory 500                \nmix_all_points                       \nscale_symmetry_functions             \ncenter_symmetry_functions             \nfitting_unit  eV                      \n########################################################################################################################\n### fitting options ( mode 2): electrostatic range part only:\n########################################################################################################################\noptmode_short_energy 1                 \noptmode_short_force 1                   \nshort_energy_error_threshold 0.8\t \nshort_force_error_threshold 0.8\t\t \nkalman_lambda_charge 0.98000                \nkalman_nue_charge 0.99870                   \nkalman_lambda_short 0.98000                \nkalman_nue_short 0.99870                   \n#use_old_weights_electrostatic               \n#force_update_scaling -1.0d0          \n#electrostatic_energy_group 1         \n#electrostatic_energy_fraction 1.00           \n#electrostatic_force_group 1                 \n\nshort_force_fraction 0.025            \nuse_short_forces                    \nweights_min -1.0                 \nweights_max 1.0                  \nprecondition_weights            \nrepeated_energy_update          \nnguyen_widrow_weights_short     \nregularize_fit_param 0.00001 ## 4G cases L2 regularization \n########################################################################################################################\n### output options for mode 2 (fitting):  \n########################################################################################################################\nwrite_trainpoints              \nwrite_trainforces      \n#write_traincharges\n########################################################################################################################\n### output options for mode 3 (prediction):  \n########################################################################################################################\ncalculate_forces     \n#calculate_stress       \n\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/nnatoms.out",
    "content": "################################################################################\n# Energy contributions calculated from NNP.\n################################################################################\n# Col  Name      Description\n################################################################################\n# 1    conf      Configuration index (starting with 1).\n# 2    index     Atom index (starting with 1).\n# 3    Z         Nuclear charge of atom.\n# 4    Qref      Reference atomic charge.\n# 5    Qnnp      NNP atomic charge.\n# 6    Eref_atom Reference atomic energy contribution.\n# 7    Ennp_atom Atomic energy contribution (physical units, no mean or offset energy added).\n#############################################################################################################################\n#        1          2   3                        4                        5                        6                        7\n#     conf      index   Z                     Qref                     Qnnp                Eref_atom                Ennp_atom\n#############################################################################################################################\n         1          1   6   0.0000000000000000E+00  -3.2458644274754651E-02   0.0000000000000000E+00  -2.0479710438970580E-01\n         1          2   6   0.0000000000000000E+00  -5.6141778584216068E-02   0.0000000000000000E+00  -1.7130864053608713E-01\n         1          3   1   0.0000000000000000E+00   1.0294145062705674E-01   0.0000000000000000E+00  -4.2142060824865357E-01\n         1          4   6   0.0000000000000000E+00  -7.1556348953342435E-03   0.0000000000000000E+00  -2.7430064475745047E-01\n         1          5   6   0.0000000000000000E+00   8.3432748292313285E-04   0.0000000000000000E+00  -2.7002047650869254E-01\n         1          6   6   0.0000000000000000E+00  -2.3599719595358937E-03   0.0000000000000000E+00  -2.7250138971765969E-01\n         1          7   6   0.0000000000000000E+00  -8.4907158646713859E-03   0.0000000000000000E+00  -2.6180345487358536E-01\n         1          8   6   0.0000000000000000E+00  -1.0534113290044665E-02   0.0000000000000000E+00  -2.7086885868262611E-01\n         1          9   6   0.0000000000000000E+00   8.1462340324302566E-04   0.0000000000000000E+00  -2.6482089673470777E-01\n         1         10   6   0.0000000000000000E+00  -2.8345993789409479E-02   0.0000000000000000E+00  -2.0394673774174502E-01\n         1         11   6   0.0000000000000000E+00  -6.0647343034107404E-02   0.0000000000000000E+00  -1.7483492203211570E-01\n         1         12   1   0.0000000000000000E+00   1.0154379417885089E-01   0.0000000000000000E+00  -4.2123934102023231E-01\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/nnforces.out",
    "content": "################################################################################\n# Atomic force comparison (ordered by atom index).\n################################################################################\n# Col  Name  Description\n################################################################################\n# 1    conf  Configuration index (starting with 1).\n# 2    index Atom index (starting with 1).\n# 3    fxRef Reference force in x direction.\n# 4    fyRef Reference force in y direction.\n# 5    fzRef Reference force in z direction.\n# 6    fx    Force in x direction.\n# 7    fy    Force in y direction.\n# 8    fz    Force in z direction.\n###########################################################################################################################################################################\n#        1          2                        3                        4                        5                        6                        7                        8\n#     conf      index                    fxRef                    fyRef                    fzRef                       fx                       fy                       fz\n###########################################################################################################################################################################\n         1          1   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00  -3.0848483621290768E-02   9.9437229539220684E-03   2.0352999337438824E-02\n         1          2   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   3.5753209472753004E-02  -8.1237628180204809E-03  -2.0608404213202990E-02\n         1          3   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   8.1787276673429710E-03   1.8014717534816583E-04   2.6440476603640309E-03\n         1          4   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00  -3.2672415145898345E-02   1.2041500311444986E-02  -1.8572895160292656E-03\n         1          5   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   3.5963999960799249E-02  -1.3088993906111521E-02  -3.9444423243935513E-03\n         1          6   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   3.5103202289331878E-02  -9.2789354753794961E-04   1.6136905570554479E-02\n         1          7   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00  -2.0214969739033205E-02   1.6807648404055854E-03  -7.5111141444395750E-04\n         1          8   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00  -1.6458402959242311E-02  -5.7981475984617377E-03  -1.6396064514211335E-02\n         1          9   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   2.9295943813836588E-03  -7.9390824921095359E-04   1.3703484666740151E-02\n         1         10   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   1.2240824229741747E-02   1.7344969704443759E-02  -1.6093273578742517E-02\n         1         11   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00  -2.4413138020654052E-02  -5.9316238120533807E-03   1.4779052720039060E-02\n         1         12   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00  -5.5621485152346096E-03  -6.5267750541684114E-03  -7.9659043941128650E-03\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/nnp-predict.log",
    "content": "\n*******************************************************************************\n\nWELCOME TO n²p², A SOFTWARE PACKAGE FOR NEURAL NETWORK POTENTIALS!\n------------------------------------------------------------------\n\nn²p² version      : v2.1.1-62-g8827e5b\n------------------------------------------------------------\nGit branch        : 4G-HDNNP-prediction\nGit revision      : 8827e5b707e89d6fef99548e0a4d5d9571739766\nCompile date/time : Jun 23 2021 19:31:05\n------------------------------------------------------------\n\nPlease cite the following papers when publishing results obtained with n²p²:\n-------------------------------------------------------------------------------\n * General citation for n²p² and the LAMMPS interface:\n\n Singraber, A.; Behler, J.; Dellago, C.\n Library-Based LAMMPS Implementation of High-Dimensional\n Neural Network Potentials.\n J. Chem. Theory Comput. 2019 15 (3), 1827–1840.\n https://doi.org/10.1021/acs.jctc.8b00770\n-------------------------------------------------------------------------------\n * Additionally, if you use the NNP training features of n²p²:\n\n Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C.\n Parallel Multistream Training of High-Dimensional Neural\n Network Potentials.\n J. Chem. Theory Comput. 2019, 15 (5), 3075–3092.\n https://doi.org/10.1021/acs.jctc.8b01092\n-------------------------------------------------------------------------------\n * Additionally, if polynomial symmetry functions are used:\n\n Bircher, M. P.; Singraber, A.; Dellago, C.\n Improved Description of Atomic Environments Using Low-Cost\n Polynomial Functions with Compact Support.\n arXiv:2010.14414 [cond-mat, physics:physics] 2020.\n https://arxiv.org/abs/2010.14414\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 185 lines.\nWARNING: Unknown keyword \"bond_threshold\" at line 34.\nWARNING: Unknown keyword \"calculate_forces\" at line 183.\nWARNING: Unknown keyword \"energy_threshold\" at line 33.\nWARNING: Unknown keyword \"fitting_unit\" at line 148.\nWARNING: Unknown keyword \"kalman_lambda_charge\" at line 156.\nWARNING: Unknown keyword \"kalman_nue_charge\" at line 157.\nWARNING: Unknown keyword \"mix_all_points\" at line 145.\nWARNING: Unknown keyword \"optmode_short_energy\" at line 152.\nWARNING: Unknown keyword \"optmode_short_force\" at line 153.\nWARNING: Unknown keyword \"points_in_memory\" at line 144.\nWARNING: Unknown keyword \"random_number_type\" at line 25.\nWARNING: Unknown keyword \"regularize_fit_param\" at line 173.\nWARNING: Unknown keyword \"remove_atom_energies\" at line 26.\nWARNING: Unknown keyword \"runner_mode\" at line 20.\nWARNING: Unknown keyword \"use_electrostatics\" at line 17.\nWARNING: Unknown keyword \"use_short_nn\" at line 18.\nWARNING: 16 problems detected (0 critical).\nFound 113 lines with keywords.\nThis settings file defines a NNP with electrostatics and\nnon-local charge transfer (4G-HDNNP).\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is not used.\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  H (  1)\nElement  1:  C (  6)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:  -4.58907306E-01\nElement  1:  -3.77481119E+01\nEnergy offsets are automatically subtracted from reference energies.\n*******************************************************************************\n\n*** SETUP: ELECTROSTATICS *****************************************************\n\nAtomic hardness file name format: hardness.%03zu.data\nAtomic hardness for element  H from file hardness.001.data:   8.89533120E-03\nAtomic hardness for element  C from file hardness.006.data:   6.61189426E-02\n\nGaussian width of charge distribution per element:\nElement  0:   5.85815056E-01\nElement  1:   1.37949997E+00\n\nEwald precision:   1.00000000E-06\n\nScreening function information:\nInner radius :   4.80000000E+00\nOuter radius :   8.00000000E+00\nTransition region functional form:\nx     := (r - inner) / (outer - inner)\nfs(x) := 1 - f(x)\nCoreFunction::Type::COS (0):\nf(x) := 1/2 * (cos(pi*x) + 1)\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_TANHU (2)\nf(r) = tanh^3(1 - r/rc)\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\ntp ..... Symmetry function type.\nsbtp ... Symmetry function subtype (e.g. cutoff type).\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs/rl... Shift distance of Gaussian or left cutoff radius for polynomial.\nangl.... Left cutoff angle for polynomial.\nangr.... Right cutoff angle for polynomial.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius / right cutoff radius for polynomial.\na ...... Free parameter alpha (e.g. cutoff alpha).\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  H :\n-------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln\n-------------------------------------------------------------------------------------------------\n   1  H  2  ct2  H    0.000E+00  0.000E+00  8.000E+00                       0.00    59\n   2  H  2  ct2  C    0.000E+00  0.000E+00  8.000E+00                       0.00    74\n   3  H  2  ct2  H    6.000E-03  0.000E+00  8.000E+00                       0.00    60\n   4  H  2  ct2  H    1.100E-02  0.000E+00  8.000E+00                       0.00    61\n   5  H  2  ct2  C    1.300E-02  0.000E+00  8.000E+00                       0.00    75\n   6  H  2  ct2  H    1.800E-02  0.000E+00  8.000E+00                       0.00    62\n   7  H  2  ct2  H    2.600E-02  0.000E+00  8.000E+00                       0.00    63\n   8  H  2  ct2  C    2.900E-02  0.000E+00  8.000E+00                       0.00    76\n   9  H  2  ct2  H    3.500E-02  0.000E+00  8.000E+00                       0.00    64\n  10  H  2  ct2  C    5.400E-02  0.000E+00  8.000E+00                       0.00    77\n  11  H  2  ct2  C    9.300E-02  0.000E+00  8.000E+00                       0.00    78\n  12  H  2  ct2  C    1.610E-01  0.000E+00  8.000E+00                       0.00    79\n  13  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   134\n  14  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   125\n  15  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   130\n  16  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   121\n  17  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   135\n  18  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   126\n  19  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   131\n  20  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   122\n  21  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   132\n  22  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   123\n  23  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   133\n  24  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   124\n-------------------------------------------------------------------------------------------------\nShort range atomic symmetry functions element  C :\n-------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln\n-------------------------------------------------------------------------------------------------\n   1  C  2  ct2  H    0.000E+00  0.000E+00  8.000E+00                       0.00    67\n   2  C  2  ct2  C    0.000E+00  0.000E+00  8.000E+00                       0.00    82\n   3  C  2  ct2  C    1.000E-02  0.000E+00  8.000E+00                       0.00    83\n   4  C  2  ct2  H    1.300E-02  0.000E+00  8.000E+00                       0.00    68\n   5  C  2  ct2  C    2.300E-02  0.000E+00  8.000E+00                       0.00    84\n   6  C  2  ct2  H    2.900E-02  0.000E+00  8.000E+00                       0.00    69\n   7  C  2  ct2  C    4.100E-02  0.000E+00  8.000E+00                       0.00    85\n   8  C  2  ct2  H    5.400E-02  0.000E+00  8.000E+00                       0.00    70\n   9  C  2  ct2  C    6.500E-02  0.000E+00  8.000E+00                       0.00    86\n  10  C  2  ct2  H    9.300E-02  0.000E+00  8.000E+00                       0.00    71\n  11  C  2  ct2  C    1.030E-01  0.000E+00  8.000E+00                       0.00    87\n  12  C  2  ct2  H    1.610E-01  0.000E+00  8.000E+00                       0.00    72\n  13  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   106\n  14  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   115\n  15  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00    97\n  16  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   102\n  17  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   111\n  18  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00    93\n  19  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   107\n  20  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   116\n  21  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00    98\n  22  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   103\n  23  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   112\n  24  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00    94\n  25  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  4.0 0.00   108\n  26  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  4.0 0.00   117\n  27  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  4.0 0.00    99\n  28  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   104\n  29  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   113\n  30  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00    95\n  31  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  8.0 0.00   109\n  32  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  8.0 0.00   118\n  33  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  8.0 0.00   100\n  34  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   105\n  35  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   114\n  36  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00    96\n-------------------------------------------------------------------------------------------------\nMinimum cutoff radius for element  H: 8.000000\nMinimum cutoff radius for element  C: 8.000000\nMaximum cutoff radius (global)      : 8.000000\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION MEMORY *******************************************\n\nSymmetry function derivatives memory table for element  H :\n-------------------------------------------------------------------------------\nRelevant symmetry functions for neighbors with element:\n-  H:   12 of   24 ( 50.0 )\n-  C:   18 of   24 ( 75.0 )\n-------------------------------------------------------------------------------\nSymmetry function derivatives memory table for element  C :\n-------------------------------------------------------------------------------\nRelevant symmetry functions for neighbors with element:\n-  H:   22 of   36 ( 61.1 )\n-  C:   22 of   36 ( 61.1 )\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION CACHE ********************************************\n\nElement  H: in total 4 caches, used 15.00 times on average.\nElement  C: in total 4 caches, used 22.00 times on average.\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\ntp ..... Symmetry function type.\nsbtp ... Symmetry function subtype (e.g. cutoff type).\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs/rl... Shift distance of Gaussian or left cutoff radius for polynomial.\nangl.... Left cutoff angle for polynomial.\nangr.... Right cutoff angle for polynomial.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius / right cutoff radius for polynomial.\na ...... Free parameter alpha (e.g. cutoff alpha).\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  H :\n----------------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln   mi  sfi e\n----------------------------------------------------------------------------------------------------------\n   1  H  2  ct2  H            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    59    1    1  \n   -  -  -    -  -    6.000E-03  0.000E+00          -                          -    60    2    3  \n   -  -  -    -  -    1.100E-02  0.000E+00          -                          -    61    3    4  \n   -  -  -    -  -    1.800E-02  0.000E+00          -                          -    62    4    6  \n   -  -  -    -  -    2.600E-02  0.000E+00          -                          -    63    5    7  \n   -  -  -    -  -    3.500E-02  0.000E+00          -                          -    64    6    9  \n   2  H  2  ct2  C            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    74    1    2  \n   -  -  -    -  -    1.300E-02  0.000E+00          -                          -    75    2    5  \n   -  -  -    -  -    2.900E-02  0.000E+00          -                          -    76    3    8  \n   -  -  -    -  -    5.400E-02  0.000E+00          -                          -    77    4   10  \n   -  -  -    -  -    9.300E-02  0.000E+00          -                          -    78    5   11  \n   -  -  -    -  -    1.610E-01  0.000E+00          -                          -    79    6   12  \n   3  H  3  ct2  H  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   134    1   13 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   130    2   15 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   135    3   17 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   131    4   19 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   132    5   21 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   133    6   23 0\n   4  H  3  ct2  C  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   125    1   14 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   121    2   16 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   126    3   18 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   122    4   20 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   123    5   22 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   124    6   24 0\n----------------------------------------------------------------------------------------------------------\nShort range atomic symmetry function groups element  C :\n----------------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln   mi  sfi e\n----------------------------------------------------------------------------------------------------------\n   1  C  2  ct2  H            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    67    1    1  \n   -  -  -    -  -    1.300E-02  0.000E+00          -                          -    68    2    4  \n   -  -  -    -  -    2.900E-02  0.000E+00          -                          -    69    3    6  \n   -  -  -    -  -    5.400E-02  0.000E+00          -                          -    70    4    8  \n   -  -  -    -  -    9.300E-02  0.000E+00          -                          -    71    5   10  \n   -  -  -    -  -    1.610E-01  0.000E+00          -                          -    72    6   12  \n   2  C  2  ct2  C            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    82    1    2  \n   -  -  -    -  -    1.000E-02  0.000E+00          -                          -    83    2    3  \n   -  -  -    -  -    2.300E-02  0.000E+00          -                          -    84    3    5  \n   -  -  -    -  -    4.100E-02  0.000E+00          -                          -    85    4    7  \n   -  -  -    -  -    6.500E-02  0.000E+00          -                          -    86    5    9  \n   -  -  -    -  -    1.030E-01  0.000E+00          -                          -    87    6   11  \n   3  C  3  ct2  H  H         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   106    1   13 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   102    2   16 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   107    3   19 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   103    4   22 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  4.0    -   108    5   25 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   104    6   28 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  8.0    -   109    7   31 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   105    8   34 0\n   4  C  3  ct2  H  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   115    1   14 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   111    2   17 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   116    3   20 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   112    4   23 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  4.0    -   117    5   26 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   113    6   29 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  8.0    -   118    7   32 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   114    8   35 0\n   5  C  3  ct2  C  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -    97    1   15 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -    93    2   18 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -    98    3   21 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -    94    4   24 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  4.0    -    99    5   27 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -    95    6   30 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  8.0    -   100    7   33 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -    96    8   36 0\n----------------------------------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic electronegativity NN for element  H :\nNumber of weights    :    600\nNumber of biases     :     31\nNumber of connections:    631\nArchitecture       24   15   15    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n-------------------------------------------------------------------------------\nAtomic electronegativity NN for element  C :\nNumber of weights    :    780\nNumber of biases     :     31\nNumber of connections:    811\nArchitecture       36   15   15    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n  25   G            \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  H :\nNumber of weights    :    360\nNumber of biases     :     21\nNumber of connections:    381\nArchitecture       25   10   10    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G            \n  12   G            \n  13   G            \n  14   G            \n  15   G            \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n  25   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  C :\nNumber of weights    :    480\nNumber of biases     :     21\nNumber of connections:    501\nArchitecture       37   10   10    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G            \n  12   G            \n  13   G            \n  14   G            \n  15   G            \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n  25   G            \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n  37   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALECENTER (3)\nGs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\nWARNING: Keyword \"scale_min_short\" not found.\n         Default value for Smin = 0.0.\nWARNING: Keyword \"scale_max_short\" not found.\n         Default value for Smax = 1.0.\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  0.00E+00  1.68E-01  5.14E-02  0.00E+00  5.94E+00  0.00  1.00 3\n   2  3.04E-01  4.17E-01  3.46E-01  0.00E+00  8.85E+00  0.00  1.00 3\n   3  0.00E+00  1.59E-01  4.77E-02  0.00E+00  6.27E+00  0.00  1.00 3\n   4  0.00E+00  1.52E-01  4.48E-02  0.00E+00  6.56E+00  0.00  1.00 3\n   5  2.70E-01  3.77E-01  3.12E-01  0.00E+00  9.35E+00  0.00  1.00 3\n   6  0.00E+00  1.43E-01  4.10E-02  0.00E+00  7.00E+00  0.00  1.00 3\n   7  0.00E+00  1.33E-01  3.71E-02  0.00E+00  7.53E+00  0.00  1.00 3\n   8  2.36E-01  3.37E-01  2.78E-01  0.00E+00  9.97E+00  0.00  1.00 3\n   9  0.00E+00  1.22E-01  3.31E-02  0.00E+00  8.18E+00  0.00  1.00 3\n  10  1.94E-01  2.86E-01  2.36E-01  0.00E+00  1.09E+01  0.00  1.00 3\n  11  1.46E-01  2.31E-01  1.88E-01  0.00E+00  1.18E+01  0.00  1.00 3\n  12  9.43E-02  1.67E-01  1.33E-01  0.00E+00  1.37E+01  0.00  1.00 3\n  13  0.00E+00  3.94E-03  7.66E-04  0.00E+00  2.54E+02  0.00  1.00 3\n  14  0.00E+00  2.18E-03  3.95E-04  0.00E+00  4.59E+02  0.00  1.00 3\n  15  0.00E+00  2.26E-02  6.69E-03  0.00E+00  4.42E+01  0.00  1.00 3\n  16  6.80E-03  1.48E-02  9.85E-03  0.00E+00  1.25E+02  0.00  1.00 3\n  17  0.00E+00  7.54E-04  1.18E-04  0.00E+00  1.33E+03  0.00  1.00 3\n  18  0.00E+00  3.07E-04  3.12E-05  0.00E+00  3.26E+03  0.00  1.00 3\n  19  0.00E+00  2.02E-02  6.04E-03  0.00E+00  4.96E+01  0.00  1.00 3\n  20  6.45E-03  1.30E-02  9.49E-03  0.00E+00  1.53E+02  0.00  1.00 3\n  21  0.00E+00  1.67E-02  5.00E-03  0.00E+00  5.97E+01  0.00  1.00 3\n  22  5.80E-03  1.11E-02  8.84E-03  0.00E+00  1.88E+02  0.00  1.00 3\n  23  0.00E+00  1.27E-02  3.57E-03  0.00E+00  7.90E+01  0.00  1.00 3\n  24  4.42E-03  1.10E-02  7.82E-03  0.00E+00  1.51E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element  C :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  0.00E+00  5.28E-01  8.65E-02  0.00E+00  1.89E+00  0.00  1.00 3\n   2  2.44E-01  5.76E-01  4.78E-01  0.00E+00  3.00E+00  0.00  1.00 3\n   3  2.20E-01  5.27E-01  4.38E-01  0.00E+00  3.26E+00  0.00  1.00 3\n   4  0.00E+00  5.04E-01  7.81E-02  0.00E+00  1.99E+00  0.00  1.00 3\n   5  1.95E-01  4.73E-01  3.93E-01  0.00E+00  3.59E+00  0.00  1.00 3\n   6  0.00E+00  4.75E-01  6.95E-02  0.00E+00  2.11E+00  0.00  1.00 3\n   7  1.66E-01  4.12E-01  3.41E-01  0.00E+00  4.07E+00  0.00  1.00 3\n   8  0.00E+00  4.33E-01  5.90E-02  0.00E+00  2.31E+00  0.00  1.00 3\n   9  1.36E-01  3.48E-01  2.86E-01  0.00E+00  4.72E+00  0.00  1.00 3\n  10  0.00E+00  3.76E-01  4.70E-02  0.00E+00  2.66E+00  0.00  1.00 3\n  11  1.02E-01  2.73E-01  2.22E-01  0.00E+00  5.83E+00  0.00  1.00 3\n  12  0.00E+00  2.93E-01  3.33E-02  0.00E+00  3.41E+00  0.00  1.00 3\n  13  0.00E+00  1.53E-02  6.08E-04  0.00E+00  6.55E+01  0.00  1.00 3\n  14  0.00E+00  2.04E-02  2.32E-03  0.00E+00  4.91E+01  0.00  1.00 3\n  15  0.00E+00  6.66E-03  3.99E-03  0.00E+00  1.50E+02  0.00  1.00 3\n  16  0.00E+00  9.28E-03  3.24E-04  0.00E+00  1.08E+02  0.00  1.00 3\n  17  0.00E+00  2.50E-02  2.80E-03  0.00E+00  4.00E+01  0.00  1.00 3\n  18  3.52E-03  1.25E-02  8.03E-03  0.00E+00  1.11E+02  0.00  1.00 3\n  19  0.00E+00  1.19E-02  4.30E-04  0.00E+00  8.39E+01  0.00  1.00 3\n  20  0.00E+00  1.56E-02  2.02E-03  0.00E+00  6.43E+01  0.00  1.00 3\n  21  0.00E+00  6.52E-03  3.94E-03  0.00E+00  1.53E+02  0.00  1.00 3\n  22  0.00E+00  3.82E-03  1.46E-04  0.00E+00  2.62E+02  0.00  1.00 3\n  23  0.00E+00  2.34E-02  2.50E-03  0.00E+00  4.27E+01  0.00  1.00 3\n  24  3.51E-03  1.24E-02  7.98E-03  0.00E+00  1.12E+02  0.00  1.00 3\n  25  0.00E+00  8.68E-03  2.29E-04  0.00E+00  1.15E+02  0.00  1.00 3\n  26  0.00E+00  1.07E-02  1.70E-03  0.00E+00  9.33E+01  0.00  1.00 3\n  27  0.00E+00  6.38E-03  3.88E-03  0.00E+00  1.57E+02  0.00  1.00 3\n  28  0.00E+00  1.76E-03  6.00E-05  0.00E+00  5.69E+02  0.00  1.00 3\n  29  0.00E+00  2.11E-02  2.32E-03  0.00E+00  4.74E+01  0.00  1.00 3\n  30  3.50E-03  1.23E-02  7.95E-03  0.00E+00  1.13E+02  0.00  1.00 3\n  31  0.00E+00  4.70E-03  6.92E-05  0.00E+00  2.13E+02  0.00  1.00 3\n  32  0.00E+00  1.07E-02  1.36E-03  0.00E+00  9.34E+01  0.00  1.00 3\n  33  0.00E+00  6.34E-03  3.76E-03  0.00E+00  1.58E+02  0.00  1.00 3\n  34  0.00E+00  9.43E-04  2.30E-05  0.00E+00  1.06E+03  0.00  1.00 3\n  35  0.00E+00  1.71E-02  2.11E-03  0.00E+00  5.84E+01  0.00  1.00 3\n  36  3.48E-03  1.22E-02  7.88E-03  0.00E+00  1.15E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORK WEIGHTS *********************************************\n\nElectronegativity weight file name format: weightse.%03zu.data\nSetting weights for element  H from file: weightse.001.data\nSetting weights for element  C from file: weightse.006.data\nShort range weight file name format: weights.%03zu.data\nSetting weights for element  H from file: weights.001.data\nSetting weights for element  C from file: weights.006.data\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 1\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** PREDICTION ****************************************************************\n\nReading structure file...\nStructure contains 12 atoms (2 elements).\nCalculating NNP prediction...\nAtom     0 ( C) chi:  -1.46685182E-01\nAtom     1 ( C) chi:  -1.62299217E-01\nAtom     2 ( H) chi:  -2.28364737E-01\nAtom     3 ( C) chi:  -1.49331912E-01\nAtom     4 ( C) chi:  -1.48572339E-01\nAtom     5 ( C) chi:  -1.50034638E-01\nAtom     6 ( C) chi:  -1.49457838E-01\nAtom     7 ( C) chi:  -1.49032144E-01\nAtom     8 ( C) chi:  -1.48516264E-01\nAtom     9 ( C) chi:  -1.46835351E-01\nAtom    10 ( C) chi:  -1.60732085E-01\nAtom    11 ( H) chi:  -2.25971939E-01\nSolve relative error:   4.19968408E-16\nAtom     0 ( C) q:  -3.24586443E-02\nAtom     1 ( C) q:  -5.61417786E-02\nAtom     2 ( H) q:   1.02941451E-01\nAtom     3 ( C) q:  -7.15563490E-03\nAtom     4 ( C) q:   8.34327483E-04\nAtom     5 ( C) q:  -2.35997196E-03\nAtom     6 ( C) q:  -8.49071586E-03\nAtom     7 ( C) q:  -1.05341133E-02\nAtom     8 ( C) q:   8.14623403E-04\nAtom     9 ( C) q:  -2.83459938E-02\nAtom    10 ( C) q:  -6.06473430E-02\nAtom    11 ( H) q:   1.01543794E-01\nTotal charge:   1.38777878E-17 (ref:   0.00000000E+00)\nElectrostatic energy:  -1.57390645E-05\nAtom     0 ( C) energy:  -2.04797104E-01\nAtom     1 ( C) energy:  -1.71308641E-01\nAtom     2 ( H) energy:  -4.21420608E-01\nAtom     3 ( C) energy:  -2.74300645E-01\nAtom     4 ( C) energy:  -2.70020477E-01\nAtom     5 ( C) energy:  -2.72501390E-01\nAtom     6 ( C) energy:  -2.61803455E-01\nAtom     7 ( C) energy:  -2.70868859E-01\nAtom     8 ( C) energy:  -2.64820897E-01\nAtom     9 ( C) energy:  -2.03946738E-01\nAtom    10 ( C) energy:  -1.74834922E-01\nAtom    11 ( H) energy:  -4.21239341E-01\n\n-------------------------------------------------------------------------------\nNNP energy:  -3.81610813E+02\n\nNNP forces:\n         1  C  -3.08484836E-02   9.94372295E-03   2.03529993E-02\n         2  C   3.57532095E-02  -8.12376282E-03  -2.06084042E-02\n         3  H   8.17872767E-03   1.80147175E-04   2.64404766E-03\n         4  C  -3.26724151E-02   1.20415003E-02  -1.85728952E-03\n         5  C   3.59640000E-02  -1.30889939E-02  -3.94444232E-03\n         6  C   3.51032023E-02  -9.27893548E-04   1.61369056E-02\n         7  C  -2.02149697E-02   1.68076484E-03  -7.51111414E-04\n         8  C  -1.64584030E-02  -5.79814760E-03  -1.63960645E-02\n         9  C   2.92959438E-03  -7.93908249E-04   1.37034847E-02\n        10  C   1.22408242E-02   1.73449697E-02  -1.60932736E-02\n        11  C  -2.44131380E-02  -5.93162381E-03   1.47790527E-02\n        12  H  -5.56214852E-03  -6.52677505E-03  -7.96590439E-03\n-------------------------------------------------------------------------------\nWriting output files...\n - energy.out\n - nnatoms.out\n - nnforces.out\nWriting structure with NNP prediction to \"output.data\".\nFinished.\n*******************************************************************************\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/output.data",
    "content": "begin\ncomment \natom  -8.6089840636623833E+00   1.1721101618520001E-01   9.8323591084281514E-02  C  -3.2458644274754651E-02   0.0000000000000000E+00  -3.0848483621290768E-02   9.9437229539220684E-03   2.0352999337438824E-02\natom  -1.0887890663537627E+01   4.1179249277052421E-01   6.9490967680382398E-01  C  -5.6141778584216068E-02   0.0000000000000000E+00   3.5753209472753004E-02  -8.1237628180204809E-03  -2.0608404213202990E-02\natom  -1.2930485451086453E+01   5.2506382642642058E-01   7.2809053422821779E-01  H   1.0294145062705674E-01   0.0000000000000000E+00   8.1787276673429710E-03   1.8014717534816583E-04   2.6440476603640309E-03\natom  -3.6915315204094927E+00  -3.3414993292840278E-01  -2.1088572536199013E-01  C  -7.1556348953342435E-03   0.0000000000000000E+00  -3.2672415145898345E-02   1.2041500311444986E-02  -1.8572895160292656E-03\natom  -6.0680299107700124E+00  -2.5620260955245030E-03  -7.0543207699589230E-02  C   8.3432748292313285E-04   0.0000000000000000E+00   3.5963999960799249E-02  -1.3088993906111521E-02  -3.9444423243935513E-03\natom   1.1729073318400078E+00  -1.7250595988097372E-01  -6.6741810230359422E-01  C  -2.3599719595358937E-03   0.0000000000000000E+00   3.5103202289331878E-02  -9.2789354753794961E-04   1.6136905570554479E-02\natom  -1.1595817453608341E+00  -3.5063784106789647E-01  -4.6759951235815161E-01  C  -8.4907158646713859E-03   0.0000000000000000E+00  -2.0214969739033205E-02   1.6807648404055854E-03  -7.5111141444395750E-04\natom   3.7259094240411681E+00  -8.3808446129817402E-02  -2.2980808620118351E-01  C  -1.0534113290044665E-02   0.0000000000000000E+00  -1.6458402959242311E-02  -5.7981475984617377E-03  -1.6396064514211335E-02\natom   6.0775914248949645E+00  -1.6674672212588620E-01  -1.4499820679122288E-01  C   8.1462340324302566E-04   0.0000000000000000E+00   2.9295943813836588E-03  -7.9390824921095359E-04   1.3703484666740151E-02\natom   8.5916667587931013E+00  -8.0658783933167305E-02   4.0220650606187225E-01  C  -2.8345993789409479E-02   0.0000000000000000E+00   1.2240824229741747E-02   1.7344969704443759E-02  -1.6093273578742517E-02\natom   1.0870494591100982E+01   5.1580223738887498E-01   4.3585444122535055E-01  C  -6.0647343034107404E-02   0.0000000000000000E+00  -2.4413138020654052E-02  -5.9316238120533807E-03   1.4779052720039060E-02\natom   1.2661796981509699E+01   1.1948282077976258E+00   1.1689054257962741E+00  H   1.0154379417885089E-01   0.0000000000000000E+00  -5.5621485152346096E-03  -6.5267750541684114E-03  -7.9659043941128650E-03\nenergy  -3.8161081273904063E+02\ncharge   1.3877787807814457E-17\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/scaling.data",
    "content": "   1    1        0.000000000       0.168474325       0.051436597\n   1    2        0.304058579       0.417104776       0.345915594\n   1    3        0.000000000       0.159465228       0.047693255\n   1    4        0.000000000       0.152326768       0.044784312\n   1    5        0.270367239       0.377289298       0.312242885\n   1    6        0.000000000       0.142866546       0.041009575\n   1    7        0.000000000       0.132772126       0.037086368\n   1    8        0.236241291       0.336573119       0.278003131\n   1    9        0.000000000       0.122265892       0.033122717\n   1   10        0.194043783       0.286076543       0.235857711\n   1   11        0.146413959       0.230979612       0.188000406\n   1   12        0.094328785       0.167444236       0.133300930\n   1   13        0.000000000       0.003940598       0.000766277\n   1   14        0.000000000       0.002179848       0.000395242\n   1   15        0.000000000       0.022615147       0.006688070\n   1   16        0.006799063       0.014786064       0.009854503\n   1   17        0.000000000       0.000754211       0.000118471\n   1   18        0.000000000       0.000307111       0.000031177\n   1   19        0.000000000       0.020171446       0.006040265\n   1   20        0.006447566       0.012997039       0.009490438\n   1   21        0.000000000       0.016749223       0.005002441\n   1   22        0.005799086       0.011113091       0.008844953\n   1   23        0.000000000       0.012662314       0.003565243\n   1   24        0.004417978       0.011019545       0.007821957\n   2    1        0.000000000       0.528085920       0.086499956\n   2    2        0.243551003       0.576397651       0.478191952\n   2    3        0.220486953       0.527469369       0.437635603\n   2    4        0.000000000       0.503534550       0.078079729\n   2    5        0.195097154       0.473305655       0.392510705\n   2    6        0.000000000       0.474879557       0.069517706\n   2    7        0.166254512       0.411783730       0.340934855\n   2    8        0.000000000       0.433337270       0.058978785\n   2    9        0.136220939       0.347964660       0.286400724\n   2   10        0.000000000       0.375671652       0.047011546\n   2   11        0.101581283       0.273092311       0.221977741\n   2   12        0.000000000       0.292877983       0.033333347\n   2   13        0.000000000       0.015267809       0.000607918\n   2   14        0.000000000       0.020367325       0.002323101\n   2   15        0.000000000       0.006658033       0.003990472\n   2   16        0.000000000       0.009284484       0.000324103\n   2   17        0.000000000       0.024985840       0.002803020\n   2   18        0.003522361       0.012523471       0.008029970\n   2   19        0.000000000       0.011921850       0.000429967\n   2   20        0.000000000       0.015558424       0.002023934\n   2   21        0.000000000       0.006518589       0.003941639\n   2   22        0.000000000       0.003823383       0.000146152\n   2   23        0.000000000       0.023446294       0.002503853\n   2   24        0.003512986       0.012433317       0.007981137\n   2   25        0.000000000       0.008678726       0.000229107\n   2   26        0.000000000       0.010714201       0.001695750\n   2   27        0.000000000       0.006384431       0.003878387\n   2   28        0.000000000       0.001758371       0.000060041\n   2   29        0.000000000       0.021095757       0.002319082\n   2   30        0.003504699       0.012339772       0.007947861\n   2   31        0.000000000       0.004699984       0.000069193\n   2   32        0.000000000       0.010701233       0.001357400\n   2   33        0.000000000       0.006338867       0.003757820\n   2   34        0.000000000       0.000942648       0.000023014\n   2   35        0.000000000       0.017137757       0.002111679\n   2   36        0.003476868       0.012155470       0.007883155\n       -0.2691374625       -0.2381480047\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/structure.out",
    "content": "********************************\nSTRUCTURE                       \n********************************\n********************************\nELEMENT MAP                     \n********************************\n--------------------------------\nforwardMap                 [*] : 2\n--------------------------------\n                            C  : 1\n                            H  : 0\n--------------------------------\n--------------------------------\nreverseMap                 [*] : 2\n--------------------------------\n                            0  : H\n                            1  : C\n--------------------------------\n********************************\nindex                          : 0\nisPeriodic                     : 0\nisTriclinic                    : 0\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nnumAtoms                       : 12\nnumElements                    : 2\nnumElementsPresent             : 2\npbc                            : 0 0 0\nenergy                         :  -3.81650775E+02\nenergyRef                      :   0.00000000E+00\ncharge                         :   0.00000000E+00\nchargeRef                      :   0.00000000E+00\nvolume                         :   0.00000000E+00\nsampleType                     : 0\ncomment                        : \nbox[0]                         :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nbox[1]                         :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nbox[2]                         :   0.00000000E+00   0.00000000E+00   0.00000000E+00\ninvbox[0]                      :   0.00000000E+00   0.00000000E+00   0.00000000E+00\ninvbox[1]                      :   0.00000000E+00   0.00000000E+00   0.00000000E+00\ninvbox[2]                      :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nnumAtomsPerElement         [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 10\n--------------------------------\n--------------------------------\natoms                      [*] : 12\n--------------------------------\n                            0  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 0\nindexStructure                 : 0\ntag                            : 0\nelement                        : 1\nnumNeighbors                   : 5\nnumNeighborsUnique             : 6\nnumSymmetryFunctions           : 36\nenergy                         :  -2.08976560E-01\nchi                            :  -1.46685182E-01\ncharge                         :   1.88081199E-03\nchargeRef                      :   0.00000000E+00\nr                              :  -8.60898406E+00   1.17211016E-01   9.83235911E-02\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 6\n--------------------------------\n                            0  : 0\n                            1  : 1\n                            2  : 2\n                            3  : 3\n                            4  : 4\n                            5  : 6\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 1\n                            1  : 4\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 22\n                            1  : 22\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 36\n--------------------------------\n                            0  :  -2.01493731E-02\n                            1  :   3.61112008E-03\n                            2  :   1.91118741E-02\n                            3  :  -3.77455842E-02\n                            4  :   3.57463110E-02\n                            5  :  -5.49519508E-02\n                            6  :   5.30333835E-02\n                            7  :  -7.41584313E-02\n                            8  :   6.74711735E-02\n                            9  :  -9.13975395E-02\n                           10  :   7.65579355E-02\n                           11  :  -1.02114008E-01\n                           12  :  -3.98169770E-02\n                           13  :  -1.09033744E-01\n                           14  :   9.80651355E-02\n                           15  :  -3.49080250E-02\n                           16  :   2.28057313E-01\n                           17  :  -3.94573815E-01\n                           18  :  -3.60654596E-02\n                           19  :  -1.25320463E-01\n                           20  :   9.99259970E-02\n                           21  :  -3.82258330E-02\n                           22  :   2.54587797E-01\n                           23  :  -3.98320053E-01\n                           24  :  -2.63986903E-02\n                           25  :  -1.51388080E-01\n                           26  :   9.70714059E-02\n                           27  :  -3.41458088E-02\n                           28  :   2.89064471E-01\n                           29  :  -3.98949759E-01\n                           30  :  -1.47219650E-02\n                           31  :  -1.20010220E-01\n                           32  :   8.77742095E-02\n                           33  :  -2.44142034E-02\n                           34  :   3.61470030E-01\n                           35  :  -3.99693325E-01\n--------------------------------\n--------------------------------\ndEdG                       [*] : 37\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n                           36  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 36\n--------------------------------\n                            0  :  -1.02909195E-01   9.71232003E-03   1.49968271E-02\n                            1  :   1.37643298E-01   8.34377987E-03   4.03859969E-02\n                            2  :   1.27406037E-01   1.22645062E-02   4.83887718E-02\n                            3  :  -9.72269643E-02   9.17604486E-03   1.41687628E-02\n                            4  :   1.12289771E-01   1.75342890E-02   5.89524361E-02\n                            5  :  -8.84241785E-02   8.34525931E-03   1.28859439E-02\n                            6  :   8.91915484E-02   2.49157980E-02   7.35578732E-02\n                            7  :  -7.32881540E-02   6.91675806E-03   1.06801902E-02\n                            8  :   5.68296697E-02   3.44236314E-02   9.22522507E-02\n                            9  :  -5.12949136E-02   4.84108942E-03   7.47514301E-03\n                           10  :   7.27991096E-03   4.82203389E-02   1.19734232E-01\n                           11  :  -2.46606447E-02   2.32741178E-03   3.59376462E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -4.51126607E-03  -7.67905023E-04  -3.51739913E-03\n                           14  :   3.59917190E-02   3.91801818E-02   1.02045498E-01\n                           15  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           16  :  -3.69899587E-01   4.04103382E-02   7.22733904E-02\n                           17  :   6.37037081E-01  -6.38791030E-02  -7.98892427E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -1.45285039E-03   3.56652913E-04   5.61199619E-04\n                           20  :   4.66748123E-02   6.45005037E-02   1.55912940E-01\n                           21  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           22  :  -3.91233410E-01   4.39675188E-02   8.04469466E-02\n                           23  :   6.50049949E-01  -4.65670502E-02  -4.28439013E-02\n                           24  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           25  :  -2.02371171E-03   7.25970366E-04   1.19261669E-03\n                           26  :   6.81560230E-02   1.08555755E-01   2.61818939E-01\n                           27  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           28  :  -4.28334819E-01   5.07556606E-02   9.67868524E-02\n                           29  :   6.55818816E-01  -4.24081597E-02  -4.27345483E-02\n                           30  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           31  :  -1.92174730E-03   1.11159913E-03   1.84099997E-03\n                           32  :   1.07348421E-01   1.89983897E-01   4.57553255E-01\n                           33  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           34  :  -5.11525828E-01   6.70287436E-02   1.36926552E-01\n                           35  :   6.66284266E-01  -3.45066856E-02  -4.40994961E-02\n--------------------------------\n--------------------------------\nneighbors                  [*] : 5\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 1\ntag                            : 1\nelement                        : 1\nd                              :   2.37404897E+00\ndr                             :   2.27890660E+00  -2.94581477E-01  -5.96586086E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.23011099E-01\n                            1  :  -8.71910841E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   2.51457587E-01  -3.25045121E-02  -6.58281026E-02\n                            1  :   2.88998440E-01  -3.73572077E-02  -7.56557765E-02\n                            2  :   3.38080317E-01  -4.37017467E-02  -8.85047299E-02\n                            3  :   4.05262911E-01  -5.23860638E-02  -1.06092199E-01\n                            4  :   4.90341941E-01  -6.33837530E-02  -1.28364708E-01\n                            5  :   6.14682046E-01  -7.94565011E-02  -1.60915220E-01\n                            6  :   2.82035960E-03   2.63065032E-03   9.22582258E-03\n                            7  :   8.61755883E-01  -9.73314220E-02  -1.91512082E-01\n                            8  :   4.24028708E-03  -1.19631366E-02  -3.90841891E-02\n                            9  :   1.29698030E-02   7.49362382E-03   1.84573216E-02\n                           10  :   2.42741222E-05   2.29202070E-05   8.03320169E-05\n                           11  :   8.62556250E-01  -1.09536474E-01  -2.20547836E-01\n                           12  :   2.08483358E-03  -1.50186518E-02  -4.96115413E-02\n                           13  :   2.01024254E-04   1.64063037E-04   4.00147401E-04\n                           14  :   7.67227636E-10   7.28872973E-10   2.55380377E-09\n                           15  :   8.45499334E-01  -1.31836306E-01  -2.74466166E-01\n                           16  :  -3.03965716E-03  -2.16875086E-02  -7.26588307E-02\n                           17  :   3.60652589E-08   3.64911277E-08   8.85705436E-08\n                           18  :   1.82603085E-19   1.74004570E-19   6.09578252E-19\n                           19  :   7.83933775E-01  -1.70454267E-01  -3.69340079E-01\n                           20  :  -1.66698881E-02  -3.87494094E-02  -1.31711444E-01\n                           21  :   7.62662705E-16   8.73196527E-16   2.11376789E-15\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 2\ntag                            : 2\nelement                        : 0\nd                              :   4.38615145E+00\ndr                             :   4.32150139E+00  -4.07852810E-01  -6.29766943E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   7.58593558E-02\n                            1  :  -5.51579018E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.02909195E-01  -9.71232003E-03  -1.49968271E-02\n                            1  :   9.72269643E-02  -9.17604486E-03  -1.41687628E-02\n                            2  :   8.84241785E-02  -8.34525931E-03  -1.28859439E-02\n                            3  :   7.32881540E-02  -6.91675806E-03  -1.06801902E-02\n                            4  :   5.12949136E-02  -4.84108942E-03  -7.47514301E-03\n                            5  :   2.46606447E-02  -2.32741178E-03  -3.59376462E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   1.31749418E-02  -2.66783475E-03  -6.91423534E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   3.65674308E-01  -2.84755747E-02  -3.32366225E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   1.64381072E-02  -1.38812222E-03  -2.14419476E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   3.89148600E-01  -2.89489883E-02  -3.08356086E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   2.37497764E-02  -2.05950641E-03  -3.15572643E-03\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   4.31374476E-01  -2.90681520E-02  -2.41280217E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   2.35351062E-02  -2.18756673E-03  -3.37332709E-03\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   5.28195716E-01  -2.82793343E-02  -5.21510890E-03\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 3\ntag                            : 3\nelement                        : 1\nd                              :   4.94779513E+00\ndr                             :  -4.91745254E+00   4.51360949E-01   3.09209316E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   4.82411211E-02\n                            1  :  -4.31091524E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.28722292E-01   1.18151046E-02   8.09405513E-03\n                            1  :  -1.21360442E-01   1.11393784E-02   7.63114216E-03\n                            2  :  -1.10035595E-01   1.00998983E-02   6.91903600E-03\n                            3  :  -9.29950743E-02   8.53579056E-03   5.84752839E-03\n                            4  :  -7.08750148E-02   6.50544437E-03   4.45661950E-03\n                            5  :  -4.29595970E-02   3.94315640E-03   2.70129859E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -1.18142812E-02  -1.79736537E-03   1.51764701E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -6.27558686E-01   6.89760655E-02   3.85775736E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -1.12726504E-02   1.12543993E-03   1.20673423E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -6.32661128E-01   7.17646409E-02   3.86759913E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -1.12990120E-02   1.11462218E-03   1.12187999E-03\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -6.37748319E-01   7.68477333E-02   3.86239184E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -1.09686428E-02   1.05009878E-03   9.19593879E-04\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -6.47179677E-01   8.71463673E-02   3.84582287E-02\n--------------------------------\n********************************\n                            3  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 4\ntag                            : 4\nelement                        : 1\nd                              :   2.54937435E+00\ndr                             :  -2.54095415E+00   1.19773042E-01   1.68866799E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.07876779E-01\n                            1  :  -8.54153091E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -2.55773029E-01   1.20563819E-02   1.69981707E-02\n                            1  :  -2.92119167E-01   1.37696311E-02   1.94136634E-02\n                            2  :  -3.38725913E-01   1.59665349E-02   2.25110558E-02\n                            3  :  -4.00765508E-01   1.88908974E-02   2.66340848E-02\n                            4  :  -4.76075205E-01   2.24407731E-02   3.16390186E-02\n                            5  :  -5.78967130E-01   2.72907933E-02   3.84770130E-02\n                            6  :  -1.14840353E-02   8.05089451E-04   1.20581189E-03\n                            7  :  -8.85931592E-01   5.99478034E-02   8.79500085E-02\n                            8  :  -1.50078692E-05   2.83732097E-05   4.74212146E-05\n                            9  :  -1.48093012E-02  -1.30605098E-02   2.22644054E-02\n                           10  :  -1.50095310E-02   1.00854910E-03   1.50266313E-03\n                           11  :  -8.97958412E-01   4.39105298E-02   6.34281627E-02\n                           12  :  -2.35156465E-08   1.21320585E-07   2.03281521E-07\n                           13  :  -9.88306358E-03  -2.58352344E-02   3.17167907E-03\n                           14  :  -2.17260655E-02   1.33353531E-03   1.96310718E-03\n                           15  :  -9.02356345E-01   2.21659290E-02   1.15253465E-02\n                           16  :  -2.23045546E-14   1.12684715E-12   1.89059355E-12\n                           17  :  -1.02919851E-02  -3.49165543E-02   3.50709263E-03\n                           18  :  -2.16133589E-02   1.07596760E-03   1.53232712E-03\n                           19  :  -8.80313553E-01  -2.05797287E-02  -8.91327698E-02\n                           20  :   3.40274389E-24   4.93737081E-23   8.28932263E-23\n                           21  :  -1.11910951E-02  -5.31227746E-02   5.02365828E-03\n--------------------------------\n********************************\n                            4  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 6\ntag                            : 6\nelement                        : 1\nd                              :   7.48550242E+00\ndr                             :  -7.44940232E+00   4.67848857E-01   5.65923103E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.64902175E-04\n                            1  :  -1.54037544E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -4.60556455E-03   2.89245770E-04   3.49879798E-04\n                            1  :  -2.92486800E-03   1.83692072E-04   2.22199084E-04\n                            2  :  -1.60858025E-03   1.01024539E-04   1.22202116E-04\n                            3  :  -6.93876923E-04   4.35779290E-05   5.27130855E-05\n                            4  :  -2.21391497E-04   1.39041703E-05   1.68188745E-05\n                            5  :  -3.52300504E-05   2.21257198E-06   2.67638914E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -1.72835020E-06   8.02114963E-07  -1.07124173E-06\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -7.63889660E-03   4.69923474E-04   5.89941970E-04\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -3.46022072E-10   6.63045295E-10  -4.13630297E-10\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -7.70678167E-03   4.73580711E-04   5.96083513E-04\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -1.77214733E-17   9.88942654E-17  -4.49109853E-17\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -7.77854805E-03   4.76944252E-04   6.03448719E-04\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -5.64792529E-32   7.84307498E-31  -3.48492454E-31\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -7.91349342E-03   4.83092812E-04   6.17609111E-04\n--------------------------------\n********************************\n--------------------------------\n********************************\n                            1  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 1\nindexStructure                 : 0\ntag                            : 1\nelement                        : 1\nnumNeighbors                   : 4\nnumNeighborsUnique             : 5\nnumSymmetryFunctions           : 36\nenergy                         :  -1.75106987E-01\nchi                            :  -1.62299217E-01\ncharge                         :   2.36205007E-02\nchargeRef                      :   0.00000000E+00\nr                              :  -1.08878907E+01   4.11792493E-01   6.94909677E-01\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 5\n--------------------------------\n                            0  : 1\n                            1  : 0\n                            2  : 2\n                            3  : 3\n                            4  : 4\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 1\n                            1  : 3\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 22\n                            1  : 22\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 36\n--------------------------------\n                            0  :   3.13554558E-01\n                            1  :  -6.13101526E-01\n                            2  :  -6.08414464E-01\n                            3  :   3.19049143E-01\n                            4  :  -6.01597639E-01\n                            5  :   3.23762564E-01\n                            6  :  -5.90565392E-01\n                            7  :   3.27926432E-01\n                            8  :  -5.72250240E-01\n                            9  :   3.29493404E-01\n                           10  :  -5.41741712E-01\n                           11  :   3.24877473E-01\n                           12  :  -3.98169770E-02\n                           13  :   3.01203756E-01\n                           14  :  -5.97375803E-01\n                           15  :  -3.49080250E-02\n                           16  :  -1.06926949E-01\n                           17  :  -3.70828590E-01\n                           18  :  -3.60654596E-02\n                           19  :   4.05216917E-01\n                           20  :  -6.04671082E-01\n                           21  :  -3.82258330E-02\n                           22  :  -1.06705044E-01\n                           23  :  -3.70179468E-01\n                           24  :  -2.63986903E-02\n                           25  :   5.95466938E-01\n                           26  :  -6.07475748E-01\n                           27  :  -3.41458088E-02\n                           28  :  -1.09931183E-01\n                           29  :  -3.72935515E-01\n                           30  :  -1.47219650E-02\n                           31  :   5.82700894E-01\n                           32  :  -5.92822030E-01\n                           33  :  -2.44142034E-02\n                           34  :  -1.23217933E-01\n                           35  :  -3.78160034E-01\n--------------------------------\n--------------------------------\ndEdG                       [*] : 37\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n                           36  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 36\n--------------------------------\n                            0  :  -1.70007984E-01   9.42772945E-03   2.76168856E-03\n                            1  :   3.90737210E-01  -4.46304266E-02  -8.76637399E-02\n                            2  :   4.18591771E-01  -4.85985062E-02  -9.60497846E-02\n                            3  :  -1.94032573E-01   1.07600041E-02   3.15195515E-03\n                            4  :   4.54536895E-01  -5.37712212E-02  -1.06891585E-01\n                            5  :  -2.23142661E-01   1.23742932E-02   3.62483292E-03\n                            6  :   5.03372302E-01  -6.08470063E-02  -1.21623517E-01\n                            7  :  -2.67628010E-01   1.48412117E-02   4.34747356E-03\n                            8  :   5.65436730E-01  -6.98487711E-02  -1.40273436E-01\n                            9  :  -3.34641775E-01   1.85574351E-02   5.43607625E-03\n                           10  :   6.60878378E-01  -8.34295930E-02  -1.68248636E-01\n                           11  :  -4.44771860E-01   2.46646580E-02   7.22508046E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   2.59060116E-03  -2.49811984E-02  -8.28134312E-02\n                           14  :   5.51678560E-03   2.63176801E-03   6.54362991E-03\n                           15  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           16  :   5.64234756E-03   1.04142921E-02   3.56273238E-02\n                           17  :   6.54868654E-01  -6.73081513E-02  -1.29166759E-01\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -5.39448891E-03  -4.89103488E-02  -1.63858736E-01\n                           20  :   2.45111326E-05   1.57330357E-05   3.87635833E-05\n                           21  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           22  :   1.82776522E-04   3.42999962E-04   1.17216784E-03\n                           23  :   6.56699132E-01  -6.98704919E-02  -1.35192206E-01\n                           24  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           25  :  -3.21864276E-02  -1.15913096E-01  -3.91522474E-01\n                           26  :   3.38530699E-10   2.57170877E-10   6.35367176E-10\n                           27  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           28  :   9.54236884E-08   1.80519595E-07   6.16606838E-07\n                           29  :   6.54811591E-01  -7.44534505E-02  -1.46216734E-01\n                           30  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           31  :  -7.65770462E-02  -1.97662029E-01  -6.71235117E-01\n                           32  :   4.17314202E-20   3.29973218E-20   8.61904775E-20\n                           33  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           34  :   1.30625672E-14   2.48113559E-14   8.47371260E-14\n                           35  :   6.50089505E-01  -8.36145727E-02  -1.68299334E-01\n--------------------------------\n--------------------------------\nneighbors                  [*] : 4\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 0\ntag                            : 0\nelement                        : 1\nd                              :   2.37404897E+00\ndr                             :  -2.27890660E+00   2.94581477E-01   5.96586086E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.23011099E-01\n                            1  :  -8.71910841E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -2.51457587E-01   3.25045121E-02   6.58281026E-02\n                            1  :  -2.88998440E-01   3.73572077E-02   7.56557765E-02\n                            2  :  -3.38080317E-01   4.37017467E-02   8.85047299E-02\n                            3  :  -4.05262911E-01   5.23860638E-02   1.06092199E-01\n                            4  :  -4.90341941E-01   6.33837530E-02   1.28364708E-01\n                            5  :  -6.14682046E-01   7.94565011E-02   1.60915220E-01\n                            6  :  -4.44155651E-01   5.36071627E-02   1.03611269E-01\n                            7  :  -4.30996326E-03  -5.68937866E-03  -1.37619201E-02\n                            8  :  -1.06082056E-02  -4.05751482E-03  -1.52827395E-02\n                            9  :   2.18137234E-02   1.93247630E-02   4.71426648E-02\n                           10  :  -5.64784352E-01   7.64772644E-02   1.59398807E-01\n                           11  :  -2.48353859E-05  -3.26474056E-05  -7.90845943E-05\n                           12  :  -2.53637369E-04  -1.42846269E-04  -5.17874967E-04\n                           13  :   2.52100185E-02   2.37223903E-02   5.77835183E-02\n                           14  :  -7.73394157E-01   1.28445861E-01   2.97186253E-01\n                           15  :  -4.00209312E-10  -5.23078814E-10  -1.27408726E-09\n                           16  :  -1.08500648E-07  -7.75776014E-08  -2.76329697E-07\n                           17  :   3.18578841E-02   3.24062080E-02   7.87920847E-02\n                           18  :  -6.86913207E-01   1.59984352E-01   4.16653960E-01\n                           19  :  -5.23500132E-20  -6.61054993E-20  -1.68021727E-19\n                           20  :  -1.31996833E-14  -1.08239175E-14  -3.82283904E-14\n                           21  :   4.52519790E-02   4.99153936E-02   1.21150155E-01\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 2\ntag                            : 2\nelement                        : 0\nd                              :   2.04600216E+00\ndr                             :   2.04259479E+00  -1.13271334E-01  -3.31808574E-02\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.52083703E-01\n                            1  :  -8.99285877E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.70007984E-01  -9.42772945E-03  -2.76168856E-03\n                            1  :   1.94032573E-01  -1.07600041E-02  -3.15195515E-03\n                            2  :   2.23142661E-01  -1.23742932E-02  -3.62483292E-03\n                            3  :   2.67628010E-01  -1.48412117E-02  -4.34747356E-03\n                            4  :   3.34641775E-01  -1.85574351E-02  -5.43607625E-03\n                            5  :   4.44771860E-01  -2.46646580E-02  -7.22508046E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   4.52107408E-01  -2.94685414E-02  -2.21743293E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   5.01652345E-03  -6.35336445E-03  -2.03163344E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   5.83898806E-01  -2.86753167E-02   2.61313063E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   7.11728914E-05  -2.00096633E-04  -6.53950490E-04\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   8.25270863E-01  -1.41576059E-02   9.15263916E-02\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   1.30881840E-08  -1.02938026E-07  -3.40255881E-07\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   7.82746046E-01   3.60216879E-02   2.51520280E-01\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   1.37129372E-16  -1.39874310E-14  -4.65086974E-14\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 3\ntag                            : 3\nelement                        : 1\nd                              :   7.29139769E+00\ndr                             :  -7.19635914E+00   7.45942426E-01   9.05795402E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   6.89503784E-04\n                            1  :  -2.90393031E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -8.61081077E-03   8.92558160E-04   1.08383040E-03\n                            1  :  -5.67632622E-03   5.88382606E-04   7.14471038E-04\n                            2  :  -3.27452247E-03   3.39422365E-04   4.12159447E-04\n                            3  :  -1.50725391E-03   1.56235204E-04   1.89715887E-04\n                            4  :  -5.23417910E-04   5.42551612E-05   6.58818614E-05\n                            5  :  -9.49050277E-05   9.83743100E-06   1.19455597E-05\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -4.91205569E-05   6.00901965E-06   3.06755953E-05\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -1.60208158E-02   1.66640591E-03   1.86184484E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -1.92009552E-07   5.08468917E-08   2.01951703E-07\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.61293713E-02   1.67704832E-03   1.85595663E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -3.18965538E-12   1.60051556E-12   7.14449724E-12\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -1.62116913E-02   1.68436177E-03   1.82837416E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -7.94633856E-22   9.91554088E-22   4.92547067E-21\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -1.63563862E-02   1.69711887E-03   1.77049342E-03\n--------------------------------\n********************************\n                            3  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 4\ntag                            : 4\nelement                        : 1\nd                              :   4.89782252E+00\ndr                             :  -4.81986075E+00   4.14354519E-01   7.65452885E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   5.04225616E-02\n                            1  :  -4.41961751E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.30668813E-01   1.12333563E-02   2.07518069E-02\n                            1  :  -1.23917005E-01   1.06529158E-02   1.96795371E-02\n                            2  :  -1.13182055E-01   9.73005207E-03   1.79746958E-02\n                            3  :  -9.66021379E-02   8.30470721E-03   1.53416019E-02\n                            4  :  -7.45713710E-02   6.41076291E-03   1.18428465E-02\n                            5  :  -4.61014270E-02   3.96325446E-03   7.32147091E-03\n                            6  :  -1.05423577E-02   8.42577074E-04   1.37649127E-03\n                            7  :  -1.15770179E-03   3.05160163E-03   7.18761456E-03\n                            8  :  -5.06654366E-05  -3.41278962E-06  -2.82498778E-05\n                            9  :  -6.60661561E-01   4.63169823E-02   8.01622497E-02\n                           10  :  -1.37199644E-02   1.10840113E-03   1.84679788E-03\n                           11  :   5.16262793E-07   1.68635229E-05   4.01190592E-05\n                           12  :  -3.12044816E-07  -5.70596076E-08  -3.42380256E-07\n                           13  :  -6.65779779E-01   4.44710533E-02   7.55527314E-02\n                           14  :  -1.96902784E-02   1.62484113E-03   2.80982938E-03\n                           15  :   6.48682686E-11   2.64307421E-10   6.31575584E-10\n                           16  :  -1.12240202E-11  -3.96699016E-12  -2.12607067E-11\n                           17  :  -6.70457783E-01   4.03628807E-02   6.55962748E-02\n                           18  :  -1.92557930E-02   1.65598887E-03   3.06087741E-03\n                           19  :   1.14132269E-20   3.21166234E-20   7.69057785E-20\n                           20  :  -1.33044515E-20  -7.48087619E-21  -3.81838154E-20\n                           21  :  -6.78985098E-01   3.20020603E-02   4.53786858E-02\n--------------------------------\n********************************\n--------------------------------\n********************************\n                            2  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 2\nindexStructure                 : 0\ntag                            : 2\nelement                        : 0\nnumNeighbors                   : 3\nnumNeighborsUnique             : 4\nnumSymmetryFunctions           : 24\nenergy                         :  -4.32913882E-01\nchi                            :  -2.28364737E-01\ncharge                         :  -2.47466264E-02\nchargeRef                      :   0.00000000E+00\nr                              :  -1.29304855E+01   5.25063826E-01   7.28090534E-01\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 4\n--------------------------------\n                            0  : 2\n                            1  : 0\n                            2  : 1\n                            3  : 4\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 0\n                            1  : 3\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 12\n                            1  : 18\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 24\n--------------------------------\n                            0  :  -3.05308224E-01\n                            1  :  -1.38128282E-01\n                            2  :  -2.99082475E-01\n                            3  :  -2.94001590E-01\n                            4  :  -1.23214015E-01\n                            5  :  -2.87048131E-01\n                            6  :  -2.79323448E-01\n                            7  :  -1.06936697E-01\n                            8  :  -2.70907254E-01\n                            9  :  -8.42806463E-02\n                           10  :  -5.32641768E-02\n                           11  :  -1.90204000E-02\n                           12  :  -1.94457034E-01\n                           13  :  -1.63816412E-01\n                           14  :  -2.95734094E-01\n                           15  :  -1.53889587E-01\n                           16  :  -1.57079385E-01\n                           17  :  -1.00965272E-01\n                           18  :  -2.99446306E-01\n                           19  :  -1.37878109E-01\n                           20  :  -2.98667049E-01\n                           21  :  -6.26634595E-02\n                           22  :  -2.81563307E-01\n                           23  :   8.19657837E-02\n--------------------------------\n--------------------------------\ndEdG                       [*] : 25\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 24\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 24\n--------------------------------\n                            0  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            1  :   1.33207749E+00  -9.38065290E-02  -8.96104350E-02\n                            2  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            3  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            4  :   1.40613456E+00  -9.65377115E-02  -8.55831657E-02\n                            5  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   1.49300512E+00  -9.94769198E-02  -8.02803339E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   1.61188303E+00  -1.02960893E-01  -7.15347971E-02\n                           10  :   1.71576110E+00  -1.04043916E-01  -5.75063539E-02\n                           11  :   1.88047225E+00  -1.08127316E-01  -4.33451302E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   2.46961091E-02  -2.16532484E-02  -6.80613968E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   1.19404239E+00  -9.17036503E-02  -1.05467875E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   9.57706694E-04  -1.31820658E-03  -4.22935575E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   1.44794522E+00  -1.04686467E-01  -1.06162344E-01\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   1.76459657E+00  -1.11639552E-01  -7.62213047E-02\n                           22  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           23  :   1.38878092E+00  -6.25940398E-02   2.42795091E-02\n--------------------------------\n--------------------------------\nneighbors                  [*] : 3\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 0\ntag                            : 0\nelement                        : 1\nd                              :   4.38615145E+00\ndr                             :  -4.32150139E+00   4.07852810E-01   6.29766943E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   7.58593558E-02\n                            1  :  -5.51579018E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 18\n--------------------------------\n                            0  :  -4.80731758E-01   4.53702963E-02   7.00564324E-02\n                            1  :  -4.57876851E-01   4.32133057E-02   6.67258156E-02\n                            2  :  -4.18519582E-01   3.94988621E-02   6.09903304E-02\n                            3  :  -3.45078085E-01   3.25676320E-02   5.02877938E-02\n                            4  :  -2.27870823E-01   2.15058951E-02   3.32073274E-02\n                            5  :  -9.87829490E-02   9.32289493E-03   1.43955145E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -2.87864567E-02  -1.44544563E-02  -5.28175286E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -1.16080920E+00   1.28402963E-01   2.31539415E-01\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -1.21687295E-03  -9.73597973E-04  -3.44313469E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.40606853E+00   1.61351013E-01   2.99777142E-01\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -1.70970255E+00   2.10442835E-01   4.11815956E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -1.33945192E+00   1.87509348E-01   3.97789440E-01\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 1\ntag                            : 1\nelement                        : 1\nd                              :   2.04600216E+00\ndr                             :  -2.04259479E+00   1.13271334E-01   3.31808574E-02\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.52083703E-01\n                            1  :  -8.99285877E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 18\n--------------------------------\n                            0  :  -7.94178175E-01   4.40408551E-02   1.29009988E-02\n                            1  :  -9.13769389E-01   5.06727413E-02   1.48436939E-02\n                            2  :  -1.05615427E+00   5.85686416E-02   1.71566599E-02\n                            3  :  -1.26012945E+00   6.98800095E-02   2.04701274E-02\n                            4  :  -1.48660152E+00   8.24389340E-02   2.41490448E-02\n                            5  :  -1.78161912E+00   9.87990251E-02   2.89414476E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   4.38999522E-03   3.60842555E-02   1.20968811E-01\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   2.30590790E-02  -4.09726435E-02  -1.32741072E-01\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   2.64792957E-04   2.29274704E-03   7.67876110E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   2.66715636E-02  -6.18679715E-02  -2.01777832E-01\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   2.93470011E-02  -1.05196958E-01  -3.45727469E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   1.80916902E-02  -1.30030043E-01  -4.30337840E-01\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 4\ntag                            : 4\nelement                        : 1\nd                              :   6.92888887E+00\ndr                             :  -6.86245554E+00   5.27625853E-01   7.98633742E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.35765782E-03\n                            1  :  -6.52513751E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 18\n--------------------------------\n                            0  :  -5.71675605E-02   4.39537752E-03   6.65300379E-03\n                            1  :  -3.44883212E-02   2.65166452E-03   4.01365617E-03\n                            2  :  -1.83312758E-02   1.40941605E-03   2.13334356E-03\n                            3  :  -6.67549592E-03   5.13251299E-04   7.76875894E-04\n                            4  :  -1.28875431E-03   9.90869943E-05   1.49981690E-04\n                            5  :  -7.01868634E-05   5.39637794E-06   8.16815454E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -2.99647554E-04   2.34492108E-05  -8.98855827E-05\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -5.62922706E-02   4.27333125E-03   6.66953175E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -5.62669784E-06  -9.42486353E-07  -6.27065179E-06\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -6.85482577E-02   5.20342565E-03   8.16303355E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -8.42410220E-02   6.39367537E-03   1.01328178E-02\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -6.74206949E-02   5.11473516E-03   8.26889096E-03\n--------------------------------\n********************************\n--------------------------------\n********************************\n                            3  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 3\nindexStructure                 : 0\ntag                            : 3\nelement                        : 1\nnumNeighbors                   : 6\nnumNeighborsUnique             : 7\nnumSymmetryFunctions           : 36\nenergy                         :  -2.74407753E-01\nchi                            :  -1.49331912E-01\ncharge                         :  -1.51993282E-04\nchargeRef                      :   0.00000000E+00\nr                              :  -3.69153152E+00  -3.34149933E-01  -2.10885725E-01\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 7\n--------------------------------\n                            0  : 3\n                            1  : 0\n                            2  : 1\n                            3  : 4\n                            4  : 5\n                            5  : 6\n                            6  : 7\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 0\n                            1  : 6\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 22\n                            1  : 22\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 36\n--------------------------------\n                            0  :  -1.63799020E-01\n                            1  :   1.52140112E-01\n                            2  :   1.43446597E-01\n                            3  :  -1.55063300E-01\n                            4  :   1.33163199E-01\n                            5  :  -1.46390185E-01\n                            6  :   1.20455513E-01\n                            7  :  -1.36103652E-01\n                            8  :   1.05451989E-01\n                            9  :  -1.25139988E-01\n                           10  :   8.56282930E-02\n                           11  :  -1.13813086E-01\n                           12  :  -3.98169770E-02\n                           13  :  -1.14060192E-01\n                           14  :   7.32604079E-02\n                           15  :  -3.49080250E-02\n                           16  :  -1.12184341E-01\n                           17  :   1.36045133E-01\n                           18  :  -3.60654596E-02\n                           19  :  -1.30086055E-01\n                           20  :   7.83465926E-02\n                           21  :  -3.82258330E-02\n                           22  :  -1.06790992E-01\n                           23  :   1.39848648E-01\n                           24  :  -2.63986903E-02\n                           25  :  -1.58271251E-01\n                           26  :   8.32353329E-02\n                           27  :  -3.41458088E-02\n                           28  :  -1.09931206E-01\n                           29  :   1.43942725E-01\n                           30  :  -1.47219650E-02\n                           31  :  -1.26845196E-01\n                           32  :   8.96213493E-02\n                           33  :  -2.44142034E-02\n                           34  :  -1.23217933E-01\n                           35  :   1.51940263E-01\n--------------------------------\n--------------------------------\ndEdG                       [*] : 37\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n                           36  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            1  :  -1.47238553E-03   5.16717567E-02  -1.39489172E-02\n                            2  :  -1.88255679E-03   5.54986537E-02  -1.55715635E-02\n                            3  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            4  :  -3.79233978E-03   6.04496785E-02  -1.73560380E-02\n                            5  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            6  :  -8.68008350E-03   6.71835249E-02  -1.93657699E-02\n                            7  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            8  :  -1.84698621E-02   7.57246310E-02  -2.13936886E-02\n                            9  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           10  :  -3.96141468E-02   8.87266265E-02  -2.36630669E-02\n                           11  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           14  :   1.44416364E-02   7.00019689E-02  -2.31215354E-02\n                           15  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   4.24662604E-02   5.67799644E-02  -1.68057928E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           20  :   1.69596350E-02   1.08022480E-01  -3.60711921E-02\n                           21  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           22  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           23  :   4.44651078E-02   8.39835918E-02  -2.60595846E-02\n                           24  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           25  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           26  :   2.07380725E-02   1.82644492E-01  -6.01856686E-02\n                           27  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           28  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           29  :   4.56558283E-02   8.58954310E-02  -2.76470287E-02\n                           30  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           31  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           32  :   2.75776683E-02   3.25508772E-01  -1.06313533E-01\n                           33  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           34  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           35  :   4.79993983E-02   8.91495094E-02  -3.06883458E-02\n--------------------------------\n--------------------------------\nneighbors                  [*] : 6\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 0\ntag                            : 0\nelement                        : 1\nd                              :   4.94779513E+00\ndr                             :   4.91745254E+00  -4.51360949E-01  -3.09209316E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   4.82411211E-02\n                            1  :  -4.31091524E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.28722292E-01  -1.18151046E-02  -8.09405513E-03\n                            1  :   1.21360442E-01  -1.11393784E-02  -7.63114216E-03\n                            2  :   1.10035595E-01  -1.00998983E-02  -6.91903600E-03\n                            3  :   9.29950743E-02  -8.53579056E-03  -5.84752839E-03\n                            4  :   7.08750148E-02  -6.50544437E-03  -4.45661950E-03\n                            5  :   4.29595970E-02  -3.94315640E-03  -2.70129859E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   5.53251454E-03  -3.54415591E-03  -1.65763540E-04\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   6.38093422E-01  -4.72189684E-02  -4.08995122E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   5.42579782E-03  -3.79235109E-04  -3.96184084E-04\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   6.43707276E-01  -4.52783759E-02  -4.14356721E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   5.51501066E-03  -3.95990669E-04  -3.96557630E-04\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   6.49604813E-01  -4.09321392E-02  -4.21756864E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   5.50495355E-03  -4.23595115E-04  -3.83042420E-04\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   6.60676847E-01  -3.19636181E-02  -4.36263494E-02\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 1\ntag                            : 1\nelement                        : 1\nd                              :   7.29139769E+00\ndr                             :   7.19635914E+00  -7.45942426E-01  -9.05795402E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   6.89503784E-04\n                            1  :  -2.90393031E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   8.61081077E-03  -8.92558160E-04  -1.08383040E-03\n                            1  :   5.67632622E-03  -5.88382606E-04  -7.14471038E-04\n                            2  :   3.27452247E-03  -3.39422365E-04  -4.12159447E-04\n                            3  :   1.50725391E-03  -1.56235204E-04  -1.89715887E-04\n                            4  :   5.23417910E-04  -5.42551612E-05  -6.58818614E-05\n                            5  :   9.49050277E-05  -9.83743100E-06  -1.19455597E-05\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   2.83223268E-05  -6.70466504E-06   1.62245776E-05\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   1.59959900E-02  -1.64514645E-03  -2.16049506E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   3.82222763E-08  -1.62866462E-08   4.42644288E-08\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   1.61197318E-02  -1.65505187E-03  -2.19213714E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   7.06982831E-14  -6.41878921E-14   1.50006265E-13\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   1.62327403E-02  -1.66097786E-03  -2.23758151E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   2.66505704E-25  -5.13886739E-25   9.77094328E-25\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   1.64391253E-02  -1.67061763E-03  -2.32698446E-03\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 4\ntag                            : 4\nelement                        : 1\nd                              :   2.40362043E+00\ndr                             :   2.37649839E+00  -3.31587907E-01  -1.40342518E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.20436919E-01\n                            1  :  -8.69068320E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   2.58155493E-01  -3.60199021E-02  -1.52451994E-02\n                            1  :   2.96407123E-01  -4.13570730E-02  -1.75041237E-02\n                            2  :   3.46264882E-01  -4.83136231E-02  -2.04484403E-02\n                            3  :   4.14210432E-01  -5.77939252E-02  -2.44609191E-02\n                            4  :   4.99690672E-01  -6.97208064E-02  -2.95088973E-02\n                            5  :   6.23335531E-01  -8.69727179E-02  -3.68106615E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   8.62093087E-01  -9.05312882E-02  -5.87197466E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -6.41638348E-03  -8.72007199E-03  -1.98922496E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   8.73192365E-01  -1.17141454E-01  -5.29376886E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.18399918E-02  -2.68293871E-02   3.13595348E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   8.78456712E-01  -1.56045094E-01  -4.11232277E-02\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -1.32708543E-02  -3.68944580E-02   4.12137256E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   8.58925377E-01  -2.28430122E-01  -1.61091896E-02\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -1.61186740E-02  -5.71932526E-02   6.04272814E-03\n--------------------------------\n********************************\n                            3  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 5\ntag                            : 5\nelement                        : 1\nd                              :   4.88848810E+00\ndr                             :  -4.86443885E+00  -1.61643973E-01   4.56532377E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   5.08360544E-02\n                            1  :  -4.43991218E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.32735894E-01  -4.41077746E-03   1.24573944E-02\n                            1  :  -1.26013588E-01  -4.18739708E-03   1.18264994E-02\n                            2  :  -1.15253891E-01  -3.82985528E-03   1.08166912E-02\n                            3  :  -9.85505090E-02  -3.27480647E-03   9.24906233E-03\n                            4  :  -7.62560077E-02  -2.53396629E-03   7.15670142E-03\n                            5  :  -4.73159107E-02  -1.57229477E-03   4.44064482E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -1.29376307E-02   3.00303260E-03   1.64342393E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -6.65106720E-01  -3.30192505E-02   6.04376062E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -1.26954389E-02   8.28310730E-05   1.09071490E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -6.70750438E-01  -3.54991597E-02   6.05553194E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -1.27603003E-02  -1.02163290E-05   1.11421861E-03\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -6.76604708E-01  -4.01725808E-02   6.02723139E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -1.24551248E-02  -1.87955774E-04   1.12342024E-03\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -6.87547314E-01  -4.96922126E-02   5.95967276E-02\n--------------------------------\n********************************\n                            4  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 6\ntag                            : 6\nelement                        : 1\nd                              :   2.54498398E+00\ndr                             :  -2.53194978E+00   1.64879081E-02   2.56713787E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.08251887E-01\n                            1  :  -8.54624293E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -2.55447160E-01   1.66345690E-03   2.58997270E-02\n                            1  :  -2.91797041E-01   1.90016518E-03   2.95852328E-02\n                            2  :  -3.38432944E-01   2.20385544E-03   3.43136359E-02\n                            3  :  -4.00558331E-01   2.60841231E-03   4.06125142E-02\n                            4  :  -4.76060019E-01   3.10007486E-03   4.82676123E-02\n                            5  :  -5.79409573E-01   3.77308109E-03   5.87461991E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -8.69124118E-01   2.10751128E-02   8.03326113E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -1.49293461E-02   3.41831498E-02   1.50355964E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -8.82882310E-01   9.41537811E-03   8.83142306E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.15321439E-02   2.56428237E-02   6.09402288E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -8.91949494E-01  -2.61931911E-02   1.00591235E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -1.14007801E-02   3.41356921E-02   7.78746568E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -8.79552874E-01  -9.64670982E-02   1.21682344E-01\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -1.11504558E-02   5.17538369E-02   1.11694028E-02\n--------------------------------\n********************************\n                            5  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 7\ntag                            : 7\nelement                        : 1\nd                              :   7.42168843E+00\ndr                             :  -7.41744094E+00  -2.50341487E-01   1.89223608E-02\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   3.75793243E-04\n                            1  :  -1.94265821E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -5.83315597E-03  -1.96871259E-04   1.48807497E-05\n                            1  :  -3.75070541E-03  -1.26587751E-04   9.56828665E-06\n                            2  :  -2.09582521E-03  -7.07349075E-05   5.34658263E-06\n                            3  :  -9.23836431E-04  -3.11798351E-05   2.35676515E-06\n                            4  :  -3.03216597E-04  -1.02336769E-05   7.73524711E-07\n                            5  :  -5.04027622E-05  -1.70111262E-06   1.28580633E-07\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -3.38109329E-05   2.03445157E-06   1.47857343E-05\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -1.01032235E-02  -3.59676807E-04  -8.61408491E-05\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -8.73599511E-08   1.55012904E-08   7.50364785E-08\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.01695421E-02  -3.64441062E-04  -9.79019762E-05\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -6.08329116E-13   2.80530318E-13   9.99953242E-13\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -1.02170400E-02  -3.70967213E-04  -1.20855550E-04\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -3.39213157E-23   3.74970020E-23   1.04526765E-22\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -1.02989271E-02  -3.83645314E-04  -1.67178813E-04\n--------------------------------\n********************************\n--------------------------------\n********************************\n                            4  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 4\nindexStructure                 : 0\ntag                            : 4\nelement                        : 1\nnumNeighbors                   : 6\nnumNeighborsUnique             : 7\nnumSymmetryFunctions           : 36\nenergy                         :  -2.69999525E-01\nchi                            :  -1.48572339E-01\ncharge                         :  -4.72554224E-04\nchargeRef                      :   0.00000000E+00\nr                              :  -6.06802991E+00  -2.56202610E-03  -7.05432077E-02\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 7\n--------------------------------\n                            0  : 4\n                            1  : 0\n                            2  : 1\n                            3  : 2\n                            4  : 3\n                            5  : 5\n                            6  : 6\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 1\n                            1  : 5\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 22\n                            1  : 22\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 36\n--------------------------------\n                            0  :  -1.59334485E-01\n                            1  :   1.50289716E-01\n                            2  :   1.41768617E-01\n                            3  :  -1.52554892E-01\n                            4  :   1.31521084E-01\n                            5  :  -1.45156399E-01\n                            6  :   1.18684118E-01\n                            7  :  -1.35696515E-01\n                            8  :   1.03397284E-01\n                            9  :  -1.25067778E-01\n                           10  :   8.31099725E-02\n                           11  :  -1.13809547E-01\n                           12  :  -3.98169770E-02\n                           13  :  -1.14055866E-01\n                           14  :   6.89558839E-02\n                           15  :  -3.49080250E-02\n                           16  :  -1.06813116E-01\n                           17  :   1.27103530E-01\n                           18  :  -3.60654596E-02\n                           19  :  -1.30086051E-01\n                           20  :   7.38832145E-02\n                           21  :  -3.82258330E-02\n                           22  :  -1.01070833E-01\n                           23  :   1.30777279E-01\n                           24  :  -2.63986903E-02\n                           25  :  -1.58271251E-01\n                           26  :   8.24287132E-02\n                           27  :  -3.41458088E-02\n                           28  :  -1.03582032E-01\n                           29  :   1.31963640E-01\n                           30  :  -1.47219650E-02\n                           31  :  -1.26845196E-01\n                           32  :   9.62189664E-02\n                           33  :  -2.44142034E-02\n                           34  :  -1.15422891E-01\n                           35  :   1.34028406E-01\n--------------------------------\n--------------------------------\ndEdG                       [*] : 37\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n                           36  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 36\n--------------------------------\n                            0  :  -1.22377345E-02   9.40908845E-04   1.42419396E-03\n                            1  :   1.04849588E-02  -2.21306146E-02   1.12649540E-02\n                            2  :   8.75943517E-03  -2.57474399E-02   1.11939669E-02\n                            3  :  -7.32335510E-03   5.63062516E-04   8.52271968E-04\n                            4  :   8.93898512E-03  -3.05732896E-02   1.07630041E-02\n                            5  :  -3.87300397E-03   2.97779273E-04   4.50729572E-04\n                            6  :   1.25262196E-02  -3.73050968E-02   9.77215762E-03\n                            7  :  -1.41775092E-03   1.09005010E-04   1.64993961E-04\n                            8  :   2.14909924E-02  -4.59792090E-02   8.11166964E-03\n                            9  :  -2.90105334E-04   2.23050005E-05   3.37616626E-05\n                           10  :   4.21255340E-02  -5.88237683E-02   5.43983243E-03\n                           11  :  -1.75217820E-05   1.34717742E-06   2.03913690E-06\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.39996173E-05   1.36496066E-05   2.04089702E-05\n                           14  :  -1.62274699E-02  -4.02185315E-02   9.79353571E-03\n                           15  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           16  :  -1.80091793E-02   1.35693700E-03   2.10751144E-03\n                           17  :  -7.98424476E-03   2.28544398E-03   3.18366152E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -1.15174006E-08   2.87831544E-08   4.54120597E-08\n                           20  :  -1.84680716E-02  -7.34047878E-02   7.51635150E-03\n                           21  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           22  :  -1.91795564E-02   1.43419905E-03   2.22819752E-03\n                           23  :  -9.44021059E-03  -2.13162269E-02   3.03077541E-02\n                           24  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           25  :  -6.29881057E-15   5.67168329E-14   9.34851924E-14\n                           26  :  -2.32664946E-02  -1.25236333E-01   1.21133524E-02\n                           27  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           28  :  -2.12895960E-02   1.56775021E-03   2.43722711E-03\n                           29  :  -9.12804249E-03  -3.26916622E-02   2.37475923E-02\n                           30  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           31  :   1.28234926E-28   5.22102145E-26   8.74810108E-26\n                           32  :  -3.22098181E-02  -2.26108654E-01   2.10809600E-02\n                           33  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           34  :  -2.61401501E-02   1.86551116E-03   2.90399401E-03\n                           35  :  -8.47744481E-03  -5.56387616E-02   1.04421931E-02\n--------------------------------\n--------------------------------\nneighbors                  [*] : 6\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 0\ntag                            : 0\nelement                        : 1\nd                              :   2.54937435E+00\ndr                             :   2.54095415E+00  -1.19773042E-01  -1.68866799E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.07876779E-01\n                            1  :  -8.54153091E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   2.55773029E-01  -1.20563819E-02  -1.69981707E-02\n                            1  :   2.92119167E-01  -1.37696311E-02  -1.94136634E-02\n                            2  :   3.38725913E-01  -1.59665349E-02  -2.25110558E-02\n                            3  :   4.00765508E-01  -1.88908974E-02  -2.66340848E-02\n                            4  :   4.76075205E-01  -2.24407731E-02  -3.16390186E-02\n                            5  :   5.78967130E-01  -2.72907933E-02  -3.84770130E-02\n                            6  :  -4.24742134E-06  -2.07947426E-05  -3.49477400E-05\n                            7  :   8.64365789E-01  -6.04038588E-02  -6.87251326E-02\n                            8  :  -9.09731208E-04   1.60711687E-04   2.58179817E-04\n                            9  :   1.95045456E-02   1.00997519E-02   4.66512138E-02\n                           10  :  -8.16206181E-09  -4.49843019E-08  -7.55878548E-08\n                           11  :   8.82544434E-01  -4.42252593E-02  -5.85515044E-02\n                           12  :  -9.65782345E-04   1.89298569E-04   3.05440832E-04\n                           13  :   1.94534320E-02   2.29580690E-02   5.55824347E-02\n                           14  :  -1.50916242E-14  -8.87242577E-14  -1.49072091E-13\n                           15  :   8.98358382E-01  -2.03235598E-02  -6.15094940E-02\n                           16  :  -1.06522055E-03   2.50378334E-04   4.06677285E-04\n                           17  :   2.11499693E-02   3.09035330E-02   7.44651072E-02\n                           18  :  -1.34386892E-26  -8.17253325E-26  -1.37306841E-25\n                           19  :   8.99325164E-01   2.88714817E-02  -6.55091087E-02\n                           20  :  -1.29120663E-03   4.06161733E-04   6.65229177E-04\n                           21  :   2.45600804E-02   4.68819666E-02   1.12623180E-01\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 1\ntag                            : 1\nelement                        : 1\nd                              :   4.89782252E+00\ndr                             :   4.81986075E+00  -4.14354519E-01  -7.65452885E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   5.04225616E-02\n                            1  :  -4.41961751E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.30668813E-01  -1.12333563E-02  -2.07518069E-02\n                            1  :   1.23917005E-01  -1.06529158E-02  -1.96795371E-02\n                            2  :   1.13182055E-01  -9.73005207E-03  -1.79746958E-02\n                            3  :   9.66021379E-02  -8.30470721E-03  -1.53416019E-02\n                            4  :   7.45713710E-02  -6.41076291E-03  -1.18428465E-02\n                            5  :   4.61014270E-02  -3.96325446E-03  -7.32147091E-03\n                            6  :   2.83525668E-06   2.44415562E-06   1.21083402E-05\n                            7  :   1.48663122E-02   1.31235543E-03   4.46269107E-03\n                            8  :   1.21246064E-03  -1.32492068E-04  -3.24587918E-04\n                            9  :   6.40483129E-01  -6.55420704E-02  -1.26603224E-01\n                           10  :   2.93739950E-09   2.91280515E-09   1.43228087E-08\n                           11  :   1.17350941E-02  -1.14165265E-03  -1.55842538E-03\n                           12  :   1.28961305E-03  -1.43313106E-04  -3.56409992E-04\n                           13  :   6.43762541E-01  -6.79493906E-02  -1.32219423E-01\n                           14  :   1.60200187E-15   1.71466942E-15   8.40047289E-15\n                           15  :   1.18904526E-02  -1.14509074E-03  -1.65945866E-03\n                           16  :   1.42784076E-03  -1.63990160E-04  -4.19449696E-04\n                           17  :   6.44967852E-01  -7.22641212E-02  -1.42426615E-01\n                           18  :   1.25252124E-28   1.39538887E-28   6.82383105E-28\n                           19  :   1.18170990E-02  -1.08697500E-03  -1.74430815E-03\n                           20  :   1.74418387E-03  -2.13424942E-04  -5.73597360E-04\n                           21  :   6.46503291E-01  -8.09044376E-02  -1.62906268E-01\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 2\ntag                            : 2\nelement                        : 0\nd                              :   6.92888887E+00\ndr                             :   6.86245554E+00  -5.27625853E-01  -7.98633742E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.35765782E-03\n                            1  :  -6.52513751E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.22377345E-02  -9.40908845E-04  -1.42419396E-03\n                            1  :   7.32335510E-03  -5.63062516E-04  -8.52271968E-04\n                            2  :   3.87300397E-03  -2.97779273E-04  -4.50729572E-04\n                            3  :   1.41775092E-03  -1.09005010E-04  -1.64993961E-04\n                            4  :   2.90105334E-04  -2.23050005E-05  -3.37616626E-05\n                            5  :   1.75217820E-05  -1.34717742E-06  -2.03913690E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   1.54117819E-05   4.70098030E-06   2.43042962E-06\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   1.77064499E-02  -1.38515662E-03  -2.04110334E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   1.67420629E-08   1.32883423E-08   1.58529863E-08\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   1.88557257E-02  -1.48018451E-03  -2.17722836E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   1.97884329E-14   3.02927555E-14   4.71864252E-14\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   2.09269758E-02  -1.65413838E-03  -2.42445470E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   1.31852022E-26   2.93755791E-26   4.91434475E-26\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   2.56871729E-02  -2.05824795E-03  -2.99562583E-03\n--------------------------------\n********************************\n                            3  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 3\ntag                            : 3\nelement                        : 1\nd                              :   2.40362043E+00\ndr                             :  -2.37649839E+00   3.31587907E-01   1.40342518E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.20436919E-01\n                            1  :  -8.69068320E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -2.58155493E-01   3.60199021E-02   1.52451994E-02\n                            1  :  -2.96407123E-01   4.13570730E-02   1.75041237E-02\n                            2  :  -3.46264882E-01   4.83136231E-02   2.04484403E-02\n                            3  :  -4.14210432E-01   5.77939252E-02   2.44609191E-02\n                            4  :  -4.99690672E-01   6.97208064E-02   2.95088973E-02\n                            5  :  -6.23335531E-01   8.69727179E-02   3.68106615E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -8.56684771E-01   9.42905800E-02   5.54452523E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   8.33163602E-03   2.36995583E-02  -1.05874595E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -8.70321585E-01   1.18405017E-01   5.21743530E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   1.18337242E-02   4.00619862E-02  -1.39402947E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -8.81380786E-01   1.46339104E-01   5.06215077E-02\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   1.36227641E-02   5.45536132E-02  -1.87174914E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -8.73295881E-01   1.97947871E-01   4.57307276E-02\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   1.72355324E-02   8.39554255E-02  -2.84272840E-02\n--------------------------------\n********************************\n                            4  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 5\ntag                            : 5\nelement                        : 1\nd                              :   7.26748325E+00\ndr                             :  -7.24093724E+00   1.69943934E-01   5.96874895E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   7.61287457E-04\n                            1  :  -3.10047074E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -9.28098761E-03   2.17823673E-04   7.65037497E-04\n                            1  :  -6.14576482E-03   1.44240368E-04   5.06599160E-04\n                            2  :  -3.56581765E-03   8.36893152E-05   2.93932534E-04\n                            3  :  -1.65421462E-03   3.88242199E-05   1.36357925E-04\n                            4  :  -5.80325886E-04   1.36201794E-05   4.78366184E-05\n                            5  :  -1.06882781E-04   2.50852612E-06   8.81041313E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -4.93007416E-05   2.90466365E-05  -1.86000891E-07\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -1.75526368E-02   2.26449980E-04   1.47114935E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -1.54713968E-07   1.53389547E-07  -1.58499003E-08\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.76749021E-02   2.06932635E-04   1.48459874E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -1.81505318E-12   3.45655735E-12  -5.37029274E-13\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -1.77717280E-02   1.65714605E-04   1.49914721E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -2.51684052E-22   9.66512462E-22  -1.72737424E-22\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -1.79433902E-02   8.20722642E-05   1.52648901E-03\n--------------------------------\n********************************\n                            5  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 6\ntag                            : 6\nelement                        : 1\nd                              :   4.93676755E+00\ndr                             :  -4.90844817E+00   3.48075815E-01   3.97056305E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   4.87178335E-02\n                            1  :  -4.33490876E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.29490320E-01   9.18262699E-03   1.04747868E-02\n                            1  :  -1.22242719E-01   8.66867339E-03   9.88851070E-03\n                            2  :  -1.11016254E-01   7.87256412E-03   8.98037463E-03\n                            3  :  -9.40292188E-02   6.66795204E-03   7.60625210E-03\n                            4  :  -7.18665701E-02   5.09631845E-03   5.81346156E-03\n                            5  :  -4.37516772E-02   3.10258970E-03   3.53917953E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -6.27055906E-03   4.99040825E-03  -9.76160503E-04\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -6.42782429E-01   2.92308662E-02   5.72317048E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -5.48971613E-03   3.66529739E-04   4.19241127E-04\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -6.47934585E-01   2.60386297E-02   5.87849307E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -5.60155369E-03   3.65878743E-04   4.34092549E-04\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -6.52840815E-01   1.93329226E-02   6.14322601E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -5.63656431E-03   3.76275697E-04   4.41729286E-04\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -6.61878069E-01   5.62373477E-03   6.67416898E-02\n--------------------------------\n********************************\n--------------------------------\n********************************\n                            5  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 5\nindexStructure                 : 0\ntag                            : 5\nelement                        : 1\nnumNeighbors                   : 6\nnumNeighborsUnique             : 7\nnumSymmetryFunctions           : 36\nenergy                         :  -2.72523946E-01\nchi                            :  -1.50034638E-01\ncharge                         :  -5.48894165E-04\nchargeRef                      :   0.00000000E+00\nr                              :   1.17290733E+00  -1.72505960E-01  -6.67418102E-01\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 7\n--------------------------------\n                            0  : 5\n                            1  : 3\n                            2  : 4\n                            3  : 6\n                            4  : 7\n                            5  : 8\n                            6  : 9\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 0\n                            1  : 6\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 22\n                            1  : 22\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 36\n--------------------------------\n                            0  :  -1.63799020E-01\n                            1  :   1.56618918E-01\n                            2  :   1.48367866E-01\n                            3  :  -1.55063300E-01\n                            4  :   1.38647224E-01\n                            5  :  -1.46390185E-01\n                            6  :   1.26740576E-01\n                            7  :  -1.36103652E-01\n                            8  :   1.12883329E-01\n                            9  :  -1.25139988E-01\n                           10  :   9.51501221E-02\n                           11  :  -1.13813086E-01\n                           12  :  -3.98169770E-02\n                           13  :  -1.14060192E-01\n                           14  :   9.08077293E-02\n                           15  :  -3.49080250E-02\n                           16  :  -1.12184341E-01\n                           17  :   1.49196681E-01\n                           18  :  -3.60654596E-02\n                           19  :  -1.30086055E-01\n                           20  :   8.73533577E-02\n                           21  :  -3.82258330E-02\n                           22  :  -1.06790992E-01\n                           23  :   1.46603923E-01\n                           24  :  -2.63986903E-02\n                           25  :  -1.58271251E-01\n                           26  :   7.58982880E-02\n                           27  :  -3.41458088E-02\n                           28  :  -1.09931206E-01\n                           29  :   1.49812069E-01\n                           30  :  -1.47219650E-02\n                           31  :  -1.26845196E-01\n                           32  :   5.10146109E-02\n                           33  :  -2.44142034E-02\n                           34  :  -1.23217933E-01\n                           35  :   1.56258295E-01\n--------------------------------\n--------------------------------\ndEdG                       [*] : 37\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n                           36  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            1  :  -1.74026877E-02  -1.51826914E-02   9.31336615E-02\n                            2  :  -2.03300345E-02  -1.68317091E-02   1.00645214E-01\n                            3  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            4  :  -2.58834320E-02  -1.89273887E-02   1.10159973E-01\n                            5  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            6  :  -3.63372584E-02  -2.17784253E-02   1.22734758E-01\n                            7  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            8  :  -5.42753779E-02  -2.54880881E-02   1.38050990E-01\n                            9  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           10  :  -9.03088840E-02  -3.13824236E-02   1.60010132E-01\n                           11  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           14  :   1.68469842E-02  -2.07487816E-02   1.39189635E-01\n                           15  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -2.97328821E-02  -1.55175366E-02   9.58351430E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           20  :   1.36416155E-02  -3.39062207E-02   2.13974180E-01\n                           21  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           22  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           23  :  -3.26078298E-02  -2.49485921E-02   1.49176439E-01\n                           24  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           25  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           26  :   9.74287850E-03  -5.65315619E-02   3.51929335E-01\n                           27  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           28  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           29  :  -3.50578739E-02  -2.75710513E-02   1.56785687E-01\n                           30  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           31  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           32  :   2.16382626E-03  -9.66987888E-02   5.96524535E-01\n                           33  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           34  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           35  :  -3.99018292E-02  -3.23489995E-02   1.68523312E-01\n--------------------------------\n--------------------------------\nneighbors                  [*] : 6\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 3\ntag                            : 3\nelement                        : 1\nd                              :   4.88848810E+00\ndr                             :   4.86443885E+00   1.61643973E-01  -4.56532377E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   5.08360544E-02\n                            1  :  -4.43991218E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.32735894E-01   4.41077746E-03  -1.24573944E-02\n                            1  :   1.26013588E-01   4.18739708E-03  -1.18264994E-02\n                            2  :   1.15253891E-01   3.82985528E-03  -1.08166912E-02\n                            3  :   9.85505090E-02   3.27480647E-03  -9.24906233E-03\n                            4  :   7.62560077E-02   2.53396629E-03  -7.15670142E-03\n                            5  :   4.73159107E-02   1.57229477E-03  -4.44064482E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   7.33955687E-03   3.36746727E-03   4.20966053E-04\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   6.77691763E-01   1.17396934E-02  -6.56708979E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   6.97393669E-03   2.37519599E-04  -1.71341146E-04\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   6.83446760E-01   9.50613333E-03  -6.67050005E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   6.87148254E-03   2.30697746E-04  -2.31012873E-04\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   6.89454166E-01   4.88608668E-03  -6.81931699E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   6.44559489E-03   2.15738369E-04  -3.32597197E-04\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   7.00692730E-01  -4.59191041E-03  -7.11353548E-02\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 4\ntag                            : 4\nelement                        : 1\nd                              :   7.26748325E+00\ndr                             :   7.24093724E+00  -1.69943934E-01  -5.96874895E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   7.61287457E-04\n                            1  :  -3.10047074E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   9.28098761E-03  -2.17823673E-04  -7.65037497E-04\n                            1  :   6.14576482E-03  -1.44240368E-04  -5.06599160E-04\n                            2  :   3.56581765E-03  -8.36893152E-05  -2.93932534E-04\n                            3  :   1.65421462E-03  -3.88242199E-05  -1.36357925E-04\n                            4  :   5.80325886E-04  -1.36201794E-05  -4.78366184E-05\n                            5  :   1.06882781E-04  -2.50852612E-06  -8.81041313E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   4.04756819E-05   2.57706529E-05  -5.86761312E-06\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   1.75773871E-02  -5.95989293E-04  -1.42724338E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   8.70257977E-08   1.00392620E-07  -1.33269742E-08\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   1.77064140E-02  -6.20547895E-04  -1.43579815E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   5.07308121E-13   1.08068515E-12  -8.12229264E-14\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   1.78165962E-02  -6.65007855E-04  -1.44085904E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   1.95469413E-23   7.95072049E-23  -4.20764600E-24\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   1.80150427E-02  -7.54434401E-04  -1.44905002E-03\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 6\ntag                            : 6\nelement                        : 1\nd                              :   2.34779976E+00\ndr                             :   2.33248908E+00   1.78131881E-01  -1.99818590E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.25303049E-01\n                            1  :  -8.74382048E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   2.60985037E-01   1.99313926E-02  -2.23579448E-02\n                            1  :   3.00199395E-01   2.29261879E-02  -2.57173422E-02\n                            2  :   3.51605966E-01   2.68521010E-02  -3.01212165E-02\n                            3  :   4.22238471E-01   3.22462960E-02  -3.61721291E-02\n                            4  :   5.12195889E-01   3.91163320E-02  -4.38785593E-02\n                            5  :   6.44833757E-01   4.92458684E-02  -5.52413185E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   8.71680241E-01   5.25286968E-02  -3.17217649E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   3.02715228E-04   1.83756241E-02   3.31704678E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   8.71595147E-01   6.52249254E-02  -6.81210215E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.33829674E-02   2.69987402E-02   7.36773620E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   8.53562094E-01   7.60211740E-02  -1.41393574E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -1.43600430E-02   3.72594757E-02   8.41713146E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   7.90742782E-01   9.34939062E-02  -2.72882774E-01\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -1.57848999E-02   5.79592404E-02   1.24495915E-02\n--------------------------------\n********************************\n                            3  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 7\ntag                            : 7\nelement                        : 1\nd                              :   2.59175413E+00\ndr                             :  -2.55300209E+00  -8.86975138E-02  -4.37610016E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.04266639E-01\n                            1  :  -8.49534803E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -2.51416838E-01  -8.73483358E-03  -4.30953530E-02\n                            1  :  -2.86658130E-01  -9.95920197E-03  -4.91360620E-02\n                            2  :  -3.31616131E-01  -1.15211525E-02  -5.68423116E-02\n                            3  :  -3.91015597E-01  -1.35848346E-02  -6.70239723E-02\n                            4  :  -4.62292345E-01  -1.60611626E-02  -7.92415177E-02\n                            5  :  -5.57850375E-01  -1.93810814E-02  -9.56211169E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -8.82160367E-01  -3.26686731E-02  -1.02681208E-01\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -2.43626165E-02  -2.18800694E-02  -1.02280309E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -8.78971981E-01  -3.13143183E-02  -1.44823894E-01\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -8.46323350E-03  -2.05778215E-02  -3.95115606E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -8.56953771E-01  -1.95262313E-02  -2.09352678E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -5.88140820E-03  -2.70145461E-02  -5.28188778E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -7.86607687E-01   3.09556422E-03  -3.22185426E-01\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -1.26189400E-03  -4.04128684E-02  -7.82326780E-02\n--------------------------------\n********************************\n                            4  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 8\ntag                            : 8\nelement                        : 1\nd                              :   4.93243163E+00\ndr                             :  -4.90468409E+00  -5.75923776E-03  -5.22419896E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   4.89059964E-02\n                            1  :  -4.34434203E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.29786580E-01  -1.52399575E-04  -1.38241506E-02\n                            1  :  -1.22584666E-01  -1.43942857E-04  -1.30570425E-02\n                            2  :  -1.11397995E-01  -1.30807107E-04  -1.18654999E-02\n                            3  :  -9.44335406E-02  -1.10886900E-04  -1.00585398E-02\n                            4  :  -7.22559225E-02  -8.48452274E-05  -7.69630231E-03\n                            5  :  -4.40643414E-02  -5.17417665E-05  -4.69349059E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -1.37435234E-02  -2.50387435E-03  -5.20178157E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -6.34166860E-01   7.96748751E-03  -5.06157056E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -1.32388038E-02  -2.42006076E-04  -8.57910091E-04\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -6.39325957E-01   9.73165362E-03  -4.78184345E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -1.32226841E-02  -1.94078578E-04  -9.52071149E-04\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -6.44532171E-01   1.31945609E-02  -4.16661417E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -1.27445161E-02  -1.06420003E-04  -1.12373855E-03\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -6.54196070E-01   2.02382502E-02  -2.90524524E-02\n--------------------------------\n********************************\n                            5  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 9\ntag                            : 9\nelement                        : 1\nd                              :   7.49603389E+00\ndr                             :  -7.41875943E+00  -9.18471759E-02  -1.06962461E+00\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.49007333E-04\n                            1  :  -1.47837184E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -4.39581332E-03  -5.44219075E-05  -6.33781180E-04\n                            1  :  -2.78591631E-03  -3.44907458E-05  -4.01668860E-04\n                            2  :  -1.52811719E-03  -1.89186952E-05  -2.20321438E-04\n                            3  :  -6.56799012E-04  -8.13143154E-06  -9.46962080E-05\n                            4  :  -2.08576939E-04  -2.58226500E-06  -3.00722822E-05\n                            5  :  -3.29503869E-05  -4.07938822E-07  -4.75073292E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -3.36739292E-06  -6.05666446E-07   2.13239482E-08\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -7.30950709E-03  -8.92096684E-05  -1.06373314E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -1.22425973E-09  -2.69285815E-10   4.28804763E-10\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -7.37318662E-03  -8.95656503E-05  -1.07338149E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -1.75658816E-16  -2.69428928E-18   2.36093339E-16\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -7.43926673E-03  -8.95180976E-05  -1.08377012E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -4.24477708E-30   2.85916734E-30   1.33046960E-29\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -7.56307976E-03  -8.92778967E-05  -1.10336834E-03\n--------------------------------\n********************************\n--------------------------------\n********************************\n                            6  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 6\nindexStructure                 : 0\ntag                            : 6\nelement                        : 1\nnumNeighbors                   : 6\nnumNeighborsUnique             : 7\nnumSymmetryFunctions           : 36\nenergy                         :  -2.62042224E-01\nchi                            :  -1.49457838E-01\ncharge                         :   1.78378050E-04\nchargeRef                      :   0.00000000E+00\nr                              :  -1.15958175E+00  -3.50637841E-01  -4.67599512E-01\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 7\n--------------------------------\n                            0  : 6\n                            1  : 0\n                            2  : 3\n                            3  : 4\n                            4  : 5\n                            5  : 7\n                            6  : 8\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 0\n                            1  : 6\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 22\n                            1  : 22\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 36\n--------------------------------\n                            0  :  -1.63799020E-01\n                            1  :   1.66935185E-01\n                            2  :   1.60390843E-01\n                            3  :  -1.55063300E-01\n                            4  :   1.52923044E-01\n                            5  :  -1.46390185E-01\n                            6  :   1.44079607E-01\n                            7  :  -1.36103652E-01\n                            8  :   1.33983115E-01\n                            9  :  -1.25139988E-01\n                           10  :   1.21349718E-01\n                           11  :  -1.13813086E-01\n                           12  :  -3.98169770E-02\n                           13  :  -1.14060192E-01\n                           14  :   1.23526563E-01\n                           15  :  -3.49080250E-02\n                           16  :  -1.12184341E-01\n                           17  :   1.23414760E-01\n                           18  :  -3.60654596E-02\n                           19  :  -1.30086055E-01\n                           20  :   1.28318907E-01\n                           21  :  -3.82258330E-02\n                           22  :  -1.06790992E-01\n                           23  :   1.26103405E-01\n                           24  :  -2.63986903E-02\n                           25  :  -1.58271251E-01\n                           26  :   1.38247175E-01\n                           27  :  -3.41458088E-02\n                           28  :  -1.09931206E-01\n                           29  :   1.25164754E-01\n                           30  :  -1.47219650E-02\n                           31  :  -1.26845196E-01\n                           32  :   1.52933916E-01\n                           33  :  -2.44142034E-02\n                           34  :  -1.23217933E-01\n                           35  :   1.22964433E-01\n--------------------------------\n--------------------------------\ndEdG                       [*] : 37\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n                           36  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            1  :   1.36536901E-02   3.85467335E-02   2.12480370E-02\n                            2  :   1.53002436E-02   4.07008259E-02   2.03798443E-02\n                            3  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            4  :   1.90023879E-02   4.33878227E-02   1.90449017E-02\n                            5  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            6  :   2.65724597E-02   4.69549201E-02   1.69406372E-02\n                            7  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            8  :   4.01874355E-02   5.14667213E-02   1.39226904E-02\n                            9  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           10  :   6.84230522E-02   5.86756017E-02   9.32345793E-03\n                           11  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           14  :  -1.24018580E-02   5.03757019E-02   1.99887501E-02\n                           15  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   1.45534014E-02   5.32885046E-02   5.21723705E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           20  :  -1.81602293E-02   7.31518332E-02   1.59115390E-02\n                           21  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           22  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           23  :   1.06710923E-02   6.96273873E-02   4.93529076E-02\n                           24  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           25  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           26  :  -1.94509688E-02   1.24735273E-01   2.57752114E-02\n                           27  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           28  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           29  :   3.38402266E-03   6.60189289E-02   3.64067816E-02\n                           30  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           31  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           32  :  -2.13234776E-02   2.25360553E-01   4.51385812E-02\n                           33  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           34  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           35  :  -1.12583397E-02   5.83313420E-02   1.05317400E-02\n--------------------------------\n--------------------------------\nneighbors                  [*] : 6\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 0\ntag                            : 0\nelement                        : 1\nd                              :   7.48550242E+00\ndr                             :   7.44940232E+00  -4.67848857E-01  -5.65923103E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.64902175E-04\n                            1  :  -1.54037544E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   4.60556455E-03  -2.89245770E-04  -3.49879798E-04\n                            1  :   2.92486800E-03  -1.83692072E-04  -2.22199084E-04\n                            2  :   1.60858025E-03  -1.01024539E-04  -1.22202116E-04\n                            3  :   6.93876923E-04  -4.35779290E-05  -5.27130855E-05\n                            4  :   2.21391497E-04  -1.39041703E-05  -1.68188745E-05\n                            5  :   3.52300504E-05  -2.21257198E-06  -2.67638914E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   5.18638342E-06   2.21137429E-06  -1.99913397E-06\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   7.63685359E-03  -4.92895353E-04  -5.69780435E-04\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   5.02275291E-09   5.41460699E-09  -2.98992016E-09\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   7.70214253E-03  -4.99005406E-04  -5.73450196E-04\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   4.72036962E-15   1.01889920E-14  -5.09376608E-15\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   7.76866950E-03  -5.07133775E-04  -5.75981919E-04\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   4.01695873E-27   1.65529152E-26  -7.89425498E-27\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   7.89290215E-03  -5.22974056E-04  -5.80281077E-04\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 3\ntag                            : 3\nelement                        : 1\nd                              :   2.54498398E+00\ndr                             :   2.53194978E+00  -1.64879081E-02  -2.56713787E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.08251887E-01\n                            1  :  -8.54624293E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   2.55447160E-01  -1.66345690E-03  -2.58997270E-02\n                            1  :   2.91797041E-01  -1.90016518E-03  -2.95852328E-02\n                            2  :   3.38432944E-01  -2.20385544E-03  -3.43136359E-02\n                            3  :   4.00558331E-01  -2.60841231E-03  -4.06125142E-02\n                            4  :   4.76060019E-01  -3.10007486E-03  -4.82676123E-02\n                            5  :   5.79409573E-01  -3.77308109E-03  -5.87461991E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   9.20102065E-01  -1.06938808E-03  -8.75541404E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   1.01722753E-02   4.05904171E-02  -9.57425643E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   9.37562447E-01  -4.35376915E-03  -9.42195880E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   8.64049933E-03   3.85746223E-02  -1.31631157E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   9.53216032E-01  -2.84843423E-02  -1.00436569E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   8.37676441E-03   5.15381650E-02  -1.72794853E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   9.51967645E-01  -7.66411963E-02  -1.09583811E-01\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   7.83208177E-03   7.79924658E-02  -2.56465399E-02\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 4\ntag                            : 4\nelement                        : 1\nd                              :   4.93676755E+00\ndr                             :   4.90844817E+00  -3.48075815E-01  -3.97056305E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   4.87178335E-02\n                            1  :  -4.33490876E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.29490320E-01  -9.18262699E-03  -1.04747868E-02\n                            1  :   1.22242719E-01  -8.66867339E-03  -9.88851070E-03\n                            2  :   1.11016254E-01  -7.87256412E-03  -8.98037463E-03\n                            3  :   9.40292188E-02  -6.66795204E-03  -7.60625210E-03\n                            4  :   7.18665701E-02  -5.09631845E-03  -5.81346156E-03\n                            5  :   4.37516772E-02  -3.10258970E-03  -3.53917953E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   1.34988176E-02   3.82608858E-03  -2.48699249E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   6.32809335E-01  -6.13521498E-02  -4.59425939E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   1.25323588E-02  -4.65970333E-04  -1.03034739E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   6.37622546E-01  -6.51039903E-02  -4.52553022E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   1.26521094E-02  -5.56676319E-04  -1.03450029E-03\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   6.42029985E-01  -7.21128099E-02  -4.34816537E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   1.24617540E-02  -6.98541289E-04  -1.01406490E-03\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   6.50065985E-01  -8.63146997E-02  -3.97949967E-02\n--------------------------------\n********************************\n                            3  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 5\ntag                            : 5\nelement                        : 1\nd                              :   2.34779976E+00\ndr                             :  -2.33248908E+00  -1.78131881E-01   1.99818590E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.25303049E-01\n                            1  :  -8.74382048E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -2.60985037E-01  -1.99313926E-02   2.23579448E-02\n                            1  :  -3.00199395E-01  -2.29261879E-02   2.57173422E-02\n                            2  :  -3.51605966E-01  -2.68521010E-02   3.01212165E-02\n                            3  :  -4.22238471E-01  -3.22462960E-02   3.61721291E-02\n                            4  :  -5.12195889E-01  -3.91163320E-02   4.38785593E-02\n                            5  :  -6.44833757E-01  -4.92458684E-02   5.52413185E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -9.09551224E-01  -5.11024192E-02   6.09743456E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   1.30322771E-02  -8.85008602E-04   6.97752957E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -9.24699816E-01  -6.80364323E-02   7.93227657E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   1.62986076E-02  -1.24688204E-02   8.28622183E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -9.39152092E-01  -9.53971257E-02   7.58047993E-02\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   1.91810941E-02  -1.71167662E-02   1.12304854E-01\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -9.35982460E-01  -1.47700036E-01   6.56383970E-02\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   2.49111769E-02  -2.63219509E-02   1.71047200E-01\n--------------------------------\n********************************\n                            4  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 7\ntag                            : 7\nelement                        : 1\nd                              :   4.89854740E+00\ndr                             :  -4.88549117E+00  -2.66829395E-01  -2.37791426E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   5.03905304E-02\n                            1  :  -4.41804133E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.32381258E-01  -7.23022717E-03  -6.44339066E-03\n                            1  :  -1.25530401E-01  -6.85605599E-03  -6.10993902E-03\n                            2  :  -1.14643541E-01  -6.26145162E-03  -5.58004305E-03\n                            3  :  -9.78356213E-02  -5.34345856E-03  -4.76195148E-03\n                            4  :  -7.55096280E-02  -4.12408653E-03  -3.67527880E-03\n                            5  :  -4.66681822E-02  -2.54886200E-03  -2.27147961E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -1.15854850E-02  -2.01555213E-03   9.06010849E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -6.59412893E-01  -3.07748725E-02  -6.49024694E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -7.23443864E-03  -2.95562756E-04   1.54100995E-05\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -6.62023615E-01  -2.97651569E-02  -7.22413008E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -7.26508029E-03  -2.97129075E-04  -1.08941870E-04\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -6.61747307E-01  -2.74765261E-02  -8.63538665E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -7.12346187E-03  -3.20780060E-04  -1.79101977E-04\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -6.60309948E-01  -2.28635045E-02  -1.14460548E-01\n--------------------------------\n********************************\n                            5  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 8\ntag                            : 8\nelement                        : 1\nd                              :   7.24669325E+00\ndr                             :  -7.23717317E+00  -1.83891119E-01  -3.22601306E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   8.27566288E-04\n                            1  :  -3.27633296E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -9.83043939E-03  -2.49784060E-04  -4.38197692E-04\n                            1  :  -6.53507580E-03  -1.66051354E-04  -2.91304897E-04\n                            2  :  -3.81065911E-03  -9.68259776E-05  -1.69862400E-04\n                            3  :  -1.77979411E-03  -4.52232277E-05  -7.93353827E-05\n                            4  :  -6.29899147E-04  -1.60052629E-05  -2.80781297E-05\n                            5  :  -1.17593198E-04  -2.98795459E-06  -5.24178686E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -6.75013853E-05  -1.66424182E-05   1.99279280E-05\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -1.87912500E-02  -3.73995479E-04  -9.58566117E-04\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -3.26533211E-07  -1.04086233E-07   2.23533138E-07\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.89112725E-02  -3.65036586E-04  -9.81957143E-04\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -8.01429259E-12  -4.70953048E-12   1.11580994E-11\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -1.89932283E-02  -3.43857860E-04  -1.02064830E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -4.67010100E-21  -5.13838914E-21   1.26210424E-20\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -1.91338584E-02  -3.00678628E-04  -1.09657408E-03\n--------------------------------\n********************************\n--------------------------------\n********************************\n                            7  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 7\nindexStructure                 : 0\ntag                            : 7\nelement                        : 1\nnumNeighbors                   : 6\nnumNeighborsUnique             : 7\nnumSymmetryFunctions           : 36\nenergy                         :  -2.71020173E-01\nchi                            :  -1.49032144E-01\ncharge                         :   4.64496010E-04\nchargeRef                      :   0.00000000E+00\nr                              :   3.72590942E+00  -8.38084461E-02  -2.29808086E-01\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 7\n--------------------------------\n                            0  : 7\n                            1  : 3\n                            2  : 5\n                            3  : 6\n                            4  : 8\n                            5  : 9\n                            6  : 10\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 0\n                            1  : 6\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 22\n                            1  : 22\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 36\n--------------------------------\n                            0  :  -1.63799020E-01\n                            1  :   1.57927099E-01\n                            2  :   1.48925498E-01\n                            3  :  -1.55063300E-01\n                            4  :   1.38375124E-01\n                            5  :  -1.46390185E-01\n                            6  :   1.25494830E-01\n                            7  :  -1.36103652E-01\n                            8  :   1.10546065E-01\n                            9  :  -1.25139988E-01\n                           10  :   9.14017380E-02\n                           11  :  -1.13813086E-01\n                           12  :  -3.98169770E-02\n                           13  :  -1.14060192E-01\n                           14  :   7.90814077E-02\n                           15  :  -3.49080250E-02\n                           16  :  -1.12184341E-01\n                           17  :   1.43480566E-01\n                           18  :  -3.60654596E-02\n                           19  :  -1.30086055E-01\n                           20  :   7.99233863E-02\n                           21  :  -3.82258330E-02\n                           22  :  -1.06790992E-01\n                           23  :   1.44158938E-01\n                           24  :  -2.63986903E-02\n                           25  :  -1.58271251E-01\n                           26  :   8.36294320E-02\n                           27  :  -3.41458088E-02\n                           28  :  -1.09931206E-01\n                           29  :   1.42756572E-01\n                           30  :  -1.47219650E-02\n                           31  :  -1.26845196E-01\n                           32  :   8.76734101E-02\n                           33  :  -2.44142034E-02\n                           34  :  -1.23217933E-01\n                           35  :   1.39593015E-01\n--------------------------------\n--------------------------------\ndEdG                       [*] : 37\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n                           36  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            1  :   1.46260255E-02  -2.44017541E-02  -2.20167018E-02\n                            2  :   1.71263212E-02  -2.68767217E-02  -2.75444849E-02\n                            3  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            4  :   2.23014811E-02  -2.98658418E-02  -3.45652134E-02\n                            5  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            6  :   3.25524745E-02  -3.36684517E-02  -4.37716307E-02\n                            7  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            8  :   5.06580213E-02  -3.82009281E-02  -5.46645728E-02\n                            9  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           10  :   8.73482433E-02  -4.46717653E-02  -6.86334651E-02\n                           11  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           14  :  -1.46508560E-02  -3.65967133E-02  -5.92743545E-02\n                           15  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -2.85306903E-03  -2.45267951E-02   2.50415716E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           20  :  -8.32027328E-03  -5.77069709E-02  -1.11618826E-01\n                           21  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           22  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           23  :   1.97623301E-03  -3.96032705E-02  -1.20561340E-02\n                           24  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           25  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           26  :  -1.05843230E-03  -9.71321966E-02  -1.86851629E-01\n                           27  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           28  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           29  :   6.33203586E-03  -4.20462187E-02  -3.41307612E-02\n                           30  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           31  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           32  :   1.33682696E-02  -1.72190254E-01  -3.29842939E-01\n                           33  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           34  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           35  :   1.50153640E-02  -4.66418183E-02  -7.80007971E-02\n--------------------------------\n--------------------------------\nneighbors                  [*] : 6\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 3\ntag                            : 3\nelement                        : 1\nd                              :   7.42168843E+00\ndr                             :   7.41744094E+00   2.50341487E-01  -1.89223608E-02\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   3.75793243E-04\n                            1  :  -1.94265821E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   5.83315597E-03   1.96871259E-04  -1.48807497E-05\n                            1  :   3.75070541E-03   1.26587751E-04  -9.56828665E-06\n                            2  :   2.09582521E-03   7.07349075E-05  -5.34658263E-06\n                            3  :   9.23836431E-04   3.11798351E-05  -2.35676515E-06\n                            4  :   3.03216597E-04   1.02336769E-05  -7.73524711E-07\n                            5  :   5.04027622E-05   1.70111262E-06  -1.28580633E-07\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   5.73395600E-05   3.65448653E-06   1.67390724E-05\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   1.00757017E-02   3.23990989E-04  -1.42352204E-04\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   3.99599409E-07   1.71941305E-08   2.04550002E-07\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   1.01244377E-02   3.24209821E-04  -1.55985665E-04\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   2.21322547E-11   8.78601674E-13   2.24981573E-11\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   1.01371823E-02   3.21893544E-04  -1.81971723E-04\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   6.68535708E-20   3.03630592E-21   1.36600941E-19\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   1.01504820E-02   3.16762253E-04  -2.33325855E-04\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 5\ntag                            : 5\nelement                        : 1\nd                              :   2.59175413E+00\ndr                             :   2.55300209E+00   8.86975138E-02   4.37610016E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.04266639E-01\n                            1  :  -8.49534803E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   2.51416838E-01   8.73483358E-03   4.30953530E-02\n                            1  :   2.86658130E-01   9.95920197E-03   4.91360620E-02\n                            2  :   3.31616131E-01   1.15211525E-02   5.68423116E-02\n                            3  :   3.91015597E-01   1.35848346E-02   6.70239723E-02\n                            4  :   4.62292345E-01   1.60611626E-02   7.92415177E-02\n                            5  :   5.57850375E-01   1.93810814E-02   9.56211169E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   8.71199014E-01   2.20090957E-02   1.12137917E-01\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   1.60679419E-02  -1.64655531E-02   5.28594851E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   8.78803698E-01   2.87444583E-02   1.47081298E-01\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   8.15189948E-03  -1.20367988E-02   7.71203019E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   8.80536502E-01   4.74271713E-02   1.83539125E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   4.17009906E-03  -1.60926103E-02   1.01316862E-01\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   8.53992523E-01   8.29895335E-02   2.49508093E-01\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -3.74087801E-03  -2.43743155E-02   1.49523404E-01\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 6\ntag                            : 6\nelement                        : 1\nd                              :   4.89854740E+00\ndr                             :   4.88549117E+00   2.66829395E-01   2.37791426E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   5.03905304E-02\n                            1  :  -4.41804133E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.32381258E-01   7.23022717E-03   6.44339066E-03\n                            1  :   1.25530401E-01   6.85605599E-03   6.10993902E-03\n                            2  :   1.14643541E-01   6.26145162E-03   5.58004305E-03\n                            3  :   9.78356213E-02   5.34345856E-03   4.76195148E-03\n                            4  :   7.55096280E-02   4.12408653E-03   3.67527880E-03\n                            5  :   4.66681822E-02   2.54886200E-03   2.27147961E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   1.65201258E-02  -7.68887184E-04   9.21716953E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   6.47492009E-01   4.07032290E-02  -1.37766545E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   1.38310231E-02   4.66732225E-04   6.99662118E-04\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   6.51132117E-01   4.19867775E-02  -7.75844836E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   1.40503051E-02   5.38099452E-04   6.51707240E-04\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   6.52992341E-01   4.41802077E-02  -2.05513383E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   1.40290323E-02   6.43993265E-04   6.65688268E-04\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   6.55849253E-01   4.85288468E-02  -4.62341784E-02\n--------------------------------\n********************************\n                            3  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 8\ntag                            : 8\nelement                        : 1\nd                              :   2.35467189E+00\ndr                             :  -2.35168200E+00   8.29382760E-02  -8.48098794E-02\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.24702383E-01\n                            1  :  -8.73739802E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -2.62171892E-01   9.24618410E-03  -9.45483553E-03\n                            1  :  -3.01499305E-01   1.06331692E-02  -1.08731196E-02\n                            2  :  -3.53018448E-01   1.24501278E-02  -1.27310801E-02\n                            3  :  -4.23735857E-01   1.49441640E-02  -1.52813973E-02\n                            4  :  -5.13668927E-01   1.81158912E-02  -1.85246984E-02\n                            5  :  -6.45967721E-01   2.27817575E-02  -2.32958557E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -8.64811450E-01   1.28813998E-02  -6.75511261E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   5.68484177E-03   1.11002884E-02   3.38979258E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -8.79042005E-01   2.85345735E-02  -3.54521845E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   8.85611873E-03   2.24381011E-02   5.87173689E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -8.88161868E-01   4.92143185E-02   3.41133589E-03\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   8.45066673E-03   3.06297819E-02   7.97342129E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -8.75998016E-01   8.85933902E-02   8.04098971E-02\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   7.58183326E-03   4.70048628E-02   1.21854764E-01\n--------------------------------\n********************************\n                            4  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 9\ntag                            : 9\nelement                        : 1\nd                              :   4.90663294E+00\ndr                             :  -4.86575733E+00  -3.14966220E-03  -6.32014592E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   5.00340188E-02\n                            1  :  -4.40045869E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.31105417E-01  -8.48660851E-05  -1.70293196E-02\n                            1  :  -1.24203808E-01  -8.03985921E-05  -1.61328677E-02\n                            2  :  -1.13297926E-01  -7.33390860E-05  -1.47162996E-02\n                            3  :  -9.65339134E-02  -6.24875424E-05  -1.25388172E-02\n                            4  :  -7.43517518E-02  -4.81287672E-05  -9.65757001E-03\n                            5  :  -4.58066698E-02  -2.96511984E-05  -5.94984126E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -8.21471490E-03   2.43353074E-03   5.45793472E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -6.54943388E-01  -9.00277408E-03  -1.08281963E-01\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -5.27245206E-03  -3.91029639E-05  -7.10200851E-04\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -6.58595806E-01  -1.09292339E-02  -1.13855246E-01\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -5.36650679E-03  -4.73925913E-05  -7.50539409E-04\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -6.60376923E-01  -1.47361565E-02  -1.24162355E-01\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -5.39180834E-03  -3.66631567E-05  -7.40740238E-04\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -6.63058149E-01  -2.24251531E-02  -1.44862607E-01\n--------------------------------\n********************************\n                            5  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 10\ntag                            : 10\nelement                        : 1\nd                              :   7.20053726E+00\ndr                             :  -7.14458517E+00  -5.99610684E-01  -6.65662527E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   9.88092704E-04\n                            1  :  -3.68326655E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.09799681E-02  -9.21495930E-04  -1.02300597E-03\n                            1  :  -7.36244493E-03  -6.17894606E-04  -6.85960568E-04\n                            2  :  -4.34060315E-03  -3.64285954E-04  -4.04414924E-04\n                            3  :  -2.05775840E-03  -1.72697769E-04  -1.91721790E-04\n                            4  :  -7.42531521E-04  -6.23171006E-05  -6.91818205E-05\n                            5  :  -1.42812306E-04  -1.19855502E-05  -1.33058531E-05\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -9.94591625E-05   3.79197187E-05  -4.27954285E-06\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -2.15240371E-02  -2.13238605E-03  -1.99700155E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -3.89680477E-07   2.92564865E-07   4.71535946E-08\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -2.16449999E-02  -2.17978515E-03  -2.01185695E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -7.12858800E-12   9.51906137E-12   3.56582344E-12\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -2.17054027E-02  -2.25689765E-03  -2.02464877E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -2.82431136E-21   6.41655430E-21   2.90317077E-21\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -2.17979056E-02  -2.40918495E-03  -2.04726013E-03\n--------------------------------\n********************************\n--------------------------------\n********************************\n                            8  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 8\nindexStructure                 : 0\ntag                            : 8\nelement                        : 1\nnumNeighbors                   : 6\nnumNeighborsUnique             : 7\nnumSymmetryFunctions           : 36\nenergy                         :  -2.64793348E-01\nchi                            :  -1.48516264E-01\ncharge                         :  -7.41970412E-04\nchargeRef                      :   0.00000000E+00\nr                              :   6.07759142E+00  -1.66746722E-01  -1.44998207E-01\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 7\n--------------------------------\n                            0  : 8\n                            1  : 5\n                            2  : 6\n                            3  : 7\n                            4  : 9\n                            5  : 10\n                            6  : 11\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 1\n                            1  : 5\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 22\n                            1  : 22\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 36\n--------------------------------\n                            0  :  -1.58298379E-01\n                            1  :   1.60378965E-01\n                            2  :   1.52616191E-01\n                            3  :  -1.51929158E-01\n                            4  :   1.43364568E-01\n                            5  :  -1.44821818E-01\n                            6  :   1.31919126E-01\n                            7  :  -1.35571976E-01\n                            8  :   1.18477377E-01\n                            9  :  -1.25041642E-01\n                           10  :   1.01188775E-01\n                           11  :  -1.13807899E-01\n                           12  :  -3.98169770E-02\n                           13  :  -1.14019335E-01\n                           14  :   9.79655042E-02\n                           15  :  -3.49080250E-02\n                           16  :  -1.05441932E-01\n                           17  :   1.39723530E-01\n                           18  :  -3.60654596E-02\n                           19  :  -1.30085733E-01\n                           20  :   9.63990481E-02\n                           21  :  -3.82258330E-02\n                           22  :  -9.96411373E-02\n                           23  :   1.38312701E-01\n                           24  :  -2.63986903E-02\n                           25  :  -1.58271251E-01\n                           26  :   9.53598901E-02\n                           27  :  -3.41458088E-02\n                           28  :  -1.02062409E-01\n                           29  :   1.36444337E-01\n                           30  :  -1.47219650E-02\n                           31  :  -1.26845196E-01\n                           32  :   8.96805501E-02\n                           33  :  -2.44142034E-02\n                           34  :  -1.13719716E-01\n                           35  :   1.32436800E-01\n--------------------------------\n--------------------------------\ndEdG                       [*] : 37\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n                           36  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 36\n--------------------------------\n                            0  :   1.36115628E-02   2.81479102E-03   2.71623990E-03\n                            1  :  -2.00520119E-02   3.61850717E-02   4.66442590E-02\n                            2  :  -2.01651232E-02   3.79445238E-02   5.30174380E-02\n                            3  :   8.29209481E-03   1.71475637E-03   1.65471953E-03\n                            4  :  -2.32506141E-02   3.98902109E-02   6.09994405E-02\n                            5  :   4.47992155E-03   9.26421391E-04   8.93985637E-04\n                            6  :  -3.17177793E-02   4.21613905E-02   7.13448080E-02\n                            7  :   1.69372709E-03   3.50252787E-04   3.37989779E-04\n                            8  :  -4.84200046E-02   4.47129090E-02   8.35031703E-02\n                            9  :   3.63800505E-04   7.52318018E-05   7.25977950E-05\n                           10  :  -8.35810451E-02   4.86545337E-02   9.94296468E-02\n                           11  :   2.38304902E-05   4.92800501E-06   4.75546630E-06\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   1.30103370E-04   1.23309108E-04   2.42074640E-05\n                           14  :   1.14302797E-02   4.37257205E-02   9.03606189E-02\n                           15  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           16  :   2.07528979E-02   3.78475949E-03   3.96900893E-03\n                           17  :   1.15854155E-02   5.95944313E-02   1.75977940E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   1.09124396E-06   1.93670561E-06   9.05171159E-08\n                           20  :   1.61297462E-04   5.90306064E-02   1.52089989E-01\n                           21  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           22  :   2.20032943E-02   3.92744587E-03   4.20865614E-03\n                           23  :   3.27676763E-03   7.06347111E-02   6.14537536E-02\n                           24  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           25  :   8.26677075E-11   2.57023384E-10  -7.85509822E-12\n                           26  :  -1.20448532E-02   9.85126589E-02   2.53122160E-01\n                           27  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           28  :   2.42077305E-02   4.13403299E-03   4.63118514E-03\n                           29  :  -4.63045506E-03   6.44677773E-02   7.81643396E-02\n                           30  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           31  :   2.48020598E-19   1.20508782E-18  -7.15062528E-20\n                           32  :  -3.53142702E-02   1.72178862E-01   4.41124233E-01\n                           33  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           34  :   2.92015039E-02   4.54038869E-03   5.58750347E-03\n                           35  :  -2.03072478E-02   5.17328726E-02   1.10378206E-01\n--------------------------------\n--------------------------------\nneighbors                  [*] : 6\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 5\ntag                            : 5\nelement                        : 1\nd                              :   4.93243163E+00\ndr                             :   4.90468409E+00   5.75923776E-03   5.22419896E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   4.89059964E-02\n                            1  :  -4.34434203E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.29786580E-01   1.52399575E-04   1.38241506E-02\n                            1  :   1.22584666E-01   1.43942857E-04   1.30570425E-02\n                            2  :   1.11397995E-01   1.30807107E-04   1.18654999E-02\n                            3  :   9.44335406E-02   1.10886900E-04   1.00585398E-02\n                            4  :   7.22559225E-02   8.48452274E-05   7.69630231E-03\n                            5  :   4.40643414E-02   5.17417665E-05   4.69349059E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   6.94228012E-03  -2.41160139E-03  -3.90128129E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   6.44539161E-01   9.38377293E-03   8.56192040E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   5.16857868E-03   4.34727160E-05   6.87419770E-04\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   6.48971187E-01   1.13005083E-02   8.98087459E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   5.24161618E-03   4.70020552E-05   6.95595351E-04\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   6.52428621E-01   1.50950028E-02   9.75524563E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   5.21599775E-03   3.66212292E-05   6.58077743E-04\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   6.58514192E-01   2.28006259E-02   1.13180418E-01\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 6\ntag                            : 6\nelement                        : 1\nd                              :   7.24669325E+00\ndr                             :   7.23717317E+00   1.83891119E-01   3.22601306E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   8.27566288E-04\n                            1  :  -3.27633296E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   9.83043939E-03   2.49784060E-04   4.38197692E-04\n                            1  :   6.53507580E-03   1.66051354E-04   2.91304897E-04\n                            2  :   3.81065911E-03   9.68259776E-05   1.69862400E-04\n                            3  :   1.77979411E-03   4.52232277E-05   7.93353827E-05\n                            4  :   6.29899147E-04   1.60052629E-05   2.80781297E-05\n                            5  :   1.17593198E-04   2.98795459E-06   5.24178686E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   2.56902864E-05  -1.55447119E-05   1.09933080E-05\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   1.88257164E-02   5.83313650E-04   7.37597566E-04\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   2.64958299E-08  -3.18771132E-08   2.38686924E-08\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   1.89770390E-02   6.00175010E-04   7.36089122E-04\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   2.76907509E-14  -6.42793219E-14   5.88930613E-14\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   1.91215442E-02   6.29277927E-04   7.26711361E-04\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   2.96047993E-26  -1.32974545E-25   1.75259522E-25\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   1.93878971E-02   6.87800851E-04   7.06471204E-04\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 7\ntag                            : 7\nelement                        : 1\nd                              :   2.35467189E+00\ndr                             :   2.35168200E+00  -8.29382760E-02   8.48098794E-02\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.24702383E-01\n                            1  :  -8.73739802E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   2.62171892E-01  -9.24618410E-03   9.45483553E-03\n                            1  :   3.01499305E-01  -1.06331692E-02   1.08731196E-02\n                            2  :   3.53018448E-01  -1.24501278E-02   1.27310801E-02\n                            3  :   4.23735857E-01  -1.49441640E-02   1.52813973E-02\n                            4  :   5.13668927E-01  -1.81158912E-02   1.85246984E-02\n                            5  :   6.45967721E-01  -2.27817575E-02   2.32958557E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   8.82155930E-01  -1.29959589E-02   7.26253458E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -5.94564758E-03  -1.04422254E-02  -1.54866214E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   8.93624947E-01  -2.86878999E-02   3.69224161E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.14084297E-02  -2.18006176E-02  -4.28522973E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   8.97066004E-01  -4.94023030E-02  -1.61959510E-02\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -1.12654467E-02  -2.99284718E-02  -5.85403426E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   8.73388693E-01  -8.80273900E-02  -1.19007347E-01\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -1.08620004E-02  -4.61579940E-02  -8.96689178E-02\n--------------------------------\n********************************\n                            3  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 9\ntag                            : 9\nelement                        : 1\nd                              :   2.57437738E+00\ndr                             :  -2.51407533E+00  -8.60879382E-02  -5.47204713E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.05744515E-01\n                            1  :  -8.51443707E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -2.49814607E-01  -8.55424821E-03  -5.43737605E-02\n                            1  :  -2.85031481E-01  -9.76015803E-03  -6.20389405E-02\n                            2  :  -3.30054285E-01  -1.13018463E-02  -7.18384441E-02\n                            3  :  -3.89724105E-01  -1.33450833E-02  -8.48259654E-02\n                            4  :  -4.61670228E-01  -1.58086902E-02  -1.00485503E-01\n                            5  :  -5.58890451E-01  -1.91377426E-02  -1.21646112E-01\n                            6  :   1.02427772E-05  -1.42514385E-04   1.72175431E-05\n                            7  :  -8.80435010E-01  -3.36757876E-02  -1.50231546E-01\n                            8  :   9.95823068E-04   8.56027038E-04   1.30517981E-04\n                            9  :  -2.29424929E-02   6.21235812E-02  -3.63177548E-02\n                           10  :   1.08700246E-07  -2.66991946E-06   3.04153981E-07\n                           11  :  -8.83314101E-01  -2.88541793E-02  -1.88029792E-01\n                           12  :   1.05238589E-03   1.03426374E-03   1.24333434E-04\n                           13  :  -1.14910683E-02   6.67359941E-02  -6.19195017E-02\n                           14  :   9.84584463E-12  -3.84041132E-10   4.24685578E-11\n                           15  :  -8.74644021E-01  -4.74246188E-02  -2.35964443E-01\n                           16  :   1.15026521E-03   1.41492812E-03   1.06053204E-04\n                           17  :  -8.02319629E-03   8.85639771E-02  -8.09758586E-02\n                           18  :   3.38151833E-20  -1.85583364E-18   2.02179112E-19\n                           19  :  -8.28193951E-01  -8.22696156E-02  -3.21056279E-01\n                           20  :   1.36935993E-03   2.36718345E-03   5.46255088E-05\n                           21  :  -1.35104375E-03   1.32227354E-01  -1.18260545E-01\n--------------------------------\n********************************\n                            4  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 10\ntag                            : 10\nelement                        : 1\nd                              :   4.87598027E+00\ndr                             :  -4.79290317E+00  -6.82548960E-01  -5.80852648E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   5.13930914E-02\n                            1  :  -4.46709989E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.31922293E-01  -1.87868230E-02  -1.59876823E-02\n                            1  :  -1.25422443E-01  -1.78611908E-02  -1.51999645E-02\n                            2  :  -1.14922203E-01  -1.63658699E-02  -1.39274388E-02\n                            3  :  -9.85073071E-02  -1.40282534E-02  -1.19381152E-02\n                            4  :  -7.64645168E-02  -1.08891781E-02  -9.26674617E-03\n                            5  :  -4.76781595E-02  -6.78976333E-03  -5.77812325E-03\n                            6  :   1.94879251E-06  -2.25015671E-05  -2.74881451E-05\n                            7  :  -2.01191702E-02   5.37317209E-03  -8.86413069E-03\n                            8  :  -1.63248347E-03   8.10035563E-06   9.49671739E-05\n                            9  :  -6.46062152E-01  -1.21242874E-01  -5.21502194E-02\n                           10  :   2.56416287E-08  -1.35588749E-07  -1.66361204E-07\n                           11  :  -1.56407492E-02  -1.53196800E-03  -1.67005599E-03\n                           12  :  -1.74135254E-03   2.80889327E-05   1.24970977E-04\n                           13  :  -6.48325495E-01  -1.27470771E-01  -4.72267896E-02\n                           14  :   5.01957000E-13  -2.08786968E-12  -2.56730503E-12\n                           15  :  -1.56187459E-02  -1.73273919E-03  -1.65736062E-03\n                           16  :  -1.93904674E-03   7.41692379E-05   1.91361725E-04\n                           17  :  -6.47631067E-01  -1.38827563E-01  -3.69273060E-02\n                           18  :   3.12873153E-23  -1.17586316E-22  -1.44744865E-22\n                           19  :  -1.50964694E-02  -1.91847786E-03  -1.71868455E-03\n                           20  :  -2.39563048E-03   1.95580462E-04   3.62934368E-04\n                           21  :  -6.45381797E-01  -1.61290659E-01  -1.63356323E-02\n--------------------------------\n********************************\n                            5  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 11\ntag                            : 11\nelement                        : 0\nd                              :   6.85069280E+00\ndr                             :  -6.58420556E+00  -1.36157493E+00  -1.31390363E+00\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.90481085E-03\n                            1  :  -7.47900274E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.36115628E-02  -2.81479102E-03  -2.71623990E-03\n                            1  :  -8.29209481E-03  -1.71475637E-03  -1.65471953E-03\n                            2  :  -4.47992155E-03  -9.26421391E-04  -8.93985637E-04\n                            3  :  -1.69372709E-03  -3.50252787E-04  -3.37989779E-04\n                            4  :  -3.63800505E-04  -7.52318018E-05  -7.25977950E-05\n                            5  :  -2.38304902E-05  -4.92800501E-06  -4.75546630E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -1.42294940E-04   4.17068444E-05  -1.39368619E-05\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -2.01162375E-02  -4.64888689E-03  -4.19449409E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -1.22558584E-06   8.68802600E-07  -2.28309893E-07\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -2.13143276E-02  -4.98979854E-03  -4.45796055E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -9.30155091E-11   1.29105618E-10  -3.20461546E-11\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -2.34189490E-02  -5.62313034E-03  -4.92860007E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -2.81867069E-19   6.50863408E-19  -1.30528114E-19\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -2.81752334E-02  -7.10315260E-03  -6.00506335E-03\n--------------------------------\n********************************\n--------------------------------\n********************************\n                            9  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 9\nindexStructure                 : 0\ntag                            : 9\nelement                        : 1\nnumNeighbors                   : 5\nnumNeighborsUnique             : 6\nnumSymmetryFunctions           : 36\nenergy                         :  -2.07184350E-01\nchi                            :  -1.46835351E-01\ncharge                         :   1.65043470E-03\nchargeRef                      :   0.00000000E+00\nr                              :   8.59166676E+00  -8.06587839E-02   4.02206506E-01\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 6\n--------------------------------\n                            0  : 9\n                            1  : 5\n                            2  : 7\n                            3  : 8\n                            4  : 10\n                            5  : 11\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 1\n                            1  : 4\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 22\n                            1  : 22\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 36\n--------------------------------\n                            0  :  -1.46128719E-02\n                            1  :   7.31998904E-03\n                            2  :   2.23503799E-02\n                            3  :  -3.24968905E-02\n                            4  :   3.83117968E-02\n                            5  :  -5.01589822E-02\n                            6  :   5.46472236E-02\n                            7  :  -7.01612170E-02\n                            8  :   6.79322470E-02\n                            9  :  -8.85733063E-02\n                           10  :   7.56997912E-02\n                           11  :  -1.00734027E-01\n                           12  :  -3.98169770E-02\n                           13  :  -1.06355969E-01\n                           14  :   1.03123462E-01\n                           15  :  -3.49080250E-02\n                           16  :   2.41696157E-01\n                           17  :  -3.66473599E-01\n                           18  :  -3.60654596E-02\n                           19  :  -1.24215636E-01\n                           20  :   9.56591762E-02\n                           21  :  -3.82258330E-02\n                           22  :   2.67529212E-01\n                           23  :  -3.76858856E-01\n                           24  :  -2.63986903E-02\n                           25  :  -1.50087385E-01\n                           26  :   7.65836420E-02\n                           27  :  -3.41458088E-02\n                           28  :   3.00098534E-01\n                           29  :  -3.79156341E-01\n                           30  :  -1.47219650E-02\n                           31  :  -1.19215743E-01\n                           32  :   3.77292104E-02\n                           33  :  -2.44142034E-02\n                           34  :   3.67063440E-01\n                           35  :  -3.82923377E-01\n--------------------------------\n--------------------------------\ndEdG                       [*] : 37\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n                           36  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 36\n--------------------------------\n                            0  :   1.00040931E-01   3.13505710E-02   1.88449189E-02\n                            1  :  -1.31422917E-01   5.77604664E-02  -6.82880162E-02\n                            2  :  -1.20053512E-01   6.65446568E-02  -7.42624405E-02\n                            3  :   9.51607160E-02   2.98212216E-02   1.79256226E-02\n                            4  :  -1.03040310E-01   7.80791962E-02  -8.17276409E-02\n                            5  :   8.72475805E-02   2.73414235E-02   1.64350087E-02\n                            6  :  -7.66293407E-02   9.39725310E-02  -9.14014261E-02\n                            7  :   7.32061227E-02   2.29411474E-02   1.37899900E-02\n                            8  :  -3.89230613E-02   1.14305999E-01  -1.02830173E-01\n                            9  :   5.22034031E-02   1.63593688E-02   9.83366393E-03\n                           10  :   2.05440397E-02   1.44491615E-01  -1.18368245E-01\n                           11  :   2.59117063E-02   8.12014420E-03   4.88104216E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   5.27325623E-03   4.53325489E-03   7.57935828E-03\n                           14  :  -2.79544838E-02   1.23944187E-01  -1.09339055E-01\n                           15  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           16  :   3.69788575E-01   1.07036062E-01   4.09649154E-02\n                           17  :  -6.58553319E-01  -5.42662442E-02  -6.73744347E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   1.49902784E-03   2.14813155E-03   2.38761212E-04\n                           20  :  -2.74959384E-02   1.84203767E-01  -1.70493404E-01\n                           21  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           22  :   3.90483825E-01   1.11551838E-01   3.72291807E-02\n                           23  :  -6.63744844E-01  -1.26600989E-02  -1.10964279E-01\n                           24  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           25  :   1.89057374E-03   4.26574388E-03  -2.92163048E-05\n                           26  :  -3.31264062E-02   3.01886240E-01  -2.76649646E-01\n                           27  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           28  :   4.26237105E-01   1.17866944E-01   2.74863747E-02\n                           29  :  -6.64773082E-01  -1.38232738E-02  -1.21225738E-01\n                           30  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           31  :   1.49222526E-03   6.45581193E-03  -3.47133170E-04\n                           32  :  -4.21155652E-02   5.03131497E-01  -4.57971358E-01\n                           33  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           34  :   5.06078600E-01   1.30558850E-01   1.07685438E-03\n                           35  :  -6.65714628E-01  -2.02650757E-02  -1.38186880E-01\n--------------------------------\n--------------------------------\nneighbors                  [*] : 5\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 5\ntag                            : 5\nelement                        : 1\nd                              :   7.49603389E+00\ndr                             :   7.41875943E+00   9.18471759E-02   1.06962461E+00\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.49007333E-04\n                            1  :  -1.47837184E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   4.39581332E-03   5.44219075E-05   6.33781180E-04\n                            1  :   2.78591631E-03   3.44907458E-05   4.01668860E-04\n                            2  :   1.52811719E-03   1.89186952E-05   2.20321438E-04\n                            3  :   6.56799012E-04   8.13143154E-06   9.46962080E-05\n                            4  :   2.08576939E-04   2.58226500E-06   3.00722822E-05\n                            5  :   3.29503869E-05   4.07938822E-07   4.75073292E-06\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   6.98338819E-06   5.55304142E-07   3.85299178E-06\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   7.31206939E-03   8.98492067E-05   1.03992403E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   8.41770842E-09   3.00116930E-09   1.11654679E-08\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   7.37307844E-03   9.02505661E-05   1.04647350E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   1.33294960E-14   1.17724730E-14   4.09374429E-14\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   7.43373405E-03   9.02955877E-05   1.05080588E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   2.76375751E-26   8.41624162E-26   2.85704357E-25\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   7.54646936E-03   9.02688515E-05   1.05811131E-03\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 7\ntag                            : 7\nelement                        : 1\nd                              :   4.90663294E+00\ndr                             :   4.86575733E+00   3.14966220E-03   6.32014592E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   5.00340188E-02\n                            1  :  -4.40045869E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.31105417E-01   8.48660851E-05   1.70293196E-02\n                            1  :   1.24203808E-01   8.03985921E-05   1.61328677E-02\n                            2  :   1.13297926E-01   7.33390860E-05   1.47162996E-02\n                            3  :   9.65339134E-02   6.24875424E-05   1.25388172E-02\n                            4  :   7.43517518E-02   4.81287672E-05   9.65757001E-03\n                            5  :   4.58066698E-02   2.96511984E-05   5.94984126E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   1.59903354E-02   3.23577048E-03   7.68788884E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   6.47574592E-01  -8.38315710E-03   6.08908997E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   1.49656516E-02   8.56656138E-04   1.60043466E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   6.52440014E-01  -1.02482068E-02   5.68736792E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   1.46838960E-02   6.62605875E-04   1.61932116E-03\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   6.57159489E-01  -1.37869709E-02   4.82442689E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   1.36588107E-02   3.02619970E-04   1.64460979E-03\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   6.65812093E-01  -2.09460771E-02   3.06547073E-02\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 8\ntag                            : 8\nelement                        : 1\nd                              :   2.57437738E+00\ndr                             :   2.51407533E+00   8.60879382E-02   5.47204713E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.05744515E-01\n                            1  :  -8.51443707E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   2.49814607E-01   8.55424821E-03   5.43737605E-02\n                            1  :   2.85031481E-01   9.76015803E-03   6.20389405E-02\n                            2  :   3.30054285E-01   1.13018463E-02   7.18384441E-02\n                            3  :   3.89724105E-01   1.33450833E-02   8.48259654E-02\n                            4  :   4.61670228E-01   1.58086902E-02   1.00485503E-01\n                            5  :   5.58890451E-01   1.91377426E-02   1.21646112E-01\n                            6  :   1.30769483E-02   2.15165191E-03   2.66752770E-03\n                            7  :   8.76107819E-01   5.95326895E-02   1.48720206E-01\n                            8  :   1.89749045E-04   2.26854429E-04   1.81822125E-05\n                            9  :   2.39169588E-02   4.16313434E-02   2.90588760E-02\n                           10  :   1.68194622E-02   2.46427380E-03   3.46275711E-03\n                           11  :   8.67992483E-01   3.32014903E-02   1.85754472E-01\n                           12  :   3.53604058E-06   7.88915426E-06  -4.53148841E-08\n                           13  :   4.50775453E-03   2.18360238E-02   5.40602315E-02\n                           14  :   2.35772138E-02   2.60493632E-03   4.94314487E-03\n                           15  :   8.38719170E-01  -2.73671088E-02   2.32572959E-01\n                           16  :   1.20135020E-09   5.25327365E-09  -2.85329337E-10\n                           17  :   1.80262563E-04   2.75189697E-02   7.19316352E-02\n                           18  :   2.19971988E-02   8.47202134E-04   4.77797417E-03\n                           19  :   7.56350328E-01  -1.35491231E-01   3.08558491E-01\n                           20  :   1.37965914E-16   1.23654313E-15  -9.92022942E-17\n                           21  :  -7.64393434E-03   4.11208840E-02   1.06474061E-01\n--------------------------------\n********************************\n                            3  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 10\ntag                            : 10\nelement                        : 1\nd                              :   2.35583408E+00\ndr                             :  -2.27882783E+00  -5.96461021E-01  -3.36479352E-02\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.24600844E-01\n                            1  :  -8.73630856E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -2.53892921E-01  -6.64540026E-02  -3.74884509E-03\n                            1  :  -2.91967694E-01  -7.64197042E-02  -4.31103653E-03\n                            2  :  -3.41840019E-01  -8.94733003E-02  -5.04742422E-03\n                            3  :  -4.10285477E-01  -1.07388233E-01  -6.05805271E-03\n                            4  :  -4.97307495E-01  -1.30165400E-01  -7.34297261E-03\n                            5  :  -6.25274111E-01  -1.63659417E-01  -9.23245821E-03\n                            6  :   1.10793139E-03  -4.09441048E-03  -1.47242063E-02\n                            7  :  -8.64150654E-01  -1.86713203E-01  -4.70728934E-02\n                            8  :  -2.38062032E-02   1.03887967E-02   5.55251852E-02\n                            9  :  -2.02503008E-02   2.09282086E-02  -2.36152650E-02\n                           10  :   2.29062472E-05  -7.81319393E-05  -2.82502220E-04\n                           11  :  -8.55462205E-01  -2.18261917E-01  -1.68615139E-02\n                           12  :  -2.63166195E-02   1.45758383E-02   7.17742770E-02\n                           13  :  -5.76002715E-04   9.82031292E-04  -1.01610567E-03\n                           14  :   3.62681932E-09  -1.19171970E-08  -4.32041764E-08\n                           15  :  -8.20276660E-01  -2.75181737E-01   4.24573660E-02\n                           16  :  -3.13045097E-02   2.38203579E-02   1.07170407E-01\n                           17  :  -4.03638093E-07   9.79454879E-07  -9.71778875E-07\n                           18  :   2.02806066E-17  -6.54458269E-17  -2.37579150E-16\n                           19  :  -7.27893574E-01  -3.67942887E-01   1.47768257E-01\n                           20  :  -4.33556324E-02   4.72647994E-02   1.96418590E-01\n                           21  :  -1.53222151E-13   4.66320132E-13  -4.53376115E-13\n--------------------------------\n********************************\n                            4  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 11\ntag                            : 11\nelement                        : 0\nd                              :   4.33366523E+00\ndr                             :  -4.07013022E+00  -1.27548699E+00  -7.66698920E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   7.87831041E-02\n                            1  :  -5.62508862E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.00040931E-01  -3.13505710E-02  -1.88449189E-02\n                            1  :  -9.51607160E-02  -2.98212216E-02  -1.79256226E-02\n                            2  :  -8.72475805E-02  -2.73414235E-02  -1.64350087E-02\n                            3  :  -7.32061227E-02  -2.29411474E-02  -1.37899900E-02\n                            4  :  -5.22034031E-02  -1.63593688E-02  -9.83366393E-03\n                            5  :  -2.59117063E-02  -8.12014420E-03  -4.88104216E-03\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -1.94581359E-02  -2.59049632E-03   4.47732033E-03\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -3.46172121E-01  -1.17651714E-01  -9.65082828E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -1.83413963E-02  -4.53427342E-03  -3.41901610E-03\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -3.64170742E-01  -1.26135566E-01  -1.09003412E-01\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -2.54677912E-02  -6.87066828E-03  -4.91388536E-03\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -3.94932597E-01  -1.41687307E-01  -1.34656781E-01\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -2.34894240E-02  -7.30301407E-03  -4.43084100E-03\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -4.62722967E-01  -1.77823650E-01  -1.97495444E-01\n--------------------------------\n********************************\n--------------------------------\n********************************\n                           10  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 10\nindexStructure                 : 0\ntag                            : 10\nelement                        : 1\nnumNeighbors                   : 4\nnumNeighborsUnique             : 5\nnumSymmetryFunctions           : 36\nenergy                         :  -1.78640854E-01\nchi                            :  -1.60732085E-01\ncharge                         :   2.32183987E-02\nchargeRef                      :   0.00000000E+00\nr                              :   1.08704946E+01   5.15802237E-01   4.35854441E-01\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 5\n--------------------------------\n                            0  : 10\n                            1  : 7\n                            2  : 8\n                            3  : 9\n                            4  : 11\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 1\n                            1  : 3\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 22\n                            1  : 22\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 36\n--------------------------------\n                            0  :   3.12678605E-01\n                            1  :  -6.04512393E-01\n                            2  :  -5.99558260E-01\n                            3  :   3.18049471E-01\n                            4  :  -5.92290519E-01\n                            5  :   3.22613034E-01\n                            6  :  -5.80528208E-01\n                            7  :   3.26547997E-01\n                            8  :  -5.61181005E-01\n                            9  :   3.27770392E-01\n                           10  :  -5.28970631E-01\n                           11  :   3.22588895E-01\n                           12  :  -3.98169770E-02\n                           13  :   3.12243492E-01\n                           14  :  -5.95024281E-01\n                           15  :  -3.49080250E-02\n                           16  :  -1.00289260E-01\n                           17  :  -3.62614376E-01\n                           18  :  -3.60654596E-02\n                           19  :   4.09512128E-01\n                           20  :  -6.04650100E-01\n                           21  :  -3.82258330E-02\n                           22  :  -1.06371299E-01\n                           23  :  -3.63630685E-01\n                           24  :  -2.63986903E-02\n                           25  :   5.74288140E-01\n                           26  :  -6.07475747E-01\n                           27  :  -3.41458088E-02\n                           28  :  -1.09930694E-01\n                           29  :  -3.69790730E-01\n                           30  :  -1.47219650E-02\n                           31  :   5.14222837E-01\n                           32  :  -5.92822030E-01\n                           33  :  -2.44142034E-02\n                           34  :  -1.23217933E-01\n                           35  :  -3.81833583E-01\n--------------------------------\n--------------------------------\ndEdG                       [*] : 37\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n                           36  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 36\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n                           25  :   0.00000000E+00\n                           26  :   0.00000000E+00\n                           27  :   0.00000000E+00\n                           28  :   0.00000000E+00\n                           29  :   0.00000000E+00\n                           30  :   0.00000000E+00\n                           31  :   0.00000000E+00\n                           32  :   0.00000000E+00\n                           33  :   0.00000000E+00\n                           34  :   0.00000000E+00\n                           35  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 36\n--------------------------------\n                            0  :   1.48657311E-01   5.63512758E-02   6.08347250E-02\n                            1  :  -3.96795181E-01  -8.61623216E-02  -2.07595334E-02\n                            2  :  -4.24752582E-01  -9.48987896E-02  -2.01969616E-02\n                            3  :   1.69642192E-01   6.43059791E-02   6.94223246E-02\n                            4  :  -4.61102825E-01  -1.06203456E-01  -1.93792780E-02\n                            5  :   1.95052697E-01   7.39382961E-02   7.98210130E-02\n                            6  :  -5.10850543E-01  -1.21589184E-01  -1.81878897E-02\n                            7  :   2.33848607E-01   8.86445962E-02   9.56973833E-02\n                            8  :  -5.74514543E-01  -1.41116895E-01  -1.66789006E-02\n                            9  :   2.92206211E-01   1.10766115E-01   1.19578945E-01\n                           10  :  -6.73095083E-01  -1.70461166E-01  -1.50238873E-02\n                           11  :   3.87870410E-01   1.47029381E-01   1.58727408E-01\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -4.82345035E-02   2.33239810E-02   1.17964549E-01\n                           14  :  -9.29668173E-03   7.40033914E-03  -8.85017707E-03\n                           15  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           16  :   1.47846198E-02  -1.19716760E-02  -5.25641177E-02\n                           17  :  -6.64121234E-01  -1.23751183E-01  -5.30244711E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -8.52716337E-02   4.84757329E-02   2.33171256E-01\n                           20  :  -8.13519336E-05   9.71466057E-05  -1.06035538E-04\n                           21  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           22  :   1.07145802E-03  -8.51455404E-04  -3.76194515E-03\n                           23  :  -6.63255765E-01  -1.30324363E-01  -4.69764550E-02\n                           24  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           25  :  -1.81523075E-01   1.17280180E-01   5.44221063E-01\n                           26  :  -4.86064571E-09   7.50857369E-09  -7.78390136E-09\n                           27  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           28  :   2.64607859E-06  -2.08095297E-06  -9.24223812E-06\n                           29  :  -6.55942585E-01  -1.42379918E-01  -3.44793140E-02\n                           30  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           31  :  -2.73944777E-01   1.92743045E-01   8.74647150E-01\n                           32  :  -1.23793870E-17   2.22979619E-17  -2.14971353E-17\n                           33  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           34  :   7.90161854E-12  -6.17585907E-12  -2.75483407E-11\n                           35  :  -6.40559686E-01  -1.66085938E-01  -9.65774905E-03\n--------------------------------\n--------------------------------\nneighbors                  [*] : 4\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 7\ntag                            : 7\nelement                        : 1\nd                              :   7.20053726E+00\ndr                             :   7.14458517E+00   5.99610684E-01   6.65662527E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   9.88092704E-04\n                            1  :  -3.68326655E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.09799681E-02   9.21495930E-04   1.02300597E-03\n                            1  :   7.36244493E-03   6.17894606E-04   6.85960568E-04\n                            2  :   4.34060315E-03   3.64285954E-04   4.04414924E-04\n                            3  :   2.05775840E-03   1.72697769E-04   1.91721790E-04\n                            4  :   7.42531521E-04   6.23171006E-05   6.91818205E-05\n                            5  :   1.42812306E-04   1.19855502E-05   1.33058531E-05\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   1.46334705E-04   6.34864647E-05   3.49794889E-06\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   2.15312857E-02   1.47258233E-03   2.03635922E-03\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   1.21379644E-06   8.34444284E-07  -1.84275541E-07\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   2.16179290E-02   1.43914166E-03   2.05205419E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   9.48256368E-11   1.23586574E-10  -4.20966637E-11\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   2.16104344E-02   1.36039125E-03   2.06591392E-03\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :   5.67979294E-19   1.51839786E-18  -5.95576380E-19\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :   2.15706498E-02   1.20348452E-03   2.08950422E-03\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 8\ntag                            : 8\nelement                        : 1\nd                              :   4.87598027E+00\ndr                             :   4.79290317E+00   6.82548960E-01   5.80852648E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   5.13930914E-02\n                            1  :  -4.46709989E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   1.31922293E-01   1.87868230E-02   1.59876823E-02\n                            1  :   1.25422443E-01   1.78611908E-02   1.51999645E-02\n                            2  :   1.14922203E-01   1.63658699E-02   1.39274388E-02\n                            3  :   9.85073071E-02   1.40282534E-02   1.19381152E-02\n                            4  :   7.64645168E-02   1.08891781E-02   9.26674617E-03\n                            5  :   4.76781595E-02   6.78976333E-03   5.77812325E-03\n                            6  :   1.19778842E-02   2.19979712E-03   2.05290444E-03\n                            7  :   5.12406864E-03   8.96627020E-03  -6.75231782E-03\n                            8  :   2.45638660E-04   1.11316916E-04   1.22677087E-04\n                            9  :   6.61506715E-01   6.52188599E-02   1.06278405E-01\n                           10  :   1.52952377E-02   2.70824951E-03   2.49879165E-03\n                           11  :   2.97253406E-05   1.06761423E-04  -8.78930647E-05\n                           12  :   6.39002775E-06   4.83905284E-06   5.55644814E-06\n                           13  :   6.63694235E-01   5.91951512E-02   1.12216445E-01\n                           14  :   2.11335850E-02   3.46499385E-03   3.11544370E-03\n                           15  :   9.69980136E-10   7.75330482E-09  -6.67405591E-09\n                           16  :   4.15004655E-09   6.37056868E-09   7.53722822E-09\n                           17  :   6.62485106E-01   4.66436191E-02   1.23154440E-01\n                           18  :   1.91559731E-02   2.64399187E-03   2.21930752E-03\n                           19  :   9.42660375E-19   2.02427598E-17  -1.78192751E-17\n                           20  :   1.54120182E-15   6.89081860E-15   8.30643194E-15\n                           21  :   6.59189768E-01   2.16970388E-02   1.44674605E-01\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 9\ntag                            : 9\nelement                        : 1\nd                              :   2.35583408E+00\ndr                             :   2.27882783E+00   5.96461021E-01   3.36479352E-02\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.24600844E-01\n                            1  :  -8.73630856E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :   2.53892921E-01   6.64540026E-02   3.74884509E-03\n                            1  :   2.91967694E-01   7.64197042E-02   4.31103653E-03\n                            2  :   3.41840019E-01   8.94733003E-02   5.04742422E-03\n                            3  :   4.10285477E-01   1.07388233E-01   6.05805271E-03\n                            4  :   4.97307495E-01   1.30165400E-01   7.34297261E-03\n                            5  :   6.25274111E-01   1.63659417E-01   9.23245821E-03\n                            6  :   4.45279607E-01   1.21676803E-01   2.38193621E-02\n                            7  :   4.02627838E-03  -1.64300958E-02   1.55989969E-02\n                            8  :   1.01111565E-02   1.08060924E-02   2.75822470E-02\n                            9  :  -1.89167672E-02   5.70597405E-02  -5.52902932E-02\n                           10  :   5.67089833E-01   1.42888130E-01  -1.02595270E-02\n                           11  :   5.04127965E-05  -2.04742473E-04   1.94112878E-04\n                           12  :   2.77456878E-04   6.34744739E-04   1.89398158E-03\n                           13  :  -2.20563986E-02   6.96900697E-02  -6.72920439E-02\n                           14  :   7.79308477E-01   1.63782328E-01  -1.23627597E-01\n                           15  :   3.79583993E-09  -1.53854651E-08   1.45000539E-08\n                           16  :   1.44023752E-07   1.39351266E-06   4.56044443E-06\n                           17  :  -2.81529552E-02   9.43759080E-02  -9.07410397E-02\n                           18  :   6.98467134E-01   9.04842683E-02  -3.00113812E-01\n                           19  :   1.08687474E-17  -4.40591195E-17   3.99119868E-17\n                           20  :  -3.65669706E-13   3.91106805E-12   1.34655822E-11\n                           21  :  -4.02007327E-02   1.43185415E-01  -1.37106360E-01\n--------------------------------\n********************************\n                            3  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 11\ntag                            : 11\nelement                        : 0\nd                              :   2.05114706E+00\ndr                             :  -1.79130239E+00  -6.79025970E-01  -7.33050985E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.51621125E-01\n                            1  :  -8.98915265E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 22\n--------------------------------\n                            0  :  -1.48657311E-01  -5.63512758E-02  -6.08347250E-02\n                            1  :  -1.69642192E-01  -6.43059791E-02  -6.94223246E-02\n                            2  :  -1.95052697E-01  -7.39382961E-02  -7.98210130E-02\n                            3  :  -2.33848607E-01  -8.86445962E-02  -9.56973833E-02\n                            4  :  -2.92206211E-01  -1.10766115E-01  -1.19578945E-01\n                            5  :  -3.87870410E-01  -1.47029381E-01  -1.58727408E-01\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -4.09022988E-01  -1.47200581E-01  -1.43836816E-01\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -2.51414149E-02   1.05426668E-03   2.48591937E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -4.97113437E-01  -1.94072112E-01  -2.25410521E-01\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.35530493E-03   2.11871612E-04   1.86240712E-03\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -6.18918988E-01  -2.84527502E-01  -4.23708910E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -2.79425239E-06   6.81069739E-07   4.67425646E-06\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -4.43678330E-01  -2.85871305E-01  -5.76752645E-01\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -7.53749004E-12   2.25790021E-12   1.40744521E-11\n--------------------------------\n********************************\n--------------------------------\n********************************\n                           11  :\n********************************\nATOM                            \n********************************\nhasNeighborList                : 1\nhasSymmetryFunctions           : 1\nhasSymmetryFunctionDerivatives : 1\nuseChargeNeuron                : 1\nindex                          : 11\nindexStructure                 : 0\ntag                            : 11\nelement                        : 0\nnumNeighbors                   : 3\nnumNeighborsUnique             : 4\nnumSymmetryFunctions           : 24\nenergy                         :  -4.32601584E-01\nchi                            :  -2.25971939E-01\ncharge                         :  -2.43509816E-02\nchargeRef                      :   0.00000000E+00\nr                              :   1.26617970E+01   1.19482821E+00   1.16890543E+00\nf                              :   0.00000000E+00   0.00000000E+00   0.00000000E+00\nfRef                           :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n--------------------------------\nneighborsUnique            [*] : 4\n--------------------------------\n                            0  : 11\n                            1  : 8\n                            2  : 9\n                            3  : 10\n--------------------------------\n--------------------------------\nnumNeighborsPerElement     [*] : 2\n--------------------------------\n                            0  : 0\n                            1  : 3\n--------------------------------\n--------------------------------\nnumSymmetryFunctionDeriv.  [*] : 2\n--------------------------------\n                            0  : 12\n                            1  : 18\n--------------------------------\n--------------------------------\ncacheSizePerElement        [*] : 2\n--------------------------------\n                            0  : 2\n                            1  : 2\n--------------------------------\n--------------------------------\nG                          [*] : 24\n--------------------------------\n                            0  :  -3.05308224E-01\n                            1  :  -1.11516837E-01\n                            2  :  -2.99082475E-01\n                            3  :  -2.94001590E-01\n                            4  :  -1.00257031E-01\n                            5  :  -2.87048131E-01\n                            6  :  -2.79323448E-01\n                            7  :  -8.81083774E-02\n                            8  :  -2.70907254E-01\n                            9  :  -7.13637048E-02\n                           10  :  -4.82560457E-02\n                           11  :  -2.26533602E-02\n                           12  :  -1.94457034E-01\n                           13  :  -1.41686466E-01\n                           14  :  -2.95734094E-01\n                           15  :  -1.08532163E-01\n                           16  :  -1.57079385E-01\n                           17  :  -9.88205181E-02\n                           18  :  -2.99446306E-01\n                           19  :  -8.98301899E-02\n                           20  :  -2.98667049E-01\n                           21  :  -2.09861681E-02\n                           22  :  -2.81563307E-01\n                           23  :   8.84240526E-02\n--------------------------------\n--------------------------------\ndEdG                       [*] : 25\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n                           24  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndQdG                       [*] : 24\n--------------------------------\n                            0  :   0.00000000E+00\n                            1  :   0.00000000E+00\n                            2  :   0.00000000E+00\n                            3  :   0.00000000E+00\n                            4  :   0.00000000E+00\n                            5  :   0.00000000E+00\n                            6  :   0.00000000E+00\n                            7  :   0.00000000E+00\n                            8  :   0.00000000E+00\n                            9  :   0.00000000E+00\n                           10  :   0.00000000E+00\n                           11  :   0.00000000E+00\n                           12  :   0.00000000E+00\n                           13  :   0.00000000E+00\n                           14  :   0.00000000E+00\n                           15  :   0.00000000E+00\n                           16  :   0.00000000E+00\n                           17  :   0.00000000E+00\n                           18  :   0.00000000E+00\n                           19  :   0.00000000E+00\n                           20  :   0.00000000E+00\n                           21  :   0.00000000E+00\n                           22  :   0.00000000E+00\n                           23  :   0.00000000E+00\n--------------------------------\n--------------------------------\ndGdr                       [*] : 24\n--------------------------------\n                            0  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            1  :  -1.22535847E+00  -4.22840955E-01  -3.84905528E-01\n                            2  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            3  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            4  :  -1.28610289E+00  -4.51354353E-01  -4.19145667E-01\n                            5  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :  -1.35735645E+00  -4.83750849E-01  -4.59819714E-01\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -1.45374553E+00  -5.27051879E-01  -5.17113939E-01\n                           10  :  -1.53160998E+00  -5.65072239E-01  -5.75220790E-01\n                           11  :  -1.65757920E+00  -6.21500964E-01  -6.55384123E-01\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.00488603E-01  -2.03338949E-03   7.68266782E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -1.13133919E+00  -3.80028163E-01  -3.17304366E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -1.09759588E-02   6.34852290E-04   1.11728579E-02\n                           18  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           19  :  -1.34672334E+00  -4.62733088E-01  -4.11994899E-01\n                           20  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           21  :  -1.58052248E+00  -5.68466747E-01  -5.67619952E-01\n                           22  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           23  :  -1.15042028E+00  -4.54291264E-01  -5.47341262E-01\n--------------------------------\n--------------------------------\nneighbors                  [*] : 3\n--------------------------------\n                            0  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 8\ntag                            : 8\nelement                        : 1\nd                              :   6.85069280E+00\ndr                             :   6.58420556E+00   1.36157493E+00   1.31390363E+00\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.90481085E-03\n                            1  :  -7.47900274E-03\n--------------------------------\n--------------------------------\ndGdr                       [*] : 18\n--------------------------------\n                            0  :   6.35852852E-02   1.31490625E-02   1.26886891E-02\n                            1  :   3.90504660E-02   8.07540637E-03   7.79267122E-03\n                            2  :   2.12038712E-02   4.38483569E-03   4.23131435E-03\n                            3  :   7.97493279E-03   1.64916913E-03   1.59142862E-03\n                            4  :   1.61613530E-03   3.34207261E-04   3.22506037E-04\n                            5  :   9.54576058E-05   1.97400707E-05   1.90489337E-05\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   1.60395737E-03   9.93397084E-04   7.17982051E-04\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   6.48155748E-02   1.18832359E-02   1.22820783E-02\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   1.15063664E-04   1.03038244E-04   1.05015677E-04\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   7.85133421E-02   1.41656598E-02   1.47438017E-02\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   9.54841715E-02   1.66734648E-02   1.76124912E-02\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   7.48572399E-02   1.22109085E-02   1.33320115E-02\n--------------------------------\n********************************\n                            1  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 9\ntag                            : 9\nelement                        : 1\nd                              :   4.33366523E+00\ndr                             :   4.07013022E+00   1.27548699E+00   7.66698920E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   7.87831041E-02\n                            1  :  -5.62508862E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 18\n--------------------------------\n                            0  :   4.67332901E-01   1.46451588E-01   8.80324734E-02\n                            1  :   4.48146143E-01   1.40438891E-01   8.44182237E-02\n                            2  :   4.12950638E-01   1.29409414E-01   7.77883731E-02\n                            3  :   3.44691840E-01   1.08018646E-01   6.49303208E-02\n                            4  :   2.31906666E-01   7.26743175E-02   4.36847425E-02\n                            5  :   1.03794317E-01   3.25267973E-02   1.95519519E-02\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   1.84816204E-02   3.15728306E-02   9.18873253E-02\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :   1.16521748E+00   3.37785388E-01   1.22400595E-01\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :  -2.83935327E-04   3.51299089E-03   1.21175699E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :   1.41480373E+00   4.01581492E-01   1.19251535E-01\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :   1.72849478E+00   4.70047817E-01   7.50526781E-02\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :   1.36671105E+00   3.40152997E-01  -4.89585029E-02\n--------------------------------\n********************************\n                            2  :\n********************************\nNEIGHBOR                        \n********************************\nindex                          : 10\ntag                            : 10\nelement                        : 1\nd                              :   2.05114706E+00\ndr                             :   1.79130239E+00   6.79025970E-01   7.33050985E-01\n--------------------------------\ncache                      [*] : 2\n--------------------------------\n                            0  :   2.51621125E-01\n                            1  :  -8.98915265E-02\n--------------------------------\n--------------------------------\ndGdr                       [*] : 18\n--------------------------------\n                            0  :   6.94440283E-01   2.63240305E-01   2.84184365E-01\n                            1  :   7.98906285E-01   3.02840055E-01   3.26934772E-01\n                            2  :   9.23201939E-01   3.49956599E-01   3.77800026E-01\n                            3  :   1.10107876E+00   4.17384063E-01   4.50592189E-01\n                            4  :   1.29808718E+00   4.92063714E-01   5.31213541E-01\n                            5  :   1.55368943E+00   5.88954426E-01   6.35813122E-01\n                            6  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            7  :   8.04030249E-02  -3.05328382E-02  -1.69431986E-01\n                            8  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                            9  :  -9.86938698E-02   3.03595388E-02   1.82621693E-01\n                           10  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           11  :   1.11448305E-02  -4.25088142E-03  -2.33954435E-02\n                           12  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           13  :  -1.46593735E-01   4.69859362E-02   2.77999562E-01\n                           14  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           15  :  -2.43456473E-01   8.17454648E-02   4.74954782E-01\n                           16  :   0.00000000E+00   0.00000000E+00   0.00000000E+00\n                           17  :  -2.91148007E-01   1.01927359E-01   5.82967753E-01\n--------------------------------\n********************************\n--------------------------------\n********************************\n--------------------------------\n********************************\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/weights.001.data",
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  },
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  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/hdnnp-data/weightse.006.data",
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0.9514517105\n     -0.5609427673\n     -0.2681244852\n     -0.2380255405\n     -0.6299317154\n     -0.0444312503\n      0.6723833199\n     -0.1755227672\n      0.0214165418\n     -0.5909926702\n      0.1439287461\n     -0.4741347554\n     -0.7723338598\n     -0.2175892032\n     -0.1319381853\n      0.8237379200\n     -0.6223845297\n      0.0655192356\n      0.0791274955\n      0.0241765665\n     -0.2064087004\n     -0.3940068910\n     -0.5444628729\n     -0.1359227526\n      0.3800822323\n      0.5993674359\n     -0.7269496390\n      0.8367187022\n      0.1374179268\n      0.7344415866\n     -0.2551345486\n     -0.1743276516\n      0.9910772307\n      0.3316258177\n      1.2238138235\n     -0.4179177766\n     -0.2008342288\n      0.6387734163\n     -0.1928348474\n      0.6881137644\n     -0.7000929936\n      0.0735157620\n     -0.3324781162\n      0.0420307653\n      0.9959977273\n     -0.7450342041\n     -0.8529960883\n      0.2969544922\n     -0.0602600691\n      0.2766838148\n     -0.1003145324\n      0.1700644349\n     -0.0641415901\n     -0.9352716760\n     -0.6402313900\n     -0.4651572692\n      0.7722681957\n      1.0887719406\n     -0.4964838793\n      0.7038089902\n     -0.7986021023\n      0.5782880196\n     -0.6165892783\n     -1.0079411424\n     -0.9160050730\n      0.7999285374\n      0.1367149508\n     -0.0647141492\n      0.7688656893\n      0.2878636341\n     -0.3722237651\n      0.1111473417\n      0.3828950059\n     -0.4378732916\n     -0.1316414863\n     -0.1096866025\n     -0.3705437296\n     -0.4851148132\n      0.6206502475\n      0.7147946611\n     -0.0178212911\n      0.3792484954\n     -0.2507005539\n      1.0659073038\n     -0.2027245679\n      0.2017199777\n      0.3003215698\n     -0.8389435343\n     -0.6369460665\n     -0.0933321836\n      0.5776260865\n     -0.5767028069\n     -0.4353569523\n     -0.7078700015\n     -0.4528725887\n      0.4402600593\n      0.0847773972\n      0.2788315779\n      0.2652386196\n     -0.5934642654\n      0.0606796684\n     -0.0240946437\n     -0.5221134615\n     -0.2158837878\n     -0.1666201799\n      0.2831691942\n      0.1548712159\n      0.4069982742\n      0.0614233895\n      0.0076948724\n      0.1343740575\n     -0.1587786167\n     -0.2949905912\n      0.0568310441\n      0.2915891973\n      0.2089325098\n      0.0021438982\n      0.1311775629\n     -0.6705841369\n      0.7347319618\n     -0.1484791977\n     -0.2162294124\n      0.8309982253\n     -0.0401276045\n      0.8479086493\n     -0.2065159209\n      0.9296989088\n     -0.0481041026\n      0.5809043146\n      0.4089903880\n      0.2223221997\n      0.1160041545\n     -0.4602602639\n     -0.1334080950\n     -0.0435590321\n      1.0788682386\n      0.1605417540\n      0.4218863145\n     -0.3317259475\n      0.4283293595\n      0.0611642978\n      0.9183707139\n     -0.2723340672\n     -1.0920471036\n     -0.3713786255\n     -0.2472463119\n     -0.4721194768\n      1.4978735406\n      0.3286069439\n      0.0938603768\n      0.1690412455\n     -0.5012145404\n      0.6166936354\n     -0.8298359733\n     -0.6693731422\n      0.5221510234\n      0.4215053294\n      0.0656388111\n      0.4861742881\n     -0.0081073075\n     -0.4925803428\n     -0.6600221667\n      0.1272019508\n     -0.0090456956\n     -1.3715130022\n      0.3109905053\n      0.4535667158\n     -1.6915038027\n      0.8338429940\n      2.2347737978\n      0.0804225592\n     -0.0308499916\n     -0.1486614136\n      0.9753636261\n      0.3032806837\n      0.0604180499\n     -0.2851974368\n     -0.1318419288\n     -0.1369773622\n     -1.0050621724\n      0.4592854729\n     -0.5367611149\n     -0.7810309148\n     -0.9202002259\n      0.0669989367\n      1.7276884639\n     -0.9999769999\n      1.0285707457\n      1.1542196303\n     -0.6086259937\n     -0.0759605467\n     -0.9023685322\n     -0.1508870075\n      0.6164065665\n      0.3333376818\n     -0.7858766466\n      0.4294231053\n     -0.4407090829\n      0.7736383708\n     -0.2359834008\n     -0.0202907128\n     -0.2180730486\n     -0.6840055578\n     -0.8463543049\n     -0.1538054213\n      0.8565837683\n     -0.2703235873\n     -0.0508505534\n      0.0559036001\n     -1.2569307297\n      0.0145876741\n      0.3387996939\n      0.3199708674\n     -0.2029252897\n     -0.0472493730\n     -0.6309356950\n      0.8896411965\n     -2.0955514047\n      0.4279469201\n      0.0266378958\n      1.4070332400\n     -0.0294007300\n      0.3407484478\n     -0.8172902279\n      1.6487546807\n     -0.0623547386\n      0.3883346270\n      0.0784087968\n      0.5987994829\n     -2.0482785708\n     -0.0878347656\n     -1.5024420974\n      2.8311533001\n     -1.9208463310\n     -0.9728285530\n     -0.4000267303\n      0.0916188942\n      0.0652916261\n     -0.2063674689\n     -0.4998824884\n      0.5934900052\n     -0.3538291998\n     -0.2192364250\n      0.7330223549\n     -0.0143295732\n     -1.0152116046\n      0.4316079184\n     -2.2107091847\n     -2.7316551236\n     -0.6181078170\n     -2.3335805886\n     -0.2451520870\n     -0.3100282558\n      0.0797196058\n     -0.5008548511\n     -0.8840659238\n     -0.1130072915\n      0.2551511750\n     -0.3179275739\n      1.0384571273\n      0.6575601296\n      1.6034851298\n     -2.3886312909\n     -0.9339623524\n     -1.2643663283\n     -0.0148557048\n      0.1206068884\n      0.0133351930\n     -0.3060192388\n      1.2442941197\n      1.2913622498\n      0.4127824106\n     -0.0259057296\n     -0.6683841364\n     -0.7607917591\n     -1.5364039498\n     -2.0420547619\n      1.0021196401\n      0.6885654807\n      0.8722571125\n     -1.8557931911\n     -0.1943362643\n     -0.0334702134\n     -0.1250534993\n      0.7684573398\n     -0.6287528033\n     -0.1237433239\n      0.3552105233\n     -0.1326254090\n     -1.1625292734\n     -0.3730818618\n     -0.1193215635\n      5.2965831132\n     -0.4618024048\n     -0.0004434927\n      4.2724404576\n     -0.2706485705\n     -0.2992525783\n      0.4444540238\n      1.1950931653\n      0.2349044910\n     -0.1070516985\n      0.4369045762\n     -0.0444983410\n      0.2153442351\n     -1.1251010384\n     -1.4979626726\n     -0.5551913574\n     -2.0694528611\n      0.2606234991\n     -2.2022190083\n     -0.1144456894\n     -0.1258836280\n     -0.3684364718\n     -0.2583360506\n     -0.4544922852\n     -0.2618750396\n      0.2359057839\n      0.1613573769\n      0.9904412492\n     -0.1016524499\n     -1.0657100465\n      0.8605886894\n      0.1413029799\n     -0.1893761626\n     -3.7391061335\n      0.0036828432\n      0.3886376713\n     -0.6562280624\n      0.1083763220\n     -0.0391240429\n      0.2267509693\n     -0.2058136409\n     -0.1430979256\n      0.7009168993\n      0.4931955095\n      0.7863721995\n      0.2472528221\n     -1.2495204718\n      0.6875830102\n      1.9466142831\n      0.1023390652\n     -0.2558956548\n      0.2852365762\n      0.0029291118\n      0.9868865541\n      0.0403577509\n     -0.1047418136\n     -0.3488408483\n     -0.9674470264\n      0.1494635568\n      0.2065713356\n      2.3167621560\n     -0.4749087023\n      1.3388042843\n      2.6993169368\n      0.0429258126\n      0.0103415735\n      0.2764993198\n      0.6813767545\n     -0.4331521111\n      0.2551211682\n     -0.2364161739\n     -0.3079983949\n      0.6467916994\n     -1.5260399719\n      0.6265168530\n     -0.8105200453\n     -0.3736370520\n      0.3084884217\n     -0.2992212659\n     -0.0273815678\n      0.1049134175\n      0.2536801614\n     -1.1511637867\n     -0.9000689224\n      0.1443339389\n      0.0620394402\n      1.9992994309\n      0.7843928157\n      1.4391271323\n     -0.3321939402\n     -2.4382905743\n     -1.6734428117\n     -0.9249641999\n     -1.3018867082\n      0.0152212636\n      0.3104785525\n     -0.2492140028\n     -0.8955123746\n      0.9869474327\n      0.0822669444\n     -0.1830559445\n     -1.1230333927\n     -0.1385515232\n     -0.3696105195\n      0.1082286260\n      0.1748680549\n     -1.2177151081\n      0.1079492551\n     -0.2859594318\n     -0.3121904922\n      0.1034155480\n      0.1806808724\n     -0.2580117886\n      0.3535325828\n      0.0229540981\n      0.3238516401\n     -0.7821787424\n     -0.5357628124\n      1.2345527437\n      1.8953010665\n      0.3961253271\n     -0.4570288514\n      0.4972780485\n      1.5141288000\n      0.1366535654\n     -0.0558186183\n      0.5826411377\n     -0.1801513810\n      0.4953259346\n     -0.0545313333\n     -0.1340448904\n     -0.1234905918\n     -1.2417564423\n     -0.8220806959\n      0.1234736475\n     -0.3094409144\n      0.3831220587\n     -0.1464400551\n     -0.2343229869\n      0.0007787294\n     -0.4790095880\n      0.6993700632\n     -0.1998249300\n      0.2858428262\n     -0.2110018462\n      0.1624702703\n      0.6789582127\n     -0.4868270904\n     -0.2768406958\n     -0.7069002115\n     -0.6879166506\n     -2.0867370236\n     -0.7994656137\n      0.1719842944\n     -0.0000752220\n     -0.0003613176\n     -0.0029232214\n      0.0445647221\n      0.0222816566\n     -0.0003398342\n      0.0003305899\n     -0.0272082042\n     -0.0176071818\n      0.0295840498\n      0.0939072748\n     -0.0735707973\n      0.0340777246\n     -0.0573394490\n     -0.1135653336\n     -0.1319696539\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/md-external.lmp",
    "content": "###############################################################################\n# MD simulation for carbon chain\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"carbon-chain.data\"\n# Timesteps\nvariable numSteps        equal  5\nvariable dt              equal  0.0005\n# NN\nvariable nnpCutoff       equal  8.01\nvariable nnpDir          string \"nnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_O          equal  15.9994\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary s s s\natom_style atomic\nread_data ${cfgFile}\nmass 1 ${mass_H}\nmass 2 ${mass_O}\ntimestep ${dt}\nthermo 1\n\n###############################################################################\n# NN\n###############################################################################\npair_style nnp/external \"H C\" dir ${nnpDir} command \"/Users/emirkocer/CLionProjects/JonasRuNNer/build/RuNNer-gaussian.x\" cflength 1.0 cfenergy 1.0\n#pair_style nnp/external \"H C\" dir ${nnpDir} command \"nnp-predict 0\" cflength 1.0 cfenergy 1.0\npair_coeff * * ${nnpCutoff}\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\n#dump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/lammps-nnp/md.lmp",
    "content": "###############################################################################\n# MD simulation for carbon chain\n###############################################################################\n\n###############################################################################\n# VARIABLES\n###############################################################################\nclear\n# Configuration files\nvariable cfgFile         string \"carbon-chain.data\"\n# Timesteps\nvariable numSteps        equal  0\nvariable dt              equal  0.0005\n# NN\nvariable hdnnpCutoff     equal  8.01\nvariable hdnnpDir        string \"hdnnp-data\"\n# Masses\nvariable mass_H          equal  1.00794\nvariable mass_C          equal  12.0107\n\n###############################################################################\n# GENERAL SETUP\n###############################################################################\nunits metal\nboundary s s s\natom_style charge\natom_modify map yes\nread_data ${cfgFile}\nmass 1 ${mass_H}\nmass 2 ${mass_C}\ntimestep ${dt}\nthermo 1\n\n###############################################################################\n# NN\n###############################################################################\npair_style hdnnp/4g dir ${hdnnpDir} showew no showewsum 10 resetew no maxew 100 cflength 1.0 cfenergy 1.0 emap \"1:H,2:C\"\npair_coeff * * ${hdnnpCutoff}\nfix 1 all hdnnp 1 1.0e-8 1.0e-8 1.0e-2 100 nnp\n\n\n###############################################################################\n# INTEGRATOR\n###############################################################################\nfix INT all nve\n#dump 1 all atom 1 traj.dump\n\n###############################################################################\n# SIMULATION\n###############################################################################\nrun ${numSteps}\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/energy.out",
    "content": "################################################################################\n# Energy comparison.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    conf     Configuration index (starting with 1).\n# 2    natoms   Number of atoms in configuration.\n# 3    Eref     Reference potential energy.\n# 4    Ennp     Potential energy predicted by NNP.\n# 5    Ediff    Difference in energy per atom between reference and NNP prediction.\n# 6    E_offset Sum of atomic offset energies (included in column Ennp).\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#     conf     natoms                     Eref                     Ennp                    Ediff                 E_offset\n#########################################################################################################################\n         1         12  -3.8161152544399999E+02  -3.8161078713069378E+02  -6.1526108851239769E-05  -3.7839893392473289E+02\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/hardness.001.data",
    "content": "      0.0088953312\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/hardness.006.data",
    "content": "      0.0661189426\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/input.data",
    "content": "begin\natom 1.17284095486 -0.172504222684 -0.667448516865 C -0.00802366916667 0.0 0.0347925826351 -0.00110373556182 0.0172205087376\natom -1.1595434822 -0.350641000445 -0.467598107194 C -0.00855427916667 0.0 -0.0190916650141 0.00319122911054 0.00166842074686\natom 3.72594054969 -0.0837975179097 -0.229777168673 C -0.00986190916667 0.0 -0.0218470438236 -0.00628540399811 -0.0170756379211\natom -3.69146983116 -0.334172643167 -0.21088223315 C -0.0100583891667 0.0 -0.0301687534058 0.0106478678179 -0.00452518599678\natom 6.07758586771 -0.166745226042 -0.145024035228 C -0.00672012916667 0.0 0.00266924762633 -0.00156314063781 0.0115961079544\natom -6.06809789367 -0.00253733508489 -0.0705357610724 C -0.00417966916667 0.0 0.0380293993069 -0.012272279507 -0.00385017456324\natom 8.59164353464 -0.0806915075831 0.402236831619 C -0.0283825591667 0.0 0.0114358510185 0.0168883247486 -0.0145042007862\natom -8.60892564573 0.117192245354 0.0982851777904 C -0.0314335491667 0.0 -0.0313212312302 0.00897304604753 0.0196935694367\natom 10.8705405815 0.51581338865 0.435826522093 C -0.0539909791667 0.0 -0.0207616703214 -0.00491358425534 0.014173822701\natom -10.8879581104 0.411807821319 0.694948565342 C -0.0495567391667 0.0 0.0330796233985 -0.00720705271362 -0.0192967826535\natom 12.661965991 1.19502446714 1.1691448209 H 0.104980830833 0.0 -0.00448104672571 -0.00638001418343 -0.00747636563225\natom -12.9307322131 0.525058551796 0.728011456903 H 0.105781040833 0.0 0.00766470653545 2.474313253e-05 0.00237591797661\nenergy -381.611525444\ncharge  -0.0\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/input.nn",
    "content": "## #############################################################\n### This is the input file for RuNNer \n### #############################################################\n### General remarks: \n### - commands can be switched off by using the # character at the BEGINNING of the line\n### - the input file can be structured by blank lines and comment lines\n### - the order of the keywords is arbitrary\n### - if keywords are missing, default values will be used and written to runner.out\n### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message \n\n### THIS INPUT.NN IS AN EXAMPLE, IT IS NOT A REALISTIC CASE\n### It contains only a subset of all keywords\n\n########################################################################################################################\n### general keywords\n########################################################################################################################\nuse_electrostatics\nuse_short_nn\nnnp_gen 4 # nnp_type_gen --> nnp_gen \nrunner_mode 3\nparallel_mode 1                         \nnumber_of_elements 2                  \nelements  C H                          \nrandom_seed 10                         \nrandom_number_type 5                      \nremove_atom_energies                     \natom_energy H -0.458907306351869\natom_energy C -37.748111931202914\ninitial_hardness H 10.0 ## fixed_atomhardness--> initial_hardness \ninitial_hardness C 10.0 \nfixed_gausswidth H 0.585815056466\nfixed_gausswidth C 1.379499971678\nenergy_threshold 100.0d0              \nbond_threshold 0.4d0                 \newald_prec 1.0e-6 # for optimal combination of ewald parameters\nscreen_electrostatics 4.8 8.0\n########################################################################################################################\n### NN structure of the electrostatic-range NN  \n########################################################################################################################\nglobal_hidden_layers_electrostatic 2              \nglobal_nodes_electrostatic 15 15                 \nglobal_activation_electrostatic t t l            \nglobal_hidden_layers_short 2              \nglobal_nodes_short 10 10                 \nglobal_activation_short t t l            \n## element_hidden_layers_electrostatic needs to take care !!! should check the output  \n########################################################################################################################\n### symmetry function generation ( mode 1): \n########################################################################################################################\ntest_fraction 0.1      \n\n########################################################################################################################\n### symmetry function definitions (all modes): \n########################################################################################################################\ncutoff_type 2\n\n\n# radial H H\nsymfunction H  2  H 0.000000      0.000000      8.000000  \nsymfunction H  2  H 0.006000      0.000000      8.000000  \nsymfunction H  2  H 0.011000      0.000000      8.000000  \nsymfunction H  2  H 0.018000      0.000000      8.000000  \nsymfunction H  2  H 0.026000      0.000000      8.000000  \nsymfunction H  2  H 0.035000      0.000000      8.000000  \n\n#radial C H\nsymfunction C  2  H 0.000000      0.000000      8.000000  \nsymfunction C  2  H 0.013000      0.000000      8.000000  \nsymfunction C  2  H 0.029000      0.000000      8.000000  \nsymfunction C  2  H 0.054000      0.000000      8.000000  \nsymfunction C  2  H 0.093000      0.000000      8.000000  \nsymfunction C  2  H 0.161000      0.000000      8.000000  \n\nsymfunction H  2  C 0.000000      0.000000      8.000000  \nsymfunction H  2  C 0.013000      0.000000      8.000000  \nsymfunction H  2  C 0.029000      0.000000      8.000000  \nsymfunction H  2  C 0.054000      0.000000      8.000000  \nsymfunction H  2  C 0.093000      0.000000      8.000000  \nsymfunction H  2  C 0.161000      0.000000      8.000000  \n\n# radial C C \nsymfunction C  2  C 0.000000      0.000000      8.000000\nsymfunction C  2  C 0.010000      0.000000      8.000000\nsymfunction C  2  C 0.023000      0.000000      8.000000\nsymfunction C  2  C 0.041000      0.000000      8.000000\nsymfunction C  2  C 0.065000      0.000000      8.000000\nsymfunction C  2  C 0.103000      0.000000      8.000000\n\n\n#\n# angular\n\nsymfunction C 3 C C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction C 3 H H 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 H H 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction C 3 C H 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction C 3 C H 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\n\nsymfunction H 3 C C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 C C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 C C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 C C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\nsymfunction H 3 H C 0.0  1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  -1.0 1.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\nsymfunction H 3 H C 0.0  -1.0 2.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 H C 0.0  -1.0 4.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n#symfunction H 3 H C 0.0  -1.0 8.0  8.000000     ! central_atom type neighbor_atom1 neighbor_atom2 eta lambda zeta funccutoff\n\n\n########################################################################################################################\n### fitting (mode 2):general inputs for electrostatic range AND electrostatic part:\n########################################################################################################################\nepochs 10                          \npoints_in_memory 500                \nmix_all_points                       \nscale_symmetry_functions             \ncenter_symmetry_functions             \nfitting_unit  eV                      \n########################################################################################################################\n### fitting options ( mode 2): electrostatic range part only:\n########################################################################################################################\noptmode_short_energy 1                 \noptmode_short_force 1                   \nshort_energy_error_threshold 0.8\t \nshort_force_error_threshold 0.8\t\t \nkalman_lambda_charge 0.98000                \nkalman_nue_charge 0.99870                   \nkalman_lambda_short 0.98000                \nkalman_nue_short 0.99870                   \n#use_old_weights_electrostatic               \n#force_update_scaling -1.0d0          \n#electrostatic_energy_group 1         \n#electrostatic_energy_fraction 1.00           \n#electrostatic_force_group 1                 \n\nshort_force_fraction 0.025            \nuse_short_forces                    \nweights_min -1.0                 \nweights_max 1.0                  \nprecondition_weights            \nrepeated_energy_update          \nnguyen_widrow_weights_short     \nregularize_fit_param 0.00001 ## 4G cases L2 regularization \n########################################################################################################################\n### output options for mode 2 (fitting):  \n########################################################################################################################\nwrite_trainpoints              \nwrite_trainforces      \n#write_traincharges\n########################################################################################################################\n### output options for mode 3 (prediction):  \n########################################################################################################################\ncalculate_forces     \n#calculate_stress       \n\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/nnatoms.out",
    "content": "################################################################################\n# Energy contributions calculated from NNP.\n################################################################################\n# Col  Name      Description\n################################################################################\n# 1    conf      Configuration index (starting with 1).\n# 2    index     Atom index (starting with 1).\n# 3    Z         Nuclear charge of atom.\n# 4    Qref      Reference atomic charge.\n# 5    Qnnp      NNP atomic charge.\n# 6    Eref_atom Reference atomic energy contribution.\n# 7    Ennp_atom Atomic energy contribution (physical units, no mean or offset energy added).\n#############################################################################################################################\n#        1          2   3                        4                        5                        6                        7\n#     conf      index   Z                     Qref                     Qnnp                Eref_atom                Ennp_atom\n#############################################################################################################################\n         1          1   6  -8.0236691666699996E-03  -2.3524823684152795E-03   0.0000000000000000E+00  -2.7250515638214623E-01\n         1          2   6  -8.5542791666700004E-03  -8.4942086481964076E-03   0.0000000000000000E+00  -2.6177206845636780E-01\n         1          3   6  -9.8619091666699993E-03  -1.0537654209871102E-02   0.0000000000000000E+00  -2.7088006119054531E-01\n         1          4   6  -1.0058389166700000E-02  -7.1248303653208261E-03   0.0000000000000000E+00  -2.7432729767876585E-01\n         1          5   6  -6.7201291666699999E-03   8.2658839443283238E-04   0.0000000000000000E+00  -2.6480583491973142E-01\n         1          6   6  -4.1796691666700003E-03   8.1741828473709803E-04   0.0000000000000000E+00  -2.7001383025822279E-01\n         1          7   6  -2.8382559166699999E-02  -2.8351566345695845E-02   0.0000000000000000E+00  -2.0397182296237129E-01\n         1          8   6  -3.1433549166699999E-02  -3.2468734085716766E-02   0.0000000000000000E+00  -2.0480779326445372E-01\n         1          9   6  -5.3990979166700002E-02  -6.0669724234771107E-02   0.0000000000000000E+00  -1.7486001433553769E-01\n         1         10   6  -4.9556739166700003E-02  -5.6146955747858017E-02   0.0000000000000000E+00  -1.7132387729341647E-01\n         1         11   1   1.0498083083300000E-01   1.0155744000109204E-01   0.0000000000000000E+00  -4.2118982678316602E-01\n         1         12   1   1.0578104083300000E-01   1.0294470932558338E-01   0.0000000000000000E+00  -4.2137996820117252E-01\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/nnforces.out",
    "content": "################################################################################\n# Atomic force comparison (ordered by atom index).\n################################################################################\n# Col  Name  Description\n################################################################################\n# 1    conf  Configuration index (starting with 1).\n# 2    index Atom index (starting with 1).\n# 3    fxRef Reference force in x direction.\n# 4    fyRef Reference force in y direction.\n# 5    fzRef Reference force in z direction.\n# 6    fx    Force in x direction.\n# 7    fy    Force in y direction.\n# 8    fz    Force in z direction.\n###########################################################################################################################################################################\n#        1          2                        3                        4                        5                        6                        7                        8\n#     conf      index                    fxRef                    fyRef                    fzRef                       fx                       fy                       fz\n###########################################################################################################################################################################\n         1          1   3.4792582635100003E-02  -1.1037355618200000E-03   1.7220508737600001E-02   3.5244238802598936E-02  -9.2064728582576792E-04   1.6139279140426486E-02\n         1          2  -1.9091665014100000E-02   3.1912291105400002E-03   1.6684207468599999E-03  -2.0320505353455472E-02   1.6756423734835108E-03  -7.4457791136594144E-04\n         1          3  -2.1847043823600001E-02  -6.2854039981100002E-03  -1.7075637921100000E-02  -1.6527242561909055E-02  -5.7989817531996874E-03  -1.6407639020990412E-02\n         1          4  -3.0168753405800001E-02   1.0647867817900000E-02  -4.5251859967799998E-03  -3.2745976522587684E-02   1.2052512199310998E-02  -1.8522742363607386E-03\n         1          5   2.6692476263300000E-03  -1.5631406378100001E-03   1.1596107954400000E-02   2.9524805895551585E-03  -7.9386012929745281E-04   1.3705716946330639E-02\n         1          6   3.8029399306899997E-02  -1.2272279507000000E-02  -3.8501745632399998E-03   3.6094736091666753E-02  -1.3104246537253889E-02  -3.9527368127116212E-03\n         1          7   1.1435851018500000E-02   1.6888324748600001E-02  -1.4504200786199999E-02   1.2339197396340543E-02   1.7367830541731095E-02  -1.6091368599610911E-02\n         1          8  -3.1321231230200003E-02   8.9730460475299992E-03   1.9693569436700000E-02  -3.1026908616236346E-02   9.9635507686791063E-03   2.0389044528357523E-02\n         1          9  -2.0761670321400000E-02  -4.9135842553400004E-03   1.4173822701000000E-02  -2.4402146254685439E-02  -5.9144467478372100E-03   1.4821559975006723E-02\n         1         10   3.3079623398499999E-02  -7.2070527136200001E-03  -1.9296782653499999E-02   3.5796249466896496E-02  -8.1357128272733104E-03  -2.0640604603679190E-02\n         1         11  -4.4810467257099997E-03  -6.3800141834300002E-03  -7.4763656322500002E-03  -5.6665404254611345E-03  -6.5672357918272230E-03  -8.0097656828994248E-03\n         1         12   7.6647065354499997E-03   2.4743132529999999E-05   2.3759179766099999E-03   8.2624173872767118E-03   1.7559518930972563E-04   2.6433662774967082E-03\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/nnp-predict.log",
    "content": "\n*******************************************************************************\n\nWELCOME TO n²p², A SOFTWARE PACKAGE FOR NEURAL NETWORK POTENTIALS!\n------------------------------------------------------------------\n\nn²p² version      : v2.1.1-63-ga041104\n------------------------------------------------------------\nGit branch        : 4G-HDNNP-prediction\nGit revision      : a0411041f93eed45b833a27b591c2b1c0bfc73dd\nCompile date/time : Jul 28 2021 16:18:12\n------------------------------------------------------------\n\nPlease cite the following papers when publishing results obtained with n²p²:\n-------------------------------------------------------------------------------\n * General citation for n²p² and the LAMMPS interface:\n\n Singraber, A.; Behler, J.; Dellago, C.\n Library-Based LAMMPS Implementation of High-Dimensional\n Neural Network Potentials.\n J. Chem. Theory Comput. 2019 15 (3), 1827–1840.\n https://doi.org/10.1021/acs.jctc.8b00770\n-------------------------------------------------------------------------------\n * Additionally, if you use the NNP training features of n²p²:\n\n Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C.\n Parallel Multistream Training of High-Dimensional Neural\n Network Potentials.\n J. Chem. Theory Comput. 2019, 15 (5), 3075–3092.\n https://doi.org/10.1021/acs.jctc.8b01092\n-------------------------------------------------------------------------------\n * Additionally, if polynomial symmetry functions are used:\n\n Bircher, M. P.; Singraber, A.; Dellago, C.\n Improved Description of Atomic Environments Using Low-Cost\n Polynomial Functions with Compact Support.\n arXiv:2010.14414 [cond-mat, physics:physics] 2020.\n https://arxiv.org/abs/2010.14414\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 185 lines.\nWARNING: Unknown keyword \"bond_threshold\" at line 34.\nWARNING: Unknown keyword \"calculate_forces\" at line 183.\nWARNING: Unknown keyword \"energy_threshold\" at line 33.\nWARNING: Unknown keyword \"fitting_unit\" at line 148.\nWARNING: Unknown keyword \"kalman_lambda_charge\" at line 156.\nWARNING: Unknown keyword \"kalman_nue_charge\" at line 157.\nWARNING: Unknown keyword \"mix_all_points\" at line 145.\nWARNING: Unknown keyword \"optmode_short_energy\" at line 152.\nWARNING: Unknown keyword \"optmode_short_force\" at line 153.\nWARNING: Unknown keyword \"points_in_memory\" at line 144.\nWARNING: Unknown keyword \"random_number_type\" at line 25.\nWARNING: Unknown keyword \"regularize_fit_param\" at line 173.\nWARNING: Unknown keyword \"remove_atom_energies\" at line 26.\nWARNING: Unknown keyword \"runner_mode\" at line 20.\nWARNING: Unknown keyword \"use_electrostatics\" at line 17.\nWARNING: Unknown keyword \"use_short_nn\" at line 18.\nWARNING: 16 problems detected (0 critical).\nFound 113 lines with keywords.\nThis settings file defines a NNP with electrostatics and\nnon-local charge transfer (4G-HDNNP).\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is not used.\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  H (  1)\nElement  1:  C (  6)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:  -4.58907306E-01\nElement  1:  -3.77481119E+01\nEnergy offsets are automatically subtracted from reference energies.\n*******************************************************************************\n\n*** SETUP: ELECTROSTATICS *****************************************************\n\nAtomic hardness file name format: hardness.%03zu.data\nAtomic hardness for element  H from file hardness.001.data:   8.89533120E-03\nAtomic hardness for element  C from file hardness.006.data:   6.61189426E-02\n\nGaussian width of charge distribution per element:\nElement  0:   5.85815056E-01\nElement  1:   1.37949997E+00\n\nEwald precision:   1.00000000E-06\n\nScreening function information:\nInner radius :   4.80000000E+00\nOuter radius :   8.00000000E+00\nTransition region functional form:\nx     := (r - inner) / (outer - inner)\nfs(x) := 1 - f(x)\nCoreFunction::Type::COS (0):\nf(x) := 1/2 * (cos(pi*x) + 1)\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_TANHU (2)\nf(r) = tanh^3(1 - r/rc)\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\ntp ..... Symmetry function type.\nsbtp ... Symmetry function subtype (e.g. cutoff type).\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs/rl... Shift distance of Gaussian or left cutoff radius for polynomial.\nangl.... Left cutoff angle for polynomial.\nangr.... Right cutoff angle for polynomial.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius / right cutoff radius for polynomial.\na ...... Free parameter alpha (e.g. cutoff alpha).\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  H :\n-------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln\n-------------------------------------------------------------------------------------------------\n   1  H  2  ct2  H    0.000E+00  0.000E+00  8.000E+00                       0.00    59\n   2  H  2  ct2  C    0.000E+00  0.000E+00  8.000E+00                       0.00    74\n   3  H  2  ct2  H    6.000E-03  0.000E+00  8.000E+00                       0.00    60\n   4  H  2  ct2  H    1.100E-02  0.000E+00  8.000E+00                       0.00    61\n   5  H  2  ct2  C    1.300E-02  0.000E+00  8.000E+00                       0.00    75\n   6  H  2  ct2  H    1.800E-02  0.000E+00  8.000E+00                       0.00    62\n   7  H  2  ct2  H    2.600E-02  0.000E+00  8.000E+00                       0.00    63\n   8  H  2  ct2  C    2.900E-02  0.000E+00  8.000E+00                       0.00    76\n   9  H  2  ct2  H    3.500E-02  0.000E+00  8.000E+00                       0.00    64\n  10  H  2  ct2  C    5.400E-02  0.000E+00  8.000E+00                       0.00    77\n  11  H  2  ct2  C    9.300E-02  0.000E+00  8.000E+00                       0.00    78\n  12  H  2  ct2  C    1.610E-01  0.000E+00  8.000E+00                       0.00    79\n  13  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   134\n  14  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   125\n  15  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   130\n  16  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   121\n  17  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   135\n  18  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   126\n  19  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   131\n  20  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   122\n  21  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   132\n  22  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   123\n  23  H  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   133\n  24  H  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   124\n-------------------------------------------------------------------------------------------------\nShort range atomic symmetry functions element  C :\n-------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln\n-------------------------------------------------------------------------------------------------\n   1  C  2  ct2  H    0.000E+00  0.000E+00  8.000E+00                       0.00    67\n   2  C  2  ct2  C    0.000E+00  0.000E+00  8.000E+00                       0.00    82\n   3  C  2  ct2  C    1.000E-02  0.000E+00  8.000E+00                       0.00    83\n   4  C  2  ct2  H    1.300E-02  0.000E+00  8.000E+00                       0.00    68\n   5  C  2  ct2  C    2.300E-02  0.000E+00  8.000E+00                       0.00    84\n   6  C  2  ct2  H    2.900E-02  0.000E+00  8.000E+00                       0.00    69\n   7  C  2  ct2  C    4.100E-02  0.000E+00  8.000E+00                       0.00    85\n   8  C  2  ct2  H    5.400E-02  0.000E+00  8.000E+00                       0.00    70\n   9  C  2  ct2  C    6.500E-02  0.000E+00  8.000E+00                       0.00    86\n  10  C  2  ct2  H    9.300E-02  0.000E+00  8.000E+00                       0.00    71\n  11  C  2  ct2  C    1.030E-01  0.000E+00  8.000E+00                       0.00    87\n  12  C  2  ct2  H    1.610E-01  0.000E+00  8.000E+00                       0.00    72\n  13  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   106\n  14  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00   115\n  15  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  1.0 0.00    97\n  16  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   102\n  17  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00   111\n  18  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  1.0 0.00    93\n  19  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   107\n  20  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00   116\n  21  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  2.0 0.00    98\n  22  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   103\n  23  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00   112\n  24  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  2.0 0.00    94\n  25  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  4.0 0.00   108\n  26  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  4.0 0.00   117\n  27  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  4.0 0.00    99\n  28  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   104\n  29  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00   113\n  30  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  4.0 0.00    95\n  31  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00               -1  8.0 0.00   109\n  32  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00               -1  8.0 0.00   118\n  33  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00               -1  8.0 0.00   100\n  34  C  3  ct2  H  H 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   105\n  35  C  3  ct2  H  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00   114\n  36  C  3  ct2  C  C 0.000E+00  0.000E+00  8.000E+00                1  8.0 0.00    96\n-------------------------------------------------------------------------------------------------\nMinimum cutoff radius for element  H: 8.000000\nMinimum cutoff radius for element  C: 8.000000\nMaximum cutoff radius (global)      : 8.000000\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION MEMORY *******************************************\n\nSymmetry function derivatives memory table for element  H :\n-------------------------------------------------------------------------------\nRelevant symmetry functions for neighbors with element:\n-  H:   12 of   24 ( 50.0 )\n-  C:   18 of   24 ( 75.0 )\n-------------------------------------------------------------------------------\nSymmetry function derivatives memory table for element  C :\n-------------------------------------------------------------------------------\nRelevant symmetry functions for neighbors with element:\n-  H:   22 of   36 ( 61.1 )\n-  C:   22 of   36 ( 61.1 )\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION CACHE ********************************************\n\nElement  H: in total 4 caches, used 15.00 times on average.\nElement  C: in total 4 caches, used 22.00 times on average.\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\ntp ..... Symmetry function type.\nsbtp ... Symmetry function subtype (e.g. cutoff type).\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs/rl... Shift distance of Gaussian or left cutoff radius for polynomial.\nangl.... Left cutoff angle for polynomial.\nangr.... Right cutoff angle for polynomial.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius / right cutoff radius for polynomial.\na ...... Free parameter alpha (e.g. cutoff alpha).\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  H :\n----------------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln   mi  sfi e\n----------------------------------------------------------------------------------------------------------\n   1  H  2  ct2  H            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    59    1    1  \n   -  -  -    -  -    6.000E-03  0.000E+00          -                          -    60    2    3  \n   -  -  -    -  -    1.100E-02  0.000E+00          -                          -    61    3    4  \n   -  -  -    -  -    1.800E-02  0.000E+00          -                          -    62    4    6  \n   -  -  -    -  -    2.600E-02  0.000E+00          -                          -    63    5    7  \n   -  -  -    -  -    3.500E-02  0.000E+00          -                          -    64    6    9  \n   2  H  2  ct2  C            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    74    1    2  \n   -  -  -    -  -    1.300E-02  0.000E+00          -                          -    75    2    5  \n   -  -  -    -  -    2.900E-02  0.000E+00          -                          -    76    3    8  \n   -  -  -    -  -    5.400E-02  0.000E+00          -                          -    77    4   10  \n   -  -  -    -  -    9.300E-02  0.000E+00          -                          -    78    5   11  \n   -  -  -    -  -    1.610E-01  0.000E+00          -                          -    79    6   12  \n   3  H  3  ct2  H  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   134    1   13 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   130    2   15 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   135    3   17 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   131    4   19 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   132    5   21 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   133    6   23 0\n   4  H  3  ct2  C  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   125    1   14 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   121    2   16 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   126    3   18 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   122    4   20 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   123    5   22 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   124    6   24 0\n----------------------------------------------------------------------------------------------------------\nShort range atomic symmetry function groups element  C :\n----------------------------------------------------------------------------------------------------------\n ind ec tp sbtp e1 e2       eta      rs/rl         rc   angl   angr la zeta    a    ln   mi  sfi e\n----------------------------------------------------------------------------------------------------------\n   1  C  2  ct2  H            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    67    1    1  \n   -  -  -    -  -    1.300E-02  0.000E+00          -                          -    68    2    4  \n   -  -  -    -  -    2.900E-02  0.000E+00          -                          -    69    3    6  \n   -  -  -    -  -    5.400E-02  0.000E+00          -                          -    70    4    8  \n   -  -  -    -  -    9.300E-02  0.000E+00          -                          -    71    5   10  \n   -  -  -    -  -    1.610E-01  0.000E+00          -                          -    72    6   12  \n   2  C  2  ct2  C            *          *  8.000E+00                       0.00     *    *    *  \n   -  -  -    -  -    0.000E+00  0.000E+00          -                          -    82    1    2  \n   -  -  -    -  -    1.000E-02  0.000E+00          -                          -    83    2    3  \n   -  -  -    -  -    2.300E-02  0.000E+00          -                          -    84    3    5  \n   -  -  -    -  -    4.100E-02  0.000E+00          -                          -    85    4    7  \n   -  -  -    -  -    6.500E-02  0.000E+00          -                          -    86    5    9  \n   -  -  -    -  -    1.030E-01  0.000E+00          -                          -    87    6   11  \n   3  C  3  ct2  H  H         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   106    1   13 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   102    2   16 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   107    3   19 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   103    4   22 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  4.0    -   108    5   25 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   104    6   28 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  8.0    -   109    7   31 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   105    8   34 0\n   4  C  3  ct2  H  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -   115    1   14 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -   111    2   17 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -   116    3   20 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -   112    4   23 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  4.0    -   117    5   26 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -   113    6   29 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  8.0    -   118    7   32 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -   114    8   35 0\n   5  C  3  ct2  C  C         *          *  8.000E+00                *    * 0.00     *    *    * *\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  1.0    -    97    1   15 1\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  1.0    -    93    2   18 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  2.0    -    98    3   21 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  2.0    -    94    4   24 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  4.0    -    99    5   27 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  4.0    -    95    6   30 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -               -1  8.0    -   100    7   33 0\n   -  -  -    -  -  - 0.000E+00  0.000E+00          -                1  8.0    -    96    8   36 0\n----------------------------------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic electronegativity NN for element  H :\nNumber of weights    :    600\nNumber of biases     :     31\nNumber of connections:    631\nArchitecture       24   15   15    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n-------------------------------------------------------------------------------\nAtomic electronegativity NN for element  C :\nNumber of weights    :    780\nNumber of biases     :     31\nNumber of connections:    811\nArchitecture       36   15   15    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n  25   G            \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  H :\nNumber of weights    :    360\nNumber of biases     :     21\nNumber of connections:    381\nArchitecture       25   10   10    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G            \n  12   G            \n  13   G            \n  14   G            \n  15   G            \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n  25   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  C :\nNumber of weights    :    480\nNumber of biases     :     21\nNumber of connections:    501\nArchitecture       37   10   10    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G            \n  12   G            \n  13   G            \n  14   G            \n  15   G            \n  16   G            \n  17   G            \n  18   G            \n  19   G            \n  20   G            \n  21   G            \n  22   G            \n  23   G            \n  24   G            \n  25   G            \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n  37   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALECENTER (3)\nGs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\nWARNING: Keyword \"scale_min_short\" not found.\n         Default value for Smin = 0.0.\nWARNING: Keyword \"scale_max_short\" not found.\n         Default value for Smax = 1.0.\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  0.00E+00  1.68E-01  5.14E-02  0.00E+00  5.94E+00  0.00  1.00 3\n   2  3.04E-01  4.17E-01  3.46E-01  0.00E+00  8.85E+00  0.00  1.00 3\n   3  0.00E+00  1.59E-01  4.77E-02  0.00E+00  6.27E+00  0.00  1.00 3\n   4  0.00E+00  1.52E-01  4.48E-02  0.00E+00  6.56E+00  0.00  1.00 3\n   5  2.70E-01  3.77E-01  3.12E-01  0.00E+00  9.35E+00  0.00  1.00 3\n   6  0.00E+00  1.43E-01  4.10E-02  0.00E+00  7.00E+00  0.00  1.00 3\n   7  0.00E+00  1.33E-01  3.71E-02  0.00E+00  7.53E+00  0.00  1.00 3\n   8  2.36E-01  3.37E-01  2.78E-01  0.00E+00  9.97E+00  0.00  1.00 3\n   9  0.00E+00  1.22E-01  3.31E-02  0.00E+00  8.18E+00  0.00  1.00 3\n  10  1.94E-01  2.86E-01  2.36E-01  0.00E+00  1.09E+01  0.00  1.00 3\n  11  1.46E-01  2.31E-01  1.88E-01  0.00E+00  1.18E+01  0.00  1.00 3\n  12  9.43E-02  1.67E-01  1.33E-01  0.00E+00  1.37E+01  0.00  1.00 3\n  13  0.00E+00  3.94E-03  7.66E-04  0.00E+00  2.54E+02  0.00  1.00 3\n  14  0.00E+00  2.18E-03  3.95E-04  0.00E+00  4.59E+02  0.00  1.00 3\n  15  0.00E+00  2.26E-02  6.69E-03  0.00E+00  4.42E+01  0.00  1.00 3\n  16  6.80E-03  1.48E-02  9.85E-03  0.00E+00  1.25E+02  0.00  1.00 3\n  17  0.00E+00  7.54E-04  1.18E-04  0.00E+00  1.33E+03  0.00  1.00 3\n  18  0.00E+00  3.07E-04  3.12E-05  0.00E+00  3.26E+03  0.00  1.00 3\n  19  0.00E+00  2.02E-02  6.04E-03  0.00E+00  4.96E+01  0.00  1.00 3\n  20  6.45E-03  1.30E-02  9.49E-03  0.00E+00  1.53E+02  0.00  1.00 3\n  21  0.00E+00  1.67E-02  5.00E-03  0.00E+00  5.97E+01  0.00  1.00 3\n  22  5.80E-03  1.11E-02  8.84E-03  0.00E+00  1.88E+02  0.00  1.00 3\n  23  0.00E+00  1.27E-02  3.57E-03  0.00E+00  7.90E+01  0.00  1.00 3\n  24  4.42E-03  1.10E-02  7.82E-03  0.00E+00  1.51E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element  C :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  0.00E+00  5.28E-01  8.65E-02  0.00E+00  1.89E+00  0.00  1.00 3\n   2  2.44E-01  5.76E-01  4.78E-01  0.00E+00  3.00E+00  0.00  1.00 3\n   3  2.20E-01  5.27E-01  4.38E-01  0.00E+00  3.26E+00  0.00  1.00 3\n   4  0.00E+00  5.04E-01  7.81E-02  0.00E+00  1.99E+00  0.00  1.00 3\n   5  1.95E-01  4.73E-01  3.93E-01  0.00E+00  3.59E+00  0.00  1.00 3\n   6  0.00E+00  4.75E-01  6.95E-02  0.00E+00  2.11E+00  0.00  1.00 3\n   7  1.66E-01  4.12E-01  3.41E-01  0.00E+00  4.07E+00  0.00  1.00 3\n   8  0.00E+00  4.33E-01  5.90E-02  0.00E+00  2.31E+00  0.00  1.00 3\n   9  1.36E-01  3.48E-01  2.86E-01  0.00E+00  4.72E+00  0.00  1.00 3\n  10  0.00E+00  3.76E-01  4.70E-02  0.00E+00  2.66E+00  0.00  1.00 3\n  11  1.02E-01  2.73E-01  2.22E-01  0.00E+00  5.83E+00  0.00  1.00 3\n  12  0.00E+00  2.93E-01  3.33E-02  0.00E+00  3.41E+00  0.00  1.00 3\n  13  0.00E+00  1.53E-02  6.08E-04  0.00E+00  6.55E+01  0.00  1.00 3\n  14  0.00E+00  2.04E-02  2.32E-03  0.00E+00  4.91E+01  0.00  1.00 3\n  15  0.00E+00  6.66E-03  3.99E-03  0.00E+00  1.50E+02  0.00  1.00 3\n  16  0.00E+00  9.28E-03  3.24E-04  0.00E+00  1.08E+02  0.00  1.00 3\n  17  0.00E+00  2.50E-02  2.80E-03  0.00E+00  4.00E+01  0.00  1.00 3\n  18  3.52E-03  1.25E-02  8.03E-03  0.00E+00  1.11E+02  0.00  1.00 3\n  19  0.00E+00  1.19E-02  4.30E-04  0.00E+00  8.39E+01  0.00  1.00 3\n  20  0.00E+00  1.56E-02  2.02E-03  0.00E+00  6.43E+01  0.00  1.00 3\n  21  0.00E+00  6.52E-03  3.94E-03  0.00E+00  1.53E+02  0.00  1.00 3\n  22  0.00E+00  3.82E-03  1.46E-04  0.00E+00  2.62E+02  0.00  1.00 3\n  23  0.00E+00  2.34E-02  2.50E-03  0.00E+00  4.27E+01  0.00  1.00 3\n  24  3.51E-03  1.24E-02  7.98E-03  0.00E+00  1.12E+02  0.00  1.00 3\n  25  0.00E+00  8.68E-03  2.29E-04  0.00E+00  1.15E+02  0.00  1.00 3\n  26  0.00E+00  1.07E-02  1.70E-03  0.00E+00  9.33E+01  0.00  1.00 3\n  27  0.00E+00  6.38E-03  3.88E-03  0.00E+00  1.57E+02  0.00  1.00 3\n  28  0.00E+00  1.76E-03  6.00E-05  0.00E+00  5.69E+02  0.00  1.00 3\n  29  0.00E+00  2.11E-02  2.32E-03  0.00E+00  4.74E+01  0.00  1.00 3\n  30  3.50E-03  1.23E-02  7.95E-03  0.00E+00  1.13E+02  0.00  1.00 3\n  31  0.00E+00  4.70E-03  6.92E-05  0.00E+00  2.13E+02  0.00  1.00 3\n  32  0.00E+00  1.07E-02  1.36E-03  0.00E+00  9.34E+01  0.00  1.00 3\n  33  0.00E+00  6.34E-03  3.76E-03  0.00E+00  1.58E+02  0.00  1.00 3\n  34  0.00E+00  9.43E-04  2.30E-05  0.00E+00  1.06E+03  0.00  1.00 3\n  35  0.00E+00  1.71E-02  2.11E-03  0.00E+00  5.84E+01  0.00  1.00 3\n  36  3.48E-03  1.22E-02  7.88E-03  0.00E+00  1.15E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORK WEIGHTS *********************************************\n\nElectronegativity weight file name format: weightse.%03zu.data\nSetting weights for element  H from file: weightse.001.data\nSetting weights for element  C from file: weightse.006.data\nShort range weight file name format: weights.%03zu.data\nSetting weights for element  H from file: weights.001.data\nSetting weights for element  C from file: weights.006.data\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 1\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** PREDICTION ****************************************************************\n\nReading structure file...\nStructure contains 12 atoms (2 elements).\nCalculating NNP prediction...\nAtom     0 ( C) chi:  -1.50037876E-01\nAtom     1 ( C) chi:  -1.49461645E-01\nAtom     2 ( C) chi:  -1.49033407E-01\nAtom     3 ( C) chi:  -1.49337351E-01\nAtom     4 ( C) chi:  -1.48516909E-01\nAtom     5 ( C) chi:  -1.48569008E-01\nAtom     6 ( C) chi:  -1.46830562E-01\nAtom     7 ( C) chi:  -1.46678106E-01\nAtom     8 ( C) chi:  -1.60724572E-01\nAtom     9 ( C) chi:  -1.62293124E-01\nAtom    10 ( H) chi:  -2.25977980E-01\nAtom    11 ( H) chi:  -2.28364821E-01\nSolve relative error:   2.46817332E-16\nAtom     0 ( C) q:  -2.35248237E-03\nAtom     1 ( C) q:  -8.49420865E-03\nAtom     2 ( C) q:  -1.05376542E-02\nAtom     3 ( C) q:  -7.12483037E-03\nAtom     4 ( C) q:   8.26588394E-04\nAtom     5 ( C) q:   8.17418285E-04\nAtom     6 ( C) q:  -2.83515663E-02\nAtom     7 ( C) q:  -3.24687341E-02\nAtom     8 ( C) q:  -6.06697242E-02\nAtom     9 ( C) q:  -5.61469557E-02\nAtom    10 ( H) q:   1.01557440E-01\nAtom    11 ( H) q:   1.02944709E-01\nTotal charge:  -1.38777878E-17 (ref:  -0.00000000E+00)\nElectrostatic energy:  -1.56542350E-05\nAtom     0 ( C) energy:  -2.72505156E-01\nAtom     1 ( C) energy:  -2.61772068E-01\nAtom     2 ( C) energy:  -2.70880061E-01\nAtom     3 ( C) energy:  -2.74327298E-01\nAtom     4 ( C) energy:  -2.64805835E-01\nAtom     5 ( C) energy:  -2.70013830E-01\nAtom     6 ( C) energy:  -2.03971823E-01\nAtom     7 ( C) energy:  -2.04807793E-01\nAtom     8 ( C) energy:  -1.74860014E-01\nAtom     9 ( C) energy:  -1.71323877E-01\nAtom    10 ( H) energy:  -4.21189827E-01\nAtom    11 ( H) energy:  -4.21379968E-01\n\n-------------------------------------------------------------------------------\nNNP energy:  -3.81610787E+02\n\nNNP forces:\n         1  C   3.52442388E-02  -9.20647286E-04   1.61392791E-02\n         2  C  -2.03205054E-02   1.67564237E-03  -7.44577911E-04\n         3  C  -1.65272426E-02  -5.79898175E-03  -1.64076390E-02\n         4  C  -3.27459765E-02   1.20525122E-02  -1.85227424E-03\n         5  C   2.95248059E-03  -7.93860129E-04   1.37057169E-02\n         6  C   3.60947361E-02  -1.31042465E-02  -3.95273681E-03\n         7  C   1.23391974E-02   1.73678305E-02  -1.60913686E-02\n         8  C  -3.10269086E-02   9.96355077E-03   2.03890445E-02\n         9  C  -2.44021463E-02  -5.91444675E-03   1.48215600E-02\n        10  C   3.57962495E-02  -8.13571283E-03  -2.06406046E-02\n        11  H  -5.66654043E-03  -6.56723579E-03  -8.00976568E-03\n        12  H   8.26241739E-03   1.75595189E-04   2.64336628E-03\n-------------------------------------------------------------------------------\nWriting output files...\n - energy.out\n - nnatoms.out\n - nnforces.out\nWriting structure with NNP prediction to \"output.data\".\nFinished.\n*******************************************************************************\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/output.data",
    "content": "begin\ncomment \natom   1.1728409548600001E+00  -1.7250422268400001E-01  -6.6744851686499995E-01  C  -2.3524823684152795E-03   0.0000000000000000E+00   3.5244238802598936E-02  -9.2064728582576792E-04   1.6139279140426486E-02\natom  -1.1595434821999999E+00  -3.5064100044500002E-01  -4.6759810719400002E-01  C  -8.4942086481964076E-03   0.0000000000000000E+00  -2.0320505353455472E-02   1.6756423734835108E-03  -7.4457791136594144E-04\natom   3.7259405496900002E+00  -8.3797517909699998E-02  -2.2977716867299999E-01  C  -1.0537654209871102E-02   0.0000000000000000E+00  -1.6527242561909055E-02  -5.7989817531996874E-03  -1.6407639020990412E-02\natom  -3.6914698311600000E+00  -3.3417264316700002E-01  -2.1088223314999999E-01  C  -7.1248303653208261E-03   0.0000000000000000E+00  -3.2745976522587684E-02   1.2052512199310998E-02  -1.8522742363607386E-03\natom   6.0775858677099999E+00  -1.6674522604200001E-01  -1.4502403522800000E-01  C   8.2658839443283238E-04   0.0000000000000000E+00   2.9524805895551585E-03  -7.9386012929745281E-04   1.3705716946330639E-02\natom  -6.0680978936700001E+00  -2.5373350848899999E-03  -7.0535761072400005E-02  C   8.1741828473709803E-04   0.0000000000000000E+00   3.6094736091666753E-02  -1.3104246537253889E-02  -3.9527368127116212E-03\natom   8.5916435346399993E+00  -8.0691507583099994E-02   4.0223683161899998E-01  C  -2.8351566345695845E-02   0.0000000000000000E+00   1.2339197396340543E-02   1.7367830541731095E-02  -1.6091368599610911E-02\natom  -8.6089256457300003E+00   1.1719224535400000E-01   9.8285177790399997E-02  C  -3.2468734085716766E-02   0.0000000000000000E+00  -3.1026908616236346E-02   9.9635507686791063E-03   2.0389044528357523E-02\natom   1.0870540581500000E+01   5.1581338865000004E-01   4.3582652209299999E-01  C  -6.0669724234771107E-02   0.0000000000000000E+00  -2.4402146254685439E-02  -5.9144467478372100E-03   1.4821559975006723E-02\natom  -1.0887958110400000E+01   4.1180782131900001E-01   6.9494856534200000E-01  C  -5.6146955747858017E-02   0.0000000000000000E+00   3.5796249466896496E-02  -8.1357128272733104E-03  -2.0640604603679190E-02\natom   1.2661965991000001E+01   1.1950244671400001E+00   1.1691448208999999E+00  H   1.0155744000109204E-01   0.0000000000000000E+00  -5.6665404254611345E-03  -6.5672357918272230E-03  -8.0097656828994248E-03\natom  -1.2930732213100001E+01   5.2505855179600003E-01   7.2801145690299995E-01  H   1.0294470932558338E-01   0.0000000000000000E+00   8.2624173872767118E-03   1.7559518930972563E-04   2.6433662774967082E-03\nenergy  -3.8161078713069378E+02\ncharge  -1.3877787807814457E-17\nend\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/scaling.data",
    "content": "   1    1        0.000000000       0.168474325       0.051436597\n   1    2        0.304058579       0.417104776       0.345915594\n   1    3        0.000000000       0.159465228       0.047693255\n   1    4        0.000000000       0.152326768       0.044784312\n   1    5        0.270367239       0.377289298       0.312242885\n   1    6        0.000000000       0.142866546       0.041009575\n   1    7        0.000000000       0.132772126       0.037086368\n   1    8        0.236241291       0.336573119       0.278003131\n   1    9        0.000000000       0.122265892       0.033122717\n   1   10        0.194043783       0.286076543       0.235857711\n   1   11        0.146413959       0.230979612       0.188000406\n   1   12        0.094328785       0.167444236       0.133300930\n   1   13        0.000000000       0.003940598       0.000766277\n   1   14        0.000000000       0.002179848       0.000395242\n   1   15        0.000000000       0.022615147       0.006688070\n   1   16        0.006799063       0.014786064       0.009854503\n   1   17        0.000000000       0.000754211       0.000118471\n   1   18        0.000000000       0.000307111       0.000031177\n   1   19        0.000000000       0.020171446       0.006040265\n   1   20        0.006447566       0.012997039       0.009490438\n   1   21        0.000000000       0.016749223       0.005002441\n   1   22        0.005799086       0.011113091       0.008844953\n   1   23        0.000000000       0.012662314       0.003565243\n   1   24        0.004417978       0.011019545       0.007821957\n   2    1        0.000000000       0.528085920       0.086499956\n   2    2        0.243551003       0.576397651       0.478191952\n   2    3        0.220486953       0.527469369       0.437635603\n   2    4        0.000000000       0.503534550       0.078079729\n   2    5        0.195097154       0.473305655       0.392510705\n   2    6        0.000000000       0.474879557       0.069517706\n   2    7        0.166254512       0.411783730       0.340934855\n   2    8        0.000000000       0.433337270       0.058978785\n   2    9        0.136220939       0.347964660       0.286400724\n   2   10        0.000000000       0.375671652       0.047011546\n   2   11        0.101581283       0.273092311       0.221977741\n   2   12        0.000000000       0.292877983       0.033333347\n   2   13        0.000000000       0.015267809       0.000607918\n   2   14        0.000000000       0.020367325       0.002323101\n   2   15        0.000000000       0.006658033       0.003990472\n   2   16        0.000000000       0.009284484       0.000324103\n   2   17        0.000000000       0.024985840       0.002803020\n   2   18        0.003522361       0.012523471       0.008029970\n   2   19        0.000000000       0.011921850       0.000429967\n   2   20        0.000000000       0.015558424       0.002023934\n   2   21        0.000000000       0.006518589       0.003941639\n   2   22        0.000000000       0.003823383       0.000146152\n   2   23        0.000000000       0.023446294       0.002503853\n   2   24        0.003512986       0.012433317       0.007981137\n   2   25        0.000000000       0.008678726       0.000229107\n   2   26        0.000000000       0.010714201       0.001695750\n   2   27        0.000000000       0.006384431       0.003878387\n   2   28        0.000000000       0.001758371       0.000060041\n   2   29        0.000000000       0.021095757       0.002319082\n   2   30        0.003504699       0.012339772       0.007947861\n   2   31        0.000000000       0.004699984       0.000069193\n   2   32        0.000000000       0.010701233       0.001357400\n   2   33        0.000000000       0.006338867       0.003757820\n   2   34        0.000000000       0.000942648       0.000023014\n   2   35        0.000000000       0.017137757       0.002111679\n   2   36        0.003476868       0.012155470       0.007883155\n       -0.2691374625       -0.2381480047\n"
  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/weights.001.data",
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  {
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  },
  {
    "path": "examples/interface-LAMMPS/TO_BE_CHECKED/carbon-chain2/nnp-predict/weightse.006.data",
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  },
  {
    "path": "examples/nnp-atomenv/Cu2S_PBE/input.data",
    "content": "begin\ncomment source_file_name=OUTCAR_6_1\nlattice 15.594764320 0.000000000 0.000000000\nlattice 0.000000000 12.155855908 0.000000000\nlattice -6.126368446 0.000000000 12.368579086\natom 9.63890 0.96312 10.51091 S 0.0 0.0 0.350210 -0.554056 0.113180\natom -3.00763 6.95453 7.97469 S 0.0 0.0 -0.752995 0.652737 -0.990832\natom -0.27520 11.31741 1.87879 S 0.0 0.0 0.141941 -0.154466 -0.838454\natom 12.83483 4.97391 4.57177 S 0.0 0.0 -0.160867 -0.271579 0.083792\natom -2.11030 0.79776 4.27963 S 0.0 0.0 -0.838203 0.531100 0.027313\natom -0.24651 7.77005 2.23788 S 0.0 0.0 0.272415 -0.988896 -0.541814\natom -3.21096 11.38980 7.66647 S 0.0 0.0 0.215740 -0.090022 0.738258\natom 9.82484 4.70192 10.30542 S 0.0 0.0 0.089792 0.445747 0.462798\natom 9.62785 1.12949 6.66571 S 0.0 0.0 -0.426435 -0.486012 -0.263742\natom -3.37275 6.87430 11.94513 S 0.0 0.0 0.621769 -0.117179 0.712745\natom 0.46861 10.82795 6.00841 S 0.0 0.0 0.371337 -0.883786 1.682212\natom 12.43163 5.26750 0.42978 S 0.0 0.0 -0.357114 -0.926522 -1.411186\natom 12.21606 1.00390 0.12092 S 0.0 0.0 -0.357790 -0.594407 0.510448\natom 0.13736 6.66514 6.39415 S 0.0 0.0 0.695648 -0.333962 0.299355\natom -2.84095 10.84000 12.22732 S 0.0 0.0 -0.672717 -1.409009 0.517012\natom 9.38344 4.90882 6.34489 S 0.0 0.0 0.055830 0.454730 -0.205986\natom 3.07808 1.39839 7.66418 S 0.0 0.0 0.244107 -0.111242 0.370838\natom 3.16249 7.32809 10.98372 S 0.0 0.0 -0.714034 -0.950478 -0.111294\natom 6.31273 11.12718 5.14045 S 0.0 0.0 -0.274480 0.662357 -0.306943\natom 5.85868 4.64735 1.18800 S 0.0 0.0 0.782752 -0.045454 -0.180128\natom 6.58355 0.54045 1.55272 S 0.0 0.0 0.087304 0.415076 -0.680424\natom 6.25457 7.25608 5.22585 S 0.0 0.0 -0.147039 -0.567389 -0.019753\natom 2.91569 11.23516 10.86736 S 0.0 0.0 0.209372 0.036625 0.859137\natom 3.52214 5.52811 7.31099 S 0.0 0.0 0.111239 -0.729708 0.189434\natom -0.26421 0.60508 9.68063 S 0.0 0.0 0.154653 0.337527 -0.335222\natom 7.00375 6.81245 9.22905 S 0.0 0.0 -0.800917 0.279124 0.382910\natom 9.50698 10.85115 2.98481 S 0.0 0.0 0.207452 0.400685 -0.237485\natom 2.86852 5.14912 3.42989 S 0.0 0.0 0.958484 -0.292527 0.253351\natom 3.33036 1.37921 3.07273 S 0.0 0.0 -0.147258 -0.437699 1.521814\natom 9.75984 6.77951 2.40684 S 0.0 0.0 -0.051671 0.134460 0.703435\natom 6.63744 11.19827 8.93785 S 0.0 0.0 -0.218518 0.452267 -0.394139\natom -0.29301 4.68877 10.03355 S 0.0 0.0 0.167882 -0.157980 -0.194136\natom 6.38348 3.00550 8.80720 S 0.0 0.0 0.396542 -0.367888 -0.069142\natom -0.00145 8.77276 9.69386 S 0.0 0.0 -0.630931 -0.354581 -0.138339\natom 3.32647 9.05424 3.41360 S 0.0 0.0 0.470596 0.259571 -0.307733\natom 9.72993 3.10925 2.99770 S 0.0 0.0 0.117259 0.016193 1.507463\natom 6.18881 3.07866 5.12600 S 0.0 0.0 -0.620834 -0.750541 0.247720\natom 6.62155 9.17688 1.21793 S 0.0 0.0 -0.043947 -0.216793 -0.620279\natom 3.68682 9.21703 7.64680 S 0.0 0.0 -0.582258 -0.171337 0.057281\natom 3.43916 3.43558 11.20238 S 0.0 0.0 -0.561531 -0.805216 -0.194839\natom 0.45249 2.73204 6.06382 S 0.0 0.0 -0.734543 0.324681 0.400481\natom 12.28070 8.69179 0.18017 S 0.0 0.0 0.589753 0.702281 -0.672977\natom 9.39626 9.04258 6.36578 S 0.0 0.0 0.464964 -0.343255 -0.057120\natom -2.46286 2.56042 11.73074 S 0.0 0.0 -0.290660 0.433399 0.493213\natom 0.07826 3.23719 1.35581 S 0.0 0.0 -0.287273 -0.426902 0.436177\natom 12.65943 8.86407 4.39292 S 0.0 0.0 0.157043 -0.219561 -0.684782\natom 9.62989 9.46664 10.61323 S 0.0 0.0 -0.042922 -0.606046 0.070045\natom -3.10610 3.01981 7.78888 S 0.0 0.0 0.177979 0.070013 0.430926\natom 11.88291 2.48588 3.55560 Cu 0.0 0.0 -0.515835 -0.969894 0.271462\natom 1.82932 6.72661 2.29972 Cu 0.0 0.0 -0.770300 0.614955 -0.128436\natom -2.19706 9.36109 8.15394 Cu 0.0 0.0 -0.392773 -0.154234 0.399804\natom 8.76665 2.81892 9.53887 Cu 0.0 0.0 -0.780372 0.215782 0.003786\natom 5.28644 0.96172 8.39890 Cu 0.0 0.0 0.136369 0.156347 0.134575\natom 1.08726 6.34064 10.51175 Cu 0.0 0.0 0.407399 0.295713 -0.071598\natom 3.11846 11.24369 3.53539 Cu 0.0 0.0 0.054436 0.546157 -0.273634\natom 8.10032 5.09901 1.64997 Cu 0.0 0.0 0.605351 0.509909 -0.058306\natom 7.92746 2.22430 2.15267 Cu 0.0 0.0 -0.285030 -0.425962 -0.328757\natom 4.02530 7.63044 5.06780 Cu 0.0 0.0 0.098085 -0.020258 -0.150083\natom 0.84801 10.78258 10.08574 Cu 0.0 0.0 -0.012781 0.060098 -0.196227\natom 5.66910 5.17798 8.21035 Cu 0.0 0.0 -0.004776 -0.162723 0.169885\natom 4.94376 2.60399 1.88864 Cu 0.0 0.0 0.462375 -0.260189 -0.200248\natom 7.40734 9.18738 5.43795 Cu 0.0 0.0 -0.302900 0.121631 -0.378230\natom 4.17166 9.21653 11.54214 Cu 0.0 0.0 0.177297 0.858315 -0.057104\natom 2.46372 3.44918 6.94156 Cu 0.0 0.0 -0.152158 0.793010 0.123405\natom -3.70282 0.82198 11.11736 Cu 0.0 0.0 -0.732741 -0.151285 0.137772\natom 10.33710 7.04935 7.03988 Cu 0.0 0.0 0.008680 -0.390136 0.120207\natom 12.82669 10.86539 0.91417 Cu 0.0 0.0 0.146845 -0.152872 -0.227162\natom -0.46169 4.69825 5.33611 Cu 0.0 0.0 -0.102652 -0.282304 -0.105253\natom -2.05266 2.56551 5.95929 Cu 0.0 0.0 0.473966 -0.394692 -0.863912\natom 13.81805 6.84579 0.77730 Cu 0.0 0.0 0.662267 0.802520 0.341623\natom 10.09263 10.93454 7.23191 Cu 0.0 0.0 0.284999 0.287854 -0.489273\natom -3.24744 4.63597 11.36161 Cu 0.0 0.0 0.080581 0.591194 0.458826\natom 12.81367 3.06887 1.23080 Cu 0.0 0.0 -0.428769 -0.680859 -1.237602\natom -1.81844 7.63989 5.93215 Cu 0.0 0.0 -0.486275 0.022661 0.133889\natom -5.20591 11.04101 12.22676 Cu 0.0 0.0 0.042424 -0.306878 0.164773\natom 10.32286 3.17376 7.49533 Cu 0.0 0.0 -0.348939 0.043161 -0.402185\natom 11.79971 0.65657 5.78571 Cu 0.0 0.0 -0.368350 0.060982 -0.021615\natom 0.68742 7.76707 0.10380 Cu 0.0 0.0 -0.013731 0.167446 -0.084235\natom -2.38604 10.38676 5.82587 Cu 0.0 0.0 0.304418 0.435957 0.098024\natom 8.32753 4.36853 12.03424 Cu 0.0 0.0 0.495856 0.244356 0.032684\natom 9.64126 5.38370 4.18339 Cu 0.0 0.0 -0.273690 0.116320 -0.088167\natom 3.45786 8.42182 1.30771 Cu 0.0 0.0 -0.049939 -0.381608 -0.759553\natom 0.03395 8.71504 7.35714 Cu 0.0 0.0 0.474216 0.715643 -0.104378\natom 6.20203 4.14493 10.72187 Cu 0.0 0.0 0.021725 -0.431982 0.231612\natom -0.53441 1.11158 11.87948 Cu 0.0 0.0 0.117618 0.141784 0.490200\natom 5.70291 8.52449 3.23686 Cu 0.0 0.0 -0.786597 -0.056109 0.043648\natom 8.50197 10.71637 0.84741 Cu 0.0 0.0 0.273063 0.173012 -0.235396\natom 4.17338 4.61907 5.27744 Cu 0.0 0.0 0.288215 0.035539 0.071291\natom 4.26979 2.02951 5.90729 Cu 0.0 0.0 0.441252 0.061816 -0.283423\natom 8.57385 7.61490 0.63568 Cu 0.0 0.0 -0.112718 0.308720 0.399107\natom 5.39892 10.45005 7.03329 Cu 0.0 0.0 0.539084 0.343420 0.176989\natom 1.35797 3.95076 11.84888 Cu 0.0 0.0 -0.280319 0.248548 -0.095396\natom -2.03636 4.83174 8.36966 Cu 0.0 0.0 0.143964 0.389341 0.588647\natom 5.51672 8.49240 8.69273 Cu 0.0 0.0 0.349160 -0.426342 0.115098\natom 11.61805 8.80095 2.24001 Cu 0.0 0.0 -0.117756 0.322267 0.627920\natom 1.80554 1.75034 4.70120 Cu 0.0 0.0 0.443307 -0.124167 -0.515893\natom 8.55794 0.17438 8.66293 Cu 0.0 0.0 0.108060 0.196887 -0.155359\natom -2.28377 6.99602 9.99632 Cu 0.0 0.0 0.118645 0.112049 0.598567\natom -0.16013 11.38324 4.11808 Cu 0.0 0.0 -0.064353 0.446815 -0.880797\natom 11.74353 4.95169 2.55846 Cu 0.0 0.0 -0.034973 0.069073 0.153059\natom 10.79854 12.10314 1.63791 Cu 0.0 0.0 -0.092629 0.261468 -0.551144\natom 1.69017 6.43345 4.80581 Cu 0.0 0.0 -0.367641 -0.188162 -0.286776\natom -1.95308 11.28276 10.36773 Cu 0.0 0.0 0.526209 0.275986 -1.094353\natom 7.89584 7.84344 7.49851 Cu 0.0 0.0 -0.011144 -0.048114 0.219074\natom -4.18769 3.03213 9.83693 Cu 0.0 0.0 -0.247626 -0.238604 0.002403\natom 11.06681 8.45215 9.02190 Cu 0.0 0.0 0.258285 -0.066074 0.192159\natom 14.18925 9.60390 2.77560 Cu 0.0 0.0 -0.592992 0.192691 0.066795\natom 13.96762 3.48130 3.22778 Cu 0.0 0.0 1.424278 0.598057 0.475767\natom 7.75127 0.54836 5.67181 Cu 0.0 0.0 0.264939 -0.047939 0.334680\natom 6.32302 6.95165 1.22252 Cu 0.0 0.0 -0.635357 -0.348345 0.130776\natom 3.42464 11.49578 8.21037 Cu 0.0 0.0 -0.252074 -0.970223 0.254409\natom 3.40801 4.40459 9.27523 Cu 0.0 0.0 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0.0 0.0 -0.315855 -0.020495 -0.334533\natom 7.36472 6.42711 5.90427 Cu 0.0 0.0 -0.686462 0.625180 -0.525536\natom 13.60217 9.76897 2.24664 Cu 0.0 0.0 -0.438918 -0.335261 0.237930\natom -0.66989 5.39234 5.76535 Cu 0.0 0.0 0.212794 0.060264 -0.022974\natom 1.14471 1.66256 7.72996 Cu 0.0 0.0 -0.049823 0.244333 0.515953\natom 13.44259 7.25717 0.71848 Cu 0.0 0.0 -0.170634 0.271201 0.101703\natom 8.32492 9.61652 8.03735 Cu 0.0 0.0 -0.243768 -0.374760 0.081974\natom -4.00483 6.34274 10.28917 Cu 0.0 0.0 -0.140905 -0.202524 -0.213438\natom 2.38524 2.70601 1.68050 Cu 0.0 0.0 -0.078609 -0.273888 -0.003881\natom 11.02820 5.23731 5.42291 Cu 0.0 0.0 -0.374172 0.045292 0.120036\natom -3.57278 8.78594 11.75544 Cu 0.0 0.0 -0.120113 -0.013979 -0.023119\natom 10.23774 2.47740 8.42932 Cu 0.0 0.0 0.119225 -0.466315 -0.213476\natom -1.87407 2.73456 6.04800 Cu 0.0 0.0 -0.590790 -0.319146 0.256777\natom 2.03491 6.72843 1.28193 Cu 0.0 0.0 0.075369 0.051151 -0.103746\natom -0.85831 9.69200 4.91078 Cu 0.0 0.0 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-0.318301 -0.285213 -0.275662\natom 12.54658 5.55408 4.26068 S 0.0 0.0 0.247331 -0.009356 -1.278018\natom 12.64364 1.41845 4.26281 S 0.0 0.0 0.360005 0.591246 -0.488483\natom -0.39222 7.13348 1.82277 S 0.0 0.0 0.592497 0.203758 0.304372\natom -3.33398 11.65280 7.94998 S 0.0 0.0 -0.046456 -0.864229 -0.200171\natom 9.76883 4.75122 10.84802 S 0.0 0.0 -0.568813 -0.360570 -0.601469\natom 9.20919 1.19447 6.53652 S 0.0 0.0 -0.063997 0.542399 -0.551088\natom -2.83990 7.05472 11.90197 S 0.0 0.0 0.074340 0.726232 0.429158\natom 0.10034 11.12123 5.80558 S 0.0 0.0 0.693152 0.967509 1.573627\natom 12.05865 5.42245 0.15090 S 0.0 0.0 -0.005216 -0.064823 0.591861\natom 5.98017 1.26448 12.20416 S 0.0 0.0 -0.041939 -0.328534 0.017176\natom -0.01370 7.08958 5.90967 S 0.0 0.0 -0.127715 -0.398236 0.608652\natom -2.85626 10.90853 12.04336 S 0.0 0.0 -0.854673 -0.322929 -0.475137\natom 8.68570 5.17786 6.30474 S 0.0 0.0 0.522381 -0.000617 -0.300714\natom 3.18799 1.38592 7.76209 S 0.0 0.0 -0.194331 -0.339452 -0.733105\natom 2.83632 7.26526 11.17058 S 0.0 0.0 0.166006 -0.309623 0.159412\natom 6.01408 11.38648 4.70482 S 0.0 0.0 0.978988 -0.243598 0.192810\natom 6.58813 5.36553 1.04964 S 0.0 0.0 -0.751800 -0.111761 0.618048\natom 6.58982 1.12922 1.18185 S 0.0 0.0 -0.368215 -0.265120 0.337082\natom 5.95214 7.23248 4.99179 S 0.0 0.0 -0.291518 0.873634 -0.497107\natom 2.69918 10.59997 11.07013 S 0.0 0.0 0.343208 0.546882 0.338102\natom 3.70338 5.22286 7.78038 S 0.0 0.0 -0.944508 -0.125933 -0.520136\natom 0.07541 0.87985 9.58243 S 0.0 0.0 0.711442 -0.100208 -0.923294\natom 6.42934 7.27663 8.59544 S 0.0 0.0 -0.495867 -0.741549 1.154220\natom 10.07804 11.65919 2.55524 S 0.0 0.0 0.257914 -0.257515 0.068332\natom 2.69713 5.14672 3.50226 S 0.0 0.0 0.026037 0.185388 -0.328706\natom 3.08935 0.92756 3.56274 S 0.0 0.0 -0.890016 0.452045 0.259027\natom 9.64746 7.50208 2.79449 S 0.0 0.0 0.169887 0.247904 0.250646\natom 6.52103 10.82295 8.61840 S 0.0 0.0 0.170185 0.594626 0.233921\natom -0.30469 5.08016 9.87263 S 0.0 0.0 0.769273 -0.698464 -0.590558\natom 6.77541 2.98065 8.74371 S 0.0 0.0 -1.283497 -0.029035 -0.348337\natom -0.13759 9.09686 9.30966 S 0.0 0.0 0.099631 -0.410761 0.075561\natom 2.55926 9.59077 3.48474 S 0.0 0.0 0.863735 0.031501 0.719300\natom 9.28541 3.35511 2.40321 S 0.0 0.0 0.603354 -0.061214 0.067810\natom 6.03569 2.91589 4.70605 S 0.0 0.0 0.189944 0.594063 0.172699\natom 6.35465 9.23059 0.94509 S 0.0 0.0 0.535239 0.271264 0.524659\natom 3.05643 9.11995 7.08068 S 0.0 0.0 0.567097 -0.295655 -0.625579\natom 2.95991 2.93402 11.35155 S 0.0 0.0 1.071405 0.651270 -0.554452\natom 0.18048 3.41502 5.68687 S 0.0 0.0 0.384600 -0.529489 0.419188\natom 12.32408 9.26587 0.57127 S 0.0 0.0 0.433722 1.301119 0.164050\natom 9.43002 9.16702 6.50398 S 0.0 0.0 -0.256599 -0.054431 0.683706\natom -2.62578 3.06685 11.79800 S 0.0 0.0 -0.240121 0.372020 0.619817\natom -0.04290 3.14787 1.59548 S 0.0 0.0 0.970254 0.089043 -0.259683\natom 12.98623 9.17263 4.67240 S 0.0 0.0 0.152440 0.575905 0.302111\natom 9.53227 8.91491 10.30591 S 0.0 0.0 -0.685112 1.038407 0.295325\natom -3.13225 3.48488 7.90077 S 0.0 0.0 -0.014811 1.301442 0.094384\natom 9.59481 0.06700 4.65342 Cu 0.0 0.0 0.116751 -0.064238 -0.164732\natom 0.91039 8.99072 2.35376 Cu 0.0 0.0 -1.176160 -0.677189 -0.677117\natom -2.21893 9.78821 9.01786 Cu 0.0 0.0 -0.593941 0.121961 -0.299343\natom 8.37207 2.37395 9.98311 Cu 0.0 0.0 1.194117 -0.603994 0.721221\natom 4.93516 0.23853 8.26135 Cu 0.0 0.0 0.446226 -0.298511 0.225435\natom 0.70476 7.31121 10.33450 Cu 0.0 0.0 0.209507 -0.210476 -0.067451\natom 3.86738 11.03035 4.71473 Cu 0.0 0.0 -0.576510 0.170405 -0.462694\natom 7.89124 6.15898 2.74528 Cu 0.0 0.0 -0.083416 -0.235114 -0.044081\natom 8.60080 1.18897 2.50596 Cu 0.0 0.0 -0.342912 0.267708 -0.171332\natom 4.91751 5.93606 3.04608 Cu 0.0 0.0 0.585264 -0.301841 0.431588\natom -0.18604 11.00069 8.11343 Cu 0.0 0.0 0.629607 0.595878 -0.019950\natom 7.46381 4.58557 11.16522 Cu 0.0 0.0 0.431971 -0.055251 -0.369768\natom 5.43783 3.17330 0.58628 Cu 0.0 0.0 0.751054 -0.134144 0.145780\natom 7.79346 10.21145 5.36072 Cu 0.0 0.0 -0.210713 0.346441 0.087814\natom 4.44456 8.65607 11.93527 Cu 0.0 0.0 -0.621723 -0.044484 -0.542199\natom 3.19521 3.19368 8.99586 Cu 0.0 0.0 0.301098 0.373849 0.640625\natom -3.22247 0.98810 11.45025 Cu 0.0 0.0 -0.778177 -0.055368 0.462538\natom 10.02141 6.87428 6.96463 Cu 0.0 0.0 -0.466054 -0.395813 0.092533\natom 8.34192 9.26032 12.20548 Cu 0.0 0.0 -0.107000 0.040393 -0.361411\natom -0.77776 5.23806 4.74389 Cu 0.0 0.0 -0.445008 -0.012097 -0.053846\natom -0.36609 1.17627 5.25964 Cu 0.0 0.0 0.140315 -0.025360 -0.102878\natom 13.09292 7.32370 1.23212 Cu 0.0 0.0 -0.140317 -0.422094 -0.368668\natom 10.14531 11.26053 6.98040 Cu 0.0 0.0 -0.011902 -0.397193 -0.275866\natom -3.76666 5.10667 11.65684 Cu 0.0 0.0 -0.055709 -0.506695 0.140251\natom 14.05497 0.06633 0.03914 Cu 0.0 0.0 -0.030520 -0.035995 -0.000693\natom 11.86066 8.41714 6.51012 Cu 0.0 0.0 0.408466 0.739350 -0.581657\natom 8.67005 11.27913 10.07961 Cu 0.0 0.0 -0.320749 -0.635851 -0.423068\natom 12.32437 4.14522 5.78607 Cu 0.0 0.0 0.341482 -0.504738 0.648137\natom -1.23479 2.91699 3.35672 Cu 0.0 0.0 -0.659016 -0.454841 0.956127\natom 1.00522 7.50527 0.07590 Cu 0.0 0.0 0.104719 -0.094210 0.230070\natom -1.99280 10.56364 6.50865 Cu 0.0 0.0 -0.309346 -0.304530 -0.349435\natom 13.69559 2.74277 0.61079 Cu 0.0 0.0 -0.740031 -0.331046 -0.172883\natom 9.22275 4.45011 4.25023 Cu 0.0 0.0 -0.086758 0.039734 0.653019\natom 2.35601 11.26059 1.86454 Cu 0.0 0.0 0.179650 0.453328 -0.213761\natom -1.37705 7.77102 7.59437 Cu 0.0 0.0 0.019134 0.081708 -0.016318\natom 5.24701 2.62007 10.44240 Cu 0.0 0.0 0.062540 0.190268 0.046835\natom 1.12658 1.70875 11.43506 Cu 0.0 0.0 -0.028160 -0.375365 0.233956\natom 5.05132 7.90735 7.05512 Cu 0.0 0.0 -0.684530 -0.018753 -0.767936\natom 0.89312 11.42172 12.24069 Cu 0.0 0.0 0.401105 -0.161167 -0.065176\natom 4.80786 2.67143 6.46370 Cu 0.0 0.0 -0.695051 -0.144742 0.568310\natom 3.89943 3.26604 3.96128 Cu 0.0 0.0 -0.090352 -0.349887 -0.112373\natom 8.40738 8.35514 1.17016 Cu 0.0 0.0 -0.034714 0.043088 -0.120182\natom 5.27885 10.37154 6.67410 Cu 0.0 0.0 -0.250277 0.126462 -0.097865\natom 1.25782 4.50206 11.46215 Cu 0.0 0.0 -0.123207 -0.331732 0.001009\natom -0.82658 2.74934 10.24214 Cu 0.0 0.0 -0.521650 0.541842 -0.060889\natom 8.08190 8.58671 8.41195 Cu 0.0 0.0 1.144309 0.589912 -0.271331\natom 9.54522 9.77145 3.53392 Cu 0.0 0.0 0.090725 -0.229175 -0.557742\natom 2.28363 4.17761 6.17525 Cu 0.0 0.0 0.204788 0.502059 0.376952\natom 10.19798 0.92426 8.58233 Cu 0.0 0.0 -0.355278 0.500551 0.641861\natom -1.82880 6.56791 9.80804 Cu 0.0 0.0 -0.763870 0.542832 0.019441\natom 2.22932 1.80515 5.77201 Cu 0.0 0.0 -0.104699 -0.565560 -0.809516\natom 10.97333 3.53351 0.80184 Cu 0.0 0.0 -0.205191 -0.235996 0.165607\natom 11.80272 1.24535 2.06890 Cu 0.0 0.0 -0.487391 0.130022 0.150697\natom 3.00571 6.73402 1.85671 Cu 0.0 0.0 -0.600708 0.065040 -0.335741\natom -1.61013 11.91303 10.25029 Cu 0.0 0.0 0.031080 -0.582186 0.281713\natom 7.68284 0.54805 8.04037 Cu 0.0 0.0 -0.278114 -0.190353 0.073341\natom 10.89265 5.16226 8.86992 Cu 0.0 0.0 0.358718 -0.100269 -0.118323\natom -3.93790 8.51324 10.43345 Cu 0.0 0.0 0.580563 -0.236735 -0.083439\natom -0.29568 10.93883 3.75567 Cu 0.0 0.0 0.128843 -0.663979 -0.496995\natom 13.27170 4.82049 2.13767 Cu 0.0 0.0 -0.135176 0.306625 -0.043096\natom 7.29394 1.14258 4.96414 Cu 0.0 0.0 0.169748 -0.388981 0.298195\natom 5.23011 7.33966 0.78583 Cu 0.0 0.0 0.053700 -0.376640 -0.113537\natom 2.45545 9.49932 9.10105 Cu 0.0 0.0 -0.246187 0.300136 0.543202\natom 3.64948 5.17028 11.54319 Cu 0.0 0.0 0.107048 0.070810 -0.128099\natom 2.44681 11.30359 7.00374 Cu 0.0 0.0 -0.025781 0.254965 -0.101382\natom 6.39355 6.84172 10.86966 Cu 0.0 0.0 -0.213037 0.417160 -0.537863\natom 6.27812 9.95906 3.03080 Cu 0.0 0.0 -0.116200 0.123076 -0.099084\natom 3.31501 4.07767 1.56361 Cu 0.0 0.0 -0.315375 1.401912 0.111342\natom 3.38122 1.81596 1.55210 Cu 0.0 0.0 0.090393 -1.319310 -0.168675\natom 8.57339 7.96150 4.77577 Cu 0.0 0.0 -0.366746 -0.849091 -0.112655\natom 4.38742 12.02636 11.50090 Cu 0.0 0.0 -0.175537 -0.153927 -0.249788\natom 1.84360 5.20187 9.08090 Cu 0.0 0.0 -0.156068 0.456102 -0.271046\natom 5.91895 5.09469 8.77448 Cu 0.0 0.0 0.125797 -0.231646 0.083385\natom 4.30660 7.72042 9.50751 Cu 0.0 0.0 0.179000 -0.188776 0.056495\natom 4.21376 8.31056 3.87950 Cu 0.0 0.0 0.870269 -0.676225 0.047322\natom 6.67121 3.81184 2.80464 Cu 0.0 0.0 0.090315 0.428700 -0.556452\natom 13.93805 0.39667 2.72421 Cu 0.0 0.0 0.029497 0.250155 -0.018355\natom -0.92222 7.90297 3.96300 Cu 0.0 0.0 0.374962 -0.074293 -0.363626\natom -4.33044 11.18292 9.90598 Cu 0.0 0.0 0.254680 -0.281597 0.362052\natom 8.47752 4.52744 8.41032 Cu 0.0 0.0 0.064395 -0.005497 0.308827\natom 2.57199 0.02115 9.51645 Cu 0.0 0.0 -0.228133 0.148818 -0.092243\natom 1.97386 6.68146 6.86444 Cu 0.0 0.0 0.408201 -0.291500 0.279006\natom 4.78898 11.72322 0.93063 Cu 0.0 0.0 0.794492 0.883178 0.446575\natom 6.57658 5.15737 4.99169 Cu 0.0 0.0 0.233445 -0.519434 0.053256\natom 10.43995 3.29143 7.08732 Cu 0.0 0.0 -1.086618 -0.277490 -0.117102\natom -0.90918 9.66235 11.41394 Cu 0.0 0.0 -0.266128 -0.014263 -0.318448\natom 1.41159 8.57133 5.21934 Cu 0.0 0.0 0.314563 0.646491 -0.433158\natom 11.50956 3.52153 3.42247 Cu 0.0 0.0 -0.139381 -0.305530 0.038078\natom 0.79275 1.23641 2.51953 Cu 0.0 0.0 0.653530 -0.079349 0.244066\natom 11.59329 7.62853 4.01148 Cu 0.0 0.0 -0.511545 -0.275537 -0.334251\natom 6.43229 10.48680 10.82005 Cu 0.0 0.0 -0.355451 -0.501428 0.623257\natom -0.23605 4.30054 7.76004 Cu 0.0 0.0 0.077534 -0.220355 -0.205188\natom -2.91320 1.52962 8.65219 Cu 0.0 0.0 0.411510 -0.407871 0.288589\natom 9.20344 6.74618 10.18158 Cu 0.0 0.0 -0.198351 -0.092953 -0.096834\natom 12.10971 10.62549 3.34070 Cu 0.0 0.0 -0.659836 0.570467 -0.332356\natom 0.70651 5.18060 2.06950 Cu 0.0 0.0 0.283177 0.137366 0.218396\nenergy -562.538410\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/nnp-atomenv/Cu2S_PBE/input.nn",
    "content": "###############################################################################\n# HDNNP for copper sulfide Cu2S\n###############################################################################\n# Length unit     : Angstrom\n# Energy unit     : eV\n# Reference method: PBE\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\n#mean_energy  -3.8640662064628053E+00\n#conv_energy   7.3890846653659121E+00\n#conv_length   6.1376931796181502E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type.\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n"
  },
  {
    "path": "examples/nnp-atomenv/Cu2S_PBE/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   9.1739161189824411E-08   7.0593095050533450E-01   2.2372649929284196E-02   9.6379208796011293E-02\n         1          2   2.6433999906765265E-01   2.4749666370750676E+00   1.0378805142792313E+00   1.9413782463770093E-01\n         1          3   1.5504686427401054E-05   1.4168627312588329E+00   5.5254915214857578E-02   2.1495058826125538E-01\n         1          4   1.4086411910634238E+00   4.7388215758712082E+00   3.1031877925923803E+00   3.5864448236496921E-01\n         1          5   9.8043626772015909E-04   1.9535901883323099E+00   1.1429456309160095E-01   2.2901461288065855E-01\n         1          6   2.2158364445227399E+00   6.0748308460582043E+00   3.8835182764170546E+00   3.9299243538518969E-01\n         1          7   1.0255080523534783E+00   5.1401074554660049E+00   2.5810215644603796E+00   4.3835591238870431E-01\n         1          8   4.8489829707261999E-03   3.9129781874325281E-01   4.7557455423079396E-02   2.7778419734655713E-02\n         1          9   9.3223803365223998E-02   2.8346930075434797E+00   6.0185719975366336E-01   3.1949957606875956E-01\n         1         10   6.7206749586119430E-01   4.4876923880381465E+00   2.1991872165248538E+00   4.1504796440380803E-01\n         1         11   2.2128378766968923E-02   8.6593017344520318E-01   1.4060436434125115E-01   7.5838421599526348E-02\n         1         12   8.4205124330445313E-01   7.0656885702864862E+00   2.9013712601439368E+00   7.3052821449417049E-01\n         1         13   1.4518778507164800E+00   9.6462711741708382E+00   4.3715329035264965E+00   8.3811671947643118E-01\n         1         14   2.4300884834352513E-06   5.3039215356450418E-02   2.8067394350178213E-04   1.6541693025921896E-03\n         1         15   4.3805855934107564E-04   3.3431366727997386E-01   1.5056637491023487E-02   3.6381498406602590E-02\n         1         16   1.8742403996648012E-02   5.3094282134884740E-01   1.9287359264197504E-01   5.3785992354357007E-02\n         1         17   5.6391705067135155E-03   2.7103176024192799E-01   3.6199336036120536E-02   2.2235092628611220E-02\n         1         18   5.8157340520125522E-01   3.0394483797974066E+00   1.5432926655352674E+00   2.9013849228704902E-01\n         1         19   3.5474335876025032E-01   2.8914948266501281E+00   1.2453633098426364E+00   2.6070492382053573E-01\n         1         20   1.3050150224953865E-03   2.0977615521049353E-01   1.6466279986318652E-02   1.6175233794254219E-02\n         1         21   3.3625763520090814E-02   1.6019727512861448E+00   2.6707302954572526E-01   1.9158906783856428E-01\n         1         22   3.5314748293148263E-01   2.5968432133168928E+00   1.2041087980295160E+00   2.3880745648555143E-01\n         1         23   5.6279184570511148E-03   4.8263719913200909E-01   4.8674878532957294E-02   4.5579012837321450E-02\n         1         24   3.5640890668898983E-01   3.9354254479681789E+00   1.3506519169134916E+00   4.3100694380807969E-01\n         1         25   7.1435545388184229E-01   5.4083380133399706E+00   2.3405335217844168E+00   4.7481787957091687E-01\n         1         26   6.0302894280955782E-07   2.4282702757490063E-02   1.0392381208153868E-04   6.9514343858439293E-04\n         1         27   1.4152015883516988E-04   1.8793440136817721E-01   6.7319944252965166E-03   1.8860146728064606E-02\n         1         28   7.6669273315039489E-03   2.8853650966579203E-01   9.6832241039761832E-02   2.8591400835791262E-02\n         1         29   1.4586287100215936E-03   1.2827520308122028E-01   1.2535333774723276E-02   1.2196652689168296E-02\n         1         30   2.4306078779227119E-01   1.5771292876622454E+00   7.3118666045976355E-01   1.6033491927751306E-01\n         1         31   1.5700215118676836E-01   1.4950427209078341E+00   6.2168623298528469E-01   1.3878720233016123E-01\n         1         32   8.0322135442977674E-08   9.1020506427165644E-03   1.1758299063219979E-04   7.2850621729108440E-04\n         1         33   3.8387499554503460E-05   4.6879099417593433E-02   2.2899299020297070E-03   6.3507919696978174E-03\n         1         34   2.5111603817039843E-07   2.6638155845094137E-02   3.5204871838944324E-04   2.1803344919789219E-03\n         1         35   7.8176366916082938E-04   1.2144199943350505E-01   1.0237823308897595E-02   1.5551953673898984E-02\n         1         36   6.0784771853405629E-03   1.5177813800129991E-01   4.5342256644197804E-02   1.4422755174681633E-02\n         1         37   6.5208235096380454E-08   6.8957085587219831E-03   8.4477914517405974E-05   5.1826403434160535E-04\n         1         38   5.1003186367566016E-04   3.3817704100212627E-02   5.0495259674331701E-03   4.2413701977289924E-03\n         1         39   3.0092380409832575E-01   3.9241027015819827E+00   1.6245850308330121E+00   3.6115017167195557E-01\n         1         40   2.9205060411645536E+00   2.0972699454192377E+01   1.0685030237788666E+01   1.8434608066664662E+00\n         1         41   5.8304225749625562E+00   3.3157582599900756E+01   1.6937338463410185E+01   2.8416990087236536E+00\n         1         42   2.8963706388516774E-01   3.4220973094358569E+00   1.3527222233246401E+00   2.9841578592458634E-01\n         1         43   3.3240856510350132E+00   1.9977206504626281E+01   1.0533032366441756E+01   1.8362183066460305E+00\n         1         44   5.5968160844972745E+00   2.9479500954936675E+01   1.4663357897716818E+01   2.4340402007751933E+00\n         1         45   7.3194532436105672E-02   1.4240027432637063E+00   4.6184059564430718E-01   1.0603619804309938E-01\n         1         46   7.4351404260172327E-01   6.1601360099088307E+00   3.0926623459215312E+00   5.2746971733324144E-01\n         1         47   1.0304047665725904E+00   9.5490875529313932E+00   4.6615470051220029E+00   8.8228607777747381E-01\n         1         48   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2.7321455653550736E-03   2.6718628880300366E-01   6.8392239083035003E-02   1.8417271845608391E-02\n         2         17   1.4998879259624551E-04   2.8869834404308442E-01   3.2421219256901605E-02   2.1462316150937667E-02\n         2         18   9.6976148378458242E-03   6.9986551977156553E-01   7.4501947267367571E-02   9.2109247490457000E-02\n         2         19   7.5554776729931772E-01   3.8650650491408283E+00   2.1261658860729638E+00   2.9459249679651817E-01\n         2         20   2.2984860438624041E-01   2.2399640197541903E+00   8.4832685420611464E-01   2.2013029667841760E-01\n         2         21   3.1742242534198488E-02   6.9305314098138393E-01   2.0239450285654340E-01   6.2019223320811959E-02\n         2         22   1.6267388613945685E-01   1.8982342788109985E+00   8.1342448996901984E-01   1.7017885772188068E-01\n         2         23   4.3623299253776143E-02   1.8524213261728384E+00   4.3372964228967342E-01   1.6475284995752615E-01\n         2         24   1.1782155855406862E-02   1.3256780035707432E+00   2.0203673375826020E-01   1.2375770385162231E-01\n         2         25   9.5572013219445029E-01   5.1585503300832807E+00   2.7312178298449119E+00   4.5027566865612645E-01\n         2         26   2.1346552007948805E-01   3.7560054368796258E+00   1.2309867059977997E+00   3.8895981570570448E-01\n         2         27   1.0778454975081308E-03   1.6230009416534466E-01   3.4353839552470775E-02   1.0338804556484340E-02\n         2         28   4.1455680376600344E-05   1.3561930079689324E-01   1.3464607540962245E-02   9.4307016558753589E-03\n         2         29   2.9811923400491925E-03   3.9674788724187127E-01   3.2946560522656709E-02   5.3575100644579036E-02\n         2         30   4.0860996892032608E-01   2.1541090596644543E+00   1.1291055145629398E+00   1.6554701558125592E-01\n         2         31   8.7689965003411183E-02   1.1196100344004409E+00   3.9704096379805787E-01   1.1606734505235136E-01\n         2         32   2.0029888316796539E-05   1.7556653440553127E-02   1.4233102888664287E-03   1.3598121443903737E-03\n         2         33   5.2716716179610746E-06   4.4644993845652417E-02   1.7086280138653978E-03   4.2643079956046579E-03\n         2         34   8.8339290835669212E-07   1.2139204575362132E-02   4.1922038284938451E-04   1.5155281653507265E-03\n         2         35   1.2653672947005059E+00   8.9337925904902882E+00   4.2637335795708999E+00   5.9362291906692699E-01\n         2         36   4.3025897744283652E+00   2.4744209023066571E+01   1.4272525712868205E+01   1.9700222663219151E+00\n         2         37   2.9677470818795189E+00   2.5847640450705327E+01   1.1788593731598802E+01   2.3639335745006553E+00\n         2         38   4.8673248345854536E-01   6.9220258514917292E+00   2.9410791137038919E+00   5.0416378898015868E-01\n         2         39   4.7312413761643519E+00   2.4784350068345699E+01   1.4182436900763136E+01   1.9734981280505293E+00\n         2         40   2.7914940844674572E+00   2.2909604188642842E+01   1.0258913931047273E+01   2.0538117984713926E+00\n         2         41   5.1976352609600407E-01   3.0581982698648895E+00   1.1910833091075925E+00   2.2566892125976182E-01\n         2         42   1.0695804209866875E+00   7.2313250376604037E+00   3.9928775708897235E+00   5.8095727320582324E-01\n         2         43   8.4628209088378592E-01   7.5313801441068913E+00   3.3982729265620653E+00   7.1123273080942895E-01\n         2         44   7.0763463381880415E-02   1.2969398476188700E+00   3.1793764328087359E-01   1.3617384576811825E-01\n         2         45   1.3721123798749537E+00   6.3973513973729199E+00   3.7457022157866304E+00   5.0158792550110110E-01\n         2         46   6.3964342968618404E-01   4.7161013997028380E+00   1.9947659320351354E+00   4.2776493844298569E-01\n         2         47   8.6532747970285151E-01   6.1240088873304499E+00   2.7402018484921369E+00   4.0552538612845523E-01\n         2         48   2.5315105294788682E+00   1.5776758660822487E+01   8.7867531123795093E+00   1.2800885070636867E+00\n         2         49   1.5679508239487920E+00   1.6123025100421103E+01   6.9389600266532643E+00   1.5752331036924878E+00\n         2         50   2.4475421880204548E-01   4.5715135037651979E+00   1.7778621079614614E+00   3.3311384228682872E-01\n         2         51   2.8365798870360606E+00   1.5735394223700631E+01   8.7129345829426814E+00   1.2788947945672131E+00\n         2         52   1.4825266957775993E+00   1.4111085036729261E+01   5.9550381055833128E+00   1.3412575984240060E+00\n         2         53   2.9486345514961088E-01   2.1632897998459173E+00   7.6894782290828789E-01   1.6439255789853263E-01\n         2         54   6.1183454216254696E-01   4.7418024842673727E+00   2.4364672738977449E+00   3.8379810845509604E-01\n         2         55   4.2978046698724798E-01   4.7295979558909700E+00   2.0069121315341767E+00   4.7649159304923261E-01\n         2         56   3.3379248097225291E-02   8.3272635081969881E-01   1.7274845946125020E-01   8.7956031429209408E-02\n         2         57   8.2656009161897048E-01   3.9467471262168639E+00   2.2459243943426777E+00   3.1269124051179731E-01\n         2         58   3.1171589063801924E-01   2.7714452296122714E+00   1.1129251102859337E+00   2.6297335909685149E-01\n         2         59   2.6592109568248031E-02   5.6825603390221913E-01   2.0877471778793405E-01   4.9135988886466996E-02\n         2         60   7.2485536842319745E-02   1.1034806181844534E+00   4.5818934497666303E-01   1.0344323974312900E-01\n         2         61   5.9263838221524185E-03   1.2515028539804678E+00   2.4502825958578195E-01   1.1006546541667923E-01\n         2         62   3.5994334696395447E-03   3.9125406849266531E-01   8.9107610428087070E-02   3.1854933024728180E-02\n         2         63   7.2533340578499653E-02   1.0927078443379801E+00   4.4612155612487853E-01   1.0164232620041405E-01\n         2         64   5.4706332551405917E-03   9.8645463183530846E-01   1.9457952454956559E-01   8.6829363320211461E-02\n         2         65   1.7435002600794914E-04   5.6940854477051987E-02   3.9265019004702875E-03   5.9979210203388224E-03\n         2         66   2.1035187678847361E-02   2.2735828246294021E-01   9.5459655622289877E-02   2.0577872261152416E-02\n"
  },
  {
    "path": "examples/nnp-atomenv/H2O_RPBE-D3/input.data",
    "content": " begin\ncomment written by RuNNerDecom\nlattice      24.623508      0.000000      0.000000\nlattice       0.000000     24.623508      0.000000\nlattice       0.000000      0.000000     24.623508\natom     3.735290838    2.327841157    3.501304856   O   -0.226389360    0.000000000   -0.006530137   -0.002852459   -0.027992554\natom     5.246524320    3.393061301    3.627368536   H    0.120793430    0.000000000    0.004517488   -0.000517262    0.005052573\natom     3.558676964    2.038939712    1.628158442   H    0.127225380    0.000000000    0.000095815    0.002211264    0.023427576\natom     4.652261909   21.146799653   16.174455806   O   -0.240350190    0.000000000   -0.000231046   -0.007150914    0.026944723\natom     4.197045601   22.522898765   15.074691455   H    0.132518870    0.000000000   -0.001535223    0.002790532   -0.018391035\natom     5.012047009   19.588530870   15.274057640   H    0.135733700    0.000000000    0.002788938    0.006272370   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   0.000000000    0.018523075   -0.024840566    0.006342047\natom    14.267430368    9.977754135   11.829684586   H    0.113782900    0.000000000   -0.008734593    0.013546003   -0.004698673\natom    13.341466088    2.570026664   13.832795076   O   -0.251475360    0.000000000   -0.015742622   -0.000636180    0.011361147\natom    11.829684586    1.625165115   13.171390669   H    0.099712130    0.000000000    0.007216544    0.006519813    0.005108999\natom    13.058007056    2.721204814   15.722520064   H    0.100370950    0.000000000   -0.000646872   -0.005633644   -0.027299357\natom     7.615595538    2.702307545    2.777896621   O   -0.268232650    0.000000000   -0.006388347    0.017789459    0.001065508\natom     5.763665087    2.456643051    3.136944727   H    0.092468900    0.000000000    0.016202665    0.002093654   -0.005620775\natom     7.804568226    4.554239886    2.305464901   H    0.099699310    0.000000000    0.000470339   -0.019376041   -0.000827069\natom     8.106924526    7.502211925    0.642507138   O   -0.263270120    0.000000000    0.020686620    0.015792202   -0.000682679\natom     9.316349728    7.596698269   -0.831479826   H    0.102961080    0.000000000   -0.014186950    0.000417599    0.017292866\natom     8.617150783    8.976198890    1.757445996   H    0.096057990    0.000000000   -0.010091877   -0.018942608   -0.019618862\natom     9.562014222   14.380813981   11.848581854   O   -0.256632660    0.000000000   -0.011765853   -0.010018943    0.002842842\natom     8.806123471   14.607581206   10.110033127   H    0.102472630    0.000000000    0.004058043   -0.001074281    0.017472896\natom     8.144719064   13.681616926   12.925726175   H    0.109190280    0.000000000    0.014044582    0.010410352   -0.022798551\natom     9.732089641    7.747876419    6.916396593   O   -0.232893070    0.000000000   -0.012576693    0.028565651   -0.023777005\natom     9.713192372    9.278555190    5.744767819   H    0.127167330    0.000000000    0.009144702   -0.032698501    0.022742913\natom     7.861260032    7.540006463    7.199855625   H    0.107351080    0.000000000    0.013807420   -0.005137071   -0.003691936\natom     4.837698917   13.379260625   13.870589614   O   -0.217673370    0.000000000   -0.010876559   -0.007494039    0.019947357\natom     3.231431071   12.491088993   13.322568819   H    0.113873520    0.000000000    0.017450008    0.012636472    0.013258230\natom     4.724315305   13.757206001   15.741417333   H    0.129587430    0.000000000   -0.008265304   -0.004854866   -0.031505650\natom     2.116492213    7.275444700   15.344574689   O   -0.271519240    0.000000000    0.003721200    0.008520093   -0.025792126\natom     1.398397890    8.825020740   14.494197594   H    0.119856700    0.000000000    0.017408675   -0.028056072    0.015153435\natom     3.401506490    6.519553949   14.135149487   H    0.133218540    0.000000000   -0.021344903    0.016767178    0.021407706\natom     7.369931044    0.302356300    7.294341969   O   -0.220182040    0.000000000   -0.016962630   -0.007854252   -0.022791701\natom     7.899054570    1.398397890    5.820356894   H    0.106388840    0.000000000   -0.006952790   -0.001015854    0.010976189\natom     5.574692400   -0.188972688    6.840807518   H    0.119706610    0.000000000    0.034102223    0.009248015    0.015697746\natom     3.174739265    1.058247052    4.062910897   O   -0.220255450    0.000000000   -0.032726729   -0.000354508   -0.001364851\natom     1.511781502    1.927521415    3.722760059   H    0.119615460    0.000000000    0.022869270   -0.014738414    0.009684134\natom     2.740102083   -0.377945376    5.253438830   H    0.102308210    0.000000000   -0.003629110    0.006732548   -0.010769141\natom     2.154286751   11.961965467    7.180958356   O   -0.240775800    0.000000000    0.009122791   -0.004982979    0.009900370\natom     3.004663846   10.261211277    7.199855625   H    0.123082890    0.000000000   -0.010714630    0.021314294    0.006951169\natom     1.719651459   12.453294455    8.976198890   H    0.115761200    0.000000000    0.004591800   -0.017597022   -0.019732886\natom    13.417055163    3.703862791    4.025116360   O   -0.190128900    0.000000000   -0.016402162    0.055351873   -0.001006850\natom    12.018657273    4.610931692    4.969979799   H    0.147045320    0.000000000    0.013413052   -0.020709035   -0.006834321\natom    13.983973226    5.234541562    3.023561115   H    0.144388550    0.000000000    0.004029892   -0.019854074    0.010580859\nenergy   -1225.06985518\ncharge         0.0000000000\n end\n begin\ncomment written by RuNNerDecom\nlattice      14.782194      0.000000      0.000000\nlattice       0.000000     14.782194      0.000000\nlattice       0.000000      0.000000     14.782194\natom    11.400096754   13.987044033    9.287814852   O   -0.266631430    0.000000000    0.006003401   -0.027296987    0.010331412\natom    10.894553240   15.711153357    8.813633246   H    0.111583360    0.000000000   -0.012856778   -0.023375192   -0.000005688\natom     9.989260682   12.684784108    9.613887225   H    0.102455090    0.000000000    0.009113211    0.044638185   -0.012928939\natom     3.784639166    4.760530031    3.007759219   O   -0.260999230    0.000000000    0.034864635   -0.019137222    0.012190007\natom     4.967651655    3.453789564    2.067306402   H    0.108108550    0.000000000   -0.024519111    0.028424641    0.033241519\natom     4.205485121    4.673938966    4.966644431   H    0.108102810    0.000000000   -0.013144228   -0.012505323   -0.050529493\natom    13.578277212    3.357430501    2.230852815   O   -0.265503680    0.000000000    0.009457228   -0.025689021   -0.013174336\natom    13.339323138    1.531657650    1.585991077   H    0.115799580    0.000000000    0.011157472    0.042412027    0.010049623\natom    15.462896158    3.843626991    2.153211496   H    0.099211820    0.000000000   -0.026633251   -0.012328516    0.005608888\natom     3.813761747    3.362360798    8.004416292   O   -0.214916570    0.000000000    0.008445927    0.005222495    0.012662183\natom     3.456112038    1.605016847    8.458634824   H    0.135238140    0.000000000   -0.000182282    0.003156323    0.000822673\natom     4.981178320    3.899152835    9.399015830   H    0.106653320    0.000000000   -0.009589671   -0.007144409   -0.005923857\natom     9.210570376   11.605559199    3.402619539   O   -0.227137870    0.000000000   -0.033575788    0.016123566    0.007429402\natom     9.248047440    9.949538623    2.619751047   H    0.095161930    0.000000000    0.005363792   -0.018134607   -0.010848833\natom     7.354594021   11.651177205    3.888407848   H    0.111705120    0.000000000    0.023188742   -0.007382475    0.005319132\natom     7.048673695    0.959875429    1.289804735   O   -0.236808690    0.000000000    0.021968981    0.008023820   -0.035555297\natom     7.801130813   -0.612322531    1.904277775   H    0.099419770    0.000000000    0.004213325   -0.004190418    0.007204636\natom     8.258688492    1.311510137   -0.157293306   H    0.129396420    0.000000000   -0.023374625    0.001187028    0.020493432\natom     7.453687519    3.722763839   11.647259802   O   -0.240670670    0.000000000    0.016604663    0.022272654   -0.011433843\natom     7.856987360    5.010620265   13.029311554   H    0.125042720    0.000000000   -0.000216408   -0.016545721   -0.033123534\natom     8.390846541    4.027654263    9.891138504   H    0.106641770    0.000000000   -0.009744176    0.001311510    0.044557312\natom     9.591922929    3.636051831    7.006617824   O   -0.177886700    0.000000000    0.020764716    0.035866214   -0.040602524\natom     8.602308868    4.123867817    5.436077154   H    0.158810880    0.000000000    0.014144342   -0.013886115    0.027733004\natom    11.323245341    4.420328170    6.580941726   H    0.148643600    0.000000000   -0.029316584   -0.013759021    0.010165974\natom    13.932772966   11.010916952    5.324033357   O   -0.272368940    0.000000000   -0.031709980    0.005941426   -0.006211509\natom    12.986711441   11.510171455    6.882593159   H    0.109058660    0.000000000    0.018464083    0.004702735   -0.009185046\natom    12.372742957   10.941276737    4.222519119   H    0.100176900    0.000000000    0.023484862    0.002710255    0.013910920\natom    10.011969530    7.147831444    1.138367692   O   -0.268084950    0.000000000    0.031903865   -0.017360031   -0.048087715\natom    11.217428195    5.579743640    1.382070649   H    0.098718200    0.000000000   -0.016376190    0.031900049   -0.001302878\natom    10.623543729    7.870842837   -0.679143273   H    0.098891220    0.000000000   -0.007531025   -0.020993194    0.044532202\natom     6.933814206   11.473883030    9.595456719   O   -0.241122680    0.000000000   -0.032274345    0.007556561    0.028589313\natom     5.418459230   12.248465069   10.718861553   H    0.113480820    0.000000000    0.030225503   -0.024059407   -0.038121028\natom     6.210708326   10.792666726    8.038197049   H    0.120956070    0.000000000   -0.002256347    0.002910467    0.006395998\natom     4.475508195   10.014764436    4.589674154   O   -0.212648850    0.000000000   -0.005810155    0.033746537    0.030551251\natom     3.020095356   11.175706805    4.948741158   H    0.144660760    0.000000000    0.007883643   -0.020866638   -0.013752232\natom     4.165759283    9.011098366    3.129378261   H    0.143832960    0.000000000   -0.010141226   -0.013952791   -0.014587652\natom    13.398157894   13.398773945   14.086271701   O   -0.218599430    0.000000000    0.007131722   -0.029858862    0.015231412\natom    13.735940904   11.982187434   15.384710598   H    0.151347450    0.000000000   -0.008535887    0.029667214   -0.041657848\natom    12.971302608   12.717421581   12.342530004   H    0.117807410    0.000000000   -0.003346494    0.003600482    0.027404308\natom    -0.029853905    6.883301806    7.971228908   O   -0.223990930    0.000000000    0.024264161   -0.006314132   -0.021693996\natom     0.977655869    7.473268868    6.440535019   H    0.133521400    0.000000000   -0.025902051   -0.005351332    0.030962871\natom     1.060898338    5.576689841    8.725726931   H    0.114826910    0.000000000   -0.001307442    0.000374352   -0.007600117\natom     3.181506377   14.173805740   11.779022898   O   -0.232149600    0.000000000   -0.012334071   -0.008570649   -0.022345041\natom     4.514030277   14.870986456   12.792615703   H    0.125547620    0.000000000   -0.004584722    0.015890876    0.020256429\natom     1.399554402   14.377221610   12.428251795   H    0.122711800    0.000000000    0.025412017   -0.004414577    0.010547137\natom    11.530616410    8.776902624   11.168391672   O   -0.228946230    0.000000000   -0.036161915    0.015805311    0.029203899\natom     9.749297494    8.859990136   10.577149045   H    0.128448790    0.000000000    0.020958541   -0.001422328   -0.005878341\natom    12.710696043    8.032102680    9.992569594   H    0.102458220    0.000000000    0.006405910   -0.008905758   -0.020845229\nenergy   -1225.02203483\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/nnp-atomenv/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-atomenv/H2O_RPBE-D3/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "examples/nnp-checkdw/H2O_RPBE-D3/input.data",
    "content": " begin\ncomment written by RuNNerDecom\nlattice      14.782194      0.000000      0.000000\nlattice       0.000000     14.782194      0.000000\nlattice       0.000000      0.000000     14.782194\natom     0.642507138    5.688076012   14.059560412   O   -0.223804650    0.000000000   -0.012843144   -0.012768831    0.020115876\natom    -0.415739913    4.573137154   15.212293807   H    0.123401960    0.000000000    0.018853582    0.026511418   -0.014393530\natom     1.058247052    7.313239238   14.947732044   H    0.118244300    0.000000000   -0.001610950   -0.022831932   -0.011001476\natom     5.858151431    1.473986965    7.256547431   O   -0.223298820    0.000000000   -0.020285563    0.014001355   -0.027641789\natom     6.651834830    0.888171633    5.631384206   H    0.112270890    0.000000000    0.002511650    0.001550816    0.013843836\natom     4.818801649    2.910177502    6.557348486   H    0.118618850    0.000000000    0.011831258   -0.012126922    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3.155841996   O   -0.221094910    0.000000000   -0.004813985    0.038302265    0.000856240\natom     9.013993428   12.774548025    4.781007111   H    0.118896120    0.000000000    0.001659542   -0.006987235   -0.015766624\natom     9.278555190   13.322568819    1.908624147   H    0.145929140    0.000000000    0.004257843   -0.022545823    0.021135192\natom    15.023321119   11.716300973   11.999760005   O   -0.198777980    0.000000000   -0.019413194    0.009913657   -0.001400088\natom    13.568233313   12.963520712   11.924170930   H    0.143207780    0.000000000    0.018523075   -0.024840566    0.006342047\natom    14.267430368    9.977754135   11.829684586   H    0.113782900    0.000000000   -0.008734593    0.013546003   -0.004698673\natom    13.341466088    2.570026664   13.832795076   O   -0.251475360    0.000000000   -0.015742622   -0.000636180    0.011361147\natom    11.829684586    1.625165115   13.171390669   H    0.099712130    0.000000000    0.007216544    0.006519813    0.005108999\natom    13.058007056    2.721204814   15.722520064   H    0.100370950    0.000000000   -0.000646872   -0.005633644   -0.027299357\natom     7.615595538    2.702307545    2.777896621   O   -0.268232650    0.000000000   -0.006388347    0.017789459    0.001065508\natom     5.763665087    2.456643051    3.136944727   H    0.092468900    0.000000000    0.016202665    0.002093654   -0.005620775\natom     7.804568226    4.554239886    2.305464901   H    0.099699310    0.000000000    0.000470339   -0.019376041   -0.000827069\natom     8.106924526    7.502211925    0.642507138   O   -0.263270120    0.000000000    0.020686620    0.015792202   -0.000682679\natom     9.316349728    7.596698269   -0.831479826   H    0.102961080    0.000000000   -0.014186950    0.000417599    0.017292866\natom     8.617150783    8.976198890    1.757445996   H    0.096057990    0.000000000   -0.010091877   -0.018942608   -0.019618862\natom     9.562014222   14.380813981   11.848581854   O   -0.256632660    0.000000000   -0.011765853   -0.010018943    0.002842842\natom     8.806123471   14.607581206   10.110033127   H    0.102472630    0.000000000    0.004058043   -0.001074281    0.017472896\natom     8.144719064   13.681616926   12.925726175   H    0.109190280    0.000000000    0.014044582    0.010410352   -0.022798551\natom     9.732089641    7.747876419    6.916396593   O   -0.232893070    0.000000000   -0.012576693    0.028565651   -0.023777005\natom     9.713192372    9.278555190    5.744767819   H    0.127167330    0.000000000    0.009144702   -0.032698501    0.022742913\natom     7.861260032    7.540006463    7.199855625   H    0.107351080    0.000000000    0.013807420   -0.005137071   -0.003691936\natom     4.837698917   13.379260625   13.870589614   O   -0.217673370    0.000000000   -0.010876559   -0.007494039    0.019947357\natom     3.231431071   12.491088993   13.322568819   H    0.113873520    0.000000000    0.017450008    0.012636472    0.013258230\natom     4.724315305   13.757206001   15.741417333   H    0.129587430    0.000000000   -0.008265304   -0.004854866   -0.031505650\natom     2.116492213    7.275444700   15.344574689   O   -0.271519240    0.000000000    0.003721200    0.008520093   -0.025792126\natom     1.398397890    8.825020740   14.494197594   H    0.119856700    0.000000000    0.017408675   -0.028056072    0.015153435\natom     3.401506490    6.519553949   14.135149487   H    0.133218540    0.000000000   -0.021344903    0.016767178    0.021407706\natom     7.369931044    0.302356300    7.294341969   O   -0.220182040    0.000000000   -0.016962630   -0.007854252   -0.022791701\natom     7.899054570    1.398397890    5.820356894   H    0.106388840    0.000000000   -0.006952790   -0.001015854    0.010976189\natom     5.574692400   -0.188972688    6.840807518   H    0.119706610    0.000000000    0.034102223    0.009248015    0.015697746\natom     3.174739265    1.058247052    4.062910897   O   -0.220255450    0.000000000   -0.032726729   -0.000354508   -0.001364851\natom     1.511781502    1.927521415    3.722760059   H    0.119615460    0.000000000    0.022869270   -0.014738414    0.009684134\natom     2.740102083   -0.377945376    5.253438830   H    0.102308210    0.000000000   -0.003629110    0.006732548   -0.010769141\natom     2.154286751   11.961965467    7.180958356   O   -0.240775800    0.000000000    0.009122791   -0.004982979    0.009900370\natom     3.004663846   10.261211277    7.199855625   H    0.123082890    0.000000000   -0.010714630    0.021314294    0.006951169\natom     1.719651459   12.453294455    8.976198890   H    0.115761200    0.000000000    0.004591800   -0.017597022   -0.019732886\natom    13.417055163    3.703862791    4.025116360   O   -0.190128900    0.000000000   -0.016402162    0.055351873   -0.001006850\natom    12.018657273    4.610931692    4.969979799   H    0.147045320    0.000000000    0.013413052   -0.020709035   -0.006834321\natom    13.983973226    5.234541562    3.023561115   H    0.144388550    0.000000000    0.004029892   -0.019854074    0.010580859\nenergy   -1225.06985518\ncharge         0.0000000000\n end\n begin\ncomment written by RuNNerDecom\nlattice      14.782194      0.000000      0.000000\nlattice       0.000000     14.782194      0.000000\nlattice       0.000000      0.000000     14.782194\natom    11.400096754   13.987044033    9.287814852   O   -0.266631430    0.000000000    0.006003401   -0.027296987    0.010331412\natom    10.894553240   15.711153357    8.813633246   H    0.111583360    0.000000000   -0.012856778   -0.023375192   -0.000005688\natom     9.989260682   12.684784108    9.613887225   H    0.102455090    0.000000000    0.009113211    0.044638185   -0.012928939\natom     3.784639166    4.760530031    3.007759219   O   -0.260999230    0.000000000    0.034864635   -0.019137222    0.012190007\natom     4.967651655    3.453789564    2.067306402   H    0.108108550    0.000000000   -0.024519111    0.028424641    0.033241519\natom     4.205485121    4.673938966    4.966644431   H    0.108102810    0.000000000   -0.013144228   -0.012505323   -0.050529493\natom    13.578277212    3.357430501    2.230852815   O   -0.265503680    0.000000000    0.009457228   -0.025689021   -0.013174336\natom    13.339323138    1.531657650    1.585991077   H    0.115799580    0.000000000    0.011157472    0.042412027    0.010049623\natom    15.462896158    3.843626991    2.153211496   H    0.099211820    0.000000000   -0.026633251   -0.012328516    0.005608888\natom     3.813761747    3.362360798    8.004416292   O   -0.214916570    0.000000000    0.008445927    0.005222495    0.012662183\natom     3.456112038    1.605016847    8.458634824   H    0.135238140    0.000000000   -0.000182282    0.003156323    0.000822673\natom     4.981178320    3.899152835    9.399015830   H    0.106653320    0.000000000   -0.009589671   -0.007144409   -0.005923857\natom     9.210570376   11.605559199    3.402619539   O   -0.227137870    0.000000000   -0.033575788    0.016123566    0.007429402\natom     9.248047440    9.949538623    2.619751047   H    0.095161930    0.000000000    0.005363792   -0.018134607   -0.010848833\natom     7.354594021   11.651177205    3.888407848   H    0.111705120    0.000000000    0.023188742   -0.007382475    0.005319132\natom     7.048673695    0.959875429    1.289804735   O   -0.236808690    0.000000000    0.021968981    0.008023820   -0.035555297\natom     7.801130813   -0.612322531    1.904277775   H    0.099419770    0.000000000    0.004213325   -0.004190418    0.007204636\natom     8.258688492    1.311510137   -0.157293306   H    0.129396420    0.000000000   -0.023374625    0.001187028    0.020493432\natom     7.453687519    3.722763839   11.647259802   O   -0.240670670    0.000000000    0.016604663    0.022272654   -0.011433843\natom     7.856987360    5.010620265   13.029311554   H    0.125042720    0.000000000   -0.000216408   -0.016545721   -0.033123534\natom     8.390846541    4.027654263    9.891138504   H    0.106641770    0.000000000   -0.009744176    0.001311510    0.044557312\natom     9.591922929    3.636051831    7.006617824   O   -0.177886700    0.000000000    0.020764716    0.035866214   -0.040602524\natom     8.602308868    4.123867817    5.436077154   H    0.158810880    0.000000000    0.014144342   -0.013886115    0.027733004\natom    11.323245341    4.420328170    6.580941726   H    0.148643600    0.000000000   -0.029316584   -0.013759021    0.010165974\natom    13.932772966   11.010916952    5.324033357   O   -0.272368940    0.000000000   -0.031709980    0.005941426   -0.006211509\natom    12.986711441   11.510171455    6.882593159   H    0.109058660    0.000000000    0.018464083    0.004702735   -0.009185046\natom    12.372742957   10.941276737    4.222519119   H    0.100176900    0.000000000    0.023484862    0.002710255    0.013910920\natom    10.011969530    7.147831444    1.138367692   O   -0.268084950    0.000000000    0.031903865   -0.017360031   -0.048087715\natom    11.217428195    5.579743640    1.382070649   H    0.098718200    0.000000000   -0.016376190    0.031900049   -0.001302878\natom    10.623543729    7.870842837   -0.679143273   H    0.098891220    0.000000000   -0.007531025   -0.020993194    0.044532202\natom     6.933814206   11.473883030    9.595456719   O   -0.241122680    0.000000000   -0.032274345    0.007556561    0.028589313\natom     5.418459230   12.248465069   10.718861553   H    0.113480820    0.000000000    0.030225503   -0.024059407   -0.038121028\natom     6.210708326   10.792666726    8.038197049   H    0.120956070    0.000000000   -0.002256347    0.002910467    0.006395998\natom     4.475508195   10.014764436    4.589674154   O   -0.212648850    0.000000000   -0.005810155    0.033746537    0.030551251\natom     3.020095356   11.175706805    4.948741158   H    0.144660760    0.000000000    0.007883643   -0.020866638   -0.013752232\natom     4.165759283    9.011098366    3.129378261   H    0.143832960    0.000000000   -0.010141226   -0.013952791   -0.014587652\natom    13.398157894   13.398773945   14.086271701   O   -0.218599430    0.000000000    0.007131722   -0.029858862    0.015231412\natom    13.735940904   11.982187434   15.384710598   H    0.151347450    0.000000000   -0.008535887    0.029667214   -0.041657848\natom    12.971302608   12.717421581   12.342530004   H    0.117807410    0.000000000   -0.003346494    0.003600482    0.027404308\natom    -0.029853905    6.883301806    7.971228908   O   -0.223990930    0.000000000    0.024264161   -0.006314132   -0.021693996\natom     0.977655869    7.473268868    6.440535019   H    0.133521400    0.000000000   -0.025902051   -0.005351332    0.030962871\natom     1.060898338    5.576689841    8.725726931   H    0.114826910    0.000000000   -0.001307442    0.000374352   -0.007600117\natom     3.181506377   14.173805740   11.779022898   O   -0.232149600    0.000000000   -0.012334071   -0.008570649   -0.022345041\natom     4.514030277   14.870986456   12.792615703   H    0.125547620    0.000000000   -0.004584722    0.015890876    0.020256429\natom     1.399554402   14.377221610   12.428251795   H    0.122711800    0.000000000    0.025412017   -0.004414577    0.010547137\natom    11.530616410    8.776902624   11.168391672   O   -0.228946230    0.000000000   -0.036161915    0.015805311    0.029203899\natom     9.749297494    8.859990136   10.577149045   H    0.128448790    0.000000000    0.020958541   -0.001422328   -0.005878341\natom    12.710696043    8.032102680    9.992569594   H    0.102458220    0.000000000    0.006405910   -0.008905758   -0.020845229\nenergy   -1225.02203483\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/nnp-checkdw/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-checkdw/H2O_RPBE-D3/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "examples/nnp-checkdw/H2O_RPBE-D3/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.2539155865352127E+00 a         1     0     1     1     1\n  2.2490365890661286E+00 a         2     0     1     1     2\n  4.9361851928374572E+00 a         3     0     1     1     3\n -2.3971991574908125E+00 a         4     0     1     1     4\n -1.8596992303156465E+00 a         5     0     1     1     5\n  3.8287764168815897E+00 a         6     0     1     1     6\n  7.4523181738636106E+00 a         7     0     1     1     7\n  6.0971861116881998E+00 a         8     0     1     1     8\n -8.7239359226117639E+00 a         9     0     1     1     9\n -1.8255232070184267E+01 a        10     0     1     1    10\n -7.8065643887610179E+00 a        11     0     1     1    11\n  1.4247237398130265E+01 a        12     0     1     1    12\n -3.2217879518334338E+00 a        13     0     1     1    13\n -5.7395252086520712E+00 a        14     0     1     1    14\n  2.0353040522911576E+00 a        15     0     1     1    15\n  7.7520578160630560E+00 a        16     0     1     1    16\n  2.9357257867412252E+00 a        17     0     1     1    17\n -2.9719860930100790E+00 a        18     0     1     1    18\n  8.9245382590288980E+00 a        19     0     1     1    19\n  6.6848134049442169E+00 a        20     0     1     1    20\n -2.2992719903495891E+00 a        21     0     1     1    21\n -1.4401533482181721E+01 a        22     0     1     1    22\n -2.0574070545285186E+00 a        23     0     1     1    23\n -6.3544667277888678E+00 a        24     0     1     1    24\n  3.9668360525851707E+00 a        25     0     1     1    25\n  1.0930597297534963E+01 a        26     0     2     1     1\n  3.0058866618169424E+00 a        27     0     2     1     2\n -4.9950943102999927E+00 a        28     0     2     1     3\n -1.9930957240687266E+00 a        29     0     2     1     4\n  1.6790893133342006E+00 a        30     0     2     1     5\n -4.5254006136507128E+00 a        31     0     2     1     6\n -9.6165021729265252E+00 a        32     0     2     1     7\n -8.7465722730176285E+00 a        33     0     2     1     8\n  1.5506950040431201E+01 a        34     0     2     1     9\n  2.1903342918227118E+01 a        35     0     2     1    10\n -1.0685216745153280E+01 a        36     0     2     1    11\n -2.5859690636594280E+01 a        37     0     2     1    12\n -3.2423603491405122E+00 a        38     0     2     1    13\n  5.3753900550878555E+00 a        39     0     2     1    14\n -3.0291935617567991E+00 a        40     0     2     1    15\n -1.3534893178408465E+01 a        41     0     2     1    16\n -5.7625138055631471E+00 a        42     0     2     1    17\n  1.0216765318459601E+01 a        43     0     2     1    18\n -1.4416012930050949E+01 a        44     0     2     1    19\n -4.7226757471872144E-01 a        45     0     2     1    20\n  7.8981385188798026E+00 a        46     0     2     1    21\n  1.2202710023744410E+00 a        47     0     2     1    22\n  8.0560891210932120E+00 a        48     0     2     1    23\n  4.5972445013263297E-01 a        49     0     2     1    24\n  1.3374237019728858E+01 a        50     0     2     1    25\n -1.0644910441621166E+01 a        51     0     3     1     1\n -5.6098794516515920E+00 a        52     0     3     1     2\n -1.0236653403367724E+01 a        53     0     3     1     3\n  1.3552139405799508E+00 a        54     0     3     1     4\n  1.3201025058567883E+00 a        55     0     3     1     5\n  1.6531266759009673E+00 a        56     0     3     1     6\n -1.0303768926395865E+01 a        57     0     3     1     7\n  1.9927521303470008E-01 a        58     0     3     1     8\n  8.1216226663758366E+00 a        59     0     3     1     9\n  2.1349555016157687E+01 a        60     0     3     1    10\n  1.0105416692705148E+01 a        61     0     3     1    11\n -1.1444993918278378E+01 a        62     0     3     1    12\n  2.9861675555209538E-01 a        63     0     3     1    13\n  9.3552992513120543E+00 a        64     0     3     1    14\n -2.2844869025933630E+00 a        65     0     3     1    15\n -3.8047300595857316E+00 a        66     0     3     1    16\n -3.0512161452147448E+00 a        67     0     3     1    17\n  2.7887340590896472E+00 a        68     0     3     1    18\n -1.5988439945122812E+01 a        69     0     3     1    19\n -1.6917164763280326E+01 a        70     0     3     1    20\n  3.2170907488709326E+00 a        71     0     3     1    21\n  2.1641888770160929E+01 a        72     0     3     1    22\n  3.2604671723420497E+00 a        73     0     3     1    23\n  1.5230689068493776E+01 a        74     0     3     1    24\n -1.4713830039823366E+01 a        75     0     3     1    25\n -2.3544214523969775E+00 a        76     0     4     1     1\n -5.8299691629399382E+00 a        77     0     4     1     2\n  1.7168784391956539E+01 a        78     0     4     1     3\n  1.0050003860864617E+01 a        79     0     4     1     4\n  3.5168903759752812E+00 a        80     0     4     1     5\n -4.4828111046589010E+00 a        81     0     4     1     6\n  1.8299193380051442E+01 a        82     0     4     1     7\n  6.9717289110204188E+00 a        83     0     4     1     8\n -2.0364082994445859E+01 a        84     0     4     1     9\n -3.5062338388300589E+01 a        85     0     4     1    10\n  1.8010375764887119E+01 a        86     0     4     1    11\n  4.2133659287179640E+01 a        87     0     4     1    12\n  1.1988736553417061E+01 a        88     0     4     1    13\n -1.2351529706885179E+01 a        89     0     4     1    14\n  5.4139212296285057E+00 a        90     0     4     1    15\n  1.6705967069968899E+01 a        91     0     4     1    16\n  8.3219076874511639E+00 a        92     0     4     1    17\n -1.8555777504879448E+01 a        93     0     4     1    18\n  3.1433889377775369E+01 a        94     0     4     1    19\n  6.7043459658252780E-01 a        95     0     4     1    20\n -1.3837570456349678E+01 a        96     0     4     1    21\n  5.0298368971353791E-01 a        97     0     4     1    22\n -2.2656240789613065E+01 a        98     0     4     1    23\n -2.4243684644962626E+00 a        99     0     4     1    24\n -2.8280330035212309E+01 a       100     0     4     1    25\n  4.2306100814115322E+00 a       101     0     5     1     1\n  9.9770374716830084E+00 a       102     0     5     1     2\n  2.0487048112933808E+00 a       103     0     5     1     3\n -1.3702212470739978E+00 a       104     0     5     1     4\n  2.8131124422603837E+00 a       105     0     5     1     5\n  3.2845640151619522E-03 a       106     0     5     1     6\n  2.4065616021196026E+00 a       107     0     5     1     7\n -1.0461000723401572E+01 a       108     0     5     1     8\n -1.0180720750329515E+01 a       109     0     5     1     9\n -8.8668996772076660E+00 a       110     0     5     1    10\n  6.5256092481271502E+00 a       111     0     5     1    11\n -6.9831054240027211E+00 a       112     0     5     1    12\n  4.0892074148312876E+00 a       113     0     5     1    13\n -5.1951354450201128E+00 a       114     0     5     1    14\n  1.6657989141753051E+00 a       115     0     5     1    15\n -7.3542511663155619E+00 a       116     0     5     1    16\n  5.1573102842565115E+00 a       117     0     5     1    17\n  3.4929930175122172E+00 a       118     0     5     1    18\n  2.5382184218789963E+00 a       119     0     5     1    19\n  2.0045179007481050E+01 a       120     0     5     1    20\n -1.6165269676512768E+00 a       121     0     5     1    21\n  2.4869117790922393E+00 a       122     0     5     1    22\n  6.0131560843540068E+00 a       123     0     5     1    23\n -1.2231651850388728E+01 a       124     0     5     1    24\n  3.5372450187997345E+01 a       125     0     5     1    25\n -1.0433252604911765E+01 a       126     0     6     1     1\n -2.3715834640656657E+00 a       127     0     6     1     2\n -1.8239608965373137E+01 a       128     0     6     1     3\n -3.6510816169583777E+00 a       129     0     6     1     4\n -1.7632327653119535E+01 a       130     0     6     1     5\n  1.0040509177650593E+01 a       131     0     6     1     6\n -1.5407385349225459E+01 a       132     0     6     1     7\n -7.0553605774310779E-01 a       133     0     6     1     8\n  1.3204892207903583E+01 a       134     0     6     1     9\n  2.9596389655595953E+01 a       135     0     6     1    10\n -2.0620173259628203E+01 a       136     0     6     1    11\n -3.0803380363815094E+01 a       137     0     6     1    12\n -1.4917676387082279E+01 a       138     0     6     1    13\n  9.6935054799166185E+00 a       139     0     6     1    14\n  4.6937319413252743E+00 a       140     0     6     1    15\n -5.0263591258131060E+00 a       141     0     6     1    16\n -9.7243575590712439E+00 a       142     0     6     1    17\n  1.5625340951727363E+01 a       143     0     6     1    18\n -2.8266776356585389E+01 a       144     0     6     1    19\n  2.5386057418612946E+00 a       145     0     6     1    20\n  1.6302330128073283E+01 a       146     0     6     1    21\n -8.5166226512297030E+00 a       147     0     6     1    22\n  2.5040570504752605E+01 a       148     0     6     1    23\n -8.5008658358878897E-01 a       149     0     6     1    24\n  2.0458930574550632E+01 a       150     0     6     1    25\n  7.8529627796707677E+00 a       151     0     7     1     1\n -4.5279242985866821E+00 a       152     0     7     1     2\n  4.7942839133231594E+00 a       153     0     7     1     3\n -6.2431002330064649E+00 a       154     0     7     1     4\n  4.3358077462982054E+00 a       155     0     7     1     5\n -6.8037589596444281E+00 a       156     0     7     1     6\n  1.8980667946224101E+00 a       157     0     7     1     7\n  1.9802532239433695E+01 a       158     0     7     1     8\n  8.4826746941006572E+00 a       159     0     7     1     9\n  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-4.6552795168897604E-01 a      1221     1    21     2    21\n  1.1611386377657384E+00 a      1222     1    21     2    22\n -1.2972265245341139E+00 a      1223     1    21     2    23\n  1.8117173751313085E+00 a      1224     1    21     2    24\n  1.0433495561237927E+00 a      1225     1    21     2    25\n  1.5410314634266913E+00 a      1226     1    22     2     1\n  6.6201420998527072E-01 a      1227     1    22     2     2\n  1.1189293597068475E+00 a      1228     1    22     2     3\n -1.1536147566508355E+00 a      1229     1    22     2     4\n -8.4859080711662893E-01 a      1230     1    22     2     5\n  3.7903158089014494E-01 a      1231     1    22     2     6\n -2.6461659405296234E+00 a      1232     1    22     2     7\n  2.2472472042954434E+00 a      1233     1    22     2     8\n -9.2281733258289744E-01 a      1234     1    22     2     9\n  8.7312141982063785E-01 a      1235     1    22     2    10\n -4.3593190134289528E-01 a      1236     1    22     2    11\n  5.1912574126564559E-01 a      1237     1    22     2    12\n -5.9029854481930821E-01 a      1238     1    22     2    13\n -7.2255183403800793E-01 a      1239     1    22     2    14\n  4.1024670935059383E-02 a      1240     1    22     2    15\n  2.0425371936604741E-01 a      1241     1    22     2    16\n -1.0394832812330597E+00 a      1242     1    22     2    17\n  4.7202219372950349E-01 a      1243     1    22     2    18\n -1.9958648332222221E-03 a      1244     1    22     2    19\n -1.4664186611455649E-02 a      1245     1    22     2    20\n  1.0689476163444707E+00 a      1246     1    22     2    21\n  8.4484833020425232E-01 a      1247     1    22     2    22\n -1.4147373614558330E+00 a      1248     1    22     2    23\n  1.9187324467269602E+00 a      1249     1    22     2    24\n  1.5330124676330812E+00 a      1250     1    22     2    25\n  2.3019050197742894E+00 a      1251     1    23     2     1\n -1.3828322911066271E-01 a      1252     1    23     2     2\n -2.3555430378419923E-01 a      1253     1    23     2     3\n -1.3434989779696097E-01 a      1254     1    23     2     4\n  3.7852663531566189E-01 a      1255     1    23     2     5\n  9.8266847359694973E-02 a      1256     1    23     2     6\n  3.2721968443206462E-01 a      1257     1    23     2     7\n -3.7061171550241617E-01 a      1258     1    23     2     8\n  2.2862436245090851E+00 a      1259     1    23     2     9\n  1.7674065728047832E+00 a      1260     1    23     2    10\n -5.2627257197444939E-02 a      1261     1    23     2    11\n  9.4094481148145870E-01 a      1262     1    23     2    12\n  1.0616552648143298E+00 a      1263     1    23     2    13\n -1.6065739188681796E-01 a      1264     1    23     2    14\n  1.6833160475834315E+00 a      1265     1    23     2    15\n -5.5679530352182072E-01 a      1266     1    23     2    16\n  4.2170082515325280E-01 a      1267     1    23     2    17\n  1.8142946234467967E+00 a      1268     1    23     2    18\n -6.0004075552166369E-01 a      1269     1    23     2    19\n  8.6767695096505049E-01 a      1270     1    23     2    20\n  1.7471709925670367E-01 a      1271     1    23     2    21\n  6.3494817986861019E-01 a      1272     1    23     2    22\n  7.9839233743975266E-02 a      1273     1    23     2    23\n -8.7497499907984810E-01 a      1274     1    23     2    24\n -2.1279336414401262E-01 a      1275     1    23     2    25\n -1.0628518357816100E+01 a      1276     1    24     2     1\n -3.4149879843865938E-01 a      1277     1    24     2     2\n -4.0534872173827868E-01 a      1278     1    24     2     3\n  1.0980204380257913E-01 a      1279     1    24     2     4\n  1.8376924276804879E-01 a      1280     1    24     2     5\n  8.5047887536146360E-01 a      1281     1    24     2     6\n  4.3913590571042438E-01 a      1282     1    24     2     7\n  2.7167430357232609E+00 a      1283     1    24     2     8\n  2.9682659556600960E-01 a      1284     1    24     2     9\n -1.6032245851281013E+00 a      1285     1    24     2    10\n -6.7567048640865046E-01 a      1286     1    24     2    11\n -1.5253382251900995E+00 a      1287     1    24     2    12\n -6.7540631566041298E-01 a      1288     1    24     2    13\n -1.4565321192168545E+00 a      1289     1    24     2    14\n -1.3315414628143039E+00 a      1290     1    24     2    15\n  1.2552098425264056E+00 a      1291     1    24     2    16\n -1.1701558601459501E+00 a      1292     1    24     2    17\n  2.1967564647703792E+00 a      1293     1    24     2    18\n  3.6767594091430167E-01 a      1294     1    24     2    19\n  1.4791781996464841E+00 a      1295     1    24     2    20\n -2.4597335939693896E+00 a      1296     1    24     2    21\n  1.8222789722776007E+00 a      1297     1    24     2    22\n -2.4818384588216302E+00 a      1298     1    24     2    23\n -1.3359962912345340E+00 a      1299     1    24     2    24\n -1.6060924344568878E-02 a      1300     1    24     2    25\n -1.1558703878945702E+00 a      1301     1    25     2     1\n  5.5859771317693908E-02 a      1302     1    25     2     2\n -1.9275021348316721E+00 a      1303     1    25     2     3\n  4.2881321046205173E-01 a      1304     1    25     2     4\n  6.6308764508018558E-01 a      1305     1    25     2     5\n -2.5357661809360188E-01 a      1306     1    25     2     6\n  7.7965409617466697E-01 a      1307     1    25     2     7\n -1.9470416731652336E+00 a      1308     1    25     2     8\n  2.0923659915641873E-01 a      1309     1    25     2     9\n  8.9211452410465542E-01 a      1310     1    25     2    10\n -1.9807939822570442E-01 a      1311     1    25     2    11\n -5.0922943173038127E-01 a      1312     1    25     2    12\n  1.3378430979044107E+00 a      1313     1    25     2    13\n -6.8964614083753073E-01 a      1314     1    25     2    14\n  7.6939619343191556E-01 a      1315     1    25     2    15\n -1.5783243312480257E+00 a      1316     1    25     2    16\n  2.3586020281744577E+00 a      1317     1    25     2    17\n -5.1641666185758928E-01 a      1318     1    25     2    18\n  1.0291540870545792E+00 a      1319     1    25     2    19\n  1.5269830348487650E+00 a      1320     1    25     2    20\n -2.8987700591417855E+00 a      1321     1    25     2    21\n  9.0207337792476916E-01 a      1322     1    25     2    22\n  1.9890049402284911E+00 a      1323     1    25     2    23\n  3.9387622927433424E-01 a      1324     1    25     2    24\n  9.9397126232482103E-01 a      1325     1    25     2    25\n  2.5306467041996967E+00 b      1326     2     1\n  3.1633393474977245E+00 b      1327     2     2\n -1.1644295509710691E+00 b      1328     2     3\n -5.7686722641223600E+00 b      1329     2     4\n  2.0065022303893989E+00 b      1330     2     5\n -5.9106057000795840E+00 b      1331     2     6\n -1.1326093285804056E+01 b      1332     2     7\n -3.9025063397327071E+00 b      1333     2     8\n  4.4520505166676267E+00 b      1334     2     9\n -1.7352681951318241E+00 b      1335     2    10\n -2.1518912430432668E+00 b      1336     2    11\n  5.0463376560082969E+00 b      1337     2    12\n -2.2614514173852837E-01 b      1338     2    13\n -4.1454590614747211E+00 b      1339     2    14\n  1.6688417293495756E+00 b      1340     2    15\n -5.8649976938793378E+00 b      1341     2    16\n -3.8350084459541849E+00 b      1342     2    17\n  1.3730477223722950E+00 b      1343     2    18\n  1.8506935712854127E+00 b      1344     2    19\n  5.7362757779153428E+00 b      1345     2    20\n  7.2901484895568780E+00 b      1346     2    21\n  3.9773783666446022E-01 b      1347     2    22\n -6.1298011242151409E+00 b      1348     2    23\n  9.9698755072742991E+00 b      1349     2    24\n  1.1801564149295556E+00 b      1350     2    25\n  1.2704098997067026E+01 a      1351     2     1     3     1\n  1.5947733940307620E+00 a      1352     2     2     3     1\n -1.6022927057878529E+00 a      1353     2     3     3     1\n -1.5507258540777733E+00 a      1354     2     4     3     1\n  1.8696884022727636E+00 a      1355     2     5     3     1\n -8.2051908880071633E-01 a      1356     2     6     3     1\n  9.4325719092522542E-01 a      1357     2     7     3     1\n  2.4098435369626174E+00 a      1358     2     8     3     1\n  1.4100759633042474E+00 a      1359     2     9     3     1\n -1.4613034838529613E+00 a      1360     2    10     3     1\n  1.0296574685193380E+00 a      1361     2    11     3     1\n  1.2413851904356363E+00 a      1362     2    12     3     1\n -6.3168181712211169E-01 a      1363     2    13     3     1\n  7.6424175125347729E+00 a      1364     2    14     3     1\n -1.3477038299214714E+00 a      1365     2    15     3     1\n -1.6064659765754943E+00 a      1366     2    16     3     1\n -8.9624380518145874E-01 a      1367     2    17     3     1\n -1.0509865792522375E+00 a      1368     2    18     3     1\n  8.1847872933853638E-01 a      1369     2    19     3     1\n  1.2845504810303034E+00 a      1370     2    20     3     1\n -5.1879822944368881E-01 a      1371     2    21     3     1\n -7.2018714033119180E-01 a      1372     2    22     3     1\n  5.9870832883780798E+00 a      1373     2    23     3     1\n -6.0589155387470683E-01 a      1374     2    24     3     1\n  5.0177609140285355E+00 a      1375     2    25     3     1\n  9.7386086372975722E+00 b      1376     3     1\n"
  },
  {
    "path": "examples/nnp-checkdw/H2O_RPBE-D3/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -4.2252995889643252E-01 a         1     0     1     1     1\n -6.0555645962054347E+00 a         2     0     1     1     2\n  1.4040722027928377E+01 a         3     0     1     1     3\n -2.7041370011942618E+00 a         4     0     1     1     4\n -3.8202743208058858E+00 a         5     0     1     1     5\n -3.3612643261393358E+00 a         6     0     1     1     6\n -2.0418101025905258E+00 a         7     0     1     1     7\n  7.5707237340996727E+00 a         8     0     1     1     8\n -5.8098755815926548E+00 a         9     0     1     1     9\n -6.0966886893925210E-01 a        10     0     1     1    10\n  5.8061564015115206E+00 a        11     0     1     1    11\n -1.5509339733099867E+00 a        12     0     1     1    12\n  1.9747395485200818E+00 a        13     0     1     1    13\n  4.5260782279680539E-01 a        14     0     1     1    14\n  9.9210415760283279E+00 a        15     0     1     1    15\n -6.5078831481547121E+00 a        16     0     1     1    16\n -3.4768832871318085E+00 a        17     0     1     1    17\n -1.9463994340943838E+00 a        18     0     1     1    18\n -3.4186058699290269E+00 a        19     0     1     1    19\n  1.2263643166698479E+00 a        20     0     1     1    20\n -5.9171161834436594E+00 a        21     0     1     1    21\n  1.8436267358458363E+00 a        22     0     1     1    22\n -2.3139530616378448E+00 a        23     0     1     1    23\n -1.7228542411478951E+01 a        24     0     1     1    24\n  2.2888610253215895E+00 a        25     0     1     1    25\n  8.0819405565169262E+00 a        26     0     2     1     1\n  8.0066409422078735E+00 a        27     0     2     1     2\n -2.8439251469462398E+01 a        28     0     2     1     3\n -1.1146087290797917E+01 a        29     0     2     1     4\n -7.5292172093563314E+00 a        30     0     2     1     5\n -4.0783685663337641E+00 a        31     0     2     1     6\n -4.4130406528599337E+00 a        32     0     2     1     7\n  1.0563249167508673E+01 a        33     0     2     1     8\n  1.0933105521974941E+01 a        34     0     2     1     9\n -1.1646509907117448E+01 a        35     0     2     1    10\n -7.5007478428041727E+00 a        36     0     2     1    11\n  7.7790182254249176E+00 a        37     0     2     1    12\n  1.1567034492555623E+01 a        38     0     2     1    13\n -4.2051741520233508E+00 a        39     0     2     1    14\n  3.1165306119132130E+00 a        40     0     2     1    15\n  1.6385645103485370E+01 a        41     0     2     1    16\n  2.6440539124381655E+00 a        42     0     2     1    17\n -3.9524518111687827E+00 a        43     0     2     1    18\n -8.7912410635652076E+00 a        44     0     2     1    19\n  4.3903318583813933E+00 a        45     0     2     1    20\n  3.3748047065442632E-01 a        46     0     2     1    21\n -6.6858946327311741E-01 a        47     0     2     1    22\n  5.4447187026310928E+00 a        48     0     2     1    23\n  1.9966018946508100E+01 a        49     0     2     1    24\n -1.7414420670154115E+01 a        50     0     2     1    25\n -3.9418657694849879E-01 a        51     0     3     1     1\n  9.1804829174186846E+00 a        52     0     3     1     2\n -1.0485089041850278E+01 a        53     0     3     1     3\n  8.9380499555048889E+00 a        54     0     3     1     4\n  1.0758607876097068E+01 a        55     0     3     1     5\n  7.2881492125393788E+00 a        56     0     3     1     6\n  8.2627077997774609E+00 a        57     0     3     1     7\n -1.2523613158520124E+01 a        58     0     3     1     8\n  4.5963999046141870E+00 a        59     0     3     1     9\n  8.2776469521184293E+00 a        60     0     3     1    10\n -2.1354371687617113E+00 a        61     0     3     1    11\n -9.0381751821938234E+00 a        62     0     3     1    12\n -1.2209592338152297E+00 a        63     0     3     1    13\n  4.7653671372245672E+00 a        64     0     3     1    14\n -1.7909124818088952E+01 a        65     0     3     1    15\n  3.2182917515973237E+00 a        66     0     3     1    16\n -2.3712750109800793E+00 a        67     0     3     1    17\n  4.6394007836500366E+00 a        68     0     3     1    18\n  2.3761984937954490E+00 a        69     0     3     1    19\n -1.0484832585147684E+01 a        70     0     3     1    20\n  1.2317970755621140E+01 a        71     0     3     1    21\n -1.5014054499447769E+00 a        72     0     3     1    22\n -1.1215435083480425E+00 a        73     0     3     1    23\n  8.9428653321614355E+00 a        74     0     3     1    24\n  1.2636165742848842E+00 a        75     0     3     1    25\n -1.3406492086741725E+01 a        76     0     4     1     1\n -1.0241053204283523E+01 a        77     0     4     1     2\n  4.3016369326050899E+01 a        78     0     4     1     3\n  2.0170433813810671E+01 a        79     0     4     1     4\n  1.3209328101408278E+01 a        80     0     4     1     5\n  1.2456789467161695E+01 a        81     0     4     1     6\n  4.3498515722861573E+00 a        82     0     4     1     7\n -2.1948185511490657E+01 a        83     0     4     1     8\n -1.5329558038416376E+01 a        84     0     4     1     9\n  1.4173337432869845E+01 a        85     0     4     1    10\n  5.6040631650516088E+00 a        86     0     4     1    11\n -9.7646834958548663E+00 a        87     0     4     1    12\n -1.3810669587629080E+01 a        88     0     4     1    13\n -1.5274915717855073E+00 a        89     0     4     1    14\n -1.3662043326477198E+01 a        90     0     4     1    15\n -2.5095635769057225E+01 a        91     0     4     1    16\n  5.4033548590960638E+00 a        92     0     4     1    17\n  1.1047593171711565E+01 a        93     0     4     1    18\n  1.9404912122904062E+01 a        94     0     4     1    19\n  2.4043652449872512E+00 a        95     0     4     1    20\n -3.3818087825635010E+00 a        96     0     4     1    21\n -4.9505657938825802E+00 a        97     0     4     1    22\n  6.2159614529590854E+00 a        98     0     4     1    23\n -1.9315299866781363E+01 a        99     0     4     1    24\n  2.4149549923763363E+01 a       100     0     4     1    25\n  2.2633190213689671E+00 a       101     0     5     1     1\n -1.1275056403465689E+01 a       102     0     5     1     2\n  1.2588751117785917E+00 a       103     0     5     1     3\n -1.7399288116611554E+01 a       104     0     5     1     4\n -1.8915392010979964E+01 a       105     0     5     1     5\n -6.5088880348621911E+00 a       106     0     5     1     6\n -8.7022768117985532E+00 a       107     0     5     1     7\n  9.5716939158219958E+00 a       108     0     5     1     8\n  6.7173652175539926E+00 a       109     0     5     1     9\n -1.0675975211687946E+01 a       110     0     5     1    10\n -9.8676303718126039E+00 a       111     0     5     1    11\n  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1.5566506128138184E+00 a      1237     1    19     2    12\n -9.4986537106149321E-02 a      1238     1    19     2    13\n -2.3530503270088396E-01 a      1239     1    19     2    14\n  3.6439425212581661E-01 a      1240     1    19     2    15\n  1.2871636736138770E+00 a      1241     1    19     2    16\n -8.4712787652121069E-01 a      1242     1    19     2    17\n -1.0234220464653516E+00 a      1243     1    19     2    18\n -1.3802013894870373E+00 a      1244     1    19     2    19\n  4.6238544527464259E-01 a      1245     1    19     2    20\n -3.1736140472371468E+00 a      1246     1    19     2    21\n  1.7897235482645921E+00 a      1247     1    19     2    22\n -1.2075712900497950E+00 a      1248     1    19     2    23\n -3.1032297572767770E-01 a      1249     1    19     2    24\n  2.1706205401676661E+00 a      1250     1    19     2    25\n  6.9973782486580109E+00 a      1251     1    20     2     1\n  2.9325190821916197E-01 a      1252     1    20     2     2\n -1.2648655109330131E+00 a      1253     1    20     2     3\n -4.3905910522706337E-01 a      1254     1    20     2     4\n  4.2887555555714030E-01 a      1255     1    20     2     5\n  1.3300944280643934E+00 a      1256     1    20     2     6\n  1.0988390404457922E+00 a      1257     1    20     2     7\n  2.3801051936039075E+00 a      1258     1    20     2     8\n  1.1789379212300943E-01 a      1259     1    20     2     9\n  3.9144297908957699E+00 a      1260     1    20     2    10\n  5.5000952527940228E-01 a      1261     1    20     2    11\n  2.4087943927489916E-01 a      1262     1    20     2    12\n -3.7997171313505251E-01 a      1263     1    20     2    13\n -5.4744714104500347E-01 a      1264     1    20     2    14\n  8.9095280999944937E-01 a      1265     1    20     2    15\n -8.7130940035564164E-01 a      1266     1    20     2    16\n  3.7900358553306007E-01 a      1267     1    20     2    17\n  2.1342515402584987E+00 a      1268     1    20     2    18\n  1.2475880574414706E+00 a      1269     1    20     2    19\n  7.8956439485340524E-01 a      1270     1    20     2    20\n  4.6968348528891219E+00 a      1271     1    20     2    21\n  2.4464240930319816E+00 a      1272     1    20     2    22\n -5.7785142905302376E+00 a      1273     1    20     2    23\n -2.3074149497856417E-01 a      1274     1    20     2    24\n -2.6800082940155296E+00 a      1275     1    20     2    25\n -3.2729577955630704E+00 a      1276     1    21     2     1\n -1.2928637501931926E+00 a      1277     1    21     2     2\n -2.2664219916515152E-01 a      1278     1    21     2     3\n  6.8197406796553048E-02 a      1279     1    21     2     4\n  2.2800043902454539E-01 a      1280     1    21     2     5\n -1.4547709606717896E+00 a      1281     1    21     2     6\n -8.9797316703694119E-02 a      1282     1    21     2     7\n -7.9615421262219899E-01 a      1283     1    21     2     8\n -2.5074736863647562E-01 a      1284     1    21     2     9\n -3.2383137185187805E-01 a      1285     1    21     2    10\n -7.7486670060442631E-01 a      1286     1    21     2    11\n -1.7378145875987788E-01 a      1287     1    21     2    12\n  1.7001762592878558E+00 a      1288     1    21     2    13\n -1.7033999809142997E+00 a      1289     1    21     2    14\n  3.7961258225336264E-01 a      1290     1    21     2    15\n  6.0929689839357426E-01 a      1291     1    21     2    16\n -1.9171250145280534E+00 a      1292     1    21     2    17\n -1.6594854242769004E+00 a      1293     1    21     2    18\n -2.8219229087100910E+00 a      1294     1    21     2    19\n -4.3902463688638738E-01 a      1295     1    21     2    20\n -1.1744026035352828E+00 a      1296     1    21     2    21\n  3.9648025457334164E+00 a      1297     1    21     2    22\n -1.3587513635268793E+00 a      1298     1    21     2    23\n  3.9463311556495906E-02 a      1299     1    21     2    24\n -4.6280624473662763E-01 a      1300     1    21     2    25\n  8.3725910272757709E+00 a      1301     1    22     2     1\n  1.2030400911595496E+00 a      1302     1    22     2     2\n  5.2723639396495003E-01 a      1303     1    22     2     3\n  2.4863416823271995E+00 a      1304     1    22     2     4\n  5.0656775645932173E-01 a      1305     1    22     2     5\n  7.8889662692367113E-01 a      1306     1    22     2     6\n  2.7467021112668549E-01 a      1307     1    22     2     7\n  3.5551997281423904E+00 a      1308     1    22     2     8\n -6.9074567194666425E-01 a      1309     1    22     2     9\n  9.2831069742658789E-01 a      1310     1    22     2    10\n -2.7305664188353734E-01 a      1311     1    22     2    11\n -1.6732686793215996E+00 a      1312     1    22     2    12\n -1.2508123463191103E+00 a      1313     1    22     2    13\n  1.4253551144285490E+00 a      1314     1    22     2    14\n -1.2730453204508483E+00 a      1315     1    22     2    15\n -5.6234386233504563E-01 a      1316     1    22     2    16\n  4.7348930208036427E-01 a      1317     1    22     2    17\n  1.4228359329011722E+00 a      1318     1    22     2    18\n -3.0896237212805277E-02 a      1319     1    22     2    19\n -7.7625773033108136E-01 a      1320     1    22     2    20\n  5.1571228251110171E-02 a      1321     1    22     2    21\n -1.5781774955827834E+00 a      1322     1    22     2    22\n -1.7313703986673430E+00 a      1323     1    22     2    23\n -1.3316987118953665E+00 a      1324     1    22     2    24\n -7.0760527312605037E-01 a      1325     1    22     2    25\n -8.1466385165616928E-01 a      1326     1    23     2     1\n  6.8912340727205368E-01 a      1327     1    23     2     2\n  8.4582890184800619E-01 a      1328     1    23     2     3\n  3.8163700575566650E-01 a      1329     1    23     2     4\n -6.6556600373886232E-01 a      1330     1    23     2     5\n -1.3399458536680564E+00 a      1331     1    23     2     6\n -1.7425009694107033E-01 a      1332     1    23     2     7\n -2.6104662248332646E+00 a      1333     1    23     2     8\n -1.9788280313555501E-01 a      1334     1    23     2     9\n -4.6341960827595043E+00 a      1335     1    23     2    10\n -4.1560774205921192E-01 a      1336     1    23     2    11\n -1.3453315295733928E-01 a      1337     1    23     2    12\n  5.9251987079212687E-01 a      1338     1    23     2    13\n  1.3014540212114664E-01 a      1339     1    23     2    14\n  2.4962768316839337E-01 a      1340     1    23     2    15\n  3.3868458734074913E-01 a      1341     1    23     2    16\n -2.1103970517135956E-01 a      1342     1    23     2    17\n -2.7311756320323316E-01 a      1343     1    23     2    18\n  7.7825779463422798E-02 a      1344     1    23     2    19\n -1.5510879185574573E+00 a      1345     1    23     2    20\n -3.3731285186903501E+00 a      1346     1    23     2    21\n  1.5012690395440691E+00 a      1347     1    23     2    22\n -1.4938786629136067E+00 a      1348     1    23     2    23\n  1.5155834326942672E-01 a      1349     1    23     2    24\n  2.2135367884980521E+00 a      1350     1    23     2    25\n  7.6092107307961931E-01 a      1351     1    24     2     1\n  2.5019321183393825E-02 a      1352     1    24     2     2\n  2.4714648764760871E-01 a      1353     1    24     2     3\n -4.2700090187223255E-01 a      1354     1    24     2     4\n  1.9684439924637190E-01 a      1355     1    24     2     5\n -1.6150658390090172E-01 a      1356     1    24     2     6\n -8.4941771549071021E-01 a      1357     1    24     2     7\n  3.2616941337700417E-01 a      1358     1    24     2     8\n -6.0235251095177200E-01 a      1359     1    24     2     9\n  2.0073315297316108E+00 a      1360     1    24     2    10\n  6.8678637919958119E-01 a      1361     1    24     2    11\n -1.4709309602563259E+00 a      1362     1    24     2    12\n -7.3119546383323997E-01 a      1363     1    24     2    13\n  5.9624465461749732E-01 a      1364     1    24     2    14\n  1.1965703107989687E+00 a      1365     1    24     2    15\n -4.8078015734066326E-01 a      1366     1    24     2    16\n  2.8731897539798784E-01 a      1367     1    24     2    17\n  2.8943049077679879E+00 a      1368     1    24     2    18\n  4.4309374097560666E-01 a      1369     1    24     2    19\n -5.2571668466848664E-01 a      1370     1    24     2    20\n  2.6293009755349539E+00 a      1371     1    24     2    21\n  1.1166360248787797E+00 a      1372     1    24     2    22\n  1.4367909042068954E+00 a      1373     1    24     2    23\n  1.2263949730702137E+00 a      1374     1    24     2    24\n -1.5658327417588482E+00 a      1375     1    24     2    25\n -3.0524380712257440E+00 a      1376     1    25     2     1\n -1.6248402538917406E-01 a      1377     1    25     2     2\n  5.3725239557723847E-01 a      1378     1    25     2     3\n -3.1435543583372311E-01 a      1379     1    25     2     4\n  8.0294309812719877E-01 a      1380     1    25     2     5\n -3.3745709161028831E-01 a      1381     1    25     2     6\n  2.9618139473335392E-01 a      1382     1    25     2     7\n -1.3606606680314999E+00 a      1383     1    25     2     8\n  2.9886863438452965E-01 a      1384     1    25     2     9\n  3.4365095196288835E+00 a      1385     1    25     2    10\n  2.8778063903425566E-01 a      1386     1    25     2    11\n -5.2312889094867954E-01 a      1387     1    25     2    12\n  4.5730896273705224E-01 a      1388     1    25     2    13\n -8.8949447500584955E-01 a      1389     1    25     2    14\n -8.1389897744929640E-01 a      1390     1    25     2    15\n -4.0077086298379117E-01 a      1391     1    25     2    16\n  7.2544627916775950E-01 a      1392     1    25     2    17\n -9.8029709488119798E-01 a      1393     1    25     2    18\n  8.5017837869712165E-01 a      1394     1    25     2    19\n -2.9795775527520296E-01 a      1395     1    25     2    20\n  1.1940911570260535E+00 a      1396     1    25     2    21\n -4.1259772504588357E-02 a      1397     1    25     2    22\n  1.0619824936744515E+00 a      1398     1    25     2    23\n -6.5325825341918264E-01 a      1399     1    25     2    24\n  3.7575240210802421E+00 a      1400     1    25     2    25\n -1.0787018434494783E+01 b      1401     2     1\n -8.4067078142086771E-01 b      1402     2     2\n  9.3201271110229211E-01 b      1403     2     3\n -1.8318272256547821E+00 b      1404     2     4\n -2.1732436845179119E+00 b      1405     2     5\n -2.6390929073478930E+00 b      1406     2     6\n  3.7489748853957300E-01 b      1407     2     7\n -2.3789675524866163E+00 b      1408     2     8\n  2.7252644932624959E+00 b      1409     2     9\n  2.5100559841854970E+00 b      1410     2    10\n -2.4897033671113025E-01 b      1411     2    11\n  2.6913296692082476E+00 b      1412     2    12\n  5.8162695990329221E+00 b      1413     2    13\n -1.5170700889568940E+00 b      1414     2    14\n  4.2121259244130220E+00 b      1415     2    15\n  2.2987725066596130E+00 b      1416     2    16\n -7.1493650128731911E-01 b      1417     2    17\n -3.9961443472349811E-01 b      1418     2    18\n  7.8083705485664430E+00 b      1419     2    19\n -4.0462773256448170E-01 b      1420     2    20\n -1.4333029489891109E+00 b      1421     2    21\n -4.9517224038431467E+00 b      1422     2    22\n  1.0702867307710989E+01 b      1423     2    23\n -9.7535853921453985E-01 b      1424     2    24\n  5.3161969295054172E+00 b      1425     2    25\n -5.1941647295982207E-01 a      1426     2     1     3     1\n -7.7346657642095373E-01 a      1427     2     2     3     1\n  1.4003893583106508E+00 a      1428     2     3     3     1\n  8.9188080044914464E-01 a      1429     2     4     3     1\n -2.0147808233792022E+00 a      1430     2     5     3     1\n -1.8131831735812174E+00 a      1431     2     6     3     1\n  3.3217884596641700E+00 a      1432     2     7     3     1\n -1.2675289031787327E+00 a      1433     2     8     3     1\n -1.2791140359120716E+00 a      1434     2     9     3     1\n  1.9731828075446340E+00 a      1435     2    10     3     1\n -2.3928332883234411E+00 a      1436     2    11     3     1\n -1.1755085043375486E+00 a      1437     2    12     3     1\n  2.6525670286472951E+00 a      1438     2    13     3     1\n -2.4861988521743901E+00 a      1439     2    14     3     1\n  1.2534500349238071E+00 a      1440     2    15     3     1\n  2.8804282010183990E+00 a      1441     2    16     3     1\n -2.0327745898215275E+00 a      1442     2    17     3     1\n -1.1760164122204946E+00 a      1443     2    18     3     1\n -9.9841804355412322E-01 a      1444     2    19     3     1\n -1.8663330516323837E+00 a      1445     2    20     3     1\n  6.3266049836286531E-01 a      1446     2    21     3     1\n  1.2025500357718348E+00 a      1447     2    22     3     1\n  1.1367820678861495E-01 a      1448     2    23     3     1\n -2.6481374255863193E+00 a      1449     2    24     3     1\n  5.2166795947347921E-01 a      1450     2    25     3     1\n  4.8693043186011655E+00 b      1451     3     1\n"
  },
  {
    "path": "examples/nnp-checkdw/LJ/input.data",
    "content": "begin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.38564065E+01  -1.38564065E+01  -1.38564065E+01\natom   5.77350269E-01   5.77350269E-01   5.77350269E-01 Ne   0.00000000E+00   0.00000000E+00   1.38564065E+01   1.38564065E+01   1.38564065E+01\nenergy   0.00000000E+00\ncomment r =   1.00000000E+00, E =   0.00000000E+00, dEdr =  -2.40000000E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.14260918E+01  -1.14260918E+01  -1.14260918E+01\natom   5.83123772E-01   5.83123772E-01   5.83123772E-01 Ne   0.00000000E+00   0.00000000E+00   1.14260918E+01   1.14260918E+01   1.14260918E+01\nenergy  -2.18384040E-01\ncomment r =   1.01000000E+00, E =  -2.18384040E-01, dEdr =  -1.97905715E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -9.36007007E+00  -9.36007007E+00  -9.36007007E+00\natom   5.88897275E-01   5.88897275E-01   5.88897275E-01 Ne   0.00000000E+00   0.00000000E+00   9.36007007E+00   9.36007007E+00   9.36007007E+00\nenergy  -3.97912826E-01\ncomment r =   1.02000000E+00, E =  -3.97912826E-01, dEdr =  -1.62121169E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -7.60455062E+00  -7.60455062E+00  -7.60455062E+00\natom   5.94670777E-01   5.94670777E-01   5.94670777E-01 Ne   0.00000000E+00   0.00000000E+00   7.60455062E+00   7.60455062E+00   7.60455062E+00\nenergy  -5.44417506E-01\ncomment r =   1.03000000E+00, E =  -5.44417506E-01, dEdr =  -1.31714680E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -6.11386720E+00  -6.11386720E+00  -6.11386720E+00\natom   6.00444280E-01   6.00444280E-01   6.00444280E-01 Ne   0.00000000E+00   0.00000000E+00   6.11386720E+00   6.11386720E+00   6.11386720E+00\nenergy  -6.62869905E-01\ncomment r =   1.04000000E+00, E =  -6.62869905E-01, dEdr =  -1.05895286E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -4.84920700E+00  -4.84920700E+00  -4.84920700E+00\natom   6.06217783E-01   6.06217783E-01   6.06217783E-01 Ne   0.00000000E+00   0.00000000E+00   4.84920700E+00   4.84920700E+00   4.84920700E+00\nenergy  -7.57511914E-01\ncomment r =   1.05000000E+00, E =  -7.57511914E-01, dEdr =  -8.39907291E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -3.77754643E+00  -3.77754643E+00  -3.77754643E+00\natom   6.11991285E-01   6.11991285E-01   6.11991285E-01 Ne   0.00000000E+00   0.00000000E+00   3.77754643E+00   3.77754643E+00   3.77754643E+00\nenergy  -8.31964707E-01\ncomment r =   1.06000000E+00, E =  -8.31964707E-01, dEdr =  -6.54290234E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -2.87075857E+00  -2.87075857E+00  -2.87075857E+00\natom   6.17764788E-01   6.17764788E-01   6.17764788E-01 Ne   0.00000000E+00   0.00000000E+00   2.87075857E+00   2.87075857E+00   2.87075857E+00\nenergy  -8.89321058E-01\ncomment r =   1.07000000E+00, E =  -8.89321058E-01, dEdr =  -4.97229969E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -2.10486372E+00  -2.10486372E+00  -2.10486372E+00\natom   6.23538291E-01   6.23538291E-01   6.23538291E-01 Ne   0.00000000E+00   0.00000000E+00   2.10486372E+00   2.10486372E+00   2.10486372E+00\nenergy  -9.32223473E-01\ncomment r =   1.08000000E+00, E =  -9.32223473E-01, dEdr =  -3.64573090E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.45939898E+00  -1.45939898E+00  -1.45939898E+00\natom   6.29311793E-01   6.29311793E-01   6.29311793E-01 Ne   0.00000000E+00   0.00000000E+00   1.45939898E+00   1.45939898E+00   1.45939898E+00\nenergy  -9.62930407E-01\ncomment r =   1.09000000E+00, E =  -9.62930407E-01, dEdr =  -2.52775317E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -9.16887301E-01  -9.16887301E-01  -9.16887301E-01\natom   6.35085296E-01   6.35085296E-01   6.35085296E-01 Ne   0.00000000E+00   0.00000000E+00   9.16887301E-01   9.16887301E-01   9.16887301E-01\nenergy  -9.83372449E-01\ncomment r =   1.10000000E+00, E =  -9.83372449E-01, dEdr =  -1.58809539E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -4.62389671E-01  -4.62389671E-01  -4.62389671E-01\natom   6.40858799E-01   6.40858799E-01   6.40858799E-01 Ne   0.00000000E+00   0.00000000E+00   4.62389671E-01   4.62389671E-01   4.62389671E-01\nenergy  -9.95200050E-01\ncomment r =   1.11000000E+00, E =  -9.95200050E-01, dEdr =  -8.00882403E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -8.31268676E-02  -8.31268676E-02  -8.31268676E-02\natom   6.46632301E-01   6.46632301E-01   6.46632301E-01 Ne   0.00000000E+00   0.00000000E+00   8.31268676E-02   8.31268676E-02   8.31268676E-02\nenergy  -9.99824113E-01\ncomment r =   1.12000000E+00, E =  -9.99824113E-01, dEdr =  -1.43979958E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.31840388E-01   2.31840388E-01   2.31840388E-01\natom   6.52405804E-01   6.52405804E-01   6.52405804E-01 Ne   0.00000000E+00   0.00000000E+00  -2.31840388E-01  -2.31840388E-01  -2.31840388E-01\nenergy  -9.98450559E-01\ncomment r =   1.13000000E+00, E =  -9.98450559E-01, dEdr =   4.01559331E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.91882287E-01   4.91882287E-01   4.91882287E-01\natom   6.58179307E-01   6.58179307E-01   6.58179307E-01 Ne   0.00000000E+00   0.00000000E+00  -4.91882287E-01  -4.91882287E-01  -4.91882287E-01\nenergy  -9.92109781E-01\ncomment r =   1.14000000E+00, E =  -9.92109781E-01, dEdr =   8.51965112E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.05029571E-01   7.05029571E-01   7.05029571E-01\natom   6.63952810E-01   6.63952810E-01   6.63952810E-01 Ne   0.00000000E+00   0.00000000E+00  -7.05029571E-01  -7.05029571E-01  -7.05029571E-01\nenergy  -9.81681783E-01\ncomment r =   1.15000000E+00, E =  -9.81681783E-01, dEdr =   1.22114704E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.78168464E-01   8.78168464E-01   8.78168464E-01\natom   6.69726312E-01   6.69726312E-01   6.69726312E-01 Ne   0.00000000E+00   0.00000000E+00  -8.78168464E-01  -8.78168464E-01  -8.78168464E-01\nenergy  -9.67917641E-01\ncomment r =   1.16000000E+00, E =  -9.67917641E-01, dEdr =   1.52103240E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.01720634E+00   1.01720634E+00   1.01720634E+00\natom   6.75499815E-01   6.75499815E-01   6.75499815E-01 Ne   0.00000000E+00   0.00000000E+00  -1.01720634E+00  -1.01720634E+00  -1.01720634E+00\nenergy  -9.51457857E-01\ncomment r =   1.17000000E+00, E =  -9.51457857E-01, dEdr =   1.76185306E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.12721266E+00   1.12721266E+00   1.12721266E+00\natom   6.81273318E-01   6.81273318E-01   6.81273318E-01 Ne   0.00000000E+00   0.00000000E+00  -1.12721266E+00  -1.12721266E+00  -1.12721266E+00\nenergy  -9.32848056E-01\ncomment r =   1.18000000E+00, E =  -9.32848056E-01, dEdr =   1.95238960E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.21253907E+00   1.21253907E+00   1.21253907E+00\natom   6.87046820E-01   6.87046820E-01   6.87046820E-01 Ne   0.00000000E+00   0.00000000E+00  -1.21253907E+00  -1.21253907E+00  -1.21253907E+00\nenergy  -9.12552436E-01\ncomment r =   1.19000000E+00, E =  -9.12552436E-01, dEdr =   2.10017928E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.27692175E+00   1.27692175E+00   1.27692175E+00\natom   6.92820323E-01   6.92820323E-01   6.92820323E-01 Ne   0.00000000E+00   0.00000000E+00  -1.27692175E+00  -1.27692175E+00  -1.27692175E+00\nenergy  -8.90965288E-01\ncomment r =   1.20000000E+00, E =  -8.90965288E-01, dEdr =   2.21169334E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.32356877E+00   1.32356877E+00   1.32356877E+00\natom   6.98593826E-01   6.98593826E-01   6.98593826E-01 Ne   0.00000000E+00   0.00000000E+00  -1.32356877E+00  -1.32356877E+00  -1.32356877E+00\nenergy  -8.68420879E-01\ncomment r =   1.21000000E+00, E =  -8.68420879E-01, dEdr =   2.29248836E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.35523484E+00   1.35523484E+00   1.35523484E+00\natom   7.04367328E-01   7.04367328E-01   7.04367328E-01 Ne   0.00000000E+00   0.00000000E+00  -1.35523484E+00  -1.35523484E+00  -1.35523484E+00\nenergy  -8.45201938E-01\ncomment r =   1.22000000E+00, E =  -8.45201938E-01, dEdr =   2.34733561E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.37428509E+00   1.37428509E+00   1.37428509E+00\natom   7.10140831E-01   7.10140831E-01   7.10140831E-01 Ne   0.00000000E+00   0.00000000E+00  -1.37428509E+00  -1.37428509E+00  -1.37428509E+00\nenergy  -8.21546940E-01\ncomment r =   1.23000000E+00, E =  -8.21546940E-01, dEdr =   2.38033160E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38274975E+00   1.38274975E+00   1.38274975E+00\natom   7.15914334E-01   7.15914334E-01   7.15914334E-01 Ne   0.00000000E+00   0.00000000E+00  -1.38274975E+00  -1.38274975E+00  -1.38274975E+00\nenergy  -7.97656367E-01\ncomment r =   1.24000000E+00, E =  -7.97656367E-01, dEdr =   2.39499283E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38237105E+00   1.38237105E+00   1.38237105E+00\natom   7.21687836E-01   7.21687836E-01   7.21687836E-01 Ne   0.00000000E+00   0.00000000E+00  -1.38237105E+00  -1.38237105E+00  -1.38237105E+00\nenergy  -7.73698093E-01\ncomment r =   1.25000000E+00, E =  -7.73698093E-01, dEdr =   2.39433689E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.37464330E+00   1.37464330E+00   1.37464330E+00\natom   7.27461339E-01   7.27461339E-01   7.27461339E-01 Ne   0.00000000E+00   0.00000000E+00  -1.37464330E+00  -1.37464330E+00  -1.37464330E+00\nenergy  -7.49812018E-01\ncomment r =   1.26000000E+00, E =  -7.49812018E-01, dEdr =   2.38095204E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.36084745E+00   1.36084745E+00   1.36084745E+00\natom   7.33234842E-01   7.33234842E-01   7.33234842E-01 Ne   0.00000000E+00   0.00000000E+00  -1.36084745E+00  -1.36084745E+00  -1.36084745E+00\nenergy  -7.26114051E-01\ncomment r =   1.27000000E+00, E =  -7.26114051E-01, dEdr =   2.35705692E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.34208064E+00   1.34208064E+00   1.34208064E+00\natom   7.39008345E-01   7.39008345E-01   7.39008345E-01 Ne   0.00000000E+00   0.00000000E+00  -1.34208064E+00  -1.34208064E+00  -1.34208064E+00\nenergy  -7.02699549E-01\ncomment r =   1.28000000E+00, E =  -7.02699549E-01, dEdr =   2.32455185E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.31928169E+00   1.31928169E+00   1.31928169E+00\natom   7.44781847E-01   7.44781847E-01   7.44781847E-01 Ne   0.00000000E+00   0.00000000E+00  -1.31928169E+00  -1.31928169E+00  -1.31928169E+00\nenergy  -6.79646267E-01\ncomment r =   1.29000000E+00, E =  -6.79646267E-01, dEdr =   2.28506292E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.29325302E+00   1.29325302E+00   1.29325302E+00\natom   7.50555350E-01   7.50555350E-01   7.50555350E-01 Ne   0.00000000E+00   0.00000000E+00  -1.29325302E+00  -1.29325302E+00  -1.29325302E+00\nenergy  -6.57016914E-01\ncomment r =   1.30000000E+00, E =  -6.57016914E-01, dEdr =   2.23997993E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.26467942E+00   1.26467942E+00   1.26467942E+00\natom   7.56328853E-01   7.56328853E-01   7.56328853E-01 Ne   0.00000000E+00   0.00000000E+00  -1.26467942E+00  -1.26467942E+00  -1.26467942E+00\nenergy  -6.34861342E-01\ncomment r =   1.31000000E+00, E =  -6.34861342E-01, dEdr =   2.19048901E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.23414440E+00   1.23414440E+00   1.23414440E+00\natom   7.62102355E-01   7.62102355E-01   7.62102355E-01 Ne   0.00000000E+00   0.00000000E+00  -1.23414440E+00  -1.23414440E+00  -1.23414440E+00\nenergy  -6.13218442E-01\ncomment r =   1.32000000E+00, E =  -6.13218442E-01, dEdr =   2.13760080E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.20214407E+00   1.20214407E+00   1.20214407E+00\natom   7.67875858E-01   7.67875858E-01   7.67875858E-01 Ne   0.00000000E+00   0.00000000E+00  -1.20214407E+00  -1.20214407E+00  -1.20214407E+00\nenergy  -5.92117772E-01\ncomment r =   1.33000000E+00, E =  -5.92117772E-01, dEdr =   2.08217461E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.16909931E+00   1.16909931E+00   1.16909931E+00\natom   7.73649361E-01   7.73649361E-01   7.73649361E-01 Ne   0.00000000E+00   0.00000000E+00  -1.16909931E+00  -1.16909931E+00  -1.16909931E+00\nenergy  -5.71580967E-01\ncomment r =   1.34000000E+00, E =  -5.71580967E-01, dEdr =   2.02493940E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.13536610E+00   1.13536610E+00   1.13536610E+00\natom   7.79422863E-01   7.79422863E-01   7.79422863E-01 Ne   0.00000000E+00   0.00000000E+00  -1.13536610E+00  -1.13536610E+00  -1.13536610E+00\nenergy  -5.51622948E-01\ncomment r =   1.35000000E+00, E =  -5.51622948E-01, dEdr =   1.96651177E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.10124456E+00   1.10124456E+00   1.10124456E+00\natom   7.85196366E-01   7.85196366E-01   7.85196366E-01 Ne   0.00000000E+00   0.00000000E+00  -1.10124456E+00  -1.10124456E+00  -1.10124456E+00\nenergy  -5.32252964E-01\ncomment r =   1.36000000E+00, E =  -5.32252964E-01, dEdr =   1.90741154E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.06698669E+00   1.06698669E+00   1.06698669E+00\natom   7.90969869E-01   7.90969869E-01   7.90969869E-01 Ne   0.00000000E+00   0.00000000E+00  -1.06698669E+00  -1.06698669E+00  -1.06698669E+00\nenergy  -5.13475496E-01\ncomment r =   1.37000000E+00, E =  -5.13475496E-01, dEdr =   1.84807516E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.03280308E+00   1.03280308E+00   1.03280308E+00\natom   7.96743371E-01   7.96743371E-01   7.96743371E-01 Ne   0.00000000E+00   0.00000000E+00  -1.03280308E+00  -1.03280308E+00  -1.03280308E+00\nenergy  -4.95291026E-01\ncomment r =   1.38000000E+00, E =  -4.95291026E-01, dEdr =   1.78886740E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.98868680E-01   9.98868680E-01   9.98868680E-01\natom   8.02516874E-01   8.02516874E-01   8.02516874E-01 Ne   0.00000000E+00   0.00000000E+00  -9.98868680E-01  -9.98868680E-01  -9.98868680E-01\nenergy  -4.77696704E-01\ncomment r =   1.39000000E+00, E =  -4.77696704E-01, dEdr =   1.73009130E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.65327860E-01   9.65327860E-01   9.65327860E-01\natom   8.08290377E-01   8.08290377E-01   8.08290377E-01 Ne   0.00000000E+00   0.00000000E+00  -9.65327860E-01  -9.65327860E-01  -9.65327860E-01\nenergy  -4.60686922E-01\ncomment r =   1.40000000E+00, E =  -4.60686922E-01, dEdr =   1.67199690E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.32298690E-01   9.32298690E-01   9.32298690E-01\natom   8.14063880E-01   8.14063880E-01   8.14063880E-01 Ne   0.00000000E+00   0.00000000E+00  -9.32298690E-01  -9.32298690E-01  -9.32298690E-01\nenergy  -4.44253807E-01\ncomment r =   1.41000000E+00, E =  -4.44253807E-01, dEdr =   1.61478870E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.99876705E-01   8.99876705E-01   8.99876705E-01\natom   8.19837382E-01   8.19837382E-01   8.19837382E-01 Ne   0.00000000E+00   0.00000000E+00  -8.99876705E-01  -8.99876705E-01  -8.99876705E-01\nenergy  -4.28387639E-01\ncomment r =   1.42000000E+00, E =  -4.28387639E-01, dEdr =   1.55863217E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.68138141E-01   8.68138141E-01   8.68138141E-01\natom   8.25610885E-01   8.25610885E-01   8.25610885E-01 Ne   0.00000000E+00   0.00000000E+00  -8.68138141E-01  -8.68138141E-01  -8.68138141E-01\nenergy  -4.13077215E-01\ncomment r =   1.43000000E+00, E =  -4.13077215E-01, dEdr =   1.50365937E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.37142729E-01   8.37142729E-01   8.37142729E-01\natom   8.31384388E-01   8.31384388E-01   8.31384388E-01 Ne   0.00000000E+00   0.00000000E+00  -8.37142729E-01  -8.37142729E-01  -8.37142729E-01\nenergy  -3.98310158E-01\ncomment r =   1.44000000E+00, E =  -3.98310158E-01, dEdr =   1.44997374E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.06936119E-01   8.06936119E-01   8.06936119E-01\natom   8.37157890E-01   8.37157890E-01   8.37157890E-01 Ne   0.00000000E+00   0.00000000E+00  -8.06936119E-01  -8.06936119E-01  -8.06936119E-01\nenergy  -3.84073184E-01\ncomment r =   1.45000000E+00, E =  -3.84073184E-01, dEdr =   1.39765436E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.77551972E-01   7.77551972E-01   7.77551972E-01\natom   8.42931393E-01   8.42931393E-01   8.42931393E-01 Ne   0.00000000E+00   0.00000000E+00  -7.77551972E-01  -7.77551972E-01  -7.77551972E-01\nenergy  -3.70352321E-01\ncomment r =   1.46000000E+00, E =  -3.70352321E-01, dEdr =   1.34675952E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.49013769E-01   7.49013769E-01   7.49013769E-01\natom   8.48704896E-01   8.48704896E-01   8.48704896E-01 Ne   0.00000000E+00   0.00000000E+00  -7.49013769E-01  -7.49013769E-01  -7.49013769E-01\nenergy  -3.57133107E-01\ncomment r =   1.47000000E+00, E =  -3.57133107E-01, dEdr =   1.29732990E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.21336370E-01   7.21336370E-01   7.21336370E-01\natom   8.54478398E-01   8.54478398E-01   8.54478398E-01 Ne   0.00000000E+00   0.00000000E+00  -7.21336370E-01  -7.21336370E-01  -7.21336370E-01\nenergy  -3.44400751E-01\ncomment r =   1.48000000E+00, E =  -3.44400751E-01, dEdr =   1.24939124E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.94527370E-01   6.94527370E-01   6.94527370E-01\natom   8.60251901E-01   8.60251901E-01   8.60251901E-01 Ne   0.00000000E+00   0.00000000E+00  -6.94527370E-01  -6.94527370E-01  -6.94527370E-01\nenergy  -3.32140268E-01\ncomment r =   1.49000000E+00, E =  -3.32140268E-01, dEdr =   1.20295669E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.68588257E-01   6.68588257E-01   6.68588257E-01\natom   8.66025404E-01   8.66025404E-01   8.66025404E-01 Ne   0.00000000E+00   0.00000000E+00  -6.68588257E-01  -6.68588257E-01  -6.68588257E-01\nenergy  -3.20336594E-01\ncomment r =   1.50000000E+00, E =  -3.20336594E-01, dEdr =   1.15802883E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.43515424E-01   6.43515424E-01   6.43515424E-01\natom   8.71798906E-01   8.71798906E-01   8.71798906E-01 Ne   0.00000000E+00   0.00000000E+00  -6.43515424E-01  -6.43515424E-01  -6.43515424E-01\nenergy  -3.08974689E-01\ncomment r =   1.51000000E+00, E =  -3.08974689E-01, dEdr =   1.11460141E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.19301030E-01   6.19301030E-01   6.19301030E-01\natom   8.77572409E-01   8.77572409E-01   8.77572409E-01 Ne   0.00000000E+00   0.00000000E+00  -6.19301030E-01  -6.19301030E-01  -6.19301030E-01\nenergy  -2.98039609E-01\ncomment r =   1.52000000E+00, E =  -2.98039609E-01, dEdr =   1.07266085E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.95933747E-01   5.95933747E-01   5.95933747E-01\natom   8.83345912E-01   8.83345912E-01   8.83345912E-01 Ne   0.00000000E+00   0.00000000E+00  -5.95933747E-01  -5.95933747E-01  -5.95933747E-01\nenergy  -2.87516580E-01\ncomment r =   1.53000000E+00, E =  -2.87516580E-01, dEdr =   1.03218753E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.73399404E-01   5.73399404E-01   5.73399404E-01\natom   8.89119415E-01   8.89119415E-01   8.89119415E-01 Ne   0.00000000E+00   0.00000000E+00  -5.73399404E-01  -5.73399404E-01  -5.73399404E-01\nenergy  -2.77391049E-01\ncomment r =   1.54000000E+00, E =  -2.77391049E-01, dEdr =   9.93156900E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.51681534E-01   5.51681534E-01   5.51681534E-01\natom   8.94892917E-01   8.94892917E-01   8.94892917E-01 Ne   0.00000000E+00   0.00000000E+00  -5.51681534E-01  -5.51681534E-01  -5.51681534E-01\nenergy  -2.67648728E-01\ncomment r =   1.55000000E+00, E =  -2.67648728E-01, dEdr =   9.55540446E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.30761850E-01   5.30761850E-01   5.30761850E-01\natom   9.00666420E-01   9.00666420E-01   9.00666420E-01 Ne   0.00000000E+00   0.00000000E+00  -5.30761850E-01  -5.30761850E-01  -5.30761850E-01\nenergy  -2.58275632E-01\ncomment r =   1.56000000E+00, E =  -2.58275632E-01, dEdr =   9.19306492E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.10620650E-01   5.10620650E-01   5.10620650E-01\natom   9.06439923E-01   9.06439923E-01   9.06439923E-01 Ne   0.00000000E+00   0.00000000E+00  -5.10620650E-01  -5.10620650E-01  -5.10620650E-01\nenergy  -2.49258104E-01\ncomment r =   1.57000000E+00, E =  -2.49258104E-01, dEdr =   8.84420909E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.91237157E-01   4.91237157E-01   4.91237157E-01\natom   9.12213425E-01   9.12213425E-01   9.12213425E-01 Ne   0.00000000E+00   0.00000000E+00  -4.91237157E-01  -4.91237157E-01  -4.91237157E-01\nenergy  -2.40582839E-01\ncomment r =   1.58000000E+00, E =  -2.40582839E-01, dEdr =   8.50847714E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.72589820E-01   4.72589820E-01   4.72589820E-01\natom   9.17986928E-01   9.17986928E-01   9.17986928E-01 Ne   0.00000000E+00   0.00000000E+00  -4.72589820E-01  -4.72589820E-01  -4.72589820E-01\nenergy  -2.32236899E-01\ncomment r =   1.59000000E+00, E =  -2.32236899E-01, dEdr =   8.18549579E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.54656560E-01   4.54656560E-01   4.54656560E-01\natom   9.23760431E-01   9.23760431E-01   9.23760431E-01 Ne   0.00000000E+00   0.00000000E+00  -4.54656560E-01  -4.54656560E-01  -4.54656560E-01\nenergy  -2.24207724E-01\ncomment r =   1.60000000E+00, E =  -2.24207724E-01, dEdr =   7.87488261E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.37414983E-01   4.37414983E-01   4.37414983E-01\natom   9.29533933E-01   9.29533933E-01   9.29533933E-01 Ne   0.00000000E+00   0.00000000E+00  -4.37414983E-01  -4.37414983E-01  -4.37414983E-01\nenergy  -2.16483140E-01\ncomment r =   1.61000000E+00, E =  -2.16483140E-01, dEdr =   7.57624975E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.20842560E-01   4.20842560E-01   4.20842560E-01\natom   9.35307436E-01   9.35307436E-01   9.35307436E-01 Ne   0.00000000E+00   0.00000000E+00  -4.20842560E-01  -4.20842560E-01  -4.20842560E-01\nenergy  -2.09051362E-01\ncomment r =   1.62000000E+00, E =  -2.09051362E-01, dEdr =   7.28920696E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.04916775E-01   4.04916775E-01   4.04916775E-01\natom   9.41080939E-01   9.41080939E-01   9.41080939E-01 Ne   0.00000000E+00   0.00000000E+00  -4.04916775E-01  -4.04916775E-01  -4.04916775E-01\nenergy  -2.01900993E-01\ncomment r =   1.63000000E+00, E =  -2.01900993E-01, dEdr =   7.01336426E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.89615248E-01   3.89615248E-01   3.89615248E-01\natom   9.46854441E-01   9.46854441E-01   9.46854441E-01 Ne   0.00000000E+00   0.00000000E+00  -3.89615248E-01  -3.89615248E-01  -3.89615248E-01\nenergy  -1.95021029E-01\ncomment r =   1.64000000E+00, E =  -1.95021029E-01, dEdr =   6.74833406E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.74915846E-01   3.74915846E-01   3.74915846E-01\natom   9.52627944E-01   9.52627944E-01   9.52627944E-01 Ne   0.00000000E+00   0.00000000E+00  -3.74915846E-01  -3.74915846E-01  -3.74915846E-01\nenergy  -1.88400849E-01\ncomment r =   1.65000000E+00, E =  -1.88400849E-01, dEdr =   6.49373295E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.60796761E-01   3.60796761E-01   3.60796761E-01\natom   9.58401447E-01   9.58401447E-01   9.58401447E-01 Ne   0.00000000E+00   0.00000000E+00  -3.60796761E-01  -3.60796761E-01  -3.60796761E-01\nenergy  -1.82030213E-01\ncomment r =   1.66000000E+00, E =  -1.82030213E-01, dEdr =   6.24918320E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.47236580E-01   3.47236580E-01   3.47236580E-01\natom   9.64174950E-01   9.64174950E-01   9.64174950E-01 Ne   0.00000000E+00   0.00000000E+00  -3.47236580E-01  -3.47236580E-01  -3.47236580E-01\nenergy  -1.75899255E-01\ncomment r =   1.67000000E+00, E =  -1.75899255E-01, dEdr =   6.01431398E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.34214345E-01   3.34214345E-01   3.34214345E-01\natom   9.69948452E-01   9.69948452E-01   9.69948452E-01 Ne   0.00000000E+00   0.00000000E+00  -3.34214345E-01  -3.34214345E-01  -3.34214345E-01\nenergy  -1.69998479E-01\ncomment r =   1.68000000E+00, E =  -1.69998479E-01, dEdr =   5.78876226E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.21709594E-01   3.21709594E-01   3.21709594E-01\natom   9.75721955E-01   9.75721955E-01   9.75721955E-01 Ne   0.00000000E+00   0.00000000E+00  -3.21709594E-01  -3.21709594E-01  -3.21709594E-01\nenergy  -1.64318743E-01\ncomment r =   1.69000000E+00, E =  -1.64318743E-01, dEdr =   5.57217362E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.09702395E-01   3.09702395E-01   3.09702395E-01\natom   9.81495458E-01   9.81495458E-01   9.81495458E-01 Ne   0.00000000E+00   0.00000000E+00  -3.09702395E-01  -3.09702395E-01  -3.09702395E-01\nenergy  -1.58851259E-01\ncomment r =   1.70000000E+00, E =  -1.58851259E-01, dEdr =   5.36420284E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.98173372E-01   2.98173372E-01   2.98173372E-01\natom   9.87268960E-01   9.87268960E-01   9.87268960E-01 Ne   0.00000000E+00   0.00000000E+00  -2.98173372E-01  -2.98173372E-01  -2.98173372E-01\nenergy  -1.53587577E-01\ncomment r =   1.71000000E+00, E =  -1.53587577E-01, dEdr =   5.16451429E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.87103720E-01   2.87103720E-01   2.87103720E-01\natom   9.93042463E-01   9.93042463E-01   9.93042463E-01 Ne   0.00000000E+00   0.00000000E+00  -2.87103720E-01  -2.87103720E-01  -2.87103720E-01\nenergy  -1.48519579E-01\ncomment r =   1.72000000E+00, E =  -1.48519579E-01, dEdr =   4.97278230E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.76475222E-01   2.76475222E-01   2.76475222E-01\natom   9.98815966E-01   9.98815966E-01   9.98815966E-01 Ne   0.00000000E+00   0.00000000E+00  -2.76475222E-01  -2.76475222E-01  -2.76475222E-01\nenergy  -1.43639466E-01\ncomment r =   1.73000000E+00, E =  -1.43639466E-01, dEdr =   4.78869131E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.66270250E-01   2.66270250E-01   2.66270250E-01\natom   1.00458947E+00   1.00458947E+00   1.00458947E+00 Ne   0.00000000E+00   0.00000000E+00  -2.66270250E-01  -2.66270250E-01  -2.66270250E-01\nenergy  -1.38939751E-01\ncomment r =   1.74000000E+00, E =  -1.38939751E-01, dEdr =   4.61193602E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.56471773E-01   2.56471773E-01   2.56471773E-01\natom   1.01036297E+00   1.01036297E+00   1.01036297E+00 Ne   0.00000000E+00   0.00000000E+00  -2.56471773E-01  -2.56471773E-01  -2.56471773E-01\nenergy  -1.34413247E-01\ncomment r =   1.75000000E+00, E =  -1.34413247E-01, dEdr =   4.44222142E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.47063348E-01   2.47063348E-01   2.47063348E-01\natom   1.01613647E+00   1.01613647E+00   1.01613647E+00 Ne   0.00000000E+00   0.00000000E+00  -2.47063348E-01  -2.47063348E-01  -2.47063348E-01\nenergy  -1.30053056E-01\ncomment r =   1.76000000E+00, E =  -1.30053056E-01, dEdr =   4.27926272E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.38029122E-01   2.38029122E-01   2.38029122E-01\natom   1.02190998E+00   1.02190998E+00   1.02190998E+00 Ne   0.00000000E+00   0.00000000E+00  -2.38029122E-01  -2.38029122E-01  -2.38029122E-01\nenergy  -1.25852561E-01\ncomment r =   1.77000000E+00, E =  -1.25852561E-01, dEdr =   4.12278533E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.29353819E-01   2.29353819E-01   2.29353819E-01\natom   1.02768348E+00   1.02768348E+00   1.02768348E+00 Ne   0.00000000E+00   0.00000000E+00  -2.29353819E-01  -2.29353819E-01  -2.29353819E-01\nenergy  -1.21805413E-01\ncomment r =   1.78000000E+00, E =  -1.21805413E-01, dEdr =   3.97252467E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.21022735E-01   2.21022735E-01   2.21022735E-01\natom   1.03345698E+00   1.03345698E+00   1.03345698E+00 Ne   0.00000000E+00   0.00000000E+00  -2.21022735E-01  -2.21022735E-01  -2.21022735E-01\nenergy  -1.17905524E-01\ncomment r =   1.79000000E+00, E =  -1.17905524E-01, dEdr =   3.82822607E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.13021724E-01   2.13021724E-01   2.13021724E-01\natom   1.03923048E+00   1.03923048E+00   1.03923048E+00 Ne   0.00000000E+00   0.00000000E+00  -2.13021724E-01  -2.13021724E-01  -2.13021724E-01\nenergy  -1.14147056E-01\ncomment r =   1.80000000E+00, E =  -1.14147056E-01, dEdr =   3.68964449E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.05337187E-01   2.05337187E-01   2.05337187E-01\natom   1.04500399E+00   1.04500399E+00   1.04500399E+00 Ne   0.00000000E+00   0.00000000E+00  -2.05337187E-01  -2.05337187E-01  -2.05337187E-01\nenergy  -1.10524408E-01\ncomment r =   1.81000000E+00, E =  -1.10524408E-01, dEdr =   3.55654440E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.97956057E-01   1.97956057E-01   1.97956057E-01\natom   1.05077749E+00   1.05077749E+00   1.05077749E+00 Ne   0.00000000E+00   0.00000000E+00  -1.97956057E-01  -1.97956057E-01  -1.97956057E-01\nenergy  -1.07032215E-01\ncomment r =   1.82000000E+00, E =  -1.07032215E-01, dEdr =   3.42869948E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.90865785E-01   1.90865785E-01   1.90865785E-01\natom   1.05655099E+00   1.05655099E+00   1.05655099E+00 Ne   0.00000000E+00   0.00000000E+00  -1.90865785E-01  -1.90865785E-01  -1.90865785E-01\nenergy  -1.03665330E-01\ncomment r =   1.83000000E+00, E =  -1.03665330E-01, dEdr =   3.30589238E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.84054328E-01   1.84054328E-01   1.84054328E-01\natom   1.06232450E+00   1.06232450E+00   1.06232450E+00 Ne   0.00000000E+00   0.00000000E+00  -1.84054328E-01  -1.84054328E-01  -1.84054328E-01\nenergy  -1.00418821E-01\ncomment r =   1.84000000E+00, E =  -1.00418821E-01, dEdr =   3.18791447E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.77510126E-01   1.77510126E-01   1.77510126E-01\natom   1.06809800E+00   1.06809800E+00   1.06809800E+00 Ne   0.00000000E+00   0.00000000E+00  -1.77510126E-01  -1.77510126E-01  -1.77510126E-01\nenergy  -9.72879584E-02\ncomment r =   1.85000000E+00, E =  -9.72879584E-02, dEdr =   3.07456558E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.71222096E-01   1.71222096E-01   1.71222096E-01\natom   1.07387150E+00   1.07387150E+00   1.07387150E+00 Ne   0.00000000E+00   0.00000000E+00  -1.71222096E-01  -1.71222096E-01  -1.71222096E-01\nenergy  -9.42682107E-02\ncomment r =   1.86000000E+00, E =  -9.42682107E-02, dEdr =   2.96565370E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.65179609E-01   1.65179609E-01   1.65179609E-01\natom   1.07964500E+00   1.07964500E+00   1.07964500E+00 Ne   0.00000000E+00   0.00000000E+00  -1.65179609E-01  -1.65179609E-01  -1.65179609E-01\nenergy  -9.13552334E-02\ncomment r =   1.87000000E+00, E =  -9.13552334E-02, dEdr =   2.86099475E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.59372475E-01   1.59372475E-01   1.59372475E-01\natom   1.08541851E+00   1.08541851E+00   1.08541851E+00 Ne   0.00000000E+00   0.00000000E+00  -1.59372475E-01  -1.59372475E-01  -1.59372475E-01\nenergy  -8.85448625E-02\ncomment r =   1.88000000E+00, E =  -8.85448625E-02, dEdr =   2.76041225E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.53790932E-01   1.53790932E-01   1.53790932E-01\natom   1.09119201E+00   1.09119201E+00   1.09119201E+00 Ne   0.00000000E+00   0.00000000E+00  -1.53790932E-01  -1.53790932E-01  -1.53790932E-01\nenergy  -8.58331065E-02\ncomment r =   1.89000000E+00, E =  -8.58331065E-02, dEdr =   2.66373709E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.48425625E-01   1.48425625E-01   1.48425625E-01\natom   1.09696551E+00   1.09696551E+00   1.09696551E+00 Ne   0.00000000E+00   0.00000000E+00  -1.48425625E-01  -1.48425625E-01  -1.48425625E-01\nenergy  -8.32161399E-02\ncomment r =   1.90000000E+00, E =  -8.32161399E-02, dEdr =   2.57080724E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.43267593E-01   1.43267593E-01   1.43267593E-01\natom   1.10273901E+00   1.10273901E+00   1.10273901E+00 Ne   0.00000000E+00   0.00000000E+00  -1.43267593E-01  -1.43267593E-01  -1.43267593E-01\nenergy  -8.06902954E-02\ncomment r =   1.91000000E+00, E =  -8.06902954E-02, dEdr =   2.48146751E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38308255E-01   1.38308255E-01   1.38308255E-01\natom   1.10851252E+00   1.10851252E+00   1.10851252E+00 Ne   0.00000000E+00   0.00000000E+00  -1.38308255E-01  -1.38308255E-01  -1.38308255E-01\nenergy  -7.82520578E-02\ncomment r =   1.92000000E+00, E =  -7.82520578E-02, dEdr =   2.39556925E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.33539391E-01   1.33539391E-01   1.33539391E-01\natom   1.11428602E+00   1.11428602E+00   1.11428602E+00 Ne   0.00000000E+00   0.00000000E+00  -1.33539391E-01  -1.33539391E-01  -1.33539391E-01\nenergy  -7.58980573E-02\ncomment r =   1.93000000E+00, E =  -7.58980573E-02, dEdr =   2.31297011E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.28953134E-01   1.28953134E-01   1.28953134E-01\natom   1.12005952E+00   1.12005952E+00   1.12005952E+00 Ne   0.00000000E+00   0.00000000E+00  -1.28953134E-01  -1.28953134E-01  -1.28953134E-01\nenergy  -7.36250634E-02\ncomment r =   1.94000000E+00, E =  -7.36250634E-02, dEdr =   2.23353381E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.24541951E-01   1.24541951E-01   1.24541951E-01\natom   1.12583302E+00   1.12583302E+00   1.12583302E+00 Ne   0.00000000E+00   0.00000000E+00  -1.24541951E-01  -1.24541951E-01  -1.24541951E-01\nenergy  -7.14299790E-02\ncomment r =   1.95000000E+00, E =  -7.14299790E-02, dEdr =   2.15712986E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.20298629E-01   1.20298629E-01   1.20298629E-01\natom   1.13160653E+00   1.13160653E+00   1.13160653E+00 Ne   0.00000000E+00   0.00000000E+00  -1.20298629E-01  -1.20298629E-01  -1.20298629E-01\nenergy  -6.93098346E-02\ncomment r =   1.96000000E+00, E =  -6.93098346E-02, dEdr =   2.08363337E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.16216266E-01   1.16216266E-01   1.16216266E-01\natom   1.13738003E+00   1.13738003E+00   1.13738003E+00 Ne   0.00000000E+00   0.00000000E+00  -1.16216266E-01  -1.16216266E-01  -1.16216266E-01\nenergy  -6.72617830E-02\ncomment r =   1.97000000E+00, E =  -6.72617830E-02, dEdr =   2.01292477E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.12288255E-01   1.12288255E-01   1.12288255E-01\natom   1.14315353E+00   1.14315353E+00   1.14315353E+00 Ne   0.00000000E+00   0.00000000E+00  -1.12288255E-01  -1.12288255E-01  -1.12288255E-01\nenergy  -6.52830939E-02\ncomment r =   1.98000000E+00, E =  -6.52830939E-02, dEdr =   1.94488962E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.08508271E-01   1.08508271E-01   1.08508271E-01\natom   1.14892704E+00   1.14892704E+00   1.14892704E+00 Ne   0.00000000E+00   0.00000000E+00  -1.08508271E-01  -1.08508271E-01  -1.08508271E-01\nenergy  -6.33711491E-02\ncomment r =   1.99000000E+00, E =  -6.33711491E-02, dEdr =   1.87941839E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.04870264E-01   1.04870264E-01   1.04870264E-01\natom   1.15470054E+00   1.15470054E+00   1.15470054E+00 Ne   0.00000000E+00   0.00000000E+00  -1.04870264E-01  -1.04870264E-01  -1.04870264E-01\nenergy  -6.15234375E-02\ncomment r =   2.00000000E+00, E =  -6.15234375E-02, dEdr =   1.81640625E-01\nend\n"
  },
  {
    "path": "examples/nnp-checkdw/LJ/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              1              # Number of elements.\nelements                        Ne             # Specification of elements.\n#atom_energy                     Ne 0.0         # Free atom reference energy (Ne).\ncutoff_type                     2              # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      1              # Number of hidden layers.\nglobal_nodes_short              3              # Number of nodes in each hidden layer.\nglobal_activation_short         t l            # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    1.0            # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.167          # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# radial Ne Ne\nsymfunction_short Ne 2 Ne 1.000 0.00 3.00\nsymfunction_short Ne 2 Ne 1.000 0.25 3.00\nsymfunction_short Ne 2 Ne 1.000 0.50 3.00\nsymfunction_short Ne 2 Ne 1.000 0.75 3.00\nsymfunction_short Ne 2 Ne 1.000 1.00 3.00\n"
  },
  {
    "path": "examples/nnp-checkdw/LJ/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   6.0871865837434718E-04   7.2815866278251790E-02   1.9093305172662212E-02   2.0241240265275205E-02\n         1          2   1.5544175511327358E-03   1.1277941989452710E-01   3.3134472337730189E-02   3.1972702944828152E-02\n         1          3   3.5029340302491388E-03   1.5415119007009570E-01   5.1275563979636354E-02   4.4402666633939228E-02\n         1          4   6.9664161692094993E-03   1.8594182841625700E-01   7.0845240019947853E-02   5.4073736544960498E-02\n         1          5   1.2226441157255801E-02   1.9793404599765610E-01   8.7507815525083174E-02   5.7502177573987671E-02\n"
  },
  {
    "path": "examples/nnp-checkdw/LJ/weights.010.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  7.1289683273892379E-01 a         1     0     1     1     1\n  1.0495883843662790E+01 a         2     0     1     1     2\n -1.1574157686813686E+00 a         3     0     1     1     3\n  6.4799962786573706E-01 a         4     0     2     1     1\n -5.4599309824857345E-01 a         5     0     2     1     2\n -1.3938446745959876E+00 a         6     0     2     1     3\n  1.4765399939509904E+00 a         7     0     3     1     1\n -5.1760448988710932E+00 a         8     0     3     1     2\n  3.4349118505771320E-01 a         9     0     3     1     3\n  2.7605647283658095E+00 a        10     0     4     1     1\n -5.7967091488298879E+00 a        11     0     4     1     2\n -4.2234815912119011E-01 a        12     0     4     1     3\n  3.0320678573808363E-01 a        13     0     5     1     1\n  3.4806650267415351E-01 a        14     0     5     1     2\n  9.8678647412933629E-01 a        15     0     5     1     3\n  1.9203733149922300E+00 b        16     1     1\n -7.0323031244499068E-01 b        17     1     2\n  2.3427527876891785E-01 b        18     1     3\n  1.3731392066926247E+00 a        19     1     1     2     1\n  1.2639210463211468E+00 a        20     1     2     2     1\n  4.2373331685651211E-01 a        21     1     3     2     1\n -6.2527778527617084E-01 b        22     2     1\n"
  },
  {
    "path": "examples/nnp-checkf/H2O_RPBE-D3/input.data",
    "content": " begin\ncomment written by RuNNerDecom\nlattice      14.782194      0.000000      0.000000\nlattice       0.000000     14.782194      0.000000\nlattice       0.000000      0.000000     14.782194\natom     0.642507138    5.688076012   14.059560412   O   -0.223804650    0.000000000   -0.012843144   -0.012768831    0.020115876\natom    -0.415739913    4.573137154   15.212293807   H    0.123401960    0.000000000    0.018853582    0.026511418   -0.014393530\natom     1.058247052    7.313239238   14.947732044   H    0.118244300    0.000000000   -0.001610950   -0.022831932   -0.011001476\natom     5.858151431    1.473986965    7.256547431   O   -0.223298820    0.000000000   -0.020285563    0.014001355   -0.027641789\natom     6.651834830    0.888171633    5.631384206   H    0.112270890    0.000000000    0.002511650    0.001550816    0.013843836\natom     4.818801649    2.910177502    6.557348486   H    0.118618850    0.000000000    0.011831258   -0.012126922    0.005252066\natom     3.212533802    0.812582557   13.795000539   O   -0.271600670    0.000000000   -0.009699309    0.011565349   -0.007164009\natom     2.418848514    0.302356300   12.132040886   H    0.109717810    0.000000000    0.009741586    0.008033517    0.017907689\natom     2.834588427    2.664513008   14.078457681   H    0.116411780    0.000000000    0.001762741   -0.024834462   -0.010352696\natom     3.911732747    8.825020740    9.637603297   O   -0.232487160    0.000000000    0.004650911   -0.029766297    0.008598910\natom     3.533787372    7.653390076    8.182513601   H    0.114730110    0.000000000    0.005318212    0.016230464    0.009282071\natom     4.762109842    7.634492807   10.884821147   H    0.117914860    0.000000000   -0.011481994    0.013548446   -0.020267833\natom     9.599808760    9.505322416    7.955746376   O   -0.266941130    0.000000000    0.018980184   -0.011340038    0.011813416\natom     8.862815277   10.676951190    9.259657922   H    0.096853870  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0.007077184    0.005879847\natom     6.330581261    3.458198297    9.921062329   H    0.112119250    0.000000000    0.005611887    0.007695415    0.018661832\natom     3.307020146    9.694295104    1.171630664   O   -0.223789930    0.000000000   -0.004608133    0.033860322   -0.010218339\natom     5.158952487   10.072238589    1.417295158   H    0.119446070    0.000000000   -0.017902968   -0.004751831    0.003188165\natom     2.437745783   11.300561060    0.585815332   H    0.149043090    0.000000000    0.021724014   -0.024211809    0.013500201\natom     8.258102676    9.618706028    3.004663846   O   -0.219889910    0.000000000    0.010485892    0.003725800   -0.009410036\natom     9.184068847   11.243869254    2.607821202   H    0.141331680    0.000000000   -0.015287376   -0.027667444    0.018337968\natom     8.579356246    8.995096159    4.781007111   H    0.123118020    0.000000000    0.002771554    0.026161870   -0.008261825\natom     1.511781502   13.265877013    9.051787965   O  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13.757206001   15.741417333   H    0.129587430    0.000000000   -0.008265304   -0.004854866   -0.031505650\natom     2.116492213    7.275444700   15.344574689   O   -0.271519240    0.000000000    0.003721200    0.008520093   -0.025792126\natom     1.398397890    8.825020740   14.494197594   H    0.119856700    0.000000000    0.017408675   -0.028056072    0.015153435\natom     3.401506490    6.519553949   14.135149487   H    0.133218540    0.000000000   -0.021344903    0.016767178    0.021407706\natom     7.369931044    0.302356300    7.294341969   O   -0.220182040    0.000000000   -0.016962630   -0.007854252   -0.022791701\natom     7.899054570    1.398397890    5.820356894   H    0.106388840    0.000000000   -0.006952790   -0.001015854    0.010976189\natom     5.574692400   -0.188972688    6.840807518   H    0.119706610    0.000000000    0.034102223    0.009248015    0.015697746\natom     3.174739265    1.058247052    4.062910897   O   -0.220255450    0.000000000   -0.032726729   -0.000354508   -0.001364851\natom     1.511781502    1.927521415    3.722760059   H    0.119615460    0.000000000    0.022869270   -0.014738414    0.009684134\natom     2.740102083   -0.377945376    5.253438830   H    0.102308210    0.000000000   -0.003629110    0.006732548   -0.010769141\natom     2.154286751   11.961965467    7.180958356   O   -0.240775800    0.000000000    0.009122791   -0.004982979    0.009900370\natom     3.004663846   10.261211277    7.199855625   H    0.123082890    0.000000000   -0.010714630    0.021314294    0.006951169\natom     1.719651459   12.453294455    8.976198890   H    0.115761200    0.000000000    0.004591800   -0.017597022   -0.019732886\natom    13.417055163    3.703862791    4.025116360   O   -0.190128900    0.000000000   -0.016402162    0.055351873   -0.001006850\natom    12.018657273    4.610931692    4.969979799   H    0.147045320    0.000000000    0.013413052   -0.020709035   -0.006834321\natom    13.983973226    5.234541562    3.023561115   H    0.144388550    0.000000000    0.004029892   -0.019854074    0.010580859\nenergy   -1225.06985518\ncharge         0.0000000000\n end\n begin\ncomment written by RuNNerDecom\nlattice      14.782194      0.000000      0.000000\nlattice       0.000000     14.782194      0.000000\nlattice       0.000000      0.000000     14.782194\natom    11.400096754   13.987044033    9.287814852   O   -0.266631430    0.000000000    0.006003401   -0.027296987    0.010331412\natom    10.894553240   15.711153357    8.813633246   H    0.111583360    0.000000000   -0.012856778   -0.023375192   -0.000005688\natom     9.989260682   12.684784108    9.613887225   H    0.102455090    0.000000000    0.009113211    0.044638185   -0.012928939\natom     3.784639166    4.760530031    3.007759219   O   -0.260999230    0.000000000    0.034864635   -0.019137222    0.012190007\natom     4.967651655    3.453789564    2.067306402   H    0.108108550    0.000000000   -0.024519111    0.028424641    0.033241519\natom     4.205485121    4.673938966    4.966644431   H    0.108102810    0.000000000   -0.013144228   -0.012505323   -0.050529493\natom    13.578277212    3.357430501    2.230852815   O   -0.265503680    0.000000000    0.009457228   -0.025689021   -0.013174336\natom    13.339323138    1.531657650    1.585991077   H    0.115799580    0.000000000    0.011157472    0.042412027    0.010049623\natom    15.462896158    3.843626991    2.153211496   H    0.099211820    0.000000000   -0.026633251   -0.012328516    0.005608888\natom     3.813761747    3.362360798    8.004416292   O   -0.214916570    0.000000000    0.008445927    0.005222495    0.012662183\natom     3.456112038    1.605016847    8.458634824   H    0.135238140    0.000000000   -0.000182282    0.003156323    0.000822673\natom     4.981178320    3.899152835    9.399015830   H    0.106653320    0.000000000   -0.009589671   -0.007144409   -0.005923857\natom     9.210570376   11.605559199    3.402619539   O   -0.227137870    0.000000000   -0.033575788    0.016123566    0.007429402\natom     9.248047440    9.949538623    2.619751047   H    0.095161930    0.000000000    0.005363792   -0.018134607   -0.010848833\natom     7.354594021   11.651177205    3.888407848   H    0.111705120    0.000000000    0.023188742   -0.007382475    0.005319132\natom     7.048673695    0.959875429    1.289804735   O   -0.236808690    0.000000000    0.021968981    0.008023820   -0.035555297\natom     7.801130813   -0.612322531    1.904277775   H    0.099419770    0.000000000    0.004213325   -0.004190418    0.007204636\natom     8.258688492    1.311510137   -0.157293306   H    0.129396420    0.000000000   -0.023374625    0.001187028    0.020493432\natom     7.453687519    3.722763839   11.647259802   O   -0.240670670    0.000000000    0.016604663    0.022272654   -0.011433843\natom     7.856987360    5.010620265   13.029311554   H    0.125042720    0.000000000   -0.000216408   -0.016545721   -0.033123534\natom     8.390846541    4.027654263    9.891138504   H    0.106641770    0.000000000   -0.009744176    0.001311510    0.044557312\natom     9.591922929    3.636051831    7.006617824   O   -0.177886700    0.000000000    0.020764716    0.035866214   -0.040602524\natom     8.602308868    4.123867817    5.436077154   H    0.158810880    0.000000000    0.014144342   -0.013886115    0.027733004\natom    11.323245341    4.420328170    6.580941726   H    0.148643600    0.000000000   -0.029316584   -0.013759021    0.010165974\natom    13.932772966   11.010916952    5.324033357   O   -0.272368940    0.000000000   -0.031709980    0.005941426   -0.006211509\natom    12.986711441   11.510171455    6.882593159   H    0.109058660    0.000000000    0.018464083    0.004702735   -0.009185046\natom    12.372742957   10.941276737    4.222519119   H    0.100176900    0.000000000    0.023484862    0.002710255    0.013910920\natom    10.011969530    7.147831444    1.138367692   O   -0.268084950    0.000000000    0.031903865   -0.017360031   -0.048087715\natom    11.217428195    5.579743640    1.382070649   H    0.098718200    0.000000000   -0.016376190    0.031900049   -0.001302878\natom    10.623543729    7.870842837   -0.679143273   H    0.098891220    0.000000000   -0.007531025   -0.020993194    0.044532202\natom     6.933814206   11.473883030    9.595456719   O   -0.241122680    0.000000000   -0.032274345    0.007556561    0.028589313\natom     5.418459230   12.248465069   10.718861553   H    0.113480820    0.000000000    0.030225503   -0.024059407   -0.038121028\natom     6.210708326   10.792666726    8.038197049   H    0.120956070    0.000000000   -0.002256347    0.002910467    0.006395998\natom     4.475508195   10.014764436    4.589674154   O   -0.212648850    0.000000000   -0.005810155    0.033746537    0.030551251\natom     3.020095356   11.175706805    4.948741158   H    0.144660760    0.000000000    0.007883643   -0.020866638   -0.013752232\natom     4.165759283    9.011098366    3.129378261   H    0.143832960    0.000000000   -0.010141226   -0.013952791   -0.014587652\natom    13.398157894   13.398773945   14.086271701   O   -0.218599430    0.000000000    0.007131722   -0.029858862    0.015231412\natom    13.735940904   11.982187434   15.384710598   H    0.151347450    0.000000000   -0.008535887    0.029667214   -0.041657848\natom    12.971302608   12.717421581   12.342530004   H    0.117807410    0.000000000   -0.003346494    0.003600482    0.027404308\natom    -0.029853905    6.883301806    7.971228908   O   -0.223990930    0.000000000    0.024264161   -0.006314132   -0.021693996\natom     0.977655869    7.473268868    6.440535019   H    0.133521400    0.000000000   -0.025902051   -0.005351332    0.030962871\natom     1.060898338    5.576689841    8.725726931   H    0.114826910    0.000000000   -0.001307442    0.000374352   -0.007600117\natom     3.181506377   14.173805740   11.779022898   O   -0.232149600    0.000000000   -0.012334071   -0.008570649   -0.022345041\natom     4.514030277   14.870986456   12.792615703   H    0.125547620    0.000000000   -0.004584722    0.015890876    0.020256429\natom     1.399554402   14.377221610   12.428251795   H    0.122711800    0.000000000    0.025412017   -0.004414577    0.010547137\natom    11.530616410    8.776902624   11.168391672   O   -0.228946230    0.000000000   -0.036161915    0.015805311    0.029203899\natom     9.749297494    8.859990136   10.577149045   H    0.128448790    0.000000000    0.020958541   -0.001422328   -0.005878341\natom    12.710696043    8.032102680    9.992569594   H    0.102458220    0.000000000    0.006405910   -0.008905758   -0.020845229\nenergy   -1225.02203483\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/nnp-checkf/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-checkf/H2O_RPBE-D3/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "examples/nnp-checkf/H2O_RPBE-D3/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.2539155865352127E+00 a         1     0     1     1     1\n  2.2490365890661286E+00 a         2     0     1     1     2\n  4.9361851928374572E+00 a         3     0     1     1     3\n -2.3971991574908125E+00 a         4     0     1     1     4\n -1.8596992303156465E+00 a         5     0     1     1     5\n  3.8287764168815897E+00 a         6     0     1     1     6\n  7.4523181738636106E+00 a         7     0     1     1     7\n  6.0971861116881998E+00 a         8     0     1     1     8\n -8.7239359226117639E+00 a         9     0     1     1     9\n -1.8255232070184267E+01 a        10     0     1     1    10\n -7.8065643887610179E+00 a        11     0     1     1    11\n  1.4247237398130265E+01 a        12     0     1     1    12\n -3.2217879518334338E+00 a        13     0     1     1    13\n -5.7395252086520712E+00 a        14     0     1     1    14\n  2.0353040522911576E+00 a        15     0     1     1    15\n  7.7520578160630560E+00 a        16     0     1     1    16\n  2.9357257867412252E+00 a        17     0     1     1    17\n -2.9719860930100790E+00 a        18     0     1     1    18\n  8.9245382590288980E+00 a        19     0     1     1    19\n  6.6848134049442169E+00 a        20     0     1     1    20\n -2.2992719903495891E+00 a        21     0     1     1    21\n -1.4401533482181721E+01 a        22     0     1     1    22\n -2.0574070545285186E+00 a        23     0     1     1    23\n -6.3544667277888678E+00 a        24     0     1     1    24\n  3.9668360525851707E+00 a        25     0     1     1    25\n  1.0930597297534963E+01 a        26     0     2     1     1\n  3.0058866618169424E+00 a        27     0     2     1     2\n -4.9950943102999927E+00 a        28     0     2     1     3\n -1.9930957240687266E+00 a        29     0     2     1     4\n  1.6790893133342006E+00 a        30     0     2     1     5\n -4.5254006136507128E+00 a        31     0     2     1     6\n -9.6165021729265252E+00 a        32     0     2     1     7\n -8.7465722730176285E+00 a        33     0     2     1     8\n  1.5506950040431201E+01 a        34     0     2     1     9\n  2.1903342918227118E+01 a        35     0     2     1    10\n -1.0685216745153280E+01 a        36     0     2     1    11\n -2.5859690636594280E+01 a        37     0     2     1    12\n -3.2423603491405122E+00 a        38     0     2     1    13\n  5.3753900550878555E+00 a        39     0     2     1    14\n -3.0291935617567991E+00 a        40     0     2     1    15\n -1.3534893178408465E+01 a        41     0     2     1    16\n -5.7625138055631471E+00 a        42     0     2     1    17\n  1.0216765318459601E+01 a        43     0     2     1    18\n -1.4416012930050949E+01 a        44     0     2     1    19\n -4.7226757471872144E-01 a        45     0     2     1    20\n  7.8981385188798026E+00 a        46     0     2     1    21\n  1.2202710023744410E+00 a        47     0     2     1    22\n  8.0560891210932120E+00 a        48     0     2     1    23\n  4.5972445013263297E-01 a        49     0     2     1    24\n  1.3374237019728858E+01 a        50     0     2     1    25\n -1.0644910441621166E+01 a        51     0     3     1     1\n -5.6098794516515920E+00 a        52     0     3     1     2\n -1.0236653403367724E+01 a        53     0     3     1     3\n  1.3552139405799508E+00 a        54     0     3     1     4\n  1.3201025058567883E+00 a        55     0     3     1     5\n  1.6531266759009673E+00 a        56     0     3     1     6\n -1.0303768926395865E+01 a        57     0     3     1     7\n  1.9927521303470008E-01 a        58     0     3     1     8\n  8.1216226663758366E+00 a        59     0     3     1     9\n  2.1349555016157687E+01 a        60     0     3     1    10\n  1.0105416692705148E+01 a        61     0     3     1    11\n -1.1444993918278378E+01 a        62     0     3     1    12\n  2.9861675555209538E-01 a        63     0     3     1    13\n  9.3552992513120543E+00 a        64     0     3     1    14\n -2.2844869025933630E+00 a        65     0     3     1    15\n -3.8047300595857316E+00 a        66     0     3     1    16\n -3.0512161452147448E+00 a        67     0     3     1    17\n  2.7887340590896472E+00 a        68     0     3     1    18\n -1.5988439945122812E+01 a        69     0     3     1    19\n -1.6917164763280326E+01 a        70     0     3     1    20\n  3.2170907488709326E+00 a        71     0     3     1    21\n  2.1641888770160929E+01 a        72     0     3     1    22\n  3.2604671723420497E+00 a        73     0     3     1    23\n  1.5230689068493776E+01 a        74     0     3     1    24\n -1.4713830039823366E+01 a        75     0     3     1    25\n -2.3544214523969775E+00 a        76     0     4     1     1\n -5.8299691629399382E+00 a        77     0     4     1     2\n  1.7168784391956539E+01 a        78     0     4     1     3\n  1.0050003860864617E+01 a        79     0     4     1     4\n  3.5168903759752812E+00 a        80     0     4     1     5\n -4.4828111046589010E+00 a        81     0     4     1     6\n  1.8299193380051442E+01 a        82     0     4     1     7\n  6.9717289110204188E+00 a        83     0     4     1     8\n -2.0364082994445859E+01 a        84     0     4     1     9\n -3.5062338388300589E+01 a        85     0     4     1    10\n  1.8010375764887119E+01 a        86     0     4     1    11\n  4.2133659287179640E+01 a        87     0     4     1    12\n  1.1988736553417061E+01 a        88     0     4     1    13\n -1.2351529706885179E+01 a        89     0     4     1    14\n  5.4139212296285057E+00 a        90     0     4     1    15\n  1.6705967069968899E+01 a        91     0     4     1    16\n  8.3219076874511639E+00 a        92     0     4     1    17\n -1.8555777504879448E+01 a        93     0     4     1    18\n  3.1433889377775369E+01 a        94     0     4     1    19\n  6.7043459658252780E-01 a        95     0     4     1    20\n -1.3837570456349678E+01 a        96     0     4     1    21\n  5.0298368971353791E-01 a        97     0     4     1    22\n -2.2656240789613065E+01 a        98     0     4     1    23\n -2.4243684644962626E+00 a        99     0     4     1    24\n -2.8280330035212309E+01 a       100     0     4     1    25\n  4.2306100814115322E+00 a       101     0     5     1     1\n  9.9770374716830084E+00 a       102     0     5     1     2\n  2.0487048112933808E+00 a       103     0     5     1     3\n -1.3702212470739978E+00 a       104     0     5     1     4\n  2.8131124422603837E+00 a       105     0     5     1     5\n  3.2845640151619522E-03 a       106     0     5     1     6\n  2.4065616021196026E+00 a       107     0     5     1     7\n -1.0461000723401572E+01 a       108     0     5     1     8\n -1.0180720750329515E+01 a       109     0     5     1     9\n -8.8668996772076660E+00 a       110     0     5     1    10\n  6.5256092481271502E+00 a       111     0     5     1    11\n -6.9831054240027211E+00 a       112     0     5     1    12\n  4.0892074148312876E+00 a       113     0     5     1    13\n -5.1951354450201128E+00 a       114     0     5     1    14\n  1.6657989141753051E+00 a       115     0     5     1    15\n -7.3542511663155619E+00 a       116     0     5     1    16\n  5.1573102842565115E+00 a       117     0     5     1    17\n  3.4929930175122172E+00 a       118     0     5     1    18\n  2.5382184218789963E+00 a       119     0     5     1    19\n  2.0045179007481050E+01 a       120     0     5     1    20\n -1.6165269676512768E+00 a       121     0     5     1    21\n  2.4869117790922393E+00 a       122     0     5     1    22\n  6.0131560843540068E+00 a       123     0     5     1    23\n -1.2231651850388728E+01 a       124     0     5     1    24\n  3.5372450187997345E+01 a       125     0     5     1    25\n -1.0433252604911765E+01 a       126     0     6     1     1\n -2.3715834640656657E+00 a       127     0     6     1     2\n -1.8239608965373137E+01 a       128     0     6     1     3\n -3.6510816169583777E+00 a       129     0     6     1     4\n -1.7632327653119535E+01 a       130     0     6     1     5\n  1.0040509177650593E+01 a       131     0     6     1     6\n -1.5407385349225459E+01 a       132     0     6     1     7\n -7.0553605774310779E-01 a       133     0     6     1     8\n  1.3204892207903583E+01 a       134     0     6     1     9\n  2.9596389655595953E+01 a       135     0     6     1    10\n -2.0620173259628203E+01 a       136     0     6     1    11\n -3.0803380363815094E+01 a       137     0     6     1    12\n -1.4917676387082279E+01 a       138     0     6     1    13\n  9.6935054799166185E+00 a       139     0     6     1    14\n  4.6937319413252743E+00 a       140     0     6     1    15\n -5.0263591258131060E+00 a       141     0     6     1    16\n -9.7243575590712439E+00 a       142     0     6     1    17\n  1.5625340951727363E+01 a       143     0     6     1    18\n -2.8266776356585389E+01 a       144     0     6     1    19\n  2.5386057418612946E+00 a       145     0     6     1    20\n  1.6302330128073283E+01 a       146     0     6     1    21\n -8.5166226512297030E+00 a       147     0     6     1    22\n  2.5040570504752605E+01 a       148     0     6     1    23\n -8.5008658358878897E-01 a       149     0     6     1    24\n  2.0458930574550632E+01 a       150     0     6     1    25\n  7.8529627796707677E+00 a       151     0     7     1     1\n -4.5279242985866821E+00 a       152     0     7     1     2\n  4.7942839133231594E+00 a       153     0     7     1     3\n -6.2431002330064649E+00 a       154     0     7     1     4\n  4.3358077462982054E+00 a       155     0     7     1     5\n -6.8037589596444281E+00 a       156     0     7     1     6\n  1.8980667946224101E+00 a       157     0     7     1     7\n  1.9802532239433695E+01 a       158     0     7     1     8\n  8.4826746941006572E+00 a       159     0     7     1     9\n  4.3614399548619884E+00 a       160     0     7     1    10\n -1.6073795583709572E+01 a       161     0     7     1    11\n  1.6345358363876109E+01 a       162     0     7     1    12\n -8.4662611499242502E+00 a       163     0     7     1    13\n  8.0952183951712298E-01 a       164     0     7     1    14\n -1.1658877435292819E+01 a       165     0     7     1    15\n  1.3236001648494756E+01 a       166     0     7     1    16\n -1.2875720369407999E+01 a       167     0     7     1    17\n -2.0324369268053388E+00 a       168     0     7     1    18\n  1.0874203669721311E+01 a       169     0     7     1    19\n -1.7284078771261807E+01 a       170     0     7     1    20\n -2.9714643625232693E+00 a       171     0     7     1    21\n -1.9329510057793893E+01 a       172     0     7     1    22\n -1.0307360045133033E+01 a       173     0     7     1    23\n  4.2080100442235366E+00 a       174     0     7     1    24\n -3.8428801618815640E+01 a       175     0     7     1    25\n 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-6.0004075552166369E-01 a      1269     1    23     2    19\n  8.6767695096505049E-01 a      1270     1    23     2    20\n  1.7471709925670367E-01 a      1271     1    23     2    21\n  6.3494817986861019E-01 a      1272     1    23     2    22\n  7.9839233743975266E-02 a      1273     1    23     2    23\n -8.7497499907984810E-01 a      1274     1    23     2    24\n -2.1279336414401262E-01 a      1275     1    23     2    25\n -1.0628518357816100E+01 a      1276     1    24     2     1\n -3.4149879843865938E-01 a      1277     1    24     2     2\n -4.0534872173827868E-01 a      1278     1    24     2     3\n  1.0980204380257913E-01 a      1279     1    24     2     4\n  1.8376924276804879E-01 a      1280     1    24     2     5\n  8.5047887536146360E-01 a      1281     1    24     2     6\n  4.3913590571042438E-01 a      1282     1    24     2     7\n  2.7167430357232609E+00 a      1283     1    24     2     8\n  2.9682659556600960E-01 a      1284     1    24     2     9\n -1.6032245851281013E+00 a      1285     1    24     2    10\n -6.7567048640865046E-01 a      1286     1    24     2    11\n -1.5253382251900995E+00 a      1287     1    24     2    12\n -6.7540631566041298E-01 a      1288     1    24     2    13\n -1.4565321192168545E+00 a      1289     1    24     2    14\n -1.3315414628143039E+00 a      1290     1    24     2    15\n  1.2552098425264056E+00 a      1291     1    24     2    16\n -1.1701558601459501E+00 a      1292     1    24     2    17\n  2.1967564647703792E+00 a      1293     1    24     2    18\n  3.6767594091430167E-01 a      1294     1    24     2    19\n  1.4791781996464841E+00 a      1295     1    24     2    20\n -2.4597335939693896E+00 a      1296     1    24     2    21\n  1.8222789722776007E+00 a      1297     1    24     2    22\n -2.4818384588216302E+00 a      1298     1    24     2    23\n -1.3359962912345340E+00 a      1299     1    24     2    24\n -1.6060924344568878E-02 a      1300     1    24     2    25\n -1.1558703878945702E+00 a      1301     1    25     2     1\n  5.5859771317693908E-02 a      1302     1    25     2     2\n -1.9275021348316721E+00 a      1303     1    25     2     3\n  4.2881321046205173E-01 a      1304     1    25     2     4\n  6.6308764508018558E-01 a      1305     1    25     2     5\n -2.5357661809360188E-01 a      1306     1    25     2     6\n  7.7965409617466697E-01 a      1307     1    25     2     7\n -1.9470416731652336E+00 a      1308     1    25     2     8\n  2.0923659915641873E-01 a      1309     1    25     2     9\n  8.9211452410465542E-01 a      1310     1    25     2    10\n -1.9807939822570442E-01 a      1311     1    25     2    11\n -5.0922943173038127E-01 a      1312     1    25     2    12\n  1.3378430979044107E+00 a      1313     1    25     2    13\n -6.8964614083753073E-01 a      1314     1    25     2    14\n  7.6939619343191556E-01 a      1315     1    25     2    15\n -1.5783243312480257E+00 a      1316     1    25     2    16\n  2.3586020281744577E+00 a      1317     1    25     2    17\n -5.1641666185758928E-01 a      1318     1    25     2    18\n  1.0291540870545792E+00 a      1319     1    25     2    19\n  1.5269830348487650E+00 a      1320     1    25     2    20\n -2.8987700591417855E+00 a      1321     1    25     2    21\n  9.0207337792476916E-01 a      1322     1    25     2    22\n  1.9890049402284911E+00 a      1323     1    25     2    23\n  3.9387622927433424E-01 a      1324     1    25     2    24\n  9.9397126232482103E-01 a      1325     1    25     2    25\n  2.5306467041996967E+00 b      1326     2     1\n  3.1633393474977245E+00 b      1327     2     2\n -1.1644295509710691E+00 b      1328     2     3\n -5.7686722641223600E+00 b      1329     2     4\n  2.0065022303893989E+00 b      1330     2     5\n -5.9106057000795840E+00 b      1331     2     6\n -1.1326093285804056E+01 b      1332     2     7\n -3.9025063397327071E+00 b      1333     2     8\n  4.4520505166676267E+00 b      1334     2     9\n -1.7352681951318241E+00 b      1335     2    10\n -2.1518912430432668E+00 b      1336     2    11\n  5.0463376560082969E+00 b      1337     2    12\n -2.2614514173852837E-01 b      1338     2    13\n -4.1454590614747211E+00 b      1339     2    14\n  1.6688417293495756E+00 b      1340     2    15\n -5.8649976938793378E+00 b      1341     2    16\n -3.8350084459541849E+00 b      1342     2    17\n  1.3730477223722950E+00 b      1343     2    18\n  1.8506935712854127E+00 b      1344     2    19\n  5.7362757779153428E+00 b      1345     2    20\n  7.2901484895568780E+00 b      1346     2    21\n  3.9773783666446022E-01 b      1347     2    22\n -6.1298011242151409E+00 b      1348     2    23\n  9.9698755072742991E+00 b      1349     2    24\n  1.1801564149295556E+00 b      1350     2    25\n  1.2704098997067026E+01 a      1351     2     1     3     1\n  1.5947733940307620E+00 a      1352     2     2     3     1\n -1.6022927057878529E+00 a      1353     2     3     3     1\n -1.5507258540777733E+00 a      1354     2     4     3     1\n  1.8696884022727636E+00 a      1355     2     5     3     1\n -8.2051908880071633E-01 a      1356     2     6     3     1\n  9.4325719092522542E-01 a      1357     2     7     3     1\n  2.4098435369626174E+00 a      1358     2     8     3     1\n  1.4100759633042474E+00 a      1359     2     9     3     1\n -1.4613034838529613E+00 a      1360     2    10     3     1\n  1.0296574685193380E+00 a      1361     2    11     3     1\n  1.2413851904356363E+00 a      1362     2    12     3     1\n -6.3168181712211169E-01 a      1363     2    13     3     1\n  7.6424175125347729E+00 a      1364     2    14     3     1\n -1.3477038299214714E+00 a      1365     2    15     3     1\n -1.6064659765754943E+00 a      1366     2    16     3     1\n -8.9624380518145874E-01 a      1367     2    17     3     1\n -1.0509865792522375E+00 a      1368     2    18     3     1\n  8.1847872933853638E-01 a      1369     2    19     3     1\n  1.2845504810303034E+00 a      1370     2    20     3     1\n -5.1879822944368881E-01 a      1371     2    21     3     1\n -7.2018714033119180E-01 a      1372     2    22     3     1\n  5.9870832883780798E+00 a      1373     2    23     3     1\n -6.0589155387470683E-01 a      1374     2    24     3     1\n  5.0177609140285355E+00 a      1375     2    25     3     1\n  9.7386086372975722E+00 b      1376     3     1\n"
  },
  {
    "path": "examples/nnp-checkf/H2O_RPBE-D3/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -4.2252995889643252E-01 a         1     0     1     1     1\n -6.0555645962054347E+00 a         2     0     1     1     2\n  1.4040722027928377E+01 a         3     0     1     1     3\n -2.7041370011942618E+00 a         4     0     1     1     4\n -3.8202743208058858E+00 a         5     0     1     1     5\n -3.3612643261393358E+00 a         6     0     1     1     6\n -2.0418101025905258E+00 a         7     0     1     1     7\n  7.5707237340996727E+00 a         8     0     1     1     8\n -5.8098755815926548E+00 a         9     0     1     1     9\n -6.0966886893925210E-01 a        10     0     1     1    10\n  5.8061564015115206E+00 a        11     0     1     1    11\n -1.5509339733099867E+00 a        12     0     1     1    12\n  1.9747395485200818E+00 a        13     0     1     1    13\n  4.5260782279680539E-01 a        14     0     1     1    14\n  9.9210415760283279E+00 a        15     0     1     1    15\n -6.5078831481547121E+00 a        16     0     1     1    16\n -3.4768832871318085E+00 a        17     0     1     1    17\n -1.9463994340943838E+00 a        18     0     1     1    18\n -3.4186058699290269E+00 a        19     0     1     1    19\n  1.2263643166698479E+00 a        20     0     1     1    20\n -5.9171161834436594E+00 a        21     0     1     1    21\n  1.8436267358458363E+00 a        22     0     1     1    22\n -2.3139530616378448E+00 a        23     0     1     1    23\n -1.7228542411478951E+01 a        24     0     1     1    24\n  2.2888610253215895E+00 a        25     0     1     1    25\n  8.0819405565169262E+00 a        26     0     2     1     1\n  8.0066409422078735E+00 a        27     0     2     1     2\n -2.8439251469462398E+01 a        28     0     2     1     3\n -1.1146087290797917E+01 a        29     0     2     1     4\n -7.5292172093563314E+00 a        30     0     2     1     5\n -4.0783685663337641E+00 a        31     0     2     1     6\n -4.4130406528599337E+00 a        32     0     2     1     7\n  1.0563249167508673E+01 a        33     0     2     1     8\n  1.0933105521974941E+01 a        34     0     2     1     9\n -1.1646509907117448E+01 a        35     0     2     1    10\n -7.5007478428041727E+00 a        36     0     2     1    11\n  7.7790182254249176E+00 a        37     0     2     1    12\n  1.1567034492555623E+01 a        38     0     2     1    13\n -4.2051741520233508E+00 a        39     0     2     1    14\n  3.1165306119132130E+00 a        40     0     2     1    15\n  1.6385645103485370E+01 a        41     0     2     1    16\n  2.6440539124381655E+00 a        42     0     2     1    17\n -3.9524518111687827E+00 a        43     0     2     1    18\n -8.7912410635652076E+00 a        44     0     2     1    19\n  4.3903318583813933E+00 a        45     0     2     1    20\n  3.3748047065442632E-01 a        46     0     2     1    21\n -6.6858946327311741E-01 a        47     0     2     1    22\n  5.4447187026310928E+00 a        48     0     2     1    23\n  1.9966018946508100E+01 a        49     0     2     1    24\n -1.7414420670154115E+01 a        50     0     2     1    25\n -3.9418657694849879E-01 a        51     0     3     1     1\n  9.1804829174186846E+00 a        52     0     3     1     2\n -1.0485089041850278E+01 a        53     0     3     1     3\n  8.9380499555048889E+00 a        54     0     3     1     4\n  1.0758607876097068E+01 a        55     0     3     1     5\n  7.2881492125393788E+00 a        56     0     3     1     6\n  8.2627077997774609E+00 a        57     0     3     1     7\n -1.2523613158520124E+01 a        58     0     3     1     8\n  4.5963999046141870E+00 a        59     0     3     1     9\n  8.2776469521184293E+00 a        60     0     3     1    10\n -2.1354371687617113E+00 a        61     0     3     1    11\n -9.0381751821938234E+00 a        62     0     3     1    12\n -1.2209592338152297E+00 a        63     0     3     1    13\n  4.7653671372245672E+00 a        64     0     3     1    14\n -1.7909124818088952E+01 a        65     0     3     1    15\n  3.2182917515973237E+00 a        66     0     3     1    16\n -2.3712750109800793E+00 a        67     0     3     1    17\n  4.6394007836500366E+00 a        68     0     3     1    18\n  2.3761984937954490E+00 a        69     0     3     1    19\n -1.0484832585147684E+01 a        70     0     3     1    20\n  1.2317970755621140E+01 a        71     0     3     1    21\n -1.5014054499447769E+00 a        72     0     3     1    22\n -1.1215435083480425E+00 a        73     0     3     1    23\n  8.9428653321614355E+00 a        74     0     3     1    24\n  1.2636165742848842E+00 a        75     0     3     1    25\n -1.3406492086741725E+01 a        76     0     4     1     1\n -1.0241053204283523E+01 a        77     0     4     1     2\n  4.3016369326050899E+01 a        78     0     4     1     3\n  2.0170433813810671E+01 a        79     0     4     1     4\n  1.3209328101408278E+01 a        80     0     4     1     5\n  1.2456789467161695E+01 a        81     0     4     1     6\n  4.3498515722861573E+00 a        82     0     4     1     7\n -2.1948185511490657E+01 a        83     0     4     1     8\n -1.5329558038416376E+01 a        84     0     4     1     9\n  1.4173337432869845E+01 a        85     0     4     1    10\n  5.6040631650516088E+00 a        86     0     4     1    11\n -9.7646834958548663E+00 a        87     0     4     1    12\n -1.3810669587629080E+01 a        88     0     4     1    13\n -1.5274915717855073E+00 a        89     0     4     1    14\n -1.3662043326477198E+01 a        90     0     4     1    15\n -2.5095635769057225E+01 a        91     0     4     1    16\n  5.4033548590960638E+00 a        92     0     4     1    17\n  1.1047593171711565E+01 a        93     0     4     1    18\n  1.9404912122904062E+01 a        94     0     4     1    19\n  2.4043652449872512E+00 a        95     0     4     1    20\n -3.3818087825635010E+00 a        96     0     4     1    21\n -4.9505657938825802E+00 a        97     0     4     1    22\n  6.2159614529590854E+00 a        98     0     4     1    23\n -1.9315299866781363E+01 a        99     0     4     1    24\n  2.4149549923763363E+01 a       100     0     4     1    25\n  2.2633190213689671E+00 a       101     0     5     1     1\n -1.1275056403465689E+01 a       102     0     5     1     2\n  1.2588751117785917E+00 a       103     0     5     1     3\n -1.7399288116611554E+01 a       104     0     5     1     4\n -1.8915392010979964E+01 a       105     0     5     1     5\n -6.5088880348621911E+00 a       106     0     5     1     6\n -8.7022768117985532E+00 a       107     0     5     1     7\n  9.5716939158219958E+00 a       108     0     5     1     8\n  6.7173652175539926E+00 a       109     0     5     1     9\n -1.0675975211687946E+01 a       110     0     5     1    10\n -9.8676303718126039E+00 a       111     0     5     1    11\n  2.2213929552875065E+01 a       112     0     5     1    12\n -3.9036053816020080E+00 a       113     0     5     1    13\n -1.0319098765495239E+01 a       114     0     5     1    14\n  2.0443220229254024E+01 a       115     0     5     1    15\n -1.4108663925115768E+00 a       116     0     5     1    16\n  8.2741724462704607E+00 a       117     0     5     1    17\n -5.3497533478370061E+00 a       118     0     5     1    18\n  1.0188467515179238E+00 a       119     0     5     1    19\n  3.3447636806848529E+00 a       120     0     5     1    20\n -6.3209134939668381E+00 a       121     0     5     1    21\n  7.0841649292282804E+00 a       122     0     5     1    22\n -1.3545092924552248E+01 a       123     0     5     1    23\n -1.0559922896741500E+00 a       124     0     5     1    24\n -1.6720809451360648E+00 a       125     0     5     1    25\n  2.8772403595811382E+00 a       126     0     6     1     1\n  6.6056181351338488E+00 a       127     0     6     1     2\n -2.1395393088585266E+01 a       128     0     6     1     3\n -1.6735909985964671E+01 a       129     0     6     1     4\n -4.4466039540570526E+00 a       130     0     6     1     5\n -1.9134274750411421E+01 a       131     0     6     1     6\n  7.4840405517853625E+00 a       132     0     6     1     7\n  1.5375004378912831E+01 a       133     0     6     1     8\n -3.2781218210557539E-01 a       134     0     6     1     9\n  5.1424696656729978E+00 a       135     0     6     1    10\n  2.4028588442306344E+00 a       136     0     6     1    11\n  1.6576032835324068E+00 a       137     0     6     1    12\n -1.8331489599850683E+00 a       138     0     6     1    13\n  1.5714883034771246E+01 a       139     0     6     1    14\n  1.3932522318533026E+01 a       140     0     6     1    15\n  3.0252340531342401E+01 a       141     0     6     1    16\n -2.0172838001093005E+01 a       142     0     6     1    17\n -1.3208548828817202E+01 a       143     0     6     1    18\n -1.1333313633908213E+01 a       144     0     6     1    19\n -2.2075367220543007E-01 a       145     0     6     1    20\n  5.4183716265511874E+00 a       146     0     6     1    21\n  4.4469214579975294E+00 a       147     0     6     1    22\n -1.7974421141420628E+01 a       148     0     6     1    23\n  1.3331466657294333E+01 a       149     0     6     1    24\n -1.0273470133062483E+01 a       150     0     6     1    25\n -1.3893961251032516E+00 a       151     0     7     1     1\n  4.8442398001659086E+00 a       152     0     7     1     2\n -1.4036072623897150E+01 a       153     0     7     1     3\n  1.9115742411572878E+01 a       154     0     7     1     4\n  1.7609386484170951E+01 a       155     0     7     1     5\n  7.6541742060341660E+00 a       156     0     7     1     6\n  2.6652782695389745E+00 a       157     0     7     1     7\n -4.1794554937287582E+00 a       158     0     7     1     8\n -1.1905203283691870E+01 a       159     0     7     1     9\n  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-1.2648655109330131E+00 a      1253     1    20     2     3\n -4.3905910522706337E-01 a      1254     1    20     2     4\n  4.2887555555714030E-01 a      1255     1    20     2     5\n  1.3300944280643934E+00 a      1256     1    20     2     6\n  1.0988390404457922E+00 a      1257     1    20     2     7\n  2.3801051936039075E+00 a      1258     1    20     2     8\n  1.1789379212300943E-01 a      1259     1    20     2     9\n  3.9144297908957699E+00 a      1260     1    20     2    10\n  5.5000952527940228E-01 a      1261     1    20     2    11\n  2.4087943927489916E-01 a      1262     1    20     2    12\n -3.7997171313505251E-01 a      1263     1    20     2    13\n -5.4744714104500347E-01 a      1264     1    20     2    14\n  8.9095280999944937E-01 a      1265     1    20     2    15\n -8.7130940035564164E-01 a      1266     1    20     2    16\n  3.7900358553306007E-01 a      1267     1    20     2    17\n  2.1342515402584987E+00 a      1268     1    20     2    18\n  1.2475880574414706E+00 a      1269     1    20     2    19\n  7.8956439485340524E-01 a      1270     1    20     2    20\n  4.6968348528891219E+00 a      1271     1    20     2    21\n  2.4464240930319816E+00 a      1272     1    20     2    22\n -5.7785142905302376E+00 a      1273     1    20     2    23\n -2.3074149497856417E-01 a      1274     1    20     2    24\n -2.6800082940155296E+00 a      1275     1    20     2    25\n -3.2729577955630704E+00 a      1276     1    21     2     1\n -1.2928637501931926E+00 a      1277     1    21     2     2\n -2.2664219916515152E-01 a      1278     1    21     2     3\n  6.8197406796553048E-02 a      1279     1    21     2     4\n  2.2800043902454539E-01 a      1280     1    21     2     5\n -1.4547709606717896E+00 a      1281     1    21     2     6\n -8.9797316703694119E-02 a      1282     1    21     2     7\n -7.9615421262219899E-01 a      1283     1    21     2     8\n -2.5074736863647562E-01 a      1284     1    21     2     9\n -3.2383137185187805E-01 a      1285     1    21     2    10\n -7.7486670060442631E-01 a      1286     1    21     2    11\n -1.7378145875987788E-01 a      1287     1    21     2    12\n  1.7001762592878558E+00 a      1288     1    21     2    13\n -1.7033999809142997E+00 a      1289     1    21     2    14\n  3.7961258225336264E-01 a      1290     1    21     2    15\n  6.0929689839357426E-01 a      1291     1    21     2    16\n -1.9171250145280534E+00 a      1292     1    21     2    17\n -1.6594854242769004E+00 a      1293     1    21     2    18\n -2.8219229087100910E+00 a      1294     1    21     2    19\n -4.3902463688638738E-01 a      1295     1    21     2    20\n -1.1744026035352828E+00 a      1296     1    21     2    21\n  3.9648025457334164E+00 a      1297     1    21     2    22\n -1.3587513635268793E+00 a      1298     1    21     2    23\n  3.9463311556495906E-02 a      1299     1    21     2    24\n -4.6280624473662763E-01 a      1300     1    21     2    25\n  8.3725910272757709E+00 a      1301     1    22     2     1\n  1.2030400911595496E+00 a      1302     1    22     2     2\n  5.2723639396495003E-01 a      1303     1    22     2     3\n  2.4863416823271995E+00 a      1304     1    22     2     4\n  5.0656775645932173E-01 a      1305     1    22     2     5\n  7.8889662692367113E-01 a      1306     1    22     2     6\n  2.7467021112668549E-01 a      1307     1    22     2     7\n  3.5551997281423904E+00 a      1308     1    22     2     8\n -6.9074567194666425E-01 a      1309     1    22     2     9\n  9.2831069742658789E-01 a      1310     1    22     2    10\n -2.7305664188353734E-01 a      1311     1    22     2    11\n -1.6732686793215996E+00 a      1312     1    22     2    12\n -1.2508123463191103E+00 a      1313     1    22     2    13\n  1.4253551144285490E+00 a      1314     1    22     2    14\n -1.2730453204508483E+00 a      1315     1    22     2    15\n -5.6234386233504563E-01 a      1316     1    22     2    16\n  4.7348930208036427E-01 a      1317     1    22     2    17\n  1.4228359329011722E+00 a      1318     1    22     2    18\n -3.0896237212805277E-02 a      1319     1    22     2    19\n -7.7625773033108136E-01 a      1320     1    22     2    20\n  5.1571228251110171E-02 a      1321     1    22     2    21\n -1.5781774955827834E+00 a      1322     1    22     2    22\n -1.7313703986673430E+00 a      1323     1    22     2    23\n -1.3316987118953665E+00 a      1324     1    22     2    24\n -7.0760527312605037E-01 a      1325     1    22     2    25\n -8.1466385165616928E-01 a      1326     1    23     2     1\n  6.8912340727205368E-01 a      1327     1    23     2     2\n  8.4582890184800619E-01 a      1328     1    23     2     3\n  3.8163700575566650E-01 a      1329     1    23     2     4\n -6.6556600373886232E-01 a      1330     1    23     2     5\n -1.3399458536680564E+00 a      1331     1    23     2     6\n -1.7425009694107033E-01 a      1332     1    23     2     7\n -2.6104662248332646E+00 a      1333     1    23     2     8\n -1.9788280313555501E-01 a      1334     1    23     2     9\n -4.6341960827595043E+00 a      1335     1    23     2    10\n -4.1560774205921192E-01 a      1336     1    23     2    11\n -1.3453315295733928E-01 a      1337     1    23     2    12\n  5.9251987079212687E-01 a      1338     1    23     2    13\n  1.3014540212114664E-01 a      1339     1    23     2    14\n  2.4962768316839337E-01 a      1340     1    23     2    15\n  3.3868458734074913E-01 a      1341     1    23     2    16\n -2.1103970517135956E-01 a      1342     1    23     2    17\n -2.7311756320323316E-01 a      1343     1    23     2    18\n  7.7825779463422798E-02 a      1344     1    23     2    19\n -1.5510879185574573E+00 a      1345     1    23     2    20\n -3.3731285186903501E+00 a      1346     1    23     2    21\n  1.5012690395440691E+00 a      1347     1    23     2    22\n -1.4938786629136067E+00 a      1348     1    23     2    23\n  1.5155834326942672E-01 a      1349     1    23     2    24\n  2.2135367884980521E+00 a      1350     1    23     2    25\n  7.6092107307961931E-01 a      1351     1    24     2     1\n  2.5019321183393825E-02 a      1352     1    24     2     2\n  2.4714648764760871E-01 a      1353     1    24     2     3\n -4.2700090187223255E-01 a      1354     1    24     2     4\n  1.9684439924637190E-01 a      1355     1    24     2     5\n -1.6150658390090172E-01 a      1356     1    24     2     6\n -8.4941771549071021E-01 a      1357     1    24     2     7\n  3.2616941337700417E-01 a      1358     1    24     2     8\n -6.0235251095177200E-01 a      1359     1    24     2     9\n  2.0073315297316108E+00 a      1360     1    24     2    10\n  6.8678637919958119E-01 a      1361     1    24     2    11\n -1.4709309602563259E+00 a      1362     1    24     2    12\n -7.3119546383323997E-01 a      1363     1    24     2    13\n  5.9624465461749732E-01 a      1364     1    24     2    14\n  1.1965703107989687E+00 a      1365     1    24     2    15\n -4.8078015734066326E-01 a      1366     1    24     2    16\n  2.8731897539798784E-01 a      1367     1    24     2    17\n  2.8943049077679879E+00 a      1368     1    24     2    18\n  4.4309374097560666E-01 a      1369     1    24     2    19\n -5.2571668466848664E-01 a      1370     1    24     2    20\n  2.6293009755349539E+00 a      1371     1    24     2    21\n  1.1166360248787797E+00 a      1372     1    24     2    22\n  1.4367909042068954E+00 a      1373     1    24     2    23\n  1.2263949730702137E+00 a      1374     1    24     2    24\n -1.5658327417588482E+00 a      1375     1    24     2    25\n -3.0524380712257440E+00 a      1376     1    25     2     1\n -1.6248402538917406E-01 a      1377     1    25     2     2\n  5.3725239557723847E-01 a      1378     1    25     2     3\n -3.1435543583372311E-01 a      1379     1    25     2     4\n  8.0294309812719877E-01 a      1380     1    25     2     5\n -3.3745709161028831E-01 a      1381     1    25     2     6\n  2.9618139473335392E-01 a      1382     1    25     2     7\n -1.3606606680314999E+00 a      1383     1    25     2     8\n  2.9886863438452965E-01 a      1384     1    25     2     9\n  3.4365095196288835E+00 a      1385     1    25     2    10\n  2.8778063903425566E-01 a      1386     1    25     2    11\n -5.2312889094867954E-01 a      1387     1    25     2    12\n  4.5730896273705224E-01 a      1388     1    25     2    13\n -8.8949447500584955E-01 a      1389     1    25     2    14\n -8.1389897744929640E-01 a      1390     1    25     2    15\n -4.0077086298379117E-01 a      1391     1    25     2    16\n  7.2544627916775950E-01 a      1392     1    25     2    17\n -9.8029709488119798E-01 a      1393     1    25     2    18\n  8.5017837869712165E-01 a      1394     1    25     2    19\n -2.9795775527520296E-01 a      1395     1    25     2    20\n  1.1940911570260535E+00 a      1396     1    25     2    21\n -4.1259772504588357E-02 a      1397     1    25     2    22\n  1.0619824936744515E+00 a      1398     1    25     2    23\n -6.5325825341918264E-01 a      1399     1    25     2    24\n  3.7575240210802421E+00 a      1400     1    25     2    25\n -1.0787018434494783E+01 b      1401     2     1\n -8.4067078142086771E-01 b      1402     2     2\n  9.3201271110229211E-01 b      1403     2     3\n -1.8318272256547821E+00 b      1404     2     4\n -2.1732436845179119E+00 b      1405     2     5\n -2.6390929073478930E+00 b      1406     2     6\n  3.7489748853957300E-01 b      1407     2     7\n -2.3789675524866163E+00 b      1408     2     8\n  2.7252644932624959E+00 b      1409     2     9\n  2.5100559841854970E+00 b      1410     2    10\n -2.4897033671113025E-01 b      1411     2    11\n  2.6913296692082476E+00 b      1412     2    12\n  5.8162695990329221E+00 b      1413     2    13\n -1.5170700889568940E+00 b      1414     2    14\n  4.2121259244130220E+00 b      1415     2    15\n  2.2987725066596130E+00 b      1416     2    16\n -7.1493650128731911E-01 b      1417     2    17\n -3.9961443472349811E-01 b      1418     2    18\n  7.8083705485664430E+00 b      1419     2    19\n -4.0462773256448170E-01 b      1420     2    20\n -1.4333029489891109E+00 b      1421     2    21\n -4.9517224038431467E+00 b      1422     2    22\n  1.0702867307710989E+01 b      1423     2    23\n -9.7535853921453985E-01 b      1424     2    24\n  5.3161969295054172E+00 b      1425     2    25\n -5.1941647295982207E-01 a      1426     2     1     3     1\n -7.7346657642095373E-01 a      1427     2     2     3     1\n  1.4003893583106508E+00 a      1428     2     3     3     1\n  8.9188080044914464E-01 a      1429     2     4     3     1\n -2.0147808233792022E+00 a      1430     2     5     3     1\n -1.8131831735812174E+00 a      1431     2     6     3     1\n  3.3217884596641700E+00 a      1432     2     7     3     1\n -1.2675289031787327E+00 a      1433     2     8     3     1\n -1.2791140359120716E+00 a      1434     2     9     3     1\n  1.9731828075446340E+00 a      1435     2    10     3     1\n -2.3928332883234411E+00 a      1436     2    11     3     1\n -1.1755085043375486E+00 a      1437     2    12     3     1\n  2.6525670286472951E+00 a      1438     2    13     3     1\n -2.4861988521743901E+00 a      1439     2    14     3     1\n  1.2534500349238071E+00 a      1440     2    15     3     1\n  2.8804282010183990E+00 a      1441     2    16     3     1\n -2.0327745898215275E+00 a      1442     2    17     3     1\n -1.1760164122204946E+00 a      1443     2    18     3     1\n -9.9841804355412322E-01 a      1444     2    19     3     1\n -1.8663330516323837E+00 a      1445     2    20     3     1\n  6.3266049836286531E-01 a      1446     2    21     3     1\n  1.2025500357718348E+00 a      1447     2    22     3     1\n  1.1367820678861495E-01 a      1448     2    23     3     1\n -2.6481374255863193E+00 a      1449     2    24     3     1\n  5.2166795947347921E-01 a      1450     2    25     3     1\n  4.8693043186011655E+00 b      1451     3     1\n"
  },
  {
    "path": "examples/nnp-checkf/LJ/input.data",
    "content": "begin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.38564065E+01  -1.38564065E+01  -1.38564065E+01\natom   5.77350269E-01   5.77350269E-01   5.77350269E-01 Ne   0.00000000E+00   0.00000000E+00   1.38564065E+01   1.38564065E+01   1.38564065E+01\nenergy   0.00000000E+00\ncomment r =   1.00000000E+00, E =   0.00000000E+00, dEdr =  -2.40000000E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.14260918E+01  -1.14260918E+01  -1.14260918E+01\natom   5.83123772E-01   5.83123772E-01   5.83123772E-01 Ne   0.00000000E+00   0.00000000E+00   1.14260918E+01   1.14260918E+01   1.14260918E+01\nenergy  -2.18384040E-01\ncomment r =   1.01000000E+00, E =  -2.18384040E-01, dEdr =  -1.97905715E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -9.36007007E+00  -9.36007007E+00  -9.36007007E+00\natom   5.88897275E-01   5.88897275E-01   5.88897275E-01 Ne   0.00000000E+00   0.00000000E+00   9.36007007E+00   9.36007007E+00   9.36007007E+00\nenergy  -3.97912826E-01\ncomment r =   1.02000000E+00, E =  -3.97912826E-01, dEdr =  -1.62121169E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -7.60455062E+00  -7.60455062E+00  -7.60455062E+00\natom   5.94670777E-01   5.94670777E-01   5.94670777E-01 Ne   0.00000000E+00   0.00000000E+00   7.60455062E+00   7.60455062E+00   7.60455062E+00\nenergy  -5.44417506E-01\ncomment r =   1.03000000E+00, E =  -5.44417506E-01, dEdr =  -1.31714680E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -6.11386720E+00  -6.11386720E+00  -6.11386720E+00\natom   6.00444280E-01   6.00444280E-01   6.00444280E-01 Ne   0.00000000E+00   0.00000000E+00   6.11386720E+00   6.11386720E+00   6.11386720E+00\nenergy  -6.62869905E-01\ncomment r =   1.04000000E+00, E =  -6.62869905E-01, dEdr =  -1.05895286E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -4.84920700E+00  -4.84920700E+00  -4.84920700E+00\natom   6.06217783E-01   6.06217783E-01   6.06217783E-01 Ne   0.00000000E+00   0.00000000E+00   4.84920700E+00   4.84920700E+00   4.84920700E+00\nenergy  -7.57511914E-01\ncomment r =   1.05000000E+00, E =  -7.57511914E-01, dEdr =  -8.39907291E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -3.77754643E+00  -3.77754643E+00  -3.77754643E+00\natom   6.11991285E-01   6.11991285E-01   6.11991285E-01 Ne   0.00000000E+00   0.00000000E+00   3.77754643E+00   3.77754643E+00   3.77754643E+00\nenergy  -8.31964707E-01\ncomment r =   1.06000000E+00, E =  -8.31964707E-01, dEdr =  -6.54290234E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -2.87075857E+00  -2.87075857E+00  -2.87075857E+00\natom   6.17764788E-01   6.17764788E-01   6.17764788E-01 Ne   0.00000000E+00   0.00000000E+00   2.87075857E+00   2.87075857E+00   2.87075857E+00\nenergy  -8.89321058E-01\ncomment r =   1.07000000E+00, E =  -8.89321058E-01, dEdr =  -4.97229969E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -2.10486372E+00  -2.10486372E+00  -2.10486372E+00\natom   6.23538291E-01   6.23538291E-01   6.23538291E-01 Ne   0.00000000E+00   0.00000000E+00   2.10486372E+00   2.10486372E+00   2.10486372E+00\nenergy  -9.32223473E-01\ncomment r =   1.08000000E+00, E =  -9.32223473E-01, dEdr =  -3.64573090E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.45939898E+00  -1.45939898E+00  -1.45939898E+00\natom   6.29311793E-01   6.29311793E-01   6.29311793E-01 Ne   0.00000000E+00   0.00000000E+00   1.45939898E+00   1.45939898E+00   1.45939898E+00\nenergy  -9.62930407E-01\ncomment r =   1.09000000E+00, E =  -9.62930407E-01, dEdr =  -2.52775317E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -9.16887301E-01  -9.16887301E-01  -9.16887301E-01\natom   6.35085296E-01   6.35085296E-01   6.35085296E-01 Ne   0.00000000E+00   0.00000000E+00   9.16887301E-01   9.16887301E-01   9.16887301E-01\nenergy  -9.83372449E-01\ncomment r =   1.10000000E+00, E =  -9.83372449E-01, dEdr =  -1.58809539E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -4.62389671E-01  -4.62389671E-01  -4.62389671E-01\natom   6.40858799E-01   6.40858799E-01   6.40858799E-01 Ne   0.00000000E+00   0.00000000E+00   4.62389671E-01   4.62389671E-01   4.62389671E-01\nenergy  -9.95200050E-01\ncomment r =   1.11000000E+00, E =  -9.95200050E-01, dEdr =  -8.00882403E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -8.31268676E-02  -8.31268676E-02  -8.31268676E-02\natom   6.46632301E-01   6.46632301E-01   6.46632301E-01 Ne   0.00000000E+00   0.00000000E+00   8.31268676E-02   8.31268676E-02   8.31268676E-02\nenergy  -9.99824113E-01\ncomment r =   1.12000000E+00, E =  -9.99824113E-01, dEdr =  -1.43979958E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.31840388E-01   2.31840388E-01   2.31840388E-01\natom   6.52405804E-01   6.52405804E-01   6.52405804E-01 Ne   0.00000000E+00   0.00000000E+00  -2.31840388E-01  -2.31840388E-01  -2.31840388E-01\nenergy  -9.98450559E-01\ncomment r =   1.13000000E+00, E =  -9.98450559E-01, dEdr =   4.01559331E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.91882287E-01   4.91882287E-01   4.91882287E-01\natom   6.58179307E-01   6.58179307E-01   6.58179307E-01 Ne   0.00000000E+00   0.00000000E+00  -4.91882287E-01  -4.91882287E-01  -4.91882287E-01\nenergy  -9.92109781E-01\ncomment r =   1.14000000E+00, E =  -9.92109781E-01, dEdr =   8.51965112E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.05029571E-01   7.05029571E-01   7.05029571E-01\natom   6.63952810E-01   6.63952810E-01   6.63952810E-01 Ne   0.00000000E+00   0.00000000E+00  -7.05029571E-01  -7.05029571E-01  -7.05029571E-01\nenergy  -9.81681783E-01\ncomment r =   1.15000000E+00, E =  -9.81681783E-01, dEdr =   1.22114704E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.78168464E-01   8.78168464E-01   8.78168464E-01\natom   6.69726312E-01   6.69726312E-01   6.69726312E-01 Ne   0.00000000E+00   0.00000000E+00  -8.78168464E-01  -8.78168464E-01  -8.78168464E-01\nenergy  -9.67917641E-01\ncomment r =   1.16000000E+00, E =  -9.67917641E-01, dEdr =   1.52103240E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.01720634E+00   1.01720634E+00   1.01720634E+00\natom   6.75499815E-01   6.75499815E-01   6.75499815E-01 Ne   0.00000000E+00   0.00000000E+00  -1.01720634E+00  -1.01720634E+00  -1.01720634E+00\nenergy  -9.51457857E-01\ncomment r =   1.17000000E+00, E =  -9.51457857E-01, dEdr =   1.76185306E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.12721266E+00   1.12721266E+00   1.12721266E+00\natom   6.81273318E-01   6.81273318E-01   6.81273318E-01 Ne   0.00000000E+00   0.00000000E+00  -1.12721266E+00  -1.12721266E+00  -1.12721266E+00\nenergy  -9.32848056E-01\ncomment r =   1.18000000E+00, E =  -9.32848056E-01, dEdr =   1.95238960E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.21253907E+00   1.21253907E+00   1.21253907E+00\natom   6.87046820E-01   6.87046820E-01   6.87046820E-01 Ne   0.00000000E+00   0.00000000E+00  -1.21253907E+00  -1.21253907E+00  -1.21253907E+00\nenergy  -9.12552436E-01\ncomment r =   1.19000000E+00, E =  -9.12552436E-01, dEdr =   2.10017928E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.27692175E+00   1.27692175E+00   1.27692175E+00\natom   6.92820323E-01   6.92820323E-01   6.92820323E-01 Ne   0.00000000E+00   0.00000000E+00  -1.27692175E+00  -1.27692175E+00  -1.27692175E+00\nenergy  -8.90965288E-01\ncomment r =   1.20000000E+00, E =  -8.90965288E-01, dEdr =   2.21169334E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.32356877E+00   1.32356877E+00   1.32356877E+00\natom   6.98593826E-01   6.98593826E-01   6.98593826E-01 Ne   0.00000000E+00   0.00000000E+00  -1.32356877E+00  -1.32356877E+00  -1.32356877E+00\nenergy  -8.68420879E-01\ncomment r =   1.21000000E+00, E =  -8.68420879E-01, dEdr =   2.29248836E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.35523484E+00   1.35523484E+00   1.35523484E+00\natom   7.04367328E-01   7.04367328E-01   7.04367328E-01 Ne   0.00000000E+00   0.00000000E+00  -1.35523484E+00  -1.35523484E+00  -1.35523484E+00\nenergy  -8.45201938E-01\ncomment r =   1.22000000E+00, E =  -8.45201938E-01, dEdr =   2.34733561E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.37428509E+00   1.37428509E+00   1.37428509E+00\natom   7.10140831E-01   7.10140831E-01   7.10140831E-01 Ne   0.00000000E+00   0.00000000E+00  -1.37428509E+00  -1.37428509E+00  -1.37428509E+00\nenergy  -8.21546940E-01\ncomment r =   1.23000000E+00, E =  -8.21546940E-01, dEdr =   2.38033160E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38274975E+00   1.38274975E+00   1.38274975E+00\natom   7.15914334E-01   7.15914334E-01   7.15914334E-01 Ne   0.00000000E+00   0.00000000E+00  -1.38274975E+00  -1.38274975E+00  -1.38274975E+00\nenergy  -7.97656367E-01\ncomment r =   1.24000000E+00, E =  -7.97656367E-01, dEdr =   2.39499283E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38237105E+00   1.38237105E+00   1.38237105E+00\natom   7.21687836E-01   7.21687836E-01   7.21687836E-01 Ne   0.00000000E+00   0.00000000E+00  -1.38237105E+00  -1.38237105E+00  -1.38237105E+00\nenergy  -7.73698093E-01\ncomment r =   1.25000000E+00, E =  -7.73698093E-01, dEdr =   2.39433689E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.37464330E+00   1.37464330E+00   1.37464330E+00\natom   7.27461339E-01   7.27461339E-01   7.27461339E-01 Ne   0.00000000E+00   0.00000000E+00  -1.37464330E+00  -1.37464330E+00  -1.37464330E+00\nenergy  -7.49812018E-01\ncomment r =   1.26000000E+00, E =  -7.49812018E-01, dEdr =   2.38095204E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.36084745E+00   1.36084745E+00   1.36084745E+00\natom   7.33234842E-01   7.33234842E-01   7.33234842E-01 Ne   0.00000000E+00   0.00000000E+00  -1.36084745E+00  -1.36084745E+00  -1.36084745E+00\nenergy  -7.26114051E-01\ncomment r =   1.27000000E+00, E =  -7.26114051E-01, dEdr =   2.35705692E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.34208064E+00   1.34208064E+00   1.34208064E+00\natom   7.39008345E-01   7.39008345E-01   7.39008345E-01 Ne   0.00000000E+00   0.00000000E+00  -1.34208064E+00  -1.34208064E+00  -1.34208064E+00\nenergy  -7.02699549E-01\ncomment r =   1.28000000E+00, E =  -7.02699549E-01, dEdr =   2.32455185E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.31928169E+00   1.31928169E+00   1.31928169E+00\natom   7.44781847E-01   7.44781847E-01   7.44781847E-01 Ne   0.00000000E+00   0.00000000E+00  -1.31928169E+00  -1.31928169E+00  -1.31928169E+00\nenergy  -6.79646267E-01\ncomment r =   1.29000000E+00, E =  -6.79646267E-01, dEdr =   2.28506292E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.29325302E+00   1.29325302E+00   1.29325302E+00\natom   7.50555350E-01   7.50555350E-01   7.50555350E-01 Ne   0.00000000E+00   0.00000000E+00  -1.29325302E+00  -1.29325302E+00  -1.29325302E+00\nenergy  -6.57016914E-01\ncomment r =   1.30000000E+00, E =  -6.57016914E-01, dEdr =   2.23997993E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.26467942E+00   1.26467942E+00   1.26467942E+00\natom   7.56328853E-01   7.56328853E-01   7.56328853E-01 Ne   0.00000000E+00   0.00000000E+00  -1.26467942E+00  -1.26467942E+00  -1.26467942E+00\nenergy  -6.34861342E-01\ncomment r =   1.31000000E+00, E =  -6.34861342E-01, dEdr =   2.19048901E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.23414440E+00   1.23414440E+00   1.23414440E+00\natom   7.62102355E-01   7.62102355E-01   7.62102355E-01 Ne   0.00000000E+00   0.00000000E+00  -1.23414440E+00  -1.23414440E+00  -1.23414440E+00\nenergy  -6.13218442E-01\ncomment r =   1.32000000E+00, E =  -6.13218442E-01, dEdr =   2.13760080E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.20214407E+00   1.20214407E+00   1.20214407E+00\natom   7.67875858E-01   7.67875858E-01   7.67875858E-01 Ne   0.00000000E+00   0.00000000E+00  -1.20214407E+00  -1.20214407E+00  -1.20214407E+00\nenergy  -5.92117772E-01\ncomment r =   1.33000000E+00, E =  -5.92117772E-01, dEdr =   2.08217461E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.16909931E+00   1.16909931E+00   1.16909931E+00\natom   7.73649361E-01   7.73649361E-01   7.73649361E-01 Ne   0.00000000E+00   0.00000000E+00  -1.16909931E+00  -1.16909931E+00  -1.16909931E+00\nenergy  -5.71580967E-01\ncomment r =   1.34000000E+00, E =  -5.71580967E-01, dEdr =   2.02493940E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.13536610E+00   1.13536610E+00   1.13536610E+00\natom   7.79422863E-01   7.79422863E-01   7.79422863E-01 Ne   0.00000000E+00   0.00000000E+00  -1.13536610E+00  -1.13536610E+00  -1.13536610E+00\nenergy  -5.51622948E-01\ncomment r =   1.35000000E+00, E =  -5.51622948E-01, dEdr =   1.96651177E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.10124456E+00   1.10124456E+00   1.10124456E+00\natom   7.85196366E-01   7.85196366E-01   7.85196366E-01 Ne   0.00000000E+00   0.00000000E+00  -1.10124456E+00  -1.10124456E+00  -1.10124456E+00\nenergy  -5.32252964E-01\ncomment r =   1.36000000E+00, E =  -5.32252964E-01, dEdr =   1.90741154E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.06698669E+00   1.06698669E+00   1.06698669E+00\natom   7.90969869E-01   7.90969869E-01   7.90969869E-01 Ne   0.00000000E+00   0.00000000E+00  -1.06698669E+00  -1.06698669E+00  -1.06698669E+00\nenergy  -5.13475496E-01\ncomment r =   1.37000000E+00, E =  -5.13475496E-01, dEdr =   1.84807516E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.03280308E+00   1.03280308E+00   1.03280308E+00\natom   7.96743371E-01   7.96743371E-01   7.96743371E-01 Ne   0.00000000E+00   0.00000000E+00  -1.03280308E+00  -1.03280308E+00  -1.03280308E+00\nenergy  -4.95291026E-01\ncomment r =   1.38000000E+00, E =  -4.95291026E-01, dEdr =   1.78886740E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.98868680E-01   9.98868680E-01   9.98868680E-01\natom   8.02516874E-01   8.02516874E-01   8.02516874E-01 Ne   0.00000000E+00   0.00000000E+00  -9.98868680E-01  -9.98868680E-01  -9.98868680E-01\nenergy  -4.77696704E-01\ncomment r =   1.39000000E+00, E =  -4.77696704E-01, dEdr =   1.73009130E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.65327860E-01   9.65327860E-01   9.65327860E-01\natom   8.08290377E-01   8.08290377E-01   8.08290377E-01 Ne   0.00000000E+00   0.00000000E+00  -9.65327860E-01  -9.65327860E-01  -9.65327860E-01\nenergy  -4.60686922E-01\ncomment r =   1.40000000E+00, E =  -4.60686922E-01, dEdr =   1.67199690E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.32298690E-01   9.32298690E-01   9.32298690E-01\natom   8.14063880E-01   8.14063880E-01   8.14063880E-01 Ne   0.00000000E+00   0.00000000E+00  -9.32298690E-01  -9.32298690E-01  -9.32298690E-01\nenergy  -4.44253807E-01\ncomment r =   1.41000000E+00, E =  -4.44253807E-01, dEdr =   1.61478870E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.99876705E-01   8.99876705E-01   8.99876705E-01\natom   8.19837382E-01   8.19837382E-01   8.19837382E-01 Ne   0.00000000E+00   0.00000000E+00  -8.99876705E-01  -8.99876705E-01  -8.99876705E-01\nenergy  -4.28387639E-01\ncomment r =   1.42000000E+00, E =  -4.28387639E-01, dEdr =   1.55863217E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.68138141E-01   8.68138141E-01   8.68138141E-01\natom   8.25610885E-01   8.25610885E-01   8.25610885E-01 Ne   0.00000000E+00   0.00000000E+00  -8.68138141E-01  -8.68138141E-01  -8.68138141E-01\nenergy  -4.13077215E-01\ncomment r =   1.43000000E+00, E =  -4.13077215E-01, dEdr =   1.50365937E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.37142729E-01   8.37142729E-01   8.37142729E-01\natom   8.31384388E-01   8.31384388E-01   8.31384388E-01 Ne   0.00000000E+00   0.00000000E+00  -8.37142729E-01  -8.37142729E-01  -8.37142729E-01\nenergy  -3.98310158E-01\ncomment r =   1.44000000E+00, E =  -3.98310158E-01, dEdr =   1.44997374E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.06936119E-01   8.06936119E-01   8.06936119E-01\natom   8.37157890E-01   8.37157890E-01   8.37157890E-01 Ne   0.00000000E+00   0.00000000E+00  -8.06936119E-01  -8.06936119E-01  -8.06936119E-01\nenergy  -3.84073184E-01\ncomment r =   1.45000000E+00, E =  -3.84073184E-01, dEdr =   1.39765436E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.77551972E-01   7.77551972E-01   7.77551972E-01\natom   8.42931393E-01   8.42931393E-01   8.42931393E-01 Ne   0.00000000E+00   0.00000000E+00  -7.77551972E-01  -7.77551972E-01  -7.77551972E-01\nenergy  -3.70352321E-01\ncomment r =   1.46000000E+00, E =  -3.70352321E-01, dEdr =   1.34675952E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.49013769E-01   7.49013769E-01   7.49013769E-01\natom   8.48704896E-01   8.48704896E-01   8.48704896E-01 Ne   0.00000000E+00   0.00000000E+00  -7.49013769E-01  -7.49013769E-01  -7.49013769E-01\nenergy  -3.57133107E-01\ncomment r =   1.47000000E+00, E =  -3.57133107E-01, dEdr =   1.29732990E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.21336370E-01   7.21336370E-01   7.21336370E-01\natom   8.54478398E-01   8.54478398E-01   8.54478398E-01 Ne   0.00000000E+00   0.00000000E+00  -7.21336370E-01  -7.21336370E-01  -7.21336370E-01\nenergy  -3.44400751E-01\ncomment r =   1.48000000E+00, E =  -3.44400751E-01, dEdr =   1.24939124E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.94527370E-01   6.94527370E-01   6.94527370E-01\natom   8.60251901E-01   8.60251901E-01   8.60251901E-01 Ne   0.00000000E+00   0.00000000E+00  -6.94527370E-01  -6.94527370E-01  -6.94527370E-01\nenergy  -3.32140268E-01\ncomment r =   1.49000000E+00, E =  -3.32140268E-01, dEdr =   1.20295669E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.68588257E-01   6.68588257E-01   6.68588257E-01\natom   8.66025404E-01   8.66025404E-01   8.66025404E-01 Ne   0.00000000E+00   0.00000000E+00  -6.68588257E-01  -6.68588257E-01  -6.68588257E-01\nenergy  -3.20336594E-01\ncomment r =   1.50000000E+00, E =  -3.20336594E-01, dEdr =   1.15802883E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.43515424E-01   6.43515424E-01   6.43515424E-01\natom   8.71798906E-01   8.71798906E-01   8.71798906E-01 Ne   0.00000000E+00   0.00000000E+00  -6.43515424E-01  -6.43515424E-01  -6.43515424E-01\nenergy  -3.08974689E-01\ncomment r =   1.51000000E+00, E =  -3.08974689E-01, dEdr =   1.11460141E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.19301030E-01   6.19301030E-01   6.19301030E-01\natom   8.77572409E-01   8.77572409E-01   8.77572409E-01 Ne   0.00000000E+00   0.00000000E+00  -6.19301030E-01  -6.19301030E-01  -6.19301030E-01\nenergy  -2.98039609E-01\ncomment r =   1.52000000E+00, E =  -2.98039609E-01, dEdr =   1.07266085E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.95933747E-01   5.95933747E-01   5.95933747E-01\natom   8.83345912E-01   8.83345912E-01   8.83345912E-01 Ne   0.00000000E+00   0.00000000E+00  -5.95933747E-01  -5.95933747E-01  -5.95933747E-01\nenergy  -2.87516580E-01\ncomment r =   1.53000000E+00, E =  -2.87516580E-01, dEdr =   1.03218753E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.73399404E-01   5.73399404E-01   5.73399404E-01\natom   8.89119415E-01   8.89119415E-01   8.89119415E-01 Ne   0.00000000E+00   0.00000000E+00  -5.73399404E-01  -5.73399404E-01  -5.73399404E-01\nenergy  -2.77391049E-01\ncomment r =   1.54000000E+00, E =  -2.77391049E-01, dEdr =   9.93156900E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.51681534E-01   5.51681534E-01   5.51681534E-01\natom   8.94892917E-01   8.94892917E-01   8.94892917E-01 Ne   0.00000000E+00   0.00000000E+00  -5.51681534E-01  -5.51681534E-01  -5.51681534E-01\nenergy  -2.67648728E-01\ncomment r =   1.55000000E+00, E =  -2.67648728E-01, dEdr =   9.55540446E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.30761850E-01   5.30761850E-01   5.30761850E-01\natom   9.00666420E-01   9.00666420E-01   9.00666420E-01 Ne   0.00000000E+00   0.00000000E+00  -5.30761850E-01  -5.30761850E-01  -5.30761850E-01\nenergy  -2.58275632E-01\ncomment r =   1.56000000E+00, E =  -2.58275632E-01, dEdr =   9.19306492E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.10620650E-01   5.10620650E-01   5.10620650E-01\natom   9.06439923E-01   9.06439923E-01   9.06439923E-01 Ne   0.00000000E+00   0.00000000E+00  -5.10620650E-01  -5.10620650E-01  -5.10620650E-01\nenergy  -2.49258104E-01\ncomment r =   1.57000000E+00, E =  -2.49258104E-01, dEdr =   8.84420909E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.91237157E-01   4.91237157E-01   4.91237157E-01\natom   9.12213425E-01   9.12213425E-01   9.12213425E-01 Ne   0.00000000E+00   0.00000000E+00  -4.91237157E-01  -4.91237157E-01  -4.91237157E-01\nenergy  -2.40582839E-01\ncomment r =   1.58000000E+00, E =  -2.40582839E-01, dEdr =   8.50847714E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.72589820E-01   4.72589820E-01   4.72589820E-01\natom   9.17986928E-01   9.17986928E-01   9.17986928E-01 Ne   0.00000000E+00   0.00000000E+00  -4.72589820E-01  -4.72589820E-01  -4.72589820E-01\nenergy  -2.32236899E-01\ncomment r =   1.59000000E+00, E =  -2.32236899E-01, dEdr =   8.18549579E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.54656560E-01   4.54656560E-01   4.54656560E-01\natom   9.23760431E-01   9.23760431E-01   9.23760431E-01 Ne   0.00000000E+00   0.00000000E+00  -4.54656560E-01  -4.54656560E-01  -4.54656560E-01\nenergy  -2.24207724E-01\ncomment r =   1.60000000E+00, E =  -2.24207724E-01, dEdr =   7.87488261E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.37414983E-01   4.37414983E-01   4.37414983E-01\natom   9.29533933E-01   9.29533933E-01   9.29533933E-01 Ne   0.00000000E+00   0.00000000E+00  -4.37414983E-01  -4.37414983E-01  -4.37414983E-01\nenergy  -2.16483140E-01\ncomment r =   1.61000000E+00, E =  -2.16483140E-01, dEdr =   7.57624975E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.20842560E-01   4.20842560E-01   4.20842560E-01\natom   9.35307436E-01   9.35307436E-01   9.35307436E-01 Ne   0.00000000E+00   0.00000000E+00  -4.20842560E-01  -4.20842560E-01  -4.20842560E-01\nenergy  -2.09051362E-01\ncomment r =   1.62000000E+00, E =  -2.09051362E-01, dEdr =   7.28920696E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.04916775E-01   4.04916775E-01   4.04916775E-01\natom   9.41080939E-01   9.41080939E-01   9.41080939E-01 Ne   0.00000000E+00   0.00000000E+00  -4.04916775E-01  -4.04916775E-01  -4.04916775E-01\nenergy  -2.01900993E-01\ncomment r =   1.63000000E+00, E =  -2.01900993E-01, dEdr =   7.01336426E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.89615248E-01   3.89615248E-01   3.89615248E-01\natom   9.46854441E-01   9.46854441E-01   9.46854441E-01 Ne   0.00000000E+00   0.00000000E+00  -3.89615248E-01  -3.89615248E-01  -3.89615248E-01\nenergy  -1.95021029E-01\ncomment r =   1.64000000E+00, E =  -1.95021029E-01, dEdr =   6.74833406E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.74915846E-01   3.74915846E-01   3.74915846E-01\natom   9.52627944E-01   9.52627944E-01   9.52627944E-01 Ne   0.00000000E+00   0.00000000E+00  -3.74915846E-01  -3.74915846E-01  -3.74915846E-01\nenergy  -1.88400849E-01\ncomment r =   1.65000000E+00, E =  -1.88400849E-01, dEdr =   6.49373295E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.60796761E-01   3.60796761E-01   3.60796761E-01\natom   9.58401447E-01   9.58401447E-01   9.58401447E-01 Ne   0.00000000E+00   0.00000000E+00  -3.60796761E-01  -3.60796761E-01  -3.60796761E-01\nenergy  -1.82030213E-01\ncomment r =   1.66000000E+00, E =  -1.82030213E-01, dEdr =   6.24918320E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.47236580E-01   3.47236580E-01   3.47236580E-01\natom   9.64174950E-01   9.64174950E-01   9.64174950E-01 Ne   0.00000000E+00   0.00000000E+00  -3.47236580E-01  -3.47236580E-01  -3.47236580E-01\nenergy  -1.75899255E-01\ncomment r =   1.67000000E+00, E =  -1.75899255E-01, dEdr =   6.01431398E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.34214345E-01   3.34214345E-01   3.34214345E-01\natom   9.69948452E-01   9.69948452E-01   9.69948452E-01 Ne   0.00000000E+00   0.00000000E+00  -3.34214345E-01  -3.34214345E-01  -3.34214345E-01\nenergy  -1.69998479E-01\ncomment r =   1.68000000E+00, E =  -1.69998479E-01, dEdr =   5.78876226E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.21709594E-01   3.21709594E-01   3.21709594E-01\natom   9.75721955E-01   9.75721955E-01   9.75721955E-01 Ne   0.00000000E+00   0.00000000E+00  -3.21709594E-01  -3.21709594E-01  -3.21709594E-01\nenergy  -1.64318743E-01\ncomment r =   1.69000000E+00, E =  -1.64318743E-01, dEdr =   5.57217362E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.09702395E-01   3.09702395E-01   3.09702395E-01\natom   9.81495458E-01   9.81495458E-01   9.81495458E-01 Ne   0.00000000E+00   0.00000000E+00  -3.09702395E-01  -3.09702395E-01  -3.09702395E-01\nenergy  -1.58851259E-01\ncomment r =   1.70000000E+00, E =  -1.58851259E-01, dEdr =   5.36420284E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.98173372E-01   2.98173372E-01   2.98173372E-01\natom   9.87268960E-01   9.87268960E-01   9.87268960E-01 Ne   0.00000000E+00   0.00000000E+00  -2.98173372E-01  -2.98173372E-01  -2.98173372E-01\nenergy  -1.53587577E-01\ncomment r =   1.71000000E+00, E =  -1.53587577E-01, dEdr =   5.16451429E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.87103720E-01   2.87103720E-01   2.87103720E-01\natom   9.93042463E-01   9.93042463E-01   9.93042463E-01 Ne   0.00000000E+00   0.00000000E+00  -2.87103720E-01  -2.87103720E-01  -2.87103720E-01\nenergy  -1.48519579E-01\ncomment r =   1.72000000E+00, E =  -1.48519579E-01, dEdr =   4.97278230E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.76475222E-01   2.76475222E-01   2.76475222E-01\natom   9.98815966E-01   9.98815966E-01   9.98815966E-01 Ne   0.00000000E+00   0.00000000E+00  -2.76475222E-01  -2.76475222E-01  -2.76475222E-01\nenergy  -1.43639466E-01\ncomment r =   1.73000000E+00, E =  -1.43639466E-01, dEdr =   4.78869131E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.66270250E-01   2.66270250E-01   2.66270250E-01\natom   1.00458947E+00   1.00458947E+00   1.00458947E+00 Ne   0.00000000E+00   0.00000000E+00  -2.66270250E-01  -2.66270250E-01  -2.66270250E-01\nenergy  -1.38939751E-01\ncomment r =   1.74000000E+00, E =  -1.38939751E-01, dEdr =   4.61193602E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.56471773E-01   2.56471773E-01   2.56471773E-01\natom   1.01036297E+00   1.01036297E+00   1.01036297E+00 Ne   0.00000000E+00   0.00000000E+00  -2.56471773E-01  -2.56471773E-01  -2.56471773E-01\nenergy  -1.34413247E-01\ncomment r =   1.75000000E+00, E =  -1.34413247E-01, dEdr =   4.44222142E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.47063348E-01   2.47063348E-01   2.47063348E-01\natom   1.01613647E+00   1.01613647E+00   1.01613647E+00 Ne   0.00000000E+00   0.00000000E+00  -2.47063348E-01  -2.47063348E-01  -2.47063348E-01\nenergy  -1.30053056E-01\ncomment r =   1.76000000E+00, E =  -1.30053056E-01, dEdr =   4.27926272E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.38029122E-01   2.38029122E-01   2.38029122E-01\natom   1.02190998E+00   1.02190998E+00   1.02190998E+00 Ne   0.00000000E+00   0.00000000E+00  -2.38029122E-01  -2.38029122E-01  -2.38029122E-01\nenergy  -1.25852561E-01\ncomment r =   1.77000000E+00, E =  -1.25852561E-01, dEdr =   4.12278533E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.29353819E-01   2.29353819E-01   2.29353819E-01\natom   1.02768348E+00   1.02768348E+00   1.02768348E+00 Ne   0.00000000E+00   0.00000000E+00  -2.29353819E-01  -2.29353819E-01  -2.29353819E-01\nenergy  -1.21805413E-01\ncomment r =   1.78000000E+00, E =  -1.21805413E-01, dEdr =   3.97252467E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.21022735E-01   2.21022735E-01   2.21022735E-01\natom   1.03345698E+00   1.03345698E+00   1.03345698E+00 Ne   0.00000000E+00   0.00000000E+00  -2.21022735E-01  -2.21022735E-01  -2.21022735E-01\nenergy  -1.17905524E-01\ncomment r =   1.79000000E+00, E =  -1.17905524E-01, dEdr =   3.82822607E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.13021724E-01   2.13021724E-01   2.13021724E-01\natom   1.03923048E+00   1.03923048E+00   1.03923048E+00 Ne   0.00000000E+00   0.00000000E+00  -2.13021724E-01  -2.13021724E-01  -2.13021724E-01\nenergy  -1.14147056E-01\ncomment r =   1.80000000E+00, E =  -1.14147056E-01, dEdr =   3.68964449E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.05337187E-01   2.05337187E-01   2.05337187E-01\natom   1.04500399E+00   1.04500399E+00   1.04500399E+00 Ne   0.00000000E+00   0.00000000E+00  -2.05337187E-01  -2.05337187E-01  -2.05337187E-01\nenergy  -1.10524408E-01\ncomment r =   1.81000000E+00, E =  -1.10524408E-01, dEdr =   3.55654440E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.97956057E-01   1.97956057E-01   1.97956057E-01\natom   1.05077749E+00   1.05077749E+00   1.05077749E+00 Ne   0.00000000E+00   0.00000000E+00  -1.97956057E-01  -1.97956057E-01  -1.97956057E-01\nenergy  -1.07032215E-01\ncomment r =   1.82000000E+00, E =  -1.07032215E-01, dEdr =   3.42869948E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.90865785E-01   1.90865785E-01   1.90865785E-01\natom   1.05655099E+00   1.05655099E+00   1.05655099E+00 Ne   0.00000000E+00   0.00000000E+00  -1.90865785E-01  -1.90865785E-01  -1.90865785E-01\nenergy  -1.03665330E-01\ncomment r =   1.83000000E+00, E =  -1.03665330E-01, dEdr =   3.30589238E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.84054328E-01   1.84054328E-01   1.84054328E-01\natom   1.06232450E+00   1.06232450E+00   1.06232450E+00 Ne   0.00000000E+00   0.00000000E+00  -1.84054328E-01  -1.84054328E-01  -1.84054328E-01\nenergy  -1.00418821E-01\ncomment r =   1.84000000E+00, E =  -1.00418821E-01, dEdr =   3.18791447E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.77510126E-01   1.77510126E-01   1.77510126E-01\natom   1.06809800E+00   1.06809800E+00   1.06809800E+00 Ne   0.00000000E+00   0.00000000E+00  -1.77510126E-01  -1.77510126E-01  -1.77510126E-01\nenergy  -9.72879584E-02\ncomment r =   1.85000000E+00, E =  -9.72879584E-02, dEdr =   3.07456558E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.71222096E-01   1.71222096E-01   1.71222096E-01\natom   1.07387150E+00   1.07387150E+00   1.07387150E+00 Ne   0.00000000E+00   0.00000000E+00  -1.71222096E-01  -1.71222096E-01  -1.71222096E-01\nenergy  -9.42682107E-02\ncomment r =   1.86000000E+00, E =  -9.42682107E-02, dEdr =   2.96565370E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.65179609E-01   1.65179609E-01   1.65179609E-01\natom   1.07964500E+00   1.07964500E+00   1.07964500E+00 Ne   0.00000000E+00   0.00000000E+00  -1.65179609E-01  -1.65179609E-01  -1.65179609E-01\nenergy  -9.13552334E-02\ncomment r =   1.87000000E+00, E =  -9.13552334E-02, dEdr =   2.86099475E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.59372475E-01   1.59372475E-01   1.59372475E-01\natom   1.08541851E+00   1.08541851E+00   1.08541851E+00 Ne   0.00000000E+00   0.00000000E+00  -1.59372475E-01  -1.59372475E-01  -1.59372475E-01\nenergy  -8.85448625E-02\ncomment r =   1.88000000E+00, E =  -8.85448625E-02, dEdr =   2.76041225E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.53790932E-01   1.53790932E-01   1.53790932E-01\natom   1.09119201E+00   1.09119201E+00   1.09119201E+00 Ne   0.00000000E+00   0.00000000E+00  -1.53790932E-01  -1.53790932E-01  -1.53790932E-01\nenergy  -8.58331065E-02\ncomment r =   1.89000000E+00, E =  -8.58331065E-02, dEdr =   2.66373709E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.48425625E-01   1.48425625E-01   1.48425625E-01\natom   1.09696551E+00   1.09696551E+00   1.09696551E+00 Ne   0.00000000E+00   0.00000000E+00  -1.48425625E-01  -1.48425625E-01  -1.48425625E-01\nenergy  -8.32161399E-02\ncomment r =   1.90000000E+00, E =  -8.32161399E-02, dEdr =   2.57080724E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.43267593E-01   1.43267593E-01   1.43267593E-01\natom   1.10273901E+00   1.10273901E+00   1.10273901E+00 Ne   0.00000000E+00   0.00000000E+00  -1.43267593E-01  -1.43267593E-01  -1.43267593E-01\nenergy  -8.06902954E-02\ncomment r =   1.91000000E+00, E =  -8.06902954E-02, dEdr =   2.48146751E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38308255E-01   1.38308255E-01   1.38308255E-01\natom   1.10851252E+00   1.10851252E+00   1.10851252E+00 Ne   0.00000000E+00   0.00000000E+00  -1.38308255E-01  -1.38308255E-01  -1.38308255E-01\nenergy  -7.82520578E-02\ncomment r =   1.92000000E+00, E =  -7.82520578E-02, dEdr =   2.39556925E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.33539391E-01   1.33539391E-01   1.33539391E-01\natom   1.11428602E+00   1.11428602E+00   1.11428602E+00 Ne   0.00000000E+00   0.00000000E+00  -1.33539391E-01  -1.33539391E-01  -1.33539391E-01\nenergy  -7.58980573E-02\ncomment r =   1.93000000E+00, E =  -7.58980573E-02, dEdr =   2.31297011E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.28953134E-01   1.28953134E-01   1.28953134E-01\natom   1.12005952E+00   1.12005952E+00   1.12005952E+00 Ne   0.00000000E+00   0.00000000E+00  -1.28953134E-01  -1.28953134E-01  -1.28953134E-01\nenergy  -7.36250634E-02\ncomment r =   1.94000000E+00, E =  -7.36250634E-02, dEdr =   2.23353381E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.24541951E-01   1.24541951E-01   1.24541951E-01\natom   1.12583302E+00   1.12583302E+00   1.12583302E+00 Ne   0.00000000E+00   0.00000000E+00  -1.24541951E-01  -1.24541951E-01  -1.24541951E-01\nenergy  -7.14299790E-02\ncomment r =   1.95000000E+00, E =  -7.14299790E-02, dEdr =   2.15712986E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.20298629E-01   1.20298629E-01   1.20298629E-01\natom   1.13160653E+00   1.13160653E+00   1.13160653E+00 Ne   0.00000000E+00   0.00000000E+00  -1.20298629E-01  -1.20298629E-01  -1.20298629E-01\nenergy  -6.93098346E-02\ncomment r =   1.96000000E+00, E =  -6.93098346E-02, dEdr =   2.08363337E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.16216266E-01   1.16216266E-01   1.16216266E-01\natom   1.13738003E+00   1.13738003E+00   1.13738003E+00 Ne   0.00000000E+00   0.00000000E+00  -1.16216266E-01  -1.16216266E-01  -1.16216266E-01\nenergy  -6.72617830E-02\ncomment r =   1.97000000E+00, E =  -6.72617830E-02, dEdr =   2.01292477E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.12288255E-01   1.12288255E-01   1.12288255E-01\natom   1.14315353E+00   1.14315353E+00   1.14315353E+00 Ne   0.00000000E+00   0.00000000E+00  -1.12288255E-01  -1.12288255E-01  -1.12288255E-01\nenergy  -6.52830939E-02\ncomment r =   1.98000000E+00, E =  -6.52830939E-02, dEdr =   1.94488962E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.08508271E-01   1.08508271E-01   1.08508271E-01\natom   1.14892704E+00   1.14892704E+00   1.14892704E+00 Ne   0.00000000E+00   0.00000000E+00  -1.08508271E-01  -1.08508271E-01  -1.08508271E-01\nenergy  -6.33711491E-02\ncomment r =   1.99000000E+00, E =  -6.33711491E-02, dEdr =   1.87941839E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.04870264E-01   1.04870264E-01   1.04870264E-01\natom   1.15470054E+00   1.15470054E+00   1.15470054E+00 Ne   0.00000000E+00   0.00000000E+00  -1.04870264E-01  -1.04870264E-01  -1.04870264E-01\nenergy  -6.15234375E-02\ncomment r =   2.00000000E+00, E =  -6.15234375E-02, dEdr =   1.81640625E-01\nend\n"
  },
  {
    "path": "examples/nnp-checkf/LJ/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              1              # Number of elements.\nelements                        Ne             # Specification of elements.\n#atom_energy                     Ne 0.0         # Free atom reference energy (Ne).\ncutoff_type                     2              # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      1              # Number of hidden layers.\nglobal_nodes_short              3              # Number of nodes in each hidden layer.\nglobal_activation_short         t l            # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    1.0            # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.167          # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# radial Ne Ne\nsymfunction_short Ne 2 Ne 1.000 0.00 3.00\nsymfunction_short Ne 2 Ne 1.000 0.25 3.00\nsymfunction_short Ne 2 Ne 1.000 0.50 3.00\nsymfunction_short Ne 2 Ne 1.000 0.75 3.00\nsymfunction_short Ne 2 Ne 1.000 1.00 3.00\n"
  },
  {
    "path": "examples/nnp-checkf/LJ/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   6.0871865837434718E-04   7.2815866278251790E-02   1.9093305172662212E-02   2.0241240265275205E-02\n         1          2   1.5544175511327358E-03   1.1277941989452710E-01   3.3134472337730189E-02   3.1972702944828152E-02\n         1          3   3.5029340302491388E-03   1.5415119007009570E-01   5.1275563979636354E-02   4.4402666633939228E-02\n         1          4   6.9664161692094993E-03   1.8594182841625700E-01   7.0845240019947853E-02   5.4073736544960498E-02\n         1          5   1.2226441157255801E-02   1.9793404599765610E-01   8.7507815525083174E-02   5.7502177573987671E-02\n"
  },
  {
    "path": "examples/nnp-checkf/LJ/weights.010.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  7.1289683273892379E-01 a         1     0     1     1     1\n  1.0495883843662790E+01 a         2     0     1     1     2\n -1.1574157686813686E+00 a         3     0     1     1     3\n  6.4799962786573706E-01 a         4     0     2     1     1\n -5.4599309824857345E-01 a         5     0     2     1     2\n -1.3938446745959876E+00 a         6     0     2     1     3\n  1.4765399939509904E+00 a         7     0     3     1     1\n -5.1760448988710932E+00 a         8     0     3     1     2\n  3.4349118505771320E-01 a         9     0     3     1     3\n  2.7605647283658095E+00 a        10     0     4     1     1\n -5.7967091488298879E+00 a        11     0     4     1     2\n -4.2234815912119011E-01 a        12     0     4     1     3\n  3.0320678573808363E-01 a        13     0     5     1     1\n  3.4806650267415351E-01 a        14     0     5     1     2\n  9.8678647412933629E-01 a        15     0     5     1     3\n  1.9203733149922300E+00 b        16     1     1\n -7.0323031244499068E-01 b        17     1     2\n  2.3427527876891785E-01 b        18     1     3\n  1.3731392066926247E+00 a        19     1     1     2     1\n  1.2639210463211468E+00 a        20     1     2     2     1\n  4.2373331685651211E-01 a        21     1     3     2     1\n -6.2527778527617084E-01 b        22     2     1\n"
  },
  {
    "path": "examples/nnp-comp2/Cu2S_PBE/input.data",
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1.1458552800000000E+01   3.8331531574624051E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1419389039897609E+01   5.5165528000000013E+00   2.2128297407432820E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0936796418726180E+01   7.4156159999999993E-01   2.0205674845803410E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3145250017590930E+00   6.6835616000000000E+00   4.0254154136253462E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.6801535777556369E+00   1.1142438400000000E+01   1.0071398311831031E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.9421178392114449E+00   5.2004384000000003E+00   8.0665503827860281E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.2270609982025480E+00   2.4302779999999999E+00   9.3374159879888623E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0489025259658360E+01   8.3722779999999997E+00   8.8005327066281982E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3483703839173090E+01   9.4537220000000008E+00   2.7545498084225111E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.2323824186878189E+00   3.5117219999999998E+00   3.2914330897831761E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.9652557811310523E+00   9.4477800000000001E-01   3.4268631067029829E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2860656393542182E+00   6.8867780000000014E+00   2.6191197915027038E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.2913870598394870E+00   1.0939221999999999E+01   8.6651026897083909E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.9705772016163241E+00   4.9972219999999998E+00   9.4728460049086696E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.7597168992464747E-01   5.1576560000000016E-01   7.5332946911642864E+00 Cu   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6.4542004000000004E+00   4.4268686780662039E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.4085877645645866E+00   1.1371799599999999E+01   1.0472851576271889E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.5337649689122408E-01   5.4297996000000008E+00   7.6650971183451704E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.4757056949440801E+00   2.4742487999999998E+00   9.1209698002330999E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.7862585665117332E+00   8.4162488000000000E+00   9.0169788943839624E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.7809371460264609E+00   9.4097512000000005E+00   2.9709959961782748E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.4703842744588087E+00   3.4677512000000008E+00   3.0749869020274119E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3936508439354220E+01   1.0172703999999999E+00   2.6191197915027029E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.6851870188689480E+00   6.9592704000000003E+00   3.4268631067029829E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.6798655983836763E+00   1.0866729599999999E+01   9.4728460049086696E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0941829859839491E+01   4.9247296000000000E+00   8.6651026897083909E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7852278917290239E+00   1.2264288000000001E+00   1.1524852600559679E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4767363697267890E+00   7.1684288000000009E+00   6.6130960940573811E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.4714149492415158E+00   1.0657571200000000E+01   5.6711319585169406E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.7799064712437493E+00   4.7155712000000003E+00   5.4788697023539941E+00 Cu   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2.4587995999999999E+00   1.6904568183383100E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.9967447513175891E+00   8.4007995999999991E+00   4.3555260798673769E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.0020661718028574E+00   9.4252004000000014E+00   1.0401508978073061E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -7.4010191034704897E-01   3.4832003999999999E+00   7.7364397165439973E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.0731956466969068E+00   1.1479944000000000E+00   8.2116539723429653E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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9.8348991497244645E-02   1.2172057341967104E+01\natom   9.7522454668779446E+00   1.1022086070312240E+00   1.0169315272111451E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.2907627531498767E+00   7.1749021884340678E+00   7.9106370831600596E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.6746940024324573E-01   1.1003436089299020E+01   1.7859230173048504E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2790012433811054E+01   4.9849116224085481E+00   4.1741460623727233E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2279454998218764E+01   9.2343856199715868E-01   4.0235268183775066E+00  S   0.0000000000000000E+00   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8.9841657732344302E-03  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5302818777645667E-01   1.1271358708708680E+01   5.9023060216822474E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2041797844720895E+01   5.0160728757312167E+00   1.1666158673316626E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1472633217718053E+00   8.7523898256363386E-01   1.2092613524708913E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3834762663397289E-01   7.0649314585597791E+00   6.0782049398811653E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.7268713771532078E+00   1.1506819211647819E+01   1.2169592973714263E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.0844640469086428E+00   5.1066032451830452E+00   6.2545020441099135E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3828320060349273E+00   1.2307792332384191E+00   7.5665386838572246E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1255030894185793E+00   7.2133020102534511E+00   1.0910086258940403E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.0924721165873459E+00   1.1165574354732280E+01   4.7444339670056213E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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7.8700836846433422E+00   1.1349088669933914E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.1655994928483251E+00   1.0250814225108812E+01   6.0710659777721601E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.1570206954453983E+00   4.4631180232929326E+00   1.2135272005743762E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.0052693368939494E+00   3.1446490487828718E+00   5.0157901018183146E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.0550361351755710E+00   9.3684990603280820E+00   1.0353055475976238E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.9166291924033239E-03   9.1696159307220633E+00   7.1995058214537027E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1056496508083669E+00   3.0277610208551051E+00   1.1438423470122242E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.2545180147699835E-01   2.0862338860194791E+00   1.1334194294738051E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.1576239733120390E+00   8.0791340337528066E+00   6.5893544957780357E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.9551950946769878E+00   1.0260226795356312E+01   7.1998467566516866E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.1666903623913782E+00   4.2320659572757142E+00   5.2078951669818645E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7832717067021409E+00   1.5962051747973540E+00   5.4157889268238515E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.3301034817805935E+00   7.6421416367335775E+00   8.3356215338027650E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.6334111505386435E+00   1.0518305861910500E+01   6.7981409906943790E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.2301222393219078E-01   4.7081825246738127E+00   1.1098844817359442E+01 Cu   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6.4757652717976044E-01   8.2057687301275415E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.5153472415272500E+00   6.4392355623726916E+00   9.9928578775374639E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.3105191045561035E-01   1.1566106004269491E+01   3.8962191880691219E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1594946703023178E+01   5.5346807048041411E+00   2.3398017646093057E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1219435209017949E+01   6.4199927152877112E-01   1.8883219642687530E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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5.7826150037115243E+00   1.5331968095279589E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.0740042480835577E+00   7.1446316521499664E-01   1.7745245759380208E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.3728459335629584E+00   6.6608862227313992E+00   4.3559191337403664E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.4982843590094372E+00   1.1312047478021791E+01   1.0443347335804681E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.0341477896850009E-01   5.5403412249595902E+00   7.6005987895960621E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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9.8251968655739077E+00   5.3684241480225730E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0243019805762918E+01   3.7100410805157908E+00   8.2208324934703669E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.3664967567024848E+00   2.4703804034374199E+00   1.6999600016524279E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.8572874578980301E+00   8.7686670648644434E+00   4.4356237931958225E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.9981564257447069E+00   9.3271394732160324E+00   1.0428883884388121E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5385148426984266E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice  -5.9853634821791617E-02   1.2040987142727165E+01   0.0000000000000000E+00\nlattice  -6.0400916228148125E+00  -1.1456695795516558E-01   1.2081053377195291E+01\natom   9.6922309529115616E+00   9.1918635497273793E-01   1.0195786426068491E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.3949600766656123E+00   7.0890480765404442E+00   7.8912952934605007E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.8117224314427012E-01   1.0983671509088854E+01   1.8708302824180061E+00  S   0.0000000000000000E+00   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1.0181606444350971E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.1575209660315799E+00   8.6906744635534972E-01   6.0268888571464281E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.9147813973939312E+00   6.7424507753685701E+00   1.2016669404711481E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.3636298634589140E-01   1.1204113157044084E+01   6.0076743390088332E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2276799076633349E+01   5.2814738772735277E+00   2.0622383926420249E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.9224875939713320E+00   9.8943020571856277E-01   1.2033550265088842E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4640653733062292E-01   6.9836915726523880E+00   6.1769255496336326E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1697367680910267E+00   1.1039525979370357E+01   3.2993455013802429E-02  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.1624313506469512E+00   4.9469567885769878E+00   5.9094503336744335E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3416307255598698E+00   9.9706960827797342E-01   7.4217011785163081E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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-4.8118731275085009E+00   1.1031465772677716E+01   9.5850220480585975E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.4279525314376533E+00   4.9718678598569417E+00   8.8324313573366364E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5728544820077528E+00   1.2515582460687242E+00   1.1327235746165170E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4529038967310957E+00   7.2111810456358967E+00   6.8639128911331904E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5368274614660749E+00   1.0851476558805356E+01   5.0272126572110454E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.8381944242142803E+00   4.5462861498715483E+00   5.4482697515988541E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.3539250746433344E+00   2.1089895496306643E+00   6.7985813334901808E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.1630394606026473E+00   7.9203993267041035E+00   1.1251417951923830E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.8245619180373398E+00   9.6909647079808110E+00   5.1818758901459230E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0463000249273989E+01   3.9559037593749102E+00   7.5618372779011067E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.3833389187210816E+00   2.5025147339873435E+00   1.6222471551899831E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0086973481858362E+01   8.5562274363502269E+00   4.4050216766377774E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.0255852928664657E+00   9.3408008856141116E+00   1.0591499303788471E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -8.2206531413885786E-01   3.4996421665619253E+00   7.7114549932460310E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.0596126717835861E+00   1.2898408812514273E+00   8.0836606318043636E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.3376424528794395E+00   7.1110458500319087E+00   9.8411011088853808E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1546852093366951E+01   1.0916886869105465E+01   4.0152141135609236E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0910613731050307E+00   4.7774104415223491E+00   2.1982273811263342E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5452281757592967E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   1.6600105429517242E-01   1.1962237854644114E+01   0.0000000000000000E+00\nlattice  -6.0381505592328262E+00  -6.2237092994503550E-02   1.2214775808302521E+01\natom   9.6248754519916169E+00   7.4455955511621297E-01   1.0156039276505535E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.2767684694734163E+00   6.9974733982223150E+00   7.8682818951880211E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.1301948411083637E-01   1.0890763897610272E+01   1.8747440533644522E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2696554360521780E+01   5.0077872787835211E+00   4.1667249111447360E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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6.1564951035414577E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.6034909057965603E+00   1.1062903516955974E+01   1.2182162004928944E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.3287137662424264E+00   5.0709009092192066E+00   6.1541277003650832E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.4121086896150019E+00   1.0228917661447976E+00   7.4974335041642837E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.0486062324596999E+00   7.1518091665967169E+00   1.0673021785888695E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   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9.7320993534372988E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5639271176197855E+00   7.5474491825205914E-01   8.2386560234100816E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.5320609937216254E-01   6.8299749142257955E+00   9.8764060869572177E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.1286594503109528E+00   1.1164146641904113E+01   4.2299159847848955E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.7983171895259744E+00   5.3140744782220342E+00   1.9457091709410492E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.6773565490092750E+00   9.8954281756430307E-01   1.8991435886184753E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.9676170521135377E+00   6.9860369292852598E+00   4.4772940820170453E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2254102854912499E+00   1.0809831361961782E+01   1.0237021520100834E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.3915797613243788E+00   4.5387824113793815E+00   8.0562724938055794E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.2976936138042072E+00   2.9375290922717707E+00   1.0856693686560133E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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6.7455118067392856E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.7166582526274912E+00   4.9888635468104940E+00   1.1443783076482445E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.6075336151043125E+00   1.7109343069891390E+00   1.1928425294949255E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.7644413134210661E+00   7.5181109797477266E+00   6.1438713549848476E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3443257802969357E+00   1.0415456826123833E+01   1.6041929372335528E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1514767829604288E+01   4.1963514437936009E+00   6.1283053179842168E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1332582813333399E+01   1.5912020918273369E+00   6.1884554662398870E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3996908385725237E+00   7.8303840165275540E+00   7.6529105599354247E-02 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.6854325661951941E+00   1.0204435847237322E+01   6.1975617559193825E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4359564878620450E+01   4.2525556421059472E+00   4.1270089891690120E-03 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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7.2717841857318455E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.7264899659574162E+00   1.0251503464934263E+01   6.8611074131023901E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.6177913373801207E-01   4.3570767345870935E+00   1.1337300611526075E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -8.3120040886683633E-01   2.5757553297815892E+00   1.0689136960622974E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.6518389672486400E+00   8.6372327107483695E+00   7.9606412554346679E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0853370611217908E+01   9.3255255549607892E+00   1.7428907748329503E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.7788176417040749E+00   3.0647281748154960E+00   4.2366899437995587E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.3488740141266433E+00   6.9494169195718414E-01   8.1981875075564581E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.3501083657969772E+00   6.4366909217295989E+00   9.8808407225704045E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.8149313695529341E-01   1.1197936923981683E+01   3.9033945571318340E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1679622585106880E+01   5.3385273849816199E+00   2.1715082536238173E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1244113555492248E+01   4.5754155222492215E-01   1.9109455850073123E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3860679438041819E+00   6.4766912849693226E+00   4.2140196789275413E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.4219584902936262E+00   1.0958162894186463E+01   1.0151746105281955E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.8648281425314375E+00   4.9259358658858918E+00   7.7774970210894896E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0800258014536240E+01   2.0657295888841678E+00   8.9016006993216124E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0791706522056739E+01   8.4081004328677977E+00   8.7361394452504761E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3917816209868519E+01   9.3923758350969635E+00   2.7911088538117981E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.4873100747055692E+00   3.4339980281782410E+00   3.2946827463507771E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.0255643523983862E+00   1.2030387968299490E+00   3.6715678156257803E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.7258999971198694E+00   6.9091542520507030E+00   2.7200114313616481E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5977885137951118E+00   1.1003911504975923E+01   8.8517896642816183E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.9065986856274990E+00   4.9040902196864433E+00   9.6152951840067011E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2569903456001508E+00   5.8071954560104655E-01   7.7478321583231020E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.1546526097643728E+00   6.2871503060280887E+00   1.0446521399965574E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.7040579408248995E+00   1.1370675804061253E+01   4.6280651593288136E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.1464071333764450E+00   5.1967586398385652E+00   1.4737645569351931E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.0652823235521112E+00   8.2705674452711908E-01   2.1288530057324224E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.7739575161687924E+00   6.6373514652596901E+00   4.3223309490912971E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5996193933460612E+00   1.1218088321615573E+01   1.0466541140724445E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.6698524838800219E-01   5.4121435571641641E+00   7.8121373248689556E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7488766638030877E+00   2.3562989018851841E+00   9.2215138089577753E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4960302557998868E+00   8.8543925556341065E+00   9.3132301467535576E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2577879931230482E+00   9.8138705498861629E+00   3.0222570330198972E+00 Cu   0.0000000000000000E+00   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8.7090812664750956E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.9173343722098437E+00   1.3813831319788790E+00   1.1757961390677295E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.6943193001612906E+00   7.3494025328561916E+00   6.9130696450132749E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.4225840330829147E+00   1.0777369829225623E+01   8.5400098830342941E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.0489230034398664E+00   4.8545502785111969E+00   5.3516473265411975E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.0869199013960040E+00   2.3508689840035180E+00   6.7193890827804044E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -8.7707222704723531E-01   8.2642464375014715E+00   1.1407907827324275E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.1518485896716979E+00   9.6325232924308981E+00   5.2855706717880704E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0560582643054367E+01   3.6068475366576109E+00   7.2542098107259712E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.0969740369021226E+00   2.3969640600345050E+00   1.7895674968456312E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0316494642788669E+01   8.6474400732291876E+00   4.4031352263556816E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.5333252024458295E+00   9.3916957546703834E+00   1.0574513847365004E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -6.1219361560219898E-01   3.2415746985038147E+00   7.9728391505891887E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.4528508330565133E+00   9.2538129974698069E-01   8.5802716189228327E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.7487881768972962E+00   6.9423832364389764E+00   9.5613481111746630E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1706468951167658E+01   1.0768239672876502E+01   3.9554941567586801E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.6817324212909854E-01   4.6955055936553380E+00   2.4019140163088553E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5332759180105528E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   4.1801614515025939E-02   1.2052255398106766E+01   0.0000000000000000E+00\nlattice  -5.8843194021350742E+00   5.9765192252208311E-02   1.2074923850605462E+01\natom   9.8129416573731092E+00   1.1121556484135209E+00   1.0158488260654785E+01  S   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6.7983723347316563E+00   1.8209575040934718E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.8310271845878803E+00   1.1333834132124622E+01   7.7985229780468570E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.4588784289757779E+00   5.2900116812734188E+00   1.0091926861451697E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.9841446186255034E+00   9.9593243033419399E-01   6.0106325791125990E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.6828739000888384E+00   7.1540440293875056E+00   1.2074462569283316E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.4436394181492629E+00   1.0833568245167822E+01   8.5972091576009575E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1214031739706898E+00   4.9653628000327172E+00   9.4276380927039085E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2233380978830648E+00   5.9173186439789327E-01   7.6558903917390495E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.4138635295016915E+00   6.9432495532939118E+00   1.0407995350656385E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.1469107799567837E+00   1.1660915892438513E+01   4.4662199185101121E+00 Cu   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5.3204983987440535E+00   7.5896569297292560E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.9938553824510099E+00   2.0827382275988287E+00   9.2498237005417288E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5518673354105568E+00   8.1301404716715417E+00   8.9510507755957569E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5975532203695151E+00   9.5762266526974216E+00   2.9641270564449487E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.6064666375028596E+00   3.4082820522176989E+00   3.1335199145508579E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4628395946695050E+00   7.3931274212278000E+00   6.8441310562036541E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.6619936961877864E+00   1.0964832350345670E+01   6.5419280924856027E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.9387434173985305E+00   4.7502498478476136E+00   5.2977962757423489E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.6224933490987574E+00   2.5461793509733290E+00   6.8646875506447884E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.0571538691334863E+00   8.4829682134853961E+00   1.1257742089413014E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.0503017510151218E+00   9.8541672001435039E+00   5.2652506208612087E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0644196002511627E+01   3.7238353350338360E+00   6.0029986905006538E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4129317810684987E+00   2.4736122463043708E+00   1.6140815116945169E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0228635412051458E+01   8.2924716561187992E+00   4.4046054913762420E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.2399190455742399E+00   9.6529020407262998E+00   1.0466711222336965E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.0916863268671733E+00   3.6866833889121891E+00   7.6430354014771487E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.0886592719617183E+00   1.2679069731102039E+00   8.5675288725665162E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.3067829335584609E+00   7.4936049407864269E+00   1.0339020689498614E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1428255392988127E+01   1.0833201128078223E+01   3.8402922302578300E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.3963553674430572E-01   1.0906499713074446E+01   2.2195855493072436E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2552480245897607E+01   4.8933166216451447E+00   4.0042893889036559E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2421645735926486E+01   6.8517025643323970E-01   4.3294488146632446E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.8514576465159183E-01   6.6865303117468695E+00   2.0270614173836665E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.0883911752656266E+00   1.1412857330632907E+01   7.9491429341411388E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.0429076403701174E+00   5.2200425999992515E+00   1.0433942337375644E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.9789976241731413E+00   1.0102951320396323E+00   6.1657224312840322E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.2049759492360383E+00   6.9293378686697595E+00   7.4133562829611740E-02  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3126801512184597E-01   1.0979138895806337E+01   6.0130067741385664E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2196281309634836E+01   5.0140453998751351E+00   2.0379122231953239E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.0046572542265917E+00   8.5238218634510299E-01   1.2036450706843492E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.8298078390224285E-01   6.8704949662012513E+00   6.0458847562355906E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1081113834248035E+00   1.1337305190038066E+01   2.2198759390457110E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.8961223782607952E+00   5.2572899979975949E+00   6.0169856097717256E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1011027383042045E+00   9.5662383401133944E-01   7.6022177757781639E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1353839663276553E+00   7.1536946917155371E+00   1.0764605809728842E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.9987485467461861E+00   1.0996216015541256E+01   4.4909934514623444E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1701495160722875E+00   4.9256970076743469E+00   1.4522986061630756E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2453947292607772E+00   8.1751398605857450E-01   1.0379120532499162E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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9.2744313130914886E+00   3.1943311345260654E+00   2.7408162995258127E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.6177775218224895E+00   2.6783812531688662E+00   5.0899968843819208E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2984140578596399E+00   8.6620611250328707E+00   8.6484605482253174E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3978848079253852E+00   9.4349480875919021E+00   7.2295515196965878E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.6271399815640692E+00   3.5066551197912985E+00   1.1251843440638293E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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2.6085208517733736E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.0681668871882875E+00   9.4376590451155824E+00   8.7260329961586223E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.4163627847028728E+00   3.0557858049259412E+00   9.8970436250362930E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.2287398933917411E+00   8.0414892892057799E-01   8.4982444449291883E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.4438113318405126E-01   6.7995511321161430E+00   1.0167102784410833E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   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2.8518804258989774E+00   4.9847746259336461E+00   9.4017803368353619E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.5812935569351012E-01   3.5454820899034545E-01   7.7326936269113604E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.3426141472710675E+00   6.1967649655430037E+00   1.0566395900659554E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.2916329062672194E+00   1.1893838115672967E+01   4.3881278469905380E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.1313321646509218E+00   5.6200905294459389E+00   1.7012057628521926E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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3.7029074573710616E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.2983408309785656E+00   1.0739377848660556E+01   9.6539029808629024E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.4581616412231106E+00   4.7865424669326924E+00   8.9938128757001756E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.6628498684370392E+00   1.5119275608703893E+00   1.1539298442079613E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.5587660036568805E+00   7.4885185760740871E+00   6.6943607104428100E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.3907075242365412E+00   1.0778993153536897E+01   4.2994775816720632E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.6517587984207758E+00   4.6153784871149286E+00   5.4633169804305473E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.3391530016573885E+00   2.5667858383734545E+00   6.8114104034382832E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.3576690530656665E+00   8.0475337106360367E+00   1.1087409443933112E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.9809889996306573E+00   9.7168322313380653E+00   5.2297778708119278E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5487145768160847E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice  -9.7739031512794866E-02   1.1884305950999062E+01   0.0000000000000000E+00\nlattice  -6.0593983721770028E+00  -4.9821739443285294E-02   1.2159940807616611E+01\natom   9.6925137196640385E+00   1.1811698955339685E+00   1.0424905296692820E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.3319153619675448E+00   7.1445147583819892E+00   7.9330644693473493E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.8602089602932632E-01   1.0878691468795095E+01   1.7433143012734185E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2753793328592518E+01   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0931471205762168E+01   9.2109511264125281E+00   1.8178010857237756E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.7901017059778093E+00   3.0526588275974835E+00   4.4649440508779490E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.7030576678523275E+00   4.3128615968502265E-01   8.5645284456742043E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.0617311679418386E+00   6.4778294079669489E+00   1.0102969880701009E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5494059014309527E-01   1.1288790156508826E+01   3.7237194664639737E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1582163963570448E+01   5.4398211487563346E+00   2.3144417776351918E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1337720370605936E+01   3.7979886169686489E-01   1.9541374046410935E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.6409673422881292E-01   6.3746553720020600E+00   3.7902547430024054E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.8747901772074738E+00   1.1105722570021115E+01   1.0342915281525540E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.8773694592772534E+00   4.9539502092595447E+00   7.8102398921962681E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.4387939621060823E+00   2.7193785788909492E+00   9.3612770367269924E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0344744893240396E+01   8.7659401301734121E+00   8.4272455315974515E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3685803363469969E+01   9.6665524434879746E+00   3.0617767690733877E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3950675826297726E+01   3.8344531788979745E+00   2.8797049160079675E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.6863361541656721E+00   1.0819700159076473E+00   3.5225332723003504E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.5983132150088482E+00   7.0586423204611091E+00   2.6760996975219755E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3612467587662214E+00   1.0933885569162525E+01   8.6972616819024129E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.8315431602736632E+00   4.6326268461176632E+00   9.4129111703969137E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0872775526946814E+00   6.5185289381772005E-01   7.5014940886743977E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.7386199971463538E+00   6.7157459091151290E+00   1.0720724053513560E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.5405654689207111E+00   1.1555762362295136E+01   4.5356439801980706E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7399380517800642E+00   5.0781234450618307E+00   1.5872906069691926E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.8856969009969773E+00   5.5466339176982182E-01   1.6940373573407885E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.4741842454807923E+00   6.6152115947007601E+00   4.3441599432856375E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.2357808925878970E+00   1.1243425008492766E+01   1.0414246768574600E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.5072299662284534E-01   5.3727794968132745E+00   7.8379650481443264E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.2348132169199042E+00   2.1768879978139983E+00   9.2597491367069811E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.8277555080251413E+00   8.3255642494026976E+00   9.0119538443532949E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.3053005060340670E+00   9.2026545058147775E+00   3.1573042269377085E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.6517028616938809E+00   3.3404682838077564E+00   2.9970061588813146E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3978672031251136E+01   7.4429262433987076E-01   2.4788130886562527E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3351077366269077E+01   7.0677565391325725E+00   3.2818411493044435E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.7041386886476930E+00   1.1147500908216735E+01   9.7979037343249615E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.1038469450397210E+00   5.1490305096361011E+00   8.6345519994488509E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7472665069676823E+00   1.2533074303033043E+00   1.2146138318022050E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.3357823635066164E+00   7.2867784685430328E+00   6.5818706080073559E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.1120161928023453E+00   1.0520406850589536E+01   5.9478946397426002E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.0101467292763084E+00   4.7294658708107526E+00   5.3606392381715509E+00 Cu   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2.4106810809180392E+00   1.6164588947457526E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0157903512574357E+01   8.6133792387775507E+00   4.3070832309223341E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.2864811281533175E+00   9.5967752955345507E+00   1.0355017970793060E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -8.7495866626057683E-01   3.6338351197422774E+00   7.6593886930438524E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.2098830091694119E+00   1.3048257756771624E+00   8.5709664464498712E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.3788879940676040E+00   6.9356700525729478E+00   1.0102775427872219E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1692132339867516E+01   1.0897682205102436E+01   3.9209795236418015E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0840527112745832E+00   4.7857398240064146E+00   1.9540586149853556E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5522702646225202E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice  -1.2930816293777288E-02   1.1868371649838259E+01   0.0000000000000000E+00\nlattice  -5.9700026382264930E+00   6.0263395162332848E-03   1.2164833394915489E+01\natom   1.0095676801943457E+01   1.2728828109959760E+00   1.0136746375419261E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.2684601759694059E+00   6.9536310362674882E+00   7.9175674328472869E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.3862557239341138E-01   1.0826284288768520E+01   1.9241854858368370E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2720729828550370E+01   5.0494329325770231E+00   4.2277452509141735E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2426713347728910E+01   9.8615667265620599E-01   3.9316133952392072E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2239483946578655E-01   6.7660933414156625E+00   1.8923239509244940E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.1219122821119556E+00   1.1161340592734511E+01   7.8165211934769658E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.4446961571834400E+00   4.9172996647783354E+00   1.0078963889815451E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.1504032096029810E+00   1.1402444637418070E+00   6.0944753367130984E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.7668718311822396E+00   6.9961175205605945E+00   1.2019378383361001E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.8407821673277747E-01   1.1001923915957121E+01   5.9407428195352914E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2052091631176271E+01   4.8940396101543362E+00   3.7057011465244892E-02  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1746670439486850E+00   6.9997740002819298E-01   1.2103667334952950E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.1290026798393242E-01   6.9315454468752380E+00   6.1907193004672019E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3062881621916964E+00   1.0987713392318771E+01   6.4040797819489181E-02  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.2406286221413634E+00   5.2359933494855211E+00   5.9891117999043946E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1924554635790794E+00   8.4465185738008297E-01   7.3972981021045676E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.0706542051313663E+00   7.1348094914661946E+00   1.0880921739672610E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1956020874352156E+00   1.0773102327028280E+01   4.7989883565103373E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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7.7857286786242961E+00   1.0209372739806864E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.9851166322141029E+00   1.0523240965404600E+01   6.0741812638532036E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4462474518519414E+01   4.2118739119183859E+00   1.4393303889010098E-02 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.1753676928361614E+00   3.0914872424733755E+00   4.9675378756615522E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3143704651795249E+00   8.9433159530014201E+00   1.0341414614500544E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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7.7737446237286922E-01   8.4240152653331855E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.1539395773905370E+00   6.5233266058003867E+00   1.0088159596609476E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0946143167868940E+00   1.1696068922646599E+01   3.7051845781231583E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1630646717271222E+01   5.6804158304134891E+00   1.9484382808417253E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0925906989752804E+01   6.1104235770330650E-01   1.7913834414228573E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5330054439818859E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   4.3105728737359482E-02   1.2002323215489605E+01   0.0000000000000000E+00\nlattice  -5.9601021351319297E+00   6.3150692692886257E-02   1.2227832181201560E+01\natom   9.8206539896885943E+00   9.9484457862536535E-01   1.0318044440721220E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.9807492931833877E+00   7.1951999331494507E+00   8.0275550984050987E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.3796270501352368E-01   1.1264618045559073E+01   2.1026542517463165E+00  S   0.0000000000000000E+00   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1.0360859268629650E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.9930816726031875E+00   1.0572499268892934E+00   6.1426004683731206E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.5749977766575998E+00   7.0148428047757996E+00   1.2218394141014759E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3924559691027500E-01   1.0937061508939173E+01   5.9971871336284233E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.8894084603064547E+00   4.9953528462605634E+00   1.2097637965244697E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   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9.1384483228684701E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.6027809877575390E+00   9.7133928729236771E+00   2.8986000274338983E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.7263851861669224E+00   3.3144721983852246E+00   3.1963553146542205E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3879202019020196E+01   1.3455305260925745E+00   2.5690940613891451E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.3466312687485815E+00   7.3547930729558182E+00   3.4399494752596151E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.4713886546186110E+00   1.0931168686273443E+01   9.4040250060567843E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.2371254783252033E+00   5.2204000974865128E+00   8.9319799497252426E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.6054749989226442E+00   1.2269463062194084E+00   1.1202349486790887E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4237338635339762E+00   7.3905440935929452E+00   6.7198768849054114E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5743473278837428E+00   1.0765794320329363E+01   6.7722915131427075E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.8668062066512858E+00   4.5618324439801938E+00   5.6640508521573700E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.2265321658502506E+00   2.1948768645883594E+00   7.0219594828158005E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.5938505832847265E+00   8.8102933448121252E+00   1.1173010122724168E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.5997439987899633E+00   9.1539106128979171E+00   5.0934091856724404E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0216756404423226E+01   3.3784937073453216E+00   9.7527750485056153E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.1466043664403753E+00   2.3353566049483274E+00   1.5084456130537054E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0302827948221436E+01   8.2524475858424715E+00   4.4718290512578722E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.7830601816900185E+00   8.9854015922542629E+00   1.0304891097168078E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -7.4808173136290268E-01   3.8262499757925603E+00   7.6223826608705902E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.2169834799506716E+00   1.4200907981054374E+00   8.3095183521060747E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.9666056028136332E+00   7.1005247054523668E+00   1.0145839130776118E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1333568776193006E+01   1.0908910866665824E+01   3.7713725738801402E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.3805934475560973E-01   4.7380788726955103E+00   2.4463877748540694E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5531011306812864E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   3.8348116987870884E-02   1.2000429338784166E+01   0.0000000000000000E+00\nlattice  -5.8350170089377604E+00   5.9705231973261616E-03   1.2181386358939031E+01\natom   1.0043137137395316E+01   9.9000258061510515E-01   1.0375934894844482E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.1539157969066722E+00   7.0572095516335134E+00   8.0034463847703901E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -6.6715040060729314E-02   1.0936634719837464E+01   1.9064591358866154E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2842410296529888E+01   4.9971083288436766E+00   4.4374573750878561E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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6.1314154266799550E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.4933910332554343E+00   1.1040456405658514E+01   1.2133840955592612E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.2865611009625901E+00   5.0549714997002146E+00   5.8093502320483381E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5357445762645425E+00   1.2818942683834011E+00   7.5025084891940992E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3849604650471625E+00   7.1654823199817717E+00   1.0570157735075583E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   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9.7948285046209254E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.6460897526677263E+00   9.7306074927593844E-01   8.3293078092788502E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0645945023183812E+00   6.7781455026230342E+00   9.7192858792070922E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.1914800440278599E+00   1.1030543084411544E+01   3.8587320387565893E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.6882816662974278E+00   5.0399519250516622E+00   2.0742244499156852E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.1135915163271761E+00   1.2100062406126562E+00   2.0905993922075723E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.2730090260275659E+00   7.0351530961856446E+00   4.3359195771254591E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.5097517210790277E+00   1.0726873405419834E+01   1.0147812880787162E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.3083952907164837E+00   4.6583100030944031E+00   8.0124491672153901E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.1483777910580129E+00   3.0230406748462344E+00   7.7827136222730531E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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1.1287340033469288E+01   4.2257529959933207E+00   5.9925103481391409E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1388633055580847E+01   1.5044176450063222E+00   6.2562699947231595E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.6735148130113171E-01   7.6276422114104419E+00   4.1613154043391914E-02 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.8774082612386453E+00   1.0383156644890317E+01   6.1235177855990193E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.5060866762514387E+00   4.5212076583622141E+00   1.2075703976961702E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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4.8782147302376822E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.8811684280709784E+00   1.0529854152980324E+01   7.0841846654965970E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1183958303146335E+00   4.3761846471364230E+00   1.1130703800995102E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.2809712920295193E+00   3.1682387474311322E+00   1.0293853691431783E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.8029419898152170E+00   8.7488499064298928E+00   7.9964626395528340E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0516699843455118E+01   9.0760951993647545E+00   1.9177483708310274E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.0391878402765036E+00   3.2594479390058955E+00   4.3318453729917623E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.8142679946965856E+00   5.3848494356602283E-01   8.3881192044254380E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.0715759608594513E+00   6.5283840037935823E+00   9.9438813670540895E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0703447500486782E+00   1.1541797235191627E+01   3.7403122564878006E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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3.2622123754266013E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.0839477049785700E+00   6.9685665676294697E+00   2.5719164966016876E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.6678794296980288E+00   1.1407308965907905E+01   8.6048988207048822E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1373188902996767E+00   5.0619887409011151E+00   9.5679245065281062E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4705021333295747E+00   1.6627865364802175E-01   7.6929637629047658E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5796725123016069E+00   6.1782671172442463E+00   1.0645771825193723E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.2566496092361490E+00   1.1647920950770555E+01   4.2586418737174698E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.2237650616215641E+00   5.4352895633040417E+00   1.4486921755443594E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.0043628286522157E+00   6.5670434898829577E-01   1.4116774000340244E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.4349267121834792E+00   6.7143549071580431E+00   4.1593615334729748E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1378547035382480E+00   1.1306212742108830E+01   8.7050078571028351E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.0699263881593439E+00   4.8271080250554821E+00   9.4165465910030832E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.4834515663636481E-01   6.0458419723332923E-01   7.4122731469773520E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.6302271037227642E+00   6.6483993038268636E+00   1.0695278616723314E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.4778632007811705E+00   1.1394710583430410E+01   4.8485428019802983E+00 Cu   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5.3329266584989012E+00   7.7777225912921359E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.2982451339550130E+00   2.1856317062760975E+00   9.0823877143727998E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5633847520103470E+00   8.4241239323417894E+00   8.9255209143563370E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.8411151312718790E+00   9.5437329548561003E+00   3.1195262077149715E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.5438059150882193E+00   3.4418357734699714E+00   2.9973251028387367E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4080174215151818E+01   9.4574294059899655E-01   2.5129542578022237E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.3955229589670590E+00   6.9815712973386237E+00   3.8404773286915677E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.6211970341605664E+00   1.0956210241176489E+01   9.5515573485848577E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0804379118267727E+01   5.0393785094283627E+00   8.4412661015614745E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7194684825176241E+00   1.1892793356732483E+00   1.1448794792206925E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4902323819225791E+00   7.4004802027155607E+00   6.5070953048042401E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.4928206039617473E+00   1.0679360630653370E+01   5.7204752009329329E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.6879928379252807E+00   4.8748521757306742E+00   5.5969241864937986E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.3568800110994452E+00   2.6713306846089795E+00   7.0283996613677013E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.4000620506739612E+00   8.8014984549612620E+00   1.1091580244422754E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.8487558268659730E+00   9.8643109299508147E+00   5.1927887681039415E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0506149598026846E+01   3.5200191753754781E+00   7.5320753695371467E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.3002518332522870E+00   2.4906548093572205E+00   1.5687312002285465E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0323796693288157E+01   8.3425778615149184E+00   4.4900898009896535E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.3335699510368419E+00   9.6931446705237150E+00   1.0629986500621765E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.0486807345579001E+00   3.7915201381825394E+00   7.7824406169159142E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.2096526983123241E+00   1.3130901025186623E+00   8.6222630010982613E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.4373240409519354E+00   7.3509160863481817E+00   1.0138965290317763E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1314597747581146E+01   1.0819802897380981E+01   3.9330438362515325E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.8452614549093909E+00   5.1562807533030934E+00   1.0268382274306163E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.1800946237929928E+00   1.1861345036239732E+00   6.0964367560921753E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1838695517030167E+00   6.9621420274163501E+00   8.4168222817425448E-02  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.6285268930582362E-02   1.1106438733423733E+01   6.0804896417222132E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2290871162458291E+01   5.0166219216528667E+00   2.3423921513323764E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.9384477024462239E+00   1.3242571623433042E+00   1.2145431736246120E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.0808750515958296E-01   6.9786895469646844E+00   5.9983423151369362E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.8718364324887755E+00   1.1083930251501315E+01   1.2034848488809651E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.2767150259107964E+00   5.2601929075309330E+00   5.8155246478132758E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.2626871699317324E+00   1.1846413034755772E+00   7.4133495247517152E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.2718554697131674E+00   7.2028768789833872E+00   1.0617230312768623E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1990922244519924E+00   1.1188624636608903E+01   4.6204486030050642E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.0383838934594181E+00   5.0907276626073266E+00   1.3771473965445629E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.3374468712767511E+00   6.1009204408939011E-01   1.0303334864253124E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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9.3453031869457561E+00   3.1417579236719613E+00   2.6796669400183859E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.8675632800307325E+00   2.5995117976390083E+00   4.8207978602091455E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.6063146745667973E+00   8.6593352943695301E+00   1.1071311225419758E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.4536051994634422E+00   9.3467480046113138E+00   6.9812023780434158E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.8447016710885307E+00   3.3970625017634020E+00   1.0894551048679642E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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2.6544885193706778E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.2416771613054545E+00   9.0221804134343877E+00   8.9055256513236607E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.6598789464637491E+00   2.8777183840155671E+00   9.5960312766287110E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.3531307938661223E+00   7.1201604968996579E-01   8.2105578701421749E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1264080442215445E+00   7.0064422342646315E+00   9.8359665606766242E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   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-8.8448807393024076E-01   2.8089000710131153E+00   1.0311072889534064E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.4441538770265225E+00   8.7694750792718885E+00   8.0068185978164834E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0238306112290402E+01   9.1978152072487056E+00   1.5987094406748359E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.5421027027028436E+00   3.5734378052256983E+00   4.3567316484852725E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.5847599929072302E+00   3.1310078239650985E-01   8.1110017184515506E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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2.6874177912666219E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -8.7602904189891273E-01   3.3250683642432763E+00   3.7239274226620389E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1167268235218026E+00   1.0170026624379274E+00   3.2315675329884250E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.4910487828589014E+00   6.9846791037012181E+00   2.7781017942658530E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3378867533721643E+00   1.1308945923315434E+01   8.5097192366364069E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.9138075515783854E+00   5.0758178298763914E+00   9.5554048001973690E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.7986278182444053E-01   6.2756283613982566E-01   7.6775849376104288E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.9240340815188137E+00   6.1690447119883931E+00   1.0523917194861902E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.3835133171332075E+00   1.2058994801753563E+01   4.4056459081467843E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3005481537677386E+00   4.9184920175754607E+00   1.5251774868767869E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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5.4962803906956719E+00   1.0611760010027695E+01   5.0276046788139528E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.6164918359365981E+00   4.7820912279443029E+00   5.4273918248894981E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.3668724614477794E+00   2.5806416318702263E+00   6.7485963588550728E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.1952031335307325E+00   8.5960606101448249E+00   1.1355035727656372E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.9100492616046725E+00   9.7572700632201759E+00   5.4565271058114426E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5645870424808507E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   2.6185549811710179E-01   1.2014684641838421E+01   0.0000000000000000E+00\nlattice  -6.3381799289003062E+00  -3.1013737514787265E-01   1.2477464239231708E+01\natom   9.5691936601217122E+00   8.6478471283854164E-01   1.0298156386144491E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.0427862589280279E+00   7.0773447886023471E+00   8.3741158549527448E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.1461222226556572E-01   1.1242019829301668E+01   1.9422256630565926E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2875524870119328E+01   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1.1728309360237379E+01   3.6267352505563126E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3188606921711498E+01   5.0671089734757038E+00   2.1326207471546716E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.5631150811978700E+00   3.5529534899497289E-01   1.2227598564349549E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.5398479068322359E+00   6.6344450581226653E+00   4.4063305043390866E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.0219988837879121E-01   8.9539459293895831E+00   1.1745379507242461E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.6725001030126627E+00   3.1333716577709221E+00   7.0835111793233523E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.1456888415924200E+00   2.4833969339454267E+00   1.0088545994467072E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0745877301617709E+01   8.0423407262333768E+00   9.3552736560541234E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.3166733214569091E+00   8.1437372871246545E+00   3.0047919843921065E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.1873454022163561E+00   1.2054834450326719E+00   2.7876105947192547E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.1019745021112684E+00   8.6959583030307674E-01   5.6165699250611612E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1043501424138629E+01   5.4508421201016093E+00   5.7049412502826122E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.0066592257507581E+00   1.1174216142823798E+01   6.8197543744990909E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.3692692375279898E+00   8.5081115413371151E+00   9.4022129436508806E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.7708638798780889E-01   4.5392762857156238E-01   7.7574894046758374E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.2164412876696620E+00   5.1167162575736764E+00   1.1613879528655911E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.2531571567935007E+00   1.3242862961720708E-01   4.4343311415568056E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.3151428477912592E+00   5.7343233205859301E+00   1.9955624939990926E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1713793951957108E+00   1.1793039983472070E+01   1.5760375876313326E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.1201677277841693E+00   1.1712370453533751E+01   3.3242026576935655E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2352977815252908E+00   1.2080506140734788E+00   1.0357771732361989E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.7419795986107820E+00   4.8807448832270648E+00   8.8997499971764036E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.1008383415105811E+00   3.8870069350272201E+00   9.2818022626733274E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.3398254376634782E+00   8.8050608428748340E+00   8.7772599195908541E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.7547003280680675E+00   7.5896118703546751E+00   2.9909955740647796E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1648861616154980E+00   5.1487789212177786E+00   3.6719418758075486E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0124618657536647E+01   1.1058613853623910E+01   6.9102213958493897E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1860778289238809E+01   7.1189422269982501E+00   3.8384980805175077E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0703879531838989E+01   1.0958158834492359E+01   9.5632699196431936E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   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2.7303111172897920E+00   1.3754504333079196E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.2207335701370674E+00   7.4003622676034810E+00   4.7690921525601100E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.2009836103676381E+00   8.4981203132117074E+00   1.0906909829877179E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.5956527795577928E-01   5.3433595340941968E+00   7.8271612756540483E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.9321280933181759E+00   7.9503339459006717E-01   8.5755349803203238E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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1.8272403121592107E-02   1.2800859383796119E+01\natom   9.3885205619517471E+00   1.4402630799129932E+00   1.0948678492737415E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.4278333039144635E+00   7.5492470277286223E+00   8.0321327076987394E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.2724532338783663E-01   1.1322664304262752E+01   1.9379936790399623E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2789811549111455E+01   5.2081691746197780E+00   4.3350919857694237E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2808807215330997E+01   1.5929620363979011E+00   4.4659504108317565E+00  S   0.0000000000000000E+00   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1.2477808769771102E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3789657777740744E-02   1.1324619003745550E+01   6.2222261098153471E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2525808138865237E+01   5.3989778443165015E+00   2.2694179108542203E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2417547530916845E+01   1.4997588434861051E+00   3.3849847475396633E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2604165515720150E-02   7.4995591676264768E+00   6.0308071221121429E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  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0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.6639045364973208E+00   7.4093929726791279E+00   4.9414016984772874E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5490567546534644E+00   7.4676056301248694E+00   3.9855445210472622E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.8794379997219579E-01   8.1441939663788188E-01   1.2349800537333934E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.7276255848305406E+00   2.8717735128522182E+00   5.3056894682447786E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0022757890483657E+01   6.4214061555803301E+00   4.9262312561323558E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5571000220863356E+00   4.8487098060479117E-01   1.1161871310602095E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0865477890572532E+00   6.8743305960397052E+00   4.2844027339863970E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.5460174452676765E+00   1.5173115072180983E+00   9.2150415699242423E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2500526938794891E+00   6.9057884951224136E+00   1.1525698590728183E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2028505203429486E+01   1.1355636021320581E+01   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1.0962877162308747E+01   1.0738131829643432E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -5.0912363510207248E-01   9.1086402695643791E+00   5.2425409468121602E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.3902524443168712E-02   6.4514506536348248E+00   1.3851161587946254E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0105493053934708E+01   3.2141224279602718E+00   7.6081693709474978E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.4965212318875203E+00   9.2897022395032884E+00   1.2178275687250594E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.4020725505278913E+00   3.7090797530434969E+00   7.4350170034717529E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.4289946757115279E+00   3.5793913656607007E-01   6.3370721363455509E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0965136375570463E+01   5.7379689067416679E+00   1.9424691565035186E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.3919725693913456E+00   1.3083378223589550E+00   8.6117114644245056E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.3947649351097127E+00   5.9001955778138386E+00   3.2321867533015136E-02 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1144475746414972E-01   3.3830465747105789E+00   1.0677841764437133E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.0861890197058477E+00   9.1815743572201924E+00   6.0479904465429168E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.0956073202050263E+00   3.6443135500592110E+00   7.8529804137146519E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.9052294760795200E-02   3.3994274814314478E+00   4.0386003856343180E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -5.0792980132990744E+00  -8.7479644348090357E-02   1.0009336907906921E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.6145261945102556E+00   6.1316547616181234E+00   9.9638902801001663E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.8696477350721961E+00   9.8592710619909069E-02   4.9929497473558380E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7479699955864199E-02   9.6302955952499190E+00   1.2058194883814533E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.6303483639217400E+00  -3.6096401087285637E-02   1.1124834570313222E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0630093075012903E+00   5.0031981303917243E+00   2.0555869681621033E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5443412583740974E+00   1.1395371354079245E+01   9.0893701573135877E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.0353919127987039E+00   6.4696501943055313E+00   2.9869357945218518E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.9762347984855091E+00   6.3854545253845254E+00   1.1256032827266242E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.6914508928507566E+00   7.1898154748099836E+00   1.0418922733165711E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3097184051930753E+01   9.6465198532054544E+00   2.0963832017574346E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1053637033920992E+01   8.1991476278510902E+00   1.5016854600321765E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.9697191035882673E+00   1.3183660783859890E+00   6.2134259185623080E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2193861061761574E+01   6.4977625562881398E+00   6.4031261867748261E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.0039337963926878E+00   1.1022702672283565E+01   7.5237513812678403E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -5.0450255361992813E-01   4.8870878965345887E-01   7.9220465410869387E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5294707048739631E+00   3.6882295415102390E-01   9.7150342181883182E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7831178409254149E+00   5.0331958070779113E+00   1.1841694276076762E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.1946156064948390E+00   2.8752491088239491E+00   4.4182047316465463E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.3206613319926968E+00   5.0939649612832261E+00   1.2423635152718923E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.2656679613372281E+00   1.1376387402771186E+01   3.8682035616108004E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1322789456971094E+01   8.9675869596699904E+00   5.9023547519587094E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.9240044382333341E+00   1.1544018190556784E+01   7.9500499749566247E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.2972867250586400E+00   5.2995102685426039E+00   8.6809593763068840E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.5171099221187259E+00   3.0056187617612871E+00   1.0523817894815291E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.2403559008666631E+00   9.1562610264965052E+00   8.7516792717335967E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.0026497503497831E+00   6.5830642897418699E+00   1.8867100551235196E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.0578219190026754E+00   3.3501763862333389E+00   4.3330361194751106E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3838993354941731E+01   1.1412729262329215E+01   2.6009425304608913E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2000543683319904E+01   7.2520144333762344E+00   3.7565287540294676E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.2005601259911352E+00   9.4208122367796570E+00   8.9708766763191221E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.5652085519041758E+00   5.9574552843182387E+00   8.0750296363229559E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.4863232350983000E+00   9.7139543140636520E-01   1.2436887292661414E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.3882514607130299E+00   7.1532864025024061E+00   6.8059504759276299E+00 Cu   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7.2554187214361718E+00   4.3302467740576560E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.3426186650108978E-01   1.0688509664640808E-01   1.2844250683844823E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4618697521630470E+00   3.0036141102232659E+00   6.7046044307723118E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.9569391767291222E+00   6.5755503745116286E+00   5.1231849015289193E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.6987214167312006E+00   4.5411118836859460E-01   1.1174332734561983E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5700992882310858E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   8.0392624287783473E-02   1.1899148686257469E+01   0.0000000000000000E+00\nlattice  -6.6091206914012837E+00  -6.9087160615146997E-02   1.2925342256788911E+01\natom   9.6979447193185209E+00   1.3722234566927647E+00   1.1020627051186027E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.3072138549844423E+00   7.3921656404551390E+00   8.5909184116657240E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.7850583898028588E-02   1.1449145845071030E+01   2.0216431061496225E+00  S   0.0000000000000000E+00   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1.0969312263624726E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.3461433065451622E+00   1.1708752962959865E+00   6.7674888643598905E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.1369784286655111E+00   7.1243949010311400E+00   1.2667114062177136E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.2188962417611542E-01   1.1232443166570778E+01   6.2031589215972627E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2508741421842460E+01   5.3484150856162396E+00   6.8034717173160253E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2673300930660030E+01   1.4692615480177706E+00   2.1519572382376739E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.2963072073505550E-01   7.3943568524636323E+00   6.3321996147611035E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.0396910913574731E+00   1.1224553178498471E+01   1.2673814255757677E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.1813317348719199E+00   5.0355939586551290E+00   6.7548176348901769E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5563566700913429E+00   1.5213151160592686E+00   7.6814809593529798E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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9.5955667897420973E+00   9.6691222536114374E+00   9.0290468494597622E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.7017838171568300E+00   6.1682334810460713E+00   8.0545331172142021E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7999269655881398E+00   9.9540246872862992E-01   1.2464178751514206E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4674058962135126E+00   7.6322610731159370E+00   7.1305429145337138E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1115656056865806E+00   7.4456610390691014E-01   1.5294057732224389E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.7144306451694269E+00   3.0800165429355078E+00   9.9189781511615005E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0039925684968038E+01   6.0311728331109400E+00   5.0871248971853378E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.7078181186784747E+00   3.6500946292088060E-01   1.1064509931990367E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.5019301028084777E+00   6.2292277590114500E+00   4.8799113340687308E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.5034884020574393E+00   1.2598504404729276E+00   9.2560103067998849E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.5554029110379606E+00   5.7509315697270873E+00   1.1556204442290527E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1753589487207810E+01   1.1237074998062610E+01   4.6330805466798965E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4267485682237801E+01   5.7121417590015913E+00   2.8339131006653626E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5609523287228876E+01   0.0000000000000000E+00   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8.8958205772125396E+00   3.2072366832709776E-01   4.8849645221811446E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.5793674841938818E+00   3.7559073038698026E-01   6.5068036356757606E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.0777532622269508E+00   1.1293270755427951E+01   1.0730132584982876E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -8.4674796745428482E-01   9.1642152003732065E+00   5.9357587623999954E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.1143933407275799E-01   6.8301280148337691E+00   2.5217559014946789E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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2.4469137375235879E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.3721437745625913E+00   1.1635373225712544E+00   8.5263733475729140E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2786706248580961E+00   6.3421156343191631E+00   1.2680901368859466E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.3974729059067048E-01   3.3516635437077023E+00   1.0625715828819747E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.8650117301046478E+00   9.4127949525807182E+00   5.7621201241525268E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.5392129820308114E+00   3.7504357637601342E+00   7.4463476717506127E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.6048144677218122E-01   3.9722294916885001E+00   3.9561214273721510E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0607091273024471E+01   6.0263157663288802E-01   9.1790746312965510E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.4533653136029319E+00   6.0687275051312417E+00   1.0019891100094878E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.9761889706887952E+00   1.1674478906081401E+01   4.8561688476369920E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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3.9671928005380170E+00   5.4726551238633947E+00   1.1832705412607186E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.9983240781662008E+00   2.9681599839855473E+00   4.3595173850941489E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.2608680200348577E+00   5.0977017330861862E+00   1.2520743294803125E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.0982977772052562E+00   1.1269477731949241E+01   3.7436763108539290E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0885533512048971E+01   9.2248750077347843E+00   5.7749375192793231E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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6.4361062497160066E+00   1.0244799205467636E+00   3.6685163469687070E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.7199066723298433E+00   7.5340253557489660E+00   4.7187300255244219E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.8813609432878713E+00   7.4180219962945673E+00   4.4904102217954494E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.6815981102617661E+00   1.1796151426596172E+01   1.0216214067972113E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.5948748984143033E+00   2.6968682181864012E+00   6.7027704303450608E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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7.1676839035107980E+00   2.0215183717731056E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.5601922932628063E+00   1.1501134981593250E+01   8.6696048745733290E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.4870922618817097E+00   5.3241433605582680E+00   1.1035421714066176E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.0316891928159961E+00   1.4498271064450323E+00   6.8307935352199376E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.4463396961891530E+00   7.5966708326010366E+00   1.2484368531415825E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.1905622710887575E-02   1.1306666892034372E+01   6.3075487723078476E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2556972419585222E+01   5.2906524685376697E+00   3.8863648399140888E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2324742651765792E+01   1.4215546341780805E+00   4.8514412165203463E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5055639059288364E-01   7.3961000493584770E+00   6.1624053444867917E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.9557234251897881E+00   1.1364713144160351E+01   1.2396513559844616E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   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5.5773893379608381E+00   8.6154056793420590E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.5257622635263530E+00   3.1263575942776862E+00   1.0649427956733236E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.0305295871407125E+00   9.3018536724691145E+00   9.1712717101656125E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5008877703643368E+00   6.6740776969749511E+00   1.8558675222955645E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.2991139175455642E+00   3.1190379331392766E+00   4.1969351436963933E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3440956124061021E+01   1.1285430380536450E+01   4.5622060389511343E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2172959761116150E+01   7.2353803880232412E+00   3.7681936830156184E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.3216251754510751E+00   9.4660159239941493E+00   8.8612039123225568E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.5681323506957225E+00   5.9720499095580406E+00   8.2806058105770912E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.4353050599074000E+00   1.5080235002722113E+00   1.2296628161677626E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.8606642485190310E+00   7.4412428889589002E+00   7.1991543423011386E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1946248626201590E+00   5.1495089666726657E-01   1.4778561147099196E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.2067899127560802E+00   5.5848095867803478E+00   5.3530137997768978E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.5039538146692752E+00   6.9567835151226465E-01   3.2829508479318714E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5466131877670355E+00   7.5629860129972730E+00   6.0660675441839484E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.9302078870126951E+00   7.2124996430383934E+00   4.5810474148225868E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1615365337539822E+00   2.0057881897864638E-01   1.2698953252453705E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.7667886543924989E+00   2.8770584365799974E+00   9.3162991782703275E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.4315471997136697E+00   6.6837558107943602E+00   5.0908458038040010E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5905133948638532E+00   4.6106683252816538E-01   1.1149003636382906E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4722930307045969E+00   6.0623642125576618E+00   4.6976883951766784E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.7225631942431092E+00   1.7447146084694913E+00   8.9209943856236205E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.6980840250695062E+00   9.0293496716072745E+00   1.2118184387230375E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1877117795008701E+01   1.1038059711187731E+01   4.6101537189836188E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00 \natom  -8.4105269576189412E-02   1.1623704516863253E+01   1.8402503528212910E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2831517934591218E+01   5.1484842201743923E+00   4.5790583779450991E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2705670256101378E+01   1.3563738314546079E+00   4.9052830467565771E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.4546452468732768E-01   7.4359746919524721E+00   2.0132822837106019E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.6499576503092639E+00   1.1131801276290521E+01   8.7784669328731866E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.3251415947671852E+00   5.1929273982116992E+00   1.1208355707364728E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.8771520751269719E+00   1.1741558805792018E+00   6.9840700198348262E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.1834582362430308E+00   7.4873659852141810E+00   1.2593467458529188E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.5290772074762771E-01   1.1159684571814083E+01   6.4345648094753587E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2570010331690799E+01   5.3549504770437206E+00   3.8418593762540421E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2437257163069809E+01   1.5878627909038958E+00   5.9223994240161437E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1583156344082308E-01   7.3899086862017480E+00   6.1200414975518642E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.1968256763271099E+00   1.1277806191166803E+01   1.2942218807712178E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.8269327453758564E+00   5.2484975839901100E+00   6.8252558151342813E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.0981720309605181E+00   1.3060130347210730E+00   7.8013955954921705E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.6624365599151383E+00   7.2520121116691376E+00   1.1568421431225898E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1339320321895476E+00   1.0971625323367572E+01   5.3030668509624608E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.8599998508962985E+00   5.4021272452744507E+00   1.1119957491569141E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.6288385215446493E+00   1.4457222150572639E+00   1.4871735911403550E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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9.7844148081449056E+00   3.2753222502668571E+00   3.3659319770067921E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.7128461182112096E+00   3.2185341496828057E+00   5.4491617936638104E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.9084021612286239E+00   9.2060562101176835E+00   1.5575746543011699E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3076363560252253E+00   9.2456341946269269E+00   8.0810515237112188E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4220000036916334E+00   3.2915320321874528E+00   1.1805475021515589E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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2.4457853445512110E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.5229211498357880E+00   9.2184987727507739E+00   9.0344389825395144E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.0353939868858788E+00   3.3685769626369071E+00   1.0635491478232687E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1804851950506032E+00   9.0578743254339642E+00   9.0226767554281402E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.1238864884590640E-01   7.0299138884006673E+00   1.0999562836259758E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.0251756674255628E+00   9.1145432043932715E+00   2.7121449113928278E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.4831156480709353E+00   5.1673324594333421E+00   2.7293382286494161E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.8494744237788652E+00   1.2795566551296529E+00   2.3620434741625380E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.1620221057071540E+00   9.5481365960942419E+00   5.9427894588253123E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.7022580254608322E-01   1.1312726278456211E+01   1.0535540800991898E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.6743991868853523E+00   6.5485457937727185E+00   9.4728856629293556E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.6649754100131275E+00   3.4156852284765988E+00   8.7791708590367756E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.8227535260506320E+00   6.2127623469399653E+00   6.5133779489064025E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5414787797599230E+00   9.3295625943832121E+00   1.2232210030947927E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.0535718645186303E+00   3.2943579852088121E+00   7.1730205657629407E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.1465919656352908E+00   1.4034719823082018E+00   1.1807292890989078E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0056179754943173E+01   7.2281877124207021E+00   7.1658161437773531E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3816985666024138E+01   4.3464385793428179E-01   3.0271196014599751E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.0326143625490207E+00   5.2851078830675897E+00   5.9536339580727704E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -8.9665340715785580E-01   1.0302434329283408E+00   5.6725330943326577E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2495342454171530E+00   6.4309410896626638E+00   1.1419859564441218E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0201091026472657E+01   1.1242156757531312E+01   7.2548135786996912E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.7636234225373588E+00   3.9454251100387809E+00   1.0561546212325618E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.1381886851947849E-01   1.3350630295595629E+00   2.9444904513814349E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.2806991235177954E-01   6.1660320297119187E+00   8.0149768225757025E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.7539258501426289E-02   1.3762602960606980E+00   3.3151142707946779E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.0429181130089660E+00   3.0962552815462091E-01   4.9986152103811126E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.2527661323906738E+00   9.0264100825377808E-02   6.7857403469705702E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.8881150610103123E+00   1.1500170891844082E+01   1.1190839153497478E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.0216695629876509E+00   9.1192377287631317E+00   5.9201522152961603E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -6.7047990212346367E+00   6.5265343678742207E+00   1.2913391965256588E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.9427411888642681E+00   3.1503020697037769E+00   7.3924952872800418E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.3840684344361565E+00   9.4123737658869331E+00   1.2495172998661777E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.6819913990007207E+00   2.4438543461619200E+00   7.5932170709267393E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3444499075025579E+01   3.4216766235082021E+00   1.1665294919382654E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1097635957305958E+01   3.0699632082847234E-01   1.9674781236822780E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.9335892757935094E+00   5.5317852730042096E+00   9.2370162765570960E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.7180818559633160E+00   3.4448245931714689E+00   1.1267862475473811E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.1528799544290189E+00   4.2208101459716492E+00   7.5777153442032636E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.3266214198746669E+00   1.1851654074895492E+01   6.6168116471225673E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.1719729950711468E+00   5.6698160746623669E+00   3.2079824508596628E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.3453655728019633E+00   1.4045981780041259E+00   8.7187001661387615E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0773136849305370E+01   6.0913100615551938E+00   1.5818792661417169E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.8793169221377338E-01   3.3532987213358658E+00   1.0552632288596069E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.4154146982264306E+00   9.1830840451157023E+00   5.1554381624532759E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2778800111753849E+01   9.8939123069251274E+00   2.3629124380584221E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.6651150361651545E-01   3.5114566863404590E+00   4.1244935320238580E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0156188650007866E+01   6.2528478678486529E-02   9.7337041052518476E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.8151036364569046E+00   6.4066681018639686E+00   1.0027796459480115E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.7358675076933032E+00  -1.8940546054884322E-02   4.9218464031500080E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -9.1597410566388981E-02   9.5944281155874123E+00   1.2270894648015648E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.7256353551979069E+00   2.8626221603628893E-01   1.1857961992199279E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1312662037987369E+00   5.2886307668794510E+00   2.0945672697950490E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.6881441705056028E+00   1.1358327252259542E+01   1.2319227932153445E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2886458814013091E+00   6.5232923133368272E+00   2.9385454708783958E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.1954182054884108E+00   6.1491530430867227E+00   1.1183980550896989E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.5708898371891848E+00   7.3605266936507858E+00   1.0523608269671637E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.8210805212912717E+00   9.2385067005665995E+00   2.8022562355602458E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.6454089431191703E+00   5.5403190705157126E+00   1.2745191439997289E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.7287364048955798E+00   1.1384217017047760E+00   6.0796050356999949E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2187462355797869E+01   6.2529625194096869E+00   6.4503349972846458E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.2072446289817922E+00   1.1084023520861212E+01   7.8193786364741351E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.6195200791068659E-01   4.3866966121295259E-01   8.2084250634995328E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.9913312796673641E+00   4.2264069309850211E-01   9.9320619649552757E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.8293430475432171E+00   5.2327103621759816E+00   1.1801557746705939E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.5992029389751385E+00   3.0062727773939297E+00   4.2408292173355804E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.5089237984823018E+00   5.2633229822618466E+00   1.2544936774308647E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.4702821762185536E+00   1.1531471447737683E+01   3.9566974906696268E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0957765796874678E+01   9.2542931994312845E+00   5.5750702694856678E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.6969010419700981E+00  -2.2825884697751729E-02   8.5155977038653052E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.4642514592757077E+00   5.1423301075366492E+00   8.4460990245945720E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.1139899466727936E+00   3.2671483361483240E+00   1.0324006394442931E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.2801503502305618E+00   9.3453767186394607E+00   9.3892539482401354E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5823346516980892E+00   6.7751221573028015E+00   1.8569275184024621E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.9663018571982041E+00   3.6777412994094920E+00   4.1396201606139780E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3677293585201948E+01   1.1757314458738712E+01   6.0096158025773905E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1813646962595559E+01   7.2131335063550015E+00   4.1702170527246096E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.9140560286380115E+00   9.5524504248242970E+00   9.0184300982018311E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.4376049341932351E+00   6.6025136011533023E+00   7.8350241369176485E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.3245691583235342E+00   1.2026360295084020E+00   1.2893206497856408E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.5579137436509574E+00   7.4334181357969449E+00   6.9269547454907707E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.0749220404130742E+00   2.3615213929354181E-01   1.9696911441978120E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.9947475181973200E+00   5.3120660066626080E+00   5.2225534154096920E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.8063545994004038E+00   5.9115483699208826E-01   3.7010756147151098E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.8140173236659942E+00   7.4303020274488834E+00   5.6837417081783148E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.9190964437366151E+00   7.2847770577778110E+00   4.2276866168327540E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.3815197118390596E-01   2.8698042603163582E-01   1.2824504717727418E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.0358390642092514E+00   3.2845013039680238E+00   8.8530961082812509E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.5526370835552363E+00   6.0437694392108785E+00   4.8691398125452636E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.4251899788524423E+00   7.0558212574004053E-01   1.1419565628702628E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4139700973293852E+00   6.2678371178254517E+00   4.7135352769466898E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.8804015876084117E+00   1.2469026000520749E+00   9.6035379807636652E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.5051117609080231E+00   9.4368776977269668E+00   1.2322573598539819E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1887496178608679E+01   1.1384981807718891E+01   4.4723096694390936E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3621849718993328E+01   7.6914665552804626E+00   1.0756963972948621E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5769805075932117E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   2.1277288814191605E-02   1.2063851949195778E+01   0.0000000000000000E+00\nlattice  -6.9104859333970072E+00  -3.0802334263471075E-02   1.2732303473489672E+01\natom   9.5691671944283438E+00   1.4073502901239154E+00   1.0884949576080810E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.6116148899261096E+00   7.4401631035966904E+00   8.2220915670924093E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.6746911698919351E-01   1.1558643553382904E+01   2.0452013447887749E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2992011491387315E+01   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0.0000000000000000E+00 \natom   6.0441033525443286E+00   6.6395156427925919E+00   3.0368533806155287E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.1033105487737487E+00   6.1833156743839961E+00   1.1079917758684299E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.6084346446036335E+00   7.4202117272962544E+00   1.0120549309882907E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.5584020408543573E+00   9.4286860185313159E+00   2.6765130902763388E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.8677119764398835E+00   6.4687666252305460E+00   7.0262396452062004E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.1857561005625588E+00   1.1070500926605105E+00   5.9036239874058021E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2014547990933774E+01   6.2207814224955280E+00   6.3557256352684872E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.1576524936562906E+00   1.1142080743186254E+01   8.0898800027753790E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.7258661877032200E-01   5.6223945500069217E-01   8.3119565042970702E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.9606611680869843E+00   4.9616231536953243E-01   9.9146065192935957E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7648197662853344E+00   5.3825490565546747E+00   1.1645242095396632E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.0715106298333659E+00   2.7506344990598066E+00   4.0935825237062868E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.2332860643428623E+00   5.4499509578452896E+00   1.2267117949506332E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.1618511674600214E+00   1.1341398288718244E+01   3.9114748251352029E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0813946845354316E+01   8.9272742639226159E+00   5.6470998588317078E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.1306830240339423E+00   1.2019050670739954E+01   8.2921166283469834E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.4300861881627887E+00   5.0062911401858443E+00   8.7937708515710575E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.5540777639956795E+00   3.0149276345887395E+00   1.0418663849651551E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.2538141150041753E+00   9.4075611008227096E+00   9.0722179636515854E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.4981988065302545E+00   6.8572161175860549E+00   1.8009279652461727E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.9870817857770162E+00   3.2324394982309395E+00   3.9440170757874320E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3829705013372726E+01   1.1609263412193464E+01   5.9104316293144510E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2070906944028286E+01   7.3304479320198661E+00   3.7759465737145548E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.9105880531689952E+00   9.6493134634484701E+00   8.9141694771308906E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.0939691750852205E+00   6.2476747515762598E+00   7.5964934234943984E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.4641394855046905E+00   1.5065958110550715E+00   1.2325409302926950E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.2310010668579143E+00   7.3838546545089061E+00   6.8630349817768606E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.7954724905531014E+00   4.8460703265369476E-01   1.6756774009478619E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.1361394550449457E+00   5.3923823652392544E+00   4.9197184968319059E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.8327280574930125E+00   5.4780717008153079E-01   3.3842201427806180E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.8393674183472140E+00   7.5953773762029142E+00   7.6162033068212032E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.6186366064219904E+00   7.2029246817402530E+00   4.4040965235161371E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2013597928944701E+00   4.4620327451390923E-01   1.2567162284375300E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.9247971970201814E+00   3.0028560351300855E+00   1.2716794987509257E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.7616905589991596E+00   6.5371452357650828E+00   4.8899098407931865E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.7401276135356829E+00   9.1808630953270487E-01   1.1153299770419359E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4920603984374674E+00   5.9231137628551629E+00   4.4380962006938480E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.2313696007078585E+00   1.4796452225265715E+00   9.1737526247151848E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.9197784063257757E+00   9.3207242110402841E+00   1.2447901320735181E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1673604494296816E+01   1.1349964576007135E+01   4.5396067353942238E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3441046048798365E+01   7.4194202432950203E+00   1.0015025809027200E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5575043731045179E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   3.0409232129953438E-02   1.1988108980651290E+01   0.0000000000000000E+00\nlattice  -6.5887882326427283E+00  -2.6164269794931638E-02   1.2965249033324683E+01\natom   9.7025291301781369E+00   1.4470083018821835E+00   1.0985699957053511E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.0413513003417361E+00   7.4621640538952345E+00   8.2054459701583813E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.9699262454622075E-02   1.1456975059019786E+01   1.7740543931504988E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2932293861504579E+01   5.1232706353785611E+00   4.5648592963482999E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2909193411486150E+01   1.3759010664270215E+00   4.6220121782471040E+00  S   0.0000000000000000E+00   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3.9760526967999976E-02  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.0582052903761143E-01   1.1328130309404788E+01   6.4648373009630999E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2232739787310329E+01   5.2280573403455577E+00   4.2218538994145782E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2370024612020551E+01   1.4478304291343005E+00   3.0709597822698087E-01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4918290149510192E-01   7.4367289185950103E+00   6.4655939539219469E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.6251749553167381E+00   1.1135735245000429E+01   9.7006642818298905E-02  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.0547543705721871E+00   5.3510535259729419E+00   6.9154497112468940E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.4573610837774789E+00   1.6164662784189345E+00   7.8289655990749756E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.6061234158312838E+00   7.4035256811455099E+00   1.2131841014857661E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2419025521049445E+00   1.1353400664317146E+01   5.4372901732348460E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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-2.7842729973035052E-01   9.3260796147032927E+00   1.0075753085026633E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.6821061622507929E+00   9.3020416275864122E+00   3.6681883159473787E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.7303130131225384E+00   3.2997846487896294E+00   3.0211754230915391E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.9924717168073762E+00   3.3871030414299037E+00   5.2081672322035457E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.7539563520529047E+00   9.2686816273649271E+00   1.6862781348197138E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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3.6538946472683058E+00   1.3923680297603986E+00   1.2487510410566831E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.4082056598815060E+00   7.4627962770245304E+00   7.2372575301406679E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.6140287719400570E+00   8.6921850566313152E-01   1.5777763333379708E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.1189179630867319E+00   5.3309129748587454E+00   5.5122006237790790E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.4118522634241426E+00   5.6250265327244586E-01   3.5566041948051961E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.5794003604287372E+00   7.1235278479056223E+00   7.4358479436075209E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7205169271144038E+00   7.5467661532381518E+00   4.7603436932538576E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1666974797215819E+00   3.4860091109324171E-01   1.2906871245183421E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3944587245842559E+00   3.0135950993230867E+00   6.3887217761683213E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.5566412375440422E+00   6.7018519941073853E+00   5.2721054062541706E+00 Cu   0.0000000000000000E+00   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6.8382432705177909E-02   9.6009389844959028E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.6294811439311525E+00   5.6066221656894051E+00   9.5255417498370623E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.0063280394647753E+00   3.5693535415709743E-01   5.1628478403769718E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.6449758597943038E-01   9.5777758921887362E+00   1.2209138902772365E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.6107105848362546E+00   3.2608366886192025E-01   1.1569037838186796E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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5.1002527737386014E+00   1.2382425234350906E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.2425204582873954E+00   1.1473504070426159E+01   3.9229008046390157E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0659586294823900E+01   9.1345009794363055E+00   5.5680530005949738E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.4130903855818904E+00   4.9778008531173729E-02   7.9310864532777554E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.2994057919252806E+00   5.0006935341606553E+00   8.5072827864289451E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.6008626684798788E+00   3.1199429744859759E+00   1.0530642408696375E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.2729550731590358E+00   9.1208436426060988E+00   9.4270914727125650E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.6143334043407025E+00   6.2065401851315167E+00   1.7478076372247335E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.0676729727569878E+00   3.3562062296152790E+00   4.2716453890520718E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3598892178106109E+01   1.1575152204886630E+01   6.6708542111346236E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   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7.3395024067723664E+00   4.6471808651198865E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.9343685634708514E-01   3.8428761011985635E-01   1.2609185215474096E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.6166255969356864E+00   2.9761476712938220E+00   8.2120099350891218E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.9227314648383214E+00   5.9154767846937704E+00   5.1613162080299055E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.0221197333047334E+00   7.3736451887972221E-01   1.0974279424589806E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5519309979465451E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice  -8.6714989976807114E-02   1.2004390300016890E+01   0.0000000000000000E+00\nlattice  -6.7622335281720014E+00  -9.0707374161257973E-02   1.2996703607977691E+01\natom   9.2747785108571996E+00   1.3363436954293759E+00   1.1256846997099119E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.4478828577410305E+00   7.1765744532540632E+00   8.6104655689138774E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -5.3826619971261508E-02   1.1049425114590052E+01   1.7358140322810278E+00  S   0.0000000000000000E+00   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0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.8730491567480367E+00   5.1565551840061792E+00   5.5509939145507978E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.4620306777527396E+00   3.4829917316700953E-01   3.6545208730425376E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.7889431136138629E+00   7.1484236738825162E+00   7.7852994392238672E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5610477046026583E+00   7.2748197039202340E+00   4.2057329049080323E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.9027851078365767E+00   4.7460318648007543E-01   2.8276288142571049E-02 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.7796728001719604E+00   2.8448408791396367E+00   9.5366702382056745E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.3340211429309363E+00   6.3236169830494511E+00   4.9313084002247685E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.2997737182832969E+00   2.2058889137298487E-01   1.1489153924932308E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3231545972270944E+00   6.0634178670359971E+00   5.0213624565753374E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.6002420469184093E+00   1.0472974357529534E+00   9.0858156068026243E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.4285121432320027E+00   8.8304921429503391E+00   1.2508101513427968E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1468356022847260E+01   1.1379284629433084E+01   4.4819007957797234E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3221842388386399E+01   7.3216572801766748E+00   1.2088411663475014E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\nbegin\ncomment Generated from states.cdmp, TIMESTEP: 0\nlattice   1.5758192382291153E+01   0.0000000000000000E+00   0.0000000000000000E+00\nlattice   4.4575020620614983E-02   1.1891333754785450E+01   0.0000000000000000E+00\nlattice  -6.7606075681747342E+00  -1.0547094270861174E-01   1.2824844005082056E+01\natom   9.6422738853523775E+00   1.2113888308894287E+00   1.1018848575323666E+01  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.5458744672691571E+00   7.1821875879970110E+00   8.5105821539151982E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -9.9147258615371325E-02   1.1026458313761541E+01   1.9636036822040799E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2952982373150078E+01   5.1579606333175176E+00   4.7288975949799852E+00  S   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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8.0468041643560859E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4628822853237831E+00   9.3088480709302921E+00   8.8398263355354842E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.0616331464142146E-01   7.2559927532843966E+00   1.0135480061250163E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -4.2804963141159620E+00   8.9638922406120720E+00   1.2440060017732865E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.2186321977517132E+00   4.9728832710771975E+00   2.2414836222896941E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   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1.1064136559357671E+01   7.9094266891685816E-01   1.8572793068502549E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -1.7493404130625190E-01   3.0506960858383998E+00   4.3007207412942066E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.6939890567418487E+00   3.2653190731253798E+00   1.0782161267824456E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0549774810051542E+01   6.3972031835019267E+00   9.8493283266788616E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0624359062799105E+00   6.4863275850641888E-01   4.8596268437799370E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   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5.4096421717320533E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.7584598974231569E+00   5.8671721018227778E+00   6.8886097875265433E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.5995089538505232E+00   1.1047349842291791E+01   7.3049636893436958E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4826998474793207E-01   2.5385995388069477E-01   8.5457115468847533E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.7620669492007219E+00  -5.8554186689153694E-02   9.8324120117153164E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.7994859016312090E+00   5.0697482707833732E+00   1.2399009973239455E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.0216440736446017E+00   3.7348858030885257E+00   4.0724208812358258E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -3.8982163153963674E+00   5.2874389521743836E+00   1.1851434701369875E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.0623863619495379E+00   1.1184022300203200E+01   4.4292837663723015E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.0940588705963400E+01   9.3989504273350093E+00   5.7144309608477153E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.1758753232495662E+00   9.2892577382483559E+00   5.7735680247098946E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.7209826413010729E+00   5.2538850484074882E+00   9.4021173035373451E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.6240244282699852E+00   3.1859605956196098E+00   1.0608772595946235E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.7456565373722501E+00   9.1923113092203437E+00   9.0149797326303975E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.9958392848477251E+00   5.8596503655361110E+00   1.7243444397434049E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.9358227921628459E+00   3.0948604668368409E+00   4.5435798541881072E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3556119340852959E+01   1.1077390416323169E+01   1.4944071434553958E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1780456119631030E+01   7.1799555796857417E+00   4.5864760936049933E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.7360341634976031E+00   8.8867206788623285E+00   9.0265331142588856E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.0166692986030910E+00   5.9353467053141147E+00   8.3377110599112090E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.0562810377773015E+00   1.2113854232971777E+00   1.2249340093139246E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.0996034778505619E+00   6.9076141571805119E+00   7.6780320621810727E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   3.5835906216040430E+00   1.4545277188992459E-01   1.9952993432177579E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.0373881026962462E+00   5.3886892135831399E+00   5.7877749009793957E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.3492003687469527E+00   3.7809654114708541E-01   3.5385659425196638E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   5.7922267018130373E+00   7.1208848994252731E+00   1.1876692859565634E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   4.3625979411341635E+00   7.2913715045309377E+00   3.6935766025091561E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   8.1793894120119877E+00   5.0137257078074482E-01   3.8765382017970246E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   2.1509197141340408E+00   3.6454034314053478E+00   1.2175039573280326E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   9.3500652741561190E+00   5.9114312702881699E+00   4.7215507934658190E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   6.2664376210609749E+00   1.1691342851643149E+01   1.1541425067405825E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.6931308314572551E+00   6.5350827593648990E+00   5.2279681153854405E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom  -2.3917432635696709E+00   1.1481213328521969E+00   8.7526782630552162E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   7.8150752187773556E+00   9.8117709005181020E+00   1.2166502715268123E+01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.2104857736378669E+01   1.1127929381952512E+01   3.7460376484983460E+00 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3860415110105070E+01   7.2222525677589360E+00   6.8475277147619618E-01 Cu   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\n"
  },
  {
    "path": "examples/nnp-comp2/Cu2S_PBE/nnp-data-1/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.9058400653162604E+00\nconv_energy   1.1065438723452953E+01\nconv_length   1.1108978337775813E+01\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type.\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              15 15          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \n#symfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\n#symfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \n# symfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\n# symfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \n# symfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n"
  },
  {
    "path": "examples/nnp-comp2/Cu2S_PBE/nnp-data-1/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   4.4265075533537512E-01   2.4749666370750694E+00   1.1060722509726018E+00   1.7529945320684118E-01\n         1          2   1.9388935120109099E+00   4.4097236813336176E+00   3.2978532722457570E+00   2.5128573402537990E-01\n         1          3   1.0807838070518886E-02   4.1304458483662820E-01   7.1868741885005083E-02   3.4662740758690899E-02\n         1          4   2.6547690535721169E+00   5.1765886817791573E+00   4.0454007565017012E+00   2.5579520863782829E-01\n         1          5   1.4995320530771344E-01   1.3519360603219461E+00   5.0922021208534995E-01   1.2262469346514367E-01\n         1          6   1.3478375671698186E+00   4.1418336720929823E+00   2.5639172172860367E+00   3.7353134785219438E-01\n         1          7   8.1186515243907842E-01   2.4990660558808346E+00   1.5882886682336448E+00   1.6357025849311374E-01\n         1          8   8.3560066574306779E-01   3.5190788505185737E+00   1.8937518336778314E+00   3.5586606866248682E-01\n         1          9   1.3835259104473252E+00   2.6464501497863053E+00   2.2079115860694039E+00   1.3890110758612836E-01\n         1         10   1.1951184603566023E+00   2.8927959575917903E+00   2.0316656202063745E+00   2.0737960708933709E-01\n         1         11   9.8808644349834496E-01   1.6027978035707744E+00   1.3843071713511630E+00   7.8529797179971425E-02\n         1         12   9.1981902848818131E-01   2.2238977642164559E+00   1.6225786253237706E+00   1.8739973313204333E-01\n         1         13   4.0816882531663007E-01   1.1121383932041731E+00   8.0641623097483783E-01   9.8682708643096709E-02\n         1         14   2.2597919343915630E-02   1.2708403027630688E-01   5.1881770327387181E-02   8.3606264892797395E-03\n         1         15   3.8408359796381125E-01   9.9411428648517852E-01   6.2027578566565089E-01   5.8321113787023079E-02\n         1         16   1.4083722552013387E+00   4.0837798882115868E+00   2.3948910589466421E+00   2.7205794214050266E-01\n         1         17   7.1017533056026858E-02   3.5924947585956063E-01   1.5467611295933245E-01   2.3262660654328696E-02\n         1         18   2.2565953627627136E+00   4.5529270325456537E+00   3.2026845490445135E+00   2.2099610481145684E-01\n         1         19   2.9798875096866855E+00   6.8397125214329391E+00   4.6222211152781112E+00   4.9994275841001823E-01\n         1         20   8.3935452330094168E-02   4.9012718923180415E-01   2.1931677551585280E-01   3.8677705768792127E-02\n         1         21   1.8289258558169381E-02   8.3618131814199373E-02   3.8152360442568929E-02   5.6588748087349648E-03\n         1         22   1.3046135311117131E+00   2.4200616155686863E+00   1.7341246117915960E+00   1.1785806355696596E-01\n         1         23   8.0199454261870406E-01   1.9483510241268203E+00   1.2961643168731083E+00   1.4672710574320125E-01\n         1         24   6.4374558536931794E-03   4.8182460226993802E-02   1.6707732409685424E-02   3.2034525707065878E-03\n         1         25   1.5318897938282255E-01   4.5416402718924276E-01   2.6291575700052811E-01   2.8677843631321493E-02\n         1         26   6.9418423813301466E-01   2.4541868250982004E+00   1.3137330249991466E+00   1.6387572931667668E-01\n         1         27   2.0299364848972126E-02   1.3683512999502856E-01   4.9832084435863372E-02   8.9516084933796824E-03\n         1         28   9.8701872413726255E-01   2.2586534755453709E+00   1.4780519754057804E+00   1.1871005779401544E-01\n         1         29   1.5186918852877633E+00   3.9050329487971425E+00   2.4766215129303397E+00   2.9079756604312895E-01\n         1         30   3.8161695126727853E-02   2.7674887655318292E-01   1.1058155022715112E-01   2.1905596415412825E-02\n         1         31   5.8977740954298397E-01   1.2386293684496201E+00   8.2364153102433180E-01   6.5551076498813768E-02\n         1         32   3.8193645094435219E-01   1.0506523465236675E+00   6.4620992439490277E-01   8.2156802905661991E-02\n         1         33   6.4597446487351350E-03   1.0699762617667154E-01   2.6412435342863798E-02   6.6449440626847088E-03\n         1         34   3.5736611503091914E-03   2.7529951654377712E-02   8.3504346203378647E-03   1.8855808380056672E-03\n         1         35   1.4133754202830619E-02   1.4099822922781846E-01   4.8306571362672600E-02   1.0997547989269251E-02\n         1         36   1.0877216711266600E+00   2.8800857695995274E+00   1.8376742285101342E+00   1.7208854608735455E-01\n         1         37   8.8783936606988565E+00   1.4736206648360312E+01   1.1698178703687816E+01   6.1086423843563575E-01\n         1         38   1.3732816872509948E+01   2.4205696120591984E+01   1.8301681574699320E+01   1.4667109447685063E+00\n         1         39   9.0278290856362930E-01   2.4756737855204465E+00   1.5308385269169829E+00   1.4436373406542297E-01\n         1         40   8.9087476076510974E+00   1.4693677789914243E+01   1.1598835757597929E+01   6.1413283845889899E-01\n         1         41   1.1456139379005354E+01   2.1316973822535566E+01   1.5642394988112523E+01   1.3052104326252827E+00\n         1         42   3.1207603245335580E-01   7.9305367236179369E-01   5.2362587414852413E-01   4.9119449966743223E-02\n         1         43   2.5379941726465405E+00   4.3361767105514337E+00   3.3765899739621799E+00   1.8298023565504315E-01\n         1         44   3.6421208177618460E+00   6.8311536891079561E+00   5.0762844334415771E+00   4.5568219422020401E-01\n         1         45   1.3689487135523365E-01   3.6820433872931851E-01   2.2763176703809612E-01   2.1660654887416739E-02\n         1         46   2.5649159161016786E+00   4.1963702184459795E+00   3.2443756016118601E+00   1.8134089138334111E-01\n         1         47   2.0642465841299500E+00   4.1692860632438746E+00   2.9548001264619574E+00   2.6394004100571961E-01\n         1         48   4.6512029522926740E-01   1.4664174976442483E+00   8.5498686781623590E-01   9.3059828249480767E-02\n         1         49   4.6547662784275197E+00   8.4479388434646854E+00   6.4237386473137450E+00   3.8411325204761104E-01\n         1         50   8.6415653134619532E+00   1.6278459810269940E+01   1.1787210979312956E+01   1.0179454392709681E+00\n         1         51   3.8547816500338000E-01   1.2767023692244872E+00   7.1226405976144813E-01   7.8602173939313374E-02\n         1         52   4.6789216668759375E+00   8.4098137810639617E+00   6.3515226749250546E+00   3.8255728791957827E-01\n         1         53   6.9948460709494453E+00   1.3576561360549128E+01   9.8530015506444073E+00   8.9220167841463538E-01\n         1         54   1.3368052908889996E-01   3.9480780749423111E-01   2.4318877739968350E-01   2.6424765019592393E-02\n         1         55   1.3296050002218320E+00   2.5112834184004242E+00   1.8605136293226228E+00   1.1617142815775323E-01\n         1         56   2.2651205823176861E+00   4.5657352835038028E+00   3.2381271278722017E+00   3.2239976604583942E-01\n         1         57   5.8271222801219491E-02   1.8954030778131817E-01   1.0498686421401084E-01   1.1616221414215330E-02\n         1         58   1.3485470042844463E+00   2.4053107174498130E+00   1.7699194452312146E+00   1.1270742957344337E-01\n         1         59   1.1637151841314661E+00   2.5500691319681228E+00   1.7421774640240988E+00   1.7312511619868448E-01\n         1         60   5.8091597474659751E-02   2.3494762568236605E-01   1.1437039970122209E-01   1.7173555213931348E-02\n         1         61   4.4790780968218247E-01   1.8123258976262868E+00   9.1548128537474582E-01   1.2057744180124463E-01\n         1         62   5.6625365929518660E-02   2.3732586931975447E-01   1.1026918667512448E-01   1.6052748969046394E-02\n         1         63   3.2703691263144347E-01   1.2807469549823705E+00   6.7617223012470840E-01   8.8530225610365720E-02\n         1         64   3.5654812189807282E-02   1.4389848715155315E-01   7.2964299421384674E-02   1.1496198432486410E-02\n         2          1   1.5743455957850613E-01   1.5073065774351941E+00   5.5303612548630132E-01   1.1899585890474287E-01\n         2          2   1.0499049602999246E-02   8.6977355932082434E-01   1.8767905028057794E-01   8.0999273778781938E-02\n         2          3   8.1374754443656305E-01   2.4261950387937841E+00   1.6489266361228783E+00   1.8141831271144424E-01\n         2          4   1.6145285517255994E-01   2.5518950524850439E+00   1.1085810713423514E+00   3.0666977013499336E-01\n         2          5   9.4883860757335603E-01   2.6710371110933706E+00   2.0227003782508501E+00   1.9067433597095923E-01\n         2          6   9.6539811175376589E-01   4.8423104282718699E+00   2.8219530812454505E+00   4.7918479666939673E-01\n         2          7   4.7529037518360068E-01   2.3097294285577390E+00   1.2819586086430184E+00   1.9684407624800027E-01\n         2          8   1.7095723912637146E+00   5.1341988940591596E+00   3.4864385967612606E+00   3.8797019939122079E-01\n         2          9   3.1233518617392186E-01   1.8219399362068016E+00   9.4687591683891648E-01   1.9153423627191457E-01\n         2         10   1.4849362232349019E+00   4.3982496825582134E+00   2.8497598112262224E+00   3.4995896483784322E-01\n         2         11   3.5767426586678325E-01   1.6223983964512552E+00   1.0158328101031879E+00   2.0438269411930965E-01\n         2         12   1.0137865774210515E+00   3.5680165380478712E+00   2.1790772630319624E+00   3.3886299872978104E-01\n         2         13   3.0941620316795870E-01   1.2113971995541650E+00   8.1128931266188542E-01   1.3619945830873967E-01\n         2         14   8.0297363351047590E-01   2.3107656663902336E+00   1.4508630468415395E+00   1.9851647413327050E-01\n         2         15   1.4039898861459954E-01   6.1468637178325269E-01   4.0320811548741942E-01   6.3527049808239547E-02\n         2         16   2.0707073331993908E-01   1.0337121848367778E+00   4.8189215108834055E-01   8.2852701405279283E-02\n         2         17   8.2193625876920096E-01   2.6219750037393883E+00   1.6246945966895010E+00   1.6181008698586691E-01\n         2         18   3.4456131789121569E-01   1.9177774581312250E+00   9.1804106293915821E-01   1.9508948177749674E-01\n         2         19   2.4458465228606030E-01   9.2849994113117507E-01   4.7384793258920110E-01   6.6048360078919607E-02\n         2         20   3.8379277734053305E+00   7.3005509674816178E+00   5.3924175775352499E+00   3.4350110848414023E-01\n         2         21   1.3880228332655034E+00   4.3361502232155660E+00   2.5900317962172914E+00   3.7347009392110642E-01\n         2         22   2.1484844584477185E-02   2.6334808335921994E-01   7.2660811029078703E-02   1.5611227962074608E-02\n         2         23   2.3312476084988785E-02   2.9805602022674860E-01   8.8306912423691541E-02   1.9292008893662619E-02\n         2         24   2.3557010049827989E-03   1.3344124238795912E-01   3.1300938638510842E-02   1.5186282501073151E-02\n         2         25   2.7195526816721900E-02   1.2294682924678357E-01   5.9508063803285792E-02   9.1362387893595305E-03\n         2         26   1.8338777683487169E+00   3.1165354847033653E+00   2.3131465623530860E+00   1.2906733784622765E-01\n         2         27   4.9520703398617671E-01   1.3739936187945998E+00   8.5886930842858833E-01   1.0719798991816548E-01\n         2         28   8.3372459829371623E-02   5.9799519441710691E-01   2.3109776020291722E-01   4.7860816214886359E-02\n         2         29   3.8387545763852293E-01   1.5190933343391366E+00   8.5913087479927619E-01   9.8683853404507374E-02\n         2         30   1.3695758827157153E-01   9.8943867324686252E-01   4.3201869514899510E-01   1.0492395861599907E-01\n         2         31   9.2344997100998055E-02   4.6313711150328485E-01   2.0414417289865988E-01   3.4759250455299269E-02\n         2         32   1.9125391528191629E+00   4.2554336862028403E+00   2.9312236631302082E+00   2.2284144795806357E-01\n         2         33   5.6703537659832792E-01   2.2331423792366145E+00   1.2254617118290669E+00   2.1291909229192083E-01\n         2         34   8.7466581491831251E-03   1.5578055355040685E-01   3.7072425840003614E-02   9.2701812094135964E-03\n         2         35   9.2178393180946533E-03   1.5904126501260279E-01   4.0348551352842446E-02   9.5003668218397400E-03\n         2         36   9.4575868619178344E-03   5.1293191545885380E-02   2.2368346063196393E-02   3.9509509521853895E-03\n         2         37   9.2761896250624876E-01   1.7921935800038666E+00   1.2308347709940852E+00   8.0254390629725877E-02\n         2         38   2.0159751859216588E-01   6.8263459163972073E-01   3.9620994276101978E-01   5.8856944009654792E-02\n         2         39   3.1444741124815137E-03   6.0419108582346011E-02   1.5722835439959473E-02   3.8011947230805437E-03\n         2         40   2.6932989982444847E-04   1.8159226758941289E-02   3.3066578569261990E-03   1.5589992154407400E-03\n         2         41   1.8664138936449807E-02   2.0528233698508752E-01   5.8996171265576887E-02   1.2127819025198241E-02\n         2         42   1.1913970321003086E-03   4.8027741432042435E-02   9.6735670738170437E-03   4.1724473585085511E-03\n         2         43   9.1202524005712503E-03   6.7278846278479063E-02   2.1113240418557132E-02   4.1014379356923755E-03\n         2         44   3.2335303640640407E+00   6.2800805982849672E+00   4.5844950729868890E+00   2.9899493759159784E-01\n         2         45   1.2157054366093822E+01   1.8705346938457929E+01   1.5194740546143654E+01   7.2484700079972553E-01\n         2         46   7.9921665749592199E+00   1.7643832919265371E+01   1.2475514463185192E+01   1.2154982160899783E+00\n         2         47   2.1807932118933904E+00   4.5852265968783925E+00   3.1833153239195777E+00   2.3238027423515445E-01\n         2         48   1.2108995132489303E+01   1.8698532669729367E+01   1.5120860751112655E+01   7.2733912128396438E-01\n         2         49   7.0165185028024153E+00   1.5401626639949257E+01   1.0792131828621983E+01   1.0398487914522918E+00\n         2         50   7.8202016983210931E-01   1.8611702516693229E+00   1.2174201587607194E+00   1.1147820578875754E-01\n         2         51   3.2709677848274334E+00   5.4223547723084513E+00   4.2602646606465866E+00   2.7314590833102631E-01\n         2         52   2.2651344778022735E+00   5.0863609156322838E+00   3.5902774962451893E+00   3.5808456983868103E-01\n         2         53   1.9453916371177205E-01   5.2428294654973473E-01   3.2666614703573060E-01   3.3752889916549095E-02\n         2         54   3.3374664427470768E+00   5.1743679146252255E+00   4.0448520764617184E+00   1.9237711912273595E-01\n         2         55   1.3929130654519679E+00   3.0394486810407773E+00   2.0655732163336640E+00   2.0369407259850125E-01\n         2         56   1.9994637331940199E+00   4.1338816564289589E+00   2.9547223524158195E+00   2.2378987872487088E-01\n         2         57   7.0024276367635920E+00   1.2030420415617256E+01   9.3380137489663113E+00   5.1318226612730578E-01\n         2         58   4.2164884610310587E+00   1.0982260050282811E+01   7.2964881447285777E+00   8.6437104938712894E-01\n         2         59   1.2626170541578807E+00   2.8532820982381413E+00   1.9301828785358952E+00   1.6090649059496773E-01\n         2         60   6.9131495181976197E+00   1.1993764170970396E+01   9.2801906041296842E+00   5.1334742977278891E-01\n         2         61   3.6648854802162818E+00   9.3657087980349765E+00   6.2138002856746217E+00   7.2113430819953039E-01\n         2         62   4.5980423684463972E-01   1.3560623799760794E+00   7.7522092031619327E-01   8.5451710984528917E-02\n         2         63   1.8705975374375172E+00   3.5090502773932890E+00   2.5942084944102217E+00   2.0373417922112785E-01\n         2         64   1.1651564701031334E+00   3.1755530133217258E+00   2.1080271338825565E+00   2.5349787826375941E-01\n         2         65   1.0053065805206919E-01   2.9582602902027616E-01   1.7423572452553945E-01   1.9707524568074092E-02\n         2         66   1.9253405309213385E+00   3.2577395800436522E+00   2.4269493476824469E+00   1.2964719332891439E-01\n         2         67   7.1139248247643916E-01   1.7309524970829380E+00   1.1411509287449384E+00   1.3030995199739998E-01\n         2         68   9.3937729881137341E-02   5.5676161934251234E-01   2.3077136041721213E-01   4.0182083755630246E-02\n         2         69   1.8436273033597170E-01   9.8356822105150410E-01   4.8304060547071725E-01   6.5046747553556633E-02\n         2         70   4.9304521543447596E-02   6.4119617560461051E-01   2.4559335034632787E-01   7.3681477269694498E-02\n         2         71   3.0228810309978836E-02   2.3518837402996010E-01   9.9940377533517463E-02   2.1148844612514289E-02\n         2         72   1.7856551824141351E-01   9.9275407174597208E-01   4.7418706397868426E-01   6.4289221475592739E-02\n         2         73   4.0092925562913710E-02   5.0140686705026560E-01   1.9062950626089070E-01   5.6453140178347211E-02\n         2         74   1.9617033002142608E-02   2.7103674973192993E-01   6.3632576461854620E-02   1.7254705957629523E-02\n         2         75   4.5960636175893750E-02   2.2735828246294021E-01   1.0320965328121219E-01   1.3911736509373249E-02\n         2         76   6.7010548711732816E-03   6.7557318200940089E-02   2.7223098089251895E-02   7.6928676004739882E-03\n"
  },
  {
    "path": "examples/nnp-comp2/Cu2S_PBE/nnp-data-1/weights.016.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  3.8617652869212821E-01 a         1     0     1     1     1\n -6.4125888351429605E-01 a         2     0     1     1     2\n -1.9080593343133594E+00 a         3     0     1     1     3\n -2.1991365082599121E+00 a         4     0     1     1     4\n -4.7265232373042458E+00 a         5     0     1     1     5\n  1.6349102494688283E-01 a         6     0     1     1     6\n  2.6606576850243933E+00 a         7     0     1     1     7\n  4.4164338833289762E-01 a         8     0     1     1     8\n  4.8313139738260560E+00 a         9     0     1     1     9\n  9.0774913164913862E-01 a        10     0     1     1    10\n -2.3024807580410842E+00 a        11     0     1     1    11\n  1.3817307910334600E-01 a        12     0     1     1    12\n  2.6504834219686231E+00 a        13     0     1     1    13\n -1.1414836284993717E+00 a        14     0     1     1    14\n  1.4760242980999397E-01 a        15     0     1     1    15\n  3.1629620423850419E-01 a        16     0     2     1     1\n  3.1688366289949899E-01 a        17     0     2     1     2\n -3.3645334388690812E-01 a        18     0     2     1     3\n  1.0402228046107300E+00 a        19     0     2     1     4\n -4.4113181804131658E+00 a        20     0     2     1     5\n  1.3146284381644002E+00 a        21     0     2     1     6\n -3.8293488472172865E-01 a        22     0     2     1     7\n -9.2288923602619442E-03 a        23     0     2     1     8\n  1.8923280250952060E-01 a        24     0     2     1     9\n  2.3710956962357724E-01 a        25     0     2     1    10\n -6.1136692487116429E-01 a        26     0     2     1    11\n -2.3776227732091275E+00 a        27     0     2     1    12\n -5.6169899439578730E-01 a        28     0     2     1    13\n -1.0449828982435071E-01 a        29     0     2     1    14\n -1.5267216324955360E-01 a        30     0     2     1    15\n -1.7064105794464624E-01 a        31     0     3     1     1\n -7.5271667828828714E-02 a        32     0     3     1     2\n -8.4974282871044429E-02 a        33     0     3     1     3\n  4.9599865482582318E-03 a        34     0     3     1     4\n -2.3398967000057880E-01 a        35     0     3     1     5\n  3.8058994913649319E-01 a        36     0     3     1     6\n  3.1298221248015407E-01 a        37     0     3     1     7\n  1.6693242700224335E-03 a        38     0     3     1     8\n  7.4749565122557038E-01 a        39     0     3     1     9\n -3.6542571992429063E-01 a        40     0     3     1    10\n -2.5696130220826041E-01 a        41     0     3     1    11\n  1.6596113335099580E-01 a        42     0     3     1    12\n  5.3126959392497142E-01 a        43     0     3     1    13\n -2.1706487995036686E-01 a        44     0     3     1    14\n -5.3593456781769709E-02 a        45     0     3     1    15\n  4.4007170938589857E-01 a        46     0     4     1     1\n -3.6226908753745107E-01 a        47     0     4     1     2\n -2.0259294083208372E+00 a        48     0     4     1     3\n -1.1260655480648898E+00 a        49     0     4     1     4\n -3.2655877169419152E+00 a        50     0     4     1     5\n  1.1046588421192036E+00 a        51     0     4     1     6\n  2.5769867080644060E+00 a        52     0     4     1     7\n  3.9660619828435528E-01 a        53     0     4     1     8\n  3.9412244330095723E+00 a        54     0     4     1     9\n  7.8886700558061218E-01 a        55     0     4     1    10\n -2.1305939478903255E+00 a        56     0     4     1    11\n -1.3085631139776699E-01 a        57     0     4     1    12\n  2.5290780539327202E+00 a        58     0     4     1    13\n -4.6654384132871735E-01 a        59     0     4     1    14\n -2.8700426471918555E-01 a        60     0     4     1    15\n  2.6020480865105627E-01 a        61     0     5     1     1\n -2.6775212682587557E-01 a        62     0     5     1     2\n -5.2871669604947802E-01 a        63     0     5     1     3\n -3.4446478796505192E-01 a        64     0     5     1     4\n -1.0911765495657265E-01 a        65     0     5     1     5\n  2.1608537932767224E-01 a        66     0     5     1     6\n -2.6424060867151894E-01 a        67     0     5     1     7\n  3.7170833702642148E-01 a        68     0     5     1     8\n  2.2913626803709025E-01 a        69     0     5     1     9\n  6.9344893815259068E-01 a        70     0     5     1    10\n -1.0764890155277314E-01 a        71     0     5     1    11\n -4.0269631201887091E-01 a        72     0     5     1    12\n  1.8840001185466129E-01 a        73     0     5     1    13\n  4.0708866617461326E-01 a        74     0     5     1    14\n -2.7118487721002643E-01 a        75     0     5     1    15\n  3.9947083328192534E-01 a        76     0     6     1     1\n  3.0699524711876458E-01 a        77     0     6     1     2\n -2.0259037714144341E+00 a        78     0     6     1     3\n  1.0540497189361835E+00 a        79     0     6     1     4\n -4.2156153713500988E+00 a        80     0     6     1     5\n  2.0723789478000918E+00 a        81     0     6     1     6\n  3.9453497194720322E-01 a        82     0     6     1     7\n -1.9911059217408511E-01 a        83     0     6     1     8\n  1.2935593716020326E+00 a        84     0     6     1     9\n -2.5988073231384305E-02 a        85     0     6     1    10\n -3.6812789339662250E-01 a        86     0     6     1    11\n -2.4263028339623336E+00 a        87     0     6     1    12\n  9.1018612483602090E-01 a        88     0     6     1    13\n  4.4468712631672747E-01 a        89     0     6     1    14\n  8.9327761980964426E-01 a        90     0     6     1    15\n -2.7698606190854574E-01 a        91     0     7     1     1\n -4.7207278374087791E-01 a        92     0     7     1     2\n -1.5366783706141385E+00 a        93     0     7     1     3\n -5.2550907415360482E-01 a        94     0     7     1     4\n -7.0243282838864096E-01 a        95     0     7     1     5\n  1.8272112120072344E+00 a        96     0     7     1     6\n  2.5341425111042065E-01 a        97     0     7     1     7\n  1.0620787715280119E-01 a        98     0     7     1     8\n  2.9118226190159877E+00 a        99     0     7     1     9\n  2.1099644274917728E-01 a       100     0     7     1    10\n -3.9216969750708441E-01 a       101     0     7     1    11\n  4.5752796454372113E-01 a       102     0     7     1    12\n  1.7347455855238429E+00 a       103     0     7     1    13\n -2.3133447615225458E-01 a       104     0     7     1    14\n  2.2180318731404530E-01 a       105     0     7     1    15\n  5.2678337133743547E-01 a       106     0     8     1     1\n -8.0377243455779956E-02 a       107     0     8     1     2\n -1.9430828570011378E+00 a       108     0     8     1     3\n -1.0145269654700213E+00 a       109     0     8     1     4\n -2.6154703536294308E+00 a       110     0     8     1     5\n  7.9245103641616177E-01 a       111     0     8     1     6\n  2.5062348106189991E+00 a       112     0     8     1     7\n  1.3658037868636483E-01 a       113     0     8     1     8\n  3.6633977646550746E+00 a       114     0     8     1     9\n  7.0270446900735650E-01 a       115     0     8     1    10\n -1.2948540236934203E+00 a       116     0     8     1    11\n  1.3740136186585039E-02 a       117     0     8     1    12\n  2.2092600908892157E+00 a       118     0     8     1    13\n -3.6268828921972662E-01 a       119     0     8     1    14\n  7.4398480051875848E-01 a       120     0     8     1    15\n  4.1534440223563306E-02 a       121     0     9     1     1\n -1.6737772645337282E-01 a       122     0     9     1     2\n -1.6958344499050572E-02 a       123     0     9     1     3\n -2.3412494607313264E-01 a       124     0     9     1     4\n -1.6709433954330666E-01 a       125     0     9     1     5\n  4.6867238726575911E-01 a       126     0     9     1     6\n  2.1763852474944778E-01 a       127     0     9     1     7\n  1.2826659430535944E-01 a       128     0     9     1     8\n  1.1832422738954994E-01 a       129     0     9     1     9\n  1.0518237431718493E+00 a       130     0     9     1    10\n  1.8830672476191374E-02 a       131     0     9     1    11\n -9.6577971039370533E-02 a       132     0     9     1    12\n  3.0797187751108257E-01 a       133     0     9     1    13\n  1.5957786341892019E-01 a       134     0     9     1    14\n  3.0179431558164049E-02 a       135     0     9     1    15\n  5.4272702220550591E-02 a       136     0    10     1     1\n  8.3338732979209101E-02 a       137     0    10     1     2\n -5.3373030146151357E-01 a       138     0    10     1     3\n  3.8262782914769433E-01 a       139     0    10     1     4\n -1.3828266919262184E+00 a       140     0    10     1     5\n  8.9526978197997431E-01 a       141     0    10     1     6\n  3.8762204860197724E-01 a       142     0    10     1     7\n -2.2073743495151618E-01 a       143     0    10     1     8\n  3.4484925400608263E-01 a       144     0    10     1     9\n -8.6904229185536072E-02 a       145     0    10     1    10\n  1.7229508089716453E-01 a       146     0    10     1    11\n -6.6796652679447199E-01 a       147     0    10     1    12\n  5.0735603676368657E-01 a       148     0    10     1    13\n  4.1846440143555103E-01 a       149     0    10     1    14\n  4.1649767551422079E-01 a       150     0    10     1    15\n -1.7214080518646030E-01 a       151     0    11     1     1\n -1.9600149297946370E-01 a       152     0    11     1     2\n -3.6593824104389100E-01 a       153     0    11     1     3\n -3.4924674227065750E-01 a       154     0    11     1     4\n -2.2704588365718753E-01 a       155     0    11     1     5\n  9.0008020265967048E-01 a       156     0    11     1     6\n -1.1443985112764083E-02 a       157     0    11     1     7\n -3.3730625524002043E-02 a       158     0    11     1     8\n  8.2281510048338025E-01 a       159     0    11     1     9\n -1.2928579159940756E-01 a       160     0    11     1    10\n -5.2595270519083866E-02 a       161     0    11     1    11\n  2.4403123633181345E-01 a       162     0    11     1    12\n  9.3504494807309346E-01 a       163     0    11     1    13\n -3.7605857022182027E-02 a       164     0    11     1    14\n  2.1472382089006850E-01 a       165     0    11     1    15\n  2.0393862519352346E-01 a       166     0    12     1     1\n  4.6267472117297717E-02 a       167     0    12     1     2\n -2.9684614607402565E-01 a       168     0    12     1     3\n -2.3490308725280357E-01 a       169     0    12     1     4\n -7.6994876719071492E-01 a       170     0    12     1     5\n -2.7283545654232377E-01 a       171     0    12     1     6\n  9.3270843217007793E-01 a       172     0    12     1     7\n -7.5045636210823372E-02 a       173     0    12     1     8\n  1.3731612585181849E+00 a       174     0    12     1     9\n  5.5918332130257009E-01 a       175     0    12     1    10\n -1.6386762041891631E-01 a       176     0    12     1    11\n  7.1100575902852584E-02 a       177     0    12     1    12\n  2.0883490079718697E-01 a       178     0    12     1    13\n  2.9032673033528505E-01 a       179     0    12     1    14\n  2.9366775210709617E-01 a       180     0    12     1    15\n -1.2862328555594528E-02 a       181     0    13     1     1\n  2.9615888192706333E-02 a       182     0    13     1     2\n -1.1263299728016328E-01 a       183     0    13     1     3\n  6.4572444261886319E-01 a       184     0    13     1     4\n -4.3958273303724998E-01 a       185     0    13     1     5\n  1.2947991768866804E-01 a       186     0    13     1     6\n  2.0835875539075638E-01 a       187     0    13     1     7\n -1.0630380606023544E-01 a       188     0    13     1     8\n -2.1641874929506033E-02 a       189     0    13     1     9\n -1.8737869720303546E-01 a       190     0    13     1    10\n  2.3465587921993356E-01 a       191     0    13     1    11\n -4.8323814095563973E-02 a       192     0    13     1    12\n  1.9277764595580433E-03 a       193     0    13     1    13\n  1.5123499222760231E-01 a       194     0    13     1    14\n  7.3315953670876635E-02 a       195     0    13     1    15\n -9.9670561949501035E-01 a       196     0    14     1     1\n -5.8836131284008653E-01 a       197     0    14     1     2\n  1.5235405212748426E-01 a       198     0    14     1     3\n -1.0029811094915793E+00 a       199     0    14     1     4\n  2.9195049750330639E+00 a       200     0    14     1     5\n -2.3091961862144879E+00 a       201     0    14     1     6\n  5.8437987709056731E+00 a       202     0    14     1     7\n -8.1665045379088463E-01 a       203     0    14     1     8\n  8.3980839339726654E-01 a       204     0    14     1     9\n  2.6098346591517467E+00 a       205     0    14     1    10\n -2.5490005496326722E-02 a       206     0    14     1    11\n  1.0154569949083823E+00 a       207     0    14     1    12\n  3.5885276419557233E+00 a       208     0    14     1    13\n  2.5285269495137173E+00 a       209     0    14     1    14\n -2.3827681868264166E+00 a       210     0    14     1    15\n -9.5897133685849545E-01 a       211     0    15     1     1\n -7.1449956321792274E-01 a       212     0    15     1     2\n  4.4791736636890844E+00 a       213     0    15     1     3\n  5.5185289291748125E+00 a       214     0    15     1     4\n -4.0954767656508062E-01 a       215     0    15     1     5\n -9.9291617665414833E-01 a       216     0    15     1     6\n  3.2663861871643882E+00 a       217     0    15     1     7\n -7.5142363689931768E-01 a       218     0    15     1     8\n -1.0817034565205179E+00 a       219     0    15     1     9\n  5.8498507019911461E+00 a       220     0    15     1    10\n  1.1282009598617444E+00 a       221     0    15     1    11\n  1.1147775082365654E+00 a       222     0    15     1    12\n  9.5705781539189894E-01 a       223     0    15     1    13\n -4.1391324625976228E-01 a       224     0    15     1    14\n  7.8743699764752928E-01 a       225     0    15     1    15\n -7.8577768281470173E-01 a       226     0    16     1     1\n  2.2092772683060138E-01 a       227     0    16     1     2\n -2.7812915810161845E+00 a       228     0    16     1     3\n -1.1240809824701032E+00 a       229     0    16     1     4\n -4.2819210127890823E+00 a       230     0    16     1     5\n  1.1972288269688578E-02 a       231     0    16     1     6\n -4.9485691118301228E-01 a       232     0    16     1     7\n -1.1503742819020234E-01 a       233     0    16     1     8\n -3.4195420761463904E+00 a       234     0    16     1     9\n  8.4114123098251508E+00 a       235     0    16     1    10\n -7.8764051692489623E-02 a       236     0    16     1    11\n -1.9373677056750742E+00 a       237     0    16     1    12\n -2.8474193304043229E+00 a       238     0    16     1    13\n -3.6631430206207347E+00 a       239     0    16     1    14\n  7.3365986881749401E-01 a       240     0    16     1    15\n  1.1620374500767956E+00 a       241     0    17     1     1\n  1.5925426977291073E+00 a       242     0    17     1     2\n  3.0206666456032392E+00 a       243     0    17     1     3\n -5.1791776788258881E+00 a       244     0    17     1     4\n -4.0185376694242505E+00 a       245     0    17     1     5\n -2.6004930087389835E+00 a       246     0    17     1     6\n -2.4020418732126716E+00 a       247     0    17     1     7\n -9.6457529539576237E-01 a       248     0    17     1     8\n -8.1469570103882489E+00 a       249     0    17     1     9\n -1.1295378021650848E+00 a       250     0    17     1    10\n  3.0300834437881368E+00 a       251     0    17     1    11\n -2.2020036613528866E+00 a       252     0    17     1    12\n -5.4089824307981660E+00 a       253     0    17     1    13\n  2.9755131817955846E-02 a       254     0    17     1    14\n  9.2546059109666234E-01 a       255     0    17     1    15\n -9.8207105506254111E-01 a       256     0    18     1     1\n  7.1004578593518619E-01 a       257     0    18     1     2\n  1.3373750066668573E+00 a       258     0    18     1     3\n -5.2630778188373935E+00 a       259     0    18     1     4\n  3.1059215148553232E+00 a       260     0    18     1     5\n  6.2747769378959868E+00 a       261     0    18     1     6\n -1.0800049456866709E+01 a       262     0    18     1     7\n  5.0771389802566058E-01 a       263     0    18     1     8\n  4.6629345251410497E+00 a       264     0    18     1     9\n -1.1252638655917254E+01 a       265     0    18     1    10\n -7.7005957078964027E+00 a       266     0    18     1    11\n  1.0188771270469985E+00 a       267     0    18     1    12\n  3.9406032370941810E+00 a       268     0    18     1    13\n -6.9195367347284158E+00 a       269     0    18     1    14\n -4.8335129236309875E+00 a       270     0    18     1    15\n -2.0648582433363414E+00 a       271     0    19     1     1\n 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3.6885702523779906E-01 a      1123     1    10     2    13\n -1.9094237372534065E-01 a      1124     1    10     2    14\n -1.4719040325119989E-01 a      1125     1    10     2    15\n -4.2581703198656790E-01 a      1126     1    11     2     1\n  1.6285051139963751E-02 a      1127     1    11     2     2\n -4.4806900688550694E-01 a      1128     1    11     2     3\n  7.2931061346964432E-01 a      1129     1    11     2     4\n  3.1922633043146403E-01 a      1130     1    11     2     5\n  7.4517941149290823E-01 a      1131     1    11     2     6\n -1.7361025790160525E-01 a      1132     1    11     2     7\n -2.8010693322366392E-01 a      1133     1    11     2     8\n -3.9299457790893322E-01 a      1134     1    11     2     9\n  1.4062173179795332E+00 a      1135     1    11     2    10\n -2.8337834309420771E+00 a      1136     1    11     2    11\n  7.8206713517949189E-01 a      1137     1    11     2    12\n  1.0724700604283623E+00 a      1138     1    11     2    13\n -3.9786008473940310E-01 a      1139     1    11     2    14\n  9.6738557890673416E-01 a      1140     1    11     2    15\n -1.5233501091622146E+00 a      1141     1    12     2     1\n  4.0784120244969246E-01 a      1142     1    12     2     2\n  4.9991272753437027E-01 a      1143     1    12     2     3\n -1.0648089496039125E-01 a      1144     1    12     2     4\n  8.7755608227452042E-01 a      1145     1    12     2     5\n  6.5119644065754456E-01 a      1146     1    12     2     6\n -1.8175348549803069E-02 a      1147     1    12     2     7\n  1.9109729178160391E+00 a      1148     1    12     2     8\n -3.3297303777402765E-01 a      1149     1    12     2     9\n -6.9336032478323806E-01 a      1150     1    12     2    10\n  6.9719098566300142E-01 a      1151     1    12     2    11\n -2.3322186556888574E-01 a      1152     1    12     2    12\n  4.2160522611759721E-01 a      1153     1    12     2    13\n  2.0222570465473142E+00 a      1154     1    12     2    14\n  1.1621449646991433E+00 a      1155     1    12     2    15\n  1.7682478710233093E-01 a      1156     1    13     2     1\n  3.6469820323497443E-01 a      1157     1    13     2     2\n  3.4087533232164613E-01 a      1158     1    13     2     3\n  7.6653950876506699E-02 a      1159     1    13     2     4\n -1.2622957274809046E+00 a      1160     1    13     2     5\n  2.5480292201993093E-01 a      1161     1    13     2     6\n -5.9219903419101889E-02 a      1162     1    13     2     7\n -7.6716452637680366E-01 a      1163     1    13     2     8\n -6.9503151734370128E-01 a      1164     1    13     2     9\n  7.2268374596788684E-02 a      1165     1    13     2    10\n -1.8188024306787172E+00 a      1166     1    13     2    11\n  8.4590295735287901E-01 a      1167     1    13     2    12\n -9.7522198816583569E-02 a      1168     1    13     2    13\n  2.6665754624462140E-01 a      1169     1    13     2    14\n -1.9727970605387729E-01 a      1170     1    13     2    15\n  1.9795570885298658E-01 a      1171     1    14     2     1\n  3.4485211236090735E-01 a      1172     1    14     2     2\n  7.7552744105843563E-01 a      1173     1    14     2     3\n  1.4380078763706161E-01 a      1174     1    14     2     4\n  1.9089180634727381E+00 a      1175     1    14     2     5\n  1.3990113168016460E-01 a      1176     1    14     2     6\n  9.3962954584302181E-03 a      1177     1    14     2     7\n  1.3836801856404829E-01 a      1178     1    14     2     8\n  3.9912216168200981E-01 a      1179     1    14     2     9\n -1.3698742717646613E+00 a      1180     1    14     2    10\n  6.0883739548030824E-01 a      1181     1    14     2    11\n  7.5759234940851683E-01 a      1182     1    14     2    12\n -1.6221385683433873E-01 a      1183     1    14     2    13\n  8.6501979955934094E-01 a      1184     1    14     2    14\n -2.3714595719882721E+00 a      1185     1    14     2    15\n -5.7825349881929367E-01 a      1186     1    15     2     1\n  8.6326617795785632E-01 a      1187     1    15     2     2\n  1.7132319625670339E-01 a      1188     1    15     2     3\n -3.3658485418023570E-01 a      1189     1    15     2     4\n  1.0052023727139032E+00 a      1190     1    15     2     5\n -6.5883930543382918E-01 a      1191     1    15     2     6\n  1.2869125967375014E-01 a      1192     1    15     2     7\n  8.5958157734999055E-02 a      1193     1    15     2     8\n  2.8656824709871004E-01 a      1194     1    15     2     9\n -5.3677097397198203E-01 a      1195     1    15     2    10\n  6.6373498304306533E-01 a      1196     1    15     2    11\n -3.7325631399106546E-01 a      1197     1    15     2    12\n  4.9984754556468836E-01 a      1198     1    15     2    13\n  4.4879983024493453E-01 a      1199     1    15     2    14\n  4.0203646308516430E-02 a      1200     1    15     2    15\n  3.4293002184659005E-01 b      1201     2     1\n -1.4375353290476786E-01 b      1202     2     2\n  2.2190284141135415E+00 b      1203     2     3\n -1.7696668249739895E+00 b      1204     2     4\n  1.2958077587411005E+00 b      1205     2     5\n -5.9370183497806184E-01 b      1206     2     6\n  4.1183580431551166E+00 b      1207     2     7\n -5.0604912897585375E-01 b      1208     2     8\n -1.3618313307564720E+00 b      1209     2     9\n  3.2248442370208923E+00 b      1210     2    10\n  1.8637524212476728E+00 b      1211     2    11\n -3.3976229192094276E-01 b      1212     2    12\n  1.2123688896678984E+00 b      1213     2    13\n -2.2583299559115119E-01 b      1214     2    14\n  1.3041105887299231E+00 b      1215     2    15\n  2.7745993342463060E-01 a      1216     2     1     3     1\n  3.5782814869578716E-01 a      1217     2     2     3     1\n  9.6131833710785208E-01 a      1218     2     3     3     1\n  2.5831142163540655E+00 a      1219     2     4     3     1\n  1.7521965911228246E-01 a      1220     2     5     3     1\n  4.0500200700152972E-01 a      1221     2     6     3     1\n -1.6230457228975497E+00 a      1222     2     7     3     1\n  2.0279270628057006E-01 a      1223     2     8     3     1\n -1.7256903371345067E-01 a      1224     2     9     3     1\n  5.6486035246079425E-01 a      1225     2    10     3     1\n -1.1621719054523770E-02 a      1226     2    11     3     1\n -8.4891860528339680E-01 a      1227     2    12     3     1\n  4.7471365912110325E-01 a      1228     2    13     3     1\n -1.5597373206438592E-01 a      1229     2    14     3     1\n  2.4336630166766644E-02 a      1230     2    15     3     1\n -1.9471899223752354E+00 b      1231     3     1\n"
  },
  {
    "path": "examples/nnp-comp2/Cu2S_PBE/nnp-data-1/weights.029.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -2.0615965509486389E+00 a         1     0     1     1     1\n  8.5673677619780375E-01 a         2     0     1     1     2\n -2.0578812067045900E+00 a         3     0     1     1     3\n -1.9079290893362891E-01 a         4     0     1     1     4\n  2.1931297710075319E+00 a         5     0     1     1     5\n -1.0718728887216178E+00 a         6     0     1     1     6\n -6.5700133979754516E-01 a         7     0     1     1     7\n  1.4276606007404813E+00 a         8     0     1     1     8\n -3.2618900363071655E+00 a         9     0     1     1     9\n  7.9535902296231964E-01 a        10     0     1     1    10\n -5.4007190820651214E+00 a        11     0     1     1    11\n -1.1507026233433577E+00 a        12     0     1     1    12\n  2.3016974119671243E+00 a        13     0     1     1    13\n  4.4143912978630642E+00 a        14     0     1     1    14\n -1.9729637257437407E+00 a        15     0     1     1    15\n -8.2636991646342173E-01 a        16     0     2     1     1\n  1.5592003190811479E+00 a        17     0     2     1     2\n -1.3337547974568691E+00 a        18     0     2     1     3\n  3.7011218674124220E-02 a        19     0     2     1     4\n -7.2589676541032999E-01 a        20     0     2     1     5\n  5.4282206142477718E-01 a        21     0     2     1     6\n  9.8866948058744264E-01 a        22     0     2     1     7\n  3.9032408798180320E+00 a        23     0     2     1     8\n  4.6275245621025463E-01 a        24     0     2     1     9\n -2.2967200020839848E-01 a        25     0     2     1    10\n -2.9827286313845101E-02 a        26     0     2     1    11\n  3.1593717978322339E-01 a        27     0     2     1    12\n  4.2578945999572804E-01 a        28     0     2     1    13\n  9.4526637804176292E-02 a        29     0     2     1    14\n -1.4042663146580214E+00 a        30     0     2     1    15\n -1.1592055708996953E-01 a        31     0     3     1     1\n  1.5110755814239869E+00 a        32     0     3     1     2\n -1.6397758409412864E+00 a        33     0     3     1     3\n -1.8880655795417645E-01 a        34     0     3     1     4\n  5.2813641766091546E-01 a        35     0     3     1     5\n -1.6053042169641432E+00 a        36     0     3     1     6\n -1.3572317071820350E+00 a        37     0     3     1     7\n -7.6736656406749826E-01 a        38     0     3     1     8\n -3.0511569283675963E+00 a        39     0     3     1     9\n  3.3655053157327308E-01 a        40     0     3     1    10\n -7.8368278976802772E+00 a        41     0     3     1    11\n -2.6592926213494428E-01 a        42     0     3     1    12\n  1.8217642341634670E+00 a        43     0     3     1    13\n  5.5573749943293005E-01 a        44     0     3     1    14\n -2.1270301263642173E+00 a        45     0     3     1    15\n -5.9567377812078615E-01 a        46     0     4     1     1\n -1.6340541369259609E+00 a        47     0     4     1     2\n  2.5588475083647239E-01 a        48     0     4     1     3\n  2.0349602699281163E-01 a        49     0     4     1     4\n  3.3347366525840920E+00 a        50     0     4     1     5\n -2.6775220754684361E+00 a        51     0     4     1     6\n -9.3583893519611494E-01 a        52     0     4     1     7\n -6.3740509682438624E+00 a        53     0     4     1     8\n -2.7195407128166731E+00 a        54     0     4     1     9\n -4.4444625465889992E-01 a        55     0     4     1    10\n -5.3157202211851970E+00 a        56     0     4     1    11\n -8.9267021174052469E-02 a        57     0     4     1    12\n  3.1924873828819216E+00 a        58     0     4     1    13\n  2.8555011816248239E+00 a        59     0     4     1    14\n  6.5374770421580841E-01 a        60     0     4     1    15\n -2.0135265843067232E+00 a        61     0     5     1     1\n  1.2516530965740262E+00 a        62     0     5     1     2\n -2.0057693453842300E+00 a        63     0     5     1     3\n -2.0129360438290372E-01 a        64     0     5     1     4\n  9.7446334827343029E-01 a        65     0     5     1     5\n -5.9017735225663537E-01 a        66     0     5     1     6\n -1.4120719080714916E-01 a        67     0     5     1     7\n  7.0443990307711868E-01 a        68     0     5     1     8\n -3.6156485553983710E+00 a        69     0     5     1     9\n  1.0776491151089169E+00 a        70     0     5     1    10\n -7.0423672073320382E+00 a        71     0     5     1    11\n -8.5148885750339454E-01 a        72     0     5     1    12\n  1.9524627542423540E+00 a        73     0     5     1    13\n  2.7051519631821037E+00 a        74     0     5     1    14\n -2.3180608911930261E+00 a        75     0     5     1    15\n -4.2675221167096815E+00 a        76     0     6     1     1\n  2.8655346981250038E+00 a        77     0     6     1     2\n -2.9646245983916928E+00 a        78     0     6     1     3\n  1.3062736053043297E-01 a        79     0     6     1     4\n -9.4280660747229783E-01 a        80     0     6     1     5\n  8.5494573488070491E-01 a        81     0     6     1     6\n  1.6947862920172914E+00 a        82     0     6     1     7\n  6.2568974363286936E+00 a        83     0     6     1     8\n -8.2823301623587853E-01 a        84     0     6     1     9\n -1.0657037571463661E+00 a        85     0     6     1    10\n -3.9007482644547364E+00 a        86     0     6     1    11\n  1.2198214150529685E+00 a        87     0     6     1    12\n  2.1518878037954638E+00 a        88     0     6     1    13\n  1.1189929903899125E-02 a        89     0     6     1    14\n -2.2271237203822345E+00 a        90     0     6     1    15\n  6.0348010433214549E-01 a        91     0     7     1     1\n  1.4195424847740963E+00 a        92     0     7     1     2\n -2.0418283073246872E+00 a        93     0     7     1     3\n -2.4519682086595277E-02 a        94     0     7     1     4\n  6.2642768359888856E-01 a        95     0     7     1     5\n -1.9231821311106130E+00 a        96     0     7     1     6\n -1.3868652485733126E+00 a        97     0     7     1     7\n  7.2051084198304194E-01 a        98     0     7     1     8\n -3.5217186930287490E+00 a        99     0     7     1     9\n  7.9849801957427791E-01 a       100     0     7     1    10\n -5.6852767012226844E+00 a       101     0     7     1    11\n -1.0247131730543830E+00 a       102     0     7     1    12\n  1.5088276746114593E+00 a       103     0     7     1    13\n  8.5850186811734486E-01 a       104     0     7     1    14\n -1.7881758141607986E+00 a       105     0     7     1    15\n -6.1911387356267911E-01 a       106     0     8     1     1\n -2.9974957141547570E-01 a       107     0     8     1     2\n -3.5289028749729162E-01 a       108     0     8     1     3\n  2.1981037279120616E-01 a       109     0     8     1     4\n  1.3583769266270735E+00 a       110     0     8     1     5\n -1.0151675037636654E+00 a       111     0     8     1     6\n  2.8542102541185060E-01 a       112     0     8     1     7\n -1.9392274380177272E+00 a       113     0     8     1     8\n -1.9569617611941503E+00 a       114     0     8     1     9\n -3.0045589096628994E-01 a       115     0     8     1    10\n -2.7345929739553583E+00 a       116     0     8     1    11\n  1.8227816088649978E-01 a       117     0     8     1    12\n  2.2105931599950916E+00 a       118     0     8     1    13\n  1.2116679239526187E+00 a       119     0     8     1    14\n -3.8212068013316025E-01 a       120     0     8     1    15\n -1.5658639650870354E+00 a       121     0     9     1     1\n  1.0789013365196081E+00 a       122     0     9     1     2\n -1.7342186450183721E+00 a       123     0     9     1     3\n -6.7778170993275183E-02 a       124     0     9     1     4\n -8.8530339064632785E-02 a       125     0     9     1     5\n -5.2107875730116560E-01 a       126     0     9     1     6\n  1.1983822520992767E-01 a       127     0     9     1     7\n  1.5033592857059383E-01 a       128     0     9     1     8\n -2.4575490742510713E+00 a       129     0     9     1     9\n  6.6245423580780050E-01 a       130     0     9     1    10\n -4.2340108195700843E+00 a       131     0     9     1    11\n -1.0055392096577171E+00 a       132     0     9     1    12\n  1.6277327782959641E+00 a       133     0     9     1    13\n  2.6975642414828160E-01 a       134     0     9     1    14\n -1.6734366289942577E+00 a       135     0     9     1    15\n -2.5579485616675237E+00 a       136     0    10     1     1\n  1.0773448957684908E+00 a       137     0    10     1     2\n -1.0232072953555751E+00 a       138     0    10     1     3\n  1.7823224739908117E-01 a       139     0    10     1     4\n -3.1389106714698545E-01 a       140     0    10     1     5\n -2.1351450535440827E-01 a       141     0    10     1     6\n  1.3627053981507689E+00 a       142     0    10     1     7\n  2.1779206865531555E+00 a       143     0    10     1     8\n -1.0898627827720309E+00 a       144     0    10     1     9\n -1.6916662739211333E-01 a       145     0    10     1    10\n -1.5375167494513982E+00 a       146     0    10     1    11\n  5.7070272167013839E-02 a       147     0    10     1    12\n  1.5257824441301278E+00 a       148     0    10     1    13\n -2.9695215263794766E-01 a       149     0    10     1    14\n -9.1845702488768410E-01 a       150     0    10     1    15\n  1.4950407388215656E-01 a       151     0    11     1     1\n  1.1581657072145257E+00 a       152     0    11     1     2\n -1.7838484019694618E+00 a       153     0    11     1     3\n  3.5118327248120851E-01 a       154     0    11     1     4\n -1.9608662261206056E-01 a       155     0    11     1     5\n -2.2880540302847852E+00 a       156     0    11     1     6\n -1.1956677626171117E+00 a       157     0    11     1     7\n  1.3191709025309424E+00 a       158     0    11     1     8\n -2.7800635232854463E+00 a       159     0    11     1     9\n  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6.2384580422535429E-01 a      1219     1     5     2     4\n -2.9237798721709191E-01 a      1220     1     5     2     5\n -3.1409156804193822E-01 a      1221     1     5     2     6\n -1.1282961398160872E-01 a      1222     1     5     2     7\n  1.1916708175493464E-01 a      1223     1     5     2     8\n -1.5580896109411733E+00 a      1224     1     5     2     9\n -1.8911118400915716E-01 a      1225     1     5     2    10\n -2.5981420924502846E-01 a      1226     1     5     2    11\n -4.1319590638023640E-01 a      1227     1     5     2    12\n  1.8490724039279243E-02 a      1228     1     5     2    13\n  3.0151283574804920E-02 a      1229     1     5     2    14\n  6.2045204982454083E-01 a      1230     1     5     2    15\n  4.2736183648785153E-03 a      1231     1     6     2     1\n -4.8550246848180857E-02 a      1232     1     6     2     2\n -1.7170974581130936E+00 a      1233     1     6     2     3\n -3.8312671031379547E-01 a      1234     1     6     2     4\n  1.8225024640703258E-01 a      1235     1     6     2     5\n -2.1918808554225697E-01 a      1236     1     6     2     6\n -3.4020944663030855E-01 a      1237     1     6     2     7\n -2.1939227751577479E-02 a      1238     1     6     2     8\n -9.4195847800326263E-02 a      1239     1     6     2     9\n -4.2027816941138552E-02 a      1240     1     6     2    10\n  1.5600544956741805E-01 a      1241     1     6     2    11\n -4.3112077172499702E-01 a      1242     1     6     2    12\n  8.2397043750255569E-02 a      1243     1     6     2    13\n  3.5979895308947213E-01 a      1244     1     6     2    14\n -3.6383765734940154E-01 a      1245     1     6     2    15\n  6.3360971284591161E-01 a      1246     1     7     2     1\n -9.2025630674226117E-02 a      1247     1     7     2     2\n  1.7612767647879463E-01 a      1248     1     7     2     3\n -1.3176371390512152E+00 a      1249     1     7     2     4\n -1.2641799037095072E-01 a      1250     1     7     2     5\n -1.6073747779550157E-01 a      1251     1     7     2     6\n  1.5380024688380375E-01 a      1252     1     7     2     7\n -1.1099179691467932E-01 a      1253     1     7     2     8\n -3.1035049655659092E-01 a      1254     1     7     2     9\n  8.6623160924940004E-02 a      1255     1     7     2    10\n  3.7305147532984051E-01 a      1256     1     7     2    11\n -1.6626050593647279E+00 a      1257     1     7     2    12\n -3.6413114922412372E-02 a      1258     1     7     2    13\n  4.1939383359029936E-01 a      1259     1     7     2    14\n  5.5868849190938485E-01 a      1260     1     7     2    15\n -9.6670576332538938E-01 a      1261     1     8     2     1\n -1.2283835472281095E-01 a      1262     1     8     2     2\n -1.0948601726003631E+00 a      1263     1     8     2     3\n -4.6973433489019489E-01 a      1264     1     8     2     4\n  1.0454405292620307E-01 a      1265     1     8     2     5\n  3.4810327387674372E-01 a      1266     1     8     2     6\n  1.3765212590784653E-01 a      1267     1     8     2     7\n  4.0261771111952428E-02 a      1268     1     8     2     8\n -7.3430757708292682E-01 a      1269     1     8     2     9\n -2.9892101407252081E-01 a      1270     1     8     2    10\n  5.6297716728102931E-01 a      1271     1     8     2    11\n -9.0290721250318307E-01 a      1272     1     8     2    12\n  1.7911516917998049E-01 a      1273     1     8     2    13\n  1.3397550270352387E-01 a      1274     1     8     2    14\n  3.2983163907377316E-01 a      1275     1     8     2    15\n  4.7533516143466370E-01 a      1276     1     9     2     1\n  9.0738895118959037E-02 a      1277     1     9     2     2\n  3.2706813011368553E-02 a      1278     1     9     2     3\n -1.7168066966844020E+00 a      1279     1     9     2     4\n -6.1577155596252131E-01 a      1280     1     9     2     5\n  2.7650003956194810E-02 a      1281     1     9     2     6\n  3.4679851234020365E-01 a      1282     1     9     2     7\n -1.0761392661168358E-02 a      1283     1     9     2     8\n  1.4105034707343220E-01 a      1284     1     9     2     9\n  6.5333544777694888E-02 a      1285     1     9     2    10\n -9.8647558809217106E-02 a      1286     1     9     2    11\n -4.7354422991140388E-01 a      1287     1     9     2    12\n  1.0522996977985052E-03 a      1288     1     9     2    13\n -2.1221906229203288E-01 a      1289     1     9     2    14\n -7.2986688997362026E-01 a      1290     1     9     2    15\n -1.1019468000284463E-01 a      1291     1    10     2     1\n  7.0334766905683022E-01 a      1292     1    10     2     2\n  5.3049679439862674E-01 a      1293     1    10     2     3\n  5.6191442861048280E-01 a      1294     1    10     2     4\n  3.5499936503182694E-01 a      1295     1    10     2     5\n  3.3177060466840735E-01 a      1296     1    10     2     6\n -3.6086171594277872E-01 a      1297     1    10     2     7\n -3.4316303507024432E-01 a      1298     1    10     2     8\n -4.3668730842475995E-02 a      1299     1    10     2     9\n -2.2238731099736192E-01 a      1300     1    10     2    10\n -2.2568772685681990E-01 a      1301     1    10     2    11\n -6.2907038867849840E-01 a      1302     1    10     2    12\n -2.9942399413893173E-01 a      1303     1    10     2    13\n -1.0335854627000016E+00 a      1304     1    10     2    14\n -3.8804412418993441E-02 a      1305     1    10     2    15\n -1.1456946387862267E-01 a      1306     1    11     2     1\n  3.4247890240615524E-02 a      1307     1    11     2     2\n -9.0420388073783969E-02 a      1308     1    11     2     3\n -2.2766882690517171E-01 a      1309     1    11     2     4\n -1.8811301659460239E-01 a      1310     1    11     2     5\n -6.3035385398640442E-01 a      1311     1    11     2     6\n  1.3948332539390992E-01 a      1312     1    11     2     7\n  1.2200607405779924E-01 a      1313     1    11     2     8\n -1.4957359295527590E+00 a      1314     1    11     2     9\n  3.0948587406817712E-01 a      1315     1    11     2    10\n -1.8579130576283776E-01 a      1316     1    11     2    11\n -5.9078392679148362E-01 a      1317     1    11     2    12\n  1.7524218555467377E-01 a      1318     1    11     2    13\n -9.9969905871487097E-01 a      1319     1    11     2    14\n  1.9378568562645091E+00 a      1320     1    11     2    15\n -1.7200321650382262E+00 a      1321     1    12     2     1\n -8.9142099529358493E-03 a      1322     1    12     2     2\n -2.0393041146752039E-01 a      1323     1    12     2     3\n -6.9000835297876773E-01 a      1324     1    12     2     4\n  1.0428725566696373E+00 a      1325     1    12     2     5\n -1.6848519577676932E-01 a      1326     1    12     2     6\n -1.5743042826299619E-01 a      1327     1    12     2     7\n -1.4376412710932862E-01 a      1328     1    12     2     8\n  2.9805064945746379E-01 a      1329     1    12     2     9\n -1.0196859653920623E-02 a      1330     1    12     2    10\n -3.4285288697311561E-03 a      1331     1    12     2    11\n  2.3575486239672205E-01 a      1332     1    12     2    12\n  1.8597867776101362E-01 a      1333     1    12     2    13\n -1.7219482934054575E+00 a      1334     1    12     2    14\n -1.1104723422097662E+00 a      1335     1    12     2    15\n -1.2078541530541429E+00 a      1336     1    13     2     1\n  8.1219701890282145E-02 a      1337     1    13     2     2\n -2.9435260381395117E-01 a      1338     1    13     2     3\n -2.0676934860465623E+00 a      1339     1    13     2     4\n  9.6402057805122454E-02 a      1340     1    13     2     5\n  1.3378384635207846E-01 a      1341     1    13     2     6\n -1.2788863264881636E-01 a      1342     1    13     2     7\n  3.6552790066743106E-02 a      1343     1    13     2     8\n -1.0846542368238193E-01 a      1344     1    13     2     9\n -7.5384805277046135E-02 a      1345     1    13     2    10\n -3.2164176205679340E-01 a      1346     1    13     2    11\n  1.1065068685359858E+00 a      1347     1    13     2    12\n -9.7160827736155891E-02 a      1348     1    13     2    13\n  1.1079500851250927E+00 a      1349     1    13     2    14\n -1.6615149252029643E-01 a      1350     1    13     2    15\n -3.5291388742972724E-01 a      1351     1    14     2     1\n  1.5397460931823087E-02 a      1352     1    14     2     2\n  1.3325653569991763E-01 a      1353     1    14     2     3\n -1.4615950146667103E+00 a      1354     1    14     2     4\n  2.9375796441618470E-02 a      1355     1    14     2     5\n -1.8147399352175473E+00 a      1356     1    14     2     6\n -3.2420690497474919E-01 a      1357     1    14     2     7\n -2.9027675775289713E-01 a      1358     1    14     2     8\n  7.7784883975161379E-01 a      1359     1    14     2     9\n -3.0059365429927770E-01 a      1360     1    14     2    10\n  2.6626115085782709E-01 a      1361     1    14     2    11\n -6.6174223565204776E-02 a      1362     1    14     2    12\n -1.0576862654606288E-01 a      1363     1    14     2    13\n -5.0213547438835848E-01 a      1364     1    14     2    14\n  5.1562012879626906E-01 a      1365     1    14     2    15\n -2.3076410227737765E+00 a      1366     1    15     2     1\n -8.8071470660702936E-02 a      1367     1    15     2     2\n -6.7774341197031729E-01 a      1368     1    15     2     3\n -7.7274605882685488E-01 a      1369     1    15     2     4\n  2.2372057054501190E-01 a      1370     1    15     2     5\n -9.6861151148145419E-02 a      1371     1    15     2     6\n -4.0579598962519592E+00 a      1372     1    15     2     7\n  4.1586647120832709E-01 a      1373     1    15     2     8\n  1.3995058839201306E+00 a      1374     1    15     2     9\n -2.9473800623040047E-01 a      1375     1    15     2    10\n  1.6532395366466761E+00 a      1376     1    15     2    11\n  1.1203454280314746E+00 a      1377     1    15     2    12\n  4.6100702863684118E-01 a      1378     1    15     2    13\n  7.1821301928389891E-01 a      1379     1    15     2    14\n  2.6392522071371038E+00 a      1380     1    15     2    15\n  5.6857122291207807E-01 b      1381     2     1\n -3.4348431149226006E+00 b      1382     2     2\n -2.0086418606633285E+00 b      1383     2     3\n  2.1725312238251258E+00 b      1384     2     4\n -2.3886424154196235E+00 b      1385     2     5\n -4.2236829740831677E-02 b      1386     2     6\n -1.9617438572889678E-01 b      1387     2     7\n -4.9151746671534715E+00 b      1388     2     8\n  2.1269533594375374E+00 b      1389     2     9\n -1.0652281184413546E+00 b      1390     2    10\n -3.6703671102447615E+00 b      1391     2    11\n -4.6060194139627120E+00 b      1392     2    12\n -2.5178005784211619E+00 b      1393     2    13\n  1.0263144248898695E-01 b      1394     2    14\n -1.1074423114563154E+00 b      1395     2    15\n  1.9119252798811948E-01 a      1396     2     1     3     1\n -7.3622833620930572E-01 a      1397     2     2     3     1\n  2.2971456158334369E-01 a      1398     2     3     3     1\n -7.6077755460766935E-02 a      1399     2     4     3     1\n -2.9150000514937752E-01 a      1400     2     5     3     1\n -4.4903956468121514E-01 a      1401     2     6     3     1\n -1.1145033905117251E-01 a      1402     2     7     3     1\n  2.5185640924346337E+00 a      1403     2     8     3     1\n -4.0539919733959229E-01 a      1404     2     9     3     1\n  3.5543795901171271E-01 a      1405     2    10     3     1\n  3.4947113675155478E-01 a      1406     2    11     3     1\n  7.3886097618684488E-01 a      1407     2    12     3     1\n  1.0581920921962007E+00 a      1408     2    13     3     1\n -1.9649884591851044E-01 a      1409     2    14     3     1\n  2.6856529380200378E-01 a      1410     2    15     3     1\n -4.0780420424690282E+00 b      1411     3     1\n"
  },
  {
    "path": "examples/nnp-comp2/Cu2S_PBE/nnp-data-2/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.9058400653162604E+00\nconv_energy   1.1065438723452953E+01\nconv_length   1.1108978337775813E+01\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type.\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              15 15          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \n#symfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\n#symfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \n# symfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\n# symfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \n# symfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n"
  },
  {
    "path": "examples/nnp-comp2/Cu2S_PBE/nnp-data-2/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   4.4265075533537512E-01   2.4749666370750694E+00   1.1060722509726018E+00   1.7529945320684118E-01\n         1          2   1.9388935120109099E+00   4.4097236813336176E+00   3.2978532722457570E+00   2.5128573402537990E-01\n         1          3   1.0807838070518886E-02   4.1304458483662820E-01   7.1868741885005083E-02   3.4662740758690899E-02\n         1          4   2.6547690535721169E+00   5.1765886817791573E+00   4.0454007565017012E+00   2.5579520863782829E-01\n         1          5   1.4995320530771344E-01   1.3519360603219461E+00   5.0922021208534995E-01   1.2262469346514367E-01\n         1          6   1.3478375671698186E+00   4.1418336720929823E+00   2.5639172172860367E+00   3.7353134785219438E-01\n         1          7   8.1186515243907842E-01   2.4990660558808346E+00   1.5882886682336448E+00   1.6357025849311374E-01\n         1          8   8.3560066574306779E-01   3.5190788505185737E+00   1.8937518336778314E+00   3.5586606866248682E-01\n         1          9   1.3835259104473252E+00   2.6464501497863053E+00   2.2079115860694039E+00   1.3890110758612836E-01\n         1         10   1.1951184603566023E+00   2.8927959575917903E+00   2.0316656202063745E+00   2.0737960708933709E-01\n         1         11   9.8808644349834496E-01   1.6027978035707744E+00   1.3843071713511630E+00   7.8529797179971425E-02\n         1         12   9.1981902848818131E-01   2.2238977642164559E+00   1.6225786253237706E+00   1.8739973313204333E-01\n         1         13   2.2597919343915630E-02   1.2708403027630688E-01   5.1881770327387181E-02   8.3606264892797395E-03\n         1         14   3.8408359796381125E-01   9.9411428648517852E-01   6.2027578566565089E-01   5.8321113787023079E-02\n         1         15   1.4083722552013387E+00   4.0837798882115868E+00   2.3948910589466421E+00   2.7205794214050266E-01\n         1         16   7.1017533056026858E-02   3.5924947585956063E-01   1.5467611295933245E-01   2.3262660654328696E-02\n         1         17   2.2565953627627136E+00   4.5529270325456537E+00   3.2026845490445135E+00   2.2099610481145684E-01\n         1         18   2.9798875096866855E+00   6.8397125214329391E+00   4.6222211152781112E+00   4.9994275841001823E-01\n         1         19   8.3935452330094168E-02   4.9012718923180415E-01   2.1931677551585280E-01   3.8677705768792127E-02\n         1         20   1.3046135311117131E+00   2.4200616155686863E+00   1.7341246117915960E+00   1.1785806355696596E-01\n         1         21   8.0199454261870406E-01   1.9483510241268203E+00   1.2961643168731083E+00   1.4672710574320125E-01\n         1         22   6.4374558536931794E-03   4.8182460226993802E-02   1.6707732409685424E-02   3.2034525707065878E-03\n         1         23   1.5318897938282255E-01   4.5416402718924276E-01   2.6291575700052811E-01   2.8677843631321493E-02\n         1         24   6.9418423813301466E-01   2.4541868250982004E+00   1.3137330249991466E+00   1.6387572931667668E-01\n         1         25   2.0299364848972126E-02   1.3683512999502856E-01   4.9832084435863372E-02   8.9516084933796824E-03\n         1         26   9.8701872413726255E-01   2.2586534755453709E+00   1.4780519754057804E+00   1.1871005779401544E-01\n         1         27   1.5186918852877633E+00   3.9050329487971425E+00   2.4766215129303397E+00   2.9079756604312895E-01\n         1         28   3.8161695126727853E-02   2.7674887655318292E-01   1.1058155022715112E-01   2.1905596415412825E-02\n         1         29   5.8977740954298397E-01   1.2386293684496201E+00   8.2364153102433180E-01   6.5551076498813768E-02\n         1         30   3.8193645094435219E-01   1.0506523465236675E+00   6.4620992439490277E-01   8.2156802905661991E-02\n         1         31   1.0877216711266600E+00   2.8800857695995274E+00   1.8376742285101342E+00   1.7208854608735455E-01\n         1         32   8.8783936606988565E+00   1.4736206648360312E+01   1.1698178703687816E+01   6.1086423843563575E-01\n         1         33   1.3732816872509948E+01   2.4205696120591984E+01   1.8301681574699320E+01   1.4667109447685063E+00\n         1         34   9.0278290856362930E-01   2.4756737855204465E+00   1.5308385269169829E+00   1.4436373406542297E-01\n         1         35   8.9087476076510974E+00   1.4693677789914243E+01   1.1598835757597929E+01   6.1413283845889899E-01\n         1         36   1.1456139379005354E+01   2.1316973822535566E+01   1.5642394988112523E+01   1.3052104326252827E+00\n         1         37   2.5379941726465405E+00   4.3361767105514337E+00   3.3765899739621799E+00   1.8298023565504315E-01\n         1         38   3.6421208177618460E+00   6.8311536891079561E+00   5.0762844334415771E+00   4.5568219422020401E-01\n         1         39   1.3689487135523365E-01   3.6820433872931851E-01   2.2763176703809612E-01   2.1660654887416739E-02\n         1         40   2.5649159161016786E+00   4.1963702184459795E+00   3.2443756016118601E+00   1.8134089138334111E-01\n         1         41   2.0642465841299500E+00   4.1692860632438746E+00   2.9548001264619574E+00   2.6394004100571961E-01\n         1         42   4.6512029522926740E-01   1.4664174976442483E+00   8.5498686781623590E-01   9.3059828249480767E-02\n         1         43   4.6547662784275197E+00   8.4479388434646854E+00   6.4237386473137450E+00   3.8411325204761104E-01\n         1         44   8.6415653134619532E+00   1.6278459810269940E+01   1.1787210979312956E+01   1.0179454392709681E+00\n         1         45   3.8547816500338000E-01   1.2767023692244872E+00   7.1226405976144813E-01   7.8602173939313374E-02\n         1         46   4.6789216668759375E+00   8.4098137810639617E+00   6.3515226749250546E+00   3.8255728791957827E-01\n         1         47   6.9948460709494453E+00   1.3576561360549128E+01   9.8530015506444073E+00   8.9220167841463538E-01\n         1         48   1.3368052908889996E-01   3.9480780749423111E-01   2.4318877739968350E-01   2.6424765019592393E-02\n         1         49   1.3296050002218320E+00   2.5112834184004242E+00   1.8605136293226228E+00   1.1617142815775323E-01\n         1         50   2.2651205823176861E+00   4.5657352835038028E+00   3.2381271278722017E+00   3.2239976604583942E-01\n         1         51   5.8271222801219491E-02   1.8954030778131817E-01   1.0498686421401084E-01   1.1616221414215330E-02\n         1         52   1.3485470042844463E+00   2.4053107174498130E+00   1.7699194452312146E+00   1.1270742957344337E-01\n         1         53   1.1637151841314661E+00   2.5500691319681228E+00   1.7421774640240988E+00   1.7312511619868448E-01\n         1         54   4.4790780968218247E-01   1.8123258976262868E+00   9.1548128537474582E-01   1.2057744180124463E-01\n         1         55   5.6625365929518660E-02   2.3732586931975447E-01   1.1026918667512448E-01   1.6052748969046394E-02\n         2          1   1.5743455957850613E-01   1.5073065774351941E+00   5.5303612548630132E-01   1.1899585890474287E-01\n         2          2   1.0499049602999246E-02   8.6977355932082434E-01   1.8767905028057794E-01   8.0999273778781938E-02\n         2          3   8.1374754443656305E-01   2.4261950387937841E+00   1.6489266361228783E+00   1.8141831271144424E-01\n         2          4   1.6145285517255994E-01   2.5518950524850439E+00   1.1085810713423514E+00   3.0666977013499336E-01\n         2          5   9.4883860757335603E-01   2.6710371110933706E+00   2.0227003782508501E+00   1.9067433597095923E-01\n         2          6   9.6539811175376589E-01   4.8423104282718699E+00   2.8219530812454505E+00   4.7918479666939673E-01\n         2          7   4.7529037518360068E-01   2.3097294285577390E+00   1.2819586086430184E+00   1.9684407624800027E-01\n         2          8   1.7095723912637146E+00   5.1341988940591596E+00   3.4864385967612606E+00   3.8797019939122079E-01\n         2          9   3.1233518617392186E-01   1.8219399362068016E+00   9.4687591683891648E-01   1.9153423627191457E-01\n         2         10   3.5767426586678325E-01   1.6223983964512552E+00   1.0158328101031879E+00   2.0438269411930965E-01\n         2         11   1.0137865774210515E+00   3.5680165380478712E+00   2.1790772630319624E+00   3.3886299872978104E-01\n         2         12   3.0941620316795870E-01   1.2113971995541650E+00   8.1128931266188542E-01   1.3619945830873967E-01\n         2         13   2.0707073331993908E-01   1.0337121848367778E+00   4.8189215108834055E-01   8.2852701405279283E-02\n         2         14   8.2193625876920096E-01   2.6219750037393883E+00   1.6246945966895010E+00   1.6181008698586691E-01\n         2         15   3.4456131789121569E-01   1.9177774581312250E+00   9.1804106293915821E-01   1.9508948177749674E-01\n         2         16   2.4458465228606030E-01   9.2849994113117507E-01   4.7384793258920110E-01   6.6048360078919607E-02\n         2         17   3.8379277734053305E+00   7.3005509674816178E+00   5.3924175775352499E+00   3.4350110848414023E-01\n         2         18   1.3880228332655034E+00   4.3361502232155660E+00   2.5900317962172914E+00   3.7347009392110642E-01\n         2         19   2.1484844584477185E-02   2.6334808335921994E-01   7.2660811029078703E-02   1.5611227962074608E-02\n         2         20   2.3312476084988785E-02   2.9805602022674860E-01   8.8306912423691541E-02   1.9292008893662619E-02\n         2         21   2.7195526816721900E-02   1.2294682924678357E-01   5.9508063803285792E-02   9.1362387893595305E-03\n         2         22   1.8338777683487169E+00   3.1165354847033653E+00   2.3131465623530860E+00   1.2906733784622765E-01\n         2         23   4.9520703398617671E-01   1.3739936187945998E+00   8.5886930842858833E-01   1.0719798991816548E-01\n         2         24   8.3372459829371623E-02   5.9799519441710691E-01   2.3109776020291722E-01   4.7860816214886359E-02\n         2         25   3.8387545763852293E-01   1.5190933343391366E+00   8.5913087479927619E-01   9.8683853404507374E-02\n         2         26   1.3695758827157153E-01   9.8943867324686252E-01   4.3201869514899510E-01   1.0492395861599907E-01\n         2         27   9.2344997100998055E-02   4.6313711150328485E-01   2.0414417289865988E-01   3.4759250455299269E-02\n         2         28   1.9125391528191629E+00   4.2554336862028403E+00   2.9312236631302082E+00   2.2284144795806357E-01\n         2         29   5.6703537659832792E-01   2.2331423792366145E+00   1.2254617118290669E+00   2.1291909229192083E-01\n         2         30   8.7466581491831251E-03   1.5578055355040685E-01   3.7072425840003614E-02   9.2701812094135964E-03\n         2         31   9.2178393180946533E-03   1.5904126501260279E-01   4.0348551352842446E-02   9.5003668218397400E-03\n         2         32   9.2761896250624876E-01   1.7921935800038666E+00   1.2308347709940852E+00   8.0254390629725877E-02\n         2         33   2.0159751859216588E-01   6.8263459163972073E-01   3.9620994276101978E-01   5.8856944009654792E-02\n         2         34   1.8664138936449807E-02   2.0528233698508752E-01   5.8996171265576887E-02   1.2127819025198241E-02\n         2         35   9.1202524005712503E-03   6.7278846278479063E-02   2.1113240418557132E-02   4.1014379356923755E-03\n         2         36   3.2335303640640407E+00   6.2800805982849672E+00   4.5844950729868890E+00   2.9899493759159784E-01\n         2         37   1.2157054366093822E+01   1.8705346938457929E+01   1.5194740546143654E+01   7.2484700079972553E-01\n         2         38   7.9921665749592199E+00   1.7643832919265371E+01   1.2475514463185192E+01   1.2154982160899783E+00\n         2         39   2.1807932118933904E+00   4.5852265968783925E+00   3.1833153239195777E+00   2.3238027423515445E-01\n         2         40   1.2108995132489303E+01   1.8698532669729367E+01   1.5120860751112655E+01   7.2733912128396438E-01\n         2         41   7.0165185028024153E+00   1.5401626639949257E+01   1.0792131828621983E+01   1.0398487914522918E+00\n         2         42   7.8202016983210931E-01   1.8611702516693229E+00   1.2174201587607194E+00   1.1147820578875754E-01\n         2         43   3.2709677848274334E+00   5.4223547723084513E+00   4.2602646606465866E+00   2.7314590833102631E-01\n         2         44   2.2651344778022735E+00   5.0863609156322838E+00   3.5902774962451893E+00   3.5808456983868103E-01\n         2         45   1.9453916371177205E-01   5.2428294654973473E-01   3.2666614703573060E-01   3.3752889916549095E-02\n         2         46   3.3374664427470768E+00   5.1743679146252255E+00   4.0448520764617184E+00   1.9237711912273595E-01\n         2         47   1.3929130654519679E+00   3.0394486810407773E+00   2.0655732163336640E+00   2.0369407259850125E-01\n         2         48   1.9994637331940199E+00   4.1338816564289589E+00   2.9547223524158195E+00   2.2378987872487088E-01\n         2         49   7.0024276367635920E+00   1.2030420415617256E+01   9.3380137489663113E+00   5.1318226612730578E-01\n         2         50   4.2164884610310587E+00   1.0982260050282811E+01   7.2964881447285777E+00   8.6437104938712894E-01\n         2         51   1.2626170541578807E+00   2.8532820982381413E+00   1.9301828785358952E+00   1.6090649059496773E-01\n         2         52   6.9131495181976197E+00   1.1993764170970396E+01   9.2801906041296842E+00   5.1334742977278891E-01\n         2         53   3.6648854802162818E+00   9.3657087980349765E+00   6.2138002856746217E+00   7.2113430819953039E-01\n         2         54   4.5980423684463972E-01   1.3560623799760794E+00   7.7522092031619327E-01   8.5451710984528917E-02\n         2         55   1.8705975374375172E+00   3.5090502773932890E+00   2.5942084944102217E+00   2.0373417922112785E-01\n         2         56   1.1651564701031334E+00   3.1755530133217258E+00   2.1080271338825565E+00   2.5349787826375941E-01\n         2         57   1.0053065805206919E-01   2.9582602902027616E-01   1.7423572452553945E-01   1.9707524568074092E-02\n         2         58   1.9253405309213385E+00   3.2577395800436522E+00   2.4269493476824469E+00   1.2964719332891439E-01\n         2         59   7.1139248247643916E-01   1.7309524970829380E+00   1.1411509287449384E+00   1.3030995199739998E-01\n         2         60   9.3937729881137341E-02   5.5676161934251234E-01   2.3077136041721213E-01   4.0182083755630246E-02\n         2         61   1.8436273033597170E-01   9.8356822105150410E-01   4.8304060547071725E-01   6.5046747553556633E-02\n         2         62   4.9304521543447596E-02   6.4119617560461051E-01   2.4559335034632787E-01   7.3681477269694498E-02\n         2         63   1.7856551824141351E-01   9.9275407174597208E-01   4.7418706397868426E-01   6.4289221475592739E-02\n         2         64   4.0092925562913710E-02   5.0140686705026560E-01   1.9062950626089070E-01   5.6453140178347211E-02\n         2         65   4.5960636175893750E-02   2.2735828246294021E-01   1.0320965328121219E-01   1.3911736509373249E-02\n         2         66   6.7010548711732816E-03   6.7557318200940089E-02   2.7223098089251895E-02   7.6928676004739882E-03\n"
  },
  {
    "path": "examples/nnp-comp2/Cu2S_PBE/nnp-data-2/weights.016.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  3.2195940469770823E-01 a         1     0     1     1     1\n  1.4369141139186226E+00 a         2     0     1     1     2\n -1.6378193660601843E+00 a         3     0     1     1     3\n -1.3297725407586964E+00 a         4     0     1     1     4\n  1.6275666838797385E+00 a         5     0     1     1     5\n -9.8150706987131409E-01 a         6     0     1     1     6\n -2.0314682816557492E+00 a         7     0     1     1     7\n  1.2298159547152223E+00 a         8     0     1     1     8\n  3.7734356010694037E-01 a         9     0     1     1     9\n -7.4798724498994540E-01 a        10     0     1     1    10\n -1.0264023972652625E+00 a        11     0     1     1    11\n  2.1548149161547818E+00 a        12     0     1     1    12\n -4.4383386262545370E+00 a        13     0     1     1    13\n -2.4435473317133219E-01 a        14     0     1     1    14\n -6.1027926322828363E-01 a        15     0     1     1    15\n  4.4428450832284844E-01 a        16     0     2     1     1\n  2.5280321355901667E-02 a        17     0     2     1     2\n -5.1348956424873464E-02 a        18     0     2     1     3\n -6.7389386998728484E-02 a        19     0     2     1     4\n  7.9017156493080665E-01 a        20     0     2     1     5\n -1.3027417422848386E+00 a        21     0     2     1     6\n -8.6714642372970363E-01 a        22     0     2     1     7\n -1.2330008219699118E-01 a        23     0     2     1     8\n  1.3863371339510064E-01 a        24     0     2     1     9\n  9.8662582047645675E-01 a        25     0     2     1    10\n -6.6860689167710663E-01 a        26     0     2     1    11\n -5.7702855477656523E-01 a        27     0     2     1    12\n -3.3785518275739794E+00 a        28     0     2     1    13\n -3.7273617992723512E-01 a        29     0     2     1    14\n  3.4919879688918898E-01 a        30     0     2     1    15\n -1.1291234535760492E-02 a        31     0     3     1     1\n -1.7267433768383151E-02 a        32     0     3     1     2\n  7.6271861145437436E-02 a        33     0     3     1     3\n  1.1280578662037109E-02 a        34     0     3     1     4\n -5.7070445187209196E-01 a        35     0     3     1     5\n -1.7500160164081546E-01 a        36     0     3     1     6\n -1.7314591536609669E-01 a        37     0     3     1     7\n  4.5384400542541042E-01 a        38     0     3     1     8\n -3.6132022310766843E-01 a        39     0     3     1     9\n -1.1481692001568665E-02 a        40     0     3     1    10\n -2.8007638457697592E-01 a        41     0     3     1    11\n -2.4661198714086346E-01 a        42     0     3     1    12\n -4.8738483506853686E-01 a        43     0     3     1    13\n -1.7515676237207672E-01 a        44     0     3     1    14\n -2.7698774645408064E-01 a        45     0     3     1    15\n -7.3353809816319518E-02 a        46     0     4     1     1\n  1.3319982387588443E+00 a        47     0     4     1     2\n -1.6045032259616718E+00 a        48     0     4     1     3\n -5.6171405803716890E-01 a        49     0     4     1     4\n  1.0965593065022521E+00 a        50     0     4     1     5\n -1.0946614607300647E+00 a        51     0     4     1     6\n -1.6401004311121448E+00 a        52     0     4     1     7\n  1.3286018634786556E+00 a        53     0     4     1     8\n  3.8768393465651180E-01 a        54     0     4     1     9\n -2.6203400815630551E-01 a        55     0     4     1    10\n -9.9315256776717176E-01 a        56     0     4     1    11\n  2.0765210174191768E+00 a        57     0     4     1    12\n -3.2601414935951527E+00 a        58     0     4     1    13\n  3.3661719012512709E-01 a        59     0     4     1    14\n -3.4690439886050933E-01 a        60     0     4     1    15\n  1.0801949325794261E-01 a        61     0     5     1     1\n  9.9574459631645529E-01 a        62     0     5     1     2\n  5.9677868604416995E-01 a        63     0     5     1     3\n  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-5.0020217591609545E-02 a       883     1     3     2    13\n -1.1057395711635998E+00 a       884     1     3     2    14\n  6.5242339517503101E-01 a       885     1     3     2    15\n  7.1526692910887957E-01 a       886     1     4     2     1\n -9.6325742269420633E-01 a       887     1     4     2     2\n  4.9791714382759683E-01 a       888     1     4     2     3\n  3.3555881912930779E-01 a       889     1     4     2     4\n -7.4646819469277015E-01 a       890     1     4     2     5\n -1.3366761181596428E-02 a       891     1     4     2     6\n  1.4678158824246515E-01 a       892     1     4     2     7\n -5.9265770569664633E-01 a       893     1     4     2     8\n -1.6105545870245319E+00 a       894     1     4     2     9\n -8.1539388570963744E-01 a       895     1     4     2    10\n -3.2153364635326342E-01 a       896     1     4     2    11\n -1.9742490403764998E-01 a       897     1     4     2    12\n -9.6010576546179310E-02 a       898     1     4     2    13\n  5.4053132625754807E-01 a       899     1     4     2    14\n -6.6527536182595381E-01 a       900     1     4     2    15\n -1.0311239401661291E-02 a       901     1     5     2     1\n -2.4391728047902564E-01 a       902     1     5     2     2\n -2.6053783765441443E+00 a       903     1     5     2     3\n  1.2225362450009616E+00 a       904     1     5     2     4\n -1.0533233368032811E-01 a       905     1     5     2     5\n  3.9063758049525305E-01 a       906     1     5     2     6\n  8.6911460669551499E-01 a       907     1     5     2     7\n -2.8396349307894353E-01 a       908     1     5     2     8\n -1.1444538651221616E+00 a       909     1     5     2     9\n -1.3882572065091192E+00 a       910     1     5     2    10\n -6.4429067042418764E-01 a       911     1     5     2    11\n -1.6120360969190065E-01 a       912     1     5     2    12\n -7.4543066835039501E-02 a       913     1     5     2    13\n -1.2541957859225519E-01 a       914     1     5     2    14\n  8.4106912061765127E-02 a       915     1     5     2    15\n  1.4282822602470033E-01 a       916     1     6     2     1\n  3.0092192373842963E-01 a       917     1     6     2     2\n -1.0310276549359855E-01 a       918     1     6     2     3\n -1.6282692155933154E+00 a       919     1     6     2     4\n -4.7788521164490289E-01 a       920     1     6     2     5\n  1.5377478325632215E+00 a       921     1     6     2     6\n  1.6683922965223971E-01 a       922     1     6     2     7\n -2.1713348497945326E-01 a       923     1     6     2     8\n  1.2287879679019704E+00 a       924     1     6     2     9\n  1.1748461827919205E+00 a       925     1     6     2    10\n -8.2717155877677612E-02 a       926     1     6     2    11\n  1.1224892616936032E-03 a       927     1     6     2    12\n -9.9088592513948026E-02 a       928     1     6     2    13\n -5.0703330096911958E-01 a       929     1     6     2    14\n -6.0425054966407332E-01 a       930     1     6     2    15\n  3.7342128518449774E-01 a       931     1     7     2     1\n -7.0642579809140793E-01 a       932     1     7     2     2\n  4.1366474794403780E+00 a       933     1     7     2     3\n -4.1975051488578707E-01 a       934     1     7     2     4\n -8.1967295421237296E-01 a       935     1     7     2     5\n -4.1064476866785515E-01 a       936     1     7     2     6\n  7.5472306350085705E-01 a       937     1     7     2     7\n -2.9576917550856396E-02 a       938     1     7     2     8\n  7.8866023554320530E-01 a       939     1     7     2     9\n  6.9615420733537980E-01 a       940     1     7     2    10\n  6.4787906025376096E-01 a       941     1     7     2    11\n  2.2823555869337062E-01 a       942     1     7     2    12\n -5.3906263510364101E-02 a       943     1     7     2    13\n  3.4219518915182448E-02 a       944     1     7     2    14\n  5.5173287361705092E-01 a       945     1     7     2    15\n  6.7381005428227214E-01 a       946     1     8     2     1\n -4.8504285100374700E-01 a       947     1     8     2     2\n -4.0054718199284869E+00 a       948     1     8     2     3\n  6.4590244494383897E-01 a       949     1     8     2     4\n -1.3993359913123446E-01 a       950     1     8     2     5\n  5.6309904903964991E-01 a       951     1     8     2     6\n -1.7093284369040360E-01 a       952     1     8     2     7\n -3.2847051004760497E-01 a       953     1     8     2     8\n  6.3785905862873804E-01 a       954     1     8     2     9\n  2.0408302789033098E-01 a       955     1     8     2    10\n  2.7519798226070225E-01 a       956     1     8     2    11\n -1.4697286715080818E-01 a       957     1     8     2    12\n -5.9875296533764910E-01 a       958     1     8     2    13\n  1.3629477620010486E+00 a       959     1     8     2    14\n  5.3057142275106084E-01 a       960     1     8     2    15\n -2.6593320337980675E-01 a       961     1     9     2     1\n -8.9718803244171308E-01 a       962     1     9     2     2\n  2.4410241313517052E+00 a       963     1     9     2     3\n  7.1440766170921477E-01 a       964     1     9     2     4\n  9.4754041748308271E-01 a       965     1     9     2     5\n  4.0957239760157593E-01 a       966     1     9     2     6\n  3.3451652473186766E-01 a       967     1     9     2     7\n -7.4606728036216552E-01 a       968     1     9     2     8\n  9.0283613717749234E-01 a       969     1     9     2     9\n -6.3579450250688474E-01 a       970     1     9     2    10\n  1.7234960435283180E+00 a       971     1     9     2    11\n  4.9737378929858944E-01 a       972     1     9     2    12\n -6.1808673087844168E-01 a       973     1     9     2    13\n -6.8387111575964971E-02 a       974     1     9     2    14\n -4.5080467691957071E-01 a       975     1     9     2    15\n -1.1552771656253302E-01 a       976     1    10     2     1\n  1.1510942362062679E+00 a       977     1    10     2     2\n -4.7508942297479367E-01 a       978     1    10     2     3\n -7.0264494439358879E-02 a       979     1    10     2     4\n  3.1329128725830391E-01 a       980     1    10     2     5\n  1.1362060718778118E+00 a       981     1    10     2     6\n -7.3020925727955388E-01 a       982     1    10     2     7\n  3.0907528768278064E-01 a       983     1    10     2     8\n -3.1559455024928501E-01 a       984     1    10     2     9\n  3.5667615125433022E-01 a       985     1    10     2    10\n -2.1683634417276573E-01 a       986     1    10     2    11\n  4.4995234727876016E-01 a       987     1    10     2    12\n -6.1327768590084830E-01 a       988     1    10     2    13\n  3.7257638589846959E-01 a       989     1    10     2    14\n  4.4351899148031415E-01 a       990     1    10     2    15\n  1.3770485751117165E+00 a       991     1    11     2     1\n  1.1517293854181467E+00 a       992     1    11     2     2\n  2.7297462798809722E+00 a       993     1    11     2     3\n -9.1821922842826720E-01 a       994     1    11     2     4\n -1.0420983506703921E-01 a       995     1    11     2     5\n -2.1954200783432909E-01 a       996     1    11     2     6\n  5.0952884829037613E-02 a       997     1    11     2     7\n -2.2342464479497986E-02 a       998     1    11     2     8\n  6.6549567586524057E-03 a       999     1    11     2     9\n -7.5218469044430514E-01 a      1000     1    11     2    10\n -1.1904400228736616E+00 a      1001     1    11     2    11\n -3.4873848378600622E-02 a      1002     1    11     2    12\n  1.7224847865686976E-01 a      1003     1    11     2    13\n -1.8756646278834987E+00 a      1004     1    11     2    14\n  6.8572107849869091E-01 a      1005     1    11     2    15\n -5.7365145234382653E-01 a      1006     1    12     2     1\n -4.5829056785651823E-01 a      1007     1    12     2     2\n  9.0803327330119321E-01 a      1008     1    12     2     3\n  2.3717982946521401E-01 a      1009     1    12     2     4\n  5.0627177482194689E-02 a      1010     1    12     2     5\n  3.3958443332639543E-01 a      1011     1    12     2     6\n -2.2943204436635853E+00 a      1012     1    12     2     7\n  4.6036016360183271E-02 a      1013     1    12     2     8\n  2.7061919529894923E-01 a      1014     1    12     2     9\n  5.8336597372191312E-01 a      1015     1    12     2    10\n -2.4468809756395457E-01 a      1016     1    12     2    11\n  2.3316351039215480E-01 a      1017     1    12     2    12\n -4.0417948881589966E-01 a      1018     1    12     2    13\n  2.7145919426060872E-01 a      1019     1    12     2    14\n  5.2676503503779815E-01 a      1020     1    12     2    15\n -3.2451632850953666E-01 a      1021     1    13     2     1\n  1.4400985484115374E+00 a      1022     1    13     2     2\n -5.1403190834760681E-01 a      1023     1    13     2     3\n -8.2509295302280139E-01 a      1024     1    13     2     4\n -4.4988384197368803E-01 a      1025     1    13     2     5\n  1.7654436438153512E-01 a      1026     1    13     2     6\n -7.5586960108977974E-01 a      1027     1    13     2     7\n  1.1574954711083248E-01 a      1028     1    13     2     8\n -5.5134904803128471E-01 a      1029     1    13     2     9\n  7.6814769590216414E-01 a      1030     1    13     2    10\n  3.2274026143295681E-01 a      1031     1    13     2    11\n -1.0874785011892589E-01 a      1032     1    13     2    12\n  7.3121480808032580E-01 a      1033     1    13     2    13\n -3.6760648545987756E-01 a      1034     1    13     2    14\n -1.2040378566646095E+00 a      1035     1    13     2    15\n  2.1035641283748334E+00 a      1036     1    14     2     1\n -1.0401602759801443E-01 a      1037     1    14     2     2\n -1.9108101405849625E+00 a      1038     1    14     2     3\n -9.5004265511852803E-01 a      1039     1    14     2     4\n -2.2859168409450490E+00 a      1040     1    14     2     5\n -3.4242369565107683E-01 a      1041     1    14     2     6\n -5.8153691994552603E-01 a      1042     1    14     2     7\n -1.6970622309496672E-01 a      1043     1    14     2     8\n -5.4491201446134188E-02 a      1044     1    14     2     9\n  1.4384352023574090E+00 a      1045     1    14     2    10\n -4.8487117731149421E-01 a      1046     1    14     2    11\n  2.2052840508964752E-01 a      1047     1    14     2    12\n -5.3598690903012445E-03 a      1048     1    14     2    13\n -2.0278856242085208E+00 a      1049     1    14     2    14\n  3.1157232197366325E-01 a      1050     1    14     2    15\n  5.7316637539491400E-01 a      1051     1    15     2     1\n -9.2934788626337583E-01 a      1052     1    15     2     2\n -5.6668799776519030E-01 a      1053     1    15     2     3\n  3.8853495892803330E-01 a      1054     1    15     2     4\n  1.5129878764100284E+00 a      1055     1    15     2     5\n  1.3081701226495998E-01 a      1056     1    15     2     6\n  2.6015288744371318E-01 a      1057     1    15     2     7\n -4.5075107996919050E-01 a      1058     1    15     2     8\n -6.8096127716591008E-03 a      1059     1    15     2     9\n  3.0388041387494719E-01 a      1060     1    15     2    10\n  5.1118397621351774E-01 a      1061     1    15     2    11\n  9.3654135537755112E-01 a      1062     1    15     2    12\n -3.4240309648393807E-01 a      1063     1    15     2    13\n  2.4905289395175798E-01 a      1064     1    15     2    14\n  7.4566810295180186E-01 a      1065     1    15     2    15\n -1.1935767292827559E+00 b      1066     2     1\n  3.8419653184773339E+00 b      1067     2     2\n  3.9774546360951493E+00 b      1068     2     3\n -2.8827813366305710E+00 b      1069     2     4\n -2.6995528443715688E+00 b      1070     2     5\n -2.8812846196820461E+00 b      1071     2     6\n -9.0425945923083381E-02 b      1072     2     7\n  3.8353195155187261E+00 b      1073     2     8\n  6.1842726566105244E-01 b      1074     2     9\n  3.1935730633298247E+00 b      1075     2    10\n -2.6575252030687664E+00 b      1076     2    11\n -2.0522355773505083E+00 b      1077     2    12\n -1.0331368038700155E+00 b      1078     2    13\n  2.4512913442225234E-01 b      1079     2    14\n -1.1561942425098355E+00 b      1080     2    15\n -4.5715408373777011E-01 a      1081     2     1     3     1\n  1.7696100380422413E+00 a      1082     2     2     3     1\n  6.2132075972024647E-01 a      1083     2     3     3     1\n -8.7915184671220795E-02 a      1084     2     4     3     1\n -2.7208633650057218E-01 a      1085     2     5     3     1\n -2.9627040256040249E-01 a      1086     2     6     3     1\n  7.0783254068890064E-02 a      1087     2     7     3     1\n -2.7220123157998781E+00 a      1088     2     8     3     1\n -2.5166911333525277E-01 a      1089     2     9     3     1\n  1.0376387200101467E+00 a      1090     2    10     3     1\n -1.5526649799050393E-01 a      1091     2    11     3     1\n -1.0135662907081178E+00 a      1092     2    12     3     1\n  4.4343355884720239E+00 a      1093     2    13     3     1\n  5.7893951448258443E-02 a      1094     2    14     3     1\n  2.4536449114181622E-01 a      1095     2    15     3     1\n -1.6549710909970781E+00 b      1096     3     1\n"
  },
  {
    "path": "examples/nnp-comp2/Cu2S_PBE/nnp-data-2/weights.029.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -1.8106107312134547E+00 a         1     0     1     1     1\n -1.7361647980817299E+00 a         2     0     1     1     2\n  1.5835335042260468E+00 a         3     0     1     1     3\n -2.9031977295015876E+00 a         4     0     1     1     4\n  5.8292159417945766E-01 a         5     0     1     1     5\n -6.7588490502437792E-01 a         6     0     1     1     6\n -2.4198710581938383E+00 a         7     0     1     1     7\n  4.2221160182839601E-01 a         8     0     1     1     8\n  1.5960552137102288E-01 a         9     0     1     1     9\n -3.1683388713249689E+00 a        10     0     1     1    10\n -2.9311362741703957E+00 a        11     0     1     1    11\n  4.7618136344419604E-01 a        12     0     1     1    12\n  1.8876715400104964E+00 a        13     0     1     1    13\n -1.7171211114446112E+00 a        14     0     1     1    14\n  1.0058834036740747E-02 a        15     0     1     1    15\n -2.0385505330353906E-01 a        16     0     2     1     1\n -8.5713219403928800E-02 a        17     0     2     1     2\n -3.0974766558871442E-01 a        18     0     2     1     3\n  1.4063985395399554E+00 a        19     0     2     1     4\n  1.1852207126490935E+00 a        20     0     2     1     5\n  1.5935125884324519E-01 a        21     0     2     1     6\n -1.1033116056940153E+00 a        22     0     2     1     7\n  1.3091818235224535E+00 a        23     0     2     1     8\n -6.3824991473749693E-01 a        24     0     2     1     9\n -5.1479501204983319E-02 a        25     0     2     1    10\n -1.5066931567749131E-01 a        26     0     2     1    11\n -1.2554535090324165E-01 a        27     0     2     1    12\n -5.7657349833683369E-01 a        28     0     2     1    13\n  2.1863073223861326E-01 a        29     0     2     1    14\n  1.5381523943286893E-01 a        30     0     2     1    15\n -1.0912675853953420E+00 a        31     0     3     1     1\n  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  },
  {
    "path": "examples/nnp-convert/Cu2S_PBE/input.data",
    "content": "begin\ncomment source_file_name=OUTCAR_4_1\nlattice 15.415349658 0.000000000 0.000000000\nlattice 0.000000000 12.016005204 0.000000000\nlattice -6.055885795 0.000000000 12.226281044\natom 9.66279 1.04561 10.73808 S 0.0 0.0 0.107416 0.024235 -0.891279\natom -3.16184 6.79866 8.04560 S 0.0 0.0 0.066538 0.139566 0.120509\natom -0.30404 11.04333 1.97659 S 0.0 0.0 -0.953672 -0.464533 -1.796811\natom 12.83426 5.06839 4.33902 S 0.0 0.0 0.393296 -0.326470 -0.518344\natom 12.39515 0.83117 4.16637 S 0.0 0.0 -0.063080 -0.611946 0.506821\natom -0.04295 7.13059 1.93130 S 0.0 0.0 -0.643788 -0.077636 0.315228\natom -3.25380 10.86483 8.16358 S 0.0 0.0 0.302005 0.898190 -0.193786\natom 9.41762 5.14521 10.58660 S 0.0 0.0 -0.644394 -0.340890 -0.050007\natom 9.00831 1.11279 6.18474 S 0.0 0.0 0.511148 0.550276 -0.454197\natom 3.34802 6.99932 0.09625 S 0.0 0.0 0.108918 0.284724 0.514152\natom 0.30069 11.03010 5.97943 S 0.0 0.0 0.216866 -0.247468 0.308978\natom 12.12524 5.04060 0.14613 S 0.0 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0.0 0.0 0.197651 -0.410017 -0.474082\natom 12.07390 8.62516 0.18008 S 0.0 0.0 0.955619 0.478197 -0.371759\natom 9.29009 9.21675 6.39687 S 0.0 0.0 -0.053343 -0.438911 -0.538072\natom -2.79943 3.30466 11.86546 S 0.0 0.0 0.397348 0.490476 0.572317\natom 0.22927 2.73487 1.72492 S 0.0 0.0 -0.311377 0.041312 -0.093182\natom 12.80848 9.20714 4.54446 S 0.0 0.0 -1.078226 -0.482916 -0.754490\natom 9.57560 8.83412 10.64965 S 0.0 0.0 -0.180223 0.207007 -0.965804\natom -3.02133 3.13287 7.77891 S 0.0 0.0 -0.431739 0.229304 -0.188167\natom 11.52491 2.71697 3.53948 Cu 0.0 0.0 -0.524195 0.593531 -0.018888\natom 0.94130 9.18527 2.48932 Cu 0.0 0.0 0.344344 -0.016827 -0.038025\natom -2.17737 8.90566 8.67171 Cu 0.0 0.0 -0.080113 -0.460384 -0.097485\natom 8.60937 2.99411 9.87382 Cu 0.0 0.0 0.242483 0.166370 -0.096114\natom 5.78704 0.81660 8.10398 Cu 0.0 0.0 -0.650869 0.037090 0.138420\natom 1.13645 6.89390 9.81986 Cu 0.0 0.0 -0.922068 -0.415802 0.004088\natom 3.98661 11.22749 4.05170 Cu 0.0 0.0 -0.169993 0.048173 -0.094445\natom 8.48776 5.35715 2.31898 Cu 0.0 0.0 -0.235778 -0.425782 -0.273045\natom 8.46457 1.29601 1.87017 Cu 0.0 0.0 -0.176692 0.115597 0.370769\natom 4.03103 6.96064 3.88549 Cu 0.0 0.0 0.138133 0.336666 0.141528\natom 0.94448 10.87127 10.21508 Cu 0.0 0.0 0.488695 0.336434 0.182050\natom 5.52896 4.74049 8.15135 Cu 0.0 0.0 -0.555966 -0.104080 -0.202623\natom 5.25495 2.85580 0.88760 Cu 0.0 0.0 -0.236780 0.111323 0.058556\natom 7.20832 9.00509 5.25253 Cu 0.0 0.0 -0.093050 -0.067663 0.112018\natom 4.02963 9.12378 11.29065 Cu 0.0 0.0 0.214455 -0.397161 -0.297440\natom 2.00869 2.95149 6.95641 Cu 0.0 0.0 0.242228 0.086186 0.256424\natom -3.59727 1.31298 11.56779 Cu 0.0 0.0 -0.234649 0.051811 -0.011230\natom 10.17489 7.11535 7.19747 Cu 0.0 0.0 -0.205621 -0.373986 -0.133792\natom 13.14051 10.69193 0.61472 Cu 0.0 0.0 -0.227511 0.015227 -0.013204\natom -0.15851 4.93004 5.03782 Cu 0.0 0.0 -0.407379 -0.188360 -0.079197\natom -1.03043 0.75778 5.49457 Cu 0.0 0.0 -0.614057 0.276670 -0.421905\natom 13.29870 6.86184 0.95026 Cu 0.0 0.0 0.173253 -0.290646 0.319586\natom 9.90736 11.28706 7.03112 Cu 0.0 0.0 0.528504 -0.034630 0.164799\natom -4.08827 5.25818 11.63154 Cu 0.0 0.0 0.507294 -0.050859 0.108014\natom 14.22568 1.81408 0.08656 Cu 0.0 0.0 0.571499 0.026055 -0.038863\natom -1.97034 7.15598 6.03887 Cu 0.0 0.0 -0.449980 0.314388 0.305998\natom -5.20546 10.47006 12.19513 Cu 0.0 0.0 0.395519 -0.013242 0.783300\natom 11.23565 4.47173 5.73470 Cu 0.0 0.0 -0.177903 -0.216022 0.218810\natom 11.50533 1.75385 6.16054 Cu 0.0 0.0 -0.082071 0.040075 -0.078104\natom 1.05145 7.68106 0.13325 Cu 0.0 0.0 0.678999 0.031254 -0.143904\natom -1.99506 10.44925 6.34486 Cu 0.0 0.0 0.240461 0.040601 0.140157\natom 14.46480 4.42495 0.30428 Cu 0.0 0.0 -0.397487 -0.006486 -0.227579\natom 9.50706 3.23697 7.16092 Cu 0.0 0.0 0.420873 -0.228470 -0.137433\natom 3.09422 9.25746 0.87162 Cu 0.0 0.0 0.083127 -0.013205 -0.008907\natom 0.08332 8.97416 7.15956 Cu 0.0 0.0 0.004363 -0.110554 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4.59107 9.25548 Cu 0.0 0.0 0.004397 0.377740 -0.175196\natom 0.44256 0.79397 7.51533 Cu 0.0 0.0 0.392843 -0.098361 0.143483\natom 5.25134 6.41678 10.66453 Cu 0.0 0.0 0.475273 -0.138365 -0.079004\natom 8.24962 11.81450 4.48984 Cu 0.0 0.0 0.215133 -0.064211 -0.350886\natom 4.18342 5.45581 1.75203 Cu 0.0 0.0 -0.080309 -0.016133 -0.219496\natom 4.01003 0.66675 1.73762 Cu 0.0 0.0 0.028881 -0.323578 0.033634\natom 8.34839 6.92699 4.24743 Cu 0.0 0.0 -0.310258 0.036970 0.397137\natom 5.48094 11.18523 10.58182 Cu 0.0 0.0 0.514304 0.188252 -0.630833\natom 1.07131 5.38871 7.37534 Cu 0.0 0.0 0.320279 0.188182 0.416405\natom 4.21301 2.62568 9.10014 Cu 0.0 0.0 -0.197230 -0.370539 -0.076098\natom 2.86651 8.26904 9.12445 Cu 0.0 0.0 0.813195 0.821609 -0.598471\natom 5.34637 9.52143 2.76224 Cu 0.0 0.0 0.183371 -0.205205 0.073164\natom 6.83808 3.46300 3.01720 Cu 0.0 0.0 0.096663 -0.107759 -0.264892\natom -1.22919 1.20692 2.84928 Cu 0.0 0.0 0.111910 0.175226 -0.288781\natom 12.57696 7.12242 3.51550 Cu 0.0 0.0 -0.080300 0.482168 0.355862\natom 9.16529 10.95579 10.07757 Cu 0.0 0.0 -0.015034 0.485749 -0.534452\natom 10.74902 4.75363 8.87895 Cu 0.0 0.0 0.538526 -0.144405 -0.516937\natom 4.19619 1.36541 11.49226 Cu 0.0 0.0 -0.380785 -0.030453 -0.004198\natom 2.45878 7.37775 6.65467 Cu 0.0 0.0 0.066074 -0.078546 0.088615\natom 5.31896 10.66606 0.43882 Cu 0.0 0.0 0.385710 -0.001102 -0.031416\natom 6.91402 4.80767 5.46184 Cu 0.0 0.0 0.125936 0.245444 -0.030834\natom 7.15034 2.69321 6.67590 Cu 0.0 0.0 -0.238705 -0.448773 0.259050\natom -0.81738 8.39491 11.50197 Cu 0.0 0.0 -0.436133 -0.344043 -0.296601\natom 2.10487 9.67028 5.38794 Cu 0.0 0.0 -0.077371 0.125704 -0.228517\natom 9.68527 3.42373 0.94518 Cu 0.0 0.0 0.175207 -0.068417 -0.088789\natom 2.62334 2.67217 1.88371 Cu 0.0 0.0 -0.048296 0.199486 -0.370291\natom 10.41720 8.36449 4.55256 Cu 0.0 0.0 0.315948 0.348300 0.091776\natom 7.21584 9.43029 10.57027 Cu 0.0 0.0 0.126790 -0.352963 0.043304\natom -0.52072 3.61443 7.80169 Cu 0.0 0.0 -0.368694 -0.497919 0.257311\natom -2.05660 1.09117 8.12167 Cu 0.0 0.0 -0.050113 -0.337128 0.262282\natom 8.62319 6.99659 9.55662 Cu 0.0 0.0 -0.012621 0.030326 0.525793\natom 11.01715 10.84050 3.79143 Cu 0.0 0.0 0.398331 -0.525816 0.304382\natom 0.75801 4.98978 2.17022 Cu 0.0 0.0 -0.010398 -0.002406 0.096091\nenergy -567.404752\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_124\nlattice 15.500587762 0.000000000 0.000000000\nlattice 0.000000000 12.082446869 0.000000000\nlattice -6.089371395 0.000000000 12.293885415\natom 9.50410 0.76802 10.45161 S 0.0 0.0 0.640875 0.266748 -0.858945\natom -3.15994 7.08941 7.80010 S 0.0 0.0 -0.365604 0.003541 0.417022\natom -0.48097 10.88463 1.58416 S 0.0 0.0 0.136805 0.509213 0.137938\natom 12.70994 4.97717 4.24055 S 0.0 0.0 0.201329 0.059868 0.266074\natom 12.64729 1.13865 4.14005 S 0.0 0.0 -0.875522 0.232730 0.574094\natom 0.25057 6.85877 1.67778 S 0.0 0.0 -0.662225 0.558296 -0.255495\natom -3.09982 11.31509 8.18143 S 0.0 0.0 -0.483827 -0.076863 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4.84685 S 0.0 0.0 0.046278 -0.535626 0.770606\natom 2.99879 11.05220 11.20888 S 0.0 0.0 1.276722 0.658678 0.859274\natom 3.14585 5.11138 7.20061 S 0.0 0.0 -0.092766 0.264892 -0.306700\natom -0.27624 0.74540 9.54612 S 0.0 0.0 0.323450 0.593758 0.302291\natom 6.57534 6.65908 8.84863 S 0.0 0.0 0.215819 0.970077 -0.006143\natom 9.75993 11.26999 2.88786 S 0.0 0.0 0.388648 -0.810920 -0.279678\natom 2.77744 4.99138 3.30057 S 0.0 0.0 0.701894 0.417218 0.448955\natom 2.70076 0.96030 3.46247 S 0.0 0.0 -0.454814 -0.539713 -0.699747\natom 9.94109 6.96658 2.80803 S 0.0 0.0 0.113005 0.192000 -0.211853\natom 6.71358 11.19431 8.83920 S 0.0 0.0 0.674425 -0.294603 0.293181\natom -0.67627 5.35741 9.47180 S 0.0 0.0 0.314933 -0.949434 0.248633\natom 6.27267 3.14164 9.01196 S 0.0 0.0 0.335462 -0.920261 -0.021531\natom -0.31676 9.15485 9.48235 S 0.0 0.0 0.617476 0.149300 0.399309\natom 2.82395 8.97047 3.80219 S 0.0 0.0 0.003876 -0.139610 -0.931010\natom 9.28327 2.94096 2.66345 S 0.0 0.0 0.500363 -0.064275 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9.14403 8.20163 Cu 0.0 0.0 -0.736542 -0.170504 -0.135000\natom 8.78257 2.91894 9.94865 Cu 0.0 0.0 0.074663 0.111987 -0.087260\natom 5.44081 0.91688 8.74315 Cu 0.0 0.0 -0.180289 0.645887 -0.366148\natom 0.77289 7.30984 9.98548 Cu 0.0 0.0 -0.277405 -0.881330 0.335080\natom 3.85512 10.95899 3.91346 Cu 0.0 0.0 0.260423 0.320780 -0.193056\natom 8.53235 5.11107 2.48624 Cu 0.0 0.0 -0.058014 -0.089280 -0.050176\natom 8.43690 0.63670 1.96905 Cu 0.0 0.0 0.099391 0.927992 0.179655\natom 3.99811 6.95598 3.90500 Cu 0.0 0.0 -0.352701 -0.011541 0.050527\natom 1.18262 10.61798 10.28166 Cu 0.0 0.0 -1.094495 -0.340401 -0.726245\natom 5.10052 4.88890 8.30125 Cu 0.0 0.0 0.018158 0.149382 -0.187026\natom 5.10993 2.61008 0.77614 Cu 0.0 0.0 -0.275247 0.260318 -0.417356\natom 7.25024 8.89725 5.25590 Cu 0.0 0.0 0.639651 0.022245 0.247963\natom 4.08558 8.88878 11.36107 Cu 0.0 0.0 0.524273 0.774990 0.801272\natom 2.21835 3.02757 6.84923 Cu 0.0 0.0 -0.169081 0.275750 0.105148\natom -3.87773 0.67325 11.41533 Cu 0.0 0.0 0.251774 0.280134 0.178852\natom 9.32650 7.13585 7.16763 Cu 0.0 0.0 0.548313 -0.054311 -0.557519\natom 12.78822 11.27114 0.55769 Cu 0.0 0.0 0.294325 -0.384911 -0.009479\natom -0.88291 4.97952 5.49548 Cu 0.0 0.0 0.564377 0.282694 -0.115547\natom -0.94004 0.86817 5.17878 Cu 0.0 0.0 0.531793 -0.105153 0.480341\natom 13.50445 7.21972 0.82994 Cu 0.0 0.0 0.202768 -0.216719 0.219452\natom 10.42550 11.49942 6.83806 Cu 0.0 0.0 0.645052 -0.311437 0.297678\natom -4.02735 4.98160 11.70489 Cu 0.0 0.0 -0.046036 -0.144755 -0.350289\natom 8.20421 1.34114 12.16595 Cu 0.0 0.0 -0.136416 0.398756 0.126365\natom -1.77903 7.86620 5.88147 Cu 0.0 0.0 0.105846 -0.233096 0.554421\natom 1.66504 10.96535 0.86414 Cu 0.0 0.0 -0.184789 0.089984 -0.093283\natom 11.43269 4.94510 6.15516 Cu 0.0 0.0 0.189353 -0.287190 0.179424\natom 11.54652 1.99240 6.03084 Cu 0.0 0.0 -0.256757 -0.069354 0.081431\natom 1.32088 8.42018 0.03724 Cu 0.0 0.0 0.539276 -0.848730 0.280594\natom -2.06691 10.78843 6.10765 Cu 0.0 0.0 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0.191471 0.144924\natom 7.53328 8.64255 7.81010 Cu 0.0 0.0 -0.410488 -0.373785 0.688861\natom 10.55700 9.25204 1.89577 Cu 0.0 0.0 0.008971 -0.108409 0.159629\natom 1.92211 3.05547 4.24761 Cu 0.0 0.0 0.075546 0.396327 -0.235163\natom 8.65383 0.55413 8.23760 Cu 0.0 0.0 0.005452 0.005784 0.424360\natom -2.55086 6.53265 10.09238 Cu 0.0 0.0 -0.262719 0.202456 -0.932792\natom 0.90508 11.74169 3.78313 Cu 0.0 0.0 -0.150431 -0.455428 0.140236\natom 11.78802 5.54212 2.32963 Cu 0.0 0.0 -0.124617 0.257916 -0.409950\natom 11.61932 0.94869 2.18215 Cu 0.0 0.0 -0.353023 -0.227486 -0.564353\natom 1.05562 6.53028 3.96023 Cu 0.0 0.0 0.168913 -0.084876 0.016187\natom -1.76094 11.00618 9.97517 Cu 0.0 0.0 0.098497 0.074319 0.555086\natom 7.69498 4.65712 7.98759 Cu 0.0 0.0 -0.445991 -0.271844 0.809157\natom -4.24716 2.00227 9.25078 Cu 0.0 0.0 -0.534140 -0.083126 0.310756\natom 10.82742 8.28566 8.92735 Cu 0.0 0.0 0.289489 -0.198715 -0.063571\natom 13.45709 9.48564 2.56436 Cu 0.0 0.0 -0.094304 -0.251934 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Cu 0.0 0.0 -0.576462 -0.180970 -0.049483\natom 7.32782 4.31071 5.82521 Cu 0.0 0.0 -0.522107 0.353251 -0.959985\natom 7.66354 2.73122 7.50603 Cu 0.0 0.0 -0.166669 0.192502 0.201686\natom -1.43250 8.41399 11.77217 Cu 0.0 0.0 0.347823 0.068297 -0.186494\natom 2.11419 9.49110 5.62346 Cu 0.0 0.0 -0.042565 0.158531 -0.223262\natom 11.03887 2.73447 1.15455 Cu 0.0 0.0 -0.117768 0.166711 0.190583\natom 2.43931 2.81590 1.89111 Cu 0.0 0.0 0.006521 0.227399 -0.415608\natom 10.21714 8.56313 4.34968 Cu 0.0 0.0 0.258534 0.100881 -0.558522\natom 7.09611 9.38395 10.57802 Cu 0.0 0.0 0.393663 0.075645 0.014443\natom -1.59050 4.06116 7.81026 Cu 0.0 0.0 0.776427 0.169641 0.044501\natom -2.15370 1.08495 8.85227 Cu 0.0 0.0 -0.251265 -0.119388 -0.127210\natom 8.67455 7.22254 10.03372 Cu 0.0 0.0 -0.079222 0.387976 -0.021438\natom 11.53372 11.21480 3.96977 Cu 0.0 0.0 -0.374950 -0.033082 -0.260344\natom 0.47515 5.15818 2.57476 Cu 0.0 0.0 0.420379 -0.030283 -0.128469\nenergy -564.447991\ncharge 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-0.454017\natom 10.13844 7.11491 6.40231 Cu 0.0 0.0 -0.569071 0.250542 0.601601\natom 12.72990 10.98411 0.96736 Cu 0.0 0.0 -0.176046 0.318766 -0.333106\natom -0.00737 5.09788 5.75926 Cu 0.0 0.0 -0.029219 -0.200811 -0.079748\natom -0.93295 1.16232 5.26955 Cu 0.0 0.0 -0.492524 -0.633635 -0.250378\natom 13.28385 7.15458 0.66812 Cu 0.0 0.0 -0.301181 0.074160 -0.102055\natom 10.40943 11.12950 6.96072 Cu 0.0 0.0 -0.117897 -0.028344 -0.116176\natom -4.00996 5.24507 11.33974 Cu 0.0 0.0 0.012991 0.023391 -0.094382\natom 13.31640 2.97016 0.83392 Cu 0.0 0.0 -0.423414 0.150964 -0.607954\natom 12.47100 6.88116 5.74444 Cu 0.0 0.0 0.557164 -0.303740 -0.871168\natom 1.06901 10.65973 0.19548 Cu 0.0 0.0 0.012070 -0.284940 -0.273374\natom 11.29234 4.27251 5.96161 Cu 0.0 0.0 0.086863 0.332260 -0.115234\natom 11.62120 1.62573 6.08354 Cu 0.0 0.0 -0.048666 0.292079 0.471397\natom -4.65422 7.87348 11.91059 Cu 0.0 0.0 -0.960416 0.488317 -0.211798\natom -1.63735 10.42263 6.09840 Cu 0.0 0.0 -1.113106 -0.544845 -0.000427\natom 15.05717 4.96662 0.22650 Cu 0.0 0.0 -0.379133 -0.304059 0.136958\natom 9.28967 2.88898 5.08692 Cu 0.0 0.0 0.117682 0.616494 -0.306475\natom 3.16447 9.17559 1.14169 Cu 0.0 0.0 0.030456 0.037399 -0.640928\natom 0.37739 8.70188 7.70190 Cu 0.0 0.0 -0.001689 -0.201921 -0.548107\natom 5.28792 3.60439 10.55368 Cu 0.0 0.0 0.457627 -0.225015 0.531135\natom 1.03295 1.75095 11.62696 Cu 0.0 0.0 -0.173491 0.095705 -0.022558\natom 4.60570 7.55834 6.86272 Cu 0.0 0.0 0.674104 0.042332 -0.067677\natom 8.25251 10.54132 0.76591 Cu 0.0 0.0 0.114499 -0.291107 0.149544\natom 4.46596 4.18082 5.48738 Cu 0.0 0.0 -0.557451 -0.253554 0.050618\natom 3.58863 1.51455 5.07176 Cu 0.0 0.0 0.718783 0.669856 0.870525\natom 8.40039 7.59253 0.80712 Cu 0.0 0.0 0.343056 -0.036320 -0.525589\natom 5.48965 10.34826 6.97892 Cu 0.0 0.0 0.024921 -0.042790 0.317892\natom 0.80000 4.87994 11.68969 Cu 0.0 0.0 0.246354 -0.347015 0.236503\natom -1.18845 2.71278 10.31996 Cu 0.0 0.0 -0.104547 0.273178 0.306075\natom 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3.84134 Cu 0.0 0.0 -0.210706 0.227822 -0.550197\natom 5.58912 1.00407 3.49382 Cu 0.0 0.0 0.373138 0.265093 0.159110\natom 6.57741 7.14653 2.56683 Cu 0.0 0.0 -0.417628 -0.291723 0.407608\natom 3.58870 10.89339 8.71247 Cu 0.0 0.0 -0.305316 0.000667 0.350551\natom 3.42368 4.98435 9.96699 Cu 0.0 0.0 -0.255185 1.082788 -0.716166\natom 1.28762 0.71788 7.99947 Cu 0.0 0.0 0.405352 -0.190991 -0.277226\natom 5.85996 6.34795 10.61468 Cu 0.0 0.0 -0.073768 -0.028163 -0.035427\natom 8.15201 11.55962 4.48578 Cu 0.0 0.0 -0.644758 -0.427102 -0.395821\natom 3.57494 4.73989 1.23786 Cu 0.0 0.0 -0.051561 0.396326 0.465236\natom 3.80726 0.43646 1.82202 Cu 0.0 0.0 -0.125559 0.146887 -0.029206\natom 8.40548 6.57428 4.21744 Cu 0.0 0.0 0.033844 0.295766 0.253862\natom 5.44343 11.21633 10.68925 Cu 0.0 0.0 0.092219 0.324847 -0.419697\natom 1.28907 5.09385 8.21174 Cu 0.0 0.0 0.381162 0.156476 0.140724\natom 3.34804 2.44109 9.26473 Cu 0.0 0.0 -0.277518 -0.018140 -0.412823\natom 2.59851 8.50015 8.96715 Cu 0.0 0.0 0.547576 0.164492 -0.235145\natom 5.46695 9.56576 3.01182 Cu 0.0 0.0 -0.207159 -0.026245 0.447183\natom 6.44944 3.62350 3.24347 Cu 0.0 0.0 -0.156367 -0.066807 -0.150968\natom -1.15831 0.90865 2.49817 Cu 0.0 0.0 -0.273470 0.402750 0.455927\natom -1.43657 6.76605 3.45714 Cu 0.0 0.0 0.143092 0.088504 -0.315961\natom 10.61313 11.13935 9.64448 Cu 0.0 0.0 0.247714 -0.513574 -0.422224\natom 10.71616 5.88205 8.81022 Cu 0.0 0.0 -0.529668 -0.693187 0.651642\natom 4.10225 1.57707 11.62967 Cu 0.0 0.0 -0.964105 -0.349743 -0.468824\natom 2.27900 6.88276 6.49927 Cu 0.0 0.0 -0.242226 0.105661 0.469384\natom 5.47666 10.56877 0.54818 Cu 0.0 0.0 -0.820864 1.388044 -0.266691\natom 6.83940 4.80600 5.57295 Cu 0.0 0.0 0.265387 -0.258445 0.065663\natom 8.00253 2.70036 7.01505 Cu 0.0 0.0 -0.779860 -0.197739 0.669692\natom -0.74210 8.04227 11.91283 Cu 0.0 0.0 -0.411558 -0.039897 -0.461576\natom 1.78696 9.71606 5.17893 Cu 0.0 0.0 0.180707 -0.015326 -0.140653\natom 10.82165 2.95042 1.22111 Cu 0.0 0.0 0.578328 0.526833 -0.807511\natom 2.16585 2.42165 1.58537 Cu 0.0 0.0 0.211844 0.052891 0.426346\natom 10.33151 8.33328 4.29213 Cu 0.0 0.0 0.170112 0.321127 -0.128360\natom 7.31421 9.55438 10.40212 Cu 0.0 0.0 -0.388305 0.078768 0.793821\natom -0.83764 3.95521 7.79240 Cu 0.0 0.0 -0.441797 -0.573566 0.419583\natom -2.06260 1.25249 8.16312 Cu 0.0 0.0 0.535082 -0.202285 -0.088209\natom 8.74820 7.00627 10.02256 Cu 0.0 0.0 -0.248813 0.245293 -0.031917\natom 11.56092 10.71251 3.58256 Cu 0.0 0.0 0.131702 -0.072963 0.190967\natom 1.00507 4.78711 2.44966 Cu 0.0 0.0 -0.447225 0.040965 -0.384033\nenergy -565.607832\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_21\nlattice 15.424131298 0.000000000 0.000000000\nlattice 0.000000000 12.022850344 0.000000000\nlattice -6.059335643 0.000000000 12.233245972\natom 9.69752 0.99718 10.31507 S 0.0 0.0 0.428489 0.864370 0.668883\natom -3.29298 7.22335 8.22515 S 0.0 0.0 -0.544722 -1.225831 -0.911920\natom -0.28490 11.25245 1.86478 S 0.0 0.0 0.547659 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0.0 0.0 0.674174 -0.336296 -0.251820\natom 6.52311 2.47794 9.01798 S 0.0 0.0 -0.368600 0.495413 -0.415155\natom -0.34032 9.26133 9.34661 S 0.0 0.0 -0.021809 0.035197 0.079901\natom 2.96215 9.03787 3.49597 S 0.0 0.0 -0.791542 -0.321400 0.131101\natom 9.48058 2.84442 2.74864 S 0.0 0.0 -0.176657 0.007876 0.530057\natom 5.84339 2.45195 5.07287 S 0.0 0.0 0.477930 -0.166367 -0.131116\natom 6.59664 8.63061 1.20540 S 0.0 0.0 0.320953 0.243389 -0.019120\natom 3.51010 9.26075 7.38912 S 0.0 0.0 -0.193849 -0.273587 -0.566212\natom 2.89753 3.25684 10.89907 S 0.0 0.0 -0.471085 -0.501682 0.516292\natom 0.26655 3.22616 5.72619 S 0.0 0.0 -0.387580 -0.984291 -0.479125\natom 12.48509 8.66812 0.25024 S 0.0 0.0 -1.460864 0.077459 1.676333\natom 9.02451 9.17407 6.18832 S 0.0 0.0 0.798591 0.041943 0.377210\natom -2.85996 3.18226 12.19742 S 0.0 0.0 0.090256 0.383348 -0.656936\natom -0.35694 3.07919 1.69350 S 0.0 0.0 0.369782 -0.178452 -0.008726\natom 12.86472 8.88547 4.67116 S 0.0 0.0 -0.808055 -0.392928 0.316984\natom 9.44482 9.35669 10.52433 S 0.0 0.0 0.123355 0.136570 -0.495146\natom -3.02449 3.30194 7.82746 S 0.0 0.0 0.212687 0.170418 -0.175442\natom 11.67543 3.17715 3.82097 Cu 0.0 0.0 -0.132108 -0.273595 0.073435\natom 0.84980 9.08603 2.52848 Cu 0.0 0.0 0.234813 0.480321 -0.150752\natom -2.61598 9.20958 8.16868 Cu 0.0 0.0 0.323066 1.558654 0.182828\natom 8.31095 3.30571 10.14593 Cu 0.0 0.0 0.065294 -0.220710 -0.531475\natom 5.36347 0.56375 8.47158 Cu 0.0 0.0 -0.273093 -0.159461 -0.117278\natom 1.04700 7.54401 9.94402 Cu 0.0 0.0 -1.381842 0.395253 -0.408891\natom 3.61068 11.09913 3.60760 Cu 0.0 0.0 0.280395 0.348068 0.571919\natom 8.32091 5.09934 1.98609 Cu 0.0 0.0 0.512465 0.379369 0.764857\natom 8.73278 0.81142 2.02043 Cu 0.0 0.0 -0.204404 -0.102945 0.142097\natom 3.97343 7.12833 4.11889 Cu 0.0 0.0 -0.098439 -0.034560 -0.227143\natom 0.94047 11.06189 10.14298 Cu 0.0 0.0 0.334059 0.026774 0.089888\natom 6.01770 4.52176 8.06381 Cu 0.0 0.0 -0.223240 -0.163693 0.263484\natom 5.48212 2.68766 1.02042 Cu 0.0 0.0 -0.538722 0.241714 -0.276965\natom 7.10132 8.75242 5.01571 Cu 0.0 0.0 -0.128632 0.028158 0.504093\natom 4.19171 9.03316 11.47110 Cu 0.0 0.0 0.353379 -0.080336 0.119637\natom 2.16518 3.12633 6.89857 Cu 0.0 0.0 0.244781 0.219714 0.162134\natom -3.75606 0.63179 11.51750 Cu 0.0 0.0 0.048407 0.763425 -0.517493\natom 9.58941 6.87478 6.71054 Cu 0.0 0.0 0.219831 0.234185 -0.445892\natom 13.06049 11.03756 1.02745 Cu 0.0 0.0 -0.079314 -0.677939 0.286754\natom -0.78852 5.13166 5.22801 Cu 0.0 0.0 0.352833 0.379884 0.287873\natom -1.15115 1.30344 5.50785 Cu 0.0 0.0 0.380819 0.210585 -0.356781\natom 13.32304 6.68263 0.99937 Cu 0.0 0.0 0.392733 0.172661 -0.326537\natom 10.38163 11.11523 6.56486 Cu 0.0 0.0 -0.415950 -0.661426 -0.007447\natom -3.99277 5.13629 11.52678 Cu 0.0 0.0 0.080316 -0.215417 -0.053770\natom 8.38323 1.75060 12.14468 Cu 0.0 0.0 0.043482 -0.321417 -0.081744\natom 12.45114 6.85202 5.91286 Cu 0.0 0.0 -0.063381 0.145723 0.345637\natom 1.13538 10.68873 0.06046 Cu 0.0 0.0 -0.639656 -0.502632 0.278945\natom 11.25623 4.59140 6.17465 Cu 0.0 0.0 -0.167411 -0.323254 -0.088040\natom 10.74056 2.00309 7.23737 Cu 0.0 0.0 0.280785 0.289572 -0.082256\natom -5.03746 8.11584 12.01208 Cu 0.0 0.0 0.382434 -0.449550 0.445620\natom -1.94857 10.87638 5.61594 Cu 0.0 0.0 -0.285999 -0.126621 0.554910\natom 14.45612 4.56956 0.00791 Cu 0.0 0.0 -0.114656 -0.112373 0.378247\natom 9.32861 2.94473 5.03697 Cu 0.0 0.0 0.104405 -0.208697 0.101586\natom 3.08177 8.78775 1.26265 Cu 0.0 0.0 0.100098 -0.033736 -0.066842\natom 1.26045 9.79223 7.72958 Cu 0.0 0.0 -0.106339 -0.101528 0.011347\natom 6.12331 2.90073 11.91474 Cu 0.0 0.0 0.156307 -1.352597 -0.162173\natom 1.12871 1.68462 11.50637 Cu 0.0 0.0 0.069475 0.126589 -0.086201\natom 5.05905 7.48840 7.06112 Cu 0.0 0.0 0.463196 -0.016689 0.081990\natom 8.40755 10.03140 0.85379 Cu 0.0 0.0 -0.103302 0.414453 0.198273\natom 4.19600 4.03461 5.11551 Cu 0.0 0.0 -0.219619 0.038422 -0.014174\natom 3.56644 1.49862 5.41080 Cu 0.0 0.0 0.234035 -0.036657 -0.454735\natom 8.72902 7.59530 0.74147 Cu 0.0 0.0 0.123026 -0.281970 0.957122\natom 5.56866 10.32012 7.03680 Cu 0.0 0.0 0.169582 -0.128866 0.703760\natom 1.48670 4.95793 11.90663 Cu 0.0 0.0 0.052588 -0.328052 -0.652362\natom -1.74031 2.21696 10.63434 Cu 0.0 0.0 0.151283 -0.204439 0.260796\natom 7.65387 8.31434 7.74379 Cu 0.0 0.0 -0.795498 0.110111 -0.042840\natom 10.83395 9.56114 1.67275 Cu 0.0 0.0 0.314023 -0.435341 -0.464040\natom 1.94549 3.21212 4.06976 Cu 0.0 0.0 -0.293057 0.242289 0.654646\natom 8.55219 0.18003 8.55453 Cu 0.0 0.0 0.040797 0.046556 -0.286245\natom -1.72254 6.44827 9.67915 Cu 0.0 0.0 -0.764494 0.441190 0.642362\natom 0.65615 11.92408 3.78245 Cu 0.0 0.0 0.233332 -0.113658 0.379664\natom 11.60765 5.39051 2.18275 Cu 0.0 0.0 -0.368245 -0.232081 -0.002309\natom 11.32107 0.65347 2.15549 Cu 0.0 0.0 0.235145 0.234520 -0.420560\natom 1.45518 5.95060 4.27110 Cu 0.0 0.0 -0.460392 0.513157 0.585860\natom -1.51766 11.16689 10.24190 Cu 0.0 0.0 -0.338060 0.202179 0.235401\natom 8.44816 5.07613 8.25802 Cu 0.0 0.0 0.056234 0.186547 0.382363\natom -4.22248 2.80056 9.82683 Cu 0.0 0.0 -0.124053 -1.046375 0.339479\natom 10.21695 8.52238 8.32123 Cu 0.0 0.0 0.246815 0.593058 0.572485\natom -1.45089 10.01232 3.25558 Cu 0.0 0.0 0.558700 0.024738 -0.512596\natom -1.30663 4.94609 2.67861 Cu 0.0 0.0 0.116202 -0.059950 -0.298398\natom 6.50197 0.51792 3.68434 Cu 0.0 0.0 -0.449054 0.490378 -0.230439\natom 6.30679 6.74451 2.60751 Cu 0.0 0.0 -0.143249 0.431872 0.162513\natom 3.27261 11.05442 8.79737 Cu 0.0 0.0 0.088914 0.202669 0.055355\natom 2.20232 5.17800 8.76920 Cu 0.0 0.0 -0.544103 0.011140 0.083524\natom 1.06039 0.41653 7.85303 Cu 0.0 0.0 0.133753 0.002416 -0.235867\natom 5.08769 6.88505 10.68469 Cu 0.0 0.0 -0.338914 -0.377961 0.587730\natom 8.27064 11.32272 4.83664 Cu 0.0 0.0 -0.013078 -0.297463 0.174367\natom 3.72235 6.00358 1.37287 Cu 0.0 0.0 0.246339 -0.293514 0.294988\natom 3.88533 0.37916 1.53747 Cu 0.0 0.0 0.066676 0.846589 0.222740\natom 8.26314 6.44043 4.33352 Cu 0.0 0.0 -0.055601 -0.620551 -0.163899\natom 5.25481 11.15345 10.56730 Cu 0.0 0.0 0.515022 0.073468 -0.549762\natom -0.10732 6.32892 7.90190 Cu 0.0 0.0 0.614815 0.374366 -0.689606\natom 4.03424 3.10700 8.96040 Cu 0.0 0.0 -0.070604 -0.245349 -0.141646\natom 3.24539 7.80876 8.98313 Cu 0.0 0.0 0.381602 -0.071906 0.184768\natom 5.88289 9.54405 3.04948 Cu 0.0 0.0 -0.307999 0.117592 -0.086001\natom 6.97649 3.12229 3.11330 Cu 0.0 0.0 0.081078 -0.049690 0.171484\natom 14.00685 1.30478 2.63737 Cu 0.0 0.0 -0.376572 -0.171602 0.375310\natom -0.73886 7.58435 3.84135 Cu 0.0 0.0 -0.079898 -0.142675 0.156969\natom -4.67615 10.97554 9.48726 Cu 0.0 0.0 0.180010 -0.143702 -0.281537\natom -4.05310 4.92678 8.85705 Cu 0.0 0.0 -0.465214 1.265766 0.192168\natom 3.65138 1.23209 11.73213 Cu 0.0 0.0 0.320207 -0.216919 -0.016849\natom 2.72416 6.84443 6.42931 Cu 0.0 0.0 -0.201811 -0.129502 0.404569\natom 5.65014 10.79163 0.52835 Cu 0.0 0.0 0.378108 -0.367916 0.074316\natom 6.68295 4.57131 5.27043 Cu 0.0 0.0 0.067931 -0.211691 0.118409\natom 7.12518 1.59470 6.97899 Cu 0.0 0.0 -0.046693 0.579110 -0.224163\natom -0.76211 8.33615 11.69957 Cu 0.0 0.0 -0.405789 0.076152 -0.621886\natom 0.98180 9.55503 5.02535 Cu 0.0 0.0 0.138730 -0.266626 -0.009083\natom 9.89123 3.50855 0.72891 Cu 0.0 0.0 0.239491 0.252843 -0.563085\natom 2.21321 2.47103 1.72695 Cu 0.0 0.0 -0.469181 0.046264 -0.566015\natom 9.67661 8.29993 4.24294 Cu 0.0 0.0 0.595732 0.872025 0.381690\natom 6.94673 9.28986 10.58324 Cu 0.0 0.0 0.305991 0.325527 -0.682343\natom -0.40525 3.93547 7.66333 Cu 0.0 0.0 0.015551 -0.333179 0.575055\natom -2.10338 1.24926 8.35676 Cu 0.0 0.0 -0.181614 -0.182304 -0.025722\natom 8.42906 7.42512 9.83040 Cu 0.0 0.0 0.319895 -0.661271 0.340294\natom 11.56322 10.71821 3.71966 Cu 0.0 0.0 0.863463 -0.094005 0.789171\natom 1.09542 4.85435 1.98275 Cu 0.0 0.0 0.117948 0.321282 -0.199674\nenergy -564.943315\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_227\nlattice 15.402975099 0.000000000 0.000000000\nlattice 0.000000000 12.006359444 0.000000000\nlattice -6.051024477 0.000000000 12.216466487\natom 9.40189 1.10075 10.15653 S 0.0 0.0 -0.525866 -0.003471 -0.421346\natom -3.14508 6.84314 8.11453 S 0.0 0.0 -0.215216 0.498400 -0.053561\natom -0.51949 11.30985 2.11255 S 0.0 0.0 0.599989 0.550979 0.348948\natom 12.48436 4.91707 4.34653 S 0.0 0.0 0.743172 0.016851 -0.209299\natom 12.77645 1.00834 4.51412 S 0.0 0.0 -0.782197 -0.886427 -0.981209\natom -0.09487 7.04217 1.77025 S 0.0 0.0 0.055644 0.156629 -1.339379\natom -3.18111 11.30403 7.98047 S 0.0 0.0 1.070194 -0.209974 -1.180582\natom 9.38333 5.20226 10.19643 S 0.0 0.0 0.175139 -0.061473 0.340499\natom 9.18560 0.91443 6.13888 S 0.0 0.0 0.015399 -0.034332 0.568838\natom -2.69683 6.91604 12.16468 S 0.0 0.0 -0.514586 0.261907 -0.241018\natom 0.35180 10.87095 6.29739 S 0.0 0.0 -0.173435 -0.755570 0.675041\natom 12.28098 5.16959 0.15300 S 0.0 0.0 -0.206539 -0.454554 0.467149\natom 12.14645 0.97681 0.09187 S 0.0 0.0 0.326579 0.831980 -0.435559\natom 0.16611 7.23928 5.61443 S 0.0 0.0 -0.177721 0.253180 -0.222942\natom 2.90485 11.28634 0.18003 S 0.0 0.0 -0.346132 -0.688304 -0.285618\natom 9.02936 5.00820 5.98508 S 0.0 0.0 0.399117 0.234230 0.131286\natom 3.41035 0.96622 7.67801 S 0.0 0.0 -0.321964 0.391678 -0.362249\natom 2.92394 6.91704 11.00767 S 0.0 0.0 0.398261 0.396974 0.412408\natom 6.28243 10.99437 4.71230 S 0.0 0.0 0.111084 -0.476227 -0.058713\natom 6.63707 4.92124 0.97856 S 0.0 0.0 -0.859659 0.302063 0.102513\natom 6.27765 0.75931 1.22414 S 0.0 0.0 -1.137267 0.175844 -0.708171\natom 5.80057 6.81080 4.88059 S 0.0 0.0 1.502987 -0.356771 0.320135\natom 2.95020 11.34282 10.97187 S 0.0 0.0 0.275555 -0.091305 -0.041164\natom 3.18115 5.06453 7.32510 S 0.0 0.0 0.289075 0.263638 -0.160045\natom -0.07142 0.82282 9.74045 S 0.0 0.0 -0.743755 -0.400067 -0.916145\natom 6.46899 6.86245 8.85560 S 0.0 0.0 -0.241183 0.738756 -0.432005\natom 9.69052 11.18738 2.56183 S 0.0 0.0 -0.446160 -0.627574 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0.45622 S 0.0 0.0 -0.912320 -1.003811 0.311702\natom 9.45930 8.98345 6.21662 S 0.0 0.0 -0.796992 -0.575739 0.295445\natom -2.84615 2.84786 11.96526 S 0.0 0.0 -0.799751 0.518563 0.644071\natom 0.04275 2.96022 1.49476 S 0.0 0.0 -0.785260 -0.140283 0.333171\natom 12.64196 8.61780 4.62439 S 0.0 0.0 0.159040 0.192586 1.768480\natom 9.40685 9.41478 10.64060 S 0.0 0.0 1.269105 -0.289032 -0.548124\natom -3.08889 3.27384 7.69809 S 0.0 0.0 0.430441 0.187464 0.246703\natom 11.52624 2.66955 3.63386 Cu 0.0 0.0 0.178007 0.323487 0.306316\natom 0.77625 8.96645 2.49884 Cu 0.0 0.0 -0.117896 0.201380 0.245443\natom -2.57539 9.15917 8.37379 Cu 0.0 0.0 0.729022 -0.423189 0.392675\natom 8.39756 3.13624 9.44373 Cu 0.0 0.0 0.073393 0.220707 0.312663\natom 5.61793 0.66567 8.43490 Cu 0.0 0.0 -0.249905 0.157531 -0.027465\natom 1.22492 7.00630 9.40630 Cu 0.0 0.0 -0.324409 -0.009963 0.173526\natom 4.11427 11.10460 4.04082 Cu 0.0 0.0 -0.191831 -0.238881 -0.152240\natom 8.50870 5.10563 2.16419 Cu 0.0 0.0 0.390286 0.166547 0.114091\natom 8.15390 0.99127 2.14780 Cu 0.0 0.0 0.958431 0.061715 0.550308\natom 3.91171 7.05858 3.94693 Cu 0.0 0.0 -0.593287 0.563440 -0.613666\natom 0.84233 10.68690 10.18157 Cu 0.0 0.0 -0.773124 -0.301789 -0.002082\natom 5.26278 5.03082 8.28175 Cu 0.0 0.0 -0.024658 -0.048603 -0.221183\natom 5.33385 2.97441 0.32510 Cu 0.0 0.0 -0.155059 -0.606661 0.350608\natom 7.13637 8.74433 5.23109 Cu 0.0 0.0 0.107513 -0.007236 -0.941867\natom 3.93104 9.28260 11.30744 Cu 0.0 0.0 -0.054279 -0.082426 0.425705\natom 2.29236 3.05478 6.94063 Cu 0.0 0.0 -0.355398 -0.670930 0.250804\natom -3.96522 1.12788 11.00629 Cu 0.0 0.0 0.143495 -0.065307 0.184808\natom 10.09341 6.98320 7.41685 Cu 0.0 0.0 0.067943 0.412064 -0.481542\natom 12.67090 11.08148 1.08576 Cu 0.0 0.0 0.318328 -0.218203 0.548704\natom -0.89798 4.49077 5.28438 Cu 0.0 0.0 0.084834 0.085855 -0.071555\natom -0.90652 0.60283 5.76942 Cu 0.0 0.0 0.174943 0.118883 0.025746\natom 13.18747 7.17871 0.89452 Cu 0.0 0.0 0.030141 0.238899 -0.092813\natom 10.57360 10.89400 6.63928 Cu 0.0 0.0 -0.666176 0.126670 -0.403751\natom -3.95147 4.98063 11.59260 Cu 0.0 0.0 -0.031975 -0.105223 -0.277240\natom 8.19846 1.98544 11.98002 Cu 0.0 0.0 -0.055328 -0.064033 -0.195278\natom -2.23740 6.53498 6.04648 Cu 0.0 0.0 -0.161913 0.244207 -0.325942\natom 0.42210 10.35118 0.43048 Cu 0.0 0.0 0.227701 -0.059048 -0.475039\natom 11.15981 4.20774 5.95940 Cu 0.0 0.0 -0.326276 -0.094082 0.165285\natom 11.82935 1.46090 6.44280 Cu 0.0 0.0 -0.844942 0.020513 -0.229682\natom -4.97219 7.64322 12.04309 Cu 0.0 0.0 0.248125 0.167426 0.209344\natom -2.03497 10.23831 6.19369 Cu 0.0 0.0 0.231600 0.082310 -0.437070\natom 14.54501 4.55982 0.08900 Cu 0.0 0.0 0.045033 -0.066800 -0.278679\natom 9.25296 2.79613 4.83886 Cu 0.0 0.0 -0.223198 0.072561 0.727911\natom 4.05989 8.47657 1.70449 Cu 0.0 0.0 0.586266 -0.295570 -0.819765\natom 0.17063 8.52876 7.49350 Cu 0.0 0.0 -0.141486 0.735078 -0.039861\natom 6.19544 3.83779 10.57627 Cu 0.0 0.0 0.024396 -0.188444 0.080560\natom 1.53664 1.72721 10.84714 Cu 0.0 0.0 0.078035 0.319768 0.369381\natom 5.22050 7.88927 6.76847 Cu 0.0 0.0 0.157444 -0.671022 0.412933\natom 7.93323 10.54466 0.49770 Cu 0.0 0.0 -0.244667 -0.368220 0.493466\natom 3.97707 4.00516 5.37104 Cu 0.0 0.0 0.487677 0.064783 -0.114850\natom 4.14569 1.27047 5.44463 Cu 0.0 0.0 -0.229985 0.329857 0.509785\natom 8.60070 7.74534 1.20477 Cu 0.0 0.0 -0.222494 0.078646 -0.059131\natom 5.46247 10.32666 6.77296 Cu 0.0 0.0 0.389763 0.678031 -0.028391\natom 0.77818 4.14352 11.07585 Cu 0.0 0.0 0.710249 0.091945 0.042840\natom -2.03971 3.57901 10.07552 Cu 0.0 0.0 0.056195 0.174251 -0.306246\natom 7.52477 8.84811 7.52561 Cu 0.0 0.0 0.373785 0.022630 1.049059\natom 11.79066 8.56243 2.69914 Cu 0.0 0.0 -0.657496 -0.036112 -1.212240\natom 1.59296 3.78609 4.53421 Cu 0.0 0.0 -0.286303 -0.685100 0.139181\natom 8.25121 0.15969 8.21043 Cu 0.0 0.0 0.160832 0.013432 0.192410\natom -1.93085 6.46651 10.05052 Cu 0.0 0.0 -0.138020 0.117795 0.259108\natom 0.97360 11.41610 4.28596 Cu 0.0 0.0 -0.014056 0.185524 -0.862979\natom 11.52553 5.30790 2.37743 Cu 0.0 0.0 0.256471 -0.144463 -0.603064\natom 10.80790 1.09153 1.89892 Cu 0.0 0.0 -0.019321 -0.076711 -0.383196\natom 1.68183 6.23307 4.42374 Cu 0.0 0.0 -0.243586 -0.011855 -0.120223\natom -1.87128 11.76502 10.68888 Cu 0.0 0.0 0.640043 0.083334 -0.446739\natom 8.13397 5.56651 7.93130 Cu 0.0 0.0 -0.423619 -0.428718 0.100977\natom 10.70794 2.25357 8.76261 Cu 0.0 0.0 -0.106956 -0.013716 0.335948\natom -4.41206 8.17752 9.67390 Cu 0.0 0.0 0.276208 -0.387555 -0.430613\natom 13.70504 10.01305 3.31585 Cu 0.0 0.0 0.414771 -0.249604 0.255288\natom 13.73304 3.64037 2.85404 Cu 0.0 0.0 0.522658 0.415626 0.040275\natom 5.76760 1.00746 3.47078 Cu 0.0 0.0 0.333859 0.012078 -0.235374\natom 6.42130 7.39571 2.73410 Cu 0.0 0.0 -0.101190 -0.329321 0.487881\natom 2.99229 10.70748 8.85769 Cu 0.0 0.0 0.419757 -0.095925 -0.435644\natom 2.73717 4.95425 9.59201 Cu 0.0 0.0 0.270206 0.564614 -0.638823\natom 1.04479 0.70311 7.56489 Cu 0.0 0.0 0.014249 -0.174170 0.522684\natom 5.18317 6.36625 10.81283 Cu 0.0 0.0 -0.214810 0.260237 -0.537882\natom 8.69784 11.48037 4.50091 Cu 0.0 0.0 -0.193064 0.047017 0.095723\natom 4.58416 5.89450 1.63141 Cu 0.0 0.0 0.216909 -0.279348 -0.126868\natom 3.94569 0.45096 1.80470 Cu 0.0 0.0 -0.175552 0.322117 0.465767\natom 8.59222 6.62006 4.36053 Cu 0.0 0.0 -0.611487 -0.169427 0.672643\natom 5.64553 11.26185 10.87209 Cu 0.0 0.0 -0.033775 -0.032469 -0.404609\natom -0.13634 6.06048 7.39439 Cu 0.0 0.0 0.064881 -0.903679 0.515902\natom 4.10068 2.75920 9.20853 Cu 0.0 0.0 0.036713 -0.301824 -0.543378\natom 3.48420 8.04223 9.23234 Cu 0.0 0.0 0.009075 0.452588 -0.974432\natom 7.14713 9.74242 2.84920 Cu 0.0 0.0 -0.155895 0.318316 -0.030286\natom 6.28278 3.48344 2.53849 Cu 0.0 0.0 0.043173 -0.336382 1.182775\natom 13.43777 1.25970 2.26051 Cu 0.0 0.0 0.139460 -0.110830 0.013725\natom -1.24232 7.32609 3.51738 Cu 0.0 0.0 -0.581870 0.403351 0.776642\natom -4.16418 10.72484 9.71795 Cu 0.0 0.0 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6.30428 Cu 0.0 0.0 -0.322831 0.139102 0.206135\natom 8.02163 10.08801 12.23225 Cu 0.0 0.0 -0.222858 0.131274 0.256342\natom -0.56212 5.14775 5.32292 Cu 0.0 0.0 -0.076425 -0.606583 0.030943\natom -0.80989 0.93651 5.32614 Cu 0.0 0.0 -0.238610 0.307378 0.097839\natom 13.22050 6.98149 0.64487 Cu 0.0 0.0 0.169634 -0.132976 -0.014427\natom 10.68960 10.99004 6.55602 Cu 0.0 0.0 -0.031273 -0.115594 0.335940\natom -3.98489 5.49480 11.84622 Cu 0.0 0.0 -0.086968 -0.378460 -0.357526\natom 8.50023 0.72367 12.08366 Cu 0.0 0.0 -0.557422 0.104888 0.767138\natom -2.28814 7.03102 6.10286 Cu 0.0 0.0 0.247534 0.091236 -0.365017\natom 1.18362 10.23521 0.06025 Cu 0.0 0.0 -0.211480 0.405759 0.032660\natom 12.41333 4.38140 6.00365 Cu 0.0 0.0 -0.256548 -0.029173 0.576026\natom 11.51756 1.83507 6.64050 Cu 0.0 0.0 -0.221897 -0.172319 -0.401036\natom -4.27596 7.93845 11.17010 Cu 0.0 0.0 -0.066611 0.205050 0.002508\natom -2.00185 10.57175 5.51422 Cu 0.0 0.0 0.265903 -0.184834 0.472879\natom 14.56384 4.46179 0.08498 Cu 0.0 0.0 -0.076981 -0.184061 0.460070\natom 9.29155 2.94824 6.05561 Cu 0.0 0.0 0.356971 -0.083707 -0.140828\natom 2.79320 8.86419 1.18304 Cu 0.0 0.0 0.402123 0.043113 0.408780\natom 0.71620 9.62470 7.49043 Cu 0.0 0.0 -0.026539 -0.009460 -0.138752\natom 6.67586 3.02149 11.33699 Cu 0.0 0.0 -0.187888 -0.450268 -0.364371\natom 1.35323 2.05907 12.05236 Cu 0.0 0.0 -0.289119 -0.302741 -0.339240\natom 4.97791 7.50315 6.52953 Cu 0.0 0.0 0.236291 -0.531066 -0.158393\natom 8.66633 10.67540 0.88180 Cu 0.0 0.0 -0.009262 -0.265512 0.181465\natom 3.88832 4.68600 5.21390 Cu 0.0 0.0 0.190584 -0.315626 0.305439\natom 3.59371 1.95851 5.58261 Cu 0.0 0.0 0.415568 -0.230631 -1.048671\natom 8.69567 7.62597 0.52674 Cu 0.0 0.0 -0.222160 -0.053461 0.049758\natom 5.55294 9.85689 6.89807 Cu 0.0 0.0 0.412270 0.909727 0.119868\natom 0.54967 4.55307 11.71433 Cu 0.0 0.0 0.104313 0.066133 -0.114549\natom -1.42787 2.58175 10.69710 Cu 0.0 0.0 0.124508 -0.017162 0.078447\natom 7.63841 8.49022 7.73689 Cu 0.0 0.0 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10.55069 S 0.0 0.0 0.073929 -0.154241 0.018321\natom -3.38107 2.91741 7.55176 S 0.0 0.0 0.715325 0.928195 -0.216603\natom 11.71801 2.98914 3.89390 Cu 0.0 0.0 -0.467988 -0.665921 -0.676485\natom 0.99904 9.01667 2.40789 Cu 0.0 0.0 -0.279413 0.098695 0.211728\natom -2.45788 8.89150 8.68152 Cu 0.0 0.0 0.460491 0.312367 0.059293\natom 8.65654 3.07551 9.75934 Cu 0.0 0.0 -0.419582 -0.382171 0.055251\natom 5.56828 0.93060 7.75629 Cu 0.0 0.0 -0.487518 -0.636133 0.688723\natom 0.75015 7.02990 10.06052 Cu 0.0 0.0 0.496763 -0.785950 0.118159\natom 3.90282 11.00621 3.48431 Cu 0.0 0.0 -0.488871 0.504442 0.314079\natom 8.29519 5.46566 1.61428 Cu 0.0 0.0 0.357376 -0.010017 0.440791\natom 9.15076 1.34525 2.56253 Cu 0.0 0.0 -0.093506 -0.615875 0.049226\natom 4.17865 6.69824 3.69420 Cu 0.0 0.0 -0.163601 0.398007 0.556611\natom 1.01648 10.72034 10.10046 Cu 0.0 0.0 -0.078193 -0.522280 0.140449\natom 5.62156 4.68027 8.04338 Cu 0.0 0.0 -0.708620 0.555179 -0.066652\natom 5.19654 2.96726 0.75982 Cu 0.0 0.0 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0.141225\natom 8.48774 9.23201 2.05606 Cu 0.0 0.0 0.470603 0.254027 0.207617\natom 5.39323 10.31506 7.02597 Cu 0.0 0.0 0.128387 0.525209 0.325742\natom 1.27201 4.13500 11.12724 Cu 0.0 0.0 0.100106 0.027229 0.148301\natom -1.08356 2.34871 10.36440 Cu 0.0 0.0 -0.115961 0.201545 -0.039684\natom 7.41684 9.00449 7.99731 Cu 0.0 0.0 -0.346857 -0.262197 0.497363\natom 11.91265 8.39927 2.42959 Cu 0.0 0.0 -0.131640 -0.321162 0.508974\natom 1.18746 1.93982 4.73443 Cu 0.0 0.0 0.316395 0.106054 -0.281281\natom 8.46428 0.58439 8.38410 Cu 0.0 0.0 -0.201599 -0.093222 -0.211731\natom -2.28228 6.03105 9.60677 Cu 0.0 0.0 -0.147047 0.154758 0.109189\natom 1.21645 11.58938 3.94392 Cu 0.0 0.0 0.036200 -0.091983 -0.032970\natom 11.10207 5.65120 2.47741 Cu 0.0 0.0 0.624661 -0.133601 -0.503282\natom 11.98936 0.59789 2.16769 Cu 0.0 0.0 -0.295112 0.256572 0.643703\natom 1.00043 6.73888 4.04158 Cu 0.0 0.0 0.529960 -0.354381 -0.658114\natom -2.12839 11.43922 9.97281 Cu 0.0 0.0 0.000413 -0.492403 0.310696\natom 8.12816 5.13331 8.11130 Cu 0.0 0.0 -0.210146 -0.302608 0.172841\natom 10.78163 1.78273 8.80755 Cu 0.0 0.0 -1.043324 -0.559393 0.927563\natom 10.41516 8.39121 8.64204 Cu 0.0 0.0 -0.395131 0.185406 0.035433\natom -1.53040 9.72295 3.36888 Cu 0.0 0.0 0.372856 0.130296 -0.400832\natom -1.41696 3.69703 3.19491 Cu 0.0 0.0 0.883350 -0.223926 -0.494067\natom 6.86443 1.73542 3.49266 Cu 0.0 0.0 0.244556 -0.303366 0.007376\natom 6.17918 6.97435 2.30802 Cu 0.0 0.0 0.209760 0.297266 -0.013530\natom 3.15940 10.95802 8.61593 Cu 0.0 0.0 0.193136 0.470719 0.148909\natom 2.88208 5.70957 9.23450 Cu 0.0 0.0 0.345822 -0.702524 -1.280960\natom 1.02004 12.01249 7.53204 Cu 0.0 0.0 -0.087097 0.438165 0.233971\natom 5.64859 6.84766 10.85928 Cu 0.0 0.0 -0.078639 0.031924 0.721273\natom 8.29656 11.31184 4.35364 Cu 0.0 0.0 -0.069122 0.018563 -0.176049\natom 3.67725 5.60939 1.57633 Cu 0.0 0.0 0.669505 0.757452 -1.443874\natom 4.00798 0.58669 1.47240 Cu 0.0 0.0 0.031678 0.170501 -0.276929\natom 8.25979 6.53135 4.39946 Cu 0.0 0.0 0.121604 -0.341586 -0.191260\natom 5.39557 11.25483 10.68752 Cu 0.0 0.0 -0.291604 -0.204365 -0.334073\natom 0.69703 5.65959 7.86760 Cu 0.0 0.0 -0.169854 -0.013095 -0.561101\natom 3.58008 2.31552 9.18250 Cu 0.0 0.0 0.116022 -0.224291 -0.555338\natom 3.05372 8.56933 9.43560 Cu 0.0 0.0 -0.411349 -0.314710 -0.570380\natom 5.68123 9.41030 3.31150 Cu 0.0 0.0 0.618118 -0.382904 -0.575557\natom 5.80858 4.17257 3.20862 Cu 0.0 0.0 0.124705 0.093073 -0.161157\natom -0.92440 1.11899 2.92312 Cu 0.0 0.0 0.062937 0.078153 0.035106\natom -1.44711 7.09351 3.54192 Cu 0.0 0.0 -0.344783 0.146651 -0.067587\natom 10.58942 10.83708 9.44404 Cu 0.0 0.0 0.459607 0.762299 -0.252833\natom 10.98782 4.51094 8.77469 Cu 0.0 0.0 -0.161489 0.006589 0.115299\natom 10.51264 2.34015 0.87372 Cu 0.0 0.0 0.354363 -0.027526 -0.319758\natom 2.56194 7.08435 6.78565 Cu 0.0 0.0 -0.177923 -0.212799 0.073616\natom 6.01815 11.05039 1.09580 Cu 0.0 0.0 -0.430044 1.160378 0.444636\natom 6.69093 4.86762 5.60643 Cu 0.0 0.0 -0.056310 -0.085972 0.047007\natom 7.13023 2.57847 6.91158 Cu 0.0 0.0 0.637455 0.182186 -0.414937\natom -1.18043 9.53299 11.44896 Cu 0.0 0.0 0.153076 -0.123030 0.152320\natom 1.74350 9.08802 5.03185 Cu 0.0 0.0 -0.309832 0.050675 0.116414\natom 4.09435 4.72815 11.62063 Cu 0.0 0.0 -0.488835 0.401761 -0.293672\natom 2.59578 3.44791 1.65468 Cu 0.0 0.0 0.001195 -0.804295 -0.231591\natom 9.73089 8.57633 4.39194 Cu 0.0 0.0 0.036982 0.288261 0.452128\natom 7.37620 9.13211 10.85042 Cu 0.0 0.0 -0.392944 0.094802 -0.026504\natom -1.05087 3.39136 8.03506 Cu 0.0 0.0 -0.158547 0.227874 0.594507\natom -2.23135 0.98797 8.10515 Cu 0.0 0.0 0.302332 0.190919 0.039003\natom 8.44600 6.93280 9.76244 Cu 0.0 0.0 0.794447 0.231274 0.607530\natom 11.43175 10.56534 3.95892 Cu 0.0 0.0 -0.479032 0.815489 -0.428313\natom 0.56312 5.02524 2.03818 Cu 0.0 0.0 0.206743 -0.955342 0.150812\nenergy -565.073649\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_279\nlattice 15.400727029 0.000000000 0.000000000\nlattice 0.000000000 12.004607111 0.000000000\nlattice -6.050141328 0.000000000 12.214683488\natom 9.65434 1.13629 10.42689 S 0.0 0.0 -0.027450 0.265189 0.059099\natom -3.69623 6.92843 7.97749 S 0.0 0.0 0.339291 0.304709 -0.296444\natom -0.30842 11.07389 1.81163 S 0.0 0.0 -0.347143 0.290416 -0.265011\natom 12.69913 4.92715 4.38423 S 0.0 0.0 -0.221622 0.137567 -0.221864\natom 12.81886 1.06893 3.99055 S 0.0 0.0 -0.445042 0.266383 0.093812\natom -0.18531 6.99544 1.90757 S 0.0 0.0 0.143616 0.002630 -0.419620\natom -2.90946 10.95025 7.86991 S 0.0 0.0 -0.270380 0.623666 0.222735\natom 9.57120 5.13156 10.74113 S 0.0 0.0 0.229174 -0.046146 -0.018056\natom 9.05460 0.97974 6.19685 S 0.0 0.0 0.481142 0.398229 0.331226\natom -3.06588 7.00845 11.87544 S 0.0 0.0 0.597812 -0.917245 0.172220\natom 0.42980 11.01015 6.07632 S 0.0 0.0 -0.133291 -0.160642 -0.311381\natom 11.78799 4.99460 0.01902 S 0.0 0.0 0.873595 0.681268 0.337014\natom 12.15741 1.15010 0.35007 S 0.0 0.0 -0.533612 -0.776279 0.057191\natom 0.21000 6.72252 6.13407 S 0.0 0.0 0.050020 0.620973 -0.365571\natom -2.81709 10.91384 12.20682 S 0.0 0.0 0.804004 -0.174437 -0.129138\natom 9.01094 4.82929 6.42686 S 0.0 0.0 0.290862 0.045045 -0.468485\natom 3.52205 0.72389 7.42145 S 0.0 0.0 -0.706904 0.747540 0.274162\natom 2.77862 6.94939 11.04289 S 0.0 0.0 0.696009 0.196816 -1.191073\natom 5.69056 11.08645 4.73966 S 0.0 0.0 1.228142 -0.081054 0.284577\natom 6.10330 4.86873 1.26284 S 0.0 0.0 -0.348331 0.574917 0.823367\natom 6.48304 0.87752 1.20088 S 0.0 0.0 -1.205732 -0.362291 -0.851227\natom 5.92901 6.66692 5.13927 S 0.0 0.0 0.547833 0.519141 -0.525032\natom 3.07500 11.16805 11.17593 S 0.0 0.0 -0.212242 -0.190401 0.271072\natom 3.16284 5.16247 7.09927 S 0.0 0.0 0.588442 -0.756420 0.612938\natom 0.03720 0.67302 9.60886 S 0.0 0.0 0.314782 0.360945 0.404808\natom 6.36915 7.02952 8.99250 S 0.0 0.0 -0.007432 0.203433 -0.383531\natom 9.53633 10.91032 3.10898 S 0.0 0.0 -0.378398 0.163635 -0.149693\natom 3.25425 4.97004 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8.38814 0.81594 2.05597 Cu 0.0 0.0 1.087838 -0.069441 0.729638\natom 4.02764 7.41026 4.45263 Cu 0.0 0.0 -0.375365 0.294501 -0.662878\natom 1.09170 10.70841 10.12471 Cu 0.0 0.0 -0.096600 -0.101774 -0.010295\natom 5.29100 5.16403 8.07640 Cu 0.0 0.0 -0.083630 -0.100913 0.265753\natom 5.41270 2.75931 0.72858 Cu 0.0 0.0 -0.029070 -0.044443 0.283989\natom 7.16192 9.32876 5.24564 Cu 0.0 0.0 -0.205326 -0.106932 0.193270\natom 4.25522 9.22371 11.54870 Cu 0.0 0.0 -0.110040 0.003881 -0.279273\natom 2.46996 2.86206 6.92385 Cu 0.0 0.0 -0.437845 0.058486 -0.186360\natom -3.69824 0.93079 11.51239 Cu 0.0 0.0 -0.528848 -0.553449 -0.476950\natom 8.18162 7.24408 7.58625 Cu 0.0 0.0 -0.066860 -0.017268 -0.020829\natom 13.01532 11.05932 0.49142 Cu 0.0 0.0 0.193724 -0.171706 0.316688\natom -0.43528 4.76027 5.25475 Cu 0.0 0.0 -0.014576 -0.355329 -0.064321\natom -0.91878 0.67847 5.48290 Cu 0.0 0.0 -0.285952 0.149133 -0.267101\natom 13.42130 6.64028 0.35803 Cu 0.0 0.0 0.077954 0.188468 0.565580\natom 10.55055 11.38916 6.88428 Cu 0.0 0.0 -0.183498 0.144817 -0.245487\natom -3.36792 4.81748 11.17599 Cu 0.0 0.0 -0.543630 -0.230396 0.405871\natom 8.21425 1.65171 12.19874 Cu 0.0 0.0 0.643216 -0.192794 -0.201816\natom 11.80791 6.92370 5.31055 Cu 0.0 0.0 0.253792 0.084301 0.386113\natom -5.08359 10.78705 12.13169 Cu 0.0 0.0 -0.287906 -0.201018 0.252104\natom 11.31575 4.59021 6.09702 Cu 0.0 0.0 -0.367090 -0.498877 0.099718\natom 11.47516 1.68583 5.88820 Cu 0.0 0.0 -0.069929 -0.086020 -0.247185\natom -5.44689 7.82624 11.94118 Cu 0.0 0.0 -0.149588 -0.247335 0.340774\natom -2.18526 9.88681 6.08793 Cu 0.0 0.0 0.088100 -0.104267 -0.641500\natom 14.08306 4.12963 0.16499 Cu 0.0 0.0 -0.114203 0.641912 0.116931\natom 9.29780 3.00009 4.99117 Cu 0.0 0.0 -0.027990 0.079308 0.087680\natom 2.69882 8.77207 0.78791 Cu 0.0 0.0 -0.043134 1.043673 0.739696\natom 0.17794 8.95078 6.89682 Cu 0.0 0.0 -0.516005 -0.436177 0.460935\natom 6.06030 3.02882 11.17722 Cu 0.0 0.0 0.021239 -0.557262 -0.148721\natom 1.33702 1.70640 11.35346 Cu 0.0 0.0 -0.173388 0.140541 -0.189028\natom 5.11245 7.74479 6.93217 Cu 0.0 0.0 0.421601 0.056960 0.113577\natom 8.24396 10.34956 1.21142 Cu 0.0 0.0 0.182989 -0.305282 -0.034122\natom 4.38653 4.15265 5.40633 Cu 0.0 0.0 -0.153409 0.294314 0.143012\natom 3.90180 1.60979 5.13212 Cu 0.0 0.0 0.121887 -0.408556 -0.086019\natom 8.56950 7.30516 0.96892 Cu 0.0 0.0 -0.348738 0.297050 0.376032\natom 5.95239 10.92008 7.04416 Cu 0.0 0.0 -0.295917 -0.246031 -0.626765\natom 0.88052 4.37533 11.53395 Cu 0.0 0.0 0.226771 -0.072623 -0.840530\natom -1.01699 2.80331 10.20025 Cu 0.0 0.0 0.586820 -0.568188 0.271337\natom 8.45376 10.06381 8.04991 Cu 0.0 0.0 -0.608008 0.349645 0.594028\natom 10.91943 8.19009 1.63815 Cu 0.0 0.0 -0.622651 -0.182141 0.406856\natom 2.17443 3.29759 4.35635 Cu 0.0 0.0 -0.666198 -0.221666 0.294757\natom 8.76230 0.53596 8.40783 Cu 0.0 0.0 0.255561 0.533831 0.132131\natom -2.19473 6.61348 9.84131 Cu 0.0 0.0 0.082533 0.222275 -0.441892\natom 0.74102 11.61955 3.75073 Cu 0.0 0.0 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0.568117\natom 5.10691 6.72910 10.85439 Cu 0.0 0.0 -0.247390 0.012722 -0.115851\natom 8.09573 11.66333 4.74762 Cu 0.0 0.0 -0.380796 -0.187217 -0.497365\natom 3.89861 5.65300 1.38974 Cu 0.0 0.0 0.206767 0.733346 -1.712023\natom 3.72861 0.65856 1.35498 Cu 0.0 0.0 0.199741 0.023604 0.568100\natom 8.87537 6.49500 4.85784 Cu 0.0 0.0 0.065586 0.173447 0.448166\natom 5.28922 11.61664 10.73261 Cu 0.0 0.0 0.382254 -0.121849 -0.149241\natom 1.01401 5.20040 7.88581 Cu 0.0 0.0 -0.266200 -0.116373 0.002711\natom 3.35006 2.22894 9.18589 Cu 0.0 0.0 -0.329387 0.110881 0.372311\natom 3.28298 8.22004 9.04472 Cu 0.0 0.0 -0.173302 -0.476694 1.180064\natom 5.97588 9.72319 2.92188 Cu 0.0 0.0 0.418192 -0.520572 0.038207\natom 5.63801 3.59003 3.25572 Cu 0.0 0.0 0.341480 0.255657 -0.204462\natom -0.58736 1.48686 2.64282 Cu 0.0 0.0 -0.428627 -0.597132 0.281811\natom 13.26234 8.59716 2.25889 Cu 0.0 0.0 1.192576 -0.144180 -0.356367\natom 10.66361 10.90208 9.36498 Cu 0.0 0.0 -0.021550 -0.079435 0.266917\natom -3.03723 4.70978 8.54988 Cu 0.0 0.0 -0.353626 0.492962 -0.318408\natom 3.86555 1.26076 12.11565 Cu 0.0 0.0 -0.394991 0.031432 -0.551437\natom 2.48989 7.28693 6.71758 Cu 0.0 0.0 -0.474364 0.241244 -0.225704\natom 5.63424 10.87951 0.67509 Cu 0.0 0.0 -0.170893 -0.253830 -0.082775\natom 7.03761 4.76715 5.21144 Cu 0.0 0.0 -0.279416 -0.661557 -0.067166\natom 7.63233 2.67356 7.19500 Cu 0.0 0.0 0.266248 -0.279091 -0.202780\natom -1.09448 8.23442 11.39464 Cu 0.0 0.0 -0.000643 0.172447 0.257186\natom 1.65589 9.49824 5.00695 Cu 0.0 0.0 0.339049 -0.179186 -0.445788\natom 10.29569 3.62937 0.86254 Cu 0.0 0.0 -0.297019 -0.093742 0.347960\natom 2.58193 3.17311 1.89072 Cu 0.0 0.0 0.358917 -0.456653 -0.602447\natom 9.05373 8.73571 3.57224 Cu 0.0 0.0 -0.153146 0.452311 0.000540\natom 5.94399 9.25011 9.24171 Cu 0.0 0.0 -0.116690 0.325987 -0.143172\natom -0.87653 3.40259 7.81309 Cu 0.0 0.0 0.268177 -0.269184 -1.093559\natom -1.64270 0.94564 8.22072 Cu 0.0 0.0 -0.406635 0.049550 -0.029093\natom 8.26660 6.91319 10.21133 Cu 0.0 0.0 0.426108 -0.045893 -0.236280\natom 11.88806 11.08188 4.22145 Cu 0.0 0.0 -0.069410 -0.273711 -0.153051\natom 1.03226 5.04014 2.66085 Cu 0.0 0.0 -0.247581 0.287013 -0.203919\nenergy -565.111055\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_296\nlattice 15.463777200 0.000000000 0.000000000\nlattice 0.000000000 12.053753656 0.000000000\nlattice -6.074910447 0.000000000 12.264690081\natom 9.59413 0.96783 10.57278 S 0.0 0.0 0.346300 -0.137397 -1.121629\natom -2.68602 6.71076 7.96014 S 0.0 0.0 -1.208815 0.744476 0.423387\natom -0.06390 10.87276 2.00398 S 0.0 0.0 0.038899 0.042418 -0.360703\natom 12.69540 4.92373 4.29215 S 0.0 0.0 -0.094540 0.526336 -0.057451\natom 12.43441 0.73162 4.66904 S 0.0 0.0 0.183514 -0.372937 -0.615548\natom -0.31411 6.85536 1.70885 S 0.0 0.0 -0.196162 0.784649 0.107756\natom -3.04952 10.98798 8.00627 S 0.0 0.0 -0.282368 0.192436 -0.334371\natom 9.50949 5.18194 10.50431 S 0.0 0.0 0.670014 -0.339791 0.077834\natom 9.37229 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Cu 0.0 0.0 0.297698 0.280237 0.342135\natom 5.63955 0.68693 8.59493 Cu 0.0 0.0 -0.284858 1.164875 -0.273901\natom 0.99234 7.12437 10.02156 Cu 0.0 0.0 0.291310 -0.094609 -0.154963\natom 4.26476 11.05351 4.03807 Cu 0.0 0.0 -0.135334 0.496674 0.209101\natom 9.35048 5.14152 2.78948 Cu 0.0 0.0 -0.397765 0.698479 -0.107401\natom 7.09437 3.46705 2.87700 Cu 0.0 0.0 0.154622 -0.286286 0.626391\natom 4.61235 7.62902 3.97199 Cu 0.0 0.0 -0.776719 0.739128 -0.415097\natom 0.75140 11.20110 10.45689 Cu 0.0 0.0 -0.035332 -0.347693 -0.428419\natom 5.46156 4.57165 8.35079 Cu 0.0 0.0 -0.445057 0.542046 -0.332669\natom 5.50832 2.74619 0.92811 Cu 0.0 0.0 0.008404 0.042370 0.046395\natom 7.33602 8.87388 5.51081 Cu 0.0 0.0 0.221632 -0.231389 -0.759786\natom 4.29560 9.09480 11.25367 Cu 0.0 0.0 -0.373222 0.115962 -0.016236\natom 2.02184 3.21172 6.90396 Cu 0.0 0.0 0.802661 -0.304376 -0.032985\natom -3.82786 1.17256 11.51540 Cu 0.0 0.0 0.249634 -0.138391 -0.221822\natom 10.52571 7.01357 7.10499 Cu 0.0 0.0 0.196093 -0.514237 0.069269\natom 12.73284 10.79750 1.00759 Cu 0.0 0.0 0.322784 1.110356 0.316976\natom -0.61292 5.04408 5.01739 Cu 0.0 0.0 -0.099418 -0.146983 -0.011236\natom -1.00797 0.89234 5.59127 Cu 0.0 0.0 0.659388 -0.014512 0.178730\natom 13.11639 6.88375 0.41410 Cu 0.0 0.0 0.120379 0.761308 0.151347\natom 10.25236 11.24357 7.04142 Cu 0.0 0.0 0.486852 -0.703417 0.162744\natom -3.78914 4.90979 11.64754 Cu 0.0 0.0 -0.562557 0.868287 -0.307699\natom 7.97327 1.00806 12.01927 Cu 0.0 0.0 -0.320661 -0.261778 0.669270\natom -2.66364 6.77284 5.72900 Cu 0.0 0.0 0.139583 0.019303 -0.109989\natom 1.20070 10.29289 0.05535 Cu 0.0 0.0 0.128534 -0.142367 0.170485\natom 11.56341 4.52622 6.20016 Cu 0.0 0.0 -0.422768 -0.016949 -0.036187\natom 11.38589 1.88456 6.19868 Cu 0.0 0.0 0.372210 0.381362 0.737046\natom 1.40326 7.62107 0.05935 Cu 0.0 0.0 -0.033455 0.158910 -0.065999\natom -1.58357 10.14682 6.04642 Cu 0.0 0.0 -0.379767 0.174140 -0.180950\natom 14.96000 4.73947 0.51353 Cu 0.0 0.0 0.006641 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3.09760 Cu 0.0 0.0 0.272462 0.156177 -0.187015\natom 6.72896 6.68660 2.38717 Cu 0.0 0.0 -0.256522 -0.018980 0.335159\natom 3.67571 11.09697 8.86140 Cu 0.0 0.0 -0.088144 -0.340246 -0.388276\natom 3.12084 5.15555 9.24911 Cu 0.0 0.0 -0.184530 0.230609 1.072112\natom 1.05251 0.68247 7.85059 Cu 0.0 0.0 0.190857 0.169244 0.174255\natom 5.41042 6.02785 10.84761 Cu 0.0 0.0 -0.263230 -0.059625 0.128623\natom 8.87918 11.70123 4.72201 Cu 0.0 0.0 -0.350901 -0.217265 -0.302340\natom 4.71735 5.14723 1.62155 Cu 0.0 0.0 -0.037088 0.297995 -0.184864\natom 3.57371 1.10987 1.44231 Cu 0.0 0.0 -0.197962 -0.265239 -0.091625\natom 8.87277 6.99746 4.73890 Cu 0.0 0.0 0.146668 -0.004404 -0.370001\natom 5.79905 11.57054 10.82641 Cu 0.0 0.0 -0.057973 -0.331349 0.238891\natom 0.48660 5.87614 7.54282 Cu 0.0 0.0 0.132922 -0.203636 0.016477\natom 3.51808 2.53755 9.07380 Cu 0.0 0.0 -0.056264 -0.171712 0.096410\natom 3.21469 8.21910 8.95145 Cu 0.0 0.0 -0.033383 0.163191 -0.104063\natom 5.96330 9.79846 2.91535 Cu 0.0 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0.880564 0.255728\natom 12.48062 1.07683 4.27994 S 0.0 0.0 -0.316347 -1.027131 -0.094489\natom -0.04479 6.61087 1.55906 S 0.0 0.0 0.308733 0.461656 0.520550\natom -2.95597 10.83931 7.88751 S 0.0 0.0 -0.546322 1.118162 0.026506\natom 9.37507 5.12144 10.53558 S 0.0 0.0 0.279298 -0.411908 0.419070\natom 8.94845 0.95941 6.00327 S 0.0 0.0 0.291624 0.068005 -0.141155\natom -2.38905 7.15920 11.92073 S 0.0 0.0 -1.162472 -0.626538 0.818775\natom 0.31585 10.87958 6.05820 S 0.0 0.0 -0.093190 0.109477 -0.217973\natom 12.10077 4.76210 0.01304 S 0.0 0.0 1.034410 0.346477 0.862563\natom 11.82591 0.92861 0.28207 S 0.0 0.0 -0.191254 0.177209 -0.876314\natom -0.09276 6.75665 6.04221 S 0.0 0.0 1.604115 -0.825764 -0.211824\natom 3.06876 11.17691 0.12659 S 0.0 0.0 0.877242 0.845130 -1.087003\natom 9.07478 5.09955 6.29768 S 0.0 0.0 0.378950 -0.071979 0.924003\natom 3.08099 0.87762 7.19200 S 0.0 0.0 0.947365 0.539492 0.086533\natom 2.97503 7.00409 11.12474 S 0.0 0.0 0.420024 0.079390 -0.870386\natom 5.95981 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5.21104 Cu 0.0 0.0 0.245095 -0.446805 0.418171\natom 4.46850 9.26065 11.12519 Cu 0.0 0.0 0.306807 -0.334017 0.208098\natom 2.26961 3.05527 6.77589 Cu 0.0 0.0 -0.353764 0.114041 -0.013309\natom -3.90401 1.03284 11.46200 Cu 0.0 0.0 0.001015 0.337714 -0.325268\natom 10.04011 7.25985 6.84980 Cu 0.0 0.0 0.244773 -0.320630 0.146804\natom 13.21623 11.02955 0.89163 Cu 0.0 0.0 0.112597 -0.567873 -0.018682\natom -0.51286 4.85669 5.10751 Cu 0.0 0.0 0.253876 -1.088299 -0.207555\natom -1.04706 0.72587 5.52506 Cu 0.0 0.0 -0.099741 -0.138001 -0.186971\natom 13.36150 6.86658 0.76794 Cu 0.0 0.0 -0.569603 0.126375 -0.339053\natom 10.12348 11.14436 6.92507 Cu 0.0 0.0 0.593908 0.253869 -0.057492\natom -3.89692 5.17103 11.34088 Cu 0.0 0.0 0.395195 0.075991 0.300955\natom 7.87836 1.23229 12.01207 Cu 0.0 0.0 0.600315 0.231568 -0.311218\natom -2.28976 7.34384 6.19682 Cu 0.0 0.0 -0.380809 -0.111907 0.356839\natom 0.90592 10.61238 0.07715 Cu 0.0 0.0 -0.021947 -0.526168 -0.337515\natom 11.21629 4.63957 6.08514 Cu 0.0 0.0 0.631695 -0.363444 -0.142808\natom 11.47399 1.84913 6.17495 Cu 0.0 0.0 -0.256208 0.011497 0.228798\natom -4.72531 7.79138 12.13660 Cu 0.0 0.0 -0.093923 -0.235496 -0.291658\natom -1.97425 10.19444 5.89992 Cu 0.0 0.0 0.234500 0.468924 -0.024111\natom 14.39111 4.08618 0.16464 Cu 0.0 0.0 -0.556085 0.585623 -0.525095\natom 9.22431 3.12924 5.09010 Cu 0.0 0.0 -0.022337 -0.006849 0.451603\natom 3.15359 9.23676 0.94540 Cu 0.0 0.0 0.062331 -1.208447 0.413546\natom -0.14476 8.70876 6.83661 Cu 0.0 0.0 0.152332 1.033735 -0.156566\natom 4.89805 3.75290 10.52765 Cu 0.0 0.0 0.148448 -0.525528 -1.048912\natom 1.18373 1.85350 11.20431 Cu 0.0 0.0 -0.813557 -0.325455 -0.019585\natom 4.99915 8.31554 8.33002 Cu 0.0 0.0 -0.257787 -0.231200 -0.043920\natom 8.01583 10.44061 0.99761 Cu 0.0 0.0 -0.396911 -0.277273 -0.135587\natom 4.05055 4.30653 4.67827 Cu 0.0 0.0 0.299631 -0.319010 0.353422\natom 3.83077 1.60663 5.02926 Cu 0.0 0.0 0.612574 0.439723 0.812241\natom 8.32052 7.15493 0.99878 Cu 0.0 0.0 0.178705 0.211878 0.312601\natom 5.31374 10.44631 7.10559 Cu 0.0 0.0 -0.354311 -0.281023 -1.135853\natom 1.12518 4.64450 11.67392 Cu 0.0 0.0 -0.277880 0.128297 -0.280548\natom -1.30573 2.55086 10.57811 Cu 0.0 0.0 -0.008750 -0.009660 -0.035862\natom 7.46860 8.82404 8.06806 Cu 0.0 0.0 0.039688 0.204694 -0.202483\natom 10.45443 8.74277 1.60883 Cu 0.0 0.0 0.320506 0.807210 -0.591092\natom 0.40520 2.33976 3.62951 Cu 0.0 0.0 0.013737 -0.045044 0.864332\natom 8.66463 0.73061 8.19653 Cu 0.0 0.0 -0.174718 -0.295994 0.199312\natom -1.97525 6.28816 9.83168 Cu 0.0 0.0 0.495945 -0.286401 0.350103\natom 0.76393 11.69432 3.87744 Cu 0.0 0.0 -0.024257 -0.126497 0.636625\natom 11.45416 5.49355 2.10991 Cu 0.0 0.0 0.169950 -0.109548 0.207235\natom 11.20002 12.00074 2.11239 Cu 0.0 0.0 0.408159 0.209588 0.561218\natom 1.61709 6.57877 4.30650 Cu 0.0 0.0 -0.516641 0.156065 0.445606\natom -1.82946 11.15477 10.15416 Cu 0.0 0.0 -0.323224 0.021610 0.381308\natom 8.47378 5.28515 8.51925 Cu 0.0 0.0 -0.291915 0.348682 -0.815617\natom -4.45212 1.94910 9.00188 Cu 0.0 0.0 0.146912 0.374676 -0.046818\natom 10.66299 8.41691 9.11260 Cu 0.0 0.0 -0.313353 0.113297 0.242159\natom -1.56062 9.96863 3.30079 Cu 0.0 0.0 -0.278408 -0.485308 0.103815\natom 13.73967 3.97375 2.71086 Cu 0.0 0.0 0.336940 -0.819309 -0.583271\natom 5.92778 1.35655 3.15688 Cu 0.0 0.0 0.070707 -0.219348 -0.260031\natom 6.54915 7.05855 2.75279 Cu 0.0 0.0 -0.088029 -0.071413 0.494950\natom 3.01547 11.62749 9.14424 Cu 0.0 0.0 -0.024791 0.003903 -0.523111\natom 3.35876 6.03323 9.07133 Cu 0.0 0.0 -0.095102 -0.063640 0.046690\natom 0.93017 0.74594 7.66931 Cu 0.0 0.0 -0.694347 -0.219155 0.041993\natom 5.26306 6.14718 10.73979 Cu 0.0 0.0 -0.103324 1.119268 -0.267892\natom 8.20036 11.21140 4.38288 Cu 0.0 0.0 0.004602 0.466955 0.202930\natom 4.49282 6.02257 1.56161 Cu 0.0 0.0 -0.009942 -0.094018 -0.233662\natom 3.75924 1.04894 1.35025 Cu 0.0 0.0 -0.166689 -0.284036 0.339482\natom 8.66395 6.58551 4.76169 Cu 0.0 0.0 -0.422704 0.486288 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0.185854\natom 6.72647 3.36344 3.13401 Cu 0.0 0.0 0.076229 0.649473 -0.191995\natom 13.43144 1.17425 2.35847 Cu 0.0 0.0 -0.024154 0.484279 -0.278269\natom -1.33140 7.29165 3.46685 Cu 0.0 0.0 -0.005651 0.021867 -0.144259\natom -4.56035 10.74940 9.82563 Cu 0.0 0.0 0.079017 -0.091598 -0.327849\natom 11.18471 5.03689 8.54341 Cu 0.0 0.0 -0.178459 -0.385846 0.399103\natom 3.76512 1.21307 11.84350 Cu 0.0 0.0 0.225466 0.873535 -0.175913\natom 2.73076 7.20423 7.16718 Cu 0.0 0.0 -0.256518 0.430094 -0.124481\natom 5.50669 10.83828 0.49333 Cu 0.0 0.0 0.784932 -0.382042 0.233489\natom 6.87650 4.79090 5.21529 Cu 0.0 0.0 -0.314584 0.323137 0.060103\natom 7.96189 2.92785 7.30116 Cu 0.0 0.0 -0.044054 0.067920 -0.437947\natom -1.16153 8.18641 11.26996 Cu 0.0 0.0 0.297148 0.206065 -0.040745\natom 1.84239 9.63947 5.13552 Cu 0.0 0.0 -0.125355 0.243608 0.284855\natom 11.47668 2.95602 1.20412 Cu 0.0 0.0 0.043196 0.128106 -0.338968\natom 2.24530 2.58721 1.67052 Cu 0.0 0.0 -0.205593 0.029137 0.373175\natom 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7.78762 S 0.0 0.0 0.307424 0.468046 -0.003713\natom 11.73155 2.72999 3.65429 Cu 0.0 0.0 -0.205403 0.640337 -0.151061\natom 0.66613 8.60344 2.43088 Cu 0.0 0.0 0.355992 -0.185770 -0.193305\natom -2.29146 9.07539 8.56173 Cu 0.0 0.0 -0.042250 -0.301201 0.203443\natom 8.80854 2.86845 9.60856 Cu 0.0 0.0 -0.320755 -0.172987 0.168747\natom 5.30302 0.86141 8.63190 Cu 0.0 0.0 -0.108091 0.111894 -0.000144\natom 0.76235 6.97487 10.00323 Cu 0.0 0.0 0.193386 0.458556 0.543800\natom 3.73917 11.16368 3.99209 Cu 0.0 0.0 0.098091 -0.299638 -0.050441\natom 8.67336 4.89055 2.05390 Cu 0.0 0.0 -0.160631 -0.313052 -0.310123\natom 8.64053 1.22491 1.89864 Cu 0.0 0.0 -0.531404 -0.329692 0.082656\natom 3.87060 7.15001 3.98688 Cu 0.0 0.0 0.343764 -0.245635 0.192519\natom 0.86747 10.99916 10.12815 Cu 0.0 0.0 0.553844 0.504072 -0.015565\natom 5.37338 4.54608 7.96600 Cu 0.0 0.0 -0.790988 0.612881 0.188971\natom 5.30235 2.96679 0.74196 Cu 0.0 0.0 -0.279765 0.053589 0.061152\natom 7.17235 8.95634 5.48649 Cu 0.0 0.0 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0.229835\natom 5.98003 10.54222 7.01848 Cu 0.0 0.0 -0.268979 0.613439 -0.609902\natom 0.90330 4.52668 11.09130 Cu 0.0 0.0 -0.015860 -0.009756 0.061747\natom -1.32816 3.08064 10.41773 Cu 0.0 0.0 -0.493890 -0.065188 0.008047\natom 9.10624 9.49641 8.40497 Cu 0.0 0.0 -0.542911 -0.259645 -0.523702\natom 10.54298 9.22840 1.73106 Cu 0.0 0.0 0.204844 -0.051950 0.245926\natom 1.86215 3.19365 4.41637 Cu 0.0 0.0 -0.141626 0.355328 -0.128984\natom 8.65817 0.51941 8.36583 Cu 0.0 0.0 -0.022819 -0.077019 -0.417244\natom -2.29063 6.73982 10.04842 Cu 0.0 0.0 -0.249279 0.046797 0.036677\natom 0.78869 11.47440 3.73836 Cu 0.0 0.0 0.042456 0.785562 0.690769\natom 11.47010 5.64750 2.12577 Cu 0.0 0.0 0.841797 -0.701578 -0.310140\natom 11.01177 0.57843 1.86130 Cu 0.0 0.0 0.197024 -0.015556 -0.043231\natom 1.22968 6.56272 4.18906 Cu 0.0 0.0 0.397033 0.185775 -0.533834\natom -1.52602 10.80217 10.42185 Cu 0.0 0.0 0.048520 -0.018238 -0.396147\natom 7.92076 4.83320 8.23419 Cu 0.0 0.0 -0.018300 0.409796 0.050275\natom -3.94273 2.51079 9.87109 Cu 0.0 0.0 0.017620 0.266824 0.223522\natom -4.55916 7.98488 9.42777 Cu 0.0 0.0 0.221198 0.396508 0.242025\natom 13.87117 9.54453 2.93125 Cu 0.0 0.0 -0.109165 0.414871 0.021803\natom -1.40621 3.62781 3.03879 Cu 0.0 0.0 -0.153347 -0.155868 -0.157467\natom 6.05605 0.98838 3.61087 Cu 0.0 0.0 0.089056 0.351384 -0.322776\natom 6.52273 6.78567 2.73100 Cu 0.0 0.0 -0.159560 0.079069 -0.461882\natom 3.34673 10.94069 8.63529 Cu 0.0 0.0 -0.013092 -0.001600 0.434844\natom 3.01646 5.57841 9.56349 Cu 0.0 0.0 0.011887 -0.100686 -0.196458\natom 1.10921 0.20152 7.76368 Cu 0.0 0.0 -0.048169 0.377541 0.179621\natom 5.12377 6.74708 10.50326 Cu 0.0 0.0 0.292989 -0.078557 -0.046372\natom 8.33426 11.37061 4.39522 Cu 0.0 0.0 -0.309672 0.456973 1.103821\natom 4.01440 5.33921 1.45196 Cu 0.0 0.0 0.281696 -0.159501 0.221087\natom 4.17980 0.49294 1.84301 Cu 0.0 0.0 -0.708562 0.503849 0.133844\natom 8.51653 6.09526 4.09474 Cu 0.0 0.0 -0.112062 0.324024 0.920042\natom 5.80361 11.03217 11.01922 Cu 0.0 0.0 0.246308 0.819800 -0.409801\natom 0.95847 5.79446 7.92616 Cu 0.0 0.0 0.062632 -0.810195 -0.092027\natom 2.96305 2.39870 9.28766 Cu 0.0 0.0 -0.376596 -0.385463 -0.239446\natom 3.60853 8.44318 9.05850 Cu 0.0 0.0 -0.562347 -0.238037 -0.236064\natom 5.48287 9.48018 3.23817 Cu 0.0 0.0 0.111306 -0.286517 -0.380803\natom 6.21831 3.58996 3.10914 Cu 0.0 0.0 0.319425 0.713190 -0.944335\natom 13.74706 1.16261 2.84686 Cu 0.0 0.0 0.354621 -0.100438 -0.423985\natom -1.29721 7.00319 3.41310 Cu 0.0 0.0 -0.206902 0.041096 -0.118138\natom -4.68435 10.69262 9.66255 Cu 0.0 0.0 0.380924 0.151717 0.212082\natom 10.57580 4.76256 8.65377 Cu 0.0 0.0 0.531670 -0.061357 -0.271865\natom 3.71797 0.98293 11.40162 Cu 0.0 0.0 0.525492 0.658514 0.307460\natom 2.53480 7.54988 6.78049 Cu 0.0 0.0 -0.334903 -0.538353 -0.101635\natom 5.79484 10.98424 0.86999 Cu 0.0 0.0 0.006181 -0.680788 -0.287408\natom 6.64317 4.95970 5.79592 Cu 0.0 0.0 0.078628 0.412810 -0.470822\natom 7.34928 2.85016 6.85061 Cu 0.0 0.0 0.305209 -0.869851 0.282557\natom -0.96136 8.40340 11.57072 Cu 0.0 0.0 0.322996 0.123072 -0.046541\natom 1.70149 9.70799 5.02821 Cu 0.0 0.0 0.494988 -0.725456 0.395173\natom 11.19334 3.07832 0.70713 Cu 0.0 0.0 0.017619 0.066578 0.468611\natom 2.09418 2.35857 1.90076 Cu 0.0 0.0 0.590285 0.046588 0.179024\natom 10.33836 8.78125 4.31616 Cu 0.0 0.0 0.065755 -0.568139 -0.425498\natom 5.89067 9.24446 8.99449 Cu 0.0 0.0 0.523743 -0.721595 0.604441\natom -1.14274 3.80931 7.90099 Cu 0.0 0.0 0.308959 -0.339936 -0.691805\natom -2.36795 1.21533 8.28698 Cu 0.0 0.0 0.203000 0.092259 0.005930\natom 8.53458 7.21069 9.64141 Cu 0.0 0.0 -0.409408 -0.413745 -0.018811\natom 11.55690 10.92225 3.71225 Cu 0.0 0.0 0.189831 -0.055151 0.044155\natom 0.69592 4.64286 2.31510 Cu 0.0 0.0 0.344125 0.135702 -0.065281\nenergy -565.990879\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_381\nlattice 15.385741848 0.000000000 0.000000000\nlattice 0.000000000 11.992926415 0.000000000\nlattice 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0.91658 3.51003 S 0.0 0.0 -0.025710 0.218997 0.164401\natom 9.72191 7.07385 2.57166 S 0.0 0.0 0.252975 -0.489957 -0.533307\natom 6.96231 11.13555 8.52477 S 0.0 0.0 -0.102876 -0.192364 0.693199\natom -0.16488 5.00468 9.68879 S 0.0 0.0 -0.214984 -0.149486 0.200145\natom 6.20210 2.77235 8.90275 S 0.0 0.0 0.469766 0.358906 -0.272382\natom 0.03756 9.00345 9.32576 S 0.0 0.0 -0.168706 -0.326194 0.277892\natom 3.12586 9.23074 3.37204 S 0.0 0.0 -0.259214 0.082255 0.040123\natom 9.21873 3.12578 2.76508 S 0.0 0.0 0.533195 -0.199118 -0.390083\natom 5.89762 2.41070 5.31104 S 0.0 0.0 0.156862 0.784978 -0.415392\natom 6.46045 8.82153 1.01071 S 0.0 0.0 -0.092926 -0.697439 0.131623\natom 3.53235 9.36614 6.97528 S 0.0 0.0 -0.513743 0.042048 0.929375\natom 2.75437 3.11046 11.15101 S 0.0 0.0 0.244122 0.086010 -0.281202\natom 0.19551 2.85135 5.93667 S 0.0 0.0 0.027964 1.746397 0.752066\natom 12.18158 8.96670 0.13662 S 0.0 0.0 1.320401 -0.448471 -0.550601\natom 9.20715 9.29605 6.30654 S 0.0 0.0 0.048463 0.052221 -0.147774\natom -2.92174 3.34768 11.88610 S 0.0 0.0 0.050199 0.007954 0.053206\natom -0.01405 3.10105 1.74874 S 0.0 0.0 -1.256553 -0.991026 -0.911636\natom 12.54325 8.73734 4.60141 S 0.0 0.0 -0.668099 0.095902 0.446299\natom 9.62451 9.13033 10.77019 S 0.0 0.0 -0.951899 -0.199389 -1.096222\natom -3.10511 3.22896 7.68996 S 0.0 0.0 -0.191980 0.090752 0.181160\natom 11.71159 3.05493 3.42301 Cu 0.0 0.0 -0.614346 -0.362901 0.023987\natom 0.79889 9.09650 2.66785 Cu 0.0 0.0 0.238005 -0.467958 0.174566\natom -2.08133 8.83859 8.65215 Cu 0.0 0.0 -0.179033 0.047382 0.078499\natom 8.38345 2.76307 9.68602 Cu 0.0 0.0 0.229534 0.245422 0.262122\natom 5.54077 0.71040 7.81966 Cu 0.0 0.0 -0.543723 0.104156 0.062864\natom 0.99210 6.95531 9.77437 Cu 0.0 0.0 -0.602864 0.096841 -0.245447\natom 4.20764 11.27650 3.97750 Cu 0.0 0.0 -0.278442 -0.155795 -0.117456\natom 8.13159 5.19745 2.25772 Cu 0.0 0.0 0.413031 0.147334 -0.261297\natom 8.36442 1.04172 2.16453 Cu 0.0 0.0 0.107403 0.359153 0.029200\natom 4.04014 7.43026 4.19327 Cu 0.0 0.0 0.025806 -0.391033 -0.250307\natom 1.08559 10.74557 10.13730 Cu 0.0 0.0 0.244089 0.321486 0.307173\natom 5.43244 4.84036 8.49903 Cu 0.0 0.0 -0.042731 0.001572 -0.263977\natom 4.95985 2.74918 0.76036 Cu 0.0 0.0 0.650124 -0.342751 0.513306\natom 7.22194 8.55888 5.13075 Cu 0.0 0.0 0.101469 0.485354 0.064326\natom 4.08575 8.93844 11.41566 Cu 0.0 0.0 -0.063231 -0.122843 -0.190502\natom 2.43992 3.21396 7.47876 Cu 0.0 0.0 -0.077031 -0.429449 -0.733630\natom -3.69931 1.28064 11.77260 Cu 0.0 0.0 -0.000236 -0.476267 -0.203761\natom 9.59453 7.14221 6.76060 Cu 0.0 0.0 0.064258 0.528379 -0.184228\natom 12.93847 11.01270 0.90444 Cu 0.0 0.0 0.145432 0.063889 0.019712\natom -0.67141 5.34105 5.72446 Cu 0.0 0.0 0.298332 -0.441454 -0.161557\natom -1.03351 1.21550 5.48592 Cu 0.0 0.0 -0.822244 -0.480912 -0.710894\natom 13.53716 7.27495 0.93480 Cu 0.0 0.0 -0.455545 0.179711 -0.179631\natom 10.44943 11.14808 6.98596 Cu 0.0 0.0 0.042278 -0.186179 -0.387224\natom -3.95394 5.16669 11.07826 Cu 0.0 0.0 0.068204 0.464504 0.580785\natom 14.40140 1.55724 0.07078 Cu 0.0 0.0 -0.175878 0.077724 -0.485831\natom 12.39439 6.48209 5.81842 Cu 0.0 0.0 -0.038046 -0.033224 -0.289350\natom 1.04454 10.25970 0.33599 Cu 0.0 0.0 0.362430 0.420358 0.063403\natom 11.23577 4.09764 5.81212 Cu 0.0 0.0 0.196093 0.306465 0.077735\natom 11.34717 1.45856 5.99899 Cu 0.0 0.0 -0.229240 0.458238 0.843086\natom -4.88353 7.68744 12.16439 Cu 0.0 0.0 0.051403 -0.373407 0.449964\natom -2.41629 11.10057 5.98287 Cu 0.0 0.0 -0.056673 -0.124752 -0.355872\natom 14.06539 4.26781 0.26329 Cu 0.0 0.0 0.564317 -0.090832 -0.077447\natom 9.07661 3.06429 4.99900 Cu 0.0 0.0 0.095513 -0.073796 -0.030946\natom 3.26713 9.15368 1.12967 Cu 0.0 0.0 -0.131499 -0.290807 -0.245339\natom -0.75901 9.07992 5.52474 Cu 0.0 0.0 0.102919 0.030057 0.034120\natom 6.22595 3.07567 11.14685 Cu 0.0 0.0 -0.035081 -0.198247 0.345145\natom 1.04384 1.46412 11.32789 Cu 0.0 0.0 0.052973 0.431111 0.163237\natom 5.40090 7.63747 6.67094 Cu 0.0 0.0 -0.331470 0.252398 0.495228\natom 8.19074 10.20427 0.59092 Cu 0.0 0.0 0.040328 -0.185457 0.244075\natom 4.33223 4.14579 5.18777 Cu 0.0 0.0 0.336363 -0.551805 0.367652\natom 3.73865 1.60189 5.41475 Cu 0.0 0.0 -0.207445 -0.174537 -0.155598\natom 8.32237 7.46590 0.77550 Cu 0.0 0.0 0.261253 0.027276 0.048673\natom 5.56080 10.18706 6.52803 Cu 0.0 0.0 -0.120393 0.271156 0.429619\natom 0.90273 4.27241 11.65507 Cu 0.0 0.0 -0.421922 0.020559 0.088453\natom -1.32779 2.49177 10.47752 Cu 0.0 0.0 -0.066978 -0.009727 -0.291503\natom 7.50996 9.04857 7.85521 Cu 0.0 0.0 -0.114700 -0.644251 -0.023218\natom 10.73365 9.18162 1.73432 Cu 0.0 0.0 -0.426919 -0.210149 0.411827\natom 1.68706 3.88963 4.75733 Cu 0.0 0.0 0.421421 0.255337 -0.128322\natom 8.90235 0.55317 8.27384 Cu 0.0 0.0 -0.356851 0.199562 0.968593\natom -1.91232 6.50406 9.88035 Cu 0.0 0.0 -0.013697 -0.067394 0.369268\natom 0.70885 11.72524 3.95941 Cu 0.0 0.0 0.192362 0.149447 -0.950886\natom 11.46683 5.56791 2.08637 Cu 0.0 0.0 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0.666495\natom 8.74565 10.95480 4.44779 Cu 0.0 0.0 -0.025090 0.028731 0.033567\natom 3.54443 5.02070 1.41742 Cu 0.0 0.0 0.589850 0.094526 -0.614166\natom 3.89299 0.51950 1.67325 Cu 0.0 0.0 -0.211794 0.375796 0.197401\natom 8.49610 6.58551 4.36667 Cu 0.0 0.0 -0.229787 -0.505967 0.349418\natom 5.35664 11.62425 10.17223 Cu 0.0 0.0 0.338571 -0.174452 0.098649\natom 1.15555 5.17702 7.77428 Cu 0.0 0.0 -0.311910 0.969390 -0.102685\natom 3.94218 2.34269 9.26197 Cu 0.0 0.0 -0.013668 0.177291 0.664866\natom 3.02818 8.36965 9.09589 Cu 0.0 0.0 0.170657 0.738510 -0.961676\natom 6.08672 9.67955 3.02232 Cu 0.0 0.0 0.062660 0.005973 0.143035\natom 6.72045 3.34718 3.28666 Cu 0.0 0.0 0.081021 0.143585 0.156367\natom 14.07917 1.21330 2.58036 Cu 0.0 0.0 0.075805 0.108580 0.212462\natom -1.33035 7.12343 3.72602 Cu 0.0 0.0 -0.031493 -0.175596 -0.252433\natom -4.20539 10.27979 9.69921 Cu 0.0 0.0 -0.862454 -0.412546 0.637965\natom 11.05511 5.10139 8.71689 Cu 0.0 0.0 -0.367556 -0.100313 -0.305517\natom 3.50289 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3.60685 Cu 0.0 0.0 0.342318 0.178983 0.464401\natom 1.29509 4.75239 2.38412 Cu 0.0 0.0 -0.188202 1.031223 0.388228\nenergy -566.742004\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_399\nlattice 15.429132687 0.000000000 0.000000000\nlattice 0.000000000 12.026748842 0.000000000\nlattice -6.061300427 0.000000000 12.237212693\natom 9.63118 0.94105 10.33837 S 0.0 0.0 0.161978 0.342383 -1.036946\natom -3.45782 7.03106 8.10910 S 0.0 0.0 -0.293940 0.230258 0.415449\natom -0.33796 11.02851 1.84294 S 0.0 0.0 0.371324 0.241528 -0.653168\natom 12.64709 5.14342 4.13109 S 0.0 0.0 0.285255 -0.515714 -0.327370\natom 12.29531 1.13384 4.22325 S 0.0 0.0 -0.152218 -0.360157 0.021551\natom 0.31179 6.90210 1.97612 S 0.0 0.0 -0.286591 0.249480 -0.164542\natom -3.21062 11.15093 7.57547 S 0.0 0.0 0.661076 -0.123605 0.259053\natom 9.27747 5.10082 10.19174 S 0.0 0.0 1.019952 -0.634056 0.211471\natom 9.29646 1.03574 6.19031 S 0.0 0.0 -0.972366 -0.077911 -0.266220\natom -2.89894 7.17709 12.18380 S 0.0 0.0 -0.479905 -0.608058 0.292084\natom 0.04381 10.97949 6.13080 S 0.0 0.0 -0.132460 -0.174697 -0.713302\natom 12.08516 5.21474 0.10644 S 0.0 0.0 0.081313 0.271054 -0.328909\natom 5.93447 1.10263 12.15566 S 0.0 0.0 0.286232 -0.496299 -0.273498\natom 0.06609 6.83092 6.16126 S 0.0 0.0 0.033487 -0.265203 0.459967\natom -2.76587 10.85331 11.79307 S 0.0 0.0 0.236606 -0.243204 0.798289\natom 9.10132 4.95788 6.31266 S 0.0 0.0 0.748096 -0.362291 0.006701\natom 3.30910 1.23513 7.59499 S 0.0 0.0 1.035824 0.092063 0.083380\natom 2.98211 7.18940 10.44456 S 0.0 0.0 -0.095129 -0.066502 0.501925\natom 6.05903 10.89435 4.88424 S 0.0 0.0 0.463751 -0.229201 -0.263033\natom 6.01468 4.92139 1.37132 S 0.0 0.0 -0.468987 -0.749525 0.107585\natom 6.36879 0.74906 1.24094 S 0.0 0.0 0.310955 0.020940 -0.159411\natom 6.09617 6.60835 4.95176 S 0.0 0.0 -1.035906 0.065541 0.302588\natom 3.17529 11.43602 10.89371 S 0.0 0.0 -1.083594 -0.173260 -0.047961\natom 3.30341 4.82560 7.37512 S 0.0 0.0 -1.079887 1.037804 0.107379\natom 0.07890 1.19981 9.21250 S 0.0 0.0 0.036836 -0.742948 0.043561\natom 6.13072 6.83610 8.65083 S 0.0 0.0 0.467466 0.093881 -1.245717\natom 9.46629 10.90198 2.75063 S 0.0 0.0 0.413494 0.843834 0.141010\natom 2.91274 4.88251 3.51609 S 0.0 0.0 0.516560 0.510248 0.343316\natom 2.47749 0.84218 3.27234 S 0.0 0.0 -0.294238 0.048022 0.441510\natom 9.55918 6.72564 2.52760 S 0.0 0.0 0.031178 0.759188 -0.826097\natom 6.86651 11.00197 8.75562 S 0.0 0.0 -0.388735 0.555506 -1.507087\natom -0.49613 4.97704 9.71319 S 0.0 0.0 0.401916 -0.082379 -0.024213\natom 6.32773 2.94703 8.80158 S 0.0 0.0 0.318250 -0.954028 0.875751\natom -0.22996 9.08067 9.50542 S 0.0 0.0 0.336580 0.737860 -0.336180\natom 3.01466 8.98418 3.56060 S 0.0 0.0 -0.255020 -0.139129 -0.237660\natom 9.25856 3.01141 2.49602 S 0.0 0.0 -0.237795 0.339681 0.548963\natom 5.95365 2.74183 5.30893 S 0.0 0.0 -0.342236 -0.706774 -0.735241\natom 6.33957 8.43840 1.25199 S 0.0 0.0 0.122957 0.897171 -0.589693\natom 3.39730 9.09858 7.02177 S 0.0 0.0 -0.287845 0.907897 0.132987\natom 2.62746 3.11460 11.23648 S 0.0 0.0 0.858091 -0.356245 0.024125\natom -0.06122 2.88713 5.90646 S 0.0 0.0 -0.264980 -1.005669 -0.043997\natom 12.17418 8.86226 0.01577 S 0.0 0.0 0.419422 0.009413 0.393304\natom 9.15714 8.91615 6.20708 S 0.0 0.0 0.356026 1.326317 -0.293624\natom -3.03406 3.15913 11.84785 S 0.0 0.0 0.247702 0.694820 -0.424211\natom -0.16747 2.55616 1.59513 S 0.0 0.0 0.368780 0.597668 0.091520\natom 12.46753 8.52814 4.35781 S 0.0 0.0 -0.695637 0.106041 -0.549693\natom 9.44867 9.16297 10.51369 S 0.0 0.0 0.513536 0.221546 0.277105\natom -3.25396 3.24988 7.65767 S 0.0 0.0 0.205002 0.144088 0.863088\natom 11.27168 3.33596 3.42419 Cu 0.0 0.0 0.375693 -0.434321 0.303582\natom 0.73450 9.16616 2.70459 Cu 0.0 0.0 0.555770 0.047788 0.021851\natom -2.28245 9.06332 8.35212 Cu 0.0 0.0 -0.292738 -0.109961 -0.088971\natom 8.54316 2.98101 9.52115 Cu 0.0 0.0 0.023346 0.004564 0.193232\natom 5.60867 0.81007 8.35658 Cu 0.0 0.0 -0.427253 -0.017732 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3.44327 10.24238 1.77073 Cu 0.0 0.0 -0.350057 -0.176774 -0.256603\natom -0.03280 8.81250 7.12799 Cu 0.0 0.0 -0.041940 0.420079 0.097492\natom 6.46455 3.37543 11.06979 Cu 0.0 0.0 -0.353013 0.286262 -0.382891\natom 0.93281 1.43790 11.35287 Cu 0.0 0.0 0.307421 0.333833 0.134033\natom 4.98237 7.67647 6.73481 Cu 0.0 0.0 0.646501 -0.510815 -0.073037\natom 8.22109 9.63094 1.66601 Cu 0.0 0.0 -1.147843 -1.102191 -0.619118\natom 4.02130 4.00831 5.51665 Cu 0.0 0.0 0.173977 -0.433642 -0.819676\natom 3.01648 1.21991 5.37519 Cu 0.0 0.0 0.204883 0.430032 -0.046187\natom 8.71496 7.24901 0.41989 Cu 0.0 0.0 0.028850 -0.022814 0.239184\natom 5.53143 10.22296 6.96858 Cu 0.0 0.0 0.160567 0.179981 0.538441\natom 0.85345 4.32598 11.49647 Cu 0.0 0.0 -0.538446 0.337959 0.345063\natom -1.29048 2.61315 10.23283 Cu 0.0 0.0 -0.299114 0.570145 0.723668\natom 7.69541 8.57343 7.82927 Cu 0.0 0.0 -0.729899 -0.109052 0.363813\natom 10.64911 10.02171 1.08460 Cu 0.0 0.0 0.128979 0.109735 0.435639\natom 1.47720 3.44615 4.36867 Cu 0.0 0.0 -0.114276 -0.230592 0.287064\natom 8.72304 0.21063 8.19764 Cu 0.0 0.0 -0.192633 0.367962 0.438521\natom -2.16120 6.36592 10.10799 Cu 0.0 0.0 -0.494501 0.210617 0.060073\natom 0.56732 11.61300 3.93830 Cu 0.0 0.0 0.010921 -0.343774 0.100572\natom 11.35659 5.51648 2.20087 Cu 0.0 0.0 0.498229 -0.120575 -0.029479\natom 11.56200 0.72730 2.10855 Cu 0.0 0.0 0.008456 0.072176 -0.164480\natom 1.10430 6.29081 4.35545 Cu 0.0 0.0 0.618673 -0.113613 -0.754336\natom -1.03856 0.07794 10.94100 Cu 0.0 0.0 -0.051909 -0.302481 -0.497623\natom 8.10432 6.04634 7.98365 Cu 0.0 0.0 -0.110391 -0.390517 -0.309706\natom -3.96247 2.24019 9.62523 Cu 0.0 0.0 -0.592591 0.331202 -0.089427\natom 10.22205 8.85141 8.38912 Cu 0.0 0.0 0.293962 -0.253980 0.213099\natom 13.56027 9.84290 2.83780 Cu 0.0 0.0 -0.052248 -0.059945 0.126373\natom -1.18772 3.59737 3.31697 Cu 0.0 0.0 -0.126922 0.126883 0.083608\natom 6.09030 0.88726 3.61543 Cu 0.0 0.0 0.705088 0.195842 0.805285\natom 6.59092 6.83284 2.81258 Cu 0.0 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0.507960\natom 8.34727 1.45761 12.13804 Cu 0.0 0.0 -0.243015 -0.063355 0.384000\natom -1.91304 7.87559 6.27224 Cu 0.0 0.0 0.182465 -0.125591 -0.042310\natom 1.22350 10.01820 0.09676 Cu 0.0 0.0 0.329541 0.496820 0.527121\natom 11.03890 4.23073 6.01320 Cu 0.0 0.0 0.292541 0.331663 -0.043652\natom 11.16626 1.63740 5.92045 Cu 0.0 0.0 0.082946 -0.262730 0.096357\natom 1.35930 7.49830 0.32093 Cu 0.0 0.0 0.515749 -0.127466 -0.306337\natom -0.85889 10.05124 5.32919 Cu 0.0 0.0 -1.065336 -0.557422 -0.438531\natom 14.30901 4.24465 0.08140 Cu 0.0 0.0 -0.109927 0.237845 -0.214746\natom 9.13306 2.95525 5.08939 Cu 0.0 0.0 -0.026585 0.633991 -0.361295\natom 3.35563 8.63970 1.52747 Cu 0.0 0.0 0.084884 -0.344084 -0.620736\natom 0.05199 10.35869 7.80543 Cu 0.0 0.0 0.069402 -0.307704 0.363921\natom 6.24559 2.85868 11.46795 Cu 0.0 0.0 -0.045526 0.210162 -0.045442\natom -0.90545 3.86279 7.69139 Cu 0.0 0.0 0.435370 0.040458 0.173097\natom 5.54793 7.73506 7.04433 Cu 0.0 0.0 -0.163665 -0.165320 -0.216939\natom 8.07550 10.08907 0.73957 Cu 0.0 0.0 0.274589 0.224532 -0.123789\natom 3.86209 3.99357 5.47504 Cu 0.0 0.0 0.713637 -0.120590 -0.371456\natom 3.71869 1.30131 5.20309 Cu 0.0 0.0 0.295541 0.532457 0.277208\natom 8.40070 7.55699 1.22324 Cu 0.0 0.0 0.918084 -0.017097 -0.172116\natom 5.46091 10.31389 6.88238 Cu 0.0 0.0 0.636379 0.305708 -0.274427\natom 7.51135 4.14117 0.07082 Cu 0.0 0.0 -0.806049 0.048342 0.411963\natom -0.51039 2.11068 12.19002 Cu 0.0 0.0 -0.204222 0.342347 -0.129231\natom 7.64971 8.80134 8.07465 Cu 0.0 0.0 0.024751 0.202055 -0.029493\natom 10.63996 9.17796 1.90314 Cu 0.0 0.0 -0.099927 -0.100229 -0.384760\natom 1.91044 3.03927 4.31101 Cu 0.0 0.0 -0.164463 -0.083120 -0.642104\natom 8.54230 0.59236 8.32153 Cu 0.0 0.0 0.100847 0.345645 -0.240471\natom -1.94652 6.36568 9.71590 Cu 0.0 0.0 -0.478626 0.132312 -0.016137\natom 0.70683 11.56552 3.80038 Cu 0.0 0.0 0.008461 -0.141396 -0.923532\natom 11.99474 5.27822 2.27860 Cu 0.0 0.0 -0.046479 -0.015532 -0.072183\natom 10.62870 0.31821 1.25739 Cu 0.0 0.0 -0.076343 -0.123905 0.577853\natom 1.70035 6.52242 4.52969 Cu 0.0 0.0 -0.279728 -0.075011 -0.557715\natom -3.24874 11.45552 9.69927 Cu 0.0 0.0 0.144854 -0.195696 0.557575\natom 7.73758 4.97325 7.80800 Cu 0.0 0.0 -0.044919 0.103196 0.649776\natom 10.96720 1.77377 8.69401 Cu 0.0 0.0 -0.300278 -0.312687 0.318857\natom 10.82361 8.87007 8.96418 Cu 0.0 0.0 0.231775 -0.245660 0.012344\natom 14.05468 9.39456 2.79846 Cu 0.0 0.0 0.039430 0.506389 -0.355454\natom -0.99274 3.66799 3.45835 Cu 0.0 0.0 -1.391409 -0.130586 1.244523\natom 5.85981 0.99793 3.45645 Cu 0.0 0.0 0.350906 -0.124246 -0.365691\natom 6.48697 6.99586 2.70234 Cu 0.0 0.0 -0.115451 -0.567635 0.286672\natom 2.93836 10.45460 9.06873 Cu 0.0 0.0 -0.020449 -0.147844 -0.074972\natom 2.87856 5.04724 9.79968 Cu 0.0 0.0 0.021081 0.802603 -0.883295\natom 1.29372 0.50868 8.19919 Cu 0.0 0.0 0.102742 0.247199 0.257831\natom 5.13997 6.95690 10.71659 Cu 0.0 0.0 0.318380 -0.429011 0.569694\natom 9.21189 11.04964 4.94144 Cu 0.0 0.0 -0.226220 0.047172 -0.338081\natom 4.17990 5.48315 1.65625 Cu 0.0 0.0 -0.061149 0.024759 0.018456\natom 4.10194 0.86935 1.46185 Cu 0.0 0.0 -0.325118 -0.356689 0.351853\natom 8.58370 6.73929 4.48938 Cu 0.0 0.0 -0.183253 0.073806 -0.336752\natom 5.26307 11.59673 10.20705 Cu 0.0 0.0 0.019433 -0.355420 0.226874\natom 1.13195 5.80679 7.86158 Cu 0.0 0.0 -0.111944 0.087901 -0.238204\natom 3.31937 2.27542 9.37690 Cu 0.0 0.0 -0.379342 0.001606 -0.305208\natom 3.34483 7.75485 9.18163 Cu 0.0 0.0 0.229823 0.791373 -1.131988\natom 6.39482 9.67667 3.15210 Cu 0.0 0.0 -0.094336 -0.795504 -1.057292\natom 7.22236 3.07618 3.37057 Cu 0.0 0.0 -0.235709 0.757783 -0.201253\natom 13.81610 1.37747 2.41015 Cu 0.0 0.0 -0.421134 -0.441437 0.596880\natom 13.61863 6.95911 3.36775 Cu 0.0 0.0 0.023890 -0.090556 0.088628\natom 9.66897 10.87854 9.80118 Cu 0.0 0.0 -0.033376 -0.779259 -0.024728\natom 10.82688 4.33130 8.82018 Cu 0.0 0.0 0.025061 0.077835 -0.093269\natom 0.52093 2.93256 9.86635 Cu 0.0 0.0 -0.188157 0.007009 0.046775\natom 3.05650 7.20429 6.37008 Cu 0.0 0.0 0.120817 0.632245 0.914727\natom 5.20021 10.41570 0.87518 Cu 0.0 0.0 -0.188866 0.673383 -0.290560\natom 6.42686 4.58096 5.63885 Cu 0.0 0.0 -0.033889 0.762947 -0.354041\natom 7.36790 2.66841 6.96813 Cu 0.0 0.0 -0.012373 -0.662690 0.449303\natom -1.75746 8.94560 11.22149 Cu 0.0 0.0 -0.054235 0.048564 0.114417\natom 1.59161 9.16276 5.19623 Cu 0.0 0.0 0.020031 -0.301564 0.165598\natom 10.50996 3.65139 0.92879 Cu 0.0 0.0 0.046307 0.222299 -0.224030\natom 2.01792 2.44696 1.65061 Cu 0.0 0.0 -0.342256 0.024552 0.104635\natom 10.30682 8.44864 4.52417 Cu 0.0 0.0 0.305590 0.465815 -0.017841\natom 7.37748 10.13132 10.55358 Cu 0.0 0.0 -0.193255 -0.757234 0.590322\natom -2.71285 3.62703 10.24934 Cu 0.0 0.0 0.527769 -0.745936 -0.242669\natom -2.00328 1.53124 8.67936 Cu 0.0 0.0 -0.218742 -0.112512 -0.294307\natom 8.67784 6.86853 9.57287 Cu 0.0 0.0 0.367175 0.005611 0.281933\natom 11.50050 10.89754 3.55966 Cu 0.0 0.0 0.489069 -0.022825 0.280065\natom 0.89763 4.90137 2.64962 Cu 0.0 0.0 -0.158200 0.447650 -0.491001\nenergy -565.862799\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_84\nlattice 15.394732161 0.000000000 0.000000000\nlattice 0.000000000 11.999934213 0.000000000\nlattice -6.047786257 0.000000000 12.209928816\natom 9.61168 1.01608 10.42083 S 0.0 0.0 -1.191961 0.326660 -1.181596\natom -3.21463 7.13012 7.92824 S 0.0 0.0 0.049036 -0.759072 0.181961\natom -0.42418 11.01723 1.89660 S 0.0 0.0 0.333188 0.647869 -0.641060\natom 12.57968 4.81260 4.21805 S 0.0 0.0 -0.689337 0.705370 -0.234277\natom 12.37573 0.60830 4.48839 S 0.0 0.0 0.095115 0.347347 -0.081025\natom -0.23392 7.11563 2.18372 S 0.0 0.0 0.321971 -0.092889 -0.125810\natom -3.13570 10.97664 7.97003 S 0.0 0.0 -0.416872 0.419920 0.025070\natom 9.30709 5.19093 10.26152 S 0.0 0.0 -0.754127 -0.201431 -0.317495\natom 9.13516 1.37154 6.38042 S 0.0 0.0 -1.096006 -0.210231 0.119114\natom -2.70337 6.66340 12.17485 S 0.0 0.0 -0.157448 -0.296626 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0.98887 6.80797 9.65854 Cu 0.0 0.0 0.315449 0.420092 0.858395\natom 3.98611 11.29356 4.10338 Cu 0.0 0.0 -0.059508 -0.194572 -0.276054\natom 8.64481 4.91039 2.26137 Cu 0.0 0.0 -0.328978 0.165652 0.435556\natom 8.75433 1.02416 1.86991 Cu 0.0 0.0 -0.162032 0.422745 0.038880\natom 4.00536 7.36720 4.38927 Cu 0.0 0.0 -0.419183 -0.459053 -0.186304\natom 0.88893 11.18860 10.19854 Cu 0.0 0.0 0.031607 0.013853 -0.013245\natom 5.40073 4.66855 8.09789 Cu 0.0 0.0 -0.310233 0.364814 0.004740\natom 4.87332 3.39932 0.69978 Cu 0.0 0.0 0.290394 -0.353057 0.154532\natom 7.09795 8.93120 5.14333 Cu 0.0 0.0 -0.138698 0.057681 -0.002073\natom 3.70509 9.16447 11.39834 Cu 0.0 0.0 0.437228 0.207239 0.318415\natom 2.14836 3.16801 6.88630 Cu 0.0 0.0 0.123592 0.057810 0.339965\natom -4.01817 0.82592 11.54874 Cu 0.0 0.0 1.075584 0.120868 0.176741\natom 9.89746 7.31258 6.48309 Cu 0.0 0.0 -0.066838 0.070502 0.539386\natom 12.83146 10.85639 0.92260 Cu 0.0 0.0 -0.084247 -1.064775 -0.010222\natom -0.85835 5.29316 5.27531 Cu 0.0 0.0 0.266740 0.088528 0.150937\natom -0.96231 0.67333 5.44880 Cu 0.0 0.0 -0.125972 -0.190869 -0.229224\natom 13.27310 6.79948 0.98173 Cu 0.0 0.0 0.313132 0.102051 -0.307492\natom 10.35055 11.21868 6.73618 Cu 0.0 0.0 -0.021537 0.094407 0.324178\natom -4.07327 5.24861 11.02907 Cu 0.0 0.0 0.502192 -0.418966 0.619331\natom 14.59142 1.31024 0.24868 Cu 0.0 0.0 -0.068794 0.045746 -0.445258\natom -1.74385 7.33635 6.30245 Cu 0.0 0.0 -0.103437 0.578930 -0.038327\natom -3.35489 8.70890 11.45086 Cu 0.0 0.0 -0.023471 0.541481 -0.089149\natom 11.31328 4.92819 6.00106 Cu 0.0 0.0 0.124277 -0.354520 0.331290\natom 11.25926 1.71899 6.14910 Cu 0.0 0.0 0.576058 0.153646 0.284591\natom 0.98756 7.18957 0.34767 Cu 0.0 0.0 0.148718 -0.153860 -0.137073\natom -1.89896 10.08005 6.27442 Cu 0.0 0.0 0.269953 0.252167 0.119336\natom 14.82866 4.39039 0.09180 Cu 0.0 0.0 -0.340573 0.056927 -0.147375\natom 8.87065 3.15774 4.77775 Cu 0.0 0.0 0.162618 -0.061351 -0.073613\natom 4.26291 8.24195 1.31598 Cu 0.0 0.0 -0.565867 -0.359922 0.446488\natom 0.22021 8.94420 7.17875 Cu 0.0 0.0 -0.009841 -0.048517 -0.177917\natom 6.40085 2.98501 11.36531 Cu 0.0 0.0 -0.043523 0.040280 0.578155\natom 0.68234 1.70256 11.28986 Cu 0.0 0.0 -0.186826 -0.000683 0.598754\natom 5.26580 7.81845 6.92142 Cu 0.0 0.0 -0.445676 0.563885 -0.652128\natom 7.95813 10.36362 0.83491 Cu 0.0 0.0 0.260321 0.279152 0.286081\natom 4.02707 4.53549 5.72216 Cu 0.0 0.0 0.303080 -0.344855 -0.551618\natom 4.88474 0.93701 5.70079 Cu 0.0 0.0 0.230608 -0.147864 0.000888\natom 8.40394 7.67556 0.92211 Cu 0.0 0.0 0.254484 -0.067652 -0.202682\natom 5.45731 10.49026 6.43732 Cu 0.0 0.0 -0.319092 -0.150872 0.710175\natom 1.92198 5.32701 11.97658 Cu 0.0 0.0 -0.166622 -0.121822 -0.420830\natom -1.69666 2.70600 10.16369 Cu 0.0 0.0 0.358334 -0.239200 -0.109338\natom 7.73517 8.65378 7.88721 Cu 0.0 0.0 0.014459 0.573296 -0.606470\natom 10.68735 9.34588 1.74641 Cu 0.0 0.0 -0.439726 -0.201238 -0.448797\natom 3.64684 3.23269 3.42151 Cu 0.0 0.0 -0.105829 0.453683 0.248434\natom 8.16102 0.46510 8.73219 Cu 0.0 0.0 0.192188 -0.096106 -0.270723\natom -1.85848 6.99743 9.97666 Cu 0.0 0.0 -0.218796 -0.500547 0.105423\natom 0.44296 10.99190 3.89648 Cu 0.0 0.0 0.053204 -0.031752 0.450723\natom 11.40933 5.64462 2.13470 Cu 0.0 0.0 -0.351827 -0.331935 0.076030\natom 11.37718 0.81774 2.06734 Cu 0.0 0.0 -0.611435 -0.193327 0.366000\natom 1.24707 3.95096 4.76029 Cu 0.0 0.0 0.324235 0.241591 -0.679982\natom -1.73266 11.65475 10.37157 Cu 0.0 0.0 0.212860 0.380882 -0.393675\natom 7.92981 5.30116 8.00521 Cu 0.0 0.0 -0.074729 0.092064 0.136868\natom -4.37850 2.67262 9.46103 Cu 0.0 0.0 0.057103 -0.274483 0.202197\natom 10.74864 8.24225 9.06354 Cu 0.0 0.0 -0.023471 -0.253329 -0.343244\natom -1.34377 9.25254 2.80510 Cu 0.0 0.0 0.066385 -0.309898 -0.212381\natom -1.25306 3.50180 3.61142 Cu 0.0 0.0 0.828273 -0.763521 -0.530900\natom 4.64858 1.24230 2.50442 Cu 0.0 0.0 -0.291803 0.025681 0.328332\natom 6.53044 7.12313 2.58618 Cu 0.0 0.0 -0.404324 -0.176835 0.114015\natom 3.42063 11.23257 8.81961 Cu 0.0 0.0 -0.139718 -0.054750 0.343706\natom 1.61485 4.27536 9.16077 Cu 0.0 0.0 0.642162 0.094405 0.089876\natom 1.26903 0.78491 7.43404 Cu 0.0 0.0 -1.098981 -0.221546 0.289553\natom 5.44186 6.51461 10.64828 Cu 0.0 0.0 -0.234590 0.410853 -0.301251\natom 8.72291 11.76178 4.86728 Cu 0.0 0.0 -0.175245 -0.098272 -0.519528\natom 4.27688 5.51884 1.91924 Cu 0.0 0.0 -0.221023 0.180796 0.180334\natom 1.77230 11.62345 1.70957 Cu 0.0 0.0 0.079069 -0.087724 -0.045952\natom 8.38154 6.62650 4.33873 Cu 0.0 0.0 -0.248326 -0.078102 0.530087\natom 5.44621 11.15069 10.67735 Cu 0.0 0.0 -0.260829 0.197381 0.016748\natom 0.25174 6.00863 7.54331 Cu 0.0 0.0 -0.473189 -0.146569 -0.892481\natom 3.67802 2.75104 8.87314 Cu 0.0 0.0 0.089110 -0.140927 0.371747\natom 2.51073 8.84239 9.22448 Cu 0.0 0.0 0.304691 -0.146943 -0.082301\natom 5.64252 9.90858 2.81814 Cu 0.0 0.0 0.513423 -0.142304 0.173443\natom 6.39122 3.17193 2.99785 Cu 0.0 0.0 -0.031973 0.226428 -0.106016\natom 13.78888 1.08302 2.77159 Cu 0.0 0.0 0.380818 -0.054563 -0.043082\natom 13.12264 6.93811 3.58588 Cu 0.0 0.0 0.102637 -0.131678 0.110528\natom -4.66009 10.58928 9.71670 Cu 0.0 0.0 0.270843 0.740876 -0.231055\natom 10.75300 5.17700 8.48767 Cu 0.0 0.0 0.320537 0.022315 -0.106267\natom 4.11156 1.42512 11.60725 Cu 0.0 0.0 -0.071191 -0.081941 -0.092444\natom 2.32526 7.33053 7.02235 Cu 0.0 0.0 0.427606 0.281319 -0.144109\natom 5.26791 11.54654 0.92695 Cu 0.0 0.0 0.083201 -0.202086 -0.734203\natom 6.67048 4.91449 5.73851 Cu 0.0 0.0 0.114596 -0.072935 -0.046294\natom 7.31983 2.84405 7.11799 Cu 0.0 0.0 0.238880 -0.435311 -0.009822\natom -0.99607 9.51313 11.51918 Cu 0.0 0.0 0.286827 0.011185 -0.967809\natom 2.19299 9.57686 5.32161 Cu 0.0 0.0 0.241050 0.033235 0.022089\natom 9.93250 3.87375 0.41602 Cu 0.0 0.0 0.481727 -0.314361 -0.455733\natom 2.25099 2.16311 1.55201 Cu 0.0 0.0 -0.161767 0.376937 -0.281467\natom 10.36062 8.54543 4.32968 Cu 0.0 0.0 0.069128 -0.029650 -0.123427\natom 7.34497 9.46663 10.56599 Cu 0.0 0.0 0.041764 -0.020438 0.077561\natom -0.98405 3.73778 7.63702 Cu 0.0 0.0 0.162342 -0.121758 -0.145897\natom -2.40276 1.09063 8.20590 Cu 0.0 0.0 -0.080006 0.099818 0.070596\natom 8.38212 7.22719 9.70741 Cu 0.0 0.0 0.218579 0.053630 0.432589\natom 11.63611 10.66180 3.47400 Cu 0.0 0.0 -0.056787 0.347671 0.309465\natom 0.79475 4.80215 2.38119 Cu 0.0 0.0 0.125964 0.706002 0.158111\nenergy -566.729768\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/nnp-dataset/Cu2S_PBE/input.data",
    "content": "begin\ncomment source_file_name=OUTCAR_4_1\nlattice 15.415349658 0.000000000 0.000000000\nlattice 0.000000000 12.016005204 0.000000000\nlattice -6.055885795 0.000000000 12.226281044\natom 9.66279 1.04561 10.73808 S 0.0 0.0 0.107416 0.024235 -0.891279\natom -3.16184 6.79866 8.04560 S 0.0 0.0 0.066538 0.139566 0.120509\natom -0.30404 11.04333 1.97659 S 0.0 0.0 -0.953672 -0.464533 -1.796811\natom 12.83426 5.06839 4.33902 S 0.0 0.0 0.393296 -0.326470 -0.518344\natom 12.39515 0.83117 4.16637 S 0.0 0.0 -0.063080 -0.611946 0.506821\natom -0.04295 7.13059 1.93130 S 0.0 0.0 -0.643788 -0.077636 0.315228\natom -3.25380 10.86483 8.16358 S 0.0 0.0 0.302005 0.898190 -0.193786\natom 9.41762 5.14521 10.58660 S 0.0 0.0 -0.644394 -0.340890 -0.050007\natom 9.00831 1.11279 6.18474 S 0.0 0.0 0.511148 0.550276 -0.454197\natom 3.34802 6.99932 0.09625 S 0.0 0.0 0.108918 0.284724 0.514152\natom 0.30069 11.03010 5.97943 S 0.0 0.0 0.216866 -0.247468 0.308978\natom 12.12524 5.04060 0.14613 S 0.0 0.0 0.501229 -0.426423 -0.428415\natom 6.18973 0.76543 12.21862 S 0.0 0.0 0.711680 -0.222174 -0.534560\natom 0.27700 6.96838 5.89276 S 0.0 0.0 0.301012 0.404099 0.020448\natom -2.83579 11.33619 12.07566 S 0.0 0.0 -0.366454 -1.013699 0.180780\natom 9.11071 5.30752 5.88412 S 0.0 0.0 0.521382 -0.161316 1.257161\natom 3.29671 1.11468 7.49721 S 0.0 0.0 0.423783 0.469883 0.109794\natom 3.12703 6.91177 10.90503 S 0.0 0.0 -0.330671 0.236197 -0.223073\natom 6.12068 10.97358 4.59954 S 0.0 0.0 0.157883 -0.563474 0.377419\natom 6.40437 4.95096 1.33698 S 0.0 0.0 -0.271097 0.026027 -0.062192\natom 6.26122 0.72292 1.03040 S 0.0 0.0 0.479811 0.556269 0.374940\natom 6.11755 6.85613 4.84907 S 0.0 0.0 -0.163743 0.501150 0.586061\natom 3.26768 11.19922 10.85073 S 0.0 0.0 -0.977102 0.340434 0.160795\natom 3.52987 5.32717 7.24188 S 0.0 0.0 -0.660281 -0.466761 -0.537193\natom -0.16538 0.79379 9.67493 S 0.0 0.0 0.082621 0.738076 -0.305641\natom 6.38897 6.71555 8.70905 S 0.0 0.0 0.714567 0.858927 -0.006896\natom 9.21963 11.13097 2.41939 S 0.0 0.0 0.578520 0.128482 0.160710\natom 2.69797 5.15168 3.47535 S 0.0 0.0 0.444296 -0.868870 -0.367079\natom 2.57642 0.90122 3.58188 S 0.0 0.0 0.258623 0.391067 -0.413657\natom 9.93715 6.97306 2.74299 S 0.0 0.0 0.641907 0.681899 -0.621142\natom 6.98678 11.02130 8.74051 S 0.0 0.0 -0.283456 -0.455182 0.418023\natom -0.27493 5.08709 9.39966 S 0.0 0.0 -0.364478 0.475103 0.470787\natom 6.51424 2.93256 8.87090 S 0.0 0.0 0.248611 -0.532822 0.261379\natom -0.07028 9.08780 9.47600 S 0.0 0.0 0.334238 -1.001614 -0.353571\natom 3.02649 8.97677 3.38093 S 0.0 0.0 0.257971 0.378857 -0.128484\natom 9.22001 3.23692 3.10270 S 0.0 0.0 0.394135 -0.561144 -0.530672\natom 5.74428 2.95266 4.87537 S 0.0 0.0 0.504185 -0.767518 0.098132\natom 6.59397 8.58770 1.02620 S 0.0 0.0 -0.052306 0.889508 0.134244\natom 3.55928 9.31404 7.15633 S 0.0 0.0 0.007547 0.236500 0.509320\natom 2.96180 3.18689 11.02470 S 0.0 0.0 0.388499 0.335359 -0.153235\natom 0.00319 2.81986 5.84202 S 0.0 0.0 0.197651 -0.410017 -0.474082\natom 12.07390 8.62516 0.18008 S 0.0 0.0 0.955619 0.478197 -0.371759\natom 9.29009 9.21675 6.39687 S 0.0 0.0 -0.053343 -0.438911 -0.538072\natom -2.79943 3.30466 11.86546 S 0.0 0.0 0.397348 0.490476 0.572317\natom 0.22927 2.73487 1.72492 S 0.0 0.0 -0.311377 0.041312 -0.093182\natom 12.80848 9.20714 4.54446 S 0.0 0.0 -1.078226 -0.482916 -0.754490\natom 9.57560 8.83412 10.64965 S 0.0 0.0 -0.180223 0.207007 -0.965804\natom -3.02133 3.13287 7.77891 S 0.0 0.0 -0.431739 0.229304 -0.188167\natom 11.52491 2.71697 3.53948 Cu 0.0 0.0 -0.524195 0.593531 -0.018888\natom 0.94130 9.18527 2.48932 Cu 0.0 0.0 0.344344 -0.016827 -0.038025\natom -2.17737 8.90566 8.67171 Cu 0.0 0.0 -0.080113 -0.460384 -0.097485\natom 8.60937 2.99411 9.87382 Cu 0.0 0.0 0.242483 0.166370 -0.096114\natom 5.78704 0.81660 8.10398 Cu 0.0 0.0 -0.650869 0.037090 0.138420\natom 1.13645 6.89390 9.81986 Cu 0.0 0.0 -0.922068 -0.415802 0.004088\natom 3.98661 11.22749 4.05170 Cu 0.0 0.0 -0.169993 0.048173 -0.094445\natom 8.48776 5.35715 2.31898 Cu 0.0 0.0 -0.235778 -0.425782 -0.273045\natom 8.46457 1.29601 1.87017 Cu 0.0 0.0 -0.176692 0.115597 0.370769\natom 4.03103 6.96064 3.88549 Cu 0.0 0.0 0.138133 0.336666 0.141528\natom 0.94448 10.87127 10.21508 Cu 0.0 0.0 0.488695 0.336434 0.182050\natom 5.52896 4.74049 8.15135 Cu 0.0 0.0 -0.555966 -0.104080 -0.202623\natom 5.25495 2.85580 0.88760 Cu 0.0 0.0 -0.236780 0.111323 0.058556\natom 7.20832 9.00509 5.25253 Cu 0.0 0.0 -0.093050 -0.067663 0.112018\natom 4.02963 9.12378 11.29065 Cu 0.0 0.0 0.214455 -0.397161 -0.297440\natom 2.00869 2.95149 6.95641 Cu 0.0 0.0 0.242228 0.086186 0.256424\natom -3.59727 1.31298 11.56779 Cu 0.0 0.0 -0.234649 0.051811 -0.011230\natom 10.17489 7.11535 7.19747 Cu 0.0 0.0 -0.205621 -0.373986 -0.133792\natom 13.14051 10.69193 0.61472 Cu 0.0 0.0 -0.227511 0.015227 -0.013204\natom -0.15851 4.93004 5.03782 Cu 0.0 0.0 -0.407379 -0.188360 -0.079197\natom -1.03043 0.75778 5.49457 Cu 0.0 0.0 -0.614057 0.276670 -0.421905\natom 13.29870 6.86184 0.95026 Cu 0.0 0.0 0.173253 -0.290646 0.319586\natom 9.90736 11.28706 7.03112 Cu 0.0 0.0 0.528504 -0.034630 0.164799\natom -4.08827 5.25818 11.63154 Cu 0.0 0.0 0.507294 -0.050859 0.108014\natom 14.22568 1.81408 0.08656 Cu 0.0 0.0 0.571499 0.026055 -0.038863\natom -1.97034 7.15598 6.03887 Cu 0.0 0.0 -0.449980 0.314388 0.305998\natom -5.20546 10.47006 12.19513 Cu 0.0 0.0 0.395519 -0.013242 0.783300\natom 11.23565 4.47173 5.73470 Cu 0.0 0.0 -0.177903 -0.216022 0.218810\natom 11.50533 1.75385 6.16054 Cu 0.0 0.0 -0.082071 0.040075 -0.078104\natom 1.05145 7.68106 0.13325 Cu 0.0 0.0 0.678999 0.031254 -0.143904\natom -1.99506 10.44925 6.34486 Cu 0.0 0.0 0.240461 0.040601 0.140157\natom 14.46480 4.42495 0.30428 Cu 0.0 0.0 -0.397487 -0.006486 -0.227579\natom 9.50706 3.23697 7.16092 Cu 0.0 0.0 0.420873 -0.228470 -0.137433\natom 3.09422 9.25746 0.87162 Cu 0.0 0.0 0.083127 -0.013205 -0.008907\natom 0.08332 8.97416 7.15956 Cu 0.0 0.0 0.004363 -0.110554 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9.14403 8.20163 Cu 0.0 0.0 -0.736542 -0.170504 -0.135000\natom 8.78257 2.91894 9.94865 Cu 0.0 0.0 0.074663 0.111987 -0.087260\natom 5.44081 0.91688 8.74315 Cu 0.0 0.0 -0.180289 0.645887 -0.366148\natom 0.77289 7.30984 9.98548 Cu 0.0 0.0 -0.277405 -0.881330 0.335080\natom 3.85512 10.95899 3.91346 Cu 0.0 0.0 0.260423 0.320780 -0.193056\natom 8.53235 5.11107 2.48624 Cu 0.0 0.0 -0.058014 -0.089280 -0.050176\natom 8.43690 0.63670 1.96905 Cu 0.0 0.0 0.099391 0.927992 0.179655\natom 3.99811 6.95598 3.90500 Cu 0.0 0.0 -0.352701 -0.011541 0.050527\natom 1.18262 10.61798 10.28166 Cu 0.0 0.0 -1.094495 -0.340401 -0.726245\natom 5.10052 4.88890 8.30125 Cu 0.0 0.0 0.018158 0.149382 -0.187026\natom 5.10993 2.61008 0.77614 Cu 0.0 0.0 -0.275247 0.260318 -0.417356\natom 7.25024 8.89725 5.25590 Cu 0.0 0.0 0.639651 0.022245 0.247963\natom 4.08558 8.88878 11.36107 Cu 0.0 0.0 0.524273 0.774990 0.801272\natom 2.21835 3.02757 6.84923 Cu 0.0 0.0 -0.169081 0.275750 0.105148\natom -3.87773 0.67325 11.41533 Cu 0.0 0.0 0.251774 0.280134 0.178852\natom 9.32650 7.13585 7.16763 Cu 0.0 0.0 0.548313 -0.054311 -0.557519\natom 12.78822 11.27114 0.55769 Cu 0.0 0.0 0.294325 -0.384911 -0.009479\natom -0.88291 4.97952 5.49548 Cu 0.0 0.0 0.564377 0.282694 -0.115547\natom -0.94004 0.86817 5.17878 Cu 0.0 0.0 0.531793 -0.105153 0.480341\natom 13.50445 7.21972 0.82994 Cu 0.0 0.0 0.202768 -0.216719 0.219452\natom 10.42550 11.49942 6.83806 Cu 0.0 0.0 0.645052 -0.311437 0.297678\natom -4.02735 4.98160 11.70489 Cu 0.0 0.0 -0.046036 -0.144755 -0.350289\natom 8.20421 1.34114 12.16595 Cu 0.0 0.0 -0.136416 0.398756 0.126365\natom -1.77903 7.86620 5.88147 Cu 0.0 0.0 0.105846 -0.233096 0.554421\natom 1.66504 10.96535 0.86414 Cu 0.0 0.0 -0.184789 0.089984 -0.093283\natom 11.43269 4.94510 6.15516 Cu 0.0 0.0 0.189353 -0.287190 0.179424\natom 11.54652 1.99240 6.03084 Cu 0.0 0.0 -0.256757 -0.069354 0.081431\natom 1.32088 8.42018 0.03724 Cu 0.0 0.0 0.539276 -0.848730 0.280594\natom -2.06691 10.78843 6.10765 Cu 0.0 0.0 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0.167616\natom -1.13919 3.60534 3.37464 Cu 0.0 0.0 -0.081470 -0.216910 -0.268008\natom 5.81252 0.87416 3.69546 Cu 0.0 0.0 0.239683 -0.389727 -0.441421\natom 6.27049 6.44284 2.73448 Cu 0.0 0.0 0.593297 -0.267458 -0.209278\natom 3.31810 11.57108 8.96326 Cu 0.0 0.0 -0.094871 0.025466 -0.063309\natom 2.93597 5.49182 9.37236 Cu 0.0 0.0 -0.352565 0.166649 0.402671\natom 1.19319 0.86485 7.88775 Cu 0.0 0.0 0.112395 -0.280213 0.120366\natom 5.26044 6.78722 10.70638 Cu 0.0 0.0 0.200201 -0.557848 -0.024562\natom 8.36755 11.16562 4.67475 Cu 0.0 0.0 0.099281 0.195008 -0.022501\natom 4.26368 5.66242 1.58437 Cu 0.0 0.0 -0.713695 -0.342037 -0.255913\natom 3.94831 0.44729 1.60572 Cu 0.0 0.0 -0.373471 0.103052 0.100319\natom 8.51632 6.74447 4.54446 Cu 0.0 0.0 -0.287029 -0.070477 0.054991\natom 5.26048 11.15558 10.54689 Cu 0.0 0.0 0.010288 0.017542 0.174574\natom 0.80269 5.77855 7.91179 Cu 0.0 0.0 0.151297 -0.299896 -0.394095\natom 3.54421 2.88108 9.06926 Cu 0.0 0.0 0.134787 -0.405971 -0.278721\natom 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Cu 0.0 0.0 -0.576462 -0.180970 -0.049483\natom 7.32782 4.31071 5.82521 Cu 0.0 0.0 -0.522107 0.353251 -0.959985\natom 7.66354 2.73122 7.50603 Cu 0.0 0.0 -0.166669 0.192502 0.201686\natom -1.43250 8.41399 11.77217 Cu 0.0 0.0 0.347823 0.068297 -0.186494\natom 2.11419 9.49110 5.62346 Cu 0.0 0.0 -0.042565 0.158531 -0.223262\natom 11.03887 2.73447 1.15455 Cu 0.0 0.0 -0.117768 0.166711 0.190583\natom 2.43931 2.81590 1.89111 Cu 0.0 0.0 0.006521 0.227399 -0.415608\natom 10.21714 8.56313 4.34968 Cu 0.0 0.0 0.258534 0.100881 -0.558522\natom 7.09611 9.38395 10.57802 Cu 0.0 0.0 0.393663 0.075645 0.014443\natom -1.59050 4.06116 7.81026 Cu 0.0 0.0 0.776427 0.169641 0.044501\natom -2.15370 1.08495 8.85227 Cu 0.0 0.0 -0.251265 -0.119388 -0.127210\natom 8.67455 7.22254 10.03372 Cu 0.0 0.0 -0.079222 0.387976 -0.021438\natom 11.53372 11.21480 3.96977 Cu 0.0 0.0 -0.374950 -0.033082 -0.260344\natom 0.47515 5.15818 2.57476 Cu 0.0 0.0 0.420379 -0.030283 -0.128469\nenergy -564.447991\ncharge 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3.75629 10.61762 Cu 0.0 0.0 -0.473425 -0.110636 -0.590338\natom 1.05952 1.47514 11.44673 Cu 0.0 0.0 0.195146 -0.113334 -0.029193\natom 5.10503 7.84909 6.58179 Cu 0.0 0.0 -0.060244 0.529389 0.274714\natom 8.69693 9.23535 2.74652 Cu 0.0 0.0 0.198904 0.042220 0.139482\natom 4.18862 4.32075 5.08468 Cu 0.0 0.0 -0.687486 0.252557 0.046419\natom 3.56995 1.66576 5.17934 Cu 0.0 0.0 0.350572 0.113282 0.055055\natom 8.38102 7.55761 0.67249 Cu 0.0 0.0 0.221268 -0.096170 0.196745\natom 5.88457 10.48193 6.82940 Cu 0.0 0.0 -0.527455 -0.073681 -0.327656\natom 0.68402 4.12479 11.24727 Cu 0.0 0.0 0.274571 0.302013 0.432248\natom -1.12364 2.61442 10.69119 Cu 0.0 0.0 -0.406000 -0.415393 -0.376120\natom 7.54822 8.75270 7.69958 Cu 0.0 0.0 0.122682 -0.295042 0.353740\natom 10.67731 10.00740 1.48796 Cu 0.0 0.0 0.004412 0.290884 -0.025178\natom 1.83663 3.28932 4.22959 Cu 0.0 0.0 -0.080904 0.356566 -0.023366\natom 8.33507 0.56145 8.60945 Cu 0.0 0.0 0.114603 -0.021616 -0.355167\natom -2.04215 6.77389 9.82833 Cu 0.0 0.0 -0.007534 -0.717134 0.011035\natom 1.04834 11.37616 3.74608 Cu 0.0 0.0 -0.288259 0.230254 0.065589\natom 11.58793 5.79437 2.84809 Cu 0.0 0.0 -0.244081 -0.079537 -0.320782\natom 11.64504 0.70716 2.02330 Cu 0.0 0.0 -0.989841 -0.364179 0.552394\natom 1.11142 7.40922 4.23882 Cu 0.0 0.0 0.371931 0.133288 -0.489418\natom -1.88783 11.40659 10.34487 Cu 0.0 0.0 -0.096300 -0.299633 0.370507\natom 7.92534 5.01851 7.96233 Cu 0.0 0.0 0.356730 0.125769 -0.314713\natom -4.13829 2.80083 9.99982 Cu 0.0 0.0 0.131330 -0.067725 -0.257719\natom -4.32990 7.99757 9.60330 Cu 0.0 0.0 -0.389135 -0.044329 -0.182795\natom -1.56293 10.02503 3.28950 Cu 0.0 0.0 -0.163143 -0.170593 -0.024373\natom -1.30134 3.47561 3.73172 Cu 0.0 0.0 -0.100760 0.130375 -0.806868\natom 6.17439 1.10633 3.40005 Cu 0.0 0.0 0.336882 0.359130 0.398025\natom 6.37044 7.00825 2.48371 Cu 0.0 0.0 0.015742 -0.275627 0.324090\natom 3.44024 11.20972 8.87800 Cu 0.0 0.0 0.400193 -0.136619 -0.546082\natom 2.97105 4.56706 9.15608 Cu 0.0 0.0 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0.285689\natom 10.67763 11.28842 9.58969 Cu 0.0 0.0 -0.021239 -0.492052 0.293759\natom 10.65236 5.18394 8.51971 Cu 0.0 0.0 0.006797 -0.195878 0.204414\natom 4.18590 1.38357 11.39813 Cu 0.0 0.0 -0.375486 -0.017114 0.060248\natom 2.27516 7.42030 6.67243 Cu 0.0 0.0 0.523978 0.082577 0.237924\natom 7.84663 10.07741 0.39405 Cu 0.0 0.0 1.164994 1.031202 -0.529445\natom 6.81010 4.81633 5.60962 Cu 0.0 0.0 0.055794 -0.470187 0.015497\natom 7.14424 2.58987 7.06385 Cu 0.0 0.0 0.121366 0.070144 -0.525206\natom -1.45274 8.82216 11.02617 Cu 0.0 0.0 0.165812 0.240095 0.481689\natom 2.10769 9.84569 5.36999 Cu 0.0 0.0 -0.159444 -0.140440 0.752452\natom 10.47994 3.75604 1.23239 Cu 0.0 0.0 -0.380032 -0.307886 0.942959\natom 2.04626 2.36807 1.60570 Cu 0.0 0.0 0.448066 0.067754 -0.297946\natom 10.35379 8.55398 4.73610 Cu 0.0 0.0 -0.846167 -0.056089 -0.118372\natom 6.98392 9.10700 10.37288 Cu 0.0 0.0 0.323577 0.072657 -0.086433\natom -1.21280 3.26685 7.73503 Cu 0.0 0.0 0.632881 0.536764 -0.025554\natom 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-0.454017\natom 10.13844 7.11491 6.40231 Cu 0.0 0.0 -0.569071 0.250542 0.601601\natom 12.72990 10.98411 0.96736 Cu 0.0 0.0 -0.176046 0.318766 -0.333106\natom -0.00737 5.09788 5.75926 Cu 0.0 0.0 -0.029219 -0.200811 -0.079748\natom -0.93295 1.16232 5.26955 Cu 0.0 0.0 -0.492524 -0.633635 -0.250378\natom 13.28385 7.15458 0.66812 Cu 0.0 0.0 -0.301181 0.074160 -0.102055\natom 10.40943 11.12950 6.96072 Cu 0.0 0.0 -0.117897 -0.028344 -0.116176\natom -4.00996 5.24507 11.33974 Cu 0.0 0.0 0.012991 0.023391 -0.094382\natom 13.31640 2.97016 0.83392 Cu 0.0 0.0 -0.423414 0.150964 -0.607954\natom 12.47100 6.88116 5.74444 Cu 0.0 0.0 0.557164 -0.303740 -0.871168\natom 1.06901 10.65973 0.19548 Cu 0.0 0.0 0.012070 -0.284940 -0.273374\natom 11.29234 4.27251 5.96161 Cu 0.0 0.0 0.086863 0.332260 -0.115234\natom 11.62120 1.62573 6.08354 Cu 0.0 0.0 -0.048666 0.292079 0.471397\natom -4.65422 7.87348 11.91059 Cu 0.0 0.0 -0.960416 0.488317 -0.211798\natom -1.63735 10.42263 6.09840 Cu 0.0 0.0 -1.113106 -0.544845 -0.000427\natom 15.05717 4.96662 0.22650 Cu 0.0 0.0 -0.379133 -0.304059 0.136958\natom 9.28967 2.88898 5.08692 Cu 0.0 0.0 0.117682 0.616494 -0.306475\natom 3.16447 9.17559 1.14169 Cu 0.0 0.0 0.030456 0.037399 -0.640928\natom 0.37739 8.70188 7.70190 Cu 0.0 0.0 -0.001689 -0.201921 -0.548107\natom 5.28792 3.60439 10.55368 Cu 0.0 0.0 0.457627 -0.225015 0.531135\natom 1.03295 1.75095 11.62696 Cu 0.0 0.0 -0.173491 0.095705 -0.022558\natom 4.60570 7.55834 6.86272 Cu 0.0 0.0 0.674104 0.042332 -0.067677\natom 8.25251 10.54132 0.76591 Cu 0.0 0.0 0.114499 -0.291107 0.149544\natom 4.46596 4.18082 5.48738 Cu 0.0 0.0 -0.557451 -0.253554 0.050618\natom 3.58863 1.51455 5.07176 Cu 0.0 0.0 0.718783 0.669856 0.870525\natom 8.40039 7.59253 0.80712 Cu 0.0 0.0 0.343056 -0.036320 -0.525589\natom 5.48965 10.34826 6.97892 Cu 0.0 0.0 0.024921 -0.042790 0.317892\natom 0.80000 4.87994 11.68969 Cu 0.0 0.0 0.246354 -0.347015 0.236503\natom -1.18845 2.71278 10.31996 Cu 0.0 0.0 -0.104547 0.273178 0.306075\natom 7.74051 8.91758 8.13752 Cu 0.0 0.0 0.049964 -0.170213 -0.999522\natom 10.48370 9.12538 1.78660 Cu 0.0 0.0 -0.230378 0.303888 0.064862\natom 1.91891 3.29915 4.27351 Cu 0.0 0.0 0.103973 -0.149358 0.076156\natom 8.90773 0.68042 8.32039 Cu 0.0 0.0 -0.030220 -0.417289 -0.470863\natom -2.05926 6.88862 10.08014 Cu 0.0 0.0 -0.020613 -0.503358 -0.342970\natom 0.33878 11.19732 3.80187 Cu 0.0 0.0 -0.123164 0.282004 0.020037\natom 11.66133 5.63913 2.26741 Cu 0.0 0.0 0.299874 -0.442205 -0.049257\natom 11.00732 0.62113 2.05454 Cu 0.0 0.0 0.351663 0.228427 -0.428361\natom 1.36998 6.69689 4.18645 Cu 0.0 0.0 0.103537 0.079873 -0.356966\natom -1.86578 11.23486 10.05585 Cu 0.0 0.0 0.008994 0.332376 0.409030\natom 8.08590 5.16301 8.16202 Cu 0.0 0.0 0.423053 0.152242 -0.431543\natom -4.17281 1.86071 9.12892 Cu 0.0 0.0 -0.704965 0.135013 0.282517\natom 10.47716 8.49401 8.57627 Cu 0.0 0.0 -0.352614 0.402205 0.284235\natom 13.40013 9.15702 2.52916 Cu 0.0 0.0 0.591148 -0.035331 -0.781858\natom -0.76134 3.33565 3.84134 Cu 0.0 0.0 -0.210706 0.227822 -0.550197\natom 5.58912 1.00407 3.49382 Cu 0.0 0.0 0.373138 0.265093 0.159110\natom 6.57741 7.14653 2.56683 Cu 0.0 0.0 -0.417628 -0.291723 0.407608\natom 3.58870 10.89339 8.71247 Cu 0.0 0.0 -0.305316 0.000667 0.350551\natom 3.42368 4.98435 9.96699 Cu 0.0 0.0 -0.255185 1.082788 -0.716166\natom 1.28762 0.71788 7.99947 Cu 0.0 0.0 0.405352 -0.190991 -0.277226\natom 5.85996 6.34795 10.61468 Cu 0.0 0.0 -0.073768 -0.028163 -0.035427\natom 8.15201 11.55962 4.48578 Cu 0.0 0.0 -0.644758 -0.427102 -0.395821\natom 3.57494 4.73989 1.23786 Cu 0.0 0.0 -0.051561 0.396326 0.465236\natom 3.80726 0.43646 1.82202 Cu 0.0 0.0 -0.125559 0.146887 -0.029206\natom 8.40548 6.57428 4.21744 Cu 0.0 0.0 0.033844 0.295766 0.253862\natom 5.44343 11.21633 10.68925 Cu 0.0 0.0 0.092219 0.324847 -0.419697\natom 1.28907 5.09385 8.21174 Cu 0.0 0.0 0.381162 0.156476 0.140724\natom 3.34804 2.44109 9.26473 Cu 0.0 0.0 -0.277518 -0.018140 -0.412823\natom 2.59851 8.50015 8.96715 Cu 0.0 0.0 0.547576 0.164492 -0.235145\natom 5.46695 9.56576 3.01182 Cu 0.0 0.0 -0.207159 -0.026245 0.447183\natom 6.44944 3.62350 3.24347 Cu 0.0 0.0 -0.156367 -0.066807 -0.150968\natom -1.15831 0.90865 2.49817 Cu 0.0 0.0 -0.273470 0.402750 0.455927\natom -1.43657 6.76605 3.45714 Cu 0.0 0.0 0.143092 0.088504 -0.315961\natom 10.61313 11.13935 9.64448 Cu 0.0 0.0 0.247714 -0.513574 -0.422224\natom 10.71616 5.88205 8.81022 Cu 0.0 0.0 -0.529668 -0.693187 0.651642\natom 4.10225 1.57707 11.62967 Cu 0.0 0.0 -0.964105 -0.349743 -0.468824\natom 2.27900 6.88276 6.49927 Cu 0.0 0.0 -0.242226 0.105661 0.469384\natom 5.47666 10.56877 0.54818 Cu 0.0 0.0 -0.820864 1.388044 -0.266691\natom 6.83940 4.80600 5.57295 Cu 0.0 0.0 0.265387 -0.258445 0.065663\natom 8.00253 2.70036 7.01505 Cu 0.0 0.0 -0.779860 -0.197739 0.669692\natom -0.74210 8.04227 11.91283 Cu 0.0 0.0 -0.411558 -0.039897 -0.461576\natom 1.78696 9.71606 5.17893 Cu 0.0 0.0 0.180707 -0.015326 -0.140653\natom 10.82165 2.95042 1.22111 Cu 0.0 0.0 0.578328 0.526833 -0.807511\natom 2.16585 2.42165 1.58537 Cu 0.0 0.0 0.211844 0.052891 0.426346\natom 10.33151 8.33328 4.29213 Cu 0.0 0.0 0.170112 0.321127 -0.128360\natom 7.31421 9.55438 10.40212 Cu 0.0 0.0 -0.388305 0.078768 0.793821\natom -0.83764 3.95521 7.79240 Cu 0.0 0.0 -0.441797 -0.573566 0.419583\natom -2.06260 1.25249 8.16312 Cu 0.0 0.0 0.535082 -0.202285 -0.088209\natom 8.74820 7.00627 10.02256 Cu 0.0 0.0 -0.248813 0.245293 -0.031917\natom 11.56092 10.71251 3.58256 Cu 0.0 0.0 0.131702 -0.072963 0.190967\natom 1.00507 4.78711 2.44966 Cu 0.0 0.0 -0.447225 0.040965 -0.384033\nenergy -565.607832\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_21\nlattice 15.424131298 0.000000000 0.000000000\nlattice 0.000000000 12.022850344 0.000000000\nlattice -6.059335643 0.000000000 12.233245972\natom 9.69752 0.99718 10.31507 S 0.0 0.0 0.428489 0.864370 0.668883\natom -3.29298 7.22335 8.22515 S 0.0 0.0 -0.544722 -1.225831 -0.911920\natom -0.28490 11.25245 1.86478 S 0.0 0.0 0.547659 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2.76037 6.80089 10.96883 S 0.0 0.0 1.094328 -0.402412 -0.273848\natom 5.68820 10.79280 4.88494 S 0.0 0.0 0.801381 0.210444 -0.496512\natom 6.15976 4.81090 1.45572 S 0.0 0.0 -0.061945 -0.261604 -0.223970\natom 6.40857 0.73345 1.36879 S 0.0 0.0 0.480463 -0.015484 -0.299160\natom 6.03563 6.72053 4.92171 S 0.0 0.0 -0.417680 0.120146 0.389146\natom 3.09881 11.00716 11.14289 S 0.0 0.0 -0.891480 0.491997 -0.094117\natom 3.81478 4.90866 7.23920 S 0.0 0.0 -0.119598 0.042797 -0.066682\natom -0.11913 1.23370 9.52792 S 0.0 0.0 0.060491 -0.485502 0.640642\natom 6.40106 6.62710 9.01335 S 0.0 0.0 0.729499 0.380687 -1.668554\natom 9.52081 10.81228 2.98988 S 0.0 0.0 -0.855756 0.262232 -0.899884\natom 3.04717 5.04917 3.24171 S 0.0 0.0 1.031843 -0.420996 -0.066096\natom 2.63381 1.13804 3.35271 S 0.0 0.0 -0.025372 -1.174073 0.772809\natom 9.85008 6.87363 2.63539 S 0.0 0.0 -0.339174 -0.761700 -0.630269\natom 6.96076 10.63299 8.88377 S 0.0 0.0 -1.161484 0.729976 -1.033973\natom -0.13334 4.96537 9.69493 S 0.0 0.0 0.674174 -0.336296 -0.251820\natom 6.52311 2.47794 9.01798 S 0.0 0.0 -0.368600 0.495413 -0.415155\natom -0.34032 9.26133 9.34661 S 0.0 0.0 -0.021809 0.035197 0.079901\natom 2.96215 9.03787 3.49597 S 0.0 0.0 -0.791542 -0.321400 0.131101\natom 9.48058 2.84442 2.74864 S 0.0 0.0 -0.176657 0.007876 0.530057\natom 5.84339 2.45195 5.07287 S 0.0 0.0 0.477930 -0.166367 -0.131116\natom 6.59664 8.63061 1.20540 S 0.0 0.0 0.320953 0.243389 -0.019120\natom 3.51010 9.26075 7.38912 S 0.0 0.0 -0.193849 -0.273587 -0.566212\natom 2.89753 3.25684 10.89907 S 0.0 0.0 -0.471085 -0.501682 0.516292\natom 0.26655 3.22616 5.72619 S 0.0 0.0 -0.387580 -0.984291 -0.479125\natom 12.48509 8.66812 0.25024 S 0.0 0.0 -1.460864 0.077459 1.676333\natom 9.02451 9.17407 6.18832 S 0.0 0.0 0.798591 0.041943 0.377210\natom -2.85996 3.18226 12.19742 S 0.0 0.0 0.090256 0.383348 -0.656936\natom -0.35694 3.07919 1.69350 S 0.0 0.0 0.369782 -0.178452 -0.008726\natom 12.86472 8.88547 4.67116 S 0.0 0.0 -0.808055 -0.392928 0.316984\natom 9.44482 9.35669 10.52433 S 0.0 0.0 0.123355 0.136570 -0.495146\natom -3.02449 3.30194 7.82746 S 0.0 0.0 0.212687 0.170418 -0.175442\natom 11.67543 3.17715 3.82097 Cu 0.0 0.0 -0.132108 -0.273595 0.073435\natom 0.84980 9.08603 2.52848 Cu 0.0 0.0 0.234813 0.480321 -0.150752\natom -2.61598 9.20958 8.16868 Cu 0.0 0.0 0.323066 1.558654 0.182828\natom 8.31095 3.30571 10.14593 Cu 0.0 0.0 0.065294 -0.220710 -0.531475\natom 5.36347 0.56375 8.47158 Cu 0.0 0.0 -0.273093 -0.159461 -0.117278\natom 1.04700 7.54401 9.94402 Cu 0.0 0.0 -1.381842 0.395253 -0.408891\natom 3.61068 11.09913 3.60760 Cu 0.0 0.0 0.280395 0.348068 0.571919\natom 8.32091 5.09934 1.98609 Cu 0.0 0.0 0.512465 0.379369 0.764857\natom 8.73278 0.81142 2.02043 Cu 0.0 0.0 -0.204404 -0.102945 0.142097\natom 3.97343 7.12833 4.11889 Cu 0.0 0.0 -0.098439 -0.034560 -0.227143\natom 0.94047 11.06189 10.14298 Cu 0.0 0.0 0.334059 0.026774 0.089888\natom 6.01770 4.52176 8.06381 Cu 0.0 0.0 -0.223240 -0.163693 0.263484\natom 5.48212 2.68766 1.02042 Cu 0.0 0.0 -0.538722 0.241714 -0.276965\natom 7.10132 8.75242 5.01571 Cu 0.0 0.0 -0.128632 0.028158 0.504093\natom 4.19171 9.03316 11.47110 Cu 0.0 0.0 0.353379 -0.080336 0.119637\natom 2.16518 3.12633 6.89857 Cu 0.0 0.0 0.244781 0.219714 0.162134\natom -3.75606 0.63179 11.51750 Cu 0.0 0.0 0.048407 0.763425 -0.517493\natom 9.58941 6.87478 6.71054 Cu 0.0 0.0 0.219831 0.234185 -0.445892\natom 13.06049 11.03756 1.02745 Cu 0.0 0.0 -0.079314 -0.677939 0.286754\natom -0.78852 5.13166 5.22801 Cu 0.0 0.0 0.352833 0.379884 0.287873\natom -1.15115 1.30344 5.50785 Cu 0.0 0.0 0.380819 0.210585 -0.356781\natom 13.32304 6.68263 0.99937 Cu 0.0 0.0 0.392733 0.172661 -0.326537\natom 10.38163 11.11523 6.56486 Cu 0.0 0.0 -0.415950 -0.661426 -0.007447\natom -3.99277 5.13629 11.52678 Cu 0.0 0.0 0.080316 -0.215417 -0.053770\natom 8.38323 1.75060 12.14468 Cu 0.0 0.0 0.043482 -0.321417 -0.081744\natom 12.45114 6.85202 5.91286 Cu 0.0 0.0 -0.063381 0.145723 0.345637\natom 1.13538 10.68873 0.06046 Cu 0.0 0.0 -0.639656 -0.502632 0.278945\natom 11.25623 4.59140 6.17465 Cu 0.0 0.0 -0.167411 -0.323254 -0.088040\natom 10.74056 2.00309 7.23737 Cu 0.0 0.0 0.280785 0.289572 -0.082256\natom -5.03746 8.11584 12.01208 Cu 0.0 0.0 0.382434 -0.449550 0.445620\natom -1.94857 10.87638 5.61594 Cu 0.0 0.0 -0.285999 -0.126621 0.554910\natom 14.45612 4.56956 0.00791 Cu 0.0 0.0 -0.114656 -0.112373 0.378247\natom 9.32861 2.94473 5.03697 Cu 0.0 0.0 0.104405 -0.208697 0.101586\natom 3.08177 8.78775 1.26265 Cu 0.0 0.0 0.100098 -0.033736 -0.066842\natom 1.26045 9.79223 7.72958 Cu 0.0 0.0 -0.106339 -0.101528 0.011347\natom 6.12331 2.90073 11.91474 Cu 0.0 0.0 0.156307 -1.352597 -0.162173\natom 1.12871 1.68462 11.50637 Cu 0.0 0.0 0.069475 0.126589 -0.086201\natom 5.05905 7.48840 7.06112 Cu 0.0 0.0 0.463196 -0.016689 0.081990\natom 8.40755 10.03140 0.85379 Cu 0.0 0.0 -0.103302 0.414453 0.198273\natom 4.19600 4.03461 5.11551 Cu 0.0 0.0 -0.219619 0.038422 -0.014174\natom 3.56644 1.49862 5.41080 Cu 0.0 0.0 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0.45622 S 0.0 0.0 -0.912320 -1.003811 0.311702\natom 9.45930 8.98345 6.21662 S 0.0 0.0 -0.796992 -0.575739 0.295445\natom -2.84615 2.84786 11.96526 S 0.0 0.0 -0.799751 0.518563 0.644071\natom 0.04275 2.96022 1.49476 S 0.0 0.0 -0.785260 -0.140283 0.333171\natom 12.64196 8.61780 4.62439 S 0.0 0.0 0.159040 0.192586 1.768480\natom 9.40685 9.41478 10.64060 S 0.0 0.0 1.269105 -0.289032 -0.548124\natom -3.08889 3.27384 7.69809 S 0.0 0.0 0.430441 0.187464 0.246703\natom 11.52624 2.66955 3.63386 Cu 0.0 0.0 0.178007 0.323487 0.306316\natom 0.77625 8.96645 2.49884 Cu 0.0 0.0 -0.117896 0.201380 0.245443\natom -2.57539 9.15917 8.37379 Cu 0.0 0.0 0.729022 -0.423189 0.392675\natom 8.39756 3.13624 9.44373 Cu 0.0 0.0 0.073393 0.220707 0.312663\natom 5.61793 0.66567 8.43490 Cu 0.0 0.0 -0.249905 0.157531 -0.027465\natom 1.22492 7.00630 9.40630 Cu 0.0 0.0 -0.324409 -0.009963 0.173526\natom 4.11427 11.10460 4.04082 Cu 0.0 0.0 -0.191831 -0.238881 -0.152240\natom 8.50870 5.10563 2.16419 Cu 0.0 0.0 0.390286 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0.080560\natom 1.53664 1.72721 10.84714 Cu 0.0 0.0 0.078035 0.319768 0.369381\natom 5.22050 7.88927 6.76847 Cu 0.0 0.0 0.157444 -0.671022 0.412933\natom 7.93323 10.54466 0.49770 Cu 0.0 0.0 -0.244667 -0.368220 0.493466\natom 3.97707 4.00516 5.37104 Cu 0.0 0.0 0.487677 0.064783 -0.114850\natom 4.14569 1.27047 5.44463 Cu 0.0 0.0 -0.229985 0.329857 0.509785\natom 8.60070 7.74534 1.20477 Cu 0.0 0.0 -0.222494 0.078646 -0.059131\natom 5.46247 10.32666 6.77296 Cu 0.0 0.0 0.389763 0.678031 -0.028391\natom 0.77818 4.14352 11.07585 Cu 0.0 0.0 0.710249 0.091945 0.042840\natom -2.03971 3.57901 10.07552 Cu 0.0 0.0 0.056195 0.174251 -0.306246\natom 7.52477 8.84811 7.52561 Cu 0.0 0.0 0.373785 0.022630 1.049059\natom 11.79066 8.56243 2.69914 Cu 0.0 0.0 -0.657496 -0.036112 -1.212240\natom 1.59296 3.78609 4.53421 Cu 0.0 0.0 -0.286303 -0.685100 0.139181\natom 8.25121 0.15969 8.21043 Cu 0.0 0.0 0.160832 0.013432 0.192410\natom -1.93085 6.46651 10.05052 Cu 0.0 0.0 -0.138020 0.117795 0.259108\natom 0.97360 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6.30428 Cu 0.0 0.0 -0.322831 0.139102 0.206135\natom 8.02163 10.08801 12.23225 Cu 0.0 0.0 -0.222858 0.131274 0.256342\natom -0.56212 5.14775 5.32292 Cu 0.0 0.0 -0.076425 -0.606583 0.030943\natom -0.80989 0.93651 5.32614 Cu 0.0 0.0 -0.238610 0.307378 0.097839\natom 13.22050 6.98149 0.64487 Cu 0.0 0.0 0.169634 -0.132976 -0.014427\natom 10.68960 10.99004 6.55602 Cu 0.0 0.0 -0.031273 -0.115594 0.335940\natom -3.98489 5.49480 11.84622 Cu 0.0 0.0 -0.086968 -0.378460 -0.357526\natom 8.50023 0.72367 12.08366 Cu 0.0 0.0 -0.557422 0.104888 0.767138\natom -2.28814 7.03102 6.10286 Cu 0.0 0.0 0.247534 0.091236 -0.365017\natom 1.18362 10.23521 0.06025 Cu 0.0 0.0 -0.211480 0.405759 0.032660\natom 12.41333 4.38140 6.00365 Cu 0.0 0.0 -0.256548 -0.029173 0.576026\natom 11.51756 1.83507 6.64050 Cu 0.0 0.0 -0.221897 -0.172319 -0.401036\natom -4.27596 7.93845 11.17010 Cu 0.0 0.0 -0.066611 0.205050 0.002508\natom -2.00185 10.57175 5.51422 Cu 0.0 0.0 0.265903 -0.184834 0.472879\natom 14.56384 4.46179 0.08498 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0.141225\natom 8.48774 9.23201 2.05606 Cu 0.0 0.0 0.470603 0.254027 0.207617\natom 5.39323 10.31506 7.02597 Cu 0.0 0.0 0.128387 0.525209 0.325742\natom 1.27201 4.13500 11.12724 Cu 0.0 0.0 0.100106 0.027229 0.148301\natom -1.08356 2.34871 10.36440 Cu 0.0 0.0 -0.115961 0.201545 -0.039684\natom 7.41684 9.00449 7.99731 Cu 0.0 0.0 -0.346857 -0.262197 0.497363\natom 11.91265 8.39927 2.42959 Cu 0.0 0.0 -0.131640 -0.321162 0.508974\natom 1.18746 1.93982 4.73443 Cu 0.0 0.0 0.316395 0.106054 -0.281281\natom 8.46428 0.58439 8.38410 Cu 0.0 0.0 -0.201599 -0.093222 -0.211731\natom -2.28228 6.03105 9.60677 Cu 0.0 0.0 -0.147047 0.154758 0.109189\natom 1.21645 11.58938 3.94392 Cu 0.0 0.0 0.036200 -0.091983 -0.032970\natom 11.10207 5.65120 2.47741 Cu 0.0 0.0 0.624661 -0.133601 -0.503282\natom 11.98936 0.59789 2.16769 Cu 0.0 0.0 -0.295112 0.256572 0.643703\natom 1.00043 6.73888 4.04158 Cu 0.0 0.0 0.529960 -0.354381 -0.658114\natom -2.12839 11.43922 9.97281 Cu 0.0 0.0 0.000413 -0.492403 0.310696\natom 8.12816 5.13331 8.11130 Cu 0.0 0.0 -0.210146 -0.302608 0.172841\natom 10.78163 1.78273 8.80755 Cu 0.0 0.0 -1.043324 -0.559393 0.927563\natom 10.41516 8.39121 8.64204 Cu 0.0 0.0 -0.395131 0.185406 0.035433\natom -1.53040 9.72295 3.36888 Cu 0.0 0.0 0.372856 0.130296 -0.400832\natom -1.41696 3.69703 3.19491 Cu 0.0 0.0 0.883350 -0.223926 -0.494067\natom 6.86443 1.73542 3.49266 Cu 0.0 0.0 0.244556 -0.303366 0.007376\natom 6.17918 6.97435 2.30802 Cu 0.0 0.0 0.209760 0.297266 -0.013530\natom 3.15940 10.95802 8.61593 Cu 0.0 0.0 0.193136 0.470719 0.148909\natom 2.88208 5.70957 9.23450 Cu 0.0 0.0 0.345822 -0.702524 -1.280960\natom 1.02004 12.01249 7.53204 Cu 0.0 0.0 -0.087097 0.438165 0.233971\natom 5.64859 6.84766 10.85928 Cu 0.0 0.0 -0.078639 0.031924 0.721273\natom 8.29656 11.31184 4.35364 Cu 0.0 0.0 -0.069122 0.018563 -0.176049\natom 3.67725 5.60939 1.57633 Cu 0.0 0.0 0.669505 0.757452 -1.443874\natom 4.00798 0.58669 1.47240 Cu 0.0 0.0 0.031678 0.170501 -0.276929\natom 8.25979 6.53135 4.39946 Cu 0.0 0.0 0.121604 -0.341586 -0.191260\natom 5.39557 11.25483 10.68752 Cu 0.0 0.0 -0.291604 -0.204365 -0.334073\natom 0.69703 5.65959 7.86760 Cu 0.0 0.0 -0.169854 -0.013095 -0.561101\natom 3.58008 2.31552 9.18250 Cu 0.0 0.0 0.116022 -0.224291 -0.555338\natom 3.05372 8.56933 9.43560 Cu 0.0 0.0 -0.411349 -0.314710 -0.570380\natom 5.68123 9.41030 3.31150 Cu 0.0 0.0 0.618118 -0.382904 -0.575557\natom 5.80858 4.17257 3.20862 Cu 0.0 0.0 0.124705 0.093073 -0.161157\natom -0.92440 1.11899 2.92312 Cu 0.0 0.0 0.062937 0.078153 0.035106\natom -1.44711 7.09351 3.54192 Cu 0.0 0.0 -0.344783 0.146651 -0.067587\natom 10.58942 10.83708 9.44404 Cu 0.0 0.0 0.459607 0.762299 -0.252833\natom 10.98782 4.51094 8.77469 Cu 0.0 0.0 -0.161489 0.006589 0.115299\natom 10.51264 2.34015 0.87372 Cu 0.0 0.0 0.354363 -0.027526 -0.319758\natom 2.56194 7.08435 6.78565 Cu 0.0 0.0 -0.177923 -0.212799 0.073616\natom 6.01815 11.05039 1.09580 Cu 0.0 0.0 -0.430044 1.160378 0.444636\natom 6.69093 4.86762 5.60643 Cu 0.0 0.0 -0.056310 -0.085972 0.047007\natom 7.13023 2.57847 6.91158 Cu 0.0 0.0 0.637455 0.182186 -0.414937\natom -1.18043 9.53299 11.44896 Cu 0.0 0.0 0.153076 -0.123030 0.152320\natom 1.74350 9.08802 5.03185 Cu 0.0 0.0 -0.309832 0.050675 0.116414\natom 4.09435 4.72815 11.62063 Cu 0.0 0.0 -0.488835 0.401761 -0.293672\natom 2.59578 3.44791 1.65468 Cu 0.0 0.0 0.001195 -0.804295 -0.231591\natom 9.73089 8.57633 4.39194 Cu 0.0 0.0 0.036982 0.288261 0.452128\natom 7.37620 9.13211 10.85042 Cu 0.0 0.0 -0.392944 0.094802 -0.026504\natom -1.05087 3.39136 8.03506 Cu 0.0 0.0 -0.158547 0.227874 0.594507\natom -2.23135 0.98797 8.10515 Cu 0.0 0.0 0.302332 0.190919 0.039003\natom 8.44600 6.93280 9.76244 Cu 0.0 0.0 0.794447 0.231274 0.607530\natom 11.43175 10.56534 3.95892 Cu 0.0 0.0 -0.479032 0.815489 -0.428313\natom 0.56312 5.02524 2.03818 Cu 0.0 0.0 0.206743 -0.955342 0.150812\nenergy -565.073649\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_279\nlattice 15.400727029 0.000000000 0.000000000\nlattice 0.000000000 12.004607111 0.000000000\nlattice -6.050141328 0.000000000 12.214683488\natom 9.65434 1.13629 10.42689 S 0.0 0.0 -0.027450 0.265189 0.059099\natom -3.69623 6.92843 7.97749 S 0.0 0.0 0.339291 0.304709 -0.296444\natom -0.30842 11.07389 1.81163 S 0.0 0.0 -0.347143 0.290416 -0.265011\natom 12.69913 4.92715 4.38423 S 0.0 0.0 -0.221622 0.137567 -0.221864\natom 12.81886 1.06893 3.99055 S 0.0 0.0 -0.445042 0.266383 0.093812\natom -0.18531 6.99544 1.90757 S 0.0 0.0 0.143616 0.002630 -0.419620\natom -2.90946 10.95025 7.86991 S 0.0 0.0 -0.270380 0.623666 0.222735\natom 9.57120 5.13156 10.74113 S 0.0 0.0 0.229174 -0.046146 -0.018056\natom 9.05460 0.97974 6.19685 S 0.0 0.0 0.481142 0.398229 0.331226\natom -3.06588 7.00845 11.87544 S 0.0 0.0 0.597812 -0.917245 0.172220\natom 0.42980 11.01015 6.07632 S 0.0 0.0 -0.133291 -0.160642 -0.311381\natom 11.78799 4.99460 0.01902 S 0.0 0.0 0.873595 0.681268 0.337014\natom 12.15741 1.15010 0.35007 S 0.0 0.0 -0.533612 -0.776279 0.057191\natom 0.21000 6.72252 6.13407 S 0.0 0.0 0.050020 0.620973 -0.365571\natom -2.81709 10.91384 12.20682 S 0.0 0.0 0.804004 -0.174437 -0.129138\natom 9.01094 4.82929 6.42686 S 0.0 0.0 0.290862 0.045045 -0.468485\natom 3.52205 0.72389 7.42145 S 0.0 0.0 -0.706904 0.747540 0.274162\natom 2.77862 6.94939 11.04289 S 0.0 0.0 0.696009 0.196816 -1.191073\natom 5.69056 11.08645 4.73966 S 0.0 0.0 1.228142 -0.081054 0.284577\natom 6.10330 4.86873 1.26284 S 0.0 0.0 -0.348331 0.574917 0.823367\natom 6.48304 0.87752 1.20088 S 0.0 0.0 -1.205732 -0.362291 -0.851227\natom 5.92901 6.66692 5.13927 S 0.0 0.0 0.547833 0.519141 -0.525032\natom 3.07500 11.16805 11.17593 S 0.0 0.0 -0.212242 -0.190401 0.271072\natom 3.16284 5.16247 7.09927 S 0.0 0.0 0.588442 -0.756420 0.612938\natom 0.03720 0.67302 9.60886 S 0.0 0.0 0.314782 0.360945 0.404808\natom 6.36915 7.02952 8.99250 S 0.0 0.0 -0.007432 0.203433 -0.383531\natom 9.53633 10.91032 3.10898 S 0.0 0.0 -0.378398 0.163635 -0.149693\natom 3.25425 4.97004 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0.426950 -1.191887\natom 9.06005 8.90682 6.36594 S 0.0 0.0 0.486279 -0.637644 -1.151151\natom -2.57506 2.76632 11.81978 S 0.0 0.0 -0.503384 0.777826 0.249587\natom 0.25132 3.12716 1.48115 S 0.0 0.0 -0.608301 0.109693 0.098321\natom 12.32916 8.79573 4.13935 S 0.0 0.0 -0.474549 0.731131 1.726422\natom 9.27795 9.47557 10.55517 S 0.0 0.0 -0.338265 -0.093140 0.046796\natom -3.15825 2.63234 7.82168 S 0.0 0.0 0.021963 -0.095534 -0.521092\natom 11.34384 2.78908 3.49134 Cu 0.0 0.0 0.266402 0.203551 0.017728\natom 0.47052 9.09979 2.61623 Cu 0.0 0.0 0.054596 -0.163264 -0.200579\natom -2.32029 8.85643 8.46865 Cu 0.0 0.0 0.117873 -0.638327 0.121556\natom 8.49454 3.25681 10.00919 Cu 0.0 0.0 0.300843 -0.311172 -0.223946\natom 5.45084 1.27657 8.42583 Cu 0.0 0.0 0.615805 0.295081 0.036292\natom 0.82063 6.87439 9.97517 Cu 0.0 0.0 -0.278155 -0.090576 -0.276165\natom 3.81072 10.79548 3.67498 Cu 0.0 0.0 -0.716326 0.710999 -0.232144\natom 7.92842 4.97030 2.53819 Cu 0.0 0.0 0.582939 -0.122379 0.115492\natom 8.38814 0.81594 2.05597 Cu 0.0 0.0 1.087838 -0.069441 0.729638\natom 4.02764 7.41026 4.45263 Cu 0.0 0.0 -0.375365 0.294501 -0.662878\natom 1.09170 10.70841 10.12471 Cu 0.0 0.0 -0.096600 -0.101774 -0.010295\natom 5.29100 5.16403 8.07640 Cu 0.0 0.0 -0.083630 -0.100913 0.265753\natom 5.41270 2.75931 0.72858 Cu 0.0 0.0 -0.029070 -0.044443 0.283989\natom 7.16192 9.32876 5.24564 Cu 0.0 0.0 -0.205326 -0.106932 0.193270\natom 4.25522 9.22371 11.54870 Cu 0.0 0.0 -0.110040 0.003881 -0.279273\natom 2.46996 2.86206 6.92385 Cu 0.0 0.0 -0.437845 0.058486 -0.186360\natom -3.69824 0.93079 11.51239 Cu 0.0 0.0 -0.528848 -0.553449 -0.476950\natom 8.18162 7.24408 7.58625 Cu 0.0 0.0 -0.066860 -0.017268 -0.020829\natom 13.01532 11.05932 0.49142 Cu 0.0 0.0 0.193724 -0.171706 0.316688\natom -0.43528 4.76027 5.25475 Cu 0.0 0.0 -0.014576 -0.355329 -0.064321\natom -0.91878 0.67847 5.48290 Cu 0.0 0.0 -0.285952 0.149133 -0.267101\natom 13.42130 6.64028 0.35803 Cu 0.0 0.0 0.077954 0.188468 0.565580\natom 10.55055 11.38916 6.88428 Cu 0.0 0.0 -0.183498 0.144817 -0.245487\natom -3.36792 4.81748 11.17599 Cu 0.0 0.0 -0.543630 -0.230396 0.405871\natom 8.21425 1.65171 12.19874 Cu 0.0 0.0 0.643216 -0.192794 -0.201816\natom 11.80791 6.92370 5.31055 Cu 0.0 0.0 0.253792 0.084301 0.386113\natom -5.08359 10.78705 12.13169 Cu 0.0 0.0 -0.287906 -0.201018 0.252104\natom 11.31575 4.59021 6.09702 Cu 0.0 0.0 -0.367090 -0.498877 0.099718\natom 11.47516 1.68583 5.88820 Cu 0.0 0.0 -0.069929 -0.086020 -0.247185\natom -5.44689 7.82624 11.94118 Cu 0.0 0.0 -0.149588 -0.247335 0.340774\natom -2.18526 9.88681 6.08793 Cu 0.0 0.0 0.088100 -0.104267 -0.641500\natom 14.08306 4.12963 0.16499 Cu 0.0 0.0 -0.114203 0.641912 0.116931\natom 9.29780 3.00009 4.99117 Cu 0.0 0.0 -0.027990 0.079308 0.087680\natom 2.69882 8.77207 0.78791 Cu 0.0 0.0 -0.043134 1.043673 0.739696\natom 0.17794 8.95078 6.89682 Cu 0.0 0.0 -0.516005 -0.436177 0.460935\natom 6.06030 3.02882 11.17722 Cu 0.0 0.0 0.021239 -0.557262 -0.148721\natom 1.33702 1.70640 11.35346 Cu 0.0 0.0 -0.173388 0.140541 -0.189028\natom 5.11245 7.74479 6.93217 Cu 0.0 0.0 0.421601 0.056960 0.113577\natom 8.24396 10.34956 1.21142 Cu 0.0 0.0 0.182989 -0.305282 -0.034122\natom 4.38653 4.15265 5.40633 Cu 0.0 0.0 -0.153409 0.294314 0.143012\natom 3.90180 1.60979 5.13212 Cu 0.0 0.0 0.121887 -0.408556 -0.086019\natom 8.56950 7.30516 0.96892 Cu 0.0 0.0 -0.348738 0.297050 0.376032\natom 5.95239 10.92008 7.04416 Cu 0.0 0.0 -0.295917 -0.246031 -0.626765\natom 0.88052 4.37533 11.53395 Cu 0.0 0.0 0.226771 -0.072623 -0.840530\natom -1.01699 2.80331 10.20025 Cu 0.0 0.0 0.586820 -0.568188 0.271337\natom 8.45376 10.06381 8.04991 Cu 0.0 0.0 -0.608008 0.349645 0.594028\natom 10.91943 8.19009 1.63815 Cu 0.0 0.0 -0.622651 -0.182141 0.406856\natom 2.17443 3.29759 4.35635 Cu 0.0 0.0 -0.666198 -0.221666 0.294757\natom 8.76230 0.53596 8.40783 Cu 0.0 0.0 0.255561 0.533831 0.132131\natom -2.19473 6.61348 9.84131 Cu 0.0 0.0 0.082533 0.222275 -0.441892\natom 0.74102 11.61955 3.75073 Cu 0.0 0.0 0.315413 -0.176986 0.092736\natom 11.78721 5.27157 2.29624 Cu 0.0 0.0 0.141177 -0.080132 0.020972\natom 10.83954 0.42471 2.18170 Cu 0.0 0.0 0.856780 0.201493 -0.149031\natom 1.54432 6.78331 4.27307 Cu 0.0 0.0 -0.093575 0.398207 0.124091\natom -2.23069 10.97328 10.04453 Cu 0.0 0.0 0.312285 0.099643 0.231177\natom 9.66209 5.04106 8.47482 Cu 0.0 0.0 0.209062 0.299418 0.707911\natom -4.23381 2.81476 9.81062 Cu 0.0 0.0 -0.349520 -0.109296 -0.047465\natom 10.12146 8.40247 8.83273 Cu 0.0 0.0 0.633616 -0.643772 -0.017811\natom -1.01264 8.12579 4.66389 Cu 0.0 0.0 0.376057 -0.256776 0.294272\natom -1.28669 4.13849 2.86920 Cu 0.0 0.0 0.009072 -0.291488 -0.248712\natom 6.06333 1.16828 3.37770 Cu 0.0 0.0 -0.086179 -0.208226 0.642861\natom 6.36806 6.97257 2.76006 Cu 0.0 0.0 -0.069933 0.429001 0.190181\natom 3.54527 10.71041 8.94148 Cu 0.0 0.0 0.041255 0.220004 0.011190\natom 3.03101 5.15533 9.44897 Cu 0.0 0.0 -0.030281 -0.085289 0.209628\natom 0.89000 0.70574 7.43576 Cu 0.0 0.0 0.308386 0.408788 0.568117\natom 5.10691 6.72910 10.85439 Cu 0.0 0.0 -0.247390 0.012722 -0.115851\natom 8.09573 11.66333 4.74762 Cu 0.0 0.0 -0.380796 -0.187217 -0.497365\natom 3.89861 5.65300 1.38974 Cu 0.0 0.0 0.206767 0.733346 -1.712023\natom 3.72861 0.65856 1.35498 Cu 0.0 0.0 0.199741 0.023604 0.568100\natom 8.87537 6.49500 4.85784 Cu 0.0 0.0 0.065586 0.173447 0.448166\natom 5.28922 11.61664 10.73261 Cu 0.0 0.0 0.382254 -0.121849 -0.149241\natom 1.01401 5.20040 7.88581 Cu 0.0 0.0 -0.266200 -0.116373 0.002711\natom 3.35006 2.22894 9.18589 Cu 0.0 0.0 -0.329387 0.110881 0.372311\natom 3.28298 8.22004 9.04472 Cu 0.0 0.0 -0.173302 -0.476694 1.180064\natom 5.97588 9.72319 2.92188 Cu 0.0 0.0 0.418192 -0.520572 0.038207\natom 5.63801 3.59003 3.25572 Cu 0.0 0.0 0.341480 0.255657 -0.204462\natom -0.58736 1.48686 2.64282 Cu 0.0 0.0 -0.428627 -0.597132 0.281811\natom 13.26234 8.59716 2.25889 Cu 0.0 0.0 1.192576 -0.144180 -0.356367\natom 10.66361 10.90208 9.36498 Cu 0.0 0.0 -0.021550 -0.079435 0.266917\natom -3.03723 4.70978 8.54988 Cu 0.0 0.0 -0.353626 0.492962 -0.318408\natom 3.86555 1.26076 12.11565 Cu 0.0 0.0 -0.394991 0.031432 -0.551437\natom 2.48989 7.28693 6.71758 Cu 0.0 0.0 -0.474364 0.241244 -0.225704\natom 5.63424 10.87951 0.67509 Cu 0.0 0.0 -0.170893 -0.253830 -0.082775\natom 7.03761 4.76715 5.21144 Cu 0.0 0.0 -0.279416 -0.661557 -0.067166\natom 7.63233 2.67356 7.19500 Cu 0.0 0.0 0.266248 -0.279091 -0.202780\natom -1.09448 8.23442 11.39464 Cu 0.0 0.0 -0.000643 0.172447 0.257186\natom 1.65589 9.49824 5.00695 Cu 0.0 0.0 0.339049 -0.179186 -0.445788\natom 10.29569 3.62937 0.86254 Cu 0.0 0.0 -0.297019 -0.093742 0.347960\natom 2.58193 3.17311 1.89072 Cu 0.0 0.0 0.358917 -0.456653 -0.602447\natom 9.05373 8.73571 3.57224 Cu 0.0 0.0 -0.153146 0.452311 0.000540\natom 5.94399 9.25011 9.24171 Cu 0.0 0.0 -0.116690 0.325987 -0.143172\natom -0.87653 3.40259 7.81309 Cu 0.0 0.0 0.268177 -0.269184 -1.093559\natom -1.64270 0.94564 8.22072 Cu 0.0 0.0 -0.406635 0.049550 -0.029093\natom 8.26660 6.91319 10.21133 Cu 0.0 0.0 0.426108 -0.045893 -0.236280\natom 11.88806 11.08188 4.22145 Cu 0.0 0.0 -0.069410 -0.273711 -0.153051\natom 1.03226 5.04014 2.66085 Cu 0.0 0.0 -0.247581 0.287013 -0.203919\nenergy -565.111055\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_296\nlattice 15.463777200 0.000000000 0.000000000\nlattice 0.000000000 12.053753656 0.000000000\nlattice -6.074910447 0.000000000 12.264690081\natom 9.59413 0.96783 10.57278 S 0.0 0.0 0.346300 -0.137397 -1.121629\natom -2.68602 6.71076 7.96014 S 0.0 0.0 -1.208815 0.744476 0.423387\natom -0.06390 10.87276 2.00398 S 0.0 0.0 0.038899 0.042418 -0.360703\natom 12.69540 4.92373 4.29215 S 0.0 0.0 -0.094540 0.526336 -0.057451\natom 12.43441 0.73162 4.66904 S 0.0 0.0 0.183514 -0.372937 -0.615548\natom -0.31411 6.85536 1.70885 S 0.0 0.0 -0.196162 0.784649 0.107756\natom -3.04952 10.98798 8.00627 S 0.0 0.0 -0.282368 0.192436 -0.334371\natom 9.50949 5.18194 10.50431 S 0.0 0.0 0.670014 -0.339791 0.077834\natom 9.37229 1.06855 6.29398 S 0.0 0.0 -1.434508 0.442600 0.149486\natom 3.58489 6.97060 0.19683 S 0.0 0.0 -0.230838 0.020967 -0.281463\natom 0.38636 11.01562 6.47731 S 0.0 0.0 0.407030 0.510863 -1.058761\natom 12.49180 4.76240 0.27011 S 0.0 0.0 0.557476 0.560894 -0.507492\natom 11.79477 0.89585 0.56389 S 0.0 0.0 0.395618 -0.583010 -0.216847\natom 0.67623 6.78619 5.61587 S 0.0 0.0 -0.918958 1.053858 -0.230230\natom -2.65191 11.19793 12.24610 S 0.0 0.0 0.083320 0.103144 -0.167245\natom 9.30737 5.18932 6.08970 S 0.0 0.0 -0.232263 0.232587 0.378174\natom 3.55829 0.88378 7.45440 S 0.0 0.0 -0.575218 0.722962 0.347407\natom 3.22069 7.06875 10.85332 S 0.0 0.0 -0.006368 -0.643000 -0.013595\natom 6.51976 10.87357 4.86397 S 0.0 0.0 -0.471258 0.279518 -0.440517\natom 6.83723 4.73017 1.11176 S 0.0 0.0 -0.118580 0.665826 -0.346324\natom 6.79019 0.88680 1.11376 S 0.0 0.0 -0.462049 -0.332732 0.680211\natom 6.34702 6.86312 4.86896 S 0.0 0.0 0.908213 -0.521055 0.418192\natom 2.96397 10.88052 10.94175 S 0.0 0.0 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6.46732 8.59542 0.98026 S 0.0 0.0 0.207044 0.343762 0.506216\natom 3.40626 9.38274 7.07906 S 0.0 0.0 0.037789 -1.086407 0.613770\natom 3.14003 3.21029 11.26334 S 0.0 0.0 -0.261213 -0.204309 -0.725762\natom 0.18301 3.03193 5.83027 S 0.0 0.0 -0.796940 -0.675118 -0.251891\natom 6.25719 8.99058 12.22648 S 0.0 0.0 -0.251795 -1.357515 0.497604\natom 9.65951 9.02008 6.67172 S 0.0 0.0 -1.351429 -0.003309 0.375604\natom -2.57991 3.11694 12.20582 S 0.0 0.0 0.694278 -0.587292 -0.630484\natom -0.59588 2.38646 1.51630 S 0.0 0.0 0.747942 0.530385 -0.329014\natom 12.56786 8.87900 4.69747 S 0.0 0.0 -0.282670 0.708205 0.639604\natom 9.75649 8.98905 10.47745 S 0.0 0.0 -0.670194 0.819142 1.433553\natom -3.15157 3.18818 7.87562 S 0.0 0.0 0.082411 0.046060 0.011513\natom 11.79357 2.81586 3.88933 Cu 0.0 0.0 -0.348866 -0.155734 -0.050328\natom 0.87872 8.74121 2.44832 Cu 0.0 0.0 -0.135920 0.066824 -0.250703\natom -2.08919 8.95376 8.63595 Cu 0.0 0.0 -0.090333 -0.000479 -0.293908\natom 8.52565 3.19539 10.02838 Cu 0.0 0.0 0.297698 0.280237 0.342135\natom 5.63955 0.68693 8.59493 Cu 0.0 0.0 -0.284858 1.164875 -0.273901\natom 0.99234 7.12437 10.02156 Cu 0.0 0.0 0.291310 -0.094609 -0.154963\natom 4.26476 11.05351 4.03807 Cu 0.0 0.0 -0.135334 0.496674 0.209101\natom 9.35048 5.14152 2.78948 Cu 0.0 0.0 -0.397765 0.698479 -0.107401\natom 7.09437 3.46705 2.87700 Cu 0.0 0.0 0.154622 -0.286286 0.626391\natom 4.61235 7.62902 3.97199 Cu 0.0 0.0 -0.776719 0.739128 -0.415097\natom 0.75140 11.20110 10.45689 Cu 0.0 0.0 -0.035332 -0.347693 -0.428419\natom 5.46156 4.57165 8.35079 Cu 0.0 0.0 -0.445057 0.542046 -0.332669\natom 5.50832 2.74619 0.92811 Cu 0.0 0.0 0.008404 0.042370 0.046395\natom 7.33602 8.87388 5.51081 Cu 0.0 0.0 0.221632 -0.231389 -0.759786\natom 4.29560 9.09480 11.25367 Cu 0.0 0.0 -0.373222 0.115962 -0.016236\natom 2.02184 3.21172 6.90396 Cu 0.0 0.0 0.802661 -0.304376 -0.032985\natom -3.82786 1.17256 11.51540 Cu 0.0 0.0 0.249634 -0.138391 -0.221822\natom 10.52571 7.01357 7.10499 Cu 0.0 0.0 0.196093 -0.514237 0.069269\natom 12.73284 10.79750 1.00759 Cu 0.0 0.0 0.322784 1.110356 0.316976\natom -0.61292 5.04408 5.01739 Cu 0.0 0.0 -0.099418 -0.146983 -0.011236\natom -1.00797 0.89234 5.59127 Cu 0.0 0.0 0.659388 -0.014512 0.178730\natom 13.11639 6.88375 0.41410 Cu 0.0 0.0 0.120379 0.761308 0.151347\natom 10.25236 11.24357 7.04142 Cu 0.0 0.0 0.486852 -0.703417 0.162744\natom -3.78914 4.90979 11.64754 Cu 0.0 0.0 -0.562557 0.868287 -0.307699\natom 7.97327 1.00806 12.01927 Cu 0.0 0.0 -0.320661 -0.261778 0.669270\natom -2.66364 6.77284 5.72900 Cu 0.0 0.0 0.139583 0.019303 -0.109989\natom 1.20070 10.29289 0.05535 Cu 0.0 0.0 0.128534 -0.142367 0.170485\natom 11.56341 4.52622 6.20016 Cu 0.0 0.0 -0.422768 -0.016949 -0.036187\natom 11.38589 1.88456 6.19868 Cu 0.0 0.0 0.372210 0.381362 0.737046\natom 1.40326 7.62107 0.05935 Cu 0.0 0.0 -0.033455 0.158910 -0.065999\natom -1.58357 10.14682 6.04642 Cu 0.0 0.0 -0.379767 0.174140 -0.180950\natom 14.96000 4.73947 0.51353 Cu 0.0 0.0 0.006641 -0.111737 -0.663340\natom 9.29990 3.14755 5.15272 Cu 0.0 0.0 0.061569 -0.071409 -0.358628\natom 3.53691 9.25165 1.30906 Cu 0.0 0.0 -0.125188 0.014477 -0.355908\natom 0.12350 8.58777 6.97217 Cu 0.0 0.0 0.252618 -0.140246 0.211007\natom 6.05665 1.96577 10.95461 Cu 0.0 0.0 -0.283723 0.768305 -0.764843\natom 1.18112 1.75131 11.43049 Cu 0.0 0.0 0.333113 0.363145 -0.628417\natom 5.30761 7.55794 7.06217 Cu 0.0 0.0 0.075613 0.089545 0.076289\natom 8.25350 9.94587 0.90472 Cu 0.0 0.0 0.156252 0.411619 -0.017478\natom 4.20292 4.21519 4.99966 Cu 0.0 0.0 0.439937 0.186328 0.429797\natom 4.21872 1.27195 5.32118 Cu 0.0 0.0 -0.390136 0.091093 -0.241003\natom 8.58249 7.39808 0.79129 Cu 0.0 0.0 0.151405 0.076977 -0.139024\natom 5.41339 10.15269 6.72431 Cu 0.0 0.0 0.421021 0.246152 -0.150048\natom 1.18172 4.35109 10.91327 Cu 0.0 0.0 -0.019770 0.068034 0.017337\natom -2.18879 3.57592 9.94910 Cu 0.0 0.0 0.202534 -0.045578 0.220734\natom 7.61115 8.85323 7.83294 Cu 0.0 0.0 0.134966 -0.097336 0.851080\natom 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3.09760 Cu 0.0 0.0 0.272462 0.156177 -0.187015\natom 6.72896 6.68660 2.38717 Cu 0.0 0.0 -0.256522 -0.018980 0.335159\natom 3.67571 11.09697 8.86140 Cu 0.0 0.0 -0.088144 -0.340246 -0.388276\natom 3.12084 5.15555 9.24911 Cu 0.0 0.0 -0.184530 0.230609 1.072112\natom 1.05251 0.68247 7.85059 Cu 0.0 0.0 0.190857 0.169244 0.174255\natom 5.41042 6.02785 10.84761 Cu 0.0 0.0 -0.263230 -0.059625 0.128623\natom 8.87918 11.70123 4.72201 Cu 0.0 0.0 -0.350901 -0.217265 -0.302340\natom 4.71735 5.14723 1.62155 Cu 0.0 0.0 -0.037088 0.297995 -0.184864\natom 3.57371 1.10987 1.44231 Cu 0.0 0.0 -0.197962 -0.265239 -0.091625\natom 8.87277 6.99746 4.73890 Cu 0.0 0.0 0.146668 -0.004404 -0.370001\natom 5.79905 11.57054 10.82641 Cu 0.0 0.0 -0.057973 -0.331349 0.238891\natom 0.48660 5.87614 7.54282 Cu 0.0 0.0 0.132922 -0.203636 0.016477\natom 3.51808 2.53755 9.07380 Cu 0.0 0.0 -0.056264 -0.171712 0.096410\natom 3.21469 8.21910 8.95145 Cu 0.0 0.0 -0.033383 0.163191 -0.104063\natom 5.96330 9.79846 2.91535 Cu 0.0 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5.21104 Cu 0.0 0.0 0.245095 -0.446805 0.418171\natom 4.46850 9.26065 11.12519 Cu 0.0 0.0 0.306807 -0.334017 0.208098\natom 2.26961 3.05527 6.77589 Cu 0.0 0.0 -0.353764 0.114041 -0.013309\natom -3.90401 1.03284 11.46200 Cu 0.0 0.0 0.001015 0.337714 -0.325268\natom 10.04011 7.25985 6.84980 Cu 0.0 0.0 0.244773 -0.320630 0.146804\natom 13.21623 11.02955 0.89163 Cu 0.0 0.0 0.112597 -0.567873 -0.018682\natom -0.51286 4.85669 5.10751 Cu 0.0 0.0 0.253876 -1.088299 -0.207555\natom -1.04706 0.72587 5.52506 Cu 0.0 0.0 -0.099741 -0.138001 -0.186971\natom 13.36150 6.86658 0.76794 Cu 0.0 0.0 -0.569603 0.126375 -0.339053\natom 10.12348 11.14436 6.92507 Cu 0.0 0.0 0.593908 0.253869 -0.057492\natom -3.89692 5.17103 11.34088 Cu 0.0 0.0 0.395195 0.075991 0.300955\natom 7.87836 1.23229 12.01207 Cu 0.0 0.0 0.600315 0.231568 -0.311218\natom -2.28976 7.34384 6.19682 Cu 0.0 0.0 -0.380809 -0.111907 0.356839\natom 0.90592 10.61238 0.07715 Cu 0.0 0.0 -0.021947 -0.526168 -0.337515\natom 11.21629 4.63957 6.08514 Cu 0.0 0.0 0.631695 -0.363444 -0.142808\natom 11.47399 1.84913 6.17495 Cu 0.0 0.0 -0.256208 0.011497 0.228798\natom -4.72531 7.79138 12.13660 Cu 0.0 0.0 -0.093923 -0.235496 -0.291658\natom -1.97425 10.19444 5.89992 Cu 0.0 0.0 0.234500 0.468924 -0.024111\natom 14.39111 4.08618 0.16464 Cu 0.0 0.0 -0.556085 0.585623 -0.525095\natom 9.22431 3.12924 5.09010 Cu 0.0 0.0 -0.022337 -0.006849 0.451603\natom 3.15359 9.23676 0.94540 Cu 0.0 0.0 0.062331 -1.208447 0.413546\natom -0.14476 8.70876 6.83661 Cu 0.0 0.0 0.152332 1.033735 -0.156566\natom 4.89805 3.75290 10.52765 Cu 0.0 0.0 0.148448 -0.525528 -1.048912\natom 1.18373 1.85350 11.20431 Cu 0.0 0.0 -0.813557 -0.325455 -0.019585\natom 4.99915 8.31554 8.33002 Cu 0.0 0.0 -0.257787 -0.231200 -0.043920\natom 8.01583 10.44061 0.99761 Cu 0.0 0.0 -0.396911 -0.277273 -0.135587\natom 4.05055 4.30653 4.67827 Cu 0.0 0.0 0.299631 -0.319010 0.353422\natom 3.83077 1.60663 5.02926 Cu 0.0 0.0 0.612574 0.439723 0.812241\natom 8.32052 7.15493 0.99878 Cu 0.0 0.0 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2.46552 4.42771 Cu 0.0 0.0 -0.188209 -0.209773 0.685848\natom 2.84329 9.02647 0.89470 Cu 0.0 0.0 0.371717 0.515513 -0.026191\natom -0.34393 9.17943 7.03999 Cu 0.0 0.0 0.471892 0.582224 -0.019573\natom 5.33064 3.56966 10.70737 Cu 0.0 0.0 -0.399926 0.130172 0.596025\natom 1.05972 2.11438 10.15431 Cu 0.0 0.0 -0.718098 -0.330092 -0.354223\natom 5.10288 8.07193 6.44549 Cu 0.0 0.0 0.132556 -0.656152 -0.222280\natom 8.23428 10.62487 1.00344 Cu 0.0 0.0 -0.383120 -0.348728 0.290531\natom 4.26793 4.03251 5.37922 Cu 0.0 0.0 0.173414 0.401816 0.140236\natom 3.88090 1.48691 5.09628 Cu 0.0 0.0 0.446610 0.451931 1.046696\natom 8.68604 7.43322 0.82228 Cu 0.0 0.0 -0.057976 0.051102 0.148079\natom 5.80908 10.29903 7.15036 Cu 0.0 0.0 0.017333 0.468693 0.113093\natom 0.58906 4.28541 11.67626 Cu 0.0 0.0 0.123722 0.167641 -0.252301\natom -2.22381 3.92945 10.06964 Cu 0.0 0.0 -0.176000 -0.517677 -0.037408\natom 8.52022 8.06816 8.42355 Cu 0.0 0.0 -0.539787 -0.009521 0.329340\natom 9.41015 9.06777 2.70081 Cu 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0.185854\natom 6.72647 3.36344 3.13401 Cu 0.0 0.0 0.076229 0.649473 -0.191995\natom 13.43144 1.17425 2.35847 Cu 0.0 0.0 -0.024154 0.484279 -0.278269\natom -1.33140 7.29165 3.46685 Cu 0.0 0.0 -0.005651 0.021867 -0.144259\natom -4.56035 10.74940 9.82563 Cu 0.0 0.0 0.079017 -0.091598 -0.327849\natom 11.18471 5.03689 8.54341 Cu 0.0 0.0 -0.178459 -0.385846 0.399103\natom 3.76512 1.21307 11.84350 Cu 0.0 0.0 0.225466 0.873535 -0.175913\natom 2.73076 7.20423 7.16718 Cu 0.0 0.0 -0.256518 0.430094 -0.124481\natom 5.50669 10.83828 0.49333 Cu 0.0 0.0 0.784932 -0.382042 0.233489\natom 6.87650 4.79090 5.21529 Cu 0.0 0.0 -0.314584 0.323137 0.060103\natom 7.96189 2.92785 7.30116 Cu 0.0 0.0 -0.044054 0.067920 -0.437947\natom -1.16153 8.18641 11.26996 Cu 0.0 0.0 0.297148 0.206065 -0.040745\natom 1.84239 9.63947 5.13552 Cu 0.0 0.0 -0.125355 0.243608 0.284855\natom 11.47668 2.95602 1.20412 Cu 0.0 0.0 0.043196 0.128106 -0.338968\natom 2.24530 2.58721 1.67052 Cu 0.0 0.0 -0.205593 0.029137 0.373175\natom 10.62441 8.88619 4.88068 Cu 0.0 0.0 -1.307493 -0.356001 0.820718\natom 7.20227 9.21429 10.96714 Cu 0.0 0.0 1.033546 0.128614 -0.900206\natom -0.50952 2.99767 8.13693 Cu 0.0 0.0 0.352371 0.136043 -0.042488\natom -2.52217 0.89947 8.28566 Cu 0.0 0.0 -0.367935 -0.888869 -0.183422\natom 8.07793 6.37133 10.22021 Cu 0.0 0.0 0.262309 -0.134192 0.317673\natom 11.51480 11.05542 3.77604 Cu 0.0 0.0 0.217547 0.093776 0.155530\natom 1.04284 4.86593 2.32444 Cu 0.0 0.0 0.409966 -0.257020 0.289949\nenergy -565.869365\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_364\nlattice 15.407895943 0.000000000 0.000000000\nlattice 0.000000000 12.010195158 0.000000000\nlattice -6.052957620 0.000000000 12.220369325\natom 9.90969 0.88005 10.22538 S 0.0 0.0 0.061660 0.067318 -0.013678\natom -3.37387 6.88266 7.97768 S 0.0 0.0 0.671599 -0.033925 -0.217290\natom -0.07517 11.00717 1.84789 S 0.0 0.0 -0.796247 -0.842819 -0.270703\natom 12.83106 5.03137 4.29282 S 0.0 0.0 -0.156444 0.375730 -1.205419\natom 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7.78762 S 0.0 0.0 0.307424 0.468046 -0.003713\natom 11.73155 2.72999 3.65429 Cu 0.0 0.0 -0.205403 0.640337 -0.151061\natom 0.66613 8.60344 2.43088 Cu 0.0 0.0 0.355992 -0.185770 -0.193305\natom -2.29146 9.07539 8.56173 Cu 0.0 0.0 -0.042250 -0.301201 0.203443\natom 8.80854 2.86845 9.60856 Cu 0.0 0.0 -0.320755 -0.172987 0.168747\natom 5.30302 0.86141 8.63190 Cu 0.0 0.0 -0.108091 0.111894 -0.000144\natom 0.76235 6.97487 10.00323 Cu 0.0 0.0 0.193386 0.458556 0.543800\natom 3.73917 11.16368 3.99209 Cu 0.0 0.0 0.098091 -0.299638 -0.050441\natom 8.67336 4.89055 2.05390 Cu 0.0 0.0 -0.160631 -0.313052 -0.310123\natom 8.64053 1.22491 1.89864 Cu 0.0 0.0 -0.531404 -0.329692 0.082656\natom 3.87060 7.15001 3.98688 Cu 0.0 0.0 0.343764 -0.245635 0.192519\natom 0.86747 10.99916 10.12815 Cu 0.0 0.0 0.553844 0.504072 -0.015565\natom 5.37338 4.54608 7.96600 Cu 0.0 0.0 -0.790988 0.612881 0.188971\natom 5.30235 2.96679 0.74196 Cu 0.0 0.0 -0.279765 0.053589 0.061152\natom 7.17235 8.95634 5.48649 Cu 0.0 0.0 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0.229835\natom 5.98003 10.54222 7.01848 Cu 0.0 0.0 -0.268979 0.613439 -0.609902\natom 0.90330 4.52668 11.09130 Cu 0.0 0.0 -0.015860 -0.009756 0.061747\natom -1.32816 3.08064 10.41773 Cu 0.0 0.0 -0.493890 -0.065188 0.008047\natom 9.10624 9.49641 8.40497 Cu 0.0 0.0 -0.542911 -0.259645 -0.523702\natom 10.54298 9.22840 1.73106 Cu 0.0 0.0 0.204844 -0.051950 0.245926\natom 1.86215 3.19365 4.41637 Cu 0.0 0.0 -0.141626 0.355328 -0.128984\natom 8.65817 0.51941 8.36583 Cu 0.0 0.0 -0.022819 -0.077019 -0.417244\natom -2.29063 6.73982 10.04842 Cu 0.0 0.0 -0.249279 0.046797 0.036677\natom 0.78869 11.47440 3.73836 Cu 0.0 0.0 0.042456 0.785562 0.690769\natom 11.47010 5.64750 2.12577 Cu 0.0 0.0 0.841797 -0.701578 -0.310140\natom 11.01177 0.57843 1.86130 Cu 0.0 0.0 0.197024 -0.015556 -0.043231\natom 1.22968 6.56272 4.18906 Cu 0.0 0.0 0.397033 0.185775 -0.533834\natom -1.52602 10.80217 10.42185 Cu 0.0 0.0 0.048520 -0.018238 -0.396147\natom 7.92076 4.83320 8.23419 Cu 0.0 0.0 -0.018300 0.409796 0.050275\natom -3.94273 2.51079 9.87109 Cu 0.0 0.0 0.017620 0.266824 0.223522\natom -4.55916 7.98488 9.42777 Cu 0.0 0.0 0.221198 0.396508 0.242025\natom 13.87117 9.54453 2.93125 Cu 0.0 0.0 -0.109165 0.414871 0.021803\natom -1.40621 3.62781 3.03879 Cu 0.0 0.0 -0.153347 -0.155868 -0.157467\natom 6.05605 0.98838 3.61087 Cu 0.0 0.0 0.089056 0.351384 -0.322776\natom 6.52273 6.78567 2.73100 Cu 0.0 0.0 -0.159560 0.079069 -0.461882\natom 3.34673 10.94069 8.63529 Cu 0.0 0.0 -0.013092 -0.001600 0.434844\natom 3.01646 5.57841 9.56349 Cu 0.0 0.0 0.011887 -0.100686 -0.196458\natom 1.10921 0.20152 7.76368 Cu 0.0 0.0 -0.048169 0.377541 0.179621\natom 5.12377 6.74708 10.50326 Cu 0.0 0.0 0.292989 -0.078557 -0.046372\natom 8.33426 11.37061 4.39522 Cu 0.0 0.0 -0.309672 0.456973 1.103821\natom 4.01440 5.33921 1.45196 Cu 0.0 0.0 0.281696 -0.159501 0.221087\natom 4.17980 0.49294 1.84301 Cu 0.0 0.0 -0.708562 0.503849 0.133844\natom 8.51653 6.09526 4.09474 Cu 0.0 0.0 -0.112062 0.324024 0.920042\natom 5.80361 11.03217 11.01922 Cu 0.0 0.0 0.246308 0.819800 -0.409801\natom 0.95847 5.79446 7.92616 Cu 0.0 0.0 0.062632 -0.810195 -0.092027\natom 2.96305 2.39870 9.28766 Cu 0.0 0.0 -0.376596 -0.385463 -0.239446\natom 3.60853 8.44318 9.05850 Cu 0.0 0.0 -0.562347 -0.238037 -0.236064\natom 5.48287 9.48018 3.23817 Cu 0.0 0.0 0.111306 -0.286517 -0.380803\natom 6.21831 3.58996 3.10914 Cu 0.0 0.0 0.319425 0.713190 -0.944335\natom 13.74706 1.16261 2.84686 Cu 0.0 0.0 0.354621 -0.100438 -0.423985\natom -1.29721 7.00319 3.41310 Cu 0.0 0.0 -0.206902 0.041096 -0.118138\natom -4.68435 10.69262 9.66255 Cu 0.0 0.0 0.380924 0.151717 0.212082\natom 10.57580 4.76256 8.65377 Cu 0.0 0.0 0.531670 -0.061357 -0.271865\natom 3.71797 0.98293 11.40162 Cu 0.0 0.0 0.525492 0.658514 0.307460\natom 2.53480 7.54988 6.78049 Cu 0.0 0.0 -0.334903 -0.538353 -0.101635\natom 5.79484 10.98424 0.86999 Cu 0.0 0.0 0.006181 -0.680788 -0.287408\natom 6.64317 4.95970 5.79592 Cu 0.0 0.0 0.078628 0.412810 -0.470822\natom 7.34928 2.85016 6.85061 Cu 0.0 0.0 0.305209 -0.869851 0.282557\natom -0.96136 8.40340 11.57072 Cu 0.0 0.0 0.322996 0.123072 -0.046541\natom 1.70149 9.70799 5.02821 Cu 0.0 0.0 0.494988 -0.725456 0.395173\natom 11.19334 3.07832 0.70713 Cu 0.0 0.0 0.017619 0.066578 0.468611\natom 2.09418 2.35857 1.90076 Cu 0.0 0.0 0.590285 0.046588 0.179024\natom 10.33836 8.78125 4.31616 Cu 0.0 0.0 0.065755 -0.568139 -0.425498\natom 5.89067 9.24446 8.99449 Cu 0.0 0.0 0.523743 -0.721595 0.604441\natom -1.14274 3.80931 7.90099 Cu 0.0 0.0 0.308959 -0.339936 -0.691805\natom -2.36795 1.21533 8.28698 Cu 0.0 0.0 0.203000 0.092259 0.005930\natom 8.53458 7.21069 9.64141 Cu 0.0 0.0 -0.409408 -0.413745 -0.018811\natom 11.55690 10.92225 3.71225 Cu 0.0 0.0 0.189831 -0.055151 0.044155\natom 0.69592 4.64286 2.31510 Cu 0.0 0.0 0.344125 0.135702 -0.065281\nenergy -565.990879\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_381\nlattice 15.385741848 0.000000000 0.000000000\nlattice 0.000000000 11.992926415 0.000000000\nlattice 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0.91658 3.51003 S 0.0 0.0 -0.025710 0.218997 0.164401\natom 9.72191 7.07385 2.57166 S 0.0 0.0 0.252975 -0.489957 -0.533307\natom 6.96231 11.13555 8.52477 S 0.0 0.0 -0.102876 -0.192364 0.693199\natom -0.16488 5.00468 9.68879 S 0.0 0.0 -0.214984 -0.149486 0.200145\natom 6.20210 2.77235 8.90275 S 0.0 0.0 0.469766 0.358906 -0.272382\natom 0.03756 9.00345 9.32576 S 0.0 0.0 -0.168706 -0.326194 0.277892\natom 3.12586 9.23074 3.37204 S 0.0 0.0 -0.259214 0.082255 0.040123\natom 9.21873 3.12578 2.76508 S 0.0 0.0 0.533195 -0.199118 -0.390083\natom 5.89762 2.41070 5.31104 S 0.0 0.0 0.156862 0.784978 -0.415392\natom 6.46045 8.82153 1.01071 S 0.0 0.0 -0.092926 -0.697439 0.131623\natom 3.53235 9.36614 6.97528 S 0.0 0.0 -0.513743 0.042048 0.929375\natom 2.75437 3.11046 11.15101 S 0.0 0.0 0.244122 0.086010 -0.281202\natom 0.19551 2.85135 5.93667 S 0.0 0.0 0.027964 1.746397 0.752066\natom 12.18158 8.96670 0.13662 S 0.0 0.0 1.320401 -0.448471 -0.550601\natom 9.20715 9.29605 6.30654 S 0.0 0.0 0.048463 0.052221 -0.147774\natom -2.92174 3.34768 11.88610 S 0.0 0.0 0.050199 0.007954 0.053206\natom -0.01405 3.10105 1.74874 S 0.0 0.0 -1.256553 -0.991026 -0.911636\natom 12.54325 8.73734 4.60141 S 0.0 0.0 -0.668099 0.095902 0.446299\natom 9.62451 9.13033 10.77019 S 0.0 0.0 -0.951899 -0.199389 -1.096222\natom -3.10511 3.22896 7.68996 S 0.0 0.0 -0.191980 0.090752 0.181160\natom 11.71159 3.05493 3.42301 Cu 0.0 0.0 -0.614346 -0.362901 0.023987\natom 0.79889 9.09650 2.66785 Cu 0.0 0.0 0.238005 -0.467958 0.174566\natom -2.08133 8.83859 8.65215 Cu 0.0 0.0 -0.179033 0.047382 0.078499\natom 8.38345 2.76307 9.68602 Cu 0.0 0.0 0.229534 0.245422 0.262122\natom 5.54077 0.71040 7.81966 Cu 0.0 0.0 -0.543723 0.104156 0.062864\natom 0.99210 6.95531 9.77437 Cu 0.0 0.0 -0.602864 0.096841 -0.245447\natom 4.20764 11.27650 3.97750 Cu 0.0 0.0 -0.278442 -0.155795 -0.117456\natom 8.13159 5.19745 2.25772 Cu 0.0 0.0 0.413031 0.147334 -0.261297\natom 8.36442 1.04172 2.16453 Cu 0.0 0.0 0.107403 0.359153 0.029200\natom 4.04014 7.43026 4.19327 Cu 0.0 0.0 0.025806 -0.391033 -0.250307\natom 1.08559 10.74557 10.13730 Cu 0.0 0.0 0.244089 0.321486 0.307173\natom 5.43244 4.84036 8.49903 Cu 0.0 0.0 -0.042731 0.001572 -0.263977\natom 4.95985 2.74918 0.76036 Cu 0.0 0.0 0.650124 -0.342751 0.513306\natom 7.22194 8.55888 5.13075 Cu 0.0 0.0 0.101469 0.485354 0.064326\natom 4.08575 8.93844 11.41566 Cu 0.0 0.0 -0.063231 -0.122843 -0.190502\natom 2.43992 3.21396 7.47876 Cu 0.0 0.0 -0.077031 -0.429449 -0.733630\natom -3.69931 1.28064 11.77260 Cu 0.0 0.0 -0.000236 -0.476267 -0.203761\natom 9.59453 7.14221 6.76060 Cu 0.0 0.0 0.064258 0.528379 -0.184228\natom 12.93847 11.01270 0.90444 Cu 0.0 0.0 0.145432 0.063889 0.019712\natom -0.67141 5.34105 5.72446 Cu 0.0 0.0 0.298332 -0.441454 -0.161557\natom -1.03351 1.21550 5.48592 Cu 0.0 0.0 -0.822244 -0.480912 -0.710894\natom 13.53716 7.27495 0.93480 Cu 0.0 0.0 -0.455545 0.179711 -0.179631\natom 10.44943 11.14808 6.98596 Cu 0.0 0.0 0.042278 -0.186179 -0.387224\natom -3.95394 5.16669 11.07826 Cu 0.0 0.0 0.068204 0.464504 0.580785\natom 14.40140 1.55724 0.07078 Cu 0.0 0.0 -0.175878 0.077724 -0.485831\natom 12.39439 6.48209 5.81842 Cu 0.0 0.0 -0.038046 -0.033224 -0.289350\natom 1.04454 10.25970 0.33599 Cu 0.0 0.0 0.362430 0.420358 0.063403\natom 11.23577 4.09764 5.81212 Cu 0.0 0.0 0.196093 0.306465 0.077735\natom 11.34717 1.45856 5.99899 Cu 0.0 0.0 -0.229240 0.458238 0.843086\natom -4.88353 7.68744 12.16439 Cu 0.0 0.0 0.051403 -0.373407 0.449964\natom -2.41629 11.10057 5.98287 Cu 0.0 0.0 -0.056673 -0.124752 -0.355872\natom 14.06539 4.26781 0.26329 Cu 0.0 0.0 0.564317 -0.090832 -0.077447\natom 9.07661 3.06429 4.99900 Cu 0.0 0.0 0.095513 -0.073796 -0.030946\natom 3.26713 9.15368 1.12967 Cu 0.0 0.0 -0.131499 -0.290807 -0.245339\natom -0.75901 9.07992 5.52474 Cu 0.0 0.0 0.102919 0.030057 0.034120\natom 6.22595 3.07567 11.14685 Cu 0.0 0.0 -0.035081 -0.198247 0.345145\natom 1.04384 1.46412 11.32789 Cu 0.0 0.0 0.052973 0.431111 0.163237\natom 5.40090 7.63747 6.67094 Cu 0.0 0.0 -0.331470 0.252398 0.495228\natom 8.19074 10.20427 0.59092 Cu 0.0 0.0 0.040328 -0.185457 0.244075\natom 4.33223 4.14579 5.18777 Cu 0.0 0.0 0.336363 -0.551805 0.367652\natom 3.73865 1.60189 5.41475 Cu 0.0 0.0 -0.207445 -0.174537 -0.155598\natom 8.32237 7.46590 0.77550 Cu 0.0 0.0 0.261253 0.027276 0.048673\natom 5.56080 10.18706 6.52803 Cu 0.0 0.0 -0.120393 0.271156 0.429619\natom 0.90273 4.27241 11.65507 Cu 0.0 0.0 -0.421922 0.020559 0.088453\natom -1.32779 2.49177 10.47752 Cu 0.0 0.0 -0.066978 -0.009727 -0.291503\natom 7.50996 9.04857 7.85521 Cu 0.0 0.0 -0.114700 -0.644251 -0.023218\natom 10.73365 9.18162 1.73432 Cu 0.0 0.0 -0.426919 -0.210149 0.411827\natom 1.68706 3.88963 4.75733 Cu 0.0 0.0 0.421421 0.255337 -0.128322\natom 8.90235 0.55317 8.27384 Cu 0.0 0.0 -0.356851 0.199562 0.968593\natom -1.91232 6.50406 9.88035 Cu 0.0 0.0 -0.013697 -0.067394 0.369268\natom 0.70885 11.72524 3.95941 Cu 0.0 0.0 0.192362 0.149447 -0.950886\natom 11.46683 5.56791 2.08637 Cu 0.0 0.0 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0.666495\natom 8.74565 10.95480 4.44779 Cu 0.0 0.0 -0.025090 0.028731 0.033567\natom 3.54443 5.02070 1.41742 Cu 0.0 0.0 0.589850 0.094526 -0.614166\natom 3.89299 0.51950 1.67325 Cu 0.0 0.0 -0.211794 0.375796 0.197401\natom 8.49610 6.58551 4.36667 Cu 0.0 0.0 -0.229787 -0.505967 0.349418\natom 5.35664 11.62425 10.17223 Cu 0.0 0.0 0.338571 -0.174452 0.098649\natom 1.15555 5.17702 7.77428 Cu 0.0 0.0 -0.311910 0.969390 -0.102685\natom 3.94218 2.34269 9.26197 Cu 0.0 0.0 -0.013668 0.177291 0.664866\natom 3.02818 8.36965 9.09589 Cu 0.0 0.0 0.170657 0.738510 -0.961676\natom 6.08672 9.67955 3.02232 Cu 0.0 0.0 0.062660 0.005973 0.143035\natom 6.72045 3.34718 3.28666 Cu 0.0 0.0 0.081021 0.143585 0.156367\natom 14.07917 1.21330 2.58036 Cu 0.0 0.0 0.075805 0.108580 0.212462\natom -1.33035 7.12343 3.72602 Cu 0.0 0.0 -0.031493 -0.175596 -0.252433\natom -4.20539 10.27979 9.69921 Cu 0.0 0.0 -0.862454 -0.412546 0.637965\natom 11.05511 5.10139 8.71689 Cu 0.0 0.0 -0.367556 -0.100313 -0.305517\natom 3.50289 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0.507960\natom 8.34727 1.45761 12.13804 Cu 0.0 0.0 -0.243015 -0.063355 0.384000\natom -1.91304 7.87559 6.27224 Cu 0.0 0.0 0.182465 -0.125591 -0.042310\natom 1.22350 10.01820 0.09676 Cu 0.0 0.0 0.329541 0.496820 0.527121\natom 11.03890 4.23073 6.01320 Cu 0.0 0.0 0.292541 0.331663 -0.043652\natom 11.16626 1.63740 5.92045 Cu 0.0 0.0 0.082946 -0.262730 0.096357\natom 1.35930 7.49830 0.32093 Cu 0.0 0.0 0.515749 -0.127466 -0.306337\natom -0.85889 10.05124 5.32919 Cu 0.0 0.0 -1.065336 -0.557422 -0.438531\natom 14.30901 4.24465 0.08140 Cu 0.0 0.0 -0.109927 0.237845 -0.214746\natom 9.13306 2.95525 5.08939 Cu 0.0 0.0 -0.026585 0.633991 -0.361295\natom 3.35563 8.63970 1.52747 Cu 0.0 0.0 0.084884 -0.344084 -0.620736\natom 0.05199 10.35869 7.80543 Cu 0.0 0.0 0.069402 -0.307704 0.363921\natom 6.24559 2.85868 11.46795 Cu 0.0 0.0 -0.045526 0.210162 -0.045442\natom -0.90545 3.86279 7.69139 Cu 0.0 0.0 0.435370 0.040458 0.173097\natom 5.54793 7.73506 7.04433 Cu 0.0 0.0 -0.163665 -0.165320 -0.216939\natom 8.07550 10.08907 0.73957 Cu 0.0 0.0 0.274589 0.224532 -0.123789\natom 3.86209 3.99357 5.47504 Cu 0.0 0.0 0.713637 -0.120590 -0.371456\natom 3.71869 1.30131 5.20309 Cu 0.0 0.0 0.295541 0.532457 0.277208\natom 8.40070 7.55699 1.22324 Cu 0.0 0.0 0.918084 -0.017097 -0.172116\natom 5.46091 10.31389 6.88238 Cu 0.0 0.0 0.636379 0.305708 -0.274427\natom 7.51135 4.14117 0.07082 Cu 0.0 0.0 -0.806049 0.048342 0.411963\natom -0.51039 2.11068 12.19002 Cu 0.0 0.0 -0.204222 0.342347 -0.129231\natom 7.64971 8.80134 8.07465 Cu 0.0 0.0 0.024751 0.202055 -0.029493\natom 10.63996 9.17796 1.90314 Cu 0.0 0.0 -0.099927 -0.100229 -0.384760\natom 1.91044 3.03927 4.31101 Cu 0.0 0.0 -0.164463 -0.083120 -0.642104\natom 8.54230 0.59236 8.32153 Cu 0.0 0.0 0.100847 0.345645 -0.240471\natom -1.94652 6.36568 9.71590 Cu 0.0 0.0 -0.478626 0.132312 -0.016137\natom 0.70683 11.56552 3.80038 Cu 0.0 0.0 0.008461 -0.141396 -0.923532\natom 11.99474 5.27822 2.27860 Cu 0.0 0.0 -0.046479 -0.015532 -0.072183\natom 10.62870 0.31821 1.25739 Cu 0.0 0.0 -0.076343 -0.123905 0.577853\natom 1.70035 6.52242 4.52969 Cu 0.0 0.0 -0.279728 -0.075011 -0.557715\natom -3.24874 11.45552 9.69927 Cu 0.0 0.0 0.144854 -0.195696 0.557575\natom 7.73758 4.97325 7.80800 Cu 0.0 0.0 -0.044919 0.103196 0.649776\natom 10.96720 1.77377 8.69401 Cu 0.0 0.0 -0.300278 -0.312687 0.318857\natom 10.82361 8.87007 8.96418 Cu 0.0 0.0 0.231775 -0.245660 0.012344\natom 14.05468 9.39456 2.79846 Cu 0.0 0.0 0.039430 0.506389 -0.355454\natom -0.99274 3.66799 3.45835 Cu 0.0 0.0 -1.391409 -0.130586 1.244523\natom 5.85981 0.99793 3.45645 Cu 0.0 0.0 0.350906 -0.124246 -0.365691\natom 6.48697 6.99586 2.70234 Cu 0.0 0.0 -0.115451 -0.567635 0.286672\natom 2.93836 10.45460 9.06873 Cu 0.0 0.0 -0.020449 -0.147844 -0.074972\natom 2.87856 5.04724 9.79968 Cu 0.0 0.0 0.021081 0.802603 -0.883295\natom 1.29372 0.50868 8.19919 Cu 0.0 0.0 0.102742 0.247199 0.257831\natom 5.13997 6.95690 10.71659 Cu 0.0 0.0 0.318380 -0.429011 0.569694\natom 9.21189 11.04964 4.94144 Cu 0.0 0.0 -0.226220 0.047172 -0.338081\natom 4.17990 5.48315 1.65625 Cu 0.0 0.0 -0.061149 0.024759 0.018456\natom 4.10194 0.86935 1.46185 Cu 0.0 0.0 -0.325118 -0.356689 0.351853\natom 8.58370 6.73929 4.48938 Cu 0.0 0.0 -0.183253 0.073806 -0.336752\natom 5.26307 11.59673 10.20705 Cu 0.0 0.0 0.019433 -0.355420 0.226874\natom 1.13195 5.80679 7.86158 Cu 0.0 0.0 -0.111944 0.087901 -0.238204\natom 3.31937 2.27542 9.37690 Cu 0.0 0.0 -0.379342 0.001606 -0.305208\natom 3.34483 7.75485 9.18163 Cu 0.0 0.0 0.229823 0.791373 -1.131988\natom 6.39482 9.67667 3.15210 Cu 0.0 0.0 -0.094336 -0.795504 -1.057292\natom 7.22236 3.07618 3.37057 Cu 0.0 0.0 -0.235709 0.757783 -0.201253\natom 13.81610 1.37747 2.41015 Cu 0.0 0.0 -0.421134 -0.441437 0.596880\natom 13.61863 6.95911 3.36775 Cu 0.0 0.0 0.023890 -0.090556 0.088628\natom 9.66897 10.87854 9.80118 Cu 0.0 0.0 -0.033376 -0.779259 -0.024728\natom 10.82688 4.33130 8.82018 Cu 0.0 0.0 0.025061 0.077835 -0.093269\natom 0.52093 2.93256 9.86635 Cu 0.0 0.0 -0.188157 0.007009 0.046775\natom 3.05650 7.20429 6.37008 Cu 0.0 0.0 0.120817 0.632245 0.914727\natom 5.20021 10.41570 0.87518 Cu 0.0 0.0 -0.188866 0.673383 -0.290560\natom 6.42686 4.58096 5.63885 Cu 0.0 0.0 -0.033889 0.762947 -0.354041\natom 7.36790 2.66841 6.96813 Cu 0.0 0.0 -0.012373 -0.662690 0.449303\natom -1.75746 8.94560 11.22149 Cu 0.0 0.0 -0.054235 0.048564 0.114417\natom 1.59161 9.16276 5.19623 Cu 0.0 0.0 0.020031 -0.301564 0.165598\natom 10.50996 3.65139 0.92879 Cu 0.0 0.0 0.046307 0.222299 -0.224030\natom 2.01792 2.44696 1.65061 Cu 0.0 0.0 -0.342256 0.024552 0.104635\natom 10.30682 8.44864 4.52417 Cu 0.0 0.0 0.305590 0.465815 -0.017841\natom 7.37748 10.13132 10.55358 Cu 0.0 0.0 -0.193255 -0.757234 0.590322\natom -2.71285 3.62703 10.24934 Cu 0.0 0.0 0.527769 -0.745936 -0.242669\natom -2.00328 1.53124 8.67936 Cu 0.0 0.0 -0.218742 -0.112512 -0.294307\natom 8.67784 6.86853 9.57287 Cu 0.0 0.0 0.367175 0.005611 0.281933\natom 11.50050 10.89754 3.55966 Cu 0.0 0.0 0.489069 -0.022825 0.280065\natom 0.89763 4.90137 2.64962 Cu 0.0 0.0 -0.158200 0.447650 -0.491001\nenergy -565.862799\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_84\nlattice 15.394732161 0.000000000 0.000000000\nlattice 0.000000000 11.999934213 0.000000000\nlattice -6.047786257 0.000000000 12.209928816\natom 9.61168 1.01608 10.42083 S 0.0 0.0 -1.191961 0.326660 -1.181596\natom -3.21463 7.13012 7.92824 S 0.0 0.0 0.049036 -0.759072 0.181961\natom -0.42418 11.01723 1.89660 S 0.0 0.0 0.333188 0.647869 -0.641060\natom 12.57968 4.81260 4.21805 S 0.0 0.0 -0.689337 0.705370 -0.234277\natom 12.37573 0.60830 4.48839 S 0.0 0.0 0.095115 0.347347 -0.081025\natom -0.23392 7.11563 2.18372 S 0.0 0.0 0.321971 -0.092889 -0.125810\natom -3.13570 10.97664 7.97003 S 0.0 0.0 -0.416872 0.419920 0.025070\natom 9.30709 5.19093 10.26152 S 0.0 0.0 -0.754127 -0.201431 -0.317495\natom 9.13516 1.37154 6.38042 S 0.0 0.0 -1.096006 -0.210231 0.119114\natom -2.70337 6.66340 12.17485 S 0.0 0.0 -0.157448 -0.296626 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1.08496 9.38773 S 0.0 0.0 0.075403 -0.259372 -0.621188\natom 6.34054 6.96441 8.61398 S 0.0 0.0 0.402595 -0.723001 0.756399\natom 9.44702 11.07522 2.60649 S 0.0 0.0 0.124143 -0.220298 0.690966\natom 2.72174 5.30293 3.64982 S 0.0 0.0 0.266566 0.028388 -0.153975\natom 2.60106 0.99820 3.39868 S 0.0 0.0 0.133698 0.036970 0.506408\natom 9.67221 7.04953 2.66653 S 0.0 0.0 0.663083 0.216520 -0.406805\natom 6.55951 10.81941 8.71656 S 0.0 0.0 0.888808 -0.578877 0.126432\natom -0.43056 5.03803 9.41733 S 0.0 0.0 -0.875998 0.186108 0.476104\natom 6.23491 2.85458 9.12792 S 0.0 0.0 -0.171363 -0.175101 -0.393890\natom 0.26889 9.09982 9.39944 S 0.0 0.0 -0.960259 -0.011127 0.730988\natom 3.33550 9.12756 3.25851 S 0.0 0.0 -0.476551 0.507590 0.573442\natom 9.77520 2.96453 2.59647 S 0.0 0.0 -0.566787 -0.098178 0.053217\natom 5.79508 2.94445 5.16220 S 0.0 0.0 -0.192775 0.225588 -0.442090\natom 6.39349 8.80687 0.95628 S 0.0 0.0 0.536297 0.033054 0.478046\natom 3.57897 9.37915 7.30478 S 0.0 0.0 -0.089353 -0.299949 -0.470851\natom 2.54131 2.93520 10.85817 S 0.0 0.0 0.548588 0.635996 0.557775\natom 0.11490 2.58780 5.99619 S 0.0 0.0 -0.279109 0.432643 0.237834\natom 12.07420 8.66439 0.11760 S 0.0 0.0 0.137315 0.465733 -0.244200\natom 9.11578 9.42753 6.08890 S 0.0 0.0 0.085813 -0.380959 0.423167\natom -3.06738 3.08427 11.82586 S 0.0 0.0 -0.476050 0.444938 -0.035933\natom -0.16711 2.91929 1.70250 S 0.0 0.0 0.112141 -0.369133 0.403277\natom 12.70125 8.95407 4.51622 S 0.0 0.0 -0.614318 -0.276546 0.371311\natom 9.74225 8.92619 10.84282 S 0.0 0.0 -1.202930 0.042308 0.276779\natom -3.20438 3.20878 7.65061 S 0.0 0.0 -0.289725 0.255052 -0.043827\natom 11.61231 2.69652 3.80240 Cu 0.0 0.0 0.391770 -0.054206 -0.012242\natom 1.41467 9.00327 2.21273 Cu 0.0 0.0 -0.693663 -0.090294 0.140010\natom -2.02004 9.24063 8.95087 Cu 0.0 0.0 -0.002940 0.062471 -0.095837\natom 8.47278 3.04012 9.76366 Cu 0.0 0.0 0.100954 0.077138 -0.004811\natom 5.55379 0.69555 8.27037 Cu 0.0 0.0 -0.295086 0.648668 0.173849\natom 0.98887 6.80797 9.65854 Cu 0.0 0.0 0.315449 0.420092 0.858395\natom 3.98611 11.29356 4.10338 Cu 0.0 0.0 -0.059508 -0.194572 -0.276054\natom 8.64481 4.91039 2.26137 Cu 0.0 0.0 -0.328978 0.165652 0.435556\natom 8.75433 1.02416 1.86991 Cu 0.0 0.0 -0.162032 0.422745 0.038880\natom 4.00536 7.36720 4.38927 Cu 0.0 0.0 -0.419183 -0.459053 -0.186304\natom 0.88893 11.18860 10.19854 Cu 0.0 0.0 0.031607 0.013853 -0.013245\natom 5.40073 4.66855 8.09789 Cu 0.0 0.0 -0.310233 0.364814 0.004740\natom 4.87332 3.39932 0.69978 Cu 0.0 0.0 0.290394 -0.353057 0.154532\natom 7.09795 8.93120 5.14333 Cu 0.0 0.0 -0.138698 0.057681 -0.002073\natom 3.70509 9.16447 11.39834 Cu 0.0 0.0 0.437228 0.207239 0.318415\natom 2.14836 3.16801 6.88630 Cu 0.0 0.0 0.123592 0.057810 0.339965\natom -4.01817 0.82592 11.54874 Cu 0.0 0.0 1.075584 0.120868 0.176741\natom 9.89746 7.31258 6.48309 Cu 0.0 0.0 -0.066838 0.070502 0.539386\natom 12.83146 10.85639 0.92260 Cu 0.0 0.0 -0.084247 -1.064775 -0.010222\natom -0.85835 5.29316 5.27531 Cu 0.0 0.0 0.266740 0.088528 0.150937\natom -0.96231 0.67333 5.44880 Cu 0.0 0.0 -0.125972 -0.190869 -0.229224\natom 13.27310 6.79948 0.98173 Cu 0.0 0.0 0.313132 0.102051 -0.307492\natom 10.35055 11.21868 6.73618 Cu 0.0 0.0 -0.021537 0.094407 0.324178\natom -4.07327 5.24861 11.02907 Cu 0.0 0.0 0.502192 -0.418966 0.619331\natom 14.59142 1.31024 0.24868 Cu 0.0 0.0 -0.068794 0.045746 -0.445258\natom -1.74385 7.33635 6.30245 Cu 0.0 0.0 -0.103437 0.578930 -0.038327\natom -3.35489 8.70890 11.45086 Cu 0.0 0.0 -0.023471 0.541481 -0.089149\natom 11.31328 4.92819 6.00106 Cu 0.0 0.0 0.124277 -0.354520 0.331290\natom 11.25926 1.71899 6.14910 Cu 0.0 0.0 0.576058 0.153646 0.284591\natom 0.98756 7.18957 0.34767 Cu 0.0 0.0 0.148718 -0.153860 -0.137073\natom -1.89896 10.08005 6.27442 Cu 0.0 0.0 0.269953 0.252167 0.119336\natom 14.82866 4.39039 0.09180 Cu 0.0 0.0 -0.340573 0.056927 -0.147375\natom 8.87065 3.15774 4.77775 Cu 0.0 0.0 0.162618 -0.061351 -0.073613\natom 4.26291 8.24195 1.31598 Cu 0.0 0.0 -0.565867 -0.359922 0.446488\natom 0.22021 8.94420 7.17875 Cu 0.0 0.0 -0.009841 -0.048517 -0.177917\natom 6.40085 2.98501 11.36531 Cu 0.0 0.0 -0.043523 0.040280 0.578155\natom 0.68234 1.70256 11.28986 Cu 0.0 0.0 -0.186826 -0.000683 0.598754\natom 5.26580 7.81845 6.92142 Cu 0.0 0.0 -0.445676 0.563885 -0.652128\natom 7.95813 10.36362 0.83491 Cu 0.0 0.0 0.260321 0.279152 0.286081\natom 4.02707 4.53549 5.72216 Cu 0.0 0.0 0.303080 -0.344855 -0.551618\natom 4.88474 0.93701 5.70079 Cu 0.0 0.0 0.230608 -0.147864 0.000888\natom 8.40394 7.67556 0.92211 Cu 0.0 0.0 0.254484 -0.067652 -0.202682\natom 5.45731 10.49026 6.43732 Cu 0.0 0.0 -0.319092 -0.150872 0.710175\natom 1.92198 5.32701 11.97658 Cu 0.0 0.0 -0.166622 -0.121822 -0.420830\natom -1.69666 2.70600 10.16369 Cu 0.0 0.0 0.358334 -0.239200 -0.109338\natom 7.73517 8.65378 7.88721 Cu 0.0 0.0 0.014459 0.573296 -0.606470\natom 10.68735 9.34588 1.74641 Cu 0.0 0.0 -0.439726 -0.201238 -0.448797\natom 3.64684 3.23269 3.42151 Cu 0.0 0.0 -0.105829 0.453683 0.248434\natom 8.16102 0.46510 8.73219 Cu 0.0 0.0 0.192188 -0.096106 -0.270723\natom -1.85848 6.99743 9.97666 Cu 0.0 0.0 -0.218796 -0.500547 0.105423\natom 0.44296 10.99190 3.89648 Cu 0.0 0.0 0.053204 -0.031752 0.450723\natom 11.40933 5.64462 2.13470 Cu 0.0 0.0 -0.351827 -0.331935 0.076030\natom 11.37718 0.81774 2.06734 Cu 0.0 0.0 -0.611435 -0.193327 0.366000\natom 1.24707 3.95096 4.76029 Cu 0.0 0.0 0.324235 0.241591 -0.679982\natom -1.73266 11.65475 10.37157 Cu 0.0 0.0 0.212860 0.380882 -0.393675\natom 7.92981 5.30116 8.00521 Cu 0.0 0.0 -0.074729 0.092064 0.136868\natom -4.37850 2.67262 9.46103 Cu 0.0 0.0 0.057103 -0.274483 0.202197\natom 10.74864 8.24225 9.06354 Cu 0.0 0.0 -0.023471 -0.253329 -0.343244\natom -1.34377 9.25254 2.80510 Cu 0.0 0.0 0.066385 -0.309898 -0.212381\natom -1.25306 3.50180 3.61142 Cu 0.0 0.0 0.828273 -0.763521 -0.530900\natom 4.64858 1.24230 2.50442 Cu 0.0 0.0 -0.291803 0.025681 0.328332\natom 6.53044 7.12313 2.58618 Cu 0.0 0.0 -0.404324 -0.176835 0.114015\natom 3.42063 11.23257 8.81961 Cu 0.0 0.0 -0.139718 -0.054750 0.343706\natom 1.61485 4.27536 9.16077 Cu 0.0 0.0 0.642162 0.094405 0.089876\natom 1.26903 0.78491 7.43404 Cu 0.0 0.0 -1.098981 -0.221546 0.289553\natom 5.44186 6.51461 10.64828 Cu 0.0 0.0 -0.234590 0.410853 -0.301251\natom 8.72291 11.76178 4.86728 Cu 0.0 0.0 -0.175245 -0.098272 -0.519528\natom 4.27688 5.51884 1.91924 Cu 0.0 0.0 -0.221023 0.180796 0.180334\natom 1.77230 11.62345 1.70957 Cu 0.0 0.0 0.079069 -0.087724 -0.045952\natom 8.38154 6.62650 4.33873 Cu 0.0 0.0 -0.248326 -0.078102 0.530087\natom 5.44621 11.15069 10.67735 Cu 0.0 0.0 -0.260829 0.197381 0.016748\natom 0.25174 6.00863 7.54331 Cu 0.0 0.0 -0.473189 -0.146569 -0.892481\natom 3.67802 2.75104 8.87314 Cu 0.0 0.0 0.089110 -0.140927 0.371747\natom 2.51073 8.84239 9.22448 Cu 0.0 0.0 0.304691 -0.146943 -0.082301\natom 5.64252 9.90858 2.81814 Cu 0.0 0.0 0.513423 -0.142304 0.173443\natom 6.39122 3.17193 2.99785 Cu 0.0 0.0 -0.031973 0.226428 -0.106016\natom 13.78888 1.08302 2.77159 Cu 0.0 0.0 0.380818 -0.054563 -0.043082\natom 13.12264 6.93811 3.58588 Cu 0.0 0.0 0.102637 -0.131678 0.110528\natom -4.66009 10.58928 9.71670 Cu 0.0 0.0 0.270843 0.740876 -0.231055\natom 10.75300 5.17700 8.48767 Cu 0.0 0.0 0.320537 0.022315 -0.106267\natom 4.11156 1.42512 11.60725 Cu 0.0 0.0 -0.071191 -0.081941 -0.092444\natom 2.32526 7.33053 7.02235 Cu 0.0 0.0 0.427606 0.281319 -0.144109\natom 5.26791 11.54654 0.92695 Cu 0.0 0.0 0.083201 -0.202086 -0.734203\natom 6.67048 4.91449 5.73851 Cu 0.0 0.0 0.114596 -0.072935 -0.046294\natom 7.31983 2.84405 7.11799 Cu 0.0 0.0 0.238880 -0.435311 -0.009822\natom -0.99607 9.51313 11.51918 Cu 0.0 0.0 0.286827 0.011185 -0.967809\natom 2.19299 9.57686 5.32161 Cu 0.0 0.0 0.241050 0.033235 0.022089\natom 9.93250 3.87375 0.41602 Cu 0.0 0.0 0.481727 -0.314361 -0.455733\natom 2.25099 2.16311 1.55201 Cu 0.0 0.0 -0.161767 0.376937 -0.281467\natom 10.36062 8.54543 4.32968 Cu 0.0 0.0 0.069128 -0.029650 -0.123427\natom 7.34497 9.46663 10.56599 Cu 0.0 0.0 0.041764 -0.020438 0.077561\natom -0.98405 3.73778 7.63702 Cu 0.0 0.0 0.162342 -0.121758 -0.145897\natom -2.40276 1.09063 8.20590 Cu 0.0 0.0 -0.080006 0.099818 0.070596\natom 8.38212 7.22719 9.70741 Cu 0.0 0.0 0.218579 0.053630 0.432589\natom 11.63611 10.66180 3.47400 Cu 0.0 0.0 -0.056787 0.347671 0.309465\natom 0.79475 4.80215 2.38119 Cu 0.0 0.0 0.125964 0.706002 0.158111\nenergy -566.729768\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/nnp-dataset/Cu2S_PBE/input.nn",
    "content": "###############################################################################\n# HDNNP for copper sulfide Cu2S\n###############################################################################\n# Length unit     : Angstrom\n# Energy unit     : eV\n# Reference method: PBE\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.8640662064628053E+00\nconv_energy   7.3890846653659121E+00\nconv_length   6.1376931796181502E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type.\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n"
  },
  {
    "path": "examples/nnp-dataset/Cu2S_PBE/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   9.1739161189824411E-08   7.0593095050533450E-01   2.2372649929284196E-02   9.6379208796011293E-02\n         1          2   2.6433999906765265E-01   2.4749666370750676E+00   1.0378805142792313E+00   1.9413782463770093E-01\n         1          3   1.5504686427401054E-05   1.4168627312588329E+00   5.5254915214857578E-02   2.1495058826125538E-01\n         1          4   1.4086411910634238E+00   4.7388215758712082E+00   3.1031877925923803E+00   3.5864448236496921E-01\n         1          5   9.8043626772015909E-04   1.9535901883323099E+00   1.1429456309160095E-01   2.2901461288065855E-01\n         1          6   2.2158364445227399E+00   6.0748308460582043E+00   3.8835182764170546E+00   3.9299243538518969E-01\n         1          7   1.0255080523534783E+00   5.1401074554660049E+00   2.5810215644603796E+00   4.3835591238870431E-01\n         1          8   4.8489829707261999E-03   3.9129781874325281E-01   4.7557455423079396E-02   2.7778419734655713E-02\n         1          9   9.3223803365223998E-02   2.8346930075434797E+00   6.0185719975366336E-01   3.1949957606875956E-01\n         1         10   6.7206749586119430E-01   4.4876923880381465E+00   2.1991872165248538E+00   4.1504796440380803E-01\n         1         11   2.2128378766968923E-02   8.6593017344520318E-01   1.4060436434125115E-01   7.5838421599526348E-02\n         1         12   8.4205124330445313E-01   7.0656885702864862E+00   2.9013712601439368E+00   7.3052821449417049E-01\n         1         13   1.4518778507164800E+00   9.6462711741708382E+00   4.3715329035264965E+00   8.3811671947643118E-01\n         1         14   2.4300884834352513E-06   5.3039215356450418E-02   2.8067394350178213E-04   1.6541693025921896E-03\n         1         15   4.3805855934107564E-04   3.3431366727997386E-01   1.5056637491023487E-02   3.6381498406602590E-02\n         1         16   1.8742403996648012E-02   5.3094282134884740E-01   1.9287359264197504E-01   5.3785992354357007E-02\n         1         17   5.6391705067135155E-03   2.7103176024192799E-01   3.6199336036120536E-02   2.2235092628611220E-02\n         1         18   5.8157340520125522E-01   3.0394483797974066E+00   1.5432926655352674E+00   2.9013849228704902E-01\n         1         19   3.5474335876025032E-01   2.8914948266501281E+00   1.2453633098426364E+00   2.6070492382053573E-01\n         1         20   1.3050150224953865E-03   2.0977615521049353E-01   1.6466279986318652E-02   1.6175233794254219E-02\n         1         21   3.3625763520090814E-02   1.6019727512861448E+00   2.6707302954572526E-01   1.9158906783856428E-01\n         1         22   3.5314748293148263E-01   2.5968432133168928E+00   1.2041087980295160E+00   2.3880745648555143E-01\n         1         23   5.6279184570511148E-03   4.8263719913200909E-01   4.8674878532957294E-02   4.5579012837321450E-02\n         1         24   3.5640890668898983E-01   3.9354254479681789E+00   1.3506519169134916E+00   4.3100694380807969E-01\n         1         25   7.1435545388184229E-01   5.4083380133399706E+00   2.3405335217844168E+00   4.7481787957091687E-01\n         1         26   6.0302894280955782E-07   2.4282702757490063E-02   1.0392381208153868E-04   6.9514343858439293E-04\n         1         27   1.4152015883516988E-04   1.8793440136817721E-01   6.7319944252965166E-03   1.8860146728064606E-02\n         1         28   7.6669273315039489E-03   2.8853650966579203E-01   9.6832241039761832E-02   2.8591400835791262E-02\n         1         29   1.4586287100215936E-03   1.2827520308122028E-01   1.2535333774723276E-02   1.2196652689168296E-02\n         1         30   2.4306078779227119E-01   1.5771292876622454E+00   7.3118666045976355E-01   1.6033491927751306E-01\n         1         31   1.5700215118676836E-01   1.4950427209078341E+00   6.2168623298528469E-01   1.3878720233016123E-01\n         1         32   8.0322135442977674E-08   9.1020506427165644E-03   1.1758299063219979E-04   7.2850621729108440E-04\n         1         33   3.8387499554503460E-05   4.6879099417593433E-02   2.2899299020297070E-03   6.3507919696978174E-03\n         1         34   2.5111603817039843E-07   2.6638155845094137E-02   3.5204871838944324E-04   2.1803344919789219E-03\n         1         35   7.8176366916082938E-04   1.2144199943350505E-01   1.0237823308897595E-02   1.5551953673898984E-02\n         1         36   6.0784771853405629E-03   1.5177813800129991E-01   4.5342256644197804E-02   1.4422755174681633E-02\n         1         37   6.5208235096380454E-08   6.8957085587219831E-03   8.4477914517405974E-05   5.1826403434160535E-04\n         1         38   5.1003186367566016E-04   3.3817704100212627E-02   5.0495259674331701E-03   4.2413701977289924E-03\n         1         39   3.0092380409832575E-01   3.9241027015819827E+00   1.6245850308330121E+00   3.6115017167195557E-01\n         1         40   2.9205060411645536E+00   2.0972699454192377E+01   1.0685030237788666E+01   1.8434608066664662E+00\n         1         41   5.8304225749625562E+00   3.3157582599900756E+01   1.6937338463410185E+01   2.8416990087236536E+00\n         1         42   2.8963706388516774E-01   3.4220973094358569E+00   1.3527222233246401E+00   2.9841578592458634E-01\n         1         43   3.3240856510350132E+00   1.9977206504626281E+01   1.0533032366441756E+01   1.8362183066460305E+00\n         1         44   5.5968160844972745E+00   2.9479500954936675E+01   1.4663357897716818E+01   2.4340402007751933E+00\n         1         45   7.3194532436105672E-02   1.4240027432637063E+00   4.6184059564430718E-01   1.0603619804309938E-01\n         1         46   7.4351404260172327E-01   6.1601360099088307E+00   3.0926623459215312E+00   5.2746971733324144E-01\n         1         47   1.0304047665725904E+00   9.5490875529313932E+00   4.6615470051220029E+00   8.8228607777747381E-01\n         1         48   5.3439780036913555E-02   6.0792049084128386E-01   2.0133541277710790E-01   4.7497199912796259E-02\n         1         49   1.0984946263275692E+00   5.3381605458179147E+00   2.9222626179881503E+00   4.9078113758325748E-01\n         1         50   9.3741001607568142E-01   6.0472356274080674E+00   2.8114797251218855E+00   5.0873676433244819E-01\n         1         51   1.1424085007079182E-01   2.3139492223359586E+00   7.5719953168832033E-01   2.0833570661709583E-01\n         1         52   1.4315113742496002E+00   1.3300925195398728E+01   5.8838374866614309E+00   1.2171600869775945E+00\n         1         53   3.5503714858105737E+00   2.1312715022502385E+01   1.0871674742056101E+01   1.8799426423890726E+00\n         1         54   1.0963309213378970E-01   2.0788696656585590E+00   6.3126459151902947E-01   1.7541529953806104E-01\n         1         55   1.6510272306266744E+00   1.2357046870783602E+01   5.7724472752012481E+00   1.1927743223366301E+00\n         1         56   3.3307522004182251E+00   1.8663597697385917E+01   9.2207406968320633E+00   1.5761279490996694E+00\n         1         57   2.7455727216146104E-02   9.1674320906634155E-01   2.1461170716720621E-01   6.1714021121502906E-02\n         1         58   3.6192386693953038E-01   3.8875893126984216E+00   1.7092032560335464E+00   3.4843371038350474E-01\n         1         59   5.6557210052590146E-01   6.1563972117346957E+00   2.9617726398537609E+00   5.9044611830216798E-01\n         1         60   2.0196364035104716E-02   3.3469617649847838E-01   9.3035775655912298E-02   2.7640180745065839E-02\n         1         61   5.5357670454431462E-01   3.1907980705952856E+00   1.5901399654465433E+00   3.0513520444755149E-01\n         1         62   5.3781344801473907E-01   3.6339755326587713E+00   1.6575261374157455E+00   3.1383714619102349E-01\n         1         63   9.6664268597268675E-05   1.4867672619417913E-01   4.3177785208556420E-03   8.2707901241799234E-03\n         1         64   1.2006437712525238E-02   1.1332481089585240E+00   1.2838035367153358E-01   1.3388538744183132E-01\n         1         65   2.0772479772511018E-01   1.8626169502984133E+00   8.2255201121385824E-01   1.7849382645365078E-01\n         1         66   8.7907438908811975E-05   1.2622839046469150E-01   4.4000149614673457E-03   1.1827043706432264E-02\n         1         67   1.3369106385547676E-02   8.7813896596785235E-01   1.1827747851010054E-01   1.1347348778532439E-01\n         1         68   1.7657303404092337E-01   1.4295433698727396E+00   6.2121356605669209E-01   1.2933064669650537E-01\n         1         69   2.8597998667575309E-03   3.7304172172637867E-01   3.7665097851475426E-02   3.7208167402427196E-02\n         1         70   1.5902143209986809E-05   2.6009225424800504E-02   7.2450937404019229E-04   2.4859888979869879E-03\n         1         71   4.7171431923273572E-03   1.6025670770457742E-01   2.8821358718588475E-02   1.9416774232856850E-02\n         1         72   1.5331295649388408E-02   1.9310943777686740E-01   6.9677412943044442E-02   1.7784064753732315E-02\n         2          1   2.4721472942648627E-02   1.5073065774351924E+00   5.1894025713961534E-01   1.2292746613848948E-01\n         2          2   2.4966843476303169E-01   2.6917832996745195E+00   1.5515938962961904E+00   2.2894178892035891E-01\n         2          3   1.8582961795319244E-03   3.8171243121869747E+00   1.1221679663414206E+00   3.9926224172528085E-01\n         2          4   6.9308990079045429E-01   3.9421018903882858E+00   1.9417591382085293E+00   2.7982355416028953E-01\n         2          5   5.2213352864915873E-02   5.9786240694290029E+00   2.7894744649522680E+00   6.8818475947171043E-01\n         2          6   3.4706330958249576E-01   2.8061894414477742E+00   1.2905107822301898E+00   2.5049917129048904E-01\n         2          7   5.6650782795607790E-01   6.0129804050995874E+00   3.4024808580901604E+00   5.3817898895468230E-01\n         2          8   8.2160472578002200E-02   2.1591157175155038E+00   9.5893716661004147E-01   2.2068746057755104E-01\n         2          9   9.7533565633843480E-02   8.0520717520847240E-01   3.9574121682754421E-01   7.2843087896835634E-02\n         2         10   7.5624736998622447E-02   1.2151161903363619E+00   4.2414909548153323E-01   1.1030205700397629E-01\n         2         11   3.8590027688988915E-01   3.4170303616374733E+00   1.5389187655267780E+00   2.9839201545750010E-01\n         2         12   1.2653139464575366E-01   3.3448693047411142E+00   9.0701446886275106E-01   3.0808232807716252E-01\n         2         13   3.5754079396564345E-02   2.3051636092543291E+00   4.5165801949286744E-01   2.0529180913687342E-01\n         2         14   1.7360244301899754E+00   9.1860981352526956E+00   5.0318013545245659E+00   7.7006828863188448E-01\n         2         15   5.6096556948092302E-01   6.9184291400548386E+00   2.5593433032311834E+00   7.0382259666666958E-01\n         2         16   2.7321455653550736E-03   2.6718628880300366E-01   6.8392239083035003E-02   1.8417271845608391E-02\n         2         17   1.4998879259624551E-04   2.8869834404308442E-01   3.2421219256901605E-02   2.1462316150937667E-02\n         2         18   9.6976148378458242E-03   6.9986551977156553E-01   7.4501947267367571E-02   9.2109247490457000E-02\n         2         19   7.5554776729931772E-01   3.8650650491408283E+00   2.1261658860729638E+00   2.9459249679651817E-01\n         2         20   2.2984860438624041E-01   2.2399640197541903E+00   8.4832685420611464E-01   2.2013029667841760E-01\n         2         21   3.1742242534198488E-02   6.9305314098138393E-01   2.0239450285654340E-01   6.2019223320811959E-02\n         2         22   1.6267388613945685E-01   1.8982342788109985E+00   8.1342448996901984E-01   1.7017885772188068E-01\n         2         23   4.3623299253776143E-02   1.8524213261728384E+00   4.3372964228967342E-01   1.6475284995752615E-01\n         2         24   1.1782155855406862E-02   1.3256780035707432E+00   2.0203673375826020E-01   1.2375770385162231E-01\n         2         25   9.5572013219445029E-01   5.1585503300832807E+00   2.7312178298449119E+00   4.5027566865612645E-01\n         2         26   2.1346552007948805E-01   3.7560054368796258E+00   1.2309867059977997E+00   3.8895981570570448E-01\n         2         27   1.0778454975081308E-03   1.6230009416534466E-01   3.4353839552470775E-02   1.0338804556484340E-02\n         2         28   4.1455680376600344E-05   1.3561930079689324E-01   1.3464607540962245E-02   9.4307016558753589E-03\n         2         29   2.9811923400491925E-03   3.9674788724187127E-01   3.2946560522656709E-02   5.3575100644579036E-02\n         2         30   4.0860996892032608E-01   2.1541090596644543E+00   1.1291055145629398E+00   1.6554701558125592E-01\n         2         31   8.7689965003411183E-02   1.1196100344004409E+00   3.9704096379805787E-01   1.1606734505235136E-01\n         2         32   2.0029888316796539E-05   1.7556653440553127E-02   1.4233102888664287E-03   1.3598121443903737E-03\n         2         33   5.2716716179610746E-06   4.4644993845652417E-02   1.7086280138653978E-03   4.2643079956046579E-03\n         2         34   8.8339290835669212E-07   1.2139204575362132E-02   4.1922038284938451E-04   1.5155281653507265E-03\n         2         35   1.2653672947005059E+00   8.9337925904902882E+00   4.2637335795708999E+00   5.9362291906692699E-01\n         2         36   4.3025897744283652E+00   2.4744209023066571E+01   1.4272525712868205E+01   1.9700222663219151E+00\n         2         37   2.9677470818795189E+00   2.5847640450705327E+01   1.1788593731598802E+01   2.3639335745006553E+00\n         2         38   4.8673248345854536E-01   6.9220258514917292E+00   2.9410791137038919E+00   5.0416378898015868E-01\n         2         39   4.7312413761643519E+00   2.4784350068345699E+01   1.4182436900763136E+01   1.9734981280505293E+00\n         2         40   2.7914940844674572E+00   2.2909604188642842E+01   1.0258913931047273E+01   2.0538117984713926E+00\n         2         41   5.1976352609600407E-01   3.0581982698648895E+00   1.1910833091075925E+00   2.2566892125976182E-01\n         2         42   1.0695804209866875E+00   7.2313250376604037E+00   3.9928775708897235E+00   5.8095727320582324E-01\n         2         43   8.4628209088378592E-01   7.5313801441068913E+00   3.3982729265620653E+00   7.1123273080942895E-01\n         2         44   7.0763463381880415E-02   1.2969398476188700E+00   3.1793764328087359E-01   1.3617384576811825E-01\n         2         45   1.3721123798749537E+00   6.3973513973729199E+00   3.7457022157866304E+00   5.0158792550110110E-01\n         2         46   6.3964342968618404E-01   4.7161013997028380E+00   1.9947659320351354E+00   4.2776493844298569E-01\n         2         47   8.6532747970285151E-01   6.1240088873304499E+00   2.7402018484921369E+00   4.0552538612845523E-01\n         2         48   2.5315105294788682E+00   1.5776758660822487E+01   8.7867531123795093E+00   1.2800885070636867E+00\n         2         49   1.5679508239487920E+00   1.6123025100421103E+01   6.9389600266532643E+00   1.5752331036924878E+00\n         2         50   2.4475421880204548E-01   4.5715135037651979E+00   1.7778621079614614E+00   3.3311384228682872E-01\n         2         51   2.8365798870360606E+00   1.5735394223700631E+01   8.7129345829426814E+00   1.2788947945672131E+00\n         2         52   1.4825266957775993E+00   1.4111085036729261E+01   5.9550381055833128E+00   1.3412575984240060E+00\n         2         53   2.9486345514961088E-01   2.1632897998459173E+00   7.6894782290828789E-01   1.6439255789853263E-01\n         2         54   6.1183454216254696E-01   4.7418024842673727E+00   2.4364672738977449E+00   3.8379810845509604E-01\n         2         55   4.2978046698724798E-01   4.7295979558909700E+00   2.0069121315341767E+00   4.7649159304923261E-01\n         2         56   3.3379248097225291E-02   8.3272635081969881E-01   1.7274845946125020E-01   8.7956031429209408E-02\n         2         57   8.2656009161897048E-01   3.9467471262168639E+00   2.2459243943426777E+00   3.1269124051179731E-01\n         2         58   3.1171589063801924E-01   2.7714452296122714E+00   1.1129251102859337E+00   2.6297335909685149E-01\n         2         59   2.6592109568248031E-02   5.6825603390221913E-01   2.0877471778793405E-01   4.9135988886466996E-02\n         2         60   7.2485536842319745E-02   1.1034806181844534E+00   4.5818934497666303E-01   1.0344323974312900E-01\n         2         61   5.9263838221524185E-03   1.2515028539804678E+00   2.4502825958578195E-01   1.1006546541667923E-01\n         2         62   3.5994334696395447E-03   3.9125406849266531E-01   8.9107610428087070E-02   3.1854933024728180E-02\n         2         63   7.2533340578499653E-02   1.0927078443379801E+00   4.4612155612487853E-01   1.0164232620041405E-01\n         2         64   5.4706332551405917E-03   9.8645463183530846E-01   1.9457952454956559E-01   8.6829363320211461E-02\n         2         65   1.7435002600794914E-04   5.6940854477051987E-02   3.9265019004702875E-03   5.9979210203388224E-03\n         2         66   2.1035187678847361E-02   2.2735828246294021E-01   9.5459655622289877E-02   2.0577872261152416E-02\n"
  },
  {
    "path": "examples/nnp-dataset/Cu2S_PBE/weights.016.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -3.5529535307974660E+00 a         1     0     1     1     1\n  7.2419212968357530E-02 a         2     0     1     1     2\n  6.6238167719007179E-01 a         3     0     1     1     3\n  1.3187085002852068E+00 a         4     0     1     1     4\n  8.0230438760649514E-01 a         5     0     1     1     5\n  8.3955862269426929E-01 a         6     0     1     1     6\n  6.0886672237242623E-01 a         7     0     1     1     7\n  1.8038521037244075E+00 a         8     0     1     1     8\n -9.4212226737513360E-01 a         9     0     1     1     9\n -5.1556581063883433E-01 a        10     0     1     1    10\n -1.1787308470438386E-01 a        11     0     1     1    11\n  2.7402309255936421E+00 a        12     0     1     1    12\n -1.4988157706430596E+00 a        13     0     1     1    13\n -1.4218948987030877E+00 a        14     0     1     1    14\n -3.1471248905197000E+00 a        15     0     1     1    15\n -2.7242744362012289E-01 a        16     0     1     1    16\n -1.4939110915197420E+00 a        17     0     1     1    17\n -4.5760625854044340E-01 a        18     0     1     1    18\n  1.8320965746572428E+00 a        19     0     1     1    19\n  1.4829292005742705E+00 a        20     0     1     1    20\n -4.7531481220841671E+00 a        21     0     1     1    21\n  6.9284365000837844E-01 a        22     0     1     1    22\n -1.4360334184866708E+00 a        23     0     1     1    23\n -6.9988606086712224E-01 a        24     0     1     1    24\n -2.6821117310359570E+00 a        25     0     1     1    25\n  1.2328185292695659E+00 a        26     0     2     1     1\n  6.8539081540980901E-02 a        27     0     2     1     2\n  1.1312525424757594E-01 a        28     0     2     1     3\n  3.3791299053992763E-01 a        29     0     2     1     4\n  1.3203780104475105E+00 a        30     0     2     1     5\n -1.4531712477250573E+00 a        31     0     2     1     6\n  2.4379072742488564E-01 a        32     0     2     1     7\n  7.2963026955779986E-01 a        33     0     2     1     8\n -1.2591734762557112E+00 a        34     0     2     1     9\n -4.7096176379988147E-01 a        35     0     2     1    10\n  1.1052943930835461E-01 a        36     0     2     1    11\n  1.2282514057948777E+00 a        37     0     2     1    12\n -5.8437787869506075E-01 a        38     0     2     1    13\n  1.4166787422902487E+00 a        39     0     2     1    14\n -1.6938650584717402E-01 a        40     0     2     1    15\n  2.3030826774815769E+00 a        41     0     2     1    16\n -1.4473769335578126E+00 a        42     0     2     1    17\n  4.0195075881174241E-01 a        43     0     2     1    18\n  1.1043558865793792E+00 a        44     0     2     1    19\n -3.4549061205961434E-01 a        45     0     2     1    20\n  8.1879232157423720E-01 a        46     0     2     1    21\n -2.7007345535606064E-01 a        47     0     2     1    22\n -8.2869143511169474E-01 a        48     0     2     1    23\n -2.9469119089022022E-01 a        49     0     2     1    24\n -5.7206441642229700E-01 a        50     0     2     1    25\n  7.7333844542414798E-01 a        51     0     3     1     1\n -2.8005034461966472E+00 a        52     0     3     1     2\n -2.0054154055351620E-01 a        53     0     3     1     3\n -2.3648818664674390E-01 a        54     0     3     1     4\n -6.4064022093719220E-01 a        55     0     3     1     5\n  6.9876341352721461E-01 a        56     0     3     1     6\n  1.2138517429043079E+00 a        57     0     3     1     7\n -1.0872828987358620E+00 a        58     0     3     1     8\n  2.4009903950784475E+00 a        59     0     3     1     9\n -7.1414550990900871E-01 a        60     0     3     1    10\n  4.8262298434516965E-01 a        61     0     3     1    11\n  1.2017235942575036E-01 a        62     0     3     1    12\n -5.0067742187524500E-01 a        63     0     3     1    13\n  1.6682617398315705E-01 a        64     0     3     1    14\n -1.9521789463955752E+00 a        65     0     3     1    15\n  1.3587159322569415E+00 a        66     0     3     1    16\n  1.9824040428450457E-01 a        67     0     3     1    17\n  5.0478176436946609E-01 a        68     0     3     1    18\n  1.7968971934667841E+00 a        69     0     3     1    19\n -2.6819167691107553E+00 a        70     0     3     1    20\n  3.1361294632323173E+00 a        71     0     3     1    21\n -7.2813429885436576E-01 a        72     0     3     1    22\n  7.9662962027149486E-01 a        73     0     3     1    23\n  5.3906067437318705E-01 a        74     0     3     1    24\n  1.8219650246428634E+00 a        75     0     3     1    25\n  5.8927722128305347E-02 a        76     0     4     1     1\n  3.4478358925805858E-01 a        77     0     4     1     2\n  2.1711984340886667E-01 a        78     0     4     1     3\n -7.5943721634464512E-01 a        79     0     4     1     4\n -2.1415789791334832E+00 a        80     0     4     1     5\n  3.0855930522672659E-01 a        81     0     4     1     6\n -7.4505867442699159E-01 a        82     0     4     1     7\n -4.1258347929987922E+00 a        83     0     4     1     8\n -8.9911876538844360E-02 a        84     0     4     1     9\n  8.0135720853704462E-01 a        85     0     4     1    10\n -6.4314476008779209E-01 a        86     0     4     1    11\n -6.6301798112622423E-01 a        87     0     4     1    12\n -1.6975741162472407E-01 a        88     0     4     1    13\n  1.5616634992334104E+00 a        89     0     4     1    14\n  5.4073426424790072E-01 a        90     0     4     1    15\n  1.1663760214127676E+00 a        91     0     4     1    16\n -7.2592084481083807E-01 a        92     0     4     1    17\n  1.1933746575167552E+00 a        93     0     4     1    18\n  5.8471587235867606E-01 a        94     0     4     1    19\n  9.9434818278332526E-01 a        95     0     4     1    20\n  3.0868993139314660E-01 a        96     0     4     1    21\n -4.1822451550640703E-02 a        97     0     4     1    22\n  4.3484284598560397E-01 a        98     0     4     1    23\n  3.4675230994513656E-01 a        99     0     4     1    24\n -7.9366614810023273E-01 a       100     0     4     1    25\n -7.1415208213408676E-01 a       101     0     5     1     1\n  5.5359292712059338E-01 a       102     0     5     1     2\n  4.6091614481806420E-01 a       103     0     5     1     3\n  2.3210532804307410E-01 a       104     0     5     1     4\n -3.5974858266384940E-01 a       105     0     5     1     5\n  8.7207348428923104E-01 a       106     0     5     1     6\n -2.6428893993697733E-01 a       107     0     5     1     7\n  1.2687679723738343E+00 a       108     0     5     1     8\n  3.0350814520079739E-01 a       109     0     5     1     9\n  4.0127959961420190E-01 a       110     0     5     1    10\n  2.5760664947260187E-01 a       111     0     5     1    11\n  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-1.0371067287322926E+00 a      1792     0    72     1    17\n -4.3760611806115551E-01 a      1793     0    72     1    18\n  9.8623879832675329E-02 a      1794     0    72     1    19\n -7.5410028995025702E-01 a      1795     0    72     1    20\n -1.2313787058509964E+00 a      1796     0    72     1    21\n -4.6741452879831155E-02 a      1797     0    72     1    22\n -4.4269157854319681E-02 a      1798     0    72     1    23\n  1.7151129017615777E-01 a      1799     0    72     1    24\n  3.2149250192846229E-01 a      1800     0    72     1    25\n -1.2487799204729562E+00 b      1801     1     1\n  7.7797875052564691E-02 b      1802     1     2\n -1.1527934681933877E-01 b      1803     1     3\n -2.8431889201310762E-01 b      1804     1     4\n  5.5831725553046441E-01 b      1805     1     5\n  2.8860892427759248E+00 b      1806     1     6\n -1.3445325409540025E+00 b      1807     1     7\n  6.6670686103261509E+00 b      1808     1     8\n  3.5820158276553177E-01 b      1809     1     9\n  3.5785148839511103E+00 b      1810     1    10\n -8.8101281474293580E-01 b      1811     1    11\n -5.3726668973875906E+00 b      1812     1    12\n -6.4114714028020847E-01 b      1813     1    13\n  1.5565127033840587E+00 b      1814     1    14\n -1.7602464299350837E-02 b      1815     1    15\n  1.8777261894948953E+00 b      1816     1    16\n  1.4994055174586114E+00 b      1817     1    17\n -7.2199500908977243E-01 b      1818     1    18\n  9.2731866344858893E-01 b      1819     1    19\n -4.4839087509791570E-01 b      1820     1    20\n -2.1355087601187956E+00 b      1821     1    21\n -5.9468786076051305E-01 b      1822     1    22\n -1.4586824355018946E+00 b      1823     1    23\n -1.0118916679592884E+00 b      1824     1    24\n -1.1773719431755225E+00 b      1825     1    25\n -1.5657428780940730E+00 a      1826     1     1     2     1\n -1.5012822554420542E+00 a      1827     1     1     2     2\n -1.2445510657315391E+00 a      1828     1     1     2     3\n  4.6535124151521978E-01 a      1829     1     1     2     4\n -3.0238704945460926E+00 a      1830     1     1     2     5\n -2.0379620934455489E+00 a      1831     1     1     2     6\n  7.4948788266366556E-02 a      1832     1     1     2     7\n -6.0290099180791534E-01 a      1833     1     1     2     8\n  1.7460323129727879E+00 a      1834     1     1     2     9\n  2.5007013971091658E+00 a      1835     1     1     2    10\n -1.4583060785096735E-01 a      1836     1     1     2    11\n -1.9262900473130924E+00 a      1837     1     1     2    12\n  5.8244956699951933E-01 a      1838     1     1     2    13\n -2.4157948338689561E+00 a      1839     1     1     2    14\n  1.3930646447971677E+00 a      1840     1     1     2    15\n -3.3884524734286364E-01 a      1841     1     1     2    16\n  5.0915893349041390E-02 a      1842     1     1     2    17\n -5.6109069774343445E-01 a      1843     1     1     2    18\n -9.4868143504376856E-01 a      1844     1     1     2    19\n  9.6827317475849287E-02 a      1845     1     1     2    20\n -5.9013678435448087E+00 a      1846     1     1     2    21\n  9.7890502371388077E-01 a      1847     1     1     2    22\n -4.4111725189133528E+00 a      1848     1     1     2    23\n  1.8482352604811032E-02 a      1849     1     1     2    24\n -2.8284859187456629E-01 a      1850     1     1     2    25\n  2.0628489763983970E-01 a      1851     1     2     2     1\n -5.5396624504985370E-01 a      1852     1     2     2     2\n -1.5193082965932591E-02 a      1853     1     2     2     3\n  7.5033900530820685E-01 a      1854     1     2     2     4\n  1.6660381270511398E-01 a      1855     1     2     2     5\n -3.3264378673577971E-01 a      1856     1     2     2     6\n  6.0446696452873461E-01 a      1857     1     2     2     7\n  4.8182119618694658E-01 a      1858     1     2     2     8\n -6.1254123670479155E-01 a      1859     1     2     2     9\n  1.1417688385928499E+00 a      1860     1     2     2    10\n -1.5054546644990752E+00 a      1861     1     2     2    11\n  1.8610934627716093E-02 a      1862     1     2     2    12\n  7.0237315233166497E-01 a      1863     1     2     2    13\n  9.4212554739512056E-01 a      1864     1     2     2    14\n -6.4243325216574909E-01 a      1865     1     2     2    15\n  2.0638482947612933E+00 a      1866     1     2     2    16\n -7.8489263650035335E-02 a      1867     1     2     2    17\n  8.8188283383270472E-01 a      1868     1     2     2    18\n  5.6847475917655665E-01 a      1869     1     2     2    19\n  3.4854878075637896E-01 a      1870     1     2     2    20\n  1.4875468096208677E-01 a      1871     1     2     2    21\n  1.1162641631624876E-01 a      1872     1     2     2    22\n  1.1416286121652623E+00 a      1873     1     2     2    23\n  8.0566577322750998E-01 a      1874     1     2     2    24\n -1.3768822327400507E+00 a      1875     1     2     2    25\n  5.2100349813620650E-01 a      1876     1     3     2     1\n  3.0316390750570238E-01 a      1877     1     3     2     2\n -2.3370128152310604E-01 a      1878     1     3     2     3\n -1.0820688792652087E+00 a      1879     1     3     2     4\n  2.1060281157526037E-01 a      1880     1     3     2     5\n -3.6728393525156205E-01 a      1881     1     3     2     6\n -1.7794340421478609E+00 a      1882     1     3     2     7\n -4.3969196635008256E-01 a      1883     1     3     2     8\n -6.5240078672733570E-01 a      1884     1     3     2     9\n  1.3030748053589755E-01 a      1885     1     3     2    10\n  8.0208201643578281E-01 a      1886     1     3     2    11\n -5.0642791152315048E-01 a      1887     1     3     2    12\n  1.7175121486555200E-02 a      1888     1     3     2    13\n -1.7539793329208120E-01 a      1889     1     3     2    14\n -1.9760102634297960E+00 a      1890     1     3     2    15\n -6.5964298566673879E-02 a      1891     1     3     2    16\n  2.1354437430032353E-01 a      1892     1     3     2    17\n  3.7292555470519495E-01 a      1893     1     3     2    18\n -2.8759373610684746E-01 a      1894     1     3     2    19\n -3.0111096782562924E-01 a      1895     1     3     2    20\n -1.7306176309591917E-01 a      1896     1     3     2    21\n -1.2005571011494226E-01 a      1897     1     3     2    22\n  1.3295388504771954E-01 a      1898     1     3     2    23\n  8.3138458757209516E-02 a      1899     1     3     2    24\n  1.5856154095117295E-04 a      1900     1     3     2    25\n  6.4572709345253165E-01 a      1901     1     4     2     1\n -5.7946715376023517E-01 a      1902     1     4     2     2\n -1.0108148324035785E-02 a      1903     1     4     2     3\n -1.6260047633919668E+00 a      1904     1     4     2     4\n  1.2063924357050895E+00 a      1905     1     4     2     5\n -1.3308086608013470E-01 a      1906     1     4     2     6\n -2.0744033026290049E-01 a      1907     1     4     2     7\n  8.7004036554679898E-04 a      1908     1     4     2     8\n  1.3776545639614570E+00 a      1909     1     4     2     9\n -4.1679170481413325E-01 a      1910     1     4     2    10\n  1.2085768686834414E-01 a      1911     1     4     2    11\n  6.7417090723776829E-02 a      1912     1     4     2    12\n  7.2831441702454858E-01 a      1913     1     4     2    13\n  4.1882179725900914E-01 a      1914     1     4     2    14\n  8.6071127382993529E-01 a      1915     1     4     2    15\n -1.0475505670392704E+00 a      1916     1     4     2    16\n  4.1797053832508835E-01 a      1917     1     4     2    17\n  9.0950721709203083E-02 a      1918     1     4     2    18\n -2.0125699174728634E-01 a      1919     1     4     2    19\n  4.3360061561778840E-01 a      1920     1     4     2    20\n -8.7167096012562095E-01 a      1921     1     4     2    21\n -2.4539897225218532E-01 a      1922     1     4     2    22\n -5.3604239110809038E-01 a      1923     1     4     2    23\n -2.2337993987488888E-01 a      1924     1     4     2    24\n  3.1846049011561406E-01 a      1925     1     4     2    25\n  1.1434219399741365E-01 a      1926     1     5     2     1\n  1.7880919133127568E-01 a      1927     1     5     2     2\n -1.8179159527255145E-01 a      1928     1     5     2     3\n -4.5488815247472342E-01 a      1929     1     5     2     4\n -6.1598699822076874E-01 a      1930     1     5     2     5\n -2.4359478240808174E-01 a      1931     1     5     2     6\n -2.7633669765488156E-01 a      1932     1     5     2     7\n  5.6548513047232192E-02 a      1933     1     5     2     8\n -1.1856375180802950E-01 a      1934     1     5     2     9\n  1.9838320239404128E-01 a      1935     1     5     2    10\n -5.5839996553118054E-01 a      1936     1     5     2    11\n  8.5683677871477751E-02 a      1937     1     5     2    12\n -4.3990229216539417E-02 a      1938     1     5     2    13\n -8.2580380946034065E-02 a      1939     1     5     2    14\n -2.5926939478179243E+00 a      1940     1     5     2    15\n -2.9263488552138478E-01 a      1941     1     5     2    16\n  7.4326458357632263E-01 a      1942     1     5     2    17\n  4.2013924569516037E-01 a      1943     1     5     2    18\n -5.8280302654581832E-02 a      1944     1     5     2    19\n -3.2612804852919446E-02 a      1945     1     5     2    20\n  3.0897375192782450E-01 a      1946     1     5     2    21\n -3.4554814584389509E-01 a      1947     1     5     2    22\n  5.6462638020854716E-01 a      1948     1     5     2    23\n -2.2840636874785014E-01 a      1949     1     5     2    24\n -4.9669234553755076E-01 a      1950     1     5     2    25\n  1.1758939649783381E-01 a      1951     1     6     2     1\n  8.6738679928268236E-01 a      1952     1     6     2     2\n -8.2268243221940873E-01 a      1953     1     6     2     3\n -1.7656641024661676E-01 a      1954     1     6     2     4\n -7.3983486152494982E-01 a      1955     1     6     2     5\n  5.9385478664743296E-01 a      1956     1     6     2     6\n -4.2593570872866021E-01 a      1957     1     6     2     7\n -1.9801025124105215E-01 a      1958     1     6     2     8\n -4.6730416799726238E-01 a      1959     1     6     2     9\n  1.8116336463074925E-01 a      1960     1     6     2    10\n -7.5935659696139179E-01 a      1961     1     6     2    11\n -2.7885626460361607E-01 a      1962     1     6     2    12\n  2.2498372487170440E-01 a      1963     1     6     2    13\n -2.6922194278960770E-01 a      1964     1     6     2    14\n  8.2356834198746176E-02 a      1965     1     6     2    15\n -1.9959174200148408E+00 a      1966     1     6     2    16\n -9.1441649022992150E-02 a      1967     1     6     2    17\n -3.2893725936322316E-01 a      1968     1     6     2    18\n  8.4708812890909327E-02 a      1969     1     6     2    19\n -9.8738542155083330E-03 a      1970     1     6     2    20\n -1.5706979176219785E-01 a      1971     1     6     2    21\n -3.3385820430832114E-01 a      1972     1     6     2    22\n -8.1658461786034431E-01 a      1973     1     6     2    23\n  4.2826805041754107E-01 a      1974     1     6     2    24\n  6.7595378736221203E-03 a      1975     1     6     2    25\n -1.4858293771378450E-01 a      1976     1     7     2     1\n -4.8665064878920916E-01 a      1977     1     7     2     2\n  9.3147532658334302E-03 a      1978     1     7     2     3\n  2.2071434698840436E-01 a      1979     1     7     2     4\n -3.1521981986003578E+00 a      1980     1     7     2     5\n  1.4896102615333093E-01 a      1981     1     7     2     6\n  2.0639082326871608E-01 a      1982     1     7     2     7\n  1.4764434422173356E+00 a      1983     1     7     2     8\n -8.5415180586937678E-01 a      1984     1     7     2     9\n  2.0056826451387089E+00 a      1985     1     7     2    10\n -1.6035541337428121E+00 a      1986     1     7     2    11\n -1.0126746741541708E-01 a      1987     1     7     2    12\n  1.0176837892450277E+00 a      1988     1     7     2    13\n  5.8650237148957363E-01 a      1989     1     7     2    14\n  6.8764775335937489E-01 a      1990     1     7     2    15\n -1.6327881928548789E+00 a      1991     1     7     2    16\n -2.6588597247788198E-01 a      1992     1     7     2    17\n  1.9718370666773979E-01 a      1993     1     7     2    18\n  4.3601566297954825E-01 a      1994     1     7     2    19\n -2.7082844396133726E-01 a      1995     1     7     2    20\n  3.2206390922604272E-01 a      1996     1     7     2    21\n  5.0949702830703934E-03 a      1997     1     7     2    22\n -1.3049790188741632E+00 a      1998     1     7     2    23\n  4.2026808266723220E-01 a      1999     1     7     2    24\n -6.3063301866048659E-03 a      2000     1     7     2    25\n -2.6986778384233595E-01 a      2001     1     8     2     1\n  1.0472413049447822E+00 a      2002     1     8     2     2\n  2.1270075261563209E-01 a      2003     1     8     2     3\n  1.0059956884525167E-02 a      2004     1     8     2     4\n -5.6674331507128162E-01 a      2005     1     8     2     5\n -4.1069951508364727E-01 a      2006     1     8     2     6\n -5.7946760577066525E-01 a      2007     1     8     2     7\n -6.9320514952269952E-01 a      2008     1     8     2     8\n -2.6235771311219197E-01 a      2009     1     8     2     9\n -4.9114985182179943E-01 a      2010     1     8     2    10\n -6.4751077129371837E-01 a      2011     1     8     2    11\n  1.6623516048991380E-01 a      2012     1     8     2    12\n -1.3252784721447061E-01 a      2013     1     8     2    13\n  6.3617130518492077E-02 a      2014     1     8     2    14\n -7.9749770183388205E-02 a      2015     1     8     2    15\n  2.6810344620231513E-01 a      2016     1     8     2    16\n -1.0886590179511721E-01 a      2017     1     8     2    17\n -8.5635070249057671E-02 a      2018     1     8     2    18\n -8.5883419432118385E-02 a      2019     1     8     2    19\n  1.4001812857233212E-01 a      2020     1     8     2    20\n  2.4652559241660935E-01 a      2021     1     8     2    21\n -1.1705271450291483E-02 a      2022     1     8     2    22\n  5.1059887324814701E-01 a      2023     1     8     2    23\n -9.2777234250212143E-02 a      2024     1     8     2    24\n -6.6631934340703591E-01 a      2025     1     8     2    25\n  4.4575672600804567E-01 a      2026     1     9     2     1\n -6.7107163032432227E-01 a      2027     1     9     2     2\n -3.0179267369944862E-01 a      2028     1     9     2     3\n -1.3598496288690123E+00 a      2029     1     9     2     4\n -1.4940270248112404E+00 a      2030     1     9     2     5\n -2.2080339138801010E-02 a      2031     1     9     2     6\n -5.7301816910865744E-01 a      2032     1     9     2     7\n -1.0063124051587569E-01 a      2033     1     9     2     8\n -2.3012172042264027E+00 a      2034     1     9     2     9\n  1.0885556179246252E+00 a      2035     1     9     2    10\n -1.1526492907689538E+00 a      2036     1     9     2    11\n  3.9520279659304998E-02 a      2037     1     9     2    12\n  2.7509795088948047E-01 a      2038     1     9     2    13\n -3.2176987618681385E-01 a      2039     1     9     2    14\n  1.2152345255401775E+00 a      2040     1     9     2    15\n  6.7561788359563746E-01 a      2041     1     9     2    16\n  1.2756402711221351E-01 a      2042     1     9     2    17\n  4.2778010903937930E-02 a      2043     1     9     2    18\n  2.2524717454514478E-01 a      2044     1     9     2    19\n -5.9203499543104976E-01 a      2045     1     9     2    20\n  1.9472787318819443E-01 a      2046     1     9     2    21\n  2.6372584248809827E-01 a      2047     1     9     2    22\n -1.2605296128570485E+00 a      2048     1     9     2    23\n -4.2493619774884570E-02 a      2049     1     9     2    24\n -3.2689975704292223E-01 a      2050     1     9     2    25\n -5.0316442252296556E-01 a      2051     1    10     2     1\n -1.2776598471010672E+00 a      2052     1    10     2     2\n  3.2727687173561748E-01 a      2053     1    10     2     3\n -5.2750979806146270E-01 a      2054     1    10     2     4\n -5.2100917223171461E-01 a      2055     1    10     2     5\n  1.0271103871270988E+00 a      2056     1    10     2     6\n -1.3174585043808176E+00 a      2057     1    10     2     7\n  1.7860344423744762E-01 a      2058     1    10     2     8\n -3.1935218220133910E-01 a      2059     1    10     2     9\n  4.0624355231658738E-01 a      2060     1    10     2    10\n -8.4263015301232114E-01 a      2061     1    10     2    11\n -4.1311568727252523E-01 a      2062     1    10     2    12\n -2.0250507836832625E+00 a      2063     1    10     2    13\n -4.9669616476317113E-01 a      2064     1    10     2    14\n  1.4542353491363211E+00 a      2065     1    10     2    15\n -1.0829455537390682E-01 a      2066     1    10     2    16\n  3.0637661429549540E-01 a      2067     1    10     2    17\n  3.9830418172493465E-01 a      2068     1    10     2    18\n -1.6636558535137880E+00 a      2069     1    10     2    19\n  7.0498166711701593E-01 a      2070     1    10     2    20\n -3.8215339196853010E-01 a      2071     1    10     2    21\n -2.9475963780786207E-01 a      2072     1    10     2    22\n  1.2815404826499932E+00 a      2073     1    10     2    23\n  3.7464874577430729E-01 a      2074     1    10     2    24\n  6.7369985980501002E-01 a      2075     1    10     2    25\n  1.4787802212199200E-01 a      2076     1    11     2     1\n  2.3652422194864106E-01 a      2077     1    11     2     2\n -2.9319277439498237E-01 a      2078     1    11     2     3\n  8.1893235515044593E-01 a      2079     1    11     2     4\n -5.4251461750474061E-01 a      2080     1    11     2     5\n -7.9432325051447306E-01 a      2081     1    11     2     6\n  5.6741940214747433E-01 a      2082     1    11     2     7\n -1.9883538594217587E-01 a      2083     1    11     2     8\n  2.4059652163192724E-01 a      2084     1    11     2     9\n  9.0487535694630072E-01 a      2085     1    11     2    10\n  2.1500450010677571E-01 a      2086     1    11     2    11\n -8.8392848708160249E-02 a      2087     1    11     2    12\n  4.8911199216330936E-01 a      2088     1    11     2    13\n  3.8501747509679890E-01 a      2089     1    11     2    14\n  2.0880386832367939E-01 a      2090     1    11     2    15\n -1.2898150999726214E+00 a      2091     1    11     2    16\n -6.7684897098766336E-02 a      2092     1    11     2    17\n -1.3226797298228404E-01 a      2093     1    11     2    18\n -7.0860409533946489E-01 a      2094     1    11     2    19\n  2.0428970671759283E-01 a      2095     1    11     2    20\n  6.1788460934391509E-01 a      2096     1    11     2    21\n -1.5387742244322317E-02 a      2097     1    11     2    22\n -2.9187261106596285E-01 a      2098     1    11     2    23\n -2.7435985561202314E-01 a      2099     1    11     2    24\n -2.9893757922781268E-02 a      2100     1    11     2    25\n  1.4366492019663546E-01 a      2101     1    12     2     1\n -8.3708506447152686E-01 a      2102     1    12     2     2\n  8.4900741982625050E-01 a      2103     1    12     2     3\n -3.1763858239521897E-01 a      2104     1    12     2     4\n -8.5836557564984983E-02 a      2105     1    12     2     5\n  4.8971995238975233E-02 a      2106     1    12     2     6\n -8.6345064469884769E-01 a      2107     1    12     2     7\n -1.8877691890216164E+00 a      2108     1    12     2     8\n  4.7870208924774238E-01 a      2109     1    12     2     9\n -2.6803285718567860E-01 a      2110     1    12     2    10\n -8.3576740507701341E-01 a      2111     1    12     2    11\n -2.0233607775747742E-01 a      2112     1    12     2    12\n -2.0851336604971404E+00 a      2113     1    12     2    13\n  5.5710849793933925E-02 a      2114     1    12     2    14\n -2.5441709390192631E+00 a      2115     1    12     2    15\n  1.1056110845657674E+00 a      2116     1    12     2    16\n  4.1604534414542688E-01 a      2117     1    12     2    17\n -2.4025453894460813E-01 a      2118     1    12     2    18\n -4.8834369066457661E-01 a      2119     1    12     2    19\n  1.2885571052723108E-01 a      2120     1    12     2    20\n -5.4132000309146744E-01 a      2121     1    12     2    21\n -1.7269282812154974E-01 a      2122     1    12     2    22\n -5.8064851629878863E-03 a      2123     1    12     2    23\n -1.4394463497698487E-01 a      2124     1    12     2    24\n -4.2487948203957382E-01 a      2125     1    12     2    25\n  5.8675042735952393E-02 a      2126     1    13     2     1\n  1.7863972211172008E-01 a      2127     1    13     2     2\n  4.5741880103604365E-01 a      2128     1    13     2     3\n  9.1416506499137384E-01 a      2129     1    13     2     4\n -7.3674367315233913E-01 a      2130     1    13     2     5\n -3.0779431852369288E-01 a      2131     1    13     2     6\n -3.2999352842234286E-01 a      2132     1    13     2     7\n -5.4956662968530401E-01 a      2133     1    13     2     8\n -8.2136164243233878E-01 a      2134     1    13     2     9\n  1.2183161209162805E+00 a      2135     1    13     2    10\n -1.2314580021681576E-04 a      2136     1    13     2    11\n -1.0026980899080576E-01 a      2137     1    13     2    12\n -7.5923362473088618E-01 a      2138     1    13     2    13\n  8.7341315448514784E-02 a      2139     1    13     2    14\n  2.5889498070253123E+00 a      2140     1    13     2    15\n  3.2846563407201890E-01 a      2141     1    13     2    16\n  2.4140079639811293E-01 a      2142     1    13     2    17\n  6.6559640464078706E-01 a      2143     1    13     2    18\n -6.0228182791517193E-01 a      2144     1    13     2    19\n  5.0959148190761594E-01 a      2145     1    13     2    20\n -1.8343764259383200E-01 a      2146     1    13     2    21\n -2.0541935684248189E-01 a      2147     1    13     2    22\n  5.2020354314273987E-01 a      2148     1    13     2    23\n  2.8411193388383044E-01 a      2149     1    13     2    24\n  1.5031583886753237E+00 a      2150     1    13     2    25\n -1.5611135743074465E+00 a      2151     1    14     2     1\n -3.2360297425207724E-01 a      2152     1    14     2     2\n -2.8070095488766600E-01 a      2153     1    14     2     3\n -4.2682370987576490E-01 a      2154     1    14     2     4\n -8.0124669652434721E-01 a      2155     1    14     2     5\n  6.0916260028745439E-01 a      2156     1    14     2     6\n -1.3043834885545900E+00 a      2157     1    14     2     7\n -1.1114567839213945E+00 a      2158     1    14     2     8\n -7.6508338871898718E-01 a      2159     1    14     2     9\n  1.7394319780653198E+00 a      2160     1    14     2    10\n  6.1580012015667462E-01 a      2161     1    14     2    11\n -2.1501534971396988E-01 a      2162     1    14     2    12\n  8.1316399521310057E-01 a      2163     1    14     2    13\n -1.2944835426827954E+00 a      2164     1    14     2    14\n  3.6338934043065596E-02 a      2165     1    14     2    15\n -9.7464822438627852E-01 a      2166     1    14     2    16\n -2.4145501724766127E-01 a      2167     1    14     2    17\n -8.8876835360975071E-03 a      2168     1    14     2    18\n -5.8076528324547438E-01 a      2169     1    14     2    19\n -2.0411437917641737E+00 a      2170     1    14     2    20\n -4.2526015090964880E-01 a      2171     1    14     2    21\n  5.9996421373152897E-01 a      2172     1    14     2    22\n -3.6675255943507928E-02 a      2173     1    14     2    23\n  1.3185398858057240E-01 a      2174     1    14     2    24\n -2.0032286135136248E+00 a      2175     1    14     2    25\n  5.1591662327951759E-01 a      2176     1    15     2     1\n -2.5446052702797714E-03 a      2177     1    15     2     2\n -8.1769338860501051E-01 a      2178     1    15     2     3\n -6.8480492422848949E-01 a      2179     1    15     2     4\n  1.6061689254540090E+00 a      2180     1    15     2     5\n -3.6828605283363745E+00 a      2181     1    15     2     6\n -2.6949729107316758E+00 a      2182     1    15     2     7\n -8.7436479908358988E-01 a      2183     1    15     2     8\n -7.2537234627087488E-01 a      2184     1    15     2     9\n  1.7554101736285144E+00 a      2185     1    15     2    10\n -1.5729036376143151E+00 a      2186     1    15     2    11\n -4.7196403406815074E-01 a      2187     1    15     2    12\n  2.4686309706562368E+00 a      2188     1    15     2    13\n -8.1429048034865914E-01 a      2189     1    15     2    14\n  1.2457943097534157E+00 a      2190     1    15     2    15\n -1.8238343315299035E+00 a      2191     1    15     2    16\n -9.1710155695980261E-02 a      2192     1    15     2    17\n -1.7104412957602122E+00 a      2193     1    15     2    18\n  2.7030869802557012E-01 a      2194     1    15     2    19\n -1.7298684033912173E+00 a      2195     1    15     2    20\n -3.1058841915893948E-01 a      2196     1    15     2    21\n  1.8274844624858664E+00 a      2197     1    15     2    22\n -1.3513314668634027E+00 a      2198     1    15     2    23\n -1.1539080164302253E+00 a      2199     1    15     2    24\n  3.7623134982371026E-01 a      2200     1    15     2    25\n  3.8564708777748902E-01 a      2201     1    16     2     1\n -3.7485013341251339E-01 a      2202     1    16     2     2\n  3.0694902381634054E-01 a      2203     1    16     2     3\n -6.3820812530951954E-01 a      2204     1    16     2     4\n  6.1596951581411624E-02 a      2205     1    16     2     5\n  3.1823666483179947E-01 a      2206     1    16     2     6\n -1.7451214484287221E+00 a      2207     1    16     2     7\n  6.6928800449640258E-01 a      2208     1    16     2     8\n -1.1768614713311631E+00 a      2209     1    16     2     9\n -1.2657577834196381E+00 a      2210     1    16     2    10\n -3.0160201061177228E-01 a      2211     1    16     2    11\n -5.3877877406889563E-01 a      2212     1    16     2    12\n -8.6493612190989910E-01 a      2213     1    16     2    13\n -8.8460225776662071E-01 a      2214     1    16     2    14\n  1.9057948312439157E+00 a      2215     1    16     2    15\n -2.7200418390588271E-01 a      2216     1    16     2    16\n  1.9952889394862189E-01 a      2217     1    16     2    17\n  7.9321718120701656E-02 a      2218     1    16     2    18\n -7.5240700188026213E-02 a      2219     1    16     2    19\n  3.5188674964451849E-01 a      2220     1    16     2    20\n  4.4883278162576262E-01 a      2221     1    16     2    21\n  2.4951384292998435E-01 a      2222     1    16     2    22\n  1.6851679055279442E-01 a      2223     1    16     2    23\n -4.8371544786080266E-02 a      2224     1    16     2    24\n  8.1495784381186021E-01 a      2225     1    16     2    25\n -7.7932092504504180E-01 a      2226     1    17     2     1\n  8.4308356300312914E-01 a      2227     1    17     2     2\n  6.2801495977484001E-01 a      2228     1    17     2     3\n -1.6671863188240814E-02 a      2229     1    17     2     4\n  4.9617622666448757E-01 a      2230     1    17     2     5\n  2.8578791610744131E-01 a      2231     1    17     2     6\n  5.0261300134126208E-01 a      2232     1    17     2     7\n  4.2973672296612153E-01 a      2233     1    17     2     8\n  2.0605776991439645E-02 a      2234     1    17     2     9\n  3.1505912130803543E-01 a      2235     1    17     2    10\n -4.8141644197770223E-01 a      2236     1    17     2    11\n  6.5147019223382929E-01 a      2237     1    17     2    12\n  1.3223922139341173E-02 a      2238     1    17     2    13\n  1.3552951191767832E+00 a      2239     1    17     2    14\n -2.7683725661405684E-01 a      2240     1    17     2    15\n -1.4553982661789062E+00 a      2241     1    17     2    16\n  1.3934738472514663E-01 a      2242     1    17     2    17\n  6.5662014192387624E-02 a      2243     1    17     2    18\n  3.9097955051468730E-01 a      2244     1    17     2    19\n -1.5329149954135943E+00 a      2245     1    17     2    20\n -4.9182889227766408E-01 a      2246     1    17     2    21\n -8.4101247787721850E-02 a      2247     1    17     2    22\n  1.1079957740309260E-01 a      2248     1    17     2    23\n  1.2653734338244162E+00 a      2249     1    17     2    24\n  5.1889782109670390E-01 a      2250     1    17     2    25\n -3.5701303156391490E-01 a      2251     1    18     2     1\n -2.3369886700637788E-01 a      2252     1    18     2     2\n  1.8192889993017079E-02 a      2253     1    18     2     3\n -1.9089403601514085E-01 a      2254     1    18     2     4\n -2.2245213004847283E-01 a      2255     1    18     2     5\n -4.1704360216982245E-01 a      2256     1    18     2     6\n -5.9376327509449600E-01 a      2257     1    18     2     7\n  4.7700366121749904E-01 a      2258     1    18     2     8\n -2.4234013871626243E+00 a      2259     1    18     2     9\n -3.4319600817672740E+00 a      2260     1    18     2    10\n  1.4602063702387118E+00 a      2261     1    18     2    11\n -4.8017949262669966E-02 a      2262     1    18     2    12\n -2.5388955532842389E-01 a      2263     1    18     2    13\n -4.4955574787101665E-01 a      2264     1    18     2    14\n -5.9686971656068388E-01 a      2265     1    18     2    15\n  1.5329181413373798E+00 a      2266     1    18     2    16\n -1.7745540088419492E-01 a      2267     1    18     2    17\n -6.8356066126928808E-02 a      2268     1    18     2    18\n -5.7868883010994010E-01 a      2269     1    18     2    19\n -2.4958945618463482E-01 a      2270     1    18     2    20\n -8.8915588088891362E-01 a      2271     1    18     2    21\n  4.6796145878627105E-01 a      2272     1    18     2    22\n  3.7239838802427244E-01 a      2273     1    18     2    23\n  5.8825012698306467E-01 a      2274     1    18     2    24\n -2.5213870537746796E-01 a      2275     1    18     2    25\n -4.0945577957805229E-01 a      2276     1    19     2     1\n -6.3926426566269479E-01 a      2277     1    19     2     2\n -2.4803832950792159E-03 a      2278     1    19     2     3\n -9.5504254863097604E-01 a      2279     1    19     2     4\n  2.4385416954208063E-02 a      2280     1    19     2     5\n  1.8105456314263782E-01 a      2281     1    19     2     6\n -1.3959803913453275E+00 a      2282     1    19     2     7\n -1.4647235163838312E+00 a      2283     1    19     2     8\n -8.0598524282205181E-02 a      2284     1    19     2     9\n -6.8890711362406043E-01 a      2285     1    19     2    10\n  7.4049128505740025E-01 a      2286     1    19     2    11\n -1.8107652733146301E-01 a      2287     1    19     2    12\n  1.1180459617056233E-01 a      2288     1    19     2    13\n -9.7523288912192785E-01 a      2289     1    19     2    14\n  5.4031707452495070E-01 a      2290     1    19     2    15\n -8.6865875639635415E-01 a      2291     1    19     2    16\n -1.1736299949303194E-03 a      2292     1    19     2    17\n -2.1796832363882152E-01 a      2293     1    19     2    18\n -2.0197745129587785E-01 a      2294     1    19     2    19\n -2.0649260039989298E-01 a      2295     1    19     2    20\n -2.5945409305212930E-01 a      2296     1    19     2    21\n -5.3195384264402990E-01 a      2297     1    19     2    22\n  6.1477888542849975E-02 a      2298     1    19     2    23\n -6.9385778198627257E-01 a      2299     1    19     2    24\n  3.3845607119781312E-01 a      2300     1    19     2    25\n  4.0809678373584041E-02 a      2301     1    20     2     1\n  3.2924070883990825E-01 a      2302     1    20     2     2\n -3.9610966191553226E-01 a      2303     1    20     2     3\n -2.0132651897409879E+00 a      2304     1    20     2     4\n  2.4484241841952716E+00 a      2305     1    20     2     5\n  5.3570194814429040E-01 a      2306     1    20     2     6\n  3.9782963410556638E-01 a      2307     1    20     2     7\n  4.9250587897907255E-01 a      2308     1    20     2     8\n -9.0581905870919688E-01 a      2309     1    20     2     9\n  9.6720818758476146E-01 a      2310     1    20     2    10\n -2.4290730668752603E+00 a      2311     1    20     2    11\n  8.5170505147369346E-01 a      2312     1    20     2    12\n -2.1483680686887496E-01 a      2313     1    20     2    13\n  1.0883989821232398E+00 a      2314     1    20     2    14\n -4.2448276419305673E+00 a      2315     1    20     2    15\n  1.3220278308357323E+00 a      2316     1    20     2    16\n  2.0515176886377723E-01 a      2317     1    20     2    17\n  4.3773484307033583E-01 a      2318     1    20     2    18\n -1.3786340518033451E+00 a      2319     1    20     2    19\n -2.2372534223710475E-01 a      2320     1    20     2    20\n -2.7758118237942005E-02 a      2321     1    20     2    21\n -3.6463714150317883E-01 a      2322     1    20     2    22\n -1.4652346461706460E+00 a      2323     1    20     2    23\n -1.9948609569365011E-01 a      2324     1    20     2    24\n -1.2992922004186624E+00 a      2325     1    20     2    25\n -5.4234465116761910E-01 a      2326     1    21     2     1\n -1.1703464645203435E-01 a      2327     1    21     2     2\n  2.7846604110004280E-01 a      2328     1    21     2     3\n  4.2152065037688702E-01 a      2329     1    21     2     4\n -3.1812648076931704E-01 a      2330     1    21     2     5\n  2.5354733798445972E-01 a      2331     1    21     2     6\n  5.0508300555905372E-01 a      2332     1    21     2     7\n -1.8871360552404024E+00 a      2333     1    21     2     8\n -1.8179368004635235E+00 a      2334     1    21     2     9\n -9.1331416740862581E-01 a      2335     1    21     2    10\n  1.0900023434903663E+00 a      2336     1    21     2    11\n  8.9874047451855385E-02 a      2337     1    21     2    12\n -1.2847531299662041E+00 a      2338     1    21     2    13\n -7.4525540480534103E-01 a      2339     1    21     2    14\n  1.0535696198186528E+00 a      2340     1    21     2    15\n  7.8428574671901730E-01 a      2341     1    21     2    16\n  1.3814042929844125E-01 a      2342     1    21     2    17\n  6.9643061019999272E-02 a      2343     1    21     2    18\n  8.0359279616965651E-01 a      2344     1    21     2    19\n -5.6529681854842539E-01 a      2345     1    21     2    20\n -2.3488037904274034E-02 a      2346     1    21     2    21\n  2.1341829380240665E-01 a      2347     1    21     2    22\n -1.4102093313296238E-01 a      2348     1    21     2    23\n -1.6582794027459599E-01 a      2349     1    21     2    24\n -2.1114013691856662E-01 a      2350     1    21     2    25\n  2.4212589160209405E-01 a      2351     1    22     2     1\n  3.9327330796009152E-01 a      2352     1    22     2     2\n -3.6566016634832049E-01 a      2353     1    22     2     3\n  1.0287117668616212E+00 a      2354     1    22     2     4\n  1.6899708282115562E+00 a      2355     1    22     2     5\n  4.3429485581693034E-01 a      2356     1    22     2     6\n  1.7977381066015556E+00 a      2357     1    22     2     7\n  2.9196281691007775E-01 a      2358     1    22     2     8\n  8.9048235778413076E-01 a      2359     1    22     2     9\n -2.7029855626099626E+00 a      2360     1    22     2    10\n -9.9842398461553661E-01 a      2361     1    22     2    11\n  1.3261280174131618E-01 a      2362     1    22     2    12\n  7.8677628275123768E-01 a      2363     1    22     2    13\n -1.6176772224659823E+00 a      2364     1    22     2    14\n -2.9218429770545273E+00 a      2365     1    22     2    15\n -1.0470075932239322E+00 a      2366     1    22     2    16\n -6.2813242798639934E-01 a      2367     1    22     2    17\n -1.1926621420051280E+00 a      2368     1    22     2    18\n  5.6467524440711148E-01 a      2369     1    22     2    19\n  7.0550764585496206E-01 a      2370     1    22     2    20\n  6.7061497370680800E-01 a      2371     1    22     2    21\n  3.2149813491975643E-01 a      2372     1    22     2    22\n -6.5948083157745863E-01 a      2373     1    22     2    23\n  1.4878019494104766E-01 a      2374     1    22     2    24\n -1.4238392562512412E+00 a      2375     1    22     2    25\n -2.9244659427496789E+00 a      2376     1    23     2     1\n  1.1485640801249154E-01 a      2377     1    23     2     2\n  1.1880136805560255E-01 a      2378     1    23     2     3\n  1.9995339152108655E+00 a      2379     1    23     2     4\n -8.8052571584319517E-01 a      2380     1    23     2     5\n -7.6723479106454269E+00 a      2381     1    23     2     6\n -1.6775055426770660E-01 a      2382     1    23     2     7\n  1.1568877491878693E+00 a      2383     1    23     2     8\n -3.6248359285478049E-01 a      2384     1    23     2     9\n -1.0171667144821397E+00 a      2385     1    23     2    10\n -9.7885097010848721E-01 a      2386     1    23     2    11\n  1.7525905926099136E-01 a      2387     1    23     2    12\n  1.6667129102202356E+00 a      2388     1    23     2    13\n -6.3496168416867071E-01 a      2389     1    23     2    14\n -3.9752798317985540E+00 a      2390     1    23     2    15\n -3.0889419514464751E+00 a      2391     1    23     2    16\n -1.6580901185939814E-01 a      2392     1    23     2    17\n -3.0257630892267329E-01 a      2393     1    23     2    18\n  1.1693501120123342E+00 a      2394     1    23     2    19\n -4.4706334843197343E-01 a      2395     1    23     2    20\n  6.3453286866045877E-01 a      2396     1    23     2    21\n  1.9358044980890732E+00 a      2397     1    23     2    22\n  3.1113852281756920E+00 a      2398     1    23     2    23\n -1.9662951755400133E+00 a      2399     1    23     2    24\n -7.5262034829552482E-01 a      2400     1    23     2    25\n -1.0570204013747100E+00 a      2401     1    24     2     1\n  2.0242154350721828E-01 a      2402     1    24     2     2\n -6.1919254330906649E-02 a      2403     1    24     2     3\n -9.3075303350374716E-01 a      2404     1    24     2     4\n -9.4855833806427159E-01 a      2405     1    24     2     5\n  1.2813916759344554E-01 a      2406     1    24     2     6\n -2.0331973717312746E+00 a      2407     1    24     2     7\n  3.0837174823873076E-01 a      2408     1    24     2     8\n  3.7215037809188369E-02 a      2409     1    24     2     9\n  3.9279821894082573E-01 a      2410     1    24     2    10\n  1.1362819017641221E-01 a      2411     1    24     2    11\n -1.3856723422770947E-01 a      2412     1    24     2    12\n -9.0761795928204336E-01 a      2413     1    24     2    13\n -1.9312687936000594E+00 a      2414     1    24     2    14\n  2.4072402343893264E+00 a      2415     1    24     2    15\n -1.3575532169402038E+00 a      2416     1    24     2    16\n -5.0043337242109498E-01 a      2417     1    24     2    17\n  6.6622788206750017E-01 a      2418     1    24     2    18\n -2.7744853244980633E-01 a      2419     1    24     2    19\n -3.3208589628698015E-01 a      2420     1    24     2    20\n -6.5082760242357884E-01 a      2421     1    24     2    21\n -7.4238152455462947E-01 a      2422     1    24     2    22\n  3.5709111009352618E-01 a      2423     1    24     2    23\n  6.1990222796862571E-01 a      2424     1    24     2    24\n  1.1667603307669538E+00 a      2425     1    24     2    25\n  3.4874499133420743E-02 a      2426     1    25     2     1\n  4.6834087122092077E-01 a      2427     1    25     2     2\n -2.4278656264438364E-01 a      2428     1    25     2     3\n -4.7923572182631186E-01 a      2429     1    25     2     4\n  9.1932774354097346E-01 a      2430     1    25     2     5\n  6.9805008912145541E-03 a      2431     1    25     2     6\n -4.0244240337174698E-02 a      2432     1    25     2     7\n  2.3085018839417204E-01 a      2433     1    25     2     8\n  4.1477758640374958E-02 a      2434     1    25     2     9\n -2.9907893871952584E-01 a      2435     1    25     2    10\n  9.9861813798121868E-01 a      2436     1    25     2    11\n  6.1719473832720140E-01 a      2437     1    25     2    12\n  7.7349291753880958E-02 a      2438     1    25     2    13\n  1.9789467747705813E-01 a      2439     1    25     2    14\n -1.6963001394405985E+00 a      2440     1    25     2    15\n  1.6964283624354803E+00 a      2441     1    25     2    16\n -1.2412318165627852E-02 a      2442     1    25     2    17\n -3.0090042509304782E+00 a      2443     1    25     2    18\n -5.2854050109483008E-01 a      2444     1    25     2    19\n -4.0883552444931642E-01 a      2445     1    25     2    20\n -6.7332635048994605E-01 a      2446     1    25     2    21\n -1.9391822634747917E-02 a      2447     1    25     2    22\n  3.7493997817479574E-01 a      2448     1    25     2    23\n -3.1982153221239995E-01 a      2449     1    25     2    24\n -6.5908145380152439E-02 a      2450     1    25     2    25\n  3.6520581763320918E+00 b      2451     2     1\n  8.0350355841113590E+00 b      2452     2     2\n  1.0328413848960700E+00 b      2453     2     3\n  7.2118044450618859E+00 b      2454     2     4\n  1.6897857032469032E+00 b      2455     2     5\n -5.3128298088875221E+00 b      2456     2     6\n  1.1119283095513778E+01 b      2457     2     7\n  5.6335078037870667E-01 b      2458     2     8\n  3.1863573747908753E+00 b      2459     2     9\n -1.5027072914328254E+01 b      2460     2    10\n  4.2491825701309507E+00 b      2461     2    11\n  1.1953389718194374E+00 b      2462     2    12\n -3.7826613521070804E+00 b      2463     2    13\n  2.5804189796272916E+00 b      2464     2    14\n -1.8825899893966049E+01 b      2465     2    15\n  5.0689924546781171E+00 b      2466     2    16\n -4.2675620759638759E+00 b      2467     2    17\n -2.2492760679197388E+00 b      2468     2    18\n  3.5306849260434596E+00 b      2469     2    19\n -4.5612849025174862E+00 b      2470     2    20\n  2.5261284082068989E+00 b      2471     2    21\n  4.9997935137889167E+00 b      2472     2    22\n -1.0317047947417777E+01 b      2473     2    23\n -8.8894968314347089E+00 b      2474     2    24\n -2.4854869056932949E+00 b      2475     2    25\n  7.7377789653328519E-02 a      2476     2     1     3     1\n  3.8948596770158572E-01 a      2477     2     2     3     1\n  1.7977756447195445E-01 a      2478     2     3     3     1\n  6.2246542349685442E-02 a      2479     2     4     3     1\n -1.1775426437182669E-02 a      2480     2     5     3     1\n  7.4084231368981346E-02 a      2481     2     6     3     1\n -2.6739218038996107E-02 a      2482     2     7     3     1\n -1.4199418404546765E-01 a      2483     2     8     3     1\n -1.3644380226489719E-01 a      2484     2     9     3     1\n  4.2740071857011105E-02 a      2485     2    10     3     1\n -8.4658663941687990E-03 a      2486     2    11     3     1\n  1.8776930772068579E-01 a      2487     2    12     3     1\n -6.7008756457919524E-02 a      2488     2    13     3     1\n  4.7698142607044192E-02 a      2489     2    14     3     1\n -1.3372183470389412E-01 a      2490     2    15     3     1\n  4.0870498106272558E-02 a      2491     2    16     3     1\n  1.7572570907757842E-01 a      2492     2    17     3     1\n -1.6327794687227459E-01 a      2493     2    18     3     1\n -5.9707729641314558E-02 a      2494     2    19     3     1\n  1.0563906282310645E-01 a      2495     2    20     3     1\n  6.6231803238242182E-02 a      2496     2    21     3     1\n -2.7962585890502650E-01 a      2497     2    22     3     1\n  1.6032832788645526E-01 a      2498     2    23     3     1\n -1.0623041830538342E-01 a      2499     2    24     3     1\n  1.0896429147371821E-01 a      2500     2    25     3     1\n -1.3407810853851474E+00 b      2501     3     1\n"
  },
  {
    "path": "examples/nnp-dataset/Cu2S_PBE/weights.029.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -6.2446602207005186E-01 a         1     0     1     1     1\n  7.9109168478070069E-01 a         2     0     1     1     2\n  5.0258947941284748E-01 a         3     0     1     1     3\n  5.5154910097820120E-01 a         4     0     1     1     4\n  1.4505158314343458E+00 a         5     0     1     1     5\n -3.6571470924977034E-01 a         6     0     1     1     6\n  4.7092493582249750E-01 a         7     0     1     1     7\n  1.7219501990786370E+00 a         8     0     1     1     8\n -1.3599868727171069E-01 a         9     0     1     1     9\n  5.5171059902123576E-01 a        10     0     1     1    10\n -1.3239450297968971E+00 a        11     0     1     1    11\n  7.9289101991721189E-01 a        12     0     1     1    12\n -2.4436241907430895E-01 a        13     0     1     1    13\n  1.2669669007011655E+00 a        14     0     1     1    14\n -1.0859472353178850E+00 a        15     0     1     1    15\n  5.7149297331656246E-01 a        16     0     1     1    16\n  1.1787879403665555E+00 a        17     0     1     1    17\n  5.1959050316647970E-01 a        18     0     1     1    18\n -5.2070371830737283E-01 a        19     0     1     1    19\n -8.6539404799579653E-02 a        20     0     1     1    20\n -1.1403926908826987E+00 a        21     0     1     1    21\n  7.2846619332612425E-02 a        22     0     1     1    22\n -6.0675985144277489E-01 a        23     0     1     1    23\n  1.6628179166765720E+00 a        24     0     1     1    24\n  1.0538483108672489E+00 a        25     0     1     1    25\n -7.0622748176492056E-01 a        26     0     2     1     1\n  1.0910592071347260E+00 a        27     0     2     1     2\n  2.4631386883986663E+00 a        28     0     2     1     3\n  1.1474600047546029E+00 a        29     0     2     1     4\n -2.7984407189871603E+00 a        30     0     2     1     5\n  1.0533577807665364E-02 a        31     0     2     1     6\n 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1.6244338649202151E-02 a      1893     1     9     2    18\n  2.8159940956926782E-02 a      1894     1     9     2    19\n -7.3760105274932919E-01 a      1895     1     9     2    20\n  1.0604614152784235E-01 a      1896     1     9     2    21\n  1.3087759494518761E-01 a      1897     1     9     2    22\n  2.9873262087000452E-01 a      1898     1     9     2    23\n -7.5121649539691160E-01 a      1899     1     9     2    24\n -5.3923107796072600E-01 a      1900     1     9     2    25\n -9.4224670371027917E-03 a      1901     1    10     2     1\n  1.7582720220947401E-01 a      1902     1    10     2     2\n -4.3499560356818456E-02 a      1903     1    10     2     3\n  2.7310295785198496E-01 a      1904     1    10     2     4\n -1.4711568084768856E+00 a      1905     1    10     2     5\n -4.4204405689495387E-02 a      1906     1    10     2     6\n  6.0834648389602855E-02 a      1907     1    10     2     7\n -2.4139577578874571E+00 a      1908     1    10     2     8\n 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3.4421830988038693E-01 a      1925     1    10     2    25\n  6.4169421416549660E-02 a      1926     1    11     2     1\n -1.5453028953359832E-01 a      1927     1    11     2     2\n -3.3937811286737152E-01 a      1928     1    11     2     3\n -2.7264685928399618E-02 a      1929     1    11     2     4\n -1.3046027284183024E+00 a      1930     1    11     2     5\n -2.7987570911040532E-01 a      1931     1    11     2     6\n -7.1818879614311160E-01 a      1932     1    11     2     7\n -1.1206386399096295E+00 a      1933     1    11     2     8\n  5.8589221854259044E-01 a      1934     1    11     2     9\n -3.7755430943908636E-01 a      1935     1    11     2    10\n -2.4227661602201420E-01 a      1936     1    11     2    11\n -6.6802170984862275E-01 a      1937     1    11     2    12\n -1.0335031399378087E+00 a      1938     1    11     2    13\n  2.7352884921752563E-01 a      1939     1    11     2    14\n -7.7644903482906286E-02 a      1940     1    11     2    15\n -1.2483161225817251E-01 a      1941     1    11     2    16\n -1.0076823380037454E-01 a      1942     1    11     2    17\n  1.8474479042673506E-02 a      1943     1    11     2    18\n  1.5921923675493641E-01 a      1944     1    11     2    19\n -8.6092467903913172E-01 a      1945     1    11     2    20\n  3.1597658763496336E-02 a      1946     1    11     2    21\n  1.2582027961569384E-01 a      1947     1    11     2    22\n  4.1552569278194468E-01 a      1948     1    11     2    23\n -1.8547083512843898E-01 a      1949     1    11     2    24\n -3.1841028886761663E-01 a      1950     1    11     2    25\n  1.8006197092716905E-01 a      1951     1    12     2     1\n -5.4024199178819454E-01 a      1952     1    12     2     2\n  3.3523776691134710E-01 a      1953     1    12     2     3\n  2.7560028312601675E-01 a      1954     1    12     2     4\n  8.6177633437044554E-01 a      1955     1    12     2     5\n  1.0087407297301751E+00 a      1956     1    12     2     6\n -1.2380927066334282E-01 a      1957     1    12     2     7\n -1.5229780941544174E-01 a      1958     1    12     2     8\n  2.9946743134146903E-01 a      1959     1    12     2     9\n  1.9819105447401073E+00 a      1960     1    12     2    10\n -8.0628486303151947E-01 a      1961     1    12     2    11\n -9.3151349622473523E-01 a      1962     1    12     2    12\n  1.5051328872455074E+00 a      1963     1    12     2    13\n -8.9627139441554438E-01 a      1964     1    12     2    14\n -3.1439437993199801E-02 a      1965     1    12     2    15\n  1.3701630178002484E+00 a      1966     1    12     2    16\n -2.9138443586057278E-01 a      1967     1    12     2    17\n -3.9087530619619010E-01 a      1968     1    12     2    18\n -2.2753042561066517E-01 a      1969     1    12     2    19\n -8.0931038915796594E-01 a      1970     1    12     2    20\n  1.2030804656668543E+00 a      1971     1    12     2    21\n -1.3389862350446610E-01 a      1972     1    12     2    22\n  4.8419262676478225E-01 a      1973     1    12     2    23\n  1.2108153439974718E+00 a      1974     1    12     2    24\n -1.9519966513619349E+00 a      1975     1    12     2    25\n -1.5047045953264607E-01 a      1976     1    13     2     1\n -6.5196314968694580E-01 a      1977     1    13     2     2\n -1.9444580576963033E-01 a      1978     1    13     2     3\n -3.0635873068371338E-03 a      1979     1    13     2     4\n  1.4891889558793558E+00 a      1980     1    13     2     5\n -2.7617795790820687E-01 a      1981     1    13     2     6\n  1.3155600760922213E+00 a      1982     1    13     2     7\n  1.6548881500952060E+00 a      1983     1    13     2     8\n  1.2939743974749243E+00 a      1984     1    13     2     9\n -8.8087806931438950E-01 a      1985     1    13     2    10\n -7.3026619095577089E-02 a      1986     1    13     2    11\n -6.7521271933403364E+00 a      1987     1    13     2    12\n  3.4361606414546986E-01 a      1988     1    13     2    13\n  8.7558578977526269E-01 a      1989     1    13     2    14\n -2.2881702674887253E-01 a      1990     1    13     2    15\n -6.2816527553206336E-01 a      1991     1    13     2    16\n -8.9317308141201190E-01 a      1992     1    13     2    17\n  9.7069680211539489E-01 a      1993     1    13     2    18\n -5.6927576536010438E-01 a      1994     1    13     2    19\n  8.2910381395357602E-01 a      1995     1    13     2    20\n -3.8934674186907103E-01 a      1996     1    13     2    21\n -1.0181364553104701E+00 a      1997     1    13     2    22\n -9.1002882788836370E-01 a      1998     1    13     2    23\n  2.1075571090156360E+00 a      1999     1    13     2    24\n  2.3017239447035212E-01 a      2000     1    13     2    25\n -3.5483123954045620E-01 a      2001     1    14     2     1\n -9.6047986054177317E-02 a      2002     1    14     2     2\n  3.3071183118138114E-01 a      2003     1    14     2     3\n  1.7705379181791761E-01 a      2004     1    14     2     4\n -1.2043718203406772E+00 a      2005     1    14     2     5\n -5.7806038919408154E-01 a      2006     1    14     2     6\n  6.5633162044623850E-01 a      2007     1    14     2     7\n -1.3450535190144031E-01 a      2008     1    14     2     8\n -1.2862521179205477E-01 a      2009     1    14     2     9\n -1.5177254021629161E-01 a      2010     1    14     2    10\n -2.9016357432381029E-01 a      2011     1    14     2    11\n  1.2793982277409728E+00 a      2012     1    14     2    12\n -3.7109006944139383E-01 a      2013     1    14     2    13\n -4.5064222698368622E-01 a      2014     1    14     2    14\n  3.9087439217392134E-02 a      2015     1    14     2    15\n -1.7890737007331405E+00 a      2016     1    14     2    16\n -3.5761366598992050E-01 a      2017     1    14     2    17\n  3.8280249413524364E-01 a      2018     1    14     2    18\n -3.4580266787944813E-01 a      2019     1    14     2    19\n -2.3102511719307051E-01 a      2020     1    14     2    20\n  6.1712210683785684E-02 a      2021     1    14     2    21\n -3.3548067811281668E-01 a      2022     1    14     2    22\n -7.9862203729164616E-01 a      2023     1    14     2    23\n -5.1952466530501407E-01 a      2024     1    14     2    24\n  2.5810393446929092E-01 a      2025     1    14     2    25\n -4.3558412131876484E-01 a      2026     1    15     2     1\n  1.1902629233075568E-01 a      2027     1    15     2     2\n  1.1747512026211912E-01 a      2028     1    15     2     3\n  1.5495247101048408E-02 a      2029     1    15     2     4\n -1.2065420500806932E+00 a      2030     1    15     2     5\n  3.3479165215501783E-01 a      2031     1    15     2     6\n  2.8245317600466197E-01 a      2032     1    15     2     7\n  6.6749992551384099E-02 a      2033     1    15     2     8\n -3.1396609925815760E-01 a      2034     1    15     2     9\n  3.0054714990159620E-01 a      2035     1    15     2    10\n  6.0483428643207637E-01 a      2036     1    15     2    11\n -1.2454958402656351E+00 a      2037     1    15     2    12\n  6.3389744137669779E-01 a      2038     1    15     2    13\n -5.9521423079842484E-01 a      2039     1    15     2    14\n  1.2019169256706089E-01 a      2040     1    15     2    15\n -1.1987245524864630E-01 a      2041     1    15     2    16\n -5.6896152994198784E-02 a      2042     1    15     2    17\n  2.8941200439853954E-01 a      2043     1    15     2    18\n  1.6309209946798925E-01 a      2044     1    15     2    19\n  8.7949523201494928E-01 a      2045     1    15     2    20\n  6.4769343609644300E-02 a      2046     1    15     2    21\n  4.8521193987474981E-01 a      2047     1    15     2    22\n  4.9988972941182691E-01 a      2048     1    15     2    23\n -2.3016622688408100E-01 a      2049     1    15     2    24\n -5.4074197586570194E-01 a      2050     1    15     2    25\n -4.8573302372386212E-01 a      2051     1    16     2     1\n -1.2895431219807293E-01 a      2052     1    16     2     2\n -3.6183115010678968E-01 a      2053     1    16     2     3\n -1.9197089311858578E-01 a      2054     1    16     2     4\n  1.6791441443786570E+00 a      2055     1    16     2     5\n  1.4524232953370153E+00 a      2056     1    16     2     6\n  8.1332800345877809E-01 a      2057     1    16     2     7\n -6.8993826377906453E-01 a      2058     1    16     2     8\n -6.4581623589215043E-01 a      2059     1    16     2     9\n -1.9086496482644792E+00 a      2060     1    16     2    10\n -7.6174424886678238E-01 a      2061     1    16     2    11\n -6.6106476479584952E-01 a      2062     1    16     2    12\n -6.5143307233530923E-01 a      2063     1    16     2    13\n  6.3145424574265796E-01 a      2064     1    16     2    14\n -2.3081494763260896E-01 a      2065     1    16     2    15\n  1.1456064040705682E-01 a      2066     1    16     2    16\n  1.6252315194690317E-01 a      2067     1    16     2    17\n -1.2291397585047813E-01 a      2068     1    16     2    18\n -6.7674808608296347E-02 a      2069     1    16     2    19\n  5.4942310825997287E-01 a      2070     1    16     2    20\n -1.0797615834794017E-01 a      2071     1    16     2    21\n  2.4950326732348715E-01 a      2072     1    16     2    22\n -7.9414639176233692E-01 a      2073     1    16     2    23\n  2.0544441738751792E-01 a      2074     1    16     2    24\n  1.8992443483722937E-01 a      2075     1    16     2    25\n -4.6582766497660771E-01 a      2076     1    17     2     1\n  2.9539156697999569E-01 a      2077     1    17     2     2\n -2.2097168205408066E-01 a      2078     1    17     2     3\n -1.4860622629638501E-01 a      2079     1    17     2     4\n -3.2498215361218613E-01 a      2080     1    17     2     5\n  3.4427076522021333E-01 a      2081     1    17     2     6\n  8.6586127926198697E-01 a      2082     1    17     2     7\n -1.1418000025514305E-01 a      2083     1    17     2     8\n -6.0056682073398004E-01 a      2084     1    17     2     9\n  2.0450736509644665E-01 a      2085     1    17     2    10\n -1.8519278941182027E-01 a      2086     1    17     2    11\n -1.4644629512368172E+00 a      2087     1    17     2    12\n -2.9378404760799470E-01 a      2088     1    17     2    13\n  5.5384788915605931E-01 a      2089     1    17     2    14\n -1.5004256050064771E-01 a      2090     1    17     2    15\n  3.2806846888851510E-01 a      2091     1    17     2    16\n  2.7598536643862270E-01 a      2092     1    17     2    17\n  4.1850888007058207E-01 a      2093     1    17     2    18\n -5.5362304975505497E-02 a      2094     1    17     2    19\n  2.6951266238898874E-01 a      2095     1    17     2    20\n -2.4264170360616094E-02 a      2096     1    17     2    21\n -1.8676465863061775E-01 a      2097     1    17     2    22\n -3.8787011654837039E-01 a      2098     1    17     2    23\n  3.4485637458118229E-01 a      2099     1    17     2    24\n -3.0786400824237545E-02 a      2100     1    17     2    25\n -1.4217762050351745E-01 a      2101     1    18     2     1\n -7.0998782591968046E-01 a      2102     1    18     2     2\n -9.6362930548428383E-01 a      2103     1    18     2     3\n  7.5180370041830813E-02 a      2104     1    18     2     4\n  9.3452511163166374E-01 a      2105     1    18     2     5\n  7.5072353982545093E-01 a      2106     1    18     2     6\n -1.4600462437868158E+00 a      2107     1    18     2     7\n -1.0484471284226574E-01 a      2108     1    18     2     8\n -1.5226425654047304E+00 a      2109     1    18     2     9\n -8.8296305768438263E-02 a      2110     1    18     2    10\n -3.6274389516383643E-01 a      2111     1    18     2    11\n  8.8349447132068071E-01 a      2112     1    18     2    12\n  3.6371290147774743E-01 a      2113     1    18     2    13\n -4.7916817706816656E-01 a      2114     1    18     2    14\n  1.3662341082955812E-01 a      2115     1    18     2    15\n  1.3172314297178116E+00 a      2116     1    18     2    16\n  3.4403068584860565E-02 a      2117     1    18     2    17\n  3.6061432566306936E-02 a      2118     1    18     2    18\n  4.5896212647717503E-02 a      2119     1    18     2    19\n -1.8589693017644275E+00 a      2120     1    18     2    20\n  1.5237137982152765E-01 a      2121     1    18     2    21\n -3.8234921593024973E-01 a      2122     1    18     2    22\n  3.5542438141750315E-02 a      2123     1    18     2    23\n -3.9944133636062124E-01 a      2124     1    18     2    24\n -6.5550378551330324E-01 a      2125     1    18     2    25\n  1.2816550559385723E-01 a      2126     1    19     2     1\n  3.5486759391369166E-02 a      2127     1    19     2     2\n  4.6182319454349319E-01 a      2128     1    19     2     3\n -5.5122652267036590E-03 a      2129     1    19     2     4\n -3.5080949888496260E+00 a      2130     1    19     2     5\n  7.1486948663206473E-01 a      2131     1    19     2     6\n -2.1201853030552007E+00 a      2132     1    19     2     7\n  7.2604028903282403E-01 a      2133     1    19     2     8\n  5.1081128242304719E-01 a      2134     1    19     2     9\n -4.9137504534121196E-01 a      2135     1    19     2    10\n -1.0472694822448174E+00 a      2136     1    19     2    11\n -1.3523763718593251E+00 a      2137     1    19     2    12\n  2.3568530190159431E-01 a      2138     1    19     2    13\n  5.9584736557607831E-01 a      2139     1    19     2    14\n -3.0079808992756946E-02 a      2140     1    19     2    15\n -1.5268283743999284E-01 a      2141     1    19     2    16\n  9.6122412178057212E-02 a      2142     1    19     2    17\n -1.0684936989401796E-01 a      2143     1    19     2    18\n -5.7716017213991798E-02 a      2144     1    19     2    19\n -2.1338482417439314E-01 a      2145     1    19     2    20\n -3.2012152562395965E-02 a      2146     1    19     2    21\n  6.6195535336631889E-02 a      2147     1    19     2    22\n -4.0717271079249823E-01 a      2148     1    19     2    23\n  4.3854075768154355E-01 a      2149     1    19     2    24\n  5.4824793644114189E-01 a      2150     1    19     2    25\n -1.6683810612646832E-01 a      2151     1    20     2     1\n  2.3322749612412674E-01 a      2152     1    20     2     2\n -4.4183715955442193E-01 a      2153     1    20     2     3\n -7.2076827728753526E-02 a      2154     1    20     2     4\n -5.9352383243727491E-01 a      2155     1    20     2     5\n -3.9339117998165263E-01 a      2156     1    20     2     6\n -5.4931274369409873E-02 a      2157     1    20     2     7\n -4.5548835587531822E-01 a      2158     1    20     2     8\n -6.5732706177413358E-01 a      2159     1    20     2     9\n -1.1236237633542311E-01 a      2160     1    20     2    10\n  1.1351566319349074E-02 a      2161     1    20     2    11\n -1.2386831457708261E+00 a      2162     1    20     2    12\n  4.5243628166561789E-01 a      2163     1    20     2    13\n -5.8831183211013338E-01 a      2164     1    20     2    14\n -8.3869411335455488E-02 a      2165     1    20     2    15\n -7.0984549162019170E-02 a      2166     1    20     2    16\n  3.3054811913793787E-02 a      2167     1    20     2    17\n  1.9644857020909354E-01 a      2168     1    20     2    18\n  1.5161782757226400E-01 a      2169     1    20     2    19\n -2.3505702805909551E-01 a      2170     1    20     2    20\n -1.7918789556131143E-01 a      2171     1    20     2    21\n  3.4990356667744421E-01 a      2172     1    20     2    22\n  6.4840494486623490E-01 a      2173     1    20     2    23\n -1.4478590661265617E-01 a      2174     1    20     2    24\n  2.1297816904812697E-01 a      2175     1    20     2    25\n  3.4493308448955345E-01 a      2176     1    21     2     1\n  3.5266855354427494E-02 a      2177     1    21     2     2\n -2.7754410875303576E-01 a      2178     1    21     2     3\n  4.6768620046741878E-02 a      2179     1    21     2     4\n -1.5769313809619548E-01 a      2180     1    21     2     5\n  1.3497835265205210E-01 a      2181     1    21     2     6\n -3.7341652004504744E-01 a      2182     1    21     2     7\n -3.0627556863254835E-01 a      2183     1    21     2     8\n -2.2925939617710103E-01 a      2184     1    21     2     9\n -3.8592084381092573E-01 a      2185     1    21     2    10\n  4.1234641447800625E-02 a      2186     1    21     2    11\n -9.5022250284578980E-01 a      2187     1    21     2    12\n -1.1125930303081784E+00 a      2188     1    21     2    13\n -5.3122650273704952E-01 a      2189     1    21     2    14\n  2.3060682491837362E-02 a      2190     1    21     2    15\n -1.5104224681786016E+00 a      2191     1    21     2    16\n  1.4753038731650985E-03 a      2192     1    21     2    17\n  1.5143866707297242E-02 a      2193     1    21     2    18\n  8.6090707736472302E-02 a      2194     1    21     2    19\n -6.2430761394861624E-02 a      2195     1    21     2    20\n -6.1308060604509992E-03 a      2196     1    21     2    21\n 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  },
  {
    "path": "examples/nnp-dataset/H2O_RPBE-D3/input.data",
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  -0.194094220    0.000000000    0.031139053   -0.066276697    0.021098669\natom     6.518835853   17.598527525    5.812888693   H    0.156894820    0.000000000   -0.042755679    0.033516151    0.011475343\natom     4.178872098   17.417123193    7.699892475   H    0.137280880    0.000000000    0.015711127    0.037753788   -0.030393813\natom    21.151675148   20.879473220    7.686178727   O   -0.248140030    0.000000000   -0.009994913   -0.003084252    0.015181890\natom    21.725161902   21.081677775    5.962589077   H    0.096696550    0.000000000    0.004375907    0.001697312   -0.018251199\natom    22.673568579   21.355735416    8.583993635   H    0.139564520    0.000000000   -0.002909430   -0.001404868    0.006677838\natom    19.507253717   12.301401988   18.501302967   O   -0.199717660    0.000000000   -0.028410932   -0.035128726    0.043667183\natom    19.776549245   13.758948329   17.594513745   H    0.142371980    0.000000000    0.012693146    0.047711282   -0.031771675\natom    17.867647309   12.681150163   19.378767407   H    0.141514070    0.000000000    0.014688099   -0.002133776   -0.011109509\natom    23.134797998   17.370023640   17.326635511   O   -0.251377170    0.000000000   -0.000268730   -0.000574628   -0.003573364\natom    23.309537263   17.766571487   19.122904057   H    0.118237060    0.000000000    0.005638293   -0.001455468   -0.001185792\natom     0.463480083   18.316502796   16.477809882   H    0.138644360    0.000000000   -0.009964426   -0.001923402    0.004419419\natom     7.198349513    9.467121587   20.207068712   O   -0.243428280    0.000000000    0.009787410   -0.009154114    0.016239349\natom     7.841261053    8.491977165   21.715395794   H    0.127971510    0.000000000   -0.015877818    0.012471507   -0.019846659\natom     5.641732350   10.325405299   20.696485297   H    0.130413120    0.000000000    0.003877775    0.000013170    0.004937889\nenergy   -4900.14395256\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/nnp-dataset/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-dataset/H2O_RPBE-D3/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "examples/nnp-dataset/H2O_RPBE-D3/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.2539155865352127E+00 a         1     0     1     1     1\n  2.2490365890661286E+00 a         2     0     1     1     2\n  4.9361851928374572E+00 a         3     0     1     1     3\n -2.3971991574908125E+00 a         4     0     1     1     4\n -1.8596992303156465E+00 a         5     0     1     1     5\n  3.8287764168815897E+00 a         6     0     1     1     6\n  7.4523181738636106E+00 a         7     0     1     1     7\n  6.0971861116881998E+00 a         8     0     1     1     8\n -8.7239359226117639E+00 a         9     0     1     1     9\n -1.8255232070184267E+01 a        10     0     1     1    10\n -7.8065643887610179E+00 a        11     0     1     1    11\n  1.4247237398130265E+01 a        12     0     1     1    12\n -3.2217879518334338E+00 a        13     0     1     1    13\n -5.7395252086520712E+00 a        14     0     1     1    14\n  2.0353040522911576E+00 a        15     0     1     1    15\n  7.7520578160630560E+00 a        16     0     1     1    16\n  2.9357257867412252E+00 a        17     0     1     1    17\n -2.9719860930100790E+00 a        18     0     1     1    18\n  8.9245382590288980E+00 a        19     0     1     1    19\n  6.6848134049442169E+00 a        20     0     1     1    20\n -2.2992719903495891E+00 a        21     0     1     1    21\n -1.4401533482181721E+01 a        22     0     1     1    22\n -2.0574070545285186E+00 a        23     0     1     1    23\n -6.3544667277888678E+00 a        24     0     1     1    24\n  3.9668360525851707E+00 a        25     0     1     1    25\n  1.0930597297534963E+01 a        26     0     2     1     1\n  3.0058866618169424E+00 a        27     0     2     1     2\n -4.9950943102999927E+00 a        28     0     2     1     3\n -1.9930957240687266E+00 a        29     0     2     1     4\n  1.6790893133342006E+00 a        30     0     2     1     5\n -4.5254006136507128E+00 a        31     0     2     1     6\n -9.6165021729265252E+00 a        32     0     2     1     7\n -8.7465722730176285E+00 a        33     0     2     1     8\n  1.5506950040431201E+01 a        34     0     2     1     9\n  2.1903342918227118E+01 a        35     0     2     1    10\n -1.0685216745153280E+01 a        36     0     2     1    11\n -2.5859690636594280E+01 a        37     0     2     1    12\n -3.2423603491405122E+00 a        38     0     2     1    13\n  5.3753900550878555E+00 a        39     0     2     1    14\n -3.0291935617567991E+00 a        40     0     2     1    15\n -1.3534893178408465E+01 a        41     0     2     1    16\n -5.7625138055631471E+00 a        42     0     2     1    17\n  1.0216765318459601E+01 a        43     0     2     1    18\n -1.4416012930050949E+01 a        44     0     2     1    19\n -4.7226757471872144E-01 a        45     0     2     1    20\n  7.8981385188798026E+00 a        46     0     2     1    21\n  1.2202710023744410E+00 a        47     0     2     1    22\n  8.0560891210932120E+00 a        48     0     2     1    23\n  4.5972445013263297E-01 a        49     0     2     1    24\n  1.3374237019728858E+01 a        50     0     2     1    25\n -1.0644910441621166E+01 a        51     0     3     1     1\n -5.6098794516515920E+00 a        52     0     3     1     2\n -1.0236653403367724E+01 a        53     0     3     1     3\n  1.3552139405799508E+00 a        54     0     3     1     4\n  1.3201025058567883E+00 a        55     0     3     1     5\n  1.6531266759009673E+00 a        56     0     3     1     6\n -1.0303768926395865E+01 a        57     0     3     1     7\n  1.9927521303470008E-01 a        58     0     3     1     8\n  8.1216226663758366E+00 a        59     0     3     1     9\n  2.1349555016157687E+01 a        60     0     3     1    10\n  1.0105416692705148E+01 a        61     0     3     1    11\n -1.1444993918278378E+01 a        62     0     3     1    12\n  2.9861675555209538E-01 a        63     0     3     1    13\n  9.3552992513120543E+00 a        64     0     3     1    14\n -2.2844869025933630E+00 a        65     0     3     1    15\n -3.8047300595857316E+00 a        66     0     3     1    16\n -3.0512161452147448E+00 a        67     0     3     1    17\n  2.7887340590896472E+00 a        68     0     3     1    18\n -1.5988439945122812E+01 a        69     0     3     1    19\n -1.6917164763280326E+01 a        70     0     3     1    20\n  3.2170907488709326E+00 a        71     0     3     1    21\n  2.1641888770160929E+01 a        72     0     3     1    22\n  3.2604671723420497E+00 a        73     0     3     1    23\n  1.5230689068493776E+01 a        74     0     3     1    24\n -1.4713830039823366E+01 a        75     0     3     1    25\n -2.3544214523969775E+00 a        76     0     4     1     1\n -5.8299691629399382E+00 a        77     0     4     1     2\n  1.7168784391956539E+01 a        78     0     4     1     3\n  1.0050003860864617E+01 a        79     0     4     1     4\n  3.5168903759752812E+00 a        80     0     4     1     5\n -4.4828111046589010E+00 a        81     0     4     1     6\n  1.8299193380051442E+01 a        82     0     4     1     7\n  6.9717289110204188E+00 a        83     0     4     1     8\n -2.0364082994445859E+01 a        84     0     4     1     9\n -3.5062338388300589E+01 a        85     0     4     1    10\n  1.8010375764887119E+01 a        86     0     4     1    11\n  4.2133659287179640E+01 a        87     0     4     1    12\n  1.1988736553417061E+01 a        88     0     4     1    13\n -1.2351529706885179E+01 a        89     0     4     1    14\n  5.4139212296285057E+00 a        90     0     4     1    15\n  1.6705967069968899E+01 a        91     0     4     1    16\n  8.3219076874511639E+00 a        92     0     4     1    17\n -1.8555777504879448E+01 a        93     0     4     1    18\n  3.1433889377775369E+01 a        94     0     4     1    19\n  6.7043459658252780E-01 a        95     0     4     1    20\n -1.3837570456349678E+01 a        96     0     4     1    21\n  5.0298368971353791E-01 a        97     0     4     1    22\n -2.2656240789613065E+01 a        98     0     4     1    23\n -2.4243684644962626E+00 a        99     0     4     1    24\n -2.8280330035212309E+01 a       100     0     4     1    25\n  4.2306100814115322E+00 a       101     0     5     1     1\n  9.9770374716830084E+00 a       102     0     5     1     2\n  2.0487048112933808E+00 a       103     0     5     1     3\n -1.3702212470739978E+00 a       104     0     5     1     4\n  2.8131124422603837E+00 a       105     0     5     1     5\n  3.2845640151619522E-03 a       106     0     5     1     6\n  2.4065616021196026E+00 a       107     0     5     1     7\n -1.0461000723401572E+01 a       108     0     5     1     8\n -1.0180720750329515E+01 a       109     0     5     1     9\n -8.8668996772076660E+00 a       110     0     5     1    10\n  6.5256092481271502E+00 a       111     0     5     1    11\n -6.9831054240027211E+00 a       112     0     5     1    12\n  4.0892074148312876E+00 a       113     0     5     1    13\n -5.1951354450201128E+00 a       114     0     5     1    14\n  1.6657989141753051E+00 a       115     0     5     1    15\n -7.3542511663155619E+00 a       116     0     5     1    16\n  5.1573102842565115E+00 a       117     0     5     1    17\n  3.4929930175122172E+00 a       118     0     5     1    18\n  2.5382184218789963E+00 a       119     0     5     1    19\n  2.0045179007481050E+01 a       120     0     5     1    20\n -1.6165269676512768E+00 a       121     0     5     1    21\n  2.4869117790922393E+00 a       122     0     5     1    22\n  6.0131560843540068E+00 a       123     0     5     1    23\n -1.2231651850388728E+01 a       124     0     5     1    24\n  3.5372450187997345E+01 a       125     0     5     1    25\n -1.0433252604911765E+01 a       126     0     6     1     1\n -2.3715834640656657E+00 a       127     0     6     1     2\n -1.8239608965373137E+01 a       128     0     6     1     3\n -3.6510816169583777E+00 a       129     0     6     1     4\n -1.7632327653119535E+01 a       130     0     6     1     5\n  1.0040509177650593E+01 a       131     0     6     1     6\n -1.5407385349225459E+01 a       132     0     6     1     7\n -7.0553605774310779E-01 a       133     0     6     1     8\n  1.3204892207903583E+01 a       134     0     6     1     9\n  2.9596389655595953E+01 a       135     0     6     1    10\n -2.0620173259628203E+01 a       136     0     6     1    11\n -3.0803380363815094E+01 a       137     0     6     1    12\n -1.4917676387082279E+01 a       138     0     6     1    13\n  9.6935054799166185E+00 a       139     0     6     1    14\n  4.6937319413252743E+00 a       140     0     6     1    15\n -5.0263591258131060E+00 a       141     0     6     1    16\n -9.7243575590712439E+00 a       142     0     6     1    17\n  1.5625340951727363E+01 a       143     0     6     1    18\n -2.8266776356585389E+01 a       144     0     6     1    19\n  2.5386057418612946E+00 a       145     0     6     1    20\n  1.6302330128073283E+01 a       146     0     6     1    21\n -8.5166226512297030E+00 a       147     0     6     1    22\n  2.5040570504752605E+01 a       148     0     6     1    23\n -8.5008658358878897E-01 a       149     0     6     1    24\n  2.0458930574550632E+01 a       150     0     6     1    25\n  7.8529627796707677E+00 a       151     0     7     1     1\n -4.5279242985866821E+00 a       152     0     7     1     2\n  4.7942839133231594E+00 a       153     0     7     1     3\n -6.2431002330064649E+00 a       154     0     7     1     4\n  4.3358077462982054E+00 a       155     0     7     1     5\n -6.8037589596444281E+00 a       156     0     7     1     6\n  1.8980667946224101E+00 a       157     0     7     1     7\n  1.9802532239433695E+01 a       158     0     7     1     8\n  8.4826746941006572E+00 a       159     0     7     1     9\n  4.3614399548619884E+00 a       160     0     7     1    10\n -1.6073795583709572E+01 a       161     0     7     1    11\n  1.6345358363876109E+01 a       162     0     7     1    12\n -8.4662611499242502E+00 a       163     0     7     1    13\n  8.0952183951712298E-01 a       164     0     7     1    14\n -1.1658877435292819E+01 a       165     0     7     1    15\n  1.3236001648494756E+01 a       166     0     7     1    16\n -1.2875720369407999E+01 a       167     0     7     1    17\n -2.0324369268053388E+00 a       168     0     7     1    18\n  1.0874203669721311E+01 a       169     0     7     1    19\n -1.7284078771261807E+01 a       170     0     7     1    20\n -2.9714643625232693E+00 a       171     0     7     1    21\n -1.9329510057793893E+01 a       172     0     7     1    22\n -1.0307360045133033E+01 a       173     0     7     1    23\n  4.2080100442235366E+00 a       174     0     7     1    24\n -3.8428801618815640E+01 a       175     0     7     1    25\n -5.7115809702208011E+00 a       176     0     8     1     1\n  3.7056719936859976E+00 a       177     0     8     1     2\n  1.3966886453850773E+01 a       178     0     8     1     3\n  1.4914576601367306E+00 a       179     0     8     1     4\n  2.3064842131482180E+01 a       180     0     8     1     5\n -7.9541458640647837E+00 a       181     0     8     1     6\n  1.1404558568383607E+01 a       182     0     8     1     7\n -3.6573585449246653E+00 a       183     0     8     1     8\n -4.9561031023561952E+00 a       184     0     8     1     9\n -1.2066502127308031E+01 a       185     0     8     1    10\n  1.1843534640137769E+01 a       186     0     8     1    11\n  1.9616511468009570E+01 a       187     0     8     1    12\n  1.3417323502712899E+01 a       188     0     8     1    13\n -4.0678344152400447E-01 a       189     0     8     1    14\n -1.9507569881192218E+01 a       190     0     8     1    15\n -6.5169441798944456E+00 a       191     0     8     1    16\n  5.2178654198561141E+00 a       192     0     8     1    17\n -1.4240290695317738E+01 a       193     0     8     1    18\n  2.1343226894748700E+01 a       194     0     8     1    19\n -2.7623196634808984E+00 a       195     0     8     1    20\n -9.2884558848667620E+00 a       196     0     8     1    21\n  6.0789935054152480E+00 a       197     0     8     1    22\n -1.6374423786268370E+01 a       198     0     8     1    23\n  2.1963692862828306E+00 a       199     0     8     1    24\n -1.6477619048440658E+01 a       200     0     8     1    25\n -5.4652541826246170E-01 a       201     0     9     1     1\n  2.9686567892883864E+00 a       202     0     9     1     2\n -6.5132434460788122E+00 a       203     0     9     1     3\n -4.8064981499516870E+00 a       204     0     9     1     4\n -6.9010601385214585E+00 a       205     0     9     1     5\n  6.0243408819244291E+00 a       206     0     9     1     6\n -4.7253212010125401E+00 a       207     0     9     1     7\n  4.4892697548578031E+00 a       208     0     9     1     8\n  2.8691390395969503E+00 a       209     0     9     1     9\n  4.8905119819707235E+00 a       210     0     9     1    10\n  8.0125760629983089E-01 a       211     0     9     1    11\n -7.1577963461867160E+00 a       212     0     9     1    12\n -7.1141706979801747E+00 a       213     0     9     1    13\n -9.2736585757849166E-01 a       214     0     9     1    14\n  1.4028916807873271E+01 a       215     0     9     1    15\n -3.6974926166345901E-01 a       216     0     9     1    16\n  1.1388278367792175E+00 a       217     0     9     1    17\n -6.0994976654902651E+00 a       218     0     9     1    18\n -8.0444468725663523E+00 a       219     0     9     1    19\n  1.0211480086068931E+00 a       220     0     9     1    20\n  8.7528435866785532E+00 a       221     0     9     1    21\n -5.2843722120300427E+00 a       222     0     9     1    22\n  8.0008339624272278E+00 a       223     0     9     1    23\n -1.5207898046701156E+00 a       224     0     9     1    24\n  2.7661111317119200E+00 a       225     0     9     1    25\n -7.8044247731064234E+00 a       226     0    10     1     1\n  1.3132447209010347E+00 a       227     0    10     1     2\n -4.7278121268044551E+00 a       228     0    10     1     3\n  3.6601689040473118E+00 a       229     0    10     1     4\n -9.6267150529386480E+00 a       230     0    10     1     5\n  2.6091275381190444E+00 a       231     0    10     1     6\n -3.1848404329162414E+00 a       232     0    10     1     7\n -9.5389607349646521E+00 a       233     0    10     1     8\n -2.6987985247358575E+00 a       234     0    10     1     9\n -6.2833399930784530E+00 a       235     0    10     1    10\n  1.6489253885816758E+01 a       236     0    10     1    11\n -1.7107772306689530E+01 a       237     0    10     1    12\n  3.4088466354687279E+00 a       238     0    10     1    13\n -1.2348801832413381E+00 a       239     0    10     1    14\n  1.0154267479292665E+01 a       240     0    10     1    15\n -6.0502934471257728E+00 a       241     0    10     1    16\n  1.0160696494987546E+01 a       242     0    10     1    17\n  2.4492206768318772E+00 a       243     0    10     1    18\n -7.3188978315096689E+00 a       244     0    10     1    19\n  8.8753153140216963E+00 a       245     0    10     1    20\n -3.1414578717572117E+00 a       246     0    10     1    21\n  1.1781935452921802E+01 a       247     0    10     1    22\n  4.2162781958159847E+00 a       248     0    10     1    23\n  6.3461905733038693E+00 a       249     0    10     1    24\n  1.8925601045188980E+01 a       250     0    10     1    25\n  4.6477877749677310E+00 a       251     0    11     1     1\n -1.6344868480777182E+00 a       252     0    11     1     2\n  3.2048890105307217E+00 a       253     0    11     1     3\n  3.0235679638931630E+00 a       254     0    11     1     4\n  4.2225303889491732E+00 a       255     0    11     1     5\n -3.7068606308347563E+00 a       256     0    11     1     6\n  1.9942469773127267E+00 a       257     0    11     1     7\n -7.5618287055529032E-02 a       258     0    11     1     8\n -4.3483903145704721E+00 a       259     0    11     1     9\n -6.4188170693407043E-01 a       260     0    11     1    10\n -1.7151247607053004E+00 a       261     0    11     1    11\n  1.1831911154836730E+00 a       262     0    11     1    12\n  8.5390777529689998E+00 a       263     0    11     1    13\n -1.2567544621838858E+00 a       264     0    11     1    14\n -6.5836237830818582E+00 a       265     0    11     1    15\n  1.0147377375097664E+00 a       266     0    11     1    16\n -4.1323735892759546E+00 a       267     0    11     1    17\n -2.6316384615004618E-01 a       268     0    11     1    18\n  2.4143335868624547E+00 a       269     0    11     1    19\n  2.6061142983025900E+00 a       270     0    11     1    20\n -4.4998702636369865E+00 a       271     0    11     1    21\n  1.3890302621242303E-02 a       272     0    11     1    22\n -7.8084731995076311E+00 a       273     0    11     1    23\n -1.2474549203322676E+00 a       274     0    11     1    24\n  4.4163797527377591E-02 a       275     0    11     1    25\n  2.8407201242614737E+00 a       276     0    12     1     1\n  1.3632905709235899E-01 a       277     0    12     1     2\n  1.2685237989280235E-01 a       278     0    12     1     3\n  2.2654235227594675E+00 a       279     0    12     1     4\n  2.5395548140674755E+00 a       280     0    12     1     5\n -9.3520481583438890E+00 a       281     0    12     1     6\n -1.9669962665207585E-01 a       282     0    12     1     7\n  5.7045527454931977E-01 a       283     0    12     1     8\n -2.9864201174461678E+00 a       284     0    12     1     9\n  3.9052149431886622E+00 a       285     0    12     1    10\n -9.0833042649786648E+00 a       286     0    12     1    11\n  5.0812751299215018E+00 a       287     0    12     1    12\n -1.6164442006858799E+00 a       288     0    12     1    13\n -5.6075225833495623E-01 a       289     0    12     1    14\n -2.3615673680840406E+00 a       290     0    12     1    15\n  3.0947011553478285E+00 a       291     0    12     1    16\n -8.3551823427496270E+00 a       292     0    12     1    17\n  5.9941345197218849E+00 a       293     0    12     1    18\n -1.8953925485822552E-02 a       294     0    12     1    19\n -2.7547195481515581E+00 a       295     0    12     1    20\n -1.9804726751840331E+00 a       296     0    12     1    21\n -3.8317244940395995E-01 a       297     0    12     1    22\n  4.8745188041841092E-01 a       298     0    12     1    23\n -8.4590760980141351E+00 a       299     0    12     1    24\n  1.0766033918315021E+00 a       300     0    12     1    25\n -2.2091804164374422E+00 a       301     0    13     1     1\n -5.5101800091867448E-01 a       302     0    13     1     2\n -1.0329728270730296E+00 a       303     0    13     1     3\n  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3.4156738519131671E+00 a      1093     1    16     2    18\n -3.2336496919934206E+00 a      1094     1    16     2    19\n -7.3798227198293331E-01 a      1095     1    16     2    20\n  3.3624363552486471E+00 a      1096     1    16     2    21\n -1.0132468162040502E+00 a      1097     1    16     2    22\n  3.7056369669165354E-02 a      1098     1    16     2    23\n -1.8312393074518960E+00 a      1099     1    16     2    24\n  4.5500578248263041E-01 a      1100     1    16     2    25\n  2.2302269048313073E+00 a      1101     1    17     2     1\n  1.6214906410771059E+00 a      1102     1    17     2     2\n  1.6349509659918811E+00 a      1103     1    17     2     3\n  5.4145408574619934E-02 a      1104     1    17     2     4\n  4.3252906684142584E-01 a      1105     1    17     2     5\n -1.3736969218541635E+00 a      1106     1    17     2     6\n  2.8184234047867172E+00 a      1107     1    17     2     7\n  2.8896867628176515E+00 a      1108     1    17     2     8\n  1.4299248969157874E-01 a      1109     1    17     2     9\n  1.9927781151509179E+00 a      1110     1    17     2    10\n  2.3711262701763500E+00 a      1111     1    17     2    11\n  1.3223116695652687E-01 a      1112     1    17     2    12\n -3.4794814095323376E+00 a      1113     1    17     2    13\n  1.1510988640273812E+00 a      1114     1    17     2    14\n -3.3985921784982023E+00 a      1115     1    17     2    15\n  1.0076465563953010E+00 a      1116     1    17     2    16\n -8.3104650289513449E-01 a      1117     1    17     2    17\n  1.3398030994767187E+00 a      1118     1    17     2    18\n  3.8575481988101741E+00 a      1119     1    17     2    19\n -8.6313597613197934E-01 a      1120     1    17     2    20\n  1.0420089629653122E+00 a      1121     1    17     2    21\n -8.3635927268506283E-01 a      1122     1    17     2    22\n  2.9149953695805464E+00 a      1123     1    17     2    23\n  2.4188178674036467E-01 a      1124     1    17     2    24\n -1.0422371721462642E+00 a      1125     1    17     2    25\n -9.8074696676452633E-01 a      1126     1    18     2     1\n -7.0261356217276538E-01 a      1127     1    18     2     2\n -1.5539162592863331E+00 a      1128     1    18     2     3\n  2.5663709887311525E-01 a      1129     1    18     2     4\n  1.1790597159349452E+00 a      1130     1    18     2     5\n -5.1283413704919667E-01 a      1131     1    18     2     6\n  2.8209081194780357E+00 a      1132     1    18     2     7\n -2.9530441812628777E-01 a      1133     1    18     2     8\n  1.1911675111813969E+00 a      1134     1    18     2     9\n -7.1781562917361630E-01 a      1135     1    18     2    10\n  7.5615420324814075E-01 a      1136     1    18     2    11\n  1.0383917710970614E+00 a      1137     1    18     2    12\n -7.4096563311439467E-01 a      1138     1    18     2    13\n -2.7861243720701795E-01 a      1139     1    18     2    14\n  6.9344913926308305E-01 a      1140     1    18     2    15\n  7.2770779951192111E-01 a      1141     1    18     2    16\n  1.7348650121938709E+00 a      1142     1    18     2    17\n  7.2380729647406006E-01 a      1143     1    18     2    18\n -2.1671682060080908E+00 a      1144     1    18     2    19\n -1.8448084445689281E-01 a      1145     1    18     2    20\n  1.3024719111160912E+00 a      1146     1    18     2    21\n -1.2909789979215052E+00 a      1147     1    18     2    22\n -2.0330008356136617E+00 a      1148     1    18     2    23\n -3.5287322032224533E-01 a      1149     1    18     2    24\n -4.4414575257293076E-01 a      1150     1    18     2    25\n -2.7258373164925753E-02 a      1151     1    19     2     1\n  1.7786409180863971E+00 a      1152     1    19     2     2\n -6.2433485311638581E-01 a      1153     1    19     2     3\n -7.0729056795105427E-01 a      1154     1    19     2     4\n  5.1264534381277294E-01 a      1155     1    19     2     5\n -8.6616294143739847E-01 a      1156     1    19     2     6\n  8.0698814912956451E-01 a      1157     1    19     2     7\n -1.8175081356783283E+00 a      1158     1    19     2     8\n -3.2026939775244762E-01 a      1159     1    19     2     9\n -6.7288331966478787E-01 a      1160     1    19     2    10\n  1.7148578091095124E-01 a      1161     1    19     2    11\n  3.2140265958315151E-01 a      1162     1    19     2    12\n -8.1210044120660096E-01 a      1163     1    19     2    13\n -7.6231158138043847E-02 a      1164     1    19     2    14\n -1.5851767882039058E+00 a      1165     1    19     2    15\n  1.2557130027742122E-01 a      1166     1    19     2    16\n  4.8654065981248962E-01 a      1167     1    19     2    17\n  9.1550158332637088E-01 a      1168     1    19     2    18\n  1.7945138007319117E+00 a      1169     1    19     2    19\n -6.2793744117252037E-01 a      1170     1    19     2    20\n  4.9770901971481168E-01 a      1171     1    19     2    21\n  7.9199978603495880E-01 a      1172     1    19     2    22\n  1.3566279316779111E+00 a      1173     1    19     2    23\n -6.4989908124401896E-01 a      1174     1    19     2    24\n -1.2130061691278531E+00 a      1175     1    19     2    25\n  2.1718589739533791E+00 a      1176     1    20     2     1\n  2.9938291414473661E-01 a      1177     1    20     2     2\n  9.2914772861453521E-01 a      1178     1    20     2     3\n  1.7565171250248528E+00 a      1179     1    20     2     4\n -1.7171376009305626E+00 a      1180     1    20     2     5\n  2.8704512164424800E+00 a      1181     1    20     2     6\n -4.0609063853165461E-01 a      1182     1    20     2     7\n -8.8956304852711987E-01 a      1183     1    20     2     8\n  1.5588822278177381E+00 a      1184     1    20     2     9\n -5.3859945323628011E-01 a      1185     1    20     2    10\n -8.9087250387841876E-01 a      1186     1    20     2    11\n -8.9835382331213787E-01 a      1187     1    20     2    12\n -1.1369908152037626E-01 a      1188     1    20     2    13\n -5.7966570046060373E-01 a      1189     1    20     2    14\n  1.1066980646243854E+00 a      1190     1    20     2    15\n  3.1244375834572546E-01 a      1191     1    20     2    16\n  2.1974097139332476E+00 a      1192     1    20     2    17\n -7.6349397720541767E-01 a      1193     1    20     2    18\n -3.6503418073743810E-01 a      1194     1    20     2    19\n -6.0642338824938813E-01 a      1195     1    20     2    20\n  2.2802643907348267E-02 a      1196     1    20     2    21\n  8.3743733952396715E-01 a      1197     1    20     2    22\n -3.9872923910188316E+00 a      1198     1    20     2    23\n -3.3066587159099775E-01 a      1199     1    20     2    24\n -3.3827603813335005E-01 a      1200     1    20     2    25\n  2.0707890624068246E+00 a      1201     1    21     2     1\n  8.1792094222389677E-01 a      1202     1    21     2     2\n  1.0420587694448914E-01 a      1203     1    21     2     3\n  3.8654442605274053E-01 a      1204     1    21     2     4\n -1.0273245523110555E+00 a      1205     1    21     2     5\n  4.8026156110006928E-02 a      1206     1    21     2     6\n -1.2317220364565722E+00 a      1207     1    21     2     7\n -9.2171220979112878E-01 a      1208     1    21     2     8\n -8.3293051813215280E-01 a      1209     1    21     2     9\n  3.7826002267822101E-01 a      1210     1    21     2    10\n -1.2566916573054130E+00 a      1211     1    21     2    11\n -1.4542331491456711E-01 a      1212     1    21     2    12\n -1.0890378021893508E+00 a      1213     1    21     2    13\n -5.8298836953764355E-01 a      1214     1    21     2    14\n -1.9020824106971643E+00 a      1215     1    21     2    15\n  4.4353810152599149E-01 a      1216     1    21     2    16\n -2.9928311527046703E-01 a      1217     1    21     2    17\n -7.7527928990984052E-01 a      1218     1    21     2    18\n  2.6159175407438195E-01 a      1219     1    21     2    19\n -2.6604337400489050E-02 a      1220     1    21     2    20\n -4.6552795168897604E-01 a      1221     1    21     2    21\n  1.1611386377657384E+00 a      1222     1    21     2    22\n -1.2972265245341139E+00 a      1223     1    21     2    23\n  1.8117173751313085E+00 a      1224     1    21     2    24\n  1.0433495561237927E+00 a      1225     1    21     2    25\n  1.5410314634266913E+00 a      1226     1    22     2     1\n  6.6201420998527072E-01 a      1227     1    22     2     2\n  1.1189293597068475E+00 a      1228     1    22     2     3\n -1.1536147566508355E+00 a      1229     1    22     2     4\n -8.4859080711662893E-01 a      1230     1    22     2     5\n  3.7903158089014494E-01 a      1231     1    22     2     6\n -2.6461659405296234E+00 a      1232     1    22     2     7\n  2.2472472042954434E+00 a      1233     1    22     2     8\n -9.2281733258289744E-01 a      1234     1    22     2     9\n  8.7312141982063785E-01 a      1235     1    22     2    10\n -4.3593190134289528E-01 a      1236     1    22     2    11\n  5.1912574126564559E-01 a      1237     1    22     2    12\n -5.9029854481930821E-01 a      1238     1    22     2    13\n -7.2255183403800793E-01 a      1239     1    22     2    14\n  4.1024670935059383E-02 a      1240     1    22     2    15\n  2.0425371936604741E-01 a      1241     1    22     2    16\n -1.0394832812330597E+00 a      1242     1    22     2    17\n  4.7202219372950349E-01 a      1243     1    22     2    18\n -1.9958648332222221E-03 a      1244     1    22     2    19\n -1.4664186611455649E-02 a      1245     1    22     2    20\n  1.0689476163444707E+00 a      1246     1    22     2    21\n  8.4484833020425232E-01 a      1247     1    22     2    22\n -1.4147373614558330E+00 a      1248     1    22     2    23\n  1.9187324467269602E+00 a      1249     1    22     2    24\n  1.5330124676330812E+00 a      1250     1    22     2    25\n  2.3019050197742894E+00 a      1251     1    23     2     1\n -1.3828322911066271E-01 a      1252     1    23     2     2\n -2.3555430378419923E-01 a      1253     1    23     2     3\n -1.3434989779696097E-01 a      1254     1    23     2     4\n  3.7852663531566189E-01 a      1255     1    23     2     5\n  9.8266847359694973E-02 a      1256     1    23     2     6\n  3.2721968443206462E-01 a      1257     1    23     2     7\n -3.7061171550241617E-01 a      1258     1    23     2     8\n  2.2862436245090851E+00 a      1259     1    23     2     9\n  1.7674065728047832E+00 a      1260     1    23     2    10\n -5.2627257197444939E-02 a      1261     1    23     2    11\n  9.4094481148145870E-01 a      1262     1    23     2    12\n  1.0616552648143298E+00 a      1263     1    23     2    13\n -1.6065739188681796E-01 a      1264     1    23     2    14\n  1.6833160475834315E+00 a      1265     1    23     2    15\n -5.5679530352182072E-01 a      1266     1    23     2    16\n  4.2170082515325280E-01 a      1267     1    23     2    17\n  1.8142946234467967E+00 a      1268     1    23     2    18\n -6.0004075552166369E-01 a      1269     1    23     2    19\n  8.6767695096505049E-01 a      1270     1    23     2    20\n  1.7471709925670367E-01 a      1271     1    23     2    21\n  6.3494817986861019E-01 a      1272     1    23     2    22\n  7.9839233743975266E-02 a      1273     1    23     2    23\n -8.7497499907984810E-01 a      1274     1    23     2    24\n -2.1279336414401262E-01 a      1275     1    23     2    25\n -1.0628518357816100E+01 a      1276     1    24     2     1\n -3.4149879843865938E-01 a      1277     1    24     2     2\n -4.0534872173827868E-01 a      1278     1    24     2     3\n  1.0980204380257913E-01 a      1279     1    24     2     4\n  1.8376924276804879E-01 a      1280     1    24     2     5\n  8.5047887536146360E-01 a      1281     1    24     2     6\n  4.3913590571042438E-01 a      1282     1    24     2     7\n  2.7167430357232609E+00 a      1283     1    24     2     8\n  2.9682659556600960E-01 a      1284     1    24     2     9\n -1.6032245851281013E+00 a      1285     1    24     2    10\n -6.7567048640865046E-01 a      1286     1    24     2    11\n -1.5253382251900995E+00 a      1287     1    24     2    12\n -6.7540631566041298E-01 a      1288     1    24     2    13\n -1.4565321192168545E+00 a      1289     1    24     2    14\n -1.3315414628143039E+00 a      1290     1    24     2    15\n  1.2552098425264056E+00 a      1291     1    24     2    16\n -1.1701558601459501E+00 a      1292     1    24     2    17\n  2.1967564647703792E+00 a      1293     1    24     2    18\n  3.6767594091430167E-01 a      1294     1    24     2    19\n  1.4791781996464841E+00 a      1295     1    24     2    20\n -2.4597335939693896E+00 a      1296     1    24     2    21\n  1.8222789722776007E+00 a      1297     1    24     2    22\n -2.4818384588216302E+00 a      1298     1    24     2    23\n -1.3359962912345340E+00 a      1299     1    24     2    24\n -1.6060924344568878E-02 a      1300     1    24     2    25\n -1.1558703878945702E+00 a      1301     1    25     2     1\n  5.5859771317693908E-02 a      1302     1    25     2     2\n -1.9275021348316721E+00 a      1303     1    25     2     3\n  4.2881321046205173E-01 a      1304     1    25     2     4\n  6.6308764508018558E-01 a      1305     1    25     2     5\n -2.5357661809360188E-01 a      1306     1    25     2     6\n  7.7965409617466697E-01 a      1307     1    25     2     7\n -1.9470416731652336E+00 a      1308     1    25     2     8\n  2.0923659915641873E-01 a      1309     1    25     2     9\n  8.9211452410465542E-01 a      1310     1    25     2    10\n -1.9807939822570442E-01 a      1311     1    25     2    11\n -5.0922943173038127E-01 a      1312     1    25     2    12\n  1.3378430979044107E+00 a      1313     1    25     2    13\n -6.8964614083753073E-01 a      1314     1    25     2    14\n  7.6939619343191556E-01 a      1315     1    25     2    15\n -1.5783243312480257E+00 a      1316     1    25     2    16\n  2.3586020281744577E+00 a      1317     1    25     2    17\n -5.1641666185758928E-01 a      1318     1    25     2    18\n  1.0291540870545792E+00 a      1319     1    25     2    19\n  1.5269830348487650E+00 a      1320     1    25     2    20\n -2.8987700591417855E+00 a      1321     1    25     2    21\n  9.0207337792476916E-01 a      1322     1    25     2    22\n  1.9890049402284911E+00 a      1323     1    25     2    23\n  3.9387622927433424E-01 a      1324     1    25     2    24\n  9.9397126232482103E-01 a      1325     1    25     2    25\n  2.5306467041996967E+00 b      1326     2     1\n  3.1633393474977245E+00 b      1327     2     2\n -1.1644295509710691E+00 b      1328     2     3\n -5.7686722641223600E+00 b      1329     2     4\n  2.0065022303893989E+00 b      1330     2     5\n -5.9106057000795840E+00 b      1331     2     6\n -1.1326093285804056E+01 b      1332     2     7\n -3.9025063397327071E+00 b      1333     2     8\n  4.4520505166676267E+00 b      1334     2     9\n -1.7352681951318241E+00 b      1335     2    10\n -2.1518912430432668E+00 b      1336     2    11\n  5.0463376560082969E+00 b      1337     2    12\n -2.2614514173852837E-01 b      1338     2    13\n -4.1454590614747211E+00 b      1339     2    14\n  1.6688417293495756E+00 b      1340     2    15\n -5.8649976938793378E+00 b      1341     2    16\n -3.8350084459541849E+00 b      1342     2    17\n  1.3730477223722950E+00 b      1343     2    18\n  1.8506935712854127E+00 b      1344     2    19\n  5.7362757779153428E+00 b      1345     2    20\n  7.2901484895568780E+00 b      1346     2    21\n  3.9773783666446022E-01 b      1347     2    22\n -6.1298011242151409E+00 b      1348     2    23\n  9.9698755072742991E+00 b      1349     2    24\n  1.1801564149295556E+00 b      1350     2    25\n  1.2704098997067026E+01 a      1351     2     1     3     1\n  1.5947733940307620E+00 a      1352     2     2     3     1\n -1.6022927057878529E+00 a      1353     2     3     3     1\n -1.5507258540777733E+00 a      1354     2     4     3     1\n  1.8696884022727636E+00 a      1355     2     5     3     1\n -8.2051908880071633E-01 a      1356     2     6     3     1\n  9.4325719092522542E-01 a      1357     2     7     3     1\n  2.4098435369626174E+00 a      1358     2     8     3     1\n  1.4100759633042474E+00 a      1359     2     9     3     1\n -1.4613034838529613E+00 a      1360     2    10     3     1\n  1.0296574685193380E+00 a      1361     2    11     3     1\n  1.2413851904356363E+00 a      1362     2    12     3     1\n -6.3168181712211169E-01 a      1363     2    13     3     1\n  7.6424175125347729E+00 a      1364     2    14     3     1\n -1.3477038299214714E+00 a      1365     2    15     3     1\n -1.6064659765754943E+00 a      1366     2    16     3     1\n -8.9624380518145874E-01 a      1367     2    17     3     1\n -1.0509865792522375E+00 a      1368     2    18     3     1\n  8.1847872933853638E-01 a      1369     2    19     3     1\n  1.2845504810303034E+00 a      1370     2    20     3     1\n -5.1879822944368881E-01 a      1371     2    21     3     1\n -7.2018714033119180E-01 a      1372     2    22     3     1\n  5.9870832883780798E+00 a      1373     2    23     3     1\n -6.0589155387470683E-01 a      1374     2    24     3     1\n  5.0177609140285355E+00 a      1375     2    25     3     1\n  9.7386086372975722E+00 b      1376     3     1\n"
  },
  {
    "path": "examples/nnp-dataset/H2O_RPBE-D3/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -4.2252995889643252E-01 a         1     0     1     1     1\n -6.0555645962054347E+00 a         2     0     1     1     2\n  1.4040722027928377E+01 a         3     0     1     1     3\n -2.7041370011942618E+00 a         4     0     1     1     4\n -3.8202743208058858E+00 a         5     0     1     1     5\n -3.3612643261393358E+00 a         6     0     1     1     6\n -2.0418101025905258E+00 a         7     0     1     1     7\n  7.5707237340996727E+00 a         8     0     1     1     8\n -5.8098755815926548E+00 a         9     0     1     1     9\n -6.0966886893925210E-01 a        10     0     1     1    10\n  5.8061564015115206E+00 a        11     0     1     1    11\n -1.5509339733099867E+00 a        12     0     1     1    12\n  1.9747395485200818E+00 a        13     0     1     1    13\n  4.5260782279680539E-01 a        14     0     1     1    14\n  9.9210415760283279E+00 a        15     0     1     1    15\n -6.5078831481547121E+00 a        16     0     1     1    16\n -3.4768832871318085E+00 a        17     0     1     1    17\n -1.9463994340943838E+00 a        18     0     1     1    18\n -3.4186058699290269E+00 a        19     0     1     1    19\n  1.2263643166698479E+00 a        20     0     1     1    20\n -5.9171161834436594E+00 a        21     0     1     1    21\n  1.8436267358458363E+00 a        22     0     1     1    22\n -2.3139530616378448E+00 a        23     0     1     1    23\n -1.7228542411478951E+01 a        24     0     1     1    24\n  2.2888610253215895E+00 a        25     0     1     1    25\n  8.0819405565169262E+00 a        26     0     2     1     1\n  8.0066409422078735E+00 a        27     0     2     1     2\n -2.8439251469462398E+01 a        28     0     2     1     3\n -1.1146087290797917E+01 a        29     0     2     1     4\n -7.5292172093563314E+00 a        30     0     2     1     5\n -4.0783685663337641E+00 a        31     0     2     1     6\n -4.4130406528599337E+00 a        32     0     2     1     7\n  1.0563249167508673E+01 a        33     0     2     1     8\n  1.0933105521974941E+01 a        34     0     2     1     9\n -1.1646509907117448E+01 a        35     0     2     1    10\n -7.5007478428041727E+00 a        36     0     2     1    11\n  7.7790182254249176E+00 a        37     0     2     1    12\n  1.1567034492555623E+01 a        38     0     2     1    13\n -4.2051741520233508E+00 a        39     0     2     1    14\n  3.1165306119132130E+00 a        40     0     2     1    15\n  1.6385645103485370E+01 a        41     0     2     1    16\n  2.6440539124381655E+00 a        42     0     2     1    17\n -3.9524518111687827E+00 a        43     0     2     1    18\n -8.7912410635652076E+00 a        44     0     2     1    19\n  4.3903318583813933E+00 a        45     0     2     1    20\n  3.3748047065442632E-01 a        46     0     2     1    21\n -6.6858946327311741E-01 a        47     0     2     1    22\n  5.4447187026310928E+00 a        48     0     2     1    23\n  1.9966018946508100E+01 a        49     0     2     1    24\n -1.7414420670154115E+01 a        50     0     2     1    25\n -3.9418657694849879E-01 a        51     0     3     1     1\n  9.1804829174186846E+00 a        52     0     3     1     2\n -1.0485089041850278E+01 a        53     0     3     1     3\n  8.9380499555048889E+00 a        54     0     3     1     4\n  1.0758607876097068E+01 a        55     0     3     1     5\n  7.2881492125393788E+00 a        56     0     3     1     6\n  8.2627077997774609E+00 a        57     0     3     1     7\n -1.2523613158520124E+01 a        58     0     3     1     8\n  4.5963999046141870E+00 a        59     0     3     1     9\n  8.2776469521184293E+00 a        60     0     3     1    10\n -2.1354371687617113E+00 a        61     0     3     1    11\n -9.0381751821938234E+00 a        62     0     3     1    12\n -1.2209592338152297E+00 a        63     0     3     1    13\n  4.7653671372245672E+00 a        64     0     3     1    14\n -1.7909124818088952E+01 a        65     0     3     1    15\n  3.2182917515973237E+00 a        66     0     3     1    16\n -2.3712750109800793E+00 a        67     0     3     1    17\n  4.6394007836500366E+00 a        68     0     3     1    18\n  2.3761984937954490E+00 a        69     0     3     1    19\n -1.0484832585147684E+01 a        70     0     3     1    20\n  1.2317970755621140E+01 a        71     0     3     1    21\n -1.5014054499447769E+00 a        72     0     3     1    22\n -1.1215435083480425E+00 a        73     0     3     1    23\n  8.9428653321614355E+00 a        74     0     3     1    24\n  1.2636165742848842E+00 a        75     0     3     1    25\n -1.3406492086741725E+01 a        76     0     4     1     1\n -1.0241053204283523E+01 a        77     0     4     1     2\n  4.3016369326050899E+01 a        78     0     4     1     3\n  2.0170433813810671E+01 a        79     0     4     1     4\n  1.3209328101408278E+01 a        80     0     4     1     5\n  1.2456789467161695E+01 a        81     0     4     1     6\n  4.3498515722861573E+00 a        82     0     4     1     7\n -2.1948185511490657E+01 a        83     0     4     1     8\n -1.5329558038416376E+01 a        84     0     4     1     9\n  1.4173337432869845E+01 a        85     0     4     1    10\n  5.6040631650516088E+00 a        86     0     4     1    11\n -9.7646834958548663E+00 a        87     0     4     1    12\n -1.3810669587629080E+01 a        88     0     4     1    13\n -1.5274915717855073E+00 a        89     0     4     1    14\n -1.3662043326477198E+01 a        90     0     4     1    15\n -2.5095635769057225E+01 a        91     0     4     1    16\n  5.4033548590960638E+00 a        92     0     4     1    17\n  1.1047593171711565E+01 a        93     0     4     1    18\n  1.9404912122904062E+01 a        94     0     4     1    19\n  2.4043652449872512E+00 a        95     0     4     1    20\n -3.3818087825635010E+00 a        96     0     4     1    21\n -4.9505657938825802E+00 a        97     0     4     1    22\n  6.2159614529590854E+00 a        98     0     4     1    23\n -1.9315299866781363E+01 a        99     0     4     1    24\n  2.4149549923763363E+01 a       100     0     4     1    25\n  2.2633190213689671E+00 a       101     0     5     1     1\n -1.1275056403465689E+01 a       102     0     5     1     2\n  1.2588751117785917E+00 a       103     0     5     1     3\n -1.7399288116611554E+01 a       104     0     5     1     4\n -1.8915392010979964E+01 a       105     0     5     1     5\n -6.5088880348621911E+00 a       106     0     5     1     6\n -8.7022768117985532E+00 a       107     0     5     1     7\n  9.5716939158219958E+00 a       108     0     5     1     8\n  6.7173652175539926E+00 a       109     0     5     1     9\n -1.0675975211687946E+01 a       110     0     5     1    10\n -9.8676303718126039E+00 a       111     0     5     1    11\n  2.2213929552875065E+01 a       112     0     5     1    12\n -3.9036053816020080E+00 a       113     0     5     1    13\n -1.0319098765495239E+01 a       114     0     5     1    14\n  2.0443220229254024E+01 a       115     0     5     1    15\n -1.4108663925115768E+00 a       116     0     5     1    16\n  8.2741724462704607E+00 a       117     0     5     1    17\n -5.3497533478370061E+00 a       118     0     5     1    18\n  1.0188467515179238E+00 a       119     0     5     1    19\n  3.3447636806848529E+00 a       120     0     5     1    20\n -6.3209134939668381E+00 a       121     0     5     1    21\n  7.0841649292282804E+00 a       122     0     5     1    22\n -1.3545092924552248E+01 a       123     0     5     1    23\n -1.0559922896741500E+00 a       124     0     5     1    24\n -1.6720809451360648E+00 a       125     0     5     1    25\n  2.8772403595811382E+00 a       126     0     6     1     1\n  6.6056181351338488E+00 a       127     0     6     1     2\n -2.1395393088585266E+01 a       128     0     6     1     3\n -1.6735909985964671E+01 a       129     0     6     1     4\n -4.4466039540570526E+00 a       130     0     6     1     5\n -1.9134274750411421E+01 a       131     0     6     1     6\n  7.4840405517853625E+00 a       132     0     6     1     7\n  1.5375004378912831E+01 a       133     0     6     1     8\n -3.2781218210557539E-01 a       134     0     6     1     9\n  5.1424696656729978E+00 a       135     0     6     1    10\n  2.4028588442306344E+00 a       136     0     6     1    11\n  1.6576032835324068E+00 a       137     0     6     1    12\n -1.8331489599850683E+00 a       138     0     6     1    13\n  1.5714883034771246E+01 a       139     0     6     1    14\n  1.3932522318533026E+01 a       140     0     6     1    15\n  3.0252340531342401E+01 a       141     0     6     1    16\n -2.0172838001093005E+01 a       142     0     6     1    17\n -1.3208548828817202E+01 a       143     0     6     1    18\n -1.1333313633908213E+01 a       144     0     6     1    19\n -2.2075367220543007E-01 a       145     0     6     1    20\n  5.4183716265511874E+00 a       146     0     6     1    21\n  4.4469214579975294E+00 a       147     0     6     1    22\n -1.7974421141420628E+01 a       148     0     6     1    23\n  1.3331466657294333E+01 a       149     0     6     1    24\n -1.0273470133062483E+01 a       150     0     6     1    25\n -1.3893961251032516E+00 a       151     0     7     1     1\n  4.8442398001659086E+00 a       152     0     7     1     2\n -1.4036072623897150E+01 a       153     0     7     1     3\n  1.9115742411572878E+01 a       154     0     7     1     4\n  1.7609386484170951E+01 a       155     0     7     1     5\n  7.6541742060341660E+00 a       156     0     7     1     6\n  2.6652782695389745E+00 a       157     0     7     1     7\n -4.1794554937287582E+00 a       158     0     7     1     8\n -1.1905203283691870E+01 a       159     0     7     1     9\n  9.5475237719776391E+00 a       160     0     7     1    10\n  7.7121176720610016E+00 a       161     0     7     1    11\n -1.6773486202682584E+01 a       162     0     7     1    12\n  8.6676731368122528E+00 a       163     0     7     1    13\n -1.2293039810028539E+00 a       164     0     7     1    14\n -2.2811823974655120E+01 a       165     0     7     1    15\n -7.1906975038556888E+00 a       166     0     7     1    16\n -1.1100936660627136E+01 a       167     0     7     1    17\n  2.5096456515549410E+00 a       168     0     7     1    18\n -8.2830054125661903E+00 a       169     0     7     1    19\n  1.4308990630020320E+01 a       170     0     7     1    20\n -1.4211125648871650E+00 a       171     0     7     1    21\n -7.1030788471181472E-01 a       172     0     7     1    22\n  1.9855633135275369E+01 a       173     0     7     1    23\n -5.0222825995011018E+00 a       174     0     7     1    24\n  2.8336876309217565E+00 a       175     0     7     1    25\n  1.2989870863882689E+00 a       176     0     8     1     1\n  1.6317155326554985E+01 a       177     0     8     1     2\n  1.1299807220875589E+01 a       178     0     8     1     3\n  1.6662446968000719E+01 a       179     0     8     1     4\n -2.1148958055015852E+00 a       180     0     8     1     5\n  8.0807820713485157E+00 a       181     0     8     1     6\n  1.4756928529491644E+00 a       182     0     8     1     7\n -1.8576498548437503E+00 a       183     0     8     1     8\n -6.5803763266761752E+00 a       184     0     8     1     9\n -1.4617321665219620E+01 a       185     0     8     1    10\n  2.5420127922121498E+00 a       186     0     8     1    11\n -1.1459546725077542E+01 a       187     0     8     1    12\n -5.7279252792377344E-01 a       188     0     8     1    13\n  6.6995479956870465E+00 a       189     0     8     1    14\n  6.5026121098595775E+00 a       190     0     8     1    15\n -2.4146992911321604E+01 a       191     0     8     1    16\n  1.7592777430005096E+01 a       192     0     8     1    17\n -4.4088079834404530E+00 a       193     0     8     1    18\n  2.6619475322128787E+00 a       194     0     8     1    19\n -2.7620162813322896E+01 a       195     0     8     1    20\n  1.1312775745303194E+01 a       196     0     8     1    21\n  7.8960900397005016E+00 a       197     0     8     1    22\n -9.2584890220611644E+00 a       198     0     8     1    23\n -7.5829075251590856E+00 a       199     0     8     1    24\n -1.5702889381396949E+01 a       200     0     8     1    25\n -6.0639703911359019E-02 a       201     0     9     1     1\n -4.9247565651287832E+00 a       202     0     9     1     2\n  1.2106355466042226E+01 a       203     0     9     1     3\n -8.5040672154593562E+00 a       204     0     9     1     4\n -1.9730634072023652E+00 a       205     0     9     1     5\n  1.3338172438762994E+00 a       206     0     9     1     6\n  1.0403848598882854E+00 a       207     0     9     1     7\n  3.1716127040577504E+00 a       208     0     9     1     8\n  4.8548323846115409E+00 a       209     0     9     1     9\n  2.8285159512886676E-01 a       210     0     9     1    10\n -7.2538963241095287E+00 a       211     0     9     1    11\n  5.6605292741969135E+00 a       212     0     9     1    12\n -7.3281447205805028E+00 a       213     0     9     1    13\n -7.2323271523996810E+00 a       214     0     9     1    14\n  2.7162165549305191E+00 a       215     0     9     1    15\n  4.7371512123906303E+00 a       216     0     9     1    16\n -1.2795462595586067E+00 a       217     0     9     1    17\n -1.2479842668197239E+00 a       218     0     9     1    18\n  8.2517482868477465E+00 a       219     0     9     1    19\n  1.5771106219004059E+00 a       220     0     9     1    20\n  1.1199186705905022E+00 a       221     0     9     1    21\n -2.3206003597031788E-01 a       222     0     9     1    22\n -1.8081347949376255E+01 a       223     0     9     1    23\n  6.4100804204621458E+00 a       224     0     9     1    24\n  2.0638413110708587E-01 a       225     0     9     1    25\n  5.4946010011519562E+00 a       226     0    10     1     1\n -1.0007883449351111E+01 a       227     0    10     1     2\n -4.2092466490417992E+00 a       228     0    10     1     3\n -5.1484334386740827E+00 a       229     0    10     1     4\n  3.8492140234244099E+00 a       230     0    10     1     5\n  3.7806988156875683E+00 a       231     0    10     1     6\n -3.3355303672289521E-01 a       232     0    10     1     7\n  8.5957281207011293E-01 a       233     0    10     1     8\n  2.6318043159412694E+00 a       234     0    10     1     9\n -2.0370256057905092E+00 a       235     0    10     1    10\n -6.0705410865883813E+00 a       236     0    10     1    11\n  7.7663948435164212E+00 a       237     0    10     1    12\n  5.2575997574986886E+00 a       238     0    10     1    13\n -1.0970226410597640E+01 a       239     0    10     1    14\n -8.2022944757991745E+00 a       240     0    10     1    15\n  1.4611135167439018E+00 a       241     0    10     1    16\n -9.6067700839357795E-01 a       242     0    10     1    17\n  2.8969685517227264E+00 a       243     0    10     1    18\n  5.1871728208292078E-01 a       244     0    10     1    19\n  5.9723981759776086E+00 a       245     0    10     1    20\n -5.6526426853755227E+00 a       246     0    10     1    21\n -5.7012415503934060E+00 a       247     0    10     1    22\n  1.3226673860538469E+01 a       248     0    10     1    23\n -1.1596542017869393E+00 a       249     0    10     1    24\n  4.5181717464756330E+00 a       250     0    10     1    25\n  2.9081108390343352E-01 a       251     0    11     1     1\n  7.0173519357555021E+00 a       252     0    11     1     2\n -2.7343225639603612E+00 a       253     0    11     1     3\n  6.7125648985634467E-01 a       254     0    11     1     4\n -1.4389607300831309E+00 a       255     0    11     1     5\n  2.0863810552553317E+00 a       256     0    11     1     6\n -2.8278441217480297E+00 a       257     0    11     1     7\n -1.8684390261232542E+00 a       258     0    11     1     8\n  1.5173228455949850E+00 a       259     0    11     1     9\n -1.7720802500487582E+00 a       260     0    11     1    10\n  2.9615007040584400E+00 a       261     0    11     1    11\n  5.5888676956090788E-01 a       262     0    11     1    12\n -4.1893717343842518E-01 a       263     0    11     1    13\n -4.5555017384864960E-01 a       264     0    11     1    14\n -1.2004787116771394E+00 a       265     0    11     1    15\n -4.3671713173561306E+00 a       266     0    11     1    16\n  2.6268170207311425E+00 a       267     0    11     1    17\n  2.0861374981960101E+00 a       268     0    11     1    18\n -3.9467976641769651E+00 a       269     0    11     1    19\n -2.8568852978075676E+00 a       270     0    11     1    20\n -3.6298673422613743E+00 a       271     0    11     1    21\n -2.3751659557584084E+00 a       272     0    11     1    22\n  9.6961030126275300E+00 a       273     0    11     1    23\n -3.8360345397984514E+00 a       274     0    11     1    24\n  7.4917832681719021E-01 a       275     0    11     1    25\n -3.8601565331430994E+00 a       276     0    12     1     1\n  1.2334085724542578E+00 a       277     0    12     1     2\n  1.3883137264471166E+00 a       278     0    12     1     3\n  3.5605774607307024E+00 a       279     0    12     1     4\n -5.7819414222489574E+00 a       280     0    12     1     5\n -1.2501210997170223E-01 a       281     0    12     1     6\n -4.2808961405835779E+00 a       282     0    12     1     7\n -7.3252216114344915E+00 a       283     0    12     1     8\n  6.0219945070033543E-01 a       284     0    12     1     9\n  3.1395849109967169E+00 a       285     0    12     1    10\n  3.0305896266861554E+00 a       286     0    12     1    11\n -1.4143455695905820E+00 a       287     0    12     1    12\n -5.4638828890258671E+00 a       288     0    12     1    13\n  6.4792557797350705E+00 a       289     0    12     1    14\n  4.5371436871747193E+00 a       290     0    12     1    15\n -1.1533461552353546E+00 a       291     0    12     1    16\n -2.3558298927391648E+00 a       292     0    12     1    17\n  1.7399171589274749E+00 a       293     0    12     1    18\n -4.8487063398429440E+00 a       294     0    12     1    19\n -5.7033421532043960E-01 a       295     0    12     1    20\n -1.4257707367342978E+00 a       296     0    12     1    21\n -2.6397293314995309E+00 a       297     0    12     1    22\n -2.2627535308920042E+00 a       298     0    12     1    23\n -2.7717009651755204E+00 a       299     0    12     1    24\n  2.7387478336632087E+00 a       300     0    12     1    25\n  2.4186741478605520E+00 a       301     0    13     1     1\n -3.4944840306430418E+00 a       302     0    13     1     2\n  2.1030004854108602E+00 a       303     0    13     1     3\n  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  },
  {
    "path": "examples/nnp-dist/Cu2S_PBE/input.data",
    "content": "begin\ncomment source_file_name=OUTCAR_4_1\nlattice 15.415349658 0.000000000 0.000000000\nlattice 0.000000000 12.016005204 0.000000000\nlattice -6.055885795 0.000000000 12.226281044\natom 9.66279 1.04561 10.73808 S 0.0 0.0 0.107416 0.024235 -0.891279\natom -3.16184 6.79866 8.04560 S 0.0 0.0 0.066538 0.139566 0.120509\natom -0.30404 11.04333 1.97659 S 0.0 0.0 -0.953672 -0.464533 -1.796811\natom 12.83426 5.06839 4.33902 S 0.0 0.0 0.393296 -0.326470 -0.518344\natom 12.39515 0.83117 4.16637 S 0.0 0.0 -0.063080 -0.611946 0.506821\natom -0.04295 7.13059 1.93130 S 0.0 0.0 -0.643788 -0.077636 0.315228\natom -3.25380 10.86483 8.16358 S 0.0 0.0 0.302005 0.898190 -0.193786\natom 9.41762 5.14521 10.58660 S 0.0 0.0 -0.644394 -0.340890 -0.050007\natom 9.00831 1.11279 6.18474 S 0.0 0.0 0.511148 0.550276 -0.454197\natom 3.34802 6.99932 0.09625 S 0.0 0.0 0.108918 0.284724 0.514152\natom 0.30069 11.03010 5.97943 S 0.0 0.0 0.216866 -0.247468 0.308978\natom 12.12524 5.04060 0.14613 S 0.0 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0.0 0.0 0.197651 -0.410017 -0.474082\natom 12.07390 8.62516 0.18008 S 0.0 0.0 0.955619 0.478197 -0.371759\natom 9.29009 9.21675 6.39687 S 0.0 0.0 -0.053343 -0.438911 -0.538072\natom -2.79943 3.30466 11.86546 S 0.0 0.0 0.397348 0.490476 0.572317\natom 0.22927 2.73487 1.72492 S 0.0 0.0 -0.311377 0.041312 -0.093182\natom 12.80848 9.20714 4.54446 S 0.0 0.0 -1.078226 -0.482916 -0.754490\natom 9.57560 8.83412 10.64965 S 0.0 0.0 -0.180223 0.207007 -0.965804\natom -3.02133 3.13287 7.77891 S 0.0 0.0 -0.431739 0.229304 -0.188167\natom 11.52491 2.71697 3.53948 Cu 0.0 0.0 -0.524195 0.593531 -0.018888\natom 0.94130 9.18527 2.48932 Cu 0.0 0.0 0.344344 -0.016827 -0.038025\natom -2.17737 8.90566 8.67171 Cu 0.0 0.0 -0.080113 -0.460384 -0.097485\natom 8.60937 2.99411 9.87382 Cu 0.0 0.0 0.242483 0.166370 -0.096114\natom 5.78704 0.81660 8.10398 Cu 0.0 0.0 -0.650869 0.037090 0.138420\natom 1.13645 6.89390 9.81986 Cu 0.0 0.0 -0.922068 -0.415802 0.004088\natom 3.98661 11.22749 4.05170 Cu 0.0 0.0 -0.169993 0.048173 -0.094445\natom 8.48776 5.35715 2.31898 Cu 0.0 0.0 -0.235778 -0.425782 -0.273045\natom 8.46457 1.29601 1.87017 Cu 0.0 0.0 -0.176692 0.115597 0.370769\natom 4.03103 6.96064 3.88549 Cu 0.0 0.0 0.138133 0.336666 0.141528\natom 0.94448 10.87127 10.21508 Cu 0.0 0.0 0.488695 0.336434 0.182050\natom 5.52896 4.74049 8.15135 Cu 0.0 0.0 -0.555966 -0.104080 -0.202623\natom 5.25495 2.85580 0.88760 Cu 0.0 0.0 -0.236780 0.111323 0.058556\natom 7.20832 9.00509 5.25253 Cu 0.0 0.0 -0.093050 -0.067663 0.112018\natom 4.02963 9.12378 11.29065 Cu 0.0 0.0 0.214455 -0.397161 -0.297440\natom 2.00869 2.95149 6.95641 Cu 0.0 0.0 0.242228 0.086186 0.256424\natom -3.59727 1.31298 11.56779 Cu 0.0 0.0 -0.234649 0.051811 -0.011230\natom 10.17489 7.11535 7.19747 Cu 0.0 0.0 -0.205621 -0.373986 -0.133792\natom 13.14051 10.69193 0.61472 Cu 0.0 0.0 -0.227511 0.015227 -0.013204\natom -0.15851 4.93004 5.03782 Cu 0.0 0.0 -0.407379 -0.188360 -0.079197\natom -1.03043 0.75778 5.49457 Cu 0.0 0.0 -0.614057 0.276670 -0.421905\natom 13.29870 6.86184 0.95026 Cu 0.0 0.0 0.173253 -0.290646 0.319586\natom 9.90736 11.28706 7.03112 Cu 0.0 0.0 0.528504 -0.034630 0.164799\natom -4.08827 5.25818 11.63154 Cu 0.0 0.0 0.507294 -0.050859 0.108014\natom 14.22568 1.81408 0.08656 Cu 0.0 0.0 0.571499 0.026055 -0.038863\natom -1.97034 7.15598 6.03887 Cu 0.0 0.0 -0.449980 0.314388 0.305998\natom -5.20546 10.47006 12.19513 Cu 0.0 0.0 0.395519 -0.013242 0.783300\natom 11.23565 4.47173 5.73470 Cu 0.0 0.0 -0.177903 -0.216022 0.218810\natom 11.50533 1.75385 6.16054 Cu 0.0 0.0 -0.082071 0.040075 -0.078104\natom 1.05145 7.68106 0.13325 Cu 0.0 0.0 0.678999 0.031254 -0.143904\natom -1.99506 10.44925 6.34486 Cu 0.0 0.0 0.240461 0.040601 0.140157\natom 14.46480 4.42495 0.30428 Cu 0.0 0.0 -0.397487 -0.006486 -0.227579\natom 9.50706 3.23697 7.16092 Cu 0.0 0.0 0.420873 -0.228470 -0.137433\natom 3.09422 9.25746 0.87162 Cu 0.0 0.0 0.083127 -0.013205 -0.008907\natom 0.08332 8.97416 7.15956 Cu 0.0 0.0 0.004363 -0.110554 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4.59107 9.25548 Cu 0.0 0.0 0.004397 0.377740 -0.175196\natom 0.44256 0.79397 7.51533 Cu 0.0 0.0 0.392843 -0.098361 0.143483\natom 5.25134 6.41678 10.66453 Cu 0.0 0.0 0.475273 -0.138365 -0.079004\natom 8.24962 11.81450 4.48984 Cu 0.0 0.0 0.215133 -0.064211 -0.350886\natom 4.18342 5.45581 1.75203 Cu 0.0 0.0 -0.080309 -0.016133 -0.219496\natom 4.01003 0.66675 1.73762 Cu 0.0 0.0 0.028881 -0.323578 0.033634\natom 8.34839 6.92699 4.24743 Cu 0.0 0.0 -0.310258 0.036970 0.397137\natom 5.48094 11.18523 10.58182 Cu 0.0 0.0 0.514304 0.188252 -0.630833\natom 1.07131 5.38871 7.37534 Cu 0.0 0.0 0.320279 0.188182 0.416405\natom 4.21301 2.62568 9.10014 Cu 0.0 0.0 -0.197230 -0.370539 -0.076098\natom 2.86651 8.26904 9.12445 Cu 0.0 0.0 0.813195 0.821609 -0.598471\natom 5.34637 9.52143 2.76224 Cu 0.0 0.0 0.183371 -0.205205 0.073164\natom 6.83808 3.46300 3.01720 Cu 0.0 0.0 0.096663 -0.107759 -0.264892\natom -1.22919 1.20692 2.84928 Cu 0.0 0.0 0.111910 0.175226 -0.288781\natom 12.57696 7.12242 3.51550 Cu 0.0 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0.157264 0.197031\natom 1.02280 10.58200 0.06181 Cu 0.0 0.0 -0.218236 -0.187763 0.031161\natom 11.66814 4.65161 6.11953 Cu 0.0 0.0 -0.070981 -0.144674 0.268308\natom 11.17925 1.32646 5.84452 Cu 0.0 0.0 0.023128 -0.035360 0.242812\natom -4.61050 7.95128 11.73329 Cu 0.0 0.0 0.329658 -0.333983 0.292666\natom -1.78278 10.52749 5.82970 Cu 0.0 0.0 0.034615 -0.364520 0.129266\natom 9.00914 5.78702 12.09242 Cu 0.0 0.0 0.994671 -0.386441 -0.075135\natom 7.80736 2.39500 4.07240 Cu 0.0 0.0 0.441504 0.017547 -0.066392\natom 3.16731 9.66801 1.33663 Cu 0.0 0.0 -0.274231 -0.649275 1.020066\natom -0.04408 8.60360 7.36891 Cu 0.0 0.0 0.180492 0.364851 0.169512\natom 13.36768 3.03761 0.20609 Cu 0.0 0.0 0.978545 -0.227040 0.222372\natom 1.44044 1.67482 11.32771 Cu 0.0 0.0 -1.101495 -0.309701 0.206537\natom 5.63563 7.79884 6.93017 Cu 0.0 0.0 -0.324695 0.238419 -0.473087\natom 8.51250 10.83254 1.12027 Cu 0.0 0.0 0.488465 -0.159050 -0.471260\natom 3.85876 4.58544 5.21483 Cu 0.0 0.0 0.259699 -0.580176 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0.69367 1.61273 Cu 0.0 0.0 0.352183 -0.330605 -0.433545\natom 8.42771 6.69296 4.47460 Cu 0.0 0.0 0.689370 -0.431659 -0.180798\natom 5.46930 11.27210 10.45754 Cu 0.0 0.0 -0.131870 0.167259 -0.200839\natom 1.02843 5.27934 7.63758 Cu 0.0 0.0 -0.362658 0.007936 -0.282589\natom 2.81917 2.00618 9.27301 Cu 0.0 0.0 0.318462 0.074140 0.001576\natom 2.64013 8.64133 9.20612 Cu 0.0 0.0 0.128971 -0.137565 0.331888\natom 6.04710 9.36861 3.07892 Cu 0.0 0.0 -0.667901 0.845714 0.059480\natom 6.00274 4.27888 2.85114 Cu 0.0 0.0 -0.037020 0.057974 -0.353457\natom 12.92783 1.12272 2.04760 Cu 0.0 0.0 0.401960 0.151104 1.434726\natom 13.37407 7.13313 3.29031 Cu 0.0 0.0 0.324719 -0.201409 -0.364960\natom -4.65025 11.33050 9.53169 Cu 0.0 0.0 -0.565266 1.138113 1.042211\natom 11.04888 4.60936 8.68318 Cu 0.0 0.0 0.940677 -0.174636 -0.571331\natom 4.02365 1.31607 11.56031 Cu 0.0 0.0 -0.376401 -0.380534 -0.131713\natom 2.46413 7.30893 6.98392 Cu 0.0 0.0 -0.328069 -0.319872 0.014500\natom 6.16733 10.98807 0.73595 Cu 0.0 0.0 -0.576462 -0.180970 -0.049483\natom 7.32782 4.31071 5.82521 Cu 0.0 0.0 -0.522107 0.353251 -0.959985\natom 7.66354 2.73122 7.50603 Cu 0.0 0.0 -0.166669 0.192502 0.201686\natom -1.43250 8.41399 11.77217 Cu 0.0 0.0 0.347823 0.068297 -0.186494\natom 2.11419 9.49110 5.62346 Cu 0.0 0.0 -0.042565 0.158531 -0.223262\natom 11.03887 2.73447 1.15455 Cu 0.0 0.0 -0.117768 0.166711 0.190583\natom 2.43931 2.81590 1.89111 Cu 0.0 0.0 0.006521 0.227399 -0.415608\natom 10.21714 8.56313 4.34968 Cu 0.0 0.0 0.258534 0.100881 -0.558522\natom 7.09611 9.38395 10.57802 Cu 0.0 0.0 0.393663 0.075645 0.014443\natom -1.59050 4.06116 7.81026 Cu 0.0 0.0 0.776427 0.169641 0.044501\natom -2.15370 1.08495 8.85227 Cu 0.0 0.0 -0.251265 -0.119388 -0.127210\natom 8.67455 7.22254 10.03372 Cu 0.0 0.0 -0.079222 0.387976 -0.021438\natom 11.53372 11.21480 3.96977 Cu 0.0 0.0 -0.374950 -0.033082 -0.260344\natom 0.47515 5.15818 2.57476 Cu 0.0 0.0 0.420379 -0.030283 -0.128469\nenergy -564.447991\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_176\nlattice 15.463955202 0.000000000 0.000000000\nlattice 0.000000000 12.053892406 0.000000000\nlattice -6.074980375 0.000000000 12.264831259\natom 9.66285 1.13396 10.35953 S 0.0 0.0 0.059331 0.466949 -0.252002\natom -3.34021 7.01825 7.89525 S 0.0 0.0 0.013108 -0.377592 0.106189\natom -0.33307 11.13913 1.83530 S 0.0 0.0 0.190905 0.101275 0.012557\natom 12.84785 5.15702 4.46957 S 0.0 0.0 0.781157 -0.254804 -0.012527\natom 12.44940 1.02530 4.51863 S 0.0 0.0 -0.678636 0.645963 -0.073725\natom -0.40165 6.94989 1.45069 S 0.0 0.0 -0.414465 -0.480092 0.533069\natom -3.18688 11.35965 7.96824 S 0.0 0.0 -0.109083 -1.189397 -0.178564\natom 9.42211 5.27973 10.76485 S 0.0 0.0 0.605880 -0.929977 0.707081\natom 8.86475 1.11073 6.19884 S 0.0 0.0 -0.300114 0.358714 0.564408\natom -2.63355 7.01827 12.08403 S 0.0 0.0 -0.156676 0.110675 0.236263\natom 0.31827 11.07834 6.16183 S 0.0 0.0 0.650049 0.304402 -0.264113\natom 12.06705 4.59763 0.13430 S 0.0 0.0 0.561013 1.611998 0.192934\natom 6.16555 1.02111 12.25565 S 0.0 0.0 0.995092 -0.381545 -0.518864\natom 0.19593 6.71797 6.06409 S 0.0 0.0 -0.359264 0.580047 0.566627\natom 3.43019 11.17345 0.23481 S 0.0 0.0 0.111344 -0.466229 -0.294129\natom 9.19687 5.06887 5.95682 S 0.0 0.0 -0.620737 0.947887 0.781180\natom 3.47484 0.85546 7.27266 S 0.0 0.0 0.282027 0.027802 -0.173750\natom 2.87215 7.11764 10.74581 S 0.0 0.0 0.539568 -1.150546 0.227819\natom 6.06409 11.04047 4.64475 S 0.0 0.0 -0.287356 -0.462820 0.112927\natom 6.18876 4.82254 1.18148 S 0.0 0.0 -0.059584 0.123912 0.094320\natom 6.55072 0.49489 1.19980 S 0.0 0.0 0.005871 -0.638718 -0.327630\natom 6.08033 6.79862 4.87843 S 0.0 0.0 0.180856 0.427868 -0.190605\natom 3.22039 11.23071 11.07410 S 0.0 0.0 -0.157242 -0.068576 0.934038\natom 3.38936 5.31636 7.20173 S 0.0 0.0 0.286741 0.030167 -0.971897\natom -0.10619 0.74172 9.60268 S 0.0 0.0 -0.277689 -0.109803 0.195716\natom 6.52269 7.06115 8.74997 S 0.0 0.0 -0.115919 -0.523606 -0.077707\natom 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0.185371 -0.392556 -0.207226\natom 12.07641 8.95908 0.14265 S 0.0 0.0 0.441586 -0.584793 0.196521\natom 9.22628 9.55966 6.46445 S 0.0 0.0 1.188211 -0.824610 0.517735\natom -2.91541 3.20849 11.88179 S 0.0 0.0 -0.324162 -0.287234 0.678644\natom -0.17466 2.74423 1.66850 S 0.0 0.0 -0.372012 0.572366 0.638305\natom 12.50872 8.96375 4.69524 S 0.0 0.0 1.048691 -0.373282 -0.185449\natom 9.63818 9.19569 10.62692 S 0.0 0.0 -0.332292 0.705799 -0.043748\natom -3.39740 3.10418 7.82119 S 0.0 0.0 -0.394274 0.204585 0.179593\natom 11.41337 2.93384 3.62262 Cu 0.0 0.0 -0.137120 -0.022584 -0.215086\natom 0.42729 8.98124 2.15855 Cu 0.0 0.0 0.280879 -0.322722 0.213868\natom -2.31587 9.10396 8.70111 Cu 0.0 0.0 0.410500 0.664991 -0.503630\natom 8.78767 3.43602 9.81686 Cu 0.0 0.0 0.475583 -0.513672 0.132257\natom 5.64818 1.02099 8.42292 Cu 0.0 0.0 -0.271670 -0.353939 0.232634\natom 0.84887 6.77692 9.62394 Cu 0.0 0.0 0.162007 -0.779704 0.161309\natom 3.93285 11.07174 4.04964 Cu 0.0 0.0 -0.368359 0.036225 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3.75629 10.61762 Cu 0.0 0.0 -0.473425 -0.110636 -0.590338\natom 1.05952 1.47514 11.44673 Cu 0.0 0.0 0.195146 -0.113334 -0.029193\natom 5.10503 7.84909 6.58179 Cu 0.0 0.0 -0.060244 0.529389 0.274714\natom 8.69693 9.23535 2.74652 Cu 0.0 0.0 0.198904 0.042220 0.139482\natom 4.18862 4.32075 5.08468 Cu 0.0 0.0 -0.687486 0.252557 0.046419\natom 3.56995 1.66576 5.17934 Cu 0.0 0.0 0.350572 0.113282 0.055055\natom 8.38102 7.55761 0.67249 Cu 0.0 0.0 0.221268 -0.096170 0.196745\natom 5.88457 10.48193 6.82940 Cu 0.0 0.0 -0.527455 -0.073681 -0.327656\natom 0.68402 4.12479 11.24727 Cu 0.0 0.0 0.274571 0.302013 0.432248\natom -1.12364 2.61442 10.69119 Cu 0.0 0.0 -0.406000 -0.415393 -0.376120\natom 7.54822 8.75270 7.69958 Cu 0.0 0.0 0.122682 -0.295042 0.353740\natom 10.67731 10.00740 1.48796 Cu 0.0 0.0 0.004412 0.290884 -0.025178\natom 1.83663 3.28932 4.22959 Cu 0.0 0.0 -0.080904 0.356566 -0.023366\natom 8.33507 0.56145 8.60945 Cu 0.0 0.0 0.114603 -0.021616 -0.355167\natom -2.04215 6.77389 9.82833 Cu 0.0 0.0 -0.007534 -0.717134 0.011035\natom 1.04834 11.37616 3.74608 Cu 0.0 0.0 -0.288259 0.230254 0.065589\natom 11.58793 5.79437 2.84809 Cu 0.0 0.0 -0.244081 -0.079537 -0.320782\natom 11.64504 0.70716 2.02330 Cu 0.0 0.0 -0.989841 -0.364179 0.552394\natom 1.11142 7.40922 4.23882 Cu 0.0 0.0 0.371931 0.133288 -0.489418\natom -1.88783 11.40659 10.34487 Cu 0.0 0.0 -0.096300 -0.299633 0.370507\natom 7.92534 5.01851 7.96233 Cu 0.0 0.0 0.356730 0.125769 -0.314713\natom -4.13829 2.80083 9.99982 Cu 0.0 0.0 0.131330 -0.067725 -0.257719\natom -4.32990 7.99757 9.60330 Cu 0.0 0.0 -0.389135 -0.044329 -0.182795\natom -1.56293 10.02503 3.28950 Cu 0.0 0.0 -0.163143 -0.170593 -0.024373\natom -1.30134 3.47561 3.73172 Cu 0.0 0.0 -0.100760 0.130375 -0.806868\natom 6.17439 1.10633 3.40005 Cu 0.0 0.0 0.336882 0.359130 0.398025\natom 6.37044 7.00825 2.48371 Cu 0.0 0.0 0.015742 -0.275627 0.324090\natom 3.44024 11.20972 8.87800 Cu 0.0 0.0 0.400193 -0.136619 -0.546082\natom 2.97105 4.56706 9.15608 Cu 0.0 0.0 0.063497 -0.348631 0.869253\natom 1.11599 0.64474 7.71934 Cu 0.0 0.0 0.175512 -0.174809 -0.067116\natom 5.23451 6.73209 10.62367 Cu 0.0 0.0 -0.215596 -0.206785 -0.046550\natom 8.13870 11.76967 4.64228 Cu 0.0 0.0 0.487756 -0.098486 -0.494435\natom 3.85755 5.39281 1.58245 Cu 0.0 0.0 0.667425 0.130359 -0.757463\natom 4.38669 0.61896 1.89101 Cu 0.0 0.0 -0.570598 -0.425698 -0.733302\natom 8.35009 6.83976 4.34297 Cu 0.0 0.0 -0.244335 -0.298785 0.428117\natom 5.60381 11.27390 10.53830 Cu 0.0 0.0 -0.027636 0.251980 0.082386\natom 1.00684 5.01967 7.69590 Cu 0.0 0.0 -0.486415 0.395445 0.104399\natom 3.08799 1.84265 9.12936 Cu 0.0 0.0 0.003704 0.021041 -0.495337\natom 2.97923 8.47613 9.00604 Cu 0.0 0.0 -0.203620 0.077976 0.018959\natom 6.20070 9.57946 2.99805 Cu 0.0 0.0 -0.144488 0.063499 -0.145917\natom 5.95888 3.89722 3.21338 Cu 0.0 0.0 0.189135 -0.088177 -0.244990\natom 13.80292 1.30259 2.79979 Cu 0.0 0.0 0.959629 -0.100412 -0.408433\natom 13.82911 7.37330 3.25673 Cu 0.0 0.0 -0.216742 0.234423 0.285689\natom 10.67763 11.28842 9.58969 Cu 0.0 0.0 -0.021239 -0.492052 0.293759\natom 10.65236 5.18394 8.51971 Cu 0.0 0.0 0.006797 -0.195878 0.204414\natom 4.18590 1.38357 11.39813 Cu 0.0 0.0 -0.375486 -0.017114 0.060248\natom 2.27516 7.42030 6.67243 Cu 0.0 0.0 0.523978 0.082577 0.237924\natom 7.84663 10.07741 0.39405 Cu 0.0 0.0 1.164994 1.031202 -0.529445\natom 6.81010 4.81633 5.60962 Cu 0.0 0.0 0.055794 -0.470187 0.015497\natom 7.14424 2.58987 7.06385 Cu 0.0 0.0 0.121366 0.070144 -0.525206\natom -1.45274 8.82216 11.02617 Cu 0.0 0.0 0.165812 0.240095 0.481689\natom 2.10769 9.84569 5.36999 Cu 0.0 0.0 -0.159444 -0.140440 0.752452\natom 10.47994 3.75604 1.23239 Cu 0.0 0.0 -0.380032 -0.307886 0.942959\natom 2.04626 2.36807 1.60570 Cu 0.0 0.0 0.448066 0.067754 -0.297946\natom 10.35379 8.55398 4.73610 Cu 0.0 0.0 -0.846167 -0.056089 -0.118372\natom 6.98392 9.10700 10.37288 Cu 0.0 0.0 0.323577 0.072657 -0.086433\natom -1.21280 3.26685 7.73503 Cu 0.0 0.0 0.632881 0.536764 -0.025554\natom 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-0.454017\natom 10.13844 7.11491 6.40231 Cu 0.0 0.0 -0.569071 0.250542 0.601601\natom 12.72990 10.98411 0.96736 Cu 0.0 0.0 -0.176046 0.318766 -0.333106\natom -0.00737 5.09788 5.75926 Cu 0.0 0.0 -0.029219 -0.200811 -0.079748\natom -0.93295 1.16232 5.26955 Cu 0.0 0.0 -0.492524 -0.633635 -0.250378\natom 13.28385 7.15458 0.66812 Cu 0.0 0.0 -0.301181 0.074160 -0.102055\natom 10.40943 11.12950 6.96072 Cu 0.0 0.0 -0.117897 -0.028344 -0.116176\natom -4.00996 5.24507 11.33974 Cu 0.0 0.0 0.012991 0.023391 -0.094382\natom 13.31640 2.97016 0.83392 Cu 0.0 0.0 -0.423414 0.150964 -0.607954\natom 12.47100 6.88116 5.74444 Cu 0.0 0.0 0.557164 -0.303740 -0.871168\natom 1.06901 10.65973 0.19548 Cu 0.0 0.0 0.012070 -0.284940 -0.273374\natom 11.29234 4.27251 5.96161 Cu 0.0 0.0 0.086863 0.332260 -0.115234\natom 11.62120 1.62573 6.08354 Cu 0.0 0.0 -0.048666 0.292079 0.471397\natom -4.65422 7.87348 11.91059 Cu 0.0 0.0 -0.960416 0.488317 -0.211798\natom -1.63735 10.42263 6.09840 Cu 0.0 0.0 -1.113106 -0.544845 -0.000427\natom 15.05717 4.96662 0.22650 Cu 0.0 0.0 -0.379133 -0.304059 0.136958\natom 9.28967 2.88898 5.08692 Cu 0.0 0.0 0.117682 0.616494 -0.306475\natom 3.16447 9.17559 1.14169 Cu 0.0 0.0 0.030456 0.037399 -0.640928\natom 0.37739 8.70188 7.70190 Cu 0.0 0.0 -0.001689 -0.201921 -0.548107\natom 5.28792 3.60439 10.55368 Cu 0.0 0.0 0.457627 -0.225015 0.531135\natom 1.03295 1.75095 11.62696 Cu 0.0 0.0 -0.173491 0.095705 -0.022558\natom 4.60570 7.55834 6.86272 Cu 0.0 0.0 0.674104 0.042332 -0.067677\natom 8.25251 10.54132 0.76591 Cu 0.0 0.0 0.114499 -0.291107 0.149544\natom 4.46596 4.18082 5.48738 Cu 0.0 0.0 -0.557451 -0.253554 0.050618\natom 3.58863 1.51455 5.07176 Cu 0.0 0.0 0.718783 0.669856 0.870525\natom 8.40039 7.59253 0.80712 Cu 0.0 0.0 0.343056 -0.036320 -0.525589\natom 5.48965 10.34826 6.97892 Cu 0.0 0.0 0.024921 -0.042790 0.317892\natom 0.80000 4.87994 11.68969 Cu 0.0 0.0 0.246354 -0.347015 0.236503\natom -1.18845 2.71278 10.31996 Cu 0.0 0.0 -0.104547 0.273178 0.306075\natom 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3.84134 Cu 0.0 0.0 -0.210706 0.227822 -0.550197\natom 5.58912 1.00407 3.49382 Cu 0.0 0.0 0.373138 0.265093 0.159110\natom 6.57741 7.14653 2.56683 Cu 0.0 0.0 -0.417628 -0.291723 0.407608\natom 3.58870 10.89339 8.71247 Cu 0.0 0.0 -0.305316 0.000667 0.350551\natom 3.42368 4.98435 9.96699 Cu 0.0 0.0 -0.255185 1.082788 -0.716166\natom 1.28762 0.71788 7.99947 Cu 0.0 0.0 0.405352 -0.190991 -0.277226\natom 5.85996 6.34795 10.61468 Cu 0.0 0.0 -0.073768 -0.028163 -0.035427\natom 8.15201 11.55962 4.48578 Cu 0.0 0.0 -0.644758 -0.427102 -0.395821\natom 3.57494 4.73989 1.23786 Cu 0.0 0.0 -0.051561 0.396326 0.465236\natom 3.80726 0.43646 1.82202 Cu 0.0 0.0 -0.125559 0.146887 -0.029206\natom 8.40548 6.57428 4.21744 Cu 0.0 0.0 0.033844 0.295766 0.253862\natom 5.44343 11.21633 10.68925 Cu 0.0 0.0 0.092219 0.324847 -0.419697\natom 1.28907 5.09385 8.21174 Cu 0.0 0.0 0.381162 0.156476 0.140724\natom 3.34804 2.44109 9.26473 Cu 0.0 0.0 -0.277518 -0.018140 -0.412823\natom 2.59851 8.50015 8.96715 Cu 0.0 0.0 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0.316984\natom 9.44482 9.35669 10.52433 S 0.0 0.0 0.123355 0.136570 -0.495146\natom -3.02449 3.30194 7.82746 S 0.0 0.0 0.212687 0.170418 -0.175442\natom 11.67543 3.17715 3.82097 Cu 0.0 0.0 -0.132108 -0.273595 0.073435\natom 0.84980 9.08603 2.52848 Cu 0.0 0.0 0.234813 0.480321 -0.150752\natom -2.61598 9.20958 8.16868 Cu 0.0 0.0 0.323066 1.558654 0.182828\natom 8.31095 3.30571 10.14593 Cu 0.0 0.0 0.065294 -0.220710 -0.531475\natom 5.36347 0.56375 8.47158 Cu 0.0 0.0 -0.273093 -0.159461 -0.117278\natom 1.04700 7.54401 9.94402 Cu 0.0 0.0 -1.381842 0.395253 -0.408891\natom 3.61068 11.09913 3.60760 Cu 0.0 0.0 0.280395 0.348068 0.571919\natom 8.32091 5.09934 1.98609 Cu 0.0 0.0 0.512465 0.379369 0.764857\natom 8.73278 0.81142 2.02043 Cu 0.0 0.0 -0.204404 -0.102945 0.142097\natom 3.97343 7.12833 4.11889 Cu 0.0 0.0 -0.098439 -0.034560 -0.227143\natom 0.94047 11.06189 10.14298 Cu 0.0 0.0 0.334059 0.026774 0.089888\natom 6.01770 4.52176 8.06381 Cu 0.0 0.0 -0.223240 -0.163693 0.263484\natom 5.48212 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Cu 0.0 0.0 -0.639656 -0.502632 0.278945\natom 11.25623 4.59140 6.17465 Cu 0.0 0.0 -0.167411 -0.323254 -0.088040\natom 10.74056 2.00309 7.23737 Cu 0.0 0.0 0.280785 0.289572 -0.082256\natom -5.03746 8.11584 12.01208 Cu 0.0 0.0 0.382434 -0.449550 0.445620\natom -1.94857 10.87638 5.61594 Cu 0.0 0.0 -0.285999 -0.126621 0.554910\natom 14.45612 4.56956 0.00791 Cu 0.0 0.0 -0.114656 -0.112373 0.378247\natom 9.32861 2.94473 5.03697 Cu 0.0 0.0 0.104405 -0.208697 0.101586\natom 3.08177 8.78775 1.26265 Cu 0.0 0.0 0.100098 -0.033736 -0.066842\natom 1.26045 9.79223 7.72958 Cu 0.0 0.0 -0.106339 -0.101528 0.011347\natom 6.12331 2.90073 11.91474 Cu 0.0 0.0 0.156307 -1.352597 -0.162173\natom 1.12871 1.68462 11.50637 Cu 0.0 0.0 0.069475 0.126589 -0.086201\natom 5.05905 7.48840 7.06112 Cu 0.0 0.0 0.463196 -0.016689 0.081990\natom 8.40755 10.03140 0.85379 Cu 0.0 0.0 -0.103302 0.414453 0.198273\natom 4.19600 4.03461 5.11551 Cu 0.0 0.0 -0.219619 0.038422 -0.014174\natom 3.56644 1.49862 5.41080 Cu 0.0 0.0 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6.30428 Cu 0.0 0.0 -0.322831 0.139102 0.206135\natom 8.02163 10.08801 12.23225 Cu 0.0 0.0 -0.222858 0.131274 0.256342\natom -0.56212 5.14775 5.32292 Cu 0.0 0.0 -0.076425 -0.606583 0.030943\natom -0.80989 0.93651 5.32614 Cu 0.0 0.0 -0.238610 0.307378 0.097839\natom 13.22050 6.98149 0.64487 Cu 0.0 0.0 0.169634 -0.132976 -0.014427\natom 10.68960 10.99004 6.55602 Cu 0.0 0.0 -0.031273 -0.115594 0.335940\natom -3.98489 5.49480 11.84622 Cu 0.0 0.0 -0.086968 -0.378460 -0.357526\natom 8.50023 0.72367 12.08366 Cu 0.0 0.0 -0.557422 0.104888 0.767138\natom -2.28814 7.03102 6.10286 Cu 0.0 0.0 0.247534 0.091236 -0.365017\natom 1.18362 10.23521 0.06025 Cu 0.0 0.0 -0.211480 0.405759 0.032660\natom 12.41333 4.38140 6.00365 Cu 0.0 0.0 -0.256548 -0.029173 0.576026\natom 11.51756 1.83507 6.64050 Cu 0.0 0.0 -0.221897 -0.172319 -0.401036\natom -4.27596 7.93845 11.17010 Cu 0.0 0.0 -0.066611 0.205050 0.002508\natom -2.00185 10.57175 5.51422 Cu 0.0 0.0 0.265903 -0.184834 0.472879\natom 14.56384 4.46179 0.08498 Cu 0.0 0.0 -0.076981 -0.184061 0.460070\natom 9.29155 2.94824 6.05561 Cu 0.0 0.0 0.356971 -0.083707 -0.140828\natom 2.79320 8.86419 1.18304 Cu 0.0 0.0 0.402123 0.043113 0.408780\natom 0.71620 9.62470 7.49043 Cu 0.0 0.0 -0.026539 -0.009460 -0.138752\natom 6.67586 3.02149 11.33699 Cu 0.0 0.0 -0.187888 -0.450268 -0.364371\natom 1.35323 2.05907 12.05236 Cu 0.0 0.0 -0.289119 -0.302741 -0.339240\natom 4.97791 7.50315 6.52953 Cu 0.0 0.0 0.236291 -0.531066 -0.158393\natom 8.66633 10.67540 0.88180 Cu 0.0 0.0 -0.009262 -0.265512 0.181465\natom 3.88832 4.68600 5.21390 Cu 0.0 0.0 0.190584 -0.315626 0.305439\natom 3.59371 1.95851 5.58261 Cu 0.0 0.0 0.415568 -0.230631 -1.048671\natom 8.69567 7.62597 0.52674 Cu 0.0 0.0 -0.222160 -0.053461 0.049758\natom 5.55294 9.85689 6.89807 Cu 0.0 0.0 0.412270 0.909727 0.119868\natom 0.54967 4.55307 11.71433 Cu 0.0 0.0 0.104313 0.066133 -0.114549\natom -1.42787 2.58175 10.69710 Cu 0.0 0.0 0.124508 -0.017162 0.078447\natom 7.63841 8.49022 7.73689 Cu 0.0 0.0 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-0.124887\natom 5.86688 9.56649 3.14262 Cu 0.0 0.0 -0.065061 0.131836 -0.551547\natom 7.25690 3.36116 3.14582 Cu 0.0 0.0 -0.011123 0.449408 0.143481\natom 13.94918 0.75037 2.82362 Cu 0.0 0.0 -0.191972 0.112782 0.135722\natom 13.52029 7.17132 3.33495 Cu 0.0 0.0 0.396371 -0.196837 -0.389273\natom -4.60781 10.42544 9.41729 Cu 0.0 0.0 0.379390 0.534571 -0.131199\natom 10.95215 4.93405 8.71385 Cu 0.0 0.0 0.046524 -0.177882 0.268881\natom 3.70882 1.18234 11.44669 Cu 0.0 0.0 0.478668 -0.145618 0.317542\natom 2.19800 7.16113 6.60811 Cu 0.0 0.0 -0.049952 0.386545 0.019818\natom 5.46788 10.89348 0.69516 Cu 0.0 0.0 0.595939 -0.967020 0.053046\natom 6.75504 4.92581 5.44408 Cu 0.0 0.0 -0.471192 -0.558760 0.004329\natom 6.94719 2.59723 6.99465 Cu 0.0 0.0 -0.363036 -0.065506 -0.441084\natom -0.53772 8.58625 11.57564 Cu 0.0 0.0 -0.154595 0.005370 -0.389952\natom 2.35242 9.91666 5.38753 Cu 0.0 0.0 -0.228784 -0.075660 0.021979\natom 10.53701 3.13823 0.79965 Cu 0.0 0.0 0.142064 0.159419 0.102862\natom 1.83115 2.12383 1.32680 Cu 0.0 0.0 -0.000513 0.388412 -0.178296\natom 9.86276 8.58750 4.23015 Cu 0.0 0.0 0.165429 -0.374009 -0.582075\natom 6.25401 9.81429 10.35848 Cu 0.0 0.0 -0.003169 0.438295 -0.463030\natom -0.40899 3.57584 8.13020 Cu 0.0 0.0 -0.226630 0.007697 -0.035426\natom -2.25922 1.24340 8.59967 Cu 0.0 0.0 0.330032 -0.533475 0.117152\natom 8.29838 7.22805 10.20971 Cu 0.0 0.0 -0.136638 0.131888 -0.118130\natom 11.70801 10.87039 3.90521 Cu 0.0 0.0 -0.649110 0.460998 -0.133177\natom 0.41048 4.73426 2.30406 Cu 0.0 0.0 0.156004 0.016041 -0.078820\nenergy -565.036508\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_261\nlattice 15.415026976 0.000000000 0.000000000\nlattice 0.000000000 12.015753678 0.000000000\nlattice -6.055759030 0.000000000 12.226025117\natom 9.33391 0.91596 10.48946 S 0.0 0.0 0.786740 0.127686 -0.436092\natom -3.43521 6.99419 7.88172 S 0.0 0.0 0.345123 -0.297495 1.207748\natom -0.16959 10.98461 1.99420 S 0.0 0.0 0.436167 -0.190197 0.450593\natom 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S 0.0 0.0 0.268124 0.824389 1.741362\natom 5.91565 10.92115 4.94652 S 0.0 0.0 0.816206 -0.069857 -0.458061\natom 6.19505 4.97784 1.19607 S 0.0 0.0 0.020261 0.232791 -0.436911\natom 6.51300 1.22938 1.43819 S 0.0 0.0 -0.034982 -0.914875 -0.946866\natom 6.07306 6.94380 4.93668 S 0.0 0.0 -1.069947 -0.817955 -0.382670\natom 3.08405 10.84138 10.97219 S 0.0 0.0 0.582596 -0.294231 -0.234379\natom 3.34583 5.01451 7.17457 S 0.0 0.0 0.433933 -0.515564 -0.059070\natom -0.10769 0.53439 9.55190 S 0.0 0.0 -0.246487 0.575358 -0.641655\natom 6.46784 6.93696 8.86987 S 0.0 0.0 0.195445 -0.871740 -0.723818\natom 9.71726 11.16132 2.44952 S 0.0 0.0 -0.350855 -0.023043 0.716478\natom 2.74777 4.92832 3.37943 S 0.0 0.0 -1.240342 0.662845 0.569114\natom 2.86321 1.09691 3.37519 S 0.0 0.0 0.168622 -0.323482 0.654758\natom 9.54365 7.17388 2.63388 S 0.0 0.0 -0.312841 0.398204 -0.329716\natom 6.68798 10.98009 8.90353 S 0.0 0.0 -0.149860 0.287866 -0.563104\natom -0.34160 4.88543 9.68239 S 0.0 0.0 -0.117975 -0.374465 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10.55069 S 0.0 0.0 0.073929 -0.154241 0.018321\natom -3.38107 2.91741 7.55176 S 0.0 0.0 0.715325 0.928195 -0.216603\natom 11.71801 2.98914 3.89390 Cu 0.0 0.0 -0.467988 -0.665921 -0.676485\natom 0.99904 9.01667 2.40789 Cu 0.0 0.0 -0.279413 0.098695 0.211728\natom -2.45788 8.89150 8.68152 Cu 0.0 0.0 0.460491 0.312367 0.059293\natom 8.65654 3.07551 9.75934 Cu 0.0 0.0 -0.419582 -0.382171 0.055251\natom 5.56828 0.93060 7.75629 Cu 0.0 0.0 -0.487518 -0.636133 0.688723\natom 0.75015 7.02990 10.06052 Cu 0.0 0.0 0.496763 -0.785950 0.118159\natom 3.90282 11.00621 3.48431 Cu 0.0 0.0 -0.488871 0.504442 0.314079\natom 8.29519 5.46566 1.61428 Cu 0.0 0.0 0.357376 -0.010017 0.440791\natom 9.15076 1.34525 2.56253 Cu 0.0 0.0 -0.093506 -0.615875 0.049226\natom 4.17865 6.69824 3.69420 Cu 0.0 0.0 -0.163601 0.398007 0.556611\natom 1.01648 10.72034 10.10046 Cu 0.0 0.0 -0.078193 -0.522280 0.140449\natom 5.62156 4.68027 8.04338 Cu 0.0 0.0 -0.708620 0.555179 -0.066652\natom 5.19654 2.96726 0.75982 Cu 0.0 0.0 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0.141225\natom 8.48774 9.23201 2.05606 Cu 0.0 0.0 0.470603 0.254027 0.207617\natom 5.39323 10.31506 7.02597 Cu 0.0 0.0 0.128387 0.525209 0.325742\natom 1.27201 4.13500 11.12724 Cu 0.0 0.0 0.100106 0.027229 0.148301\natom -1.08356 2.34871 10.36440 Cu 0.0 0.0 -0.115961 0.201545 -0.039684\natom 7.41684 9.00449 7.99731 Cu 0.0 0.0 -0.346857 -0.262197 0.497363\natom 11.91265 8.39927 2.42959 Cu 0.0 0.0 -0.131640 -0.321162 0.508974\natom 1.18746 1.93982 4.73443 Cu 0.0 0.0 0.316395 0.106054 -0.281281\natom 8.46428 0.58439 8.38410 Cu 0.0 0.0 -0.201599 -0.093222 -0.211731\natom -2.28228 6.03105 9.60677 Cu 0.0 0.0 -0.147047 0.154758 0.109189\natom 1.21645 11.58938 3.94392 Cu 0.0 0.0 0.036200 -0.091983 -0.032970\natom 11.10207 5.65120 2.47741 Cu 0.0 0.0 0.624661 -0.133601 -0.503282\natom 11.98936 0.59789 2.16769 Cu 0.0 0.0 -0.295112 0.256572 0.643703\natom 1.00043 6.73888 4.04158 Cu 0.0 0.0 0.529960 -0.354381 -0.658114\natom -2.12839 11.43922 9.97281 Cu 0.0 0.0 0.000413 -0.492403 0.310696\natom 8.12816 5.13331 8.11130 Cu 0.0 0.0 -0.210146 -0.302608 0.172841\natom 10.78163 1.78273 8.80755 Cu 0.0 0.0 -1.043324 -0.559393 0.927563\natom 10.41516 8.39121 8.64204 Cu 0.0 0.0 -0.395131 0.185406 0.035433\natom -1.53040 9.72295 3.36888 Cu 0.0 0.0 0.372856 0.130296 -0.400832\natom -1.41696 3.69703 3.19491 Cu 0.0 0.0 0.883350 -0.223926 -0.494067\natom 6.86443 1.73542 3.49266 Cu 0.0 0.0 0.244556 -0.303366 0.007376\natom 6.17918 6.97435 2.30802 Cu 0.0 0.0 0.209760 0.297266 -0.013530\natom 3.15940 10.95802 8.61593 Cu 0.0 0.0 0.193136 0.470719 0.148909\natom 2.88208 5.70957 9.23450 Cu 0.0 0.0 0.345822 -0.702524 -1.280960\natom 1.02004 12.01249 7.53204 Cu 0.0 0.0 -0.087097 0.438165 0.233971\natom 5.64859 6.84766 10.85928 Cu 0.0 0.0 -0.078639 0.031924 0.721273\natom 8.29656 11.31184 4.35364 Cu 0.0 0.0 -0.069122 0.018563 -0.176049\natom 3.67725 5.60939 1.57633 Cu 0.0 0.0 0.669505 0.757452 -1.443874\natom 4.00798 0.58669 1.47240 Cu 0.0 0.0 0.031678 0.170501 -0.276929\natom 8.25979 6.53135 4.39946 Cu 0.0 0.0 0.121604 -0.341586 -0.191260\natom 5.39557 11.25483 10.68752 Cu 0.0 0.0 -0.291604 -0.204365 -0.334073\natom 0.69703 5.65959 7.86760 Cu 0.0 0.0 -0.169854 -0.013095 -0.561101\natom 3.58008 2.31552 9.18250 Cu 0.0 0.0 0.116022 -0.224291 -0.555338\natom 3.05372 8.56933 9.43560 Cu 0.0 0.0 -0.411349 -0.314710 -0.570380\natom 5.68123 9.41030 3.31150 Cu 0.0 0.0 0.618118 -0.382904 -0.575557\natom 5.80858 4.17257 3.20862 Cu 0.0 0.0 0.124705 0.093073 -0.161157\natom -0.92440 1.11899 2.92312 Cu 0.0 0.0 0.062937 0.078153 0.035106\natom -1.44711 7.09351 3.54192 Cu 0.0 0.0 -0.344783 0.146651 -0.067587\natom 10.58942 10.83708 9.44404 Cu 0.0 0.0 0.459607 0.762299 -0.252833\natom 10.98782 4.51094 8.77469 Cu 0.0 0.0 -0.161489 0.006589 0.115299\natom 10.51264 2.34015 0.87372 Cu 0.0 0.0 0.354363 -0.027526 -0.319758\natom 2.56194 7.08435 6.78565 Cu 0.0 0.0 -0.177923 -0.212799 0.073616\natom 6.01815 11.05039 1.09580 Cu 0.0 0.0 -0.430044 1.160378 0.444636\natom 6.69093 4.86762 5.60643 Cu 0.0 0.0 -0.056310 -0.085972 0.047007\natom 7.13023 2.57847 6.91158 Cu 0.0 0.0 0.637455 0.182186 -0.414937\natom -1.18043 9.53299 11.44896 Cu 0.0 0.0 0.153076 -0.123030 0.152320\natom 1.74350 9.08802 5.03185 Cu 0.0 0.0 -0.309832 0.050675 0.116414\natom 4.09435 4.72815 11.62063 Cu 0.0 0.0 -0.488835 0.401761 -0.293672\natom 2.59578 3.44791 1.65468 Cu 0.0 0.0 0.001195 -0.804295 -0.231591\natom 9.73089 8.57633 4.39194 Cu 0.0 0.0 0.036982 0.288261 0.452128\natom 7.37620 9.13211 10.85042 Cu 0.0 0.0 -0.392944 0.094802 -0.026504\natom -1.05087 3.39136 8.03506 Cu 0.0 0.0 -0.158547 0.227874 0.594507\natom -2.23135 0.98797 8.10515 Cu 0.0 0.0 0.302332 0.190919 0.039003\natom 8.44600 6.93280 9.76244 Cu 0.0 0.0 0.794447 0.231274 0.607530\natom 11.43175 10.56534 3.95892 Cu 0.0 0.0 -0.479032 0.815489 -0.428313\natom 0.56312 5.02524 2.03818 Cu 0.0 0.0 0.206743 -0.955342 0.150812\nenergy -565.073649\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_279\nlattice 15.400727029 0.000000000 0.000000000\nlattice 0.000000000 12.004607111 0.000000000\nlattice -6.050141328 0.000000000 12.214683488\natom 9.65434 1.13629 10.42689 S 0.0 0.0 -0.027450 0.265189 0.059099\natom -3.69623 6.92843 7.97749 S 0.0 0.0 0.339291 0.304709 -0.296444\natom -0.30842 11.07389 1.81163 S 0.0 0.0 -0.347143 0.290416 -0.265011\natom 12.69913 4.92715 4.38423 S 0.0 0.0 -0.221622 0.137567 -0.221864\natom 12.81886 1.06893 3.99055 S 0.0 0.0 -0.445042 0.266383 0.093812\natom -0.18531 6.99544 1.90757 S 0.0 0.0 0.143616 0.002630 -0.419620\natom -2.90946 10.95025 7.86991 S 0.0 0.0 -0.270380 0.623666 0.222735\natom 9.57120 5.13156 10.74113 S 0.0 0.0 0.229174 -0.046146 -0.018056\natom 9.05460 0.97974 6.19685 S 0.0 0.0 0.481142 0.398229 0.331226\natom -3.06588 7.00845 11.87544 S 0.0 0.0 0.597812 -0.917245 0.172220\natom 0.42980 11.01015 6.07632 S 0.0 0.0 -0.133291 -0.160642 -0.311381\natom 11.78799 4.99460 0.01902 S 0.0 0.0 0.873595 0.681268 0.337014\natom 12.15741 1.15010 0.35007 S 0.0 0.0 -0.533612 -0.776279 0.057191\natom 0.21000 6.72252 6.13407 S 0.0 0.0 0.050020 0.620973 -0.365571\natom -2.81709 10.91384 12.20682 S 0.0 0.0 0.804004 -0.174437 -0.129138\natom 9.01094 4.82929 6.42686 S 0.0 0.0 0.290862 0.045045 -0.468485\natom 3.52205 0.72389 7.42145 S 0.0 0.0 -0.706904 0.747540 0.274162\natom 2.77862 6.94939 11.04289 S 0.0 0.0 0.696009 0.196816 -1.191073\natom 5.69056 11.08645 4.73966 S 0.0 0.0 1.228142 -0.081054 0.284577\natom 6.10330 4.86873 1.26284 S 0.0 0.0 -0.348331 0.574917 0.823367\natom 6.48304 0.87752 1.20088 S 0.0 0.0 -1.205732 -0.362291 -0.851227\natom 5.92901 6.66692 5.13927 S 0.0 0.0 0.547833 0.519141 -0.525032\natom 3.07500 11.16805 11.17593 S 0.0 0.0 -0.212242 -0.190401 0.271072\natom 3.16284 5.16247 7.09927 S 0.0 0.0 0.588442 -0.756420 0.612938\natom 0.03720 0.67302 9.60886 S 0.0 0.0 0.314782 0.360945 0.404808\natom 6.36915 7.02952 8.99250 S 0.0 0.0 -0.007432 0.203433 -0.383531\natom 9.53633 10.91032 3.10898 S 0.0 0.0 -0.378398 0.163635 -0.149693\natom 3.25425 4.97004 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0.426950 -1.191887\natom 9.06005 8.90682 6.36594 S 0.0 0.0 0.486279 -0.637644 -1.151151\natom -2.57506 2.76632 11.81978 S 0.0 0.0 -0.503384 0.777826 0.249587\natom 0.25132 3.12716 1.48115 S 0.0 0.0 -0.608301 0.109693 0.098321\natom 12.32916 8.79573 4.13935 S 0.0 0.0 -0.474549 0.731131 1.726422\natom 9.27795 9.47557 10.55517 S 0.0 0.0 -0.338265 -0.093140 0.046796\natom -3.15825 2.63234 7.82168 S 0.0 0.0 0.021963 -0.095534 -0.521092\natom 11.34384 2.78908 3.49134 Cu 0.0 0.0 0.266402 0.203551 0.017728\natom 0.47052 9.09979 2.61623 Cu 0.0 0.0 0.054596 -0.163264 -0.200579\natom -2.32029 8.85643 8.46865 Cu 0.0 0.0 0.117873 -0.638327 0.121556\natom 8.49454 3.25681 10.00919 Cu 0.0 0.0 0.300843 -0.311172 -0.223946\natom 5.45084 1.27657 8.42583 Cu 0.0 0.0 0.615805 0.295081 0.036292\natom 0.82063 6.87439 9.97517 Cu 0.0 0.0 -0.278155 -0.090576 -0.276165\natom 3.81072 10.79548 3.67498 Cu 0.0 0.0 -0.716326 0.710999 -0.232144\natom 7.92842 4.97030 2.53819 Cu 0.0 0.0 0.582939 -0.122379 0.115492\natom 8.38814 0.81594 2.05597 Cu 0.0 0.0 1.087838 -0.069441 0.729638\natom 4.02764 7.41026 4.45263 Cu 0.0 0.0 -0.375365 0.294501 -0.662878\natom 1.09170 10.70841 10.12471 Cu 0.0 0.0 -0.096600 -0.101774 -0.010295\natom 5.29100 5.16403 8.07640 Cu 0.0 0.0 -0.083630 -0.100913 0.265753\natom 5.41270 2.75931 0.72858 Cu 0.0 0.0 -0.029070 -0.044443 0.283989\natom 7.16192 9.32876 5.24564 Cu 0.0 0.0 -0.205326 -0.106932 0.193270\natom 4.25522 9.22371 11.54870 Cu 0.0 0.0 -0.110040 0.003881 -0.279273\natom 2.46996 2.86206 6.92385 Cu 0.0 0.0 -0.437845 0.058486 -0.186360\natom -3.69824 0.93079 11.51239 Cu 0.0 0.0 -0.528848 -0.553449 -0.476950\natom 8.18162 7.24408 7.58625 Cu 0.0 0.0 -0.066860 -0.017268 -0.020829\natom 13.01532 11.05932 0.49142 Cu 0.0 0.0 0.193724 -0.171706 0.316688\natom -0.43528 4.76027 5.25475 Cu 0.0 0.0 -0.014576 -0.355329 -0.064321\natom -0.91878 0.67847 5.48290 Cu 0.0 0.0 -0.285952 0.149133 -0.267101\natom 13.42130 6.64028 0.35803 Cu 0.0 0.0 0.077954 0.188468 0.565580\natom 10.55055 11.38916 6.88428 Cu 0.0 0.0 -0.183498 0.144817 -0.245487\natom -3.36792 4.81748 11.17599 Cu 0.0 0.0 -0.543630 -0.230396 0.405871\natom 8.21425 1.65171 12.19874 Cu 0.0 0.0 0.643216 -0.192794 -0.201816\natom 11.80791 6.92370 5.31055 Cu 0.0 0.0 0.253792 0.084301 0.386113\natom -5.08359 10.78705 12.13169 Cu 0.0 0.0 -0.287906 -0.201018 0.252104\natom 11.31575 4.59021 6.09702 Cu 0.0 0.0 -0.367090 -0.498877 0.099718\natom 11.47516 1.68583 5.88820 Cu 0.0 0.0 -0.069929 -0.086020 -0.247185\natom -5.44689 7.82624 11.94118 Cu 0.0 0.0 -0.149588 -0.247335 0.340774\natom -2.18526 9.88681 6.08793 Cu 0.0 0.0 0.088100 -0.104267 -0.641500\natom 14.08306 4.12963 0.16499 Cu 0.0 0.0 -0.114203 0.641912 0.116931\natom 9.29780 3.00009 4.99117 Cu 0.0 0.0 -0.027990 0.079308 0.087680\natom 2.69882 8.77207 0.78791 Cu 0.0 0.0 -0.043134 1.043673 0.739696\natom 0.17794 8.95078 6.89682 Cu 0.0 0.0 -0.516005 -0.436177 0.460935\natom 6.06030 3.02882 11.17722 Cu 0.0 0.0 0.021239 -0.557262 -0.148721\natom 1.33702 1.70640 11.35346 Cu 0.0 0.0 -0.173388 0.140541 -0.189028\natom 5.11245 7.74479 6.93217 Cu 0.0 0.0 0.421601 0.056960 0.113577\natom 8.24396 10.34956 1.21142 Cu 0.0 0.0 0.182989 -0.305282 -0.034122\natom 4.38653 4.15265 5.40633 Cu 0.0 0.0 -0.153409 0.294314 0.143012\natom 3.90180 1.60979 5.13212 Cu 0.0 0.0 0.121887 -0.408556 -0.086019\natom 8.56950 7.30516 0.96892 Cu 0.0 0.0 -0.348738 0.297050 0.376032\natom 5.95239 10.92008 7.04416 Cu 0.0 0.0 -0.295917 -0.246031 -0.626765\natom 0.88052 4.37533 11.53395 Cu 0.0 0.0 0.226771 -0.072623 -0.840530\natom -1.01699 2.80331 10.20025 Cu 0.0 0.0 0.586820 -0.568188 0.271337\natom 8.45376 10.06381 8.04991 Cu 0.0 0.0 -0.608008 0.349645 0.594028\natom 10.91943 8.19009 1.63815 Cu 0.0 0.0 -0.622651 -0.182141 0.406856\natom 2.17443 3.29759 4.35635 Cu 0.0 0.0 -0.666198 -0.221666 0.294757\natom 8.76230 0.53596 8.40783 Cu 0.0 0.0 0.255561 0.533831 0.132131\natom -2.19473 6.61348 9.84131 Cu 0.0 0.0 0.082533 0.222275 -0.441892\natom 0.74102 11.61955 3.75073 Cu 0.0 0.0 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0.523397\natom 4.20116 7.26377 4.16271 Cu 0.0 0.0 -0.438788 -0.146050 -0.310512\natom 0.95089 10.93709 10.32815 Cu 0.0 0.0 -0.102930 -0.257076 -0.218507\natom 5.43512 4.81066 8.45901 Cu 0.0 0.0 0.165254 -0.469123 0.015637\natom 5.03306 3.05532 0.73324 Cu 0.0 0.0 -0.271601 -0.365026 0.196978\natom 7.01767 9.05103 5.31687 Cu 0.0 0.0 -0.284260 0.056308 -0.397343\natom 4.26988 9.13160 11.55232 Cu 0.0 0.0 0.084051 0.019160 -0.104325\natom 2.25333 3.25087 7.22689 Cu 0.0 0.0 -0.136874 -0.592799 -0.209411\natom -3.50126 1.01997 11.01735 Cu 0.0 0.0 -0.612945 0.433497 0.228423\natom 10.08787 6.90286 6.96913 Cu 0.0 0.0 0.142625 0.095945 0.153444\natom 12.97211 10.66945 1.05195 Cu 0.0 0.0 0.244472 -0.012246 -0.226987\natom -0.67878 5.07409 4.97391 Cu 0.0 0.0 -0.286554 0.451790 -0.405286\natom -0.30644 1.09064 5.65606 Cu 0.0 0.0 -0.517726 0.391980 -0.187947\natom 13.47505 6.68267 0.61362 Cu 0.0 0.0 -0.176660 -0.037461 -0.146618\natom 10.10439 10.90559 7.08669 Cu 0.0 0.0 -0.393993 -0.296026 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11.42114 5.38310 1.94298 Cu 0.0 0.0 0.075951 0.425932 1.041462\natom 10.70567 1.00731 1.84688 Cu 0.0 0.0 0.223407 0.460631 0.647478\natom 1.90497 6.05672 4.77712 Cu 0.0 0.0 -0.259846 0.014966 -0.403398\natom -1.65585 11.68537 10.50567 Cu 0.0 0.0 0.268929 -0.707850 0.123446\natom 7.82215 5.48886 7.69180 Cu 0.0 0.0 0.380108 -0.177917 -0.130356\natom -4.42527 2.91274 9.64339 Cu 0.0 0.0 0.418973 0.370299 -0.445789\natom -4.19924 8.09144 9.57067 Cu 0.0 0.0 -0.260352 0.155246 -0.281942\natom -1.54616 9.88953 3.13799 Cu 0.0 0.0 0.349213 -0.120284 0.223816\natom 13.83430 3.84871 2.76269 Cu 0.0 0.0 -0.691911 0.450026 0.830477\natom 6.00171 1.13082 3.73239 Cu 0.0 0.0 0.098110 -0.566170 0.492193\natom 6.36143 6.95491 2.47509 Cu 0.0 0.0 -0.083912 0.125975 0.453908\natom 3.32728 11.29262 8.98225 Cu 0.0 0.0 -0.620479 -0.387307 -0.143286\natom 3.21657 5.03458 9.89750 Cu 0.0 0.0 -0.274916 -0.619830 -0.546933\natom 0.82229 0.13098 7.69079 Cu 0.0 0.0 0.438388 0.346984 0.670891\natom 5.09347 6.53680 10.60139 Cu 0.0 0.0 0.337538 -0.049954 0.164278\natom 8.21358 11.66913 4.51337 Cu 0.0 0.0 -0.343163 -0.056985 -0.025961\natom 3.93413 6.02726 1.59945 Cu 0.0 0.0 0.489399 0.526914 -0.814016\natom 3.94376 0.70044 1.63113 Cu 0.0 0.0 -0.123210 -0.302805 0.182278\natom 8.75881 7.34042 4.59194 Cu 0.0 0.0 0.209668 -0.195761 -0.054017\natom 5.20963 11.49503 10.49665 Cu 0.0 0.0 0.128236 -0.088421 0.002172\natom 0.79096 5.24340 7.74830 Cu 0.0 0.0 -0.269998 -0.047888 0.903317\natom 4.01411 2.54816 9.34197 Cu 0.0 0.0 0.007589 0.071441 -0.217994\natom 2.93521 8.60930 9.25798 Cu 0.0 0.0 0.151766 0.215699 -0.252560\natom 6.29266 9.50900 2.96155 Cu 0.0 0.0 -0.310873 0.377971 0.158102\natom 6.62111 3.10464 2.68527 Cu 0.0 0.0 0.171896 0.983184 0.487710\natom 13.39829 1.22636 2.24611 Cu 0.0 0.0 0.050971 0.059745 0.260887\natom 13.86998 7.31557 3.08116 Cu 0.0 0.0 0.471160 -0.357974 -0.191337\natom -4.30255 11.00313 9.50116 Cu 0.0 0.0 -0.049573 -0.211658 0.053019\natom -4.30044 5.52854 8.80646 Cu 0.0 0.0 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0.324178\natom 5.88982 0.73452 8.63276 Cu 0.0 0.0 -0.622485 -0.563224 -0.142045\natom 0.79752 6.86381 9.84725 Cu 0.0 0.0 0.682134 1.102318 0.258538\natom 4.15518 11.26781 4.05532 Cu 0.0 0.0 -0.382752 -0.335446 -0.523601\natom 8.43879 5.18875 2.01899 Cu 0.0 0.0 -0.521069 0.080386 0.227965\natom 8.23032 1.51809 2.02800 Cu 0.0 0.0 0.274933 -0.217530 0.080775\natom 4.09179 7.31485 3.81976 Cu 0.0 0.0 -0.350764 0.394703 -0.175752\natom 1.07376 10.90111 9.98153 Cu 0.0 0.0 -0.398227 -0.048638 0.093686\natom 5.46699 4.73378 8.28133 Cu 0.0 0.0 -0.087166 0.211269 -0.358015\natom 5.16720 2.84364 1.19692 Cu 0.0 0.0 0.046259 0.201715 -0.356204\natom 7.16256 9.03567 5.16722 Cu 0.0 0.0 -0.218735 -0.396738 -0.260383\natom 3.73656 9.21724 11.57400 Cu 0.0 0.0 0.334667 0.231045 0.028330\natom 2.33159 3.06921 6.86393 Cu 0.0 0.0 -0.133697 -0.171327 0.450428\natom -3.81102 0.80098 11.52015 Cu 0.0 0.0 0.173927 0.663246 0.047117\natom 10.05517 6.74784 6.76599 Cu 0.0 0.0 0.235281 0.287885 0.196644\natom 13.08403 11.03620 1.03971 Cu 0.0 0.0 -1.762495 -0.456507 -0.716181\natom -0.63174 5.30808 5.10175 Cu 0.0 0.0 0.241826 -0.041153 0.295433\natom -0.64372 1.03701 5.29732 Cu 0.0 0.0 -0.257431 0.740593 0.440301\natom 13.51339 7.39384 1.00709 Cu 0.0 0.0 0.370298 -0.324317 -0.371142\natom 9.83696 11.03363 6.64159 Cu 0.0 0.0 0.439562 0.005226 0.322419\natom -3.97699 4.81529 11.90457 Cu 0.0 0.0 -0.165398 0.076871 -0.316354\natom 15.10523 0.97018 0.45335 Cu 0.0 0.0 0.108855 0.349277 -0.195362\natom -1.87717 7.59875 5.94873 Cu 0.0 0.0 0.139248 -0.584412 0.412171\natom 0.81659 10.83165 0.01596 Cu 0.0 0.0 0.517358 -0.674483 -0.194676\natom 11.26107 4.24369 6.09709 Cu 0.0 0.0 -0.162982 0.508744 0.077368\natom 11.60629 1.86990 6.11246 Cu 0.0 0.0 -0.307392 -0.501398 0.118571\natom -4.97881 7.54115 12.09636 Cu 0.0 0.0 -0.056304 -0.017572 -0.326777\natom -1.92231 10.89385 5.82448 Cu 0.0 0.0 0.073982 -0.083700 0.204187\natom 14.72874 4.60296 0.15773 Cu 0.0 0.0 -0.332554 0.302974 -0.483146\natom 9.29036 2.46552 4.42771 Cu 0.0 0.0 -0.188209 -0.209773 0.685848\natom 2.84329 9.02647 0.89470 Cu 0.0 0.0 0.371717 0.515513 -0.026191\natom -0.34393 9.17943 7.03999 Cu 0.0 0.0 0.471892 0.582224 -0.019573\natom 5.33064 3.56966 10.70737 Cu 0.0 0.0 -0.399926 0.130172 0.596025\natom 1.05972 2.11438 10.15431 Cu 0.0 0.0 -0.718098 -0.330092 -0.354223\natom 5.10288 8.07193 6.44549 Cu 0.0 0.0 0.132556 -0.656152 -0.222280\natom 8.23428 10.62487 1.00344 Cu 0.0 0.0 -0.383120 -0.348728 0.290531\natom 4.26793 4.03251 5.37922 Cu 0.0 0.0 0.173414 0.401816 0.140236\natom 3.88090 1.48691 5.09628 Cu 0.0 0.0 0.446610 0.451931 1.046696\natom 8.68604 7.43322 0.82228 Cu 0.0 0.0 -0.057976 0.051102 0.148079\natom 5.80908 10.29903 7.15036 Cu 0.0 0.0 0.017333 0.468693 0.113093\natom 0.58906 4.28541 11.67626 Cu 0.0 0.0 0.123722 0.167641 -0.252301\natom -2.22381 3.92945 10.06964 Cu 0.0 0.0 -0.176000 -0.517677 -0.037408\natom 8.52022 8.06816 8.42355 Cu 0.0 0.0 -0.539787 -0.009521 0.329340\natom 9.41015 9.06777 2.70081 Cu 0.0 0.0 0.003757 -0.144894 -0.127005\natom 2.04981 3.35501 4.39939 Cu 0.0 0.0 -0.306911 -0.136632 -0.331552\natom 8.46391 0.56332 8.53779 Cu 0.0 0.0 0.014234 -0.209744 -0.187799\natom -2.49925 6.32074 10.02140 Cu 0.0 0.0 0.114758 0.672497 0.111257\natom 0.66349 11.72804 3.80601 Cu 0.0 0.0 0.331794 -0.575369 -0.504069\natom 11.97605 5.53404 2.21191 Cu 0.0 0.0 0.023685 0.114533 0.475695\natom 10.95036 0.51499 1.84102 Cu 0.0 0.0 -0.005119 -0.038255 -0.300475\natom 1.47037 6.98637 4.14054 Cu 0.0 0.0 0.246226 -0.107223 -0.710336\natom -1.63433 10.92061 10.35736 Cu 0.0 0.0 0.104327 -0.093011 -0.381544\natom 8.06348 5.42901 7.94802 Cu 0.0 0.0 -0.201098 0.049119 -0.220587\natom -4.31809 2.29518 9.61272 Cu 0.0 0.0 -0.010356 0.290214 -0.453399\natom 10.82460 7.85769 9.26637 Cu 0.0 0.0 0.323123 -0.313607 -0.222887\natom 12.08219 8.80475 2.52277 Cu 0.0 0.0 -0.055283 0.015678 -0.608081\natom -1.41413 3.87069 3.06677 Cu 0.0 0.0 -0.673074 0.284088 0.558807\natom 5.94795 1.11352 3.38936 Cu 0.0 0.0 0.159578 -0.547441 0.000765\natom 6.45330 7.15467 2.31140 Cu 0.0 0.0 -0.057220 -0.071145 0.332183\natom 3.26794 11.07258 8.78709 Cu 0.0 0.0 0.603739 0.295476 0.252979\natom 3.38345 5.06937 9.65509 Cu 0.0 0.0 -0.350459 -0.013806 0.127865\natom 1.44722 0.51259 7.96815 Cu 0.0 0.0 0.137348 0.343267 -0.463857\natom 5.54977 6.23703 10.56869 Cu 0.0 0.0 -0.237339 -0.018620 0.327488\natom 8.33384 12.02725 4.82294 Cu 0.0 0.0 -0.280141 0.179797 -0.112280\natom 3.74750 5.38033 1.62662 Cu 0.0 0.0 0.703834 0.182198 -1.483773\natom 4.05177 0.74929 1.84785 Cu 0.0 0.0 -0.041559 -0.597855 -0.356890\natom 8.65400 7.10522 4.38060 Cu 0.0 0.0 -0.342721 -0.028593 0.445403\natom 5.77761 11.34882 10.89133 Cu 0.0 0.0 -0.110803 -0.052958 -0.260191\natom 0.45203 5.53726 7.66699 Cu 0.0 0.0 0.152501 -0.023085 -0.424709\natom 3.37939 2.52818 9.24746 Cu 0.0 0.0 0.177407 -0.421363 -0.533103\natom 2.84552 8.72925 9.26239 Cu 0.0 0.0 -0.076708 -0.424983 0.014802\natom 5.98490 9.64966 2.72209 Cu 0.0 0.0 0.343133 0.019114 0.185854\natom 6.72647 3.36344 3.13401 Cu 0.0 0.0 0.076229 0.649473 -0.191995\natom 13.43144 1.17425 2.35847 Cu 0.0 0.0 -0.024154 0.484279 -0.278269\natom -1.33140 7.29165 3.46685 Cu 0.0 0.0 -0.005651 0.021867 -0.144259\natom -4.56035 10.74940 9.82563 Cu 0.0 0.0 0.079017 -0.091598 -0.327849\natom 11.18471 5.03689 8.54341 Cu 0.0 0.0 -0.178459 -0.385846 0.399103\natom 3.76512 1.21307 11.84350 Cu 0.0 0.0 0.225466 0.873535 -0.175913\natom 2.73076 7.20423 7.16718 Cu 0.0 0.0 -0.256518 0.430094 -0.124481\natom 5.50669 10.83828 0.49333 Cu 0.0 0.0 0.784932 -0.382042 0.233489\natom 6.87650 4.79090 5.21529 Cu 0.0 0.0 -0.314584 0.323137 0.060103\natom 7.96189 2.92785 7.30116 Cu 0.0 0.0 -0.044054 0.067920 -0.437947\natom -1.16153 8.18641 11.26996 Cu 0.0 0.0 0.297148 0.206065 -0.040745\natom 1.84239 9.63947 5.13552 Cu 0.0 0.0 -0.125355 0.243608 0.284855\natom 11.47668 2.95602 1.20412 Cu 0.0 0.0 0.043196 0.128106 -0.338968\natom 2.24530 2.58721 1.67052 Cu 0.0 0.0 -0.205593 0.029137 0.373175\natom 10.62441 8.88619 4.88068 Cu 0.0 0.0 -1.307493 -0.356001 0.820718\natom 7.20227 9.21429 10.96714 Cu 0.0 0.0 1.033546 0.128614 -0.900206\natom -0.50952 2.99767 8.13693 Cu 0.0 0.0 0.352371 0.136043 -0.042488\natom -2.52217 0.89947 8.28566 Cu 0.0 0.0 -0.367935 -0.888869 -0.183422\natom 8.07793 6.37133 10.22021 Cu 0.0 0.0 0.262309 -0.134192 0.317673\natom 11.51480 11.05542 3.77604 Cu 0.0 0.0 0.217547 0.093776 0.155530\natom 1.04284 4.86593 2.32444 Cu 0.0 0.0 0.409966 -0.257020 0.289949\nenergy -565.869365\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_364\nlattice 15.407895943 0.000000000 0.000000000\nlattice 0.000000000 12.010195158 0.000000000\nlattice -6.052957620 0.000000000 12.220369325\natom 9.90969 0.88005 10.22538 S 0.0 0.0 0.061660 0.067318 -0.013678\natom -3.37387 6.88266 7.97768 S 0.0 0.0 0.671599 -0.033925 -0.217290\natom -0.07517 11.00717 1.84789 S 0.0 0.0 -0.796247 -0.842819 -0.270703\natom 12.83106 5.03137 4.29282 S 0.0 0.0 -0.156444 0.375730 -1.205419\natom 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7.78762 S 0.0 0.0 0.307424 0.468046 -0.003713\natom 11.73155 2.72999 3.65429 Cu 0.0 0.0 -0.205403 0.640337 -0.151061\natom 0.66613 8.60344 2.43088 Cu 0.0 0.0 0.355992 -0.185770 -0.193305\natom -2.29146 9.07539 8.56173 Cu 0.0 0.0 -0.042250 -0.301201 0.203443\natom 8.80854 2.86845 9.60856 Cu 0.0 0.0 -0.320755 -0.172987 0.168747\natom 5.30302 0.86141 8.63190 Cu 0.0 0.0 -0.108091 0.111894 -0.000144\natom 0.76235 6.97487 10.00323 Cu 0.0 0.0 0.193386 0.458556 0.543800\natom 3.73917 11.16368 3.99209 Cu 0.0 0.0 0.098091 -0.299638 -0.050441\natom 8.67336 4.89055 2.05390 Cu 0.0 0.0 -0.160631 -0.313052 -0.310123\natom 8.64053 1.22491 1.89864 Cu 0.0 0.0 -0.531404 -0.329692 0.082656\natom 3.87060 7.15001 3.98688 Cu 0.0 0.0 0.343764 -0.245635 0.192519\natom 0.86747 10.99916 10.12815 Cu 0.0 0.0 0.553844 0.504072 -0.015565\natom 5.37338 4.54608 7.96600 Cu 0.0 0.0 -0.790988 0.612881 0.188971\natom 5.30235 2.96679 0.74196 Cu 0.0 0.0 -0.279765 0.053589 0.061152\natom 7.17235 8.95634 5.48649 Cu 0.0 0.0 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0.229835\natom 5.98003 10.54222 7.01848 Cu 0.0 0.0 -0.268979 0.613439 -0.609902\natom 0.90330 4.52668 11.09130 Cu 0.0 0.0 -0.015860 -0.009756 0.061747\natom -1.32816 3.08064 10.41773 Cu 0.0 0.0 -0.493890 -0.065188 0.008047\natom 9.10624 9.49641 8.40497 Cu 0.0 0.0 -0.542911 -0.259645 -0.523702\natom 10.54298 9.22840 1.73106 Cu 0.0 0.0 0.204844 -0.051950 0.245926\natom 1.86215 3.19365 4.41637 Cu 0.0 0.0 -0.141626 0.355328 -0.128984\natom 8.65817 0.51941 8.36583 Cu 0.0 0.0 -0.022819 -0.077019 -0.417244\natom -2.29063 6.73982 10.04842 Cu 0.0 0.0 -0.249279 0.046797 0.036677\natom 0.78869 11.47440 3.73836 Cu 0.0 0.0 0.042456 0.785562 0.690769\natom 11.47010 5.64750 2.12577 Cu 0.0 0.0 0.841797 -0.701578 -0.310140\natom 11.01177 0.57843 1.86130 Cu 0.0 0.0 0.197024 -0.015556 -0.043231\natom 1.22968 6.56272 4.18906 Cu 0.0 0.0 0.397033 0.185775 -0.533834\natom -1.52602 10.80217 10.42185 Cu 0.0 0.0 0.048520 -0.018238 -0.396147\natom 7.92076 4.83320 8.23419 Cu 0.0 0.0 -0.018300 0.409796 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0.052221 -0.147774\natom -2.92174 3.34768 11.88610 S 0.0 0.0 0.050199 0.007954 0.053206\natom -0.01405 3.10105 1.74874 S 0.0 0.0 -1.256553 -0.991026 -0.911636\natom 12.54325 8.73734 4.60141 S 0.0 0.0 -0.668099 0.095902 0.446299\natom 9.62451 9.13033 10.77019 S 0.0 0.0 -0.951899 -0.199389 -1.096222\natom -3.10511 3.22896 7.68996 S 0.0 0.0 -0.191980 0.090752 0.181160\natom 11.71159 3.05493 3.42301 Cu 0.0 0.0 -0.614346 -0.362901 0.023987\natom 0.79889 9.09650 2.66785 Cu 0.0 0.0 0.238005 -0.467958 0.174566\natom -2.08133 8.83859 8.65215 Cu 0.0 0.0 -0.179033 0.047382 0.078499\natom 8.38345 2.76307 9.68602 Cu 0.0 0.0 0.229534 0.245422 0.262122\natom 5.54077 0.71040 7.81966 Cu 0.0 0.0 -0.543723 0.104156 0.062864\natom 0.99210 6.95531 9.77437 Cu 0.0 0.0 -0.602864 0.096841 -0.245447\natom 4.20764 11.27650 3.97750 Cu 0.0 0.0 -0.278442 -0.155795 -0.117456\natom 8.13159 5.19745 2.25772 Cu 0.0 0.0 0.413031 0.147334 -0.261297\natom 8.36442 1.04172 2.16453 Cu 0.0 0.0 0.107403 0.359153 0.029200\natom 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5.16669 11.07826 Cu 0.0 0.0 0.068204 0.464504 0.580785\natom 14.40140 1.55724 0.07078 Cu 0.0 0.0 -0.175878 0.077724 -0.485831\natom 12.39439 6.48209 5.81842 Cu 0.0 0.0 -0.038046 -0.033224 -0.289350\natom 1.04454 10.25970 0.33599 Cu 0.0 0.0 0.362430 0.420358 0.063403\natom 11.23577 4.09764 5.81212 Cu 0.0 0.0 0.196093 0.306465 0.077735\natom 11.34717 1.45856 5.99899 Cu 0.0 0.0 -0.229240 0.458238 0.843086\natom -4.88353 7.68744 12.16439 Cu 0.0 0.0 0.051403 -0.373407 0.449964\natom -2.41629 11.10057 5.98287 Cu 0.0 0.0 -0.056673 -0.124752 -0.355872\natom 14.06539 4.26781 0.26329 Cu 0.0 0.0 0.564317 -0.090832 -0.077447\natom 9.07661 3.06429 4.99900 Cu 0.0 0.0 0.095513 -0.073796 -0.030946\natom 3.26713 9.15368 1.12967 Cu 0.0 0.0 -0.131499 -0.290807 -0.245339\natom -0.75901 9.07992 5.52474 Cu 0.0 0.0 0.102919 0.030057 0.034120\natom 6.22595 3.07567 11.14685 Cu 0.0 0.0 -0.035081 -0.198247 0.345145\natom 1.04384 1.46412 11.32789 Cu 0.0 0.0 0.052973 0.431111 0.163237\natom 5.40090 7.63747 6.67094 Cu 0.0 0.0 -0.331470 0.252398 0.495228\natom 8.19074 10.20427 0.59092 Cu 0.0 0.0 0.040328 -0.185457 0.244075\natom 4.33223 4.14579 5.18777 Cu 0.0 0.0 0.336363 -0.551805 0.367652\natom 3.73865 1.60189 5.41475 Cu 0.0 0.0 -0.207445 -0.174537 -0.155598\natom 8.32237 7.46590 0.77550 Cu 0.0 0.0 0.261253 0.027276 0.048673\natom 5.56080 10.18706 6.52803 Cu 0.0 0.0 -0.120393 0.271156 0.429619\natom 0.90273 4.27241 11.65507 Cu 0.0 0.0 -0.421922 0.020559 0.088453\natom -1.32779 2.49177 10.47752 Cu 0.0 0.0 -0.066978 -0.009727 -0.291503\natom 7.50996 9.04857 7.85521 Cu 0.0 0.0 -0.114700 -0.644251 -0.023218\natom 10.73365 9.18162 1.73432 Cu 0.0 0.0 -0.426919 -0.210149 0.411827\natom 1.68706 3.88963 4.75733 Cu 0.0 0.0 0.421421 0.255337 -0.128322\natom 8.90235 0.55317 8.27384 Cu 0.0 0.0 -0.356851 0.199562 0.968593\natom -1.91232 6.50406 9.88035 Cu 0.0 0.0 -0.013697 -0.067394 0.369268\natom 0.70885 11.72524 3.95941 Cu 0.0 0.0 0.192362 0.149447 -0.950886\natom 11.46683 5.56791 2.08637 Cu 0.0 0.0 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7.57952 Cu 0.0 0.0 0.753475 0.611000 -0.355301\natom 3.52075 1.97610 9.25572 Cu 0.0 0.0 0.112054 -0.426083 -0.762882\natom 3.26902 8.05342 9.03638 Cu 0.0 0.0 -0.157608 -0.565383 0.382513\natom 6.24172 9.98896 2.84463 Cu 0.0 0.0 0.003933 -0.138988 0.313051\natom 6.43948 3.61142 3.09045 Cu 0.0 0.0 -0.060870 -0.031435 0.141111\natom 13.69400 1.53934 2.62912 Cu 0.0 0.0 0.335950 0.186153 0.053134\natom 0.10282 6.95017 3.92907 Cu 0.0 0.0 -0.087201 -0.379768 0.513462\natom 10.27674 10.90234 9.71186 Cu 0.0 0.0 -0.130954 0.044084 0.051030\natom 10.78148 5.62170 8.62304 Cu 0.0 0.0 0.225660 0.075907 0.231229\natom 4.08450 0.96778 11.65065 Cu 0.0 0.0 -0.942692 0.584827 0.378703\natom 1.56751 8.44109 5.49639 Cu 0.0 0.0 0.776519 0.455451 -0.498322\natom 5.86360 11.00627 0.29875 Cu 0.0 0.0 -0.174387 0.309697 0.215419\natom 6.84270 4.79087 5.65818 Cu 0.0 0.0 -0.019140 -0.147352 -0.202036\natom 7.41095 2.15234 7.06265 Cu 0.0 0.0 -0.138064 0.659121 -0.120287\natom -1.56302 8.97419 11.56691 Cu 0.0 0.0 0.361844 0.152706 -0.183741\natom 2.20625 10.78629 6.56346 Cu 0.0 0.0 -0.261686 0.468924 0.098358\natom 10.28961 3.38087 0.70884 Cu 0.0 0.0 0.421617 0.194674 -0.807809\natom 2.22367 2.29936 1.67960 Cu 0.0 0.0 -0.265866 -0.257214 0.654316\natom 10.12344 8.73026 4.22911 Cu 0.0 0.0 -0.471823 -0.443444 -0.098388\natom 7.02590 9.64543 10.80660 Cu 0.0 0.0 0.328841 0.093988 -0.529030\natom -0.68291 3.58552 7.68339 Cu 0.0 0.0 -0.634678 -1.092178 -0.209949\natom -2.35594 1.09296 8.02549 Cu 0.0 0.0 0.171107 0.496459 -0.079950\natom 8.94965 6.92338 10.11464 Cu 0.0 0.0 -0.154993 0.167321 -0.101779\natom 11.47675 11.01482 3.68364 Cu 0.0 0.0 -1.272556 0.754215 -0.569692\natom 1.03833 4.85681 2.68082 Cu 0.0 0.0 0.647871 0.231656 -0.088701\nenergy -565.510497\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_52\nlattice 15.452772050 0.000000000 0.000000000\nlattice 0.000000000 12.045175328 0.000000000\nlattice -6.070587099 0.000000000 12.255961635\natom 9.68829 0.88849 10.39469 S 0.0 0.0 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-0.315783 -0.830057\natom -0.27492 2.93000 1.65662 S 0.0 0.0 1.317144 -0.472014 -1.478939\natom 12.70682 8.83360 4.38230 S 0.0 0.0 -0.314408 0.423262 0.566147\natom 9.55891 8.83086 10.81540 S 0.0 0.0 -0.632277 -0.260585 -0.656271\natom -3.13973 3.21023 7.57021 S 0.0 0.0 0.035096 -0.125648 0.261547\natom 11.67545 2.89950 3.60542 Cu 0.0 0.0 0.304505 -0.063909 0.234011\natom 1.05856 8.88570 2.64150 Cu 0.0 0.0 0.080229 -0.118842 -0.092864\natom -2.03469 9.25706 8.62281 Cu 0.0 0.0 -0.862891 0.167669 -0.411915\natom 8.48896 2.80002 9.97195 Cu 0.0 0.0 0.354960 0.225683 -0.303977\natom 5.45597 1.28499 8.47908 Cu 0.0 0.0 0.410477 0.205054 -0.304789\natom 1.05344 7.23415 10.04549 Cu 0.0 0.0 -0.163714 -0.542530 -0.155902\natom 4.27941 11.21374 3.88343 Cu 0.0 0.0 -0.222332 0.285825 -0.273272\natom 8.59142 5.23398 2.42178 Cu 0.0 0.0 -0.271659 -0.215243 -0.287463\natom 8.41791 1.16182 2.20372 Cu 0.0 0.0 -0.394520 -0.568841 -0.253266\natom 4.38860 7.53723 4.27049 Cu 0.0 0.0 -0.180703 0.028054 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0.507960\natom 8.34727 1.45761 12.13804 Cu 0.0 0.0 -0.243015 -0.063355 0.384000\natom -1.91304 7.87559 6.27224 Cu 0.0 0.0 0.182465 -0.125591 -0.042310\natom 1.22350 10.01820 0.09676 Cu 0.0 0.0 0.329541 0.496820 0.527121\natom 11.03890 4.23073 6.01320 Cu 0.0 0.0 0.292541 0.331663 -0.043652\natom 11.16626 1.63740 5.92045 Cu 0.0 0.0 0.082946 -0.262730 0.096357\natom 1.35930 7.49830 0.32093 Cu 0.0 0.0 0.515749 -0.127466 -0.306337\natom -0.85889 10.05124 5.32919 Cu 0.0 0.0 -1.065336 -0.557422 -0.438531\natom 14.30901 4.24465 0.08140 Cu 0.0 0.0 -0.109927 0.237845 -0.214746\natom 9.13306 2.95525 5.08939 Cu 0.0 0.0 -0.026585 0.633991 -0.361295\natom 3.35563 8.63970 1.52747 Cu 0.0 0.0 0.084884 -0.344084 -0.620736\natom 0.05199 10.35869 7.80543 Cu 0.0 0.0 0.069402 -0.307704 0.363921\natom 6.24559 2.85868 11.46795 Cu 0.0 0.0 -0.045526 0.210162 -0.045442\natom -0.90545 3.86279 7.69139 Cu 0.0 0.0 0.435370 0.040458 0.173097\natom 5.54793 7.73506 7.04433 Cu 0.0 0.0 -0.163665 -0.165320 -0.216939\natom 8.07550 10.08907 0.73957 Cu 0.0 0.0 0.274589 0.224532 -0.123789\natom 3.86209 3.99357 5.47504 Cu 0.0 0.0 0.713637 -0.120590 -0.371456\natom 3.71869 1.30131 5.20309 Cu 0.0 0.0 0.295541 0.532457 0.277208\natom 8.40070 7.55699 1.22324 Cu 0.0 0.0 0.918084 -0.017097 -0.172116\natom 5.46091 10.31389 6.88238 Cu 0.0 0.0 0.636379 0.305708 -0.274427\natom 7.51135 4.14117 0.07082 Cu 0.0 0.0 -0.806049 0.048342 0.411963\natom -0.51039 2.11068 12.19002 Cu 0.0 0.0 -0.204222 0.342347 -0.129231\natom 7.64971 8.80134 8.07465 Cu 0.0 0.0 0.024751 0.202055 -0.029493\natom 10.63996 9.17796 1.90314 Cu 0.0 0.0 -0.099927 -0.100229 -0.384760\natom 1.91044 3.03927 4.31101 Cu 0.0 0.0 -0.164463 -0.083120 -0.642104\natom 8.54230 0.59236 8.32153 Cu 0.0 0.0 0.100847 0.345645 -0.240471\natom -1.94652 6.36568 9.71590 Cu 0.0 0.0 -0.478626 0.132312 -0.016137\natom 0.70683 11.56552 3.80038 Cu 0.0 0.0 0.008461 -0.141396 -0.923532\natom 11.99474 5.27822 2.27860 Cu 0.0 0.0 -0.046479 -0.015532 -0.072183\natom 10.62870 0.31821 1.25739 Cu 0.0 0.0 -0.076343 -0.123905 0.577853\natom 1.70035 6.52242 4.52969 Cu 0.0 0.0 -0.279728 -0.075011 -0.557715\natom -3.24874 11.45552 9.69927 Cu 0.0 0.0 0.144854 -0.195696 0.557575\natom 7.73758 4.97325 7.80800 Cu 0.0 0.0 -0.044919 0.103196 0.649776\natom 10.96720 1.77377 8.69401 Cu 0.0 0.0 -0.300278 -0.312687 0.318857\natom 10.82361 8.87007 8.96418 Cu 0.0 0.0 0.231775 -0.245660 0.012344\natom 14.05468 9.39456 2.79846 Cu 0.0 0.0 0.039430 0.506389 -0.355454\natom -0.99274 3.66799 3.45835 Cu 0.0 0.0 -1.391409 -0.130586 1.244523\natom 5.85981 0.99793 3.45645 Cu 0.0 0.0 0.350906 -0.124246 -0.365691\natom 6.48697 6.99586 2.70234 Cu 0.0 0.0 -0.115451 -0.567635 0.286672\natom 2.93836 10.45460 9.06873 Cu 0.0 0.0 -0.020449 -0.147844 -0.074972\natom 2.87856 5.04724 9.79968 Cu 0.0 0.0 0.021081 0.802603 -0.883295\natom 1.29372 0.50868 8.19919 Cu 0.0 0.0 0.102742 0.247199 0.257831\natom 5.13997 6.95690 10.71659 Cu 0.0 0.0 0.318380 -0.429011 0.569694\natom 9.21189 11.04964 4.94144 Cu 0.0 0.0 -0.226220 0.047172 -0.338081\natom 4.17990 5.48315 1.65625 Cu 0.0 0.0 -0.061149 0.024759 0.018456\natom 4.10194 0.86935 1.46185 Cu 0.0 0.0 -0.325118 -0.356689 0.351853\natom 8.58370 6.73929 4.48938 Cu 0.0 0.0 -0.183253 0.073806 -0.336752\natom 5.26307 11.59673 10.20705 Cu 0.0 0.0 0.019433 -0.355420 0.226874\natom 1.13195 5.80679 7.86158 Cu 0.0 0.0 -0.111944 0.087901 -0.238204\natom 3.31937 2.27542 9.37690 Cu 0.0 0.0 -0.379342 0.001606 -0.305208\natom 3.34483 7.75485 9.18163 Cu 0.0 0.0 0.229823 0.791373 -1.131988\natom 6.39482 9.67667 3.15210 Cu 0.0 0.0 -0.094336 -0.795504 -1.057292\natom 7.22236 3.07618 3.37057 Cu 0.0 0.0 -0.235709 0.757783 -0.201253\natom 13.81610 1.37747 2.41015 Cu 0.0 0.0 -0.421134 -0.441437 0.596880\natom 13.61863 6.95911 3.36775 Cu 0.0 0.0 0.023890 -0.090556 0.088628\natom 9.66897 10.87854 9.80118 Cu 0.0 0.0 -0.033376 -0.779259 -0.024728\natom 10.82688 4.33130 8.82018 Cu 0.0 0.0 0.025061 0.077835 -0.093269\natom 0.52093 2.93256 9.86635 Cu 0.0 0.0 -0.188157 0.007009 0.046775\natom 3.05650 7.20429 6.37008 Cu 0.0 0.0 0.120817 0.632245 0.914727\natom 5.20021 10.41570 0.87518 Cu 0.0 0.0 -0.188866 0.673383 -0.290560\natom 6.42686 4.58096 5.63885 Cu 0.0 0.0 -0.033889 0.762947 -0.354041\natom 7.36790 2.66841 6.96813 Cu 0.0 0.0 -0.012373 -0.662690 0.449303\natom -1.75746 8.94560 11.22149 Cu 0.0 0.0 -0.054235 0.048564 0.114417\natom 1.59161 9.16276 5.19623 Cu 0.0 0.0 0.020031 -0.301564 0.165598\natom 10.50996 3.65139 0.92879 Cu 0.0 0.0 0.046307 0.222299 -0.224030\natom 2.01792 2.44696 1.65061 Cu 0.0 0.0 -0.342256 0.024552 0.104635\natom 10.30682 8.44864 4.52417 Cu 0.0 0.0 0.305590 0.465815 -0.017841\natom 7.37748 10.13132 10.55358 Cu 0.0 0.0 -0.193255 -0.757234 0.590322\natom -2.71285 3.62703 10.24934 Cu 0.0 0.0 0.527769 -0.745936 -0.242669\natom -2.00328 1.53124 8.67936 Cu 0.0 0.0 -0.218742 -0.112512 -0.294307\natom 8.67784 6.86853 9.57287 Cu 0.0 0.0 0.367175 0.005611 0.281933\natom 11.50050 10.89754 3.55966 Cu 0.0 0.0 0.489069 -0.022825 0.280065\natom 0.89763 4.90137 2.64962 Cu 0.0 0.0 -0.158200 0.447650 -0.491001\nenergy -565.862799\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_84\nlattice 15.394732161 0.000000000 0.000000000\nlattice 0.000000000 11.999934213 0.000000000\nlattice -6.047786257 0.000000000 12.209928816\natom 9.61168 1.01608 10.42083 S 0.0 0.0 -1.191961 0.326660 -1.181596\natom -3.21463 7.13012 7.92824 S 0.0 0.0 0.049036 -0.759072 0.181961\natom -0.42418 11.01723 1.89660 S 0.0 0.0 0.333188 0.647869 -0.641060\natom 12.57968 4.81260 4.21805 S 0.0 0.0 -0.689337 0.705370 -0.234277\natom 12.37573 0.60830 4.48839 S 0.0 0.0 0.095115 0.347347 -0.081025\natom -0.23392 7.11563 2.18372 S 0.0 0.0 0.321971 -0.092889 -0.125810\natom -3.13570 10.97664 7.97003 S 0.0 0.0 -0.416872 0.419920 0.025070\natom 9.30709 5.19093 10.26152 S 0.0 0.0 -0.754127 -0.201431 -0.317495\natom 9.13516 1.37154 6.38042 S 0.0 0.0 -1.096006 -0.210231 0.119114\natom -2.70337 6.66340 12.17485 S 0.0 0.0 -0.157448 -0.296626 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1.08496 9.38773 S 0.0 0.0 0.075403 -0.259372 -0.621188\natom 6.34054 6.96441 8.61398 S 0.0 0.0 0.402595 -0.723001 0.756399\natom 9.44702 11.07522 2.60649 S 0.0 0.0 0.124143 -0.220298 0.690966\natom 2.72174 5.30293 3.64982 S 0.0 0.0 0.266566 0.028388 -0.153975\natom 2.60106 0.99820 3.39868 S 0.0 0.0 0.133698 0.036970 0.506408\natom 9.67221 7.04953 2.66653 S 0.0 0.0 0.663083 0.216520 -0.406805\natom 6.55951 10.81941 8.71656 S 0.0 0.0 0.888808 -0.578877 0.126432\natom -0.43056 5.03803 9.41733 S 0.0 0.0 -0.875998 0.186108 0.476104\natom 6.23491 2.85458 9.12792 S 0.0 0.0 -0.171363 -0.175101 -0.393890\natom 0.26889 9.09982 9.39944 S 0.0 0.0 -0.960259 -0.011127 0.730988\natom 3.33550 9.12756 3.25851 S 0.0 0.0 -0.476551 0.507590 0.573442\natom 9.77520 2.96453 2.59647 S 0.0 0.0 -0.566787 -0.098178 0.053217\natom 5.79508 2.94445 5.16220 S 0.0 0.0 -0.192775 0.225588 -0.442090\natom 6.39349 8.80687 0.95628 S 0.0 0.0 0.536297 0.033054 0.478046\natom 3.57897 9.37915 7.30478 S 0.0 0.0 -0.089353 -0.299949 -0.470851\natom 2.54131 2.93520 10.85817 S 0.0 0.0 0.548588 0.635996 0.557775\natom 0.11490 2.58780 5.99619 S 0.0 0.0 -0.279109 0.432643 0.237834\natom 12.07420 8.66439 0.11760 S 0.0 0.0 0.137315 0.465733 -0.244200\natom 9.11578 9.42753 6.08890 S 0.0 0.0 0.085813 -0.380959 0.423167\natom -3.06738 3.08427 11.82586 S 0.0 0.0 -0.476050 0.444938 -0.035933\natom -0.16711 2.91929 1.70250 S 0.0 0.0 0.112141 -0.369133 0.403277\natom 12.70125 8.95407 4.51622 S 0.0 0.0 -0.614318 -0.276546 0.371311\natom 9.74225 8.92619 10.84282 S 0.0 0.0 -1.202930 0.042308 0.276779\natom -3.20438 3.20878 7.65061 S 0.0 0.0 -0.289725 0.255052 -0.043827\natom 11.61231 2.69652 3.80240 Cu 0.0 0.0 0.391770 -0.054206 -0.012242\natom 1.41467 9.00327 2.21273 Cu 0.0 0.0 -0.693663 -0.090294 0.140010\natom -2.02004 9.24063 8.95087 Cu 0.0 0.0 -0.002940 0.062471 -0.095837\natom 8.47278 3.04012 9.76366 Cu 0.0 0.0 0.100954 0.077138 -0.004811\natom 5.55379 0.69555 8.27037 Cu 0.0 0.0 -0.295086 0.648668 0.173849\natom 0.98887 6.80797 9.65854 Cu 0.0 0.0 0.315449 0.420092 0.858395\natom 3.98611 11.29356 4.10338 Cu 0.0 0.0 -0.059508 -0.194572 -0.276054\natom 8.64481 4.91039 2.26137 Cu 0.0 0.0 -0.328978 0.165652 0.435556\natom 8.75433 1.02416 1.86991 Cu 0.0 0.0 -0.162032 0.422745 0.038880\natom 4.00536 7.36720 4.38927 Cu 0.0 0.0 -0.419183 -0.459053 -0.186304\natom 0.88893 11.18860 10.19854 Cu 0.0 0.0 0.031607 0.013853 -0.013245\natom 5.40073 4.66855 8.09789 Cu 0.0 0.0 -0.310233 0.364814 0.004740\natom 4.87332 3.39932 0.69978 Cu 0.0 0.0 0.290394 -0.353057 0.154532\natom 7.09795 8.93120 5.14333 Cu 0.0 0.0 -0.138698 0.057681 -0.002073\natom 3.70509 9.16447 11.39834 Cu 0.0 0.0 0.437228 0.207239 0.318415\natom 2.14836 3.16801 6.88630 Cu 0.0 0.0 0.123592 0.057810 0.339965\natom -4.01817 0.82592 11.54874 Cu 0.0 0.0 1.075584 0.120868 0.176741\natom 9.89746 7.31258 6.48309 Cu 0.0 0.0 -0.066838 0.070502 0.539386\natom 12.83146 10.85639 0.92260 Cu 0.0 0.0 -0.084247 -1.064775 -0.010222\natom -0.85835 5.29316 5.27531 Cu 0.0 0.0 0.266740 0.088528 0.150937\natom -0.96231 0.67333 5.44880 Cu 0.0 0.0 -0.125972 -0.190869 -0.229224\natom 13.27310 6.79948 0.98173 Cu 0.0 0.0 0.313132 0.102051 -0.307492\natom 10.35055 11.21868 6.73618 Cu 0.0 0.0 -0.021537 0.094407 0.324178\natom -4.07327 5.24861 11.02907 Cu 0.0 0.0 0.502192 -0.418966 0.619331\natom 14.59142 1.31024 0.24868 Cu 0.0 0.0 -0.068794 0.045746 -0.445258\natom -1.74385 7.33635 6.30245 Cu 0.0 0.0 -0.103437 0.578930 -0.038327\natom -3.35489 8.70890 11.45086 Cu 0.0 0.0 -0.023471 0.541481 -0.089149\natom 11.31328 4.92819 6.00106 Cu 0.0 0.0 0.124277 -0.354520 0.331290\natom 11.25926 1.71899 6.14910 Cu 0.0 0.0 0.576058 0.153646 0.284591\natom 0.98756 7.18957 0.34767 Cu 0.0 0.0 0.148718 -0.153860 -0.137073\natom -1.89896 10.08005 6.27442 Cu 0.0 0.0 0.269953 0.252167 0.119336\natom 14.82866 4.39039 0.09180 Cu 0.0 0.0 -0.340573 0.056927 -0.147375\natom 8.87065 3.15774 4.77775 Cu 0.0 0.0 0.162618 -0.061351 -0.073613\natom 4.26291 8.24195 1.31598 Cu 0.0 0.0 -0.565867 -0.359922 0.446488\natom 0.22021 8.94420 7.17875 Cu 0.0 0.0 -0.009841 -0.048517 -0.177917\natom 6.40085 2.98501 11.36531 Cu 0.0 0.0 -0.043523 0.040280 0.578155\natom 0.68234 1.70256 11.28986 Cu 0.0 0.0 -0.186826 -0.000683 0.598754\natom 5.26580 7.81845 6.92142 Cu 0.0 0.0 -0.445676 0.563885 -0.652128\natom 7.95813 10.36362 0.83491 Cu 0.0 0.0 0.260321 0.279152 0.286081\natom 4.02707 4.53549 5.72216 Cu 0.0 0.0 0.303080 -0.344855 -0.551618\natom 4.88474 0.93701 5.70079 Cu 0.0 0.0 0.230608 -0.147864 0.000888\natom 8.40394 7.67556 0.92211 Cu 0.0 0.0 0.254484 -0.067652 -0.202682\natom 5.45731 10.49026 6.43732 Cu 0.0 0.0 -0.319092 -0.150872 0.710175\natom 1.92198 5.32701 11.97658 Cu 0.0 0.0 -0.166622 -0.121822 -0.420830\natom -1.69666 2.70600 10.16369 Cu 0.0 0.0 0.358334 -0.239200 -0.109338\natom 7.73517 8.65378 7.88721 Cu 0.0 0.0 0.014459 0.573296 -0.606470\natom 10.68735 9.34588 1.74641 Cu 0.0 0.0 -0.439726 -0.201238 -0.448797\natom 3.64684 3.23269 3.42151 Cu 0.0 0.0 -0.105829 0.453683 0.248434\natom 8.16102 0.46510 8.73219 Cu 0.0 0.0 0.192188 -0.096106 -0.270723\natom -1.85848 6.99743 9.97666 Cu 0.0 0.0 -0.218796 -0.500547 0.105423\natom 0.44296 10.99190 3.89648 Cu 0.0 0.0 0.053204 -0.031752 0.450723\natom 11.40933 5.64462 2.13470 Cu 0.0 0.0 -0.351827 -0.331935 0.076030\natom 11.37718 0.81774 2.06734 Cu 0.0 0.0 -0.611435 -0.193327 0.366000\natom 1.24707 3.95096 4.76029 Cu 0.0 0.0 0.324235 0.241591 -0.679982\natom -1.73266 11.65475 10.37157 Cu 0.0 0.0 0.212860 0.380882 -0.393675\natom 7.92981 5.30116 8.00521 Cu 0.0 0.0 -0.074729 0.092064 0.136868\natom -4.37850 2.67262 9.46103 Cu 0.0 0.0 0.057103 -0.274483 0.202197\natom 10.74864 8.24225 9.06354 Cu 0.0 0.0 -0.023471 -0.253329 -0.343244\natom -1.34377 9.25254 2.80510 Cu 0.0 0.0 0.066385 -0.309898 -0.212381\natom -1.25306 3.50180 3.61142 Cu 0.0 0.0 0.828273 -0.763521 -0.530900\natom 4.64858 1.24230 2.50442 Cu 0.0 0.0 -0.291803 0.025681 0.328332\natom 6.53044 7.12313 2.58618 Cu 0.0 0.0 -0.404324 -0.176835 0.114015\natom 3.42063 11.23257 8.81961 Cu 0.0 0.0 -0.139718 -0.054750 0.343706\natom 1.61485 4.27536 9.16077 Cu 0.0 0.0 0.642162 0.094405 0.089876\natom 1.26903 0.78491 7.43404 Cu 0.0 0.0 -1.098981 -0.221546 0.289553\natom 5.44186 6.51461 10.64828 Cu 0.0 0.0 -0.234590 0.410853 -0.301251\natom 8.72291 11.76178 4.86728 Cu 0.0 0.0 -0.175245 -0.098272 -0.519528\natom 4.27688 5.51884 1.91924 Cu 0.0 0.0 -0.221023 0.180796 0.180334\natom 1.77230 11.62345 1.70957 Cu 0.0 0.0 0.079069 -0.087724 -0.045952\natom 8.38154 6.62650 4.33873 Cu 0.0 0.0 -0.248326 -0.078102 0.530087\natom 5.44621 11.15069 10.67735 Cu 0.0 0.0 -0.260829 0.197381 0.016748\natom 0.25174 6.00863 7.54331 Cu 0.0 0.0 -0.473189 -0.146569 -0.892481\natom 3.67802 2.75104 8.87314 Cu 0.0 0.0 0.089110 -0.140927 0.371747\natom 2.51073 8.84239 9.22448 Cu 0.0 0.0 0.304691 -0.146943 -0.082301\natom 5.64252 9.90858 2.81814 Cu 0.0 0.0 0.513423 -0.142304 0.173443\natom 6.39122 3.17193 2.99785 Cu 0.0 0.0 -0.031973 0.226428 -0.106016\natom 13.78888 1.08302 2.77159 Cu 0.0 0.0 0.380818 -0.054563 -0.043082\natom 13.12264 6.93811 3.58588 Cu 0.0 0.0 0.102637 -0.131678 0.110528\natom -4.66009 10.58928 9.71670 Cu 0.0 0.0 0.270843 0.740876 -0.231055\natom 10.75300 5.17700 8.48767 Cu 0.0 0.0 0.320537 0.022315 -0.106267\natom 4.11156 1.42512 11.60725 Cu 0.0 0.0 -0.071191 -0.081941 -0.092444\natom 2.32526 7.33053 7.02235 Cu 0.0 0.0 0.427606 0.281319 -0.144109\natom 5.26791 11.54654 0.92695 Cu 0.0 0.0 0.083201 -0.202086 -0.734203\natom 6.67048 4.91449 5.73851 Cu 0.0 0.0 0.114596 -0.072935 -0.046294\natom 7.31983 2.84405 7.11799 Cu 0.0 0.0 0.238880 -0.435311 -0.009822\natom -0.99607 9.51313 11.51918 Cu 0.0 0.0 0.286827 0.011185 -0.967809\natom 2.19299 9.57686 5.32161 Cu 0.0 0.0 0.241050 0.033235 0.022089\natom 9.93250 3.87375 0.41602 Cu 0.0 0.0 0.481727 -0.314361 -0.455733\natom 2.25099 2.16311 1.55201 Cu 0.0 0.0 -0.161767 0.376937 -0.281467\natom 10.36062 8.54543 4.32968 Cu 0.0 0.0 0.069128 -0.029650 -0.123427\natom 7.34497 9.46663 10.56599 Cu 0.0 0.0 0.041764 -0.020438 0.077561\natom -0.98405 3.73778 7.63702 Cu 0.0 0.0 0.162342 -0.121758 -0.145897\natom -2.40276 1.09063 8.20590 Cu 0.0 0.0 -0.080006 0.099818 0.070596\natom 8.38212 7.22719 9.70741 Cu 0.0 0.0 0.218579 0.053630 0.432589\natom 11.63611 10.66180 3.47400 Cu 0.0 0.0 -0.056787 0.347671 0.309465\natom 0.79475 4.80215 2.38119 Cu 0.0 0.0 0.125964 0.706002 0.158111\nenergy -566.729768\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/nnp-dist/H2O_RPBE-D3/input.data",
    "content": " begin\ncomment written by RuNNerDecom\nlattice      24.623508      0.000000      0.000000\nlattice       0.000000     24.623508      0.000000\nlattice       0.000000      0.000000     24.623508\natom     3.735290838    2.327841157    3.501304856   O   -0.226389360    0.000000000   -0.006530137   -0.002852459   -0.027992554\natom     5.246524320    3.393061301    3.627368536   H    0.120793430    0.000000000    0.004517488   -0.000517262    0.005052573\natom     3.558676964    2.038939712    1.628158442   H    0.127225380    0.000000000    0.000095815    0.002211264    0.023427576\natom     4.652261909   21.146799653   16.174455806   O   -0.240350190    0.000000000   -0.000231046   -0.007150914    0.026944723\natom     4.197045601   22.522898765   15.074691455   H    0.132518870    0.000000000   -0.001535223    0.002790532   -0.018391035\natom     5.012047009   19.588530870   15.274057640   H    0.135733700    0.000000000    0.002788938    0.006272370   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12.330477326   16.976378414   13.002709868   H    0.105804360    0.000000000   -0.008450623    0.005466588    0.004089666\natom    15.005799572   16.925270751   11.745075844   H    0.106969100    0.000000000   -0.019060852   -0.013019411    0.044592581\natom     7.862480796    4.636206789   22.996949981   O   -0.255211000    0.000000000    0.026019058    0.004901961   -0.000568282\natom     6.607577427    4.184068847   21.690317228   H    0.104519940    0.000000000    0.008125767   -0.006959821   -0.003212454\natom     9.649892191    4.419026148   22.306113077   H    0.118804020    0.000000000   -0.031718409   -0.002728319    0.010893469\natom     3.798515431    8.049864223   11.577092353   O   -0.233009840    0.000000000   -0.021582397   -0.005949985   -0.012554795\natom     4.831649902    9.433934203   11.065106760   H    0.130163010    0.000000000    0.017887414    0.015747756   -0.003688555\natom     2.260784199    8.320520355   10.505921459   H    0.115764620    0.000000000    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20.988257237   H    0.099385010    0.000000000    0.038336244   -0.026808230    0.000017966\natom     5.294918335   15.358585124   22.119375937   H    0.098640670    0.000000000    0.006613032    0.008209277   -0.013429656\natom    17.847113537    1.659677197    7.261604340   O   -0.214984170    0.000000000    0.006018312   -0.022409254    0.003621639\natom    18.987064820    0.224034680    6.782637945   H    0.134801280    0.000000000   -0.013345731    0.012413327    0.012346459\natom    17.213508902    1.225867715    9.010954747   H    0.120488240    0.000000000   -0.000443941    0.002779306   -0.013526258\natom     0.223231546    4.153421256    1.485365010   O   -0.284149710    0.000000000   -0.016138645    0.008676852    0.024731263\natom    22.710372900    4.079060503    2.742248813   H    0.105341390    0.000000000    0.039423346    0.012173922   -0.023123038\natom     1.652651192    5.001182969    2.395013389   H    0.117989360    0.000000000   -0.023819333   -0.014915583   -0.003918404\natom    18.029065889    5.395499049   22.331535573   O   -0.232616100    0.000000000   -0.022435825   -0.041986031    0.019777229\natom    18.450206642    6.009076358   20.698998634   H    0.117402890    0.000000000    0.010969888    0.018577415   -0.028888712\natom    18.471749528    6.543217109   23.632648433   H    0.122965160    0.000000000    0.008555544    0.023492454    0.010076612\natom     9.730995489   -0.013755322   18.655527357   O   -0.260468440    0.000000000    0.033447936   -0.047525024   -0.017241120\natom    10.958809623    1.192342071   19.181358978   H    0.127148600    0.000000000    0.001410520    0.021472916    0.006833322\natom     8.059414903    0.566851923   18.625879432   H    0.119766210    0.000000000   -0.033795515    0.025211959    0.007633086\natom     5.720611440   23.314163314    9.722983047   O   -0.231630130    0.000000000    0.008590611   -0.010936445   -0.025443175\natom     6.834575199    0.786704638    9.364550991   H    0.130111070    0.000000000   -0.010659177   -0.018642575    0.001906309\natom     6.037573440   21.935577321    8.393439246   H    0.130229060    0.000000000   -0.004288229    0.030206013    0.023949980\natom     9.845218141   19.848952241    1.377688373   O   -0.231982490    0.000000000    0.047210910    0.050634028    0.057109462\natom     8.964032828   21.443191975    1.821177035   H    0.130585310    0.000000000   -0.001359815   -0.006723989   -0.005653620\natom     8.864534929   18.936979498    0.325325931   H    0.140456380    0.000000000   -0.053312141   -0.042279623   -0.051814244\natom    21.486183262    2.087957338   12.058619328   O   -0.245742770    0.000000000   -0.018336922    0.012948985   -0.040170727\natom    20.067351756    2.869512469   10.984447548   H    0.132828300    0.000000000    0.028333925   -0.013530492    0.030219120\natom    22.734213694    1.753487019   10.673217090   H    0.099760430    0.000000000   -0.005192035    0.002432708    0.011480438\natom    -0.218456207   22.514791837    3.828822870   O   -0.233891290    0.000000000    0.001999487    0.001056955    0.002002219\natom    22.977963895   23.403316849    2.478210504   H    0.123135500    0.000000000   -0.006368839    0.004516237   -0.013166446\natom     0.169763614   -0.170292738    5.058420906   H    0.104258450    0.000000000    0.006641123   -0.000339229    0.001710832\natom    22.768355390   15.179884991   22.329029795   O   -0.238086150    0.000000000   -0.046086010   -0.025235881    0.005743850\natom    21.434125066   15.631748923   -0.333185305   H    0.126220700    0.000000000    0.031123799   -0.009001222   -0.035124767\natom    21.989842718   13.702640137   21.289668674   H    0.119659510    0.000000000    0.013004599    0.035317132    0.026225131\natom    12.222509671    8.189955346    1.618074860   O   -0.247919730    0.000000000   -0.001797123    0.017574523   -0.067071366\natom    12.278849988    7.760085945    3.281828197   H    0.111233780    0.000000000   -0.004235384   -0.012471568    0.070548691\natom    13.880380289    7.710926590    1.035681823   H    0.141482170    0.000000000    0.006536703    0.000642119   -0.006764662\natom    13.661907075   10.667631057   11.112100488   O   -0.216001700    0.000000000   -0.037279496   -0.013776615    0.034916697\natom    14.124858034   12.345145386   11.672595370   H    0.133272180    0.000000000    0.003591734    0.013021971    0.000895419\natom    12.435880622   10.173618657   12.581225186   H    0.147421220    0.000000000    0.029632111    0.008032176   -0.031477484\natom    17.486330661   17.032057327    9.295375649   O   -0.235087510    0.000000000   -0.006875504   -0.012809861   -0.043019615\natom    16.911783770   16.107704983    7.688512539   H    0.110665490    0.000000000    0.006713966    0.011433370    0.028267991\natom    18.328113278   18.516190235    8.528021815   H    0.118898150    0.000000000   -0.000175840   -0.004542786    0.012591957\natom     4.935770073   18.663509563    6.368200054   O   -0.194094220    0.000000000    0.031139053   -0.066276697    0.021098669\natom     6.518835853   17.598527525    5.812888693   H    0.156894820    0.000000000   -0.042755679    0.033516151    0.011475343\natom     4.178872098   17.417123193    7.699892475   H    0.137280880    0.000000000    0.015711127    0.037753788   -0.030393813\natom    21.151675148   20.879473220    7.686178727   O   -0.248140030    0.000000000   -0.009994913   -0.003084252    0.015181890\natom    21.725161902   21.081677775    5.962589077   H    0.096696550    0.000000000    0.004375907    0.001697312   -0.018251199\natom    22.673568579   21.355735416    8.583993635   H    0.139564520    0.000000000   -0.002909430   -0.001404868    0.006677838\natom    19.507253717   12.301401988   18.501302967   O   -0.199717660    0.000000000   -0.028410932   -0.035128726    0.043667183\natom    19.776549245   13.758948329   17.594513745   H    0.142371980    0.000000000    0.012693146    0.047711282   -0.031771675\natom    17.867647309   12.681150163   19.378767407   H    0.141514070    0.000000000    0.014688099   -0.002133776   -0.011109509\natom    23.134797998   17.370023640   17.326635511   O   -0.251377170    0.000000000   -0.000268730   -0.000574628   -0.003573364\natom    23.309537263   17.766571487   19.122904057   H    0.118237060    0.000000000    0.005638293   -0.001455468   -0.001185792\natom     0.463480083   18.316502796   16.477809882   H    0.138644360    0.000000000   -0.009964426   -0.001923402    0.004419419\natom     7.198349513    9.467121587   20.207068712   O   -0.243428280    0.000000000    0.009787410   -0.009154114    0.016239349\natom     7.841261053    8.491977165   21.715395794   H    0.127971510    0.000000000   -0.015877818    0.012471507   -0.019846659\natom     5.641732350   10.325405299   20.696485297   H    0.130413120    0.000000000    0.003877775    0.000013170    0.004937889\nenergy   -4900.14395256\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/nnp-norm/Cu2S_PBE/input.data",
    "content": "begin\ncomment source_file_name=OUTCAR_4_1\nlattice 15.415349658 0.000000000 0.000000000\nlattice 0.000000000 12.016005204 0.000000000\nlattice -6.055885795 0.000000000 12.226281044\natom 9.66279 1.04561 10.73808 S 0.0 0.0 0.107416 0.024235 -0.891279\natom -3.16184 6.79866 8.04560 S 0.0 0.0 0.066538 0.139566 0.120509\natom -0.30404 11.04333 1.97659 S 0.0 0.0 -0.953672 -0.464533 -1.796811\natom 12.83426 5.06839 4.33902 S 0.0 0.0 0.393296 -0.326470 -0.518344\natom 12.39515 0.83117 4.16637 S 0.0 0.0 -0.063080 -0.611946 0.506821\natom -0.04295 7.13059 1.93130 S 0.0 0.0 -0.643788 -0.077636 0.315228\natom -3.25380 10.86483 8.16358 S 0.0 0.0 0.302005 0.898190 -0.193786\natom 9.41762 5.14521 10.58660 S 0.0 0.0 -0.644394 -0.340890 -0.050007\natom 9.00831 1.11279 6.18474 S 0.0 0.0 0.511148 0.550276 -0.454197\natom 3.34802 6.99932 0.09625 S 0.0 0.0 0.108918 0.284724 0.514152\natom 0.30069 11.03010 5.97943 S 0.0 0.0 0.216866 -0.247468 0.308978\natom 12.12524 5.04060 0.14613 S 0.0 0.0 0.501229 -0.426423 -0.428415\natom 6.18973 0.76543 12.21862 S 0.0 0.0 0.711680 -0.222174 -0.534560\natom 0.27700 6.96838 5.89276 S 0.0 0.0 0.301012 0.404099 0.020448\natom -2.83579 11.33619 12.07566 S 0.0 0.0 -0.366454 -1.013699 0.180780\natom 9.11071 5.30752 5.88412 S 0.0 0.0 0.521382 -0.161316 1.257161\natom 3.29671 1.11468 7.49721 S 0.0 0.0 0.423783 0.469883 0.109794\natom 3.12703 6.91177 10.90503 S 0.0 0.0 -0.330671 0.236197 -0.223073\natom 6.12068 10.97358 4.59954 S 0.0 0.0 0.157883 -0.563474 0.377419\natom 6.40437 4.95096 1.33698 S 0.0 0.0 -0.271097 0.026027 -0.062192\natom 6.26122 0.72292 1.03040 S 0.0 0.0 0.479811 0.556269 0.374940\natom 6.11755 6.85613 4.84907 S 0.0 0.0 -0.163743 0.501150 0.586061\natom 3.26768 11.19922 10.85073 S 0.0 0.0 -0.977102 0.340434 0.160795\natom 3.52987 5.32717 7.24188 S 0.0 0.0 -0.660281 -0.466761 -0.537193\natom -0.16538 0.79379 9.67493 S 0.0 0.0 0.082621 0.738076 -0.305641\natom 6.38897 6.71555 8.70905 S 0.0 0.0 0.714567 0.858927 -0.006896\natom 9.21963 11.13097 2.41939 S 0.0 0.0 0.578520 0.128482 0.160710\natom 2.69797 5.15168 3.47535 S 0.0 0.0 0.444296 -0.868870 -0.367079\natom 2.57642 0.90122 3.58188 S 0.0 0.0 0.258623 0.391067 -0.413657\natom 9.93715 6.97306 2.74299 S 0.0 0.0 0.641907 0.681899 -0.621142\natom 6.98678 11.02130 8.74051 S 0.0 0.0 -0.283456 -0.455182 0.418023\natom -0.27493 5.08709 9.39966 S 0.0 0.0 -0.364478 0.475103 0.470787\natom 6.51424 2.93256 8.87090 S 0.0 0.0 0.248611 -0.532822 0.261379\natom -0.07028 9.08780 9.47600 S 0.0 0.0 0.334238 -1.001614 -0.353571\natom 3.02649 8.97677 3.38093 S 0.0 0.0 0.257971 0.378857 -0.128484\natom 9.22001 3.23692 3.10270 S 0.0 0.0 0.394135 -0.561144 -0.530672\natom 5.74428 2.95266 4.87537 S 0.0 0.0 0.504185 -0.767518 0.098132\natom 6.59397 8.58770 1.02620 S 0.0 0.0 -0.052306 0.889508 0.134244\natom 3.55928 9.31404 7.15633 S 0.0 0.0 0.007547 0.236500 0.509320\natom 2.96180 3.18689 11.02470 S 0.0 0.0 0.388499 0.335359 -0.153235\natom 0.00319 2.81986 5.84202 S 0.0 0.0 0.197651 -0.410017 -0.474082\natom 12.07390 8.62516 0.18008 S 0.0 0.0 0.955619 0.478197 -0.371759\natom 9.29009 9.21675 6.39687 S 0.0 0.0 -0.053343 -0.438911 -0.538072\natom -2.79943 3.30466 11.86546 S 0.0 0.0 0.397348 0.490476 0.572317\natom 0.22927 2.73487 1.72492 S 0.0 0.0 -0.311377 0.041312 -0.093182\natom 12.80848 9.20714 4.54446 S 0.0 0.0 -1.078226 -0.482916 -0.754490\natom 9.57560 8.83412 10.64965 S 0.0 0.0 -0.180223 0.207007 -0.965804\natom -3.02133 3.13287 7.77891 S 0.0 0.0 -0.431739 0.229304 -0.188167\natom 11.52491 2.71697 3.53948 Cu 0.0 0.0 -0.524195 0.593531 -0.018888\natom 0.94130 9.18527 2.48932 Cu 0.0 0.0 0.344344 -0.016827 -0.038025\natom -2.17737 8.90566 8.67171 Cu 0.0 0.0 -0.080113 -0.460384 -0.097485\natom 8.60937 2.99411 9.87382 Cu 0.0 0.0 0.242483 0.166370 -0.096114\natom 5.78704 0.81660 8.10398 Cu 0.0 0.0 -0.650869 0.037090 0.138420\natom 1.13645 6.89390 9.81986 Cu 0.0 0.0 -0.922068 -0.415802 0.004088\natom 3.98661 11.22749 4.05170 Cu 0.0 0.0 -0.169993 0.048173 -0.094445\natom 8.48776 5.35715 2.31898 Cu 0.0 0.0 -0.235778 -0.425782 -0.273045\natom 8.46457 1.29601 1.87017 Cu 0.0 0.0 -0.176692 0.115597 0.370769\natom 4.03103 6.96064 3.88549 Cu 0.0 0.0 0.138133 0.336666 0.141528\natom 0.94448 10.87127 10.21508 Cu 0.0 0.0 0.488695 0.336434 0.182050\natom 5.52896 4.74049 8.15135 Cu 0.0 0.0 -0.555966 -0.104080 -0.202623\natom 5.25495 2.85580 0.88760 Cu 0.0 0.0 -0.236780 0.111323 0.058556\natom 7.20832 9.00509 5.25253 Cu 0.0 0.0 -0.093050 -0.067663 0.112018\natom 4.02963 9.12378 11.29065 Cu 0.0 0.0 0.214455 -0.397161 -0.297440\natom 2.00869 2.95149 6.95641 Cu 0.0 0.0 0.242228 0.086186 0.256424\natom -3.59727 1.31298 11.56779 Cu 0.0 0.0 -0.234649 0.051811 -0.011230\natom 10.17489 7.11535 7.19747 Cu 0.0 0.0 -0.205621 -0.373986 -0.133792\natom 13.14051 10.69193 0.61472 Cu 0.0 0.0 -0.227511 0.015227 -0.013204\natom -0.15851 4.93004 5.03782 Cu 0.0 0.0 -0.407379 -0.188360 -0.079197\natom -1.03043 0.75778 5.49457 Cu 0.0 0.0 -0.614057 0.276670 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-0.102250\natom 12.23272 2.72008 1.12254 Cu 0.0 0.0 -0.249257 0.710722 -0.108280\natom 1.15816 2.14568 11.54656 Cu 0.0 0.0 -0.411213 -0.684450 0.384207\natom 5.27209 7.82267 6.86516 Cu 0.0 0.0 0.125328 -0.256841 -0.003757\natom 8.17277 10.18657 0.27762 Cu 0.0 0.0 -0.368442 -0.181728 0.621258\natom 3.91864 4.11751 5.06655 Cu 0.0 0.0 -0.432305 0.483675 0.538896\natom 4.00310 1.50710 5.38681 Cu 0.0 0.0 -0.237210 -0.113493 -0.033558\natom 8.72038 7.58568 0.75111 Cu 0.0 0.0 -0.048667 0.004667 0.557755\natom 5.69466 10.30930 6.99982 Cu 0.0 0.0 0.082381 0.291179 -0.205718\natom 0.73141 4.83540 11.36935 Cu 0.0 0.0 -0.060464 -0.428701 -0.029908\natom -1.02582 2.77460 10.47989 Cu 0.0 0.0 -0.129362 0.072520 -0.184218\natom 7.80433 8.30190 7.77366 Cu 0.0 0.0 -0.615739 0.187191 -0.342683\natom 10.52153 9.29163 1.56932 Cu 0.0 0.0 -0.404426 0.511279 0.817259\natom 1.76042 2.96828 4.38708 Cu 0.0 0.0 0.093553 0.136826 -0.191640\natom 8.37753 0.81962 8.31150 Cu 0.0 0.0 0.131603 0.121433 0.418584\natom 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4.59107 9.25548 Cu 0.0 0.0 0.004397 0.377740 -0.175196\natom 0.44256 0.79397 7.51533 Cu 0.0 0.0 0.392843 -0.098361 0.143483\natom 5.25134 6.41678 10.66453 Cu 0.0 0.0 0.475273 -0.138365 -0.079004\natom 8.24962 11.81450 4.48984 Cu 0.0 0.0 0.215133 -0.064211 -0.350886\natom 4.18342 5.45581 1.75203 Cu 0.0 0.0 -0.080309 -0.016133 -0.219496\natom 4.01003 0.66675 1.73762 Cu 0.0 0.0 0.028881 -0.323578 0.033634\natom 8.34839 6.92699 4.24743 Cu 0.0 0.0 -0.310258 0.036970 0.397137\natom 5.48094 11.18523 10.58182 Cu 0.0 0.0 0.514304 0.188252 -0.630833\natom 1.07131 5.38871 7.37534 Cu 0.0 0.0 0.320279 0.188182 0.416405\natom 4.21301 2.62568 9.10014 Cu 0.0 0.0 -0.197230 -0.370539 -0.076098\natom 2.86651 8.26904 9.12445 Cu 0.0 0.0 0.813195 0.821609 -0.598471\natom 5.34637 9.52143 2.76224 Cu 0.0 0.0 0.183371 -0.205205 0.073164\natom 6.83808 3.46300 3.01720 Cu 0.0 0.0 0.096663 -0.107759 -0.264892\natom -1.22919 1.20692 2.84928 Cu 0.0 0.0 0.111910 0.175226 -0.288781\natom 12.57696 7.12242 3.51550 Cu 0.0 0.0 -0.080300 0.482168 0.355862\natom 9.16529 10.95579 10.07757 Cu 0.0 0.0 -0.015034 0.485749 -0.534452\natom 10.74902 4.75363 8.87895 Cu 0.0 0.0 0.538526 -0.144405 -0.516937\natom 4.19619 1.36541 11.49226 Cu 0.0 0.0 -0.380785 -0.030453 -0.004198\natom 2.45878 7.37775 6.65467 Cu 0.0 0.0 0.066074 -0.078546 0.088615\natom 5.31896 10.66606 0.43882 Cu 0.0 0.0 0.385710 -0.001102 -0.031416\natom 6.91402 4.80767 5.46184 Cu 0.0 0.0 0.125936 0.245444 -0.030834\natom 7.15034 2.69321 6.67590 Cu 0.0 0.0 -0.238705 -0.448773 0.259050\natom -0.81738 8.39491 11.50197 Cu 0.0 0.0 -0.436133 -0.344043 -0.296601\natom 2.10487 9.67028 5.38794 Cu 0.0 0.0 -0.077371 0.125704 -0.228517\natom 9.68527 3.42373 0.94518 Cu 0.0 0.0 0.175207 -0.068417 -0.088789\natom 2.62334 2.67217 1.88371 Cu 0.0 0.0 -0.048296 0.199486 -0.370291\natom 10.41720 8.36449 4.55256 Cu 0.0 0.0 0.315948 0.348300 0.091776\natom 7.21584 9.43029 10.57027 Cu 0.0 0.0 0.126790 -0.352963 0.043304\natom -0.52072 3.61443 7.80169 Cu 0.0 0.0 -0.368694 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9.14403 8.20163 Cu 0.0 0.0 -0.736542 -0.170504 -0.135000\natom 8.78257 2.91894 9.94865 Cu 0.0 0.0 0.074663 0.111987 -0.087260\natom 5.44081 0.91688 8.74315 Cu 0.0 0.0 -0.180289 0.645887 -0.366148\natom 0.77289 7.30984 9.98548 Cu 0.0 0.0 -0.277405 -0.881330 0.335080\natom 3.85512 10.95899 3.91346 Cu 0.0 0.0 0.260423 0.320780 -0.193056\natom 8.53235 5.11107 2.48624 Cu 0.0 0.0 -0.058014 -0.089280 -0.050176\natom 8.43690 0.63670 1.96905 Cu 0.0 0.0 0.099391 0.927992 0.179655\natom 3.99811 6.95598 3.90500 Cu 0.0 0.0 -0.352701 -0.011541 0.050527\natom 1.18262 10.61798 10.28166 Cu 0.0 0.0 -1.094495 -0.340401 -0.726245\natom 5.10052 4.88890 8.30125 Cu 0.0 0.0 0.018158 0.149382 -0.187026\natom 5.10993 2.61008 0.77614 Cu 0.0 0.0 -0.275247 0.260318 -0.417356\natom 7.25024 8.89725 5.25590 Cu 0.0 0.0 0.639651 0.022245 0.247963\natom 4.08558 8.88878 11.36107 Cu 0.0 0.0 0.524273 0.774990 0.801272\natom 2.21835 3.02757 6.84923 Cu 0.0 0.0 -0.169081 0.275750 0.105148\natom -3.87773 0.67325 11.41533 Cu 0.0 0.0 0.251774 0.280134 0.178852\natom 9.32650 7.13585 7.16763 Cu 0.0 0.0 0.548313 -0.054311 -0.557519\natom 12.78822 11.27114 0.55769 Cu 0.0 0.0 0.294325 -0.384911 -0.009479\natom -0.88291 4.97952 5.49548 Cu 0.0 0.0 0.564377 0.282694 -0.115547\natom -0.94004 0.86817 5.17878 Cu 0.0 0.0 0.531793 -0.105153 0.480341\natom 13.50445 7.21972 0.82994 Cu 0.0 0.0 0.202768 -0.216719 0.219452\natom 10.42550 11.49942 6.83806 Cu 0.0 0.0 0.645052 -0.311437 0.297678\natom -4.02735 4.98160 11.70489 Cu 0.0 0.0 -0.046036 -0.144755 -0.350289\natom 8.20421 1.34114 12.16595 Cu 0.0 0.0 -0.136416 0.398756 0.126365\natom -1.77903 7.86620 5.88147 Cu 0.0 0.0 0.105846 -0.233096 0.554421\natom 1.66504 10.96535 0.86414 Cu 0.0 0.0 -0.184789 0.089984 -0.093283\natom 11.43269 4.94510 6.15516 Cu 0.0 0.0 0.189353 -0.287190 0.179424\natom 11.54652 1.99240 6.03084 Cu 0.0 0.0 -0.256757 -0.069354 0.081431\natom 1.32088 8.42018 0.03724 Cu 0.0 0.0 0.539276 -0.848730 0.280594\natom -2.06691 10.78843 6.10765 Cu 0.0 0.0 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0.167616\natom -1.13919 3.60534 3.37464 Cu 0.0 0.0 -0.081470 -0.216910 -0.268008\natom 5.81252 0.87416 3.69546 Cu 0.0 0.0 0.239683 -0.389727 -0.441421\natom 6.27049 6.44284 2.73448 Cu 0.0 0.0 0.593297 -0.267458 -0.209278\natom 3.31810 11.57108 8.96326 Cu 0.0 0.0 -0.094871 0.025466 -0.063309\natom 2.93597 5.49182 9.37236 Cu 0.0 0.0 -0.352565 0.166649 0.402671\natom 1.19319 0.86485 7.88775 Cu 0.0 0.0 0.112395 -0.280213 0.120366\natom 5.26044 6.78722 10.70638 Cu 0.0 0.0 0.200201 -0.557848 -0.024562\natom 8.36755 11.16562 4.67475 Cu 0.0 0.0 0.099281 0.195008 -0.022501\natom 4.26368 5.66242 1.58437 Cu 0.0 0.0 -0.713695 -0.342037 -0.255913\natom 3.94831 0.44729 1.60572 Cu 0.0 0.0 -0.373471 0.103052 0.100319\natom 8.51632 6.74447 4.54446 Cu 0.0 0.0 -0.287029 -0.070477 0.054991\natom 5.26048 11.15558 10.54689 Cu 0.0 0.0 0.010288 0.017542 0.174574\natom 0.80269 5.77855 7.91179 Cu 0.0 0.0 0.151297 -0.299896 -0.394095\natom 3.54421 2.88108 9.06926 Cu 0.0 0.0 0.134787 -0.405971 -0.278721\natom 2.79386 8.35830 9.40614 Cu 0.0 0.0 0.421860 0.208443 -0.662631\natom 5.51876 8.95312 3.28504 Cu 0.0 0.0 -0.516486 0.374121 0.944122\natom 6.47196 3.62579 3.03481 Cu 0.0 0.0 0.034735 -0.775339 0.537677\natom 14.15939 0.56032 2.61849 Cu 0.0 0.0 0.357476 0.155425 -0.251905\natom -1.33103 6.95771 3.30479 Cu 0.0 0.0 -0.441228 -0.034632 0.201249\natom 10.69010 10.74585 9.61767 Cu 0.0 0.0 0.383109 0.887366 -0.524036\natom -4.26198 4.65909 9.05469 Cu 0.0 0.0 -0.351208 0.015277 0.243678\natom 3.51669 1.28051 11.64637 Cu 0.0 0.0 0.130873 -0.302352 -0.216671\natom 2.38974 7.46529 6.99156 Cu 0.0 0.0 0.230953 0.041896 -0.041359\natom 5.56353 10.80506 0.96796 Cu 0.0 0.0 0.626194 -0.006385 0.114088\natom 7.22734 4.74326 5.10303 Cu 0.0 0.0 -0.291754 0.209924 0.300175\natom 7.57996 2.33894 6.91905 Cu 0.0 0.0 -0.505569 0.292717 0.181547\natom -0.98774 8.57345 11.79519 Cu 0.0 0.0 0.415435 -0.079250 -0.345337\natom 0.87942 9.02397 5.07166 Cu 0.0 0.0 0.193953 0.478963 -0.291218\natom 10.35506 3.85100 0.71450 Cu 0.0 0.0 -0.005244 -0.092026 0.344046\natom 2.08530 2.27155 1.67193 Cu 0.0 0.0 0.297269 0.059745 -0.607520\natom 10.11475 8.59559 4.45899 Cu 0.0 0.0 0.065398 0.290857 0.624966\natom 7.31810 9.47289 10.77761 Cu 0.0 0.0 0.095057 0.223664 -0.700720\natom -0.61214 3.59627 7.63285 Cu 0.0 0.0 -0.066518 0.184155 0.474062\natom -1.78829 1.25111 7.75054 Cu 0.0 0.0 0.004942 -0.258494 0.392792\natom 8.71311 7.23083 9.84811 Cu 0.0 0.0 -0.373314 -0.092349 -0.144806\natom 11.63479 11.13932 4.32592 Cu 0.0 0.0 0.193398 -0.054525 -0.140596\natom 0.85282 4.69732 2.08289 Cu 0.0 0.0 -0.006659 -0.137894 -0.260756\nenergy -565.024216\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_156\nlattice 15.476500743 0.000000000 0.000000000\nlattice 0.000000000 12.063671443 0.000000000\nlattice -6.079908863 0.000000000 12.274781426\natom 9.46546 0.80147 10.59117 S 0.0 0.0 0.567680 0.746124 -0.093120\natom -3.68163 7.22230 8.34836 S 0.0 0.0 0.387695 -0.000600 -0.616679\natom -0.52248 10.99513 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4.71253 S 0.0 0.0 -0.975836 0.509250 0.700128\natom 9.61046 9.29715 10.54329 S 0.0 0.0 -0.689819 -0.038470 0.279675\natom -3.32385 2.82722 7.63729 S 0.0 0.0 -0.481512 -0.403178 -0.397401\natom 11.85911 2.73356 3.92196 Cu 0.0 0.0 -0.479321 0.767893 -0.562323\natom 0.47693 9.02830 2.23133 Cu 0.0 0.0 0.605631 -0.267566 -0.103670\natom -2.19514 9.06196 8.75963 Cu 0.0 0.0 -0.120668 -0.075990 -0.026226\natom 8.61715 2.90429 9.93588 Cu 0.0 0.0 -0.652625 -0.157447 0.123248\natom 5.71077 1.15189 8.57530 Cu 0.0 0.0 -0.306528 -0.389515 -0.056375\natom 1.26479 6.55483 9.74342 Cu 0.0 0.0 0.008496 0.424139 -0.022828\natom 3.52146 11.10608 3.67750 Cu 0.0 0.0 0.020809 -0.597194 0.023990\natom 8.41537 4.98142 2.27163 Cu 0.0 0.0 0.235358 0.181826 0.048358\natom 8.47714 1.62571 1.63661 Cu 0.0 0.0 0.043483 -0.054413 0.120383\natom 4.23686 6.67208 3.77629 Cu 0.0 0.0 -0.192383 0.291531 -0.159868\natom 1.25660 10.66737 10.34630 Cu 0.0 0.0 -0.166772 -0.029497 -0.384436\natom 5.78458 4.84978 7.88012 Cu 0.0 0.0 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0.157264 0.197031\natom 1.02280 10.58200 0.06181 Cu 0.0 0.0 -0.218236 -0.187763 0.031161\natom 11.66814 4.65161 6.11953 Cu 0.0 0.0 -0.070981 -0.144674 0.268308\natom 11.17925 1.32646 5.84452 Cu 0.0 0.0 0.023128 -0.035360 0.242812\natom -4.61050 7.95128 11.73329 Cu 0.0 0.0 0.329658 -0.333983 0.292666\natom -1.78278 10.52749 5.82970 Cu 0.0 0.0 0.034615 -0.364520 0.129266\natom 9.00914 5.78702 12.09242 Cu 0.0 0.0 0.994671 -0.386441 -0.075135\natom 7.80736 2.39500 4.07240 Cu 0.0 0.0 0.441504 0.017547 -0.066392\natom 3.16731 9.66801 1.33663 Cu 0.0 0.0 -0.274231 -0.649275 1.020066\natom -0.04408 8.60360 7.36891 Cu 0.0 0.0 0.180492 0.364851 0.169512\natom 13.36768 3.03761 0.20609 Cu 0.0 0.0 0.978545 -0.227040 0.222372\natom 1.44044 1.67482 11.32771 Cu 0.0 0.0 -1.101495 -0.309701 0.206537\natom 5.63563 7.79884 6.93017 Cu 0.0 0.0 -0.324695 0.238419 -0.473087\natom 8.51250 10.83254 1.12027 Cu 0.0 0.0 0.488465 -0.159050 -0.471260\natom 3.85876 4.58544 5.21483 Cu 0.0 0.0 0.259699 -0.580176 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Cu 0.0 0.0 -0.576462 -0.180970 -0.049483\natom 7.32782 4.31071 5.82521 Cu 0.0 0.0 -0.522107 0.353251 -0.959985\natom 7.66354 2.73122 7.50603 Cu 0.0 0.0 -0.166669 0.192502 0.201686\natom -1.43250 8.41399 11.77217 Cu 0.0 0.0 0.347823 0.068297 -0.186494\natom 2.11419 9.49110 5.62346 Cu 0.0 0.0 -0.042565 0.158531 -0.223262\natom 11.03887 2.73447 1.15455 Cu 0.0 0.0 -0.117768 0.166711 0.190583\natom 2.43931 2.81590 1.89111 Cu 0.0 0.0 0.006521 0.227399 -0.415608\natom 10.21714 8.56313 4.34968 Cu 0.0 0.0 0.258534 0.100881 -0.558522\natom 7.09611 9.38395 10.57802 Cu 0.0 0.0 0.393663 0.075645 0.014443\natom -1.59050 4.06116 7.81026 Cu 0.0 0.0 0.776427 0.169641 0.044501\natom -2.15370 1.08495 8.85227 Cu 0.0 0.0 -0.251265 -0.119388 -0.127210\natom 8.67455 7.22254 10.03372 Cu 0.0 0.0 -0.079222 0.387976 -0.021438\natom 11.53372 11.21480 3.96977 Cu 0.0 0.0 -0.374950 -0.033082 -0.260344\natom 0.47515 5.15818 2.57476 Cu 0.0 0.0 0.420379 -0.030283 -0.128469\nenergy -564.447991\ncharge 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0.185371 -0.392556 -0.207226\natom 12.07641 8.95908 0.14265 S 0.0 0.0 0.441586 -0.584793 0.196521\natom 9.22628 9.55966 6.46445 S 0.0 0.0 1.188211 -0.824610 0.517735\natom -2.91541 3.20849 11.88179 S 0.0 0.0 -0.324162 -0.287234 0.678644\natom -0.17466 2.74423 1.66850 S 0.0 0.0 -0.372012 0.572366 0.638305\natom 12.50872 8.96375 4.69524 S 0.0 0.0 1.048691 -0.373282 -0.185449\natom 9.63818 9.19569 10.62692 S 0.0 0.0 -0.332292 0.705799 -0.043748\natom -3.39740 3.10418 7.82119 S 0.0 0.0 -0.394274 0.204585 0.179593\natom 11.41337 2.93384 3.62262 Cu 0.0 0.0 -0.137120 -0.022584 -0.215086\natom 0.42729 8.98124 2.15855 Cu 0.0 0.0 0.280879 -0.322722 0.213868\natom -2.31587 9.10396 8.70111 Cu 0.0 0.0 0.410500 0.664991 -0.503630\natom 8.78767 3.43602 9.81686 Cu 0.0 0.0 0.475583 -0.513672 0.132257\natom 5.64818 1.02099 8.42292 Cu 0.0 0.0 -0.271670 -0.353939 0.232634\natom 0.84887 6.77692 9.62394 Cu 0.0 0.0 0.162007 -0.779704 0.161309\natom 3.93285 11.07174 4.04964 Cu 0.0 0.0 -0.368359 0.036225 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-0.454017\natom 10.13844 7.11491 6.40231 Cu 0.0 0.0 -0.569071 0.250542 0.601601\natom 12.72990 10.98411 0.96736 Cu 0.0 0.0 -0.176046 0.318766 -0.333106\natom -0.00737 5.09788 5.75926 Cu 0.0 0.0 -0.029219 -0.200811 -0.079748\natom -0.93295 1.16232 5.26955 Cu 0.0 0.0 -0.492524 -0.633635 -0.250378\natom 13.28385 7.15458 0.66812 Cu 0.0 0.0 -0.301181 0.074160 -0.102055\natom 10.40943 11.12950 6.96072 Cu 0.0 0.0 -0.117897 -0.028344 -0.116176\natom -4.00996 5.24507 11.33974 Cu 0.0 0.0 0.012991 0.023391 -0.094382\natom 13.31640 2.97016 0.83392 Cu 0.0 0.0 -0.423414 0.150964 -0.607954\natom 12.47100 6.88116 5.74444 Cu 0.0 0.0 0.557164 -0.303740 -0.871168\natom 1.06901 10.65973 0.19548 Cu 0.0 0.0 0.012070 -0.284940 -0.273374\natom 11.29234 4.27251 5.96161 Cu 0.0 0.0 0.086863 0.332260 -0.115234\natom 11.62120 1.62573 6.08354 Cu 0.0 0.0 -0.048666 0.292079 0.471397\natom -4.65422 7.87348 11.91059 Cu 0.0 0.0 -0.960416 0.488317 -0.211798\natom -1.63735 10.42263 6.09840 Cu 0.0 0.0 -1.113106 -0.544845 -0.000427\natom 15.05717 4.96662 0.22650 Cu 0.0 0.0 -0.379133 -0.304059 0.136958\natom 9.28967 2.88898 5.08692 Cu 0.0 0.0 0.117682 0.616494 -0.306475\natom 3.16447 9.17559 1.14169 Cu 0.0 0.0 0.030456 0.037399 -0.640928\natom 0.37739 8.70188 7.70190 Cu 0.0 0.0 -0.001689 -0.201921 -0.548107\natom 5.28792 3.60439 10.55368 Cu 0.0 0.0 0.457627 -0.225015 0.531135\natom 1.03295 1.75095 11.62696 Cu 0.0 0.0 -0.173491 0.095705 -0.022558\natom 4.60570 7.55834 6.86272 Cu 0.0 0.0 0.674104 0.042332 -0.067677\natom 8.25251 10.54132 0.76591 Cu 0.0 0.0 0.114499 -0.291107 0.149544\natom 4.46596 4.18082 5.48738 Cu 0.0 0.0 -0.557451 -0.253554 0.050618\natom 3.58863 1.51455 5.07176 Cu 0.0 0.0 0.718783 0.669856 0.870525\natom 8.40039 7.59253 0.80712 Cu 0.0 0.0 0.343056 -0.036320 -0.525589\natom 5.48965 10.34826 6.97892 Cu 0.0 0.0 0.024921 -0.042790 0.317892\natom 0.80000 4.87994 11.68969 Cu 0.0 0.0 0.246354 -0.347015 0.236503\natom -1.18845 2.71278 10.31996 Cu 0.0 0.0 -0.104547 0.273178 0.306075\natom 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3.84134 Cu 0.0 0.0 -0.210706 0.227822 -0.550197\natom 5.58912 1.00407 3.49382 Cu 0.0 0.0 0.373138 0.265093 0.159110\natom 6.57741 7.14653 2.56683 Cu 0.0 0.0 -0.417628 -0.291723 0.407608\natom 3.58870 10.89339 8.71247 Cu 0.0 0.0 -0.305316 0.000667 0.350551\natom 3.42368 4.98435 9.96699 Cu 0.0 0.0 -0.255185 1.082788 -0.716166\natom 1.28762 0.71788 7.99947 Cu 0.0 0.0 0.405352 -0.190991 -0.277226\natom 5.85996 6.34795 10.61468 Cu 0.0 0.0 -0.073768 -0.028163 -0.035427\natom 8.15201 11.55962 4.48578 Cu 0.0 0.0 -0.644758 -0.427102 -0.395821\natom 3.57494 4.73989 1.23786 Cu 0.0 0.0 -0.051561 0.396326 0.465236\natom 3.80726 0.43646 1.82202 Cu 0.0 0.0 -0.125559 0.146887 -0.029206\natom 8.40548 6.57428 4.21744 Cu 0.0 0.0 0.033844 0.295766 0.253862\natom 5.44343 11.21633 10.68925 Cu 0.0 0.0 0.092219 0.324847 -0.419697\natom 1.28907 5.09385 8.21174 Cu 0.0 0.0 0.381162 0.156476 0.140724\natom 3.34804 2.44109 9.26473 Cu 0.0 0.0 -0.277518 -0.018140 -0.412823\natom 2.59851 8.50015 8.96715 Cu 0.0 0.0 0.547576 0.164492 -0.235145\natom 5.46695 9.56576 3.01182 Cu 0.0 0.0 -0.207159 -0.026245 0.447183\natom 6.44944 3.62350 3.24347 Cu 0.0 0.0 -0.156367 -0.066807 -0.150968\natom -1.15831 0.90865 2.49817 Cu 0.0 0.0 -0.273470 0.402750 0.455927\natom -1.43657 6.76605 3.45714 Cu 0.0 0.0 0.143092 0.088504 -0.315961\natom 10.61313 11.13935 9.64448 Cu 0.0 0.0 0.247714 -0.513574 -0.422224\natom 10.71616 5.88205 8.81022 Cu 0.0 0.0 -0.529668 -0.693187 0.651642\natom 4.10225 1.57707 11.62967 Cu 0.0 0.0 -0.964105 -0.349743 -0.468824\natom 2.27900 6.88276 6.49927 Cu 0.0 0.0 -0.242226 0.105661 0.469384\natom 5.47666 10.56877 0.54818 Cu 0.0 0.0 -0.820864 1.388044 -0.266691\natom 6.83940 4.80600 5.57295 Cu 0.0 0.0 0.265387 -0.258445 0.065663\natom 8.00253 2.70036 7.01505 Cu 0.0 0.0 -0.779860 -0.197739 0.669692\natom -0.74210 8.04227 11.91283 Cu 0.0 0.0 -0.411558 -0.039897 -0.461576\natom 1.78696 9.71606 5.17893 Cu 0.0 0.0 0.180707 -0.015326 -0.140653\natom 10.82165 2.95042 1.22111 Cu 0.0 0.0 0.578328 0.526833 -0.807511\natom 2.16585 2.42165 1.58537 Cu 0.0 0.0 0.211844 0.052891 0.426346\natom 10.33151 8.33328 4.29213 Cu 0.0 0.0 0.170112 0.321127 -0.128360\natom 7.31421 9.55438 10.40212 Cu 0.0 0.0 -0.388305 0.078768 0.793821\natom -0.83764 3.95521 7.79240 Cu 0.0 0.0 -0.441797 -0.573566 0.419583\natom -2.06260 1.25249 8.16312 Cu 0.0 0.0 0.535082 -0.202285 -0.088209\natom 8.74820 7.00627 10.02256 Cu 0.0 0.0 -0.248813 0.245293 -0.031917\natom 11.56092 10.71251 3.58256 Cu 0.0 0.0 0.131702 -0.072963 0.190967\natom 1.00507 4.78711 2.44966 Cu 0.0 0.0 -0.447225 0.040965 -0.384033\nenergy -565.607832\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_21\nlattice 15.424131298 0.000000000 0.000000000\nlattice 0.000000000 12.022850344 0.000000000\nlattice -6.059335643 0.000000000 12.233245972\natom 9.69752 0.99718 10.31507 S 0.0 0.0 0.428489 0.864370 0.668883\natom -3.29298 7.22335 8.22515 S 0.0 0.0 -0.544722 -1.225831 -0.911920\natom -0.28490 11.25245 1.86478 S 0.0 0.0 0.547659 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0.0 0.0 0.674174 -0.336296 -0.251820\natom 6.52311 2.47794 9.01798 S 0.0 0.0 -0.368600 0.495413 -0.415155\natom -0.34032 9.26133 9.34661 S 0.0 0.0 -0.021809 0.035197 0.079901\natom 2.96215 9.03787 3.49597 S 0.0 0.0 -0.791542 -0.321400 0.131101\natom 9.48058 2.84442 2.74864 S 0.0 0.0 -0.176657 0.007876 0.530057\natom 5.84339 2.45195 5.07287 S 0.0 0.0 0.477930 -0.166367 -0.131116\natom 6.59664 8.63061 1.20540 S 0.0 0.0 0.320953 0.243389 -0.019120\natom 3.51010 9.26075 7.38912 S 0.0 0.0 -0.193849 -0.273587 -0.566212\natom 2.89753 3.25684 10.89907 S 0.0 0.0 -0.471085 -0.501682 0.516292\natom 0.26655 3.22616 5.72619 S 0.0 0.0 -0.387580 -0.984291 -0.479125\natom 12.48509 8.66812 0.25024 S 0.0 0.0 -1.460864 0.077459 1.676333\natom 9.02451 9.17407 6.18832 S 0.0 0.0 0.798591 0.041943 0.377210\natom -2.85996 3.18226 12.19742 S 0.0 0.0 0.090256 0.383348 -0.656936\natom -0.35694 3.07919 1.69350 S 0.0 0.0 0.369782 -0.178452 -0.008726\natom 12.86472 8.88547 4.67116 S 0.0 0.0 -0.808055 -0.392928 0.316984\natom 9.44482 9.35669 10.52433 S 0.0 0.0 0.123355 0.136570 -0.495146\natom -3.02449 3.30194 7.82746 S 0.0 0.0 0.212687 0.170418 -0.175442\natom 11.67543 3.17715 3.82097 Cu 0.0 0.0 -0.132108 -0.273595 0.073435\natom 0.84980 9.08603 2.52848 Cu 0.0 0.0 0.234813 0.480321 -0.150752\natom -2.61598 9.20958 8.16868 Cu 0.0 0.0 0.323066 1.558654 0.182828\natom 8.31095 3.30571 10.14593 Cu 0.0 0.0 0.065294 -0.220710 -0.531475\natom 5.36347 0.56375 8.47158 Cu 0.0 0.0 -0.273093 -0.159461 -0.117278\natom 1.04700 7.54401 9.94402 Cu 0.0 0.0 -1.381842 0.395253 -0.408891\natom 3.61068 11.09913 3.60760 Cu 0.0 0.0 0.280395 0.348068 0.571919\natom 8.32091 5.09934 1.98609 Cu 0.0 0.0 0.512465 0.379369 0.764857\natom 8.73278 0.81142 2.02043 Cu 0.0 0.0 -0.204404 -0.102945 0.142097\natom 3.97343 7.12833 4.11889 Cu 0.0 0.0 -0.098439 -0.034560 -0.227143\natom 0.94047 11.06189 10.14298 Cu 0.0 0.0 0.334059 0.026774 0.089888\natom 6.01770 4.52176 8.06381 Cu 0.0 0.0 -0.223240 -0.163693 0.263484\natom 5.48212 2.68766 1.02042 Cu 0.0 0.0 -0.538722 0.241714 -0.276965\natom 7.10132 8.75242 5.01571 Cu 0.0 0.0 -0.128632 0.028158 0.504093\natom 4.19171 9.03316 11.47110 Cu 0.0 0.0 0.353379 -0.080336 0.119637\natom 2.16518 3.12633 6.89857 Cu 0.0 0.0 0.244781 0.219714 0.162134\natom -3.75606 0.63179 11.51750 Cu 0.0 0.0 0.048407 0.763425 -0.517493\natom 9.58941 6.87478 6.71054 Cu 0.0 0.0 0.219831 0.234185 -0.445892\natom 13.06049 11.03756 1.02745 Cu 0.0 0.0 -0.079314 -0.677939 0.286754\natom -0.78852 5.13166 5.22801 Cu 0.0 0.0 0.352833 0.379884 0.287873\natom -1.15115 1.30344 5.50785 Cu 0.0 0.0 0.380819 0.210585 -0.356781\natom 13.32304 6.68263 0.99937 Cu 0.0 0.0 0.392733 0.172661 -0.326537\natom 10.38163 11.11523 6.56486 Cu 0.0 0.0 -0.415950 -0.661426 -0.007447\natom -3.99277 5.13629 11.52678 Cu 0.0 0.0 0.080316 -0.215417 -0.053770\natom 8.38323 1.75060 12.14468 Cu 0.0 0.0 0.043482 -0.321417 -0.081744\natom 12.45114 6.85202 5.91286 Cu 0.0 0.0 -0.063381 0.145723 0.345637\natom 1.13538 10.68873 0.06046 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0.202179 0.235401\natom 8.44816 5.07613 8.25802 Cu 0.0 0.0 0.056234 0.186547 0.382363\natom -4.22248 2.80056 9.82683 Cu 0.0 0.0 -0.124053 -1.046375 0.339479\natom 10.21695 8.52238 8.32123 Cu 0.0 0.0 0.246815 0.593058 0.572485\natom -1.45089 10.01232 3.25558 Cu 0.0 0.0 0.558700 0.024738 -0.512596\natom -1.30663 4.94609 2.67861 Cu 0.0 0.0 0.116202 -0.059950 -0.298398\natom 6.50197 0.51792 3.68434 Cu 0.0 0.0 -0.449054 0.490378 -0.230439\natom 6.30679 6.74451 2.60751 Cu 0.0 0.0 -0.143249 0.431872 0.162513\natom 3.27261 11.05442 8.79737 Cu 0.0 0.0 0.088914 0.202669 0.055355\natom 2.20232 5.17800 8.76920 Cu 0.0 0.0 -0.544103 0.011140 0.083524\natom 1.06039 0.41653 7.85303 Cu 0.0 0.0 0.133753 0.002416 -0.235867\natom 5.08769 6.88505 10.68469 Cu 0.0 0.0 -0.338914 -0.377961 0.587730\natom 8.27064 11.32272 4.83664 Cu 0.0 0.0 -0.013078 -0.297463 0.174367\natom 3.72235 6.00358 1.37287 Cu 0.0 0.0 0.246339 -0.293514 0.294988\natom 3.88533 0.37916 1.53747 Cu 0.0 0.0 0.066676 0.846589 0.222740\natom 8.26314 6.44043 4.33352 Cu 0.0 0.0 -0.055601 -0.620551 -0.163899\natom 5.25481 11.15345 10.56730 Cu 0.0 0.0 0.515022 0.073468 -0.549762\natom -0.10732 6.32892 7.90190 Cu 0.0 0.0 0.614815 0.374366 -0.689606\natom 4.03424 3.10700 8.96040 Cu 0.0 0.0 -0.070604 -0.245349 -0.141646\natom 3.24539 7.80876 8.98313 Cu 0.0 0.0 0.381602 -0.071906 0.184768\natom 5.88289 9.54405 3.04948 Cu 0.0 0.0 -0.307999 0.117592 -0.086001\natom 6.97649 3.12229 3.11330 Cu 0.0 0.0 0.081078 -0.049690 0.171484\natom 14.00685 1.30478 2.63737 Cu 0.0 0.0 -0.376572 -0.171602 0.375310\natom -0.73886 7.58435 3.84135 Cu 0.0 0.0 -0.079898 -0.142675 0.156969\natom -4.67615 10.97554 9.48726 Cu 0.0 0.0 0.180010 -0.143702 -0.281537\natom -4.05310 4.92678 8.85705 Cu 0.0 0.0 -0.465214 1.265766 0.192168\natom 3.65138 1.23209 11.73213 Cu 0.0 0.0 0.320207 -0.216919 -0.016849\natom 2.72416 6.84443 6.42931 Cu 0.0 0.0 -0.201811 -0.129502 0.404569\natom 5.65014 10.79163 0.52835 Cu 0.0 0.0 0.378108 -0.367916 0.074316\natom 6.68295 4.57131 5.27043 Cu 0.0 0.0 0.067931 -0.211691 0.118409\natom 7.12518 1.59470 6.97899 Cu 0.0 0.0 -0.046693 0.579110 -0.224163\natom -0.76211 8.33615 11.69957 Cu 0.0 0.0 -0.405789 0.076152 -0.621886\natom 0.98180 9.55503 5.02535 Cu 0.0 0.0 0.138730 -0.266626 -0.009083\natom 9.89123 3.50855 0.72891 Cu 0.0 0.0 0.239491 0.252843 -0.563085\natom 2.21321 2.47103 1.72695 Cu 0.0 0.0 -0.469181 0.046264 -0.566015\natom 9.67661 8.29993 4.24294 Cu 0.0 0.0 0.595732 0.872025 0.381690\natom 6.94673 9.28986 10.58324 Cu 0.0 0.0 0.305991 0.325527 -0.682343\natom -0.40525 3.93547 7.66333 Cu 0.0 0.0 0.015551 -0.333179 0.575055\natom -2.10338 1.24926 8.35676 Cu 0.0 0.0 -0.181614 -0.182304 -0.025722\natom 8.42906 7.42512 9.83040 Cu 0.0 0.0 0.319895 -0.661271 0.340294\natom 11.56322 10.71821 3.71966 Cu 0.0 0.0 0.863463 -0.094005 0.789171\natom 1.09542 4.85435 1.98275 Cu 0.0 0.0 0.117948 0.321282 -0.199674\nenergy -564.943315\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_227\nlattice 15.402975099 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0.45622 S 0.0 0.0 -0.912320 -1.003811 0.311702\natom 9.45930 8.98345 6.21662 S 0.0 0.0 -0.796992 -0.575739 0.295445\natom -2.84615 2.84786 11.96526 S 0.0 0.0 -0.799751 0.518563 0.644071\natom 0.04275 2.96022 1.49476 S 0.0 0.0 -0.785260 -0.140283 0.333171\natom 12.64196 8.61780 4.62439 S 0.0 0.0 0.159040 0.192586 1.768480\natom 9.40685 9.41478 10.64060 S 0.0 0.0 1.269105 -0.289032 -0.548124\natom -3.08889 3.27384 7.69809 S 0.0 0.0 0.430441 0.187464 0.246703\natom 11.52624 2.66955 3.63386 Cu 0.0 0.0 0.178007 0.323487 0.306316\natom 0.77625 8.96645 2.49884 Cu 0.0 0.0 -0.117896 0.201380 0.245443\natom -2.57539 9.15917 8.37379 Cu 0.0 0.0 0.729022 -0.423189 0.392675\natom 8.39756 3.13624 9.44373 Cu 0.0 0.0 0.073393 0.220707 0.312663\natom 5.61793 0.66567 8.43490 Cu 0.0 0.0 -0.249905 0.157531 -0.027465\natom 1.22492 7.00630 9.40630 Cu 0.0 0.0 -0.324409 -0.009963 0.173526\natom 4.11427 11.10460 4.04082 Cu 0.0 0.0 -0.191831 -0.238881 -0.152240\natom 8.50870 5.10563 2.16419 Cu 0.0 0.0 0.390286 0.166547 0.114091\natom 8.15390 0.99127 2.14780 Cu 0.0 0.0 0.958431 0.061715 0.550308\natom 3.91171 7.05858 3.94693 Cu 0.0 0.0 -0.593287 0.563440 -0.613666\natom 0.84233 10.68690 10.18157 Cu 0.0 0.0 -0.773124 -0.301789 -0.002082\natom 5.26278 5.03082 8.28175 Cu 0.0 0.0 -0.024658 -0.048603 -0.221183\natom 5.33385 2.97441 0.32510 Cu 0.0 0.0 -0.155059 -0.606661 0.350608\natom 7.13637 8.74433 5.23109 Cu 0.0 0.0 0.107513 -0.007236 -0.941867\natom 3.93104 9.28260 11.30744 Cu 0.0 0.0 -0.054279 -0.082426 0.425705\natom 2.29236 3.05478 6.94063 Cu 0.0 0.0 -0.355398 -0.670930 0.250804\natom -3.96522 1.12788 11.00629 Cu 0.0 0.0 0.143495 -0.065307 0.184808\natom 10.09341 6.98320 7.41685 Cu 0.0 0.0 0.067943 0.412064 -0.481542\natom 12.67090 11.08148 1.08576 Cu 0.0 0.0 0.318328 -0.218203 0.548704\natom -0.89798 4.49077 5.28438 Cu 0.0 0.0 0.084834 0.085855 -0.071555\natom -0.90652 0.60283 5.76942 Cu 0.0 0.0 0.174943 0.118883 0.025746\natom 13.18747 7.17871 0.89452 Cu 0.0 0.0 0.030141 0.238899 -0.092813\natom 10.57360 10.89400 6.63928 Cu 0.0 0.0 -0.666176 0.126670 -0.403751\natom -3.95147 4.98063 11.59260 Cu 0.0 0.0 -0.031975 -0.105223 -0.277240\natom 8.19846 1.98544 11.98002 Cu 0.0 0.0 -0.055328 -0.064033 -0.195278\natom -2.23740 6.53498 6.04648 Cu 0.0 0.0 -0.161913 0.244207 -0.325942\natom 0.42210 10.35118 0.43048 Cu 0.0 0.0 0.227701 -0.059048 -0.475039\natom 11.15981 4.20774 5.95940 Cu 0.0 0.0 -0.326276 -0.094082 0.165285\natom 11.82935 1.46090 6.44280 Cu 0.0 0.0 -0.844942 0.020513 -0.229682\natom -4.97219 7.64322 12.04309 Cu 0.0 0.0 0.248125 0.167426 0.209344\natom -2.03497 10.23831 6.19369 Cu 0.0 0.0 0.231600 0.082310 -0.437070\natom 14.54501 4.55982 0.08900 Cu 0.0 0.0 0.045033 -0.066800 -0.278679\natom 9.25296 2.79613 4.83886 Cu 0.0 0.0 -0.223198 0.072561 0.727911\natom 4.05989 8.47657 1.70449 Cu 0.0 0.0 0.586266 -0.295570 -0.819765\natom 0.17063 8.52876 7.49350 Cu 0.0 0.0 -0.141486 0.735078 -0.039861\natom 6.19544 3.83779 10.57627 Cu 0.0 0.0 0.024396 -0.188444 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6.30428 Cu 0.0 0.0 -0.322831 0.139102 0.206135\natom 8.02163 10.08801 12.23225 Cu 0.0 0.0 -0.222858 0.131274 0.256342\natom -0.56212 5.14775 5.32292 Cu 0.0 0.0 -0.076425 -0.606583 0.030943\natom -0.80989 0.93651 5.32614 Cu 0.0 0.0 -0.238610 0.307378 0.097839\natom 13.22050 6.98149 0.64487 Cu 0.0 0.0 0.169634 -0.132976 -0.014427\natom 10.68960 10.99004 6.55602 Cu 0.0 0.0 -0.031273 -0.115594 0.335940\natom -3.98489 5.49480 11.84622 Cu 0.0 0.0 -0.086968 -0.378460 -0.357526\natom 8.50023 0.72367 12.08366 Cu 0.0 0.0 -0.557422 0.104888 0.767138\natom -2.28814 7.03102 6.10286 Cu 0.0 0.0 0.247534 0.091236 -0.365017\natom 1.18362 10.23521 0.06025 Cu 0.0 0.0 -0.211480 0.405759 0.032660\natom 12.41333 4.38140 6.00365 Cu 0.0 0.0 -0.256548 -0.029173 0.576026\natom 11.51756 1.83507 6.64050 Cu 0.0 0.0 -0.221897 -0.172319 -0.401036\natom -4.27596 7.93845 11.17010 Cu 0.0 0.0 -0.066611 0.205050 0.002508\natom -2.00185 10.57175 5.51422 Cu 0.0 0.0 0.265903 -0.184834 0.472879\natom 14.56384 4.46179 0.08498 Cu 0.0 0.0 -0.076981 -0.184061 0.460070\natom 9.29155 2.94824 6.05561 Cu 0.0 0.0 0.356971 -0.083707 -0.140828\natom 2.79320 8.86419 1.18304 Cu 0.0 0.0 0.402123 0.043113 0.408780\natom 0.71620 9.62470 7.49043 Cu 0.0 0.0 -0.026539 -0.009460 -0.138752\natom 6.67586 3.02149 11.33699 Cu 0.0 0.0 -0.187888 -0.450268 -0.364371\natom 1.35323 2.05907 12.05236 Cu 0.0 0.0 -0.289119 -0.302741 -0.339240\natom 4.97791 7.50315 6.52953 Cu 0.0 0.0 0.236291 -0.531066 -0.158393\natom 8.66633 10.67540 0.88180 Cu 0.0 0.0 -0.009262 -0.265512 0.181465\natom 3.88832 4.68600 5.21390 Cu 0.0 0.0 0.190584 -0.315626 0.305439\natom 3.59371 1.95851 5.58261 Cu 0.0 0.0 0.415568 -0.230631 -1.048671\natom 8.69567 7.62597 0.52674 Cu 0.0 0.0 -0.222160 -0.053461 0.049758\natom 5.55294 9.85689 6.89807 Cu 0.0 0.0 0.412270 0.909727 0.119868\natom 0.54967 4.55307 11.71433 Cu 0.0 0.0 0.104313 0.066133 -0.114549\natom -1.42787 2.58175 10.69710 Cu 0.0 0.0 0.124508 -0.017162 0.078447\natom 7.63841 8.49022 7.73689 Cu 0.0 0.0 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11.35346 Cu 0.0 0.0 -0.173388 0.140541 -0.189028\natom 5.11245 7.74479 6.93217 Cu 0.0 0.0 0.421601 0.056960 0.113577\natom 8.24396 10.34956 1.21142 Cu 0.0 0.0 0.182989 -0.305282 -0.034122\natom 4.38653 4.15265 5.40633 Cu 0.0 0.0 -0.153409 0.294314 0.143012\natom 3.90180 1.60979 5.13212 Cu 0.0 0.0 0.121887 -0.408556 -0.086019\natom 8.56950 7.30516 0.96892 Cu 0.0 0.0 -0.348738 0.297050 0.376032\natom 5.95239 10.92008 7.04416 Cu 0.0 0.0 -0.295917 -0.246031 -0.626765\natom 0.88052 4.37533 11.53395 Cu 0.0 0.0 0.226771 -0.072623 -0.840530\natom -1.01699 2.80331 10.20025 Cu 0.0 0.0 0.586820 -0.568188 0.271337\natom 8.45376 10.06381 8.04991 Cu 0.0 0.0 -0.608008 0.349645 0.594028\natom 10.91943 8.19009 1.63815 Cu 0.0 0.0 -0.622651 -0.182141 0.406856\natom 2.17443 3.29759 4.35635 Cu 0.0 0.0 -0.666198 -0.221666 0.294757\natom 8.76230 0.53596 8.40783 Cu 0.0 0.0 0.255561 0.533831 0.132131\natom -2.19473 6.61348 9.84131 Cu 0.0 0.0 0.082533 0.222275 -0.441892\natom 0.74102 11.61955 3.75073 Cu 0.0 0.0 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6.91319 10.21133 Cu 0.0 0.0 0.426108 -0.045893 -0.236280\natom 11.88806 11.08188 4.22145 Cu 0.0 0.0 -0.069410 -0.273711 -0.153051\natom 1.03226 5.04014 2.66085 Cu 0.0 0.0 -0.247581 0.287013 -0.203919\nenergy -565.111055\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_296\nlattice 15.463777200 0.000000000 0.000000000\nlattice 0.000000000 12.053753656 0.000000000\nlattice -6.074910447 0.000000000 12.264690081\natom 9.59413 0.96783 10.57278 S 0.0 0.0 0.346300 -0.137397 -1.121629\natom -2.68602 6.71076 7.96014 S 0.0 0.0 -1.208815 0.744476 0.423387\natom -0.06390 10.87276 2.00398 S 0.0 0.0 0.038899 0.042418 -0.360703\natom 12.69540 4.92373 4.29215 S 0.0 0.0 -0.094540 0.526336 -0.057451\natom 12.43441 0.73162 4.66904 S 0.0 0.0 0.183514 -0.372937 -0.615548\natom -0.31411 6.85536 1.70885 S 0.0 0.0 -0.196162 0.784649 0.107756\natom -3.04952 10.98798 8.00627 S 0.0 0.0 -0.282368 0.192436 -0.334371\natom 9.50949 5.18194 10.50431 S 0.0 0.0 0.670014 -0.339791 0.077834\natom 9.37229 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Cu 0.0 0.0 0.297698 0.280237 0.342135\natom 5.63955 0.68693 8.59493 Cu 0.0 0.0 -0.284858 1.164875 -0.273901\natom 0.99234 7.12437 10.02156 Cu 0.0 0.0 0.291310 -0.094609 -0.154963\natom 4.26476 11.05351 4.03807 Cu 0.0 0.0 -0.135334 0.496674 0.209101\natom 9.35048 5.14152 2.78948 Cu 0.0 0.0 -0.397765 0.698479 -0.107401\natom 7.09437 3.46705 2.87700 Cu 0.0 0.0 0.154622 -0.286286 0.626391\natom 4.61235 7.62902 3.97199 Cu 0.0 0.0 -0.776719 0.739128 -0.415097\natom 0.75140 11.20110 10.45689 Cu 0.0 0.0 -0.035332 -0.347693 -0.428419\natom 5.46156 4.57165 8.35079 Cu 0.0 0.0 -0.445057 0.542046 -0.332669\natom 5.50832 2.74619 0.92811 Cu 0.0 0.0 0.008404 0.042370 0.046395\natom 7.33602 8.87388 5.51081 Cu 0.0 0.0 0.221632 -0.231389 -0.759786\natom 4.29560 9.09480 11.25367 Cu 0.0 0.0 -0.373222 0.115962 -0.016236\natom 2.02184 3.21172 6.90396 Cu 0.0 0.0 0.802661 -0.304376 -0.032985\natom -3.82786 1.17256 11.51540 Cu 0.0 0.0 0.249634 -0.138391 -0.221822\natom 10.52571 7.01357 7.10499 Cu 0.0 0.0 0.196093 -0.514237 0.069269\natom 12.73284 10.79750 1.00759 Cu 0.0 0.0 0.322784 1.110356 0.316976\natom -0.61292 5.04408 5.01739 Cu 0.0 0.0 -0.099418 -0.146983 -0.011236\natom -1.00797 0.89234 5.59127 Cu 0.0 0.0 0.659388 -0.014512 0.178730\natom 13.11639 6.88375 0.41410 Cu 0.0 0.0 0.120379 0.761308 0.151347\natom 10.25236 11.24357 7.04142 Cu 0.0 0.0 0.486852 -0.703417 0.162744\natom -3.78914 4.90979 11.64754 Cu 0.0 0.0 -0.562557 0.868287 -0.307699\natom 7.97327 1.00806 12.01927 Cu 0.0 0.0 -0.320661 -0.261778 0.669270\natom -2.66364 6.77284 5.72900 Cu 0.0 0.0 0.139583 0.019303 -0.109989\natom 1.20070 10.29289 0.05535 Cu 0.0 0.0 0.128534 -0.142367 0.170485\natom 11.56341 4.52622 6.20016 Cu 0.0 0.0 -0.422768 -0.016949 -0.036187\natom 11.38589 1.88456 6.19868 Cu 0.0 0.0 0.372210 0.381362 0.737046\natom 1.40326 7.62107 0.05935 Cu 0.0 0.0 -0.033455 0.158910 -0.065999\natom -1.58357 10.14682 6.04642 Cu 0.0 0.0 -0.379767 0.174140 -0.180950\natom 14.96000 4.73947 0.51353 Cu 0.0 0.0 0.006641 -0.111737 -0.663340\natom 9.29990 3.14755 5.15272 Cu 0.0 0.0 0.061569 -0.071409 -0.358628\natom 3.53691 9.25165 1.30906 Cu 0.0 0.0 -0.125188 0.014477 -0.355908\natom 0.12350 8.58777 6.97217 Cu 0.0 0.0 0.252618 -0.140246 0.211007\natom 6.05665 1.96577 10.95461 Cu 0.0 0.0 -0.283723 0.768305 -0.764843\natom 1.18112 1.75131 11.43049 Cu 0.0 0.0 0.333113 0.363145 -0.628417\natom 5.30761 7.55794 7.06217 Cu 0.0 0.0 0.075613 0.089545 0.076289\natom 8.25350 9.94587 0.90472 Cu 0.0 0.0 0.156252 0.411619 -0.017478\natom 4.20292 4.21519 4.99966 Cu 0.0 0.0 0.439937 0.186328 0.429797\natom 4.21872 1.27195 5.32118 Cu 0.0 0.0 -0.390136 0.091093 -0.241003\natom 8.58249 7.39808 0.79129 Cu 0.0 0.0 0.151405 0.076977 -0.139024\natom 5.41339 10.15269 6.72431 Cu 0.0 0.0 0.421021 0.246152 -0.150048\natom 1.18172 4.35109 10.91327 Cu 0.0 0.0 -0.019770 0.068034 0.017337\natom -2.18879 3.57592 9.94910 Cu 0.0 0.0 0.202534 -0.045578 0.220734\natom 7.61115 8.85323 7.83294 Cu 0.0 0.0 0.134966 -0.097336 0.851080\natom 11.51023 8.83597 2.30743 Cu 0.0 0.0 0.491918 0.338112 -0.235292\natom 0.09713 2.47268 3.64238 Cu 0.0 0.0 0.258676 0.426328 0.371619\natom 8.37767 0.47399 8.19502 Cu 0.0 0.0 -0.417862 -0.209120 0.491987\natom -2.26835 6.57991 10.23625 Cu 0.0 0.0 0.072291 -0.082292 0.129992\natom 0.71424 11.84636 3.95468 Cu 0.0 0.0 -0.341936 -0.374358 0.182295\natom 11.74232 5.85731 2.23398 Cu 0.0 0.0 -0.330638 -0.045910 0.161296\natom 8.62871 1.18077 2.33480 Cu 0.0 0.0 0.056734 -0.224896 0.150444\natom 2.27539 6.88268 4.12977 Cu 0.0 0.0 0.192496 0.044154 -0.612151\natom -2.04173 11.34745 9.95543 Cu 0.0 0.0 0.484241 -0.259775 1.108367\natom 7.93886 5.07659 7.84698 Cu 0.0 0.0 -0.153518 0.274031 0.347679\natom 10.71752 2.46371 9.24247 Cu 0.0 0.0 0.256356 -0.349581 0.210532\natom -4.25719 8.09373 9.29761 Cu 0.0 0.0 0.727486 -0.945194 -0.793172\natom -1.60068 10.02401 3.25751 Cu 0.0 0.0 -0.278530 -0.164172 0.049777\natom 13.58714 4.00922 2.50877 Cu 0.0 0.0 0.517779 -0.307518 -0.255973\natom 5.57215 0.94795 3.09760 Cu 0.0 0.0 0.272462 0.156177 -0.187015\natom 6.72896 6.68660 2.38717 Cu 0.0 0.0 -0.256522 -0.018980 0.335159\natom 3.67571 11.09697 8.86140 Cu 0.0 0.0 -0.088144 -0.340246 -0.388276\natom 3.12084 5.15555 9.24911 Cu 0.0 0.0 -0.184530 0.230609 1.072112\natom 1.05251 0.68247 7.85059 Cu 0.0 0.0 0.190857 0.169244 0.174255\natom 5.41042 6.02785 10.84761 Cu 0.0 0.0 -0.263230 -0.059625 0.128623\natom 8.87918 11.70123 4.72201 Cu 0.0 0.0 -0.350901 -0.217265 -0.302340\natom 4.71735 5.14723 1.62155 Cu 0.0 0.0 -0.037088 0.297995 -0.184864\natom 3.57371 1.10987 1.44231 Cu 0.0 0.0 -0.197962 -0.265239 -0.091625\natom 8.87277 6.99746 4.73890 Cu 0.0 0.0 0.146668 -0.004404 -0.370001\natom 5.79905 11.57054 10.82641 Cu 0.0 0.0 -0.057973 -0.331349 0.238891\natom 0.48660 5.87614 7.54282 Cu 0.0 0.0 0.132922 -0.203636 0.016477\natom 3.51808 2.53755 9.07380 Cu 0.0 0.0 -0.056264 -0.171712 0.096410\natom 3.21469 8.21910 8.95145 Cu 0.0 0.0 -0.033383 0.163191 -0.104063\natom 5.96330 9.79846 2.91535 Cu 0.0 0.0 0.664333 -0.696710 0.053760\natom 2.48846 3.07570 3.82200 Cu 0.0 0.0 -0.235639 -1.089542 -0.184870\natom 13.81819 1.00379 2.96669 Cu 0.0 0.0 -0.369088 -0.609779 -0.279585\natom 13.45681 7.44681 3.39775 Cu 0.0 0.0 0.944601 -0.716836 -1.107859\natom -4.54319 11.14495 9.81017 Cu 0.0 0.0 -0.492316 -0.092611 -0.117205\natom -4.10855 5.01804 8.98035 Cu 0.0 0.0 -0.396266 0.419441 0.229571\natom 3.65543 0.99317 11.34404 Cu 0.0 0.0 0.020508 -0.357919 -0.121245\natom 2.67714 6.95343 6.68645 Cu 0.0 0.0 0.504458 0.724977 0.326081\natom 5.72337 11.00336 0.84044 Cu 0.0 0.0 -0.347741 -0.068829 -0.508611\natom 6.94986 4.67187 5.49527 Cu 0.0 0.0 -0.031709 -0.054092 -0.218147\natom 7.14784 2.26127 6.70852 Cu 0.0 0.0 0.065489 0.165183 -0.016782\natom -0.98552 8.46758 11.40905 Cu 0.0 0.0 -0.018185 -0.023036 -0.369429\natom 2.22166 10.12344 5.30081 Cu 0.0 0.0 -0.941719 0.415955 0.742094\natom 10.76196 3.61899 0.73302 Cu 0.0 0.0 -0.708160 -0.384422 0.111482\natom 1.59591 3.05865 0.91854 Cu 0.0 0.0 -1.216556 -0.277737 0.943070\natom 10.22686 9.48264 4.61806 Cu 0.0 0.0 -0.095136 0.038053 -0.622159\natom 7.51090 9.73788 10.62657 Cu 0.0 0.0 0.555934 0.004632 -0.754704\natom 0.15190 3.14460 8.49006 Cu 0.0 0.0 -0.219232 -0.179002 0.418170\natom -2.44141 1.19258 8.53938 Cu 0.0 0.0 0.162735 -0.129620 -0.135526\natom 8.54089 7.07569 9.52146 Cu 0.0 0.0 1.061552 0.229869 0.417672\natom 11.42474 11.35794 3.22063 Cu 0.0 0.0 0.565355 0.156622 0.181819\natom 0.90887 5.20568 2.46757 Cu 0.0 0.0 0.103170 -0.237376 0.270010\nenergy -564.152503\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_312\nlattice 15.400728027 0.000000000 0.000000000\nlattice 0.000000000 12.004607889 0.000000000\nlattice -6.050141720 0.000000000 12.214684280\natom 9.45458 0.97680 10.34020 S 0.0 0.0 -0.071478 0.048476 0.217869\natom -3.37910 6.86048 8.22454 S 0.0 0.0 -0.472818 0.108462 -0.859823\natom -0.07626 10.87071 2.01645 S 0.0 0.0 -0.741120 0.152005 -0.245544\natom 12.78363 4.98881 4.30825 S 0.0 0.0 -1.124751 0.880564 0.255728\natom 12.48062 1.07683 4.27994 S 0.0 0.0 -0.316347 -1.027131 -0.094489\natom -0.04479 6.61087 1.55906 S 0.0 0.0 0.308733 0.461656 0.520550\natom -2.95597 10.83931 7.88751 S 0.0 0.0 -0.546322 1.118162 0.026506\natom 9.37507 5.12144 10.53558 S 0.0 0.0 0.279298 -0.411908 0.419070\natom 8.94845 0.95941 6.00327 S 0.0 0.0 0.291624 0.068005 -0.141155\natom -2.38905 7.15920 11.92073 S 0.0 0.0 -1.162472 -0.626538 0.818775\natom 0.31585 10.87958 6.05820 S 0.0 0.0 -0.093190 0.109477 -0.217973\natom 12.10077 4.76210 0.01304 S 0.0 0.0 1.034410 0.346477 0.862563\natom 11.82591 0.92861 0.28207 S 0.0 0.0 -0.191254 0.177209 -0.876314\natom -0.09276 6.75665 6.04221 S 0.0 0.0 1.604115 -0.825764 -0.211824\natom 3.06876 11.17691 0.12659 S 0.0 0.0 0.877242 0.845130 -1.087003\natom 9.07478 5.09955 6.29768 S 0.0 0.0 0.378950 -0.071979 0.924003\natom 3.08099 0.87762 7.19200 S 0.0 0.0 0.947365 0.539492 0.086533\natom 2.97503 7.00409 11.12474 S 0.0 0.0 0.420024 0.079390 -0.870386\natom 5.95981 10.91539 4.79588 S 0.0 0.0 -0.343252 0.677178 0.136649\natom 6.57219 4.79908 1.56159 S 0.0 0.0 -0.401619 0.865473 0.179067\natom 6.48279 0.78268 0.95681 S 0.0 0.0 0.209841 0.000963 0.733182\natom 6.20503 7.02714 5.09847 S 0.0 0.0 0.008343 -0.730589 -0.306543\natom 2.92413 10.82322 11.16908 S 0.0 0.0 -0.469053 0.058517 -0.057050\natom 3.45781 4.96161 7.07879 S 0.0 0.0 0.001784 0.459721 -0.096769\natom -0.22452 0.76900 9.62689 S 0.0 0.0 0.211273 -0.104000 0.206687\natom 6.63466 6.92411 8.97127 S 0.0 0.0 0.001732 -0.081359 0.218773\natom 9.55217 10.71412 2.66158 S 0.0 0.0 -0.253353 -0.356559 0.004241\natom 2.90636 5.22849 3.03039 S 0.0 0.0 -0.037243 -0.005050 -0.052137\natom 2.66770 0.83435 3.46031 S 0.0 0.0 -0.706503 -0.203968 -0.901672\natom 9.86571 7.08480 2.82929 S 0.0 0.0 -0.528982 -2.050110 -0.616181\natom 6.71180 11.10966 8.54915 S 0.0 0.0 1.331900 0.427828 1.083397\natom -0.20352 4.77790 9.74260 S 0.0 0.0 -0.148008 0.634375 -0.190254\natom 6.38845 2.83149 8.82704 S 0.0 0.0 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-3.05602 3.19818 7.82268 S 0.0 0.0 -0.176969 0.067144 -0.221873\natom 11.56689 3.15615 3.83739 Cu 0.0 0.0 -0.156630 -0.055853 -0.177253\natom 0.70789 8.68161 2.27550 Cu 0.0 0.0 0.002292 -0.201218 0.265993\natom -2.29511 8.86229 8.53595 Cu 0.0 0.0 0.436632 -0.272258 0.262213\natom 8.63012 2.99254 9.33957 Cu 0.0 0.0 -0.158537 -0.016122 0.463883\natom 5.18784 0.73318 8.13152 Cu 0.0 0.0 -0.081488 0.672069 0.269998\natom 0.94326 6.90049 9.81026 Cu 0.0 0.0 -0.331470 -0.008271 0.221018\natom 3.78750 10.92840 3.87353 Cu 0.0 0.0 0.337318 -0.162965 -0.155901\natom 8.99749 4.85542 1.92577 Cu 0.0 0.0 -0.179323 -0.359283 0.375068\natom 8.62649 0.78005 2.02017 Cu 0.0 0.0 -0.456929 0.019830 0.019667\natom 4.31232 7.26665 3.96403 Cu 0.0 0.0 -0.443957 0.118743 0.106102\natom 0.60234 10.51604 10.69187 Cu 0.0 0.0 0.429782 0.198204 -0.482430\natom 5.64792 5.04615 8.29947 Cu 0.0 0.0 -0.081667 -0.697598 -0.192382\natom 5.44310 2.86819 1.05089 Cu 0.0 0.0 -0.148057 0.142129 -0.258956\natom 7.17973 9.05444 5.21104 Cu 0.0 0.0 0.245095 -0.446805 0.418171\natom 4.46850 9.26065 11.12519 Cu 0.0 0.0 0.306807 -0.334017 0.208098\natom 2.26961 3.05527 6.77589 Cu 0.0 0.0 -0.353764 0.114041 -0.013309\natom -3.90401 1.03284 11.46200 Cu 0.0 0.0 0.001015 0.337714 -0.325268\natom 10.04011 7.25985 6.84980 Cu 0.0 0.0 0.244773 -0.320630 0.146804\natom 13.21623 11.02955 0.89163 Cu 0.0 0.0 0.112597 -0.567873 -0.018682\natom -0.51286 4.85669 5.10751 Cu 0.0 0.0 0.253876 -1.088299 -0.207555\natom -1.04706 0.72587 5.52506 Cu 0.0 0.0 -0.099741 -0.138001 -0.186971\natom 13.36150 6.86658 0.76794 Cu 0.0 0.0 -0.569603 0.126375 -0.339053\natom 10.12348 11.14436 6.92507 Cu 0.0 0.0 0.593908 0.253869 -0.057492\natom -3.89692 5.17103 11.34088 Cu 0.0 0.0 0.395195 0.075991 0.300955\natom 7.87836 1.23229 12.01207 Cu 0.0 0.0 0.600315 0.231568 -0.311218\natom -2.28976 7.34384 6.19682 Cu 0.0 0.0 -0.380809 -0.111907 0.356839\natom 0.90592 10.61238 0.07715 Cu 0.0 0.0 -0.021947 -0.526168 -0.337515\natom 11.21629 4.63957 6.08514 Cu 0.0 0.0 0.631695 -0.363444 -0.142808\natom 11.47399 1.84913 6.17495 Cu 0.0 0.0 -0.256208 0.011497 0.228798\natom -4.72531 7.79138 12.13660 Cu 0.0 0.0 -0.093923 -0.235496 -0.291658\natom -1.97425 10.19444 5.89992 Cu 0.0 0.0 0.234500 0.468924 -0.024111\natom 14.39111 4.08618 0.16464 Cu 0.0 0.0 -0.556085 0.585623 -0.525095\natom 9.22431 3.12924 5.09010 Cu 0.0 0.0 -0.022337 -0.006849 0.451603\natom 3.15359 9.23676 0.94540 Cu 0.0 0.0 0.062331 -1.208447 0.413546\natom -0.14476 8.70876 6.83661 Cu 0.0 0.0 0.152332 1.033735 -0.156566\natom 4.89805 3.75290 10.52765 Cu 0.0 0.0 0.148448 -0.525528 -1.048912\natom 1.18373 1.85350 11.20431 Cu 0.0 0.0 -0.813557 -0.325455 -0.019585\natom 4.99915 8.31554 8.33002 Cu 0.0 0.0 -0.257787 -0.231200 -0.043920\natom 8.01583 10.44061 0.99761 Cu 0.0 0.0 -0.396911 -0.277273 -0.135587\natom 4.05055 4.30653 4.67827 Cu 0.0 0.0 0.299631 -0.319010 0.353422\natom 3.83077 1.60663 5.02926 Cu 0.0 0.0 0.612574 0.439723 0.812241\natom 8.32052 7.15493 0.99878 Cu 0.0 0.0 0.178705 0.211878 0.312601\natom 5.31374 10.44631 7.10559 Cu 0.0 0.0 -0.354311 -0.281023 -1.135853\natom 1.12518 4.64450 11.67392 Cu 0.0 0.0 -0.277880 0.128297 -0.280548\natom -1.30573 2.55086 10.57811 Cu 0.0 0.0 -0.008750 -0.009660 -0.035862\natom 7.46860 8.82404 8.06806 Cu 0.0 0.0 0.039688 0.204694 -0.202483\natom 10.45443 8.74277 1.60883 Cu 0.0 0.0 0.320506 0.807210 -0.591092\natom 0.40520 2.33976 3.62951 Cu 0.0 0.0 0.013737 -0.045044 0.864332\natom 8.66463 0.73061 8.19653 Cu 0.0 0.0 -0.174718 -0.295994 0.199312\natom -1.97525 6.28816 9.83168 Cu 0.0 0.0 0.495945 -0.286401 0.350103\natom 0.76393 11.69432 3.87744 Cu 0.0 0.0 -0.024257 -0.126497 0.636625\natom 11.45416 5.49355 2.10991 Cu 0.0 0.0 0.169950 -0.109548 0.207235\natom 11.20002 12.00074 2.11239 Cu 0.0 0.0 0.408159 0.209588 0.561218\natom 1.61709 6.57877 4.30650 Cu 0.0 0.0 -0.516641 0.156065 0.445606\natom -1.82946 11.15477 10.15416 Cu 0.0 0.0 -0.323224 0.021610 0.381308\natom 8.47378 5.28515 8.51925 Cu 0.0 0.0 -0.291915 0.348682 -0.815617\natom -4.45212 1.94910 9.00188 Cu 0.0 0.0 0.146912 0.374676 -0.046818\natom 10.66299 8.41691 9.11260 Cu 0.0 0.0 -0.313353 0.113297 0.242159\natom -1.56062 9.96863 3.30079 Cu 0.0 0.0 -0.278408 -0.485308 0.103815\natom 13.73967 3.97375 2.71086 Cu 0.0 0.0 0.336940 -0.819309 -0.583271\natom 5.92778 1.35655 3.15688 Cu 0.0 0.0 0.070707 -0.219348 -0.260031\natom 6.54915 7.05855 2.75279 Cu 0.0 0.0 -0.088029 -0.071413 0.494950\natom 3.01547 11.62749 9.14424 Cu 0.0 0.0 -0.024791 0.003903 -0.523111\natom 3.35876 6.03323 9.07133 Cu 0.0 0.0 -0.095102 -0.063640 0.046690\natom 0.93017 0.74594 7.66931 Cu 0.0 0.0 -0.694347 -0.219155 0.041993\natom 5.26306 6.14718 10.73979 Cu 0.0 0.0 -0.103324 1.119268 -0.267892\natom 8.20036 11.21140 4.38288 Cu 0.0 0.0 0.004602 0.466955 0.202930\natom 4.49282 6.02257 1.56161 Cu 0.0 0.0 -0.009942 -0.094018 -0.233662\natom 3.75924 1.04894 1.35025 Cu 0.0 0.0 -0.166689 -0.284036 0.339482\natom 8.66395 6.58551 4.76169 Cu 0.0 0.0 -0.422704 0.486288 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7.78762 S 0.0 0.0 0.307424 0.468046 -0.003713\natom 11.73155 2.72999 3.65429 Cu 0.0 0.0 -0.205403 0.640337 -0.151061\natom 0.66613 8.60344 2.43088 Cu 0.0 0.0 0.355992 -0.185770 -0.193305\natom -2.29146 9.07539 8.56173 Cu 0.0 0.0 -0.042250 -0.301201 0.203443\natom 8.80854 2.86845 9.60856 Cu 0.0 0.0 -0.320755 -0.172987 0.168747\natom 5.30302 0.86141 8.63190 Cu 0.0 0.0 -0.108091 0.111894 -0.000144\natom 0.76235 6.97487 10.00323 Cu 0.0 0.0 0.193386 0.458556 0.543800\natom 3.73917 11.16368 3.99209 Cu 0.0 0.0 0.098091 -0.299638 -0.050441\natom 8.67336 4.89055 2.05390 Cu 0.0 0.0 -0.160631 -0.313052 -0.310123\natom 8.64053 1.22491 1.89864 Cu 0.0 0.0 -0.531404 -0.329692 0.082656\natom 3.87060 7.15001 3.98688 Cu 0.0 0.0 0.343764 -0.245635 0.192519\natom 0.86747 10.99916 10.12815 Cu 0.0 0.0 0.553844 0.504072 -0.015565\natom 5.37338 4.54608 7.96600 Cu 0.0 0.0 -0.790988 0.612881 0.188971\natom 5.30235 2.96679 0.74196 Cu 0.0 0.0 -0.279765 0.053589 0.061152\natom 7.17235 8.95634 5.48649 Cu 0.0 0.0 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0.229835\natom 5.98003 10.54222 7.01848 Cu 0.0 0.0 -0.268979 0.613439 -0.609902\natom 0.90330 4.52668 11.09130 Cu 0.0 0.0 -0.015860 -0.009756 0.061747\natom -1.32816 3.08064 10.41773 Cu 0.0 0.0 -0.493890 -0.065188 0.008047\natom 9.10624 9.49641 8.40497 Cu 0.0 0.0 -0.542911 -0.259645 -0.523702\natom 10.54298 9.22840 1.73106 Cu 0.0 0.0 0.204844 -0.051950 0.245926\natom 1.86215 3.19365 4.41637 Cu 0.0 0.0 -0.141626 0.355328 -0.128984\natom 8.65817 0.51941 8.36583 Cu 0.0 0.0 -0.022819 -0.077019 -0.417244\natom -2.29063 6.73982 10.04842 Cu 0.0 0.0 -0.249279 0.046797 0.036677\natom 0.78869 11.47440 3.73836 Cu 0.0 0.0 0.042456 0.785562 0.690769\natom 11.47010 5.64750 2.12577 Cu 0.0 0.0 0.841797 -0.701578 -0.310140\natom 11.01177 0.57843 1.86130 Cu 0.0 0.0 0.197024 -0.015556 -0.043231\natom 1.22968 6.56272 4.18906 Cu 0.0 0.0 0.397033 0.185775 -0.533834\natom -1.52602 10.80217 10.42185 Cu 0.0 0.0 0.048520 -0.018238 -0.396147\natom 7.92076 4.83320 8.23419 Cu 0.0 0.0 -0.018300 0.409796 0.050275\natom -3.94273 2.51079 9.87109 Cu 0.0 0.0 0.017620 0.266824 0.223522\natom -4.55916 7.98488 9.42777 Cu 0.0 0.0 0.221198 0.396508 0.242025\natom 13.87117 9.54453 2.93125 Cu 0.0 0.0 -0.109165 0.414871 0.021803\natom -1.40621 3.62781 3.03879 Cu 0.0 0.0 -0.153347 -0.155868 -0.157467\natom 6.05605 0.98838 3.61087 Cu 0.0 0.0 0.089056 0.351384 -0.322776\natom 6.52273 6.78567 2.73100 Cu 0.0 0.0 -0.159560 0.079069 -0.461882\natom 3.34673 10.94069 8.63529 Cu 0.0 0.0 -0.013092 -0.001600 0.434844\natom 3.01646 5.57841 9.56349 Cu 0.0 0.0 0.011887 -0.100686 -0.196458\natom 1.10921 0.20152 7.76368 Cu 0.0 0.0 -0.048169 0.377541 0.179621\natom 5.12377 6.74708 10.50326 Cu 0.0 0.0 0.292989 -0.078557 -0.046372\natom 8.33426 11.37061 4.39522 Cu 0.0 0.0 -0.309672 0.456973 1.103821\natom 4.01440 5.33921 1.45196 Cu 0.0 0.0 0.281696 -0.159501 0.221087\natom 4.17980 0.49294 1.84301 Cu 0.0 0.0 -0.708562 0.503849 0.133844\natom 8.51653 6.09526 4.09474 Cu 0.0 0.0 -0.112062 0.324024 0.920042\natom 5.80361 11.03217 11.01922 Cu 0.0 0.0 0.246308 0.819800 -0.409801\natom 0.95847 5.79446 7.92616 Cu 0.0 0.0 0.062632 -0.810195 -0.092027\natom 2.96305 2.39870 9.28766 Cu 0.0 0.0 -0.376596 -0.385463 -0.239446\natom 3.60853 8.44318 9.05850 Cu 0.0 0.0 -0.562347 -0.238037 -0.236064\natom 5.48287 9.48018 3.23817 Cu 0.0 0.0 0.111306 -0.286517 -0.380803\natom 6.21831 3.58996 3.10914 Cu 0.0 0.0 0.319425 0.713190 -0.944335\natom 13.74706 1.16261 2.84686 Cu 0.0 0.0 0.354621 -0.100438 -0.423985\natom -1.29721 7.00319 3.41310 Cu 0.0 0.0 -0.206902 0.041096 -0.118138\natom -4.68435 10.69262 9.66255 Cu 0.0 0.0 0.380924 0.151717 0.212082\natom 10.57580 4.76256 8.65377 Cu 0.0 0.0 0.531670 -0.061357 -0.271865\natom 3.71797 0.98293 11.40162 Cu 0.0 0.0 0.525492 0.658514 0.307460\natom 2.53480 7.54988 6.78049 Cu 0.0 0.0 -0.334903 -0.538353 -0.101635\natom 5.79484 10.98424 0.86999 Cu 0.0 0.0 0.006181 -0.680788 -0.287408\natom 6.64317 4.95970 5.79592 Cu 0.0 0.0 0.078628 0.412810 -0.470822\natom 7.34928 2.85016 6.85061 Cu 0.0 0.0 0.305209 -0.869851 0.282557\natom -0.96136 8.40340 11.57072 Cu 0.0 0.0 0.322996 0.123072 -0.046541\natom 1.70149 9.70799 5.02821 Cu 0.0 0.0 0.494988 -0.725456 0.395173\natom 11.19334 3.07832 0.70713 Cu 0.0 0.0 0.017619 0.066578 0.468611\natom 2.09418 2.35857 1.90076 Cu 0.0 0.0 0.590285 0.046588 0.179024\natom 10.33836 8.78125 4.31616 Cu 0.0 0.0 0.065755 -0.568139 -0.425498\natom 5.89067 9.24446 8.99449 Cu 0.0 0.0 0.523743 -0.721595 0.604441\natom -1.14274 3.80931 7.90099 Cu 0.0 0.0 0.308959 -0.339936 -0.691805\natom -2.36795 1.21533 8.28698 Cu 0.0 0.0 0.203000 0.092259 0.005930\natom 8.53458 7.21069 9.64141 Cu 0.0 0.0 -0.409408 -0.413745 -0.018811\natom 11.55690 10.92225 3.71225 Cu 0.0 0.0 0.189831 -0.055151 0.044155\natom 0.69592 4.64286 2.31510 Cu 0.0 0.0 0.344125 0.135702 -0.065281\nenergy -565.990879\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_381\nlattice 15.385741848 0.000000000 0.000000000\nlattice 0.000000000 11.992926415 0.000000000\nlattice 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0.052221 -0.147774\natom -2.92174 3.34768 11.88610 S 0.0 0.0 0.050199 0.007954 0.053206\natom -0.01405 3.10105 1.74874 S 0.0 0.0 -1.256553 -0.991026 -0.911636\natom 12.54325 8.73734 4.60141 S 0.0 0.0 -0.668099 0.095902 0.446299\natom 9.62451 9.13033 10.77019 S 0.0 0.0 -0.951899 -0.199389 -1.096222\natom -3.10511 3.22896 7.68996 S 0.0 0.0 -0.191980 0.090752 0.181160\natom 11.71159 3.05493 3.42301 Cu 0.0 0.0 -0.614346 -0.362901 0.023987\natom 0.79889 9.09650 2.66785 Cu 0.0 0.0 0.238005 -0.467958 0.174566\natom -2.08133 8.83859 8.65215 Cu 0.0 0.0 -0.179033 0.047382 0.078499\natom 8.38345 2.76307 9.68602 Cu 0.0 0.0 0.229534 0.245422 0.262122\natom 5.54077 0.71040 7.81966 Cu 0.0 0.0 -0.543723 0.104156 0.062864\natom 0.99210 6.95531 9.77437 Cu 0.0 0.0 -0.602864 0.096841 -0.245447\natom 4.20764 11.27650 3.97750 Cu 0.0 0.0 -0.278442 -0.155795 -0.117456\natom 8.13159 5.19745 2.25772 Cu 0.0 0.0 0.413031 0.147334 -0.261297\natom 8.36442 1.04172 2.16453 Cu 0.0 0.0 0.107403 0.359153 0.029200\natom 4.04014 7.43026 4.19327 Cu 0.0 0.0 0.025806 -0.391033 -0.250307\natom 1.08559 10.74557 10.13730 Cu 0.0 0.0 0.244089 0.321486 0.307173\natom 5.43244 4.84036 8.49903 Cu 0.0 0.0 -0.042731 0.001572 -0.263977\natom 4.95985 2.74918 0.76036 Cu 0.0 0.0 0.650124 -0.342751 0.513306\natom 7.22194 8.55888 5.13075 Cu 0.0 0.0 0.101469 0.485354 0.064326\natom 4.08575 8.93844 11.41566 Cu 0.0 0.0 -0.063231 -0.122843 -0.190502\natom 2.43992 3.21396 7.47876 Cu 0.0 0.0 -0.077031 -0.429449 -0.733630\natom -3.69931 1.28064 11.77260 Cu 0.0 0.0 -0.000236 -0.476267 -0.203761\natom 9.59453 7.14221 6.76060 Cu 0.0 0.0 0.064258 0.528379 -0.184228\natom 12.93847 11.01270 0.90444 Cu 0.0 0.0 0.145432 0.063889 0.019712\natom -0.67141 5.34105 5.72446 Cu 0.0 0.0 0.298332 -0.441454 -0.161557\natom -1.03351 1.21550 5.48592 Cu 0.0 0.0 -0.822244 -0.480912 -0.710894\natom 13.53716 7.27495 0.93480 Cu 0.0 0.0 -0.455545 0.179711 -0.179631\natom 10.44943 11.14808 6.98596 Cu 0.0 0.0 0.042278 -0.186179 -0.387224\natom -3.95394 5.16669 11.07826 Cu 0.0 0.0 0.068204 0.464504 0.580785\natom 14.40140 1.55724 0.07078 Cu 0.0 0.0 -0.175878 0.077724 -0.485831\natom 12.39439 6.48209 5.81842 Cu 0.0 0.0 -0.038046 -0.033224 -0.289350\natom 1.04454 10.25970 0.33599 Cu 0.0 0.0 0.362430 0.420358 0.063403\natom 11.23577 4.09764 5.81212 Cu 0.0 0.0 0.196093 0.306465 0.077735\natom 11.34717 1.45856 5.99899 Cu 0.0 0.0 -0.229240 0.458238 0.843086\natom -4.88353 7.68744 12.16439 Cu 0.0 0.0 0.051403 -0.373407 0.449964\natom -2.41629 11.10057 5.98287 Cu 0.0 0.0 -0.056673 -0.124752 -0.355872\natom 14.06539 4.26781 0.26329 Cu 0.0 0.0 0.564317 -0.090832 -0.077447\natom 9.07661 3.06429 4.99900 Cu 0.0 0.0 0.095513 -0.073796 -0.030946\natom 3.26713 9.15368 1.12967 Cu 0.0 0.0 -0.131499 -0.290807 -0.245339\natom -0.75901 9.07992 5.52474 Cu 0.0 0.0 0.102919 0.030057 0.034120\natom 6.22595 3.07567 11.14685 Cu 0.0 0.0 -0.035081 -0.198247 0.345145\natom 1.04384 1.46412 11.32789 Cu 0.0 0.0 0.052973 0.431111 0.163237\natom 5.40090 7.63747 6.67094 Cu 0.0 0.0 -0.331470 0.252398 0.495228\natom 8.19074 10.20427 0.59092 Cu 0.0 0.0 0.040328 -0.185457 0.244075\natom 4.33223 4.14579 5.18777 Cu 0.0 0.0 0.336363 -0.551805 0.367652\natom 3.73865 1.60189 5.41475 Cu 0.0 0.0 -0.207445 -0.174537 -0.155598\natom 8.32237 7.46590 0.77550 Cu 0.0 0.0 0.261253 0.027276 0.048673\natom 5.56080 10.18706 6.52803 Cu 0.0 0.0 -0.120393 0.271156 0.429619\natom 0.90273 4.27241 11.65507 Cu 0.0 0.0 -0.421922 0.020559 0.088453\natom -1.32779 2.49177 10.47752 Cu 0.0 0.0 -0.066978 -0.009727 -0.291503\natom 7.50996 9.04857 7.85521 Cu 0.0 0.0 -0.114700 -0.644251 -0.023218\natom 10.73365 9.18162 1.73432 Cu 0.0 0.0 -0.426919 -0.210149 0.411827\natom 1.68706 3.88963 4.75733 Cu 0.0 0.0 0.421421 0.255337 -0.128322\natom 8.90235 0.55317 8.27384 Cu 0.0 0.0 -0.356851 0.199562 0.968593\natom -1.91232 6.50406 9.88035 Cu 0.0 0.0 -0.013697 -0.067394 0.369268\natom 0.70885 11.72524 3.95941 Cu 0.0 0.0 0.192362 0.149447 -0.950886\natom 11.46683 5.56791 2.08637 Cu 0.0 0.0 -0.205546 0.221663 0.755158\natom 11.12837 0.93821 1.95062 Cu 0.0 0.0 -0.170357 -0.128714 0.227141\natom 1.10717 6.89431 4.41461 Cu 0.0 0.0 0.409095 -0.105304 -0.443211\natom -1.62829 10.99574 10.14678 Cu 0.0 0.0 -0.013272 -0.058563 0.376513\natom 7.89455 5.38054 8.23545 Cu 0.0 0.0 0.195167 0.220683 0.185867\natom -4.33780 2.69159 9.58719 Cu 0.0 0.0 0.148522 -0.010422 -0.226214\natom 10.42286 7.71443 9.04380 Cu 0.0 0.0 0.180430 0.343856 0.407769\natom 13.59898 9.41325 2.84851 Cu 0.0 0.0 0.411101 0.547253 -0.642139\natom -0.68934 3.68111 3.74432 Cu 0.0 0.0 -0.600767 -0.011363 0.699921\natom 5.75971 1.15659 3.36089 Cu 0.0 0.0 0.168844 -0.403426 0.093433\natom 6.38806 7.14563 2.63964 Cu 0.0 0.0 0.047498 -0.128173 0.064556\natom 3.21022 11.18077 8.72892 Cu 0.0 0.0 0.113851 -0.619359 -0.099589\natom 2.92513 4.79116 9.44668 Cu 0.0 0.0 0.299573 0.081449 0.381697\natom 0.79453 0.45792 7.60935 Cu 0.0 0.0 0.258115 0.033999 0.331234\natom 5.06463 6.41802 10.53342 Cu 0.0 0.0 -0.071002 -0.195166 0.666495\natom 8.74565 10.95480 4.44779 Cu 0.0 0.0 -0.025090 0.028731 0.033567\natom 3.54443 5.02070 1.41742 Cu 0.0 0.0 0.589850 0.094526 -0.614166\natom 3.89299 0.51950 1.67325 Cu 0.0 0.0 -0.211794 0.375796 0.197401\natom 8.49610 6.58551 4.36667 Cu 0.0 0.0 -0.229787 -0.505967 0.349418\natom 5.35664 11.62425 10.17223 Cu 0.0 0.0 0.338571 -0.174452 0.098649\natom 1.15555 5.17702 7.77428 Cu 0.0 0.0 -0.311910 0.969390 -0.102685\natom 3.94218 2.34269 9.26197 Cu 0.0 0.0 -0.013668 0.177291 0.664866\natom 3.02818 8.36965 9.09589 Cu 0.0 0.0 0.170657 0.738510 -0.961676\natom 6.08672 9.67955 3.02232 Cu 0.0 0.0 0.062660 0.005973 0.143035\natom 6.72045 3.34718 3.28666 Cu 0.0 0.0 0.081021 0.143585 0.156367\natom 14.07917 1.21330 2.58036 Cu 0.0 0.0 0.075805 0.108580 0.212462\natom -1.33035 7.12343 3.72602 Cu 0.0 0.0 -0.031493 -0.175596 -0.252433\natom -4.20539 10.27979 9.69921 Cu 0.0 0.0 -0.862454 -0.412546 0.637965\natom 11.05511 5.10139 8.71689 Cu 0.0 0.0 -0.367556 -0.100313 -0.305517\natom 3.50289 1.11508 11.92630 Cu 0.0 0.0 0.442182 0.145683 -0.011099\natom 2.85233 7.29819 6.45952 Cu 0.0 0.0 -0.628348 -0.172878 0.391756\natom 5.50735 10.87181 0.63355 Cu 0.0 0.0 -0.358786 -1.246181 -0.441754\natom 6.96259 4.55404 5.58269 Cu 0.0 0.0 -0.155708 -0.154948 0.032886\natom 7.68896 2.52694 7.09349 Cu 0.0 0.0 -0.536607 0.017101 0.256045\natom -1.02391 8.56589 11.34197 Cu 0.0 0.0 -0.093723 -0.175061 -0.221678\natom 1.71389 9.68890 5.09190 Cu 0.0 0.0 0.167635 -0.160460 0.254682\natom 10.26265 3.83587 0.50575 Cu 0.0 0.0 -0.114538 -0.207311 0.461783\natom 2.12911 2.50085 1.86655 Cu 0.0 0.0 0.817852 -0.409138 -0.143551\natom 9.95087 8.59631 4.21500 Cu 0.0 0.0 0.111068 0.212603 0.454293\natom 7.31088 9.71708 10.39353 Cu 0.0 0.0 -0.048693 0.065440 0.131592\natom -0.86100 3.77318 7.96470 Cu 0.0 0.0 -0.121587 -0.405748 -0.481204\natom -2.59552 1.16236 8.30463 Cu 0.0 0.0 0.130364 -0.092707 0.019456\natom 8.17367 7.19536 10.26210 Cu 0.0 0.0 0.113939 -0.115175 -0.380765\natom 11.48478 10.71273 3.60685 Cu 0.0 0.0 0.342318 0.178983 0.464401\natom 1.29509 4.75239 2.38412 Cu 0.0 0.0 -0.188202 1.031223 0.388228\nenergy -566.742004\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_399\nlattice 15.429132687 0.000000000 0.000000000\nlattice 0.000000000 12.026748842 0.000000000\nlattice -6.061300427 0.000000000 12.237212693\natom 9.63118 0.94105 10.33837 S 0.0 0.0 0.161978 0.342383 -1.036946\natom -3.45782 7.03106 8.10910 S 0.0 0.0 -0.293940 0.230258 0.415449\natom -0.33796 11.02851 1.84294 S 0.0 0.0 0.371324 0.241528 -0.653168\natom 12.64709 5.14342 4.13109 S 0.0 0.0 0.285255 -0.515714 -0.327370\natom 12.29531 1.13384 4.22325 S 0.0 0.0 -0.152218 -0.360157 0.021551\natom 0.31179 6.90210 1.97612 S 0.0 0.0 -0.286591 0.249480 -0.164542\natom -3.21062 11.15093 7.57547 S 0.0 0.0 0.661076 -0.123605 0.259053\natom 9.27747 5.10082 10.19174 S 0.0 0.0 1.019952 -0.634056 0.211471\natom 9.29646 1.03574 6.19031 S 0.0 0.0 -0.972366 -0.077911 -0.266220\natom -2.89894 7.17709 12.18380 S 0.0 0.0 -0.479905 -0.608058 0.292084\natom 0.04381 10.97949 6.13080 S 0.0 0.0 -0.132460 -0.174697 -0.713302\natom 12.08516 5.21474 0.10644 S 0.0 0.0 0.081313 0.271054 -0.328909\natom 5.93447 1.10263 12.15566 S 0.0 0.0 0.286232 -0.496299 -0.273498\natom 0.06609 6.83092 6.16126 S 0.0 0.0 0.033487 -0.265203 0.459967\natom -2.76587 10.85331 11.79307 S 0.0 0.0 0.236606 -0.243204 0.798289\natom 9.10132 4.95788 6.31266 S 0.0 0.0 0.748096 -0.362291 0.006701\natom 3.30910 1.23513 7.59499 S 0.0 0.0 1.035824 0.092063 0.083380\natom 2.98211 7.18940 10.44456 S 0.0 0.0 -0.095129 -0.066502 0.501925\natom 6.05903 10.89435 4.88424 S 0.0 0.0 0.463751 -0.229201 -0.263033\natom 6.01468 4.92139 1.37132 S 0.0 0.0 -0.468987 -0.749525 0.107585\natom 6.36879 0.74906 1.24094 S 0.0 0.0 0.310955 0.020940 -0.159411\natom 6.09617 6.60835 4.95176 S 0.0 0.0 -1.035906 0.065541 0.302588\natom 3.17529 11.43602 10.89371 S 0.0 0.0 -1.083594 -0.173260 -0.047961\natom 3.30341 4.82560 7.37512 S 0.0 0.0 -1.079887 1.037804 0.107379\natom 0.07890 1.19981 9.21250 S 0.0 0.0 0.036836 -0.742948 0.043561\natom 6.13072 6.83610 8.65083 S 0.0 0.0 0.467466 0.093881 -1.245717\natom 9.46629 10.90198 2.75063 S 0.0 0.0 0.413494 0.843834 0.141010\natom 2.91274 4.88251 3.51609 S 0.0 0.0 0.516560 0.510248 0.343316\natom 2.47749 0.84218 3.27234 S 0.0 0.0 -0.294238 0.048022 0.441510\natom 9.55918 6.72564 2.52760 S 0.0 0.0 0.031178 0.759188 -0.826097\natom 6.86651 11.00197 8.75562 S 0.0 0.0 -0.388735 0.555506 -1.507087\natom -0.49613 4.97704 9.71319 S 0.0 0.0 0.401916 -0.082379 -0.024213\natom 6.32773 2.94703 8.80158 S 0.0 0.0 0.318250 -0.954028 0.875751\natom -0.22996 9.08067 9.50542 S 0.0 0.0 0.336580 0.737860 -0.336180\natom 3.01466 8.98418 3.56060 S 0.0 0.0 -0.255020 -0.139129 -0.237660\natom 9.25856 3.01141 2.49602 S 0.0 0.0 -0.237795 0.339681 0.548963\natom 5.95365 2.74183 5.30893 S 0.0 0.0 -0.342236 -0.706774 -0.735241\natom 6.33957 8.43840 1.25199 S 0.0 0.0 0.122957 0.897171 -0.589693\natom 3.39730 9.09858 7.02177 S 0.0 0.0 -0.287845 0.907897 0.132987\natom 2.62746 3.11460 11.23648 S 0.0 0.0 0.858091 -0.356245 0.024125\natom -0.06122 2.88713 5.90646 S 0.0 0.0 -0.264980 -1.005669 -0.043997\natom 12.17418 8.86226 0.01577 S 0.0 0.0 0.419422 0.009413 0.393304\natom 9.15714 8.91615 6.20708 S 0.0 0.0 0.356026 1.326317 -0.293624\natom -3.03406 3.15913 11.84785 S 0.0 0.0 0.247702 0.694820 -0.424211\natom -0.16747 2.55616 1.59513 S 0.0 0.0 0.368780 0.597668 0.091520\natom 12.46753 8.52814 4.35781 S 0.0 0.0 -0.695637 0.106041 -0.549693\natom 9.44867 9.16297 10.51369 S 0.0 0.0 0.513536 0.221546 0.277105\natom -3.25396 3.24988 7.65767 S 0.0 0.0 0.205002 0.144088 0.863088\natom 11.27168 3.33596 3.42419 Cu 0.0 0.0 0.375693 -0.434321 0.303582\natom 0.73450 9.16616 2.70459 Cu 0.0 0.0 0.555770 0.047788 0.021851\natom -2.28245 9.06332 8.35212 Cu 0.0 0.0 -0.292738 -0.109961 -0.088971\natom 8.54316 2.98101 9.52115 Cu 0.0 0.0 0.023346 0.004564 0.193232\natom 5.60867 0.81007 8.35658 Cu 0.0 0.0 -0.427253 -0.017732 -0.069299\natom 0.63593 7.03561 9.82364 Cu 0.0 0.0 0.239737 -0.327184 0.130958\natom 3.90721 11.19803 4.13877 Cu 0.0 0.0 0.155680 0.013025 -0.360140\natom 8.20011 4.93665 1.84065 Cu 0.0 0.0 0.085314 0.157624 0.111839\natom 8.65536 0.91174 2.02036 Cu 0.0 0.0 -0.150331 -0.243236 0.302822\natom 3.73820 6.84429 4.53796 Cu 0.0 0.0 0.244354 0.088018 -0.369568\natom 1.15716 11.06807 9.75394 Cu 0.0 0.0 -0.197052 0.147786 0.253912\natom 5.31164 4.74697 8.34879 Cu 0.0 0.0 -0.223441 0.624065 -0.012916\natom 5.02292 2.74531 0.69828 Cu 0.0 0.0 0.417907 0.556436 -0.267353\natom 7.04093 8.58132 5.15590 Cu 0.0 0.0 0.368659 0.423796 0.375745\natom 3.64239 9.29130 11.24450 Cu 0.0 0.0 -0.465650 -0.425076 -0.595255\natom 1.83745 2.94608 7.00283 Cu 0.0 0.0 0.186397 -0.058116 -0.273046\natom -3.21430 0.98297 11.66114 Cu 0.0 0.0 -0.242837 -0.198281 0.071914\natom 10.15257 6.95824 6.46491 Cu 0.0 0.0 0.261849 -0.280040 0.356020\natom 12.90073 10.97657 0.64705 Cu 0.0 0.0 0.246116 0.325079 -0.140392\natom -0.84298 4.85504 5.45012 Cu 0.0 0.0 -0.371023 0.542453 -0.110225\natom -1.22028 0.94657 5.45268 Cu 0.0 0.0 0.136511 -0.203132 -0.180363\natom 13.75092 6.34261 1.19228 Cu 0.0 0.0 -0.161216 -0.141453 -0.360111\natom 10.41368 11.05242 6.31225 Cu 0.0 0.0 -0.623584 -0.474096 0.063136\natom -4.21384 5.33806 12.01155 Cu 0.0 0.0 0.181885 -0.149338 -0.743505\natom 8.10662 1.73098 11.79049 Cu 0.0 0.0 0.188423 -0.407354 0.287054\natom -2.28498 7.14711 6.26338 Cu 0.0 0.0 0.147996 0.185556 -0.338675\natom -5.34845 11.35909 11.80787 Cu 0.0 0.0 -0.145813 -0.470814 0.271356\natom 11.34735 4.54660 5.78729 Cu 0.0 0.0 -0.293629 0.061421 0.441019\natom 11.30692 1.89932 6.23798 Cu 0.0 0.0 0.223817 -0.202321 -0.577643\natom -5.11275 7.91934 12.20466 Cu 0.0 0.0 0.015148 -0.003183 -0.145892\natom -2.22683 10.04530 5.64910 Cu 0.0 0.0 0.251813 0.703603 0.984982\natom 9.11154 4.11073 12.21121 Cu 0.0 0.0 -0.596198 -0.036600 -0.216577\natom 8.30790 2.12919 4.37461 Cu 0.0 0.0 -0.110424 0.237633 0.113861\natom 3.44327 10.24238 1.77073 Cu 0.0 0.0 -0.350057 -0.176774 -0.256603\natom -0.03280 8.81250 7.12799 Cu 0.0 0.0 -0.041940 0.420079 0.097492\natom 6.46455 3.37543 11.06979 Cu 0.0 0.0 -0.353013 0.286262 -0.382891\natom 0.93281 1.43790 11.35287 Cu 0.0 0.0 0.307421 0.333833 0.134033\natom 4.98237 7.67647 6.73481 Cu 0.0 0.0 0.646501 -0.510815 -0.073037\natom 8.22109 9.63094 1.66601 Cu 0.0 0.0 -1.147843 -1.102191 -0.619118\natom 4.02130 4.00831 5.51665 Cu 0.0 0.0 0.173977 -0.433642 -0.819676\natom 3.01648 1.21991 5.37519 Cu 0.0 0.0 0.204883 0.430032 -0.046187\natom 8.71496 7.24901 0.41989 Cu 0.0 0.0 0.028850 -0.022814 0.239184\natom 5.53143 10.22296 6.96858 Cu 0.0 0.0 0.160567 0.179981 0.538441\natom 0.85345 4.32598 11.49647 Cu 0.0 0.0 -0.538446 0.337959 0.345063\natom -1.29048 2.61315 10.23283 Cu 0.0 0.0 -0.299114 0.570145 0.723668\natom 7.69541 8.57343 7.82927 Cu 0.0 0.0 -0.729899 -0.109052 0.363813\natom 10.64911 10.02171 1.08460 Cu 0.0 0.0 0.128979 0.109735 0.435639\natom 1.47720 3.44615 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1.08496 9.38773 S 0.0 0.0 0.075403 -0.259372 -0.621188\natom 6.34054 6.96441 8.61398 S 0.0 0.0 0.402595 -0.723001 0.756399\natom 9.44702 11.07522 2.60649 S 0.0 0.0 0.124143 -0.220298 0.690966\natom 2.72174 5.30293 3.64982 S 0.0 0.0 0.266566 0.028388 -0.153975\natom 2.60106 0.99820 3.39868 S 0.0 0.0 0.133698 0.036970 0.506408\natom 9.67221 7.04953 2.66653 S 0.0 0.0 0.663083 0.216520 -0.406805\natom 6.55951 10.81941 8.71656 S 0.0 0.0 0.888808 -0.578877 0.126432\natom -0.43056 5.03803 9.41733 S 0.0 0.0 -0.875998 0.186108 0.476104\natom 6.23491 2.85458 9.12792 S 0.0 0.0 -0.171363 -0.175101 -0.393890\natom 0.26889 9.09982 9.39944 S 0.0 0.0 -0.960259 -0.011127 0.730988\natom 3.33550 9.12756 3.25851 S 0.0 0.0 -0.476551 0.507590 0.573442\natom 9.77520 2.96453 2.59647 S 0.0 0.0 -0.566787 -0.098178 0.053217\natom 5.79508 2.94445 5.16220 S 0.0 0.0 -0.192775 0.225588 -0.442090\natom 6.39349 8.80687 0.95628 S 0.0 0.0 0.536297 0.033054 0.478046\natom 3.57897 9.37915 7.30478 S 0.0 0.0 -0.089353 -0.299949 -0.470851\natom 2.54131 2.93520 10.85817 S 0.0 0.0 0.548588 0.635996 0.557775\natom 0.11490 2.58780 5.99619 S 0.0 0.0 -0.279109 0.432643 0.237834\natom 12.07420 8.66439 0.11760 S 0.0 0.0 0.137315 0.465733 -0.244200\natom 9.11578 9.42753 6.08890 S 0.0 0.0 0.085813 -0.380959 0.423167\natom -3.06738 3.08427 11.82586 S 0.0 0.0 -0.476050 0.444938 -0.035933\natom -0.16711 2.91929 1.70250 S 0.0 0.0 0.112141 -0.369133 0.403277\natom 12.70125 8.95407 4.51622 S 0.0 0.0 -0.614318 -0.276546 0.371311\natom 9.74225 8.92619 10.84282 S 0.0 0.0 -1.202930 0.042308 0.276779\natom -3.20438 3.20878 7.65061 S 0.0 0.0 -0.289725 0.255052 -0.043827\natom 11.61231 2.69652 3.80240 Cu 0.0 0.0 0.391770 -0.054206 -0.012242\natom 1.41467 9.00327 2.21273 Cu 0.0 0.0 -0.693663 -0.090294 0.140010\natom -2.02004 9.24063 8.95087 Cu 0.0 0.0 -0.002940 0.062471 -0.095837\natom 8.47278 3.04012 9.76366 Cu 0.0 0.0 0.100954 0.077138 -0.004811\natom 5.55379 0.69555 8.27037 Cu 0.0 0.0 -0.295086 0.648668 0.173849\natom 0.98887 6.80797 9.65854 Cu 0.0 0.0 0.315449 0.420092 0.858395\natom 3.98611 11.29356 4.10338 Cu 0.0 0.0 -0.059508 -0.194572 -0.276054\natom 8.64481 4.91039 2.26137 Cu 0.0 0.0 -0.328978 0.165652 0.435556\natom 8.75433 1.02416 1.86991 Cu 0.0 0.0 -0.162032 0.422745 0.038880\natom 4.00536 7.36720 4.38927 Cu 0.0 0.0 -0.419183 -0.459053 -0.186304\natom 0.88893 11.18860 10.19854 Cu 0.0 0.0 0.031607 0.013853 -0.013245\natom 5.40073 4.66855 8.09789 Cu 0.0 0.0 -0.310233 0.364814 0.004740\natom 4.87332 3.39932 0.69978 Cu 0.0 0.0 0.290394 -0.353057 0.154532\natom 7.09795 8.93120 5.14333 Cu 0.0 0.0 -0.138698 0.057681 -0.002073\natom 3.70509 9.16447 11.39834 Cu 0.0 0.0 0.437228 0.207239 0.318415\natom 2.14836 3.16801 6.88630 Cu 0.0 0.0 0.123592 0.057810 0.339965\natom -4.01817 0.82592 11.54874 Cu 0.0 0.0 1.075584 0.120868 0.176741\natom 9.89746 7.31258 6.48309 Cu 0.0 0.0 -0.066838 0.070502 0.539386\natom 12.83146 10.85639 0.92260 Cu 0.0 0.0 -0.084247 -1.064775 -0.010222\natom -0.85835 5.29316 5.27531 Cu 0.0 0.0 0.266740 0.088528 0.150937\natom -0.96231 0.67333 5.44880 Cu 0.0 0.0 -0.125972 -0.190869 -0.229224\natom 13.27310 6.79948 0.98173 Cu 0.0 0.0 0.313132 0.102051 -0.307492\natom 10.35055 11.21868 6.73618 Cu 0.0 0.0 -0.021537 0.094407 0.324178\natom -4.07327 5.24861 11.02907 Cu 0.0 0.0 0.502192 -0.418966 0.619331\natom 14.59142 1.31024 0.24868 Cu 0.0 0.0 -0.068794 0.045746 -0.445258\natom -1.74385 7.33635 6.30245 Cu 0.0 0.0 -0.103437 0.578930 -0.038327\natom -3.35489 8.70890 11.45086 Cu 0.0 0.0 -0.023471 0.541481 -0.089149\natom 11.31328 4.92819 6.00106 Cu 0.0 0.0 0.124277 -0.354520 0.331290\natom 11.25926 1.71899 6.14910 Cu 0.0 0.0 0.576058 0.153646 0.284591\natom 0.98756 7.18957 0.34767 Cu 0.0 0.0 0.148718 -0.153860 -0.137073\natom -1.89896 10.08005 6.27442 Cu 0.0 0.0 0.269953 0.252167 0.119336\natom 14.82866 4.39039 0.09180 Cu 0.0 0.0 -0.340573 0.056927 -0.147375\natom 8.87065 3.15774 4.77775 Cu 0.0 0.0 0.162618 -0.061351 -0.073613\natom 4.26291 8.24195 1.31598 Cu 0.0 0.0 -0.565867 -0.359922 0.446488\natom 0.22021 8.94420 7.17875 Cu 0.0 0.0 -0.009841 -0.048517 -0.177917\natom 6.40085 2.98501 11.36531 Cu 0.0 0.0 -0.043523 0.040280 0.578155\natom 0.68234 1.70256 11.28986 Cu 0.0 0.0 -0.186826 -0.000683 0.598754\natom 5.26580 7.81845 6.92142 Cu 0.0 0.0 -0.445676 0.563885 -0.652128\natom 7.95813 10.36362 0.83491 Cu 0.0 0.0 0.260321 0.279152 0.286081\natom 4.02707 4.53549 5.72216 Cu 0.0 0.0 0.303080 -0.344855 -0.551618\natom 4.88474 0.93701 5.70079 Cu 0.0 0.0 0.230608 -0.147864 0.000888\natom 8.40394 7.67556 0.92211 Cu 0.0 0.0 0.254484 -0.067652 -0.202682\natom 5.45731 10.49026 6.43732 Cu 0.0 0.0 -0.319092 -0.150872 0.710175\natom 1.92198 5.32701 11.97658 Cu 0.0 0.0 -0.166622 -0.121822 -0.420830\natom -1.69666 2.70600 10.16369 Cu 0.0 0.0 0.358334 -0.239200 -0.109338\natom 7.73517 8.65378 7.88721 Cu 0.0 0.0 0.014459 0.573296 -0.606470\natom 10.68735 9.34588 1.74641 Cu 0.0 0.0 -0.439726 -0.201238 -0.448797\natom 3.64684 3.23269 3.42151 Cu 0.0 0.0 -0.105829 0.453683 0.248434\natom 8.16102 0.46510 8.73219 Cu 0.0 0.0 0.192188 -0.096106 -0.270723\natom -1.85848 6.99743 9.97666 Cu 0.0 0.0 -0.218796 -0.500547 0.105423\natom 0.44296 10.99190 3.89648 Cu 0.0 0.0 0.053204 -0.031752 0.450723\natom 11.40933 5.64462 2.13470 Cu 0.0 0.0 -0.351827 -0.331935 0.076030\natom 11.37718 0.81774 2.06734 Cu 0.0 0.0 -0.611435 -0.193327 0.366000\natom 1.24707 3.95096 4.76029 Cu 0.0 0.0 0.324235 0.241591 -0.679982\natom -1.73266 11.65475 10.37157 Cu 0.0 0.0 0.212860 0.380882 -0.393675\natom 7.92981 5.30116 8.00521 Cu 0.0 0.0 -0.074729 0.092064 0.136868\natom -4.37850 2.67262 9.46103 Cu 0.0 0.0 0.057103 -0.274483 0.202197\natom 10.74864 8.24225 9.06354 Cu 0.0 0.0 -0.023471 -0.253329 -0.343244\natom -1.34377 9.25254 2.80510 Cu 0.0 0.0 0.066385 -0.309898 -0.212381\natom -1.25306 3.50180 3.61142 Cu 0.0 0.0 0.828273 -0.763521 -0.530900\natom 4.64858 1.24230 2.50442 Cu 0.0 0.0 -0.291803 0.025681 0.328332\natom 6.53044 7.12313 2.58618 Cu 0.0 0.0 -0.404324 -0.176835 0.114015\natom 3.42063 11.23257 8.81961 Cu 0.0 0.0 -0.139718 -0.054750 0.343706\natom 1.61485 4.27536 9.16077 Cu 0.0 0.0 0.642162 0.094405 0.089876\natom 1.26903 0.78491 7.43404 Cu 0.0 0.0 -1.098981 -0.221546 0.289553\natom 5.44186 6.51461 10.64828 Cu 0.0 0.0 -0.234590 0.410853 -0.301251\natom 8.72291 11.76178 4.86728 Cu 0.0 0.0 -0.175245 -0.098272 -0.519528\natom 4.27688 5.51884 1.91924 Cu 0.0 0.0 -0.221023 0.180796 0.180334\natom 1.77230 11.62345 1.70957 Cu 0.0 0.0 0.079069 -0.087724 -0.045952\natom 8.38154 6.62650 4.33873 Cu 0.0 0.0 -0.248326 -0.078102 0.530087\natom 5.44621 11.15069 10.67735 Cu 0.0 0.0 -0.260829 0.197381 0.016748\natom 0.25174 6.00863 7.54331 Cu 0.0 0.0 -0.473189 -0.146569 -0.892481\natom 3.67802 2.75104 8.87314 Cu 0.0 0.0 0.089110 -0.140927 0.371747\natom 2.51073 8.84239 9.22448 Cu 0.0 0.0 0.304691 -0.146943 -0.082301\natom 5.64252 9.90858 2.81814 Cu 0.0 0.0 0.513423 -0.142304 0.173443\natom 6.39122 3.17193 2.99785 Cu 0.0 0.0 -0.031973 0.226428 -0.106016\natom 13.78888 1.08302 2.77159 Cu 0.0 0.0 0.380818 -0.054563 -0.043082\natom 13.12264 6.93811 3.58588 Cu 0.0 0.0 0.102637 -0.131678 0.110528\natom -4.66009 10.58928 9.71670 Cu 0.0 0.0 0.270843 0.740876 -0.231055\natom 10.75300 5.17700 8.48767 Cu 0.0 0.0 0.320537 0.022315 -0.106267\natom 4.11156 1.42512 11.60725 Cu 0.0 0.0 -0.071191 -0.081941 -0.092444\natom 2.32526 7.33053 7.02235 Cu 0.0 0.0 0.427606 0.281319 -0.144109\natom 5.26791 11.54654 0.92695 Cu 0.0 0.0 0.083201 -0.202086 -0.734203\natom 6.67048 4.91449 5.73851 Cu 0.0 0.0 0.114596 -0.072935 -0.046294\natom 7.31983 2.84405 7.11799 Cu 0.0 0.0 0.238880 -0.435311 -0.009822\natom -0.99607 9.51313 11.51918 Cu 0.0 0.0 0.286827 0.011185 -0.967809\natom 2.19299 9.57686 5.32161 Cu 0.0 0.0 0.241050 0.033235 0.022089\natom 9.93250 3.87375 0.41602 Cu 0.0 0.0 0.481727 -0.314361 -0.455733\natom 2.25099 2.16311 1.55201 Cu 0.0 0.0 -0.161767 0.376937 -0.281467\natom 10.36062 8.54543 4.32968 Cu 0.0 0.0 0.069128 -0.029650 -0.123427\natom 7.34497 9.46663 10.56599 Cu 0.0 0.0 0.041764 -0.020438 0.077561\natom -0.98405 3.73778 7.63702 Cu 0.0 0.0 0.162342 -0.121758 -0.145897\natom -2.40276 1.09063 8.20590 Cu 0.0 0.0 -0.080006 0.099818 0.070596\natom 8.38212 7.22719 9.70741 Cu 0.0 0.0 0.218579 0.053630 0.432589\natom 11.63611 10.66180 3.47400 Cu 0.0 0.0 -0.056787 0.347671 0.309465\natom 0.79475 4.80215 2.38119 Cu 0.0 0.0 0.125964 0.706002 0.158111\nenergy -566.729768\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/nnp-norm/Cu2S_PBE/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type (optional argument: shift parameter alpha).\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              15 15          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n"
  },
  {
    "path": "examples/nnp-norm/H2O_RPBE-D3/input.data",
    "content": " begin\ncomment written by RuNNerDecom\nlattice      24.623508      0.000000      0.000000\nlattice       0.000000     24.623508      0.000000\nlattice       0.000000      0.000000     24.623508\natom     3.735290838    2.327841157    3.501304856   O   -0.226389360    0.000000000   -0.006530137   -0.002852459   -0.027992554\natom     5.246524320    3.393061301    3.627368536   H    0.120793430    0.000000000    0.004517488   -0.000517262    0.005052573\natom     3.558676964    2.038939712    1.628158442   H    0.127225380    0.000000000    0.000095815    0.002211264    0.023427576\natom     4.652261909   21.146799653   16.174455806   O   -0.240350190    0.000000000   -0.000231046   -0.007150914    0.026944723\natom     4.197045601   22.522898765   15.074691455   H    0.132518870    0.000000000   -0.001535223    0.002790532   -0.018391035\natom     5.012047009   19.588530870   15.274057640   H    0.135733700    0.000000000    0.002788938    0.006272370   -0.006171035\natom    16.857157435    3.327223216    5.017451628   O   -0.214010320    0.000000000    0.010171588    0.016012738    0.035099119\natom    16.307700448    2.330278905    3.636288047   H    0.108559530    0.000000000   -0.008301162   -0.024899500   -0.030394951\natom    17.367119130    2.071367425    6.332134617   H    0.121384900    0.000000000   -0.006697761    0.007081892   -0.003219491\natom    18.117794235   -0.374704494   19.251970513   O   -0.253642250    0.000000000   -0.024405004   -0.012754375    0.012242947\natom    16.521636428    0.337611045   19.927736844   H    0.120809200    0.000000000    0.002220741   -0.011811043   -0.009670033\natom    19.148602452    1.088431659   19.427148194   H    0.114155690    0.000000000    0.021230736    0.022132545   -0.006007141\natom    17.757139861    0.050971603    9.130347691   O   -0.215317630    0.000000000   -0.005434943   -0.001827901    0.005465729\natom    16.259474618   23.846841416    9.848217137   H    0.133741170    0.000000000   -0.001711391    0.010244935   -0.002774444\natom    18.540979672   23.231546345    8.347755099   H    0.146150570    0.000000000    0.014635404   -0.006670669   -0.004527888\natom    12.013315016    3.780360824   -0.071301285   O   -0.253689050    0.000000000    0.005359628    0.024749295   -0.005332222\natom    13.294852195    5.203022807   -0.128943624   H    0.114078030    0.000000000   -0.012906774   -0.026389114   -0.001326269\natom    12.919722513    2.259754298    0.424517694   H    0.116540600    0.000000000    0.006743413    0.003879913   -0.000468813\natom    12.529890755    5.212376955   15.827331876   O   -0.253986350    0.000000000   -0.000119721    0.008266330    0.006530251\natom    12.425917982    4.306290712   14.234424399   H    0.112634320    0.000000000    0.000140603   -0.011164836   -0.001375189\natom    12.764916087    3.876925868   17.158077543   H    0.100753240    0.000000000   -0.002300020   -0.000231651   -0.007826174\natom    20.033183604   16.544426534   23.913170829   O   -0.260620870    0.000000000    0.006524698   -0.028540501   -0.005264426\natom    21.355047555   15.177379213   23.397275392   H    0.111928170    0.000000000   -0.031707302    0.026134828    0.007143786\natom    18.354350246   15.846210247   23.385937031   H    0.123277260    0.000000000    0.019731649    0.005955325    0.004549934\natom    12.144518753   18.052825425   18.706274082   O   -0.210341170    0.000000000   -0.014866699   -0.011665448    0.026560721\natom    13.507181907   18.024574008   17.526007366   H    0.124395570    0.000000000    0.020090667    0.001476881   -0.008312401\natom    12.731845866   16.994559476   20.149212834   H    0.144891080    0.000000000   -0.003199444    0.006143511   -0.016646283\natom    16.912564227   19.121579358   16.214744783   O   -0.214062700    0.000000000   -0.002538630    0.026152342    0.005346098\natom    17.405216024   20.866931102   16.692259868   H    0.148034420    0.000000000   -0.013977441   -0.005713738   -0.002595361\natom    18.524312281   18.360227296   16.480704944   H    0.131237310    0.000000000    0.020632529   -0.022303425    0.004792410\natom    20.116898505    4.922757414   19.585318334   O   -0.241188010    0.000000000    0.001047194   -0.008189572    0.009275614\natom    18.468829900    5.729349537   19.695867356   H    0.141751490    0.000000000    0.004325710    0.000224611    0.005073355\natom    20.829892456    4.864629415   21.353157828   H    0.110757650    0.000000000   -0.004199404    0.009172873   -0.016789747\natom    12.029245413   15.603096884    8.902182068   O   -0.266938200    0.000000000    0.054595746   -0.006876686    0.018733486\natom    10.441270123   16.269792527    8.454656948   H    0.098486210    0.000000000   -0.033110457    0.019565416    0.002657365\natom    13.112417962   16.912299665    9.851505262   H    0.107149850    0.000000000   -0.019172455   -0.019589210   -0.019407954\natom     9.762518023    8.972177551   12.034574443   O 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  -0.194094220    0.000000000    0.031139053   -0.066276697    0.021098669\natom     6.518835853   17.598527525    5.812888693   H    0.156894820    0.000000000   -0.042755679    0.033516151    0.011475343\natom     4.178872098   17.417123193    7.699892475   H    0.137280880    0.000000000    0.015711127    0.037753788   -0.030393813\natom    21.151675148   20.879473220    7.686178727   O   -0.248140030    0.000000000   -0.009994913   -0.003084252    0.015181890\natom    21.725161902   21.081677775    5.962589077   H    0.096696550    0.000000000    0.004375907    0.001697312   -0.018251199\natom    22.673568579   21.355735416    8.583993635   H    0.139564520    0.000000000   -0.002909430   -0.001404868    0.006677838\natom    19.507253717   12.301401988   18.501302967   O   -0.199717660    0.000000000   -0.028410932   -0.035128726    0.043667183\natom    19.776549245   13.758948329   17.594513745   H    0.142371980    0.000000000    0.012693146    0.047711282   -0.031771675\natom    17.867647309   12.681150163   19.378767407   H    0.141514070    0.000000000    0.014688099   -0.002133776   -0.011109509\natom    23.134797998   17.370023640   17.326635511   O   -0.251377170    0.000000000   -0.000268730   -0.000574628   -0.003573364\natom    23.309537263   17.766571487   19.122904057   H    0.118237060    0.000000000    0.005638293   -0.001455468   -0.001185792\natom     0.463480083   18.316502796   16.477809882   H    0.138644360    0.000000000   -0.009964426   -0.001923402    0.004419419\natom     7.198349513    9.467121587   20.207068712   O   -0.243428280    0.000000000    0.009787410   -0.009154114    0.016239349\natom     7.841261053    8.491977165   21.715395794   H    0.127971510    0.000000000   -0.015877818    0.012471507   -0.019846659\natom     5.641732350   10.325405299   20.696485297   H    0.130413120    0.000000000    0.003877775    0.000013170    0.004937889\nenergy   -4900.14395256\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/nnp-norm/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\natom_energy                     H -0.45890771  # Free atom reference energy (H).\natom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-norm2/Cu2S_PBE/input.data",
    "content": "begin\ncomment source_file_name=OUTCAR_4_1\nlattice 15.415349658 0.000000000 0.000000000\nlattice 0.000000000 12.016005204 0.000000000\nlattice -6.055885795 0.000000000 12.226281044\natom 9.66279 1.04561 10.73808 S 0.0 0.0 0.107416 0.024235 -0.891279\natom -3.16184 6.79866 8.04560 S 0.0 0.0 0.066538 0.139566 0.120509\natom -0.30404 11.04333 1.97659 S 0.0 0.0 -0.953672 -0.464533 -1.796811\natom 12.83426 5.06839 4.33902 S 0.0 0.0 0.393296 -0.326470 -0.518344\natom 12.39515 0.83117 4.16637 S 0.0 0.0 -0.063080 -0.611946 0.506821\natom -0.04295 7.13059 1.93130 S 0.0 0.0 -0.643788 -0.077636 0.315228\natom -3.25380 10.86483 8.16358 S 0.0 0.0 0.302005 0.898190 -0.193786\natom 9.41762 5.14521 10.58660 S 0.0 0.0 -0.644394 -0.340890 -0.050007\natom 9.00831 1.11279 6.18474 S 0.0 0.0 0.511148 0.550276 -0.454197\natom 3.34802 6.99932 0.09625 S 0.0 0.0 0.108918 0.284724 0.514152\natom 0.30069 11.03010 5.97943 S 0.0 0.0 0.216866 -0.247468 0.308978\natom 12.12524 5.04060 0.14613 S 0.0 0.0 0.501229 -0.426423 -0.428415\natom 6.18973 0.76543 12.21862 S 0.0 0.0 0.711680 -0.222174 -0.534560\natom 0.27700 6.96838 5.89276 S 0.0 0.0 0.301012 0.404099 0.020448\natom -2.83579 11.33619 12.07566 S 0.0 0.0 -0.366454 -1.013699 0.180780\natom 9.11071 5.30752 5.88412 S 0.0 0.0 0.521382 -0.161316 1.257161\natom 3.29671 1.11468 7.49721 S 0.0 0.0 0.423783 0.469883 0.109794\natom 3.12703 6.91177 10.90503 S 0.0 0.0 -0.330671 0.236197 -0.223073\natom 6.12068 10.97358 4.59954 S 0.0 0.0 0.157883 -0.563474 0.377419\natom 6.40437 4.95096 1.33698 S 0.0 0.0 -0.271097 0.026027 -0.062192\natom 6.26122 0.72292 1.03040 S 0.0 0.0 0.479811 0.556269 0.374940\natom 6.11755 6.85613 4.84907 S 0.0 0.0 -0.163743 0.501150 0.586061\natom 3.26768 11.19922 10.85073 S 0.0 0.0 -0.977102 0.340434 0.160795\natom 3.52987 5.32717 7.24188 S 0.0 0.0 -0.660281 -0.466761 -0.537193\natom -0.16538 0.79379 9.67493 S 0.0 0.0 0.082621 0.738076 -0.305641\natom 6.38897 6.71555 8.70905 S 0.0 0.0 0.714567 0.858927 -0.006896\natom 9.21963 11.13097 2.41939 S 0.0 0.0 0.578520 0.128482 0.160710\natom 2.69797 5.15168 3.47535 S 0.0 0.0 0.444296 -0.868870 -0.367079\natom 2.57642 0.90122 3.58188 S 0.0 0.0 0.258623 0.391067 -0.413657\natom 9.93715 6.97306 2.74299 S 0.0 0.0 0.641907 0.681899 -0.621142\natom 6.98678 11.02130 8.74051 S 0.0 0.0 -0.283456 -0.455182 0.418023\natom -0.27493 5.08709 9.39966 S 0.0 0.0 -0.364478 0.475103 0.470787\natom 6.51424 2.93256 8.87090 S 0.0 0.0 0.248611 -0.532822 0.261379\natom -0.07028 9.08780 9.47600 S 0.0 0.0 0.334238 -1.001614 -0.353571\natom 3.02649 8.97677 3.38093 S 0.0 0.0 0.257971 0.378857 -0.128484\natom 9.22001 3.23692 3.10270 S 0.0 0.0 0.394135 -0.561144 -0.530672\natom 5.74428 2.95266 4.87537 S 0.0 0.0 0.504185 -0.767518 0.098132\natom 6.59397 8.58770 1.02620 S 0.0 0.0 -0.052306 0.889508 0.134244\natom 3.55928 9.31404 7.15633 S 0.0 0.0 0.007547 0.236500 0.509320\natom 2.96180 3.18689 11.02470 S 0.0 0.0 0.388499 0.335359 -0.153235\natom 0.00319 2.81986 5.84202 S 0.0 0.0 0.197651 -0.410017 -0.474082\natom 12.07390 8.62516 0.18008 S 0.0 0.0 0.955619 0.478197 -0.371759\natom 9.29009 9.21675 6.39687 S 0.0 0.0 -0.053343 -0.438911 -0.538072\natom -2.79943 3.30466 11.86546 S 0.0 0.0 0.397348 0.490476 0.572317\natom 0.22927 2.73487 1.72492 S 0.0 0.0 -0.311377 0.041312 -0.093182\natom 12.80848 9.20714 4.54446 S 0.0 0.0 -1.078226 -0.482916 -0.754490\natom 9.57560 8.83412 10.64965 S 0.0 0.0 -0.180223 0.207007 -0.965804\natom -3.02133 3.13287 7.77891 S 0.0 0.0 -0.431739 0.229304 -0.188167\natom 11.52491 2.71697 3.53948 Cu 0.0 0.0 -0.524195 0.593531 -0.018888\natom 0.94130 9.18527 2.48932 Cu 0.0 0.0 0.344344 -0.016827 -0.038025\natom -2.17737 8.90566 8.67171 Cu 0.0 0.0 -0.080113 -0.460384 -0.097485\natom 8.60937 2.99411 9.87382 Cu 0.0 0.0 0.242483 0.166370 -0.096114\natom 5.78704 0.81660 8.10398 Cu 0.0 0.0 -0.650869 0.037090 0.138420\natom 1.13645 6.89390 9.81986 Cu 0.0 0.0 -0.922068 -0.415802 0.004088\natom 3.98661 11.22749 4.05170 Cu 0.0 0.0 -0.169993 0.048173 -0.094445\natom 8.48776 5.35715 2.31898 Cu 0.0 0.0 -0.235778 -0.425782 -0.273045\natom 8.46457 1.29601 1.87017 Cu 0.0 0.0 -0.176692 0.115597 0.370769\natom 4.03103 6.96064 3.88549 Cu 0.0 0.0 0.138133 0.336666 0.141528\natom 0.94448 10.87127 10.21508 Cu 0.0 0.0 0.488695 0.336434 0.182050\natom 5.52896 4.74049 8.15135 Cu 0.0 0.0 -0.555966 -0.104080 -0.202623\natom 5.25495 2.85580 0.88760 Cu 0.0 0.0 -0.236780 0.111323 0.058556\natom 7.20832 9.00509 5.25253 Cu 0.0 0.0 -0.093050 -0.067663 0.112018\natom 4.02963 9.12378 11.29065 Cu 0.0 0.0 0.214455 -0.397161 -0.297440\natom 2.00869 2.95149 6.95641 Cu 0.0 0.0 0.242228 0.086186 0.256424\natom -3.59727 1.31298 11.56779 Cu 0.0 0.0 -0.234649 0.051811 -0.011230\natom 10.17489 7.11535 7.19747 Cu 0.0 0.0 -0.205621 -0.373986 -0.133792\natom 13.14051 10.69193 0.61472 Cu 0.0 0.0 -0.227511 0.015227 -0.013204\natom -0.15851 4.93004 5.03782 Cu 0.0 0.0 -0.407379 -0.188360 -0.079197\natom -1.03043 0.75778 5.49457 Cu 0.0 0.0 -0.614057 0.276670 -0.421905\natom 13.29870 6.86184 0.95026 Cu 0.0 0.0 0.173253 -0.290646 0.319586\natom 9.90736 11.28706 7.03112 Cu 0.0 0.0 0.528504 -0.034630 0.164799\natom -4.08827 5.25818 11.63154 Cu 0.0 0.0 0.507294 -0.050859 0.108014\natom 14.22568 1.81408 0.08656 Cu 0.0 0.0 0.571499 0.026055 -0.038863\natom -1.97034 7.15598 6.03887 Cu 0.0 0.0 -0.449980 0.314388 0.305998\natom -5.20546 10.47006 12.19513 Cu 0.0 0.0 0.395519 -0.013242 0.783300\natom 11.23565 4.47173 5.73470 Cu 0.0 0.0 -0.177903 -0.216022 0.218810\natom 11.50533 1.75385 6.16054 Cu 0.0 0.0 -0.082071 0.040075 -0.078104\natom 1.05145 7.68106 0.13325 Cu 0.0 0.0 0.678999 0.031254 -0.143904\natom -1.99506 10.44925 6.34486 Cu 0.0 0.0 0.240461 0.040601 0.140157\natom 14.46480 4.42495 0.30428 Cu 0.0 0.0 -0.397487 -0.006486 -0.227579\natom 9.50706 3.23697 7.16092 Cu 0.0 0.0 0.420873 -0.228470 -0.137433\natom 3.09422 9.25746 0.87162 Cu 0.0 0.0 0.083127 -0.013205 -0.008907\natom 0.08332 8.97416 7.15956 Cu 0.0 0.0 0.004363 -0.110554 -0.102250\natom 12.23272 2.72008 1.12254 Cu 0.0 0.0 -0.249257 0.710722 -0.108280\natom 1.15816 2.14568 11.54656 Cu 0.0 0.0 -0.411213 -0.684450 0.384207\natom 5.27209 7.82267 6.86516 Cu 0.0 0.0 0.125328 -0.256841 -0.003757\natom 8.17277 10.18657 0.27762 Cu 0.0 0.0 -0.368442 -0.181728 0.621258\natom 3.91864 4.11751 5.06655 Cu 0.0 0.0 -0.432305 0.483675 0.538896\natom 4.00310 1.50710 5.38681 Cu 0.0 0.0 -0.237210 -0.113493 -0.033558\natom 8.72038 7.58568 0.75111 Cu 0.0 0.0 -0.048667 0.004667 0.557755\natom 5.69466 10.30930 6.99982 Cu 0.0 0.0 0.082381 0.291179 -0.205718\natom 0.73141 4.83540 11.36935 Cu 0.0 0.0 -0.060464 -0.428701 -0.029908\natom -1.02582 2.77460 10.47989 Cu 0.0 0.0 -0.129362 0.072520 -0.184218\natom 7.80433 8.30190 7.77366 Cu 0.0 0.0 -0.615739 0.187191 -0.342683\natom 10.52153 9.29163 1.56932 Cu 0.0 0.0 -0.404426 0.511279 0.817259\natom 1.76042 2.96828 4.38708 Cu 0.0 0.0 0.093553 0.136826 -0.191640\natom 8.37753 0.81962 8.31150 Cu 0.0 0.0 0.131603 0.121433 0.418584\natom -2.20379 6.60031 10.26349 Cu 0.0 0.0 0.092194 -0.113727 -1.102924\natom 0.72604 11.56260 3.71135 Cu 0.0 0.0 0.581182 0.170853 1.405298\natom 11.59545 5.02775 2.26956 Cu 0.0 0.0 -0.090177 0.088087 0.453039\natom 11.37961 0.26551 1.88897 Cu 0.0 0.0 -0.706411 0.099231 0.493076\natom 1.44878 6.95846 3.91255 Cu 0.0 0.0 -0.462398 0.338316 0.310223\natom -1.69988 11.16574 10.04945 Cu 0.0 0.0 -0.380264 -0.023048 0.218466\natom 8.06333 4.95413 8.13816 Cu 0.0 0.0 0.026219 0.286594 -0.450587\natom -4.36341 1.98604 9.11700 Cu 0.0 0.0 -0.498227 0.092957 0.168919\natom 10.68527 9.24350 8.40739 Cu 0.0 0.0 -0.570331 -0.426422 0.683351\natom 13.82938 9.09178 2.35866 Cu 0.0 0.0 -0.230559 -0.185157 0.613580\natom 13.96975 3.83629 2.66623 Cu 0.0 0.0 -0.518971 0.102803 0.913475\natom 6.06301 1.07695 3.45090 Cu 0.0 0.0 -0.024730 -0.119319 -0.317544\natom 6.31390 6.99170 2.63117 Cu 0.0 0.0 0.084965 -0.013747 -0.351411\natom 3.43713 11.21558 8.61998 Cu 0.0 0.0 0.027260 -0.463362 -0.130044\natom 2.71760 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9.14403 8.20163 Cu 0.0 0.0 -0.736542 -0.170504 -0.135000\natom 8.78257 2.91894 9.94865 Cu 0.0 0.0 0.074663 0.111987 -0.087260\natom 5.44081 0.91688 8.74315 Cu 0.0 0.0 -0.180289 0.645887 -0.366148\natom 0.77289 7.30984 9.98548 Cu 0.0 0.0 -0.277405 -0.881330 0.335080\natom 3.85512 10.95899 3.91346 Cu 0.0 0.0 0.260423 0.320780 -0.193056\natom 8.53235 5.11107 2.48624 Cu 0.0 0.0 -0.058014 -0.089280 -0.050176\natom 8.43690 0.63670 1.96905 Cu 0.0 0.0 0.099391 0.927992 0.179655\natom 3.99811 6.95598 3.90500 Cu 0.0 0.0 -0.352701 -0.011541 0.050527\natom 1.18262 10.61798 10.28166 Cu 0.0 0.0 -1.094495 -0.340401 -0.726245\natom 5.10052 4.88890 8.30125 Cu 0.0 0.0 0.018158 0.149382 -0.187026\natom 5.10993 2.61008 0.77614 Cu 0.0 0.0 -0.275247 0.260318 -0.417356\natom 7.25024 8.89725 5.25590 Cu 0.0 0.0 0.639651 0.022245 0.247963\natom 4.08558 8.88878 11.36107 Cu 0.0 0.0 0.524273 0.774990 0.801272\natom 2.21835 3.02757 6.84923 Cu 0.0 0.0 -0.169081 0.275750 0.105148\natom -3.87773 0.67325 11.41533 Cu 0.0 0.0 0.251774 0.280134 0.178852\natom 9.32650 7.13585 7.16763 Cu 0.0 0.0 0.548313 -0.054311 -0.557519\natom 12.78822 11.27114 0.55769 Cu 0.0 0.0 0.294325 -0.384911 -0.009479\natom -0.88291 4.97952 5.49548 Cu 0.0 0.0 0.564377 0.282694 -0.115547\natom -0.94004 0.86817 5.17878 Cu 0.0 0.0 0.531793 -0.105153 0.480341\natom 13.50445 7.21972 0.82994 Cu 0.0 0.0 0.202768 -0.216719 0.219452\natom 10.42550 11.49942 6.83806 Cu 0.0 0.0 0.645052 -0.311437 0.297678\natom -4.02735 4.98160 11.70489 Cu 0.0 0.0 -0.046036 -0.144755 -0.350289\natom 8.20421 1.34114 12.16595 Cu 0.0 0.0 -0.136416 0.398756 0.126365\natom -1.77903 7.86620 5.88147 Cu 0.0 0.0 0.105846 -0.233096 0.554421\natom 1.66504 10.96535 0.86414 Cu 0.0 0.0 -0.184789 0.089984 -0.093283\natom 11.43269 4.94510 6.15516 Cu 0.0 0.0 0.189353 -0.287190 0.179424\natom 11.54652 1.99240 6.03084 Cu 0.0 0.0 -0.256757 -0.069354 0.081431\natom 1.32088 8.42018 0.03724 Cu 0.0 0.0 0.539276 -0.848730 0.280594\natom -2.06691 10.78843 6.10765 Cu 0.0 0.0 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0.167616\natom -1.13919 3.60534 3.37464 Cu 0.0 0.0 -0.081470 -0.216910 -0.268008\natom 5.81252 0.87416 3.69546 Cu 0.0 0.0 0.239683 -0.389727 -0.441421\natom 6.27049 6.44284 2.73448 Cu 0.0 0.0 0.593297 -0.267458 -0.209278\natom 3.31810 11.57108 8.96326 Cu 0.0 0.0 -0.094871 0.025466 -0.063309\natom 2.93597 5.49182 9.37236 Cu 0.0 0.0 -0.352565 0.166649 0.402671\natom 1.19319 0.86485 7.88775 Cu 0.0 0.0 0.112395 -0.280213 0.120366\natom 5.26044 6.78722 10.70638 Cu 0.0 0.0 0.200201 -0.557848 -0.024562\natom 8.36755 11.16562 4.67475 Cu 0.0 0.0 0.099281 0.195008 -0.022501\natom 4.26368 5.66242 1.58437 Cu 0.0 0.0 -0.713695 -0.342037 -0.255913\natom 3.94831 0.44729 1.60572 Cu 0.0 0.0 -0.373471 0.103052 0.100319\natom 8.51632 6.74447 4.54446 Cu 0.0 0.0 -0.287029 -0.070477 0.054991\natom 5.26048 11.15558 10.54689 Cu 0.0 0.0 0.010288 0.017542 0.174574\natom 0.80269 5.77855 7.91179 Cu 0.0 0.0 0.151297 -0.299896 -0.394095\natom 3.54421 2.88108 9.06926 Cu 0.0 0.0 0.134787 -0.405971 -0.278721\natom 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Cu 0.0 0.0 -0.576462 -0.180970 -0.049483\natom 7.32782 4.31071 5.82521 Cu 0.0 0.0 -0.522107 0.353251 -0.959985\natom 7.66354 2.73122 7.50603 Cu 0.0 0.0 -0.166669 0.192502 0.201686\natom -1.43250 8.41399 11.77217 Cu 0.0 0.0 0.347823 0.068297 -0.186494\natom 2.11419 9.49110 5.62346 Cu 0.0 0.0 -0.042565 0.158531 -0.223262\natom 11.03887 2.73447 1.15455 Cu 0.0 0.0 -0.117768 0.166711 0.190583\natom 2.43931 2.81590 1.89111 Cu 0.0 0.0 0.006521 0.227399 -0.415608\natom 10.21714 8.56313 4.34968 Cu 0.0 0.0 0.258534 0.100881 -0.558522\natom 7.09611 9.38395 10.57802 Cu 0.0 0.0 0.393663 0.075645 0.014443\natom -1.59050 4.06116 7.81026 Cu 0.0 0.0 0.776427 0.169641 0.044501\natom -2.15370 1.08495 8.85227 Cu 0.0 0.0 -0.251265 -0.119388 -0.127210\natom 8.67455 7.22254 10.03372 Cu 0.0 0.0 -0.079222 0.387976 -0.021438\natom 11.53372 11.21480 3.96977 Cu 0.0 0.0 -0.374950 -0.033082 -0.260344\natom 0.47515 5.15818 2.57476 Cu 0.0 0.0 0.420379 -0.030283 -0.128469\nenergy -564.447991\ncharge 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3.75629 10.61762 Cu 0.0 0.0 -0.473425 -0.110636 -0.590338\natom 1.05952 1.47514 11.44673 Cu 0.0 0.0 0.195146 -0.113334 -0.029193\natom 5.10503 7.84909 6.58179 Cu 0.0 0.0 -0.060244 0.529389 0.274714\natom 8.69693 9.23535 2.74652 Cu 0.0 0.0 0.198904 0.042220 0.139482\natom 4.18862 4.32075 5.08468 Cu 0.0 0.0 -0.687486 0.252557 0.046419\natom 3.56995 1.66576 5.17934 Cu 0.0 0.0 0.350572 0.113282 0.055055\natom 8.38102 7.55761 0.67249 Cu 0.0 0.0 0.221268 -0.096170 0.196745\natom 5.88457 10.48193 6.82940 Cu 0.0 0.0 -0.527455 -0.073681 -0.327656\natom 0.68402 4.12479 11.24727 Cu 0.0 0.0 0.274571 0.302013 0.432248\natom -1.12364 2.61442 10.69119 Cu 0.0 0.0 -0.406000 -0.415393 -0.376120\natom 7.54822 8.75270 7.69958 Cu 0.0 0.0 0.122682 -0.295042 0.353740\natom 10.67731 10.00740 1.48796 Cu 0.0 0.0 0.004412 0.290884 -0.025178\natom 1.83663 3.28932 4.22959 Cu 0.0 0.0 -0.080904 0.356566 -0.023366\natom 8.33507 0.56145 8.60945 Cu 0.0 0.0 0.114603 -0.021616 -0.355167\natom -2.04215 6.77389 9.82833 Cu 0.0 0.0 -0.007534 -0.717134 0.011035\natom 1.04834 11.37616 3.74608 Cu 0.0 0.0 -0.288259 0.230254 0.065589\natom 11.58793 5.79437 2.84809 Cu 0.0 0.0 -0.244081 -0.079537 -0.320782\natom 11.64504 0.70716 2.02330 Cu 0.0 0.0 -0.989841 -0.364179 0.552394\natom 1.11142 7.40922 4.23882 Cu 0.0 0.0 0.371931 0.133288 -0.489418\natom -1.88783 11.40659 10.34487 Cu 0.0 0.0 -0.096300 -0.299633 0.370507\natom 7.92534 5.01851 7.96233 Cu 0.0 0.0 0.356730 0.125769 -0.314713\natom -4.13829 2.80083 9.99982 Cu 0.0 0.0 0.131330 -0.067725 -0.257719\natom -4.32990 7.99757 9.60330 Cu 0.0 0.0 -0.389135 -0.044329 -0.182795\natom -1.56293 10.02503 3.28950 Cu 0.0 0.0 -0.163143 -0.170593 -0.024373\natom -1.30134 3.47561 3.73172 Cu 0.0 0.0 -0.100760 0.130375 -0.806868\natom 6.17439 1.10633 3.40005 Cu 0.0 0.0 0.336882 0.359130 0.398025\natom 6.37044 7.00825 2.48371 Cu 0.0 0.0 0.015742 -0.275627 0.324090\natom 3.44024 11.20972 8.87800 Cu 0.0 0.0 0.400193 -0.136619 -0.546082\natom 2.97105 4.56706 9.15608 Cu 0.0 0.0 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0.285689\natom 10.67763 11.28842 9.58969 Cu 0.0 0.0 -0.021239 -0.492052 0.293759\natom 10.65236 5.18394 8.51971 Cu 0.0 0.0 0.006797 -0.195878 0.204414\natom 4.18590 1.38357 11.39813 Cu 0.0 0.0 -0.375486 -0.017114 0.060248\natom 2.27516 7.42030 6.67243 Cu 0.0 0.0 0.523978 0.082577 0.237924\natom 7.84663 10.07741 0.39405 Cu 0.0 0.0 1.164994 1.031202 -0.529445\natom 6.81010 4.81633 5.60962 Cu 0.0 0.0 0.055794 -0.470187 0.015497\natom 7.14424 2.58987 7.06385 Cu 0.0 0.0 0.121366 0.070144 -0.525206\natom -1.45274 8.82216 11.02617 Cu 0.0 0.0 0.165812 0.240095 0.481689\natom 2.10769 9.84569 5.36999 Cu 0.0 0.0 -0.159444 -0.140440 0.752452\natom 10.47994 3.75604 1.23239 Cu 0.0 0.0 -0.380032 -0.307886 0.942959\natom 2.04626 2.36807 1.60570 Cu 0.0 0.0 0.448066 0.067754 -0.297946\natom 10.35379 8.55398 4.73610 Cu 0.0 0.0 -0.846167 -0.056089 -0.118372\natom 6.98392 9.10700 10.37288 Cu 0.0 0.0 0.323577 0.072657 -0.086433\natom -1.21280 3.26685 7.73503 Cu 0.0 0.0 0.632881 0.536764 -0.025554\natom 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-0.454017\natom 10.13844 7.11491 6.40231 Cu 0.0 0.0 -0.569071 0.250542 0.601601\natom 12.72990 10.98411 0.96736 Cu 0.0 0.0 -0.176046 0.318766 -0.333106\natom -0.00737 5.09788 5.75926 Cu 0.0 0.0 -0.029219 -0.200811 -0.079748\natom -0.93295 1.16232 5.26955 Cu 0.0 0.0 -0.492524 -0.633635 -0.250378\natom 13.28385 7.15458 0.66812 Cu 0.0 0.0 -0.301181 0.074160 -0.102055\natom 10.40943 11.12950 6.96072 Cu 0.0 0.0 -0.117897 -0.028344 -0.116176\natom -4.00996 5.24507 11.33974 Cu 0.0 0.0 0.012991 0.023391 -0.094382\natom 13.31640 2.97016 0.83392 Cu 0.0 0.0 -0.423414 0.150964 -0.607954\natom 12.47100 6.88116 5.74444 Cu 0.0 0.0 0.557164 -0.303740 -0.871168\natom 1.06901 10.65973 0.19548 Cu 0.0 0.0 0.012070 -0.284940 -0.273374\natom 11.29234 4.27251 5.96161 Cu 0.0 0.0 0.086863 0.332260 -0.115234\natom 11.62120 1.62573 6.08354 Cu 0.0 0.0 -0.048666 0.292079 0.471397\natom -4.65422 7.87348 11.91059 Cu 0.0 0.0 -0.960416 0.488317 -0.211798\natom -1.63735 10.42263 6.09840 Cu 0.0 0.0 -1.113106 -0.544845 -0.000427\natom 15.05717 4.96662 0.22650 Cu 0.0 0.0 -0.379133 -0.304059 0.136958\natom 9.28967 2.88898 5.08692 Cu 0.0 0.0 0.117682 0.616494 -0.306475\natom 3.16447 9.17559 1.14169 Cu 0.0 0.0 0.030456 0.037399 -0.640928\natom 0.37739 8.70188 7.70190 Cu 0.0 0.0 -0.001689 -0.201921 -0.548107\natom 5.28792 3.60439 10.55368 Cu 0.0 0.0 0.457627 -0.225015 0.531135\natom 1.03295 1.75095 11.62696 Cu 0.0 0.0 -0.173491 0.095705 -0.022558\natom 4.60570 7.55834 6.86272 Cu 0.0 0.0 0.674104 0.042332 -0.067677\natom 8.25251 10.54132 0.76591 Cu 0.0 0.0 0.114499 -0.291107 0.149544\natom 4.46596 4.18082 5.48738 Cu 0.0 0.0 -0.557451 -0.253554 0.050618\natom 3.58863 1.51455 5.07176 Cu 0.0 0.0 0.718783 0.669856 0.870525\natom 8.40039 7.59253 0.80712 Cu 0.0 0.0 0.343056 -0.036320 -0.525589\natom 5.48965 10.34826 6.97892 Cu 0.0 0.0 0.024921 -0.042790 0.317892\natom 0.80000 4.87994 11.68969 Cu 0.0 0.0 0.246354 -0.347015 0.236503\natom -1.18845 2.71278 10.31996 Cu 0.0 0.0 -0.104547 0.273178 0.306075\natom 7.74051 8.91758 8.13752 Cu 0.0 0.0 0.049964 -0.170213 -0.999522\natom 10.48370 9.12538 1.78660 Cu 0.0 0.0 -0.230378 0.303888 0.064862\natom 1.91891 3.29915 4.27351 Cu 0.0 0.0 0.103973 -0.149358 0.076156\natom 8.90773 0.68042 8.32039 Cu 0.0 0.0 -0.030220 -0.417289 -0.470863\natom -2.05926 6.88862 10.08014 Cu 0.0 0.0 -0.020613 -0.503358 -0.342970\natom 0.33878 11.19732 3.80187 Cu 0.0 0.0 -0.123164 0.282004 0.020037\natom 11.66133 5.63913 2.26741 Cu 0.0 0.0 0.299874 -0.442205 -0.049257\natom 11.00732 0.62113 2.05454 Cu 0.0 0.0 0.351663 0.228427 -0.428361\natom 1.36998 6.69689 4.18645 Cu 0.0 0.0 0.103537 0.079873 -0.356966\natom -1.86578 11.23486 10.05585 Cu 0.0 0.0 0.008994 0.332376 0.409030\natom 8.08590 5.16301 8.16202 Cu 0.0 0.0 0.423053 0.152242 -0.431543\natom -4.17281 1.86071 9.12892 Cu 0.0 0.0 -0.704965 0.135013 0.282517\natom 10.47716 8.49401 8.57627 Cu 0.0 0.0 -0.352614 0.402205 0.284235\natom 13.40013 9.15702 2.52916 Cu 0.0 0.0 0.591148 -0.035331 -0.781858\natom -0.76134 3.33565 3.84134 Cu 0.0 0.0 -0.210706 0.227822 -0.550197\natom 5.58912 1.00407 3.49382 Cu 0.0 0.0 0.373138 0.265093 0.159110\natom 6.57741 7.14653 2.56683 Cu 0.0 0.0 -0.417628 -0.291723 0.407608\natom 3.58870 10.89339 8.71247 Cu 0.0 0.0 -0.305316 0.000667 0.350551\natom 3.42368 4.98435 9.96699 Cu 0.0 0.0 -0.255185 1.082788 -0.716166\natom 1.28762 0.71788 7.99947 Cu 0.0 0.0 0.405352 -0.190991 -0.277226\natom 5.85996 6.34795 10.61468 Cu 0.0 0.0 -0.073768 -0.028163 -0.035427\natom 8.15201 11.55962 4.48578 Cu 0.0 0.0 -0.644758 -0.427102 -0.395821\natom 3.57494 4.73989 1.23786 Cu 0.0 0.0 -0.051561 0.396326 0.465236\natom 3.80726 0.43646 1.82202 Cu 0.0 0.0 -0.125559 0.146887 -0.029206\natom 8.40548 6.57428 4.21744 Cu 0.0 0.0 0.033844 0.295766 0.253862\natom 5.44343 11.21633 10.68925 Cu 0.0 0.0 0.092219 0.324847 -0.419697\natom 1.28907 5.09385 8.21174 Cu 0.0 0.0 0.381162 0.156476 0.140724\natom 3.34804 2.44109 9.26473 Cu 0.0 0.0 -0.277518 -0.018140 -0.412823\natom 2.59851 8.50015 8.96715 Cu 0.0 0.0 0.547576 0.164492 -0.235145\natom 5.46695 9.56576 3.01182 Cu 0.0 0.0 -0.207159 -0.026245 0.447183\natom 6.44944 3.62350 3.24347 Cu 0.0 0.0 -0.156367 -0.066807 -0.150968\natom -1.15831 0.90865 2.49817 Cu 0.0 0.0 -0.273470 0.402750 0.455927\natom -1.43657 6.76605 3.45714 Cu 0.0 0.0 0.143092 0.088504 -0.315961\natom 10.61313 11.13935 9.64448 Cu 0.0 0.0 0.247714 -0.513574 -0.422224\natom 10.71616 5.88205 8.81022 Cu 0.0 0.0 -0.529668 -0.693187 0.651642\natom 4.10225 1.57707 11.62967 Cu 0.0 0.0 -0.964105 -0.349743 -0.468824\natom 2.27900 6.88276 6.49927 Cu 0.0 0.0 -0.242226 0.105661 0.469384\natom 5.47666 10.56877 0.54818 Cu 0.0 0.0 -0.820864 1.388044 -0.266691\natom 6.83940 4.80600 5.57295 Cu 0.0 0.0 0.265387 -0.258445 0.065663\natom 8.00253 2.70036 7.01505 Cu 0.0 0.0 -0.779860 -0.197739 0.669692\natom -0.74210 8.04227 11.91283 Cu 0.0 0.0 -0.411558 -0.039897 -0.461576\natom 1.78696 9.71606 5.17893 Cu 0.0 0.0 0.180707 -0.015326 -0.140653\natom 10.82165 2.95042 1.22111 Cu 0.0 0.0 0.578328 0.526833 -0.807511\natom 2.16585 2.42165 1.58537 Cu 0.0 0.0 0.211844 0.052891 0.426346\natom 10.33151 8.33328 4.29213 Cu 0.0 0.0 0.170112 0.321127 -0.128360\natom 7.31421 9.55438 10.40212 Cu 0.0 0.0 -0.388305 0.078768 0.793821\natom -0.83764 3.95521 7.79240 Cu 0.0 0.0 -0.441797 -0.573566 0.419583\natom -2.06260 1.25249 8.16312 Cu 0.0 0.0 0.535082 -0.202285 -0.088209\natom 8.74820 7.00627 10.02256 Cu 0.0 0.0 -0.248813 0.245293 -0.031917\natom 11.56092 10.71251 3.58256 Cu 0.0 0.0 0.131702 -0.072963 0.190967\natom 1.00507 4.78711 2.44966 Cu 0.0 0.0 -0.447225 0.040965 -0.384033\nenergy -565.607832\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_21\nlattice 15.424131298 0.000000000 0.000000000\nlattice 0.000000000 12.022850344 0.000000000\nlattice -6.059335643 0.000000000 12.233245972\natom 9.69752 0.99718 10.31507 S 0.0 0.0 0.428489 0.864370 0.668883\natom -3.29298 7.22335 8.22515 S 0.0 0.0 -0.544722 -1.225831 -0.911920\natom -0.28490 11.25245 1.86478 S 0.0 0.0 0.547659 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2.76037 6.80089 10.96883 S 0.0 0.0 1.094328 -0.402412 -0.273848\natom 5.68820 10.79280 4.88494 S 0.0 0.0 0.801381 0.210444 -0.496512\natom 6.15976 4.81090 1.45572 S 0.0 0.0 -0.061945 -0.261604 -0.223970\natom 6.40857 0.73345 1.36879 S 0.0 0.0 0.480463 -0.015484 -0.299160\natom 6.03563 6.72053 4.92171 S 0.0 0.0 -0.417680 0.120146 0.389146\natom 3.09881 11.00716 11.14289 S 0.0 0.0 -0.891480 0.491997 -0.094117\natom 3.81478 4.90866 7.23920 S 0.0 0.0 -0.119598 0.042797 -0.066682\natom -0.11913 1.23370 9.52792 S 0.0 0.0 0.060491 -0.485502 0.640642\natom 6.40106 6.62710 9.01335 S 0.0 0.0 0.729499 0.380687 -1.668554\natom 9.52081 10.81228 2.98988 S 0.0 0.0 -0.855756 0.262232 -0.899884\natom 3.04717 5.04917 3.24171 S 0.0 0.0 1.031843 -0.420996 -0.066096\natom 2.63381 1.13804 3.35271 S 0.0 0.0 -0.025372 -1.174073 0.772809\natom 9.85008 6.87363 2.63539 S 0.0 0.0 -0.339174 -0.761700 -0.630269\natom 6.96076 10.63299 8.88377 S 0.0 0.0 -1.161484 0.729976 -1.033973\natom -0.13334 4.96537 9.69493 S 0.0 0.0 0.674174 -0.336296 -0.251820\natom 6.52311 2.47794 9.01798 S 0.0 0.0 -0.368600 0.495413 -0.415155\natom -0.34032 9.26133 9.34661 S 0.0 0.0 -0.021809 0.035197 0.079901\natom 2.96215 9.03787 3.49597 S 0.0 0.0 -0.791542 -0.321400 0.131101\natom 9.48058 2.84442 2.74864 S 0.0 0.0 -0.176657 0.007876 0.530057\natom 5.84339 2.45195 5.07287 S 0.0 0.0 0.477930 -0.166367 -0.131116\natom 6.59664 8.63061 1.20540 S 0.0 0.0 0.320953 0.243389 -0.019120\natom 3.51010 9.26075 7.38912 S 0.0 0.0 -0.193849 -0.273587 -0.566212\natom 2.89753 3.25684 10.89907 S 0.0 0.0 -0.471085 -0.501682 0.516292\natom 0.26655 3.22616 5.72619 S 0.0 0.0 -0.387580 -0.984291 -0.479125\natom 12.48509 8.66812 0.25024 S 0.0 0.0 -1.460864 0.077459 1.676333\natom 9.02451 9.17407 6.18832 S 0.0 0.0 0.798591 0.041943 0.377210\natom -2.85996 3.18226 12.19742 S 0.0 0.0 0.090256 0.383348 -0.656936\natom -0.35694 3.07919 1.69350 S 0.0 0.0 0.369782 -0.178452 -0.008726\natom 12.86472 8.88547 4.67116 S 0.0 0.0 -0.808055 -0.392928 0.316984\natom 9.44482 9.35669 10.52433 S 0.0 0.0 0.123355 0.136570 -0.495146\natom -3.02449 3.30194 7.82746 S 0.0 0.0 0.212687 0.170418 -0.175442\natom 11.67543 3.17715 3.82097 Cu 0.0 0.0 -0.132108 -0.273595 0.073435\natom 0.84980 9.08603 2.52848 Cu 0.0 0.0 0.234813 0.480321 -0.150752\natom -2.61598 9.20958 8.16868 Cu 0.0 0.0 0.323066 1.558654 0.182828\natom 8.31095 3.30571 10.14593 Cu 0.0 0.0 0.065294 -0.220710 -0.531475\natom 5.36347 0.56375 8.47158 Cu 0.0 0.0 -0.273093 -0.159461 -0.117278\natom 1.04700 7.54401 9.94402 Cu 0.0 0.0 -1.381842 0.395253 -0.408891\natom 3.61068 11.09913 3.60760 Cu 0.0 0.0 0.280395 0.348068 0.571919\natom 8.32091 5.09934 1.98609 Cu 0.0 0.0 0.512465 0.379369 0.764857\natom 8.73278 0.81142 2.02043 Cu 0.0 0.0 -0.204404 -0.102945 0.142097\natom 3.97343 7.12833 4.11889 Cu 0.0 0.0 -0.098439 -0.034560 -0.227143\natom 0.94047 11.06189 10.14298 Cu 0.0 0.0 0.334059 0.026774 0.089888\natom 6.01770 4.52176 8.06381 Cu 0.0 0.0 -0.223240 -0.163693 0.263484\natom 5.48212 2.68766 1.02042 Cu 0.0 0.0 -0.538722 0.241714 -0.276965\natom 7.10132 8.75242 5.01571 Cu 0.0 0.0 -0.128632 0.028158 0.504093\natom 4.19171 9.03316 11.47110 Cu 0.0 0.0 0.353379 -0.080336 0.119637\natom 2.16518 3.12633 6.89857 Cu 0.0 0.0 0.244781 0.219714 0.162134\natom -3.75606 0.63179 11.51750 Cu 0.0 0.0 0.048407 0.763425 -0.517493\natom 9.58941 6.87478 6.71054 Cu 0.0 0.0 0.219831 0.234185 -0.445892\natom 13.06049 11.03756 1.02745 Cu 0.0 0.0 -0.079314 -0.677939 0.286754\natom -0.78852 5.13166 5.22801 Cu 0.0 0.0 0.352833 0.379884 0.287873\natom -1.15115 1.30344 5.50785 Cu 0.0 0.0 0.380819 0.210585 -0.356781\natom 13.32304 6.68263 0.99937 Cu 0.0 0.0 0.392733 0.172661 -0.326537\natom 10.38163 11.11523 6.56486 Cu 0.0 0.0 -0.415950 -0.661426 -0.007447\natom -3.99277 5.13629 11.52678 Cu 0.0 0.0 0.080316 -0.215417 -0.053770\natom 8.38323 1.75060 12.14468 Cu 0.0 0.0 0.043482 -0.321417 -0.081744\natom 12.45114 6.85202 5.91286 Cu 0.0 0.0 -0.063381 0.145723 0.345637\natom 1.13538 10.68873 0.06046 Cu 0.0 0.0 -0.639656 -0.502632 0.278945\natom 11.25623 4.59140 6.17465 Cu 0.0 0.0 -0.167411 -0.323254 -0.088040\natom 10.74056 2.00309 7.23737 Cu 0.0 0.0 0.280785 0.289572 -0.082256\natom -5.03746 8.11584 12.01208 Cu 0.0 0.0 0.382434 -0.449550 0.445620\natom -1.94857 10.87638 5.61594 Cu 0.0 0.0 -0.285999 -0.126621 0.554910\natom 14.45612 4.56956 0.00791 Cu 0.0 0.0 -0.114656 -0.112373 0.378247\natom 9.32861 2.94473 5.03697 Cu 0.0 0.0 0.104405 -0.208697 0.101586\natom 3.08177 8.78775 1.26265 Cu 0.0 0.0 0.100098 -0.033736 -0.066842\natom 1.26045 9.79223 7.72958 Cu 0.0 0.0 -0.106339 -0.101528 0.011347\natom 6.12331 2.90073 11.91474 Cu 0.0 0.0 0.156307 -1.352597 -0.162173\natom 1.12871 1.68462 11.50637 Cu 0.0 0.0 0.069475 0.126589 -0.086201\natom 5.05905 7.48840 7.06112 Cu 0.0 0.0 0.463196 -0.016689 0.081990\natom 8.40755 10.03140 0.85379 Cu 0.0 0.0 -0.103302 0.414453 0.198273\natom 4.19600 4.03461 5.11551 Cu 0.0 0.0 -0.219619 0.038422 -0.014174\natom 3.56644 1.49862 5.41080 Cu 0.0 0.0 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0.45622 S 0.0 0.0 -0.912320 -1.003811 0.311702\natom 9.45930 8.98345 6.21662 S 0.0 0.0 -0.796992 -0.575739 0.295445\natom -2.84615 2.84786 11.96526 S 0.0 0.0 -0.799751 0.518563 0.644071\natom 0.04275 2.96022 1.49476 S 0.0 0.0 -0.785260 -0.140283 0.333171\natom 12.64196 8.61780 4.62439 S 0.0 0.0 0.159040 0.192586 1.768480\natom 9.40685 9.41478 10.64060 S 0.0 0.0 1.269105 -0.289032 -0.548124\natom -3.08889 3.27384 7.69809 S 0.0 0.0 0.430441 0.187464 0.246703\natom 11.52624 2.66955 3.63386 Cu 0.0 0.0 0.178007 0.323487 0.306316\natom 0.77625 8.96645 2.49884 Cu 0.0 0.0 -0.117896 0.201380 0.245443\natom -2.57539 9.15917 8.37379 Cu 0.0 0.0 0.729022 -0.423189 0.392675\natom 8.39756 3.13624 9.44373 Cu 0.0 0.0 0.073393 0.220707 0.312663\natom 5.61793 0.66567 8.43490 Cu 0.0 0.0 -0.249905 0.157531 -0.027465\natom 1.22492 7.00630 9.40630 Cu 0.0 0.0 -0.324409 -0.009963 0.173526\natom 4.11427 11.10460 4.04082 Cu 0.0 0.0 -0.191831 -0.238881 -0.152240\natom 8.50870 5.10563 2.16419 Cu 0.0 0.0 0.390286 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0.080560\natom 1.53664 1.72721 10.84714 Cu 0.0 0.0 0.078035 0.319768 0.369381\natom 5.22050 7.88927 6.76847 Cu 0.0 0.0 0.157444 -0.671022 0.412933\natom 7.93323 10.54466 0.49770 Cu 0.0 0.0 -0.244667 -0.368220 0.493466\natom 3.97707 4.00516 5.37104 Cu 0.0 0.0 0.487677 0.064783 -0.114850\natom 4.14569 1.27047 5.44463 Cu 0.0 0.0 -0.229985 0.329857 0.509785\natom 8.60070 7.74534 1.20477 Cu 0.0 0.0 -0.222494 0.078646 -0.059131\natom 5.46247 10.32666 6.77296 Cu 0.0 0.0 0.389763 0.678031 -0.028391\natom 0.77818 4.14352 11.07585 Cu 0.0 0.0 0.710249 0.091945 0.042840\natom -2.03971 3.57901 10.07552 Cu 0.0 0.0 0.056195 0.174251 -0.306246\natom 7.52477 8.84811 7.52561 Cu 0.0 0.0 0.373785 0.022630 1.049059\natom 11.79066 8.56243 2.69914 Cu 0.0 0.0 -0.657496 -0.036112 -1.212240\natom 1.59296 3.78609 4.53421 Cu 0.0 0.0 -0.286303 -0.685100 0.139181\natom 8.25121 0.15969 8.21043 Cu 0.0 0.0 0.160832 0.013432 0.192410\natom -1.93085 6.46651 10.05052 Cu 0.0 0.0 -0.138020 0.117795 0.259108\natom 0.97360 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6.30428 Cu 0.0 0.0 -0.322831 0.139102 0.206135\natom 8.02163 10.08801 12.23225 Cu 0.0 0.0 -0.222858 0.131274 0.256342\natom -0.56212 5.14775 5.32292 Cu 0.0 0.0 -0.076425 -0.606583 0.030943\natom -0.80989 0.93651 5.32614 Cu 0.0 0.0 -0.238610 0.307378 0.097839\natom 13.22050 6.98149 0.64487 Cu 0.0 0.0 0.169634 -0.132976 -0.014427\natom 10.68960 10.99004 6.55602 Cu 0.0 0.0 -0.031273 -0.115594 0.335940\natom -3.98489 5.49480 11.84622 Cu 0.0 0.0 -0.086968 -0.378460 -0.357526\natom 8.50023 0.72367 12.08366 Cu 0.0 0.0 -0.557422 0.104888 0.767138\natom -2.28814 7.03102 6.10286 Cu 0.0 0.0 0.247534 0.091236 -0.365017\natom 1.18362 10.23521 0.06025 Cu 0.0 0.0 -0.211480 0.405759 0.032660\natom 12.41333 4.38140 6.00365 Cu 0.0 0.0 -0.256548 -0.029173 0.576026\natom 11.51756 1.83507 6.64050 Cu 0.0 0.0 -0.221897 -0.172319 -0.401036\natom -4.27596 7.93845 11.17010 Cu 0.0 0.0 -0.066611 0.205050 0.002508\natom -2.00185 10.57175 5.51422 Cu 0.0 0.0 0.265903 -0.184834 0.472879\natom 14.56384 4.46179 0.08498 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0.141225\natom 8.48774 9.23201 2.05606 Cu 0.0 0.0 0.470603 0.254027 0.207617\natom 5.39323 10.31506 7.02597 Cu 0.0 0.0 0.128387 0.525209 0.325742\natom 1.27201 4.13500 11.12724 Cu 0.0 0.0 0.100106 0.027229 0.148301\natom -1.08356 2.34871 10.36440 Cu 0.0 0.0 -0.115961 0.201545 -0.039684\natom 7.41684 9.00449 7.99731 Cu 0.0 0.0 -0.346857 -0.262197 0.497363\natom 11.91265 8.39927 2.42959 Cu 0.0 0.0 -0.131640 -0.321162 0.508974\natom 1.18746 1.93982 4.73443 Cu 0.0 0.0 0.316395 0.106054 -0.281281\natom 8.46428 0.58439 8.38410 Cu 0.0 0.0 -0.201599 -0.093222 -0.211731\natom -2.28228 6.03105 9.60677 Cu 0.0 0.0 -0.147047 0.154758 0.109189\natom 1.21645 11.58938 3.94392 Cu 0.0 0.0 0.036200 -0.091983 -0.032970\natom 11.10207 5.65120 2.47741 Cu 0.0 0.0 0.624661 -0.133601 -0.503282\natom 11.98936 0.59789 2.16769 Cu 0.0 0.0 -0.295112 0.256572 0.643703\natom 1.00043 6.73888 4.04158 Cu 0.0 0.0 0.529960 -0.354381 -0.658114\natom -2.12839 11.43922 9.97281 Cu 0.0 0.0 0.000413 -0.492403 0.310696\natom 8.12816 5.13331 8.11130 Cu 0.0 0.0 -0.210146 -0.302608 0.172841\natom 10.78163 1.78273 8.80755 Cu 0.0 0.0 -1.043324 -0.559393 0.927563\natom 10.41516 8.39121 8.64204 Cu 0.0 0.0 -0.395131 0.185406 0.035433\natom -1.53040 9.72295 3.36888 Cu 0.0 0.0 0.372856 0.130296 -0.400832\natom -1.41696 3.69703 3.19491 Cu 0.0 0.0 0.883350 -0.223926 -0.494067\natom 6.86443 1.73542 3.49266 Cu 0.0 0.0 0.244556 -0.303366 0.007376\natom 6.17918 6.97435 2.30802 Cu 0.0 0.0 0.209760 0.297266 -0.013530\natom 3.15940 10.95802 8.61593 Cu 0.0 0.0 0.193136 0.470719 0.148909\natom 2.88208 5.70957 9.23450 Cu 0.0 0.0 0.345822 -0.702524 -1.280960\natom 1.02004 12.01249 7.53204 Cu 0.0 0.0 -0.087097 0.438165 0.233971\natom 5.64859 6.84766 10.85928 Cu 0.0 0.0 -0.078639 0.031924 0.721273\natom 8.29656 11.31184 4.35364 Cu 0.0 0.0 -0.069122 0.018563 -0.176049\natom 3.67725 5.60939 1.57633 Cu 0.0 0.0 0.669505 0.757452 -1.443874\natom 4.00798 0.58669 1.47240 Cu 0.0 0.0 0.031678 0.170501 -0.276929\natom 8.25979 6.53135 4.39946 Cu 0.0 0.0 0.121604 -0.341586 -0.191260\natom 5.39557 11.25483 10.68752 Cu 0.0 0.0 -0.291604 -0.204365 -0.334073\natom 0.69703 5.65959 7.86760 Cu 0.0 0.0 -0.169854 -0.013095 -0.561101\natom 3.58008 2.31552 9.18250 Cu 0.0 0.0 0.116022 -0.224291 -0.555338\natom 3.05372 8.56933 9.43560 Cu 0.0 0.0 -0.411349 -0.314710 -0.570380\natom 5.68123 9.41030 3.31150 Cu 0.0 0.0 0.618118 -0.382904 -0.575557\natom 5.80858 4.17257 3.20862 Cu 0.0 0.0 0.124705 0.093073 -0.161157\natom -0.92440 1.11899 2.92312 Cu 0.0 0.0 0.062937 0.078153 0.035106\natom -1.44711 7.09351 3.54192 Cu 0.0 0.0 -0.344783 0.146651 -0.067587\natom 10.58942 10.83708 9.44404 Cu 0.0 0.0 0.459607 0.762299 -0.252833\natom 10.98782 4.51094 8.77469 Cu 0.0 0.0 -0.161489 0.006589 0.115299\natom 10.51264 2.34015 0.87372 Cu 0.0 0.0 0.354363 -0.027526 -0.319758\natom 2.56194 7.08435 6.78565 Cu 0.0 0.0 -0.177923 -0.212799 0.073616\natom 6.01815 11.05039 1.09580 Cu 0.0 0.0 -0.430044 1.160378 0.444636\natom 6.69093 4.86762 5.60643 Cu 0.0 0.0 -0.056310 -0.085972 0.047007\natom 7.13023 2.57847 6.91158 Cu 0.0 0.0 0.637455 0.182186 -0.414937\natom -1.18043 9.53299 11.44896 Cu 0.0 0.0 0.153076 -0.123030 0.152320\natom 1.74350 9.08802 5.03185 Cu 0.0 0.0 -0.309832 0.050675 0.116414\natom 4.09435 4.72815 11.62063 Cu 0.0 0.0 -0.488835 0.401761 -0.293672\natom 2.59578 3.44791 1.65468 Cu 0.0 0.0 0.001195 -0.804295 -0.231591\natom 9.73089 8.57633 4.39194 Cu 0.0 0.0 0.036982 0.288261 0.452128\natom 7.37620 9.13211 10.85042 Cu 0.0 0.0 -0.392944 0.094802 -0.026504\natom -1.05087 3.39136 8.03506 Cu 0.0 0.0 -0.158547 0.227874 0.594507\natom -2.23135 0.98797 8.10515 Cu 0.0 0.0 0.302332 0.190919 0.039003\natom 8.44600 6.93280 9.76244 Cu 0.0 0.0 0.794447 0.231274 0.607530\natom 11.43175 10.56534 3.95892 Cu 0.0 0.0 -0.479032 0.815489 -0.428313\natom 0.56312 5.02524 2.03818 Cu 0.0 0.0 0.206743 -0.955342 0.150812\nenergy -565.073649\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_279\nlattice 15.400727029 0.000000000 0.000000000\nlattice 0.000000000 12.004607111 0.000000000\nlattice -6.050141328 0.000000000 12.214683488\natom 9.65434 1.13629 10.42689 S 0.0 0.0 -0.027450 0.265189 0.059099\natom -3.69623 6.92843 7.97749 S 0.0 0.0 0.339291 0.304709 -0.296444\natom -0.30842 11.07389 1.81163 S 0.0 0.0 -0.347143 0.290416 -0.265011\natom 12.69913 4.92715 4.38423 S 0.0 0.0 -0.221622 0.137567 -0.221864\natom 12.81886 1.06893 3.99055 S 0.0 0.0 -0.445042 0.266383 0.093812\natom -0.18531 6.99544 1.90757 S 0.0 0.0 0.143616 0.002630 -0.419620\natom -2.90946 10.95025 7.86991 S 0.0 0.0 -0.270380 0.623666 0.222735\natom 9.57120 5.13156 10.74113 S 0.0 0.0 0.229174 -0.046146 -0.018056\natom 9.05460 0.97974 6.19685 S 0.0 0.0 0.481142 0.398229 0.331226\natom -3.06588 7.00845 11.87544 S 0.0 0.0 0.597812 -0.917245 0.172220\natom 0.42980 11.01015 6.07632 S 0.0 0.0 -0.133291 -0.160642 -0.311381\natom 11.78799 4.99460 0.01902 S 0.0 0.0 0.873595 0.681268 0.337014\natom 12.15741 1.15010 0.35007 S 0.0 0.0 -0.533612 -0.776279 0.057191\natom 0.21000 6.72252 6.13407 S 0.0 0.0 0.050020 0.620973 -0.365571\natom -2.81709 10.91384 12.20682 S 0.0 0.0 0.804004 -0.174437 -0.129138\natom 9.01094 4.82929 6.42686 S 0.0 0.0 0.290862 0.045045 -0.468485\natom 3.52205 0.72389 7.42145 S 0.0 0.0 -0.706904 0.747540 0.274162\natom 2.77862 6.94939 11.04289 S 0.0 0.0 0.696009 0.196816 -1.191073\natom 5.69056 11.08645 4.73966 S 0.0 0.0 1.228142 -0.081054 0.284577\natom 6.10330 4.86873 1.26284 S 0.0 0.0 -0.348331 0.574917 0.823367\natom 6.48304 0.87752 1.20088 S 0.0 0.0 -1.205732 -0.362291 -0.851227\natom 5.92901 6.66692 5.13927 S 0.0 0.0 0.547833 0.519141 -0.525032\natom 3.07500 11.16805 11.17593 S 0.0 0.0 -0.212242 -0.190401 0.271072\natom 3.16284 5.16247 7.09927 S 0.0 0.0 0.588442 -0.756420 0.612938\natom 0.03720 0.67302 9.60886 S 0.0 0.0 0.314782 0.360945 0.404808\natom 6.36915 7.02952 8.99250 S 0.0 0.0 -0.007432 0.203433 -0.383531\natom 9.53633 10.91032 3.10898 S 0.0 0.0 -0.378398 0.163635 -0.149693\natom 3.25425 4.97004 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0.426950 -1.191887\natom 9.06005 8.90682 6.36594 S 0.0 0.0 0.486279 -0.637644 -1.151151\natom -2.57506 2.76632 11.81978 S 0.0 0.0 -0.503384 0.777826 0.249587\natom 0.25132 3.12716 1.48115 S 0.0 0.0 -0.608301 0.109693 0.098321\natom 12.32916 8.79573 4.13935 S 0.0 0.0 -0.474549 0.731131 1.726422\natom 9.27795 9.47557 10.55517 S 0.0 0.0 -0.338265 -0.093140 0.046796\natom -3.15825 2.63234 7.82168 S 0.0 0.0 0.021963 -0.095534 -0.521092\natom 11.34384 2.78908 3.49134 Cu 0.0 0.0 0.266402 0.203551 0.017728\natom 0.47052 9.09979 2.61623 Cu 0.0 0.0 0.054596 -0.163264 -0.200579\natom -2.32029 8.85643 8.46865 Cu 0.0 0.0 0.117873 -0.638327 0.121556\natom 8.49454 3.25681 10.00919 Cu 0.0 0.0 0.300843 -0.311172 -0.223946\natom 5.45084 1.27657 8.42583 Cu 0.0 0.0 0.615805 0.295081 0.036292\natom 0.82063 6.87439 9.97517 Cu 0.0 0.0 -0.278155 -0.090576 -0.276165\natom 3.81072 10.79548 3.67498 Cu 0.0 0.0 -0.716326 0.710999 -0.232144\natom 7.92842 4.97030 2.53819 Cu 0.0 0.0 0.582939 -0.122379 0.115492\natom 8.38814 0.81594 2.05597 Cu 0.0 0.0 1.087838 -0.069441 0.729638\natom 4.02764 7.41026 4.45263 Cu 0.0 0.0 -0.375365 0.294501 -0.662878\natom 1.09170 10.70841 10.12471 Cu 0.0 0.0 -0.096600 -0.101774 -0.010295\natom 5.29100 5.16403 8.07640 Cu 0.0 0.0 -0.083630 -0.100913 0.265753\natom 5.41270 2.75931 0.72858 Cu 0.0 0.0 -0.029070 -0.044443 0.283989\natom 7.16192 9.32876 5.24564 Cu 0.0 0.0 -0.205326 -0.106932 0.193270\natom 4.25522 9.22371 11.54870 Cu 0.0 0.0 -0.110040 0.003881 -0.279273\natom 2.46996 2.86206 6.92385 Cu 0.0 0.0 -0.437845 0.058486 -0.186360\natom -3.69824 0.93079 11.51239 Cu 0.0 0.0 -0.528848 -0.553449 -0.476950\natom 8.18162 7.24408 7.58625 Cu 0.0 0.0 -0.066860 -0.017268 -0.020829\natom 13.01532 11.05932 0.49142 Cu 0.0 0.0 0.193724 -0.171706 0.316688\natom -0.43528 4.76027 5.25475 Cu 0.0 0.0 -0.014576 -0.355329 -0.064321\natom -0.91878 0.67847 5.48290 Cu 0.0 0.0 -0.285952 0.149133 -0.267101\natom 13.42130 6.64028 0.35803 Cu 0.0 0.0 0.077954 0.188468 0.565580\natom 10.55055 11.38916 6.88428 Cu 0.0 0.0 -0.183498 0.144817 -0.245487\natom -3.36792 4.81748 11.17599 Cu 0.0 0.0 -0.543630 -0.230396 0.405871\natom 8.21425 1.65171 12.19874 Cu 0.0 0.0 0.643216 -0.192794 -0.201816\natom 11.80791 6.92370 5.31055 Cu 0.0 0.0 0.253792 0.084301 0.386113\natom -5.08359 10.78705 12.13169 Cu 0.0 0.0 -0.287906 -0.201018 0.252104\natom 11.31575 4.59021 6.09702 Cu 0.0 0.0 -0.367090 -0.498877 0.099718\natom 11.47516 1.68583 5.88820 Cu 0.0 0.0 -0.069929 -0.086020 -0.247185\natom -5.44689 7.82624 11.94118 Cu 0.0 0.0 -0.149588 -0.247335 0.340774\natom -2.18526 9.88681 6.08793 Cu 0.0 0.0 0.088100 -0.104267 -0.641500\natom 14.08306 4.12963 0.16499 Cu 0.0 0.0 -0.114203 0.641912 0.116931\natom 9.29780 3.00009 4.99117 Cu 0.0 0.0 -0.027990 0.079308 0.087680\natom 2.69882 8.77207 0.78791 Cu 0.0 0.0 -0.043134 1.043673 0.739696\natom 0.17794 8.95078 6.89682 Cu 0.0 0.0 -0.516005 -0.436177 0.460935\natom 6.06030 3.02882 11.17722 Cu 0.0 0.0 0.021239 -0.557262 -0.148721\natom 1.33702 1.70640 11.35346 Cu 0.0 0.0 -0.173388 0.140541 -0.189028\natom 5.11245 7.74479 6.93217 Cu 0.0 0.0 0.421601 0.056960 0.113577\natom 8.24396 10.34956 1.21142 Cu 0.0 0.0 0.182989 -0.305282 -0.034122\natom 4.38653 4.15265 5.40633 Cu 0.0 0.0 -0.153409 0.294314 0.143012\natom 3.90180 1.60979 5.13212 Cu 0.0 0.0 0.121887 -0.408556 -0.086019\natom 8.56950 7.30516 0.96892 Cu 0.0 0.0 -0.348738 0.297050 0.376032\natom 5.95239 10.92008 7.04416 Cu 0.0 0.0 -0.295917 -0.246031 -0.626765\natom 0.88052 4.37533 11.53395 Cu 0.0 0.0 0.226771 -0.072623 -0.840530\natom -1.01699 2.80331 10.20025 Cu 0.0 0.0 0.586820 -0.568188 0.271337\natom 8.45376 10.06381 8.04991 Cu 0.0 0.0 -0.608008 0.349645 0.594028\natom 10.91943 8.19009 1.63815 Cu 0.0 0.0 -0.622651 -0.182141 0.406856\natom 2.17443 3.29759 4.35635 Cu 0.0 0.0 -0.666198 -0.221666 0.294757\natom 8.76230 0.53596 8.40783 Cu 0.0 0.0 0.255561 0.533831 0.132131\natom -2.19473 6.61348 9.84131 Cu 0.0 0.0 0.082533 0.222275 -0.441892\natom 0.74102 11.61955 3.75073 Cu 0.0 0.0 0.315413 -0.176986 0.092736\natom 11.78721 5.27157 2.29624 Cu 0.0 0.0 0.141177 -0.080132 0.020972\natom 10.83954 0.42471 2.18170 Cu 0.0 0.0 0.856780 0.201493 -0.149031\natom 1.54432 6.78331 4.27307 Cu 0.0 0.0 -0.093575 0.398207 0.124091\natom -2.23069 10.97328 10.04453 Cu 0.0 0.0 0.312285 0.099643 0.231177\natom 9.66209 5.04106 8.47482 Cu 0.0 0.0 0.209062 0.299418 0.707911\natom -4.23381 2.81476 9.81062 Cu 0.0 0.0 -0.349520 -0.109296 -0.047465\natom 10.12146 8.40247 8.83273 Cu 0.0 0.0 0.633616 -0.643772 -0.017811\natom -1.01264 8.12579 4.66389 Cu 0.0 0.0 0.376057 -0.256776 0.294272\natom -1.28669 4.13849 2.86920 Cu 0.0 0.0 0.009072 -0.291488 -0.248712\natom 6.06333 1.16828 3.37770 Cu 0.0 0.0 -0.086179 -0.208226 0.642861\natom 6.36806 6.97257 2.76006 Cu 0.0 0.0 -0.069933 0.429001 0.190181\natom 3.54527 10.71041 8.94148 Cu 0.0 0.0 0.041255 0.220004 0.011190\natom 3.03101 5.15533 9.44897 Cu 0.0 0.0 -0.030281 -0.085289 0.209628\natom 0.89000 0.70574 7.43576 Cu 0.0 0.0 0.308386 0.408788 0.568117\natom 5.10691 6.72910 10.85439 Cu 0.0 0.0 -0.247390 0.012722 -0.115851\natom 8.09573 11.66333 4.74762 Cu 0.0 0.0 -0.380796 -0.187217 -0.497365\natom 3.89861 5.65300 1.38974 Cu 0.0 0.0 0.206767 0.733346 -1.712023\natom 3.72861 0.65856 1.35498 Cu 0.0 0.0 0.199741 0.023604 0.568100\natom 8.87537 6.49500 4.85784 Cu 0.0 0.0 0.065586 0.173447 0.448166\natom 5.28922 11.61664 10.73261 Cu 0.0 0.0 0.382254 -0.121849 -0.149241\natom 1.01401 5.20040 7.88581 Cu 0.0 0.0 -0.266200 -0.116373 0.002711\natom 3.35006 2.22894 9.18589 Cu 0.0 0.0 -0.329387 0.110881 0.372311\natom 3.28298 8.22004 9.04472 Cu 0.0 0.0 -0.173302 -0.476694 1.180064\natom 5.97588 9.72319 2.92188 Cu 0.0 0.0 0.418192 -0.520572 0.038207\natom 5.63801 3.59003 3.25572 Cu 0.0 0.0 0.341480 0.255657 -0.204462\natom -0.58736 1.48686 2.64282 Cu 0.0 0.0 -0.428627 -0.597132 0.281811\natom 13.26234 8.59716 2.25889 Cu 0.0 0.0 1.192576 -0.144180 -0.356367\natom 10.66361 10.90208 9.36498 Cu 0.0 0.0 -0.021550 -0.079435 0.266917\natom -3.03723 4.70978 8.54988 Cu 0.0 0.0 -0.353626 0.492962 -0.318408\natom 3.86555 1.26076 12.11565 Cu 0.0 0.0 -0.394991 0.031432 -0.551437\natom 2.48989 7.28693 6.71758 Cu 0.0 0.0 -0.474364 0.241244 -0.225704\natom 5.63424 10.87951 0.67509 Cu 0.0 0.0 -0.170893 -0.253830 -0.082775\natom 7.03761 4.76715 5.21144 Cu 0.0 0.0 -0.279416 -0.661557 -0.067166\natom 7.63233 2.67356 7.19500 Cu 0.0 0.0 0.266248 -0.279091 -0.202780\natom -1.09448 8.23442 11.39464 Cu 0.0 0.0 -0.000643 0.172447 0.257186\natom 1.65589 9.49824 5.00695 Cu 0.0 0.0 0.339049 -0.179186 -0.445788\natom 10.29569 3.62937 0.86254 Cu 0.0 0.0 -0.297019 -0.093742 0.347960\natom 2.58193 3.17311 1.89072 Cu 0.0 0.0 0.358917 -0.456653 -0.602447\natom 9.05373 8.73571 3.57224 Cu 0.0 0.0 -0.153146 0.452311 0.000540\natom 5.94399 9.25011 9.24171 Cu 0.0 0.0 -0.116690 0.325987 -0.143172\natom -0.87653 3.40259 7.81309 Cu 0.0 0.0 0.268177 -0.269184 -1.093559\natom -1.64270 0.94564 8.22072 Cu 0.0 0.0 -0.406635 0.049550 -0.029093\natom 8.26660 6.91319 10.21133 Cu 0.0 0.0 0.426108 -0.045893 -0.236280\natom 11.88806 11.08188 4.22145 Cu 0.0 0.0 -0.069410 -0.273711 -0.153051\natom 1.03226 5.04014 2.66085 Cu 0.0 0.0 -0.247581 0.287013 -0.203919\nenergy -565.111055\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_296\nlattice 15.463777200 0.000000000 0.000000000\nlattice 0.000000000 12.053753656 0.000000000\nlattice -6.074910447 0.000000000 12.264690081\natom 9.59413 0.96783 10.57278 S 0.0 0.0 0.346300 -0.137397 -1.121629\natom -2.68602 6.71076 7.96014 S 0.0 0.0 -1.208815 0.744476 0.423387\natom -0.06390 10.87276 2.00398 S 0.0 0.0 0.038899 0.042418 -0.360703\natom 12.69540 4.92373 4.29215 S 0.0 0.0 -0.094540 0.526336 -0.057451\natom 12.43441 0.73162 4.66904 S 0.0 0.0 0.183514 -0.372937 -0.615548\natom -0.31411 6.85536 1.70885 S 0.0 0.0 -0.196162 0.784649 0.107756\natom -3.04952 10.98798 8.00627 S 0.0 0.0 -0.282368 0.192436 -0.334371\natom 9.50949 5.18194 10.50431 S 0.0 0.0 0.670014 -0.339791 0.077834\natom 9.37229 1.06855 6.29398 S 0.0 0.0 -1.434508 0.442600 0.149486\natom 3.58489 6.97060 0.19683 S 0.0 0.0 -0.230838 0.020967 -0.281463\natom 0.38636 11.01562 6.47731 S 0.0 0.0 0.407030 0.510863 -1.058761\natom 12.49180 4.76240 0.27011 S 0.0 0.0 0.557476 0.560894 -0.507492\natom 11.79477 0.89585 0.56389 S 0.0 0.0 0.395618 -0.583010 -0.216847\natom 0.67623 6.78619 5.61587 S 0.0 0.0 -0.918958 1.053858 -0.230230\natom -2.65191 11.19793 12.24610 S 0.0 0.0 0.083320 0.103144 -0.167245\natom 9.30737 5.18932 6.08970 S 0.0 0.0 -0.232263 0.232587 0.378174\natom 3.55829 0.88378 7.45440 S 0.0 0.0 -0.575218 0.722962 0.347407\natom 3.22069 7.06875 10.85332 S 0.0 0.0 -0.006368 -0.643000 -0.013595\natom 6.51976 10.87357 4.86397 S 0.0 0.0 -0.471258 0.279518 -0.440517\natom 6.83723 4.73017 1.11176 S 0.0 0.0 -0.118580 0.665826 -0.346324\natom 6.79019 0.88680 1.11376 S 0.0 0.0 -0.462049 -0.332732 0.680211\natom 6.34702 6.86312 4.86896 S 0.0 0.0 0.908213 -0.521055 0.418192\natom 2.96397 10.88052 10.94175 S 0.0 0.0 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6.46732 8.59542 0.98026 S 0.0 0.0 0.207044 0.343762 0.506216\natom 3.40626 9.38274 7.07906 S 0.0 0.0 0.037789 -1.086407 0.613770\natom 3.14003 3.21029 11.26334 S 0.0 0.0 -0.261213 -0.204309 -0.725762\natom 0.18301 3.03193 5.83027 S 0.0 0.0 -0.796940 -0.675118 -0.251891\natom 6.25719 8.99058 12.22648 S 0.0 0.0 -0.251795 -1.357515 0.497604\natom 9.65951 9.02008 6.67172 S 0.0 0.0 -1.351429 -0.003309 0.375604\natom -2.57991 3.11694 12.20582 S 0.0 0.0 0.694278 -0.587292 -0.630484\natom -0.59588 2.38646 1.51630 S 0.0 0.0 0.747942 0.530385 -0.329014\natom 12.56786 8.87900 4.69747 S 0.0 0.0 -0.282670 0.708205 0.639604\natom 9.75649 8.98905 10.47745 S 0.0 0.0 -0.670194 0.819142 1.433553\natom -3.15157 3.18818 7.87562 S 0.0 0.0 0.082411 0.046060 0.011513\natom 11.79357 2.81586 3.88933 Cu 0.0 0.0 -0.348866 -0.155734 -0.050328\natom 0.87872 8.74121 2.44832 Cu 0.0 0.0 -0.135920 0.066824 -0.250703\natom -2.08919 8.95376 8.63595 Cu 0.0 0.0 -0.090333 -0.000479 -0.293908\natom 8.52565 3.19539 10.02838 Cu 0.0 0.0 0.297698 0.280237 0.342135\natom 5.63955 0.68693 8.59493 Cu 0.0 0.0 -0.284858 1.164875 -0.273901\natom 0.99234 7.12437 10.02156 Cu 0.0 0.0 0.291310 -0.094609 -0.154963\natom 4.26476 11.05351 4.03807 Cu 0.0 0.0 -0.135334 0.496674 0.209101\natom 9.35048 5.14152 2.78948 Cu 0.0 0.0 -0.397765 0.698479 -0.107401\natom 7.09437 3.46705 2.87700 Cu 0.0 0.0 0.154622 -0.286286 0.626391\natom 4.61235 7.62902 3.97199 Cu 0.0 0.0 -0.776719 0.739128 -0.415097\natom 0.75140 11.20110 10.45689 Cu 0.0 0.0 -0.035332 -0.347693 -0.428419\natom 5.46156 4.57165 8.35079 Cu 0.0 0.0 -0.445057 0.542046 -0.332669\natom 5.50832 2.74619 0.92811 Cu 0.0 0.0 0.008404 0.042370 0.046395\natom 7.33602 8.87388 5.51081 Cu 0.0 0.0 0.221632 -0.231389 -0.759786\natom 4.29560 9.09480 11.25367 Cu 0.0 0.0 -0.373222 0.115962 -0.016236\natom 2.02184 3.21172 6.90396 Cu 0.0 0.0 0.802661 -0.304376 -0.032985\natom -3.82786 1.17256 11.51540 Cu 0.0 0.0 0.249634 -0.138391 -0.221822\natom 10.52571 7.01357 7.10499 Cu 0.0 0.0 0.196093 -0.514237 0.069269\natom 12.73284 10.79750 1.00759 Cu 0.0 0.0 0.322784 1.110356 0.316976\natom -0.61292 5.04408 5.01739 Cu 0.0 0.0 -0.099418 -0.146983 -0.011236\natom -1.00797 0.89234 5.59127 Cu 0.0 0.0 0.659388 -0.014512 0.178730\natom 13.11639 6.88375 0.41410 Cu 0.0 0.0 0.120379 0.761308 0.151347\natom 10.25236 11.24357 7.04142 Cu 0.0 0.0 0.486852 -0.703417 0.162744\natom -3.78914 4.90979 11.64754 Cu 0.0 0.0 -0.562557 0.868287 -0.307699\natom 7.97327 1.00806 12.01927 Cu 0.0 0.0 -0.320661 -0.261778 0.669270\natom -2.66364 6.77284 5.72900 Cu 0.0 0.0 0.139583 0.019303 -0.109989\natom 1.20070 10.29289 0.05535 Cu 0.0 0.0 0.128534 -0.142367 0.170485\natom 11.56341 4.52622 6.20016 Cu 0.0 0.0 -0.422768 -0.016949 -0.036187\natom 11.38589 1.88456 6.19868 Cu 0.0 0.0 0.372210 0.381362 0.737046\natom 1.40326 7.62107 0.05935 Cu 0.0 0.0 -0.033455 0.158910 -0.065999\natom -1.58357 10.14682 6.04642 Cu 0.0 0.0 -0.379767 0.174140 -0.180950\natom 14.96000 4.73947 0.51353 Cu 0.0 0.0 0.006641 -0.111737 -0.663340\natom 9.29990 3.14755 5.15272 Cu 0.0 0.0 0.061569 -0.071409 -0.358628\natom 3.53691 9.25165 1.30906 Cu 0.0 0.0 -0.125188 0.014477 -0.355908\natom 0.12350 8.58777 6.97217 Cu 0.0 0.0 0.252618 -0.140246 0.211007\natom 6.05665 1.96577 10.95461 Cu 0.0 0.0 -0.283723 0.768305 -0.764843\natom 1.18112 1.75131 11.43049 Cu 0.0 0.0 0.333113 0.363145 -0.628417\natom 5.30761 7.55794 7.06217 Cu 0.0 0.0 0.075613 0.089545 0.076289\natom 8.25350 9.94587 0.90472 Cu 0.0 0.0 0.156252 0.411619 -0.017478\natom 4.20292 4.21519 4.99966 Cu 0.0 0.0 0.439937 0.186328 0.429797\natom 4.21872 1.27195 5.32118 Cu 0.0 0.0 -0.390136 0.091093 -0.241003\natom 8.58249 7.39808 0.79129 Cu 0.0 0.0 0.151405 0.076977 -0.139024\natom 5.41339 10.15269 6.72431 Cu 0.0 0.0 0.421021 0.246152 -0.150048\natom 1.18172 4.35109 10.91327 Cu 0.0 0.0 -0.019770 0.068034 0.017337\natom -2.18879 3.57592 9.94910 Cu 0.0 0.0 0.202534 -0.045578 0.220734\natom 7.61115 8.85323 7.83294 Cu 0.0 0.0 0.134966 -0.097336 0.851080\natom 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3.09760 Cu 0.0 0.0 0.272462 0.156177 -0.187015\natom 6.72896 6.68660 2.38717 Cu 0.0 0.0 -0.256522 -0.018980 0.335159\natom 3.67571 11.09697 8.86140 Cu 0.0 0.0 -0.088144 -0.340246 -0.388276\natom 3.12084 5.15555 9.24911 Cu 0.0 0.0 -0.184530 0.230609 1.072112\natom 1.05251 0.68247 7.85059 Cu 0.0 0.0 0.190857 0.169244 0.174255\natom 5.41042 6.02785 10.84761 Cu 0.0 0.0 -0.263230 -0.059625 0.128623\natom 8.87918 11.70123 4.72201 Cu 0.0 0.0 -0.350901 -0.217265 -0.302340\natom 4.71735 5.14723 1.62155 Cu 0.0 0.0 -0.037088 0.297995 -0.184864\natom 3.57371 1.10987 1.44231 Cu 0.0 0.0 -0.197962 -0.265239 -0.091625\natom 8.87277 6.99746 4.73890 Cu 0.0 0.0 0.146668 -0.004404 -0.370001\natom 5.79905 11.57054 10.82641 Cu 0.0 0.0 -0.057973 -0.331349 0.238891\natom 0.48660 5.87614 7.54282 Cu 0.0 0.0 0.132922 -0.203636 0.016477\natom 3.51808 2.53755 9.07380 Cu 0.0 0.0 -0.056264 -0.171712 0.096410\natom 3.21469 8.21910 8.95145 Cu 0.0 0.0 -0.033383 0.163191 -0.104063\natom 5.96330 9.79846 2.91535 Cu 0.0 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5.21104 Cu 0.0 0.0 0.245095 -0.446805 0.418171\natom 4.46850 9.26065 11.12519 Cu 0.0 0.0 0.306807 -0.334017 0.208098\natom 2.26961 3.05527 6.77589 Cu 0.0 0.0 -0.353764 0.114041 -0.013309\natom -3.90401 1.03284 11.46200 Cu 0.0 0.0 0.001015 0.337714 -0.325268\natom 10.04011 7.25985 6.84980 Cu 0.0 0.0 0.244773 -0.320630 0.146804\natom 13.21623 11.02955 0.89163 Cu 0.0 0.0 0.112597 -0.567873 -0.018682\natom -0.51286 4.85669 5.10751 Cu 0.0 0.0 0.253876 -1.088299 -0.207555\natom -1.04706 0.72587 5.52506 Cu 0.0 0.0 -0.099741 -0.138001 -0.186971\natom 13.36150 6.86658 0.76794 Cu 0.0 0.0 -0.569603 0.126375 -0.339053\natom 10.12348 11.14436 6.92507 Cu 0.0 0.0 0.593908 0.253869 -0.057492\natom -3.89692 5.17103 11.34088 Cu 0.0 0.0 0.395195 0.075991 0.300955\natom 7.87836 1.23229 12.01207 Cu 0.0 0.0 0.600315 0.231568 -0.311218\natom -2.28976 7.34384 6.19682 Cu 0.0 0.0 -0.380809 -0.111907 0.356839\natom 0.90592 10.61238 0.07715 Cu 0.0 0.0 -0.021947 -0.526168 -0.337515\natom 11.21629 4.63957 6.08514 Cu 0.0 0.0 0.631695 -0.363444 -0.142808\natom 11.47399 1.84913 6.17495 Cu 0.0 0.0 -0.256208 0.011497 0.228798\natom -4.72531 7.79138 12.13660 Cu 0.0 0.0 -0.093923 -0.235496 -0.291658\natom -1.97425 10.19444 5.89992 Cu 0.0 0.0 0.234500 0.468924 -0.024111\natom 14.39111 4.08618 0.16464 Cu 0.0 0.0 -0.556085 0.585623 -0.525095\natom 9.22431 3.12924 5.09010 Cu 0.0 0.0 -0.022337 -0.006849 0.451603\natom 3.15359 9.23676 0.94540 Cu 0.0 0.0 0.062331 -1.208447 0.413546\natom -0.14476 8.70876 6.83661 Cu 0.0 0.0 0.152332 1.033735 -0.156566\natom 4.89805 3.75290 10.52765 Cu 0.0 0.0 0.148448 -0.525528 -1.048912\natom 1.18373 1.85350 11.20431 Cu 0.0 0.0 -0.813557 -0.325455 -0.019585\natom 4.99915 8.31554 8.33002 Cu 0.0 0.0 -0.257787 -0.231200 -0.043920\natom 8.01583 10.44061 0.99761 Cu 0.0 0.0 -0.396911 -0.277273 -0.135587\natom 4.05055 4.30653 4.67827 Cu 0.0 0.0 0.299631 -0.319010 0.353422\natom 3.83077 1.60663 5.02926 Cu 0.0 0.0 0.612574 0.439723 0.812241\natom 8.32052 7.15493 0.99878 Cu 0.0 0.0 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2.46552 4.42771 Cu 0.0 0.0 -0.188209 -0.209773 0.685848\natom 2.84329 9.02647 0.89470 Cu 0.0 0.0 0.371717 0.515513 -0.026191\natom -0.34393 9.17943 7.03999 Cu 0.0 0.0 0.471892 0.582224 -0.019573\natom 5.33064 3.56966 10.70737 Cu 0.0 0.0 -0.399926 0.130172 0.596025\natom 1.05972 2.11438 10.15431 Cu 0.0 0.0 -0.718098 -0.330092 -0.354223\natom 5.10288 8.07193 6.44549 Cu 0.0 0.0 0.132556 -0.656152 -0.222280\natom 8.23428 10.62487 1.00344 Cu 0.0 0.0 -0.383120 -0.348728 0.290531\natom 4.26793 4.03251 5.37922 Cu 0.0 0.0 0.173414 0.401816 0.140236\natom 3.88090 1.48691 5.09628 Cu 0.0 0.0 0.446610 0.451931 1.046696\natom 8.68604 7.43322 0.82228 Cu 0.0 0.0 -0.057976 0.051102 0.148079\natom 5.80908 10.29903 7.15036 Cu 0.0 0.0 0.017333 0.468693 0.113093\natom 0.58906 4.28541 11.67626 Cu 0.0 0.0 0.123722 0.167641 -0.252301\natom -2.22381 3.92945 10.06964 Cu 0.0 0.0 -0.176000 -0.517677 -0.037408\natom 8.52022 8.06816 8.42355 Cu 0.0 0.0 -0.539787 -0.009521 0.329340\natom 9.41015 9.06777 2.70081 Cu 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0.185854\natom 6.72647 3.36344 3.13401 Cu 0.0 0.0 0.076229 0.649473 -0.191995\natom 13.43144 1.17425 2.35847 Cu 0.0 0.0 -0.024154 0.484279 -0.278269\natom -1.33140 7.29165 3.46685 Cu 0.0 0.0 -0.005651 0.021867 -0.144259\natom -4.56035 10.74940 9.82563 Cu 0.0 0.0 0.079017 -0.091598 -0.327849\natom 11.18471 5.03689 8.54341 Cu 0.0 0.0 -0.178459 -0.385846 0.399103\natom 3.76512 1.21307 11.84350 Cu 0.0 0.0 0.225466 0.873535 -0.175913\natom 2.73076 7.20423 7.16718 Cu 0.0 0.0 -0.256518 0.430094 -0.124481\natom 5.50669 10.83828 0.49333 Cu 0.0 0.0 0.784932 -0.382042 0.233489\natom 6.87650 4.79090 5.21529 Cu 0.0 0.0 -0.314584 0.323137 0.060103\natom 7.96189 2.92785 7.30116 Cu 0.0 0.0 -0.044054 0.067920 -0.437947\natom -1.16153 8.18641 11.26996 Cu 0.0 0.0 0.297148 0.206065 -0.040745\natom 1.84239 9.63947 5.13552 Cu 0.0 0.0 -0.125355 0.243608 0.284855\natom 11.47668 2.95602 1.20412 Cu 0.0 0.0 0.043196 0.128106 -0.338968\natom 2.24530 2.58721 1.67052 Cu 0.0 0.0 -0.205593 0.029137 0.373175\natom 10.62441 8.88619 4.88068 Cu 0.0 0.0 -1.307493 -0.356001 0.820718\natom 7.20227 9.21429 10.96714 Cu 0.0 0.0 1.033546 0.128614 -0.900206\natom -0.50952 2.99767 8.13693 Cu 0.0 0.0 0.352371 0.136043 -0.042488\natom -2.52217 0.89947 8.28566 Cu 0.0 0.0 -0.367935 -0.888869 -0.183422\natom 8.07793 6.37133 10.22021 Cu 0.0 0.0 0.262309 -0.134192 0.317673\natom 11.51480 11.05542 3.77604 Cu 0.0 0.0 0.217547 0.093776 0.155530\natom 1.04284 4.86593 2.32444 Cu 0.0 0.0 0.409966 -0.257020 0.289949\nenergy -565.869365\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_364\nlattice 15.407895943 0.000000000 0.000000000\nlattice 0.000000000 12.010195158 0.000000000\nlattice -6.052957620 0.000000000 12.220369325\natom 9.90969 0.88005 10.22538 S 0.0 0.0 0.061660 0.067318 -0.013678\natom -3.37387 6.88266 7.97768 S 0.0 0.0 0.671599 -0.033925 -0.217290\natom -0.07517 11.00717 1.84789 S 0.0 0.0 -0.796247 -0.842819 -0.270703\natom 12.83106 5.03137 4.29282 S 0.0 0.0 -0.156444 0.375730 -1.205419\natom 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7.78762 S 0.0 0.0 0.307424 0.468046 -0.003713\natom 11.73155 2.72999 3.65429 Cu 0.0 0.0 -0.205403 0.640337 -0.151061\natom 0.66613 8.60344 2.43088 Cu 0.0 0.0 0.355992 -0.185770 -0.193305\natom -2.29146 9.07539 8.56173 Cu 0.0 0.0 -0.042250 -0.301201 0.203443\natom 8.80854 2.86845 9.60856 Cu 0.0 0.0 -0.320755 -0.172987 0.168747\natom 5.30302 0.86141 8.63190 Cu 0.0 0.0 -0.108091 0.111894 -0.000144\natom 0.76235 6.97487 10.00323 Cu 0.0 0.0 0.193386 0.458556 0.543800\natom 3.73917 11.16368 3.99209 Cu 0.0 0.0 0.098091 -0.299638 -0.050441\natom 8.67336 4.89055 2.05390 Cu 0.0 0.0 -0.160631 -0.313052 -0.310123\natom 8.64053 1.22491 1.89864 Cu 0.0 0.0 -0.531404 -0.329692 0.082656\natom 3.87060 7.15001 3.98688 Cu 0.0 0.0 0.343764 -0.245635 0.192519\natom 0.86747 10.99916 10.12815 Cu 0.0 0.0 0.553844 0.504072 -0.015565\natom 5.37338 4.54608 7.96600 Cu 0.0 0.0 -0.790988 0.612881 0.188971\natom 5.30235 2.96679 0.74196 Cu 0.0 0.0 -0.279765 0.053589 0.061152\natom 7.17235 8.95634 5.48649 Cu 0.0 0.0 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0.229835\natom 5.98003 10.54222 7.01848 Cu 0.0 0.0 -0.268979 0.613439 -0.609902\natom 0.90330 4.52668 11.09130 Cu 0.0 0.0 -0.015860 -0.009756 0.061747\natom -1.32816 3.08064 10.41773 Cu 0.0 0.0 -0.493890 -0.065188 0.008047\natom 9.10624 9.49641 8.40497 Cu 0.0 0.0 -0.542911 -0.259645 -0.523702\natom 10.54298 9.22840 1.73106 Cu 0.0 0.0 0.204844 -0.051950 0.245926\natom 1.86215 3.19365 4.41637 Cu 0.0 0.0 -0.141626 0.355328 -0.128984\natom 8.65817 0.51941 8.36583 Cu 0.0 0.0 -0.022819 -0.077019 -0.417244\natom -2.29063 6.73982 10.04842 Cu 0.0 0.0 -0.249279 0.046797 0.036677\natom 0.78869 11.47440 3.73836 Cu 0.0 0.0 0.042456 0.785562 0.690769\natom 11.47010 5.64750 2.12577 Cu 0.0 0.0 0.841797 -0.701578 -0.310140\natom 11.01177 0.57843 1.86130 Cu 0.0 0.0 0.197024 -0.015556 -0.043231\natom 1.22968 6.56272 4.18906 Cu 0.0 0.0 0.397033 0.185775 -0.533834\natom -1.52602 10.80217 10.42185 Cu 0.0 0.0 0.048520 -0.018238 -0.396147\natom 7.92076 4.83320 8.23419 Cu 0.0 0.0 -0.018300 0.409796 0.050275\natom -3.94273 2.51079 9.87109 Cu 0.0 0.0 0.017620 0.266824 0.223522\natom -4.55916 7.98488 9.42777 Cu 0.0 0.0 0.221198 0.396508 0.242025\natom 13.87117 9.54453 2.93125 Cu 0.0 0.0 -0.109165 0.414871 0.021803\natom -1.40621 3.62781 3.03879 Cu 0.0 0.0 -0.153347 -0.155868 -0.157467\natom 6.05605 0.98838 3.61087 Cu 0.0 0.0 0.089056 0.351384 -0.322776\natom 6.52273 6.78567 2.73100 Cu 0.0 0.0 -0.159560 0.079069 -0.461882\natom 3.34673 10.94069 8.63529 Cu 0.0 0.0 -0.013092 -0.001600 0.434844\natom 3.01646 5.57841 9.56349 Cu 0.0 0.0 0.011887 -0.100686 -0.196458\natom 1.10921 0.20152 7.76368 Cu 0.0 0.0 -0.048169 0.377541 0.179621\natom 5.12377 6.74708 10.50326 Cu 0.0 0.0 0.292989 -0.078557 -0.046372\natom 8.33426 11.37061 4.39522 Cu 0.0 0.0 -0.309672 0.456973 1.103821\natom 4.01440 5.33921 1.45196 Cu 0.0 0.0 0.281696 -0.159501 0.221087\natom 4.17980 0.49294 1.84301 Cu 0.0 0.0 -0.708562 0.503849 0.133844\natom 8.51653 6.09526 4.09474 Cu 0.0 0.0 -0.112062 0.324024 0.920042\natom 5.80361 11.03217 11.01922 Cu 0.0 0.0 0.246308 0.819800 -0.409801\natom 0.95847 5.79446 7.92616 Cu 0.0 0.0 0.062632 -0.810195 -0.092027\natom 2.96305 2.39870 9.28766 Cu 0.0 0.0 -0.376596 -0.385463 -0.239446\natom 3.60853 8.44318 9.05850 Cu 0.0 0.0 -0.562347 -0.238037 -0.236064\natom 5.48287 9.48018 3.23817 Cu 0.0 0.0 0.111306 -0.286517 -0.380803\natom 6.21831 3.58996 3.10914 Cu 0.0 0.0 0.319425 0.713190 -0.944335\natom 13.74706 1.16261 2.84686 Cu 0.0 0.0 0.354621 -0.100438 -0.423985\natom -1.29721 7.00319 3.41310 Cu 0.0 0.0 -0.206902 0.041096 -0.118138\natom -4.68435 10.69262 9.66255 Cu 0.0 0.0 0.380924 0.151717 0.212082\natom 10.57580 4.76256 8.65377 Cu 0.0 0.0 0.531670 -0.061357 -0.271865\natom 3.71797 0.98293 11.40162 Cu 0.0 0.0 0.525492 0.658514 0.307460\natom 2.53480 7.54988 6.78049 Cu 0.0 0.0 -0.334903 -0.538353 -0.101635\natom 5.79484 10.98424 0.86999 Cu 0.0 0.0 0.006181 -0.680788 -0.287408\natom 6.64317 4.95970 5.79592 Cu 0.0 0.0 0.078628 0.412810 -0.470822\natom 7.34928 2.85016 6.85061 Cu 0.0 0.0 0.305209 -0.869851 0.282557\natom -0.96136 8.40340 11.57072 Cu 0.0 0.0 0.322996 0.123072 -0.046541\natom 1.70149 9.70799 5.02821 Cu 0.0 0.0 0.494988 -0.725456 0.395173\natom 11.19334 3.07832 0.70713 Cu 0.0 0.0 0.017619 0.066578 0.468611\natom 2.09418 2.35857 1.90076 Cu 0.0 0.0 0.590285 0.046588 0.179024\natom 10.33836 8.78125 4.31616 Cu 0.0 0.0 0.065755 -0.568139 -0.425498\natom 5.89067 9.24446 8.99449 Cu 0.0 0.0 0.523743 -0.721595 0.604441\natom -1.14274 3.80931 7.90099 Cu 0.0 0.0 0.308959 -0.339936 -0.691805\natom -2.36795 1.21533 8.28698 Cu 0.0 0.0 0.203000 0.092259 0.005930\natom 8.53458 7.21069 9.64141 Cu 0.0 0.0 -0.409408 -0.413745 -0.018811\natom 11.55690 10.92225 3.71225 Cu 0.0 0.0 0.189831 -0.055151 0.044155\natom 0.69592 4.64286 2.31510 Cu 0.0 0.0 0.344125 0.135702 -0.065281\nenergy -565.990879\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_381\nlattice 15.385741848 0.000000000 0.000000000\nlattice 0.000000000 11.992926415 0.000000000\nlattice 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0.91658 3.51003 S 0.0 0.0 -0.025710 0.218997 0.164401\natom 9.72191 7.07385 2.57166 S 0.0 0.0 0.252975 -0.489957 -0.533307\natom 6.96231 11.13555 8.52477 S 0.0 0.0 -0.102876 -0.192364 0.693199\natom -0.16488 5.00468 9.68879 S 0.0 0.0 -0.214984 -0.149486 0.200145\natom 6.20210 2.77235 8.90275 S 0.0 0.0 0.469766 0.358906 -0.272382\natom 0.03756 9.00345 9.32576 S 0.0 0.0 -0.168706 -0.326194 0.277892\natom 3.12586 9.23074 3.37204 S 0.0 0.0 -0.259214 0.082255 0.040123\natom 9.21873 3.12578 2.76508 S 0.0 0.0 0.533195 -0.199118 -0.390083\natom 5.89762 2.41070 5.31104 S 0.0 0.0 0.156862 0.784978 -0.415392\natom 6.46045 8.82153 1.01071 S 0.0 0.0 -0.092926 -0.697439 0.131623\natom 3.53235 9.36614 6.97528 S 0.0 0.0 -0.513743 0.042048 0.929375\natom 2.75437 3.11046 11.15101 S 0.0 0.0 0.244122 0.086010 -0.281202\natom 0.19551 2.85135 5.93667 S 0.0 0.0 0.027964 1.746397 0.752066\natom 12.18158 8.96670 0.13662 S 0.0 0.0 1.320401 -0.448471 -0.550601\natom 9.20715 9.29605 6.30654 S 0.0 0.0 0.048463 0.052221 -0.147774\natom -2.92174 3.34768 11.88610 S 0.0 0.0 0.050199 0.007954 0.053206\natom -0.01405 3.10105 1.74874 S 0.0 0.0 -1.256553 -0.991026 -0.911636\natom 12.54325 8.73734 4.60141 S 0.0 0.0 -0.668099 0.095902 0.446299\natom 9.62451 9.13033 10.77019 S 0.0 0.0 -0.951899 -0.199389 -1.096222\natom -3.10511 3.22896 7.68996 S 0.0 0.0 -0.191980 0.090752 0.181160\natom 11.71159 3.05493 3.42301 Cu 0.0 0.0 -0.614346 -0.362901 0.023987\natom 0.79889 9.09650 2.66785 Cu 0.0 0.0 0.238005 -0.467958 0.174566\natom -2.08133 8.83859 8.65215 Cu 0.0 0.0 -0.179033 0.047382 0.078499\natom 8.38345 2.76307 9.68602 Cu 0.0 0.0 0.229534 0.245422 0.262122\natom 5.54077 0.71040 7.81966 Cu 0.0 0.0 -0.543723 0.104156 0.062864\natom 0.99210 6.95531 9.77437 Cu 0.0 0.0 -0.602864 0.096841 -0.245447\natom 4.20764 11.27650 3.97750 Cu 0.0 0.0 -0.278442 -0.155795 -0.117456\natom 8.13159 5.19745 2.25772 Cu 0.0 0.0 0.413031 0.147334 -0.261297\natom 8.36442 1.04172 2.16453 Cu 0.0 0.0 0.107403 0.359153 0.029200\natom 4.04014 7.43026 4.19327 Cu 0.0 0.0 0.025806 -0.391033 -0.250307\natom 1.08559 10.74557 10.13730 Cu 0.0 0.0 0.244089 0.321486 0.307173\natom 5.43244 4.84036 8.49903 Cu 0.0 0.0 -0.042731 0.001572 -0.263977\natom 4.95985 2.74918 0.76036 Cu 0.0 0.0 0.650124 -0.342751 0.513306\natom 7.22194 8.55888 5.13075 Cu 0.0 0.0 0.101469 0.485354 0.064326\natom 4.08575 8.93844 11.41566 Cu 0.0 0.0 -0.063231 -0.122843 -0.190502\natom 2.43992 3.21396 7.47876 Cu 0.0 0.0 -0.077031 -0.429449 -0.733630\natom -3.69931 1.28064 11.77260 Cu 0.0 0.0 -0.000236 -0.476267 -0.203761\natom 9.59453 7.14221 6.76060 Cu 0.0 0.0 0.064258 0.528379 -0.184228\natom 12.93847 11.01270 0.90444 Cu 0.0 0.0 0.145432 0.063889 0.019712\natom -0.67141 5.34105 5.72446 Cu 0.0 0.0 0.298332 -0.441454 -0.161557\natom -1.03351 1.21550 5.48592 Cu 0.0 0.0 -0.822244 -0.480912 -0.710894\natom 13.53716 7.27495 0.93480 Cu 0.0 0.0 -0.455545 0.179711 -0.179631\natom 10.44943 11.14808 6.98596 Cu 0.0 0.0 0.042278 -0.186179 -0.387224\natom -3.95394 5.16669 11.07826 Cu 0.0 0.0 0.068204 0.464504 0.580785\natom 14.40140 1.55724 0.07078 Cu 0.0 0.0 -0.175878 0.077724 -0.485831\natom 12.39439 6.48209 5.81842 Cu 0.0 0.0 -0.038046 -0.033224 -0.289350\natom 1.04454 10.25970 0.33599 Cu 0.0 0.0 0.362430 0.420358 0.063403\natom 11.23577 4.09764 5.81212 Cu 0.0 0.0 0.196093 0.306465 0.077735\natom 11.34717 1.45856 5.99899 Cu 0.0 0.0 -0.229240 0.458238 0.843086\natom -4.88353 7.68744 12.16439 Cu 0.0 0.0 0.051403 -0.373407 0.449964\natom -2.41629 11.10057 5.98287 Cu 0.0 0.0 -0.056673 -0.124752 -0.355872\natom 14.06539 4.26781 0.26329 Cu 0.0 0.0 0.564317 -0.090832 -0.077447\natom 9.07661 3.06429 4.99900 Cu 0.0 0.0 0.095513 -0.073796 -0.030946\natom 3.26713 9.15368 1.12967 Cu 0.0 0.0 -0.131499 -0.290807 -0.245339\natom -0.75901 9.07992 5.52474 Cu 0.0 0.0 0.102919 0.030057 0.034120\natom 6.22595 3.07567 11.14685 Cu 0.0 0.0 -0.035081 -0.198247 0.345145\natom 1.04384 1.46412 11.32789 Cu 0.0 0.0 0.052973 0.431111 0.163237\natom 5.40090 7.63747 6.67094 Cu 0.0 0.0 -0.331470 0.252398 0.495228\natom 8.19074 10.20427 0.59092 Cu 0.0 0.0 0.040328 -0.185457 0.244075\natom 4.33223 4.14579 5.18777 Cu 0.0 0.0 0.336363 -0.551805 0.367652\natom 3.73865 1.60189 5.41475 Cu 0.0 0.0 -0.207445 -0.174537 -0.155598\natom 8.32237 7.46590 0.77550 Cu 0.0 0.0 0.261253 0.027276 0.048673\natom 5.56080 10.18706 6.52803 Cu 0.0 0.0 -0.120393 0.271156 0.429619\natom 0.90273 4.27241 11.65507 Cu 0.0 0.0 -0.421922 0.020559 0.088453\natom -1.32779 2.49177 10.47752 Cu 0.0 0.0 -0.066978 -0.009727 -0.291503\natom 7.50996 9.04857 7.85521 Cu 0.0 0.0 -0.114700 -0.644251 -0.023218\natom 10.73365 9.18162 1.73432 Cu 0.0 0.0 -0.426919 -0.210149 0.411827\natom 1.68706 3.88963 4.75733 Cu 0.0 0.0 0.421421 0.255337 -0.128322\natom 8.90235 0.55317 8.27384 Cu 0.0 0.0 -0.356851 0.199562 0.968593\natom -1.91232 6.50406 9.88035 Cu 0.0 0.0 -0.013697 -0.067394 0.369268\natom 0.70885 11.72524 3.95941 Cu 0.0 0.0 0.192362 0.149447 -0.950886\natom 11.46683 5.56791 2.08637 Cu 0.0 0.0 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0.666495\natom 8.74565 10.95480 4.44779 Cu 0.0 0.0 -0.025090 0.028731 0.033567\natom 3.54443 5.02070 1.41742 Cu 0.0 0.0 0.589850 0.094526 -0.614166\natom 3.89299 0.51950 1.67325 Cu 0.0 0.0 -0.211794 0.375796 0.197401\natom 8.49610 6.58551 4.36667 Cu 0.0 0.0 -0.229787 -0.505967 0.349418\natom 5.35664 11.62425 10.17223 Cu 0.0 0.0 0.338571 -0.174452 0.098649\natom 1.15555 5.17702 7.77428 Cu 0.0 0.0 -0.311910 0.969390 -0.102685\natom 3.94218 2.34269 9.26197 Cu 0.0 0.0 -0.013668 0.177291 0.664866\natom 3.02818 8.36965 9.09589 Cu 0.0 0.0 0.170657 0.738510 -0.961676\natom 6.08672 9.67955 3.02232 Cu 0.0 0.0 0.062660 0.005973 0.143035\natom 6.72045 3.34718 3.28666 Cu 0.0 0.0 0.081021 0.143585 0.156367\natom 14.07917 1.21330 2.58036 Cu 0.0 0.0 0.075805 0.108580 0.212462\natom -1.33035 7.12343 3.72602 Cu 0.0 0.0 -0.031493 -0.175596 -0.252433\natom -4.20539 10.27979 9.69921 Cu 0.0 0.0 -0.862454 -0.412546 0.637965\natom 11.05511 5.10139 8.71689 Cu 0.0 0.0 -0.367556 -0.100313 -0.305517\natom 3.50289 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0.507960\natom 8.34727 1.45761 12.13804 Cu 0.0 0.0 -0.243015 -0.063355 0.384000\natom -1.91304 7.87559 6.27224 Cu 0.0 0.0 0.182465 -0.125591 -0.042310\natom 1.22350 10.01820 0.09676 Cu 0.0 0.0 0.329541 0.496820 0.527121\natom 11.03890 4.23073 6.01320 Cu 0.0 0.0 0.292541 0.331663 -0.043652\natom 11.16626 1.63740 5.92045 Cu 0.0 0.0 0.082946 -0.262730 0.096357\natom 1.35930 7.49830 0.32093 Cu 0.0 0.0 0.515749 -0.127466 -0.306337\natom -0.85889 10.05124 5.32919 Cu 0.0 0.0 -1.065336 -0.557422 -0.438531\natom 14.30901 4.24465 0.08140 Cu 0.0 0.0 -0.109927 0.237845 -0.214746\natom 9.13306 2.95525 5.08939 Cu 0.0 0.0 -0.026585 0.633991 -0.361295\natom 3.35563 8.63970 1.52747 Cu 0.0 0.0 0.084884 -0.344084 -0.620736\natom 0.05199 10.35869 7.80543 Cu 0.0 0.0 0.069402 -0.307704 0.363921\natom 6.24559 2.85868 11.46795 Cu 0.0 0.0 -0.045526 0.210162 -0.045442\natom -0.90545 3.86279 7.69139 Cu 0.0 0.0 0.435370 0.040458 0.173097\natom 5.54793 7.73506 7.04433 Cu 0.0 0.0 -0.163665 -0.165320 -0.216939\natom 8.07550 10.08907 0.73957 Cu 0.0 0.0 0.274589 0.224532 -0.123789\natom 3.86209 3.99357 5.47504 Cu 0.0 0.0 0.713637 -0.120590 -0.371456\natom 3.71869 1.30131 5.20309 Cu 0.0 0.0 0.295541 0.532457 0.277208\natom 8.40070 7.55699 1.22324 Cu 0.0 0.0 0.918084 -0.017097 -0.172116\natom 5.46091 10.31389 6.88238 Cu 0.0 0.0 0.636379 0.305708 -0.274427\natom 7.51135 4.14117 0.07082 Cu 0.0 0.0 -0.806049 0.048342 0.411963\natom -0.51039 2.11068 12.19002 Cu 0.0 0.0 -0.204222 0.342347 -0.129231\natom 7.64971 8.80134 8.07465 Cu 0.0 0.0 0.024751 0.202055 -0.029493\natom 10.63996 9.17796 1.90314 Cu 0.0 0.0 -0.099927 -0.100229 -0.384760\natom 1.91044 3.03927 4.31101 Cu 0.0 0.0 -0.164463 -0.083120 -0.642104\natom 8.54230 0.59236 8.32153 Cu 0.0 0.0 0.100847 0.345645 -0.240471\natom -1.94652 6.36568 9.71590 Cu 0.0 0.0 -0.478626 0.132312 -0.016137\natom 0.70683 11.56552 3.80038 Cu 0.0 0.0 0.008461 -0.141396 -0.923532\natom 11.99474 5.27822 2.27860 Cu 0.0 0.0 -0.046479 -0.015532 -0.072183\natom 10.62870 0.31821 1.25739 Cu 0.0 0.0 -0.076343 -0.123905 0.577853\natom 1.70035 6.52242 4.52969 Cu 0.0 0.0 -0.279728 -0.075011 -0.557715\natom -3.24874 11.45552 9.69927 Cu 0.0 0.0 0.144854 -0.195696 0.557575\natom 7.73758 4.97325 7.80800 Cu 0.0 0.0 -0.044919 0.103196 0.649776\natom 10.96720 1.77377 8.69401 Cu 0.0 0.0 -0.300278 -0.312687 0.318857\natom 10.82361 8.87007 8.96418 Cu 0.0 0.0 0.231775 -0.245660 0.012344\natom 14.05468 9.39456 2.79846 Cu 0.0 0.0 0.039430 0.506389 -0.355454\natom -0.99274 3.66799 3.45835 Cu 0.0 0.0 -1.391409 -0.130586 1.244523\natom 5.85981 0.99793 3.45645 Cu 0.0 0.0 0.350906 -0.124246 -0.365691\natom 6.48697 6.99586 2.70234 Cu 0.0 0.0 -0.115451 -0.567635 0.286672\natom 2.93836 10.45460 9.06873 Cu 0.0 0.0 -0.020449 -0.147844 -0.074972\natom 2.87856 5.04724 9.79968 Cu 0.0 0.0 0.021081 0.802603 -0.883295\natom 1.29372 0.50868 8.19919 Cu 0.0 0.0 0.102742 0.247199 0.257831\natom 5.13997 6.95690 10.71659 Cu 0.0 0.0 0.318380 -0.429011 0.569694\natom 9.21189 11.04964 4.94144 Cu 0.0 0.0 -0.226220 0.047172 -0.338081\natom 4.17990 5.48315 1.65625 Cu 0.0 0.0 -0.061149 0.024759 0.018456\natom 4.10194 0.86935 1.46185 Cu 0.0 0.0 -0.325118 -0.356689 0.351853\natom 8.58370 6.73929 4.48938 Cu 0.0 0.0 -0.183253 0.073806 -0.336752\natom 5.26307 11.59673 10.20705 Cu 0.0 0.0 0.019433 -0.355420 0.226874\natom 1.13195 5.80679 7.86158 Cu 0.0 0.0 -0.111944 0.087901 -0.238204\natom 3.31937 2.27542 9.37690 Cu 0.0 0.0 -0.379342 0.001606 -0.305208\natom 3.34483 7.75485 9.18163 Cu 0.0 0.0 0.229823 0.791373 -1.131988\natom 6.39482 9.67667 3.15210 Cu 0.0 0.0 -0.094336 -0.795504 -1.057292\natom 7.22236 3.07618 3.37057 Cu 0.0 0.0 -0.235709 0.757783 -0.201253\natom 13.81610 1.37747 2.41015 Cu 0.0 0.0 -0.421134 -0.441437 0.596880\natom 13.61863 6.95911 3.36775 Cu 0.0 0.0 0.023890 -0.090556 0.088628\natom 9.66897 10.87854 9.80118 Cu 0.0 0.0 -0.033376 -0.779259 -0.024728\natom 10.82688 4.33130 8.82018 Cu 0.0 0.0 0.025061 0.077835 -0.093269\natom 0.52093 2.93256 9.86635 Cu 0.0 0.0 -0.188157 0.007009 0.046775\natom 3.05650 7.20429 6.37008 Cu 0.0 0.0 0.120817 0.632245 0.914727\natom 5.20021 10.41570 0.87518 Cu 0.0 0.0 -0.188866 0.673383 -0.290560\natom 6.42686 4.58096 5.63885 Cu 0.0 0.0 -0.033889 0.762947 -0.354041\natom 7.36790 2.66841 6.96813 Cu 0.0 0.0 -0.012373 -0.662690 0.449303\natom -1.75746 8.94560 11.22149 Cu 0.0 0.0 -0.054235 0.048564 0.114417\natom 1.59161 9.16276 5.19623 Cu 0.0 0.0 0.020031 -0.301564 0.165598\natom 10.50996 3.65139 0.92879 Cu 0.0 0.0 0.046307 0.222299 -0.224030\natom 2.01792 2.44696 1.65061 Cu 0.0 0.0 -0.342256 0.024552 0.104635\natom 10.30682 8.44864 4.52417 Cu 0.0 0.0 0.305590 0.465815 -0.017841\natom 7.37748 10.13132 10.55358 Cu 0.0 0.0 -0.193255 -0.757234 0.590322\natom -2.71285 3.62703 10.24934 Cu 0.0 0.0 0.527769 -0.745936 -0.242669\natom -2.00328 1.53124 8.67936 Cu 0.0 0.0 -0.218742 -0.112512 -0.294307\natom 8.67784 6.86853 9.57287 Cu 0.0 0.0 0.367175 0.005611 0.281933\natom 11.50050 10.89754 3.55966 Cu 0.0 0.0 0.489069 -0.022825 0.280065\natom 0.89763 4.90137 2.64962 Cu 0.0 0.0 -0.158200 0.447650 -0.491001\nenergy -565.862799\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_4_84\nlattice 15.394732161 0.000000000 0.000000000\nlattice 0.000000000 11.999934213 0.000000000\nlattice -6.047786257 0.000000000 12.209928816\natom 9.61168 1.01608 10.42083 S 0.0 0.0 -1.191961 0.326660 -1.181596\natom -3.21463 7.13012 7.92824 S 0.0 0.0 0.049036 -0.759072 0.181961\natom -0.42418 11.01723 1.89660 S 0.0 0.0 0.333188 0.647869 -0.641060\natom 12.57968 4.81260 4.21805 S 0.0 0.0 -0.689337 0.705370 -0.234277\natom 12.37573 0.60830 4.48839 S 0.0 0.0 0.095115 0.347347 -0.081025\natom -0.23392 7.11563 2.18372 S 0.0 0.0 0.321971 -0.092889 -0.125810\natom -3.13570 10.97664 7.97003 S 0.0 0.0 -0.416872 0.419920 0.025070\natom 9.30709 5.19093 10.26152 S 0.0 0.0 -0.754127 -0.201431 -0.317495\natom 9.13516 1.37154 6.38042 S 0.0 0.0 -1.096006 -0.210231 0.119114\natom -2.70337 6.66340 12.17485 S 0.0 0.0 -0.157448 -0.296626 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1.08496 9.38773 S 0.0 0.0 0.075403 -0.259372 -0.621188\natom 6.34054 6.96441 8.61398 S 0.0 0.0 0.402595 -0.723001 0.756399\natom 9.44702 11.07522 2.60649 S 0.0 0.0 0.124143 -0.220298 0.690966\natom 2.72174 5.30293 3.64982 S 0.0 0.0 0.266566 0.028388 -0.153975\natom 2.60106 0.99820 3.39868 S 0.0 0.0 0.133698 0.036970 0.506408\natom 9.67221 7.04953 2.66653 S 0.0 0.0 0.663083 0.216520 -0.406805\natom 6.55951 10.81941 8.71656 S 0.0 0.0 0.888808 -0.578877 0.126432\natom -0.43056 5.03803 9.41733 S 0.0 0.0 -0.875998 0.186108 0.476104\natom 6.23491 2.85458 9.12792 S 0.0 0.0 -0.171363 -0.175101 -0.393890\natom 0.26889 9.09982 9.39944 S 0.0 0.0 -0.960259 -0.011127 0.730988\natom 3.33550 9.12756 3.25851 S 0.0 0.0 -0.476551 0.507590 0.573442\natom 9.77520 2.96453 2.59647 S 0.0 0.0 -0.566787 -0.098178 0.053217\natom 5.79508 2.94445 5.16220 S 0.0 0.0 -0.192775 0.225588 -0.442090\natom 6.39349 8.80687 0.95628 S 0.0 0.0 0.536297 0.033054 0.478046\natom 3.57897 9.37915 7.30478 S 0.0 0.0 -0.089353 -0.299949 -0.470851\natom 2.54131 2.93520 10.85817 S 0.0 0.0 0.548588 0.635996 0.557775\natom 0.11490 2.58780 5.99619 S 0.0 0.0 -0.279109 0.432643 0.237834\natom 12.07420 8.66439 0.11760 S 0.0 0.0 0.137315 0.465733 -0.244200\natom 9.11578 9.42753 6.08890 S 0.0 0.0 0.085813 -0.380959 0.423167\natom -3.06738 3.08427 11.82586 S 0.0 0.0 -0.476050 0.444938 -0.035933\natom -0.16711 2.91929 1.70250 S 0.0 0.0 0.112141 -0.369133 0.403277\natom 12.70125 8.95407 4.51622 S 0.0 0.0 -0.614318 -0.276546 0.371311\natom 9.74225 8.92619 10.84282 S 0.0 0.0 -1.202930 0.042308 0.276779\natom -3.20438 3.20878 7.65061 S 0.0 0.0 -0.289725 0.255052 -0.043827\natom 11.61231 2.69652 3.80240 Cu 0.0 0.0 0.391770 -0.054206 -0.012242\natom 1.41467 9.00327 2.21273 Cu 0.0 0.0 -0.693663 -0.090294 0.140010\natom -2.02004 9.24063 8.95087 Cu 0.0 0.0 -0.002940 0.062471 -0.095837\natom 8.47278 3.04012 9.76366 Cu 0.0 0.0 0.100954 0.077138 -0.004811\natom 5.55379 0.69555 8.27037 Cu 0.0 0.0 -0.295086 0.648668 0.173849\natom 0.98887 6.80797 9.65854 Cu 0.0 0.0 0.315449 0.420092 0.858395\natom 3.98611 11.29356 4.10338 Cu 0.0 0.0 -0.059508 -0.194572 -0.276054\natom 8.64481 4.91039 2.26137 Cu 0.0 0.0 -0.328978 0.165652 0.435556\natom 8.75433 1.02416 1.86991 Cu 0.0 0.0 -0.162032 0.422745 0.038880\natom 4.00536 7.36720 4.38927 Cu 0.0 0.0 -0.419183 -0.459053 -0.186304\natom 0.88893 11.18860 10.19854 Cu 0.0 0.0 0.031607 0.013853 -0.013245\natom 5.40073 4.66855 8.09789 Cu 0.0 0.0 -0.310233 0.364814 0.004740\natom 4.87332 3.39932 0.69978 Cu 0.0 0.0 0.290394 -0.353057 0.154532\natom 7.09795 8.93120 5.14333 Cu 0.0 0.0 -0.138698 0.057681 -0.002073\natom 3.70509 9.16447 11.39834 Cu 0.0 0.0 0.437228 0.207239 0.318415\natom 2.14836 3.16801 6.88630 Cu 0.0 0.0 0.123592 0.057810 0.339965\natom -4.01817 0.82592 11.54874 Cu 0.0 0.0 1.075584 0.120868 0.176741\natom 9.89746 7.31258 6.48309 Cu 0.0 0.0 -0.066838 0.070502 0.539386\natom 12.83146 10.85639 0.92260 Cu 0.0 0.0 -0.084247 -1.064775 -0.010222\natom -0.85835 5.29316 5.27531 Cu 0.0 0.0 0.266740 0.088528 0.150937\natom -0.96231 0.67333 5.44880 Cu 0.0 0.0 -0.125972 -0.190869 -0.229224\natom 13.27310 6.79948 0.98173 Cu 0.0 0.0 0.313132 0.102051 -0.307492\natom 10.35055 11.21868 6.73618 Cu 0.0 0.0 -0.021537 0.094407 0.324178\natom -4.07327 5.24861 11.02907 Cu 0.0 0.0 0.502192 -0.418966 0.619331\natom 14.59142 1.31024 0.24868 Cu 0.0 0.0 -0.068794 0.045746 -0.445258\natom -1.74385 7.33635 6.30245 Cu 0.0 0.0 -0.103437 0.578930 -0.038327\natom -3.35489 8.70890 11.45086 Cu 0.0 0.0 -0.023471 0.541481 -0.089149\natom 11.31328 4.92819 6.00106 Cu 0.0 0.0 0.124277 -0.354520 0.331290\natom 11.25926 1.71899 6.14910 Cu 0.0 0.0 0.576058 0.153646 0.284591\natom 0.98756 7.18957 0.34767 Cu 0.0 0.0 0.148718 -0.153860 -0.137073\natom -1.89896 10.08005 6.27442 Cu 0.0 0.0 0.269953 0.252167 0.119336\natom 14.82866 4.39039 0.09180 Cu 0.0 0.0 -0.340573 0.056927 -0.147375\natom 8.87065 3.15774 4.77775 Cu 0.0 0.0 0.162618 -0.061351 -0.073613\natom 4.26291 8.24195 1.31598 Cu 0.0 0.0 -0.565867 -0.359922 0.446488\natom 0.22021 8.94420 7.17875 Cu 0.0 0.0 -0.009841 -0.048517 -0.177917\natom 6.40085 2.98501 11.36531 Cu 0.0 0.0 -0.043523 0.040280 0.578155\natom 0.68234 1.70256 11.28986 Cu 0.0 0.0 -0.186826 -0.000683 0.598754\natom 5.26580 7.81845 6.92142 Cu 0.0 0.0 -0.445676 0.563885 -0.652128\natom 7.95813 10.36362 0.83491 Cu 0.0 0.0 0.260321 0.279152 0.286081\natom 4.02707 4.53549 5.72216 Cu 0.0 0.0 0.303080 -0.344855 -0.551618\natom 4.88474 0.93701 5.70079 Cu 0.0 0.0 0.230608 -0.147864 0.000888\natom 8.40394 7.67556 0.92211 Cu 0.0 0.0 0.254484 -0.067652 -0.202682\natom 5.45731 10.49026 6.43732 Cu 0.0 0.0 -0.319092 -0.150872 0.710175\natom 1.92198 5.32701 11.97658 Cu 0.0 0.0 -0.166622 -0.121822 -0.420830\natom -1.69666 2.70600 10.16369 Cu 0.0 0.0 0.358334 -0.239200 -0.109338\natom 7.73517 8.65378 7.88721 Cu 0.0 0.0 0.014459 0.573296 -0.606470\natom 10.68735 9.34588 1.74641 Cu 0.0 0.0 -0.439726 -0.201238 -0.448797\natom 3.64684 3.23269 3.42151 Cu 0.0 0.0 -0.105829 0.453683 0.248434\natom 8.16102 0.46510 8.73219 Cu 0.0 0.0 0.192188 -0.096106 -0.270723\natom -1.85848 6.99743 9.97666 Cu 0.0 0.0 -0.218796 -0.500547 0.105423\natom 0.44296 10.99190 3.89648 Cu 0.0 0.0 0.053204 -0.031752 0.450723\natom 11.40933 5.64462 2.13470 Cu 0.0 0.0 -0.351827 -0.331935 0.076030\natom 11.37718 0.81774 2.06734 Cu 0.0 0.0 -0.611435 -0.193327 0.366000\natom 1.24707 3.95096 4.76029 Cu 0.0 0.0 0.324235 0.241591 -0.679982\natom -1.73266 11.65475 10.37157 Cu 0.0 0.0 0.212860 0.380882 -0.393675\natom 7.92981 5.30116 8.00521 Cu 0.0 0.0 -0.074729 0.092064 0.136868\natom -4.37850 2.67262 9.46103 Cu 0.0 0.0 0.057103 -0.274483 0.202197\natom 10.74864 8.24225 9.06354 Cu 0.0 0.0 -0.023471 -0.253329 -0.343244\natom -1.34377 9.25254 2.80510 Cu 0.0 0.0 0.066385 -0.309898 -0.212381\natom -1.25306 3.50180 3.61142 Cu 0.0 0.0 0.828273 -0.763521 -0.530900\natom 4.64858 1.24230 2.50442 Cu 0.0 0.0 -0.291803 0.025681 0.328332\natom 6.53044 7.12313 2.58618 Cu 0.0 0.0 -0.404324 -0.176835 0.114015\natom 3.42063 11.23257 8.81961 Cu 0.0 0.0 -0.139718 -0.054750 0.343706\natom 1.61485 4.27536 9.16077 Cu 0.0 0.0 0.642162 0.094405 0.089876\natom 1.26903 0.78491 7.43404 Cu 0.0 0.0 -1.098981 -0.221546 0.289553\natom 5.44186 6.51461 10.64828 Cu 0.0 0.0 -0.234590 0.410853 -0.301251\natom 8.72291 11.76178 4.86728 Cu 0.0 0.0 -0.175245 -0.098272 -0.519528\natom 4.27688 5.51884 1.91924 Cu 0.0 0.0 -0.221023 0.180796 0.180334\natom 1.77230 11.62345 1.70957 Cu 0.0 0.0 0.079069 -0.087724 -0.045952\natom 8.38154 6.62650 4.33873 Cu 0.0 0.0 -0.248326 -0.078102 0.530087\natom 5.44621 11.15069 10.67735 Cu 0.0 0.0 -0.260829 0.197381 0.016748\natom 0.25174 6.00863 7.54331 Cu 0.0 0.0 -0.473189 -0.146569 -0.892481\natom 3.67802 2.75104 8.87314 Cu 0.0 0.0 0.089110 -0.140927 0.371747\natom 2.51073 8.84239 9.22448 Cu 0.0 0.0 0.304691 -0.146943 -0.082301\natom 5.64252 9.90858 2.81814 Cu 0.0 0.0 0.513423 -0.142304 0.173443\natom 6.39122 3.17193 2.99785 Cu 0.0 0.0 -0.031973 0.226428 -0.106016\natom 13.78888 1.08302 2.77159 Cu 0.0 0.0 0.380818 -0.054563 -0.043082\natom 13.12264 6.93811 3.58588 Cu 0.0 0.0 0.102637 -0.131678 0.110528\natom -4.66009 10.58928 9.71670 Cu 0.0 0.0 0.270843 0.740876 -0.231055\natom 10.75300 5.17700 8.48767 Cu 0.0 0.0 0.320537 0.022315 -0.106267\natom 4.11156 1.42512 11.60725 Cu 0.0 0.0 -0.071191 -0.081941 -0.092444\natom 2.32526 7.33053 7.02235 Cu 0.0 0.0 0.427606 0.281319 -0.144109\natom 5.26791 11.54654 0.92695 Cu 0.0 0.0 0.083201 -0.202086 -0.734203\natom 6.67048 4.91449 5.73851 Cu 0.0 0.0 0.114596 -0.072935 -0.046294\natom 7.31983 2.84405 7.11799 Cu 0.0 0.0 0.238880 -0.435311 -0.009822\natom -0.99607 9.51313 11.51918 Cu 0.0 0.0 0.286827 0.011185 -0.967809\natom 2.19299 9.57686 5.32161 Cu 0.0 0.0 0.241050 0.033235 0.022089\natom 9.93250 3.87375 0.41602 Cu 0.0 0.0 0.481727 -0.314361 -0.455733\natom 2.25099 2.16311 1.55201 Cu 0.0 0.0 -0.161767 0.376937 -0.281467\natom 10.36062 8.54543 4.32968 Cu 0.0 0.0 0.069128 -0.029650 -0.123427\natom 7.34497 9.46663 10.56599 Cu 0.0 0.0 0.041764 -0.020438 0.077561\natom -0.98405 3.73778 7.63702 Cu 0.0 0.0 0.162342 -0.121758 -0.145897\natom -2.40276 1.09063 8.20590 Cu 0.0 0.0 -0.080006 0.099818 0.070596\natom 8.38212 7.22719 9.70741 Cu 0.0 0.0 0.218579 0.053630 0.432589\natom 11.63611 10.66180 3.47400 Cu 0.0 0.0 -0.056787 0.347671 0.309465\natom 0.79475 4.80215 2.38119 Cu 0.0 0.0 0.125964 0.706002 0.158111\nenergy -566.729768\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/nnp-norm2/Cu2S_PBE/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type (optional argument: shift parameter alpha).\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              15 15          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.02315        # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n"
  },
  {
    "path": "examples/nnp-norm2/Cu2S_PBE/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   9.0599751834064512E-06   1.0532468503252377E-04   3.6847021293483606E-05   1.7835227890378858E-05\n         1          2   9.7407364273681052E-01   1.3707738052511558E+00   1.1369440745957258E+00   7.8204475954228067E-02\n         1          3   7.1848939224232239E-04   4.4674859070114722E-03   2.0895924503338856E-03   7.3120307120467013E-04\n         1          4   3.0839567122259082E+00   3.7813435073058135E+00   3.4528586198914484E+00   1.4064243940314194E-01\n         1          5   2.2189388498896456E-02   7.9061298236177566E-02   4.6882111087211208E-02   1.1334173255596679E-02\n         1          6   3.8952165155842438E+00   4.3441311727516858E+00   4.1103871329683823E+00   1.0081266947910023E-01\n         1          7   2.6712677530189782E-01   5.9473970044295299E-01   4.2213464431656117E-01   6.6280004153616373E-02\n         1          8   1.7488245369534008E+00   2.9970797892758485E+00   2.4245345856012999E+00   3.3547211267555982E-01\n         1          9   1.2449429394722318E+00   1.9865309035277523E+00   1.5467135618608816E+00   1.4014804188095897E-01\n         1         10   1.1223156151012470E+00   2.5212331659045919E+00   1.7587293340594636E+00   3.2461918457849698E-01\n         1         11   2.1481809886285510E+00   2.6220186753539645E+00   2.3310995299236956E+00   8.8131868940220931E-02\n         1         12   1.7776050347753956E+00   2.3809724095942570E+00   2.0364639196570282E+00   1.3155538475628997E-01\n         1         13   1.3332847701336610E+00   1.5746629195008022E+00   1.4563536842862850E+00   4.2017894226904072E-02\n         1         14   1.2858206220015138E+00   2.0264861435690955E+00   1.6934105509660398E+00   1.7102915724852555E-01\n         1         15   2.9294864910145735E-01   4.4946746329067233E-01   3.8841663360361012E-01   2.7956119240284072E-02\n         1         16   5.7872135122682178E-01   9.8756180790304116E-01   8.3451027680267253E-01   1.0555635785949544E-01\n         1         17   3.8741023011801198E-02   7.2203189636501464E-02   5.8498155834018059E-02   7.5296916290786700E-03\n         1         18   2.0277259701907649E-01   3.0112576816621817E-01   2.5147215506855941E-01   2.3499268876717772E-02\n         1         19   3.7801436874671336E-02   7.0536882716121713E-02   4.9634849414845854E-02   6.1773772857441848E-03\n         1         20   5.0064324676730110E-01   7.4508315795400359E-01   6.0180452708486698E-01   5.1996620314567893E-02\n         1         21   2.1149505846062664E+00   3.0086297694152004E+00   2.4747104151629071E+00   1.7292530958618688E-01\n         1         22   1.1394588610202373E-01   2.1081557230804215E-01   1.4831150247830030E-01   1.8362267327821737E-02\n         1         23   2.7720108269028820E+00   3.8299737046031495E+00   3.2180772088958483E+00   2.3336401126515627E-01\n         1         24   3.6286754324115282E+00   5.7694079721003524E+00   4.5677164220944100E+00   4.0055418877074411E-01\n         1         25   4.7719054215943416E-05   1.2246818750522671E-04   7.4309480650870812E-05   1.4049426561453186E-05\n         1         26   4.4333857694921347E-03   1.0168132968853614E-02   6.4777145172573158E-03   1.0560078551356503E-03\n         1         27   1.8935344189773007E-01   2.9276868067133349E-01   2.3061829866368203E-01   1.9869300862039235E-02\n         1         28   2.7495263408916264E-02   5.1213942108460010E-02   3.6085221024876463E-02   4.5471765030753852E-03\n         1         29   1.5310085616939009E+00   2.1188212216180502E+00   1.7827060035919868E+00   1.2407502507441381E-01\n         1         30   9.1939368654489029E-01   1.5687613774310878E+00   1.2194589135682272E+00   1.1985456906857926E-01\n         1         31   1.1384194008436653E-02   2.3126249430002573E-02   1.5575425703929386E-02   2.2146366574977774E-03\n         1         32   2.0448065764191037E-01   3.1629369745824260E-01   2.5154663060838428E-01   2.3850462668791081E-02\n         1         33   1.1626342355721448E+00   1.6596585560150436E+00   1.3609763259982417E+00   9.7025354891779811E-02\n         1         34   3.4316641363009756E-02   6.9456153312452348E-02   4.6556693792454321E-02   6.6083772055404314E-03\n         1         35   1.2570958839654798E+00   1.7927721704892265E+00   1.4803334101702972E+00   1.1860808472662136E-01\n         1         36   1.9184389026233195E+00   3.1127425453883704E+00   2.4371296559244344E+00   2.2052811165984698E-01\n         1         37   1.3666602477642141E-05   3.6887119050541216E-05   2.2035946317575125E-05   4.3651698230106994E-06\n         1         38   1.5546007659584370E-03   3.7299211557246326E-03   2.3070975415581158E-03   3.9808430326865882E-04\n         1         39   9.5479248087773236E-02   1.4915614707917241E-01   1.1672777818282745E-01   1.0800506748273341E-02\n         1         40   8.2256292725268153E-03   1.6899821492838311E-02   1.1302096732556740E-02   1.6295481703454844E-03\n         1         41   7.1803116051488303E-01   1.0254065821299467E+00   8.4691642411810830E-01   6.5464610909859736E-02\n         1         42   4.3595215959198219E-01   7.9518024924121622E-01   5.9831255803436056E-01   6.6317667245823150E-02\n         1         43   1.6018052377239585E-06   6.3139472908861676E-06   3.1301163360828299E-06   8.9765713700450499E-07\n         1         44   5.5894373857206245E-04   1.2582981249606513E-03   8.3605542167432972E-04   1.3725912741223295E-04\n         1         45   1.9834153225893669E-02   3.6953383616309544E-02   2.6655881843534047E-02   3.2893647917620217E-03\n         1         46   4.8532464966417719E-06   1.9377662342507640E-05   9.3658745542551994E-06   2.6969170145130424E-06\n         1         47   5.7210047587520222E-03   1.1312250481264765E-02   7.9476527861615121E-03   1.1714188135300359E-03\n         1         48   3.3967605349763057E-02   6.3249588182648683E-02   4.5545662343088447E-02   5.6959930803433916E-03\n         1         49   1.5639262624940886E-09   8.3504433474424934E-09   3.7442340287849395E-09   1.1995146772038598E-09\n         1         50   7.8957248103475445E-07   2.9544681844058944E-06   1.5151455992697584E-06   3.9867319456010048E-07\n         1         51   7.2498799380692138E-04   1.3809328629292383E-03   9.6644345650243621E-04   1.3123931111184769E-04\n         1         52   1.1513160050255707E-06   4.7893410133550852E-06   2.2589402933267841E-06   6.5898376566604767E-07\n         1         53   3.6899770288464700E-03   7.1094664560615549E-03   5.0980228781949740E-03   7.3353667640355786E-04\n         1         54   4.7965507914503420E-03   9.9638635159890153E-03   6.7789560394143624E-03   9.7722280949143615E-04\n         1         55   1.5451956482050941E+00   2.3220436338643187E+00   1.8415448061529172E+00   1.4900811986127621E-01\n         1         56   1.0376025533554976E+01   1.3514156671640468E+01   1.1711913234153359E+01   6.9043448028822885E-01\n         1         57   1.5701057712031107E+01   2.1962128408086549E+01   1.8503912750199724E+01   1.2048466878385966E+00\n         1         58   1.2864599135285206E+00   1.9362796091456074E+00   1.5296352202317265E+00   1.2444939857329487E-01\n         1         59   1.0320708418905122E+01   1.3479378639347569E+01   1.1669078130198949E+01   6.9581154676801382E-01\n         1         60   1.3090165473148913E+01   1.8879509137434656E+01   1.5695674905250980E+01   1.0931378423262064E+00\n         1         61   4.3949671163273307E-01   6.6160243665646234E-01   5.2723334425502655E-01   4.2993883711550253E-02\n         1         62   2.9890536869213755E+00   3.9500888865673107E+00   3.3855167809122926E+00   2.0324895614210023E-01\n         1         63   4.2275144808489822E+00   6.1612946214333260E+00   5.0958280611414732E+00   3.6862169589359611E-01\n         1         64   1.9185607361878201E-01   2.8944064348772253E-01   2.2731439323863312E-01   1.8996742597552314E-02\n         1         65   2.9026605370229617E+00   3.8497469707096537E+00   3.3051920388798002E+00   1.9911530882408360E-01\n         1         66   2.3438496537639137E+00   3.5204619280878231E+00   2.8884010974233134E+00   2.1832718765517053E-01\n         1         67   6.9283609471405960E-01   1.1058987063631822E+00   8.4968265286534050E-01   7.8761639155134011E-02\n         1         68   5.6199553705237868E+00   7.4791069644037620E+00   6.4024365024328160E+00   4.1010868642000720E-01\n         1         69   1.0122784690107945E+01   1.4291263786081892E+01   1.1953107220137360E+01   8.1231683230934826E-01\n         1         70   5.7630325723191356E-01   9.2120973806494955E-01   7.0451206294375790E-01   6.5503757358981521E-02\n         1         71   5.5816677967841954E+00   7.4524531203782809E+00   6.3701823389995216E+00   4.1337199146852777E-01\n         1         72   8.1814308596273086E+00   1.2046187228492565E+01   9.8959454279237082E+00   7.3693018572142865E-01\n         1         73   1.9683621110198224E-01   3.1483962875013105E-01   2.4341849856766945E-01   2.2785709321534491E-02\n         1         74   1.6224327804059289E+00   2.2000746987409392E+00   1.8576991122906539E+00   1.2119788736172697E-01\n         1         75   2.6824556989527628E+00   3.9796129564866725E+00   3.2536477391535117E+00   2.5391823361142091E-01\n         1         76   8.5437320410141501E-02   1.3697848298848525E-01   1.0393883860134831E-01   9.8598667429722949E-03\n         1         77   1.5658995991452884E+00   2.1246128383334932E+00   1.8015087956004576E+00   1.1834810393072710E-01\n         1         78   1.3424688092108374E+00   2.1185521226749700E+00   1.6933096448820459E+00   1.4372755682490063E-01\n         1         79   1.8399604045159085E-03   4.6078436172890926E-03   2.8732492264063715E-03   5.3669875232076759E-04\n         1         80   8.3119007268670886E-02   1.4143987144302400E-01   1.0720479470296071E-01   1.2233438802574289E-02\n         1         81   8.2986229100932440E-01   1.1659993267145721E+00   9.5731232407073363E-01   6.2937506381837788E-02\n         1         82   1.5195998543626908E-03   3.8170540359299199E-03   2.3668873493119533E-03   4.3917065596871631E-04\n         1         83   8.3135091173795000E-02   1.3792368162367827E-01   1.0504414743580952E-01   1.1948444459807837E-02\n         1         84   5.9272476782117589E-01   8.5144251489636957E-01   6.9438400963164004E-01   5.0523816606940102E-02\n         1         85   5.1242702350366395E-04   1.3164833282719027E-03   8.2580897561123105E-04   1.6044356357127206E-04\n         1         86   2.4177855790506391E-02   4.2547629449549935E-02   3.2115297327594376E-02   3.6713016163428484E-03\n         1         87   2.0122938661082074E-01   3.1075655422908821E-01   2.4139090930899196E-01   2.1214491900174683E-02\n         1         88   2.2132439378046761E-04   5.5088453823861694E-04   3.3668003207199519E-04   6.2376803338715469E-05\n         1         89   2.3027980736970780E-02   3.8841317908682060E-02   2.9292718346934195E-02   3.3895769533309845E-03\n         1         90   5.2372336035986039E-02   9.0714868461914608E-02   6.8656095125797234E-02   7.2445739677856899E-03\n         2          1   4.0474971172859331E-01   7.5006567516921008E-01   5.6847203729786222E-01   6.0430206098981788E-02\n         2          2   1.3353906173596923E+00   1.9806788567435805E+00   1.7264293099457233E+00   1.1122407155180723E-01\n         2          3   2.7536142595336643E-01   1.6894860339160629E+00   9.4702751302538624E-01   2.2067010751820818E-01\n         2          4   1.5876722829708281E+00   2.4217772337436254E+00   2.0551935664841889E+00   1.2712120842704425E-01\n         2          5   1.4511042760308031E+00   3.5922343911407904E+00   2.7594257532435136E+00   3.7513591802481777E-01\n         2          6   8.5814050322533819E-01   1.6441451598733146E+00   1.2122672928006482E+00   1.7190521428635971E-01\n         2          7   3.0078311930034207E+00   4.2487019279912408E+00   3.6580019562692998E+00   2.6991737605934291E-01\n         2          8   6.1100547250486992E-01   1.1886079210423453E+00   8.7936466702973159E-01   1.1360805119566607E-01\n         2          9   2.3721421380267542E+00   4.1224470139175287E+00   2.9755098267290143E+00   2.8098369790820915E-01\n         2         10   5.6108720328738604E-01   1.4458120707216497E+00   1.0182319598285139E+00   1.9514169765972178E-01\n         2         11   1.5109081390331569E+00   2.8788713701577131E+00   2.2108452631677888E+00   3.1011945809770602E-01\n         2         12   6.1792055810799862E-01   1.1603464814608015E+00   8.4670527548301966E-01   1.2995048804049558E-01\n         2         13   1.0615056624169890E+00   1.8857477549274466E+00   1.4396598836902490E+00   1.7317124283867941E-01\n         2         14   3.3270237895325261E-01   5.4191124490734888E-01   4.1725513840133621E-01   4.3778794272664942E-02\n         2         15   5.3998480145205663E-01   9.2791508619766461E-01   7.1227247840008556E-01   6.3682279386797214E-02\n         2         16   7.6412956388619363E-02   1.7328848000985436E-01   1.2573607753427973E-01   2.7267517483162949E-02\n         2         17   1.6484707519840752E-01   3.9009224653142621E-01   2.6521305089996344E-01   4.3286456399155585E-02\n         2         18   3.7035009562869875E-01   6.7340728612782041E-01   4.9412274857479327E-01   5.1089795554998201E-02\n         2         19   1.2029190895961805E+00   1.9737544680797443E+00   1.5968227035810045E+00   1.2581845339983122E-01\n         2         20   5.1973156450199820E-01   1.3018517286558244E+00   8.7456817249090490E-01   1.3694358773059637E-01\n         2         21   3.3842258746633935E-01   6.2519118150691022E-01   4.6084768542038518E-01   4.6068154352970521E-02\n         2         22   4.6697488042548958E+00   6.4166565216867069E+00   5.4456041336763024E+00   3.1869234590817225E-01\n         2         23   1.8677358418035883E+00   3.2822728183389396E+00   2.4780580508547652E+00   2.4609190542743561E-01\n         2         24   5.6392866964169404E-02   1.0506481202213031E-01   7.5697740272970007E-02   7.4355551695651839E-03\n         2         25   4.3065975423585368E-02   1.3036115047831273E-01   8.2943455920119619E-02   1.4889586170872110E-02\n         2         26   5.2816130547569595E-03   6.2287415311250330E-02   2.5593847758110935E-02   9.5708091233591835E-03\n         2         27   3.6712465685067676E-02   7.9259568522760795E-02   5.5284621941296914E-02   7.3475243523464231E-03\n         2         28   2.1141609301816788E+00   2.7488986070800467E+00   2.3742455069141060E+00   1.2963195224982030E-01\n         2         29   6.2712628223860023E-01   1.0738921139460145E+00   8.0573045811556010E-01   7.7971825073565426E-02\n         2         30   1.6607907847763759E-01   3.3826739218472440E-01   2.3692128148627437E-01   2.8810363549669725E-02\n         2         31   5.9757981452146103E-01   1.0636712565134816E+00   8.3959217727950775E-01   7.6316933142163104E-02\n         2         32   2.1736066482646946E-01   6.3251543867608839E-01   4.0207599705127822E-01   7.0819648650692998E-02\n         2         33   1.3563987111899592E-01   2.7914311585597890E-01   1.9604872870839607E-01   2.2548910149263378E-02\n         2         34   2.4464500593819585E+00   3.5955968335220412E+00   2.9585138046431712E+00   1.9850715242021319E-01\n         2         35   8.0832094385969488E-01   1.5774770035410111E+00   1.1449938485700757E+00   1.3052879241405127E-01\n         2         36   2.8167007928499344E-02   5.4686841405124309E-02   3.8909334876594141E-02   4.3685799270078342E-03\n         2         37   1.8331399003310937E-02   6.1497188402318569E-02   3.7307975732735560E-02   6.9262760890092647E-03\n         2         38   1.8896568313787098E-03   2.6897417454648655E-02   1.0257940854010531E-02   4.1488575001855672E-03\n         2         39   1.2849094460607837E-02   3.0518949214805757E-02   2.0315313896012273E-02   2.9816385781476929E-03\n         2         40   1.1200069428594479E+00   1.5052341251528873E+00   1.2644868420755846E+00   7.5320733889483113E-02\n         2         41   2.7035646948676634E-01   4.8489183467683100E-01   3.6349586483938395E-01   3.8377617987964179E-02\n         2         42   5.3053949124328196E-04   2.7155325962249467E-03   1.4693706396216907E-03   3.8959415772759525E-04\n         2         43   6.7401629277260401E-03   2.3201286281629065E-02   1.4640944577609236E-02   2.8410089366966932E-03\n         2         44   6.2382619651656502E-04   5.2265286032864176E-03   2.3699618414709639E-03   6.7793659350880262E-04\n         2         45   2.6923091933240488E-04   1.4956100254684128E-03   7.2655641233727007E-04   2.0295830894179534E-04\n         2         46   3.2691667338044829E-02   9.0678442175656987E-02   5.7560599609013351E-02   9.2644559468720508E-03\n         2         47   2.5937848143038644E-03   1.2533306717853509E-02   6.9449698875901373E-03   1.7521094867609646E-03\n         2         48   1.1065671090876680E-04   5.4798479633027641E-04   2.9144248910504801E-04   7.1966742641759755E-05\n         2         49   4.2464545684178411E-05   2.8233031802457707E-04   1.3361662448779281E-04   3.5206701689485923E-05\n         2         50   1.3985409801474869E-06   8.0809588283117185E-05   1.9431382375333407E-05   1.1895376337492369E-05\n         2         51   9.3054019716473673E-06   4.5823632299949390E-05   2.0833880149240340E-05   5.6751784807832736E-06\n         2         52   1.4127772597413950E-02   3.2356665294159391E-02   2.1092417412416062E-02   2.8295007137645318E-03\n         2         53   9.3446004825515315E-04   3.6559524548675734E-03   1.8978259865259034E-03   4.5497373887397015E-04\n         2         54   4.0561647183293212E+00   5.3511577891440112E+00   4.6299711825673793E+00   2.2607822910404016E-01\n         2         55   1.3598851789599252E+01   1.7522575343380147E+01   1.5225011184328473E+01   7.5455973105827512E-01\n         2         56   1.0186356996981489E+01   1.5257814554190935E+01   1.2478419186183244E+01   9.1756486891402489E-01\n         2         57   2.7241660240997270E+00   3.7698883318628948E+00   3.1934340302677016E+00   1.8765055324504912E-01\n         2         58   1.3545579675136834E+01   1.7514804194574715E+01   1.5199810125789872E+01   7.5915073035722924E-01\n         2         59   8.8851120452209802E+00   1.3256296184968930E+01   1.0736474670433749E+01   7.9122842999635556E-01\n         2         60   1.0130416975282888E+00   1.5036523945636526E+00   1.1885993721615742E+00   8.1010289342067873E-02\n         2         61   3.6133840749526054E+00   5.1096678879492874E+00   4.2872076737458364E+00   2.6485342899517916E-01\n         2         62   2.8494365098555194E+00   4.4459160112327343E+00   3.5826499046457894E+00   2.7485250904747510E-01\n         2         63   2.4375420511185292E-01   4.1663930223766316E-01   3.2326219517445198E-01   3.1566376420327835E-02\n         2         64   3.7003668077057017E+00   4.7192393274186761E+00   4.1158588543986783E+00   2.0664910066653569E-01\n         2         65   1.6589704302371600E+00   2.5877436611459506E+00   2.0115238927871433E+00   1.6306868634052005E-01\n         2         66   2.5963528414021813E+00   3.5218793656644802E+00   2.9921826210911271E+00   1.5552052039732187E-01\n         2         67   8.2238157571478609E+00   1.0803164078057993E+01   9.3347528178496813E+00   4.9147550494653136E-01\n         2         68   5.5611304318497634E+00   9.1293484032953121E+00   7.2557889620379079E+00   6.2786096878168174E-01\n         2         69   1.6121748987358080E+00   2.3371344880840348E+00   1.9357424405774888E+00   1.1896949214700171E-01\n         2         70   8.2105637462642793E+00   1.0800628439808063E+01   9.3157682461350078E+00   4.9412756165437338E-01\n         2         71   4.8073368871987823E+00   7.7369778643852101E+00   6.1367836252185359E+00   5.1983904151939253E-01\n         2         72   6.2988707120700604E-01   9.8692333079101313E-01   7.5208143541006034E-01   5.8234954693069350E-02\n         2         73   2.1258939549125095E+00   3.1953321974494178E+00   2.6053098950512541E+00   1.9044359659135826E-01\n         2         74   1.5532917130260473E+00   2.6786394254347994E+00   2.0917915229492960E+00   1.8405163928151611E-01\n         2         75   1.2680840736192861E-01   2.2743803731173898E-01   1.7161871974367363E-01   1.8074450438878394E-02\n         2         76   2.2187136985027069E+00   2.8717265218436463E+00   2.4709253283527790E+00   1.3019821416751270E-01\n         2         77   8.8937590898946162E-01   1.4167443362993217E+00   1.1010921888654341E+00   9.5096999539252561E-02\n         2         78   1.8095300556787580E-01   3.1865892584027239E-01   2.4081718922875694E-01   2.2579145563875809E-02\n         2         79   3.1034765586116075E-01   6.2838739580430603E-01   4.6656206018035334E-01   4.9790359551596046E-02\n         2         80   8.9424525698192814E-02   3.9172310190582765E-01   2.2474102076393884E-01   5.0164682483254008E-02\n         2         81   6.6680066826495618E-02   1.4602524718659396E-01   1.0238561277224975E-01   1.3703616384293111E-02\n         2         82   3.1023524376987938E-01   6.1638213549206122E-01   4.6331788482672748E-01   4.9308256727297883E-02\n         2         83   7.1389802836884592E-02   2.8832043829742227E-01   1.6967824403698251E-01   3.6589276735868807E-02\n         2         84   4.3370227935276298E-02   1.0846900715747354E-01   6.1129492385788950E-02   1.0853245385807411E-02\n         2         85   6.9316304367965598E-02   1.9508052518438243E-01   1.1971583803839188E-01   2.5300929630640793E-02\n         2         86   2.5217510355375110E-02   1.2016559641469156E-01   6.8216863995031865E-02   1.4209452257220126E-02\n         2         87   1.7423748428411860E-03   3.8517619122972941E-03   2.6021654639886860E-03   3.6341248057496277E-04\n         2         88   7.5311468371945661E-02   1.4247228480150345E-01   1.0371568981364995E-01   1.1112216486815122E-02\n         2         89   1.1928281484783265E-02   3.5334682941661040E-02   2.3195830907486233E-02   3.9360272836743357E-03\n"
  },
  {
    "path": "examples/nnp-norm2/H2O_RPBE-D3/input.data",
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-0.003918404\natom    18.029065889    5.395499049   22.331535573   O   -0.232616100    0.000000000   -0.022435825   -0.041986031    0.019777229\natom    18.450206642    6.009076358   20.698998634   H    0.117402890    0.000000000    0.010969888    0.018577415   -0.028888712\natom    18.471749528    6.543217109   23.632648433   H    0.122965160    0.000000000    0.008555544    0.023492454    0.010076612\natom     9.730995489   -0.013755322   18.655527357   O   -0.260468440    0.000000000    0.033447936   -0.047525024   -0.017241120\natom    10.958809623    1.192342071   19.181358978   H    0.127148600    0.000000000    0.001410520    0.021472916    0.006833322\natom     8.059414903    0.566851923   18.625879432   H    0.119766210    0.000000000   -0.033795515    0.025211959    0.007633086\natom     5.720611440   23.314163314    9.722983047   O   -0.231630130    0.000000000    0.008590611   -0.010936445   -0.025443175\natom     6.834575199    0.786704638    9.364550991   H    0.130111070    0.000000000   -0.010659177   -0.018642575    0.001906309\natom     6.037573440   21.935577321    8.393439246   H    0.130229060    0.000000000   -0.004288229    0.030206013    0.023949980\natom     9.845218141   19.848952241    1.377688373   O   -0.231982490    0.000000000    0.047210910    0.050634028    0.057109462\natom     8.964032828   21.443191975    1.821177035   H    0.130585310    0.000000000   -0.001359815   -0.006723989   -0.005653620\natom     8.864534929   18.936979498    0.325325931   H    0.140456380    0.000000000   -0.053312141   -0.042279623   -0.051814244\natom    21.486183262    2.087957338   12.058619328   O   -0.245742770    0.000000000   -0.018336922    0.012948985   -0.040170727\natom    20.067351756    2.869512469   10.984447548   H    0.132828300    0.000000000    0.028333925   -0.013530492    0.030219120\natom    22.734213694    1.753487019   10.673217090   H    0.099760430    0.000000000   -0.005192035    0.002432708    0.011480438\natom    -0.218456207   22.514791837    3.828822870   O   -0.233891290    0.000000000    0.001999487    0.001056955    0.002002219\natom    22.977963895   23.403316849    2.478210504   H    0.123135500    0.000000000   -0.006368839    0.004516237   -0.013166446\natom     0.169763614   -0.170292738    5.058420906   H    0.104258450    0.000000000    0.006641123   -0.000339229    0.001710832\natom    22.768355390   15.179884991   22.329029795   O   -0.238086150    0.000000000   -0.046086010   -0.025235881    0.005743850\natom    21.434125066   15.631748923   -0.333185305   H    0.126220700    0.000000000    0.031123799   -0.009001222   -0.035124767\natom    21.989842718   13.702640137   21.289668674   H    0.119659510    0.000000000    0.013004599    0.035317132    0.026225131\natom    12.222509671    8.189955346    1.618074860   O   -0.247919730    0.000000000   -0.001797123    0.017574523   -0.067071366\natom    12.278849988    7.760085945    3.281828197   H    0.111233780    0.000000000   -0.004235384   -0.012471568    0.070548691\natom    13.880380289    7.710926590    1.035681823   H    0.141482170    0.000000000    0.006536703    0.000642119   -0.006764662\natom    13.661907075   10.667631057   11.112100488   O   -0.216001700    0.000000000   -0.037279496   -0.013776615    0.034916697\natom    14.124858034   12.345145386   11.672595370   H    0.133272180    0.000000000    0.003591734    0.013021971    0.000895419\natom    12.435880622   10.173618657   12.581225186   H    0.147421220    0.000000000    0.029632111    0.008032176   -0.031477484\natom    17.486330661   17.032057327    9.295375649   O   -0.235087510    0.000000000   -0.006875504   -0.012809861   -0.043019615\natom    16.911783770   16.107704983    7.688512539   H    0.110665490    0.000000000    0.006713966    0.011433370    0.028267991\natom    18.328113278   18.516190235    8.528021815   H    0.118898150    0.000000000   -0.000175840   -0.004542786    0.012591957\natom     4.935770073   18.663509563    6.368200054   O   -0.194094220    0.000000000    0.031139053   -0.066276697    0.021098669\natom     6.518835853   17.598527525    5.812888693   H    0.156894820    0.000000000   -0.042755679    0.033516151    0.011475343\natom     4.178872098   17.417123193    7.699892475   H    0.137280880    0.000000000    0.015711127    0.037753788   -0.030393813\natom    21.151675148   20.879473220    7.686178727   O   -0.248140030    0.000000000   -0.009994913   -0.003084252    0.015181890\natom    21.725161902   21.081677775    5.962589077   H    0.096696550    0.000000000    0.004375907    0.001697312   -0.018251199\natom    22.673568579   21.355735416    8.583993635   H    0.139564520    0.000000000   -0.002909430   -0.001404868    0.006677838\natom    19.507253717   12.301401988   18.501302967   O   -0.199717660    0.000000000   -0.028410932   -0.035128726    0.043667183\natom    19.776549245   13.758948329   17.594513745   H    0.142371980    0.000000000    0.012693146    0.047711282   -0.031771675\natom    17.867647309   12.681150163   19.378767407   H    0.141514070    0.000000000    0.014688099   -0.002133776   -0.011109509\natom    23.134797998   17.370023640   17.326635511   O   -0.251377170    0.000000000   -0.000268730   -0.000574628   -0.003573364\natom    23.309537263   17.766571487   19.122904057   H    0.118237060    0.000000000    0.005638293   -0.001455468   -0.001185792\natom     0.463480083   18.316502796   16.477809882   H    0.138644360    0.000000000   -0.009964426   -0.001923402    0.004419419\natom     7.198349513    9.467121587   20.207068712   O   -0.243428280    0.000000000    0.009787410   -0.009154114    0.016239349\natom     7.841261053    8.491977165   21.715395794   H    0.127971510    0.000000000   -0.015877818    0.012471507   -0.019846659\natom     5.641732350   10.325405299   20.696485297   H    0.130413120    0.000000000    0.003877775    0.000013170    0.004937889\nenergy   -4900.14395256\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/nnp-norm2/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\natom_energy                     H -0.45890771  # Free atom reference energy (H).\natom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.0041         # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-norm2/H2O_RPBE-D3/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.3221693617312411E+00   2.6431829268494309E+00   2.1712109289368211E+00   1.8491740949754865E-01\n         1          2   8.8165507590121150E-01   1.5021513119899590E+00   1.2778122580628937E+00   9.2610524821423193E-02\n         1          3   9.5063170525557483E-01   1.9645434630136041E+00   1.5754555245780282E+00   1.4788592306892495E-01\n         1          4   6.8720926352748557E-01   1.1734596705047000E+00   9.8013669175527418E-01   7.3842159315803318E-02\n         1          5   5.3114680346458376E-01   1.1735104787393884E+00   8.6903918776136291E-01   9.7965057245763557E-02\n         1          6   4.5446803146192011E-01   7.7208808607104440E-01   6.2874675223192622E-01   4.9613886357228562E-02\n         1          7   2.7732917100342269E-01   6.5610689623748530E-01   4.3632718893459976E-01   5.9842739811322473E-02\n         1          8   3.0248121122588545E-01   5.0262343273858556E-01   4.1296646104933438E-01   3.3605991719978266E-02\n         1          9   2.7091763975787958E-01   4.3771867263061898E-01   3.5532262189207031E-01   3.0837550827151866E-02\n         1         10   3.0607810460301704E-01   8.2737294952385632E-01   5.1367846789526717E-01   8.2396345907449139E-02\n         1         11   1.6781481618321603E-01   3.3262544522941584E-01   2.6405877879038225E-01   2.0079773509946830E-02\n         1         12   1.5199899860595487E-01   5.1758403256923147E-01   2.8216876544103786E-01   5.3030699298770759E-02\n         1         13   7.9964213161399539E-02   2.7810985736196053E-01   1.8323412046338658E-01   2.0256908897343304E-02\n         1         14   5.0022559628496853E-02   3.1251552588862541E-01   1.4532438879262641E-01   3.5408976290196639E-02\n         1         15   1.0972758958750323E-02   1.9780403448379363E-01   7.5743125451543408E-02   2.0368083851198718E-02\n         1         16   4.0564819222288929E-03   2.0020915524049140E-01   4.5553334901545346E-02   2.6816652873187446E-02\n         1         17   1.6392409428096447E-03   2.9517020055424961E-02   1.6279759210012987E-02   5.1720047323677923E-03\n         1         18   5.9064708278282335E-03   2.9881994921192988E-02   1.8893635227048098E-02   3.4996722469230767E-03\n         1         19   1.8153163715731997E-03   3.2340440598797260E-02   1.5251396366744187E-02   4.9976078942981228E-03\n         1         20   7.7218851587917817E-02   1.9164313445186615E-01   1.3079740560426881E-01   1.8047175980621721E-02\n         1         21   6.4007973804529085E-03   3.4352270791092009E-02   1.6008839167468644E-02   4.4985079286083869E-03\n         1         22   7.1919475628770427E-04   1.1394644806220967E-02   5.5243272719661379E-03   2.1112600852613100E-03\n         1         23   4.6183461439172707E-02   1.1842669503328147E-01   7.3672710889966644E-02   1.1140003788632082E-02\n         1         24   9.1433846516636246E-04   7.2448079200631453E-03   3.4708660085473373E-03   1.0041987311934573E-03\n         1         25   1.1212823920457925E-03   7.4909848911080303E-03   3.3413578741542951E-03   9.5694251844215597E-04\n         1         26   1.4490733031593294E-02   3.4896169686888266E-02   2.2593555563529325E-02   3.2185820632296114E-03\n         1         27   6.2962266934873338E-04   5.1814478231837560E-03   2.0022000098156752E-03   6.1375837903328550E-04\n         2          1   1.7278003594190612E+00   3.0200705624254782E+00   2.5556245161257864E+00   1.8104733161286587E-01\n         2          2   5.2830234917918673E-01   1.1347830825159733E+00   9.1702802710027076E-01   8.9012140951749405E-02\n         2          3   1.3413913725634967E+00   2.3281910061725970E+00   1.9602733835105492E+00   1.4178250890732702E-01\n         2          4   3.3973454632955868E-01   7.9106176901817504E-01   6.2374175167509027E-01   6.7920469352681950E-02\n         2          5   9.1198642957067100E-01   1.5175524019444977E+00   1.2574935044638531E+00   9.0840547884065884E-02\n         2          6   1.4007970492770014E-01   3.9737354984873224E-01   2.8710959644163986E-01   3.9568021301260234E-02\n         2          7   6.6026020925081808E-01   9.9631802932099356E-01   8.2593292209866853E-01   5.6260988440501335E-02\n         2          8   4.2701723604415549E-02   1.5473052305514301E-01   1.0198348350484386E-01   1.9093898225897559E-02\n         2          9   5.9779238984500482E-01   8.7214154955749057E-01   7.1064524378414085E-01   4.5991882003602061E-02\n         2         10   1.9985378144803514E-01   6.5655897218566894E-01   4.4271239561305453E-01   7.3593849758180452E-02\n         2         11   4.1502563461045067E-01   6.5057595299175830E-01   5.2811755758076440E-01   2.9733597901087361E-02\n         2         12   1.0539027020125716E-01   4.7399188573233930E-01   2.8778725245738251E-01   6.7239561345988727E-02\n         2         13   2.4956202107947600E-01   4.9952217805446975E-01   3.6646824092677327E-01   2.9672553474082333E-02\n         2         14   3.1300696765894295E-02   3.1614843646709484E-01   1.5249418366539025E-01   5.4780305337940489E-02\n         2         15   6.3223700189372165E-02   3.0994899667375020E-01   1.5148625090308679E-01   2.9292310574299443E-02\n         2         16   8.5041679154014842E-04   1.3041346013164093E-01   3.7068123760173058E-02   2.4399391242546552E-02\n         2         17   4.4317519796445081E-03   2.5144073105818975E-02   1.3864844737089635E-02   3.2528315804001926E-03\n         2         18   8.1860993427251071E-05   1.3466045085857874E-03   5.5084028256248212E-04   2.3430301127519475E-04\n         2         19   7.9083037432116490E-02   2.5796793485264985E-01   1.7694123779133991E-01   2.7939522253685803E-02\n         2         20   2.1441033279915650E-03   1.4776262369620617E-02   8.7339425459512163E-03   2.1168859996502751E-03\n         2         21   1.3804891348827978E-02   4.9194759330688440E-02   2.8874387893367045E-02   5.8165890736636416E-03\n         2         22   2.6051407335652452E-02   1.0496356106048180E-01   6.4565049831895718E-02   1.2764836900154985E-02\n         2         23   2.9045826947719750E-02   7.2380719406296798E-02   4.5302566117440039E-02   7.3746817680981859E-03\n         2         24   1.3607528794234713E-03   1.0984596811105142E-02   5.4354345893373179E-03   1.6123179093972310E-03\n         2         25   1.6511705563216422E-05   5.2501188368496877E-04   1.8911718281856260E-04   8.6408752300015161E-05\n         2         26   2.0072212589651677E-02   7.6648328811296088E-02   4.4378983939995231E-02   8.7718911463090226E-03\n         2         27   1.0836132444402223E-02   5.4980675069752655E-02   3.0545338532716584E-02   7.5167668082524765E-03\n         2         28   6.2351340984659318E-05   1.4410461325923972E-03   5.3991094439800945E-04   2.2577401100509146E-04\n         2         29   8.4843170594598311E-03   2.6368291824445372E-02   1.5321153812859305E-02   2.3405182276765900E-03\n         2         30   4.2231192236936999E-03   1.8846153205016307E-02   1.0613759624824323E-02   2.2975215777576064E-03\n"
  },
  {
    "path": "examples/nnp-predict/AlAuMgO_4G/hardness.008.data",
    "content": "     12.9752105872\n"
  },
  {
    "path": "examples/nnp-predict/AlAuMgO_4G/hardness.012.data",
    "content": "     14.5786310784\n"
  },
  {
    "path": "examples/nnp-predict/AlAuMgO_4G/hardness.013.data",
    "content": "      1.4392244883\n"
  },
  {
    "path": "examples/nnp-predict/AlAuMgO_4G/hardness.079.data",
    "content": "      0.0175182304\n"
  },
  {
    "path": "examples/nnp-predict/AlAuMgO_4G/input.data",
    "content": "begin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -1.9775793498e-02 -6.4032231288e-02  2.0026111119e+01 Mg  3.8788494400e-01 0.0  4.0412140453e-03  7.0265869263e-03 -8.4677419696e-03\natom  2.8784590473e+00  2.8904829958e+00  2.0053576907e+01 O  -3.5909487600e-01 0.0 -3.5357067955e-03 -4.5792491166e-03  9.7973038610e-04\natom  7.2652159693e-02 -1.6211222263e-02  2.4043132172e+01 O  -3.4594157600e-01 0.0 -9.9524052388e-03  8.2613919709e-04  9.0438549577e-03\natom  2.8780260733e+00  2.8998185635e+00  2.4032640394e+01 Mg  3.2864151400e-01 0.0 -4.1635240288e-03 -8.3031064753e-03 -7.5802494690e-03\natom -5.6795412231e-02 -2.2440590601e-02  2.8111288946e+01 Mg  3.4539947400e-01 0.0  8.7251795163e-03 -6.4186986345e-05 -2.4363991342e-02\natom  2.8421666140e+00  2.8834652149e+00  2.8032859289e+01 O  -3.4176807600e-01 0.0 -4.0428635156e-04 -4.3146904728e-03  1.5444027344e-02\natom  6.5214500558e-02 -3.8745751143e-02  3.2113867333e+01 O  -3.0785905600e-01 0.0 -8.7729091934e-03  1.9519751482e-03  1.9968874099e-02\natom  2.8332198764e+00  2.7977822229e+00  3.2113907679e+01 Mg  3.3011505400e-01 0.0  2.2963600668e-03  5.3318657122e-03 -1.5343107719e-02\natom  1.9864553928e-02  1.0486013922e-02  3.6088078099e+01 Al  3.9917245400e-01 0.0  6.7803750166e-05 -7.0094514898e-04  1.5053560097e-02\natom  2.7981764575e+00  2.8796998036e+00  3.6124511960e+01 O  -2.8949547600e-01 0.0  3.6273019714e-03 -2.8183589325e-03 -7.9325270091e-03\natom -8.4521774292e-03 -2.2604637714e-02  4.0153894391e+01 O  -3.6598870600e-01 0.0 -5.8418150328e-04  2.0246535621e-03 -2.5173725174e-02\natom  2.8234702698e+00  2.8619477366e+00  4.0124676317e+01 Mg  3.7450518400e-01 0.0  1.3973418832e-03  7.8928841829e-05  1.5591933809e-02\natom -1.3119630546e-02  5.6888413584e+00  2.0013899747e+01 Mg  3.5809711400e-01 0.0  1.0417032765e-03  1.3876195467e-03 -1.2083096942e-02\natom  2.8848335277e+00  8.5308909417e+00  1.9989943256e+01 O  -3.9844002600e-01 0.0 -3.7448860438e-03  5.0357737828e-03  5.7879501668e-03\natom  1.8241298201e-02  5.6837552365e+00  2.4026099826e+01 O  -3.4215310600e-01 0.0 -2.8868044844e-03  2.3195077530e-03  1.1176398239e-02\natom  2.9361062157e+00  8.4795591997e+00  2.4082757439e+01 Mg  3.2952672400e-01 0.0 -7.9282995215e-03  7.7984136030e-03 -1.5464891041e-02\natom  1.6188356579e-02  5.6698041265e+00  2.8051270020e+01 Mg  3.3684778400e-01 0.0  2.2916383144e-03  4.1861975500e-03 -8.6622492722e-03\natom  2.8977599905e+00  8.5660735578e+00  2.8036115495e+01 O  -3.4409367600e-01 0.0 -3.3334995364e-03 -5.1017646429e-03  1.4470957486e-02\natom  9.8433937020e-04  5.6927154290e+00  3.2118501962e+01 O  -3.4614451600e-01 0.0  9.1005095975e-04 -4.0730943899e-03  4.9154030300e-03\natom  2.8073628502e+00  8.5498039808e+00  3.2128399704e+01 Mg  3.3498536400e-01 0.0  1.6059193804e-03  2.0542016438e-03 -1.6551022033e-02\natom -5.0996334501e-02  5.7492786883e+00  3.6121753734e+01 Mg  3.1982162400e-01 0.0  2.0618641544e-03 -3.0958082828e-03  5.5585234542e-03\natom  2.9059518581e+00  8.5723518134e+00  3.6118083754e+01 O  -3.1404623600e-01 0.0  6.9455266915e-03 -1.4599515105e-02 -4.8605312468e-03\natom  5.2199900983e-04  5.6455106974e+00  4.0180597258e+01 O  -4.0522186600e-01 0.0  7.6228232308e-04  7.0096828995e-03 -8.2712198059e-03\natom  2.8610732470e+00  8.5614353199e+00  4.0139419524e+01 Mg  3.8989854400e-01 0.0 -1.8149964341e-03  3.0632250705e-03  1.2872167566e-02\natom -3.9339238487e-02  1.1415957378e+01  1.9959977720e+01 Mg  4.3559881400e-01 0.0  5.0407268883e-03 -4.9856774589e-03  7.3154652172e-04\natom  2.9183726113e+00  1.4291678042e+01  1.9988445497e+01 O  -3.9816017600e-01 0.0 -9.0864151516e-03 -6.5665931399e-03  2.3483399976e-03\natom -2.1271587207e-02  1.1421205582e+01  2.4027048544e+01 O  -3.4569412600e-01 0.0 -1.6480077969e-03 -2.5662981317e-03  8.0363346320e-03\natom  2.9026486927e+00  1.4185336528e+01  2.4050086987e+01 Mg  3.2444578400e-01 0.0 -6.8689188539e-03  3.2051673130e-03 -1.0907852568e-02\natom -5.1509735258e-02  1.1382810885e+01  2.8094293015e+01 Mg  3.3699468400e-01 0.0  1.0337570946e-02 -2.4454976218e-03 -1.5847585775e-02\natom  2.9119668371e+00  1.4181088046e+01  2.8044752601e+01 O  -3.4257456600e-01 0.0 -8.2941301304e-03  6.6795718730e-03  1.4777589094e-02\natom  1.0413278368e-02  1.1323763827e+01  3.2100372838e+01 O  -3.4337754600e-01 0.0 -4.7694216653e-03  8.0178829511e-03  7.6432220993e-03\natom  2.7888050607e+00  1.4200832470e+01  3.2081624640e+01 Mg  3.3130130400e-01 0.0  1.3617006170e-02 -3.0759183427e-03 -9.3055525579e-03\natom -5.2366574815e-03  1.1380297134e+01  3.6148026784e+01 Mg  3.2297365400e-01 0.0  4.1066729168e-03  2.2768915629e-05  3.9804170447e-03\natom  2.8964801357e+00  1.4225437477e+01  3.6102833042e+01 O  -3.1847690600e-01 0.0 -1.5460639298e-02  1.3193699226e-02 -5.8103963873e-03\natom -4.8130810704e-02  1.1455866520e+01  4.0155035313e+01 O  -4.0505696600e-01 0.0  3.7970831683e-03 -6.3408931789e-03 -7.8798399309e-03\natom  2.8743271236e+00  1.4294384262e+01  4.0132651036e+01 Mg  3.8473278400e-01 0.0 -2.4948861758e-03 -7.5442135624e-03  1.0956968603e-02\natom  5.7360837333e+00 -1.4033161883e-02  2.0040227467e+01 Mg  3.7834282400e-01 0.0 -3.1145522209e-03  4.7039978880e-03 -9.5377403839e-03\natom  8.5193853072e+00  2.8764031199e+00  1.9994398985e+01 O  -3.9950044600e-01 0.0  4.0226856182e-03 -1.0833243234e-03  7.0920793159e-03\natom  5.6375475999e+00 -4.0667772549e-02  2.4029267612e+01 O  -3.4229819600e-01 0.0  8.2987266746e-03  5.1601950377e-03  1.3653884031e-02\natom  8.5444746323e+00  2.8328648158e+00  2.4073209126e+01 Mg  3.3553648400e-01 0.0 -1.1939707021e-03  3.5132870514e-04 -1.7099589602e-02\natom  5.6374929679e+00  8.9788629595e-03  2.8040190972e+01 Mg  3.3864572400e-01 0.0  3.1101976032e-03 -4.7262982395e-03 -8.3170798198e-03\natom  8.5205746819e+00  2.8135749087e+00  2.8097702553e+01 O  -3.3886362600e-01 0.0  3.7845103628e-03  5.8571539814e-03  6.9679588563e-03\natom  5.7090540565e+00  1.6821528168e-02  3.2068389906e+01 O  -3.4666686600e-01 0.0 -3.1239594304e-03  4.1799787804e-04  9.7581195600e-03\natom  8.5099907612e+00  2.8387661466e+00  3.2089405586e+01 Mg  3.3338522400e-01 0.0  4.5954450282e-03 -3.2823725103e-03 -7.8829159998e-03\natom  5.7491607505e+00  2.6551802873e-02  3.6161801185e+01 Mg  3.2062906400e-01 0.0 -4.1993310165e-03 -4.5241656508e-03 -9.8132859281e-04\natom  8.5696933090e+00  2.8243981820e+00  3.6095548904e+01 O  -3.1752737600e-01 0.0 -1.1989515676e-02  1.2992190124e-02 -4.1340044842e-03\natom  5.6004605747e+00 -3.9012674939e-02  4.0102869653e+01 O  -4.0424763600e-01 0.0  9.1904512527e-03  8.0531063374e-03 -4.3266832980e-03\natom  8.5839177868e+00  2.8525893410e+00  4.0129186941e+01 Mg  3.9453091400e-01 0.0 -8.9551899583e-04 -1.2966259170e-03  1.1905612997e-02\natom  5.6735244868e+00  5.6849201959e+00  1.9979804725e+01 Mg  3.6383293400e-01 0.0  4.5971562540e-03  2.1902624151e-03 -9.8381440608e-03\natom  8.5832999976e+00  8.5656793232e+00  1.9987182839e+01 O  -3.9964279600e-01 0.0 -1.8118615688e-03  4.3394088546e-03  1.8180132199e-03\natom  5.7075209596e+00  5.6897493150e+00  2.4036549652e+01 O  -3.4040861600e-01 0.0  3.2875388794e-03 -1.8092081345e-03  1.0919704276e-02\natom  8.6020291474e+00  8.5486919149e+00  2.3965788409e+01 Mg  3.2910246400e-01 0.0 -6.5282823297e-03 -1.9398922850e-05 -7.6593529797e-03\natom  5.7493104546e+00  5.6905967816e+00  2.8035716479e+01 Mg  3.3820629400e-01 0.0 -6.9332970705e-03  2.1950535253e-03 -1.1109486024e-02\natom  8.5305642648e+00  8.5336383576e+00  2.8041326565e+01 O  -3.4017292600e-01 0.0  6.2200847315e-03 -2.1695478471e-03  1.4204631174e-02\natom  5.6467260935e+00  5.6755829275e+00  3.2090861072e+01 O  -3.0795973600e-01 0.0  5.3782896637e-03  2.2777776459e-03  2.4895982323e-02\natom  8.5337005863e+00  8.5466174493e+00  3.2081751157e+01 Mg  3.3673371400e-01 0.0 -9.4849000381e-04  1.9614202195e-03 -1.0185315242e-02\natom  5.6610188849e+00  5.6993559450e+00  3.6064080941e+01 Al  3.9695487400e-01 0.0  2.0843440953e-03  5.4869365378e-03  1.3686507699e-02\natom  8.5010303798e+00  8.5362875267e+00  3.6131963187e+01 O  -2.9557145600e-01 0.0  3.0568550055e-04 -1.8106929285e-03 -1.0374877539e-02\natom  5.6984002350e+00  5.7462274801e+00  4.0178786901e+01 O  -3.6865153600e-01 0.0 -1.4045906970e-04 -5.9452336267e-03 -2.4798495009e-02\natom  8.5592887234e+00  8.5947597306e+00  4.0146193152e+01 Mg  3.7318686400e-01 0.0 -1.1433119464e-03 -3.5399292035e-03  1.3056911106e-02\natom  5.6032739042e+00  1.1399683984e+01  1.9913916443e+01 Mg  4.3835344400e-01 0.0  6.6418467348e-03 -1.1775122828e-03  3.1477360114e-03\natom  8.5029228270e+00  1.4343324046e+01  2.0023014406e+01 O  -3.9907663600e-01 0.0  7.2713665230e-03 -1.1173914494e-02  1.7166732560e-03\natom  5.6720512753e+00  1.1358988262e+01  2.4060251956e+01 O  -3.4351320600e-01 0.0  7.0636885577e-03  1.6039809108e-03  4.6649418728e-03\natom  8.5254411798e+00  1.4231011829e+01  2.4012346344e+01 Mg  3.3264691400e-01 0.0 -1.3993287519e-04  1.1852947065e-03 -7.4662349067e-03\natom  5.7426630600e+00  1.1378874680e+01  2.8023933603e+01 Mg  3.3174515400e-01 0.0 -3.6900886505e-03  1.8336596819e-03 -5.5396560217e-03\natom  8.6362523685e+00  1.4255022857e+01  2.8036097202e+01 O  -3.4397266600e-01 0.0 -5.0705193303e-03 -7.5718061593e-04  1.1779551880e-02\natom  5.7117658322e+00  1.1454697101e+01  3.2073160784e+01 O  -3.4651384600e-01 0.0  2.1618711944e-03 -7.4378623137e-03  8.9025832048e-03\natom  8.5246584175e+00  1.4270581047e+01  3.2102696917e+01 Mg  3.3500711400e-01 0.0 -3.8221904068e-03  2.1794735203e-03 -1.2919341424e-02\natom  5.7186666391e+00  1.1422359335e+01  3.6101213660e+01 Mg  3.2162119400e-01 0.0 -2.1102349976e-03  6.9409950913e-04  6.0550268388e-03\natom  8.5627598477e+00  1.4273198941e+01  3.6166519038e+01 O  -3.1534753600e-01 0.0  1.2512748219e-02 -1.2697967497e-02 -1.3121498323e-02\natom  5.7264381750e+00  1.1398781375e+01  4.0260042284e+01 O  -4.0657984600e-01 0.0 -1.9984775388e-03  6.5175188640e-04 -1.2874514248e-02\natom  8.5102664156e+00  1.4232221424e+01  4.0091178051e+01 Mg  3.8243331400e-01 0.0  2.3236357718e-04  3.0747797589e-03  1.6241732204e-02\natom  1.1401532344e+01  4.5076087540e-02  2.0029059110e+01 Mg  4.2144506400e-01 0.0 -2.6338069933e-03  1.8692072892e-03 -7.1830928865e-03\natom  1.4239757122e+01  2.8608573080e+00  1.9951038844e+01 O  -3.9885712600e-01 0.0 -6.7963033186e-04 -3.3978674162e-03  1.0028046590e-02\natom  1.1393443466e+01 -4.2770168300e-04  2.4001081706e+01 O  -3.4229476600e-01 0.0  2.0189146226e-03  9.1299232460e-04  1.4398345789e-02\natom  1.4231685554e+01  2.8864018680e+00  2.4021645383e+01 Mg  3.3282959400e-01 0.0  3.8787517487e-03 -2.8789314967e-03 -1.2767519873e-02\natom  1.1402686003e+01  3.9371628390e-02  2.8113584925e+01 Mg  3.3652098400e-01 0.0 -3.2700826696e-03 -6.2824640544e-03 -1.5263318317e-02\natom  1.4244927525e+01  2.8375641675e+00  2.8036863637e+01 O  -3.3851908600e-01 0.0 -1.3208680593e-03 -5.9644746145e-04  1.4148312919e-02\natom  1.1395989211e+01  4.7920427509e-03  3.2086785538e+01 O  -3.4427758600e-01 0.0  4.7319631798e-03 -7.9854064381e-04  8.2523928680e-03\natom  1.4238799238e+01  2.8820363931e+00  3.2090336900e+01 Mg  3.3852211400e-01 0.0 -1.2291432619e-03  1.8897942996e-03 -5.9334117928e-03\natom  1.1420507253e+01  1.8697459157e-02  3.6120652572e+01 Mg  3.2123483400e-01 0.0 -1.2722942429e-03  7.4047551684e-04  5.9269917397e-03\natom  1.4268517750e+01  2.8561106375e+00  3.6168027133e+01 O  -3.1630029600e-01 0.0  9.9977910458e-03 -1.4624310110e-02 -1.2145468097e-02\natom  1.1414591957e+01 -8.2592458544e-02  4.0173253651e+01 O  -4.0620398600e-01 0.0 -2.6302655582e-03  6.6918761996e-03 -8.7626692688e-03\natom  1.4256298422e+01  2.8717039194e+00  4.0140854601e+01 Mg  3.8601067400e-01 0.0 -2.8596898963e-03 -1.4777345476e-03  1.2289643997e-02\natom  1.1393721861e+01  5.7236951244e+00  2.0010035088e+01 Mg  4.2033274400e-01 0.0 -8.1139904315e-04 -3.0861963554e-03 -7.3630749684e-03\natom  1.4257639788e+01  8.4981605285e+00  1.9925047364e+01 O  -3.9897923600e-01 0.0 -1.7423814112e-03  8.5171378710e-03  8.0062458716e-03\natom  1.1373306754e+01  5.7232945403e+00  2.3983895820e+01 O  -3.4182347600e-01 0.0  4.0244773526e-03 -2.4137289154e-03  1.8159649360e-02\natom  1.4251016393e+01  8.5961130012e+00  2.4011062539e+01 Mg  3.3498552400e-01 0.0  4.4389163746e-03 -4.4172058062e-03 -9.4928399393e-03\natom  1.1392303111e+01  5.6922237034e+00  2.8086502355e+01 Mg  3.4501975400e-01 0.0  1.8134973837e-03  2.6779993312e-03 -1.2349980602e-02\natom  1.4307995467e+01  8.5052796177e+00  2.8127594522e+01 O  -3.4156871600e-01 0.0 -7.9013844901e-03  2.5678006408e-03  3.0349451961e-03\natom  1.1467787838e+01  5.7303018143e+00  3.2140124452e+01 O  -3.4440377600e-01 0.0 -1.1083574237e-02 -3.6233205620e-03  5.7329971301e-04\natom  1.4223684114e+01  8.5394621152e+00  3.2083417385e+01 Mg  3.2495508400e-01 0.0  7.0578324494e-03 -4.2671290167e-03 -7.2611099535e-03\natom  1.1398360231e+01  5.6984501048e+00  3.6109137659e+01 Mg  3.1960005400e-01 0.0 -6.5266005394e-05  4.8167648923e-04  7.8354922050e-03\natom  1.4243599161e+01  8.4926708934e+00  3.6111924268e+01 O  -3.1767765600e-01 0.0 -9.4029885467e-03  1.7964035274e-02 -4.5031305790e-03\natom  1.1387116342e+01  5.7224672938e+00  4.0150551843e+01 O  -4.0551030600e-01 0.0  2.9192985592e-04 -2.0199560577e-03 -6.7187072234e-03\natom  1.4251826367e+01  8.5541300360e+00  4.0169736719e+01 Mg  3.8899702400e-01 0.0  1.3419741060e-03 -3.7739771689e-03  9.1943222875e-03\natom  1.1397087406e+01  1.1432029951e+01  1.9991521329e+01 Mg  4.3234339400e-01 0.0 -2.9331678203e-03 -2.3537332479e-03 -3.5884246025e-03\natom  1.4222100486e+01  1.4237423386e+01  1.9890837446e+01 O  -3.9647633600e-01 0.0  1.2213495570e-04 -8.6001771121e-04  9.1625308313e-03\natom  1.1397172085e+01  1.1362254484e+01  2.4106729256e+01 O  -3.4142175600e-01 0.0  2.0876450668e-03  4.4046296191e-03  2.7239861311e-04\natom  1.4223050564e+01  1.4272733426e+01  2.4026767277e+01 Mg  3.3476471400e-01 0.0  5.0484460649e-03 -9.0630921718e-04 -9.3487312430e-03\natom  1.1412415162e+01  1.1398466358e+01  2.8036581274e+01 Mg  3.3912875400e-01 0.0 -2.3330411841e-03 -2.8659618461e-04 -1.1392465406e-02\natom  1.4265352610e+01  1.4216093689e+01  2.8052093903e+01 O  -3.3926433600e-01 0.0 -6.8569593497e-04  3.6447957468e-03  1.5464750274e-02\natom  1.1401696599e+01  1.1369599225e+01  3.2083243398e+01 O  -3.0799256600e-01 0.0 -1.8796304720e-04  3.6748951931e-03  2.3090729543e-02\natom  1.4233083328e+01  1.4215807831e+01  3.2083725032e+01 Mg  3.3553753400e-01 0.0  6.4488285943e-04  1.0481239340e-03 -1.1624902137e-02\natom  1.1446195847e+01  1.1455486685e+01  3.6062830566e+01 Al  3.9603740400e-01 0.0 -3.7845126362e-03 -5.5501858565e-03  1.3573459514e-02\natom  1.4275939497e+01  1.4231407235e+01  3.6076973257e+01 O  -2.8918410600e-01 0.0 -2.8119721838e-03  5.1917246104e-04 -6.1571751814e-03\natom  1.1412436308e+01  1.1399368513e+01  4.0122450030e+01 O  -3.6358139600e-01 0.0 -8.7882158509e-04 -9.1956096436e-04 -2.2866358560e-02\natom  1.4206953179e+01  1.4201432515e+01  4.0151366429e+01 Mg  3.7335335400e-01 0.0  3.7450445387e-03  5.1525057893e-03  1.4302349011e-02\natom  2.7674441650e+00  3.2676547854e+00  1.5266538963e+01 Au -1.8129486000e-02 0.0  4.7752095368e-04 -2.2142671411e-03  5.1007575752e-02\natom  2.7884963173e+00  3.1844017731e+00  1.0716139442e+01 Au -2.1088749600e-01 0.0 -3.8108279331e-05  1.9467681277e-04 -4.1132711694e-02\nenergy -5.4395981012e+04\ncharge  0.0000000000e+00\nend\n"
  },
  {
    "path": "examples/nnp-predict/AlAuMgO_4G/input.nn",
    "content": "################################################################################\n### This is the input file for n2p2\n### It contains only a subset of all keywords\n################################################################################\n\n\n################################################################################\n### general keywords\n################################################################################\n\nnnp_generation 4\nuse_short_forces\n\nnumber_of_elements 4\nelements Al O Mg Au\n\ninitial_hardness        O        10.0\ninitial_hardness       Mg        10.0\ninitial_hardness       Al        10.0\ninitial_hardness       Au        10.0\n\nfixed_gausswidth Mg 4.289\nfixed_gausswidth  O 2.872\nfixed_gausswidth Al 3.477\nfixed_gausswidth Au 3.288\n\nscreen_electrostatics 3.2 8.0\n\nrandom_seed 12346\n\natom_energy     O   -75.29000258799172\natom_energy    Mg   -200.61689378490792\natom_energy    Au   -19684.765036573383\natom_energy    Al   -243.09681374120558\n\newald_truncation_error_method 1\newald_prec 1.e-5 0.45\n\n################################################################################\n### NN structure of the short-range NN\n################################################################################\nglobal_hidden_layers_short 2\nglobal_nodes_short 15 15\nglobal_activation_short t t l\n\n################################################################################\n### NN structure of the electrostatic NN\n################################################################################\nglobal_hidden_layers_electrostatic 2\nglobal_nodes_electrostatic 15 15\nglobal_activation_electrostatic t t l\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (General)\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nupdater_type                    1              # Weight update method\n                                               # (0 = Gradient Descent,\n                                               # 1 = Kalman filter).\nparallel_mode                   1              # Training parallelization used\n                                               # (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  0              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                          # Precondition weights with initial energies.\nwrite_weights_epoch             10             # Write weights every this many epochs.\nscale_symmetry_functions\ncenter_symmetry_functions\n#write_neuronstats               1             # Write neuron statistics every this many epochs.\n#write_trainlog                                # Write training log file.\n\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (charges, stage 1)\n################################################################################\ntask_batch_size_charge          1\n#nguyen_widrow_weights_charge                  # Initialize neural network weights according to Nguyen-Widrow scheme.\ncharge_fraction                 1.000\n#write_traincharges              1             # Write charge comparison. Can produce large files.\n#use_old_weights_charge                        # Restart fitting with old weight parameters.\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (short-range, stage 2)\n################################################################################\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.02315        # Fraction of force updates per epoch.\n#short_energy_error_threshold    0.80          # RMSE threshold for energy update candidates.\n#short_force_error_threshold     0.80          # RMSE threshold for force update candidates.\n#use_old_weights_short                         # Restart fitting with old weight parameters.\n#repeated_energy_update\n#nguyen_widrow_weights_short                   # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               0              # Write energy comparison every this many epochs.\nwrite_trainforces               0              # Write force comparison every this many epochs.\n\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\n#kalman_lambda_short 0.98000                   # Only for fading memory Kalman filter\n#kalman_nue_short 0.99870\n\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon, covariance matrix initialization (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0, initial process noise (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin, final process noise (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n\n\n################################################################################\n### symmetry function definitions (all modes):\n################################################################################\ncutoff_type 2\n\nsymfunction Mg  2  Mg    0.000000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.001000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.002000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.003000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.004000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.005000      0.000000      8.000000\n\n\nsymfunction O  2 Mg     0.000000      0.000000      8.000000\nsymfunction O  2 Mg     0.004000      0.000000      8.000000\nsymfunction O  2 Mg     0.007000      0.000000      8.000000\nsymfunction O  2 Mg     0.010000      0.000000      8.000000\nsymfunction O  2 Mg     0.014000      0.000000      8.000000\nsymfunction O  2 Mg     0.018000      0.000000      8.000000\n\nsymfunction Mg 2  O    0.000000      0.000000      8.000000\nsymfunction Mg 2  O    0.004000      0.000000      8.000000\nsymfunction Mg 2  O    0.007000      0.000000      8.000000\nsymfunction Mg 2  O    0.010000      0.000000      8.000000\nsymfunction Mg 2  O    0.014000      0.000000      8.000000\nsymfunction Mg 2  O    0.018000      0.000000      8.000000\n\nsymfunction O  2  O    0.000000      0.000000      8.000000\nsymfunction O  2  O    0.001000      0.000000      8.000000\nsymfunction O  2  O    0.002000      0.000000      8.000000\nsymfunction O  2  O    0.003000      0.000000      8.000000\nsymfunction O  2  O    0.004000      0.000000      8.000000\nsymfunction O  2  O    0.005000      0.000000      8.000000\n\nsymfunction Mg  2  Au    0.000000      0.000000      8.000000\nsymfunction Mg  2  Au    0.001000      0.000000      8.000000\nsymfunction Mg  2  Au    0.002000      0.000000      8.000000\nsymfunction Mg  2  Au    0.003000      0.000000      8.000000\nsymfunction Mg  2  Au    0.004000      0.000000      8.000000\nsymfunction Mg  2  Au    0.005000      0.000000      8.000000\n\nsymfunction Au  2  Mg    0.000000      0.000000      8.000000\nsymfunction Au  2  Mg    0.001000      0.000000      8.000000\nsymfunction Au  2  Mg    0.002000      0.000000      8.000000\nsymfunction Au  2  Mg    0.003000      0.000000      8.000000\nsymfunction Au  2  Mg    0.004000      0.000000      8.000000\nsymfunction Au  2  Mg    0.005000      0.000000      8.000000\n\n\nsymfunction Au  2 O     0.000000      0.000000      8.000000\nsymfunction Au  2 O     0.004000      0.000000      8.000000\nsymfunction Au  2 O     0.008000      0.000000      8.000000\nsymfunction Au  2 O     0.013000      0.000000      8.000000\nsymfunction Au  2 O     0.018000      0.000000      8.000000\nsymfunction Au  2 O     0.024000      0.000000      8.000000\n\nsymfunction O  2 Au     0.000000      0.000000      8.000000\nsymfunction O  2 Au     0.004000      0.000000      8.000000\nsymfunction O  2 Au     0.008000      0.000000      8.000000\nsymfunction O  2 Au     0.013000      0.000000      8.000000\nsymfunction O  2 Au     0.018000      0.000000      8.000000\nsymfunction O  2 Au     0.024000      0.000000      8.000000\n\nsymfunction Au  2 Au     0.000000      0.000000      8.000000\nsymfunction Au  2 Au     0.004000      0.000000      8.000000\nsymfunction Au  2 Au     0.008000      0.000000      8.000000\nsymfunction Au  2 Au     0.012000      0.000000      8.000000\nsymfunction Au  2 Au     0.017000      0.000000      8.000000\nsymfunction Au  2 Au     0.022000      0.000000      8.000000\n\n\nsymfunction O  2  Al    0.000000      0.000000      8.000000\nsymfunction O  2  Al    0.003000      0.000000      8.000000\nsymfunction O  2  Al    0.005000      0.000000      8.000000\nsymfunction O  2  Al    0.008000      0.000000      8.000000\nsymfunction O  2  Al    0.011000      0.000000      8.000000\nsymfunction O  2  Al    0.014000      0.000000      8.000000\n\nsymfunction Al  2  O    0.000000      0.000000      8.000000\nsymfunction Al  2  O    0.003000      0.000000      8.000000\nsymfunction Al  2  O    0.005000      0.000000      8.000000\nsymfunction Al  2  O    0.008000      0.000000      8.000000\nsymfunction Al  2  O    0.011000      0.000000      8.000000\nsymfunction Al  2  O    0.014000      0.000000      8.000000\n\nsymfunction Al  2  Mg    0.000000      0.000000      8.000000\nsymfunction Al  2  Mg    0.001000      0.000000      8.000000\nsymfunction Al  2  Mg    0.002000      0.000000      8.000000\nsymfunction Al  2  Mg    0.003000      0.000000      8.000000\nsymfunction Al  2  Mg    0.004000      0.000000      8.000000\nsymfunction Al  2  Mg    0.005000      0.000000      8.000000\n\nsymfunction Mg  2  Al    0.000000      0.000000      8.000000\nsymfunction Mg  2  Al    0.001000      0.000000      8.000000\nsymfunction Mg  2  Al    0.002000      0.000000      8.000000\nsymfunction Mg  2  Al    0.003000      0.000000      8.000000\nsymfunction Mg  2  Al    0.004000      0.000000      8.000000\nsymfunction Mg  2  Al    0.005000      0.000000      8.000000\n\n#symfunction Al  2  Al    0.000000      0.000000      8.000000\n#symfunction Al  2  Al    0.001000      0.000000      8.000000\n#symfunction Al  2  Al    0.002000      0.000000      8.000000\n#symfunction Al  2  Al    0.003000      0.000000      8.000000\n#symfunction Al  2  Al    0.004000      0.000000      8.000000\n#symfunction Al  2  Al    0.005000      0.000000      8.000000\n\n\nsymfunction Mg 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction Mg 3 Mg Mg 0.0  1.0 2.0  8.0\nsymfunction Mg 3 Mg Mg 0.0  1.0 4.0  8.0\n#symfunction Mg 3 Mg Mg 0.0  1.0 8.0  8.0\nsymfunction Mg 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 4.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 8.0  8.0\nsymfunction Mg 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction Mg 3 Mg  O 0.0 -1.0 2.0  8.0\n#symfunction Mg 3 Mg  O 0.0 -1.0 4.0  8.0\n#symfunction Mg 3 Mg  O 0.0 -1.0 8.0  8.0\n\n#symfunction Mg 3 Mg Al 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Mg Al 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Mg Al 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Al 0.0 -1.0 2.0  8.0\n\n#symfunction Mg 3 Mg Au 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Mg Au 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Mg Au 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3  O  O 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O  O 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O  O 0.0  1.0 4.0  8.0\n#symfunction Mg 3  O  O 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 1.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 2.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 4.0  8.0\n#symfunction Mg 3  O  O 0.0 -1.0 8.0  8.0\n\nsymfunction Mg 3  O Al 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 4.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O Al 0.0 -1.0 1.0  8.0\n#symfunction Mg 3  O Al 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3  O Au 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 4.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O Au 0.0 -1.0 1.0  8.0\nsymfunction Mg 3  O Au 0.0 -1.0 2.0  8.0\n\n#symfunction Mg 3 Al Al 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Al Al 0.0  1.0 2.0  8.0\n\n#symfunction Mg 3 Au Au 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Au Au 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Au Au 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Au Au 0.0 -1.0 2.0  8.0\n\n\n\nsymfunction  O 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Mg 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Mg 0.0  1.0 4.0  8.0\n#symfunction  O 3 Mg Mg 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 2.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg Mg 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 4.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg  O 0.0 -1.0 2.0  8.0\n#symfunction  O 3 Mg  O 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg  O 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg Al 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Al 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Al 0.0  1.0 4.0  8.0\n#symfunction  O 3 Mg Al 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 2.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg Al 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg Au 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Au 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Au 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction  O 3  O  O 0.0  1.0 1.0  8.0\nsymfunction  O 3  O  O 0.0  1.0 2.0  8.0\nsymfunction  O 3  O  O 0.0 -1.0 1.0  8.0\n\nsymfunction  O 3  O Al 0.0  1.0 1.0  8.0\nsymfunction  O 3  O Al 0.0  1.0 2.0  8.0\nsymfunction  O 3  O Al 0.0 -1.0 1.0  8.0\nsymfunction  O 3  O Al 0.0 -1.0 2.0  8.0\n\n#symfunction  O 3  O Au 0.0  1.0 1.0  8.0\n\nsymfunction Al 3 Mg Mg 0.0  1.0 1.0  8.0\n#symfunction Al 3 Mg Mg 0.0  1.0 2.0  8.0\n#symfunction Al 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Al 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Al 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Al 3 Mg  O 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg  O 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3 Mg Al 0.0  1.0 1.0  8.0\n#symfunction Al 3 Mg Al 0.0  1.0 2.0  8.0\n#symfunction Al 3 Mg Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg Al 0.0 -1.0 2.0  8.0\n\nsymfunction Al 3  O  O 0.0  1.0 1.0  8.0\nsymfunction Al 3  O  O 0.0  1.0 2.0  8.0\nsymfunction Al 3  O  O 0.0 -1.0 1.0  8.0\nsymfunction Al 3  O  O 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3  O Al 0.0  1.0 1.0  8.0\n#symfunction Al 3  O Al 0.0  1.0 2.0  8.0\n#symfunction Al 3  O Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3  O Al 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3 Al Al 0.0  1.0 1.0  8.0\n#symfunction Al 3 Al Al 0.0  1.0 2.0  8.0\n#symfunction Al 3 Al Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Al Al 0.0 -1.0 2.0  8.0\n\n\n\nsymfunction Au 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction Au 3 Mg Mg 0.0  1.0 2.0  8.0\n#symfunction Au 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Au 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Au 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Au 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction Au 3 Mg  O 0.0 -1.0 2.0  8.0\n\n#symfunction Au 3 Mg Au 0.0  1.0 1.0  8.0\n#symfunction Au 3 Mg Au 0.0  1.0 2.0  8.0\n#symfunction Au 3 Mg Au 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction Au 3  O  O 0.0  1.0 1.0  8.0\n#symfunction Au 3  O  O 0.0  1.0 2.0  8.0\n#symfunction Au 3  O  O 0.0 -1.0 1.0  8.0\n#symfunction Au 3  O  O 0.0 -1.0 2.0  8.0\n\n#symfunction Au 3  O Au 0.0  1.0 1.0  8.0\n#symfunction Au 3  O Au 0.0  1.0 2.0  8.0\nsymfunction Au 3  O Au 0.0  1.0 -1.0  8.0\nsymfunction Au 3  O Au 0.0  1.0 -2.0  8.0\n\n#symfunction Au 3 Au Au 0.0  1.0 1.0  8.0\n#symfunction Au 3 Au Au 0.0  1.0 2.0  8.0\n#symfunction Au 3 Au Au 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Au Au 0.0 -1.0 2.0  8.0\n\n"
  },
  {
    "path": "examples/nnp-predict/AlAuMgO_4G/scaling.data",
    "content": "   1    1        0.157132975       0.280279850       0.234169887\n   1    2        0.379295480       0.622179554       0.545652438\n   1    3        0.000000000       0.205184943       0.016565410\n   1    4        0.000000000       0.167300348       0.001157152\n   1    5        0.151966913       0.271484679       0.226693585\n   1    6        0.146970813       0.262965553       0.219456059\n   1    7        0.142139079       0.254713806       0.212449681\n   1    8        0.000000000       0.195870161       0.015737764\n   1    9        0.137466301       0.246721045       0.205667064\n   1   10        0.353782761       0.582354440       0.509841176\n   1   11        0.000000000       0.161223776       0.001045601\n   1   12        0.132947244       0.238979140       0.199101062\n   1   13        0.000000000       0.189896965       0.015211084\n   1   14        0.335850555       0.554313578       0.484647540\n   1   15        0.000000000       0.181277733       0.014456530\n   1   16        0.000000000       0.155367918       0.000947149\n   1   17        0.318878593       0.527730187       0.460782520\n   1   18        0.000000000       0.173050590       0.013742142\n   1   19        0.000000000       0.148346286       0.000839806\n   1   20        0.297643309       0.494532513       0.430890275\n   1   21        0.000000000       0.165197661       0.013065428\n   1   22        0.277886581       0.463747515       0.403042058\n   1   23        0.000000000       0.141641990       0.000747240\n   1   24        0.000000000       0.133995570       0.000652336\n   1   25        0.000045839       0.000152977       0.000106156\n   1   26        0.000680557       0.001734569       0.001348253\n   1   27        0.000000000       0.000580779       0.000043631\n   1   28        0.000687759       0.003088959       0.002094644\n   1   29        0.000000000       0.001975434       0.000139623\n   1   30        0.000000000       0.002858460       0.000006888\n   1   31        0.000141138       0.000459099       0.000318440\n   1   32        0.003883787       0.009565828       0.007507740\n   1   33        0.000000000       0.003170549       0.000242247\n   1   34        0.000723568       0.003193167       0.002190205\n   1   35        0.000000000       0.002015297       0.000146458\n   1   36        0.000000000       0.002849448       0.000008773\n   1   37        0.000108434       0.000298716       0.000226841\n   1   38        0.000000000       0.000100115       0.000007401\n   1   39        0.000337708       0.001533218       0.001037438\n   1   40        0.000000000       0.000985795       0.000069101\n   1   41        0.000000000       0.001452136       0.000003254\n   1   42        0.000106418       0.000344381       0.000238835\n   1   43        0.003311665       0.008129974       0.006386328\n   1   44        0.000000000       0.002695024       0.000206016\n   1   45        0.000376278       0.001638804       0.001133000\n   1   46        0.000000000       0.001025445       0.000075936\n   1   47        0.000000000       0.001443125       0.000005139\n   1   48        0.000083248       0.000381693       0.000258183\n   1   49        0.000000000       0.000247525       0.000017187\n   1   50        0.002416132       0.005909800       0.004645819\n   1   51        0.000108377       0.000463908       0.000321719\n   1   52        0.000000000       0.000274278       0.000021729\n   1   53        0.001290479       0.003153152       0.002478974\n   2    1        0.465366967       0.622899345       0.561220975\n   2    2        0.119958755       0.278325877       0.225814452\n   2    3        0.000000000       0.052290984       0.007517999\n   2    4        0.000000000       0.082321041       0.001283464\n   2    5        0.116028951       0.269574643       0.218604882\n   2    6        0.000000000       0.050704245       0.007277988\n   2    7        0.000000000       0.080774026       0.001244257\n   2    8        0.112227916       0.261098625       0.211625571\n   2    9        0.000000000       0.049165662       0.007045642\n   2   10        0.000000000       0.079257371       0.001206277\n   2   11        0.108551431       0.252889168       0.204869161\n   2   12        0.000000000       0.047673774       0.006820716\n   2   13        0.000000000       0.077770417       0.001169485\n   2   14        0.434143302       0.583124772       0.524387947\n   2   15        0.104995412       0.244937885       0.198328532\n   2   16        0.000000000       0.046227162       0.006602973\n   2   17        0.000000000       0.076312525       0.001133843\n   2   18        0.101555912       0.237236656       0.191996789\n   2   19        0.000000000       0.044824453       0.006392183\n   2   20        0.000000000       0.074883070       0.001099315\n   2   21        0.412169183       0.555114045       0.498475487\n   2   22        0.391351992       0.528554985       0.473929551\n   2   23        0.365280511       0.495248302       0.443184422\n   2   24        0.341001583       0.464173404       0.414541640\n   2   25        0.001304697       0.003073521       0.002226260\n   2   26        0.000658301       0.001747757       0.001341772\n   2   27        0.000000000       0.000344142       0.000044915\n   2   28        0.000000000       0.000536511       0.000003397\n   2   29        0.000015937       0.000150219       0.000098274\n   2   30        0.001379442       0.003196463       0.002328076\n   2   31        0.003777691       0.009615500       0.007472434\n   2   32        0.000000000       0.001853922       0.000249329\n   2   33        0.000000000       0.001669339       0.000012712\n   2   34        0.000048632       0.000451042       0.000294796\n   2   35        0.000640789       0.001524318       0.001102595\n   2   36        0.000104063       0.000302504       0.000225688\n   2   37        0.000000000       0.000263424       0.000001016\n   2   38        0.000709709       0.001647260       0.001204412\n   2   39        0.003223454       0.008170246       0.006356350\n   2   40        0.000000000       0.001575067       0.000212033\n   2   41        0.000000000       0.001450386       0.000010331\n   2   42        0.000036630       0.000338360       0.000221102\n   2   43        0.000156394       0.000379666       0.000274392\n   2   44        0.000197865       0.000461980       0.000342083\n   2   45        0.002354467       0.005937258       0.004624037\n   2   46        0.000000000       0.001144834       0.000154222\n   2   47        0.000000000       0.001123811       0.000007188\n   2   48        0.000020441       0.000190427       0.000124392\n   2   49        0.001262549       0.003166018       0.002467335\n   2   50        0.000000000       0.000611201       0.000082309\n   2   51        0.000000000       0.000698347       0.000003778\n   3    1        0.577136243       0.616694005       0.597156670\n   3    2        0.250892044       0.277137801       0.263493918\n   3    3        0.242773609       0.268416021       0.255081906\n   3    4        0.234917966       0.259968821       0.246938538\n   3    5        0.547624822       0.586625275       0.567321361\n   3    6        0.227316605       0.251787552       0.239055233\n   3    7        0.219961293       0.243863841       0.231423681\n   3    8        0.528861449       0.567471623       0.548335377\n   3    9        0.212844062       0.236189575       0.224035841\n   3   10        0.502003814       0.540003438       0.521134901\n   3   11        0.476603541       0.513965831       0.495382352\n   3   12        0.452569426       0.489271173       0.470987896\n   3   13        0.002144387       0.002924649       0.002514975\n   3   14        0.001446412       0.001705750       0.001573953\n   3   15        0.002255498       0.003054915       0.002637746\n   3   16        0.008084071       0.009374504       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  {
    "path": "examples/nnp-predict/Anisole_SCAN/input.data",
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  },
  {
    "path": "examples/nnp-predict/Anisole_SCAN/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.7798465944668833E+00\nconv_energy   9.6165975309496139E+02\nconv_length   1.6441069294475543E+01\n###############################################################################\n\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              3              # Number of elements.\nelements                        C O H          # Specification of elements.\ncutoff_type                     6 0.0          # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              30 20          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                  987654321        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          30             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                   10.0            # Good to play with / Weight of force updates relative to energy updates.\nshort_energy_fraction           1.0000000       # Fraction of energy updates per epoch.\nshort_force_fraction            0.008057       # 0.0008057, could be 10 times larger / Fraction of force updates per epoch.\nshort_energy_error_threshold    0.000          # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.000          # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # increasing does rarely help / Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                    -1.0            # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               1              # fractional complete / Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\n# gradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\n# gradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\n# gradient_adam_eta               1.0E-3         # Adam parameter eta.\n# gradient_adam_beta1             0.9            # Adam parameter beta1.\n# gradient_adam_beta2             0.999          # Adam parameter beta2.\n# gradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n##########################################################################\n\nsymfunction_short C 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 C -1.40E+01 1.40E+01 p2a\nsymfunction_short C 20 C -1.20E+01 1.20E+01 p2a\nsymfunction_short C 20 C -1.00E+01 1.00E+01 p2a\nsymfunction_short C 20 C -8.00E+00 8.00E+00 p2a\nsymfunction_short C 20 C -6.00E+00 6.00E+00 p2a\nsymfunction_short C 20 C -5.00E+00 5.00E+00 p2a\nsymfunction_short C 20 C -2.50E+00 7.50E+00 p2a\nsymfunction_short C 20 C 0.00E+00 1.00E+01 p2a\nsymfunction_short C 20 C 2.50E+00 1.25E+01 p2a\nsymfunction_short C 20 C 5.00E+00 1.50E+01 p2a\n \nsymfunction_short C 20 O -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 O -1.40E+01 1.40E+01 p2a\nsymfunction_short C 20 O -1.20E+01 1.20E+01 p2a\nsymfunction_short C 20 O -1.00E+01 1.00E+01 p2a\nsymfunction_short C 20 O -8.00E+00 8.00E+00 p2a\nsymfunction_short C 20 O -6.00E+00 6.00E+00 p2a\nsymfunction_short C 20 O -5.00E+00 5.00E+00 p2a\nsymfunction_short C 20 O -2.50E+00 7.50E+00 p2a\nsymfunction_short C 20 O 0.00E+00 1.00E+01 p2a\nsymfunction_short C 20 O 2.50E+00 1.25E+01 p2a\nsymfunction_short C 20 O 5.00E+00 1.50E+01 p2a\n \nsymfunction_short C 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 H -1.40E+01 1.40E+01 p2a\nsymfunction_short C 20 H -1.20E+01 1.20E+01 p2a\nsymfunction_short C 20 H -1.00E+01 1.00E+01 p2a\nsymfunction_short C 20 H -8.00E+00 8.00E+00 p2a\nsymfunction_short C 20 H -6.00E+00 6.00E+00 p2a\nsymfunction_short C 20 H -5.00E+00 5.00E+00 p2a\nsymfunction_short C 20 H -2.50E+00 7.50E+00 p2a\nsymfunction_short C 20 H 0.00E+00 1.00E+01 p2a\nsymfunction_short C 20 H 2.50E+00 1.25E+01 p2a\nsymfunction_short C 20 H 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short O 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short O 20 C -1.40E+01 1.40E+01 p2a\nsymfunction_short O 20 C -1.20E+01 1.20E+01 p2a\nsymfunction_short O 20 C -1.00E+01 1.00E+01 p2a\nsymfunction_short O 20 C -8.00E+00 8.00E+00 p2a\nsymfunction_short O 20 C -6.00E+00 6.00E+00 p2a\nsymfunction_short O 20 C -5.00E+00 5.00E+00 p2a\nsymfunction_short O 20 C -2.50E+00 7.50E+00 p2a\nsymfunction_short O 20 C 0.00E+00 1.00E+01 p2a\nsymfunction_short O 20 C 2.50E+00 1.25E+01 p2a\nsymfunction_short O 20 C 5.00E+00 1.50E+01 p2a\n \nsymfunction_short O 20 O -1.50E+01 1.50E+01 p2\nsymfunction_short O 20 O -1.40E+01 1.40E+01 p2a\nsymfunction_short O 20 O -1.20E+01 1.20E+01 p2a\nsymfunction_short O 20 O -1.00E+01 1.00E+01 p2a\nsymfunction_short O 20 O -8.00E+00 8.00E+00 p2a\nsymfunction_short O 20 O -6.00E+00 6.00E+00 p2a\n# symfunction_short  O  280  O      -5.00E+00  5.00E+00\nsymfunction_short O 20 O -2.50E+00 7.50E+00 p2a\nsymfunction_short O 20 O 0.00E+00 1.00E+01 p2a\nsymfunction_short O 20 O 2.50E+00 1.25E+01 p2a\nsymfunction_short O 20 O 5.00E+00 1.50E+01 p2a\n \nsymfunction_short O 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short O 20 H -1.40E+01 1.40E+01 p2a\nsymfunction_short O 20 H -1.20E+01 1.20E+01 p2a\nsymfunction_short O 20 H -1.00E+01 1.00E+01 p2a\nsymfunction_short O 20 H -8.00E+00 8.00E+00 p2a\nsymfunction_short O 20 H -6.00E+00 6.00E+00 p2a\nsymfunction_short O 20 H -5.00E+00 5.00E+00 p2a\nsymfunction_short O 20 H -2.50E+00 7.50E+00 p2a\nsymfunction_short O 20 H 0.00E+00 1.00E+01 p2a\nsymfunction_short O 20 H 2.50E+00 1.25E+01 p2a\nsymfunction_short O 20 H 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short H 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 C -1.40E+01 1.40E+01 p2a\nsymfunction_short H 20 C -1.20E+01 1.20E+01 p2a\nsymfunction_short H 20 C -1.00E+01 1.00E+01 p2a\nsymfunction_short H 20 C -8.00E+00 8.00E+00 p2a\nsymfunction_short H 20 C -6.00E+00 6.00E+00 p2a\nsymfunction_short H 20 C -5.00E+00 5.00E+00 p2a\nsymfunction_short H 20 C -2.50E+00 7.50E+00 p2a\nsymfunction_short H 20 C 0.00E+00 1.00E+01 p2a\nsymfunction_short H 20 C 2.50E+00 1.25E+01 p2a\nsymfunction_short H 20 C 5.00E+00 1.50E+01 p2a\n \nsymfunction_short H 20 O -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 O -1.40E+01 1.40E+01 p2a\nsymfunction_short H 20 O -1.20E+01 1.20E+01 p2a\nsymfunction_short H 20 O -1.00E+01 1.00E+01 p2a\nsymfunction_short H 20 O -8.00E+00 8.00E+00 p2a\nsymfunction_short H 20 O -6.00E+00 6.00E+00 p2a\nsymfunction_short H 20 O -5.00E+00 5.00E+00 p2a\nsymfunction_short H 20 O -2.50E+00 7.50E+00 p2a\nsymfunction_short H 20 O 0.00E+00 1.00E+01 p2a\nsymfunction_short H 20 O 2.50E+00 1.25E+01 p2a\nsymfunction_short H 20 O 5.00E+00 1.50E+01 p2a\n \nsymfunction_short H 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 H -1.40E+01 1.40E+01 p2a\nsymfunction_short H 20 H -1.20E+01 1.20E+01 p2a\nsymfunction_short H 20 H -1.00E+01 1.00E+01 p2a\nsymfunction_short H 20 H -8.00E+00 8.00E+00 p2a\nsymfunction_short H 20 H -6.00E+00 6.00E+00 p2a\nsymfunction_short H 20 H -5.00E+00 5.00E+00 p2a\nsymfunction_short H 20 H -2.50E+00 7.50E+00 p2a\nsymfunction_short H 20 H 0.00E+00 1.00E+01 p2a\nsymfunction_short H 20 H 2.50E+00 1.25E+01 p2a\nsymfunction_short H 20 H 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short C 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short C 22 C O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short C 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short C 22 O O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 O O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 O O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 O O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 O O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 O O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  C  890  O   O   -6.00E+00  -90.00   90.00  6.00E+00\n# symfunction_short  C  890  O   O   -6.00E+00   90.00  270.00  6.00E+00\nsymfunction_short C 22 O O -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 O O -6.00E+00 6.00E+00 0.00 120.00 p2a\n# symfunction_short  C  890  O   O   -6.00E+00   60.00  180.00  6.00E+00\nsymfunction_short C 22 O O -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short C 22 O H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 O H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 O H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 O H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 O H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 O H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short C 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \nsymfunction_short O 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short O 22 C O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 C O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 C O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 C O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 C O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 C O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  O  890  C   O   -6.00E+00  -90.00   90.00  6.00E+00\n# symfunction_short  O  890  C   O   -6.00E+00   90.00  270.00  6.00E+00\nsymfunction_short O 22 C O -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C O -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C O -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C O -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short O 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short O 22 O O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 O O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 O O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 O O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 O O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 O O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 49.10 169.10 p2a\n# symfunction_short  O  890  O   O   -1.20E+01  -90.00   90.00  1.20E+01\nsymfunction_short O 22 O O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 O O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 O O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 O O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O -1.20E+01 1.20E+01 49.10 169.10 p2a\n# symfunction_short  O  890  O   O   -1.00E+01  -90.00   90.00  1.00E+01\n# symfunction_short  O  890  O   O   -1.00E+01   90.00  270.00  1.00E+01\nsymfunction_short O 22 O O -1.00E+01 1.00E+01 0.00 180.00 p2a\n# symfunction_short  O  890  O   O   -1.00E+01    0.00  120.00  1.00E+01\nsymfunction_short O 22 O O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O -1.00E+01 1.00E+01 49.10 169.10 p2a\n# symfunction_short  O  890  O   O   -8.00E+00  -90.00   90.00  8.00E+00\n# symfunction_short  O  890  O   O   -8.00E+00   90.00  270.00  8.00E+00\n# symfunction_short  O  890  O   O   -8.00E+00    0.00  180.00  8.00E+00\n# symfunction_short  O  890  O   O   -8.00E+00    0.00  120.00  8.00E+00\n# symfunction_short  O  890  O   O   -8.00E+00   60.00  180.00  8.00E+00\n# symfunction_short  O  890  O   O   -8.00E+00   49.10  169.10  8.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00  -90.00   90.00  6.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00   90.00  270.00  6.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00    0.00  180.00  6.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00    0.00  120.00  6.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00   60.00  180.00  6.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00   49.10  169.10  6.00E+00\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short O 22 O H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 O H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 O H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 O H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 O H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 O H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  O  890  O   H   -6.00E+00  -90.00   90.00  6.00E+00\n# symfunction_short  O  890  O   H   -6.00E+00   90.00  270.00  6.00E+00\n# symfunction_short  O  890  O   H   -6.00E+00    0.00  180.00  6.00E+00\n# symfunction_short  O  890  O   H   -6.00E+00    0.00  120.00  6.00E+00\n# symfunction_short  O  890  O   H   -6.00E+00   60.00  180.00  6.00E+00\n# symfunction_short  O  890  O   H   -6.00E+00   49.10  169.10  6.00E+00\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short O 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  O  890  H   H   -6.00E+00  -90.00   90.00  6.00E+00\nsymfunction_short O 22 H H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 H H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 H H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 H H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 H H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \nsymfunction_short H 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short H 22 C O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short H 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short H 22 O O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 O O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 O O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 O O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 O O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 O O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  H  890  O   O   -6.00E+00  -90.00   90.00  6.00E+00\n# symfunction_short  H  890  O   O   -6.00E+00   90.00  270.00  6.00E+00\nsymfunction_short H 22 O O -6.00E+00 6.00E+00 0.00 180.00 p2a\n# symfunction_short  H  890  O   O   -6.00E+00    0.00  120.00  6.00E+00\n# symfunction_short  H  890  O   O   -6.00E+00   60.00  180.00  6.00E+00\n# symfunction_short  H  890  O   O   -6.00E+00   49.10  169.10  6.00E+00\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short H 22 O H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 O H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 O H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 O H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 O H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 O H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  H  890  O   H   -6.00E+00  -90.00   90.00  6.00E+00\nsymfunction_short H 22 O H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 O H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 O H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 O H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 O H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short H 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \n"
  },
  {
    "path": "examples/nnp-predict/Anisole_SCAN/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0770318149875953E+01   1.9986398163731312E+01   1.5743821889794004E+01   1.1811294669196695E+00\n         1          2   7.8312775891892521E+00   1.9026924919587330E+01   1.4627464272348128E+01   1.3991210665860847E+00\n         1          3   5.2287534502987143E-01   3.8141380911012730E+00   2.1103743851065158E+00   4.9579949887052388E-01\n         1          4  -1.5543122344752192E-15   1.6579324287122832E-01   9.7841041210104777E-03   1.2416965578542126E-02\n         1          5   8.4632164887299410E-07   4.4379506330220853E-01   5.4373317731267461E-02   5.5899533822951500E-02\n         1          6   2.4394543912101829E-02   4.3142690427210102E+00   1.3623025761500003E+00   7.7237303355901965E-01\n         1          7   6.8706479057903946E-03   1.3131159448690370E+00   3.2700091023303485E-01   2.0503436165401862E-01\n         1          8   1.0764675633144916E-01   2.3291770324719794E+00   8.9267237397895693E-01   3.5317824974029721E-01\n         1          9   1.4002302154398407E+00   1.1823007840905614E+01   6.2160038099819497E+00   1.2813554811197465E+00\n         1         10   5.3477351451739341E-01   3.5853960625993455E+00   1.7886120377963679E+00   4.8170446482741447E-01\n         1         11   6.6938877197329925E+00   2.2780154923081366E+01   1.4782862949083480E+01   2.0707727502900801E+00\n         1         12   1.3710541859538115E+00   5.2505979592825911E+00   3.0846141976198549E+00   5.9443102844654661E-01\n         1         13   1.5294754831709664E+01   3.7168763545438878E+01   2.5581652815073703E+01   2.5858200899069512E+00\n         1         14   1.2477248736782487E-01   3.2139666520467502E-01   2.2970627086661496E-01   1.8189956271748162E-02\n         1         15   2.4905992117991849E-01   5.1266970165686565E-01   3.8621741665909887E-01   2.4695561666683425E-02\n         1         16   9.1801484475507888E-01   3.7779547390997159E+00   1.6779701612264089E+00   4.3215618195327871E-01\n         1         17   4.8661658599089908E-01   1.2464130664796027E+00   7.5090321062817023E-01   9.8266020690496919E-02\n         1         18   7.0400649123739278E-01   2.4455378972814081E+00   1.2721638193766069E+00   2.4653618676208328E-01\n         1         19   6.8332227390056133E-01   1.3437659977418182E+01   5.4176102967321000E+00   1.5869769209226949E+00\n         1         20   9.3159811724544406E-01   3.9761713203949642E+00   2.0763674220555082E+00   4.3227796058287543E-01\n         1         21   3.9381864829255417E+00   2.3315215132150293E+01   1.3615207680921213E+01   2.3955922018341669E+00\n         1         22   1.4629405570046021E+00   5.8816319844481075E+00   3.2515379213034152E+00   6.1714112456700509E-01\n         1         23   9.6939336001263943E+00   3.7833644465588371E+01   2.2462397581257605E+01   3.7382525941196265E+00\n         1         24  -1.7763568394002505E-15   2.3772083001581290E-02   4.5574528426809303E-04   8.4339525841937448E-04\n         1         25  -1.3322676295501878E-15   8.6562277422057909E-02   6.1653384914609685E-03   8.2740351239212282E-03\n         1         26  -1.7763568394002505E-15   1.4100891851342134E+00   2.5526522806996405E-01   2.5588897734458743E-01\n         1         27  -1.7763568394002505E-15   3.4737367978637013E-01   5.6028203142713374E-02   5.6676976983962048E-02\n         1         28  -1.7763568394002505E-15   7.0475929803101289E-01   1.5718079528286294E-01   1.2992173607677063E-01\n         1         29  -6.6613381477509392E-16   3.1532460601819374E+00   9.3536514194868059E-01   6.0612705388964983E-01\n         1         30   1.5217856355420611E-04   1.0734899430352809E+00   2.9802357783586103E-01   2.0608975869846163E-01\n         1         31   7.1599490789923115E-03   5.5610710668407730E+00   1.7639889122304782E+00   8.4913036627713445E-01\n         1         32   5.6970389119334053E-03   1.4409094458787184E+00   4.8152001401516226E-01   2.7249634580370724E-01\n         1         33   8.8369361932250423E-02   7.5425872037501200E+00   3.2324969019432173E+00   1.1371343181324518E+00\n         1         34   8.2462306757590866E+00   2.8131309654034975E+01   1.7583309322271525E+01   2.7005875435417090E+00\n         1         35   2.4810270446417945E+01   8.3490428787600052E+01   5.1620630730954467E+01   7.8229298428358893E+00\n         1         36   3.8213403872742390E+01   1.3399268389366674E+02   8.3246853700356624E+01   1.2511495098191897E+01\n         1         37   2.5021268785945132E+01   9.2397701025516398E+01   5.7272511119926826E+01   8.6213290037298904E+00\n         1         38   2.2382339587123724E+01   8.5219923089860103E+01   5.2534552017576075E+01   7.9141348319530103E+00\n         1         39   8.0370241695844733E+00   3.2601601950582371E+01   2.0057198216375767E+01   3.0702602026469581E+00\n         1         40   1.6931535944862880E+01   5.6926564890258909E+01   3.7240473570311671E+01   4.7996180186619348E+00\n         1         41   4.0370492753359905E+01   1.5410483087625499E+02   9.8248656902031058E+01   1.4373967265800120E+01\n         1         42   6.0192683916505828E+01   2.4432953738558845E+02   1.5662973142499033E+02   2.2959395052994211E+01\n         1         43   3.9262302330503424E+01   1.6810298743867904E+02   1.0706582546429206E+02   1.5831911907435323E+01\n         1         44   3.5116594977863414E+01   1.5265580990243916E+02   9.7952251583358944E+01   1.4450444578712318E+01\n         1         45   1.1673995895577544E+01   5.9724259491508924E+01   3.7109991415166355E+01   5.5768149391062281E+00\n         1         46   1.0023330902681222E+00   1.1018150106971305E+01   5.4389215137885794E+00   1.4347579555551704E+00\n         1         47   3.0023752082446449E+00   2.9319739423061648E+01   1.4454614912557457E+01   3.9515939375152818E+00\n         1         48   4.4790551699643633E+00   4.5130417192290643E+01   2.2620748561081665E+01   6.0983333793997243E+00\n         1         49   2.8443760013673307E+00   3.0439954665741482E+01   1.5282937103388720E+01   4.1299452901682825E+00\n         1         50   2.6787250892029832E+00   2.7767190694014843E+01   1.3997588949576697E+01   3.8079081624772653E+00\n         1         51   1.1234250425775465E+00   1.1440947317424198E+01   5.3542205933772751E+00   1.5089020912310827E+00\n         1         52   5.9623853546519481E+00   2.9745510915059722E+01   1.7393370201945430E+01   2.9639834287452183E+00\n         1         53   1.2452345268593449E+01   7.3038089055790920E+01   4.1894061392626533E+01   8.0818649939351612E+00\n         1         54   1.9214002650447274E+01   1.1662543448321061E+02   6.9572298302767308E+01   1.3706892801651017E+01\n         1         55   1.2503287178082664E+01   8.6095623597928807E+01   4.8965357813195126E+01   1.0090617512341291E+01\n         1         56   1.0722871603838465E+01   7.9870675361271097E+01   4.5142560174570939E+01   9.2847750886499298E+00\n         1         57   3.4010841446956124E+00   3.1639561628297159E+01   1.7370383938901863E+01   3.6947401150542811E+00\n         1         58   1.3457874073380038E+00   9.6584542522569308E+00   5.2617009319517640E+00   1.2486638117293218E+00\n         1         59   2.1097632571102398E+00   2.5263460375296415E+01   1.2916669268854649E+01   3.3676066832457940E+00\n         1         60   3.4708533375902597E+00   4.0514761912452641E+01   2.0609412772851503E+01   5.3780915323067608E+00\n         1         61   2.5075666662412552E+00   2.9767124572793993E+01   1.4135657918879614E+01   3.8360059105354818E+00\n         1         62   2.3978670830272164E+00   2.7910683974979150E+01   1.2975661589425545E+01   3.4995598981769214E+00\n         1         63   7.6458186209218426E-01   1.0060858125847639E+01   4.9882380253470195E+00   1.4276024237913671E+00\n         1         64   3.2259144583412377E-03   5.7339332488173567E-01   1.4306397927264281E-01   8.8608699648347597E-02\n         1         65   2.7736049077714441E-02   2.6579677980696803E+00   6.9754204374623163E-01   3.7478277834420881E-01\n         1         66   7.0684973204101331E-02   4.5755775380305019E+00   1.3150951302257565E+00   6.5981115172504401E-01\n         1         67   5.4367825162013592E-02   3.6111397565896737E+00   9.7985203575016511E-01   5.2184210313273549E-01\n         1         68   6.1841511600480764E-02   3.4094899831583714E+00   9.1239056796207818E-01   4.8747914093795097E-01\n         1         69   5.6402190304026059E-03   1.4520326469856797E+00   3.5598345619981375E-01   2.1568868274501576E-01\n         1         70  -6.2374004893334783E-18   4.3317346978946911E-03   2.1932430749888008E-04   2.9467086108696993E-04\n         1         71  -1.1438218586901202E-17   2.3046417967650654E-02   1.1706503041916693E-03   1.6449383128655502E-03\n         1         72  -3.9138868240349145E-19   5.3056544542124502E-02   1.2621828441503841E-03   2.0392994300200110E-03\n         1         73  -1.8491215289180094E-23   4.9023037230443725E-02   4.5924166028450257E-04   1.2247836523162992E-03\n         1         74  -7.2134845708393115E-17   4.9255603715700286E-02   4.2079293955527182E-04   1.2485277865039051E-03\n         1         75  -4.2323800755455422E-17   2.5137402943928397E-02   2.0864555207279317E-04   7.1148898235901220E-04\n         1         76   8.9418760595812121E-10   5.0831265062803034E-02   4.9834013413530900E-03   5.5395192451946924E-03\n         1         77   1.0494421437996694E-06   2.5431064818323201E-01   2.7068951090151679E-02   3.0556751563398481E-02\n         1         78   3.2179583527709046E-06   5.1623301660783016E-01   3.6689503056634064E-02   4.2619121691922564E-02\n         1         79   1.3841653842051163E-06   4.5440278667915651E-01   1.9920244367306647E-02   2.6621413667699337E-02\n         1         80   7.3093203434029042E-07   4.3093190644247298E-01   1.8927741650750510E-02   2.6300969752112893E-02\n         1         81   9.2637619487239718E-09   1.9615125468370415E-01   8.4498321711642902E-03   1.3345960877120564E-02\n         1         82   2.1774466101503638E-04   2.2602282086933029E-01   3.4328847199264614E-02   2.7445014317132668E-02\n         1         83   1.6082467432423297E-03   1.0278434179472808E+00   1.6349625516832617E-01   1.3337457064443639E-01\n         1         84   3.2647890377054492E-03   1.6668221261738243E+00   2.5666834994730897E-01   2.0246955310806941E-01\n         1         85   1.9390788768481782E-03   1.4187278825343281E+00   1.6566794865111717E-01   1.3365663685310258E-01\n         1         86   1.5910162593839004E-03   1.3071037552025035E+00   1.5698083210250496E-01   1.2894055829983656E-01\n         1         87   2.2948689179983427E-04   5.7296654270264336E-01   6.5298174626826785E-02   6.0121883495873406E-02\n         1         88   1.1327621784634290E-01   8.3045563652164383E+00   2.0943990569976267E+00   1.0218542897588423E+00\n         1         89   3.3370613510673158E-01   2.9453497292036595E+01   7.5877530824612389E+00   3.4109404950038580E+00\n         1         90   4.7988518927896195E-01   4.5660257302987425E+01   1.2637059872280588E+01   5.3778903087750551E+00\n         1         91   2.5775942414330383E-01   3.0532850369921658E+01   8.8551248167813821E+00   3.7434375700289295E+00\n         1         92   2.6123078884028328E-01   2.8390268043629735E+01   8.1706989431009660E+00   3.4173361669359688E+00\n         1         93   7.6890317232756175E-02   1.1503636136151936E+01   3.1270580184191670E+00   1.3684376161777125E+00\n         1         94   9.8619138473020306E-03   7.1512320230830972E-01   1.5929985005464631E-01   8.9061613834491737E-02\n         1         95   4.2708856676889201E-02   2.5945888498940120E+00   6.2928743842250778E-01   3.5749504062968335E-01\n         1         96   7.1382360407220194E-02   4.1294697970582952E+00   1.0318579765799314E+00   5.6205462834461606E-01\n         1         97   4.8485102483644640E-02   3.0682392304483188E+00   7.0270610075178364E-01   3.8109396274199092E-01\n         1         98   4.2982508668804750E-02   2.7812729531227500E+00   6.5835563695387112E-01   3.6057606040887158E-01\n         1         99   1.0305314920747077E-02   1.2836559468232112E+00   2.6314071553691487E-01   1.5792461750625936E-01\n         1        100   2.6795277697586091E+00   3.7483923873874772E+01   1.4558399796789585E+01   4.3217073571883597E+00\n         1        101   9.6861712985647603E+00   1.1079249709138742E+02   4.5755874983565917E+01   1.2920257848346751E+01\n         1        102   1.4602609037671213E+01   1.7421990484882818E+02   7.3729573762831834E+01   2.0668512730675921E+01\n         1        103   9.4814690533414847E+00   1.1973218870187333E+02   5.0597636079669449E+01   1.4253762328980228E+01\n         1        104   8.5058331373421225E+00   1.0943031578033759E+02   4.6341929165007045E+01   1.3106613048889903E+01\n         1        105   2.9741105811066335E+00   4.0793548760149861E+01   1.7629616989937688E+01   5.0598468249510669E+00\n         1        106   9.3198014095011453E-02   1.8646283811502087E+00   5.4440304534609596E-01   2.1781056048893171E-01\n         1        107   3.1864613522519958E-01   5.4161859740604319E+00   1.8888416360851201E+00   7.6264264692602912E-01\n         1        108   5.5570661971605728E-01   8.5383677428330902E+00   3.1087163360886203E+00   1.2110633017081061E+00\n         1        109   3.8217936156556126E-01   6.1354008965889211E+00   2.1460414184138812E+00   8.2878282155774807E-01\n         1        110   3.4386186649561573E-01   5.7027035595026847E+00   1.9916190831293090E+00   7.7329764916945687E-01\n         1        111   9.1490542162076582E-02   2.7215498328821832E+00   7.7880625409665438E-01   3.2395774171899855E-01\n         1        112   1.6531386252622308E+01   1.0152504027161164E+02   4.7514745292601489E+01   9.9017413881682721E+00\n         1        113   4.8968388988984174E+01   2.9121194650532118E+02   1.3829099779888946E+02   2.8230738162769132E+01\n         1        114   7.6329120816769134E+01   4.6466980123929432E+02   2.2086375515410890E+02   4.4968692071886515E+01\n         1        115   5.1249370212032915E+01   3.1827602373954085E+02   1.5126341884851288E+02   3.0888363761516239E+01\n         1        116   4.6913869832124554E+01   2.9009237025303764E+02   1.3864440478931155E+02   2.8310681193931000E+01\n         1        117   1.9597393807129524E+01   1.0986942732597737E+02   5.2931971015194144E+01   1.0858089969763240E+01\n         1        118   1.2152370911691392E-07   5.2265742615602455E-02   1.0069020600744980E-02   1.3036533397304307E-02\n         1        119   2.4459580901221437E-07   8.1328928871128969E-02   1.0725523562561625E-02   1.2871660148616289E-02\n         1        120   1.4821427439506633E-07   1.1443843270033990E-01   8.6493593302056828E-03   8.6311206056388784E-03\n         1        121  -5.6483120918067203E-16   1.0231106970138439E-01   3.9510452328287930E-03   6.6364854362518672E-03\n         1        122  -5.6690117799857142E-16   1.1135049197957866E-01   4.1740456396089243E-03   7.1315120163183083E-03\n         1        123  -1.0593587831838508E-16   8.5274708390060294E-02   1.7585622959728488E-03   4.4294017486752983E-03\n         1        124   2.0041898963602668E-03   3.0462458283923632E-01   7.6346878619169792E-02   7.8516570557692872E-02\n         1        125   3.7848514420379471E-03   4.4030055603436230E-01   1.0905601483159978E-01   6.7622411634581117E-02\n         1        126   2.7669441344468715E-03   6.3917475127430268E-01   1.2723446389170617E-01   6.4830615646937623E-02\n         1        127   2.9630171901262610E-06   5.6197480815094336E-01   7.6283777915212431E-02   6.0043336923884888E-02\n         1        128   2.7199277339843227E-06   5.8105656826759322E-01   7.4225051064060507E-02   6.1212009896402887E-02\n         1        129   2.5875766924341708E-08   3.8073237701940543E-01   2.8434007672895282E-02   3.3570355158285228E-02\n         1        130   3.7609816347695113E-02   7.7843858610943606E-01   2.4709999260446422E-01   1.5993842727120319E-01\n         1        131   7.6729087245930028E-02   1.4196809169059283E+00   4.6701056450601114E-01   1.5366501741456301E-01\n         1        132   8.2952905630474846E-02   2.4149650732222967E+00   6.8474455181594662E-01   2.5833742481719885E-01\n         1        133   3.5267352723956352E-03   2.0418281512541823E+00   4.6198911226251327E-01   2.3277456622475548E-01\n         1        134   3.3110006952649430E-03   2.0002611450545733E+00   4.3283126514287384E-01   2.2703716393230650E-01\n         1        135   3.8308693622682598E-04   9.4769342375777110E-01   1.6047567623294595E-01   1.1260598477272853E-01\n         1        136   3.1954782567957662E-01   1.5776925537844500E+01   5.7669983909176166E+00   2.0512915931859421E+00\n         1        137   7.5450753528668091E-01   4.7632674324532765E+01   1.3925376083334463E+01   5.9254825512190870E+00\n         1        138   8.2069958737773074E-01   7.4689567830423243E+01   2.3199352136795635E+01   9.6887177124693977E+00\n         1        139   3.2859444950928068E-01   5.2380898649259180E+01   1.6394041354593227E+01   6.9055195614356206E+00\n         1        140   3.1181469531260941E-01   4.4956056489679696E+01   1.4771842334102876E+01   6.1835885621115478E+00\n         1        141   7.9333979944650329E-02   1.7186788066409836E+01   5.3768531231560130E+00   2.3341680208180509E+00\n         1        142   1.9648714794188082E-01   1.5688995005843331E+00   6.6137286769311865E-01   2.3786089846268693E-01\n         1        143   5.1221895577866394E-01   4.1121186212903806E+00   1.5042117660025605E+00   3.9616174272653926E-01\n         1        144   4.3904635208661275E-01   6.7837815934718257E+00   2.4124794960172755E+00   7.6522053246854038E-01\n         1        145   8.1922434405018910E-02   5.2032404170208864E+00   1.6847841174678806E+00   6.3321490996819840E-01\n         1        146   7.7521108725653362E-02   4.9287301604198817E+00   1.5530434886712003E+00   5.9687334602637987E-01\n         1        147   1.5915564667138976E-02   1.9546030000174897E+00   5.7288136729457106E-01   2.6766251669505281E-01\n         1        148   8.4097101846191720E+00   7.5597518103614433E+01   3.3250725463031998E+01   7.9744345621289066E+00\n         1        149   1.6224043521765932E+01   2.0060910494258761E+02   8.6318270391028378E+01   2.2518359076840422E+01\n         1        150   2.8195767208650128E+01   3.0862826179464707E+02   1.3689887451533019E+02   3.5058142340561687E+01\n         1        151   2.0341009194300554E+01   2.0643261016892305E+02   9.2955071596663572E+01   2.3747396675826725E+01\n         1        152   1.7559393193182078E+01   1.8876524477375509E+02   8.5177200954685446E+01   2.1772971874490867E+01\n         1        153   4.1690097670032165E+00   7.4960766695340908E+01   3.2513713810941887E+01   8.4751165999800335E+00\n         1        154   7.2923008261745248E-01   3.2550080151893850E+00   1.6539163160612629E+00   3.7572399598979667E-01\n         1        155   1.5092301739014640E+00   9.3187091618107374E+00   4.1220216609884099E+00   9.8715306804584757E-01\n         1        156   1.5056613693099841E+00   1.6113832483161740E+01   6.7235072167829681E+00   1.8046438451129481E+00\n         1        157   6.4690411294584482E-01   1.1483604083382872E+01   4.6943319337704459E+00   1.3940979831078544E+00\n         1        158   5.9690450114477200E-01   1.0163227996675404E+01   4.2981940621687702E+00   1.2874338770256830E+00\n         1        159   1.1970829685362548E-01   3.9000889726093733E+00   1.5930689419664921E+00   5.3500368917553243E-01\n         1        160   2.9541673135164832E+01   1.7956505264559704E+02   9.4233007113744449E+01   1.9207833490125875E+01\n         1        161   7.8466958661931827E+01   4.8055826494351561E+02   2.4477082141349300E+02   5.0879432649094198E+01\n         1        162   1.2414941499339503E+02   7.6316847899069273E+02   3.8873584114390383E+02   7.9944611533586354E+01\n         1        163   8.0405677866192534E+01   5.2134615684113589E+02   2.6581721407254992E+02   5.4678262150570191E+01\n         1        164   7.4634807471521285E+01   4.7528202973617630E+02   2.4387092268516506E+02   5.0243814964774508E+01\n         1        165   2.8470350889835405E+01   1.7994297409160947E+02   9.2817237463201536E+01   1.9352816642770065E+01\n         1        166  -1.1848436914858111E-17   8.9009857217323338E-03   6.1293284923072671E-04   8.7168795335746069E-04\n         1        167  -1.2015749556800137E-17   1.0130173922777663E-02   5.8388995696158222E-04   8.6362698466414855E-04\n         1        168  -1.2985772917813876E-17   8.0997458075157038E-03   1.4029428054841033E-04   2.9729062311109806E-04\n         1        169  -1.2593053555347082E-17   7.0567169327866086E-03   6.5259189123179933E-05   2.2304815668721219E-04\n         1        170  -2.2588863879013769E-17   4.7778173753099855E-03   2.7876783979929873E-05   1.3165679419191833E-04\n         1        171  -2.7103098933058901E-16   2.3766710708078127E-02   2.9378222367593223E-03   3.4995128092543035E-03\n         1        172  -4.2027072196860628E-16   1.5114342726094493E-01   2.1351943012046463E-02   2.6619812702909914E-02\n         1        173  -5.2856472166402743E-16   1.8629785653965808E-01   2.2235896092200124E-02   2.7740024632666924E-02\n         1        174  -2.8953948008639497E-16   1.3609778207672604E-01   7.2828285816926739E-03   1.0528689064650917E-02\n         1        175  -1.7461686218799382E-16   1.2333659922841630E-01   4.9046842579432278E-03   8.2512114789903297E-03\n         1        176  -1.3984948167886373E-16   5.9646143074191083E-02   2.0972424057325518E-03   4.5178341862623242E-03\n         1        177  -1.1629224144565324E-16   1.1103865245242017E-01   1.7713789051717346E-02   1.7185175512937488E-02\n         1        178  -4.8768602191517616E-16   6.6396138628631540E-01   1.1228612736258256E-01   1.2242209111690140E-01\n         1        179  -1.1549643570420682E-15   8.6998487698736837E-01   1.3242193593986573E-01   1.3854018305683574E-01\n         1        180  -9.1661402142886631E-16   5.8311219891437838E-01   5.8472054251598245E-02   6.2268459395751138E-02\n         1        181  -8.4738455496057840E-16   5.6022160182620906E-01   4.7398091146176463E-02   5.2262347906107814E-02\n         1        182  -1.5216116031280500E-16   2.6728364211818134E-01   1.9456993348504866E-02   2.6451263797231766E-02\n         1        183  -5.5302595796431788E-16   4.6651873395875327E+00   7.6909735850328687E-01   6.1648173691501940E-01\n         1        184  -2.9027787117986680E-15   1.3804010329500246E+01   2.5968061245462728E+00   1.8636732831002352E+00\n         1        185  -3.6502171249638293E-15   1.7964105748489615E+01   4.0281018617082278E+00   2.7936885987751228E+00\n         1        186  -1.8431118408104498E-15   1.2277178752171039E+01   2.7103656977299622E+00   1.9407644882074722E+00\n         1        187  -1.3286955774162453E-15   1.2004442777720838E+01   2.5291743355617133E+00   1.8217269973617438E+00\n         1        188  -6.8905495876393187E-17   4.7710669452929295E+00   9.5557441333226800E-01   7.2784654846627661E-01\n         1        189   2.1638294884443980E-05   3.0376921083261915E-01   6.7693096069933539E-02   5.0988507447609063E-02\n         1        190   8.3544004308620990E-05   1.5512838067556292E+00   3.3173736784806074E-01   3.0129809262072244E-01\n         1        191   1.2713261653773589E-04   2.2523338664821662E+00   4.3528671080786330E-01   3.7255612924423231E-01\n         1        192   4.4610837853624061E-05   1.5405481366005049E+00   2.3290161226386707E-01   1.9375445777335393E-01\n         1        193   4.2696017045032018E-05   1.3939044550492212E+00   2.0320769767244087E-01   1.7020887190083797E-01\n         1        194   1.8481569575251545E-05   6.8977849059845231E-01   8.0839185639507441E-02   7.9608943152934750E-02\n         1        195   2.0507302384727047E-02   1.4428390047148968E+01   4.2471849773414512E+00   2.1473454583006570E+00\n         1        196   4.7418491980313074E-02   3.6914526365739619E+01   1.1181869993841593E+01   5.7047006671757163E+00\n         1        197   6.8070838738142861E-02   6.0435522001861777E+01   1.7601459785057873E+01   8.9045172962186800E+00\n         1        198   4.2721245114197233E-02   4.2564830351571736E+01   1.2017010394988983E+01   6.1287680557567921E+00\n         1        199   3.7321898107842456E-02   3.9115799781401520E+01   1.1015042064683902E+01   5.6427058826835390E+00\n         1        200   1.5705056992766524E-02   1.4218103757441645E+01   4.2287567914021258E+00   2.2335729792188630E+00\n         1        201   1.4695863642724398E-03   7.2132465108210375E-01   2.0672220383389153E-01   1.2189503966229270E-01\n         1        202   5.6141504233920723E-03   2.9220514545754477E+00   7.8862378714698200E-01   5.7107396151348511E-01\n         1        203   7.5366075204429317E-03   4.4494559564896230E+00   1.1146430967543648E+00   7.6131000191571485E-01\n         1        204   3.6789424554416628E-03   3.0317906856812291E+00   6.6636163644726731E-01   4.3808273253418528E-01\n         1        205   3.6466010608769508E-03   2.6903619267099073E+00   5.9812633097382728E-01   3.9425900259000507E-01\n         1        206   1.7070620138373745E-03   1.3608846201739351E+00   2.3340608455587861E-01   1.7352915593961865E-01\n         1        207   3.6155260424126623E-01   3.7017017531650090E+01   1.3540828477785897E+01   5.0609540678117044E+00\n         1        208   9.4909047785280287E-01   9.5162345183920010E+01   3.5022731034642987E+01   1.3025741382532960E+01\n         1        209   1.3837148347347041E+00   1.5056385241623857E+02   5.5790855562789964E+01   2.0567682439239288E+01\n         1        210   8.6723409361975856E-01   1.0527726240242093E+02   3.8260397354562485E+01   1.4119806037506219E+01\n         1        211   8.0076038099326297E-01   9.6583839881220953E+01   3.5107657641297479E+01   1.2970062214109774E+01\n         1        212   2.9548144546513727E-01   3.8363713918580679E+01   1.3352499746537719E+01   5.0005234769351636E+00\n         1        213  -4.3000975313373299E-16   1.4970235613521284E-02   3.3229490889538746E-03   2.6988336124648513E-03\n         1        214  -4.0598359456622110E-16   2.2396547721997718E-02   3.1659370389059524E-03   2.5832496518005264E-03\n         1        215  -4.0195162322780411E-16   2.4771250700016966E-02   1.6433500791575165E-03   1.3239952533196319E-03\n         1        216  -4.2579480156484828E-16   2.4704502988387264E-02   1.8155578163881223E-04   5.5134048902809112E-04\n         1        217  -4.0583805475647870E-16   2.4470190895643333E-02   1.8599919547246664E-04   6.2166053036710766E-04\n         1        218  -6.3909108264545264E-16   2.8875879499062604E-02   1.1925630027341996E-04   6.1250047851503693E-04\n         1        219   7.3255479742123241E-05   1.3189328703304892E-01   5.3000156366609132E-02   4.0042565542700401E-02\n         1        220   5.0679887366284870E-05   1.8827820705368936E-01   5.7677053995509944E-02   3.7530017711271887E-02\n         1        221   2.1267002843113076E-05   3.3804058224403977E-01   4.2369858543345983E-02   2.5407089634032827E-02\n         1        222   0.0000000000000000E+00   2.9512295332674587E-01   1.5006194900413047E-02   1.6895407912780058E-02\n         1        223  -2.7302858178001829E-19   2.5501513125914987E-01   1.4513950862696041E-02   1.8258963982074800E-02\n         1        224  -1.4581876722379970E-16   2.5862683019007265E-01   7.4645000848107207E-03   1.3899313891801929E-02\n         1        225   6.1062965959253904E-03   5.2024057158259585E-01   1.9918250626563580E-01   1.3557719423266895E-01\n         1        226   4.1814483428114233E-03   8.1776210105984470E-01   2.4841383263632225E-01   1.3014349079675774E-01\n         1        227   2.5590837051746342E-03   1.3199556561403507E+00   2.6095250096932399E-01   1.3707702905729788E-01\n         1        228   4.1186264653910376E-04   1.0458855587979277E+00   1.4268192048687262E-01   1.0668138184756649E-01\n         1        229   1.5457103733667005E-04   1.1118613205853334E+00   1.3875536593111648E-01   1.1277732870219868E-01\n         1        230   4.9021287046954801E-06   8.7753074270569575E-01   6.5340600383226491E-02   7.4741042881604297E-02\n         1        231   5.3451998165513936E-02   1.3722614207889087E+01   2.8110476150328205E+00   1.6452005325782018E+00\n         1        232   4.4434038916910244E-02   3.2607793048948054E+01   5.1612383538240021E+00   3.3027559240380091E+00\n         1        233   6.6893413720019723E-02   5.7945920745276460E+01   8.8058428750733633E+00   5.6088401648719994E+00\n         1        234   2.4239589213376406E-02   4.3327056370631851E+01   6.4014188927810398E+00   4.2792268578420281E+00\n         1        235   3.2025535247987014E-02   4.1615620921024224E+01   6.1329985990220219E+00   4.1066638222379863E+00\n         1        236   7.6381284733007828E-04   1.3111071878297237E+01   2.4987016271359206E+00   1.8233122722230599E+00\n         1        237   3.8927012875684681E-02   1.3601037242170322E+00   5.2191108385165441E-01   3.0233680993856527E-01\n         1        238   4.1091311635999279E-02   2.4330785717461167E+00   7.3130333326035568E-01   3.1907409070760351E-01\n         1        239   4.5319841202538971E-02   4.4901400842656169E+00   9.8149544150482171E-01   4.5746721636142462E-01\n         1        240   1.3490140904256312E-02   3.6928602344745114E+00   6.3640062962135868E-01   3.6508286936081719E-01\n         1        241   1.2598408948273783E-02   3.6172964439095692E+00   6.1453783808074280E-01   3.7403397674381633E-01\n         1        242   8.8826803100064064E-04   2.0295108836003597E+00   2.7046268016259550E-01   2.1814504494226578E-01\n         1        243   1.8759755379521450E+00   4.1774794902115673E+01   1.4528658438776793E+01   4.9750208746846702E+00\n         1        244   2.9542045694139185E+00   1.0899750956958944E+02   3.5926645693474185E+01   1.3258192891276828E+01\n         1        245   3.8304878966649492E+00   1.7792731663356429E+02   6.0915297522147412E+01   2.2007042956571190E+01\n         1        246   2.2789732056899221E+00   1.2645444370768000E+02   4.3349665806191290E+01   1.5814726283403534E+01\n         1        247   2.1294848951226468E+00   1.1913070248320449E+02   3.9699403435023406E+01   1.4312492268882965E+01\n         1        248   6.6756549939528098E-01   4.3693275919329992E+01   1.5055529966193294E+01   5.4585910288840953E+00\n         1        249   1.7722206788910308E-01   2.7040536880764821E+00   1.1573280402547617E+00   5.4092630771256778E-01\n         1        250   1.8412595675254104E-01   5.6141175802178500E+00   1.8623374306036700E+00   6.8510697112792673E-01\n         1        251   2.7260477341066441E-01   1.0824524222237070E+01   2.8439395662717581E+00   1.1275498049626269E+00\n         1        252   1.1354458880225779E-01   8.6505247088905648E+00   1.9653679014177534E+00   8.9589551275207047E-01\n         1        253   1.0904004720122391E-01   8.3979833194155873E+00   1.8728450533617604E+00   8.9159828736555979E-01\n         1        254   1.5420453962276939E-02   3.8791351746354166E+00   7.8294377734526877E-01   4.6500546676739390E-01\n         1        255   7.5661177794389554E+00   1.0137991761355863E+02   3.9975695133170987E+01   1.2470111894942587E+01\n         1        256   1.5749658322885811E+01   3.0212642568924912E+02   1.0501132337324783E+02   3.5927719146810936E+01\n         1        257   2.9359724892100107E+01   4.8206417334141508E+02   1.7034570441585672E+02   5.8182189299795354E+01\n         1        258   2.0394873343867829E+01   3.2654394940794083E+02   1.1718980461023428E+02   4.0215808756470835E+01\n         1        259   1.8616438114919038E+01   2.9920713076019598E+02   1.0728266208625732E+02   3.6894493238629785E+01\n         1        260   6.3867043023256223E+00   1.1669661054232476E+02   4.0664641161206035E+01   1.4261335462615461E+01\n         1        261  -2.1148880698555696E-17   9.7091160297992831E-03   1.1903931781245534E-03   1.6205253345015953E-03\n         1        262  -2.5961668340350929E-16   2.4734997461048732E-02   1.7937221884292947E-03   2.5404424424614411E-03\n         1        263  -4.8058010279700336E-16   2.5171551563703671E-02   1.0317986855025135E-03   1.4651469685379639E-03\n         1        264  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-1.0225638544993166E-15   1.3518273758444476E+01   1.9976102909659905E+00   1.6256331969142730E+00\n         1        281  -7.0972833662419045E-16   2.1568706622359496E+01   3.2228226140946572E+00   2.6686529734490865E+00\n         1        282  -2.6521067045062343E-16   1.5766092992197748E+01   2.3122045757250489E+00   2.0333564693392243E+00\n         1        283  -1.7635518551726226E-16   1.4684408153666491E+01   2.1478584141871915E+00   1.8606953439049330E+00\n         1        284  -6.2859702648111543E-19   5.2658939024659928E+00   8.1377805831736183E-01   7.7940575895957687E-01\n         1        285   9.8960743064583037E-05   5.8144130349883061E-01   1.5517155810119362E-01   1.2376205352778050E-01\n         1        286   7.0121008496359854E-05   1.3982261270486775E+00   2.8477555931360926E-01   1.9930619983507467E-01\n         1        287   8.2383214902720809E-05   2.1196618214372385E+00   3.4170901709766560E-01   2.3998228579228495E-01\n         1        288   3.8195204102453020E-05   1.4032576394796905E+00   1.9723596634074936E-01   1.6857030916332894E-01\n         1        289   3.7864902327405356E-05   1.2764188742268572E+00   1.8674153384592607E-01   1.6383800911802235E-01\n         1        290   8.6671479554384641E-06   9.4314124574518388E-01   7.9342689558002721E-02   9.4413814190556805E-02\n         1        291   1.4120258745390146E-02   1.4389927509398794E+01   4.1363670761429763E+00   2.1955971286058307E+00\n         1        292   5.1475185128733864E-02   3.6254220974183504E+01   9.9371214973091941E+00   5.3973477079602210E+00\n         1        293   8.1432721679340500E-02   5.7243352005477213E+01   1.6138993911944223E+01   8.6342018161577982E+00\n         1        294   5.3456264770985383E-02   4.0040748403411385E+01   1.1119609088266834E+01   6.0594409118378030E+00\n         1        295   5.2293397131346134E-02   3.6352980691073647E+01   1.0150769674881372E+01   5.5303562547169038E+00\n         1        296   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-1.6787227806912034E-16   2.8416073762637984E-02   1.9195361895907168E-04   8.9661390570185259E-04\n         1        313  -1.7764119777771352E-16   2.3061143546043241E-02   1.8584707364104362E-04   8.9586881650174780E-04\n         1        314  -1.6798416521647816E-16   2.1700798654479912E-02   2.0304653537784600E-04   9.5913144385747888E-04\n         1        315  -1.3115279964135579E-16   2.4994377220843599E-02   1.1894458114985284E-04   8.1381080336820203E-04\n         1        316  -1.3177061049622312E-16   1.0969027776753548E-02   4.1353049524839276E-05   2.2871261564803228E-04\n         1        317  -2.7528524562362418E-16   8.6160734040985468E-02   7.6680725990990197E-04   3.0018909236925470E-03\n         1        318  -1.7607390293398846E-16   1.1551389665952154E-01   2.6518922848760809E-03   7.0375825014900063E-03\n         1        319  -1.0668260541984058E-16   9.9960228837551082E-02   2.4649372574469413E-03   6.9402510559031464E-03\n         1        320  -3.2093507783452474E-16   9.4673589497312360E-02   2.5576869443322404E-03   7.2468336265971850E-03\n         1        321  -2.8370748783745319E-16   1.0712697552932823E-01   1.2733738927325931E-03   5.2506212094371877E-03\n         1        322  -8.6051851181298153E-16   4.5420110181390810E-01   5.4581891847823062E-03   2.0158458800118049E-02\n         1        323  -1.8681751270233328E-15   1.9917888667493993E+00   6.9835511204640821E-02   1.6009111758083816E-01\n         1        324  -1.1079320437943234E-15   3.1322870927148956E+00   1.9022511298576653E-01   3.3338776104754742E-01\n         1        325  -9.0841184779847062E-16   2.9716310154867553E+00   1.6528460399347120E-01   3.0743479555007097E-01\n         1        326  -8.4166320600932235E-16   2.9534923451991073E+00   1.6116910760723452E-01   2.9580274869961498E-01\n         1        327  -7.8406824003543401E-16   1.0734353587305678E+00   6.7310462169898985E-02   1.4749263482868955E-01\n         1        328  -2.3700324034380827E-17   3.1238223822295883E-02   4.2281682336613272E-04   1.2669934854046393E-03\n         1        329  -3.1429277342042671E-17   1.7964892540031832E-01   4.8995440882093578E-03   1.1306800548750053E-02\n         1        330   2.0315367224002399E-13   2.5915883489442870E-01   1.4000186208050179E-02   2.4929308631085445E-02\n         1        331   0.0000000000000000E+00   2.4832146503931771E-01   1.2351856455411007E-02   2.3870362876190803E-02\n         1        332  -5.2648558513060306E-17   2.6061724405948949E-01   1.2370962223237900E-02   2.4221783619927193E-02\n         1        333  -5.6327718287287329E-18   2.3775258680342709E-01   5.6287533989128691E-03   1.5540936232544943E-02\n         1        334  -3.6730021725519453E-17   1.3201013164099837E+00   7.6742756276333382E-02   1.1903134842705339E-01\n         1        335   1.2212607424253870E-09   6.2654746902195493E+00   4.9714276036925947E-01   5.9753396613820353E-01\n         1        336   1.2976299860715776E-05   9.4688087487172776E+00   9.5781990256922811E-01   1.0207757876830421E+00\n         1        337   0.0000000000000000E+00   6.1206499535430936E+00   7.1556713090341206E-01   7.8090968199806454E-01\n         1        338   0.0000000000000000E+00   5.7566375825879996E+00   6.5956730493035443E-01   7.2178388932463922E-01\n         1        339   0.0000000000000000E+00   2.5310664911090091E+00   2.4614721432697698E-01   3.0892643571172745E-01\n         1        340   1.9016804904533030E-11   6.2983136379773777E-02   2.2937122245780964E-03   4.3086590994617837E-03\n         1        341   1.0992400221986136E-07   3.0194362082612236E-01   1.9087324900981768E-02   2.9118716904287596E-02\n         1        342   1.9215740083786509E-06   5.2728199957353783E-01   4.6994041773351793E-02   6.0567186736187627E-02\n         1        343   2.2002678965637838E-06   4.9134578878640522E-01   3.9401883024866628E-02   5.5653072954543061E-02\n         1        344   2.6182889584095577E-06   5.1746262483342353E-01   3.8470812332549967E-02   5.5074739509189216E-02\n         1        345   7.4486927914759211E-08   3.9079422367154815E-01   1.6552509356257770E-02   3.1923037063115951E-02\n         1        346   6.8002073953750842E-05   3.1616218405733121E+00   4.4013684688592053E-01   4.0110277190282401E-01\n         1        347   1.0458786395398296E-04   1.1353558726643103E+01   2.0234626083246541E+00   1.5832818310176431E+00\n         1        348   2.1902474908233167E-03   1.8174385224697780E+01   3.4192601816925867E+00   2.5344409423211278E+00\n         1        349   1.6452087369477073E-03   1.3426053514568649E+01   2.3929457933775153E+00   1.8010448428971906E+00\n         1        350   1.3343644056231702E-03   1.2211023766237968E+01   2.1897069374449187E+00   1.6667009374665416E+00\n         1        351   2.1264107590565271E-04   5.2047173609919151E+00   8.2729312537611677E-01   6.9161629317817519E-01\n         2          1   1.2370111408686368E+01   2.1106915763222830E+01   1.6717102025540722E+01   1.1029074323103294E+00\n         2          2   7.9590730670167282E+00   1.7980151488989012E+01   1.3727152659455774E+01   1.3032121764937137E+00\n         2          3   6.5390904532813776E-01   3.6951604406790430E+00   2.0692239750973549E+00   4.5364075001243037E-01\n         2          4   5.5698361138611929E-05   8.2331148431728463E-01   2.6252145241898867E-01   1.8788755283563099E-01\n         2          5   6.9326147389832116E-03   1.2850588009647286E+00   4.4139133332468433E-01   3.0164276627384268E-01\n         2          6   6.9024945296797180E-01   4.4218717391819489E+00   1.9176801842587543E+00   5.8679724393795440E-01\n         2          7   1.4722010659422669E-01   2.2222264323186627E+00   8.5817509786076596E-01   4.3959747385550069E-01\n         2          8   5.7634876296928739E-01   3.2300100744155245E+00   1.4539015078589808E+00   4.8013631495471565E-01\n         2          9   1.6318561665780154E+00   1.2012366767060303E+01   6.1915546248366855E+00   1.4444237174830148E+00\n         2         10   1.2984520227451501E+00   4.5743572758519893E+00   2.3729913394920095E+00   4.9287073468277093E-01\n         2         11   7.4966735937289073E+00   2.3086817023360908E+01   1.5560237349624256E+01   2.0459722463495025E+00\n         2         12   2.3370275435840728E+00   6.2708271678021870E+00   3.7160433386324749E+00   5.2890775352150821E-01\n         2         13   1.5778594842220002E+01   3.6936429044044289E+01   2.5671311521437264E+01   2.6059122410147086E+00\n         2         14  -1.3322676295501878E-15   2.4206174037762840E-01   1.3427071432874801E-01   5.5929481041713178E-02\n         2         15   4.6605013387268635E-05   4.9852575174481706E-01   3.1835455461930129E-01   1.3020438481204638E-01\n         2         16   7.4877699205972759E-02   3.2426085664740025E+00   2.2456019325544858E+00   8.0611298862141512E-01\n         2         17   1.7735519611401962E-02   1.1491288268501287E+00   8.0970209186926678E-01   3.0693532610845292E-01\n         2         18   1.3128974617946443E-01   2.0501235897044916E+00   1.4409235566419056E+00   4.7462707730696974E-01\n         2         19   2.0922142594625068E+00   9.9468706601424852E+00   4.6429239824000899E+00   9.0672882127713683E-01\n         2         20   4.4655285022276237E-01   3.3670472299918202E+00   2.2368334298459787E+00   5.9416759710846012E-01\n         2         21   2.0067274419346290E+00   2.2286998738766798E+01   1.1297006129182956E+01   2.9016549001783871E+00\n         2         22   9.5221877526134946E-01   4.9451894437029633E+00   3.2907137868455658E+00   6.6536167808957503E-01\n         2         23   1.1008019389088860E+01   3.6633891119572553E+01   2.3355589023259903E+01   3.4846285068938907E+00\n         2         24  -1.1102230246251565E-15   1.4184055103230586E-01   2.1223720773868693E-02   3.4451115815381537E-02\n         2         25  -1.3322676295501878E-15   2.7105278307761815E-01   5.1147870492171212E-02   8.0375138915515093E-02\n         2         26  -1.7763568394002505E-15   1.5313628024466892E+00   3.5664546750150672E-01   4.1930548116329808E-01\n         2         27  -1.7763568394002505E-15   5.3871149107085148E-01   1.2887322630977524E-01   1.7285596573003989E-01\n         2         28   5.6915894155462610E-05   8.6243760615291798E-01   2.2095468251343731E-01   2.3772502411405563E-01\n         2         29   3.4088716392320917E-03   2.9964813469995333E+00   6.2879803932500045E-01   4.7454756857605707E-01\n         2         30   6.6483401614776394E-03   1.1293624006275655E+00   3.3754947964447080E-01   2.7728759222894234E-01\n         2         31   2.5055430516308652E-03   5.9666429106341701E+00   1.8798829121108092E+00   9.4500388056567175E-01\n         2         32   4.0455424107940452E-02   1.3581981583290548E+00   4.9713670074178296E-01   2.9898524444802016E-01\n         2         33   1.9056719306665537E-01   8.1743448797834670E+00   3.2919724019133016E+00   1.1569970627931025E+00\n         2         34   1.0490829605667448E+01   3.2448612403044457E+01   1.9864336724882346E+01   2.7329237836938267E+00\n         2         35   3.0916996476275806E+01   9.3633766733736877E+01   5.8173725811384259E+01   7.9357103300306848E+00\n         2         36   5.0148769557962339E+01   1.4839436783964052E+02   9.3772708667709765E+01   1.2568792091837715E+01\n         2         37   3.4923556542687706E+01   1.0174193955719564E+02   6.4649016164958468E+01   8.6123432880881765E+00\n         2         38   3.1884762870308919E+01   9.3596113140372367E+01   5.9054216602733867E+01   7.8774466072726099E+00\n         2         39   1.2683838878185455E+01   3.6742068700298070E+01   2.2560116110172320E+01   2.9685693144973246E+00\n         2         40   1.7853732273689396E+01   5.7757113928998344E+01   3.7575031479805006E+01   4.7910342647743276E+00\n         2         41   4.2360258940408322E+01   1.4984924237392428E+02   9.6046796610797671E+01   1.3775914996232904E+01\n         2         42   6.7969480916005480E+01   2.3814754540271986E+02   1.5468174157531126E+02   2.1767484452347421E+01\n         2         43   4.4717815990799956E+01   1.6490078753817681E+02   1.0644629268911434E+02   1.4895923631856354E+01\n         2         44   4.1094225400058754E+01   1.5189742447251245E+02   9.7865199416330142E+01   1.3637300540001899E+01\n         2         45   1.6274974825449913E+01   5.9490462642359553E+01   3.7832748751297572E+01   5.1890594385442883E+00\n         2         46   1.5047596186319243E+00   1.1697774055160188E+01   5.6797434538455205E+00   1.4168630115661052E+00\n         2         47   3.6830361630492998E+00   3.0215374864867016E+01   1.4716088343270338E+01   3.6604480950959903E+00\n         2         48   5.5607139336214892E+00   4.7736013797240012E+01   2.3475252722684814E+01   5.8884047333260678E+00\n         2         49   3.7009840431909118E+00   3.2692854767634401E+01   1.6178300828689416E+01   4.1510667558618897E+00\n         2         50   3.2449870535713017E+00   2.9804755175073776E+01   1.4727778893771768E+01   3.8010322545504605E+00\n         2         51   1.3597803459387674E+00   1.1422782820088740E+01   5.5784463850670996E+00   1.3617504771750930E+00\n         2         52   6.6050184344182057E+00   2.3520792686831065E+01   1.4196278130439875E+01   2.4463088137190776E+00\n         2         53   1.2089130198999424E+01   6.4506931261072893E+01   3.8291432040749498E+01   7.3781006144107986E+00\n         2         54   1.8995524141532911E+01   1.0812256532348557E+02   6.2697565304924836E+01   1.2212396939598225E+01\n         2         55   1.3031352981520142E+01   7.6505637761955512E+01   4.3573246145471565E+01   8.7370272853912017E+00\n         2         56   1.2058976049597680E+01   7.0516117446951156E+01   3.9647126201919960E+01   7.9467541550671301E+00\n         2         57   4.4421383058301185E+00   2.5360437591597645E+01   1.4763667743001324E+01   3.0523541754156258E+00\n         2         58   1.6296132905884495E+00   9.1003463508489695E+00   4.7692096792848124E+00   1.0757410587390290E+00\n         2         59   2.6724993575418190E+00   2.2860742795192284E+01   1.1720345863796613E+01   2.9343130143749234E+00\n         2         60   4.3591786493216675E+00   3.7192233430810369E+01   1.8979973070147150E+01   4.7466649398674097E+00\n         2         61   2.7805078715473970E+00   2.7366473294693094E+01   1.3110133248370786E+01   3.4237190980996175E+00\n         2         62   2.5098646642828655E+00   2.4873870399552292E+01   1.2056867407871897E+01   3.1528736324426050E+00\n         2         63   6.8021637891979148E-01   9.3119256580709084E+00   4.6849151296678357E+00   1.3091671420867326E+00\n         2         64   1.5204848098227860E-03   6.5950200588995445E-01   1.5351330864361537E-01   1.0034992913069611E-01\n         2         65   1.5573499703493487E-02   2.5652081003777707E+00   7.1693841284916737E-01   3.9315644805821581E-01\n         2         66   6.1600247347199370E-02   4.4598900277265319E+00   1.2784617108569720E+00   6.2967891396221942E-01\n         2         67   4.2864378734796690E-02   3.2119679036800406E+00   9.2398385530991922E-01   4.7388281403048294E-01\n         2         68   3.8944104810090356E-02   2.7606418422663275E+00   8.3482007635845501E-01   4.2930984594983962E-01\n         2         69   2.3148923429607078E-03   1.3515883499893624E+00   2.9340076046952596E-01   1.8233330868560657E-01\n         2         70  -3.8343165722002626E-16   1.2273920872761083E-02   6.8770333961471006E-05   2.3995420389576492E-04\n         2         71   8.5617156608656675E-13   1.1205905790113074E-01   5.2075973728551526E-03   8.8557803208937740E-03\n         2         72   7.0041457456641406E-08   5.0589966722753954E-01   5.8209286903255171E-02   1.3031003528391472E-01\n         2         73   2.8106581751314836E-11   5.2802377001603840E-01   6.1817266343333219E-02   1.4095015222995086E-01\n         2         74   9.4172528095885996E-08   5.0990792586616684E-01   5.7817887134402349E-02   1.3450127977190729E-01\n         2         75  -1.4997571384882273E-19   1.0293257670072954E-01   4.8555153663802988E-03   1.2225105358126320E-02\n         2         76   7.4066681231413311E-06   1.0528555834961313E-01   5.5518031061540605E-03   7.2112520617481366E-03\n         2         77   4.5392826401123435E-04   4.9702163745575723E-01   5.2848727978024417E-02   3.8086769729494624E-02\n         2         78   1.2470712591659463E-03   1.4500098978071343E+00   2.2741493530981596E-01   3.3075632063269833E-01\n         2         79   7.1850738477417667E-04   1.4548280617918981E+00   2.1944671796296303E-01   3.5202777526540829E-01\n         2         80   1.0427512552816083E-03   1.4086743548515410E+00   1.9309838486762501E-01   3.3940731514493649E-01\n         2         81   1.5316505699911688E-04   3.9170739576143243E-01   2.1690928391021241E-02   3.5951638124914538E-02\n         2         82   2.3226248027929980E-03   4.0659992967230246E-01   5.3837090521652087E-02   4.0925587509594595E-02\n         2         83   2.5108500941182360E-02   1.4626692013948281E+00   2.6569996271015145E-01   1.3967026247132786E-01\n         2         84   5.7226401547664188E-02   3.2631936005913977E+00   6.5763555812799035E-01   5.5826011511479856E-01\n         2         85   4.2129399962387695E-02   2.9152985915898517E+00   5.5493710174127275E-01   5.5249689475335928E-01\n         2         86   4.5090529564537220E-02   2.7890934485354242E+00   4.7691611927976857E-01   5.3407108975361495E-01\n         2         87   1.4465090111904569E-02   9.0063376561065744E-01   1.0171767821188143E-01   7.7884524062057633E-02\n         2         88   5.0830647099082707E-02   8.8733804165813375E+00   2.1914102288604869E+00   1.1831643328625014E+00\n         2         89   3.3869582455722153E-01   3.0264786460839161E+01   7.7756892916172973E+00   3.8603874071781519E+00\n         2         90   6.6087247809897265E-01   4.8130300813065347E+01   1.2721739742585562E+01   6.1253997018409194E+00\n         2         91   3.3466931646599773E-01   3.3401951454076382E+01   8.9028581289087434E+00   4.2662149632188902E+00\n         2         92   3.0024409868720120E-01   2.9456666352094416E+01   8.1173663820764439E+00   3.8522240089987516E+00\n         2         93   5.2767254489325274E-02   1.0482800211221702E+01   3.2189580132889946E+00   1.4648654836794395E+00\n         2         94   3.1444988560374837E-02   1.1413580776284868E+00   2.4362092810468247E-01   1.1839705939806393E-01\n         2         95   2.0698560158538329E-01   3.4665426737029224E+00   9.2623735419833431E-01   3.5855841513650888E-01\n         2         96   4.0637266706254599E-01   6.6198826316005954E+00   1.7831167036130755E+00   8.8257798470134108E-01\n         2         97   3.1839051103845656E-01   5.3726652161096364E+00   1.3597339867698643E+00   7.7949643213847009E-01\n         2         98   3.0639613382632469E-01   5.1215237594393423E+00   1.1882858358499524E+00   7.4559261772624819E-01\n         2         99   1.1549620642267347E-01   1.6857587926847877E+00   3.6716516487330109E-01   1.4841820434101499E-01\n         2        100   2.6789219942925810E+00   3.8339377458539474E+01   1.6259928339346143E+01   4.4950598220973026E+00\n         2        101   1.1068050063581769E+01   1.1562319725612882E+02   5.0727869667887454E+01   1.3542522508471061E+01\n         2        102   1.7525521953978522E+01   1.7994323447293985E+02   8.1618074462960749E+01   2.1603256718203220E+01\n         2        103   1.2279762752268180E+01   1.2363741101986318E+02   5.6020958578498025E+01   1.4872386219588417E+01\n         2        104   1.1480014998190741E+01   1.1226536447066910E+02   5.1259605154295464E+01   1.3639594665514641E+01\n         2        105   4.2037313527534490E+00   4.4833915487648014E+01   1.9496208299720774E+01   5.2386898305042022E+00\n         2        106   1.8892447412261551E-01   2.5211605759340014E+00   7.6037211994682374E-01   2.5467250652753382E-01\n         2        107   7.3893874127555204E-01   7.1374664222614959E+00   2.5676320015809524E+00   7.4985259589550979E-01\n         2        108   1.5202185447952643E+00   1.2465541601305318E+01   4.4687202861875406E+00   1.4221861677200898E+00\n         2        109   1.1326061194023906E+00   9.5284562527869436E+00   3.2337410445843329E+00   1.1179219868688535E+00\n         2        110   1.0032115750903061E+00   9.0981278933293961E+00   2.8808470288700398E+00   1.0507534671367857E+00\n         2        111   4.4555901532250702E-01   3.1244373336343108E+00   1.0238754016729235E+00   2.7051246115752403E-01\n         2        112   1.6650150598674831E+01   1.0173905973731840E+02   4.7873484114725450E+01   9.9940626651734075E+00\n         2        113   5.0383861869528367E+01   2.8528848194660964E+02   1.3908452190325804E+02   2.8601210822034794E+01\n         2        114   8.2696087352995278E+01   4.5781301896385105E+02   2.2232667856802766E+02   4.5571136636998510E+01\n         2        115   5.7650365416382378E+01   3.1459116718713244E+02   1.5230491482671894E+02   3.1318202467614771E+01\n         2        116   5.2969556775412457E+01   2.8821730855230101E+02   1.3955756962744783E+02   2.8738095158631932E+01\n         2        117   1.9907302404473956E+01   1.0781830096039809E+02   5.3239548507381066E+01   1.1040189292647714E+01\n         2        118  -2.6916037117720294E-19   9.2580862216124441E-03   2.2460153187443795E-03   1.2661728624613949E-03\n         2        119   4.6375051425780368E-06   2.4119571350881327E-02   1.5523595541206026E-03   1.1070405857839076E-03\n         2        120   5.1812853190775508E-05   1.7748531988237190E-01   7.9473166531189271E-02   4.9545065282283751E-02\n         2        121   4.1346394860205331E-05   1.9745052245942549E-01   9.4292453455491754E-02   5.9224268795783484E-02\n         2        122   3.4337801702531530E-05   1.9806736923054635E-01   1.0053335972932777E-01   6.2833827684229793E-02\n         2        123   1.7533292044559839E-06   6.3038619994557621E-02   2.3744448869216027E-02   1.4454259189452864E-02\n         2        124   1.2127688322655566E-05   1.0952733275438213E-01   5.1414745858739827E-02   2.5396079495490081E-02\n         2        125   1.9089148981614097E-03   2.4457303823757143E-01   4.9030864381825183E-02   1.8654004601577855E-02\n         2        126   2.7085815149184695E-02   8.5222594527800288E-01   3.5869650694760968E-01   1.6866740994183033E-01\n         2        127   2.8050655073247287E-02   8.6916230512082193E-01   3.9170581631674301E-01   2.0134924679505281E-01\n         2        128   2.5671227290251810E-02   8.8613741685603920E-01   4.3592837480514485E-01   2.2536177028057267E-01\n         2        129   1.2856998140145805E-03   3.2745656407759960E-01   1.6113859855472645E-01   7.5600080406566919E-02\n         2        130   4.0389828086697241E-03   4.7170215268649945E-01   2.3892835434657475E-01   9.6688517913066901E-02\n         2        131   3.3391544214664122E-02   1.3089212826311087E+00   3.5821022271621628E-01   1.1460121428745927E-01\n         2        132   2.5410063817101891E-01   2.6120326565931973E+00   1.1090729919467739E+00   3.2219731959315739E-01\n         2        133   2.2446123646543592E-01   2.3574403282348722E+00   1.0342709262745253E+00   3.5059377257582863E-01\n         2        134   1.9475560428125821E-01   2.3566472926187121E+00   1.1385011214293543E+00   4.1357562447740182E-01\n         2        135   2.2613172995687776E-02   9.8508691353374933E-01   5.3972204989204453E-01   2.0319473652572673E-01\n         2        136   9.8070945502725471E-01   1.3428145649127558E+01   4.9442940391552428E+00   1.6530857166611226E+00\n         2        137   1.4502769436558918E+00   3.8089689785352434E+01   1.1496370756286733E+01   4.0843916453868001E+00\n         2        138   1.9324192978892187E+00   6.2540030143559051E+01   1.9666274894986337E+01   7.1755571559548610E+00\n         2        139   5.8719863749961287E-01   4.6714340847352155E+01   1.3982101009035850E+01   5.4064455057326226E+00\n         2        140   4.9152445312688148E-01   4.1232311942801580E+01   1.2754045636311758E+01   5.0214764727091490E+00\n         2        141   8.3744836068373033E-02   1.5603532699915776E+01   4.7469013368485378E+00   2.1845964104586808E+00\n         2        142   6.5442705702925819E-02   1.4566102822849432E+00   7.3478130834920696E-01   2.1835599904057587E-01\n         2        143   3.0059391209111858E-01   3.8659547014509372E+00   1.4235637437371764E+00   3.7825905710091057E-01\n         2        144   9.6087791864551897E-01   6.4650213541971411E+00   3.0809713957801668E+00   7.0490623610497816E-01\n         2        145   7.9922576625002206E-01   5.2700248273371209E+00   2.5083436077885772E+00   6.0463743293223815E-01\n         2        146   6.5809905645336941E-01   5.1027774769420651E+00   2.6026757001835161E+00   6.7039781983059910E-01\n         2        147   1.1233144290602627E-01   2.2206040611599973E+00   1.2598148061956222E+00   3.7896533797681742E-01\n         2        148   4.3230481940948344E+00   7.0527362342118792E+01   2.9133364830006762E+01   8.6431941827054093E+00\n         2        149   8.8690638079805684E+00   1.8835544771727226E+02   7.4553505702010838E+01   2.4007885714500706E+01\n         2        150   1.4186728052316663E+01   3.0027555182137047E+02   1.1932592535007872E+02   3.7378064687139634E+01\n         2        151   9.8473291753004482E+00   2.0529221141215254E+02   8.1581087900498702E+01   2.5323400437240377E+01\n         2        152   8.6013923692890852E+00   1.8696883396210535E+02   7.4700093136459941E+01   2.3267400575834280E+01\n         2        153   3.0267945120084914E+00   7.0256031210577675E+01   2.8442640219823065E+01   8.9678175847195156E+00\n         2        154   3.3921820722647394E-01   3.4494340795167728E+00   1.8651383842515223E+00   4.1409375040266427E-01\n         2        155   1.1308362939738343E+00   9.0586120688475606E+00   4.1093243710060587E+00   9.2010297640064076E-01\n         2        156   2.4937186536904199E+00   1.4408494521675427E+01   7.6216832461340127E+00   1.5537129120056046E+00\n         2        157   1.8721576360833032E+00   1.0555668014925683E+01   5.7202559583691190E+00   1.1682679544032026E+00\n         2        158   1.6458627990678911E+00   1.0384542991606466E+01   5.6221986286363785E+00   1.1627675185266153E+00\n         2        159   3.4386095236273007E-01   4.5380473956281380E+00   2.5543879882736387E+00   6.0656594988754975E-01\n         2        160   4.1285646328038140E+01   1.9176484393483648E+02   9.8506461623465142E+01   1.9147257944556802E+01\n         2        161   1.0069294284593688E+02   5.0694163473841928E+02   2.5577257934003188E+02   5.1102419456965308E+01\n         2        162   1.5811362639640694E+02   7.8133890751357444E+02   4.0586284169715537E+02   8.0288193892869586E+01\n         2        163   1.0749058870590703E+02   5.2326779530723729E+02   2.7734176120314254E+02   5.4889817972537216E+01\n         2        164   1.0114308350571523E+02   4.7348822137414777E+02   2.5434956378477432E+02   5.0404822554215613E+01\n         2        165   3.5661991395485849E+01   1.7796549450952944E+02   9.6929082027756110E+01   1.9343176705527547E+01\n         2        166  -2.5494001516139498E-16   1.3191113410235776E-03   8.7211985226169567E-06   2.9330027830678834E-05\n         2        167  -5.0492320490329704E-16   4.7190960019697678E-02   1.9584637866019382E-03   4.1673893800176290E-03\n         2        168  -4.6890670706039519E-16   2.5353743852281613E-01   2.4406535653061619E-02   5.7839361349603727E-02\n         2        169  -3.9914313530512123E-16   2.7860015625068940E-01   2.6018079482324149E-02   6.2301078488400399E-02\n         2        170  -3.5037369872061447E-16   2.7389830500202123E-01   2.4415305830307207E-02   5.9057974644057529E-02\n         2        171  -2.4212370771499073E-17   4.3971611639061756E-02   1.9701382689985480E-03   5.0753817151005772E-03\n         2        172  -3.7951168900475239E-16   2.3705357271273226E-02   1.3946123406273338E-03   2.6132855458290108E-03\n         2        173  -4.2823166277308245E-16   2.0082277451533773E-01   2.0258147539834390E-02   2.4218229032522715E-02\n         2        174  -1.0619951948429922E-15   8.3642135780920246E-01   1.1484294749667777E-01   2.1762227217975760E-01\n         2        175  -1.0799867219897119E-15   8.8589836338618666E-01   1.1483490786260576E-01   2.3289582387235064E-01\n         2        176  -1.0722427499520293E-15   8.5488039950137606E-01   1.0352249822342323E-01   2.2099329718350288E-01\n         2        177  -1.1138652422279678E-15   1.5360705071016442E-01   9.4758627543343101E-03   1.9694823126490943E-02\n         2        178   1.8779425161118000E-06   1.2832710702693523E-01   1.6429742024520102E-02   2.2230563749590360E-02\n         2        179   3.2530659628354226E-05   5.4690230560778719E-01   9.4065382349243540E-02   9.8471518500877736E-02\n         2        180   4.7282706403794731E-05   1.7654919467068066E+00   2.9590914465165019E-01   4.2618780278779311E-01\n         2        181   2.6929795424016122E-05   1.7422128241014432E+00   2.6684417451143932E-01   4.3589189921444615E-01\n         2        182   1.5127892865727845E-05   1.6298760214031724E+00   2.3305689850532724E-01   4.1059365568972883E-01\n         2        183   2.4578044718036309E-05   3.2899165816559606E-01   3.5057248105119225E-02   4.3482426206068792E-02\n         2        184   2.1053261780298541E-03   4.2296446568574941E+00   5.9915048093706413E-01   5.3032213225190028E-01\n         2        185   7.9892624457163879E-03   1.3198907761370378E+01   1.7748794733517530E+00   1.5104096300717225E+00\n         2        186   1.1195305506846987E-02   1.7848904272832684E+01   2.5866839403712412E+00   2.0989424222577631E+00\n         2        187   7.0204701397032819E-03   1.1183911132708301E+01   1.7015265236411035E+00   1.3912543461337250E+00\n         2        188   4.2848987784550796E-03   9.6096503742581429E+00   1.5438248414422429E+00   1.2608950331548801E+00\n         2        189   1.8788792085643415E-04   4.5318930016521612E+00   6.8955374425644667E-01   6.1790343662567848E-01\n         2        190   7.1837531547354957E-04   3.8461163480833827E-01   7.6681439430651477E-02   7.1999303095500747E-02\n         2        191   6.4193745075507586E-03   1.4673401952647176E+00   2.9190900274982429E-01   2.4675747957419247E-01\n         2        192   9.4917520835970364E-03   3.1421860172666460E+00   6.5014999381271987E-01   6.9301324738529635E-01\n         2        193   5.5999553680636926E-03   2.8813005806952585E+00   5.2833381871048368E-01   6.5483660707235591E-01\n         2        194   3.3162917921341082E-03   2.7056337504667578E+00   4.6046579326078563E-01   6.0839360397683739E-01\n         2        195   2.9185681179858133E-03   6.0764038222466132E-01   1.1065922133253923E-01   8.5983124783962486E-02\n         2        196   5.5750725530591873E-03   1.9533650104690750E+01   4.8378012102681405E+00   2.5493843877900573E+00\n         2        197   1.3311540467677723E-02   4.8614736657886205E+01   1.2560227908621535E+01   6.6420278018307304E+00\n         2        198   2.4679215226359994E-02   7.9078150739060291E+01   1.9735262534925202E+01   1.0386157618046196E+01\n         2        199   1.8285711755099816E-02   5.5967108800381382E+01   1.3500468950091134E+01   7.1829041347555407E+00\n         2        200   1.6579574901830593E-02   5.1136391912905083E+01   1.2358009605099134E+01   6.6127608672613691E+00\n         2        201   6.5361744164033125E-03   1.7272121821397366E+01   4.6999965491309323E+00   2.5901658611492357E+00\n         2        202   1.1859819088534880E-02   8.4263185144825103E-01   2.3535958221348796E-01   1.5484805009439165E-01\n         2        203   4.9875006725589165E-02   2.8862392352523853E+00   7.3959983229967674E-01   4.7073828886630198E-01\n         2        204   7.1408304468075362E-02   5.1435235114689926E+00   1.3749047213482537E+00   1.0441093030221296E+00\n         2        205   4.5001480022145317E-02   4.4647499147632663E+00   1.0349814951966048E+00   9.0779705128558208E-01\n         2        206   2.9884620214659593E-02   4.2345995990742695E+00   9.1279213319137653E-01   8.3288667328417876E-01\n         2        207   2.3972101177354252E-02   1.1329866889957134E+00   2.8387537762228865E-01   1.5468025619680381E-01\n         2        208   6.7352094942232577E-01   3.7917353861056107E+01   1.3765426176022839E+01   5.1173334089323470E+00\n         2        209   2.0410610743667830E+00   9.7119458200248346E+01   3.5842850256247829E+01   1.3204661741118706E+01\n         2        210   3.3440775865141199E+00   1.5526910183288726E+02   5.7081085013758702E+01   2.0867703128760215E+01\n         2        211   2.1070911846325218E+00   1.1246431739152105E+02   3.9119580313743185E+01   1.4348101223999732E+01\n         2        212   1.9727073207583001E+00   1.0287113799433520E+02   3.5822328696989068E+01   1.3148239756186769E+01\n         2        213   7.7793884597979368E-01   3.7518032047949376E+01   1.3566767554690344E+01   5.0189002964557359E+00\n         2        214  -3.1611591744313104E-18   2.2056098909780729E-03   4.6947952971885805E-04   2.3374964101878135E-04\n         2        215  -1.0836468369828224E-18   9.2726851101144359E-03   6.7306069354257977E-04   3.5386118373610583E-04\n         2        216  -4.1317068003547389E-19   5.0112489764702839E-02   2.3617701860949310E-02   1.0031253789803336E-02\n         2        217  -4.1427570345589064E-18   5.8760470577606673E-02   2.7952724872908653E-02   1.1820158922369409E-02\n         2        218  -2.9264837085136436E-18   6.0819748395247231E-02   2.9151294082052047E-02   1.2319390329209472E-02\n         2        219  -3.0359165229561437E-18   2.2830932352789605E-02   6.0671890698357515E-03   3.0563112119906064E-03\n         2        220   3.1272861234208321E-06   6.2059491453399770E-02   2.9678798187126081E-02   1.2377204906071934E-02\n         2        221   2.0837646955958633E-06   1.1617651124679668E-01   4.7873078710262876E-02   2.0438540858565363E-02\n         2        222   1.0616059304349316E-06   3.1419648540967104E-01   1.6814635147208035E-01   7.0165699492299158E-02\n         2        223  -4.1356853943372865E-17   3.1096013283847429E-01   1.6776465912998181E-01   7.0072906643880287E-02\n         2        224  -3.1946742444925609E-17   3.1382204345890169E-01   1.6383849352612664E-01   6.8730463212520729E-02\n         2        225  -1.6927353802655058E-17   1.0857527321843860E-01   3.2529288030837225E-02   1.6493719723398560E-02\n         2        226   1.6660244065637251E-03   2.8394731819011121E-01   1.6741379427368022E-01   6.4663274354430075E-02\n         2        227   7.8915524824049233E-04   6.1794816645082651E-01   3.0113612325124756E-01   1.2330058281885389E-01\n         2        228   7.9823062233508183E-04   1.1631727611906499E+00   5.7706457738598982E-01   2.4076785431459399E-01\n         2        229   2.5922923448270803E-05   9.7847589078595043E-01   4.6754197624287303E-01   1.9865681870449436E-01\n         2        230   2.0058596855900044E-05   9.0665471627350003E-01   4.2604627095348019E-01   1.8394709549203109E-01\n         2        231   6.2437800243708238E-07   2.9089618340254197E-01   8.8919439031294137E-02   5.0601563609109348E-02\n         2        232   7.7079742115885685E-01   9.0473657627876136E+00   2.2674103097451783E+00   5.8702452070091393E-01\n         2        233   4.4721523457695361E-01   1.8587954891339198E+01   4.0012467570551378E+00   1.6427625976033298E+00\n         2        234   2.8277451643140106E-01   3.1310238734454462E+01   5.7580859002880516E+00   3.0355577439983707E+00\n         2        235   1.3580201515896806E-02   2.4661372388061636E+01   3.7825838339684124E+00   2.4648382785376586E+00\n         2        236   1.1760818380188618E-02   2.3893712165959506E+01   3.4972842584072334E+00   2.3058011008154442E+00\n         2        237   7.7084417791727230E-04   8.9996282482473902E+00   1.4040037966835337E+00   1.0325873874153799E+00\n         2        238   2.5408913205892402E-02   7.5189499699853890E-01   4.5389016423937756E-01   1.5498917894180189E-01\n         2        239   2.0473272420916191E-02   1.8911248332620583E+00   9.0534256741111585E-01   3.5046052589766341E-01\n         2        240   1.6011879384216245E-02   3.4564266849491569E+00   1.4636129575090517E+00   5.8524410762642998E-01\n         2        241   5.0958251057742140E-03   2.6800786459126251E+00   1.0575775288103657E+00   4.3846262403515318E-01\n         2        242   4.7244390327035313E-03   2.4411187589296506E+00   9.3371889989219214E-01   3.9389532195405802E-01\n         2        243   5.7280450023139027E-04   8.2951219597558568E-01   2.3204759978797024E-01   1.2431949163344429E-01\n         2        244   3.3609695572096487E-01   3.7898945558389869E+01   1.1367913893629229E+01   5.6173149401910658E+00\n         2        245   8.5749397668855221E-01   9.8679527165150134E+01   2.6093924990307269E+01   1.3742178722062768E+01\n         2        246   1.2117975615710617E+00   1.5890852876767158E+02   4.2176535732828427E+01   2.3014397369461758E+01\n         2        247   7.0273013876132817E-01   1.1895263373318599E+02   2.9153235781036077E+01   1.6574912154056843E+01\n         2        248   5.2088890824658263E-01   1.0772670616336991E+02   2.6661192011530410E+01   1.5018652139159339E+01\n         2        249   1.0908088976950713E-01   4.5084676144696040E+01   1.0391495708695533E+01   5.7117082324682267E+00\n         2        250   1.3981767047961852E-01   1.7220955722607805E+00   9.4123114128735996E-01   2.6282080294708166E-01\n         2        251   1.1747358138581923E-01   4.7211753874395939E+00   2.0989431405988741E+00   7.2633145973865332E-01\n         2        252   1.4542957538689177E-01   7.9023952906147699E+00   3.3123215526630894E+00   1.1812072053624671E+00\n         2        253   8.1634908239566678E-02   5.9819307764573733E+00   2.3104342026624924E+00   8.6206811911344550E-01\n         2        254   7.8987695950721262E-02   5.5692101626010899E+00   2.0399244873836482E+00   7.6962136796785297E-01\n         2        255   1.6640872417570830E-02   1.8559774438035899E+00   6.0389206280834706E-01   2.6165825666554204E-01\n         2        256   9.4961741753695339E+00   1.0348699505241775E+02   4.2701870068768898E+01   1.2181004686602527E+01\n         2        257   2.4384491793901525E+01   2.6925397637082625E+02   1.1246284975530376E+02   3.4043823114387372E+01\n         2        258   3.7810277720014675E+01   4.4882766312306950E+02   1.8349316899713617E+02   5.5471449432586390E+01\n         2        259   2.5151721817638144E+01   3.1421842816432235E+02   1.2669793054701798E+02   3.8496728034129767E+01\n         2        260   2.3362284921735235E+01   2.9033789869451289E+02   1.1613261160860596E+02   3.5341857374692843E+01\n         2        261   8.7687791503824339E+00   1.1012695134413345E+02   4.4006005476250138E+01   1.3897284984640002E+01\n         2        262  -3.1467633334010568E-17   2.1752762245976251E-03   1.7632341351685765E-04   2.0034343438611862E-04\n         2        263  -2.4365028993261572E-16   1.6285630874639839E-02   1.8793114982012770E-04   3.6276892134350065E-04\n         2        264  -4.6799327022854813E-16   9.3335798245309409E-02   7.9574640891394051E-03   1.9420381434809363E-02\n         2        265  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3.5751949316787665E-03   9.5518141113724955E+00   1.2642145092130928E+00   1.1127503863911330E+00\n         2        282   5.7506851098996304E-03   1.9672137062737729E+01   2.0541939003091487E+00   1.9687322163974863E+00\n         2        283   8.6533122447899073E-04   1.7133679566153205E+01   1.4382688717842733E+00   1.5031217215477679E+00\n         2        284   4.3008475783315231E-04   1.5127524169114215E+01   1.2716957099109780E+00   1.3303734070413826E+00\n         2        285   2.1227139819237377E-05   3.4492741112399705E+00   4.0019609048987398E-01   4.2765115819995964E-01\n         2        286   3.5195494114410681E-03   3.9345290687925893E-01   1.3823554726455087E-01   8.5871965796480043E-02\n         2        287   6.0305302019842393E-03   1.1653004873608499E+00   1.9011576084038950E-01   1.2614160793042037E-01\n         2        288   9.4402262132682151E-03   2.4396809932670638E+00   3.7051210977902277E-01   3.3544117075298185E-01\n         2        289   6.1995471635940336E-04   2.1952483991429004E+00   2.9785460830070321E-01   3.5608759025685754E-01\n         2        290   1.8747282258845145E-04   2.1513925099168079E+00   3.2436543041669968E-01   4.0945405314962702E-01\n         2        291   1.1954703033539322E-05   8.6546777829228638E-01   1.7065666269504576E-01   2.2056581908247369E-01\n         2        292   3.6558396396751715E-03   1.5288771885562616E+01   3.8571592215806736E+00   2.1871992540176795E+00\n         2        293   7.3332787771524521E-03   3.5412942117497835E+01   8.6714236823477382E+00   5.3828885408820257E+00\n         2        294   1.1616198716055457E-02   5.6262206544632789E+01   1.4167383117828665E+01   8.6333815651762489E+00\n         2        295   7.8735368684923600E-03   3.8191156716683231E+01   9.8302936607056957E+00   6.0901652544315450E+00\n         2        296   7.4300367047902818E-03   3.5947973198495191E+01   9.0683690563614618E+00   5.5694061789781104E+00\n         2        297   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-3.3708089626330151E-16   2.9782387354410061E-03   2.3151841233235869E-06   3.1257020530487835E-05\n         2        314  -5.7880265206462675E-16   4.4083484478076335E-02   3.0406422883091795E-05   3.4931242369601610E-04\n         2        315  -7.0455864885675093E-16   4.7476581574526250E-02   5.8533174838151352E-05   4.5070514338632259E-04\n         2        316  -4.5238432670633027E-16   1.8435666709758856E-02   4.2777699356617614E-05   2.9945958228646397E-04\n         2        317  -4.4941472137828128E-16   1.3766066109439083E-02   3.8028865094466531E-05   2.6640766451936952E-04\n         2        318  -4.4694751728115652E-16   1.6071672926534226E-02   1.9744790852316184E-05   2.8624418642841568E-04\n         2        319  -7.2970594384551471E-16   1.7822859853681875E-02   7.7641908064885219E-05   4.6145683843864101E-04\n         2        320  -5.3817449719545877E-16   1.4312837068816836E-01   7.2520123637357335E-04   3.0184869731706282E-03\n         2        321  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-5.0860966963475577E-17   1.3160756695064355E+00   8.3616355639794998E-02   1.3292807620494870E-01\n         2        338   0.0000000000000000E+00   7.8691978338880677E+00   5.7662482340920973E-01   7.1764852296083048E-01\n         2        339   2.3453455905980648E-14   1.1455384440973058E+01   1.1192569578455807E+00   1.2383682438427153E+00\n         2        340   8.4890366668183127E-15   7.0048424115669299E+00   8.3886205993113994E-01   9.3981977066076394E-01\n         2        341   1.8991275722811086E-19   6.6738171321656354E+00   7.7170095356179647E-01   8.6271562124626144E-01\n         2        342  -6.1581396050981082E-17   2.5154724997554911E+00   2.9290661853497441E-01   3.7490881932016229E-01\n         2        343   2.3101059266481205E-09   1.0927269785432800E-01   3.2932791030088971E-03   7.1140489741605521E-03\n         2        344   4.5766528264904676E-07   4.0007924938567041E-01   2.0274053816216366E-02   3.1313560956805091E-02\n         2        345   3.2762375058363147E-06   4.4574271242392144E-01   3.7994746982204737E-02   4.8443395533813639E-02\n         2        346   6.1058460184347876E-07   3.9611457655606058E-01   2.8077730795575698E-02   3.9051832396318584E-02\n         2        347   3.7946929031186537E-07   3.9768740443138967E-01   2.4553736471770348E-02   3.5240865537623366E-02\n         2        348   3.8241716229917413E-10   2.8457932605077785E-01   7.6929239539755626E-03   1.8283585653414088E-02\n         2        349   1.5468106269497946E-04   2.8250037168447713E+00   4.5107531572993054E-01   3.9707013413177150E-01\n         2        350   4.4410632959344994E-03   1.3749415464622384E+01   2.0813030883174131E+00   1.5974849823717563E+00\n         2        351   7.1744039058201934E-03   2.1819611489098019E+01   3.5421506237218621E+00   2.6098473059341334E+00\n         2        352   3.5849897794546122E-03   1.4274740807670216E+01   2.4911785100260588E+00   1.8711102535810242E+00\n         2        353   1.1176598997939084E-03   1.3579035524114536E+01   2.2890239088280673E+00   1.7380821604486389E+00\n         2        354   5.2654191488935248E-04   5.6823115705057061E+00   8.8236899310203076E-01   7.3421931441370680E-01\n         3          1   1.3071805784346152E+01   2.0292545185734930E+01   1.6882995080852130E+01   1.0655105617538705E+00\n         3          2   9.9765182803656725E+00   1.7560579858924843E+01   1.4484567825681484E+01   1.1797448908414465E+00\n         3          3   3.7476842557531798E-01   2.6090888274816648E+00   1.3373709754077781E+00   4.0215480267492371E-01\n         3          4   1.5126067246240549E-04   2.7550210187201163E-02   3.6459622741447447E-03   1.7248700707970148E-03\n         3          5   1.2636270118342230E-02   1.3605526229044529E-01   4.9322707931687755E-02   1.1053425734565546E-02\n         3          6   1.2852495011622809E+00   3.4478051674971857E+00   2.0421218245597124E+00   2.6308509719664530E-01\n         3          7   2.6844470118134167E-01   7.7061374240528513E-01   4.4822562514170677E-01   6.0138313519205580E-02\n         3          8   8.5907494948304386E-01   2.0143380797867536E+00   1.2574463622629037E+00   1.5086332057374569E-01\n         3          9   4.0174643136744654E+00   1.1702045618775839E+01   7.4829211355894429E+00   1.1692841556424693E+00\n         3         10   1.6224391508642264E+00   3.6490789385172282E+00   2.3841886226868865E+00   2.7231309702587847E-01\n         3         11   8.0525240937710763E+00   2.2249511251116687E+01   1.4111911297843834E+01   1.8888983698976862E+00\n         3         12   2.6182582663943448E+00   5.5659977631632360E+00   3.8521601121212963E+00   4.0547179825898150E-01\n         3         13   1.7621821049113890E+01   3.6116925453747250E+01   2.5859975215545752E+01   2.6240606986096155E+00\n         3         14   6.6738792002968617E-02   2.3340198427840619E-01   1.4856604541708091E-01   1.5731824116049436E-02\n         3         15   2.1388203197881983E-01   4.8331760786918410E-01   3.5803509344519840E-01   2.5316165204275626E-02\n         3         16   2.1347838695794144E+00   3.3252267877502395E+00   2.4965182725105479E+00   6.9172244500539895E-02\n         3         17   6.8066426419693915E-01   1.0751910408613734E+00   9.0211258416842688E-01   3.8475301986136995E-02\n         3         18   1.2560561407334521E+00   2.2299869852652252E+00   1.5466827775940608E+00   7.0606383660737460E-02\n         3         19   2.7258785527295872E+00   1.1462901191852431E+01   4.4015862752750046E+00   9.6608245597430398E-01\n         3         20   1.9772721944513978E+00   3.8285087930341293E+00   2.3628463575112950E+00   1.6186380503817893E-01\n         3         21   5.9892726046351346E+00   2.0144669481911937E+01   1.3159180384775656E+01   2.1810696445725015E+00\n         3         22   2.7366189682309017E+00   5.6963601219005735E+00   3.4799569051924801E+00   2.9900359865039955E-01\n         3         23   8.9026830217410033E+00   3.2676933215829663E+01   2.3043806813393111E+01   3.2575812437062370E+00\n         3         24  -1.1102230246251565E-15   8.9223563447500265E-03   1.1549612772429045E-05   1.6931045422369725E-04\n         3         25  -6.6613381477509392E-16   4.3546728478400043E-01   4.4753574847651084E-03   2.0697979316350677E-02\n         3         26  -1.3322676295501878E-15   9.2288536393856591E-02   1.1079051889191390E-03   4.4409301446067086E-03\n         3         27  -8.8817841970012523E-16   2.3533591873927895E-01   1.0980682908189982E-02   2.1300307171736345E-02\n         3         28  -4.4408920985006262E-16   1.7438237393069875E+00   2.5904183049130436E-01   3.2533312783901674E-01\n         3         29   1.5393273211650182E-07   3.9647049069742457E-01   4.6690499249910575E-02   5.3433635875517770E-02\n         3         30   1.7242501299049584E-03   4.4156685596793146E+00   1.4939772563656339E+00   8.1626722999049550E-01\n         3         31   1.3245700538102589E-03   5.8061179101105664E-01   1.2747445461717799E-01   9.8284283325590860E-02\n         3         32   5.3974076879932553E-01   6.3031854720847633E+00   3.1010467049135180E+00   1.0188243130078107E+00\n         3         33   1.1998378252668456E+01   2.9782617734245719E+01   2.0324164918275613E+01   2.6555386556494094E+00\n         3         34   3.6498988811560167E+01   8.5709876281842753E+01   5.9879220506397068E+01   7.6924529633825927E+00\n         3         35   5.7040302227725014E+01   1.3728485940570729E+02   9.5477039909035227E+01   1.2178535272171521E+01\n         3         36   3.7877632199676150E+01   9.4020428970973498E+01   6.5158940729141563E+01   8.3317484866471805E+00\n         3         37   3.4593433498302126E+01   8.7190633442845495E+01   5.9888600235959153E+01   7.6140541024697654E+00\n         3         38   1.3243358826686876E+01   3.3820779400325165E+01   2.2999308504641828E+01   2.9481657312076992E+00\n         3         39   2.3799404912326175E+01   5.4497963892317031E+01   3.9497979195335510E+01   4.5370439666742071E+00\n         3         40   5.7069039366939506E+01   1.4167169063644508E+02   1.0326156995918699E+02   1.3041950150377611E+01\n         3         41   8.9902345366406564E+01   2.2502577311803583E+02   1.6583183461643370E+02   2.0971855778967758E+01\n         3         42   5.9229472569544640E+01   1.5389295692752950E+02   1.1411166844155764E+02   1.4581847544551712E+01\n         3         43   5.4478703731238809E+01   1.4049039994405581E+02   1.0445853543751677E+02   1.3446797845077077E+01\n         3         44   2.1332966547201284E+01   5.4059375919033535E+01   3.9835038671556617E+01   5.1252339810096599E+00\n         3         45   1.2183280050775258E+00   7.1586990151861309E+00   3.7922087812509950E+00   1.2583297340011041E+00\n         3         46   2.7638293784244419E+00   1.8528681250151791E+01   9.6201127251722145E+00   3.2167258339293343E+00\n         3         47   4.2558485772658292E+00   3.0013625355257965E+01   1.5271317720563930E+01   4.9870384818805613E+00\n         3         48   2.8796740697842402E+00   2.1147943562175119E+01   1.0466504487121538E+01   3.4079397793952597E+00\n         3         49   2.6350395380078231E+00   1.9172699461941583E+01   9.5855447233012931E+00   3.1160758564828925E+00\n         3         50   9.4114712482971596E-01   7.3808125392913357E+00   3.6387717483890083E+00   1.2261752109985002E+00\n         3         51   9.8531275909188061E+00   2.5232981942809349E+01   1.6924187453577563E+01   2.3087628947089467E+00\n         3         52   1.8706907071227395E+01   6.1715521394906879E+01   4.0809134513040028E+01   6.9741292912831980E+00\n         3         53   3.0379205806778106E+01   1.0077309032477089E+02   6.8817988099368563E+01   1.1586408527436728E+01\n         3         54   2.1202627613019523E+01   7.4778215381282990E+01   4.8864270388588309E+01   8.6275808506486129E+00\n         3         55   1.9639999406553802E+01   6.9556051062131971E+01   4.4869916842590754E+01   7.8785036055707751E+00\n         3         56   6.2516111720199801E+00   2.5448825093753566E+01   1.6226459170983510E+01   3.0131797706373757E+00\n         3         57   9.1748290242091202E-01   6.6003753745611604E+00   2.9577741623998541E+00   9.5085938315072149E-01\n         3         58   2.6322197472080533E+00   1.7053111649859407E+01   8.0772641797987781E+00   2.7385799851448245E+00\n         3         59   3.8770419901281827E+00   2.6750506890358032E+01   1.3319048186016174E+01   4.4193935174549157E+00\n         3         60   2.4963999751771611E+00   1.8854778991897319E+01   9.2783280329862432E+00   3.1306936463872330E+00\n         3         61   2.3131423137043621E+00   1.7432155237681158E+01   8.5072474676779244E+00   2.8205235306972538E+00\n         3         62   9.3702893634815843E-01   6.5425088879665285E+00   3.1563445647390465E+00   1.0499149857157808E+00\n         3         63   1.0777023267829946E-03   2.1477867906145987E-01   5.5646380197854867E-02   4.0250894604743445E-02\n         3         64   1.9769790040215094E-02   1.2005711079226877E+00   2.9060038277536065E-01   2.0152737490504527E-01\n         3         65   4.3117189119923578E-02   2.2527600696158259E+00   5.3724628295453558E-01   3.5345294595452703E-01\n         3         66   2.9335696785015453E-02   1.6422502419640881E+00   3.9541072850471815E-01   2.7095036692311958E-01\n         3         67   2.7795378566643630E-02   1.5144256898213833E+00   3.6788926063195937E-01   2.5753904698896884E-01\n         3         68   4.7565343064947477E-03   7.0277076908358482E-01   1.4622739076932878E-01   1.1450510720452380E-01\n         3         69   3.9367032823867001E-05   3.6504818200479550E-03   7.1153664842585459E-04   2.9082789274275197E-04\n         3         70   3.5374341056771194E-05   4.6272990317393382E-03   5.6536157755917823E-04   3.4460959640911194E-04\n         3         71   1.8563513233959969E-07   3.3005973577681109E-03   1.1712337000889910E-04   2.3481062833764150E-04\n         3         72   1.5967330065250938E-07   3.4123239310143699E-03   1.1500106204227826E-04   2.2066166850347445E-04\n         3         73   6.5739753614947940E-08   1.6999056425241730E-03   5.1354081580895227E-05   8.5849400121204369E-05\n         3         74   5.5710246390615111E-03   4.1824892048856262E-02   1.6589399245100729E-02   2.5327417132429975E-03\n         3         75   1.4567077230449388E-02   1.2859960848022389E-01   5.0853144177989647E-02   1.2060089895468739E-02\n         3         76   1.7053769524795641E-02   1.8297247766002042E-01   5.2108859364447535E-02   1.9191228508818273E-02\n         3         77   2.4388647783237416E-03   1.1552581208076082E-01   2.1705268426303180E-02   1.4216487439468869E-02\n         3         78   3.0678679934307380E-03   1.1601393700887204E-01   2.1797243317817835E-02   1.3172897863250129E-02\n         3         79   3.0250992387144675E-04   5.0942029356123582E-02   1.0655334332601223E-02   6.0087886843150909E-03\n         3         80   5.7962833762863639E-02   2.5160972786221658E-01   1.0807654034344534E-01   1.7429458513088848E-02\n         3         81   1.5772216907628978E-01   8.4106202021993548E-01   3.6254701521284405E-01   8.1462236469850263E-02\n         3         82   1.8199222882333566E-01   1.2567666004936675E+00   4.5119570722177088E-01   1.3957316742960646E-01\n         3         83   5.0315220179236002E-02   8.6274169681156043E-01   2.4482421708730093E-01   1.0358595506238299E-01\n         3         84   7.2558646940725280E-02   8.6449094891986089E-01   2.3940314014817637E-01   9.4308892188051482E-02\n         3         85   5.8878027670777400E-03   3.5786570232309106E-01   1.0808404237052797E-01   4.1260825785928081E-02\n         3         86   6.4340139804662233E-01   8.9801104930092830E+00   2.8934962906308015E+00   1.0680953424295163E+00\n         3         87   2.3176190203817879E+00   2.8864688746615432E+01   1.1105631781889178E+01   3.7692432131691498E+00\n         3         88   4.3873152279477212E+00   4.4924535866888874E+01   1.8282999671620274E+01   6.0567909114308041E+00\n         3         89   2.9446638588375733E+00   3.2105607597588033E+01   1.2583846227674638E+01   4.2038747026842325E+00\n         3         90   2.9122062026409505E+00   2.9907581807462059E+01   1.1794840941195568E+01   3.8166715473615591E+00\n         3         91   5.8069976930128886E-01   1.1122689432135465E+01   4.6388661658990396E+00   1.4791826676933133E+00\n         3         92   1.8337961768192226E-01   8.0775030648697776E-01   3.5868925058912476E-01   6.9994707558929295E-02\n         3         93   5.3548539752919699E-01   2.7081313006654724E+00   1.2383805728966606E+00   2.8048787480273768E-01\n         3         94   7.1314796646991219E-01   4.1745549568637372E+00   1.7297798213450100E+00   4.7060646281128798E-01\n         3         95   3.1407390046052513E-01   2.9233299751898545E+00   1.0526602513197316E+00   3.4046481852505250E-01\n         3         96   3.4616342685507850E-01   2.8780546114124519E+00   1.0065197517610662E+00   3.0856065137705918E-01\n         3         97   4.8564120798129988E-02   1.1550363773206707E+00   4.2603371470398982E-01   1.2773077449038175E-01\n         3         98   3.8918550718611931E+00   3.3162642248295846E+01   1.3121481657216268E+01   3.6607822921407789E+00\n         3         99   1.2318690854382888E+01   1.0283170026060917E+02   4.1550939264614094E+01   1.1275093856631470E+01\n         3        100   2.0576068092032660E+01   1.6635381526136260E+02   6.7113956232172910E+01   1.8076639269107872E+01\n         3        101   1.4700359535260906E+01   1.1492909468963249E+02   4.6121053897673832E+01   1.2465631635176408E+01\n         3        102   1.3144717464854210E+01   1.0581370500353039E+02   4.2241557972809332E+01   1.1443414413294438E+01\n         3        103   4.9016935275761968E+00   3.9231078817365393E+01   1.6036332722087874E+01   4.4286394787557875E+00\n         3        104   4.7530900595918685E-01   1.9796668046899009E+00   9.3929084069675028E-01   1.9128514733374027E-01\n         3        105   1.2932639819348752E+00   6.3357608693574754E+00   3.1559844799065861E+00   6.7739371916514035E-01\n         3        106   1.9392641367260108E+00   9.9530583911043973E+00   4.7062187045181840E+00   1.1077329074173845E+00\n         3        107   1.1829125784279741E+00   6.9701786973659710E+00   3.0330768767501683E+00   7.8266913313933606E-01\n         3        108   1.1354145648192375E+00   6.7083075884741694E+00   2.8535828553866516E+00   7.0971962600787197E-01\n         3        109   2.3781394446602153E-01   2.6368513557574369E+00   1.1585161834191700E+00   2.8341300238744133E-01\n         3        110   2.2087210350635331E+01   9.6364923722368374E+01   4.8523078908917320E+01   1.0042992733783597E+01\n         3        111   6.4860150765213760E+01   2.7495440985458436E+02   1.4150506714631365E+02   2.8904617024969394E+01\n         3        112   1.0331499312183557E+02   4.3614358251925273E+02   2.2578201716335553E+02   4.6326143486596813E+01\n         3        113   7.0279968258143356E+01   2.9675351653885537E+02   1.5450651565524291E+02   3.1946765240437259E+01\n         3        114   6.4518026872682924E+01   2.7252962633390803E+02   1.4149277451816087E+02   2.9327180959503828E+01\n         3        115   2.4744531394138598E+01   1.0470779291799020E+02   5.4031635010324067E+01   1.1192700896519089E+01\n         3        116   6.2653640370759580E-04   1.7231546925243067E-02   5.8283368471957857E-03   1.4112126338704683E-03\n         3        117   8.5356164387468151E-04   2.4108911161528974E-02   5.5236556660806756E-03   1.6541297790929237E-03\n         3        118   2.1322127150788187E-03   3.6146691961077997E-02   8.8330834793400696E-03   2.7559267232903123E-03\n         3        119   1.6755388566639614E-03   3.7059156947251190E-02   7.0000824941341732E-03   2.4780211220025053E-03\n         3        120   1.8067877084444618E-03   3.6891139402244533E-02   7.2612812068355058E-03   2.4988818658075742E-03\n         3        121   2.7955531655141102E-04   1.3988422960301301E-02   3.0962204850476334E-03   1.3357627262048683E-03\n         3        122   4.6718149149442077E-02   1.8571788615868406E-01   1.1390595306603495E-01   1.2483455580519304E-02\n         3        123   5.6128722660603952E-02   2.9690097161389906E-01   1.3821691045850409E-01   2.4861039831718740E-02\n         3        124   1.0800618996201514E-01   5.3643044780924243E-01   2.2095980994699188E-01   4.4765906644182299E-02\n         3        125   7.8769693952300185E-02   4.4386643511727453E-01   1.6664715711068864E-01   3.9243173308709696E-02\n         3        126   7.5336187668895008E-02   4.0958468712635449E-01   1.6589847892139664E-01   3.7680813092072600E-02\n         3        127   1.1766527944291947E-02   1.6843591399025812E-01   7.0279481486079390E-02   2.0737784960339387E-02\n         3        128   2.8019592583653202E-01   6.3417325807172631E-01   4.4820767498535163E-01   3.1887074040955442E-02\n         3        129   3.2524512178621351E-01   1.4863048805800940E+00   7.0591085215065263E-01   1.1642113569954066E-01\n         3        130   6.1018914686401760E-01   2.4631742404973425E+00   1.1581771810114583E+00   2.1848009271387273E-01\n         3        131   4.5284824600463297E-01   1.9399179106010593E+00   8.5416076794164264E-01   1.8556877330835489E-01\n         3        132   3.7356266229242585E-01   1.7816109168170611E+00   8.2172552077541750E-01   1.7297915197321645E-01\n         3        133   6.2626975433098600E-02   6.6915137255842860E-01   3.4321774781194209E-01   8.5520741119141735E-02\n         3        134   2.1469295573562519E+00   1.4465415836392973E+01   5.1645199318702044E+00   1.4903576759670680E+00\n         3        135   3.8412181566448602E+00   4.5141035558109920E+01   1.3333939239524824E+01   4.2948891700850922E+00\n         3        136   6.7424262239501287E+00   7.4299371488025088E+01   2.2800202201850258E+01   7.2246469317123667E+00\n         3        137   5.1491423943959020E+00   5.1221531785172701E+01   1.6390403274785612E+01   5.2501468391851205E+00\n         3        138   4.4907944420124171E+00   4.4930284520215800E+01   1.4558905851676295E+01   4.8151125188427990E+00\n         3        139   1.0178864457726391E+00   1.5135589932805027E+01   5.3859768861699102E+00   1.8638722600424229E+00\n         3        140   8.0432728962985267E-01   1.7102513600202309E+00   1.0867779516132654E+00   9.0280814459307343E-02\n         3        141   9.6159265250432402E-01   4.8103827489353597E+00   2.1348913197495452E+00   3.6425921602128264E-01\n         3        142   1.7084417649305643E+00   7.4092811785119199E+00   3.5773961611243701E+00   6.6398249698545064E-01\n         3        143   1.3457269141321282E+00   5.1109992882397410E+00   2.6078501736896826E+00   5.3456356810942707E-01\n         3        144   1.0813000530584298E+00   4.6227388430668013E+00   2.4471347361699252E+00   4.9413783346142831E-01\n         3        145   2.2403726420577816E-01   1.7447071498035776E+00   9.8872357615456163E-01   2.1741728803391941E-01\n         3        146   1.1807594579584499E+01   6.1707123163009790E+01   3.1383226534353181E+01   7.1445351823063161E+00\n         3        147   2.4328500097255578E+01   1.6691981592255513E+02   7.9474239288725528E+01   1.9929100380852447E+01\n         3        148   3.4757038661686614E+01   2.6545455495746040E+02   1.2596440893565148E+02   3.1646233296290106E+01\n         3        149   2.1658989992534266E+01   1.8060632495368864E+02   8.5573280694602204E+01   2.1843160095999284E+01\n         3        150   1.9055198918632943E+01   1.6462924230387929E+02   7.8355482333199177E+01   2.0231713976013076E+01\n         3        151   6.8708333676079301E+00   6.5091803763614749E+01   2.9913972184408298E+01   7.9726323568214230E+00\n         3        152   1.6145334411406786E+00   3.8494651243030158E+00   2.3095565245620300E+00   2.5120473731385340E-01\n         3        153   2.4393247239995914E+00   1.1470868457962494E+01   5.2747729006052362E+00   8.9945436945399904E-01\n         3        154   4.2323202068494039E+00   1.8084866993175154E+01   8.8393759987557541E+00   1.5734112662360822E+00\n         3        155   3.0452753320770238E+00   1.2225283352972905E+01   6.3485827551911003E+00   1.2023612538364594E+00\n         3        156   2.6856263095546620E+00   1.0862615450252264E+01   5.8731455895047713E+00   1.1085527988499051E+00\n         3        157   6.9676721221208693E-01   3.8118017346494879E+00   2.3081357705259582E+00   4.5499790961181685E-01\n         3        158   3.9258146106068743E+01   1.6301144587542407E+02   9.7381905377217052E+01   1.7543009662125730E+01\n         3        159   9.2272239680418508E+01   4.1958807740895338E+02   2.5432093358186776E+02   4.6490336991228808E+01\n         3        160   1.3747233932343283E+02   6.5526182731209406E+02   4.0304658632233645E+02   7.3386147880135411E+01\n         3        161   8.9700517942741328E+01   4.4475332791432965E+02   2.7517465236137940E+02   5.0412563093232343E+01\n         3        162   8.1549925458314590E+01   4.0827712775089412E+02   2.5210856549934530E+02   4.6203983875104207E+01\n         3        163   3.3167556682665200E+01   1.5124871606629199E+02   9.6141546561292472E+01   1.7759614163649346E+01\n         3        164  -3.0775128425780430E-16   2.8956424726662368E-03   3.5229061710285188E-05   1.5427872911675736E-04\n         3        165  -3.9072364875383973E-16   1.8042551476390313E-02   2.0806517516575344E-04   8.7943770536477337E-04\n         3        166  -5.1781002647680079E-16   3.6727300885709586E-02   4.0199864462331955E-04   1.7251741594422618E-03\n         3        167  -4.3664583668461169E-16   3.0272036535488420E-02   3.0266042639421882E-04   1.3495987793993602E-03\n         3        168  -3.8578029218908534E-16   3.1440002708932373E-02   2.7068903633678868E-04   1.2194041372432149E-03\n         3        169  -2.2479901181416147E-16   1.1244266222617670E-02   7.6648565423891127E-05   3.8713002063569808E-04\n         3        170  -1.4326086843391004E-16   2.6911199389970938E-02   1.3922287829500099E-03   2.6901380455535409E-03\n         3        171  -1.8296564768592388E-16   1.4603024788637203E-01   5.9258162493008842E-03   1.2284061549278056E-02\n         3        172  -5.7662357137685567E-16   2.8007681985104566E-01   1.0442429212224697E-02   2.1663433325926625E-02\n         3        173  -5.5345559259688319E-16   2.0146782528604656E-01   7.5483793531863621E-03   1.6036214088098071E-02\n         3        174  -6.0198832920155626E-16   1.9466575797780675E-01   6.7849842569831622E-03   1.4482491519691176E-02\n         3        175  -3.7610845661031404E-16   7.2984212150041639E-02   2.1555688092182918E-03   5.1331258805085165E-03\n         3        176  -1.7588106345638890E-16   1.8283865021624053E+00   2.8566920344244656E-01   3.6639836554102817E-01\n         3        177  -1.3755864713011917E-15   6.3030903945064658E+00   8.6093702792754323E-01   1.1453277571424232E+00\n         3        178  -2.7901483901096170E-15   8.8125192582114007E+00   1.3397234537478397E+00   1.7343720637661202E+00\n         3        179  -2.1427450086068749E-15   6.1808673375181558E+00   9.1429196918765510E-01   1.1807664253900949E+00\n         3        180  -1.9335190688632992E-15   5.6527689334842552E+00   8.3553571030109364E-01   1.0724071369097863E+00\n         3        181  -5.0355366094046538E-16   2.1904784304648879E+00   3.1566483867754741E-01   4.2357602648982401E-01\n         3        182   5.8635704865177738E-08   1.1428530712795956E-01   1.4608589329276764E-02   1.6094775343114594E-02\n         3        183   1.8401866271028754E-07   4.7509632356779957E-01   4.8182740920951823E-02   5.9207821191203200E-02\n         3        184   2.8676164401796794E-07   8.7289504058207112E-01   8.0297919022305653E-02   9.7792663719474163E-02\n         3        185   1.9876080547958574E-07   6.2413461133170378E-01   5.6663485798587432E-02   7.0010145600832588E-02\n         3        186   1.6089532570922378E-07   5.6455151072807752E-01   5.1254967219483354E-02   6.3206402445097065E-02\n         3        187   3.8275108362551878E-08   2.2243267177574483E-01   1.7586913066705644E-02   2.3495545307587063E-02\n         3        188   4.0059887200286498E-03   1.0236957837544802E+01   3.5690489254071074E+00   2.0452926304181465E+00\n         3        189   1.0753265902465309E-02   2.5838382671009317E+01   9.0447690138210142E+00   5.2527636101021367E+00\n         3        190   1.7956633874559886E-02   4.1243556678903104E+01   1.4239458782769777E+01   8.1167474101856687E+00\n         3        191   1.2751047908716813E-02   2.8218687738346603E+01   9.7363077230281974E+00   5.5598674222623492E+00\n         3        192   1.1975102897218932E-02   2.5865268156845794E+01   8.9044550911709326E+00   5.0792840085598669E+00\n         3        193   5.2352497324445876E-03   9.4353553756823079E+00   3.3605600381049401E+00   1.9767743893744687E+00\n         3        194   8.7415756718665482E-04   3.1339491522301716E-01   7.4291738102471763E-02   5.6925192193623880E-02\n         3        195   2.1900802052770194E-03   1.0940024998703981E+00   2.1261358846198328E-01   1.7722647253021684E-01\n         3        196   3.6643202926095356E-03   1.9502353022483079E+00   3.4401220340994471E-01   2.8144828321486626E-01\n         3        197   2.6119808680144184E-03   1.3937363933099616E+00   2.3923301131571278E-01   1.9707766135232818E-01\n         3        198   2.3152207456855443E-03   1.2786661396761010E+00   2.1744133873836791E-01   1.7819511369961477E-01\n         3        199   4.0438427525894203E-04   4.8736348400465651E-01   7.8279272780132539E-02   6.8113354104469490E-02\n         3        200   2.5750747459732879E+00   2.7222273248034387E+01   1.2971739295751840E+01   4.6059116472185071E+00\n         3        201   5.8073869523123429E+00   6.9995730686027258E+01   3.3998816998704925E+01   1.1798590009309669E+01\n         3        202   9.2157559927294379E+00   1.1274089624906352E+02   5.4169446485663450E+01   1.8552186714793091E+01\n         3        203   6.1698128080850916E+00   7.8685071088231780E+01   3.7118450335570586E+01   1.2703402554364880E+01\n         3        204   5.6683759096458646E+00   7.2639712321633496E+01   3.3980544477347138E+01   1.1602323154100564E+01\n         3        205   2.6031912084080138E+00   2.7779751176706601E+01   1.2867989995398050E+01   4.4617877583934122E+00\n         3        206   3.2697131996451545E-05   2.6378276538800037E-03   6.7199829704598843E-04   2.2578482400275208E-04\n         3        207   7.5631858497720539E-05   1.2423570669886310E-02   9.7408366099742166E-04   8.2147049614567579E-04\n         3        208   8.1276842664877082E-03   5.2542930521788933E-02   2.6282028986897275E-02   4.2371958517669495E-03\n         3        209   8.3328580041482393E-03   5.6425729576885346E-02   3.0187847634923274E-02   4.4770182093267254E-03\n         3        210   1.0168729245279813E-02   5.7356930602515156E-02   3.1040826871205688E-02   4.6039201596387216E-03\n         3        211   3.0094814396890681E-05   2.7473117717514567E-02   5.6956064348821127E-03   3.0318129709524214E-03\n         3        212   1.0734824259029446E-02   6.2215165812276686E-02   3.3101700409816338E-02   4.4304701397625407E-03\n         3        213   1.0505702600875050E-02   1.1034398994909959E-01   3.4042882476841702E-02   8.2545899269826535E-03\n         3        214   7.4334358987337798E-02   3.3892182844030316E-01   1.7107270941307193E-01   2.1153723338952258E-02\n         3        215   6.5336809191059692E-02   3.0616112167973802E-01   1.7949981904397858E-01   1.8792500948255467E-02\n         3        216   9.1674926734591475E-02   2.7424225285848014E-01   1.8428283055843894E-01   1.7083335977145838E-02\n         3        217   1.9472092929856511E-04   1.5332777121438462E-01   4.1329043682018118E-02   1.8830865254551545E-02\n         3        218   8.8963265326237106E-02   2.5935177232330331E-01   1.6947239367085193E-01   1.4177438348010630E-02\n         3        219   8.8164679614018748E-02   6.8780824100878546E-01   1.9365699840772663E-01   3.8665333014925238E-02\n         3        220   2.7095883608694787E-01   1.5814175661300145E+00   5.3908214334681714E-01   8.4198609754666170E-02\n         3        221   2.2527456067220775E-01   1.3142139609533054E+00   5.0450040550697484E-01   7.7554644247827889E-02\n         3        222   2.6589593700839820E-01   1.1861531389950548E+00   5.0933789678874264E-01   6.9857234133993681E-02\n         3        223   1.7983369992475720E-03   3.8372011353875746E-01   1.3430301932554639E-01   5.1484940656047869E-02\n         3        224   1.1059019335103148E+00   9.8659764129996610E+00   1.9203233395248871E+00   7.4961112365738258E-01\n         3        225   1.4847361337204208E+00   2.2269553414967596E+01   3.7860037370042736E+00   1.6584091736313731E+00\n         3        226   1.3727897115817029E+00   4.0062753135945080E+01   5.6760407779255049E+00   3.1141414996150591E+00\n         3        227   3.1978964321447484E-01   3.0245578989153671E+01   3.6907803132083012E+00   2.5331790041762527E+00\n         3        228   2.4638460017603631E-01   2.9413248309849802E+01   3.3383703324655025E+00   2.3513897897640454E+00\n         3        229   2.9630136327664904E-02   1.1581039868541124E+01   1.1322731009332287E+00   9.0241420778106618E-01\n         3        230   3.1764591970994005E-01   8.9997249884563890E-01   4.8699086931297042E-01   3.7415935307412523E-02\n         3        231   3.1975532077832947E-01   2.2818553099967582E+00   6.4021767642270777E-01   1.3941542767636569E-01\n         3        232   7.3867957175300869E-01   4.7485625680297474E+00   1.3977138938709239E+00   2.9874473868411566E-01\n         3        233   5.4031884326134050E-01   3.8048229752764842E+00   1.1889042895373070E+00   2.6858418539254403E-01\n         3        234   5.8228542693342600E-01   3.5067053344009222E+00   1.1672353368073323E+00   2.4677834680067995E-01\n         3        235   3.2096214464731807E-02   9.3087719914818812E-01   3.3980000757332657E-01   1.1340581398017179E-01\n         3        236   3.4938935211865116E+00   3.0695240526639942E+01   1.3886065855839069E+01   4.4675185710920697E+00\n         3        237   6.4231524118637209E+00   7.9262009806797082E+01   3.3328315084147142E+01   1.1081081101232297E+01\n         3        238   1.0923137383219416E+01   1.3592262308209916E+02   5.6436610143560515E+01   1.8700321773412504E+01\n         3        239   6.3184712502113891E+00   1.0069516826110501E+02   4.0136544450107124E+01   1.3796393965570324E+01\n         3        240   5.3191611255827569E+00   9.1029183169967141E+01   3.6573861568744547E+01   1.2666050765260943E+01\n         3        241   1.2759090358542184E+00   3.2270527431922787E+01   1.3613613344904712E+01   5.2217132501491426E+00\n         3        242   8.0519136118659684E-01   2.2102940351105644E+00   1.1183590113685711E+00   1.0756544391484510E-01\n         3        243   8.3087850509451056E-01   5.2842849897717903E+00   1.7275496320649586E+00   3.9042824061406040E-01\n         3        244   1.7305295302897865E+00   1.0466454757896404E+01   3.3526145880551796E+00   7.8557123086721481E-01\n         3        245   1.3068624685786863E+00   8.2259926114154940E+00   2.6596638964419168E+00   6.7861373482783616E-01\n         3        246   1.2870353484677513E+00   7.7015843195954989E+00   2.5425187491159140E+00   6.2401626811390032E-01\n         3        247   1.7631198952733065E-01   2.3263502049460589E+00   7.9376489248038495E-01   2.4283433799790308E-01\n         3        248   9.0867824001203648E+00   8.0485956467869158E+01   4.2738291334737788E+01   1.0912391194019976E+01\n         3        249   1.8169908871521159E+01   2.1012862175095657E+02   1.0968486366895851E+02   2.9792359092096333E+01\n         3        250   2.2489794881396243E+01   3.5420108028233875E+02   1.7729477415271691E+02   4.9158689042876702E+01\n         3        251   1.2480196535139823E+01   2.5029610471446395E+02   1.2177726508141885E+02   3.4704954826044847E+01\n         3        252   1.1411346250800655E+01   2.3088200105996626E+02   1.1156380011427476E+02   3.2229221614494399E+01\n         3        253   5.7217542683103071E+00   8.6396315464252567E+01   4.2294910688687096E+01   1.3103287123206963E+01\n         3        254  -3.2773975569480938E-16   2.1447442200417132E-03   1.0119828147132442E-06   2.7423897154973828E-05\n         3        255  -3.6047495463912627E-16   3.0341677286782232E-03   3.5752709665374702E-06   5.4269337774467655E-05\n         3        256  -4.0270793892653777E-16   2.6483406784484184E-03   3.3794536693802627E-06   4.5759647026655676E-05\n         3        257  -4.2628941742518535E-16   2.2685322379359693E-03   3.0820218208106951E-06   3.9708758775674887E-05\n         3        258  -4.2873373632860711E-16   9.1003512280071440E-03   1.4897794248356281E-05   1.5250500610672663E-04\n         3        259  -1.1261745032298863E-15   5.8554793387908699E-02   2.5976942910112093E-04   1.3385083029844732E-03\n         3        260  -1.0083299962301777E-15   7.9578826052966165E-02   8.2327100123485758E-04   3.4690548888292481E-03\n         3        261  -1.1144931298590368E-15   6.9518999450832064E-02   7.5498463529483800E-04   3.2606637998928759E-03\n         3        262  -1.1634058081514093E-15   5.9759895625134757E-02   6.9583757683056805E-04   3.0451048181020252E-03\n         3        263  -2.9494688965407553E-16   1.2465857385767573E-02   1.7580610849245954E-04   7.7787529677283865E-04\n         3        264  -1.2477728111140212E-16   6.8436227755417495E-02   6.9700832561874382E-04   1.9137407189687510E-03\n         3        265  -3.9107201835958415E-16   2.8303081472611008E-01   5.2069746301960703E-03   1.1500093943178538E-02\n         3        266  -9.8485775570098949E-16   4.0113097805309528E-01   1.3439217996183658E-02   2.7621741281772763E-02\n         3        267  -8.4920795071881915E-16   3.1514167535087390E-01   1.1538340076691883E-02   2.5235009957941212E-02\n         3        268  -8.4323739566359950E-16   2.7468102831367447E-01   1.0605302531582927E-02   2.3563937221349709E-02\n         3        269  -3.2247164227979080E-16   7.3043620665020265E-02   3.1244687513743920E-03   7.2272344360553411E-03\n         3        270  -1.1823417791772494E-16   2.4247287087898184E+00   1.9392270959300970E-01   3.2820213967424283E-01\n         3        271  -5.4323712488909992E-16   5.3532211878454978E+00   4.2858229330890346E-01   6.1376242798427783E-01\n         3        272  -1.0844860785944083E-15   7.9386919100731141E+00   7.9253161356007051E-01   1.0503593720128770E+00\n         3        273  -8.6018042226012912E-16   5.2499651400177028E+00   5.9950827478080260E-01   8.2042352813123798E-01\n         3        274  -8.6458881926565691E-16   5.1408617680688451E+00   5.5638387205207984E-01   7.6867031119897877E-01\n         3        275  -8.7711231321440461E-16   2.1400405707354153E+00   2.0214426027202781E-01   3.2961328939677464E-01\n         3        276   4.4479365240249114E-08   2.1086008503487477E-01   8.5256964659873903E-03   1.1415405771673940E-02\n         3        277   2.4812051655587384E-07   7.5239192273064748E-01   3.8593414492823566E-02   4.7503414760012429E-02\n         3        278   3.0953429801891321E-07   1.1225745740607909E+00   8.4109702548192875E-02   1.0231345944226115E-01\n         3        279   1.6192460228885639E-07   8.2715009604378142E-01   6.7630259191043124E-02   8.9625775407566735E-02\n         3        280   1.0318591479768654E-07   7.3172722273513202E-01   6.1871785006430105E-02   8.2981361229504669E-02\n         3        281   8.1582984547041242E-09   2.1856535256040238E-01   1.9495438983860466E-02   2.7808680165757528E-02\n         3        282   4.5629679558248865E-03   1.2026740730782761E+01   3.5100487367055351E+00   2.0939166464846566E+00\n         3        283   1.2604526050270057E-02   3.0576168345064108E+01   8.1000483182910745E+00   5.1774224381423188E+00\n         3        284   1.9734520894264494E-02   4.9523830350229616E+01   1.3222957206475980E+01   8.0717436482540332E+00\n         3        285   1.3248056609838675E-02   3.4546480820458584E+01   9.1737647246003622E+00   5.5572017130914526E+00\n         3        286   1.1962573059349417E-02   3.0554688695127503E+01   8.4362126502853165E+00   5.0468927117410374E+00\n         3        287   5.1980855161655251E-03   1.1460518808903680E+01   3.1351409250053406E+00   1.9517109954111269E+00\n         3        288   5.5636368616198101E-04   4.7041825488507866E-01   4.7655576506132398E-02   4.0661124491805992E-02\n         3        289   2.3057413590377648E-03   1.5509771103139069E+00   1.6795357441007275E-01   1.3945032042678271E-01\n         3        290   3.5703756032694919E-03   2.3167493837806430E+00   3.2697116470910564E-01   2.7060675325036782E-01\n         3        291   1.6448601832993823E-03   1.6408812184341692E+00   2.4966729941857274E-01   2.2495216497313866E-01\n         3        292   1.2200564657208199E-03   1.4694771117408731E+00   2.2798143421561537E-01   2.0582726875614557E-01\n         3        293   4.9262332390579951E-04   4.6724608688069008E-01   7.5327620507255819E-02   7.1165647379917721E-02\n         3        294   1.1007878765033776E+00   2.7946175325109632E+01   1.2227471804665463E+01   4.5571114701800797E+00\n         3        295   2.3593456376136994E+00   7.6245027074676116E+01   3.0033820715525284E+01   1.1394282713910393E+01\n         3        296   4.6249701123897200E+00   1.1965266802200235E+02   4.7984784874994268E+01   1.7997173700650130E+01\n         3        297   3.5754319612643890E+00   8.0372970678573338E+01   3.2869155054656360E+01   1.2492882471346771E+01\n         3        298   3.6766112868651830E+00   7.1699639394051474E+01   3.0343831925300677E+01   1.1535117031331541E+01\n         3        299   1.4848792726072879E+00   2.9470880181117529E+01   1.1675345187452214E+01   4.6232672614899188E+00\n         3        300  -4.7560871347965801E-17   1.8327284650080094E-03   1.2646933605987180E-05   7.3403130263805210E-05\n         3        301  -4.5638678264011175E-17   2.0303834699724626E-03   1.2660605427638042E-05   7.8504930724904366E-05\n         3        302  -3.5412399071936617E-17   2.0007891374034794E-03   1.3605090688523725E-05   8.2288142870173126E-05\n         3        303  -5.9807940588296230E-17   2.5135521402326395E-02   1.5551833533781060E-04   1.2130518119413507E-03\n         3        304  -1.3468221305837976E-16   2.3050032554245023E-01   2.7116194116442150E-03   1.2531112386622901E-02\n         3        305  -3.0868531471921408E-16   6.8866302155125880E-01   1.0640129957363948E-02   4.1199678494024013E-02\n         3        306  -2.9163261466470822E-16   7.5839430849216016E-01   1.0159951948206352E-02   4.2369089794662980E-02\n         3        307  -2.2039022073357421E-16   7.4728523527420820E-01   1.0638094132775338E-02   4.3959819327677438E-02\n         3        308  -1.9098688330695927E-16   3.9919102123441580E-01   4.5680053059795290E-03   2.4018164130766496E-02\n         3        309  -1.4927054569349683E-17   5.4288060143951669E-03   1.2646124594880721E-04   3.4917625077484119E-04\n         3        310   0.0000000000000000E+00   1.5585417274844278E-02   3.9486990848092645E-04   1.0658555350373041E-03\n         3        311   0.0000000000000000E+00   1.7039639851509056E-02   3.5661737119803449E-04   1.0722969492159731E-03\n         3        312   0.0000000000000000E+00   1.6765634107290116E-02   3.6354432449997403E-04   1.1234112108672919E-03\n         3        313  -1.6874946464159030E-18   9.1465856708756992E-03   1.5271678756041579E-04   5.8704379061977623E-04\n         3        314  -7.6655367114397210E-16   6.3128931254110887E-01   4.6172806271438591E-02   8.5474619706774876E-02\n         3        315   6.7994130105837849E-17   3.1715634736016582E+00   3.2809747120755345E-01   4.5621415671956828E-01\n         3        316   2.9301464602148734E-07   5.7571549511923807E+00   6.5875204898820228E-01   7.8442966002571146E-01\n         3        317   2.6389037602795601E-07   4.4976121935612037E+00   5.0475908322295127E-01   6.1790286433623542E-01\n         3        318   1.6261811765265133E-07   4.2795420466560214E+00   4.7788920924137318E-01   5.9684317850444413E-01\n         3        319   0.0000000000000000E+00   1.7276650817778056E+00   1.8873727410404212E-01   2.7521743580783409E-01\n         3        320   7.8335248314188614E-11   3.6499757463674606E-03   1.7787909767522534E-04   3.4973829267240177E-04\n         3        321   3.3849207237937759E-08   2.3779041650772107E-02   1.5421769223248674E-03   2.5763170192341350E-03\n         3        322   1.8142915388567406E-07   5.7717883167940132E-02   3.7846054172045495E-03   6.2797228426095912E-03\n         3        323   1.7570652428813138E-07   6.0904566778856965E-02   3.1628360488713762E-03   5.8433085971484880E-03\n         3        324   1.7951302861338428E-07   5.9527449290661186E-02   3.1077168524934191E-03   5.9525480201561426E-03\n         3        325   2.7185832177170496E-08   3.4758679184872882E-02   1.2727481788324599E-03   3.0404858020360143E-03\n         3        326   3.6729299654012415E-04   2.6660410072146479E+00   3.6809792778420070E-01   3.3555332324089504E-01\n         3        327   1.7031335464568816E-02   7.5226104125868947E+00   1.7464646710982246E+00   1.2943455063438440E+00\n         3        328   6.0288306939422699E-02   1.3125400614483535E+01   3.0380350184825127E+00   2.0851125801436869E+00\n         3        329   3.1957087804619949E-02   1.0036474514483098E+01   2.1665861225215042E+00   1.5281150671522268E+00\n         3        330   2.5177921586288610E-02   9.3706637976168992E+00   1.9899469242603924E+00   1.4112096780264611E+00\n         3        331   9.8988167484363059E-04   3.1756759318717269E+00   7.8534243572036044E-01   6.2547885393945013E-01\n"
  },
  {
    "path": "examples/nnp-predict/Anisole_SCAN/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.9749524986944524E+00 a         1     0     1     1     1\n -1.1727677476771443E+00 a         2     0     1     1     2\n  2.3670083874627159E+00 a         3     0     1     1     3\n  1.5350008890598528E+00 a         4     0     1     1     4\n -2.4991458866543339E+00 a         5     0     1     1     5\n -8.1048167707954342E+00 a         6     0     1     1     6\n -2.5122024995587542E+00 a         7     0     1     1     7\n -5.9184160196994329E+00 a         8     0     1     1     8\n  6.2405897016146570E+00 a         9     0     1     1     9\n  6.1011687863436442E-02 a        10     0     1     1    10\n  5.0370507950967633E+00 a        11     0     1     1    11\n -6.9388217299408588E+00 a        12     0     1     1    12\n -4.9243912303720512E+00 a        13     0     1     1    13\n -6.9840027709581705E+00 a        14     0     1     1    14\n  2.1815487728443553E-01 a        15     0     1     1    15\n -8.9983343757076675E+00 a        16     0     1     1    16\n -9.2862731322621155E+00 a        17     0     1     1    17\n  3.8416033169906152E+00 a        18     0     1     1    18\n -2.5373093635544275E-01 a        19     0     1     1    19\n  4.1105222124275249E+00 a        20     0     1     1    20\n  1.2844973733179619E+00 a        21     0     1     1    21\n -3.0634143478079601E+00 a        22     0     1     1    22\n -6.7997728833691147E+00 a        23     0     1     1    23\n  5.4005303860896410E+00 a        24     0     1     1    24\n  1.2540506323738827E+00 a        25     0     1     1    25\n  2.8350326218703645E+00 a        26     0     1     1    26\n  1.1168814583606019E+00 a        27     0     1     1    27\n  1.5315593736281889E+00 a        28     0     1     1    28\n  1.0286846439450088E+01 a        29     0     1     1    29\n -7.4750008131612091E+00 a        30     0     1     1    30\n -1.0459128443072387E+00 a        31     0     2     1     1\n  2.2016668904962180E+00 a        32     0     2     1     2\n -1.5034013149239440E+01 a        33     0     2     1     3\n -1.0584707585295450E-01 a        34     0     2     1     4\n -4.6247028380296547E+00 a        35     0     2     1     5\n  1.0992377487246067E+01 a        36     0     2     1     6\n  3.2909805579001836E+00 a        37     0     2     1     7\n -8.5144529541146046E+00 a        38     0     2     1     8\n -5.2514364793564958E+00 a        39     0     2     1     9\n -6.6926976061835477E+00 a        40     0     2     1    10\n -1.3123012288190221E+00 a        41     0     2     1    11\n  3.2389226200578323E+00 a        42     0     2     1    12\n -5.2909732571980967E+00 a        43     0     2     1    13\n -2.1376829600147609E-01 a        44     0     2     1    14\n -1.7239810378011997E+00 a        45     0     2     1    15\n -1.3105069462509715E+00 a        46     0     2     1    16\n -1.3068789187179304E+00 a        47     0     2     1    17\n  2.1543056322756007E+00 a        48     0     2     1    18\n  3.0911113639642647E+00 a        49     0     2     1    19\n  5.9213173902677085E-01 a        50     0     2     1    20\n -6.2844167812212079E+00 a        51     0     2     1    21\n -2.4883531796341982E+00 a        52     0     2     1    22\n -1.9120468016085304E+00 a        53     0     2     1    23\n -1.5017392146225348E+00 a        54     0     2     1    24\n -1.6738708882802966E+00 a        55     0     2     1    25\n -3.2885712224907260E+00 a        56     0     2     1    26\n  7.2452328630734453E+00 a        57     0     2     1    27\n  3.2784607839923883E+00 a        58     0     2     1    28\n  3.8243107317169431E+00 a        59     0     2     1    29\n -4.9623718979595992E+00 a        60     0     2     1    30\n -8.5296950293464024E-01 a        61     0     3     1     1\n  1.2473240592262670E-01 a        62     0     3     1     2\n  2.6085768101627078E+00 a        63     0     3     1     3\n -1.2758071049907285E+00 a        64     0     3     1     4\n -7.1390772098791082E+00 a        65     0     3     1     5\n -4.9960391246879494E+00 a        66     0     3     1     6\n  2.2882542591792583E+00 a        67     0     3     1     7\n  2.9181752383366186E+00 a        68     0     3     1     8\n  4.9096460756762426E+00 a        69     0     3     1     9\n  1.5793889008331435E+01 a        70     0     3     1    10\n  8.6165028726388613E+00 a        71     0     3     1    11\n -3.8911827041031031E+00 a        72     0     3     1    12\n  1.5433957974347541E+01 a        73     0     3     1    13\n -3.0705819276220442E-01 a        74     0     3     1    14\n -1.7156567467377482E+00 a        75     0     3     1    15\n -2.7821307962279564E+00 a        76     0     3     1    16\n  7.4560839875927281E+00 a        77     0     3     1    17\n -7.3244485727116464E+00 a        78     0     3     1    18\n  3.9404530211374622E+00 a        79     0     3     1    19\n -1.0370177555966073E+01 a        80     0     3     1    20\n  8.3251093503406857E+00 a        81     0     3     1    21\n  1.4812598567883057E+00 a        82     0     3     1    22\n -1.5477361444698505E+00 a        83     0     3     1    23\n -1.8220081234592883E-01 a        84     0     3     1    24\n  3.0688673637766910E+00 a        85     0     3     1    25\n -3.6247386887118775E+00 a        86     0     3     1    26\n -6.3432452417448970E-01 a        87     0     3     1    27\n -2.7759297384433865E+00 a        88     0     3     1    28\n  3.1919234130362124E+00 a        89     0     3     1    29\n -8.0091571843446250E+00 a        90     0     3     1    30\n  3.8344709043599310E+00 a        91     0     4     1     1\n -1.9300405913538296E-01 a        92     0     4     1     2\n -1.9823179747094428E+00 a        93     0     4     1     3\n  7.6781526810043921E-01 a        94     0     4     1     4\n  4.1636488412151005E+00 a        95     0     4     1     5\n  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1.7947485733618898E+00 a      1952     0    66     1     2\n  2.0959895299187772E-01 a      1953     0    66     1     3\n -6.0033698124291153E+00 a      1954     0    66     1     4\n  2.7048619888400065E+00 a      1955     0    66     1     5\n -9.2401278006473320E-01 a      1956     0    66     1     6\n  2.2970609315213792E+00 a      1957     0    66     1     7\n -3.9856707470005639E+00 a      1958     0    66     1     8\n -7.7588786083481889E+00 a      1959     0    66     1     9\n -3.2271977679020423E+00 a      1960     0    66     1    10\n  9.7203920306584148E+00 a      1961     0    66     1    11\n  8.2653327613231813E+00 a      1962     0    66     1    12\n  4.4631913563386734E+00 a      1963     0    66     1    13\n -3.6350317578683726E+00 a      1964     0    66     1    14\n  4.6316096619835045E+00 a      1965     0    66     1    15\n -2.7467169789066368E+00 a      1966     0    66     1    16\n -6.6574789436036612E+00 a      1967     0    66     1    17\n -1.5385535871292246E+00 a      1968     0    66     1    18\n  2.4473650361236926E-01 a      1969     0    66     1    19\n -1.0791127850009536E+01 a      1970     0    66     1    20\n  1.9644893545762492E+00 a      1971     0    66     1    21\n  1.9137157405673406E+00 a      1972     0    66     1    22\n  1.4746864615874236E+00 a      1973     0    66     1    23\n  1.9112012825013593E+00 a      1974     0    66     1    24\n  2.8073921461437262E-01 a      1975     0    66     1    25\n  8.2091986223370288E+00 a      1976     0    66     1    26\n -2.9403883811907647E+00 a      1977     0    66     1    27\n -5.3793413165501898E+00 a      1978     0    66     1    28\n -1.5450727803025233E+00 a      1979     0    66     1    29\n  5.0508009062519026E+00 a      1980     0    66     1    30\n  7.8536161605245436E-01 a      1981     0    67     1     1\n -2.6709168712707467E+00 a      1982     0    67     1     2\n -9.7260931210100559E+00 a      1983     0    67     1     3\n  3.3261616476390929E+00 a      1984     0    67     1     4\n  9.4686794460224954E-01 a      1985     0    67     1     5\n -3.1829794935510103E+00 a      1986     0    67     1     6\n -1.2745485150902964E+00 a      1987     0    67     1     7\n  2.7415529956496347E+00 a      1988     0    67     1     8\n  1.0416936232781232E+01 a      1989     0    67     1     9\n -3.4948346810260222E+00 a      1990     0    67     1    10\n -3.6972466821379948E+00 a      1991     0    67     1    11\n  5.4734513600827803E+00 a      1992     0    67     1    12\n  2.7666615871144429E-01 a      1993     0    67     1    13\n  1.8115784245712951E+00 a      1994     0    67     1    14\n -5.1364867929403335E+00 a      1995     0    67     1    15\n -6.0652859795628178E+00 a      1996     0    67     1    16\n  5.0942159216521974E+00 a      1997     0    67     1    17\n -2.9650891295409143E+00 a      1998     0    67     1    18\n -3.0341786355391638E+00 a      1999     0    67     1    19\n  3.7296534296465484E+00 a      2000     0    67     1    20\n -3.1405494615311662E+00 a      2001     0    67     1    21\n  1.2770074054823559E+00 a      2002     0    67     1    22\n -2.5845857098984553E+00 a      2003     0    67     1    23\n -6.4165587287534231E+00 a      2004     0    67     1    24\n  4.1448655661687619E+00 a      2005     0    67     1    25\n -7.7538037876528403E+00 a      2006     0    67     1    26\n  4.9618143048011104E-01 a      2007     0    67     1    27\n -1.5255690572718743E+00 a      2008     0    67     1    28\n  4.6683028122337555E-01 a      2009     0    67     1    29\n -3.1365879206426150E+00 a      2010     0    67     1    30\n  6.3282693610360141E+00 a      2011     0    68     1     1\n  1.2392099095198863E+00 a      2012     0    68     1     2\n  9.1746538030991012E+00 a      2013     0    68     1     3\n -5.9708841427319692E-01 a      2014     0    68     1     4\n -4.1104907669703661E-01 a      2015     0    68     1     5\n  2.5495064414901734E+00 a      2016     0    68     1     6\n -5.0523590635423945E+00 a      2017     0    68     1     7\n -3.1333654981583425E-01 a      2018     0    68     1     8\n -6.9992779295473166E+00 a      2019     0    68     1     9\n  1.0170006098975137E+00 a      2020     0    68     1    10\n -5.0261351178342233E+00 a      2021     0    68     1    11\n -6.8391330317858019E+00 a      2022     0    68     1    12\n  8.9762857799992926E+00 a      2023     0    68     1    13\n  4.3534340611862921E-01 a      2024     0    68     1    14\n  1.9974447147339027E+00 a      2025     0    68     1    15\n -2.4548722664283313E+00 a      2026     0    68     1    16\n  1.6253062784357770E+00 a      2027     0    68     1    17\n  1.6463814109756882E+00 a      2028     0    68     1    18\n  5.3912511671194148E+00 a      2029     0    68     1    19\n  2.6651909474065549E+00 a      2030     0    68     1    20\n -3.7598832707041372E+00 a      2031     0    68     1    21\n  1.4974387094926773E+00 a      2032     0    68     1    22\n  1.0082269273131633E+01 a      2033     0    68     1    23\n  1.1779490000724750E+00 a      2034     0    68     1    24\n -4.7148736936377658E+00 a      2035     0    68     1    25\n -1.3741753705419271E+00 a      2036     0    68     1    26\n  8.0374256732235523E+00 a      2037     0    68     1    27\n  3.6935306369121830E+00 a      2038     0    68     1    28\n -5.1321368081796026E-01 a      2039     0    68     1    29\n -5.1077642241291112E+00 a      2040     0    68     1    30\n  1.9807541165468572E+00 a      2041     0    69     1     1\n  2.5054025095227483E-01 a      2042     0    69     1     2\n -4.6444879546875328E-01 a      2043     0    69     1     3\n -4.8623212892192047E-01 a      2044     0    69     1     4\n  2.0999145547294251E+00 a      2045     0    69     1     5\n  1.7004704390605649E+00 a      2046     0    69     1     6\n -2.6404964045969797E+00 a      2047     0    69     1     7\n 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4.6020027621545241E+00 a      2128     0    71     1    28\n  2.8208943276438134E+00 a      2129     0    71     1    29\n  1.0462529186919253E+01 a      2130     0    71     1    30\n -2.2944939187288442E+00 a      2131     0    72     1     1\n -2.0130726368006697E+00 a      2132     0    72     1     2\n -1.6669130103052651E-01 a      2133     0    72     1     3\n  5.7237350789648911E-01 a      2134     0    72     1     4\n -4.0842150767513203E+00 a      2135     0    72     1     5\n -3.0665372331711800E+00 a      2136     0    72     1     6\n -1.5771148654488978E+00 a      2137     0    72     1     7\n  3.4778038388480392E+00 a      2138     0    72     1     8\n -2.2072463770283339E+00 a      2139     0    72     1     9\n  5.2879308581346984E-01 a      2140     0    72     1    10\n -4.2364229375964770E+00 a      2141     0    72     1    11\n -3.8332514720832642E+00 a      2142     0    72     1    12\n -3.4288325323236548E+00 a      2143     0    72     1    13\n 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3.6630341679761244E-02 a     10918     1    18     2    18\n -5.0792796520547974E-02 a     10919     1    18     2    19\n  7.0833040191672703E-01 a     10920     1    18     2    20\n  1.7356252860967805E-01 a     10921     1    19     2     1\n -1.7815086525976125E+00 a     10922     1    19     2     2\n -8.5816460549365176E-02 a     10923     1    19     2     3\n  1.6094148968262750E-01 a     10924     1    19     2     4\n -1.3189307761345115E+00 a     10925     1    19     2     5\n -7.9891068125627750E-03 a     10926     1    19     2     6\n  4.8789709767950856E-01 a     10927     1    19     2     7\n  3.2650073848671896E-01 a     10928     1    19     2     8\n  1.7941477416501972E-01 a     10929     1    19     2     9\n  1.4158343426706737E+00 a     10930     1    19     2    10\n -1.3210791372370589E-01 a     10931     1    19     2    11\n -6.0077674024177408E-01 a     10932     1    19     2    12\n -4.5795018704142820E-01 a     10933     1    19     2    13\n -4.6692096109717252E+00 a     10934     1    19     2    14\n -1.0735704417732042E+00 a     10935     1    19     2    15\n  3.5969529334416922E-01 a     10936     1    19     2    16\n  2.4722970647302156E-01 a     10937     1    19     2    17\n  2.6421944644497780E-01 a     10938     1    19     2    18\n  1.4568593605792513E-01 a     10939     1    19     2    19\n  8.6695627702796052E-01 a     10940     1    19     2    20\n -1.9961379955500044E-01 a     10941     1    20     2     1\n -2.6584678115753761E+00 a     10942     1    20     2     2\n  3.5037603966485020E-01 a     10943     1    20     2     3\n  6.4288054133549799E-01 a     10944     1    20     2     4\n  4.7063665047517633E-01 a     10945     1    20     2     5\n -1.0751711284345449E+00 a     10946     1    20     2     6\n -1.2484990492146704E+00 a     10947     1    20     2     7\n -3.0182723124311528E-01 a     10948     1    20     2     8\n  3.6230727024036902E-01 a     10949     1    20     2     9\n  1.9629680525407617E-01 a     10950     1    20     2    10\n -1.4971500547659333E-01 a     10951     1    20     2    11\n  1.4594159059341749E-01 a     10952     1    20     2    12\n -3.5312832189128124E-01 a     10953     1    20     2    13\n  2.6149503310347626E+00 a     10954     1    20     2    14\n -3.3944097071288581E+00 a     10955     1    20     2    15\n -6.1772432875414762E-01 a     10956     1    20     2    16\n -1.9228874002055532E+00 a     10957     1    20     2    17\n -3.4342371063763527E-01 a     10958     1    20     2    18\n  2.3730274475565197E-01 a     10959     1    20     2    19\n -1.6622100249507246E-01 a     10960     1    20     2    20\n  1.6538516439074280E-01 a     10961     1    21     2     1\n  8.4511755161776425E-01 a     10962     1    21     2     2\n -3.1494337922338445E-01 a     10963     1    21     2     3\n  1.3736966246950144E+00 a     10964     1    21     2     4\n  2.1776723730374942E-01 a     10965     1    21     2     5\n -4.2126548317296741E-01 a     10966     1    21     2     6\n -7.2244940578070238E-01 a     10967     1    21     2     7\n  2.7381961319773718E-01 a     10968     1    21     2     8\n -9.1465687668451520E-02 a     10969     1    21     2     9\n  3.1836333212979084E-01 a     10970     1    21     2    10\n  5.1775590130850431E-02 a     10971     1    21     2    11\n  4.1191453992266612E-02 a     10972     1    21     2    12\n -2.0731778833262227E+00 a     10973     1    21     2    13\n  1.8257149614219674E+00 a     10974     1    21     2    14\n -7.4426166913095881E-01 a     10975     1    21     2    15\n  3.8633210652992128E-01 a     10976     1    21     2    16\n  1.5511986191521196E-01 a     10977     1    21     2    17\n  6.2340655210495766E-01 a     10978     1    21     2    18\n -6.1453969750886905E-01 a     10979     1    21     2    19\n  8.4040227855261496E-01 a     10980     1    21     2    20\n -3.5696956583101297E-01 a     10981     1    22     2     1\n  8.0563377504006140E-01 a     10982     1    22     2     2\n  8.6025927668714897E-01 a     10983     1    22     2     3\n -4.1039262107675983E-01 a     10984     1    22     2     4\n -1.3528168969245764E+00 a     10985     1    22     2     5\n  4.0143993613758875E+00 a     10986     1    22     2     6\n  1.0779186199945607E+00 a     10987     1    22     2     7\n  6.1374726170127503E-01 a     10988     1    22     2     8\n  5.0210695810812223E-02 a     10989     1    22     2     9\n  1.5544826334084025E+00 a     10990     1    22     2    10\n  1.2867093433958943E-01 a     10991     1    22     2    11\n  1.3050512966266908E-01 a     10992     1    22     2    12\n  6.3797235523888962E-01 a     10993     1    22     2    13\n -1.1973484563321202E+00 a     10994     1    22     2    14\n  2.8052017234698639E+00 a     10995     1    22     2    15\n -2.1349379084553929E-01 a     10996     1    22     2    16\n -8.1369068958726906E-02 a     10997     1    22     2    17\n -4.0877427036235486E-01 a     10998     1    22     2    18\n  5.9646659477283509E-02 a     10999     1    22     2    19\n -1.8374682688422905E+00 a     11000     1    22     2    20\n -6.6525929481377333E-01 a     11001     1    23     2     1\n -2.8503045260742526E+00 a     11002     1    23     2     2\n  3.6400097287117419E-02 a     11003     1    23     2     3\n  1.0167603036316764E+00 a     11004     1    23     2     4\n -5.1981713699148002E-01 a     11005     1    23     2     5\n -8.9729817381079624E-01 a     11006     1    23     2     6\n  5.2196161272443087E-01 a     11007     1    23     2     7\n -5.6627120261110009E-01 a     11008     1    23     2     8\n  2.8799332952580542E-01 a     11009     1    23     2     9\n  9.6869505348576787E-02 a     11010     1    23     2    10\n -1.2106475521259337E-01 a     11011     1    23     2    11\n  1.2967038644479381E-01 a     11012     1    23     2    12\n -2.0208952253587387E+00 a     11013     1    23     2    13\n  1.5345434396474893E+00 a     11014     1    23     2    14\n -5.6402760746375535E-01 a     11015     1    23     2    15\n  7.5895764607096128E-01 a     11016     1    23     2    16\n -1.1658619688124652E+00 a     11017     1    23     2    17\n -6.2697131457677091E-01 a     11018     1    23     2    18\n -7.8394417563141361E-01 a     11019     1    23     2    19\n -1.9425570749291274E+00 a     11020     1    23     2    20\n -4.1605424796216171E-02 a     11021     1    24     2     1\n  2.9086371382185239E-01 a     11022     1    24     2     2\n  6.4266672226547084E-01 a     11023     1    24     2     3\n  3.3597457784610085E-01 a     11024     1    24     2     4\n  2.2440267680897974E+00 a     11025     1    24     2     5\n -2.8267672061048787E+00 a     11026     1    24     2     6\n  1.2539806417210586E-01 a     11027     1    24     2     7\n  3.3955070296327106E-01 a     11028     1    24     2     8\n  2.1206806870999271E-02 a     11029     1    24     2     9\n -1.3055929285183796E+00 a     11030     1    24     2    10\n -5.4977832772496911E-02 a     11031     1    24     2    11\n -9.8952779410743402E-02 a     11032     1    24     2    12\n -1.1871643558352938E+00 a     11033     1    24     2    13\n  1.7054266728729151E+00 a     11034     1    24     2    14\n  2.2436383768933106E+00 a     11035     1    24     2    15\n  8.8928672831608685E-02 a     11036     1    24     2    16\n -4.1793381018844172E-01 a     11037     1    24     2    17\n  6.0061801500315794E-02 a     11038     1    24     2    18\n -5.7122210995832112E-01 a     11039     1    24     2    19\n -2.9180648978698820E-01 a     11040     1    24     2    20\n  4.2388725382392761E-01 a     11041     1    25     2     1\n -2.6026140950249150E+00 a     11042     1    25     2     2\n  6.0233398456913023E-01 a     11043     1    25     2     3\n  1.3339099909248124E+00 a     11044     1    25     2     4\n  2.0797828929811355E+00 a     11045     1    25     2     5\n -3.2457788639776042E+00 a     11046     1    25     2     6\n -2.6390838224388316E+00 a     11047     1    25     2     7\n -1.3065567973540573E+00 a     11048     1    25     2     8\n  6.4780807701049337E-01 a     11049     1    25     2     9\n  1.3047302548549387E+00 a     11050     1    25     2    10\n -1.3348295921048384E-01 a     11051     1    25     2    11\n -5.6436219775635454E-01 a     11052     1    25     2    12\n -4.2150078563091391E+00 a     11053     1    25     2    13\n  3.9442115851796040E+00 a     11054     1    25     2    14\n  2.7507773655369379E+00 a     11055     1    25     2    15\n  8.4447977021750986E-01 a     11056     1    25     2    16\n  9.2677234375727435E-01 a     11057     1    25     2    17\n -1.6060645715140256E+00 a     11058     1    25     2    18\n -5.6297665187582979E-01 a     11059     1    25     2    19\n -1.1619762113838552E+00 a     11060     1    25     2    20\n -1.6527444394960217E-01 a     11061     1    26     2     1\n  3.7993995530148994E-01 a     11062     1    26     2     2\n -1.0259496009724096E+00 a     11063     1    26     2     3\n -6.0245974549209547E-02 a     11064     1    26     2     4\n -2.2632211432698259E+00 a     11065     1    26     2     5\n  6.9527443397655930E-01 a     11066     1    26     2     6\n -5.9966383116113520E-01 a     11067     1    26     2     7\n  9.3476592325536872E-02 a     11068     1    26     2     8\n  1.4348612198079621E-02 a     11069     1    26     2     9\n  6.5641206085959347E-01 a     11070     1    26     2    10\n  2.7966834633998992E-02 a     11071     1    26     2    11\n  1.6545050024914471E-01 a     11072     1    26     2    12\n  6.4845957215155581E-01 a     11073     1    26     2    13\n -9.8674438539031142E-02 a     11074     1    26     2    14\n  1.2136587580744669E-01 a     11075     1    26     2    15\n  4.2485713059291363E-01 a     11076     1    26     2    16\n  2.5888223077303336E+00 a     11077     1    26     2    17\n -1.7714315518617751E-01 a     11078     1    26     2    18\n -9.0610108805878242E-01 a     11079     1    26     2    19\n -2.0507960182098506E+00 a     11080     1    26     2    20\n  1.3171625927613156E-01 a     11081     1    27     2     1\n -8.0527161548753412E-01 a     11082     1    27     2     2\n -7.4436832488130211E-01 a     11083     1    27     2     3\n  1.4403926674814127E-01 a     11084     1    27     2     4\n  2.2166560063953424E+00 a     11085     1    27     2     5\n -1.9300401629753998E+00 a     11086     1    27     2     6\n -6.3480496063326808E-01 a     11087     1    27     2     7\n -6.9471569627674493E-02 a     11088     1    27     2     8\n -3.4862821594748067E-01 a     11089     1    27     2     9\n  7.7410936500885541E-01 a     11090     1    27     2    10\n  1.6903613196761885E-01 a     11091     1    27     2    11\n -7.8598979180250739E-01 a     11092     1    27     2    12\n -4.8259778613434712E-01 a     11093     1    27     2    13\n -1.7654655603858083E+00 a     11094     1    27     2    14\n -1.5238246042389547E+00 a     11095     1    27     2    15\n  4.1079414230333217E-01 a     11096     1    27     2    16\n  1.5052042974066839E+00 a     11097     1    27     2    17\n  9.2515589186416880E-01 a     11098     1    27     2    18\n  7.3659551418637936E-01 a     11099     1    27     2    19\n -1.4635683491502935E+00 a     11100     1    27     2    20\n  5.1654726550745378E-01 a     11101     1    28     2     1\n  1.3651433632169947E+00 a     11102     1    28     2     2\n -8.8337234847466695E-01 a     11103     1    28     2     3\n -7.0374144995301757E-02 a     11104     1    28     2     4\n  1.2651200744091082E+00 a     11105     1    28     2     5\n  1.6121255582700211E+00 a     11106     1    28     2     6\n  1.1027322263558608E+00 a     11107     1    28     2     7\n -3.3663905581833264E-01 a     11108     1    28     2     8\n  5.1644239772195268E-02 a     11109     1    28     2     9\n  8.1554791423286532E-01 a     11110     1    28     2    10\n -3.7227571126328338E-02 a     11111     1    28     2    11\n -4.1387271227819233E-01 a     11112     1    28     2    12\n -2.6005776608512057E+00 a     11113     1    28     2    13\n -8.9465432253632016E-01 a     11114     1    28     2    14\n -2.3310593605673615E+00 a     11115     1    28     2    15\n -2.3319567185688492E-01 a     11116     1    28     2    16\n -4.7097293258185138E-02 a     11117     1    28     2    17\n -6.8715198794572913E-02 a     11118     1    28     2    18\n -6.8655256253466568E-01 a     11119     1    28     2    19\n -8.2273389030700472E-02 a     11120     1    28     2    20\n -2.7629894352555007E-01 a     11121     1    29     2     1\n  1.5733596880615732E+00 a     11122     1    29     2     2\n -8.5838396901143019E-02 a     11123     1    29     2     3\n  1.4365906062224884E-01 a     11124     1    29     2     4\n -9.6027557188341905E-01 a     11125     1    29     2     5\n  1.7698549560320933E+00 a     11126     1    29     2     6\n  1.2825421476813752E+00 a     11127     1    29     2     7\n -1.2307294511050433E-01 a     11128     1    29     2     8\n  2.0758173525504223E-01 a     11129     1    29     2     9\n -8.4396524902691539E-01 a     11130     1    29     2    10\n  7.0135622629802075E-01 a     11131     1    29     2    11\n  7.8582947364924507E-02 a     11132     1    29     2    12\n -1.5953699759369271E+00 a     11133     1    29     2    13\n -1.2049932998645048E+00 a     11134     1    29     2    14\n -9.1645200676950389E-01 a     11135     1    29     2    15\n  1.6403563208734588E+00 a     11136     1    29     2    16\n -5.7618947144012511E-01 a     11137     1    29     2    17\n -3.0748290435239911E-01 a     11138     1    29     2    18\n  1.1530056611449119E-01 a     11139     1    29     2    19\n -2.0474086297437477E+00 a     11140     1    29     2    20\n  9.8228042408367286E-02 a     11141     1    30     2     1\n  5.2560694336138747E-01 a     11142     1    30     2     2\n  2.6256372138302436E-01 a     11143     1    30     2     3\n  8.8027633574760489E-01 a     11144     1    30     2     4\n  1.2713479794868694E+00 a     11145     1    30     2     5\n  1.2274271062410291E+00 a     11146     1    30     2     6\n -1.3005612172335508E+00 a     11147     1    30     2     7\n -5.0508651179865438E-01 a     11148     1    30     2     8\n -1.1270651055924877E-01 a     11149     1    30     2     9\n -2.4826737343557163E-03 a     11150     1    30     2    10\n -3.2745160642162596E-02 a     11151     1    30     2    11\n -3.5756581890613309E-01 a     11152     1    30     2    12\n -1.5421649753880264E+00 a     11153     1    30     2    13\n -8.2724545920372194E-01 a     11154     1    30     2    14\n -1.8544892764890102E+00 a     11155     1    30     2    15\n  4.5137551411729281E-02 a     11156     1    30     2    16\n -2.8324645317537556E+00 a     11157     1    30     2    17\n  6.4831455965679782E-03 a     11158     1    30     2    18\n -5.4121868534987416E-01 a     11159     1    30     2    19\n  2.5043173049551337E-01 a     11160     1    30     2    20\n -5.1349889638148960E-01 b     11161     2     1\n  3.6657380586403914E+00 b     11162     2     2\n -2.0307300651087949E+00 b     11163     2     3\n -5.8024576331296296E-01 b     11164     2     4\n -4.4100198758174908E-01 b     11165     2     5\n  1.2845063393558942E-01 b     11166     2     6\n  2.0578013120683822E+00 b     11167     2     7\n  1.0974625419406585E+00 b     11168     2     8\n -1.6897365970311475E+00 b     11169     2     9\n -4.0650350049641819E+00 b     11170     2    10\n -5.1369841178235278E+00 b     11171     2    11\n  1.3405121336832497E+00 b     11172     2    12\n  5.7450538265881823E+00 b     11173     2    13\n -6.4135481659424718E+00 b     11174     2    14\n  2.6216352022354590E+00 b     11175     2    15\n -2.3766711251604966E+00 b     11176     2    16\n -3.0898538462902096E+00 b     11177     2    17\n  1.5656661027987642E+00 b     11178     2    18\n -7.9284256386200465E+00 b     11179     2    19\n  1.1215139558987874E+01 b     11180     2    20\n  3.0707345728547603E-01 a     11181     2     1     3     1\n  1.1435572191425788E-02 a     11182     2     2     3     1\n  6.7457639421818941E-02 a     11183     2     3     3     1\n -1.2142552209035141E-01 a     11184     2     4     3     1\n -4.3696792203084100E-03 a     11185     2     5     3     1\n -1.0718748863557882E-03 a     11186     2     6     3     1\n  1.7376642249757011E-02 a     11187     2     7     3     1\n  1.2253750244800493E-01 a     11188     2     8     3     1\n  7.3540933053045243E-01 a     11189     2     9     3     1\n  2.6207686813745456E-03 a     11190     2    10     3     1\n  7.5957070673395355E-01 a     11191     2    11     3     1\n -4.7862590766954864E-02 a     11192     2    12     3     1\n -1.3132905931751402E-03 a     11193     2    13     3     1\n -4.8393630820568970E-03 a     11194     2    14     3     1\n -5.2779385306427800E-03 a     11195     2    15     3     1\n  5.6206260068789415E-01 a     11196     2    16     3     1\n -7.6169651994482633E-03 a     11197     2    17     3     1\n -5.9573269821951651E-02 a     11198     2    18     3     1\n  2.5812799989544479E+00 a     11199     2    19     3     1\n  3.4862067126539423E-03 a     11200     2    20     3     1\n  3.7106250300594783E+00 b     11201     3     1\n"
  },
  {
    "path": "examples/nnp-predict/Anisole_SCAN/weights.006.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -8.0080144822938362E+00 a         1     0     1     1     1\n  2.2090435882245330E+00 a         2     0     1     1     2\n  1.0290693704206223E+01 a         3     0     1     1     3\n -2.8417139830274922E+00 a         4     0     1     1     4\n -2.8526241158413090E+00 a         5     0     1     1     5\n -9.4645546531270219E-01 a         6     0     1     1     6\n  6.1415566370839629E+00 a         7     0     1     1     7\n  2.1363851070147483E-01 a         8     0     1     1     8\n  3.2617069746963709E+00 a         9     0     1     1     9\n -1.4182211548670178E+00 a        10     0     1     1    10\n  2.3693590116344461E+00 a        11     0     1     1    11\n -9.9221711756408730E+00 a        12     0     1     1    12\n  7.2400551171497032E+00 a        13     0     1     1    13\n  3.6169275386382185E+00 a        14     0     1     1    14\n -7.7499761466918766E+00 a        15     0     1     1    15\n -8.0210653620027728E+00 a        16     0     1     1    16\n  1.4764781202734159E+01 a        17     0     1     1    17\n  3.6295756480079904E+00 a        18     0     1     1    18\n -9.9800220940048778E-01 a        19     0     1     1    19\n -8.9417148805152831E+00 a        20     0     1     1    20\n -2.0043699908613175E+00 a        21     0     1     1    21\n -4.2354066441247538E+00 a        22     0     1     1    22\n -2.1699482246785680E+00 a        23     0     1     1    23\n -5.3961515631073578E+00 a        24     0     1     1    24\n -6.3863026277481305E+00 a        25     0     1     1    25\n  1.9683476771876054E+00 a        26     0     1     1    26\n -2.4678358791451966E+00 a        27     0     1     1    27\n -2.9543614115730654E+00 a        28     0     1     1    28\n  1.7876871592822536E+00 a        29     0     1     1    29\n  4.9212749063860795E+00 a        30     0     1     1    30\n  1.2232210673279283E+01 a        31     0     2     1     1\n  2.2234640406788384E+00 a        32     0     2     1     2\n  2.7351745986105289E+00 a        33     0     2     1     3\n  1.6970146042135649E+01 a        34     0     2     1     4\n  7.4548210825054708E+00 a        35     0     2     1     5\n  1.6530956814050821E+01 a        36     0     2     1     6\n -6.0142405997336796E+00 a        37     0     2     1     7\n  1.8279819708033389E+00 a        38     0     2     1     8\n  1.0853195826121659E+01 a        39     0     2     1     9\n -6.9179658889049422E+00 a        40     0     2     1    10\n -1.5994297647508591E+00 a        41     0     2     1    11\n -4.2234425106452962E+00 a        42     0     2     1    12\n -8.7863042344507980E-01 a        43     0     2     1    13\n  1.2827967448991356E-01 a        44     0     2     1    14\n  8.9851668670358933E+00 a        45     0     2     1    15\n -7.9497422120021344E-01 a        46     0     2     1    16\n -4.7953859667281795E-01 a        47     0     2     1    17\n  3.9826550416012960E+00 a        48     0     2     1    18\n  7.0634136051966812E-01 a        49     0     2     1    19\n  1.4776961948906658E-01 a        50     0     2     1    20\n -5.4659569321985069E-01 a        51     0     2     1    21\n -1.2350049156730551E+00 a        52     0     2     1    22\n -4.6965060905626803E+00 a        53     0     2     1    23\n -1.3266788411411850E+00 a        54     0     2     1    24\n -7.1499990025827698E-01 a        55     0     2     1    25\n  7.3631503451048124E+00 a        56     0     2     1    26\n -3.7356137649714438E-01 a        57     0     2     1    27\n -1.7661859900775281E+00 a        58     0     2     1    28\n  3.1663704824029693E+00 a        59     0     2     1    29\n -6.1130719891691800E+00 a        60     0     2     1    30\n -1.9714017978728338E+00 a        61     0     3     1     1\n -1.3923278425298147E+00 a        62     0     3     1     2\n -9.8697683471843345E-01 a        63     0     3     1     3\n -7.1262652365963808E-01 a        64     0     3     1     4\n  9.5400275950841209E+00 a        65     0     3     1     5\n  8.6566030566285301E-01 a        66     0     3     1     6\n -1.4577949159722980E+00 a        67     0     3     1     7\n  1.9145227638310052E+00 a        68     0     3     1     8\n  1.0102518694345802E-01 a        69     0     3     1     9\n  8.3730751826762404E+00 a        70     0     3     1    10\n  1.2934817062433470E+00 a        71     0     3     1    11\n -7.2972061645521373E+00 a        72     0     3     1    12\n -6.9463656226862271E+00 a        73     0     3     1    13\n  3.2266910507204791E+00 a        74     0     3     1    14\n -6.7352174258563453E+00 a        75     0     3     1    15\n -6.1733813127176884E-01 a        76     0     3     1    16\n -3.0415277002146959E+00 a        77     0     3     1    17\n  3.7231122957607155E+00 a        78     0     3     1    18\n  8.0659351427534243E-01 a        79     0     3     1    19\n -4.2003427419630155E+00 a        80     0     3     1    20\n  3.7180335792394539E+00 a        81     0     3     1    21\n -1.0826907486576876E+00 a        82     0     3     1    22\n  4.4742316238978108E-01 a        83     0     3     1    23\n -3.6373590333193730E+00 a        84     0     3     1    24\n  1.2041213393086658E+00 a        85     0     3     1    25\n -3.6420223199326411E+00 a        86     0     3     1    26\n -3.3015813808266917E-02 a        87     0     3     1    27\n  2.1280403639259569E+00 a        88     0     3     1    28\n -3.9736837562465079E+00 a        89     0     3     1    29\n -4.8546639832441185E-01 a        90     0     3     1    30\n  5.2320718082075706E+00 a        91     0     4     1     1\n -8.8780125725376244E+00 a        92     0     4     1     2\n  4.5055017557061321E+00 a        93     0     4     1     3\n  3.2189948005008420E-02 a        94     0     4     1     4\n -6.9674283793363967E-01 a        95     0     4     1     5\n -4.9368938023767353E+00 a        96     0     4     1     6\n  9.8848239189178280E+00 a        97     0     4     1     7\n -8.4271360804483941E-01 a        98     0     4     1     8\n  1.3814708496581870E+01 a        99     0     4     1     9\n  3.4563008794579542E-01 a       100     0     4     1    10\n -1.1660179130342160E+01 a       101     0     4     1    11\n -3.6078324205347827E+00 a       102     0     4     1    12\n -1.0140943818455446E+01 a       103     0     4     1    13\n  3.3378874927013000E+00 a       104     0     4     1    14\n  1.0499040166073681E+00 a       105     0     4     1    15\n -7.9595288052838309E-01 a       106     0     4     1    16\n  4.0177970917741606E+00 a       107     0     4     1    17\n  1.4279057564434673E+01 a       108     0     4     1    18\n -6.6143506420987750E+00 a       109     0     4     1    19\n  6.5031679277173895E+00 a       110     0     4     1    20\n  8.4261623458506882E+00 a       111     0     4     1    21\n  6.5973670699895957E+00 a       112     0     4     1    22\n  1.7952236757057543E+00 a       113     0     4     1    23\n -4.0997307846352466E+00 a       114     0     4     1    24\n -7.1490342645013607E+00 a       115     0     4     1    25\n -3.8258530117236647E+00 a       116     0     4     1    26\n  1.4746764108933247E+01 a       117     0     4     1    27\n  1.3410884642563792E+01 a       118     0     4     1    28\n -4.9218470183282941E+00 a       119     0     4     1    29\n  2.4513490821111339E+00 a       120     0     4     1    30\n  3.1707232322979810E+00 a       121     0     5     1     1\n -5.5252362210164039E+00 a       122     0     5     1     2\n  4.8292808737997399E+00 a       123     0     5     1     3\n -1.7032006109102142E+00 a       124     0     5     1     4\n -3.2289525763128579E+00 a       125     0     5     1     5\n -5.2423765825138329E+00 a       126     0     5     1     6\n -7.1212017151819902E+00 a       127     0     5     1     7\n  3.1064862941893150E+00 a       128     0     5     1     8\n -4.5455982693018226E+00 a       129     0     5     1     9\n -1.7479603287029191E+00 a       130     0     5     1    10\n  9.0759137918162143E+00 a       131     0     5     1    11\n  2.9317524176534939E+00 a       132     0     5     1    12\n  3.0415352735528582E+00 a       133     0     5     1    13\n -3.9751923118222514E+00 a       134     0     5     1    14\n -9.3788894458025087E+00 a       135     0     5     1    15\n  1.7409434120762894E+00 a       136     0     5     1    16\n  2.4689108484712881E+00 a       137     0     5     1    17\n -3.6143831986559488E-01 a       138     0     5     1    18\n -9.0206010285339104E+00 a       139     0     5     1    19\n -3.1877193212757695E+00 a       140     0     5     1    20\n -1.2285170334331985E+00 a       141     0     5     1    21\n -6.4870668516790806E+00 a       142     0     5     1    22\n  2.7510935781920414E+00 a       143     0     5     1    23\n  1.9775510181580627E+00 a       144     0     5     1    24\n  1.0853157702741956E+00 a       145     0     5     1    25\n  5.8212943959309822E+00 a       146     0     5     1    26\n -1.7583290384967469E+01 a       147     0     5     1    27\n -8.4056337232549438E+00 a       148     0     5     1    28\n  2.5876247569103659E+00 a       149     0     5     1    29\n  4.3231252240823403E+00 a       150     0     5     1    30\n  3.1376841339809280E-01 a       151     0     6     1     1\n -4.0709405518169319E+00 a       152     0     6     1     2\n -9.0925283988613899E+00 a       153     0     6     1     3\n -8.1627333612751158E+00 a       154     0     6     1     4\n  6.8972209327054719E+00 a       155     0     6     1     5\n  6.0980595616682907E+00 a       156     0     6     1     6\n  8.4207708244030055E+00 a       157     0     6     1     7\n -3.6116814572330966E+00 a       158     0     6     1     8\n  1.1001805935188463E+01 a       159     0     6     1     9\n -9.1371431502944844E+00 a       160     0     6     1    10\n -1.7937957484714335E+00 a       161     0     6     1    11\n -1.2364603018198645E+01 a       162     0     6     1    12\n -6.7837986173810974E+00 a       163     0     6     1    13\n  7.5687054828742495E+00 a       164     0     6     1    14\n -1.0190046111263671E+01 a       165     0     6     1    15\n -1.8744230991177147E+00 a       166     0     6     1    16\n -5.0630008992543010E+00 a       167     0     6     1    17\n  3.0195621521490055E+00 a       168     0     6     1    18\n -1.6687355857311825E+01 a       169     0     6     1    19\n  2.0123528506264918E+00 a       170     0     6     1    20\n  1.2760730993527252E+00 a       171     0     6     1    21\n  3.1398227250523947E+00 a       172     0     6     1    22\n  5.2013611160693278E+00 a       173     0     6     1    23\n  3.9320637613434717E+00 a       174     0     6     1    24\n -7.0014488025663946E+00 a       175     0     6     1    25\n -3.5251046645010140E+00 a       176     0     6     1    26\n  7.2788988953483260E+00 a       177     0     6     1    27\n  5.1689065560904339E+00 a       178     0     6     1    28\n -1.3955318316854722E+01 a       179     0     6     1    29\n -5.6497312184518238E+00 a       180     0     6     1    30\n  1.0814323960244585E+00 a       181     0     7     1     1\n -3.6716853847794244E+00 a       182     0     7     1     2\n  1.4554998835752404E+00 a       183     0     7     1     3\n -5.3564841979605218E+00 a       184     0     7     1     4\n -1.7402501581840562E+00 a       185     0     7     1     5\n -2.2242597075361639E+00 a       186     0     7     1     6\n -9.1525009709232066E+00 a       187     0     7     1     7\n  2.2103822633840098E+00 a       188     0     7     1     8\n -9.6513004817900292E+00 a       189     0     7     1     9\n -2.5061749372792392E+00 a       190     0     7     1    10\n  8.2668806955377896E+00 a       191     0     7     1    11\n  7.4998353023785869E-01 a       192     0     7     1    12\n  3.8220834217640403E+00 a       193     0     7     1    13\n -3.0647929034661296E+00 a       194     0     7     1    14\n -6.7767820725873689E+00 a       195     0     7     1    15\n  1.7638123522437366E+00 a       196     0     7     1    16\n  7.7653012440164582E-01 a       197     0     7     1    17\n -2.8085376700842435E+00 a       198     0     7     1    18\n  2.0278077122949789E+01 a       199     0     7     1    19\n -6.6976054956098459E+00 a       200     0     7     1    20\n -1.0233671396856754E+00 a       201     0     7     1    21\n -5.6823195481636350E+00 a       202     0     7     1    22\n  3.3281140330170927E-01 a       203     0     7     1    23\n  3.8925713547823624E+00 a       204     0     7     1    24\n -9.7585882994033668E-01 a       205     0     7     1    25\n  2.6598156785563916E+00 a       206     0     7     1    26\n -1.0864032439151687E+01 a       207     0     7     1    27\n -1.2212311858007501E+01 a       208     0     7     1    28\n  3.6641150198755010E+00 a       209     0     7     1    29\n -6.5297673914992025E+00 a       210     0     7     1    30\n  7.2065877741791073E+00 a       211     0     8     1     1\n -1.4934468810542021E+00 a       212     0     8     1     2\n -1.1175905157698898E+00 a       213     0     8     1     3\n -6.0065196302021944E+00 a       214     0     8     1     4\n  2.3029180490095142E+00 a       215     0     8     1     5\n  7.8709629023473537E+00 a       216     0     8     1     6\n -8.3396870418766529E+00 a       217     0     8     1     7\n  3.4319790411440918E+00 a       218     0     8     1     8\n -3.6281451021775069E+00 a       219     0     8     1     9\n -8.8876497180545826E+00 a       220     0     8     1    10\n  1.3477583425742103E+00 a       221     0     8     1    11\n  7.8337033082206027E+00 a       222     0     8     1    12\n  1.3534588924822760E-01 a       223     0     8     1    13\n  1.3959326022966803E+00 a       224     0     8     1    14\n  7.8516531400221107E-02 a       225     0     8     1    15\n -2.6813521037869137E+00 a       226     0     8     1    16\n -5.4890399212610008E+00 a       227     0     8     1    17\n -1.2367627027213026E+00 a       228     0     8     1    18\n  1.1792011710392021E+00 a       229     0     8     1    19\n  7.3889251026795195E+00 a       230     0     8     1    20\n  1.4523546697818423E+01 a       231     0     8     1    21\n  5.4268567748008589E+00 a       232     0     8     1    22\n -9.1677080382550249E-02 a       233     0     8     1    23\n -6.6173313558278513E-01 a       234     0     8     1    24\n  2.6495031260502810E-01 a       235     0     8     1    25\n -7.2320391701040769E+00 a       236     0     8     1    26\n  3.3353742793897396E+00 a       237     0     8     1    27\n -3.9808124638288662E+00 a       238     0     8     1    28\n  1.1933602503592351E+01 a       239     0     8     1    29\n -2.7280035457924162E-01 a       240     0     8     1    30\n -1.4974192077932955E+00 a       241     0     9     1     1\n -3.1399413913766230E+00 a       242     0     9     1     2\n -4.7804686842986728E+00 a       243     0     9     1     3\n -2.4669931000577887E+00 a       244     0     9     1     4\n  1.8126118814773802E+00 a       245     0     9     1     5\n  8.9420503632153991E+00 a       246     0     9     1     6\n -4.1254671317101836E+00 a       247     0     9     1     7\n  4.5189392439920280E+00 a       248     0     9     1     8\n  2.9322130997519738E+00 a       249     0     9     1     9\n -6.9351385154902072E+00 a       250     0     9     1    10\n  2.2001836423725576E-01 a       251     0     9     1    11\n  5.2572281809236920E-01 a       252     0     9     1    12\n  1.4300774814682726E+00 a       253     0     9     1    13\n  1.6626196699620506E+00 a       254     0     9     1    14\n  2.9881082988407068E+00 a       255     0     9     1    15\n  1.1383880203445831E+00 a       256     0     9     1    16\n -2.1677741659287570E+00 a       257     0     9     1    17\n -2.0245180077142684E+00 a       258     0     9     1    18\n  1.5139561713816632E+00 a       259     0     9     1    19\n  6.3442472511664443E+00 a       260     0     9     1    20\n  1.0776520139267225E+00 a       261     0     9     1    21\n  1.1673586744086619E+00 a       262     0     9     1    22\n  1.8466915973942573E+00 a       263     0     9     1    23\n -6.9615582230009316E+00 a       264     0     9     1    24\n  4.1179782100364548E+00 a       265     0     9     1    25\n  8.7369485682727550E+00 a       266     0     9     1    26\n  1.5333886354589032E+00 a       267     0     9     1    27\n  8.6149069925912658E-01 a       268     0     9     1    28\n  6.5787757980455785E-01 a       269     0     9     1    29\n -2.5656337417677895E+00 a       270     0     9     1    30\n  6.5038664422540817E+00 a       271     0    10     1     1\n  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7.0459392131612972E+00 a      1936     0    65     1    16\n  3.1257238482760796E-01 a      1937     0    65     1    17\n -2.8910381512939685E+00 a      1938     0    65     1    18\n -7.0113563994536632E-01 a      1939     0    65     1    19\n  1.9926519484651284E+00 a      1940     0    65     1    20\n  2.5067187474014627E+00 a      1941     0    65     1    21\n  3.8182779698375704E+00 a      1942     0    65     1    22\n  1.1011238883856758E+00 a      1943     0    65     1    23\n -1.7668505853979874E+00 a      1944     0    65     1    24\n -1.0378446520542719E+00 a      1945     0    65     1    25\n  2.1078704737176812E+00 a      1946     0    65     1    26\n  1.1291371579020764E+00 a      1947     0    65     1    27\n -4.0066579204228442E-01 a      1948     0    65     1    28\n  2.3832532777375488E+00 a      1949     0    65     1    29\n -2.3375603262296654E+00 a      1950     0    65     1    30\n  4.9811558032609344E+00 a      1951     0    66     1     1\n -1.0255605361022960E+01 a      1952     0    66     1     2\n -1.6119099003074910E+00 a      1953     0    66     1     3\n -1.6307807602773852E+00 a      1954     0    66     1     4\n  1.1325490164429968E+00 a      1955     0    66     1     5\n -8.1171246020694117E+00 a      1956     0    66     1     6\n -3.3663567397237243E-01 a      1957     0    66     1     7\n  3.5184625271073006E-01 a      1958     0    66     1     8\n  2.4876146030781814E+00 a      1959     0    66     1     9\n  4.8978055549921438E+00 a      1960     0    66     1    10\n -4.9774088767988873E+00 a      1961     0    66     1    11\n -5.8187314095919636E+00 a      1962     0    66     1    12\n  1.1207791192940830E+01 a      1963     0    66     1    13\n  7.6882752808577388E+00 a      1964     0    66     1    14\n -1.4666307593295913E+00 a      1965     0    66     1    15\n -5.3030749227915119E-01 a      1966     0    66     1    16\n -1.2399480142659003E+00 a      1967     0    66     1    17\n  1.5713345976373119E+00 a      1968     0    66     1    18\n  1.6833971955154949E+00 a      1969     0    66     1    19\n -4.8841720912809077E+00 a      1970     0    66     1    20\n -5.0988893636415309E+00 a      1971     0    66     1    21\n -1.2018266037348024E+01 a      1972     0    66     1    22\n -1.7914240004373903E+00 a      1973     0    66     1    23\n -1.5077061460663705E+00 a      1974     0    66     1    24\n  4.1301320740417395E+00 a      1975     0    66     1    25\n  6.1109512581944903E-01 a      1976     0    66     1    26\n -1.5697958004616241E+00 a      1977     0    66     1    27\n -3.8712505922031069E+00 a      1978     0    66     1    28\n -4.2701227148846016E-01 a      1979     0    66     1    29\n  2.1652478470295371E+00 a      1980     0    66     1    30\n -9.6019282096973746E-01 a      1981     0    67     1     1\n  1.1377379687445819E+00 a      1982     0    67     1     2\n -7.1404703821928006E+00 a      1983     0    67     1     3\n  1.3426512952047063E+00 a      1984     0    67     1     4\n  6.2965705976427406E+00 a      1985     0    67     1     5\n  7.4633436120413221E-01 a      1986     0    67     1     6\n -9.0076352105389312E-01 a      1987     0    67     1     7\n -5.9355303577225271E-01 a      1988     0    67     1     8\n -4.0474245469647157E+00 a      1989     0    67     1     9\n -3.2493513972969903E+00 a      1990     0    67     1    10\n  4.3405640181410896E-02 a      1991     0    67     1    11\n -1.5803381282115860E+00 a      1992     0    67     1    12\n -6.5912860743201200E+00 a      1993     0    67     1    13\n -2.8025796618745478E+00 a      1994     0    67     1    14\n  2.9307522296599022E+00 a      1995     0    67     1    15\n -3.5989681060055405E+00 a      1996     0    67     1    16\n  1.4615411330688262E+00 a      1997     0    67     1    17\n -4.6443894692706538E+00 a      1998     0    67     1    18\n  5.1984677741146645E-01 a      1999     0    67     1    19\n  4.5029713466337631E+00 a      2000     0    67     1    20\n  1.6991462086827154E+00 a      2001     0    67     1    21\n  3.6982673335245759E+00 a      2002     0    67     1    22\n -4.3267313920534750E-01 a      2003     0    67     1    23\n  2.2363744614039232E+00 a      2004     0    67     1    24\n -3.4954121276940904E+00 a      2005     0    67     1    25\n -1.6899748619710084E+00 a      2006     0    67     1    26\n  5.5494847930104918E-01 a      2007     0    67     1    27\n  2.5752407445448062E+00 a      2008     0    67     1    28\n -2.4938859194049784E-01 a      2009     0    67     1    29\n  2.6615673287976527E-01 a      2010     0    67     1    30\n -4.1565547069969833E-01 a      2011     0    68     1     1\n  9.9058367091153432E+00 a      2012     0    68     1     2\n -2.2320885930751251E+00 a      2013     0    68     1     3\n -1.5201566097023014E+00 a      2014     0    68     1     4\n -1.9131268906634347E+00 a      2015     0    68     1     5\n  2.0050031250105977E+00 a      2016     0    68     1     6\n  7.4459925737901889E-01 a      2017     0    68     1     7\n  4.6179912915134622E+00 a      2018     0    68     1     8\n  2.0194072964686210E-01 a      2019     0    68     1     9\n  1.1836566557254549E+00 a      2020     0    68     1    10\n  3.7262670672160172E+00 a      2021     0    68     1    11\n  3.3077570991840992E+00 a      2022     0    68     1    12\n  4.1772416249066846E-01 a      2023     0    68     1    13\n  6.0117632144715509E+00 a      2024     0    68     1    14\n -1.6658721036765127E+00 a      2025     0    68     1    15\n  3.5156039717415788E+00 a      2026     0    68     1    16\n -1.0737198376068824E+00 a      2027     0    68     1    17\n -9.2079296108100206E-01 a      2028     0    68     1    18\n -1.5716606072121988E+00 a      2029     0    68     1    19\n -2.0575217452636467E+00 a      2030     0    68     1    20\n  5.2081717347392587E-02 a      2031     0    68     1    21\n  2.4987394136174816E+00 a      2032     0    68     1    22\n  2.5458377021865486E+00 a      2033     0    68     1    23\n  3.0776926027892486E+00 a      2034     0    68     1    24\n  4.6476913024032225E+00 a      2035     0    68     1    25\n  6.0202176126218832E-01 a      2036     0    68     1    26\n  5.4970802452372780E-01 a      2037     0    68     1    27\n -1.1102512030389236E+00 a      2038     0    68     1    28\n  3.3658749792248885E+00 a      2039     0    68     1    29\n -2.3416926280242318E+00 a      2040     0    68     1    30\n  1.3639146474347106E+00 a      2041     0    69     1     1\n  1.4599358927437662E+00 a      2042     0    69     1     2\n  1.6576068039363284E-01 a      2043     0    69     1     3\n  2.9319127788319284E+00 a      2044     0    69     1     4\n  7.4962477238828624E+00 a      2045     0    69     1     5\n -2.2528802393924270E+00 a      2046     0    69     1     6\n -9.9641230150479909E-01 a      2047     0    69     1     7\n -2.4739461585998472E+00 a      2048     0    69     1     8\n -1.3749072769086710E+00 a      2049     0    69     1     9\n  2.6588466252738687E+00 a      2050     0    69     1    10\n -1.5262033415023973E-01 a      2051     0    69     1    11\n -8.1739160540050015E-01 a      2052     0    69     1    12\n  1.0305781421203501E+00 a      2053     0    69     1    13\n  7.7778774212346502E-01 a      2054     0    69     1    14\n -2.2127646673830217E+00 a      2055     0    69     1    15\n  4.2409860972873377E+00 a      2056     0    69     1    16\n  1.1007065426481715E+00 a      2057     0    69     1    17\n -7.1770597354016830E-01 a      2058     0    69     1    18\n -4.1450901628849479E-01 a      2059     0    69     1    19\n  8.8434338787486563E-02 a      2060     0    69     1    20\n -3.9824459806182544E+00 a      2061     0    69     1    21\n -9.2536536811059877E-01 a      2062     0    69     1    22\n -1.9091501406627345E+00 a      2063     0    69     1    23\n -3.4821235723393178E+00 a      2064     0    69     1    24\n  4.6819195152073556E-02 a      2065     0    69     1    25\n  1.4328040854968258E+00 a      2066     0    69     1    26\n -2.9728350993648345E-02 a      2067     0    69     1    27\n  4.1199953171803672E-01 a      2068     0    69     1    28\n  4.4000628987590593E+00 a      2069     0    69     1    29\n  6.1350343648059635E-01 a      2070     0    69     1    30\n  4.0708257962887258E+00 a      2071     0    70     1     1\n  3.9202063651669783E+00 a      2072     0    70     1     2\n  9.5362247765065788E+00 a      2073     0    70     1     3\n  2.1152395867300964E+00 a      2074     0    70     1     4\n  8.9309959591702937E-01 a      2075     0    70     1     5\n -1.0580039524233880E+01 a      2076     0    70     1     6\n -5.2266675439055756E+00 a      2077     0    70     1     7\n  3.2819537926951350E+00 a      2078     0    70     1     8\n  2.2065581787546273E+00 a      2079     0    70     1     9\n  1.8018716794744649E+00 a      2080     0    70     1    10\n -5.3343732375093662E+00 a      2081     0    70     1    11\n  1.2371421981265385E+00 a      2082     0    70     1    12\n  3.1515260520007637E+00 a      2083     0    70     1    13\n -4.4432611590811284E+00 a      2084     0    70     1    14\n  1.6647206402438552E-01 a      2085     0    70     1    15\n  4.4880845869826418E+00 a      2086     0    70     1    16\n -5.9153458773746346E+00 a      2087     0    70     1    17\n -3.1758069345165296E+00 a      2088     0    70     1    18\n  1.5262827162325741E+00 a      2089     0    70     1    19\n  6.4577210984060471E+00 a      2090     0    70     1    20\n  2.5395777705129569E-01 a      2091     0    70     1    21\n  4.0330288509422720E+00 a      2092     0    70     1    22\n -1.7564368192694708E+00 a      2093     0    70     1    23\n  8.5276077086748980E+00 a      2094     0    70     1    24\n -2.1043314701911515E+00 a      2095     0    70     1    25\n  6.3585267532835582E-02 a      2096     0    70     1    26\n  9.7982038474276512E-01 a      2097     0    70     1    27\n -4.0051128278821775E+00 a      2098     0    70     1    28\n -4.2846508839209934E+00 a      2099     0    70     1    29\n  6.6851190879338711E+00 a      2100     0    70     1    30\n -1.3350087251983642E+00 a      2101     0    71     1     1\n  2.2594197973112857E+00 a      2102     0    71     1     2\n  3.0778642064694783E+00 a      2103     0    71     1     3\n -5.3196309372790758E+00 a      2104     0    71     1     4\n -7.3406328447172449E+00 a      2105     0    71     1     5\n  3.2340678439235671E+00 a      2106     0    71     1     6\n -3.2697468713521718E+00 a      2107     0    71     1     7\n -6.0265619745725019E+00 a      2108     0    71     1     8\n  1.1956545959983240E+00 a      2109     0    71     1     9\n  4.4578703162872744E+00 a      2110     0    71     1    10\n -5.3693106309717686E-01 a      2111     0    71     1    11\n  7.4579678352027845E-01 a      2112     0    71     1    12\n -8.3223649221812146E-01 a      2113     0    71     1    13\n -3.0576162316566529E+00 a      2114     0    71     1    14\n  8.3466268555069867E-01 a      2115     0    71     1    15\n  3.5299719802532104E-01 a      2116     0    71     1    16\n -1.3861621996516520E+00 a      2117     0    71     1    17\n -4.3586297990544187E+00 a      2118     0    71     1    18\n -6.4158698177666853E+00 a      2119     0    71     1    19\n -4.4540964060035106E+00 a      2120     0    71     1    20\n  4.7227294178052688E+00 a      2121     0    71     1    21\n  5.1675909675286524E+00 a      2122     0    71     1    22\n  6.0674715765237561E+00 a      2123     0    71     1    23\n -7.9671056146734456E+00 a      2124     0    71     1    24\n  3.1009050541030037E-01 a      2125     0    71     1    25\n -1.3065882002183768E+00 a      2126     0    71     1    26\n -4.2477514275733190E+00 a      2127     0    71     1    27\n -5.7822022353710212E-01 a      2128     0    71     1    28\n -3.0716820985662543E+00 a      2129     0    71     1    29\n -1.7423114762064926E+00 a      2130     0    71     1    30\n -7.8382241039678702E+00 a      2131     0    72     1     1\n  2.1379265203581523E+00 a      2132     0    72     1     2\n -6.2342760437491496E+00 a      2133     0    72     1     3\n -2.0893711290729203E-01 a      2134     0    72     1     4\n  3.3360337351986175E-01 a      2135     0    72     1     5\n -8.2734716406211515E+00 a      2136     0    72     1     6\n  3.1228828769936134E-01 a      2137     0    72     1     7\n  5.3647116471618572E-01 a      2138     0    72     1     8\n -3.5284637758761646E+00 a      2139     0    72     1     9\n  1.1502945792506158E+00 a      2140     0    72     1    10\n  1.1316499997608719E+01 a      2141     0    72     1    11\n -2.2260505012500658E+00 a      2142     0    72     1    12\n  2.4234375807778843E+00 a      2143     0    72     1    13\n  2.5716808588671660E+00 a      2144     0    72     1    14\n  1.0031502137056687E+01 a      2145     0    72     1    15\n  2.7726369031350551E+00 a      2146     0    72     1    16\n -9.6342379582257305E+00 a      2147     0    72     1    17\n -5.2207725695189633E-01 a      2148     0    72     1    18\n -6.7756294875987111E+00 a      2149     0    72     1    19\n -1.4753103832965206E+00 a      2150     0    72     1    20\n  4.9624887107326261E+00 a      2151     0    72     1    21\n -4.6977161784781103E+00 a      2152     0    72     1    22\n  1.2619426286001392E+01 a      2153     0    72     1    23\n -5.9131359858548382E-01 a      2154     0    72     1    24\n  8.4138216319651580E+00 a      2155     0    72     1    25\n  2.0032159198805868E+00 a      2156     0    72     1    26\n  2.0434146621766306E+01 a      2157     0    72     1    27\n -1.2070123856246218E-01 a      2158     0    72     1    28\n  3.3174226911137839E-01 a      2159     0    72     1    29\n 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1.7132888009358346E-01 a     11158     1    26     2     8\n  3.9640471772063490E+00 a     11159     1    26     2     9\n  2.7131493157059988E-01 a     11160     1    26     2    10\n  7.6150734189777902E-01 a     11161     1    26     2    11\n  1.3814191653975358E-01 a     11162     1    26     2    12\n -4.8788145360410784E-01 a     11163     1    26     2    13\n  6.1896448987212660E-01 a     11164     1    26     2    14\n -4.5134721875586627E-02 a     11165     1    26     2    15\n -3.3909377111217687E-01 a     11166     1    26     2    16\n  1.3587669314811954E+00 a     11167     1    26     2    17\n -2.6993270124690566E-01 a     11168     1    26     2    18\n -7.1054019494727294E-01 a     11169     1    26     2    19\n -8.2060913409987568E-01 a     11170     1    26     2    20\n  1.9357717962560703E+00 a     11171     1    27     2     1\n -2.4335076211157575E-01 a     11172     1    27     2     2\n -5.6489669485829319E-01 a     11173     1    27     2     3\n -6.1597526315008544E-01 a     11174     1    27     2     4\n  1.5278808340070069E-01 a     11175     1    27     2     5\n -1.9606652048657863E-01 a     11176     1    27     2     6\n -1.6572928535776312E+00 a     11177     1    27     2     7\n  2.3333251909020489E-01 a     11178     1    27     2     8\n -6.1495341416309648E-02 a     11179     1    27     2     9\n  5.1742082958223428E+00 a     11180     1    27     2    10\n -1.2265543313505489E-01 a     11181     1    27     2    11\n -1.5217657582113466E+00 a     11182     1    27     2    12\n -2.7007007985781395E-01 a     11183     1    27     2    13\n  2.9483608113433077E+00 a     11184     1    27     2    14\n  2.2871020024827948E+00 a     11185     1    27     2    15\n -1.5017394994581312E-01 a     11186     1    27     2    16\n -1.0796669297772064E+00 a     11187     1    27     2    17\n  1.3755269860560462E-01 a     11188     1    27     2    18\n  2.3603436568722394E-01 a     11189     1    27     2    19\n  9.5108154624825669E-01 a     11190     1    27     2    20\n -1.5488120836008454E+00 a     11191     1    28     2     1\n -5.5095745573888149E+00 a     11192     1    28     2     2\n  1.4210272748416470E+00 a     11193     1    28     2     3\n -4.2065676876208730E-01 a     11194     1    28     2     4\n -2.3332910790393009E+00 a     11195     1    28     2     5\n -3.8433306764348631E+00 a     11196     1    28     2     6\n  5.0781828410585588E+00 a     11197     1    28     2     7\n  5.2010767131458635E-01 a     11198     1    28     2     8\n -5.1410280311135237E-01 a     11199     1    28     2     9\n  4.8024697256838228E-01 a     11200     1    28     2    10\n -2.1854129485101890E+00 a     11201     1    28     2    11\n  8.5615632813308729E+00 a     11202     1    28     2    12\n -1.3044036186779409E-03 a     11203     1    28     2    13\n  9.1093108911146392E-01 a     11204     1    28     2    14\n  5.0430423419219723E+00 a     11205     1    28     2    15\n  1.2499175956754645E+00 a     11206     1    28     2    16\n  2.0364282895328567E-01 a     11207     1    28     2    17\n -3.2440215119148402E-01 a     11208     1    28     2    18\n  1.6563039262162016E-01 a     11209     1    28     2    19\n  9.9549316465737336E-01 a     11210     1    28     2    20\n -3.8280165383991099E-01 a     11211     1    29     2     1\n -2.6904461568026052E+00 a     11212     1    29     2     2\n  1.1266202052848859E+00 a     11213     1    29     2     3\n -4.2455328842719753E-01 a     11214     1    29     2     4\n  2.2421771938899289E+00 a     11215     1    29     2     5\n -4.4628143284606576E+00 a     11216     1    29     2     6\n  8.8711606620989913E-01 a     11217     1    29     2     7\n  1.7613360848928122E-01 a     11218     1    29     2     8\n  2.3384878915931213E+00 a     11219     1    29     2     9\n  1.3654466026401233E+00 a     11220     1    29     2    10\n  5.4573074028344681E-01 a     11221     1    29     2    11\n  7.0127278079529376E-01 a     11222     1    29     2    12\n -2.9667313414683355E-01 a     11223     1    29     2    13\n -6.2011650991871392E-01 a     11224     1    29     2    14\n -1.6897743207557703E+00 a     11225     1    29     2    15\n  1.4460018873476202E-01 a     11226     1    29     2    16\n  1.5425705550911477E+00 a     11227     1    29     2    17\n  1.1199015289181156E+00 a     11228     1    29     2    18\n -8.5974398027033938E-01 a     11229     1    29     2    19\n -3.4278385680228507E-01 a     11230     1    29     2    20\n -6.2512423886936952E-01 a     11231     1    30     2     1\n  5.6310002863349551E-01 a     11232     1    30     2     2\n  2.1017598857567945E+00 a     11233     1    30     2     3\n -1.2813157213009911E+00 a     11234     1    30     2     4\n -1.2476306233896500E-01 a     11235     1    30     2     5\n -6.0551583780043522E-02 a     11236     1    30     2     6\n  2.5543972431130766E+00 a     11237     1    30     2     7\n  1.2926942224400710E+00 a     11238     1    30     2     8\n  1.5877392725662114E+00 a     11239     1    30     2     9\n  1.7705548735253283E+00 a     11240     1    30     2    10\n  1.5201241139620603E+00 a     11241     1    30     2    11\n -2.5144525128236088E+00 a     11242     1    30     2    12\n -1.8551291092757534E+00 a     11243     1    30     2    13\n  3.3247977732255456E-02 a     11244     1    30     2    14\n  7.2975854204192159E-01 a     11245     1    30     2    15\n -2.3210161291255971E-01 a     11246     1    30     2    16\n -1.8199521801886045E+00 a     11247     1    30     2    17\n  3.5610896632038225E+00 a     11248     1    30     2    18\n -1.0797278981623819E+00 a     11249     1    30     2    19\n  5.3406039255950388E-01 a     11250     1    30     2    20\n -3.0442618105965300E+00 b     11251     2     1\n  1.2912549064721692E+00 b     11252     2     2\n -1.1766950443116373E+01 b     11253     2     3\n -8.1184926976465732E+00 b     11254     2     4\n  1.5391938866748854E+01 b     11255     2     5\n  5.5852513101020929E+00 b     11256     2     6\n  3.5241435858923493E+00 b     11257     2     7\n  8.5826790157816446E-01 b     11258     2     8\n -9.6310473003271717E+00 b     11259     2     9\n -9.1360843339705262E+00 b     11260     2    10\n -1.3938404148222991E+00 b     11261     2    11\n  2.8640222977365486E+00 b     11262     2    12\n  1.1438370425993079E+00 b     11263     2    13\n  5.5739608956829398E+00 b     11264     2    14\n  3.8424168101946363E+00 b     11265     2    15\n -9.8370245790869404E-01 b     11266     2    16\n  1.4724002144229171E+00 b     11267     2    17\n -3.1402198502618219E+00 b     11268     2    18\n  3.8340480278026927E+00 b     11269     2    19\n -1.2419165294071883E+00 b     11270     2    20\n -4.8209086798797129E-01 a     11271     2     1     3     1\n -6.6113516633439255E-03 a     11272     2     2     3     1\n -1.2616335960253163E-02 a     11273     2     3     3     1\n -3.3593347793028683E-01 a     11274     2     4     3     1\n -1.2096018555373318E-03 a     11275     2     5     3     1\n -1.8417852908408999E-02 a     11276     2     6     3     1\n  1.6023811570513833E-03 a     11277     2     7     3     1\n  4.9442311258794630E-01 a     11278     2     8     3     1\n  1.7558997875814261E-02 a     11279     2     9     3     1\n  9.7474984731094928E-03 a     11280     2    10     3     1\n  9.9143192341286882E-03 a     11281     2    11     3     1\n  2.7151274335435365E-03 a     11282     2    12     3     1\n -6.6767599223926466E-01 a     11283     2    13     3     1\n  9.5885808211704071E-01 a     11284     2    14     3     1\n  2.1482748192035842E-03 a     11285     2    15     3     1\n -3.2154973309140988E-01 a     11286     2    16     3     1\n -2.8130743222112981E-01 a     11287     2    17     3     1\n -7.7350220219195333E-03 a     11288     2    18     3     1\n  3.6363593349086065E-01 a     11289     2    19     3     1\n -4.7821766548453126E-01 a     11290     2    20     3     1\n  3.2467969014148550E+00 b     11291     3     1\n"
  },
  {
    "path": "examples/nnp-predict/Anisole_SCAN/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -1.4892912926746951E+00 a         1     0     1     1     1\n  1.3786206112635062E+01 a         2     0     1     1     2\n  5.6935313569430752E+00 a         3     0     1     1     3\n -8.9265479837094954E+00 a         4     0     1     1     4\n  3.9445105420916344E+00 a         5     0     1     1     5\n -6.0852827471830535E+00 a         6     0     1     1     6\n -5.0021844069602128E+00 a         7     0     1     1     7\n -1.3014792773009494E+00 a         8     0     1     1     8\n -3.2783764688039492E+00 a         9     0     1     1     9\n -2.9070028724163777E+00 a        10     0     1     1    10\n -6.2298040928764005E+00 a        11     0     1     1    11\n -4.0669141239251578E+00 a        12     0     1     1    12\n -1.0743453391806076E+01 a        13     0     1     1    13\n -6.3243960696439752E+00 a        14     0     1     1    14\n -4.8128745937781163E+00 a        15     0     1     1    15\n  4.1935640172663682E+00 a        16     0     1     1    16\n -9.1937662981065351E+00 a        17     0     1     1    17\n  4.1217718130973182E+00 a        18     0     1     1    18\n  3.4695366930742546E+00 a        19     0     1     1    19\n  3.9296052289662371E+00 a        20     0     1     1    20\n -5.2397703048574362E+00 a        21     0     1     1    21\n  1.8239998764649912E+00 a        22     0     1     1    22\n -3.4201379933282072E+00 a        23     0     1     1    23\n  4.3150620390257100E+00 a        24     0     1     1    24\n -1.6968527725388069E-01 a        25     0     1     1    25\n -3.2546655458682348E+00 a        26     0     1     1    26\n -7.0567352851674094E+00 a        27     0     1     1    27\n -2.4322180077260529E+00 a        28     0     1     1    28\n -3.0097777128248078E+00 a        29     0     1     1    29\n  3.0092611618221414E+00 a        30     0     1     1    30\n  5.4050226263714668E-02 a        31     0     2     1     1\n -3.9566521169796331E+00 a        32     0     2     1     2\n -2.5929974799720101E+00 a        33     0     2     1     3\n -8.2748055115294648E+00 a        34     0     2     1     4\n -1.5281057523532721E-01 a        35     0     2     1     5\n -9.4878826507577880E+00 a        36     0     2     1     6\n -8.3001657733812029E-01 a        37     0     2     1     7\n -2.7292698728039180E+00 a        38     0     2     1     8\n  6.0948317967327599E+00 a        39     0     2     1     9\n -8.8447883302337651E+00 a        40     0     2     1    10\n -7.1673150173484128E+00 a        41     0     2     1    11\n -3.6694592471602645E+00 a        42     0     2     1    12\n -8.3647530422359928E+00 a        43     0     2     1    13\n -6.8528642150937360E+00 a        44     0     2     1    14\n -5.2730219181465880E+00 a        45     0     2     1    15\n  2.0385488482607759E+01 a        46     0     2     1    16\n -1.9474079278160563E+00 a        47     0     2     1    17\n  1.2470227393921414E+00 a        48     0     2     1    18\n -5.2915411198338349E+00 a        49     0     2     1    19\n  2.8066354839834600E+00 a        50     0     2     1    20\n  5.2597505725820746E+00 a        51     0     2     1    21\n  6.2081542925572659E+00 a        52     0     2     1    22\n -1.4022995282546884E+01 a        53     0     2     1    23\n -1.1626271124721386E+00 a        54     0     2     1    24\n  1.3108087549976558E+01 a        55     0     2     1    25\n  5.5138975173573908E+00 a        56     0     2     1    26\n  5.8791694872925326E+00 a        57     0     2     1    27\n  3.6009861384233020E+00 a        58     0     2     1    28\n -1.1839462340153907E-02 a        59     0     2     1    29\n  1.3319766534695956E+00 a        60     0     2     1    30\n -6.7660433402513442E+00 a        61     0     3     1     1\n  4.3608780137178362E+00 a        62     0     3     1     2\n  1.0141951311866718E+01 a        63     0     3     1     3\n  9.0909654849340049E-01 a        64     0     3     1     4\n  1.9773603721644442E+00 a        65     0     3     1     5\n  3.7363706457617962E-01 a        66     0     3     1     6\n -1.0141512583522317E+01 a        67     0     3     1     7\n  5.5729275218113786E-02 a        68     0     3     1     8\n  1.2168057294370614E+01 a        69     0     3     1     9\n -1.1337712428721204E+01 a        70     0     3     1    10\n  7.2000584957732086E+00 a        71     0     3     1    11\n  2.3674065995690863E+00 a        72     0     3     1    12\n  3.6338706996042522E+00 a        73     0     3     1    13\n  2.4996211333424907E+00 a        74     0     3     1    14\n -1.9237719645353630E+00 a        75     0     3     1    15\n -1.2686487845247347E+00 a        76     0     3     1    16\n -3.3405421019195045E+00 a        77     0     3     1    17\n -4.9225679371895241E+00 a        78     0     3     1    18\n  2.1471956527865927E+00 a        79     0     3     1    19\n -2.8470090817918980E+00 a        80     0     3     1    20\n -8.7537525820327016E+00 a        81     0     3     1    21\n  4.2052152897112713E-02 a        82     0     3     1    22\n  1.0554206269804212E+01 a        83     0     3     1    23\n  8.4334960068718556E-01 a        84     0     3     1    24\n  4.6456623168499478E-01 a        85     0     3     1    25\n -3.7341929322804193E+00 a        86     0     3     1    26\n  1.1166100409590300E+01 a        87     0     3     1    27\n -1.8304074401813091E+00 a        88     0     3     1    28\n -3.4162421319264036E+00 a        89     0     3     1    29\n -8.8446223367418284E+00 a        90     0     3     1    30\n  5.1517018108506081E+00 a        91     0     4     1     1\n  9.3719785146199470E+00 a        92     0     4     1     2\n -6.4859923110760391E+00 a        93     0     4     1     3\n -2.9145735164648828E-02 a        94     0     4     1     4\n -9.0964984469513999E-01 a        95     0     4     1     5\n -7.6632420422754055E-01 a        96     0     4     1     6\n -6.9662813937797141E+00 a        97     0     4     1     7\n -1.1863943203772700E+00 a        98     0     4     1     8\n  1.3801910489263394E+01 a        99     0     4     1     9\n  4.5909188179582188E+00 a       100     0     4     1    10\n  8.9977404234702938E+00 a       101     0     4     1    11\n  5.7070453974299928E-01 a       102     0     4     1    12\n  5.4226002069580681E-01 a       103     0     4     1    13\n -2.5367722645635289E+00 a       104     0     4     1    14\n -1.3857699734301572E+00 a       105     0     4     1    15\n -5.7013756288857909E-02 a       106     0     4     1    16\n -1.4368027811771402E+00 a       107     0     4     1    17\n  8.3816731936878242E-01 a       108     0     4     1    18\n  1.4678784316036095E+00 a       109     0     4     1    19\n -4.1527100241007684E+00 a       110     0     4     1    20\n  5.1767768330432942E+00 a       111     0     4     1    21\n  1.2374233720168766E+01 a       112     0     4     1    22\n  1.7099552809000343E-01 a       113     0     4     1    23\n -1.7689160474819472E+00 a       114     0     4     1    24\n -4.3389267533620837E+00 a       115     0     4     1    25\n  1.0153888198489649E+00 a       116     0     4     1    26\n  3.1586047332774623E+00 a       117     0     4     1    27\n -7.0799204300389018E-01 a       118     0     4     1    28\n  7.2905318443053799E-02 a       119     0     4     1    29\n -2.6312081929783937E+00 a       120     0     4     1    30\n  2.9032324820156008E+00 a       121     0     5     1     1\n -6.5829948892935031E+00 a       122     0     5     1     2\n -7.7859804150783116E+00 a       123     0     5     1     3\n -1.7511955910002459E+00 a       124     0     5     1     4\n -2.5236304821176812E+00 a       125     0     5     1     5\n  8.8212100270557092E-01 a       126     0     5     1     6\n  1.8663943553871987E+00 a       127     0     5     1     7\n  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3.1868788496979721E+00 a      1968     0    66     1    18\n -6.3659190318127709E-02 a      1969     0    66     1    19\n -6.0377257716237276E+00 a      1970     0    66     1    20\n -6.8243203372275811E+00 a      1971     0    66     1    21\n -6.6948377711010387E+00 a      1972     0    66     1    22\n  6.8216012932050099E+00 a      1973     0    66     1    23\n -3.1894637385052942E+00 a      1974     0    66     1    24\n  3.5411150231651729E+00 a      1975     0    66     1    25\n  5.1919686170075530E-01 a      1976     0    66     1    26\n -8.6688141282229463E+00 a      1977     0    66     1    27\n -3.2066106978209481E+00 a      1978     0    66     1    28\n  1.6856974114276784E+00 a      1979     0    66     1    29\n  2.6838966765315391E+00 a      1980     0    66     1    30\n -1.0066553546637930E+01 a      1981     0    67     1     1\n -3.2676051290292656E+00 a      1982     0    67     1     2\n  1.2155510343846935E+01 a      1983     0    67     1     3\n -1.2829331097051375E+01 a      1984     0    67     1     4\n -2.1156061552578707E+00 a      1985     0    67     1     5\n -2.8468743258091593E+00 a      1986     0    67     1     6\n  2.7883057967799503E+00 a      1987     0    67     1     7\n  3.5248571252324212E-01 a      1988     0    67     1     8\n  8.2328560343542474E+00 a      1989     0    67     1     9\n  6.1278186002327217E+00 a      1990     0    67     1    10\n -6.1048800664636884E+00 a      1991     0    67     1    11\n -3.1725308424634018E+00 a      1992     0    67     1    12\n -3.8122394155706947E+00 a      1993     0    67     1    13\n -4.4916199319312122E+00 a      1994     0    67     1    14\n -8.9932112925241299E+00 a      1995     0    67     1    15\n  2.3123441927071182E+00 a      1996     0    67     1    16\n -3.9442117527031226E+00 a      1997     0    67     1    17\n -5.5666173468889566E+00 a      1998     0    67     1    18\n -4.4609218885996551E+00 a      1999     0    67     1    19\n  4.4185559571327664E+00 a      2000     0    67     1    20\n  9.3695438691592727E+00 a      2001     0    67     1    21\n -1.3030397525450290E+01 a      2002     0    67     1    22\n -2.4239504740668081E+00 a      2003     0    67     1    23\n -3.1423441832096080E+00 a      2004     0    67     1    24\n  2.5299660757286152E-01 a      2005     0    67     1    25\n  4.0427964397263967E+00 a      2006     0    67     1    26\n  1.3763724422822603E+00 a      2007     0    67     1    27\n -5.9992514901502994E-03 a      2008     0    67     1    28\n  4.5074864598892574E+00 a      2009     0    67     1    29\n -3.2045029061682060E+00 a      2010     0    67     1    30\n -3.2143257614725926E+00 a      2011     0    68     1     1\n -5.9667639325500348E+00 a      2012     0    68     1     2\n  7.6704732439861143E+00 a      2013     0    68     1     3\n -1.3391711017500634E+00 a      2014     0    68     1     4\n -6.8834813921483695E+00 a      2015     0    68     1     5\n  1.2482065744870803E+00 a      2016     0    68     1     6\n -3.7149528581821984E+00 a      2017     0    68     1     7\n  8.8937416285610862E+00 a      2018     0    68     1     8\n -8.6285030480401770E-01 a      2019     0    68     1     9\n  4.7467826148241277E-01 a      2020     0    68     1    10\n  5.2246769221143881E+00 a      2021     0    68     1    11\n  9.1266091657688875E-01 a      2022     0    68     1    12\n -4.9986686226314916E+00 a      2023     0    68     1    13\n -5.8793718539428097E-01 a      2024     0    68     1    14\n -5.6750658893902690E+00 a      2025     0    68     1    15\n  6.4373522718012322E-01 a      2026     0    68     1    16\n -4.6294877231174114E+00 a      2027     0    68     1    17\n -1.0565047944668107E+01 a      2028     0    68     1    18\n  3.5598079529910787E+00 a      2029     0    68     1    19\n -3.8099476733873567E+00 a      2030     0    68     1    20\n  2.3275523704234948E+00 a      2031     0    68     1    21\n 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2.6935370197791564E-01 a     10438     1    24     2    18\n  5.4339448602431117E-01 a     10439     1    24     2    19\n -3.3214320527381641E-01 a     10440     1    24     2    20\n -2.2371482189750269E+00 a     10441     1    25     2     1\n -6.4427416395920156E-01 a     10442     1    25     2     2\n  6.6573975793408113E-01 a     10443     1    25     2     3\n  7.5312778884177844E-01 a     10444     1    25     2     4\n -2.1559323829494801E+00 a     10445     1    25     2     5\n  7.4284316734655062E-02 a     10446     1    25     2     6\n -2.3747413750097843E+00 a     10447     1    25     2     7\n -9.0314481774201361E-01 a     10448     1    25     2     8\n -1.5459304963438867E+00 a     10449     1    25     2     9\n  1.6781709126216608E+00 a     10450     1    25     2    10\n  2.1808372307962713E+00 a     10451     1    25     2    11\n  2.3033562064873219E+00 a     10452     1    25     2    12\n  4.8655757099423172E-02 a     10453     1    25     2    13\n  6.2292324283456757E-01 a     10454     1    25     2    14\n -1.0413071738047613E-01 a     10455     1    25     2    15\n -8.8198720103022987E-01 a     10456     1    25     2    16\n  1.8723432439746406E+00 a     10457     1    25     2    17\n -1.1653640353505037E+00 a     10458     1    25     2    18\n -8.0443880528711564E-01 a     10459     1    25     2    19\n  1.0788134708597794E+00 a     10460     1    25     2    20\n  1.6427933213312154E-01 a     10461     1    26     2     1\n -6.4407581990519169E-01 a     10462     1    26     2     2\n  1.0082942376833108E+00 a     10463     1    26     2     3\n -2.7009787589291412E-01 a     10464     1    26     2     4\n  8.7923639055035960E-02 a     10465     1    26     2     5\n -4.2963337870448520E-01 a     10466     1    26     2     6\n -1.7448182622459489E+00 a     10467     1    26     2     7\n -2.5849633320380621E+00 a     10468     1    26     2     8\n  7.3369429880103898E-01 a     10469     1    26     2     9\n  3.3863060227926722E-01 a     10470     1    26     2    10\n  1.3823116919031351E+00 a     10471     1    26     2    11\n  3.7082348939142307E-01 a     10472     1    26     2    12\n -9.7122697483857212E-01 a     10473     1    26     2    13\n  1.3588077534903265E+00 a     10474     1    26     2    14\n  1.2536591934077737E+00 a     10475     1    26     2    15\n -6.5398289409766430E-01 a     10476     1    26     2    16\n -3.0250643484764672E-01 a     10477     1    26     2    17\n -1.8386110581472255E+00 a     10478     1    26     2    18\n  3.7878798210665129E-02 a     10479     1    26     2    19\n  5.3962372220476895E-01 a     10480     1    26     2    20\n  2.0103193340822871E+00 a     10481     1    27     2     1\n -2.6625957144393770E-02 a     10482     1    27     2     2\n  3.0703454221413307E-01 a     10483     1    27     2     3\n -6.1118727756985880E-01 a     10484     1    27     2     4\n  1.7471139651180407E+00 a     10485     1    27     2     5\n  1.0867597011470271E+00 a     10486     1    27     2     6\n  1.5169298138532146E+00 a     10487     1    27     2     7\n -2.0970054897169952E+00 a     10488     1    27     2     8\n -5.0338365901425874E-01 a     10489     1    27     2     9\n  6.5781057678945820E-01 a     10490     1    27     2    10\n -1.3445806944440188E+00 a     10491     1    27     2    11\n -1.5995653873745411E-01 a     10492     1    27     2    12\n -1.5585365254131762E+00 a     10493     1    27     2    13\n -4.9733708869828813E-01 a     10494     1    27     2    14\n  7.6870147256530474E-01 a     10495     1    27     2    15\n  8.0606125442028509E-01 a     10496     1    27     2    16\n  2.7565408523353313E-01 a     10497     1    27     2    17\n -1.0351524780257726E+00 a     10498     1    27     2    18\n  1.6997154241973220E-01 a     10499     1    27     2    19\n  2.0407894244970546E+00 a     10500     1    27     2    20\n  1.5460500083022444E+00 a     10501     1    28     2     1\n -5.0534414393942417E-01 a     10502     1    28     2     2\n  2.2725214203984785E+00 a     10503     1    28     2     3\n  2.1115999129838121E+00 a     10504     1    28     2     4\n -5.6243438113246269E-01 a     10505     1    28     2     5\n  2.2390907510078542E+00 a     10506     1    28     2     6\n  2.4987683655889806E-01 a     10507     1    28     2     7\n -5.7892180882644972E-02 a     10508     1    28     2     8\n  1.4299556642380675E+00 a     10509     1    28     2     9\n  5.8755651222240279E-01 a     10510     1    28     2    10\n  6.5807698425641581E-01 a     10511     1    28     2    11\n  2.7678277714340277E-01 a     10512     1    28     2    12\n  1.6506852277292245E+00 a     10513     1    28     2    13\n -8.7012304541909036E-01 a     10514     1    28     2    14\n -2.8194790665587688E-01 a     10515     1    28     2    15\n -2.8146224884209650E+00 a     10516     1    28     2    16\n -1.3891189814709959E+00 a     10517     1    28     2    17\n  2.2060362536945735E-01 a     10518     1    28     2    18\n  3.1158814076123920E-01 a     10519     1    28     2    19\n  4.4023061538902084E+00 a     10520     1    28     2    20\n  1.3422233069068823E+00 a     10521     1    29     2     1\n  2.9130463113447735E-01 a     10522     1    29     2     2\n  1.9973609745350747E+00 a     10523     1    29     2     3\n -6.3695684991123447E-01 a     10524     1    29     2     4\n -2.1911021605422145E+00 a     10525     1    29     2     5\n  1.5121610496707201E+00 a     10526     1    29     2     6\n  1.7146817156558458E+00 a     10527     1    29     2     7\n  4.4558277583039863E-01 a     10528     1    29     2     8\n  3.1306635921011661E-01 a     10529     1    29     2     9\n -7.1280598071877171E-02 a     10530     1    29     2    10\n -1.2095644352398949E+00 a     10531     1    29     2    11\n -7.9856254561567275E-01 a     10532     1    29     2    12\n  1.4788943169403246E+00 a     10533     1    29     2    13\n  5.3864709925862553E-01 a     10534     1    29     2    14\n  2.6692909354021416E-01 a     10535     1    29     2    15\n -2.1972557880327068E-01 a     10536     1    29     2    16\n -1.0346990826109503E+00 a     10537     1    29     2    17\n -5.2468551112941708E-01 a     10538     1    29     2    18\n  1.8883380494637833E-01 a     10539     1    29     2    19\n  1.6256209131929505E-01 a     10540     1    29     2    20\n -6.0535890229810418E-01 a     10541     1    30     2     1\n  2.9108091077060988E-01 a     10542     1    30     2     2\n -1.0236084969791954E+00 a     10543     1    30     2     3\n  9.1548100019632317E-01 a     10544     1    30     2     4\n -1.0750615027977797E+00 a     10545     1    30     2     5\n  2.0224323574640075E+00 a     10546     1    30     2     6\n  1.0890527414115256E+00 a     10547     1    30     2     7\n -9.7595352526629015E-02 a     10548     1    30     2     8\n -1.8947793443664713E+00 a     10549     1    30     2     9\n -4.5225267715063172E-01 a     10550     1    30     2    10\n  2.7958930988576824E-01 a     10551     1    30     2    11\n -6.3626272279496920E-01 a     10552     1    30     2    12\n  3.0348025602065914E-01 a     10553     1    30     2    13\n -1.4232401974219648E+00 a     10554     1    30     2    14\n -3.0246284031444393E-01 a     10555     1    30     2    15\n  2.2479278585755805E-01 a     10556     1    30     2    16\n  4.0832628907054025E-01 a     10557     1    30     2    17\n -5.6014638423900830E-02 a     10558     1    30     2    18\n  1.5809428659510447E+00 a     10559     1    30     2    19\n  5.1196273083623844E-01 a     10560     1    30     2    20\n  9.9903466240451877E+00 b     10561     2     1\n -4.1513754444907152E+00 b     10562     2     2\n -1.9838813114644920E+00 b     10563     2     3\n  4.5766582065808570E-01 b     10564     2     4\n  5.4989694224725758E+00 b     10565     2     5\n -8.8054559208946381E-01 b     10566     2     6\n  2.7620887175618281E+00 b     10567     2     7\n  1.7075452939746377E+01 b     10568     2     8\n -1.7141928542414151E+00 b     10569     2     9\n  3.3832919102859358E+00 b     10570     2    10\n -1.7206432541048007E+00 b     10571     2    11\n -4.9391083488161129E+00 b     10572     2    12\n  1.0224034245647149E+00 b     10573     2    13\n  8.0221921498551048E+00 b     10574     2    14\n -3.7445302409888268E+00 b     10575     2    15\n -1.2661999609654199E+01 b     10576     2    16\n  7.0298962468109112E+00 b     10577     2    17\n  2.6181052048580669E+00 b     10578     2    18\n  8.4281364797389746E-01 b     10579     2    19\n  1.0664488944249935E+00 b     10580     2    20\n -1.0557065063045376E-03 a     10581     2     1     3     1\n  2.6701368355046244E+00 a     10582     2     2     3     1\n  8.5736458052644883E-03 a     10583     2     3     3     1\n  8.4425546814101884E-03 a     10584     2     4     3     1\n -2.0822056135789246E-02 a     10585     2     5     3     1\n -2.8153424057891551E-03 a     10586     2     6     3     1\n -8.8513610087836495E-03 a     10587     2     7     3     1\n  1.7504804692691420E-02 a     10588     2     8     3     1\n  1.1567408354269551E-02 a     10589     2     9     3     1\n  5.1459489281085202E-01 a     10590     2    10     3     1\n -6.2354041590818796E-03 a     10591     2    11     3     1\n  1.9068385143113643E-04 a     10592     2    12     3     1\n -7.4624623347023539E-03 a     10593     2    13     3     1\n -3.0897325872564704E-03 a     10594     2    14     3     1\n -2.5322813543927142E-01 a     10595     2    15     3     1\n  3.7586687158479909E-03 a     10596     2    16     3     1\n  1.6021186570534030E-03 a     10597     2    17     3     1\n -2.2330537566456452E-02 a     10598     2    18     3     1\n  1.6707153336643946E-01 a     10599     2    19     3     1\n  2.4731799846569105E-02 a     10600     2    20     3     1\n  4.6382812877716184E-01 b     10601     3     1\n"
  },
  {
    "path": "examples/nnp-predict/Carbon_chain_4G/hardness.001.data",
    "content": "      0.0088953312\n"
  },
  {
    "path": "examples/nnp-predict/Carbon_chain_4G/hardness.006.data",
    "content": "      0.0661189426\n"
  },
  {
    "path": "examples/nnp-predict/Carbon_chain_4G/input.data",
    "content": "begin\natom 1.17284095486 -0.172504222684 -0.667448516865 C -0.00802366916667 0.0 0.0347925826351 -0.00110373556182 0.0172205087376\natom -1.1595434822 -0.350641000445 -0.467598107194 C -0.00855427916667 0.0 -0.0190916650141 0.00319122911054 0.00166842074686\natom 3.72594054969 -0.0837975179097 -0.229777168673 C -0.00986190916667 0.0 -0.0218470438236 -0.00628540399811 -0.0170756379211\natom -3.69146983116 -0.334172643167 -0.21088223315 C -0.0100583891667 0.0 -0.0301687534058 0.0106478678179 -0.00452518599678\natom 6.07758586771 -0.166745226042 -0.145024035228 C -0.00672012916667 0.0 0.00266924762633 -0.00156314063781 0.0115961079544\natom -6.06809789367 -0.00253733508489 -0.0705357610724 C -0.00417966916667 0.0 0.0380293993069 -0.012272279507 -0.00385017456324\natom 8.59164353464 -0.0806915075831 0.402236831619 C -0.0283825591667 0.0 0.0114358510185 0.0168883247486 -0.0145042007862\natom -8.60892564573 0.117192245354 0.0982851777904 C -0.0314335491667 0.0 -0.0313212312302 0.00897304604753 0.0196935694367\natom 10.8705405815 0.51581338865 0.435826522093 C -0.0539909791667 0.0 -0.0207616703214 -0.00491358425534 0.014173822701\natom -10.8879581104 0.411807821319 0.694948565342 C -0.0495567391667 0.0 0.0330796233985 -0.00720705271362 -0.0192967826535\natom 12.661965991 1.19502446714 1.1691448209 H 0.104980830833 0.0 -0.00448104672571 -0.00638001418343 -0.00747636563225\natom -12.9307322131 0.525058551796 0.728011456903 H 0.105781040833 0.0 0.00766470653545 2.474313253e-05 0.00237591797661\nenergy -381.611525444\ncharge  -0.0\nend\n"
  },
  {
    "path": "examples/nnp-predict/Carbon_chain_4G/input.nn",
    "content": "################################################################################\n### This is the input file for n2p2\n### It contains only a subset of all keywords\n################################################################################\n\n################################################################################\n### general keywords\n################################################################################\n\nnnp_generation 4\nuse_short_forces\n\nnumber_of_elements 2\nelements  C H\n\ninitial_hardness H 10.0\ninitial_hardness C 10.0\n\nfixed_gausswidth H 0.585815056466\nfixed_gausswidth C 1.379499971678\n\natom_energy H -0.458907306351869\natom_energy C -37.748111931202914\n\nscreen_electrostatics 4.8 8.0\n\nrandom_seed 12346\n\newald_truncation_error_method 1\newald_prec 1.e-5 0.16\n\n################################################################################\n### NN structure of the short-range NN\n################################################################################\nglobal_hidden_layers_short 2\nglobal_nodes_short 15 15\nglobal_activation_short t t l\n\n################################################################################\n### NN structure of the electrostatic NN\n################################################################################\nglobal_hidden_layers_electrostatic 2\nglobal_nodes_electrostatic 15 15\nglobal_activation_electrostatic t t l\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (General)\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10              # Number of training epochs.\nupdater_type                    1               # Weight update method\n                                                # (0 = Gradient Descent,\n                                                # 1 = Kalman filter).\nparallel_mode                   1               # Training parallelization used\n                                                # (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1               # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0               # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  0               # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                        # Keep symmetry function results in memory.\nrmse_threshold_trials           3               # Maximum number of RMSE threshold trials.\nmain_error_metric               RMSEpa          # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\ntest_fraction                   0.1             # Fraction of structures kept for testing.\nweights_min                     -1.0            # Minimum value for initial random weights.\nweights_max                     1.0             # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\nwrite_weights_epoch             1               # Write weights every this many epochs.\nscale_symmetry_functions\ncenter_symmetry_functions\n#write_neuronstats               1              # Write neuron statistics every this many epochs.\n#write_trainlog                                 # Write training log file.\n\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (charges, stage 1)\n################################################################################\ntask_batch_size_charge          1\n#nguyen_widrow_weights_charge                   # Initialize neural network weights according to Nguyen-Widrow scheme.\ncharge_fraction                 1.000\n#write_traincharges              1              # Write charge comparison. Can produce large files.\n#use_old_weights_charge                         # Restart fitting with old weight parameters.\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (short-range, stage 2)\n################################################################################\ntask_batch_size_energy          1               # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1               # Number of force update candidates prepared per task for each update (0 = Entire training set).\nforce_weight                    10.0            # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000           # Fraction of energy updates per epoch.\nshort_force_fraction            0.025           # Fraction of force updates per epoch.\n#short_energy_error_threshold    0.80           # RMSE threshold for energy update candidates.\n#short_force_error_threshold     0.80           # RMSE threshold for force update candidates.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\n#repeated_energy_update\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               0               # Write energy comparison every this many epochs.\nwrite_trainforces               0               # Write force comparison every this many epochs.\n\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\n#kalman_lambda_short 0.98000                    # Only for fading memory Kalman filter\n#kalman_nue_short 0.99870\n\nkalman_type                     0               # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2          # General Kalman filter parameter epsilon, covariance matrix initialization (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01            # General Kalman filter parameter q0, initial process noise (\"large\").\nkalman_qtau                     2.302           # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6          # General Kalman filter parameter qmin, final process noise (typ. 1.0E-6).\nkalman_eta                      0.001           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302           # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0             # Standard Kalman filter parameter etamax (1.0+).\n\n\n################################################################################\n### symmetry function definitions (all modes):\n################################################################################\ncutoff_type 2\n\n# radial H H\nsymfunction H  2  H 0.000000  0.000000  8.000000\nsymfunction H  2  H 0.006000  0.000000  8.000000\nsymfunction H  2  H 0.011000  0.000000  8.000000\nsymfunction H  2  H 0.018000  0.000000  8.000000\nsymfunction H  2  H 0.026000  0.000000  8.000000\nsymfunction H  2  H 0.035000  0.000000  8.000000\n\n#radial C H\nsymfunction C  2  H 0.000000  0.000000  8.000000\nsymfunction C  2  H 0.013000  0.000000  8.000000\nsymfunction C  2  H 0.029000  0.000000  8.000000\nsymfunction C  2  H 0.054000  0.000000  8.000000\nsymfunction C  2  H 0.093000  0.000000  8.000000\nsymfunction C  2  H 0.161000  0.000000  8.000000\n\nsymfunction H  2  C 0.000000  0.000000  8.000000\nsymfunction H  2  C 0.013000  0.000000  8.000000\nsymfunction H  2  C 0.029000  0.000000  8.000000\nsymfunction H  2  C 0.054000  0.000000  8.000000\nsymfunction H  2  C 0.093000  0.000000  8.000000\nsymfunction H  2  C 0.161000  0.000000  8.000000\n\n# radial C C\nsymfunction C  2  C 0.000000  0.000000  8.000000\nsymfunction C  2  C 0.010000  0.000000  8.000000\nsymfunction C  2  C 0.023000  0.000000  8.000000\nsymfunction C  2  C 0.041000  0.000000  8.000000\nsymfunction C  2  C 0.065000  0.000000  8.000000\nsymfunction C  2  C 0.103000  0.000000  8.000000\n\n# angular\n\nsymfunction C  3  C  C 0.0   1.0  1.0  8.000000\nsymfunction C  3  C  C 0.0   1.0  2.0  8.000000\nsymfunction C  3  C  C 0.0   1.0  4.0  8.000000\nsymfunction C  3  C  C 0.0   1.0  8.0  8.000000\nsymfunction C  3  C  C 0.0  -1.0  1.0  8.000000\nsymfunction C  3  C  C 0.0  -1.0  2.0  8.000000\nsymfunction C  3  C  C 0.0  -1.0  4.0  8.000000\nsymfunction C  3  C  C 0.0  -1.0  8.0  8.000000\n\nsymfunction C  3  H  H 0.0   1.0  1.0  8.000000\nsymfunction C  3  H  H 0.0   1.0  2.0  8.000000\nsymfunction C  3  H  H 0.0   1.0  4.0  8.000000\nsymfunction C  3  H  H 0.0   1.0  8.0  8.000000\nsymfunction C  3  H  H 0.0  -1.0  1.0  8.000000\nsymfunction C  3  H  H 0.0  -1.0  2.0  8.000000\nsymfunction C  3  H  H 0.0  -1.0  4.0  8.000000\nsymfunction C  3  H  H 0.0  -1.0  8.0  8.000000\n\nsymfunction C  3  C  H 0.0   1.0  1.0  8.000000\nsymfunction C  3  C  H 0.0   1.0  2.0  8.000000\nsymfunction C  3  C  H 0.0   1.0  4.0  8.000000\nsymfunction C  3  C  H 0.0   1.0  8.0  8.000000\nsymfunction C  3  C  H 0.0  -1.0  1.0  8.000000\nsymfunction C  3  C  H 0.0  -1.0  2.0  8.000000\nsymfunction C  3  C  H 0.0  -1.0  4.0  8.000000\nsymfunction C  3  C  H 0.0  -1.0  8.0  8.000000\n\n\nsymfunction H  3  C  C 0.0   1.0  1.0  8.000000\nsymfunction H  3  C  C 0.0   1.0  2.0  8.000000\nsymfunction H  3  C  C 0.0   1.0  4.0  8.000000\nsymfunction H  3  C  C 0.0   1.0  8.0  8.000000\nsymfunction H  3  C  C 0.0  -1.0  1.0  8.000000\nsymfunction H  3  C  C 0.0  -1.0  2.0  8.000000\n#symfunction H 3  C  C 0.0  -1.0  4.0  8.000000\n#symfunction H 3  C  C 0.0  -1.0  8.0  8.000000\n\nsymfunction H  3  H  C 0.0   1.0  1.0  8.000000\nsymfunction H  3  H  C 0.0   1.0  2.0  8.000000\nsymfunction H  3  H  C 0.0   1.0  4.0  8.000000\nsymfunction H  3  H  C 0.0   1.0  8.0  8.000000\nsymfunction H  3  H  C 0.0  -1.0  1.0  8.000000\nsymfunction H  3  H  C 0.0  -1.0  2.0  8.000000\n#symfunction H 3  H  C 0.0  -1.0  4.0  8.000000\n#symfunction H 3  H  C 0.0  -1.0  8.0  8.000000\n\n"
  },
  {
    "path": "examples/nnp-predict/Carbon_chain_4G/scaling.data",
    "content": "   1    1        0.000000000       0.168474325       0.051436597\n   1    2        0.304058579       0.417104776       0.345915594\n   1    3        0.000000000       0.159465228       0.047693255\n   1    4        0.000000000       0.152326768       0.044784312\n   1    5        0.270367239       0.377289298       0.312242885\n   1    6        0.000000000       0.142866546       0.041009575\n   1    7        0.000000000       0.132772126       0.037086368\n   1    8        0.236241291       0.336573119       0.278003131\n   1    9        0.000000000       0.122265892       0.033122717\n   1   10        0.194043783       0.286076543       0.235857711\n   1   11        0.146413959       0.230979612       0.188000406\n   1   12        0.094328785       0.167444236       0.133300930\n   1   13        0.000000000       0.003940598       0.000766277\n   1   14        0.000000000       0.002179848       0.000395242\n   1   15        0.000000000       0.022615147       0.006688070\n   1   16        0.006799063       0.014786064       0.009854503\n   1   17        0.000000000       0.000754211       0.000118471\n   1   18        0.000000000       0.000307111       0.000031177\n   1   19        0.000000000       0.020171446       0.006040265\n   1   20        0.006447566       0.012997039       0.009490438\n   1   21        0.000000000       0.016749223       0.005002441\n   1   22        0.005799086       0.011113091       0.008844953\n   1   23        0.000000000       0.012662314       0.003565243\n   1   24        0.004417978       0.011019545       0.007821957\n   2    1        0.000000000       0.528085920       0.086499956\n   2    2        0.243551003       0.576397651       0.478191952\n   2    3        0.220486953       0.527469369       0.437635603\n   2    4        0.000000000       0.503534550       0.078079729\n   2    5        0.195097154       0.473305655       0.392510705\n   2    6        0.000000000       0.474879557       0.069517706\n   2    7        0.166254512       0.411783730       0.340934855\n   2    8        0.000000000       0.433337270       0.058978785\n   2    9        0.136220939       0.347964660       0.286400724\n   2   10        0.000000000       0.375671652       0.047011546\n   2   11        0.101581283       0.273092311       0.221977741\n   2   12        0.000000000       0.292877983       0.033333347\n   2   13        0.000000000       0.015267809       0.000607918\n   2   14        0.000000000       0.020367325       0.002323101\n   2   15        0.000000000       0.006658033       0.003990472\n   2   16        0.000000000       0.009284484       0.000324103\n   2   17        0.000000000       0.024985840       0.002803020\n   2   18        0.003522361       0.012523471       0.008029970\n   2   19        0.000000000       0.011921850       0.000429967\n   2   20        0.000000000       0.015558424       0.002023934\n   2   21        0.000000000       0.006518589       0.003941639\n   2   22        0.000000000       0.003823383       0.000146152\n   2   23        0.000000000       0.023446294       0.002503853\n   2   24        0.003512986       0.012433317       0.007981137\n   2   25        0.000000000       0.008678726       0.000229107\n   2   26        0.000000000       0.010714201       0.001695750\n   2   27        0.000000000       0.006384431       0.003878387\n   2   28        0.000000000       0.001758371       0.000060041\n   2   29        0.000000000       0.021095757       0.002319082\n   2   30        0.003504699       0.012339772       0.007947861\n   2   31        0.000000000       0.004699984       0.000069193\n   2   32        0.000000000       0.010701233       0.001357400\n   2   33        0.000000000       0.006338867       0.003757820\n   2   34        0.000000000       0.000942648       0.000023014\n   2   35        0.000000000       0.017137757       0.002111679\n   2   36        0.003476868       0.012155470       0.007883155\n       -0.2691374625       -0.2381480047\n"
  },
  {
    "path": "examples/nnp-predict/Carbon_chain_4G/weights.001.data",
    "content": "     -1.4888017024\n     -1.0017511436\n     -1.1705029344\n      0.6414103790\n      0.2140403300\n     -0.1026432602\n     -0.0174383388\n      0.3331085986\n      0.3793430722\n     -0.3303750465\n      1.4789792152\n     -0.8809387034\n     -0.7433616539\n      1.9484973301\n      0.3899739566\n     -1.5454192398\n     -0.9055489974\n     -0.8277917923\n     -0.5777927282\n     -0.5223132192\n     -0.8810762974\n     -0.1101163560\n     -0.1533430498\n     -0.2377377963\n      0.2138962565\n     -0.0132007576\n      0.4904505541\n     -0.0335941714\n     -0.3806985032\n     -0.5236784919\n     -0.6209355724\n     -0.1368801342\n     -0.0088625262\n     -0.3759965136\n     -0.0733722403\n     -0.0012326042\n     -0.1624516438\n     -0.0273982461\n      0.3317405833\n      0.2815090995\n      0.1875439696\n      0.6260027685\n      0.5215529418\n     -0.5322396567\n      0.3446091767\n      0.0347493778\n     -0.4563104126\n      0.1104412679\n     -0.1347965805\n     -0.5622254472\n      0.3871238242\n      0.3362064347\n      0.1822209069\n     -0.3223321905\n      0.0701017737\n      0.3762275128\n      0.3961039164\n      0.4778753236\n     -0.5685960130\n      0.4814378311\n      0.1993690095\n     -0.1235293614\n      0.2910057032\n     -0.9505893382\n      0.2692414487\n      0.6278566042\n      0.1037176712\n      0.4841582715\n     -0.1892464641\n      0.9434407586\n     -0.6178794870\n      0.9091361754\n      1.1933435533\n     -1.4155870671\n     -0.1189239170\n      0.7269244449\n      0.2703700120\n     -0.1793085568\n      0.1248321810\n      0.2106361067\n      0.8806724501\n      0.4276010456\n      0.4776106525\n      0.0506541684\n     -0.1786751640\n     -0.0763037363\n     -0.3420462616\n     -0.1143970958\n      0.3704849225\n      1.5066744083\n     -0.2367170132\n     -0.1457966423\n     -0.0308319311\n     -0.2730000774\n      0.6488153491\n      0.8879587482\n      0.2063419313\n      0.0122982782\n      0.4502714143\n      0.1871250710\n     -0.2165619759\n     -0.0435890354\n     -0.5560803877\n      1.4521312199\n      0.2342364551\n      0.7601873569\n     -0.1991963220\n      0.2642172811\n      0.1158846780\n      1.1960869146\n     -1.0889586625\n     -0.8817908502\n      0.3506735846\n     -0.8351667224\n     -0.9248840778\n     -0.5400175749\n      0.4998695561\n     -0.3882540978\n     -0.3622393196\n     -0.6569324324\n      0.0363303904\n      0.5447484487\n     -0.7338996921\n     -0.0781323293\n      0.2238236356\n     -0.9167299330\n      0.4580166800\n      0.0143999708\n      0.5247884201\n     -1.0815517756\n      0.0402330966\n      0.1056890409\n     -0.0094211343\n     -0.0013035368\n      0.4797689057\n      0.5187854610\n      0.5723168941\n     -0.1819713182\n      0.4015321816\n     -0.1681640071\n      0.5301870488\n      0.0931431814\n      0.0290987728\n      0.4205243136\n      0.4264724644\n     -0.6957253717\n      0.1909090918\n      0.3581991152\n     -0.1416601912\n     -0.1123970840\n     -0.1314235841\n      0.1688318613\n     -0.1379177947\n      0.3532596357\n     -0.6704295045\n     -0.2946578835\n     -0.1720089868\n     -0.1537416401\n     -0.2688881698\n     -0.3799738100\n     -0.7106331481\n      0.4367219986\n      0.5855889382\n     -0.3899779563\n     -0.2792952026\n     -1.5245808139\n     -0.5513806266\n      0.8692974234\n     -0.2741632804\n     -0.6062190375\n     -0.3604725451\n      0.3259486516\n      0.3363966232\n     -0.0442549617\n     -0.0188410038\n      0.6462078306\n     -0.1180726862\n      0.3669540581\n      0.3128139913\n      0.0581398132\n      0.1778325171\n      0.0148846415\n     -0.4429995921\n      0.2390172381\n     -0.1331025880\n     -0.6024920452\n      0.5117700657\n     -0.2691642687\n     -0.2315779607\n     -0.3163003641\n     -0.0127591756\n     -0.4391654338\n     -0.3925018208\n     -0.4744533821\n     -0.2107614189\n      0.0018311472\n      0.0994113312\n     -0.3325323373\n     -0.0877343069\n     -0.0968864505\n      0.6322296571\n     -0.6009314321\n      0.5239541145\n      0.4070156005\n     -0.2424100255\n      0.1701964662\n     -0.1891924004\n     -0.1725962288\n     -0.7454897924\n     -0.5669621459\n      0.1908183223\n      0.1942187055\n      0.0604871372\n     -0.2492556116\n     -0.0385591976\n     -0.4468781371\n     -0.5177978893\n     -0.4064720805\n     -0.1066245329\n     -0.0948811797\n      0.1951580772\n     -0.4209040086\n      0.3766356111\n     -0.3915380758\n     -0.0757449805\n      0.1359964622\n     -0.3250915212\n      0.0933939924\n      1.1579791964\n      0.0838738469\n      0.2034585376\n     -0.1635881649\n     -0.1456949933\n     -0.3592021673\n      0.2137216945\n      0.8663164242\n     -0.5406019849\n      0.5695388479\n     -0.5641558406\n     -0.5315446888\n      0.1534782506\n      0.1169388218\n      0.5654266064\n      1.0147237347\n      1.3732022653\n      0.6500158986\n      1.1632835797\n     -0.5884712191\n      0.2854592057\n     -0.7358820889\n     -1.4883158150\n     -1.4659492093\n      0.6832997457\n     -0.8368397154\n     -1.1717355422\n     -1.1242763048\n      0.8232282353\n      1.0516581383\n     -1.2828360647\n     -0.6386923945\n     -0.1513156265\n     -0.9376289558\n      1.3851629835\n      0.8867636168\n      0.7387855490\n     -0.8683467466\n     -0.4716412042\n     -0.6897128476\n      0.4095249979\n      0.5762449737\n     -0.2665504893\n      0.3188790824\n      0.1051138437\n      0.6889232475\n      0.9968166073\n      1.1289109944\n      0.6421847440\n      0.6455952692\n     -1.3277342307\n      0.6607803174\n      0.3282420919\n     -0.6982637371\n      0.6609483163\n      0.3439666041\n     -0.3715966414\n      0.0159730175\n     -0.1205577528\n      1.0197327655\n     -1.3260767632\n      0.4947942862\n     -0.1771262309\n      0.2152509228\n      0.7073444199\n      0.4952289425\n     -0.3648873709\n     -0.6717529937\n     -0.8970037869\n     -0.3106776487\n      1.4756607507\n      1.3109554608\n      0.7761662035\n      0.2478030259\n      0.7158647333\n     -0.9846390602\n     -0.2666931357\n      0.7091981268\n     -0.5826017017\n     -0.5602419898\n      0.7390021308\n     -0.5504342883\n     -0.1375936285\n     -0.4514210761\n      0.2099406133\n      0.2125369737\n     -0.2521348016\n     -0.0029157092\n      0.4677337161\n      0.1809599129\n      1.0144127591\n      0.3451893959\n     -0.6337317414\n     -0.0508060743\n     -0.3488065093\n     -0.5868150461\n     -0.4057516293\n     -0.5513580134\n     -0.5037365214\n      1.0618947134\n     -0.4053124485\n     -0.1073099713\n     -0.1983561674\n      0.9143174940\n      0.3711851453\n      0.1675915481\n      0.9442410385\n      1.4169059444\n      0.8964498483\n      0.6351748598\n      0.3771924872\n      0.1182449734\n      0.5090113687\n      0.6708904047\n     -0.8270112269\n     -0.5649866970\n     -0.4874200759\n     -0.3287438684\n      0.3092346389\n     -0.2279650134\n     -0.4421639806\n      0.4831869975\n     -0.7094794603\n      0.1960570902\n     -0.4975532963\n     -0.9423000986\n      1.0156191991\n      0.0337459525\n      0.4260312858\n     -0.0937523612\n     -0.0741517372\n     -0.7627368761\n     -0.0551132364\n     -1.2669094800\n      1.5714913564\n     -0.4710485224\n      0.3959194509\n     -1.4738849406\n      0.6445191585\n      0.6742980006\n     -0.0153435455\n     -0.1322922446\n     -0.1080074201\n      0.2635518470\n      0.0378352369\n      0.0536731840\n      0.0140530090\n     -0.2031779658\n     -0.0237474741\n      0.0096196990\n      0.2266015533\n     -0.0147361168\n     -0.1884361464\n"
  },
  {
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  },
  {
    "path": "examples/nnp-predict/Carbon_chain_4G/weightse.006.data",
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  },
  {
    "path": "examples/nnp-predict/Cu2S_PBE/input.data",
    "content": "begin\ncomment source_file_name=OUTCAR_0_1\nlattice 15.246000000 0.000000000 0.000000000\nlattice 0.000000000 11.884000000 0.000000000\nlattice -5.989357159 0.000000000 12.091965796\natom 9.55381 0.98518 10.18385 S 0.0 0.0 -0.125331 0.028415 0.031193\natom -3.29184 6.92718 7.95410 S 0.0 0.0 0.125331 0.028415 -0.031193\natom -0.29717 10.89882 1.90811 S 0.0 0.0 0.125331 -0.028415 -0.031193\natom 12.54849 4.95682 4.13787 S 0.0 0.0 -0.125331 -0.028415 0.031193\natom 12.27754 0.91269 4.18624 S 0.0 0.0 -0.126394 -0.041931 0.027223\natom -0.02622 6.85469 1.85974 S 0.0 0.0 0.126394 -0.041931 -0.027223\natom -3.02090 10.97131 7.90573 S 0.0 0.0 0.126394 0.041931 -0.027223\natom 9.28287 5.02931 10.23222 S 0.0 0.0 -0.126394 0.041931 0.027223\natom 9.06992 0.97924 6.12821 S 0.0 0.0 -0.013446 -0.068418 -0.051411\natom -2.80795 6.92124 12.00974 S 0.0 0.0 0.013446 -0.068418 0.051411\natom 0.18673 10.90476 5.96376 S 0.0 0.0 0.013446 0.068418 0.051411\natom 12.06460 4.96276 0.08223 S 0.0 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5.76303 S 0.0 0.0 -0.063213 -0.002445 -0.183871\natom 12.10239 8.77515 0.28295 S 0.0 0.0 0.063213 -0.002445 0.183871\natom 9.10771 9.05085 6.32893 S 0.0 0.0 0.063213 0.002445 0.183871\natom -2.84574 3.10885 11.80901 S 0.0 0.0 -0.063213 0.002445 -0.183871\natom -0.06140 2.76184 1.61065 S 0.0 0.0 0.033374 -0.217794 -0.226789\natom 12.31272 8.70384 4.43533 S 0.0 0.0 -0.033374 -0.217794 0.226789\natom 9.31804 9.12216 10.48132 S 0.0 0.0 -0.033374 0.217794 0.226789\natom -3.05608 3.18016 7.65663 S 0.0 0.0 0.033374 0.217794 -0.226789\natom 11.42708 2.96625 3.53932 Cu 0.0 0.0 -0.056517 -0.018383 -0.066026\natom 0.82424 8.90825 2.50666 Cu 0.0 0.0 0.056517 -0.018383 0.066026\natom -2.17044 8.91775 8.55265 Cu 0.0 0.0 0.056517 0.018383 0.066026\natom 8.43240 2.97575 9.58530 Cu 0.0 0.0 -0.056517 0.018383 -0.066026\natom 5.35651 0.87942 8.18021 Cu 0.0 0.0 -0.068978 -0.042620 0.067357\natom 0.90546 6.82142 9.95773 Cu 0.0 0.0 0.068978 -0.042620 -0.067357\natom 3.90014 11.00458 3.91175 Cu 0.0 0.0 0.068978 0.042620 -0.067357\natom 8.35119 5.06258 2.13423 Cu 0.0 0.0 -0.068978 0.042620 0.067357\natom 8.29869 1.08857 2.02782 Cu 0.0 0.0 -0.013003 -0.079744 -0.061412\natom 3.95263 7.03057 4.01816 Cu 0.0 0.0 0.013003 -0.079744 0.061412\natom 0.95795 10.79543 10.06414 Cu 0.0 0.0 0.013003 0.079744 0.061412\natom 5.30402 4.85343 8.07381 Cu 0.0 0.0 -0.013003 0.079744 -0.061412\natom 5.09343 2.85216 0.88392 Cu 0.0 0.0 -0.071088 -0.013473 -0.002685\natom 7.15789 8.79416 5.16206 Cu 0.0 0.0 0.071088 -0.013473 0.002685\natom 4.16322 9.03184 11.20804 Cu 0.0 0.0 0.071088 0.013473 0.002685\natom 2.09875 3.08984 6.92991 Cu 0.0 0.0 -0.071088 0.013473 -0.002685\natom -3.71515 1.00895 11.42812 Cu 0.0 0.0 0.067641 0.039805 0.039650\natom 9.97712 6.95095 6.70983 Cu 0.0 0.0 -0.067641 0.039805 -0.039650\natom 12.97179 10.87505 0.66385 Cu 0.0 0.0 -0.067641 -0.039805 -0.039650\natom -0.72047 4.93305 5.38213 Cu 0.0 0.0 0.067641 -0.039805 0.039650\natom -1.02899 0.93052 5.35553 Cu 0.0 0.0 0.007293 -0.021110 -0.015108\natom 13.28031 6.87252 0.69045 Cu 0.0 0.0 -0.007293 -0.021110 0.015108\natom 10.28563 10.95348 6.73643 Cu 0.0 0.0 -0.007293 0.021110 0.015108\natom -4.02367 5.01148 11.40151 Cu 0.0 0.0 0.007293 0.021110 -0.015108\natom 8.30415 1.46530 11.99886 Cu 0.0 0.0 -0.140674 0.136237 -0.040072\natom -2.04218 7.40730 6.13909 Cu 0.0 0.0 0.140674 0.136237 0.040072\natom 0.95249 10.41870 0.09311 Cu 0.0 0.0 0.140674 -0.136237 0.040072\natom 11.29883 4.47670 5.95287 Cu 0.0 0.0 -0.140674 -0.136237 -0.040072\natom 11.29861 1.67802 6.16569 Cu 0.0 0.0 0.015271 0.116590 -0.074616\natom -5.03665 7.62002 11.97226 Cu 0.0 0.0 -0.015271 0.116590 0.074616\natom -2.04197 10.20598 5.92627 Cu 0.0 0.0 -0.015271 -0.116590 0.074616\natom 14.29329 4.26398 0.11971 Cu 0.0 0.0 0.015271 -0.116590 -0.074616\natom 9.14880 2.97575 4.96859 Cu 0.0 0.0 0.164959 0.084500 0.087098\natom 3.10252 8.91775 1.07739 Cu 0.0 0.0 -0.164959 0.084500 -0.087098\natom 0.10784 8.90825 7.12338 Cu 0.0 0.0 -0.164959 -0.084500 -0.087098\natom 6.15412 2.96625 11.01457 Cu 0.0 0.0 0.164959 -0.084500 0.087098\natom 1.15360 1.75527 11.30357 Cu 0.0 0.0 -0.063629 0.156987 0.058610\natom 5.10836 7.69727 6.83438 Cu 0.0 0.0 0.063629 0.156987 -0.058610\natom 8.10304 10.12873 0.78840 Cu 0.0 0.0 0.063629 -0.156987 -0.058610\natom 4.14828 4.18673 5.25759 Cu 0.0 0.0 -0.063629 -0.156987 0.058610\natom 3.85752 1.46054 5.30595 Cu 0.0 0.0 0.025586 0.159786 -0.058692\natom 8.39380 7.40254 0.74003 Cu 0.0 0.0 -0.025586 0.159786 0.058692\natom 5.39912 10.42346 6.78601 Cu 0.0 0.0 -0.025586 -0.159786 0.058692\natom 0.86284 4.48146 11.35194 Cu 0.0 0.0 0.025586 -0.159786 -0.058692\natom -1.16473 2.80106 10.28664 Cu 0.0 0.0 0.114949 0.029868 0.062123\natom 7.42669 8.74306 7.85131 Cu 0.0 0.0 -0.114949 0.029868 -0.062123\natom 10.42137 9.08294 1.80533 Cu 0.0 0.0 -0.114949 -0.029868 -0.062123\natom 1.82995 3.14094 4.24065 Cu 0.0 0.0 0.114949 -0.029868 0.062123\natom 8.42471 0.42545 8.25881 Cu 0.0 0.0 -0.006801 -0.023883 -0.023161\natom -2.16275 6.36745 9.87914 Cu 0.0 0.0 0.006801 -0.023883 0.023161\natom 0.83193 11.45855 3.83315 Cu 0.0 0.0 0.006801 0.023883 0.023161\natom 11.41939 5.51655 2.21283 Cu 0.0 0.0 -0.006801 0.023883 -0.023161\natom 10.93680 0.74156 2.02057 Cu 0.0 0.0 -0.002607 0.001704 -0.015858\natom 1.31453 6.68356 4.02542 Cu 0.0 0.0 0.002607 0.001704 0.015858\natom -1.68015 11.14244 10.07140 Cu 0.0 0.0 0.002607 -0.001704 0.015858\natom 7.94212 5.20044 8.06655 Cu 0.0 0.0 -0.002607 -0.001704 -0.015858\natom -4.22706 2.43028 9.33742 Cu 0.0 0.0 -0.057628 -0.032284 0.078709\natom 10.48903 8.37228 8.80053 Cu 0.0 0.0 0.057628 -0.032284 -0.078709\natom 13.48370 9.45372 2.75455 Cu 0.0 0.0 0.057628 0.032284 -0.078709\natom -1.23238 3.51172 3.29143 Cu 0.0 0.0 -0.057628 0.032284 0.078709\natom 5.96526 0.94478 3.42686 Cu 0.0 0.0 -0.017114 0.034111 0.052038\natom 6.28607 6.88678 2.61912 Cu 0.0 0.0 0.017114 0.034111 -0.052038\natom 3.29139 10.93922 8.66510 Cu 0.0 0.0 0.017114 -0.034111 -0.052038\natom 2.97058 4.99722 9.47285 Cu 0.0 0.0 -0.017114 -0.034111 0.052038\natom 0.87597 0.51577 7.53329 Cu 0.0 0.0 -0.012110 -0.004506 0.081390\natom 5.38599 6.45777 10.60465 Cu 0.0 0.0 0.012110 -0.004506 -0.081390\natom 8.38067 11.36823 4.55867 Cu 0.0 0.0 0.012110 0.004506 -0.081390\natom 3.87065 5.42623 1.48731 Cu 0.0 0.0 -0.012110 0.004506 0.081390\natom 3.84806 0.51220 1.61911 Cu 0.0 0.0 0.106207 0.025692 0.047083\natom 8.40327 6.45420 4.42687 Cu 0.0 0.0 -0.106207 0.025692 -0.047083\natom 5.40859 11.37180 10.47285 Cu 0.0 0.0 -0.106207 -0.025692 -0.047083\natom 0.85338 5.42980 7.66510 Cu 0.0 0.0 0.106207 -0.025692 0.047083\natom 3.47571 2.47425 9.12097 Cu 0.0 0.0 0.013369 -0.021692 -0.063355\natom 2.78626 8.41625 9.01698 Cu 0.0 0.0 -0.013369 -0.021692 0.063355\natom 5.78094 9.40975 2.97100 Cu 0.0 0.0 -0.013369 0.021692 0.063355\natom 6.47038 3.46775 3.07499 Cu 0.0 0.0 0.013369 0.021692 -0.063355\natom 13.93651 1.01727 2.61912 Cu 0.0 0.0 0.070095 0.058281 0.058871\natom -1.68519 6.95927 3.42686 Cu 0.0 0.0 -0.070095 0.058281 -0.058871\natom -4.67987 10.86673 9.47285 Cu 0.0 0.0 -0.070095 -0.058281 -0.058871\natom 10.94183 4.92473 8.66510 Cu 0.0 0.0 0.070095 -0.058281 0.058871\natom 3.78523 1.22643 11.52485 Cu 0.0 0.0 -0.055512 0.072701 0.045980\natom 2.47674 7.16843 6.61310 Cu 0.0 0.0 0.055512 0.072701 -0.045980\natom 5.47141 10.65757 0.56711 Cu 0.0 0.0 0.055512 -0.072701 -0.045980\natom 6.77991 4.71557 5.47887 Cu 0.0 0.0 -0.055512 -0.072701 0.045980\natom 7.33923 2.31025 6.84284 Cu 0.0 0.0 0.008001 0.031273 -0.008244\natom -1.07727 8.25225 11.29511 Cu 0.0 0.0 -0.008001 0.031273 0.008244\natom 1.91741 9.57375 5.24912 Cu 0.0 0.0 -0.008001 -0.031273 0.008244\natom 10.33391 3.63175 0.79686 Cu 0.0 0.0 0.008001 -0.031273 -0.008244\natom 2.25458 2.45880 1.69046 Cu 0.0 0.0 0.009284 0.010061 0.048810\natom 9.99674 8.40080 4.35553 Cu 0.0 0.0 -0.009284 0.010061 -0.048810\natom 7.00207 9.42520 10.40151 Cu 0.0 0.0 -0.009284 -0.010061 -0.048810\natom -0.74010 3.48320 7.73644 Cu 0.0 0.0 0.009284 -0.010061 0.048810\natom -2.07320 1.14799 8.21165 Cu 0.0 0.0 0.008891 0.031001 0.014345\natom 8.33516 7.08999 9.92629 Cu 0.0 0.0 -0.008891 0.031001 -0.014345\natom 11.32984 10.73601 3.88031 Cu 0.0 0.0 -0.008891 -0.031001 -0.014345\natom 0.92148 4.79401 2.16567 Cu 0.0 0.0 0.008891 -0.031001 0.014345\nenergy -573.700369\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/nnp-predict/Cu2S_PBE/input.nn",
    "content": "###############################################################################\n# HDNNP for copper sulfide Cu2S\n###############################################################################\n# Length unit     : Angstrom\n# Energy unit     : eV\n# Reference method: PBE\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.8640662064628053E+00\nconv_energy   7.3890846653659121E+00\nconv_length   6.1376931796181502E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type.\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n"
  },
  {
    "path": "examples/nnp-predict/Cu2S_PBE/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   9.1739161189824411E-08   7.0593095050533450E-01   2.2372649929284196E-02   9.6379208796011293E-02\n         1          2   2.6433999906765265E-01   2.4749666370750676E+00   1.0378805142792313E+00   1.9413782463770093E-01\n         1          3   1.5504686427401054E-05   1.4168627312588329E+00   5.5254915214857578E-02   2.1495058826125538E-01\n         1          4   1.4086411910634238E+00   4.7388215758712082E+00   3.1031877925923803E+00   3.5864448236496921E-01\n         1          5   9.8043626772015909E-04   1.9535901883323099E+00   1.1429456309160095E-01   2.2901461288065855E-01\n         1          6   2.2158364445227399E+00   6.0748308460582043E+00   3.8835182764170546E+00   3.9299243538518969E-01\n         1          7   1.0255080523534783E+00   5.1401074554660049E+00   2.5810215644603796E+00   4.3835591238870431E-01\n         1          8   4.8489829707261999E-03   3.9129781874325281E-01   4.7557455423079396E-02   2.7778419734655713E-02\n         1          9   9.3223803365223998E-02   2.8346930075434797E+00   6.0185719975366336E-01   3.1949957606875956E-01\n         1         10   6.7206749586119430E-01   4.4876923880381465E+00   2.1991872165248538E+00   4.1504796440380803E-01\n         1         11   2.2128378766968923E-02   8.6593017344520318E-01   1.4060436434125115E-01   7.5838421599526348E-02\n         1         12   8.4205124330445313E-01   7.0656885702864862E+00   2.9013712601439368E+00   7.3052821449417049E-01\n         1         13   1.4518778507164800E+00   9.6462711741708382E+00   4.3715329035264965E+00   8.3811671947643118E-01\n         1         14   2.4300884834352513E-06   5.3039215356450418E-02   2.8067394350178213E-04   1.6541693025921896E-03\n         1         15   4.3805855934107564E-04   3.3431366727997386E-01   1.5056637491023487E-02   3.6381498406602590E-02\n         1         16   1.8742403996648012E-02   5.3094282134884740E-01   1.9287359264197504E-01   5.3785992354357007E-02\n         1         17   5.6391705067135155E-03   2.7103176024192799E-01   3.6199336036120536E-02   2.2235092628611220E-02\n         1         18   5.8157340520125522E-01   3.0394483797974066E+00   1.5432926655352674E+00   2.9013849228704902E-01\n         1         19   3.5474335876025032E-01   2.8914948266501281E+00   1.2453633098426364E+00   2.6070492382053573E-01\n         1         20   1.3050150224953865E-03   2.0977615521049353E-01   1.6466279986318652E-02   1.6175233794254219E-02\n         1         21   3.3625763520090814E-02   1.6019727512861448E+00   2.6707302954572526E-01   1.9158906783856428E-01\n         1         22   3.5314748293148263E-01   2.5968432133168928E+00   1.2041087980295160E+00   2.3880745648555143E-01\n         1         23   5.6279184570511148E-03   4.8263719913200909E-01   4.8674878532957294E-02   4.5579012837321450E-02\n         1         24   3.5640890668898983E-01   3.9354254479681789E+00   1.3506519169134916E+00   4.3100694380807969E-01\n         1         25   7.1435545388184229E-01   5.4083380133399706E+00   2.3405335217844168E+00   4.7481787957091687E-01\n         1         26   6.0302894280955782E-07   2.4282702757490063E-02   1.0392381208153868E-04   6.9514343858439293E-04\n         1         27   1.4152015883516988E-04   1.8793440136817721E-01   6.7319944252965166E-03   1.8860146728064606E-02\n         1         28   7.6669273315039489E-03   2.8853650966579203E-01   9.6832241039761832E-02   2.8591400835791262E-02\n         1         29   1.4586287100215936E-03   1.2827520308122028E-01   1.2535333774723276E-02   1.2196652689168296E-02\n         1         30   2.4306078779227119E-01   1.5771292876622454E+00   7.3118666045976355E-01   1.6033491927751306E-01\n         1         31   1.5700215118676836E-01   1.4950427209078341E+00   6.2168623298528469E-01   1.3878720233016123E-01\n         1         32   8.0322135442977674E-08   9.1020506427165644E-03   1.1758299063219979E-04   7.2850621729108440E-04\n         1         33   3.8387499554503460E-05   4.6879099417593433E-02   2.2899299020297070E-03   6.3507919696978174E-03\n         1         34   2.5111603817039843E-07   2.6638155845094137E-02   3.5204871838944324E-04   2.1803344919789219E-03\n         1         35   7.8176366916082938E-04   1.2144199943350505E-01   1.0237823308897595E-02   1.5551953673898984E-02\n         1         36   6.0784771853405629E-03   1.5177813800129991E-01   4.5342256644197804E-02   1.4422755174681633E-02\n         1         37   6.5208235096380454E-08   6.8957085587219831E-03   8.4477914517405974E-05   5.1826403434160535E-04\n         1         38   5.1003186367566016E-04   3.3817704100212627E-02   5.0495259674331701E-03   4.2413701977289924E-03\n         1         39   3.0092380409832575E-01   3.9241027015819827E+00   1.6245850308330121E+00   3.6115017167195557E-01\n         1         40   2.9205060411645536E+00   2.0972699454192377E+01   1.0685030237788666E+01   1.8434608066664662E+00\n         1         41   5.8304225749625562E+00   3.3157582599900756E+01   1.6937338463410185E+01   2.8416990087236536E+00\n         1         42   2.8963706388516774E-01   3.4220973094358569E+00   1.3527222233246401E+00   2.9841578592458634E-01\n         1         43   3.3240856510350132E+00   1.9977206504626281E+01   1.0533032366441756E+01   1.8362183066460305E+00\n         1         44   5.5968160844972745E+00   2.9479500954936675E+01   1.4663357897716818E+01   2.4340402007751933E+00\n         1         45   7.3194532436105672E-02   1.4240027432637063E+00   4.6184059564430718E-01   1.0603619804309938E-01\n         1         46   7.4351404260172327E-01   6.1601360099088307E+00   3.0926623459215312E+00   5.2746971733324144E-01\n         1         47   1.0304047665725904E+00   9.5490875529313932E+00   4.6615470051220029E+00   8.8228607777747381E-01\n         1         48   5.3439780036913555E-02   6.0792049084128386E-01   2.0133541277710790E-01   4.7497199912796259E-02\n         1         49   1.0984946263275692E+00   5.3381605458179147E+00   2.9222626179881503E+00   4.9078113758325748E-01\n         1         50   9.3741001607568142E-01   6.0472356274080674E+00   2.8114797251218855E+00   5.0873676433244819E-01\n         1         51   1.1424085007079182E-01   2.3139492223359586E+00   7.5719953168832033E-01   2.0833570661709583E-01\n         1         52   1.4315113742496002E+00   1.3300925195398728E+01   5.8838374866614309E+00   1.2171600869775945E+00\n         1         53   3.5503714858105737E+00   2.1312715022502385E+01   1.0871674742056101E+01   1.8799426423890726E+00\n         1         54   1.0963309213378970E-01   2.0788696656585590E+00   6.3126459151902947E-01   1.7541529953806104E-01\n         1         55   1.6510272306266744E+00   1.2357046870783602E+01   5.7724472752012481E+00   1.1927743223366301E+00\n         1         56   3.3307522004182251E+00   1.8663597697385917E+01   9.2207406968320633E+00   1.5761279490996694E+00\n         1         57   2.7455727216146104E-02   9.1674320906634155E-01   2.1461170716720621E-01   6.1714021121502906E-02\n         1         58   3.6192386693953038E-01   3.8875893126984216E+00   1.7092032560335464E+00   3.4843371038350474E-01\n         1         59   5.6557210052590146E-01   6.1563972117346957E+00   2.9617726398537609E+00   5.9044611830216798E-01\n         1         60   2.0196364035104716E-02   3.3469617649847838E-01   9.3035775655912298E-02   2.7640180745065839E-02\n         1         61   5.5357670454431462E-01   3.1907980705952856E+00   1.5901399654465433E+00   3.0513520444755149E-01\n         1         62   5.3781344801473907E-01   3.6339755326587713E+00   1.6575261374157455E+00   3.1383714619102349E-01\n         1         63   9.6664268597268675E-05   1.4867672619417913E-01   4.3177785208556420E-03   8.2707901241799234E-03\n         1         64   1.2006437712525238E-02   1.1332481089585240E+00   1.2838035367153358E-01   1.3388538744183132E-01\n         1         65   2.0772479772511018E-01   1.8626169502984133E+00   8.2255201121385824E-01   1.7849382645365078E-01\n         1         66   8.7907438908811975E-05   1.2622839046469150E-01   4.4000149614673457E-03   1.1827043706432264E-02\n         1         67   1.3369106385547676E-02   8.7813896596785235E-01   1.1827747851010054E-01   1.1347348778532439E-01\n         1         68   1.7657303404092337E-01   1.4295433698727396E+00   6.2121356605669209E-01   1.2933064669650537E-01\n         1         69   2.8597998667575309E-03   3.7304172172637867E-01   3.7665097851475426E-02   3.7208167402427196E-02\n         1         70   1.5902143209986809E-05   2.6009225424800504E-02   7.2450937404019229E-04   2.4859888979869879E-03\n         1         71   4.7171431923273572E-03   1.6025670770457742E-01   2.8821358718588475E-02   1.9416774232856850E-02\n         1         72   1.5331295649388408E-02   1.9310943777686740E-01   6.9677412943044442E-02   1.7784064753732315E-02\n         2          1   2.4721472942648627E-02   1.5073065774351924E+00   5.1894025713961534E-01   1.2292746613848948E-01\n         2          2   2.4966843476303169E-01   2.6917832996745195E+00   1.5515938962961904E+00   2.2894178892035891E-01\n         2          3   1.8582961795319244E-03   3.8171243121869747E+00   1.1221679663414206E+00   3.9926224172528085E-01\n         2          4   6.9308990079045429E-01   3.9421018903882858E+00   1.9417591382085293E+00   2.7982355416028953E-01\n         2          5   5.2213352864915873E-02   5.9786240694290029E+00   2.7894744649522680E+00   6.8818475947171043E-01\n         2          6   3.4706330958249576E-01   2.8061894414477742E+00   1.2905107822301898E+00   2.5049917129048904E-01\n         2          7   5.6650782795607790E-01   6.0129804050995874E+00   3.4024808580901604E+00   5.3817898895468230E-01\n         2          8   8.2160472578002200E-02   2.1591157175155038E+00   9.5893716661004147E-01   2.2068746057755104E-01\n         2          9   9.7533565633843480E-02   8.0520717520847240E-01   3.9574121682754421E-01   7.2843087896835634E-02\n         2         10   7.5624736998622447E-02   1.2151161903363619E+00   4.2414909548153323E-01   1.1030205700397629E-01\n         2         11   3.8590027688988915E-01   3.4170303616374733E+00   1.5389187655267780E+00   2.9839201545750010E-01\n         2         12   1.2653139464575366E-01   3.3448693047411142E+00   9.0701446886275106E-01   3.0808232807716252E-01\n         2         13   3.5754079396564345E-02   2.3051636092543291E+00   4.5165801949286744E-01   2.0529180913687342E-01\n         2         14   1.7360244301899754E+00   9.1860981352526956E+00   5.0318013545245659E+00   7.7006828863188448E-01\n         2         15   5.6096556948092302E-01   6.9184291400548386E+00   2.5593433032311834E+00   7.0382259666666958E-01\n         2         16   2.7321455653550736E-03   2.6718628880300366E-01   6.8392239083035003E-02   1.8417271845608391E-02\n         2         17   1.4998879259624551E-04   2.8869834404308442E-01   3.2421219256901605E-02   2.1462316150937667E-02\n         2         18   9.6976148378458242E-03   6.9986551977156553E-01   7.4501947267367571E-02   9.2109247490457000E-02\n         2         19   7.5554776729931772E-01   3.8650650491408283E+00   2.1261658860729638E+00   2.9459249679651817E-01\n         2         20   2.2984860438624041E-01   2.2399640197541903E+00   8.4832685420611464E-01   2.2013029667841760E-01\n         2         21   3.1742242534198488E-02   6.9305314098138393E-01   2.0239450285654340E-01   6.2019223320811959E-02\n         2         22   1.6267388613945685E-01   1.8982342788109985E+00   8.1342448996901984E-01   1.7017885772188068E-01\n         2         23   4.3623299253776143E-02   1.8524213261728384E+00   4.3372964228967342E-01   1.6475284995752615E-01\n         2         24   1.1782155855406862E-02   1.3256780035707432E+00   2.0203673375826020E-01   1.2375770385162231E-01\n         2         25   9.5572013219445029E-01   5.1585503300832807E+00   2.7312178298449119E+00   4.5027566865612645E-01\n         2         26   2.1346552007948805E-01   3.7560054368796258E+00   1.2309867059977997E+00   3.8895981570570448E-01\n         2         27   1.0778454975081308E-03   1.6230009416534466E-01   3.4353839552470775E-02   1.0338804556484340E-02\n         2         28   4.1455680376600344E-05   1.3561930079689324E-01   1.3464607540962245E-02   9.4307016558753589E-03\n         2         29   2.9811923400491925E-03   3.9674788724187127E-01   3.2946560522656709E-02   5.3575100644579036E-02\n         2         30   4.0860996892032608E-01   2.1541090596644543E+00   1.1291055145629398E+00   1.6554701558125592E-01\n         2         31   8.7689965003411183E-02   1.1196100344004409E+00   3.9704096379805787E-01   1.1606734505235136E-01\n         2         32   2.0029888316796539E-05   1.7556653440553127E-02   1.4233102888664287E-03   1.3598121443903737E-03\n         2         33   5.2716716179610746E-06   4.4644993845652417E-02   1.7086280138653978E-03   4.2643079956046579E-03\n         2         34   8.8339290835669212E-07   1.2139204575362132E-02   4.1922038284938451E-04   1.5155281653507265E-03\n         2         35   1.2653672947005059E+00   8.9337925904902882E+00   4.2637335795708999E+00   5.9362291906692699E-01\n         2         36   4.3025897744283652E+00   2.4744209023066571E+01   1.4272525712868205E+01   1.9700222663219151E+00\n         2         37   2.9677470818795189E+00   2.5847640450705327E+01   1.1788593731598802E+01   2.3639335745006553E+00\n         2         38   4.8673248345854536E-01   6.9220258514917292E+00   2.9410791137038919E+00   5.0416378898015868E-01\n         2         39   4.7312413761643519E+00   2.4784350068345699E+01   1.4182436900763136E+01   1.9734981280505293E+00\n         2         40   2.7914940844674572E+00   2.2909604188642842E+01   1.0258913931047273E+01   2.0538117984713926E+00\n         2         41   5.1976352609600407E-01   3.0581982698648895E+00   1.1910833091075925E+00   2.2566892125976182E-01\n         2         42   1.0695804209866875E+00   7.2313250376604037E+00   3.9928775708897235E+00   5.8095727320582324E-01\n         2         43   8.4628209088378592E-01   7.5313801441068913E+00   3.3982729265620653E+00   7.1123273080942895E-01\n         2         44   7.0763463381880415E-02   1.2969398476188700E+00   3.1793764328087359E-01   1.3617384576811825E-01\n         2         45   1.3721123798749537E+00   6.3973513973729199E+00   3.7457022157866304E+00   5.0158792550110110E-01\n         2         46   6.3964342968618404E-01   4.7161013997028380E+00   1.9947659320351354E+00   4.2776493844298569E-01\n         2         47   8.6532747970285151E-01   6.1240088873304499E+00   2.7402018484921369E+00   4.0552538612845523E-01\n         2         48   2.5315105294788682E+00   1.5776758660822487E+01   8.7867531123795093E+00   1.2800885070636867E+00\n         2         49   1.5679508239487920E+00   1.6123025100421103E+01   6.9389600266532643E+00   1.5752331036924878E+00\n         2         50   2.4475421880204548E-01   4.5715135037651979E+00   1.7778621079614614E+00   3.3311384228682872E-01\n         2         51   2.8365798870360606E+00   1.5735394223700631E+01   8.7129345829426814E+00   1.2788947945672131E+00\n         2         52   1.4825266957775993E+00   1.4111085036729261E+01   5.9550381055833128E+00   1.3412575984240060E+00\n         2         53   2.9486345514961088E-01   2.1632897998459173E+00   7.6894782290828789E-01   1.6439255789853263E-01\n         2         54   6.1183454216254696E-01   4.7418024842673727E+00   2.4364672738977449E+00   3.8379810845509604E-01\n         2         55   4.2978046698724798E-01   4.7295979558909700E+00   2.0069121315341767E+00   4.7649159304923261E-01\n         2         56   3.3379248097225291E-02   8.3272635081969881E-01   1.7274845946125020E-01   8.7956031429209408E-02\n         2         57   8.2656009161897048E-01   3.9467471262168639E+00   2.2459243943426777E+00   3.1269124051179731E-01\n         2         58   3.1171589063801924E-01   2.7714452296122714E+00   1.1129251102859337E+00   2.6297335909685149E-01\n         2         59   2.6592109568248031E-02   5.6825603390221913E-01   2.0877471778793405E-01   4.9135988886466996E-02\n         2         60   7.2485536842319745E-02   1.1034806181844534E+00   4.5818934497666303E-01   1.0344323974312900E-01\n         2         61   5.9263838221524185E-03   1.2515028539804678E+00   2.4502825958578195E-01   1.1006546541667923E-01\n         2         62   3.5994334696395447E-03   3.9125406849266531E-01   8.9107610428087070E-02   3.1854933024728180E-02\n         2         63   7.2533340578499653E-02   1.0927078443379801E+00   4.4612155612487853E-01   1.0164232620041405E-01\n         2         64   5.4706332551405917E-03   9.8645463183530846E-01   1.9457952454956559E-01   8.6829363320211461E-02\n         2         65   1.7435002600794914E-04   5.6940854477051987E-02   3.9265019004702875E-03   5.9979210203388224E-03\n         2         66   2.1035187678847361E-02   2.2735828246294021E-01   9.5459655622289877E-02   2.0577872261152416E-02\n"
  },
  {
    "path": "examples/nnp-predict/Cu2S_PBE/weights.016.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -3.5529535307974660E+00 a         1     0     1     1     1\n  7.2419212968357530E-02 a         2     0     1     1     2\n  6.6238167719007179E-01 a         3     0     1     1     3\n  1.3187085002852068E+00 a         4     0     1     1     4\n  8.0230438760649514E-01 a         5     0     1     1     5\n  8.3955862269426929E-01 a         6     0     1     1     6\n  6.0886672237242623E-01 a         7     0     1     1     7\n  1.8038521037244075E+00 a         8     0     1     1     8\n -9.4212226737513360E-01 a         9     0     1     1     9\n -5.1556581063883433E-01 a        10     0     1     1    10\n -1.1787308470438386E-01 a        11     0     1     1    11\n  2.7402309255936421E+00 a        12     0     1     1    12\n -1.4988157706430596E+00 a        13     0     1     1    13\n -1.4218948987030877E+00 a        14     0     1     1    14\n -3.1471248905197000E+00 a        15     0     1     1    15\n -2.7242744362012289E-01 a        16     0     1     1    16\n -1.4939110915197420E+00 a        17     0     1     1    17\n -4.5760625854044340E-01 a        18     0     1     1    18\n  1.8320965746572428E+00 a        19     0     1     1    19\n  1.4829292005742705E+00 a        20     0     1     1    20\n -4.7531481220841671E+00 a        21     0     1     1    21\n  6.9284365000837844E-01 a        22     0     1     1    22\n -1.4360334184866708E+00 a        23     0     1     1    23\n -6.9988606086712224E-01 a        24     0     1     1    24\n -2.6821117310359570E+00 a        25     0     1     1    25\n  1.2328185292695659E+00 a        26     0     2     1     1\n  6.8539081540980901E-02 a        27     0     2     1     2\n  1.1312525424757594E-01 a        28     0     2     1     3\n  3.3791299053992763E-01 a        29     0     2     1     4\n  1.3203780104475105E+00 a        30     0     2     1     5\n -1.4531712477250573E+00 a        31     0     2     1     6\n  2.4379072742488564E-01 a        32     0     2     1     7\n  7.2963026955779986E-01 a        33     0     2     1     8\n -1.2591734762557112E+00 a        34     0     2     1     9\n -4.7096176379988147E-01 a        35     0     2     1    10\n  1.1052943930835461E-01 a        36     0     2     1    11\n  1.2282514057948777E+00 a        37     0     2     1    12\n -5.8437787869506075E-01 a        38     0     2     1    13\n  1.4166787422902487E+00 a        39     0     2     1    14\n -1.6938650584717402E-01 a        40     0     2     1    15\n  2.3030826774815769E+00 a        41     0     2     1    16\n -1.4473769335578126E+00 a        42     0     2     1    17\n  4.0195075881174241E-01 a        43     0     2     1    18\n  1.1043558865793792E+00 a        44     0     2     1    19\n -3.4549061205961434E-01 a        45     0     2     1    20\n  8.1879232157423720E-01 a        46     0     2     1    21\n -2.7007345535606064E-01 a        47     0     2     1    22\n -8.2869143511169474E-01 a        48     0     2     1    23\n -2.9469119089022022E-01 a        49     0     2     1    24\n -5.7206441642229700E-01 a        50     0     2     1    25\n  7.7333844542414798E-01 a        51     0     3     1     1\n -2.8005034461966472E+00 a        52     0     3     1     2\n -2.0054154055351620E-01 a        53     0     3     1     3\n -2.3648818664674390E-01 a        54     0     3     1     4\n -6.4064022093719220E-01 a        55     0     3     1     5\n  6.9876341352721461E-01 a        56     0     3     1     6\n  1.2138517429043079E+00 a        57     0     3     1     7\n -1.0872828987358620E+00 a        58     0     3     1     8\n  2.4009903950784475E+00 a        59     0     3     1     9\n -7.1414550990900871E-01 a        60     0     3     1    10\n  4.8262298434516965E-01 a        61     0     3     1    11\n  1.2017235942575036E-01 a        62     0     3     1    12\n -5.0067742187524500E-01 a        63     0     3     1    13\n  1.6682617398315705E-01 a        64     0     3     1    14\n -1.9521789463955752E+00 a        65     0     3     1    15\n  1.3587159322569415E+00 a        66     0     3     1    16\n  1.9824040428450457E-01 a        67     0     3     1    17\n  5.0478176436946609E-01 a        68     0     3     1    18\n  1.7968971934667841E+00 a        69     0     3     1    19\n -2.6819167691107553E+00 a        70     0     3     1    20\n  3.1361294632323173E+00 a        71     0     3     1    21\n -7.2813429885436576E-01 a        72     0     3     1    22\n  7.9662962027149486E-01 a        73     0     3     1    23\n  5.3906067437318705E-01 a        74     0     3     1    24\n  1.8219650246428634E+00 a        75     0     3     1    25\n  5.8927722128305347E-02 a        76     0     4     1     1\n  3.4478358925805858E-01 a        77     0     4     1     2\n  2.1711984340886667E-01 a        78     0     4     1     3\n -7.5943721634464512E-01 a        79     0     4     1     4\n -2.1415789791334832E+00 a        80     0     4     1     5\n  3.0855930522672659E-01 a        81     0     4     1     6\n -7.4505867442699159E-01 a        82     0     4     1     7\n -4.1258347929987922E+00 a        83     0     4     1     8\n -8.9911876538844360E-02 a        84     0     4     1     9\n  8.0135720853704462E-01 a        85     0     4     1    10\n -6.4314476008779209E-01 a        86     0     4     1    11\n -6.6301798112622423E-01 a        87     0     4     1    12\n -1.6975741162472407E-01 a        88     0     4     1    13\n  1.5616634992334104E+00 a        89     0     4     1    14\n  5.4073426424790072E-01 a        90     0     4     1    15\n  1.1663760214127676E+00 a        91     0     4     1    16\n -7.2592084481083807E-01 a        92     0     4     1    17\n  1.1933746575167552E+00 a        93     0     4     1    18\n  5.8471587235867606E-01 a        94     0     4     1    19\n  9.9434818278332526E-01 a        95     0     4     1    20\n  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-3.4792334227780373E+00 a      1760     0    71     1    10\n  3.6144947917176755E+00 a      1761     0    71     1    11\n -5.3242607337722907E+00 a      1762     0    71     1    12\n -4.2011996309939885E+00 a      1763     0    71     1    13\n  3.2298751228608515E+00 a      1764     0    71     1    14\n  1.8825051584889532E+00 a      1765     0    71     1    15\n -1.8961857615891467E-01 a      1766     0    71     1    16\n -1.1204727218381718E+00 a      1767     0    71     1    17\n  5.8296231817923125E+00 a      1768     0    71     1    18\n -2.7569769703652081E+00 a      1769     0    71     1    19\n  6.2509652869303896E+00 a      1770     0    71     1    20\n  7.3099341385745902E+00 a      1771     0    71     1    21\n  3.4091684101779327E+00 a      1772     0    71     1    22\n  7.7927094737192535E+00 a      1773     0    71     1    23\n  7.1032964612989176E+00 a      1774     0    71     1    24\n -2.1248316536988008E+00 a      1775     0    71     1    25\n -2.8565429715710794E-01 a      1776     0    72     1     1\n  5.3486017758130078E-01 a      1777     0    72     1     2\n  5.3877247586652199E-01 a      1778     0    72     1     3\n  2.3453143416704650E-01 a      1779     0    72     1     4\n  1.3489336844355190E-01 a      1780     0    72     1     5\n  9.1964253840021981E-01 a      1781     0    72     1     6\n -4.2626451962297102E-01 a      1782     0    72     1     7\n -3.6185888408055283E-01 a      1783     0    72     1     8\n  3.6939568629994013E-01 a      1784     0    72     1     9\n -2.5882852755145358E-01 a      1785     0    72     1    10\n -1.5569841670453506E+00 a      1786     0    72     1    11\n -1.8835587727618484E+00 a      1787     0    72     1    12\n -7.7120877965652712E-01 a      1788     0    72     1    13\n  8.1980833234742223E-01 a      1789     0    72     1    14\n  1.9481422398229112E-01 a      1790     0    72     1    15\n -8.0628825824878236E-01 a      1791     0    72     1    16\n -1.0371067287322926E+00 a      1792     0    72     1    17\n -4.3760611806115551E-01 a      1793     0    72     1    18\n  9.8623879832675329E-02 a      1794     0    72     1    19\n -7.5410028995025702E-01 a      1795     0    72     1    20\n -1.2313787058509964E+00 a      1796     0    72     1    21\n -4.6741452879831155E-02 a      1797     0    72     1    22\n -4.4269157854319681E-02 a      1798     0    72     1    23\n  1.7151129017615777E-01 a      1799     0    72     1    24\n  3.2149250192846229E-01 a      1800     0    72     1    25\n -1.2487799204729562E+00 b      1801     1     1\n  7.7797875052564691E-02 b      1802     1     2\n -1.1527934681933877E-01 b      1803     1     3\n -2.8431889201310762E-01 b      1804     1     4\n  5.5831725553046441E-01 b      1805     1     5\n  2.8860892427759248E+00 b      1806     1     6\n -1.3445325409540025E+00 b      1807     1     7\n  6.6670686103261509E+00 b      1808     1     8\n  3.5820158276553177E-01 b      1809     1     9\n  3.5785148839511103E+00 b      1810     1    10\n -8.8101281474293580E-01 b      1811     1    11\n -5.3726668973875906E+00 b      1812     1    12\n -6.4114714028020847E-01 b      1813     1    13\n  1.5565127033840587E+00 b      1814     1    14\n -1.7602464299350837E-02 b      1815     1    15\n  1.8777261894948953E+00 b      1816     1    16\n  1.4994055174586114E+00 b      1817     1    17\n -7.2199500908977243E-01 b      1818     1    18\n  9.2731866344858893E-01 b      1819     1    19\n -4.4839087509791570E-01 b      1820     1    20\n -2.1355087601187956E+00 b      1821     1    21\n -5.9468786076051305E-01 b      1822     1    22\n -1.4586824355018946E+00 b      1823     1    23\n -1.0118916679592884E+00 b      1824     1    24\n -1.1773719431755225E+00 b      1825     1    25\n -1.5657428780940730E+00 a      1826     1     1     2     1\n -1.5012822554420542E+00 a      1827     1     1     2     2\n -1.2445510657315391E+00 a      1828     1     1     2     3\n  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-1.5054546644990752E+00 a      1861     1     2     2    11\n  1.8610934627716093E-02 a      1862     1     2     2    12\n  7.0237315233166497E-01 a      1863     1     2     2    13\n  9.4212554739512056E-01 a      1864     1     2     2    14\n -6.4243325216574909E-01 a      1865     1     2     2    15\n  2.0638482947612933E+00 a      1866     1     2     2    16\n -7.8489263650035335E-02 a      1867     1     2     2    17\n  8.8188283383270472E-01 a      1868     1     2     2    18\n  5.6847475917655665E-01 a      1869     1     2     2    19\n  3.4854878075637896E-01 a      1870     1     2     2    20\n  1.4875468096208677E-01 a      1871     1     2     2    21\n  1.1162641631624876E-01 a      1872     1     2     2    22\n  1.1416286121652623E+00 a      1873     1     2     2    23\n  8.0566577322750998E-01 a      1874     1     2     2    24\n -1.3768822327400507E+00 a      1875     1     2     2    25\n  5.2100349813620650E-01 a      1876     1     3     2     1\n  3.0316390750570238E-01 a      1877     1     3     2     2\n -2.3370128152310604E-01 a      1878     1     3     2     3\n -1.0820688792652087E+00 a      1879     1     3     2     4\n  2.1060281157526037E-01 a      1880     1     3     2     5\n -3.6728393525156205E-01 a      1881     1     3     2     6\n -1.7794340421478609E+00 a      1882     1     3     2     7\n -4.3969196635008256E-01 a      1883     1     3     2     8\n -6.5240078672733570E-01 a      1884     1     3     2     9\n  1.3030748053589755E-01 a      1885     1     3     2    10\n  8.0208201643578281E-01 a      1886     1     3     2    11\n -5.0642791152315048E-01 a      1887     1     3     2    12\n  1.7175121486555200E-02 a      1888     1     3     2    13\n -1.7539793329208120E-01 a      1889     1     3     2    14\n -1.9760102634297960E+00 a      1890     1     3     2    15\n -6.5964298566673879E-02 a      1891     1     3     2    16\n  2.1354437430032353E-01 a      1892     1     3     2    17\n  3.7292555470519495E-01 a      1893     1     3     2    18\n -2.8759373610684746E-01 a      1894     1     3     2    19\n -3.0111096782562924E-01 a      1895     1     3     2    20\n -1.7306176309591917E-01 a      1896     1     3     2    21\n -1.2005571011494226E-01 a      1897     1     3     2    22\n  1.3295388504771954E-01 a      1898     1     3     2    23\n  8.3138458757209516E-02 a      1899     1     3     2    24\n  1.5856154095117295E-04 a      1900     1     3     2    25\n  6.4572709345253165E-01 a      1901     1     4     2     1\n -5.7946715376023517E-01 a      1902     1     4     2     2\n -1.0108148324035785E-02 a      1903     1     4     2     3\n -1.6260047633919668E+00 a      1904     1     4     2     4\n  1.2063924357050895E+00 a      1905     1     4     2     5\n -1.3308086608013470E-01 a      1906     1     4     2     6\n -2.0744033026290049E-01 a      1907     1     4     2     7\n  8.7004036554679898E-04 a      1908     1     4     2     8\n  1.3776545639614570E+00 a      1909     1     4     2     9\n -4.1679170481413325E-01 a      1910     1     4     2    10\n  1.2085768686834414E-01 a      1911     1     4     2    11\n  6.7417090723776829E-02 a      1912     1     4     2    12\n  7.2831441702454858E-01 a      1913     1     4     2    13\n  4.1882179725900914E-01 a      1914     1     4     2    14\n  8.6071127382993529E-01 a      1915     1     4     2    15\n -1.0475505670392704E+00 a      1916     1     4     2    16\n  4.1797053832508835E-01 a      1917     1     4     2    17\n  9.0950721709203083E-02 a      1918     1     4     2    18\n -2.0125699174728634E-01 a      1919     1     4     2    19\n  4.3360061561778840E-01 a      1920     1     4     2    20\n -8.7167096012562095E-01 a      1921     1     4     2    21\n -2.4539897225218532E-01 a      1922     1     4     2    22\n -5.3604239110809038E-01 a      1923     1     4     2    23\n -2.2337993987488888E-01 a      1924     1     4     2    24\n  3.1846049011561406E-01 a      1925     1     4     2    25\n  1.1434219399741365E-01 a      1926     1     5     2     1\n  1.7880919133127568E-01 a      1927     1     5     2     2\n -1.8179159527255145E-01 a      1928     1     5     2     3\n -4.5488815247472342E-01 a      1929     1     5     2     4\n -6.1598699822076874E-01 a      1930     1     5     2     5\n -2.4359478240808174E-01 a      1931     1     5     2     6\n -2.7633669765488156E-01 a      1932     1     5     2     7\n  5.6548513047232192E-02 a      1933     1     5     2     8\n -1.1856375180802950E-01 a      1934     1     5     2     9\n  1.9838320239404128E-01 a      1935     1     5     2    10\n -5.5839996553118054E-01 a      1936     1     5     2    11\n  8.5683677871477751E-02 a      1937     1     5     2    12\n -4.3990229216539417E-02 a      1938     1     5     2    13\n -8.2580380946034065E-02 a      1939     1     5     2    14\n -2.5926939478179243E+00 a      1940     1     5     2    15\n -2.9263488552138478E-01 a      1941     1     5     2    16\n  7.4326458357632263E-01 a      1942     1     5     2    17\n  4.2013924569516037E-01 a      1943     1     5     2    18\n -5.8280302654581832E-02 a      1944     1     5     2    19\n -3.2612804852919446E-02 a      1945     1     5     2    20\n  3.0897375192782450E-01 a      1946     1     5     2    21\n -3.4554814584389509E-01 a      1947     1     5     2    22\n  5.6462638020854716E-01 a      1948     1     5     2    23\n -2.2840636874785014E-01 a      1949     1     5     2    24\n -4.9669234553755076E-01 a      1950     1     5     2    25\n  1.1758939649783381E-01 a      1951     1     6     2     1\n  8.6738679928268236E-01 a      1952     1     6     2     2\n -8.2268243221940873E-01 a      1953     1     6     2     3\n -1.7656641024661676E-01 a      1954     1     6     2     4\n -7.3983486152494982E-01 a      1955     1     6     2     5\n  5.9385478664743296E-01 a      1956     1     6     2     6\n -4.2593570872866021E-01 a      1957     1     6     2     7\n -1.9801025124105215E-01 a      1958     1     6     2     8\n -4.6730416799726238E-01 a      1959     1     6     2     9\n  1.8116336463074925E-01 a      1960     1     6     2    10\n -7.5935659696139179E-01 a      1961     1     6     2    11\n -2.7885626460361607E-01 a      1962     1     6     2    12\n  2.2498372487170440E-01 a      1963     1     6     2    13\n -2.6922194278960770E-01 a      1964     1     6     2    14\n  8.2356834198746176E-02 a      1965     1     6     2    15\n -1.9959174200148408E+00 a      1966     1     6     2    16\n -9.1441649022992150E-02 a      1967     1     6     2    17\n -3.2893725936322316E-01 a      1968     1     6     2    18\n  8.4708812890909327E-02 a      1969     1     6     2    19\n -9.8738542155083330E-03 a      1970     1     6     2    20\n -1.5706979176219785E-01 a      1971     1     6     2    21\n -3.3385820430832114E-01 a      1972     1     6     2    22\n -8.1658461786034431E-01 a      1973     1     6     2    23\n  4.2826805041754107E-01 a      1974     1     6     2    24\n  6.7595378736221203E-03 a      1975     1     6     2    25\n -1.4858293771378450E-01 a      1976     1     7     2     1\n -4.8665064878920916E-01 a      1977     1     7     2     2\n  9.3147532658334302E-03 a      1978     1     7     2     3\n  2.2071434698840436E-01 a      1979     1     7     2     4\n -3.1521981986003578E+00 a      1980     1     7     2     5\n  1.4896102615333093E-01 a      1981     1     7     2     6\n  2.0639082326871608E-01 a      1982     1     7     2     7\n  1.4764434422173356E+00 a      1983     1     7     2     8\n -8.5415180586937678E-01 a      1984     1     7     2     9\n  2.0056826451387089E+00 a      1985     1     7     2    10\n -1.6035541337428121E+00 a      1986     1     7     2    11\n -1.0126746741541708E-01 a      1987     1     7     2    12\n  1.0176837892450277E+00 a      1988     1     7     2    13\n  5.8650237148957363E-01 a      1989     1     7     2    14\n  6.8764775335937489E-01 a      1990     1     7     2    15\n -1.6327881928548789E+00 a      1991     1     7     2    16\n -2.6588597247788198E-01 a      1992     1     7     2    17\n  1.9718370666773979E-01 a      1993     1     7     2    18\n  4.3601566297954825E-01 a      1994     1     7     2    19\n -2.7082844396133726E-01 a      1995     1     7     2    20\n  3.2206390922604272E-01 a      1996     1     7     2    21\n  5.0949702830703934E-03 a      1997     1     7     2    22\n -1.3049790188741632E+00 a      1998     1     7     2    23\n  4.2026808266723220E-01 a      1999     1     7     2    24\n -6.3063301866048659E-03 a      2000     1     7     2    25\n -2.6986778384233595E-01 a      2001     1     8     2     1\n  1.0472413049447822E+00 a      2002     1     8     2     2\n  2.1270075261563209E-01 a      2003     1     8     2     3\n  1.0059956884525167E-02 a      2004     1     8     2     4\n -5.6674331507128162E-01 a      2005     1     8     2     5\n -4.1069951508364727E-01 a      2006     1     8     2     6\n -5.7946760577066525E-01 a      2007     1     8     2     7\n -6.9320514952269952E-01 a      2008     1     8     2     8\n -2.6235771311219197E-01 a      2009     1     8     2     9\n -4.9114985182179943E-01 a      2010     1     8     2    10\n -6.4751077129371837E-01 a      2011     1     8     2    11\n  1.6623516048991380E-01 a      2012     1     8     2    12\n -1.3252784721447061E-01 a      2013     1     8     2    13\n  6.3617130518492077E-02 a      2014     1     8     2    14\n -7.9749770183388205E-02 a      2015     1     8     2    15\n  2.6810344620231513E-01 a      2016     1     8     2    16\n -1.0886590179511721E-01 a      2017     1     8     2    17\n -8.5635070249057671E-02 a      2018     1     8     2    18\n -8.5883419432118385E-02 a      2019     1     8     2    19\n  1.4001812857233212E-01 a      2020     1     8     2    20\n  2.4652559241660935E-01 a      2021     1     8     2    21\n -1.1705271450291483E-02 a      2022     1     8     2    22\n  5.1059887324814701E-01 a      2023     1     8     2    23\n -9.2777234250212143E-02 a      2024     1     8     2    24\n -6.6631934340703591E-01 a      2025     1     8     2    25\n  4.4575672600804567E-01 a      2026     1     9     2     1\n -6.7107163032432227E-01 a      2027     1     9     2     2\n -3.0179267369944862E-01 a      2028     1     9     2     3\n -1.3598496288690123E+00 a      2029     1     9     2     4\n -1.4940270248112404E+00 a      2030     1     9     2     5\n -2.2080339138801010E-02 a      2031     1     9     2     6\n -5.7301816910865744E-01 a      2032     1     9     2     7\n -1.0063124051587569E-01 a      2033     1     9     2     8\n -2.3012172042264027E+00 a      2034     1     9     2     9\n  1.0885556179246252E+00 a      2035     1     9     2    10\n -1.1526492907689538E+00 a      2036     1     9     2    11\n  3.9520279659304998E-02 a      2037     1     9     2    12\n  2.7509795088948047E-01 a      2038     1     9     2    13\n -3.2176987618681385E-01 a      2039     1     9     2    14\n  1.2152345255401775E+00 a      2040     1     9     2    15\n  6.7561788359563746E-01 a      2041     1     9     2    16\n  1.2756402711221351E-01 a      2042     1     9     2    17\n  4.2778010903937930E-02 a      2043     1     9     2    18\n  2.2524717454514478E-01 a      2044     1     9     2    19\n -5.9203499543104976E-01 a      2045     1     9     2    20\n  1.9472787318819443E-01 a      2046     1     9     2    21\n  2.6372584248809827E-01 a      2047     1     9     2    22\n -1.2605296128570485E+00 a      2048     1     9     2    23\n -4.2493619774884570E-02 a      2049     1     9     2    24\n -3.2689975704292223E-01 a      2050     1     9     2    25\n -5.0316442252296556E-01 a      2051     1    10     2     1\n -1.2776598471010672E+00 a      2052     1    10     2     2\n  3.2727687173561748E-01 a      2053     1    10     2     3\n -5.2750979806146270E-01 a      2054     1    10     2     4\n -5.2100917223171461E-01 a      2055     1    10     2     5\n  1.0271103871270988E+00 a      2056     1    10     2     6\n -1.3174585043808176E+00 a      2057     1    10     2     7\n  1.7860344423744762E-01 a      2058     1    10     2     8\n -3.1935218220133910E-01 a      2059     1    10     2     9\n  4.0624355231658738E-01 a      2060     1    10     2    10\n -8.4263015301232114E-01 a      2061     1    10     2    11\n -4.1311568727252523E-01 a      2062     1    10     2    12\n -2.0250507836832625E+00 a      2063     1    10     2    13\n -4.9669616476317113E-01 a      2064     1    10     2    14\n  1.4542353491363211E+00 a      2065     1    10     2    15\n -1.0829455537390682E-01 a      2066     1    10     2    16\n  3.0637661429549540E-01 a      2067     1    10     2    17\n  3.9830418172493465E-01 a      2068     1    10     2    18\n -1.6636558535137880E+00 a      2069     1    10     2    19\n  7.0498166711701593E-01 a      2070     1    10     2    20\n -3.8215339196853010E-01 a      2071     1    10     2    21\n -2.9475963780786207E-01 a      2072     1    10     2    22\n  1.2815404826499932E+00 a      2073     1    10     2    23\n  3.7464874577430729E-01 a      2074     1    10     2    24\n  6.7369985980501002E-01 a      2075     1    10     2    25\n  1.4787802212199200E-01 a      2076     1    11     2     1\n  2.3652422194864106E-01 a      2077     1    11     2     2\n -2.9319277439498237E-01 a      2078     1    11     2     3\n  8.1893235515044593E-01 a      2079     1    11     2     4\n -5.4251461750474061E-01 a      2080     1    11     2     5\n -7.9432325051447306E-01 a      2081     1    11     2     6\n  5.6741940214747433E-01 a      2082     1    11     2     7\n -1.9883538594217587E-01 a      2083     1    11     2     8\n  2.4059652163192724E-01 a      2084     1    11     2     9\n  9.0487535694630072E-01 a      2085     1    11     2    10\n  2.1500450010677571E-01 a      2086     1    11     2    11\n -8.8392848708160249E-02 a      2087     1    11     2    12\n  4.8911199216330936E-01 a      2088     1    11     2    13\n  3.8501747509679890E-01 a      2089     1    11     2    14\n  2.0880386832367939E-01 a      2090     1    11     2    15\n -1.2898150999726214E+00 a      2091     1    11     2    16\n -6.7684897098766336E-02 a      2092     1    11     2    17\n -1.3226797298228404E-01 a      2093     1    11     2    18\n -7.0860409533946489E-01 a      2094     1    11     2    19\n  2.0428970671759283E-01 a      2095     1    11     2    20\n  6.1788460934391509E-01 a      2096     1    11     2    21\n -1.5387742244322317E-02 a      2097     1    11     2    22\n -2.9187261106596285E-01 a      2098     1    11     2    23\n -2.7435985561202314E-01 a      2099     1    11     2    24\n -2.9893757922781268E-02 a      2100     1    11     2    25\n  1.4366492019663546E-01 a      2101     1    12     2     1\n -8.3708506447152686E-01 a      2102     1    12     2     2\n  8.4900741982625050E-01 a      2103     1    12     2     3\n -3.1763858239521897E-01 a      2104     1    12     2     4\n -8.5836557564984983E-02 a      2105     1    12     2     5\n  4.8971995238975233E-02 a      2106     1    12     2     6\n -8.6345064469884769E-01 a      2107     1    12     2     7\n -1.8877691890216164E+00 a      2108     1    12     2     8\n  4.7870208924774238E-01 a      2109     1    12     2     9\n -2.6803285718567860E-01 a      2110     1    12     2    10\n -8.3576740507701341E-01 a      2111     1    12     2    11\n -2.0233607775747742E-01 a      2112     1    12     2    12\n -2.0851336604971404E+00 a      2113     1    12     2    13\n  5.5710849793933925E-02 a      2114     1    12     2    14\n -2.5441709390192631E+00 a      2115     1    12     2    15\n  1.1056110845657674E+00 a      2116     1    12     2    16\n  4.1604534414542688E-01 a      2117     1    12     2    17\n -2.4025453894460813E-01 a      2118     1    12     2    18\n -4.8834369066457661E-01 a      2119     1    12     2    19\n  1.2885571052723108E-01 a      2120     1    12     2    20\n -5.4132000309146744E-01 a      2121     1    12     2    21\n -1.7269282812154974E-01 a      2122     1    12     2    22\n -5.8064851629878863E-03 a      2123     1    12     2    23\n -1.4394463497698487E-01 a      2124     1    12     2    24\n -4.2487948203957382E-01 a      2125     1    12     2    25\n  5.8675042735952393E-02 a      2126     1    13     2     1\n  1.7863972211172008E-01 a      2127     1    13     2     2\n  4.5741880103604365E-01 a      2128     1    13     2     3\n  9.1416506499137384E-01 a      2129     1    13     2     4\n -7.3674367315233913E-01 a      2130     1    13     2     5\n -3.0779431852369288E-01 a      2131     1    13     2     6\n -3.2999352842234286E-01 a      2132     1    13     2     7\n -5.4956662968530401E-01 a      2133     1    13     2     8\n -8.2136164243233878E-01 a      2134     1    13     2     9\n  1.2183161209162805E+00 a      2135     1    13     2    10\n -1.2314580021681576E-04 a      2136     1    13     2    11\n -1.0026980899080576E-01 a      2137     1    13     2    12\n -7.5923362473088618E-01 a      2138     1    13     2    13\n  8.7341315448514784E-02 a      2139     1    13     2    14\n  2.5889498070253123E+00 a      2140     1    13     2    15\n  3.2846563407201890E-01 a      2141     1    13     2    16\n  2.4140079639811293E-01 a      2142     1    13     2    17\n  6.6559640464078706E-01 a      2143     1    13     2    18\n -6.0228182791517193E-01 a      2144     1    13     2    19\n  5.0959148190761594E-01 a      2145     1    13     2    20\n -1.8343764259383200E-01 a      2146     1    13     2    21\n -2.0541935684248189E-01 a      2147     1    13     2    22\n  5.2020354314273987E-01 a      2148     1    13     2    23\n  2.8411193388383044E-01 a      2149     1    13     2    24\n  1.5031583886753237E+00 a      2150     1    13     2    25\n -1.5611135743074465E+00 a      2151     1    14     2     1\n -3.2360297425207724E-01 a      2152     1    14     2     2\n -2.8070095488766600E-01 a      2153     1    14     2     3\n -4.2682370987576490E-01 a      2154     1    14     2     4\n -8.0124669652434721E-01 a      2155     1    14     2     5\n  6.0916260028745439E-01 a      2156     1    14     2     6\n -1.3043834885545900E+00 a      2157     1    14     2     7\n -1.1114567839213945E+00 a      2158     1    14     2     8\n -7.6508338871898718E-01 a      2159     1    14     2     9\n  1.7394319780653198E+00 a      2160     1    14     2    10\n  6.1580012015667462E-01 a      2161     1    14     2    11\n -2.1501534971396988E-01 a      2162     1    14     2    12\n  8.1316399521310057E-01 a      2163     1    14     2    13\n -1.2944835426827954E+00 a      2164     1    14     2    14\n  3.6338934043065596E-02 a      2165     1    14     2    15\n -9.7464822438627852E-01 a      2166     1    14     2    16\n -2.4145501724766127E-01 a      2167     1    14     2    17\n -8.8876835360975071E-03 a      2168     1    14     2    18\n -5.8076528324547438E-01 a      2169     1    14     2    19\n -2.0411437917641737E+00 a      2170     1    14     2    20\n -4.2526015090964880E-01 a      2171     1    14     2    21\n  5.9996421373152897E-01 a      2172     1    14     2    22\n -3.6675255943507928E-02 a      2173     1    14     2    23\n  1.3185398858057240E-01 a      2174     1    14     2    24\n -2.0032286135136248E+00 a      2175     1    14     2    25\n  5.1591662327951759E-01 a      2176     1    15     2     1\n -2.5446052702797714E-03 a      2177     1    15     2     2\n -8.1769338860501051E-01 a      2178     1    15     2     3\n -6.8480492422848949E-01 a      2179     1    15     2     4\n  1.6061689254540090E+00 a      2180     1    15     2     5\n -3.6828605283363745E+00 a      2181     1    15     2     6\n -2.6949729107316758E+00 a      2182     1    15     2     7\n -8.7436479908358988E-01 a      2183     1    15     2     8\n -7.2537234627087488E-01 a      2184     1    15     2     9\n  1.7554101736285144E+00 a      2185     1    15     2    10\n -1.5729036376143151E+00 a      2186     1    15     2    11\n -4.7196403406815074E-01 a      2187     1    15     2    12\n  2.4686309706562368E+00 a      2188     1    15     2    13\n -8.1429048034865914E-01 a      2189     1    15     2    14\n  1.2457943097534157E+00 a      2190     1    15     2    15\n -1.8238343315299035E+00 a      2191     1    15     2    16\n -9.1710155695980261E-02 a      2192     1    15     2    17\n -1.7104412957602122E+00 a      2193     1    15     2    18\n  2.7030869802557012E-01 a      2194     1    15     2    19\n -1.7298684033912173E+00 a      2195     1    15     2    20\n -3.1058841915893948E-01 a      2196     1    15     2    21\n  1.8274844624858664E+00 a      2197     1    15     2    22\n -1.3513314668634027E+00 a      2198     1    15     2    23\n -1.1539080164302253E+00 a      2199     1    15     2    24\n  3.7623134982371026E-01 a      2200     1    15     2    25\n  3.8564708777748902E-01 a      2201     1    16     2     1\n -3.7485013341251339E-01 a      2202     1    16     2     2\n  3.0694902381634054E-01 a      2203     1    16     2     3\n -6.3820812530951954E-01 a      2204     1    16     2     4\n  6.1596951581411624E-02 a      2205     1    16     2     5\n  3.1823666483179947E-01 a      2206     1    16     2     6\n -1.7451214484287221E+00 a      2207     1    16     2     7\n  6.6928800449640258E-01 a      2208     1    16     2     8\n -1.1768614713311631E+00 a      2209     1    16     2     9\n -1.2657577834196381E+00 a      2210     1    16     2    10\n -3.0160201061177228E-01 a      2211     1    16     2    11\n -5.3877877406889563E-01 a      2212     1    16     2    12\n -8.6493612190989910E-01 a      2213     1    16     2    13\n -8.8460225776662071E-01 a      2214     1    16     2    14\n  1.9057948312439157E+00 a      2215     1    16     2    15\n -2.7200418390588271E-01 a      2216     1    16     2    16\n  1.9952889394862189E-01 a      2217     1    16     2    17\n  7.9321718120701656E-02 a      2218     1    16     2    18\n -7.5240700188026213E-02 a      2219     1    16     2    19\n  3.5188674964451849E-01 a      2220     1    16     2    20\n  4.4883278162576262E-01 a      2221     1    16     2    21\n  2.4951384292998435E-01 a      2222     1    16     2    22\n  1.6851679055279442E-01 a      2223     1    16     2    23\n -4.8371544786080266E-02 a      2224     1    16     2    24\n  8.1495784381186021E-01 a      2225     1    16     2    25\n -7.7932092504504180E-01 a      2226     1    17     2     1\n  8.4308356300312914E-01 a      2227     1    17     2     2\n  6.2801495977484001E-01 a      2228     1    17     2     3\n -1.6671863188240814E-02 a      2229     1    17     2     4\n  4.9617622666448757E-01 a      2230     1    17     2     5\n  2.8578791610744131E-01 a      2231     1    17     2     6\n  5.0261300134126208E-01 a      2232     1    17     2     7\n  4.2973672296612153E-01 a      2233     1    17     2     8\n  2.0605776991439645E-02 a      2234     1    17     2     9\n  3.1505912130803543E-01 a      2235     1    17     2    10\n -4.8141644197770223E-01 a      2236     1    17     2    11\n  6.5147019223382929E-01 a      2237     1    17     2    12\n  1.3223922139341173E-02 a      2238     1    17     2    13\n  1.3552951191767832E+00 a      2239     1    17     2    14\n -2.7683725661405684E-01 a      2240     1    17     2    15\n -1.4553982661789062E+00 a      2241     1    17     2    16\n  1.3934738472514663E-01 a      2242     1    17     2    17\n  6.5662014192387624E-02 a      2243     1    17     2    18\n  3.9097955051468730E-01 a      2244     1    17     2    19\n -1.5329149954135943E+00 a      2245     1    17     2    20\n -4.9182889227766408E-01 a      2246     1    17     2    21\n -8.4101247787721850E-02 a      2247     1    17     2    22\n  1.1079957740309260E-01 a      2248     1    17     2    23\n  1.2653734338244162E+00 a      2249     1    17     2    24\n  5.1889782109670390E-01 a      2250     1    17     2    25\n -3.5701303156391490E-01 a      2251     1    18     2     1\n -2.3369886700637788E-01 a      2252     1    18     2     2\n  1.8192889993017079E-02 a      2253     1    18     2     3\n -1.9089403601514085E-01 a      2254     1    18     2     4\n -2.2245213004847283E-01 a      2255     1    18     2     5\n -4.1704360216982245E-01 a      2256     1    18     2     6\n -5.9376327509449600E-01 a      2257     1    18     2     7\n  4.7700366121749904E-01 a      2258     1    18     2     8\n -2.4234013871626243E+00 a      2259     1    18     2     9\n -3.4319600817672740E+00 a      2260     1    18     2    10\n  1.4602063702387118E+00 a      2261     1    18     2    11\n -4.8017949262669966E-02 a      2262     1    18     2    12\n -2.5388955532842389E-01 a      2263     1    18     2    13\n -4.4955574787101665E-01 a      2264     1    18     2    14\n -5.9686971656068388E-01 a      2265     1    18     2    15\n  1.5329181413373798E+00 a      2266     1    18     2    16\n -1.7745540088419492E-01 a      2267     1    18     2    17\n -6.8356066126928808E-02 a      2268     1    18     2    18\n -5.7868883010994010E-01 a      2269     1    18     2    19\n -2.4958945618463482E-01 a      2270     1    18     2    20\n -8.8915588088891362E-01 a      2271     1    18     2    21\n  4.6796145878627105E-01 a      2272     1    18     2    22\n  3.7239838802427244E-01 a      2273     1    18     2    23\n  5.8825012698306467E-01 a      2274     1    18     2    24\n -2.5213870537746796E-01 a      2275     1    18     2    25\n -4.0945577957805229E-01 a      2276     1    19     2     1\n -6.3926426566269479E-01 a      2277     1    19     2     2\n -2.4803832950792159E-03 a      2278     1    19     2     3\n -9.5504254863097604E-01 a      2279     1    19     2     4\n  2.4385416954208063E-02 a      2280     1    19     2     5\n  1.8105456314263782E-01 a      2281     1    19     2     6\n -1.3959803913453275E+00 a      2282     1    19     2     7\n -1.4647235163838312E+00 a      2283     1    19     2     8\n -8.0598524282205181E-02 a      2284     1    19     2     9\n -6.8890711362406043E-01 a      2285     1    19     2    10\n  7.4049128505740025E-01 a      2286     1    19     2    11\n -1.8107652733146301E-01 a      2287     1    19     2    12\n  1.1180459617056233E-01 a      2288     1    19     2    13\n -9.7523288912192785E-01 a      2289     1    19     2    14\n  5.4031707452495070E-01 a      2290     1    19     2    15\n -8.6865875639635415E-01 a      2291     1    19     2    16\n -1.1736299949303194E-03 a      2292     1    19     2    17\n -2.1796832363882152E-01 a      2293     1    19     2    18\n -2.0197745129587785E-01 a      2294     1    19     2    19\n -2.0649260039989298E-01 a      2295     1    19     2    20\n -2.5945409305212930E-01 a      2296     1    19     2    21\n -5.3195384264402990E-01 a      2297     1    19     2    22\n  6.1477888542849975E-02 a      2298     1    19     2    23\n -6.9385778198627257E-01 a      2299     1    19     2    24\n  3.3845607119781312E-01 a      2300     1    19     2    25\n  4.0809678373584041E-02 a      2301     1    20     2     1\n  3.2924070883990825E-01 a      2302     1    20     2     2\n -3.9610966191553226E-01 a      2303     1    20     2     3\n -2.0132651897409879E+00 a      2304     1    20     2     4\n  2.4484241841952716E+00 a      2305     1    20     2     5\n  5.3570194814429040E-01 a      2306     1    20     2     6\n  3.9782963410556638E-01 a      2307     1    20     2     7\n  4.9250587897907255E-01 a      2308     1    20     2     8\n -9.0581905870919688E-01 a      2309     1    20     2     9\n  9.6720818758476146E-01 a      2310     1    20     2    10\n -2.4290730668752603E+00 a      2311     1    20     2    11\n  8.5170505147369346E-01 a      2312     1    20     2    12\n -2.1483680686887496E-01 a      2313     1    20     2    13\n  1.0883989821232398E+00 a      2314     1    20     2    14\n -4.2448276419305673E+00 a      2315     1    20     2    15\n  1.3220278308357323E+00 a      2316     1    20     2    16\n  2.0515176886377723E-01 a      2317     1    20     2    17\n  4.3773484307033583E-01 a      2318     1    20     2    18\n -1.3786340518033451E+00 a      2319     1    20     2    19\n -2.2372534223710475E-01 a      2320     1    20     2    20\n -2.7758118237942005E-02 a      2321     1    20     2    21\n -3.6463714150317883E-01 a      2322     1    20     2    22\n -1.4652346461706460E+00 a      2323     1    20     2    23\n -1.9948609569365011E-01 a      2324     1    20     2    24\n -1.2992922004186624E+00 a      2325     1    20     2    25\n -5.4234465116761910E-01 a      2326     1    21     2     1\n -1.1703464645203435E-01 a      2327     1    21     2     2\n  2.7846604110004280E-01 a      2328     1    21     2     3\n  4.2152065037688702E-01 a      2329     1    21     2     4\n -3.1812648076931704E-01 a      2330     1    21     2     5\n  2.5354733798445972E-01 a      2331     1    21     2     6\n  5.0508300555905372E-01 a      2332     1    21     2     7\n -1.8871360552404024E+00 a      2333     1    21     2     8\n -1.8179368004635235E+00 a      2334     1    21     2     9\n -9.1331416740862581E-01 a      2335     1    21     2    10\n  1.0900023434903663E+00 a      2336     1    21     2    11\n  8.9874047451855385E-02 a      2337     1    21     2    12\n -1.2847531299662041E+00 a      2338     1    21     2    13\n -7.4525540480534103E-01 a      2339     1    21     2    14\n  1.0535696198186528E+00 a      2340     1    21     2    15\n  7.8428574671901730E-01 a      2341     1    21     2    16\n  1.3814042929844125E-01 a      2342     1    21     2    17\n  6.9643061019999272E-02 a      2343     1    21     2    18\n  8.0359279616965651E-01 a      2344     1    21     2    19\n -5.6529681854842539E-01 a      2345     1    21     2    20\n -2.3488037904274034E-02 a      2346     1    21     2    21\n  2.1341829380240665E-01 a      2347     1    21     2    22\n -1.4102093313296238E-01 a      2348     1    21     2    23\n -1.6582794027459599E-01 a      2349     1    21     2    24\n -2.1114013691856662E-01 a      2350     1    21     2    25\n  2.4212589160209405E-01 a      2351     1    22     2     1\n  3.9327330796009152E-01 a      2352     1    22     2     2\n -3.6566016634832049E-01 a      2353     1    22     2     3\n  1.0287117668616212E+00 a      2354     1    22     2     4\n  1.6899708282115562E+00 a      2355     1    22     2     5\n  4.3429485581693034E-01 a      2356     1    22     2     6\n  1.7977381066015556E+00 a      2357     1    22     2     7\n  2.9196281691007775E-01 a      2358     1    22     2     8\n  8.9048235778413076E-01 a      2359     1    22     2     9\n -2.7029855626099626E+00 a      2360     1    22     2    10\n -9.9842398461553661E-01 a      2361     1    22     2    11\n  1.3261280174131618E-01 a      2362     1    22     2    12\n  7.8677628275123768E-01 a      2363     1    22     2    13\n -1.6176772224659823E+00 a      2364     1    22     2    14\n -2.9218429770545273E+00 a      2365     1    22     2    15\n -1.0470075932239322E+00 a      2366     1    22     2    16\n -6.2813242798639934E-01 a      2367     1    22     2    17\n -1.1926621420051280E+00 a      2368     1    22     2    18\n  5.6467524440711148E-01 a      2369     1    22     2    19\n  7.0550764585496206E-01 a      2370     1    22     2    20\n  6.7061497370680800E-01 a      2371     1    22     2    21\n  3.2149813491975643E-01 a      2372     1    22     2    22\n -6.5948083157745863E-01 a      2373     1    22     2    23\n  1.4878019494104766E-01 a      2374     1    22     2    24\n -1.4238392562512412E+00 a      2375     1    22     2    25\n -2.9244659427496789E+00 a      2376     1    23     2     1\n  1.1485640801249154E-01 a      2377     1    23     2     2\n  1.1880136805560255E-01 a      2378     1    23     2     3\n  1.9995339152108655E+00 a      2379     1    23     2     4\n -8.8052571584319517E-01 a      2380     1    23     2     5\n -7.6723479106454269E+00 a      2381     1    23     2     6\n -1.6775055426770660E-01 a      2382     1    23     2     7\n  1.1568877491878693E+00 a      2383     1    23     2     8\n -3.6248359285478049E-01 a      2384     1    23     2     9\n -1.0171667144821397E+00 a      2385     1    23     2    10\n -9.7885097010848721E-01 a      2386     1    23     2    11\n  1.7525905926099136E-01 a      2387     1    23     2    12\n  1.6667129102202356E+00 a      2388     1    23     2    13\n -6.3496168416867071E-01 a      2389     1    23     2    14\n -3.9752798317985540E+00 a      2390     1    23     2    15\n -3.0889419514464751E+00 a      2391     1    23     2    16\n -1.6580901185939814E-01 a      2392     1    23     2    17\n -3.0257630892267329E-01 a      2393     1    23     2    18\n  1.1693501120123342E+00 a      2394     1    23     2    19\n -4.4706334843197343E-01 a      2395     1    23     2    20\n  6.3453286866045877E-01 a      2396     1    23     2    21\n  1.9358044980890732E+00 a      2397     1    23     2    22\n  3.1113852281756920E+00 a      2398     1    23     2    23\n -1.9662951755400133E+00 a      2399     1    23     2    24\n -7.5262034829552482E-01 a      2400     1    23     2    25\n -1.0570204013747100E+00 a      2401     1    24     2     1\n  2.0242154350721828E-01 a      2402     1    24     2     2\n -6.1919254330906649E-02 a      2403     1    24     2     3\n -9.3075303350374716E-01 a      2404     1    24     2     4\n -9.4855833806427159E-01 a      2405     1    24     2     5\n  1.2813916759344554E-01 a      2406     1    24     2     6\n -2.0331973717312746E+00 a      2407     1    24     2     7\n  3.0837174823873076E-01 a      2408     1    24     2     8\n  3.7215037809188369E-02 a      2409     1    24     2     9\n  3.9279821894082573E-01 a      2410     1    24     2    10\n  1.1362819017641221E-01 a      2411     1    24     2    11\n -1.3856723422770947E-01 a      2412     1    24     2    12\n -9.0761795928204336E-01 a      2413     1    24     2    13\n -1.9312687936000594E+00 a      2414     1    24     2    14\n  2.4072402343893264E+00 a      2415     1    24     2    15\n -1.3575532169402038E+00 a      2416     1    24     2    16\n -5.0043337242109498E-01 a      2417     1    24     2    17\n  6.6622788206750017E-01 a      2418     1    24     2    18\n -2.7744853244980633E-01 a      2419     1    24     2    19\n -3.3208589628698015E-01 a      2420     1    24     2    20\n -6.5082760242357884E-01 a      2421     1    24     2    21\n -7.4238152455462947E-01 a      2422     1    24     2    22\n  3.5709111009352618E-01 a      2423     1    24     2    23\n  6.1990222796862571E-01 a      2424     1    24     2    24\n  1.1667603307669538E+00 a      2425     1    24     2    25\n  3.4874499133420743E-02 a      2426     1    25     2     1\n  4.6834087122092077E-01 a      2427     1    25     2     2\n -2.4278656264438364E-01 a      2428     1    25     2     3\n -4.7923572182631186E-01 a      2429     1    25     2     4\n  9.1932774354097346E-01 a      2430     1    25     2     5\n  6.9805008912145541E-03 a      2431     1    25     2     6\n -4.0244240337174698E-02 a      2432     1    25     2     7\n  2.3085018839417204E-01 a      2433     1    25     2     8\n  4.1477758640374958E-02 a      2434     1    25     2     9\n -2.9907893871952584E-01 a      2435     1    25     2    10\n  9.9861813798121868E-01 a      2436     1    25     2    11\n  6.1719473832720140E-01 a      2437     1    25     2    12\n  7.7349291753880958E-02 a      2438     1    25     2    13\n  1.9789467747705813E-01 a      2439     1    25     2    14\n -1.6963001394405985E+00 a      2440     1    25     2    15\n  1.6964283624354803E+00 a      2441     1    25     2    16\n -1.2412318165627852E-02 a      2442     1    25     2    17\n -3.0090042509304782E+00 a      2443     1    25     2    18\n -5.2854050109483008E-01 a      2444     1    25     2    19\n -4.0883552444931642E-01 a      2445     1    25     2    20\n -6.7332635048994605E-01 a      2446     1    25     2    21\n -1.9391822634747917E-02 a      2447     1    25     2    22\n  3.7493997817479574E-01 a      2448     1    25     2    23\n -3.1982153221239995E-01 a      2449     1    25     2    24\n -6.5908145380152439E-02 a      2450     1    25     2    25\n  3.6520581763320918E+00 b      2451     2     1\n  8.0350355841113590E+00 b      2452     2     2\n  1.0328413848960700E+00 b      2453     2     3\n  7.2118044450618859E+00 b      2454     2     4\n  1.6897857032469032E+00 b      2455     2     5\n -5.3128298088875221E+00 b      2456     2     6\n  1.1119283095513778E+01 b      2457     2     7\n  5.6335078037870667E-01 b      2458     2     8\n  3.1863573747908753E+00 b      2459     2     9\n -1.5027072914328254E+01 b      2460     2    10\n  4.2491825701309507E+00 b      2461     2    11\n  1.1953389718194374E+00 b      2462     2    12\n -3.7826613521070804E+00 b      2463     2    13\n  2.5804189796272916E+00 b      2464     2    14\n -1.8825899893966049E+01 b      2465     2    15\n  5.0689924546781171E+00 b      2466     2    16\n -4.2675620759638759E+00 b      2467     2    17\n -2.2492760679197388E+00 b      2468     2    18\n  3.5306849260434596E+00 b      2469     2    19\n -4.5612849025174862E+00 b      2470     2    20\n  2.5261284082068989E+00 b      2471     2    21\n  4.9997935137889167E+00 b      2472     2    22\n -1.0317047947417777E+01 b      2473     2    23\n -8.8894968314347089E+00 b      2474     2    24\n -2.4854869056932949E+00 b      2475     2    25\n  7.7377789653328519E-02 a      2476     2     1     3     1\n  3.8948596770158572E-01 a      2477     2     2     3     1\n  1.7977756447195445E-01 a      2478     2     3     3     1\n  6.2246542349685442E-02 a      2479     2     4     3     1\n -1.1775426437182669E-02 a      2480     2     5     3     1\n  7.4084231368981346E-02 a      2481     2     6     3     1\n -2.6739218038996107E-02 a      2482     2     7     3     1\n -1.4199418404546765E-01 a      2483     2     8     3     1\n -1.3644380226489719E-01 a      2484     2     9     3     1\n  4.2740071857011105E-02 a      2485     2    10     3     1\n -8.4658663941687990E-03 a      2486     2    11     3     1\n  1.8776930772068579E-01 a      2487     2    12     3     1\n -6.7008756457919524E-02 a      2488     2    13     3     1\n  4.7698142607044192E-02 a      2489     2    14     3     1\n -1.3372183470389412E-01 a      2490     2    15     3     1\n  4.0870498106272558E-02 a      2491     2    16     3     1\n  1.7572570907757842E-01 a      2492     2    17     3     1\n -1.6327794687227459E-01 a      2493     2    18     3     1\n -5.9707729641314558E-02 a      2494     2    19     3     1\n  1.0563906282310645E-01 a      2495     2    20     3     1\n  6.6231803238242182E-02 a      2496     2    21     3     1\n -2.7962585890502650E-01 a      2497     2    22     3     1\n  1.6032832788645526E-01 a      2498     2    23     3     1\n -1.0623041830538342E-01 a      2499     2    24     3     1\n  1.0896429147371821E-01 a      2500     2    25     3     1\n -1.3407810853851474E+00 b      2501     3     1\n"
  },
  {
    "path": "examples/nnp-predict/Cu2S_PBE/weights.029.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -6.2446602207005186E-01 a         1     0     1     1     1\n  7.9109168478070069E-01 a         2     0     1     1     2\n  5.0258947941284748E-01 a         3     0     1     1     3\n  5.5154910097820120E-01 a         4     0     1     1     4\n  1.4505158314343458E+00 a         5     0     1     1     5\n -3.6571470924977034E-01 a         6     0     1     1     6\n  4.7092493582249750E-01 a         7     0     1     1     7\n  1.7219501990786370E+00 a         8     0     1     1     8\n -1.3599868727171069E-01 a         9     0     1     1     9\n  5.5171059902123576E-01 a        10     0     1     1    10\n -1.3239450297968971E+00 a        11     0     1     1    11\n  7.9289101991721189E-01 a        12     0     1     1    12\n -2.4436241907430895E-01 a        13     0     1     1    13\n  1.2669669007011655E+00 a        14     0     1     1    14\n -1.0859472353178850E+00 a        15     0     1     1    15\n  5.7149297331656246E-01 a        16     0     1     1    16\n  1.1787879403665555E+00 a        17     0     1     1    17\n  5.1959050316647970E-01 a        18     0     1     1    18\n -5.2070371830737283E-01 a        19     0     1     1    19\n -8.6539404799579653E-02 a        20     0     1     1    20\n -1.1403926908826987E+00 a        21     0     1     1    21\n  7.2846619332612425E-02 a        22     0     1     1    22\n -6.0675985144277489E-01 a        23     0     1     1    23\n  1.6628179166765720E+00 a        24     0     1     1    24\n  1.0538483108672489E+00 a        25     0     1     1    25\n -7.0622748176492056E-01 a        26     0     2     1     1\n  1.0910592071347260E+00 a        27     0     2     1     2\n  2.4631386883986663E+00 a        28     0     2     1     3\n  1.1474600047546029E+00 a        29     0     2     1     4\n -2.7984407189871603E+00 a        30     0     2     1     5\n  1.0533577807665364E-02 a        31     0     2     1     6\n 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1.6244338649202151E-02 a      1893     1     9     2    18\n  2.8159940956926782E-02 a      1894     1     9     2    19\n -7.3760105274932919E-01 a      1895     1     9     2    20\n  1.0604614152784235E-01 a      1896     1     9     2    21\n  1.3087759494518761E-01 a      1897     1     9     2    22\n  2.9873262087000452E-01 a      1898     1     9     2    23\n -7.5121649539691160E-01 a      1899     1     9     2    24\n -5.3923107796072600E-01 a      1900     1     9     2    25\n -9.4224670371027917E-03 a      1901     1    10     2     1\n  1.7582720220947401E-01 a      1902     1    10     2     2\n -4.3499560356818456E-02 a      1903     1    10     2     3\n  2.7310295785198496E-01 a      1904     1    10     2     4\n -1.4711568084768856E+00 a      1905     1    10     2     5\n -4.4204405689495387E-02 a      1906     1    10     2     6\n  6.0834648389602855E-02 a      1907     1    10     2     7\n -2.4139577578874571E+00 a      1908     1    10     2     8\n -3.2330445150185877E-01 a      1909     1    10     2     9\n -6.8558897710748834E-01 a      1910     1    10     2    10\n -2.6306695094273136E-01 a      1911     1    10     2    11\n -2.9406094777407277E+00 a      1912     1    10     2    12\n -1.0262257550335584E-01 a      1913     1    10     2    13\n -4.4889806212745592E-01 a      1914     1    10     2    14\n  1.2729127190479747E-01 a      1915     1    10     2    15\n -5.4339870455363115E-01 a      1916     1    10     2    16\n -4.3051833335864892E-01 a      1917     1    10     2    17\n  2.2774840440979685E-01 a      1918     1    10     2    18\n -4.6577095617807179E-01 a      1919     1    10     2    19\n  6.7677527850068725E-02 a      1920     1    10     2    20\n -5.4331229454547138E-02 a      1921     1    10     2    21\n -7.2517226150440761E-01 a      1922     1    10     2    22\n -1.1034679805264240E+00 a      1923     1    10     2    23\n -2.0195864669569050E+00 a      1924     1    10     2    24\n  3.4421830988038693E-01 a      1925     1    10     2    25\n  6.4169421416549660E-02 a      1926     1    11     2     1\n -1.5453028953359832E-01 a      1927     1    11     2     2\n -3.3937811286737152E-01 a      1928     1    11     2     3\n -2.7264685928399618E-02 a      1929     1    11     2     4\n -1.3046027284183024E+00 a      1930     1    11     2     5\n -2.7987570911040532E-01 a      1931     1    11     2     6\n -7.1818879614311160E-01 a      1932     1    11     2     7\n -1.1206386399096295E+00 a      1933     1    11     2     8\n  5.8589221854259044E-01 a      1934     1    11     2     9\n -3.7755430943908636E-01 a      1935     1    11     2    10\n -2.4227661602201420E-01 a      1936     1    11     2    11\n -6.6802170984862275E-01 a      1937     1    11     2    12\n -1.0335031399378087E+00 a      1938     1    11     2    13\n  2.7352884921752563E-01 a      1939     1    11     2    14\n -7.7644903482906286E-02 a      1940     1    11     2    15\n -1.2483161225817251E-01 a      1941     1    11     2    16\n -1.0076823380037454E-01 a      1942     1    11     2    17\n  1.8474479042673506E-02 a      1943     1    11     2    18\n  1.5921923675493641E-01 a      1944     1    11     2    19\n -8.6092467903913172E-01 a      1945     1    11     2    20\n  3.1597658763496336E-02 a      1946     1    11     2    21\n  1.2582027961569384E-01 a      1947     1    11     2    22\n  4.1552569278194468E-01 a      1948     1    11     2    23\n -1.8547083512843898E-01 a      1949     1    11     2    24\n -3.1841028886761663E-01 a      1950     1    11     2    25\n  1.8006197092716905E-01 a      1951     1    12     2     1\n -5.4024199178819454E-01 a      1952     1    12     2     2\n  3.3523776691134710E-01 a      1953     1    12     2     3\n  2.7560028312601675E-01 a      1954     1    12     2     4\n  8.6177633437044554E-01 a      1955     1    12     2     5\n  1.0087407297301751E+00 a      1956     1    12     2     6\n -1.2380927066334282E-01 a      1957     1    12     2     7\n -1.5229780941544174E-01 a      1958     1    12     2     8\n  2.9946743134146903E-01 a      1959     1    12     2     9\n  1.9819105447401073E+00 a      1960     1    12     2    10\n -8.0628486303151947E-01 a      1961     1    12     2    11\n -9.3151349622473523E-01 a      1962     1    12     2    12\n  1.5051328872455074E+00 a      1963     1    12     2    13\n -8.9627139441554438E-01 a      1964     1    12     2    14\n -3.1439437993199801E-02 a      1965     1    12     2    15\n  1.3701630178002484E+00 a      1966     1    12     2    16\n -2.9138443586057278E-01 a      1967     1    12     2    17\n -3.9087530619619010E-01 a      1968     1    12     2    18\n -2.2753042561066517E-01 a      1969     1    12     2    19\n -8.0931038915796594E-01 a      1970     1    12     2    20\n  1.2030804656668543E+00 a      1971     1    12     2    21\n -1.3389862350446610E-01 a      1972     1    12     2    22\n  4.8419262676478225E-01 a      1973     1    12     2    23\n  1.2108153439974718E+00 a      1974     1    12     2    24\n -1.9519966513619349E+00 a      1975     1    12     2    25\n -1.5047045953264607E-01 a      1976     1    13     2     1\n -6.5196314968694580E-01 a      1977     1    13     2     2\n -1.9444580576963033E-01 a      1978     1    13     2     3\n -3.0635873068371338E-03 a      1979     1    13     2     4\n  1.4891889558793558E+00 a      1980     1    13     2     5\n -2.7617795790820687E-01 a      1981     1    13     2     6\n  1.3155600760922213E+00 a      1982     1    13     2     7\n  1.6548881500952060E+00 a      1983     1    13     2     8\n  1.2939743974749243E+00 a      1984     1    13     2     9\n -8.8087806931438950E-01 a      1985     1    13     2    10\n -7.3026619095577089E-02 a      1986     1    13     2    11\n -6.7521271933403364E+00 a      1987     1    13     2    12\n  3.4361606414546986E-01 a      1988     1    13     2    13\n  8.7558578977526269E-01 a      1989     1    13     2    14\n -2.2881702674887253E-01 a      1990     1    13     2    15\n -6.2816527553206336E-01 a      1991     1    13     2    16\n -8.9317308141201190E-01 a      1992     1    13     2    17\n  9.7069680211539489E-01 a      1993     1    13     2    18\n -5.6927576536010438E-01 a      1994     1    13     2    19\n  8.2910381395357602E-01 a      1995     1    13     2    20\n -3.8934674186907103E-01 a      1996     1    13     2    21\n -1.0181364553104701E+00 a      1997     1    13     2    22\n -9.1002882788836370E-01 a      1998     1    13     2    23\n  2.1075571090156360E+00 a      1999     1    13     2    24\n  2.3017239447035212E-01 a      2000     1    13     2    25\n -3.5483123954045620E-01 a      2001     1    14     2     1\n -9.6047986054177317E-02 a      2002     1    14     2     2\n  3.3071183118138114E-01 a      2003     1    14     2     3\n  1.7705379181791761E-01 a      2004     1    14     2     4\n -1.2043718203406772E+00 a      2005     1    14     2     5\n -5.7806038919408154E-01 a      2006     1    14     2     6\n  6.5633162044623850E-01 a      2007     1    14     2     7\n -1.3450535190144031E-01 a      2008     1    14     2     8\n -1.2862521179205477E-01 a      2009     1    14     2     9\n -1.5177254021629161E-01 a      2010     1    14     2    10\n -2.9016357432381029E-01 a      2011     1    14     2    11\n  1.2793982277409728E+00 a      2012     1    14     2    12\n -3.7109006944139383E-01 a      2013     1    14     2    13\n -4.5064222698368622E-01 a      2014     1    14     2    14\n  3.9087439217392134E-02 a      2015     1    14     2    15\n -1.7890737007331405E+00 a      2016     1    14     2    16\n -3.5761366598992050E-01 a      2017     1    14     2    17\n  3.8280249413524364E-01 a      2018     1    14     2    18\n -3.4580266787944813E-01 a      2019     1    14     2    19\n -2.3102511719307051E-01 a      2020     1    14     2    20\n  6.1712210683785684E-02 a      2021     1    14     2    21\n -3.3548067811281668E-01 a      2022     1    14     2    22\n -7.9862203729164616E-01 a      2023     1    14     2    23\n -5.1952466530501407E-01 a      2024     1    14     2    24\n  2.5810393446929092E-01 a      2025     1    14     2    25\n -4.3558412131876484E-01 a      2026     1    15     2     1\n  1.1902629233075568E-01 a      2027     1    15     2     2\n  1.1747512026211912E-01 a      2028     1    15     2     3\n  1.5495247101048408E-02 a      2029     1    15     2     4\n -1.2065420500806932E+00 a      2030     1    15     2     5\n  3.3479165215501783E-01 a      2031     1    15     2     6\n  2.8245317600466197E-01 a      2032     1    15     2     7\n  6.6749992551384099E-02 a      2033     1    15     2     8\n -3.1396609925815760E-01 a      2034     1    15     2     9\n  3.0054714990159620E-01 a      2035     1    15     2    10\n  6.0483428643207637E-01 a      2036     1    15     2    11\n -1.2454958402656351E+00 a      2037     1    15     2    12\n  6.3389744137669779E-01 a      2038     1    15     2    13\n -5.9521423079842484E-01 a      2039     1    15     2    14\n  1.2019169256706089E-01 a      2040     1    15     2    15\n -1.1987245524864630E-01 a      2041     1    15     2    16\n -5.6896152994198784E-02 a      2042     1    15     2    17\n  2.8941200439853954E-01 a      2043     1    15     2    18\n  1.6309209946798925E-01 a      2044     1    15     2    19\n  8.7949523201494928E-01 a      2045     1    15     2    20\n  6.4769343609644300E-02 a      2046     1    15     2    21\n  4.8521193987474981E-01 a      2047     1    15     2    22\n  4.9988972941182691E-01 a      2048     1    15     2    23\n -2.3016622688408100E-01 a      2049     1    15     2    24\n -5.4074197586570194E-01 a      2050     1    15     2    25\n -4.8573302372386212E-01 a      2051     1    16     2     1\n -1.2895431219807293E-01 a      2052     1    16     2     2\n -3.6183115010678968E-01 a      2053     1    16     2     3\n -1.9197089311858578E-01 a      2054     1    16     2     4\n  1.6791441443786570E+00 a      2055     1    16     2     5\n  1.4524232953370153E+00 a      2056     1    16     2     6\n  8.1332800345877809E-01 a      2057     1    16     2     7\n -6.8993826377906453E-01 a      2058     1    16     2     8\n -6.4581623589215043E-01 a      2059     1    16     2     9\n -1.9086496482644792E+00 a      2060     1    16     2    10\n -7.6174424886678238E-01 a      2061     1    16     2    11\n -6.6106476479584952E-01 a      2062     1    16     2    12\n -6.5143307233530923E-01 a      2063     1    16     2    13\n  6.3145424574265796E-01 a      2064     1    16     2    14\n -2.3081494763260896E-01 a      2065     1    16     2    15\n  1.1456064040705682E-01 a      2066     1    16     2    16\n  1.6252315194690317E-01 a      2067     1    16     2    17\n -1.2291397585047813E-01 a      2068     1    16     2    18\n -6.7674808608296347E-02 a      2069     1    16     2    19\n  5.4942310825997287E-01 a      2070     1    16     2    20\n -1.0797615834794017E-01 a      2071     1    16     2    21\n  2.4950326732348715E-01 a      2072     1    16     2    22\n -7.9414639176233692E-01 a      2073     1    16     2    23\n  2.0544441738751792E-01 a      2074     1    16     2    24\n  1.8992443483722937E-01 a      2075     1    16     2    25\n -4.6582766497660771E-01 a      2076     1    17     2     1\n  2.9539156697999569E-01 a      2077     1    17     2     2\n -2.2097168205408066E-01 a      2078     1    17     2     3\n -1.4860622629638501E-01 a      2079     1    17     2     4\n -3.2498215361218613E-01 a      2080     1    17     2     5\n  3.4427076522021333E-01 a      2081     1    17     2     6\n  8.6586127926198697E-01 a      2082     1    17     2     7\n -1.1418000025514305E-01 a      2083     1    17     2     8\n -6.0056682073398004E-01 a      2084     1    17     2     9\n  2.0450736509644665E-01 a      2085     1    17     2    10\n -1.8519278941182027E-01 a      2086     1    17     2    11\n -1.4644629512368172E+00 a      2087     1    17     2    12\n -2.9378404760799470E-01 a      2088     1    17     2    13\n  5.5384788915605931E-01 a      2089     1    17     2    14\n -1.5004256050064771E-01 a      2090     1    17     2    15\n  3.2806846888851510E-01 a      2091     1    17     2    16\n  2.7598536643862270E-01 a      2092     1    17     2    17\n  4.1850888007058207E-01 a      2093     1    17     2    18\n -5.5362304975505497E-02 a      2094     1    17     2    19\n  2.6951266238898874E-01 a      2095     1    17     2    20\n -2.4264170360616094E-02 a      2096     1    17     2    21\n -1.8676465863061775E-01 a      2097     1    17     2    22\n -3.8787011654837039E-01 a      2098     1    17     2    23\n  3.4485637458118229E-01 a      2099     1    17     2    24\n -3.0786400824237545E-02 a      2100     1    17     2    25\n -1.4217762050351745E-01 a      2101     1    18     2     1\n -7.0998782591968046E-01 a      2102     1    18     2     2\n -9.6362930548428383E-01 a      2103     1    18     2     3\n  7.5180370041830813E-02 a      2104     1    18     2     4\n  9.3452511163166374E-01 a      2105     1    18     2     5\n  7.5072353982545093E-01 a      2106     1    18     2     6\n -1.4600462437868158E+00 a      2107     1    18     2     7\n -1.0484471284226574E-01 a      2108     1    18     2     8\n -1.5226425654047304E+00 a      2109     1    18     2     9\n -8.8296305768438263E-02 a      2110     1    18     2    10\n -3.6274389516383643E-01 a      2111     1    18     2    11\n  8.8349447132068071E-01 a      2112     1    18     2    12\n  3.6371290147774743E-01 a      2113     1    18     2    13\n -4.7916817706816656E-01 a      2114     1    18     2    14\n  1.3662341082955812E-01 a      2115     1    18     2    15\n  1.3172314297178116E+00 a      2116     1    18     2    16\n  3.4403068584860565E-02 a      2117     1    18     2    17\n  3.6061432566306936E-02 a      2118     1    18     2    18\n  4.5896212647717503E-02 a      2119     1    18     2    19\n -1.8589693017644275E+00 a      2120     1    18     2    20\n  1.5237137982152765E-01 a      2121     1    18     2    21\n -3.8234921593024973E-01 a      2122     1    18     2    22\n  3.5542438141750315E-02 a      2123     1    18     2    23\n -3.9944133636062124E-01 a      2124     1    18     2    24\n -6.5550378551330324E-01 a      2125     1    18     2    25\n  1.2816550559385723E-01 a      2126     1    19     2     1\n  3.5486759391369166E-02 a      2127     1    19     2     2\n  4.6182319454349319E-01 a      2128     1    19     2     3\n -5.5122652267036590E-03 a      2129     1    19     2     4\n -3.5080949888496260E+00 a      2130     1    19     2     5\n  7.1486948663206473E-01 a      2131     1    19     2     6\n -2.1201853030552007E+00 a      2132     1    19     2     7\n  7.2604028903282403E-01 a      2133     1    19     2     8\n  5.1081128242304719E-01 a      2134     1    19     2     9\n -4.9137504534121196E-01 a      2135     1    19     2    10\n -1.0472694822448174E+00 a      2136     1    19     2    11\n -1.3523763718593251E+00 a      2137     1    19     2    12\n  2.3568530190159431E-01 a      2138     1    19     2    13\n  5.9584736557607831E-01 a      2139     1    19     2    14\n -3.0079808992756946E-02 a      2140     1    19     2    15\n -1.5268283743999284E-01 a      2141     1    19     2    16\n  9.6122412178057212E-02 a      2142     1    19     2    17\n -1.0684936989401796E-01 a      2143     1    19     2    18\n -5.7716017213991798E-02 a      2144     1    19     2    19\n -2.1338482417439314E-01 a      2145     1    19     2    20\n -3.2012152562395965E-02 a      2146     1    19     2    21\n  6.6195535336631889E-02 a      2147     1    19     2    22\n -4.0717271079249823E-01 a      2148     1    19     2    23\n  4.3854075768154355E-01 a      2149     1    19     2    24\n  5.4824793644114189E-01 a      2150     1    19     2    25\n -1.6683810612646832E-01 a      2151     1    20     2     1\n  2.3322749612412674E-01 a      2152     1    20     2     2\n -4.4183715955442193E-01 a      2153     1    20     2     3\n -7.2076827728753526E-02 a      2154     1    20     2     4\n -5.9352383243727491E-01 a      2155     1    20     2     5\n -3.9339117998165263E-01 a      2156     1    20     2     6\n -5.4931274369409873E-02 a      2157     1    20     2     7\n -4.5548835587531822E-01 a      2158     1    20     2     8\n -6.5732706177413358E-01 a      2159     1    20     2     9\n -1.1236237633542311E-01 a      2160     1    20     2    10\n  1.1351566319349074E-02 a      2161     1    20     2    11\n -1.2386831457708261E+00 a      2162     1    20     2    12\n  4.5243628166561789E-01 a      2163     1    20     2    13\n -5.8831183211013338E-01 a      2164     1    20     2    14\n -8.3869411335455488E-02 a      2165     1    20     2    15\n -7.0984549162019170E-02 a      2166     1    20     2    16\n  3.3054811913793787E-02 a      2167     1    20     2    17\n  1.9644857020909354E-01 a      2168     1    20     2    18\n  1.5161782757226400E-01 a      2169     1    20     2    19\n -2.3505702805909551E-01 a      2170     1    20     2    20\n -1.7918789556131143E-01 a      2171     1    20     2    21\n  3.4990356667744421E-01 a      2172     1    20     2    22\n  6.4840494486623490E-01 a      2173     1    20     2    23\n -1.4478590661265617E-01 a      2174     1    20     2    24\n  2.1297816904812697E-01 a      2175     1    20     2    25\n  3.4493308448955345E-01 a      2176     1    21     2     1\n  3.5266855354427494E-02 a      2177     1    21     2     2\n -2.7754410875303576E-01 a      2178     1    21     2     3\n  4.6768620046741878E-02 a      2179     1    21     2     4\n -1.5769313809619548E-01 a      2180     1    21     2     5\n  1.3497835265205210E-01 a      2181     1    21     2     6\n -3.7341652004504744E-01 a      2182     1    21     2     7\n -3.0627556863254835E-01 a      2183     1    21     2     8\n -2.2925939617710103E-01 a      2184     1    21     2     9\n -3.8592084381092573E-01 a      2185     1    21     2    10\n  4.1234641447800625E-02 a      2186     1    21     2    11\n -9.5022250284578980E-01 a      2187     1    21     2    12\n -1.1125930303081784E+00 a      2188     1    21     2    13\n -5.3122650273704952E-01 a      2189     1    21     2    14\n  2.3060682491837362E-02 a      2190     1    21     2    15\n -1.5104224681786016E+00 a      2191     1    21     2    16\n  1.4753038731650985E-03 a      2192     1    21     2    17\n  1.5143866707297242E-02 a      2193     1    21     2    18\n  8.6090707736472302E-02 a      2194     1    21     2    19\n -6.2430761394861624E-02 a      2195     1    21     2    20\n -6.1308060604509992E-03 a      2196     1    21     2    21\n -1.4270727537208755E-01 a      2197     1    21     2    22\n  4.1134552752308873E-01 a      2198     1    21     2    23\n -6.8567787253466550E-01 a      2199     1    21     2    24\n -6.7206916205524492E-01 a      2200     1    21     2    25\n -1.5391019835641329E+00 a      2201     1    22     2     1\n  1.7206752534353434E-01 a      2202     1    22     2     2\n  6.7593465480848644E-02 a      2203     1    22     2     3\n -8.5997555363846803E-02 a      2204     1    22     2     4\n -9.6065684505879689E-01 a      2205     1    22     2     5\n  1.1113173657279094E+00 a      2206     1    22     2     6\n -3.0842014372062625E+00 a      2207     1    22     2     7\n -1.4384158041499902E+00 a      2208     1    22     2     8\n  1.1309101459634252E+00 a      2209     1    22     2     9\n  1.5105165505154550E-01 a      2210     1    22     2    10\n  3.0645396828385907E-01 a      2211     1    22     2    11\n  6.4601478772770526E-01 a      2212     1    22     2    12\n  4.8724111088572403E-01 a      2213     1    22     2    13\n -4.6620160034283531E-01 a      2214     1    22     2    14\n -4.8803479432276621E-02 a      2215     1    22     2    15\n -9.0430630054920480E-01 a      2216     1    22     2    16\n -6.9889480249312042E-01 a      2217     1    22     2    17\n -1.4468447857571731E+00 a      2218     1    22     2    18\n  2.3039464990726008E-01 a      2219     1    22     2    19\n  5.4576177723516872E-01 a      2220     1    22     2    20\n -7.8015018576137352E-02 a      2221     1    22     2    21\n -1.6133123661713483E-01 a      2222     1    22     2    22\n -1.8319296597374665E-01 a      2223     1    22     2    23\n  2.7253642896910552E-01 a      2224     1    22     2    24\n -1.1584411372851944E+00 a      2225     1    22     2    25\n -5.5424557394569851E-01 a      2226     1    23     2     1\n  7.0029876501251875E-01 a      2227     1    23     2     2\n  8.6637467798596698E-02 a      2228     1    23     2     3\n -7.8591217867498966E-02 a      2229     1    23     2     4\n -3.8578050693417802E+00 a      2230     1    23     2     5\n -1.5514902939375283E-02 a      2231     1    23     2     6\n  5.3013810166945474E-01 a      2232     1    23     2     7\n -6.0550270203294210E-01 a      2233     1    23     2     8\n  4.3671597358238062E-01 a      2234     1    23     2     9\n -3.5715147706396755E-01 a      2235     1    23     2    10\n  1.0882856270043771E-01 a      2236     1    23     2    11\n  1.7281037261210461E+00 a      2237     1    23     2    12\n -5.7515626421966193E-01 a      2238     1    23     2    13\n -1.3375042180867350E-01 a      2239     1    23     2    14\n -6.5503722712337037E-02 a      2240     1    23     2    15\n -2.2025191432304744E-02 a      2241     1    23     2    16\n -8.2655071054651752E-02 a      2242     1    23     2    17\n -2.1027511956094072E-01 a      2243     1    23     2    18\n  2.8902376330777999E-02 a      2244     1    23     2    19\n  1.3213999048426042E-01 a      2245     1    23     2    20\n -1.1460728829522189E-01 a      2246     1    23     2    21\n -5.8828720552246631E-02 a      2247     1    23     2    22\n -6.0152091553027887E-01 a      2248     1    23     2    23\n -7.1147789709956066E-01 a      2249     1    23     2    24\n  5.2100860083053230E-02 a      2250     1    23     2    25\n -1.4344935215141292E+00 a      2251     1    24     2     1\n  9.2746205501548851E-01 a      2252     1    24     2     2\n -7.7216665110619850E-02 a      2253     1    24     2     3\n -2.8798885399279067E-01 a      2254     1    24     2     4\n  3.7454428387915351E+00 a      2255     1    24     2     5\n -1.5625207926251825E+00 a      2256     1    24     2     6\n  3.6660395247444808E+00 a      2257     1    24     2     7\n  2.0253108718040456E+00 a      2258     1    24     2     8\n  1.6318897346220811E+00 a      2259     1    24     2     9\n  2.4800845209015692E+00 a      2260     1    24     2    10\n  1.4907673234653401E-01 a      2261     1    24     2    11\n -4.8613830479267428E-01 a      2262     1    24     2    12\n -6.2019617622102718E-01 a      2263     1    24     2    13\n  2.5952895630277122E+00 a      2264     1    24     2    14\n -4.5829312494493707E-01 a      2265     1    24     2    15\n -2.3487736500391203E+00 a      2266     1    24     2    16\n -3.0197296181118466E-01 a      2267     1    24     2    17\n -2.3095098659235344E-01 a      2268     1    24     2    18\n -3.3608639629945564E-01 a      2269     1    24     2    19\n  6.8582631891122880E-01 a      2270     1    24     2    20\n -5.0043316001326121E-01 a      2271     1    24     2    21\n  1.0373154633440593E-01 a      2272     1    24     2    22\n -1.6204291412423728E+00 a      2273     1    24     2    23\n  1.5638127191591980E+00 a      2274     1    24     2    24\n -2.3309635202853114E+00 a      2275     1    24     2    25\n  2.4489203274966312E-01 a      2276     1    25     2     1\n -2.1518661593071592E-01 a      2277     1    25     2     2\n -5.5802781061846052E-02 a      2278     1    25     2     3\n  4.8845808066633911E-02 a      2279     1    25     2     4\n -1.7557830120404228E-01 a      2280     1    25     2     5\n  2.7192371503339396E-01 a      2281     1    25     2     6\n  5.1576877441197089E-01 a      2282     1    25     2     7\n -2.5099882589234657E-01 a      2283     1    25     2     8\n  3.9307512202972061E-01 a      2284     1    25     2     9\n -1.1210987406922690E+00 a      2285     1    25     2    10\n -1.0439036996834390E-01 a      2286     1    25     2    11\n -4.6783720798261658E-01 a      2287     1    25     2    12\n -3.4722854444840895E-01 a      2288     1    25     2    13\n  3.6029120328851533E-01 a      2289     1    25     2    14\n -2.8984025140998956E-02 a      2290     1    25     2    15\n -2.4076394027143521E-02 a      2291     1    25     2    16\n -3.5643134150827477E-01 a      2292     1    25     2    17\n -8.0475176631190595E-02 a      2293     1    25     2    18\n -4.1056819128214495E-01 a      2294     1    25     2    19\n  7.9766759746990878E-02 a      2295     1    25     2    20\n -6.3351379628206916E-02 a      2296     1    25     2    21\n -6.6416236384591232E-01 a      2297     1    25     2    22\n  9.9799168900512741E-02 a      2298     1    25     2    23\n  3.6809534821907935E-01 a      2299     1    25     2    24\n  4.4938760583598990E-02 a      2300     1    25     2    25\n  1.2254169285344445E+00 b      2301     2     1\n -1.2971586668099495E+00 b      2302     2     2\n  1.5496818967172494E+00 b      2303     2     3\n -5.1016745940541508E+00 b      2304     2     4\n  1.0570990409883480E+01 b      2305     2     5\n -4.5156912340057982E+00 b      2306     2     6\n -5.3447216226080076E+00 b      2307     2     7\n  4.9121474463955411E-01 b      2308     2     8\n  1.8948035234025085E+00 b      2309     2     9\n  8.0589028128011697E-01 b      2310     2    10\n -1.7792287088770824E+00 b      2311     2    11\n  1.4582711867438684E+01 b      2312     2    12\n -1.7367556115635654E+00 b      2313     2    13\n -1.9740162795480241E+00 b      2314     2    14\n -2.4240966432157127E+00 b      2315     2    15\n -2.8599154334878940E+00 b      2316     2    16\n  4.0042881027206061E+00 b      2317     2    17\n -4.2248506318729575E+00 b      2318     2    18\n  4.0200826303003624E-02 b      2319     2    19\n -1.2474151269634015E+00 b      2320     2    20\n -9.2525707564953397E+00 b      2321     2    21\n  3.6900482337635778E+00 b      2322     2    22\n  1.2241959433351147E+01 b      2323     2    23\n -3.6270070547836308E+00 b      2324     2    24\n -9.9424710717210443E-02 b      2325     2    25\n -1.7929412362301902E-01 a      2326     2     1     3     1\n -7.9318720367251710E-02 a      2327     2     2     3     1\n -1.2245497150588677E-01 a      2328     2     3     3     1\n  2.6686957929803099E+00 a      2329     2     4     3     1\n  2.2208281256188907E-02 a      2330     2     5     3     1\n -1.3827880546853433E-01 a      2331     2     6     3     1\n  5.8883707570105491E-02 a      2332     2     7     3     1\n -1.8503473008958521E-01 a      2333     2     8     3     1\n  7.9941146090854662E-02 a      2334     2     9     3     1\n  6.0980780074337042E-02 a      2335     2    10     3     1\n  4.2898647862968903E-01 a      2336     2    11     3     1\n -1.6418700509588654E-02 a      2337     2    12     3     1\n  9.2626066276151567E-02 a      2338     2    13     3     1\n  1.6213121749951970E-01 a      2339     2    14     3     1\n  5.0025887501899446E-01 a      2340     2    15     3     1\n -9.3228633980085102E-02 a      2341     2    16     3     1\n -4.2506309509736678E-01 a      2342     2    17     3     1\n -2.8020236882301058E-01 a      2343     2    18     3     1\n  1.3369952476903810E+00 a      2344     2    19     3     1\n  7.6998543117290666E-02 a      2345     2    20     3     1\n  5.8165502415695283E+00 a      2346     2    21     3     1\n  4.9617644425128343E-01 a      2347     2    22     3     1\n  3.8051021746990116E-01 a      2348     2    23     3     1\n  1.1951241138280733E-01 a      2349     2    24     3     1\n  1.3087209279691459E-01 a      2350     2    25     3     1\n -2.6815621704168309E+00 b      2351     3     1\n"
  },
  {
    "path": "examples/nnp-predict/DMABN_SCAN/input.data",
    "content": "begin\ncomment       frame number       51\natom      19.83251167146305      16.41913713228821      14.16783556224251     C  0.00  0.00       0.00570937805307       0.08432160529386      -0.03802980568277\natom      19.94312355646866      11.69393878949732      14.17410262328673     C  0.00  0.00      -0.07435648445475       0.02184249364754       0.00881332970143\natom      15.84154197252689      14.18721189705679      14.24155885726955     C  0.00  0.00       0.02998903171000       0.01161345609006      -0.01614157184062\natom      14.46771974192691      16.52911346925335      14.15446414798641     C  0.00  0.00       0.02825211245628      -0.00679186972071       0.01067765902089\natom      11.90001209045941      16.50440326164718      14.10001557121353     C  0.00  0.00       0.00762251101379      -0.04054091659537       0.01107218637850\natom      10.52693843736862      14.19175453817904      14.24867638671206     C  0.00  0.00       0.04489483017033      -0.00970003430984      -0.02024170809199\natom      11.88525530053014      11.87627801089468      14.03804339218586     C  0.00  0.00       0.01050492288895      -0.03025563548793       0.04062107513648\natom      14.55399939930356      11.88307666854348      14.16029752399963     C  0.00  0.00      -0.00430630286069      -0.01331581049870      -0.00376499999923\natom       7.94035181627116      14.20878640658312      14.21053262433509     C  0.00  0.00      -0.07441555771308      -0.00325503384669       0.00082781395929\natom      18.51576746385395      14.23362538195587      14.14454518191298     N  0.00  0.00      -0.03910867744178      -0.07459503409686       0.00679871752372\natom       5.70790049494324      14.17883214623779      14.18710950383843     N  0.00  0.00       0.04080327791136       0.00177504000833       0.00118773139851\natom      21.79028529767151      16.11497933011361      14.26552105714931     H  0.00  0.00       0.02518293764933      -0.00361728537155       0.00618743342718\natom      19.61077628263096      17.86917886537563      12.41697223367492     H  0.00  0.00      -0.00091709441398      -0.03521300054738       0.01742148802879\natom      19.21953158661805      17.71831608185630      15.59063976560335     H  0.00  0.00       0.00199657064710       0.00520019321164       0.02297470209990\natom      21.82497590676626      12.12531471861068      14.29058750869887     H  0.00  0.00       0.04538124820076       0.00616351842390      -0.00154483025617\natom      19.32669969441613      10.57749722415571      15.86241146777433     H  0.00  0.00       0.00591786395647       0.00729899135856      -0.01249697562980\natom      19.35969488797767      10.76021845677893      12.44205910126362     H  0.00  0.00       0.00829470188437      -0.00858990474455      -0.00147517152114\natom      15.56901622106281      18.30123521694460      14.42236692729784     H  0.00  0.00      -0.01360814881885      -0.01287249963721      -0.00929548183066\natom      10.91615035702339      18.17723906171991      14.17763298181264     H  0.00  0.00      -0.02115105437214       0.03530021184193       0.00007051927839\natom      11.03999403230822       9.89099801104345      14.54005436633091     H  0.00  0.00       0.00478517659222       0.04200087762286      -0.02092001237780\natom      15.70700931574327      10.08078663320902      14.18667669126373     H  0.00  0.00      -0.02236155378428       0.02151554633149      -0.00040927268169\nenergy     -76.86434126036589\ncharge       0\nend\n"
  },
  {
    "path": "examples/nnp-predict/DMABN_SCAN/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.6581036498775639E+00\nconv_energy   1.1608720067118788E+03\nconv_length   3.8128564085005848E+01\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              3              # Number of elements.\nelements                        C N H          # Specification of elements.\ncutoff_type                     6 0.0          # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\nrandom_seed 987654321\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\njacobian_mode                   1\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntask_batch_size_energy          1\ntask_batch_size_force           1\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints                5             # Write energy comparison.\nwrite_trainforces                5             # Write force comparison.\nwrite_weights_epoch              5             # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n## ####################\n## # GRADIENT DESCENT #\n## ####################\n## gradient_type                   0              # Gradient descent type (0 = Fixed step size).\n## gradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\nsymfunction_short C 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 C -1.30E+01 1.30E+01 p2\nsymfunction_short C 20 C -1.10E+01 1.10E+01 p2\nsymfunction_short C 20 C -9.00E+00 9.00E+00 p2\nsymfunction_short C 20 C -7.00E+00 7.00E+00 p2\nsymfunction_short C 20 C -5.00E+00 5.00E+00 p2\nsymfunction_short C 20 C -3.00E+00 3.00E+00 p2\nsymfunction_short C 20 C 0.00E+00 6.00E+00 p2\nsymfunction_short C 20 C 3.00E+00 9.00E+00 p2\nsymfunction_short C 20 C 6.00E+00 1.20E+01 p2\nsymfunction_short C 20 C 9.00E+00 1.50E+01 p2\n \nsymfunction_short C 20 N -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 N -1.30E+01 1.30E+01 p2\nsymfunction_short C 20 N -1.10E+01 1.10E+01 p2\nsymfunction_short C 20 N -9.00E+00 9.00E+00 p2\nsymfunction_short C 20 N -7.00E+00 7.00E+00 p2\nsymfunction_short C 20 N -5.00E+00 5.00E+00 p2\nsymfunction_short C 20 N -3.00E+00 3.00E+00 p2\nsymfunction_short C 20 N 0.00E+00 6.00E+00 p2\nsymfunction_short C 20 N 3.00E+00 9.00E+00 p2\nsymfunction_short C 20 N 6.00E+00 1.20E+01 p2\nsymfunction_short C 20 N 9.00E+00 1.50E+01 p2\n \nsymfunction_short C 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 H -1.30E+01 1.30E+01 p2\nsymfunction_short C 20 H -1.10E+01 1.10E+01 p2\nsymfunction_short C 20 H -9.00E+00 9.00E+00 p2\nsymfunction_short C 20 H -7.00E+00 7.00E+00 p2\nsymfunction_short C 20 H -5.00E+00 5.00E+00 p2\nsymfunction_short C 20 H -3.00E+00 3.00E+00 p2\nsymfunction_short C 20 H 0.00E+00 6.00E+00 p2\nsymfunction_short C 20 H 3.00E+00 9.00E+00 p2\nsymfunction_short C 20 H 6.00E+00 1.20E+01 p2\nsymfunction_short C 20 H 9.00E+00 1.50E+01 p2\n \n \nsymfunction_short N 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short N 20 C -1.30E+01 1.30E+01 p2\nsymfunction_short N 20 C -1.10E+01 1.10E+01 p2\nsymfunction_short N 20 C -9.00E+00 9.00E+00 p2\nsymfunction_short N 20 C -7.00E+00 7.00E+00 p2\nsymfunction_short N 20 C -5.00E+00 5.00E+00 p2\nsymfunction_short N 20 C -3.00E+00 3.00E+00 p2\nsymfunction_short N 20 C 0.00E+00 6.00E+00 p2\nsymfunction_short N 20 C 3.00E+00 9.00E+00 p2\nsymfunction_short N 20 C 6.00E+00 1.20E+01 p2\nsymfunction_short N 20 C 9.00E+00 1.50E+01 p2\n \nsymfunction_short N 20 N -1.50E+01 1.50E+01 p2\nsymfunction_short N 20 N -1.30E+01 1.30E+01 p2\n# symfunction_short  N   28  N      -1.10E+01  1.10E+01\n# symfunction_short  N   28  N      -9.00E+00  9.00E+00\n# symfunction_short  N   28  N      -7.00E+00  7.00E+00\n# symfunction_short  N   28  N      -5.00E+00  5.00E+00\n# symfunction_short  N   28  N      -3.00E+00  3.00E+00\n# symfunction_short  N   28  N       0.00E+00  6.00E+00\n# symfunction_short  N   28  N       3.00E+00  9.00E+00\n# symfunction_short  N   28  N       6.00E+00  1.20E+01\nsymfunction_short N 20 N 9.00E+00 1.50E+01 p2\n \nsymfunction_short N 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short N 20 H -1.30E+01 1.30E+01 p2\nsymfunction_short N 20 H -1.10E+01 1.10E+01 p2\nsymfunction_short N 20 H -9.00E+00 9.00E+00 p2\nsymfunction_short N 20 H -7.00E+00 7.00E+00 p2\nsymfunction_short N 20 H -5.00E+00 5.00E+00 p2\n# symfunction_short  N   28  H      -3.00E+00  3.00E+00\nsymfunction_short N 20 H 0.00E+00 6.00E+00 p2\nsymfunction_short N 20 H 3.00E+00 9.00E+00 p2\nsymfunction_short N 20 H 6.00E+00 1.20E+01 p2\nsymfunction_short N 20 H 9.00E+00 1.50E+01 p2\n \n \nsymfunction_short H 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 C -1.30E+01 1.30E+01 p2\nsymfunction_short H 20 C -1.10E+01 1.10E+01 p2\nsymfunction_short H 20 C -9.00E+00 9.00E+00 p2\nsymfunction_short H 20 C -7.00E+00 7.00E+00 p2\nsymfunction_short H 20 C -5.00E+00 5.00E+00 p2\nsymfunction_short H 20 C -3.00E+00 3.00E+00 p2\nsymfunction_short H 20 C 0.00E+00 6.00E+00 p2\nsymfunction_short H 20 C 3.00E+00 9.00E+00 p2\nsymfunction_short H 20 C 6.00E+00 1.20E+01 p2\nsymfunction_short H 20 C 9.00E+00 1.50E+01 p2\n \nsymfunction_short H 20 N -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 N -1.30E+01 1.30E+01 p2\nsymfunction_short H 20 N -1.10E+01 1.10E+01 p2\nsymfunction_short H 20 N -9.00E+00 9.00E+00 p2\nsymfunction_short H 20 N -7.00E+00 7.00E+00 p2\nsymfunction_short H 20 N -5.00E+00 5.00E+00 p2\n# symfunction_short  H   28  N      -3.00E+00  3.00E+00\nsymfunction_short H 20 N 0.00E+00 6.00E+00 p2\nsymfunction_short H 20 N 3.00E+00 9.00E+00 p2\nsymfunction_short H 20 N 6.00E+00 1.20E+01 p2\nsymfunction_short H 20 N 9.00E+00 1.50E+01 p2\n \nsymfunction_short H 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 H -1.30E+01 1.30E+01 p2\nsymfunction_short H 20 H -1.10E+01 1.10E+01 p2\nsymfunction_short H 20 H -9.00E+00 9.00E+00 p2\nsymfunction_short H 20 H -7.00E+00 7.00E+00 p2\nsymfunction_short H 20 H -5.00E+00 5.00E+00 p2\nsymfunction_short H 20 H -3.00E+00 3.00E+00 p2\nsymfunction_short H 20 H 0.00E+00 6.00E+00 p2\nsymfunction_short H 20 H 3.00E+00 9.00E+00 p2\nsymfunction_short H 20 H 6.00E+00 1.20E+01 p2\nsymfunction_short H 20 H 9.00E+00 1.50E+01 p2\n \n \nsymfunction_short C 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short C 22 C N -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C N -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C N -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C N -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C N -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short C 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \nsymfunction_short C 22 N N -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 N N -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 N N -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 N N -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 N N -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 N N -1.50E+01 1.50E+01 49.10 169.10 p2\n# symfunction_short  C   89  N   N   -1.30E+01  -90.00   90.00  1.30E+01\nsymfunction_short C 22 N N -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 N N -1.30E+01 1.30E+01 0.00 180.00 p2\n# symfunction_short  C   89  N   N   -1.30E+01    0.00  120.00  1.30E+01\nsymfunction_short C 22 N N -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 N N -1.30E+01 1.30E+01 49.10 169.10 p2\n# symfunction_short  C   89  N   N   -1.10E+01  -90.00   90.00  1.10E+01\nsymfunction_short C 22 N N -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 N N -1.10E+01 1.10E+01 0.00 180.00 p2\n# symfunction_short  C   89  N   N   -1.10E+01    0.00  120.00  1.10E+01\nsymfunction_short C 22 N N -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 N N -1.10E+01 1.10E+01 49.10 169.10 p2\n# symfunction_short  C   89  N   N   -9.00E+00  -90.00   90.00  9.00E+00\nsymfunction_short C 22 N N -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 N N -9.00E+00 9.00E+00 0.00 180.00 p2\n# symfunction_short  C   89  N   N   -9.00E+00    0.00  120.00  9.00E+00\nsymfunction_short C 22 N N -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 N N -9.00E+00 9.00E+00 49.10 169.10 p2\n# symfunction_short  C   89  N   N   -7.00E+00  -90.00   90.00  7.00E+00\n# symfunction_short  C   89  N   N   -7.00E+00   90.00  270.00  7.00E+00\n# symfunction_short  C   89  N   N   -7.00E+00    0.00  180.00  7.00E+00\n# symfunction_short  C   89  N   N   -7.00E+00    0.00  120.00  7.00E+00\n# symfunction_short  C   89  N   N   -7.00E+00   60.00  180.00  7.00E+00\n# symfunction_short  C   89  N   N   -7.00E+00   49.10  169.10  7.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00  -90.00   90.00  5.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00   90.00  270.00  5.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00    0.00  180.00  5.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00    0.00  120.00  5.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00   60.00  180.00  5.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00   49.10  169.10  5.00E+00\n# symfunction_short  C   89  N   N    0.00E+00  -90.00   90.00  1.00E+01\nsymfunction_short C 22 N N 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 N N 0.00E+00 1.00E+01 0.00 180.00 p2\n# symfunction_short  C   89  N   N    0.00E+00    0.00  120.00  1.00E+01\nsymfunction_short C 22 N N 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 N N 0.00E+00 1.00E+01 49.10 169.10 p2\n# symfunction_short  C   89  N   N    2.50E+00  -90.00   90.00  1.25E+01\nsymfunction_short C 22 N N 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 N N 2.50E+00 1.25E+01 0.00 180.00 p2\n# symfunction_short  C   89  N   N    2.50E+00    0.00  120.00  1.25E+01\nsymfunction_short C 22 N N 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 N N 2.50E+00 1.25E+01 49.10 169.10 p2\n# symfunction_short  C   89  N   N    5.00E+00  -90.00   90.00  1.50E+01\nsymfunction_short C 22 N N 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 N N 5.00E+00 1.50E+01 0.00 180.00 p2\n# symfunction_short  C   89  N   N    5.00E+00    0.00  120.00  1.50E+01\nsymfunction_short C 22 N N 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 N N 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short C 22 N H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 N H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 N H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 N H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 N H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \nsymfunction_short C 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \n \nsymfunction_short N 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short N 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short N 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short N 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2\n# symfunction_short  N   89  C   C    5.00E+00   90.00  270.00  1.50E+01\nsymfunction_short N 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2\n# symfunction_short  N   89  C   C    5.00E+00   60.00  180.00  1.50E+01\n# symfunction_short  N   89  C   C    5.00E+00   49.10  169.10  1.50E+01\n \nsymfunction_short N 22 C N -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short N 22 C N -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short N 22 C N -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C N -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 C N -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 C N -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 49.10 169.10 p2\n# symfunction_short  N   89  C   N   -1.10E+01  -90.00   90.00  1.10E+01\n# symfunction_short  N   89  C   N   -1.10E+01   90.00  270.00  1.10E+01\n# symfunction_short  N   89  C   N   -1.10E+01    0.00  180.00  1.10E+01\n# symfunction_short  N   89  C   N   -1.10E+01    0.00  120.00  1.10E+01\n# symfunction_short  N   89  C   N   -1.10E+01   60.00  180.00  1.10E+01\n# symfunction_short  N   89  C   N   -1.10E+01   49.10  169.10  1.10E+01\n# symfunction_short  N   89  C   N   -9.00E+00  -90.00   90.00  9.00E+00\n# symfunction_short  N   89  C   N   -9.00E+00   90.00  270.00  9.00E+00\n# symfunction_short  N   89  C   N   -9.00E+00    0.00  180.00  9.00E+00\n# symfunction_short  N   89  C   N   -9.00E+00    0.00  120.00  9.00E+00\n# symfunction_short  N   89  C   N   -9.00E+00   60.00  180.00  9.00E+00\n# symfunction_short  N   89  C   N   -9.00E+00   49.10  169.10  9.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00  -90.00   90.00  7.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00   90.00  270.00  7.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00    0.00  180.00  7.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00    0.00  120.00  7.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00   60.00  180.00  7.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00   49.10  169.10  7.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00  -90.00   90.00  5.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00   90.00  270.00  5.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00    0.00  180.00  5.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00    0.00  120.00  5.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00   60.00  180.00  5.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00   49.10  169.10  5.00E+00\n# symfunction_short  N   89  C   N    0.00E+00  -90.00   90.00  1.00E+01\n# symfunction_short  N   89  C   N    0.00E+00   90.00  270.00  1.00E+01\n# symfunction_short  N   89  C   N    0.00E+00    0.00  180.00  1.00E+01\n# symfunction_short  N   89  C   N    0.00E+00    0.00  120.00  1.00E+01\n# symfunction_short  N   89  C   N    0.00E+00   60.00  180.00  1.00E+01\n# symfunction_short  N   89  C   N    0.00E+00   49.10  169.10  1.00E+01\nsymfunction_short N 22 C N 2.50E+00 1.25E+01 -90.00 90.00 p2\n# symfunction_short  N   89  C   N    2.50E+00   90.00  270.00  1.25E+01\nsymfunction_short N 22 C N 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short N 22 C N 2.50E+00 1.25E+01 0.00 120.00 p2\n# symfunction_short  N   89  C   N    2.50E+00   60.00  180.00  1.25E+01\n# symfunction_short  N   89  C   N    2.50E+00   49.10  169.10  1.25E+01\nsymfunction_short N 22 C N 5.00E+00 1.50E+01 -90.00 90.00 p2\n# symfunction_short  N   89  C   N    5.00E+00   90.00  270.00  1.50E+01\nsymfunction_short N 22 C N 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C N 5.00E+00 1.50E+01 0.00 120.00 p2\n# symfunction_short  N   89  C   N    5.00E+00   60.00  180.00  1.50E+01\n# symfunction_short  N   89  C   N    5.00E+00   49.10  169.10  1.50E+01\n \nsymfunction_short N 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short N 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short N 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short N 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2\n# symfunction_short  N   89  C   H    5.00E+00   90.00  270.00  1.50E+01\nsymfunction_short N 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2\n# symfunction_short  N   89  C   H    5.00E+00   60.00  180.00  1.50E+01\nsymfunction_short N 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \n# symfunction_short  N   89  N   N   -1.50E+01  -90.00   90.00  1.50E+01\n# symfunction_short  N   89  N   N   -1.50E+01   90.00  270.00  1.50E+01\n# symfunction_short  N   89  N   N   -1.50E+01    0.00  180.00  1.50E+01\n# symfunction_short  N   89  N   N   -1.50E+01    0.00  120.00  1.50E+01\n# symfunction_short  N   89  N   N   -1.50E+01   60.00  180.00  1.50E+01\n# symfunction_short  N   89  N   N   -1.50E+01   49.10  169.10  1.50E+01\n# symfunction_short  N   89  N   N   -1.30E+01  -90.00   90.00  1.30E+01\n# symfunction_short  N   89  N   N   -1.30E+01   90.00  270.00  1.30E+01\n# symfunction_short  N   89  N   N   -1.30E+01    0.00  180.00  1.30E+01\n# symfunction_short  N   89  N   N   -1.30E+01    0.00  120.00  1.30E+01\n# symfunction_short  N   89  N   N   -1.30E+01   60.00  180.00  1.30E+01\n# symfunction_short  N   89  N   N   -1.30E+01   49.10  169.10  1.30E+01\n# symfunction_short  N   89  N   N   -1.10E+01  -90.00   90.00  1.10E+01\n# symfunction_short  N   89  N   N   -1.10E+01   90.00  270.00  1.10E+01\n# symfunction_short  N   89  N   N   -1.10E+01    0.00  180.00  1.10E+01\n# symfunction_short  N   89  N   N   -1.10E+01    0.00  120.00  1.10E+01\n# symfunction_short  N   89  N   N   -1.10E+01   60.00  180.00  1.10E+01\n# symfunction_short  N   89  N   N   -1.10E+01   49.10  169.10  1.10E+01\n# symfunction_short  N   89  N   N   -9.00E+00  -90.00   90.00  9.00E+00\n# symfunction_short  N   89  N   N   -9.00E+00   90.00  270.00  9.00E+00\n# symfunction_short  N   89  N   N   -9.00E+00    0.00  180.00  9.00E+00\n# symfunction_short  N   89  N   N   -9.00E+00    0.00  120.00  9.00E+00\n# symfunction_short  N   89  N   N   -9.00E+00   60.00  180.00  9.00E+00\n# symfunction_short  N   89  N   N   -9.00E+00   49.10  169.10  9.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00  -90.00   90.00  7.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00   90.00  270.00  7.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00    0.00  180.00  7.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00    0.00  120.00  7.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00   60.00  180.00  7.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00   49.10  169.10  7.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00  -90.00   90.00  5.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00   90.00  270.00  5.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00    0.00  180.00  5.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00    0.00  120.00  5.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00   60.00  180.00  5.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00   49.10  169.10  5.00E+00\n# symfunction_short  N   89  N   N    0.00E+00  -90.00   90.00  1.00E+01\n# symfunction_short  N   89  N   N    0.00E+00   90.00  270.00  1.00E+01\n# symfunction_short  N   89  N   N    0.00E+00    0.00  180.00  1.00E+01\n# symfunction_short  N   89  N   N    0.00E+00    0.00  120.00  1.00E+01\n# symfunction_short  N   89  N   N    0.00E+00   60.00  180.00  1.00E+01\n# symfunction_short  N   89  N   N    0.00E+00   49.10  169.10  1.00E+01\n# symfunction_short  N   89  N   N    2.50E+00  -90.00   90.00  1.25E+01\n# symfunction_short  N   89  N   N    2.50E+00   90.00  270.00  1.25E+01\n# symfunction_short  N   89  N   N    2.50E+00    0.00  180.00  1.25E+01\n# symfunction_short  N   89  N   N    2.50E+00    0.00  120.00  1.25E+01\n# symfunction_short  N   89  N   N    2.50E+00   60.00  180.00  1.25E+01\n# symfunction_short  N   89  N   N    2.50E+00   49.10  169.10  1.25E+01\n# symfunction_short  N   89  N   N    5.00E+00  -90.00   90.00  1.50E+01\n# symfunction_short  N   89  N   N    5.00E+00   90.00  270.00  1.50E+01\n# symfunction_short  N   89  N   N    5.00E+00    0.00  180.00  1.50E+01\n# symfunction_short  N   89  N   N    5.00E+00    0.00  120.00  1.50E+01\n# symfunction_short  N   89  N   N    5.00E+00   60.00  180.00  1.50E+01\n# symfunction_short  N   89  N   N    5.00E+00   49.10  169.10  1.50E+01\n \nsymfunction_short N 22 N H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short N 22 N H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short N 22 N H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 N H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 N H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 N H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 49.10 169.10 p2\n# symfunction_short  N   89  N   H   -1.10E+01  -90.00   90.00  1.10E+01\n# symfunction_short  N   89  N   H   -1.10E+01   90.00  270.00  1.10E+01\n# symfunction_short  N   89  N   H   -1.10E+01    0.00  180.00  1.10E+01\n# symfunction_short  N   89  N   H   -1.10E+01    0.00  120.00  1.10E+01\n# symfunction_short  N   89  N   H   -1.10E+01   60.00  180.00  1.10E+01\n# symfunction_short  N   89  N   H   -1.10E+01   49.10  169.10  1.10E+01\n# symfunction_short  N   89  N   H   -9.00E+00  -90.00   90.00  9.00E+00\n# symfunction_short  N   89  N   H   -9.00E+00   90.00  270.00  9.00E+00\n# symfunction_short  N   89  N   H   -9.00E+00    0.00  180.00  9.00E+00\n# symfunction_short  N   89  N   H   -9.00E+00    0.00  120.00  9.00E+00\n# symfunction_short  N   89  N   H   -9.00E+00   60.00  180.00  9.00E+00\n# symfunction_short  N   89  N   H   -9.00E+00   49.10  169.10  9.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00  -90.00   90.00  7.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00   90.00  270.00  7.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00    0.00  180.00  7.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00    0.00  120.00  7.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00   60.00  180.00  7.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00   49.10  169.10  7.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00  -90.00   90.00  5.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00   90.00  270.00  5.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00    0.00  180.00  5.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00    0.00  120.00  5.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00   60.00  180.00  5.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00   49.10  169.10  5.00E+00\n# symfunction_short  N   89  N   H    0.00E+00  -90.00   90.00  1.00E+01\n# symfunction_short  N   89  N   H    0.00E+00   90.00  270.00  1.00E+01\n# symfunction_short  N   89  N   H    0.00E+00    0.00  180.00  1.00E+01\n# symfunction_short  N   89  N   H    0.00E+00    0.00  120.00  1.00E+01\n# symfunction_short  N   89  N   H    0.00E+00   60.00  180.00  1.00E+01\n# symfunction_short  N   89  N   H    0.00E+00   49.10  169.10  1.00E+01\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short N 22 N H 5.00E+00 1.50E+01 -90.00 90.00 p2\n# symfunction_short  N   89  N   H    5.00E+00   90.00  270.00  1.50E+01\nsymfunction_short N 22 N H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 N H 5.00E+00 1.50E+01 0.00 120.00 p2\n# symfunction_short  N   89  N   H    5.00E+00   60.00  180.00  1.50E+01\n# symfunction_short  N   89  N   H    5.00E+00   49.10  169.10  1.50E+01\n \n \nsymfunction_short N 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short N 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short N 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short N 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2\n# symfunction_short  N   89  H   H    5.00E+00   90.00  270.00  1.50E+01\nsymfunction_short N 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \n \nsymfunction_short H 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short H 22 C N -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C N -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C N -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C N -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C N -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C N -5.00E+00 5.00E+00 -90.00 90.00 p2\n# symfunction_short  H   89  C   N   -5.00E+00   90.00  270.00  5.00E+00\nsymfunction_short H 22 C N -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C N -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C N -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C N -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short H 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \nsymfunction_short H 22 N N -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 N N -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 N N -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 N N -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 N N -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 N N -1.50E+01 1.50E+01 49.10 169.10 p2\n# symfunction_short  H   89  N   N   -1.30E+01  -90.00   90.00  1.30E+01\nsymfunction_short H 22 N N -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 N N -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 N N -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 N N -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 N N -1.30E+01 1.30E+01 49.10 169.10 p2\n# symfunction_short  H   89  N   N   -1.10E+01  -90.00   90.00  1.10E+01\nsymfunction_short H 22 N N -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 N N -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 N N -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 N N -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 N N -1.10E+01 1.10E+01 49.10 169.10 p2\n# symfunction_short  H   89  N   N   -9.00E+00  -90.00   90.00  9.00E+00\n# symfunction_short  H   89  N   N   -9.00E+00   90.00  270.00  9.00E+00\nsymfunction_short H 22 N N -9.00E+00 9.00E+00 0.00 180.00 p2\n# symfunction_short  H   89  N   N   -9.00E+00    0.00  120.00  9.00E+00\nsymfunction_short H 22 N N -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 N N -9.00E+00 9.00E+00 49.10 169.10 p2\n# symfunction_short  H   89  N   N   -7.00E+00  -90.00   90.00  7.00E+00\n# symfunction_short  H   89  N   N   -7.00E+00   90.00  270.00  7.00E+00\n# symfunction_short  H   89  N   N   -7.00E+00    0.00  180.00  7.00E+00\n# symfunction_short  H   89  N   N   -7.00E+00    0.00  120.00  7.00E+00\n# symfunction_short  H   89  N   N   -7.00E+00   60.00  180.00  7.00E+00\n# symfunction_short  H   89  N   N   -7.00E+00   49.10  169.10  7.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00  -90.00   90.00  5.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00   90.00  270.00  5.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00    0.00  180.00  5.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00    0.00  120.00  5.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00   60.00  180.00  5.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00   49.10  169.10  5.00E+00\n# symfunction_short  H   89  N   N    0.00E+00  -90.00   90.00  1.00E+01\nsymfunction_short H 22 N N 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 N N 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 N N 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 N N 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 N N 0.00E+00 1.00E+01 49.10 169.10 p2\n# symfunction_short  H   89  N   N    2.50E+00  -90.00   90.00  1.25E+01\nsymfunction_short H 22 N N 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 N N 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 N N 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 N N 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 N N 2.50E+00 1.25E+01 49.10 169.10 p2\n# symfunction_short  H   89  N   N    5.00E+00  -90.00   90.00  1.50E+01\nsymfunction_short H 22 N N 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 N N 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 N N 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 N N 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 N N 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short H 22 N H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 N H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 N H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 N H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 N H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short H 22 N H -5.00E+00 5.00E+00 -90.00 90.00 p2\n# symfunction_short  H   89  N   H   -5.00E+00   90.00  270.00  5.00E+00\nsymfunction_short H 22 N H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short H 22 N H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short H 22 N H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short H 22 N H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \nsymfunction_short H 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \n \n"
  },
  {
    "path": "examples/nnp-predict/DMABN_SCAN/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   0.0000000000000000E+00   8.9256522521687920E-03   2.1193691142807063E-05   2.8186351799893859E-04\n         1          2   0.0000000000000000E+00   9.0700888046097716E-01   2.8576381266700673E-01   2.1092873186201827E-01\n         1          3   3.0195033033699081E-02   3.7500074021719896E+00   1.8578479493308084E+00   9.1152666615775380E-01\n         1          4   6.6031505277643232E-02   2.0452529717163346E+00   1.0150425459608330E+00   5.0268744284813327E-01\n         1          5   3.2377304639348359E-01   3.2661719444302033E+00   1.8061799390235969E+00   7.5936163395571532E-01\n         1          6   2.4304331955263980E-01   5.7086975789220835E+00   2.5143121459887037E+00   9.5683418222321315E-01\n         1          7   6.8396772830898045E-01   4.2572589291083114E+00   2.7058959418894597E+00   9.7181375055539310E-01\n         1          8   6.9462380456302553E-01   6.5958770747160260E+00   3.1123984883562117E+00   1.2300024965727658E+00\n         1          9   1.2365227913043952E+00   5.1633496520728004E+00   3.6519600786058115E+00   1.0660271704060633E+00\n         1         10   2.0502650228337305E+00   5.9127524978644335E+00   4.5514758691484127E+00   1.0465915668934862E+00\n         1         11   0.0000000000000000E+00   4.8920182697896291E+00   1.4925322646477586E+00   1.2727208114747384E+00\n         1         12   1.9588702750826026E-02   3.5496915700992948E-01   1.7273156425717565E-01   4.8652622105060592E-02\n         1         13   4.6358856026644546E-01   9.6690906167814550E-01   6.9550684680044461E-01   7.4338483356896953E-02\n         1         14   7.1353898653629000E-01   3.1849472187417098E+00   1.6879270299619309E+00   7.3464774899133045E-01\n         1         15   8.0368406740490139E-01   2.0894662819874230E+00   1.3113934265207201E+00   3.3650418449605968E-01\n         1         16   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0.0000000000000000E+00   1.2064451024439849E+01   4.7287969713063047E+00   4.8104413341225678E+00\n         3        126   2.3259310742768453E+00   9.3072757179470891E+00   5.1486074755169975E+00   2.0333143851442643E+00\n         3        127   1.3044507707695725E+00   4.8216881642556233E+00   2.6347193176945511E+00   8.6870585263019129E-01\n         3        128   5.8004139868332238E-01   2.3721569403147518E+00   1.2561626071939613E+00   4.4685169142380748E-01\n         3        129   0.0000000000000000E+00   1.7220464563364832E-02   1.6993796631803737E-03   1.9447962666725928E-03\n         3        130   0.0000000000000000E+00   6.4497202571936465E-03   6.5399816900671987E-05   4.4174684327490560E-04\n         3        131   0.0000000000000000E+00   7.4321974335568950E-03   6.6809117387447937E-05   4.6133220483126751E-04\n         3        132   0.0000000000000000E+00   7.2994115922299183E-03   4.9474618702096379E-05   3.7712090507415011E-04\n         3        133   0.0000000000000000E+00   3.3734111590142711E-03   1.5374892258314301E-05   1.5579040044192490E-04\n         3        134   0.0000000000000000E+00   3.3822091492704655E-03   1.5369686298104343E-05   1.5512793996336896E-04\n         3        135   0.0000000000000000E+00   1.0819104408964209E-03   5.3654806055732672E-06   5.2676060038313820E-05\n         3        136   0.0000000000000000E+00   2.1271945388634593E-03   1.4292347885232800E-04   2.7244351386970518E-04\n         3        137   0.0000000000000000E+00   5.7084149278799727E-03   2.7614712272664717E-04   5.9577851295345742E-04\n         3        138   0.0000000000000000E+00   1.2666745942360771E-02   4.6254999321284599E-04   1.2194762560267694E-03\n         3        139   0.0000000000000000E+00   1.0296178662047314E-02   3.3618711742489701E-04   9.7231453273321242E-04\n         3        140   0.0000000000000000E+00   1.0943562182431192E-02   3.4935115895625785E-04   1.0137544200343152E-03\n         3        141   0.0000000000000000E+00   4.0281834649266825E-03   1.3503994606344858E-04   3.9270294710472856E-04\n         3        142   1.0798355524139150E-02   5.9318125879533876E-02   2.8311459747204590E-02   8.0584582911864943E-03\n         3        143   8.4907826425551745E-03   1.2716446900392064E-01   4.5401206868869337E-02   2.4044167609004793E-02\n         3        144   3.8438479166110423E-03   2.5945373779583081E-01   7.0599923091242245E-02   6.3445363584594752E-02\n         3        145   0.0000000000000000E+00   2.0658192769820705E-01   5.0147917247430097E-02   5.3726419823795536E-02\n         3        146   0.0000000000000000E+00   2.1981466770232580E-01   5.1715982754949569E-02   5.5671316199532472E-02\n         3        147   0.0000000000000000E+00   9.5381087915491505E-02   1.9371326436630327E-02   2.1584069975236635E-02\n         3        148   2.7931367993415024E-01   1.5741524583069244E+00   7.2369008069533125E-01   2.3511900021045912E-01\n         3        149   1.5131104833674924E-01   7.2653078529240722E-01   3.3312243956074661E-01   8.0660084857515899E-02\n         3        150   6.1898490242672417E-02   3.2651093305998635E-01   1.3886755237398829E-01   3.5651372900497816E-02\n         3        151   0.0000000000000000E+00   1.5031053204378248E-02   1.9020118001833359E-03   2.2208604232359618E-03\n         3        152   0.0000000000000000E+00   6.4241302263013583E-02   5.1163399896796092E-03   7.8288521731106273E-03\n         3        153   0.0000000000000000E+00   5.2405091512168001E-01   2.0904800194072842E-01   2.1084918680293815E-01\n         3        154   0.0000000000000000E+00   6.1690299265384618E-01   2.4331345453505185E-01   2.4544812102548538E-01\n         3        155   0.0000000000000000E+00   6.5134520600413293E-01   2.5299712497946958E-01   2.5538741315708724E-01\n         3        156   0.0000000000000000E+00   1.8389263535977701E-01   5.0159125634532946E-02   5.3064424085919437E-02\n         3        157   8.7734262651493283E-02   3.5196973667162923E-01   2.0095697162308601E-01   6.3395415028838900E-02\n         3        158   2.9473194885637119E-05   5.3379709989904256E-01   1.7830178486140599E-01   1.7743241522941827E-01\n         3        159   1.0818297187750856E-05   1.9943903895152408E+00   8.4238911060042276E-01   8.4329837474336089E-01\n         3        160   0.0000000000000000E+00   2.1110251976520478E+00   8.7181286991137774E-01   8.7470226337795931E-01\n         3        161   0.0000000000000000E+00   2.1604234952467798E+00   8.9886590369767938E-01   9.0107000285735661E-01\n         3        162   0.0000000000000000E+00   7.5845301941020926E-01   2.4191219705372846E-01   2.5243569939496613E-01\n         3        163   5.0942647523115192E-01   1.1780505265479460E+00   8.0202708281168422E-01   1.4255860090335176E-01\n         3        164   4.6458845436134606E-02   1.5179103906171585E+00   6.0969749552074615E-01   5.1065962620097738E-01\n         3        165   1.7337927152011788E-02   3.9106341432939393E+00   1.6747672471758837E+00   1.6370186590575673E+00\n         3        166   0.0000000000000000E+00   3.9396694026417740E+00   1.5591498779303730E+00   1.5666305827896807E+00\n         3        167   0.0000000000000000E+00   4.0138344159306127E+00   1.6037920844796403E+00   1.6087180359905053E+00\n         3        168   0.0000000000000000E+00   1.5091893709735424E+00   5.0180822772966394E-01   5.2309052312605542E-01\n         3        169   2.5264361242029407E+00   5.8548795458333283E+00   4.0641393448548868E+00   1.0446504518677489E+00\n         3        170   7.5175412481206938E-01   6.0491915894633328E+00   2.7912046359913494E+00   1.6908607007556695E+00\n         3        171   3.1302661987763947E-01   7.3675356257548472E+00   3.3076133821917959E+00   2.8309557463925108E+00\n         3        172   0.0000000000000000E+00   5.6036572770595763E+00   2.0525279109461891E+00   2.0779545144509575E+00\n         3        173   0.0000000000000000E+00   5.4974091121215070E+00   2.1147903042361587E+00   2.1326037973653307E+00\n         3        174   0.0000000000000000E+00   2.4256329144693147E+00   7.8084033321832080E-01   8.1763163370647507E-01\n         3        175   1.3759613228806920E+00   2.6911206594478072E+00   1.9736723956634545E+00   3.2121410143533713E-01\n         3        176   2.1745134785617978E-01   2.9128177728750613E+00   1.2780220510262488E+00   9.1012167714547443E-01\n         3        177   8.4762323410835380E-02   6.1449273966047970E+00   2.6749047972120317E+00   2.5254668585911135E+00\n         3        178   0.0000000000000000E+00   5.8510814087087120E+00   2.3062870491808658E+00   2.3194820161549310E+00\n         3        179   0.0000000000000000E+00   5.9633131534037949E+00   2.3803153698686099E+00   2.3884251146339945E+00\n         3        180   0.0000000000000000E+00   2.3175610530139714E+00   7.7770513762542393E-01   8.1094980716443343E-01\n         3        181   4.4730762478889803E+00   7.6504678370803481E+00   5.8793945412588071E+00   9.3399157619631756E-01\n         3        182   1.9804489718609235E+00   3.2552843606719595E+00   2.5381448797134913E+00   1.7602861977611073E-01\n         3        183   8.3752582631440531E-01   1.5655828654525372E+00   1.2011454344168695E+00   1.1082134775619010E-01\n         3        184   0.0000000000000000E+00   7.1482854541392360E-02   1.0240183460962853E-02   1.2609394975938428E-02\n         3        185   0.0000000000000000E+00   6.4799546548227477E-02   7.9804834229192240E-03   1.1062346269159968E-02\n         3        186   0.0000000000000000E+00   2.5932958830711596E-02   2.5065133189365366E-03   3.7218599583779734E-03\n         3        187   2.8682537469179183E+00   4.5586270277181562E+00   3.6716587592274030E+00   3.8826629123545109E-01\n         3        188   5.3184311792544858E-01   4.3914873612678882E+00   2.0703862000918019E+00   1.2547229035506695E+00\n         3        189   2.1217569405740649E-01   8.2496983879554264E+00   3.6726138368838077E+00   3.3333622253574249E+00\n         3        190   0.0000000000000000E+00   7.5529308962971493E+00   2.9994280873825208E+00   3.0172473321835316E+00\n         3        191   0.0000000000000000E+00   7.7060637483862875E+00   3.1057048737624218E+00   3.1159618649139711E+00\n         3        192   0.0000000000000000E+00   3.0342146314538043E+00   1.0189917595919784E+00   1.0629602834829577E+00\n         3        193   4.7993545918739056E+00   6.4923299672576196E+00   5.6446922366399415E+00   3.4082468511190522E-01\n         3        194   9.3810638034054117E-01   5.7589295137162262E+00   2.8704304060002253E+00   1.5156759936085604E+00\n         3        195   3.7784683765045562E-01   1.0054429327614857E+01   4.5782769008045934E+00   4.0100324950405284E+00\n         3        196   0.0000000000000000E+00   8.9733432374080042E+00   3.6010953483361754E+00   3.6222580333144219E+00\n         3        197   0.0000000000000000E+00   9.1626804218457281E+00   3.7376383468626093E+00   3.7491152376275663E+00\n         3        198   0.0000000000000000E+00   3.6249203976033630E+00   1.2167389283522099E+00   1.2695832885263578E+00\n         3        199   9.8415463508333578E-01   4.4043442972666345E+00   2.7371207312831660E+00   1.0483965370947292E+00\n         3        200   1.7438426638874374E-01   1.2982238564110971E+00   6.4775313482199037E-01   3.7260415663336804E-01\n         3        201   6.8383908570577440E-02   5.4462129470807807E-01   2.6304941944840748E-01   1.5482948466171720E-01\n         3        202   0.0000000000000000E+00   1.6351180946724456E-02   1.5181531931493793E-04   1.0488631156613799E-03\n         3        203   0.0000000000000000E+00   3.4474491411356735E-03   3.0427540017497121E-05   2.1749249270905130E-04\n         3        204   0.0000000000000000E+00   1.4849489713062755E-03   1.2147034518224958E-05   8.8639816852757787E-05\n         3        205   0.0000000000000000E+00   9.1006878875634824E-03   5.8719849713919400E-04   1.1219726814402913E-03\n         3        206   0.0000000000000000E+00   3.8328410575109960E-03   1.4298808779026774E-04   3.3078835861347045E-04\n         3        207   0.0000000000000000E+00   5.4514407480856343E-03   1.8875186837256279E-04   5.0521558231940162E-04\n         3        208   0.0000000000000000E+00   4.6319172792174141E-03   1.5719271924057539E-04   4.5178163368523515E-04\n         3        209   0.0000000000000000E+00   5.0908507250858872E-03   1.6939430940113146E-04   4.8825464840686252E-04\n         3        210   0.0000000000000000E+00   1.3624519315845894E-03   4.1989553602825332E-05   1.2556040559165961E-04\n         3        211   3.7636176535169472E-02   2.0195226384691767E-01   9.8059091348624436E-02   2.8423962766891235E-02\n         3        212   2.7461282539233581E-03   8.1045334186492304E-02   2.0348307792322294E-02   1.2328297261465872E-02\n         3        213   9.7401278723618532E-04   1.0770429670003327E-01   2.7156647682140673E-02   2.5144020757316567E-02\n         3        214   0.0000000000000000E+00   8.9193114480282665E-02   2.2779791254796559E-02   2.4343066401206623E-02\n         3        215   0.0000000000000000E+00   9.8026414791324179E-02   2.4288791724394628E-02   2.6055936187046921E-02\n         3        216   0.0000000000000000E+00   3.3404009826364885E-02   5.6131949958147433E-03   6.5793910850868937E-03\n         3        217   4.8631071528394060E-01   2.0463726147038317E+00   1.0778097491661256E+00   2.8130780687997087E-01\n         3        218   2.4946208518389711E-02   2.5202590040394685E-01   8.4387437615384142E-02   3.8977600360448172E-02\n         3        219   8.8794973986827050E-03   9.2821403358363544E-02   3.0174377537242406E-02   1.3817948994681554E-02\n"
  },
  {
    "path": "examples/nnp-predict/DMABN_SCAN/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  7.6700469000180993E-01 a         1     0     1     1     1\n -6.0190855511745439E-03 a         2     0     1     1     2\n  1.0579574412865869E-01 a         3     0     1     1     3\n  6.7860849664543998E-01 a         4     0     1     1     4\n -7.8540603665791453E-01 a         5     0     1     1     5\n  1.3824026004182208E-01 a         6     0     1     1     6\n  6.3652521971281995E-01 a         7     0     1     1     7\n -1.1617582936184434E+00 a         8     0     1     1     8\n  1.0412246142918693E+00 a         9     0     1     1     9\n -1.2111012669651891E-01 a        10     0     1     1    10\n  5.7258060862746840E-01 a        11     0     1     1    11\n -2.5396892476943000E-01 a        12     0     1     1    12\n -1.9004867051987739E-01 a        13     0     1     1    13\n -3.4437863452369655E-01 a        14     0     1     1    14\n -1.1799633122830752E-01 a        15     0     1     1    15\n  1.5393270030223383E-01 a        16     0     1     1    16\n -6.3117461493428867E-02 a        17     0     1     1    17\n  8.5244971293802119E-01 a        18     0     1     1    18\n -7.0952236524210532E-01 a        19     0     1     1    19\n -3.4936179293794121E+00 a        20     0     1     1    20\n -2.6021108832923017E+00 a        21     0     1     1    21\n -1.2555168264627528E-01 a        22     0     1     1    22\n  3.7216482784088190E-01 a        23     0     1     1    23\n  2.1187549376406092E+00 a        24     0     1     1    24\n -1.6686561352735790E-01 a        25     0     1     1    25\n -9.1280745890339099E-01 a        26     0     2     1     1\n  3.0058038824323080E-01 a        27     0     2     1     2\n -3.1540969172228928E+00 a        28     0     2     1     3\n  3.2518728481465846E+00 a        29     0     2     1     4\n  2.5836187348444450E-01 a        30     0     2     1     5\n  1.2741137607840769E+00 a        31     0     2     1     6\n 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2.8180176023717269E-02 a      1952     0    79     1     2\n -2.0209870872016711E+00 a      1953     0    79     1     3\n  1.7338999609446863E+00 a      1954     0    79     1     4\n -3.6140607534589947E-01 a      1955     0    79     1     5\n -3.7164435720118810E-01 a      1956     0    79     1     6\n  2.0835792796211131E-01 a      1957     0    79     1     7\n  4.2256146512280163E-01 a      1958     0    79     1     8\n -4.2639335680714141E-01 a      1959     0    79     1     9\n -4.6995360732449731E-01 a      1960     0    79     1    10\n  9.4793559915270081E-02 a      1961     0    79     1    11\n  2.6949946587872353E+00 a      1962     0    79     1    12\n -2.3614222010287702E+00 a      1963     0    79     1    13\n  2.8557652789045793E+00 a      1964     0    79     1    14\n -1.6157502722132091E+00 a      1965     0    79     1    15\n  1.4707537328376374E-01 a      1966     0    79     1    16\n -2.5348457466804364E-01 a      1967     0    79     1    17\n -1.9646490682425530E+00 a      1968     0    79     1    18\n -8.2395010039097916E-01 a      1969     0    79     1    19\n -2.1246351916446446E-01 a      1970     0    79     1    20\n -1.7108495242219797E+00 a      1971     0    79     1    21\n  8.7162123438614014E-01 a      1972     0    79     1    22\n  4.5768216407765305E-01 a      1973     0    79     1    23\n  1.4593364505671960E+00 a      1974     0    79     1    24\n  2.7710216155783201E+00 a      1975     0    79     1    25\n  3.5155429038738375E+00 a      1976     0    80     1     1\n  3.3101639660531124E-01 a      1977     0    80     1     2\n  1.1064561273931135E+00 a      1978     0    80     1     3\n -1.0308251115873794E+00 a      1979     0    80     1     4\n  1.8968919588612441E+00 a      1980     0    80     1     5\n  1.4760117428130526E-01 a      1981     0    80     1     6\n  3.1195824347104306E+00 a      1982     0    80     1     7\n -3.4354030144323837E+00 a      1983     0    80     1     8\n  2.3754789147026627E+00 a      1984     0    80     1     9\n -2.2175493355555465E+00 a      1985     0    80     1    10\n  3.5779789892265584E-01 a      1986     0    80     1    11\n -4.9238133678089708E+00 a      1987     0    80     1    12\n -1.4776399441065415E+00 a      1988     0    80     1    13\n  4.6856598223867846E-01 a      1989     0    80     1    14\n -1.7226989956183458E+00 a      1990     0    80     1    15\n -2.3831886824009416E+00 a      1991     0    80     1    16\n -7.7800915855597041E-01 a      1992     0    80     1    17\n -1.8618551377239745E+00 a      1993     0    80     1    18\n  4.8694910652160706E-01 a      1994     0    80     1    19\n  1.4735309021562415E+00 a      1995     0    80     1    20\n  2.9798890651954379E+00 a      1996     0    80     1    21\n  4.0989081315762205E-01 a      1997     0    80     1    22\n  3.6672581048421131E+00 a      1998     0    80     1    23\n  4.5744734558321798E-01 a      1999     0    80     1    24\n  2.3282405029562212E+00 a      2000     0    80     1    25\n -1.4650178497670969E+00 a      2001     0    81     1     1\n -1.2540727406267103E+00 a      2002     0    81     1     2\n  6.4296470829623109E-01 a      2003     0    81     1     3\n  1.9713949629332024E+00 a      2004     0    81     1     4\n  4.7985295138739575E-01 a      2005     0    81     1     5\n -5.8980630534280565E-01 a      2006     0    81     1     6\n -2.9379908360135554E+00 a      2007     0    81     1     7\n  2.5126008113420277E+00 a      2008     0    81     1     8\n  2.4425919680558699E+00 a      2009     0    81     1     9\n -1.7387808082006861E+00 a      2010     0    81     1    10\n -1.5375630809501493E+00 a      2011     0    81     1    11\n -7.1247019169760550E-01 a      2012     0    81     1    12\n  1.7007246528383648E+00 a      2013     0    81     1    13\n -1.3353281289218000E-01 a      2014     0    81     1    14\n  5.0013963301090081E-01 a      2015     0    81     1    15\n -1.9166936355178692E+00 a      2016     0    81     1    16\n  5.9435212333259289E+00 a      2017     0    81     1    17\n -1.0587473501745399E+00 a      2018     0    81     1    18\n -3.4931986826935124E+00 a      2019     0    81     1    19\n  9.9420020232258866E-01 a      2020     0    81     1    20\n -7.5064109651786143E-02 a      2021     0    81     1    21\n  6.3013213909829791E-01 a      2022     0    81     1    22\n -4.1489055307302819E-01 a      2023     0    81     1    23\n -2.5855264565527900E+00 a      2024     0    81     1    24\n -1.4785070884093898E+00 a      2025     0    81     1    25\n -1.5878846238762958E+00 a      2026     0    82     1     1\n -2.2419310549117601E+00 a      2027     0    82     1     2\n -3.2754001501772295E-02 a      2028     0    82     1     3\n  2.5561709636100898E+00 a      2029     0    82     1     4\n -4.8612337754981666E-01 a      2030     0    82     1     5\n -1.4608949543350769E+00 a      2031     0    82     1     6\n  3.7158719943990981E+00 a      2032     0    82     1     7\n  2.8309360345003216E+00 a      2033     0    82     1     8\n  1.5111748124718727E+00 a      2034     0    82     1     9\n  7.6268506487330001E-01 a      2035     0    82     1    10\n  1.5798625408381948E+00 a      2036     0    82     1    11\n -5.3023626154719461E-01 a      2037     0    82     1    12\n  1.0879214733151927E+00 a      2038     0    82     1    13\n  2.9107615666486946E+00 a      2039     0    82     1    14\n -2.9774893365477989E-01 a      2040     0    82     1    15\n -2.1067236835337231E+00 a      2041     0    82     1    16\n  2.7590328001820530E-01 a      2042     0    82     1    17\n  2.1515202032394365E+00 a      2043     0    82     1    18\n  1.0694007845216393E+00 a      2044     0    82     1    19\n -2.9272111276016566E+00 a      2045     0    82     1    20\n -3.1651564844030484E+00 a      2046     0    82     1    21\n  6.6758371633873725E-01 a      2047     0    82     1    22\n  4.8232195666591595E+00 a      2048     0    82     1    23\n -3.4700227080008972E+00 a      2049     0    82     1    24\n  4.8528925124466316E+00 a      2050     0    82     1    25\n  7.1763712610137675E-01 a      2051     0    83     1     1\n  1.2203387643953729E+00 a      2052     0    83     1     2\n  4.0717868078975422E-01 a      2053     0    83     1     3\n  1.3668949531636576E-01 a      2054     0    83     1     4\n  3.4097254572084357E-01 a      2055     0    83     1     5\n -1.4391398976333289E+00 a      2056     0    83     1     6\n -1.1760708995623901E+00 a      2057     0    83     1     7\n -7.1251851851676118E-01 a      2058     0    83     1     8\n  3.3639673728461061E+00 a      2059     0    83     1     9\n -5.0274539391369970E+00 a      2060     0    83     1    10\n -1.7298333803816022E+00 a      2061     0    83     1    11\n  4.3137775503680070E-01 a      2062     0    83     1    12\n  1.7848088456814126E-01 a      2063     0    83     1    13\n -3.5351223742800211E+00 a      2064     0    83     1    14\n -1.8343065720545388E+00 a      2065     0    83     1    15\n -2.6893707805711489E+00 a      2066     0    83     1    16\n  1.8927671710929608E+00 a      2067     0    83     1    17\n -1.2908120514153221E+00 a      2068     0    83     1    18\n -1.0643041430394038E+00 a      2069     0    83     1    19\n -1.5487041767070429E+00 a      2070     0    83     1    20\n  2.4289395950177077E+00 a      2071     0    83     1    21\n -1.6124853334308591E+00 a      2072     0    83     1    22\n -3.2559648389747693E+00 a      2073     0    83     1    23\n  2.5651747888754941E+00 a      2074     0    83     1    24\n -2.1165643210681577E+00 a      2075     0    83     1    25\n  9.6191916938139699E-01 a      2076     0    84     1     1\n -6.1730844693918618E-01 a      2077     0    84     1     2\n -3.5295337483719275E-01 a      2078     0    84     1     3\n  1.1133441506142641E+00 a      2079     0    84     1     4\n  1.4349697719117760E+00 a      2080     0    84     1     5\n -3.9285899094048865E-01 a      2081     0    84     1     6\n -7.2953169272674625E+00 a      2082     0    84     1     7\n -1.1233492660443229E+00 a      2083     0    84     1     8\n -3.7217034630145346E-01 a      2084     0    84     1     9\n -7.2310082424490396E-01 a      2085     0    84     1    10\n -5.1872605954942030E-01 a      2086     0    84     1    11\n  2.9424065352949019E-01 a      2087     0    84     1    12\n  1.1623580677931671E-01 a      2088     0    84     1    13\n  1.9579455255859468E+00 a      2089     0    84     1    14\n -1.2000417793074993E+00 a      2090     0    84     1    15\n  1.7523108904154485E+00 a      2091     0    84     1    16\n -6.5353579481864106E+00 a      2092     0    84     1    17\n -3.2094845633843638E+00 a      2093     0    84     1    18\n -3.4286762865463499E-01 a      2094     0    84     1    19\n  9.7852315545309498E-01 a      2095     0    84     1    20\n -3.8587535570545803E+00 a      2096     0    84     1    21\n  4.7082293832720300E-02 a      2097     0    84     1    22\n  1.6848181653955807E-01 a      2098     0    84     1    23\n  2.8008542421172309E+00 a      2099     0    84     1    24\n  3.0825453482166358E-02 a      2100     0    84     1    25\n -6.0772411369893187E-01 a      2101     0    85     1     1\n  4.1168518079911531E-01 a      2102     0    85     1     2\n  4.1610082855885838E-01 a      2103     0    85     1     3\n -7.0600851543623433E-01 a      2104     0    85     1     4\n -4.8734851283043473E-01 a      2105     0    85     1     5\n  7.9315070989830105E-01 a      2106     0    85     1     6\n  5.1881450447801472E+00 a      2107     0    85     1     7\n  7.8352094361541691E-01 a      2108     0    85     1     8\n  2.6453668485582871E-01 a      2109     0    85     1     9\n  4.0579625752594536E-02 a      2110     0    85     1    10\n  1.0415867237774370E+00 a      2111     0    85     1    11\n  1.1919458361815061E-01 a      2112     0    85     1    12\n  5.2121202706399729E-02 a      2113     0    85     1    13\n -1.2861601462825706E-01 a      2114     0    85     1    14\n  1.9206191784830207E-01 a      2115     0    85     1    15\n  1.7337365278602992E-01 a      2116     0    85     1    16\n  4.2199740955140674E+00 a      2117     0    85     1    17\n  3.8150628960736210E-01 a      2118     0    85     1    18\n -1.7944596151702514E+00 a      2119     0    85     1    19\n -1.7190777765294520E+00 a      2120     0    85     1    20\n  3.1041421015440389E+00 a      2121     0    85     1    21\n  4.0495625759685655E-01 a      2122     0    85     1    22\n -1.1009191347375953E+00 a      2123     0    85     1    23\n -3.8059282989541874E+00 a      2124     0    85     1    24\n  4.2771438993128227E-02 a      2125     0    85     1    25\n  8.8433021947755722E-02 a      2126     0    86     1     1\n  1.2961443988138391E-01 a      2127     0    86     1     2\n  3.1673331283177458E-01 a      2128     0    86     1     3\n -6.1616911146585927E-02 a      2129     0    86     1     4\n -4.1052393758817179E-01 a      2130     0    86     1     5\n -2.7783011975780242E-01 a      2131     0    86     1     6\n  3.4631102597554070E-01 a      2132     0    86     1     7\n -8.0885447634935514E-01 a      2133     0    86     1     8\n  1.4689495731434457E-01 a      2134     0    86     1     9\n  3.9087406731978458E-01 a      2135     0    86     1    10\n  7.2461210438336454E-01 a      2136     0    86     1    11\n  2.6672611436460037E-03 a      2137     0    86     1    12\n  5.0808453821032451E-01 a      2138     0    86     1    13\n -2.1448038444633485E-01 a      2139     0    86     1    14\n  1.1644628807255832E-01 a      2140     0    86     1    15\n  5.5053399973945139E-01 a      2141     0    86     1    16\n -1.3496575580524051E+00 a      2142     0    86     1    17\n  1.1055696865047069E+00 a      2143     0    86     1    18\n  2.3677271640531170E-01 a      2144     0    86     1    19\n -1.3211116750157847E+00 a      2145     0    86     1    20\n -2.8321102760624250E-01 a      2146     0    86     1    21\n  4.6895770962415755E-02 a      2147     0    86     1    22\n  1.9362804432961239E-01 a      2148     0    86     1    23\n -3.8923196175317731E-01 a      2149     0    86     1    24\n  8.7390040487394266E-02 a      2150     0    86     1    25\n  1.3877217796549755E+00 a      2151     0    87     1     1\n  2.3938754504426280E-01 a      2152     0    87     1     2\n  1.0723957183715729E+00 a      2153     0    87     1     3\n -1.6287197619163591E+00 a      2154     0    87     1     4\n  9.4890910576606502E-01 a      2155     0    87     1     5\n  8.4824905150740360E-01 a      2156     0    87     1     6\n  3.8187729058637299E-01 a      2157     0    87     1     7\n -2.2386437996951831E+00 a      2158     0    87     1     8\n -8.5890450030707055E-01 a      2159     0    87     1     9\n  1.6353396822470812E-01 a      2160     0    87     1    10\n  1.5936326008932595E+00 a      2161     0    87     1    11\n -2.3307479738598733E-01 a      2162     0    87     1    12\n  3.0569423480387541E+00 a      2163     0    87     1    13\n  1.4841529924902734E+00 a      2164     0    87     1    14\n -1.9976076146887580E+00 a      2165     0    87     1    15\n  1.3231893706948614E-01 a      2166     0    87     1    16\n  3.1237989538459114E+00 a      2167     0    87     1    17\n -3.7846189633027878E+00 a      2168     0    87     1    18\n -5.0664991507491819E-01 a      2169     0    87     1    19\n  1.8620417252482906E+00 a      2170     0    87     1    20\n -6.9778019325923235E-01 a      2171     0    87     1    21\n -1.2720276431113990E+00 a      2172     0    87     1    22\n  7.9187009935529495E-01 a      2173     0    87     1    23\n -4.0976789661527420E+00 a      2174     0    87     1    24\n -1.5920005703897966E+00 a      2175     0    87     1    25\n -5.4710750819724518E+00 a      2176     0    88     1     1\n -2.5182712714953670E+00 a      2177     0    88     1     2\n -2.0475769625578715E+00 a      2178     0    88     1     3\n -5.2466955426530086E+00 a      2179     0    88     1     4\n -2.0587850460408714E+00 a      2180     0    88     1     5\n -1.8900572344872828E+00 a      2181     0    88     1     6\n -1.8670324124693090E+00 a      2182     0    88     1     7\n -1.2104515071751876E+00 a      2183     0    88     1     8\n -3.4292917959609059E-01 a      2184     0    88     1     9\n -1.2855283846997585E+00 a      2185     0    88     1    10\n  7.5060098682922149E-01 a      2186     0    88     1    11\n  2.5989201739458445E+00 a      2187     0    88     1    12\n -1.8533290598040564E-01 a      2188     0    88     1    13\n -2.7900827816769618E+00 a      2189     0    88     1    14\n  1.7937482979090635E-01 a      2190     0    88     1    15\n  8.6304457040064386E-01 a      2191     0    88     1    16\n 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5.0192044044327366E-01 a      8789     1    17     2    14\n -1.9513612951461381E+00 a      8790     1    17     2    15\n  1.2750318953369875E+00 a      8791     1    17     2    16\n  9.4075493096091278E-01 a      8792     1    17     2    17\n -1.4874137983315563E+00 a      8793     1    17     2    18\n -5.5467227017947773E-01 a      8794     1    17     2    19\n -4.2937414871299005E-02 a      8795     1    17     2    20\n  1.9190442912021977E-01 a      8796     1    17     2    21\n -1.1004608715612696E+00 a      8797     1    17     2    22\n -4.8649109946958449E+00 a      8798     1    17     2    23\n -6.9135133782502889E-01 a      8799     1    17     2    24\n -3.9376785894082125E-02 a      8800     1    17     2    25\n  5.4677656548312270E-01 a      8801     1    18     2     1\n -4.5993714071359360E-01 a      8802     1    18     2     2\n  7.2088424005440388E-01 a      8803     1    18     2     3\n -1.0662682581805945E+00 a      8804     1    18     2     4\n -4.8407996275257929E-02 a      8805     1    18     2     5\n  1.2094693143856325E+00 a      8806     1    18     2     6\n -7.2529152026621102E-01 a      8807     1    18     2     7\n -1.4504287046950775E+00 a      8808     1    18     2     8\n  1.0926803845313240E+00 a      8809     1    18     2     9\n  3.0295408413815833E-01 a      8810     1    18     2    10\n -5.4562746898145782E-02 a      8811     1    18     2    11\n -6.4696108929785723E-01 a      8812     1    18     2    12\n  3.2858781426621569E-01 a      8813     1    18     2    13\n  4.5549222717323118E-01 a      8814     1    18     2    14\n -3.9493765704004047E+00 a      8815     1    18     2    15\n  2.7380852381895880E-02 a      8816     1    18     2    16\n -1.2348986401155060E+00 a      8817     1    18     2    17\n -1.5882072117579034E+00 a      8818     1    18     2    18\n  9.9688197369239340E-01 a      8819     1    18     2    19\n  9.7103505608569074E-01 a      8820     1    18     2    20\n -6.1385624571003150E-01 a      8821     1    18     2    21\n  2.7455601936649154E-01 a      8822     1    18     2    22\n  1.5560613085371717E+00 a      8823     1    18     2    23\n  5.7347079987673588E-01 a      8824     1    18     2    24\n  3.9967783909592763E-01 a      8825     1    18     2    25\n -1.3686703128660744E+00 a      8826     1    19     2     1\n  4.1739731515905715E-01 a      8827     1    19     2     2\n  3.8790919208001506E-01 a      8828     1    19     2     3\n  1.9257306122971736E+00 a      8829     1    19     2     4\n -1.0936225663262797E+00 a      8830     1    19     2     5\n -7.3245692653847960E-01 a      8831     1    19     2     6\n  9.5216299112420200E-01 a      8832     1    19     2     7\n -8.4748892749880134E-01 a      8833     1    19     2     8\n -4.1100017645308001E-01 a      8834     1    19     2     9\n -1.6003532508137772E+00 a      8835     1    19     2    10\n -9.3027494613094985E-01 a      8836     1    19     2    11\n  7.8135228083574579E-02 a      8837     1    19     2    12\n  2.0816294728622523E-01 a      8838     1    19     2    13\n -6.6306719155139426E-01 a      8839     1    19     2    14\n  5.4976205960942781E-01 a      8840     1    19     2    15\n -1.9874946297684368E-01 a      8841     1    19     2    16\n  3.7842094311817216E+00 a      8842     1    19     2    17\n -7.1268365425790159E-01 a      8843     1    19     2    18\n  5.3998155097232114E-01 a      8844     1    19     2    19\n  1.1047621425547807E-01 a      8845     1    19     2    20\n -1.3524093589275060E-01 a      8846     1    19     2    21\n  1.9945760501794711E+00 a      8847     1    19     2    22\n  7.1371533413228294E-01 a      8848     1    19     2    23\n  7.2964282511905521E-01 a      8849     1    19     2    24\n  8.0051983901632640E-01 a      8850     1    19     2    25\n -5.1442659708492711E-02 a      8851     1    20     2     1\n -7.4159630562891876E-01 a      8852     1    20     2     2\n -5.8521986636073697E-01 a      8853     1    20     2     3\n -4.7260565371588265E-01 a      8854     1    20     2     4\n -3.5502988199681179E-01 a      8855     1    20     2     5\n -3.4307932070592306E-01 a      8856     1    20     2     6\n -7.9171164489046542E-01 a      8857     1    20     2     7\n -9.2365306511665668E-01 a      8858     1    20     2     8\n  1.9852746809138209E+00 a      8859     1    20     2     9\n -1.2221510079490165E+00 a      8860     1    20     2    10\n -5.1846661113933323E-01 a      8861     1    20     2    11\n -2.5397782202360081E-01 a      8862     1    20     2    12\n  4.4312588115066831E-01 a      8863     1    20     2    13\n -1.6557207716595115E+00 a      8864     1    20     2    14\n -3.4765799812999489E+00 a      8865     1    20     2    15\n  7.3192391182278072E-01 a      8866     1    20     2    16\n -7.9588932210418339E-01 a      8867     1    20     2    17\n -1.4631607896707796E-01 a      8868     1    20     2    18\n  1.9230037115588433E-01 a      8869     1    20     2    19\n  1.5616864766662508E-01 a      8870     1    20     2    20\n  1.0007305487489053E+00 a      8871     1    20     2    21\n  9.6387691277768994E-01 a      8872     1    20     2    22\n  4.4351256184842353E-01 a      8873     1    20     2    23\n -2.0566901428934767E+00 a      8874     1    20     2    24\n -3.2020739251068531E-01 a      8875     1    20     2    25\n -1.0063316371620552E+00 a      8876     1    21     2     1\n -5.6190451294698940E-01 a      8877     1    21     2     2\n -2.0321132316507260E+00 a      8878     1    21     2     3\n -1.2193425809207332E+00 a      8879     1    21     2     4\n  6.6811166815192713E-01 a      8880     1    21     2     5\n  1.1259910127701840E+00 a      8881     1    21     2     6\n  9.1232027828733442E-01 a      8882     1    21     2     7\n  2.9487103859470676E-02 a      8883     1    21     2     8\n -3.8739358476853442E-01 a      8884     1    21     2     9\n  6.1920125247456226E-01 a      8885     1    21     2    10\n  8.2348046453097534E-01 a      8886     1    21     2    11\n -3.7458988012124700E-01 a      8887     1    21     2    12\n -7.9031967197477049E-01 a      8888     1    21     2    13\n  2.5660428409501859E+00 a      8889     1    21     2    14\n -3.3276298104621321E-01 a      8890     1    21     2    15\n  1.7215908998336424E+00 a      8891     1    21     2    16\n  1.5903242954462844E+00 a      8892     1    21     2    17\n  1.9299746652775496E+00 a      8893     1    21     2    18\n -1.0644733102255930E+00 a      8894     1    21     2    19\n  7.7672217052890791E-01 a      8895     1    21     2    20\n -7.8796611698121233E-01 a      8896     1    21     2    21\n  1.8767759246216081E-01 a      8897     1    21     2    22\n -1.1889405011387266E+00 a      8898     1    21     2    23\n  1.0175693936875037E-01 a      8899     1    21     2    24\n  8.1062033901151753E-01 a      8900     1    21     2    25\n  1.2727943457845952E+00 a      8901     1    22     2     1\n -1.3284378742716152E+00 a      8902     1    22     2     2\n  1.2948635603082694E+00 a      8903     1    22     2     3\n -7.0355553111883151E-01 a      8904     1    22     2     4\n  6.0268419562018882E-01 a      8905     1    22     2     5\n -2.4527594727691188E-01 a      8906     1    22     2     6\n -1.7317344604546407E+00 a      8907     1    22     2     7\n  2.8757500010389028E+00 a      8908     1    22     2     8\n -2.9475265040968818E-01 a      8909     1    22     2     9\n  3.5375897192097554E+00 a      8910     1    22     2    10\n  1.0786695653485935E-01 a      8911     1    22     2    11\n  2.7844782831240669E+00 a      8912     1    22     2    12\n  2.2437465570939445E+00 a      8913     1    22     2    13\n -4.1120127829934938E-01 a      8914     1    22     2    14\n -6.7462483429309522E-02 a      8915     1    22     2    15\n -2.1326085756284270E+00 a      8916     1    22     2    16\n -6.0280683053460260E-01 a      8917     1    22     2    17\n -2.4176014813038398E+00 a      8918     1    22     2    18\n  4.3592836948755270E-01 a      8919     1    22     2    19\n  1.4222048524478563E+00 a      8920     1    22     2    20\n  1.4728096199503884E-01 a      8921     1    22     2    21\n -9.5680821567581759E-02 a      8922     1    22     2    22\n -3.5172680003125958E+00 a      8923     1    22     2    23\n -1.6277218240332745E+00 a      8924     1    22     2    24\n -1.0942602781793707E+00 a      8925     1    22     2    25\n  9.2659932366403785E-01 a      8926     1    23     2     1\n  1.6303760059822558E-01 a      8927     1    23     2     2\n -1.0177147331356582E+00 a      8928     1    23     2     3\n  9.3955059784358841E-01 a      8929     1    23     2     4\n  1.9744458820475230E-01 a      8930     1    23     2     5\n -1.9980190546908069E-01 a      8931     1    23     2     6\n -9.9694650484615333E-01 a      8932     1    23     2     7\n  2.6196652686114555E-02 a      8933     1    23     2     8\n -1.6635913885401774E-01 a      8934     1    23     2     9\n  1.7581266896915622E+00 a      8935     1    23     2    10\n  1.8863931340595905E-01 a      8936     1    23     2    11\n  4.5523936938389814E-01 a      8937     1    23     2    12\n -3.0635472260330240E-02 a      8938     1    23     2    13\n -9.2958704952957327E-01 a      8939     1    23     2    14\n -3.8860376031648775E-01 a      8940     1    23     2    15\n  6.1555023891468730E-01 a      8941     1    23     2    16\n -1.5920643255991653E+00 a      8942     1    23     2    17\n -2.5753018654581866E-01 a      8943     1    23     2    18\n  5.0870035393534585E-01 a      8944     1    23     2    19\n  6.2885048198225091E-01 a      8945     1    23     2    20\n -2.8731497944066753E-01 a      8946     1    23     2    21\n -5.0714910882177300E-01 a      8947     1    23     2    22\n  1.6452056418904384E+00 a      8948     1    23     2    23\n  3.3865129998232923E-01 a      8949     1    23     2    24\n -5.8231617120510015E-01 a      8950     1    23     2    25\n -3.1559266763370186E-01 a      8951     1    24     2     1\n  4.5899716445902566E-01 a      8952     1    24     2     2\n  1.7828266150148847E-01 a      8953     1    24     2     3\n  4.4738656629769717E-02 a      8954     1    24     2     4\n -6.2437585783096872E-01 a      8955     1    24     2     5\n  9.0545319451397141E-02 a      8956     1    24     2     6\n -1.6641054278112039E-01 a      8957     1    24     2     7\n -8.7496889903865749E-01 a      8958     1    24     2     8\n  1.0502079125306880E+00 a      8959     1    24     2     9\n -3.6890054980897746E-01 a      8960     1    24     2    10\n -1.7661396804175777E-01 a      8961     1    24     2    11\n -5.0373288543340422E-01 a      8962     1    24     2    12\n -3.2173606545851297E-01 a      8963     1    24     2    13\n -8.3565402814069367E-01 a      8964     1    24     2    14\n -6.0681797940330795E-01 a      8965     1    24     2    15\n  3.3474354717832383E-01 a      8966     1    24     2    16\n  5.8212400434953182E-01 a      8967     1    24     2    17\n -9.5734372280181990E-01 a      8968     1    24     2    18\n  1.3936206085232909E+00 a      8969     1    24     2    19\n -9.0491613558769102E-01 a      8970     1    24     2    20\n -3.0300620000312223E-01 a      8971     1    24     2    21\n -1.9406437913054916E-01 a      8972     1    24     2    22\n  1.4946774040594124E+00 a      8973     1    24     2    23\n  1.3214159472465539E+00 a      8974     1    24     2    24\n -9.4118201153245951E-01 a      8975     1    24     2    25\n  2.4828201016079139E+00 a      8976     1    25     2     1\n -1.5336081600324888E-01 a      8977     1    25     2     2\n  1.9935378418630993E+00 a      8978     1    25     2     3\n  8.4280830343488577E-01 a      8979     1    25     2     4\n -4.7381020709494298E-01 a      8980     1    25     2     5\n -5.4318049519129918E-01 a      8981     1    25     2     6\n  3.5173133189035743E+00 a      8982     1    25     2     7\n -1.0328349399773640E+00 a      8983     1    25     2     8\n -1.9794243128970941E+00 a      8984     1    25     2     9\n -7.7605495214067899E-01 a      8985     1    25     2    10\n -9.2624903244076984E-01 a      8986     1    25     2    11\n  1.0079789495216460E+00 a      8987     1    25     2    12\n  1.6533790133252002E+00 a      8988     1    25     2    13\n -2.2337682294795669E+00 a      8989     1    25     2    14\n -5.0067442796831474E-01 a      8990     1    25     2    15\n  4.2742263622482396E-01 a      8991     1    25     2    16\n -2.1956097193652049E+00 a      8992     1    25     2    17\n -6.2054829625087293E-01 a      8993     1    25     2    18\n  8.0066400242767621E-01 a      8994     1    25     2    19\n -3.6543535398183591E-01 a      8995     1    25     2    20\n  2.4104415414061398E-01 a      8996     1    25     2    21\n  6.2788190476165151E-01 a      8997     1    25     2    22\n -1.3283045798125370E-01 a      8998     1    25     2    23\n -1.2648200204715294E+00 a      8999     1    25     2    24\n  8.2510141236731366E-02 a      9000     1    25     2    25\n  1.6541342904122054E+00 b      9001     2     1\n  2.1516097515432766E+00 b      9002     2     2\n -3.0123423211724858E+00 b      9003     2     3\n  1.1493001537321035E+00 b      9004     2     4\n  2.8640046132633703E+00 b      9005     2     5\n -3.8132296134594825E+00 b      9006     2     6\n -6.4119544151905905E-02 b      9007     2     7\n -4.7281148978477727E+00 b      9008     2     8\n  3.9678729007605598E+00 b      9009     2     9\n -2.0982384210900347E+00 b      9010     2    10\n  6.3248691917373701E-01 b      9011     2    11\n -4.0259531419272934E+00 b      9012     2    12\n -3.6004309172211983E+00 b      9013     2    13\n  2.1803876248724952E-01 b      9014     2    14\n  2.9170132872739023E+00 b      9015     2    15\n -1.6063626922511116E+00 b      9016     2    16\n  3.1270717282106091E+00 b      9017     2    17\n  2.0963465008576657E-01 b      9018     2    18\n -7.0260248032579309E-01 b      9019     2    19\n -5.5948812707729623E-01 b      9020     2    20\n -3.8969204495339548E-02 b      9021     2    21\n -6.3964222775896662E-01 b      9022     2    22\n  2.7728079122349397E-01 b      9023     2    23\n -2.2073369872301689E+00 b      9024     2    24\n  1.4048995582501693E+00 b      9025     2    25\n  2.4639204051649602E-01 a      9026     2     1     3     1\n -1.3802884461836176E+00 a      9027     2     2     3     1\n  6.9007682276971327E-01 a      9028     2     3     3     1\n  9.5483111153964029E-01 a      9029     2     4     3     1\n  9.2152745054917562E-01 a      9030     2     5     3     1\n  5.0291661100596563E-01 a      9031     2     6     3     1\n -2.2997158340951313E-02 a      9032     2     7     3     1\n  7.9590684786984806E-02 a      9033     2     8     3     1\n -6.8570172993916545E-01 a      9034     2     9     3     1\n  2.5569182480462613E-02 a      9035     2    10     3     1\n -2.2657510485896107E-01 a      9036     2    11     3     1\n  6.1587847887954172E-01 a      9037     2    12     3     1\n  1.1286473488670512E+00 a      9038     2    13     3     1\n  3.8541249148011725E-01 a      9039     2    14     3     1\n  1.8631851860030546E-01 a      9040     2    15     3     1\n  2.6069265968724969E-01 a      9041     2    16     3     1\n -2.0037719275175982E-02 a      9042     2    17     3     1\n  1.0143788830600912E-02 a      9043     2    18     3     1\n  1.0899469593768871E+00 a      9044     2    19     3     1\n  1.0218132117205663E+00 a      9045     2    20     3     1\n  1.0363505575503407E+00 a      9046     2    21     3     1\n -2.7431224616661670E-01 a      9047     2    22     3     1\n -2.6607521294142733E-02 a      9048     2    23     3     1\n -1.5910341915720569E-01 a      9049     2    24     3     1\n -1.3394580706661012E+00 a      9050     2    25     3     1\n  2.7538766074480834E+00 b      9051     3     1\n"
  },
  {
    "path": "examples/nnp-predict/DMABN_SCAN/weights.006.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  2.7383304992527409E+00 a         1     0     1     1     1\n -1.2621905738510548E+00 a         2     0     1     1     2\n -3.3755889009176978E+00 a         3     0     1     1     3\n -5.9860937814953550E+00 a         4     0     1     1     4\n -4.3640807985117025E+00 a         5     0     1     1     5\n -2.4479937808931078E+00 a         6     0     1     1     6\n  4.1920894805128917E-01 a         7     0     1     1     7\n  9.6391601838587571E-01 a         8     0     1     1     8\n  2.9854181934749375E+00 a         9     0     1     1     9\n  1.0342802096221779E+00 a        10     0     1     1    10\n  1.5333657099734965E+00 a        11     0     1     1    11\n -7.2097266357622503E-01 a        12     0     1     1    12\n -1.6660805257695439E+00 a        13     0     1     1    13\n -2.4552056422253328E+00 a        14     0     1     1    14\n  1.7994760339369671E+00 a        15     0     1     1    15\n  5.9783587475887146E-01 a        16     0     1     1    16\n -2.8574947541284695E-01 a        17     0     1     1    17\n  5.7972823073903157E-01 a        18     0     1     1    18\n  1.2620399224595726E+00 a        19     0     1     1    19\n  1.3897110359343479E+00 a        20     0     1     1    20\n -5.0851854756441117E-01 a        21     0     1     1    21\n -4.3547849098627820E+00 a        22     0     1     1    22\n -1.8668384881409912E+00 a        23     0     1     1    23\n  9.9767109922395347E-02 a        24     0     1     1    24\n -5.1685445048373762E+00 a        25     0     1     1    25\n -4.0057065605423183E+00 a        26     0     2     1     1\n  1.0520717198969416E+01 a        27     0     2     1     2\n  1.1844023063168900E+00 a        28     0     2     1     3\n  4.8266400620021095E+00 a        29     0     2     1     4\n  1.0976327036895519E+01 a        30     0     2     1     5\n -3.9537279878730291E-01 a        31     0     2     1     6\n 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2.7862563455700755E+00 a      1936     0    78     1    11\n -2.9719786295521726E+00 a      1937     0    78     1    12\n -1.3095450885457427E+00 a      1938     0    78     1    13\n -6.9861180713568416E-01 a      1939     0    78     1    14\n  9.0538930731159306E-01 a      1940     0    78     1    15\n -4.2764407912949283E+00 a      1941     0    78     1    16\n  5.6355811440352765E-01 a      1942     0    78     1    17\n -1.4252039275762876E+00 a      1943     0    78     1    18\n  4.6826154012733512E-01 a      1944     0    78     1    19\n  6.3702187026217960E-01 a      1945     0    78     1    20\n -2.1059576682766159E+00 a      1946     0    78     1    21\n -2.4646132504557570E+00 a      1947     0    78     1    22\n -1.9205004559987757E+00 a      1948     0    78     1    23\n  1.8486919871870553E+00 a      1949     0    78     1    24\n -8.2147176960627399E-01 a      1950     0    78     1    25\n -1.0325450491030954E+00 a      1951     0    79     1     1\n -7.7508163130461105E-01 a      1952     0    79     1     2\n  2.1445866213352556E+00 a      1953     0    79     1     3\n -3.6169461297733947E+00 a      1954     0    79     1     4\n  1.2005308409666759E+00 a      1955     0    79     1     5\n -1.8936751083799763E+00 a      1956     0    79     1     6\n -2.2085823263986568E+00 a      1957     0    79     1     7\n  1.3157464359803399E+00 a      1958     0    79     1     8\n -9.1421053633735982E-01 a      1959     0    79     1     9\n  2.1590731262023728E+00 a      1960     0    79     1    10\n -5.6470006241176467E+00 a      1961     0    79     1    11\n -1.7044351003778904E+00 a      1962     0    79     1    12\n  1.2064432029445971E+00 a      1963     0    79     1    13\n  1.9196128829334338E+00 a      1964     0    79     1    14\n  4.3446708244495991E+00 a      1965     0    79     1    15\n  5.9550414595724444E-01 a      1966     0    79     1    16\n  9.4690347407052927E-02 a      1967     0    79     1    17\n  1.7340176591681826E+00 a      1968     0    79     1    18\n -2.0351241139253999E+00 a      1969     0    79     1    19\n  1.8918718647814809E+00 a      1970     0    79     1    20\n  1.5816481268832807E+00 a      1971     0    79     1    21\n -1.3167792113863983E-01 a      1972     0    79     1    22\n -2.4463061293819170E+00 a      1973     0    79     1    23\n  8.2178073715823408E-01 a      1974     0    79     1    24\n -1.1028322046514376E+00 a      1975     0    79     1    25\n -4.6678228303017182E+00 a      1976     0    80     1     1\n  2.4232501556258468E+00 a      1977     0    80     1     2\n  4.4199901743062942E+00 a      1978     0    80     1     3\n -5.2351379806118870E-01 a      1979     0    80     1     4\n -1.5313206474807592E+00 a      1980     0    80     1     5\n -2.1690322793451733E+00 a      1981     0    80     1     6\n -2.4363668589285954E+00 a      1982     0    80     1     7\n  5.9685990028209637E-02 a      1983     0    80     1     8\n  5.3170431448847513E+00 a      1984     0    80     1     9\n -4.0755166520061170E+00 a      1985     0    80     1    10\n  4.4101859324201200E+00 a      1986     0    80     1    11\n -1.4141418401921917E+00 a      1987     0    80     1    12\n  1.1294025341881513E+00 a      1988     0    80     1    13\n  1.4205306286539932E-01 a      1989     0    80     1    14\n -1.6710920517056760E+00 a      1990     0    80     1    15\n  4.1282622720596229E-01 a      1991     0    80     1    16\n -1.3545903624825966E+00 a      1992     0    80     1    17\n -5.7202504713078162E-01 a      1993     0    80     1    18\n  2.3767078269054736E+00 a      1994     0    80     1    19\n  3.4037658536466693E+00 a      1995     0    80     1    20\n -8.0109282029988660E-01 a      1996     0    80     1    21\n  1.7142953101211482E+00 a      1997     0    80     1    22\n  5.8845248922551552E-01 a      1998     0    80     1    23\n -2.2292787354429024E+00 a      1999     0    80     1    24\n -1.0154907952249954E+00 a      2000     0    80     1    25\n -2.0685680896105598E+00 a      2001     0    81     1     1\n -1.3673919880269977E-01 a      2002     0    81     1     2\n  2.8976765507221889E+00 a      2003     0    81     1     3\n -2.2980014376168585E+00 a      2004     0    81     1     4\n  3.1299478654216681E+00 a      2005     0    81     1     5\n -1.0444799311073878E+00 a      2006     0    81     1     6\n -3.9414818305456176E+00 a      2007     0    81     1     7\n  3.3028524634162886E+00 a      2008     0    81     1     8\n  1.4101783343652088E-01 a      2009     0    81     1     9\n -1.7825128123693093E-01 a      2010     0    81     1    10\n  4.4846983887067928E+00 a      2011     0    81     1    11\n -1.4085820006717256E+00 a      2012     0    81     1    12\n -1.2018719206385144E+00 a      2013     0    81     1    13\n -5.7907652127642173E+00 a      2014     0    81     1    14\n -2.4711375044242843E+00 a      2015     0    81     1    15\n -7.0732307395162308E-01 a      2016     0    81     1    16\n  3.7457627167592233E-01 a      2017     0    81     1    17\n -1.8917354445115291E+00 a      2018     0    81     1    18\n -2.1848867582343496E+00 a      2019     0    81     1    19\n -6.1852317725461992E-01 a      2020     0    81     1    20\n  3.0689111870152366E+00 a      2021     0    81     1    21\n  2.9581136677359171E-01 a      2022     0    81     1    22\n  7.6628377437493045E-01 a      2023     0    81     1    23\n -1.8209697848550077E-01 a      2024     0    81     1    24\n -4.1689738692604505E+00 a      2025     0    81     1    25\n  3.9110830466641904E+00 a      2026     0    82     1     1\n -1.1712301085340124E+00 a      2027     0    82     1     2\n -6.0763985758325034E-02 a      2028     0    82     1     3\n -9.0665128017518870E-01 a      2029     0    82     1     4\n  1.8248219690665730E+00 a      2030     0    82     1     5\n  8.6993979328798610E-01 a      2031     0    82     1     6\n -3.6897593736905460E-01 a      2032     0    82     1     7\n  5.3083935136244165E-01 a      2033     0    82     1     8\n -1.5314038909794420E-01 a      2034     0    82     1     9\n  1.7677902185973464E+00 a      2035     0    82     1    10\n  2.4467669959048490E+00 a      2036     0    82     1    11\n  8.2834397033051943E-01 a      2037     0    82     1    12\n -2.4162608599290158E+00 a      2038     0    82     1    13\n -1.0726609155321805E+00 a      2039     0    82     1    14\n  4.4621441472249428E+00 a      2040     0    82     1    15\n  9.3249693507493880E-01 a      2041     0    82     1    16\n -2.5032079823706490E+00 a      2042     0    82     1    17\n  4.7305533947806272E-01 a      2043     0    82     1    18\n -1.7460582059461345E+00 a      2044     0    82     1    19\n -5.6640486642835175E-01 a      2045     0    82     1    20\n  1.5762175380816463E+00 a      2046     0    82     1    21\n  1.7808575442903285E+00 a      2047     0    82     1    22\n -3.6886996094663642E+00 a      2048     0    82     1    23\n -4.5135036811128249E+00 a      2049     0    82     1    24\n  4.6539208055168070E-02 a      2050     0    82     1    25\n -6.8101541046659753E-01 a      2051     0    83     1     1\n  1.6367869525297607E+00 a      2052     0    83     1     2\n  2.2551253117978436E+00 a      2053     0    83     1     3\n -2.8720005943700704E+00 a      2054     0    83     1     4\n -2.6309910998202559E+00 a      2055     0    83     1     5\n -1.0916211885512623E+00 a      2056     0    83     1     6\n -3.4298714806646119E-01 a      2057     0    83     1     7\n -3.3558482732776058E+00 a      2058     0    83     1     8\n -4.8917244503585664E+00 a      2059     0    83     1     9\n  1.7417477278187399E+00 a      2060     0    83     1    10\n  7.2259788319301521E-02 a      2061     0    83     1    11\n -1.6921237428597191E-01 a      2062     0    83     1    12\n -3.3205896295262507E+00 a      2063     0    83     1    13\n -1.2719724204430700E+00 a      2064     0    83     1    14\n  2.2710425203908664E+00 a      2065     0    83     1    15\n  2.5053973085214563E+00 a      2066     0    83     1    16\n -1.5058148067353272E-01 a      2067     0    83     1    17\n -4.4397546147842037E-01 a      2068     0    83     1    18\n  8.6448984386966854E-01 a      2069     0    83     1    19\n  1.7742768386961567E+00 a      2070     0    83     1    20\n  4.5527891082022602E+00 a      2071     0    83     1    21\n -7.0615230056202061E-01 a      2072     0    83     1    22\n -1.6584185055220644E+00 a      2073     0    83     1    23\n  4.4986030144511896E-01 a      2074     0    83     1    24\n  9.1770785145515410E-01 a      2075     0    83     1    25\n -3.8145712721259502E+00 a      2076     0    84     1     1\n -2.5145200601023086E+00 a      2077     0    84     1     2\n -4.2169929330264860E-01 a      2078     0    84     1     3\n  2.0689982362267694E+00 a      2079     0    84     1     4\n -4.0696272673038845E+00 a      2080     0    84     1     5\n -9.4738636185132852E-01 a      2081     0    84     1     6\n  1.2168554149082336E+00 a      2082     0    84     1     7\n -1.5528759736957551E+00 a      2083     0    84     1     8\n -1.9943907692858371E+00 a      2084     0    84     1     9\n  3.6744512555299208E-01 a      2085     0    84     1    10\n  1.7987095051339763E+00 a      2086     0    84     1    11\n  1.5611222442819459E+00 a      2087     0    84     1    12\n  2.9865536936203632E+00 a      2088     0    84     1    13\n -4.0976493578631414E+00 a      2089     0    84     1    14\n  1.2370566139116121E+00 a      2090     0    84     1    15\n -3.8804572309374097E-01 a      2091     0    84     1    16\n  9.9275502867032728E-01 a      2092     0    84     1    17\n  1.2428254086248287E+00 a      2093     0    84     1    18\n  1.1992135958422698E+00 a      2094     0    84     1    19\n -1.8339008369782659E+00 a      2095     0    84     1    20\n -2.7435501659103609E+00 a      2096     0    84     1    21\n -7.4511297332309423E-01 a      2097     0    84     1    22\n  4.7677246120773846E+00 a      2098     0    84     1    23\n -2.1345341164742409E+00 a      2099     0    84     1    24\n  2.8781512426503347E-01 a      2100     0    84     1    25\n  2.8749626042363141E-01 a      2101     0    85     1     1\n -1.7550151452179452E+00 a      2102     0    85     1     2\n -1.1401438613955355E+00 a      2103     0    85     1     3\n  1.8594458944558443E-02 a      2104     0    85     1     4\n  7.8426316340148106E-01 a      2105     0    85     1     5\n -4.2917358143104432E+00 a      2106     0    85     1     6\n -1.6626598727984204E-01 a      2107     0    85     1     7\n  3.0347190126450587E+00 a      2108     0    85     1     8\n  3.8113244528231188E-01 a      2109     0    85     1     9\n  6.9193073912482261E-01 a      2110     0    85     1    10\n -3.0914132510192673E+00 a      2111     0    85     1    11\n  4.4900896577440530E-01 a      2112     0    85     1    12\n  1.4695040752223913E+00 a      2113     0    85     1    13\n -9.6243633609541712E-01 a      2114     0    85     1    14\n  1.2616757289593470E+00 a      2115     0    85     1    15\n -5.4668539527328897E-01 a      2116     0    85     1    16\n  9.7729709435926504E-01 a      2117     0    85     1    17\n  1.6983940069576984E+00 a      2118     0    85     1    18\n -1.3412043780205507E-01 a      2119     0    85     1    19\n  1.2116678418643672E+00 a      2120     0    85     1    20\n -6.2474504988570745E-01 a      2121     0    85     1    21\n -7.5448642041665392E-01 a      2122     0    85     1    22\n -3.0044900436747661E+00 a      2123     0    85     1    23\n  1.7500089163787638E+00 a      2124     0    85     1    24\n  5.8563922935551971E-01 a      2125     0    85     1    25\n  3.4528390812414607E-03 a      2126     0    86     1     1\n  3.7478103237123833E-01 a      2127     0    86     1     2\n  1.1620162768842017E+00 a      2128     0    86     1     3\n  2.5456908897422310E+00 a      2129     0    86     1     4\n  3.9571688166703067E-01 a      2130     0    86     1     5\n  2.9241594404943116E+00 a      2131     0    86     1     6\n  1.7330197962186858E-01 a      2132     0    86     1     7\n -4.2898211583719803E+00 a      2133     0    86     1     8\n -5.3061575740670242E-01 a      2134     0    86     1     9\n -1.1133083446172420E+00 a      2135     0    86     1    10\n  1.6420908125966760E+00 a      2136     0    86     1    11\n -9.9958003981329435E-01 a      2137     0    86     1    12\n -3.0620116026877242E+00 a      2138     0    86     1    13\n -3.3319202920660613E+00 a      2139     0    86     1    14\n -3.2670834636460935E+00 a      2140     0    86     1    15\n  1.8881417119762106E-01 a      2141     0    86     1    16\n -3.9233035227926933E+00 a      2142     0    86     1    17\n  3.3588393104933084E-01 a      2143     0    86     1    18\n  7.6114016668792872E-01 a      2144     0    86     1    19\n  8.7277312886229530E-01 a      2145     0    86     1    20\n  5.4418287314896896E-01 a      2146     0    86     1    21\n  1.2764374069205566E+00 a      2147     0    86     1    22\n  7.7478718400336688E-01 a      2148     0    86     1    23\n -1.4310204684658627E+00 a      2149     0    86     1    24\n -1.7950279515762924E-01 a      2150     0    86     1    25\n -4.2828896266193744E-01 a      2151     0    87     1     1\n  2.5606837564546842E-01 a      2152     0    87     1     2\n -5.2073375822496692E-01 a      2153     0    87     1     3\n -3.0657626435895544E+00 a      2154     0    87     1     4\n -1.1312414537843978E+00 a      2155     0    87     1     5\n -1.6586429114011596E+00 a      2156     0    87     1     6\n  3.7038186963350062E-01 a      2157     0    87     1     7\n -1.3734474352300143E+00 a      2158     0    87     1     8\n -1.3389750407868268E+00 a      2159     0    87     1     9\n -2.4935565856071484E-01 a      2160     0    87     1    10\n  3.5561421263345239E-01 a      2161     0    87     1    11\n -2.7010466817496446E+00 a      2162     0    87     1    12\n  1.9941680200825993E+00 a      2163     0    87     1    13\n  1.5723648520993422E-01 a      2164     0    87     1    14\n -1.2742301274261532E+00 a      2165     0    87     1    15\n  5.8733687438643711E-01 a      2166     0    87     1    16\n -1.0650191091468435E+00 a      2167     0    87     1    17\n  1.7924605585713398E-02 a      2168     0    87     1    18\n  5.1839822861297069E-02 a      2169     0    87     1    19\n -1.9693727989714653E+00 a      2170     0    87     1    20\n -2.4770997045208540E-01 a      2171     0    87     1    21\n  6.8082243135466258E-01 a      2172     0    87     1    22\n -5.4878512229475385E-01 a      2173     0    87     1    23\n -1.2741616587757760E+00 a      2174     0    87     1    24\n  1.1890598336112055E+00 a      2175     0    87     1    25\n  1.1818051384143641E-01 a      2176     0    88     1     1\n -3.1956414290950930E-01 a      2177     0    88     1     2\n  4.9703933278633775E-02 a      2178     0    88     1     3\n -3.2471251480911971E+00 a      2179     0    88     1     4\n  1.3601985543292909E+00 a      2180     0    88     1     5\n -2.2636391624300090E+00 a      2181     0    88     1     6\n  4.7166466026724085E-01 a      2182     0    88     1     7\n  1.8088729523242837E+00 a      2183     0    88     1     8\n  1.2095942551927168E+00 a      2184     0    88     1     9\n  8.2176561111559254E-01 a      2185     0    88     1    10\n -1.4493679618775099E+00 a      2186     0    88     1    11\n  2.3830802132361684E+00 a      2187     0    88     1    12\n -2.2179193887778021E+00 a      2188     0    88     1    13\n -1.7405246050073773E+00 a      2189     0    88     1    14\n -8.6445468251123037E-01 a      2190     0    88     1    15\n -3.3763679771916855E-02 a      2191     0    88     1    16\n 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5.5019169428638304E-01 a      8741     1    16     2    16\n -3.4249669321966278E+00 a      8742     1    16     2    17\n -3.1423819742262493E-01 a      8743     1    16     2    18\n -1.3989925834700034E+00 a      8744     1    16     2    19\n  7.9747595510460012E-02 a      8745     1    16     2    20\n -2.3947459779644440E+00 a      8746     1    16     2    21\n  9.5085447424314828E-01 a      8747     1    16     2    22\n  7.7384832921845037E-01 a      8748     1    16     2    23\n -7.7706748030743056E-01 a      8749     1    16     2    24\n  1.0280647480895837E+00 a      8750     1    16     2    25\n  1.0434658577470174E-01 a      8751     1    17     2     1\n -1.5210367542796770E+00 a      8752     1    17     2     2\n -1.0511409072729181E+00 a      8753     1    17     2     3\n -8.0420729520108480E-02 a      8754     1    17     2     4\n  6.4968217814826673E-02 a      8755     1    17     2     5\n  3.7214481157037121E-01 a      8756     1    17     2     6\n -3.6290593720144504E-01 a      8757     1    17     2     7\n -3.4849606532490141E-01 a      8758     1    17     2     8\n  6.7753154237041380E-01 a      8759     1    17     2     9\n -6.3397018455628107E-01 a      8760     1    17     2    10\n  8.5615875927314167E-01 a      8761     1    17     2    11\n  2.8331563190589542E+00 a      8762     1    17     2    12\n  5.1311332097484763E-01 a      8763     1    17     2    13\n -1.8640833959223484E+00 a      8764     1    17     2    14\n -1.6376936554431791E+00 a      8765     1    17     2    15\n  8.6194139773843481E-01 a      8766     1    17     2    16\n  2.7635270649521970E-01 a      8767     1    17     2    17\n  5.1610611545474383E-01 a      8768     1    17     2    18\n -1.6901534840953572E+00 a      8769     1    17     2    19\n -1.3146911931860341E+00 a      8770     1    17     2    20\n  6.5398619578525818E-01 a      8771     1    17     2    21\n  1.8780797694651331E-02 a      8772     1    17     2    22\n -1.2828369138248208E+00 a      8773     1    17     2    23\n  9.2541808320774341E-02 a      8774     1    17     2    24\n  3.6303518963102227E-01 a      8775     1    17     2    25\n  1.7844985903242812E+00 a      8776     1    18     2     1\n -4.6129890164196059E+00 a      8777     1    18     2     2\n  2.4046876199252094E+00 a      8778     1    18     2     3\n  8.9653438214233472E-01 a      8779     1    18     2     4\n  4.0482512907985840E-01 a      8780     1    18     2     5\n -1.5730514515811844E+00 a      8781     1    18     2     6\n -6.6585765577360723E-01 a      8782     1    18     2     7\n -4.0462213699134464E-01 a      8783     1    18     2     8\n -3.9977943101636493E-01 a      8784     1    18     2     9\n  2.2656822423954361E+00 a      8785     1    18     2    10\n  1.1499354389613394E+00 a      8786     1    18     2    11\n -1.2172431946991304E+00 a      8787     1    18     2    12\n  4.1901408770896093E-01 a      8788     1    18     2    13\n  4.3427089800458729E-01 a      8789     1    18     2    14\n  1.0269601424509849E+00 a      8790     1    18     2    15\n -7.5150498608914884E-01 a      8791     1    18     2    16\n -4.8202117614779694E-01 a      8792     1    18     2    17\n -1.5707202564396059E+00 a      8793     1    18     2    18\n  1.7917477142510190E+00 a      8794     1    18     2    19\n  4.5744870242609467E-02 a      8795     1    18     2    20\n  1.2591705021360899E-01 a      8796     1    18     2    21\n  3.1058645950056174E-01 a      8797     1    18     2    22\n  6.6127437120545185E-01 a      8798     1    18     2    23\n  7.0752987239104925E-01 a      8799     1    18     2    24\n -1.1032145244624643E+00 a      8800     1    18     2    25\n  2.4736645223665268E-01 a      8801     1    19     2     1\n  9.2681189169842415E-01 a      8802     1    19     2     2\n -2.0334818442555287E+00 a      8803     1    19     2     3\n  1.2319425067894045E+00 a      8804     1    19     2     4\n  1.0091533129830501E+00 a      8805     1    19     2     5\n  1.3101348202655485E+00 a      8806     1    19     2     6\n  1.2876540568367965E+00 a      8807     1    19     2     7\n -1.9462858632592206E-01 a      8808     1    19     2     8\n -1.1321002224932226E-01 a      8809     1    19     2     9\n  2.0009983800607158E+00 a      8810     1    19     2    10\n -1.1250406545195766E+00 a      8811     1    19     2    11\n -3.4389214804685925E-01 a      8812     1    19     2    12\n -6.1934237276541171E-01 a      8813     1    19     2    13\n  1.7458791741771966E+00 a      8814     1    19     2    14\n  5.8398348877805295E-01 a      8815     1    19     2    15\n -1.7529217972599895E-01 a      8816     1    19     2    16\n  7.8292398741523173E-01 a      8817     1    19     2    17\n  1.8070936516818714E-01 a      8818     1    19     2    18\n -1.2635541271379785E-01 a      8819     1    19     2    19\n -2.1796249286352047E+00 a      8820     1    19     2    20\n  3.2949873711342698E-01 a      8821     1    19     2    21\n -3.2070057485432585E-01 a      8822     1    19     2    22\n  1.7582771382676135E-01 a      8823     1    19     2    23\n -9.7254898090562564E-02 a      8824     1    19     2    24\n  9.1997475286734465E-02 a      8825     1    19     2    25\n -6.6783776183946209E-02 a      8826     1    20     2     1\n -1.0367383620105466E+00 a      8827     1    20     2     2\n -5.0635918792281878E-03 a      8828     1    20     2     3\n -7.3965916311591906E-01 a      8829     1    20     2     4\n  2.4179220241745603E-01 a      8830     1    20     2     5\n -1.4269228450744231E-01 a      8831     1    20     2     6\n -3.2850401471105289E-01 a      8832     1    20     2     7\n  1.1122933376723334E+00 a      8833     1    20     2     8\n -1.7997830510951567E+00 a      8834     1    20     2     9\n -1.8459708986190904E+00 a      8835     1    20     2    10\n  1.0584103355904910E+00 a      8836     1    20     2    11\n  9.3322460571707055E-01 a      8837     1    20     2    12\n -1.8512482930987018E-01 a      8838     1    20     2    13\n  2.3378584402429589E-01 a      8839     1    20     2    14\n -9.6065536985668276E-02 a      8840     1    20     2    15\n  1.2925540670114162E+00 a      8841     1    20     2    16\n -1.8485906257217257E+00 a      8842     1    20     2    17\n -1.5575773892589289E+00 a      8843     1    20     2    18\n  7.4157846781092085E-01 a      8844     1    20     2    19\n  7.2127070991890707E-01 a      8845     1    20     2    20\n -7.5959033378675622E-01 a      8846     1    20     2    21\n  3.3496609798867005E-01 a      8847     1    20     2    22\n -2.2145380937668278E+00 a      8848     1    20     2    23\n  7.1192969230908501E-03 a      8849     1    20     2    24\n -6.7114288812328105E-01 a      8850     1    20     2    25\n -1.0305091984860848E+00 a      8851     1    21     2     1\n  2.4826611778875174E+00 a      8852     1    21     2     2\n  1.3946507521941012E+00 a      8853     1    21     2     3\n -5.0287223248530633E-01 a      8854     1    21     2     4\n  1.9156869390047898E-01 a      8855     1    21     2     5\n -4.7114962311982195E-01 a      8856     1    21     2     6\n  1.9295093167526289E+00 a      8857     1    21     2     7\n  7.5908911618125563E-01 a      8858     1    21     2     8\n  4.1508620015220143E-01 a      8859     1    21     2     9\n  2.7139861919273706E-01 a      8860     1    21     2    10\n -5.1747848415114824E-02 a      8861     1    21     2    11\n -4.2534958936829703E-01 a      8862     1    21     2    12\n -2.5013343826676743E-01 a      8863     1    21     2    13\n -1.4914098793330355E+00 a      8864     1    21     2    14\n  1.1014486192017088E+00 a      8865     1    21     2    15\n  5.2297193219530531E-02 a      8866     1    21     2    16\n -1.7355374204370299E-03 a      8867     1    21     2    17\n  3.8369929185181766E+00 a      8868     1    21     2    18\n -3.0386765892739476E-01 a      8869     1    21     2    19\n -1.7261659359399306E+00 a      8870     1    21     2    20\n  3.7217279809336568E-01 a      8871     1    21     2    21\n  5.4610462484717825E-01 a      8872     1    21     2    22\n -1.6224448942779552E+00 a      8873     1    21     2    23\n  5.0213577399174780E-01 a      8874     1    21     2    24\n -7.0732097446139827E-02 a      8875     1    21     2    25\n  1.4673260499285137E+00 a      8876     1    22     2     1\n  4.2206936772615000E-01 a      8877     1    22     2     2\n  2.7537348204858275E-01 a      8878     1    22     2     3\n -1.7000406019530814E+00 a      8879     1    22     2     4\n -1.5153756459296526E+00 a      8880     1    22     2     5\n -8.1109909640822964E-01 a      8881     1    22     2     6\n -5.6078705051847019E-02 a      8882     1    22     2     7\n -1.6799527003317505E+00 a      8883     1    22     2     8\n  1.2558538698546033E+00 a      8884     1    22     2     9\n  4.0831368770552778E-01 a      8885     1    22     2    10\n  1.5107306927745854E+00 a      8886     1    22     2    11\n  1.7029997111881162E-01 a      8887     1    22     2    12\n  1.3827695580182775E+00 a      8888     1    22     2    13\n  2.1753781312239062E+00 a      8889     1    22     2    14\n -8.6201548158296359E-01 a      8890     1    22     2    15\n  1.2574285160193052E-01 a      8891     1    22     2    16\n -1.5950997458440513E-01 a      8892     1    22     2    17\n -4.5967301121023257E-01 a      8893     1    22     2    18\n -1.1095793417769297E-01 a      8894     1    22     2    19\n  4.4972878475561323E-01 a      8895     1    22     2    20\n -7.7306000355928356E-02 a      8896     1    22     2    21\n -1.7994775304904129E+00 a      8897     1    22     2    22\n  2.8623812807247764E+00 a      8898     1    22     2    23\n -5.8448227655716700E-01 a      8899     1    22     2    24\n -6.5115472585496281E-01 a      8900     1    22     2    25\n  1.0804126172077615E+00 a      8901     1    23     2     1\n  1.7278844207552331E+00 a      8902     1    23     2     2\n -1.8724392983954325E+00 a      8903     1    23     2     3\n -5.1519709274830472E-01 a      8904     1    23     2     4\n -9.5700224499989023E-02 a      8905     1    23     2     5\n -7.3922304886884463E-02 a      8906     1    23     2     6\n -3.4891258604659168E+00 a      8907     1    23     2     7\n  4.7327597906818841E-01 a      8908     1    23     2     8\n  2.2479057735736037E+00 a      8909     1    23     2     9\n  6.2998477090336458E-01 a      8910     1    23     2    10\n  1.3167085613795646E+00 a      8911     1    23     2    11\n -3.2265075583916303E-01 a      8912     1    23     2    12\n  1.8724788870524902E+00 a      8913     1    23     2    13\n -2.4435132577249492E+00 a      8914     1    23     2    14\n -1.7478542009273379E-01 a      8915     1    23     2    15\n -4.6824993019357490E-02 a      8916     1    23     2    16\n -5.8782193412285866E-01 a      8917     1    23     2    17\n -1.6980349046664429E+00 a      8918     1    23     2    18\n  1.0090307154265397E+00 a      8919     1    23     2    19\n  2.3992459833659008E+00 a      8920     1    23     2    20\n -2.5882242228655639E-01 a      8921     1    23     2    21\n  8.2966907898332432E-01 a      8922     1    23     2    22\n -1.0153341195139198E+00 a      8923     1    23     2    23\n -3.1967790050681877E-01 a      8924     1    23     2    24\n  1.9652140445765414E+00 a      8925     1    23     2    25\n  2.6971244557131291E-01 a      8926     1    24     2     1\n -2.3371393725534917E+00 a      8927     1    24     2     2\n  1.3003866784238831E+00 a      8928     1    24     2     3\n  1.5276070521578917E+00 a      8929     1    24     2     4\n  1.9017330783851097E-01 a      8930     1    24     2     5\n -1.4480586853466553E+00 a      8931     1    24     2     6\n  3.0592993147395908E-01 a      8932     1    24     2     7\n -6.6806214353359616E-01 a      8933     1    24     2     8\n -1.7293599563129067E+00 a      8934     1    24     2     9\n  1.9559816846428027E-01 a      8935     1    24     2    10\n -1.4953667100058550E+00 a      8936     1    24     2    11\n -7.3952032796660086E-02 a      8937     1    24     2    12\n -1.2792957423746931E+00 a      8938     1    24     2    13\n  1.7330377638627557E+00 a      8939     1    24     2    14\n  1.0274437995229191E+00 a      8940     1    24     2    15\n -4.3050738658969223E-01 a      8941     1    24     2    16\n  3.0455018241551639E+00 a      8942     1    24     2    17\n  3.3381685022483398E-01 a      8943     1    24     2    18\n  9.3456436334264625E-01 a      8944     1    24     2    19\n -1.1286187411359493E-01 a      8945     1    24     2    20\n  2.8725180306121906E-01 a      8946     1    24     2    21\n  3.8260388557024128E-01 a      8947     1    24     2    22\n  1.2343929371229763E+00 a      8948     1    24     2    23\n  1.5315318181929878E+00 a      8949     1    24     2    24\n  6.7747115029120719E-01 a      8950     1    24     2    25\n -8.6361029803221201E-01 a      8951     1    25     2     1\n -2.7918967028663122E-01 a      8952     1    25     2     2\n  8.6566498777006196E-01 a      8953     1    25     2     3\n  1.5990278627428536E+00 a      8954     1    25     2     4\n  8.9477594499644675E-01 a      8955     1    25     2     5\n  2.1199698152453004E+00 a      8956     1    25     2     6\n -9.0881080226896638E-01 a      8957     1    25     2     7\n  2.2480927967666686E-01 a      8958     1    25     2     8\n -1.2653379923961772E+00 a      8959     1    25     2     9\n  1.0004197254928477E+00 a      8960     1    25     2    10\n  2.8786469197148674E-02 a      8961     1    25     2    11\n  1.0869851341574510E+00 a      8962     1    25     2    12\n -5.0453089645542337E-01 a      8963     1    25     2    13\n -5.8835771566201844E-01 a      8964     1    25     2    14\n  7.3047327465327361E-01 a      8965     1    25     2    15\n -7.9019625297211193E-01 a      8966     1    25     2    16\n -1.2239667028337129E+00 a      8967     1    25     2    17\n  2.1423737018196305E+00 a      8968     1    25     2    18\n -5.3641001364055763E-01 a      8969     1    25     2    19\n  9.3965720225372040E-01 a      8970     1    25     2    20\n -1.8946262533832001E-01 a      8971     1    25     2    21\n -7.2768411906009167E-01 a      8972     1    25     2    22\n -8.4009171005852501E-01 a      8973     1    25     2    23\n -9.6210895587692621E-02 a      8974     1    25     2    24\n  1.0294900253191936E+00 a      8975     1    25     2    25\n -6.1409827602752971E+00 b      8976     2     1\n -7.3435363751884586E-01 b      8977     2     2\n -5.4609281355163128E+00 b      8978     2     3\n -8.0445299479364107E-01 b      8979     2     4\n -2.7915603687780917E+00 b      8980     2     5\n -1.5869680305406451E+00 b      8981     2     6\n  5.1861639276596629E-02 b      8982     2     7\n -2.0170381000945410E+00 b      8983     2     8\n -1.3620725843388071E-01 b      8984     2     9\n -9.4490480827058398E-01 b      8985     2    10\n  3.7444987345693981E-01 b      8986     2    11\n -3.9673915726294515E+00 b      8987     2    12\n  9.0040768070585253E-01 b      8988     2    13\n  2.0652705054465290E+00 b      8989     2    14\n -1.6937755256917253E+00 b      8990     2    15\n  1.0928532409789391E+00 b      8991     2    16\n -4.2737789958368244E-01 b      8992     2    17\n  1.1600415930588150E+00 b      8993     2    18\n  1.7891861212833393E+00 b      8994     2    19\n  3.1373979554958009E-01 b      8995     2    20\n -5.9302439501067394E-01 b      8996     2    21\n  1.5705083345779005E+00 b      8997     2    22\n -2.2164103433440160E-01 b      8998     2    23\n  3.8312930277173701E-01 b      8999     2    24\n -3.1342349265758063E-01 b      9000     2    25\n  3.6304805461502632E-01 a      9001     2     1     3     1\n -6.5823799219877216E-03 a      9002     2     2     3     1\n -1.3121314208977258E-01 a      9003     2     3     3     1\n  7.1586566958173031E-02 a      9004     2     4     3     1\n -5.4372803926883717E-01 a      9005     2     5     3     1\n -4.2026697252852768E-01 a      9006     2     6     3     1\n -3.9435467280032055E-02 a      9007     2     7     3     1\n -2.5212591471480967E-03 a      9008     2     8     3     1\n  1.7449373076267763E-01 a      9009     2     9     3     1\n -6.0002877894158274E-04 a      9010     2    10     3     1\n  5.5300363498743121E-01 a      9011     2    11     3     1\n -3.5541446026866685E-01 a      9012     2    12     3     1\n  1.6102460198142304E-01 a      9013     2    13     3     1\n -5.5378817205560060E-01 a      9014     2    14     3     1\n -1.3701138428302488E+00 a      9015     2    15     3     1\n -9.0104042914602123E-01 a      9016     2    16     3     1\n -2.5611227485930576E-03 a      9017     2    17     3     1\n -1.3485021173759795E+00 a      9018     2    18     3     1\n  1.0024376080324708E+00 a      9019     2    19     3     1\n  1.4001790972679468E-02 a      9020     2    20     3     1\n  7.9429263074196277E-01 a      9021     2    21     3     1\n  5.9092476845946285E-01 a      9022     2    22     3     1\n  9.3204133982188275E-01 a      9023     2    23     3     1\n -8.2707424519823036E-01 a      9024     2    24     3     1\n  4.8028155477385344E-03 a      9025     2    25     3     1\n  2.4784889468279641E+00 b      9026     3     1\n"
  },
  {
    "path": "examples/nnp-predict/DMABN_SCAN/weights.007.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -3.5369504107014866E+00 a         1     0     1     1     1\n  2.5396762681640106E+00 a         2     0     1     1     2\n  5.3737086807515388E-01 a         3     0     1     1     3\n  3.3181932998498191E+00 a         4     0     1     1     4\n  3.3981664467635913E+00 a         5     0     1     1     5\n  3.2465972875061313E+00 a         6     0     1     1     6\n -1.2403935054144948E+00 a         7     0     1     1     7\n  1.1307419369244407E+00 a         8     0     1     1     8\n  8.4866583151700026E-01 a         9     0     1     1     9\n  7.6140092891142785E-01 a        10     0     1     1    10\n  3.3739810113376794E+00 a        11     0     1     1    11\n -3.5028092681158909E+00 a        12     0     1     1    12\n  1.4745993853393073E+00 a        13     0     1     1    13\n  1.1081649365446951E+00 a        14     0     1     1    14\n -3.6522674441852532E-01 a        15     0     1     1    15\n  1.8013731727753872E+00 a        16     0     1     1    16\n  6.4473949657733931E-01 a        17     0     1     1    17\n -1.8897655255018206E+00 a        18     0     1     1    18\n -2.8797270652304743E+00 a        19     0     1     1    19\n  4.7358582495094304E+00 a        20     0     1     1    20\n  8.9497367876562617E-01 a        21     0     1     1    21\n -5.9979238386008715E-01 a        22     0     1     1    22\n -6.2029062408324993E+00 a        23     0     1     1    23\n  1.4841013053889547E+00 a        24     0     1     1    24\n -4.2337402404705848E-01 a        25     0     1     1    25\n -4.8423132565005034E-01 a        26     0     2     1     1\n -4.9549149754103644E-01 a        27     0     2     1     2\n  9.3104303701160596E-01 a        28     0     2     1     3\n  1.9540960757003016E+00 a        29     0     2     1     4\n  4.2376922693734755E+00 a        30     0     2     1     5\n -2.7271027313772609E+00 a        31     0     2     1     6\n  2.1582732186477331E+00 a        32     0     2     1     7\n -1.4332564004991794E-01 a        33     0     2     1     8\n -2.3619676627300470E-01 a        34     0     2     1     9\n  2.6898227423718629E-01 a        35     0     2     1    10\n  3.7452186602811608E+00 a        36     0     2     1    11\n -1.9374213998844403E+00 a        37     0     2     1    12\n  1.6164305649583353E+00 a        38     0     2     1    13\n  4.7856650305411037E+00 a        39     0     2     1    14\n  5.9317731612542834E-01 a        40     0     2     1    15\n -1.1748391855770293E+00 a        41     0     2     1    16\n -7.9204542293086622E-01 a        42     0     2     1    17\n  1.5991077119236101E+00 a        43     0     2     1    18\n -1.6410056375191431E+00 a        44     0     2     1    19\n  2.0394598945410802E-01 a        45     0     2     1    20\n  1.5177999824312389E+00 a        46     0     2     1    21\n -2.8449242418852638E-01 a        47     0     2     1    22\n  1.7158339717498070E+00 a        48     0     2     1    23\n -8.2576714725380340E-01 a        49     0     2     1    24\n -6.0384305773984115E-01 a        50     0     2     1    25\n -1.6615228926257042E+00 a        51     0     3     1     1\n  2.1019980813239825E-01 a        52     0     3     1     2\n  2.8976731747304645E+00 a        53     0     3     1     3\n  5.1591873279295344E+00 a        54     0     3     1     4\n  2.9578519581752793E+00 a        55     0     3     1     5\n  1.5922593170366808E+00 a        56     0     3     1     6\n  1.9708021381212191E+00 a        57     0     3     1     7\n  1.7522264377470143E-01 a        58     0     3     1     8\n -7.2744693304019725E-01 a        59     0     3     1     9\n  5.6864048834071079E-01 a        60     0     3     1    10\n  2.1185073757589721E+00 a        61     0     3     1    11\n  2.2137675460624312E-01 a        62     0     3     1    12\n  1.5004000701801765E+00 a        63     0     3     1    13\n  3.3376862065889976E+00 a        64     0     3     1    14\n  7.5809549958819689E-01 a        65     0     3     1    15\n  8.3661664872419966E-02 a        66     0     3     1    16\n  9.6849074314036177E-01 a        67     0     3     1    17\n  7.4521614669691527E-01 a        68     0     3     1    18\n -1.2359085834555514E+00 a        69     0     3     1    19\n  5.8994870842785452E-01 a        70     0     3     1    20\n -1.6261704189098432E+00 a        71     0     3     1    21\n -1.3407155465071025E-01 a        72     0     3     1    22\n -2.2788980414484157E+00 a        73     0     3     1    23\n  5.9726184489456058E-01 a        74     0     3     1    24\n  2.7859367291242004E-01 a        75     0     3     1    25\n  1.6137775622660802E-01 a        76     0     4     1     1\n  1.3265631948912675E+00 a        77     0     4     1     2\n  9.1699448746998968E-01 a        78     0     4     1     3\n  2.0710751376956007E+00 a        79     0     4     1     4\n  1.2834637068190666E+00 a        80     0     4     1     5\n  5.6200826316323416E-01 a        81     0     4     1     6\n  1.2004204723087921E+00 a        82     0     4     1     7\n  2.7128043760988069E-01 a        83     0     4     1     8\n  1.3788939740835870E+00 a        84     0     4     1     9\n  1.1459941982839992E+00 a        85     0     4     1    10\n  7.4814724037637714E-01 a        86     0     4     1    11\n -1.6336102315671188E+00 a        87     0     4     1    12\n  2.2724200714200466E+00 a        88     0     4     1    13\n  1.3718333545279562E+00 a        89     0     4     1    14\n -3.1593167113522957E-01 a        90     0     4     1    15\n -2.2482201609029254E-01 a        91     0     4     1    16\n  7.2124342076845493E-01 a        92     0     4     1    17\n  9.5786133504820736E-01 a        93     0     4     1    18\n -1.2888083614406223E+00 a        94     0     4     1    19\n  3.4331191220547419E-01 a        95     0     4     1    20\n  1.2942324858923577E+00 a        96     0     4     1    21\n  8.8022606716584051E-01 a        97     0     4     1    22\n -1.7667962687723222E+00 a        98     0     4     1    23\n -3.3512537310168961E-01 a        99     0     4     1    24\n  7.4812436846970098E-01 a       100     0     4     1    25\n -8.2360181611159022E-01 a       101     0     5     1     1\n  1.2389074587677156E+00 a       102     0     5     1     2\n -2.7480085413885793E+00 a       103     0     5     1     3\n -3.1859977838059073E+00 a       104     0     5     1     4\n  3.4141656815739330E+00 a       105     0     5     1     5\n -4.7732483562378158E+00 a       106     0     5     1     6\n  2.3523432138491729E+00 a       107     0     5     1     7\n  1.0301737280285617E+00 a       108     0     5     1     8\n  2.5492092219543898E+00 a       109     0     5     1     9\n  1.1077244960626917E+00 a       110     0     5     1    10\n -4.5045413443101001E+00 a       111     0     5     1    11\n -8.1186174547060952E-01 a       112     0     5     1    12\n  1.2533108018348613E+00 a       113     0     5     1    13\n -1.3372931909988894E+00 a       114     0     5     1    14\n  2.5296444014339325E-01 a       115     0     5     1    15\n  4.7724859575399980E+00 a       116     0     5     1    16\n  2.1403985985822938E+00 a       117     0     5     1    17\n  2.7779036863945872E-01 a       118     0     5     1    18\n -2.9996254051595863E+00 a       119     0     5     1    19\n -3.3842515391272281E+00 a       120     0     5     1    20\n -5.3379214596119260E+00 a       121     0     5     1    21\n -1.9817419047697455E+00 a       122     0     5     1    22\n -1.6726908270652059E+00 a       123     0     5     1    23\n -6.8556070871757424E-01 a       124     0     5     1    24\n -2.6142771202482811E+00 a       125     0     5     1    25\n  1.2259423853446638E+00 a       126     0     6     1     1\n -3.3394907579456745E-01 a       127     0     6     1     2\n  7.0880818803740619E-01 a       128     0     6     1     3\n  1.7666631896846139E+00 a       129     0     6     1     4\n  1.8355136403565278E+00 a       130     0     6     1     5\n -4.8623229625847975E-01 a       131     0     6     1     6\n  4.9653634068105418E-01 a       132     0     6     1     7\n -6.0359238857950592E-01 a       133     0     6     1     8\n  9.1810801996011204E-01 a       134     0     6     1     9\n  1.6854477406661306E+00 a       135     0     6     1    10\n  4.9418968882985015E-01 a       136     0     6     1    11\n -3.2675024782229021E+00 a       137     0     6     1    12\n  1.1399565063123112E+00 a       138     0     6     1    13\n  1.4998674747796750E+00 a       139     0     6     1    14\n  5.2978287848528494E-01 a       140     0     6     1    15\n  2.1264030434087960E-01 a       141     0     6     1    16\n -2.9555371696446975E-01 a       142     0     6     1    17\n  1.3892481175900235E+00 a       143     0     6     1    18\n -1.8904848855771703E-01 a       144     0     6     1    19\n  4.7200678300320503E-01 a       145     0     6     1    20\n  2.2951627198092424E+00 a       146     0     6     1    21\n  1.0946505322833169E+00 a       147     0     6     1    22\n -1.0486222160093548E+00 a       148     0     6     1    23\n -6.1341141372558450E-01 a       149     0     6     1    24\n  4.1037519088469276E-01 a       150     0     6     1    25\n  5.7581129827271060E-01 a       151     0     7     1     1\n -1.4179307877998559E+00 a       152     0     7     1     2\n -1.9653000433073284E+00 a       153     0     7     1     3\n -2.3286820920099810E-01 a       154     0     7     1     4\n  2.0836337836196188E+00 a       155     0     7     1     5\n -4.4582845471313820E-01 a       156     0     7     1     6\n -2.3377083089113473E+00 a       157     0     7     1     7\n -3.6643640174046543E-01 a       158     0     7     1     8\n  4.6784911178417268E+00 a       159     0     7     1     9\n  3.3022553293757512E-01 a       160     0     7     1    10\n -1.2959385768968392E+00 a       161     0     7     1    11\n  5.8499791887073926E-01 a       162     0     7     1    12\n  1.1531291281898310E+00 a       163     0     7     1    13\n -2.3054239228455762E+00 a       164     0     7     1    14\n  3.5247398928248069E-01 a       165     0     7     1    15\n  1.6146837084281047E+00 a       166     0     7     1    16\n  2.1203472491305080E+00 a       167     0     7     1    17\n -1.8361957578663717E+00 a       168     0     7     1    18\n -1.2340931627757279E-01 a       169     0     7     1    19\n -2.7461865270306909E+00 a       170     0     7     1    20\n -1.9189369712374460E+00 a       171     0     7     1    21\n  3.3180021245116675E+00 a       172     0     7     1    22\n -4.4281524647448239E-01 a       173     0     7     1    23\n  2.6549921115541699E+00 a       174     0     7     1    24\n -1.7328749320819510E+00 a       175     0     7     1    25\n  5.8066234918825999E-01 a       176     0     8     1     1\n -2.9916388302819075E-01 a       177     0     8     1     2\n  1.0762660131515738E+00 a       178     0     8     1     3\n  1.5814866457341863E+00 a       179     0     8     1     4\n  1.0966557619637038E+00 a       180     0     8     1     5\n -1.3814188779290431E+00 a       181     0     8     1     6\n  1.0160324863294588E+00 a       182     0     8     1     7\n -3.7624402488680214E-01 a       183     0     8     1     8\n -2.0001002057236408E-01 a       184     0     8     1     9\n  1.3580344299300324E+00 a       185     0     8     1    10\n  8.1967136445873057E-02 a       186     0     8     1    11\n -1.7657447391915786E+00 a       187     0     8     1    12\n  1.6828458992949018E+00 a       188     0     8     1    13\n  1.7108480693960313E+00 a       189     0     8     1    14\n -3.0102712245660512E-01 a       190     0     8     1    15\n  7.1462136054979974E-01 a       191     0     8     1    16\n  6.5357801443900077E-01 a       192     0     8     1    17\n  7.6949828410288423E-01 a       193     0     8     1    18\n  2.8130249680720304E-01 a       194     0     8     1    19\n -3.6094141127346091E-01 a       195     0     8     1    20\n  1.5315179724838315E+00 a       196     0     8     1    21\n  2.1869673147199932E-02 a       197     0     8     1    22\n -1.1839123219002545E+00 a       198     0     8     1    23\n  2.6273244631137654E-01 a       199     0     8     1    24\n -2.9786466533803396E-01 a       200     0     8     1    25\n -2.8423806276941194E-01 a       201     0     9     1     1\n  1.5182459071207557E+00 a       202     0     9     1     2\n  1.0117936185726237E+00 a       203     0     9     1     3\n  7.7597709991981445E-01 a       204     0     9     1     4\n  2.0044073175914647E+00 a       205     0     9     1     5\n -3.0051919474603433E-01 a       206     0     9     1     6\n  4.3862499672140409E-01 a       207     0     9     1     7\n  1.5378988336897817E-01 a       208     0     9     1     8\n -2.9340386492649256E-01 a       209     0     9     1     9\n  6.0369528188690535E-01 a       210     0     9     1    10\n  1.6080117634296287E+00 a       211     0     9     1    11\n -2.5781038542659074E+00 a       212     0     9     1    12\n  2.2856449746398799E+00 a       213     0     9     1    13\n  2.7908141156908557E+00 a       214     0     9     1    14\n  9.4397074903973854E-01 a       215     0     9     1    15\n -6.2441132967208157E-01 a       216     0     9     1    16\n  4.7604712301386415E-01 a       217     0     9     1    17\n  1.0794779806027370E+00 a       218     0     9     1    18\n  2.9326477859013628E-01 a       219     0     9     1    19\n -8.6447554836389762E-01 a       220     0     9     1    20\n  1.9534046462820254E+00 a       221     0     9     1    21\n  6.6171444006364522E-01 a       222     0     9     1    22\n -1.6190252598095867E+00 a       223     0     9     1    23\n -1.1214274320290180E-01 a       224     0     9     1    24\n -7.7873766708465475E-01 a       225     0     9     1    25\n  2.1922515273458129E-01 a       226     0    10     1     1\n  6.1900571403456073E-01 a       227     0    10     1     2\n  2.7917094717539399E-02 a       228     0    10     1     3\n  8.6391795720088593E-02 a       229     0    10     1     4\n  1.9807717572422867E+00 a       230     0    10     1     5\n  7.8352980726175070E-01 a       231     0    10     1     6\n -2.1062674455157371E+00 a       232     0    10     1     7\n  1.1749389745474137E+00 a       233     0    10     1     8\n -3.1676076872318992E+00 a       234     0    10     1     9\n  8.4269331764199137E-02 a       235     0    10     1    10\n -1.6865214268857009E+00 a       236     0    10     1    11\n  1.1857601578439116E+00 a       237     0    10     1    12\n  1.5839429394128990E+00 a       238     0    10     1    13\n -3.5128972887231069E-01 a       239     0    10     1    14\n -1.3594967627177972E+00 a       240     0    10     1    15\n -2.4697479144904406E+00 a       241     0    10     1    16\n -3.6717766821821001E+00 a       242     0    10     1    17\n -2.0739154619538267E+00 a       243     0    10     1    18\n -4.1906488461252320E-02 a       244     0    10     1    19\n  1.0143575179083719E+00 a       245     0    10     1    20\n -8.8332836755727784E-01 a       246     0    10     1    21\n -4.8443924636936542E-01 a       247     0    10     1    22\n -2.8628865345566710E+00 a       248     0    10     1    23\n  1.4055097902341183E+00 a       249     0    10     1    24\n -2.6195950322194257E+00 a       250     0    10     1    25\n  7.9679355222818660E-03 a       251     0    11     1     1\n  9.7108654234050007E-01 a       252     0    11     1     2\n  1.9025274067511575E+00 a       253     0    11     1     3\n -2.1464172477598469E+00 a       254     0    11     1     4\n  2.0402343485064454E+00 a       255     0    11     1     5\n  4.0734458067825621E+00 a       256     0    11     1     6\n  2.3918993125104877E+00 a       257     0    11     1     7\n -1.9685457336367871E+00 a       258     0    11     1     8\n -2.0227347565404374E-01 a       259     0    11     1     9\n  4.6255887685820225E+00 a       260     0    11     1    10\n  4.8015843576594086E-01 a       261     0    11     1    11\n  6.6042388553309872E-01 a       262     0    11     1    12\n  2.6415482859443125E+00 a       263     0    11     1    13\n -3.2484790365838556E-01 a       264     0    11     1    14\n -1.2441413248612294E-01 a       265     0    11     1    15\n -1.4328677961766330E+00 a       266     0    11     1    16\n  1.8974805922055420E+00 a       267     0    11     1    17\n  8.0751889634880961E-02 a       268     0    11     1    18\n  1.6950461845207432E+00 a       269     0    11     1    19\n  9.0709393644411440E-01 a       270     0    11     1    20\n -1.3112506094733818E+00 a       271     0    11     1    21\n  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5.6046563572575252E+00 a      1936     0    78     1    11\n -1.8518577275242660E+00 a      1937     0    78     1    12\n  2.2083687354038082E+00 a      1938     0    78     1    13\n  1.4772749737540514E+00 a      1939     0    78     1    14\n -6.4996310003107050E-01 a      1940     0    78     1    15\n -2.3938127460621770E+00 a      1941     0    78     1    16\n  3.0821423070618789E-02 a      1942     0    78     1    17\n -1.1242502355641322E+00 a      1943     0    78     1    18\n  2.5690001397520414E+00 a      1944     0    78     1    19\n  1.0597212178581785E+00 a      1945     0    78     1    20\n -1.2483110381506159E+00 a      1946     0    78     1    21\n -2.4451774558367654E+00 a      1947     0    78     1    22\n  3.4760189355277031E+00 a      1948     0    78     1    23\n  1.1324166100771771E+00 a      1949     0    78     1    24\n -3.7046827899093575E+00 a      1950     0    78     1    25\n  1.1699373183102337E+00 a      1951     0    79     1     1\n -3.4999560873525444E+00 a      1952     0    79     1     2\n -1.7390351072645140E+00 a      1953     0    79     1     3\n -1.9014825030221971E-01 a      1954     0    79     1     4\n  5.7650358587736328E-01 a      1955     0    79     1     5\n  2.0486641790637656E+00 a      1956     0    79     1     6\n -6.7958823453819983E-01 a      1957     0    79     1     7\n -2.8352920291014367E+00 a      1958     0    79     1     8\n  6.2981550936933450E-01 a      1959     0    79     1     9\n  1.1311526832523301E-01 a      1960     0    79     1    10\n -9.2556436631323447E-01 a      1961     0    79     1    11\n -4.5465118998353055E-01 a      1962     0    79     1    12\n -6.1742009139705756E-01 a      1963     0    79     1    13\n -3.1558668533585182E-01 a      1964     0    79     1    14\n  1.5544933740445883E+00 a      1965     0    79     1    15\n  1.2195499538184944E+00 a      1966     0    79     1    16\n  1.0787882024646700E+00 a      1967     0    79     1    17\n -3.3423787173372475E+00 a      1968     0    79     1    18\n  1.0208155259915410E+00 a      1969     0    79     1    19\n -1.8410958503935839E+00 a      1970     0    79     1    20\n -6.2746945231714091E-02 a      1971     0    79     1    21\n  5.3657939685807921E-01 a      1972     0    79     1    22\n  1.4300315820270415E+00 a      1973     0    79     1    23\n -3.7167617689817329E+00 a      1974     0    79     1    24\n -2.1429838428281855E+00 a      1975     0    79     1    25\n -1.2519762109713295E+00 a      1976     0    80     1     1\n  3.8729630184505159E-01 a      1977     0    80     1     2\n -1.8540880807827131E+00 a      1978     0    80     1     3\n -1.0123771318006507E+00 a      1979     0    80     1     4\n  4.9051784541708415E-02 a      1980     0    80     1     5\n -2.1307958330985479E+00 a      1981     0    80     1     6\n -3.5404974064714909E+00 a      1982     0    80     1     7\n  4.6106294456257899E+00 a      1983     0    80     1     8\n  1.4912768372807195E+00 a      1984     0    80     1     9\n  1.2802186526512287E+00 a      1985     0    80     1    10\n  6.4400545081208960E-01 a      1986     0    80     1    11\n  8.6631813625829068E-01 a      1987     0    80     1    12\n -4.1630204884292521E+00 a      1988     0    80     1    13\n  2.1063988437892589E+00 a      1989     0    80     1    14\n  4.0221327543926511E-01 a      1990     0    80     1    15\n  3.1015234889214921E-01 a      1991     0    80     1    16\n -2.0531955145315597E-01 a      1992     0    80     1    17\n -8.1858473501889906E-01 a      1993     0    80     1    18\n -8.0673716084881453E-01 a      1994     0    80     1    19\n -2.9576699686446806E-01 a      1995     0    80     1    20\n -1.7846332340852669E+00 a      1996     0    80     1    21\n  1.2099267750449125E+00 a      1997     0    80     1    22\n -8.0919743489400897E-01 a      1998     0    80     1    23\n  1.9049130779274256E-01 a      1999     0    80     1    24\n -9.0793975500887525E-01 a      2000     0    80     1    25\n  9.8963745848246865E-01 a      2001     0    81     1     1\n  2.8104679660715388E+00 a      2002     0    81     1     2\n -2.6054790077443801E+00 a      2003     0    81     1     3\n -1.2380577188709692E+00 a      2004     0    81     1     4\n -8.9929834535761907E-02 a      2005     0    81     1     5\n  6.9221895667354294E-01 a      2006     0    81     1     6\n  2.1608042149712410E+00 a      2007     0    81     1     7\n  2.5096979977441908E-01 a      2008     0    81     1     8\n  3.1730849834651051E+00 a      2009     0    81     1     9\n -7.8995284095423723E-01 a      2010     0    81     1    10\n  1.1126035261070453E+00 a      2011     0    81     1    11\n  1.2980698341277914E+00 a      2012     0    81     1    12\n -1.4032327815764938E+00 a      2013     0    81     1    13\n -3.3651065378404259E+00 a      2014     0    81     1    14\n -1.2267849824962915E+00 a      2015     0    81     1    15\n -2.7495438717997014E+00 a      2016     0    81     1    16\n -4.7924992408243228E-01 a      2017     0    81     1    17\n  8.4238072645860451E-01 a      2018     0    81     1    18\n -7.8568904218935232E-01 a      2019     0    81     1    19\n -1.6514634643985704E+00 a      2020     0    81     1    20\n -2.5454090166579846E+00 a      2021     0    81     1    21\n -2.2714608095042113E-01 a      2022     0    81     1    22\n  2.9381831994656129E+00 a      2023     0    81     1    23\n  2.2853762437093326E+00 a      2024     0    81     1    24\n  6.6483118474587855E-01 a      2025     0    81     1    25\n  3.4580309782497265E-01 a      2026     0    82     1     1\n -1.6636632039812640E+00 a      2027     0    82     1     2\n -2.8533769752620226E+00 a      2028     0    82     1     3\n -5.9149651290287686E-01 a      2029     0    82     1     4\n -4.0540275583290991E-01 a      2030     0    82     1     5\n  1.9010946749190749E+00 a      2031     0    82     1     6\n  7.7407306144684662E-02 a      2032     0    82     1     7\n  3.9010624748567930E+00 a      2033     0    82     1     8\n -1.6708679364183534E+00 a      2034     0    82     1     9\n -2.7676035062499371E-01 a      2035     0    82     1    10\n  7.7399167821432446E-01 a      2036     0    82     1    11\n  1.7957063897489960E+00 a      2037     0    82     1    12\n -1.4116110951123451E+00 a      2038     0    82     1    13\n -1.4719226446021707E+00 a      2039     0    82     1    14\n -5.3775393453060769E-03 a      2040     0    82     1    15\n  5.0644231906149972E-01 a      2041     0    82     1    16\n -1.1776936120017458E+00 a      2042     0    82     1    17\n  2.0114783069886752E+00 a      2043     0    82     1    18\n -8.8049187018897690E-01 a      2044     0    82     1    19\n -1.5574861174499643E+00 a      2045     0    82     1    20\n -4.6735711196880274E+00 a      2046     0    82     1    21\n  5.7151629930590691E+00 a      2047     0    82     1    22\n -3.0392760284472042E+00 a      2048     0    82     1    23\n  1.0088048147600619E+00 a      2049     0    82     1    24\n -6.0058245005557098E-01 a      2050     0    82     1    25\n -1.4129606335180411E+00 a      2051     0    83     1     1\n -2.3301200908584696E+00 a      2052     0    83     1     2\n  2.3025967782457131E+00 a      2053     0    83     1     3\n -1.1256867418364545E+00 a      2054     0    83     1     4\n -1.2567771423069003E+00 a      2055     0    83     1     5\n  9.7624692155149551E-01 a      2056     0    83     1     6\n  3.1512825691726691E+00 a      2057     0    83     1     7\n  3.4403643865901410E+00 a      2058     0    83     1     8\n  3.4470775987725171E+00 a      2059     0    83     1     9\n  1.0312923991922447E+00 a      2060     0    83     1    10\n -1.1384716373972918E+00 a      2061     0    83     1    11\n -3.4604865167681549E+00 a      2062     0    83     1    12\n  3.2983941553367444E+00 a      2063     0    83     1    13\n -5.2601160301318561E-01 a      2064     0    83     1    14\n  2.4779949688240781E+00 a      2065     0    83     1    15\n  4.6975829572898702E+00 a      2066     0    83     1    16\n -9.0176618086769467E-01 a      2067     0    83     1    17\n -1.8370204749211532E+00 a      2068     0    83     1    18\n -3.2701524271182052E+00 a      2069     0    83     1    19\n  2.0765788783194125E-01 a      2070     0    83     1    20\n  9.5711301178162317E-02 a      2071     0    83     1    21\n  2.5478903218124289E+00 a      2072     0    83     1    22\n -3.0133129094716313E+00 a      2073     0    83     1    23\n  9.3011985919731177E-01 a      2074     0    83     1    24\n  3.9604751874423534E+00 a      2075     0    83     1    25\n  2.8411853280969890E+00 a      2076     0    84     1     1\n  5.0273463665643914E-01 a      2077     0    84     1     2\n  2.2035261374112985E-01 a      2078     0    84     1     3\n  2.0156240764669140E+00 a      2079     0    84     1     4\n  4.1475081428715193E+00 a      2080     0    84     1     5\n  2.1556487762674350E+00 a      2081     0    84     1     6\n  6.2312917756599315E+00 a      2082     0    84     1     7\n -1.3392921201738335E+00 a      2083     0    84     1     8\n -2.8523130808420272E-01 a      2084     0    84     1     9\n  2.3329551247683065E+00 a      2085     0    84     1    10\n  3.7537528298794820E+00 a      2086     0    84     1    11\n  1.7837707693054017E+00 a      2087     0    84     1    12\n  1.3684487458348522E+00 a      2088     0    84     1    13\n  1.9431711446093884E+00 a      2089     0    84     1    14\n -5.3156670418548879E-01 a      2090     0    84     1    15\n -1.4536229184270499E+00 a      2091     0    84     1    16\n  5.3662653143135744E-02 a      2092     0    84     1    17\n  5.8081828243849620E-01 a      2093     0    84     1    18\n  1.4646786630828024E+00 a      2094     0    84     1    19\n -1.3363179633208813E+00 a      2095     0    84     1    20\n -5.6026357121489057E-01 a      2096     0    84     1    21\n  7.3848454338698821E-01 a      2097     0    84     1    22\n -1.2920055778703279E+00 a      2098     0    84     1    23\n  1.8873800747307370E+00 a      2099     0    84     1    24\n -4.2409929140803886E+00 a      2100     0    84     1    25\n -7.1505124959921940E-01 a      2101     0    85     1     1\n  9.6784383027406917E-01 a      2102     0    85     1     2\n  2.8007659467429702E-01 a      2103     0    85     1     3\n -6.9208309673234469E-01 a      2104     0    85     1     4\n -9.2380783441488867E-01 a      2105     0    85     1     5\n  1.0023159361464298E+00 a      2106     0    85     1     6\n  2.9670265572246851E-01 a      2107     0    85     1     7\n -8.8810942686575967E-01 a      2108     0    85     1     8\n -1.7014197875604595E+00 a      2109     0    85     1     9\n -3.6018130748246611E+00 a      2110     0    85     1    10\n  2.9651286565045361E+00 a      2111     0    85     1    11\n  4.4757353261205060E+00 a      2112     0    85     1    12\n  3.9020327185644005E-01 a      2113     0    85     1    13\n -5.1514191772100004E-01 a      2114     0    85     1    14\n  1.5898342921159506E-01 a      2115     0    85     1    15\n -2.8105429197212561E-01 a      2116     0    85     1    16\n  2.9824164584254373E+00 a      2117     0    85     1    17\n  7.9786950806819157E-01 a      2118     0    85     1    18\n  2.1979111636896290E-01 a      2119     0    85     1    19\n -2.9006550501959077E-01 a      2120     0    85     1    20\n -1.3298976020282940E+00 a      2121     0    85     1    21\n  1.9465186247481499E+00 a      2122     0    85     1    22\n  2.1220863316223597E+00 a      2123     0    85     1    23\n  3.3517647843148451E-01 a      2124     0    85     1    24\n  2.6807153716205151E-01 a      2125     0    85     1    25\n -2.6521357816115776E+00 a      2126     0    86     1     1\n  2.0611889401163226E+00 a      2127     0    86     1     2\n  2.0441483563792979E+00 a      2128     0    86     1     3\n -8.9437297819651418E-01 a      2129     0    86     1     4\n -2.4171924838075137E-01 a      2130     0    86     1     5\n -1.4289724372162758E+00 a      2131     0    86     1     6\n -7.5741278098496023E-01 a      2132     0    86     1     7\n  1.4295202066372050E+00 a      2133     0    86     1     8\n -2.6910235940166696E+00 a      2134     0    86     1     9\n -2.3598091945491380E+00 a      2135     0    86     1    10\n -4.3137581168416361E-01 a      2136     0    86     1    11\n  1.8481935739748611E-02 a      2137     0    86     1    12\n -1.9427976327121557E-01 a      2138     0    86     1    13\n  1.1846748160820451E+00 a      2139     0    86     1    14\n  3.9655077152763507E-01 a      2140     0    86     1    15\n  1.6336726766660348E+00 a      2141     0    86     1    16\n  1.1789111624737423E+00 a      2142     0    86     1    17\n  8.3965705138934588E-01 a      2143     0    86     1    18\n  1.1192330802581236E+00 a      2144     0    86     1    19\n  1.2087283642350153E+00 a      2145     0    86     1    20\n  1.4346753713148717E+00 a      2146     0    86     1    21\n  1.3204441487669138E+00 a      2147     0    86     1    22\n  5.1143133061864499E-01 a      2148     0    86     1    23\n -2.1721082405339806E-02 a      2149     0    86     1    24\n -3.5488330386313349E-01 a      2150     0    86     1    25\n  1.7775026745981628E+00 a      2151     0    87     1     1\n  9.4737384706948380E-01 a      2152     0    87     1     2\n  2.1936540431661764E+00 a      2153     0    87     1     3\n  2.4111833263225106E+00 a      2154     0    87     1     4\n  1.4403174726340995E-01 a      2155     0    87     1     5\n -3.3871270209548752E+00 a      2156     0    87     1     6\n  4.0713191577747274E+00 a      2157     0    87     1     7\n -1.6895043401279199E+00 a      2158     0    87     1     8\n -8.8532784776786755E-01 a      2159     0    87     1     9\n -3.5941705422798931E+00 a      2160     0    87     1    10\n  4.3580379730801138E+00 a      2161     0    87     1    11\n -2.4357414008432148E+00 a      2162     0    87     1    12\n  2.8866570553394704E+00 a      2163     0    87     1    13\n  3.9628703370211338E+00 a      2164     0    87     1    14\n -1.0298514567031141E+00 a      2165     0    87     1    15\n -1.8112724692644218E+00 a      2166     0    87     1    16\n -4.0989560502588834E-01 a      2167     0    87     1    17\n  6.4079561308084765E-01 a      2168     0    87     1    18\n -6.8136885379239329E-02 a      2169     0    87     1    19\n -9.9565494627090101E-01 a      2170     0    87     1    20\n  3.6949310057914588E+00 a      2171     0    87     1    21\n  7.8343270700304490E-01 a      2172     0    87     1    22\n  3.7452731766573906E+00 a      2173     0    87     1    23\n  1.5564428181259020E+00 a      2174     0    87     1    24\n  1.3555942151329516E+00 a      2175     0    87     1    25\n  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  },
  {
    "path": "examples/nnp-predict/Ethylbenzene_SCAN/input.data",
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  },
  {
    "path": "examples/nnp-predict/Ethylbenzene_SCAN/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.8547021561081563E+00\nconv_energy   6.2674740310100970E+03\nconv_length   9.4927514173056764E+01\n###############################################################################\n\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        C H          # Specification of elements.\ncutoff_type                     6 0.0          # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\nrandom_seed 987654321\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\njacobian_mode                   1\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntask_batch_size_energy          1\ntask_batch_size_force           1\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints                5             # Write energy comparison.\nwrite_trainforces                5             # Write force comparison.\nwrite_weights_epoch              5             # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n## ####################\n## # GRADIENT DESCENT #\n## ####################\n## gradient_type                   0              # Gradient descent type (0 = Fixed step size).\n## gradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\nsymfunction_short C 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 C -1.40E+01 1.40E+01 p2a\nsymfunction_short C 20 C -1.20E+01 1.20E+01 p2a\nsymfunction_short C 20 C -1.00E+01 1.00E+01 p2a\nsymfunction_short C 20 C -8.00E+00 8.00E+00 p2a\nsymfunction_short C 20 C -6.00E+00 6.00E+00 p2a\nsymfunction_short C 20 C -5.00E+00 5.00E+00 p2a\nsymfunction_short C 20 C -2.50E+00 7.50E+00 p2a\nsymfunction_short C 20 C 0.00E+00 1.00E+01 p2a\nsymfunction_short C 20 C 2.50E+00 1.25E+01 p2a\nsymfunction_short C 20 C 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short C 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 H -1.40E+01 1.40E+01 p2a\nsymfunction_short C 20 H -1.20E+01 1.20E+01 p2a\nsymfunction_short C 20 H -1.00E+01 1.00E+01 p2a\nsymfunction_short C 20 H -8.00E+00 8.00E+00 p2a\nsymfunction_short C 20 H -6.00E+00 6.00E+00 p2a\nsymfunction_short C 20 H -5.00E+00 5.00E+00 p2a\nsymfunction_short C 20 H -2.50E+00 7.50E+00 p2a\nsymfunction_short C 20 H 0.00E+00 1.00E+01 p2a\nsymfunction_short C 20 H 2.50E+00 1.25E+01 p2a\nsymfunction_short C 20 H 5.00E+00 1.50E+01 p2a\n \n \n \n \n \n \nsymfunction_short H 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 C -1.40E+01 1.40E+01 p2a\nsymfunction_short H 20 C -1.20E+01 1.20E+01 p2a\nsymfunction_short H 20 C -1.00E+01 1.00E+01 p2a\nsymfunction_short H 20 C -8.00E+00 8.00E+00 p2a\nsymfunction_short H 20 C -6.00E+00 6.00E+00 p2a\nsymfunction_short H 20 C -5.00E+00 5.00E+00 p2a\nsymfunction_short H 20 C -2.50E+00 7.50E+00 p2a\nsymfunction_short H 20 C 0.00E+00 1.00E+01 p2a\nsymfunction_short H 20 C 2.50E+00 1.25E+01 p2a\nsymfunction_short H 20 C 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short H 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 H -1.40E+01 1.40E+01 p2a\nsymfunction_short H 20 H -1.20E+01 1.20E+01 p2a\nsymfunction_short H 20 H -1.00E+01 1.00E+01 p2a\nsymfunction_short H 20 H -8.00E+00 8.00E+00 p2a\nsymfunction_short H 20 H -6.00E+00 6.00E+00 p2a\nsymfunction_short H 20 H -5.00E+00 5.00E+00 p2a\nsymfunction_short H 20 H -2.50E+00 7.50E+00 p2a\nsymfunction_short H 20 H 0.00E+00 1.00E+01 p2a\nsymfunction_short H 20 H 2.50E+00 1.25E+01 p2a\nsymfunction_short H 20 H 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short C 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short C 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \n \n \nsymfunction_short C 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \n \n \n \n \n \n \n \n \n \n \nsymfunction_short H 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short H 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \n \n \nsymfunction_short H 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \n"
  },
  {
    "path": "examples/nnp-predict/Ethylbenzene_SCAN/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.2546559757006401E+01   2.2343237809189908E+01   1.7734001143187928E+01   1.5596535256693718E+00\n         1          2   8.4533975944444197E+00   2.1378779062642725E+01   1.4885243204618567E+01   1.5871257822529075E+00\n         1          3   7.9657391793830357E-12   1.0513500116637253E-01   1.1261160053477924E-02   1.2038805389511614E-02\n         1          4   3.2997737249129688E-04   3.1113020951761805E-01   6.0626282023127649E-02   5.4291529654562604E-02\n         1          5   1.5720242124501316E-01   4.7256846191877742E+00   1.5556007191186063E+00   8.1649964464959968E-01\n         1          6   3.5752850090918997E-02   1.1592433021208004E+00   3.7312762322190912E-01   2.1349296622080433E-01\n         1          7   2.6206282443333084E-01   2.4378489559361651E+00   1.0449960051979448E+00   4.0805586442113517E-01\n         1          8   2.5821153643652530E+00   1.2794766759988073E+01   7.5130296376665928E+00   1.4891343054266262E+00\n         1          9   6.9778339100918063E-01   3.9769851182683120E+00   2.1015392604699823E+00   6.0101308833116851E-01\n         1         10   8.5324837037667152E+00   2.3546437703374927E+01   1.5918683552428156E+01   2.2759350502150575E+00\n         1         11   1.5119723535932765E+00   5.9038933591739546E+00   3.5934926372302365E+00   7.7524836078321291E-01\n         1         12   1.6580918248956802E+01   4.0274494709533137E+01   2.8547335650502522E+01   2.9444637993862446E+00\n         1         13   1.5221829849547830E-01   2.9838454964920813E-01   2.2872753891630551E-01   1.7508427448017064E-02\n         1         14   2.8906994167262723E-01   4.7884690846049305E-01   3.8897782076968046E-01   2.2160473442697660E-02\n         1         15   1.2372708366562235E+00   3.9050979054798409E+00   1.8736489455075844E+00   2.9250480103403287E-01\n         1         16   5.9435951834012546E-01   1.2554307977700960E+00   7.9127552044115068E-01   6.8871393296862454E-02\n         1         17   9.0641050046735971E-01   2.6629626722354978E+00   1.3745239054093017E+00   1.9158056413794630E-01\n         1         18   1.4518879387119599E+00   1.4304905990949930E+01   5.6516688787416589E+00   1.6455028258248543E+00\n         1         19   1.3082280042611956E+00   4.5267890533831912E+00   2.2297170718049215E+00   3.6884535265454182E-01\n         1         20   5.0222131059497048E+00   2.4997839839437475E+01   1.3374858966201369E+01   2.6607953227781573E+00\n         1         21   1.8771357878995758E+00   6.5988113977254068E+00   3.4362059203438395E+00   5.6597320336964529E-01\n         1         22   7.0153315416294948E+00   3.7193435117007851E+01   2.2751999873847460E+01   3.8708970076340701E+00\n         1         23   1.0466011331190366E+01   3.5920230473543590E+01   2.3123927695433384E+01   3.9744229289012516E+00\n         1         24   3.1407729274565483E+01   1.0401738843325803E+02   6.6105737514679220E+01   1.1722348997880802E+01\n         1         25   5.1953808005467771E+01   1.6792456174664284E+02   1.0568808481727804E+02   1.8738756250124165E+01\n         1         26   3.6631405125687685E+01   1.1595656018025753E+02   7.2461531813491845E+01   1.2897889522962057E+01\n         1         27   3.3368267044783970E+01   1.0752473124808681E+02   6.6428912601389229E+01   1.1798125884415610E+01\n         1         28   1.2739493368476229E+01   4.0384642180645791E+01   2.5361590401427087E+01   4.5573289045654350E+00\n         1         29   2.5373693987483545E+01   6.9415090420987568E+01   4.3712011981856847E+01   6.2170040677462817E+00\n         1         30   5.2707593124605211E+01   1.8922530072300341E+02   1.1262852164121868E+02   1.8663230872909676E+01\n         1         31   7.8477865443126134E+01   3.0064453633619149E+02   1.7885807885739868E+02   2.9661861098635576E+01\n         1         32   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2.7576163061603197E+01   2.1564911647937311E+02   1.0509959479946249E+02   2.3195878466047024E+01\n         1        137   4.5655214708306935E-04   1.0497199613149117E-02   4.0238907069097725E-03   1.7361040614934269E-03\n         1        138   3.8253942946254776E-04   1.8681462878789627E-02   4.6023957976248156E-03   1.9840636301389656E-03\n         1        139   1.6766796315220145E-04   1.3842814029604213E-02   2.4125032793031746E-03   1.2022401720029332E-03\n         1        140  -4.6441097676199194E-16   9.0093640481115206E-03   1.4187754576004880E-04   4.0089063673459571E-04\n         1        141  -5.8327890528959447E-16   9.8306723832768377E-03   1.4970215131859577E-04   5.1987950687165760E-04\n         1        142  -4.0070117581484566E-16   2.0312556557895059E-02   1.1611439909679991E-04   5.5854342305950008E-04\n         1        143   1.9728612614413617E-02   1.1809140135903519E-01   6.5492438568020381E-02   2.3588306355076871E-02\n         1        144   1.7558727664990479E-02   2.2096391355234332E-01   8.4239787657303486E-02   2.9040789028782366E-02\n         1        145   9.6677676986976664E-03   2.9666191476308712E-01   5.7528121310560190E-02   2.5910730834023229E-02\n         1        146   1.1598805333232927E-07   2.1740786315523450E-01   1.4989244184272523E-02   1.6684457988440742E-02\n         1        147   8.6948487907996964E-08   2.3783447732788712E-01   1.3802653248513328E-02   1.8905675375065194E-02\n         1        148  -6.1682400176145661E-17   2.2383731619675554E-01   7.2201031068754740E-03   1.5060778731785322E-02\n         1        149   8.3695608151578504E-02   5.4210963633104847E-01   2.4434919399205207E-01   8.4228598874693333E-02\n         1        150   8.0272711798478447E-02   1.1707207183262294E+00   3.5199508525221868E-01   1.1839828045347257E-01\n         1        151   5.2642620224437900E-02   1.8978816142985209E+00   3.2910600021800857E-01   1.5150171819592734E-01\n         1        152   1.4926908288559926E-03   1.3520012399668215E+00   1.5101489599993984E-01   1.1546402993548585E-01\n         1        153   8.2380203749053758E-04   1.3285844235625062E+00   1.4057376160559620E-01   1.2339997290207937E-01\n         1        154   7.9577718651318891E-06   7.8014303016822961E-01   6.3752169597091526E-02   8.3467101142772157E-02\n         1        155   3.0991348875259678E-01   1.6060310320128451E+01   3.2520062681561059E+00   1.7736769690675145E+00\n         1        156   1.0950721707393307E-01   3.5428257048362582E+01   5.9069145745765148E+00   3.7865400920395573E+00\n         1        157   2.2194519998071627E-01   6.3030954964358415E+01   9.5841653354003284E+00   6.3241185459500180E+00\n         1        158   8.4692074756437405E-02   4.8420017540232273E+01   6.8015221967900947E+00   4.7608853224495302E+00\n         1        159   4.5878103526638833E-02   4.6249824100705112E+01   6.4116116380945423E+00   4.5659643847716360E+00\n         1        160   1.8768677406752028E-03   1.7409543159487839E+01   2.5338750243379593E+00   2.0551077290994968E+00\n         1        161   2.1098668855046537E-01   1.5171133688454141E+00   6.1897392760894332E-01   2.0945550588467904E-01\n         1        162   2.0495215327061578E-01   3.6711400558325704E+00   9.6812626549042646E-01   3.2791822226274536E-01\n         1        163   1.6612723766458456E-01   6.1405317769564967E+00   1.1586848699470682E+00   5.0889898759817009E-01\n         1        164   4.4741376100373868E-02   4.3983414728262993E+00   6.7715886867904485E-01   3.9866745137742698E-01\n         1        165   2.2693100754651755E-02   4.1363559280970135E+00   6.3444823651843074E-01   4.0698245521697540E-01\n         1        166   1.6603775956097327E-03   1.9245790728670908E+00   2.6944428144147459E-01   2.4302429439380327E-01\n         1        167   2.7332861680161717E+00   5.0896256962233331E+01   1.5147122699982654E+01   5.8628462970765085E+00\n         1        168   3.7886350444597068E+00   1.1734871916065721E+02   3.4345754450118861E+01   1.4595983735849568E+01\n         1        169   6.6046698868307603E+00   1.9947841636931801E+02   5.8240354061401895E+01   2.4477614231341263E+01\n         1        170   3.8914233089639390E+00   1.4431792553104302E+02   4.1621292209114685E+01   1.7777996637655356E+01\n         1        171   2.7018548415703805E+00   1.3587262880412180E+02   3.8416552492075752E+01   1.6270838644674612E+01\n         1        172   5.2372735138685278E-01   5.3918208091843574E+01   1.4664785399595678E+01   6.2186903657576122E+00\n         1        173   4.5877854702900894E-01   3.3549331057236649E+00   1.3310157711292494E+00   4.1564650392545216E-01\n         1        174   4.7696160169867141E-01   8.0901564907280665E+00   2.2832124287103612E+00   7.5181089020743275E-01\n         1        175   5.9823346357564844E-01   1.3647930676682734E+01   3.1923637690886180E+00   1.2498397126060981E+00\n         1        176   2.7334936636448992E-01   9.7912841348947595E+00   2.0736374345878046E+00   9.7174675873031324E-01\n         1        177   1.9713196483401321E-01   9.0580557428434698E+00   1.9406343352692832E+00   9.5734757552102723E-01\n         1        178   2.0849431259173590E-02   3.9074914478902456E+00   7.9380386690542104E-01   5.1450227679090677E-01\n         1        179   4.1658709074439422E+00   1.0314113975657527E+02   4.1870816671991676E+01   1.3343380563596151E+01\n         1        180   8.5655829127939640E+00   2.9029900497660361E+02   1.0719491225996300E+02   3.7280360147391207E+01\n         1        181   1.3923969009544516E+01   4.6712207142172917E+02   1.7451027569855944E+02   5.9971382453327621E+01\n         1        182   9.3578098551949083E+00   3.2100999642058457E+02   1.2054865315632786E+02   4.1449875854972809E+01\n         1        183   9.4662158704897070E+00   2.9108110726903089E+02   1.0999850509775632E+02   3.7892882585534082E+01\n         1        184   4.8167325246627959E+00   1.1002907165391024E+02   4.1577202220509250E+01   1.4860960635764441E+01\n         2          1   1.3776363591373302E+01   2.2957951972848651E+01   1.8606554005773212E+01   1.5073318700135985E+00\n         2          2   8.7199990012375146E+00   2.0454273577725090E+01   1.4022355297269060E+01   1.4746846180685842E+00\n         2          3   6.4814111526789731E-04   8.1213506707982974E-01   2.8590942364538185E-01   1.8651064349546770E-01\n         2          4   2.5059956987351750E-02   1.2667159798183374E+00   4.8622227596210038E-01   3.0236780811406250E-01\n         2          5   1.3470935864030293E+00   4.6296472882944428E+00   2.3420611818844792E+00   8.2275752986446493E-01\n         2          6   3.3422186968815737E-01   2.1786967394313095E+00   9.8909440055143860E-01   4.7679670377394512E-01\n         2          7   1.0576441794647604E+00   3.3869792746896885E+00   1.7181548817616268E+00   5.9905248168628600E-01\n         2          8   2.6878421392017882E+00   1.2692697538027918E+01   7.0645860984270739E+00   1.5787360497153005E+00\n         2          9   1.8203218195793918E+00   4.9717324173758648E+00   2.7871463397561520E+00   6.9347371462237362E-01\n         2         10   8.7475704232050866E+00   2.5173360646478670E+01   1.6718573707751705E+01   2.4840986758238208E+00\n         2         11   2.7382618384943500E+00   6.9453447160046098E+00   4.2952574004297990E+00   7.8111920208212704E-01\n         2         12   1.8851144037212421E+01   3.9011067373622524E+01   2.8439999842309334E+01   2.8973610223390494E+00\n         2         13   2.1938704604525072E-02   2.4278596181240208E-01   1.3966656398260360E-01   4.7743689190339902E-02\n         2         14   8.2453786654100192E-02   5.6813570538856517E-01   3.4226650459011293E-01   1.0383952107048113E-01\n         2         15   9.7738620935843368E-01   3.9576248397183154E+00   2.5040397514391461E+00   6.4045850733191390E-01\n         2         16   2.8758294162978215E-01   1.4088012487930615E+00   8.8731969282744738E-01   2.4352444127974410E-01\n         2         17   5.7309158143535921E-01   2.5570553746833258E+00   1.5740797410192757E+00   3.9814294951135115E-01\n         2         18   1.9196879204445652E+00   1.3516067305596030E+01   4.8492264697717165E+00   1.2284755250693586E+00\n         2         19   9.3819918019549753E-01   4.0321505810489775E+00   2.4224123294478863E+00   5.3249268478067002E-01\n         2         20   2.7189036470485117E+00   2.5764632658647479E+01   1.1363393780854373E+01   3.1435260622044825E+00\n         2         21   1.5272520603339936E+00   6.1065438911067842E+00   3.5214170867706738E+00   6.4225879456699486E-01\n         2         22   1.0536246615404965E+01   3.4812337399220780E+01   2.2784150253713509E+01   3.6647639767937608E+00\n         2         23   1.2985440522266781E+01   3.8374012290107089E+01   2.5288549463799669E+01   4.0687725377970283E+00\n         2         24   3.8903748971999491E+01   1.1099309074081349E+02   7.2623233195889412E+01   1.2041651588081979E+01\n         2         25   6.2500060925543018E+01   1.7759035930318592E+02   1.1638170889738701E+02   1.9277833770631165E+01\n         2         26   4.2888959474698424E+01   1.2257577626993633E+02   8.0042470615650984E+01   1.3275308071500660E+01\n         2         27   3.9506077892099192E+01   1.1212113281750891E+02   7.3172707144088449E+01   1.2106000881404475E+01\n         2         28   1.5793062344615720E+01   4.2971666278141029E+01   2.7893101020471658E+01   4.3702736918234084E+00\n         2         29   2.4802673249924243E+01   6.9017933881112768E+01   4.3389312830921035E+01   5.9495629405692609E+00\n         2         30   5.9618367367357486E+01   1.8443557117191736E+02   1.0871019873537360E+02   1.7910093269006353E+01\n         2         31   9.6575915089425990E+01   2.9719406014649456E+02   1.7551161719348224E+02   2.8196436429474836E+01\n         2         32   6.5473848476456752E+01   2.0584211888267521E+02   1.2123004518753439E+02   1.9222780522792540E+01\n         2         33   5.8982987051376384E+01   1.8992722621955798E+02   1.1142245394148748E+02   1.7399153370562129E+01\n         2         34   2.0605581937033215E+01   7.4209573187776883E+01   4.2817295904223712E+01   6.4911336102606061E+00\n         2         35   7.4456208890198781E+00   3.1906049388983991E+01   1.5563708404776683E+01   3.0388966016741130E+00\n         2         36   1.3812051897570651E+01   8.7424746821207094E+01   3.9435770596362822E+01   8.6976616818069363E+00\n         2         37   2.3453616215882981E+01   1.3834065405260489E+02   6.4996967466943119E+01   1.4497361586952412E+01\n         2         38   1.6838046182766828E+01   9.4686112773616316E+01   4.5511126916323065E+01   1.0554164051726149E+01\n         2         39   1.5270218684494301E+01   8.6019931901723126E+01   4.1524240495394437E+01   9.6207851983673027E+00\n         2         40   3.7653429920482191E+00   3.2997631116746184E+01   1.5272747297903418E+01   3.6428308941773397E+00\n         2         41  -2.0800952413783606E-16   2.9783467238342172E-03   8.6047052876964117E-05   1.7504994945839993E-04\n         2         42   9.2362942243410839E-05   9.5375046073687950E-02   8.4595739891389216E-03   1.2689979040796287E-02\n         2         43   1.4156944817621988E-04   4.9342300512255999E-01   7.2206254631782096E-02   1.3299354745310160E-01\n         2         44   8.3590548533974391E-05   5.3092175879535841E-01   7.4877946187766400E-02   1.4034038090021839E-01\n         2         45   7.5552134521690293E-05   5.1515723573033345E-01   6.8442671402915822E-02   1.3089060818694798E-01\n         2         46   0.0000000000000000E+00   6.4144708898461703E-02   4.9436206852273516E-03   1.0154308868373882E-02\n         2         47   1.4854099217966100E-05   6.1891989609639875E-02   8.4765092465489428E-03   8.3545162372741216E-03\n         2         48   1.3377824499372810E-02   4.4208760871679770E-01   8.7337893231215935E-02   6.6740831898821032E-02\n         2         49   2.8694583683801286E-02   1.5654365689397023E+00   3.2701527205384123E-01   4.1874818207502423E-01\n         2         50   1.7537273691342860E-02   1.5223378355083639E+00   3.0762936598079910E-01   4.2782455848808010E-01\n         2         51   1.5088319624021764E-02   1.4187167620570111E+00   2.7088803612965551E-01   4.0313134067579370E-01\n         2         52   5.8767973226431865E-04   2.4590915357590398E-01   3.5837588159585924E-02   4.9938185080239138E-02\n         2         53   3.2890211803067765E-03   3.5922289785658601E-01   7.8006264071889680E-02   5.5812221516648684E-02\n         2         54   9.8445057311949288E-02   1.5765263516542394E+00   4.2388573038514571E-01   2.4101985580778179E-01\n         2         55   2.5460515478681611E-01   3.8043361709366872E+00   1.0059336958797560E+00   8.6412903684893982E-01\n         2         56   1.9086933513449286E-01   3.2824189130985082E+00   8.3711809858829589E-01   8.2539366213035437E-01\n         2         57   1.3143884802675210E-01   3.0670111185000741E+00   7.2963128585573356E-01   7.8538854888319598E-01\n         2         58   3.4700789601495918E-02   7.3515802519785289E-01   1.6425977617278434E-01   1.3974695264052150E-01\n         2         59   3.7377796397893398E-01   9.2379553617057173E+00   2.9756886218548342E+00   1.4249861408764428E+00\n         2         60   1.2123099317454138E+00   3.3841363869788943E+01   1.0513008251336796E+01   4.9758240569983840E+00\n         2         61   1.7184623163577115E+00   5.3905134558728676E+01   1.6600840725833685E+01   7.7390649061672496E+00\n         2         62   1.1128939908099134E+00   3.6813730092768317E+01   1.1281878838968936E+01   5.2401517605507717E+00\n         2         63   1.0516915858050273E+00   3.2955289994218880E+01   1.0323906971470020E+01   4.7356552149701976E+00\n         2         64   5.3544541987168459E-01   1.2739587768489036E+01   4.1807757158013583E+00   1.7749578413961338E+00\n         2         65   4.2707247611989130E-02   1.0590721683720392E+00   3.3455245860743160E-01   1.7123423289240797E-01\n         2         66   3.5082973159644787E-01   4.1534680530596111E+00   1.3702422227098261E+00   6.0694836308784539E-01\n         2         67   8.7224764024501367E-01   8.3025130654234154E+00   2.6212650824198569E+00   1.5088064146196265E+00\n         2         68   6.1832207058833433E-01   6.3346372632766119E+00   1.9913552085863533E+00   1.3232799013388454E+00\n         2         69   5.0808746451269016E-01   5.8706203341426404E+00   1.7576701800087593E+00   1.2616960218012157E+00\n         2         70   2.3381764005597483E-01   1.7998107581680003E+00   5.3529525212717122E-01   2.7733529889238734E-01\n         2         71   4.8471321473736078E+00   4.4651897236891372E+01   1.9728055590722011E+01   5.9051897436620111E+00\n         2         72   1.4338569841046743E+01   1.3577974538230833E+02   5.9305312028115658E+01   1.7729217936081078E+01\n         2         73   2.5092175017592307E+01   2.1200359331886986E+02   9.4433246862732020E+01   2.7977584883020835E+01\n         2         74   1.8197893344543903E+01   1.4303827055879447E+02   6.4652918383034830E+01   1.9157517744434319E+01\n         2         75   1.6824995700405168E+01   1.3089165287629916E+02   5.9126852958279692E+01   1.7501776574132972E+01\n         2         76   5.6645849798224850E+00   5.0322748250689152E+01   2.2515595594225768E+01   6.7109304259830722E+00\n         2         77   2.3157469860024391E-01   2.5763181571942937E+00   1.0133756261850342E+00   3.7733256170682322E-01\n         2         78   1.0495359920129748E+00   8.9558307045087240E+00   3.5642278529303439E+00   1.2330623460930439E+00\n         2         79   2.1902201930704019E+00   1.6147363575960142E+01   6.1878848389164514E+00   2.4661300297146354E+00\n         2         80   1.6245497067506340E+00   1.1654335261310516E+01   4.4675196088161160E+00   1.9830693767990843E+00\n         2         81   1.3829442373224961E+00   1.0843027113070345E+01   4.0008461987199651E+00   1.8776603882077787E+00\n         2         82   6.4969878964138073E-01   3.7653419890324229E+00   1.3950056495229592E+00   4.8214978823104671E-01\n         2         83   2.5477934878676898E+01   1.1125290943670808E+02   6.0286552443623762E+01   1.2469629332334007E+01\n         2         84   7.3495535373271991E+01   3.1795727335908953E+02   1.7048363167330717E+02   3.5155467087667184E+01\n         2         85   1.1894965248416000E+02   5.1090686209467026E+02   2.7261259740474759E+02   5.6142269402976709E+01\n         2         86   8.0418668416325943E+01   3.5079811030509387E+02   1.8698900652479787E+02   3.8631419217085146E+01\n         2         87   7.2350287681903552E+01   3.2281587741926535E+02   1.7153812918881835E+02   3.5505300852010421E+01\n         2         88   2.5787725278712198E+01   1.2412317282454136E+02   6.5264680716321706E+01   1.3640785164101242E+01\n         2         89   5.2341035619083733E-04   8.8967640360901479E-03   2.8205313053402928E-03   1.3196552646362633E-03\n         2         90   2.7187703591868303E-04   3.6553280679833940E-02   4.1677799285378594E-03   4.4164048960438941E-03\n         2         91   5.0880015289545511E-03   2.2761283969577040E-01   1.0865510496573706E-01   4.3679199554560261E-02\n         2         92   4.2402439089947236E-03   2.4244184316279138E-01   1.2464346185249230E-01   4.8341452093109451E-02\n         2         93   4.7478809271539668E-03   2.3407790513972329E-01   1.2783705920455568E-01   4.7539688319504718E-02\n         2         94   2.4787974848261376E-03   4.9580895027098906E-02   2.4082866262788744E-02   1.1135660333080595E-02\n         2         95   2.5654050858959568E-02   1.6822857184470494E-01   6.9702831580278374E-02   2.7741393845116053E-02\n         2         96   2.2140931866466040E-02   2.7196778682998091E-01   8.4259207296709396E-02   4.5716757413234908E-02\n         2         97   2.0366880530198120E-01   1.1167725860096198E+00   5.2958585892848742E-01   1.7316732799250439E-01\n         2         98   1.6679852337100293E-01   1.1171594513417007E+00   5.5985613213438523E-01   1.8015605594313813E-01\n         2         99   1.7941533471921048E-01   1.0561238258776573E+00   5.8600056214151774E-01   1.5989411976702117E-01\n         2        100   2.5371138381238934E-02   2.7307525456475151E-01   1.6825135339362496E-01   5.6848316510319193E-02\n         2        101   1.7592581845260452E-01   7.1865274903905041E-01   3.2621725584219446E-01   1.0787968465080154E-01\n         2        102   1.9800851512877610E-01   1.5084242236143335E+00   5.2387856086323958E-01   2.0324810638344695E-01\n         2        103   9.7941648414195071E-01   3.2395281539184757E+00   1.5895662960002834E+00   4.2513107962706959E-01\n         2        104   9.8396910714038455E-01   2.9123883218531383E+00   1.4674048470067600E+00   3.8331769816002542E-01\n         2        105   1.0370877080943639E+00   2.6978769520099628E+00   1.5235353024082325E+00   2.9996278098110785E-01\n         2        106   1.1863209652235732E-01   9.1178931261902563E-01   5.8418752403428320E-01   1.6943033439055766E-01\n         2        107   1.8307424152062497E+00   2.0437917976337584E+01   6.0752728607426150E+00   2.3769972440138178E+00\n         2        108   4.0966689771516895E+00   6.2055800124979356E+01   1.4122478853724635E+01   5.5565586560638263E+00\n         2        109   4.5567449528614041E+00   1.0304260410387892E+02   2.3340653535370439E+01   9.4263869915278331E+00\n         2        110   1.6474340140541335E+00   7.1361001493979913E+01   1.6355694086262439E+01   6.9341722620372588E+00\n         2        111   1.6136778756652950E+00   6.3585920568925772E+01   1.4895460723207105E+01   6.4270980789089815E+00\n         2        112   3.1905601384379806E-01   2.0375770586228541E+01   5.6262630204553021E+00   2.7395671158907700E+00\n         2        113   5.1542385112864264E-01   1.9726700610269656E+00   9.6419872854352928E-01   2.4652131439439007E-01\n         2        114   7.7364039322841360E-01   4.7520409178938063E+00   1.8930544670448473E+00   5.6361111723022039E-01\n         2        115   2.1337507637326540E+00   8.2722107043034256E+00   4.1205893125139816E+00   1.0035896772124882E+00\n         2        116   1.8994552821336530E+00   6.5553092680717624E+00   3.3720727689203200E+00   8.0337971906483041E-01\n         2        117   2.0939144411929331E+00   5.9963101894806723E+00   3.3754750578718622E+00   6.5199844296118381E-01\n         2        118   3.0041211470459456E-01   2.2662831979447589E+00   1.4110287695441504E+00   3.5731595737294441E-01\n         2        119   6.3645295918998119E+00   8.7212967757256152E+01   3.2999251403539361E+01   1.0472571387848804E+01\n         2        120   1.1470464105459323E+01   2.3108019172751102E+02   7.9630918638296791E+01   2.8187908404727580E+01\n         2        121   2.1278468890529783E+01   3.5972769076286005E+02   1.2763304974564760E+02   4.3828684349843144E+01\n         2        122   1.5016319864502123E+01   2.4273095418898779E+02   8.7675054692177014E+01   2.9692307131959524E+01\n         2        123   1.3507978865763311E+01   2.2320662989797964E+02   8.0565386884466008E+01   2.7401351716692588E+01\n         2        124   5.5230004899537359E+00   8.8850729952253431E+01   3.1042037979064560E+01   1.0882449128654935E+01\n         2        125   1.1636119785202896E+00   4.5036402203019765E+00   2.3478796624434710E+00   4.8265993273892083E-01\n         2        126   2.3292981718935204E+00   1.2229027528558655E+01   5.1580281323875408E+00   1.2866312017459265E+00\n         2        127   4.6725406244153413E+00   2.0307004650689692E+01   9.6307942388527348E+00   2.1840849806647440E+00\n         2        128   3.5960466975756584E+00   1.4549561134118768E+01   7.2888067213445797E+00   1.6395125504091692E+00\n         2        129   3.7172419192939641E+00   1.3349831546287628E+01   7.0359035762346691E+00   1.4093840322206532E+00\n         2        130   7.9602109152306455E-01   5.2586961758272857E+00   2.9223324008128762E+00   6.3962019985531415E-01\n         2        131   4.2421478573481984E+01   2.1545181819624941E+02   1.0840530824286394E+02   2.1280742623483889E+01\n         2        132   9.6935173042244656E+01   5.6668783891883800E+02   2.7461268021164659E+02   5.7681929399081511E+01\n         2        133   1.5210882937768412E+02   8.8925741560567019E+02   4.3735048132336811E+02   9.1184415336723418E+01\n         2        134   1.0347513318466906E+02   6.0380074576797506E+02   2.9943882878430333E+02   6.2384768408519868E+01\n         2        135   9.3396073689498138E+01   5.5469398890179070E+02   2.7447701011688076E+02   5.7185345071924651E+01\n         2        136   3.4355694072592165E+01   2.1107653688670561E+02   1.0409634123431266E+02   2.2107043344353411E+01\n         2        137   2.4022363709054806E-07   1.4209115821242895E-03   4.6954629301672541E-04   2.4735563007031688E-04\n         2        138   6.3457185982437510E-08   5.4800912820231777E-03   6.6624277800292591E-04   3.7478772804472120E-04\n         2        139   2.3465461867642480E-08   8.4829701101682142E-02   2.7051666106326658E-02   1.7350673234620057E-02\n         2        140  -8.9797768154659563E-17   1.0092377361332103E-01   3.2037161939427482E-02   2.0673658576894762E-02\n         2        141  -7.9559883822224519E-17   1.0551261015470774E-01   3.3469879976410127E-02   2.1768973148138884E-02\n         2        142  -6.7366611645040197E-17   2.3242839120778132E-02   6.9921256402471878E-03   4.9169809307105456E-03\n         2        143   2.1062911326034371E-03   6.1447473859088206E-02   3.2877146410023129E-02   1.2804152045721986E-02\n         2        144   5.7157434811921156E-04   1.0661056388118885E-01   4.7620217324603080E-02   2.1615833409957323E-02\n         2        145   4.5170916276817753E-04   5.5075659510487152E-01   1.9155508169139884E-01   1.1198950107926528E-01\n         2        146   0.0000000000000000E+00   5.8821435134888034E-01   1.9609497371072843E-01   1.2336481024357500E-01\n         2        147   0.0000000000000000E+00   5.9426956377417672E-01   1.9667701555066086E-01   1.2916424776317159E-01\n         2        148  -7.1981824677217043E-17   1.6083012208762279E-01   4.4099885244901757E-02   3.6123732306916567E-02\n         2        149   3.1183844346484878E-02   3.3165377905314603E-01   1.9041656834773138E-01   6.5697318094721319E-02\n         2        150   1.7468703748095709E-02   8.9203887178036811E-01   3.0884291346297571E-01   1.3273333751276145E-01\n         2        151   1.1261065376785638E-02   1.9587562376845749E+00   6.4645669881307943E-01   3.2535127365086136E-01\n         2        152   3.5896493555871560E-04   1.7984970154113824E+00   5.4624534475215858E-01   3.1422371262402737E-01\n         2        153   3.2146558481187351E-04   1.7361200969750212E+00   5.2249399261790697E-01   3.2640477488401864E-01\n         2        154   1.9170802304639301E-05   5.1906530341340473E-01   1.3476576860610107E-01   1.2209998866602599E-01\n         2        155   8.1840259755860201E-01   1.5594249159894881E+01   2.5480147563845170E+00   9.4023878385982484E-01\n         2        156   4.7542569721655870E-01   3.3531589358968453E+01   4.6171453650268921E+00   2.6132171279273386E+00\n         2        157   3.0738894874348899E-01   5.7340549971175506E+01   6.6908487004451844E+00   4.5807701389511966E+00\n         2        158   6.3567156810183684E-02   4.5023216995322620E+01   4.3956044310167721E+00   3.5205232224344187E+00\n         2        159   5.2863448949719533E-02   4.2086094131093930E+01   4.0035851413359147E+00   3.1976205970551832E+00\n         2        160   6.4149968172717243E-03   1.8618075218843980E+01   1.4526833514225641E+00   1.2454636282220404E+00\n         2        161   1.4489452028832114E-01   1.0966593756356586E+00   5.3004356792959717E-01   1.5513127698684248E-01\n         2        162   1.0160574133187714E-01   3.1794557079835268E+00   9.5836851107842136E-01   3.8524701364310232E-01\n         2        163   7.6627314589045967E-02   5.4252913236855393E+00   1.6367931186779705E+00   7.1591678637586287E-01\n         2        164   2.2150001218022141E-02   4.0466331490957383E+00   1.2274854143268068E+00   6.0454284097536792E-01\n         2        165   1.8186823617799081E-02   3.7609945630553550E+00   1.1346293008253177E+00   6.0545850230785114E-01\n         2        166   3.1357228989072096E-03   1.2192894333018813E+00   3.2998396439263078E-01   2.6273445408423063E-01\n         2        167   5.9356688579077210E-01   5.2896811534252933E+01   1.2078900205515192E+01   6.4786720785965324E+00\n         2        168   7.8528450885121448E-01   1.2575672322168535E+02   2.5065916633656958E+01   1.4425120732404041E+01\n         2        169   1.5733945396317028E+00   2.1726161055496939E+02   4.2201295670647291E+01   2.4535911912158429E+01\n         2        170   1.2159121415855736E+00   1.5869487889684305E+02   3.0162630017512182E+01   1.7994902781170296E+01\n         2        171   9.7485945117709216E-01   1.4714352248898922E+02   2.8039385191222166E+01   1.6665425989282063E+01\n         2        172   5.7624328908054490E-01   5.2032605990435684E+01   1.1071136356893190E+01   6.5728652022350857E+00\n         2        173   3.8517869050529824E-01   2.6591072511076432E+00   1.1210065844709651E+00   2.6444065096677188E-01\n         2        174   3.7589446543088439E-01   7.5514221977898792E+00   2.2627973144563094E+00   8.2426976480805092E-01\n         2        175   3.8997673154004053E-01   1.2225782863663438E+01   3.6780385740373758E+00   1.4134595048547403E+00\n         2        176   1.8953769370358300E-01   8.5686057365350567E+00   2.6268076245223408E+00   1.0976078894743850E+00\n         2        177   1.7729708284564194E-01   7.7764375456882009E+00   2.3901076550888796E+00   1.0395830672085906E+00\n         2        178   3.5684992206404427E-02   2.7311579294234547E+00   7.5811964912914154E-01   4.4846628465095084E-01\n         2        179   7.4826693027104820E+00   9.9940754137346929E+01   4.2059453974550216E+01   1.2605635816476459E+01\n         2        180   1.7255242213055784E+01   2.6152979584973161E+02   1.0683124719178711E+02   3.4806498209133352E+01\n         2        181   3.1693079220817939E+01   4.0935023753583840E+02   1.7443471186787590E+02   5.5955565273310349E+01\n         2        182   2.4378595634715843E+01   2.7492475597054482E+02   1.2074254543255512E+02   3.8674324322101114E+01\n         2        183   2.3107639172579024E+01   2.4680054433882918E+02   1.0996855652172252E+02   3.5165587138237356E+01\n         2        184   7.3539876973635625E+00   9.7128322747635494E+01   4.1413102151684384E+01   1.3806641806589422E+01\n"
  },
  {
    "path": "examples/nnp-predict/Ethylbenzene_SCAN/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -8.5559815049257306E+00 a         1     0     1     1     1\n  2.4455922401502130E+00 a         2     0     1     1     2\n  4.7522987330844790E+00 a         3     0     1     1     3\n -1.0544783349437394E+00 a         4     0     1     1     4\n  1.5860148045724824E+01 a         5     0     1     1     5\n  5.2740934002911546E+00 a         6     0     1     1     6\n -9.5856767902945546E+00 a         7     0     1     1     7\n  2.0208327915361588E+00 a         8     0     1     1     8\n -1.9221356432217263E-01 a         9     0     1     1     9\n  7.5509300171317122E+00 a        10     0     1     1    10\n  6.2488419702363194E+00 a        11     0     1     1    11\n  2.6500993233507542E+00 a        12     0     1     1    12\n -5.2976905163930770E+00 a        13     0     1     1    13\n -4.8296586807394855E+00 a        14     0     1     1    14\n  1.0750476036231758E+00 a        15     0     1     1    15\n -5.5679934068210435E-01 a        16     0     1     1    16\n  6.4518972784428490E+00 a        17     0     1     1    17\n -7.1327132812553842E+00 a        18     0     1     1    18\n -4.0392860056000508E+00 a        19     0     1     1    19\n  5.8010102453890440E+00 a        20     0     1     1    20\n -8.9590987302254632E+00 a        21     0     1     1    21\n  1.0731310874487839E+01 a        22     0     1     1    22\n  5.1548460695436893E-01 a        23     0     1     1    23\n  6.1343221569693815E+00 a        24     0     1     1    24\n  1.4235283083426873E+00 a        25     0     1     1    25\n -4.9169480836061492E+00 a        26     0     2     1     1\n -7.9769803801795396E+00 a        27     0     2     1     2\n -1.4353198359731416E+00 a        28     0     2     1     3\n  2.5859753346393188E+00 a        29     0     2     1     4\n  1.2998899000677383E+01 a        30     0     2     1     5\n -3.0058509859378448E+00 a        31     0     2     1     6\n  2.3428175954307708E+01 a        32     0     2     1     7\n -5.2965336655135999E+00 a        33     0     2     1     8\n  1.0429193716860453E+01 a        34     0     2     1     9\n  7.6452203557715643E+00 a        35     0     2     1    10\n  2.1156153724827798E+00 a        36     0     2     1    11\n -9.5104829181514425E+00 a        37     0     2     1    12\n -1.1260896921327607E+01 a        38     0     2     1    13\n -7.4313861462858000E-01 a        39     0     2     1    14\n -1.2099211359122032E+01 a        40     0     2     1    15\n -3.8078794322987894E+00 a        41     0     2     1    16\n  6.5263320236671598E+00 a        42     0     2     1    17\n -7.0181738280440555E+00 a        43     0     2     1    18\n  1.2754346067739859E+00 a        44     0     2     1    19\n -1.2160813658403619E+01 a        45     0     2     1    20\n  1.7046398372248357E+00 a        46     0     2     1    21\n -5.1466591039032084E+00 a        47     0     2     1    22\n 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1.1008932859225469E+00 a      1952     0    79     1     2\n  5.1394713480774197E+00 a      1953     0    79     1     3\n -6.8899012680035332E+00 a      1954     0    79     1     4\n  6.6378138553888348E+00 a      1955     0    79     1     5\n  3.8829030744033943E+00 a      1956     0    79     1     6\n -7.5090676818920432E+00 a      1957     0    79     1     7\n  2.1953105473271934E+00 a      1958     0    79     1     8\n -4.3231641521829340E+00 a      1959     0    79     1     9\n -1.9648053295801626E-01 a      1960     0    79     1    10\n  8.5225280099334064E+00 a      1961     0    79     1    11\n -2.2519772429179068E+00 a      1962     0    79     1    12\n  2.0877071686080018E+00 a      1963     0    79     1    13\n -5.3718900886827035E+00 a      1964     0    79     1    14\n  3.9682780334546339E+00 a      1965     0    79     1    15\n -5.4267302690686936E+00 a      1966     0    79     1    16\n  5.6249537611030593E+00 a      1967     0    79     1    17\n -2.6248724896874853E-01 a      1968     0    79     1    18\n  5.9282764098940541E+00 a      1969     0    79     1    19\n -2.1876693122171442E+00 a      1970     0    79     1    20\n -7.4045189778393414E+00 a      1971     0    79     1    21\n -1.1570611702898470E+00 a      1972     0    79     1    22\n  1.0519204361415867E-01 a      1973     0    79     1    23\n -5.1112178610584325E+00 a      1974     0    79     1    24\n -6.8045441043555730E+00 a      1975     0    79     1    25\n -3.9822500290250678E+00 a      1976     0    80     1     1\n  7.5393055145217964E+00 a      1977     0    80     1     2\n  1.0631946081157944E+01 a      1978     0    80     1     3\n -2.3657264322381288E+00 a      1979     0    80     1     4\n -5.2400086863654911E+00 a      1980     0    80     1     5\n -2.4924267722257039E+00 a      1981     0    80     1     6\n -1.4482203648300669E+00 a      1982     0    80     1     7\n -8.2507990895167840E+00 a      1983     0    80     1     8\n -2.9837948724493817E+00 a      1984     0    80     1     9\n  4.8047923027977752E+00 a      1985     0    80     1    10\n -3.4977814850738977E+00 a      1986     0    80     1    11\n -5.5266538738766713E-01 a      1987     0    80     1    12\n  2.2720375785361502E+00 a      1988     0    80     1    13\n  8.1155659544794378E+00 a      1989     0    80     1    14\n  1.5720298093394950E+01 a      1990     0    80     1    15\n  7.8920008837825684E+00 a      1991     0    80     1    16\n  8.0507098433621849E-01 a      1992     0    80     1    17\n  5.9185244874451151E+00 a      1993     0    80     1    18\n  2.5642424607541399E+00 a      1994     0    80     1    19\n -5.3442171958241929E+00 a      1995     0    80     1    20\n  5.0753912654216238E-01 a      1996     0    80     1    21\n -2.8532756294433184E+00 a      1997     0    80     1    22\n -4.5575543912850192E+00 a      1998     0    80     1    23\n -1.0326301296439699E+01 a      1999     0    80     1    24\n  1.7566566950260485E+00 a      2000     0    80     1    25\n  1.7968148866675133E+00 a      2001     0    81     1     1\n -2.8353407603544944E+00 a      2002     0    81     1     2\n -6.2809064144104001E+00 a      2003     0    81     1     3\n  1.7440412456468848E-01 a      2004     0    81     1     4\n  1.4735776942301784E-01 a      2005     0    81     1     5\n -1.4395670405482102E+00 a      2006     0    81     1     6\n  4.0729304076735318E+00 a      2007     0    81     1     7\n  5.0534537872499321E+00 a      2008     0    81     1     8\n  2.5277147126964650E-01 a      2009     0    81     1     9\n  3.6106926395649226E+00 a      2010     0    81     1    10\n  3.2273355219817446E+00 a      2011     0    81     1    11\n -1.0107090935910866E+01 a      2012     0    81     1    12\n  8.3523398519442882E+00 a      2013     0    81     1    13\n  8.3650159540184432E-01 a      2014     0    81     1    14\n  4.5453198949959788E+00 a      2015     0    81     1    15\n -8.2733085531604456E+00 a      2016     0    81     1    16\n  1.8397194357244531E-01 a      2017     0    81     1    17\n  6.3496792061827967E-01 a      2018     0    81     1    18\n  2.8727760317705937E+00 a      2019     0    81     1    19\n -4.4165925602418206E+00 a      2020     0    81     1    20\n  4.9032748494183593E+00 a      2021     0    81     1    21\n -9.6593330433473501E-01 a      2022     0    81     1    22\n  2.5823903430280120E+00 a      2023     0    81     1    23\n -4.3176804760716312E+00 a      2024     0    81     1    24\n  6.8415578724064083E+00 a      2025     0    81     1    25\n -7.0952354627464391E+00 a      2026     0    82     1     1\n -3.3805929128229444E+00 a      2027     0    82     1     2\n -5.5995925180536679E+00 a      2028     0    82     1     3\n  2.5410875611382560E+00 a      2029     0    82     1     4\n  3.5475693099544254E+00 a      2030     0    82     1     5\n -2.8396973568982302E+00 a      2031     0    82     1     6\n -2.7908053926657641E+00 a      2032     0    82     1     7\n  1.6772138719507588E+01 a      2033     0    82     1     8\n  6.4349275393852281E+00 a      2034     0    82     1     9\n  6.9847260931487458E+00 a      2035     0    82     1    10\n -3.8204886525794648E+00 a      2036     0    82     1    11\n -1.8465803707811859E+00 a      2037     0    82     1    12\n  9.9292201773087854E+00 a      2038     0    82     1    13\n -1.0935503791844912E+01 a      2039     0    82     1    14\n -3.8140726339991327E-01 a      2040     0    82     1    15\n  4.6540033524793589E+00 a      2041     0    82     1    16\n  1.4685057997665270E+00 a      2042     0    82     1    17\n  1.3830554099950021E+01 a      2043     0    82     1    18\n  6.2396568204822689E-01 a      2044     0    82     1    19\n -2.2755365047213876E+00 a      2045     0    82     1    20\n  1.2432619763584272E+00 a      2046     0    82     1    21\n  4.8275980504502005E+00 a      2047     0    82     1    22\n  2.4316903028913206E+00 a      2048     0    82     1    23\n  9.6668016270186623E+00 a      2049     0    82     1    24\n  1.8012613037724272E+00 a      2050     0    82     1    25\n  1.4172723208009139E+00 a      2051     0    83     1     1\n  1.2654490622972401E+00 a      2052     0    83     1     2\n -2.2970849224577479E+00 a      2053     0    83     1     3\n  4.0804115213357289E-01 a      2054     0    83     1     4\n  2.6004152586545830E+00 a      2055     0    83     1     5\n -7.1564843502605697E+00 a      2056     0    83     1     6\n -1.2295423536268091E+00 a      2057     0    83     1     7\n  7.5868943262656456E+00 a      2058     0    83     1     8\n  2.3782591543105407E+00 a      2059     0    83     1     9\n -1.2781424969935067E+01 a      2060     0    83     1    10\n -7.7751177599047621E+00 a      2061     0    83     1    11\n -5.3311133888918780E+00 a      2062     0    83     1    12\n -5.3122344469638900E+00 a      2063     0    83     1    13\n -5.8879482327874069E+00 a      2064     0    83     1    14\n -8.7608390301070105E-01 a      2065     0    83     1    15\n  2.4835128045713861E+00 a      2066     0    83     1    16\n  3.9512633914990278E+00 a      2067     0    83     1    17\n -4.7060617240652283E+00 a      2068     0    83     1    18\n -3.4766759657878882E-01 a      2069     0    83     1    19\n -9.0167460425013175E+00 a      2070     0    83     1    20\n  9.0775226142549670E+00 a      2071     0    83     1    21\n  9.1868627460771215E+00 a      2072     0    83     1    22\n  7.9634958142067808E-02 a      2073     0    83     1    23\n -5.6237588666689806E+00 a      2074     0    83     1    24\n -4.8745055833310511E+00 a      2075     0    83     1    25\n -1.0038948717066685E+01 a      2076     0    84     1     1\n -5.4069391881162887E-01 a      2077     0    84     1     2\n  2.0062972265574408E+00 a      2078     0    84     1     3\n -5.5007858591572778E-01 a      2079     0    84     1     4\n  6.2616034776869114E+00 a      2080     0    84     1     5\n  1.2278199722854149E+01 a      2081     0    84     1     6\n  7.5282270186139657E+00 a      2082     0    84     1     7\n -7.6278920181868139E+00 a      2083     0    84     1     8\n  2.6699324500683770E+00 a      2084     0    84     1     9\n -9.2015320919202388E+00 a      2085     0    84     1    10\n -4.4702379692661637E-01 a      2086     0    84     1    11\n  2.9150677780203389E+00 a      2087     0    84     1    12\n  2.2612920162108816E+00 a      2088     0    84     1    13\n  2.3917395308121221E+00 a      2089     0    84     1    14\n -5.1397696843441008E+00 a      2090     0    84     1    15\n -2.7891537471716541E+00 a      2091     0    84     1    16\n -1.9248230321271137E-01 a      2092     0    84     1    17\n  4.3777467145251485E+00 a      2093     0    84     1    18\n -1.1523775865932386E+01 a      2094     0    84     1    19\n  6.4275664273636695E+00 a      2095     0    84     1    20\n -1.1823974215133900E+01 a      2096     0    84     1    21\n -5.6595365159974982E+00 a      2097     0    84     1    22\n  5.1366266571893859E-01 a      2098     0    84     1    23\n -8.4421620077322679E+00 a      2099     0    84     1    24\n  3.9324980478328428E+00 a      2100     0    84     1    25\n  1.2424175267524284E+01 a      2101     0    85     1     1\n -8.9428378700895772E-01 a      2102     0    85     1     2\n -2.9641108341041664E+00 a      2103     0    85     1     3\n  5.8753114929334691E+00 a      2104     0    85     1     4\n -1.5433695699960004E-01 a      2105     0    85     1     5\n -8.4070230303250764E+00 a      2106     0    85     1     6\n  2.0711492597346819E+00 a      2107     0    85     1     7\n  4.5411716610154835E+00 a      2108     0    85     1     8\n -1.3959555631903160E+00 a      2109     0    85     1     9\n  3.5657376539548862E+00 a      2110     0    85     1    10\n  1.8558886237035148E+00 a      2111     0    85     1    11\n -1.4024833371639950E-01 a      2112     0    85     1    12\n -3.5428499997835501E+00 a      2113     0    85     1    13\n  6.0100997452714013E+00 a      2114     0    85     1    14\n -7.2660416239924706E+00 a      2115     0    85     1    15\n -3.5250723775375050E+00 a      2116     0    85     1    16\n  2.0997326349355254E+00 a      2117     0    85     1    17\n  6.3441144822116846E-01 a      2118     0    85     1    18\n  1.2954874069801255E+01 a      2119     0    85     1    19\n  3.3683349994453144E+00 a      2120     0    85     1    20\n  2.3511669514941334E+00 a      2121     0    85     1    21\n -1.6271896567050650E+00 a      2122     0    85     1    22\n -3.4921943473663442E-01 a      2123     0    85     1    23\n -3.7750437597088475E+00 a      2124     0    85     1    24\n  5.7492134315805643E+00 a      2125     0    85     1    25\n -5.3325376757363561E+00 a      2126     0    86     1     1\n -1.6336885681542390E+00 a      2127     0    86     1     2\n  1.2508425493150908E+00 a      2128     0    86     1     3\n -1.0193874788753815E+01 a      2129     0    86     1     4\n -8.2435696550600941E+00 a      2130     0    86     1     5\n -2.8488310804130643E+00 a      2131     0    86     1     6\n  4.8904882864392452E+00 a      2132     0    86     1     7\n  1.3503741849284790E+01 a      2133     0    86     1     8\n -1.4729846103640425E+00 a      2134     0    86     1     9\n  8.3687585264393949E+00 a      2135     0    86     1    10\n  1.0055163198213558E+01 a      2136     0    86     1    11\n  3.4077762794179662E+00 a      2137     0    86     1    12\n  3.9215206834612260E-01 a      2138     0    86     1    13\n  9.2197295642307248E-02 a      2139     0    86     1    14\n -5.5278256993762644E+00 a      2140     0    86     1    15\n  1.0736430974590759E+01 a      2141     0    86     1    16\n  1.6231889275526772E+00 a      2142     0    86     1    17\n  7.7011906034460997E+00 a      2143     0    86     1    18\n  2.7651889030914538E+00 a      2144     0    86     1    19\n -4.3522186925487167E+00 a      2145     0    86     1    20\n  2.6464861679117755E+00 a      2146     0    86     1    21\n -2.2466680328716482E-01 a      2147     0    86     1    22\n -3.8303615866467497E+00 a      2148     0    86     1    23\n -4.0115705224488059E+00 a      2149     0    86     1    24\n -3.3681290775818757E+00 a      2150     0    86     1    25\n  4.6634776346164966E+00 a      2151     0    87     1     1\n  1.6270769641856289E+00 a      2152     0    87     1     2\n -3.5104973497955333E-01 a      2153     0    87     1     3\n  6.7838113987278046E+00 a      2154     0    87     1     4\n  7.2638356016929215E+00 a      2155     0    87     1     5\n  4.7875706768887989E+00 a      2156     0    87     1     6\n -1.2887627940923290E+01 a      2157     0    87     1     7\n -1.7288995160777663E+01 a      2158     0    87     1     8\n -6.4553062296222832E+00 a      2159     0    87     1     9\n  6.1662177333147143E+00 a      2160     0    87     1    10\n  1.6284389485854529E+00 a      2161     0    87     1    11\n -4.0533349057327817E+00 a      2162     0    87     1    12\n  9.1949292089125159E+00 a      2163     0    87     1    13\n  1.0683792349446193E+00 a      2164     0    87     1    14\n  6.6733553028918040E+00 a      2165     0    87     1    15\n -1.8708794395875787E+00 a      2166     0    87     1    16\n  1.0200036088169178E+00 a      2167     0    87     1    17\n -3.9538308200098435E+00 a      2168     0    87     1    18\n -9.1427157730264561E+00 a      2169     0    87     1    19\n -6.1603286571475149E+00 a      2170     0    87     1    20\n -2.4329836934081142E+00 a      2171     0    87     1    21\n -1.1258212524176587E+01 a      2172     0    87     1    22\n  3.4259050868449745E+00 a      2173     0    87     1    23\n -6.4642154673806473E+00 a      2174     0    87     1    24\n -4.0010616737263810E-01 a      2175     0    87     1    25\n -1.1336702910235485E+00 a      2176     0    88     1     1\n -1.1314136632522374E+00 a      2177     0    88     1     2\n  1.2683037967837019E+00 a      2178     0    88     1     3\n -2.0797594074920021E+00 a      2179     0    88     1     4\n -3.3228274069478270E-01 a      2180     0    88     1     5\n -4.3911846831803283E+00 a      2181     0    88     1     6\n  1.8324287568326552E+00 a      2182     0    88     1     7\n  5.7814502644040502E+00 a      2183     0    88     1     8\n  1.2843161242704044E+01 a      2184     0    88     1     9\n -3.7248559379450352E+00 a      2185     0    88     1    10\n -3.3737949091073949E+00 a      2186     0    88     1    11\n -3.7330573447711124E-01 a      2187     0    88     1    12\n  2.3944998424436954E+00 a      2188     0    88     1    13\n -2.8558738524649292E+00 a      2189     0    88     1    14\n -7.4214391232245616E+00 a      2190     0    88     1    15\n  3.7443196066239053E+00 a      2191     0    88     1    16\n 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-4.0155910464813429E+00 a      5109     1    20     2     9\n -6.7816960805191795E-01 a      5110     1    20     2    10\n  2.8474201226715783E+00 a      5111     1    20     2    11\n  9.0929096525302078E-01 a      5112     1    20     2    12\n -2.4776121962228217E-01 a      5113     1    20     2    13\n -1.2735505460128325E+00 a      5114     1    20     2    14\n -3.0606132818625559E-01 a      5115     1    20     2    15\n  1.1725720798255974E+00 a      5116     1    20     2    16\n -5.3035661945148904E+00 a      5117     1    20     2    17\n -5.2390442942604043E+00 a      5118     1    20     2    18\n  9.1455379178731744E-01 a      5119     1    20     2    19\n -5.5427819719931923E+00 a      5120     1    20     2    20\n -1.3747643391659073E-01 a      5121     1    20     2    21\n  1.5115423807107053E+00 a      5122     1    20     2    22\n  8.9611936097922473E-01 a      5123     1    20     2    23\n -8.0509920495798548E-01 a      5124     1    20     2    24\n -4.0330719326684008E+00 a      5125     1    20     2    25\n  1.6004363527422369E+00 a      5126     1    21     2     1\n -3.4057934379229199E-01 a      5127     1    21     2     2\n -1.6471074820617013E+00 a      5128     1    21     2     3\n -1.2695306296023590E+00 a      5129     1    21     2     4\n  1.1671989840726993E+00 a      5130     1    21     2     5\n  5.0333073521920457E-01 a      5131     1    21     2     6\n  3.4735510561517851E+00 a      5132     1    21     2     7\n -1.9448615006400041E+00 a      5133     1    21     2     8\n  9.4671336113124949E-01 a      5134     1    21     2     9\n  5.8200370835875681E-01 a      5135     1    21     2    10\n -5.9262977866150761E+00 a      5136     1    21     2    11\n  6.7980696116865691E-02 a      5137     1    21     2    12\n -1.2482888616557203E-01 a      5138     1    21     2    13\n -7.4588543458861023E-01 a      5139     1    21     2    14\n  8.9238897174008858E-01 a      5140     1    21     2    15\n  1.8118920305522195E+00 a      5141     1    21     2    16\n  2.3827363812434887E+00 a      5142     1    21     2    17\n  8.9021534670549496E-01 a      5143     1    21     2    18\n  3.0298161953804397E+00 a      5144     1    21     2    19\n  2.7449696603173979E+00 a      5145     1    21     2    20\n  1.2719730937775531E+00 a      5146     1    21     2    21\n  2.7121325289774618E+00 a      5147     1    21     2    22\n  9.7998619269786891E-01 a      5148     1    21     2    23\n  3.5152666748715808E+00 a      5149     1    21     2    24\n  7.2639256397906304E-01 a      5150     1    21     2    25\n  3.8786317580510904E-01 a      5151     1    22     2     1\n  4.1431766406784853E-01 a      5152     1    22     2     2\n -1.7773489021342901E+00 a      5153     1    22     2     3\n  2.9686346262650518E-02 a      5154     1    22     2     4\n  6.4179804439566537E+00 a      5155     1    22     2     5\n  1.5659211447177285E-01 a      5156     1    22     2     6\n -3.7645216869478293E-01 a      5157     1    22     2     7\n  2.5925800945632216E+00 a      5158     1    22     2     8\n  2.5248886010279827E+00 a      5159     1    22     2     9\n  1.8114625993328564E+00 a      5160     1    22     2    10\n -9.0149397674712279E+00 a      5161     1    22     2    11\n -5.5385587174359971E-02 a      5162     1    22     2    12\n -1.6107074578350947E-01 a      5163     1    22     2    13\n -7.9308104512869082E-01 a      5164     1    22     2    14\n  2.2384868971120248E-01 a      5165     1    22     2    15\n -4.1184468379177180E-01 a      5166     1    22     2    16\n  1.0849002402293559E-01 a      5167     1    22     2    17\n -4.7987500778945191E-01 a      5168     1    22     2    18\n -2.2679690439890510E+00 a      5169     1    22     2    19\n  2.6345690965876090E+00 a      5170     1    22     2    20\n -2.7751942532008222E-01 a      5171     1    22     2    21\n  1.0268619970039047E+01 a      5172     1    22     2    22\n  1.4893635278433395E-01 a      5173     1    22     2    23\n  1.4227143851470730E-01 a      5174     1    22     2    24\n -1.5042838009093256E+00 a      5175     1    22     2    25\n -1.3355939919682664E+00 a      5176     1    23     2     1\n -2.2144508716901412E-01 a      5177     1    23     2     2\n  2.5997713625687595E+00 a      5178     1    23     2     3\n -1.7318950240483666E+00 a      5179     1    23     2     4\n -9.5091628980213816E-01 a      5180     1    23     2     5\n  1.1133773822338948E+00 a      5181     1    23     2     6\n -7.9577813502221567E-02 a      5182     1    23     2     7\n -1.8388390251277080E+00 a      5183     1    23     2     8\n  5.5929352010197864E-01 a      5184     1    23     2     9\n -1.1946805434431096E-01 a      5185     1    23     2    10\n -8.7264618366332924E-01 a      5186     1    23     2    11\n -1.1541160540958666E+00 a      5187     1    23     2    12\n  1.5656714273925130E+00 a      5188     1    23     2    13\n -7.3791117385890781E-02 a      5189     1    23     2    14\n  2.3955983106343531E-01 a      5190     1    23     2    15\n -1.8856249079760081E+00 a      5191     1    23     2    16\n -3.1482729046499052E+00 a      5192     1    23     2    17\n -1.8728562410856650E-01 a      5193     1    23     2    18\n -2.3683894268376497E+00 a      5194     1    23     2    19\n -1.0236970649186015E+00 a      5195     1    23     2    20\n -6.1950476011404243E-01 a      5196     1    23     2    21\n  1.9328772515255446E+00 a      5197     1    23     2    22\n -4.0552484852582236E+00 a      5198     1    23     2    23\n -3.9225587485999975E+00 a      5199     1    23     2    24\n -1.9947394385213868E-01 a      5200     1    23     2    25\n -4.3704749791359072E+00 a      5201     1    24     2     1\n  1.8787915296639122E-02 a      5202     1    24     2     2\n  5.4855213699962135E+00 a      5203     1    24     2     3\n -2.0001774899086429E+00 a      5204     1    24     2     4\n  3.0776769741503069E+00 a      5205     1    24     2     5\n  1.0866694787429930E-01 a      5206     1    24     2     6\n  1.5162064624690874E+00 a      5207     1    24     2     7\n  5.7137598874813484E+00 a      5208     1    24     2     8\n -2.0348536998309732E+00 a      5209     1    24     2     9\n -1.7394173179378547E+00 a      5210     1    24     2    10\n -7.4283419565582296E+00 a      5211     1    24     2    11\n -5.2762955285750555E-02 a      5212     1    24     2    12\n -1.7274346044059652E-01 a      5213     1    24     2    13\n -1.0419050294186168E-01 a      5214     1    24     2    14\n  1.2289760527975269E+00 a      5215     1    24     2    15\n  3.1274543350202659E+00 a      5216     1    24     2    16\n -6.0104880150504081E-01 a      5217     1    24     2    17\n -2.7046905251099869E+00 a      5218     1    24     2    18\n  1.0165961309731903E+00 a      5219     1    24     2    19\n -2.8243253828152994E+00 a      5220     1    24     2    20\n -2.7749144343156789E+00 a      5221     1    24     2    21\n -1.9245703775340668E+00 a      5222     1    24     2    22\n  5.9231071389482037E-01 a      5223     1    24     2    23\n -5.4690233253062264E+00 a      5224     1    24     2    24\n  1.3696049678759725E+00 a      5225     1    24     2    25\n  2.4357226368059322E+00 a      5226     1    25     2     1\n  1.6587565578760983E+00 a      5227     1    25     2     2\n  1.7197066660190599E+00 a      5228     1    25     2     3\n -1.7813605909515366E+00 a      5229     1    25     2     4\n -2.6171420111577968E+00 a      5230     1    25     2     5\n -2.9093749981786254E-01 a      5231     1    25     2     6\n -6.3694812287910108E-01 a      5232     1    25     2     7\n -4.1838484230148270E+00 a      5233     1    25     2     8\n -1.3114644901140601E-01 a      5234     1    25     2     9\n  6.3965614327051434E-01 a      5235     1    25     2    10\n  3.3558970148580813E-01 a      5236     1    25     2    11\n  3.0894458355433296E-01 a      5237     1    25     2    12\n  2.6857432259124497E-01 a      5238     1    25     2    13\n -4.2763308447273746E-01 a      5239     1    25     2    14\n  2.5256388068261366E-02 a      5240     1    25     2    15\n -1.7373289104656737E+00 a      5241     1    25     2    16\n -1.6010902904762014E+00 a      5242     1    25     2    17\n -1.4843504716535252E+00 a      5243     1    25     2    18\n -9.0399698420668317E-01 a      5244     1    25     2    19\n  1.0901933854756902E+00 a      5245     1    25     2    20\n -9.4420803683339616E-01 a      5246     1    25     2    21\n  3.3181848441236694E-01 a      5247     1    25     2    22\n  4.8310165776460140E-01 a      5248     1    25     2    23\n  2.0959433474371774E+00 a      5249     1    25     2    24\n -7.6535075511009698E-01 a      5250     1    25     2    25\n  2.3972689148636626E+00 b      5251     2     1\n  1.7154180017402040E-01 b      5252     2     2\n -5.5229867823392125E+00 b      5253     2     3\n  5.2616342734534960E-01 b      5254     2     4\n -1.0459668892134305E+01 b      5255     2     5\n -4.9240169341224718E+00 b      5256     2     6\n -3.0876746240972053E+00 b      5257     2     7\n -1.3619194046410812E+00 b      5258     2     8\n -1.1722074879829588E+01 b      5259     2     9\n  2.4868702377366771E+00 b      5260     2    10\n  1.5281225445127375E+00 b      5261     2    11\n  5.1943459822183702E-01 b      5262     2    12\n -6.0362400492902824E+00 b      5263     2    13\n -8.1513270116304071E-01 b      5264     2    14\n -4.9091965829559525E+00 b      5265     2    15\n  5.4383035515541478E-01 b      5266     2    16\n  1.1668928810435484E+00 b      5267     2    17\n  4.0101172502430344E+00 b      5268     2    18\n -8.2348953525181017E+00 b      5269     2    19\n -2.1463193168851635E+00 b      5270     2    20\n  5.8825775611798061E+00 b      5271     2    21\n  4.4741597846306069E+00 b      5272     2    22\n  9.4398394490750288E+00 b      5273     2    23\n  4.8558416975347685E+00 b      5274     2    24\n  1.3459518328767128E+01 b      5275     2    25\n -1.9641317243382372E-01 a      5276     2     1     3     1\n -1.4363721187863440E-01 a      5277     2     2     3     1\n -2.2575853398233182E-02 a      5278     2     3     3     1\n -1.5893554344107930E-01 a      5279     2     4     3     1\n  3.9290061853094492E-02 a      5280     2     5     3     1\n  3.0871348097189051E+00 a      5281     2     6     3     1\n  1.7050864514192923E-01 a      5282     2     7     3     1\n -3.0100747498387394E-02 a      5283     2     8     3     1\n  2.2665351135907555E-01 a      5284     2     9     3     1\n -2.0618778428614079E-01 a      5285     2    10     3     1\n  2.2450691698885042E-02 a      5286     2    11     3     1\n  1.3395018583777025E+00 a      5287     2    12     3     1\n  2.1759064697369035E+00 a      5288     2    13     3     1\n -5.3285490347452236E-01 a      5289     2    14     3     1\n  1.7560192941575337E+00 a      5290     2    15     3     1\n  2.2263668095263745E-02 a      5291     2    16     3     1\n -1.1089303526928738E-01 a      5292     2    17     3     1\n -1.2788396467490229E-01 a      5293     2    18     3     1\n  2.9730180868325084E-02 a      5294     2    19     3     1\n -1.9993534904303990E-02 a      5295     2    20     3     1\n  7.7910673578683076E-01 a      5296     2    21     3     1\n  3.8236672016762840E-03 a      5297     2    22     3     1\n -1.7389683319831688E+00 a      5298     2    23     3     1\n  2.7984518602650405E-02 a      5299     2    24     3     1\n -5.6807596349854765E-02 a      5300     2    25     3     1\n  1.1936191511085166E+01 b      5301     3     1\n"
  },
  {
    "path": "examples/nnp-predict/Ethylbenzene_SCAN/weights.006.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -2.1697495595969407E+00 a         1     0     1     1     1\n -3.6698733385174749E+00 a         2     0     1     1     2\n -2.7618742921732444E+01 a         3     0     1     1     3\n  5.6385655464465438E+00 a         4     0     1     1     4\n  6.6552362998554928E+00 a         5     0     1     1     5\n -8.6811718844364414E+00 a         6     0     1     1     6\n  4.9217156963090432E+00 a         7     0     1     1     7\n -7.9801135158011549E-01 a         8     0     1     1     8\n -1.9125102590905214E+00 a         9     0     1     1     9\n  8.6811209997195409E+00 a        10     0     1     1    10\n  1.5324812732052255E+00 a        11     0     1     1    11\n -3.0465651002167654E-01 a        12     0     1     1    12\n -6.8972611589896204E-01 a        13     0     1     1    13\n  1.3389756685960588E+01 a        14     0     1     1    14\n  2.9931379991461449E-01 a        15     0     1     1    15\n  5.9523411091219369E+00 a        16     0     1     1    16\n -4.1349645544673272E+00 a        17     0     1     1    17\n -6.7028651496791172E+00 a        18     0     1     1    18\n -9.7792323168697379E+00 a        19     0     1     1    19\n -2.5735909159575980E+00 a        20     0     1     1    20\n -5.1681860291918849E+00 a        21     0     1     1    21\n -5.0623431085542885E+00 a        22     0     1     1    22\n  7.9782617850621680E+00 a        23     0     1     1    23\n -8.6866709540450646E+00 a        24     0     1     1    24\n -9.9535031749897058E+00 a        25     0     1     1    25\n -1.9455386834957047E+00 a        26     0     2     1     1\n -2.5918942174754189E+00 a        27     0     2     1     2\n  1.1822517686651599E+01 a        28     0     2     1     3\n  1.8709205874842080E+01 a        29     0     2     1     4\n  1.2236033610648279E+01 a        30     0     2     1     5\n  6.2061417070579594E+00 a        31     0     2     1     6\n -5.2697753868176260E+00 a        32     0     2     1     7\n  4.3403712837243784E+00 a        33     0     2     1     8\n  1.0346135337977957E+01 a        34     0     2     1     9\n  4.7866293229894090E+00 a        35     0     2     1    10\n -1.3260579040711664E+00 a        36     0     2     1    11\n -4.5200017402115424E+00 a        37     0     2     1    12\n -8.3762598704082549E+00 a        38     0     2     1    13\n -1.0469880750696952E+01 a        39     0     2     1    14\n -1.7254224419473587E+00 a        40     0     2     1    15\n -6.3727626650659124E+00 a        41     0     2     1    16\n -8.4216192969686410E-01 a        42     0     2     1    17\n  2.7327371894811185E+00 a        43     0     2     1    18\n  3.9665987626588102E+00 a        44     0     2     1    19\n  4.3560808937899145E+00 a        45     0     2     1    20\n  3.6156740459833978E+00 a        46     0     2     1    21\n -1.0492483980445360E+00 a        47     0     2     1    22\n  1.1155297753949098E+01 a        48     0     2     1    23\n -1.9271875214683667E+00 a        49     0     2     1    24\n  3.2937562957701334E+00 a        50     0     2     1    25\n  8.6019178867934993E+00 a        51     0     3     1     1\n -6.0634025577768842E+00 a        52     0     3     1     2\n -1.5118181156667754E+00 a        53     0     3     1     3\n  2.6692735161462705E-01 a        54     0     3     1     4\n  2.1751372197619411E+01 a        55     0     3     1     5\n  6.9517620954129624E+00 a        56     0     3     1     6\n -5.6536071671219172E+00 a        57     0     3     1     7\n -5.2178538450219225E+00 a        58     0     3     1     8\n  2.4854051027670980E+01 a        59     0     3     1     9\n -3.0658065897030875E+00 a        60     0     3     1    10\n -3.8521951383859204E+01 a        61     0     3     1    11\n  1.2410533840990382E+01 a        62     0     3     1    12\n  8.0706658545767542E+00 a        63     0     3     1    13\n -1.3812510309637116E+01 a        64     0     3     1    14\n -9.1685313056523547E+00 a        65     0     3     1    15\n -1.4877117155227912E+01 a        66     0     3     1    16\n  6.6110524146803973E-01 a        67     0     3     1    17\n  1.4679926392547351E+00 a        68     0     3     1    18\n -5.7298030749400564E+00 a        69     0     3     1    19\n  1.9306232432323604E+01 a        70     0     3     1    20\n -9.6581511079398492E+00 a        71     0     3     1    21\n  1.0337349009327287E+01 a        72     0     3     1    22\n  8.0826221461751147E-01 a        73     0     3     1    23\n  2.1737846027275860E+00 a        74     0     3     1    24\n  2.9211928752049023E+01 a        75     0     3     1    25\n  7.2497055256452887E+00 a        76     0     4     1     1\n -4.6419294640108850E+00 a        77     0     4     1     2\n  2.6088381554328421E+00 a        78     0     4     1     3\n  5.7340340494192112E+00 a        79     0     4     1     4\n -1.5773393528415966E+01 a        80     0     4     1     5\n  7.1245322342565229E+00 a        81     0     4     1     6\n -7.9604135177035209E+00 a        82     0     4     1     7\n -1.0071913755748535E-04 a        83     0     4     1     8\n -2.3786613761448322E+01 a        84     0     4     1     9\n  1.6226844935585572E+01 a        85     0     4     1    10\n  2.0339749793568451E+01 a        86     0     4     1    11\n  4.5430002446480572E-01 a        87     0     4     1    12\n -1.1956096668597067E+00 a        88     0     4     1    13\n  8.0513442562228015E+00 a        89     0     4     1    14\n -2.1459880337616801E+00 a        90     0     4     1    15\n -5.5141730352313401E-01 a        91     0     4     1    16\n  1.8410607549442226E+01 a        92     0     4     1    17\n  2.1806094511598487E-01 a        93     0     4     1    18\n -9.6585986426439963E-01 a        94     0     4     1    19\n -1.6361697199128233E+01 a        95     0     4     1    20\n  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-6.9201464763502747E+00 a      1952     0    79     1     2\n  8.1709032994097406E+00 a      1953     0    79     1     3\n  6.7973157489406466E+00 a      1954     0    79     1     4\n  3.7772691526595334E+00 a      1955     0    79     1     5\n -3.6645210163559634E+00 a      1956     0    79     1     6\n -5.7585648354726029E+00 a      1957     0    79     1     7\n -3.6735810500536239E+00 a      1958     0    79     1     8\n -4.5309316850747399E+00 a      1959     0    79     1     9\n  3.2521043078215710E+00 a      1960     0    79     1    10\n  2.1046642638245392E+00 a      1961     0    79     1    11\n  1.2323152379063529E+01 a      1962     0    79     1    12\n  5.4812592642731550E+00 a      1963     0    79     1    13\n  1.2720848879446409E+01 a      1964     0    79     1    14\n -1.6258216880519054E+01 a      1965     0    79     1    15\n -4.8753114362892340E+00 a      1966     0    79     1    16\n  1.8783179544739944E+01 a      1967     0    79     1    17\n 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-1.5258569934947865E+01 a      1984     0    80     1     9\n -4.9214593092999737E+00 a      1985     0    80     1    10\n -1.9168513794976583E+01 a      1986     0    80     1    11\n -7.8253907975327630E+00 a      1987     0    80     1    12\n  2.0805197572312760E+01 a      1988     0    80     1    13\n -2.0136348375511279E-01 a      1989     0    80     1    14\n -1.0722415934205777E+01 a      1990     0    80     1    15\n  9.3258393178319192E+00 a      1991     0    80     1    16\n -6.2407291906097093E+00 a      1992     0    80     1    17\n -3.4079921931394206E+00 a      1993     0    80     1    18\n -1.9305342009692532E+00 a      1994     0    80     1    19\n -3.3259506864868480E+00 a      1995     0    80     1    20\n  6.4097975977911776E+00 a      1996     0    80     1    21\n -8.1072758192225560E+00 a      1997     0    80     1    22\n -2.5048448889005193E+00 a      1998     0    80     1    23\n -1.5220694885647783E+01 a      1999     0    80     1    24\n  5.2274960828283126E+00 a      2000     0    80     1    25\n -1.4243347078200361E+00 a      2001     0    81     1     1\n -1.0964671462628049E+01 a      2002     0    81     1     2\n  2.0150399089561808E+00 a      2003     0    81     1     3\n  8.8755273764421165E+00 a      2004     0    81     1     4\n -1.4769374490889529E+00 a      2005     0    81     1     5\n  1.3361156794288496E+00 a      2006     0    81     1     6\n  3.4839704111322320E+00 a      2007     0    81     1     7\n -1.2389969337556202E+01 a      2008     0    81     1     8\n  2.3076862076207036E+00 a      2009     0    81     1     9\n -8.2011027614464211E+00 a      2010     0    81     1    10\n  1.2796174161960991E+01 a      2011     0    81     1    11\n -4.9977822914032579E+00 a      2012     0    81     1    12\n -1.5566111207733790E+01 a      2013     0    81     1    13\n -1.2086443983441791E+01 a      2014     0    81     1    14\n  1.1435969100045966E+01 a      2015     0    81     1    15\n  5.9029453354603556E-01 a      2016     0    81     1    16\n  1.1963883008717800E-01 a      2017     0    81     1    17\n -6.4884181494454163E-01 a      2018     0    81     1    18\n -1.8429595951562030E+00 a      2019     0    81     1    19\n -3.2040783062032907E-01 a      2020     0    81     1    20\n  8.6850349699645495E+00 a      2021     0    81     1    21\n  4.2329106831563337E+00 a      2022     0    81     1    22\n  1.3419187081939459E+01 a      2023     0    81     1    23\n  5.5782241258714098E+00 a      2024     0    81     1    24\n  1.1050013375539850E+01 a      2025     0    81     1    25\n -4.9474790801113605E-01 a      2026     0    82     1     1\n  3.9645548923153773E+00 a      2027     0    82     1     2\n -1.4845303034569753E+01 a      2028     0    82     1     3\n -1.3469533681831251E+01 a      2029     0    82     1     4\n  8.8211724988018183E+00 a      2030     0    82     1     5\n  5.6962283855325060E+00 a      2031     0    82     1     6\n -7.9372230197475746E+00 a      2032     0    82     1     7\n -4.7279065224518080E+00 a      2033     0    82     1     8\n -4.8176310438319331E-01 a      2034     0    82     1     9\n  3.4184190630414317E+00 a      2035     0    82     1    10\n  1.8157129644893164E+00 a      2036     0    82     1    11\n -1.0788744308039704E+00 a      2037     0    82     1    12\n  2.3306724366883254E+00 a      2038     0    82     1    13\n  1.3451831418219440E+01 a      2039     0    82     1    14\n  5.5431970033223033E-01 a      2040     0    82     1    15\n  1.7171852736699689E+00 a      2041     0    82     1    16\n -1.1359908973424047E+00 a      2042     0    82     1    17\n -1.0284104796745149E+01 a      2043     0    82     1    18\n -7.9031200938787016E+00 a      2044     0    82     1    19\n  1.2602047024714105E+00 a      2045     0    82     1    20\n  1.1693824472606419E+01 a      2046     0    82     1    21\n  3.7325650995365072E+00 a      2047     0    82     1    22\n -8.2740795949735695E+00 a      2048     0    82     1    23\n -4.9261964714432960E+00 a      2049     0    82     1    24\n  1.2298814271432419E+00 a      2050     0    82     1    25\n -6.0795653082429113E-01 a      2051     0    83     1     1\n -6.5504958326154095E-01 a      2052     0    83     1     2\n -2.7579675896828717E+00 a      2053     0    83     1     3\n -2.4843669083440498E+00 a      2054     0    83     1     4\n  4.0073320391174878E+00 a      2055     0    83     1     5\n -2.9379903506880285E+00 a      2056     0    83     1     6\n  4.9132791879881932E+00 a      2057     0    83     1     7\n  4.6910077090565627E+00 a      2058     0    83     1     8\n -1.3349800065706807E+00 a      2059     0    83     1     9\n -5.9151370311355622E-01 a      2060     0    83     1    10\n  5.1759672239511278E+00 a      2061     0    83     1    11\n -1.0681326524023102E-01 a      2062     0    83     1    12\n -8.4348161316736214E-01 a      2063     0    83     1    13\n  2.2532225546106708E+00 a      2064     0    83     1    14\n  1.4058574177267378E+00 a      2065     0    83     1    15\n -1.1514517289411177E+00 a      2066     0    83     1    16\n -1.0747396887562696E-01 a      2067     0    83     1    17\n  2.2174635219570762E+00 a      2068     0    83     1    18\n -3.6468560131068126E+00 a      2069     0    83     1    19\n  2.8296291452914430E+00 a      2070     0    83     1    20\n -8.7829842862319263E-01 a      2071     0    83     1    21\n  2.6748062657577116E+00 a      2072     0    83     1    22\n  1.3855852423108328E+00 a      2073     0    83     1    23\n -3.6244308801488373E-01 a      2074     0    83     1    24\n  8.1479731385199088E+00 a      2075     0    83     1    25\n  3.1102915121257415E+00 a      2076     0    84     1     1\n -9.1044012081775524E-02 a      2077     0    84     1     2\n  1.0112002973877896E+01 a      2078     0    84     1     3\n  6.0138111981033437E-01 a      2079     0    84     1     4\n -4.1165090158213049E+00 a      2080     0    84     1     5\n  2.2080407009619440E+00 a      2081     0    84     1     6\n -4.5695298461408953E+00 a      2082     0    84     1     7\n  3.1694445151585833E+00 a      2083     0    84     1     8\n  3.5528329112528549E+00 a      2084     0    84     1     9\n -3.3630310467624285E+00 a      2085     0    84     1    10\n  1.8983692664923024E+00 a      2086     0    84     1    11\n -8.1181059099105513E-01 a      2087     0    84     1    12\n  8.4052322327041722E+00 a      2088     0    84     1    13\n -1.4911838543553297E+00 a      2089     0    84     1    14\n -5.5326420918847772E+00 a      2090     0    84     1    15\n -9.5987868115457925E-02 a      2091     0    84     1    16\n  3.1523788755289508E+00 a      2092     0    84     1    17\n  4.0201735077591376E+00 a      2093     0    84     1    18\n  8.0807216317065862E+00 a      2094     0    84     1    19\n -2.5334191401283590E+00 a      2095     0    84     1    20\n -3.0173259250892586E+00 a      2096     0    84     1    21\n -7.1789165689646657E+00 a      2097     0    84     1    22\n -9.8381570609539022E+00 a      2098     0    84     1    23\n  4.2000704304964565E+00 a      2099     0    84     1    24\n  1.7386150624886234E+00 a      2100     0    84     1    25\n -5.2092165362139164E+00 a      2101     0    85     1     1\n  5.5902421451457984E+00 a      2102     0    85     1     2\n  2.3693569541496631E+00 a      2103     0    85     1     3\n -8.0220670449386144E+00 a      2104     0    85     1     4\n -2.3865980224775813E+00 a      2105     0    85     1     5\n  2.1257980152867959E+00 a      2106     0    85     1     6\n  7.9122972753239047E+00 a      2107     0    85     1     7\n  3.5469003315420138E+00 a      2108     0    85     1     8\n -1.0871180389177118E+01 a      2109     0    85     1     9\n  7.9778733003390441E+00 a      2110     0    85     1    10\n  5.6040195674238031E+00 a      2111     0    85     1    11\n  2.5939528874486286E+00 a      2112     0    85     1    12\n -7.2154364980680787E+00 a      2113     0    85     1    13\n  1.0755117846890828E+01 a      2114     0    85     1    14\n  8.6148567064083803E+00 a      2115     0    85     1    15\n -8.0034015140884538E+00 a      2116     0    85     1    16\n -1.4614568467291086E+01 a      2117     0    85     1    17\n -9.8643799827336931E+00 a      2118     0    85     1    18\n -1.0858018793104169E+00 a      2119     0    85     1    19\n -2.0040784525251150E+00 a      2120     0    85     1    20\n  7.3099576628877108E+00 a      2121     0    85     1    21\n  3.4105121242322562E+00 a      2122     0    85     1    22\n  7.3338427323772679E+00 a      2123     0    85     1    23\n  1.5850206163363370E+00 a      2124     0    85     1    24\n  2.7808998120015671E-01 a      2125     0    85     1    25\n  4.7527171907452255E+00 a      2126     0    86     1     1\n  4.9909530668955711E+00 a      2127     0    86     1     2\n  6.6378218991612359E+00 a      2128     0    86     1     3\n  9.6473332865777266E+00 a      2129     0    86     1     4\n -3.8507802407579992E+00 a      2130     0    86     1     5\n  2.2248984205885951E+00 a      2131     0    86     1     6\n -5.2683295604656877E+00 a      2132     0    86     1     7\n -2.4483940052706124E+00 a      2133     0    86     1     8\n -3.8659280492756634E+00 a      2134     0    86     1     9\n -1.6543465037556258E+00 a      2135     0    86     1    10\n  8.8679999075250926E-01 a      2136     0    86     1    11\n  6.1908409549138685E+00 a      2137     0    86     1    12\n -1.1521239970381004E+01 a      2138     0    86     1    13\n -3.6300065106202064E+00 a      2139     0    86     1    14\n  4.2018799900451773E+00 a      2140     0    86     1    15\n  2.8527641569835054E+00 a      2141     0    86     1    16\n  2.1088447686634026E+00 a      2142     0    86     1    17\n  1.5344173197112843E+00 a      2143     0    86     1    18\n -1.7804816017306432E+01 a      2144     0    86     1    19\n  5.5544392756954633E+00 a      2145     0    86     1    20\n -8.8574238728528876E+00 a      2146     0    86     1    21\n -1.0406880706553459E-01 a      2147     0    86     1    22\n -1.1534798721004401E+01 a      2148     0    86     1    23\n  1.5207218608391602E+00 a      2149     0    86     1    24\n -4.1091964998211488E+00 a      2150     0    86     1    25\n -1.0186402081670147E+00 a      2151     0    87     1     1\n -6.6428062631968068E+00 a      2152     0    87     1     2\n -8.6184194410074326E+00 a      2153     0    87     1     3\n -4.3480323517218764E+00 a      2154     0    87     1     4\n -8.0396976612158131E+00 a      2155     0    87     1     5\n  3.6143059562750177E+00 a      2156     0    87     1     6\n  2.8609864497707643E-01 a      2157     0    87     1     7\n  1.6668447115313656E+00 a      2158     0    87     1     8\n  1.1876761041767219E+01 a      2159     0    87     1     9\n -4.9214466174142918E-01 a      2160     0    87     1    10\n -1.6698655682788561E+00 a      2161     0    87     1    11\n -2.9966475760892299E+00 a      2162     0    87     1    12\n  1.6698108317775983E+01 a      2163     0    87     1    13\n -9.0203423999209527E+00 a      2164     0    87     1    14\n -6.0424343156931366E+00 a      2165     0    87     1    15\n  1.5719150428186701E+00 a      2166     0    87     1    16\n  4.3359387761245820E+00 a      2167     0    87     1    17\n  4.2849823739190285E+00 a      2168     0    87     1    18\n  1.6606918544149362E+01 a      2169     0    87     1    19\n -5.8684651372907135E+00 a      2170     0    87     1    20\n  3.6820944805076539E+00 a      2171     0    87     1    21\n -7.0465520691919481E-01 a      2172     0    87     1    22\n  1.8923929120249083E+00 a      2173     0    87     1    23\n -3.9182076130728851E+00 a      2174     0    87     1    24\n  9.1808171767785467E+00 a      2175     0    87     1    25\n -1.8829287364979277E-01 a      2176     0    88     1     1\n -5.0858591239351314E-01 a      2177     0    88     1     2\n -1.0632088621231270E+00 a      2178     0    88     1     3\n -2.7936229610420780E+00 a      2179     0    88     1     4\n -5.1658365850127481E+00 a      2180     0    88     1     5\n -2.2925912472321969E-01 a      2181     0    88     1     6\n  3.6109015583198714E+00 a      2182     0    88     1     7\n -6.5818515431240705E+00 a      2183     0    88     1     8\n -1.6472293595530261E+00 a      2184     0    88     1     9\n  8.0593544821898300E-01 a      2185     0    88     1    10\n  2.4907320133184867E+00 a      2186     0    88     1    11\n -1.9318567373834075E+00 a      2187     0    88     1    12\n -3.1871591160976833E+00 a      2188     0    88     1    13\n  5.9620380688937047E-01 a      2189     0    88     1    14\n  2.3070098746052587E+00 a      2190     0    88     1    15\n -6.9591321761895175E-01 a      2191     0    88     1    16\n  9.3005214901267674E-01 a      2192     0    88     1    17\n -1.5358575237234502E+00 a      2193     0    88     1    18\n -1.6379816507430847E+00 a      2194     0    88     1    19\n  4.0904622340138292E+00 a      2195     0    88     1    20\n -9.0672282030788864E-01 a      2196     0    88     1    21\n  4.2657029923479302E+00 a      2197     0    88     1    22\n  2.4051678008959789E+00 a      2198     0    88     1    23\n -1.8514393298887508E+00 a      2199     0    88     1    24\n -1.3064754649757739E+00 a      2200     0    88     1    25\n -1.1570535351866478E+00 a      2201     0    89     1     1\n  2.5190720570822394E+00 a      2202     0    89     1     2\n -8.0183848200116326E-01 a      2203     0    89     1     3\n  1.9656250905218693E+00 a      2204     0    89     1     4\n  2.4285227205294149E+00 a      2205     0    89     1     5\n -7.5716803848313852E+00 a      2206     0    89     1     6\n -3.8947530529509429E+00 a      2207     0    89     1     7\n  9.8854923718865084E-01 a      2208     0    89     1     8\n -1.4829905309760238E+00 a      2209     0    89     1     9\n -5.2339596597768490E-01 a      2210     0    89     1    10\n -6.7419649802297883E+00 a      2211     0    89     1    11\n -1.5362948785847361E+00 a      2212     0    89     1    12\n  1.9831370783982540E+00 a      2213     0    89     1    13\n -1.6006402241746862E+00 a      2214     0    89     1    14\n -4.2175698941913859E+00 a      2215     0    89     1    15\n  1.6203231368975406E+00 a      2216     0    89     1    16\n -2.8737395606567899E+00 a      2217     0    89     1    17\n -1.1314511681374146E+00 a      2218     0    89     1    18\n -1.8531108201364554E+00 a      2219     0    89     1    19\n -9.4764178575644009E-01 a      2220     0    89     1    20\n  1.9620744135919885E+00 a      2221     0    89     1    21\n  2.5682155421582120E+00 a      2222     0    89     1    22\n  1.6453253029039649E+00 a      2223     0    89     1    23\n 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  {
    "path": "examples/nnp-predict/H2O_RPBE-D3/input.data",
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0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.3329690406923969E+01   2.7628961667849993E+01   1.2098952694655752E+01  O   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.4472577874780081E+01   2.6346971459358471E+01   1.1391099079831529E+01  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \natom   1.1736840249586850E+01   2.6907464230346957E+01   1.2589242139810713E+01  H   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00   0.0000000000000000E+00 \nenergy   0.0000000000000000E+00\ncharge   0.0000000000000000E+00\nend\n"
  },
  {
    "path": "examples/nnp-predict/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-predict/H2O_RPBE-D3/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "examples/nnp-predict/H2O_RPBE-D3/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.2539155865352127E+00 a         1     0     1     1     1\n  2.2490365890661286E+00 a         2     0     1     1     2\n  4.9361851928374572E+00 a         3     0     1     1     3\n -2.3971991574908125E+00 a         4     0     1     1     4\n -1.8596992303156465E+00 a         5     0     1     1     5\n  3.8287764168815897E+00 a         6     0     1     1     6\n  7.4523181738636106E+00 a         7     0     1     1     7\n  6.0971861116881998E+00 a         8     0     1     1     8\n -8.7239359226117639E+00 a         9     0     1     1     9\n -1.8255232070184267E+01 a        10     0     1     1    10\n -7.8065643887610179E+00 a        11     0     1     1    11\n  1.4247237398130265E+01 a        12     0     1     1    12\n -3.2217879518334338E+00 a        13     0     1     1    13\n -5.7395252086520712E+00 a        14     0     1     1    14\n  2.0353040522911576E+00 a        15     0     1     1    15\n  7.7520578160630560E+00 a        16     0     1     1    16\n  2.9357257867412252E+00 a        17     0     1     1    17\n -2.9719860930100790E+00 a        18     0     1     1    18\n  8.9245382590288980E+00 a        19     0     1     1    19\n  6.6848134049442169E+00 a        20     0     1     1    20\n -2.2992719903495891E+00 a        21     0     1     1    21\n -1.4401533482181721E+01 a        22     0     1     1    22\n -2.0574070545285186E+00 a        23     0     1     1    23\n -6.3544667277888678E+00 a        24     0     1     1    24\n  3.9668360525851707E+00 a        25     0     1     1    25\n  1.0930597297534963E+01 a        26     0     2     1     1\n  3.0058866618169424E+00 a        27     0     2     1     2\n -4.9950943102999927E+00 a        28     0     2     1     3\n -1.9930957240687266E+00 a        29     0     2     1     4\n  1.6790893133342006E+00 a        30     0     2     1     5\n -4.5254006136507128E+00 a        31     0     2     1     6\n -9.6165021729265252E+00 a        32     0     2     1     7\n -8.7465722730176285E+00 a        33     0     2     1     8\n  1.5506950040431201E+01 a        34     0     2     1     9\n  2.1903342918227118E+01 a        35     0     2     1    10\n -1.0685216745153280E+01 a        36     0     2     1    11\n -2.5859690636594280E+01 a        37     0     2     1    12\n -3.2423603491405122E+00 a        38     0     2     1    13\n  5.3753900550878555E+00 a        39     0     2     1    14\n -3.0291935617567991E+00 a        40     0     2     1    15\n -1.3534893178408465E+01 a        41     0     2     1    16\n -5.7625138055631471E+00 a        42     0     2     1    17\n  1.0216765318459601E+01 a        43     0     2     1    18\n -1.4416012930050949E+01 a        44     0     2     1    19\n -4.7226757471872144E-01 a        45     0     2     1    20\n  7.8981385188798026E+00 a        46     0     2     1    21\n  1.2202710023744410E+00 a        47     0     2     1    22\n  8.0560891210932120E+00 a        48     0     2     1    23\n  4.5972445013263297E-01 a        49     0     2     1    24\n  1.3374237019728858E+01 a        50     0     2     1    25\n -1.0644910441621166E+01 a        51     0     3     1     1\n -5.6098794516515920E+00 a        52     0     3     1     2\n -1.0236653403367724E+01 a        53     0     3     1     3\n  1.3552139405799508E+00 a        54     0     3     1     4\n  1.3201025058567883E+00 a        55     0     3     1     5\n  1.6531266759009673E+00 a        56     0     3     1     6\n -1.0303768926395865E+01 a        57     0     3     1     7\n  1.9927521303470008E-01 a        58     0     3     1     8\n  8.1216226663758366E+00 a        59     0     3     1     9\n  2.1349555016157687E+01 a        60     0     3     1    10\n  1.0105416692705148E+01 a        61     0     3     1    11\n -1.1444993918278378E+01 a        62     0     3     1    12\n  2.9861675555209538E-01 a        63     0     3     1    13\n  9.3552992513120543E+00 a        64     0     3     1    14\n -2.2844869025933630E+00 a        65     0     3     1    15\n -3.8047300595857316E+00 a        66     0     3     1    16\n -3.0512161452147448E+00 a        67     0     3     1    17\n  2.7887340590896472E+00 a        68     0     3     1    18\n -1.5988439945122812E+01 a        69     0     3     1    19\n -1.6917164763280326E+01 a        70     0     3     1    20\n  3.2170907488709326E+00 a        71     0     3     1    21\n  2.1641888770160929E+01 a        72     0     3     1    22\n  3.2604671723420497E+00 a        73     0     3     1    23\n  1.5230689068493776E+01 a        74     0     3     1    24\n -1.4713830039823366E+01 a        75     0     3     1    25\n -2.3544214523969775E+00 a        76     0     4     1     1\n -5.8299691629399382E+00 a        77     0     4     1     2\n  1.7168784391956539E+01 a        78     0     4     1     3\n  1.0050003860864617E+01 a        79     0     4     1     4\n  3.5168903759752812E+00 a        80     0     4     1     5\n -4.4828111046589010E+00 a        81     0     4     1     6\n  1.8299193380051442E+01 a        82     0     4     1     7\n  6.9717289110204188E+00 a        83     0     4     1     8\n -2.0364082994445859E+01 a        84     0     4     1     9\n -3.5062338388300589E+01 a        85     0     4     1    10\n  1.8010375764887119E+01 a        86     0     4     1    11\n  4.2133659287179640E+01 a        87     0     4     1    12\n  1.1988736553417061E+01 a        88     0     4     1    13\n -1.2351529706885179E+01 a        89     0     4     1    14\n  5.4139212296285057E+00 a        90     0     4     1    15\n  1.6705967069968899E+01 a        91     0     4     1    16\n  8.3219076874511639E+00 a        92     0     4     1    17\n -1.8555777504879448E+01 a        93     0     4     1    18\n  3.1433889377775369E+01 a        94     0     4     1    19\n  6.7043459658252780E-01 a        95     0     4     1    20\n -1.3837570456349678E+01 a        96     0     4     1    21\n  5.0298368971353791E-01 a        97     0     4     1    22\n -2.2656240789613065E+01 a        98     0     4     1    23\n -2.4243684644962626E+00 a        99     0     4     1    24\n -2.8280330035212309E+01 a       100     0     4     1    25\n  4.2306100814115322E+00 a       101     0     5     1     1\n  9.9770374716830084E+00 a       102     0     5     1     2\n  2.0487048112933808E+00 a       103     0     5     1     3\n -1.3702212470739978E+00 a       104     0     5     1     4\n  2.8131124422603837E+00 a       105     0     5     1     5\n  3.2845640151619522E-03 a       106     0     5     1     6\n  2.4065616021196026E+00 a       107     0     5     1     7\n -1.0461000723401572E+01 a       108     0     5     1     8\n -1.0180720750329515E+01 a       109     0     5     1     9\n -8.8668996772076660E+00 a       110     0     5     1    10\n  6.5256092481271502E+00 a       111     0     5     1    11\n -6.9831054240027211E+00 a       112     0     5     1    12\n  4.0892074148312876E+00 a       113     0     5     1    13\n -5.1951354450201128E+00 a       114     0     5     1    14\n  1.6657989141753051E+00 a       115     0     5     1    15\n -7.3542511663155619E+00 a       116     0     5     1    16\n  5.1573102842565115E+00 a       117     0     5     1    17\n  3.4929930175122172E+00 a       118     0     5     1    18\n  2.5382184218789963E+00 a       119     0     5     1    19\n  2.0045179007481050E+01 a       120     0     5     1    20\n -1.6165269676512768E+00 a       121     0     5     1    21\n  2.4869117790922393E+00 a       122     0     5     1    22\n  6.0131560843540068E+00 a       123     0     5     1    23\n -1.2231651850388728E+01 a       124     0     5     1    24\n  3.5372450187997345E+01 a       125     0     5     1    25\n -1.0433252604911765E+01 a       126     0     6     1     1\n -2.3715834640656657E+00 a       127     0     6     1     2\n -1.8239608965373137E+01 a       128     0     6     1     3\n -3.6510816169583777E+00 a       129     0     6     1     4\n -1.7632327653119535E+01 a       130     0     6     1     5\n  1.0040509177650593E+01 a       131     0     6     1     6\n -1.5407385349225459E+01 a       132     0     6     1     7\n -7.0553605774310779E-01 a       133     0     6     1     8\n  1.3204892207903583E+01 a       134     0     6     1     9\n  2.9596389655595953E+01 a       135     0     6     1    10\n -2.0620173259628203E+01 a       136     0     6     1    11\n -3.0803380363815094E+01 a       137     0     6     1    12\n -1.4917676387082279E+01 a       138     0     6     1    13\n  9.6935054799166185E+00 a       139     0     6     1    14\n  4.6937319413252743E+00 a       140     0     6     1    15\n -5.0263591258131060E+00 a       141     0     6     1    16\n -9.7243575590712439E+00 a       142     0     6     1    17\n  1.5625340951727363E+01 a       143     0     6     1    18\n -2.8266776356585389E+01 a       144     0     6     1    19\n  2.5386057418612946E+00 a       145     0     6     1    20\n  1.6302330128073283E+01 a       146     0     6     1    21\n -8.5166226512297030E+00 a       147     0     6     1    22\n  2.5040570504752605E+01 a       148     0     6     1    23\n -8.5008658358878897E-01 a       149     0     6     1    24\n  2.0458930574550632E+01 a       150     0     6     1    25\n  7.8529627796707677E+00 a       151     0     7     1     1\n -4.5279242985866821E+00 a       152     0     7     1     2\n  4.7942839133231594E+00 a       153     0     7     1     3\n -6.2431002330064649E+00 a       154     0     7     1     4\n  4.3358077462982054E+00 a       155     0     7     1     5\n -6.8037589596444281E+00 a       156     0     7     1     6\n  1.8980667946224101E+00 a       157     0     7     1     7\n  1.9802532239433695E+01 a       158     0     7     1     8\n  8.4826746941006572E+00 a       159     0     7     1     9\n  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5.1912574126564559E-01 a      1237     1    22     2    12\n -5.9029854481930821E-01 a      1238     1    22     2    13\n -7.2255183403800793E-01 a      1239     1    22     2    14\n  4.1024670935059383E-02 a      1240     1    22     2    15\n  2.0425371936604741E-01 a      1241     1    22     2    16\n -1.0394832812330597E+00 a      1242     1    22     2    17\n  4.7202219372950349E-01 a      1243     1    22     2    18\n -1.9958648332222221E-03 a      1244     1    22     2    19\n -1.4664186611455649E-02 a      1245     1    22     2    20\n  1.0689476163444707E+00 a      1246     1    22     2    21\n  8.4484833020425232E-01 a      1247     1    22     2    22\n -1.4147373614558330E+00 a      1248     1    22     2    23\n  1.9187324467269602E+00 a      1249     1    22     2    24\n  1.5330124676330812E+00 a      1250     1    22     2    25\n  2.3019050197742894E+00 a      1251     1    23     2     1\n -1.3828322911066271E-01 a      1252     1    23     2     2\n -2.3555430378419923E-01 a      1253     1    23     2     3\n -1.3434989779696097E-01 a      1254     1    23     2     4\n  3.7852663531566189E-01 a      1255     1    23     2     5\n  9.8266847359694973E-02 a      1256     1    23     2     6\n  3.2721968443206462E-01 a      1257     1    23     2     7\n -3.7061171550241617E-01 a      1258     1    23     2     8\n  2.2862436245090851E+00 a      1259     1    23     2     9\n  1.7674065728047832E+00 a      1260     1    23     2    10\n -5.2627257197444939E-02 a      1261     1    23     2    11\n  9.4094481148145870E-01 a      1262     1    23     2    12\n  1.0616552648143298E+00 a      1263     1    23     2    13\n -1.6065739188681796E-01 a      1264     1    23     2    14\n  1.6833160475834315E+00 a      1265     1    23     2    15\n -5.5679530352182072E-01 a      1266     1    23     2    16\n  4.2170082515325280E-01 a      1267     1    23     2    17\n  1.8142946234467967E+00 a      1268     1    23     2    18\n -6.0004075552166369E-01 a      1269     1    23     2    19\n  8.6767695096505049E-01 a      1270     1    23     2    20\n  1.7471709925670367E-01 a      1271     1    23     2    21\n  6.3494817986861019E-01 a      1272     1    23     2    22\n  7.9839233743975266E-02 a      1273     1    23     2    23\n -8.7497499907984810E-01 a      1274     1    23     2    24\n -2.1279336414401262E-01 a      1275     1    23     2    25\n -1.0628518357816100E+01 a      1276     1    24     2     1\n -3.4149879843865938E-01 a      1277     1    24     2     2\n -4.0534872173827868E-01 a      1278     1    24     2     3\n  1.0980204380257913E-01 a      1279     1    24     2     4\n  1.8376924276804879E-01 a      1280     1    24     2     5\n  8.5047887536146360E-01 a      1281     1    24     2     6\n  4.3913590571042438E-01 a      1282     1    24     2     7\n  2.7167430357232609E+00 a      1283     1    24     2     8\n  2.9682659556600960E-01 a      1284     1    24     2     9\n -1.6032245851281013E+00 a      1285     1    24     2    10\n -6.7567048640865046E-01 a      1286     1    24     2    11\n -1.5253382251900995E+00 a      1287     1    24     2    12\n -6.7540631566041298E-01 a      1288     1    24     2    13\n -1.4565321192168545E+00 a      1289     1    24     2    14\n -1.3315414628143039E+00 a      1290     1    24     2    15\n  1.2552098425264056E+00 a      1291     1    24     2    16\n -1.1701558601459501E+00 a      1292     1    24     2    17\n  2.1967564647703792E+00 a      1293     1    24     2    18\n  3.6767594091430167E-01 a      1294     1    24     2    19\n  1.4791781996464841E+00 a      1295     1    24     2    20\n -2.4597335939693896E+00 a      1296     1    24     2    21\n  1.8222789722776007E+00 a      1297     1    24     2    22\n -2.4818384588216302E+00 a      1298     1    24     2    23\n -1.3359962912345340E+00 a      1299     1    24     2    24\n -1.6060924344568878E-02 a      1300     1    24     2    25\n -1.1558703878945702E+00 a      1301     1    25     2     1\n  5.5859771317693908E-02 a      1302     1    25     2     2\n -1.9275021348316721E+00 a      1303     1    25     2     3\n  4.2881321046205173E-01 a      1304     1    25     2     4\n  6.6308764508018558E-01 a      1305     1    25     2     5\n -2.5357661809360188E-01 a      1306     1    25     2     6\n  7.7965409617466697E-01 a      1307     1    25     2     7\n -1.9470416731652336E+00 a      1308     1    25     2     8\n  2.0923659915641873E-01 a      1309     1    25     2     9\n  8.9211452410465542E-01 a      1310     1    25     2    10\n -1.9807939822570442E-01 a      1311     1    25     2    11\n -5.0922943173038127E-01 a      1312     1    25     2    12\n  1.3378430979044107E+00 a      1313     1    25     2    13\n -6.8964614083753073E-01 a      1314     1    25     2    14\n  7.6939619343191556E-01 a      1315     1    25     2    15\n -1.5783243312480257E+00 a      1316     1    25     2    16\n  2.3586020281744577E+00 a      1317     1    25     2    17\n -5.1641666185758928E-01 a      1318     1    25     2    18\n  1.0291540870545792E+00 a      1319     1    25     2    19\n  1.5269830348487650E+00 a      1320     1    25     2    20\n -2.8987700591417855E+00 a      1321     1    25     2    21\n  9.0207337792476916E-01 a      1322     1    25     2    22\n  1.9890049402284911E+00 a      1323     1    25     2    23\n  3.9387622927433424E-01 a      1324     1    25     2    24\n  9.9397126232482103E-01 a      1325     1    25     2    25\n  2.5306467041996967E+00 b      1326     2     1\n  3.1633393474977245E+00 b      1327     2     2\n -1.1644295509710691E+00 b      1328     2     3\n -5.7686722641223600E+00 b      1329     2     4\n  2.0065022303893989E+00 b      1330     2     5\n -5.9106057000795840E+00 b      1331     2     6\n -1.1326093285804056E+01 b      1332     2     7\n -3.9025063397327071E+00 b      1333     2     8\n  4.4520505166676267E+00 b      1334     2     9\n -1.7352681951318241E+00 b      1335     2    10\n -2.1518912430432668E+00 b      1336     2    11\n  5.0463376560082969E+00 b      1337     2    12\n -2.2614514173852837E-01 b      1338     2    13\n -4.1454590614747211E+00 b      1339     2    14\n  1.6688417293495756E+00 b      1340     2    15\n -5.8649976938793378E+00 b      1341     2    16\n -3.8350084459541849E+00 b      1342     2    17\n  1.3730477223722950E+00 b      1343     2    18\n  1.8506935712854127E+00 b      1344     2    19\n  5.7362757779153428E+00 b      1345     2    20\n  7.2901484895568780E+00 b      1346     2    21\n  3.9773783666446022E-01 b      1347     2    22\n -6.1298011242151409E+00 b      1348     2    23\n  9.9698755072742991E+00 b      1349     2    24\n  1.1801564149295556E+00 b      1350     2    25\n  1.2704098997067026E+01 a      1351     2     1     3     1\n  1.5947733940307620E+00 a      1352     2     2     3     1\n -1.6022927057878529E+00 a      1353     2     3     3     1\n -1.5507258540777733E+00 a      1354     2     4     3     1\n  1.8696884022727636E+00 a      1355     2     5     3     1\n -8.2051908880071633E-01 a      1356     2     6     3     1\n  9.4325719092522542E-01 a      1357     2     7     3     1\n  2.4098435369626174E+00 a      1358     2     8     3     1\n  1.4100759633042474E+00 a      1359     2     9     3     1\n -1.4613034838529613E+00 a      1360     2    10     3     1\n  1.0296574685193380E+00 a      1361     2    11     3     1\n  1.2413851904356363E+00 a      1362     2    12     3     1\n -6.3168181712211169E-01 a      1363     2    13     3     1\n  7.6424175125347729E+00 a      1364     2    14     3     1\n -1.3477038299214714E+00 a      1365     2    15     3     1\n -1.6064659765754943E+00 a      1366     2    16     3     1\n -8.9624380518145874E-01 a      1367     2    17     3     1\n -1.0509865792522375E+00 a      1368     2    18     3     1\n  8.1847872933853638E-01 a      1369     2    19     3     1\n  1.2845504810303034E+00 a      1370     2    20     3     1\n -5.1879822944368881E-01 a      1371     2    21     3     1\n -7.2018714033119180E-01 a      1372     2    22     3     1\n  5.9870832883780798E+00 a      1373     2    23     3     1\n -6.0589155387470683E-01 a      1374     2    24     3     1\n  5.0177609140285355E+00 a      1375     2    25     3     1\n  9.7386086372975722E+00 b      1376     3     1\n"
  },
  {
    "path": "examples/nnp-predict/H2O_RPBE-D3/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -4.2252995889643252E-01 a         1     0     1     1     1\n -6.0555645962054347E+00 a         2     0     1     1     2\n  1.4040722027928377E+01 a         3     0     1     1     3\n -2.7041370011942618E+00 a         4     0     1     1     4\n -3.8202743208058858E+00 a         5     0     1     1     5\n -3.3612643261393358E+00 a         6     0     1     1     6\n -2.0418101025905258E+00 a         7     0     1     1     7\n  7.5707237340996727E+00 a         8     0     1     1     8\n -5.8098755815926548E+00 a         9     0     1     1     9\n -6.0966886893925210E-01 a        10     0     1     1    10\n  5.8061564015115206E+00 a        11     0     1     1    11\n -1.5509339733099867E+00 a        12     0     1     1    12\n  1.9747395485200818E+00 a        13     0     1     1    13\n  4.5260782279680539E-01 a        14     0     1     1    14\n  9.9210415760283279E+00 a        15     0     1     1    15\n -6.5078831481547121E+00 a        16     0     1     1    16\n -3.4768832871318085E+00 a        17     0     1     1    17\n -1.9463994340943838E+00 a        18     0     1     1    18\n -3.4186058699290269E+00 a        19     0     1     1    19\n  1.2263643166698479E+00 a        20     0     1     1    20\n -5.9171161834436594E+00 a        21     0     1     1    21\n  1.8436267358458363E+00 a        22     0     1     1    22\n -2.3139530616378448E+00 a        23     0     1     1    23\n -1.7228542411478951E+01 a        24     0     1     1    24\n  2.2888610253215895E+00 a        25     0     1     1    25\n  8.0819405565169262E+00 a        26     0     2     1     1\n  8.0066409422078735E+00 a        27     0     2     1     2\n -2.8439251469462398E+01 a        28     0     2     1     3\n -1.1146087290797917E+01 a        29     0     2     1     4\n -7.5292172093563314E+00 a        30     0     2     1     5\n -4.0783685663337641E+00 a        31     0     2     1     6\n -4.4130406528599337E+00 a        32     0     2     1     7\n  1.0563249167508673E+01 a        33     0     2     1     8\n  1.0933105521974941E+01 a        34     0     2     1     9\n -1.1646509907117448E+01 a        35     0     2     1    10\n -7.5007478428041727E+00 a        36     0     2     1    11\n  7.7790182254249176E+00 a        37     0     2     1    12\n  1.1567034492555623E+01 a        38     0     2     1    13\n -4.2051741520233508E+00 a        39     0     2     1    14\n  3.1165306119132130E+00 a        40     0     2     1    15\n  1.6385645103485370E+01 a        41     0     2     1    16\n  2.6440539124381655E+00 a        42     0     2     1    17\n -3.9524518111687827E+00 a        43     0     2     1    18\n -8.7912410635652076E+00 a        44     0     2     1    19\n  4.3903318583813933E+00 a        45     0     2     1    20\n  3.3748047065442632E-01 a        46     0     2     1    21\n -6.6858946327311741E-01 a        47     0     2     1    22\n  5.4447187026310928E+00 a        48     0     2     1    23\n  1.9966018946508100E+01 a        49     0     2     1    24\n -1.7414420670154115E+01 a        50     0     2     1    25\n -3.9418657694849879E-01 a        51     0     3     1     1\n  9.1804829174186846E+00 a        52     0     3     1     2\n -1.0485089041850278E+01 a        53     0     3     1     3\n  8.9380499555048889E+00 a        54     0     3     1     4\n  1.0758607876097068E+01 a        55     0     3     1     5\n  7.2881492125393788E+00 a        56     0     3     1     6\n  8.2627077997774609E+00 a        57     0     3     1     7\n -1.2523613158520124E+01 a        58     0     3     1     8\n  4.5963999046141870E+00 a        59     0     3     1     9\n  8.2776469521184293E+00 a        60     0     3     1    10\n -2.1354371687617113E+00 a        61     0     3     1    11\n -9.0381751821938234E+00 a        62     0     3     1    12\n -1.2209592338152297E+00 a        63     0     3     1    13\n  4.7653671372245672E+00 a        64     0     3     1    14\n -1.7909124818088952E+01 a        65     0     3     1    15\n  3.2182917515973237E+00 a        66     0     3     1    16\n -2.3712750109800793E+00 a        67     0     3     1    17\n  4.6394007836500366E+00 a        68     0     3     1    18\n  2.3761984937954490E+00 a        69     0     3     1    19\n -1.0484832585147684E+01 a        70     0     3     1    20\n  1.2317970755621140E+01 a        71     0     3     1    21\n -1.5014054499447769E+00 a        72     0     3     1    22\n -1.1215435083480425E+00 a        73     0     3     1    23\n  8.9428653321614355E+00 a        74     0     3     1    24\n  1.2636165742848842E+00 a        75     0     3     1    25\n -1.3406492086741725E+01 a        76     0     4     1     1\n -1.0241053204283523E+01 a        77     0     4     1     2\n  4.3016369326050899E+01 a        78     0     4     1     3\n  2.0170433813810671E+01 a        79     0     4     1     4\n  1.3209328101408278E+01 a        80     0     4     1     5\n  1.2456789467161695E+01 a        81     0     4     1     6\n  4.3498515722861573E+00 a        82     0     4     1     7\n -2.1948185511490657E+01 a        83     0     4     1     8\n -1.5329558038416376E+01 a        84     0     4     1     9\n  1.4173337432869845E+01 a        85     0     4     1    10\n  5.6040631650516088E+00 a        86     0     4     1    11\n -9.7646834958548663E+00 a        87     0     4     1    12\n -1.3810669587629080E+01 a        88     0     4     1    13\n -1.5274915717855073E+00 a        89     0     4     1    14\n -1.3662043326477198E+01 a        90     0     4     1    15\n -2.5095635769057225E+01 a        91     0     4     1    16\n  5.4033548590960638E+00 a        92     0     4     1    17\n  1.1047593171711565E+01 a        93     0     4     1    18\n  1.9404912122904062E+01 a        94     0     4     1    19\n  2.4043652449872512E+00 a        95     0     4     1    20\n -3.3818087825635010E+00 a        96     0     4     1    21\n -4.9505657938825802E+00 a        97     0     4     1    22\n  6.2159614529590854E+00 a        98     0     4     1    23\n -1.9315299866781363E+01 a        99     0     4     1    24\n  2.4149549923763363E+01 a       100     0     4     1    25\n  2.2633190213689671E+00 a       101     0     5     1     1\n -1.1275056403465689E+01 a       102     0     5     1     2\n  1.2588751117785917E+00 a       103     0     5     1     3\n -1.7399288116611554E+01 a       104     0     5     1     4\n -1.8915392010979964E+01 a       105     0     5     1     5\n -6.5088880348621911E+00 a       106     0     5     1     6\n -8.7022768117985532E+00 a       107     0     5     1     7\n  9.5716939158219958E+00 a       108     0     5     1     8\n  6.7173652175539926E+00 a       109     0     5     1     9\n -1.0675975211687946E+01 a       110     0     5     1    10\n -9.8676303718126039E+00 a       111     0     5     1    11\n  2.2213929552875065E+01 a       112     0     5     1    12\n -3.9036053816020080E+00 a       113     0     5     1    13\n -1.0319098765495239E+01 a       114     0     5     1    14\n  2.0443220229254024E+01 a       115     0     5     1    15\n -1.4108663925115768E+00 a       116     0     5     1    16\n  8.2741724462704607E+00 a       117     0     5     1    17\n -5.3497533478370061E+00 a       118     0     5     1    18\n  1.0188467515179238E+00 a       119     0     5     1    19\n  3.3447636806848529E+00 a       120     0     5     1    20\n -6.3209134939668381E+00 a       121     0     5     1    21\n  7.0841649292282804E+00 a       122     0     5     1    22\n -1.3545092924552248E+01 a       123     0     5     1    23\n -1.0559922896741500E+00 a       124     0     5     1    24\n -1.6720809451360648E+00 a       125     0     5     1    25\n  2.8772403595811382E+00 a       126     0     6     1     1\n  6.6056181351338488E+00 a       127     0     6     1     2\n 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  {
    "path": "examples/nnp-predict/H2O_RPBE-D3_4G/input.nn",
    "content": "################################################################\n### This is the input file for n2p2\n### It contains only a subset of all keywords\n#################################################################\n\n################################################################################\n### general keywords\n################################################################################\n\nnnp_generation 4\nuse_short_forces\n\nnumber_of_elements 2\nelements H O\n\ninitial_hardness        H        10.0\ninitial_hardness        O        10.0\n\nfixed_gausswidth  H 0.5858120110359424\nfixed_gausswidth  O 1.2491023848218\n\n\nscreen_electrostatics 4.8 12.0\n\nrandom_seed 12346\n\newald_truncation_error_method 1\newald_prec 1.e-5 0.36\nfour_pi_epsilon 1.0                             # Value of 4*pi*epsilon (1/Coulomb constant)\n\n################################################################################\n### NN structure of the short-range NN\n################################################################################\nglobal_hidden_layers_short 2\nglobal_nodes_short 25 25\nglobal_activation_short t t l\n\n################################################################################\n### NN structure of the electrostatic NN\n################################################################################\nglobal_hidden_layers_electrostatic 2\nglobal_nodes_electrostatic 25 25\nglobal_activation_electrostatic t t l\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (General)\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10              # Number of training epochs.\nupdater_type                    1               # Weight update method\n                                                # (0 = Gradient Descent,\n                                                # 1 = Kalman filter).\nparallel_mode                   1               # Training parallelization used\n                                                # (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1               # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0               # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2               # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\n#memorize_symfunc_results                       # Keep symmetry function results in memory.\nrmse_threshold_trials           4               # Maximum number of RMSE threshold trials.\nmain_error_metric               RMSEpa          # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\ntest_fraction                   0.1             # Fraction of structures kept for testing.\nweights_min                     -1.0            # Minimum value for initial random weights.\nweights_max                     1.0             # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\nwrite_weights_epoch             10              # Write weights every this many epochs.\nscale_symmetry_functions\ncenter_symmetry_functions\n#write_neuronstats               1              # Write neuron statistics every this many epochs.\n#write_trainlog                                 # Write training log file.\n\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (charges, stage 1)\n################################################################################\ntask_batch_size_charge          1\n#nguyen_widrow_weights_charge                   # Initialize neural network weights according to Nguyen-Widrow scheme.\ncharge_fraction                 1.000\n#write_traincharges              1              # Write charge comparison. Can produce large files.\n#use_old_weights_charge                         # Restart fitting with old weight parameters.\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (short-range, stage 2)\n################################################################################\ntask_batch_size_energy          1               # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1               # Number of force update candidates prepared per task for each update (0 = Entire training set).\nforce_weight                    10.0            # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000           # Fraction of energy updates per epoch.\nshort_force_fraction            0.025           # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.80            # RMSE threshold for energy update candidates.\nshort_force_error_threshold     0.80            # RMSE threshold for force update candidates.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\n#repeated_energy_update\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\n#write_trainpoints               1              # Write energy comparison every this many epochs.\n#write_trainforces               1              # Write force comparison every this many epochs.\n\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# These two parameters are only used if \"updater_type\" is \"1\".\n#kalman_lambda_short 0.98000\n#kalman_nue_short 0.99870\n\nkalman_type                     0               # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2          # General Kalman filter parameter epsilon, covariance matrix initialization (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01            # General Kalman filter parameter q0, initial process noise (\"large\").\nkalman_qtau                     2.302           # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6          # General Kalman filter parameter qmin, final process noise (typ. 1.0E-6).\nkalman_eta                      0.01            # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302           # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   0.500           # Standard Kalman filter parameter etamax (1.0+).\n\n\n################################################################################\n### symmetry function definitions (all modes):\n################################################################################\ncutoff_type 2\n\n#radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-predict/H2O_RPBE-D3_4G/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170768E+00   9.6166419119419100E+00   2.2691752247542198E+00   6.7883526611658851E-01\n         1          2   7.3274438904180605E-01   5.0028559321574226E+00   1.3272332317543585E+00   3.3936750181780473E-01\n         1          3   7.6010783783215707E-01   7.1427942966219833E+00   1.6470726712825299E+00   5.0771115927384247E-01\n         1          4   5.4842285884800812E-01   3.7661771168267748E+00   1.0163698211361722E+00   2.5362958053787693E-01\n         1          5   4.0080665126604670E-01   4.1469832401668647E+00   9.0925040981537886E-01   2.9758019277508418E-01\n         1          6   3.6209352253798222E-01   2.2678239402766063E+00   6.4931154122889645E-01   1.4835420345383105E-01\n         1          7   1.8919103878435906E-01   2.2292652677252813E+00   4.5693857051003844E-01   1.5976079618578098E-01\n         1          8   2.6704178695764291E-01   1.3208742362468950E+00   4.2395636902644862E-01   8.0492394978464013E-02\n         1          9   2.4513099752055154E-01   9.4751160662053036E-01   3.6244199023263701E-01   5.2993540556106881E-02\n         1         10   2.2248910067848979E-01   2.7596216013647377E+00   5.3891576898130733E-01   2.0137334230483903E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910822E-01   2.6188094566404644E-02\n         1         12   9.9110926426029297E-02   1.7265405335201476E+00   2.9553976311554875E-01   1.1619768775752870E-01\n         1         13   6.5093699123904183E-02   3.4521757733971209E-01   1.8521249136783141E-01   1.9741155185936082E-02\n         1         14   3.1653527247864993E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038543E-02\n         1         15   2.9202821602466629E-03   2.6453981776124164E-01   7.6525296616004670E-02   1.8780956137549890E-02\n         1         16   3.2145385719803426E-04   2.8696425565429251E-01   4.5792284631233637E-02   2.3263495133569036E-02\n         1         17   2.4693757528509687E-04   1.3848731138266307E-01   1.7693289653297618E-02   9.7460303038080891E-03\n         1         18   5.0992836797990751E-03   5.8319173651547451E-01   2.3851656540978417E-02   3.7790771891778180E-02\n         1         19   3.2282960174310137E-04   2.1613962298381934E-01   1.7072560754702336E-02   1.4026518665786074E-02\n         1         20   4.9647513277769798E-02   1.6851617426880205E+00   1.4541325969622548E-01   1.0954306125703019E-01\n         1         21   3.4073471604482279E-03   3.1637071808861694E-01   1.8422597685566731E-02   2.0125274191649705E-02\n         1         22   1.3121382132811758E-04   1.0258348935693717E-01   6.3684016949344113E-03   6.6071626858835008E-03\n         1         23   3.3813162813665920E-02   9.1618560879938959E-01   8.1266384503339659E-02   5.7918502576695619E-02\n         1         24   4.1708500446352941E-04   1.5785966980407004E-01   4.6646981268568680E-03   9.8630700614506534E-03\n         1         25   7.3528900917695659E-04   5.9225627251013005E-02   3.7042174075139775E-03   3.3118079036492604E-03\n         1         26   8.9828333062972488E-03   1.9426085555380748E-01   2.4093377110646314E-02   1.0980657457661641E-02\n         1         27   2.1228022180417680E-04   8.7777813240869623E-03   2.0550705761547975E-03   5.8802103858137062E-04\n         2          1   1.5142595331454249E+00   1.0005711988560002E+01   2.6544664635087183E+00   6.7806617585689344E-01\n         2          2   4.4366445360926210E-01   4.6195409357987094E+00   9.6587051599896079E-01   3.3688559575009175E-01\n         2          3   1.1907810568758721E+00   7.5323544094345012E+00   2.0327396422723472E+00   5.0607867531004291E-01\n         2          4   2.7576036468694687E-01   3.3862131032504497E+00   6.5929732667024821E-01   2.5004687333979797E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577938E+00   2.9449908325462504E-01\n         2          6   1.0517053799863607E-01   1.8909877539194522E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859717E-01   2.6154328621607861E+00   8.4791273805289535E-01   1.5714071578589722E-01\n         2          8   2.3251646720171409E-02   9.3641034200657891E-01   1.1140979781150938E-01   6.9796654369842920E-02\n         2          9   5.1354161698115453E-01   1.8545341781448568E+00   7.2488398046527269E-01   9.8011511620610281E-02\n         2         10   1.1057465545812288E-01   2.9121456897811355E+00   4.7474421797982730E-01   2.3441807910092263E-01\n         2         11   3.5269317308496512E-01   1.0714592032613126E+00   5.3547944391821689E-01   4.5179661104164701E-02\n         2         12   3.0424313539726335E-02   2.5277642768509310E+00   3.1652845366685034E-01   2.1026891409654727E-01\n         2         13   1.5980022688828249E-01   6.6348817066386478E-01   3.7042498273566316E-01   3.0753700953609124E-02\n         2         14   2.7781847150922792E-03   2.3030057819082543E+00   1.7737800292869685E-01   1.8600239464755822E-01\n         2         15   9.5641036809350141E-03   3.9085233064570801E-01   1.5305059323200967E-01   2.7862233984302306E-02\n         2         16   3.7500170432291853E-06   2.0367068825281995E+00   5.4144316535640356E-02   1.4305857218443541E-01\n         2         17   2.4726232100491102E-03   3.4335400617385059E-01   1.6684597803376656E-02   2.1902951351570873E-02\n         2         18   1.7405672406959621E-05   5.6319316766205323E-02   9.5478184601751812E-04   3.3588039002222379E-03\n         2         19   5.4785372164648002E-02   3.0182597583971473E+00   2.0392031625072374E-01   2.0088721011517160E-01\n         2         20   1.3795234987637444E-03   4.9878800454061345E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814470E-03   2.6739582842775922E-01   3.0851859894574375E-02   1.7089886758420002E-02\n         2         22   1.7021399438214367E-02   1.4167796508898465E+00   7.6274174813506776E-02   9.2852504206357725E-02\n         2         23   1.9759831791959889E-02   4.0756378297923918E-01   4.8843503112397928E-02   2.5474332458885442E-02\n         2         24   5.2768632746659277E-04   2.3324050667069179E-01   7.2057238727819490E-03   1.4495435261027756E-02\n         2         25   1.1144879740881774E-05   3.5285772934088605E-02   4.2545240948261046E-04   2.0471375111486014E-03\n         2         26   1.6013752685265070E-02   8.2245409953473070E-01   5.0845479076508424E-02   5.2802834522172978E-02\n         2         27   3.9898424495541755E-03   7.8557031440100333E-01   3.6926675414383131E-02   5.0474458307624807E-02\n         2         28   4.0523818189746801E-05   9.8448068666706065E-02   1.2119235889230273E-03   5.7945700128174682E-03\n         2         29   6.0374649986214670E-03   9.9251766407842473E-02   1.6156539248049703E-02   5.5245068674135544E-03\n         2         30   2.9595491075765702E-03   1.5478537567691847E-01   1.1641055270110558E-02   8.9415193910804582E-03\n"
  },
  {
    "path": "examples/nnp-predict/H2O_RPBE-D3_4G/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -1.3579533059871329E+00 a         1     0     1     1     1\n -1.0270142525820705E+00 a         2     0     1     1     2\n  7.6059182570761896E-01 a         3     0     1     1     3\n  2.2236470657725857E-01 a         4     0     1     1     4\n -3.8566398157431792E-02 a         5     0     1     1     5\n  2.9862291948442882E-01 a         6     0     1     1     6\n  3.1318545547641169E-01 a         7     0     1     1     7\n -1.5988297714557185E+00 a         8     0     1     1     8\n  1.2724570711276795E-01 a         9     0     1     1     9\n  2.6381738234998131E-01 a        10     0     1     1    10\n -2.6763137941599534E-02 a        11     0     1     1    11\n -1.0234955022594629E-01 a        12     0     1     1    12\n -3.7565966844004972E-01 a        13     0     1     1    13\n  1.3778496063099630E+00 a        14     0     1     1    14\n -7.9164887427893016E-01 a        15     0     1     1    15\n  1.0380076236714839E+00 a        16     0     1     1    16\n  1.4905037331079694E+00 a        17     0     1     1    17\n  8.0314864288343546E-01 a        18     0     1     1    18\n  8.0579523528468722E-01 a        19     0     1     1    19\n -1.2151222957934904E+00 a        20     0     1     1    20\n -7.3546966764841537E-01 a        21     0     1     1    21\n -1.2491799699253334E+00 a        22     0     1     1    22\n  1.8013916923568937E-01 a        23     0     1     1    23\n -7.1908594492107791E-02 a        24     0     1     1    24\n -2.4144386249506156E-01 a        25     0     1     1    25\n  1.9580363382997734E+00 a        26     0     2     1     1\n -1.7054276333917524E+00 a        27     0     2     1     2\n -6.2947609519212011E-01 a        28     0     2     1     3\n  2.5657381959095421E-01 a        29     0     2     1     4\n  3.5478089717920808E-01 a        30     0     2     1     5\n -1.1532661899873311E+00 a        31     0     2     1     6\n -4.8321860879869222E-01 a        32     0     2     1     7\n  1.3346786647673037E+00 a        33     0     2     1     8\n  2.3902986109278632E-01 a        34     0     2     1     9\n  6.0734785190989092E-02 a        35     0     2     1    10\n  7.9212947574471193E-01 a        36     0     2     1    11\n -1.5039838199368552E-01 a        37     0     2     1    12\n  7.0897572159410574E-02 a        38     0     2     1    13\n -1.3746834517347228E+00 a        39     0     2     1    14\n  4.0995913074676182E-01 a        40     0     2     1    15\n -7.9209759488593479E-01 a        41     0     2     1    16\n -3.4334827872267626E-01 a        42     0     2     1    17\n -6.8117205329419173E-01 a        43     0     2     1    18\n -1.6184267295701815E+00 a        44     0     2     1    19\n -1.9878901960054121E-01 a        45     0     2     1    20\n  1.2702693383560040E-01 a        46     0     2     1    21\n -2.4744823207720310E-01 a        47     0     2     1    22\n  2.3915158603540110E-01 a        48     0     2     1    23\n  6.3452698343367009E-01 a        49     0     2     1    24\n -2.1701756137729070E-01 a        50     0     2     1    25\n -2.9893430977183999E-01 a        51     0     3     1     1\n -1.7224435543210750E-01 a        52     0     3     1     2\n  5.3527038643161787E-02 a        53     0     3     1     3\n  7.7551951916332462E-01 a        54     0     3     1     4\n  7.6383914143427680E-03 a        55     0     3     1     5\n -3.6331823623896331E-01 a        56     0     3     1     6\n  6.1919407458410103E-01 a        57     0     3     1     7\n  2.2175010437554596E+00 a        58     0     3     1     8\n -3.0228645804321946E-01 a        59     0     3     1     9\n  8.2612933256858545E-01 a        60     0     3     1    10\n  6.3921683099827473E-02 a        61     0     3     1    11\n  1.6498841269912204E-01 a        62     0     3     1    12\n  1.0525000056463365E+00 a        63     0     3     1    13\n 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4.8845826492838795E-01 a      1157     1    18     2     7\n -3.9714562529975450E-01 a      1158     1    18     2     8\n  4.2125218090334604E-01 a      1159     1    18     2     9\n -6.7300204517786177E-01 a      1160     1    18     2    10\n -4.7343506320260875E-01 a      1161     1    18     2    11\n -2.2596591947743317E-02 a      1162     1    18     2    12\n  2.6547553196924523E-01 a      1163     1    18     2    13\n -7.4763791190472884E-01 a      1164     1    18     2    14\n  2.2702038402878286E-01 a      1165     1    18     2    15\n -9.7624431982398552E-01 a      1166     1    18     2    16\n -1.6370502663828548E-01 a      1167     1    18     2    17\n -1.5721973032881004E-01 a      1168     1    18     2    18\n  2.8824794369582007E-01 a      1169     1    18     2    19\n  4.2330054377380838E-01 a      1170     1    18     2    20\n  2.4383499753782098E-01 a      1171     1    18     2    21\n -7.4801694516068429E-01 a      1172     1    18     2    22\n -6.5840546980000580E-01 a      1173     1    18     2    23\n  1.2427091713714903E-02 a      1174     1    18     2    24\n -6.2763704186516911E-01 a      1175     1    18     2    25\n  2.2370760859554592E-01 a      1176     1    19     2     1\n  1.0058070913621044E-02 a      1177     1    19     2     2\n -4.7097248297818339E-01 a      1178     1    19     2     3\n -7.2316450642597938E-02 a      1179     1    19     2     4\n  1.6497402549415874E-01 a      1180     1    19     2     5\n  9.6018725480158010E-02 a      1181     1    19     2     6\n -4.0709830882055903E-01 a      1182     1    19     2     7\n  1.4231840449709651E-01 a      1183     1    19     2     8\n  8.7982765721726841E-01 a      1184     1    19     2     9\n -1.7568700166639678E-01 a      1185     1    19     2    10\n  2.7887582794018806E-01 a      1186     1    19     2    11\n -3.5615647695955363E-02 a      1187     1    19     2    12\n -2.6955687404923317E-01 a      1188     1    19     2    13\n -3.8608133858919375E-01 a      1189     1    19     2    14\n  2.4455585789787720E-01 a      1190     1    19     2    15\n  1.2872676212589945E-01 a      1191     1    19     2    16\n  2.1592048712400717E-02 a      1192     1    19     2    17\n  6.2899724378455424E-01 a      1193     1    19     2    18\n  2.5395758142681307E-01 a      1194     1    19     2    19\n  1.3968030378271523E-02 a      1195     1    19     2    20\n -2.4931342054779818E-01 a      1196     1    19     2    21\n -2.2364413006951611E-01 a      1197     1    19     2    22\n -2.7465382685842804E-01 a      1198     1    19     2    23\n  1.8849991103516689E-01 a      1199     1    19     2    24\n  9.1535686174808162E-01 a      1200     1    19     2    25\n  6.0699758429500926E-03 a      1201     1    20     2     1\n  4.5664705907304637E-01 a      1202     1    20     2     2\n -2.2428060779760978E-01 a      1203     1    20     2     3\n  2.8588265157234516E-01 a      1204     1    20     2     4\n  5.8347622262670880E-02 a      1205     1    20     2     5\n  8.1546924912823532E-02 a      1206     1    20     2     6\n  1.6040145090224711E-01 a      1207     1    20     2     7\n -5.2690838258132278E-01 a      1208     1    20     2     8\n  1.5238102332824907E-01 a      1209     1    20     2     9\n -1.9673688073688006E-01 a      1210     1    20     2    10\n  5.6579620111177176E-01 a      1211     1    20     2    11\n -8.2264233067402076E-02 a      1212     1    20     2    12\n -3.1596190763489990E-01 a      1213     1    20     2    13\n -7.5428247741821830E-02 a      1214     1    20     2    14\n -3.4640533100084187E-01 a      1215     1    20     2    15\n -6.8377628085333417E-02 a      1216     1    20     2    16\n  4.1094683222624034E-01 a      1217     1    20     2    17\n -1.6747268212716063E-01 a      1218     1    20     2    18\n  4.3420392954311099E-01 a      1219     1    20     2    19\n -3.4048242722452071E-01 a      1220     1    20     2    20\n  1.5453477893149101E-01 a      1221     1    20     2    21\n  2.8002348439138397E-01 a      1222     1    20     2    22\n -7.5337718523896469E-01 a      1223     1    20     2    23\n  1.9678562159433727E-01 a      1224     1    20     2    24\n -6.1497435038362680E-01 a      1225     1    20     2    25\n  9.7394488680156399E-01 a      1226     1    21     2     1\n -1.9777549751469675E-01 a      1227     1    21     2     2\n  6.1318886499506209E-01 a      1228     1    21     2     3\n  9.6306278426559921E-01 a      1229     1    21     2     4\n -1.7791630314538820E-01 a      1230     1    21     2     5\n -5.6418431607192976E-01 a      1231     1    21     2     6\n -2.7825401626400514E-01 a      1232     1    21     2     7\n  7.6609803256463049E-01 a      1233     1    21     2     8\n -2.2727765564625463E-01 a      1234     1    21     2     9\n  1.0352967362767000E+00 a      1235     1    21     2    10\n -1.8474239851654117E-01 a      1236     1    21     2    11\n -8.6306613495307238E-01 a      1237     1    21     2    12\n  5.3061331463622952E-01 a      1238     1    21     2    13\n -3.7006634412895628E-01 a      1239     1    21     2    14\n -2.6933514889664562E-01 a      1240     1    21     2    15\n  4.8439259295964371E-01 a      1241     1    21     2    16\n  2.4471281569845274E-01 a      1242     1    21     2    17\n -1.2105980517155721E+00 a      1243     1    21     2    18\n  3.7861373721198466E-01 a      1244     1    21     2    19\n  2.6149266982272178E-02 a      1245     1    21     2    20\n  8.0534549803372213E-01 a      1246     1    21     2    21\n -2.4452138679702048E-01 a      1247     1    21     2    22\n -3.5226130399192046E-01 a      1248     1    21     2    23\n -1.3315368523161900E-01 a      1249     1    21     2    24\n -2.1250623876782243E-01 a      1250     1    21     2    25\n  8.4094607405580474E-02 a      1251     1    22     2     1\n -5.4681038925969871E-01 a      1252     1    22     2     2\n  1.8973344218768315E-01 a      1253     1    22     2     3\n -1.7853121005719865E-02 a      1254     1    22     2     4\n  1.8611444464076723E-01 a      1255     1    22     2     5\n  4.7849176059744647E-01 a      1256     1    22     2     6\n  4.1133749807267550E-01 a      1257     1    22     2     7\n  2.8606108284110260E-03 a      1258     1    22     2     8\n -8.0827371106961338E-02 a      1259     1    22     2     9\n -1.1858987833056625E-01 a      1260     1    22     2    10\n  2.5535764334370548E-01 a      1261     1    22     2    11\n -3.7022535448648375E-01 a      1262     1    22     2    12\n  3.0201236360436684E-01 a      1263     1    22     2    13\n  6.0759905243394874E-01 a      1264     1    22     2    14\n  3.0020117354634876E-02 a      1265     1    22     2    15\n -2.1512271598036731E-01 a      1266     1    22     2    16\n  7.5088782371369289E-02 a      1267     1    22     2    17\n -5.7551743597658543E-02 a      1268     1    22     2    18\n -1.2129894401759753E-01 a      1269     1    22     2    19\n  2.5059650328311694E-01 a      1270     1    22     2    20\n -1.3758878788224682E-01 a      1271     1    22     2    21\n  3.9077302028605092E-02 a      1272     1    22     2    22\n -4.8038530894576031E-01 a      1273     1    22     2    23\n  1.5775336432260503E-02 a      1274     1    22     2    24\n -2.0721875145781549E-01 a      1275     1    22     2    25\n -1.2243231500227254E-01 a      1276     1    23     2     1\n -8.6050263808684202E-01 a      1277     1    23     2     2\n  1.0777019755747727E-02 a      1278     1    23     2     3\n  2.4491420760091379E-01 a      1279     1    23     2     4\n -4.7062680984719496E-01 a      1280     1    23     2     5\n -4.5016626850063790E-01 a      1281     1    23     2     6\n  7.3033008218945128E-01 a      1282     1    23     2     7\n  6.8601371325457172E-01 a      1283     1    23     2     8\n  4.1181402934896921E-01 a      1284     1    23     2     9\n  4.3170942633322724E-02 a      1285     1    23     2    10\n  2.9068300108686584E-01 a      1286     1    23     2    11\n -5.7363319699415949E-01 a      1287     1    23     2    12\n  1.9570102481123386E-01 a      1288     1    23     2    13\n  3.6742375878715799E-01 a      1289     1    23     2    14\n -1.7706207522341069E-01 a      1290     1    23     2    15\n  1.0324473789953412E+00 a      1291     1    23     2    16\n -8.1897373271229879E-01 a      1292     1    23     2    17\n -1.2111002488781659E+00 a      1293     1    23     2    18\n  7.5076816823410886E-01 a      1294     1    23     2    19\n  2.2883227767759240E-01 a      1295     1    23     2    20\n  2.6206049049427994E-03 a      1296     1    23     2    21\n  2.7018909870127672E-01 a      1297     1    23     2    22\n -1.0237763833381774E+00 a      1298     1    23     2    23\n  1.3179301889845499E-01 a      1299     1    23     2    24\n  2.5871135426235103E-01 a      1300     1    23     2    25\n -1.7040986096411587E-01 a      1301     1    24     2     1\n -3.7324805049729076E-01 a      1302     1    24     2     2\n  2.4006516876295803E-01 a      1303     1    24     2     3\n -4.9096311184924990E-01 a      1304     1    24     2     4\n  1.6863705210527388E-01 a      1305     1    24     2     5\n  2.5469557506599505E-01 a      1306     1    24     2     6\n  4.4670082683274825E-01 a      1307     1    24     2     7\n -5.0081922256471434E-01 a      1308     1    24     2     8\n  5.2375132328212326E-01 a      1309     1    24     2     9\n -3.0908958634923445E-01 a      1310     1    24     2    10\n  1.4432949732291181E-01 a      1311     1    24     2    11\n -1.6932651695473208E-01 a      1312     1    24     2    12\n -7.8037669553592481E-02 a      1313     1    24     2    13\n  4.8041574626565736E-01 a      1314     1    24     2    14\n -2.4720227677513293E-01 a      1315     1    24     2    15\n  3.3731060168627253E-01 a      1316     1    24     2    16\n -1.4161038387639591E-01 a      1317     1    24     2    17\n -6.0427219841689683E-01 a      1318     1    24     2    18\n  1.2219460674488312E-01 a      1319     1    24     2    19\n -5.2528314301490422E-02 a      1320     1    24     2    20\n  3.1834532954553768E-01 a      1321     1    24     2    21\n  7.0755713359387640E-01 a      1322     1    24     2    22\n  1.3101938661736368E-01 a      1323     1    24     2    23\n -1.1082316846338994E-01 a      1324     1    24     2    24\n -2.0568569391110925E-01 a      1325     1    24     2    25\n  4.4125743376232839E-02 a      1326     1    25     2     1\n -2.9399052391817254E-01 a      1327     1    25     2     2\n -6.3640597978108193E-01 a      1328     1    25     2     3\n  3.5126950721680823E-02 a      1329     1    25     2     4\n  3.0300204578097834E-01 a      1330     1    25     2     5\n -8.4108707942903493E-01 a      1331     1    25     2     6\n -6.5124576052080463E-01 a      1332     1    25     2     7\n -2.3486353100816629E-01 a      1333     1    25     2     8\n -3.9838453818580627E-01 a      1334     1    25     2     9\n -1.5601769082850742E-01 a      1335     1    25     2    10\n  6.8606136180249766E-01 a      1336     1    25     2    11\n  8.4377054233104853E-01 a      1337     1    25     2    12\n  2.8153362068069354E-01 a      1338     1    25     2    13\n -3.3737763546824229E-01 a      1339     1    25     2    14\n -4.3430994169229392E-01 a      1340     1    25     2    15\n  7.5663116594323440E-02 a      1341     1    25     2    16\n -1.4456997296467172E-01 a      1342     1    25     2    17\n  3.0922338406744482E-01 a      1343     1    25     2    18\n -2.8393017235285711E-01 a      1344     1    25     2    19\n -6.8755394762288813E-01 a      1345     1    25     2    20\n -4.7623564600245749E-01 a      1346     1    25     2    21\n  1.4284614353952738E-01 a      1347     1    25     2    22\n -1.5360644504587614E-02 a      1348     1    25     2    23\n -7.1480980198088448E-02 a      1349     1    25     2    24\n -4.1736087572949854E-01 a      1350     1    25     2    25\n  1.8789564286640585E+00 b      1351     2     1\n -1.1750094945339578E+00 b      1352     2     2\n -1.5719913820203872E+00 b      1353     2     3\n -6.4935502080991003E-01 b      1354     2     4\n -9.6224360954704979E-01 b      1355     2     5\n  1.6868578226698367E+00 b      1356     2     6\n  1.2593057796685796E+00 b      1357     2     7\n  2.1737669887896947E+00 b      1358     2     8\n -1.7371982745799910E+00 b      1359     2     9\n -1.3829005180551979E+00 b      1360     2    10\n  2.7273094922039592E-01 b      1361     2    11\n -6.8392341148789904E-01 b      1362     2    12\n -8.6682521508287136E-01 b      1363     2    13\n -1.8984691858658236E+00 b      1364     2    14\n  1.2116371655387401E+00 b      1365     2    15\n  8.6848372703130872E-01 b      1366     2    16\n  2.9618121377310802E-01 b      1367     2    17\n  1.6672832153564778E+00 b      1368     2    18\n -1.4823693977982726E+00 b      1369     2    19\n  5.3696375730732249E-01 b      1370     2    20\n  1.7895516857297333E-01 b      1371     2    21\n  1.8056375515273140E+00 b      1372     2    22\n -1.2397094368301642E+00 b      1373     2    23\n  7.7575217780672856E-01 b      1374     2    24\n  1.7792277961937286E+00 b      1375     2    25\n -1.4758586190854777E+00 a      1376     2     1     3     1\n  1.3779652593189025E+00 a      1377     2     2     3     1\n  1.0979087794601805E+00 a      1378     2     3     3     1\n  1.3576885352106565E+00 a      1379     2     4     3     1\n  1.0758220851759079E+00 a      1380     2     5     3     1\n -1.1830577435626908E+00 a      1381     2     6     3     1\n -2.0733962904894594E+00 a      1382     2     7     3     1\n -1.5059136062051963E+00 a      1383     2     8     3     1\n  1.5337847137662963E+00 a      1384     2     9     3     1\n  1.1430309817330371E+00 a      1385     2    10     3     1\n -8.4267078388334316E-01 a      1386     2    11     3     1\n  9.7099919033617255E-01 a      1387     2    12     3     1\n  1.4260942407404569E+00 a      1388     2    13     3     1\n  1.4183794591936838E+00 a      1389     2    14     3     1\n -5.9558230752899433E-01 a      1390     2    15     3     1\n -1.3634741462405153E+00 a      1391     2    16     3     1\n -2.4508616242970330E-01 a      1392     2    17     3     1\n -1.3949708188472048E+00 a      1393     2    18     3     1\n  1.1989633287077390E+00 a      1394     2    19     3     1\n -7.8811803196284191E-01 a      1395     2    20     3     1\n  5.7031861523374794E-01 a      1396     2    21     3     1\n -1.3856497414757920E+00 a      1397     2    22     3     1\n  1.2505226566879293E+00 a      1398     2    23     3     1\n -8.7288871738616169E-01 a      1399     2    24     3     1\n -1.7026726710121438E+00 a      1400     2    25     3     1\n -3.0792998280590238E+00 b      1401     3     1\n"
  },
  {
    "path": "examples/nnp-predict/H2O_RPBE-D3_4G/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -2.9422332570564236E-01 a         1     0     1     1     1\n -8.6242968305505707E-01 a         2     0     1     1     2\n  1.4984269258952362E-01 a         3     0     1     1     3\n -1.2409563118422011E+00 a         4     0     1     1     4\n  4.0042409765381654E-01 a         5     0     1     1     5\n -1.2320994861918082E+00 a         6     0     1     1     6\n -8.1103730348523106E-01 a         7     0     1     1     7\n -6.4652981857524261E-01 a         8     0     1     1     8\n -3.3412864213069637E-01 a         9     0     1     1     9\n -7.4371115709111910E-02 a        10     0     1     1    10\n -9.5070171126510949E-01 a        11     0     1     1    11\n  3.6109449159015083E-01 a        12     0     1     1    12\n  5.2839043147262188E-01 a        13     0     1     1    13\n -7.4957857100217340E-01 a        14     0     1     1    14\n  3.1492263358132089E-01 a        15     0     1     1    15\n  1.1863329666356316E-01 a        16     0     1     1    16\n -6.0979091657382434E-01 a        17     0     1     1    17\n  2.4472520553129076E-01 a        18     0     1     1    18\n -1.3341553193115157E+00 a        19     0     1     1    19\n  5.0440017184546970E-01 a        20     0     1     1    20\n -5.0826978136358347E-01 a        21     0     1     1    21\n -1.6379745994230226E+00 a        22     0     1     1    22\n -8.3379128057362847E-02 a        23     0     1     1    23\n  1.6949669804612509E-02 a        24     0     1     1    24\n  1.2118866474140913E-01 a        25     0     1     1    25\n -3.6004545018678008E-01 a        26     0     2     1     1\n  8.1061415908630727E-03 a        27     0     2     1     2\n -8.0770763582819827E-01 a        28     0     2     1     3\n  1.6415119695579954E+00 a        29     0     2     1     4\n -8.2596054945166242E-01 a        30     0     2     1     5\n  2.3858608190844222E+00 a        31     0     2     1     6\n  1.4272362416426936E+00 a        32     0     2     1     7\n  3.7545030039492977E-01 a        33     0     2     1     8\n -1.0065497568219210E+00 a        34     0     2     1     9\n  8.3764535764831383E-01 a        35     0     2     1    10\n  6.2655048783943446E-01 a        36     0     2     1    11\n -5.0209299183184442E-01 a        37     0     2     1    12\n -6.1243023185123524E-01 a        38     0     2     1    13\n -7.9106615389479317E-04 a        39     0     2     1    14\n -9.1342929899286485E-01 a        40     0     2     1    15\n -2.5545288448899145E-01 a        41     0     2     1    16\n -1.5273580931611166E+00 a        42     0     2     1    17\n  4.3023007446252653E-01 a        43     0     2     1    18\n  4.9489772654756831E-01 a        44     0     2     1    19\n  2.3689665629646192E-01 a        45     0     2     1    20\n -1.2060031152787423E+00 a        46     0     2     1    21\n  1.4854291846265191E+00 a        47     0     2     1    22\n -2.5725436250364658E-01 a        48     0     2     1    23\n -9.9501361535215371E-01 a        49     0     2     1    24\n  1.3193835892580313E-02 a        50     0     2     1    25\n -9.7911466787197499E-01 a        51     0     3     1     1\n  8.1600705736050028E-01 a        52     0     3     1     2\n  3.6568306957595548E-01 a        53     0     3     1     3\n  1.8129608852324869E-01 a        54     0     3     1     4\n -8.7631397246523690E-01 a        55     0     3     1     5\n -1.9798961827503636E-01 a        56     0     3     1     6\n  7.6449659945582793E-01 a        57     0     3     1     7\n  1.1155543874214544E+00 a        58     0     3     1     8\n -5.4414597298818468E-01 a        59     0     3     1     9\n -2.7883628825759948E-01 a        60     0     3     1    10\n  2.3687254519178885E-01 a        61     0     3     1    11\n -3.3710772784630492E-02 a        62     0     3     1    12\n -3.1030070237085927E-01 a        63     0     3     1    13\n  4.9893657405998315E-01 a        64     0     3     1    14\n -4.9655088327066116E-01 a        65     0     3     1    15\n  5.9956708064326969E-01 a        66     0     3     1    16\n -3.7255672776395915E-01 a        67     0     3     1    17\n  1.6312295604066016E+00 a        68     0     3     1    18\n  4.3848334702915166E-02 a        69     0     3     1    19\n  5.6421750053897657E-01 a        70     0     3     1    20\n  2.3575474456016107E-01 a        71     0     3     1    21\n -3.5252735445576583E-01 a        72     0     3     1    22\n -4.2855464144154792E-01 a        73     0     3     1    23\n  1.4283295918179528E-01 a        74     0     3     1    24\n -6.1728269264595659E-01 a        75     0     3     1    25\n -2.9996155963276845E+00 a        76     0     4     1     1\n -4.5652849083284208E-01 a        77     0     4     1     2\n -4.1057672446170551E-01 a        78     0     4     1     3\n  2.2207441517233692E-01 a        79     0     4     1     4\n  1.7996431215781084E+00 a        80     0     4     1     5\n -2.6289261340865018E+00 a        81     0     4     1     6\n -5.3930650043952766E-01 a        82     0     4     1     7\n  9.5559138405560157E-02 a        83     0     4     1     8\n  2.4166031975306779E-01 a        84     0     4     1     9\n -4.6284491852672410E-01 a        85     0     4     1    10\n  6.5019378851748533E-01 a        86     0     4     1    11\n -3.7284638843050949E-01 a        87     0     4     1    12\n  1.0800198578606079E+00 a        88     0     4     1    13\n -8.8213397319864217E-01 a        89     0     4     1    14\n  1.1736823953192932E+00 a        90     0     4     1    15\n  3.0348970368979261E-01 a        91     0     4     1    16\n  1.1882628500360206E+00 a        92     0     4     1    17\n -5.7970251979893327E-02 a        93     0     4     1    18\n -4.3902959759109537E-02 a        94     0     4     1    19\n -3.9958280685902264E-02 a        95     0     4     1    20\n -5.9956558674880100E-01 a        96     0     4     1    21\n -7.2107133882267416E-01 a        97     0     4     1    22\n  7.8130292425311287E-01 a        98     0     4     1    23\n  7.0227575751278604E-01 a        99     0     4     1    24\n -2.1269569298701643E-01 a       100     0     4     1    25\n  5.2881926716996952E-01 a       101     0     5     1     1\n  8.7695760330648864E-01 a       102     0     5     1     2\n -2.7029211280182430E-01 a       103     0     5     1     3\n -5.7190913211165317E-01 a       104     0     5     1     4\n -1.3205283453930543E+00 a       105     0     5     1     5\n  9.8779494472666785E-01 a       106     0     5     1     6\n  4.0891542710488010E-01 a       107     0     5     1     7\n -2.3994588298845351E-01 a       108     0     5     1     8\n  1.4474808032820319E-01 a       109     0     5     1     9\n -2.1950336590495523E-01 a       110     0     5     1    10\n  2.1148954638454498E-01 a       111     0     5     1    11\n -7.9315062994770857E-01 a       112     0     5     1    12\n -4.2266380526923769E-01 a       113     0     5     1    13\n  6.3267280511099033E-01 a       114     0     5     1    14\n  9.9292104763440275E-02 a       115     0     5     1    15\n -7.0363869915504904E-02 a       116     0     5     1    16\n  3.5290947342408646E-01 a       117     0     5     1    17\n  2.0417464784721062E-01 a       118     0     5     1    18\n  1.1190125774451791E+00 a       119     0     5     1    19\n  2.4177512025660097E-01 a       120     0     5     1    20\n -7.0978989517633984E-01 a       121     0     5     1    21\n  9.9376256836019827E-01 a       122     0     5     1    22\n  1.3997778177305649E+00 a       123     0     5     1    23\n  4.1044576480153257E-02 a       124     0     5     1    24\n  9.2489426334512725E-01 a       125     0     5     1    25\n  8.8541302738115835E-02 a       126     0     6     1     1\n -7.2639448808652543E-02 a       127     0     6     1     2\n -3.8091180506473164E-02 a       128     0     6     1     3\n  1.2017798432011133E+00 a       129     0     6     1     4\n  2.5529807502344082E-01 a       130     0     6     1     5\n  9.9560554489489986E-02 a       131     0     6     1     6\n -3.4609321068047155E-01 a       132     0     6     1     7\n  2.0587299366871839E-01 a       133     0     6     1     8\n  1.4511782221850042E-01 a       134     0     6     1     9\n -4.0599729517086086E-01 a       135     0     6     1    10\n  2.1020286764373428E-01 a       136     0     6     1    11\n  9.1906312029472426E-01 a       137     0     6     1    12\n -1.2342855778775570E+00 a       138     0     6     1    13\n -6.3421217344559647E-02 a       139     0     6     1    14\n  2.3490285949408210E-01 a       140     0     6     1    15\n  2.0572868165883293E-01 a       141     0     6     1    16\n -4.3155898932647485E-03 a       142     0     6     1    17\n -2.3637712439714725E-02 a       143     0     6     1    18\n  1.9541204567640827E-01 a       144     0     6     1    19\n  5.6038448295742826E-01 a       145     0     6     1    20\n -6.8359344447854031E-01 a       146     0     6     1    21\n  6.6554198564764411E-01 a       147     0     6     1    22\n -5.2895815742249086E-01 a       148     0     6     1    23\n  5.9705460999142930E-02 a       149     0     6     1    24\n  2.3153671632909106E-01 a       150     0     6     1    25\n  7.6296956118467796E-01 a       151     0     7     1     1\n -1.2386274678288511E-01 a       152     0     7     1     2\n  6.5882568512217832E-01 a       153     0     7     1     3\n -2.5447118258599316E-01 a       154     0     7     1     4\n  1.1518869650335233E+00 a       155     0     7     1     5\n -7.5926706246250986E-01 a       156     0     7     1     6\n  2.6574976434838893E-01 a       157     0     7     1     7\n  1.6715862054825465E-02 a       158     0     7     1     8\n  9.9809286775273864E-01 a       159     0     7     1     9\n  3.9698983096908885E-01 a       160     0     7     1    10\n -3.8499113476531632E-01 a       161     0     7     1    11\n  8.1153751387621542E-02 a       162     0     7     1    12\n  9.7818816381042972E-01 a       163     0     7     1    13\n  4.7058249631975546E-01 a       164     0     7     1    14\n  2.8619495981880050E-01 a       165     0     7     1    15\n  4.3513753095075786E-01 a       166     0     7     1    16\n -4.8695390240518677E-01 a       167     0     7     1    17\n -1.3354855502571936E+00 a       168     0     7     1    18\n -7.2006685338713283E-01 a       169     0     7     1    19\n -7.9557411083327290E-01 a       170     0     7     1    20\n  8.9663595328790602E-01 a       171     0     7     1    21\n  1.4469053211148319E-01 a       172     0     7     1    22\n  7.1992217302900929E-01 a       173     0     7     1    23\n  6.6540127027099194E-01 a       174     0     7     1    24\n -2.0645043740952725E-02 a       175     0     7     1    25\n  9.7174174279835135E-01 a       176     0     8     1     1\n -2.6533759890956166E-01 a       177     0     8     1     2\n -2.5791564831891062E-02 a       178     0     8     1     3\n  3.6627005334700369E-01 a       179     0     8     1     4\n  7.8022380913227218E-01 a       180     0     8     1     5\n -8.6476232675722620E-01 a       181     0     8     1     6\n -2.8076608390866375E-01 a       182     0     8     1     7\n  8.5968209643071059E-01 a       183     0     8     1     8\n  1.0738367316865637E-01 a       184     0     8     1     9\n  7.7332214799712862E-01 a       185     0     8     1    10\n -9.2391280016511346E-01 a       186     0     8     1    11\n -2.5997338610524345E-01 a       187     0     8     1    12\n  3.6868205153880024E-01 a       188     0     8     1    13\n -2.9563186118437002E-01 a       189     0     8     1    14\n -8.0081546350669908E-01 a       190     0     8     1    15\n -1.9879286578385555E-01 a       191     0     8     1    16\n -2.2263146471531350E-01 a       192     0     8     1    17\n  9.3571137724332931E-01 a       193     0     8     1    18\n -1.0305193354948512E+00 a       194     0     8     1    19\n -4.6084657701672577E-01 a       195     0     8     1    20\n  9.8101701680955467E-01 a       196     0     8     1    21\n  6.4388433590929628E-01 a       197     0     8     1    22\n -8.2924350367704869E-01 a       198     0     8     1    23\n -7.2836352957607475E-01 a       199     0     8     1    24\n -6.3543750101458263E-01 a       200     0     8     1    25\n -7.3543341050733402E-01 a       201     0     9     1     1\n  3.2168427736031685E-01 a       202     0     9     1     2\n -3.1401281725176994E-01 a       203     0     9     1     3\n -7.9326880554292323E-01 a       204     0     9     1     4\n  4.9674627582055275E-01 a       205     0     9     1     5\n  1.0617238120984573E+00 a       206     0     9     1     6\n  9.6530480091350679E-01 a       207     0     9     1     7\n  1.1252070954591333E+00 a       208     0     9     1     8\n -1.1401727296961830E+00 a       209     0     9     1     9\n  1.4541770409612091E+00 a       210     0     9     1    10\n  4.2784730818664363E-01 a       211     0     9     1    11\n  2.1901745871447234E-01 a       212     0     9     1    12\n  4.8539680502115726E-02 a       213     0     9     1    13\n  8.7419872303097654E-02 a       214     0     9     1    14\n  5.7479118595137579E-01 a       215     0     9     1    15\n -9.9029475307400217E-01 a       216     0     9     1    16\n  9.1666766504385222E-01 a       217     0     9     1    17\n  8.6544679957455528E-01 a       218     0     9     1    18\n -1.3960377017176367E-01 a       219     0     9     1    19\n  3.3276019158920594E-01 a       220     0     9     1    20\n -1.2583173310083793E+00 a       221     0     9     1    21\n -1.2703969914766062E+00 a       222     0     9     1    22\n -1.6670130236421137E+00 a       223     0     9     1    23\n -7.6457081439361774E-01 a       224     0     9     1    24\n -4.4215425515514289E-01 a       225     0     9     1    25\n  1.1009080929711608E+00 a       226     0    10     1     1\n  1.7678881988396195E-02 a       227     0    10     1     2\n  7.9485227058391339E-01 a       228     0    10     1     3\n -2.4523116835605704E-01 a       229     0    10     1     4\n -4.3349074019418676E-01 a       230     0    10     1     5\n  3.7297324644230738E-02 a       231     0    10     1     6\n -2.2511900759377465E-01 a       232     0    10     1     7\n -1.5925490355822975E+00 a       233     0    10     1     8\n  3.8064907508793444E-01 a       234     0    10     1     9\n -2.6131841516836235E-01 a       235     0    10     1    10\n  4.1622386587743793E-01 a       236     0    10     1    11\n  3.6226856376303473E-01 a       237     0    10     1    12\n -2.2535825515244659E-01 a       238     0    10     1    13\n -4.3759377768090241E-01 a       239     0    10     1    14\n -2.2728134210721737E-01 a       240     0    10     1    15\n  1.7375143599424356E-01 a       241     0    10     1    16\n -4.4965943028054367E-01 a       242     0    10     1    17\n -7.6068323385850900E-01 a       243     0    10     1    18\n -4.6141746149964281E-02 a       244     0    10     1    19\n -6.3981363343050213E-02 a       245     0    10     1    20\n -2.9894923206065394E-01 a       246     0    10     1    21\n  1.0325548609262833E+00 a       247     0    10     1    22\n -5.4912117122001181E-01 a       248     0    10     1    23\n  2.8945399598667887E-01 a       249     0    10     1    24\n  6.9893874311915938E-01 a       250     0    10     1    25\n  4.0214400440165199E-01 a       251     0    11     1     1\n -4.8104786796265403E-01 a       252     0    11     1     2\n -4.5445080902785728E-01 a       253     0    11     1     3\n -6.9375699229342325E-01 a       254     0    11     1     4\n -2.1178031156020591E-01 a       255     0    11     1     5\n -3.8656963816484624E-01 a       256     0    11     1     6\n -8.2061602584684934E-01 a       257     0    11     1     7\n  1.5676875860304865E-01 a       258     0    11     1     8\n  4.0464250368585991E-01 a       259     0    11     1     9\n -9.7479998416492508E-01 a       260     0    11     1    10\n -4.6188980685759951E-01 a       261     0    11     1    11\n -1.5451048215149878E+00 a       262     0    11     1    12\n  2.7436324817704338E-01 a       263     0    11     1    13\n  7.1366466468756717E-01 a       264     0    11     1    14\n  5.5677354091522996E-02 a       265     0    11     1    15\n -2.9543498141776675E-02 a       266     0    11     1    16\n -1.3592873100131835E+00 a       267     0    11     1    17\n -2.4974734365889562E-01 a       268     0    11     1    18\n  3.5750900493729626E-01 a       269     0    11     1    19\n -6.4599764748131938E-01 a       270     0    11     1    20\n  3.3997963898525702E-01 a       271     0    11     1    21\n  6.1566246177049255E-01 a       272     0    11     1    22\n  3.9578546709375095E-01 a       273     0    11     1    23\n -4.6225367864167693E-01 a       274     0    11     1    24\n  2.0167914110214993E-01 a       275     0    11     1    25\n -5.4039977094535352E-01 a       276     0    12     1     1\n  5.6232317183978087E-01 a       277     0    12     1     2\n -5.7905219822318987E-01 a       278     0    12     1     3\n -6.9163430749190002E-01 a       279     0    12     1     4\n -5.0090125137996377E-01 a       280     0    12     1     5\n -4.9883399265472400E-01 a       281     0    12     1     6\n  5.0255685386479176E-01 a       282     0    12     1     7\n  2.6075855293405503E-01 a       283     0    12     1     8\n -9.1859433130301871E-02 a       284     0    12     1     9\n  4.4629299458190741E-01 a       285     0    12     1    10\n -2.0134002368216022E-02 a       286     0    12     1    11\n  1.0689717649667679E-01 a       287     0    12     1    12\n  1.7299421170077633E-01 a       288     0    12     1    13\n  4.5373856416060449E-01 a       289     0    12     1    14\n  3.5432447883111434E-01 a       290     0    12     1    15\n -1.4576188606736254E-01 a       291     0    12     1    16\n -3.0121691861266148E-01 a       292     0    12     1    17\n  1.9073368844196473E-01 a       293     0    12     1    18\n  1.4463102653816853E-01 a       294     0    12     1    19\n -5.5929990097710736E-01 a       295     0    12     1    20\n  8.0415786406409517E-01 a       296     0    12     1    21\n -5.1287204545332110E-01 a       297     0    12     1    22\n  7.1951799328071242E-01 a       298     0    12     1    23\n -2.9598435728437072E-01 a       299     0    12     1    24\n -2.8054461671521458E-01 a       300     0    12     1    25\n -1.1352191635121349E-02 a       301     0    13     1     1\n  6.0980425298619589E-01 a       302     0    13     1     2\n  7.5976934796992926E-02 a       303     0    13     1     3\n  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-8.7480900902329448E-02 a      1381     1    24     2     6\n  1.9470921111976011E-01 a      1382     1    24     2     7\n  2.2037117921970700E-01 a      1383     1    24     2     8\n -2.6025283181469727E-01 a      1384     1    24     2     9\n -2.5065916404520626E-02 a      1385     1    24     2    10\n  2.4618974102136211E-02 a      1386     1    24     2    11\n  2.1689474944547740E-01 a      1387     1    24     2    12\n -4.2189964727691065E-01 a      1388     1    24     2    13\n  3.1994942310577296E-01 a      1389     1    24     2    14\n -3.1661240385522005E-01 a      1390     1    24     2    15\n -7.1113149958872346E-01 a      1391     1    24     2    16\n  4.8487452553364485E-01 a      1392     1    24     2    17\n  8.7884297477615203E-01 a      1393     1    24     2    18\n  2.3219338968921510E-01 a      1394     1    24     2    19\n -7.9988449335630429E-01 a      1395     1    24     2    20\n -7.3312126199345920E-02 a      1396     1    24     2    21\n -3.7858645868551460E-01 a      1397     1    24     2    22\n  1.5341935935301762E-01 a      1398     1    24     2    23\n  4.5648104119761673E-01 a      1399     1    24     2    24\n -3.6327547349723011E-01 a      1400     1    24     2    25\n -2.2008864094779765E-01 a      1401     1    25     2     1\n -3.1427280954047104E-01 a      1402     1    25     2     2\n -7.0152661880542966E-01 a      1403     1    25     2     3\n  4.9294253752364980E-01 a      1404     1    25     2     4\n  1.6854190508374950E-01 a      1405     1    25     2     5\n -1.3728246268951111E-01 a      1406     1    25     2     6\n  3.3126671754301212E-01 a      1407     1    25     2     7\n  1.5055967762545888E-01 a      1408     1    25     2     8\n -2.2303198009643723E-02 a      1409     1    25     2     9\n  4.3091849509270763E-01 a      1410     1    25     2    10\n -9.0288736926079483E-01 a      1411     1    25     2    11\n  1.2171290488029467E-01 a      1412     1    25     2    12\n -8.4641478341814547E-01 a      1413     1    25     2    13\n  2.6275030694420781E-01 a      1414     1    25     2    14\n -3.4740280137984780E-01 a      1415     1    25     2    15\n -1.7276822479890969E-01 a      1416     1    25     2    16\n -3.6743520765112370E-01 a      1417     1    25     2    17\n  7.8881302372583861E-01 a      1418     1    25     2    18\n -4.5739998935924076E-01 a      1419     1    25     2    19\n  2.1329548220653394E-01 a      1420     1    25     2    20\n  4.0377139154496083E-01 a      1421     1    25     2    21\n  5.7395219729029956E-01 a      1422     1    25     2    22\n  5.0546875172715244E-01 a      1423     1    25     2    23\n  9.4644388347203540E-02 a      1424     1    25     2    24\n -1.6416703941476618E-01 a      1425     1    25     2    25\n -5.9844843169938589E-01 b      1426     2     1\n -8.4632029439256440E-01 b      1427     2     2\n -6.2984936436132188E-01 b      1428     2     3\n -6.0966129443780714E-01 b      1429     2     4\n -4.9864939191092000E-01 b      1430     2     5\n  1.4717760426000948E+00 b      1431     2     6\n  1.1279690899415993E+00 b      1432     2     7\n -8.2846340989167411E-01 b      1433     2     8\n -7.7302491958448472E-01 b      1434     2     9\n  6.3368351032829384E-01 b      1435     2    10\n  2.9681892286492156E-01 b      1436     2    11\n  1.6430829564033300E-01 b      1437     2    12\n  8.2315732389295670E-01 b      1438     2    13\n -9.6890834028007278E-01 b      1439     2    14\n  4.0962332307318944E-01 b      1440     2    15\n -9.5938811526708512E-01 b      1441     2    16\n -5.3734420694457330E-01 b      1442     2    17\n  7.9223206105508859E-01 b      1443     2    18\n  6.2770992334827658E-01 b      1444     2    19\n -2.6589592435750703E-01 b      1445     2    20\n -3.1927054187698350E-01 b      1446     2    21\n  6.2431280980453314E-02 b      1447     2    22\n -1.7069634658034652E-01 b      1448     2    23\n  2.3890528536332042E-01 b      1449     2    24\n -1.1900667148116713E+00 b      1450     2    25\n  7.9851274390395466E-01 a      1451     2     1     3     1\n  1.2499329100404344E+00 a      1452     2     2     3     1\n  1.0264725605956799E+00 a      1453     2     3     3     1\n  5.3871872329413073E-01 a      1454     2     4     3     1\n  1.0846578334405872E+00 a      1455     2     5     3     1\n -1.3553526186318652E+00 a      1456     2     6     3     1\n -1.2096470434864539E+00 a      1457     2     7     3     1\n  1.0664396894257673E+00 a      1458     2     8     3     1\n  8.0573742379153857E-01 a      1459     2     9     3     1\n -7.9213753018522470E-01 a      1460     2    10     3     1\n -5.6636687635351313E-01 a      1461     2    11     3     1\n  1.3627931807746912E-02 a      1462     2    12     3     1\n -4.4665059718676886E-01 a      1463     2    13     3     1\n  1.3221212565119256E+00 a      1464     2    14     3     1\n -1.4488793388154610E+00 a      1465     2    15     3     1\n  6.9278747917666517E-01 a      1466     2    16     3     1\n  5.8042790876053951E-01 a      1467     2    17     3     1\n -1.6195875097087178E-01 a      1468     2    18     3     1\n -7.5235420291700006E-01 a      1469     2    19     3     1\n  1.5779224745095659E+00 a      1470     2    20     3     1\n  6.2330633539832991E-01 a      1471     2    21     3     1\n -7.2549227445943970E-02 a      1472     2    22     3     1\n  1.2319828828939434E-01 a      1473     2    23     3     1\n -5.6230533294864848E-01 a      1474     2    24     3     1\n  6.9825981883973254E-01 a      1475     2    25     3     1\n -1.5396499140018998E+00 b      1476     3     1\n"
  },
  {
    "path": "examples/nnp-predict/H2O_RPBE-D3_4G/weightse.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  3.8539920696065272E-03 a         1     0     1     1     1\n  1.4179202637119184E-01 a         2     0     1     1     2\n -8.4701795101902719E-02 a         3     0     1     1     3\n  4.2786441591945618E-01 a         4     0     1     1     4\n  2.9875491363892337E-01 a         5     0     1     1     5\n -4.3040317475651450E-02 a         6     0     1     1     6\n -9.3585085791213107E-02 a         7     0     1     1     7\n  1.0443745127814134E-01 a         8     0     1     1     8\n  3.1120740732567770E-01 a         9     0     1     1     9\n  3.4447534280048148E-01 a        10     0     1     1    10\n  2.5230860481679046E-01 a        11     0     1     1    11\n -3.0050874116651893E-01 a        12     0     1     1    12\n  3.4354423264210993E-01 a        13     0     1     1    13\n  2.8887290273884036E-01 a        14     0     1     1    14\n -2.6331513711801402E-01 a        15     0     1     1    15\n -2.5298145746485301E-01 a        16     0     1     1    16\n -9.8020561573758005E-02 a        17     0     1     1    17\n  3.8941624788720375E-01 a        18     0     1     1    18\n -2.1172211598632174E-01 a        19     0     1     1    19\n -1.6583082623500564E-01 a        20     0     1     1    20\n -2.1773053646246107E-01 a        21     0     1     1    21\n  2.8814918779133853E-02 a        22     0     1     1    22\n -8.6708237008355116E-02 a        23     0     1     1    23\n -3.8539466668201672E-01 a        24     0     1     1    24\n -2.4835874791249604E-01 a        25     0     1     1    25\n  2.6352326780434476E-01 a        26     0     2     1     1\n -2.1331197434023635E-01 a        27     0     2     1     2\n -2.6464885511616004E-01 a        28     0     2     1     3\n  4.5575388719498733E-01 a        29     0     2     1     4\n  3.1881715267007904E-01 a        30     0     2     1     5\n -2.3253177359157898E-01 a        31     0     2     1     6\n  1.4753879123451752E-01 a        32     0     2     1     7\n  3.5802040734673507E-01 a        33     0     2     1     8\n -9.4959421005989794E-02 a        34     0     2     1     9\n -2.5386966735921795E-01 a        35     0     2     1    10\n -2.9911926539147349E-01 a        36     0     2     1    11\n  4.0062446869435758E-01 a        37     0     2     1    12\n  2.3329962665324777E-01 a        38     0     2     1    13\n -9.1218384895913773E-02 a        39     0     2     1    14\n -1.2392802596055631E-01 a        40     0     2     1    15\n -3.8708320139018321E-01 a        41     0     2     1    16\n -2.8189815904678545E-01 a        42     0     2     1    17\n  4.3868793908807835E-01 a        43     0     2     1    18\n  3.4133367778285645E-01 a        44     0     2     1    19\n  1.8470149482930123E-01 a        45     0     2     1    20\n -2.1875811222426636E-01 a        46     0     2     1    21\n  1.2225326828409362E-01 a        47     0     2     1    22\n -2.6366345702559496E-01 a        48     0     2     1    23\n -4.2404523369582509E-01 a        49     0     2     1    24\n -3.6783669520305817E-01 a        50     0     2     1    25\n -6.4263863303950133E-02 a        51     0     3     1     1\n -5.9452364190340015E-02 a        52     0     3     1     2\n -3.4632229526821634E-01 a        53     0     3     1     3\n  3.3236756793748040E-01 a        54     0     3     1     4\n  1.9717508362626027E-01 a        55     0     3     1     5\n  4.1530194812984381E-02 a        56     0     3     1     6\n  2.2261005704435952E-01 a        57     0     3     1     7\n  1.9489528548741236E-01 a        58     0     3     1     8\n -1.0472328059078184E-01 a        59     0     3     1     9\n -8.1238279805414086E-03 a        60     0     3     1    10\n  1.0507265123107251E-01 a        61     0     3     1    11\n -2.0206168302882097E-01 a        62     0     3     1    12\n -2.5326027873034634E-01 a        63     0     3     1    13\n -1.4106112966473905E-01 a        64     0     3     1    14\n -3.3014322716597527E-01 a        65     0     3     1    15\n  8.1901790377166037E-02 a        66     0     3     1    16\n  1.3207638981287362E-01 a        67     0     3     1    17\n  3.7556247127600378E-01 a        68     0     3     1    18\n  1.0348185595883426E-01 a        69     0     3     1    19\n -1.5687138270175383E-01 a        70     0     3     1    20\n -1.6042134944355285E-01 a        71     0     3     1    21\n  1.2392290326642963E-01 a        72     0     3     1    22\n -1.2236793646545301E-01 a        73     0     3     1    23\n -3.7059901204244838E-01 a        74     0     3     1    24\n  1.3061684542802357E-01 a        75     0     3     1    25\n -2.7604393602789717E-01 a        76     0     4     1     1\n  1.7960198344638020E-01 a        77     0     4     1     2\n -3.8827561867845306E-02 a        78     0     4     1     3\n  9.1362834507325616E-02 a        79     0     4     1     4\n -1.2357529149543595E-01 a        80     0     4     1     5\n -1.8988413555073125E-01 a        81     0     4     1     6\n  1.4508970264644533E-01 a        82     0     4     1     7\n  7.7440087154751744E-02 a        83     0     4     1     8\n -5.4049837143820674E-02 a        84     0     4     1     9\n -2.3819045900282934E-01 a        85     0     4     1    10\n -3.3084516676984188E-01 a        86     0     4     1    11\n -2.3091108914648634E-02 a        87     0     4     1    12\n  9.3782654778165483E-02 a        88     0     4     1    13\n  1.4904479053656633E-01 a        89     0     4     1    14\n -5.9674435995170538E-01 a        90     0     4     1    15\n -3.0110648905458615E-01 a        91     0     4     1    16\n  2.7343367204610680E-01 a        92     0     4     1    17\n -1.5286636304630238E-01 a        93     0     4     1    18\n  5.1858552249730301E-02 a        94     0     4     1    19\n -1.4505889962407066E-02 a        95     0     4     1    20\n  1.5694767225130402E-01 a        96     0     4     1    21\n -7.1622912367683034E-01 a        97     0     4     1    22\n  2.8331356852087602E-01 a        98     0     4     1    23\n  1.4665647716618191E-01 a        99     0     4     1    24\n -2.8684039559389840E-01 a       100     0     4     1    25\n -3.5039570086147381E-01 a       101     0     5     1     1\n  4.6404016706133616E-01 a       102     0     5     1     2\n -6.3763376730681970E-02 a       103     0     5     1     3\n  2.9891548164021692E-01 a       104     0     5     1     4\n -2.3097848593653537E-02 a       105     0     5     1     5\n  3.5298232522476258E-01 a       106     0     5     1     6\n -2.2319090574630751E-01 a       107     0     5     1     7\n  1.8655533798036827E-01 a       108     0     5     1     8\n -2.1165403523721285E-01 a       109     0     5     1     9\n -6.2000733522745621E-01 a       110     0     5     1    10\n  2.3099014149544428E-01 a       111     0     5     1    11\n  3.3727801973288854E-02 a       112     0     5     1    12\n -3.4927854825101090E-01 a       113     0     5     1    13\n -2.1680904803831466E-01 a       114     0     5     1    14\n -3.9175656926790425E-01 a       115     0     5     1    15\n -1.8258947980311663E-01 a       116     0     5     1    16\n  2.2879981180489972E-01 a       117     0     5     1    17\n  7.8387684089134144E-02 a       118     0     5     1    18\n -1.0078318473300560E-01 a       119     0     5     1    19\n -1.3966057674487634E-01 a       120     0     5     1    20\n -1.7993010731475886E-01 a       121     0     5     1    21\n -3.9383576353131276E-03 a       122     0     5     1    22\n -1.7216017083384388E-01 a       123     0     5     1    23\n -4.3722741976862739E-01 a       124     0     5     1    24\n -1.7279187908737478E-01 a       125     0     5     1    25\n -2.3563464525660680E-01 a       126     0     6     1     1\n  3.5306253108556107E-01 a       127     0     6     1     2\n  4.8008950498160452E-01 a       128     0     6     1     3\n  2.1927564587945636E-01 a       129     0     6     1     4\n  5.2794981463351409E-01 a       130     0     6     1     5\n  3.2876945807832453E-01 a       131     0     6     1     6\n  1.7941570686406236E-01 a       132     0     6     1     7\n  2.7727782581442828E-01 a       133     0     6     1     8\n  9.4150673300085030E-02 a       134     0     6     1     9\n  4.8896137482360297E-01 a       135     0     6     1    10\n -1.0940964810226970E-01 a       136     0     6     1    11\n -5.2508187016410601E-01 a       137     0     6     1    12\n  3.7911978642788663E-01 a       138     0     6     1    13\n  1.9678079413389291E-01 a       139     0     6     1    14\n -8.1083810956064695E-01 a       140     0     6     1    15\n -2.1191492782298613E-01 a       141     0     6     1    16\n -4.4853983516178064E-01 a       142     0     6     1    17\n  2.5927950445018000E-01 a       143     0     6     1    18\n -5.1999117581196762E-02 a       144     0     6     1    19\n  2.0147777160058133E-01 a       145     0     6     1    20\n -4.5451995715045795E-01 a       146     0     6     1    21\n -1.3650482726966681E-01 a       147     0     6     1    22\n  5.6249513231758941E-01 a       148     0     6     1    23\n -3.0673363599458225E-01 a       149     0     6     1    24\n -1.2999769617277113E-02 a       150     0     6     1    25\n  4.8431100890231525E-02 a       151     0     7     1     1\n  1.1598638430569079E-01 a       152     0     7     1     2\n -2.2119427946271561E-01 a       153     0     7     1     3\n -1.6887552489523575E-01 a       154     0     7     1     4\n  1.3459711779810604E-01 a       155     0     7     1     5\n  1.6200609571924288E-01 a       156     0     7     1     6\n  2.2505400007913268E-01 a       157     0     7     1     7\n  1.2162833885238467E-01 a       158     0     7     1     8\n -2.1750746137530877E-01 a       159     0     7     1     9\n 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-3.4128081079645844E-01 a      1253     1    23     2     3\n -5.2306839373873190E-02 a      1254     1    23     2     4\n  1.3366763434374981E-01 a      1255     1    23     2     5\n  3.2717439715653063E-01 a      1256     1    23     2     6\n -7.9505170471509645E-01 a      1257     1    23     2     7\n  1.9333142160729985E-01 a      1258     1    23     2     8\n  3.1269978405126142E-01 a      1259     1    23     2     9\n -2.6993128572635677E-01 a      1260     1    23     2    10\n  1.9992646076319948E-01 a      1261     1    23     2    11\n -1.3485563324270358E-01 a      1262     1    23     2    12\n  4.7785237231915118E-01 a      1263     1    23     2    13\n  2.6373962913648880E-01 a      1264     1    23     2    14\n -3.1361655763061942E-02 a      1265     1    23     2    15\n  2.9817888378183038E-01 a      1266     1    23     2    16\n  2.7977184668387178E-01 a      1267     1    23     2    17\n  9.4079982471699554E-03 a      1268     1    23     2    18\n -8.8735945914368752E-01 a      1269     1    23     2    19\n -5.1905227246455077E-02 a      1270     1    23     2    20\n -1.7190855061458668E-01 a      1271     1    23     2    21\n -3.2956397581140523E-01 a      1272     1    23     2    22\n -6.5535381009087346E-01 a      1273     1    23     2    23\n -6.0512868741783070E-02 a      1274     1    23     2    24\n -6.7043898686841685E-01 a      1275     1    23     2    25\n -4.6023838278247631E-01 a      1276     1    24     2     1\n -2.6190793252611372E-01 a      1277     1    24     2     2\n  4.9993169041699193E-01 a      1278     1    24     2     3\n  2.9579537338338829E-02 a      1279     1    24     2     4\n  6.2917654183144156E-02 a      1280     1    24     2     5\n -7.6871253545146345E-01 a      1281     1    24     2     6\n -1.7136858975762176E-01 a      1282     1    24     2     7\n -1.0998141168946927E-01 a      1283     1    24     2     8\n  1.3351522439890368E-01 a      1284     1    24     2     9\n  2.2324019018686833E-01 a      1285     1    24     2    10\n -8.8147731237687765E-02 a      1286     1    24     2    11\n -1.0589842872444621E-01 a      1287     1    24     2    12\n  1.6945331832857274E-01 a      1288     1    24     2    13\n -2.6711278943719330E-01 a      1289     1    24     2    14\n  2.4101669466413589E-01 a      1290     1    24     2    15\n -1.8310260636637268E-01 a      1291     1    24     2    16\n  1.8102740208352869E-01 a      1292     1    24     2    17\n -1.8967209804342985E-01 a      1293     1    24     2    18\n -4.1819082770882754E-01 a      1294     1    24     2    19\n -3.8319336588298392E-01 a      1295     1    24     2    20\n  3.4027886503823801E-01 a      1296     1    24     2    21\n -1.7420547939173389E-01 a      1297     1    24     2    22\n  4.2203701069632510E-01 a      1298     1    24     2    23\n  1.3574099084771218E-01 a      1299     1    24     2    24\n -3.3012188502627354E-01 a      1300     1    24     2    25\n -2.3266379309933219E-01 a      1301     1    25     2     1\n -3.5651578476551821E-01 a      1302     1    25     2     2\n  2.7987079966021050E-01 a      1303     1    25     2     3\n  2.4560069204336626E-01 a      1304     1    25     2     4\n -1.6392089975048152E-01 a      1305     1    25     2     5\n  3.9323223997705153E-01 a      1306     1    25     2     6\n -9.5814754312062586E-02 a      1307     1    25     2     7\n -1.5239100995216229E-01 a      1308     1    25     2     8\n -3.6667676174041358E-01 a      1309     1    25     2     9\n -6.3258603495284560E-01 a      1310     1    25     2    10\n  7.0388368622073483E-02 a      1311     1    25     2    11\n -7.3767451726786407E-02 a      1312     1    25     2    12\n -2.4457014765957333E-01 a      1313     1    25     2    13\n -9.9183333930098247E-02 a      1314     1    25     2    14\n  2.7273644786660339E-01 a      1315     1    25     2    15\n  2.8149051283060245E-01 a      1316     1    25     2    16\n  9.0037320835149967E-02 a      1317     1    25     2    17\n -1.8668739617119712E-01 a      1318     1    25     2    18\n -2.8634789097217161E-01 a      1319     1    25     2    19\n -4.4385237341048711E-01 a      1320     1    25     2    20\n -2.6797607381376942E-02 a      1321     1    25     2    21\n  1.2830920167118481E-01 a      1322     1    25     2    22\n -3.0232234819629883E-01 a      1323     1    25     2    23\n -5.3299851173572022E-01 a      1324     1    25     2    24\n -1.3179242797513563E-01 a      1325     1    25     2    25\n  1.2063366052899795E-01 b      1326     2     1\n -1.5136529917183425E-01 b      1327     2     2\n -1.7185324042550185E-01 b      1328     2     3\n -1.8540251948371511E-01 b      1329     2     4\n -1.5235842051220030E-01 b      1330     2     5\n  1.6609324649375468E-01 b      1331     2     6\n -3.3491149296387129E-01 b      1332     2     7\n  1.1145199161783716E-01 b      1333     2     8\n -2.5001596644570157E-01 b      1334     2     9\n -1.0538847898339022E-02 b      1335     2    10\n  1.6559409529024724E-01 b      1336     2    11\n  2.1265916540938158E-02 b      1337     2    12\n  1.5862407028397876E-01 b      1338     2    13\n -2.1985197211771605E-02 b      1339     2    14\n  1.5002849308447164E-01 b      1340     2    15\n  7.0386606318518688E-02 b      1341     2    16\n  6.9614857271612859E-03 b      1342     2    17\n -2.3291413753757897E-02 b      1343     2    18\n  1.9790710575965719E-02 b      1344     2    19\n -1.6163972430455469E-02 b      1345     2    20\n -1.0894024092746835E-01 b      1346     2    21\n -1.2009645555447425E-01 b      1347     2    22\n -4.4749561974041835E-01 b      1348     2    23\n -2.7170757071715751E-01 b      1349     2    24\n -1.5358955395942009E-02 b      1350     2    25\n -1.8270466084736126E+00 a      1351     2     1     3     1\n  1.5802745399953280E+00 a      1352     2     2     3     1\n  1.4820018158747241E+00 a      1353     2     3     3     1\n  8.2937813438335606E-01 a      1354     2     4     3     1\n  6.6866069084042690E-01 a      1355     2     5     3     1\n -2.1665682393253887E+00 a      1356     2     6     3     1\n  3.1763367480266615E+00 a      1357     2     7     3     1\n -7.2271718711417943E-01 a      1358     2     8     3     1\n  3.2697633962118711E-01 a      1359     2     9     3     1\n  2.6024761370742118E+00 a      1360     2    10     3     1\n -1.0557927824958486E+00 a      1361     2    11     3     1\n -7.3645901155077520E-01 a      1362     2    12     3     1\n -1.0754962079774424E+00 a      1363     2    13     3     1\n -2.5698876576286822E-01 a      1364     2    14     3     1\n -7.6468166729267273E-01 a      1365     2    15     3     1\n -1.4720372924124216E+00 a      1366     2    16     3     1\n  3.9528354982621687E-02 a      1367     2    17     3     1\n -5.0602366702724944E-01 a      1368     2    18     3     1\n  3.0555310325850940E+00 a      1369     2    19     3     1\n  2.0788973328329532E+00 a      1370     2    20     3     1\n  1.8705729605484223E+00 a      1371     2    21     3     1\n  1.1839601179292556E+00 a      1372     2    22     3     1\n  3.2633028162307482E+00 a      1373     2    23     3     1\n  2.1033867318386021E+00 a      1374     2    24     3     1\n  2.0110968315738500E+00 a      1375     2    25     3     1\n -7.6018302849179031E-01 b      1376     3     1\n"
  },
  {
    "path": "examples/nnp-predict/H2O_RPBE-D3_4G/weightse.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -3.4531786615003407E-01 a         1     0     1     1     1\n -1.0003362228928364E-01 a         2     0     1     1     2\n -1.5433275835142375E-02 a         3     0     1     1     3\n -1.5122895095655833E-01 a         4     0     1     1     4\n  3.3238696153791526E-02 a         5     0     1     1     5\n -7.0316925865201038E-02 a         6     0     1     1     6\n -5.0805243599282637E-02 a         7     0     1     1     7\n  3.1659070745866241E-01 a         8     0     1     1     8\n -2.7930527153363977E-01 a         9     0     1     1     9\n -3.9116687694574832E-02 a        10     0     1     1    10\n  1.4882521484906723E-02 a        11     0     1     1    11\n -6.8020411576537416E-03 a        12     0     1     1    12\n -1.2112438250998128E-01 a        13     0     1     1    13\n -8.6621448058049535E-04 a        14     0     1     1    14\n  7.8441821320904673E-02 a        15     0     1     1    15\n -1.6494842052807709E-01 a        16     0     1     1    16\n -1.8997846866784318E-03 a        17     0     1     1    17\n -9.9594056955360499E-02 a        18     0     1     1    18\n -2.2601095461026455E-01 a        19     0     1     1    19\n -1.9957822748373200E-01 a        20     0     1     1    20\n  2.3486964354304057E-01 a        21     0     1     1    21\n -1.1600222912099230E-01 a        22     0     1     1    22\n  7.0265605910580592E-02 a        23     0     1     1    23\n  1.0852901367427588E-01 a        24     0     1     1    24\n  3.3262566098593743E-01 a        25     0     1     1    25\n  4.2278860258215684E-01 a        26     0     2     1     1\n -1.0840988274340525E-01 a        27     0     2     1     2\n -4.2017212187646069E-01 a        28     0     2     1     3\n -7.1275858678849599E-02 a        29     0     2     1     4\n  1.5415415355299810E-02 a        30     0     2     1     5\n  1.4441474871907597E-01 a        31     0     2     1     6\n  4.8538196921161597E-02 a        32     0     2     1     7\n  3.1058860712110581E-01 a        33     0     2     1     8\n -8.4399741325948407E-02 a        34     0     2     1     9\n -1.5274430816729428E-01 a        35     0     2     1    10\n  9.4555481151992429E-02 a        36     0     2     1    11\n  4.2533721339722518E-03 a        37     0     2     1    12\n -5.9450358796822145E-02 a        38     0     2     1    13\n  3.0548919278022402E-01 a        39     0     2     1    14\n  1.6238493047140520E-01 a        40     0     2     1    15\n -1.7426182882696878E-01 a        41     0     2     1    16\n -2.7663974243898676E-02 a        42     0     2     1    17\n  2.0440686188407597E-01 a        43     0     2     1    18\n  2.1238804092370980E-01 a        44     0     2     1    19\n  4.7485936528699903E-02 a        45     0     2     1    20\n  4.8421019737378182E-02 a        46     0     2     1    21\n -3.9569171670917686E-01 a        47     0     2     1    22\n  2.0224161174635655E-01 a        48     0     2     1    23\n -2.8550069555208829E-01 a        49     0     2     1    24\n  1.8436952668783302E-01 a        50     0     2     1    25\n -8.7527887807969065E-02 a        51     0     3     1     1\n -5.7014264589630367E-02 a        52     0     3     1     2\n  1.0202279001603556E-01 a        53     0     3     1     3\n -9.8342553914432723E-02 a        54     0     3     1     4\n  2.6887002812449854E-02 a        55     0     3     1     5\n  4.7580250133796270E-02 a        56     0     3     1     6\n -5.5712925672191174E-03 a        57     0     3     1     7\n  2.3835152302921292E-01 a        58     0     3     1     8\n  2.9978300941181080E-01 a        59     0     3     1     9\n -2.0010212567858968E-02 a        60     0     3     1    10\n  2.1117827856881541E-01 a        61     0     3     1    11\n  3.5401914682930824E-01 a        62     0     3     1    12\n -1.3351248204146168E-01 a        63     0     3     1    13\n -3.7105897740294536E-01 a        64     0     3     1    14\n -1.2213344623610659E-01 a        65     0     3     1    15\n -2.8604717820884878E-01 a        66     0     3     1    16\n  2.4826721262243526E-01 a        67     0     3     1    17\n  1.1261785910666654E-01 a        68     0     3     1    18\n -2.1204967166791197E-01 a        69     0     3     1    19\n  1.2483770288687310E-01 a        70     0     3     1    20\n -8.3971651194475583E-02 a        71     0     3     1    21\n  1.1488214631775616E-02 a        72     0     3     1    22\n  1.4552745654238328E-01 a        73     0     3     1    23\n  2.9461015651859346E-01 a        74     0     3     1    24\n  1.8171253799583939E-01 a        75     0     3     1    25\n  2.1619162621311358E-01 a        76     0     4     1     1\n  2.4634519079627926E-01 a        77     0     4     1     2\n -3.7563351388204858E-01 a        78     0     4     1     3\n -2.4049619566234334E-01 a        79     0     4     1     4\n  8.5866493746722783E-02 a        80     0     4     1     5\n  3.7036945868035703E-01 a        81     0     4     1     6\n -1.2592267398238008E-01 a        82     0     4     1     7\n  4.2025170417995117E-01 a        83     0     4     1     8\n -2.1011792262808054E-01 a        84     0     4     1     9\n  1.0144402549086637E-01 a        85     0     4     1    10\n -1.8369712607998870E-01 a        86     0     4     1    11\n  5.5155679955379466E-01 a        87     0     4     1    12\n  1.4262404281309646E-01 a        88     0     4     1    13\n -3.8627312136356118E-01 a        89     0     4     1    14\n  2.3003502792837222E-02 a        90     0     4     1    15\n -2.6303722140597691E-02 a        91     0     4     1    16\n  2.8159609608065999E-02 a        92     0     4     1    17\n  3.4333018146444039E-01 a        93     0     4     1    18\n -2.8673491116739336E-01 a        94     0     4     1    19\n -1.1162004328775915E-01 a        95     0     4     1    20\n -1.2689420307780677E-01 a        96     0     4     1    21\n  1.2856171987552692E-01 a        97     0     4     1    22\n  1.4134777486693811E-01 a        98     0     4     1    23\n  5.4298079299850012E-02 a        99     0     4     1    24\n -2.6789828290418688E-01 a       100     0     4     1    25\n -4.5422551065028305E-01 a       101     0     5     1     1\n -4.2783900262337538E-01 a       102     0     5     1     2\n -1.3732535911038865E-02 a       103     0     5     1     3\n  2.9868076965498258E-01 a       104     0     5     1     4\n -1.1575425553448000E-02 a       105     0     5     1     5\n -2.4790596366909640E-01 a       106     0     5     1     6\n  3.6605565536420698E-01 a       107     0     5     1     7\n  6.7315140708449117E-01 a       108     0     5     1     8\n  1.9314117170787923E-01 a       109     0     5     1     9\n -1.6582843754209717E-01 a       110     0     5     1    10\n -2.3939775241874067E-01 a       111     0     5     1    11\n -4.5175853580226311E-01 a       112     0     5     1    12\n -2.3592463751617079E-01 a       113     0     5     1    13\n  3.4721604313952981E-01 a       114     0     5     1    14\n  2.0471795887123431E-01 a       115     0     5     1    15\n -3.2542437021161358E-01 a       116     0     5     1    16\n -1.9422897402049319E-01 a       117     0     5     1    17\n -2.8480217393288616E-02 a       118     0     5     1    18\n  3.5544466869922436E-01 a       119     0     5     1    19\n  2.6579267339506479E-01 a       120     0     5     1    20\n -1.8140011977070039E-01 a       121     0     5     1    21\n -5.0894484510878846E-01 a       122     0     5     1    22\n -3.3855370228811738E-01 a       123     0     5     1    23\n -4.3917685813560320E-01 a       124     0     5     1    24\n -2.7943385108854496E-01 a       125     0     5     1    25\n -4.7350251733211869E-02 a       126     0     6     1     1\n  3.4240582915353684E-01 a       127     0     6     1     2\n -4.0954673174559042E-01 a       128     0     6     1     3\n -6.4261848832674440E-02 a       129     0     6     1     4\n -4.4598976089287590E-01 a       130     0     6     1     5\n -1.2189590647812509E-01 a       131     0     6     1     6\n  2.3908498198592384E-01 a       132     0     6     1     7\n  2.8711790065281756E-01 a       133     0     6     1     8\n -2.4590004905813723E-01 a       134     0     6     1     9\n  7.5293201523459655E-02 a       135     0     6     1    10\n  2.6317404900538699E-01 a       136     0     6     1    11\n -2.6288516417423907E-01 a       137     0     6     1    12\n -2.1439365613659067E-01 a       138     0     6     1    13\n -2.7328345705889728E-01 a       139     0     6     1    14\n  8.0876116286111008E-02 a       140     0     6     1    15\n -2.3975676697775766E-02 a       141     0     6     1    16\n -1.3922895770105134E-01 a       142     0     6     1    17\n  4.3087356254117692E-01 a       143     0     6     1    18\n 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4.3859004476502883E-01 a      1237     1    19     2    12\n  8.1577246323102581E-01 a      1238     1    19     2    13\n  1.4889955136758481E-01 a      1239     1    19     2    14\n  3.7146374823549660E-01 a      1240     1    19     2    15\n -9.2025876387606775E-01 a      1241     1    19     2    16\n -3.2724398486380690E-01 a      1242     1    19     2    17\n -1.0999839574339194E-01 a      1243     1    19     2    18\n -8.9289100638629260E-01 a      1244     1    19     2    19\n  1.8594960556711942E-01 a      1245     1    19     2    20\n  1.8355315298372463E-01 a      1246     1    19     2    21\n  1.5999076654312556E+00 a      1247     1    19     2    22\n  3.4678898127802220E-02 a      1248     1    19     2    23\n -5.3920020422392245E-01 a      1249     1    19     2    24\n -1.9733093580614286E-01 a      1250     1    19     2    25\n  2.0145042768145338E-01 a      1251     1    20     2     1\n  1.1747857201766843E-02 a      1252     1    20     2     2\n  1.2827723892304707E-01 a      1253     1    20     2     3\n  2.5533892695808669E-01 a      1254     1    20     2     4\n -1.0785758156361444E-02 a      1255     1    20     2     5\n -1.0000547469978285E-01 a      1256     1    20     2     6\n -7.1541041864891630E-02 a      1257     1    20     2     7\n -5.2922347762855626E-01 a      1258     1    20     2     8\n  8.9884575963143767E-02 a      1259     1    20     2     9\n  2.9701908716085351E-01 a      1260     1    20     2    10\n -4.1238891985156456E-01 a      1261     1    20     2    11\n  6.6826227001468799E-02 a      1262     1    20     2    12\n  3.1394206053262091E-01 a      1263     1    20     2    13\n  4.0890581430269485E-01 a      1264     1    20     2    14\n  4.6879884954120055E-01 a      1265     1    20     2    15\n -7.9925198594522717E-01 a      1266     1    20     2    16\n -4.5015069897485732E-01 a      1267     1    20     2    17\n  2.1922362235710371E-01 a      1268     1    20     2    18\n -1.8737927014548744E-01 a      1269     1    20     2    19\n  2.3770328303205170E-02 a      1270     1    20     2    20\n -2.7340475016844351E-01 a      1271     1    20     2    21\n  4.6677953859330129E-01 a      1272     1    20     2    22\n -3.0300929627999307E-01 a      1273     1    20     2    23\n -4.4787818865918122E-01 a      1274     1    20     2    24\n  3.0789684341085510E-01 a      1275     1    20     2    25\n -2.4461599386777660E-01 a      1276     1    21     2     1\n  1.5817937882646294E-01 a      1277     1    21     2     2\n -2.4897478655978675E-01 a      1278     1    21     2     3\n  2.4236973421438390E-01 a      1279     1    21     2     4\n  8.2892178006443981E-02 a      1280     1    21     2     5\n  2.7824668591937246E-02 a      1281     1    21     2     6\n -8.0580423755964178E-02 a      1282     1    21     2     7\n  2.2627351147812719E-01 a      1283     1    21     2     8\n -7.5422447776318416E-02 a      1284     1    21     2     9\n  2.0100090016277994E-02 a      1285     1    21     2    10\n -2.1087797744477008E-01 a      1286     1    21     2    11\n  4.0086904628319549E-02 a      1287     1    21     2    12\n  4.9737530618879217E-01 a      1288     1    21     2    13\n -3.3171939742510775E-01 a      1289     1    21     2    14\n  2.9595950347981053E-02 a      1290     1    21     2    15\n -1.8852997738898525E-01 a      1291     1    21     2    16\n -2.1511013924449884E-01 a      1292     1    21     2    17\n  2.7071130434206053E-01 a      1293     1    21     2    18\n  1.2265208555763522E-02 a      1294     1    21     2    19\n  2.4242375646088615E-01 a      1295     1    21     2    20\n -2.4921054284300306E-01 a      1296     1    21     2    21\n  2.4825643102998438E-01 a      1297     1    21     2    22\n  2.4486058613269721E-01 a      1298     1    21     2    23\n  3.1447386157572865E-01 a      1299     1    21     2    24\n  1.8273218035893060E-01 a      1300     1    21     2    25\n  2.2882978198454809E-01 a      1301     1    22     2     1\n  5.7341974499506743E-01 a      1302     1    22     2     2\n -2.6398377969115516E-01 a      1303     1    22     2     3\n -3.6169741690706803E-02 a      1304     1    22     2     4\n -2.9828673613560619E-01 a      1305     1    22     2     5\n  2.4193423433243971E-01 a      1306     1    22     2     6\n  1.8116031950581407E-01 a      1307     1    22     2     7\n  4.7128507488802907E-01 a      1308     1    22     2     8\n -7.2968670923330481E-02 a      1309     1    22     2     9\n -5.0355927227141228E-01 a      1310     1    22     2    10\n  1.9770124567199476E-01 a      1311     1    22     2    11\n -2.5962093788675078E-01 a      1312     1    22     2    12\n -2.1786835643746341E-01 a      1313     1    22     2    13\n -4.6155093890848553E-01 a      1314     1    22     2    14\n -1.5651681006031834E-01 a      1315     1    22     2    15\n  9.0934631985051328E-01 a      1316     1    22     2    16\n  5.4562517655372822E-01 a      1317     1    22     2    17\n  6.9616338991758467E-02 a      1318     1    22     2    18\n  8.8417813278759527E-01 a      1319     1    22     2    19\n  1.5570268927160280E-01 a      1320     1    22     2    20\n -2.7193674150801217E-01 a      1321     1    22     2    21\n -7.7919659590520751E-01 a      1322     1    22     2    22\n -1.7161092398057576E-01 a      1323     1    22     2    23\n  2.9900347360889096E-01 a      1324     1    22     2    24\n  6.5832855633820561E-02 a      1325     1    22     2    25\n -3.0746866021776970E-01 a      1326     1    23     2     1\n -5.7654997532860200E-02 a      1327     1    23     2     2\n -1.3608218907819614E-01 a      1328     1    23     2     3\n -9.8638164148207461E-02 a      1329     1    23     2     4\n -6.3253360051096247E-02 a      1330     1    23     2     5\n  1.0308130023825343E-01 a      1331     1    23     2     6\n -1.3019373590261840E-01 a      1332     1    23     2     7\n  2.9013207004568758E-01 a      1333     1    23     2     8\n  2.7220522531111990E-01 a      1334     1    23     2     9\n  1.8634380410292258E-02 a      1335     1    23     2    10\n  8.5537145801365608E-03 a      1336     1    23     2    11\n -1.9143292677970331E-01 a      1337     1    23     2    12\n -3.2131877947769677E-01 a      1338     1    23     2    13\n -3.1955272697819465E-01 a      1339     1    23     2    14\n  2.7920939480677587E-01 a      1340     1    23     2    15\n  2.1267122656724891E-01 a      1341     1    23     2    16\n -3.4243132021535833E-01 a      1342     1    23     2    17\n  3.7220855986706836E-01 a      1343     1    23     2    18\n -7.5033577881319258E-02 a      1344     1    23     2    19\n  3.2539167071181202E-01 a      1345     1    23     2    20\n  1.7315050759138945E-01 a      1346     1    23     2    21\n  3.1041003725394672E-01 a      1347     1    23     2    22\n  9.4685609412635069E-02 a      1348     1    23     2    23\n  1.5101845732776012E-01 a      1349     1    23     2    24\n  2.5923884184003920E-01 a      1350     1    23     2    25\n -8.2100743725374792E-02 a      1351     1    24     2     1\n  6.6251454174013999E-02 a      1352     1    24     2     2\n -3.6069715693407617E-01 a      1353     1    24     2     3\n -2.3634274879842484E-02 a      1354     1    24     2     4\n -1.2760525506158854E-01 a      1355     1    24     2     5\n -1.2765598196366132E-01 a      1356     1    24     2     6\n  2.6162333063697940E-01 a      1357     1    24     2     7\n  3.3274836777216382E-01 a      1358     1    24     2     8\n -1.3252316394506330E-01 a      1359     1    24     2     9\n -4.7511836885821307E-01 a      1360     1    24     2    10\n  3.5610186415813272E-01 a      1361     1    24     2    11\n -1.3422298432257843E-01 a      1362     1    24     2    12\n -3.4067209382217406E-01 a      1363     1    24     2    13\n -1.8325479900208286E-01 a      1364     1    24     2    14\n -4.3636625717826744E-01 a      1365     1    24     2    15\n  5.7665322931668084E-01 a      1366     1    24     2    16\n -1.3327237856262852E-01 a      1367     1    24     2    17\n -7.5189586314667614E-02 a      1368     1    24     2    18\n  6.3093239676755619E-01 a      1369     1    24     2    19\n  1.0641544772503221E-01 a      1370     1    24     2    20\n  1.2503230674538318E-01 a      1371     1    24     2    21\n -2.3108390100611362E-01 a      1372     1    24     2    22\n  2.8963336721624094E-01 a      1373     1    24     2    23\n  2.4463626139469948E-02 a      1374     1    24     2    24\n -1.6484051483184625E-01 a      1375     1    24     2    25\n -2.8139659980766502E-01 a      1376     1    25     2     1\n -1.3106400528938578E-01 a      1377     1    25     2     2\n  7.0515943245970950E-02 a      1378     1    25     2     3\n  1.2711436188386663E-01 a      1379     1    25     2     4\n  2.3198064375455796E-02 a      1380     1    25     2     5\n  3.1955855998204219E-01 a      1381     1    25     2     6\n -1.5097351247469398E-01 a      1382     1    25     2     7\n  1.7143719090779799E-01 a      1383     1    25     2     8\n -9.3402691071478972E-02 a      1384     1    25     2     9\n -2.4664946171917934E-01 a      1385     1    25     2    10\n  9.1522701272771984E-02 a      1386     1    25     2    11\n  5.7895741445414982E-03 a      1387     1    25     2    12\n -7.5360219755385288E-02 a      1388     1    25     2    13\n -1.6643080859760705E-02 a      1389     1    25     2    14\n -3.1967546772063848E-01 a      1390     1    25     2    15\n -2.5514463252272185E-01 a      1391     1    25     2    16\n  2.0181166111021745E-01 a      1392     1    25     2    17\n -1.8054511533036749E-01 a      1393     1    25     2    18\n  8.3888158136019103E-02 a      1394     1    25     2    19\n -2.7506673620638344E-01 a      1395     1    25     2    20\n  4.6013899128192558E-02 a      1396     1    25     2    21\n -4.3954716032220192E-01 a      1397     1    25     2    22\n  1.4605845067555162E-01 a      1398     1    25     2    23\n  2.7811754068570532E-01 a      1399     1    25     2    24\n -2.4015743980873919E-01 a      1400     1    25     2    25\n -2.2226254126911879E-01 b      1401     2     1\n -2.2171655100347194E-02 b      1402     2     2\n  1.2417118547721331E-01 b      1403     2     3\n  1.2086294623870163E-01 b      1404     2     4\n  1.5892429207768705E-02 b      1405     2     5\n -1.3711892658584193E-01 b      1406     2     6\n -1.4457762806643845E-01 b      1407     2     7\n  2.9550995456849999E-03 b      1408     2     8\n  2.9686400030337522E-02 b      1409     2     9\n -3.6481954369140979E-02 b      1410     2    10\n -1.2812576153868452E-01 b      1411     2    11\n -2.1167372194094633E-03 b      1412     2    12\n  2.1886413427559059E-01 b      1413     2    13\n  1.0758741658152222E-01 b      1414     2    14\n  1.1466380067910238E-01 b      1415     2    15\n  1.0166917870812149E-01 b      1416     2    16\n -1.6070622391759457E-01 b      1417     2    17\n -3.2815585789910251E-01 b      1418     2    18\n  1.9127766356655418E-01 b      1419     2    19\n  1.2163804822786453E-01 b      1420     2    20\n  8.2545039868782408E-02 b      1421     2    21\n -3.1429059972549633E-02 b      1422     2    22\n  1.8785796074914062E-02 b      1423     2    23\n  1.2466450958963603E-01 b      1424     2    24\n  7.2063405137791081E-02 b      1425     2    25\n -5.4308794634836177E-01 a      1426     2     1     3     1\n -1.4047995526079058E+00 a      1427     2     2     3     1\n  8.2624720498465842E-01 a      1428     2     3     3     1\n  3.9549907903577303E-01 a      1429     2     4     3     1\n  1.6001026778630774E+00 a      1430     2     5     3     1\n -1.7101430130199713E-01 a      1431     2     6     3     1\n -7.0068541964058839E-01 a      1432     2     7     3     1\n -1.5222967556008828E+00 a      1433     2     8     3     1\n -7.3562167316229207E-02 a      1434     2     9     3     1\n  2.6156176053486280E+00 a      1435     2    10     3     1\n -7.6197516604844173E-01 a      1436     2    11     3     1\n  1.7273423533836987E+00 a      1437     2    12     3     1\n  3.1970786687459736E+00 a      1438     2    13     3     1\n  1.3858046810800617E+00 a      1439     2    14     3     1\n  1.0302729531812271E+00 a      1440     2    15     3     1\n -3.1672317669101999E+00 a      1441     2    16     3     1\n -1.3153812827698301E+00 a      1442     2    17     3     1\n -1.0230242507541847E+00 a      1443     2    18     3     1\n -2.4990309158205108E+00 a      1444     2    19     3     1\n  1.8924086252841982E-01 a      1445     2    20     3     1\n  3.6807232875788304E-01 a      1446     2    21     3     1\n  2.6303395313154208E+00 a      1447     2    22     3     1\n  5.9008393166257438E-02 a      1448     2    23     3     1\n -1.0729584735365090E+00 a      1449     2    24     3     1\n  2.4233675092345897E-01 a      1450     2    25     3     1\n  7.6018302849182362E-01 b      1451     3     1\n"
  },
  {
    "path": "examples/nnp-prune/Cu2S_PBE/input.nn",
    "content": "###############################################################################\n# HDNNP for copper sulfide Cu2S\n###############################################################################\n# Length unit     : Angstrom\n# Energy unit     : eV\n# Reference method: PBE\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.8640662064628053E+00\nconv_energy   7.3890846653659121E+00\nconv_length   6.1376931796181502E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type.\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n"
  },
  {
    "path": "examples/nnp-prune/Cu2S_PBE/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   9.1739161189824411E-08   7.0593095050533450E-01   2.2372649929284196E-02   9.6379208796011293E-02\n         1          2   2.6433999906765265E-01   2.4749666370750676E+00   1.0378805142792313E+00   1.9413782463770093E-01\n         1          3   1.5504686427401054E-05   1.4168627312588329E+00   5.5254915214857578E-02   2.1495058826125538E-01\n         1          4   1.4086411910634238E+00   4.7388215758712082E+00   3.1031877925923803E+00   3.5864448236496921E-01\n         1          5   9.8043626772015909E-04   1.9535901883323099E+00   1.1429456309160095E-01   2.2901461288065855E-01\n         1          6   2.2158364445227399E+00   6.0748308460582043E+00   3.8835182764170546E+00   3.9299243538518969E-01\n         1          7   1.0255080523534783E+00   5.1401074554660049E+00   2.5810215644603796E+00   4.3835591238870431E-01\n         1          8   4.8489829707261999E-03   3.9129781874325281E-01   4.7557455423079396E-02   2.7778419734655713E-02\n         1          9   9.3223803365223998E-02   2.8346930075434797E+00   6.0185719975366336E-01   3.1949957606875956E-01\n         1         10   6.7206749586119430E-01   4.4876923880381465E+00   2.1991872165248538E+00   4.1504796440380803E-01\n         1         11   2.2128378766968923E-02   8.6593017344520318E-01   1.4060436434125115E-01   7.5838421599526348E-02\n         1         12   8.4205124330445313E-01   7.0656885702864862E+00   2.9013712601439368E+00   7.3052821449417049E-01\n         1         13   1.4518778507164800E+00   9.6462711741708382E+00   4.3715329035264965E+00   8.3811671947643118E-01\n         1         14   2.4300884834352513E-06   5.3039215356450418E-02   2.8067394350178213E-04   1.6541693025921896E-03\n         1         15   4.3805855934107564E-04   3.3431366727997386E-01   1.5056637491023487E-02   3.6381498406602590E-02\n         1         16   1.8742403996648012E-02   5.3094282134884740E-01   1.9287359264197504E-01   5.3785992354357007E-02\n         1         17   5.6391705067135155E-03   2.7103176024192799E-01   3.6199336036120536E-02   2.2235092628611220E-02\n         1         18   5.8157340520125522E-01   3.0394483797974066E+00   1.5432926655352674E+00   2.9013849228704902E-01\n         1         19   3.5474335876025032E-01   2.8914948266501281E+00   1.2453633098426364E+00   2.6070492382053573E-01\n         1         20   1.3050150224953865E-03   2.0977615521049353E-01   1.6466279986318652E-02   1.6175233794254219E-02\n         1         21   3.3625763520090814E-02   1.6019727512861448E+00   2.6707302954572526E-01   1.9158906783856428E-01\n         1         22   3.5314748293148263E-01   2.5968432133168928E+00   1.2041087980295160E+00   2.3880745648555143E-01\n         1         23   5.6279184570511148E-03   4.8263719913200909E-01   4.8674878532957294E-02   4.5579012837321450E-02\n         1         24   3.5640890668898983E-01   3.9354254479681789E+00   1.3506519169134916E+00   4.3100694380807969E-01\n         1         25   7.1435545388184229E-01   5.4083380133399706E+00   2.3405335217844168E+00   4.7481787957091687E-01\n         1         26   6.0302894280955782E-07   2.4282702757490063E-02   1.0392381208153868E-04   6.9514343858439293E-04\n         1         27   1.4152015883516988E-04   1.8793440136817721E-01   6.7319944252965166E-03   1.8860146728064606E-02\n         1         28   7.6669273315039489E-03   2.8853650966579203E-01   9.6832241039761832E-02   2.8591400835791262E-02\n         1         29   1.4586287100215936E-03   1.2827520308122028E-01   1.2535333774723276E-02   1.2196652689168296E-02\n         1         30   2.4306078779227119E-01   1.5771292876622454E+00   7.3118666045976355E-01   1.6033491927751306E-01\n         1         31   1.5700215118676836E-01   1.4950427209078341E+00   6.2168623298528469E-01   1.3878720233016123E-01\n         1         32   8.0322135442977674E-08   9.1020506427165644E-03   1.1758299063219979E-04   7.2850621729108440E-04\n         1         33   3.8387499554503460E-05   4.6879099417593433E-02   2.2899299020297070E-03   6.3507919696978174E-03\n         1         34   2.5111603817039843E-07   2.6638155845094137E-02   3.5204871838944324E-04   2.1803344919789219E-03\n         1         35   7.8176366916082938E-04   1.2144199943350505E-01   1.0237823308897595E-02   1.5551953673898984E-02\n         1         36   6.0784771853405629E-03   1.5177813800129991E-01   4.5342256644197804E-02   1.4422755174681633E-02\n         1         37   6.5208235096380454E-08   6.8957085587219831E-03   8.4477914517405974E-05   5.1826403434160535E-04\n         1         38   5.1003186367566016E-04   3.3817704100212627E-02   5.0495259674331701E-03   4.2413701977289924E-03\n         1         39   3.0092380409832575E-01   3.9241027015819827E+00   1.6245850308330121E+00   3.6115017167195557E-01\n         1         40   2.9205060411645536E+00   2.0972699454192377E+01   1.0685030237788666E+01   1.8434608066664662E+00\n         1         41   5.8304225749625562E+00   3.3157582599900756E+01   1.6937338463410185E+01   2.8416990087236536E+00\n         1         42   2.8963706388516774E-01   3.4220973094358569E+00   1.3527222233246401E+00   2.9841578592458634E-01\n         1         43   3.3240856510350132E+00   1.9977206504626281E+01   1.0533032366441756E+01   1.8362183066460305E+00\n         1         44   5.5968160844972745E+00   2.9479500954936675E+01   1.4663357897716818E+01   2.4340402007751933E+00\n         1         45   7.3194532436105672E-02   1.4240027432637063E+00   4.6184059564430718E-01   1.0603619804309938E-01\n         1         46   7.4351404260172327E-01   6.1601360099088307E+00   3.0926623459215312E+00   5.2746971733324144E-01\n         1         47   1.0304047665725904E+00   9.5490875529313932E+00   4.6615470051220029E+00   8.8228607777747381E-01\n         1         48   5.3439780036913555E-02   6.0792049084128386E-01   2.0133541277710790E-01   4.7497199912796259E-02\n         1         49   1.0984946263275692E+00   5.3381605458179147E+00   2.9222626179881503E+00   4.9078113758325748E-01\n         1         50   9.3741001607568142E-01   6.0472356274080674E+00   2.8114797251218855E+00   5.0873676433244819E-01\n         1         51   1.1424085007079182E-01   2.3139492223359586E+00   7.5719953168832033E-01   2.0833570661709583E-01\n         1         52   1.4315113742496002E+00   1.3300925195398728E+01   5.8838374866614309E+00   1.2171600869775945E+00\n         1         53   3.5503714858105737E+00   2.1312715022502385E+01   1.0871674742056101E+01   1.8799426423890726E+00\n         1         54   1.0963309213378970E-01   2.0788696656585590E+00   6.3126459151902947E-01   1.7541529953806104E-01\n         1         55   1.6510272306266744E+00   1.2357046870783602E+01   5.7724472752012481E+00   1.1927743223366301E+00\n         1         56   3.3307522004182251E+00   1.8663597697385917E+01   9.2207406968320633E+00   1.5761279490996694E+00\n         1         57   2.7455727216146104E-02   9.1674320906634155E-01   2.1461170716720621E-01   6.1714021121502906E-02\n         1         58   3.6192386693953038E-01   3.8875893126984216E+00   1.7092032560335464E+00   3.4843371038350474E-01\n         1         59   5.6557210052590146E-01   6.1563972117346957E+00   2.9617726398537609E+00   5.9044611830216798E-01\n         1         60   2.0196364035104716E-02   3.3469617649847838E-01   9.3035775655912298E-02   2.7640180745065839E-02\n         1         61   5.5357670454431462E-01   3.1907980705952856E+00   1.5901399654465433E+00   3.0513520444755149E-01\n         1         62   5.3781344801473907E-01   3.6339755326587713E+00   1.6575261374157455E+00   3.1383714619102349E-01\n         1         63   9.6664268597268675E-05   1.4867672619417913E-01   4.3177785208556420E-03   8.2707901241799234E-03\n         1         64   1.2006437712525238E-02   1.1332481089585240E+00   1.2838035367153358E-01   1.3388538744183132E-01\n         1         65   2.0772479772511018E-01   1.8626169502984133E+00   8.2255201121385824E-01   1.7849382645365078E-01\n         1         66   8.7907438908811975E-05   1.2622839046469150E-01   4.4000149614673457E-03   1.1827043706432264E-02\n         1         67   1.3369106385547676E-02   8.7813896596785235E-01   1.1827747851010054E-01   1.1347348778532439E-01\n         1         68   1.7657303404092337E-01   1.4295433698727396E+00   6.2121356605669209E-01   1.2933064669650537E-01\n         1         69   2.8597998667575309E-03   3.7304172172637867E-01   3.7665097851475426E-02   3.7208167402427196E-02\n         1         70   1.5902143209986809E-05   2.6009225424800504E-02   7.2450937404019229E-04   2.4859888979869879E-03\n         1         71   4.7171431923273572E-03   1.6025670770457742E-01   2.8821358718588475E-02   1.9416774232856850E-02\n         1         72   1.5331295649388408E-02   1.9310943777686740E-01   6.9677412943044442E-02   1.7784064753732315E-02\n         2          1   2.4721472942648627E-02   1.5073065774351924E+00   5.1894025713961534E-01   1.2292746613848948E-01\n         2          2   2.4966843476303169E-01   2.6917832996745195E+00   1.5515938962961904E+00   2.2894178892035891E-01\n         2          3   1.8582961795319244E-03   3.8171243121869747E+00   1.1221679663414206E+00   3.9926224172528085E-01\n         2          4   6.9308990079045429E-01   3.9421018903882858E+00   1.9417591382085293E+00   2.7982355416028953E-01\n         2          5   5.2213352864915873E-02   5.9786240694290029E+00   2.7894744649522680E+00   6.8818475947171043E-01\n         2          6   3.4706330958249576E-01   2.8061894414477742E+00   1.2905107822301898E+00   2.5049917129048904E-01\n         2          7   5.6650782795607790E-01   6.0129804050995874E+00   3.4024808580901604E+00   5.3817898895468230E-01\n         2          8   8.2160472578002200E-02   2.1591157175155038E+00   9.5893716661004147E-01   2.2068746057755104E-01\n         2          9   9.7533565633843480E-02   8.0520717520847240E-01   3.9574121682754421E-01   7.2843087896835634E-02\n         2         10   7.5624736998622447E-02   1.2151161903363619E+00   4.2414909548153323E-01   1.1030205700397629E-01\n         2         11   3.8590027688988915E-01   3.4170303616374733E+00   1.5389187655267780E+00   2.9839201545750010E-01\n         2         12   1.2653139464575366E-01   3.3448693047411142E+00   9.0701446886275106E-01   3.0808232807716252E-01\n         2         13   3.5754079396564345E-02   2.3051636092543291E+00   4.5165801949286744E-01   2.0529180913687342E-01\n         2         14   1.7360244301899754E+00   9.1860981352526956E+00   5.0318013545245659E+00   7.7006828863188448E-01\n         2         15   5.6096556948092302E-01   6.9184291400548386E+00   2.5593433032311834E+00   7.0382259666666958E-01\n         2         16   2.7321455653550736E-03   2.6718628880300366E-01   6.8392239083035003E-02   1.8417271845608391E-02\n         2         17   1.4998879259624551E-04   2.8869834404308442E-01   3.2421219256901605E-02   2.1462316150937667E-02\n         2         18   9.6976148378458242E-03   6.9986551977156553E-01   7.4501947267367571E-02   9.2109247490457000E-02\n         2         19   7.5554776729931772E-01   3.8650650491408283E+00   2.1261658860729638E+00   2.9459249679651817E-01\n         2         20   2.2984860438624041E-01   2.2399640197541903E+00   8.4832685420611464E-01   2.2013029667841760E-01\n         2         21   3.1742242534198488E-02   6.9305314098138393E-01   2.0239450285654340E-01   6.2019223320811959E-02\n         2         22   1.6267388613945685E-01   1.8982342788109985E+00   8.1342448996901984E-01   1.7017885772188068E-01\n         2         23   4.3623299253776143E-02   1.8524213261728384E+00   4.3372964228967342E-01   1.6475284995752615E-01\n         2         24   1.1782155855406862E-02   1.3256780035707432E+00   2.0203673375826020E-01   1.2375770385162231E-01\n         2         25   9.5572013219445029E-01   5.1585503300832807E+00   2.7312178298449119E+00   4.5027566865612645E-01\n         2         26   2.1346552007948805E-01   3.7560054368796258E+00   1.2309867059977997E+00   3.8895981570570448E-01\n         2         27   1.0778454975081308E-03   1.6230009416534466E-01   3.4353839552470775E-02   1.0338804556484340E-02\n         2         28   4.1455680376600344E-05   1.3561930079689324E-01   1.3464607540962245E-02   9.4307016558753589E-03\n         2         29   2.9811923400491925E-03   3.9674788724187127E-01   3.2946560522656709E-02   5.3575100644579036E-02\n         2         30   4.0860996892032608E-01   2.1541090596644543E+00   1.1291055145629398E+00   1.6554701558125592E-01\n         2         31   8.7689965003411183E-02   1.1196100344004409E+00   3.9704096379805787E-01   1.1606734505235136E-01\n         2         32   2.0029888316796539E-05   1.7556653440553127E-02   1.4233102888664287E-03   1.3598121443903737E-03\n         2         33   5.2716716179610746E-06   4.4644993845652417E-02   1.7086280138653978E-03   4.2643079956046579E-03\n         2         34   8.8339290835669212E-07   1.2139204575362132E-02   4.1922038284938451E-04   1.5155281653507265E-03\n         2         35   1.2653672947005059E+00   8.9337925904902882E+00   4.2637335795708999E+00   5.9362291906692699E-01\n         2         36   4.3025897744283652E+00   2.4744209023066571E+01   1.4272525712868205E+01   1.9700222663219151E+00\n         2         37   2.9677470818795189E+00   2.5847640450705327E+01   1.1788593731598802E+01   2.3639335745006553E+00\n         2         38   4.8673248345854536E-01   6.9220258514917292E+00   2.9410791137038919E+00   5.0416378898015868E-01\n         2         39   4.7312413761643519E+00   2.4784350068345699E+01   1.4182436900763136E+01   1.9734981280505293E+00\n         2         40   2.7914940844674572E+00   2.2909604188642842E+01   1.0258913931047273E+01   2.0538117984713926E+00\n         2         41   5.1976352609600407E-01   3.0581982698648895E+00   1.1910833091075925E+00   2.2566892125976182E-01\n         2         42   1.0695804209866875E+00   7.2313250376604037E+00   3.9928775708897235E+00   5.8095727320582324E-01\n         2         43   8.4628209088378592E-01   7.5313801441068913E+00   3.3982729265620653E+00   7.1123273080942895E-01\n         2         44   7.0763463381880415E-02   1.2969398476188700E+00   3.1793764328087359E-01   1.3617384576811825E-01\n         2         45   1.3721123798749537E+00   6.3973513973729199E+00   3.7457022157866304E+00   5.0158792550110110E-01\n         2         46   6.3964342968618404E-01   4.7161013997028380E+00   1.9947659320351354E+00   4.2776493844298569E-01\n         2         47   8.6532747970285151E-01   6.1240088873304499E+00   2.7402018484921369E+00   4.0552538612845523E-01\n         2         48   2.5315105294788682E+00   1.5776758660822487E+01   8.7867531123795093E+00   1.2800885070636867E+00\n         2         49   1.5679508239487920E+00   1.6123025100421103E+01   6.9389600266532643E+00   1.5752331036924878E+00\n         2         50   2.4475421880204548E-01   4.5715135037651979E+00   1.7778621079614614E+00   3.3311384228682872E-01\n         2         51   2.8365798870360606E+00   1.5735394223700631E+01   8.7129345829426814E+00   1.2788947945672131E+00\n         2         52   1.4825266957775993E+00   1.4111085036729261E+01   5.9550381055833128E+00   1.3412575984240060E+00\n         2         53   2.9486345514961088E-01   2.1632897998459173E+00   7.6894782290828789E-01   1.6439255789853263E-01\n         2         54   6.1183454216254696E-01   4.7418024842673727E+00   2.4364672738977449E+00   3.8379810845509604E-01\n         2         55   4.2978046698724798E-01   4.7295979558909700E+00   2.0069121315341767E+00   4.7649159304923261E-01\n         2         56   3.3379248097225291E-02   8.3272635081969881E-01   1.7274845946125020E-01   8.7956031429209408E-02\n         2         57   8.2656009161897048E-01   3.9467471262168639E+00   2.2459243943426777E+00   3.1269124051179731E-01\n         2         58   3.1171589063801924E-01   2.7714452296122714E+00   1.1129251102859337E+00   2.6297335909685149E-01\n         2         59   2.6592109568248031E-02   5.6825603390221913E-01   2.0877471778793405E-01   4.9135988886466996E-02\n         2         60   7.2485536842319745E-02   1.1034806181844534E+00   4.5818934497666303E-01   1.0344323974312900E-01\n         2         61   5.9263838221524185E-03   1.2515028539804678E+00   2.4502825958578195E-01   1.1006546541667923E-01\n         2         62   3.5994334696395447E-03   3.9125406849266531E-01   8.9107610428087070E-02   3.1854933024728180E-02\n         2         63   7.2533340578499653E-02   1.0927078443379801E+00   4.4612155612487853E-01   1.0164232620041405E-01\n         2         64   5.4706332551405917E-03   9.8645463183530846E-01   1.9457952454956559E-01   8.6829363320211461E-02\n         2         65   1.7435002600794914E-04   5.6940854477051987E-02   3.9265019004702875E-03   5.9979210203388224E-03\n         2         66   2.1035187678847361E-02   2.2735828246294021E-01   9.5459655622289877E-02   2.0577872261152416E-02\n"
  },
  {
    "path": "examples/nnp-prune/Cu2S_PBE/sensitivity.016.out",
    "content": "################################################################################\n# Sensitivity analysis for element  S.\n################################################################################\n# Col  Name          Description\n################################################################################\n# 1    index         Symmetry function index.\n# 2    sens_msa_norm Mean square average sensitivity (normalized, sum = 100%).\n# 3    sens_max_norm Maximum sensitivity (normalized, sum = 100%).\n# 4    sens_msa_phys Mean square average sensitivity (physical energy units).\n# 5    sens_max_phys Maximum sensitivity (physical energy units).\n# 6    sens_msa_int  Mean square average sensitivity (internal units).\n# 7    sens_max_int  Maximum sensitivity (internal units).\n################################################################################################################\n#        1                2                3                4                5                6                7\n#    index    sens_msa_norm    sens_max_norm    sens_msa_phys    sens_max_phys     sens_msa_int     sens_max_int\n################################################################################################################\n         1   9.81569663E-01   7.37626688E-01   5.66182497E-01   6.77473179E-01   4.18357041E+00   5.00590668E+00\n         2   3.62998646E-01   3.52247492E-01   2.09382469E-01   3.23521683E-01   1.54714479E+00   2.39052911E+00\n         3   1.16651749E-01   2.08665575E-01   6.72862874E-02   1.91648882E-01   4.97184074E-01   1.41610981E+00\n         4   8.16030741E-01   5.96580920E-01   4.70697435E-01   5.47929703E-01   3.47802320E+00   4.04869896E+00\n         5   7.05657313E-02   8.32055308E-02   4.07032567E-02   7.64201138E-02   3.00759810E-01   5.64674691E-01\n         6   1.48293403E-01   1.29581022E-01   8.55376166E-02   1.19013680E-01   6.32044691E-01   8.79402158E-01\n         7   7.35879316E-02   7.22362729E-02   4.24465022E-02   6.63453997E-02   3.13640799E-01   4.90231776E-01\n         8   1.99541040E-01   4.34623440E-01   1.15097938E-01   3.99179867E-01   8.50468408E-01   2.94957383E+00\n         9   1.32469988E+00   2.59350064E+00   7.64104592E-01   2.38200048E+00   5.64603353E+00   1.76008032E+01\n        10   2.54753549E+00   1.84829045E+00   1.46945251E+00   1.69756223E+00   1.08579090E+01   1.25434310E+01\n        11   4.42623615E-01   7.02659995E-01   2.55311215E-01   6.45358022E-01   1.88651619E+00   4.76860506E+00\n        12   3.32872668E+00   3.48669150E+00   1.92005403E+00   3.20235155E+00   1.41874418E+01   2.36624468E+01\n        13   2.18156345E+00   1.98921512E+00   1.25835495E+00   1.82699449E+00   9.29809124E+00   1.34998169E+01\n        14   1.44793302E-01   2.78530771E-01   8.35187115E-02   2.55816567E-01   6.17126830E-01   1.89025027E+00\n        15   9.07274816E-01   1.21086111E+00   5.23328237E-01   1.11211530E+00   3.86691665E+00   8.21751413E+00\n        16   6.61636241E-01   4.93394736E-01   3.81640624E-01   4.53158360E-01   2.81997488E+00   3.34842549E+00\n        17   6.48477025E-01   5.68646071E-01   3.74050213E-01   5.22272943E-01   2.76388869E+00   3.85911899E+00\n        18   2.46833873E+00   2.39282078E+00   1.42377076E+00   2.19768608E+00   1.05203627E+01   1.62388885E+01\n        19   1.90796684E+00   1.51828232E+00   1.10054076E+00   1.39446629E+00   8.13198889E+00   1.03038295E+01\n        20   4.86123909E-01   9.00956720E-01   2.80402766E-01   8.27483635E-01   2.07191978E+00   6.11434664E+00\n        21   3.57997239E+00   4.94363400E+00   2.06497591E+00   4.54048029E+00   1.52582818E+01   3.35499933E+01\n        22   2.33993178E+00   1.71686740E+00   1.34970392E+00   1.57685674E+00   9.97307653E+00   1.16515280E+01\n        23   2.65230862E-01   5.72370316E-01   1.52988705E-01   5.25693476E-01   1.13044650E+00   3.88439360E+00\n        24   3.32098154E+00   4.38227456E+00   1.91558652E+00   4.02489975E+00   1.41544310E+01   2.97403250E+01\n        25   2.64873088E+00   1.91847008E+00   1.52782336E+00   1.76201871E+00   1.12892162E+01   1.30197054E+01\n        26   3.29975943E-01   4.63500507E-01   1.90334533E-01   4.25702007E-01   1.40639798E+00   3.14554818E+00\n        27   7.70981509E-01   1.04193096E+00   4.44712436E-01   9.56961420E-01   3.28601784E+00   7.07106895E+00\n        28   5.35904062E-01   4.01247556E-01   3.09116624E-01   3.68525789E-01   2.28408890E+00   2.72306825E+00\n        29   9.00897862E-01   7.77078600E-01   5.19649924E-01   7.13707784E-01   3.83973729E+00   5.27364724E+00\n        30   2.35682170E+00   2.55170535E+00   1.35944625E+00   2.34361360E+00   1.00450634E+01   1.73171593E+01\n        31   1.58857419E+00   1.27949049E+00   9.16310819E-01   1.17514795E+00   6.77069822E+00   8.68326772E+00\n        32   2.40512468E+00   2.67482192E+00   1.38730805E+00   2.45669000E+00   1.02509367E+01   1.81526904E+01\n        33   8.39809975E-01   6.82684514E-01   4.84413615E-01   6.27011543E-01   3.57937321E+00   4.63304138E+00\n        34   4.51544977E+00   4.32457072E+00   2.60457176E+00   3.97190166E+00   1.92454013E+01   2.93487177E+01\n        35   1.45413474E-01   3.19147957E-01   8.38764347E-02   2.93121418E-01   6.19770078E-01   2.16589898E+00\n        36   4.81892730E-01   3.38069510E-01   2.77962166E-01   3.10499917E-01   2.05388598E+00   2.29431018E+00\n        37   1.65079863E+00   1.33608018E+00   9.52202705E-01   1.22712275E+00   7.03590641E+00   9.06731388E+00\n        38   5.78733586E-01   4.80623362E-01   3.33821265E-01   4.41428493E-01   2.46663359E+00   3.26175251E+00\n        39   1.56671898E+00   1.67894718E+00   9.03704440E-01   1.54202892E+00   6.67754862E+00   1.13941822E+01\n        40   7.26532563E-01   1.31639676E+00   4.19073690E-01   1.20904451E+00   3.09657098E+00   8.93373227E+00\n        41   3.69327884E+00   3.15983605E+00   2.13033258E+00   2.90215120E+00   1.57412078E+01   2.14442409E+01\n        42   1.13249701E+00   1.21336646E+00   6.53239410E-01   1.11441634E+00   4.82684130E+00   8.23451669E+00\n        43   3.58135746E-01   8.09050367E-01   2.06577484E-01   7.43072252E-01   1.52641852E+00   5.49062378E+00\n        44   6.49743044E+00   4.99646295E+00   3.74780470E+00   4.58900103E+00   2.76928462E+01   3.39085172E+01\n        45   8.71684750E-01   8.59556054E-01   5.02799411E-01   7.89459196E-01   3.71522742E+00   5.83338084E+00\n        46   9.47079774E-01   8.27713236E-01   5.46288268E-01   7.60213163E-01   4.03657026E+00   5.61727942E+00\n        47   6.75493768E-01   7.20893167E-01   3.89633831E-01   6.62104277E-01   2.87903737E+00   4.89234456E+00\n        48   2.84744824E-01   4.21061173E-01   1.64244619E-01   3.86723604E-01   1.21361740E+00   2.85753345E+00\n        49   8.77731019E-01   1.37445471E+00   5.06286980E-01   1.26236783E+00   3.74099736E+00   9.32774279E+00\n        50   1.88631124E+00   1.58179068E+00   1.08804953E+00   1.45279554E+00   8.03969008E+00   1.07348292E+01\n        51   1.64507114E+00   1.74918524E+00   9.48899013E-01   1.60653906E+00   7.01149515E+00   1.18708531E+01\n        52   1.06382594E+00   1.63643346E+00   6.13629018E-01   1.50298220E+00   4.53415677E+00   1.11056627E+01\n        53   4.27322635E+00   3.51547487E+00   2.46485406E+00   3.22878764E+00   1.82130153E+01   2.38577852E+01\n        54   9.63177857E-01   1.06660364E+00   5.55573858E-01   9.79622036E-01   4.10518227E+00   7.23851017E+00\n        55   7.20037468E-01   1.49862829E+00   4.15327233E-01   1.37641505E+00   3.06888809E+00   1.01704473E+01\n        56   7.68574001E+00   5.91525053E+00   4.43323753E+00   5.43286143E+00   3.27575675E+01   4.01438731E+01\n        57   9.78630742E-01   9.24876467E-01   5.64487288E-01   8.49452725E-01   4.17104437E+00   6.27667810E+00\n        58   1.19862805E+00   1.04078167E+00   6.91384675E-01   9.55905852E-01   5.10869990E+00   7.06326927E+00\n        59   7.09156506E-01   7.19134817E-01   4.09050948E-01   6.60489321E-01   3.02251209E+00   4.88041151E+00\n        60   7.16530648E-01   6.76836513E-01   4.13304452E-01   6.21640447E-01   3.05394159E+00   4.59335390E+00\n        61   7.74455696E-01   1.32635167E+00   4.46716394E-01   1.21818759E+00   3.30082525E+00   9.00129125E+00\n        62   1.59892490E+00   1.47792265E+00   9.22281248E-01   1.35739795E+00   6.81481423E+00   1.00299284E+01\n        63   2.02129155E-01   2.67097571E-01   1.16590798E-01   2.45315745E-01   8.61499274E-01   1.81265881E+00\n        64   1.02707300E+00   1.03581655E+00   5.92429433E-01   9.51345638E-01   4.37751124E+00   7.02957346E+00\n        65   1.25093902E+00   1.04507575E+00   7.21558339E-01   9.59849750E-01   5.33165566E+00   7.09241107E+00\n        66   3.91125658E-01   6.61975614E-01   2.25606506E-01   6.07991455E-01   1.66702557E+00   4.49250034E+00\n        67   3.85217106E+00   3.04778704E+00   2.22198374E+00   2.79923978E+00   1.64184260E+01   2.06838198E+01\n        68   3.91977677E-01   4.43831706E-01   2.26097962E-01   4.07637199E-01   1.67065698E+00   3.01206577E+00\n        69   2.88864742E-01   2.82170355E-01   1.66621043E-01   2.59159342E-01   1.23117699E+00   1.91495032E+00\n        70   7.47352880E-01   7.77554513E-01   4.31083127E-01   7.14144887E-01   3.18530973E+00   5.27687703E+00\n        71   8.06058787E-01   9.92069234E-01   4.64945479E-01   9.11165917E-01   3.43552151E+00   6.73268210E+00\n        72   1.23039294E-01   1.36427899E-01   7.09707088E-02   1.25302194E-01   5.24408576E-01   9.25868519E-01\n"
  },
  {
    "path": "examples/nnp-prune/Cu2S_PBE/sensitivity.029.out",
    "content": "################################################################################\n# Sensitivity analysis for element Cu.\n################################################################################\n# Col  Name          Description\n################################################################################\n# 1    index         Symmetry function index.\n# 2    sens_msa_norm Mean square average sensitivity (normalized, sum = 100%).\n# 3    sens_max_norm Maximum sensitivity (normalized, sum = 100%).\n# 4    sens_msa_phys Mean square average sensitivity (physical energy units).\n# 5    sens_max_phys Maximum sensitivity (physical energy units).\n# 6    sens_msa_int  Mean square average sensitivity (internal units).\n# 7    sens_max_int  Maximum sensitivity (internal units).\n################################################################################################################\n#        1                2                3                4                5                6                7\n#    index    sens_msa_norm    sens_max_norm    sens_msa_phys    sens_max_phys     sens_msa_int     sens_max_int\n################################################################################################################\n         1   7.15586842E-01   5.68992975E-01   1.42118801E-01   2.21728152E-01   1.05012785E+00   1.63836808E+00\n         2   1.68501905E+00   1.42394692E+00   3.34652446E-01   5.54891067E-01   2.47277526E+00   4.10013708E+00\n         3   1.36669323E+00   9.92829531E-01   2.71431491E-01   3.86890992E-01   2.00563027E+00   2.85877030E+00\n         4   6.29829900E-01   5.40656580E-01   1.25087082E-01   2.10685877E-01   9.24279041E-01   1.55677578E+00\n         5   6.33578067E-01   4.10256860E-01   1.25831485E-01   1.59871034E-01   9.29779497E-01   1.18130061E+00\n         6   6.29482685E-01   6.35540616E-01   1.25018124E-01   2.47660783E-01   9.23769502E-01   1.82998650E+00\n         7   3.13728117E-01   2.50628315E-01   6.23078307E-02   9.76661497E-02   4.60397836E-01   7.21663449E-01\n         8   1.55525386E-01   2.66441981E-01   3.08880490E-02   1.03828502E-01   2.28234409E-01   7.67197589E-01\n         9   5.66458457E-02   8.50637797E-02   1.12501226E-02   3.31480975E-02   8.31281080E-02   2.44934099E-01\n        10   2.92981788E+00   2.76613270E+00   5.81875155E-01   1.07792102E+00   4.29952478E+00   7.96484970E+00\n        11   1.37103349E+00   1.42829021E+00   2.72293485E-01   5.56583582E-01   2.01199962E+00   4.11264321E+00\n        12   4.42573431E-01   6.10001585E-01   8.78970959E-02   2.37708601E-01   6.49479084E-01   1.75644898E+00\n        13   1.55385108E+00   1.83323640E+00   3.08601890E-01   7.14385125E-01   2.28028550E+00   5.27865217E+00\n        14   1.70698193E+00   2.77337645E+00   3.39014375E-01   1.08074381E+00   2.50500592E+00   7.98570749E+00\n        15   1.02766915E+00   1.23161776E+00   2.04099767E-01   4.79943237E-01   1.50811046E+00   3.54634121E+00\n        16   1.00472883E+00   1.05269488E+00   1.99543714E-01   4.10219636E-01   1.47444540E+00   3.03114762E+00\n        17   2.44789736E-01   2.48116212E-01   4.86163547E-02   9.66872203E-02   3.59230361E-01   7.14430056E-01\n        18   2.02341026E+00   1.95619876E+00   4.01858478E-01   7.62301741E-01   2.96936632E+00   5.63271210E+00\n        19   8.84413300E-01   1.71267753E+00   1.75648503E-01   6.67405116E-01   1.29788166E+00   4.93151291E+00\n        20   1.43242789E+00   1.27275022E+00   2.84486692E-01   4.95971946E-01   2.10209626E+00   3.66477870E+00\n        21   5.68647267E+00   4.59647101E+00   1.12935933E+00   1.79117681E+00   8.34493171E+00   1.32351571E+01\n        22   2.74225677E+00   1.99282623E+00   5.44624665E-01   7.76574923E-01   4.02427776E+00   5.73817786E+00\n        23   6.71146919E-01   8.00476565E-01   1.33292830E-01   3.11933885E-01   9.84912007E-01   2.30490588E+00\n        24   8.32760204E-01   1.55333382E+00   1.65389963E-01   6.05311228E-01   1.22208044E+00   4.47269591E+00\n        25   1.09957602E+00   1.61957255E+00   2.18380797E-01   6.31123482E-01   1.61363420E+00   4.66342484E+00\n        26   7.12071265E-01   1.00737131E+00   1.41420591E-01   3.92557708E-01   1.04496872E+00   2.90064214E+00\n        27   1.43058583E+00   1.18633085E+00   2.84120850E-01   4.62295595E-01   2.09939302E+00   3.41594129E+00\n        28   1.95003118E-01   1.83136076E-01   3.87285059E-02   7.13654215E-02   2.86168209E-01   5.27325142E-01\n        29   1.33881216E+00   1.45803499E+00   2.65894183E-01   5.68174682E-01   1.96471463E+00   4.19829083E+00\n        30   7.61235830E-01   1.25744805E+00   1.51184897E-01   4.90008916E-01   1.11711801E+00   3.62071737E+00\n        31   1.30894241E+00   1.18179473E+00   2.59961915E-01   4.60527936E-01   1.92088060E+00   3.40287991E+00\n        32   1.14484030E+00   8.04934986E-01   2.27370489E-01   3.13671266E-01   1.68005979E+00   2.31774354E+00\n        33   3.32052731E+00   2.24419548E+00   6.59471823E-01   8.74529807E-01   4.87289314E+00   6.46197478E+00\n        34   1.71791117E+00   1.38922320E+00   3.41184971E-01   5.41359746E-01   2.52104464E+00   4.00015300E+00\n        35   4.36716679E+00   3.72833398E+00   8.67339185E-01   1.45287664E+00   6.40884267E+00   1.07354285E+01\n        36   2.58132374E+00   2.73516759E+00   5.12662633E-01   1.06585438E+00   3.78810760E+00   7.87568825E+00\n        37   1.88680182E+00   2.12043705E+00   3.74727421E-01   8.26302975E-01   2.76889264E+00   6.10562264E+00\n        38   5.26013107E+00   3.89531135E+00   1.04468595E+00   1.51794525E+00   7.71927293E+00   1.12162260E+01\n        39   2.78195467E+00   3.02669368E+00   5.52508849E-01   1.17945779E+00   4.08253466E+00   8.71511345E+00\n        40   1.11578365E+00   1.35087347E+00   2.21599707E-01   5.26415423E-01   1.63741900E+00   3.88972813E+00\n        41   1.42580463E+00   1.19877586E+00   2.83171283E-01   4.67145233E-01   2.09237659E+00   3.45177568E+00\n        42   7.38415943E-01   1.02224671E+00   1.46652764E-01   3.98354431E-01   1.08362969E+00   2.94347462E+00\n        43   2.35189657E-01   4.24165629E-01   4.67097353E-02   1.65291076E-01   3.45142189E-01   1.22134975E+00\n        44   2.07995567E+00   1.97740254E+00   4.13088654E-01   7.70564541E-01   3.05234704E+00   5.69376663E+00\n        45   1.70169193E+00   2.21736441E+00   3.37963755E-01   8.64074132E-01   2.49724280E+00   6.38471692E+00\n        46   1.38049136E+00   1.55115853E+00   2.74171862E-01   6.04463548E-01   2.02587910E+00   4.46643234E+00\n        47   5.13192267E+00   4.35124492E+00   1.01922318E+00   1.69561583E+00   7.53112636E+00   1.25290489E+01\n        48   2.48465628E+00   2.61979252E+00   4.93464035E-01   1.02089442E+00   3.64624753E+00   7.54347529E+00\n        49   2.01104486E+00   2.18660911E+00   3.99402655E-01   8.52089248E-01   2.95122003E+00   6.29615959E+00\n        50   5.19229263E+00   3.97913721E+00   1.03121293E+00   1.55061095E+00   7.61971964E+00   1.14575956E+01\n        51   2.79089372E+00   3.61552631E+00   5.54284184E-01   1.40891716E+00   4.09565277E+00   1.04106082E+01\n        52   1.19834019E+00   1.55174688E+00   2.37995812E-01   6.04692820E-01   1.75857120E+00   4.46812644E+00\n        53   1.67999278E+00   1.35841901E+00   3.33654205E-01   5.29355810E-01   2.46539917E+00   3.91145490E+00\n        54   7.92396131E-01   1.00183794E+00   1.57373475E-01   3.90401435E-01   1.16284593E+00   2.88470926E+00\n        55   2.39094922E-01   4.38423132E-01   4.74853388E-02   1.70847014E-01   3.50873189E-01   1.26240305E+00\n        56   1.97752040E+00   1.99139454E+00   3.92744544E-01   7.76017014E-01   2.90202269E+00   5.73405542E+00\n        57   1.41722516E+00   1.87846237E+00   2.81467361E-01   7.32009020E-01   2.07978616E+00   5.40887662E+00\n        58   1.37910847E+00   1.77540270E+00   2.73897214E-01   6.91848189E-01   2.02384970E+00   5.11212485E+00\n        59   4.84192971E-01   6.72082224E-01   9.61629258E-02   2.61900508E-01   7.10556000E-01   1.93520503E+00\n        60   5.35948086E-01   7.09772277E-01   1.06441727E-01   2.76587764E-01   7.86506933E-01   2.04373041E+00\n        61   6.62575956E-01   5.35142587E-01   1.31590598E-01   2.08537156E-01   9.72334069E-01   1.54089870E+00\n        62   8.39225486E-01   7.54698647E-01   1.66673998E-01   2.94094907E-01   1.23156828E+00   2.17309217E+00\n        63   3.82629864E-01   5.51341994E-01   7.59920309E-02   2.14849825E-01   5.61511550E-01   1.58754355E+00\n        64   5.41462636E-01   5.31819722E-01   1.07536942E-01   2.07242284E-01   7.94599567E-01   1.53133078E+00\n        65   4.51391467E-01   4.89432585E-01   8.96483981E-02   1.90724644E-01   6.62419604E-01   1.40928054E+00\n        66   4.83446315E-01   4.25182416E-01   9.60146366E-02   1.65687302E-01   7.09460279E-01   1.22427751E+00\n"
  },
  {
    "path": "examples/nnp-prune/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-prune/H2O_RPBE-D3/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "examples/nnp-prune/H2O_RPBE-D3/sensitivity.001.out",
    "content": "################################################################################\n# Sensitivity analysis for element  H.\n################################################################################\n# Col  Name          Description\n################################################################################\n# 1    index         Symmetry function index.\n# 2    sens_msa_norm Mean square average sensitivity (normalized, sum = 100%).\n# 3    sens_max_norm Maximum sensitivity (normalized, sum = 100%).\n# 4    sens_msa_phys Mean square average sensitivity (physical energy units).\n# 5    sens_max_phys Maximum sensitivity (physical energy units).\n# 6    sens_msa_int  Mean square average sensitivity (internal units).\n# 7    sens_max_int  Maximum sensitivity (internal units).\n################################################################################################################\n#        1                2                3                4                5                6                7\n#    index    sens_msa_norm    sens_max_norm    sens_msa_phys    sens_max_phys     sens_msa_int     sens_max_int\n################################################################################################################\n         1   1.97170552E+00   3.02857692E+00   1.44013644E-01   4.29300706E-01   3.49459883E+01   1.04173028E+02\n         2   2.00719606E+00   3.25187967E+00   1.46605878E-01   4.60953866E-01   3.55750133E+01   1.11853905E+02\n         3   3.61027972E+00   5.52864200E+00   2.63695331E-01   7.83684871E-01   6.39876452E+01   1.90166998E+02\n         4   2.47220894E+00   4.62013389E+00   1.80570484E-01   6.54903869E-01   4.38167790E+01   1.58917324E+02\n         5   5.18851575E+00   6.63378652E+00   3.78969909E-01   9.40339081E-01   9.19598842E+01   2.28180314E+02\n         6   5.34656738E+00   5.80432546E+00   3.90514022E-01   8.22762995E-01   9.47611494E+01   1.99649597E+02\n         7   1.63881962E+00   3.97255475E+00   1.19699612E-01   5.63109542E-01   2.90460064E+01   1.36642744E+02\n         8   6.11078301E+00   5.88642162E+00   4.46332438E-01   8.34400124E-01   1.08305906E+02   2.02473433E+02\n         9   2.80797933E+00   3.04080020E+00   2.05095200E-01   4.31033356E-01   4.97678848E+01   1.04593469E+02\n        10   9.40951931E-01   2.04243583E+00   6.87272594E-02   2.89515230E-01   1.66771838E+01   7.02530368E+01\n        11   1.63711285E+00   1.65489411E+00   1.19574949E-01   2.34581200E-01   2.90157562E+01   5.69228835E+01\n        12   4.26603416E-01   8.26070923E-01   3.11591726E-02   1.17095534E-01   7.56100638E+00   2.84141074E+01\n        13   1.12319823E+00   9.51965296E-01   8.20385543E-02   1.34941058E-01   1.99072691E+01   3.27444574E+01\n        14   6.33097437E-01   8.32408066E-01   4.62415245E-02   1.17993824E-01   1.12208519E+01   2.86320842E+01\n        15   4.83942340E-01   1.40593209E+00   3.53472156E-02   1.99290840E-01   8.57726635E+00   4.83594135E+01\n        16   2.34792494E-01   6.96284037E-01   1.71492763E-02   9.86982456E-02   4.16140022E+00   2.39498678E+01\n        17   3.31460159E-01   6.96370054E-01   2.42098960E-02   9.87104386E-02   5.87471241E+00   2.39528265E+01\n        18   8.80621397E+00   5.66005131E+00   6.43207088E-01   8.02312138E-01   1.56079013E+02   1.94687044E+02\n        19   2.06707567E-01   4.74240485E-01   1.50979493E-02   6.72235774E-02   3.66363038E+00   1.63123041E+01\n        20   9.43776502E+00   7.49266845E+00   6.89335665E-01   1.06208557E+00   1.67272457E+02   2.57723012E+02\n        21   7.84750991E+00   7.25796961E+00   5.73183211E-01   1.02881702E+00   1.39087195E+02   2.49650148E+02\n        22   3.29975887E+00   4.24187543E+00   2.41014845E-01   6.01285741E-01   5.84840556E+01   1.45906484E+02\n        23   1.26930715E+01   9.62183105E+00   9.27103702E-01   1.36389432E+00   2.24968651E+02   3.30959163E+02\n        24   5.50627349E+00   3.69088976E+00   4.02178979E-01   5.23183535E-01   9.75917385E+01   1.26954399E+02\n        25   6.42521799E+00   4.26905940E+00   4.69298812E-01   6.05139068E-01   1.13878868E+02   1.46841523E+02\n        26   7.70221206E+00   5.10173610E+00   5.62570636E-01   7.23170970E-01   1.36511974E+02   1.75482847E+02\n        27   1.11005541E+00   1.31619699E+00   8.10786011E-02   1.86570891E-01   1.96743292E+01   4.52728228E+01\n"
  },
  {
    "path": "examples/nnp-prune/H2O_RPBE-D3/sensitivity.008.out",
    "content": "################################################################################\n# Sensitivity analysis for element  O.\n################################################################################\n# Col  Name          Description\n################################################################################\n# 1    index         Symmetry function index.\n# 2    sens_msa_norm Mean square average sensitivity (normalized, sum = 100%).\n# 3    sens_max_norm Maximum sensitivity (normalized, sum = 100%).\n# 4    sens_msa_phys Mean square average sensitivity (physical energy units).\n# 5    sens_max_phys Maximum sensitivity (physical energy units).\n# 6    sens_msa_int  Mean square average sensitivity (internal units).\n# 7    sens_max_int  Maximum sensitivity (internal units).\n################################################################################################################\n#        1                2                3                4                5                6                7\n#    index    sens_msa_norm    sens_max_norm    sens_msa_phys    sens_max_phys     sens_msa_int     sens_max_int\n################################################################################################################\n         1   9.11698888E-01   1.25370328E+00   1.40121468E-01   3.45865883E-01   3.40015227E+01   8.39269446E+01\n         2   2.53192343E+00   4.42258713E+00   3.89138161E-01   1.22008295E+00   9.44272866E+01   2.96062258E+02\n         3   9.19746784E-01   1.53168651E+00   1.41358371E-01   4.22554614E-01   3.43016665E+01   1.02536039E+02\n         4   5.36305857E+00   8.27788182E+00   8.24262978E-01   2.28366388E+00   2.00013579E+02   5.54148129E+02\n         5   2.81855242E+00   3.67673699E+00   4.33190946E-01   1.01432125E+00   1.05117024E+02   2.46132642E+02\n         6   4.00681946E+00   6.36659805E+00   6.15818922E-01   1.75638773E+00   1.49433069E+02   4.26200624E+02\n         7   2.27278697E+00   2.58519031E+00   3.49310777E-01   7.13190386E-01   8.47628737E+01   1.73060984E+02\n         8   4.59989389E+00   6.58409353E+00   7.06970134E-01   1.81638938E+00   1.71551593E+02   4.40760473E+02\n         9   2.40804685E+00   2.08875161E+00   3.70099234E-01   5.76235166E-01   8.98073484E+01   1.39827775E+02\n        10   7.42509007E-01   1.41975265E+00   1.14118218E-01   3.91674817E-01   2.76916394E+01   9.50428250E+01\n        11   2.48569711E-01   5.63032040E-01   3.82033513E-02   1.55326684E-01   9.27032904E+00   3.76911821E+01\n        12   3.94109241E-01   5.75812932E-01   6.05717153E-02   1.58852618E-01   1.46981799E+01   3.85467763E+01\n        13   1.71929585E-01   2.94230340E-01   2.64243230E-02   8.11709102E-02   6.41205970E+00   1.96967287E+01\n        14   9.23585481E-02   3.30866586E-01   1.41948351E-02   9.12779486E-02   3.44448295E+00   2.21492772E+01\n        15   6.91535987E-01   5.61023153E-01   1.06284036E-01   1.54772482E-01   2.57906167E+01   3.75567008E+01\n        16   4.31870986E-02   8.99199802E-02   6.63754200E-03   2.48067097E-02   1.61064923E+00   6.01953372E+00\n        17   5.69708617E+00   4.26935823E+00   8.75600583E-01   1.17781087E+00   2.12471033E+02   2.85804620E+02\n        18   8.49900871E-01   1.08692545E+00   1.30623564E-01   2.99855983E-01   3.16967851E+01   7.27622980E+01\n        19   7.08623662E+00   6.15405192E+00   1.08910287E+00   1.69775148E+00   2.64278962E+02   4.11972100E+02\n        20   5.88298264E+00   4.83563424E+00   9.04171514E-01   1.33403249E+00   2.19403983E+02   3.23712965E+02\n        21   2.30587503E+00   1.67595287E+00   3.54396170E-01   4.62354153E-01   8.59968826E+01   1.12193695E+02\n        22   1.67675691E+00   1.52471023E+00   2.57705305E-01   4.20630030E-01   6.25341206E+01   1.02069024E+02\n        23   7.38305459E+00   5.25579576E+00   1.13472163E+00   1.44994471E+00   2.75348694E+02   3.51839933E+02\n        24   9.26876276E+00   8.20090766E+00   1.42454122E+00   2.26242861E+00   3.45675586E+02   5.48995230E+02\n        25   8.41294836E+00   5.77127554E+00   1.29300879E+00   1.59215289E+00   3.13758258E+02   3.86347813E+02\n        26   1.28350104E+00   1.67511234E+00   1.97264746E-01   4.62122273E-01   4.78677667E+01   1.12137427E+02\n        27   1.09586030E+01   9.50168287E+00   1.68425734E+00   2.62128048E+00   4.08697645E+02   6.36073322E+02\n        28   4.49103174E+00   4.74404592E+00   6.90238817E-01   1.30876552E+00   1.67491614E+02   3.17581747E+02\n        29   3.82582742E+00   2.82248544E+00   5.88001765E-01   7.78654275E-01   1.42683028E+02   1.88946286E+02\n        30   2.66070642E+00   1.86019462E+00   4.08931167E-01   5.13181917E-01   9.92302076E+01   1.24527432E+02\n"
  },
  {
    "path": "examples/nnp-scaling/Cu2S_PBE/input.data",
    "content": "begin\ncomment source_file_name=OUTCAR_3_1\nlattice 15.108884000 0.000000000 0.000000000\nlattice -0.444607000 11.968873000 0.000000000\nlattice -6.474115000 -0.622266000 12.064082000\natom 8.97740 0.46815 10.16037 S 0.0 0.0 -0.222358 0.152265 0.200886\natom -3.87571 6.56733 7.93575 S 0.0 0.0 0.181153 0.029206 -0.128752\natom -0.78724 10.87846 1.90371 S 0.0 0.0 0.222358 -0.152265 -0.200886\natom 12.06587 4.77928 4.12833 S 0.0 0.0 -0.181153 -0.029206 0.128752\natom 11.94651 0.70378 4.17659 S 0.0 0.0 -0.266316 0.287987 -0.135785\natom -0.36528 6.80794 1.85546 S 0.0 0.0 0.267316 -0.312061 0.046804\natom -3.75635 10.64283 7.88750 S 0.0 0.0 0.266316 -0.287987 0.135785\natom 8.55544 4.53867 10.20863 S 0.0 0.0 -0.267316 0.312061 -0.046804\natom 8.67874 0.67087 6.11408 S 0.0 0.0 -0.069678 0.254753 0.394016\natom -3.57660 6.35264 11.98205 S 0.0 0.0 0.150868 -0.078215 0.157183\natom -0.48858 10.67574 5.95001 S 0.0 0.0 0.069678 -0.254753 -0.394016\natom 11.76676 4.99397 0.08204 S 0.0 0.0 -0.150868 0.078215 -0.157183\natom 11.88653 0.97412 0.07238 S 0.0 0.0 0.171122 0.150756 0.345345\natom -0.30966 6.65489 5.95966 S 0.0 0.0 0.070471 0.029180 0.009887\natom -3.69637 10.37248 11.99170 S 0.0 0.0 -0.171122 -0.150756 -0.345345\natom 8.49982 4.69171 6.10443 S 0.0 0.0 -0.070471 -0.029180 -0.009887\natom 2.77557 0.67522 7.39890 S 0.0 0.0 -0.216263 -0.231346 -0.423473\natom 2.32132 6.48952 10.69722 S 0.0 0.0 0.148547 0.145228 -0.089181\natom 5.41460 10.67139 4.66518 S 0.0 0.0 0.216263 0.231346 0.423473\natom 5.86884 4.85708 1.36686 S 0.0 0.0 -0.148547 -0.145228 0.089181\natom 6.06254 0.80939 1.15453 S 0.0 0.0 -0.003546 0.269309 -0.245175\natom 5.52243 6.60179 4.87751 S 0.0 0.0 -0.035243 -0.385082 0.158705\natom 2.12762 10.53722 10.90955 S 0.0 0.0 0.003546 -0.269309 0.245175\natom 2.66773 4.74481 7.18657 S 0.0 0.0 0.035243 0.385082 -0.158705\natom -0.59740 0.44517 9.49202 S 0.0 0.0 0.284915 -0.318028 -0.082544\natom 5.70336 6.47540 8.60410 S 0.0 0.0 -0.333714 -0.128600 -0.028292\natom 8.78756 10.90144 2.57206 S 0.0 0.0 -0.284915 0.318028 0.082544\natom 2.48680 4.87120 3.45998 S 0.0 0.0 0.333714 0.128600 0.028292\natom 2.40104 0.81728 3.46119 S 0.0 0.0 -0.353432 -0.074392 -0.562056\natom 9.17450 6.84764 2.57086 S 0.0 0.0 0.565866 -0.129202 0.003960\natom 5.78912 10.52932 8.60290 S 0.0 0.0 0.353432 0.074392 0.562056\natom -0.98434 4.49896 9.49323 S 0.0 0.0 -0.565866 0.129202 -0.003960\natom 5.73117 2.52020 8.71027 S 0.0 0.0 -0.264889 0.230077 -0.030282\natom -0.77637 8.46979 9.38586 S 0.0 0.0 0.038205 -0.511643 -0.022736\natom 2.45900 8.82641 3.35381 S 0.0 0.0 0.264889 -0.230077 0.030282\natom 8.96653 2.87682 2.67823 S 0.0 0.0 -0.038205 0.511643 0.022736\natom 5.48094 2.41814 5.02710 S 0.0 0.0 -0.090600 -0.049752 -0.068989\natom 5.96967 8.61004 1.00494 S 0.0 0.0 0.160658 -0.216173 0.094621\natom 2.70923 8.92847 7.03698 S 0.0 0.0 0.090600 0.049752 0.068989\natom 2.22049 2.73657 11.05914 S 0.0 0.0 -0.160658 0.216173 -0.094621\natom -0.21511 2.55681 5.74974 S 0.0 0.0 -0.221792 0.383222 -0.351335\natom 11.65264 8.82325 0.28230 S 0.0 0.0 0.201957 -0.262280 0.164326\natom 8.40527 8.78980 6.31434 S 0.0 0.0 0.221792 -0.383222 0.351335\natom -3.46248 2.52335 11.78178 S 0.0 0.0 -0.201957 0.262280 -0.164326\natom -0.23592 2.69868 1.60694 S 0.0 0.0 -0.041713 -0.107677 0.082040\natom 11.67879 8.53776 4.42511 S 0.0 0.0 0.136374 -0.330995 -0.240607\natom 8.42608 8.64793 10.45715 S 0.0 0.0 0.041713 0.107677 -0.082040\natom -3.48863 2.80885 7.63898 S 0.0 0.0 -0.136374 0.330995 0.240607\natom 11.05568 2.80529 3.53116 Cu 0.0 0.0 0.041428 -0.244736 0.020236\natom 0.37189 8.84287 2.50088 Cu 0.0 0.0 -0.120754 0.245928 0.035521\natom -2.86552 8.54131 8.53292 Cu 0.0 0.0 -0.041428 0.244736 -0.020236\natom 7.81827 2.50374 9.56320 Cu 0.0 0.0 0.120754 -0.245928 -0.035521\natom 4.91105 0.46473 8.16135 Cu 0.0 0.0 0.078047 -0.299302 0.121709\natom 0.19855 6.35770 9.93477 Cu 0.0 0.0 -0.064545 0.247414 -0.040170\natom 3.27911 10.88187 3.90273 Cu 0.0 0.0 -0.078047 0.299302 -0.121709\natom 7.99161 4.98891 2.12931 Cu 0.0 0.0 0.064545 -0.247414 0.040170\natom 8.09301 0.99199 2.02315 Cu 0.0 0.0 0.139777 -0.407003 -0.073877\natom 3.47506 6.87401 4.00889 Cu 0.0 0.0 -0.156603 0.275670 -0.065123\natom 0.09716 10.35461 10.04094 Cu 0.0 0.0 -0.139777 0.407003 0.073877\natom 4.71510 4.47260 8.05519 Cu 0.0 0.0 0.156603 -0.275670 0.065123\natom 4.90154 2.82704 0.88188 Cu 0.0 0.0 0.061858 -0.361159 0.009819\natom 6.53457 8.59132 5.15016 Cu 0.0 0.0 -0.168443 0.163453 -0.166661\natom 3.28862 8.51956 11.18220 Cu 0.0 0.0 -0.061858 0.361159 -0.009819\natom 1.65559 2.75529 6.91393 Cu 0.0 0.0 0.168443 -0.163453 0.166661\natom -4.22854 0.42805 11.40176 Cu 0.0 0.0 0.212360 -0.298914 0.104173\natom 9.32845 6.65530 6.69436 Cu 0.0 0.0 -0.196286 0.425400 -0.260995\natom 12.41870 10.91855 0.66232 Cu 0.0 0.0 -0.212360 0.298914 -0.104173\natom -1.13829 4.69131 5.36972 Cu 0.0 0.0 0.196286 -0.425400 0.260995\natom -1.29310 0.66156 5.34318 Cu 0.0 0.0 0.222205 -0.354828 0.119092\natom 12.87300 6.88607 0.68886 Cu 0.0 0.0 -0.260305 0.283403 -0.098703\natom 9.48326 10.68505 6.72090 Cu 0.0 0.0 -0.222205 0.354828 -0.119092\natom -4.68284 4.46054 11.37522 Cu 0.0 0.0 0.260305 -0.283403 0.098703\natom 7.64017 0.85829 11.97119 Cu 0.0 0.0 -0.116702 -0.000516 -0.443922\natom -2.57440 7.14427 6.12493 Cu 0.0 0.0 -0.076548 0.116351 0.068077\natom 0.54999 10.48832 0.09289 Cu 0.0 0.0 0.116702 0.000516 0.443922\natom 10.76456 4.20233 5.93915 Cu 0.0 0.0 0.076548 -0.116351 -0.068077\natom 10.85957 1.37271 6.15148 Cu 0.0 0.0 -0.054746 -0.104453 -0.353573\natom -5.80972 7.05834 11.94465 Cu 0.0 0.0 -0.135939 0.092078 0.066335\natom -2.66941 9.97390 5.91261 Cu 0.0 0.0 0.054746 0.104453 0.353573\natom 13.99988 4.28827 0.11943 Cu 0.0 0.0 0.135939 -0.092078 -0.066335\natom 8.73387 2.74132 4.95713 Cu 0.0 0.0 0.128971 -0.221059 0.043926\natom 2.69299 8.92600 1.07491 Cu 0.0 0.0 -0.102359 0.348945 -0.017986\natom -0.54371 8.60529 7.10695 Cu 0.0 0.0 -0.128971 0.221059 -0.043926\natom 5.49717 2.42061 10.98917 Cu 0.0 0.0 0.102359 -0.348945 0.017986\natom 0.57405 1.18611 11.27750 Cu 0.0 0.0 -0.056031 0.160247 0.313636\natom 4.47002 7.40053 6.81862 Cu 0.0 0.0 -0.028281 0.217544 -0.150245\natom 7.61611 10.16050 0.78658 Cu 0.0 0.0 0.056031 -0.160247 -0.313636\natom 3.72014 3.94607 5.24546 Cu 0.0 0.0 0.028281 -0.217544 0.150245\natom 3.53184 1.19792 5.29372 Cu 0.0 0.0 0.082555 0.203931 0.472192\natom 8.00840 7.41733 0.73832 Cu 0.0 0.0 -0.152359 0.177430 -0.079993\natom 4.65833 10.14868 6.77036 Cu 0.0 0.0 -0.082555 -0.203931 -0.472192\natom 0.18176 3.92928 11.32576 Cu 0.0 0.0 0.152359 -0.177430 0.079993\natom -1.71725 2.29170 10.26291 Cu 0.0 0.0 0.006280 -0.003572 0.080109\natom 6.68307 8.40146 7.83321 Cu 0.0 0.0 -0.002610 0.104121 -0.088140\natom 9.90741 9.05491 1.80117 Cu 0.0 0.0 -0.006280 0.003572 -0.080109\natom 1.50709 2.94514 4.23087 Cu 0.0 0.0 0.002610 -0.104121 0.088140\natom 7.96515 0.00348 8.23977 Cu 0.0 0.0 -0.037219 0.066784 -0.472910\natom 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9.45100 Cu 0.0 0.0 0.043895 -0.263306 0.011700\natom 0.51324 0.13178 7.51592 Cu 0.0 0.0 0.026819 0.233220 0.498362\natom 4.62358 5.95816 10.58020 Cu 0.0 0.0 0.137093 -0.068788 -0.061812\natom 7.67693 11.21483 4.54816 Cu 0.0 0.0 -0.026819 -0.233220 -0.498362\natom 3.56658 5.38845 1.48388 Cu 0.0 0.0 -0.137093 0.068788 0.061812\natom 3.72216 0.43254 1.61538 Cu 0.0 0.0 -0.040870 0.279572 0.401644\natom 7.88903 6.27248 4.41666 Cu 0.0 0.0 -0.142573 -0.076326 0.005876\natom 4.46800 10.91407 10.44870 Cu 0.0 0.0 0.040870 -0.279572 -0.401644\natom 0.30113 5.07412 7.64742 Cu 0.0 0.0 0.142573 0.076326 -0.005876\natom 2.94560 2.02254 9.09994 Cu 0.0 0.0 0.040919 0.245148 0.290469\natom 2.04468 8.01233 8.99619 Cu 0.0 0.0 -0.015727 -0.057877 -0.039936\natom 5.24457 9.32406 2.96414 Cu 0.0 0.0 -0.040919 -0.245148 -0.290469\natom 6.14548 3.33427 3.06790 Cu 0.0 0.0 0.015727 0.057877 0.039936\natom 13.65645 0.88975 2.61308 Cu 0.0 0.0 -0.001253 -0.021270 0.054902\natom -2.08304 6.83262 3.41896 Cu 0.0 0.0 0.000362 0.194907 -0.105534\natom -5.46628 10.45685 9.45100 Cu 0.0 0.0 0.001253 0.021270 -0.054902\natom 10.27320 4.51398 8.64512 Cu 0.0 0.0 -0.000362 -0.194907 0.105534\natom 3.19194 0.64211 11.49828 Cu 0.0 0.0 -0.132780 0.397604 0.050572\natom 1.89170 6.87931 6.59785 Cu 0.0 0.0 0.147372 -0.288628 -0.015811\natom 4.99822 10.70450 0.56581 Cu 0.0 0.0 0.132780 -0.397604 -0.050572\natom 6.29846 4.46730 5.46624 Cu 0.0 0.0 -0.147372 0.288628 0.015811\natom 6.88199 1.97461 6.82706 Cu 0.0 0.0 0.177085 -0.092970 0.112419\natom -1.87944 7.72993 11.26906 Cu 0.0 0.0 0.066394 0.172016 -0.179726\natom 1.30817 9.37200 5.23702 Cu 0.0 0.0 -0.177085 0.092970 -0.112419\natom 10.06961 3.61668 0.79502 Cu 0.0 0.0 -0.066394 -0.172016 0.179726\natom 2.06701 2.38937 1.68656 Cu 0.0 0.0 0.157526 -0.073328 0.019306\natom 9.39853 8.23666 4.34548 Cu 0.0 0.0 -0.040495 0.188487 0.189635\natom 6.12315 8.95724 10.37752 Cu 0.0 0.0 -0.157526 0.073328 -0.019306\natom -1.20837 3.10995 7.71860 Cu 0.0 0.0 0.040495 -0.188487 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0.060146\natom 8.89445 4.59697 9.85222 S 0.0 0.0 -0.162224 0.317867 0.051220\natom 8.89285 0.74884 5.90062 S 0.0 0.0 0.111339 0.404760 0.293108\natom -3.33199 6.39950 11.56373 S 0.0 0.0 0.035717 -0.004228 0.186135\natom -0.22873 10.54084 5.74228 S 0.0 0.0 -0.111339 -0.404760 -0.293108\natom 11.99611 4.89019 0.07917 S 0.0 0.0 -0.035717 0.004228 -0.186135\natom 12.05186 0.95473 0.06986 S 0.0 0.0 0.300443 0.349162 0.241329\natom -0.11282 6.60470 5.75159 S 0.0 0.0 -0.047374 0.122470 0.084756\natom -3.38774 10.33496 11.57304 S 0.0 0.0 -0.300443 -0.349162 -0.241329\natom 8.77694 4.68498 5.89131 S 0.0 0.0 0.047374 -0.122470 -0.084756\natom 2.93601 0.77245 7.14059 S 0.0 0.0 -0.303865 -0.560216 -0.389525\natom 2.62183 6.51416 10.32376 S 0.0 0.0 0.223996 -0.097440 -0.142371\natom 5.72811 10.51724 4.50231 S 0.0 0.0 0.303865 0.560216 0.389525\natom 6.04229 4.77553 1.31914 S 0.0 0.0 -0.223996 0.097440 0.142371\natom 6.16928 0.80976 1.11423 S 0.0 0.0 0.157239 0.131858 -0.409031\natom 5.77440 6.53642 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0.391327 -0.026829\natom 5.66668 2.44300 4.85160 S 0.0 0.0 -0.364860 -0.248944 0.352942\natom 6.19979 8.44411 0.96985 S 0.0 0.0 0.426778 -0.428439 -0.384782\natom 2.99744 8.84669 6.79130 S 0.0 0.0 0.364860 0.248944 -0.352942\natom 2.46433 2.84558 10.67304 S 0.0 0.0 -0.426778 0.428439 0.384782\natom -0.08699 2.58963 5.54900 S 0.0 0.0 -0.025437 0.123138 -0.528510\natom 11.94594 8.64196 0.27244 S 0.0 0.0 0.063386 -0.351520 0.329911\natom 8.75110 8.70005 6.09389 S 0.0 0.0 0.025437 -0.123138 0.528510\natom -3.28183 2.64773 11.37045 S 0.0 0.0 -0.063386 0.351520 -0.329911\natom -0.17004 2.66613 1.55083 S 0.0 0.0 0.328740 -0.307766 0.005987\natom 12.03207 8.42486 4.27061 S 0.0 0.0 -0.275791 -0.548926 -0.163727\natom 8.83416 8.62356 10.09206 S 0.0 0.0 -0.328740 0.307766 -0.005987\natom -3.36795 2.86483 7.37228 S 0.0 0.0 0.275791 0.548926 0.163727\natom 11.29409 2.79948 3.40788 Cu 0.0 0.0 -0.053698 -0.113980 -0.109447\natom 0.55915 8.69458 2.41357 Cu 0.0 0.0 0.016962 0.257953 0.153339\natom 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11.00370 Cu 0.0 0.0 0.087619 -0.317677 0.025590\natom 9.65700 6.61616 6.46064 Cu 0.0 0.0 -0.075743 0.208545 -0.210380\natom 12.76154 10.69892 0.63920 Cu 0.0 0.0 -0.087619 0.317677 -0.025590\natom -0.99288 4.67352 5.18225 Cu 0.0 0.0 0.075743 -0.208545 0.210380\natom -1.21557 0.72812 5.15664 Cu 0.0 0.0 0.070799 -0.281791 0.102672\natom 13.15634 6.75163 0.66481 Cu 0.0 0.0 -0.094671 0.183603 -0.090640\natom 9.87968 10.56157 6.48626 Cu 0.0 0.0 -0.070799 0.281791 -0.102672\natom -4.49222 4.53805 10.97809 Cu 0.0 0.0 0.094671 -0.183603 0.090640\natom 7.93526 1.02053 11.55325 Cu 0.0 0.0 -0.387933 -0.130153 -0.345487\natom -2.39530 7.08628 5.91110 Cu 0.0 0.0 0.172661 0.003167 0.040354\natom 0.72886 10.26916 0.08965 Cu 0.0 0.0 0.387933 0.130153 0.345487\natom 11.05942 4.20341 5.73180 Cu 0.0 0.0 -0.172661 -0.003167 -0.040354\natom 11.11290 1.43649 5.93671 Cu 0.0 0.0 -0.260736 -0.208164 -0.279923\natom -5.58209 7.08980 11.52763 Cu 0.0 0.0 0.036367 -0.000678 0.045761\natom -2.44878 9.85320 5.70618 Cu 0.0 0.0 0.260736 0.208164 0.279923\natom 14.24621 4.19989 0.11526 Cu 0.0 0.0 -0.036367 0.000678 -0.045761\natom 8.96439 2.75833 4.78407 Cu 0.0 0.0 0.140680 -0.214622 0.235424\natom 2.88844 8.75448 1.03738 Cu 0.0 0.0 -0.128401 0.364323 -0.217604\natom -0.30027 8.53136 6.85883 Cu 0.0 0.0 -0.140680 0.214622 -0.235424\natom 5.77568 2.53521 10.60551 Cu 0.0 0.0 0.128401 -0.364323 0.217604\natom 0.77551 1.33101 10.88378 Cu 0.0 0.0 0.123408 0.241213 0.283180\natom 4.75197 7.34760 6.58057 Cu 0.0 0.0 -0.172148 0.277921 -0.093776\natom 7.88860 9.95868 0.75912 Cu 0.0 0.0 -0.123408 -0.241213 -0.283180\natom 3.91215 3.94209 5.06233 Cu 0.0 0.0 0.172148 -0.277921 0.093776\natom 3.67755 1.25246 5.10890 Cu 0.0 0.0 0.369887 0.303330 0.311208\natom 8.24044 7.27247 0.71255 Cu 0.0 0.0 -0.395447 0.245839 0.048050\natom 4.98657 10.03723 6.53399 Cu 0.0 0.0 -0.369887 -0.303330 -0.311208\natom 0.42368 4.01722 10.93035 Cu 0.0 0.0 0.395447 -0.245839 -0.048050\natom -1.54216 2.39807 9.90461 Cu 0.0 0.0 0.023324 0.077918 0.079022\natom 7.02467 8.34276 7.55973 Cu 0.0 0.0 -0.020919 0.089487 -0.102592\natom 10.20627 8.89161 1.73828 Cu 0.0 0.0 -0.023324 -0.077918 -0.079022\natom 1.63945 2.94693 4.08316 Cu 0.0 0.0 0.020919 -0.089487 0.102592\natom 8.19248 0.12750 7.95210 Cu 0.0 0.0 -0.220921 -0.136250 -0.309043\natom -2.60782 5.92880 9.51225 Cu 0.0 0.0 0.184056 -0.354253 -0.127323\natom 0.47163 11.16219 3.69080 Cu 0.0 0.0 0.220921 0.136250 0.309043\natom 11.27193 5.36088 2.13065 Cu 0.0 0.0 -0.184056 0.354253 0.127323\natom 10.89623 0.65972 1.94553 Cu 0.0 0.0 -0.068814 -0.007404 -0.007446\natom 1.05267 6.44743 3.87592 Cu 0.0 0.0 0.126030 0.130493 -0.018135\natom -2.23212 10.62997 9.69737 Cu 0.0 0.0 0.068814 0.007404 0.007446\natom 7.61145 4.84226 7.76698 Cu 0.0 0.0 -0.126030 -0.130493 0.018135\natom -4.57795 2.06606 8.99064 Cu 0.0 0.0 -0.059501 0.057625 0.118793\natom 10.07640 7.94362 8.47370 Cu 0.0 0.0 0.207102 -0.010090 -0.059408\natom 13.24206 9.22363 2.65225 Cu 0.0 0.0 0.059501 -0.057625 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Cu 0.0 0.0 -0.027634 -0.099603 0.037156\natom 7.98415 5.85602 8.08812 Cu 0.0 0.0 0.112184 0.072103 -0.068043\natom -4.12068 3.15755 9.36238 Cu 0.0 0.0 -0.105898 -0.053129 0.029849\natom 10.61847 9.11126 8.82407 Cu 0.0 0.0 -0.091125 0.096486 -0.023522\natom 13.65011 9.74516 2.76192 Cu 0.0 0.0 0.105898 0.053129 -0.029849\natom -1.08903 3.79145 3.30023 Cu 0.0 0.0 0.091125 -0.096486 0.023522\natom 5.89101 1.21216 3.43603 Cu 0.0 0.0 0.024483 0.318485 0.012590\natom 6.45775 7.14539 2.62612 Cu 0.0 0.0 0.032008 -0.186937 0.011693\natom 3.63843 11.69056 8.68827 Cu 0.0 0.0 -0.024483 -0.318485 -0.012590\natom 3.07169 5.75733 9.49818 Cu 0.0 0.0 -0.032008 0.186937 -0.011693\natom 0.83619 1.08980 7.55344 Cu 0.0 0.0 -0.188992 -0.143808 -0.075218\natom 5.50324 7.31629 10.63301 Cu 0.0 0.0 -0.057314 0.208219 -0.414012\natom 8.69324 11.81291 4.57086 Cu 0.0 0.0 0.188992 0.143808 0.075218\natom 4.02619 5.58643 1.49129 Cu 0.0 0.0 0.057314 -0.208219 0.414012\natom 3.79988 0.63911 1.62344 Cu 0.0 0.0 0.169202 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4.28772 0.12077 Cu 0.0 0.0 -0.030779 -0.030291 -0.209931\natom 9.12821 3.09946 5.01239 Cu 0.0 0.0 0.154435 0.188844 0.026886\natom 3.31655 8.98554 1.08689 Cu 0.0 0.0 -0.174644 -0.052501 -0.036266\natom 0.15030 9.10858 7.18617 Cu 0.0 0.0 -0.154435 -0.188844 -0.026886\natom 5.96195 3.22251 11.11166 Cu 0.0 0.0 0.174644 0.052501 0.036266\natom 0.90383 2.01187 11.40321 Cu 0.0 0.0 -0.024636 0.192456 0.120642\natom 5.14566 7.88527 6.89462 Cu 0.0 0.0 0.106161 0.146840 -0.155322\natom 8.37467 10.19617 0.79535 Cu 0.0 0.0 0.024636 -0.192456 -0.120642\natom 4.13284 4.32277 5.30393 Cu 0.0 0.0 -0.106161 -0.146840 0.155322\natom 3.76908 1.58415 5.35273 Cu 0.0 0.0 0.055005 0.170761 0.030521\natom 8.59716 7.45542 0.74655 Cu 0.0 0.0 0.006528 0.176171 -0.177685\natom 5.50942 10.62390 6.84583 Cu 0.0 0.0 -0.055005 -0.170761 -0.030521\natom 0.68134 4.75262 11.45200 Cu 0.0 0.0 -0.006528 -0.176171 0.177685\natom -1.36906 3.04054 10.37731 Cu 0.0 0.0 0.044785 0.089720 0.115769\natom 7.47275 8.95854 7.92052 Cu 0.0 0.0 -0.050998 -0.018604 -0.103138\natom 10.64757 9.16751 1.82124 Cu 0.0 0.0 -0.044785 -0.089720 -0.115769\natom 1.80575 3.24950 4.27803 Cu 0.0 0.0 0.050998 0.018604 0.103138\natom 8.24816 0.60869 8.33161 Cu 0.0 0.0 -0.029129 -0.125324 -0.040654\natom -2.26758 6.61564 9.96622 Cu 0.0 0.0 -0.022322 0.049622 0.240113\natom 1.03034 11.59935 3.86694 Cu 0.0 0.0 0.029129 0.125324 0.040654\natom 11.54608 5.59240 2.23234 Cu 0.0 0.0 0.022322 -0.049622 -0.240113\natom 10.94307 0.78955 2.03838 Cu 0.0 0.0 0.030375 0.016290 -0.116834\natom 1.38591 6.80494 4.06090 Cu 0.0 0.0 -0.088286 -0.015486 0.141967\natom -1.66457 11.41849 10.16017 Cu 0.0 0.0 -0.030375 -0.016290 0.116834\natom 7.89259 5.40310 8.13765 Cu 0.0 0.0 0.088286 0.015486 -0.141967\natom -4.42722 2.64710 9.41972 Cu 0.0 0.0 -0.037350 -0.045004 -0.046408\natom 10.51169 8.60674 8.87811 Cu 0.0 0.0 -0.055404 0.052381 0.050958\natom 13.70572 9.56094 2.77883 Cu 0.0 0.0 0.037350 0.045004 0.046408\natom -1.23319 3.60130 3.32045 Cu 0.0 0.0 0.055404 -0.052381 -0.050958\natom 5.92107 1.02461 3.45707 Cu 0.0 0.0 0.026593 0.128858 -0.020203\natom 6.41844 6.97832 2.64221 Cu 0.0 0.0 0.005486 -0.033514 0.015983\natom 3.35743 11.18343 8.74148 Cu 0.0 0.0 -0.026593 -0.128858 0.020203\natom 2.86006 5.22972 9.55635 Cu 0.0 0.0 -0.005486 0.033514 -0.015983\natom 0.69296 0.68354 7.59970 Cu 0.0 0.0 -0.082556 -0.034793 0.110183\natom 5.29230 6.72232 10.69813 Cu 0.0 0.0 0.008241 0.085868 -0.301796\natom 8.58554 11.52450 4.59885 Cu 0.0 0.0 0.082556 0.034793 -0.110183\natom 3.98621 5.48572 1.50042 Cu 0.0 0.0 -0.008241 -0.085868 0.301796\natom 3.83271 0.55025 1.63339 Cu 0.0 0.0 0.109853 -0.036001 0.058870\natom 8.48439 6.58325 4.46589 Cu 0.0 0.0 0.001338 0.135086 -0.235976\natom 5.44580 11.65779 10.56517 Cu 0.0 0.0 -0.109853 0.036001 -0.058870\natom 0.79412 5.62480 7.73266 Cu 0.0 0.0 -0.001338 -0.135086 0.235976\natom 3.31102 2.68654 9.20137 Cu 0.0 0.0 -0.032403 -0.054702 0.016874\natom 2.77573 8.65568 9.09646 Cu 0.0 0.0 0.008576 0.089472 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2.28186 2.50805 1.70536 Cu 0.0 0.0 0.005031 0.093086 -0.101755\natom 10.13611 8.53792 4.39392 Cu 0.0 0.0 -0.085084 -0.045217 -0.002422\natom 6.99664 9.69999 10.49320 Cu 0.0 0.0 -0.005031 -0.093086 0.101755\natom -0.85761 3.67012 7.80463 Cu 0.0 0.0 0.085084 0.045217 0.002422\natom -2.26875 1.33378 8.28404 Cu 0.0 0.0 -0.057011 -0.106376 -0.016110\natom 8.28677 7.34280 10.01379 Cu 0.0 0.0 0.030663 0.207340 -0.010842\natom 11.54725 10.87426 3.91452 Cu 0.0 0.0 0.057011 0.106376 0.016110\natom 0.99173 4.86524 2.18476 Cu 0.0 0.0 -0.030663 -0.207340 0.010842\nenergy -573.096418\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_31\nlattice 15.115754000 0.000000000 0.000000000\nlattice 0.156739000 11.792572000 0.000000000\nlattice -5.862450000 0.278982000 12.163257000\natom 9.54897 1.21256 10.24390 S 0.0 0.0 -0.193590 -0.085150 0.067134\natom -3.12254 7.05740 8.00099 S 0.0 0.0 0.196348 -0.011337 -0.028467\natom -0.13893 10.85899 1.91936 S 0.0 0.0 0.193590 0.085150 -0.067134\natom 12.53258 5.01415 4.16227 S 0.0 0.0 -0.196348 0.011337 0.028467\natom 12.21092 1.00225 4.21092 S 0.0 0.0 -0.119712 -0.154317 0.103679\natom 0.07606 6.84486 1.87071 S 0.0 0.0 0.112414 0.092666 -0.037703\natom -2.80087 11.06930 7.95234 S 0.0 0.0 0.119712 0.154317 -0.103679\natom 9.33399 5.22669 10.29255 S 0.0 0.0 -0.112414 -0.092666 0.037703\natom 9.04373 1.11310 6.16434 S 0.0 0.0 -0.062076 -0.206659 -0.155098\natom -2.61745 7.14508 12.08055 S 0.0 0.0 0.008312 -0.051466 -0.048526\natom 0.36631 10.95846 5.99892 S 0.0 0.0 0.062076 0.206659 0.155098\natom 12.02750 4.92648 0.08271 S 0.0 0.0 -0.008312 0.051466 0.048526\natom 11.94477 0.96513 0.07298 S 0.0 0.0 -0.037518 -0.018631 -0.077815\natom 0.34374 6.99756 6.00865 S 0.0 0.0 -0.079297 0.054486 -0.055356\natom -2.53473 11.10643 12.09028 S 0.0 0.0 0.037518 0.018631 0.077815\natom 9.06631 5.07400 6.15461 S 0.0 0.0 0.079297 -0.054486 0.055356\natom 3.20688 1.21238 7.45973 S 0.0 0.0 -0.055653 0.037319 0.101914\natom 3.22124 7.18494 10.78516 S 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10.54311 S 0.0 0.0 0.000850 0.269583 0.234685\natom -2.94007 3.33234 7.70177 S 0.0 0.0 0.039901 0.244439 -0.348167\natom 11.39075 3.02508 3.56019 Cu 0.0 0.0 -0.056205 0.085511 -0.092679\natom 0.95039 8.89755 2.52144 Cu 0.0 0.0 0.078015 -0.113909 0.066899\natom -1.98071 9.04647 8.60307 Cu 0.0 0.0 0.056205 -0.085511 0.092679\natom 8.45965 3.17401 9.64181 Cu 0.0 0.0 -0.078015 0.113909 -0.066899\natom 5.37358 1.06138 8.22844 Cu 0.0 0.0 -0.079034 0.049750 0.036472\natom 1.05006 6.99868 10.01644 Cu 0.0 0.0 0.054093 -0.169191 -0.069966\natom 4.03646 11.01017 3.93481 Cu 0.0 0.0 0.079034 -0.049750 -0.036472\natom 8.35998 5.07288 2.14681 Cu 0.0 0.0 -0.054093 0.169191 0.069966\natom 8.25486 1.12698 2.03978 Cu 0.0 0.0 -0.043480 0.031501 -0.041855\natom 4.03676 7.06919 4.04185 Cu 0.0 0.0 0.066246 -0.249199 0.112005\natom 1.15519 10.94457 10.12348 Cu 0.0 0.0 0.043480 -0.031501 0.041855\natom 5.37329 5.00236 8.12141 Cu 0.0 0.0 -0.066246 0.249199 -0.112005\natom 5.09307 2.85061 0.88913 Cu 0.0 0.0 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7.99338 5.34654 8.11411 Cu 0.0 0.0 0.071124 -0.011955 -0.049436\natom -4.10041 2.62701 9.39247 Cu 0.0 0.0 -0.041742 -0.040321 0.087343\natom 10.56496 8.51091 8.85242 Cu 0.0 0.0 -0.025843 0.022806 -0.071567\natom 13.51045 9.44454 2.77079 Cu 0.0 0.0 0.041742 0.040321 -0.087343\natom -1.15492 3.56064 3.31084 Cu 0.0 0.0 0.025843 -0.022806 0.071567\natom 5.94822 1.01657 3.44707 Cu 0.0 0.0 -0.005284 0.104844 0.007155\natom 6.33960 6.89422 2.63456 Cu 0.0 0.0 0.022234 -0.073020 0.000642\natom 3.46182 11.05498 8.71619 Cu 0.0 0.0 0.005284 -0.104844 -0.007155\natom 3.07044 5.17733 9.52870 Cu 0.0 0.0 -0.022234 0.073020 -0.000642\natom 0.92248 0.68560 7.57771 Cu 0.0 0.0 -0.091235 -0.053718 0.022875\natom 5.49158 6.65275 10.66718 Cu 0.0 0.0 0.010167 0.053941 -0.174933\natom 8.48757 11.38595 4.58555 Cu 0.0 0.0 0.091235 0.053718 -0.022875\natom 3.91847 5.41880 1.49608 Cu 0.0 0.0 -0.010167 -0.053941 0.174933\natom 3.83208 0.54562 1.62866 Cu 0.0 0.0 0.130089 -0.063840 -0.008263\natom 8.44433 6.50668 4.45297 Cu 0.0 0.0 -0.072261 0.074063 -0.149319\natom 5.57796 11.52594 10.53460 Cu 0.0 0.0 -0.130089 0.063840 0.008263\natom 0.96571 5.56487 7.71029 Cu 0.0 0.0 0.072261 -0.074063 0.149319\natom 3.53578 2.66565 9.17474 Cu 0.0 0.0 -0.003400 -0.065882 -0.089289\natom 2.92994 8.55954 9.07014 Cu 0.0 0.0 -0.029860 0.049608 0.004837\natom 5.87427 9.40590 2.98851 Cu 0.0 0.0 0.003400 0.065882 0.089289\natom 6.48011 3.51202 3.09312 Cu 0.0 0.0 0.029860 -0.049608 -0.004837\natom 13.84727 1.06987 2.63456 Cu 0.0 0.0 0.058455 0.090981 0.078033\natom -1.55754 6.98479 3.44707 Cu 0.0 0.0 -0.052253 0.016980 -0.050052\natom -4.43723 11.00168 9.52870 Cu 0.0 0.0 -0.058455 -0.090981 -0.078033\natom 10.96758 5.08676 8.71619 Cu 0.0 0.0 0.052253 -0.016980 0.050052\natom 3.84125 1.48289 11.59280 Cu 0.0 0.0 -0.034237 -0.058260 0.055365\natom 2.59155 7.26586 6.65209 Cu 0.0 0.0 0.051802 0.246546 -0.075381\natom 5.56879 10.58866 0.57046 Cu 0.0 0.0 0.034237 0.058260 -0.055365\natom 6.81850 4.80570 5.51117 Cu 0.0 0.0 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0.000000000\nlattice -0.551221000 11.982730000 0.000000000\nlattice -5.820617000 -0.307146000 12.017409000\natom 9.62160 0.73469 10.12106 S 0.0 0.0 -0.181039 -0.102028 0.036989\natom -3.50342 6.78269 7.90505 S 0.0 0.0 -0.079095 0.058626 0.086129\natom -0.77733 10.94089 1.89635 S 0.0 0.0 0.181039 0.102028 -0.036989\natom 12.34769 4.89289 4.11236 S 0.0 0.0 0.079095 -0.058626 -0.086129\natom 12.26549 0.81394 4.16043 S 0.0 0.0 -0.195452 0.148193 0.029450\natom -0.31997 6.86440 1.84828 S 0.0 0.0 0.207795 -0.329824 -0.045056\natom -3.42122 10.86164 7.85698 S 0.0 0.0 0.195452 -0.148193 -0.029450\natom 9.16423 4.81118 10.16913 S 0.0 0.0 -0.207795 0.329824 0.045056\natom 9.08628 0.83172 6.09042 S 0.0 0.0 -0.046197 0.073962 0.083264\natom -2.96755 6.67368 11.93569 S 0.0 0.0 -0.060972 -0.177434 0.335726\natom -0.24201 10.84387 5.92699 S 0.0 0.0 0.046197 -0.073962 -0.083264\natom 11.81182 5.00190 0.08172 S 0.0 0.0 0.060972 0.177434 -0.335726\natom 11.96663 0.97715 0.07210 S 0.0 0.0 0.187319 0.018512 -0.029937\natom -0.02652 6.81862 5.93660 S 0.0 0.0 -0.024109 0.010751 0.256414\natom -3.12237 10.69844 11.94530 S 0.0 0.0 -0.187319 -0.018512 0.029937\natom 8.87078 4.85696 6.08081 S 0.0 0.0 0.024109 -0.010751 -0.256414\natom 3.21509 0.86970 7.37028 S 0.0 0.0 -0.134362 -0.162023 0.000751\natom 2.89713 6.77709 10.65584 S 0.0 0.0 0.053087 0.064537 -0.267530\natom 5.62917 10.80588 4.64713 S 0.0 0.0 0.134362 0.162023 -0.000751\natom 5.94714 4.89849 1.36157 S 0.0 0.0 -0.053087 -0.064537 0.267530\natom 6.16498 0.84055 1.15007 S 0.0 0.0 0.091223 0.141895 -0.191458\natom 5.78516 6.73713 4.85864 S 0.0 0.0 -0.132024 -0.371038 0.132670\natom 2.67928 10.83503 10.86734 S 0.0 0.0 -0.091223 -0.141895 0.191458\natom 3.05910 4.93845 7.15877 S 0.0 0.0 0.132024 0.371038 -0.132670\natom -0.05940 0.69419 9.45530 S 0.0 0.0 0.162578 -0.094044 0.101626\natom 6.18287 6.70816 8.57082 S 0.0 0.0 -0.103266 -0.211875 -0.108676\natom 8.90367 10.98140 2.56211 S 0.0 0.0 -0.162578 0.094044 -0.101626\natom 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0.096736 -0.305518 0.183310\natom 8.75221 8.96529 6.28991 S 0.0 0.0 0.137933 -0.215205 0.218966\natom -2.83104 2.83472 11.73620 S 0.0 0.0 -0.096736 0.305518 -0.183310\natom -0.16847 2.74387 1.60072 S 0.0 0.0 0.123488 -0.153175 -0.326374\natom 11.94245 8.66349 4.40799 S 0.0 0.0 -0.072057 -0.362742 0.285883\natom 9.01274 8.93171 10.41669 S 0.0 0.0 -0.123488 0.153175 0.326374\natom -3.09818 3.01209 7.60942 S 0.0 0.0 0.072057 0.362742 -0.285883\natom 11.31304 2.90099 3.51750 Cu 0.0 0.0 -0.080609 -0.225391 -0.046227\natom 0.44197 8.91858 2.49121 Cu 0.0 0.0 -0.011654 0.155044 0.083824\natom -2.46878 8.77460 8.49991 Cu 0.0 0.0 0.080609 0.225391 0.046227\natom 8.40229 2.75700 9.52620 Cu 0.0 0.0 0.011654 -0.155044 -0.083824\natom 5.41142 0.67894 8.12978 Cu 0.0 0.0 -0.056531 -0.249103 0.101868\natom 0.71657 6.62515 9.89634 Cu 0.0 0.0 0.059063 0.174405 -0.025324\natom 3.43285 10.99665 3.88763 Cu 0.0 0.0 0.056531 0.249103 -0.101868\natom 8.12770 5.05043 2.12107 Cu 0.0 0.0 -0.059063 -0.174405 0.025324\natom 8.25826 1.04611 2.01532 Cu 0.0 0.0 0.017208 -0.323419 -0.116946\natom 3.67094 6.98692 3.99338 Cu 0.0 0.0 -0.039155 0.200981 0.016875\natom 0.58601 10.62947 10.00209 Cu 0.0 0.0 -0.017208 0.323419 0.116946\natom 5.17332 4.68867 8.02402 Cu 0.0 0.0 0.039155 -0.200981 -0.016875\natom 4.96262 2.85340 0.87847 Cu 0.0 0.0 -0.065993 -0.229987 -0.028653\natom 6.80298 8.73610 5.13023 Cu 0.0 0.0 0.050786 0.199954 -0.045838\natom 3.88164 8.82218 11.13894 Cu 0.0 0.0 0.065993 0.229987 0.028653\natom 2.04129 2.93948 6.88718 Cu 0.0 0.0 -0.050786 -0.199954 0.045838\natom -3.60629 0.72705 11.35765 Cu 0.0 0.0 0.095618 -0.258958 -0.006130\natom 9.72226 6.83826 6.66846 Cu 0.0 0.0 -0.095124 0.329849 -0.083485\natom 12.45055 10.94853 0.65976 Cu 0.0 0.0 -0.095618 0.258958 0.006130\natom -0.87799 4.83732 5.34895 Cu 0.0 0.0 0.095124 -0.329849 0.083485\natom -1.00060 0.80221 5.32251 Cu 0.0 0.0 -0.016979 -0.252378 0.013661\natom 12.94446 6.91207 0.68619 Cu 0.0 0.0 -0.041621 0.246863 -0.008163\natom 9.84486 10.87337 6.69490 Cu 0.0 0.0 0.016979 0.252378 -0.013661\natom -4.10020 4.76351 11.33121 Cu 0.0 0.0 0.041621 -0.246863 0.008163\natom 8.37568 1.17269 11.92487 Cu 0.0 0.0 -0.214950 0.131096 -0.097319\natom -2.30205 7.31290 6.10124 Cu 0.0 0.0 0.150545 0.203124 -0.172713\natom 0.46858 10.50289 0.09253 Cu 0.0 0.0 0.214950 -0.131096 0.097319\natom 11.14631 4.36269 5.91617 Cu 0.0 0.0 -0.150545 -0.203124 0.172713\natom 11.27867 1.53535 6.12768 Cu 0.0 0.0 -0.019049 0.094721 -0.106397\natom -5.22477 7.37922 11.89844 Cu 0.0 0.0 -0.075895 0.195414 -0.048322\natom -2.43441 10.14024 5.88973 Cu 0.0 0.0 0.019049 -0.094721 0.106397\natom 14.06904 4.29636 0.11897 Cu 0.0 0.0 0.075895 -0.195414 0.048322\natom 9.05734 2.87427 4.93795 Cu 0.0 0.0 0.175278 -0.076746 0.175916\natom 2.69679 8.96447 1.07075 Cu 0.0 0.0 -0.139898 0.257242 -0.172429\natom -0.21308 8.80131 7.07946 Cu 0.0 0.0 -0.175278 0.076746 -0.175916\natom 6.14748 2.71111 10.94666 Cu 0.0 0.0 0.139898 -0.257242 0.172429\natom 1.21668 1.48273 11.23387 Cu 0.0 0.0 -0.142815 0.120414 0.042993\natom 4.83005 7.58762 6.79224 Cu 0.0 0.0 -0.049818 0.228401 -0.008749\natom 7.62758 10.19285 0.78354 Cu 0.0 0.0 0.142815 -0.120414 -0.042993\natom 4.01421 4.08797 5.22517 Cu 0.0 0.0 0.049818 -0.228401 0.008749\natom 3.85110 1.33790 5.27324 Cu 0.0 0.0 -0.044256 0.161181 -0.056540\natom 8.04360 7.44525 0.73547 Cu 0.0 0.0 -0.106083 0.170072 0.253168\natom 4.99317 10.33768 6.74417 Cu 0.0 0.0 0.044256 -0.161181 0.056540\natom 0.80067 4.23034 11.28194 Cu 0.0 0.0 0.106083 -0.170072 -0.253168\natom -1.15881 2.56304 10.22321 Cu 0.0 0.0 0.196931 -0.122117 -0.021596\natom 7.10853 8.61626 7.80290 Cu 0.0 0.0 -0.185924 0.117906 -0.005247\natom 10.00307 9.11254 1.79420 Cu 0.0 0.0 -0.196931 0.122117 0.021596\natom 1.73573 3.05932 4.21451 Cu 0.0 0.0 0.185924 -0.117906 0.005247\natom 8.49568 0.21920 8.20789 Cu 0.0 0.0 0.056434 0.126610 -0.120240\natom -2.32558 6.16941 9.81822 Cu 0.0 0.0 0.104585 -0.171937 -0.184100\natom 0.34858 11.45638 3.80952 Cu 0.0 0.0 -0.056434 -0.126610 0.120240\natom 11.16985 5.50618 2.19919 Cu 0.0 0.0 -0.104585 0.171937 0.184100\natom 10.90719 0.69640 2.00811 Cu 0.0 0.0 0.007619 -0.025974 0.057939\natom 1.05420 6.63684 4.00060 Cu 0.0 0.0 0.119930 -0.008806 -0.117113\natom -2.06292 10.97919 10.00930 Cu 0.0 0.0 -0.007619 0.025974 -0.057939\natom 7.79006 5.03875 8.01681 Cu 0.0 0.0 -0.119930 0.008806 0.117113\natom -4.21027 2.21329 9.27984 Cu 0.0 0.0 -0.021258 0.049290 0.136483\natom 10.19438 8.21829 8.74627 Cu 0.0 0.0 0.219895 -0.142704 -0.166314\natom 13.05453 9.46229 2.73757 Cu 0.0 0.0 0.021258 -0.049290 -0.136483\natom -1.35012 3.45729 3.27114 Cu 0.0 0.0 -0.219895 0.142704 0.166314\natom 5.95423 0.86558 3.40573 Cu 0.0 0.0 -0.054552 -0.077539 0.137462\natom 5.98831 6.87746 2.60297 Cu 0.0 0.0 -0.001196 0.186064 -0.127463\natom 2.89004 10.81000 8.61168 Cu 0.0 0.0 0.054552 0.077539 -0.137462\natom 2.85595 4.79812 9.41444 Cu 0.0 0.0 0.001196 -0.186064 0.127463\natom 0.94814 0.32870 7.48685 Cu 0.0 0.0 0.055836 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0.0 0.0 0.115936 0.188847 0.018530\natom 4.89734 0.99062 8.07331 Cu 0.0 0.0 0.157599 0.189225 0.049301\natom 0.66517 6.96166 9.82760 Cu 0.0 0.0 -0.144782 -0.239314 -0.096046\natom 4.05457 11.06674 3.86063 Cu 0.0 0.0 -0.157599 -0.189225 -0.049301\natom 8.28674 5.09570 2.10634 Cu 0.0 0.0 0.144782 0.239314 0.096046\natom 8.09076 1.11688 2.00132 Cu 0.0 0.0 0.212487 0.196624 0.042856\natom 3.95139 7.09079 3.96565 Cu 0.0 0.0 -0.238112 -0.324514 0.012727\natom 0.86115 10.94047 9.93262 Cu 0.0 0.0 -0.212487 -0.196624 -0.042856\natom 5.00052 4.96656 7.96829 Cu 0.0 0.0 0.238112 0.324514 -0.012727\natom 5.06541 2.86651 0.87237 Cu 0.0 0.0 0.196941 0.106208 0.212935\natom 7.10949 8.87132 5.09460 Cu 0.0 0.0 -0.155401 -0.327172 -0.101865\natom 3.88649 9.19084 11.06157 Cu 0.0 0.0 -0.196941 -0.106208 -0.212935\natom 1.84241 3.18603 6.83934 Cu 0.0 0.0 0.155401 0.327172 0.101865\natom -4.16107 1.16412 11.27876 Cu 0.0 0.0 0.241194 0.326585 0.234804\natom 9.73333 7.04745 6.62214 Cu 0.0 0.0 -0.262943 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0.062260 -0.287918\natom 8.85451 3.04537 4.90365 Cu 0.0 0.0 0.061061 0.172723 0.078743\natom 3.32971 8.93986 1.06331 Cu 0.0 0.0 -0.096314 -0.039169 -0.082166\natom 0.09740 9.01199 7.03028 Cu 0.0 0.0 -0.061061 -0.172723 -0.078743\natom 5.62220 3.11749 10.87062 Cu 0.0 0.0 0.096314 0.039169 0.082166\natom 0.65317 1.90938 11.15584 Cu 0.0 0.0 0.076117 0.213335 0.237251\natom 4.97528 7.79608 6.74506 Cu 0.0 0.0 0.073558 0.153641 -0.307487\natom 8.29874 10.14797 0.77809 Cu 0.0 0.0 -0.076117 -0.213335 -0.237251\natom 3.97663 4.26127 5.18888 Cu 0.0 0.0 -0.073558 -0.153641 0.307487\natom 3.58622 1.53343 5.23661 Cu 0.0 0.0 0.265458 0.208897 0.264317\natom 8.48393 7.41881 0.73036 Cu 0.0 0.0 -0.136651 0.198919 -0.438279\natom 5.36569 10.52393 6.69732 Cu 0.0 0.0 -0.265458 -0.208897 -0.264317\natom 0.46798 4.63854 11.20358 Cu 0.0 0.0 0.136651 -0.198919 0.438279\natom -1.53452 2.94233 10.15220 Cu 0.0 0.0 -0.041906 0.197889 0.068859\natom 7.24170 8.85649 7.74870 Cu 0.0 0.0 0.001960 -0.053984 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Cu 0.0 0.0 -0.064070 -0.006725 -0.092414\natom 6.33474 3.51221 3.03480 Cu 0.0 0.0 0.089809 -0.190894 0.216802\natom 13.59474 1.05350 2.58489 Cu 0.0 0.0 0.002464 0.214251 0.055540\natom -1.55796 7.01144 3.38208 Cu 0.0 0.0 0.001119 -0.023073 -0.042321\natom -4.64283 11.00385 9.34905 Cu 0.0 0.0 -0.002464 -0.214251 -0.055540\natom 10.50987 5.04591 8.55186 Cu 0.0 0.0 -0.001119 0.023073 0.042321\natom 3.20631 1.38308 11.37423 Cu 0.0 0.0 -0.222586 -0.176550 0.050215\natom 2.38232 7.26380 6.52667 Cu 0.0 0.0 0.152990 0.292817 -0.046181\natom 5.74559 10.67427 0.55970 Cu 0.0 0.0 0.222586 0.176550 -0.050215\natom 6.56959 4.79355 5.40727 Cu 0.0 0.0 -0.152990 -0.292817 0.046181\natom 6.96238 2.40460 6.75341 Cu 0.0 0.0 0.011462 0.147401 0.213898\natom -1.29215 8.41176 11.14749 Cu 0.0 0.0 -0.196531 -0.058527 -0.160522\natom 1.98953 9.65275 5.18052 Cu 0.0 0.0 -0.011462 -0.147401 -0.213898\natom 10.24406 3.64559 0.78645 Cu 0.0 0.0 0.196531 0.058527 0.160522\natom 2.22451 2.48371 1.66836 Cu 0.0 0.0 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5.81671 Cu 0.0 0.0 -0.028933 -0.025652 -0.339143\natom 10.80342 1.74730 6.02466 Cu 0.0 0.0 0.049192 0.034970 -0.114152\natom -5.44724 7.83258 11.69840 Cu 0.0 0.0 -0.046728 -0.023306 0.221745\natom -2.09379 10.42632 5.79071 Cu 0.0 0.0 -0.049192 -0.034970 0.114152\natom 14.15687 4.34104 0.11697 Cu 0.0 0.0 0.046728 0.023306 -0.221745\natom 8.78911 3.06063 4.85494 Cu 0.0 0.0 0.043907 0.116535 0.227565\natom 3.21036 9.08418 1.05275 Cu 0.0 0.0 -0.067763 0.008745 -0.229009\natom -0.07949 9.11299 6.96044 Cu 0.0 0.0 -0.043907 -0.116535 -0.227565\natom 5.49927 3.08944 10.76262 Cu 0.0 0.0 0.067763 -0.008745 0.229009\natom 0.53457 1.85863 11.04501 Cu 0.0 0.0 0.133369 0.304556 0.276222\natom 4.82542 7.87850 6.67805 Cu 0.0 0.0 -0.053493 0.282949 -0.317531\natom 8.17506 10.31499 0.77036 Cu 0.0 0.0 -0.133369 -0.304556 -0.276222\natom 3.88421 4.29512 5.13732 Cu 0.0 0.0 0.053493 -0.282949 0.317531\natom 3.52817 1.52045 5.18459 Cu 0.0 0.0 0.347592 0.288994 0.337127\natom 8.39650 7.53971 0.72310 Cu 0.0 0.0 -0.280710 0.286991 -0.444369\natom 5.18146 10.65317 6.63079 Cu 0.0 0.0 -0.347592 -0.288994 -0.337127\natom 0.31313 4.63391 11.09227 Cu 0.0 0.0 0.280710 -0.286991 0.444369\natom -1.66196 2.91666 10.05134 Cu 0.0 0.0 0.009943 0.099135 0.004093\natom 7.07359 8.94948 7.67172 Cu 0.0 0.0 -0.033884 -0.049551 -0.004295\natom 10.37159 9.25696 1.76404 Cu 0.0 0.0 -0.009943 -0.099135 -0.004093\natom 1.63604 3.22414 4.14365 Cu 0.0 0.0 0.033884 0.049551 0.004295\natom 7.82668 0.48563 8.06990 Cu 0.0 0.0 -0.229101 -0.275094 -0.254733\natom -2.53235 6.54427 9.65316 Cu 0.0 0.0 0.142073 -0.126212 0.423553\natom 0.88295 11.68799 3.74547 Cu 0.0 0.0 0.229101 0.275094 0.254733\natom 11.24198 5.62935 2.16221 Cu 0.0 0.0 -0.142073 0.126212 -0.423553\natom 10.66038 0.76769 1.97435 Cu 0.0 0.0 0.018466 0.003562 -0.025301\natom 1.22879 6.82878 3.93334 Cu 0.0 0.0 -0.062201 0.016414 0.059439\natom -1.95075 11.40593 9.84102 Cu 0.0 0.0 -0.018466 -0.003562 0.025301\natom 7.48084 5.34484 7.88204 Cu 0.0 0.0 0.062201 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6.88617 2.39515 6.68632 Cu 0.0 0.0 0.162363 0.021333 0.246056\natom -1.49877 8.47181 11.03674 Cu 0.0 0.0 -0.258197 -0.092963 -0.210245\natom 1.82346 9.77847 5.12905 Cu 0.0 0.0 -0.162363 -0.021333 -0.246056\natom 10.20840 3.70181 0.77863 Cu 0.0 0.0 0.258197 0.092963 0.210245\natom 2.18201 2.51356 1.65179 Cu 0.0 0.0 0.118292 0.069708 -0.095932\natom 9.79195 8.57885 4.25590 Cu 0.0 0.0 -0.153928 -0.061658 -0.009531\natom 6.52762 9.66006 10.16358 Cu 0.0 0.0 -0.118292 -0.069708 0.095932\natom -1.08232 3.59478 7.55948 Cu 0.0 0.0 0.153928 0.061658 0.009531\natom -2.47820 1.22081 8.02382 Cu 0.0 0.0 -0.294800 -0.049843 -0.211065\natom 7.80821 7.28005 9.69924 Cu 0.0 0.0 0.258668 0.185740 0.196613\natom 11.18783 10.95281 3.79155 Cu 0.0 0.0 0.294800 0.049843 0.211065\natom 0.90142 4.89357 2.11613 Cu 0.0 0.0 -0.258668 -0.185740 -0.196613\nenergy -571.574110\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_53\nlattice 15.343468000 0.000000000 0.000000000\nlattice -0.410979000 11.904934000 0.000000000\nlattice -5.656722000 -0.285635000 12.205958000\natom 9.89321 0.74636 10.27986 S 0.0 0.0 -0.153813 -0.063504 -0.041304\natom -3.30845 6.75150 8.02908 S 0.0 0.0 -0.034039 0.044295 0.075518\natom -0.61744 10.87294 1.92610 S 0.0 0.0 0.153813 0.063504 0.041304\natom 12.58422 4.86780 4.17688 S 0.0 0.0 0.034039 -0.044295 -0.075518\natom 12.45289 0.81541 4.22570 S 0.0 0.0 -0.066558 0.134478 0.077201\natom -0.20639 6.82284 1.87728 S 0.0 0.0 0.079091 -0.243585 -0.113698\natom -3.17712 10.80389 7.98026 S 0.0 0.0 0.066558 -0.134478 -0.077201\natom 9.48216 4.79646 10.32868 S 0.0 0.0 -0.079091 0.243585 0.113698\natom 9.28202 0.83621 6.18598 S 0.0 0.0 -0.011020 -0.040769 0.039241\natom -2.69686 6.64974 12.12296 S 0.0 0.0 -0.033019 -0.242260 0.261625\natom -0.00625 10.78309 6.01998 S 0.0 0.0 0.011020 0.040769 -0.039241\natom 11.97262 4.96956 0.08300 S 0.0 0.0 0.033019 0.242260 -0.261625\natom 12.07991 0.97092 0.07324 S 0.0 0.0 0.126797 -0.030311 -0.050458\natom 0.16256 6.78400 6.02974 S 0.0 0.0 0.034474 -0.042316 0.215652\natom -2.80414 10.64838 12.13272 S 0.0 0.0 -0.126797 0.030311 0.050458\natom 9.11321 4.83530 6.17621 S 0.0 0.0 -0.034474 0.042316 -0.215652\natom 3.38519 0.87603 7.48591 S 0.0 0.0 -0.060367 -0.084773 0.042088\natom 3.19512 6.75040 10.82302 S 0.0 0.0 -0.036107 0.098412 -0.260135\natom 5.89057 10.74327 4.72004 S 0.0 0.0 0.060367 0.084773 -0.042088\natom 6.08064 4.86890 1.38294 S 0.0 0.0 0.036107 -0.098412 0.260135\natom 6.24745 0.83696 1.16811 S 0.0 0.0 0.159369 0.154897 -0.051478\natom 6.00249 6.70128 4.93487 S 0.0 0.0 -0.180107 -0.258467 0.007594\natom 3.02832 10.78234 11.03785 S 0.0 0.0 -0.159369 -0.154897 0.051478\natom 3.27328 4.91802 7.27109 S 0.0 0.0 0.180107 0.258467 -0.007594\natom 0.11870 0.70504 9.60365 S 0.0 0.0 0.157040 -0.120429 0.074528\natom 6.47000 6.67853 8.70529 S 0.0 0.0 -0.079456 -0.199354 -0.032919\natom 9.15707 10.91426 2.60231 S 0.0 0.0 -0.157040 0.120429 -0.074528\natom 2.80577 4.94077 3.50067 S 0.0 0.0 0.079456 0.199354 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6.38860 S 0.0 0.0 0.022455 -0.201406 0.120071\natom -2.60920 2.83538 11.92034 S 0.0 0.0 -0.013394 0.208766 -0.072911\natom -0.10790 2.72866 1.62583 S 0.0 0.0 0.086652 -0.154425 -0.424107\natom 12.22649 8.61440 4.47715 S 0.0 0.0 -0.054698 -0.249770 0.347231\natom 9.38366 8.89064 10.58012 S 0.0 0.0 -0.086652 0.154425 0.424107\natom -2.95072 3.00490 7.72881 S 0.0 0.0 0.054698 0.249770 -0.347231\natom 11.50613 2.88787 3.57268 Cu 0.0 0.0 -0.145431 -0.182936 -0.058800\natom 0.59833 8.86473 2.53030 Cu 0.0 0.0 0.086118 0.109421 0.092224\natom -2.23036 8.73143 8.63327 Cu 0.0 0.0 0.145431 0.182936 0.058800\natom 8.67744 2.75457 9.67566 Cu 0.0 0.0 -0.086118 -0.109421 -0.092224\natom 5.61127 0.68773 8.25733 Cu 0.0 0.0 -0.123223 -0.219594 0.096198\natom 0.98080 6.59821 10.05161 Cu 0.0 0.0 0.142795 0.100951 -0.043628\natom 3.66450 10.93157 3.94863 Cu 0.0 0.0 0.123223 0.219594 -0.096198\natom 8.29497 5.02109 2.15435 Cu 0.0 0.0 -0.142795 -0.100951 0.043628\natom 8.37631 1.04259 2.04694 Cu 0.0 0.0 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0.196294 0.087395\natom -3.87295 4.75099 11.50900 Cu 0.0 0.0 -0.088907 -0.176245 -0.091304\natom 8.67463 1.18444 12.11197 Cu 0.0 0.0 -0.217198 0.165780 -0.018924\natom -2.12308 7.27533 6.19697 Cu 0.0 0.0 0.154077 0.202274 -0.146993\natom 0.60114 10.43486 0.09399 Cu 0.0 0.0 0.217198 -0.165780 0.018924\natom 11.39885 4.34397 6.00899 Cu 0.0 0.0 -0.154077 -0.202274 0.146993\natom 11.50195 1.53533 6.22382 Cu 0.0 0.0 -0.024261 0.145356 -0.078196\natom -4.96511 7.35064 12.08512 Cu 0.0 0.0 -0.064075 0.207777 -0.012101\natom -2.22618 10.08397 5.98214 Cu 0.0 0.0 0.024261 -0.145356 0.078196\natom 14.24088 4.26866 0.12084 Cu 0.0 0.0 0.064075 -0.207777 0.012101\natom 9.25679 2.86363 5.01543 Cu 0.0 0.0 0.202946 -0.049761 0.076500\natom 2.84700 8.90801 1.08755 Cu 0.0 0.0 -0.179427 0.237171 -0.068881\natom 0.01897 8.75567 7.19053 Cu 0.0 0.0 -0.202946 0.049761 -0.076500\natom 6.42876 2.71129 11.11841 Cu 0.0 0.0 0.179427 -0.237171 0.068881\natom 1.44702 1.49135 11.41013 Cu 0.0 0.0 -0.182505 0.080659 -0.013370\natom 5.08448 7.54939 6.89881 Cu 0.0 0.0 0.027035 0.178558 0.017453\natom 7.82875 10.12795 0.79583 Cu 0.0 0.0 0.182505 -0.080659 0.013370\natom 4.19129 4.06991 5.30715 Cu 0.0 0.0 -0.027035 -0.178558 -0.017453\natom 3.99443 1.33778 5.35597 Cu 0.0 0.0 -0.129578 0.126387 -0.136412\natom 8.21417 7.39810 0.74700 Cu 0.0 0.0 0.013669 0.130735 0.273736\natom 5.28134 10.28152 6.84998 Cu 0.0 0.0 0.129578 -0.126387 0.136412\natom 1.06160 4.22120 11.45895 Cu 0.0 0.0 -0.013669 -0.130735 -0.273736\natom -0.95349 2.56300 10.38361 Cu 0.0 0.0 0.190034 -0.070772 0.020157\natom 7.41266 8.57300 7.92533 Cu 0.0 0.0 -0.192419 0.093009 -0.047781\natom 10.22926 9.05630 1.82235 Cu 0.0 0.0 -0.190034 0.070772 -0.020157\natom 1.86311 3.04630 4.28063 Cu 0.0 0.0 0.192419 -0.093009 0.047781\natom 8.71720 0.23111 8.33667 Cu 0.0 0.0 0.098861 0.145063 -0.039410\natom -2.09373 6.14530 9.97227 Cu 0.0 0.0 0.019130 -0.075648 -0.163916\natom 0.55857 11.38819 3.86929 Cu 0.0 0.0 -0.098861 -0.145063 0.039410\natom 11.36950 5.47400 2.23369 Cu 0.0 0.0 -0.019130 0.075648 0.163916\natom 11.04305 0.69514 2.03962 Cu 0.0 0.0 0.003822 -0.036422 0.001877\natom 1.21528 6.60025 4.06336 Cu 0.0 0.0 0.100897 -0.017049 -0.047897\natom -1.76728 10.92416 10.16634 Cu 0.0 0.0 -0.003822 0.036422 -0.001877\natom 8.06049 5.01905 8.14259 Cu 0.0 0.0 -0.100897 0.017049 0.047897\natom -4.05170 2.21399 9.42544 Cu 0.0 0.0 -0.029327 -0.001825 0.107580\natom 10.53651 8.17914 8.88350 Cu 0.0 0.0 0.188495 -0.158583 -0.156542\natom 13.32747 9.40531 2.78052 Cu 0.0 0.0 0.029327 0.001825 -0.107580\natom -1.26074 3.44016 3.32246 Cu 0.0 0.0 -0.188495 0.158583 0.156542\natom 6.07584 0.86549 3.45917 Cu 0.0 0.0 -0.037442 -0.091795 0.034648\natom 6.16843 6.83704 2.64381 Cu 0.0 0.0 -0.008762 0.122175 -0.029545\natom 3.19993 10.75381 8.74679 Cu 0.0 0.0 0.037442 0.091795 -0.034648\natom 3.10733 4.78226 9.56215 Cu 0.0 0.0 0.008762 -0.122175 0.029545\natom 1.09482 0.33872 7.60431 Cu 0.0 0.0 0.029247 0.011114 0.097159\natom 5.52240 6.21864 10.70463 Cu 0.0 0.0 0.063287 -0.098930 0.091028\natom 8.18095 11.28058 4.60165 Cu 0.0 0.0 -0.029247 -0.011114 -0.097159\natom 3.75337 5.40066 1.50133 Cu 0.0 0.0 -0.063287 0.098930 -0.091028\natom 3.90461 0.47486 1.63438 Cu 0.0 0.0 0.061019 0.074983 0.085854\natom 8.36958 6.36100 4.46860 Cu 0.0 0.0 -0.190807 -0.117665 0.108114\natom 5.37116 11.14444 10.57158 Cu 0.0 0.0 -0.061019 -0.074983 -0.085854\natom 0.90619 5.25830 7.73736 Cu 0.0 0.0 0.190807 0.117665 -0.108114\natom 3.69215 2.26315 9.20695 Cu 0.0 0.0 0.005109 0.011605 -0.089490\natom 2.78962 8.21808 9.10198 Cu 0.0 0.0 0.068098 -0.151469 0.193597\natom 5.58362 9.35615 2.99900 Cu 0.0 0.0 -0.005109 -0.011605 0.089490\natom 6.48615 3.40122 3.10398 Cu 0.0 0.0 -0.068098 0.151469 -0.193597\natom 14.07077 0.95719 2.64381 Cu 0.0 0.0 0.107255 -0.045802 0.019157\natom -1.83151 6.89058 3.45917 Cu 0.0 0.0 -0.143112 0.163999 -0.064776\natom -4.79500 10.66211 9.56215 Cu 0.0 0.0 -0.107255 0.045802 -0.019157\natom 11.10728 4.72872 8.74679 Cu 0.0 0.0 0.143112 -0.163999 0.064776\natom 4.12054 0.95635 11.63350 Cu 0.0 0.0 -0.019284 0.299765 0.036186\natom 2.44753 7.02484 6.67544 Cu 0.0 0.0 0.026305 -0.126960 -0.035308\natom 5.15522 10.66295 0.57246 Cu 0.0 0.0 0.019284 -0.299765 -0.036186\natom 6.82824 4.59446 5.53052 Cu 0.0 0.0 -0.026305 0.126960 0.035308\natom 7.51617 2.15268 6.90735 Cu 0.0 0.0 0.078864 -0.049270 -0.086211\natom -1.02306 7.99997 11.40159 Cu 0.0 0.0 0.153058 0.122752 0.052270\natom 1.75960 9.46662 5.29861 Cu 0.0 0.0 -0.078864 0.049270 0.086211\natom 10.29883 3.61932 0.80437 Cu 0.0 0.0 -0.153058 -0.122752 -0.052270\natom 2.23581 2.42320 1.70639 Cu 0.0 0.0 0.042598 -0.098853 0.146953\natom 9.90374 8.31271 4.39659 Cu 0.0 0.0 0.080536 0.074381 -0.040771\natom 7.03995 9.19610 10.49957 Cu 0.0 0.0 -0.042598 0.098853 -0.146953\natom -0.62797 3.30659 7.80937 Cu 0.0 0.0 -0.080536 -0.074381 0.040771\natom -1.87425 0.95604 8.28907 Cu 0.0 0.0 0.080826 0.189511 0.090753\natom 8.44775 6.86801 10.01987 Cu 0.0 0.0 -0.060290 -0.191559 -0.052698\natom 11.15002 10.66326 3.91689 Cu 0.0 0.0 -0.080826 -0.189511 -0.090753\natom 0.82802 4.75129 2.18609 Cu 0.0 0.0 0.060290 0.191559 0.052698\nenergy -572.877111\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_58\nlattice 15.220935000 0.000000000 0.000000000\nlattice -0.060897000 11.741405000 0.000000000\nlattice -6.148161000 0.599791000 11.995012000\natom 9.39102 1.47851 10.10220 S 0.0 0.0 -0.358701 -0.209562 0.234350\natom -3.43287 7.23861 7.89032 S 0.0 0.0 0.044031 0.173859 -0.043776\natom -0.37914 10.86269 1.89281 S 0.0 0.0 0.358701 0.209562 -0.234350\natom 12.44474 5.10259 4.10469 S 0.0 0.0 -0.044031 -0.173859 0.043776\natom 12.19430 1.10939 4.15267 S 0.0 0.0 -0.100835 -0.124455 0.115322\natom -0.08724 6.86469 1.84483 S 0.0 0.0 0.089826 0.058496 0.075814\natom -3.18242 11.23181 7.84234 S 0.0 0.0 0.100835 0.124455 -0.115322\natom 9.09912 5.47651 10.15018 S 0.0 0.0 -0.089826 -0.058496 -0.075814\natom 8.96452 1.27147 6.07907 S 0.0 0.0 -0.153211 -0.216499 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7.14543 S 0.0 0.0 0.233849 -0.083062 -0.195498\natom -0.27737 1.38892 9.43768 S 0.0 0.0 0.332144 0.031687 -0.018783\natom 6.23610 7.21548 8.55484 S 0.0 0.0 -0.267390 -0.419331 0.023536\natom 9.28925 10.95228 2.55734 S 0.0 0.0 -0.332144 -0.031687 0.018783\natom 2.77577 5.12572 3.44017 S 0.0 0.0 0.267390 0.419331 -0.023536\natom 2.55834 1.14896 3.44137 S 0.0 0.0 -0.356468 -0.102604 0.077183\natom 9.54793 6.97540 2.55614 S 0.0 0.0 0.550926 -0.085937 0.240607\natom 6.45354 11.19223 8.55364 S 0.0 0.0 0.356468 0.102604 -0.077183\natom -0.53606 5.36579 9.43887 S 0.0 0.0 -0.550926 0.085937 -0.240607\natom 6.13969 3.34609 8.66040 S 0.0 0.0 0.043413 -0.258280 0.055003\natom -0.20166 9.25038 9.33212 S 0.0 0.0 0.198737 0.048504 -0.233255\natom 2.87219 8.99510 3.33461 S 0.0 0.0 -0.043413 0.258280 -0.055003\natom 9.21354 3.09081 2.66289 S 0.0 0.0 -0.198737 -0.048504 0.233255\natom 5.76399 2.87649 4.99832 S 0.0 0.0 -0.177032 -0.357258 0.271962\natom 6.32517 8.54722 0.99918 S 0.0 0.0 0.075774 -0.158281 -0.124173\natom 3.24789 9.46471 6.99669 S 0.0 0.0 0.177032 0.357258 -0.271962\natom 2.68671 3.79398 10.99583 S 0.0 0.0 -0.075774 0.158281 0.124173\natom 0.05379 3.08501 5.71682 S 0.0 0.0 -0.080792 -0.120002 -0.093761\natom 12.03358 8.68389 0.28068 S 0.0 0.0 -0.028201 0.080202 0.399904\natom 8.95808 9.25618 6.27819 S 0.0 0.0 0.080792 0.120002 0.093761\natom -3.02170 3.65731 11.71433 S 0.0 0.0 0.028201 -0.080202 -0.399904\natom -0.09792 2.80859 1.59774 S 0.0 0.0 0.072815 -0.299500 0.024414\natom 12.18602 8.81941 4.39977 S 0.0 0.0 -0.163369 -0.298733 0.251864\natom 9.10979 9.53260 10.39728 S 0.0 0.0 -0.072815 0.299500 -0.024414\natom -3.17414 3.52179 7.59524 S 0.0 0.0 0.163369 0.298733 -0.251864\natom 11.34373 3.10621 3.51094 Cu 0.0 0.0 -0.089004 0.110322 -0.116568\natom 0.74227 8.92569 2.48657 Cu 0.0 0.0 0.047038 -0.058013 0.076591\natom -2.33185 9.23498 8.48407 Cu 0.0 0.0 0.089004 -0.110322 0.116568\natom 8.26960 3.41550 9.50845 Cu 0.0 0.0 -0.047038 0.058013 -0.076591\natom 5.22910 1.27462 8.11463 Cu 0.0 0.0 -0.114259 0.074356 -0.016537\natom 0.73013 7.23349 9.87789 Cu 0.0 0.0 0.064218 -0.105808 -0.054908\natom 3.78278 11.06657 3.88039 Cu 0.0 0.0 0.114259 -0.074356 0.016537\natom 8.28175 5.10770 2.11712 Cu 0.0 0.0 -0.064218 0.105808 0.054908\natom 8.25119 1.17610 2.01156 Cu 0.0 0.0 -0.028121 -0.003174 -0.044128\natom 3.85406 7.14553 3.98594 Cu 0.0 0.0 0.088401 -0.264802 0.153415\natom 0.76069 11.16510 9.98345 Cu 0.0 0.0 0.028121 0.003174 0.044128\natom 5.15782 5.19567 8.00907 Cu 0.0 0.0 -0.088401 0.264802 -0.153415\natom 5.05811 2.86178 0.87684 Cu 0.0 0.0 -0.043288 0.076750 0.044901\natom 7.02907 8.94469 5.12067 Cu 0.0 0.0 0.132829 -0.086809 0.012741\natom 3.95377 9.47941 11.11818 Cu 0.0 0.0 0.043288 -0.076750 -0.044901\natom 1.98281 3.39651 6.87434 Cu 0.0 0.0 -0.132829 0.086809 -0.012741\natom -3.87361 1.56371 11.33649 Cu 0.0 0.0 0.049275 0.152936 0.162463\natom 9.83151 7.20037 6.65603 Cu 0.0 0.0 -0.036830 -0.108809 0.036709\natom 12.88548 10.77749 0.65853 Cu 0.0 0.0 -0.049275 -0.152936 -0.162463\natom -0.81963 5.14082 5.33898 Cu 0.0 0.0 0.036830 0.108809 -0.036709\natom -1.10676 1.18500 5.31259 Cu 0.0 0.0 -0.013819 0.053962 -0.007900\natom 13.21363 6.82430 0.68492 Cu 0.0 0.0 0.005469 -0.148826 0.002226\natom 10.11864 11.15620 6.68242 Cu 0.0 0.0 0.013819 -0.053962 0.007900\natom -4.20175 5.51689 11.31010 Cu 0.0 0.0 -0.005469 0.148826 -0.002226\natom 8.11563 2.04289 11.90265 Cu 0.0 0.0 -0.016694 0.086681 -0.066142\natom -2.16241 7.62293 6.08987 Cu 0.0 0.0 0.278137 0.017950 0.172163\natom 0.89624 10.29831 0.09236 Cu 0.0 0.0 0.016694 -0.086681 0.066142\natom 11.17428 4.71826 5.90514 Cu 0.0 0.0 -0.278137 -0.017950 -0.172163\natom 11.18544 1.96372 6.11626 Cu 0.0 0.0 0.093894 0.088954 -0.071208\natom -5.23439 8.12244 11.87626 Cu 0.0 0.0 0.141962 -0.044850 0.193822\natom -2.17357 10.37748 5.87876 Cu 0.0 0.0 -0.093894 -0.088954 0.071208\natom 14.24627 4.21875 0.11875 Cu 0.0 0.0 -0.141962 0.044850 -0.193822\natom 9.04921 3.18650 4.92875 Cu 0.0 0.0 0.171457 0.399526 -0.018755\natom 3.03669 8.86419 1.06876 Cu 0.0 0.0 -0.150600 -0.242100 -0.016786\natom -0.03734 9.15469 7.06626 Cu 0.0 0.0 -0.171457 -0.399526 0.018755\natom 5.97518 3.47700 10.92626 Cu 0.0 0.0 0.150600 0.242100 0.016786\natom 0.98506 2.29489 11.21294 Cu 0.0 0.0 -0.069762 0.143728 0.013435\natom 4.96520 7.94391 6.77958 Cu 0.0 0.0 0.001648 0.134130 -0.182274\natom 8.02682 10.04631 0.78207 Cu 0.0 0.0 0.069762 -0.143728 -0.013435\natom 4.04668 4.39729 5.21543 Cu 0.0 0.0 -0.001648 -0.134130 0.182274\natom 3.76969 1.70621 5.26341 Cu 0.0 0.0 0.062272 0.126361 -0.112579\natom 8.33175 7.35043 0.73409 Cu 0.0 0.0 -0.123871 0.200997 -0.214536\natom 5.24219 10.63499 6.73160 Cu 0.0 0.0 -0.062272 -0.126361 0.112579\natom 0.68013 4.99077 11.26092 Cu 0.0 0.0 0.123871 -0.200997 0.214536\natom -1.32064 3.27769 10.20416 Cu 0.0 0.0 0.055412 -0.058178 0.126158\natom 7.26017 9.02760 7.78836 Cu 0.0 0.0 -0.004297 0.231628 -0.129225\natom 10.33251 9.06350 1.79086 Cu 0.0 0.0 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0.208346 0.013961\natom 6.20391 6.93406 2.59812 Cu 0.0 0.0 0.012843 -0.163049 0.043226\natom 3.10906 11.23777 8.59563 Cu 0.0 0.0 0.012114 -0.208346 -0.013961\natom 2.80797 5.40714 9.39689 Cu 0.0 0.0 -0.012843 0.163049 -0.043226\natom 0.76682 0.88325 7.47289 Cu 0.0 0.0 -0.073561 -0.024060 0.055042\natom 5.19614 6.90630 10.51963 Cu 0.0 0.0 -0.138070 0.209116 -0.308618\natom 8.24506 11.45795 4.52212 Cu 0.0 0.0 0.073561 0.024060 -0.055042\natom 3.81574 5.43490 1.47539 Cu 0.0 0.0 0.138070 -0.209116 0.308618\natom 3.81652 0.58637 1.60613 Cu 0.0 0.0 0.108820 -0.019438 -0.044770\natom 8.29463 6.59634 4.39137 Cu 0.0 0.0 -0.159062 0.162538 -0.258573\natom 5.19535 11.75483 10.38888 Cu 0.0 0.0 -0.108820 0.019438 0.044770\natom 0.71724 5.74486 7.60364 Cu 0.0 0.0 0.159062 -0.162538 0.258573\natom 3.33010 2.89698 9.04784 Cu 0.0 0.0 0.050720 -0.051727 -0.073597\natom 2.61279 8.76253 8.94468 Cu 0.0 0.0 -0.093278 0.119922 -0.087309\natom 5.68178 9.44421 2.94717 Cu 0.0 0.0 -0.050720 0.051727 0.073597\natom 6.39909 3.57867 3.05033 Cu 0.0 0.0 0.093278 -0.119922 0.087309\natom 13.87185 1.13498 2.59812 Cu 0.0 0.0 -0.002698 -0.003103 0.121164\natom -1.76587 7.04575 3.39939 Cu 0.0 0.0 -0.008905 0.067727 -0.062186\natom -4.85998 11.20622 9.39689 Cu 0.0 0.0 0.002698 0.003103 -0.121164\natom 10.77775 5.29545 8.59563 Cu 0.0 0.0 0.008905 -0.067727 0.062186\natom 3.61198 1.78337 11.43245 Cu 0.0 0.0 0.011913 -0.099193 0.081241\natom 2.34370 7.41044 6.56007 Cu 0.0 0.0 0.085094 0.247036 -0.130686\natom 5.39990 10.55782 0.56257 Cu 0.0 0.0 -0.011913 0.099193 -0.081241\natom 6.66818 4.93075 5.43494 Cu 0.0 0.0 -0.085094 -0.247036 0.130686\natom 7.21989 2.62195 6.78798 Cu 0.0 0.0 -0.027768 0.104775 0.032848\natom -1.27532 8.71350 11.20454 Cu 0.0 0.0 -0.071144 0.036733 0.022693\natom 1.79199 9.71924 5.20703 Cu 0.0 0.0 0.027768 -0.104775 -0.032848\natom 10.28720 3.62770 0.79047 Cu 0.0 0.0 0.071144 -0.036733 -0.022693\natom 2.21469 2.51315 1.67690 Cu 0.0 0.0 -0.058356 0.135929 -0.017449\natom 9.87651 8.51604 4.32060 Cu 0.0 0.0 -0.021711 0.050082 -0.026307\natom 6.79718 9.82805 10.31811 Cu 0.0 0.0 0.058356 -0.135929 0.017449\natom -0.86464 3.82515 7.67441 Cu 0.0 0.0 0.021711 -0.050082 0.026307\natom -2.19020 1.54154 8.14581 Cu 0.0 0.0 0.001313 -0.010607 -0.061414\natom 8.14668 7.49729 9.84670 Cu 0.0 0.0 -0.022138 0.129668 -0.006417\natom 11.20208 10.79966 3.84920 Cu 0.0 0.0 -0.001313 0.010607 0.061414\natom 0.86520 4.84391 2.14831 Cu 0.0 0.0 0.022138 -0.129668 0.006417\nenergy -572.421187\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_62\nlattice 15.110213000 0.000000000 0.000000000\nlattice 0.537764000 11.977546000 0.000000000\nlattice -5.399614000 -0.041333000 12.205022000\natom 9.96506 0.95813 10.27907 S 0.0 0.0 0.127819 0.116312 -0.236805\natom -2.59622 6.95452 8.02846 S 0.0 0.0 0.321817 -0.292752 -0.025674\natom 0.28331 10.97808 1.92595 S 0.0 0.0 -0.127819 -0.116312 0.236805\natom 12.84458 4.98169 4.17656 S 0.0 0.0 -0.321817 0.292752 0.025674\natom 12.39520 0.90557 4.22538 S 0.0 0.0 -0.211617 -0.271819 0.092346\natom 0.36669 6.90229 1.87713 S 0.0 0.0 0.214689 0.081688 -0.186853\natom -2.14683 11.03065 7.97964 S 0.0 0.0 0.211617 0.271819 -0.092346\natom 9.88167 5.03392 10.32789 S 0.0 0.0 -0.214689 -0.081688 0.186853\natom 9.30530 0.96600 6.18550 S 0.0 0.0 0.159108 -0.296087 -0.350471\natom -1.93700 6.93467 12.12203 S 0.0 0.0 0.119665 -0.159549 0.104326\natom 0.94307 10.97021 6.01952 S 0.0 0.0 -0.159108 0.296087 0.350471\natom 12.18536 5.00154 0.08299 S 0.0 0.0 -0.119665 0.159549 -0.104326\natom 11.97429 0.97832 0.07323 S 0.0 0.0 0.021383 -0.000006 -0.273494\natom 0.79287 6.94692 6.02928 S 0.0 0.0 -0.071864 -0.137697 0.198657\natom -1.72593 10.95790 12.13179 S 0.0 0.0 -0.021383 0.000006 0.273494\natom 9.45550 4.98929 6.17574 S 0.0 0.0 0.071864 0.137697 -0.198657\natom 3.52190 1.03227 7.48534 S 0.0 0.0 0.019593 0.035198 0.188954\natom 3.85275 7.00974 10.82219 S 0.0 0.0 0.026884 0.025246 -0.231093\natom 6.72647 10.90395 4.71968 S 0.0 0.0 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0.79491 8.92825 9.49551 S 0.0 0.0 0.168058 0.237335 -0.167232\natom 3.49676 8.99443 3.39300 S 0.0 0.0 0.180578 0.112006 -0.390836\natom 9.45346 3.00797 2.70951 S 0.0 0.0 -0.168058 -0.237335 0.167232\natom 6.14916 2.66215 5.08583 S 0.0 0.0 0.155183 -0.240981 0.046928\natom 6.77072 8.66471 1.01668 S 0.0 0.0 -0.099955 -0.131209 -0.163622\natom 4.09920 9.27406 7.11919 S 0.0 0.0 -0.155183 0.240981 -0.046928\natom 3.47764 3.27151 11.18834 S 0.0 0.0 0.099955 0.131209 0.163622\natom 0.53146 2.83575 5.81691 S 0.0 0.0 -0.095738 -0.237212 -0.163869\natom 12.40424 8.84325 0.28560 S 0.0 0.0 0.199716 0.132356 -0.002716\natom 9.71690 9.10047 6.38811 S 0.0 0.0 0.095738 0.237212 0.163869\natom -2.15587 3.09296 11.91942 S 0.0 0.0 -0.199716 -0.132356 0.002716\natom 0.13557 2.77808 1.62571 S 0.0 0.0 0.081420 -0.330275 -0.655466\natom 12.79367 8.75719 4.47680 S 0.0 0.0 -0.053664 -0.105605 0.518787\natom 10.11279 9.15814 10.57931 S 0.0 0.0 -0.081420 0.330275 0.655466\natom -2.54531 3.17902 7.72822 S 0.0 0.0 0.053664 0.105605 -0.518787\natom 11.61654 2.97750 3.57241 Cu 0.0 0.0 0.004802 0.054664 -0.072201\natom 1.33120 8.96980 2.53010 Cu 0.0 0.0 0.104753 -0.201410 0.055109\natom -1.36817 8.95872 8.63261 Cu 0.0 0.0 -0.004802 -0.054664 0.072201\natom 8.91716 2.96641 9.67492 Cu 0.0 0.0 -0.104753 0.201410 -0.055109\natom 5.71147 0.85838 8.25670 Cu 0.0 0.0 -0.031768 0.037671 0.053650\natom 1.64780 6.84107 10.05084 Cu 0.0 0.0 0.069626 -0.229016 -0.114567\natom 4.53690 11.07784 3.94832 Cu 0.0 0.0 0.031768 -0.037671 -0.053650\natom 8.60057 5.09514 2.15419 Cu 0.0 0.0 -0.069626 0.229016 0.114567\natom 8.36400 1.09021 2.04678 Cu 0.0 0.0 -0.009068 0.122091 -0.035994\natom 4.41381 7.07218 4.05573 Cu 0.0 0.0 -0.004257 -0.223393 0.080015\natom 1.88437 10.84600 10.15824 Cu 0.0 0.0 0.009068 -0.122091 0.035994\natom 5.83455 4.86403 8.14929 Cu 0.0 0.0 0.004257 0.223393 -0.080015\natom 5.21634 2.87159 0.89219 Cu 0.0 0.0 -0.141059 0.190825 -0.013539\natom 7.72108 8.84574 5.21032 Cu 0.0 0.0 0.101445 -0.123940 0.048327\natom 5.03203 9.06462 11.31283 Cu 0.0 0.0 0.141059 -0.190825 0.013539\natom 2.52729 3.09047 6.99470 Cu 0.0 0.0 -0.101445 0.123940 -0.048327\natom -3.12946 0.97783 11.53497 Cu 0.0 0.0 0.049389 0.274976 -0.019132\natom 10.50044 6.98273 6.77257 Cu 0.0 0.0 -0.059091 -0.131918 0.016648\natom 13.37782 10.95838 0.67006 Cu 0.0 0.0 -0.049389 -0.274976 0.019132\natom -0.25208 4.95348 5.43246 Cu 0.0 0.0 0.059091 0.131918 -0.016648\natom -0.74014 0.91954 5.40560 Cu 0.0 0.0 -0.057667 0.194012 -0.025496\natom 13.50365 6.92425 0.69691 Cu 0.0 0.0 0.113081 -0.161205 0.029548\natom 10.98851 11.01668 6.79942 Cu 0.0 0.0 0.057667 -0.194012 0.025496\natom -3.25528 5.01196 11.50811 Cu 0.0 0.0 -0.113081 0.161205 -0.029548\natom 8.82876 1.43582 12.11104 Cu 0.0 0.0 -0.176385 0.263847 0.277805\natom -1.41648 7.44462 6.19649 Cu 0.0 0.0 0.084842 0.237319 -0.052503\natom 1.41960 10.50040 0.09398 Cu 0.0 0.0 0.176385 -0.263847 -0.277805\natom 11.66484 4.49159 6.00853 Cu 0.0 0.0 -0.084842 -0.237319 0.052503\natom 11.54742 1.67015 6.22334 Cu 0.0 0.0 0.096375 0.261845 0.080796\natom -4.11588 7.63908 12.08419 Cu 0.0 0.0 -0.128369 0.233925 0.011051\natom -1.29906 10.26606 5.98168 Cu 0.0 0.0 -0.096375 -0.261845 -0.080796\natom 14.36425 4.29713 0.12083 Cu 0.0 0.0 0.128369 -0.233925 -0.011051\natom 9.42238 2.98219 5.01504 Cu 0.0 0.0 0.140483 0.127018 0.126267\natom 3.52622 8.98427 1.08747 Cu 0.0 0.0 -0.180580 0.080266 -0.100715\natom 0.82598 8.95402 7.18998 Cu 0.0 0.0 -0.140483 -0.127018 -0.126267\natom 6.72215 2.95195 11.11755 Cu 0.0 0.0 0.180580 -0.080266 0.100715\natom 1.72418 1.73045 11.40925 Cu 0.0 0.0 -0.026534 0.160863 -0.027219\natom 5.71435 7.73450 6.89828 Cu 0.0 0.0 0.255929 0.036465 0.090658\natom 8.52418 10.20577 0.79577 Cu 0.0 0.0 0.026534 -0.160863 0.027219\natom 4.53402 4.20172 5.30674 Cu 0.0 0.0 -0.255929 -0.036465 -0.090658\natom 4.12463 1.45390 5.35556 Cu 0.0 0.0 -0.022018 0.132677 -0.266094\natom 8.68685 7.45828 0.74695 Cu 0.0 0.0 0.220034 0.067996 0.260738\natom 6.12374 10.48231 6.84946 Cu 0.0 0.0 0.022018 -0.132677 0.266094\natom 1.56152 4.47793 11.45807 Cu 0.0 0.0 -0.220034 -0.067996 -0.260738\natom -0.57129 2.78795 10.38281 Cu 0.0 0.0 0.262071 0.172214 -0.051138\natom 8.10446 8.78504 7.92472 Cu 0.0 0.0 -0.276395 -0.187462 0.063553\natom 10.81965 9.14827 1.82221 Cu 0.0 0.0 -0.262071 -0.172214 0.051138\natom 2.14390 3.15117 4.28030 Cu 0.0 0.0 0.276395 0.187462 -0.063553\natom 8.73529 0.40057 8.33603 Cu 0.0 0.0 -0.070050 -0.049967 0.155724\natom -1.41711 6.38380 9.97150 Cu 0.0 0.0 -0.207197 0.219126 -0.021318\natom 1.51307 11.53565 3.86899 Cu 0.0 0.0 0.070050 0.049967 -0.155724\natom 11.66547 5.55241 2.23352 Cu 0.0 0.0 0.207197 -0.219126 0.021318\natom 10.96258 0.74049 2.03946 Cu 0.0 0.0 -0.099065 -0.070736 0.152666\natom 1.78382 6.72241 4.06305 Cu 0.0 0.0 -0.047373 0.033845 -0.086847\natom -0.71421 11.19572 10.16556 Cu 0.0 0.0 0.099065 0.070736 -0.152666\natom 8.46454 5.21380 8.14197 Cu 0.0 0.0 0.047373 -0.033845 0.086847\natom -3.66523 2.41749 9.42472 Cu 0.0 0.0 -0.184793 -0.173235 0.226266\natom 11.16485 8.40810 8.88281 Cu 0.0 0.0 -0.003379 0.058381 -0.189314\natom 13.91360 9.51872 2.78030 Cu 0.0 0.0 0.184793 0.173235 -0.226266\natom -0.91649 3.52811 3.32221 Cu 0.0 0.0 0.003379 -0.058381 0.189314\natom 6.10689 0.94050 3.45890 Cu 0.0 0.0 -0.011264 0.076665 0.077458\natom 6.65790 6.93204 2.64361 Cu 0.0 0.0 0.053886 -0.017326 -0.119291\natom 4.14147 10.99571 8.74612 Cu 0.0 0.0 0.011264 -0.076665 -0.077458\natom 3.59047 5.00418 9.56141 Cu 0.0 0.0 -0.053886 0.017326 0.119291\natom 1.22569 0.49408 7.60373 Cu 0.0 0.0 -0.060253 -0.138627 -0.173083\natom 6.10067 6.47235 10.70380 Cu 0.0 0.0 0.077010 -0.099372 0.026073\natom 9.02268 11.44214 4.60129 Cu 0.0 0.0 0.060253 0.138627 0.173083\natom 4.14770 5.46386 1.50122 Cu 0.0 0.0 -0.077010 0.099372 -0.026073\natom 3.90878 0.51070 1.63425 Cu 0.0 0.0 0.208682 -0.130961 -0.136516\natom 8.81686 6.48987 4.46826 Cu 0.0 0.0 -0.015002 0.021333 0.004975\natom 6.33958 11.42552 10.57077 Cu 0.0 0.0 -0.208682 0.130961 0.136516\natom 1.43150 5.44634 7.73676 Cu 0.0 0.0 0.015002 -0.021333 -0.004975\natom 3.96132 2.46255 9.20625 Cu 0.0 0.0 -0.088217 -0.129268 -0.244168\natom 3.54228 8.45168 9.10128 Cu 0.0 0.0 -0.005616 -0.015359 0.153653\natom 6.28704 9.47367 2.99877 Cu 0.0 0.0 0.088217 0.129268 0.244168\natom 6.70608 3.48454 3.10374 Cu 0.0 0.0 0.005616 0.015359 -0.153653\natom 13.97460 1.01633 2.64361 Cu 0.0 0.0 0.220412 0.256949 -0.034529\natom -1.20325 7.00234 3.45890 Cu 0.0 0.0 -0.175442 -0.068308 0.052004\natom -3.72624 10.91989 9.56141 Cu 0.0 0.0 -0.220412 -0.256949 0.034529\natom 11.45161 4.93388 8.74612 Cu 0.0 0.0 0.175442 0.068308 -0.052004\natom 4.31826 1.19669 11.63261 Cu 0.0 0.0 -0.113350 -0.033312 0.046633\natom 3.07241 7.20225 6.67493 Cu 0.0 0.0 0.035215 0.253275 0.004535\natom 5.93011 10.73952 0.57242 Cu 0.0 0.0 0.113350 0.033312 -0.046633\natom 7.17595 4.73396 5.53010 Cu 0.0 0.0 -0.035215 -0.253275 -0.004535\natom 7.68196 2.30504 6.90682 Cu 0.0 0.0 -0.198500 0.152088 -0.091986\natom -0.19320 8.27860 11.40071 Cu 0.0 0.0 -0.049053 -0.056427 0.095959\natom 2.56641 9.63117 5.29820 Cu 0.0 0.0 0.198500 -0.152088 0.091986\natom 10.44156 3.65761 0.80431 Cu 0.0 0.0 0.049053 0.056427 -0.095959\natom 2.42075 2.47238 1.70626 Cu 0.0 0.0 -0.014507 0.046491 0.079821\natom 10.48107 8.45204 4.39625 Cu 0.0 0.0 -0.087687 -0.156102 -0.253999\natom 7.82762 9.46384 10.49876 Cu 0.0 0.0 0.014507 -0.046491 -0.079821\natom -0.23270 3.48417 7.80877 Cu 0.0 0.0 0.087687 0.156102 0.253999\natom -1.63851 1.12896 8.28843 Cu 0.0 0.0 0.069324 -0.225031 0.040708\natom 9.02208 7.11187 10.01910 Cu 0.0 0.0 -0.072791 0.151412 -0.058514\natom 11.88688 10.80725 3.91659 Cu 0.0 0.0 -0.069324 0.225031 -0.040708\natom 1.22628 4.82434 2.18592 Cu 0.0 0.0 0.072791 -0.151412 0.058514\nenergy -572.495163\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_67\nlattice 15.082966000 0.000000000 0.000000000\nlattice -0.414362000 11.922623000 0.000000000\nlattice -5.952643000 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0.0 0.0 0.005182 -0.177427 0.112061\natom 0.35430 6.54426 9.78510 Cu 0.0 0.0 0.000607 0.181338 -0.032617\natom 3.45622 11.04183 3.84394 Cu 0.0 0.0 -0.005182 0.177427 -0.112061\natom 8.17486 5.06638 2.09723 Cu 0.0 0.0 -0.000607 -0.181338 0.032617\natom 8.24463 1.02686 1.99267 Cu 0.0 0.0 0.127345 -0.248036 -0.075535\natom 3.62407 6.99383 3.94850 Cu 0.0 0.0 -0.155918 0.195413 -0.022055\natom 0.28453 10.58378 9.88967 Cu 0.0 0.0 -0.127345 0.248036 0.075535\natom 4.90508 4.61682 7.93383 Cu 0.0 0.0 0.155918 -0.195413 0.022055\natom 5.00773 2.86699 0.86860 Cu 0.0 0.0 0.046279 -0.283463 0.004795\natom 6.75553 8.74278 5.07257 Cu 0.0 0.0 -0.125119 0.048069 -0.117205\natom 3.52143 8.74365 11.01374 Cu 0.0 0.0 -0.046279 0.283463 -0.004795\natom 1.77363 2.86787 6.80977 Cu 0.0 0.0 0.125119 -0.048069 0.117205\natom -4.17264 0.57117 11.22999 Cu 0.0 0.0 0.200598 -0.224704 0.075141\natom 9.59212 6.80552 6.59351 Cu 0.0 0.0 -0.195951 0.245194 -0.226835\natom 12.70179 11.03948 0.65234 Cu 0.0 0.0 -0.200598 0.224704 -0.075141\natom -1.06296 4.80512 5.28883 Cu 0.0 0.0 0.195951 -0.245194 0.226835\natom -1.25274 0.73339 5.26269 Cu 0.0 0.0 0.217961 -0.209785 0.107096\natom 13.13090 6.96563 0.67848 Cu 0.0 0.0 -0.242881 0.195139 -0.094958\natom 9.78190 10.87725 6.61965 Cu 0.0 0.0 -0.217961 0.209785 -0.107096\natom -4.60174 4.64501 11.20385 Cu 0.0 0.0 0.242881 -0.195139 0.094958\natom 7.88567 1.01277 11.79084 Cu 0.0 0.0 -0.260036 0.017638 -0.314668\natom -2.49347 7.29263 6.03266 Cu 0.0 0.0 0.087085 0.127434 0.035611\natom 0.64349 10.59787 0.09149 Cu 0.0 0.0 0.260036 -0.017638 0.314668\natom 11.02263 4.31802 5.84967 Cu 0.0 0.0 -0.087085 -0.127434 -0.035611\natom 11.09854 1.46173 6.05880 Cu 0.0 0.0 -0.144701 -0.057138 -0.235860\natom -5.71906 7.27659 11.76470 Cu 0.0 0.0 -0.029828 0.105554 0.041174\natom -2.56938 10.14892 5.82353 Cu 0.0 0.0 0.144701 0.057138 0.235860\natom 14.24822 4.33405 0.11764 Cu 0.0 0.0 0.029828 -0.105554 -0.041174\natom 8.93931 2.82995 4.88245 Cu 0.0 0.0 0.144463 -0.149413 0.232403\natom 2.81656 9.03134 1.05872 Cu 0.0 0.0 -0.120166 0.283482 -0.214313\natom -0.41015 8.78069 6.99988 Cu 0.0 0.0 -0.144463 0.149413 -0.232403\natom 5.71260 2.57930 10.82362 Cu 0.0 0.0 0.120166 -0.283482 0.214313\natom 0.70773 1.33555 11.10761 Cu 0.0 0.0 0.048926 0.273420 0.246242\natom 4.66713 7.55997 6.71590 Cu 0.0 0.0 -0.099487 0.300730 -0.113138\natom 7.82143 10.27510 0.77473 Cu 0.0 0.0 -0.048926 -0.273420 -0.246242\natom 3.86203 4.05067 5.16644 Cu 0.0 0.0 0.099487 -0.300730 0.113138\natom 3.64929 1.27470 5.21397 Cu 0.0 0.0 0.198784 0.275579 0.295496\natom 8.19717 7.50298 0.72720 Cu 0.0 0.0 -0.228840 0.245206 0.030155\natom 4.87986 10.33594 6.66837 Cu 0.0 0.0 -0.198784 -0.275579 -0.295496\natom 0.33199 4.10766 11.15514 Cu 0.0 0.0 0.228840 -0.245206 -0.030155\natom -1.61990 2.44023 10.10830 Cu 0.0 0.0 0.090640 -0.037418 0.028667\natom 6.93222 8.58359 7.71520 Cu 0.0 0.0 -0.086690 0.041686 -0.048667\natom 10.14905 9.17042 1.77403 Cu 0.0 0.0 -0.090640 0.037418 -0.028667\natom 1.59693 3.02705 4.16713 Cu 0.0 0.0 0.086690 -0.041686 0.048667\natom 8.17053 0.10374 8.11563 Cu 0.0 0.0 -0.146327 -0.044104 -0.361966\natom -2.71615 6.08546 9.70787 Cu 0.0 0.0 0.133378 -0.270575 -0.027011\natom 0.35863 11.50690 3.76670 Cu 0.0 0.0 0.146327 0.044104 0.361966\natom 11.24531 5.52519 2.17447 Cu 0.0 0.0 -0.133378 0.270575 0.027011\natom 10.90936 0.67404 1.98554 Cu 0.0 0.0 -0.007727 -0.074216 -0.034825\natom 0.98009 6.64043 3.95563 Cu 0.0 0.0 0.065498 0.019377 0.011204\natom -2.38020 10.93660 9.89680 Cu 0.0 0.0 0.007727 0.074216 0.034825\natom 7.54906 4.97021 7.92671 Cu 0.0 0.0 -0.065498 -0.019377 -0.011204\natom -4.65609 2.10077 9.17554 Cu 0.0 0.0 -0.012729 0.047056 0.030759\natom 9.99059 8.16847 8.64796 Cu 0.0 0.0 0.152036 -0.035056 0.014786\natom 13.18524 9.50987 2.70680 Cu 0.0 0.0 0.012729 -0.047056 -0.030759\natom -1.46143 3.44217 3.23437 Cu 0.0 0.0 -0.152036 0.035056 -0.014786\natom 5.85179 0.82478 3.36745 Cu 0.0 0.0 -0.034696 -0.058867 0.140365\natom 6.02551 6.90327 2.57371 Cu 0.0 0.0 -0.006700 0.247483 -0.146956\natom 2.67737 10.78587 8.51488 Cu 0.0 0.0 0.034696 0.058867 -0.140365\natom 2.50365 4.70737 9.30862 Cu 0.0 0.0 0.006700 -0.247483 0.146956\natom 0.59902 0.22456 7.40269 Cu 0.0 0.0 0.113224 0.175581 0.330088\natom 4.84995 6.14844 10.42081 Cu 0.0 0.0 0.045024 -0.072307 -0.009110\natom 7.93013 11.38608 4.47964 Cu 0.0 0.0 -0.113224 -0.175581 -0.330088\natom 3.67921 5.46220 1.46153 Cu 0.0 0.0 -0.045024 0.072307 0.009110\natom 3.79872 0.45666 1.59104 Cu 0.0 0.0 0.031403 0.243839 0.257457\natom 8.10445 6.39105 4.35012 Cu 0.0 0.0 -0.146671 -0.021020 0.062282\natom 4.73044 11.15399 10.29129 Cu 0.0 0.0 -0.031403 -0.243839 -0.257457\natom 0.42471 5.21960 7.53221 Cu 0.0 0.0 0.146671 0.021020 -0.062282\natom 3.09973 2.15414 8.96284 Cu 0.0 0.0 0.069968 0.159098 0.134794\natom 2.23214 8.20458 8.86066 Cu 0.0 0.0 -0.026279 -0.091037 0.049811\natom 5.42943 9.45650 2.91949 Cu 0.0 0.0 -0.069968 -0.159098 -0.134794\natom 6.29702 3.40606 3.02168 Cu 0.0 0.0 0.026279 0.091037 -0.049811\natom 13.89781 0.93074 2.57371 Cu 0.0 0.0 0.055803 0.005334 0.012156\natom -2.02484 6.94484 3.36745 Cu 0.0 0.0 -0.067014 0.168223 -0.057276\natom -5.36865 10.67991 9.30862 Cu 0.0 0.0 -0.055803 -0.005334 -0.012156\natom 10.55400 4.66580 8.51488 Cu 0.0 0.0 0.067014 -0.168223 0.057276\natom 3.36328 0.78861 11.32505 Cu 0.0 0.0 -0.115443 0.251441 0.037640\natom 2.04320 7.03067 6.49845 Cu 0.0 0.0 0.126172 -0.213700 -0.029206\natom 5.16587 10.82204 0.55728 Cu 0.0 0.0 0.115443 -0.251441 -0.037640\natom 6.48596 4.57997 5.38389 Cu 0.0 0.0 -0.126172 0.213700 0.029206\natom 7.07227 2.07806 6.72421 Cu 0.0 0.0 0.244824 -0.128040 0.045427\natom -1.73060 7.94691 11.09929 Cu 0.0 0.0 -0.047408 0.066761 -0.110267\natom 1.45688 9.53258 5.15812 Cu 0.0 0.0 -0.244824 0.128040 -0.045427\natom 10.25976 3.66374 0.78305 Cu 0.0 0.0 0.047408 -0.066761 0.110267\natom 2.13486 2.43458 1.66115 Cu 0.0 0.0 0.071239 -0.091876 0.050214\natom 9.65192 8.37466 4.28002 Cu 0.0 0.0 0.046162 0.112217 0.110158\natom 6.39430 9.17606 10.22118 Cu 0.0 0.0 -0.071239 0.091876 -0.050214\natom -1.12276 3.23599 7.60232 Cu 0.0 0.0 -0.046162 -0.112217 -0.110158\natom -2.41095 0.84085 8.06929 Cu 0.0 0.0 -0.113660 0.218257 -0.046653\natom 7.82212 6.81881 9.75421 Cu 0.0 0.0 0.153849 -0.119069 0.101061\natom 10.94011 10.76979 3.81304 Cu 0.0 0.0 0.113660 -0.218257 0.046653\natom 0.70704 4.79184 2.12813 Cu 0.0 0.0 -0.153849 0.119069 -0.101061\nenergy -572.447944\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_76\nlattice 15.521001000 0.000000000 0.000000000\nlattice 0.087909000 11.961396000 0.000000000\nlattice -5.306127000 -0.372234000 12.155296000\natom 10.39983 0.67810 10.23719 S 0.0 0.0 0.137110 0.105864 -0.336425\natom -2.77949 6.72744 7.99575 S 0.0 0.0 0.112049 -0.151548 0.098901\natom -0.09704 10.91106 1.91811 S 0.0 0.0 -0.137110 -0.105864 0.336425\natom 13.08227 4.86172 4.15954 S 0.0 0.0 -0.112049 0.151548 -0.098901\natom 12.77969 0.78977 4.20816 S 0.0 0.0 -0.107658 -0.111985 0.048217\natom 0.14571 6.84208 1.86948 S 0.0 0.0 0.131598 -0.127365 -0.202641\natom -2.47691 10.79939 7.94713 S 0.0 0.0 0.107658 0.111985 -0.048217\natom 10.15708 4.74708 10.28581 S 0.0 0.0 -0.131598 0.127365 0.202641\natom 9.64177 0.79697 6.16030 S 0.0 0.0 0.143633 -0.138625 -0.181370\natom -2.02152 6.59661 12.07264 S 0.0 0.0 -0.005982 -0.248552 0.276033\natom 0.66101 10.79219 5.99499 S 0.0 0.0 -0.143633 0.138625 0.181370\natom 12.32430 4.99255 0.08266 S 0.0 0.0 0.005982 0.248552 -0.276033\natom 12.26332 0.97501 0.07293 S 0.0 0.0 0.159273 -0.012649 -0.267284\natom 0.66293 6.77406 6.00472 S 0.0 0.0 -0.105024 -0.193214 0.368132\natom -1.96054 10.61415 12.08236 S 0.0 0.0 -0.159273 0.012649 0.267284\natom 9.63985 4.81510 6.15058 S 0.0 0.0 0.105024 0.193214 -0.368132\natom 3.72400 0.82790 7.45484 S 0.0 0.0 -0.005237 -0.067059 0.176281\natom 3.89729 6.70683 10.77810 S 0.0 0.0 -0.006952 0.130801 -0.478367\natom 6.57879 10.76126 4.70045 S 0.0 0.0 0.005237 0.067059 -0.176281\natom 6.40549 4.88233 1.37720 S 0.0 0.0 0.006952 -0.130801 0.478367\natom 6.39612 0.83277 1.16326 S 0.0 0.0 0.158544 -0.033107 -0.063018\natom 6.52854 6.69860 4.91439 S 0.0 0.0 -0.067065 -0.131629 -0.048622\natom 3.90666 10.75639 10.99203 S 0.0 0.0 -0.158544 0.033107 0.063018\natom 3.77425 4.89056 7.24091 S 0.0 0.0 0.067065 0.131629 0.048622\natom 0.48675 0.64131 9.56379 S 0.0 0.0 0.015610 -0.307154 0.220157\natom 7.13274 6.64941 8.66916 S 0.0 0.0 -0.037642 -0.035708 -0.135533\natom 9.81603 10.94785 2.59151 S 0.0 0.0 -0.015610 0.307154 -0.220157\natom 3.17004 4.93976 3.48614 S 0.0 0.0 0.037642 0.035708 0.135533\natom 2.89761 0.88839 3.48735 S 0.0 0.0 -0.358045 0.009102 0.256143\natom 10.02891 6.89656 2.59029 S 0.0 0.0 0.214599 0.043521 -0.264630\natom 7.40518 10.70077 8.66794 S 0.0 0.0 0.358045 -0.009102 -0.256143\natom 0.27387 4.69260 9.56500 S 0.0 0.0 -0.214599 -0.043521 0.264630\natom 6.99340 2.69887 8.77612 S 0.0 0.0 -0.202949 0.144688 0.408795\natom 0.65598 8.65872 9.45682 S 0.0 0.0 0.062019 0.065666 -0.215640\natom 3.30938 8.89029 3.37917 S 0.0 0.0 0.202949 -0.144688 -0.408795\natom 9.64680 2.93044 2.69848 S 0.0 0.0 -0.062019 -0.065666 0.215640\natom 6.31256 2.52065 5.06511 S 0.0 0.0 0.001769 -0.065930 0.173765\natom 6.63866 8.62546 1.01254 S 0.0 0.0 0.056012 -0.172554 -0.358765\natom 3.99022 9.06851 7.09018 S 0.0 0.0 -0.001769 0.065930 -0.173765\natom 3.66412 2.96371 11.14276 S 0.0 0.0 -0.056012 0.172554 0.358765\natom 0.54969 2.67419 5.79321 S 0.0 0.0 -0.009478 -0.049457 -0.245298\natom 12.40411 8.82358 0.28443 S 0.0 0.0 0.111212 -0.098226 -0.001696\natom 9.75309 8.91497 6.36208 S 0.0 0.0 0.009478 0.049457 0.245298\natom -2.10133 2.76558 11.87086 S 0.0 0.0 -0.111212 0.098226 0.001696\natom 0.06332 2.73025 1.61909 S 0.0 0.0 0.264388 -0.264172 -0.765592\natom 12.88943 8.62399 4.45856 S 0.0 0.0 -0.140378 -0.134530 0.516205\natom 10.23947 8.85891 10.53621 S 0.0 0.0 -0.264388 0.264172 0.765592\natom -2.58665 2.96517 7.69673 S 0.0 0.0 0.140378 0.134530 -0.516205\natom 11.88674 2.87661 3.55786 Cu 0.0 0.0 -0.108856 -0.079580 -0.066294\natom 1.06903 8.88910 2.51979 Cu 0.0 0.0 0.141128 -0.036594 0.080590\natom -1.58396 8.71255 8.59744 Cu 0.0 0.0 0.108856 0.079580 0.066294\natom 9.23375 2.70006 9.63550 Cu 0.0 0.0 -0.141128 0.036594 -0.080590\natom 5.99492 0.63333 8.22306 Cu 0.0 0.0 -0.140977 -0.096747 0.091949\natom 1.62386 6.55931 10.00989 Cu 0.0 0.0 0.197268 -0.042134 -0.083519\natom 4.30786 10.95584 3.93224 Cu 0.0 0.0 0.140977 0.096747 -0.091949\natom 8.67893 5.02986 2.14541 Cu 0.0 0.0 -0.197268 0.042134 0.083519\natom 8.58913 1.03324 2.03844 Cu 0.0 0.0 -0.090606 -0.093259 -0.106747\natom 4.33887 6.95267 4.03920 Cu 0.0 0.0 0.059893 -0.035210 0.051809\natom 1.71365 10.55592 10.11685 Cu 0.0 0.0 0.090606 0.093259 0.106747\natom 5.96392 4.63649 8.11609 Cu 0.0 0.0 -0.059893 0.035210 -0.051809\natom 5.26424 2.84352 0.88855 Cu 0.0 0.0 -0.198209 0.028605 -0.090162\natom 7.68985 8.69253 5.18910 Cu 0.0 0.0 0.166023 0.055072 0.088958\natom 5.03854 8.74564 11.26674 Cu 0.0 0.0 0.198209 -0.028605 0.090162\natom 2.61293 2.89664 6.96620 Cu 0.0 0.0 -0.166023 -0.055072 -0.088958\natom -3.02688 0.66372 11.48797 Cu 0.0 0.0 0.007359 -0.004765 -0.110752\natom 10.64757 6.78967 6.74497 Cu 0.0 0.0 -0.028792 0.071615 0.022975\natom 13.32966 10.92544 0.66733 Cu 0.0 0.0 -0.007359 0.004765 0.110752\natom -0.34479 4.79949 5.41032 Cu 0.0 0.0 0.028792 -0.071615 -0.022975\natom -0.69021 0.77171 5.38358 Cu 0.0 0.0 -0.159421 0.012004 -0.101914\natom 13.61587 6.89602 0.69407 Cu 0.0 0.0 0.159649 0.049512 0.101542\natom 10.99300 10.81745 6.77172 Cu 0.0 0.0 0.159421 -0.012004 0.101914\natom -3.31309 4.69314 11.46123 Cu 0.0 0.0 -0.159649 -0.049512 -0.101542\natom 9.24995 1.10547 12.06170 Cu 0.0 0.0 -0.394980 0.235350 0.281035\natom -1.62250 7.26655 6.17124 Cu 0.0 0.0 0.258322 0.232267 -0.207254\natom 1.05284 10.48369 0.09360 Cu 0.0 0.0 0.394980 -0.235350 -0.281035\natom 11.92528 4.32261 5.98405 Cu 0.0 0.0 -0.258322 -0.232267 0.207254\natom 11.91829 1.49915 6.19799 Cu 0.0 0.0 -0.062591 0.245999 0.085107\natom -4.28770 7.30110 12.03496 Cu 0.0 0.0 -0.026944 0.252653 -0.045642\natom -1.61551 10.09001 5.95731 Cu 0.0 0.0 0.062591 -0.245999 -0.085107\natom 14.59048 4.28806 0.12034 Cu 0.0 0.0 0.026944 -0.252653 0.045642\natom 9.66097 2.84218 4.99461 Cu 0.0 0.0 0.205194 -0.032168 0.143266\natom 3.29495 8.94267 1.08304 Cu 0.0 0.0 -0.226918 0.256032 -0.112915\natom 0.64182 8.74698 7.16068 Cu 0.0 0.0 -0.205194 0.032168 -0.143266\natom 7.00783 2.64650 11.07226 Cu 0.0 0.0 0.226918 -0.256032 0.112915\natom 1.92707 1.41873 11.36277 Cu 0.0 0.0 -0.055930 0.166451 -0.077402\natom 5.70467 7.53701 6.87017 Cu 0.0 0.0 0.072341 0.192059 0.166021\natom 8.37572 10.17043 0.79253 Cu 0.0 0.0 0.055930 -0.166451 0.077402\natom 4.59812 4.05215 5.28512 Cu 0.0 0.0 -0.072341 -0.192059 -0.166021\natom 4.28511 1.30672 5.33374 Cu 0.0 0.0 -0.078301 0.162981 -0.335856\natom 8.64839 7.42797 0.74390 Cu 0.0 0.0 0.101388 0.128573 0.498972\natom 6.01767 10.28244 6.82155 Cu 0.0 0.0 0.078301 -0.162981 0.335856\natom 1.65439 4.16119 11.41139 Cu 0.0 0.0 -0.101388 -0.128573 -0.498972\natom -0.49189 2.50264 10.34051 Cu 0.0 0.0 0.294679 0.068776 -0.042221\natom 8.13909 8.55831 7.89243 Cu 0.0 0.0 -0.321510 -0.119642 0.024045\natom 10.79467 9.08652 1.81479 Cu 0.0 0.0 -0.294679 -0.068776 0.042221\natom 2.16369 3.03085 4.26286 Cu 0.0 0.0 0.321510 0.119642 -0.024045\natom 9.12025 0.17398 8.30207 Cu 0.0 0.0 -0.024521 0.034497 0.140469\natom -1.50819 6.10480 9.93088 Cu 0.0 0.0 -0.072022 0.038655 -0.242374\natom 1.18253 11.41518 3.85323 Cu 0.0 0.0 0.024521 -0.034497 -0.140469\natom 11.81098 5.48436 2.22442 Cu 0.0 0.0 0.072022 -0.038655 0.242374\natom 11.27178 0.68419 2.03115 Cu 0.0 0.0 -0.188474 -0.141228 0.181453\natom 1.65109 6.60317 4.04650 Cu 0.0 0.0 0.173013 -0.035557 -0.182528\natom -0.96899 10.90497 10.12415 Cu 0.0 0.0 0.188474 0.141228 -0.181453\natom 8.65170 4.98599 8.10880 Cu 0.0 0.0 -0.173013 0.035557 0.182528\natom -3.67432 2.15867 9.38632 Cu 0.0 0.0 -0.232229 -0.194270 0.259609\natom 11.31604 8.15589 8.84662 Cu 0.0 0.0 0.249362 -0.166576 -0.327851\natom 13.97710 9.43050 2.76898 Cu 0.0 0.0 0.232229 0.194270 -0.259609\natom -1.01325 3.43327 3.30867 Cu 0.0 0.0 -0.249362 0.166576 0.327851\natom 6.30409 0.84544 3.44481 Cu 0.0 0.0 -0.033683 -0.070022 0.061380\natom 6.62178 6.85100 2.63284 Cu 0.0 0.0 0.026599 0.069009 -0.108291\natom 3.99870 10.74372 8.71048 Cu 0.0 0.0 0.033683 0.070022 -0.061380\natom 3.68100 4.73816 9.52246 Cu 0.0 0.0 -0.026599 -0.069009 0.108291\natom 1.38854 0.28722 7.57275 Cu 0.0 0.0 0.089842 -0.069801 -0.162851\natom 6.22485 6.17337 10.66019 Cu 0.0 0.0 0.006424 -0.135420 0.180625\natom 8.91424 11.30194 4.58255 Cu 0.0 0.0 -0.089842 0.069801 0.162851\natom 4.07793 5.41579 1.49510 Cu 0.0 0.0 -0.006424 0.135420 -0.180625\natom 4.02720 0.46569 1.62759 Cu 0.0 0.0 0.202906 -0.029848 -0.144728\natom 8.89227 6.35996 4.45005 Cu 0.0 0.0 -0.155199 -0.087435 0.198884\natom 6.27558 11.12347 10.52770 Cu 0.0 0.0 -0.202906 0.029848 0.144728\natom 1.41052 5.22920 7.70524 Cu 0.0 0.0 0.155199 0.087435 -0.198884\natom 4.15355 2.20959 9.16874 Cu 0.0 0.0 -0.037706 -0.142908 -0.328788\natom 3.48882 8.19349 9.06420 Cu 0.0 0.0 0.051027 -0.179541 0.294359\natom 6.14923 9.37958 2.98656 Cu 0.0 0.0 0.037706 0.142908 0.328788\natom 6.81396 3.39568 3.09109 Cu 0.0 0.0 -0.051027 0.179541 -0.294359\natom 14.36680 0.94327 2.63284 Cu 0.0 0.0 0.219500 0.108507 -0.039796\natom -1.43986 6.89910 3.44481 Cu 0.0 0.0 -0.222438 0.014689 0.006796\natom -4.06402 10.64589 9.52246 Cu 0.0 0.0 -0.219500 -0.108507 0.039796\natom 11.74264 4.69006 8.71048 Cu 0.0 0.0 0.222438 -0.014689 -0.006796\natom 4.61673 0.87964 11.58521 Cu 0.0 0.0 -0.054379 0.160894 0.040863\natom 3.00718 7.01154 6.64773 Cu 0.0 0.0 -0.020262 0.022223 0.010382\natom 5.68605 10.70952 0.57008 Cu 0.0 0.0 0.054379 -0.160894 -0.040863\natom 7.29560 4.57762 5.50756 Cu 0.0 0.0 0.020262 -0.022223 -0.010382\natom 7.93648 2.11465 6.87868 Cu 0.0 0.0 0.034557 -0.016686 -0.220501\natom -0.29654 7.95829 11.35426 Cu 0.0 0.0 0.025928 -0.012725 0.140345\natom 2.36630 9.47451 5.27661 Cu 0.0 0.0 -0.034557 0.016686 0.220501\natom 10.59932 3.63087 0.80103 Cu 0.0 0.0 -0.025928 0.012725 -0.140345\natom 2.42405 2.42277 1.69931 Cu 0.0 0.0 -0.057003 -0.072016 0.158058\natom 10.52422 8.32143 4.37834 Cu 0.0 0.0 0.087804 -0.079956 -0.259596\natom 7.87873 9.16639 10.45599 Cu 0.0 0.0 0.057003 0.072016 -0.158058\natom -0.22143 3.26773 7.77696 Cu 0.0 0.0 -0.087804 0.079956 0.259596\natom -1.56475 0.90269 8.25466 Cu 0.0 0.0 0.096953 -0.024056 0.119889\natom 9.18750 6.83060 9.97828 Cu 0.0 0.0 -0.080972 -0.046945 -0.080182\natom 11.86754 10.68648 3.90063 Cu 0.0 0.0 -0.096953 0.024056 -0.119889\natom 1.11528 4.75856 2.17701 Cu 0.0 0.0 0.080972 0.046945 0.080182\nenergy -571.815093\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_81\nlattice 15.225699000 0.000000000 0.000000000\nlattice 0.538760000 11.671474000 0.000000000\nlattice -5.711684000 0.492567000 11.925947000\natom 9.81289 1.38240 10.04403 S 0.0 0.0 0.000333 -0.163600 0.012871\natom -2.79601 7.12731 7.84489 S 0.0 0.0 0.231017 -0.213886 -0.044610\natom 0.23989 10.78164 1.88191 S 0.0 0.0 -0.000333 0.163600 -0.012871\natom 12.84879 5.03673 4.08106 S 0.0 0.0 -0.231017 0.213886 0.044610\natom 12.39594 1.06690 4.12876 S 0.0 0.0 -0.101576 -0.479348 0.176880\natom 0.32605 6.80786 1.83421 S 0.0 0.0 0.063975 0.274180 -0.068900\natom -2.34317 11.09714 7.79718 S 0.0 0.0 0.101576 0.479348 -0.176880\natom 9.72673 5.35618 10.09174 S 0.0 0.0 -0.063975 -0.274180 0.068900\natom 9.23892 1.21136 6.04407 S 0.0 0.0 0.026164 -0.288928 -0.405937\natom -2.22258 7.28668 11.84485 S 0.0 0.0 -0.059308 0.137604 -0.189740\natom 0.81386 10.95268 5.88188 S 0.0 0.0 -0.026164 0.288928 0.405937\natom 12.27535 4.87736 0.08110 S 0.0 0.0 0.059308 -0.137604 0.189740\natom 12.06393 0.95651 0.07156 S 0.0 0.0 -0.052916 0.075575 -0.299796\natom 0.66334 7.03262 5.89142 S 0.0 0.0 -0.260903 0.175229 -0.071663\natom -2.01116 11.20753 11.85439 S 0.0 0.0 0.052916 -0.075575 0.299796\natom 9.38944 5.13142 6.03453 S 0.0 0.0 0.260903 -0.175229 0.071663\natom 3.38246 1.33268 7.31418 S 0.0 0.0 -0.020998 -0.013926 0.287781\natom 3.64024 7.30309 10.57474 S 0.0 0.0 0.176095 -0.425889 0.236136\natom 6.67032 10.83136 4.61176 S 0.0 0.0 0.020998 0.013926 -0.287781\natom 6.41254 4.86095 1.35121 S 0.0 0.0 -0.176095 0.425889 -0.236136\natom 6.25881 0.89449 1.14131 S 0.0 0.0 0.259218 -0.532510 -0.071726\natom 6.45866 6.88223 4.82166 S 0.0 0.0 -0.247871 0.303040 0.171301\natom 3.79397 11.26955 10.78463 S 0.0 0.0 -0.259218 0.532510 0.071726\natom 3.59412 5.28181 7.10429 S 0.0 0.0 0.247871 -0.303040 -0.171301\natom 0.11431 1.29909 9.38334 S 0.0 0.0 0.155894 -0.103538 0.066929\natom 6.89740 7.09858 8.50559 S 0.0 0.0 -0.256195 -0.109720 -0.094384\natom 9.93846 10.86495 2.54261 S 0.0 0.0 -0.155894 0.103538 -0.066929\natom 3.15538 5.06546 3.42036 S 0.0 0.0 0.256195 0.109720 0.094384\natom 2.73481 1.11238 3.42155 S 0.0 0.0 -0.688161 0.004230 0.358146\natom 9.99408 6.91177 2.54142 S 0.0 0.0 0.290418 0.080648 0.085370\natom 7.31797 11.05166 8.50439 S 0.0 0.0 0.688161 -0.004230 -0.358146\natom 0.05870 5.25227 9.38453 S 0.0 0.0 -0.290418 -0.080648 -0.085370\natom 6.60692 3.25133 8.61053 S 0.0 0.0 0.016350 -0.466164 0.328098\natom 0.58797 9.11465 9.27839 S 0.0 0.0 0.219516 0.410560 -0.273827\natom 3.44586 8.91271 3.31541 S 0.0 0.0 -0.016350 0.466164 -0.328098\natom 9.46481 3.04939 2.64756 S 0.0 0.0 -0.219516 -0.410560 0.273827\natom 6.08262 2.81616 4.96954 S 0.0 0.0 -0.038285 -0.496024 0.429211\natom 6.79766 8.48768 0.99343 S 0.0 0.0 0.072396 -0.307228 -0.375592\natom 3.97015 9.34788 6.95641 S 0.0 0.0 0.038285 0.496024 -0.429211\natom 3.25512 3.67636 10.93252 S 0.0 0.0 -0.072396 0.307228 0.375592\natom 0.40571 3.01724 5.68391 S 0.0 0.0 0.002063 -0.521246 -0.162901\natom 12.49040 8.62974 0.27907 S 0.0 0.0 -0.036347 0.276688 0.313995\natom 9.64706 9.14680 6.24204 S 0.0 0.0 -0.002063 0.521246 0.162901\natom -2.43763 3.53430 11.64688 S 0.0 0.0 0.036347 -0.276688 -0.313995\natom 0.09981 2.77806 1.58854 S 0.0 0.0 0.264084 -0.530447 -0.298871\natom 12.78984 8.72886 4.37444 S 0.0 0.0 -0.315007 -0.328716 0.507989\natom 9.95296 9.38598 10.33741 S 0.0 0.0 -0.264084 0.530447 0.298871\natom -2.73706 3.43518 7.55151 S 0.0 0.0 0.315007 0.328716 -0.507989\natom 11.62528 3.05737 3.49072 Cu 0.0 0.0 -0.095008 0.319764 -0.197142\natom 1.28290 8.85105 2.47225 Cu 0.0 0.0 0.180864 -0.263362 0.129156\natom -1.57251 9.10667 8.43522 Cu 0.0 0.0 0.095008 -0.319764 0.197142\natom 8.76987 3.31299 9.45370 Cu 0.0 0.0 -0.180864 0.263362 -0.129156\natom 5.57169 1.19691 8.06790 Cu 0.0 0.0 -0.199442 0.294316 -0.090207\natom 1.43560 7.10505 9.82102 Cu 0.0 0.0 0.162008 -0.332955 -0.035966\natom 4.48108 10.96713 3.85804 Cu 0.0 0.0 0.199442 -0.294316 0.090207\natom 8.61718 5.05899 2.10493 Cu 0.0 0.0 -0.162008 0.332955 0.035966\natom 8.38222 1.15171 1.99998 Cu 0.0 0.0 -0.116311 0.228561 -0.093060\natom 4.35572 7.06852 3.96299 Cu 0.0 0.0 0.182233 -0.581379 0.257739\natom 1.67055 11.01233 9.92597 Cu 0.0 0.0 0.116311 -0.228561 0.093060\natom 5.69706 5.09552 7.96295 Cu 0.0 0.0 -0.182233 0.581379 -0.257739\natom 5.23566 2.83716 0.87179 Cu 0.0 0.0 -0.201675 0.390187 0.030331\natom 7.66218 8.84717 5.09119 Cu 0.0 0.0 0.219474 -0.259380 0.063080\natom 4.81711 9.32688 11.05416 Cu 0.0 0.0 0.201675 -0.390187 -0.030331\natom 2.39060 3.31687 6.83476 Cu 0.0 0.0 -0.219474 0.259380 -0.063080\natom -3.40957 1.45643 11.27121 Cu 0.0 0.0 -0.046020 0.451051 0.054748\natom 10.42861 7.09997 6.61771 Cu 0.0 0.0 0.040915 -0.430788 0.107527\natom 13.46235 10.70761 0.65473 Cu 0.0 0.0 0.046020 -0.451051 -0.054748\natom -0.37583 5.06407 5.30824 Cu 0.0 0.0 -0.040915 0.430788 -0.107527\natom -0.86598 1.13203 5.28200 Cu 0.0 0.0 -0.146211 0.323275 -0.061338\natom 13.58959 6.77774 0.68097 Cu 0.0 0.0 0.218817 -0.412908 0.054987\natom 10.91876 11.03201 6.64395 Cu 0.0 0.0 0.146211 -0.323275 0.061338\natom -3.53681 5.38630 11.24498 Cu 0.0 0.0 -0.218817 0.412908 -0.054987\natom 8.62714 1.92787 11.83412 Cu 0.0 0.0 -0.160625 0.141110 0.235082\natom -1.56673 7.52491 6.05480 Cu 0.0 0.0 0.333439 0.044648 0.098560\natom 1.42563 10.23617 0.09183 Cu 0.0 0.0 0.160625 -0.141110 -0.235082\natom 11.61950 4.63913 5.87114 Cu 0.0 0.0 -0.333439 -0.044648 -0.098560\natom 11.49716 1.89917 6.08104 Cu 0.0 0.0 0.085673 0.160157 0.076204\natom -4.41746 7.97144 11.80788 Cu 0.0 0.0 0.118802 -0.011562 0.155787\natom -1.44438 10.26487 5.84491 Cu 0.0 0.0 -0.085673 -0.160157 -0.076204\natom 14.47023 4.19260 0.11807 Cu 0.0 0.0 -0.118802 0.011562 -0.155787\natom 9.38234 3.12493 4.90037 Cu 0.0 0.0 0.173417 0.422081 0.049989\natom 3.52670 8.80216 1.06260 Cu 0.0 0.0 -0.196520 -0.224210 -0.068206\natom 0.67043 9.03911 7.02558 Cu 0.0 0.0 -0.173417 -0.422081 -0.049989\natom 6.52607 3.36188 10.86335 Cu 0.0 0.0 0.196520 0.224210 0.068206\natom 1.48376 2.18433 11.14838 Cu 0.0 0.0 0.060257 0.169028 -0.074272\natom 5.60295 7.83801 6.74055 Cu 0.0 0.0 0.173350 0.021758 -0.038703\natom 8.56902 9.97971 0.77757 Cu 0.0 0.0 -0.060257 -0.169028 0.074272\natom 4.44983 4.32603 5.18540 Cu 0.0 0.0 -0.173350 -0.021758 0.038703\natom 4.03694 1.65056 5.23311 Cu 0.0 0.0 0.134967 0.113866 -0.362626\natom 8.73473 7.30031 0.72987 Cu 0.0 0.0 0.035882 0.144526 0.040243\natom 6.01584 10.51348 6.69284 Cu 0.0 0.0 -0.134967 -0.113866 0.362626\natom 1.31805 4.86373 11.19608 Cu 0.0 0.0 -0.035882 -0.144526 -0.040243\natom -0.80676 3.16999 10.14540 Cu 0.0 0.0 0.146112 0.177424 0.075456\natom 7.98828 8.90653 7.74352 Cu 0.0 0.0 -0.148678 -0.026547 -0.031817\natom 10.85953 8.99405 1.78054 Cu 0.0 0.0 -0.146112 -0.177424 -0.075456\natom 2.06449 3.25751 4.18243 Cu 0.0 0.0 0.148678 0.026547 0.031817\natom 8.61698 0.75426 8.14542 Cu 0.0 0.0 -0.055748 -0.204733 0.361503\natom -1.65086 6.65600 9.74350 Cu 0.0 0.0 -0.088672 0.160559 0.088132\natom 1.43579 11.40978 3.78053 Cu 0.0 0.0 0.055748 0.204733 -0.361503\natom 11.70363 5.50804 2.18245 Cu 0.0 0.0 0.088672 -0.160559 -0.088132\natom 11.00092 0.81061 1.99283 Cu 0.0 0.0 -0.145954 0.109695 0.129322\natom 1.70556 6.72801 3.97015 Cu 0.0 0.0 -0.015970 0.020729 -0.056743\natom -0.94814 11.35343 9.93312 Cu 0.0 0.0 0.145954 -0.109695 -0.129322\natom 8.34722 5.43603 7.95580 Cu 0.0 0.0 0.015970 -0.020729 0.056743\natom -3.90299 2.76718 9.20922 Cu 0.0 0.0 -0.271555 -0.156644 0.253869\natom 11.05090 8.58104 8.67970 Cu 0.0 0.0 -0.000256 0.079262 -0.207427\natom 13.95577 9.39686 2.71673 Cu 0.0 0.0 0.271555 0.156644 -0.253869\natom -0.99813 3.58300 3.24624 Cu 0.0 0.0 0.000256 -0.079262 0.207427\natom 6.07658 1.06748 3.37981 Cu 0.0 0.0 -0.004833 0.245592 0.065101\natom 6.64832 6.87031 2.58316 Cu 0.0 0.0 0.042366 -0.244047 -0.059305\natom 3.97620 11.09656 8.54613 Cu 0.0 0.0 0.004833 -0.245592 -0.065101\natom 3.40445 5.29373 9.34279 Cu 0.0 0.0 -0.042366 0.244047 0.059305\natom 1.06621 0.81341 7.42987 Cu 0.0 0.0 -0.018947 -0.080568 -0.194989\natom 5.90811 6.77426 10.45906 Cu 0.0 0.0 -0.182753 0.206456 -0.207612\natom 8.98657 11.35063 4.49608 Cu 0.0 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0.010727\natom 1.18589 4.79649 2.13594 Cu 0.0 0.0 0.126344 -0.379930 0.060059\nenergy -571.066315\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_86\nlattice 15.250171000 0.000000000 0.000000000\nlattice -0.162479000 11.972516000 0.000000000\nlattice -6.016617000 -0.002379000 12.255553000\natom 9.52137 0.99052 10.32163 S 0.0 0.0 -0.173169 0.047043 0.041573\natom -3.40431 6.97721 8.06170 S 0.0 0.0 0.062444 0.127209 0.011765\natom -0.45030 10.97962 1.93393 S 0.0 0.0 0.173169 -0.047043 -0.041573\natom 12.47538 4.99292 4.19385 S 0.0 0.0 -0.062444 -0.127209 -0.011765\natom 12.25955 0.91867 4.24287 S 0.0 0.0 -0.106453 0.050672 0.021809\natom -0.12389 6.90538 1.88490 S 0.0 0.0 0.109426 -0.068215 -0.007471\natom -3.18848 11.05147 8.01268 S 0.0 0.0 0.106453 -0.050672 -0.021809\natom 9.19496 5.06476 10.37065 S 0.0 0.0 -0.109426 0.068215 0.007471\natom 9.04603 0.98533 6.21111 S 0.0 0.0 -0.069088 -0.082697 0.011750\natom -2.92880 6.97043 12.17221 S 0.0 0.0 0.013514 -0.103355 0.067076\natom 0.02505 10.98481 6.04444 S 0.0 0.0 0.069088 0.082697 -0.011750\natom 11.99987 4.99971 0.08334 S 0.0 0.0 -0.013514 0.103355 -0.067076\natom 12.02419 0.97814 0.07353 S 0.0 0.0 0.029481 -0.073227 0.008135\natom 0.10989 6.96324 6.05424 S 0.0 0.0 -0.005759 -0.026889 0.028680\natom -2.95311 10.99200 12.18202 S 0.0 0.0 -0.029481 0.073227 -0.008135\natom 8.96119 5.00690 6.20131 S 0.0 0.0 0.005759 0.026889 -0.028680\natom 3.14451 1.05571 7.51633 S 0.0 0.0 -0.070394 0.056348 0.061141\natom 2.97080 7.04132 10.86700 S 0.0 0.0 0.051389 0.056778 -0.063043\natom 5.92656 10.91442 4.73922 S 0.0 0.0 0.070394 -0.056348 -0.061141\natom 6.10028 4.92882 1.38855 S 0.0 0.0 -0.051389 -0.056778 0.063043\natom 6.18959 0.86898 1.17286 S 0.0 0.0 0.100769 0.031127 -0.068688\natom 5.94744 6.85450 4.95492 S 0.0 0.0 -0.131384 -0.085182 0.065372\natom 2.88148 11.10116 11.08270 S 0.0 0.0 -0.100769 -0.031127 0.068688\natom 3.12363 5.11564 7.30063 S 0.0 0.0 0.131384 0.085182 -0.065372\natom -0.17304 0.93318 9.64267 S 0.0 0.0 0.200455 -0.159273 0.001406\natom 6.29166 6.91961 8.74066 S 0.0 0.0 -0.174947 -0.237010 -0.002547\natom 9.24411 11.03696 2.61288 S 0.0 0.0 -0.200455 0.159273 -0.001406\natom 2.77941 5.05052 3.51489 S 0.0 0.0 0.174947 0.237010 0.002547\natom 2.59594 0.99543 3.51612 S 0.0 0.0 -0.223968 -0.023771 -0.120846\natom 9.53765 6.98186 2.61166 S 0.0 0.0 0.348179 -0.036762 0.067584\natom 6.47514 10.97471 8.73943 S 0.0 0.0 0.223968 0.023771 0.120846\natom -0.46657 4.98827 9.64389 S 0.0 0.0 -0.348179 0.036762 -0.067584\natom 6.22981 2.96866 8.84851 S 0.0 0.0 -0.063308 0.006503 0.088580\natom -0.16643 8.95479 9.53482 S 0.0 0.0 0.059621 -0.118281 -0.143381\natom 2.84126 9.00147 3.40704 S 0.0 0.0 0.063308 -0.006503 -0.088580\natom 9.23750 3.01535 2.72073 S 0.0 0.0 -0.059621 0.118281 0.143381\natom 5.81210 2.67726 5.10689 S 0.0 0.0 -0.025749 -0.085258 -0.015434\natom 6.27583 8.66431 1.02089 S 0.0 0.0 0.006493 -0.094016 0.045257\natom 3.25898 9.29288 7.14866 S 0.0 0.0 0.025749 0.085258 0.015434\natom 2.79524 3.30583 11.23467 S 0.0 0.0 -0.006493 0.094016 -0.045257\natom 0.09803 2.85311 5.84100 S 0.0 0.0 -0.078834 0.124446 -0.099537\natom 11.98512 8.84045 0.28678 S 0.0 0.0 0.052684 0.001779 0.125251\natom 8.97305 9.11702 6.41456 S 0.0 0.0 0.078834 -0.124446 0.099537\natom -2.91405 3.12969 11.96877 S 0.0 0.0 -0.052684 -0.001779 -0.125251\natom -0.10259 2.78210 1.63244 S 0.0 0.0 -0.078489 -0.109487 -0.172902\natom 12.18769 8.76780 4.49534 S 0.0 0.0 0.071390 -0.154637 0.192012\natom 9.17366 9.18804 10.62311 S 0.0 0.0 0.078489 0.109487 0.172902\natom -3.11662 3.20234 7.76022 S 0.0 0.0 -0.071390 0.154637 -0.192012\natom 11.38215 2.98764 3.58720 Cu 0.0 0.0 -0.066258 -0.082275 -0.026868\natom 0.69736 8.97410 2.54058 Cu 0.0 0.0 0.036158 0.003386 0.034124\natom -2.31108 8.98249 8.66835 Cu 0.0 0.0 0.066258 0.082275 0.026868\natom 8.37372 2.99603 9.71498 Cu 0.0 0.0 -0.036158 -0.003386 -0.034124\natom 5.32862 0.88436 8.29088 Cu 0.0 0.0 -0.046533 -0.106573 0.105640\natom 0.79134 6.87027 10.09245 Cu 0.0 0.0 0.042587 -0.010650 -0.094142\natom 3.74246 11.08578 3.96467 Cu 0.0 0.0 0.046533 0.106573 -0.105640\natom 8.27973 5.09987 2.16311 Cu 0.0 0.0 -0.042587 0.010650 0.094142\natom 8.28178 1.09628 2.05526 Cu 0.0 0.0 0.006148 -0.111541 -0.034809\natom 3.84907 7.08215 4.07252 Cu 0.0 0.0 -0.006508 0.005343 0.020825\natom 0.78929 10.87385 10.20030 Cu 0.0 0.0 -0.006148 0.111541 0.034809\natom 5.22200 4.88799 8.18303 Cu 0.0 0.0 0.006508 -0.005343 -0.020825\natom 5.05395 2.87323 0.89588 Cu 0.0 0.0 -0.046335 -0.075036 -0.031622\natom 7.02868 8.85865 5.23190 Cu 0.0 0.0 0.052325 0.026402 0.018208\natom 4.01712 9.09691 11.35967 Cu 0.0 0.0 0.046335 0.075036 0.031622\natom 2.04239 3.11149 7.02366 Cu 0.0 0.0 -0.052325 -0.026402 -0.018208\natom -3.75418 1.01422 11.58272 Cu 0.0 0.0 0.088303 -0.000263 0.045528\natom 9.87059 7.00140 6.80061 Cu 0.0 0.0 -0.086474 0.135059 -0.041213\natom 12.82525 10.95592 0.67283 Cu 0.0 0.0 -0.088303 0.000263 -0.045528\natom -0.79952 4.96873 5.45495 Cu 0.0 0.0 0.086474 -0.135059 0.041213\natom -1.05334 0.93639 5.42798 Cu 0.0 0.0 0.019098 -0.074501 -0.033126\natom 13.18852 6.92357 0.69979 Cu 0.0 0.0 -0.038907 0.040046 0.035906\natom 10.12441 11.03374 6.82757 Cu 0.0 0.0 -0.019098 0.074501 0.033126\natom -4.11744 5.04657 11.55576 Cu 0.0 0.0 0.038907 -0.040046 -0.035906\natom 8.26096 1.47385 12.16118 Cu 0.0 0.0 -0.078567 0.162575 -0.104321\natom -2.15702 7.46126 6.22214 Cu 0.0 0.0 0.092955 0.170823 0.042740\natom 0.81011 10.49629 0.09437 Cu 0.0 0.0 0.078567 -0.162575 0.104321\natom 11.22810 4.50888 6.03341 Cu 0.0 0.0 -0.092955 -0.170823 -0.042740\natom 11.26570 1.68931 6.24911 Cu 0.0 0.0 0.042107 0.136832 -0.101979\natom -5.16757 7.67442 12.13422 Cu 0.0 0.0 -0.042388 0.149834 0.076378\natom -2.19462 10.28083 6.00645 Cu 0.0 0.0 -0.042107 -0.136832 0.101979\natom 14.23865 4.29572 0.12133 Cu 0.0 0.0 0.042388 -0.149834 -0.076378\natom 9.10009 2.99694 5.03581 Cu 0.0 0.0 0.173728 0.068602 0.055221\natom 2.97916 8.98396 1.09197 Cu 0.0 0.0 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-0.003127\natom 3.12436 11.01900 8.78233 Cu 0.0 0.0 0.012290 -0.022001 -0.012624\natom 2.88300 5.03258 9.60100 Cu 0.0 0.0 -0.000036 -0.053317 0.003127\natom 0.85320 0.51813 7.63521 Cu 0.0 0.0 -0.060104 -0.026809 0.134873\natom 5.27670 6.50378 10.74812 Cu 0.0 0.0 0.062934 -0.045514 -0.087932\natom 8.21788 11.45201 4.62034 Cu 0.0 0.0 0.060104 0.026809 -0.134873\natom 3.79437 5.46636 1.50743 Cu 0.0 0.0 -0.062934 0.045514 0.087932\natom 3.83867 0.51570 1.64102 Cu 0.0 0.0 0.033894 0.041555 0.105813\natom 8.30794 6.50140 4.48676 Cu 0.0 0.0 -0.089728 -0.010936 -0.070037\natom 5.23240 11.45444 10.61453 Cu 0.0 0.0 -0.033894 -0.041555 -0.105813\natom 0.76313 5.46873 7.76879 Cu 0.0 0.0 0.089728 0.010936 0.070037\natom 3.42350 2.49088 9.24436 Cu 0.0 0.0 -0.025857 0.001399 -0.004656\natom 2.65285 8.47716 9.13897 Cu 0.0 0.0 0.043474 -0.040394 0.028802\natom 5.64757 9.47925 3.01119 Cu 0.0 0.0 0.025857 -0.001399 0.004656\natom 6.41823 3.49298 3.11659 Cu 0.0 0.0 -0.043474 0.040394 -0.028802\natom 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0.019037\natom 2.37490 2.90710 7.09766 Cu 0.0 0.0 -0.048686 -0.011567 -0.016276\natom -3.18801 0.64790 11.70476 Cu 0.0 0.0 0.081331 0.084913 -0.021142\natom 10.15608 6.83186 6.87226 Cu 0.0 0.0 -0.095600 0.115341 -0.051226\natom 12.92315 11.01209 0.67992 Cu 0.0 0.0 -0.081331 -0.084913 0.021142\natom -0.42094 4.82814 5.51242 Cu 0.0 0.0 0.095600 -0.115341 0.051226\natom -0.78824 0.76800 5.48517 Cu 0.0 0.0 -0.017716 0.025800 -0.006722\natom 13.16317 6.95022 0.70717 Cu 0.0 0.0 0.032534 0.021529 0.011678\natom 10.52339 10.89199 6.89950 Cu 0.0 0.0 0.017716 -0.025800 0.006722\natom -3.42803 4.70978 11.67751 Cu 0.0 0.0 -0.032534 -0.021529 -0.011678\natom 8.63154 1.09214 12.28932 Cu 0.0 0.0 -0.081720 0.277202 0.132002\natom -1.64896 7.31364 6.28770 Cu 0.0 0.0 -0.077566 0.270829 -0.044115\natom 1.10361 10.56785 0.09536 Cu 0.0 0.0 0.081720 -0.277202 -0.132002\natom 11.38410 4.34635 6.09698 Cu 0.0 0.0 0.077566 -0.270829 0.044115\natom 11.34758 1.49979 6.31495 Cu 0.0 0.0 0.129636 0.259092 0.011172\natom -4.35824 7.33766 12.26207 Cu 0.0 0.0 -0.230864 0.276823 -0.002583\natom -1.61244 10.16021 6.06973 Cu 0.0 0.0 -0.129636 -0.259092 -0.011172\natom 14.09338 4.32234 0.12261 Cu 0.0 0.0 0.230864 -0.276823 0.002583\natom 9.21325 2.85584 5.08886 Cu 0.0 0.0 0.125897 -0.020368 0.086208\natom 3.22672 9.01261 1.10347 Cu 0.0 0.0 -0.153837 0.214180 -0.047876\natom 0.52190 8.80415 7.29581 Cu 0.0 0.0 -0.125897 0.020368 -0.086208\natom 6.50842 2.64739 11.28120 Cu 0.0 0.0 0.153837 -0.214180 0.047876\natom 1.59505 1.40921 11.57720 Cu 0.0 0.0 -0.143533 0.100922 0.011952\natom 5.39675 7.58498 6.99982 Cu 0.0 0.0 0.232340 0.069930 0.066432\natom 8.14009 10.25078 0.80748 Cu 0.0 0.0 0.143533 -0.100922 -0.011952\natom 4.33839 4.07501 5.38486 Cu 0.0 0.0 -0.232340 -0.069930 -0.066432\natom 4.01168 1.30740 5.43440 Cu 0.0 0.0 -0.132215 0.107653 -0.096394\natom 8.38010 7.48635 0.75794 Cu 0.0 0.0 0.221053 0.052407 0.239019\natom 5.72346 10.35259 6.95028 Cu 0.0 0.0 0.132215 -0.107653 0.096394\natom 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0.0 0.0 0.005170 0.047363 -0.009143\natom 3.80025 2.21047 9.34176 Cu 0.0 0.0 -0.079256 -0.014704 -0.104872\natom 3.21442 8.24270 9.23525 Cu 0.0 0.0 0.041840 -0.043704 0.102765\natom 5.93489 9.44952 3.04292 Cu 0.0 0.0 0.079256 0.014704 0.104872\natom 6.52072 3.41730 3.14942 Cu 0.0 0.0 -0.041840 0.043704 -0.102765\natom 13.78807 0.94601 2.68252 Cu 0.0 0.0 0.160354 0.184271 -0.026081\natom -1.41038 6.94825 3.50982 Cu 0.0 0.0 -0.150969 0.039062 0.005451\natom -4.05293 10.71399 9.70216 Cu 0.0 0.0 -0.160354 -0.184271 0.026081\natom 11.14553 4.71174 8.87486 Cu 0.0 0.0 0.150969 -0.039062 -0.005451\natom 4.17665 0.86537 11.80384 Cu 0.0 0.0 -0.141725 0.174609 0.017969\natom 2.79833 7.05569 6.77318 Cu 0.0 0.0 0.057429 0.066136 0.053453\natom 5.55849 10.79462 0.58084 Cu 0.0 0.0 0.141725 -0.174609 -0.017969\natom 6.93681 4.60430 5.61150 Cu 0.0 0.0 -0.057429 -0.066136 -0.053453\natom 7.49978 2.11899 7.00849 Cu 0.0 0.0 -0.133534 0.079922 -0.028798\natom -0.49033 8.00139 11.56853 Cu 0.0 0.0 0.101015 0.037730 -0.002820\natom 2.23536 9.54101 5.37619 Cu 0.0 0.0 0.133534 -0.079922 0.028798\natom 10.22548 3.65860 0.81615 Cu 0.0 0.0 -0.101015 -0.037730 0.002820\natom 2.31585 2.43913 1.73138 Cu 0.0 0.0 0.129675 -0.033262 0.054196\natom 10.10768 8.38031 4.46096 Cu 0.0 0.0 -0.136777 -0.088488 -0.151916\natom 7.41929 9.22086 10.65330 Cu 0.0 0.0 -0.129675 0.033262 -0.054196\natom -0.37254 3.27969 7.92372 Cu 0.0 0.0 0.136777 0.088488 0.151916\natom -1.69906 0.89474 8.41043 Cu 0.0 0.0 0.059825 -0.052646 0.041450\natom 8.67154 6.86717 10.16658 Cu 0.0 0.0 -0.037442 -0.033340 -0.016128\natom 11.43420 10.76525 3.97424 Cu 0.0 0.0 -0.059825 0.052646 -0.041450\natom 1.06360 4.79283 2.21810 Cu 0.0 0.0 0.037442 0.033340 0.016128\nenergy -572.565892\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_95\nlattice 14.950433000 0.000000000 0.000000000\nlattice -0.204541000 11.902584000 0.000000000\nlattice -5.359512000 -0.539214000 12.252670000\natom 9.78430 0.53260 10.31920 S 0.0 0.0 -0.109680 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10.19790 Cu 0.0 0.0 0.043484 0.264807 0.125425\natom 5.46067 4.50098 8.18111 Cu 0.0 0.0 -0.002815 -0.122899 -0.006896\natom 4.98315 2.81720 0.89567 Cu 0.0 0.0 -0.149322 -0.101002 -0.031325\natom 7.08708 8.57772 5.23066 Cu 0.0 0.0 0.107677 0.198532 -0.009581\natom 4.40323 8.54617 11.35700 Cu 0.0 0.0 0.149322 0.101002 0.031325\natom 2.29930 2.78565 7.02201 Cu 0.0 0.0 -0.107677 -0.198532 0.009581\natom -3.17497 0.50092 11.58000 Cu 0.0 0.0 0.031212 -0.140479 -0.065121\natom 9.94913 6.66261 6.79901 Cu 0.0 0.0 -0.047446 0.305489 -0.058134\natom 12.56135 10.86245 0.67267 Cu 0.0 0.0 -0.031212 0.140479 0.065121\natom -0.56275 4.70076 5.45366 Cu 0.0 0.0 0.047446 -0.305489 0.058134\natom -0.79752 0.69315 5.42671 Cu 0.0 0.0 -0.119416 -0.170040 -0.022159\natom 12.93390 6.85248 0.69963 Cu 0.0 0.0 0.082819 0.185654 0.025962\natom 10.18390 10.67022 6.82596 Cu 0.0 0.0 0.119416 0.170040 0.022159\natom -3.54752 4.51089 11.55304 Cu 0.0 0.0 -0.082819 -0.185654 -0.025962\natom 8.62772 0.93253 12.15832 Cu 0.0 0.0 -0.127590 0.230719 0.099371\natom -1.86926 7.14512 6.22068 Cu 0.0 0.0 -0.036361 0.254528 -0.172618\natom 0.75866 10.43084 0.09435 Cu 0.0 0.0 0.127590 -0.230719 -0.099371\natom 11.25564 4.21825 6.03199 Cu 0.0 0.0 0.036361 -0.254528 0.172618\natom 11.31264 1.40570 6.24764 Cu 0.0 0.0 0.099769 0.206815 -0.017407\natom -4.56151 7.09806 12.13137 Cu 0.0 0.0 -0.231466 0.259144 -0.041721\natom -1.92626 9.95767 6.00503 Cu 0.0 0.0 -0.099769 -0.206815 0.017407\natom 13.94789 4.26531 0.12130 Cu 0.0 0.0 0.231466 -0.259144 0.041721\natom 9.13131 2.75884 5.03462 Cu 0.0 0.0 0.138655 -0.137581 0.051974\natom 2.93466 8.88366 1.09171 Cu 0.0 0.0 -0.147132 0.348936 -0.014869\natom 0.25507 8.60453 7.21805 Cu 0.0 0.0 -0.138655 0.137581 -0.051974\natom 6.45172 2.47971 11.16096 Cu 0.0 0.0 0.147132 -0.348936 0.014869\natom 1.58126 1.25395 11.45380 Cu 0.0 0.0 -0.218414 0.011996 -0.005813\natom 5.16721 7.40454 6.92521 Cu 0.0 0.0 0.135180 0.102873 0.100528\natom 7.80512 10.10942 0.79887 Cu 0.0 0.0 0.218414 -0.011996 0.005813\natom 4.21917 3.95883 5.32746 Cu 0.0 0.0 -0.135180 -0.102873 -0.100528\natom 3.98302 1.22622 5.37647 Cu 0.0 0.0 -0.180907 0.079864 -0.074558\natom 8.13511 7.38112 0.74986 Cu 0.0 0.0 0.120530 0.056337 0.327773\natom 5.40336 10.13715 6.87620 Cu 0.0 0.0 0.180907 -0.079864 0.074558\natom 1.25127 3.98225 11.50281 Cu 0.0 0.0 -0.120530 -0.056337 -0.327773\natom -0.75333 2.34673 10.42335 Cu 0.0 0.0 0.231571 0.054027 -0.067373\natom 7.46580 8.40662 7.95566 Cu 0.0 0.0 -0.250224 -0.027637 0.041940\natom 10.13971 9.01664 1.82932 Cu 0.0 0.0 -0.231571 -0.054027 0.067373\natom 1.92058 2.95675 4.29701 Cu 0.0 0.0 0.250224 0.027637 -0.041940\natom 8.60494 0.05783 8.36857 Cu 0.0 0.0 0.097514 0.185659 -0.051704\natom -1.81069 5.93687 10.01043 Cu 0.0 0.0 -0.113167 0.016992 -0.194435\natom 0.78144 11.30554 3.88410 Cu 0.0 0.0 -0.097514 -0.185659 0.051704\natom 11.19707 5.42650 2.24224 Cu 0.0 0.0 0.113167 -0.016992 0.194435\natom 10.79785 0.65262 2.04742 Cu 0.0 0.0 0.058727 -0.050214 0.056952\natom 1.34503 6.51451 4.07891 Cu 0.0 0.0 -0.020408 0.069255 -0.084326\natom -1.41147 10.71075 10.20525 Cu 0.0 0.0 -0.058727 0.050214 -0.056952\natom 8.04135 4.84886 8.17376 Cu 0.0 0.0 0.020408 -0.069255 0.084326\natom -3.79024 2.01770 9.46151 Cu 0.0 0.0 0.017910 0.005585 0.148376\natom 10.51547 7.99293 8.91749 Cu 0.0 0.0 0.077022 -0.067263 -0.225985\natom 13.17662 9.34567 2.79116 Cu 0.0 0.0 -0.017910 -0.005585 -0.148376\natom -1.12909 3.37044 3.33518 Cu 0.0 0.0 -0.077022 0.067263 0.225985\natom 5.97894 0.79344 3.47241 Cu 0.0 0.0 -0.054540 -0.118376 0.021346\natom 6.15694 6.78075 2.65393 Cu 0.0 0.0 0.026096 0.155776 -0.055588\natom 3.40744 10.56993 8.78026 Cu 0.0 0.0 0.054540 0.118376 -0.021346\natom 3.22944 4.58262 9.59874 Cu 0.0 0.0 -0.026096 -0.155776 0.055588\natom 1.17017 0.18064 7.63341 Cu 0.0 0.0 -0.041255 -0.025574 0.040131\natom 5.62097 5.99497 10.74559 Cu 0.0 0.0 0.181745 -0.167594 0.133492\natom 8.21621 11.18273 4.61926 Cu 0.0 0.0 0.041255 0.025574 -0.040131\natom 3.76541 5.36840 1.50708 Cu 0.0 0.0 -0.181745 0.167594 -0.133492\natom 3.83343 0.44080 1.64063 Cu 0.0 0.0 0.055174 0.061652 0.081492\natom 8.31735 6.26689 4.48570 Cu 0.0 0.0 -0.119055 -0.147727 0.130719\natom 5.55295 10.92257 10.61204 Cu 0.0 0.0 -0.055174 -0.061652 -0.081492\natom 1.06903 5.09648 7.76697 Cu 0.0 0.0 0.119055 0.147727 -0.130719\natom 3.75325 2.07139 9.24219 Cu 0.0 0.0 0.004951 0.051264 -0.108557\natom 2.97048 8.02732 9.13682 Cu 0.0 0.0 0.047308 -0.106372 0.177691\natom 5.63313 9.29198 3.01048 Cu 0.0 0.0 -0.004951 -0.051264 0.108557\natom 6.41590 3.33605 3.11585 Cu 0.0 0.0 -0.047308 0.106372 -0.177691\natom 13.76009 0.90207 2.65393 Cu 0.0 0.0 0.164358 0.069182 -0.072740\natom -1.62670 6.81734 3.47241 Cu 0.0 0.0 -0.186261 0.110950 0.022082\natom -4.37371 10.46130 9.59874 Cu 0.0 0.0 -0.164358 -0.069182 0.072740\natom 11.01308 4.54603 8.78026 Cu 0.0 0.0 0.186261 -0.110950 -0.022082\natom 4.18037 0.71442 11.67802 Cu 0.0 0.0 -0.101489 0.356380 0.065025\natom 2.58630 6.88474 6.70099 Cu 0.0 0.0 0.038586 -0.101317 -0.007189\natom 5.20600 10.64895 0.57465 Cu 0.0 0.0 0.101489 -0.356380 -0.065025\natom 6.80008 4.47863 5.55168 Cu 0.0 0.0 -0.038586 0.101317 0.007189\natom 7.44791 2.00872 6.93379 Cu 0.0 0.0 -0.017349 0.022575 -0.119170\natom -0.71854 7.76147 11.44522 Cu 0.0 0.0 0.216815 0.155755 0.027007\natom 1.93847 9.35465 5.31888 Cu 0.0 0.0 0.017349 -0.022575 0.119170\natom 10.10492 3.60190 0.80745 Cu 0.0 0.0 -0.216815 -0.155755 -0.027007\natom 2.24037 2.38726 1.71292 Cu 0.0 0.0 0.140503 -0.084826 0.143313\natom 9.84340 8.21971 4.41341 Cu 0.0 0.0 -0.042281 0.040389 -0.144535\natom 7.14601 8.97611 10.53975 Cu 0.0 0.0 -0.140503 0.084826 -0.143313\natom -0.45702 3.14366 7.83926 Cu 0.0 0.0 0.042281 -0.040389 0.144535\natom -1.70389 0.78361 8.32079 Cu 0.0 0.0 0.107295 0.134898 0.054363\natom 8.47326 6.65844 10.05822 Cu 0.0 0.0 -0.069924 -0.198432 0.008684\natom 11.09027 10.57976 3.93188 Cu 0.0 0.0 -0.107295 -0.134898 -0.054363\natom 0.91312 4.70493 2.19445 Cu 0.0 0.0 0.069924 0.198432 -0.008684\nenergy -572.328657\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_0_1\nlattice 15.246000000 0.000000000 0.000000000\nlattice 0.000000000 11.884000000 0.000000000\nlattice -5.989357159 0.000000000 12.091965796\natom 9.55381 0.98518 10.18385 S 0.0 0.0 -0.125331 0.028415 0.031193\natom -3.29184 6.92718 7.95410 S 0.0 0.0 0.125331 0.028415 -0.031193\natom -0.29717 10.89882 1.90811 S 0.0 0.0 0.125331 -0.028415 -0.031193\natom 12.54849 4.95682 4.13787 S 0.0 0.0 -0.125331 -0.028415 0.031193\natom 12.27754 0.91269 4.18624 S 0.0 0.0 -0.126394 -0.041931 0.027223\natom -0.02622 6.85469 1.85974 S 0.0 0.0 0.126394 -0.041931 -0.027223\natom -3.02090 10.97131 7.90573 S 0.0 0.0 0.126394 0.041931 -0.027223\natom 9.28287 5.02931 10.23222 S 0.0 0.0 -0.126394 0.041931 0.027223\natom 9.06992 0.97924 6.12821 S 0.0 0.0 -0.013446 -0.068418 -0.051411\natom -2.80795 6.92124 12.00974 S 0.0 0.0 0.013446 -0.068418 0.051411\natom 0.18673 10.90476 5.96376 S 0.0 0.0 0.013446 0.068418 0.051411\natom 12.06460 4.96276 0.08223 S 0.0 0.0 -0.013446 0.068418 -0.051411\natom 12.03432 0.97092 0.07255 S 0.0 0.0 0.063364 0.002358 -0.040486\natom 0.21700 6.91292 5.97343 S 0.0 0.0 -0.063364 0.002358 0.040486\natom -2.77768 10.91308 12.01941 S 0.0 0.0 -0.063364 -0.002358 0.040486\natom 9.03964 4.97108 6.11853 S 0.0 0.0 0.063364 -0.002358 -0.040486\natom 3.17371 1.04936 7.41600 S 0.0 0.0 -0.099435 -0.033364 0.051184\natom 3.08826 6.99136 10.72195 S 0.0 0.0 0.099435 -0.033364 -0.051184\natom 6.08294 10.83464 4.67596 S 0.0 0.0 0.099435 0.033364 -0.051184\natom 6.16838 4.89264 1.37002 S 0.0 0.0 -0.099435 0.033364 0.051184\natom 6.20214 0.86278 1.15720 S 0.0 0.0 0.136972 -0.061507 -0.119929\natom 6.04918 6.80478 4.88878 S 0.0 0.0 -0.136972 -0.061507 0.119929\natom 3.05450 11.02122 10.93476 S 0.0 0.0 -0.136972 0.061507 0.119929\natom 3.20746 5.07922 7.20318 S 0.0 0.0 0.136972 0.061507 -0.119929\natom -0.14015 0.92814 9.51396 S 0.0 0.0 0.207624 -0.187454 0.034062\natom 6.40212 6.87014 8.62399 S 0.0 0.0 -0.207624 -0.187454 -0.034062\natom 9.39679 10.95586 2.57801 S 0.0 0.0 -0.207624 0.187454 -0.034062\natom 2.85453 5.01386 3.46798 S 0.0 0.0 0.207624 0.187454 0.034062\natom 2.61609 0.98875 3.46918 S 0.0 0.0 -0.379594 -0.045519 -0.051010\natom 9.63523 6.93075 2.57680 S 0.0 0.0 0.379594 -0.045519 0.051010\natom 6.64055 10.89525 8.62278 S 0.0 0.0 0.379594 0.045519 0.051010\natom -0.37859 4.95325 9.51517 S 0.0 0.0 -0.379594 0.045519 -0.051010\natom 6.28690 2.94842 8.73040 S 0.0 0.0 -0.101684 -0.045832 0.134656\natom -0.02494 8.89042 9.40755 S 0.0 0.0 0.101684 -0.045832 -0.134656\natom 2.96974 8.93558 3.36157 S 0.0 0.0 0.101684 0.045832 -0.134656\natom 9.28158 2.99358 2.68442 S 0.0 0.0 -0.101684 0.045832 0.134656\natom 5.85752 2.65845 5.03872 S 0.0 0.0 -0.067582 -0.177681 0.103192\natom 6.39380 8.60045 1.00726 S 0.0 0.0 0.067582 -0.177681 -0.103192\natom 3.39912 9.22555 7.05324 S 0.0 0.0 0.067582 0.177681 -0.103192\natom 2.86284 3.28355 11.08471 S 0.0 0.0 -0.067582 0.177681 0.103192\natom 0.14893 2.83315 5.76303 S 0.0 0.0 -0.063213 -0.002445 -0.183871\natom 12.10239 8.77515 0.28295 S 0.0 0.0 0.063213 -0.002445 0.183871\natom 9.10771 9.05085 6.32893 S 0.0 0.0 0.063213 0.002445 0.183871\natom -2.84574 3.10885 11.80901 S 0.0 0.0 -0.063213 0.002445 -0.183871\natom -0.06140 2.76184 1.61065 S 0.0 0.0 0.033374 -0.217794 -0.226789\natom 12.31272 8.70384 4.43533 S 0.0 0.0 -0.033374 -0.217794 0.226789\natom 9.31804 9.12216 10.48132 S 0.0 0.0 -0.033374 0.217794 0.226789\natom -3.05608 3.18016 7.65663 S 0.0 0.0 0.033374 0.217794 -0.226789\natom 11.42708 2.96625 3.53932 Cu 0.0 0.0 -0.056517 -0.018383 -0.066026\natom 0.82424 8.90825 2.50666 Cu 0.0 0.0 0.056517 -0.018383 0.066026\natom -2.17044 8.91775 8.55265 Cu 0.0 0.0 0.056517 0.018383 0.066026\natom 8.43240 2.97575 9.58530 Cu 0.0 0.0 -0.056517 0.018383 -0.066026\natom 5.35651 0.87942 8.18021 Cu 0.0 0.0 -0.068978 -0.042620 0.067357\natom 0.90546 6.82142 9.95773 Cu 0.0 0.0 0.068978 -0.042620 -0.067357\natom 3.90014 11.00458 3.91175 Cu 0.0 0.0 0.068978 0.042620 -0.067357\natom 8.35119 5.06258 2.13423 Cu 0.0 0.0 -0.068978 0.042620 0.067357\natom 8.29869 1.08857 2.02782 Cu 0.0 0.0 -0.013003 -0.079744 -0.061412\natom 3.95263 7.03057 4.01816 Cu 0.0 0.0 0.013003 -0.079744 0.061412\natom 0.95795 10.79543 10.06414 Cu 0.0 0.0 0.013003 0.079744 0.061412\natom 5.30402 4.85343 8.07381 Cu 0.0 0.0 -0.013003 0.079744 -0.061412\natom 5.09343 2.85216 0.88392 Cu 0.0 0.0 -0.071088 -0.013473 -0.002685\natom 7.15789 8.79416 5.16206 Cu 0.0 0.0 0.071088 -0.013473 0.002685\natom 4.16322 9.03184 11.20804 Cu 0.0 0.0 0.071088 0.013473 0.002685\natom 2.09875 3.08984 6.92991 Cu 0.0 0.0 -0.071088 0.013473 -0.002685\natom -3.71515 1.00895 11.42812 Cu 0.0 0.0 0.067641 0.039805 0.039650\natom 9.97712 6.95095 6.70983 Cu 0.0 0.0 -0.067641 0.039805 -0.039650\natom 12.97179 10.87505 0.66385 Cu 0.0 0.0 -0.067641 -0.039805 -0.039650\natom -0.72047 4.93305 5.38213 Cu 0.0 0.0 0.067641 -0.039805 0.039650\natom -1.02899 0.93052 5.35553 Cu 0.0 0.0 0.007293 -0.021110 -0.015108\natom 13.28031 6.87252 0.69045 Cu 0.0 0.0 -0.007293 -0.021110 0.015108\natom 10.28563 10.95348 6.73643 Cu 0.0 0.0 -0.007293 0.021110 0.015108\natom -4.02367 5.01148 11.40151 Cu 0.0 0.0 0.007293 0.021110 -0.015108\natom 8.30415 1.46530 11.99886 Cu 0.0 0.0 -0.140674 0.136237 -0.040072\natom -2.04218 7.40730 6.13909 Cu 0.0 0.0 0.140674 0.136237 0.040072\natom 0.95249 10.41870 0.09311 Cu 0.0 0.0 0.140674 -0.136237 0.040072\natom 11.29883 4.47670 5.95287 Cu 0.0 0.0 -0.140674 -0.136237 -0.040072\natom 11.29861 1.67802 6.16569 Cu 0.0 0.0 0.015271 0.116590 -0.074616\natom -5.03665 7.62002 11.97226 Cu 0.0 0.0 -0.015271 0.116590 0.074616\natom -2.04197 10.20598 5.92627 Cu 0.0 0.0 -0.015271 -0.116590 0.074616\natom 14.29329 4.26398 0.11971 Cu 0.0 0.0 0.015271 -0.116590 -0.074616\natom 9.14880 2.97575 4.96859 Cu 0.0 0.0 0.164959 0.084500 0.087098\natom 3.10252 8.91775 1.07739 Cu 0.0 0.0 -0.164959 0.084500 -0.087098\natom 0.10784 8.90825 7.12338 Cu 0.0 0.0 -0.164959 -0.084500 -0.087098\natom 6.15412 2.96625 11.01457 Cu 0.0 0.0 0.164959 -0.084500 0.087098\natom 1.15360 1.75527 11.30357 Cu 0.0 0.0 -0.063629 0.156987 0.058610\natom 5.10836 7.69727 6.83438 Cu 0.0 0.0 0.063629 0.156987 -0.058610\natom 8.10304 10.12873 0.78840 Cu 0.0 0.0 0.063629 -0.156987 -0.058610\natom 4.14828 4.18673 5.25759 Cu 0.0 0.0 -0.063629 -0.156987 0.058610\natom 3.85752 1.46054 5.30595 Cu 0.0 0.0 0.025586 0.159786 -0.058692\natom 8.39380 7.40254 0.74003 Cu 0.0 0.0 -0.025586 0.159786 0.058692\natom 5.39912 10.42346 6.78601 Cu 0.0 0.0 -0.025586 -0.159786 0.058692\natom 0.86284 4.48146 11.35194 Cu 0.0 0.0 0.025586 -0.159786 -0.058692\natom -1.16473 2.80106 10.28664 Cu 0.0 0.0 0.114949 0.029868 0.062123\natom 7.42669 8.74306 7.85131 Cu 0.0 0.0 -0.114949 0.029868 -0.062123\natom 10.42137 9.08294 1.80533 Cu 0.0 0.0 -0.114949 -0.029868 -0.062123\natom 1.82995 3.14094 4.24065 Cu 0.0 0.0 0.114949 -0.029868 0.062123\natom 8.42471 0.42545 8.25881 Cu 0.0 0.0 -0.006801 -0.023883 -0.023161\natom -2.16275 6.36745 9.87914 Cu 0.0 0.0 0.006801 -0.023883 0.023161\natom 0.83193 11.45855 3.83315 Cu 0.0 0.0 0.006801 0.023883 0.023161\natom 11.41939 5.51655 2.21283 Cu 0.0 0.0 -0.006801 0.023883 -0.023161\natom 10.93680 0.74156 2.02057 Cu 0.0 0.0 -0.002607 0.001704 -0.015858\natom 1.31453 6.68356 4.02542 Cu 0.0 0.0 0.002607 0.001704 0.015858\natom -1.68015 11.14244 10.07140 Cu 0.0 0.0 0.002607 -0.001704 0.015858\natom 7.94212 5.20044 8.06655 Cu 0.0 0.0 -0.002607 -0.001704 -0.015858\natom -4.22706 2.43028 9.33742 Cu 0.0 0.0 -0.057628 -0.032284 0.078709\natom 10.48903 8.37228 8.80053 Cu 0.0 0.0 0.057628 -0.032284 -0.078709\natom 13.48370 9.45372 2.75455 Cu 0.0 0.0 0.057628 0.032284 -0.078709\natom -1.23238 3.51172 3.29143 Cu 0.0 0.0 -0.057628 0.032284 0.078709\natom 5.96526 0.94478 3.42686 Cu 0.0 0.0 -0.017114 0.034111 0.052038\natom 6.28607 6.88678 2.61912 Cu 0.0 0.0 0.017114 0.034111 -0.052038\natom 3.29139 10.93922 8.66510 Cu 0.0 0.0 0.017114 -0.034111 -0.052038\natom 2.97058 4.99722 9.47285 Cu 0.0 0.0 -0.017114 -0.034111 0.052038\natom 0.87597 0.51577 7.53329 Cu 0.0 0.0 -0.012110 -0.004506 0.081390\natom 5.38599 6.45777 10.60465 Cu 0.0 0.0 0.012110 -0.004506 -0.081390\natom 8.38067 11.36823 4.55867 Cu 0.0 0.0 0.012110 0.004506 -0.081390\natom 3.87065 5.42623 1.48731 Cu 0.0 0.0 -0.012110 0.004506 0.081390\natom 3.84806 0.51220 1.61911 Cu 0.0 0.0 0.106207 0.025692 0.047083\natom 8.40327 6.45420 4.42687 Cu 0.0 0.0 -0.106207 0.025692 -0.047083\natom 5.40859 11.37180 10.47285 Cu 0.0 0.0 -0.106207 -0.025692 -0.047083\natom 0.85338 5.42980 7.66510 Cu 0.0 0.0 0.106207 -0.025692 0.047083\natom 3.47571 2.47425 9.12097 Cu 0.0 0.0 0.013369 -0.021692 -0.063355\natom 2.78626 8.41625 9.01698 Cu 0.0 0.0 -0.013369 -0.021692 0.063355\natom 5.78094 9.40975 2.97100 Cu 0.0 0.0 -0.013369 0.021692 0.063355\natom 6.47038 3.46775 3.07499 Cu 0.0 0.0 0.013369 0.021692 -0.063355\natom 13.93651 1.01727 2.61912 Cu 0.0 0.0 0.070095 0.058281 0.058871\natom -1.68519 6.95927 3.42686 Cu 0.0 0.0 -0.070095 0.058281 -0.058871\natom -4.67987 10.86673 9.47285 Cu 0.0 0.0 -0.070095 -0.058281 -0.058871\natom 10.94183 4.92473 8.66510 Cu 0.0 0.0 0.070095 -0.058281 0.058871\natom 3.78523 1.22643 11.52485 Cu 0.0 0.0 -0.055512 0.072701 0.045980\natom 2.47674 7.16843 6.61310 Cu 0.0 0.0 0.055512 0.072701 -0.045980\natom 5.47141 10.65757 0.56711 Cu 0.0 0.0 0.055512 -0.072701 -0.045980\natom 6.77991 4.71557 5.47887 Cu 0.0 0.0 -0.055512 -0.072701 0.045980\natom 7.33923 2.31025 6.84284 Cu 0.0 0.0 0.008001 0.031273 -0.008244\natom -1.07727 8.25225 11.29511 Cu 0.0 0.0 -0.008001 0.031273 0.008244\natom 1.91741 9.57375 5.24912 Cu 0.0 0.0 -0.008001 -0.031273 0.008244\natom 10.33391 3.63175 0.79686 Cu 0.0 0.0 0.008001 -0.031273 -0.008244\natom 2.25458 2.45880 1.69046 Cu 0.0 0.0 0.009284 0.010061 0.048810\natom 9.99674 8.40080 4.35553 Cu 0.0 0.0 -0.009284 0.010061 -0.048810\natom 7.00207 9.42520 10.40151 Cu 0.0 0.0 -0.009284 -0.010061 -0.048810\natom -0.74010 3.48320 7.73644 Cu 0.0 0.0 0.009284 -0.010061 0.048810\natom -2.07320 1.14799 8.21165 Cu 0.0 0.0 0.008891 0.031001 0.014345\natom 8.33516 7.08999 9.92629 Cu 0.0 0.0 -0.008891 0.031001 -0.014345\natom 11.32984 10.73601 3.88031 Cu 0.0 0.0 -0.008891 -0.031001 -0.014345\natom 0.92148 4.79401 2.16567 Cu 0.0 0.0 0.008891 -0.031001 0.014345\nenergy -573.700369\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/nnp-scaling/Cu2S_PBE/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.9272369024305549E+00\nconv_energy   1.7758427376631172E+02\nconv_length   7.6802317981086702E+01\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     2 0.0          # Cutoff type (optional argument: shift parameter alpha).\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              15 15          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n"
  },
  {
    "path": "examples/nnp-scaling/H2O_RPBE-D3/input.data",
    "content": " begin\ncomment written by RuNNerDecom\nlattice      24.623508      0.000000      0.000000\nlattice       0.000000     24.623508      0.000000\nlattice       0.000000      0.000000     24.623508\natom     3.735290838    2.327841157    3.501304856   O   -0.226389360    0.000000000   -0.006530137   -0.002852459   -0.027992554\natom     5.246524320    3.393061301    3.627368536   H    0.120793430    0.000000000    0.004517488   -0.000517262    0.005052573\natom     3.558676964    2.038939712    1.628158442   H    0.127225380    0.000000000    0.000095815    0.002211264    0.023427576\natom     4.652261909   21.146799653   16.174455806   O   -0.240350190    0.000000000   -0.000231046   -0.007150914    0.026944723\natom     4.197045601   22.522898765   15.074691455   H    0.132518870    0.000000000   -0.001535223    0.002790532   -0.018391035\natom     5.012047009   19.588530870   15.274057640   H    0.135733700    0.000000000    0.002788938    0.006272370   -0.006171035\natom    16.857157435    3.327223216    5.017451628   O   -0.214010320    0.000000000    0.010171588    0.016012738    0.035099119\natom    16.307700448    2.330278905    3.636288047   H    0.108559530    0.000000000   -0.008301162   -0.024899500   -0.030394951\natom    17.367119130    2.071367425    6.332134617   H    0.121384900    0.000000000   -0.006697761    0.007081892   -0.003219491\natom    18.117794235   -0.374704494   19.251970513   O   -0.253642250    0.000000000   -0.024405004   -0.012754375    0.012242947\natom    16.521636428    0.337611045   19.927736844   H    0.120809200    0.000000000    0.002220741   -0.011811043   -0.009670033\natom    19.148602452    1.088431659   19.427148194   H    0.114155690    0.000000000    0.021230736    0.022132545   -0.006007141\natom    17.757139861    0.050971603    9.130347691   O   -0.215317630    0.000000000   -0.005434943   -0.001827901    0.005465729\natom    16.259474618   23.846841416    9.848217137   H    0.133741170    0.000000000   -0.001711391    0.010244935   -0.002774444\natom    18.540979672   23.231546345    8.347755099   H    0.146150570    0.000000000    0.014635404   -0.006670669   -0.004527888\natom    12.013315016    3.780360824   -0.071301285   O   -0.253689050    0.000000000    0.005359628    0.024749295   -0.005332222\natom    13.294852195    5.203022807   -0.128943624   H    0.114078030    0.000000000   -0.012906774   -0.026389114   -0.001326269\natom    12.919722513    2.259754298    0.424517694   H    0.116540600    0.000000000    0.006743413    0.003879913   -0.000468813\natom    12.529890755    5.212376955   15.827331876   O   -0.253986350    0.000000000   -0.000119721    0.008266330    0.006530251\natom    12.425917982    4.306290712   14.234424399   H    0.112634320    0.000000000    0.000140603   -0.011164836   -0.001375189\natom    12.764916087    3.876925868   17.158077543   H    0.100753240    0.000000000   -0.002300020   -0.000231651   -0.007826174\natom    20.033183604   16.544426534   23.913170829   O   -0.260620870    0.000000000    0.006524698   -0.028540501   -0.005264426\natom    21.355047555   15.177379213   23.397275392   H    0.111928170    0.000000000   -0.031707302    0.026134828    0.007143786\natom    18.354350246   15.846210247   23.385937031   H    0.123277260    0.000000000    0.019731649    0.005955325    0.004549934\natom    12.144518753   18.052825425   18.706274082   O   -0.210341170    0.000000000   -0.014866699   -0.011665448    0.026560721\natom    13.507181907   18.024574008   17.526007366   H    0.124395570    0.000000000    0.020090667    0.001476881   -0.008312401\natom    12.731845866   16.994559476   20.149212834   H    0.144891080    0.000000000   -0.003199444    0.006143511   -0.016646283\natom    16.912564227   19.121579358   16.214744783   O   -0.214062700    0.000000000   -0.002538630    0.026152342    0.005346098\natom    17.405216024   20.866931102   16.692259868   H    0.148034420    0.000000000   -0.013977441   -0.005713738   -0.002595361\natom    18.524312281   18.360227296   16.480704944   H    0.131237310    0.000000000    0.020632529   -0.022303425    0.004792410\natom    20.116898505    4.922757414   19.585318334   O   -0.241188010    0.000000000    0.001047194   -0.008189572    0.009275614\natom    18.468829900    5.729349537   19.695867356   H    0.141751490    0.000000000    0.004325710    0.000224611    0.005073355\natom    20.829892456    4.864629415   21.353157828   H    0.110757650    0.000000000   -0.004199404    0.009172873   -0.016789747\natom    12.029245413   15.603096884    8.902182068   O   -0.266938200    0.000000000    0.054595746   -0.006876686    0.018733486\natom    10.441270123   16.269792527    8.454656948   H    0.098486210    0.000000000   -0.033110457    0.019565416    0.002657365\natom    13.112417962   16.912299665    9.851505262   H    0.107149850    0.000000000   -0.019172455   -0.019589210   -0.019407954\natom     9.762518023    8.972177551   12.034574443   O   -0.277540080    0.000000000   -0.003205114   -0.012410450    0.017574029\natom     8.196841510    9.866755358   12.482137357   H    0.103740730    0.000000000   -0.000635995    0.000182125   -0.003014649\natom     9.748855298    7.559606710   13.275898234   H    0.119507420    0.000000000    0.002112794    0.016284777   -0.013554342\natom    11.224958757    2.122597921   11.606607997   O   -0.245529630    0.000000000   -0.010907413   -0.009461731    0.001847302\natom     9.592102453    2.288799400   12.466811672   H    0.151624050    0.000000000    0.004846576   -0.002799857   -0.008505057\natom    11.227075251    0.382450484   10.750977461   H    0.105991310    0.000000000    0.002003860    0.024044803    0.003860573\natom    15.773417968    0.020397712    1.108963541   O   -0.249425870    0.000000000   -0.020986710   -0.004981242    0.011220213\natom    14.434659859   23.547130733    1.988578491   H    0.107892190    0.000000000    0.024960938    0.000684236   -0.009393969\natom    17.204224673   23.582846571    0.577874700   H    0.113413590    0.000000000   -0.004731034   -0.002010091    0.004887777\natom     7.837283177   14.849360422    1.930431595   O   -0.246274950    0.000000000   -0.005588957   -0.014293836   -0.001271832\natom     7.496244168   13.061338645    2.271583988   H    0.122890240    0.000000000   -0.004555401    0.000409162   -0.009761648\natom     8.769712213   15.169158901    3.445595708   H    0.143023810    0.000000000    0.010803411    0.013941557    0.011111768\natom     2.743222022   10.053328092   23.736292394   O   -0.252549480    0.000000000    0.007322459    0.011795230    0.001219162\natom     3.497657684   10.068559291   22.018719634   H    0.125243770    0.000000000   -0.011934368   -0.008624966    0.006794256\natom     1.922286872    8.434682535   24.040727394   H    0.129167780    0.000000000    0.001734579   -0.001652283   -0.011524410\natom     3.161626450    0.226583922   11.717345992   O   -0.285699660    0.000000000    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  },
  {
    "path": "examples/nnp-scaling/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.3353824022135491E-01\nconv_energy   8.5167544626563699E+02\nconv_length   2.2798325235535355E+01\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\natom_energy                     H -0.45890771  # Free atom reference energy (H).\natom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-scaling/LJ/input.data",
    "content": "begin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.38564065E+01  -1.38564065E+01  -1.38564065E+01\natom   5.77350269E-01   5.77350269E-01   5.77350269E-01 Ne   0.00000000E+00   0.00000000E+00   1.38564065E+01   1.38564065E+01   1.38564065E+01\nenergy   0.00000000E+00\ncomment r =   1.00000000E+00, E =   0.00000000E+00, dEdr =  -2.40000000E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.14260918E+01  -1.14260918E+01  -1.14260918E+01\natom   5.83123772E-01   5.83123772E-01   5.83123772E-01 Ne   0.00000000E+00   0.00000000E+00   1.14260918E+01   1.14260918E+01   1.14260918E+01\nenergy  -2.18384040E-01\ncomment r =   1.01000000E+00, E =  -2.18384040E-01, dEdr =  -1.97905715E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -9.36007007E+00  -9.36007007E+00  -9.36007007E+00\natom   5.88897275E-01   5.88897275E-01   5.88897275E-01 Ne   0.00000000E+00   0.00000000E+00   9.36007007E+00   9.36007007E+00   9.36007007E+00\nenergy  -3.97912826E-01\ncomment r =   1.02000000E+00, E =  -3.97912826E-01, dEdr =  -1.62121169E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -7.60455062E+00  -7.60455062E+00  -7.60455062E+00\natom   5.94670777E-01   5.94670777E-01   5.94670777E-01 Ne   0.00000000E+00   0.00000000E+00   7.60455062E+00   7.60455062E+00   7.60455062E+00\nenergy  -5.44417506E-01\ncomment r =   1.03000000E+00, E =  -5.44417506E-01, dEdr =  -1.31714680E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -6.11386720E+00  -6.11386720E+00  -6.11386720E+00\natom   6.00444280E-01   6.00444280E-01   6.00444280E-01 Ne   0.00000000E+00   0.00000000E+00   6.11386720E+00   6.11386720E+00   6.11386720E+00\nenergy  -6.62869905E-01\ncomment r =   1.04000000E+00, E =  -6.62869905E-01, dEdr =  -1.05895286E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -4.84920700E+00  -4.84920700E+00  -4.84920700E+00\natom   6.06217783E-01   6.06217783E-01   6.06217783E-01 Ne   0.00000000E+00   0.00000000E+00   4.84920700E+00   4.84920700E+00   4.84920700E+00\nenergy  -7.57511914E-01\ncomment r =   1.05000000E+00, E =  -7.57511914E-01, dEdr =  -8.39907291E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -3.77754643E+00  -3.77754643E+00  -3.77754643E+00\natom   6.11991285E-01   6.11991285E-01   6.11991285E-01 Ne   0.00000000E+00   0.00000000E+00   3.77754643E+00   3.77754643E+00   3.77754643E+00\nenergy  -8.31964707E-01\ncomment r =   1.06000000E+00, E =  -8.31964707E-01, dEdr =  -6.54290234E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -2.87075857E+00  -2.87075857E+00  -2.87075857E+00\natom   6.17764788E-01   6.17764788E-01   6.17764788E-01 Ne   0.00000000E+00   0.00000000E+00   2.87075857E+00   2.87075857E+00   2.87075857E+00\nenergy  -8.89321058E-01\ncomment r =   1.07000000E+00, E =  -8.89321058E-01, dEdr =  -4.97229969E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -2.10486372E+00  -2.10486372E+00  -2.10486372E+00\natom   6.23538291E-01   6.23538291E-01   6.23538291E-01 Ne   0.00000000E+00   0.00000000E+00   2.10486372E+00   2.10486372E+00   2.10486372E+00\nenergy  -9.32223473E-01\ncomment r =   1.08000000E+00, E =  -9.32223473E-01, dEdr =  -3.64573090E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.45939898E+00  -1.45939898E+00  -1.45939898E+00\natom   6.29311793E-01   6.29311793E-01   6.29311793E-01 Ne   0.00000000E+00   0.00000000E+00   1.45939898E+00   1.45939898E+00   1.45939898E+00\nenergy  -9.62930407E-01\ncomment r =   1.09000000E+00, E =  -9.62930407E-01, dEdr =  -2.52775317E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -9.16887301E-01  -9.16887301E-01  -9.16887301E-01\natom   6.35085296E-01   6.35085296E-01   6.35085296E-01 Ne   0.00000000E+00   0.00000000E+00   9.16887301E-01   9.16887301E-01   9.16887301E-01\nenergy  -9.83372449E-01\ncomment r =   1.10000000E+00, E =  -9.83372449E-01, dEdr =  -1.58809539E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -4.62389671E-01  -4.62389671E-01  -4.62389671E-01\natom   6.40858799E-01   6.40858799E-01   6.40858799E-01 Ne   0.00000000E+00   0.00000000E+00   4.62389671E-01   4.62389671E-01   4.62389671E-01\nenergy  -9.95200050E-01\ncomment r =   1.11000000E+00, E =  -9.95200050E-01, dEdr =  -8.00882403E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -8.31268676E-02  -8.31268676E-02  -8.31268676E-02\natom   6.46632301E-01   6.46632301E-01   6.46632301E-01 Ne   0.00000000E+00   0.00000000E+00   8.31268676E-02   8.31268676E-02   8.31268676E-02\nenergy  -9.99824113E-01\ncomment r =   1.12000000E+00, E =  -9.99824113E-01, dEdr =  -1.43979958E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.31840388E-01   2.31840388E-01   2.31840388E-01\natom   6.52405804E-01   6.52405804E-01   6.52405804E-01 Ne   0.00000000E+00   0.00000000E+00  -2.31840388E-01  -2.31840388E-01  -2.31840388E-01\nenergy  -9.98450559E-01\ncomment r =   1.13000000E+00, E =  -9.98450559E-01, dEdr =   4.01559331E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.91882287E-01   4.91882287E-01   4.91882287E-01\natom   6.58179307E-01   6.58179307E-01   6.58179307E-01 Ne   0.00000000E+00   0.00000000E+00  -4.91882287E-01  -4.91882287E-01  -4.91882287E-01\nenergy  -9.92109781E-01\ncomment r =   1.14000000E+00, E =  -9.92109781E-01, dEdr =   8.51965112E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.05029571E-01   7.05029571E-01   7.05029571E-01\natom   6.63952810E-01   6.63952810E-01   6.63952810E-01 Ne   0.00000000E+00   0.00000000E+00  -7.05029571E-01  -7.05029571E-01  -7.05029571E-01\nenergy  -9.81681783E-01\ncomment r =   1.15000000E+00, E =  -9.81681783E-01, dEdr =   1.22114704E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.78168464E-01   8.78168464E-01   8.78168464E-01\natom   6.69726312E-01   6.69726312E-01   6.69726312E-01 Ne   0.00000000E+00   0.00000000E+00  -8.78168464E-01  -8.78168464E-01  -8.78168464E-01\nenergy  -9.67917641E-01\ncomment r =   1.16000000E+00, E =  -9.67917641E-01, dEdr =   1.52103240E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.01720634E+00   1.01720634E+00   1.01720634E+00\natom   6.75499815E-01   6.75499815E-01   6.75499815E-01 Ne   0.00000000E+00   0.00000000E+00  -1.01720634E+00  -1.01720634E+00  -1.01720634E+00\nenergy  -9.51457857E-01\ncomment r =   1.17000000E+00, E =  -9.51457857E-01, dEdr =   1.76185306E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.12721266E+00   1.12721266E+00   1.12721266E+00\natom   6.81273318E-01   6.81273318E-01   6.81273318E-01 Ne   0.00000000E+00   0.00000000E+00  -1.12721266E+00  -1.12721266E+00  -1.12721266E+00\nenergy  -9.32848056E-01\ncomment r =   1.18000000E+00, E =  -9.32848056E-01, dEdr =   1.95238960E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.21253907E+00   1.21253907E+00   1.21253907E+00\natom   6.87046820E-01   6.87046820E-01   6.87046820E-01 Ne   0.00000000E+00   0.00000000E+00  -1.21253907E+00  -1.21253907E+00  -1.21253907E+00\nenergy  -9.12552436E-01\ncomment r =   1.19000000E+00, E =  -9.12552436E-01, dEdr =   2.10017928E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.27692175E+00   1.27692175E+00   1.27692175E+00\natom   6.92820323E-01   6.92820323E-01   6.92820323E-01 Ne   0.00000000E+00   0.00000000E+00  -1.27692175E+00  -1.27692175E+00  -1.27692175E+00\nenergy  -8.90965288E-01\ncomment r =   1.20000000E+00, E =  -8.90965288E-01, dEdr =   2.21169334E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.32356877E+00   1.32356877E+00   1.32356877E+00\natom   6.98593826E-01   6.98593826E-01   6.98593826E-01 Ne   0.00000000E+00   0.00000000E+00  -1.32356877E+00  -1.32356877E+00  -1.32356877E+00\nenergy  -8.68420879E-01\ncomment r =   1.21000000E+00, E =  -8.68420879E-01, dEdr =   2.29248836E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.35523484E+00   1.35523484E+00   1.35523484E+00\natom   7.04367328E-01   7.04367328E-01   7.04367328E-01 Ne   0.00000000E+00   0.00000000E+00  -1.35523484E+00  -1.35523484E+00  -1.35523484E+00\nenergy  -8.45201938E-01\ncomment r =   1.22000000E+00, E =  -8.45201938E-01, dEdr =   2.34733561E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.37428509E+00   1.37428509E+00   1.37428509E+00\natom   7.10140831E-01   7.10140831E-01   7.10140831E-01 Ne   0.00000000E+00   0.00000000E+00  -1.37428509E+00  -1.37428509E+00  -1.37428509E+00\nenergy  -8.21546940E-01\ncomment r =   1.23000000E+00, E =  -8.21546940E-01, dEdr =   2.38033160E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38274975E+00   1.38274975E+00   1.38274975E+00\natom   7.15914334E-01   7.15914334E-01   7.15914334E-01 Ne   0.00000000E+00   0.00000000E+00  -1.38274975E+00  -1.38274975E+00  -1.38274975E+00\nenergy  -7.97656367E-01\ncomment r =   1.24000000E+00, E =  -7.97656367E-01, dEdr =   2.39499283E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38237105E+00   1.38237105E+00   1.38237105E+00\natom   7.21687836E-01   7.21687836E-01   7.21687836E-01 Ne   0.00000000E+00   0.00000000E+00  -1.38237105E+00  -1.38237105E+00  -1.38237105E+00\nenergy  -7.73698093E-01\ncomment r =   1.25000000E+00, E =  -7.73698093E-01, dEdr =   2.39433689E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.37464330E+00   1.37464330E+00   1.37464330E+00\natom   7.27461339E-01   7.27461339E-01   7.27461339E-01 Ne   0.00000000E+00   0.00000000E+00  -1.37464330E+00  -1.37464330E+00  -1.37464330E+00\nenergy  -7.49812018E-01\ncomment r =   1.26000000E+00, E =  -7.49812018E-01, dEdr =   2.38095204E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.36084745E+00   1.36084745E+00   1.36084745E+00\natom   7.33234842E-01   7.33234842E-01   7.33234842E-01 Ne   0.00000000E+00   0.00000000E+00  -1.36084745E+00  -1.36084745E+00  -1.36084745E+00\nenergy  -7.26114051E-01\ncomment r =   1.27000000E+00, E =  -7.26114051E-01, dEdr =   2.35705692E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.34208064E+00   1.34208064E+00   1.34208064E+00\natom   7.39008345E-01   7.39008345E-01   7.39008345E-01 Ne   0.00000000E+00   0.00000000E+00  -1.34208064E+00  -1.34208064E+00  -1.34208064E+00\nenergy  -7.02699549E-01\ncomment r =   1.28000000E+00, E =  -7.02699549E-01, dEdr =   2.32455185E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.31928169E+00   1.31928169E+00   1.31928169E+00\natom   7.44781847E-01   7.44781847E-01   7.44781847E-01 Ne   0.00000000E+00   0.00000000E+00  -1.31928169E+00  -1.31928169E+00  -1.31928169E+00\nenergy  -6.79646267E-01\ncomment r =   1.29000000E+00, E =  -6.79646267E-01, dEdr =   2.28506292E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.29325302E+00   1.29325302E+00   1.29325302E+00\natom   7.50555350E-01   7.50555350E-01   7.50555350E-01 Ne   0.00000000E+00   0.00000000E+00  -1.29325302E+00  -1.29325302E+00  -1.29325302E+00\nenergy  -6.57016914E-01\ncomment r =   1.30000000E+00, E =  -6.57016914E-01, dEdr =   2.23997993E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.26467942E+00   1.26467942E+00   1.26467942E+00\natom   7.56328853E-01   7.56328853E-01   7.56328853E-01 Ne   0.00000000E+00   0.00000000E+00  -1.26467942E+00  -1.26467942E+00  -1.26467942E+00\nenergy  -6.34861342E-01\ncomment r =   1.31000000E+00, E =  -6.34861342E-01, dEdr =   2.19048901E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.23414440E+00   1.23414440E+00   1.23414440E+00\natom   7.62102355E-01   7.62102355E-01   7.62102355E-01 Ne   0.00000000E+00   0.00000000E+00  -1.23414440E+00  -1.23414440E+00  -1.23414440E+00\nenergy  -6.13218442E-01\ncomment r =   1.32000000E+00, E =  -6.13218442E-01, dEdr =   2.13760080E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.20214407E+00   1.20214407E+00   1.20214407E+00\natom   7.67875858E-01   7.67875858E-01   7.67875858E-01 Ne   0.00000000E+00   0.00000000E+00  -1.20214407E+00  -1.20214407E+00  -1.20214407E+00\nenergy  -5.92117772E-01\ncomment r =   1.33000000E+00, E =  -5.92117772E-01, dEdr =   2.08217461E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.16909931E+00   1.16909931E+00   1.16909931E+00\natom   7.73649361E-01   7.73649361E-01   7.73649361E-01 Ne   0.00000000E+00   0.00000000E+00  -1.16909931E+00  -1.16909931E+00  -1.16909931E+00\nenergy  -5.71580967E-01\ncomment r =   1.34000000E+00, E =  -5.71580967E-01, dEdr =   2.02493940E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.13536610E+00   1.13536610E+00   1.13536610E+00\natom   7.79422863E-01   7.79422863E-01   7.79422863E-01 Ne   0.00000000E+00   0.00000000E+00  -1.13536610E+00  -1.13536610E+00  -1.13536610E+00\nenergy  -5.51622948E-01\ncomment r =   1.35000000E+00, E =  -5.51622948E-01, dEdr =   1.96651177E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.10124456E+00   1.10124456E+00   1.10124456E+00\natom   7.85196366E-01   7.85196366E-01   7.85196366E-01 Ne   0.00000000E+00   0.00000000E+00  -1.10124456E+00  -1.10124456E+00  -1.10124456E+00\nenergy  -5.32252964E-01\ncomment r =   1.36000000E+00, E =  -5.32252964E-01, dEdr =   1.90741154E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.06698669E+00   1.06698669E+00   1.06698669E+00\natom   7.90969869E-01   7.90969869E-01   7.90969869E-01 Ne   0.00000000E+00   0.00000000E+00  -1.06698669E+00  -1.06698669E+00  -1.06698669E+00\nenergy  -5.13475496E-01\ncomment r =   1.37000000E+00, E =  -5.13475496E-01, dEdr =   1.84807516E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.03280308E+00   1.03280308E+00   1.03280308E+00\natom   7.96743371E-01   7.96743371E-01   7.96743371E-01 Ne   0.00000000E+00   0.00000000E+00  -1.03280308E+00  -1.03280308E+00  -1.03280308E+00\nenergy  -4.95291026E-01\ncomment r =   1.38000000E+00, E =  -4.95291026E-01, dEdr =   1.78886740E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.98868680E-01   9.98868680E-01   9.98868680E-01\natom   8.02516874E-01   8.02516874E-01   8.02516874E-01 Ne   0.00000000E+00   0.00000000E+00  -9.98868680E-01  -9.98868680E-01  -9.98868680E-01\nenergy  -4.77696704E-01\ncomment r =   1.39000000E+00, E =  -4.77696704E-01, dEdr =   1.73009130E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.65327860E-01   9.65327860E-01   9.65327860E-01\natom   8.08290377E-01   8.08290377E-01   8.08290377E-01 Ne   0.00000000E+00   0.00000000E+00  -9.65327860E-01  -9.65327860E-01  -9.65327860E-01\nenergy  -4.60686922E-01\ncomment r =   1.40000000E+00, E =  -4.60686922E-01, dEdr =   1.67199690E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.32298690E-01   9.32298690E-01   9.32298690E-01\natom   8.14063880E-01   8.14063880E-01   8.14063880E-01 Ne   0.00000000E+00   0.00000000E+00  -9.32298690E-01  -9.32298690E-01  -9.32298690E-01\nenergy  -4.44253807E-01\ncomment r =   1.41000000E+00, E =  -4.44253807E-01, dEdr =   1.61478870E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.99876705E-01   8.99876705E-01   8.99876705E-01\natom   8.19837382E-01   8.19837382E-01   8.19837382E-01 Ne   0.00000000E+00   0.00000000E+00  -8.99876705E-01  -8.99876705E-01  -8.99876705E-01\nenergy  -4.28387639E-01\ncomment r =   1.42000000E+00, E =  -4.28387639E-01, dEdr =   1.55863217E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.68138141E-01   8.68138141E-01   8.68138141E-01\natom   8.25610885E-01   8.25610885E-01   8.25610885E-01 Ne   0.00000000E+00   0.00000000E+00  -8.68138141E-01  -8.68138141E-01  -8.68138141E-01\nenergy  -4.13077215E-01\ncomment r =   1.43000000E+00, E =  -4.13077215E-01, dEdr =   1.50365937E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.37142729E-01   8.37142729E-01   8.37142729E-01\natom   8.31384388E-01   8.31384388E-01   8.31384388E-01 Ne   0.00000000E+00   0.00000000E+00  -8.37142729E-01  -8.37142729E-01  -8.37142729E-01\nenergy  -3.98310158E-01\ncomment r =   1.44000000E+00, E =  -3.98310158E-01, dEdr =   1.44997374E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.06936119E-01   8.06936119E-01   8.06936119E-01\natom   8.37157890E-01   8.37157890E-01   8.37157890E-01 Ne   0.00000000E+00   0.00000000E+00  -8.06936119E-01  -8.06936119E-01  -8.06936119E-01\nenergy  -3.84073184E-01\ncomment r =   1.45000000E+00, E =  -3.84073184E-01, dEdr =   1.39765436E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.77551972E-01   7.77551972E-01   7.77551972E-01\natom   8.42931393E-01   8.42931393E-01   8.42931393E-01 Ne   0.00000000E+00   0.00000000E+00  -7.77551972E-01  -7.77551972E-01  -7.77551972E-01\nenergy  -3.70352321E-01\ncomment r =   1.46000000E+00, E =  -3.70352321E-01, dEdr =   1.34675952E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.49013769E-01   7.49013769E-01   7.49013769E-01\natom   8.48704896E-01   8.48704896E-01   8.48704896E-01 Ne   0.00000000E+00   0.00000000E+00  -7.49013769E-01  -7.49013769E-01  -7.49013769E-01\nenergy  -3.57133107E-01\ncomment r =   1.47000000E+00, E =  -3.57133107E-01, dEdr =   1.29732990E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.21336370E-01   7.21336370E-01   7.21336370E-01\natom   8.54478398E-01   8.54478398E-01   8.54478398E-01 Ne   0.00000000E+00   0.00000000E+00  -7.21336370E-01  -7.21336370E-01  -7.21336370E-01\nenergy  -3.44400751E-01\ncomment r =   1.48000000E+00, E =  -3.44400751E-01, dEdr =   1.24939124E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.94527370E-01   6.94527370E-01   6.94527370E-01\natom   8.60251901E-01   8.60251901E-01   8.60251901E-01 Ne   0.00000000E+00   0.00000000E+00  -6.94527370E-01  -6.94527370E-01  -6.94527370E-01\nenergy  -3.32140268E-01\ncomment r =   1.49000000E+00, E =  -3.32140268E-01, dEdr =   1.20295669E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.68588257E-01   6.68588257E-01   6.68588257E-01\natom   8.66025404E-01   8.66025404E-01   8.66025404E-01 Ne   0.00000000E+00   0.00000000E+00  -6.68588257E-01  -6.68588257E-01  -6.68588257E-01\nenergy  -3.20336594E-01\ncomment r =   1.50000000E+00, E =  -3.20336594E-01, dEdr =   1.15802883E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.43515424E-01   6.43515424E-01   6.43515424E-01\natom   8.71798906E-01   8.71798906E-01   8.71798906E-01 Ne   0.00000000E+00   0.00000000E+00  -6.43515424E-01  -6.43515424E-01  -6.43515424E-01\nenergy  -3.08974689E-01\ncomment r =   1.51000000E+00, E =  -3.08974689E-01, dEdr =   1.11460141E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.19301030E-01   6.19301030E-01   6.19301030E-01\natom   8.77572409E-01   8.77572409E-01   8.77572409E-01 Ne   0.00000000E+00   0.00000000E+00  -6.19301030E-01  -6.19301030E-01  -6.19301030E-01\nenergy  -2.98039609E-01\ncomment r =   1.52000000E+00, E =  -2.98039609E-01, dEdr =   1.07266085E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.95933747E-01   5.95933747E-01   5.95933747E-01\natom   8.83345912E-01   8.83345912E-01   8.83345912E-01 Ne   0.00000000E+00   0.00000000E+00  -5.95933747E-01  -5.95933747E-01  -5.95933747E-01\nenergy  -2.87516580E-01\ncomment r =   1.53000000E+00, E =  -2.87516580E-01, dEdr =   1.03218753E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.73399404E-01   5.73399404E-01   5.73399404E-01\natom   8.89119415E-01   8.89119415E-01   8.89119415E-01 Ne   0.00000000E+00   0.00000000E+00  -5.73399404E-01  -5.73399404E-01  -5.73399404E-01\nenergy  -2.77391049E-01\ncomment r =   1.54000000E+00, E =  -2.77391049E-01, dEdr =   9.93156900E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.51681534E-01   5.51681534E-01   5.51681534E-01\natom   8.94892917E-01   8.94892917E-01   8.94892917E-01 Ne   0.00000000E+00   0.00000000E+00  -5.51681534E-01  -5.51681534E-01  -5.51681534E-01\nenergy  -2.67648728E-01\ncomment r =   1.55000000E+00, E =  -2.67648728E-01, dEdr =   9.55540446E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.30761850E-01   5.30761850E-01   5.30761850E-01\natom   9.00666420E-01   9.00666420E-01   9.00666420E-01 Ne   0.00000000E+00   0.00000000E+00  -5.30761850E-01  -5.30761850E-01  -5.30761850E-01\nenergy  -2.58275632E-01\ncomment r =   1.56000000E+00, E =  -2.58275632E-01, dEdr =   9.19306492E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.10620650E-01   5.10620650E-01   5.10620650E-01\natom   9.06439923E-01   9.06439923E-01   9.06439923E-01 Ne   0.00000000E+00   0.00000000E+00  -5.10620650E-01  -5.10620650E-01  -5.10620650E-01\nenergy  -2.49258104E-01\ncomment r =   1.57000000E+00, E =  -2.49258104E-01, dEdr =   8.84420909E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.91237157E-01   4.91237157E-01   4.91237157E-01\natom   9.12213425E-01   9.12213425E-01   9.12213425E-01 Ne   0.00000000E+00   0.00000000E+00  -4.91237157E-01  -4.91237157E-01  -4.91237157E-01\nenergy  -2.40582839E-01\ncomment r =   1.58000000E+00, E =  -2.40582839E-01, dEdr =   8.50847714E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.72589820E-01   4.72589820E-01   4.72589820E-01\natom   9.17986928E-01   9.17986928E-01   9.17986928E-01 Ne   0.00000000E+00   0.00000000E+00  -4.72589820E-01  -4.72589820E-01  -4.72589820E-01\nenergy  -2.32236899E-01\ncomment r =   1.59000000E+00, E =  -2.32236899E-01, dEdr =   8.18549579E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.54656560E-01   4.54656560E-01   4.54656560E-01\natom   9.23760431E-01   9.23760431E-01   9.23760431E-01 Ne   0.00000000E+00   0.00000000E+00  -4.54656560E-01  -4.54656560E-01  -4.54656560E-01\nenergy  -2.24207724E-01\ncomment r =   1.60000000E+00, E =  -2.24207724E-01, dEdr =   7.87488261E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.37414983E-01   4.37414983E-01   4.37414983E-01\natom   9.29533933E-01   9.29533933E-01   9.29533933E-01 Ne   0.00000000E+00   0.00000000E+00  -4.37414983E-01  -4.37414983E-01  -4.37414983E-01\nenergy  -2.16483140E-01\ncomment r =   1.61000000E+00, E =  -2.16483140E-01, dEdr =   7.57624975E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.20842560E-01   4.20842560E-01   4.20842560E-01\natom   9.35307436E-01   9.35307436E-01   9.35307436E-01 Ne   0.00000000E+00   0.00000000E+00  -4.20842560E-01  -4.20842560E-01  -4.20842560E-01\nenergy  -2.09051362E-01\ncomment r =   1.62000000E+00, E =  -2.09051362E-01, dEdr =   7.28920696E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.04916775E-01   4.04916775E-01   4.04916775E-01\natom   9.41080939E-01   9.41080939E-01   9.41080939E-01 Ne   0.00000000E+00   0.00000000E+00  -4.04916775E-01  -4.04916775E-01  -4.04916775E-01\nenergy  -2.01900993E-01\ncomment r =   1.63000000E+00, E =  -2.01900993E-01, dEdr =   7.01336426E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.89615248E-01   3.89615248E-01   3.89615248E-01\natom   9.46854441E-01   9.46854441E-01   9.46854441E-01 Ne   0.00000000E+00   0.00000000E+00  -3.89615248E-01  -3.89615248E-01  -3.89615248E-01\nenergy  -1.95021029E-01\ncomment r =   1.64000000E+00, E =  -1.95021029E-01, dEdr =   6.74833406E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.74915846E-01   3.74915846E-01   3.74915846E-01\natom   9.52627944E-01   9.52627944E-01   9.52627944E-01 Ne   0.00000000E+00   0.00000000E+00  -3.74915846E-01  -3.74915846E-01  -3.74915846E-01\nenergy  -1.88400849E-01\ncomment r =   1.65000000E+00, E =  -1.88400849E-01, dEdr =   6.49373295E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.60796761E-01   3.60796761E-01   3.60796761E-01\natom   9.58401447E-01   9.58401447E-01   9.58401447E-01 Ne   0.00000000E+00   0.00000000E+00  -3.60796761E-01  -3.60796761E-01  -3.60796761E-01\nenergy  -1.82030213E-01\ncomment r =   1.66000000E+00, E =  -1.82030213E-01, dEdr =   6.24918320E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.47236580E-01   3.47236580E-01   3.47236580E-01\natom   9.64174950E-01   9.64174950E-01   9.64174950E-01 Ne   0.00000000E+00   0.00000000E+00  -3.47236580E-01  -3.47236580E-01  -3.47236580E-01\nenergy  -1.75899255E-01\ncomment r =   1.67000000E+00, E =  -1.75899255E-01, dEdr =   6.01431398E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.34214345E-01   3.34214345E-01   3.34214345E-01\natom   9.69948452E-01   9.69948452E-01   9.69948452E-01 Ne   0.00000000E+00   0.00000000E+00  -3.34214345E-01  -3.34214345E-01  -3.34214345E-01\nenergy  -1.69998479E-01\ncomment r =   1.68000000E+00, E =  -1.69998479E-01, dEdr =   5.78876226E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.21709594E-01   3.21709594E-01   3.21709594E-01\natom   9.75721955E-01   9.75721955E-01   9.75721955E-01 Ne   0.00000000E+00   0.00000000E+00  -3.21709594E-01  -3.21709594E-01  -3.21709594E-01\nenergy  -1.64318743E-01\ncomment r =   1.69000000E+00, E =  -1.64318743E-01, dEdr =   5.57217362E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.09702395E-01   3.09702395E-01   3.09702395E-01\natom   9.81495458E-01   9.81495458E-01   9.81495458E-01 Ne   0.00000000E+00   0.00000000E+00  -3.09702395E-01  -3.09702395E-01  -3.09702395E-01\nenergy  -1.58851259E-01\ncomment r =   1.70000000E+00, E =  -1.58851259E-01, dEdr =   5.36420284E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.98173372E-01   2.98173372E-01   2.98173372E-01\natom   9.87268960E-01   9.87268960E-01   9.87268960E-01 Ne   0.00000000E+00   0.00000000E+00  -2.98173372E-01  -2.98173372E-01  -2.98173372E-01\nenergy  -1.53587577E-01\ncomment r =   1.71000000E+00, E =  -1.53587577E-01, dEdr =   5.16451429E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.87103720E-01   2.87103720E-01   2.87103720E-01\natom   9.93042463E-01   9.93042463E-01   9.93042463E-01 Ne   0.00000000E+00   0.00000000E+00  -2.87103720E-01  -2.87103720E-01  -2.87103720E-01\nenergy  -1.48519579E-01\ncomment r =   1.72000000E+00, E =  -1.48519579E-01, dEdr =   4.97278230E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.76475222E-01   2.76475222E-01   2.76475222E-01\natom   9.98815966E-01   9.98815966E-01   9.98815966E-01 Ne   0.00000000E+00   0.00000000E+00  -2.76475222E-01  -2.76475222E-01  -2.76475222E-01\nenergy  -1.43639466E-01\ncomment r =   1.73000000E+00, E =  -1.43639466E-01, dEdr =   4.78869131E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.66270250E-01   2.66270250E-01   2.66270250E-01\natom   1.00458947E+00   1.00458947E+00   1.00458947E+00 Ne   0.00000000E+00   0.00000000E+00  -2.66270250E-01  -2.66270250E-01  -2.66270250E-01\nenergy  -1.38939751E-01\ncomment r =   1.74000000E+00, E =  -1.38939751E-01, dEdr =   4.61193602E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.56471773E-01   2.56471773E-01   2.56471773E-01\natom   1.01036297E+00   1.01036297E+00   1.01036297E+00 Ne   0.00000000E+00   0.00000000E+00  -2.56471773E-01  -2.56471773E-01  -2.56471773E-01\nenergy  -1.34413247E-01\ncomment r =   1.75000000E+00, E =  -1.34413247E-01, dEdr =   4.44222142E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.47063348E-01   2.47063348E-01   2.47063348E-01\natom   1.01613647E+00   1.01613647E+00   1.01613647E+00 Ne   0.00000000E+00   0.00000000E+00  -2.47063348E-01  -2.47063348E-01  -2.47063348E-01\nenergy  -1.30053056E-01\ncomment r =   1.76000000E+00, E =  -1.30053056E-01, dEdr =   4.27926272E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.38029122E-01   2.38029122E-01   2.38029122E-01\natom   1.02190998E+00   1.02190998E+00   1.02190998E+00 Ne   0.00000000E+00   0.00000000E+00  -2.38029122E-01  -2.38029122E-01  -2.38029122E-01\nenergy  -1.25852561E-01\ncomment r =   1.77000000E+00, E =  -1.25852561E-01, dEdr =   4.12278533E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.29353819E-01   2.29353819E-01   2.29353819E-01\natom   1.02768348E+00   1.02768348E+00   1.02768348E+00 Ne   0.00000000E+00   0.00000000E+00  -2.29353819E-01  -2.29353819E-01  -2.29353819E-01\nenergy  -1.21805413E-01\ncomment r =   1.78000000E+00, E =  -1.21805413E-01, dEdr =   3.97252467E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.21022735E-01   2.21022735E-01   2.21022735E-01\natom   1.03345698E+00   1.03345698E+00   1.03345698E+00 Ne   0.00000000E+00   0.00000000E+00  -2.21022735E-01  -2.21022735E-01  -2.21022735E-01\nenergy  -1.17905524E-01\ncomment r =   1.79000000E+00, E =  -1.17905524E-01, dEdr =   3.82822607E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.13021724E-01   2.13021724E-01   2.13021724E-01\natom   1.03923048E+00   1.03923048E+00   1.03923048E+00 Ne   0.00000000E+00   0.00000000E+00  -2.13021724E-01  -2.13021724E-01  -2.13021724E-01\nenergy  -1.14147056E-01\ncomment r =   1.80000000E+00, E =  -1.14147056E-01, dEdr =   3.68964449E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.05337187E-01   2.05337187E-01   2.05337187E-01\natom   1.04500399E+00   1.04500399E+00   1.04500399E+00 Ne   0.00000000E+00   0.00000000E+00  -2.05337187E-01  -2.05337187E-01  -2.05337187E-01\nenergy  -1.10524408E-01\ncomment r =   1.81000000E+00, E =  -1.10524408E-01, dEdr =   3.55654440E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.97956057E-01   1.97956057E-01   1.97956057E-01\natom   1.05077749E+00   1.05077749E+00   1.05077749E+00 Ne   0.00000000E+00   0.00000000E+00  -1.97956057E-01  -1.97956057E-01  -1.97956057E-01\nenergy  -1.07032215E-01\ncomment r =   1.82000000E+00, E =  -1.07032215E-01, dEdr =   3.42869948E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.90865785E-01   1.90865785E-01   1.90865785E-01\natom   1.05655099E+00   1.05655099E+00   1.05655099E+00 Ne   0.00000000E+00   0.00000000E+00  -1.90865785E-01  -1.90865785E-01  -1.90865785E-01\nenergy  -1.03665330E-01\ncomment r =   1.83000000E+00, E =  -1.03665330E-01, dEdr =   3.30589238E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.84054328E-01   1.84054328E-01   1.84054328E-01\natom   1.06232450E+00   1.06232450E+00   1.06232450E+00 Ne   0.00000000E+00   0.00000000E+00  -1.84054328E-01  -1.84054328E-01  -1.84054328E-01\nenergy  -1.00418821E-01\ncomment r =   1.84000000E+00, E =  -1.00418821E-01, dEdr =   3.18791447E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.77510126E-01   1.77510126E-01   1.77510126E-01\natom   1.06809800E+00   1.06809800E+00   1.06809800E+00 Ne   0.00000000E+00   0.00000000E+00  -1.77510126E-01  -1.77510126E-01  -1.77510126E-01\nenergy  -9.72879584E-02\ncomment r =   1.85000000E+00, E =  -9.72879584E-02, dEdr =   3.07456558E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.71222096E-01   1.71222096E-01   1.71222096E-01\natom   1.07387150E+00   1.07387150E+00   1.07387150E+00 Ne   0.00000000E+00   0.00000000E+00  -1.71222096E-01  -1.71222096E-01  -1.71222096E-01\nenergy  -9.42682107E-02\ncomment r =   1.86000000E+00, E =  -9.42682107E-02, dEdr =   2.96565370E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.65179609E-01   1.65179609E-01   1.65179609E-01\natom   1.07964500E+00   1.07964500E+00   1.07964500E+00 Ne   0.00000000E+00   0.00000000E+00  -1.65179609E-01  -1.65179609E-01  -1.65179609E-01\nenergy  -9.13552334E-02\ncomment r =   1.87000000E+00, E =  -9.13552334E-02, dEdr =   2.86099475E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.59372475E-01   1.59372475E-01   1.59372475E-01\natom   1.08541851E+00   1.08541851E+00   1.08541851E+00 Ne   0.00000000E+00   0.00000000E+00  -1.59372475E-01  -1.59372475E-01  -1.59372475E-01\nenergy  -8.85448625E-02\ncomment r =   1.88000000E+00, E =  -8.85448625E-02, dEdr =   2.76041225E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.53790932E-01   1.53790932E-01   1.53790932E-01\natom   1.09119201E+00   1.09119201E+00   1.09119201E+00 Ne   0.00000000E+00   0.00000000E+00  -1.53790932E-01  -1.53790932E-01  -1.53790932E-01\nenergy  -8.58331065E-02\ncomment r =   1.89000000E+00, E =  -8.58331065E-02, dEdr =   2.66373709E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.48425625E-01   1.48425625E-01   1.48425625E-01\natom   1.09696551E+00   1.09696551E+00   1.09696551E+00 Ne   0.00000000E+00   0.00000000E+00  -1.48425625E-01  -1.48425625E-01  -1.48425625E-01\nenergy  -8.32161399E-02\ncomment r =   1.90000000E+00, E =  -8.32161399E-02, dEdr =   2.57080724E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.43267593E-01   1.43267593E-01   1.43267593E-01\natom   1.10273901E+00   1.10273901E+00   1.10273901E+00 Ne   0.00000000E+00   0.00000000E+00  -1.43267593E-01  -1.43267593E-01  -1.43267593E-01\nenergy  -8.06902954E-02\ncomment r =   1.91000000E+00, E =  -8.06902954E-02, dEdr =   2.48146751E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38308255E-01   1.38308255E-01   1.38308255E-01\natom   1.10851252E+00   1.10851252E+00   1.10851252E+00 Ne   0.00000000E+00   0.00000000E+00  -1.38308255E-01  -1.38308255E-01  -1.38308255E-01\nenergy  -7.82520578E-02\ncomment r =   1.92000000E+00, E =  -7.82520578E-02, dEdr =   2.39556925E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.33539391E-01   1.33539391E-01   1.33539391E-01\natom   1.11428602E+00   1.11428602E+00   1.11428602E+00 Ne   0.00000000E+00   0.00000000E+00  -1.33539391E-01  -1.33539391E-01  -1.33539391E-01\nenergy  -7.58980573E-02\ncomment r =   1.93000000E+00, E =  -7.58980573E-02, dEdr =   2.31297011E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.28953134E-01   1.28953134E-01   1.28953134E-01\natom   1.12005952E+00   1.12005952E+00   1.12005952E+00 Ne   0.00000000E+00   0.00000000E+00  -1.28953134E-01  -1.28953134E-01  -1.28953134E-01\nenergy  -7.36250634E-02\ncomment r =   1.94000000E+00, E =  -7.36250634E-02, dEdr =   2.23353381E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.24541951E-01   1.24541951E-01   1.24541951E-01\natom   1.12583302E+00   1.12583302E+00   1.12583302E+00 Ne   0.00000000E+00   0.00000000E+00  -1.24541951E-01  -1.24541951E-01  -1.24541951E-01\nenergy  -7.14299790E-02\ncomment r =   1.95000000E+00, E =  -7.14299790E-02, dEdr =   2.15712986E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.20298629E-01   1.20298629E-01   1.20298629E-01\natom   1.13160653E+00   1.13160653E+00   1.13160653E+00 Ne   0.00000000E+00   0.00000000E+00  -1.20298629E-01  -1.20298629E-01  -1.20298629E-01\nenergy  -6.93098346E-02\ncomment r =   1.96000000E+00, E =  -6.93098346E-02, dEdr =   2.08363337E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.16216266E-01   1.16216266E-01   1.16216266E-01\natom   1.13738003E+00   1.13738003E+00   1.13738003E+00 Ne   0.00000000E+00   0.00000000E+00  -1.16216266E-01  -1.16216266E-01  -1.16216266E-01\nenergy  -6.72617830E-02\ncomment r =   1.97000000E+00, E =  -6.72617830E-02, dEdr =   2.01292477E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.12288255E-01   1.12288255E-01   1.12288255E-01\natom   1.14315353E+00   1.14315353E+00   1.14315353E+00 Ne   0.00000000E+00   0.00000000E+00  -1.12288255E-01  -1.12288255E-01  -1.12288255E-01\nenergy  -6.52830939E-02\ncomment r =   1.98000000E+00, E =  -6.52830939E-02, dEdr =   1.94488962E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.08508271E-01   1.08508271E-01   1.08508271E-01\natom   1.14892704E+00   1.14892704E+00   1.14892704E+00 Ne   0.00000000E+00   0.00000000E+00  -1.08508271E-01  -1.08508271E-01  -1.08508271E-01\nenergy  -6.33711491E-02\ncomment r =   1.99000000E+00, E =  -6.33711491E-02, dEdr =   1.87941839E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.04870264E-01   1.04870264E-01   1.04870264E-01\natom   1.15470054E+00   1.15470054E+00   1.15470054E+00 Ne   0.00000000E+00   0.00000000E+00  -1.04870264E-01  -1.04870264E-01  -1.04870264E-01\nenergy  -6.15234375E-02\ncomment r =   2.00000000E+00, E =  -6.15234375E-02, dEdr =   1.81640625E-01\nend\n"
  },
  {
    "path": "examples/nnp-scaling/LJ/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              1              # Number of elements.\nelements                        Ne             # Specification of elements.\n#atom_energy                     Ne 0.0         # Free atom reference energy (Ne).\ncutoff_type                     2              # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      1              # Number of hidden layers.\nglobal_nodes_short              3              # Number of nodes in each hidden layer.\nglobal_activation_short         t l            # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# radial Ne Ne\nsymfunction_short Ne 2 Ne 1.000 0.00 3.00\nsymfunction_short Ne 2 Ne 1.000 0.25 3.00\nsymfunction_short Ne 2 Ne 1.000 0.50 3.00\nsymfunction_short Ne 2 Ne 1.000 0.75 3.00\nsymfunction_short Ne 2 Ne 1.000 1.00 3.00\n"
  },
  {
    "path": "examples/nnp-select/H2O_RPBE-D3/input.data",
    "content": " begin\ncomment written by RuNNerDecom\nlattice      24.623508      0.000000      0.000000\nlattice       0.000000     24.623508      0.000000\nlattice       0.000000      0.000000     24.623508\natom     3.735290838    2.327841157    3.501304856   O   -0.226389360    0.000000000   -0.006530137   -0.002852459   -0.027992554\natom     5.246524320    3.393061301    3.627368536   H    0.120793430    0.000000000    0.004517488   -0.000517262    0.005052573\natom     3.558676964    2.038939712    1.628158442   H    0.127225380    0.000000000    0.000095815    0.002211264    0.023427576\natom     4.652261909   21.146799653   16.174455806   O   -0.240350190    0.000000000   -0.000231046   -0.007150914    0.026944723\natom     4.197045601   22.522898765   15.074691455   H    0.132518870    0.000000000   -0.001535223    0.002790532   -0.018391035\natom     5.012047009   19.588530870   15.274057640   H    0.135733700    0.000000000    0.002788938    0.006272370   -0.006171035\natom    16.857157435    3.327223216    5.017451628   O   -0.214010320    0.000000000    0.010171588    0.016012738    0.035099119\natom    16.307700448    2.330278905    3.636288047   H    0.108559530    0.000000000   -0.008301162   -0.024899500   -0.030394951\natom    17.367119130    2.071367425    6.332134617   H    0.121384900    0.000000000   -0.006697761    0.007081892   -0.003219491\natom    18.117794235   -0.374704494   19.251970513   O   -0.253642250    0.000000000   -0.024405004   -0.012754375    0.012242947\natom    16.521636428    0.337611045   19.927736844   H    0.120809200    0.000000000    0.002220741   -0.011811043   -0.009670033\natom    19.148602452    1.088431659   19.427148194   H    0.114155690    0.000000000    0.021230736    0.022132545   -0.006007141\natom    17.757139861    0.050971603    9.130347691   O   -0.215317630    0.000000000   -0.005434943   -0.001827901    0.005465729\natom    16.259474618   23.846841416    9.848217137   H    0.133741170    0.000000000   -0.001711391    0.010244935   -0.002774444\natom    18.540979672   23.231546345    8.347755099   H    0.146150570    0.000000000    0.014635404   -0.006670669   -0.004527888\natom    12.013315016    3.780360824   -0.071301285   O   -0.253689050    0.000000000    0.005359628    0.024749295   -0.005332222\natom    13.294852195    5.203022807   -0.128943624   H    0.114078030    0.000000000   -0.012906774   -0.026389114   -0.001326269\natom    12.919722513    2.259754298    0.424517694   H    0.116540600    0.000000000    0.006743413    0.003879913   -0.000468813\natom    12.529890755    5.212376955   15.827331876   O   -0.253986350    0.000000000   -0.000119721    0.008266330    0.006530251\natom    12.425917982    4.306290712   14.234424399   H    0.112634320    0.000000000    0.000140603   -0.011164836   -0.001375189\natom    12.764916087    3.876925868   17.158077543   H    0.100753240    0.000000000   -0.002300020   -0.000231651   -0.007826174\natom    20.033183604   16.544426534   23.913170829   O   -0.260620870    0.000000000    0.006524698   -0.028540501   -0.005264426\natom    21.355047555   15.177379213   23.397275392   H    0.111928170    0.000000000   -0.031707302    0.026134828    0.007143786\natom    18.354350246   15.846210247   23.385937031   H    0.123277260    0.000000000    0.019731649    0.005955325    0.004549934\natom    12.144518753   18.052825425   18.706274082   O   -0.210341170    0.000000000   -0.014866699   -0.011665448    0.026560721\natom    13.507181907   18.024574008   17.526007366   H    0.124395570    0.000000000    0.020090667    0.001476881   -0.008312401\natom    12.731845866   16.994559476   20.149212834   H    0.144891080    0.000000000   -0.003199444    0.006143511   -0.016646283\natom    16.912564227   19.121579358   16.214744783   O   -0.214062700    0.000000000   -0.002538630    0.026152342    0.005346098\natom    17.405216024   20.866931102   16.692259868   H    0.148034420    0.000000000   -0.013977441   -0.005713738   -0.002595361\natom    18.524312281   18.360227296   16.480704944   H    0.131237310    0.000000000    0.020632529   -0.022303425    0.004792410\natom    20.116898505    4.922757414   19.585318334   O   -0.241188010    0.000000000    0.001047194   -0.008189572    0.009275614\natom    18.468829900    5.729349537   19.695867356   H    0.141751490    0.000000000    0.004325710    0.000224611    0.005073355\natom    20.829892456    4.864629415   21.353157828   H    0.110757650    0.000000000   -0.004199404    0.009172873   -0.016789747\natom    12.029245413   15.603096884    8.902182068   O   -0.266938200    0.000000000    0.054595746   -0.006876686    0.018733486\natom    10.441270123   16.269792527    8.454656948   H    0.098486210    0.000000000   -0.033110457    0.019565416    0.002657365\natom    13.112417962   16.912299665    9.851505262   H    0.107149850    0.000000000   -0.019172455   -0.019589210   -0.019407954\natom     9.762518023    8.972177551   12.034574443   O   -0.277540080    0.000000000   -0.003205114   -0.012410450    0.017574029\natom     8.196841510    9.866755358   12.482137357   H    0.103740730    0.000000000   -0.000635995    0.000182125   -0.003014649\natom     9.748855298    7.559606710   13.275898234   H    0.119507420    0.000000000    0.002112794    0.016284777   -0.013554342\natom    11.224958757    2.122597921   11.606607997   O   -0.245529630    0.000000000   -0.010907413   -0.009461731    0.001847302\natom     9.592102453    2.288799400   12.466811672   H    0.151624050    0.000000000    0.004846576   -0.002799857   -0.008505057\natom    11.227075251    0.382450484   10.750977461   H    0.105991310    0.000000000    0.002003860    0.024044803    0.003860573\natom    15.773417968    0.020397712    1.108963541   O   -0.249425870    0.000000000   -0.020986710   -0.004981242    0.011220213\natom    14.434659859   23.547130733    1.988578491   H    0.107892190    0.000000000    0.024960938    0.000684236   -0.009393969\natom    17.204224673   23.582846571    0.577874700   H    0.113413590    0.000000000   -0.004731034   -0.002010091    0.004887777\natom     7.837283177   14.849360422    1.930431595   O   -0.246274950    0.000000000   -0.005588957   -0.014293836   -0.001271832\natom     7.496244168   13.061338645    2.271583988   H    0.122890240    0.000000000   -0.004555401    0.000409162   -0.009761648\natom     8.769712213   15.169158901    3.445595708   H    0.143023810    0.000000000    0.010803411    0.013941557    0.011111768\natom     2.743222022   10.053328092   23.736292394   O   -0.252549480    0.000000000    0.007322459    0.011795230    0.001219162\natom     3.497657684   10.068559291   22.018719634   H    0.125243770    0.000000000   -0.011934368   -0.008624966    0.006794256\natom     1.922286872    8.434682535   24.040727394   H    0.129167780    0.000000000    0.001734579   -0.001652283   -0.011524410\natom     3.161626450    0.226583922   11.717345992   O   -0.285699660    0.000000000    0.040986590    0.001100156    0.013400632\natom     1.425553265    0.479673153   12.087826946   H    0.122541680    0.000000000   -0.025013874   -0.003874071   -0.009118954\natom     3.611683803   23.808290988   10.271005732   H    0.121065410    0.000000000   -0.015436266    0.002035677   -0.004058975\natom    20.940252505    9.880059035   12.200152312   O   -0.275422060    0.000000000   -0.001938879   -0.004469234   -0.020539683\natom    20.788318464    9.814825663   10.312579723   H    0.109060890    0.000000000    0.006332770    0.006555221    0.015207528\natom    19.358929054    9.035710169   12.661623616   H    0.106588780    0.000000000    0.000923001    0.003170607    0.007646375\natom    14.396298403   10.368137693    8.807695724   O   -0.209950340    0.000000000    0.007885773    0.015339112   -0.000351684\natom    12.860952007   11.366291430    8.996328261   H    0.145488850    0.000000000    0.002826266    0.006136860    0.002973287\natom    13.798086463    8.742783605    8.253495522   H    0.110382130    0.000000000   -0.011853069   -0.021986352   -0.004594575\natom    13.239067458   10.616920237    1.925348229   O   -0.215059510    0.000000000   -0.007338457   -0.001364175   -0.018737115\natom    11.553185418    9.955364651    1.506323971   H    0.126512430    0.000000000    0.001343098    0.002205736    0.011314721\natom    13.445576811   10.495902127    3.722365107   H    0.152884150    0.000000000   -0.000174778    0.001667696    0.009753463\natom     0.280603654    4.615261056    7.314395750   O   -0.243723940    0.000000000    0.004807366   -0.014069467   -0.000753954\natom    -0.080075287    3.349899939    8.623655223   H    0.128574210    0.000000000   -0.003749374    0.009189219    0.002252593\natom     1.506813410    3.695077450    6.256810103   H    0.116843550    0.000000000   -0.000389753    0.008649305   -0.000938804\natom    12.581763758   13.096052927   15.795943512   O   -0.258711280    0.000000000    0.026171215   -0.014179379   -0.026224186\natom    11.541128961   12.460953518   14.408562730   H    0.121979740    0.000000000   -0.011525216    0.001272479    0.003251832\natom    14.196724347   12.431190320   15.023442062   H    0.120619230    0.000000000   -0.018602989    0.008217294    0.021267917\natom     9.179064850   22.130969411   19.406361199   O   -0.259792010    0.000000000   -0.020138004   -0.036495308   -0.021207667\natom     7.482940491   21.652301593   18.509912562   H    0.114889600    0.000000000    0.038012094    0.016497477    0.016307899\natom    10.263673591   20.515819849   19.111752778   H    0.096062120    0.000000000   -0.014941800    0.027661486    0.006963264\natom     8.223675632    5.622183126    4.302265594   O   -0.245736000    0.000000000    0.011079563   -0.010134595   -0.011611646\natom     9.565003770    5.226077475    5.561277229   H    0.108850670    0.000000000   -0.008796745    0.005768103   -0.004919150\natom     9.167461927    5.448932966    2.681768104   H    0.114507140    0.000000000   -0.010304827    0.003124034    0.013973134\natom    22.361327117    2.203459334   12.298040164   O   -0.255893520    0.000000000   -0.005471023    0.001791380   -0.006291432\natom    22.147410035    3.815830998   13.186684229   H    0.128045440    0.000000000    0.002391325   -0.007090681   -0.002223960\natom    20.751468790    1.793267659   11.459398273   H    0.122395850    0.000000000    0.006464068    0.002424448    0.006347075\natom     2.660225218   10.479631579    9.286420234   O   -0.271009420    0.000000000   -0.016232311    0.002386388    0.014896468\natom     3.620660006   10.464910606    7.723105880   H    0.096922670    0.000000000    0.010202527   -0.001445197   -0.011181931\natom     1.655670976    8.943548189    9.179801843   H    0.133240170    0.000000000    0.000927921   -0.000142069    0.000818874\natom     4.698994854   22.558803576    6.355378257   O   -0.276961830    0.000000000   -0.028833675   -0.023776022    0.005152779\natom     4.088575278   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0.000169458   -0.002835816\natom     6.013579577   10.506359876    4.753392532   H    0.145063750    0.000000000   -0.001970558    0.010961620    0.007571230\natom     3.118151394   11.375205272    4.806584564   H    0.128255580    0.000000000    0.012295645   -0.006476487    0.003924093\natom    10.594691379    0.663929082   12.934001289   O   -0.229582380    0.000000000   -0.005718461   -0.009204961    0.016130566\natom     9.810114574    2.351203851   12.631886873   H    0.130965550    0.000000000    0.002048060   -0.018347172    0.012319236\natom    10.477305325    0.034272087   14.740476249   H    0.133202620    0.000000000   -0.006074826    0.025088333   -0.020766319\natom    12.271704930    7.075965131    7.185826293   O   -0.214138270    0.000000000    0.014703364   -0.037033285   -0.040099260\natom    13.568972196    5.966432781    6.289377656   H    0.162923180    0.000000000   -0.028438357    0.015427135    0.020083631\natom    13.309686551    7.858690004    8.414967015   H    0.125455030    0.000000000    0.011234519    0.017085563    0.021636987\natom     0.372695714   13.548797472    5.926536868   O   -0.268084480    0.000000000    0.007614420   -0.073404173   -0.063264501\natom     0.382902129   14.703288314    7.165780070   H    0.127809330    0.000000000   -0.000950585    0.059556028    0.068283917\natom     0.966755925   14.552265121    4.457181624   H    0.107279650    0.000000000   -0.012777661    0.009268460   -0.000933885\natom    17.466446954   19.223044463   17.927731175   O   -0.219763310    0.000000000   -0.035165353   -0.017553463   -0.018934327\natom    18.940386676   18.203939325   17.931045756   H    0.127674450    0.000000000    0.032197931   -0.004780277    0.005456355\natom    16.507728038   18.239067458   16.615179798   H    0.142510840    0.000000000   -0.002326973    0.017481994    0.012448661\natom    14.013464304   16.394244270   13.426133411   O   -0.284574960    0.000000000    0.035938662    0.007538260   -0.048171816\natom    12.330477326   16.976378414   13.002709868   H    0.105804360    0.000000000   -0.008450623    0.005466588    0.004089666\natom    15.005799572   16.925270751   11.745075844   H    0.106969100    0.000000000   -0.019060852   -0.013019411    0.044592581\natom     7.862480796    4.636206789   22.996949981   O   -0.255211000    0.000000000    0.026019058    0.004901961   -0.000568282\natom     6.607577427    4.184068847   21.690317228   H    0.104519940    0.000000000    0.008125767   -0.006959821   -0.003212454\natom     9.649892191    4.419026148   22.306113077   H    0.118804020    0.000000000   -0.031718409   -0.002728319    0.010893469\natom     3.798515431    8.049864223   11.577092353   O   -0.233009840    0.000000000   -0.021582397   -0.005949985   -0.012554795\natom     4.831649902    9.433934203   11.065106760   H    0.130163010    0.000000000    0.017887414    0.015747756   -0.003688555\natom     2.260784199    8.320520355   10.505921459   H    0.115764620    0.000000000    0.007732114   -0.009542268    0.015826322\natom    12.995256786    2.891686525   22.201032925   O   -0.255490060    0.000000000   -0.004915353    0.019472311   -0.001635838\natom    14.491852443    4.010641052   22.317041368   H    0.117038160    0.000000000   -0.003270477   -0.018395304   -0.003528621\natom    13.429871291    1.114213203   22.359666047   H    0.108781130    0.000000000    0.011282327   -0.001145895    0.002319521\natom     2.512601644   20.398749379   20.640606073   O   -0.224422270    0.000000000   -0.021598908    0.009665119    0.051877148\natom     1.537532810   21.905054452   21.392409345   H    0.148959210    0.000000000    0.024157839   -0.031036950   -0.030643998\natom     2.900545564   20.619692466   18.913945617   H    0.123358800    0.000000000    0.000772829    0.021377620   -0.029067107\natom     5.744871754   16.617566523   20.785400726   O   -0.265656930    0.000000000   -0.032497393    0.020526624    0.019299565\natom     4.262486843   18.003063247   20.988257237   H    0.099385010    0.000000000    0.038336244   -0.026808230    0.000017966\natom     5.294918335   15.358585124   22.119375937   H    0.098640670    0.000000000    0.006613032    0.008209277   -0.013429656\natom    17.847113537    1.659677197    7.261604340   O   -0.214984170    0.000000000    0.006018312   -0.022409254    0.003621639\natom    18.987064820    0.224034680    6.782637945   H    0.134801280    0.000000000   -0.013345731    0.012413327    0.012346459\natom    17.213508902    1.225867715    9.010954747   H    0.120488240    0.000000000   -0.000443941    0.002779306   -0.013526258\natom     0.223231546    4.153421256    1.485365010   O   -0.284149710    0.000000000   -0.016138645    0.008676852    0.024731263\natom    22.710372900    4.079060503    2.742248813   H    0.105341390    0.000000000    0.039423346    0.012173922   -0.023123038\natom     1.652651192    5.001182969    2.395013389   H    0.117989360    0.000000000   -0.023819333   -0.014915583   -0.003918404\natom    18.029065889    5.395499049   22.331535573   O   -0.232616100    0.000000000   -0.022435825   -0.041986031    0.019777229\natom    18.450206642    6.009076358   20.698998634   H    0.117402890    0.000000000    0.010969888    0.018577415   -0.028888712\natom    18.471749528    6.543217109   23.632648433   H    0.122965160    0.000000000    0.008555544    0.023492454    0.010076612\natom     9.730995489   -0.013755322   18.655527357   O   -0.260468440    0.000000000    0.033447936   -0.047525024   -0.017241120\natom    10.958809623    1.192342071   19.181358978   H    0.127148600    0.000000000    0.001410520    0.021472916    0.006833322\natom     8.059414903    0.566851923   18.625879432   H    0.119766210    0.000000000   -0.033795515    0.025211959    0.007633086\natom     5.720611440   23.314163314    9.722983047   O   -0.231630130    0.000000000    0.008590611   -0.010936445   -0.025443175\natom     6.834575199    0.786704638    9.364550991   H    0.130111070    0.000000000   -0.010659177   -0.018642575    0.001906309\natom     6.037573440   21.935577321    8.393439246   H    0.130229060    0.000000000   -0.004288229    0.030206013    0.023949980\natom     9.845218141   19.848952241    1.377688373   O   -0.231982490    0.000000000    0.047210910    0.050634028    0.057109462\natom     8.964032828   21.443191975    1.821177035   H    0.130585310    0.000000000   -0.001359815   -0.006723989   -0.005653620\natom     8.864534929   18.936979498    0.325325931   H    0.140456380    0.000000000   -0.053312141   -0.042279623   -0.051814244\natom    21.486183262    2.087957338   12.058619328   O   -0.245742770    0.000000000   -0.018336922    0.012948985   -0.040170727\natom    20.067351756    2.869512469   10.984447548   H    0.132828300    0.000000000    0.028333925   -0.013530492    0.030219120\natom    22.734213694    1.753487019   10.673217090   H    0.099760430    0.000000000   -0.005192035    0.002432708    0.011480438\natom    -0.218456207   22.514791837    3.828822870   O   -0.233891290    0.000000000    0.001999487    0.001056955    0.002002219\natom    22.977963895   23.403316849    2.478210504   H    0.123135500    0.000000000   -0.006368839    0.004516237   -0.013166446\natom     0.169763614   -0.170292738    5.058420906   H    0.104258450    0.000000000    0.006641123   -0.000339229    0.001710832\natom    22.768355390   15.179884991   22.329029795   O   -0.238086150    0.000000000   -0.046086010   -0.025235881    0.005743850\natom    21.434125066   15.631748923   -0.333185305   H    0.126220700    0.000000000    0.031123799   -0.009001222   -0.035124767\natom    21.989842718   13.702640137   21.289668674   H    0.119659510    0.000000000    0.013004599    0.035317132    0.026225131\natom    12.222509671    8.189955346    1.618074860   O   -0.247919730    0.000000000   -0.001797123    0.017574523   -0.067071366\natom    12.278849988    7.760085945    3.281828197   H    0.111233780    0.000000000   -0.004235384   -0.012471568    0.070548691\natom    13.880380289    7.710926590    1.035681823   H    0.141482170    0.000000000    0.006536703    0.000642119   -0.006764662\natom    13.661907075   10.667631057   11.112100488   O   -0.216001700    0.000000000   -0.037279496   -0.013776615    0.034916697\natom    14.124858034   12.345145386   11.672595370   H    0.133272180    0.000000000    0.003591734    0.013021971    0.000895419\natom    12.435880622   10.173618657   12.581225186   H    0.147421220    0.000000000    0.029632111    0.008032176   -0.031477484\natom    17.486330661   17.032057327    9.295375649   O   -0.235087510    0.000000000   -0.006875504   -0.012809861   -0.043019615\natom    16.911783770   16.107704983    7.688512539   H    0.110665490    0.000000000    0.006713966    0.011433370    0.028267991\natom    18.328113278   18.516190235    8.528021815   H    0.118898150    0.000000000   -0.000175840   -0.004542786    0.012591957\natom     4.935770073   18.663509563    6.368200054   O   -0.194094220    0.000000000    0.031139053   -0.066276697    0.021098669\natom     6.518835853   17.598527525    5.812888693   H    0.156894820    0.000000000   -0.042755679    0.033516151    0.011475343\natom     4.178872098   17.417123193    7.699892475   H    0.137280880    0.000000000    0.015711127    0.037753788   -0.030393813\natom    21.151675148   20.879473220    7.686178727   O   -0.248140030    0.000000000   -0.009994913   -0.003084252    0.015181890\natom    21.725161902   21.081677775    5.962589077   H    0.096696550    0.000000000    0.004375907    0.001697312   -0.018251199\natom    22.673568579   21.355735416    8.583993635   H    0.139564520    0.000000000   -0.002909430   -0.001404868    0.006677838\natom    19.507253717   12.301401988   18.501302967   O   -0.199717660    0.000000000   -0.028410932   -0.035128726    0.043667183\natom    19.776549245   13.758948329   17.594513745   H    0.142371980    0.000000000    0.012693146    0.047711282   -0.031771675\natom    17.867647309   12.681150163   19.378767407   H    0.141514070    0.000000000    0.014688099   -0.002133776   -0.011109509\natom    23.134797998   17.370023640   17.326635511   O   -0.251377170    0.000000000   -0.000268730   -0.000574628   -0.003573364\natom    23.309537263   17.766571487   19.122904057   H    0.118237060    0.000000000    0.005638293   -0.001455468   -0.001185792\natom     0.463480083   18.316502796   16.477809882   H    0.138644360    0.000000000   -0.009964426   -0.001923402    0.004419419\natom     7.198349513    9.467121587   20.207068712   O   -0.243428280    0.000000000    0.009787410   -0.009154114    0.016239349\natom     7.841261053    8.491977165   21.715395794   H    0.127971510    0.000000000   -0.015877818    0.012471507   -0.019846659\natom     5.641732350   10.325405299   20.696485297   H    0.130413120    0.000000000    0.003877775    0.000013170    0.004937889\nenergy   -4900.14395256\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/nnp-symfunc/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/hardness.008.data",
    "content": "2.2083\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/hardness.012.data",
    "content": "2.58262\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/hardness.013.data",
    "content": "1.11216\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/hardness.079.data",
    "content": "1.44593e-05\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/input.data",
    "content": "begin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -3.0213298154e-02  5.1567693154e-02  1.9922393451e+01 Mg  3.7167807355e-01 0.0 -9.4322743680e-03 -2.2413776861e-02  7.7865627126e-03\natom  2.8719449351e+00  2.8009054486e+00  2.0024626135e+01 O  -2.9389737645e-01 0.0 -3.6350561723e-03  6.1249902685e-03  2.5786424273e-02\natom -5.2634160015e-02 -2.5517707017e-02  2.4017717039e+01 O  -3.4076981645e-01 0.0  8.4679106109e-03  6.0926179133e-03  2.1955771151e-03\natom  2.8100949782e+00  2.8406387706e+00  2.4025214149e+01 Mg  3.4857724355e-01 0.0  3.9205237589e-03  4.6573504361e-04  1.6738002017e-02\natom -5.5636292104e-02 -4.1865178524e-02  2.8057858266e+01 Mg  3.4468302355e-01 0.0  6.9017331265e-03  5.0789362535e-03  1.5897708577e-03\natom  2.8618942006e+00  2.8757223083e+00  2.8061362895e+01 O  -3.4397115645e-01 0.0 -3.0777921956e-03 -4.8146983794e-03 -3.6774832976e-03\natom  2.9544864277e-02  3.2315939569e-02  3.2054827928e+01 O  -3.3937686645e-01 0.0 -5.1774279543e-03 -7.4152121028e-03  1.3105261660e-03\natom  2.7943300715e+00  2.8407637193e+00  3.2100880305e+01 Mg  3.3692350355e-01 0.0  7.4985631291e-03  6.7221899625e-04 -1.4708620962e-03\natom -3.1920552201e-02 -3.7032034233e-02  3.6074409881e+01 Mg  3.3431710355e-01 0.0  2.4165660806e-03  8.3839159288e-03  5.0266351136e-03\natom  2.8459017708e+00  2.8417063335e+00  3.6145373438e+01 O  -3.4400321645e-01 0.0 -4.3612815550e-04 -2.8388654691e-03 -3.6981614785e-03\natom  3.0692929507e-04  3.8935007201e-02  4.0132460551e+01 O  -4.0120576645e-01 0.0 -1.3316598204e-03 -3.3735946697e-03  6.8865652233e-03\natom  2.9025325690e+00  2.8194442086e+00  4.0167552234e+01 Mg  4.1301906355e-01 0.0 -5.9968860821e-03  4.2674131130e-03 -8.8696409713e-03\natom -5.2057245568e-02  5.6577301191e+00  1.9954570326e+01 Mg  3.6361135355e-01 0.0 -7.7612753003e-03  1.6261322522e-02  8.0036738582e-03\natom  2.7806605118e+00  8.5508668005e+00  2.0035565494e+01 O  -3.9513455645e-01 0.0  7.4466430516e-03 -6.8198685115e-03 -6.3421481676e-03\natom -1.8437621834e-02  5.6894026259e+00  2.4027361143e+01 O  -3.4329628645e-01 0.0  3.4637094860e-03 -3.8396277064e-03 -1.9849209052e-03\natom  2.9099247992e+00  8.5318092163e+00  2.4026649812e+01 Mg  3.2550579355e-01 0.0 -1.0193663430e-02  3.6971378010e-03  2.2842503361e-03\natom -1.6584802194e-03  5.6522393313e+00  2.8114002422e+01 Mg  3.3956782355e-01 0.0  1.1998279804e-04  5.9990343757e-03 -4.6910202554e-03\natom  2.7951705460e+00  8.5400590040e+00  2.8066314639e+01 O  -3.4117285645e-01 0.0  1.3857232085e-03  2.5521691464e-03 -2.1820454120e-04\natom  1.5955183289e-02  5.6711235332e+00  3.2076644399e+01 O  -3.4028644645e-01 0.0 -2.2056468961e-03  4.4894673375e-03  1.3571771970e-03\natom  2.7832966984e+00  8.5575567706e+00  3.2056587017e+01 Mg  3.4476964355e-01 0.0  9.4804484181e-03 -4.9864332837e-03  3.1508439436e-03\natom -1.6645840343e-03  5.7056793839e+00  3.6148481735e+01 Mg  3.2871526355e-01 0.0  9.8866272425e-04 -3.1274305342e-03  3.6106522265e-04\natom  2.8705959542e+00  8.4527230309e+00  3.6175990269e+01 O  -3.4310635645e-01 0.0 -1.5772627830e-03  1.1248456961e-02 -8.7353878468e-03\natom  2.2886282475e-03  5.7198351323e+00  4.0146579431e+01 O  -4.0457293645e-01 0.0 -1.1387927334e-03 -4.1561870899e-04  8.8583096104e-03\natom  2.9524617753e+00  8.5784289454e+00  4.0121052805e+01 Mg  4.0898977355e-01 0.0 -1.0633482971e-02 -6.2953214009e-03 -4.0086736799e-03\natom  3.0094831231e-03  1.1359307739e+01  2.0027647863e+01 Mg  4.1548279355e-01 0.0 -1.1553258490e-03  7.9086814908e-03  1.9938230689e-03\natom  2.8229580407e+00  1.4270151871e+01  2.0025484127e+01 O  -4.0173458645e-01 0.0 -7.7859925888e-04  8.9580663613e-04 -4.8292229305e-03\natom  1.1048925499e-02  1.1395331416e+01  2.3990907402e+01 O  -3.4281219645e-01 0.0 -2.7510391882e-03  2.6278365218e-04  8.4273116234e-03\natom  2.8544680688e+00  1.4265469848e+01  2.4066166080e+01 Mg  3.2854287355e-01 0.0 -1.1656297475e-05 -2.5562658036e-03 -7.7635289407e-03\natom  4.0225822332e-02  1.1434838273e+01  2.8036044082e+01 Mg  3.4631078355e-01 0.0 -5.8977115546e-03 -6.6419122020e-03 -1.7788072371e-03\natom  2.8595430224e+00  1.4268470488e+01  2.8038520114e+01 O  -3.3996677645e-01 0.0 -3.0002977405e-03 -2.0790512045e-03  2.0328727227e-03\natom  4.2663247604e-02  1.1415590790e+01  3.2053462620e+01 O  -3.3703492645e-01 0.0 -3.8665394498e-03 -5.8381563294e-04  3.5225998071e-03\natom  2.8097964960e+00  1.4203810225e+01  3.2113045057e+01 Mg  3.4084083355e-01 0.0  8.7271412233e-03  6.3635241069e-03 -4.4496445241e-03\natom  2.3065938725e-02  1.1425087759e+01  3.6168108977e+01 Mg  3.3303540355e-01 0.0 -1.5353614530e-03 -5.7716277803e-03 -4.3450551541e-04\natom  2.8685326379e+00  1.4217323769e+01  3.6125582754e+01 O  -3.3993518645e-01 0.0 -2.3543904047e-03  2.1041584256e-03 -3.4684303649e-03\natom -1.1938173858e-02  1.1444107284e+01  4.0111277403e+01 O  -4.0173063645e-01 0.0  2.5878021826e-03 -1.0863358480e-03  9.7990049750e-03\natom  2.8513705812e+00  1.4286553843e+01  4.0132048289e+01 Mg  4.1343361355e-01 0.0 -1.7261306216e-03 -2.8219270033e-03 -5.8357127861e-03\natom  5.6203684411e+00 -1.2049440924e-02  1.9975362811e+01 Mg  3.6182934355e-01 0.0  2.4073509561e-02 -1.7801796458e-02  5.7344370812e-03\natom  8.5690350230e+00  2.8163582294e+00  2.0021939473e+01 O  -4.0221400645e-01 0.0 -4.1955077858e-03  3.3827103647e-03 -2.7603853482e-03\natom  5.7539330457e+00 -4.2472120717e-02  2.4017162707e+01 O  -3.4284981645e-01 0.0 -9.6691026651e-03  9.5819875016e-03  2.2821748478e-03\natom  8.5762896811e+00  2.8489691930e+00  2.4063830227e+01 Mg  3.3557953355e-01 0.0  9.2049103493e-04 -9.5343736062e-04 -9.0211054768e-03\natom  5.7964156355e+00 -1.2148538155e-02  2.8075873667e+01 Mg  3.4037604355e-01 0.0 -1.3147839864e-02  1.4194878570e-04 -4.1087584132e-04\natom  8.5150508049e+00  2.8320021181e+00  2.8006093720e+01 O  -3.3713105645e-01 0.0  6.4964906985e-03 -5.0033778893e-05  4.2726297669e-03\natom  5.6816748371e+00 -1.0385083657e-02  3.2061826415e+01 O  -3.4196158645e-01 0.0  7.6716261434e-04 -2.4085324304e-03  1.3619389546e-03\natom  8.5434449395e+00  2.8007979610e+00  3.2019201075e+01 Mg  3.4179853355e-01 0.0 -1.7058480677e-03  2.5689437457e-03  1.0075821803e-02\natom  5.6721743531e+00  3.2999623535e-02  3.6098898330e+01 Mg  3.3256680355e-01 0.0  4.8607220583e-03 -1.5263461095e-04 -1.1948167635e-03\natom  8.5571401994e+00  2.8283084030e+00  3.6068804708e+01 O  -3.4587541645e-01 0.0 -1.8715604416e-04  2.4791277198e-03  2.4010503939e-03\natom  5.7151274280e+00 -2.1470594251e-02  4.0105766188e+01 O  -3.9754561645e-01 0.0 -1.1180819477e-03 -7.0078759673e-04  1.0879970826e-02\natom  8.6176863398e+00  2.8178098035e+00  4.0152576363e+01 Mg  4.1244925355e-01 0.0 -7.5241131366e-03  4.6330989665e-03 -1.1661784251e-02\natom  5.6838568093e+00  5.7085769385e+00  2.0014229750e+01 Mg  3.5732788355e-01 0.0  1.5378986632e-02  7.5302070891e-03  4.9316602143e-03\natom  8.5554995015e+00  8.4581800115e+00  1.9975464100e+01 O  -3.9804842645e-01 0.0 -1.6267045339e-03  5.5855086624e-03 -2.9880579593e-03\natom  5.6128868647e+00  5.7702123737e+00  2.4038459730e+01 O  -3.4236199645e-01 0.0  5.8721058215e-03 -1.1863934324e-02 -4.3903044778e-03\natom  8.5499400033e+00  8.5334844394e+00  2.4018644441e+01 Mg  3.3380674355e-01 0.0  3.4899605326e-03  1.8911931185e-03  1.1734368968e-03\natom  5.7017798020e+00  5.7012317815e+00  2.8059735161e+01 Mg  3.3645926355e-01 0.0 -3.3667127605e-03  7.6094517555e-04  1.9156292578e-03\natom  8.4882934377e+00  8.5249537250e+00  2.8038408129e+01 O  -3.4302544645e-01 0.0  4.4242080960e-03 -1.1935372473e-04  2.8462877510e-03\natom  5.6930319392e+00  5.6564997941e+00  3.2064380550e+01 O  -3.4273845645e-01 0.0  1.3215307927e-03  2.8221791234e-03  1.5233349111e-03\natom  8.6013130547e+00  8.4654834434e+00  3.2149661408e+01 Mg  3.4147301355e-01 0.0 -7.6085133687e-03  5.3578953374e-03 -7.5219186642e-03\natom  5.6698810195e+00  5.6984872568e+00  3.6121875319e+01 Mg  3.3085534355e-01 0.0  4.7890471581e-03 -4.5750415924e-03 -2.0282595718e-03\natom  8.5731345001e+00  8.5653465802e+00  3.6093413967e+01 O  -3.4230469645e-01 0.0 -2.1781251950e-03 -1.3682465500e-03  1.4542478206e-03\natom  5.7231207611e+00  5.6266438810e+00  4.0130706659e+01 O  -4.0100549645e-01 0.0  2.2984056922e-03  5.1668762873e-03  9.2245030549e-03\natom  8.5398707684e+00  8.5722716323e+00  4.0138207076e+01 Mg  4.1835458355e-01 0.0  2.8219079682e-03 -3.0799335679e-03 -9.7518612451e-03\natom  5.6897350287e+00  1.1287088780e+01  1.9986056789e+01 Mg  4.2593918355e-01 0.0  2.2154721485e-03  1.2787952648e-02  5.5006732230e-03\natom  8.5014797566e+00  1.4232507301e+01  1.9989238880e+01 O  -4.0699202645e-01 0.0  2.2897126984e-03 -4.4288536798e-03 -4.3277701035e-03\natom  5.6772675804e+00  1.1410758288e+01  2.4068542259e+01 O  -3.4232459645e-01 0.0  1.5816885657e-03 -3.3504033204e-03 -2.6596208005e-03\natom  8.5257216152e+00  1.4257172137e+01  2.4060038908e+01 Mg  3.2852902355e-01 0.0  3.2099859776e-03 -4.0546341297e-03 -1.0541667409e-02\natom  5.6669319698e+00  1.1382919450e+01  2.8039536107e+01 Mg  3.4074732355e-01 0.0  3.8305534787e-03 -1.8034725359e-03  3.9833255406e-03\natom  8.5702007950e+00  1.4212623132e+01  2.8087268261e+01 O  -3.3871411645e-01 0.0 -3.1537896147e-03  3.9456786738e-03 -1.9625763759e-03\natom  5.7351511158e+00  1.1383034950e+01  3.2098280836e+01 O  -3.4174603645e-01 0.0 -5.6687530270e-03  5.2526489701e-05 -4.2887759202e-04\natom  8.5531064281e+00  1.4224072283e+01  3.2084772734e+01 Mg  3.3811067355e-01 0.0 -1.3782928023e-03  1.4746130817e-03  2.4194052312e-03\natom  5.7040498920e+00  1.1421448015e+01  3.6073607636e+01 Mg  3.3500091355e-01 0.0  2.0984444031e-03 -3.3124702586e-03  2.5971926328e-03\natom  8.5921869254e+00  1.4285756718e+01  3.6161009258e+01 O  -3.4357938645e-01 0.0 -6.1273849331e-03 -4.1999731854e-03 -4.0225129147e-03\natom  5.6494526469e+00  1.1349416725e+01  4.0115418757e+01 O  -3.9852446645e-01 0.0  6.6099311318e-03  5.9593493440e-03  8.4975649867e-03\natom  8.5127580760e+00  1.4280973538e+01  4.0170616689e+01 Mg  4.1849683355e-01 0.0  3.3539379170e-03 -4.2735171373e-03 -1.0140934717e-02\natom  1.1503079037e+01 -2.9005593172e-03  2.0027195028e+01 Mg  4.1231933355e-01 0.0 -1.3856179548e-02 -4.0647967304e-03  3.0002443930e-03\natom  1.4278510035e+01  2.8201391364e+00  2.0020431793e+01 O  -3.9317198645e-01 0.0  3.2625115751e-03  5.0074270623e-03 -5.9256679863e-03\natom  1.1428799408e+01 -8.9386703774e-02  2.3990967685e+01 O  -3.4378690645e-01 0.0 -1.7628599395e-03  1.0287285531e-02  9.3775199725e-03\natom  1.4307437412e+01  2.8362852198e+00  2.4074636342e+01 Mg  3.2986721355e-01 0.0 -8.8818952394e-03  1.7765005362e-03 -3.8234039155e-03\natom  1.1378663201e+01 -2.2873451236e-02  2.8050969837e+01 Mg  3.4294633355e-01 0.0  1.7383812333e-03  3.0233040383e-04  6.5518496528e-04\natom  1.4207826214e+01  2.8872592556e+00  2.8060677057e+01 O  -3.3827123645e-01 0.0  2.9094194407e-03 -7.4501523101e-03  1.1435628130e-03\natom  1.1367231890e+01 -1.4803886628e-02  3.2134362489e+01 O  -3.4147670645e-01 0.0  3.7289245635e-03  4.0700929157e-04 -7.8633171269e-03\natom  1.4231795971e+01  2.8493695692e+00  3.2072716585e+01 Mg  3.3806496355e-01 0.0  2.9092958286e-04 -7.5967046269e-04  3.7307053643e-03\natom  1.1393384960e+01 -2.3768406567e-02  3.6144033642e+01 Mg  3.3033745355e-01 0.0 -8.8224104013e-04  4.9790471739e-03 -4.6186099023e-03\natom  1.4280846360e+01  2.8701398310e+00  3.6025532100e+01 O  -3.4435678645e-01 0.0 -3.4262993178e-03 -3.2338524050e-03  8.1638060771e-03\natom  1.1375269518e+01  2.7470927799e-02  4.0154351666e+01 O  -3.9788842645e-01 0.0  4.3037020460e-03 -2.1944618745e-03  8.0293479822e-03\natom  1.4174365799e+01  2.8769983647e+00  4.0178208096e+01 Mg  4.1784188355e-01 0.0  1.0496187882e-02 -2.8408491133e-04 -1.1157000658e-02\natom  1.1432737295e+01  5.6814083291e+00  1.9948368170e+01 Mg  4.2623022355e-01 0.0 -4.6315052611e-03 -1.0715997269e-03  8.5433683660e-03\natom  1.4291761908e+01  8.5321860465e+00  1.9948330508e+01 O  -3.9849318645e-01 0.0 -5.4885361184e-03 -2.2562041728e-04 -3.0125354866e-03\natom  1.1417886410e+01  5.6984077372e+00  2.4033505946e+01 O  -3.4493466645e-01 0.0 -1.0087929891e-03 -1.7085357241e-03 -7.2138885991e-06\natom  1.4266684734e+01  8.5548006998e+00  2.3997279086e+01 Mg  3.3587914355e-01 0.0 -2.9977787177e-03 -9.2056415656e-04  3.6194052081e-03\natom  1.1438087298e+01  5.6906003342e+00  2.8103666490e+01 Mg  3.3798050355e-01 0.0 -4.7020892723e-03  4.8685280195e-03 -5.8302816993e-03\natom  1.4151474490e+01  8.5329003251e+00  2.8122663717e+01 O  -3.4394901645e-01 0.0  1.0376127435e-02  4.4197566084e-03 -4.4399083911e-03\natom  1.1456002845e+01  5.7131636625e+00  3.2101083866e+01 O  -3.3900734645e-01 0.0 -5.7799057587e-03 -2.2051036603e-03 -2.5745849891e-03\natom  1.4262311436e+01  8.5738364199e+00  3.2116664279e+01 Mg  3.4095148355e-01 0.0 -4.8847194674e-04 -2.3220974282e-03 -2.6408468875e-03\natom  1.1426030260e+01  5.7193594316e+00  3.6082076405e+01 Mg  3.3180955355e-01 0.0 -1.9206354443e-03 -4.0009018658e-03  1.7076461282e-03\natom  1.4286595417e+01  8.5881372615e+00  3.6108139676e+01 O  -3.4277923645e-01 0.0 -1.6997972870e-03 -1.2242781405e-03 -1.9658070469e-03\natom  1.1389447395e+01  5.6831719348e+00  4.0059185500e+01 O  -3.9747864645e-01 0.0  1.6034070177e-03  2.7676052305e-03  1.2029886385e-02\natom  1.4265684106e+01  8.5487766124e+00  4.0156994203e+01 Mg  4.1582491355e-01 0.0  7.3416773476e-04  1.8988530320e-03 -9.4079389515e-03\natom  1.1408257709e+01  1.1390199260e+01  1.9959488489e+01 Mg  4.2632962355e-01 0.0 -2.7670334935e-03  4.6945245185e-03  6.9095674848e-03\natom  1.4235338942e+01  1.4303460371e+01  1.9971663842e+01 O  -4.0200026645e-01 0.0  2.8192079753e-03 -7.0620993327e-03 -4.2794117056e-03\natom  1.1395398274e+01  1.1422592565e+01  2.4029541112e+01 O  -3.4364177645e-01 0.0  6.5570202040e-04 -5.2290697574e-03 -8.0168601548e-05\natom  1.4230375312e+01  1.4245631751e+01  2.4071077364e+01 Mg  3.2876661355e-01 0.0 -9.0173929015e-04 -2.6521721276e-03 -9.1696372817e-03\natom  1.1368846660e+01  1.1411699353e+01  2.8072679217e+01 Mg  3.3901107355e-01 0.0 -1.9512787892e-04 -5.6634667974e-03 -1.1591162072e-03\natom  1.4164285151e+01  1.4272533399e+01  2.8083177987e+01 O  -3.3849852645e-01 0.0  1.0316711895e-02 -2.4636398484e-03  2.6777598219e-04\natom  1.1372801781e+01  1.1412935196e+01  3.2104238102e+01 O  -3.3997604645e-01 0.0  4.2485643035e-03 -2.0290190913e-03 -7.3627135997e-04\natom  1.4283037648e+01  1.4203240113e+01  3.2112822372e+01 Mg  3.4423305355e-01 0.0 -6.4424583803e-03  5.2638647780e-03 -2.2596491575e-03\natom  1.1366237743e+01  1.1422217114e+01  3.6058137583e+01 Mg  3.2879373355e-01 0.0  3.2921788928e-03 -1.1460540821e-03  7.8352115473e-03\natom  1.4269337343e+01  1.4232338946e+01  3.6097479089e+01 O  -3.4082310645e-01 0.0  2.4899961592e-04  2.7736618824e-03 -5.1446225547e-04\natom  1.1399041194e+01  1.1415817954e+01  4.0091911208e+01 O  -4.0162039645e-01 0.0 -1.3461300050e-03 -5.1616905835e-04  1.0961979452e-02\natom  1.4275929538e+01  1.4259725951e+01  4.0146048362e+01 Mg  4.1431264355e-01 0.0 -2.5272060282e-03 -8.0647271399e-04 -6.6312116079e-03\natom  2.9139834771e+00  3.0410394685e+00  1.6211244430e+01 Au  1.5079824355e-01 0.0 -1.4390999346e-03 -5.7763432565e-03 -4.0734666476e-02\natom  2.8474291608e+00  2.5535179613e+00  1.1465988573e+01 Au -1.6489738645e-01 0.0  3.4132132328e-04  2.9511590689e-03  7.3990347458e-04\nenergy -5.4268562615e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -9.0122355205e-03 -3.5348496247e-02  1.9988606899e+01 Mg  4.1528052045e-01 0.0  1.1588046216e-04  4.7520797802e-03  9.0422542439e-03\natom  2.8256066617e+00  2.8261349346e+00  1.9999419193e+01 O  -3.9991345955e-01 0.0 -1.2109301530e-03  1.3667316886e-03 -7.4381062921e-03\natom -2.1671566610e-02 -1.9670365685e-02  2.4092588663e+01 O  -3.4141720955e-01 0.0 -1.2302242544e-03  4.0379383217e-04 -7.3811974520e-03\natom  2.8010158086e+00  2.8589275576e+00  2.4049827037e+01 Mg  3.3272377045e-01 0.0  4.6167330187e-03 -2.3713800050e-03 -3.2548865366e-06\natom  4.4046602616e-02 -3.6036696657e-03  2.8053107042e+01 Mg  3.3752065045e-01 0.0 -3.7158815669e-03 -3.1301684828e-03  4.4087505493e-03\natom  2.8500886855e+00  2.7605349489e+00  2.8047270812e+01 O  -3.4259661955e-01 0.0  1.6666103127e-03  1.1198277389e-02  2.2288409175e-03\natom  4.0519674723e-02 -6.5351071056e-02  3.2117832470e+01 O  -3.4281615955e-01 0.0 -5.9016576590e-03  5.2054900909e-03 -4.3614702773e-03\natom  2.8763433101e+00  2.8339343062e+00  3.2114245789e+01 Mg  3.4094982045e-01 0.0 -3.9544548876e-03 -4.2817061881e-03 -9.9563476536e-04\natom -6.7640190632e-02 -9.8237084264e-02  3.6163098123e+01 Mg  3.2795234045e-01 0.0  7.3544993962e-03  7.1641123116e-03 -7.5483705881e-03\natom  2.8042385095e+00  2.7976096342e+00  3.6106519160e+01 O  -3.4172254955e-01 0.0  5.0670575177e-03  2.2070661317e-03  1.6248957339e-03\natom -1.5891121578e-02  8.6335967933e-02  4.0105847767e+01 O  -3.9866190955e-01 0.0  5.2061101790e-04 -1.1317769682e-02  1.0676179594e-02\natom  2.8119690195e+00  2.8163479115e+00  4.0129119384e+01 Mg  4.1330029045e-01 0.0  2.3671999599e-03  6.5294666763e-03 -5.1909507928e-03\natom -1.8688842007e-02  5.6967515813e+00  1.9992421840e+01 Mg  4.0750677045e-01 0.0 -4.8876138494e-04 -7.5690830036e-04  6.4697616588e-03\natom  2.7855255357e+00  8.5731407740e+00  2.0009404373e+01 O  -3.9239647955e-01 0.0  6.1091610015e-03 -2.5788990582e-03 -8.0765671716e-03\natom -1.0206160621e-01  5.6641421862e+00  2.4005538738e+01 O  -3.4166125955e-01 0.0  9.6231892452e-03  3.8504350099e-03  2.3138287013e-03\natom  2.8939446526e+00  8.5668883888e+00  2.4005672663e+01 Mg  3.4039539045e-01 0.0 -5.4973764290e-03 -3.8217176932e-03  2.0368155250e-04\natom -9.6225111901e-02  5.7074977916e+00  2.8011644110e+01 Mg  3.4026578045e-01 0.0  1.2901637795e-02 -4.7308284382e-03  3.6764578745e-03\natom  2.9067830352e+00  8.5396338346e+00  2.8068138659e+01 O  -3.3781401955e-01 0.0 -4.7570529299e-03 -1.4734704862e-03 -4.6685539921e-03\natom  2.1205635770e-02  5.6793074829e+00  3.2111538548e+01 O  -3.3979818955e-01 0.0  2.9001768341e-04  1.4846946798e-03 -6.8925253427e-03\natom  2.8459597098e+00  8.5130345618e+00  3.2064608923e+01 Mg  3.4191052045e-01 0.0 -3.5340864343e-06  4.9838373120e-03  6.9880215070e-03\natom  3.8100938841e-02  5.6260687051e+00  3.6082861926e+01 Mg  3.2806051045e-01 0.0 -6.1245790762e-03  4.6035380754e-03  4.4995082539e-03\natom  2.8403296303e+00  8.4697157493e+00  3.6128130690e+01 O  -3.4403414955e-01 0.0  1.3959119027e-03  4.3237621866e-03 -2.5391165422e-03\natom -2.8023219116e-02  5.6800132011e+00  4.0149392610e+01 O  -4.0178783955e-01 0.0  1.6185294182e-03  3.0699373462e-03  6.4205007890e-03\natom  2.8050533972e+00  8.5690979509e+00  4.0191886632e+01 Mg  4.1188474045e-01 0.0  2.9762450265e-03 -4.9153661732e-03 -9.6415508780e-03\natom -1.4401639554e-02  1.1409562167e+01  2.0022653015e+01 Mg  3.9094584045e-01 0.0  1.9258726236e-03 -2.7958371244e-03  6.5924378675e-03\natom  2.8225841773e+00  1.4235052025e+01  2.0062197062e+01 O  -3.9071755955e-01 0.0 -1.3908822884e-03  1.5050459181e-03 -1.2303778914e-02\natom -3.7681041726e-02  1.1436463059e+01  2.4042726958e+01 O  -3.4225408955e-01 0.0  3.8705459455e-03 -6.5214027445e-03  1.8650696909e-04\natom  2.8780386967e+00  1.4294257688e+01  2.4029831147e+01 Mg  3.2590275045e-01 0.0 -5.0191603986e-03 -8.3476046609e-04  3.7306171958e-03\natom  5.6312379371e-02  1.1372432775e+01  2.8042645065e+01 Mg  3.4212543045e-01 0.0 -1.8879441079e-03  5.4159851596e-03  2.7897321938e-03\natom  2.8757419993e+00  1.4256808195e+01  2.8029084032e+01 O  -3.4140415955e-01 0.0 -1.5783810264e-03 -5.6226098411e-03  1.3617866526e-03\natom -1.0121126731e-02  1.1403365227e+01  3.2106008870e+01 O  -3.4104306955e-01 0.0  2.7709014572e-03 -4.1681859361e-03 -4.0365277428e-03\natom  2.8676350559e+00  1.4241144067e+01  3.2067324818e+01 Mg  3.3729629045e-01 0.0 -1.7135550322e-04 -2.5475211027e-03  4.6380515837e-03\natom -7.5395909548e-03  1.1329832530e+01  3.6146539569e+01 Mg  3.3149169045e-01 0.0  2.3474856443e-03  1.7705953013e-03 -2.9425421393e-03\natom  2.8509737009e+00  1.4203083587e+01  3.6135229144e+01 O  -3.4439847955e-01 0.0 -1.1798723417e-04  3.3733697707e-04  3.1062589309e-04\natom  9.3369471371e-03  1.1411425626e+01  4.0120307535e+01 O  -3.9898106955e-01 0.0 -1.8048060668e-03  4.2243554449e-04  1.1183571617e-02\natom  2.8696079865e+00  1.4261189449e+01  4.0114495871e+01 Mg  4.1601431045e-01 0.0 -2.9053766877e-03 -3.3039800700e-03 -7.4852000362e-03\natom  5.6303914911e+00  1.3346567740e-03  1.9997709747e+01 Mg  4.0521051045e-01 0.0  8.0406107097e-03  1.3978926636e-03  7.4226062632e-03\natom  8.5319215983e+00  2.8858527325e+00  2.0028394154e+01 O  -4.0203257955e-01 0.0  1.6184156858e-03 -4.0029841118e-03 -8.7844949964e-03\natom  5.6590362600e+00 -1.0764408354e-02  2.4000955340e+01 O  -3.4527681955e-01 0.0  2.9946551084e-03  6.0768928089e-04  3.4377300808e-03\natom  8.5463670228e+00  2.8858193033e+00  2.4024445295e+01 Mg  3.2850052045e-01 0.0 -3.5668428143e-03 -6.8773842901e-03  1.0044615675e-03\natom  5.6816059377e+00 -2.9851850264e-02  2.8109417229e+01 Mg  3.4362162045e-01 0.0  2.5938179125e-03  1.6528862588e-03 -4.0258677439e-03\natom  8.6179792851e+00  2.9177589228e+00  2.8075603549e+01 O  -3.4131615955e-01 0.0 -9.1795894619e-03 -6.2870053238e-03 -1.0200775520e-04\natom  5.6571303579e+00 -4.8897226873e-02  3.2154948672e+01 O  -3.4115885955e-01 0.0  5.4413129601e-03  6.8913025879e-03 -7.0947018787e-03\natom  8.5850680630e+00  2.8582764903e+00  3.2096016131e+01 Mg  3.4069359045e-01 0.0 -3.3217051471e-03 -1.5384099913e-03  3.2766687395e-03\natom  5.6814082535e+00  1.1829420127e-02  3.6151105412e+01 Mg  3.2815838045e-01 0.0 -6.5517443812e-04 -2.2621211980e-03 -6.0754562256e-03\natom  8.5248747534e+00  2.8607721947e+00  3.6126519434e+01 O  -3.4289257955e-01 0.0 -4.2505805156e-04 -4.8556604769e-04 -2.5548110567e-03\natom  5.7108116151e+00 -1.6585690365e-02  4.0089901503e+01 O  -3.9583655955e-01 0.0 -5.2677324998e-03  1.6894768689e-03  1.2165753788e-02\natom  8.5552699376e+00  2.8187192908e+00  4.0123769815e+01 Mg  4.0628130045e-01 0.0  2.9061744359e-04  6.6196684405e-03 -4.3852401338e-03\natom  5.7082740532e+00  5.6483566058e+00  1.9990787303e+01 Mg  4.0554866045e-01 0.0  7.3030332540e-04  3.9974037036e-03  5.5643318461e-03\natom  8.6349479852e+00  8.5096651993e+00  1.9981624361e+01 O  -3.9825333955e-01 0.0 -7.8808973024e-03  4.5984837691e-03  1.2387789751e-03\natom  5.7031247389e+00  5.6434547889e+00  2.3989637431e+01 O  -3.4340867955e-01 0.0 -3.9022367276e-03  9.4598788920e-03  5.7914512113e-03\natom  8.6152168081e+00  8.5093449663e+00  2.4019924277e+01 Mg  3.3550128045e-01 0.0 -5.4002247874e-03  5.1356365996e-04 -1.3540958619e-03\natom  5.6993539986e+00  5.7693321015e+00  2.8150679396e+01 Mg  3.4661724045e-01 0.0  4.0368714548e-04 -1.1474283114e-02 -8.5677149101e-03\natom  8.5763339384e+00  8.6208555237e+00  2.8082488652e+01 O  -3.3846525955e-01 0.0 -9.5914868926e-04 -6.7048285827e-03 -4.8866502010e-03\natom  5.6802746447e+00  5.7043475995e+00  3.2089218881e+01 O  -3.3843161955e-01 0.0  1.7674106476e-03 -9.1704997540e-04 -1.0337353631e-03\natom  8.5107049454e+00  8.6051437371e+00  3.2067763235e+01 Mg  3.4024414045e-01 0.0  4.7303869900e-03 -1.1513763351e-03  5.4715673213e-03\natom  5.6616847865e+00  5.6571396743e+00  3.6122706421e+01 Mg  3.3436294045e-01 0.0  1.8792874887e-03  3.4465154436e-03  2.9558254090e-03\natom  8.5845868821e+00  8.5179843022e+00  3.6118755552e+01 O  -3.4260961955e-01 0.0 -6.5207817176e-03  5.1457282222e-03 -3.3745081211e-03\natom  5.6980647708e+00  5.7327148999e+00  4.0199064152e+01 O  -4.0401073955e-01 0.0 -3.7563809204e-03 -7.2462183889e-03  3.0114829101e-03\natom  8.4995422962e+00  8.5088940966e+00  4.0096368505e+01 Mg  4.0409884045e-01 0.0  3.7868941441e-03  2.2415869379e-03 -2.4654290500e-03\natom  5.7098352126e+00  1.1442260417e+01  2.0018603578e+01 Mg  3.2795541045e-01 0.0  2.9731691830e-03 -4.6089816390e-03 -2.2272346470e-03\natom  8.5206538047e+00  1.4294357277e+01  1.9990607779e+01 O  -3.9755232955e-01 0.0  2.6624252601e-03 -3.7515155346e-03  6.7723372273e-04\natom  5.6179636892e+00  1.1412629212e+01  2.4009248270e+01 O  -3.3797138955e-01 0.0  8.8211122236e-03 -5.4660853473e-03 -1.3361329992e-04\natom  8.4822322171e+00  1.4154926245e+01  2.4029485062e+01 Mg  3.3473715045e-01 0.0  4.7608874210e-03  1.3303081774e-02  1.3837623361e-03\natom  5.7308746469e+00  1.1310762909e+01  2.7970603325e+01 Mg  3.3886830045e-01 0.0 -5.0972710532e-04  1.3523665976e-02  1.1412595284e-02\natom  8.5413020280e+00  1.4249993163e+01  2.8064919341e+01 O  -3.4237566955e-01 0.0 -1.6259455224e-04  6.8157727903e-04 -3.3656461213e-03\natom  5.7309744434e+00  1.1420235850e+01  3.2076912305e+01 O  -3.4282625955e-01 0.0 -3.9917432569e-03 -4.0562838843e-03  2.2180838755e-04\natom  8.5961638726e+00  1.4293727639e+01  3.2112299995e+01 Mg  3.3348841045e-01 0.0 -8.6087770355e-03 -5.5031219283e-03 -9.7990200498e-04\natom  5.7321434468e+00  1.1400236143e+01  3.6124856230e+01 Mg  3.3663196045e-01 0.0 -3.9657909031e-03 -1.6414129477e-03 -1.6169476632e-03\natom  8.5481924225e+00  1.4302434816e+01  3.6146499016e+01 O  -3.4176557955e-01 0.0  3.5969533802e-04 -5.6300764879e-03 -8.8889112065e-04\natom  5.6843823799e+00  1.1339270559e+01  4.0120038305e+01 O  -4.0049179955e-01 0.0  8.7235075545e-04  7.1864733158e-03  8.3665517143e-03\natom  8.4795287185e+00  1.4315070620e+01  4.0143339043e+01 Mg  4.1182007045e-01 0.0  7.1309458195e-03 -7.9385897647e-03 -6.0019069710e-03\natom  1.1428575343e+01 -2.9497205388e-02  2.0052577431e+01 Mg  4.0229719045e-01 0.0 -7.5468114593e-03  4.1502910575e-03  3.0379444228e-03\natom  1.4272355764e+01  2.8694982312e+00  1.9993648461e+01 O  -4.0103270955e-01 0.0 -3.2895087280e-03 -4.1860271951e-03 -6.0164988077e-03\natom  1.1378659648e+01  3.5681220302e-02  2.4019142573e+01 O  -3.4421057955e-01 0.0  3.3241447301e-03 -4.9732063293e-03  2.6957225565e-03\natom  1.4237797381e+01  2.8042431016e+00  2.4034034105e+01 Mg  3.3226764045e-01 0.0 -1.6817157984e-03  1.6769764563e-03  6.3688128404e-04\natom  1.1357379406e+01  1.8189557503e-03  2.8079694371e+01 Mg  3.4662977045e-01 0.0  3.3556845669e-03 -1.8283011343e-03 -2.0937591639e-03\natom  1.4314245604e+01  2.8949108317e+00  2.8098145713e+01 O  -3.4021643955e-01 0.0 -7.5412231953e-03 -7.1963748000e-03 -4.5396758870e-03\natom  1.1311712609e+01 -3.5724381643e-02  3.2115246040e+01 O  -3.4085667955e-01 0.0  1.0680122702e-02  4.9001271873e-03 -3.6452806544e-03\natom  1.4291246788e+01  2.9011452456e+00  3.2009262893e+01 Mg  3.4511452045e-01 0.0 -2.6305967016e-03 -6.8717171390e-03  1.1678662651e-02\natom  1.1402812558e+01 -5.4316110631e-02  3.6130629475e+01 Mg  3.3550127045e-01 0.0 -1.0879676405e-03  8.7537711833e-03 -1.4853329582e-04\natom  1.4252482555e+01  2.8664598164e+00  3.6094006604e+01 O  -3.4448624955e-01 0.0 -3.2205859183e-03 -4.1976074467e-03 -3.0645876670e-03\natom  1.1350162675e+01  3.4504658004e-02  4.0190285751e+01 O  -4.0147280955e-01 0.0  4.7299739741e-03 -3.7622865228e-03  3.5460003408e-03\natom  1.4266374517e+01  2.8473148134e+00  4.0048817859e+01 Mg  3.9880159045e-01 0.0 -5.5454187805e-03  4.4900668344e-03 -1.3278368666e-03\natom  1.1368090014e+01  5.6893206307e+00  1.9999031459e+01 Mg  4.0607072045e-01 0.0  2.1307611536e-03  1.6092753270e-04  3.9710818322e-03\natom  1.4268166166e+01  8.5776908562e+00  2.0009319826e+01 O  -3.9685348955e-01 0.0 -1.4361663893e-03 -1.8254018224e-03 -5.3841938818e-03\natom  1.1340313971e+01  5.7054995575e+00  2.4074845213e+01 O  -3.4164131955e-01 0.0  7.6789475851e-03  4.3894483655e-04 -1.9320950044e-03\natom  1.4239768611e+01  8.5152002256e+00  2.4018752817e+01 Mg  3.3453935045e-01 0.0  6.0192498939e-04  1.1499489065e-03  1.1073422913e-03\natom  1.1359388242e+01  5.6864357939e+00  2.8078984420e+01 Mg  3.3691217045e-01 0.0  3.6955313872e-03  1.8984648405e-03 -2.8175640961e-04\natom  1.4348954409e+01  8.5035741966e+00  2.8076627667e+01 O  -3.3894875955e-01 0.0 -9.6406373340e-03  5.7598439718e-03 -2.7374487315e-03\natom  1.1371531130e+01  5.6627712467e+00  3.2030787968e+01 O  -3.4169465955e-01 0.0  3.0165852076e-03  6.2446020053e-03  2.5431059279e-03\natom  1.4300391569e+01  8.5506382948e+00  3.2029341912e+01 Mg  3.4458036045e-01 0.0 -5.3670481616e-03  8.6879801964e-05  1.0177124218e-02\natom  1.1339462196e+01  5.7591645442e+00  3.6096987647e+01 Mg  3.3018682045e-01 0.0  7.2105424622e-03 -6.1439005085e-03  4.5167546119e-04\natom  1.4232513084e+01  8.5403920682e+00  3.6092819497e+01 O  -3.4473540955e-01 0.0  1.4305758910e-03  9.2843277000e-04 -3.8940645037e-04\natom  1.1359236251e+01  5.6844077778e+00  4.0115158334e+01 O  -4.0290735955e-01 0.0  2.7641230562e-03  2.9262097253e-03  7.1307769354e-03\natom  1.4231510414e+01  8.5501017260e+00  4.0155712666e+01 Mg  4.1567945045e-01 0.0 -1.9921413427e-03 -2.8580745171e-03 -9.4478581390e-03\natom  1.1453753882e+01  1.1426742422e+01  2.0035623546e+01 Mg  3.4075022045e-01 0.0 -8.1213726736e-03 -4.4166402091e-03 -3.3321079330e-03\natom  1.4259339313e+01  1.4215458590e+01  1.9992911298e+01 O  -3.9079380955e-01 0.0 -4.8482409353e-05  3.7968409454e-03 -5.8067396070e-03\natom  1.1383896363e+01  1.1403384956e+01  2.4096318964e+01 O  -3.3876419955e-01 0.0  1.3373384451e-03 -1.8879100056e-03 -6.0889505397e-03\natom  1.4271767852e+01  1.4188949760e+01  2.4034982124e+01 Mg  3.3389163045e-01 0.0 -2.9443420889e-03  6.7476718181e-03  6.2607706503e-03\natom  1.1464617312e+01  1.1411772637e+01  2.8076399993e+01 Mg  3.4097144045e-01 0.0 -5.0636487662e-03  1.4150597466e-03  3.3254503758e-03\natom  1.4233233863e+01  1.4199979353e+01  2.8106859579e+01 O  -3.4219358955e-01 0.0  2.0615140784e-03  4.5231352404e-03 -3.6193633372e-03\natom  1.1344354527e+01  1.1431348100e+01  3.2131869695e+01 O  -3.4132420955e-01 0.0  7.6773889157e-03 -3.5144366822e-03 -4.4733027081e-03\natom  1.4260904648e+01  1.4242372994e+01  3.2116119660e+01 Mg  3.3991059045e-01 0.0  6.2562955732e-04  5.2182017450e-04 -1.5408463441e-03\natom  1.1409689119e+01  1.1430783582e+01  3.6123520968e+01 Mg  3.3148436045e-01 0.0 -4.3350452055e-05 -3.6017592060e-03  1.1523290899e-03\natom  1.4280470361e+01  1.4250383486e+01  3.6130065014e+01 O  -3.4072485955e-01 0.0 -5.4508873152e-03 -1.4507826664e-03  5.1672538063e-04\natom  1.1418820899e+01  1.1456792958e+01  4.0115306224e+01 O  -4.0257104955e-01 0.0 -2.8063280684e-03 -3.6696138072e-03  8.8852971525e-03\natom  1.4220154692e+01  1.4241564078e+01  4.0196552290e+01 Mg  4.1972999045e-01 0.0  5.6574083544e-05  1.4235103246e-03 -7.9676201486e-03\natom  1.0949516407e+01  1.1867959709e+01  1.3855916810e+01 Au  6.9385870455e-02 0.0 -6.2161971783e-03 -6.2774081525e-04  3.1266922060e-03\natom  6.1430573899e+00  1.1236775506e+01  1.4221991694e+01 Au  8.6949590455e-02 0.0  5.7357437773e-03  1.8256564764e-04  2.2698608339e-03\nenergy -5.4268535427e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom  5.9682157651e-02  4.0180034271e-02  2.0088031090e+01 Mg  3.6701654527e-01 0.0 -8.8213789601e-03 -7.4220721822e-03 -1.7891076419e-02\natom  2.8498372953e+00  2.7842315459e+00  2.0046207901e+01 O  -3.5666185473e-01 0.0  1.0622202285e-03  6.1361169917e-03  6.9180219298e-03\natom -2.8067892239e-02 -8.7268491017e-03  2.4025901027e+01 O  -3.3854450473e-01 0.0  3.6761043983e-03 -2.1487061839e-04  1.4259781508e-02\natom  2.8508203685e+00  2.7850938089e+00  2.4052629992e+01 Mg  3.3147829527e-01 0.0  4.7976885854e-03  8.8867147153e-03 -7.1941501619e-03\natom -1.4790658546e-02  5.8608283064e-02  2.8046584766e+01 Mg  3.4257489527e-01 0.0 -3.2899176193e-03 -5.6777252339e-03 -1.1091612667e-02\natom  2.7942332608e+00  2.8533815709e+00  2.8033104859e+01 O  -3.3901685473e-01 0.0  5.3993322043e-03 -7.4656835106e-04  1.5038305622e-02\natom  2.7367786555e-02 -7.5154969484e-03  3.2094848167e+01 O  -3.0953390473e-01 0.0 -1.3488016936e-03 -1.5507226564e-03  2.4438868472e-02\natom  2.8198898249e+00  2.7958994322e+00  3.2071713745e+01 Mg  3.3156337527e-01 0.0  4.8240016687e-04  6.0083310556e-03 -1.0487221691e-02\natom  1.0401881431e-01 -6.7479469437e-03  3.6094918983e+01 Al  4.0340281527e-01 0.0 -1.2218412951e-02  6.9754153965e-03  7.7596939685e-03\natom  2.8316087716e+00  2.8678391652e+00  3.6097772337e+01 O  -2.8974236473e-01 0.0 -1.3010426211e-04 -3.8660625818e-03 -6.4131120225e-03\natom -2.1792924813e-02  2.7336020261e-02  4.0106496510e+01 O  -3.6120891473e-01 0.0  4.5045221845e-03 -3.2227182113e-03 -2.4571692686e-02\natom  2.7829918478e+00  2.8811832574e+00  4.0091631680e+01 Mg  3.7492828527e-01 0.0  6.8409093999e-03 -6.2867147293e-05  1.6875796246e-02\natom  4.3829321922e-02  5.6577298735e+00  2.0011507695e+01 Mg  3.7855327527e-01 0.0 -6.0144789288e-03  5.7912723922e-03 -9.7708631459e-03\natom  2.8776280592e+00  8.5447598297e+00  2.0032079875e+01 O  -3.9792305473e-01 0.0 -5.2806128302e-03  1.4886968791e-03  1.8942646331e-03\natom  6.0962069063e-02  5.6662842095e+00  2.4006448811e+01 O  -3.4265166473e-01 0.0 -3.2628447532e-03  1.7881086185e-03  1.3534822985e-02\natom  2.8609632460e+00  8.5934528150e+00  2.3979960050e+01 Mg  3.3142194527e-01 0.0  4.4642815994e-03 -7.6158827633e-03 -9.3724950153e-03\natom  3.4804425237e-02  5.7059590255e+00  2.8039572635e+01 Mg  3.4094222527e-01 0.0 -4.7496419111e-03  1.2272966072e-03 -8.6217746338e-03\natom  2.8326371038e+00  8.5934260187e+00  2.8048368289e+01 O  -3.3843965473e-01 0.0  2.5039092843e-03 -3.7509803235e-03  9.7988058898e-03\natom  3.4309014672e-02  5.6470647513e+00  3.2092670012e+01 O  -3.4773051473e-01 0.0  2.2603955841e-03  5.0888160920e-03  4.0151946174e-03\natom  2.8924030330e+00  8.5443812609e+00  3.2071688404e+01 Mg  3.3281986527e-01 0.0 -1.0337905575e-02  4.2737555318e-03 -8.7174265705e-03\natom  6.6144302437e-02  5.7855169999e+00  3.6120837595e+01 Mg  3.2207555527e-01 0.0 -1.5704646325e-02 -6.6945786124e-03  2.4741424808e-03\natom  2.7740494566e+00  8.5641496278e+00  3.6125190012e+01 O  -3.1247347473e-01 0.0  2.0142767175e-02 -9.0942003971e-03 -7.7675505065e-03\natom -3.1787761156e-02  5.7289492051e+00  4.0185631016e+01 O  -4.0521903473e-01 0.0  6.3624118324e-03 -1.1330183231e-03 -8.5938340041e-03\natom  2.8905886693e+00  8.6022488470e+00  4.0102478178e+01 Mg  3.8402979527e-01 0.0 -8.8768022758e-03 -1.7599943514e-03  1.6724937034e-02\natom  3.1763893916e-02  1.1426334241e+01  1.9995733509e+01 Mg  4.3181196527e-01 0.0 -3.7755766154e-03 -2.8181308421e-03 -6.0132702851e-03\natom  2.8455566313e+00  1.4246246932e+01  1.9957668948e+01 O  -3.9710066473e-01 0.0 -1.7246052580e-03 -2.8808719234e-04  1.0329217637e-02\natom -5.6630703714e-02  1.1397909531e+01  2.4020284875e+01 O  -3.3823040473e-01 0.0  7.1505223399e-03  2.2456478050e-03  1.2571250558e-02\natom  2.7832598488e+00  1.4232395411e+01  2.4073819017e+01 Mg  3.3513914527e-01 0.0  8.7459637973e-03  6.9268300996e-04 -1.7778952703e-02\natom  4.4061172404e-02  1.1402505364e+01  2.8000538909e+01 Mg  3.3671687527e-01 0.0 -7.7782979409e-03 -2.4326829407e-04 -6.1370001031e-04\natom  2.8012345444e+00  1.4254350134e+01  2.8063492768e+01 O  -3.3808794473e-01 0.0  1.5712530597e-03 -1.2775266672e-04  1.0095187898e-02\natom -2.8770624642e-02  1.1373718223e+01  3.2072854308e+01 O  -3.4702882473e-01 0.0  4.5694469086e-03  3.9561966806e-03  8.3902599297e-03\natom  2.8585561319e+00  1.4239117468e+01  3.2111930270e+01 Mg  3.3595555527e-01 0.0  1.7868775356e-03 -5.4236302583e-03 -1.3190620719e-02\natom  4.7585492475e-02  1.1505781383e+01  3.6109358644e+01 Mg  3.2060672527e-01 0.0 -7.0857201630e-03 -1.0341143439e-02  4.5624059385e-03\natom  2.8781812009e+00  1.4276408924e+01  3.6096454801e+01 O  -3.0985723473e-01 0.0 -1.4568116556e-02  1.2609936566e-02 -5.3090832257e-03\natom  4.3989816350e-02  1.1429007542e+01  4.0109997813e+01 O  -4.0840762473e-01 0.0 -2.4486720486e-03  2.5581361365e-03 -6.1953514156e-03\natom  2.9274548234e+00  1.4280551733e+01  4.0137100207e+01 Mg  3.9127756527e-01 0.0 -4.2392545163e-03 -2.7624517317e-03  1.1894745166e-02\natom  5.6490666326e+00  2.7880752674e-02  1.9987788799e+01 Mg  3.7943893527e-01 0.0  9.1344901745e-03 -4.7939782354e-03 -8.6721764071e-03\natom  8.5745213322e+00  2.9028922028e+00  2.0010633621e+01 O  -3.9913059473e-01 0.0 -9.2713861158e-04 -5.9453605335e-03  3.7899455678e-03\natom  5.6728296912e+00 -1.5544319064e-03  2.4082192279e+01 O  -3.4297127473e-01 0.0  7.4967763051e-04 -1.4920697472e-03  6.3605410427e-03\natom  8.5520054738e+00  2.8803398538e+00  2.4007295257e+01 Mg  3.2802547527e-01 0.0  7.2287473711e-04  3.7053584530e-04 -7.7890188557e-03\natom  5.6306459049e+00 -5.1622929844e-02  2.8070540539e+01 Mg  3.3961936527e-01 0.0  9.8456830766e-03  5.1788485747e-03 -1.2392088470e-02\natom  8.5691262779e+00  2.9460896948e+00  2.8015565481e+01 O  -3.4346220473e-01 0.0 -3.4047813249e-03 -8.4678568022e-03  1.6638712820e-02\natom  5.7191205135e+00  8.6655274933e-04  3.2074388520e+01 O  -3.4370103473e-01 0.0 -6.2686792565e-03  1.5810026232e-03  5.1786481458e-03\natom  8.5542177382e+00  2.8585459274e+00  3.2036623480e+01 Mg  3.3659410527e-01 0.0  4.0898815704e-03 -4.1034103806e-03 -5.2821930591e-03\natom  5.7043622449e+00  3.4158309025e-03  3.6060635763e+01 Mg  3.1910940527e-01 0.0  8.8707906548e-03  2.5703293557e-03  9.0437311917e-03\natom  8.5976017084e+00  2.8309619184e+00  3.6125944088e+01 O  -3.2195366473e-01 0.0 -1.7527145249e-02  1.6200318111e-02 -1.1416451275e-02\natom  5.7001706625e+00  3.0745048150e-02  4.0091838586e+01 O  -4.0556599473e-01 0.0 -4.2277350789e-03 -2.8319782382e-03 -3.7162613032e-03\natom  8.5623380231e+00  2.8585319246e+00  4.0135310844e+01 Mg  3.8337685527e-01 0.0  2.8550254756e-03 -4.5367453875e-03  6.9893595788e-03\natom  5.7064886590e+00  5.7265240631e+00  2.0038440939e+01 Mg  3.7815509527e-01 0.0  4.0116133615e-03  1.4559840737e-03 -8.9603879077e-03\natom  8.5028472569e+00  8.5606800909e+00  2.0025290732e+01 O  -4.0031129473e-01 0.0  6.3117089200e-03  1.6025988589e-03 -2.3286990274e-04\natom  5.7983029993e+00  5.7020140902e+00  2.4004953509e+01 O  -3.4680753473e-01 0.0 -1.2451140144e-02 -3.9994406815e-04  1.5076153664e-02\natom  8.5935899146e+00  8.5783715544e+00  2.4035681474e+01 Mg  3.2523562527e-01 0.0 -5.2699776546e-03 -4.5797576401e-03 -1.1399789141e-02\natom  5.6727531195e+00  5.7289433092e+00  2.8127873446e+01 Mg  3.4350237527e-01 0.0  5.7776458030e-03 -1.6348991592e-03 -2.7110448686e-02\natom  8.5340796275e+00  8.5508846584e+00  2.8043084332e+01 O  -3.4198000473e-01 0.0  8.0472044325e-04  1.9543782149e-03  1.7038434161e-02\natom  5.7051456308e+00  5.7205811961e+00  3.2103294127e+01 O  -3.0818264473e-01 0.0  3.4748942178e-05 -2.3403094746e-03  2.2097159561e-02\natom  8.6007055078e+00  8.5154784877e+00  3.2086305359e+01 Mg  3.3400827527e-01 0.0 -9.4616975272e-04  5.5594295454e-03 -1.5802646846e-02\natom  5.6887147090e+00  5.7827307690e+00  3.6098666328e+01 Al  3.9807951527e-01 0.0  5.7075754066e-03 -1.3314724329e-02  9.4019059738e-03\natom  8.5500086948e+00  8.4928963188e+00  3.6079527032e+01 O  -2.8789797473e-01 0.0 -4.7535107017e-03  2.6711626204e-03 -2.8236980491e-03\natom  5.6956831680e+00  5.6389706581e+00  4.0156876246e+01 O  -3.6318570473e-01 0.0 -2.5251488513e-03  8.2857950753e-03 -2.4805432991e-02\natom  8.5336572360e+00  8.5153197507e+00  4.0138586552e+01 Mg  3.7740215527e-01 0.0  5.1488735042e-03 -2.4890623358e-03  1.5772215130e-02\natom  5.7083916887e+00  1.1446560206e+01  2.0008184441e+01 Mg  4.2109329527e-01 0.0  6.5850885052e-04 -3.6270413382e-03 -4.1805854814e-03\natom  8.5261478618e+00  1.4226273303e+01  1.9973537544e+01 O  -4.0128542473e-01 0.0  4.0127898679e-03  5.8128588407e-03  4.9670093403e-03\natom  5.7105713931e+00  1.1382297163e+01  2.3967104092e+01 O  -3.4338074473e-01 0.0 -5.0655745109e-03  5.1978605926e-03  1.9746761531e-02\natom  8.5923108536e+00  1.4248839334e+01  2.4000285678e+01 Mg  3.3535788527e-01 0.0 -4.6922391374e-03  1.7443802900e-04 -9.4042300563e-03\natom  5.6416262144e+00  1.1420125717e+01  2.8058730639e+01 Mg  3.4090222527e-01 0.0  1.0068609521e-02 -2.0166549659e-03 -1.1406298427e-02\natom  8.5162808276e+00  1.4238345251e+01  2.8052109361e+01 O  -3.4290617473e-01 0.0  2.5736377216e-03  9.3787378841e-04  1.1466617867e-02\natom  5.7174908138e+00  1.1357584725e+01  3.2135052825e+01 O  -3.4580659473e-01 0.0 -1.5501769064e-03  1.6246633736e-03  4.2142606398e-03\natom  8.5813056752e+00  1.4252808987e+01  3.2136194314e+01 Mg  3.3350482527e-01 0.0 -5.5868859013e-03  2.3721511122e-03 -1.1503479797e-02\natom  5.6613700527e+00  1.1318600755e+01  3.6149955778e+01 Mg  3.2212799527e-01 0.0  5.6848996093e-03  1.1243661706e-02 -1.3176892728e-03\natom  8.5042630585e+00  1.4288656692e+01  3.6135882460e+01 O  -3.1980974473e-01 0.0  1.4750175651e-02 -1.7450957209e-02 -7.3729721798e-03\natom  5.7420146005e+00  1.1345643093e+01  4.0108716919e+01 O  -4.0108022473e-01 0.0 -1.8456861010e-03  2.1715138623e-03 -5.3762367594e-03\natom  8.5087036878e+00  1.4261729514e+01  4.0122764103e+01 Mg  3.8622878527e-01 0.0  7.8792117853e-04  4.4228870147e-03  8.8066880375e-03\natom  1.1471364862e+01  6.8057574411e-02  1.9967250992e+01 Mg  4.3387211527e-01 0.0 -6.0415288902e-03 -5.3912136147e-03 -2.0784686203e-03\natom  1.4219334607e+01  2.8404658040e+00  1.9980706200e+01 O  -3.9772106473e-01 0.0  5.6921382101e-03  2.1517653782e-03  6.7832314649e-03\natom  1.1503650736e+01 -7.3440610068e-03  2.4035543354e+01 O  -3.4243821473e-01 0.0 -9.6323345278e-03 -7.6100795684e-04  1.0612833628e-02\natom  1.4245755584e+01  2.8498426054e+00  2.4034010181e+01 Mg  3.3143748527e-01 0.0 -1.4397998218e-03  3.9893509206e-03 -1.1854362712e-02\natom  1.1422725980e+01 -2.5954214823e-02  2.8021035840e+01 Mg  3.4132669527e-01 0.0 -5.9081133595e-03  3.1016100140e-03 -6.9000268352e-03\natom  1.4233079246e+01  2.8344599713e+00  2.8122047553e+01 O  -3.4031699473e-01 0.0  3.4801326161e-03  2.7551276256e-04  2.5685136205e-03\natom  1.1338035434e+01  5.9543300586e-02  3.2128443791e+01 O  -3.4530042473e-01 0.0  7.3076989721e-03 -6.7571909228e-03  5.9952463622e-04\natom  1.4185615603e+01  2.8855286256e+00  3.2038965889e+01 Mg  3.3044106527e-01 0.0  4.5565871720e-03  4.8147614159e-04  3.4383575468e-04\natom  1.1446261648e+01  4.5068320766e-02  3.6130766461e+01 Mg  3.1738636527e-01 0.0 -5.5688588436e-03  3.6685311262e-03  3.3294632644e-03\natom  1.4247979206e+01  2.8868990171e+00  3.6117049035e+01 O  -3.2249999473e-01 0.0  1.7228961174e-02 -1.4789373849e-02 -7.1376355421e-03\natom  1.1378186159e+01  1.9139466066e-02  4.0130265975e+01 O  -4.0500328473e-01 0.0  3.4630935715e-03 -5.3367001487e-03 -4.4396627468e-03\natom  1.4309719181e+01  2.8309469518e+00  4.0159164062e+01 Mg  3.8667456527e-01 0.0 -1.1351484003e-02  7.2531252597e-03  4.9552138452e-03\natom  1.1412780673e+01  5.7301354806e+00  2.0004488610e+01 Mg  4.2581214527e-01 0.0 -1.6215833264e-03  3.4942179619e-04 -1.3050000662e-03\natom  1.4196033152e+01  8.5642871809e+00  2.0009540225e+01 O  -4.0093030473e-01 0.0  6.4353354379e-03 -4.9453975423e-04  2.9633903093e-03\natom  1.1415181022e+01  5.6996378732e+00  2.4042617222e+01 O  -3.4408019473e-01 0.0  4.2875529622e-03  8.6888759548e-04  9.9391376946e-03\natom  1.4258049650e+01  8.6357165934e+00  2.4075538119e+01 Mg  3.3016744527e-01 0.0 -2.8724597313e-03 -1.1143237963e-02 -1.8064343490e-02\natom  1.1420573601e+01  5.7189410840e+00  2.8017758640e+01 Mg  3.3468118527e-01 0.0 -2.4340618933e-03 -1.1211898538e-03 -9.6491432711e-03\natom  1.4231033410e+01  8.5563526939e+00  2.8020280082e+01 O  -3.4024647473e-01 0.0  4.2134721000e-03 -4.0358474656e-04  1.3772126186e-02\natom  1.1512634815e+01  5.7298216538e+00  3.2101319024e+01 O  -3.4334786473e-01 0.0 -1.3968118148e-02  2.4321038891e-03  1.7530712354e-03\natom  1.4263527550e+01  8.5560234848e+00  3.2097100853e+01 Mg  3.3233890527e-01 0.0  6.8102658311e-03 -2.5292075134e-03 -1.0027124089e-02\natom  1.1387788423e+01  5.7322691702e+00  3.6044000600e+01 Mg  3.1649537527e-01 0.0  7.3541646272e-03 -1.0730541540e-02  1.3724161470e-02\natom  1.4201528948e+01  8.5395895205e+00  3.6095911788e+01 O  -3.1629245473e-01 0.0 -9.1941280972e-03  1.8547197819e-02 -2.2255983166e-03\natom  1.1390328801e+01  5.6175220224e+00  4.0151773910e+01 O  -4.0820386473e-01 0.0 -5.4913421939e-04  1.0630208315e-02 -5.8840754248e-03\natom  1.4255641081e+01  8.5338729482e+00  4.0183161975e+01 Mg  3.9211493527e-01 0.0  2.3302869760e-03 -3.0448311989e-03  6.7357222068e-03\natom  1.1406385009e+01  1.1391674645e+01  2.0025648420e+01 Mg  4.2078151527e-01 0.0 -2.4165968109e-03  3.4640339728e-04 -4.5431923818e-03\natom  1.4233807527e+01  1.4215487295e+01  2.0022189012e+01 O  -4.0011134473e-01 0.0  2.1708518546e-03  2.9938783019e-03  2.2337297925e-03\natom  1.1377360103e+01  1.1359126401e+01  2.4045313710e+01 O  -3.4135520473e-01 0.0  3.1265453613e-03  6.8447130603e-03  1.2076349843e-02\natom  1.4249124191e+01  1.4233114621e+01  2.4009586720e+01 Mg  3.2916215527e-01 0.0 -3.3926985185e-03  1.0977029318e-03 -1.0159673152e-02\natom  1.1426066789e+01  1.1378510114e+01  2.8100914766e+01 Mg  3.3878972527e-01 0.0 -5.6144743678e-03  1.6815102232e-03 -1.8300310417e-02\natom  1.4242931276e+01  1.4220386731e+01  2.8102847767e+01 O  -3.4123458473e-01 0.0  9.7244389000e-04  3.5962274586e-03  5.9608383289e-03\natom  1.1422883602e+01  1.1430965393e+01  3.2069651732e+01 O  -3.1263553473e-01 0.0 -3.0409014009e-03 -3.0338116128e-03  2.4601114871e-02\natom  1.4212334798e+01  1.4252539115e+01  3.2056485690e+01 Mg  3.3182589527e-01 0.0  3.9104199898e-03  9.8993798616e-04 -9.2631791365e-03\natom  1.1409862861e+01  1.1390384132e+01  3.6157557163e+01 Al  3.9863599527e-01 0.0  3.1057675059e-03  6.6889982344e-04  5.7006832235e-03\natom  1.4260584359e+01  1.4267307078e+01  3.6067919561e+01 O  -2.9269494473e-01 0.0  6.9011991031e-04  2.1501267018e-04 -2.5922725714e-03\natom  1.1397998802e+01  1.1408684654e+01  4.0179361151e+01 O  -3.6191561473e-01 0.0 -8.4903106875e-04 -2.1563905607e-03 -2.4957804323e-02\natom  1.4153091963e+01  1.4279992865e+01  4.0103315251e+01 Mg  3.7561481527e-01 0.0  8.1428848804e-03 -1.0484289936e-03  1.5564228807e-02\natom  2.7219067198e+00  2.7693563410e+00  1.5270668883e+01 Au -2.7158774727e-02 0.0  7.2232847927e-04  5.0246924298e-04  1.7954707139e-02\natom  2.6326646934e+00  2.6144088255e+00  1.0521244839e+01 Au -2.2087081473e-01 0.0 -3.3082251152e-04 -2.1863555863e-04 -1.0395108242e-02\nenergy -5.4395984638e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -1.9356557788e-02  1.7481439381e-02  2.0023684182e+01 Mg  4.1749255600e-01 0.0  4.0547394632e-03 -7.7918249171e-03 -3.3597861968e-03\natom  2.8478458076e+00  2.8179714507e+00  1.9997688280e+01 O  -3.9954090400e-01 0.0 -2.6914536509e-03  4.1659971042e-03  2.3986065392e-03\natom  3.3345348904e-03 -3.9333512617e-03  2.3979940434e+01 O  -3.4249196400e-01 0.0  1.5382003613e-03  2.2635667596e-03  2.5756030800e-02\natom  2.8210309548e+00  2.9330537414e+00  2.4065670688e+01 Mg  3.2867032600e-01 0.0  9.3388163032e-03 -1.3331153887e-02 -2.0174537649e-02\natom  3.5909896044e-03 -3.9625248515e-02  2.8067264642e+01 Mg  3.4571895600e-01 0.0 -4.7264725265e-03  3.5866960477e-03 -2.4040828028e-02\natom  2.8931720381e+00  2.7978817359e+00  2.8060042752e+01 O  -3.3656552400e-01 0.0 -6.2209076684e-03  4.4877371419e-03  2.0059286067e-02\natom  2.4981062631e-02 -1.7358833959e-03  3.2073900781e+01 O  -3.0772899400e-01 0.0 -7.5976110170e-04  2.2735304207e-03  2.8123827904e-02\natom  2.8950322655e+00  2.8288041915e+00  3.2064644374e+01 Mg  3.3609177600e-01 0.0 -4.9555320352e-03  9.2477122237e-04 -1.1151656936e-02\natom -1.8909732078e-03 -1.5871903065e-02  3.6121183963e+01 Al  4.0396884600e-01 0.0  5.3445843816e-03 -2.4446381230e-03  1.0738259341e-02\natom  2.8292946132e+00  2.8875546953e+00  3.6116881133e+01 O  -2.9055354400e-01 0.0  2.8533903353e-03 -3.1350744034e-03 -6.9554903802e-03\natom  2.4236661770e-02 -7.3534907394e-03  4.0136838083e+01 O  -3.6251323400e-01 0.0 -1.3551945307e-03  8.6512191228e-04 -2.5541554850e-02\natom  2.8552015282e+00  2.8373508741e+00  4.0176689078e+01 Mg  3.8077715600e-01 0.0  1.2814685750e-03  6.4056190731e-05  1.1255847783e-02\natom -1.0063168834e-03  5.6915555151e+00  2.0016894755e+01 Mg  4.2961212600e-01 0.0 -4.9441240023e-04  1.8924897650e-03 -6.0024833282e-03\natom  2.8157235271e+00  8.5127121745e+00  2.0008982095e+01 O  -3.9402408400e-01 0.0 -3.5046326573e-03 -3.4548161402e-03  7.5011864510e-03\natom  9.8207812408e-02  5.6502712384e+00  2.4076476123e+01 O  -3.3983282400e-01 0.0 -1.0566388768e-02  2.9655302295e-03  1.0133466735e-02\natom  2.8256109325e+00  8.5517239046e+00  2.3978618684e+01 Mg  3.3004369600e-01 0.0  3.7239411994e-03 -3.3601720311e-04 -1.0517407271e-02\natom  1.3135523141e-02  5.6587227166e+00  2.8085921094e+01 Mg  3.3681396600e-01 0.0 -1.3684201442e-03  5.0848837237e-03 -1.8050708252e-02\natom  2.8607922258e+00  8.5400241575e+00  2.7997298501e+01 O  -3.4039332400e-01 0.0  1.9739634006e-03 -1.2805652220e-03  1.9488333733e-02\natom  3.2025488685e-02  5.7716663477e+00  3.2047408637e+01 O  -3.4343504400e-01 0.0 -3.2895336646e-03 -1.3534296983e-02  1.3971087913e-02\natom  2.8259494202e+00  8.4860991445e+00  3.2099548218e+01 Mg  3.2967653600e-01 0.0 -2.7995376243e-03  1.4554303660e-02 -1.2875261516e-02\natom -6.2218188825e-02  5.6986726201e+00  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-5.7720404518e-03\natom  8.5454119930e+00  8.5922146665e+00  1.9982451324e+01 O  -3.9735676400e-01 0.0 -3.2473320558e-03 -1.2455928480e-02  1.7366895128e-02\natom  5.7673644999e+00  5.6741709998e+00  2.4012076169e+01 O  -3.4326388400e-01 0.0 -9.7935119569e-03  1.6866884615e-03  1.8234986690e-02\natom  8.5146260323e+00  8.5959387873e+00  2.4024512343e+01 Mg  3.2318482600e-01 0.0  4.6630353883e-03 -6.8434866699e-03 -1.9649489038e-02\natom  5.6721554748e+00  5.6687010557e+00  2.8049456148e+01 Mg  3.4198597600e-01 0.0  6.2960061769e-03  5.4781721501e-03 -2.2262573623e-02\natom  8.5574357337e+00  8.5031412604e+00  2.8027564882e+01 O  -3.4050532400e-01 0.0 -1.7368780499e-03  6.3515242514e-03  2.3224077953e-02\natom  5.6608312162e+00  5.7108019397e+00  3.2124889141e+01 O  -3.0363604400e-01 0.0  3.4792234556e-03 -3.5102517490e-03  2.6658015760e-02\natom  8.5646142925e+00  8.5601491534e+00  3.2111412277e+01 Mg  3.3420704600e-01 0.0 -2.1526569913e-03 -6.9599084015e-04 -2.0748356479e-02\natom  5.6516279861e+00  5.6954023359e+00  3.6054886990e+01 Al  4.0203727600e-01 0.0 -1.1834523926e-03 -2.7134112780e-03  1.0943988640e-02\natom  8.5994414322e+00  8.5259438469e+00  3.6080975318e+01 O  -2.8840626400e-01 0.0 -2.0553244021e-03  5.9946538453e-03 -1.1307478497e-03\natom  5.7601233345e+00  5.6739091216e+00  4.0191344678e+01 O  -3.6676971400e-01 0.0 -7.8943113594e-03  6.7144219980e-04 -2.3800010454e-02\natom  8.4451356677e+00  8.5634968030e+00  4.0126400427e+01 Mg  3.7646214600e-01 0.0  8.9029347089e-03 -2.8002262487e-03  1.7380751330e-02\natom  5.6522744613e+00  1.1349514896e+01  2.0026174670e+01 Mg  2.9880940600e-01 0.0  8.5211427277e-03  4.4723039602e-03 -2.3202410009e-02\natom  8.5345340311e+00  1.4252969859e+01  1.9943476161e+01 O  -3.9690966400e-01 0.0  1.3055675564e-03  8.4132388155e-03  1.9669513795e-02\natom  5.6902975623e+00  1.1378914705e+01  2.3970687334e+01 O  -3.3792595400e-01 0.0 -3.7227207419e-03  2.6993772327e-03  2.5220041428e-02\natom  8.5843063522e+00  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1.9759135102e-03 -1.1292684490e-02\natom  1.1376628609e+01  5.6803579627e+00  3.6167506419e+01 Mg  3.2327509600e-01 0.0  8.3203202143e-04 -2.5658541529e-03  2.4598790972e-03\natom  1.4253113554e+01  8.5719328989e+00  3.6121207056e+01 O  -3.1359348400e-01 0.0 -1.6655758454e-02  1.0470492301e-02 -5.7891184216e-03\natom  1.1424182788e+01  5.7463731968e+00  4.0193155753e+01 O  -4.0891981400e-01 0.0 -4.4965713119e-03 -5.4929333409e-03 -1.1024773881e-02\natom  1.4238559980e+01  8.5435675449e+00  4.0072741998e+01 Mg  3.8442773600e-01 0.0  2.2948262081e-03 -4.3657329315e-03  1.8191784565e-02\natom  1.1355323573e+01  1.1416662888e+01  2.0004274523e+01 Mg  2.9452832600e-01 0.0 -2.2788894162e-03 -1.4090919341e-03 -1.7923582226e-02\natom  1.4240531834e+01  1.4239412152e+01  2.0082534425e+01 O  -3.9731722400e-01 0.0  4.5135809646e-03  3.8143617333e-03  9.4946361486e-04\natom  1.1376904490e+01  1.1382882714e+01  2.4025710826e+01 O  -3.4081652400e-01 0.0 -5.1969318055e-04  3.8964364776e-03  1.9973704470e-02\natom  1.4236947553e+01  1.4285883897e+01  2.4043575672e+01 Mg  3.2466794600e-01 0.0  4.7147779847e-04 -5.8258891032e-03 -1.8505859522e-02\natom  1.1347811365e+01  1.1433277378e+01  2.8050183163e+01 Mg  3.4332171600e-01 0.0  7.0788012261e-03 -6.2912464844e-03 -2.1099576093e-02\natom  1.4195540973e+01  1.4242148249e+01  2.8049595477e+01 O  -3.4016697400e-01 0.0  6.0218724198e-03  1.0559331310e-03  1.7751093305e-02\natom  1.1442205918e+01  1.1409832682e+01  3.2139464163e+01 O  -3.0640742400e-01 0.0 -4.5578887059e-03 -1.3230076692e-03  2.6368681477e-02\natom  1.4286709159e+01  1.4302636866e+01  3.2065290906e+01 Mg  3.3417217600e-01 0.0 -2.6887549556e-03 -7.8209918882e-03 -1.5481249396e-02\natom  1.1352161797e+01  1.1328401157e+01  3.6098784096e+01 Al  4.0648159600e-01 0.0  3.1746446908e-03  4.6365035181e-03  5.3866155062e-03\natom  1.4303110167e+01  1.4218169346e+01  3.6115005523e+01 O  -2.9243080400e-01 0.0 -4.4607645649e-03  7.5592432642e-03 -5.8809349395e-03\natom  1.1428630977e+01  1.1373183052e+01  4.0172047911e+01 O  -3.6298317400e-01 0.0 -3.4771607929e-03  5.7409529348e-04 -2.6496078840e-02\natom  1.4228370634e+01  1.4172605954e+01  4.0157395902e+01 Mg  3.7912112600e-01 0.0  3.9001106428e-03  4.9279726758e-03  1.3963532609e-02\natom  1.1031652440e+01  1.1192567294e+01  1.4670273967e+01 Au -7.3770974000e-02 0.0  5.4504259837e-03 -2.8887655385e-05 -3.0245877321e-03\natom  6.1705889023e+00  1.1367937740e+01  1.4654432394e+01 Au -7.6123924000e-02 0.0 -5.6261480028e-03  2.7309718525e-04 -2.3359358895e-03\nenergy -5.4395982358e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -2.8015641315e-02 -4.4903668941e-04  1.9990734145e+01 Mg  3.7995685400e-01 0.0 -5.1311911289e-03 -9.0067340587e-03  3.4252039045e-03\natom  2.8595102357e+00  2.9243740787e+00  1.9979460228e+01 O  -3.2180733600e-01 0.0 -3.6445791922e-03 -5.3764627774e-03 -2.1361120031e-02\natom  9.5512420642e-03  7.3651125543e-02  2.4074085903e+01 O  -3.4141110600e-01 0.0  1.8539866437e-03 -6.0945422212e-03 -5.7877427348e-03\natom  2.8454244827e+00  2.8666448395e+00  2.4003966618e+01 Mg  3.3993941400e-01 0.0  4.2512155539e-04  1.4974023016e-03  1.2614677197e-02\natom -1.7495461148e-03 -5.5614957098e-02  2.7999476467e+01 Mg  3.3912540400e-01 0.0  2.3695050149e-04  9.6977734223e-03  4.9007921800e-03\natom  2.8300821376e+00  2.9035583312e+00  2.8031283069e+01 O  -3.4330559600e-01 0.0  4.2184542757e-03 -3.9163815532e-03  2.4043044878e-03\natom -5.5087855828e-02  2.8992799727e-02  3.2002298591e+01 O  -3.4004170600e-01 0.0  8.3762444368e-03 -6.7558073263e-03  6.7264021983e-03\natom  2.8803988321e+00  2.8171100380e+00  3.2118369549e+01 Mg  3.4164419400e-01 0.0 -4.3862656636e-03  1.5654640109e-03 -4.7105296926e-03\natom  2.3757294978e-02 -1.8356042363e-03  3.6085942595e+01 Mg  3.3768911400e-01 0.0 -5.4418827120e-03 -8.4173984180e-04  5.1820727395e-03\natom  2.8444442819e+00  2.8563114776e+00  3.6111286939e+01 O  -3.4201602600e-01 0.0  2.5796789929e-03 -3.1750333549e-03  7.7768243241e-04\natom  4.5991584193e-03 -1.0200926080e-01  4.0139837380e+01 O  -4.0427446600e-01 0.0  1.3030762733e-03  1.0377165161e-02  4.4646966972e-03\natom  2.8542084394e+00  2.8068057212e+00  4.0149793402e+01 Mg  4.1921180400e-01 0.0 -5.9975462073e-03  1.9001595657e-03 -5.2890075058e-03\natom -5.2929127345e-02  5.6751673578e+00  1.9992775861e+01 Mg  3.7412477400e-01 0.0 -3.2157537714e-03  1.0541392860e-02  2.3211274283e-03\natom  2.9064803578e+00  8.5305012613e+00  1.9937564739e+01 O  -3.9870869600e-01 0.0 -6.7496442458e-03  1.1550883359e-04  9.0090308069e-04\natom -2.0885005962e-02  5.6965665204e+00  2.3995747142e+01 O  -3.4207595600e-01 0.0  5.2832730134e-03  1.5334448163e-03 -3.6791957694e-04\natom  2.8069586756e+00  8.5321319248e+00  2.3974700715e+01 Mg  3.3433178400e-01 0.0  3.3557956863e-03  2.7536911108e-04  2.5757191910e-03\natom -2.4861461873e-02  5.7142775804e+00  2.8047692353e+01 Mg  3.4661356400e-01 0.0  1.5333193928e-04 -2.3475492699e-03 -7.1944398883e-04\natom  2.8784036783e+00  8.6399587826e+00  2.8035790405e+01 O  -3.3995004600e-01 0.0 -2.8683960211e-03 -8.4317138275e-03  2.0401071408e-03\natom  2.9282778180e-02  5.7340023135e+00  3.2137529613e+01 O  -3.4070243600e-01 0.0 -2.5677170687e-03 -4.3826051846e-03 -5.4470302215e-03\natom  2.8231730348e+00  8.5413745368e+00  3.2061774939e+01 Mg  3.4251104400e-01 0.0  9.2380253134e-04  4.7172868120e-04  4.5007453709e-03\natom -2.2874131537e-02  5.7299249085e+00  3.6088965363e+01 Mg  3.3109645400e-01 0.0  2.0818281190e-03 -1.3527037606e-03  6.0910565647e-03\natom  2.8053539581e+00  8.5695222510e+00  3.6124283265e+01 O  -3.4398502600e-01 0.0  8.2025006280e-03 -1.9653379290e-03 -3.1049350511e-03\natom -1.3739763026e-02  5.7354638654e+00  4.0134932559e+01 O  -4.0224077600e-01 0.0  6.7002953682e-04 -6.9474915031e-03  6.2522364108e-03\natom  2.8311769503e+00  8.5185467980e+00  4.0144714480e+01 Mg  4.1153282400e-01 0.0  1.5825432406e-03  4.2013118390e-03 -5.7219931254e-03\natom -2.0279688933e-02  1.1393373074e+01  2.0009344714e+01 Mg  4.1998870400e-01 0.0 -1.2077953430e-03  2.3643128264e-03  1.9419048589e-03\natom  2.7834678509e+00  1.4250800718e+01  1.9992528609e+01 O  -3.9810140600e-01 0.0  4.4066498063e-03  2.6686266325e-03 -1.4105242693e-03\natom -1.1318551603e-02  1.1412078243e+01  2.4033412612e+01 O  -3.4144795600e-01 0.0  3.6321122953e-03  2.8249152680e-04  4.3575991883e-04\natom  2.8858053193e+00  1.4216220660e+01  2.4088131593e+01 Mg  3.3514163400e-01 0.0 -3.0863482219e-03  2.5286736152e-03 -8.8666408433e-03\natom  2.4191402832e-02  1.1396103388e+01  2.8071644668e+01 Mg  3.3940924400e-01 0.0 -3.7510740492e-03 -2.3164281538e-03 -1.2352457173e-03\natom  2.8814489151e+00  1.4242021259e+01  2.8027932509e+01 O  -3.3872132600e-01 0.0 -3.2729903504e-03  1.7263770301e-03  3.5702439842e-03\natom -1.3600282351e-02  1.1325423214e+01  3.2128795054e+01 O  -3.4071604600e-01 0.0  1.7738933733e-03  8.8309293729e-03 -5.8444437618e-03\natom  2.8106535812e+00  1.4207827726e+01  3.2103460612e+01 Mg  3.4848516400e-01 0.0  3.5276721162e-03  3.5393367296e-03 -1.3350257515e-03\natom  4.0823901710e-02  1.1442764993e+01  3.6185427674e+01 Mg  3.2195863400e-01 0.0 -6.3329786854e-03 -5.7063228643e-03 -4.0977185584e-03\natom  2.8230339132e+00  1.4197219503e+01  3.6152294163e+01 O  -3.4108694600e-01 0.0  5.5274727905e-03  8.0304773287e-03 -7.9567059980e-03\natom -1.4668695630e-02  1.1416494060e+01  4.0121347829e+01 O  -4.0080666600e-01 0.0  2.1278795976e-03 -3.1503346846e-03  1.0414055391e-02\natom  2.8825574094e+00  1.4222887330e+01  4.0139701868e+01 Mg  4.0407107400e-01 0.0 -3.7127157175e-03 -1.7039365153e-03 -1.8490857568e-03\natom  5.6753829945e+00 -8.8281006201e-03  2.0015350963e+01 Mg  3.7427715400e-01 0.0  7.8563252462e-03 -6.9892316659e-03 -1.3046557051e-03\natom  8.4744777455e+00  2.8205201997e+00  2.0026585308e+01 O  -3.9808697600e-01 0.0  5.4139493084e-03  4.4117289654e-03 -8.5580846419e-03\natom  5.7024103469e+00  1.6161446881e-02  2.3919593849e+01 O  -3.4118773600e-01 0.0 -7.2307094293e-03 -8.8779407375e-04  9.9499880896e-03\natom  8.5241099624e+00  2.7919058743e+00  2.4017972474e+01 Mg  3.2656091400e-01 0.0  5.5732526615e-03  7.7429782301e-03  1.0214984090e-03\natom  5.7028459476e+00  1.4914038755e-02  2.8041916217e+01 Mg  3.4580882400e-01 0.0  2.5531522115e-03  6.2015647202e-04  1.5320891279e-04\natom  8.5837581616e+00  2.8407663649e+00  2.8017686018e+01 O  -3.4196514600e-01 0.0 -7.1236053389e-03 -1.2103074831e-03  5.0465956887e-03\natom  5.7429529062e+00 -2.7557741811e-02  3.2108312559e+01 O  -3.4171916600e-01 0.0 -6.8318718240e-03  1.6036050391e-03 -1.0416153611e-03\natom  8.4889312013e+00  2.8563181106e+00  3.2059418602e+01 Mg  3.4257254400e-01 0.0  8.5578447383e-03 -3.4880835971e-03 -9.0331868461e-04\natom  5.7606175167e+00  8.6106309534e-03  3.6176663521e+01 Mg  3.3499923400e-01 0.0 -6.1369507112e-03 -2.7579135268e-03 -5.2737444331e-03\natom  8.5692962020e+00  2.8056372280e+00  3.6112368902e+01 O  -3.4053369600e-01 0.0 -3.4648665265e-03  5.9519730416e-03  1.5720161958e-03\natom  5.7064592171e+00 -5.6737151979e-02  4.0189844708e+01 O  -3.9859314600e-01 0.0  1.2033610506e-03  7.4682022426e-03  2.2525629151e-03\natom  8.4918070241e+00  2.8431614036e+00  4.0135192755e+01 Mg  4.1909261400e-01 0.0  4.2873700629e-03 -1.6047272351e-04 -2.2046937572e-03\natom  5.6855184831e+00  5.6910473489e+00  2.0001124198e+01 Mg  3.6887644400e-01 0.0  1.2223250610e-02  9.4831400194e-03  1.9031025103e-03\natom  8.6194263050e+00  8.5795994605e+00  1.9998326364e+01 O  -4.0200764600e-01 0.0 -6.7932182512e-03 -2.2921249378e-03 -4.6351268071e-03\natom  5.7489095304e+00  5.6988607234e+00  2.4028694722e+01 O  -3.4250733600e-01 0.0 -1.0279576406e-02 -8.4784422148e-04 -1.6153250812e-03\natom  8.4824632928e+00  8.5800489319e+00  2.4012424049e+01 Mg  3.3380057400e-01 0.0  1.1070670270e-02 -4.4947290152e-03 -5.4230681653e-04\natom  5.7237111115e+00  5.7396601153e+00  2.8096502841e+01 Mg  3.3974375400e-01 0.0 -1.7623751056e-03 -5.0814106179e-03 -7.6804601529e-03\natom  8.5568860691e+00  8.4978643707e+00  2.8065720981e+01 O  -3.4080514600e-01 0.0 -2.9799863675e-03  6.7380983332e-03 -1.6467329465e-04\natom  5.6795059986e+00  5.6431858998e+00  3.2074295696e+01 O  -3.3844696600e-01 0.0  1.1880689070e-03  6.3921534769e-03  1.5038387326e-03\natom  8.5343423939e+00  8.5366727284e+00  3.2073740627e+01 Mg  3.3794829400e-01 0.0  2.7656928648e-03 -1.1970269611e-03  7.2334548408e-04\natom  5.7093729478e+00  5.7142384631e+00  3.6116529303e+01 Mg  3.3493072400e-01 0.0 -3.5787957384e-03  8.9034394853e-04  2.0142908283e-03\natom  8.5293092411e+00  8.4862048558e+00  3.6095102929e+01 O  -3.4304801600e-01 0.0  1.5364791453e-03  4.6803130633e-03  1.5126806703e-03\natom  5.6836630557e+00  5.7166581816e+00  4.0185145583e+01 O  -4.0115579600e-01 0.0  3.1313498132e-03 -4.9724215580e-03  2.9969182433e-03\natom  8.6051028623e+00  8.5472089713e+00  4.0188913300e+01 Mg  4.2073229400e-01 0.0 -6.2502417792e-03  2.3263626527e-03 -7.5620718507e-03\natom  5.6407495138e+00  1.1407372466e+01  2.0025375600e+01 Mg  4.2205697400e-01 0.0  7.7712022982e-03  1.7416422249e-04 -2.8148664323e-04\natom  8.5943606394e+00  1.4303640745e+01  2.0031463409e+01 O  -4.0043465600e-01 0.0 -7.9585844353e-03 -3.6517005024e-03 -8.9316409189e-03\natom  5.7171466569e+00  1.1376380223e+01  2.4001891586e+01 O  -3.4079964600e-01 0.0 -4.7274576048e-03  2.9039475617e-03  2.0948286165e-03\natom  8.5798804817e+00  1.4262886952e+01  2.3987121147e+01 Mg  3.2675935400e-01 0.0  1.6617655278e-03 -7.6694784822e-04  1.6255460969e-03\natom  5.6848640710e+00  1.1380024786e+01  2.8031542131e+01 Mg  3.4029481400e-01 0.0  7.1037112131e-03  3.7599406810e-03  3.6933963364e-04\natom  8.5493712713e+00  1.4291280047e+01  2.7984206347e+01 O  -3.4297287600e-01 0.0 -8.7377819739e-04 -6.0696067664e-03  5.8578714928e-03\natom  5.7356361895e+00  1.1457970447e+01  3.2075294568e+01 O  -3.3965900600e-01 0.0 -4.7779666918e-03 -6.8504066380e-03 -2.2513920942e-04\natom  8.5762781159e+00  1.4227485487e+01  3.2053841113e+01 Mg  3.3995732400e-01 0.0 -2.1077608559e-03  2.9643596529e-03 -1.3746203473e-03\natom  5.6905589303e+00  1.1434459685e+01  3.6037075113e+01 Mg  3.3795627400e-01 0.0  2.4225568766e-04 -5.0855533326e-03  1.0268660189e-02\natom  8.5680323533e+00  1.4283335942e+01  3.6145584937e+01 O  -3.4058036600e-01 0.0 -2.4742688454e-03 -4.6164751764e-03 -4.3782942052e-03\natom  5.6898009046e+00  1.1421721590e+01  4.0192397898e+01 O  -4.0452559600e-01 0.0  3.4173378405e-03 -3.7281743067e-03  1.2737640582e-03\natom  8.5670263010e+00  1.4250463875e+01  4.0122438163e+01 Mg  4.0820262400e-01 0.0 -4.2566260239e-04 -2.6102422848e-03 -7.2799086985e-04\natom  1.1369545254e+01  3.4911270345e-02  1.9940154381e+01 Mg  4.2700459400e-01 0.0  8.4727000224e-05 -4.4129403564e-03  8.8656945277e-03\natom  1.4277619936e+01  2.8114422017e+00  2.0060744127e+01 O  -3.9397281600e-01 0.0 -2.5196843301e-03  4.2607666170e-03 -1.1191856658e-02\natom  1.1379424610e+01  8.0792400054e-03  2.4047665077e+01 O  -3.4271983600e-01 0.0  4.3093138059e-03  1.2211282925e-03 -1.2014309936e-03\natom  1.4208462825e+01  2.8339907712e+00  2.3994250611e+01 Mg  3.2686945400e-01 0.0 -1.1997434134e-03  4.7920073118e-03  7.0457138918e-03\natom  1.1437258275e+01 -3.9654917213e-02  2.8048589368e+01 Mg  3.3732268400e-01 0.0 -5.4452173117e-03  5.1507258854e-03 -1.6716855838e-03\natom  1.4249042120e+01  2.8699447735e+00  2.8087895820e+01 O  -3.4295771600e-01 0.0  1.6800729155e-03 -3.6505060156e-03 -3.4925739816e-03\natom  1.1391840601e+01 -2.4458950238e-02  3.2045511541e+01 O  -3.4100836600e-01 0.0 -5.0200432907e-04 -1.2567916828e-03  2.7591016964e-03\natom  1.4252111375e+01  2.8169715777e+00  3.2046152971e+01 Mg  3.3754263400e-01 0.0 -2.3110544142e-03  2.2742211351e-03  1.2299680779e-03\natom  1.1354191382e+01  1.8293208974e-02  3.6110456839e+01 Mg  3.2908630400e-01 0.0  8.1957349190e-03 -3.0379730383e-03 -1.1197369382e-03\natom  1.4216253806e+01  2.8141362140e+00  3.6092130314e+01 O  -3.4271129600e-01 0.0  2.2231865973e-03  4.3918011944e-03 -1.8462959512e-04\natom  1.1440878196e+01 -2.5359121212e-02  4.0124464195e+01 O  -4.0045133600e-01 0.0 -6.4746093978e-03  2.9709141450e-03  6.8420677053e-03\natom  1.4150555347e+01  2.8650847762e+00  4.0154247524e+01 Mg  4.1649909400e-01 0.0  1.0777756791e-02 -4.5513933713e-03 -6.2921972180e-03\natom  1.1419542245e+01  5.7237920106e+00  1.9984676722e+01 Mg  4.2967479400e-01 0.0 -4.9437717996e-03  1.4454244940e-03  9.8232093037e-03\natom  1.4236059741e+01  8.5886031734e+00  2.0006585091e+01 O  -3.9768698600e-01 0.0  4.2210103703e-03 -4.5596599526e-03 -6.0027328333e-03\natom  1.1412625867e+01  5.6879387308e+00  2.4054513103e+01 O  -3.4683316600e-01 0.0 -9.4638124797e-04  2.4660091117e-03 -3.8795490205e-03\natom  1.4238795516e+01  8.6190653674e+00  2.4004720109e+01 Mg  3.3157523400e-01 0.0 -4.9080941426e-03 -5.5061005749e-03  1.6997253707e-03\natom  1.1384187550e+01  5.6787679661e+00  2.8091469254e+01 Mg  3.3257854400e-01 0.0  2.0159481758e-03 -3.4636656085e-04 -9.0458465322e-03\natom  1.4239422924e+01  8.5646495548e+00  2.8032149111e+01 O  -3.4153459600e-01 0.0  4.9245502045e-03 -1.6239415300e-03  3.1521701573e-03\natom  1.1409352294e+01  5.6896321520e+00  3.2003129353e+01 O  -3.4140853600e-01 0.0 -1.3530483817e-03 -1.6452162955e-03  1.1949328734e-02\natom  1.4261096285e+01  8.4792158932e+00  3.2155033975e+01 Mg  3.4191900400e-01 0.0 -2.1704753071e-03  6.2504254979e-03 -2.4935476324e-03\natom  1.1413084239e+01  5.6826708739e+00  3.6161594487e+01 Mg  3.3902368400e-01 0.0 -3.8177890229e-04  2.0252649477e-03 -4.8999461960e-03\natom  1.4276761131e+01  8.6165430745e+00  3.6200016680e+01 O  -3.4331234600e-01 0.0 -6.4273347528e-03 -9.1205752240e-03 -9.0856679233e-03\natom  1.1444039254e+01  5.6959231443e+00  4.0184130687e+01 O  -3.9908881600e-01 0.0 -7.3595705829e-03 -2.3721424057e-04  3.9155031013e-03\natom  1.4269288474e+01  8.5583747574e+00  4.0126484142e+01 Mg  4.0753524400e-01 0.0  1.5069357189e-03  1.4921548576e-03 -3.5833458669e-03\natom  1.1394162904e+01  1.1420095538e+01  2.0028346381e+01 Mg  4.0883550400e-01 0.0 -1.1261436129e-03  1.7952561754e-03  2.4342321492e-03\natom  1.4219813577e+01  1.4262876086e+01  2.0021426318e+01 O  -4.0022335600e-01 0.0  3.8345212262e-03  2.0322970956e-03 -6.2399539349e-03\natom  1.1408536273e+01  1.1492291442e+01  2.3978060573e+01 O  -3.4487985600e-01 0.0 -2.5760667010e-04 -8.8290714444e-03  8.6855431432e-03\natom  1.4240819790e+01  1.4290960230e+01  2.4030615685e+01 Mg  3.3243711400e-01 0.0 -2.4222479604e-03 -2.8972384353e-03 -4.1699510682e-03\natom  1.1475111622e+01  1.1346000591e+01  2.8118900800e+01 Mg  3.4354301400e-01 0.0 -8.6255492853e-03  1.6319743899e-03 -9.3131101104e-03\natom  1.4238457803e+01  1.4203745653e+01  2.8053264512e+01 O  -3.3748989600e-01 0.0  4.2093514456e-03  2.7230942034e-03  1.6986128601e-03\natom  1.1342524648e+01  1.1293648246e+01  3.2068888756e+01 O  -3.4071834600e-01 0.0  4.9285104791e-03  9.6605068379e-03  2.9520343914e-03\natom  1.4217392555e+01  1.4251180118e+01  3.2059629892e+01 Mg  3.4455166400e-01 0.0  1.6687200548e-03 -3.8929002378e-03  5.2724235107e-03\natom  1.1371720745e+01  1.1440722388e+01  3.6144332880e+01 Mg  3.3414004400e-01 0.0  4.3691050068e-03 -5.5761917135e-03 -2.6852644691e-03\natom  1.4243857733e+01  1.4199614428e+01  3.6092206735e+01 O  -3.4402498600e-01 0.0 -9.5737891182e-04  6.2337410014e-03 -3.3034286191e-03\natom  1.1402937147e+01  1.1400570114e+01  4.0130582731e+01 O  -3.9908397600e-01 0.0 -2.0679864962e-03 -1.2214347252e-03  7.3136648221e-03\natom  1.4259258678e+01  1.4215151132e+01  4.0112872521e+01 Mg  4.0691654400e-01 0.0  1.4871773133e-03  2.7327021183e-03 -4.4434972404e-03\natom  2.8088992541e+00  2.9829026153e+00  1.5454412062e+01 Au  8.2154714000e-02 0.0 -1.6772005043e-03 -4.4714393188e-03  4.2085263539e-03\natom  2.5462290614e+00  2.5400927242e+00  1.0587600810e+01 Au -1.1007761600e-01 0.0  9.8547800867e-04  2.2567182018e-03  1.3283046039e-02\nenergy -5.4268568214e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom  3.9660510802e-02  6.5575079174e-02  1.9962188983e+01 Mg  3.6368016573e-01 0.0 -1.2444735791e-02 -1.5280759833e-02 -5.3107312453e-03\natom  2.8238591754e+00  2.8696675696e+00  1.9979677207e+01 O  -3.2855783427e-01 0.0  2.9643902593e-03  7.4293002563e-04  1.8551329079e-02\natom -4.5307012056e-02 -3.2959580241e-02  2.4004635222e+01 O  -3.4582154427e-01 0.0  4.9714005043e-03  3.1692857411e-03  8.5131988139e-03\natom  2.8294994217e+00  2.8535673498e+00  2.3920554378e+01 Mg  3.3573938573e-01 0.0 -2.8431006696e-03 -1.6680984311e-03  1.3228935926e-02\natom -9.4817303834e-02  2.1808892997e-02  2.8116906232e+01 Mg  3.3417688573e-01 0.0  1.2519605307e-02  3.4318970646e-04 -2.2401364670e-02\natom  2.8004841531e+00  2.8478446926e+00  2.8074298618e+01 O  -3.4470749427e-01 0.0  5.1626515475e-03 -1.2005902986e-03  7.8729634250e-03\natom -1.1939761227e-02  8.0918444777e-03  3.2108342360e+01 O  -3.1148883427e-01 0.0  1.5719262362e-03 -1.4510897816e-03  2.0750295015e-02\natom  2.9043056422e+00  2.8208425113e+00  3.1994454943e+01 Mg  3.3252873573e-01 0.0 -6.2664057083e-03  5.4462066473e-03 -2.2869489821e-03\natom  2.7524728298e-02  3.0569303633e-02  3.6139850053e+01 Al  3.9487424573e-01 0.0 -4.0810906430e-03 -1.4961293427e-03  8.3384901761e-03\natom  2.8897570198e+00  2.8281762356e+00  3.6151757367e+01 O  -2.9175961427e-01 0.0 -4.4988577385e-03  4.2568184961e-03 -9.8989468780e-03\natom -1.6306275480e-02 -5.1001531247e-02  4.0155233261e+01 O  -3.6358767427e-01 0.0  4.1236137094e-04  6.7423098230e-03 -2.4792482150e-02\natom  2.9108899389e+00  2.8522468471e+00  4.0140046441e+01 Mg  3.6938382573e-01 0.0 -6.7342125664e-03 -2.7230135552e-04  1.7331884080e-02\natom -2.3554659660e-02  5.7345043192e+00  1.9985527061e+01 Mg  3.7634946573e-01 0.0 -7.0550098139e-03  5.0156253182e-03 -6.6879236002e-03\natom  2.8167596072e+00  8.5327981855e+00  1.9991069155e+01 O  -3.9696956427e-01 0.0  2.2387032235e-03  3.8499232822e-04  4.9978869385e-03\natom  4.0148815998e-02  5.6250459665e+00  2.4005885333e+01 O  -3.4353227427e-01 0.0 -4.0323032092e-03  7.4866905255e-03  6.2474318525e-03\natom  2.8520338183e+00  8.5614021930e+00  2.4001141100e+01 Mg  3.3119083573e-01 0.0 -3.9857913984e-03 -2.2131337936e-03 -4.9466690285e-03\natom -2.2392553766e-02  5.6564010371e+00  2.8032210867e+01 Mg  3.3253515573e-01 0.0  3.4199772760e-03  4.5863541633e-03 -6.1801322752e-03\natom  2.8503550235e+00  8.5263469822e+00  2.8092549818e+01 O  -3.4323400427e-01 0.0  9.5199136093e-04  3.5127728751e-03  3.0486212731e-03\natom -3.4689756665e-02  5.7354544546e+00  3.2068007576e+01 O  -3.4818709427e-01 0.0  4.3764882902e-03 -7.3038478489e-03  9.9631545456e-03\natom  2.9183442087e+00  8.5151602201e+00  3.2087093166e+01 Mg  3.3050860573e-01 0.0 -1.2514146206e-02  1.3426774184e-04 -9.4658648173e-03\natom -3.4097251978e-02  5.7302623757e+00  3.6139558941e+01 Mg  3.2606827573e-01 0.0  2.7067068701e-03 -2.3987272413e-03  3.0463474640e-03\natom  2.8763887580e+00  8.5353088565e+00  3.6092380911e+01 O  -3.1798681427e-01 0.0  1.0498933166e-02 -1.3327647987e-02 -5.9801783698e-03\natom  7.4277021687e-02  5.7241082185e+00  4.0207501363e+01 O  -4.0796030427e-01 0.0 -7.1821006875e-03 -5.2514296435e-03 -1.0957991455e-02\natom  2.8172794330e+00  8.5362859015e+00  4.0209245164e+01 Mg  3.8407805573e-01 0.0  8.9636205027e-04  7.6582026485e-03  6.4552981776e-03\natom  2.8093441334e-02  1.1397454466e+01  2.0005162051e+01 Mg  4.2020360573e-01 0.0 -5.4197792694e-03  3.7973652991e-03 -5.3512152599e-03\natom  2.8473719777e+00  1.4252674193e+01  1.9939919942e+01 O  -3.9810233427e-01 0.0  2.6752048078e-03  8.8748693054e-04  7.8355656061e-03\natom -2.3024591520e-02  1.1385569224e+01  2.3948146342e+01 O  -3.4229430427e-01 0.0  1.6315396747e-03 -2.0173027296e-04  2.1063425117e-02\natom  2.8384270920e+00  1.4291572142e+01  2.4015367430e+01 Mg  3.3244800573e-01 0.0 -3.5105934558e-03 -8.0994879527e-04 -7.7706316215e-03\natom  1.2036534095e-02  1.1432013851e+01  2.8082437101e+01 Mg  3.4541654573e-01 0.0  2.7651301742e-04 -6.2955337503e-03 -1.0950189811e-02\natom  2.8109452794e+00  1.4306364180e+01  2.8088272556e+01 O  -3.4276288427e-01 0.0  2.4875415286e-03 -5.2561138087e-03  7.4689401071e-03\natom -4.7313579803e-02  1.1397449874e+01  3.2045202477e+01 O  -3.4505421427e-01 0.0  4.1407866029e-03  1.8504812804e-03  1.0121713676e-02\natom  2.8748320206e+00  1.4229025009e+01  3.2111886825e+01 Mg  3.3724641573e-01 0.0 -1.0005979559e-03  9.3424098412e-04 -1.0192542486e-02\natom  3.5919174598e-02  1.1387278670e+01  3.6075762509e+01 Mg  3.2472135573e-01 0.0 -1.0056817230e-03 -6.6561080475e-04  1.0550087050e-02\natom  2.8313916421e+00  1.4250412965e+01  3.6172414189e+01 O  -3.1508855427e-01 0.0 -9.8912136591e-03  1.2037188218e-02 -1.5200096429e-02\natom  3.9924807879e-03  1.1371613956e+01  4.0146284067e+01 O  -4.0722673427e-01 0.0 -2.3713144268e-03  3.7577620865e-03 -8.2620196452e-03\natom  2.8560762445e+00  1.4309011800e+01  4.0126151342e+01 Mg  3.7692001573e-01 0.0  2.3249876890e-03 -1.1793374570e-02  1.3996894456e-02\natom  5.6802229229e+00  2.2218831256e-02  2.0033458808e+01 Mg  3.6311355573e-01 0.0  9.6813085486e-03 -1.1145545737e-02 -1.0680128042e-02\natom  8.4908943053e+00  2.8667411021e+00  1.9992552968e+01 O  -3.9627826427e-01 0.0  3.8313883619e-03 -1.8386036578e-03  7.0842415771e-03\natom  5.6202187370e+00  4.1012968795e-02  2.4014598784e+01 O  -3.4285652427e-01 0.0  5.8429946002e-03 -7.6152559791e-04  8.1450356288e-03\natom  8.5062686436e+00  2.8979799357e+00  2.3991423940e+01 Mg  3.3155957573e-01 0.0  2.7983704010e-03 -5.7020569401e-03 -4.0294945247e-03\natom  5.7243459271e+00  1.7240669393e-02  2.8089359526e+01 Mg  3.4042378573e-01 0.0 -6.0446695749e-03  2.1644019645e-04 -1.1411704340e-02\natom  8.5075422622e+00  2.8683865243e+00  2.8063682458e+01 O  -3.4085911427e-01 0.0  4.3669601104e-03 -1.7775130829e-03  7.1543268836e-03\natom  5.7153886637e+00  7.7669930214e-02  3.2181730304e+01 O  -3.4554936427e-01 0.0 -2.6591319336e-03 -9.9104454699e-03 -1.6624185615e-03\natom  8.5742665782e+00  2.8562240400e+00  3.2133700291e+01 Mg  3.2647310573e-01 0.0  4.4048912698e-04 -2.9983819162e-03 -9.4560824684e-03\natom  5.6410369034e+00  1.4822689401e-02  3.6133885492e+01 Mg  3.2069177573e-01 0.0  1.0208189237e-02 -3.9480149914e-03  6.2488261440e-03\natom  8.5068455202e+00  2.8879934330e+00  3.6116353672e+01 O  -3.1372766427e-01 0.0 -1.1609132081e-02  1.1642917856e-02 -3.5747698273e-03\natom  5.7247695092e+00 -2.4546142195e-02  4.0182416101e+01 O  -4.0423237427e-01 0.0 -2.3101593792e-03  4.5101535813e-03 -8.2273014474e-03\natom  8.5748177546e+00  2.8162440710e+00  4.0158994213e+01 Mg  3.8237504573e-01 0.0  1.1246955553e-03 -2.4268892198e-03  9.7867089599e-03\natom  5.7057057078e+00  5.6902534750e+00  2.0041291628e+01 Mg  3.6453755573e-01 0.0  4.9982329944e-03  1.0700863962e-02 -1.2158516827e-02\natom  8.5480665667e+00  8.5612850866e+00  1.9948168275e+01 O  -4.0353409427e-01 0.0 -2.8225890498e-03 -2.8870681983e-03  8.6779011250e-03\natom  5.6596094894e+00  5.7089049761e+00  2.4058615018e+01 O  -3.4059017427e-01 0.0  2.9294276275e-03 -1.0357738976e-04  5.5753960914e-03\natom  8.4862166477e+00  8.5694963996e+00  2.4091726740e+01 Mg  3.3477781573e-01 0.0  5.3671407140e-03 -4.8294953136e-04 -1.8727792596e-02\natom  5.7631617493e+00  5.6906794193e+00  2.8100500670e+01 Mg  3.3808047573e-01 0.0 -1.1510691045e-02 -1.0953090310e-03 -1.7180935562e-02\natom  8.5087034988e+00  8.6186223400e+00  2.8092769178e+01 O  -3.3906378427e-01 0.0  2.1289835072e-03 -5.4460215234e-03  3.6601097888e-03\natom  5.7317874035e+00  5.6769379177e+00  3.2039387261e+01 O  -3.1437354427e-01 0.0 -1.9112898651e-03  2.4542882676e-03  2.5409327025e-02\natom  8.5394271741e+00  8.5504626826e+00  3.2026176640e+01 Mg  3.3132301573e-01 0.0  1.4000058621e-03 -3.5222972585e-04 -3.7709303919e-03\natom  5.7367310212e+00  5.6721488040e+00  3.6164118216e+01 Al  4.0100789573e-01 0.0 -1.4118808677e-03  1.1839633743e-03  9.3194405337e-03\natom  8.5021460362e+00  8.4905116358e+00  3.6173145041e+01 O  -2.9205142427e-01 0.0 -1.7149962466e-03  3.6691066065e-04 -1.3740383038e-02\natom  5.6985134295e+00  5.6690123124e+00  4.0077693174e+01 O  -3.5931957427e-01 0.0  2.0074394557e-03  1.0814152343e-03 -2.2953252318e-02\natom  8.5504404027e+00  8.5048254976e+00  4.0150935231e+01 Mg  3.6974851573e-01 0.0 -1.1699934521e-03  5.6971180278e-03  1.5553048484e-02\natom  5.6539648779e+00  1.1394717160e+01  2.0028115079e+01 Mg  4.2358308573e-01 0.0  7.6739519798e-03  9.4231667648e-04 -6.7719946206e-03\natom  8.6121828341e+00  1.4214088085e+01  2.0040849111e+01 O  -4.0127364427e-01 0.0 -6.1770800779e-03  4.8649302517e-03  3.0809371865e-03\natom  5.7196578382e+00  1.1406359214e+01  2.4003883470e+01 O  -3.4098419427e-01 0.0 -5.1943932397e-03  2.8809234697e-04  1.3732095845e-02\natom  8.5824947475e+00  1.4242846389e+01  2.4062927165e+01 Mg  3.3196733573e-01 0.0 -4.6218885885e-03  2.0767919346e-03 -1.3898375777e-02\natom  5.6656694249e+00  1.1364797563e+01  2.8028407359e+01 Mg  3.3752741573e-01 0.0 -1.7439532031e-03  6.0404516105e-03 -6.3002835557e-03\natom  8.5064683498e+00  1.4254254665e+01  2.8057323115e+01 O  -3.4172686427e-01 0.0  3.5227707345e-03 -8.7879874882e-04  9.3465151954e-03\natom  5.6302592669e+00  1.1379437233e+01  3.2092602814e+01 O  -3.4173102427e-01 0.0  7.9330505849e-03  2.1320258553e-03  5.9402115041e-03\natom  8.5311239449e+00  1.4195848205e+01  3.2118042569e+01 Mg  3.3654145573e-01 0.0 -1.0185624723e-03  8.8318693649e-03 -1.0150593301e-02\natom  5.6928928553e+00  1.1366981671e+01  3.6065027467e+01 Mg  3.2221140573e-01 0.0 -1.7037949355e-03  2.5426917194e-03  1.6245834111e-02\natom  8.6080604347e+00  1.4235208343e+01  3.6156377804e+01 O  -3.1382534427e-01 0.0  6.2618783512e-03 -1.4400528711e-02 -1.0621736880e-02\natom  5.6710398561e+00  1.1419965525e+01  4.0139654039e+01 O  -4.0916961427e-01 0.0  3.0924528245e-03 -4.5216776632e-03 -6.2109223951e-03\natom  8.5359110366e+00  1.4233419264e+01  4.0200148930e+01 Mg  3.8299523573e-01 0.0 -2.9470861768e-03  1.1422760031e-03  8.6617836134e-03\natom  1.1414877230e+01 -3.6100210348e-02  2.0071683052e+01 Mg  4.1987661573e-01 0.0  5.1793025489e-04 -4.6162123704e-04 -8.3745343681e-03\natom  1.4291661847e+01  2.7998579735e+00  2.0006203725e+01 O  -3.9797987427e-01 0.0 -6.3221607586e-03  8.1088000484e-03  2.7122177977e-03\natom  1.1416963279e+01  8.4972662913e-03  2.4003826949e+01 O  -3.4263829427e-01 0.0 -5.6041993793e-03 -7.7604697252e-04  1.5361583129e-02\natom  1.4243105792e+01  2.8619375131e+00  2.4004798173e+01 Mg  3.2500840573e-01 0.0  1.5709377128e-03 -4.1198289019e-03 -7.9521585615e-03\natom  1.1419543889e+01 -3.5803202114e-02  2.8094849407e+01 Mg  3.4250693573e-01 0.0 -5.9647073762e-03  5.4829113871e-03 -1.1853129535e-02\natom  1.4285515192e+01  2.8511751646e+00  2.7990097133e+01 O  -3.3964755427e-01 0.0 -8.5575345316e-03 -3.4603861765e-03  1.7078809027e-02\natom  1.1339131248e+01  1.3323154035e-02  3.2119280699e+01 O  -3.4578604427e-01 0.0  6.6809058795e-03 -3.0134521517e-03 -3.0208845005e-04\natom  1.4243073099e+01  2.7963516058e+00  3.2049072579e+01 Mg  3.3710080573e-01 0.0 -2.9747619545e-03  1.0327829333e-02 -3.8237604609e-03\natom  1.1412622862e+01 -4.7049301623e-02  3.6089384259e+01 Mg  3.2015130573e-01 0.0 -3.8717898587e-03  6.3100493797e-03  7.2967005446e-03\natom  1.4178171235e+01  2.8521681589e+00  3.6050496835e+01 O  -3.1948017427e-01 0.0  1.5789812030e-02 -8.8296469411e-03  1.9400313524e-05\natom  1.1400530487e+01 -4.8017937370e-05  4.0170273137e+01 O  -4.0444557427e-01 0.0  1.1895800977e-04 -1.0229666991e-03 -8.3219504388e-03\natom  1.4145905090e+01  2.8343744612e+00  4.0159724516e+01 Mg  3.8718862573e-01 0.0  6.4889234973e-03  4.5383458113e-03  9.7663508148e-03\natom  1.1353752928e+01  5.6584909039e+00  2.0025714144e+01 Mg  4.2804426573e-01 0.0  1.7740963777e-03  6.2038816727e-03 -5.5266693013e-03\natom  1.4190203158e+01  8.6097452010e+00  1.9975449663e+01 O  -4.0027374427e-01 0.0  4.8473861335e-03 -9.0005122960e-03  4.8993120020e-03\natom  1.1382961912e+01  5.6858276990e+00  2.4055098465e+01 O  -3.4168474427e-01 0.0 -2.4491616493e-03  2.1139317749e-03  6.8728161325e-03\natom  1.4217532489e+01  8.5541011232e+00  2.4019883213e+01 Mg  3.3496159573e-01 0.0  2.5418987776e-03 -2.6029754627e-03 -9.5207536183e-03\natom  1.1348173644e+01  5.6797215786e+00  2.8053615813e+01 Mg  3.3770078573e-01 0.0  5.9635284823e-03 -2.6368992428e-05 -7.3614674162e-03\natom  1.4214331633e+01  8.4447387874e+00  2.8087560620e+01 O  -3.4377122427e-01 0.0  2.6911597545e-04  1.2382962617e-02  2.8217928928e-03\natom  1.1316209723e+01  5.7491360896e+00  3.2055651792e+01 O  -3.4576962427e-01 0.0  4.6918098973e-03 -4.0498220470e-03  8.2032391413e-03\natom  1.4252128005e+01  8.5069428600e+00  3.2158094159e+01 Mg  3.2926883573e-01 0.0  1.3388329258e-03 -1.5024568264e-03 -1.6746592787e-02\natom  1.1378605527e+01  5.7033008425e+00  3.6101922818e+01 Mg  3.2126844573e-01 0.0  2.1531176321e-03 -1.7941709968e-03  5.8386378615e-03\natom  1.4235032712e+01  8.5904637787e+00  3.6112987957e+01 O  -3.1609008427e-01 0.0 -1.1767775212e-02  8.2810440021e-03 -5.2208982137e-03\natom  1.1373938546e+01  5.7237160247e+00  4.0161032207e+01 O  -4.0493978427e-01 0.0  2.1276422158e-03 -2.0416753459e-03 -7.6606508806e-03\natom  1.4270267712e+01  8.5790778017e+00  4.0141321817e+01 Mg  3.8109864573e-01 0.0  1.5595367148e-03 -3.6562661292e-03  1.2121053990e-02\natom  1.1445560181e+01  1.1429482336e+01  2.0043673495e+01 Mg  4.0941793573e-01 0.0 -5.3155102752e-03 -3.0468801986e-03 -7.5307949557e-03\natom  1.4257271688e+01  1.4240195141e+01  1.9959621639e+01 O  -4.0225356427e-01 0.0 -1.9555204962e-05  8.3075329315e-04  5.0754135080e-03\natom  1.1379316196e+01  1.1385540972e+01  2.4027101116e+01 O  -3.3947896427e-01 0.0  2.0989745265e-03  6.2545715227e-04  1.6175884437e-02\natom  1.4199398376e+01  1.4235914383e+01  2.4046440893e+01 Mg  3.3087074573e-01 0.0  8.0541727049e-03  3.4947598495e-03 -1.6052047952e-02\natom  1.1426719916e+01  1.1365036576e+01  2.8021051846e+01 Mg  3.4487803573e-01 0.0 -2.1231177536e-03  7.4861374660e-04 -6.6535382083e-03\natom  1.4243703928e+01  1.4315689260e+01  2.8066976761e+01 O  -3.3802952427e-01 0.0 -2.4101680656e-03 -9.6750734330e-03  9.4244700276e-03\natom  1.1370081937e+01  1.1410982901e+01  3.2079464645e+01 O  -3.1335011427e-01 0.0  6.8169797591e-04 -1.1804084878e-03  2.0500658711e-02\natom  1.4306390712e+01  1.4200053336e+01  3.2075777790e+01 Mg  3.3068728573e-01 0.0 -7.0709556258e-03  2.7670318833e-03 -7.0496335947e-03\natom  1.1374405630e+01  1.1424927832e+01  3.6128726691e+01 Al  3.9501345573e-01 0.0  2.3991998796e-03  1.1241489595e-03  1.0801674686e-02\natom  1.4227477852e+01  1.4261682819e+01  3.6066532747e+01 O  -2.9428120427e-01 0.0  2.0757822326e-03 -3.6061934246e-03 -2.8116003044e-03\natom  1.1401820886e+01  1.1412396190e+01  4.0193268910e+01 O  -3.6532453427e-01 0.0 -4.9718169653e-04 -1.1117548609e-03 -2.4896812942e-02\natom  1.4244910612e+01  1.4241816148e+01  4.0139012477e+01 Mg  3.7006804573e-01 0.0  1.3167932157e-03 -1.4888159640e-03  1.4075586373e-02\natom  2.9380261584e+00  2.7752463523e+00  1.5857923476e+01 Au  6.6300655727e-02 0.0 -6.2914153563e-04  3.7746923977e-04  4.3033525034e-02\natom  2.9115594877e+00  2.8905288784e+00  1.1403570413e+01 Au -2.0772577427e-01 0.0  8.7093577283e-05  8.5285032860e-04 -5.9260701712e-02\nenergy -5.4395980362e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -4.3547733853e-02  2.5686478445e-02  1.9918729348e+01 Mg  4.1988647736e-01 0.0  8.4667354265e-03 -5.9135494325e-04  1.4430468163e-02\natom  2.8528932279e+00  2.8837431936e+00  2.0073990936e+01 O  -4.0041237264e-01 0.0  7.2151428499e-04 -5.4878919007e-03 -1.3436424830e-02\natom -6.8150851286e-02  5.5670061508e-02  2.4041064132e+01 O  -3.4316076264e-01 0.0  7.3553779208e-03 -5.1998820606e-03 -4.7866509720e-03\natom  2.8686233637e+00  2.7798005353e+00  2.4048228177e+01 Mg  3.2676688736e-01 0.0 -5.0184528691e-03  6.7015815900e-03 -3.5311025938e-03\natom  4.4098418903e-02  8.9255878044e-02  2.8093024801e+01 Mg  3.3130007736e-01 0.0 -8.0949846659e-03 -7.2765121025e-03 -6.6880813665e-03\natom  2.8210185204e+00  2.8783326435e+00  2.8039482325e+01 O  -3.4002887264e-01 0.0  4.0746619649e-03 -6.2700462095e-04  1.6604314239e-03\natom  2.8654576569e-02  1.7659319288e-02  3.2008095817e+01 O  -3.3944958264e-01 0.0 -1.0932332218e-03  2.4192001152e-03  1.0082201357e-02\natom  2.8035816597e+00  2.8508443303e+00  3.2137711782e+01 Mg  3.4230942736e-01 0.0  9.1994868335e-03  1.1766160413e-04 -6.1968462949e-03\natom  2.9991179761e-02  5.1314847816e-02  3.6119810605e+01 Mg  3.3595453736e-01 0.0 -3.5805233084e-03 -6.7585605663e-03  7.9766862329e-04\natom  2.8638986330e+00  2.8046259601e+00  3.6115401761e+01 O  -3.3961052264e-01 0.0 -2.2002453713e-03  5.3036475394e-03  4.6947934666e-04\natom  1.2026461856e-02 -4.2938883036e-02  4.0139384583e+01 O  -4.0236528264e-01 0.0 -1.8049351381e-03  5.6137206592e-03  5.9588390691e-03\natom  2.8608386564e+00  2.8120750331e+00  4.0127476777e+01 Mg  4.1090123736e-01 0.0  6.8952973276e-04  1.0491499274e-03 -2.1045305012e-03\natom -2.3967262433e-02  5.6978806926e+00  1.9980297830e+01 Mg  4.1071438736e-01 0.0  6.8498258043e-03  2.0276821028e-04  9.0082855846e-03\natom  2.8431180155e+00  8.4913235755e+00  2.0012547630e+01 O  -3.9285735264e-01 0.0 -1.8624094616e-03  3.6924741777e-03 -8.2310589025e-03\natom  7.0013119556e-02  5.6731212948e+00  2.4035053971e+01 O  -3.4111092264e-01 0.0 -9.8500738154e-03  4.7438148167e-03  5.9595711220e-04\natom  2.7536345577e+00  8.4851009157e+00  2.4041206598e+01 Mg  3.3433488736e-01 0.0  9.9529519885e-03  7.6359447390e-03 -3.3772085812e-03\natom -2.7883662852e-03  5.7189827147e+00  2.8084284837e+01 Mg  3.4171221736e-01 0.0 -2.1027454825e-06 -8.6427484229e-04 -3.0571932573e-03\natom  2.8781649304e+00  8.4882090425e+00  2.8087312745e+01 O  -3.3764622264e-01 0.0 -1.2661533392e-03  8.1665735763e-03 -2.7335484014e-03\natom -2.4864353154e-02  5.7284033200e+00  3.2102454919e+01 O  -3.3801031264e-01 0.0  4.7298319707e-03 -2.6307486330e-03 -5.0926129455e-04\natom  2.9187635200e+00  8.5370351401e+00  3.2027881494e+01 Mg  3.4246187736e-01 0.0 -1.9619442596e-03 -1.6794288135e-03  8.3203562852e-03\natom -2.2241318995e-03  5.7191680212e+00  3.6165664315e+01 Mg  3.3197137736e-01 0.0  1.4543009366e-04  7.0294046257e-04 -3.1720997385e-03\natom  2.8910537498e+00  8.5140183720e+00  3.6088541536e+01 O  -3.4243460264e-01 0.0 -8.1669422571e-03  4.5306847017e-03  1.3841390737e-03\natom  6.9857273853e-02  5.6965423886e+00  4.0146433809e+01 O  -3.9922682264e-01 0.0 -6.0526829844e-03 -1.1976675002e-03  5.7158491824e-03\natom  2.8337562373e+00  8.5234616163e+00  4.0136436497e+01 Mg  4.0987467736e-01 0.0  4.6439733234e-03  3.7050555560e-03 -4.1486715831e-03\natom -3.4521873408e-02  1.1423903411e+01  1.9992391774e+01 Mg  3.8996894736e-01 0.0  6.3696087103e-03 -3.4634837895e-03  7.9509795108e-03\natom  2.8065702613e+00  1.4219652818e+01  1.9981692826e+01 O  -3.9229501264e-01 0.0  1.8388626271e-03  5.0993947667e-03 -7.8625481366e-03\natom  2.1945387906e-04  1.1424133486e+01  2.4032443277e+01 O  -3.4289328264e-01 0.0 -1.8713170676e-03 -3.7257192749e-03 -4.3791961675e-04\natom  2.8045080223e+00  1.4273572502e+01  2.4039781348e+01 Mg  3.3564145736e-01 0.0  2.6708652085e-03 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8.1463115844e-03  7.0045939245e-03\natom  1.1475886939e+01 -2.0363706150e-02  3.2085309322e+01 O  -3.4175434264e-01 0.0 -8.0249892923e-03  3.5926426778e-03  2.2032726983e-03\natom  1.4349848419e+01  2.8875215873e+00  3.2051324168e+01 Mg  3.4234866736e-01 0.0 -1.3086906118e-02 -4.1668126810e-03  2.7693190008e-03\natom  1.1300985466e+01 -2.0780315142e-02  3.6099638876e+01 Mg  3.3315627736e-01 0.0  1.3828887519e-02  3.1572349059e-03  6.0894509286e-04\natom  1.4229516848e+01  2.9166715745e+00  3.6089661425e+01 O  -3.4283003264e-01 0.0  3.8811320590e-03 -5.3182445052e-03  1.9395037260e-03\natom  1.1429621892e+01 -1.0409300495e-01  4.0170348027e+01 O  -4.0266273264e-01 0.0 -2.2388757239e-03  1.0354909745e-02  1.8898863862e-03\natom  1.4231341907e+01  2.8615833029e+00  4.0100698302e+01 Mg  4.1651727736e-01 0.0  2.6838195350e-04 -3.4773004568e-03 -2.9965988931e-03\natom  1.1414248688e+01  5.6765510530e+00  1.9986832503e+01 Mg  4.0726734736e-01 0.0 -4.1569280463e-03  3.6808874713e-03  6.7024595595e-03\natom  1.4270172394e+01  8.5598538082e+00  1.9992556199e+01 O  -3.8508025264e-01 0.0 -1.8870276794e-03 -1.5486879960e-03 -5.9067751916e-03\natom  1.1388173852e+01  5.6912281012e+00  2.4023546239e+01 O  -3.4280006264e-01 0.0  3.6128137431e-03  3.3107825150e-03 -1.0106809627e-04\natom  1.4218907661e+01  8.5626223512e+00  2.4041547769e+01 Mg  3.4025849736e-01 0.0  1.2252005249e-03  1.7292166578e-03  5.1129663979e-03\natom  1.1450369553e+01  5.7687671868e+00  2.8133756182e+01 Mg  3.3911281736e-01 0.0 -3.8076436054e-03 -6.0602235684e-03 -7.0325499767e-03\natom  1.4272692079e+01  8.6113656788e+00  2.8113703732e+01 O  -3.4166156264e-01 0.0  1.3911900413e-03 -4.1032315940e-03 -4.3375165431e-03\natom  1.1399767132e+01  5.7518464669e+00  3.2027779127e+01 O  -3.4237463264e-01 0.0  2.2328437365e-03 -4.2058247588e-03  7.2738878098e-03\natom  1.4290385716e+01  8.5143735838e+00  3.2131318934e+01 Mg  3.4011693736e-01 0.0 -4.5751712717e-03  6.5717191237e-03 -2.8922516095e-03\natom  1.1413877319e+01  5.7153399088e+00  3.6117564533e+01 Mg  3.3217065736e-01 0.0 -5.0389347536e-03  2.2690882469e-03 -7.6301986769e-04\natom  1.4244373250e+01  8.5307411620e+00  3.6145752763e+01 O  -3.4144480264e-01 0.0  3.2917051555e-03  4.8390859864e-03 -2.0578448518e-03\natom  1.1386494755e+01  5.7616427875e+00  4.0161741705e+01 O  -4.0270142264e-01 0.0  4.1382410491e-03 -7.3445370226e-03  5.6454304736e-03\natom  1.4298899063e+01  8.5678420957e+00  4.0167552291e+01 Mg  4.1607447736e-01 0.0 -6.7876448821e-03 -1.6012792591e-03 -6.0935647494e-03\natom  1.1341237575e+01  1.1369849538e+01  2.0070834338e+01 Mg  2.8525736736e-01 0.0 -3.4598410927e-04 -5.0303460418e-05  7.8325141735e-03\natom  1.4280166153e+01  1.4226169727e+01  2.0015542524e+01 O  -3.8352107264e-01 0.0 -4.2446042910e-03  3.4168285787e-03 -1.0189054963e-02\natom  1.1336883476e+01  1.1381140254e+01  2.4134944245e+01 O  -3.4020571264e-01 0.0  8.2077662792e-03  1.9543148342e-03 -1.0832122197e-02\natom  1.4200648619e+01  1.4288663948e+01  2.3984842119e+01 Mg  3.3307077736e-01 0.0  5.5319338445e-03 -4.6780042917e-04  1.2248038738e-02\natom  1.1357447323e+01  1.1452324021e+01  2.8085452007e+01 Mg  3.3819643736e-01 0.0  7.9464587232e-03 -1.1349311374e-03 -3.0234469933e-04\natom  1.4286772087e+01  1.4315338187e+01  2.8015901228e+01 O  -3.4515575264e-01 0.0 -3.0999415812e-03 -5.5877359810e-03  5.1251404609e-03\natom  1.1336412348e+01  1.1375330310e+01  3.2101287446e+01 O  -3.4133571264e-01 0.0  8.1909648064e-03  6.6307413620e-03 -6.2207118001e-04\natom  1.4295247980e+01  1.4256787143e+01  3.2071100094e+01 Mg  3.4116885736e-01 0.0 -4.6358127379e-03  1.3160211420e-03 -2.3643160101e-03\natom  1.1394119988e+01  1.1438632578e+01  3.6131609959e+01 Mg  3.3401562736e-01 0.0 -2.2080876761e-03 -5.5648163144e-03 -8.1601455212e-04\natom  1.4234518197e+01  1.4258492545e+01  3.6071918070e+01 O  -3.4233195264e-01 0.0  9.7018028378e-04 -1.1462618723e-03  1.8380792521e-03\natom  1.1327848904e+01  1.1391417378e+01  4.0157054844e+01 O  -4.0166597264e-01 0.0  8.1562937834e-03  1.2318974053e-03  3.4863362718e-03\natom  1.4265934948e+01  1.4177167923e+01  4.0117350983e+01 Mg  4.0646922736e-01 0.0 -2.9301466043e-03  6.6165607749e-03 -3.9075695190e-03\natom  1.0991010519e+01  1.1442403489e+01  1.5037108427e+01 Au  1.1292712736e-01 0.0 -1.3634521782e-02  1.0430312258e-04 -9.1003618778e-03\natom  6.0174512152e+00  1.1456053509e+01  1.4543021350e+01 Au  7.1321477364e-02 0.0  1.3515114670e-02  5.4102226329e-05  2.7433050061e-05\nenergy -5.4268533628e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom  2.5704430842e-02  6.6216565558e-03  2.0033275297e+01 Mg  4.1701047255e-01 0.0 -3.4007400900e-03 -5.6787470654e-03 -6.5299073252e-03\natom  2.8187717685e+00  2.8158706423e+00  1.9949108980e+01 O  -3.9549859745e-01 0.0  8.6503353522e-03 -1.6450980414e-03  5.1126891224e-03\natom  8.3116574047e-03 -3.6723725438e-02  2.4030235529e+01 O  -3.4168465745e-01 0.0 -1.6472762450e-03  4.7410890695e-03  1.4545527621e-02\natom  2.8630090445e+00  2.8120230279e+00  2.4054942997e+01 Mg  3.3170801255e-01 0.0  3.3546468700e-03  5.4709443248e-03 -1.4585195311e-02\natom -3.9373914959e-02  3.2888375366e-02  2.8052595795e+01 Mg  3.4671024255e-01 0.0  5.2288658313e-03 -6.4511896109e-03 -1.8594193312e-02\natom  2.8621727651e+00  2.9246652099e+00  2.7997883201e+01 O  -3.3922911745e-01 0.0 -3.4019761897e-03 -9.3011150014e-03  2.4471399882e-02\natom -8.3910126681e-02 -4.6382228349e-02  3.2141897828e+01 O  -3.0721690745e-01 0.0  9.6223480860e-03  5.0058992968e-03  2.6675028772e-02\natom  2.9158427973e+00  2.8967969105e+00  3.2058008224e+01 Mg  3.3804547255e-01 0.0 -4.9012603684e-03 -3.5023631336e-03 -1.6683971710e-02\natom  2.1217333174e-02  8.4745669027e-02  3.6081885335e+01 Al  4.0756240255e-01 0.0 -1.0142675467e-02 -6.7788169515e-03  3.9683816967e-03\natom  2.8441412832e+00  2.8673787524e+00  3.6136941632e+01 O  -2.8578929745e-01 0.0  1.4568438122e-04 -3.5184028961e-03 -7.2017556157e-03\natom -1.1462794388e-02  4.5392616643e-02  4.0223974784e+01 O  -3.6611721745e-01 0.0  3.4742856485e-03 -2.9748676589e-03 -2.6769229339e-02\natom  2.9106337110e+00  2.8694880456e+00  4.0170049790e+01 Mg  3.7818056255e-01 0.0 -4.2019543309e-03 -4.6567170072e-03  1.7556393796e-02\natom  3.6120827258e-02  5.6315251566e+00  2.0100323191e+01 Mg  4.0553407255e-01 0.0 -3.7327113554e-03  7.7203946711e-03 -1.2519295316e-02\natom  2.8756924696e+00  8.5050231063e+00  2.0023815140e+01 O  -3.9864098745e-01 0.0 -4.0866370108e-03  1.7780296175e-04  9.0938785026e-04\natom  1.6064976369e-02  5.6952700550e+00  2.3948534284e+01 O  -3.4352135745e-01 0.0  2.6769589348e-04 -3.0123573329e-03  2.6207865519e-02\natom  2.8346658947e+00  8.6195958701e+00  2.3952888761e+01 Mg  3.2653433255e-01 0.0  5.0029638910e-03 -6.9632876291e-03 -6.9909943564e-03\natom  4.0226181380e-02  5.6919421720e+00  2.8067694498e+01 Mg  3.4004133255e-01 0.0 -2.8076623325e-03  4.1554175780e-03 -1.8364692907e-02\natom  2.8401131055e+00  8.5094673260e+00  2.8089395771e+01 O  -3.4123609745e-01 0.0  4.4870643017e-04  3.3086783966e-03  1.4914438683e-02\natom  4.6468021909e-02  5.6648926720e+00  3.2086432499e+01 O  -3.4636964745e-01 0.0 -8.7812182176e-04 -9.4257317410e-04  1.0899314385e-02\natom  2.8589099076e+00  8.5591467105e+00  3.2118749724e+01 Mg  3.2909964255e-01 0.0 -4.2186849665e-03 -3.3320538753e-04 -1.8532594605e-02\natom  5.7929890331e-02  5.6693142717e+00  3.6179366302e+01 Mg  3.1968057255e-01 0.0 -1.1502263725e-02  6.2227241589e-03 -3.2722907447e-03\natom  2.8466978935e+00  8.5418661868e+00  3.6061761832e+01 O  -3.1004296745e-01 0.0  1.6742557945e-02 -1.3968759341e-02  4.4009344137e-03\natom  1.9076897238e-02  5.6771843002e+00  4.0181895141e+01 O  -4.0503223745e-01 0.0  3.4745278238e-03  2.5430936602e-03 -8.0912215367e-03\natom  2.8311918603e+00  8.5376311597e+00  4.0153661633e+01 Mg  3.9256338255e-01 0.0 -3.7048625599e-03  6.9243049221e-03  1.2105621488e-02\natom  1.9103013252e-02  1.1385678261e+01  1.9945010353e+01 Mg  4.1848844255e-01 0.0 -2.8987694760e-03 -1.6255916343e-03 -2.9247925237e-03\natom  2.8735845558e+00  1.4211708524e+01  1.9976912575e+01 O  -3.9713727745e-01 0.0 -4.7063061554e-03  5.7471020658e-03  7.0119828621e-03\natom -1.9128656833e-02  1.1384958918e+01  2.4046721272e+01 O  -3.4498792745e-01 0.0 -4.2721932316e-04  1.1427069456e-03  1.0520379189e-02\natom  2.8550566807e+00  1.4229846737e+01  2.4026475145e+01 Mg  3.2725245255e-01 0.0  1.0792186347e-03 -3.1695794301e-03 -1.0932542743e-02\natom  1.9416367615e-03  1.1355489699e+01  2.8112415827e+01 Mg  3.3656717255e-01 0.0  3.6262159545e-03  3.4072385129e-03 -2.2209727532e-02\natom  2.8276536318e+00  1.4210427535e+01  2.8002097403e+01 O  -3.4392755745e-01 0.0 -1.6822763425e-04  3.9162855363e-03  2.6029419700e-02\natom -1.1412168629e-02  1.1308230543e+01  3.2101314810e+01 O  -3.4294950745e-01 0.0 -2.6192812707e-03  9.9813913546e-03  9.7539194570e-03\natom  2.8826431463e+00  1.4263954288e+01  3.2147440337e+01 Mg  3.3597892255e-01 0.0 -4.7924816170e-04 -5.7896974197e-03 -2.3391314169e-02\natom  3.7664336549e-02  1.1400324147e+01  3.6050382998e+01 Mg  3.2411829255e-01 0.0 -3.7553885408e-03 -1.2973451985e-03  9.6689701827e-03\natom  2.8129396773e+00  1.4232828120e+01  3.6072845944e+01 O  -3.1583076745e-01 0.0 -1.0833442682e-02  1.6984700148e-02  1.0374072793e-04\natom -1.6102166176e-02  1.1398878318e+01  4.0177253464e+01 O  -4.0609197745e-01 0.0 -3.7181338137e-04  9.8333530354e-04 -9.5729342980e-03\natom  2.8456176316e+00  1.4291805618e+01  4.0173449653e+01 Mg  3.8872436255e-01 0.0  1.1388372164e-03 -4.2584487497e-03  8.5306027259e-03\natom  5.7041219284e+00  4.6624925858e-02  1.9955736438e+01 Mg  4.3151836255e-01 0.0  4.2860420073e-03 -1.2431017872e-02 -4.7041776268e-04\natom  8.6234977197e+00  2.8611066762e+00  1.9945469992e+01 O  -3.9587682745e-01 0.0 -7.6579007606e-03 -2.6426065264e-03  7.2180083107e-03\natom  5.6639385871e+00 -3.3974438686e-02  2.4128334097e+01 O  -3.4492982745e-01 0.0  4.9818633125e-03  5.4004436931e-03  2.6747305321e-03\natom  8.6093948458e+00  2.8261182106e+00  2.4072603488e+01 Mg  3.3903672255e-01 0.0 -8.1038602916e-03  4.8771434425e-03 -1.6697579750e-02\natom  5.7277428608e+00  7.6516895004e-03  2.8074875154e+01 Mg  3.3322601255e-01 0.0 -5.0126200794e-03 -3.7549652821e-03 -1.6123765445e-02\natom  8.5261356541e+00  2.8201421789e+00  2.8055101288e+01 O  -3.4057063745e-01 0.0  4.2075158665e-03  4.0844356928e-03  1.6111062677e-02\natom  5.6797999644e+00 -5.1090253883e-02  3.2061308214e+01 O  -3.4368420745e-01 0.0 -1.0335154057e-03  8.9937100766e-03  1.4741811913e-02\natom  8.5987976215e+00  2.8982405667e+00  3.2115315695e+01 Mg  3.3921864255e-01 0.0  2.8799835600e-04 -9.4854743607e-03 -1.4895407015e-02\natom  5.6413661881e+00  3.5962732782e-02  3.6110993068e+01 Mg  3.2805351255e-01 0.0  1.0026002436e-02 -5.5924150543e-03  4.3361010603e-03\natom  8.5792219878e+00  2.9110691794e+00  3.6171630236e+01 O  -3.1715099745e-01 0.0 -1.7356556773e-02  6.9316289474e-03 -1.6315380206e-02\natom  5.6828796131e+00  6.2281211187e-03  4.0188329941e+01 O  -4.0611602745e-01 0.0 -1.1202977093e-03  9.4476371270e-04 -1.1536809209e-02\natom  8.5934006586e+00  2.8779975762e+00  4.0052973083e+01 Mg  3.7448444255e-01 0.0  3.6074902574e-03 -8.7426225633e-03  1.7619574389e-02\natom  5.7086008436e+00  5.6202315116e+00  1.9926523126e+01 Mg  4.2710805255e-01 0.0  1.6050345648e-03  1.3310671915e-02  2.0633580903e-03\natom  8.5523051465e+00  8.5414033740e+00  1.9991151585e+01 O  -3.9635527745e-01 0.0  1.3243446386e-03 -7.3625314332e-03  1.2139207968e-02\natom  5.6985010329e+00  5.7413531020e+00  2.4041218749e+01 O  -3.4747361745e-01 0.0  2.9136160659e-03 -9.3790505854e-03  1.0580100287e-02\natom  8.6023686556e+00  8.5504316911e+00  2.3980418988e+01 Mg  3.2525339255e-01 0.0 -8.8688197507e-03 -1.0895658525e-03 -1.1490275673e-02\natom  5.6580220251e+00  5.7371173379e+00  2.8078146100e+01 Mg  3.3432185255e-01 0.0  5.1302804190e-03 -1.0155938284e-03 -2.7339509688e-02\natom  8.5776900058e+00  8.5029001503e+00  2.8059233382e+01 O  -3.4138216745e-01 0.0 -9.4818519526e-04  2.4527872949e-03  1.8393244390e-02\natom  5.7306385257e+00  5.6714929557e+00  3.2053501492e+01 O  -3.0959451745e-01 0.0 -6.9542587724e-04  1.5650622220e-03  3.1572000132e-02\natom  8.5746200893e+00  8.4938381205e+00  3.2101328416e+01 Mg  3.3037376255e-01 0.0 -2.4266591521e-03  4.5912045103e-03 -2.0133760609e-02\natom  5.6552139868e+00  5.7571690313e+00  3.6167587734e+01 Al  4.0036469255e-01 0.0  6.1775462055e-03 -4.2862965678e-03  3.4461595982e-03\natom  8.5950543011e+00  8.5704378989e+00  3.6092979916e+01 O  -2.8896338745e-01 0.0 -3.2222809913e-03  1.5847629502e-03 -6.8351045585e-04\natom  5.7531309704e+00  5.6010637374e+00  4.0160684762e+01 O  -3.5859373745e-01 0.0 -5.9558069783e-03  1.3889551449e-02 -2.4774551674e-02\natom  8.5401863149e+00  8.5421093378e+00  4.0174536718e+01 Mg  3.8194523255e-01 0.0  9.8647656431e-04 -6.0313286688e-04  1.3317059201e-02\natom  5.6896217018e+00  1.1399972942e+01  1.9981076379e+01 Mg  3.3105769255e-01 0.0  9.0201512461e-03 -1.9975033936e-03 -1.6013496539e-02\natom  8.5846961649e+00  1.4231952648e+01  2.0041775870e+01 O  -3.9785751745e-01 0.0 -4.4043728884e-03  9.2668934049e-03  1.2923196995e-02\natom  5.7236612416e+00  1.1340563812e+01  2.4054711544e+01 O  -3.4440961745e-01 0.0 -1.5873284610e-03  5.9096717365e-03  1.3743083669e-02\natom  8.5845188141e+00  1.4236212846e+01  2.4066627211e+01 Mg  3.2925343255e-01 0.0 -7.8594464166e-03 -4.3494226294e-03 -1.9699007770e-02\natom  5.7538665840e+00  1.1339621991e+01  2.8124375941e+01 Mg  3.4079039255e-01 0.0 -5.0311816145e-03  3.6551829048e-03 -2.2670807905e-02\natom  8.5490873400e+00  1.4254076804e+01  2.8057934762e+01 O  -3.3960228745e-01 0.0  3.3408984937e-03 -3.0013474974e-03  1.6434727436e-02\natom  5.7128898790e+00  1.1352932522e+01  3.2118517817e+01 O  -3.4438179745e-01 0.0  1.0422941437e-03  1.0298774286e-03  8.7486520514e-03\natom  8.6004149813e+00  1.4259059577e+01  3.2064042251e+01 Mg  3.3198826255e-01 0.0 -8.7005176548e-03  2.6259492408e-03 -1.0597756850e-02\natom  5.7124369873e+00  1.1398959652e+01  3.6082038403e+01 Mg  3.2315037255e-01 0.0 -1.3862543151e-03  5.0422393550e-03  5.7750367172e-03\natom  8.5204521898e+00  1.4265381069e+01  3.6091786422e+01 O  -3.1780938745e-01 0.0  1.3416261094e-02 -1.2739389892e-02 -2.8670139703e-03\natom  5.6396066832e+00  1.1469303455e+01  4.0181759591e+01 O  -4.0524048745e-01 0.0  4.7585070422e-03 -1.0585901663e-02 -1.0360779733e-02\natom  8.5194176026e+00  1.4217509056e+01  4.0103819071e+01 Mg  3.8745670255e-01 0.0 -1.6891092094e-03  9.8970532196e-03  1.2094662829e-02\natom  1.1405419680e+01 -1.5945885837e-03  2.0026838456e+01 Mg  4.0752101255e-01 0.0 -4.2417688294e-04 -4.8618656906e-03 -1.0991812940e-02\natom  1.4317390712e+01  2.8385243373e+00  2.0006674078e+01 O  -4.0133712745e-01 0.0 -5.1177030628e-03 -2.5103256307e-03  3.6353722516e-03\natom  1.1396931579e+01 -6.3027652953e-03  2.4015166911e+01 O  -3.3854188745e-01 0.0  7.8276279073e-04  2.7302115027e-03  1.8367070001e-02\natom  1.4287220765e+01  2.8206950371e+00  2.3980497544e+01 Mg  3.3021725255e-01 0.0 -5.9026118619e-04  4.3908262433e-03 -1.0976730886e-02\natom  1.1360591733e+01  1.0450676046e-02  2.8046440353e+01 Mg  3.3596677255e-01 0.0  2.6602424589e-03 -1.5525459885e-04 -1.1407051545e-02\natom  1.4249557638e+01  2.8607032386e+00  2.8055228372e+01 O  -3.3904312745e-01 0.0  1.4535598782e-03 -8.7854108484e-04  1.2879215982e-02\natom  1.1397636711e+01 -2.1088775115e-02  3.2046155635e+01 O  -3.4561444745e-01 0.0  6.9316012417e-04  2.4808681795e-03  1.4733836376e-02\natom  1.4266587338e+01  2.8979978881e+00  3.2032750807e+01 Mg  3.3478729255e-01 0.0 -3.5818745493e-03 -1.6632387603e-03 -6.4544249558e-03\natom  1.1410164329e+01 -3.1985880028e-02  3.6135186001e+01 Mg  3.2182181255e-01 0.0 -2.7636182963e-03  6.4760841105e-03  1.5047247003e-03\natom  1.4271781495e+01  2.8564493331e+00  3.6123765726e+01 O  -3.1377282745e-01 0.0  1.6084621871e-02 -1.4835883940e-02 -8.2263499691e-03\natom  1.1377545485e+01  8.8354440953e-02  4.0134424638e+01 O  -4.0848069745e-01 0.0  3.4110378466e-03 -1.1524815821e-02 -6.7053476141e-03\natom  1.4283762585e+01  2.8550854045e+00  4.0099659708e+01 Mg  3.8514249255e-01 0.0 -7.3274517711e-03  3.2062292948e-03  1.3235659138e-02\natom  1.1357494755e+01  5.7306538136e+00  2.0027490713e+01 Mg  4.1314663255e-01 0.0  6.3983870760e-03  1.7030995645e-03 -9.8789161948e-03\natom  1.4280732485e+01  8.4673409874e+00  1.9982031862e+01 O  -3.9815156745e-01 0.0  1.0284815127e-03  5.6147628828e-03  7.4650035512e-03\natom  1.1488796262e+01  5.7025318752e+00  2.4013374222e+01 O  -3.4123026745e-01 0.0 -7.3708891641e-03 -5.3015983587e-03  1.6300762545e-02\natom  1.4239891991e+01  8.5367518135e+00  2.4007701548e+01 Mg  3.2678668255e-01 0.0  4.5399068975e-03  1.7247758379e-03 -1.3630577695e-02\natom  1.1406576098e+01  5.7067742344e+00  2.8032463335e+01 Mg  3.3858939255e-01 0.0 -6.1063170976e-04  8.5893875843e-04 -1.5080042318e-02\natom  1.4204608237e+01  8.5861910327e+00  2.8046797398e+01 O  -3.3986310745e-01 0.0  5.5491532541e-03 -4.6253013341e-03  1.8040536864e-02\natom  1.1421559244e+01  5.7173577204e+00  3.2068366530e+01 O  -3.4160742745e-01 0.0 -2.1233689855e-03 -1.2453375559e-03  1.2339070963e-02\natom  1.4221314870e+01  8.5572928326e+00  3.2077642798e+01 Mg  3.3387263255e-01 0.0  7.5639565001e-03 -7.7592751280e-03 -1.1314678887e-02\natom  1.1350884361e+01  5.7133187902e+00  3.6086910135e+01 Mg  3.2079758255e-01 0.0  1.1251554449e-02 -3.9835895713e-03  7.3679606372e-03\natom  1.4293067501e+01  8.5063430799e+00  3.6104423530e+01 O  -3.1602957745e-01 0.0 -1.5806371634e-02  1.6777353777e-02 -3.5246794927e-03\natom  1.1384241238e+01  5.6557446785e+00  4.0111940376e+01 O  -4.0636085745e-01 0.0  2.1705735618e-03  1.0191476777e-02 -5.4046880414e-03\natom  1.4217059793e+01  8.5915238961e+00  4.0134839830e+01 Mg  3.8874657255e-01 0.0  5.1874242374e-03 -8.9303480396e-03  9.5237943483e-03\natom  1.1439883426e+01  1.1370134244e+01  2.0000842100e+01 Mg  3.1377812255e-01 0.0 -6.6740229438e-03  1.9943255923e-03 -2.0024273027e-02\natom  1.4207333222e+01  1.4293561721e+01  1.9993962288e+01 O  -3.9694302745e-01 0.0  8.9569245611e-03 -2.8086012272e-03  8.5716640848e-03\natom  1.1388096751e+01  1.1342477141e+01  2.4066557253e+01 O  -3.4028672745e-01 0.0  3.9806175054e-03  6.3043478534e-03  1.2162846882e-02\natom  1.4187710704e+01  1.4282127783e+01  2.4023445233e+01 Mg  3.3302835255e-01 0.0  7.8305198270e-03 -7.8544263907e-03 -1.4633804741e-02\natom  1.1458709802e+01  1.1411108776e+01  2.8082294162e+01 Mg  3.3722095255e-01 0.0 -7.0633212181e-03 -3.1825482000e-03 -2.4614854170e-02\natom  1.4234540609e+01  1.4263171110e+01  2.8049194969e+01 O  -3.3951110745e-01 0.0 -2.3514980239e-04 -4.1106316692e-04  1.7459106214e-02\natom  1.1350327648e+01  1.1383571084e+01  3.2059141454e+01 O  -3.0676760745e-01 0.0  6.2713022852e-03  6.9306830745e-04  3.0419570114e-02\natom  1.4213696175e+01  1.4190046500e+01  3.2045545726e+01 Mg  3.3504181255e-01 0.0  2.8356752285e-03  7.0924410903e-03 -1.1095451018e-02\natom  1.1419660617e+01  1.1377104857e+01  3.6121222079e+01 Al  4.0133678255e-01 0.0 -2.4124197320e-03  1.1014644618e-03  6.2365240739e-03\natom  1.4252574623e+01  1.4341518318e+01  3.6148674374e+01 O  -2.9367865745e-01 0.0  4.3303646001e-03 -6.9794980596e-03 -8.1060006031e-03\natom  1.1373690916e+01  1.1389870864e+01  4.0155448577e+01 O  -3.6087935745e-01 0.0  7.6902570412e-04  1.0937557987e-03 -2.3997652143e-02\natom  1.4283161652e+01  1.4227273535e+01  4.0145235855e+01 Mg  3.8177302255e-01 0.0 -2.7572483332e-03  5.5652417804e-03  1.3366006533e-02\natom  1.1115212192e+01  1.1589653923e+01  1.4417910019e+01 Au -8.3363077455e-02 0.0  1.8445630162e-02  1.1211472657e-03  2.8665070706e-03\natom  6.4031057201e+00  1.1246691560e+01  1.4077626588e+01 Au -1.0921794745e-01 0.0 -1.8758923120e-02 -1.1680480933e-03  2.1108111932e-03\nenergy -5.4395982001e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom  2.8255447543e-02  3.6659304679e-02  2.0018440683e+01 Mg  4.2192749682e-01 0.0 -3.6557291557e-03 -4.4481868980e-03 -2.8897689603e-04\natom  2.8158103978e+00  2.9083208753e+00  1.9975662049e+01 O  -3.9846081318e-01 0.0  2.2483165567e-03 -6.1603822386e-03  3.9695612663e-03\natom -1.7348478260e-02  4.1303362988e-03  2.4021233819e+01 O  -3.4438894318e-01 0.0  4.7008037629e-03  1.2521509193e-03  1.7057720736e-02\natom  2.8766792278e+00  2.8716439584e+00  2.4075703999e+01 Mg  3.3464514682e-01 0.0 -3.1884823061e-03  1.7115077011e-03 -1.9765886005e-02\natom  2.3072023643e-02 -2.6917805002e-02  2.8062700198e+01 Mg  3.4376281682e-01 0.0 -5.5773297221e-03  2.4288177819e-03 -2.2767218003e-02\natom  2.8582013548e+00  2.8749728430e+00  2.8040172831e+01 O  -3.3695581318e-01 0.0 -1.9278264763e-03 -4.5653744480e-03  2.3352585055e-02\natom  1.4710080629e-02 -5.0121315779e-02  3.2106421170e+01 O  -3.0520873318e-01 0.0 -7.2549581756e-04  7.5594360328e-03  3.0511249674e-02\natom  2.8284582016e+00  2.8143478822e+00  3.2122873219e+01 Mg  3.3908395682e-01 0.0  1.8089555182e-03  2.0987707413e-03 -2.0650548488e-02\natom -1.2888006831e-02  2.6817025915e-02  3.6110977099e+01 Al  4.0449143682e-01 0.0  3.8668417090e-03 -3.6255863662e-03  9.7905598068e-03\natom  2.8245370012e+00  2.8236844325e+00  3.6084002319e+01 O  -2.8693983318e-01 0.0  7.1312545768e-04  1.4005661661e-04 -1.3734068662e-03\natom  2.0522726592e-02 -4.6862936846e-03  4.0117465614e+01 O  -3.6183210318e-01 0.0 -3.8677940263e-03  1.7023102080e-03 -2.5582118313e-02\natom  2.8329956793e+00  2.8688792326e+00  4.0191227005e+01 Mg  3.7702819682e-01 0.0  3.1701860803e-03 -5.9695775554e-03  1.4465039436e-02\natom  4.5871624387e-02  5.7402230458e+00  1.9989351130e+01 Mg  4.2159785682e-01 0.0 -7.5146435192e-03  7.9501178982e-05  1.2195991440e-04\natom  2.8487716977e+00  8.4987932277e+00  1.9952251670e+01 O  -3.9336953318e-01 0.0 -7.0438180317e-03  3.1440910127e-03  8.1282397984e-03\natom -1.0771343649e-02  5.7242604926e+00  2.4072235351e+01 O  -3.4341963318e-01 0.0  1.8792243249e-03 -3.2081669214e-03  1.0706633754e-02\natom  2.8319658165e+00  8.6005514195e+00  2.3990546162e+01 Mg  3.2837964682e-01 0.0  1.8179040813e-03 -6.2486270841e-03 -1.0369450107e-02\natom -3.3363017842e-02  5.6782799444e+00  2.8054247964e+01 Mg  3.3815470682e-01 0.0 -2.4263781963e-03  3.6659707742e-03 -1.5188835867e-02\natom  2.8243688534e+00  8.5605674632e+00  2.8027843578e+01 O  -3.4110431318e-01 0.0  1.7547054864e-03 -2.5885804687e-03  2.1650098975e-02\natom -1.6097366272e-02  5.7300022927e+00  3.2087453310e+01 O  -3.4383265318e-01 0.0  3.3121516327e-03 -7.1612197075e-03  1.4174706252e-02\natom  2.8574771551e+00  8.5061896719e+00  3.2111944480e+01 Mg  3.3444066682e-01 0.0 -4.6086537290e-03  1.1616506023e-02 -1.8875811705e-02\natom  4.7195396339e-02  5.6250332675e+00  3.6158757064e+01 Mg  3.2361006682e-01 0.0 -8.6200154151e-03  1.3294417928e-02  8.3406597261e-05\natom  2.8835983839e+00  8.5742370418e+00  3.6079751721e+01 O  -3.1021311318e-01 0.0  8.1237513990e-03 -2.0737692581e-02  7.3587311886e-04\natom  1.1775714114e-02  5.7376326850e+00  4.0186524440e+01 O  -4.0484439318e-01 0.0  4.2065561801e-05 -3.9440425642e-03 -1.0319225365e-02\natom  2.8411150571e+00  8.5363928033e+00  4.0092462536e+01 Mg  3.8277659682e-01 0.0 -3.3832492118e-07  5.4700547143e-03  1.5818527812e-02\natom -1.3145463100e-02  1.1414960075e+01  1.9973936332e+01 Mg  4.1182522682e-01 0.0 -8.8798153263e-04 -1.7839192021e-03 -1.5813441628e-03\natom  2.8975463947e+00  1.4247304782e+01  2.0028866623e+01 O  -3.9194921318e-01 0.0 -9.4451172995e-03  4.7031259767e-03  4.4137426347e-03\natom  2.3900895256e-02  1.1351360591e+01  2.4039169209e+01 O  -3.4443862318e-01 0.0 -6.9811723476e-04  6.5209453216e-03  1.4014385453e-02\natom  2.9082765802e+00  1.4245710496e+01  2.4009536756e+01 Mg  3.2770400682e-01 0.0 -5.8564759679e-03 -8.3653643360e-04 -1.4241132565e-02\natom -8.8470923663e-03  1.1417295795e+01  2.8091757399e+01 Mg  3.3809061682e-01 0.0  3.8570467407e-04 -4.8706919914e-03 -1.9333590365e-02\natom  2.8853438482e+00  1.4268783540e+01  2.8002334356e+01 O  -3.3921199318e-01 0.0 -3.3777663946e-03  2.9206922975e-03  2.0999971682e-02\natom -3.4457244779e-02  1.1437715986e+01  3.2077453296e+01 O  -3.4488839318e-01 0.0  4.2808411687e-04 -1.4295707844e-03  1.4732404704e-02\natom  2.8163827580e+00  1.4296892326e+01  3.2090122246e+01 Mg  3.3487139682e-01 0.0  1.0804722895e-02 -1.2340247507e-02 -1.4185851357e-02\natom  1.1462888874e-02  1.1471946992e+01  3.6136270250e+01 Mg  3.2699666682e-01 0.0  2.6626961853e-03 -7.6928854560e-03 -1.2530246925e-04\natom  2.8903822545e+00  1.4218556380e+01  3.6079820280e+01 O  -3.1679306318e-01 0.0 -2.0105342396e-02  1.6324383030e-02 -1.5692831413e-03\natom  2.8040245548e-02  1.1441917735e+01  4.0217628083e+01 O  -4.0368942318e-01 0.0 -3.9430447022e-03 -2.4909659948e-03 -1.1671572868e-02\natom  2.8277523322e+00  1.4209233190e+01  4.0142326943e+01 Mg  3.8377805682e-01 0.0  9.7353525728e-03  2.2363563524e-03  1.0187687294e-02\natom  5.6694718749e+00  5.1052837308e-03  2.0009578568e+01 Mg  4.0917524682e-01 0.0  6.9815472779e-03 -5.4035707405e-03 -7.9524113633e-03\natom  8.5129056069e+00  2.8770598375e+00  1.9992525662e+01 O  -3.9860593318e-01 0.0  1.9653360353e-03 -4.9626677559e-03  1.7923348572e-03\natom  5.6940916786e+00 -1.3973918973e-02  2.4004369697e+01 O  -3.4065943318e-01 0.0  8.5278811053e-04  2.4401073377e-03  1.6312178300e-02\natom  8.5501146518e+00  2.8307399134e+00  2.3972202479e+01 Mg  3.2710621682e-01 0.0  5.5857180657e-05  6.9460879214e-03 -9.1340834036e-03\natom  5.7361392913e+00  5.2163637141e-02  2.8032683507e+01 Mg  3.3654255682e-01 0.0  6.0705267775e-04 -5.4248532519e-03 -1.3380199572e-02\natom  8.5411582198e+00  2.8573377878e+00  2.7994299619e+01 O  -3.4126212318e-01 0.0 -3.0949084731e-03 -2.2432938907e-03  2.2535923950e-02\natom  5.7690881757e+00  2.3226055208e-03  3.2094684536e+01 O  -3.4343463318e-01 0.0 -1.0059579934e-02  2.6558299016e-03  1.0606546461e-02\natom  8.5343018404e+00  2.7900231781e+00  3.2103135749e+01 Mg  3.3207822682e-01 0.0  8.1202556512e-03  2.7023625491e-03 -1.5367880332e-02\natom  5.7096622649e+00 -6.0834455867e-02  3.6133333805e+01 Mg  3.2270802682e-01 0.0  2.6199167192e-03  8.5710079436e-04  5.8283990075e-03\natom  8.5500804477e+00  2.8643641481e+00  3.6108756161e+01 O  -3.1706601318e-01 0.0 -1.4299644084e-02  1.1747947045e-02 -7.5057861056e-04\natom  5.7426517028e+00 -5.6155551011e-02  4.0155736628e+01 O  -4.0944640318e-01 0.0 -5.5719147188e-03  8.6213071576e-03 -6.3576706067e-03\natom  8.5980317722e+00  2.8660658463e+00  4.0152406798e+01 Mg  3.8472010682e-01 0.0 -6.2525746363e-03 -3.7483823536e-03  9.4527525605e-03\natom  5.6652390587e+00  5.7064648296e+00  1.9994515127e+01 Mg  4.0655043682e-01 0.0  6.7893115567e-03  5.2956011410e-03 -4.1761984578e-03\natom  8.5344222349e+00  8.4967042112e+00  1.9975601653e+01 O  -3.9541661318e-01 0.0  4.0180812850e-04 -4.6669100974e-03  1.7382017192e-02\natom  5.7423682250e+00  5.7091064586e+00  2.4020305246e+01 O  -3.4520876318e-01 0.0 -8.7795231958e-03 -3.3217913790e-03  1.6850361627e-02\natom  8.5641754792e+00  8.5496244757e+00  2.4078299538e+01 Mg  3.2759314682e-01 0.0 -1.1472491760e-03 -3.4864763522e-03 -2.0866115818e-02\natom  5.6105008400e+00  5.6391442294e+00  2.8124365094e+01 Mg  3.4407049682e-01 0.0  1.2118950384e-02  1.0279465554e-02 -2.8188429938e-02\natom  8.5733318064e+00  8.5289900285e+00  2.8077197665e+01 O  -3.4333020318e-01 0.0 -6.9002602811e-03  3.8210402662e-03  1.7104218456e-02\natom  5.7416216509e+00  5.7103009922e+00  3.2161929849e+01 O  -3.0398880318e-01 0.0 -8.8214831643e-03 -4.1665788112e-03  2.8113740894e-02\natom  8.5279930658e+00  8.5901276154e+00  3.2085130176e+01 Mg  3.2758055682e-01 0.0  1.4109688275e-03 -3.1652997659e-03 -1.8078615180e-02\natom  5.6253189563e+00  5.6988927353e+00  3.6108362720e+01 Al  4.0929306682e-01 0.0  1.1397317334e-02 -1.6896645571e-03  4.5099800386e-03\natom  8.5885213483e+00  8.5714391513e+00  3.6072956852e+01 O  -2.9399057318e-01 0.0 -1.7371558625e-04  6.8472589047e-04  3.4843981712e-03\natom  5.6418222924e+00  5.6304747902e+00  4.0175893900e+01 O  -3.6371597318e-01 0.0  4.7955136908e-03  7.8016432615e-03 -2.6709547533e-02\natom  8.5965522302e+00  8.5970352441e+00  4.0198156913e+01 Mg  3.8058520682e-01 0.0 -6.4302885429e-03 -1.1216209165e-03  9.1955197509e-03\natom  5.6963126358e+00  1.1370056463e+01  1.9981985072e+01 Mg  2.6423217682e-01 0.0  6.6054249804e-03 -2.1244492779e-03  9.3899513878e-03\natom  8.6178888429e+00  1.4238926757e+01  1.9935345048e+01 O  -3.9200332318e-01 0.0 -4.0207788744e-03  1.3666082636e-02  2.4293092336e-02\natom  5.7040515928e+00  1.1366841208e+01  2.3996186786e+01 O  -3.3903186318e-01 0.0  9.6506768732e-04  4.9148687934e-03  1.8110629332e-02\natom  8.6010073537e+00  1.4247191682e+01  2.4059573771e+01 Mg  3.3503042682e-01 0.0 -1.9132134249e-03 -3.7145323649e-03 -2.3801449102e-02\natom  5.6662650477e+00  1.1453959900e+01  2.8002077146e+01 Mg  3.4064731682e-01 0.0  3.5289781411e-03 -6.9598874729e-03 -8.0110642967e-03\natom  8.5486930298e+00  1.4258359830e+01  2.8084549947e+01 O  -3.4041514318e-01 0.0  1.7526506595e-03 -2.2981125353e-04  1.1984792865e-02\natom  5.6753006213e+00  1.1387131479e+01  3.2116871317e+01 O  -3.4819419318e-01 0.0  7.0244335059e-04  5.2534546683e-04  8.1384006972e-03\natom  8.5429922556e+00  1.4251155854e+01  3.2163135872e+01 Mg  3.3588415682e-01 0.0 -3.6313602379e-03  7.0646831543e-04 -1.8494279874e-02\natom  5.6517939985e+00  1.1337422955e+01  3.6156151906e+01 Mg  3.1337221682e-01 0.0  6.7039455333e-03  1.0293386557e-02 -2.8278695397e-03\natom  8.4930094378e+00  1.4262763364e+01  3.6169086514e+01 O  -3.1671978318e-01 0.0  2.3279782708e-02 -1.4925416065e-02 -1.0053368873e-02\natom  5.7247377618e+00  1.1482173660e+01  4.0053597770e+01 O  -4.0710904318e-01 0.0  5.3506809057e-04 -1.2521095856e-02  1.2806425551e-03\natom  8.6308864349e+00  1.4342692707e+01  4.0140352350e+01 Mg  3.7924138682e-01 0.0 -1.5513629928e-02 -4.1831346221e-03  9.1010324286e-03\natom  1.1383645218e+01  2.5178142154e-02  1.9984009158e+01 Mg  4.1306276682e-01 0.0 -5.2713740471e-04 -7.7106919711e-03 -4.7117917436e-03\natom  1.4267427416e+01  2.8006879034e+00  2.0037275582e+01 O  -4.0065113318e-01 0.0 -2.3276895696e-03  4.9989561636e-03 -2.1378732011e-03\natom  1.1398444021e+01  7.8496194005e-03  2.4032116581e+01 O  -3.4070385318e-01 0.0 -5.2036274251e-04 -1.1682602273e-03  1.3304541724e-02\natom  1.4239194701e+01  2.9245295843e+00  2.3990352900e+01 Mg  3.2810366682e-01 0.0  3.9863623861e-04 -4.3705440481e-03 -8.9522307673e-03\natom  1.1380693145e+01  3.8478600580e-03  2.7960821045e+01 Mg  3.3993196682e-01 0.0  3.2658885420e-03  2.6866989348e-03 -4.3284101272e-03\natom  1.4223459218e+01  2.7965064311e+00  2.8045195855e+01 O  -3.4343701318e-01 0.0  5.2478558430e-03  2.4676614342e-03  1.8611770796e-02\natom  1.1460070537e+01  1.1708080821e-02  3.2149350983e+01 O  -3.4571645318e-01 0.0 -3.6799282023e-03 -4.4818675790e-03  9.9373357556e-03\natom  1.4186589133e+01  2.8581425087e+00  3.2175597576e+01 Mg  3.3609366682e-01 0.0 -1.2553725193e-03  3.4051786704e-03 -2.4289281968e-02\natom  1.1411611311e+01  2.5485600573e-03  3.6148815329e+01 Mg  3.2172196682e-01 0.0 -7.4228633190e-03  1.7210469595e-03 -1.0601395450e-03\natom  1.4279115465e+01  2.8706147569e+00  3.6192122519e+01 O  -3.1105962318e-01 0.0  1.1469186409e-02 -1.5510149860e-02 -1.0688079632e-02\natom  1.1365045760e+01 -1.2758258245e-02  4.0130043743e+01 O  -4.0079818318e-01 0.0  8.8535107409e-03  3.3444702401e-03 -5.1167748495e-03\natom  1.4203184007e+01  2.8587853179e+00  4.0083422011e+01 Mg  3.8348695682e-01 0.0  2.1700414572e-03  2.9006045146e-03  1.8975952978e-02\natom  1.1351411425e+01  5.7247147638e+00  2.0010606749e+01 Mg  4.1262987682e-01 0.0 -1.9328813301e-04  5.3488306571e-03 -4.2272066774e-03\natom  1.4195755154e+01  8.5314264712e+00  2.0046545898e+01 O  -3.9688517318e-01 0.0  1.0720556008e-02 -3.6763806036e-03  2.4804834701e-03\natom  1.1372655913e+01  5.6912625698e+00  2.4050730326e+01 O  -3.4422244318e-01 0.0  3.7880987454e-03 -1.7761694322e-03  1.2564224335e-02\natom  1.4215904717e+01  8.5604606559e+00  2.4067193392e+01 Mg  3.2488518682e-01 0.0  1.4963542376e-03 -3.8077144837e-04 -1.8596275389e-02\natom  1.1420223397e+01  5.7543340266e+00  2.8116343471e+01 Mg  3.3135795682e-01 0.0 -6.0534945292e-03 -8.0030566211e-03 -1.9998949271e-02\natom  1.4155124666e+01  8.5315882317e+00  2.8034667152e+01 O  -3.4073807318e-01 0.0  9.9234022525e-03  2.4733105200e-03  2.2179126170e-02\natom  1.1354615304e+01  5.6535842493e+00  3.2065740264e+01 O  -3.4665465318e-01 0.0  3.6104523023e-03  4.3735324732e-03  1.8679851967e-02\natom  1.4261797242e+01  8.5789835233e+00  3.2148987910e+01 Mg  3.3669744682e-01 0.0 -8.4227280271e-05 -6.6076360984e-03 -1.8582755629e-02\natom  1.1351603667e+01  5.6814097842e+00  3.6157042289e+01 Mg  3.2335580682e-01 0.0  2.3315246594e-03  3.4748162235e-03 -3.5527096041e-03\natom  1.4266148846e+01  8.5648956349e+00  3.6130394620e+01 O  -3.1490522318e-01 0.0 -1.4026766198e-02  1.4768226715e-02 -3.0517651427e-03\natom  1.1403715317e+01  5.7250021912e+00  4.0160165201e+01 O  -4.0346347318e-01 0.0 -1.5369428192e-03  3.2464944802e-04 -6.5166239625e-03\natom  1.4277037579e+01  8.5728500018e+00  4.0153760692e+01 Mg  3.8446717682e-01 0.0  4.1340558998e-03 -5.1765119047e-03  1.0071553018e-02\natom  1.1444685030e+01  1.1435547090e+01  1.9952472900e+01 Mg  2.8182651682e-01 0.0 -8.1330124129e-03 -5.2572683851e-03 -7.6365291567e-03\natom  1.4237200700e+01  1.4205149965e+01  2.0079734947e+01 O  -3.9655498318e-01 0.0  9.8004396648e-03  8.8172411881e-03  1.2717800074e-03\natom  1.1431404754e+01  1.1348793474e+01  2.4015813008e+01 O  -3.4020501318e-01 0.0 -4.0209883359e-03  7.9823791113e-03  2.0277487726e-02\natom  1.4254701226e+01  1.4280923990e+01  2.4048523995e+01 Mg  3.3143805682e-01 0.0  1.8704525673e-03 -5.1742034080e-03 -1.7078615403e-02\natom  1.1404207043e+01  1.1394719466e+01  2.8074760864e+01 Mg  3.3628974682e-01 0.0 -1.8736690322e-03 -1.1158525564e-03 -2.0883105085e-02\natom  1.4267483654e+01  1.4192867861e+01  2.8098199778e+01 O  -3.4128030318e-01 0.0 -1.6951319692e-03  5.4998945103e-03  1.2994519778e-02\natom  1.1347732695e+01  1.1373347118e+01  3.2052109841e+01 O  -3.0752151318e-01 0.0  5.7790743086e-03  4.2942170673e-03  3.7118317508e-02\natom  1.4229283278e+01  1.4232699902e+01  3.2128505774e+01 Mg  3.2910155682e-01 0.0 -1.7994309418e-03  1.5425261405e-03 -2.3131726058e-02\natom  1.1436120603e+01  1.1413817547e+01  3.6146202008e+01 Al  4.1056458682e-01 0.0 -7.7427072901e-03 -4.9075945403e-03  3.7926080342e-03\natom  1.4217875229e+01  1.4259707677e+01  3.6119611692e+01 O  -2.8704764318e-01 0.0  1.1858138833e-03 -2.3577336587e-03 -2.5022502761e-03\natom  1.1432064571e+01  1.1430333223e+01  4.0072297326e+01 O  -3.5626076318e-01 0.0 -4.2007643344e-04 -1.8468182224e-03 -2.3097820092e-02\natom  1.4213292945e+01  1.4220476928e+01  4.0160631037e+01 Mg  3.7537884682e-01 0.0  6.5082537230e-03  4.9254099125e-03  1.5253279252e-02\natom  1.0861810936e+01  1.1558426825e+01  1.4908733444e+01 Au -5.9954573182e-02 0.0  4.1234756542e-02 -1.5538526822e-03 -1.4436232026e-02\natom  6.2985268288e+00  1.1685790218e+01  1.5418790784e+01 Au -2.0769793182e-02 0.0 -4.0039367126e-02  3.0589381499e-03 -3.1277636699e-02\nenergy -5.4395969475e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -3.2697229582e-02 -2.6468409265e-02  1.9930481346e+01 Mg  3.6718862318e-01 0.0 -6.9627547941e-03 -8.8988292846e-03  1.0841873937e-02\natom  2.8749016192e+00  2.8508539490e+00  2.0002962335e+01 O  -2.9735167682e-01 0.0 -4.1409506473e-03 -8.9994081938e-04  7.1755642320e-03\natom  6.4240894832e-02 -1.5764283170e-02  2.4086955579e+01 O  -3.4536313682e-01 0.0 -4.9953865757e-03  6.5857963272e-03 -8.1864095408e-03\natom  2.8072784739e+00  2.8833593714e+00  2.3996511933e+01 Mg  3.4163235318e-01 0.0  3.6917990357e-03 -3.5592848749e-03  1.0724435423e-02\natom  3.1896628270e-02  1.0645998124e-02  2.8074946605e+01 Mg  3.3357316318e-01 0.0 -6.9556702961e-03 -2.0324237929e-03 -2.0100741568e-03\natom  2.8115192080e+00  2.8434700336e+00  2.7971518462e+01 O  -3.3868931682e-01 0.0  5.2512927668e-03  1.8231661153e-03  9.6304972940e-03\natom -7.0322505495e-02 -8.8414987774e-03  3.2089546409e+01 O  -3.4101118682e-01 0.0  9.7502245191e-03  1.4746073271e-03 -2.3952290111e-04\natom  2.8359625302e+00  2.8682383320e+00  3.2078759475e+01 Mg  3.4678550318e-01 0.0 -4.0571999052e-03 -1.0334639035e-03  2.2271653647e-03\natom -1.5074060752e-02  3.7499174497e-02  3.6140469599e+01 Mg  3.2644933318e-01 0.0 -1.0465303017e-03 -5.1679154977e-03 -4.6660711384e-03\natom  2.7825755223e+00  2.8124774692e+00  3.6140211312e+01 O  -3.4285313682e-01 0.0  9.9223397482e-03  3.5600891981e-03 -2.8007222678e-03\natom -3.0195629216e-02  4.2086087492e-03  4.0078225869e+01 O  -3.9689518682e-01 0.0  1.4455670971e-03 -4.2075709702e-04  1.3630433379e-02\natom  2.8240617730e+00  2.8324083147e+00  4.0177956990e+01 Mg  4.1941143318e-01 0.0  8.3720589478e-04  2.6053042598e-03 -8.9774922232e-03\natom -2.3181760031e-02  5.7166421757e+00  1.9979798792e+01 Mg  3.7981397318e-01 0.0 -5.7469893842e-03  1.0261195431e-02  4.0985832348e-03\natom  2.8964817231e+00  8.5447997029e+00  2.0042956382e+01 O  -3.9962491682e-01 0.0 -4.3562388404e-03 -1.4599178971e-03 -8.1451268311e-03\natom -1.8375147493e-02  5.7424435494e+00  2.3963510854e+01 O  -3.4066687682e-01 0.0  4.1709453111e-03 -6.9945516821e-03  5.5873914643e-03\natom  2.8599889789e+00  8.6081585682e+00  2.4002763260e+01 Mg  3.2872685318e-01 0.0  7.3942747655e-04 -3.1274381039e-03 -3.2351607517e-04\natom  4.6010689322e-02  5.6938808419e+00  2.7979833219e+01 Mg  3.4774132318e-01 0.0 -6.7104367542e-03  2.5358274371e-03  6.7164885367e-03\natom  2.9128776850e+00  8.5015992251e+00  2.8059286729e+01 O  -3.4034322682e-01 0.0 -8.8286108116e-03  4.9595578842e-03 -1.7461142405e-04\natom  3.7634384392e-02  5.6644659907e+00  3.2099620557e+01 O  -3.4238659682e-01 0.0 -2.9362954748e-03  4.8617626136e-03 -3.2033866985e-03\natom  2.8529700074e+00  8.5337373604e+00  3.2038400540e+01 Mg  3.4251814318e-01 0.0  2.3521352304e-04  1.2307041671e-03  5.0961067484e-03\natom -2.7722204664e-02  5.7108715761e+00  3.6147051610e+01 Mg  3.3050612318e-01 0.0  3.8700027985e-03  1.6413328105e-03 -3.4484318860e-03\natom  2.8547115222e+00  8.5448674685e+00  3.6115129583e+01 O  -3.4341131682e-01 0.0 -8.6387030413e-04  5.2210061943e-04 -1.8310596298e-03\natom -1.3779598450e-02  5.7436846837e+00  4.0140368374e+01 O  -3.9963050682e-01 0.0  2.8312667965e-04 -7.3530197946e-03  7.5932878857e-03\natom  2.8658118483e+00  8.5462902999e+00  4.0125259240e+01 Mg  4.0624797318e-01 0.0 -1.5385000567e-03  1.0763237787e-03 -4.7601763226e-03\natom  4.7199326969e-02  1.1375071663e+01  2.0002790748e+01 Mg  4.2331160318e-01 0.0 -1.3724554653e-03  3.0519561310e-03  8.1254940170e-03\natom  2.8415760558e+00  1.4280150279e+01  2.0021145618e+01 O  -3.9697363682e-01 0.0  1.3632501724e-03  4.7330702069e-04 -3.7022036478e-03\natom -3.7635121385e-02  1.1341496108e+01  2.4052184678e+01 O  -3.4473021682e-01 0.0  7.0917595113e-03  7.0169728162e-03  1.6942129006e-03\natom  2.8991197050e+00  1.4289690561e+01  2.4096699724e+01 Mg  3.2962536318e-01 0.0 -7.1170027817e-03 -2.1101299509e-03 -7.3977828764e-03\natom -3.0584062393e-02  1.1454934356e+01  2.8075544193e+01 Mg  3.4514670318e-01 0.0 -1.7663927860e-04 -2.4598803919e-03 -3.7599566091e-03\natom  2.8447567103e+00  1.4291136560e+01  2.8028100373e+01 O  -3.3982938682e-01 0.0  2.4830523326e-03 -4.3011924436e-03  7.0639569908e-03\natom -7.7046452918e-02  1.1419435192e+01  3.2101927780e+01 O  -3.3808627682e-01 0.0  8.5332186275e-03 -2.3714048037e-03 -1.8441325996e-03\natom  2.8490499976e+00  1.4258278383e+01  3.2105818253e+01 Mg  3.4181200318e-01 0.0 -2.1801341580e-03 -7.5757876906e-04 -4.4670270716e-03\natom  2.8005965918e-02  1.1380707922e+01  3.6076680840e+01 Mg  3.3470394318e-01 0.0 -5.8693959153e-03  1.5313751765e-03  8.5045243753e-03\natom  2.8170315765e+00  1.4281828809e+01  3.6058264969e+01 O  -3.4092092682e-01 0.0  2.1191007772e-03 -1.6680924317e-03  4.9291085328e-03\natom  2.7316745056e-03  1.1348917176e+01  4.0159691522e+01 O  -4.0400222682e-01 0.0 -1.2234028216e-04  6.8014012146e-03  5.6488282667e-03\natom  2.8330536183e+00  1.4224936303e+01  4.0170361992e+01 Mg  4.1650153318e-01 0.0 -2.9595917011e-03 -8.0568037728e-04 -7.4829232188e-03\natom  5.7446783394e+00  6.9139404745e-04  2.0009426086e+01 Mg  3.5463759318e-01 0.0  5.5997017304e-03 -1.0170216409e-02  2.9034510638e-03\natom  8.5035719668e+00  2.9032124169e+00  1.9972920869e+01 O  -3.9672636682e-01 0.0  4.0360641078e-03 -8.3902619400e-03 -2.1064255540e-03\natom  5.7212278792e+00  5.0771835054e-03  2.4019140003e+01 O  -3.4176662682e-01 0.0 -3.7650644330e-03  3.1955910114e-03 -6.6830330990e-04\natom  8.5518713032e+00  2.8281643114e+00  2.4013841929e+01 Mg  3.2529550318e-01 0.0 -7.1713598087e-04  1.5939654258e-03  8.5844094641e-04\natom  5.7047497143e+00  4.5330312378e-02  2.8092173989e+01 Mg  3.4496111318e-01 0.0  3.4932224119e-03 -5.5488821816e-03 -7.4024243304e-03\natom  8.5780656455e+00  2.8653842789e+00  2.7997302469e+01 O  -3.4007085682e-01 0.0 -6.5936480096e-03 -2.1544077512e-04  8.1988304343e-03\natom  5.7268883456e+00 -1.9859886305e-02  3.2044695558e+01 O  -3.3632081682e-01 0.0 -5.9475834721e-03  7.0555296586e-03  5.9492186229e-03\natom  8.5075438495e+00  2.8344757883e+00  3.2097935790e+01 Mg  3.4283673318e-01 0.0  9.1070026245e-03  3.7744278259e-03 -2.5310593780e-03\natom  5.6976234064e+00  1.3393773095e-02  3.6102649096e+01 Mg  3.3993379318e-01 0.0 -2.1596239066e-03 -9.1072448946e-04  3.4205888087e-03\natom  8.6177862496e+00  2.8733413292e+00  3.6109604799e+01 O  -3.4033555682e-01 0.0 -9.6306254795e-03 -4.4165710721e-03  1.3683891655e-03\natom  5.6381730047e+00 -1.5961967405e-02  4.0142039006e+01 O  -3.9833608682e-01 0.0  3.4490719801e-03  3.4703660293e-03  6.7891612438e-03\natom  8.5115408468e+00  2.8606243237e+00  4.0191029982e+01 Mg  4.1885886318e-01 0.0  2.9123281843e-03  6.5602828052e-04 -7.2108198482e-03\natom  5.7367496161e+00  5.6463232417e+00  1.9982771161e+01 Mg  3.6386275318e-01 0.0  8.6884295013e-03  2.0404710393e-02  3.7846180518e-03\natom  8.5357273930e+00  8.5603179438e+00  1.9972846301e+01 O  -4.0474219682e-01 0.0  4.7147433306e-03 -3.3749910658e-04 -1.0543601984e-03\natom  5.6774158483e+00  5.6849596156e+00  2.4001584430e+01 O  -3.4376663682e-01 0.0 -1.2959788055e-03 -2.0792242985e-03  1.1746864535e-03\natom  8.5424455201e+00  8.5387543750e+00  2.4059050657e+01 Mg  3.3825866318e-01 0.0  8.8917293775e-04  2.1932831908e-03 -7.3803803355e-03\natom  5.6683349968e+00  5.6738318696e+00  2.8076890963e+01 Mg  3.3833796318e-01 0.0  4.2771612004e-03  2.2996486561e-03 -5.7972506710e-03\natom  8.4523757371e+00  8.5897107418e+00  2.8049705327e+01 O  -3.4042740682e-01 0.0  8.4257908539e-03 -6.8916268311e-03  4.1520299601e-04\natom  5.6989650363e+00  5.6959680064e+00  3.2089221376e+01 O  -3.3906688682e-01 0.0 -1.5389007877e-03 -4.8194657789e-03 -5.0146857994e-04\natom  8.5139575607e+00  8.5763615851e+00  3.2074642102e+01 Mg  3.3784369318e-01 0.0  2.9048004023e-03  2.9327429023e-04  4.3556015591e-03\natom  5.7261520327e+00  5.6555945020e+00  3.6122760429e+01 Mg  3.3622720318e-01 0.0 -9.3874911182e-04  9.0475792604e-03  3.5557166595e-04\natom  8.5699279941e+00  8.5747824545e+00  3.6066235361e+01 O  -3.4829982682e-01 0.0 -3.9496276679e-03 -4.3879905091e-03  6.8356129005e-03\natom  5.6930975693e+00  5.7067530317e+00  4.0138319609e+01 O  -4.0010153682e-01 0.0  4.6344588632e-04 -2.7597991884e-03  7.5587546705e-03\natom  8.6088971487e+00  8.5563769391e+00  4.0212136690e+01 Mg  4.1973439318e-01 0.0 -6.3586673285e-03  2.3956901984e-03 -1.3756311257e-02\natom  5.6915353707e+00  1.1486251349e+01  1.9989319798e+01 Mg  4.1906787318e-01 0.0  3.3666471391e-03 -9.5951734057e-03  3.4655850067e-03\natom  8.5142590664e+00  1.4240813667e+01  1.9984689969e+01 O  -3.9841779682e-01 0.0  5.2599603224e-03  3.9145711591e-03 -5.2749076254e-03\natom  5.7067800548e+00  1.1414256511e+01  2.4030499410e+01 O  -3.4113112682e-01 0.0 -1.9506059391e-03  1.7323483139e-03  1.2522739282e-03\natom  8.5061338872e+00  1.4266102434e+01  2.3973065668e+01 Mg  3.3027827318e-01 0.0  8.1678006303e-03 -4.0702183896e-03  6.4242896068e-03\natom  5.7150620813e+00  1.1389509057e+01  2.8005396846e+01 Mg  3.4011869318e-01 0.0  9.1655200745e-04  4.8421855646e-03  5.6453775976e-03\natom  8.6244992366e+00  1.4245895538e+01  2.8100876102e+01 O  -3.4457940682e-01 0.0 -1.0809824346e-02  5.6799330624e-04 -2.7565198766e-03\natom  5.6492449471e+00  1.1435842832e+01  3.2106436213e+01 O  -3.4200792682e-01 0.0 -4.2294424355e-04 -9.3111386960e-04 -1.8618347365e-03\natom  8.5201229429e+00  1.4303176231e+01  3.2132630007e+01 Mg  3.3877979318e-01 0.0  6.3666614732e-03 -9.3855996054e-03 -5.4299384813e-03\natom  5.6122768423e+00  1.1472700407e+01  3.6134463899e+01 Mg  3.3275576318e-01 0.0  1.0518096186e-02 -9.7326143126e-03 -7.2635450423e-04\natom  8.5690258578e+00  1.4224458977e+01  3.6183796557e+01 O  -3.4181679682e-01 0.0 -7.2600280742e-03  7.4283944684e-03 -5.1478635711e-03\natom  5.6890891960e+00  1.1429847526e+01  4.0181537397e+01 O  -4.0180757682e-01 0.0 -8.9513692193e-04 -1.2578856006e-03  4.7181354854e-03\natom  8.5011600150e+00  1.4287767840e+01  4.0147407245e+01 Mg  4.1175978318e-01 0.0  2.6449123374e-03 -5.7190984844e-03 -5.6759576707e-03\natom  1.1371342667e+01  2.5603897420e-04  1.9969167798e+01 Mg  4.3465043318e-01 0.0  2.2308999980e-03 -7.0945049586e-04  7.4645218985e-03\natom  1.4266957951e+01  2.8949522923e+00  2.0014834538e+01 O  -3.9768314682e-01 0.0  1.4086825274e-03 -5.5191053418e-03 -4.5040431770e-03\natom  1.1336149053e+01 -7.2231185435e-03  2.4061587595e+01 O  -3.4342966682e-01 0.0  5.8238202487e-03  1.6357472100e-03 -6.5797702626e-03\natom  1.4228600746e+01  2.9039993932e+00  2.4085886675e+01 Mg  3.3242875318e-01 0.0  8.2199742070e-04 -8.7433931632e-03 -5.0428951488e-03\natom  1.1393340419e+01 -2.1582938461e-02  2.8053962143e+01 Mg  3.3511014318e-01 0.0  7.6887719023e-04 -2.6986067207e-03  1.0960239048e-03\natom  1.4242070751e+01  2.8134769831e+00  2.8051942630e+01 O  -3.4108566682e-01 0.0  1.7012093278e-03  6.3625321366e-03  4.9086813532e-04\natom  1.1377964569e+01 -3.4727513390e-02  3.2094720063e+01 O  -3.4199860682e-01 0.0 -7.9376785283e-04  5.5162368148e-03  3.0858131814e-03\natom  1.4223284059e+01  2.8352243655e+00  3.2091930166e+01 Mg  3.4024326318e-01 0.0 -1.6900273960e-04  1.6216057042e-03 -2.7114430102e-03\natom  1.1361327800e+01  4.1899760510e-03  3.6174381469e+01 Mg  3.3035160318e-01 0.0  4.2427021903e-03 -2.0245545784e-03 -5.7696498325e-03\natom  1.4279617830e+01  2.8567112303e+00  3.6075542810e+01 O  -3.4052679682e-01 0.0 -4.7902578240e-03  1.3030894219e-03  5.2279731038e-03\natom  1.1393330479e+01  3.1494456785e-02  4.0139967242e+01 O  -3.9929900682e-01 0.0 -1.9486850343e-03 -4.5923354835e-04  9.1662916211e-03\natom  1.4310559334e+01  2.8323673076e+00  4.0092669782e+01 Mg  4.1162751318e-01 0.0 -6.6171988609e-03  3.2998353094e-03 -2.1818314708e-03\natom  1.1432967652e+01  5.6828117341e+00  2.0077433129e+01 Mg  4.1321334318e-01 0.0 -4.6309091762e-03  4.1419824462e-03 -2.2508100920e-03\natom  1.4283250488e+01  8.5690566037e+00  2.0067858511e+01 O  -3.9653101682e-01 0.0 -7.4382371224e-04 -1.9432170208e-03 -1.0794443881e-02\natom  1.1403378644e+01  5.6210464370e+00  2.3972921689e+01 O  -3.4222384682e-01 0.0 -1.2315755320e-03  9.0027002538e-03  1.0290721030e-02\natom  1.4273100108e+01  8.5645613802e+00  2.4035008939e+01 Mg  3.2749956318e-01 0.0 -3.9628021811e-03  2.7172527585e-03  2.6481489384e-05\natom  1.1369966247e+01  5.6778218181e+00  2.8100028919e+01 Mg  3.4451120318e-01 0.0  2.2046585152e-03  2.2216743196e-03 -3.1476394390e-03\natom  1.4207949632e+01  8.6081877455e+00  2.8059217603e+01 O  -3.4092786682e-01 0.0  5.4608540405e-03 -9.3729379776e-03  8.2721168997e-04\natom  1.1390098009e+01  5.7282584536e+00  3.2034293882e+01 O  -3.4356421682e-01 0.0  8.1593565547e-04 -4.3484359123e-03  4.7920927655e-03\natom  1.4270952510e+01  8.5945117230e+00  3.2119120280e+01 Mg  3.4173809318e-01 0.0 -6.0575735071e-03 -6.5200598184e-03 -2.5952251350e-03\natom  1.1432748690e+01  5.6667706250e+00  3.6170238358e+01 Mg  3.3417152318e-01 0.0 -4.3124014941e-03  7.4068231381e-03 -7.0808845262e-03\natom  1.4232193512e+01  8.5735702709e+00  3.6158466329e+01 O  -3.4225910682e-01 0.0  2.8228955136e-03 -4.6218431939e-03 -3.4425368402e-03\natom  1.1365729633e+01  5.6751913385e+00  4.0181389205e+01 O  -3.9987836682e-01 0.0  3.5319958997e-03  2.0628135331e-04  5.9174310504e-03\natom  1.4203829727e+01  8.5239107096e+00  4.0185914928e+01 Mg  4.1232200318e-01 0.0  4.6492419565e-03  5.0633088765e-03 -7.8583225154e-03\natom  1.1485608388e+01  1.1342416934e+01  1.9969317332e+01 Mg  4.2708024318e-01 0.0 -7.7160367261e-03  3.1247463865e-03  8.9877860258e-03\natom  1.4297199973e+01  1.4265206402e+01  2.0021272362e+01 O  -3.9898661682e-01 0.0 -5.4440677706e-03 -5.7087796539e-04 -6.9542002506e-03\natom  1.1412141662e+01  1.1419772848e+01  2.4049955651e+01 O  -3.4481198682e-01 0.0 -2.9290209016e-03 -4.2552468354e-03 -2.0264674849e-03\natom  1.4209274972e+01  1.4264344139e+01  2.4061504655e+01 Mg  3.3293344318e-01 0.0  2.8898029428e-03 -1.4342698009e-03 -2.3618356977e-03\natom  1.1419762587e+01  1.1347697735e+01  2.8094183448e+01 Mg  3.3681228318e-01 0.0 -4.2216993350e-03  9.1672041313e-03 -1.8979474538e-03\natom  1.4236694651e+01  1.4260999210e+01  2.8048596965e+01 O  -3.4309297682e-01 0.0  3.4629565207e-03 -7.6744705872e-04  3.8025935864e-03\natom  1.1356406462e+01  1.1366827337e+01  3.2128003334e+01 O  -3.4261319682e-01 0.0  3.8588903490e-03  3.8918807349e-03 -2.8064294668e-03\natom  1.4272500291e+01  1.4251348455e+01  3.2170426303e+01 Mg  3.3910722318e-01 0.0 -8.5054721531e-03  1.7644470862e-03 -7.2584599166e-03\natom  1.1406971089e+01  1.1394713797e+01  3.6093215036e+01 Mg  3.2588238318e-01 0.0 -3.6831674900e-03 -1.6062409621e-03  3.7572609196e-03\natom  1.4204817543e+01  1.4261814098e+01  3.6138522615e+01 O  -3.4374726682e-01 0.0  3.8289345248e-03  8.8194075031e-06  8.1023315042e-04\natom  1.1378980656e+01  1.1384831267e+01  4.0148565042e+01 O  -4.0108899682e-01 0.0  1.0505963317e-03  2.4793651555e-03  1.0214851984e-02\natom  1.4196289323e+01  1.4296237535e+01  4.0192140971e+01 Mg  4.2115043318e-01 0.0  2.5538657224e-03 -8.1797977381e-03 -1.1218326894e-02\natom  2.9745603822e+00  2.6132014417e+00  1.6073507915e+01 Au  1.3225958318e-01 0.0 -7.2544072155e-04  6.0103886771e-03 -4.0052390841e-02\natom  3.0918394982e+00  2.9107222068e+00  1.1093156501e+01 Au -1.7209788682e-01 0.0 -4.6386714614e-04 -3.0086623870e-03  2.0518462056e-02\nenergy -5.4268567509e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -1.3037030623e-03  1.2559453402e-01  2.0023192059e+01 Mg  4.0920482782e-01 0.0  1.4200276234e-03 -1.2651844892e-02  5.8342610232e-03\natom  2.9017895855e+00  2.7955334490e+00  1.9996286897e+01 O  -3.9676692218e-01 0.0 -6.4770756128e-03  6.2383579833e-03 -7.0703371180e-03\natom  2.1403206622e-02  7.4579226667e-02  2.4062794506e+01 O  -3.4251430218e-01 0.0 -1.9071227764e-03 -7.5313673812e-03 -4.5250764492e-03\natom  2.8544910857e+00  2.8640063285e+00  2.4002363583e+01 Mg  3.3335399782e-01 0.0  2.4414142424e-03 -4.3814981266e-03  4.4428685886e-03\natom -1.8152726744e-02  4.2322870158e-03  2.8054545331e+01 Mg  3.3464189782e-01 0.0  7.6725072235e-03 -1.4462865222e-03 -1.6112028182e-03\natom  2.8396412409e+00  2.8266520771e+00  2.8093062369e+01 O  -3.4213308218e-01 0.0  4.2241925570e-03  5.7489696272e-03 -3.6492258943e-03\natom -2.6732630753e-03  1.4127289135e-02  3.2041672034e+01 O  -3.3867905218e-01 0.0  1.1397096455e-03 -4.6216965167e-04  7.3271708004e-03\natom  2.8412465254e+00  2.8094828771e+00  3.2101019426e+01 Mg  3.4095667782e-01 0.0  6.2974936741e-03  4.2283025354e-03 -4.7853242662e-04\natom -2.2344346856e-02  1.0995295076e-02  3.6099503175e+01 Mg  3.4390230782e-01 0.0  9.6154878442e-03 -5.9606351837e-03  5.3690853816e-03\natom  2.9308226364e+00  2.9015254963e+00  3.6118819935e+01 O  -3.4321161218e-01 0.0 -1.4291286982e-02 -9.0862593972e-03 -3.6754942650e-03\natom  3.6574267009e-02 -7.6641994865e-03  4.0176906019e+01 O  -4.0249758218e-01 0.0 -6.0923878393e-03  3.4033638839e-03  2.0086180517e-03\natom  2.8272169917e+00  2.8959999186e+00  4.0159249704e+01 Mg  4.0946396782e-01 0.0  4.5630392359e-03 -5.2735012177e-03 -8.3517263929e-03\natom  5.2770957280e-02  5.6806295541e+00  1.9975834449e+01 Mg  4.1765175782e-01 0.0 -6.6322733629e-03  5.5248969742e-04  8.1174057145e-03\natom  2.8195811381e+00  8.5561738503e+00  1.9970814373e+01 O  -3.9224334218e-01 0.0 -2.4429147176e-03 -1.6941314775e-03 -5.2149285584e-03\natom -3.2174417990e-02  5.6567203630e+00  2.3988753625e+01 O  -3.4228630218e-01 0.0  4.3959053472e-03  5.7249523134e-03  3.2547743093e-04\natom  2.8876249365e+00  8.5871661124e+00  2.4030342544e+01 Mg  3.3774934782e-01 0.0 -1.5260097321e-03 -2.8737845160e-03  6.7849711839e-04\natom  5.1112344779e-02  5.6755306010e+00  2.8033702844e+01 Mg  3.4245840782e-01 0.0 -3.0623125446e-03  3.5212646904e-03  4.5125990446e-04\natom  2.8539301016e+00  8.5358376585e+00  2.8038856750e+01 O  -3.4128138218e-01 0.0  2.1249514295e-03  8.8683189325e-05  2.5477192956e-04\natom -2.3056490095e-02  5.7076067910e+00  3.2077739949e+01 O  -3.3799893218e-01 0.0  8.4261443964e-04 -2.6095121254e-03 -1.8366891542e-03\natom  2.8360518198e+00  8.5427479896e+00  3.2113782390e+01 Mg  3.4078954782e-01 0.0  1.9008391684e-03  8.8501735133e-04 -4.0328481370e-04\natom -4.4269136749e-02  5.6599561030e+00  3.6035361887e+01 Mg  3.3017306782e-01 0.0  1.2905655465e-02  9.1654599673e-03  1.1206558515e-02\natom  2.8288553653e+00  8.5264557548e+00  3.6034880196e+01 O  -3.4907859218e-01 0.0  8.9410337597e-04  2.6451494939e-03  5.5092739976e-03\natom -6.6481316169e-03  5.7499058506e+00  4.0102551745e+01 O  -3.9920009218e-01 0.0 -1.0087577581e-03 -6.5679491353e-03  1.0533154104e-02\natom  2.9076954705e+00  8.5579654050e+00  4.0271221487e+01 Mg  4.2236989782e-01 0.0 -1.7547169074e-03  5.9820253187e-04 -1.9251169970e-02\natom  1.5089046279e-02  1.1425815228e+01  2.0045389593e+01 Mg  3.9274191782e-01 0.0 -6.2111266589e-04  8.5060375846e-04  1.4009328899e-03\natom  2.8778902776e+00  1.4230599642e+01  1.9987471306e+01 O  -3.9359112218e-01 0.0 -4.6393795971e-03  2.1661805561e-03 -7.3683691500e-03\natom  1.4518405722e-02  1.1417157808e+01  2.4034720850e+01 O  -3.3868748218e-01 0.0  5.0521705065e-04 -3.7109077145e-03 -2.6118387606e-03\natom  2.8035943397e+00  1.4219348667e+01  2.3973093711e+01 Mg  3.3102607782e-01 0.0  7.4590105797e-03  6.9411259870e-03  6.2543376906e-03\natom -1.9818085566e-02  1.1415734145e+01  2.8030150291e+01 Mg  3.3841087782e-01 0.0  4.7930439189e-03 -2.9866663447e-03  5.8016455897e-03\natom  2.8527306925e+00  1.4273732959e+01  2.8002099425e+01 O  -3.4316422218e-01 0.0  8.1621323198e-04 -4.3066741924e-03  4.5361200835e-03\natom -2.1651308747e-02  1.1415172613e+01  3.2124751191e+01 O  -3.4253303218e-01 0.0  2.2797037420e-03 -1.2462893394e-03 -5.5512531963e-03\natom  2.9409678949e+00  1.4223521711e+01  3.2067647414e+01 Mg  3.4425439782e-01 0.0 -8.7794784820e-03  2.3457047079e-03  2.0259266078e-03\natom -6.9101175588e-02  1.1311965833e+01  3.6099468555e+01 Mg  3.3091403782e-01 0.0  1.1455751890e-02  5.9658469633e-03  3.8157353922e-03\natom  2.8670022812e+00  1.4219450523e+01  3.6151212106e+01 O  -3.4660534218e-01 0.0 -3.2254852417e-03  4.1832892802e-03 -7.0145157368e-03\natom  3.4599937988e-03  1.1392478572e+01  4.0136626018e+01 O  -4.0106737218e-01 0.0 -5.9679126368e-05 -4.3419681464e-04  8.7875677682e-03\natom  2.8796917723e+00  1.4223485164e+01  4.0172645499e+01 Mg  4.0406386782e-01 0.0  2.3822209938e-03  1.7694558784e-03 -9.0346952592e-03\natom  5.7337221994e+00 -2.7184388647e-02  1.9978686896e+01 Mg  3.9877405782e-01 0.0  4.5216452264e-03  8.0089486488e-04  6.6813088745e-03\natom  8.5209668378e+00  2.8084663368e+00  1.9962589057e+01 O  -4.0708120218e-01 0.0  4.6600588957e-03  4.5628334881e-03 -2.1873473419e-03\natom  5.7185906721e+00 -6.4469589471e-02  2.4049632092e+01 O  -3.4388707218e-01 0.0 -2.2089671260e-03  8.0471484190e-03 -4.1315733415e-05\natom  8.5740420599e+00  2.7964541424e+00  2.4091253118e+01 Mg  3.3452410782e-01 0.0 -1.3502130261e-03  8.7535057263e-04 -1.4458852680e-02\natom  5.7319935915e+00  2.2662463329e-02  2.8040088681e+01 Mg  3.3697880782e-01 0.0 -5.6538640763e-03 -4.9245046832e-03  8.5265796593e-04\natom  8.5500898019e+00  2.8371877341e+00  2.8030116786e+01 O  -3.3651135218e-01 0.0  4.0139585301e-03  3.0340764359e-03  5.1782779676e-03\natom  5.7056649086e+00  4.0358802349e-02  3.2059492471e+01 O  -3.4119566218e-01 0.0  3.7685061182e-03 -3.8130990544e-03  1.9757442207e-03\natom  8.5928730282e+00  2.8558461137e+00  3.2084543246e+01 Mg  3.4786298782e-01 0.0 -4.8362345450e-03 -7.9142332995e-04  6.0060287684e-03\natom  5.7575351847e+00  2.4950656940e-02  3.6132990253e+01 Mg  3.2932675782e-01 0.0 -7.8598479420e-03 -6.0632706011e-04  4.6475196276e-03\natom  8.4739712611e+00  2.9159075583e+00  3.6203332109e+01 O  -3.4459639218e-01 0.0  1.5118077828e-02 -1.0727012893e-02 -1.1222493414e-02\natom  5.6922594192e+00 -4.7055613308e-02  4.0173045101e+01 O  -4.0765747218e-01 0.0  3.6075465110e-03  4.4801156444e-03  5.4076131701e-03\natom  8.5996326725e+00  2.8701117875e+00  4.0120850132e+01 Mg  4.0796779782e-01 0.0 -8.1919453288e-03 -3.8290013844e-03 -4.0114646558e-03\natom  5.6007927885e+00  5.7023950212e+00  2.0014187383e+01 Mg  4.0042630782e-01 0.0  1.4503709446e-02 -2.3417691590e-03  1.5998169070e-03\natom  8.5146729164e+00  8.5514153313e+00  2.0051800394e+01 O  -3.9460569218e-01 0.0  1.6531832080e-03 -4.2600862671e-03 -7.0311535049e-03\natom  5.7197826357e+00  5.6884328185e+00  2.3960697468e+01 O  -3.4120903218e-01 0.0 -4.8249154594e-03 -7.9710976095e-04  9.5897995452e-03\natom  8.5549792600e+00  8.4696221323e+00  2.3954905155e+01 Mg  3.2870367782e-01 0.0  1.1432156805e-03  9.6481482896e-03  2.8966482454e-03\natom  5.7780513728e+00  5.6995714682e+00  2.8046260054e+01 Mg  3.4810102782e-01 0.0 -9.1197471677e-03  7.6853263763e-04  2.7720821471e-03\natom  8.5657790629e+00  8.5694953602e+00  2.8065299214e+01 O  -3.3939796218e-01 0.0 -1.3583128714e-03 -4.7054970094e-03 -8.8824235378e-04\natom  5.7287020857e+00  5.7236784759e+00  3.2181901343e+01 O  -3.4222445218e-01 0.0  9.8718974869e-05 -3.0852827652e-03 -1.5697346597e-02\natom  8.5458859741e+00  8.5110578706e+00  3.2057989667e+01 Mg  3.4196735782e-01 0.0 -5.3969461013e-04  3.6000555090e-03  8.0083093895e-03\natom  5.7000028171e+00  5.6563453657e+00  3.6120226477e+01 Mg  3.1796695782e-01 0.0 -1.0766141924e-03  1.0458916941e-02  3.3505247503e-03\natom  8.5468524556e+00  8.5298160089e+00  3.6147923869e+01 O  -3.4596524218e-01 0.0  3.0567979628e-03  5.6140690207e-03 -5.6777935468e-03\natom  5.6638608816e+00  5.6750897846e+00  4.0106114389e+01 O  -4.0018211218e-01 0.0  2.9531307836e-03  2.7292653169e-03  1.4998085093e-02\natom  8.5945856112e+00  8.5183056312e+00  4.0214785708e+01 Mg  4.1276492782e-01 0.0 -5.9460791198e-03  2.0006645077e-03 -1.3415447626e-02\natom  5.6909224758e+00  1.1423814443e+01  1.9953363037e+01 Mg  3.1593829782e-01 0.0  9.3019918119e-03 -3.9098421893e-04  4.6476760394e-03\natom  8.5839726077e+00  1.4298703798e+01  2.0040741396e+01 O  -3.9613257218e-01 0.0 -5.6378769453e-04 -3.3901003133e-03 -4.9215586649e-03\natom  5.7205650200e+00  1.1419326230e+01  2.3984768495e+01 O  -3.4164241218e-01 0.0 -3.2648281812e-03 -4.8902458156e-03  4.4191414639e-03\natom  8.5324490586e+00  1.4267668356e+01  2.4052141667e+01 Mg  3.2868051782e-01 0.0  3.6853918633e-03 -4.3462856542e-03 -4.9069822891e-03\natom  5.7200612947e+00  1.1402651610e+01  2.8017683996e+01 Mg  3.4197745782e-01 0.0 -2.3190964461e-03  1.9112919866e-03  1.9113463155e-04\natom  8.5797554196e+00  1.4261998308e+01  2.8077802510e+01 O  -3.4111832218e-01 0.0  1.6565518791e-03 -9.0411412726e-04  3.3803036850e-04\natom  5.6952931853e+00  1.1438157577e+01  3.2050385598e+01 O  -3.3894689218e-01 0.0  3.7562552632e-03 -3.8285401294e-03 -6.8431200586e-04\natom  8.5519691533e+00  1.4183597319e+01  3.2104436127e+01 Mg  3.4259035782e-01 0.0  2.1280409914e-03  6.2985967254e-03 -2.5429729314e-03\natom  5.7431637240e+00  1.1443523265e+01  3.6057814988e+01 Mg  3.3414361782e-01 0.0 -8.5262321448e-03 -9.9234414721e-03  1.0637249971e-02\natom  8.4794280905e+00  1.4253636649e+01  3.6139678806e+01 O  -3.3972771218e-01 0.0  1.0328882750e-02 -4.1147058493e-04 -5.0120905189e-03\natom  5.7380219875e+00  1.1377392436e+01  4.0220606423e+01 O  -4.0416876218e-01 0.0 -1.2991938629e-04 -1.1997027742e-03  4.6967332098e-03\natom  8.6478835942e+00  1.4229224658e+01  4.0130244602e+01 Mg  4.0445459782e-01 0.0 -1.1554577537e-02 -2.3184251083e-06 -4.9074575359e-04\natom  1.1457393419e+01 -5.2171422812e-02  2.0002974901e+01 Mg  4.0032761782e-01 0.0 -7.3470239087e-03  1.3188302571e-03  5.0461425059e-03\natom  1.4260649573e+01  2.7790088157e+00  1.9954918300e+01 O  -4.0085549218e-01 0.0  3.1924420723e-04  8.8586551146e-03 -4.4026167084e-03\natom  1.1426558344e+01 -3.6908975276e-02  2.4037661737e+01 O  -3.4238631218e-01 0.0  1.6589460147e-03  4.0235973997e-03  4.8442549585e-03\natom  1.4247276304e+01  2.8213693103e+00  2.4068390080e+01 Mg  3.3176018782e-01 0.0 -8.4320721836e-04  1.8847376158e-03 -5.5073343100e-03\natom  1.1460962752e+01  2.3527749962e-02  2.8098128970e+01 Mg  3.4658625782e-01 0.0 -3.1123166156e-03 -6.4237371971e-03 -2.2223961260e-03\natom  1.4275365474e+01  2.8362789271e+00  2.8057015732e+01 O  -3.3908636218e-01 0.0 -4.1835400166e-03  1.9634715663e-03  2.9110099536e-03\natom  1.1449408552e+01 -7.4601468742e-03  3.2145898302e+01 O  -3.3990946218e-01 0.0 -3.0916865722e-03  3.6707344804e-03 -5.6823099694e-03\natom  1.4340970071e+01  2.8612307367e+00  3.2145306969e+01 Mg  3.3966110782e-01 0.0 -7.5644690880e-03 -9.8613576906e-04 -7.9246391559e-03\natom  1.1435467023e+01 -6.5120089848e-02  3.6090545420e+01 Mg  3.3763672782e-01 0.0 -7.0282047832e-03  5.9925466487e-03  4.8368322484e-03\natom  1.4254592170e+01  2.8979708461e+00  3.6107086173e+01 O  -3.3724762218e-01 0.0  1.0431266161e-03 -7.8617087042e-03 -3.2923731564e-04\natom  1.1399047430e+01 -4.8381029322e-02  4.0193942220e+01 O  -4.0056940218e-01 0.0  4.4157818203e-03  4.8378095364e-03  9.2165360665e-04\natom  1.4244281447e+01  2.8356460956e+00  4.0123793947e+01 Mg  4.1606940782e-01 0.0  1.4293849554e-03 -1.1922773173e-05 -2.9790182129e-03\natom  1.1397616000e+01  5.7124967593e+00  1.9961592869e+01 Mg  4.0634169782e-01 0.0 -6.8626074971e-03 -5.7079339919e-03  6.6684451044e-03\natom  1.4204619292e+01  8.5508472796e+00  2.0005286017e+01 O  -3.8809638218e-01 0.0  7.6410535854e-03 -3.4980419222e-03 -1.0716385577e-02\natom  1.1366931102e+01  5.7297935725e+00  2.4048847951e+01 O  -3.4304312218e-01 0.0  4.8181544008e-03 -7.3562339981e-03 -1.3179968957e-03\natom  1.4245079459e+01  8.5793419098e+00  2.3968849387e+01 Mg  3.3106450782e-01 0.0 -1.4506598982e-03 -5.2180219971e-03  7.9545642459e-03\natom  1.1408318860e+01  5.6615059617e+00  2.8048148060e+01 Mg  3.4484475782e-01 0.0  4.5116541750e-03  6.8255732911e-03 -6.1477365942e-04\natom  1.4258529471e+01  8.5832618251e+00  2.8009633290e+01 O  -3.4334326218e-01 0.0 -6.0141298663e-05 -5.6444521833e-03  3.8252362949e-03\natom  1.1412031888e+01  5.7233702616e+00  3.2129115306e+01 O  -3.3828563218e-01 0.0  1.0916213261e-03 -4.8610011084e-03 -7.1411092165e-03\natom  1.4238564327e+01  8.5241956803e+00  3.2102670253e+01 Mg  3.4146836782e-01 0.0  1.7051755338e-03  6.5233655754e-03 -3.4330266694e-03\natom  1.1477507209e+01  5.6915729006e+00  3.6077522165e+01 Mg  3.3061844782e-01 0.0 -1.3100194609e-02  4.8260768501e-03  7.0435904331e-03\natom  1.4263742582e+01  8.5516340292e+00  3.6147635403e+01 O  -3.4153612218e-01 0.0 -3.6750169512e-03 -2.6540323631e-03 -5.6638027459e-03\natom  1.1366305395e+01  5.7191120664e+00  4.0081286507e+01 O  -3.9781328218e-01 0.0  7.1200489150e-03 -5.5170215971e-03  1.2444328975e-02\natom  1.4288054814e+01  8.5037772099e+00  4.0179047607e+01 Mg  4.1091052782e-01 0.0 -1.1674921039e-03  3.6847711619e-03 -8.8799312161e-03\natom  1.1460821703e+01  1.1371787320e+01  1.9993334313e+01 Mg  3.0447368782e-01 0.0 -1.2066596605e-02  5.5800396364e-03  4.8388979780e-03\natom  1.4283884075e+01  1.4206241301e+01  2.0033088554e+01 O  -3.9322788218e-01 0.0  3.3994323214e-03  2.7265023112e-03 -7.6198542262e-03\natom  1.1439847559e+01  1.1397297695e+01  2.3984625348e+01 O  -3.4309120218e-01 0.0 -2.3296762272e-03 -1.3308499854e-03  6.4721982982e-03\natom  1.4249893196e+01  1.4164086181e+01  2.4081313953e+01 Mg  3.3322768782e-01 0.0 -2.0402829721e-03  8.8047333879e-03 -4.3037742419e-03\natom  1.1399810633e+01  1.1374868820e+01  2.8099075344e+01 Mg  3.4080512782e-01 0.0  1.5241949404e-03  1.1977498735e-03 -5.4309038497e-03\natom  1.4331077639e+01  1.4213894785e+01  2.8065930949e+01 O  -3.3939988218e-01 0.0 -8.1698352544e-03  4.9967719253e-03 -6.2222277322e-04\natom  1.1453564116e+01  1.1425430556e+01  3.2083488911e+01 O  -3.4105529218e-01 0.0 -5.9894868423e-03 -3.3954930230e-03  1.3382916862e-03\natom  1.4289108733e+01  1.4274464377e+01  3.2057010977e+01 Mg  3.3748822782e-01 0.0 -5.2383087925e-04 -5.8226708260e-03  3.9508092779e-03\natom  1.1382001912e+01  1.1381356193e+01  3.6168324576e+01 Mg  3.3435281782e-01 0.0 -2.7285978742e-04 -3.9078628984e-03 -2.9755244443e-03\natom  1.4157188511e+01  1.4259361290e+01  3.6138453016e+01 O  -3.4195882218e-01 0.0  8.4574996135e-03 -3.1597232582e-04 -2.2117502855e-03\natom  1.1417759931e+01  1.1340052225e+01  4.0160683212e+01 O  -4.0005443218e-01 0.0  1.8506796971e-03  4.0300970424e-03  6.7190448555e-03\natom  1.4277088489e+01  1.4225174333e+01  4.0127169281e+01 Mg  4.0726267782e-01 0.0  1.4351911535e-03 -4.9894279531e-04 -2.3790936716e-03\natom  1.0861098906e+01  1.0954927278e+01  1.4586344225e+01 Au  1.0474088782e-01 0.0  6.1557756529e-02 -6.3690337798e-03  2.2481632233e-03\natom  6.4459283094e+00  1.1363509923e+01  1.4401533767e+01 Au  9.3832827818e-02 0.0 -6.1339712879e-02  6.1746157220e-03 -2.4423537336e-03\nenergy -5.4268523610e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom  1.1133509634e-03 -1.9813172278e-02  2.0033253735e+01 Mg  3.5947305191e-01 0.0 -5.1121814271e-03  7.0801184345e-04 -1.0487366672e-02\natom  2.8748945706e+00  2.8136013270e+00  1.9959147224e+01 O  -3.4061716809e-01 0.0 -3.8275384526e-03  4.9747794458e-03  1.1110913673e-02\natom -8.1876157908e-03  2.2547076660e-03  2.3977301356e+01 O  -3.4350473809e-01 0.0  2.2682379983e-03  1.0269419546e-03  1.6086695572e-02\natom  2.8780529641e+00  2.8342486244e+00  2.4066834098e+01 Mg  3.4247998191e-01 0.0 -1.5803668236e-03  5.5876483695e-04 -8.3813666355e-03\natom -4.1682612096e-02  6.6660140940e-02  2.8152704445e+01 Mg  3.3770222191e-01 0.0  5.0434729998e-03 -8.3680738050e-03 -2.4918586069e-02\natom  2.7902341093e+00  2.8465396856e+00  2.8069928419e+01 O  -3.4084404809e-01 0.0  6.3158771518e-03  7.3492094845e-04  1.0093733133e-02\natom -2.4915659214e-02  2.8012334295e-02  3.2066022570e+01 O  -3.0936895809e-01 0.0  1.2063775994e-03 -1.7312027299e-03  2.6128678172e-02\natom  2.8364370404e+00  2.8772442559e+00  3.2128948499e+01 Mg  3.3157930191e-01 0.0  2.4814517445e-04 -2.4758307841e-04 -1.3168014792e-02\natom -2.7229250742e-03 -5.6652681227e-02  3.6082213335e+01 Al  3.9874588191e-01 0.0 -5.6302978568e-03  4.8449329364e-03  1.8360193458e-02\natom  2.7837357573e+00  2.7952681314e+00  3.6140405783e+01 O  -2.9273228809e-01 0.0  2.3668979567e-03 -3.3922056292e-03 -9.6034442124e-03\natom -3.3387659869e-02 -3.1537882688e-02  4.0134282890e+01 O  -3.6660617809e-01 0.0  3.3927400869e-03  4.0698466618e-03 -2.2605990129e-02\natom  2.8652768668e+00  2.8202960593e+00  4.0134812089e+01 Mg  3.7587243191e-01 0.0 -1.9444159169e-03  2.2828146145e-03  1.4979470573e-02\natom -2.3431959752e-02  5.7054461350e+00  2.0007589839e+01 Mg  3.7412253191e-01 0.0 -2.3192090873e-03  4.6849665942e-03 -6.4997853289e-03\natom  2.8683294168e+00  8.6137078430e+00  2.0002371946e+01 O  -4.0173166809e-01 0.0 -3.6115867433e-03 -7.1748485510e-03  5.5074443821e-03\natom -8.6093667267e-02  5.7456995851e+00  2.4069177113e+01 O  -3.4189931809e-01 0.0  1.0543399538e-02 -7.4946273342e-03  7.0997987003e-03\natom  2.8597973229e+00  8.5580829271e+00  2.4167021020e+01 Mg  3.2798329191e-01 0.0  3.8107388909e-04 -1.8579009914e-04 -2.4978415972e-02\natom -1.7504040504e-02  5.6163172465e+00  2.8035819469e+01 Mg  3.3434817191e-01 0.0  2.4422307166e-04  1.0999140676e-02 -3.1771859949e-03\natom  2.8013755369e+00  8.5624998592e+00  2.8033295721e+01 O  -3.4012544809e-01 0.0  4.4104233888e-03 -2.2112496852e-03  1.7879600339e-02\natom  1.0117428537e-01  5.7465745283e+00  3.2128356259e+01 O  -3.4752040809e-01 0.0 -9.9492108390e-03 -6.0549269411e-03  3.4692476038e-03\natom  2.8225038262e+00  8.5570985310e+00  3.2090086965e+01 Mg  3.3200397191e-01 0.0 -2.9412852372e-03  8.8331913718e-04 -6.5354664521e-03\natom  2.2400622896e-03  5.7301287910e+00  3.6205799071e+01 Mg  3.1777456191e-01 0.0 -2.4242469931e-03 -2.0400346218e-03  6.4664453664e-05\natom  2.8368477535e+00  8.5125838243e+00  3.6094098861e+01 O  -3.2018135809e-01 0.0  1.4783961489e-02 -6.1180014571e-03 -6.2353157853e-03\natom -8.8559173867e-03  5.8082750833e+00  4.0128583986e+01 O  -4.0699051809e-01 0.0  1.2409735898e-03 -1.1806324561e-02 -1.9368879846e-03\natom  2.8626123343e+00  8.6140130149e+00  4.0137507821e+01 Mg  3.8140541191e-01 0.0 -4.0679562426e-03 -2.7032707760e-03  8.9587571717e-03\natom -1.2712829232e-02  1.1453302049e+01  1.9986482299e+01 Mg  4.2764279191e-01 0.0  1.4432526062e-03 -6.8791430966e-03 -1.8595861792e-03\natom  2.8748958745e+00  1.4208195258e+01  1.9992101645e+01 O  -3.9696568809e-01 0.0 -1.3088692579e-03  3.3468362266e-03  4.9349655332e-03\natom  3.6138004868e-02  1.1355533144e+01  2.4067275236e+01 O  -3.4182232809e-01 0.0 -6.9506804822e-03  6.0609375046e-03  7.5495518323e-03\natom  2.8331026000e+00  1.4203157476e+01  2.4003654587e+01 Mg  3.2897430191e-01 0.0  2.0701862538e-03  2.4110329193e-03 -7.2055716819e-03\natom -2.7892601256e-02  1.1423781656e+01  2.8046560237e+01 Mg  3.3927304191e-01 0.0 -1.4288668157e-03 -2.8412608954e-03 -7.9869365255e-03\natom  2.7793329037e+00  1.4256519842e+01  2.8030420371e+01 O  -3.4042910809e-01 0.0  4.0446888322e-03  3.7992980404e-04  1.4703651124e-02\natom -2.9845236223e-02  1.1457765033e+01  3.2080524592e+01 O  -3.4314623809e-01 0.0 -2.1851240771e-04 -1.7751689805e-03  4.9092087201e-03\natom  2.8386141937e+00  1.4158187799e+01  3.2065077915e+01 Mg  3.3791458191e-01 0.0  2.8742027219e-03  5.7294082809e-03 -5.8966500845e-03\natom -5.0489642272e-02  1.1394952828e+01  3.6099637024e+01 Mg  3.1846749191e-01 0.0  3.1035252454e-03 -3.1855806450e-03  1.0552413943e-02\natom  2.7711304157e+00  1.4185588334e+01  3.6158051138e+01 O  -3.1453518809e-01 0.0 -6.8337286987e-03  1.8048084175e-02 -1.4409026465e-02\natom -4.5695709795e-02  1.1383623770e+01  4.0144143027e+01 O  -4.0664892809e-01 0.0  2.2411596994e-03  4.3079950904e-03 -5.6026801219e-03\natom  2.8079699436e+00  1.4239676052e+01  4.0136895436e+01 Mg  3.8531379191e-01 0.0  4.7608946124e-03 -2.7381730126e-03  1.2146288972e-02\natom  5.6764819646e+00  9.7262306907e-04  2.0020478280e+01 Mg  3.7358284191e-01 0.0  7.9598114292e-03 -2.9768754340e-03 -9.6076013332e-03\natom  8.5578687077e+00  2.8768964896e+00  2.0020496384e+01 O  -4.0123424809e-01 0.0 -5.0999096142e-04 -5.3449550038e-03  3.9167571141e-04\natom  5.6827214619e+00  2.2727658876e-02  2.3988494940e+01 O  -3.4247327809e-01 0.0 -2.3036644930e-03 -3.3945097013e-03  1.3783293582e-02\natom  8.6234098852e+00  2.7715246126e+00  2.4011869415e+01 Mg  3.2230189191e-01 0.0 -6.0039730630e-03  4.7311293072e-03 -9.0319769252e-03\natom  5.6660725035e+00 -4.3399522643e-02  2.8077976535e+01 Mg  3.4241258191e-01 0.0  3.0151436076e-03  4.7158823331e-03 -1.3085519809e-02\natom  8.5960560826e+00  2.8481617508e+00  2.8067262034e+01 O  -3.4355394809e-01 0.0 -5.3477853624e-03  1.2566640648e-03  1.0708008973e-02\natom  5.6944476652e+00  2.6367082157e-02  3.2052157537e+01 O  -3.4436994809e-01 0.0 -3.4322793504e-03 -1.9997866942e-03  1.0230171053e-02\natom  8.5751846638e+00  2.8482736415e+00  3.2098118225e+01 Mg  3.3058487191e-01 0.0  1.7023811427e-03  1.2835225804e-03 -1.3534376014e-02\natom  5.6950167751e+00 -1.1237633536e-03  3.6062509634e+01 Mg  3.2545700191e-01 0.0 -3.0546480390e-04 -4.0107323457e-03  1.1448043045e-02\natom  8.5546737291e+00  2.8842585030e+00  3.6118313072e+01 O  -3.1126054809e-01 0.0 -1.6961879353e-02  9.7706707321e-03 -9.6617640530e-03\natom  5.7185377409e+00 -5.6714588651e-02  4.0170679371e+01 O  -4.0753120809e-01 0.0 -3.7409525154e-03  5.2681784104e-03 -1.0451603453e-02\natom  8.5243793239e+00  2.8728256797e+00  4.0145190710e+01 Mg  3.8172162191e-01 0.0  2.5691878397e-03 -6.2419412319e-03  1.1958491469e-02\natom  5.6941424744e+00  5.7253773018e+00  2.0005896059e+01 Mg  3.7296457191e-01 0.0  6.0209188711e-03  2.6101586475e-03 -6.2949190943e-03\natom  8.5538900219e+00  8.5228306179e+00  1.9978333460e+01 O  -4.0171346809e-01 0.0  5.0966134151e-05  4.8854990784e-03  3.0171263533e-03\natom  5.7481407709e+00  5.6661012273e+00  2.4015702667e+01 O  -3.4313691809e-01 0.0 -9.2286250586e-03  7.0536817384e-04  1.4407448326e-02\natom  8.5471146362e+00  8.5284919346e+00  2.4078962454e+01 Mg  3.3309346191e-01 0.0 -9.9093921142e-04  2.3591136594e-03 -1.9201035558e-02\natom  5.6969830349e+00  5.7182257471e+00  2.8075189605e+01 Mg  3.4582727191e-01 0.0  1.4835421826e-03 -5.1096007214e-03 -1.5638441439e-02\natom  8.4803640907e+00  8.5705330277e+00  2.8051992254e+01 O  -3.3935207809e-01 0.0  4.0253518633e-03 -5.3735675578e-04  1.1786152036e-02\natom  5.7105924636e+00  5.7443845248e+00  3.2107059898e+01 O  -3.0806831809e-01 0.0 -1.3935135082e-04 -4.0665142384e-03  2.0646065538e-02\natom  8.4902260226e+00  8.6218390127e+00  3.2045124809e+01 Mg  3.3100419191e-01 0.0  8.8515995609e-03 -7.1338031889e-03 -7.0811831496e-03\natom  5.7449891804e+00  5.6468921438e+00  3.6053536799e+01 Al  3.9712018191e-01 0.0 -2.2108881620e-03  8.5873969535e-03  1.6144641506e-02\natom  8.5952203891e+00  8.5277590043e+00  3.6124364013e+01 O  -2.9141337809e-01 0.0 -4.3008988297e-03  4.7179852386e-03 -8.3664453064e-03\natom  5.6834566976e+00  5.7206494719e+00  4.0131761164e+01 O  -3.6644548809e-01 0.0  2.1672288949e-04 -3.2638207753e-03 -2.2752923062e-02\natom  8.5502950450e+00  8.5702637984e+00  4.0244996814e+01 Mg  3.7359428191e-01 0.0 -4.5792434512e-04 -3.6336782833e-03  8.8762431440e-03\natom  5.6840743167e+00  1.1383819205e+01  1.9965062652e+01 Mg  4.2695040191e-01 0.0  2.0858376582e-03 -2.0867162322e-03  1.7014290868e-03\natom  8.6262722154e+00  1.4215873026e+01  2.0028496237e+01 O  -3.9830384809e-01 0.0 -8.7264442103e-03  2.5711449978e-03 -3.4108169920e-03\natom  5.6850967341e+00  1.1382063328e+01  2.4076513464e+01 O  -3.4426288809e-01 0.0  1.8530228891e-03  2.0659749625e-03  8.4542550762e-03\natom  8.5157887996e+00  1.4253956504e+01  2.3984890118e+01 Mg  3.2652435191e-01 0.0  4.0216611742e-03 -1.2616805941e-03 -6.0523566334e-03\natom  5.6910788129e+00  1.1402665537e+01  2.8114326718e+01 Mg  3.3702913191e-01 0.0 -1.5223827465e-03  2.2448427944e-03 -1.7776466579e-02\natom  8.5463997339e+00  1.4267206431e+01  2.8040207961e+01 O  -3.4018769809e-01 0.0 -3.5829502715e-03 -2.6073221656e-03  1.4781974681e-02\natom  5.7062206770e+00  1.1407734557e+01  3.2113241173e+01 O  -3.4172577809e-01 0.0 -1.9388417738e-03  3.3979822779e-04  3.9078777722e-03\natom  8.5689890082e+00  1.4260601688e+01  3.2070356185e+01 Mg  3.3334835191e-01 0.0 -4.4721584794e-03  3.0521985190e-03 -5.8842605157e-03\natom  5.6949986526e+00  1.1383322585e+01  3.6150195603e+01 Mg  3.2515727191e-01 0.0 -3.1619441871e-03 -1.3376091421e-04  4.7999217496e-03\natom  8.5434482654e+00  1.4300328849e+01  3.6137545532e+01 O  -3.1660044809e-01 0.0  8.3245828734e-03 -1.5408143625e-02 -1.2934699813e-02\natom  5.7181540698e+00  1.1376153626e+01  4.0130830795e+01 O  -4.0394315809e-01 0.0 -1.3341428157e-03  9.3510385366e-04 -6.2297556478e-03\natom  8.5757377488e+00  1.4208991551e+01  4.0071599394e+01 Mg  3.7539778191e-01 0.0 -6.4089327567e-03  8.6319807081e-03  1.7029886924e-02\natom  1.1415521683e+01 -3.0122232258e-04  1.9946217151e+01 Mg  4.2907690191e-01 0.0 -4.8359502254e-04  3.0760114717e-03  3.0244899085e-03\natom  1.4231933354e+01  2.8482749076e+00  2.0043374408e+01 O  -3.9971134809e-01 0.0  2.1701618676e-03  1.2439152490e-03  3.0159067182e-03\natom  1.1338914856e+01 -4.0755625910e-02  2.4048334134e+01 O  -3.4635064809e-01 0.0  8.1194668809e-03  3.2630636718e-03  1.0398277671e-02\natom  1.4224977858e+01  2.8641398565e+00  2.4112200712e+01 Mg  3.3086107191e-01 0.0 -9.5787227755e-04 -5.2339099269e-03 -2.1124703416e-02\natom  1.1412814140e+01 -1.7851731188e-02  2.8157131790e+01 Mg  3.3465869191e-01 0.0 -6.4030483383e-03  2.2584097956e-03 -2.1581492309e-02\natom  1.4283626733e+01  2.8215028194e+00  2.8072435480e+01 O  -3.3725432809e-01 0.0 -4.0623556828e-03  1.2471838623e-03  1.1523218191e-02\natom  1.1355555443e+01  1.9484473340e-02  3.2118980063e+01 O  -3.4204425809e-01 0.0  6.1772449619e-03 -2.3213369729e-03  4.6757271767e-03\natom  1.4229265231e+01  2.8672635169e+00  3.2084583195e+01 Mg  3.4016392191e-01 0.0 -2.0912451506e-03  8.9196375299e-03 -1.8060632153e-03\natom  1.1349966540e+01  2.9737597431e-02  3.6130071514e+01 Mg  3.1754013191e-01 0.0  4.5013557913e-03  5.2340880074e-04  8.2389237463e-03\natom  1.4223588891e+01  2.7787772108e+00  3.6194816891e+01 O  -3.1928370809e-01 0.0  1.5305997438e-02 -5.8564712147e-03 -1.5058121792e-02\natom  1.1408847794e+01 -4.8974138721e-04  4.0123047902e+01 O  -4.0676589809e-01 0.0 -2.7823938293e-03 -5.0855965414e-04 -3.8444915976e-03\natom  1.4193775100e+01  2.8731416985e+00  4.0220219653e+01 Mg  3.8976269191e-01 0.0  1.2807489366e-04  2.2181166391e-04  4.9259466969e-03\natom  1.1425419406e+01  5.7009913894e+00  2.0019460002e+01 Mg  4.1706881191e-01 0.0 -3.5843504097e-03 -4.9088422886e-04 -3.1018855311e-03\natom  1.4227417702e+01  8.5404013846e+00  1.9976463180e+01 O  -4.0078769809e-01 0.0  1.9044747846e-03  4.8529415313e-03  3.8148391608e-03\natom  1.1359026813e+01  5.6654214173e+00  2.3997266141e+01 O  -3.4112365809e-01 0.0  5.2317237785e-03  4.9308673065e-03  1.7613702740e-02\natom  1.4272984665e+01  8.5551416819e+00  2.4073169877e+01 Mg  3.3157577191e-01 0.0 -4.6104584885e-03  1.7891393151e-03 -1.6028433418e-02\natom  1.1407924625e+01  5.7234904482e+00  2.7987804971e+01 Mg  3.3889060191e-01 0.0 -3.6246386170e-03 -2.5620085982e-03 -1.9537063675e-04\natom  1.4199922756e+01  8.4841581503e+00  2.8089882016e+01 O  -3.4245103809e-01 0.0  2.2161547276e-03  7.9133602500e-03  7.0358359015e-03\natom  1.1397627357e+01  5.7150984207e+00  3.2079726939e+01 O  -3.4796848809e-01 0.0  3.8182676734e-04  2.5884248304e-04  6.6374350704e-03\natom  1.4279049344e+01  8.6024920925e+00  3.2130029064e+01 Mg  3.3560327191e-01 0.0 -2.0107366653e-03 -8.3665714829e-03 -1.2385434993e-02\natom  1.1376244427e+01  5.7046232349e+00  3.6090353915e+01 Mg  3.2072987191e-01 0.0  6.4372630295e-03 -1.2554533351e-03  8.3137349878e-03\natom  1.4270855190e+01  8.5430268754e+00  3.6158088044e+01 O  -3.1766402809e-01 0.0 -1.5381268241e-02  1.1658357782e-02 -1.1367671601e-02\natom  1.1325752102e+01  5.6636983274e+00  4.0160014098e+01 O  -4.0554592809e-01 0.0  4.5157267589e-03  5.2203168090e-03 -5.3194093547e-03\natom  1.4264809956e+01  8.5205770251e+00  4.0169943361e+01 Mg  3.8272614191e-01 0.0 -5.1912765593e-04  2.1559968902e-03  9.5484813879e-03\natom  1.1381346933e+01  1.1429242246e+01  1.9938720041e+01 Mg  4.2850838191e-01 0.0  1.8912595160e-03 -4.7138685754e-03  4.2774654650e-03\natom  1.4252734191e+01  1.4313478224e+01  1.9937378865e+01 O  -3.9830613809e-01 0.0  1.7815119067e-03 -7.8943132139e-03  4.7845681913e-03\natom  1.1396026325e+01  1.1456867225e+01  2.4042161779e+01 O  -3.4391351809e-01 0.0  2.3739848611e-03 -8.3734909990e-03  9.3238533243e-03\natom  1.4283615791e+01  1.4247423343e+01  2.4058327194e+01 Mg  3.3363688191e-01 0.0 -7.4531695346e-03  3.2402296782e-03 -1.4233120019e-02\natom  1.1348631506e+01  1.1428529215e+01  2.8000757040e+01 Mg  3.4070450191e-01 0.0  2.9783089190e-03 -1.2907692788e-03 -9.8225927399e-03\natom  1.4192021963e+01  1.4278604691e+01  2.8029505063e+01 O  -3.3959707809e-01 0.0  5.4618690632e-03 -1.6119218671e-03  1.6688775067e-02\natom  1.1376802860e+01  1.1410047411e+01  3.2083637859e+01 O  -3.1224426809e-01 0.0  1.0084801762e-03  2.5160042823e-03  2.0551545469e-02\natom  1.4262147162e+01  1.4337235972e+01  3.2079489136e+01 Mg  3.3459645191e-01 0.0 -5.0482771003e-03 -8.7325770200e-03 -8.4054728937e-03\natom  1.1352234117e+01  1.1389204660e+01  3.6111878631e+01 Al  3.9491101191e-01 0.0  2.9430041274e-03 -1.6851370522e-03  1.0618459660e-02\natom  1.4268252319e+01  1.4296673136e+01  3.6139964646e+01 O  -2.9217377809e-01 0.0  1.7465969658e-03  1.1909585658e-03 -1.2249449952e-02\natom  1.1374198440e+01  1.1427444267e+01  4.0174524340e+01 O  -3.6414151809e-01 0.0  1.6771206303e-03 -3.7130944475e-03 -2.3126138472e-02\natom  1.4216401299e+01  1.4282712748e+01  4.0161198692e+01 Mg  3.7225994191e-01 0.0  1.1773021202e-03 -2.7794994121e-03  1.2735973192e-02\natom  2.7396664969e+00  2.7530599866e+00  1.5605570640e+01 Au  2.9926171909e-02 0.0  1.5759702770e-04  1.6684712422e-03  5.6457079357e-02\natom  2.8589761991e+00  2.6403939184e+00  1.1130759800e+01 Au -2.0977655809e-01 0.0  7.9295338259e-04 -1.3856739893e-03 -5.4677948061e-02\nenergy -5.4395978424e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -6.1593861153e-02 -5.1896033044e-02  1.9944476411e+01 Mg  3.7308888645e-01 0.0 -1.4877094637e-03 -1.7377535579e-03  4.1867800340e-04\natom  2.7872111713e+00  2.9062283817e+00  1.9984035387e+01 O  -3.1145419355e-01 0.0  4.2284285852e-03 -3.8851834490e-03  6.1995418504e-02\natom -5.1827058046e-02  3.6145866128e-02  2.4015858286e+01 O  -3.4589860355e-01 0.0  6.7415472190e-03 -4.8455096702e-03  5.3702232904e-03\natom  2.8294029701e+00  2.9203172716e+00  2.4068705720e+01 Mg  3.3546864645e-01 0.0 -7.6739238102e-04 -1.0563211159e-02 -5.3840218655e-03\natom -3.6460297635e-02 -5.1430612430e-02  2.7997712842e+01 Mg  3.3718811645e-01 0.0  5.2934423211e-03  5.9635511093e-03 -7.1620870658e-03\natom  2.8609313096e+00  2.8170644011e+00  2.7989567915e+01 O  -3.4305181355e-01 0.0  3.0061208251e-04  6.7078032757e-03  1.6548634445e-02\natom  1.8608339680e-02 -1.2858697181e-02  3.2081668424e+01 O  -3.1261659355e-01 0.0 -2.3241258059e-03  2.8353665422e-03  2.2636244833e-02\natom  2.8008292549e+00  2.8700808716e+00  3.2156983019e+01 Mg  3.3527828645e-01 0.0  3.3349629959e-03 -5.2742242663e-03 -1.6938357157e-02\natom -1.0946445659e-02  5.8986795179e-02  3.6098097143e+01 Al  4.0140111645e-01 0.0  1.2567775053e-03 -7.6381467943e-03  8.7928570005e-03\natom  2.8791431848e+00  2.7732306950e+00  3.6131868606e+01 O  -2.9032472355e-01 0.0 -6.3494270838e-03  5.2473392289e-03 -1.0720529298e-02\natom  7.1685205802e-02  1.7300932754e-02  4.0181317754e+01 O  -3.6609865355e-01 0.0 -8.7179548641e-03 -1.1459956152e-03 -2.5526785475e-02\natom  2.8399832435e+00  2.8240626800e+00  4.0102610912e+01 Mg  3.6379004645e-01 0.0  2.2526188956e-03  3.5358392080e-03  1.8019079991e-02\natom -6.1300821344e-03  5.7112703839e+00  2.0012376836e+01 Mg  3.6897301645e-01 0.0 -7.9842457142e-03  7.5892060730e-03 -5.4844486429e-03\natom  2.8907008245e+00  8.5927018001e+00  2.0004400775e+01 O  -3.9883695355e-01 0.0 -7.4137683236e-03 -2.6778361018e-03  2.8404611445e-03\natom -1.5288355679e-02  5.6458439883e+00  2.3978061763e+01 O  -3.4300069355e-01 0.0  2.1453876554e-03  9.3707368167e-03  1.2698907957e-02\natom  2.7838498968e+00  8.5683974672e+00  2.4039081714e+01 Mg  3.3266426645e-01 0.0  4.1229824795e-03 -2.1767993053e-03 -1.1640449159e-02\natom  7.5771983917e-02  5.7027960778e+00  2.8117730757e+01 Mg  3.4355567645e-01 0.0 -1.0725819500e-02 -2.8645569568e-03 -1.0448972540e-02\natom  2.8896776135e+00  8.5365720249e+00  2.8148101110e+01 O  -3.3894229355e-01 0.0 -2.3048326187e-03 -1.6106728043e-03 -3.4428614391e-03\natom -4.2589623879e-02  5.6475283200e+00  3.2123172401e+01 O  -3.4477897355e-01 0.0  1.0098648619e-02  5.3116879578e-03  4.9389382504e-03\natom  2.8772380765e+00  8.5631050439e+00  3.2080817878e+01 Mg  3.2966975645e-01 0.0 -6.4607091811e-03  5.4155003397e-03 -3.8546548383e-03\natom  6.8000107844e-02  5.6649095094e+00  3.6160636245e+01 Mg  3.2468365645e-01 0.0 -8.4888465654e-03  4.2393597897e-03  4.6440539560e-03\natom  2.8729528393e+00  8.5472989222e+00  3.6072440919e+01 O  -3.1578100355e-01 0.0  1.1394751979e-02 -1.2977622135e-02 -4.5330040004e-03\natom  9.1054065706e-02  5.6548955113e+00  4.0109080162e+01 O  -4.0828743355e-01 0.0 -6.7628062186e-03  2.7417283293e-03 -5.6583803945e-03\natom  2.8427627092e+00  8.5433581066e+00  4.0225674102e+01 Mg  3.8497542645e-01 0.0 -2.8389164370e-03  4.2021681083e-03  6.4749256081e-03\natom  2.9478421511e-02  1.1407806706e+01  1.9959135980e+01 Mg  4.2773400645e-01 0.0 -1.1951751764e-03  5.3184348088e-04 -1.8041768278e-03\natom  2.8241717361e+00  1.4303834347e+01  1.9986105790e+01 O  -4.0045211355e-01 0.0  3.1033772991e-03 -3.6708036263e-03  2.9163072550e-03\natom -8.7505840601e-03  1.1409545538e+01  2.4004853164e+01 O  -3.4007056355e-01 0.0  5.8370986344e-04 -1.9634365444e-03  1.0418713574e-02\natom  2.8886505852e+00  1.4185381069e+01  2.3988945186e+01 Mg  3.3111686645e-01 0.0 -3.7811173130e-03  1.0259675607e-02 -4.3276038688e-03\natom  3.6900301434e-03  1.1414074512e+01  2.8037729661e+01 Mg  3.3873002645e-01 0.0  1.2333586263e-03 -9.4934209952e-05 -1.6302947918e-03\natom  2.8682059988e+00  1.4271671022e+01  2.8096854576e+01 O  -3.4424116355e-01 0.0 -3.6499690313e-03 -4.0807558537e-03  4.3642159851e-05\natom  2.9881953599e-02  1.1425414984e+01  3.2121132555e+01 O  -3.4776727355e-01 0.0 -5.7154327754e-03 -1.7676379453e-03  2.8024734944e-03\natom  2.8923982709e+00  1.4308601559e+01  3.2079347954e+01 Mg  3.2655123645e-01 0.0 -2.2601303396e-03 -6.9164190061e-03 -4.4423001578e-03\natom -3.6182583504e-04  1.1356889929e+01  3.6135432270e+01 Mg  3.2250931645e-01 0.0  6.3986369709e-03  6.0263714940e-03  4.0041671971e-03\natom  2.8589272174e+00  1.4280699150e+01  3.6130625941e+01 O  -3.2035221355e-01 0.0 -1.3651403360e-02  9.5727789961e-03 -7.5977897382e-03\natom -6.2016914110e-02  1.1412388612e+01  4.0144588284e+01 O  -4.0662514355e-01 0.0  1.0233730840e-03 -9.9926422544e-04 -7.5624014627e-03\natom  2.8768200124e+00  1.4290666982e+01  4.0166409932e+01 Mg  3.8038508645e-01 0.0 -1.9898749703e-03 -6.9599522133e-03  8.1201719388e-03\natom  5.7921643189e+00 -2.4040772774e-02  2.0078331826e+01 Mg  3.6348357645e-01 0.0 -3.0724973987e-03 -4.9567255509e-03 -8.6445920130e-03\natom  8.6108619913e+00  2.8720064645e+00  2.0059511119e+01 O  -3.9401904355e-01 0.0 -6.5309072463e-03 -3.0841763602e-03  4.5302457664e-04\natom  5.6829134958e+00 -1.2598973241e-02  2.4018656158e+01 O  -3.4511674355e-01 0.0  2.4880764339e-03  3.8258055709e-03  6.3351243584e-03\natom  8.5400240630e+00  2.8711656688e+00  2.4000978810e+01 Mg  3.3340212645e-01 0.0  1.6875345032e-03 -3.8283438689e-03 -1.6900244388e-03\natom  5.7149504552e+00  2.6064366951e-02  2.8124523264e+01 Mg  3.3482065645e-01 0.0 -4.2203302206e-03 -5.5432984277e-03 -1.4223171493e-02\natom  8.5397814222e+00  2.8775524891e+00  2.8114775169e+01 O  -3.3994493355e-01 0.0  3.5781518280e-04 -2.6210808316e-03 -4.4823142123e-04\natom  5.6768707946e+00  1.5323051048e-02  3.2099455792e+01 O  -3.4614518355e-01 0.0  3.5577089504e-03  2.6665764843e-03  5.0115617322e-03\natom  8.5192949027e+00  2.8361082281e+00  3.2009895913e+01 Mg  3.3360448645e-01 0.0  6.7249666900e-03 -3.0419990392e-03  4.2657324197e-03\natom  5.7194295782e+00  9.4034654919e-03  3.6180098079e+01 Mg  3.1541448645e-01 0.0  1.2730896160e-04 -4.7070179716e-03 -1.4402801512e-03\natom  8.5313663590e+00  2.8400933012e+00  3.6132543371e+01 O  -3.1712884355e-01 0.0 -1.0909065878e-02  1.4917885028e-02 -1.0899130038e-02\natom  5.6591313888e+00  2.0471212662e-03  4.0112803338e+01 O  -4.0357775355e-01 0.0  6.3379858271e-03  2.7951748032e-03 -1.9570799274e-03\natom  8.5340626767e+00  2.8221102529e+00  4.0091207531e+01 Mg  3.8327261645e-01 0.0  3.6694805942e-03  1.3180043212e-03  1.3141786628e-02\natom  5.7632100318e+00  5.7447457648e+00  2.0011868972e+01 Mg  3.5230600645e-01 0.0 -4.1433006349e-04  4.1348340754e-03 -6.5164366342e-03\natom  8.4807180742e+00  8.4931326858e+00  1.9983662412e+01 O  -3.9823810355e-01 0.0  9.0455970163e-03  6.3370475855e-03  3.3023031834e-03\natom  5.6485769668e+00  5.6942634547e+00  2.3992432525e+01 O  -3.4109070355e-01 0.0  3.0354708179e-03  8.0330282673e-04  1.2114018102e-02\natom  8.5112145100e+00  8.5459791376e+00  2.3994222964e+01 Mg  3.3292323645e-01 0.0  2.8764122206e-03  8.3766123236e-04 -5.4724061783e-03\natom  5.7148126563e+00  5.7095328375e+00  2.8046854675e+01 Mg  3.4126595645e-01 0.0 -5.3837973583e-05 -1.8385356624e-03 -1.0230772130e-02\natom  8.6174236301e+00  8.5363009060e+00  2.8051320589e+01 O  -3.4219034355e-01 0.0 -7.4510128387e-03 -1.2514280622e-04  8.8233261249e-03\natom  5.7387781424e+00  5.6968560643e+00  3.2092707391e+01 O  -3.0853596355e-01 0.0 -3.0389539038e-03  1.5924860442e-03  2.0280157111e-02\natom  8.5686008962e+00  8.5617170402e+00  3.2141452533e+01 Mg  3.3708585645e-01 0.0  2.4528444887e-04 -8.0633225107e-04 -1.5987927825e-02\natom  5.7193646850e+00  5.7336161669e+00  3.6066603574e+01 Al  3.9402751645e-01 0.0 -9.4983094605e-05 -1.1834354667e-03  1.8477452059e-02\natom  8.5866409197e+00  8.5759108666e+00  3.6172084583e+01 O  -2.9090145355e-01 0.0 -2.4041964372e-03  1.5009111680e-03 -1.4416345107e-02\natom  5.6941242197e+00  5.7626220247e+00  4.0082170370e+01 O  -3.6461928355e-01 0.0  2.6988219015e-03 -6.0502325689e-03 -2.2705645362e-02\natom  8.5682729721e+00  8.5603809850e+00  4.0197467674e+01 Mg  3.6668676645e-01 0.0 -4.3329958770e-03 -6.7931377996e-04  1.2746067174e-02\natom  5.7092332782e+00  1.1358188644e+01  1.9996723026e+01 Mg  4.2176703645e-01 0.0 -2.1799567864e-03  3.0999655212e-03 -4.9055816799e-03\natom  8.5660408466e+00  1.4229943113e+01  1.9988315428e+01 O  -3.9660182355e-01 0.0 -3.6848858262e-04  4.2334862173e-04  1.2725959776e-03\natom  5.6587564293e+00  1.1386980887e+01  2.3975313516e+01 O  -3.4133423355e-01 0.0  3.1602824948e-03 -2.2444601499e-03  1.3610456965e-02\natom  8.5677884463e+00  1.4219588870e+01  2.3967137352e+01 Mg  3.2934069645e-01 0.0 -1.6494056201e-03  3.4399629242e-03  4.9280095608e-04\natom  5.6988692083e+00  1.1344107010e+01  2.8046762816e+01 Mg  3.3745541645e-01 0.0  2.0093977784e-03  8.6520401577e-03 -5.1861948831e-03\natom  8.4938585295e+00  1.4218644309e+01  2.8036174586e+01 O  -3.4331679355e-01 0.0  8.4546535799e-03  1.5818478197e-03  1.0968209711e-02\natom  5.6553806984e+00  1.1420636472e+01  3.2046212535e+01 O  -3.4525457355e-01 0.0  9.8509221886e-03 -4.9633318564e-03  1.0210230869e-02\natom  8.5642111762e+00  1.4215309699e+01  3.2150987448e+01 Mg  3.3656467645e-01 0.0 -7.6806879223e-03  7.5504488299e-03 -1.1535456531e-02\natom  5.6974456966e+00  1.1402279409e+01  3.6099001112e+01 Mg  3.2466105645e-01 0.0 -4.0736585154e-03  4.5049781116e-03  1.0340630576e-02\natom  8.5178731863e+00  1.4254259238e+01  3.6131949713e+01 O  -3.1967902355e-01 0.0  1.3772459945e-02 -1.2723413394e-02 -8.4927855672e-03\natom  5.6502121467e+00  1.1416734150e+01  4.0215843690e+01 O  -4.0745650355e-01 0.0  3.6742431932e-03 -1.5227352031e-03 -9.2035365281e-03\natom  8.5254492490e+00  1.4229065071e+01  4.0163290618e+01 Mg  3.8425848645e-01 0.0 -2.2756667554e-03  3.7237874108e-03  8.4954823612e-03\natom  1.1379927277e+01  5.9571457503e-02  1.9983116810e+01 Mg  4.2610468645e-01 0.0  4.1474496344e-03 -5.3775306710e-03 -5.3301558410e-04\natom  1.4243131549e+01  2.8381202761e+00  2.0035160884e+01 O  -3.9811553355e-01 0.0 -3.4414562170e-04  1.8918754803e-03 -2.1303591126e-03\natom  1.1429055296e+01  2.1195544633e-03  2.4006854857e+01 O  -3.4316032355e-01 0.0 -5.9686122713e-03 -1.9261197616e-04  1.1033131209e-02\natom  1.4251746091e+01  2.8103725412e+00  2.4014552013e+01 Mg  3.2349770645e-01 0.0 -4.4057429880e-04  3.3548186146e-03 -3.7182505424e-03\natom  1.1376446023e+01 -6.8310722104e-02  2.8074610101e+01 Mg  3.4420271645e-01 0.0  1.6688697914e-03  5.1782748939e-03 -9.6109808211e-03\natom  1.4274826279e+01  2.8137577774e+00  2.8086626472e+01 O  -3.4469504355e-01 0.0 -3.4592010240e-03  2.3874182689e-03  4.0761864524e-03\natom  1.1443613745e+01  4.9572747222e-02  3.2151300008e+01 O  -3.4553198355e-01 0.0 -5.9170005886e-03 -7.9594871133e-03 -4.8283595369e-03\natom  1.4224663332e+01  2.9218587211e+00  3.2089554894e+01 Mg  3.2307511645e-01 0.0 -9.2247636109e-04 -4.3973248440e-03 -7.9937275465e-03\natom  1.1396483109e+01 -3.3231776373e-03  3.6094129966e+01 Mg  3.1515744645e-01 0.0 -2.1599996523e-03  3.2438498655e-03  6.2233524121e-03\natom  1.4218758997e+01  2.8158925631e+00  3.6078446808e+01 O  -3.1519208355e-01 0.0  1.8507267534e-02 -8.9695518638e-03 -1.8799889498e-03\natom  1.1445283129e+01 -3.1520629490e-05  4.0082833834e+01 O  -4.0501588355e-01 0.0 -4.5593794383e-03 -1.1264967024e-03 -3.0192281599e-03\natom  1.4212708283e+01  2.8449850648e+00  4.0149592316e+01 Mg  3.8596447645e-01 0.0  1.7402011438e-03  4.8608234495e-03  8.8697471649e-03\natom  1.1390848551e+01  5.6542503966e+00  2.0055834109e+01 Mg  4.1960185645e-01 0.0  2.5202216087e-03  5.6046532219e-03 -5.0432228934e-03\natom  1.4192667701e+01  8.5858529229e+00  2.0007427077e+01 O  -3.9859019355e-01 0.0  4.1182505694e-03 -2.3804965641e-03  6.7309725920e-05\natom  1.1395836540e+01  5.7335627633e+00  2.4033683769e+01 O  -3.4285073355e-01 0.0 -1.3974972104e-03 -2.1314342428e-03  8.9810105428e-03\natom  1.4237365919e+01  8.5961439549e+00  2.3954138078e+01 Mg  3.3418670645e-01 0.0 -1.1075487261e-03 -4.8042004844e-03  4.8580481193e-04\natom  1.1373939321e+01  5.6638414174e+00  2.8036606559e+01 Mg  3.3782620645e-01 0.0  8.6667229790e-03  3.1803233530e-03 -4.7545609748e-03\natom  1.4269948953e+01  8.5927857984e+00  2.8121098721e+01 O  -3.4485146355e-01 0.0  1.5611344118e-03 -2.9397939079e-03  1.4830115571e-03\natom  1.1475684889e+01  5.7109836180e+00  3.2101993505e+01 O  -3.4649465355e-01 0.0 -1.1817644508e-02  4.9327469661e-03  4.2350600813e-03\natom  1.4263232129e+01  8.5994471392e+00  3.2142730309e+01 Mg  3.3181271645e-01 0.0  5.5239280819e-03 -8.1173989342e-03 -1.2261368161e-02\natom  1.1339167531e+01  5.7345467247e+00  3.6090583857e+01 Mg  3.2034233645e-01 0.0  8.2374708872e-03 -8.9282407453e-03  8.8959176112e-03\natom  1.4200214171e+01  8.5406437608e+00  3.6148361341e+01 O  -3.1166895355e-01 0.0 -8.6546656543e-03  1.5754510811e-02 -1.1013319754e-02\natom  1.1423679063e+01  5.7246190492e+00  4.0135075762e+01 O  -4.0666811355e-01 0.0 -3.0566315513e-03 -7.3754265441e-04 -6.1900209054e-03\natom  1.4170373716e+01  8.6230583962e+00  4.0100408626e+01 Mg  3.7891057645e-01 0.0  9.4865299907e-03 -9.8049379407e-03  1.5134687241e-02\natom  1.1408234011e+01  1.1416693974e+01  2.0031946461e+01 Mg  4.2117740645e-01 0.0 -1.2186704410e-03 -1.2894986894e-03 -5.0352172299e-03\natom  1.4239585610e+01  1.4248294129e+01  1.9978386902e+01 O  -3.9843306355e-01 0.0 -9.8181057980e-04 -9.2681869829e-04  2.9322132921e-04\natom  1.1368807959e+01  1.1434069079e+01  2.4053674160e+01 O  -3.4233307355e-01 0.0  2.3471209370e-03 -3.8161575094e-03  3.8446596389e-03\natom  1.4249081445e+01  1.4270275781e+01  2.3986426711e+01 Mg  3.2976724645e-01 0.0 -3.3912477901e-04  3.5728472953e-04 -6.7940694996e-03\natom  1.1437284391e+01  1.1347018058e+01  2.8047193654e+01 Mg  3.3955626645e-01 0.0 -3.9740736320e-03  2.7129805989e-03 -1.2432377281e-02\natom  1.4266217651e+01  1.4232799982e+01  2.8035186505e+01 O  -3.3908039355e-01 0.0 -4.2503276847e-03 -6.8811495615e-04  9.5616464134e-03\natom  1.1395036260e+01  1.1434005868e+01  3.2142567339e+01 O  -3.0669106355e-01 0.0  6.1276597606e-04 -2.5323280631e-03  1.8480346867e-02\natom  1.4224926004e+01  1.4260751014e+01  3.2012716726e+01 Mg  3.3351629645e-01 0.0  7.6177833636e-03  2.8738519053e-03 -1.4862958234e-03\natom  1.1472822918e+01  1.1387658731e+01  3.6086485079e+01 Al  3.9530917645e-01 0.0 -6.0018123898e-03  3.9480039707e-03  1.4460429287e-02\natom  1.4217968543e+01  1.4253555542e+01  3.6101419338e+01 O  -2.9166369355e-01 0.0  8.7117579969e-04 -4.3481652285e-03 -8.2951467670e-03\natom  1.1353897284e+01  1.1421933013e+01  4.0112018894e+01 O  -3.6196844355e-01 0.0  2.5788963777e-03 -1.6867604034e-04 -2.3010016547e-02\natom  1.4219881891e+01  1.4247132458e+01  4.0076998152e+01 Mg  3.6713943645e-01 0.0  4.1565297637e-03  2.8566200720e-03  1.7791233770e-02\natom  3.0183085026e+00  2.9418123001e+00  1.6254603361e+01 Au  1.0173517645e-01 0.0 -1.4991286718e-04 -1.1486898562e-03 -4.6639218567e-02\natom  2.7552322644e+00  2.9179659045e+00  1.1603757799e+01 Au -2.4225124355e-01 0.0  6.9238375595e-04  1.6072721928e-04 -1.9158154316e-02\nenergy -5.4395978970e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -8.0970034297e-03  7.9408704890e-02  1.9975202638e+01 Mg  4.2969072409e-01 0.0 -1.0077842607e-03 -1.0794380019e-02  3.9997396588e-04\natom  2.7760197983e+00  2.8251877473e+00  1.9973016811e+01 O  -3.9582568591e-01 0.0  5.6879635968e-03  4.0520456767e-03  7.8416741266e-03\natom -3.4830711326e-02  1.2431826978e-02  2.4077905492e+01 O  -3.4283456591e-01 0.0  3.6454771225e-03  1.5898152470e-03  8.2521176835e-03\natom  2.8219261747e+00  2.8653838064e+00  2.4112279230e+01 Mg  3.3655967409e-01 0.0  2.6151936104e-03 -4.1179140050e-04 -1.9543192272e-02\natom  5.7644012584e-03  4.4877628517e-02  2.8028809077e+01 Mg  3.3319644409e-01 0.0 -3.8340158710e-03 -7.5327865579e-03 -1.5920550273e-02\natom  2.8460689738e+00  2.7866075739e+00  2.8050869682e+01 O  -3.3860821591e-01 0.0  6.8886535155e-04  7.1700188004e-03  1.8821741506e-02\natom -3.8811532505e-02 -1.8601763433e-02  3.2043412471e+01 O  -3.1199317591e-01 0.0  5.5509635734e-03  5.3546351032e-04  3.3798211502e-02\natom  2.8611319985e+00  2.8537515225e+00  3.2117183009e+01 Mg  3.3647737409e-01 0.0 -4.5113857642e-03 -2.6280047500e-03 -2.0156161563e-02\natom -7.5121918177e-02  5.7598092242e-03  3.6186436655e+01 Al  4.0907091409e-01 0.0  3.4416163343e-03 -2.6405107967e-03 -4.1535425689e-05\natom  2.8420858472e+00  2.8600584074e+00  3.6068995552e+01 O  -2.9360157591e-01 0.0 -3.6650530985e-04 -5.1850354714e-04  1.6673733524e-04\natom  1.9899381578e-02  1.7028131911e-03  4.0144787650e+01 O  -3.5816134591e-01 0.0 -3.7598571650e-03 -1.4058742445e-05 -2.6526095488e-02\natom  2.8634389571e+00  2.8580148199e+00  4.0185332156e+01 Mg  3.8006816409e-01 0.0  6.0450016430e-05  2.8852169200e-03  1.0444924169e-02\natom  2.5300218453e-02  5.7262873560e+00  2.0119720151e+01 Mg  4.0794126409e-01 0.0 -2.4932521175e-03  2.3345310273e-03 -1.0454485319e-02\natom  2.8683543612e+00  8.5731836707e+00  1.9955187851e+01 O  -3.9644525591e-01 0.0 -5.9512445894e-03 -7.6269261687e-03  1.2354508194e-02\natom -1.2360338643e-02  5.7283676231e+00  2.4072324413e+01 O  -3.4147914591e-01 0.0  4.1629360032e-03 -2.3065620962e-03  1.1741393685e-02\natom  2.8808439004e+00  8.6395401327e+00  2.3992013553e+01 Mg  3.3208566409e-01 0.0  9.6947543255e-04 -5.1424116945e-03 -1.1197591161e-02\natom  1.8632509275e-03  5.6100752926e+00  2.8006954056e+01 Mg  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4.1259091316e-03\natom  5.7193930120e+00  6.7091357513e-02  2.4051873780e+01 O  -3.4170529591e-01 0.0 -6.3305354574e-03 -2.4124602716e-03  1.2567768937e-02\natom  8.4753381566e+00  2.8974496597e+00  2.4033991246e+01 Mg  3.2609712409e-01 0.0  6.7281044280e-03 -1.4736764550e-03 -1.3129703987e-02\natom  5.6996985523e+00  2.6911587804e-04  2.8087988927e+01 Mg  3.3462110409e-01 0.0  1.7768477888e-03 -1.6295266464e-03 -1.7727386533e-02\natom  8.5124559277e+00  2.9005009246e+00  2.8051596036e+01 O  -3.4134972591e-01 0.0  1.7359921621e-03 -1.4440525469e-03  1.7838585353e-02\natom  5.7505570313e+00 -2.6107641676e-02  3.2043041348e+01 O  -3.4353116591e-01 0.0 -1.0432254585e-02  3.8879191449e-03  1.5673582669e-02\natom  8.5228220385e+00  2.8580087539e+00  3.2089313405e+01 Mg  3.3161608409e-01 0.0  9.6864643988e-03 -8.8402594285e-03 -1.5543393262e-02\natom  5.6459872107e+00 -2.4106327368e-02  3.6073709284e+01 Mg  3.2183775409e-01 0.0  7.7790985486e-03  6.2917397506e-04  5.7277740214e-03\natom  8.5003248695e+00  2.8406955757e+00  3.6072789139e+01 O  -3.1586378591e-01 0.0 -9.9565251474e-03  1.6704841532e-02  2.7679675531e-04\natom  5.6611169994e+00 -1.7109182258e-02  4.0137214913e+01 O  -4.0523890591e-01 0.0  7.2866832009e-05  1.4231426574e-03 -6.1262269806e-03\natom  8.5491929190e+00  2.8566923519e+00  4.0232842853e+01 Mg  3.8908824409e-01 0.0  1.7662269224e-03 -2.3982449595e-03  4.2515591177e-03\natom  5.6299090629e+00  5.6656251487e+00  2.0011196513e+01 Mg  4.1441554409e-01 0.0  8.1598132454e-03  9.9807869701e-03 -8.0439835386e-03\natom  8.5299008954e+00  8.4912559233e+00  1.9965641078e+01 O  -3.9880087591e-01 0.0  1.2044021549e-03 -2.5540342190e-03  1.5508851986e-02\natom  5.7684423807e+00  5.7365606057e+00  2.4048234678e+01 O  -3.4204473591e-01 0.0 -1.4749075865e-02 -3.4573411738e-03  1.3800016662e-02\natom  8.5433806699e+00  8.5296670607e+00  2.4007850383e+01 Mg  3.2487043409e-01 0.0 -2.8821161935e-04  4.4246366729e-03 -1.9651404528e-02\natom  5.6913901263e+00  5.7293418335e+00  2.8077536909e+01 Mg  3.4008030409e-01 0.0  2.0939612114e-03 -2.2086179912e-03 -2.3337073300e-02\natom  8.5125050228e+00  8.6106284967e+00  2.8076520255e+01 O  -3.3899312591e-01 0.0  2.6458808355e-03 -6.0900028462e-03  1.9152573033e-02\natom  5.7142152951e+00  5.6921375318e+00  3.2064077154e+01 O  -3.0423870591e-01 0.0 -2.0327004855e-03  2.0130331386e-03  3.3509732538e-02\natom  8.4963889104e+00  8.5683069683e+00  3.2155676009e+01 Mg  3.3627536409e-01 0.0  7.4102484663e-03 -1.4159735314e-03 -2.3479875709e-02\natom  5.7061201814e+00  5.7241351660e+00  3.6080484764e+01 Al  4.0799030409e-01 0.0 -5.3881617685e-04 -5.6391605658e-03  1.1269803080e-02\natom  8.5462409969e+00  8.5634573645e+00  3.6101658105e+01 O  -2.8989614591e-01 0.0 -8.6425914811e-04 -2.3528121945e-03 -5.2242835996e-03\natom  5.7492293287e+00  5.6872276647e+00  4.0196616824e+01 O  -3.6625350591e-01 0.0 -4.9131609219e-03 -8.7119913908e-04 -2.6222602976e-02\natom  8.5185442280e+00  8.5366984098e+00  4.0135797127e+01 Mg  3.7241895409e-01 0.0  4.5810897619e-04  6.4977003297e-04  1.4586114704e-02\natom  5.7079180478e+00  1.1417166727e+01  1.9971106770e+01 Mg  3.0830551409e-01 0.0  5.7943711675e-03 -1.6637512829e-03 -1.7838228892e-02\natom  8.5373249107e+00  1.4244022177e+01  2.0019616055e+01 O  -3.9667249591e-01 0.0 -5.0829420063e-04  1.1067812517e-02  1.3920148166e-02\natom  5.7208268416e+00  1.1402865111e+01  2.4051549975e+01 O  -3.4174846591e-01 0.0 -3.4508295591e-03  1.4601686641e-03  1.2976096668e-02\natom  8.5751964179e+00  1.4280930339e+01  2.4039006182e+01 Mg  3.2563324409e-01 0.0 -4.8171751451e-03 -3.6874544934e-03 -1.7914218684e-02\natom  5.6973006979e+00  1.1353375795e+01  2.8049109137e+01 Mg  3.3004423409e-01 0.0 -1.7236816731e-03  7.4518750814e-03 -1.8093753597e-02\natom  8.4942594538e+00  1.4253499493e+01  2.8034495187e+01 O  -3.4129159591e-01 0.0  5.1533115403e-03 -1.7338309524e-03  1.6588459563e-02\natom  5.6545735209e+00  1.1420109087e+01  3.2035900130e+01 O  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-4.4254116885e-03 -5.4522443590e-03\natom  1.4291229157e+01  2.7417587826e+00  3.6104652017e+01 O  -3.0728721591e-01 0.0  1.3737646295e-02 -7.6464064887e-03 -3.2513090862e-03\natom  1.1419102430e+01  3.2658074460e-02  4.0160012322e+01 O  -4.0348782591e-01 0.0 -9.2237186561e-04 -5.5647228494e-03 -6.0008973588e-03\natom  1.4219436312e+01  2.8244736387e+00  4.0096402709e+01 Mg  3.7753983409e-01 0.0  6.9313263646e-04  6.8539361317e-03  1.7731419514e-02\natom  1.1373130650e+01  5.6695850317e+00  1.9997340173e+01 Mg  4.1543289409e-01 0.0 -2.6838519169e-03  7.6369660628e-03 -5.3838182467e-03\natom  1.4279029180e+01  8.4741695878e+00  1.9988422235e+01 O  -3.9602169591e-01 0.0  7.2400178557e-04  3.9286784674e-03  9.4699091883e-03\natom  1.1311668805e+01  5.7087058934e+00  2.4046525572e+01 O  -3.4375972591e-01 0.0  8.9226055202e-03 -9.9083177431e-04  1.3747140973e-02\natom  1.4211479224e+01  8.6055444346e+00  2.3973278886e+01 Mg  3.3307197409e-01 0.0 -3.9922556734e-04 -4.2164101022e-03 -7.8419666521e-03\natom  1.1372439351e+01  5.7365223198e+00  2.8092830348e+01 Mg  3.3739138409e-01 0.0  1.5578867381e-03 -1.9633307114e-03 -1.8730108618e-02\natom  1.4210440763e+01  8.5682010869e+00  2.8001287599e+01 O  -3.4370466591e-01 0.0  1.4269240585e-03  2.2474352802e-04  1.9280559894e-02\natom  1.1403371331e+01  5.6882844373e+00  3.2088091565e+01 O  -3.4428928591e-01 0.0 -2.1270465368e-03  2.6002416436e-03  1.4851061164e-02\natom  1.4304970356e+01  8.4854823947e+00  3.2135184898e+01 Mg  3.2982759409e-01 0.0 -1.4110611019e-03 -6.3412101596e-04 -2.4308559644e-02\natom  1.1421453230e+01  5.6384628509e+00  3.6146951038e+01 Mg  3.2931945409e-01 0.0 -3.2096071454e-03  6.3105945050e-04  2.2543432187e-04\natom  1.4235446524e+01  8.5355105470e+00  3.6066956764e+01 O  -3.1158048591e-01 0.0 -1.2660370243e-02  1.2836818397e-02  1.4228205718e-04\natom  1.1472256492e+01  5.6624432469e+00  4.0142524533e+01 O  -4.0497216591e-01 0.0 -8.2153304684e-03  2.1495445825e-03 -9.3999313538e-03\natom  1.4211363384e+01  8.5847933346e+00  4.0117439365e+01 Mg  3.7865222409e-01 0.0  4.4096518694e-03 -1.0787540641e-02  1.4070700547e-02\natom  1.1421908824e+01  1.1409715273e+01  1.9953405612e+01 Mg  3.0134715409e-01 0.0 -1.0567524466e-02 -3.5900070414e-03 -1.5741338426e-02\natom  1.4212968706e+01  1.4217688146e+01  2.0052746297e+01 O  -3.9546500591e-01 0.0  7.0213323165e-03  7.4521836741e-03  2.8556182853e-03\natom  1.1343758469e+01  1.1438719506e+01  2.3973045221e+01 O  -3.3956499591e-01 0.0  6.7847426034e-03 -4.8834329781e-03  2.0251285511e-02\natom  1.4207231989e+01  1.4251204269e+01  2.3993704650e+01 Mg  3.3072808409e-01 0.0  3.1615485062e-03  9.5409403758e-05 -8.1314355593e-03\natom  1.1313003368e+01  1.1340656182e+01  2.8053721297e+01 Mg  3.4341540409e-01 0.0  8.4151590786e-03  7.8510892501e-03 -2.0601108918e-02\natom  1.4229139413e+01  1.4301759579e+01  2.8074710181e+01 O  -3.4415981591e-01 0.0  2.4062384618e-03 -8.0232295828e-03  1.2014423690e-02\natom  1.1423773776e+01  1.1417403037e+01  3.2097603803e+01 O  -3.0365465591e-01 0.0 -2.5964034469e-03 -4.7408140203e-03  3.3540833152e-02\natom  1.4299157389e+01  1.4220770345e+01  3.2049162964e+01 Mg  3.3126251409e-01 0.0 -5.8763346580e-03  3.3128296236e-03 -1.6622494540e-02\natom  1.1433974706e+01  1.1376884326e+01  3.6045420861e+01 Al  4.0899542409e-01 0.0 -6.2233483225e-03  2.7069560989e-03  8.9704190976e-03\natom  1.4325946900e+01  1.4273972463e+01  3.6187835751e+01 O  -2.8926989591e-01 0.0 -3.5787751594e-04 -6.1125753273e-04 -7.5837361351e-03\natom  1.1382829064e+01  1.1300800065e+01  4.0084445902e+01 O  -3.6339610591e-01 0.0  7.2617496689e-04  9.7667421209e-03 -2.3397203421e-02\natom  1.4263976115e+01  1.4191744570e+01  4.0246711665e+01 Mg  3.7596394409e-01 0.0 -3.7453337393e-03  1.2549834469e-03  1.1170876410e-02\natom  1.0753464460e+01  1.1409905342e+01  1.4660912265e+01 Au -6.7846285909e-02 0.0  2.4858419739e-02  1.1061387502e-04 -2.0340195473e-03\natom  6.0658258761e+00  1.1408809433e+01  1.4428359712e+01 Au -7.7769645909e-02 0.0 -2.3939723512e-02  1.1176958356e-04 -4.7863335386e-04\nenergy -5.4395990450e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -2.5475962970e-02  1.7262892570e-02  1.9945828340e+01 Mg  3.8544538691e-01 0.0 -4.8744862995e-03 -6.4936895830e-03  1.9834292260e-03\natom  2.8601726980e+00  2.8957708082e+00  1.9949292662e+01 O  -3.3814892309e-01 0.0 -3.7192843310e-03 -4.8417048762e-03 -2.1410014477e-02\natom  3.8793599005e-02 -3.5166421148e-02  2.3983425316e+01 O  -3.3857296309e-01 0.0 -3.0316040848e-03  4.9921530549e-03  3.6362274483e-03\natom  2.7933606798e+00  2.7782247494e+00  2.4056443893e+01 Mg  3.4118039691e-01 0.0  9.3795536846e-03  8.5646861089e-03  2.7403041422e-03\natom -1.5976612782e-02  1.6653985062e-02  2.8016574084e+01 Mg  3.4599386691e-01 0.0 -1.6340921481e-03 -1.4978733294e-03  9.2558751204e-03\natom  2.8577984085e+00  2.8756482311e+00  2.8043526225e+01 O  -3.3990530309e-01 0.0 -1.3665568328e-03 -7.0276955503e-03  7.5175696310e-04\natom -3.3439835204e-03 -5.3896421387e-02  3.2135613998e+01 O  -3.4463333309e-01 0.0  2.3680829887e-03  4.3496261983e-03 -6.7052301784e-03\natom  2.8490584825e+00  2.8340937424e+00  3.2103687304e+01 Mg  3.3923380691e-01 0.0 -2.3705143085e-03 -3.3038531956e-04 -2.0654595169e-03\natom  3.9446518231e-03 -3.4104584115e-02  3.6182663968e+01 Mg  3.3312303691e-01 0.0 -5.0486807079e-03  3.1415146635e-03 -7.0134360733e-03\natom  2.8071239321e+00  2.9535790947e+00  3.6104462534e+01 O  -3.4020232309e-01 0.0  6.0857089601e-03 -1.1812540413e-02  1.8981046807e-03\natom  1.4216276331e-02  1.3188208702e-03  4.0208741344e+01 O  -4.0143186309e-01 0.0  3.0369485500e-03 -1.7193931376e-03  3.3333775472e-03\natom  2.8973537750e+00  2.8452486437e+00  4.0115216556e+01 Mg  4.1410447691e-01 0.0 -4.3293012281e-03  6.2185297305e-03 -2.7642106554e-03\natom -2.2677732315e-02  5.6947440876e+00  2.0058148815e+01 Mg  3.7296624691e-01 0.0 -3.5776292667e-03  9.1820231111e-03 -4.1493097397e-04\natom  2.8453240627e+00  8.5758065537e+00  1.9976589923e+01 O  -3.9996197309e-01 0.0 -1.7845988178e-03 -3.2816545874e-03 -9.7875420019e-04\natom  8.0744892342e-02  5.7307685577e+00  2.4026795170e+01 O  -3.4292651309e-01 0.0 -5.2647998111e-03 -8.7306668279e-03  1.9189167570e-03\natom  2.9000555729e+00  8.5429757772e+00  2.4075623176e+01 Mg  3.3058758691e-01 0.0 -4.6502066748e-03 -5.2302439900e-05 -5.7117254674e-03\natom  5.2595004893e-02  5.7172572248e+00  2.8111832488e+01 Mg  3.3854699691e-01 0.0 -5.5071883894e-03 -9.1463590306e-04 -7.0351126568e-03\natom  2.8245767044e+00  8.5041882442e+00  2.8053218309e+01 O  -3.4092001309e-01 0.0  3.5222792969e-03  6.3772044601e-03  3.4608325337e-03\natom -6.9219718099e-03  5.5898460027e+00  3.2062051973e+01 O  -3.3927565309e-01 0.0 -7.2582208410e-04  1.1521488708e-02  7.7788871022e-04\natom  2.7710642942e+00  8.5617400193e+00  3.2072824034e+01 Mg  3.4402272691e-01 0.0  9.3370817985e-03 -1.3947578182e-03 -3.0877480796e-04\natom  5.3651191645e-02  5.7103324184e+00  3.6083216363e+01 Mg  3.3189432691e-01 0.0 -1.2104849771e-02 -3.0846230064e-03  5.1793280018e-03\natom  2.8075916960e+00  8.5256132394e+00  3.6066103250e+01 O  -3.4096978309e-01 0.0  3.3031193660e-03  3.9658464801e-03  5.0586250343e-03\natom -7.8427559157e-02  5.6892282609e+00  4.0181941231e+01 O  -4.0362242309e-01 0.0  9.0930208358e-03  4.4252859878e-03  4.3858777977e-03\natom  2.7871607534e+00  8.6129901251e+00  4.0170069727e+01 Mg  4.2041141691e-01 0.0  2.0098796596e-03 -7.8469739580e-03 -5.9271269655e-03\natom  1.7540436626e-03  1.1452431981e+01  1.9956718415e+01 Mg  4.2542894691e-01 0.0 -1.5811193436e-03 -6.4161518635e-03  7.9557908520e-03\natom  2.8914342461e+00  1.4249486716e+01  1.9941216558e+01 O  -3.9804356309e-01 0.0 -6.2772723290e-03  2.6332857053e-03  6.6757659836e-04\natom -7.8972215981e-03  1.1386783089e+01  2.4069367597e+01 O  -3.4500306309e-01 0.0  1.5880202251e-03  4.8135458807e-03 -2.0221998427e-03\natom  2.8459695364e+00  1.4269588620e+01  2.4073586920e+01 Mg  3.3478497691e-01 0.0  3.3064444139e-03 -5.1656649521e-03 -7.5914407679e-03\natom  2.3971060782e-02  1.1440831558e+01  2.8053146594e+01 Mg  3.4164420691e-01 0.0 -3.9610922807e-03 -4.5642761713e-03 -1.4367058296e-03\natom  2.8693205592e+00  1.4224383880e+01  2.8062053363e+01 O  -3.3703187309e-01 0.0 -3.9790150329e-04  3.0995499214e-03 -4.9665616307e-04\natom -6.6040046254e-02  1.1346167738e+01  3.2160920395e+01 O  -3.3948708309e-01 0.0  7.1876685080e-03  6.4845276992e-04 -1.1268367431e-02\natom  2.8475794507e+00  1.4274788031e+01  3.2049940001e+01 Mg  3.4208866691e-01 0.0 -1.6919098408e-03 -3.4016920788e-03  6.6075161117e-03\natom  4.3401469061e-02  1.1359291620e+01  3.6130180571e+01 Mg  3.2732141691e-01 0.0 -8.8354447344e-03  4.5306049746e-03 -1.2412691492e-03\natom  2.8093686999e+00  1.4212215632e+01  3.6085787959e+01 O  -3.4285254309e-01 0.0  6.5885363140e-03  4.1097420616e-03  4.4654527641e-03\natom -1.4485618977e-02  1.1406370250e+01  4.0139804480e+01 O  -3.9974608309e-01 0.0  7.6104732283e-04 -1.0128456411e-03  6.9604127294e-03\natom  2.9283123433e+00  1.4327833697e+01  4.0123455686e+01 Mg  4.1416441691e-01 0.0 -5.9445355077e-03 -2.6457839788e-03 -5.2897284771e-03\natom  5.6950848052e+00 -7.4786321739e-02  1.9970568671e+01 Mg  3.8152315691e-01 0.0  7.7660889105e-03  1.0455958189e-03  5.2253227326e-03\natom  8.5315350548e+00  2.8200755472e+00  2.0109980503e+01 O  -4.0056688309e-01 0.0 -8.1209187198e-04  1.9743075024e-03 -1.3588920508e-02\natom  5.6989666992e+00  2.7512445079e-02  2.4014348470e+01 O  -3.4319931309e-01 0.0 -5.2412826976e-03 -4.1012185943e-03  3.4838457082e-03\natom  8.5545426199e+00  2.8778484580e+00  2.4032853329e+01 Mg  3.2751600691e-01 0.0 -1.1475258127e-03 -2.0335085560e-03 -3.9606948166e-03\natom  5.7266306058e+00 -3.2895348455e-02  2.8061263571e+01 Mg  3.4544849691e-01 0.0  4.5169324029e-04  3.6075575576e-03 -1.5864129908e-03\natom  8.5392520532e+00  2.8147499403e+00  2.8079816296e+01 O  -3.3918509309e-01 0.0 -1.3914205913e-03  5.4136375419e-03 -1.6325564946e-03\natom  5.6672271072e+00 -4.5349644274e-04  3.2113651243e+01 O  -3.3827925309e-01 0.0  9.9803790371e-04  1.4199746252e-03 -3.9593588061e-03\natom  8.5240789331e+00  2.8472499392e+00  3.2121295714e+01 Mg  3.3725352691e-01 0.0  2.2865861579e-03  1.3261365988e-03 -8.4489122983e-04\natom  5.7102211891e+00  6.9350487138e-02  3.6055779847e+01 Mg  3.3510807691e-01 0.0  1.0644594220e-03 -5.3051200013e-03  5.2843091904e-03\natom  8.5728690880e+00  2.8684948245e+00  3.6135075150e+01 O  -3.4299170309e-01 0.0 -4.3872846630e-03 -1.1656609918e-03 -4.8656828059e-03\natom  5.7371879380e+00  4.6129042861e-02  4.0076453438e+01 O  -3.9788221309e-01 0.0 -3.3114177608e-03 -3.0296287632e-03  8.6234870246e-03\natom  8.5834812412e+00  2.8447404019e+00  4.0126675118e+01 Mg  4.0832424691e-01 0.0  7.9879788051e-04  4.3288928186e-03 -6.8813005029e-03\natom  5.6508474725e+00  5.6841195190e+00  1.9957112650e+01 Mg  3.8106308691e-01 0.0  1.2460022488e-02  7.2822710236e-03  6.6076576139e-03\natom  8.5304437758e+00  8.5410822907e+00  1.9935865799e+01 O  -4.0305741309e-01 0.0  4.7991789725e-04  2.8135116698e-04 -2.0126573567e-03\natom  5.7879031569e+00  5.7326144610e+00  2.4026476392e+01 O  -3.4413390309e-01 0.0 -1.0154980875e-02 -3.4071947080e-03  1.3157555649e-03\natom  8.5464426307e+00  8.6343636252e+00  2.4046176464e+01 Mg  3.2521947691e-01 0.0  1.6561594534e-03 -1.0388879679e-02 -6.3742265000e-03\natom  5.6687454264e+00  5.6702144427e+00  2.8026856045e+01 Mg  3.4330528691e-01 0.0  5.3066776630e-03  3.5113053416e-03  2.4467360259e-03\natom  8.5868794598e+00  8.6029190950e+00  2.8013642476e+01 O  -3.4127199309e-01 0.0 -2.6810864535e-03 -5.9285784990e-03  4.8405155774e-03\natom  5.7076773534e+00  5.7040195431e+00  3.2086884182e+01 O  -3.4210031309e-01 0.0 -3.6882838523e-03 -8.3201085882e-04 -1.3645445944e-03\natom  8.5121909503e+00  8.5749245808e+00  3.2085923445e+01 Mg  3.4022572691e-01 0.0 -6.1840301592e-04 -3.5576743194e-03 -8.1580976620e-04\natom  5.6737990450e+00  5.6834849679e+00  3.6113607995e+01 Mg  3.2978344691e-01 0.0  5.1873924784e-03  4.9300289750e-03  8.9495887122e-04\natom  8.5496816210e+00  8.5224576048e+00  3.6134618573e+01 O  -3.4210214309e-01 0.0 -3.2431382633e-03  7.3127786519e-03 -2.7819641893e-03\natom  5.7485300356e+00  5.7598987783e+00  4.0122308018e+01 O  -4.0327945309e-01 0.0 -7.9272275560e-03 -2.0867210949e-03  7.1985205285e-03\natom  8.5076717462e+00  8.6327708697e+00  4.0109705095e+01 Mg  4.0809962691e-01 0.0  3.6597563210e-03 -1.2271977803e-02 -3.4880668392e-03\natom  5.6262978154e+00  1.1364803422e+01  2.0053939451e+01 Mg  4.1050179691e-01 0.0  9.2436913160e-03  7.8536653517e-04 -2.4878873969e-03\natom  8.5694430526e+00  1.4285807004e+01  1.9966254048e+01 O  -4.0141569309e-01 0.0 -4.0368129461e-03 -6.1617959634e-03 -3.3616601908e-03\natom  5.7595619347e+00  1.1367509018e+01  2.4019197243e+01 O  -3.4034178309e-01 0.0 -7.9121758352e-03  7.4791198905e-03  4.4980858500e-03\natom  8.6402426761e+00  1.4213407349e+01  2.4022698489e+01 Mg  3.3253710691e-01 0.0 -5.7788840139e-03  4.7224851634e-03 -2.2766346825e-03\natom  5.7688028837e+00  1.1444386208e+01  2.8039071064e+01 Mg  3.4237749691e-01 0.0 -1.4524908629e-03 -5.4749095327e-03  2.2137327021e-03\natom  8.6276867886e+00  1.4261342063e+01  2.8083481080e+01 O  -3.4053683309e-01 0.0 -9.6496487267e-03 -1.1043272872e-03 -3.3504617954e-03\natom  5.7326383660e+00  1.1392347860e+01  3.2038261834e+01 O  -3.4275681309e-01 0.0 -6.5754063187e-03  1.8535015236e-03  3.6590546127e-03\natom  8.5508649864e+00  1.4256063605e+01  3.2082983579e+01 Mg  3.3544820691e-01 0.0 -3.6370784416e-05  6.1440733141e-04  4.1329670201e-04\natom  5.6943594717e+00  1.1414982695e+01  3.6186016569e+01 Mg  3.3765648691e-01 0.0 -1.4708816275e-03 -2.9768939285e-04 -1.0970656262e-02\natom  8.4990654238e+00  1.4288820966e+01  3.6099779982e+01 O  -3.4213831309e-01 0.0  3.4134165178e-03 -5.6271920446e-03  1.4624747906e-03\natom  5.6841036831e+00  1.1425128577e+01  4.0157937913e+01 O  -3.9635273309e-01 0.0 -7.6545810083e-04  1.4074909443e-03  5.9326700564e-03\natom  8.5717817775e+00  1.4184288410e+01  4.0146298675e+01 Mg  4.1709433691e-01 0.0  6.8813263464e-04  1.2222593819e-02 -8.5201098555e-03\natom  1.1321387912e+01 -6.3815838765e-02  1.9937198585e+01 Mg  4.2240814691e-01 0.0  3.8713082433e-03  5.7140888086e-03  9.0939916945e-03\natom  1.4233065867e+01  2.8215908617e+00  2.0046632598e+01 O  -3.9829392309e-01 0.0  3.2073764454e-03  2.3584443842e-04 -5.7333233071e-03\natom  1.1355974565e+01 -4.8669987323e-02  2.4061035625e+01 O  -3.4382431309e-01 0.0  7.5647989524e-03  6.0515637622e-03  5.7408477516e-04\natom  1.4227998604e+01  2.8551132969e+00  2.4021939424e+01 Mg  3.3815476691e-01 0.0 -1.8020777644e-03 -3.6403576849e-04 -1.2389822535e-03\natom  1.1340210131e+01  8.9429865116e-02  2.8093962426e+01 Mg  3.3223379691e-01 0.0  5.5251551426e-03 -1.2043094291e-02 -1.1713147971e-03\natom  1.4258451708e+01  2.8333505321e+00  2.8097419396e+01 O  -3.3873874309e-01 0.0 -9.5116304775e-05  3.5705914328e-03 -7.2594078687e-03\natom  1.1357540978e+01 -1.4658245446e-02  3.2058060021e+01 O  -3.4255313309e-01 0.0  1.6334041831e-03  3.8161776854e-03  4.6767756851e-03\natom  1.4241207940e+01  2.8760963607e+00  3.2045554703e+01 Mg  3.4254151691e-01 0.0 -4.7591344869e-04 -8.4925940818e-03  8.9199316546e-03\natom  1.1427255294e+01 -1.3181708044e-02  3.6114192865e+01 Mg  3.3172484691e-01 0.0  4.8358799759e-04  2.5723342005e-03 -9.2513022761e-04\natom  1.4233852163e+01  2.8561311033e+00  3.6173650051e+01 O  -3.4621337309e-01 0.0  3.0329054186e-03 -6.3194232250e-04 -7.2114006769e-03\natom  1.1407914799e+01  4.1238696564e-02  4.0103278893e+01 O  -4.0106318309e-01 0.0  5.6119781441e-04 -7.9381353862e-03  1.0875913704e-02\natom  1.4228098873e+01  2.8619523475e+00  4.0188221830e+01 Mg  4.0601536691e-01 0.0  1.2737057823e-03  8.4808304223e-04 -9.3423238335e-03\natom  1.1415910778e+01  5.7513780038e+00  2.0008078806e+01 Mg  4.1826656691e-01 0.0 -5.4820774124e-03 -5.3337781531e-03  3.5315020914e-03\natom  1.4251548161e+01  8.5094875083e+00  1.9994033587e+01 O  -3.9992276309e-01 0.0  7.8874434953e-04  2.8245159249e-03 -3.8622252785e-03\natom  1.1434610107e+01  5.7176934491e+00  2.4012970293e+01 O  -3.4206820309e-01 0.0 -8.7577002452e-04 -3.0935789014e-03  6.4963084417e-03\natom  1.4174570154e+01  8.5336356931e+00  2.4039633892e+01 Mg  3.3319389691e-01 0.0  8.6178955344e-03  4.0841149831e-03 -2.7410972227e-03\natom  1.1391195750e+01  5.6586663839e+00  2.8074331896e+01 Mg  3.4530615691e-01 0.0 -1.3813805699e-03  5.6552598595e-03 -1.7426376089e-03\natom  1.4249291772e+01  8.5802528144e+00  2.8041856633e+01 O  -3.3976763309e-01 0.0  2.6008141558e-04 -3.8362660030e-03  4.6537004423e-03\natom  1.1324580963e+01  5.6740125463e+00  3.2073703626e+01 O  -3.4024649309e-01 0.0  7.0883018684e-03  4.1773335030e-03 -2.0060875148e-03\natom  1.4237995784e+01  8.5787983112e+00  3.2074726988e+01 Mg  3.4460698691e-01 0.0 -3.4081504151e-03 -5.0498002485e-03  1.9680640678e-03\natom  1.1428048828e+01  5.7174093099e+00  3.6088876036e+01 Mg  3.2845077691e-01 0.0 -2.4642190638e-03 -4.1682502592e-03  4.6258161743e-03\natom  1.4167519379e+01  8.5410350664e+00  3.6052787693e+01 O  -3.4366199309e-01 0.0  7.0461274266e-03  1.6478002548e-03  3.8794726545e-03\natom  1.1406861447e+01  5.6928990158e+00  4.0157307009e+01 O  -4.0356376309e-01 0.0 -2.3119822138e-03  4.7411996282e-03  7.2289518021e-03\natom  1.4202046903e+01  8.5356681123e+00  4.0175154791e+01 Mg  4.1601304691e-01 0.0 -2.8789107952e-06 -2.5484276730e-03 -9.8016023923e-03\natom  1.1404664224e+01  1.1361526334e+01  1.9990680628e+01 Mg  4.1309928691e-01 0.0 -3.2580359488e-03  1.1414614348e-03  7.2502178575e-04\natom  1.4214484096e+01  1.4214581814e+01  1.9975340172e+01 O  -3.9938446309e-01 0.0  4.8962223790e-03  3.2489122975e-03 -4.0214277351e-03\natom  1.1337652727e+01  1.1375496153e+01  2.3917338196e+01 O  -3.4314813309e-01 0.0  8.9010084204e-03  2.0158402891e-03  1.1860377451e-02\natom  1.4245428889e+01  1.4289197758e+01  2.4035840022e+01 Mg  3.3774344691e-01 0.0 -3.4387105653e-03 -6.4517323473e-03 -1.9381412652e-03\natom  1.1427373742e+01  1.1343505586e+01  2.8133746204e+01 Mg  3.4078052691e-01 0.0 -1.9383553541e-03  8.4133662751e-03 -8.1545527139e-03\natom  1.4219384836e+01  1.4285659643e+01  2.8112587188e+01 O  -3.4176990309e-01 0.0  6.0052636293e-03 -4.0393501639e-03 -6.4556694123e-03\natom  1.1342017351e+01  1.1440799924e+01  3.2063371077e+01 O  -3.3878387309e-01 0.0  3.7149933457e-03 -7.2135614358e-03  3.7698985658e-03\natom  1.4237121426e+01  1.4167160501e+01  3.2088511878e+01 Mg  3.3437157691e-01 0.0  4.5889030408e-04  1.1378229590e-02  1.2199892071e-03\natom  1.1343983970e+01  1.1390400365e+01  3.6081848523e+01 Mg  3.3567150691e-01 0.0  6.0604595227e-03  2.2720858390e-03  9.6463227801e-04\natom  1.4284327840e+01  1.4246131186e+01  3.6031238127e+01 O  -3.4530927309e-01 0.0 -5.8113649786e-03 -2.7824303481e-03  1.0853846765e-02\natom  1.1370847276e+01  1.1441095307e+01  4.0139155303e+01 O  -3.9723169309e-01 0.0  1.5890854577e-03 -2.6412696142e-03  6.4939619004e-03\natom  1.4283603451e+01  1.4219368887e+01  4.0194813799e+01 Mg  4.2209049691e-01 0.0 -2.0259368829e-03  4.1718768133e-03 -1.1641617372e-02\natom  2.7412733120e+00  2.8943239017e+00  1.5016201368e+01 Au  5.8280836909e-02 0.0  2.3083617279e-04 -1.1615567057e-03  2.8243282676e-02\natom  2.5030430589e+00  2.5625885515e+00  1.0317027159e+01 Au -8.2510073091e-02 0.0 -1.0643923214e-04  1.2618052007e-04 -5.7406576890e-03\nenergy -5.4268556032e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -5.6423816513e-03 -3.9621733625e-02  2.0027585105e+01 Mg  4.0839800936e-01 0.0 -6.7848469220e-04  2.5225373284e-03  4.4768301219e-03\natom  2.8519979324e+00  2.8469753053e+00  2.0009577132e+01 O  -3.9756827064e-01 0.0 -3.9769177316e-05  2.9048254071e-03 -4.4848278405e-03\natom -2.5676368411e-02 -4.4176483483e-02  2.4039607436e+01 O  -3.4307349064e-01 0.0  2.3168429984e-03  6.8928511601e-03 -3.0894936041e-03\natom  2.8464880583e+00  2.9069540176e+00  2.3994580935e+01 Mg  3.3704282936e-01 0.0 -2.7542175494e-03 -9.5405038066e-03  6.5596498687e-03\natom -2.5145884532e-02  3.6822973847e-02  2.8071061763e+01 Mg  3.4460917936e-01 0.0  1.4211642430e-03 -5.9632767913e-03 -2.4603023711e-03\natom  2.8558264983e+00  2.8617947632e+00  2.8017409702e+01 O  -3.4110839064e-01 0.0 -1.2584899110e-03 -5.9983086905e-04  1.2368478690e-03\natom -4.0410599739e-02 -6.3216814524e-03  3.2094525308e+01 O  -3.3802688064e-01 0.0  4.3152291319e-03  2.0881970358e-03 -5.0357240273e-03\natom  2.8032912277e+00  2.7911059344e+00  3.2103238513e+01 Mg  3.4130967936e-01 0.0  3.9639070097e-03  3.9306952306e-03 -2.2714386789e-04\natom  2.9321177412e-03 -1.7187057866e-02  3.6075804027e+01 Mg  3.3337860936e-01 0.0 -4.6335770886e-03 -3.0830847972e-03  9.6038953502e-03\natom  2.8205166848e+00  2.8205429709e+00  3.6151638201e+01 O  -3.4038366064e-01 0.0  2.6449743240e-03  1.8731188258e-03 -4.3289509115e-03\natom  3.3841685435e-02  3.8922478317e-02  4.0139763662e+01 O  -4.0298788064e-01 0.0 -1.6432510641e-03 -2.2309075916e-03  6.7147108186e-03\natom  2.8598381221e+00  2.8634634480e+00  4.0226739699e+01 Mg  4.1863357936e-01 0.0 -2.5981152915e-03 -3.4272358667e-03 -7.8384012819e-03\natom  1.5973929371e-02  5.6700833902e+00  2.0002673037e+01 Mg  4.1690352936e-01 0.0 -2.9241941439e-03  6.9357910554e-04  3.7859351505e-03\natom  2.8880554349e+00  8.5276168780e+00  2.0050823576e+01 O  -3.8927609064e-01 0.0 -8.6689649781e-03 -1.6286248286e-03 -6.6303984666e-03\natom -8.9569251305e-02  5.6650896192e+00  2.4063931309e+01 O  -3.3788205064e-01 0.0  1.2036506844e-02  5.8671319500e-03 -4.6386297779e-03\natom  2.8530052697e+00  8.4996210033e+00  2.4039096095e+01 Mg  3.4208146936e-01 0.0  1.0648318928e-03  6.2938918662e-03  2.2870631285e-03\natom -1.6074198232e-03  5.7492645910e+00  2.8081046924e+01 Mg  3.4059428936e-01 0.0  1.1466328414e-03 -5.1093029045e-03  4.0325158040e-03\natom  2.8730045611e+00  8.5227007181e+00  2.8124450982e+01 O  -3.3842823064e-01 0.0 -3.8135096114e-03  4.6550727118e-04 -9.0011261510e-03\natom  3.9473201162e-02  5.6691962206e+00  3.2146077410e+01 O  -3.3949526064e-01 0.0 -3.3138959026e-03  1.0246399791e-03 -8.8440437843e-03\natom  2.8959513148e+00  8.5267050286e+00  3.2141586118e+01 Mg  3.4815070936e-01 0.0 -3.3693679659e-03  1.7427134616e-03 -1.0373597492e-04\natom  3.0124915669e-02  5.6464640263e+00  3.6095364372e+01 Mg  3.3121264936e-01 0.0 -6.3146274354e-03  4.1999364795e-03  6.4593640284e-03\natom  2.8263230191e+00  8.5467319855e+00  3.6169685462e+01 O  -3.4136434064e-01 0.0  6.9510185558e-03 -5.8549250905e-03 -1.1248151157e-02\natom -5.4459351861e-02  5.7093714171e+00  4.0167946922e+01 O  -3.9953441064e-01 0.0  4.9910968439e-03 -2.5896071043e-03  5.7539635416e-03\natom  2.8513535169e+00  8.4541631911e+00  4.0134072204e+01 Mg  4.0540499936e-01 0.0 -2.1360478203e-03  1.1883905202e-02 -3.8648273895e-03\natom  3.3699275685e-02  1.1413047011e+01  2.0087962644e+01 Mg  3.9469086936e-01 0.0 -1.8655429526e-03  4.5580585441e-04 -3.7144393962e-04\natom  2.8531440323e+00  1.4318755794e+01  1.9975667208e+01 O  -3.9078135064e-01 0.0 -1.2148293208e-03 -5.8922888487e-03 -4.6561887204e-03\natom  3.7198594681e-02  1.1497444706e+01  2.4000763948e+01 O  -3.4085979064e-01 0.0 -1.5537649932e-03 -1.3565412485e-02  1.7081467822e-03\natom  2.9200831157e+00  1.4249867515e+01  2.4067513379e+01 Mg  3.2949704936e-01 0.0 -6.8916333081e-03  8.6112048108e-04  9.6677818664e-04\natom -6.7422210739e-03  1.1357414007e+01  2.8008516859e+01 Mg  3.4599557936e-01 0.0 -1.0745221894e-03  8.7412684630e-03  7.5316814282e-03\natom  2.8784336494e+00  1.4213524418e+01  2.8091537076e+01 O  -3.4246296064e-01 0.0 -2.5324530316e-03  1.5756239112e-03 -2.4513914027e-03\natom -9.3927526352e-02  1.1470294710e+01  3.2140510542e+01 O  -3.4201428064e-01 0.0  1.3447829234e-02 -9.4588585514e-03 -1.0788059843e-02\natom  2.8433452739e+00  1.4257517522e+01  3.2074185015e+01 Mg  3.4461086936e-01 0.0  1.2549093861e-03 -3.2077710604e-03  4.3083346333e-03\natom  8.6251213722e-02  1.1349530410e+01  3.6041088626e+01 Mg  3.2763768936e-01 0.0 -1.2654531026e-02  3.5430990390e-03  1.2788875688e-02\natom  2.8455346160e+00  1.4202133490e+01  3.6185296867e+01 O  -3.4318984064e-01 0.0  3.0453490012e-03  4.5806579062e-03 -1.3606131291e-02\natom -3.0694516877e-02  1.1395169901e+01  4.0100575753e+01 O  -4.0431566064e-01 0.0  2.4649685426e-03 -7.8923342393e-04  8.5348374721e-03\natom  2.8283024692e+00  1.4221207609e+01  4.0044088517e+01 Mg  3.9954363936e-01 0.0  1.1879810164e-04 -2.6919776142e-03  3.6434838249e-03\natom  5.6921067860e+00  4.2804825875e-02  2.0010640216e+01 Mg  4.0970129936e-01 0.0  2.3027983193e-03 -8.7889040861e-03  2.6992155037e-03\natom  8.5572251048e+00  2.8653353917e+00  1.9997482677e+01 O  -3.9665991064e-01 0.0 -2.5468509780e-03 -3.0283612310e-03 -5.4368189798e-03\natom  5.6674942199e+00 -4.0228997071e-02  2.4097149234e+01 O  -3.3979983064e-01 0.0  2.2366285486e-03  7.7157813395e-03 -8.9951414020e-03\natom  8.4860911888e+00  2.8784549655e+00  2.3966654375e+01 Mg  3.3500838936e-01 0.0  1.0557835645e-02 -4.3621175273e-03  9.4315374798e-03\natom  5.7209762055e+00 -1.2758919649e-02  2.8028970101e+01 Mg  3.4055498936e-01 0.0 -1.5476884965e-03  3.8209370561e-04  8.2189123159e-03\natom  8.5862368396e+00  2.8137288079e+00  2.8043703689e+01 O  -3.4280642064e-01 0.0 -5.5105942192e-03  2.2932037789e-03 -1.6551330836e-03\natom  5.6587607946e+00  1.0458102669e-02  3.2179232162e+01 O  -3.4095388064e-01 0.0  8.4014173028e-04 -5.8974741531e-04 -9.0372708503e-03\natom  8.4955256647e+00  2.8711887612e+00  3.2125682221e+01 Mg  3.3951362936e-01 0.0  5.8676938503e-03 -8.5865097459e-04 -3.7112641457e-03\natom  5.6795493867e+00  3.6691297740e-03  3.6164919781e+01 Mg  3.3236784936e-01 0.0  6.3679001373e-04 -5.7816497662e-03  1.5422877846e-04\natom  8.5152656668e+00  2.8044817929e+00  3.6093466842e+01 O  -3.4015640064e-01 0.0  1.7254248277e-03  2.5885514692e-03  2.5053616028e-03\natom  5.7108669274e+00  6.5681584131e-03  4.0174249858e+01 O  -4.0081895064e-01 0.0  1.3665247341e-03  9.8557599260e-04  3.5021093102e-03\natom  8.5540953784e+00  2.8240781569e+00  4.0127303414e+01 Mg  4.0988195936e-01 0.0  1.2531850546e-04  1.6905017000e-03 -1.7109838587e-03\natom  5.6916849614e+00  5.6837343928e+00  1.9990988672e+01 Mg  4.0697344936e-01 0.0  5.8111960239e-03  5.0857869446e-03  1.2638163021e-03\natom  8.5243253155e+00  8.5854711037e+00  2.0028062904e+01 O  -3.9681472064e-01 0.0  1.4352698142e-03 -1.2741191081e-02 -2.0812580263e-03\natom  5.7599033704e+00  5.6923293390e+00  2.4012433914e+01 O  -3.3766845064e-01 0.0 -1.1211362323e-02 -1.2907623381e-03  1.0969852170e-03\natom  8.4979072675e+00  8.5013979315e+00  2.3978779746e+01 Mg  3.3007684936e-01 0.0  1.0486212200e-02  9.3722027074e-03  5.6968490830e-03\natom  5.7121759973e+00  5.6574349439e+00  2.8049951067e+01 Mg  3.4152478936e-01 0.0  4.4409542820e-03  1.6979035331e-03  6.7185296729e-03\natom  8.5485651898e+00  8.5764893495e+00  2.8119262947e+01 O  -3.4394094064e-01 0.0 -1.7636253781e-03 -3.1673886902e-03 -7.8569039805e-03\natom  5.7224642136e+00  5.6977003182e+00  3.2076271405e+01 O  -3.4061469064e-01 0.0 -5.6338011031e-03 -1.0650473148e-03  1.5600605427e-03\natom  8.5044429982e+00  8.6245124080e+00  3.2119925341e+01 Mg  3.3572769936e-01 0.0  9.3927577476e-03 -8.0948338379e-03 -9.7361992018e-04\natom  5.6745353768e+00  5.6068590924e+00  3.6083153813e+01 Mg  3.3919772936e-01 0.0  2.7540053220e-03  7.8547983822e-03  6.6273876848e-03\natom  8.5938788537e+00  8.5303538627e+00  3.6138911596e+01 O  -3.4201216064e-01 0.0 -3.9900946738e-03 -3.0063861467e-03 -3.0070606216e-03\natom  5.6700543829e+00  5.7507927179e+00  4.0174671833e+01 O  -4.0069094064e-01 0.0  1.9625930173e-03 -9.9619021199e-03  2.4437310149e-03\natom  8.5617251093e+00  8.5373206588e+00  4.0109434089e+01 Mg  4.0701607936e-01 0.0 -1.8402867990e-03  2.6261578321e-03 -1.1875897245e-03\natom  5.6660624502e+00  1.1353284030e+01  2.0045877766e+01 Mg  3.0445928936e-01 0.0  9.8301919976e-03  5.8659451163e-03 -9.3629813219e-04\natom  8.5473753806e+00  1.4178334205e+01  2.0030605700e+01 O  -3.9574170064e-01 0.0 -2.2452067768e-03  1.3393738898e-02 -1.5997931500e-03\natom  5.6939735140e+00  1.1390950842e+01  2.4024075495e+01 O  -3.4033966064e-01 0.0 -3.6077118049e-03 -1.8733271408e-03  3.0773730102e-03\natom  8.5339274101e+00  1.4324250569e+01  2.4028769933e+01 Mg  3.3019110936e-01 0.0  3.3878473986e-03 -1.1199450332e-02 -1.2699617954e-03\natom  5.7088891402e+00  1.1331480844e+01  2.8029441625e+01 Mg  3.3938908936e-01 0.0  1.8993093642e-03  5.5347629650e-03  5.7419825772e-03\natom  8.5372381723e+00  1.4256062698e+01  2.8107314058e+01 O  -3.3954611064e-01 0.0 -1.6882187343e-03  4.1491126386e-04 -5.0259889930e-03\natom  5.7516017852e+00  1.1413142631e+01  3.2129833912e+01 O  -3.3962593064e-01 0.0 -8.0690417876e-03 -2.1485599147e-03 -3.1910373563e-03\natom  8.5573949912e+00  1.4247642136e+01  3.2108733326e+01 Mg  3.4113108936e-01 0.0  1.9643487839e-05  2.1144044159e-03  2.8482762519e-03\natom  5.7999526356e+00  1.1353861757e+01  3.6122537574e+01 Mg  3.3011140936e-01 0.0 -8.0507385520e-03  2.7924528489e-03  7.1630797233e-03\natom  8.5773719460e+00  1.4170848925e+01  3.6115099253e+01 O  -3.4244924064e-01 0.0 -3.0003290055e-03  9.2450039607e-03 -7.8021847293e-04\natom  5.6855522336e+00  1.1362658337e+01  4.0150663110e+01 O  -4.0579399064e-01 0.0  3.7557055558e-03  2.4979383001e-03  4.0975633586e-03\natom  8.5816476401e+00  1.4292107350e+01  4.0137497635e+01 Mg  4.1191774936e-01 0.0 -1.9502593132e-03 -5.9183722480e-03 -4.3123061350e-03\natom  1.1381379852e+01 -4.3875979257e-02  1.9973288194e+01 Mg  4.0873119936e-01 0.0 -1.4254261723e-03 -1.9634026188e-03  5.1609726496e-03\natom  1.4243381541e+01  2.8394102597e+00  1.9956403001e+01 O  -4.0026742064e-01 0.0  2.3221652459e-03 -1.4210087439e-03 -2.9015322458e-03\natom  1.1385582074e+01 -2.4729181054e-02  2.3998794741e+01 O  -3.4217641064e-01 0.0 -5.8682162873e-05  5.7847456832e-03 -6.5269708985e-04\natom  1.4247760829e+01  2.8574050054e+00  2.4055775629e+01 Mg  3.3370500936e-01 0.0 -4.1993505343e-03 -5.1385923393e-03  1.8235050140e-04\natom  1.1370909844e+01 -5.1737787390e-02  2.8059401927e+01 Mg  3.3796334936e-01 0.0  7.9005060747e-04  5.8771596828e-03  7.1839651880e-04\natom  1.4247168230e+01  2.8766710831e+00  2.8069870423e+01 O  -3.3947609064e-01 0.0  2.6024816000e-03 -1.0073607250e-03 -2.2141143810e-03\natom  1.1413575454e+01  2.2742814478e-02  3.2057048602e+01 O  -3.4066812064e-01 0.0 -3.5526868437e-03 -6.8250266173e-04  1.6834831695e-04\natom  1.4219432155e+01  2.8213252985e+00  3.2011056507e+01 Mg  3.4361109936e-01 0.0 -2.0124530264e-03  2.9247462497e-03  1.0378996691e-02\natom  1.1420576587e+01  3.1504075490e-02  3.6091261399e+01 Mg  3.3190930936e-01 0.0  6.0667561444e-04 -8.2612300086e-03  3.2720324672e-03\natom  1.4218032038e+01  2.7999636848e+00  3.6168173455e+01 O  -3.4237561064e-01 0.0  3.1361088615e-03  5.0049350556e-03 -9.0943276479e-03\natom  1.1432153501e+01  7.4964485105e-03  4.0139639980e+01 O  -4.0045846064e-01 0.0 -3.9402658146e-03  7.9327915969e-04  6.1092917231e-03\natom  1.4271580296e+01  2.8785963548e+00  4.0128529978e+01 Mg  4.0413030936e-01 0.0 -6.4979570095e-04 -4.9840633124e-03 -2.0421072044e-03\natom  1.1450134660e+01  5.5993784798e+00  2.0009375951e+01 Mg  4.0794188936e-01 0.0 -6.3159045156e-03  1.0157755486e-02  4.3968854561e-03\natom  1.4223886504e+01  8.5341055735e+00  2.0005159444e+01 O  -3.8871900064e-01 0.0  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7.5177966431e-03 -4.4706938318e-03\natom  1.4271633681e+01  8.5096310330e+00  3.6119290703e+01 O  -3.4581634064e-01 0.0 -2.1263292121e-03 -1.7996026053e-03 -2.4134031899e-03\natom  1.1356479632e+01  5.6490815047e+00  4.0204793215e+01 O  -4.0127089064e-01 0.0  2.0258171996e-03  3.5732684551e-03  1.9364470333e-03\natom  1.4249316263e+01  8.5456933543e+00  4.0160509339e+01 Mg  4.1171201936e-01 0.0  1.2708224811e-03  4.0737326675e-03 -8.5517971946e-03\natom  1.1418946358e+01  1.1373416679e+01  1.9990865027e+01 Mg  2.9537792936e-01 0.0 -9.5162304484e-03 -3.3877198349e-04  6.0737085404e-03\natom  1.4233521536e+01  1.4222288098e+01  1.9937169672e+01 O  -3.8820240064e-01 0.0  4.0165784951e-03  1.3009155764e-03 -4.5584062411e-03\natom  1.1362335515e+01  1.1417982597e+01  2.4050699466e+01 O  -3.4434120064e-01 0.0  5.2249062499e-03 -1.9894278258e-03 -2.3541080519e-03\natom  1.4217249389e+01  1.4265363306e+01  2.3976003511e+01 Mg  3.2762599936e-01 0.0 -4.1291094875e-04 -2.0985796053e-03  7.2485930940e-03\natom  1.1370374466e+01  1.1479490741e+01  2.8067802571e+01 Mg  3.3883388936e-01 0.0  1.0233596326e-03 -7.9457079893e-03 -7.6150626780e-04\natom  1.4215018775e+01  1.4271612365e+01  2.8001125347e+01 O  -3.4214908064e-01 0.0  3.5341821754e-03 -5.3703936119e-04  2.9732439527e-03\natom  1.1423661470e+01  1.1434073614e+01  3.2109464895e+01 O  -3.4129078064e-01 0.0 -4.2118092374e-03 -2.2960798105e-03 -5.2601618845e-03\natom  1.4241965474e+01  1.4227754300e+01  3.2091982549e+01 Mg  3.3340386936e-01 0.0 -2.3879876093e-03  1.0584480655e-03  3.6516161995e-03\natom  1.1382548232e+01  1.1387498275e+01  3.6117705979e+01 Mg  3.2878331936e-01 0.0  9.8551903301e-03  8.2864480380e-04  2.6308909416e-03\natom  1.4221303437e+01  1.4251668820e+01  3.6088318283e+01 O  -3.4706009064e-01 0.0  3.0250942607e-03  1.6769673586e-03  2.1118299333e-04\natom  1.1438738913e+01  1.1444905826e+01  4.0149725598e+01 O  -4.0159445064e-01 0.0 -4.7531872367e-03 -5.6278083371e-03  6.9546053436e-03\natom  1.4234942723e+01  1.4256823993e+01  4.0178995867e+01 Mg  4.1181510936e-01 0.0  4.3240215330e-03 -9.6043765039e-04 -1.1880266899e-02\natom  1.1160619266e+01  1.1332088655e+01  1.4671772936e+01 Au  1.0078373936e-01 0.0 -1.9455012052e-02  3.4464754125e-04 -2.3923975723e-03\natom  6.0728622519e+00  1.1422307783e+01  1.4553194898e+01 Au  8.9384499364e-02 0.0  1.9854897683e-02  8.5511329976e-05  4.1442057105e-04\nenergy -5.4268534403e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom -1.2940465625e-02  2.9923357495e-02  2.0044169189e+01 Mg  3.7332586782e-01 0.0 -6.2044932776e-03 -1.3025562594e-02 -9.6093572991e-03\natom  2.8207238932e+00  2.8269751446e+00  2.0051021374e+01 O  -3.3050240218e-01 0.0  1.2877737863e-03  3.8505824883e-03  2.3668689500e-02\natom  6.3186673395e-02 -4.1057604123e-02  2.4043797658e+01 O  -3.4055572218e-01 0.0 -4.6205824266e-03  7.9840789696e-03  7.8265664627e-03\natom  2.8707637240e+00  2.8963002527e+00  2.4018346998e+01 Mg  3.4095046782e-01 0.0 -8.2698547806e-04 -7.2861012238e-03  2.6637575501e-03\natom -2.7583990105e-02  1.0937469460e-02  2.7967248003e+01 Mg  3.4425490782e-01 0.0  2.8255253498e-03 -4.4723006143e-03 -3.2152921306e-03\natom  2.9040940874e+00  2.8672258546e+00  2.8079289271e+01 O  -3.4080959218e-01 0.0 -7.9540080861e-03 -7.1435173056e-04  6.7143790815e-03\natom  6.0006925960e-03 -1.3909724982e-02  3.2074803655e+01 O  -3.1393052218e-01 0.0  1.9211481939e-03  2.5852138196e-03  2.1877702757e-02\natom  2.8294863637e+00  2.8526684450e+00  3.2073572876e+01 Mg  3.3502280782e-01 0.0 -3.9126422750e-03  5.2122217663e-04 -1.1674834486e-02\natom  4.1213166366e-02 -2.0511029188e-02  3.6162002781e+01 Al  4.0067587782e-01 0.0 -9.2499597834e-03  4.5159825253e-03  1.1072907689e-02\natom  2.7950634741e+00  2.8641907090e+00  3.6168989930e+01 O  -2.8754596218e-01 0.0  6.9410308774e-03 -5.0307934776e-03 -1.3350443819e-02\natom  1.0066438060e-02 -8.4434846897e-03  4.0162768922e+01 O  -3.6395788218e-01 0.0 -1.1018773378e-03 -1.6037163865e-03 -2.4815918287e-02\natom  2.8907980132e+00  2.8190558888e+00  4.0214734213e+01 Mg  3.7323886782e-01 0.0 -6.1549809820e-03  4.7589438040e-03  1.1963939704e-02\natom -5.3944212557e-02  5.6628190945e+00  2.0045297620e+01 Mg  3.6175331782e-01 0.0 -3.2697749343e-03  1.0077053578e-02 -1.0789588350e-02\natom  2.8286234959e+00  8.5424820863e+00  1.9935361394e+01 O  -3.9863669218e-01 0.0  2.1565902121e-03 -3.3696614036e-03  1.1989940709e-02\natom -4.1018581281e-02  5.7585523108e+00  2.4068833277e+01 O  -3.4132938218e-01 0.0  8.4046241632e-03 -8.6197034089e-03  4.6203137506e-03\natom  2.8928384070e+00  8.5360880094e+00  2.4084929661e+01 Mg  3.3546380782e-01 0.0 -2.5797267277e-03  4.8452075017e-03 -1.3897146192e-02\natom  4.3339391562e-02  5.7248344969e+00  2.8089412854e+01 Mg  3.3369766782e-01 0.0 -6.3415962121e-03 -2.6411006507e-03 -9.8369287875e-03\natom  2.7577023252e+00  8.5476419831e+00  2.8061124299e+01 O  -3.4007333218e-01 0.0  1.4983352862e-02 -3.9059181425e-03  9.9483266598e-03\natom -1.0663326911e-02  5.7474331064e+00  3.2096747474e+01 O  -3.4370233218e-01 0.0  7.7368316434e-03 -8.0014195522e-03  5.9758957029e-03\natom  2.8428793998e+00  8.5526494357e+00  3.2068888812e+01 Mg  3.3442021782e-01 0.0 -2.2841340789e-03  4.0626995123e-03 -6.1342225919e-03\natom  8.4224860545e-02  5.7077508259e+00  3.6110575627e+01 Mg  3.1913802782e-01 0.0 -1.2663333167e-02 -8.1464048410e-05  9.2386101322e-03\natom  2.8669854815e+00  8.5808066175e+00  3.6114185722e+01 O  -3.1897031218e-01 0.0  8.1636807582e-03 -1.3603384265e-02 -8.9348901930e-03\natom -1.9436719964e-02  5.7282962670e+00  4.0088563880e+01 O  -4.0959887218e-01 0.0  6.0504675933e-03 -2.6467050597e-03 -2.1768070226e-03\natom  2.8737270790e+00  8.5768082219e+00  4.0105135586e+01 Mg  3.8074313782e-01 0.0 -6.5409866932e-03 -1.3391894286e-03  1.3768770674e-02\natom -1.9779440669e-02  1.1351642501e+01  2.0006676686e+01 Mg  4.2247857782e-01 0.0  1.5398227123e-04  4.0041086704e-03 -4.9046482109e-03\natom  2.8496342442e+00  1.4205691466e+01  2.0008666567e+01 O  -3.9999902218e-01 0.0 -9.8328364589e-05  2.5955805774e-03  2.5449599077e-03\natom  4.4595983756e-02  1.1451490142e+01  2.4021442748e+01 O  -3.4254298218e-01 0.0 -4.8688260695e-03 -8.7617837057e-03  1.0197571672e-02\natom  2.8246652192e+00  1.4170285692e+01  2.4019278728e+01 Mg  3.2773579782e-01 0.0  9.1323550029e-03  4.4513963871e-03 -8.3940308167e-03\natom  6.5741488445e-03  1.1333530819e+01  2.8070240734e+01 Mg  3.3685817782e-01 0.0 -2.3854168853e-03  8.6012178349e-03 -6.9468704736e-03\natom  2.9256235655e+00  1.4164105627e+01  2.8051563948e+01 O  -3.4389345218e-01 0.0 -7.3514091698e-03  8.3952438672e-03  1.1173514720e-02\natom -6.7836627648e-03  1.1361634937e+01  3.2114968325e+01 O  -3.4606056218e-01 0.0  1.4619905648e-04  5.7697741211e-03  4.8719555828e-03\natom  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-5.0427338006e-03  2.4010148895e+01 O  -3.4543169218e-01 0.0 -9.3901493455e-03  2.2629892240e-03  8.0909892044e-03\natom  8.5020311031e+00  2.8330936427e+00  2.3979236851e+01 Mg  3.2652145782e-01 0.0  7.6818654807e-03 -1.3557502166e-03 -4.7803925318e-03\natom  5.6517755548e+00 -9.8944918928e-03  2.8059761334e+01 Mg  3.3167761782e-01 0.0  3.8844102437e-03 -1.1745301770e-03 -1.2693329480e-02\natom  8.4596549238e+00  2.8198841368e+00  2.8125265529e+01 O  -3.4444039218e-01 0.0  7.9874747340e-03  3.9576295794e-03  2.6592216302e-03\natom  5.6825399537e+00  3.2735477636e-02  3.2082982238e+01 O  -3.4041302218e-01 0.0 -3.9026488634e-03 -1.8635120826e-03  1.0554019559e-02\natom  8.4337287525e+00  2.8500938634e+00  3.2131522816e+01 Mg  3.2872375782e-01 0.0  2.0173938842e-02 -2.3897772673e-03 -1.5596375433e-02\natom  5.6883669616e+00  2.5362673897e-02  3.6038182058e+01 Mg  3.2508615782e-01 0.0  3.2159032022e-03 -5.9458783659e-03  1.5912167751e-02\natom  8.5650359471e+00  2.8535883447e+00  3.6109499428e+01 O  -3.1076984218e-01 0.0 -1.8704495482e-02  1.2260643965e-02 -4.1334519793e-03\natom  5.6243097481e+00  3.0886494140e-02  4.0162174168e+01 O  -4.0604348218e-01 0.0  8.2891123446e-03 -2.3427586808e-03 -8.4857844639e-03\natom  8.5139246983e+00  2.8835218500e+00  4.0164644966e+01 Mg  3.8600528782e-01 0.0  6.9268261079e-03 -6.7682222586e-03  1.0366488747e-02\natom  5.6514284877e+00  5.6721545677e+00  2.0079084447e+01 Mg  3.5885567782e-01 0.0  1.0882000993e-02  9.5288049766e-03 -1.4164609376e-02\natom  8.5511785864e+00  8.5527384985e+00  2.0059462005e+01 O  -3.9932865218e-01 0.0 -1.9746313603e-03 -1.8670900181e-04 -1.3820489691e-03\natom  5.7390599573e+00  5.6634964101e+00  2.4054133495e+01 O  -3.3858014218e-01 0.0 -7.2503241445e-03  3.7466895626e-03  8.1194106023e-03\natom  8.5512047591e+00  8.6052832745e+00  2.4042670512e+01 Mg  3.2968576782e-01 0.0  4.7129314237e-03 -5.1543137202e-03 -1.0620382179e-02\natom  5.7646447874e+00  5.6621042490e+00  2.8047095615e+01 Mg  3.4512162782e-01 0.0 -1.2384042256e-03  2.0816538108e-03 -1.0412830767e-02\natom  8.6316486559e+00  8.5842733576e+00  2.8133094891e+01 O  -3.4083900218e-01 0.0 -1.1288178315e-02 -6.0342972704e-03  2.3619364702e-03\natom  5.7318614052e+00  5.6812087740e+00  3.2099591436e+01 O  -3.0713834218e-01 0.0 -6.5880944345e-03  2.2898042956e-03  2.1844740133e-02\natom  8.5306858875e+00  8.5332942196e+00  3.2112766568e+01 Mg  3.2850845782e-01 0.0  7.2290498831e-03  2.1387339985e-03 -9.9390128088e-03\natom  5.7113415887e+00  5.6068348283e+00  3.6082471811e+01 Al  3.9465442782e-01 0.0  2.2328684082e-03  8.7290674840e-03  1.3953855596e-02\natom  8.5520434195e+00  8.5527944155e+00  3.6140121040e+01 O  -2.9303252218e-01 0.0  2.8317384546e-03 -5.4636694465e-04 -7.8279885308e-03\natom  5.7500507926e+00  5.6824965656e+00  4.0161851139e+01 O  -3.6415863218e-01 0.0 -4.0347824574e-03 -9.4381293997e-04 -2.2570569399e-02\natom  8.5447288949e+00  8.4742747700e+00  4.0118025691e+01 Mg  3.7243384782e-01 0.0  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-6.9898858741e-04  9.9036025110e-03\natom  8.5222905531e+00  1.4257552671e+01  3.2076680871e+01 Mg  3.3598320782e-01 0.0  2.8815725255e-03  1.3623986241e-03 -3.8020351617e-03\natom  5.5603184861e+00  1.1408916750e+01  3.6132464210e+01 Mg  3.2328293782e-01 0.0  1.5803931079e-02 -5.5310059692e-04  5.0434862412e-03\natom  8.5822073013e+00  1.4242845199e+01  3.6163088127e+01 O  -3.2177352218e-01 0.0  4.5768709652e-03 -1.1344346607e-02 -1.0728629093e-02\natom  5.7071761980e+00  1.1334248971e+01  4.0175810658e+01 O  -4.0761226218e-01 0.0  2.1419635944e-03  4.9878780416e-03 -8.8222595220e-03\natom  8.6166458189e+00  1.4271810805e+01  4.0112930252e+01 Mg  3.8607420782e-01 0.0 -1.1912158976e-02 -1.5769537106e-03  1.1928988620e-02\natom  1.1352564101e+01  6.2287069338e-03  1.9975201088e+01 Mg  4.2492341782e-01 0.0  2.8621428824e-03 -2.4083939993e-03 -1.2302958593e-03\natom  1.4278052721e+01  2.8253666476e+00  1.9999181843e+01 O  -3.9699204218e-01 0.0 -1.4847379959e-03  9.7848839987e-04  6.1735262634e-03\natom  1.1365481758e+01 -1.8505935428e-02  2.3971135747e+01 O  -3.4168575218e-01 0.0  5.8893704460e-03  2.3509725778e-03  1.8923674957e-02\natom  1.4233286171e+01  2.7829233075e+00  2.4046007919e+01 Mg  3.3489673782e-01 0.0 -3.2189207465e-03  6.2948815707e-03 -1.0714207987e-02\natom  1.1347327803e+01 -3.2591348235e-03  2.8073955273e+01 Mg  3.4316321782e-01 0.0  1.0054024048e-03  2.2632889605e-03 -6.2913401701e-03\natom  1.4220352470e+01  2.8769502712e+00  2.8085343461e+01 O  -3.4076634218e-01 0.0  5.2435437569e-03 -6.5181318384e-03  3.4169802842e-03\natom  1.1389758123e+01  1.0114420093e-01  3.2147836254e+01 O  -3.4738884218e-01 0.0 -1.6678112076e-03 -1.0904525849e-02  2.1806987170e-03\natom  1.4227567482e+01  2.8507116526e+00  3.2083107337e+01 Mg  3.3066091782e-01 0.0 -4.3159107539e-03  4.1195153850e-03 -3.3487951814e-03\natom  1.1329398819e+01 -1.5662823781e-02  3.6171572977e+01 Mg  3.1652120782e-01 0.0  7.5406330206e-03  5.1010758146e-03 -2.0269547664e-03\natom  1.4239733368e+01  2.8718002198e+00  3.6130411457e+01 O  -3.2267760218e-01 0.0  1.4964186722e-02 -1.5956200141e-02 -6.0438601194e-03\natom  1.1408850327e+01 -3.6723045136e-02  4.0108866208e+01 O  -4.0306616218e-01 0.0 -2.2505809484e-03  1.7382621667e-03 -1.3033406110e-03\natom  1.4252386841e+01  2.7910972227e+00  4.0225472581e+01 Mg  3.8857582782e-01 0.0 -3.3410685458e-04  8.6245777551e-03  2.0222371070e-03\natom  1.1402640800e+01  5.6875572896e+00  1.9993367988e+01 Mg  4.2763180782e-01 0.0 -9.9400272514e-04  2.4397919849e-03 -3.2916309889e-04\natom  1.4243761186e+01  8.5556189322e+00  1.9923113985e+01 O  -4.0014499218e-01 0.0 -1.0287962160e-03 -1.3626837810e-03  7.6066126127e-03\natom  1.1389289924e+01  5.6862026962e+00  2.4002626103e+01 O  -3.4501669218e-01 0.0  9.8582926275e-04  3.5312390947e-04  1.3002334034e-02\natom  1.4298254875e+01  8.5750503799e+00  2.4034093915e+01 Mg  3.3363814782e-01 0.0 -5.7795675219e-03 -1.9718750179e-03 -1.0224612558e-02\natom  1.1469032336e+01  5.6846106776e+00  2.8020552449e+01 Mg  3.3781966782e-01 0.0 -5.6489982517e-03  5.9340200752e-04 -3.4756169654e-03\natom  1.4258729158e+01  8.5015581614e+00  2.8054382172e+01 O  -3.4253984218e-01 0.0  5.5942017709e-04  6.2641500262e-03  8.4017929302e-03\natom  1.1439536321e+01  5.7392925636e+00  3.2075689029e+01 O  -3.4906592218e-01 0.0 -6.3591364213e-03 -1.4347741233e-03  8.4623182748e-03\natom  1.4293739715e+01  8.5224675448e+00  3.2133488302e+01 Mg  3.2813035782e-01 0.0 -4.6968924096e-03 -4.8515074817e-04 -1.6048482384e-02\natom  1.1420989548e+01  5.6841852625e+00  3.6109447706e+01 Mg  3.2116833782e-01 0.0  4.8977558283e-03 -4.9841090551e-03  3.8234874958e-03\natom  1.4239453348e+01  8.5341766461e+00  3.6050746543e+01 O  -3.0985280218e-01 0.0 -1.2820518077e-02  1.7290299277e-02  2.1581204115e-03\natom  1.1472076325e+01  5.6701012481e+00  4.0168895130e+01 O  -4.0545410218e-01 0.0 -8.8331132301e-03  2.4385080124e-03 -7.0957181856e-03\natom  1.4214230004e+01  8.5607007645e+00  4.0139160499e+01 Mg  3.8452424782e-01 0.0  1.1195961136e-02 -7.8190805639e-03  1.1863059041e-02\natom  1.1352456840e+01  1.1414781402e+01  2.0009786589e+01 Mg  4.1960295782e-01 0.0  3.6184689401e-03 -1.1714706704e-03 -1.9232276921e-03\natom  1.4189072460e+01  1.4237616742e+01  2.0020310964e+01 O  -4.0120078218e-01 0.0  5.5529793870e-03  8.6257451194e-04  1.1746380841e-03\natom  1.1431150775e+01  1.1403917216e+01  2.4045487564e+01 O  -3.4064653218e-01 0.0 -8.1924492226e-04 -1.7559464732e-03  1.2527184631e-02\natom  1.4212418021e+01  1.4223200344e+01  2.4014021888e+01 Mg  3.3062132782e-01 0.0  2.5905818170e-03  4.9167341958e-04 -8.4856537935e-03\natom  1.1359688765e+01  1.1338624594e+01  2.8075492962e+01 Mg  3.4149477782e-01 0.0  8.4701068234e-03  5.6931485504e-03 -1.0255618057e-02\natom  1.4296404644e+01  1.4256473335e+01  2.8088220720e+01 O  -3.4360682218e-01 0.0 -6.1265689560e-03 -1.6803802165e-04  6.6567718428e-03\natom  1.1343495193e+01  1.1415306386e+01  3.2055165830e+01 O  -3.1558821218e-01 0.0  5.7921607824e-03  5.9674061877e-04  2.6610778199e-02\natom  1.4209021825e+01  1.4291883588e+01  3.2121536144e+01 Mg  3.3400281782e-01 0.0  1.0366445024e-03 -2.7720591501e-03 -1.4485536863e-02\natom  1.1453983730e+01  1.1303481171e+01  3.6160053038e+01 Al  3.9953783782e-01 0.0 -8.5435240106e-03  5.0274606114e-03  1.3381653961e-03\natom  1.4256826790e+01  1.4261124518e+01  3.6126056905e+01 O  -2.9229326218e-01 0.0  2.0226448210e-03 -2.2397459174e-03 -6.2821441447e-03\natom  1.1420465282e+01  1.1393874607e+01  4.0189559359e+01 O  -3.6061543218e-01 0.0 -1.5897659492e-03 -3.5804923838e-03 -2.5110202181e-02\natom  1.4166433505e+01  1.4203147762e+01  4.0127810767e+01 Mg  3.7181375782e-01 0.0  1.2349806912e-02  2.3473950345e-03  1.5439660173e-02\natom  2.9159275705e+00  2.9590473192e+00  1.5905622598e+01 Au  5.1393067818e-02 0.0 -7.0855722165e-04 -2.5047854373e-03 -6.7223968064e-03\natom  2.7333869375e+00  2.3986665950e+00  1.1216359436e+01 Au -2.3784893218e-01 0.0  2.1082797054e-04  4.9096852454e-05 -1.1738168320e-02\nenergy -5.4395981159e+04\ncharge  0.0000000000e+00\nend\nbegin\nlattice  1.7097166001e+01  0.0000000000e+00  0.0000000000e+00\nlattice  0.0000000000e+00  1.7097166001e+01  0.0000000000e+00\nlattice  0.0000000000e+00  0.0000000000e+00  5.0000000001e+01\natom  2.7921079427e-02  1.5264091598e-02  1.9994754556e+01 Mg  3.5812446473e-01 0.0 -1.3898124508e-02 -1.1856978920e-02 -6.6260729075e-03\natom  2.8762735225e+00  2.8762058892e+00  2.0048006089e+01 O  -3.1372707527e-01 0.0 -2.4460608310e-04 -1.3870690186e-03  5.0349752996e-02\natom -3.2309212145e-03 -9.9533568573e-03  2.3970439553e+01 O  -3.4154503527e-01 0.0  1.1640800111e-03  4.5113105326e-03  1.1778845028e-02\natom  2.7699850528e+00  2.8415876398e+00  2.3991249745e+01 Mg  3.3871529473e-01 0.0  9.2304662205e-03  3.2633019391e-03  8.1232848695e-03\natom -2.4762893766e-02  6.9154919395e-02  2.8091262556e+01 Mg  3.4171137473e-01 0.0  2.4977212442e-03 -8.3208160795e-03 -1.3112782356e-02\natom  2.8605264736e+00  2.7901368451e+00  2.8071076937e+01 O  -3.4240361527e-01 0.0 -1.7965898762e-03  5.5288173979e-03  8.6309503670e-03\natom -6.0615701187e-02  3.3927327817e-02  3.2103178911e+01 O  -3.1411112527e-01 0.0  9.9309862461e-03 -3.2575311171e-03  2.1163273644e-02\natom  2.8451118276e+00  2.8330594009e+00  3.2064990572e+01 Mg  3.3459417473e-01 0.0 -1.1892975547e-03 -1.0422477880e-03 -8.8953057593e-03\natom  1.1169578834e-01 -5.2827290011e-02  3.6172412885e+01 Al  3.9839452473e-01 0.0 -7.6180266645e-03  5.4645998494e-04  5.4836519576e-03\natom  2.8756674496e+00  2.9000650971e+00  3.6194871182e+01 O  -2.9034656527e-01 0.0  2.2437879638e-03 -3.9096399438e-03 -1.6033126113e-02\natom -4.8869353414e-02 -1.5680417130e-02  4.0134516857e+01 O  -3.5987682527e-01 0.0  6.8676905252e-03 -7.7294628908e-04 -2.3713049237e-02\natom  2.8692231060e+00  2.8785412504e+00  4.0202909933e+01 Mg  3.7116021473e-01 0.0 -9.1879408993e-04  1.3057852397e-03  1.2550659080e-02\natom -3.2358930836e-02  5.6759668631e+00  2.0022909942e+01 Mg  3.6677476473e-01 0.0 -5.4015700155e-03  1.3341772196e-02 -4.2923813576e-03\natom  2.8244902872e+00  8.5345701248e+00  2.0025929308e+01 O  -4.0093188527e-01 0.0  4.1467511962e-03  9.4404069115e-04  1.5155812414e-03\natom  4.9765196917e-02  5.6655461014e+00  2.4054260485e+01 O  -3.4357285527e-01 0.0 -7.0742122495e-03 -6.1873303600e-05  4.9488337401e-03\natom  2.8132552048e+00  8.5567139340e+00  2.4057530051e+01 Mg  3.2531767473e-01 0.0  2.8601716442e-03 -9.1656312710e-05 -9.6322639547e-03\natom -3.0948836200e-02  5.6771589778e+00  2.8056338851e+01 Mg  3.3675048473e-01 0.0  6.0314619287e-03  5.4465614663e-03 -1.0227758636e-02\natom  2.8697631330e+00  8.6014085425e+00  2.8028538695e+01 O  -3.4450476527e-01 0.0 -5.8364822048e-04 -5.6681580619e-03  1.2280490494e-02\natom  2.4155705908e-02  5.7111805841e+00  3.2037129945e+01 O  -3.4280347527e-01 0.0 -2.0159050699e-04 -3.6269264581e-03  1.0894552852e-02\natom  2.8319047783e+00  8.5309441753e+00  3.2069360639e+01 Mg  3.3201719473e-01 0.0 -4.4986419639e-04  9.7979008571e-03 -1.0185101229e-02\natom  4.5662318336e-02  5.6778636567e+00  3.6120914507e+01 Mg  3.2322482473e-01 0.0 -7.5108079506e-03  2.8020820465e-04  9.8847680883e-03\natom  2.8569974671e+00  8.5215226440e+00  3.6106621961e+01 O  -3.1626865527e-01 0.0  1.1926356850e-02 -1.0653048515e-02 -6.1429979495e-03\natom  4.1297126892e-03  5.7059769401e+00  4.0168862835e+01 O  -4.0915837527e-01 0.0  2.2581602535e-03 -2.0789286854e-03 -6.5167060630e-03\natom  2.8181758434e+00  8.5861668631e+00  4.0167403645e+01 Mg  3.8452807473e-01 0.0  1.5238039818e-03 -3.3101793075e-03  9.5322920921e-03\natom  1.7558634687e-02  1.1424907782e+01  1.9991963676e+01 Mg  4.2427094473e-01 0.0 -2.0859988468e-03 -2.1774675732e-03 -1.7178965662e-04\natom  2.8240058938e+00  1.4278957201e+01  1.9958993816e+01 O  -3.9760718527e-01 0.0  3.6690255579e-03 -3.8663764614e-04  8.0889842575e-03\natom -1.7256788755e-03  1.1440185253e+01  2.4025918356e+01 O  -3.4455552527e-01 0.0 -1.0465595197e-03 -2.2824053036e-03  1.0262026642e-02\natom  2.8343631795e+00  1.4266228271e+01  2.4046725486e+01 Mg  3.3366127473e-01 0.0  1.1907399023e-03 -2.0046346919e-03 -8.5720620188e-03\natom -7.1700739350e-03  1.1400110854e+01  2.8077974399e+01 Mg  3.3664951473e-01 0.0  1.8883517664e-03  5.0106302052e-04 -9.5334606018e-03\natom  2.9100413008e+00  1.4242724577e+01  2.8083126397e+01 O  -3.4220807527e-01 0.0 -7.1908450212e-03  4.2288761944e-03  4.6866916957e-03\natom -1.7832588264e-02  1.1338764018e+01  3.2080117545e+01 O  -3.4597765527e-01 0.0 -2.6713087752e-03  6.1230978160e-03  8.3500869447e-03\natom  2.8770069819e+00  1.4282970828e+01  3.2068574154e+01 Mg  3.3450253473e-01 0.0 -2.0160570091e-03 -9.9175286464e-03 -7.1553406317e-03\natom -5.0916720345e-02  1.1326348972e+01  3.6118076913e+01 Mg  3.2520459473e-01 0.0  6.1053508247e-03  3.3742723360e-03  1.7313995577e-03\natom  2.8483849275e+00  1.4268356216e+01  3.6094545346e+01 O  -3.1187544527e-01 0.0 -1.5933143609e-02  1.2650179415e-02 -2.8207713707e-03\natom -5.3829392806e-02  1.1384579404e+01  4.0127020956e+01 O  -4.0092461527e-01 0.0  5.4567078940e-03  4.7935304686e-03 -6.0863275778e-03\natom  2.8167644827e+00  1.4231663784e+01  4.0186328362e+01 Mg  3.8385119473e-01 0.0  7.7569093417e-03 -1.8780263285e-04  9.1704372241e-03\natom  5.6816370426e+00  5.4207923819e-03  2.0025183396e+01 Mg  3.5797932473e-01 0.0  1.2649171658e-02 -9.8716545920e-03 -5.5553928700e-03\natom  8.5534003372e+00  2.8329200336e+00  1.9988683433e+01 O  -3.9918213527e-01 0.0 -7.7915962424e-04  1.6718942362e-03  4.7652552321e-03\natom  5.7560257849e+00  5.1515177668e-02  2.4077037220e+01 O  -3.4291289527e-01 0.0 -8.1453928225e-03 -3.7734153664e-03  1.9779702200e-03\natom  8.5251664137e+00  2.8562217534e+00  2.4028462834e+01 Mg  3.2992298473e-01 0.0  1.5793784355e-04  4.2533280277e-03 -8.9847714042e-03\natom  5.7086076088e+00 -3.7471376628e-04  2.8046734413e+01 Mg  3.3224761473e-01 0.0 -2.9806420447e-04  1.1755484993e-03 -7.4866921578e-03\natom  8.5181406581e+00  2.9128589578e+00  2.8075857623e+01 O  -3.3996104527e-01 0.0  4.6261431655e-03 -3.0817605875e-03  1.0508665853e-02\natom  5.6868416315e+00 -5.0580727064e-02  3.2069647367e+01 O  -3.4239768527e-01 0.0 -1.2355135521e-03  1.0743295505e-02  9.0824014172e-03\natom  8.5139552741e+00  2.8545173718e+00  3.2108449508e+01 Mg  3.3862338473e-01 0.0  1.0196468597e-02 -7.7408884846e-03 -7.0498028404e-03\natom  5.7770958895e+00 -1.3379524561e-02  3.6082547211e+01 Mg  3.2121049473e-01 0.0 -2.6698717593e-03 -4.3495569133e-04  1.2736295990e-02\natom  8.5782823593e+00  2.8201795955e+00  3.6152021929e+01 O  -3.1693123527e-01 0.0 -1.5483970227e-02  1.4194779735e-02 -1.2978657782e-02\natom  5.6698989341e+00  3.5826256771e-02  4.0164648708e+01 O  -4.0806860527e-01 0.0  5.1624841278e-04 -3.2732056827e-03 -6.5236606488e-03\natom  8.5282044128e+00  2.8406094798e+00  4.0176858435e+01 Mg  3.8403092473e-01 0.0  5.0500867558e-03  6.3916211981e-04  6.6356322528e-03\natom  5.7187623348e+00  5.6651967856e+00  1.9942950231e+01 Mg  3.7300554473e-01 0.0  8.4678184153e-03  1.3458131092e-02  2.1199792444e-03\natom  8.6523236377e+00  8.5040637869e+00  2.0048808618e+01 O  -3.9947912527e-01 0.0 -8.4344367663e-03  3.5390213119e-03 -3.0587651526e-03\natom  5.6942826165e+00  5.7715563657e+00  2.4072061704e+01 O  -3.4682269527e-01 0.0 -3.4672858010e-04 -8.7828574481e-03  3.3680536075e-03\natom  8.5419353697e+00  8.5475557927e+00  2.4060249650e+01 Mg  3.2619870473e-01 0.0  3.2450998807e-04 -3.0158359711e-03 -1.1095705170e-02\natom  5.7306903231e+00  5.7099584038e+00  2.8091010731e+01 Mg  3.4029529473e-01 0.0 -6.1956793983e-03  2.6627563030e-03 -1.9168751919e-02\natom  8.5590912470e+00  8.5756000634e+00  2.8077006349e+01 O  -3.3982610527e-01 0.0 -2.4038142601e-04 -2.5261045947e-03  1.1500185584e-02\natom  5.6726908530e+00  5.6862539267e+00  3.2096324194e+01 O  -3.0609396527e-01 0.0  2.5412175663e-03 -7.0466323332e-04  2.2278858412e-02\natom  8.5566493053e+00  8.5310547621e+00  3.2065972776e+01 Mg  3.3160408473e-01 0.0 -3.4713673593e-03  5.5945847878e-03 -6.9013218521e-03\natom  5.7062028947e+00  5.6932123702e+00  3.6051923673e+01 Al  4.0037884473e-01 0.0 -2.2572592058e-04  7.9918755424e-04  2.0465201815e-02\natom  8.5391486474e+00  8.6109303615e+00  3.6090551505e+01 O  -2.9157671527e-01 0.0  2.7275595010e-03 -4.2666903022e-03 -6.7171920189e-03\natom  5.7524253278e+00  5.7360525339e+00  4.0112135887e+01 O  -3.6636074527e-01 0.0 -4.8065096119e-03 -1.0890414288e-03 -2.2726129672e-02\natom  8.5645020995e+00  8.5526427461e+00  4.0171356706e+01 Mg  3.6869519473e-01 0.0 -2.4388327979e-04 -2.7651813858e-03  1.1595276331e-02\natom  5.7230238559e+00  1.1409240668e+01  2.0054906650e+01 Mg  4.2892660473e-01 0.0 -8.8789345734e-04 -2.1796867168e-03 -4.5486364068e-03\natom  8.5346931649e+00  1.4268712032e+01  2.0002402466e+01 O  -4.0014729527e-01 0.0  5.2010860813e-04 -3.2435047836e-03  3.2371431587e-03\natom  5.7248833652e+00  1.1406768434e+01  2.4035365833e+01 O  -3.4140523527e-01 0.0 -2.3014011201e-03  3.5968947260e-03  6.8178023836e-03\natom  8.5685336409e+00  1.4197466188e+01  2.4003422547e+01 Mg  3.3168313473e-01 0.0  7.3638060705e-04  5.4830505544e-03 -6.1571832435e-03\natom  5.7616757444e+00  1.1497769871e+01  2.7984129700e+01 Mg  3.3566074473e-01 0.0 -7.7681194048e-03 -8.7268270803e-03  1.0914241925e-03\natom  8.5529989027e+00  1.4283708633e+01  2.8135076552e+01 O  -3.4141015527e-01 0.0  1.4418524201e-03 -1.1895650097e-03  2.3418170282e-04\natom  5.6944594004e+00  1.1418239997e+01  3.2115197625e+01 O  -3.4891112527e-01 0.0 -3.2487083161e-04 -5.1498915594e-03  3.1797152739e-03\natom  8.4556056945e+00  1.4240837969e+01  3.2114306846e+01 Mg  3.2713886473e-01 0.0  5.7828883160e-03  2.3204892804e-03 -8.4085657019e-03\natom  5.6958582700e+00  1.1369738876e+01  3.6158521887e+01 Mg  3.1876916473e-01 0.0 -3.7050469151e-03  3.7343709495e-03  1.0038481047e-03\natom  8.4832465654e+00  1.4210189222e+01  3.6113988661e+01 O  -3.1792731527e-01 0.0  1.8800640930e-02 -8.9868122044e-03 -3.5918729281e-03\natom  5.7060646423e+00  1.1398940528e+01  4.0196142465e+01 O  -4.0510230527e-01 0.0 -2.6799566112e-03 -4.3613874295e-04 -7.9888464588e-03\natom  8.5403925596e+00  1.4206768213e+01  4.0160214296e+01 Mg  3.8582871473e-01 0.0 -1.9283219587e-03  7.9188672272e-03  9.6838336693e-03\natom  1.1421844385e+01 -1.1806025319e-02  2.0050265956e+01 Mg  4.1995015473e-01 0.0 -2.8383275746e-03 -1.2648176933e-03 -6.4442616592e-03\natom  1.4226368016e+01  2.8563494044e+00  1.9970645016e+01 O  -3.9635941527e-01 0.0  3.2402914442e-03 -1.8795054280e-04  6.4085115629e-03\natom  1.1403789376e+01  1.4689218055e-02  2.4059943363e+01 O  -3.4129343527e-01 0.0 -1.3057334721e-04 -4.8240596492e-04  7.5426759402e-03\natom  1.4165665444e+01  2.8703313547e+00  2.4038574342e+01 Mg  3.2953918473e-01 0.0  6.4160104520e-03  7.2901615291e-05 -1.0362631782e-02\natom  1.1391002299e+01  7.6051625569e-02  2.8027626128e+01 Mg  3.4109461473e-01 0.0 -1.6470783196e-05 -8.1560846811e-03  4.7579152774e-04\natom  1.4295234941e+01  2.8691367833e+00  2.8052947038e+01 O  -3.3884245527e-01 0.0 -5.7329217910e-03 -4.5628332828e-04  9.7016633558e-03\natom  1.1429627883e+01 -4.6214836421e-02  3.2102780481e+01 O  -3.4928195527e-01 0.0 -4.9821446791e-03  4.9395415915e-03  2.5829400557e-03\natom  1.4310523051e+01  2.8823959135e+00  3.2123003232e+01 Mg  3.3210369473e-01 0.0 -9.6840947989e-03 -3.4590966034e-03 -5.6523268264e-03\natom  1.1476005859e+01 -1.5359881808e-02  3.6087572031e+01 Mg  3.1841827473e-01 0.0 -8.1978524315e-03  4.1706929599e-03  6.3201436194e-03\natom  1.4185713774e+01  2.8241752321e+00  3.6108984572e+01 O  -3.2389390527e-01 0.0  2.0143547800e-02 -6.2349628196e-03 -5.6050350919e-03\natom  1.1427564132e+01  4.2938146043e-02  4.0170787445e+01 O  -4.0576523527e-01 0.0 -4.0047794301e-03 -8.3789653938e-03 -6.9627066013e-03\natom  1.4176202273e+01  2.7608067671e+00  4.0137651742e+01 Mg  3.8357219473e-01 0.0  1.8312812089e-03  1.6480874913e-02  8.3959637287e-03\natom  1.1430778310e+01  5.7053487574e+00  1.9938644944e+01 Mg  4.2989210473e-01 0.0 -2.9167630020e-03 -8.2887481579e-04  2.3420989640e-03\natom  1.4251814915e+01  8.5747291453e+00  2.0036443082e+01 O  -3.9801467527e-01 0.0  1.0696359357e-03 -4.4474698742e-03 -8.9607504641e-05\natom  1.1431624813e+01  5.6990229186e+00  2.4076945644e+01 O  -3.4319075527e-01 0.0 -3.5847761467e-03 -2.4065760963e-03  7.0639503562e-03\natom  1.4154615763e+01  8.5371994518e+00  2.4034545371e+01 Mg  3.3450080473e-01 0.0  7.3544947167e-03  3.9776098894e-03 -7.0843901089e-03\natom  1.1413048958e+01  5.6866207981e+00  2.8114851004e+01 Mg  3.3916217473e-01 0.0 -6.0640382317e-04  3.0735793785e-03 -1.1670928823e-02\natom  1.4248495914e+01  8.5542996578e+00  2.8064674546e+01 O  -3.4110679527e-01 0.0 -2.8132521375e-03 -5.6397309371e-04  9.5575123192e-03\natom  1.1405889334e+01  5.7009296332e+00  3.2149319065e+01 O  -3.4294871527e-01 0.0 -1.7946061792e-03  1.2804021200e-03 -1.2780820832e-03\natom  1.4245050849e+01  8.5345579928e+00  3.2088804332e+01 Mg  3.3469490473e-01 0.0  3.7488613545e-03 -1.5969843829e-03 -6.9793799759e-03\natom  1.1428663839e+01  5.7229032347e+00  3.6102175266e+01 Mg  3.1655379473e-01 0.0 -9.8473777518e-04 -5.5252008640e-03  1.2023735052e-02\natom  1.4249753923e+01  8.4934271618e+00  3.6198090614e+01 O  -3.1605932527e-01 0.0 -9.0348746276e-03  1.6871074161e-02 -1.8522023726e-02\natom  1.1387747643e+01  5.8114780933e+00  4.0087172040e+01 O  -4.0992705527e-01 0.0 -1.0908016220e-04 -8.5622867170e-03 -2.0341803692e-03\natom  1.4294506433e+01  8.6040415355e+00  4.0130825334e+01 Mg  3.7514360473e-01 0.0 -3.4770986467e-03 -1.3056777515e-02  1.3348531810e-02\natom  1.1438465281e+01  1.1375547856e+01  2.0014262669e+01 Mg  4.1869831473e-01 0.0 -2.6767901556e-03  1.9471100607e-03 -7.3623538316e-04\natom  1.4202245059e+01  1.4199634989e+01  1.9951867394e+01 O  -4.0105151527e-01 0.0  3.2818510134e-03  5.2398598784e-03  6.0245881028e-03\natom  1.1329123940e+01  1.1371655096e+01  2.4065256007e+01 O  -3.4352367527e-01 0.0  5.9245174664e-03  3.8813423940e-03  9.4254985120e-03\natom  1.4277529569e+01  1.4277311249e+01  2.4091269200e+01 Mg  3.3299143473e-01 0.0 -3.2970441195e-03 -5.5517802837e-03 -1.3269934618e-02\natom  1.1334275843e+01  1.1387374611e+01  2.8139905407e+01 Mg  3.4132575473e-01 0.0  6.6326058459e-03  4.3151493541e-03 -1.8898643122e-02\natom  1.4259346172e+01  1.4285534411e+01  2.8053227020e+01 O  -3.4378090527e-01 0.0 -5.5310704584e-04 -2.0695079104e-03  1.1097089384e-02\natom  1.1345333726e+01  1.1385548588e+01  3.2102182591e+01 O  -3.1036472527e-01 0.0  4.8876258086e-03 -1.5743485806e-03  2.2585675444e-02\natom  1.4195541389e+01  1.4205494519e+01  3.2131011778e+01 Mg  3.2952860473e-01 0.0  3.4857908562e-03  5.6980491039e-03 -1.6859889090e-02\natom  1.1393249372e+01  1.1387718711e+01  3.6127570216e+01 Al  4.0001037473e-01 0.0 -5.9805810720e-03 -1.0203101897e-03  1.0838252948e-02\natom  1.4264167903e+01  1.4305089919e+01  3.6063368477e+01 O  -2.9362171527e-01 0.0  3.7894734275e-03 -7.0195041401e-03  1.0583417393e-03\natom  1.1405656047e+01  1.1369504833e+01  4.0113487608e+01 O  -3.6097855527e-01 0.0 -1.2281163979e-04  7.4209423595e-03 -2.3759999265e-02\natom  1.4300245399e+01  1.4267110452e+01  4.0177367509e+01 Mg  3.6916972473e-01 0.0 -7.9360832832e-03 -2.0978096136e-03  1.1866559602e-02\natom  2.7935674347e+00  2.7474617300e+00  1.6224446547e+01 Au  9.9763634727e-02 0.0 -2.3634890433e-03  2.3974117194e-03 -5.6726700451e-02\natom  2.4089756172e+00  2.9797330535e+00  1.1420734114e+01 Au -2.5084614527e-01 0.0  7.4845975744e-04 -1.0139529033e-03  1.2283908865e-03\nenergy -5.4395981566e+04\ncharge  0.0000000000e+00\nend\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/input.nn",
    "content": "################################################################################\n### This is the input file for n2p2\n### It contains only a subset of all keywords\n################################################################################\n\n\n################################################################################\n### general keywords\n################################################################################\n\nnnp_generation 4\nuse_short_forces\n\nnumber_of_elements 4\nelements Al O Mg Au\n\ninitial_hardness        O        10.0\ninitial_hardness       Mg        10.0\ninitial_hardness       Al        10.0\ninitial_hardness       Au        10.0\n\nfixed_gausswidth Mg 4.289\nfixed_gausswidth  O 2.872\nfixed_gausswidth Al 3.477\nfixed_gausswidth Au 3.288\n\nscreen_electrostatics 3.2 8.0\n\nrandom_seed 12346\n\natom_energy     O   -75.29000258799172\natom_energy    Mg   -200.61689378490792\natom_energy    Au   -19684.765036573383\natom_energy    Al   -243.09681374120558\n\newald_truncation_error_method 1\newald_prec 1.e-5 0.45\n\n################################################################################\n### NN structure of the short-range NN\n################################################################################\nglobal_hidden_layers_short 2\nglobal_nodes_short 15 15\nglobal_activation_short t t l\n\n################################################################################\n### NN structure of the electrostatic NN\n################################################################################\nglobal_hidden_layers_electrostatic 2\nglobal_nodes_electrostatic 15 15\nglobal_activation_electrostatic t t l\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (General)\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nupdater_type                    1              # Weight update method\n                                               # (0 = Gradient Descent,\n                                               # 1 = Kalman filter).\nparallel_mode                   1              # Training parallelization used\n                                               # (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  0              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                          # Precondition weights with initial energies.\nwrite_weights_epoch             10             # Write weights every this many epochs.\nscale_symmetry_functions\ncenter_symmetry_functions\n#write_neuronstats               1             # Write neuron statistics every this many epochs.\n#write_trainlog                                # Write training log file.\n\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (charges, stage 1)\n################################################################################\ntask_batch_size_charge          1\n#nguyen_widrow_weights_charge                  # Initialize neural network weights according to Nguyen-Widrow scheme.\ncharge_fraction                 1.000\n#write_traincharges              1             # Write charge comparison. Can produce large files.\n#use_old_weights_charge                        # Restart fitting with old weight parameters.\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (short-range, stage 2)\n################################################################################\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.02315        # Fraction of force updates per epoch.\n#short_energy_error_threshold    0.80          # RMSE threshold for energy update candidates.\n#short_force_error_threshold     0.80          # RMSE threshold for force update candidates.\n#use_old_weights_short                         # Restart fitting with old weight parameters.\n#repeated_energy_update\n#nguyen_widrow_weights_short                   # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               0              # Write energy comparison every this many epochs.\nwrite_trainforces               0              # Write force comparison every this many epochs.\n\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\n#kalman_lambda_short 0.98000                   # Only for fading memory Kalman filter\n#kalman_nue_short 0.99870\n\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon, covariance matrix initialization (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0, initial process noise (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin, final process noise (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n\n\n################################################################################\n### symmetry function definitions (all modes):\n################################################################################\ncutoff_type 2\n\nsymfunction Mg  2  Mg    0.000000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.001000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.002000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.003000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.004000      0.000000      8.000000\nsymfunction Mg  2  Mg    0.005000      0.000000      8.000000\n\n\nsymfunction O  2 Mg     0.000000      0.000000      8.000000\nsymfunction O  2 Mg     0.004000      0.000000      8.000000\nsymfunction O  2 Mg     0.007000      0.000000      8.000000\nsymfunction O  2 Mg     0.010000      0.000000      8.000000\nsymfunction O  2 Mg     0.014000      0.000000      8.000000\nsymfunction O  2 Mg     0.018000      0.000000      8.000000\n\nsymfunction Mg 2  O    0.000000      0.000000      8.000000\nsymfunction Mg 2  O    0.004000      0.000000      8.000000\nsymfunction Mg 2  O    0.007000      0.000000      8.000000\nsymfunction Mg 2  O    0.010000      0.000000      8.000000\nsymfunction Mg 2  O    0.014000      0.000000      8.000000\nsymfunction Mg 2  O    0.018000      0.000000      8.000000\n\nsymfunction O  2  O    0.000000      0.000000      8.000000\nsymfunction O  2  O    0.001000      0.000000      8.000000\nsymfunction O  2  O    0.002000      0.000000      8.000000\nsymfunction O  2  O    0.003000      0.000000      8.000000\nsymfunction O  2  O    0.004000      0.000000      8.000000\nsymfunction O  2  O    0.005000      0.000000      8.000000\n\nsymfunction Mg  2  Au    0.000000      0.000000      8.000000\nsymfunction Mg  2  Au    0.001000      0.000000      8.000000\nsymfunction Mg  2  Au    0.002000      0.000000      8.000000\nsymfunction Mg  2  Au    0.003000      0.000000      8.000000\nsymfunction Mg  2  Au    0.004000      0.000000      8.000000\nsymfunction Mg  2  Au    0.005000      0.000000      8.000000\n\nsymfunction Au  2  Mg    0.000000      0.000000      8.000000\nsymfunction Au  2  Mg    0.001000      0.000000      8.000000\nsymfunction Au  2  Mg    0.002000      0.000000      8.000000\nsymfunction Au  2  Mg    0.003000      0.000000      8.000000\nsymfunction Au  2  Mg    0.004000      0.000000      8.000000\nsymfunction Au  2  Mg    0.005000      0.000000      8.000000\n\n\nsymfunction Au  2 O     0.000000      0.000000      8.000000\nsymfunction Au  2 O     0.004000      0.000000      8.000000\nsymfunction Au  2 O     0.008000      0.000000      8.000000\nsymfunction Au  2 O     0.013000      0.000000      8.000000\nsymfunction Au  2 O     0.018000      0.000000      8.000000\nsymfunction Au  2 O     0.024000      0.000000      8.000000\n\nsymfunction O  2 Au     0.000000      0.000000      8.000000\nsymfunction O  2 Au     0.004000      0.000000      8.000000\nsymfunction O  2 Au     0.008000      0.000000      8.000000\nsymfunction O  2 Au     0.013000      0.000000      8.000000\nsymfunction O  2 Au     0.018000      0.000000      8.000000\nsymfunction O  2 Au     0.024000      0.000000      8.000000\n\nsymfunction Au  2 Au     0.000000      0.000000      8.000000\nsymfunction Au  2 Au     0.004000      0.000000      8.000000\nsymfunction Au  2 Au     0.008000      0.000000      8.000000\nsymfunction Au  2 Au     0.012000      0.000000      8.000000\nsymfunction Au  2 Au     0.017000      0.000000      8.000000\nsymfunction Au  2 Au     0.022000      0.000000      8.000000\n\n\nsymfunction O  2  Al    0.000000      0.000000      8.000000\nsymfunction O  2  Al    0.003000      0.000000      8.000000\nsymfunction O  2  Al    0.005000      0.000000      8.000000\nsymfunction O  2  Al    0.008000      0.000000      8.000000\nsymfunction O  2  Al    0.011000      0.000000      8.000000\nsymfunction O  2  Al    0.014000      0.000000      8.000000\n\nsymfunction Al  2  O    0.000000      0.000000      8.000000\nsymfunction Al  2  O    0.003000      0.000000      8.000000\nsymfunction Al  2  O    0.005000      0.000000      8.000000\nsymfunction Al  2  O    0.008000      0.000000      8.000000\nsymfunction Al  2  O    0.011000      0.000000      8.000000\nsymfunction Al  2  O    0.014000      0.000000      8.000000\n\nsymfunction Al  2  Mg    0.000000      0.000000      8.000000\nsymfunction Al  2  Mg    0.001000      0.000000      8.000000\nsymfunction Al  2  Mg    0.002000      0.000000      8.000000\nsymfunction Al  2  Mg    0.003000      0.000000      8.000000\nsymfunction Al  2  Mg    0.004000      0.000000      8.000000\nsymfunction Al  2  Mg    0.005000      0.000000      8.000000\n\nsymfunction Mg  2  Al    0.000000      0.000000      8.000000\nsymfunction Mg  2  Al    0.001000      0.000000      8.000000\nsymfunction Mg  2  Al    0.002000      0.000000      8.000000\nsymfunction Mg  2  Al    0.003000      0.000000      8.000000\nsymfunction Mg  2  Al    0.004000      0.000000      8.000000\nsymfunction Mg  2  Al    0.005000      0.000000      8.000000\n\n#symfunction Al  2  Al    0.000000      0.000000      8.000000\n#symfunction Al  2  Al    0.001000      0.000000      8.000000\n#symfunction Al  2  Al    0.002000      0.000000      8.000000\n#symfunction Al  2  Al    0.003000      0.000000      8.000000\n#symfunction Al  2  Al    0.004000      0.000000      8.000000\n#symfunction Al  2  Al    0.005000      0.000000      8.000000\n\n\nsymfunction Mg 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction Mg 3 Mg Mg 0.0  1.0 2.0  8.0\nsymfunction Mg 3 Mg Mg 0.0  1.0 4.0  8.0\n#symfunction Mg 3 Mg Mg 0.0  1.0 8.0  8.0\nsymfunction Mg 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 4.0  8.0\nsymfunction Mg 3 Mg  O 0.0  1.0 8.0  8.0\nsymfunction Mg 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction Mg 3 Mg  O 0.0 -1.0 2.0  8.0\n#symfunction Mg 3 Mg  O 0.0 -1.0 4.0  8.0\n#symfunction Mg 3 Mg  O 0.0 -1.0 8.0  8.0\n\n#symfunction Mg 3 Mg Al 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Mg Al 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Mg Al 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Al 0.0 -1.0 2.0  8.0\n\n#symfunction Mg 3 Mg Au 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Mg Au 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Mg Au 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3  O  O 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O  O 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O  O 0.0  1.0 4.0  8.0\n#symfunction Mg 3  O  O 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 1.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 2.0  8.0\nsymfunction Mg 3  O  O 0.0 -1.0 4.0  8.0\n#symfunction Mg 3  O  O 0.0 -1.0 8.0  8.0\n\nsymfunction Mg 3  O Al 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 4.0  8.0\nsymfunction Mg 3  O Al 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O Al 0.0 -1.0 1.0  8.0\n#symfunction Mg 3  O Al 0.0 -1.0 2.0  8.0\n\nsymfunction Mg 3  O Au 0.0  1.0 1.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 2.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 4.0  8.0\nsymfunction Mg 3  O Au 0.0  1.0 8.0  8.0\nsymfunction Mg 3  O Au 0.0 -1.0 1.0  8.0\nsymfunction Mg 3  O Au 0.0 -1.0 2.0  8.0\n\n#symfunction Mg 3 Al Al 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Al Al 0.0  1.0 2.0  8.0\n\n#symfunction Mg 3 Au Au 0.0  1.0 1.0  8.0\n#symfunction Mg 3 Au Au 0.0  1.0 2.0  8.0\n#symfunction Mg 3 Au Au 0.0 -1.0 1.0  8.0\n#symfunction Mg 3 Au Au 0.0 -1.0 2.0  8.0\n\n\n\nsymfunction  O 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Mg 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Mg 0.0  1.0 4.0  8.0\n#symfunction  O 3 Mg Mg 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 2.0  8.0\nsymfunction  O 3 Mg Mg 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg Mg 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 4.0  8.0\nsymfunction  O 3 Mg  O 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg  O 0.0 -1.0 2.0  8.0\n#symfunction  O 3 Mg  O 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg  O 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg Al 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Al 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Al 0.0  1.0 4.0  8.0\n#symfunction  O 3 Mg Al 0.0  1.0 8.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 2.0  8.0\nsymfunction  O 3 Mg Al 0.0 -1.0 4.0  8.0\n#symfunction  O 3 Mg Al 0.0 -1.0 8.0  8.0\n\nsymfunction  O 3 Mg Au 0.0  1.0 1.0  8.0\nsymfunction  O 3 Mg Au 0.0  1.0 2.0  8.0\nsymfunction  O 3 Mg Au 0.0 -1.0 1.0  8.0\nsymfunction  O 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction  O 3  O  O 0.0  1.0 1.0  8.0\nsymfunction  O 3  O  O 0.0  1.0 2.0  8.0\nsymfunction  O 3  O  O 0.0 -1.0 1.0  8.0\n\nsymfunction  O 3  O Al 0.0  1.0 1.0  8.0\nsymfunction  O 3  O Al 0.0  1.0 2.0  8.0\nsymfunction  O 3  O Al 0.0 -1.0 1.0  8.0\nsymfunction  O 3  O Al 0.0 -1.0 2.0  8.0\n\n#symfunction  O 3  O Au 0.0  1.0 1.0  8.0\n\nsymfunction Al 3 Mg Mg 0.0  1.0 1.0  8.0\n#symfunction Al 3 Mg Mg 0.0  1.0 2.0  8.0\n#symfunction Al 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Al 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Al 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Al 3 Mg  O 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg  O 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3 Mg Al 0.0  1.0 1.0  8.0\n#symfunction Al 3 Mg Al 0.0  1.0 2.0  8.0\n#symfunction Al 3 Mg Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Mg Al 0.0 -1.0 2.0  8.0\n\nsymfunction Al 3  O  O 0.0  1.0 1.0  8.0\nsymfunction Al 3  O  O 0.0  1.0 2.0  8.0\nsymfunction Al 3  O  O 0.0 -1.0 1.0  8.0\nsymfunction Al 3  O  O 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3  O Al 0.0  1.0 1.0  8.0\n#symfunction Al 3  O Al 0.0  1.0 2.0  8.0\n#symfunction Al 3  O Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3  O Al 0.0 -1.0 2.0  8.0\n\n#symfunction Al 3 Al Al 0.0  1.0 1.0  8.0\n#symfunction Al 3 Al Al 0.0  1.0 2.0  8.0\n#symfunction Al 3 Al Al 0.0 -1.0 1.0  8.0\n#symfunction Al 3 Al Al 0.0 -1.0 2.0  8.0\n\n\n\nsymfunction Au 3 Mg Mg 0.0  1.0 1.0  8.0\nsymfunction Au 3 Mg Mg 0.0  1.0 2.0  8.0\n#symfunction Au 3 Mg Mg 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Mg Mg 0.0 -1.0 2.0  8.0\n\nsymfunction Au 3 Mg  O 0.0  1.0 1.0  8.0\nsymfunction Au 3 Mg  O 0.0  1.0 2.0  8.0\nsymfunction Au 3 Mg  O 0.0 -1.0 1.0  8.0\nsymfunction Au 3 Mg  O 0.0 -1.0 2.0  8.0\n\n#symfunction Au 3 Mg Au 0.0  1.0 1.0  8.0\n#symfunction Au 3 Mg Au 0.0  1.0 2.0  8.0\n#symfunction Au 3 Mg Au 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Mg Au 0.0 -1.0 2.0  8.0\n\nsymfunction Au 3  O  O 0.0  1.0 1.0  8.0\n#symfunction Au 3  O  O 0.0  1.0 2.0  8.0\n#symfunction Au 3  O  O 0.0 -1.0 1.0  8.0\n#symfunction Au 3  O  O 0.0 -1.0 2.0  8.0\n\n#symfunction Au 3  O Au 0.0  1.0 1.0  8.0\n#symfunction Au 3  O Au 0.0  1.0 2.0  8.0\nsymfunction Au 3  O Au 0.0  1.0 -1.0  8.0\nsymfunction Au 3  O Au 0.0  1.0 -2.0  8.0\n\n#symfunction Au 3 Au Au 0.0  1.0 1.0  8.0\n#symfunction Au 3 Au Au 0.0  1.0 2.0  8.0\n#symfunction Au 3 Au Au 0.0 -1.0 1.0  8.0\n#symfunction Au 3 Au Au 0.0 -1.0 2.0  8.0\n\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.5913246362740890E-01   2.7498027860021046E-01   2.3411070974364162E-01   4.1533231436381934E-02\n         1          2   3.8208348960582011E-01   6.1596767565978183E-01   5.4365345214195337E-01   6.2168750346181266E-02\n         1          3   0.0000000000000000E+00   2.0337444777209396E-01   1.8576859898018071E-02   4.4625560493899021E-02\n         1          4   0.0000000000000000E+00   1.5164101051381235E-01   1.3203343352844459E-03   1.0211157463807744E-02\n         1          5   1.5391381116917166E-01   2.6630566279985779E-01   2.2663568141082335E-01   4.0209778156836393E-02\n         1          6   1.4886636102567033E-01   2.5790477787348365E-01   2.1939940663111937E-01   3.8928536384299980E-02\n         1          7   1.4398449479386538E-01   2.4976898364574004E-01   2.1239425702337048E-01   3.7688158517680648E-02\n         1          8   0.0000000000000000E+00   1.9406211706928167E-01   1.7648911217202110E-02   4.2520645795885346E-02\n         1          9   1.3926277851637014E-01   2.4188991274332780E-01   2.0561284802157034E-01   3.6487340018409600E-02\n         1         10   3.5659033473577800E-01   5.7617043647213184E-01   5.0797436473966617E-01   5.7976950050853085E-02\n         1         11   0.0000000000000000E+00   1.4539600862621604E-01   1.2080612335982977E-03   9.5956010246851711E-03\n         1         12   1.3469595662418768E-01   2.3425946197908221E-01   1.9904803107952371E-01   3.5324818033081816E-02\n         1         13   0.0000000000000000E+00   1.8809201699275113E-01   1.7058393333331711E-02   4.1172309442739349E-02\n         1         14   3.3865933443703955E-01   5.4816761897885724E-01   4.8287365211335448E-01   5.5044887285242698E-02\n         1         15   0.0000000000000000E+00   1.7947947129709610E-01   1.6212369520148557E-02   3.9228848324466881E-02\n         1         16   0.0000000000000000E+00   1.3940819342211608E-01   1.1079029290115836E-03   9.0238606983715688E-03\n         1         17   3.2167867130268979E-01   5.2163502844899057E-01   4.5909660848294337E-01   5.2279563377814288E-02\n         1         18   0.0000000000000000E+00   1.7126129487398756E-01   1.5411368048689429E-02   3.7376367464040744E-02\n         1         19   0.0000000000000000E+00   1.3226899923747690E-01   9.9733208701786565E-04   8.3646228125886356E-03\n         1         20   3.0041860250661334E-01   4.8838867529404617E-01   4.2931449331560534E-01   4.8831457141969466E-02\n         1         21   0.0000000000000000E+00   1.6341942908701504E-01   1.4652596905168125E-02   3.5610690618752175E-02\n         1         22   2.8062447123113465E-01   4.5739845518552941E-01   4.0156881040680370E-01   4.5633685713583956E-02\n         1         23   0.0000000000000000E+00   1.2549540833880571E-01   9.0060796845390961E-04   7.7606786257876439E-03\n         1         24   0.0000000000000000E+00   1.1782340194594421E-01   7.9983843493257442E-04   7.1008688199004182E-03\n         1         25   4.8080975477891362E-05   1.4454236521537357E-04   1.0606138550262831E-04   3.0372661949925568E-05\n         1         26   7.0914606025698497E-04   1.6744510195351690E-03   1.3424921537840402E-03   2.7021554815884620E-04\n         1         27   0.0000000000000000E+00   5.4853339679432496E-04   4.8918824234109643E-05   1.1979835904367966E-04\n         1         28   7.1458123350106911E-04   2.8988424591760804E-03   2.0780582515160153E-03   5.2414012393671374E-04\n         1         29   0.0000000000000000E+00   1.8148844374031689E-03   1.5688952598208675E-04   3.8606024791623862E-04\n         1         30   0.0000000000000000E+00   2.2849303786486581E-03   9.8350339606152324E-06   1.0715779914260924E-04\n         1         31   1.4892822650354744E-04   4.3373787604534034E-04   3.1815667234462886E-04   9.1065360531956851E-05\n         1         32   4.0219506797962226E-03   9.2487775728862312E-03   7.4767715518134336E-03   1.4678002695749002E-03\n         1         33   0.0000000000000000E+00   3.0305462630596833E-03   2.7169254790767488E-04   6.5773132788470132E-04\n         1         34   7.5172170455342397E-04   3.0273633797592695E-03   2.1731243208738043E-03   5.4921772834580788E-04\n         1         35   0.0000000000000000E+00   1.8533362398174024E-03   1.6464081695290772E-04   3.9447357279410100E-04\n         1         36   0.0000000000000000E+00   2.2184622784054632E-03   1.1341545557416343E-05   1.0837902747683792E-04\n         1         37   1.1143704929203174E-04   2.8763385671683813E-04   2.2584657344904279E-04   4.8345027630844206E-05\n         1         38   0.0000000000000000E+00   9.3700521240144783E-05   8.2928224801076323E-06   2.0450148930311655E-05\n         1         39   3.5348159825506734E-04   1.4369216585712827E-03   1.0291543921906198E-03   2.5961292527450176E-04\n         1         40   0.0000000000000000E+00   9.0398962706883068E-04   7.7629549460939162E-05   1.9220121514820071E-04\n         1         41   0.0000000000000000E+00   1.1629195015924435E-03   4.7649451694633064E-06   5.3597908198657475E-05\n         1         42   1.1258705976848477E-04   3.2533943430389684E-04   2.3862266405011540E-04   6.8293626707686267E-05\n         1         43   3.4264224455910976E-03   7.8617625783154541E-03   6.3601259714784310E-03   1.2459351251272292E-03\n         1         44   0.0000000000000000E+00   2.5748873237476334E-03   2.3106654615367284E-04   5.5839187554174825E-04\n         1         45   3.9062206930742224E-04   1.5654425791544720E-03   1.1242204615484080E-03   2.8486887741001316E-04\n         1         46   0.0000000000000000E+00   9.4244142948306405E-04   8.5380840431760154E-05   2.0068178356825279E-04\n         1         47   0.0000000000000000E+00   1.0964514013492488E-03   6.2714567662644133E-06   5.5016306432159781E-05\n         1         48   8.7973925843085174E-05   3.5832733237607363E-04   2.5608428623379731E-04   6.4680680695290577E-05\n         1         49   0.0000000000000000E+00   2.2601720486665336E-04   1.9300846996101465E-05   4.7992361182309711E-05\n         1         50   2.4955082208680721E-03   5.7161098206143252E-03   4.6269619260169833E-03   9.0499243141407989E-04\n         1         51   1.1262325510512315E-04   4.4450081263398150E-04   3.1924617682138959E-04   8.2103934823498989E-05\n         1         52   0.0000000000000000E+00   2.5268974017304087E-04   2.4441001330304955E-05   5.3822087206804916E-05\n         1         53   1.3315925120089905E-03   3.0501155053261693E-03   2.4691301720221924E-03   4.8335291030511665E-04\n         2          1   4.6850729348206133E-01   6.1881828384306736E-01   5.6111021436669517E-01   5.0117551392186072E-02\n         2          2   1.2461983924928560E-01   2.7436953876553494E-01   2.2482112212919250E-01   4.4457135693832278E-02\n         2          3   0.0000000000000000E+00   5.0329467595954948E-02   8.4735292148864598E-03   1.5485750105466703E-02\n         2          4   0.0000000000000000E+00   6.4701496020064905E-02   1.3706417473048659E-03   5.9091928698948156E-03\n         2          5   1.2057847639207064E-01   2.6571558945859042E-01   2.1764373952280031E-01   4.3040350473031092E-02\n         2          6   0.0000000000000000E+00   4.8784011440659907E-02   8.2031408805137256E-03   1.4992130655914232E-02\n         2          7   0.0000000000000000E+00   6.3313607217018425E-02   1.3284100519227514E-03   5.7365727898173822E-03\n         2          8   1.1666819680753031E-01   2.5733477296443497E-01   2.1069557171821318E-01   4.1668753958921924E-02\n         2          9   0.0000000000000000E+00   4.7286013175160520E-02   7.9413837493846166E-03   1.4514256010148437E-02\n         2         10   0.0000000000000000E+00   6.1956238700144724E-02   1.2875022708347893E-03   5.5691589190598797E-03\n         2         11   1.1288474798800550E-01   2.4921846311396986E-01   2.0396929608793252E-01   4.0340903647116635E-02\n         2         12   0.0000000000000000E+00   4.5834015403556465E-02   7.6879821993031117E-03   1.4051623633935346E-02\n         2         13   0.0000000000000000E+00   6.0628681726168587E-02   1.2478761447973377E-03   5.4067893155935760E-03\n         2         14   4.3726310895588377E-01   5.7912358529677277E-01   5.2428546819460964E-01   4.6553564989752563E-02\n         2         15   1.0922401540736271E-01   2.4135830635435213E-01   1.9745782401706136E-01   3.9055403118731888E-02\n         2         16   0.0000000000000000E+00   4.4426605487264959E-02   7.4426694128078685E-03   1.3603747043079852E-02\n         2         17   0.0000000000000000E+00   5.9330245849939421E-02   1.2094907898757823E-03   5.2493072318270124E-03\n         2         18   1.0568201804309407E-01   2.3374621312747840E-01   1.9115429342229578E-01   3.7810900566819204E-02\n         2         19   0.0000000000000000E+00   4.3062414170447316E-02   7.2051870958023826E-03   1.3170155290484629E-02\n         2         20   0.0000000000000000E+00   5.8060258366754443E-02   1.1723066517153077E-03   5.0965609427075830E-03\n         2         21   4.1526353693422158E-01   5.5117657816318399E-01   4.9837876938304965E-01   4.4080885733220464E-02\n         2         22   3.9441355763394004E-01   5.2468404243417921E-01   4.7383824270028613E-01   4.1764001877489007E-02\n         2         23   3.6828870553383353E-01   4.9146976040040263E-01   4.4309982108262019E-01   3.8895467135923796E-02\n         2         24   3.4394730666537027E-01   4.6049072861205331E-01   4.1446322175014144E-01   3.6255067064923596E-02\n         2         25   1.3615582143922233E-03   2.9869645505319351E-03   2.2249832258608368E-03   4.1463618943314774E-04\n         2         26   7.1559410835592510E-04   1.6829724827959525E-03   1.3359517263074280E-03   2.7610905134748195E-04\n         2         27   0.0000000000000000E+00   3.2796897453510630E-04   5.0667700470174988E-05   9.2869800839701338E-05\n         2         28   0.0000000000000000E+00   3.0495451868219959E-04   3.8817049539473616E-06   1.9677197469616398E-05\n         2         29   1.7913217752739684E-05   1.4416343121903080E-04   9.7337762834055994E-05   3.3915104345265165E-05\n         2         30   1.4350801600568502E-03   3.1092474332458093E-03   2.3262423102846466E-03   4.4322284233313478E-04\n         2         31   4.0578222110951457E-03   9.2954443134226263E-03   7.4394251433045839E-03   1.5022429052576891E-03\n         2         32   0.0000000000000000E+00   1.7516085308451727E-03   2.8118701127465874E-04   5.1480389928060385E-04\n         2         33   0.0000000000000000E+00   1.3135614801765899E-03   1.7974856475213669E-05   9.8612550314733464E-05\n         2         34   5.3915294593046824E-05   4.3111333581377404E-04   2.9198757141345698E-04   1.0169857980583743E-04\n         2         35   6.6935385626475477E-04   1.4810390635326405E-03   1.1020835791625805E-03   2.0435881733808360E-04\n         2         36   1.1422409795617564E-04   2.8918951717758242E-04   2.2471666006529660E-04   4.9416280493038195E-05\n         2         37   0.0000000000000000E+00   1.4624678200354747E-04   9.6667794830230780E-07   5.5759857610400485E-06\n         2         38   7.4287580192938167E-04   1.6033219462465150E-03   1.2033426635863890E-03   2.3297515669036648E-04\n         2         39   3.4574199085207489E-03   7.9022908432634532E-03   6.3281900770624545E-03   1.2755592651761967E-03\n         2         40   0.0000000000000000E+00   1.4846324055321197E-03   2.3911442883702014E-04   4.3772219909848269E-04\n         2         41   0.0000000000000000E+00   1.1217521078580881E-03   1.5059829469568612E-05   8.4388054763599260E-05\n         2         42   4.0416363887143041E-05   3.2310004407135745E-04   2.1899550793241722E-04   7.6269991365352343E-05\n         2         43   1.6351898556305809E-04   3.6883548742261082E-04   2.7432487870005949E-04   5.0725581211104208E-05\n         2         44   2.0806355775591210E-04   4.5054957097580099E-04   3.4171952172227870E-04   6.9828568268824829E-05\n         2         45   2.5167122266857942E-03   5.7462474397179065E-03   4.6034282726170059E-03   9.2716147843826093E-04\n         2         46   0.0000000000000000E+00   1.0732366256280489E-03   1.7390085487447722E-04   3.1827770235999233E-04\n         2         47   0.0000000000000000E+00   8.4043578218272327E-04   1.0906123334625460E-05   6.3212865791849391E-05\n         2         48   2.2712425622632498E-05   1.8151830895647900E-04   1.2320667730133156E-04   4.2903953573350591E-05\n         2         49   1.3391867334646105E-03   3.0666134591118715E-03   2.4562047072404455E-03   4.9598385408605283E-04\n         2         50   0.0000000000000000E+00   5.6612272788353780E-04   9.2791409512687595E-05   1.6978142113848924E-04\n         2         51   0.0000000000000000E+00   4.9503914535093806E-04   6.0069177520887234E-06   3.6652980675482004E-05\n         3          1   5.8227573092400819E-01   6.1052379418439284E-01   5.9711335386486653E-01   5.7414165889914789E-03\n         3          2   2.5451890253172738E-01   2.7366349168554643E-01   2.6388990983503530E-01   4.0404964859999948E-03\n         3          3   2.4631330079524999E-01   2.6501778408826798E-01   2.5546924456457026E-01   3.9481256424403529E-03\n         3          4   2.3837231037757597E-01   2.5664528060442554E-01   2.4731737962369241E-01   3.8575471108636726E-03\n         3          5   5.5260937541026234E-01   5.8046079679348106E-01   5.6728643198149631E-01   5.6658460358431023E-03\n         3          6   2.3068739607982811E-01   2.4853734592406687E-01   2.3942573134972545E-01   3.7687402931473367E-03\n         3          7   2.2325029807891542E-01   2.4068561774412967E-01   2.3178599028458788E-01   3.6816840863806519E-03\n         3          8   5.3374643661630539E-01   5.6132133307870191E-01   5.4830549999994782E-01   5.6129483675505720E-03\n         3          9   2.1605302304075535E-01   2.3308199813517380E-01   2.2439011241213136E-01   3.5963569359509849E-03\n         3         10   5.0674445024833448E-01   5.3388827869493394E-01   5.2111187743334630E-01   5.5300395272364728E-03\n         3         11   4.8120522029089918E-01   5.0790056452588839E-01   4.9536540156501729E-01   5.4431592109256601E-03\n         3         12   4.5703696466370264E-01   4.8326866508146338E-01   4.7097632909468967E-01   5.3526810302512266E-03\n         3         13   2.2258131156022896E-03   2.7864535677308974E-03   2.5154796748445554E-03   1.1502056409949484E-04\n         3         14   1.4826306857867611E-03   1.6858245114748189E-03   1.5777757941196446E-03   4.0798604551876731E-05\n         3         15   2.3458439580931034E-03   2.9151698094554185E-03   2.6372030917198395E-03   1.1659772223424483E-04\n         3         16   8.2845087958219026E-03   9.2923153202801156E-03   8.7571280859337491E-03   2.0853436102558643E-04\n         3         17   3.4407575556368633E-04   4.2796253868256231E-04   3.8412539837838207E-04   1.7763851622705386E-05\n         3         18   1.1002926088384292E-03   1.3803985042248556E-03   1.2452261872855106E-03   5.7371592494829461E-05\n         3         19   1.2203234513292428E-03   1.5091147459493758E-03   1.3669496041607940E-03   5.9075556378031848E-05\n         3         20   7.0499397350296811E-03   7.8996410580930553E-03   7.4470997200960162E-03   1.7589913695366822E-04\n         4          1   0.0000000000000000E+00   1.7299285853862373E-01   3.5649027052680041E-02   4.7613692505465717E-02\n         4          2   0.0000000000000000E+00   1.5243148551931063E-01   3.5855988109495286E-02   3.9322161692672296E-02\n         4          3   3.3681689049038829E-02   8.2523934463081289E-02   5.3615238262560982E-02   1.1773237214186072E-02\n         4          4   0.0000000000000000E+00   1.4835782666498684E-01   3.4751206958299176E-02   3.8176067070273684E-02\n         4          5   0.0000000000000000E+00   1.4439345927721509E-01   3.3681059405038093E-02   3.7064362147468076E-02\n         4          6   0.0000000000000000E+00   1.4053543193453605E-01   3.2644439947898361E-02   3.5985981810070906E-02\n         4          7   0.0000000000000000E+00   1.6335101386531167E-01   3.2617653307154028E-02   4.4600728736476039E-02\n         4          8   0.0000000000000000E+00   1.3678087385213589E-01   3.1640279063150457E-02   3.4939895085384365E-02\n         4          9   3.0075840169834698E-02   7.6724920430268462E-02   4.8909865165713801E-02   1.1221752430963889E-02\n         4         10   0.0000000000000000E+00   1.3312699263188640E-01   3.0667542008872447E-02   3.3925104008006093E-02\n         4         11   0.0000000000000000E+00   1.5450694062060510E-01   2.9913379083312749E-02   4.1833036073875465E-02\n         4         12   2.6856021400959277E-02   7.1333407130080115E-02   4.4621688379153347E-02   1.0677628342686306E-02\n         4         13   2.3980905651047241E-02   6.6320759203789770E-02   4.0713342392437998E-02   1.0143848410809521E-02\n         4         14   0.0000000000000000E+00   1.4442785246447190E-01   2.6927966349482368E-02   3.8676846027672088E-02\n         4         15   2.0815912950335930E-02   6.0547350097539351E-02   3.6310568612591625E-02   9.4947599104686312E-03\n         4         16   0.0000000000000000E+00   1.3528698534792982E-01   2.4316415148255565E-02   3.5816304322100395E-02\n         4         17   1.8068635032432181E-02   5.5276532534394060E-02   3.2388695418943250E-02   8.8690939963312898E-03\n         4         18   0.0000000000000000E+00   1.2537459699030956E-01   2.1595637743179515E-02   3.2722170168606624E-02\n         4         19   0.0000000000000000E+00   3.2574898162789453E-04   9.3107954389373237E-06   3.6090785183410330E-05\n         4         20   0.0000000000000000E+00   7.8826698674801438E-05   4.1796185611898909E-06   1.1466909619662516E-05\n         4         21   0.0000000000000000E+00   8.5584156178838619E-04   8.6933135329418898E-05   1.7654242493652281E-04\n         4         22   0.0000000000000000E+00   1.1523482884162961E-04   1.0699831397747904E-05   2.2149742381444026E-05\n         4         23   0.0000000000000000E+00   3.9625511292560988E-03   4.8483451165743361E-04   8.7961921131252281E-04\n         4         24   0.0000000000000000E+00   1.8280099849920628E-04   2.0231061476371093E-05   4.0582188369934714E-05\n         4         25   0.0000000000000000E+00   1.5556340961858371E-04   1.3639907181063810E-05   3.0376916144672723E-05\n         4         26   0.0000000000000000E+00   3.2610084960127644E-03   4.1154128350907849E-04   7.3407470001283419E-04\n         4         27   0.0000000000000000E+00   1.2847753283971259E-04   1.4868485107693269E-05   2.9194338773241910E-05\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/weightse.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.1253592163966536E-01 a         1     0     1     1     1\n  3.0404190237274059E-01 a         2     0     1     1     2\n -4.5147904672857030E-02 a         3     0     1     1     3\n  1.3597677469865316E-01 a         4     0     1     1     4\n -1.9431026920255606E-01 a         5     0     1     1     5\n  2.5689290025570044E-01 a         6     0     1     1     6\n -1.7647208947115811E-01 a         7     0     1     1     7\n -1.1420426968601047E-01 a         8     0     1     1     8\n -3.9338329942140204E-02 a         9     0     1     1     9\n -1.1736391080380762E-01 a        10     0     1     1    10\n -3.8506696348120213E-02 a        11     0     1     1    11\n  4.0020942757593027E-02 a        12     0     1     1    12\n -2.7820663035232840E-01 a        13     0     1     1    13\n  1.0144681098642763E-02 a        14     0     1     1    14\n  6.1797660149629459E-02 a        15     0     1     1    15\n  1.3985536107998683E-01 a        16     0     2     1     1\n -1.8897055589869297E-01 a        17     0     2     1     2\n  1.6466980070943155E-01 a        18     0     2     1     3\n -1.2319010563323134E-01 a        19     0     2     1     4\n  8.3401483439245028E-02 a        20     0     2     1     5\n -2.4146445025780924E-01 a        21     0     2     1     6\n  6.0238698911651081E-04 a        22     0     2     1     7\n  1.6159369067271664E-01 a        23     0     2     1     8\n  5.5862136182698155E-02 a        24     0     2     1     9\n -1.2242856776485186E-01 a        25     0     2     1    10\n -4.8186277774590523E-02 a        26     0     2     1    11\n  4.3346577186280356E-02 a        27     0     2     1    12\n  2.0271557381963431E-01 a        28     0     2     1    13\n  1.0507158109814588E-01 a        29     0     2     1    14\n -7.9167243747902891E-02 a        30     0     2     1    15\n  2.8443548016455855E-01 a        31     0     3     1     1\n -2.2057205989024758E-01 a        32     0     3     1     2\n  3.8861642507687130E-02 a        33     0     3     1     3\n -2.4539193935983725E-01 a        34     0     3     1     4\n  1.4687828547951889E-01 a        35     0     3     1     5\n  1.8500923801631686E-01 a        36     0     3     1     6\n -2.6901260228997531E-01 a        37     0     3     1     7\n -1.5028886635139133E-01 a        38     0     3     1     8\n  3.7071134495160904E-02 a        39     0     3     1     9\n  2.0071736637521592E-01 a        40     0     3     1    10\n -5.2419988419607655E-02 a        41     0     3     1    11\n  5.7273075076723766E-02 a        42     0     3     1    12\n  1.6451581188940129E-01 a        43     0     3     1    13\n -5.9062665048237109E-02 a        44     0     3     1    14\n -1.7647256703411443E-01 a        45     0     3     1    15\n  2.7566080065793386E-01 a        46     0     4     1     1\n -6.0144111817233645E-03 a        47     0     4     1     2\n -1.1435628721376682E-01 a        48     0     4     1     3\n -1.4118959125257562E-02 a        49     0     4     1     4\n  1.6568264951463216E-01 a        50     0     4     1     5\n -1.8251202835468575E-01 a        51     0     4     1     6\n -5.3671784055364276E-02 a        52     0     4     1     7\n -7.1802106218291001E-02 a        53     0     4     1     8\n  6.2567831386970238E-02 a        54     0     4     1     9\n  2.4615390142357524E-01 a        55     0     4     1    10\n -2.5143665087623240E-01 a        56     0     4     1    11\n -1.4726375393937458E-01 a        57     0     4     1    12\n  1.0563540005777317E-01 a        58     0     4     1    13\n  1.0804728420817601E-01 a        59     0     4     1    14\n  2.9497264966304500E-02 a        60     0     4     1    15\n  6.8510565449051583E-02 a        61     0     5     1     1\n -1.4968411590793207E-01 a        62     0     5     1     2\n  4.2158129490097659E-02 a        63     0     5     1     3\n  2.0434102812987709E-01 a        64     0     5     1     4\n  2.7385602398181091E-01 a        65     0     5     1     5\n -1.6999723126304600E-01 a        66     0     5     1     6\n  1.6770898931513353E-01 a        67     0     5     1     7\n  1.0787057319542671E-01 a        68     0     5     1     8\n  2.1455895752217008E-01 a        69     0     5     1     9\n  4.6707307180132586E-02 a        70     0     5     1    10\n -1.0208322171413355E-01 a        71     0     5     1    11\n -1.4800589226703545E-01 a        72     0     5     1    12\n -2.4743053152041766E-01 a        73     0     5     1    13\n -2.3404113000135182E-01 a        74     0     5     1    14\n -1.7818187076424688E-01 a        75     0     5     1    15\n -5.5857511203237668E-02 a        76     0     6     1     1\n  1.0236364998682058E-02 a        77     0     6     1     2\n -2.9971049897048307E-01 a        78     0     6     1     3\n -2.3776056328884656E-02 a        79     0     6     1     4\n  1.3472647635639570E-01 a        80     0     6     1     5\n  2.0056775550989936E-01 a        81     0     6     1     6\n  2.5430850106276182E-01 a        82     0     6     1     7\n -1.2291877068683094E-01 a        83     0     6     1     8\n -6.6355733900642033E-02 a        84     0     6     1     9\n -2.1069915830813643E-01 a        85     0     6     1    10\n  1.6690234670588786E-01 a        86     0     6     1    11\n -4.2739092326936803E-02 a        87     0     6     1    12\n  8.1870281584695961E-02 a        88     0     6     1    13\n  3.0083948899101109E-01 a        89     0     6     1    14\n -2.0154552216423727E-01 a        90     0     6     1    15\n  2.7859861344044072E-03 a        91     0     7     1     1\n -1.5811007394553822E-02 a        92     0     7     1     2\n -2.6074181396882207E-01 a        93     0     7     1     3\n -1.3122370948558001E-01 a        94     0     7     1     4\n  3.0900292919252842E-01 a        95     0     7     1     5\n  2.8870993748967849E-01 a        96     0     7     1     6\n -1.6780030544421487E-01 a        97     0     7     1     7\n -1.5731170735541634E-02 a        98     0     7     1     8\n -3.0010916931958892E-01 a        99     0     7     1     9\n -1.3474322847240322E-01 a       100     0     7     1    10\n -1.1987945187281990E-01 a       101     0     7     1    11\n -1.3479684310223680E-01 a       102     0     7     1    12\n -8.0716265464135281E-02 a       103     0     7     1    13\n  1.2211506200727783E-01 a       104     0     7     1    14\n -1.8138118858536692E-01 a       105     0     7     1    15\n -1.7707386992854071E-01 a       106     0     8     1     1\n  1.9134808569201603E-01 a       107     0     8     1     2\n  1.1417884662422660E-01 a       108     0     8     1     3\n -1.0773342990981638E-01 a       109     0     8     1     4\n -2.3004243842443967E-01 a       110     0     8     1     5\n  2.6674064288019922E-01 a       111     0     8     1     6\n 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1.3644326686605304E-01 a       931     1     9     2     1\n  3.7729877522897626E-01 a       932     1     9     2     2\n -3.5436386641769246E-01 a       933     1     9     2     3\n -9.9151489446008698E-02 a       934     1     9     2     4\n  2.8381109315582226E-01 a       935     1     9     2     5\n -2.0324534301029218E-01 a       936     1     9     2     6\n -4.9160080456829909E-02 a       937     1     9     2     7\n  6.3648579865370411E-02 a       938     1     9     2     8\n  3.2147788240359831E-01 a       939     1     9     2     9\n  3.3280420149606099E-01 a       940     1     9     2    10\n -1.9897467067591909E-01 a       941     1     9     2    11\n -3.1622433047716808E-01 a       942     1     9     2    12\n -1.7475937117372756E-01 a       943     1     9     2    13\n -3.8341962269620272E-01 a       944     1     9     2    14\n  4.0349610012878590E-01 a       945     1     9     2    15\n -2.5403174282190738E-01 a       946     1    10     2     1\n  4.3059413351082121E-01 a       947     1    10     2     2\n -1.3360568075426402E-01 a       948     1    10     2     3\n  3.7019273006317355E-01 a       949     1    10     2     4\n -4.1136285462614575E-01 a       950     1    10     2     5\n -2.5151002215199064E-01 a       951     1    10     2     6\n -3.2237623014394623E-01 a       952     1    10     2     7\n -2.6457831093633616E-01 a       953     1    10     2     8\n  3.4356972848828277E-01 a       954     1    10     2     9\n -1.9233609338846311E-02 a       955     1    10     2    10\n -1.1162740971751399E-01 a       956     1    10     2    11\n  3.7319555076279987E-01 a       957     1    10     2    12\n  2.5828175652808810E-01 a       958     1    10     2    13\n -4.5429142498881547E-01 a       959     1    10     2    14\n -1.6314200497715858E-01 a       960     1    10     2    15\n  1.2515620035301158E-02 a       961     1    11     2     1\n  3.4487020206613067E-01 a       962     1    11     2     2\n  3.4447719580625918E-01 a       963     1    11     2     3\n -4.0603072140583646E-01 a       964     1    11     2     4\n -9.8142762723055901E-02 a       965     1    11     2     5\n -3.8790571583707259E-02 a       966     1    11     2     6\n -1.9883276552117882E-01 a       967     1    11     2     7\n  3.2547384877217839E-01 a       968     1    11     2     8\n -3.3331832723348481E-01 a       969     1    11     2     9\n  3.6021741145944905E-02 a       970     1    11     2    10\n  2.4861796439319164E-01 a       971     1    11     2    11\n  2.3693727726742256E-01 a       972     1    11     2    12\n  1.5576714310461692E-01 a       973     1    11     2    13\n -4.0202022298697077E-01 a       974     1    11     2    14\n  5.0560797141121150E-01 a       975     1    11     2    15\n  3.6531925926201292E-01 a       976     1    12     2     1\n -2.4526905639381524E-01 a       977     1    12     2     2\n -3.7883150542713362E-01 a       978     1    12     2     3\n  2.7284073234837358E-01 a       979     1    12     2     4\n -8.1826185206917090E-02 a       980     1    12     2     5\n  3.7612586313106766E-01 a       981     1    12     2     6\n -1.7564553485501214E-01 a       982     1    12     2     7\n -4.9583904437558740E-01 a       983     1    12     2     8\n  3.6361658137829256E-01 a       984     1    12     2     9\n  1.6344303178275990E-01 a       985     1    12     2    10\n -1.3795643359648330E-02 a       986     1    12     2    11\n -1.6102225039929316E-01 a       987     1    12     2    12\n  9.4605783110645658E-02 a       988     1    12     2    13\n  1.0906725763980238E-01 a       989     1    12     2    14\n -3.8324194341613466E-01 a       990     1    12     2    15\n -3.2132692492549775E-01 a       991     1    13     2     1\n -1.4494614021858748E-01 a       992     1    13     2     2\n  3.4552446860046832E-01 a       993     1    13     2     3\n -4.4011158481320484E-01 a       994     1    13     2     4\n -4.2971694791576293E-01 a       995     1    13     2     5\n  1.5025591773442287E-01 a       996     1    13     2     6\n -3.4583017491540063E-01 a       997     1    13     2     7\n -2.4481386677383274E-01 a       998     1    13     2     8\n -1.0512385587936150E-01 a       999     1    13     2     9\n -7.3423118032087495E-02 a      1000     1    13     2    10\n -3.2875665173754998E-01 a      1001     1    13     2    11\n -1.4419535245627321E-01 a      1002     1    13     2    12\n -4.5188095133431022E-01 a      1003     1    13     2    13\n -3.9733720691568830E-01 a      1004     1    13     2    14\n  4.0223312675760327E-02 a      1005     1    13     2    15\n -5.0249649733230838E-02 a      1006     1    14     2     1\n  4.3417316482091899E-02 a      1007     1    14     2     2\n  2.2422616947699814E-01 a      1008     1    14     2     3\n  3.7946675127903917E-01 a      1009     1    14     2     4\n -2.6574148887743304E-01 a      1010     1    14     2     5\n -3.2990082854435089E-02 a      1011     1    14     2     6\n -9.6920770873972481E-02 a      1012     1    14     2     7\n -6.4148427319012782E-02 a      1013     1    14     2     8\n -3.5915894681194355E-01 a      1014     1    14     2     9\n -4.6953452001118928E-01 a      1015     1    14     2    10\n -4.5680798751588908E-01 a      1016     1    14     2    11\n  3.2999267666625104E-01 a      1017     1    14     2    12\n -7.7737973492414368E-03 a      1018     1    14     2    13\n -3.8275966656257365E-01 a      1019     1    14     2    14\n  1.5381065444643185E-01 a      1020     1    14     2    15\n -3.5812157081643603E-01 a      1021     1    15     2     1\n  4.1205237734311356E-01 a      1022     1    15     2     2\n -3.8055171312223864E-02 a      1023     1    15     2     3\n  7.0799793699737129E-02 a      1024     1    15     2     4\n  2.8786670967897643E-01 a      1025     1    15     2     5\n  3.2984689478713530E-01 a      1026     1    15     2     6\n -4.4551660271651111E-01 a      1027     1    15     2     7\n  4.4569437621076419E-01 a      1028     1    15     2     8\n -3.3740270307779352E-01 a      1029     1    15     2     9\n  2.9324017892669846E-01 a      1030     1    15     2    10\n -3.4986909281870399E-01 a      1031     1    15     2    11\n  1.0320715461102833E-01 a      1032     1    15     2    12\n -1.4407523908550113E-01 a      1033     1    15     2    13\n  1.8522801988857757E-01 a      1034     1    15     2    14\n -1.6388437419302279E-01 a      1035     1    15     2    15\n -1.0651597949369029E-01 b      1036     2     1\n -4.6214823188455247E-02 b      1037     2     2\n -6.7378865015147352E-02 b      1038     2     3\n  3.3389482689237075E-02 b      1039     2     4\n -6.7818630308471382E-03 b      1040     2     5\n -5.8973550995914441E-02 b      1041     2     6\n -1.9394733779303994E-01 b      1042     2     7\n  1.1095072687189452E-02 b      1043     2     8\n  5.0159632715172264E-02 b      1044     2     9\n -6.2746295915221517E-02 b      1045     2    10\n -1.4546752430789264E-01 b      1046     2    11\n -3.0600760526500511E-02 b      1047     2    12\n  4.9641443699042623E-02 b      1048     2    13\n -4.9333456952938212E-02 b      1049     2    14\n  2.6742154765131393E-01 b      1050     2    15\n -8.3883528158345988E-01 a      1051     2     1     3     1\n  2.0479771224610402E-01 a      1052     2     2     3     1\n -5.7876192701594491E-02 a      1053     2     3     3     1\n  5.6970469164230297E-01 a      1054     2     4     3     1\n  5.6700916559177439E-01 a      1055     2     5     3     1\n  6.7057946508975974E-01 a      1056     2     6     3     1\n -1.0528655224804437E+00 a      1057     2     7     3     1\n  9.6452026866962948E-01 a      1058     2     8     3     1\n  4.4108627172001574E-01 a      1059     2     9     3     1\n -5.7199537577439885E-01 a      1060     2    10     3     1\n -8.7267085959396329E-01 a      1061     2    11     3     1\n -2.7530410185408565E-02 a      1062     2    12     3     1\n  7.3158132816576393E-01 a      1063     2    13     3     1\n -6.3892084292777318E-01 a      1064     2    14     3     1\n  1.4132258550276757E+00 a      1065     2    15     3     1\n  1.1514881992781666E-01 b      1066     3     1\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/weightse.012.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -1.6191494874911935E-01 a         1     0     1     1     1\n  2.0175206414055524E-01 a         2     0     1     1     2\n -2.0176415600188932E-01 a         3     0     1     1     3\n  1.5999207878188534E-01 a         4     0     1     1     4\n -2.8928259119466843E-01 a         5     0     1     1     5\n -7.9691068650974584E-02 a         6     0     1     1     6\n -1.7826922511544654E-01 a         7     0     1     1     7\n -2.9068722056027417E-02 a         8     0     1     1     8\n -1.4436457651707085E-01 a         9     0     1     1     9\n  1.5353263382479534E-01 a        10     0     1     1    10\n -1.3086856845618353E-01 a        11     0     1     1    11\n -1.6816647321299838E-01 a        12     0     1     1    12\n  1.1301854785759721E-01 a        13     0     1     1    13\n  1.5273244189172422E-01 a        14     0     1     1    14\n  1.5847374766263075E-01 a        15     0     1     1    15\n  2.7958194217609322E-01 a        16     0     2     1     1\n  1.9947979413247074E-01 a        17     0     2     1     2\n -6.8664674343611579E-02 a        18     0     2     1     3\n -3.1228534997084639E-01 a        19     0     2     1     4\n -2.1792338668342869E-02 a        20     0     2     1     5\n -7.6184649921553646E-02 a        21     0     2     1     6\n  1.1780203141391397E-01 a        22     0     2     1     7\n  8.7152643069269786E-02 a        23     0     2     1     8\n  2.0951490252274355E-01 a        24     0     2     1     9\n  6.0287366670247642E-03 a        25     0     2     1    10\n -1.6079016487637987E-01 a        26     0     2     1    11\n  2.7716391485236769E-01 a        27     0     2     1    12\n  2.7818662295462043E-01 a        28     0     2     1    13\n  1.4737678407497284E-01 a        29     0     2     1    14\n  1.2275542362056364E-01 a        30     0     2     1    15\n  6.7741884980486597E-02 a        31     0     3     1     1\n  2.4083488870391895E-01 a        32     0     3     1     2\n  1.4112455051804588E-02 a        33     0     3     1     3\n  8.7178401636244969E-03 a        34     0     3     1     4\n  2.4991512589190046E-01 a        35     0     3     1     5\n  3.6667296213528391E-02 a        36     0     3     1     6\n -3.2191332373638354E-01 a        37     0     3     1     7\n -1.3115320737969779E-01 a        38     0     3     1     8\n  2.1373483431000187E-01 a        39     0     3     1     9\n -1.4961033221424491E-01 a        40     0     3     1    10\n  8.6659803559786350E-02 a        41     0     3     1    11\n  6.8953458389252251E-02 a        42     0     3     1    12\n  9.0735467665892383E-02 a        43     0     3     1    13\n -2.0919880232280824E-01 a        44     0     3     1    14\n -4.7813748750595450E-02 a        45     0     3     1    15\n  5.6034237598775759E-02 a        46     0     4     1     1\n -1.0687902107529877E-01 a        47     0     4     1     2\n -1.8117107348449610E-01 a        48     0     4     1     3\n  2.4161486230559828E-01 a        49     0     4     1     4\n  2.6907123594595117E-01 a        50     0     4     1     5\n -2.4812347186035219E-01 a        51     0     4     1     6\n  9.1547169219238195E-02 a        52     0     4     1     7\n  1.6876799981281171E-01 a        53     0     4     1     8\n  2.1956451902066848E-01 a        54     0     4     1     9\n  1.5406765548703921E-01 a        55     0     4     1    10\n -3.0687440322751514E-01 a        56     0     4     1    11\n  3.9586224563040166E-02 a        57     0     4     1    12\n  2.8995020881548039E-01 a        58     0     4     1    13\n  1.6875025794027956E-01 a        59     0     4     1    14\n  1.6595862884335061E-01 a        60     0     4     1    15\n -6.0870157914056651E-02 a        61     0     5     1     1\n -2.6483612315170113E-01 a        62     0     5     1     2\n -2.6053551990311663E-01 a        63     0     5     1     3\n -1.9692928976227597E-01 a        64     0     5     1     4\n -2.6477306197707706E-01 a        65     0     5     1     5\n -1.1006234326799577E-01 a        66     0     5     1     6\n -1.1781422515466813E-01 a        67     0     5     1     7\n  4.6706207188567155E-02 a        68     0     5     1     8\n -2.7384447389178840E-01 a        69     0     5     1     9\n -7.1405615606388889E-02 a        70     0     5     1    10\n  5.9627840543751677E-02 a        71     0     5     1    11\n -2.7469765073619340E-01 a        72     0     5     1    12\n -9.3967776737111458E-02 a        73     0     5     1    13\n  1.7470254691218615E-01 a        74     0     5     1    14\n  2.4059200091475641E-01 a        75     0     5     1    15\n  4.4881617572298201E-02 a        76     0     6     1     1\n -2.9582410217831329E-01 a        77     0     6     1     2\n  3.2044034582400438E-01 a        78     0     6     1     3\n -2.1288465009234953E-01 a        79     0     6     1     4\n  2.8668521236273065E-01 a        80     0     6     1     5\n -8.9252766422574278E-02 a        81     0     6     1     6\n -3.2053215010876507E-01 a        82     0     6     1     7\n -1.6090609706522260E-01 a        83     0     6     1     8\n -1.9480248202625505E-02 a        84     0     6     1     9\n  2.8170848719543806E-01 a        85     0     6     1    10\n  1.0953986272185857E-01 a        86     0     6     1    11\n -1.5831389959990901E-02 a        87     0     6     1    12\n -2.8659517070916957E-01 a        88     0     6     1    13\n  1.7862790772573631E-01 a        89     0     6     1    14\n  2.6391241981506453E-01 a        90     0     6     1    15\n  6.8262621185049818E-02 a        91     0     7     1     1\n -1.5795028768855196E-01 a        92     0     7     1     2\n -3.2652001562565747E-01 a        93     0     7     1     3\n -1.4297802334911175E-01 a        94     0     7     1     4\n -3.4549790463085456E-02 a        95     0     7     1     5\n  7.1654614907441849E-02 a        96     0     7     1     6\n  3.6095536445822984E-01 a        97     0     7     1     7\n -1.5117443747270615E-01 a        98     0     7     1     8\n  5.5705310651552563E-02 a        99     0     7     1     9\n -2.0650293713810636E-01 a       100     0     7     1    10\n  2.2611551374747579E-01 a       101     0     7     1    11\n -2.0020290401532345E-02 a       102     0     7     1    12\n  4.0436118744962786E-02 a       103     0     7     1    13\n  3.5500681801431677E-02 a       104     0     7     1    14\n  3.0661265697716716E-01 a       105     0     7     1    15\n -1.0550624725744780E-01 a       106     0     8     1     1\n -2.7355090195349541E-01 a       107     0     8     1     2\n -2.7923881603709216E-01 a       108     0     8     1     3\n -2.9211195712139901E-02 a       109     0     8     1     4\n -2.5268671798172837E-01 a       110     0     8     1     5\n -2.1399356664472899E-01 a       111     0     8     1     6\n  1.3453379712495747E-01 a       112     0     8     1     7\n  3.5245687474181331E-02 a       113     0     8     1     8\n  1.4480906104434244E-01 a       114     0     8     1     9\n  2.7286431257594257E-01 a       115     0     8     1    10\n -6.0435382349653980E-03 a       116     0     8     1    11\n -2.6424268168871373E-01 a       117     0     8     1    12\n -1.9904215428226843E-01 a       118     0     8     1    13\n  2.4969200418421941E-01 a       119     0     8     1    14\n -5.5101896939835214E-02 a       120     0     8     1    15\n  2.8099636456210003E-01 a       121     0     9     1     1\n -1.3157580439544084E-02 a       122     0     9     1     2\n  2.7695667065481200E-01 a       123     0     9     1     3\n -2.6365060726805976E-02 a       124     0     9     1     4\n  1.9815652901896672E-02 a       125     0     9     1     5\n -5.2695882698124065E-02 a       126     0     9     1     6\n -1.7674987928500221E-01 a       127     0     9     1     7\n 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4.0897248532841951E-01 a       915     1     9     2    15\n -3.0421048412040891E-01 a       916     1    10     2     1\n -2.4179518666175095E-01 a       917     1    10     2     2\n  3.5168606169358818E-01 a       918     1    10     2     3\n  3.8493949921912052E-01 a       919     1    10     2     4\n -2.6621077105414914E-01 a       920     1    10     2     5\n -4.2682847792946980E-03 a       921     1    10     2     6\n -2.0526894359634873E-01 a       922     1    10     2     7\n -4.1765146361268837E-02 a       923     1    10     2     8\n -3.7444913054679635E-01 a       924     1    10     2     9\n -2.3284956662105949E-01 a       925     1    10     2    10\n  1.5081215277714194E-01 a       926     1    10     2    11\n -8.6288072467267399E-02 a       927     1    10     2    12\n -1.8422579191087976E-01 a       928     1    10     2    13\n  2.0788942789554660E-01 a       929     1    10     2    14\n -3.1803083645962649E-01 a       930     1    10     2    15\n -2.5964291976027853E-01 a       931     1    11     2     1\n  1.2062051678484029E-01 a       932     1    11     2     2\n  8.7124669220320625E-02 a       933     1    11     2     3\n  3.7494468666787345E-01 a       934     1    11     2     4\n -1.7165477113535721E-01 a       935     1    11     2     5\n  4.4657866680166491E-01 a       936     1    11     2     6\n -3.3711149926876882E-01 a       937     1    11     2     7\n  1.8345029051847897E-01 a       938     1    11     2     8\n  1.1939249890490312E-01 a       939     1    11     2     9\n  1.3017276551111104E-01 a       940     1    11     2    10\n  4.4317146721640777E-01 a       941     1    11     2    11\n  2.6280997726036409E-01 a       942     1    11     2    12\n  1.6734009233450980E-01 a       943     1    11     2    13\n -3.0541590484379971E-01 a       944     1    11     2    14\n  2.9191209592342759E-01 a       945     1    11     2    15\n -4.1804330027189196E-01 a       946     1    12     2     1\n -4.3531345060333487E-01 a       947     1    12     2     2\n -3.7901310847188430E-01 a       948     1    12     2     3\n -1.8129537931708184E-01 a       949     1    12     2     4\n  1.8892589390156214E-01 a       950     1    12     2     5\n  4.1539917640233409E-01 a       951     1    12     2     6\n  3.8864457980353206E-01 a       952     1    12     2     7\n -9.0721977008801670E-03 a       953     1    12     2     8\n -3.5903759624115267E-01 a       954     1    12     2     9\n  2.5980816147870439E-01 a       955     1    12     2    10\n  4.1553023816176932E-01 a       956     1    12     2    11\n  2.1084931879700014E-01 a       957     1    12     2    12\n  3.4282768795081214E-01 a       958     1    12     2    13\n  6.9434569873708510E-02 a       959     1    12     2    14\n -1.8780785008115916E-01 a       960     1    12     2    15\n  2.6062841972838796E-01 a       961     1    13     2     1\n  4.0500301769925617E-01 a       962     1    13     2     2\n  2.0216334098412453E-01 a       963     1    13     2     3\n -3.0890298028855262E-01 a       964     1    13     2     4\n -1.8342006421244919E-01 a       965     1    13     2     5\n -2.3136210113470970E-01 a       966     1    13     2     6\n  6.9113832873372250E-02 a       967     1    13     2     7\n  2.7504876016711777E-01 a       968     1    13     2     8\n -3.5066049475335198E-01 a       969     1    13     2     9\n -2.0153247372910818E-01 a       970     1    13     2    10\n -3.4511975465930067E-01 a       971     1    13     2    11\n  1.3279898926187869E-01 a       972     1    13     2    12\n -2.9226406987790154E-01 a       973     1    13     2    13\n -6.1282422439029226E-02 a       974     1    13     2    14\n -1.6436151578612346E-01 a       975     1    13     2    15\n  2.2235432332560853E-02 a       976     1    14     2     1\n -2.2396650822765163E-01 a       977     1    14     2     2\n -2.2601953662655991E-01 a       978     1    14     2     3\n -1.1988308323770817E-01 a       979     1    14     2     4\n -1.5620574333347723E-02 a       980     1    14     2     5\n  3.0369768931153746E-02 a       981     1    14     2     6\n -8.1832210601528232E-02 a       982     1    14     2     7\n  3.7766257272138237E-01 a       983     1    14     2     8\n  3.9720294664862638E-01 a       984     1    14     2     9\n  4.4912946671154347E-01 a       985     1    14     2    10\n -2.3614531953855272E-01 a       986     1    14     2    11\n -2.6422926417904297E-01 a       987     1    14     2    12\n -2.8228107165984140E-01 a       988     1    14     2    13\n -2.0347072482203082E-01 a       989     1    14     2    14\n -1.7203035998130681E-01 a       990     1    14     2    15\n -2.8714931625254281E-01 a       991     1    15     2     1\n -3.0669224535584144E-01 a       992     1    15     2     2\n  4.5864297207591984E-02 a       993     1    15     2     3\n -1.4009566618406147E-01 a       994     1    15     2     4\n -5.4525012623544838E-02 a       995     1    15     2     5\n  1.2735933180008085E-01 a       996     1    15     2     6\n -2.0858510129032778E-02 a       997     1    15     2     7\n  3.2924819310370174E-01 a       998     1    15     2     8\n  3.9034407810027899E-01 a       999     1    15     2     9\n -1.6096969809308725E-01 a      1000     1    15     2    10\n -3.3604858815234268E-01 a      1001     1    15     2    11\n -1.7897800882927956E-01 a      1002     1    15     2    12\n  4.6429118976512584E-02 a      1003     1    15     2    13\n  3.5343196793056553E-01 a      1004     1    15     2    14\n -2.4414766837691659E-01 a      1005     1    15     2    15\n -2.4584786494858651E-02 b      1006     2     1\n -9.8167345919322802E-02 b      1007     2     2\n  4.5872445287709056E-02 b      1008     2     3\n -1.8530950869542862E-02 b      1009     2     4\n  1.4543407477737164E-01 b      1010     2     5\n  9.5715908882993191E-03 b      1011     2     6\n -9.6149886583815236E-02 b      1012     2     7\n -4.4042691156967573E-02 b      1013     2     8\n -8.9458735114735052E-02 b      1014     2     9\n  6.3392794827471996E-02 b      1015     2    10\n -5.4966327646396584E-03 b      1016     2    11\n -1.4037647855881928E-02 b      1017     2    12\n -4.5958595925737110E-02 b      1018     2    13\n -5.7882629280518592E-02 b      1019     2    14\n -1.2915041165040057E-02 b      1020     2    15\n  8.0880225455891939E-03 a      1021     2     1     3     1\n  9.0292476619799855E-01 a      1022     2     2     3     1\n -2.9714092290475952E-01 a      1023     2     3     3     1\n  1.5075652296633174E-01 a      1024     2     4     3     1\n -1.0324044674574613E+00 a      1025     2     5     3     1\n -2.8667798272339725E-02 a      1026     2     6     3     1\n  8.9100625064759376E-01 a      1027     2     7     3     1\n  4.2287629633268620E-01 a      1028     2     8     3     1\n -9.6874864735896848E-01 a      1029     2     9     3     1\n -5.4363648380336427E-01 a      1030     2    10     3     1\n -1.3098774046712494E-01 a      1031     2    11     3     1\n -1.0059597049581397E+00 a      1032     2    12     3     1\n  1.1428002912801736E+00 a      1033     2    13     3     1\n  3.9192082335611839E-01 a      1034     2    14     3     1\n -8.5302298285186673E-01 a      1035     2    15     3     1\n -1.3095782826138994E-01 b      1036     3     1\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/weightse.013.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -6.4394688081091028E-02 a         1     0     1     1     1\n -1.3584341925158536E-01 a         2     0     1     1     2\n -8.4703243268489631E-02 a         3     0     1     1     3\n -1.0641495552880206E-01 a         4     0     1     1     4\n -2.7804198668432140E-01 a         5     0     1     1     5\n  1.3635334837420041E-01 a         6     0     1     1     6\n  2.3701279952566834E-01 a         7     0     1     1     7\n  3.1901508452682142E-01 a         8     0     1     1     8\n -1.9694480519037411E-01 a         9     0     1     1     9\n -4.0054029794180457E-01 a        10     0     1     1    10\n -3.1584533778595597E-01 a        11     0     1     1    11\n  1.2820476089424557E-01 a        12     0     1     1    12\n -1.8313148189649492E-01 a        13     0     1     1    13\n -2.9869808184049235E-02 a        14     0     1     1    14\n -3.4851679481635733E-01 a        15     0     1     1    15\n  3.5518092620362057E-01 a        16     0     2     1     1\n -2.3448781552245876E-01 a        17     0     2     1     2\n -3.1147098697540720E-01 a        18     0     2     1     3\n -2.4018794031272239E-01 a        19     0     2     1     4\n  2.7915407218043997E-01 a        20     0     2     1     5\n  3.8241244436353589E-01 a        21     0     2     1     6\n -3.7801021473390806E-01 a        22     0     2     1     7\n  5.1558292946603072E-03 a        23     0     2     1     8\n  1.1070490828690535E-01 a        24     0     2     1     9\n  4.0132005068626811E-02 a        25     0     2     1    10\n -1.0431704658009880E-01 a        26     0     2     1    11\n  3.2580715381273584E-01 a        27     0     2     1    12\n  3.6951916312268085E-01 a        28     0     2     1    13\n -4.2206773030334802E-03 a        29     0     2     1    14\n  1.5743570067664278E-01 a        30     0     2     1    15\n  1.1486657769441022E-01 a        31     0     3     1     1\n -2.3060469844124479E-01 a        32     0     3     1     2\n  2.0193470272578487E-01 a        33     0     3     1     3\n -1.8419667671221246E-01 a        34     0     3     1     4\n  8.1784033445704729E-02 a        35     0     3     1     5\n -4.0820789442525436E-02 a        36     0     3     1     6\n  4.8766282405871449E-02 a        37     0     3     1     7\n -1.9949528466838537E-01 a        38     0     3     1     8\n  2.1812093385437520E-02 a        39     0     3     1     9\n  2.0264913578143964E-01 a        40     0     3     1    10\n -2.2648745239344567E-01 a        41     0     3     1    11\n -3.6492017547340633E-01 a        42     0     3     1    12\n  3.2545425836692954E-01 a        43     0     3     1    13\n  1.3447993024115701E-02 a        44     0     3     1    14\n -1.0826263686532367E-01 a        45     0     3     1    15\n  4.1480591383339781E-02 a        46     0     4     1     1\n -3.0626671353988930E-02 a        47     0     4     1     2\n  2.1442933215203824E-02 a        48     0     4     1     3\n -1.9499856678182839E-02 a        49     0     4     1     4\n -4.0890345421517554E-01 a        50     0     4     1     5\n -3.4648675624477226E-01 a        51     0     4     1     6\n -1.4324526554105380E-01 a        52     0     4     1     7\n  3.0712613764260377E-01 a        53     0     4     1     8\n -3.6336281302309564E-01 a        54     0     4     1     9\n -2.9485055031321816E-01 a        55     0     4     1    10\n  2.3273643553554271E-01 a        56     0     4     1    11\n  3.6662557904316140E-01 a        57     0     4     1    12\n  3.1300063339014894E-01 a        58     0     4     1    13\n  3.9740514253882953E-01 a        59     0     4     1    14\n  1.0249886957636591E-01 a        60     0     4     1    15\n  7.6144734733642111E-02 a        61     0     5     1     1\n -6.3174815384586247E-02 a        62     0     5     1     2\n  3.8011167507007454E-01 a        63     0     5     1     3\n  2.6652561749142073E-01 a        64     0     5     1     4\n  2.4959938667354439E-01 a        65     0     5     1     5\n -3.6081956078432542E-01 a        66     0     5     1     6\n -2.5404368458897686E-01 a        67     0     5     1     7\n -3.5351329402512532E-01 a        68     0     5     1     8\n -2.5494022263387273E-01 a        69     0     5     1     9\n -2.5835297643620742E-01 a        70     0     5     1    10\n -2.6523151442493093E-01 a        71     0     5     1    11\n  4.7647520646092408E-02 a        72     0     5     1    12\n  1.7557651310167380E-01 a        73     0     5     1    13\n  4.3455754468263129E-02 a        74     0     5     1    14\n -2.6927040544053227E-01 a        75     0     5     1    15\n -2.1907707300952639E-01 a        76     0     6     1     1\n -2.1359819267364580E-01 a        77     0     6     1     2\n  2.1800677271263277E-01 a        78     0     6     1     3\n  1.7515438720695498E-01 a        79     0     6     1     4\n  7.8160799772921133E-02 a        80     0     6     1     5\n  3.2769391259754843E-01 a        81     0     6     1     6\n -2.9291438972895939E-01 a        82     0     6     1     7\n -3.1663151925239513E-01 a        83     0     6     1     8\n -2.1133909830047695E-01 a        84     0     6     1     9\n -2.4413287365279113E-01 a        85     0     6     1    10\n  4.5224369020302763E-01 a        86     0     6     1    11\n -1.5237135874372879E-01 a        87     0     6     1    12\n  3.4017821376236074E-01 a        88     0     6     1    13\n -3.8972336968156968E-01 a        89     0     6     1    14\n -3.8460811514376630E-01 a        90     0     6     1    15\n  7.1012547262910758E-02 a        91     0     7     1     1\n -3.7311658381733709E-01 a        92     0     7     1     2\n -1.5738364836550139E-01 a        93     0     7     1     3\n -2.5589224328092197E-01 a        94     0     7     1     4\n -3.3841906517982046E-01 a        95     0     7     1     5\n  1.4554646667665555E-01 a        96     0     7     1     6\n  6.1786996778394818E-03 a        97     0     7     1     7\n  1.8482478525318197E-01 a        98     0     7     1     8\n  1.0644417287465882E-01 a        99     0     7     1     9\n -1.9750825035905820E-01 a       100     0     7     1    10\n -3.2083474239688520E-01 a       101     0     7     1    11\n -3.1873672159544192E-01 a       102     0     7     1    12\n  8.2223058071682398E-02 a       103     0     7     1    13\n  1.1131752730712900E-01 a       104     0     7     1    14\n -3.8130379357112970E-01 a       105     0     7     1    15\n -2.0748621559544705E-01 a       106     0     8     1     1\n  1.7860871324798869E-01 a       107     0     8     1     2\n -2.6310491227537475E-01 a       108     0     8     1     3\n  3.6199250920033677E-01 a       109     0     8     1     4\n  3.3226280878390702E-01 a       110     0     8     1     5\n -1.4697091301979587E-01 a       111     0     8     1     6\n  2.0370514551583588E-01 a       112     0     8     1     7\n  8.2345306785423247E-02 a       113     0     8     1     8\n  3.9020671733108320E-01 a       114     0     8     1     9\n -9.6067592055252657E-02 a       115     0     8     1    10\n  2.5895088756912571E-01 a       116     0     8     1    11\n -2.5137175212578217E-01 a       117     0     8     1    12\n -3.6539304637443332E-01 a       118     0     8     1    13\n  2.6557054155352122E-01 a       119     0     8     1    14\n  1.5947541101874380E-01 a       120     0     8     1    15\n -3.3411980115807938E-01 a       121     0     9     1     1\n  1.4080532237500934E-01 a       122     0     9     1     2\n  4.2817154498023181E-02 a       123     0     9     1     3\n  1.4997281963897519E-02 a       124     0     9     1     4\n -5.8822644034011481E-02 a       125     0     9     1     5\n -3.5836981506505876E-02 a       126     0     9     1     6\n  3.5138719652038097E-01 a       127     0     9     1     7\n -2.9276028725996872E-01 a       128     0     9     1     8\n  1.7315078800309391E-01 a       129     0     9     1     9\n  1.7574554699791500E-01 a       130     0     9     1    10\n  1.8092535540171598E-01 a       131     0     9     1    11\n  1.8500642207257334E-01 a       132     0     9     1    12\n -1.1261210338611310E-01 a       133     0     9     1    13\n  2.5145170170501913E-01 a       134     0     9     1    14\n -6.0397388746409909E-02 a       135     0     9     1    15\n  5.9313810274456209E-02 a       136     0    10     1     1\n  5.2433523930738565E-02 a       137     0    10     1     2\n -4.0524691818446279E-01 a       138     0    10     1     3\n -3.2506744702974555E-01 a       139     0    10     1     4\n -1.1992273186452827E-01 a       140     0    10     1     5\n -2.6514088668434205E-01 a       141     0    10     1     6\n -2.6569692195271533E-01 a       142     0    10     1     7\n -3.4707040258042793E-01 a       143     0    10     1     8\n -2.7157850886440688E-01 a       144     0    10     1     9\n -4.3061619105036843E-02 a       145     0    10     1    10\n  4.1322003639363225E-01 a       146     0    10     1    11\n  2.4295589263903444E-01 a       147     0    10     1    12\n  2.7962397388378540E-01 a       148     0    10     1    13\n  1.5719818448373174E-01 a       149     0    10     1    14\n  4.0391749976528796E-01 a       150     0    10     1    15\n  2.0495190109367767E-01 a       151     0    11     1     1\n  3.9480958644155834E-01 a       152     0    11     1     2\n -2.2518479388151236E-01 a       153     0    11     1     3\n -1.3460086252582576E-01 a       154     0    11     1     4\n -1.3756987415099425E-01 a       155     0    11     1     5\n  1.9055884098084869E-01 a       156     0    11     1     6\n -8.5708287350307458E-02 a       157     0    11     1     7\n -1.0963223359342951E-02 a       158     0    11     1     8\n  8.2885290986400545E-02 a       159     0    11     1     9\n  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-1.4109957461576955E-01 a       435     1     8     2    15\n -2.1934340768442911E-01 a       436     1     9     2     1\n  3.0457562879371175E-01 a       437     1     9     2     2\n  3.9015619252219086E-01 a       438     1     9     2     3\n  1.8109538465477024E-01 a       439     1     9     2     4\n -3.4161055531661200E-01 a       440     1     9     2     5\n  1.0081525213343895E-01 a       441     1     9     2     6\n  3.0810436277112585E-01 a       442     1     9     2     7\n -2.2865502825720457E-02 a       443     1     9     2     8\n -1.7644494730442142E-03 a       444     1     9     2     9\n  4.3779691456932147E-02 a       445     1     9     2    10\n -1.9918174881134273E-02 a       446     1     9     2    11\n  4.1876843327623209E-01 a       447     1     9     2    12\n -4.2631904731865622E-02 a       448     1     9     2    13\n -3.5500024143516701E-01 a       449     1     9     2    14\n -2.3345857744985379E-01 a       450     1     9     2    15\n -1.4361319303225528E-01 a       451     1    10     2     1\n -1.6936431578462927E-01 a       452     1    10     2     2\n -2.5265375028470971E-01 a       453     1    10     2     3\n  4.1017505428019452E-01 a       454     1    10     2     4\n -1.8239521521179955E-01 a       455     1    10     2     5\n  4.0314825130196102E-01 a       456     1    10     2     6\n  9.4513028368587992E-02 a       457     1    10     2     7\n -4.2758251883416587E-02 a       458     1    10     2     8\n  4.0842872737552510E-01 a       459     1    10     2     9\n -4.5942964246066961E-02 a       460     1    10     2    10\n -3.6977344230870013E-01 a       461     1    10     2    11\n -4.3949014740602803E-02 a       462     1    10     2    12\n -4.0892966623369109E-01 a       463     1    10     2    13\n  9.9236091733964221E-02 a       464     1    10     2    14\n  2.7499207268974002E-01 a       465     1    10     2    15\n -3.5077132031555569E-01 a       466     1    11     2     1\n  9.4475023139458172E-02 a       467     1    11     2     2\n  2.1098704318382425E-01 a       468     1    11     2     3\n  3.2185257835374592E-01 a       469     1    11     2     4\n -1.8950397760286700E-01 a       470     1    11     2     5\n -1.4602157087534395E-01 a       471     1    11     2     6\n -2.2283941304655777E-01 a       472     1    11     2     7\n -4.1997782500131603E-01 a       473     1    11     2     8\n  3.7882364901445098E-01 a       474     1    11     2     9\n  3.9384493778702850E-05 a       475     1    11     2    10\n  2.8436909389825110E-01 a       476     1    11     2    11\n  3.0365924537027639E-01 a       477     1    11     2    12\n  3.0804458598049572E-01 a       478     1    11     2    13\n -3.6355427224288006E-01 a       479     1    11     2    14\n  3.5961289051759648E-01 a       480     1    11     2    15\n  2.7735235109854123E-02 a       481     1    12     2     1\n -2.8743336818348147E-01 a       482     1    12     2     2\n -4.0638752617798601E-01 a       483     1    12     2     3\n -2.3280816414137467E-01 a       484     1    12     2     4\n  3.3400130208207546E-01 a       485     1    12     2     5\n  2.0026119401344697E-01 a       486     1    12     2     6\n -2.2459394340601208E-01 a       487     1    12     2     7\n -1.8305233548383276E-01 a       488     1    12     2     8\n  2.7253290735128616E-01 a       489     1    12     2     9\n  2.4828281132163421E-01 a       490     1    12     2    10\n  1.1016673768179491E-01 a       491     1    12     2    11\n -3.6442936378510282E-01 a       492     1    12     2    12\n  3.6115661285472922E-01 a       493     1    12     2    13\n -4.5393117313664695E-02 a       494     1    12     2    14\n -1.0702756088858281E-01 a       495     1    12     2    15\n -1.2350298732576627E-01 a       496     1    13     2     1\n  3.9191522590514211E-01 a       497     1    13     2     2\n -5.8263096345629011E-04 a       498     1    13     2     3\n -3.5854147733513808E-01 a       499     1    13     2     4\n  2.1041046324063398E-01 a       500     1    13     2     5\n -7.5373685358853179E-02 a       501     1    13     2     6\n  4.2340008516838029E-01 a       502     1    13     2     7\n  6.7904930861856339E-02 a       503     1    13     2     8\n -7.6140221525758237E-02 a       504     1    13     2     9\n  4.0842541592041293E-01 a       505     1    13     2    10\n  1.0614556941221857E-01 a       506     1    13     2    11\n -8.8016639756747159E-02 a       507     1    13     2    12\n -2.8398900886726725E-01 a       508     1    13     2    13\n  4.2131305267533871E-02 a       509     1    13     2    14\n -1.5857480511697350E-01 a       510     1    13     2    15\n  2.8677092638696355E-01 a       511     1    14     2     1\n  4.7065766324339092E-02 a       512     1    14     2     2\n -3.1637441952746559E-01 a       513     1    14     2     3\n -2.4552263717245074E-01 a       514     1    14     2     4\n  1.5611874337055995E-01 a       515     1    14     2     5\n  2.9722386812129897E-01 a       516     1    14     2     6\n  7.3288999448446634E-02 a       517     1    14     2     7\n -1.7526646277963462E-01 a       518     1    14     2     8\n -2.9290576636213700E-01 a       519     1    14     2     9\n -1.8219018702053315E-02 a       520     1    14     2    10\n -4.0581306426252689E-01 a       521     1    14     2    11\n -1.6102725975576965E-01 a       522     1    14     2    12\n  2.0288492192357938E-01 a       523     1    14     2    13\n  1.0991318472837877E-01 a       524     1    14     2    14\n  1.3209821745799588E-01 a       525     1    14     2    15\n -2.7573653927558373E-01 a       526     1    15     2     1\n -2.4323449850671605E-01 a       527     1    15     2     2\n -1.0658192959826535E-01 a       528     1    15     2     3\n -3.4086219000665091E-01 a       529     1    15     2     4\n -2.5688025989189876E-02 a       530     1    15     2     5\n  3.7383024163404271E-01 a       531     1    15     2     6\n  3.7102508247114124E-01 a       532     1    15     2     7\n -2.8708390058502453E-01 a       533     1    15     2     8\n  1.9848202020552810E-01 a       534     1    15     2     9\n  4.3778348716763019E-02 a       535     1    15     2    10\n -2.1233549686239500E-01 a       536     1    15     2    11\n -2.2580891803628883E-01 a       537     1    15     2    12\n  9.3570884599902038E-02 a       538     1    15     2    13\n -3.4969295094256447E-01 a       539     1    15     2    14\n -1.1400872215059712E-01 a       540     1    15     2    15\n  2.9411893928842664E-02 b       541     2     1\n -1.3913787357809038E-02 b       542     2     2\n  3.1642147145090532E-02 b       543     2     3\n  1.0214541804532214E-02 b       544     2     4\n  3.3612469635361825E-02 b       545     2     5\n -9.9157227725551102E-03 b       546     2     6\n  4.4661779843653570E-04 b       547     2     7\n  1.7656447061111961E-02 b       548     2     8\n  1.2093040308915953E-02 b       549     2     9\n  6.1220462454364862E-03 b       550     2    10\n -4.6032041455263108E-02 b       551     2    11\n  6.4632955678753682E-03 b       552     2    12\n -5.3666660678233488E-02 b       553     2    13\n  3.5898074413792946E-02 b       554     2    14\n -2.7520312151728701E-02 b       555     2    15\n -8.9223182324697681E-01 a       556     2     1     3     1\n  6.2474966097769358E-01 a       557     2     2     3     1\n -5.6485965500358448E-01 a       558     2     3     3     1\n -1.2379653944050904E-01 a       559     2     4     3     1\n -6.2995121003645282E-01 a       560     2     5     3     1\n -7.3420964888275053E-01 a       561     2     6     3     1\n  1.2041106603913329E-01 a       562     2     7     3     1\n -5.2523556471071497E-01 a       563     2     8     3     1\n  2.4567249673756331E-01 a       564     2     9     3     1\n -3.8950630403364422E-01 a       565     2    10     3     1\n  6.2338064124199644E-01 a       566     2    11     3     1\n -1.3208507308409601E-01 a       567     2    12     3     1\n  7.5362979635187199E-01 a       568     2    13     3     1\n -4.6256556264937920E-01 a       569     2    14     3     1\n  7.6563547152323508E-01 a       570     2    15     3     1\n -8.1116138460742296E-02 b       571     3     1\n"
  },
  {
    "path": "examples/nnp-train/AlAuMgO_4G/weightse.079.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -3.4763844565856017E-01 a         1     0     1     1     1\n -4.8392136459172183E-03 a         2     0     1     1     2\n -2.7526526688408703E-01 a         3     0     1     1     3\n -2.6242592014139915E-01 a         4     0     1     1     4\n -1.3262575727184917E-01 a         5     0     1     1     5\n  1.8527134480898870E-02 a         6     0     1     1     6\n -1.5268292073278497E-01 a         7     0     1     1     7\n  3.5660594407094548E-01 a         8     0     1     1     8\n  1.9144350794327411E-01 a         9     0     1     1     9\n -2.9797445832444502E-01 a        10     0     1     1    10\n -1.4934989315231867E-01 a        11     0     1     1    11\n -2.2774410979489118E-01 a        12     0     1     1    12\n -1.5927536922479865E-01 a        13     0     1     1    13\n -2.3885971681127327E-01 a        14     0     1     1    14\n  3.4608428822189630E-01 a        15     0     1     1    15\n  1.5088779418660692E-01 a        16     0     2     1     1\n -9.9080831715684506E-02 a        17     0     2     1     2\n  1.3790005164873995E-01 a        18     0     2     1     3\n -2.5692155548022960E-01 a        19     0     2     1     4\n  4.5408432480364402E-01 a        20     0     2     1     5\n -2.1735832092570646E-02 a        21     0     2     1     6\n  4.1976640197851628E-01 a        22     0     2     1     7\n -2.6445630471660664E-01 a        23     0     2     1     8\n -5.6543608953298220E-02 a        24     0     2     1     9\n -3.5260336517386254E-01 a        25     0     2     1    10\n -3.1967560925524924E-01 a        26     0     2     1    11\n  1.7477012882185600E-01 a        27     0     2     1    12\n -5.1894900157975779E-02 a        28     0     2     1    13\n -1.9256158314751773E-01 a        29     0     2     1    14\n  1.0637785091937468E-01 a        30     0     2     1    15\n -1.8387315601577456E-01 a        31     0     3     1     1\n -2.3197629533188110E-01 a        32     0     3     1     2\n  2.7771220392565571E-01 a        33     0     3     1     3\n  2.4263625371926095E-02 a        34     0     3     1     4\n -3.1928958646813910E-01 a        35     0     3     1     5\n -1.4439949377568814E-01 a        36     0     3     1     6\n  1.1813790378951489E-01 a        37     0     3     1     7\n  2.2161629322258897E-01 a        38     0     3     1     8\n  2.4588601952587291E-01 a        39     0     3     1     9\n  2.5089921746737442E-01 a        40     0     3     1    10\n  2.6508717133607630E-02 a        41     0     3     1    11\n  2.8054983165594549E-01 a        42     0     3     1    12\n  6.1140366456071737E-02 a        43     0     3     1    13\n  1.7131720282107815E-01 a        44     0     3     1    14\n -1.0585327066853667E-01 a        45     0     3     1    15\n -1.2253481427168311E-01 a        46     0     4     1     1\n  1.9786096555626567E-01 a        47     0     4     1     2\n -5.5966544030983612E-02 a        48     0     4     1     3\n  3.5096709902257806E-01 a        49     0     4     1     4\n  4.8193514611303290E-01 a        50     0     4     1     5\n -2.4218264300793943E-01 a        51     0     4     1     6\n -2.5160285890723777E-01 a        52     0     4     1     7\n  2.8272126625901139E-01 a        53     0     4     1     8\n  2.4737737312306021E-01 a        54     0     4     1     9\n -2.9325026318613473E-01 a        55     0     4     1    10\n -2.7726765426837036E-01 a        56     0     4     1    11\n  2.2154791723408374E-01 a        57     0     4     1    12\n  1.0333450639027415E-01 a        58     0     4     1    13\n -7.2034748399289583E-02 a        59     0     4     1    14\n -2.9407702161824512E-01 a        60     0     4     1    15\n -2.9010306461251845E-01 a        61     0     5     1     1\n  1.5365165954477375E-01 a        62     0     5     1     2\n  5.1617529310367539E-02 a        63     0     5     1     3\n -2.6962940650482103E-02 a        64     0     5     1     4\n  3.6020809771606999E-01 a        65     0     5     1     5\n -2.6470057468020985E-01 a        66     0     5     1     6\n  3.0775164834611513E-01 a        67     0     5     1     7\n -2.2981425281538392E-01 a        68     0     5     1     8\n -1.9119452347523938E-01 a        69     0     5     1     9\n  7.1621601199997123E-02 a        70     0     5     1    10\n  2.4399025115853315E-01 a        71     0     5     1    11\n -3.0663477754367929E-01 a        72     0     5     1    12\n  8.3916600425606738E-02 a        73     0     5     1    13\n -2.4256002490440620E-01 a        74     0     5     1    14\n -2.1378069783583936E-01 a        75     0     5     1    15\n -3.3458173653686540E-01 a        76     0     6     1     1\n  2.3375512157994355E-01 a        77     0     6     1     2\n  2.4532024330395735E-01 a        78     0     6     1     3\n -9.0581677349727940E-02 a        79     0     6     1     4\n  3.6795991718574506E-01 a        80     0     6     1     5\n -2.1248951087310797E-01 a        81     0     6     1     6\n -6.7473499990956934E-02 a        82     0     6     1     7\n -1.4799017296707728E-01 a        83     0     6     1     8\n  1.2750298184725542E-01 a        84     0     6     1     9\n -3.9540695759920547E-01 a        85     0     6     1    10\n  7.1845795775745930E-02 a        86     0     6     1    11\n -6.5248233031728955E-02 a        87     0     6     1    12\n -2.7778795797716291E-02 a        88     0     6     1    13\n  2.3971884709682154E-01 a        89     0     6     1    14\n  6.8041080283873748E-02 a        90     0     6     1    15\n -3.5971348026027533E-01 a        91     0     7     1     1\n  3.9932121068411985E-02 a        92     0     7     1     2\n  4.5505505646070719E-02 a        93     0     7     1     3\n  3.1892074132111142E-01 a        94     0     7     1     4\n -2.1563564339476640E-01 a        95     0     7     1     5\n  4.0117683251113795E-01 a        96     0     7     1     6\n -1.4199025758757405E-01 a        97     0     7     1     7\n -3.7510695153387680E-01 a        98     0     7     1     8\n  9.9457822046395819E-02 a        99     0     7     1     9\n  1.7786161790013327E-01 a       100     0     7     1    10\n  3.5113243424636970E-01 a       101     0     7     1    11\n  1.5694513230176785E-01 a       102     0     7     1    12\n  1.2511545370645463E-01 a       103     0     7     1    13\n  4.4545038165961878E-02 a       104     0     7     1    14\n  1.6462959315086320E-01 a       105     0     7     1    15\n -2.0038326231474066E-01 a       106     0     8     1     1\n -1.7369432740171312E-01 a       107     0     8     1     2\n -1.6551954201312402E-01 a       108     0     8     1     3\n  3.3902286509595159E-01 a       109     0     8     1     4\n -1.4822278836653802E-01 a       110     0     8     1     5\n -1.9441056146308694E-01 a       111     0     8     1     6\n  3.2031866610532617E-02 a       112     0     8     1     7\n -2.6506035953714469E-01 a       113     0     8     1     8\n -2.8866874372576806E-01 a       114     0     8     1     9\n -1.5403747044027682E-01 a       115     0     8     1    10\n  1.0485234744618671E-01 a       116     0     8     1    11\n -2.1036255962837566E-01 a       117     0     8     1    12\n  1.7651852477647004E-01 a       118     0     8     1    13\n -4.5479690189358180E-01 a       119     0     8     1    14\n  1.7950270549096672E-01 a       120     0     8     1    15\n  1.7150789434575869E-01 a       121     0     9     1     1\n -3.3632553899945995E-02 a       122     0     9     1     2\n  6.5050967754068809E-02 a       123     0     9     1     3\n  1.8652249159501555E-01 a       124     0     9     1     4\n -2.5063945238633530E-02 a       125     0     9     1     5\n -2.3872112876970139E-01 a       126     0     9     1     6\n  2.0803033211450792E-01 a       127     0     9     1     7\n 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  {
    "path": "examples/nnp-train/Carbon_chain_4G/hardness.001.data",
    "content": "4.02412e-06\n"
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  {
    "path": "examples/nnp-train/Carbon_chain_4G/hardness.006.data",
    "content": "0.0185431\n"
  },
  {
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13.4460067464 0.586230985156 -0.0759167747222 C 0.0897173392308 0.0 -0.0201920101741 -0.017799211726 0.00527231726958\natom 2.12357710415 -6.37510876821 1.86864093625 H 0.130056379231 0.0 0.0091530868083 0.0236903292404 -0.0364864619477\natom 1.09637632968 -5.22823674914 -1.48235841864 H 0.128135129231 0.0 0.0160465689618 0.00395144565426 0.011203738449\natom 23.6761905464 6.04993339393 0.613766106947 H 0.146288769231 0.0 0.00274852033402 0.00529286365395 -0.00467075537052\nenergy -381.950831506\ncharge  1.0\nend\nbegin\natom 2.85421507231 -5.36869953385 -0.151962466551 C 0.00843635461538 0.0 -0.0203702287238 -0.0326952597918 -0.0227466458798\natom 21.8966180274 5.1538421676 -0.0392319587425 C 0.0796167046154 0.0 -0.0323708148124 -0.0185765755488 0.00412627290806\natom 4.97513864212 -4.17396869234 0.117995076543 C 0.101662044615 0.0 -0.00500720065617 0.00703216908999 -0.0035436422211\natom 19.8242447874 4.08445297697 0.0451388831349 C 0.0257478246154 0.0 -0.0122066390249 -0.00730325074223 0.00456720585264\natom 6.94162091621 -2.77343484209 0.129580173997 C 0.0354245046154 0.0 0.0400515989577 0.0184888978324 0.00788915065403\natom 17.5679430808 2.86616409319 0.134876924765 C 0.100243544615 0.0 0.0418552060128 0.0193434487252 -0.0143663295895\natom 9.06163326015 -1.56581516226 0.205600845854 C 0.0912468346154 0.0 -0.0079919487652 -0.00798568698475 -0.0129461667574\natom 15.6300060438 1.58718526089 -0.215824943754 C 0.0365003046154 0.0 0.00215165548817 0.0129103478519 0.00995623103357\natom 11.2656860841 -0.470817217621 -0.0813774592197 C 0.0415222346154 0.0 -0.00600039809775 0.00440405188555 0.00961841722529\natom 13.3418583347 0.744339048492 -0.0979512065164 C 0.0878950946154 0.0 -0.0321732857283 -0.0280902913071 -0.00446056901206\natom 2.39894022733 -6.28905066559 -2.09197198501 H 0.127379204615 0.0 0.00566712859246 0.0162263827507 0.0294845606879\natom 1.5943609851 -5.88192728602 1.43719638636 H 0.121488214615 0.0 0.00420885199102 0.00476810438696 -0.00602128592152\natom 23.8044189049 5.65384775269 0.0965798512637 H 0.142837134615 0.0 0.0221860747663 0.011477661852 -0.00155719898013\nenergy -381.953544779\ncharge  1.0\nend\nbegin\natom 2.99684108305 -5.30963520322 -0.462215638456 C 0.00815022461538 0.0 -0.0420863812378 -0.0118992496465 0.0200740015536\natom 21.9199875506 4.85018183393 -0.666105016174 C 0.0849493146154 0.0 -0.0525026272502 -0.0196138420343 0.014935264629\natom 5.06755470893 -4.12960304729 -0.0323634850753 C 0.105419614615 0.0 -0.00489251412844 -0.0108961616293 -0.0201408883085\natom 19.7902232001 3.96339667661 -0.216726286359 C 0.0248688646154 0.0 0.0141136159857 0.00915032052869 -0.00258064119374\natom 7.14519514433 -2.96931571224 -0.103010021885 C 0.0352908046154 0.0 0.0285771074884 0.022897572993 0.00967196974857\natom 17.4833005908 3.03428649484 0.218472941193 C 0.0953313246154 0.0 -0.00247728488761 -0.00987753998923 -0.0061069159097\natom 9.0613005361 -1.55761350581 0.11268636381 C 0.0924906246154 0.0 0.0107547587279 -0.000673336672759 0.00547496899959\natom 15.3973748786 1.90924493054 0.449382792726 C 0.0399845746154 0.0 0.0288123466425 0.0122471403394 -0.00575654797975\natom 11.1790827199 -0.376144326647 0.494707454823 C 0.0411866546154 0.0 -0.0146539682121 -0.0104232964028 -0.0121154268974\natom 13.3206620341 0.613646241627 0.3483399378 C 0.0843821746154 0.0 -0.00139242459463 0.0100162927357 0.0122754417163\natom 1.56761253734 -5.12674943066 1.08605842578 H 0.117983444615 0.0 0.00276099664206 -0.00554974794945 -0.01209839364\natom 2.52525115647 -6.46421726653 -2.12168271054 H 0.128180724615 0.0 0.00360269952852 0.00291695664801 0.00239736825338\natom 23.6743725355 5.72688214726 -0.670390328901 H 0.141781654615 0.0 0.0293836752957 0.0117048910795 -0.00603020097132\nenergy -381.953837233\ncharge  1.0\nend\nbegin\natom 1.13796033587 0.109207397162 0.206017209181 C -0.00728779083333 0.0 -0.0137469719557 0.00783495665151 0.00103913236814\natom -1.28811705586 0.179406824803 0.352451962654 C -0.0104602508333 0.0 0.0592172930313 -0.00494201304332 -0.00825028904271\natom 3.74429736684 0.21783268313 0.0285281161061 C -0.0163431208333 0.0 -0.00189072702164 -0.00885383007511 0.0094120622155\natom -3.80114879055 0.0755086317032 0.216850365767 C -0.0120808708333 0.0 -0.001057976477 0.00142070527939 0.00496060668098\natom 6.13697194309 0.0708178404707 0.0925401084289 C -0.00322173083333 0.0 -1.59553177249e-05 0.00452139704433 -0.0156791948768\natom -6.15508001561 0.0137626665051 0.179155925883 C -0.00219413083333 0.0 0.0111463230781 0.00220550572123 -0.00956507791149\natom 8.76741076609 -0.0408181758401 -0.240624063567 C -0.0303145508333 0.0 -0.0422422983177 -0.000233137368788 0.0140433135545\natom -8.65269417516 -0.0118757562082 -0.233933564293 C -0.0305421608333 0.0 -0.0167011187979 -0.00728916678336 0.00809370389143\natom 11.0763552688 -0.263433056249 -0.218479158391 C -0.0531176108333 0.0 3.70892252091e-05 -0.00599057670284 -0.00232183553785\natom -10.9694719511 -0.271031587757 -0.337953436849 C -0.0493975308333 0.0 0.00495337211474 0.00768581778134 0.00214580501711\natom 13.0520057375 -0.793685255363 -0.277791723434 H 0.108328979167 0.0 -0.00711212226288 0.00613130650279 -0.000497462996938\natom -13.0100858325 -0.175137650336 -0.262155658173 H 0.106630769167 0.0 0.00741309270129 -0.00249096500717 -0.00338076336179\nenergy -381.61314386\ncharge  -0.0\nend\nbegin\natom 1.17043624074 -0.148396496919 -0.382740207341 C -0.0065329525 0.0 0.0352843938153 0.00262735261046 0.0262450783089\natom -1.1304491286 0.00327253298076 -0.628460124906 C -0.0079888725 0.0 -0.0204659276248 -0.00179956003044 0.0102227381103\natom 3.5927768883 -0.171039042536 0.478709185781 C -0.0121571225 0.0 -0.0375676466094 -0.00285937249842 -0.0273405414399\natom -3.63470877415 0.0624157029857 -0.262748635291 C -0.0110028825 0.0 0.0878947156139 -0.00129235199143 -0.0197423983427\natom 5.90436131927 -0.270467032118 0.524223500778 C -0.0034299525 0.0 0.0337256682244 -0.00872553934695 -0.0115097566083\natom -5.88514573504 0.0482954436318 -0.192736970824 C -0.0060513625 0.0 -0.0860967607949 0.0124277494211 0.00767191801468\natom 8.41790146585 -0.225177537822 -0.00153600707805 C -0.0251708425 0.0 0.000575460434041 0.0149339470963 0.0190440427666\natom -8.4034287537 0.296291139307 0.0902075062576 C -0.0290178725 0.0 -0.00926687886594 -0.0180835814949 0.00329907303149\natom 10.6633162721 0.399837049688 -0.0859336074755 C -0.0570836825 0.0 -0.00930818510075 0.00626848940913 -0.00525739784948\natom -10.6622547563 -0.105575306017 0.45027179542 C -0.0503239325 0.0 0.00985432000539 0.00713782876871 -0.00558537636141\natom 12.2661164711 1.62348026419 -0.415205491955 H 0.1053101675 0.0 0.00167897757996 -0.0115315835209 0.000585626192168\natom -12.6570049879 -0.329188037337 0.534182073279 H 0.1034493075 0.0 -0.0063081366772 0.000896621577379 0.00236699417756\nenergy -381.598029681\ncharge  -0.0\nend\n"
  },
  {
    "path": "examples/nnp-train/Carbon_chain_4G/input.nn",
    "content": "################################################################################\n### This is the input file for n2p2\n### It contains only a subset of all keywords\n################################################################################\n\n################################################################################\n### general keywords\n################################################################################\n\nnnp_generation 4\nuse_short_forces\n\nnumber_of_elements 2\nelements  C H\n\ninitial_hardness H 10.0\ninitial_hardness C 10.0\n\nfixed_gausswidth H 0.585815056466\nfixed_gausswidth C 1.379499971678\n\natom_energy H -0.458907306351869\natom_energy C -37.748111931202914\n\nscreen_electrostatics 4.8 8.0\n\nrandom_seed 12346\n\newald_truncation_error_method 1\newald_prec 1.e-5 0.16\n\n################################################################################\n### NN structure of the short-range NN\n################################################################################\nglobal_hidden_layers_short 2\nglobal_nodes_short 15 15\nglobal_activation_short t t l\n\n################################################################################\n### NN structure of the electrostatic NN\n################################################################################\nglobal_hidden_layers_electrostatic 2\nglobal_nodes_electrostatic 15 15\nglobal_activation_electrostatic t t l\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (General)\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10              # Number of training epochs.\nupdater_type                    1               # Weight update method\n                                                # (0 = Gradient Descent,\n                                                # 1 = Kalman filter).\nparallel_mode                   1               # Training parallelization used\n                                                # (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1               # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0               # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  0               # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                        # Keep symmetry function results in memory.\nrmse_threshold_trials           3               # Maximum number of RMSE threshold trials.\nmain_error_metric               RMSEpa          # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\ntest_fraction                   0.1             # Fraction of structures kept for testing.\nweights_min                     -1.0            # Minimum value for initial random weights.\nweights_max                     1.0             # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\nwrite_weights_epoch             1               # Write weights every this many epochs.\nscale_symmetry_functions\ncenter_symmetry_functions\n#write_neuronstats               1              # Write neuron statistics every this many epochs.\n#write_trainlog                                 # Write training log file.\n\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (charges, stage 1)\n################################################################################\ntask_batch_size_charge          1\n#nguyen_widrow_weights_charge                   # Initialize neural network weights according to Nguyen-Widrow scheme.\ncharge_fraction                 1.000\n#write_traincharges              1              # Write charge comparison. Can produce large files.\n#use_old_weights_charge                         # Restart fitting with old weight parameters.\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (short-range, stage 2)\n################################################################################\ntask_batch_size_energy          1               # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1               # Number of force update candidates prepared per task for each update (0 = Entire training set).\nforce_weight                    10.0            # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000           # Fraction of energy updates per epoch.\nshort_force_fraction            0.025           # Fraction of force updates per epoch.\n#short_energy_error_threshold    0.80           # RMSE threshold for energy update candidates.\n#short_force_error_threshold     0.80           # RMSE threshold for force update candidates.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\n#repeated_energy_update\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               0               # Write energy comparison every this many epochs.\nwrite_trainforces               0               # Write force comparison every this many epochs.\n\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\n#kalman_lambda_short 0.98000                    # Only for fading memory Kalman filter\n#kalman_nue_short 0.99870\n\nkalman_type                     0               # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2          # General Kalman filter parameter epsilon, covariance matrix initialization (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01            # General Kalman filter parameter q0, initial process noise (\"large\").\nkalman_qtau                     2.302           # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6          # General Kalman filter parameter qmin, final process noise (typ. 1.0E-6).\nkalman_eta                      0.001           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302           # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0             # Standard Kalman filter parameter etamax (1.0+).\n\n\n################################################################################\n### symmetry function definitions (all modes):\n################################################################################\ncutoff_type 2\n\n# radial H H\nsymfunction H  2  H 0.000000  0.000000  8.000000\nsymfunction H  2  H 0.006000  0.000000  8.000000\nsymfunction H  2  H 0.011000  0.000000  8.000000\nsymfunction H  2  H 0.018000  0.000000  8.000000\nsymfunction H  2  H 0.026000  0.000000  8.000000\nsymfunction H  2  H 0.035000  0.000000  8.000000\n\n#radial C H\nsymfunction C  2  H 0.000000  0.000000  8.000000\nsymfunction C  2  H 0.013000  0.000000  8.000000\nsymfunction C  2  H 0.029000  0.000000  8.000000\nsymfunction C  2  H 0.054000  0.000000  8.000000\nsymfunction C  2  H 0.093000  0.000000  8.000000\nsymfunction C  2  H 0.161000  0.000000  8.000000\n\nsymfunction H  2  C 0.000000  0.000000  8.000000\nsymfunction H  2  C 0.013000  0.000000  8.000000\nsymfunction H  2  C 0.029000  0.000000  8.000000\nsymfunction H  2  C 0.054000  0.000000  8.000000\nsymfunction H  2  C 0.093000  0.000000  8.000000\nsymfunction H  2  C 0.161000  0.000000  8.000000\n\n# radial C C\nsymfunction C  2  C 0.000000  0.000000  8.000000\nsymfunction C  2  C 0.010000  0.000000  8.000000\nsymfunction C  2  C 0.023000  0.000000  8.000000\nsymfunction C  2  C 0.041000  0.000000  8.000000\nsymfunction C  2  C 0.065000  0.000000  8.000000\nsymfunction C  2  C 0.103000  0.000000  8.000000\n\n# angular\n\nsymfunction C  3  C  C 0.0   1.0  1.0  8.000000\nsymfunction C  3  C  C 0.0   1.0  2.0  8.000000\nsymfunction C  3  C  C 0.0   1.0  4.0  8.000000\nsymfunction C  3  C  C 0.0   1.0  8.0  8.000000\nsymfunction C  3  C  C 0.0  -1.0  1.0  8.000000\nsymfunction C  3  C  C 0.0  -1.0  2.0  8.000000\nsymfunction C  3  C  C 0.0  -1.0  4.0  8.000000\nsymfunction C  3  C  C 0.0  -1.0  8.0  8.000000\n\nsymfunction C  3  H  H 0.0   1.0  1.0  8.000000\nsymfunction C  3  H  H 0.0   1.0  2.0  8.000000\nsymfunction C  3  H  H 0.0   1.0  4.0  8.000000\nsymfunction C  3  H  H 0.0   1.0  8.0  8.000000\nsymfunction C  3  H  H 0.0  -1.0  1.0  8.000000\nsymfunction C  3  H  H 0.0  -1.0  2.0  8.000000\nsymfunction C  3  H  H 0.0  -1.0  4.0  8.000000\nsymfunction C  3  H  H 0.0  -1.0  8.0  8.000000\n\nsymfunction C  3  C  H 0.0   1.0  1.0  8.000000\nsymfunction C  3  C  H 0.0   1.0  2.0  8.000000\nsymfunction C  3  C  H 0.0   1.0  4.0  8.000000\nsymfunction C  3  C  H 0.0   1.0  8.0  8.000000\nsymfunction C  3  C  H 0.0  -1.0  1.0  8.000000\nsymfunction C  3  C  H 0.0  -1.0  2.0  8.000000\nsymfunction C  3  C  H 0.0  -1.0  4.0  8.000000\nsymfunction C  3  C  H 0.0  -1.0  8.0  8.000000\n\n\nsymfunction H  3  C  C 0.0   1.0  1.0  8.000000\nsymfunction H  3  C  C 0.0   1.0  2.0  8.000000\nsymfunction H  3  C  C 0.0   1.0  4.0  8.000000\nsymfunction H  3  C  C 0.0   1.0  8.0  8.000000\nsymfunction H  3  C  C 0.0  -1.0  1.0  8.000000\nsymfunction H  3  C  C 0.0  -1.0  2.0  8.000000\n#symfunction H 3  C  C 0.0  -1.0  4.0  8.000000\n#symfunction H 3  C  C 0.0  -1.0  8.0  8.000000\n\nsymfunction H  3  H  C 0.0   1.0  1.0  8.000000\nsymfunction H  3  H  C 0.0   1.0  2.0  8.000000\nsymfunction H  3  H  C 0.0   1.0  4.0  8.000000\nsymfunction H  3  H  C 0.0   1.0  8.0  8.000000\nsymfunction H  3  H  C 0.0  -1.0  1.0  8.000000\nsymfunction H  3  H  C 0.0  -1.0  2.0  8.000000\n#symfunction H 3  H  C 0.0  -1.0  4.0  8.000000\n#symfunction H 3  H  C 0.0  -1.0  8.0  8.000000\n\n"
  },
  {
    "path": "examples/nnp-train/Carbon_chain_4G/scaling.data",
    "content": "   1    1        0.000000000       0.168474325       0.051436597\n   1    2        0.304058579       0.417104776       0.345915594\n   1    3        0.000000000       0.159465228       0.047693255\n   1    4        0.000000000       0.152326768       0.044784312\n   1    5        0.270367239       0.377289298       0.312242885\n   1    6        0.000000000       0.142866546       0.041009575\n   1    7        0.000000000       0.132772126       0.037086368\n   1    8        0.236241291       0.336573119       0.278003131\n   1    9        0.000000000       0.122265892       0.033122717\n   1   10        0.194043783       0.286076543       0.235857711\n   1   11        0.146413959       0.230979612       0.188000406\n   1   12        0.094328785       0.167444236       0.133300930\n   1   13        0.000000000       0.003940598       0.000766277\n   1   14        0.000000000       0.002179848       0.000395242\n   1   15        0.000000000       0.022615147       0.006688070\n   1   16        0.006799063       0.014786064       0.009854503\n   1   17        0.000000000       0.000754211       0.000118471\n   1   18        0.000000000       0.000307111       0.000031177\n   1   19        0.000000000       0.020171446       0.006040265\n   1   20        0.006447566       0.012997039       0.009490438\n   1   21        0.000000000       0.016749223       0.005002441\n   1   22        0.005799086       0.011113091       0.008844953\n   1   23        0.000000000       0.012662314       0.003565243\n   1   24        0.004417978       0.011019545       0.007821957\n   2    1        0.000000000       0.528085920       0.086499956\n   2    2        0.243551003       0.576397651       0.478191952\n   2    3        0.220486953       0.527469369       0.437635603\n   2    4        0.000000000       0.503534550       0.078079729\n   2    5        0.195097154       0.473305655       0.392510705\n   2    6        0.000000000       0.474879557       0.069517706\n   2    7        0.166254512       0.411783730       0.340934855\n   2    8        0.000000000       0.433337270       0.058978785\n   2    9        0.136220939       0.347964660       0.286400724\n   2   10        0.000000000       0.375671652       0.047011546\n   2   11        0.101581283       0.273092311       0.221977741\n   2   12        0.000000000       0.292877983       0.033333347\n   2   13        0.000000000       0.015267809       0.000607918\n   2   14        0.000000000       0.020367325       0.002323101\n   2   15        0.000000000       0.006658033       0.003990472\n   2   16        0.000000000       0.009284484       0.000324103\n   2   17        0.000000000       0.024985840       0.002803020\n   2   18        0.003522361       0.012523471       0.008029970\n   2   19        0.000000000       0.011921850       0.000429967\n   2   20        0.000000000       0.015558424       0.002023934\n   2   21        0.000000000       0.006518589       0.003941639\n   2   22        0.000000000       0.003823383       0.000146152\n   2   23        0.000000000       0.023446294       0.002503853\n   2   24        0.003512986       0.012433317       0.007981137\n   2   25        0.000000000       0.008678726       0.000229107\n   2   26        0.000000000       0.010714201       0.001695750\n   2   27        0.000000000       0.006384431       0.003878387\n   2   28        0.000000000       0.001758371       0.000060041\n   2   29        0.000000000       0.021095757       0.002319082\n   2   30        0.003504699       0.012339772       0.007947861\n   2   31        0.000000000       0.004699984       0.000069193\n   2   32        0.000000000       0.010701233       0.001357400\n   2   33        0.000000000       0.006338867       0.003757820\n   2   34        0.000000000       0.000942648       0.000023014\n   2   35        0.000000000       0.017137757       0.002111679\n   2   36        0.003476868       0.012155470       0.007883155\n       -0.2691374625       -0.2381480047\n"
  },
  {
    "path": "examples/nnp-train/Carbon_chain_4G/weightse.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.4094508440575101E-01 a         1     0     1     1     1\n  3.0070528204618446E-01 a         2     0     1     1     2\n  3.7719975770898966E-02 a         3     0     1     1     3\n  1.3226841022136918E-01 a         4     0     1     1     4\n -2.6667142268075456E-01 a         5     0     1     1     5\n  2.4032980375612240E-01 a         6     0     1     1     6\n -1.8121430818751535E-01 a         7     0     1     1     7\n -1.2799139873079454E-01 a         8     0     1     1     8\n -3.1524480336134968E-02 a         9     0     1     1     9\n -1.4557562182205597E-01 a        10     0     1     1    10\n -6.5574468225598648E-02 a        11     0     1     1    11\n -7.8132814560180341E-03 a        12     0     1     1    12\n -2.7714897343670869E-01 a        13     0     1     1    13\n -1.5223591409396419E-02 a        14     0     1     1    14\n  5.2616332385198576E-02 a        15     0     1     1    15\n  1.6433348448235280E-01 a        16     0     2     1     1\n -1.9566275686704579E-01 a        17     0     2     1     2\n  2.4764358859164481E-01 a        18     0     2     1     3\n -1.4573453646412440E-01 a        19     0     2     1     4\n  5.3533422840721316E-02 a        20     0     2     1     5\n -2.6273150716839394E-01 a        21     0     2     1     6\n -4.2603701391388804E-02 a        22     0     2     1     7\n  1.4093934393413257E-01 a        23     0     2     1     8\n  4.3424769623654901E-02 a        24     0     2     1     9\n -1.7872615015538981E-01 a        25     0     2     1    10\n -9.8125519419984819E-02 a        26     0     2     1    11\n  9.1640444726869552E-03 a        27     0     2     1    12\n  1.7410042857398247E-01 a        28     0     2     1    13\n  4.9513129217188319E-02 a        29     0     2     1    14\n -6.4887579188224867E-02 a        30     0     2     1    15\n  2.7927542787594578E-01 a        31     0     3     1     1\n -1.9111688880165140E-01 a        32     0     3     1     2\n  4.9030164539297781E-02 a        33     0     3     1     3\n -1.5388782432430112E-01 a        34     0     3     1     4\n  9.9241381419990948E-02 a        35     0     3     1     5\n  1.8103766078703667E-01 a        36     0     3     1     6\n -2.2734512930383677E-01 a        37     0     3     1     7\n -1.7836571151795150E-01 a        38     0     3     1     8\n  2.6854033834104164E-02 a        39     0     3     1     9\n  1.9059254417165827E-01 a        40     0     3     1    10\n -5.5549405679691313E-02 a        41     0     3     1    11\n  1.0595493440650862E-01 a        42     0     3     1    12\n  1.6990643303140701E-01 a        43     0     3     1    13\n -5.6143514722402477E-02 a        44     0     3     1    14\n -2.4996338372687998E-01 a        45     0     3     1    15\n  2.8956521811348862E-01 a        46     0     4     1     1\n  1.1627799371035101E-02 a        47     0     4     1     2\n -9.0530335307595231E-02 a        48     0     4     1     3\n -4.2031306177506167E-02 a        49     0     4     1     4\n  1.7082577429108578E-01 a        50     0     4     1     5\n -2.1244191696025494E-01 a        51     0     4     1     6\n -2.3437407365876396E-02 a        52     0     4     1     7\n -6.1580029845849364E-02 a        53     0     4     1     8\n  1.0483535829550519E-01 a        54     0     4     1     9\n  2.5814120454862960E-01 a        55     0     4     1    10\n -2.2040966177774624E-01 a        56     0     4     1    11\n -1.8213749361542975E-01 a        57     0     4     1    12\n  8.8064964637641255E-02 a        58     0     4     1    13\n  1.6539037120497643E-01 a        59     0     4     1    14\n  5.0267402740948465E-02 a        60     0     4     1    15\n  9.3094283679998724E-02 a        61     0     5     1     1\n -1.7275563929494586E-01 a        62     0     5     1     2\n  1.2973236749924386E-01 a        63     0     5     1     3\n  1.9642919724191010E-01 a        64     0     5     1     4\n  2.2229582201666123E-01 a        65     0     5     1     5\n -2.0582217756393387E-01 a        66     0     5     1     6\n  1.7916464123192716E-01 a        67     0     5     1     7\n  1.0087529476393918E-01 a        68     0     5     1     8\n  2.3474948572569090E-01 a        69     0     5     1     9\n  2.4502401016229861E-02 a        70     0     5     1    10\n -1.2905418579996034E-01 a        71     0     5     1    11\n -2.0252162555696621E-01 a        72     0     5     1    12\n -2.4470565823295140E-01 a        73     0     5     1    13\n -2.6630876292565148E-01 a        74     0     5     1    14\n -1.9266795194183906E-01 a        75     0     5     1    15\n -3.5910423322811760E-02 a        76     0     6     1     1\n -8.1949551390367650E-03 a        77     0     6     1     2\n -2.2586163858331110E-01 a        78     0     6     1     3\n -4.2748072413206994E-02 a        79     0     6     1     4\n  7.9863882738283348E-02 a        80     0     6     1     5\n  1.7939665531320353E-01 a        81     0     6     1     6\n  2.6968673970590834E-01 a        82     0     6     1     7\n -1.3767713993219027E-01 a        83     0     6     1     8\n -5.5998093272765219E-02 a        84     0     6     1     9\n -2.4187917571410769E-01 a        85     0     6     1    10\n  1.5187900187343625E-01 a        86     0     6     1    11\n -9.4468484953230458E-02 a        87     0     6     1    12\n  9.7019528142093067E-02 a        88     0     6     1    13\n  2.9090826612242593E-01 a        89     0     6     1    14\n -2.1519745028023377E-01 a        90     0     6     1    15\n  2.3348263720880912E-02 a        91     0     7     1     1\n -3.7234702136082633E-02 a        92     0     7     1     2\n -1.8439067741818690E-01 a        93     0     7     1     3\n -1.6035311883432568E-01 a        94     0     7     1     4\n  2.6341195078877910E-01 a        95     0     7     1     5\n  2.6887427303729672E-01 a        96     0     7     1     6\n -1.6649066704955179E-01 a        97     0     7     1     7\n -2.7582675637959138E-02 a        98     0     7     1     8\n -2.9663608600033520E-01 a        99     0     7     1     9\n -1.6307385516163633E-01 a       100     0     7     1    10\n -1.4371764472133583E-01 a       101     0     7     1    11\n -1.8985629848678418E-01 a       102     0     7     1    12\n -7.1597212171132532E-02 a       103     0     7     1    13\n  1.0760523298821263E-01 a       104     0     7     1    14\n -1.9066837594416816E-01 a       105     0     7     1    15\n -1.7519352975225941E-01 a       106     0     8     1     1\n  2.0570826889089092E-01 a       107     0     8     1     2\n  1.2440412960165775E-01 a       108     0     8     1     3\n -5.3464138796127915E-02 a       109     0     8     1     4\n -2.6692763422564791E-01 a       110     0     8     1     5\n  2.7516528296010379E-01 a       111     0     8     1     6\n -1.4566246307639705E-01 a       112     0     8     1     7\n -1.5826525634547287E-01 a       113     0     8     1     8\n -1.8564839882745821E-01 a       114     0     8     1     9\n  2.5699263882642798E-01 a       115     0     8     1    10\n  4.8211357669526736E-02 a       116     0     8     1    11\n  2.2869365111131826E-01 a       117     0     8     1    12\n  1.2364381138182197E-02 a       118     0     8     1    13\n  1.0696492287359111E-02 a       119     0     8     1    14\n -2.4105522972255200E-01 a       120     0     8     1    15\n  1.1150754471310834E-01 a       121     0     9     1     1\n -2.1635171776622991E-01 a       122     0     9     1     2\n  2.4413132932820061E-01 a       123     0     9     1     3\n -1.8719200019813870E-01 a       124     0     9     1     4\n -9.0912812167663531E-02 a       125     0     9     1     5\n  1.5511741237488269E-01 a       126     0     9     1     6\n -1.7838410567336449E-01 a       127     0     9     1     7\n  1.9816699353931480E-01 a       128     0     9     1     8\n -1.7286436516683196E-01 a       129     0     9     1     9\n  6.7231271333059478E-02 a       130     0     9     1    10\n -1.4306743905571054E-01 a       131     0     9     1    11\n -1.8417761401520105E-01 a       132     0     9     1    12\n  1.3600837471289323E-01 a       133     0     9     1    13\n -2.3371259658984528E-01 a       134     0     9     1    14\n -1.5784923542617707E-01 a       135     0     9     1    15\n -5.2666545467480470E-03 a       136     0    10     1     1\n -2.5056201158849362E-01 a       137     0    10     1     2\n -7.2679510890007556E-02 a       138     0    10     1     3\n  2.4865258392030229E-01 a       139     0    10     1     4\n -1.7507677555601461E-01 a       140     0    10     1     5\n  1.8914493088866466E-01 a       141     0    10     1     6\n -1.6769186264922839E-01 a       142     0    10     1     7\n -1.9525848443079621E-01 a       143     0    10     1     8\n -1.4893864634065537E-01 a       144     0    10     1     9\n -1.3524063532454256E-01 a       145     0    10     1    10\n -2.8254068639407370E-01 a       146     0    10     1    11\n  1.9293260639598280E-02 a       147     0    10     1    12\n  1.7296980461444766E-01 a       148     0    10     1    13\n  1.7188211136539522E-01 a       149     0    10     1    14\n  7.9882088667891968E-02 a       150     0    10     1    15\n  7.3926915973841337E-02 a       151     0    11     1     1\n -2.5225506631073308E-01 a       152     0    11     1     2\n -1.7909066144733005E-01 a       153     0    11     1     3\n  2.7283171413808127E-01 a       154     0    11     1     4\n  1.5949663055332042E-01 a       155     0    11     1     5\n  1.2980384263151432E-01 a       156     0    11     1     6\n  2.6641192099972522E-01 a       157     0    11     1     7\n -1.2868500182187767E-01 a       158     0    11     1     8\n  2.5096877972357912E-01 a       159     0    11     1     9\n -8.4429823833787748E-02 a       160     0    11     1    10\n  4.6351824670606299E-02 a       161     0    11     1    11\n -2.0230748747733901E-01 a       162     0    11     1    12\n -2.0523625659084455E-01 a       163     0    11     1    13\n -1.6919955728662830E-01 a       164     0    11     1    14\n -1.5536629090723431E-01 a       165     0    11     1    15\n  4.6038524451021946E-02 a       166     0    12     1     1\n  2.8611950718005558E-01 a       167     0    12     1     2\n  1.6848248333987950E-01 a       168     0    12     1     3\n -2.0741071470015709E-01 a       169     0    12     1     4\n  1.9837076502464324E-01 a       170     0    12     1     5\n -2.0523240490508754E-01 a       171     0    12     1     6\n  1.2941273284745322E-01 a       172     0    12     1     7\n -1.0708642773772559E-02 a       173     0    12     1     8\n  1.4831066837619383E-01 a       174     0    12     1     9\n  1.6777914634425442E-01 a       175     0    12     1    10\n  5.5506245590999287E-02 a       176     0    12     1    11\n -3.8208440785149921E-02 a       177     0    12     1    12\n  5.5836003867228909E-02 a       178     0    12     1    13\n  5.4692565808581194E-02 a       179     0    12     1    14\n  1.2721278207919851E-02 a       180     0    12     1    15\n  1.6722133024790590E-02 a       181     0    13     1     1\n  2.8238337506065225E-01 a       182     0    13     1     2\n  7.6228586057278683E-02 a       183     0    13     1     3\n  7.2340011367032928E-02 a       184     0    13     1     4\n -2.5047636724116296E-01 a       185     0    13     1     5\n -2.3624871136395403E-01 a       186     0    13     1     6\n -2.3353247640442826E-01 a       187     0    13     1     7\n -2.0824041810737104E-01 a       188     0    13     1     8\n  2.8866606823290353E-01 a       189     0    13     1     9\n -8.3553478254417085E-02 a       190     0    13     1    10\n  9.7366155865711429E-02 a       191     0    13     1    11\n  7.5651679212290393E-02 a       192     0    13     1    12\n -7.4502750733741352E-02 a       193     0    13     1    13\n -4.5576100611956476E-03 a       194     0    13     1    14\n -2.7277737904853022E-01 a       195     0    13     1    15\n -1.2971417089197142E-02 a       196     0    14     1     1\n  2.6646774588839789E-01 a       197     0    14     1     2\n -3.7904680947930217E-02 a       198     0    14     1     3\n  2.4164579900640376E-01 a       199     0    14     1     4\n -2.0819579256967793E-01 a       200     0    14     1     5\n  4.7705766092370781E-02 a       201     0    14     1     6\n  1.9973843728677887E-01 a       202     0    14     1     7\n  2.3755546407076042E-01 a       203     0    14     1     8\n -6.9338605503516476E-02 a       204     0    14     1     9\n -5.4682560878483819E-02 a       205     0    14     1    10\n  2.7244184689249007E-01 a       206     0    14     1    11\n  7.9479642585704058E-02 a       207     0    14     1    12\n  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-2.6095107959375430E-01 a       787     1     4     2     7\n  2.0638372019972837E-01 a       788     1     4     2     8\n  6.1442078182674303E-02 a       789     1     4     2     9\n  4.1206016885625074E-01 a       790     1     4     2    10\n -9.1383893481422548E-02 a       791     1     4     2    11\n  3.7854739985441394E-01 a       792     1     4     2    12\n -1.2829770510885929E-01 a       793     1     4     2    13\n  3.7676539181985119E-01 a       794     1     4     2    14\n  2.7971215069748201E-01 a       795     1     4     2    15\n -3.0903904725390741E-01 a       796     1     5     2     1\n -2.7001457207731977E-01 a       797     1     5     2     2\n  2.3084252735283817E-01 a       798     1     5     2     3\n  1.2091487672503429E-01 a       799     1     5     2     4\n -1.6361769663277737E-01 a       800     1     5     2     5\n -2.8163079760000048E-01 a       801     1     5     2     6\n  8.6480287155213637E-02 a       802     1     5     2     7\n -4.3962532693465192E-03 a       803     1     5     2     8\n -3.1386902486676652E-02 a       804     1     5     2     9\n  3.8267987963191269E-01 a       805     1     5     2    10\n -4.8957529583911419E-02 a       806     1     5     2    11\n  1.5748109893896475E-01 a       807     1     5     2    12\n -3.1920298491992344E-01 a       808     1     5     2    13\n -3.9550539098158605E-01 a       809     1     5     2    14\n -4.4206160287231777E-01 a       810     1     5     2    15\n -3.3069849208354524E-01 a       811     1     6     2     1\n -1.5156107680817382E-01 a       812     1     6     2     2\n  8.7308067950781734E-02 a       813     1     6     2     3\n -3.9535786756528568E-01 a       814     1     6     2     4\n -7.6496217623292437E-02 a       815     1     6     2     5\n  7.2971457332835998E-02 a       816     1     6     2     6\n  4.5560329543133056E-02 a       817     1     6     2     7\n  1.9716633509387624E-01 a       818     1     6     2     8\n  4.0236264800458171E-01 a       819     1     6     2     9\n -1.0369465153209741E-01 a       820     1     6     2    10\n  8.5813771367485026E-02 a       821     1     6     2    11\n -3.8982284341849235E-02 a       822     1     6     2    12\n -4.1267244280249399E-01 a       823     1     6     2    13\n  1.9841859040675768E-02 a       824     1     6     2    14\n  3.0618172291955393E-02 a       825     1     6     2    15\n  1.1183984720441532E-01 a       826     1     7     2     1\n  3.8633894320880258E-01 a       827     1     7     2     2\n  2.1597704055767183E-01 a       828     1     7     2     3\n  2.6216231470299151E-01 a       829     1     7     2     4\n -4.3353939621203919E-01 a       830     1     7     2     5\n -1.9559389961924958E-01 a       831     1     7     2     6\n  2.5654114706170283E-01 a       832     1     7     2     7\n -1.7729302022562782E-01 a       833     1     7     2     8\n -8.0289374564561939E-03 a       834     1     7     2     9\n  1.3756933679994166E-03 a       835     1     7     2    10\n -2.2901615392191063E-01 a       836     1     7     2    11\n  1.9293794453917368E-01 a       837     1     7     2    12\n  2.6569713920599458E-01 a       838     1     7     2    13\n  1.7829539090076457E-01 a       839     1     7     2    14\n -1.4500395509036215E-01 a       840     1     7     2    15\n -3.7782059336923884E-01 a       841     1     8     2     1\n -3.9442061047868981E-01 a       842     1     8     2     2\n -3.0142102907306806E-01 a       843     1     8     2     3\n -2.9691317869155592E-01 a       844     1     8     2     4\n  1.2434463415964891E-01 a       845     1     8     2     5\n -5.8193927289762838E-02 a       846     1     8     2     6\n  6.2541598889061842E-02 a       847     1     8     2     7\n  9.2843717016822438E-02 a       848     1     8     2     8\n -1.3157613347588437E-01 a       849     1     8     2     9\n -7.9204287327816897E-02 a       850     1     8     2    10\n  3.2421909506090635E-01 a       851     1     8     2    11\n -2.4349787486575949E-01 a       852     1     8     2    12\n  2.9411390997933945E-01 a       853     1     8     2    13\n  2.3434260262901116E-01 a       854     1     8     2    14\n -1.5871653965681312E-01 a       855     1     8     2    15\n  2.1520351234005072E-01 a       856     1     9     2     1\n  2.8168963123971863E-01 a       857     1     9     2     2\n -1.0029108120114828E-01 a       858     1     9     2     3\n -3.3292597460317974E-01 a       859     1     9     2     4\n  1.4787080279097274E-02 a       860     1     9     2     5\n -3.3972445509684829E-01 a       861     1     9     2     6\n  1.2531366508736033E-01 a       862     1     9     2     7\n  1.7216748240232629E-01 a       863     1     9     2     8\n  7.1410379388928705E-02 a       864     1     9     2     9\n  3.1661661241764322E-01 a       865     1     9     2    10\n  2.5779273059374763E-01 a       866     1     9     2    11\n  9.7042375427538588E-02 a       867     1     9     2    12\n  1.3129635200340989E-01 a       868     1     9     2    13\n  6.9412706734226573E-02 a       869     1     9     2    14\n -1.8279301863281919E-01 a       870     1     9     2    15\n -3.3432335902369631E-01 a       871     1    10     2     1\n  2.8862507511552427E-01 a       872     1    10     2     2\n -2.5768945793358002E-02 a       873     1    10     2     3\n  3.2269720471478880E-01 a       874     1    10     2     4\n -1.2476229106384541E-01 a       875     1    10     2     5\n  8.8921514644887623E-02 a       876     1    10     2     6\n -6.4272633106436508E-02 a       877     1    10     2     7\n  2.5363265597891438E-01 a       878     1    10     2     8\n -3.2534505396149088E-01 a       879     1    10     2     9\n  3.2196732277570900E-01 a       880     1    10     2    10\n -1.2776099844004152E-02 a       881     1    10     2    11\n -4.5788988732724745E-02 a       882     1    10     2    12\n  3.2721475990509608E-01 a       883     1    10     2    13\n -1.2508926255100178E-01 a       884     1    10     2    14\n  7.1950519426518006E-02 a       885     1    10     2    15\n  3.7301442167436522E-01 a       886     1    11     2     1\n  1.2785846323044914E-01 a       887     1    11     2     2\n  2.1179616338725255E-01 a       888     1    11     2     3\n  2.5223653161796394E-01 a       889     1    11     2     4\n  3.5386321774303048E-01 a       890     1    11     2     5\n -2.5181740977783951E-01 a       891     1    11     2     6\n -4.1088919908605381E-01 a       892     1    11     2     7\n -1.9046364305310596E-02 a       893     1    11     2     8\n  3.5389178764442925E-01 a       894     1    11     2     9\n -3.1527099130178782E-01 a       895     1    11     2    10\n  3.6732674435412982E-01 a       896     1    11     2    11\n -6.0355270637466291E-02 a       897     1    11     2    12\n -1.8339604817747077E-01 a       898     1    11     2    13\n -7.4893285216232230E-02 a       899     1    11     2    14\n -2.3387067854645283E-01 a       900     1    11     2    15\n -3.3923036496739262E-01 a       901     1    12     2     1\n  2.0723530073176469E-01 a       902     1    12     2     2\n  3.9814871461546808E-01 a       903     1    12     2     3\n  4.1548415187193521E-01 a       904     1    12     2     4\n -3.3811369711699168E-01 a       905     1    12     2     5\n  3.1932530587085445E-01 a       906     1    12     2     6\n  2.3583343917258034E-01 a       907     1    12     2     7\n -9.2326013782133676E-02 a       908     1    12     2     8\n -4.7393967137259650E-02 a       909     1    12     2     9\n -2.5734312553676081E-01 a       910     1    12     2    10\n  1.2148664128946884E-01 a       911     1    12     2    11\n  2.4234359846293435E-01 a       912     1    12     2    12\n -4.0269997661374779E-01 a       913     1    12     2    13\n  2.8045888591652068E-01 a       914     1    12     2    14\n  3.7783461390970507E-01 a       915     1    12     2    15\n -3.3810567642168843E-01 a       916     1    13     2     1\n  2.6155059623318766E-01 a       917     1    13     2     2\n  3.5903421349194786E-01 a       918     1    13     2     3\n  2.0232542580590263E-01 a       919     1    13     2     4\n -7.8777998637715133E-02 a       920     1    13     2     5\n -2.6083654903972808E-01 a       921     1    13     2     6\n -4.1656979876656286E-01 a       922     1    13     2     7\n -4.5668733236089554E-01 a       923     1    13     2     8\n  1.0249829004184159E-01 a       924     1    13     2     9\n -1.0431906916360505E-01 a       925     1    13     2    10\n  1.0860530582334638E-01 a       926     1    13     2    11\n -3.5718754523843382E-01 a       927     1    13     2    12\n -8.8272529806557837E-02 a       928     1    13     2    13\n  5.0674435934530450E-02 a       929     1    13     2    14\n  2.9530293166143445E-01 a       930     1    13     2    15\n  2.0827120496440249E-01 a       931     1    14     2     1\n  3.7003101206776529E-01 a       932     1    14     2     2\n -3.6790949178616567E-01 a       933     1    14     2     3\n -1.2003759084257373E-01 a       934     1    14     2     4\n  2.4560948963161777E-01 a       935     1    14     2     5\n -2.1805685643286155E-01 a       936     1    14     2     6\n -2.3737232439737226E-03 a       937     1    14     2     7\n -4.9106652702272111E-03 a       938     1    14     2     8\n  3.1303153972692721E-01 a       939     1    14     2     9\n  3.5932352608090756E-01 a       940     1    14     2    10\n -1.4198130120406710E-01 a       941     1    14     2    11\n -2.9627289134064116E-01 a       942     1    14     2    12\n -2.3198821063232644E-01 a       943     1    14     2    13\n -3.7267896063412553E-01 a       944     1    14     2    14\n  3.1729455435756276E-01 a       945     1    14     2    15\n -2.6767679773409470E-01 a       946     1    15     2     1\n  4.1654370717876488E-01 a       947     1    15     2     2\n -1.0952703511307273E-01 a       948     1    15     2     3\n  3.7522037686269305E-01 a       949     1    15     2     4\n -4.1453709619266510E-01 a       950     1    15     2     5\n -3.2882010463705619E-01 a       951     1    15     2     6\n -2.9906122233908938E-01 a       952     1    15     2     7\n -3.0713493791335811E-01 a       953     1    15     2     8\n  2.7940400018845457E-01 a       954     1    15     2     9\n -2.9508374166795949E-04 a       955     1    15     2    10\n -6.6871578971002266E-02 a       956     1    15     2    11\n  3.7394442833986885E-01 a       957     1    15     2    12\n  2.2244421824448479E-01 a       958     1    15     2    13\n -4.4203275489880872E-01 a       959     1    15     2    14\n -1.4994470145600505E-01 a       960     1    15     2    15\n -5.4831179863217880E-02 b       961     2     1\n -2.3632855225058935E-02 b       962     2     2\n -9.6662000719772267E-02 b       963     2     3\n  3.7347700754445608E-02 b       964     2     4\n -2.6277616318368751E-03 b       965     2     5\n  7.9676867437818058E-02 b       966     2     6\n -3.2003270765813607E-02 b       967     2     7\n  5.1716415290229800E-02 b       968     2     8\n  8.1893446476926340E-02 b       969     2     9\n  1.9200360266989194E-02 b       970     2    10\n -1.0006887245136842E-02 b       971     2    11\n -1.7799991678972227E-02 b       972     2    12\n  3.5966263827791320E-02 b       973     2    13\n -1.7075482297708722E-03 b       974     2    14\n -8.0351199159686651E-02 b       975     2    15\n  5.7071561336482524E-01 a       976     2     1     3     1\n -3.6650606048959067E-01 a       977     2     2     3     1\n -6.5873422772861712E-01 a       978     2     3     3     1\n  4.5330190626407579E-01 a       979     2     4     3     1\n -1.1288428054959404E-01 a       980     2     5     3     1\n  6.9331432495828993E-01 a       981     2     6     3     1\n -3.7022784514697238E-01 a       982     2     7     3     1\n -8.6790873894082454E-01 a       983     2     8     3     1\n  6.9384934169874946E-01 a       984     2     9     3     1\n  3.1449432424993129E-01 a       985     2    10     3     1\n -1.3052652405689669E-01 a       986     2    11     3     1\n -2.1126466182111114E-01 a       987     2    12     3     1\n  1.9572341629230219E-01 a       988     2    13     3     1\n  2.6991274305360813E-01 a       989     2    14     3     1\n -5.9521143827482925E-01 a       990     2    15     3     1\n -6.8582376032699224E-03 b       991     3     1\n"
  },
  {
    "path": "examples/nnp-train/Carbon_chain_4G/weightse.006.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -3.7337678457561294E-02 a         1     0     1     1     1\n  2.7105490931005555E-01 a         2     0     1     1     2\n -2.4886857059472092E-01 a         3     0     1     1     3\n -1.6430288393206305E-01 a         4     0     1     1     4\n  6.7892284304085754E-02 a         5     0     1     1     5\n -1.5104206803616957E-01 a         6     0     1     1     6\n -2.9248248605725441E-01 a         7     0     1     1     7\n  2.1964240226605314E-02 a         8     0     1     1     8\n -7.7257737290702996E-02 a         9     0     1     1     9\n -1.9681597538942486E-01 a        10     0     1     1    10\n -2.3682459026336011E-01 a        11     0     1     1    11\n -1.7795472468333801E-01 a        12     0     1     1    12\n -1.5811211873744319E-01 a        13     0     1     1    13\n -7.1106760671817409E-04 a        14     0     1     1    14\n -4.3858708734360229E-02 a        15     0     1     1    15\n  6.3666573556300746E-02 a        16     0     2     1     1\n  1.8785902598701773E-01 a        17     0     2     1     2\n  2.2877728202693914E-01 a        18     0     2     1     3\n -5.9625478212477517E-02 a        19     0     2     1     4\n -7.3565857762700221E-02 a        20     0     2     1     5\n  1.9992712920904626E-02 a        21     0     2     1     6\n -2.1539364068472042E-01 a        22     0     2     1     7\n -1.4386225755196944E-01 a        23     0     2     1     8\n -2.9084081877749729E-01 a        24     0     2     1     9\n -2.5064599200619636E-01 a        25     0     2     1    10\n  3.7347146773012936E-02 a        26     0     2     1    11\n  5.9357556848358611E-02 a        27     0     2     1    12\n -1.3518057646328502E-01 a        28     0     2     1    13\n  4.0628028736902050E-02 a        29     0     2     1    14\n -2.1767247249275468E-01 a        30     0     2     1    15\n  3.2684403732055545E-01 a        31     0     3     1     1\n  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  {
    "path": "examples/nnp-train/Cu2S_PBE/input.data",
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0.119092\natom 12.87300 6.88607 0.68886 Cu 0.0 0.0 -0.260305 0.283403 -0.098703\natom 9.48326 10.68505 6.72090 Cu 0.0 0.0 -0.222205 0.354828 -0.119092\natom -4.68284 4.46054 11.37522 Cu 0.0 0.0 0.260305 -0.283403 0.098703\natom 7.64017 0.85829 11.97119 Cu 0.0 0.0 -0.116702 -0.000516 -0.443922\natom -2.57440 7.14427 6.12493 Cu 0.0 0.0 -0.076548 0.116351 0.068077\natom 0.54999 10.48832 0.09289 Cu 0.0 0.0 0.116702 0.000516 0.443922\natom 10.76456 4.20233 5.93915 Cu 0.0 0.0 0.076548 -0.116351 -0.068077\natom 10.85957 1.37271 6.15148 Cu 0.0 0.0 -0.054746 -0.104453 -0.353573\natom -5.80972 7.05834 11.94465 Cu 0.0 0.0 -0.135939 0.092078 0.066335\natom -2.66941 9.97390 5.91261 Cu 0.0 0.0 0.054746 0.104453 0.353573\natom 13.99988 4.28827 0.11943 Cu 0.0 0.0 0.135939 -0.092078 -0.066335\natom 8.73387 2.74132 4.95713 Cu 0.0 0.0 0.128971 -0.221059 0.043926\natom 2.69299 8.92600 1.07491 Cu 0.0 0.0 -0.102359 0.348945 -0.017986\natom -0.54371 8.60529 7.10695 Cu 0.0 0.0 -0.128971 0.221059 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9.45100 Cu 0.0 0.0 0.043895 -0.263306 0.011700\natom 0.51324 0.13178 7.51592 Cu 0.0 0.0 0.026819 0.233220 0.498362\natom 4.62358 5.95816 10.58020 Cu 0.0 0.0 0.137093 -0.068788 -0.061812\natom 7.67693 11.21483 4.54816 Cu 0.0 0.0 -0.026819 -0.233220 -0.498362\natom 3.56658 5.38845 1.48388 Cu 0.0 0.0 -0.137093 0.068788 0.061812\natom 3.72216 0.43254 1.61538 Cu 0.0 0.0 -0.040870 0.279572 0.401644\natom 7.88903 6.27248 4.41666 Cu 0.0 0.0 -0.142573 -0.076326 0.005876\natom 4.46800 10.91407 10.44870 Cu 0.0 0.0 0.040870 -0.279572 -0.401644\natom 0.30113 5.07412 7.64742 Cu 0.0 0.0 0.142573 0.076326 -0.005876\natom 2.94560 2.02254 9.09994 Cu 0.0 0.0 0.040919 0.245148 0.290469\natom 2.04468 8.01233 8.99619 Cu 0.0 0.0 -0.015727 -0.057877 -0.039936\natom 5.24457 9.32406 2.96414 Cu 0.0 0.0 -0.040919 -0.245148 -0.290469\natom 6.14548 3.33427 3.06790 Cu 0.0 0.0 0.015727 0.057877 0.039936\natom 13.65645 0.88975 2.61308 Cu 0.0 0.0 -0.001253 -0.021270 0.054902\natom -2.08304 6.83262 3.41896 Cu 0.0 0.0 0.000362 0.194907 -0.105534\natom -5.46628 10.45685 9.45100 Cu 0.0 0.0 0.001253 0.021270 -0.054902\natom 10.27320 4.51398 8.64512 Cu 0.0 0.0 -0.000362 -0.194907 0.105534\natom 3.19194 0.64211 11.49828 Cu 0.0 0.0 -0.132780 0.397604 0.050572\natom 1.89170 6.87931 6.59785 Cu 0.0 0.0 0.147372 -0.288628 -0.015811\natom 4.99822 10.70450 0.56581 Cu 0.0 0.0 0.132780 -0.397604 -0.050572\natom 6.29846 4.46730 5.46624 Cu 0.0 0.0 -0.147372 0.288628 0.015811\natom 6.88199 1.97461 6.82706 Cu 0.0 0.0 0.177085 -0.092970 0.112419\natom -1.87944 7.72993 11.26906 Cu 0.0 0.0 0.066394 0.172016 -0.179726\natom 1.30817 9.37200 5.23702 Cu 0.0 0.0 -0.177085 0.092970 -0.112419\natom 10.06961 3.61668 0.79502 Cu 0.0 0.0 -0.066394 -0.172016 0.179726\natom 2.06701 2.38937 1.68656 Cu 0.0 0.0 0.157526 -0.073328 0.019306\natom 9.39853 8.23666 4.34548 Cu 0.0 0.0 -0.040495 0.188487 0.189635\natom 6.12315 8.95724 10.37752 Cu 0.0 0.0 -0.157526 0.073328 -0.019306\natom -1.20837 3.10995 7.71860 Cu 0.0 0.0 0.040495 -0.188487 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0.060146\natom 8.89445 4.59697 9.85222 S 0.0 0.0 -0.162224 0.317867 0.051220\natom 8.89285 0.74884 5.90062 S 0.0 0.0 0.111339 0.404760 0.293108\natom -3.33199 6.39950 11.56373 S 0.0 0.0 0.035717 -0.004228 0.186135\natom -0.22873 10.54084 5.74228 S 0.0 0.0 -0.111339 -0.404760 -0.293108\natom 11.99611 4.89019 0.07917 S 0.0 0.0 -0.035717 0.004228 -0.186135\natom 12.05186 0.95473 0.06986 S 0.0 0.0 0.300443 0.349162 0.241329\natom -0.11282 6.60470 5.75159 S 0.0 0.0 -0.047374 0.122470 0.084756\natom -3.38774 10.33496 11.57304 S 0.0 0.0 -0.300443 -0.349162 -0.241329\natom 8.77694 4.68498 5.89131 S 0.0 0.0 0.047374 -0.122470 -0.084756\natom 2.93601 0.77245 7.14059 S 0.0 0.0 -0.303865 -0.560216 -0.389525\natom 2.62183 6.51416 10.32376 S 0.0 0.0 0.223996 -0.097440 -0.142371\natom 5.72811 10.51724 4.50231 S 0.0 0.0 0.303865 0.560216 0.389525\natom 6.04229 4.77553 1.31914 S 0.0 0.0 -0.223996 0.097440 0.142371\natom 6.16928 0.80976 1.11423 S 0.0 0.0 0.157239 0.131858 -0.409031\natom 5.77440 6.53642 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11.00370 Cu 0.0 0.0 0.087619 -0.317677 0.025590\natom 9.65700 6.61616 6.46064 Cu 0.0 0.0 -0.075743 0.208545 -0.210380\natom 12.76154 10.69892 0.63920 Cu 0.0 0.0 -0.087619 0.317677 -0.025590\natom -0.99288 4.67352 5.18225 Cu 0.0 0.0 0.075743 -0.208545 0.210380\natom -1.21557 0.72812 5.15664 Cu 0.0 0.0 0.070799 -0.281791 0.102672\natom 13.15634 6.75163 0.66481 Cu 0.0 0.0 -0.094671 0.183603 -0.090640\natom 9.87968 10.56157 6.48626 Cu 0.0 0.0 -0.070799 0.281791 -0.102672\natom -4.49222 4.53805 10.97809 Cu 0.0 0.0 0.094671 -0.183603 0.090640\natom 7.93526 1.02053 11.55325 Cu 0.0 0.0 -0.387933 -0.130153 -0.345487\natom -2.39530 7.08628 5.91110 Cu 0.0 0.0 0.172661 0.003167 0.040354\natom 0.72886 10.26916 0.08965 Cu 0.0 0.0 0.387933 0.130153 0.345487\natom 11.05942 4.20341 5.73180 Cu 0.0 0.0 -0.172661 -0.003167 -0.040354\natom 11.11290 1.43649 5.93671 Cu 0.0 0.0 -0.260736 -0.208164 -0.279923\natom -5.58209 7.08980 11.52763 Cu 0.0 0.0 0.036367 -0.000678 0.045761\natom -2.44878 9.85320 5.70618 Cu 0.0 0.0 0.260736 0.208164 0.279923\natom 14.24621 4.19989 0.11526 Cu 0.0 0.0 -0.036367 0.000678 -0.045761\natom 8.96439 2.75833 4.78407 Cu 0.0 0.0 0.140680 -0.214622 0.235424\natom 2.88844 8.75448 1.03738 Cu 0.0 0.0 -0.128401 0.364323 -0.217604\natom -0.30027 8.53136 6.85883 Cu 0.0 0.0 -0.140680 0.214622 -0.235424\natom 5.77568 2.53521 10.60551 Cu 0.0 0.0 0.128401 -0.364323 0.217604\natom 0.77551 1.33101 10.88378 Cu 0.0 0.0 0.123408 0.241213 0.283180\natom 4.75197 7.34760 6.58057 Cu 0.0 0.0 -0.172148 0.277921 -0.093776\natom 7.88860 9.95868 0.75912 Cu 0.0 0.0 -0.123408 -0.241213 -0.283180\natom 3.91215 3.94209 5.06233 Cu 0.0 0.0 0.172148 -0.277921 0.093776\natom 3.67755 1.25246 5.10890 Cu 0.0 0.0 0.369887 0.303330 0.311208\natom 8.24044 7.27247 0.71255 Cu 0.0 0.0 -0.395447 0.245839 0.048050\natom 4.98657 10.03723 6.53399 Cu 0.0 0.0 -0.369887 -0.303330 -0.311208\natom 0.42368 4.01722 10.93035 Cu 0.0 0.0 0.395447 -0.245839 -0.048050\natom -1.54216 2.39807 9.90461 Cu 0.0 0.0 0.023324 0.077918 0.079022\natom 7.02467 8.34276 7.55973 Cu 0.0 0.0 -0.020919 0.089487 -0.102592\natom 10.20627 8.89161 1.73828 Cu 0.0 0.0 -0.023324 -0.077918 -0.079022\natom 1.63945 2.94693 4.08316 Cu 0.0 0.0 0.020919 -0.089487 0.102592\natom 8.19248 0.12750 7.95210 Cu 0.0 0.0 -0.220921 -0.136250 -0.309043\natom -2.60782 5.92880 9.51225 Cu 0.0 0.0 0.184056 -0.354253 -0.127323\natom 0.47163 11.16219 3.69080 Cu 0.0 0.0 0.220921 0.136250 0.309043\natom 11.27193 5.36088 2.13065 Cu 0.0 0.0 -0.184056 0.354253 0.127323\natom 10.89623 0.65972 1.94553 Cu 0.0 0.0 -0.068814 -0.007404 -0.007446\natom 1.05267 6.44743 3.87592 Cu 0.0 0.0 0.126030 0.130493 -0.018135\natom -2.23212 10.62997 9.69737 Cu 0.0 0.0 0.068814 0.007404 0.007446\natom 7.61145 4.84226 7.76698 Cu 0.0 0.0 -0.126030 -0.130493 0.018135\natom -4.57795 2.06606 8.99064 Cu 0.0 0.0 -0.059501 0.057625 0.118793\natom 10.07640 7.94362 8.47370 Cu 0.0 0.0 0.207102 -0.010090 -0.059408\natom 13.24206 9.22363 2.65225 Cu 0.0 0.0 0.059501 -0.057625 -0.118793\natom -1.41229 3.34606 3.16920 Cu 0.0 0.0 -0.207102 0.010090 0.059408\natom 5.86072 0.81037 3.29960 Cu 0.0 0.0 -0.037658 -0.164186 0.178320\natom 6.07945 6.69751 2.52185 Cu 0.0 0.0 0.023242 0.267815 -0.195609\natom 2.80340 10.47932 8.34330 Cu 0.0 0.0 0.037658 0.164186 -0.178320\natom 2.58467 4.59218 9.12105 Cu 0.0 0.0 -0.023242 -0.267815 0.195609\natom 0.63842 0.24220 7.25352 Cu 0.0 0.0 0.269169 0.362496 0.388672\natom 4.94237 5.99221 10.21082 Cu 0.0 0.0 -0.075139 0.049768 -0.011560\natom 8.02570 11.04749 4.38937 Cu 0.0 0.0 -0.269169 -0.362496 -0.388672\natom 3.72175 5.29748 1.43208 Cu 0.0 0.0 0.075139 -0.049768 0.011560\natom 3.80072 0.44777 1.55898 Cu 0.0 0.0 0.192327 0.319006 0.272519\natom 8.15804 6.20709 4.26246 Cu 0.0 0.0 -0.259882 0.013256 0.109475\natom 4.86339 10.84192 10.08391 Cu 0.0 0.0 -0.192327 -0.319006 -0.272519\natom 0.50608 5.08259 7.38043 Cu 0.0 0.0 0.259882 -0.013256 -0.109475\natom 3.15647 2.11706 8.78224 Cu 0.0 0.0 0.240395 0.223919 0.114597\natom 2.34010 7.97932 8.68211 Cu 0.0 0.0 -0.159391 -0.062192 0.117324\natom 5.50765 9.17263 2.86066 Cu 0.0 0.0 -0.240395 -0.223919 -0.114597\natom 6.32402 3.31036 2.96079 Cu 0.0 0.0 0.159391 0.062192 -0.117324\natom 13.88191 0.91040 2.52185 Cu 0.0 0.0 0.036714 -0.045538 -0.002822\natom -1.94487 6.74043 3.29960 Cu 0.0 0.0 -0.026349 0.098805 -0.046173\natom -5.21780 10.37929 9.12105 Cu 0.0 0.0 -0.036714 0.045538 0.002822\natom 10.60899 4.54926 8.34330 Cu 0.0 0.0 0.026349 -0.098805 0.046173\natom 3.42066 0.80177 11.09684 Cu 0.0 0.0 -0.051305 0.296658 0.155193\natom 2.12957 6.83401 6.36750 Cu 0.0 0.0 0.041967 -0.254438 -0.167872\natom 5.24346 10.48791 0.54605 Cu 0.0 0.0 0.051305 -0.296658 -0.155193\natom 6.53455 4.45568 5.27540 Cu 0.0 0.0 -0.041967 0.254438 0.167872\natom 7.10594 2.03590 6.58872 Cu 0.0 0.0 0.307288 -0.070714 -0.032730\natom -1.60232 7.73709 10.87563 Cu 0.0 0.0 -0.106705 0.118413 -0.043582\natom 1.55818 9.25378 5.05418 Cu 0.0 0.0 -0.307288 0.070714 0.032730\natom 10.26644 3.55260 0.76727 Cu 0.0 0.0 0.106705 -0.118413 0.043582\natom 2.15784 2.36452 1.62768 Cu 0.0 0.0 -0.029242 0.021965 0.094936\natom 9.71722 8.12889 4.19377 Cu 0.0 0.0 0.175652 0.262082 0.097682\natom 6.50628 8.92517 10.01522 Cu 0.0 0.0 0.029242 -0.021965 -0.094936\natom -1.05310 3.16080 7.44913 Cu 0.0 0.0 -0.175652 -0.262082 -0.097682\natom -2.35496 0.84157 7.90669 Cu 0.0 0.0 -0.038739 0.277040 -0.072462\natom 7.90855 6.63954 9.55765 Cu 0.0 0.0 0.062858 -0.094191 0.124850\natom 11.01907 10.44811 3.73621 Cu 0.0 0.0 0.038739 -0.277040 0.072462\natom 0.75556 4.65015 2.08524 Cu 0.0 0.0 -0.062858 0.094191 -0.124850\nenergy -570.358649\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_18\nlattice 15.011776000 0.000000000 0.000000000\nlattice 0.491494000 11.988592000 0.000000000\nlattice -5.973837000 0.914122000 12.124300000\natom 9.38336 1.76373 10.21109 S 0.0 0.0 -0.166833 -0.136080 0.079977\natom -3.00510 7.58946 7.97536 S 0.0 0.0 0.112216 0.095154 -0.005929\natom 0.14608 11.13899 1.91321 S 0.0 0.0 0.166833 0.136080 -0.079977\natom 12.53453 5.31325 4.14894 S 0.0 0.0 -0.112216 -0.095154 0.005929\natom 12.10019 1.23719 4.19743 S 0.0 0.0 -0.241943 -0.413212 0.074910\natom 0.24591 7.05561 1.86472 S 0.0 0.0 0.224483 0.270266 0.112645\natom -2.57076 11.66552 7.92687 S 0.0 0.0 0.241943 0.413212 -0.074910\natom 9.28352 5.84710 10.25958 S 0.0 0.0 -0.224483 -0.270266 -0.112645\natom 8.93231 1.45114 6.14460 S 0.0 0.0 -0.138559 -0.257221 -0.290881\natom -2.55454 7.89006 12.04185 S 0.0 0.0 0.006732 0.191790 -0.383242\natom 0.59712 11.45158 5.97970 S 0.0 0.0 0.138559 0.257221 0.290881\natom 12.08398 5.01265 0.08245 S 0.0 0.0 -0.006732 -0.191790 0.383242\natom 11.88914 0.98495 0.07275 S 0.0 0.0 -0.116762 -0.079413 -0.131640\natom 0.46178 7.42534 5.98940 S 0.0 0.0 -0.186551 0.157799 -0.306767\natom -2.35970 11.91776 12.05155 S 0.0 0.0 0.116762 0.079413 0.131640\natom 9.06765 5.47737 6.13490 S 0.0 0.0 0.186551 -0.157799 0.306767\natom 3.12143 1.61922 7.43583 S 0.0 0.0 -0.071573 0.240668 0.232289\natom 3.26213 7.86344 10.75062 S 0.0 0.0 0.161793 -0.286266 0.506913\natom 6.40800 11.28349 4.68847 S 0.0 0.0 0.071573 -0.240668 -0.232289\natom 6.26730 5.03927 1.37368 S 0.0 0.0 -0.161793 0.286266 -0.506913\natom 6.13522 0.95785 1.16030 S 0.0 0.0 0.081655 -0.470983 -0.078363\natom 6.20675 7.23425 4.90185 S 0.0 0.0 -0.111162 0.340778 0.242398\natom 3.39421 11.94486 10.96400 S 0.0 0.0 -0.081655 0.470983 0.078363\natom 3.32268 5.66847 7.22245 S 0.0 0.0 0.111162 -0.340778 -0.242398\natom -0.15980 1.65554 9.53940 S 0.0 0.0 0.221078 0.000289 0.052863\natom 6.53334 7.58256 8.64705 S 0.0 0.0 -0.197778 -0.321521 -0.026844\natom 9.68923 11.24717 2.58490 S 0.0 0.0 -0.221078 -0.000289 -0.052863\natom 2.99610 5.32016 3.47725 S 0.0 0.0 0.197778 0.321521 0.026844\natom 2.59485 1.25971 3.47846 S 0.0 0.0 -0.480835 -0.006102 0.242653\natom 9.75754 7.18655 2.58369 S 0.0 0.0 0.282652 0.045312 0.344565\natom 6.93459 11.64300 8.64584 S 0.0 0.0 0.480835 0.006102 -0.242653\natom -0.22811 5.71617 9.54061 S 0.0 0.0 -0.282652 -0.045312 -0.344565\natom 6.25703 3.63437 8.75374 S 0.0 0.0 0.011989 -0.515443 0.086910\natom 0.28362 9.67985 9.43271 S 0.0 0.0 0.324115 0.365962 -0.135716\natom 3.27241 9.26835 3.37056 S 0.0 0.0 -0.011989 0.515443 -0.086910\natom 9.24581 3.22286 2.69159 S 0.0 0.0 -0.324115 -0.365962 0.135716\natom 5.84560 3.06276 5.05220 S 0.0 0.0 -0.052232 -0.299786 0.127035\natom 6.64490 8.75229 1.00995 S 0.0 0.0 -0.054852 -0.022767 -0.020124\natom 3.68383 9.83995 7.07210 S 0.0 0.0 0.052232 0.299786 -0.127035\natom 2.88454 4.15042 11.11435 S 0.0 0.0 0.054852 0.022767 0.020124\natom 0.22736 3.29375 5.77844 S 0.0 0.0 -0.193575 -0.366464 -0.036360\natom 12.27759 8.87377 0.28371 S 0.0 0.0 0.142848 0.393827 0.365457\natom 9.30207 9.60896 6.34586 S 0.0 0.0 0.193575 0.366464 0.036360\natom -2.74815 4.02895 11.84059 S 0.0 0.0 -0.142848 -0.393827 -0.365457\natom 0.04358 2.90791 1.61496 S 0.0 0.0 -0.112358 -0.335527 0.092071\natom 12.45547 9.11574 4.44719 S 0.0 0.0 -0.080637 -0.180157 0.233857\natom 9.48586 9.99480 10.50934 S 0.0 0.0 0.112358 0.335527 -0.092071\natom -2.92604 3.78697 7.67711 S 0.0 0.0 0.080637 0.180157 -0.233857\natom 11.35182 3.25992 3.54878 Cu 0.0 0.0 0.062440 0.260899 -0.071251\natom 1.16414 9.17615 2.51337 Cu 0.0 0.0 0.016713 -0.313960 0.000877\natom -1.82238 9.64280 8.57552 Cu 0.0 0.0 -0.062440 -0.260899 0.071251\natom 8.36529 3.72657 9.61093 Cu 0.0 0.0 -0.016713 0.313960 -0.000877\natom 5.25884 1.50556 8.20209 Cu 0.0 0.0 0.002966 0.274873 0.020167\natom 1.11067 7.63423 9.98436 Cu 0.0 0.0 -0.057059 -0.366096 -0.124015\natom 4.27060 11.39715 3.92221 Cu 0.0 0.0 -0.002966 -0.274873 -0.020167\natom 8.41876 5.26848 2.13994 Cu 0.0 0.0 0.057059 0.366096 0.124015\natom 8.20339 1.25145 2.03325 Cu 0.0 0.0 0.091476 0.331268 0.062852\natom 4.15725 7.39621 4.02890 Cu 0.0 0.0 -0.054384 -0.468746 0.134818\natom 1.32604 11.65126 10.09105 Cu 0.0 0.0 -0.091476 -0.331268 -0.062852\natom 5.37218 5.50650 8.09540 Cu 0.0 0.0 0.054384 0.468746 -0.134818\natom 5.12754 2.94408 0.88629 Cu 0.0 0.0 0.084114 0.270573 0.125950\natom 7.37898 9.26180 5.17586 Cu 0.0 0.0 0.036538 -0.347413 0.023959\natom 4.40189 9.95863 11.23801 Cu 0.0 0.0 -0.084114 -0.270573 -0.125950\natom 2.15045 3.64092 6.94844 Cu 0.0 0.0 -0.036538 0.347413 -0.023959\natom -3.68864 1.88177 11.45868 Cu 0.0 0.0 0.143452 0.503611 0.236168\natom 10.06887 7.51937 6.72777 Cu 0.0 0.0 -0.142997 -0.362640 -0.000286\natom 13.21808 11.02095 0.66562 Cu 0.0 0.0 -0.143452 -0.503611 -0.236168\natom -0.53943 5.38334 5.39653 Cu 0.0 0.0 0.142997 0.362640 0.000286\natom -1.00857 1.34357 5.36985 Cu 0.0 0.0 0.114400 0.356806 0.041984\natom 13.35615 6.98520 0.69230 Cu 0.0 0.0 -0.064111 -0.387625 -0.054750\natom 10.53801 11.55914 6.75445 Cu 0.0 0.0 -0.114400 -0.356806 -0.041984\natom -3.82671 5.91752 11.43200 Cu 0.0 0.0 0.064111 0.387625 0.054750\natom 8.16127 2.38528 12.03094 Cu 0.0 0.0 0.100375 0.176222 0.070855\natom -1.74330 7.93659 6.15551 Cu 0.0 0.0 0.182411 0.075419 0.288935\natom 1.36817 10.51744 0.09336 Cu 0.0 0.0 -0.100375 -0.176222 -0.070855\natom 11.27273 4.96613 5.96879 Cu 0.0 0.0 -0.182411 -0.075419 -0.288935\natom 11.15543 2.15890 6.18218 Cu 0.0 0.0 0.216047 0.174122 0.011645\natom -4.71986 8.59216 12.00427 Cu 0.0 0.0 0.046412 -0.021391 0.271316\natom -1.62599 10.74381 5.94212 Cu 0.0 0.0 -0.216047 -0.174122 -0.011645\natom 14.24929 4.31056 0.12003 Cu 0.0 0.0 -0.046412 0.021391 -0.271316\natom 9.09989 3.37756 4.98187 Cu 0.0 0.0 0.122743 0.487526 0.001429\natom 3.41686 9.07769 1.08028 Cu 0.0 0.0 -0.134188 -0.329399 -0.047976\natom 0.42955 9.52516 7.14243 Cu 0.0 0.0 -0.122743 -0.487526 -0.001429\natom 6.11258 3.82503 11.04402 Cu 0.0 0.0 0.134188 0.329399 0.047976\natom 1.13697 2.62524 11.33380 Cu 0.0 0.0 -0.007725 0.195219 0.009820\natom 5.30499 8.28167 6.85265 Cu 0.0 0.0 0.138761 0.076786 -0.211045\natom 8.39247 10.27748 0.79050 Cu 0.0 0.0 0.007725 -0.195219 -0.009820\natom 4.22444 4.62104 5.27165 Cu 0.0 0.0 -0.138761 -0.076786 0.211045\natom 3.82509 1.87451 5.32014 Cu 0.0 0.0 0.063680 0.114754 -0.203108\natom 8.56632 7.52364 0.74201 Cu 0.0 0.0 0.045594 0.147825 -0.297255\natom 5.70434 11.02820 6.80416 Cu 0.0 0.0 -0.063680 -0.114754 0.203108\natom 0.96311 5.37908 11.38229 Cu 0.0 0.0 -0.045594 -0.147825 0.297255\natom -1.09606 3.60336 10.31414 Cu 0.0 0.0 0.112849 0.041780 0.038763\natom 7.62452 9.41355 7.87231 Cu 0.0 0.0 -0.095116 0.015274 -0.015252\natom 10.62550 9.29936 1.81016 Cu 0.0 0.0 -0.112849 -0.041780 -0.038763\natom 1.90491 3.48917 4.25199 Cu 0.0 0.0 0.095116 -0.015274 0.015252\natom 8.26063 1.05354 8.28090 Cu 0.0 0.0 0.016279 -0.212870 0.203669\natom -1.92867 7.17033 9.90555 Cu 0.0 0.0 -0.014479 0.175244 0.361664\natom 1.26880 11.84918 3.84340 Cu 0.0 0.0 -0.016279 0.212870 -0.203669\natom 11.45811 5.73239 2.21875 Cu 0.0 0.0 0.014479 -0.175244 -0.361664\natom 10.78666 0.90084 2.02597 Cu 0.0 0.0 0.027634 0.099603 -0.037156\natom 1.54528 7.04670 4.03618 Cu 0.0 0.0 -0.112184 -0.072103 0.068043\natom -1.25723 12.00188 10.09833 Cu 0.0 0.0 -0.027634 -0.099603 0.037156\natom 7.98415 5.85602 8.08812 Cu 0.0 0.0 0.112184 0.072103 -0.068043\natom -4.12068 3.15755 9.36238 Cu 0.0 0.0 -0.105898 -0.053129 0.029849\natom 10.61847 9.11126 8.82407 Cu 0.0 0.0 -0.091125 0.096486 -0.023522\natom 13.65011 9.74516 2.76192 Cu 0.0 0.0 0.105898 0.053129 -0.029849\natom -1.08903 3.79145 3.30023 Cu 0.0 0.0 0.091125 -0.096486 0.023522\natom 5.89101 1.21216 3.43603 Cu 0.0 0.0 0.024483 0.318485 0.012590\natom 6.45775 7.14539 2.62612 Cu 0.0 0.0 0.032008 -0.186937 0.011693\natom 3.63843 11.69056 8.68827 Cu 0.0 0.0 -0.024483 -0.318485 -0.012590\natom 3.07169 5.75733 9.49818 Cu 0.0 0.0 -0.032008 0.186937 -0.011693\natom 0.83619 1.08980 7.55344 Cu 0.0 0.0 -0.188992 -0.143808 -0.075218\natom 5.50324 7.31629 10.63301 Cu 0.0 0.0 -0.057314 0.208219 -0.414012\natom 8.69324 11.81291 4.57086 Cu 0.0 0.0 0.188992 0.143808 0.075218\natom 4.02619 5.58643 1.49129 Cu 0.0 0.0 0.057314 -0.208219 0.414012\natom 3.79988 0.63911 1.62344 Cu 0.0 0.0 0.169202 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source_file_name=OUTCAR_3_22\nlattice 15.359573000 0.000000000 0.000000000\nlattice 0.047438000 12.116314000 0.000000000\nlattice -5.761711000 0.258638000 12.031632000\natom 9.85821 1.22227 10.13304 S 0.0 0.0 -0.017657 0.028493 -0.071468\natom -3.10962 7.23273 7.91441 S 0.0 0.0 -0.076018 0.111342 0.156903\natom -0.21291 11.15268 1.89859 S 0.0 0.0 0.017657 -0.028493 0.071468\natom 12.75492 5.14222 4.11722 S 0.0 0.0 0.076018 -0.111342 -0.156903\natom 12.46690 1.02007 4.16535 S 0.0 0.0 -0.198716 -0.144722 0.056900\natom 0.04282 7.02847 1.85046 S 0.0 0.0 0.185004 -0.069453 0.021066\natom -2.82160 11.35488 7.86628 S 0.0 0.0 0.198716 0.144722 -0.056900\natom 9.60248 5.34648 10.18117 S 0.0 0.0 -0.185004 0.069453 -0.021066\natom 9.27937 1.12946 6.09763 S 0.0 0.0 0.004745 -0.121267 -0.222180\natom -2.53083 7.31342 11.94982 S 0.0 0.0 -0.060928 -0.001826 0.086330\natom 0.36593 11.24549 5.93400 S 0.0 0.0 -0.004745 0.121267 0.222180\natom 12.17613 5.06153 0.08182 S 0.0 0.0 0.060928 0.001826 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-0.130468\natom 12.23394 8.95274 0.28154 S 0.0 0.0 0.091805 0.009164 0.260125\natom 9.35419 9.36316 6.29736 S 0.0 0.0 0.135243 0.090671 0.130468\natom -2.58864 3.42221 11.75009 S 0.0 0.0 -0.091805 -0.009164 -0.260125\natom -0.01457 2.85028 1.60261 S 0.0 0.0 0.050501 -0.183692 -0.296911\natom 12.53905 8.96886 4.41320 S 0.0 0.0 -0.127456 -0.179181 0.416995\natom 9.65987 9.52467 10.42902 S 0.0 0.0 -0.050501 0.183692 0.296911\natom -2.89375 3.40609 7.61843 S 0.0 0.0 0.127456 0.179181 -0.416995\natom 11.60374 3.09994 3.52166 Cu 0.0 0.0 -0.042968 -0.018916 -0.045351\natom 0.92238 9.13600 2.49416 Cu 0.0 0.0 0.043064 -0.095925 0.032763\natom -1.95844 9.27502 8.50997 Cu 0.0 0.0 0.042968 0.018916 0.045351\natom 8.72292 3.23895 9.53747 Cu 0.0 0.0 -0.043064 0.095925 -0.032763\natom 5.58411 1.07158 8.13940 Cu 0.0 0.0 -0.085144 0.001472 0.089573\natom 1.16364 7.16775 9.90805 Cu 0.0 0.0 0.062377 -0.088464 -0.109462\natom 4.06119 11.30338 3.89223 Cu 0.0 0.0 0.085144 -0.001472 -0.089573\natom 8.48166 5.20720 2.12358 Cu 0.0 0.0 -0.062377 0.088464 0.109462\natom 8.41052 1.15323 2.01770 Cu 0.0 0.0 0.055827 0.041252 -0.016347\natom 4.10061 7.25396 3.99811 Cu 0.0 0.0 -0.037279 -0.067448 0.063439\natom 1.23478 11.22172 10.01393 Cu 0.0 0.0 -0.055827 -0.041252 0.016347\natom 5.54469 5.12099 8.03352 Cu 0.0 0.0 0.037279 0.067448 -0.063439\natom 5.16266 2.92682 0.87951 Cu 0.0 0.0 -0.037955 0.003451 -0.007777\natom 7.36255 9.07648 5.13630 Cu 0.0 0.0 0.062805 -0.072531 0.026080\natom 4.48264 9.44813 11.15212 Cu 0.0 0.0 0.037955 -0.003451 0.007777\natom 2.28275 3.29847 6.89533 Cu 0.0 0.0 -0.062805 0.072531 -0.026080\natom -3.48148 1.27311 11.37110 Cu 0.0 0.0 0.113694 0.088107 0.063548\natom 10.23026 7.23035 6.67635 Cu 0.0 0.0 -0.101898 -0.035079 0.014247\natom 13.12678 11.10184 0.66054 Cu 0.0 0.0 -0.113694 -0.088107 -0.063548\natom -0.58496 5.14460 5.35528 Cu 0.0 0.0 0.101898 0.035079 -0.014247\natom -0.91235 1.06326 5.32881 Cu 0.0 0.0 0.032074 0.075852 -0.001371\natom 13.42222 7.02163 0.68701 Cu 0.0 0.0 -0.026110 -0.018069 0.002474\natom 10.55765 11.31169 6.70282 Cu 0.0 0.0 -0.032074 -0.075852 0.001371\natom -3.77692 5.35332 11.34463 Cu 0.0 0.0 0.026110 0.018069 -0.002474\natom 8.64202 1.75059 11.93899 Cu 0.0 0.0 -0.200705 0.215534 0.106341\natom -1.88960 7.68341 6.10846 Cu 0.0 0.0 0.297368 0.198007 -0.082739\natom 1.00328 10.62436 0.09264 Cu 0.0 0.0 0.200705 -0.215534 -0.106341\natom 11.53490 4.69154 5.92317 Cu 0.0 0.0 -0.297368 -0.198007 0.082739\natom 11.52830 1.84270 6.13493 Cu 0.0 0.0 0.026477 0.211047 0.021959\natom -4.77418 8.02506 11.91252 Cu 0.0 0.0 0.049968 0.179934 -0.003439\natom -1.88300 10.53225 5.89670 Cu 0.0 0.0 -0.026477 -0.211047 -0.021959\natom 14.41948 4.34989 0.11911 Cu 0.0 0.0 -0.049968 -0.179934 0.003439\natom 9.34071 3.14020 4.94380 Cu 0.0 0.0 0.179624 0.193057 0.220400\natom 3.18549 9.11513 1.07202 Cu 0.0 0.0 -0.173731 -0.007341 -0.235361\natom 0.30459 9.23475 7.08783 Cu 0.0 0.0 -0.179624 -0.193057 -0.220400\natom 6.45981 3.25982 10.95961 Cu 0.0 0.0 0.173731 0.007341 0.235361\natom 1.42371 2.03135 11.24717 Cu 0.0 0.0 -0.006965 0.249127 -0.043045\natom 5.33102 7.99392 6.80028 Cu 0.0 0.0 0.021252 0.223104 -0.011142\natom 8.22159 10.34360 0.78446 Cu 0.0 0.0 0.006965 -0.249127 0.043045\natom 4.31428 4.38103 5.23135 Cu 0.0 0.0 -0.021252 -0.223104 0.011142\natom 4.01155 1.60259 5.27948 Cu 0.0 0.0 0.025054 0.187158 -0.320648\natom 8.50254 7.56308 0.73634 Cu 0.0 0.0 -0.022385 0.204676 0.186808\natom 5.63375 10.77237 6.75215 Cu 0.0 0.0 -0.025054 -0.187158 0.320648\natom 1.14276 4.81187 11.29530 Cu 0.0 0.0 0.022385 -0.204676 -0.186808\natom -0.93061 3.07584 10.23531 Cu 0.0 0.0 0.244824 -0.069906 -0.018523\natom 7.69370 9.08191 7.81214 Cu 0.0 0.0 -0.234815 -0.027514 0.035215\natom 10.57591 9.29911 1.79632 Cu 0.0 0.0 -0.244824 0.069906 0.018523\natom 1.95160 3.29305 4.21949 Cu 0.0 0.0 0.234815 0.027514 -0.035215\natom 8.67512 0.61041 8.21760 Cu 0.0 0.0 -0.033526 -0.065280 0.128618\natom -1.93100 6.70323 9.82984 Cu 0.0 0.0 0.065136 -0.014491 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9.42558 Cu 0.0 0.0 -0.184743 -0.099369 0.005502\natom 11.23810 5.20634 8.62187 Cu 0.0 0.0 0.177345 -0.086675 -0.029066\natom 4.07781 1.49691 11.46735 Cu 0.0 0.0 -0.056855 -0.021027 -0.004325\natom 2.67270 7.45001 6.58010 Cu 0.0 0.0 0.087447 0.126079 -0.014360\natom 5.56749 10.87804 0.56428 Cu 0.0 0.0 0.056855 0.021027 0.004325\natom 6.97260 4.92494 5.45153 Cu 0.0 0.0 -0.087447 -0.126079 0.014360\natom 7.55720 2.50177 6.80870 Cu 0.0 0.0 0.012277 -0.023607 -0.074804\natom -0.79803 8.65516 11.23875 Cu 0.0 0.0 -0.095804 -0.070697 0.119990\natom 2.08810 9.87318 5.22293 Cu 0.0 0.0 -0.012277 0.023607 0.074804\natom 10.44333 3.71979 0.79288 Cu 0.0 0.0 0.095804 0.070697 -0.119990\natom 2.31925 2.54302 1.68202 Cu 0.0 0.0 -0.046905 -0.061358 0.136210\natom 10.20282 8.65818 4.33379 Cu 0.0 0.0 -0.000741 -0.098144 -0.123700\natom 7.32605 9.83193 10.34961 Cu 0.0 0.0 0.046905 0.061358 -0.136210\natom -0.55752 3.71677 7.69784 Cu 0.0 0.0 0.000741 0.098144 0.123700\natom -1.89916 1.34608 8.17068 Cu 0.0 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0.045730\natom 8.28681 3.20071 9.66979 Cu 0.0 0.0 -0.061732 0.139819 -0.017254\natom 5.18241 1.06318 8.25232 Cu 0.0 0.0 -0.050953 0.106345 0.066649\natom 0.82169 7.07358 10.04551 Cu 0.0 0.0 0.036427 -0.179572 -0.103473\natom 4.09609 11.14486 3.94623 Cu 0.0 0.0 0.050953 -0.106345 -0.066649\natom 8.45681 5.13446 2.15304 Cu 0.0 0.0 -0.036427 0.179572 0.103473\natom 8.30397 1.13844 2.04570 Cu 0.0 0.0 0.030730 0.104782 0.001073\natom 4.04299 7.15351 4.05358 Cu 0.0 0.0 -0.009333 -0.246909 0.069147\natom 0.97453 11.06960 10.15286 Cu 0.0 0.0 -0.030730 -0.104782 -0.001073\natom 5.23551 5.05453 8.14497 Cu 0.0 0.0 0.009333 0.246909 -0.069147\natom 5.16281 2.88567 0.89171 Cu 0.0 0.0 -0.000991 0.087603 0.023303\natom 7.27554 8.95092 5.20756 Cu 0.0 0.0 0.022479 -0.190739 0.036050\natom 4.11569 9.32237 11.30684 Cu 0.0 0.0 0.000991 -0.087603 -0.023303\natom 2.00296 3.25713 6.99099 Cu 0.0 0.0 -0.022479 0.190739 -0.036050\natom -4.00564 1.26459 11.52885 Cu 0.0 0.0 0.105899 0.257926 0.109435\natom 10.01646 7.13253 6.76898 Cu 0.0 0.0 -0.109759 -0.136147 -0.056043\natom 13.28414 10.94345 0.66970 Cu 0.0 0.0 -0.105899 -0.257926 -0.109435\natom -0.73795 5.07551 5.42958 Cu 0.0 0.0 0.109759 0.136147 0.056043\natom -1.15061 1.05258 5.40274 Cu 0.0 0.0 0.101030 0.126708 -0.021771\natom 13.48939 6.92169 0.69654 Cu 0.0 0.0 -0.067311 -0.200761 0.011720\natom 10.42912 11.15546 6.79581 Cu 0.0 0.0 -0.101030 -0.126708 0.021771\natom -4.21088 5.28636 11.50202 Cu 0.0 0.0 0.067311 0.200761 -0.011720\natom 8.05498 1.73571 12.10462 Cu 0.0 0.0 -0.041210 0.133888 -0.086578\natom -2.02052 7.57861 6.19321 Cu 0.0 0.0 0.109563 0.086909 0.257528\natom 1.22352 10.47233 0.09393 Cu 0.0 0.0 0.041210 -0.133888 0.086578\natom 11.29902 4.62943 6.00535 Cu 0.0 0.0 -0.109563 -0.086909 -0.257528\natom 11.22065 1.82156 6.22004 Cu 0.0 0.0 0.048118 0.107030 -0.094047\natom -5.17516 7.92033 12.07779 Cu 0.0 0.0 0.030779 0.030291 0.209931\natom -1.94215 10.38649 5.97851 Cu 0.0 0.0 -0.048118 -0.107030 0.094047\natom 14.45366 4.28772 0.12077 Cu 0.0 0.0 -0.030779 -0.030291 -0.209931\natom 9.12821 3.09946 5.01239 Cu 0.0 0.0 0.154435 0.188844 0.026886\natom 3.31655 8.98554 1.08689 Cu 0.0 0.0 -0.174644 -0.052501 -0.036266\natom 0.15030 9.10858 7.18617 Cu 0.0 0.0 -0.154435 -0.188844 -0.026886\natom 5.96195 3.22251 11.11166 Cu 0.0 0.0 0.174644 0.052501 0.036266\natom 0.90383 2.01187 11.40321 Cu 0.0 0.0 -0.024636 0.192456 0.120642\natom 5.14566 7.88527 6.89462 Cu 0.0 0.0 0.106161 0.146840 -0.155322\natom 8.37467 10.19617 0.79535 Cu 0.0 0.0 0.024636 -0.192456 -0.120642\natom 4.13284 4.32277 5.30393 Cu 0.0 0.0 -0.106161 -0.146840 0.155322\natom 3.76908 1.58415 5.35273 Cu 0.0 0.0 0.055005 0.170761 0.030521\natom 8.59716 7.45542 0.74655 Cu 0.0 0.0 0.006528 0.176171 -0.177685\natom 5.50942 10.62390 6.84583 Cu 0.0 0.0 -0.055005 -0.170761 -0.030521\natom 0.68134 4.75262 11.45200 Cu 0.0 0.0 -0.006528 -0.176171 0.177685\natom -1.36906 3.04054 10.37731 Cu 0.0 0.0 0.044785 0.089720 0.115769\natom 7.47275 8.95854 7.92052 Cu 0.0 0.0 -0.050998 -0.018604 -0.103138\natom 10.64757 9.16751 1.82124 Cu 0.0 0.0 -0.044785 -0.089720 -0.115769\natom 1.80575 3.24950 4.27803 Cu 0.0 0.0 0.050998 0.018604 0.103138\natom 8.24816 0.60869 8.33161 Cu 0.0 0.0 -0.029129 -0.125324 -0.040654\natom -2.26758 6.61564 9.96622 Cu 0.0 0.0 -0.022322 0.049622 0.240113\natom 1.03034 11.59935 3.86694 Cu 0.0 0.0 0.029129 0.125324 0.040654\natom 11.54608 5.59240 2.23234 Cu 0.0 0.0 0.022322 -0.049622 -0.240113\natom 10.94307 0.78955 2.03838 Cu 0.0 0.0 0.030375 0.016290 -0.116834\natom 1.38591 6.80494 4.06090 Cu 0.0 0.0 -0.088286 -0.015486 0.141967\natom -1.66457 11.41849 10.16017 Cu 0.0 0.0 -0.030375 -0.016290 0.116834\natom 7.89259 5.40310 8.13765 Cu 0.0 0.0 0.088286 0.015486 -0.141967\natom -4.42722 2.64710 9.41972 Cu 0.0 0.0 -0.037350 -0.045004 -0.046408\natom 10.51169 8.60674 8.87811 Cu 0.0 0.0 -0.055404 0.052381 0.050958\natom 13.70572 9.56094 2.77883 Cu 0.0 0.0 0.037350 0.045004 0.046408\natom -1.23319 3.60130 3.32045 Cu 0.0 0.0 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7.99338 5.34654 8.11411 Cu 0.0 0.0 0.071124 -0.011955 -0.049436\natom -4.10041 2.62701 9.39247 Cu 0.0 0.0 -0.041742 -0.040321 0.087343\natom 10.56496 8.51091 8.85242 Cu 0.0 0.0 -0.025843 0.022806 -0.071567\natom 13.51045 9.44454 2.77079 Cu 0.0 0.0 0.041742 0.040321 -0.087343\natom -1.15492 3.56064 3.31084 Cu 0.0 0.0 0.025843 -0.022806 0.071567\natom 5.94822 1.01657 3.44707 Cu 0.0 0.0 -0.005284 0.104844 0.007155\natom 6.33960 6.89422 2.63456 Cu 0.0 0.0 0.022234 -0.073020 0.000642\natom 3.46182 11.05498 8.71619 Cu 0.0 0.0 0.005284 -0.104844 -0.007155\natom 3.07044 5.17733 9.52870 Cu 0.0 0.0 -0.022234 0.073020 -0.000642\natom 0.92248 0.68560 7.57771 Cu 0.0 0.0 -0.091235 -0.053718 0.022875\natom 5.49158 6.65275 10.66718 Cu 0.0 0.0 0.010167 0.053941 -0.174933\natom 8.48757 11.38595 4.58555 Cu 0.0 0.0 0.091235 0.053718 -0.022875\natom 3.91847 5.41880 1.49608 Cu 0.0 0.0 -0.010167 -0.053941 0.174933\natom 3.83208 0.54562 1.62866 Cu 0.0 0.0 0.130089 -0.063840 -0.008263\natom 8.44433 6.50668 4.45297 Cu 0.0 0.0 -0.072261 0.074063 -0.149319\natom 5.57796 11.52594 10.53460 Cu 0.0 0.0 -0.130089 0.063840 0.008263\natom 0.96571 5.56487 7.71029 Cu 0.0 0.0 0.072261 -0.074063 0.149319\natom 3.53578 2.66565 9.17474 Cu 0.0 0.0 -0.003400 -0.065882 -0.089289\natom 2.92994 8.55954 9.07014 Cu 0.0 0.0 -0.029860 0.049608 0.004837\natom 5.87427 9.40590 2.98851 Cu 0.0 0.0 0.003400 0.065882 0.089289\natom 6.48011 3.51202 3.09312 Cu 0.0 0.0 0.029860 -0.049608 -0.004837\natom 13.84727 1.06987 2.63456 Cu 0.0 0.0 0.058455 0.090981 0.078033\natom -1.55754 6.98479 3.44707 Cu 0.0 0.0 -0.052253 0.016980 -0.050052\natom -4.43723 11.00168 9.52870 Cu 0.0 0.0 -0.058455 -0.090981 -0.078033\natom 10.96758 5.08676 8.71619 Cu 0.0 0.0 0.052253 -0.016980 0.050052\natom 3.84125 1.48289 11.59280 Cu 0.0 0.0 -0.034237 -0.058260 0.055365\natom 2.59155 7.26586 6.65209 Cu 0.0 0.0 0.051802 0.246546 -0.075381\natom 5.56879 10.58866 0.57046 Cu 0.0 0.0 0.034237 0.058260 -0.055365\natom 6.81850 4.80570 5.51117 Cu 0.0 0.0 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0.000000000\nlattice -0.551221000 11.982730000 0.000000000\nlattice -5.820617000 -0.307146000 12.017409000\natom 9.62160 0.73469 10.12106 S 0.0 0.0 -0.181039 -0.102028 0.036989\natom -3.50342 6.78269 7.90505 S 0.0 0.0 -0.079095 0.058626 0.086129\natom -0.77733 10.94089 1.89635 S 0.0 0.0 0.181039 0.102028 -0.036989\natom 12.34769 4.89289 4.11236 S 0.0 0.0 0.079095 -0.058626 -0.086129\natom 12.26549 0.81394 4.16043 S 0.0 0.0 -0.195452 0.148193 0.029450\natom -0.31997 6.86440 1.84828 S 0.0 0.0 0.207795 -0.329824 -0.045056\natom -3.42122 10.86164 7.85698 S 0.0 0.0 0.195452 -0.148193 -0.029450\natom 9.16423 4.81118 10.16913 S 0.0 0.0 -0.207795 0.329824 0.045056\natom 9.08628 0.83172 6.09042 S 0.0 0.0 -0.046197 0.073962 0.083264\natom -2.96755 6.67368 11.93569 S 0.0 0.0 -0.060972 -0.177434 0.335726\natom -0.24201 10.84387 5.92699 S 0.0 0.0 0.046197 -0.073962 -0.083264\natom 11.81182 5.00190 0.08172 S 0.0 0.0 0.060972 0.177434 -0.335726\natom 11.96663 0.97715 0.07210 S 0.0 0.0 0.187319 0.018512 -0.029937\natom -0.02652 6.81862 5.93660 S 0.0 0.0 -0.024109 0.010751 0.256414\natom -3.12237 10.69844 11.94530 S 0.0 0.0 -0.187319 -0.018512 0.029937\natom 8.87078 4.85696 6.08081 S 0.0 0.0 0.024109 -0.010751 -0.256414\natom 3.21509 0.86970 7.37028 S 0.0 0.0 -0.134362 -0.162023 0.000751\natom 2.89713 6.77709 10.65584 S 0.0 0.0 0.053087 0.064537 -0.267530\natom 5.62917 10.80588 4.64713 S 0.0 0.0 0.134362 0.162023 -0.000751\natom 5.94714 4.89849 1.36157 S 0.0 0.0 -0.053087 -0.064537 0.267530\natom 6.16498 0.84055 1.15007 S 0.0 0.0 0.091223 0.141895 -0.191458\natom 5.78516 6.73713 4.85864 S 0.0 0.0 -0.132024 -0.371038 0.132670\natom 2.67928 10.83503 10.86734 S 0.0 0.0 -0.091223 -0.141895 0.191458\natom 3.05910 4.93845 7.15877 S 0.0 0.0 0.132024 0.371038 -0.132670\natom -0.05940 0.69419 9.45530 S 0.0 0.0 0.162578 -0.094044 0.101626\natom 6.18287 6.70816 8.57082 S 0.0 0.0 -0.103266 -0.211875 -0.108676\natom 8.90367 10.98140 2.56211 S 0.0 0.0 -0.162578 0.094044 -0.101626\natom 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0.096736 -0.305518 0.183310\natom 8.75221 8.96529 6.28991 S 0.0 0.0 0.137933 -0.215205 0.218966\natom -2.83104 2.83472 11.73620 S 0.0 0.0 -0.096736 0.305518 -0.183310\natom -0.16847 2.74387 1.60072 S 0.0 0.0 0.123488 -0.153175 -0.326374\natom 11.94245 8.66349 4.40799 S 0.0 0.0 -0.072057 -0.362742 0.285883\natom 9.01274 8.93171 10.41669 S 0.0 0.0 -0.123488 0.153175 0.326374\natom -3.09818 3.01209 7.60942 S 0.0 0.0 0.072057 0.362742 -0.285883\natom 11.31304 2.90099 3.51750 Cu 0.0 0.0 -0.080609 -0.225391 -0.046227\natom 0.44197 8.91858 2.49121 Cu 0.0 0.0 -0.011654 0.155044 0.083824\natom -2.46878 8.77460 8.49991 Cu 0.0 0.0 0.080609 0.225391 0.046227\natom 8.40229 2.75700 9.52620 Cu 0.0 0.0 0.011654 -0.155044 -0.083824\natom 5.41142 0.67894 8.12978 Cu 0.0 0.0 -0.056531 -0.249103 0.101868\natom 0.71657 6.62515 9.89634 Cu 0.0 0.0 0.059063 0.174405 -0.025324\natom 3.43285 10.99665 3.88763 Cu 0.0 0.0 0.056531 0.249103 -0.101868\natom 8.12770 5.05043 2.12107 Cu 0.0 0.0 -0.059063 -0.174405 0.025324\natom 8.25826 1.04611 2.01532 Cu 0.0 0.0 0.017208 -0.323419 -0.116946\natom 3.67094 6.98692 3.99338 Cu 0.0 0.0 -0.039155 0.200981 0.016875\natom 0.58601 10.62947 10.00209 Cu 0.0 0.0 -0.017208 0.323419 0.116946\natom 5.17332 4.68867 8.02402 Cu 0.0 0.0 0.039155 -0.200981 -0.016875\natom 4.96262 2.85340 0.87847 Cu 0.0 0.0 -0.065993 -0.229987 -0.028653\natom 6.80298 8.73610 5.13023 Cu 0.0 0.0 0.050786 0.199954 -0.045838\natom 3.88164 8.82218 11.13894 Cu 0.0 0.0 0.065993 0.229987 0.028653\natom 2.04129 2.93948 6.88718 Cu 0.0 0.0 -0.050786 -0.199954 0.045838\natom -3.60629 0.72705 11.35765 Cu 0.0 0.0 0.095618 -0.258958 -0.006130\natom 9.72226 6.83826 6.66846 Cu 0.0 0.0 -0.095124 0.329849 -0.083485\natom 12.45055 10.94853 0.65976 Cu 0.0 0.0 -0.095618 0.258958 0.006130\natom -0.87799 4.83732 5.34895 Cu 0.0 0.0 0.095124 -0.329849 0.083485\natom -1.00060 0.80221 5.32251 Cu 0.0 0.0 -0.016979 -0.252378 0.013661\natom 12.94446 6.91207 0.68619 Cu 0.0 0.0 -0.041621 0.246863 -0.008163\natom 9.84486 10.87337 6.69490 Cu 0.0 0.0 0.016979 0.252378 -0.013661\natom -4.10020 4.76351 11.33121 Cu 0.0 0.0 0.041621 -0.246863 0.008163\natom 8.37568 1.17269 11.92487 Cu 0.0 0.0 -0.214950 0.131096 -0.097319\natom -2.30205 7.31290 6.10124 Cu 0.0 0.0 0.150545 0.203124 -0.172713\natom 0.46858 10.50289 0.09253 Cu 0.0 0.0 0.214950 -0.131096 0.097319\natom 11.14631 4.36269 5.91617 Cu 0.0 0.0 -0.150545 -0.203124 0.172713\natom 11.27867 1.53535 6.12768 Cu 0.0 0.0 -0.019049 0.094721 -0.106397\natom -5.22477 7.37922 11.89844 Cu 0.0 0.0 -0.075895 0.195414 -0.048322\natom -2.43441 10.14024 5.88973 Cu 0.0 0.0 0.019049 -0.094721 0.106397\natom 14.06904 4.29636 0.11897 Cu 0.0 0.0 0.075895 -0.195414 0.048322\natom 9.05734 2.87427 4.93795 Cu 0.0 0.0 0.175278 -0.076746 0.175916\natom 2.69679 8.96447 1.07075 Cu 0.0 0.0 -0.139898 0.257242 -0.172429\natom -0.21308 8.80131 7.07946 Cu 0.0 0.0 -0.175278 0.076746 -0.175916\natom 6.14748 2.71111 10.94666 Cu 0.0 0.0 0.139898 -0.257242 0.172429\natom 1.21668 1.48273 11.23387 Cu 0.0 0.0 -0.142815 0.120414 0.042993\natom 4.83005 7.58762 6.79224 Cu 0.0 0.0 -0.049818 0.228401 -0.008749\natom 7.62758 10.19285 0.78354 Cu 0.0 0.0 0.142815 -0.120414 -0.042993\natom 4.01421 4.08797 5.22517 Cu 0.0 0.0 0.049818 -0.228401 0.008749\natom 3.85110 1.33790 5.27324 Cu 0.0 0.0 -0.044256 0.161181 -0.056540\natom 8.04360 7.44525 0.73547 Cu 0.0 0.0 -0.106083 0.170072 0.253168\natom 4.99317 10.33768 6.74417 Cu 0.0 0.0 0.044256 -0.161181 0.056540\natom 0.80067 4.23034 11.28194 Cu 0.0 0.0 0.106083 -0.170072 -0.253168\natom -1.15881 2.56304 10.22321 Cu 0.0 0.0 0.196931 -0.122117 -0.021596\natom 7.10853 8.61626 7.80290 Cu 0.0 0.0 -0.185924 0.117906 -0.005247\natom 10.00307 9.11254 1.79420 Cu 0.0 0.0 -0.196931 0.122117 0.021596\natom 1.73573 3.05932 4.21451 Cu 0.0 0.0 0.185924 -0.117906 0.005247\natom 8.49568 0.21920 8.20789 Cu 0.0 0.0 0.056434 0.126610 -0.120240\natom -2.32558 6.16941 9.81822 Cu 0.0 0.0 0.104585 -0.171937 -0.184100\natom 0.34858 11.45638 3.80952 Cu 0.0 0.0 -0.056434 -0.126610 0.120240\natom 11.16985 5.50618 2.19919 Cu 0.0 0.0 -0.104585 0.171937 0.184100\natom 10.90719 0.69640 2.00811 Cu 0.0 0.0 0.007619 -0.025974 0.057939\natom 1.05420 6.63684 4.00060 Cu 0.0 0.0 0.119930 -0.008806 -0.117113\natom -2.06292 10.97919 10.00930 Cu 0.0 0.0 -0.007619 0.025974 -0.057939\natom 7.79006 5.03875 8.01681 Cu 0.0 0.0 -0.119930 0.008806 0.117113\natom -4.21027 2.21329 9.27984 Cu 0.0 0.0 -0.021258 0.049290 0.136483\natom 10.19438 8.21829 8.74627 Cu 0.0 0.0 0.219895 -0.142704 -0.166314\natom 13.05453 9.46229 2.73757 Cu 0.0 0.0 0.021258 -0.049290 -0.136483\natom -1.35012 3.45729 3.27114 Cu 0.0 0.0 -0.219895 0.142704 0.166314\natom 5.95423 0.86558 3.40573 Cu 0.0 0.0 -0.054552 -0.077539 0.137462\natom 5.98831 6.87746 2.60297 Cu 0.0 0.0 -0.001196 0.186064 -0.127463\natom 2.89004 10.81000 8.61168 Cu 0.0 0.0 0.054552 0.077539 -0.137462\natom 2.85595 4.79812 9.41444 Cu 0.0 0.0 0.001196 -0.186064 0.127463\natom 0.94814 0.32870 7.48685 Cu 0.0 0.0 0.055836 0.051515 0.131562\natom 5.21358 6.24205 10.53927 Cu 0.0 0.0 0.044157 -0.118439 0.138074\natom 7.89613 11.34689 4.53056 Cu 0.0 0.0 -0.055836 -0.051515 -0.131562\natom 3.63068 5.43354 1.47814 Cu 0.0 0.0 -0.044157 0.118439 -0.138074\natom 3.83777 0.47533 1.60913 Cu 0.0 0.0 0.043938 0.147317 0.109862\natom 8.14490 6.39537 4.39957 Cu 0.0 0.0 -0.228772 -0.121677 0.157885\natom 5.00649 11.20026 10.40828 Cu 0.0 0.0 -0.043938 -0.147317 -0.109862\natom 0.69937 5.28021 7.61784 Cu 0.0 0.0 0.228772 0.121677 -0.157885\natom 3.47255 2.26312 9.06473 Cu 0.0 0.0 0.060466 0.081282 -0.059828\natom 2.50749 8.25713 8.96138 Cu 0.0 0.0 0.029353 -0.146332 0.209844\natom 5.37172 9.41246 2.95268 Cu 0.0 0.0 -0.060466 -0.081282 0.059828\natom 6.33677 3.41845 3.05603 Cu 0.0 0.0 -0.029353 0.146332 -0.209844\natom 13.89600 0.95919 2.60297 Cu 0.0 0.0 0.129975 -0.053117 -0.029170\natom -1.96019 6.93004 3.40573 Cu 0.0 0.0 -0.168625 0.223347 -0.013639\natom -5.05174 10.71639 9.41444 Cu 0.0 0.0 -0.129975 0.053117 0.029170\natom 10.80445 4.74554 8.61168 Cu 0.0 0.0 0.168625 -0.223347 0.013639\natom 3.87055 0.94388 11.45379 Cu 0.0 0.0 -0.060313 0.326443 0.037706\natom 2.22524 7.06000 6.57232 Cu 0.0 0.0 0.099450 -0.193743 -0.047691\natom 4.97371 10.73171 0.56362 Cu 0.0 0.0 0.060313 -0.326443 -0.037706\natom 6.61902 4.61558 5.44509 Cu 0.0 0.0 -0.099450 0.193743 0.047691\natom 7.30653 2.15563 6.80065 Cu 0.0 0.0 0.168777 -0.104546 -0.092955\natom -1.31128 8.03390 11.22546 Cu 0.0 0.0 0.120191 0.131853 0.044588\natom 1.53774 9.51996 5.21676 Cu 0.0 0.0 -0.168777 0.104546 0.092955\natom 10.15554 3.64168 0.79195 Cu 0.0 0.0 -0.120191 -0.131853 -0.044588\natom 2.15806 2.43629 1.68003 Cu 0.0 0.0 0.069425 -0.144635 0.189701\natom 9.64403 8.35996 4.32867 Cu 0.0 0.0 0.077047 0.106078 -0.016921\natom 6.68621 9.23930 10.33737 Cu 0.0 0.0 -0.069425 0.144635 -0.189701\natom -0.79977 3.31563 7.68874 Cu 0.0 0.0 -0.077047 -0.106078 0.016921\natom -2.01576 0.94895 8.16102 Cu 0.0 0.0 0.017611 0.243942 0.030106\natom 8.11883 6.89676 9.86509 Cu 0.0 0.0 0.014297 -0.234095 0.015969\natom 10.86003 10.72664 3.85639 Cu 0.0 0.0 -0.017611 -0.243942 -0.030106\natom 0.72543 4.77882 2.15232 Cu 0.0 0.0 -0.014297 0.234095 -0.015969\nenergy -572.738073\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_44\nlattice 14.968507000 0.000000000 0.000000000\nlattice 0.447294000 11.894080000 0.000000000\nlattice -6.463893000 0.163272000 11.933936000\natom 8.92554 1.12353 10.05076 S 0.0 0.0 -0.179534 0.097162 0.138872\natom -3.35506 7.04046 7.85014 S 0.0 0.0 0.426870 -0.002238 -0.308333\natom 0.02637 10.93382 1.88318 S 0.0 0.0 0.179534 -0.097162 -0.138872\natom 12.30697 5.01689 4.08379 S 0.0 0.0 -0.426870 0.002238 0.308333\natom 11.88641 0.96999 4.13153 S 0.0 0.0 -0.395314 -0.266167 -0.108449\natom 0.14250 6.88562 1.83544 S 0.0 0.0 0.387986 0.223064 0.092776\natom -2.93450 11.08736 7.80241 S 0.0 0.0 0.395314 0.266167 0.108449\natom 8.80940 5.17173 10.09850 S 0.0 0.0 -0.387986 -0.223064 -0.092776\natom 8.64595 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6.55253 8.62135 0.99410 S 0.0 0.0 0.148959 -0.193069 0.038239\natom 3.34411 9.32861 6.96106 S 0.0 0.0 0.151215 0.250658 0.141222\natom 2.39938 3.43601 10.93984 S 0.0 0.0 -0.148959 0.193069 -0.038239\natom -0.02526 2.91336 5.68771 S 0.0 0.0 -0.277884 -0.260433 -0.348699\natom 12.19874 8.78641 0.27925 S 0.0 0.0 0.348854 0.256163 0.361314\natom 8.97717 9.14399 6.24622 S 0.0 0.0 0.277884 0.260433 0.348699\natom -3.24683 3.27094 11.65468 S 0.0 0.0 -0.348854 -0.256163 -0.361314\natom -0.03406 2.78593 1.58960 S 0.0 0.0 -0.081445 -0.368436 0.100190\natom 12.20217 8.77111 4.37737 S 0.0 0.0 0.047771 -0.181234 -0.096184\natom 8.98597 9.27142 10.34434 S 0.0 0.0 0.081445 0.368436 -0.100190\natom -3.25026 3.28624 7.55657 S 0.0 0.0 -0.047771 0.181234 0.096184\natom 11.15994 3.01655 3.49306 Cu 0.0 0.0 0.218678 0.197560 -0.012757\natom 1.02356 8.94965 2.47390 Cu 0.0 0.0 -0.115936 -0.188847 -0.018530\natom -2.20803 9.04080 8.44087 Cu 0.0 0.0 -0.218678 -0.197560 0.012757\natom 7.92835 3.10770 9.46003 Cu 0.0 0.0 0.115936 0.188847 0.018530\natom 4.89734 0.99062 8.07331 Cu 0.0 0.0 0.157599 0.189225 0.049301\natom 0.66517 6.96166 9.82760 Cu 0.0 0.0 -0.144782 -0.239314 -0.096046\natom 4.05457 11.06674 3.86063 Cu 0.0 0.0 -0.157599 -0.189225 -0.049301\natom 8.28674 5.09570 2.10634 Cu 0.0 0.0 0.144782 0.239314 0.096046\natom 8.09076 1.11688 2.00132 Cu 0.0 0.0 0.212487 0.196624 0.042856\natom 3.95139 7.09079 3.96565 Cu 0.0 0.0 -0.238112 -0.324514 0.012727\natom 0.86115 10.94047 9.93262 Cu 0.0 0.0 -0.212487 -0.196624 -0.042856\natom 5.00052 4.96656 7.96829 Cu 0.0 0.0 0.238112 0.324514 -0.012727\natom 5.06541 2.86651 0.87237 Cu 0.0 0.0 0.196941 0.106208 0.212935\natom 7.10949 8.87132 5.09460 Cu 0.0 0.0 -0.155401 -0.327172 -0.101865\natom 3.88649 9.19084 11.06157 Cu 0.0 0.0 -0.196941 -0.106208 -0.212935\natom 1.84241 3.18603 6.83934 Cu 0.0 0.0 0.155401 0.327172 0.101865\natom -4.16107 1.16412 11.27876 Cu 0.0 0.0 0.241194 0.326585 0.234804\natom 9.73333 7.04745 6.62214 Cu 0.0 0.0 -0.262943 -0.226119 -0.207668\natom 13.11298 10.89324 0.65517 Cu 0.0 0.0 -0.241194 -0.326585 -0.234804\natom -0.78143 5.00990 5.31179 Cu 0.0 0.0 0.262943 0.226119 0.207668\natom -1.23369 1.00362 5.28554 Cu 0.0 0.0 0.351608 0.218403 0.198588\natom 13.26394 6.88767 0.68143 Cu 0.0 0.0 -0.303701 -0.292043 -0.215292\natom 10.18560 11.05373 6.64840 Cu 0.0 0.0 -0.351608 -0.218403 -0.198588\natom -4.31203 5.16968 11.25251 Cu 0.0 0.0 0.303701 0.292043 0.215292\natom 7.62910 1.62855 11.84204 Cu 0.0 0.0 0.018350 0.068333 -0.112431\natom -2.02248 7.49647 6.05886 Cu 0.0 0.0 -0.007734 -0.000080 0.394202\natom 1.32281 10.42880 0.09189 Cu 0.0 0.0 -0.018350 -0.068333 0.112431\natom 10.97439 4.56088 5.87508 Cu 0.0 0.0 0.007734 0.000080 -0.394202\natom 10.85857 1.76270 6.08511 Cu 0.0 0.0 0.097445 0.033893 -0.104471\natom -5.23594 7.78814 11.81579 Cu 0.0 0.0 -0.073724 -0.062260 0.287918\natom -1.90666 10.29465 5.84882 Cu 0.0 0.0 -0.097445 -0.033893 0.104471\natom 14.18785 4.26921 0.11815 Cu 0.0 0.0 0.073724 0.062260 -0.287918\natom 8.85451 3.04537 4.90365 Cu 0.0 0.0 0.061061 0.172723 0.078743\natom 3.32971 8.93986 1.06331 Cu 0.0 0.0 -0.096314 -0.039169 -0.082166\natom 0.09740 9.01199 7.03028 Cu 0.0 0.0 -0.061061 -0.172723 -0.078743\natom 5.62220 3.11749 10.87062 Cu 0.0 0.0 0.096314 0.039169 0.082166\natom 0.65317 1.90938 11.15584 Cu 0.0 0.0 0.076117 0.213335 0.237251\natom 4.97528 7.79608 6.74506 Cu 0.0 0.0 0.073558 0.153641 -0.307487\natom 8.29874 10.14797 0.77809 Cu 0.0 0.0 -0.076117 -0.213335 -0.237251\natom 3.97663 4.26127 5.18888 Cu 0.0 0.0 -0.073558 -0.153641 0.307487\natom 3.58622 1.53343 5.23661 Cu 0.0 0.0 0.265458 0.208897 0.264317\natom 8.48393 7.41881 0.73036 Cu 0.0 0.0 -0.136651 0.198919 -0.438279\natom 5.36569 10.52393 6.69732 Cu 0.0 0.0 -0.265458 -0.208897 -0.264317\natom 0.46798 4.63854 11.20358 Cu 0.0 0.0 0.136651 -0.198919 0.438279\natom -1.53452 2.94233 10.15220 Cu 0.0 0.0 -0.041906 0.197889 0.068859\natom 7.24170 8.85649 7.74870 Cu 0.0 0.0 0.001960 -0.053984 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5.81671 Cu 0.0 0.0 -0.028933 -0.025652 -0.339143\natom 10.80342 1.74730 6.02466 Cu 0.0 0.0 0.049192 0.034970 -0.114152\natom -5.44724 7.83258 11.69840 Cu 0.0 0.0 -0.046728 -0.023306 0.221745\natom -2.09379 10.42632 5.79071 Cu 0.0 0.0 -0.049192 -0.034970 0.114152\natom 14.15687 4.34104 0.11697 Cu 0.0 0.0 0.046728 0.023306 -0.221745\natom 8.78911 3.06063 4.85494 Cu 0.0 0.0 0.043907 0.116535 0.227565\natom 3.21036 9.08418 1.05275 Cu 0.0 0.0 -0.067763 0.008745 -0.229009\natom -0.07949 9.11299 6.96044 Cu 0.0 0.0 -0.043907 -0.116535 -0.227565\natom 5.49927 3.08944 10.76262 Cu 0.0 0.0 0.067763 -0.008745 0.229009\natom 0.53457 1.85863 11.04501 Cu 0.0 0.0 0.133369 0.304556 0.276222\natom 4.82542 7.87850 6.67805 Cu 0.0 0.0 -0.053493 0.282949 -0.317531\natom 8.17506 10.31499 0.77036 Cu 0.0 0.0 -0.133369 -0.304556 -0.276222\natom 3.88421 4.29512 5.13732 Cu 0.0 0.0 0.053493 -0.282949 0.317531\natom 3.52817 1.52045 5.18459 Cu 0.0 0.0 0.347592 0.288994 0.337127\natom 8.39650 7.53971 0.72310 Cu 0.0 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6.38860 S 0.0 0.0 0.022455 -0.201406 0.120071\natom -2.60920 2.83538 11.92034 S 0.0 0.0 -0.013394 0.208766 -0.072911\natom -0.10790 2.72866 1.62583 S 0.0 0.0 0.086652 -0.154425 -0.424107\natom 12.22649 8.61440 4.47715 S 0.0 0.0 -0.054698 -0.249770 0.347231\natom 9.38366 8.89064 10.58012 S 0.0 0.0 -0.086652 0.154425 0.424107\natom -2.95072 3.00490 7.72881 S 0.0 0.0 0.054698 0.249770 -0.347231\natom 11.50613 2.88787 3.57268 Cu 0.0 0.0 -0.145431 -0.182936 -0.058800\natom 0.59833 8.86473 2.53030 Cu 0.0 0.0 0.086118 0.109421 0.092224\natom -2.23036 8.73143 8.63327 Cu 0.0 0.0 0.145431 0.182936 0.058800\natom 8.67744 2.75457 9.67566 Cu 0.0 0.0 -0.086118 -0.109421 -0.092224\natom 5.61127 0.68773 8.25733 Cu 0.0 0.0 -0.123223 -0.219594 0.096198\natom 0.98080 6.59821 10.05161 Cu 0.0 0.0 0.142795 0.100951 -0.043628\natom 3.66450 10.93157 3.94863 Cu 0.0 0.0 0.123223 0.219594 -0.096198\natom 8.29497 5.02109 2.15435 Cu 0.0 0.0 -0.142795 -0.100951 0.043628\natom 8.37631 1.04259 2.04694 Cu 0.0 0.0 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0.65853 Cu 0.0 0.0 -0.049275 -0.152936 -0.162463\natom -0.81963 5.14082 5.33898 Cu 0.0 0.0 0.036830 0.108809 -0.036709\natom -1.10676 1.18500 5.31259 Cu 0.0 0.0 -0.013819 0.053962 -0.007900\natom 13.21363 6.82430 0.68492 Cu 0.0 0.0 0.005469 -0.148826 0.002226\natom 10.11864 11.15620 6.68242 Cu 0.0 0.0 0.013819 -0.053962 0.007900\natom -4.20175 5.51689 11.31010 Cu 0.0 0.0 -0.005469 0.148826 -0.002226\natom 8.11563 2.04289 11.90265 Cu 0.0 0.0 -0.016694 0.086681 -0.066142\natom -2.16241 7.62293 6.08987 Cu 0.0 0.0 0.278137 0.017950 0.172163\natom 0.89624 10.29831 0.09236 Cu 0.0 0.0 0.016694 -0.086681 0.066142\natom 11.17428 4.71826 5.90514 Cu 0.0 0.0 -0.278137 -0.017950 -0.172163\natom 11.18544 1.96372 6.11626 Cu 0.0 0.0 0.093894 0.088954 -0.071208\natom -5.23439 8.12244 11.87626 Cu 0.0 0.0 0.141962 -0.044850 0.193822\natom -2.17357 10.37748 5.87876 Cu 0.0 0.0 -0.093894 -0.088954 0.071208\natom 14.24627 4.21875 0.11875 Cu 0.0 0.0 -0.141962 0.044850 -0.193822\natom 9.04921 3.18650 4.92875 Cu 0.0 0.0 0.171457 0.399526 -0.018755\natom 3.03669 8.86419 1.06876 Cu 0.0 0.0 -0.150600 -0.242100 -0.016786\natom -0.03734 9.15469 7.06626 Cu 0.0 0.0 -0.171457 -0.399526 0.018755\natom 5.97518 3.47700 10.92626 Cu 0.0 0.0 0.150600 0.242100 0.016786\natom 0.98506 2.29489 11.21294 Cu 0.0 0.0 -0.069762 0.143728 0.013435\natom 4.96520 7.94391 6.77958 Cu 0.0 0.0 0.001648 0.134130 -0.182274\natom 8.02682 10.04631 0.78207 Cu 0.0 0.0 0.069762 -0.143728 -0.013435\natom 4.04668 4.39729 5.21543 Cu 0.0 0.0 -0.001648 -0.134130 0.182274\natom 3.76969 1.70621 5.26341 Cu 0.0 0.0 0.062272 0.126361 -0.112579\natom 8.33175 7.35043 0.73409 Cu 0.0 0.0 -0.123871 0.200997 -0.214536\natom 5.24219 10.63499 6.73160 Cu 0.0 0.0 -0.062272 -0.126361 0.112579\natom 0.68013 4.99077 11.26092 Cu 0.0 0.0 0.123871 -0.200997 0.214536\natom -1.32064 3.27769 10.20416 Cu 0.0 0.0 0.055412 -0.058178 0.126158\natom 7.26017 9.02760 7.78836 Cu 0.0 0.0 -0.004297 0.231628 -0.129225\natom 10.33251 9.06350 1.79086 Cu 0.0 0.0 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0.208346 0.013961\natom 6.20391 6.93406 2.59812 Cu 0.0 0.0 0.012843 -0.163049 0.043226\natom 3.10906 11.23777 8.59563 Cu 0.0 0.0 0.012114 -0.208346 -0.013961\natom 2.80797 5.40714 9.39689 Cu 0.0 0.0 -0.012843 0.163049 -0.043226\natom 0.76682 0.88325 7.47289 Cu 0.0 0.0 -0.073561 -0.024060 0.055042\natom 5.19614 6.90630 10.51963 Cu 0.0 0.0 -0.138070 0.209116 -0.308618\natom 8.24506 11.45795 4.52212 Cu 0.0 0.0 0.073561 0.024060 -0.055042\natom 3.81574 5.43490 1.47539 Cu 0.0 0.0 0.138070 -0.209116 0.308618\natom 3.81652 0.58637 1.60613 Cu 0.0 0.0 0.108820 -0.019438 -0.044770\natom 8.29463 6.59634 4.39137 Cu 0.0 0.0 -0.159062 0.162538 -0.258573\natom 5.19535 11.75483 10.38888 Cu 0.0 0.0 -0.108820 0.019438 0.044770\natom 0.71724 5.74486 7.60364 Cu 0.0 0.0 0.159062 -0.162538 0.258573\natom 3.33010 2.89698 9.04784 Cu 0.0 0.0 0.050720 -0.051727 -0.073597\natom 2.61279 8.76253 8.94468 Cu 0.0 0.0 -0.093278 0.119922 -0.087309\natom 5.68178 9.44421 2.94717 Cu 0.0 0.0 -0.050720 0.051727 0.073597\natom 6.39909 3.57867 3.05033 Cu 0.0 0.0 0.093278 -0.119922 0.087309\natom 13.87185 1.13498 2.59812 Cu 0.0 0.0 -0.002698 -0.003103 0.121164\natom -1.76587 7.04575 3.39939 Cu 0.0 0.0 -0.008905 0.067727 -0.062186\natom -4.85998 11.20622 9.39689 Cu 0.0 0.0 0.002698 0.003103 -0.121164\natom 10.77775 5.29545 8.59563 Cu 0.0 0.0 0.008905 -0.067727 0.062186\natom 3.61198 1.78337 11.43245 Cu 0.0 0.0 0.011913 -0.099193 0.081241\natom 2.34370 7.41044 6.56007 Cu 0.0 0.0 0.085094 0.247036 -0.130686\natom 5.39990 10.55782 0.56257 Cu 0.0 0.0 -0.011913 0.099193 -0.081241\natom 6.66818 4.93075 5.43494 Cu 0.0 0.0 -0.085094 -0.247036 0.130686\natom 7.21989 2.62195 6.78798 Cu 0.0 0.0 -0.027768 0.104775 0.032848\natom -1.27532 8.71350 11.20454 Cu 0.0 0.0 -0.071144 0.036733 0.022693\natom 1.79199 9.71924 5.20703 Cu 0.0 0.0 0.027768 -0.104775 -0.032848\natom 10.28720 3.62770 0.79047 Cu 0.0 0.0 0.071144 -0.036733 -0.022693\natom 2.21469 2.51315 1.67690 Cu 0.0 0.0 -0.058356 0.135929 -0.017449\natom 9.87651 8.51604 4.32060 Cu 0.0 0.0 -0.021711 0.050082 -0.026307\natom 6.79718 9.82805 10.31811 Cu 0.0 0.0 0.058356 -0.135929 0.017449\natom -0.86464 3.82515 7.67441 Cu 0.0 0.0 0.021711 -0.050082 0.026307\natom -2.19020 1.54154 8.14581 Cu 0.0 0.0 0.001313 -0.010607 -0.061414\natom 8.14668 7.49729 9.84670 Cu 0.0 0.0 -0.022138 0.129668 -0.006417\natom 11.20208 10.79966 3.84920 Cu 0.0 0.0 -0.001313 0.010607 0.061414\natom 0.86520 4.84391 2.14831 Cu 0.0 0.0 0.022138 -0.129668 0.006417\nenergy -572.421187\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_62\nlattice 15.110213000 0.000000000 0.000000000\nlattice 0.537764000 11.977546000 0.000000000\nlattice -5.399614000 -0.041333000 12.205022000\natom 9.96506 0.95813 10.27907 S 0.0 0.0 0.127819 0.116312 -0.236805\natom -2.59622 6.95452 8.02846 S 0.0 0.0 0.321817 -0.292752 -0.025674\natom 0.28331 10.97808 1.92595 S 0.0 0.0 -0.127819 -0.116312 0.236805\natom 12.84458 4.98169 4.17656 S 0.0 0.0 -0.321817 0.292752 0.025674\natom 12.39520 0.90557 4.22538 S 0.0 0.0 -0.211617 -0.271819 0.092346\natom 0.36669 6.90229 1.87713 S 0.0 0.0 0.214689 0.081688 -0.186853\natom -2.14683 11.03065 7.97964 S 0.0 0.0 0.211617 0.271819 -0.092346\natom 9.88167 5.03392 10.32789 S 0.0 0.0 -0.214689 -0.081688 0.186853\natom 9.30530 0.96600 6.18550 S 0.0 0.0 0.159108 -0.296087 -0.350471\natom -1.93700 6.93467 12.12203 S 0.0 0.0 0.119665 -0.159549 0.104326\natom 0.94307 10.97021 6.01952 S 0.0 0.0 -0.159108 0.296087 0.350471\natom 12.18536 5.00154 0.08299 S 0.0 0.0 -0.119665 0.159549 -0.104326\natom 11.97429 0.97832 0.07323 S 0.0 0.0 0.021383 -0.000006 -0.273494\natom 0.79287 6.94692 6.02928 S 0.0 0.0 -0.071864 -0.137697 0.198657\natom -1.72593 10.95790 12.13179 S 0.0 0.0 -0.021383 0.000006 0.273494\natom 9.45550 4.98929 6.17574 S 0.0 0.0 0.071864 0.137697 -0.198657\natom 3.52190 1.03227 7.48534 S 0.0 0.0 0.019593 0.035198 0.188954\natom 3.85275 7.00974 10.82219 S 0.0 0.0 0.026884 0.025246 -0.231093\natom 6.72647 10.90395 4.71968 S 0.0 0.0 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0.79491 8.92825 9.49551 S 0.0 0.0 0.168058 0.237335 -0.167232\natom 3.49676 8.99443 3.39300 S 0.0 0.0 0.180578 0.112006 -0.390836\natom 9.45346 3.00797 2.70951 S 0.0 0.0 -0.168058 -0.237335 0.167232\natom 6.14916 2.66215 5.08583 S 0.0 0.0 0.155183 -0.240981 0.046928\natom 6.77072 8.66471 1.01668 S 0.0 0.0 -0.099955 -0.131209 -0.163622\natom 4.09920 9.27406 7.11919 S 0.0 0.0 -0.155183 0.240981 -0.046928\natom 3.47764 3.27151 11.18834 S 0.0 0.0 0.099955 0.131209 0.163622\natom 0.53146 2.83575 5.81691 S 0.0 0.0 -0.095738 -0.237212 -0.163869\natom 12.40424 8.84325 0.28560 S 0.0 0.0 0.199716 0.132356 -0.002716\natom 9.71690 9.10047 6.38811 S 0.0 0.0 0.095738 0.237212 0.163869\natom -2.15587 3.09296 11.91942 S 0.0 0.0 -0.199716 -0.132356 0.002716\natom 0.13557 2.77808 1.62571 S 0.0 0.0 0.081420 -0.330275 -0.655466\natom 12.79367 8.75719 4.47680 S 0.0 0.0 -0.053664 -0.105605 0.518787\natom 10.11279 9.15814 10.57931 S 0.0 0.0 -0.081420 0.330275 0.655466\natom -2.54531 3.17902 7.72822 S 0.0 0.0 0.053664 0.105605 -0.518787\natom 11.61654 2.97750 3.57241 Cu 0.0 0.0 0.004802 0.054664 -0.072201\natom 1.33120 8.96980 2.53010 Cu 0.0 0.0 0.104753 -0.201410 0.055109\natom -1.36817 8.95872 8.63261 Cu 0.0 0.0 -0.004802 -0.054664 0.072201\natom 8.91716 2.96641 9.67492 Cu 0.0 0.0 -0.104753 0.201410 -0.055109\natom 5.71147 0.85838 8.25670 Cu 0.0 0.0 -0.031768 0.037671 0.053650\natom 1.64780 6.84107 10.05084 Cu 0.0 0.0 0.069626 -0.229016 -0.114567\natom 4.53690 11.07784 3.94832 Cu 0.0 0.0 0.031768 -0.037671 -0.053650\natom 8.60057 5.09514 2.15419 Cu 0.0 0.0 -0.069626 0.229016 0.114567\natom 8.36400 1.09021 2.04678 Cu 0.0 0.0 -0.009068 0.122091 -0.035994\natom 4.41381 7.07218 4.05573 Cu 0.0 0.0 -0.004257 -0.223393 0.080015\natom 1.88437 10.84600 10.15824 Cu 0.0 0.0 0.009068 -0.122091 0.035994\natom 5.83455 4.86403 8.14929 Cu 0.0 0.0 0.004257 0.223393 -0.080015\natom 5.21634 2.87159 0.89219 Cu 0.0 0.0 -0.141059 0.190825 -0.013539\natom 7.72108 8.84574 5.21032 Cu 0.0 0.0 0.101445 -0.123940 0.048327\natom 5.03203 9.06462 11.31283 Cu 0.0 0.0 0.141059 -0.190825 0.013539\natom 2.52729 3.09047 6.99470 Cu 0.0 0.0 -0.101445 0.123940 -0.048327\natom -3.12946 0.97783 11.53497 Cu 0.0 0.0 0.049389 0.274976 -0.019132\natom 10.50044 6.98273 6.77257 Cu 0.0 0.0 -0.059091 -0.131918 0.016648\natom 13.37782 10.95838 0.67006 Cu 0.0 0.0 -0.049389 -0.274976 0.019132\natom -0.25208 4.95348 5.43246 Cu 0.0 0.0 0.059091 0.131918 -0.016648\natom -0.74014 0.91954 5.40560 Cu 0.0 0.0 -0.057667 0.194012 -0.025496\natom 13.50365 6.92425 0.69691 Cu 0.0 0.0 0.113081 -0.161205 0.029548\natom 10.98851 11.01668 6.79942 Cu 0.0 0.0 0.057667 -0.194012 0.025496\natom -3.25528 5.01196 11.50811 Cu 0.0 0.0 -0.113081 0.161205 -0.029548\natom 8.82876 1.43582 12.11104 Cu 0.0 0.0 -0.176385 0.263847 0.277805\natom -1.41648 7.44462 6.19649 Cu 0.0 0.0 0.084842 0.237319 -0.052503\natom 1.41960 10.50040 0.09398 Cu 0.0 0.0 0.176385 -0.263847 -0.277805\natom 11.66484 4.49159 6.00853 Cu 0.0 0.0 -0.084842 -0.237319 0.052503\natom 11.54742 1.67015 6.22334 Cu 0.0 0.0 0.096375 0.261845 0.080796\natom -4.11588 7.63908 12.08419 Cu 0.0 0.0 -0.128369 0.233925 0.011051\natom -1.29906 10.26606 5.98168 Cu 0.0 0.0 -0.096375 -0.261845 -0.080796\natom 14.36425 4.29713 0.12083 Cu 0.0 0.0 0.128369 -0.233925 -0.011051\natom 9.42238 2.98219 5.01504 Cu 0.0 0.0 0.140483 0.127018 0.126267\natom 3.52622 8.98427 1.08747 Cu 0.0 0.0 -0.180580 0.080266 -0.100715\natom 0.82598 8.95402 7.18998 Cu 0.0 0.0 -0.140483 -0.127018 -0.126267\natom 6.72215 2.95195 11.11755 Cu 0.0 0.0 0.180580 -0.080266 0.100715\natom 1.72418 1.73045 11.40925 Cu 0.0 0.0 -0.026534 0.160863 -0.027219\natom 5.71435 7.73450 6.89828 Cu 0.0 0.0 0.255929 0.036465 0.090658\natom 8.52418 10.20577 0.79577 Cu 0.0 0.0 0.026534 -0.160863 0.027219\natom 4.53402 4.20172 5.30674 Cu 0.0 0.0 -0.255929 -0.036465 -0.090658\natom 4.12463 1.45390 5.35556 Cu 0.0 0.0 -0.022018 0.132677 -0.266094\natom 8.68685 7.45828 0.74695 Cu 0.0 0.0 0.220034 0.067996 0.260738\natom 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2.41749 9.42472 Cu 0.0 0.0 -0.184793 -0.173235 0.226266\natom 11.16485 8.40810 8.88281 Cu 0.0 0.0 -0.003379 0.058381 -0.189314\natom 13.91360 9.51872 2.78030 Cu 0.0 0.0 0.184793 0.173235 -0.226266\natom -0.91649 3.52811 3.32221 Cu 0.0 0.0 0.003379 -0.058381 0.189314\natom 6.10689 0.94050 3.45890 Cu 0.0 0.0 -0.011264 0.076665 0.077458\natom 6.65790 6.93204 2.64361 Cu 0.0 0.0 0.053886 -0.017326 -0.119291\natom 4.14147 10.99571 8.74612 Cu 0.0 0.0 0.011264 -0.076665 -0.077458\natom 3.59047 5.00418 9.56141 Cu 0.0 0.0 -0.053886 0.017326 0.119291\natom 1.22569 0.49408 7.60373 Cu 0.0 0.0 -0.060253 -0.138627 -0.173083\natom 6.10067 6.47235 10.70380 Cu 0.0 0.0 0.077010 -0.099372 0.026073\natom 9.02268 11.44214 4.60129 Cu 0.0 0.0 0.060253 0.138627 0.173083\natom 4.14770 5.46386 1.50122 Cu 0.0 0.0 -0.077010 0.099372 -0.026073\natom 3.90878 0.51070 1.63425 Cu 0.0 0.0 0.208682 -0.130961 -0.136516\natom 8.81686 6.48987 4.46826 Cu 0.0 0.0 -0.015002 0.021333 0.004975\natom 6.33958 11.42552 10.57077 Cu 0.0 0.0 -0.208682 0.130961 0.136516\natom 1.43150 5.44634 7.73676 Cu 0.0 0.0 0.015002 -0.021333 -0.004975\natom 3.96132 2.46255 9.20625 Cu 0.0 0.0 -0.088217 -0.129268 -0.244168\natom 3.54228 8.45168 9.10128 Cu 0.0 0.0 -0.005616 -0.015359 0.153653\natom 6.28704 9.47367 2.99877 Cu 0.0 0.0 0.088217 0.129268 0.244168\natom 6.70608 3.48454 3.10374 Cu 0.0 0.0 0.005616 0.015359 -0.153653\natom 13.97460 1.01633 2.64361 Cu 0.0 0.0 0.220412 0.256949 -0.034529\natom -1.20325 7.00234 3.45890 Cu 0.0 0.0 -0.175442 -0.068308 0.052004\natom -3.72624 10.91989 9.56141 Cu 0.0 0.0 -0.220412 -0.256949 0.034529\natom 11.45161 4.93388 8.74612 Cu 0.0 0.0 0.175442 0.068308 -0.052004\natom 4.31826 1.19669 11.63261 Cu 0.0 0.0 -0.113350 -0.033312 0.046633\natom 3.07241 7.20225 6.67493 Cu 0.0 0.0 0.035215 0.253275 0.004535\natom 5.93011 10.73952 0.57242 Cu 0.0 0.0 0.113350 0.033312 -0.046633\natom 7.17595 4.73396 5.53010 Cu 0.0 0.0 -0.035215 -0.253275 -0.004535\natom 7.68196 2.30504 6.90682 Cu 0.0 0.0 -0.198500 0.152088 -0.091986\natom -0.19320 8.27860 11.40071 Cu 0.0 0.0 -0.049053 -0.056427 0.095959\natom 2.56641 9.63117 5.29820 Cu 0.0 0.0 0.198500 -0.152088 0.091986\natom 10.44156 3.65761 0.80431 Cu 0.0 0.0 0.049053 0.056427 -0.095959\natom 2.42075 2.47238 1.70626 Cu 0.0 0.0 -0.014507 0.046491 0.079821\natom 10.48107 8.45204 4.39625 Cu 0.0 0.0 -0.087687 -0.156102 -0.253999\natom 7.82762 9.46384 10.49876 Cu 0.0 0.0 0.014507 -0.046491 -0.079821\natom -0.23270 3.48417 7.80877 Cu 0.0 0.0 0.087687 0.156102 0.253999\natom -1.63851 1.12896 8.28843 Cu 0.0 0.0 0.069324 -0.225031 0.040708\natom 9.02208 7.11187 10.01910 Cu 0.0 0.0 -0.072791 0.151412 -0.058514\natom 11.88688 10.80725 3.91659 Cu 0.0 0.0 -0.069324 0.225031 -0.040708\natom 1.22628 4.82434 2.18592 Cu 0.0 0.0 0.072791 -0.151412 0.058514\nenergy -572.495163\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_67\nlattice 15.082966000 0.000000000 0.000000000\nlattice -0.414362000 11.922623000 0.000000000\nlattice -5.952643000 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0.143451\natom -3.15565 10.56819 12.00141 S 0.0 0.0 -0.140774 -0.052319 -0.095637\natom 8.75582 4.79361 6.10937 S 0.0 0.0 -0.017150 -0.006026 -0.143451\natom 3.08642 0.81809 7.40489 S 0.0 0.0 -0.152201 -0.165752 -0.161800\natom 2.78723 6.67478 10.70588 S 0.0 0.0 0.090444 0.074276 -0.164651\natom 5.62954 10.72188 4.66896 S 0.0 0.0 0.152201 0.165752 0.161800\natom 5.92873 4.86519 1.36797 S 0.0 0.0 -0.090444 -0.074276 0.164651\natom 6.10312 0.82896 1.15547 S 0.0 0.0 0.107101 0.168272 -0.203049\natom 5.73618 6.67219 4.88146 S 0.0 0.0 -0.130541 -0.346187 0.128051\natom 2.61284 10.71101 10.91838 S 0.0 0.0 -0.107101 -0.168272 0.203049\natom 2.97978 4.86778 7.19239 S 0.0 0.0 0.130541 0.346187 -0.128051\natom -0.19252 0.63008 9.49970 S 0.0 0.0 0.245656 -0.176491 0.044044\natom 6.07462 6.61956 8.61107 S 0.0 0.0 -0.215821 -0.154065 -0.060958\natom 8.90848 10.90988 2.57414 S 0.0 0.0 -0.245656 0.176491 -0.044044\natom 2.64134 4.92041 3.46278 S 0.0 0.0 0.215821 0.154065 0.060958\natom 2.54580 0.88218 3.46399 S 0.0 0.0 -0.278725 0.035956 -0.237059\natom 9.28471 6.87173 2.57294 S 0.0 0.0 0.539634 -0.015612 -0.092102\natom 6.17016 10.65779 8.60986 S 0.0 0.0 0.278725 -0.035956 0.237059\natom -0.56875 4.66824 9.50091 S 0.0 0.0 -0.539634 0.015612 0.092102\natom 6.09713 2.68173 8.71732 S 0.0 0.0 -0.242599 0.233440 0.098010\natom -0.35592 8.62161 9.39345 S 0.0 0.0 0.089111 -0.323596 -0.150542\natom 2.61883 8.85824 3.35653 S 0.0 0.0 0.242599 -0.233440 -0.098010\natom 9.07188 2.91836 2.68039 S 0.0 0.0 -0.089111 0.323596 0.150542\natom 5.69080 2.50764 5.03117 S 0.0 0.0 -0.009188 -0.134589 0.074641\natom 6.02328 8.59653 1.00575 S 0.0 0.0 0.030467 -0.276209 -0.083706\natom 3.02516 9.03233 7.04268 S 0.0 0.0 0.009188 0.134589 -0.074641\natom 2.69268 2.94344 11.06810 S 0.0 0.0 -0.030467 0.276209 0.083706\natom 0.03553 2.65998 5.75440 S 0.0 0.0 -0.147330 0.236209 -0.256729\natom 11.66636 8.79471 0.28253 S 0.0 0.0 0.139804 -0.265589 0.153758\natom 8.68043 8.87999 6.31945 S 0.0 0.0 0.147330 -0.236209 0.256729\natom -2.95040 2.74526 11.79132 S 0.0 0.0 -0.139804 0.265589 -0.153758\natom -0.16068 2.71985 1.60824 S 0.0 0.0 0.050395 -0.182428 -0.262953\natom 11.86755 8.59177 4.42869 S 0.0 0.0 0.024866 -0.324733 0.153071\natom 8.87664 8.82012 10.46561 S 0.0 0.0 -0.050395 0.182428 0.262953\natom -3.15159 2.94820 7.64516 S 0.0 0.0 -0.024866 0.324733 -0.153071\natom 11.19346 2.86388 3.53402 Cu 0.0 0.0 -0.036258 -0.213212 -0.031512\natom 0.49915 8.85787 2.50291 Cu 0.0 0.0 -0.038391 0.160909 0.071219\natom -2.47750 8.67609 8.53983 Cu 0.0 0.0 0.036258 0.213212 0.031512\natom 8.21681 2.68210 9.57094 Cu 0.0 0.0 0.038391 -0.160909 -0.071219\natom 5.25007 0.62341 8.16796 Cu 0.0 0.0 0.002544 -0.253803 0.099028\natom 0.63542 6.52847 9.94281 Cu 0.0 0.0 0.012174 0.161487 -0.034433\natom 3.46589 10.91656 3.90589 Cu 0.0 0.0 -0.002544 0.253803 -0.099028\natom 8.08054 5.01150 2.13103 Cu 0.0 0.0 -0.012174 -0.161487 0.034433\natom 8.16741 1.02794 2.02478 Cu 0.0 0.0 0.038872 -0.330107 -0.099095\natom 3.65614 6.92627 4.01214 Cu 0.0 0.0 -0.056685 0.186881 -0.003338\natom 0.54855 10.51203 10.04906 Cu 0.0 0.0 -0.038872 0.330107 0.099095\natom 5.05982 4.61370 8.06171 Cu 0.0 0.0 0.056685 -0.186881 0.003338\natom 4.93751 2.83346 0.88260 Cu 0.0 0.0 -0.038544 -0.231144 -0.006459\natom 6.76305 8.65939 5.15433 Cu 0.0 0.0 0.001828 0.185239 -0.075655\natom 3.77845 8.70651 11.19125 Cu 0.0 0.0 0.038544 0.231144 0.006459\natom 1.95291 2.88058 6.91952 Cu 0.0 0.0 -0.001828 -0.185239 0.075655\natom -3.73644 0.65058 11.41099 Cu 0.0 0.0 0.114845 -0.229374 0.025259\natom 9.61290 6.76121 6.69978 Cu 0.0 0.0 -0.110891 0.336696 -0.129702\natom 12.45240 10.88938 0.66285 Cu 0.0 0.0 -0.114845 0.229374 -0.025259\natom -0.89694 4.77876 5.37407 Cu 0.0 0.0 0.110891 -0.336696 0.129702\natom -1.06253 0.76406 5.34751 Cu 0.0 0.0 0.036114 -0.262800 0.041558\natom 12.89711 6.87300 0.68942 Cu 0.0 0.0 -0.081776 0.227311 -0.034433\natom 9.77850 10.77591 6.72634 Cu 0.0 0.0 -0.036114 0.262800 -0.041558\natom 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7.50601 6.82414 Cu 0.0 0.0 0.003197 0.185724 -0.044949\natom 7.66145 10.13670 0.78721 Cu 0.0 0.0 0.144541 -0.095460 -0.118177\natom 3.94606 4.03396 5.24971 Cu 0.0 0.0 -0.003197 -0.185724 0.044949\natom 3.75335 1.29738 5.29801 Cu 0.0 0.0 -0.028798 0.147537 0.103327\natom 8.04426 7.40318 0.73892 Cu 0.0 0.0 -0.083709 0.146304 0.129057\natom 4.96261 10.24259 6.77584 Cu 0.0 0.0 0.028798 -0.147537 -0.103327\natom 0.67170 4.13679 11.33493 Cu 0.0 0.0 0.083709 -0.146304 -0.129057\natom -1.27319 2.48464 10.27122 Cu 0.0 0.0 0.122475 -0.045546 0.016788\natom 7.02468 8.52302 7.83955 Cu 0.0 0.0 -0.116703 0.100393 -0.036105\natom 9.98915 9.05533 1.80263 Cu 0.0 0.0 -0.122475 0.045546 -0.016788\natom 1.69128 3.01695 4.23430 Cu 0.0 0.0 0.116703 -0.100393 0.036105\natom 8.30112 0.16548 8.24644 Cu 0.0 0.0 0.046531 0.115525 -0.205141\natom -2.38397 6.07551 9.86433 Cu 0.0 0.0 0.046740 -0.150827 -0.108647\natom 0.41484 11.37449 3.82741 Cu 0.0 0.0 -0.046531 -0.115525 0.205141\natom 11.09993 5.46446 2.20951 Cu 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0.0 0.0 0.005182 -0.177427 0.112061\natom 0.35430 6.54426 9.78510 Cu 0.0 0.0 0.000607 0.181338 -0.032617\natom 3.45622 11.04183 3.84394 Cu 0.0 0.0 -0.005182 0.177427 -0.112061\natom 8.17486 5.06638 2.09723 Cu 0.0 0.0 -0.000607 -0.181338 0.032617\natom 8.24463 1.02686 1.99267 Cu 0.0 0.0 0.127345 -0.248036 -0.075535\natom 3.62407 6.99383 3.94850 Cu 0.0 0.0 -0.155918 0.195413 -0.022055\natom 0.28453 10.58378 9.88967 Cu 0.0 0.0 -0.127345 0.248036 0.075535\natom 4.90508 4.61682 7.93383 Cu 0.0 0.0 0.155918 -0.195413 0.022055\natom 5.00773 2.86699 0.86860 Cu 0.0 0.0 0.046279 -0.283463 0.004795\natom 6.75553 8.74278 5.07257 Cu 0.0 0.0 -0.125119 0.048069 -0.117205\natom 3.52143 8.74365 11.01374 Cu 0.0 0.0 -0.046279 0.283463 -0.004795\natom 1.77363 2.86787 6.80977 Cu 0.0 0.0 0.125119 -0.048069 0.117205\natom -4.17264 0.57117 11.22999 Cu 0.0 0.0 0.200598 -0.224704 0.075141\natom 9.59212 6.80552 6.59351 Cu 0.0 0.0 -0.195951 0.245194 -0.226835\natom 12.70179 11.03948 0.65234 Cu 0.0 0.0 -0.200598 0.224704 -0.075141\natom -1.06296 4.80512 5.28883 Cu 0.0 0.0 0.195951 -0.245194 0.226835\natom -1.25274 0.73339 5.26269 Cu 0.0 0.0 0.217961 -0.209785 0.107096\natom 13.13090 6.96563 0.67848 Cu 0.0 0.0 -0.242881 0.195139 -0.094958\natom 9.78190 10.87725 6.61965 Cu 0.0 0.0 -0.217961 0.209785 -0.107096\natom -4.60174 4.64501 11.20385 Cu 0.0 0.0 0.242881 -0.195139 0.094958\natom 7.88567 1.01277 11.79084 Cu 0.0 0.0 -0.260036 0.017638 -0.314668\natom -2.49347 7.29263 6.03266 Cu 0.0 0.0 0.087085 0.127434 0.035611\natom 0.64349 10.59787 0.09149 Cu 0.0 0.0 0.260036 -0.017638 0.314668\natom 11.02263 4.31802 5.84967 Cu 0.0 0.0 -0.087085 -0.127434 -0.035611\natom 11.09854 1.46173 6.05880 Cu 0.0 0.0 -0.144701 -0.057138 -0.235860\natom -5.71906 7.27659 11.76470 Cu 0.0 0.0 -0.029828 0.105554 0.041174\natom -2.56938 10.14892 5.82353 Cu 0.0 0.0 0.144701 0.057138 0.235860\natom 14.24822 4.33405 0.11764 Cu 0.0 0.0 0.029828 -0.105554 -0.041174\natom 8.93931 2.82995 4.88245 Cu 0.0 0.0 0.144463 -0.149413 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0.257739\natom 1.67055 11.01233 9.92597 Cu 0.0 0.0 0.116311 -0.228561 0.093060\natom 5.69706 5.09552 7.96295 Cu 0.0 0.0 -0.182233 0.581379 -0.257739\natom 5.23566 2.83716 0.87179 Cu 0.0 0.0 -0.201675 0.390187 0.030331\natom 7.66218 8.84717 5.09119 Cu 0.0 0.0 0.219474 -0.259380 0.063080\natom 4.81711 9.32688 11.05416 Cu 0.0 0.0 0.201675 -0.390187 -0.030331\natom 2.39060 3.31687 6.83476 Cu 0.0 0.0 -0.219474 0.259380 -0.063080\natom -3.40957 1.45643 11.27121 Cu 0.0 0.0 -0.046020 0.451051 0.054748\natom 10.42861 7.09997 6.61771 Cu 0.0 0.0 0.040915 -0.430788 0.107527\natom 13.46235 10.70761 0.65473 Cu 0.0 0.0 0.046020 -0.451051 -0.054748\natom -0.37583 5.06407 5.30824 Cu 0.0 0.0 -0.040915 0.430788 -0.107527\natom -0.86598 1.13203 5.28200 Cu 0.0 0.0 -0.146211 0.323275 -0.061338\natom 13.58959 6.77774 0.68097 Cu 0.0 0.0 0.218817 -0.412908 0.054987\natom 10.91876 11.03201 6.64395 Cu 0.0 0.0 0.146211 -0.323275 0.061338\natom -3.53681 5.38630 11.24498 Cu 0.0 0.0 -0.218817 0.412908 -0.054987\natom 8.62714 1.92787 11.83412 Cu 0.0 0.0 -0.160625 0.141110 0.235082\natom -1.56673 7.52491 6.05480 Cu 0.0 0.0 0.333439 0.044648 0.098560\natom 1.42563 10.23617 0.09183 Cu 0.0 0.0 0.160625 -0.141110 -0.235082\natom 11.61950 4.63913 5.87114 Cu 0.0 0.0 -0.333439 -0.044648 -0.098560\natom 11.49716 1.89917 6.08104 Cu 0.0 0.0 0.085673 0.160157 0.076204\natom -4.41746 7.97144 11.80788 Cu 0.0 0.0 0.118802 -0.011562 0.155787\natom -1.44438 10.26487 5.84491 Cu 0.0 0.0 -0.085673 -0.160157 -0.076204\natom 14.47023 4.19260 0.11807 Cu 0.0 0.0 -0.118802 0.011562 -0.155787\natom 9.38234 3.12493 4.90037 Cu 0.0 0.0 0.173417 0.422081 0.049989\natom 3.52670 8.80216 1.06260 Cu 0.0 0.0 -0.196520 -0.224210 -0.068206\natom 0.67043 9.03911 7.02558 Cu 0.0 0.0 -0.173417 -0.422081 -0.049989\natom 6.52607 3.36188 10.86335 Cu 0.0 0.0 0.196520 0.224210 0.068206\natom 1.48376 2.18433 11.14838 Cu 0.0 0.0 0.060257 0.169028 -0.074272\natom 5.60295 7.83801 6.74055 Cu 0.0 0.0 0.173350 0.021758 -0.038703\natom 8.56902 9.97971 0.77757 Cu 0.0 0.0 -0.060257 -0.169028 0.074272\natom 4.44983 4.32603 5.18540 Cu 0.0 0.0 -0.173350 -0.021758 0.038703\natom 4.03694 1.65056 5.23311 Cu 0.0 0.0 0.134967 0.113866 -0.362626\natom 8.73473 7.30031 0.72987 Cu 0.0 0.0 0.035882 0.144526 0.040243\natom 6.01584 10.51348 6.69284 Cu 0.0 0.0 -0.134967 -0.113866 0.362626\natom 1.31805 4.86373 11.19608 Cu 0.0 0.0 -0.035882 -0.144526 -0.040243\natom -0.80676 3.16999 10.14540 Cu 0.0 0.0 0.146112 0.177424 0.075456\natom 7.98828 8.90653 7.74352 Cu 0.0 0.0 -0.148678 -0.026547 -0.031817\natom 10.85953 8.99405 1.78054 Cu 0.0 0.0 -0.146112 -0.177424 -0.075456\natom 2.06449 3.25751 4.18243 Cu 0.0 0.0 0.148678 0.026547 0.031817\natom 8.61698 0.75426 8.14542 Cu 0.0 0.0 -0.055748 -0.204733 0.361503\natom -1.65086 6.65600 9.74350 Cu 0.0 0.0 -0.088672 0.160559 0.088132\natom 1.43579 11.40978 3.78053 Cu 0.0 0.0 0.055748 0.204733 -0.361503\natom 11.70363 5.50804 2.18245 Cu 0.0 0.0 0.088672 -0.160559 -0.088132\natom 11.00092 0.81061 1.99283 Cu 0.0 0.0 -0.145954 0.109695 0.129322\natom 1.70556 6.72801 3.97015 Cu 0.0 0.0 -0.015970 0.020729 -0.056743\natom -0.94814 11.35343 9.93312 Cu 0.0 0.0 0.145954 -0.109695 -0.129322\natom 8.34722 5.43603 7.95580 Cu 0.0 0.0 0.015970 -0.020729 0.056743\natom -3.90299 2.76718 9.20922 Cu 0.0 0.0 -0.271555 -0.156644 0.253869\natom 11.05090 8.58104 8.67970 Cu 0.0 0.0 -0.000256 0.079262 -0.207427\natom 13.95577 9.39686 2.71673 Cu 0.0 0.0 0.271555 0.156644 -0.253869\natom -0.99813 3.58300 3.24624 Cu 0.0 0.0 0.000256 -0.079262 0.207427\natom 6.07658 1.06748 3.37981 Cu 0.0 0.0 -0.004833 0.245592 0.065101\natom 6.64832 6.87031 2.58316 Cu 0.0 0.0 0.042366 -0.244047 -0.059305\natom 3.97620 11.09656 8.54613 Cu 0.0 0.0 0.004833 -0.245592 -0.065101\natom 3.40445 5.29373 9.34279 Cu 0.0 0.0 -0.042366 0.244047 0.059305\natom 1.06621 0.81341 7.42987 Cu 0.0 0.0 -0.018947 -0.080568 -0.194989\natom 5.90811 6.77426 10.45906 Cu 0.0 0.0 -0.182753 0.206456 -0.207612\natom 8.98657 11.35063 4.49608 Cu 0.0 0.0 0.018947 0.080568 0.194989\natom 4.14467 5.38978 1.46689 Cu 0.0 0.0 0.182753 -0.206456 0.207612\natom 3.90226 0.56900 1.59688 Cu 0.0 0.0 0.311213 -0.183054 -0.250528\natom 8.78341 6.51911 4.36609 Cu 0.0 0.0 -0.139257 0.200169 -0.168924\natom 6.15051 11.59505 10.32906 Cu 0.0 0.0 -0.311213 0.183054 0.250528\natom 1.26936 5.64493 7.55986 Cu 0.0 0.0 0.139257 -0.200169 0.168924\natom 3.78668 2.80154 8.99574 Cu 0.0 0.0 0.011363 -0.190487 -0.293669\natom 3.36521 8.63304 8.89318 Cu 0.0 0.0 -0.159028 0.139735 0.060584\natom 6.26609 9.36250 2.93021 Cu 0.0 0.0 -0.011363 0.190487 0.293669\natom 6.68756 3.53100 3.03277 Cu 0.0 0.0 0.159028 -0.139735 -0.060584\natom 14.02249 1.10577 2.58316 Cu 0.0 0.0 0.129510 0.191257 0.044494\natom -1.29101 6.97441 3.37981 Cu 0.0 0.0 -0.104529 -0.141349 0.025259\natom -3.96971 11.05827 9.34279 Cu 0.0 0.0 -0.129510 -0.191257 -0.044494\natom 11.34379 5.18963 8.54613 Cu 0.0 0.0 0.104529 0.141349 -0.025259\natom 4.09284 1.67396 11.36662 Cu 0.0 0.0 0.011212 -0.325059 0.156493\natom 2.94592 7.30962 6.52230 Cu 0.0 0.0 -0.008054 0.505492 -0.144069\natom 5.95994 10.49008 0.55933 Cu 0.0 0.0 -0.011212 0.325059 -0.156493\natom 7.10686 4.85442 5.40365 Cu 0.0 0.0 0.008054 -0.505492 0.144069\natom 7.58682 2.54768 6.74889 Cu 0.0 0.0 -0.192478 0.230193 -0.113101\natom -0.44979 8.56478 11.14003 Cu 0.0 0.0 -0.187247 -0.060486 0.194302\natom 2.46596 9.61636 5.17705 Cu 0.0 0.0 0.192478 -0.230193 0.113101\natom 10.50257 3.59926 0.78592 Cu 0.0 0.0 0.187247 0.060486 -0.194302\natom 2.40075 2.48369 1.66725 Cu 0.0 0.0 -0.201781 0.244306 0.027376\natom 10.46143 8.42799 4.29573 Cu 0.0 0.0 -0.020993 -0.090240 -0.239066\natom 7.65203 9.68035 10.25870 Cu 0.0 0.0 0.201781 -0.244306 -0.027376\natom -0.40865 3.73605 7.63022 Cu 0.0 0.0 0.020993 0.090240 0.239066\natom -1.83524 1.46197 8.09891 Cu 0.0 0.0 0.100627 -0.318207 -0.010727\natom 8.86688 7.36755 9.79001 Cu 0.0 0.0 -0.126344 0.379930 -0.060059\natom 11.88801 10.70207 3.82704 Cu 0.0 0.0 -0.100627 0.318207 0.010727\natom 1.18589 4.79649 2.13594 Cu 0.0 0.0 0.126344 -0.379930 0.060059\nenergy -571.066315\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_86\nlattice 15.250171000 0.000000000 0.000000000\nlattice -0.162479000 11.972516000 0.000000000\nlattice -6.016617000 -0.002379000 12.255553000\natom 9.52137 0.99052 10.32163 S 0.0 0.0 -0.173169 0.047043 0.041573\natom -3.40431 6.97721 8.06170 S 0.0 0.0 0.062444 0.127209 0.011765\natom -0.45030 10.97962 1.93393 S 0.0 0.0 0.173169 -0.047043 -0.041573\natom 12.47538 4.99292 4.19385 S 0.0 0.0 -0.062444 -0.127209 -0.011765\natom 12.25955 0.91867 4.24287 S 0.0 0.0 -0.106453 0.050672 0.021809\natom -0.12389 6.90538 1.88490 S 0.0 0.0 0.109426 -0.068215 -0.007471\natom -3.18848 11.05147 8.01268 S 0.0 0.0 0.106453 -0.050672 -0.021809\natom 9.19496 5.06476 10.37065 S 0.0 0.0 -0.109426 0.068215 0.007471\natom 9.04603 0.98533 6.21111 S 0.0 0.0 -0.069088 -0.082697 0.011750\natom -2.92880 6.97043 12.17221 S 0.0 0.0 0.013514 -0.103355 0.067076\natom 0.02505 10.98481 6.04444 S 0.0 0.0 0.069088 0.082697 -0.011750\natom 11.99987 4.99971 0.08334 S 0.0 0.0 -0.013514 0.103355 -0.067076\natom 12.02419 0.97814 0.07353 S 0.0 0.0 0.029481 -0.073227 0.008135\natom 0.10989 6.96324 6.05424 S 0.0 0.0 -0.005759 -0.026889 0.028680\natom -2.95311 10.99200 12.18202 S 0.0 0.0 -0.029481 0.073227 -0.008135\natom 8.96119 5.00690 6.20131 S 0.0 0.0 0.005759 0.026889 -0.028680\natom 3.14451 1.05571 7.51633 S 0.0 0.0 -0.070394 0.056348 0.061141\natom 2.97080 7.04132 10.86700 S 0.0 0.0 0.051389 0.056778 -0.063043\natom 5.92656 10.91442 4.73922 S 0.0 0.0 0.070394 -0.056348 -0.061141\natom 6.10028 4.92882 1.38855 S 0.0 0.0 -0.051389 -0.056778 0.063043\natom 6.18959 0.86898 1.17286 S 0.0 0.0 0.100769 0.031127 -0.068688\natom 5.94744 6.85450 4.95492 S 0.0 0.0 -0.131384 -0.085182 0.065372\natom 2.88148 11.10116 11.08270 S 0.0 0.0 -0.100769 -0.031127 0.068688\natom 3.12363 5.11564 7.30063 S 0.0 0.0 0.131384 0.085182 -0.065372\natom -0.17304 0.93318 9.64267 S 0.0 0.0 0.200455 -0.159273 0.001406\natom 6.29166 6.91961 8.74066 S 0.0 0.0 -0.174947 -0.237010 -0.002547\natom 9.24411 11.03696 2.61288 S 0.0 0.0 -0.200455 0.159273 -0.001406\natom 2.77941 5.05052 3.51489 S 0.0 0.0 0.174947 0.237010 0.002547\natom 2.59594 0.99543 3.51612 S 0.0 0.0 -0.223968 -0.023771 -0.120846\natom 9.53765 6.98186 2.61166 S 0.0 0.0 0.348179 -0.036762 0.067584\natom 6.47514 10.97471 8.73943 S 0.0 0.0 0.223968 0.023771 0.120846\natom -0.46657 4.98827 9.64389 S 0.0 0.0 -0.348179 0.036762 -0.067584\natom 6.22981 2.96866 8.84851 S 0.0 0.0 -0.063308 0.006503 0.088580\natom -0.16643 8.95479 9.53482 S 0.0 0.0 0.059621 -0.118281 -0.143381\natom 2.84126 9.00147 3.40704 S 0.0 0.0 0.063308 -0.006503 -0.088580\natom 9.23750 3.01535 2.72073 S 0.0 0.0 -0.059621 0.118281 0.143381\natom 5.81210 2.67726 5.10689 S 0.0 0.0 -0.025749 -0.085258 -0.015434\natom 6.27583 8.66431 1.02089 S 0.0 0.0 0.006493 -0.094016 0.045257\natom 3.25898 9.29288 7.14866 S 0.0 0.0 0.025749 0.085258 0.015434\natom 2.79524 3.30583 11.23467 S 0.0 0.0 -0.006493 0.094016 -0.045257\natom 0.09803 2.85311 5.84100 S 0.0 0.0 -0.078834 0.124446 -0.099537\natom 11.98512 8.84045 0.28678 S 0.0 0.0 0.052684 0.001779 0.125251\natom 8.97305 9.11702 6.41456 S 0.0 0.0 0.078834 -0.124446 0.099537\natom -2.91405 3.12969 11.96877 S 0.0 0.0 -0.052684 -0.001779 -0.125251\natom -0.10259 2.78210 1.63244 S 0.0 0.0 -0.078489 -0.109487 -0.172902\natom 12.18769 8.76780 4.49534 S 0.0 0.0 0.071390 -0.154637 0.192012\natom 9.17366 9.18804 10.62311 S 0.0 0.0 0.078489 0.109487 0.172902\natom -3.11662 3.20234 7.76022 S 0.0 0.0 -0.071390 0.154637 -0.192012\natom 11.38215 2.98764 3.58720 Cu 0.0 0.0 -0.066258 -0.082275 -0.026868\natom 0.69736 8.97410 2.54058 Cu 0.0 0.0 0.036158 0.003386 0.034124\natom -2.31108 8.98249 8.66835 Cu 0.0 0.0 0.066258 0.082275 0.026868\natom 8.37372 2.99603 9.71498 Cu 0.0 0.0 -0.036158 -0.003386 -0.034124\natom 5.32862 0.88436 8.29088 Cu 0.0 0.0 -0.046533 -0.106573 0.105640\natom 0.79134 6.87027 10.09245 Cu 0.0 0.0 0.042587 -0.010650 -0.094142\natom 3.74246 11.08578 3.96467 Cu 0.0 0.0 0.046533 0.106573 -0.105640\natom 8.27973 5.09987 2.16311 Cu 0.0 0.0 -0.042587 0.010650 0.094142\natom 8.28178 1.09628 2.05526 Cu 0.0 0.0 0.006148 -0.111541 -0.034809\natom 3.84907 7.08215 4.07252 Cu 0.0 0.0 -0.006508 0.005343 0.020825\natom 0.78929 10.87385 10.20030 Cu 0.0 0.0 -0.006148 0.111541 0.034809\natom 5.22200 4.88799 8.18303 Cu 0.0 0.0 0.006508 -0.005343 -0.020825\natom 5.05395 2.87323 0.89588 Cu 0.0 0.0 -0.046335 -0.075036 -0.031622\natom 7.02868 8.85865 5.23190 Cu 0.0 0.0 0.052325 0.026402 0.018208\natom 4.01712 9.09691 11.35967 Cu 0.0 0.0 0.046335 0.075036 0.031622\natom 2.04239 3.11149 7.02366 Cu 0.0 0.0 -0.052325 -0.026402 -0.018208\natom -3.75418 1.01422 11.58272 Cu 0.0 0.0 0.088303 -0.000263 0.045528\natom 9.87059 7.00140 6.80061 Cu 0.0 0.0 -0.086474 0.135059 -0.041213\natom 12.82525 10.95592 0.67283 Cu 0.0 0.0 -0.088303 0.000263 -0.045528\natom -0.79952 4.96873 5.45495 Cu 0.0 0.0 0.086474 -0.135059 0.041213\natom -1.05334 0.93639 5.42798 Cu 0.0 0.0 0.019098 -0.074501 -0.033126\natom 13.18852 6.92357 0.69979 Cu 0.0 0.0 -0.038907 0.040046 0.035906\natom 10.12441 11.03374 6.82757 Cu 0.0 0.0 -0.019098 0.074501 0.033126\natom -4.11744 5.04657 11.55576 Cu 0.0 0.0 0.038907 -0.040046 -0.035906\natom 8.26096 1.47385 12.16118 Cu 0.0 0.0 -0.078567 0.162575 -0.104321\natom -2.15702 7.46126 6.22214 Cu 0.0 0.0 0.092955 0.170823 0.042740\natom 0.81011 10.49629 0.09437 Cu 0.0 0.0 0.078567 -0.162575 0.104321\natom 11.22810 4.50888 6.03341 Cu 0.0 0.0 -0.092955 -0.170823 -0.042740\natom 11.26570 1.68931 6.24911 Cu 0.0 0.0 0.042107 0.136832 -0.101979\natom -5.16757 7.67442 12.13422 Cu 0.0 0.0 -0.042388 0.149834 0.076378\natom -2.19462 10.28083 6.00645 Cu 0.0 0.0 -0.042107 -0.136832 0.101979\natom 14.23865 4.29572 0.12133 Cu 0.0 0.0 0.042388 -0.149834 -0.076378\natom 9.10009 2.99694 5.03581 Cu 0.0 0.0 0.173728 0.068602 0.055221\natom 2.97916 8.98396 1.09197 Cu 0.0 0.0 -0.160353 0.090483 -0.056106\natom -0.02902 8.97320 7.21975 Cu 0.0 0.0 -0.173728 -0.068602 -0.055221\natom 6.09191 2.98617 11.16358 Cu 0.0 0.0 0.160353 -0.090483 0.056106\natom 1.10597 1.76612 11.45649 Cu 0.0 0.0 -0.128376 0.135885 0.064618\natom 4.99004 7.75325 6.92684 Cu 0.0 0.0 0.071694 0.163489 -0.074413\natom 7.96511 10.20402 0.79906 Cu 0.0 0.0 0.128376 -0.135885 -0.064618\natom 4.08103 4.21688 5.32871 Cu 0.0 0.0 -0.071694 -0.163489 0.074413\natom 3.82736 1.47038 5.37774 Cu 0.0 0.0 -0.064537 0.144231 -0.024071\natom 8.29332 7.45753 0.75004 Cu 0.0 0.0 0.018561 0.155089 0.036421\natom 5.24371 10.49976 6.87782 Cu 0.0 0.0 0.064537 -0.144231 0.024071\natom 0.77775 4.51260 11.50551 Cu 0.0 0.0 -0.018561 -0.155089 -0.036421\natom -1.22514 2.81990 10.42580 Cu 0.0 0.0 0.114278 -0.032256 0.070988\natom 7.29255 8.80664 7.95753 Cu 0.0 0.0 -0.103353 0.058592 -0.077408\natom 10.29621 9.15024 1.82975 Cu 0.0 0.0 -0.114278 0.032256 -0.070988\natom 1.77852 3.16350 4.29802 Cu 0.0 0.0 0.103353 -0.058592 0.077408\natom 8.40370 0.42699 8.37054 Cu 0.0 0.0 0.052543 0.044953 -0.089249\natom -2.27133 6.41293 10.01279 Cu 0.0 0.0 0.009147 -0.026956 0.041168\natom 0.66738 11.54315 3.88501 Cu 0.0 0.0 -0.052543 -0.044953 0.089249\natom 11.34240 5.55721 2.24277 Cu 0.0 0.0 -0.009147 0.026956 -0.041168\natom 10.92537 0.74669 2.04790 Cu 0.0 0.0 0.054032 -0.013127 -0.083231\natom 1.21498 6.73255 4.07987 Cu 0.0 0.0 -0.018431 -0.028201 0.062492\natom -1.85429 11.22345 10.20765 Cu 0.0 0.0 -0.054032 0.013127 0.083231\natom 7.85610 5.23759 8.17568 Cu 0.0 0.0 0.018431 0.028201 -0.062492\natom -4.28123 2.44654 9.46374 Cu 0.0 0.0 0.002541 -0.002558 0.003951\natom 10.35878 8.43291 8.91959 Cu 0.0 0.0 0.038826 -0.058315 -0.018664\natom 13.35230 9.52359 2.79181 Cu 0.0 0.0 -0.002541 0.002558 -0.003951\natom -1.28771 3.53723 3.33596 Cu 0.0 0.0 -0.038826 0.058315 0.018664\natom 5.94671 0.95114 3.47322 Cu 0.0 0.0 -0.012290 0.022001 0.012624\natom 6.18808 6.93756 2.65455 Cu 0.0 0.0 0.000036 0.053317 -0.003127\natom 3.12436 11.01900 8.78233 Cu 0.0 0.0 0.012290 -0.022001 -0.012624\natom 2.88300 5.03258 9.60100 Cu 0.0 0.0 -0.000036 -0.053317 0.003127\natom 0.85320 0.51813 7.63521 Cu 0.0 0.0 -0.060104 -0.026809 0.134873\natom 5.27670 6.50378 10.74812 Cu 0.0 0.0 0.062934 -0.045514 -0.087932\natom 8.21788 11.45201 4.62034 Cu 0.0 0.0 0.060104 0.026809 -0.134873\natom 3.79437 5.46636 1.50743 Cu 0.0 0.0 -0.062934 0.045514 0.087932\natom 3.83867 0.51570 1.64102 Cu 0.0 0.0 0.033894 0.041555 0.105813\natom 8.30794 6.50140 4.48676 Cu 0.0 0.0 -0.089728 -0.010936 -0.070037\natom 5.23240 11.45444 10.61453 Cu 0.0 0.0 -0.033894 -0.041555 -0.105813\natom 0.76313 5.46873 7.76879 Cu 0.0 0.0 0.089728 0.010936 0.070037\natom 3.42350 2.49088 9.24436 Cu 0.0 0.0 -0.025857 0.001399 -0.004656\natom 2.65285 8.47716 9.13897 Cu 0.0 0.0 0.043474 -0.040394 0.028802\natom 5.64757 9.47925 3.01119 Cu 0.0 0.0 0.025857 -0.001399 0.004656\natom 6.41823 3.49298 3.11659 Cu 0.0 0.0 -0.043474 0.040394 -0.028802\natom 13.92086 1.02433 2.65455 Cu 0.0 0.0 0.048502 0.032677 0.085159\natom -1.78806 7.01043 3.47322 Cu 0.0 0.0 -0.059248 0.107481 -0.092227\natom -4.84979 10.94580 9.60100 Cu 0.0 0.0 -0.048502 -0.032677 -0.085159\natom 10.85913 4.95971 8.78233 Cu 0.0 0.0 0.059248 -0.107481 0.092227\natom 3.74508 1.23330 11.68077 Cu 0.0 0.0 -0.055050 0.128277 0.003221\natom 2.36539 7.22052 6.70256 Cu 0.0 0.0 0.076507 0.018701 -0.012960\natom 5.32600 10.73684 0.57479 Cu 0.0 0.0 0.055050 -0.128277 -0.003221\natom 6.70568 4.74962 5.55299 Cu 0.0 0.0 -0.076507 -0.018701 0.012960\natom 7.29516 2.32611 6.93542 Cu 0.0 0.0 0.002181 0.000554 0.031661\natom -1.21432 8.31149 11.44791 Cu 0.0 0.0 0.053975 0.051347 -0.039343\natom 1.77592 9.64403 5.32014 Cu 0.0 0.0 -0.002181 -0.000554 -0.031661\natom 10.28540 3.65864 0.80764 Cu 0.0 0.0 -0.053975 -0.051347 0.039343\natom 2.21799 2.47678 1.71333 Cu 0.0 0.0 0.061996 -0.039814 0.031326\natom 9.87539 8.46251 4.41445 Cu 0.0 0.0 -0.030297 0.016964 0.009985\natom 6.85308 9.49336 10.54223 Cu 0.0 0.0 -0.061996 0.039814 -0.031326\natom -0.80432 3.50762 7.84110 Cu 0.0 0.0 0.030297 -0.016964 -0.009985\natom -2.10686 1.15493 8.32275 Cu 0.0 0.0 0.000595 0.082437 0.028239\natom 8.21947 7.14085 10.06058 Cu 0.0 0.0 0.008649 -0.038616 -0.027302\natom 11.17793 10.81521 3.93281 Cu 0.0 0.0 -0.000595 -0.082437 -0.028239\natom 0.85160 4.82929 2.19497 Cu 0.0 0.0 -0.008649 0.038616 0.027302\nenergy -573.512746\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_3_90\nlattice 14.955524000 0.000000000 0.000000000\nlattice 0.188973000 12.057616000 0.000000000\nlattice -5.409354000 -0.397621000 12.384678000\natom 9.77982 0.66470 10.43038 S 0.0 0.0 0.023728 0.157300 -0.214147\natom -2.81251 6.76683 8.14664 S 0.0 0.0 0.302850 -0.201506 -0.042155\natom -0.04468 10.99529 1.95430 S 0.0 0.0 -0.023728 -0.157300 0.214147\natom 12.54765 4.89317 4.23804 S 0.0 0.0 -0.302850 0.201506 0.042155\natom 12.21943 0.78837 4.28758 S 0.0 0.0 -0.215017 -0.077276 0.043744\natom 0.15493 6.89368 1.90476 S 0.0 0.0 0.220074 -0.053963 -0.178468\natom -2.48429 10.87163 8.09710 S 0.0 0.0 0.215017 0.077276 -0.043744\natom 9.58021 4.76632 10.47991 S 0.0 0.0 -0.220074 0.053963 0.178468\natom 9.14880 0.79203 6.27655 S 0.0 0.0 0.085599 -0.263620 -0.151990\natom -2.18167 6.62744 12.30046 S 0.0 0.0 0.153849 -0.295586 0.176979\natom 0.58635 10.86796 6.10812 S 0.0 0.0 -0.085599 0.263620 0.151990\natom 11.91682 5.03256 0.08422 S 0.0 0.0 -0.153849 0.295586 -0.176979\natom 11.82327 0.98272 0.07431 S 0.0 0.0 0.010577 -0.062152 -0.080584\natom 0.55294 6.81749 6.11803 S 0.0 0.0 0.071068 -0.221973 0.159195\natom -2.08813 10.67727 12.31037 S 0.0 0.0 -0.010577 0.062152 0.080584\natom 9.18220 4.84250 6.26665 S 0.0 0.0 -0.071068 0.221973 -0.159195\natom 3.41566 0.82083 7.59552 S 0.0 0.0 -0.001455 0.056477 -0.017550\natom 3.55370 6.74092 10.98149 S 0.0 0.0 -0.022111 0.207563 -0.244789\natom 6.31949 10.83917 4.78915 S 0.0 0.0 0.001455 -0.056477 0.017550\natom 6.18145 4.91907 1.40318 S 0.0 0.0 0.022111 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8.95558 3.44294 S 0.0 0.0 0.229502 -0.054182 -0.313679\natom 9.25577 2.94904 2.74940 S 0.0 0.0 -0.099377 -0.012970 0.122492\natom 5.98233 2.53160 5.16070 S 0.0 0.0 0.205206 -0.087502 -0.120032\natom 6.44755 8.69297 1.03164 S 0.0 0.0 -0.149642 -0.088620 -0.029176\natom 3.75282 9.12839 7.22398 S 0.0 0.0 -0.205206 0.087502 0.120032\natom 3.28759 2.96702 11.35303 S 0.0 0.0 0.149642 0.088620 0.029176\natom 0.41319 2.68503 5.90254 S 0.0 0.0 -0.126991 0.014873 -0.147629\natom 12.02224 8.89404 0.28980 S 0.0 0.0 0.231318 0.003827 -0.081583\natom 9.32195 8.97497 6.48214 S 0.0 0.0 0.126991 -0.014873 0.147629\natom -2.28710 2.76596 12.09488 S 0.0 0.0 -0.231318 -0.003827 0.081583\natom 0.04574 2.74923 1.64964 S 0.0 0.0 -0.048426 -0.207118 -0.620580\natom 12.38742 8.68515 4.54270 S 0.0 0.0 0.143193 -0.046336 0.383129\natom 9.68940 8.91077 10.73504 S 0.0 0.0 0.048426 0.207118 0.620580\natom -2.65228 2.97484 7.84198 S 0.0 0.0 -0.143193 0.046336 -0.383129\natom 11.39290 2.89320 3.62500 Cu 0.0 0.0 0.010767 -0.106120 -0.020614\natom 1.04677 8.95596 2.56734 Cu 0.0 0.0 0.043929 -0.087881 0.029516\natom -1.65776 8.76680 8.75968 Cu 0.0 0.0 -0.010767 0.106120 0.020614\natom 8.68837 2.70403 9.81733 Cu 0.0 0.0 -0.043929 0.087881 -0.029516\natom 5.58361 0.62327 8.37823 Cu 0.0 0.0 0.053024 -0.139976 0.109561\natom 1.38034 6.59363 10.19878 Cu 0.0 0.0 0.007514 -0.109772 -0.133602\natom 4.15153 11.03672 4.00644 Cu 0.0 0.0 -0.053024 0.139976 -0.109561\natom 8.35481 5.06636 2.18590 Cu 0.0 0.0 -0.007514 0.109772 0.133602\natom 8.23602 1.03780 2.07691 Cu 0.0 0.0 0.017498 -0.023324 -0.034455\natom 4.14393 7.00116 4.11543 Cu 0.0 0.0 -0.055542 -0.003353 -0.019725\natom 1.49912 10.62220 10.30777 Cu 0.0 0.0 -0.017498 0.023324 0.034455\natom 5.59121 4.65884 8.26925 Cu 0.0 0.0 0.055542 0.003353 0.019725\natom 5.07579 2.86476 0.90532 Cu 0.0 0.0 -0.098024 0.022927 -0.019037\natom 7.36025 8.75289 5.28702 Cu 0.0 0.0 0.048686 0.011567 0.016276\natom 4.65935 8.79523 11.47936 Cu 0.0 0.0 0.098024 -0.022927 0.019037\natom 2.37490 2.90710 7.09766 Cu 0.0 0.0 -0.048686 -0.011567 -0.016276\natom -3.18801 0.64790 11.70476 Cu 0.0 0.0 0.081331 0.084913 -0.021142\natom 10.15608 6.83186 6.87226 Cu 0.0 0.0 -0.095600 0.115341 -0.051226\natom 12.92315 11.01209 0.67992 Cu 0.0 0.0 -0.081331 -0.084913 0.021142\natom -0.42094 4.82814 5.51242 Cu 0.0 0.0 0.095600 -0.115341 0.051226\natom -0.78824 0.76800 5.48517 Cu 0.0 0.0 -0.017716 0.025800 -0.006722\natom 13.16317 6.95022 0.70717 Cu 0.0 0.0 0.032534 0.021529 0.011678\natom 10.52339 10.89199 6.89950 Cu 0.0 0.0 0.017716 -0.025800 0.006722\natom -3.42803 4.70978 11.67751 Cu 0.0 0.0 -0.032534 -0.021529 -0.011678\natom 8.63154 1.09214 12.28932 Cu 0.0 0.0 -0.081720 0.277202 0.132002\natom -1.64896 7.31364 6.28770 Cu 0.0 0.0 -0.077566 0.270829 -0.044115\natom 1.10361 10.56785 0.09536 Cu 0.0 0.0 0.081720 -0.277202 -0.132002\natom 11.38410 4.34635 6.09698 Cu 0.0 0.0 0.077566 -0.270829 0.044115\natom 11.34758 1.49979 6.31495 Cu 0.0 0.0 0.129636 0.259092 0.011172\natom -4.35824 7.33766 12.26207 Cu 0.0 0.0 -0.230864 0.276823 -0.002583\natom -1.61244 10.16021 6.06973 Cu 0.0 0.0 -0.129636 -0.259092 -0.011172\natom 14.09338 4.32234 0.12261 Cu 0.0 0.0 0.230864 -0.276823 0.002583\natom 9.21325 2.85584 5.08886 Cu 0.0 0.0 0.125897 -0.020368 0.086208\natom 3.22672 9.01261 1.10347 Cu 0.0 0.0 -0.153837 0.214180 -0.047876\natom 0.52190 8.80415 7.29581 Cu 0.0 0.0 -0.125897 0.020368 -0.086208\natom 6.50842 2.64739 11.28120 Cu 0.0 0.0 0.153837 -0.214180 0.047876\natom 1.59505 1.40921 11.57720 Cu 0.0 0.0 -0.143533 0.100922 0.011952\natom 5.39675 7.58498 6.99982 Cu 0.0 0.0 0.232340 0.069930 0.066432\natom 8.14009 10.25078 0.80748 Cu 0.0 0.0 0.143533 -0.100922 -0.011952\natom 4.33839 4.07501 5.38486 Cu 0.0 0.0 -0.232340 -0.069930 -0.066432\natom 4.01168 1.30740 5.43440 Cu 0.0 0.0 -0.132215 0.107653 -0.096394\natom 8.38010 7.48635 0.75794 Cu 0.0 0.0 0.221053 0.052407 0.239019\natom 5.72346 10.35259 6.95028 Cu 0.0 0.0 0.132215 -0.107653 0.096394\natom 1.35504 4.17364 11.62674 Cu 0.0 0.0 -0.221053 -0.052407 -0.239019\natom -0.70166 2.50372 10.53565 Cu 0.0 0.0 0.220929 0.100259 -0.045867\natom 7.72672 8.61261 8.04137 Cu 0.0 0.0 -0.246545 -0.134125 0.041590\natom 10.43681 9.15627 1.84903 Cu 0.0 0.0 -0.220929 -0.100259 0.045867\natom 2.00842 3.04738 4.34331 Cu 0.0 0.0 0.246545 0.134125 -0.041590\natom 8.58917 0.16009 8.45874 Cu 0.0 0.0 0.004933 0.076701 -0.018748\natom -1.63966 6.13561 10.11828 Cu 0.0 0.0 -0.183238 0.135896 -0.038450\natom 1.14598 11.49991 3.92594 Cu 0.0 0.0 -0.004933 -0.076701 0.018748\natom 11.37480 5.52438 2.26640 Cu 0.0 0.0 0.183238 -0.135896 0.038450\natom 10.81806 0.68595 2.06948 Cu 0.0 0.0 0.028511 -0.094981 0.033175\natom 1.55085 6.64884 4.12286 Cu 0.0 0.0 -0.088787 0.028839 -0.002766\natom -1.08292 10.97404 10.31520 Cu 0.0 0.0 -0.028511 0.094981 -0.033175\natom 8.18429 5.01116 8.26182 Cu 0.0 0.0 0.088787 -0.028839 0.002766\natom -3.74812 2.15874 9.56345 Cu 0.0 0.0 -0.030734 -0.085302 0.106365\natom 10.76139 8.20520 9.01357 Cu 0.0 0.0 -0.025016 0.012407 -0.111879\natom 13.48326 9.50126 2.82123 Cu 0.0 0.0 0.030734 0.085302 -0.106365\natom -1.02625 3.45479 3.37111 Cu 0.0 0.0 0.025016 -0.012407 0.111879\natom 5.99866 0.84589 3.50982 Cu 0.0 0.0 -0.039719 -0.006937 0.022478\natom 6.37672 6.90126 2.68252 Cu 0.0 0.0 0.037403 0.078052 -0.062040\natom 3.73648 10.81410 8.87486 Cu 0.0 0.0 0.039719 0.006937 -0.022478\natom 3.35842 4.75873 9.70216 Cu 0.0 0.0 -0.037403 -0.078052 0.062040\natom 1.15773 0.27558 7.71565 Cu 0.0 0.0 -0.103759 -0.113933 -0.013158\natom 5.79465 6.20339 10.86136 Cu 0.0 0.0 0.203011 -0.170634 0.036240\natom 8.57741 11.38441 4.66902 Cu 0.0 0.0 0.103759 0.113933 0.013158\natom 3.94049 5.45660 1.52332 Cu 0.0 0.0 -0.203011 0.170634 -0.036240\natom 3.84527 0.46644 1.65831 Cu 0.0 0.0 0.067499 -0.023001 0.043894\natom 8.51636 6.40292 4.53403 Cu 0.0 0.0 -0.005170 -0.047363 0.009143\natom 5.88988 11.19355 10.72637 Cu 0.0 0.0 -0.067499 0.023001 -0.043894\natom 1.21879 5.25707 7.85065 Cu 0.0 0.0 0.005170 0.047363 -0.009143\natom 3.80025 2.21047 9.34176 Cu 0.0 0.0 -0.079256 -0.014704 -0.104872\natom 3.21442 8.24270 9.23525 Cu 0.0 0.0 0.041840 -0.043704 0.102765\natom 5.93489 9.44952 3.04292 Cu 0.0 0.0 0.079256 0.014704 0.104872\natom 6.52072 3.41730 3.14942 Cu 0.0 0.0 -0.041840 0.043704 -0.102765\natom 13.78807 0.94601 2.68252 Cu 0.0 0.0 0.160354 0.184271 -0.026081\natom -1.41038 6.94825 3.50982 Cu 0.0 0.0 -0.150969 0.039062 0.005451\natom -4.05293 10.71399 9.70216 Cu 0.0 0.0 -0.160354 -0.184271 0.026081\natom 11.14553 4.71174 8.87486 Cu 0.0 0.0 0.150969 -0.039062 -0.005451\natom 4.17665 0.86537 11.80384 Cu 0.0 0.0 -0.141725 0.174609 0.017969\natom 2.79833 7.05569 6.77318 Cu 0.0 0.0 0.057429 0.066136 0.053453\natom 5.55849 10.79462 0.58084 Cu 0.0 0.0 0.141725 -0.174609 -0.017969\natom 6.93681 4.60430 5.61150 Cu 0.0 0.0 -0.057429 -0.066136 -0.053453\natom 7.49978 2.11899 7.00849 Cu 0.0 0.0 -0.133534 0.079922 -0.028798\natom -0.49033 8.00139 11.56853 Cu 0.0 0.0 0.101015 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-0.03932 2.69434 1.63206 S 0.0 0.0 0.091314 -0.273325 -0.705096\natom 12.11265 8.51967 4.49428 S 0.0 0.0 0.042664 -0.213576 0.433805\natom 9.42570 8.66903 10.62061 S 0.0 0.0 -0.091314 0.273325 0.705096\natom -2.72627 2.84370 7.75839 S 0.0 0.0 -0.042664 0.213576 -0.433805\natom 11.30487 2.81306 3.58636 Cu 0.0 0.0 -0.056576 -0.205504 -0.058415\natom 0.76143 8.81040 2.53998 Cu 0.0 0.0 0.033178 0.072268 0.096208\natom -1.91849 8.55031 8.66631 Cu 0.0 0.0 0.056576 0.205504 0.058415\natom 8.62495 2.55297 9.71269 Cu 0.0 0.0 -0.033178 -0.072268 -0.096208\natom 5.58507 0.51601 8.28893 Cu 0.0 0.0 0.002913 -0.264755 0.094551\natom 1.19356 6.38804 10.09007 Cu 0.0 0.0 0.063862 0.046578 -0.057646\natom 3.80131 10.84736 3.96374 Cu 0.0 0.0 -0.002913 0.264755 -0.094551\natom 8.19282 4.97533 2.16260 Cu 0.0 0.0 -0.063862 -0.046578 0.057646\natom 8.20523 0.99985 2.05477 Cu 0.0 0.0 -0.043484 -0.264807 -0.125425\natom 3.92571 6.86239 4.07156 Cu 0.0 0.0 0.002815 0.122899 0.006896\natom 1.18115 10.36352 10.19790 Cu 0.0 0.0 0.043484 0.264807 0.125425\natom 5.46067 4.50098 8.18111 Cu 0.0 0.0 -0.002815 -0.122899 -0.006896\natom 4.98315 2.81720 0.89567 Cu 0.0 0.0 -0.149322 -0.101002 -0.031325\natom 7.08708 8.57772 5.23066 Cu 0.0 0.0 0.107677 0.198532 -0.009581\natom 4.40323 8.54617 11.35700 Cu 0.0 0.0 0.149322 0.101002 0.031325\natom 2.29930 2.78565 7.02201 Cu 0.0 0.0 -0.107677 -0.198532 0.009581\natom -3.17497 0.50092 11.58000 Cu 0.0 0.0 0.031212 -0.140479 -0.065121\natom 9.94913 6.66261 6.79901 Cu 0.0 0.0 -0.047446 0.305489 -0.058134\natom 12.56135 10.86245 0.67267 Cu 0.0 0.0 -0.031212 0.140479 0.065121\natom -0.56275 4.70076 5.45366 Cu 0.0 0.0 0.047446 -0.305489 0.058134\natom -0.79752 0.69315 5.42671 Cu 0.0 0.0 -0.119416 -0.170040 -0.022159\natom 12.93390 6.85248 0.69963 Cu 0.0 0.0 0.082819 0.185654 0.025962\natom 10.18390 10.67022 6.82596 Cu 0.0 0.0 0.119416 0.170040 0.022159\natom -3.54752 4.51089 11.55304 Cu 0.0 0.0 -0.082819 -0.185654 -0.025962\natom 8.62772 0.93253 12.15832 Cu 0.0 0.0 -0.127590 0.230719 0.099371\natom -1.86926 7.14512 6.22068 Cu 0.0 0.0 -0.036361 0.254528 -0.172618\natom 0.75866 10.43084 0.09435 Cu 0.0 0.0 0.127590 -0.230719 -0.099371\natom 11.25564 4.21825 6.03199 Cu 0.0 0.0 0.036361 -0.254528 0.172618\natom 11.31264 1.40570 6.24764 Cu 0.0 0.0 0.099769 0.206815 -0.017407\natom -4.56151 7.09806 12.13137 Cu 0.0 0.0 -0.231466 0.259144 -0.041721\natom -1.92626 9.95767 6.00503 Cu 0.0 0.0 -0.099769 -0.206815 0.017407\natom 13.94789 4.26531 0.12130 Cu 0.0 0.0 0.231466 -0.259144 0.041721\natom 9.13131 2.75884 5.03462 Cu 0.0 0.0 0.138655 -0.137581 0.051974\natom 2.93466 8.88366 1.09171 Cu 0.0 0.0 -0.147132 0.348936 -0.014869\natom 0.25507 8.60453 7.21805 Cu 0.0 0.0 -0.138655 0.137581 -0.051974\natom 6.45172 2.47971 11.16096 Cu 0.0 0.0 0.147132 -0.348936 0.014869\natom 1.58126 1.25395 11.45380 Cu 0.0 0.0 -0.218414 0.011996 -0.005813\natom 5.16721 7.40454 6.92521 Cu 0.0 0.0 0.135180 0.102873 0.100528\natom 7.80512 10.10942 0.79887 Cu 0.0 0.0 0.218414 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0.056952\natom 1.34503 6.51451 4.07891 Cu 0.0 0.0 -0.020408 0.069255 -0.084326\natom -1.41147 10.71075 10.20525 Cu 0.0 0.0 -0.058727 0.050214 -0.056952\natom 8.04135 4.84886 8.17376 Cu 0.0 0.0 0.020408 -0.069255 0.084326\natom -3.79024 2.01770 9.46151 Cu 0.0 0.0 0.017910 0.005585 0.148376\natom 10.51547 7.99293 8.91749 Cu 0.0 0.0 0.077022 -0.067263 -0.225985\natom 13.17662 9.34567 2.79116 Cu 0.0 0.0 -0.017910 -0.005585 -0.148376\natom -1.12909 3.37044 3.33518 Cu 0.0 0.0 -0.077022 0.067263 0.225985\natom 5.97894 0.79344 3.47241 Cu 0.0 0.0 -0.054540 -0.118376 0.021346\natom 6.15694 6.78075 2.65393 Cu 0.0 0.0 0.026096 0.155776 -0.055588\natom 3.40744 10.56993 8.78026 Cu 0.0 0.0 0.054540 0.118376 -0.021346\natom 3.22944 4.58262 9.59874 Cu 0.0 0.0 -0.026096 -0.155776 0.055588\natom 1.17017 0.18064 7.63341 Cu 0.0 0.0 -0.041255 -0.025574 0.040131\natom 5.62097 5.99497 10.74559 Cu 0.0 0.0 0.181745 -0.167594 0.133492\natom 8.21621 11.18273 4.61926 Cu 0.0 0.0 0.041255 0.025574 -0.040131\natom 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6.70099 Cu 0.0 0.0 0.038586 -0.101317 -0.007189\natom 5.20600 10.64895 0.57465 Cu 0.0 0.0 0.101489 -0.356380 -0.065025\natom 6.80008 4.47863 5.55168 Cu 0.0 0.0 -0.038586 0.101317 0.007189\natom 7.44791 2.00872 6.93379 Cu 0.0 0.0 -0.017349 0.022575 -0.119170\natom -0.71854 7.76147 11.44522 Cu 0.0 0.0 0.216815 0.155755 0.027007\natom 1.93847 9.35465 5.31888 Cu 0.0 0.0 0.017349 -0.022575 0.119170\natom 10.10492 3.60190 0.80745 Cu 0.0 0.0 -0.216815 -0.155755 -0.027007\natom 2.24037 2.38726 1.71292 Cu 0.0 0.0 0.140503 -0.084826 0.143313\natom 9.84340 8.21971 4.41341 Cu 0.0 0.0 -0.042281 0.040389 -0.144535\natom 7.14601 8.97611 10.53975 Cu 0.0 0.0 -0.140503 0.084826 -0.143313\natom -0.45702 3.14366 7.83926 Cu 0.0 0.0 0.042281 -0.040389 0.144535\natom -1.70389 0.78361 8.32079 Cu 0.0 0.0 0.107295 0.134898 0.054363\natom 8.47326 6.65844 10.05822 Cu 0.0 0.0 -0.069924 -0.198432 0.008684\natom 11.09027 10.57976 3.93188 Cu 0.0 0.0 -0.107295 -0.134898 -0.054363\natom 0.91312 4.70493 2.19445 Cu 0.0 0.0 0.069924 0.198432 -0.008684\nenergy -572.328657\ncharge 0.0\nend\nbegin\ncomment source_file_name=OUTCAR_0_1\nlattice 15.246000000 0.000000000 0.000000000\nlattice 0.000000000 11.884000000 0.000000000\nlattice -5.989357159 0.000000000 12.091965796\natom 9.55381 0.98518 10.18385 S 0.0 0.0 -0.125331 0.028415 0.031193\natom -3.29184 6.92718 7.95410 S 0.0 0.0 0.125331 0.028415 -0.031193\natom -0.29717 10.89882 1.90811 S 0.0 0.0 0.125331 -0.028415 -0.031193\natom 12.54849 4.95682 4.13787 S 0.0 0.0 -0.125331 -0.028415 0.031193\natom 12.27754 0.91269 4.18624 S 0.0 0.0 -0.126394 -0.041931 0.027223\natom -0.02622 6.85469 1.85974 S 0.0 0.0 0.126394 -0.041931 -0.027223\natom -3.02090 10.97131 7.90573 S 0.0 0.0 0.126394 0.041931 -0.027223\natom 9.28287 5.02931 10.23222 S 0.0 0.0 -0.126394 0.041931 0.027223\natom 9.06992 0.97924 6.12821 S 0.0 0.0 -0.013446 -0.068418 -0.051411\natom -2.80795 6.92124 12.00974 S 0.0 0.0 0.013446 -0.068418 0.051411\natom 0.18673 10.90476 5.96376 S 0.0 0.0 0.013446 0.068418 0.051411\natom 12.06460 4.96276 0.08223 S 0.0 0.0 -0.013446 0.068418 -0.051411\natom 12.03432 0.97092 0.07255 S 0.0 0.0 0.063364 0.002358 -0.040486\natom 0.21700 6.91292 5.97343 S 0.0 0.0 -0.063364 0.002358 0.040486\natom -2.77768 10.91308 12.01941 S 0.0 0.0 -0.063364 -0.002358 0.040486\natom 9.03964 4.97108 6.11853 S 0.0 0.0 0.063364 -0.002358 -0.040486\natom 3.17371 1.04936 7.41600 S 0.0 0.0 -0.099435 -0.033364 0.051184\natom 3.08826 6.99136 10.72195 S 0.0 0.0 0.099435 -0.033364 -0.051184\natom 6.08294 10.83464 4.67596 S 0.0 0.0 0.099435 0.033364 -0.051184\natom 6.16838 4.89264 1.37002 S 0.0 0.0 -0.099435 0.033364 0.051184\natom 6.20214 0.86278 1.15720 S 0.0 0.0 0.136972 -0.061507 -0.119929\natom 6.04918 6.80478 4.88878 S 0.0 0.0 -0.136972 -0.061507 0.119929\natom 3.05450 11.02122 10.93476 S 0.0 0.0 -0.136972 0.061507 0.119929\natom 3.20746 5.07922 7.20318 S 0.0 0.0 0.136972 0.061507 -0.119929\natom -0.14015 0.92814 9.51396 S 0.0 0.0 0.207624 -0.187454 0.034062\natom 6.40212 6.87014 8.62399 S 0.0 0.0 -0.207624 -0.187454 -0.034062\natom 9.39679 10.95586 2.57801 S 0.0 0.0 -0.207624 0.187454 -0.034062\natom 2.85453 5.01386 3.46798 S 0.0 0.0 0.207624 0.187454 0.034062\natom 2.61609 0.98875 3.46918 S 0.0 0.0 -0.379594 -0.045519 -0.051010\natom 9.63523 6.93075 2.57680 S 0.0 0.0 0.379594 -0.045519 0.051010\natom 6.64055 10.89525 8.62278 S 0.0 0.0 0.379594 0.045519 0.051010\natom -0.37859 4.95325 9.51517 S 0.0 0.0 -0.379594 0.045519 -0.051010\natom 6.28690 2.94842 8.73040 S 0.0 0.0 -0.101684 -0.045832 0.134656\natom -0.02494 8.89042 9.40755 S 0.0 0.0 0.101684 -0.045832 -0.134656\natom 2.96974 8.93558 3.36157 S 0.0 0.0 0.101684 0.045832 -0.134656\natom 9.28158 2.99358 2.68442 S 0.0 0.0 -0.101684 0.045832 0.134656\natom 5.85752 2.65845 5.03872 S 0.0 0.0 -0.067582 -0.177681 0.103192\natom 6.39380 8.60045 1.00726 S 0.0 0.0 0.067582 -0.177681 -0.103192\natom 3.39912 9.22555 7.05324 S 0.0 0.0 0.067582 0.177681 -0.103192\natom 2.86284 3.28355 11.08471 S 0.0 0.0 -0.067582 0.177681 0.103192\natom 0.14893 2.83315 5.76303 S 0.0 0.0 -0.063213 -0.002445 -0.183871\natom 12.10239 8.77515 0.28295 S 0.0 0.0 0.063213 -0.002445 0.183871\natom 9.10771 9.05085 6.32893 S 0.0 0.0 0.063213 0.002445 0.183871\natom -2.84574 3.10885 11.80901 S 0.0 0.0 -0.063213 0.002445 -0.183871\natom -0.06140 2.76184 1.61065 S 0.0 0.0 0.033374 -0.217794 -0.226789\natom 12.31272 8.70384 4.43533 S 0.0 0.0 -0.033374 -0.217794 0.226789\natom 9.31804 9.12216 10.48132 S 0.0 0.0 -0.033374 0.217794 0.226789\natom -3.05608 3.18016 7.65663 S 0.0 0.0 0.033374 0.217794 -0.226789\natom 11.42708 2.96625 3.53932 Cu 0.0 0.0 -0.056517 -0.018383 -0.066026\natom 0.82424 8.90825 2.50666 Cu 0.0 0.0 0.056517 -0.018383 0.066026\natom -2.17044 8.91775 8.55265 Cu 0.0 0.0 0.056517 0.018383 0.066026\natom 8.43240 2.97575 9.58530 Cu 0.0 0.0 -0.056517 0.018383 -0.066026\natom 5.35651 0.87942 8.18021 Cu 0.0 0.0 -0.068978 -0.042620 0.067357\natom 0.90546 6.82142 9.95773 Cu 0.0 0.0 0.068978 -0.042620 -0.067357\natom 3.90014 11.00458 3.91175 Cu 0.0 0.0 0.068978 0.042620 -0.067357\natom 8.35119 5.06258 2.13423 Cu 0.0 0.0 -0.068978 0.042620 0.067357\natom 8.29869 1.08857 2.02782 Cu 0.0 0.0 -0.013003 -0.079744 -0.061412\natom 3.95263 7.03057 4.01816 Cu 0.0 0.0 0.013003 -0.079744 0.061412\natom 0.95795 10.79543 10.06414 Cu 0.0 0.0 0.013003 0.079744 0.061412\natom 5.30402 4.85343 8.07381 Cu 0.0 0.0 -0.013003 0.079744 -0.061412\natom 5.09343 2.85216 0.88392 Cu 0.0 0.0 -0.071088 -0.013473 -0.002685\natom 7.15789 8.79416 5.16206 Cu 0.0 0.0 0.071088 -0.013473 0.002685\natom 4.16322 9.03184 11.20804 Cu 0.0 0.0 0.071088 0.013473 0.002685\natom 2.09875 3.08984 6.92991 Cu 0.0 0.0 -0.071088 0.013473 -0.002685\natom -3.71515 1.00895 11.42812 Cu 0.0 0.0 0.067641 0.039805 0.039650\natom 9.97712 6.95095 6.70983 Cu 0.0 0.0 -0.067641 0.039805 -0.039650\natom 12.97179 10.87505 0.66385 Cu 0.0 0.0 -0.067641 -0.039805 -0.039650\natom -0.72047 4.93305 5.38213 Cu 0.0 0.0 0.067641 -0.039805 0.039650\natom -1.02899 0.93052 5.35553 Cu 0.0 0.0 0.007293 -0.021110 -0.015108\natom 13.28031 6.87252 0.69045 Cu 0.0 0.0 -0.007293 -0.021110 0.015108\natom 10.28563 10.95348 6.73643 Cu 0.0 0.0 -0.007293 0.021110 0.015108\natom -4.02367 5.01148 11.40151 Cu 0.0 0.0 0.007293 0.021110 -0.015108\natom 8.30415 1.46530 11.99886 Cu 0.0 0.0 -0.140674 0.136237 -0.040072\natom -2.04218 7.40730 6.13909 Cu 0.0 0.0 0.140674 0.136237 0.040072\natom 0.95249 10.41870 0.09311 Cu 0.0 0.0 0.140674 -0.136237 0.040072\natom 11.29883 4.47670 5.95287 Cu 0.0 0.0 -0.140674 -0.136237 -0.040072\natom 11.29861 1.67802 6.16569 Cu 0.0 0.0 0.015271 0.116590 -0.074616\natom -5.03665 7.62002 11.97226 Cu 0.0 0.0 -0.015271 0.116590 0.074616\natom -2.04197 10.20598 5.92627 Cu 0.0 0.0 -0.015271 -0.116590 0.074616\natom 14.29329 4.26398 0.11971 Cu 0.0 0.0 0.015271 -0.116590 -0.074616\natom 9.14880 2.97575 4.96859 Cu 0.0 0.0 0.164959 0.084500 0.087098\natom 3.10252 8.91775 1.07739 Cu 0.0 0.0 -0.164959 0.084500 -0.087098\natom 0.10784 8.90825 7.12338 Cu 0.0 0.0 -0.164959 -0.084500 -0.087098\natom 6.15412 2.96625 11.01457 Cu 0.0 0.0 0.164959 -0.084500 0.087098\natom 1.15360 1.75527 11.30357 Cu 0.0 0.0 -0.063629 0.156987 0.058610\natom 5.10836 7.69727 6.83438 Cu 0.0 0.0 0.063629 0.156987 -0.058610\natom 8.10304 10.12873 0.78840 Cu 0.0 0.0 0.063629 -0.156987 -0.058610\natom 4.14828 4.18673 5.25759 Cu 0.0 0.0 -0.063629 -0.156987 0.058610\natom 3.85752 1.46054 5.30595 Cu 0.0 0.0 0.025586 0.159786 -0.058692\natom 8.39380 7.40254 0.74003 Cu 0.0 0.0 -0.025586 0.159786 0.058692\natom 5.39912 10.42346 6.78601 Cu 0.0 0.0 -0.025586 -0.159786 0.058692\natom 0.86284 4.48146 11.35194 Cu 0.0 0.0 0.025586 -0.159786 -0.058692\natom -1.16473 2.80106 10.28664 Cu 0.0 0.0 0.114949 0.029868 0.062123\natom 7.42669 8.74306 7.85131 Cu 0.0 0.0 -0.114949 0.029868 -0.062123\natom 10.42137 9.08294 1.80533 Cu 0.0 0.0 -0.114949 -0.029868 -0.062123\natom 1.82995 3.14094 4.24065 Cu 0.0 0.0 0.114949 -0.029868 0.062123\natom 8.42471 0.42545 8.25881 Cu 0.0 0.0 -0.006801 -0.023883 -0.023161\natom -2.16275 6.36745 9.87914 Cu 0.0 0.0 0.006801 -0.023883 0.023161\natom 0.83193 11.45855 3.83315 Cu 0.0 0.0 0.006801 0.023883 0.023161\natom 11.41939 5.51655 2.21283 Cu 0.0 0.0 -0.006801 0.023883 -0.023161\natom 10.93680 0.74156 2.02057 Cu 0.0 0.0 -0.002607 0.001704 -0.015858\natom 1.31453 6.68356 4.02542 Cu 0.0 0.0 0.002607 0.001704 0.015858\natom -1.68015 11.14244 10.07140 Cu 0.0 0.0 0.002607 -0.001704 0.015858\natom 7.94212 5.20044 8.06655 Cu 0.0 0.0 -0.002607 -0.001704 -0.015858\natom -4.22706 2.43028 9.33742 Cu 0.0 0.0 -0.057628 -0.032284 0.078709\natom 10.48903 8.37228 8.80053 Cu 0.0 0.0 0.057628 -0.032284 -0.078709\natom 13.48370 9.45372 2.75455 Cu 0.0 0.0 0.057628 0.032284 -0.078709\natom -1.23238 3.51172 3.29143 Cu 0.0 0.0 -0.057628 0.032284 0.078709\natom 5.96526 0.94478 3.42686 Cu 0.0 0.0 -0.017114 0.034111 0.052038\natom 6.28607 6.88678 2.61912 Cu 0.0 0.0 0.017114 0.034111 -0.052038\natom 3.29139 10.93922 8.66510 Cu 0.0 0.0 0.017114 -0.034111 -0.052038\natom 2.97058 4.99722 9.47285 Cu 0.0 0.0 -0.017114 -0.034111 0.052038\natom 0.87597 0.51577 7.53329 Cu 0.0 0.0 -0.012110 -0.004506 0.081390\natom 5.38599 6.45777 10.60465 Cu 0.0 0.0 0.012110 -0.004506 -0.081390\natom 8.38067 11.36823 4.55867 Cu 0.0 0.0 0.012110 0.004506 -0.081390\natom 3.87065 5.42623 1.48731 Cu 0.0 0.0 -0.012110 0.004506 0.081390\natom 3.84806 0.51220 1.61911 Cu 0.0 0.0 0.106207 0.025692 0.047083\natom 8.40327 6.45420 4.42687 Cu 0.0 0.0 -0.106207 0.025692 -0.047083\natom 5.40859 11.37180 10.47285 Cu 0.0 0.0 -0.106207 -0.025692 -0.047083\natom 0.85338 5.42980 7.66510 Cu 0.0 0.0 0.106207 -0.025692 0.047083\natom 3.47571 2.47425 9.12097 Cu 0.0 0.0 0.013369 -0.021692 -0.063355\natom 2.78626 8.41625 9.01698 Cu 0.0 0.0 -0.013369 -0.021692 0.063355\natom 5.78094 9.40975 2.97100 Cu 0.0 0.0 -0.013369 0.021692 0.063355\natom 6.47038 3.46775 3.07499 Cu 0.0 0.0 0.013369 0.021692 -0.063355\natom 13.93651 1.01727 2.61912 Cu 0.0 0.0 0.070095 0.058281 0.058871\natom -1.68519 6.95927 3.42686 Cu 0.0 0.0 -0.070095 0.058281 -0.058871\natom -4.67987 10.86673 9.47285 Cu 0.0 0.0 -0.070095 -0.058281 -0.058871\natom 10.94183 4.92473 8.66510 Cu 0.0 0.0 0.070095 -0.058281 0.058871\natom 3.78523 1.22643 11.52485 Cu 0.0 0.0 -0.055512 0.072701 0.045980\natom 2.47674 7.16843 6.61310 Cu 0.0 0.0 0.055512 0.072701 -0.045980\natom 5.47141 10.65757 0.56711 Cu 0.0 0.0 0.055512 -0.072701 -0.045980\natom 6.77991 4.71557 5.47887 Cu 0.0 0.0 -0.055512 -0.072701 0.045980\natom 7.33923 2.31025 6.84284 Cu 0.0 0.0 0.008001 0.031273 -0.008244\natom -1.07727 8.25225 11.29511 Cu 0.0 0.0 -0.008001 0.031273 0.008244\natom 1.91741 9.57375 5.24912 Cu 0.0 0.0 -0.008001 -0.031273 0.008244\natom 10.33391 3.63175 0.79686 Cu 0.0 0.0 0.008001 -0.031273 -0.008244\natom 2.25458 2.45880 1.69046 Cu 0.0 0.0 0.009284 0.010061 0.048810\natom 9.99674 8.40080 4.35553 Cu 0.0 0.0 -0.009284 0.010061 -0.048810\natom 7.00207 9.42520 10.40151 Cu 0.0 0.0 -0.009284 -0.010061 -0.048810\natom -0.74010 3.48320 7.73644 Cu 0.0 0.0 0.009284 -0.010061 0.048810\natom -2.07320 1.14799 8.21165 Cu 0.0 0.0 0.008891 0.031001 0.014345\natom 8.33516 7.08999 9.92629 Cu 0.0 0.0 -0.008891 0.031001 -0.014345\natom 11.32984 10.73601 3.88031 Cu 0.0 0.0 -0.008891 -0.031001 -0.014345\natom 0.92148 4.79401 2.16567 Cu 0.0 0.0 0.008891 -0.031001 0.014345\nenergy -573.700369\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/nnp-train/Cu2S_PBE/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.9745355631944457E+00\nconv_energy   1.6464963191344094E+02\nconv_length   2.7000746146526534E+01\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type (optional argument: shift parameter alpha).\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              15 15          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.02315        # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n"
  },
  {
    "path": "examples/nnp-train/Cu2S_PBE/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   9.0599751834064512E-06   1.0532468503252377E-04   3.6847021293483606E-05   1.7835227890378858E-05\n         1          2   9.7407364273681052E-01   1.3707738052511558E+00   1.1369440745957258E+00   7.8204475954228067E-02\n         1          3   7.1848939224232239E-04   4.4674859070114722E-03   2.0895924503338856E-03   7.3120307120467013E-04\n         1          4   3.0839567122259082E+00   3.7813435073058135E+00   3.4528586198914484E+00   1.4064243940314194E-01\n         1          5   2.2189388498896456E-02   7.9061298236177566E-02   4.6882111087211208E-02   1.1334173255596679E-02\n         1          6   3.8952165155842438E+00   4.3441311727516858E+00   4.1103871329683823E+00   1.0081266947910023E-01\n         1          7   2.6712677530189782E-01   5.9473970044295299E-01   4.2213464431656117E-01   6.6280004153616373E-02\n         1          8   1.7488245369534008E+00   2.9970797892758485E+00   2.4245345856012999E+00   3.3547211267555982E-01\n         1          9   1.2449429394722318E+00   1.9865309035277523E+00   1.5467135618608816E+00   1.4014804188095897E-01\n         1         10   1.1223156151012470E+00   2.5212331659045919E+00   1.7587293340594636E+00   3.2461918457849698E-01\n         1         11   2.1481809886285510E+00   2.6220186753539645E+00   2.3310995299236956E+00   8.8131868940220931E-02\n         1         12   1.7776050347753956E+00   2.3809724095942570E+00   2.0364639196570282E+00   1.3155538475628997E-01\n         1         13   1.3332847701336610E+00   1.5746629195008022E+00   1.4563536842862850E+00   4.2017894226904072E-02\n         1         14   1.2858206220015138E+00   2.0264861435690955E+00   1.6934105509660398E+00   1.7102915724852555E-01\n         1         15   2.9294864910145735E-01   4.4946746329067233E-01   3.8841663360361012E-01   2.7956119240284072E-02\n         1         16   5.7872135122682178E-01   9.8756180790304116E-01   8.3451027680267253E-01   1.0555635785949544E-01\n         1         17   3.8741023011801198E-02   7.2203189636501464E-02   5.8498155834018059E-02   7.5296916290786700E-03\n         1         18   2.0277259701907649E-01   3.0112576816621817E-01   2.5147215506855941E-01   2.3499268876717772E-02\n         1         19   3.7801436874671336E-02   7.0536882716121713E-02   4.9634849414845854E-02   6.1773772857441848E-03\n         1         20   5.0064324676730110E-01   7.4508315795400359E-01   6.0180452708486698E-01   5.1996620314567893E-02\n         1         21   2.1149505846062664E+00   3.0086297694152004E+00   2.4747104151629071E+00   1.7292530958618688E-01\n         1         22   1.1394588610202373E-01   2.1081557230804215E-01   1.4831150247830030E-01   1.8362267327821737E-02\n         1         23   2.7720108269028820E+00   3.8299737046031495E+00   3.2180772088958483E+00   2.3336401126515627E-01\n         1         24   3.6286754324115282E+00   5.7694079721003524E+00   4.5677164220944100E+00   4.0055418877074411E-01\n         1         25   4.7719054215943416E-05   1.2246818750522671E-04   7.4309480650870812E-05   1.4049426561453186E-05\n         1         26   4.4333857694921347E-03   1.0168132968853614E-02   6.4777145172573158E-03   1.0560078551356503E-03\n         1         27   1.8935344189773007E-01   2.9276868067133349E-01   2.3061829866368203E-01   1.9869300862039235E-02\n         1         28   2.7495263408916264E-02   5.1213942108460010E-02   3.6085221024876463E-02   4.5471765030753852E-03\n         1         29   1.5310085616939009E+00   2.1188212216180502E+00   1.7827060035919868E+00   1.2407502507441381E-01\n         1         30   9.1939368654489029E-01   1.5687613774310878E+00   1.2194589135682272E+00   1.1985456906857926E-01\n         1         31   1.1384194008436653E-02   2.3126249430002573E-02   1.5575425703929386E-02   2.2146366574977774E-03\n         1         32   2.0448065764191037E-01   3.1629369745824260E-01   2.5154663060838428E-01   2.3850462668791081E-02\n         1         33   1.1626342355721448E+00   1.6596585560150436E+00   1.3609763259982417E+00   9.7025354891779811E-02\n         1         34   3.4316641363009756E-02   6.9456153312452348E-02   4.6556693792454321E-02   6.6083772055404314E-03\n         1         35   1.2570958839654798E+00   1.7927721704892265E+00   1.4803334101702972E+00   1.1860808472662136E-01\n         1         36   1.9184389026233195E+00   3.1127425453883704E+00   2.4371296559244344E+00   2.2052811165984698E-01\n         1         37   1.3666602477642141E-05   3.6887119050541216E-05   2.2035946317575125E-05   4.3651698230106994E-06\n         1         38   1.5546007659584370E-03   3.7299211557246326E-03   2.3070975415581158E-03   3.9808430326865882E-04\n         1         39   9.5479248087773236E-02   1.4915614707917241E-01   1.1672777818282745E-01   1.0800506748273341E-02\n         1         40   8.2256292725268153E-03   1.6899821492838311E-02   1.1302096732556740E-02   1.6295481703454844E-03\n         1         41   7.1803116051488303E-01   1.0254065821299467E+00   8.4691642411810830E-01   6.5464610909859736E-02\n         1         42   4.3595215959198219E-01   7.9518024924121622E-01   5.9831255803436056E-01   6.6317667245823150E-02\n         1         43   1.6018052377239585E-06   6.3139472908861676E-06   3.1301163360828299E-06   8.9765713700450499E-07\n         1         44   5.5894373857206245E-04   1.2582981249606513E-03   8.3605542167432972E-04   1.3725912741223295E-04\n         1         45   1.9834153225893669E-02   3.6953383616309544E-02   2.6655881843534047E-02   3.2893647917620217E-03\n         1         46   4.8532464966417719E-06   1.9377662342507640E-05   9.3658745542551994E-06   2.6969170145130424E-06\n         1         47   5.7210047587520222E-03   1.1312250481264765E-02   7.9476527861615121E-03   1.1714188135300359E-03\n         1         48   3.3967605349763057E-02   6.3249588182648683E-02   4.5545662343088447E-02   5.6959930803433916E-03\n         1         49   1.5639262624940886E-09   8.3504433474424934E-09   3.7442340287849395E-09   1.1995146772038598E-09\n         1         50   7.8957248103475445E-07   2.9544681844058944E-06   1.5151455992697584E-06   3.9867319456010048E-07\n         1         51   7.2498799380692138E-04   1.3809328629292383E-03   9.6644345650243621E-04   1.3123931111184769E-04\n         1         52   1.1513160050255707E-06   4.7893410133550852E-06   2.2589402933267841E-06   6.5898376566604767E-07\n         1         53   3.6899770288464700E-03   7.1094664560615549E-03   5.0980228781949740E-03   7.3353667640355786E-04\n         1         54   4.7965507914503420E-03   9.9638635159890153E-03   6.7789560394143624E-03   9.7722280949143615E-04\n         1         55   1.5451956482050941E+00   2.3220436338643187E+00   1.8415448061529172E+00   1.4900811986127621E-01\n         1         56   1.0376025533554976E+01   1.3514156671640468E+01   1.1711913234153359E+01   6.9043448028822885E-01\n         1         57   1.5701057712031107E+01   2.1962128408086549E+01   1.8503912750199724E+01   1.2048466878385966E+00\n         1         58   1.2864599135285206E+00   1.9362796091456074E+00   1.5296352202317265E+00   1.2444939857329487E-01\n         1         59   1.0320708418905122E+01   1.3479378639347569E+01   1.1669078130198949E+01   6.9581154676801382E-01\n         1         60   1.3090165473148913E+01   1.8879509137434656E+01   1.5695674905250980E+01   1.0931378423262064E+00\n         1         61   4.3949671163273307E-01   6.6160243665646234E-01   5.2723334425502655E-01   4.2993883711550253E-02\n         1         62   2.9890536869213755E+00   3.9500888865673107E+00   3.3855167809122926E+00   2.0324895614210023E-01\n         1         63   4.2275144808489822E+00   6.1612946214333260E+00   5.0958280611414732E+00   3.6862169589359611E-01\n         1         64   1.9185607361878201E-01   2.8944064348772253E-01   2.2731439323863312E-01   1.8996742597552314E-02\n         1         65   2.9026605370229617E+00   3.8497469707096537E+00   3.3051920388798002E+00   1.9911530882408360E-01\n         1         66   2.3438496537639137E+00   3.5204619280878231E+00   2.8884010974233134E+00   2.1832718765517053E-01\n         1         67   6.9283609471405960E-01   1.1058987063631822E+00   8.4968265286534050E-01   7.8761639155134011E-02\n         1         68   5.6199553705237868E+00   7.4791069644037620E+00   6.4024365024328160E+00   4.1010868642000720E-01\n         1         69   1.0122784690107945E+01   1.4291263786081892E+01   1.1953107220137360E+01   8.1231683230934826E-01\n         1         70   5.7630325723191356E-01   9.2120973806494955E-01   7.0451206294375790E-01   6.5503757358981521E-02\n         1         71   5.5816677967841954E+00   7.4524531203782809E+00   6.3701823389995216E+00   4.1337199146852777E-01\n         1         72   8.1814308596273086E+00   1.2046187228492565E+01   9.8959454279237082E+00   7.3693018572142865E-01\n         1         73   1.9683621110198224E-01   3.1483962875013105E-01   2.4341849856766945E-01   2.2785709321534491E-02\n         1         74   1.6224327804059289E+00   2.2000746987409392E+00   1.8576991122906539E+00   1.2119788736172697E-01\n         1         75   2.6824556989527628E+00   3.9796129564866725E+00   3.2536477391535117E+00   2.5391823361142091E-01\n         1         76   8.5437320410141501E-02   1.3697848298848525E-01   1.0393883860134831E-01   9.8598667429722949E-03\n         1         77   1.5658995991452884E+00   2.1246128383334932E+00   1.8015087956004576E+00   1.1834810393072710E-01\n         1         78   1.3424688092108374E+00   2.1185521226749700E+00   1.6933096448820459E+00   1.4372755682490063E-01\n         1         79   1.8399604045159085E-03   4.6078436172890926E-03   2.8732492264063715E-03   5.3669875232076759E-04\n         1         80   8.3119007268670886E-02   1.4143987144302400E-01   1.0720479470296071E-01   1.2233438802574289E-02\n         1         81   8.2986229100932440E-01   1.1659993267145721E+00   9.5731232407073363E-01   6.2937506381837788E-02\n         1         82   1.5195998543626908E-03   3.8170540359299199E-03   2.3668873493119533E-03   4.3917065596871631E-04\n         1         83   8.3135091173795000E-02   1.3792368162367827E-01   1.0504414743580952E-01   1.1948444459807837E-02\n         1         84   5.9272476782117589E-01   8.5144251489636957E-01   6.9438400963164004E-01   5.0523816606940102E-02\n         1         85   5.1242702350366395E-04   1.3164833282719027E-03   8.2580897561123105E-04   1.6044356357127206E-04\n         1         86   2.4177855790506391E-02   4.2547629449549935E-02   3.2115297327594376E-02   3.6713016163428484E-03\n         1         87   2.0122938661082074E-01   3.1075655422908821E-01   2.4139090930899196E-01   2.1214491900174683E-02\n         1         88   2.2132439378046761E-04   5.5088453823861694E-04   3.3668003207199519E-04   6.2376803338715469E-05\n         1         89   2.3027980736970780E-02   3.8841317908682060E-02   2.9292718346934195E-02   3.3895769533309845E-03\n         1         90   5.2372336035986039E-02   9.0714868461914608E-02   6.8656095125797234E-02   7.2445739677856899E-03\n         2          1   4.0474971172859331E-01   7.5006567516921008E-01   5.6847203729786222E-01   6.0430206098981788E-02\n         2          2   1.3353906173596923E+00   1.9806788567435805E+00   1.7264293099457233E+00   1.1122407155180723E-01\n         2          3   2.7536142595336643E-01   1.6894860339160629E+00   9.4702751302538624E-01   2.2067010751820818E-01\n         2          4   1.5876722829708281E+00   2.4217772337436254E+00   2.0551935664841889E+00   1.2712120842704425E-01\n         2          5   1.4511042760308031E+00   3.5922343911407904E+00   2.7594257532435136E+00   3.7513591802481777E-01\n         2          6   8.5814050322533819E-01   1.6441451598733146E+00   1.2122672928006482E+00   1.7190521428635971E-01\n         2          7   3.0078311930034207E+00   4.2487019279912408E+00   3.6580019562692998E+00   2.6991737605934291E-01\n         2          8   6.1100547250486992E-01   1.1886079210423453E+00   8.7936466702973159E-01   1.1360805119566607E-01\n         2          9   2.3721421380267542E+00   4.1224470139175287E+00   2.9755098267290143E+00   2.8098369790820915E-01\n         2         10   5.6108720328738604E-01   1.4458120707216497E+00   1.0182319598285139E+00   1.9514169765972178E-01\n         2         11   1.5109081390331569E+00   2.8788713701577131E+00   2.2108452631677888E+00   3.1011945809770602E-01\n         2         12   6.1792055810799862E-01   1.1603464814608015E+00   8.4670527548301966E-01   1.2995048804049558E-01\n         2         13   1.0615056624169890E+00   1.8857477549274466E+00   1.4396598836902490E+00   1.7317124283867941E-01\n         2         14   3.3270237895325261E-01   5.4191124490734888E-01   4.1725513840133621E-01   4.3778794272664942E-02\n         2         15   5.3998480145205663E-01   9.2791508619766461E-01   7.1227247840008556E-01   6.3682279386797214E-02\n         2         16   7.6412956388619363E-02   1.7328848000985436E-01   1.2573607753427973E-01   2.7267517483162949E-02\n         2         17   1.6484707519840752E-01   3.9009224653142621E-01   2.6521305089996344E-01   4.3286456399155585E-02\n         2         18   3.7035009562869875E-01   6.7340728612782041E-01   4.9412274857479327E-01   5.1089795554998201E-02\n         2         19   1.2029190895961805E+00   1.9737544680797443E+00   1.5968227035810045E+00   1.2581845339983122E-01\n         2         20   5.1973156450199820E-01   1.3018517286558244E+00   8.7456817249090490E-01   1.3694358773059637E-01\n         2         21   3.3842258746633935E-01   6.2519118150691022E-01   4.6084768542038518E-01   4.6068154352970521E-02\n         2         22   4.6697488042548958E+00   6.4166565216867069E+00   5.4456041336763024E+00   3.1869234590817225E-01\n         2         23   1.8677358418035883E+00   3.2822728183389396E+00   2.4780580508547652E+00   2.4609190542743561E-01\n         2         24   5.6392866964169404E-02   1.0506481202213031E-01   7.5697740272970007E-02   7.4355551695651839E-03\n         2         25   4.3065975423585368E-02   1.3036115047831273E-01   8.2943455920119619E-02   1.4889586170872110E-02\n         2         26   5.2816130547569595E-03   6.2287415311250330E-02   2.5593847758110935E-02   9.5708091233591835E-03\n         2         27   3.6712465685067676E-02   7.9259568522760795E-02   5.5284621941296914E-02   7.3475243523464231E-03\n         2         28   2.1141609301816788E+00   2.7488986070800467E+00   2.3742455069141060E+00   1.2963195224982030E-01\n         2         29   6.2712628223860023E-01   1.0738921139460145E+00   8.0573045811556010E-01   7.7971825073565426E-02\n         2         30   1.6607907847763759E-01   3.3826739218472440E-01   2.3692128148627437E-01   2.8810363549669725E-02\n         2         31   5.9757981452146103E-01   1.0636712565134816E+00   8.3959217727950775E-01   7.6316933142163104E-02\n         2         32   2.1736066482646946E-01   6.3251543867608839E-01   4.0207599705127822E-01   7.0819648650692998E-02\n         2         33   1.3563987111899592E-01   2.7914311585597890E-01   1.9604872870839607E-01   2.2548910149263378E-02\n         2         34   2.4464500593819585E+00   3.5955968335220412E+00   2.9585138046431712E+00   1.9850715242021319E-01\n         2         35   8.0832094385969488E-01   1.5774770035410111E+00   1.1449938485700757E+00   1.3052879241405127E-01\n         2         36   2.8167007928499344E-02   5.4686841405124309E-02   3.8909334876594141E-02   4.3685799270078342E-03\n         2         37   1.8331399003310937E-02   6.1497188402318569E-02   3.7307975732735560E-02   6.9262760890092647E-03\n         2         38   1.8896568313787098E-03   2.6897417454648655E-02   1.0257940854010531E-02   4.1488575001855672E-03\n         2         39   1.2849094460607837E-02   3.0518949214805757E-02   2.0315313896012273E-02   2.9816385781476929E-03\n         2         40   1.1200069428594479E+00   1.5052341251528873E+00   1.2644868420755846E+00   7.5320733889483113E-02\n         2         41   2.7035646948676634E-01   4.8489183467683100E-01   3.6349586483938395E-01   3.8377617987964179E-02\n         2         42   5.3053949124328196E-04   2.7155325962249467E-03   1.4693706396216907E-03   3.8959415772759525E-04\n         2         43   6.7401629277260401E-03   2.3201286281629065E-02   1.4640944577609236E-02   2.8410089366966932E-03\n         2         44   6.2382619651656502E-04   5.2265286032864176E-03   2.3699618414709639E-03   6.7793659350880262E-04\n         2         45   2.6923091933240488E-04   1.4956100254684128E-03   7.2655641233727007E-04   2.0295830894179534E-04\n         2         46   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  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3/input.data",
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22.277451590   O   -0.250659780    0.000000000    0.014962062   -0.036921584    0.020768044\natom    23.404443126    7.523201122   22.934469941   H    0.127971540    0.000000000   -0.013364312    0.032177829   -0.011672658\natom     0.398783394   10.242784550   22.483505519   H    0.114592290    0.000000000   -0.000853489    0.000749003   -0.001440154\natom    17.528048271    7.212186093   10.887255115   O   -0.285050470    0.000000000   -0.004877593    0.043257083   -0.081036434\natom    17.139206730    6.987815041   12.539607730   H    0.110542790    0.000000000   -0.011950003   -0.017241594    0.078214473\natom    16.255294542    8.669849597   10.566472088   H    0.101490000    0.000000000    0.026201298   -0.024116491    0.006216459\natom    18.043790641    0.167807747   17.108583706   O   -0.272862820    0.000000000   -0.008976413    0.033411259   -0.003502375\natom    17.797016877   22.412011482   17.309125302   H    0.094485140    0.000000000    0.002140642   -0.026392467    0.002321756\natom    19.791306123    0.403381099   16.673060243   H    0.135466030    0.000000000    0.007300874   -0.001511841   -0.002631261\natom     4.387622667    5.349905608    5.734684236   O   -0.244070880    0.000000000    0.006036707   -0.002395292   -0.007121226\natom     5.561779896    4.386347101    4.687272878   H    0.132242000    0.000000000   -0.001600843   -0.006100575    0.002766324\natom     4.544428424    7.058727042    5.033047544   H    0.105441580    0.000000000   -0.007509432    0.001400767    0.002801820\natom    12.207452327   13.810638028    0.785451749   O   -0.299231180    0.000000000    0.008830351    0.043755567   -0.020647161\natom    12.237085134   12.043310650    0.901348698   H    0.099587150    0.000000000   -0.001848726   -0.040808947    0.003856916\natom    12.980288259   14.130026437   23.097774469   H    0.108720700    0.000000000   -0.009686812   -0.004306622    0.018477729\natom    10.994413967   10.449928852   16.407704794   O   -0.251217290  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22.476902813   14.527774261   H    0.138662860    0.000000000    0.004746171    0.007331837   -0.004406990\natom     3.457032335   12.750752584   23.404722805   O   -0.228693350    0.000000000    0.123278715   -0.099684528   -0.046435375\natom     2.211953656   13.787133606   23.479659925   H    0.114599780    0.000000000   -0.126789826    0.100662559    0.021674136\natom     4.049690368   11.984079051    0.898181516   H    0.116759010    0.000000000   -0.001963257   -0.003975942    0.026550270\natom    16.315367070   14.145497631    4.688686394   O   -0.257095370    0.000000000    0.019415748    0.011961034    0.015573235\natom    16.879503455   12.564315909    3.976306604   H    0.112639780    0.000000000    0.007203556   -0.010557103   -0.005524374\natom    14.604502841   14.302482912    4.175823968   H    0.123197200    0.000000000   -0.022297483    0.002539158   -0.013545090\natom     4.398802291   10.339742657    3.897875380   O   -0.202867670    0.000000000   -0.007595701    0.000169458   -0.002835816\natom     6.013579577   10.506359876    4.753392532   H    0.145063750    0.000000000   -0.001970558    0.010961620    0.007571230\natom     3.118151394   11.375205272    4.806584564   H    0.128255580    0.000000000    0.012295645   -0.006476487    0.003924093\natom    10.594691379    0.663929082   12.934001289   O   -0.229582380    0.000000000   -0.005718461   -0.009204961    0.016130566\natom     9.810114574    2.351203851   12.631886873   H    0.130965550    0.000000000    0.002048060   -0.018347172    0.012319236\natom    10.477305325    0.034272087   14.740476249   H    0.133202620    0.000000000   -0.006074826    0.025088333   -0.020766319\natom    12.271704930    7.075965131    7.185826293   O   -0.214138270    0.000000000    0.014703364   -0.037033285   -0.040099260\natom    13.568972196    5.966432781    6.289377656   H    0.162923180    0.000000000   -0.028438357    0.015427135    0.020083631\natom    13.309686551    7.858690004    8.414967015   H    0.125455030    0.000000000    0.011234519    0.017085563    0.021636987\natom     0.372695714   13.548797472    5.926536868   O   -0.268084480    0.000000000    0.007614420   -0.073404173   -0.063264501\natom     0.382902129   14.703288314    7.165780070   H    0.127809330    0.000000000   -0.000950585    0.059556028    0.068283917\natom     0.966755925   14.552265121    4.457181624   H    0.107279650    0.000000000   -0.012777661    0.009268460   -0.000933885\natom    17.466446954   19.223044463   17.927731175   O   -0.219763310    0.000000000   -0.035165353   -0.017553463   -0.018934327\natom    18.940386676   18.203939325   17.931045756   H    0.127674450    0.000000000    0.032197931   -0.004780277    0.005456355\natom    16.507728038   18.239067458   16.615179798   H    0.142510840    0.000000000   -0.002326973    0.017481994    0.012448661\natom    14.013464304   16.394244270   13.426133411   O   -0.284574960    0.000000000    0.035938662    0.007538260   -0.048171816\natom    12.330477326   16.976378414   13.002709868   H    0.105804360    0.000000000   -0.008450623    0.005466588    0.004089666\natom    15.005799572   16.925270751   11.745075844   H    0.106969100    0.000000000   -0.019060852   -0.013019411    0.044592581\natom     7.862480796    4.636206789   22.996949981   O   -0.255211000    0.000000000    0.026019058    0.004901961   -0.000568282\natom     6.607577427    4.184068847   21.690317228   H    0.104519940    0.000000000    0.008125767   -0.006959821   -0.003212454\natom     9.649892191    4.419026148   22.306113077   H    0.118804020    0.000000000   -0.031718409   -0.002728319    0.010893469\natom     3.798515431    8.049864223   11.577092353   O   -0.233009840    0.000000000   -0.021582397   -0.005949985   -0.012554795\natom     4.831649902    9.433934203   11.065106760   H    0.130163010    0.000000000    0.017887414    0.015747756   -0.003688555\natom     2.260784199    8.320520355   10.505921459   H    0.115764620    0.000000000    0.007732114   -0.009542268    0.015826322\natom    12.995256786    2.891686525   22.201032925   O   -0.255490060    0.000000000   -0.004915353    0.019472311   -0.001635838\natom    14.491852443    4.010641052   22.317041368   H    0.117038160    0.000000000   -0.003270477   -0.018395304   -0.003528621\natom    13.429871291    1.114213203   22.359666047   H    0.108781130    0.000000000    0.011282327   -0.001145895    0.002319521\natom     2.512601644   20.398749379   20.640606073   O   -0.224422270    0.000000000   -0.021598908    0.009665119    0.051877148\natom     1.537532810   21.905054452   21.392409345   H    0.148959210    0.000000000    0.024157839   -0.031036950   -0.030643998\natom     2.900545564   20.619692466   18.913945617   H    0.123358800    0.000000000    0.000772829    0.021377620   -0.029067107\natom     5.744871754   16.617566523   20.785400726   O   -0.265656930    0.000000000   -0.032497393    0.020526624    0.019299565\natom     4.262486843   18.003063247   20.988257237   H    0.099385010    0.000000000    0.038336244   -0.026808230    0.000017966\natom     5.294918335   15.358585124   22.119375937   H    0.098640670    0.000000000    0.006613032    0.008209277   -0.013429656\natom    17.847113537    1.659677197    7.261604340   O   -0.214984170    0.000000000    0.006018312   -0.022409254    0.003621639\natom    18.987064820    0.224034680    6.782637945   H    0.134801280    0.000000000   -0.013345731    0.012413327    0.012346459\natom    17.213508902    1.225867715    9.010954747   H    0.120488240    0.000000000   -0.000443941    0.002779306   -0.013526258\natom     0.223231546    4.153421256    1.485365010   O   -0.284149710    0.000000000   -0.016138645    0.008676852    0.024731263\natom    22.710372900    4.079060503    2.742248813   H    0.105341390    0.000000000    0.039423346    0.012173922   -0.023123038\natom     1.652651192    5.001182969    2.395013389   H    0.117989360    0.000000000   -0.023819333   -0.014915583   -0.003918404\natom    18.029065889    5.395499049   22.331535573   O   -0.232616100    0.000000000   -0.022435825   -0.041986031    0.019777229\natom    18.450206642    6.009076358   20.698998634   H    0.117402890    0.000000000    0.010969888    0.018577415   -0.028888712\natom    18.471749528    6.543217109   23.632648433   H    0.122965160    0.000000000    0.008555544    0.023492454    0.010076612\natom     9.730995489   -0.013755322   18.655527357   O   -0.260468440    0.000000000    0.033447936   -0.047525024   -0.017241120\natom    10.958809623    1.192342071   19.181358978   H    0.127148600    0.000000000    0.001410520    0.021472916    0.006833322\natom     8.059414903    0.566851923   18.625879432   H    0.119766210    0.000000000   -0.033795515    0.025211959    0.007633086\natom     5.720611440   23.314163314    9.722983047   O   -0.231630130    0.000000000    0.008590611   -0.010936445   -0.025443175\natom     6.834575199    0.786704638    9.364550991   H    0.130111070    0.000000000   -0.010659177   -0.018642575    0.001906309\natom     6.037573440   21.935577321    8.393439246   H    0.130229060    0.000000000   -0.004288229    0.030206013    0.023949980\natom     9.845218141   19.848952241    1.377688373   O   -0.231982490    0.000000000    0.047210910    0.050634028    0.057109462\natom     8.964032828   21.443191975    1.821177035   H    0.130585310    0.000000000   -0.001359815   -0.006723989   -0.005653620\natom     8.864534929   18.936979498    0.325325931   H    0.140456380    0.000000000   -0.053312141   -0.042279623   -0.051814244\natom    21.486183262    2.087957338   12.058619328   O   -0.245742770    0.000000000   -0.018336922    0.012948985   -0.040170727\natom    20.067351756    2.869512469   10.984447548   H    0.132828300    0.000000000    0.028333925   -0.013530492    0.030219120\natom    22.734213694    1.753487019   10.673217090   H    0.099760430    0.000000000   -0.005192035    0.002432708    0.011480438\natom    -0.218456207   22.514791837    3.828822870   O   -0.233891290    0.000000000    0.001999487    0.001056955    0.002002219\natom    22.977963895   23.403316849    2.478210504   H    0.123135500    0.000000000   -0.006368839    0.004516237   -0.013166446\natom     0.169763614   -0.170292738    5.058420906   H    0.104258450    0.000000000    0.006641123   -0.000339229    0.001710832\natom    22.768355390   15.179884991   22.329029795   O   -0.238086150    0.000000000   -0.046086010   -0.025235881    0.005743850\natom    21.434125066   15.631748923   -0.333185305   H    0.126220700    0.000000000    0.031123799   -0.009001222   -0.035124767\natom    21.989842718   13.702640137   21.289668674   H    0.119659510    0.000000000    0.013004599    0.035317132    0.026225131\natom    12.222509671    8.189955346    1.618074860   O   -0.247919730    0.000000000   -0.001797123    0.017574523   -0.067071366\natom    12.278849988    7.760085945    3.281828197   H    0.111233780    0.000000000   -0.004235384   -0.012471568    0.070548691\natom    13.880380289    7.710926590    1.035681823   H    0.141482170    0.000000000    0.006536703    0.000642119   -0.006764662\natom    13.661907075   10.667631057   11.112100488   O   -0.216001700    0.000000000   -0.037279496   -0.013776615    0.034916697\natom    14.124858034   12.345145386   11.672595370   H    0.133272180    0.000000000    0.003591734    0.013021971    0.000895419\natom    12.435880622   10.173618657   12.581225186   H    0.147421220    0.000000000    0.029632111    0.008032176   -0.031477484\natom    17.486330661   17.032057327    9.295375649   O   -0.235087510    0.000000000   -0.006875504   -0.012809861   -0.043019615\natom    16.911783770   16.107704983    7.688512539   H    0.110665490    0.000000000    0.006713966    0.011433370    0.028267991\natom    18.328113278   18.516190235    8.528021815   H    0.118898150    0.000000000   -0.000175840   -0.004542786    0.012591957\natom     4.935770073   18.663509563    6.368200054   O   -0.194094220    0.000000000    0.031139053   -0.066276697    0.021098669\natom     6.518835853   17.598527525    5.812888693   H    0.156894820    0.000000000   -0.042755679    0.033516151    0.011475343\natom     4.178872098   17.417123193    7.699892475   H    0.137280880    0.000000000    0.015711127    0.037753788   -0.030393813\natom    21.151675148   20.879473220    7.686178727   O   -0.248140030    0.000000000   -0.009994913   -0.003084252    0.015181890\natom    21.725161902   21.081677775    5.962589077   H    0.096696550    0.000000000    0.004375907    0.001697312   -0.018251199\natom    22.673568579   21.355735416    8.583993635   H    0.139564520    0.000000000   -0.002909430   -0.001404868    0.006677838\natom    19.507253717   12.301401988   18.501302967   O   -0.199717660    0.000000000   -0.028410932   -0.035128726    0.043667183\natom    19.776549245   13.758948329   17.594513745   H    0.142371980    0.000000000    0.012693146    0.047711282   -0.031771675\natom    17.867647309   12.681150163   19.378767407   H    0.141514070    0.000000000    0.014688099   -0.002133776   -0.011109509\natom    23.134797998   17.370023640   17.326635511   O   -0.251377170    0.000000000   -0.000268730   -0.000574628   -0.003573364\natom    23.309537263   17.766571487   19.122904057   H    0.118237060    0.000000000    0.005638293   -0.001455468   -0.001185792\natom     0.463480083   18.316502796   16.477809882   H    0.138644360    0.000000000   -0.009964426   -0.001923402    0.004419419\natom     7.198349513    9.467121587   20.207068712   O   -0.243428280    0.000000000    0.009787410   -0.009154114    0.016239349\natom     7.841261053    8.491977165   21.715395794   H    0.127971510    0.000000000   -0.015877818    0.012471507   -0.019846659\natom     5.641732350   10.325405299   20.696485297   H    0.130413120    0.000000000    0.003877775    0.000013170    0.004937889\nenergy   -4900.14395256\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.3353824022135491E-01\nconv_energy   8.5167544626563699E+02\nconv_length   2.2798325235535355E+01\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\natom_energy                     H -0.45890771  # Free atom reference energy (H).\natom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          2              # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.0041         # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.3221693617312411E+00   2.6431829268494309E+00   2.1712109289368211E+00   1.8491740949754865E-01\n         1          2   8.8165507590121150E-01   1.5021513119899590E+00   1.2778122580628937E+00   9.2610524821423193E-02\n         1          3   9.5063170525557483E-01   1.9645434630136041E+00   1.5754555245780282E+00   1.4788592306892495E-01\n         1          4   6.8720926352748557E-01   1.1734596705047000E+00   9.8013669175527418E-01   7.3842159315803318E-02\n         1          5   5.3114680346458376E-01   1.1735104787393884E+00   8.6903918776136291E-01   9.7965057245763557E-02\n         1          6   4.5446803146192011E-01   7.7208808607104440E-01   6.2874675223192622E-01   4.9613886357228562E-02\n         1          7   2.7732917100342269E-01   6.5610689623748530E-01   4.3632718893459976E-01   5.9842739811322473E-02\n         1          8   3.0248121122588545E-01   5.0262343273858556E-01   4.1296646104933438E-01   3.3605991719978266E-02\n         1          9   2.7091763975787958E-01   4.3771867263061898E-01   3.5532262189207031E-01   3.0837550827151866E-02\n         1         10   3.0607810460301704E-01   8.2737294952385632E-01   5.1367846789526717E-01   8.2396345907449139E-02\n         1         11   1.6781481618321603E-01   3.3262544522941584E-01   2.6405877879038225E-01   2.0079773509946830E-02\n         1         12   1.5199899860595487E-01   5.1758403256923147E-01   2.8216876544103786E-01   5.3030699298770759E-02\n         1         13   7.9964213161399539E-02   2.7810985736196053E-01   1.8323412046338658E-01   2.0256908897343304E-02\n         1         14   5.0022559628496853E-02   3.1251552588862541E-01   1.4532438879262641E-01   3.5408976290196639E-02\n         1         15   1.0972758958750323E-02   1.9780403448379363E-01   7.5743125451543408E-02   2.0368083851198718E-02\n         1         16   4.0564819222288929E-03   2.0020915524049140E-01   4.5553334901545346E-02   2.6816652873187446E-02\n         1         17   1.6392409428096447E-03   2.9517020055424961E-02   1.6279759210012987E-02   5.1720047323677923E-03\n         1         18   5.9064708278282335E-03   2.9881994921192988E-02   1.8893635227048098E-02   3.4996722469230767E-03\n         1         19   1.8153163715731997E-03   3.2340440598797260E-02   1.5251396366744187E-02   4.9976078942981228E-03\n         1         20   7.7218851587917817E-02   1.9164313445186615E-01   1.3079740560426881E-01   1.8047175980621721E-02\n         1         21   6.4007973804529085E-03   3.4352270791092009E-02   1.6008839167468644E-02   4.4985079286083869E-03\n         1         22   7.1919475628770427E-04   1.1394644806220967E-02   5.5243272719661379E-03   2.1112600852613100E-03\n         1         23   4.6183461439172707E-02   1.1842669503328147E-01   7.3672710889966644E-02   1.1140003788632082E-02\n         1         24   9.1433846516636246E-04   7.2448079200631453E-03   3.4708660085473373E-03   1.0041987311934573E-03\n         1         25   1.1212823920457925E-03   7.4909848911080303E-03   3.3413578741542951E-03   9.5694251844215597E-04\n         1         26   1.4490733031593294E-02   3.4896169686888266E-02   2.2593555563529325E-02   3.2185820632296114E-03\n         1         27   6.2962266934873338E-04   5.1814478231837560E-03   2.0022000098156752E-03   6.1375837903328550E-04\n         2          1   1.7278003594190612E+00   3.0200705624254782E+00   2.5556245161257864E+00   1.8104733161286587E-01\n         2          2   5.2830234917918673E-01   1.1347830825159733E+00   9.1702802710027076E-01   8.9012140951749405E-02\n         2          3   1.3413913725634967E+00   2.3281910061725970E+00   1.9602733835105492E+00   1.4178250890732702E-01\n         2          4   3.3973454632955868E-01   7.9106176901817504E-01   6.2374175167509027E-01   6.7920469352681950E-02\n         2          5   9.1198642957067100E-01   1.5175524019444977E+00   1.2574935044638531E+00   9.0840547884065884E-02\n         2          6   1.4007970492770014E-01   3.9737354984873224E-01   2.8710959644163986E-01   3.9568021301260234E-02\n         2          7   6.6026020925081808E-01   9.9631802932099356E-01   8.2593292209866853E-01   5.6260988440501335E-02\n         2          8   4.2701723604415549E-02   1.5473052305514301E-01   1.0198348350484386E-01   1.9093898225897559E-02\n         2          9   5.9779238984500482E-01   8.7214154955749057E-01   7.1064524378414085E-01   4.5991882003602061E-02\n         2         10   1.9985378144803514E-01   6.5655897218566894E-01   4.4271239561305453E-01   7.3593849758180452E-02\n         2         11   4.1502563461045067E-01   6.5057595299175830E-01   5.2811755758076440E-01   2.9733597901087361E-02\n         2         12   1.0539027020125716E-01   4.7399188573233930E-01   2.8778725245738251E-01   6.7239561345988727E-02\n         2         13   2.4956202107947600E-01   4.9952217805446975E-01   3.6646824092677327E-01   2.9672553474082333E-02\n         2         14   3.1300696765894295E-02   3.1614843646709484E-01   1.5249418366539025E-01   5.4780305337940489E-02\n         2         15   6.3223700189372165E-02   3.0994899667375020E-01   1.5148625090308679E-01   2.9292310574299443E-02\n         2         16   8.5041679154014842E-04   1.3041346013164093E-01   3.7068123760173058E-02   2.4399391242546552E-02\n         2         17   4.4317519796445081E-03   2.5144073105818975E-02   1.3864844737089635E-02   3.2528315804001926E-03\n         2         18   8.1860993427251071E-05   1.3466045085857874E-03   5.5084028256248212E-04   2.3430301127519475E-04\n         2         19   7.9083037432116490E-02   2.5796793485264985E-01   1.7694123779133991E-01   2.7939522253685803E-02\n         2         20   2.1441033279915650E-03   1.4776262369620617E-02   8.7339425459512163E-03   2.1168859996502751E-03\n         2         21   1.3804891348827978E-02   4.9194759330688440E-02   2.8874387893367045E-02   5.8165890736636416E-03\n         2         22   2.6051407335652452E-02   1.0496356106048180E-01   6.4565049831895718E-02   1.2764836900154985E-02\n         2         23   2.9045826947719750E-02   7.2380719406296798E-02   4.5302566117440039E-02   7.3746817680981859E-03\n         2         24   1.3607528794234713E-03   1.0984596811105142E-02   5.4354345893373179E-03   1.6123179093972310E-03\n         2         25   1.6511705563216422E-05   5.2501188368496877E-04   1.8911718281856260E-04   8.6408752300015161E-05\n         2         26   2.0072212589651677E-02   7.6648328811296088E-02   4.4378983939995231E-02   8.7718911463090226E-03\n         2         27   1.0836132444402223E-02   5.4980675069752655E-02   3.0545338532716584E-02   7.5167668082524765E-03\n         2         28   6.2351340984659318E-05   1.4410461325923972E-03   5.3991094439800945E-04   2.2577401100509146E-04\n         2         29   8.4843170594598311E-03   2.6368291824445372E-02   1.5321153812859305E-02   2.3405182276765900E-03\n         2         30   4.2231192236936999E-03   1.8846153205016307E-02   1.0613759624824323E-02   2.2975215777576064E-03\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3_4G/hardness.001.data",
    "content": "9.76488\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3_4G/hardness.008.data",
    "content": "9.2819\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3_4G/input.data",
    "content": "begin\ncomment written by RuNNerDecom\nlattice      17.007526      0.000000      0.000000\nlattice       0.000000     14.728517      0.000000\nlattice       0.000000      0.000000     13.885701\natom    -0.004100346   -0.049554341   -0.016880525   O   -0.217594850    0.000000000   -0.000019447    0.000481580    0.000359981\natom     1.492583556    0.873520660    0.644659612   H    0.109115980    0.000000000   -0.000202677   -0.000257027   -0.000178676\natom    15.503581693    0.881917393    0.626419599   H    0.109022510    0.000000000    0.000192110   -0.000262625   -0.000150233\natom     8.498589062    0.043176894    0.025537700   O   -0.218598620    0.000000000   -0.000007438   -0.000488982   -0.000352494\natom     8.491160360   12.981354552    0.599284097   H    0.108512460    0.000000000   -0.000026810    0.000429873    0.000083216\natom     8.499220060   -0.027896059   12.033864819   H    0.108863030    0.000000000    0.000016251    0.000174304    0.000408875\natom     4.277295961    7.375744190   -0.020977565   O   -0.217668440    0.000000000   -0.000310168   -0.000213050    0.000420406\natom     4.228769952    5.619750841    0.645799003   H    0.109194280    0.000000000   -0.000016797    0.000296803   -0.000285047\natom     2.727070736    8.215583168    0.628405228   H    0.109614200    0.000000000    0.000339790   -0.000057912   -0.000203425\natom    12.695333412    7.352384758    0.005785717   O   -0.218143300    0.000000000    0.000391141    0.000214480   -0.000352045\natom    14.242870010    8.239469758    0.596217904   H    0.109580130    0.000000000   -0.000330012   -0.000204820    0.000033924\natom    12.778339040    7.376230719   12.014619869   H    0.108920890    0.000000000   -0.000185235   -0.000081185    0.000359839\natom     4.207316271    2.472274106    1.730280339   O   -0.218226050    0.000000000    0.000393457   -0.000233996    0.000350147\natom     5.753769376    1.579438121    1.146854142   H    0.109643110  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-0.000472218\natom     7.428693349    0.841322810    8.494342261   H    0.114658320    0.000000000    0.000454770    0.000017789    0.000269920\natom     8.926769979   13.732170069    8.461023992   H    0.114512150    0.000000000    0.000212452    0.000381930    0.000294301\natom     4.425625090    7.705534540    9.092138124   O   -0.228907560    0.000000000    0.000548187    0.000326435    0.000462891\natom     4.483381106    7.739233192   10.957375909   H    0.114152140    0.000000000   -0.000262391   -0.000176055   -0.000448850\natom     5.974141247    8.582266903    8.531898203   H    0.115099330    0.000000000   -0.000440676   -0.000292415   -0.000136103\natom    13.354726669    7.747307141    9.108017265   O   -0.228880370    0.000000000    0.000544735   -0.000320663   -0.000478656\natom    13.415351271    6.001067121    8.452751603   H    0.114683450    0.000000000   -0.000208654    0.000387213    0.000302987\natom    14.903704411    8.568365323    8.467711922   H    0.114458740    0.000000000   -0.000459994    0.000032098    0.000271941\nenergy   -1225.21103773\ncharge         0.0000000000\nend\n\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3_4G/input.nn",
    "content": "################################################################################\n### This is the input file for n2p2\n### It contains only a subset of all keywords\n################################################################################\n\n################################################################################\n### general keywords\n################################################################################\n\nnnp_generation 4\nuse_short_forces\n\nnumber_of_elements 2\nelements H O\n\ninitial_hardness        H        10.0\ninitial_hardness        O        10.0\n\nfixed_gausswidth  H 0.5858120110359424\nfixed_gausswidth  O 1.2491023848218\n\nscreen_electrostatics 4.8 12.0\n\nrandom_seed 12346\n\newald_truncation_error_method 1\newald_prec 1.e-5 0.36\nfour_pi_epsilon 1.0                             # Value of 4*pi*epsilon (1/Coulomb constant)\n\n################################################################################\n### NN structure of the short-range NN\n################################################################################\nglobal_hidden_layers_short 2\nglobal_nodes_short 15 15\nglobal_activation_short t t l\n\n################################################################################\n### NN structure of the electrostatic NN\n################################################################################\nglobal_hidden_layers_electrostatic 2\nglobal_nodes_electrostatic 15 15\nglobal_activation_electrostatic t t l\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (General)\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10              # Number of training epochs.\nupdater_type                    1               # Weight update method\n                                                # (0 = Gradient Descent,\n                                                # 1 = Kalman filter).\nparallel_mode                   1               # Training parallelization used\n                                                # (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1               # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0               # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2               # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\n#memorize_symfunc_results                       # Keep symmetry function results in memory.\nrmse_threshold_trials           4               # Maximum number of RMSE threshold trials.\nmain_error_metric               RMSEpa          # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\ntest_fraction                   0.1             # Fraction of structures kept for testing.\nweights_min                     -1.0            # Minimum value for initial random weights.\nweights_max                     1.0             # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\nwrite_weights_epoch             10              # Write weights every this many epochs.\nscale_symmetry_functions\ncenter_symmetry_functions\nwrite_neuronstats               0               # Write neuron statistics every this many epochs.\n#write_trainlog                                 # Write training log file.\n\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (charges, stage 1)\n################################################################################\ntask_batch_size_charge          1\n#nguyen_widrow_weights_charge                   # Initialize neural network weights according to Nguyen-Widrow scheme.\ncharge_fraction                 1.000\n#write_traincharges              1              # Write charge comparison. Can produce large files.\n#use_old_weights_charge                         # Restart fitting with old weight parameters.\n\n################################################################################\n# ADDITIONAL SETTINGS FOR TRAINING (short-range, stage 2)\n################################################################################\ntask_batch_size_energy          1               # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1               # Number of force update candidates prepared per task for each update (0 = Entire training set).\nforce_weight                    10.0            # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000           # Fraction of energy updates per epoch.\nshort_force_fraction            0.025           # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.80            # RMSE threshold for energy update candidates.\nshort_force_error_threshold     0.80            # RMSE threshold for force update candidates.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\n#repeated_energy_update\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               0               # Write energy comparison every this many epochs.\nwrite_trainforces               0               # Write force comparison every this many epochs.\n\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# These two parameters are only used if \"updater_type\" is \"1\".\n#kalman_lambda_short 0.98000                    # Only for fading memory Kalman filter\n#kalman_nue_short 0.99870\n\nkalman_type                     0               # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2          # General Kalman filter parameter epsilon, covariance matrix initialization (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01            # General Kalman filter parameter q0, initial process noise (\"large\").\nkalman_qtau                     2.302           # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6          # General Kalman filter parameter qmin, final process noise (typ. 1.0E-6).\nkalman_eta                      0.01            # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302           # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   0.500           # Standard Kalman filter parameter etamax (1.0+).\n\n\n################################################################################\n### symmetry function definitions (all modes):\n################################################################################\ncutoff_type 2\n\n#radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3_4G/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170768E+00   9.6166419119419100E+00   2.2691752247542198E+00   6.7883526611658851E-01\n         1          2   7.3274438904180605E-01   5.0028559321574226E+00   1.3272332317543585E+00   3.3936750181780473E-01\n         1          3   7.6010783783215707E-01   7.1427942966219833E+00   1.6470726712825299E+00   5.0771115927384247E-01\n         1          4   5.4842285884800812E-01   3.7661771168267748E+00   1.0163698211361722E+00   2.5362958053787693E-01\n         1          5   4.0080665126604670E-01   4.1469832401668647E+00   9.0925040981537886E-01   2.9758019277508418E-01\n         1          6   3.6209352253798222E-01   2.2678239402766063E+00   6.4931154122889645E-01   1.4835420345383105E-01\n         1          7   1.8919103878435906E-01   2.2292652677252813E+00   4.5693857051003844E-01   1.5976079618578098E-01\n         1          8   2.6704178695764291E-01   1.3208742362468950E+00   4.2395636902644862E-01   8.0492394978464013E-02\n         1          9   2.4513099752055154E-01   9.4751160662053036E-01   3.6244199023263701E-01   5.2993540556106881E-02\n         1         10   2.2248910067848979E-01   2.7596216013647377E+00   5.3891576898130733E-01   2.0137334230483903E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910822E-01   2.6188094566404644E-02\n         1         12   9.9110926426029297E-02   1.7265405335201476E+00   2.9553976311554875E-01   1.1619768775752870E-01\n         1         13   6.5093699123904183E-02   3.4521757733971209E-01   1.8521249136783141E-01   1.9741155185936082E-02\n         1         14   3.1653527247864993E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038543E-02\n         1         15   2.9202821602466629E-03   2.6453981776124164E-01   7.6525296616004670E-02   1.8780956137549890E-02\n         1         16   3.2145385719803426E-04   2.8696425565429251E-01   4.5792284631233637E-02   2.3263495133569036E-02\n         1         17   2.4693757528509687E-04   1.3848731138266307E-01   1.7693289653297618E-02   9.7460303038080891E-03\n         1         18   5.0992836797990751E-03   5.8319173651547451E-01   2.3851656540978417E-02   3.7790771891778180E-02\n         1         19   3.2282960174310137E-04   2.1613962298381934E-01   1.7072560754702336E-02   1.4026518665786074E-02\n         1         20   4.9647513277769798E-02   1.6851617426880205E+00   1.4541325969622548E-01   1.0954306125703019E-01\n         1         21   3.4073471604482279E-03   3.1637071808861694E-01   1.8422597685566731E-02   2.0125274191649705E-02\n         1         22   1.3121382132811758E-04   1.0258348935693717E-01   6.3684016949344113E-03   6.6071626858835008E-03\n         1         23   3.3813162813665920E-02   9.1618560879938959E-01   8.1266384503339659E-02   5.7918502576695619E-02\n         1         24   4.1708500446352941E-04   1.5785966980407004E-01   4.6646981268568680E-03   9.8630700614506534E-03\n         1         25   7.3528900917695659E-04   5.9225627251013005E-02   3.7042174075139775E-03   3.3118079036492604E-03\n         1         26   8.9828333062972488E-03   1.9426085555380748E-01   2.4093377110646314E-02   1.0980657457661641E-02\n         1         27   2.1228022180417680E-04   8.7777813240869623E-03   2.0550705761547975E-03   5.8802103858137062E-04\n         2          1   1.5142595331454249E+00   1.0005711988560002E+01   2.6544664635087183E+00   6.7806617585689344E-01\n         2          2   4.4366445360926210E-01   4.6195409357987094E+00   9.6587051599896079E-01   3.3688559575009175E-01\n         2          3   1.1907810568758721E+00   7.5323544094345012E+00   2.0327396422723472E+00   5.0607867531004291E-01\n         2          4   2.7576036468694687E-01   3.3862131032504497E+00   6.5929732667024821E-01   2.5004687333979797E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577938E+00   2.9449908325462504E-01\n         2          6   1.0517053799863607E-01   1.8909877539194522E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859717E-01   2.6154328621607861E+00   8.4791273805289535E-01   1.5714071578589722E-01\n         2          8   2.3251646720171409E-02   9.3641034200657891E-01   1.1140979781150938E-01   6.9796654369842920E-02\n         2          9   5.1354161698115453E-01   1.8545341781448568E+00   7.2488398046527269E-01   9.8011511620610281E-02\n         2         10   1.1057465545812288E-01   2.9121456897811355E+00   4.7474421797982730E-01   2.3441807910092263E-01\n         2         11   3.5269317308496512E-01   1.0714592032613126E+00   5.3547944391821689E-01   4.5179661104164701E-02\n         2         12   3.0424313539726335E-02   2.5277642768509310E+00   3.1652845366685034E-01   2.1026891409654727E-01\n         2         13   1.5980022688828249E-01   6.6348817066386478E-01   3.7042498273566316E-01   3.0753700953609124E-02\n         2         14   2.7781847150922792E-03   2.3030057819082543E+00   1.7737800292869685E-01   1.8600239464755822E-01\n         2         15   9.5641036809350141E-03   3.9085233064570801E-01   1.5305059323200967E-01   2.7862233984302306E-02\n         2         16   3.7500170432291853E-06   2.0367068825281995E+00   5.4144316535640356E-02   1.4305857218443541E-01\n         2         17   2.4726232100491102E-03   3.4335400617385059E-01   1.6684597803376656E-02   2.1902951351570873E-02\n         2         18   1.7405672406959621E-05   5.6319316766205323E-02   9.5478184601751812E-04   3.3588039002222379E-03\n         2         19   5.4785372164648002E-02   3.0182597583971473E+00   2.0392031625072374E-01   2.0088721011517160E-01\n         2         20   1.3795234987637444E-03   4.9878800454061345E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814470E-03   2.6739582842775922E-01   3.0851859894574375E-02   1.7089886758420002E-02\n         2         22   1.7021399438214367E-02   1.4167796508898465E+00   7.6274174813506776E-02   9.2852504206357725E-02\n         2         23   1.9759831791959889E-02   4.0756378297923918E-01   4.8843503112397928E-02   2.5474332458885442E-02\n         2         24   5.2768632746659277E-04   2.3324050667069179E-01   7.2057238727819490E-03   1.4495435261027756E-02\n         2         25   1.1144879740881774E-05   3.5285772934088605E-02   4.2545240948261046E-04   2.0471375111486014E-03\n         2         26   1.6013752685265070E-02   8.2245409953473070E-01   5.0845479076508424E-02   5.2802834522172978E-02\n         2         27   3.9898424495541755E-03   7.8557031440100333E-01   3.6926675414383131E-02   5.0474458307624807E-02\n         2         28   4.0523818189746801E-05   9.8448068666706065E-02   1.2119235889230273E-03   5.7945700128174682E-03\n         2         29   6.0374649986214670E-03   9.9251766407842473E-02   1.6156539248049703E-02   5.5245068674135544E-03\n         2         30   2.9595491075765702E-03   1.5478537567691847E-01   1.1641055270110558E-02   8.9415193910804582E-03\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3_4G/weightse.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.5961892521418283E-01 a         1     0     1     1     1\n  3.4656022377475404E-01 a         2     0     1     1     2\n  8.0831084843607810E-03 a         3     0     1     1     3\n  1.7122266166423891E-01 a         4     0     1     1     4\n -3.0859393566191118E-01 a         5     0     1     1     5\n  3.0041429892044019E-01 a         6     0     1     1     6\n -2.1927180883441963E-01 a         7     0     1     1     7\n -1.4553314010595697E-01 a         8     0     1     1     8\n -1.0982527143677157E-03 a         9     0     1     1     9\n -1.5980399612309548E-01 a        10     0     1     1    10\n -7.0754493042881714E-02 a        11     0     1     1    11\n  4.4146899949475564E-02 a        12     0     1     1    12\n -3.0948106272712228E-01 a        13     0     1     1    13\n -1.5727778715379736E-02 a        14     0     1     1    14\n  5.9590074526087500E-02 a        15     0     1     1    15\n  1.8572717413386380E-01 a        16     0     2     1     1\n -2.5938308477066208E-01 a        17     0     2     1     2\n  2.6648115430290475E-01 a        18     0     2     1     3\n -1.6967465192116246E-01 a        19     0     2     1     4\n  8.3423483692718334E-02 a        20     0     2     1     5\n -3.1675088338888729E-01 a        21     0     2     1     6\n -4.8427193718736820E-02 a        22     0     2     1     7\n  1.8240037347855922E-01 a        23     0     2     1     8\n  8.9300711184150991E-02 a        24     0     2     1     9\n -2.0043120055080463E-01 a        25     0     2     1    10\n -1.0937244931923044E-01 a        26     0     2     1    11\n  6.3942262532993149E-02 a        27     0     2     1    12\n  2.4207356594790108E-01 a        28     0     2     1    13\n  6.5535137808707775E-02 a        29     0     2     1    14\n -8.1964938481805930E-02 a        30     0     2     1    15\n  3.5519912574240092E-01 a        31     0     3     1     1\n -2.8346403622306693E-01 a        32     0     3     1     2\n  1.9593738300924413E-02 a        33     0     3     1     3\n -2.1753281805580696E-01 a        34     0     3     1     4\n  1.6571754552354589E-01 a        35     0     3     1     5\n  2.4200618143049996E-01 a        36     0     3     1     6\n -3.0104335224667761E-01 a        37     0     3     1     7\n -1.8330480428021656E-01 a        38     0     3     1     8\n  2.4682809325814726E-02 a        39     0     3     1     9\n  2.6116155456656154E-01 a        40     0     3     1    10\n -7.3917154488235881E-02 a        41     0     3     1    11\n  1.0533804894392076E-01 a        42     0     3     1    12\n  2.3498634909495042E-01 a        43     0     3     1    13\n -8.6790119500668422E-02 a        44     0     3     1    14\n -2.7953105320779520E-01 a        45     0     3     1    15\n  3.6596517366968673E-01 a        46     0     4     1     1\n -3.3751480334935823E-02 a        47     0     4     1     2\n -1.5037085292708394E-01 a        48     0     4     1     3\n -8.0896110087048570E-02 a        49     0     4     1     4\n  2.5327497277742722E-01 a        50     0     4     1     5\n -2.4060461475319309E-01 a        51     0     4     1     6\n -5.0527357957673540E-02 a        52     0     4     1     7\n -4.1363861218892864E-02 a        53     0     4     1     8\n  1.1912029117174308E-01 a        54     0     4     1     9\n  3.4390173219744941E-01 a        55     0     4     1    10\n -2.7493210845218408E-01 a        56     0     4     1    11\n -2.4826865529940462E-01 a        57     0     4     1    12\n  1.3398059886984678E-01 a        58     0     4     1    13\n  1.8598043268192035E-01 a        59     0     4     1    14\n  8.9801004371839965E-02 a        60     0     4     1    15\n  9.3149672831425015E-02 a        61     0     5     1     1\n -2.2439630376930492E-01 a        62     0     5     1     2\n  1.2434902852316126E-01 a        63     0     5     1     3\n  2.5344988186078649E-01 a        64     0     5     1     4\n  2.8895990268491284E-01 a        65     0     5     1     5\n -2.4687060908798333E-01 a        66     0     5     1     6\n  2.2386695242300730E-01 a        67     0     5     1     7\n  1.3215951038858112E-01 a        68     0     5     1     8\n  3.1715206778679694E-01 a        69     0     5     1     9\n  5.0290080557515243E-02 a        70     0     5     1    10\n -1.4459442991296040E-01 a        71     0     5     1    11\n -2.0108314273694949E-01 a        72     0     5     1    12\n -2.7539407849531400E-01 a        73     0     5     1    13\n -3.1609596136000095E-01 a        74     0     5     1    14\n -2.3405216023177669E-01 a        75     0     5     1    15\n -6.7339958354442772E-02 a        76     0     6     1     1\n -2.1029595928910738E-02 a        77     0     6     1     2\n -3.0986045336526497E-01 a        78     0     6     1     3\n -4.0042412525918052E-02 a        79     0     6     1     4\n  1.1438898188216973E-01 a        80     0     6     1     5\n  2.2415410112489209E-01 a        81     0     6     1     6\n  3.3579833214872912E-01 a        82     0     6     1     7\n -1.6155087952700939E-01 a        83     0     6     1     8\n -4.0483211779376284E-02 a        84     0     6     1     9\n -2.7589540019250958E-01 a        85     0     6     1    10\n  2.0068645937192642E-01 a        86     0     6     1    11\n -6.9879568857933783E-02 a        87     0     6     1    12\n  1.4215389592830130E-01 a        88     0     6     1    13\n  3.6834588236264271E-01 a        89     0     6     1    14\n -2.5956105685069791E-01 a        90     0     6     1    15\n  1.5612429939521255E-02 a        91     0     7     1     1\n -6.2579762140316117E-02 a        92     0     7     1     2\n -2.6486785729612827E-01 a        93     0     7     1     3\n -1.7830268635347446E-01 a        94     0     7     1     4\n  3.3923216841888743E-01 a        95     0     7     1     5\n  3.4023756736329719E-01 a        96     0     7     1     6\n -2.0407234877780411E-01 a        97     0     7     1     7\n -1.9252737365625803E-02 a        98     0     7     1     8\n -3.3234942039133042E-01 a        99     0     7     1     9\n -1.7777547366931928E-01 a       100     0     7     1    10\n -1.6642429699364364E-01 a       101     0     7     1    11\n -1.8563025265514474E-01 a       102     0     7     1    12\n -6.1516582550561152E-02 a       103     0     7     1    13\n  1.3654177163922729E-01 a       104     0     7     1    14\n -2.3958045129107974E-01 a       105     0     7     1    15\n -2.2782731865118427E-01 a       106     0     8     1     1\n  2.3482764937152986E-01 a       107     0     8     1     2\n  1.1337952826574324E-01 a       108     0     8     1     3\n -4.7644787205397492E-02 a       109     0     8     1     4\n -3.1015021064794024E-01 a       110     0     8     1     5\n  3.4862334951209750E-01 a       111     0     8     1     6\n -1.7840539892470655E-01 a       112     0     8     1     7\n -1.7962352363315173E-01 a       113     0     8     1     8\n -1.9688228250216311E-01 a       114     0     8     1     9\n  3.3686007318957811E-01 a       115     0     8     1    10\n  6.8745782857769069E-02 a       116     0     8     1    11\n  3.2652343136625828E-01 a       117     0     8     1    12\n  4.1464602905104259E-02 a       118     0     8     1    13\n  1.8133052035603701E-02 a       119     0     8     1    14\n -3.0144335490257956E-01 a       120     0     8     1    15\n  1.5227502492447267E-01 a       121     0     9     1     1\n -3.3776720439702074E-01 a       122     0     9     1     2\n  2.3830079633648713E-01 a       123     0     9     1     3\n -2.3056938190654142E-01 a       124     0     9     1     4\n -5.6948732816647647E-02 a       125     0     9     1     5\n  2.3451146537917955E-01 a       126     0     9     1     6\n -2.4514900557027924E-01 a       127     0     9     1     7\n  2.8059771609648787E-01 a       128     0     9     1     8\n -1.9455442286436586E-01 a       129     0     9     1     9\n  1.2876802074366700E-01 a       130     0     9     1    10\n -1.8279980586952357E-01 a       131     0     9     1    11\n -2.0198420948823811E-01 a       132     0     9     1    12\n  2.1257691861276942E-01 a       133     0     9     1    13\n -3.1483281091571336E-01 a       134     0     9     1    14\n -1.8938871952346042E-01 a       135     0     9     1    15\n  6.5873273235361133E-04 a       136     0    10     1     1\n -3.7198788095692636E-01 a       137     0    10     1     2\n -1.4489806992471696E-01 a       138     0    10     1     3\n  3.0213594162285512E-01 a       139     0    10     1     4\n -1.6109176847862736E-01 a       140     0    10     1     5\n  2.7043010440308957E-01 a       141     0    10     1     6\n -2.2853181714063897E-01 a       142     0    10     1     7\n -2.0593605210703053E-01 a       143     0    10     1     8\n -1.6932588152853345E-01 a       144     0    10     1     9\n -1.1962741554063351E-01 a       145     0    10     1    10\n -3.4931275282978580E-01 a       146     0    10     1    11\n  4.4690294197135431E-02 a       147     0    10     1    12\n  2.5339814395309362E-01 a       148     0    10     1    13\n  1.8857008696379651E-01 a       149     0    10     1    14\n  1.1059526537848953E-01 a       150     0    10     1    15\n  7.3952175467275352E-02 a       151     0    11     1     1\n -3.2149903282124109E-01 a       152     0    11     1     2\n -2.5780092757610601E-01 a       153     0    11     1     3\n  3.5688351566622045E-01 a       154     0    11     1     4\n  2.1164603441201676E-01 a       155     0    11     1     5\n  1.7427652426671325E-01 a       156     0    11     1     6\n  3.2617806125572707E-01 a       157     0    11     1     7\n -1.4313936971743821E-01 a       158     0    11     1     8\n  3.3169940998736902E-01 a       159     0    11     1     9\n -7.9111111932396574E-02 a       160     0    11     1    10\n  6.8072391540370578E-02 a       161     0    11     1    11\n -2.0737530149794084E-01 a       162     0    11     1    12\n -2.2819894043317124E-01 a       163     0    11     1    13\n -1.9863503162223548E-01 a       164     0    11     1    14\n -1.9452813225453267E-01 a       165     0    11     1    15\n  3.3892426443544739E-02 a       166     0    12     1     1\n  3.4367297429287591E-01 a       167     0    12     1     2\n  1.7161213426342081E-01 a       168     0    12     1     3\n -2.3215387973955789E-01 a       169     0    12     1     4\n  2.5813571695022081E-01 a       170     0    12     1     5\n -2.4124162806000138E-01 a       171     0    12     1     6\n  1.6069291067995928E-01 a       172     0    12     1     7\n -2.0444068970211617E-03 a       173     0    12     1     8\n  2.0330941593935217E-01 a       174     0    12     1     9\n  2.2945122266218845E-01 a       175     0    12     1    10\n  8.2272275674245540E-02 a       176     0    12     1    11\n -7.7974365732761831E-03 a       177     0    12     1    12\n  8.8194467622775233E-02 a       178     0    12     1    13\n  8.0273115768527720E-02 a       179     0    12     1    14\n  1.7531736639536763E-02 a       180     0    12     1    15\n -1.9617099660193687E-02 a       181     0    13     1     1\n  3.5644675622925348E-01 a       182     0    13     1     2\n  6.8067351895113787E-02 a       183     0    13     1     3\n  1.1248926867118524E-01 a       184     0    13     1     4\n -2.9436422500311599E-01 a       185     0    13     1     5\n -2.8450030386854991E-01 a       186     0    13     1     6\n -2.7841637297724287E-01 a       187     0    13     1     7\n -2.5286405755340241E-01 a       188     0    13     1     8\n  3.6053325822011395E-01 a       189     0    13     1     9\n -7.5884544097963760E-02 a       190     0    13     1    10\n  1.4219552696678181E-01 a       191     0    13     1    11\n  1.2019905457667143E-01 a       192     0    13     1    12\n -8.1620147367363560E-02 a       193     0    13     1    13\n  2.3186257207433322E-02 a       194     0    13     1    14\n -3.1749678288336008E-01 a       195     0    13     1    15\n -4.2963579722791363E-02 a       196     0    14     1     1\n  3.2722709681629186E-01 a       197     0    14     1     2\n -7.8448220342279926E-02 a       198     0    14     1     3\n  3.2249122427589710E-01 a       199     0    14     1     4\n -2.4190948735642995E-01 a       200     0    14     1     5\n  6.7686859519853065E-02 a       201     0    14     1     6\n  2.4667115787035035E-01 a       202     0    14     1     7\n  3.0094767624751606E-01 a       203     0    14     1     8\n -7.0176891597692539E-02 a       204     0    14     1     9\n -4.0709796041564460E-02 a       205     0    14     1    10\n  3.5026375104825230E-01 a       206     0    14     1    11\n  1.3055551941096433E-01 a       207     0    14     1    12\n  6.7263327950906476E-02 a       208     0    14     1    13\n  1.7452755518875959E-01 a       209     0    14     1    14\n -2.7236479627021731E-01 a       210     0    14     1    15\n -4.5719059331667901E-02 a       211     0    15     1     1\n -2.8594391505747119E-01 a       212     0    15     1     2\n  1.1731800937258784E-01 a       213     0    15     1     3\n  3.6169979809798164E-01 a       214     0    15     1     4\n  2.9607574561738337E-01 a       215     0    15     1     5\n -2.5654655489675793E-01 a       216     0    15     1     6\n -1.1644241122788977E-01 a       217     0    15     1     7\n -2.8677795690312197E-01 a       218     0    15     1     8\n -3.3765336186046957E-01 a       219     0    15     1     9\n  1.4649099145657093E-02 a       220     0    15     1    10\n -2.1912713836920744E-01 a       221     0    15     1    11\n -3.1119543910794339E-01 a       222     0    15     1    12\n  1.3260643985552761E-01 a       223     0    15     1    13\n -2.3569835958023083E-01 a       224     0    15     1    14\n  6.0505187703423807E-02 a       225     0    15     1    15\n -2.2601052352141798E-01 a       226     0    16     1     1\n  2.0037117205101385E-01 a       227     0    16     1     2\n  2.2672069302822434E-01 a       228     0    16     1     3\n -2.6388772715931624E-01 a       229     0    16     1     4\n -2.2399582851354413E-01 a       230     0    16     1     5\n -2.3983820924667371E-01 a       231     0    16     1     6\n  3.2660565154357307E-01 a       232     0    16     1     7\n -1.1359831153031637E-02 a       233     0    16     1     8\n -3.4183504684955157E-01 a       234     0    16     1     9\n -3.6223747496791131E-01 a       235     0    16     1    10\n  2.2385632070820177E-01 a       236     0    16     1    11\n -1.8703564766932693E-01 a       237     0    16     1    12\n  3.4948358559515336E-01 a       238     0    16     1    13\n -2.2438417266550581E-01 a       239     0    16     1    14\n -3.8023999119202134E-01 a       240     0    16     1    15\n -6.7681367513890270E-02 a       241     0    17     1     1\n -5.9443853204432524E-04 a       242     0    17     1     2\n -1.2237049246850495E-01 a       243     0    17     1     3\n  1.7596269015243646E-01 a       244     0    17     1     4\n  3.6820259493624835E-01 a       245     0    17     1     5\n  2.3711713416196586E-01 a       246     0    17     1     6\n  2.8632577645562540E-01 a       247     0    17     1     7\n  1.2387540663547884E-01 a       248     0    17     1     8\n -3.4623393718649409E-01 a       249     0    17     1     9\n  3.5860198489341621E-01 a       250     0    17     1    10\n -1.4210042993424357E-01 a       251     0    17     1    11\n  2.6865289061947595E-01 a       252     0    17     1    12\n  8.0430056581844694E-03 a       253     0    17     1    13\n -2.7429551080437042E-01 a       254     0    17     1    14\n -2.2547235714308086E-01 a       255     0    17     1    15\n -6.7142843669077565E-02 a       256     0    18     1     1\n  1.5348757425764459E-01 a       257     0    18     1     2\n  2.9573378630398783E-01 a       258     0    18     1     3\n  3.3087582079458661E-01 a       259     0    18     1     4\n -3.3816565805168752E-01 a       260     0    18     1     5\n  3.4354612153866637E-01 a       261     0    18     1     6\n -1.9586521699349488E-01 a       262     0    18     1     7\n  7.9230652127956991E-02 a       263     0    18     1     8\n  2.0052678447913688E-01 a       264     0    18     1     9\n -3.2448602706940699E-01 a       265     0    18     1    10\n  1.1108601437910656E-01 a       266     0    18     1    11\n -1.3807338909329872E-01 a       267     0    18     1    12\n  2.6207151462116696E-01 a       268     0    18     1    13\n  3.6633516023536528E-01 a       269     0    18     1    14\n -7.4329516392534017E-02 a       270     0    18     1    15\n -3.2453923656860278E-01 a       271     0    19     1     1\n 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-3.6057379134242215E-02 a       547     1     9     2     7\n  2.7435787254467980E-01 a       548     1     9     2     8\n  1.1722184221081686E-01 a       549     1     9     2     9\n -2.7703606110861152E-02 a       550     1     9     2    10\n  2.0282288432205212E-01 a       551     1     9     2    11\n  5.3180954439511326E-02 a       552     1     9     2    12\n  3.2646537691766858E-01 a       553     1     9     2    13\n  2.2792576075874121E-01 a       554     1     9     2    14\n  2.1813623952645400E-01 a       555     1     9     2    15\n  2.1562426892406072E-01 a       556     1    10     2     1\n  2.4594695727404300E-02 a       557     1    10     2     2\n  2.6127583816575206E-01 a       558     1    10     2     3\n -3.3424421096227321E-02 a       559     1    10     2     4\n -7.5199022366450527E-02 a       560     1    10     2     5\n -4.9129435491737088E-02 a       561     1    10     2     6\n  1.0151227487720427E-01 a       562     1    10     2     7\n  2.6776373544687126E-01 a       563     1    10     2     8\n -1.5174422534772580E-01 a       564     1    10     2     9\n  2.4987283799331639E-01 a       565     1    10     2    10\n  4.1304457821035423E-01 a       566     1    10     2    11\n  1.5767964745602428E-01 a       567     1    10     2    12\n  3.0740016403871934E-01 a       568     1    10     2    13\n -3.6710247216877284E-01 a       569     1    10     2    14\n -3.8895933928032972E-01 a       570     1    10     2    15\n -2.7186838084765835E-01 a       571     1    11     2     1\n  4.3997858510995053E-01 a       572     1    11     2     2\n -1.4950931077298679E-01 a       573     1    11     2     3\n  2.3673676030613322E-01 a       574     1    11     2     4\n  2.4798337767234896E-01 a       575     1    11     2     5\n -2.3089103065193450E-01 a       576     1    11     2     6\n -2.7788157528676277E-01 a       577     1    11     2     7\n  4.0086376929788031E-01 a       578     1    11     2     8\n -2.3160354313533638E-01 a       579     1    11     2     9\n  1.4685809544562853E-01 a       580     1    11     2    10\n -2.0339969208008082E-01 a       581     1    11     2    11\n  4.3879534084305862E-03 a       582     1    11     2    12\n  3.2898228043862104E-01 a       583     1    11     2    13\n -3.4015782541057044E-01 a       584     1    11     2    14\n  3.7899641925050953E-01 a       585     1    11     2    15\n  2.7942309821239764E-01 a       586     1    12     2     1\n -4.0534109178762606E-01 a       587     1    12     2     2\n  3.4684931398322322E-01 a       588     1    12     2     3\n  2.7416828078233757E-01 a       589     1    12     2     4\n  1.0712584461245424E-01 a       590     1    12     2     5\n -2.1668715323384616E-01 a       591     1    12     2     6\n -2.3052731570722390E-01 a       592     1    12     2     7\n -2.2404770889818940E-01 a       593     1    12     2     8\n -2.8051802174230417E-01 a       594     1    12     2     9\n  4.0672668851387017E-01 a       595     1    12     2    10\n -2.2398282072555348E-01 a       596     1    12     2    11\n -3.8921710189869077E-02 a       597     1    12     2    12\n -1.1810014614471391E-01 a       598     1    12     2    13\n  2.6072920890630219E-01 a       599     1    12     2    14\n  3.7775458827270203E-01 a       600     1    12     2    15\n -1.5394263439943837E-01 a       601     1    13     2     1\n -1.3882956705239799E-01 a       602     1    13     2     2\n  2.3969409135975694E-01 a       603     1    13     2     3\n -3.5109667237079810E-03 a       604     1    13     2     4\n -3.1341888800124779E-01 a       605     1    13     2     5\n  2.8196125430424868E-01 a       606     1    13     2     6\n -2.2827858703774134E-01 a       607     1    13     2     7\n  3.4928864910825919E-01 a       608     1    13     2     8\n -7.6407736705525184E-02 a       609     1    13     2     9\n -2.3204047883796033E-01 a       610     1    13     2    10\n  2.5712196719288355E-01 a       611     1    13     2    11\n -2.1822920825930150E-01 a       612     1    13     2    12\n -3.9207890153190351E-02 a       613     1    13     2    13\n  1.0851085307387530E-01 a       614     1    13     2    14\n  3.8687807675199715E-01 a       615     1    13     2    15\n -3.2551283198746617E-02 a       616     1    14     2     1\n  3.1551415063820615E-01 a       617     1    14     2     2\n -2.6650935651352031E-01 a       618     1    14     2     3\n  1.3902449368009209E-01 a       619     1    14     2     4\n  1.2867936654662290E-01 a       620     1    14     2     5\n -1.3086825253404258E-01 a       621     1    14     2     6\n  3.0756057080454718E-01 a       622     1    14     2     7\n -2.3391069595917077E-02 a       623     1    14     2     8\n -3.0923026101835732E-01 a       624     1    14     2     9\n  1.7545532059325662E-02 a       625     1    14     2    10\n -1.4817797814735711E-01 a       626     1    14     2    11\n  3.2557279631872432E-01 a       627     1    14     2    12\n -1.3079144341190931E-02 a       628     1    14     2    13\n  2.8754238190290643E-01 a       629     1    14     2    14\n -1.6556088410456185E-01 a       630     1    14     2    15\n -3.8704201999746807E-01 a       631     1    15     2     1\n  4.4248988086806007E-01 a       632     1    15     2     2\n -2.2148978347027706E-01 a       633     1    15     2     3\n  3.7568745501865503E-01 a       634     1    15     2     4\n  4.0561629746830141E-01 a       635     1    15     2     5\n -3.8566049196990482E-01 a       636     1    15     2     6\n  5.3440981313649827E-02 a       637     1    15     2     7\n  1.1944137465114614E-02 a       638     1    15     2     8\n -5.6781833342442106E-02 a       639     1    15     2     9\n  5.0359273469110136E-02 a       640     1    15     2    10\n  3.5783794720915074E-01 a       641     1    15     2    11\n  1.8048793184027284E-01 a       642     1    15     2    12\n  5.6893672524889222E-02 a       643     1    15     2    13\n  1.7383752809310440E-01 a       644     1    15     2    14\n  1.2338214664611379E-01 a       645     1    15     2    15\n -1.1763745953066596E-01 b       646     2     1\n  1.9665371944260987E-01 b       647     2     2\n -3.8851294237210940E-02 b       648     2     3\n -4.5284094587132145E-02 b       649     2     4\n -1.5054156828867662E-01 b       650     2     5\n -1.3627637396131861E-01 b       651     2     6\n  1.6569138512157627E-01 b       652     2     7\n -8.2279410751446430E-02 b       653     2     8\n -3.3128000825695246E-02 b       654     2     9\n  1.0583648206528301E-01 b       655     2    10\n -2.2245622253072657E-03 b       656     2    11\n -1.2048677501066957E-01 b       657     2    12\n  1.9766523435319525E-01 b       658     2    13\n  1.2461770799485626E-01 b       659     2    14\n  1.1606709014082351E-02 b       660     2    15\n  5.7116953779676694E-01 a       661     2     1     3     1\n -8.6502026302617485E-01 a       662     2     2     3     1\n  2.0992183620883895E-01 a       663     2     3     3     1\n  2.1411161404704615E-01 a       664     2     4     3     1\n  6.1882328704751643E-01 a       665     2     5     3     1\n  6.8438607018108277E-01 a       666     2     6     3     1\n -7.7168406427637359E-01 a       667     2     7     3     1\n  3.7531203259694601E-01 a       668     2     8     3     1\n  1.8168800326101769E-01 a       669     2     9     3     1\n -4.8967185100082150E-01 a       670     2    10     3     1\n  2.6230998751565728E-02 a       671     2    11     3     1\n  4.9399870902983090E-01 a       672     2    12     3     1\n -8.9816652308923695E-01 a       673     2    13     3     1\n -5.7277687751470674E-01 a       674     2    14     3     1\n -6.2917302736122477E-02 a       675     2    15     3     1\n -2.3328948714509032E-01 b       676     3     1\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3_4G/weightse.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -2.9672741436856331E-01 a         1     0     1     1     1\n -1.0442211119224025E-01 a         2     0     1     1     2\n  1.3119087641592631E-01 a         3     0     1     1     3\n -1.3769619253735235E-01 a         4     0     1     1     4\n -1.1603824174393756E-01 a         5     0     1     1     5\n -1.8810926135926423E-01 a         6     0     1     1     6\n  2.4313079445602537E-01 a         7     0     1     1     7\n  3.4207948396134957E-01 a         8     0     1     1     8\n -7.2666478910425993E-03 a         9     0     1     1     9\n -1.5569404442274302E-02 a        10     0     1     1    10\n -1.9025206098090594E-01 a        11     0     1     1    11\n  4.1406881305679613E-02 a        12     0     1     1    12\n  2.2554099192046977E-02 a        13     0     1     1    13\n  3.6852562962503298E-02 a        14     0     1     1    14\n  2.0271613913215608E-01 a        15     0     1     1    15\n -2.5393319256267605E-01 a        16     0     2     1     1\n -3.1543196322279687E-01 a        17     0     2     1     2\n -2.2720769862564741E-01 a        18     0     2     1     3\n -3.4632777931119313E-01 a        19     0     2     1     4\n -1.6778088796390972E-01 a        20     0     2     1     5\n -3.1353822058732922E-01 a        21     0     2     1     6\n -2.0497378537751153E-02 a        22     0     2     1     7\n -2.2509057007432354E-01 a        23     0     2     1     8\n -1.4044796968765544E-01 a        24     0     2     1     9\n -2.4720239285223755E-01 a        25     0     2     1    10\n -7.9063958938340506E-02 a        26     0     2     1    11\n  1.0008853298114566E-01 a        27     0     2     1    12\n  1.7249075430244806E-01 a        28     0     2     1    13\n -3.4322139332869483E-01 a        29     0     2     1    14\n -8.3003417707360992E-03 a        30     0     2     1    15\n -1.9198608788031543E-01 a        31     0     3     1     1\n -3.1164899344220476E-01 a        32     0     3     1     2\n -2.3351194489919760E-01 a        33     0     3     1     3\n  1.5807718078057467E-01 a        34     0     3     1     4\n  2.1208861216289873E-01 a        35     0     3     1     5\n  9.4349975063805130E-02 a        36     0     3     1     6\n -3.2467823100531668E-01 a        37     0     3     1     7\n  4.8740017374594276E-02 a        38     0     3     1     8\n  2.1315375585122248E-01 a        39     0     3     1     9\n -6.9098064505998799E-02 a        40     0     3     1    10\n  3.5828764612556840E-01 a        41     0     3     1    11\n -2.0970559175048878E-02 a        42     0     3     1    12\n  1.9685049232796220E-01 a        43     0     3     1    13\n  2.3909343754531309E-01 a        44     0     3     1    14\n -2.8565322991097092E-01 a        45     0     3     1    15\n  3.5481890571581735E-02 a        46     0     4     1     1\n -1.0668846512763409E-02 a        47     0     4     1     2\n  3.5991069186625112E-02 a        48     0     4     1     3\n  3.6617669198747005E-01 a        49     0     4     1     4\n  1.5940318626423855E-01 a        50     0     4     1     5\n -2.0102027522217114E-01 a        51     0     4     1     6\n  2.9040801085921070E-01 a        52     0     4     1     7\n -2.7258234334710679E-01 a        53     0     4     1     8\n -2.9913891626265998E-01 a        54     0     4     1     9\n -3.5592091274132820E-01 a        55     0     4     1    10\n  1.5687795879567595E-01 a        56     0     4     1    11\n -7.8961869540492530E-02 a        57     0     4     1    12\n  1.4386127781261721E-01 a        58     0     4     1    13\n  1.5905954474681250E-01 a        59     0     4     1    14\n  2.7674276558433580E-01 a        60     0     4     1    15\n -6.0479399910369136E-03 a        61     0     5     1     1\n -1.7919873906700612E-01 a        62     0     5     1     2\n  2.7506578683942190E-01 a        63     0     5     1     3\n -1.2407221838041819E-01 a        64     0     5     1     4\n  1.6364917425998496E-01 a        65     0     5     1     5\n  1.5464971370726457E-01 a        66     0     5     1     6\n  2.8716400649308821E-01 a        67     0     5     1     7\n  8.0267524896521572E-02 a        68     0     5     1     8\n  2.2109841223704396E-01 a        69     0     5     1     9\n  2.4942752429285672E-01 a        70     0     5     1    10\n -3.5399921559021374E-01 a        71     0     5     1    11\n  3.0357862618110604E-01 a        72     0     5     1    12\n -1.8941946770485021E-01 a        73     0     5     1    13\n -8.3456361917446611E-02 a        74     0     5     1    14\n  2.4760660874546270E-01 a        75     0     5     1    15\n  3.7755699449612229E-01 a        76     0     6     1     1\n -2.9706723552650660E-01 a        77     0     6     1     2\n  3.0191127515955163E-01 a        78     0     6     1     3\n  1.8791298878813964E-02 a        79     0     6     1     4\n -1.1270356486783028E-02 a        80     0     6     1     5\n -2.7910823461433504E-01 a        81     0     6     1     6\n  7.9203820480067910E-02 a        82     0     6     1     7\n -4.7232516676605343E-02 a        83     0     6     1     8\n  1.8701204229529447E-01 a        84     0     6     1     9\n  5.0067302144749025E-04 a        85     0     6     1    10\n -3.3014044918247276E-01 a        86     0     6     1    11\n -2.8547591939057410E-01 a        87     0     6     1    12\n -1.3141344856126819E-01 a        88     0     6     1    13\n -4.2893834378255218E-02 a        89     0     6     1    14\n  1.9570050433936528E-01 a        90     0     6     1    15\n -3.3247980291462337E-01 a        91     0     7     1     1\n -3.6153517858512701E-01 a        92     0     7     1     2\n  2.7237178194262385E-01 a        93     0     7     1     3\n -1.6001495112123626E-01 a        94     0     7     1     4\n  3.4264627483884880E-01 a        95     0     7     1     5\n  2.3437927116393589E-01 a        96     0     7     1     6\n  7.8678786165833958E-02 a        97     0     7     1     7\n -8.4918012688162889E-02 a        98     0     7     1     8\n -4.0836752108514070E-02 a        99     0     7     1     9\n -1.1422281558983370E-01 a       100     0     7     1    10\n -3.6210695048898606E-01 a       101     0     7     1    11\n  3.6376053520002954E-01 a       102     0     7     1    12\n -3.6086662812954529E-01 a       103     0     7     1    13\n  3.3338044855085858E-01 a       104     0     7     1    14\n -3.5407504954969976E-01 a       105     0     7     1    15\n  2.8464582105961883E-01 a       106     0     8     1     1\n  2.9395114113613624E-01 a       107     0     8     1     2\n -3.2093182340148652E-01 a       108     0     8     1     3\n -3.0139526822362123E-01 a       109     0     8     1     4\n -2.2640944266521862E-01 a       110     0     8     1     5\n -1.5649485596304541E-01 a       111     0     8     1     6\n  2.7126538130896927E-01 a       112     0     8     1     7\n -6.4568581568645755E-02 a       113     0     8     1     8\n  3.1451083927422208E-01 a       114     0     8     1     9\n -5.6845488801374355E-02 a       115     0     8     1    10\n  3.4119393179635871E-01 a       116     0     8     1    11\n -1.2650115312683691E-01 a       117     0     8     1    12\n  2.7518830202133188E-01 a       118     0     8     1    13\n  3.0752980859020002E-01 a       119     0     8     1    14\n -3.1265069288846181E-01 a       120     0     8     1    15\n -2.0394961107595638E-01 a       121     0     9     1     1\n  2.1353201490775420E-01 a       122     0     9     1     2\n  9.8460916136164436E-02 a       123     0     9     1     3\n -1.1658592775711316E-01 a       124     0     9     1     4\n -2.3135941277075914E-01 a       125     0     9     1     5\n  9.6104777018198861E-02 a       126     0     9     1     6\n  1.7639588076902909E-02 a       127     0     9     1     7\n -5.2828401076185569E-02 a       128     0     9     1     8\n  3.2296763606599788E-01 a       129     0     9     1     9\n -3.5702298020343234E-02 a       130     0     9     1    10\n  1.2793309027042790E-01 a       131     0     9     1    11\n -2.5239421501861553E-01 a       132     0     9     1    12\n -3.4865127279245384E-01 a       133     0     9     1    13\n -3.5719949006152840E-01 a       134     0     9     1    14\n -3.1271656738312481E-01 a       135     0     9     1    15\n -9.4099754426127349E-02 a       136     0    10     1     1\n  9.3743735278202747E-02 a       137     0    10     1     2\n -3.1722289914101620E-01 a       138     0    10     1     3\n -4.5332815142230753E-02 a       139     0    10     1     4\n  6.0838989955815687E-02 a       140     0    10     1     5\n  6.8812437389474276E-02 a       141     0    10     1     6\n  1.6246117403864366E-01 a       142     0    10     1     7\n  3.0255075284275218E-01 a       143     0    10     1     8\n 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  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3_norm-force/input.data",
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-0.003918404\natom    18.029065889    5.395499049   22.331535573   O   -0.232616100    0.000000000   -0.022435825   -0.041986031    0.019777229\natom    18.450206642    6.009076358   20.698998634   H    0.117402890    0.000000000    0.010969888    0.018577415   -0.028888712\natom    18.471749528    6.543217109   23.632648433   H    0.122965160    0.000000000    0.008555544    0.023492454    0.010076612\natom     9.730995489   -0.013755322   18.655527357   O   -0.260468440    0.000000000    0.033447936   -0.047525024   -0.017241120\natom    10.958809623    1.192342071   19.181358978   H    0.127148600    0.000000000    0.001410520    0.021472916    0.006833322\natom     8.059414903    0.566851923   18.625879432   H    0.119766210    0.000000000   -0.033795515    0.025211959    0.007633086\natom     5.720611440   23.314163314    9.722983047   O   -0.231630130    0.000000000    0.008590611   -0.010936445   -0.025443175\natom     6.834575199    0.786704638    9.364550991   H    0.130111070    0.000000000   -0.010659177   -0.018642575    0.001906309\natom     6.037573440   21.935577321    8.393439246   H    0.130229060    0.000000000   -0.004288229    0.030206013    0.023949980\natom     9.845218141   19.848952241    1.377688373   O   -0.231982490    0.000000000    0.047210910    0.050634028    0.057109462\natom     8.964032828   21.443191975    1.821177035   H    0.130585310    0.000000000   -0.001359815   -0.006723989   -0.005653620\natom     8.864534929   18.936979498    0.325325931   H    0.140456380    0.000000000   -0.053312141   -0.042279623   -0.051814244\natom    21.486183262    2.087957338   12.058619328   O   -0.245742770    0.000000000   -0.018336922    0.012948985   -0.040170727\natom    20.067351756    2.869512469   10.984447548   H    0.132828300    0.000000000    0.028333925   -0.013530492    0.030219120\natom    22.734213694    1.753487019   10.673217090   H    0.099760430    0.000000000   -0.005192035    0.002432708    0.011480438\natom    -0.218456207   22.514791837    3.828822870   O   -0.233891290    0.000000000    0.001999487    0.001056955    0.002002219\natom    22.977963895   23.403316849    2.478210504   H    0.123135500    0.000000000   -0.006368839    0.004516237   -0.013166446\natom     0.169763614   -0.170292738    5.058420906   H    0.104258450    0.000000000    0.006641123   -0.000339229    0.001710832\natom    22.768355390   15.179884991   22.329029795   O   -0.238086150    0.000000000   -0.046086010   -0.025235881    0.005743850\natom    21.434125066   15.631748923   -0.333185305   H    0.126220700    0.000000000    0.031123799   -0.009001222   -0.035124767\natom    21.989842718   13.702640137   21.289668674   H    0.119659510    0.000000000    0.013004599    0.035317132    0.026225131\natom    12.222509671    8.189955346    1.618074860   O   -0.247919730    0.000000000   -0.001797123    0.017574523   -0.067071366\natom    12.278849988    7.760085945    3.281828197   H    0.111233780    0.000000000   -0.004235384   -0.012471568    0.070548691\natom    13.880380289    7.710926590    1.035681823   H    0.141482170    0.000000000    0.006536703    0.000642119   -0.006764662\natom    13.661907075   10.667631057   11.112100488   O   -0.216001700    0.000000000   -0.037279496   -0.013776615    0.034916697\natom    14.124858034   12.345145386   11.672595370   H    0.133272180    0.000000000    0.003591734    0.013021971    0.000895419\natom    12.435880622   10.173618657   12.581225186   H    0.147421220    0.000000000    0.029632111    0.008032176   -0.031477484\natom    17.486330661   17.032057327    9.295375649   O   -0.235087510    0.000000000   -0.006875504   -0.012809861   -0.043019615\natom    16.911783770   16.107704983    7.688512539   H    0.110665490    0.000000000    0.006713966    0.011433370    0.028267991\natom    18.328113278   18.516190235    8.528021815   H    0.118898150    0.000000000   -0.000175840   -0.004542786    0.012591957\natom     4.935770073   18.663509563    6.368200054   O   -0.194094220    0.000000000    0.031139053   -0.066276697    0.021098669\natom     6.518835853   17.598527525    5.812888693   H    0.156894820    0.000000000   -0.042755679    0.033516151    0.011475343\natom     4.178872098   17.417123193    7.699892475   H    0.137280880    0.000000000    0.015711127    0.037753788   -0.030393813\natom    21.151675148   20.879473220    7.686178727   O   -0.248140030    0.000000000   -0.009994913   -0.003084252    0.015181890\natom    21.725161902   21.081677775    5.962589077   H    0.096696550    0.000000000    0.004375907    0.001697312   -0.018251199\natom    22.673568579   21.355735416    8.583993635   H    0.139564520    0.000000000   -0.002909430   -0.001404868    0.006677838\natom    19.507253717   12.301401988   18.501302967   O   -0.199717660    0.000000000   -0.028410932   -0.035128726    0.043667183\natom    19.776549245   13.758948329   17.594513745   H    0.142371980    0.000000000    0.012693146    0.047711282   -0.031771675\natom    17.867647309   12.681150163   19.378767407   H    0.141514070    0.000000000    0.014688099   -0.002133776   -0.011109509\natom    23.134797998   17.370023640   17.326635511   O   -0.251377170    0.000000000   -0.000268730   -0.000574628   -0.003573364\natom    23.309537263   17.766571487   19.122904057   H    0.118237060    0.000000000    0.005638293   -0.001455468   -0.001185792\natom     0.463480083   18.316502796   16.477809882   H    0.138644360    0.000000000   -0.009964426   -0.001923402    0.004419419\natom     7.198349513    9.467121587   20.207068712   O   -0.243428280    0.000000000    0.009787410   -0.009154114    0.016239349\natom     7.841261053    8.491977165   21.715395794   H    0.127971510    0.000000000   -0.015877818    0.012471507   -0.019846659\natom     5.641732350   10.325405299   20.696485297   H    0.130413120    0.000000000    0.003877775    0.000013170    0.004937889\nenergy   -4900.14395256\ncharge         0.0000000000\n end\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3_norm-force/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\natom_energy                     H -0.45890771  # Free atom reference energy (H).\natom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          2              # Number of training epochs.\nnormalize_data_set              force          # Normalize data set prior to training (ref = via ref. data, force = via force prediction, stats-only = use existing).\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    1.0            # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\n#short_force_fraction            0.0041         # Fraction of force updates per epoch.\nforce_energy_ratio              3.0            # Specifies ratio between force and energy updates (ratio = updates_force / updates_energy).\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/nnp-train/H2O_RPBE-D3_norm-force/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.3221693617312411E+00   2.6431829268494309E+00   2.1712109289368211E+00   1.8491740949754865E-01\n         1          2   8.8165507590121150E-01   1.5021513119899590E+00   1.2778122580628937E+00   9.2610524821423193E-02\n         1          3   9.5063170525557483E-01   1.9645434630136041E+00   1.5754555245780282E+00   1.4788592306892495E-01\n         1          4   6.8720926352748557E-01   1.1734596705047000E+00   9.8013669175527418E-01   7.3842159315803318E-02\n         1          5   5.3114680346458376E-01   1.1735104787393884E+00   8.6903918776136291E-01   9.7965057245763557E-02\n         1          6   4.5446803146192011E-01   7.7208808607104440E-01   6.2874675223192622E-01   4.9613886357228562E-02\n         1          7   2.7732917100342269E-01   6.5610689623748530E-01   4.3632718893459976E-01   5.9842739811322473E-02\n         1          8   3.0248121122588545E-01   5.0262343273858556E-01   4.1296646104933438E-01   3.3605991719978266E-02\n         1          9   2.7091763975787958E-01   4.3771867263061898E-01   3.5532262189207031E-01   3.0837550827151866E-02\n         1         10   3.0607810460301704E-01   8.2737294952385632E-01   5.1367846789526717E-01   8.2396345907449139E-02\n         1         11   1.6781481618321603E-01   3.3262544522941584E-01   2.6405877879038225E-01   2.0079773509946830E-02\n         1         12   1.5199899860595487E-01   5.1758403256923147E-01   2.8216876544103786E-01   5.3030699298770759E-02\n         1         13   7.9964213161399539E-02   2.7810985736196053E-01   1.8323412046338658E-01   2.0256908897343304E-02\n         1         14   5.0022559628496853E-02   3.1251552588862541E-01   1.4532438879262641E-01   3.5408976290196639E-02\n         1         15   1.0972758958750323E-02   1.9780403448379363E-01   7.5743125451543408E-02   2.0368083851198718E-02\n         1         16   4.0564819222288929E-03   2.0020915524049140E-01   4.5553334901545346E-02   2.6816652873187446E-02\n         1         17   1.6392409428096447E-03   2.9517020055424961E-02   1.6279759210012987E-02   5.1720047323677923E-03\n         1         18   5.9064708278282335E-03   2.9881994921192988E-02   1.8893635227048098E-02   3.4996722469230767E-03\n         1         19   1.8153163715731997E-03   3.2340440598797260E-02   1.5251396366744187E-02   4.9976078942981228E-03\n         1         20   7.7218851587917817E-02   1.9164313445186615E-01   1.3079740560426881E-01   1.8047175980621721E-02\n         1         21   6.4007973804529085E-03   3.4352270791092009E-02   1.6008839167468644E-02   4.4985079286083869E-03\n         1         22   7.1919475628770427E-04   1.1394644806220967E-02   5.5243272719661379E-03   2.1112600852613100E-03\n         1         23   4.6183461439172707E-02   1.1842669503328147E-01   7.3672710889966644E-02   1.1140003788632082E-02\n         1         24   9.1433846516636246E-04   7.2448079200631453E-03   3.4708660085473373E-03   1.0041987311934573E-03\n         1         25   1.1212823920457925E-03   7.4909848911080303E-03   3.3413578741542951E-03   9.5694251844215597E-04\n         1         26   1.4490733031593294E-02   3.4896169686888266E-02   2.2593555563529325E-02   3.2185820632296114E-03\n         1         27   6.2962266934873338E-04   5.1814478231837560E-03   2.0022000098156752E-03   6.1375837903328550E-04\n         2          1   1.7278003594190612E+00   3.0200705624254782E+00   2.5556245161257864E+00   1.8104733161286587E-01\n         2          2   5.2830234917918673E-01   1.1347830825159733E+00   9.1702802710027076E-01   8.9012140951749405E-02\n         2          3   1.3413913725634967E+00   2.3281910061725970E+00   1.9602733835105492E+00   1.4178250890732702E-01\n         2          4   3.3973454632955868E-01   7.9106176901817504E-01   6.2374175167509027E-01   6.7920469352681950E-02\n         2          5   9.1198642957067100E-01   1.5175524019444977E+00   1.2574935044638531E+00   9.0840547884065884E-02\n         2          6   1.4007970492770014E-01   3.9737354984873224E-01   2.8710959644163986E-01   3.9568021301260234E-02\n         2          7   6.6026020925081808E-01   9.9631802932099356E-01   8.2593292209866853E-01   5.6260988440501335E-02\n         2          8   4.2701723604415549E-02   1.5473052305514301E-01   1.0198348350484386E-01   1.9093898225897559E-02\n         2          9   5.9779238984500482E-01   8.7214154955749057E-01   7.1064524378414085E-01   4.5991882003602061E-02\n         2         10   1.9985378144803514E-01   6.5655897218566894E-01   4.4271239561305453E-01   7.3593849758180452E-02\n         2         11   4.1502563461045067E-01   6.5057595299175830E-01   5.2811755758076440E-01   2.9733597901087361E-02\n         2         12   1.0539027020125716E-01   4.7399188573233930E-01   2.8778725245738251E-01   6.7239561345988727E-02\n         2         13   2.4956202107947600E-01   4.9952217805446975E-01   3.6646824092677327E-01   2.9672553474082333E-02\n         2         14   3.1300696765894295E-02   3.1614843646709484E-01   1.5249418366539025E-01   5.4780305337940489E-02\n         2         15   6.3223700189372165E-02   3.0994899667375020E-01   1.5148625090308679E-01   2.9292310574299443E-02\n         2         16   8.5041679154014842E-04   1.3041346013164093E-01   3.7068123760173058E-02   2.4399391242546552E-02\n         2         17   4.4317519796445081E-03   2.5144073105818975E-02   1.3864844737089635E-02   3.2528315804001926E-03\n         2         18   8.1860993427251071E-05   1.3466045085857874E-03   5.5084028256248212E-04   2.3430301127519475E-04\n         2         19   7.9083037432116490E-02   2.5796793485264985E-01   1.7694123779133991E-01   2.7939522253685803E-02\n         2         20   2.1441033279915650E-03   1.4776262369620617E-02   8.7339425459512163E-03   2.1168859996502751E-03\n         2         21   1.3804891348827978E-02   4.9194759330688440E-02   2.8874387893367045E-02   5.8165890736636416E-03\n         2         22   2.6051407335652452E-02   1.0496356106048180E-01   6.4565049831895718E-02   1.2764836900154985E-02\n         2         23   2.9045826947719750E-02   7.2380719406296798E-02   4.5302566117440039E-02   7.3746817680981859E-03\n         2         24   1.3607528794234713E-03   1.0984596811105142E-02   5.4354345893373179E-03   1.6123179093972310E-03\n         2         25   1.6511705563216422E-05   5.2501188368496877E-04   1.8911718281856260E-04   8.6408752300015161E-05\n         2         26   2.0072212589651677E-02   7.6648328811296088E-02   4.4378983939995231E-02   8.7718911463090226E-03\n         2         27   1.0836132444402223E-02   5.4980675069752655E-02   3.0545338532716584E-02   7.5167668082524765E-03\n         2         28   6.2351340984659318E-05   1.4410461325923972E-03   5.3991094439800945E-04   2.2577401100509146E-04\n         2         29   8.4843170594598311E-03   2.6368291824445372E-02   1.5321153812859305E-02   2.3405182276765900E-03\n         2         30   4.2231192236936999E-03   1.8846153205016307E-02   1.0613759624824323E-02   2.2975215777576064E-03\n"
  },
  {
    "path": "examples/nnp-train/LJ/input.data",
    "content": "begin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.38564065E+01  -1.38564065E+01  -1.38564065E+01\natom   5.77350269E-01   5.77350269E-01   5.77350269E-01 Ne   0.00000000E+00   0.00000000E+00   1.38564065E+01   1.38564065E+01   1.38564065E+01\nenergy   0.00000000E+00\ncomment r =   1.00000000E+00, E =   0.00000000E+00, dEdr =  -2.40000000E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.14260918E+01  -1.14260918E+01  -1.14260918E+01\natom   5.83123772E-01   5.83123772E-01   5.83123772E-01 Ne   0.00000000E+00   0.00000000E+00   1.14260918E+01   1.14260918E+01   1.14260918E+01\nenergy  -2.18384040E-01\ncomment r =   1.01000000E+00, E =  -2.18384040E-01, dEdr =  -1.97905715E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -9.36007007E+00  -9.36007007E+00  -9.36007007E+00\natom   5.88897275E-01   5.88897275E-01   5.88897275E-01 Ne   0.00000000E+00   0.00000000E+00   9.36007007E+00   9.36007007E+00   9.36007007E+00\nenergy  -3.97912826E-01\ncomment r =   1.02000000E+00, E =  -3.97912826E-01, dEdr =  -1.62121169E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -7.60455062E+00  -7.60455062E+00  -7.60455062E+00\natom   5.94670777E-01   5.94670777E-01   5.94670777E-01 Ne   0.00000000E+00   0.00000000E+00   7.60455062E+00   7.60455062E+00   7.60455062E+00\nenergy  -5.44417506E-01\ncomment r =   1.03000000E+00, E =  -5.44417506E-01, dEdr =  -1.31714680E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -6.11386720E+00  -6.11386720E+00  -6.11386720E+00\natom   6.00444280E-01   6.00444280E-01   6.00444280E-01 Ne   0.00000000E+00   0.00000000E+00   6.11386720E+00   6.11386720E+00   6.11386720E+00\nenergy  -6.62869905E-01\ncomment r =   1.04000000E+00, E =  -6.62869905E-01, dEdr =  -1.05895286E+01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -4.84920700E+00  -4.84920700E+00  -4.84920700E+00\natom   6.06217783E-01   6.06217783E-01   6.06217783E-01 Ne   0.00000000E+00   0.00000000E+00   4.84920700E+00   4.84920700E+00   4.84920700E+00\nenergy  -7.57511914E-01\ncomment r =   1.05000000E+00, E =  -7.57511914E-01, dEdr =  -8.39907291E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -3.77754643E+00  -3.77754643E+00  -3.77754643E+00\natom   6.11991285E-01   6.11991285E-01   6.11991285E-01 Ne   0.00000000E+00   0.00000000E+00   3.77754643E+00   3.77754643E+00   3.77754643E+00\nenergy  -8.31964707E-01\ncomment r =   1.06000000E+00, E =  -8.31964707E-01, dEdr =  -6.54290234E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -2.87075857E+00  -2.87075857E+00  -2.87075857E+00\natom   6.17764788E-01   6.17764788E-01   6.17764788E-01 Ne   0.00000000E+00   0.00000000E+00   2.87075857E+00   2.87075857E+00   2.87075857E+00\nenergy  -8.89321058E-01\ncomment r =   1.07000000E+00, E =  -8.89321058E-01, dEdr =  -4.97229969E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -2.10486372E+00  -2.10486372E+00  -2.10486372E+00\natom   6.23538291E-01   6.23538291E-01   6.23538291E-01 Ne   0.00000000E+00   0.00000000E+00   2.10486372E+00   2.10486372E+00   2.10486372E+00\nenergy  -9.32223473E-01\ncomment r =   1.08000000E+00, E =  -9.32223473E-01, dEdr =  -3.64573090E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -1.45939898E+00  -1.45939898E+00  -1.45939898E+00\natom   6.29311793E-01   6.29311793E-01   6.29311793E-01 Ne   0.00000000E+00   0.00000000E+00   1.45939898E+00   1.45939898E+00   1.45939898E+00\nenergy  -9.62930407E-01\ncomment r =   1.09000000E+00, E =  -9.62930407E-01, dEdr =  -2.52775317E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -9.16887301E-01  -9.16887301E-01  -9.16887301E-01\natom   6.35085296E-01   6.35085296E-01   6.35085296E-01 Ne   0.00000000E+00   0.00000000E+00   9.16887301E-01   9.16887301E-01   9.16887301E-01\nenergy  -9.83372449E-01\ncomment r =   1.10000000E+00, E =  -9.83372449E-01, dEdr =  -1.58809539E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -4.62389671E-01  -4.62389671E-01  -4.62389671E-01\natom   6.40858799E-01   6.40858799E-01   6.40858799E-01 Ne   0.00000000E+00   0.00000000E+00   4.62389671E-01   4.62389671E-01   4.62389671E-01\nenergy  -9.95200050E-01\ncomment r =   1.11000000E+00, E =  -9.95200050E-01, dEdr =  -8.00882403E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00  -8.31268676E-02  -8.31268676E-02  -8.31268676E-02\natom   6.46632301E-01   6.46632301E-01   6.46632301E-01 Ne   0.00000000E+00   0.00000000E+00   8.31268676E-02   8.31268676E-02   8.31268676E-02\nenergy  -9.99824113E-01\ncomment r =   1.12000000E+00, E =  -9.99824113E-01, dEdr =  -1.43979958E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.31840388E-01   2.31840388E-01   2.31840388E-01\natom   6.52405804E-01   6.52405804E-01   6.52405804E-01 Ne   0.00000000E+00   0.00000000E+00  -2.31840388E-01  -2.31840388E-01  -2.31840388E-01\nenergy  -9.98450559E-01\ncomment r =   1.13000000E+00, E =  -9.98450559E-01, dEdr =   4.01559331E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.91882287E-01   4.91882287E-01   4.91882287E-01\natom   6.58179307E-01   6.58179307E-01   6.58179307E-01 Ne   0.00000000E+00   0.00000000E+00  -4.91882287E-01  -4.91882287E-01  -4.91882287E-01\nenergy  -9.92109781E-01\ncomment r =   1.14000000E+00, E =  -9.92109781E-01, dEdr =   8.51965112E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.05029571E-01   7.05029571E-01   7.05029571E-01\natom   6.63952810E-01   6.63952810E-01   6.63952810E-01 Ne   0.00000000E+00   0.00000000E+00  -7.05029571E-01  -7.05029571E-01  -7.05029571E-01\nenergy  -9.81681783E-01\ncomment r =   1.15000000E+00, E =  -9.81681783E-01, dEdr =   1.22114704E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.78168464E-01   8.78168464E-01   8.78168464E-01\natom   6.69726312E-01   6.69726312E-01   6.69726312E-01 Ne   0.00000000E+00   0.00000000E+00  -8.78168464E-01  -8.78168464E-01  -8.78168464E-01\nenergy  -9.67917641E-01\ncomment r =   1.16000000E+00, E =  -9.67917641E-01, dEdr =   1.52103240E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.01720634E+00   1.01720634E+00   1.01720634E+00\natom   6.75499815E-01   6.75499815E-01   6.75499815E-01 Ne   0.00000000E+00   0.00000000E+00  -1.01720634E+00  -1.01720634E+00  -1.01720634E+00\nenergy  -9.51457857E-01\ncomment r =   1.17000000E+00, E =  -9.51457857E-01, dEdr =   1.76185306E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.12721266E+00   1.12721266E+00   1.12721266E+00\natom   6.81273318E-01   6.81273318E-01   6.81273318E-01 Ne   0.00000000E+00   0.00000000E+00  -1.12721266E+00  -1.12721266E+00  -1.12721266E+00\nenergy  -9.32848056E-01\ncomment r =   1.18000000E+00, E =  -9.32848056E-01, dEdr =   1.95238960E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.21253907E+00   1.21253907E+00   1.21253907E+00\natom   6.87046820E-01   6.87046820E-01   6.87046820E-01 Ne   0.00000000E+00   0.00000000E+00  -1.21253907E+00  -1.21253907E+00  -1.21253907E+00\nenergy  -9.12552436E-01\ncomment r =   1.19000000E+00, E =  -9.12552436E-01, dEdr =   2.10017928E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.27692175E+00   1.27692175E+00   1.27692175E+00\natom   6.92820323E-01   6.92820323E-01   6.92820323E-01 Ne   0.00000000E+00   0.00000000E+00  -1.27692175E+00  -1.27692175E+00  -1.27692175E+00\nenergy  -8.90965288E-01\ncomment r =   1.20000000E+00, E =  -8.90965288E-01, dEdr =   2.21169334E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.32356877E+00   1.32356877E+00   1.32356877E+00\natom   6.98593826E-01   6.98593826E-01   6.98593826E-01 Ne   0.00000000E+00   0.00000000E+00  -1.32356877E+00  -1.32356877E+00  -1.32356877E+00\nenergy  -8.68420879E-01\ncomment r =   1.21000000E+00, E =  -8.68420879E-01, dEdr =   2.29248836E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.35523484E+00   1.35523484E+00   1.35523484E+00\natom   7.04367328E-01   7.04367328E-01   7.04367328E-01 Ne   0.00000000E+00   0.00000000E+00  -1.35523484E+00  -1.35523484E+00  -1.35523484E+00\nenergy  -8.45201938E-01\ncomment r =   1.22000000E+00, E =  -8.45201938E-01, dEdr =   2.34733561E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.37428509E+00   1.37428509E+00   1.37428509E+00\natom   7.10140831E-01   7.10140831E-01   7.10140831E-01 Ne   0.00000000E+00   0.00000000E+00  -1.37428509E+00  -1.37428509E+00  -1.37428509E+00\nenergy  -8.21546940E-01\ncomment r =   1.23000000E+00, E =  -8.21546940E-01, dEdr =   2.38033160E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38274975E+00   1.38274975E+00   1.38274975E+00\natom   7.15914334E-01   7.15914334E-01   7.15914334E-01 Ne   0.00000000E+00   0.00000000E+00  -1.38274975E+00  -1.38274975E+00  -1.38274975E+00\nenergy  -7.97656367E-01\ncomment r =   1.24000000E+00, E =  -7.97656367E-01, dEdr =   2.39499283E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38237105E+00   1.38237105E+00   1.38237105E+00\natom   7.21687836E-01   7.21687836E-01   7.21687836E-01 Ne   0.00000000E+00   0.00000000E+00  -1.38237105E+00  -1.38237105E+00  -1.38237105E+00\nenergy  -7.73698093E-01\ncomment r =   1.25000000E+00, E =  -7.73698093E-01, dEdr =   2.39433689E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.37464330E+00   1.37464330E+00   1.37464330E+00\natom   7.27461339E-01   7.27461339E-01   7.27461339E-01 Ne   0.00000000E+00   0.00000000E+00  -1.37464330E+00  -1.37464330E+00  -1.37464330E+00\nenergy  -7.49812018E-01\ncomment r =   1.26000000E+00, E =  -7.49812018E-01, dEdr =   2.38095204E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.36084745E+00   1.36084745E+00   1.36084745E+00\natom   7.33234842E-01   7.33234842E-01   7.33234842E-01 Ne   0.00000000E+00   0.00000000E+00  -1.36084745E+00  -1.36084745E+00  -1.36084745E+00\nenergy  -7.26114051E-01\ncomment r =   1.27000000E+00, E =  -7.26114051E-01, dEdr =   2.35705692E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.34208064E+00   1.34208064E+00   1.34208064E+00\natom   7.39008345E-01   7.39008345E-01   7.39008345E-01 Ne   0.00000000E+00   0.00000000E+00  -1.34208064E+00  -1.34208064E+00  -1.34208064E+00\nenergy  -7.02699549E-01\ncomment r =   1.28000000E+00, E =  -7.02699549E-01, dEdr =   2.32455185E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.31928169E+00   1.31928169E+00   1.31928169E+00\natom   7.44781847E-01   7.44781847E-01   7.44781847E-01 Ne   0.00000000E+00   0.00000000E+00  -1.31928169E+00  -1.31928169E+00  -1.31928169E+00\nenergy  -6.79646267E-01\ncomment r =   1.29000000E+00, E =  -6.79646267E-01, dEdr =   2.28506292E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.29325302E+00   1.29325302E+00   1.29325302E+00\natom   7.50555350E-01   7.50555350E-01   7.50555350E-01 Ne   0.00000000E+00   0.00000000E+00  -1.29325302E+00  -1.29325302E+00  -1.29325302E+00\nenergy  -6.57016914E-01\ncomment r =   1.30000000E+00, E =  -6.57016914E-01, dEdr =   2.23997993E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.26467942E+00   1.26467942E+00   1.26467942E+00\natom   7.56328853E-01   7.56328853E-01   7.56328853E-01 Ne   0.00000000E+00   0.00000000E+00  -1.26467942E+00  -1.26467942E+00  -1.26467942E+00\nenergy  -6.34861342E-01\ncomment r =   1.31000000E+00, E =  -6.34861342E-01, dEdr =   2.19048901E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.23414440E+00   1.23414440E+00   1.23414440E+00\natom   7.62102355E-01   7.62102355E-01   7.62102355E-01 Ne   0.00000000E+00   0.00000000E+00  -1.23414440E+00  -1.23414440E+00  -1.23414440E+00\nenergy  -6.13218442E-01\ncomment r =   1.32000000E+00, E =  -6.13218442E-01, dEdr =   2.13760080E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.20214407E+00   1.20214407E+00   1.20214407E+00\natom   7.67875858E-01   7.67875858E-01   7.67875858E-01 Ne   0.00000000E+00   0.00000000E+00  -1.20214407E+00  -1.20214407E+00  -1.20214407E+00\nenergy  -5.92117772E-01\ncomment r =   1.33000000E+00, E =  -5.92117772E-01, dEdr =   2.08217461E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.16909931E+00   1.16909931E+00   1.16909931E+00\natom   7.73649361E-01   7.73649361E-01   7.73649361E-01 Ne   0.00000000E+00   0.00000000E+00  -1.16909931E+00  -1.16909931E+00  -1.16909931E+00\nenergy  -5.71580967E-01\ncomment r =   1.34000000E+00, E =  -5.71580967E-01, dEdr =   2.02493940E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.13536610E+00   1.13536610E+00   1.13536610E+00\natom   7.79422863E-01   7.79422863E-01   7.79422863E-01 Ne   0.00000000E+00   0.00000000E+00  -1.13536610E+00  -1.13536610E+00  -1.13536610E+00\nenergy  -5.51622948E-01\ncomment r =   1.35000000E+00, E =  -5.51622948E-01, dEdr =   1.96651177E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.10124456E+00   1.10124456E+00   1.10124456E+00\natom   7.85196366E-01   7.85196366E-01   7.85196366E-01 Ne   0.00000000E+00   0.00000000E+00  -1.10124456E+00  -1.10124456E+00  -1.10124456E+00\nenergy  -5.32252964E-01\ncomment r =   1.36000000E+00, E =  -5.32252964E-01, dEdr =   1.90741154E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.06698669E+00   1.06698669E+00   1.06698669E+00\natom   7.90969869E-01   7.90969869E-01   7.90969869E-01 Ne   0.00000000E+00   0.00000000E+00  -1.06698669E+00  -1.06698669E+00  -1.06698669E+00\nenergy  -5.13475496E-01\ncomment r =   1.37000000E+00, E =  -5.13475496E-01, dEdr =   1.84807516E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.03280308E+00   1.03280308E+00   1.03280308E+00\natom   7.96743371E-01   7.96743371E-01   7.96743371E-01 Ne   0.00000000E+00   0.00000000E+00  -1.03280308E+00  -1.03280308E+00  -1.03280308E+00\nenergy  -4.95291026E-01\ncomment r =   1.38000000E+00, E =  -4.95291026E-01, dEdr =   1.78886740E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.98868680E-01   9.98868680E-01   9.98868680E-01\natom   8.02516874E-01   8.02516874E-01   8.02516874E-01 Ne   0.00000000E+00   0.00000000E+00  -9.98868680E-01  -9.98868680E-01  -9.98868680E-01\nenergy  -4.77696704E-01\ncomment r =   1.39000000E+00, E =  -4.77696704E-01, dEdr =   1.73009130E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.65327860E-01   9.65327860E-01   9.65327860E-01\natom   8.08290377E-01   8.08290377E-01   8.08290377E-01 Ne   0.00000000E+00   0.00000000E+00  -9.65327860E-01  -9.65327860E-01  -9.65327860E-01\nenergy  -4.60686922E-01\ncomment r =   1.40000000E+00, E =  -4.60686922E-01, dEdr =   1.67199690E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   9.32298690E-01   9.32298690E-01   9.32298690E-01\natom   8.14063880E-01   8.14063880E-01   8.14063880E-01 Ne   0.00000000E+00   0.00000000E+00  -9.32298690E-01  -9.32298690E-01  -9.32298690E-01\nenergy  -4.44253807E-01\ncomment r =   1.41000000E+00, E =  -4.44253807E-01, dEdr =   1.61478870E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.99876705E-01   8.99876705E-01   8.99876705E-01\natom   8.19837382E-01   8.19837382E-01   8.19837382E-01 Ne   0.00000000E+00   0.00000000E+00  -8.99876705E-01  -8.99876705E-01  -8.99876705E-01\nenergy  -4.28387639E-01\ncomment r =   1.42000000E+00, E =  -4.28387639E-01, dEdr =   1.55863217E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.68138141E-01   8.68138141E-01   8.68138141E-01\natom   8.25610885E-01   8.25610885E-01   8.25610885E-01 Ne   0.00000000E+00   0.00000000E+00  -8.68138141E-01  -8.68138141E-01  -8.68138141E-01\nenergy  -4.13077215E-01\ncomment r =   1.43000000E+00, E =  -4.13077215E-01, dEdr =   1.50365937E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.37142729E-01   8.37142729E-01   8.37142729E-01\natom   8.31384388E-01   8.31384388E-01   8.31384388E-01 Ne   0.00000000E+00   0.00000000E+00  -8.37142729E-01  -8.37142729E-01  -8.37142729E-01\nenergy  -3.98310158E-01\ncomment r =   1.44000000E+00, E =  -3.98310158E-01, dEdr =   1.44997374E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   8.06936119E-01   8.06936119E-01   8.06936119E-01\natom   8.37157890E-01   8.37157890E-01   8.37157890E-01 Ne   0.00000000E+00   0.00000000E+00  -8.06936119E-01  -8.06936119E-01  -8.06936119E-01\nenergy  -3.84073184E-01\ncomment r =   1.45000000E+00, E =  -3.84073184E-01, dEdr =   1.39765436E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.77551972E-01   7.77551972E-01   7.77551972E-01\natom   8.42931393E-01   8.42931393E-01   8.42931393E-01 Ne   0.00000000E+00   0.00000000E+00  -7.77551972E-01  -7.77551972E-01  -7.77551972E-01\nenergy  -3.70352321E-01\ncomment r =   1.46000000E+00, E =  -3.70352321E-01, dEdr =   1.34675952E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.49013769E-01   7.49013769E-01   7.49013769E-01\natom   8.48704896E-01   8.48704896E-01   8.48704896E-01 Ne   0.00000000E+00   0.00000000E+00  -7.49013769E-01  -7.49013769E-01  -7.49013769E-01\nenergy  -3.57133107E-01\ncomment r =   1.47000000E+00, E =  -3.57133107E-01, dEdr =   1.29732990E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   7.21336370E-01   7.21336370E-01   7.21336370E-01\natom   8.54478398E-01   8.54478398E-01   8.54478398E-01 Ne   0.00000000E+00   0.00000000E+00  -7.21336370E-01  -7.21336370E-01  -7.21336370E-01\nenergy  -3.44400751E-01\ncomment r =   1.48000000E+00, E =  -3.44400751E-01, dEdr =   1.24939124E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.94527370E-01   6.94527370E-01   6.94527370E-01\natom   8.60251901E-01   8.60251901E-01   8.60251901E-01 Ne   0.00000000E+00   0.00000000E+00  -6.94527370E-01  -6.94527370E-01  -6.94527370E-01\nenergy  -3.32140268E-01\ncomment r =   1.49000000E+00, E =  -3.32140268E-01, dEdr =   1.20295669E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.68588257E-01   6.68588257E-01   6.68588257E-01\natom   8.66025404E-01   8.66025404E-01   8.66025404E-01 Ne   0.00000000E+00   0.00000000E+00  -6.68588257E-01  -6.68588257E-01  -6.68588257E-01\nenergy  -3.20336594E-01\ncomment r =   1.50000000E+00, E =  -3.20336594E-01, dEdr =   1.15802883E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.43515424E-01   6.43515424E-01   6.43515424E-01\natom   8.71798906E-01   8.71798906E-01   8.71798906E-01 Ne   0.00000000E+00   0.00000000E+00  -6.43515424E-01  -6.43515424E-01  -6.43515424E-01\nenergy  -3.08974689E-01\ncomment r =   1.51000000E+00, E =  -3.08974689E-01, dEdr =   1.11460141E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   6.19301030E-01   6.19301030E-01   6.19301030E-01\natom   8.77572409E-01   8.77572409E-01   8.77572409E-01 Ne   0.00000000E+00   0.00000000E+00  -6.19301030E-01  -6.19301030E-01  -6.19301030E-01\nenergy  -2.98039609E-01\ncomment r =   1.52000000E+00, E =  -2.98039609E-01, dEdr =   1.07266085E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.95933747E-01   5.95933747E-01   5.95933747E-01\natom   8.83345912E-01   8.83345912E-01   8.83345912E-01 Ne   0.00000000E+00   0.00000000E+00  -5.95933747E-01  -5.95933747E-01  -5.95933747E-01\nenergy  -2.87516580E-01\ncomment r =   1.53000000E+00, E =  -2.87516580E-01, dEdr =   1.03218753E+00\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.73399404E-01   5.73399404E-01   5.73399404E-01\natom   8.89119415E-01   8.89119415E-01   8.89119415E-01 Ne   0.00000000E+00   0.00000000E+00  -5.73399404E-01  -5.73399404E-01  -5.73399404E-01\nenergy  -2.77391049E-01\ncomment r =   1.54000000E+00, E =  -2.77391049E-01, dEdr =   9.93156900E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.51681534E-01   5.51681534E-01   5.51681534E-01\natom   8.94892917E-01   8.94892917E-01   8.94892917E-01 Ne   0.00000000E+00   0.00000000E+00  -5.51681534E-01  -5.51681534E-01  -5.51681534E-01\nenergy  -2.67648728E-01\ncomment r =   1.55000000E+00, E =  -2.67648728E-01, dEdr =   9.55540446E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.30761850E-01   5.30761850E-01   5.30761850E-01\natom   9.00666420E-01   9.00666420E-01   9.00666420E-01 Ne   0.00000000E+00   0.00000000E+00  -5.30761850E-01  -5.30761850E-01  -5.30761850E-01\nenergy  -2.58275632E-01\ncomment r =   1.56000000E+00, E =  -2.58275632E-01, dEdr =   9.19306492E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   5.10620650E-01   5.10620650E-01   5.10620650E-01\natom   9.06439923E-01   9.06439923E-01   9.06439923E-01 Ne   0.00000000E+00   0.00000000E+00  -5.10620650E-01  -5.10620650E-01  -5.10620650E-01\nenergy  -2.49258104E-01\ncomment r =   1.57000000E+00, E =  -2.49258104E-01, dEdr =   8.84420909E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.91237157E-01   4.91237157E-01   4.91237157E-01\natom   9.12213425E-01   9.12213425E-01   9.12213425E-01 Ne   0.00000000E+00   0.00000000E+00  -4.91237157E-01  -4.91237157E-01  -4.91237157E-01\nenergy  -2.40582839E-01\ncomment r =   1.58000000E+00, E =  -2.40582839E-01, dEdr =   8.50847714E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.72589820E-01   4.72589820E-01   4.72589820E-01\natom   9.17986928E-01   9.17986928E-01   9.17986928E-01 Ne   0.00000000E+00   0.00000000E+00  -4.72589820E-01  -4.72589820E-01  -4.72589820E-01\nenergy  -2.32236899E-01\ncomment r =   1.59000000E+00, E =  -2.32236899E-01, dEdr =   8.18549579E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.54656560E-01   4.54656560E-01   4.54656560E-01\natom   9.23760431E-01   9.23760431E-01   9.23760431E-01 Ne   0.00000000E+00   0.00000000E+00  -4.54656560E-01  -4.54656560E-01  -4.54656560E-01\nenergy  -2.24207724E-01\ncomment r =   1.60000000E+00, E =  -2.24207724E-01, dEdr =   7.87488261E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.37414983E-01   4.37414983E-01   4.37414983E-01\natom   9.29533933E-01   9.29533933E-01   9.29533933E-01 Ne   0.00000000E+00   0.00000000E+00  -4.37414983E-01  -4.37414983E-01  -4.37414983E-01\nenergy  -2.16483140E-01\ncomment r =   1.61000000E+00, E =  -2.16483140E-01, dEdr =   7.57624975E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.20842560E-01   4.20842560E-01   4.20842560E-01\natom   9.35307436E-01   9.35307436E-01   9.35307436E-01 Ne   0.00000000E+00   0.00000000E+00  -4.20842560E-01  -4.20842560E-01  -4.20842560E-01\nenergy  -2.09051362E-01\ncomment r =   1.62000000E+00, E =  -2.09051362E-01, dEdr =   7.28920696E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   4.04916775E-01   4.04916775E-01   4.04916775E-01\natom   9.41080939E-01   9.41080939E-01   9.41080939E-01 Ne   0.00000000E+00   0.00000000E+00  -4.04916775E-01  -4.04916775E-01  -4.04916775E-01\nenergy  -2.01900993E-01\ncomment r =   1.63000000E+00, E =  -2.01900993E-01, dEdr =   7.01336426E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.89615248E-01   3.89615248E-01   3.89615248E-01\natom   9.46854441E-01   9.46854441E-01   9.46854441E-01 Ne   0.00000000E+00   0.00000000E+00  -3.89615248E-01  -3.89615248E-01  -3.89615248E-01\nenergy  -1.95021029E-01\ncomment r =   1.64000000E+00, E =  -1.95021029E-01, dEdr =   6.74833406E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.74915846E-01   3.74915846E-01   3.74915846E-01\natom   9.52627944E-01   9.52627944E-01   9.52627944E-01 Ne   0.00000000E+00   0.00000000E+00  -3.74915846E-01  -3.74915846E-01  -3.74915846E-01\nenergy  -1.88400849E-01\ncomment r =   1.65000000E+00, E =  -1.88400849E-01, dEdr =   6.49373295E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.60796761E-01   3.60796761E-01   3.60796761E-01\natom   9.58401447E-01   9.58401447E-01   9.58401447E-01 Ne   0.00000000E+00   0.00000000E+00  -3.60796761E-01  -3.60796761E-01  -3.60796761E-01\nenergy  -1.82030213E-01\ncomment r =   1.66000000E+00, E =  -1.82030213E-01, dEdr =   6.24918320E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.47236580E-01   3.47236580E-01   3.47236580E-01\natom   9.64174950E-01   9.64174950E-01   9.64174950E-01 Ne   0.00000000E+00   0.00000000E+00  -3.47236580E-01  -3.47236580E-01  -3.47236580E-01\nenergy  -1.75899255E-01\ncomment r =   1.67000000E+00, E =  -1.75899255E-01, dEdr =   6.01431398E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.34214345E-01   3.34214345E-01   3.34214345E-01\natom   9.69948452E-01   9.69948452E-01   9.69948452E-01 Ne   0.00000000E+00   0.00000000E+00  -3.34214345E-01  -3.34214345E-01  -3.34214345E-01\nenergy  -1.69998479E-01\ncomment r =   1.68000000E+00, E =  -1.69998479E-01, dEdr =   5.78876226E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.21709594E-01   3.21709594E-01   3.21709594E-01\natom   9.75721955E-01   9.75721955E-01   9.75721955E-01 Ne   0.00000000E+00   0.00000000E+00  -3.21709594E-01  -3.21709594E-01  -3.21709594E-01\nenergy  -1.64318743E-01\ncomment r =   1.69000000E+00, E =  -1.64318743E-01, dEdr =   5.57217362E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   3.09702395E-01   3.09702395E-01   3.09702395E-01\natom   9.81495458E-01   9.81495458E-01   9.81495458E-01 Ne   0.00000000E+00   0.00000000E+00  -3.09702395E-01  -3.09702395E-01  -3.09702395E-01\nenergy  -1.58851259E-01\ncomment r =   1.70000000E+00, E =  -1.58851259E-01, dEdr =   5.36420284E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.98173372E-01   2.98173372E-01   2.98173372E-01\natom   9.87268960E-01   9.87268960E-01   9.87268960E-01 Ne   0.00000000E+00   0.00000000E+00  -2.98173372E-01  -2.98173372E-01  -2.98173372E-01\nenergy  -1.53587577E-01\ncomment r =   1.71000000E+00, E =  -1.53587577E-01, dEdr =   5.16451429E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.87103720E-01   2.87103720E-01   2.87103720E-01\natom   9.93042463E-01   9.93042463E-01   9.93042463E-01 Ne   0.00000000E+00   0.00000000E+00  -2.87103720E-01  -2.87103720E-01  -2.87103720E-01\nenergy  -1.48519579E-01\ncomment r =   1.72000000E+00, E =  -1.48519579E-01, dEdr =   4.97278230E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.76475222E-01   2.76475222E-01   2.76475222E-01\natom   9.98815966E-01   9.98815966E-01   9.98815966E-01 Ne   0.00000000E+00   0.00000000E+00  -2.76475222E-01  -2.76475222E-01  -2.76475222E-01\nenergy  -1.43639466E-01\ncomment r =   1.73000000E+00, E =  -1.43639466E-01, dEdr =   4.78869131E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.66270250E-01   2.66270250E-01   2.66270250E-01\natom   1.00458947E+00   1.00458947E+00   1.00458947E+00 Ne   0.00000000E+00   0.00000000E+00  -2.66270250E-01  -2.66270250E-01  -2.66270250E-01\nenergy  -1.38939751E-01\ncomment r =   1.74000000E+00, E =  -1.38939751E-01, dEdr =   4.61193602E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.56471773E-01   2.56471773E-01   2.56471773E-01\natom   1.01036297E+00   1.01036297E+00   1.01036297E+00 Ne   0.00000000E+00   0.00000000E+00  -2.56471773E-01  -2.56471773E-01  -2.56471773E-01\nenergy  -1.34413247E-01\ncomment r =   1.75000000E+00, E =  -1.34413247E-01, dEdr =   4.44222142E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.47063348E-01   2.47063348E-01   2.47063348E-01\natom   1.01613647E+00   1.01613647E+00   1.01613647E+00 Ne   0.00000000E+00   0.00000000E+00  -2.47063348E-01  -2.47063348E-01  -2.47063348E-01\nenergy  -1.30053056E-01\ncomment r =   1.76000000E+00, E =  -1.30053056E-01, dEdr =   4.27926272E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.38029122E-01   2.38029122E-01   2.38029122E-01\natom   1.02190998E+00   1.02190998E+00   1.02190998E+00 Ne   0.00000000E+00   0.00000000E+00  -2.38029122E-01  -2.38029122E-01  -2.38029122E-01\nenergy  -1.25852561E-01\ncomment r =   1.77000000E+00, E =  -1.25852561E-01, dEdr =   4.12278533E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.29353819E-01   2.29353819E-01   2.29353819E-01\natom   1.02768348E+00   1.02768348E+00   1.02768348E+00 Ne   0.00000000E+00   0.00000000E+00  -2.29353819E-01  -2.29353819E-01  -2.29353819E-01\nenergy  -1.21805413E-01\ncomment r =   1.78000000E+00, E =  -1.21805413E-01, dEdr =   3.97252467E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.21022735E-01   2.21022735E-01   2.21022735E-01\natom   1.03345698E+00   1.03345698E+00   1.03345698E+00 Ne   0.00000000E+00   0.00000000E+00  -2.21022735E-01  -2.21022735E-01  -2.21022735E-01\nenergy  -1.17905524E-01\ncomment r =   1.79000000E+00, E =  -1.17905524E-01, dEdr =   3.82822607E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.13021724E-01   2.13021724E-01   2.13021724E-01\natom   1.03923048E+00   1.03923048E+00   1.03923048E+00 Ne   0.00000000E+00   0.00000000E+00  -2.13021724E-01  -2.13021724E-01  -2.13021724E-01\nenergy  -1.14147056E-01\ncomment r =   1.80000000E+00, E =  -1.14147056E-01, dEdr =   3.68964449E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   2.05337187E-01   2.05337187E-01   2.05337187E-01\natom   1.04500399E+00   1.04500399E+00   1.04500399E+00 Ne   0.00000000E+00   0.00000000E+00  -2.05337187E-01  -2.05337187E-01  -2.05337187E-01\nenergy  -1.10524408E-01\ncomment r =   1.81000000E+00, E =  -1.10524408E-01, dEdr =   3.55654440E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.97956057E-01   1.97956057E-01   1.97956057E-01\natom   1.05077749E+00   1.05077749E+00   1.05077749E+00 Ne   0.00000000E+00   0.00000000E+00  -1.97956057E-01  -1.97956057E-01  -1.97956057E-01\nenergy  -1.07032215E-01\ncomment r =   1.82000000E+00, E =  -1.07032215E-01, dEdr =   3.42869948E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.90865785E-01   1.90865785E-01   1.90865785E-01\natom   1.05655099E+00   1.05655099E+00   1.05655099E+00 Ne   0.00000000E+00   0.00000000E+00  -1.90865785E-01  -1.90865785E-01  -1.90865785E-01\nenergy  -1.03665330E-01\ncomment r =   1.83000000E+00, E =  -1.03665330E-01, dEdr =   3.30589238E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.84054328E-01   1.84054328E-01   1.84054328E-01\natom   1.06232450E+00   1.06232450E+00   1.06232450E+00 Ne   0.00000000E+00   0.00000000E+00  -1.84054328E-01  -1.84054328E-01  -1.84054328E-01\nenergy  -1.00418821E-01\ncomment r =   1.84000000E+00, E =  -1.00418821E-01, dEdr =   3.18791447E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.77510126E-01   1.77510126E-01   1.77510126E-01\natom   1.06809800E+00   1.06809800E+00   1.06809800E+00 Ne   0.00000000E+00   0.00000000E+00  -1.77510126E-01  -1.77510126E-01  -1.77510126E-01\nenergy  -9.72879584E-02\ncomment r =   1.85000000E+00, E =  -9.72879584E-02, dEdr =   3.07456558E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.71222096E-01   1.71222096E-01   1.71222096E-01\natom   1.07387150E+00   1.07387150E+00   1.07387150E+00 Ne   0.00000000E+00   0.00000000E+00  -1.71222096E-01  -1.71222096E-01  -1.71222096E-01\nenergy  -9.42682107E-02\ncomment r =   1.86000000E+00, E =  -9.42682107E-02, dEdr =   2.96565370E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.65179609E-01   1.65179609E-01   1.65179609E-01\natom   1.07964500E+00   1.07964500E+00   1.07964500E+00 Ne   0.00000000E+00   0.00000000E+00  -1.65179609E-01  -1.65179609E-01  -1.65179609E-01\nenergy  -9.13552334E-02\ncomment r =   1.87000000E+00, E =  -9.13552334E-02, dEdr =   2.86099475E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.59372475E-01   1.59372475E-01   1.59372475E-01\natom   1.08541851E+00   1.08541851E+00   1.08541851E+00 Ne   0.00000000E+00   0.00000000E+00  -1.59372475E-01  -1.59372475E-01  -1.59372475E-01\nenergy  -8.85448625E-02\ncomment r =   1.88000000E+00, E =  -8.85448625E-02, dEdr =   2.76041225E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.53790932E-01   1.53790932E-01   1.53790932E-01\natom   1.09119201E+00   1.09119201E+00   1.09119201E+00 Ne   0.00000000E+00   0.00000000E+00  -1.53790932E-01  -1.53790932E-01  -1.53790932E-01\nenergy  -8.58331065E-02\ncomment r =   1.89000000E+00, E =  -8.58331065E-02, dEdr =   2.66373709E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.48425625E-01   1.48425625E-01   1.48425625E-01\natom   1.09696551E+00   1.09696551E+00   1.09696551E+00 Ne   0.00000000E+00   0.00000000E+00  -1.48425625E-01  -1.48425625E-01  -1.48425625E-01\nenergy  -8.32161399E-02\ncomment r =   1.90000000E+00, E =  -8.32161399E-02, dEdr =   2.57080724E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.43267593E-01   1.43267593E-01   1.43267593E-01\natom   1.10273901E+00   1.10273901E+00   1.10273901E+00 Ne   0.00000000E+00   0.00000000E+00  -1.43267593E-01  -1.43267593E-01  -1.43267593E-01\nenergy  -8.06902954E-02\ncomment r =   1.91000000E+00, E =  -8.06902954E-02, dEdr =   2.48146751E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.38308255E-01   1.38308255E-01   1.38308255E-01\natom   1.10851252E+00   1.10851252E+00   1.10851252E+00 Ne   0.00000000E+00   0.00000000E+00  -1.38308255E-01  -1.38308255E-01  -1.38308255E-01\nenergy  -7.82520578E-02\ncomment r =   1.92000000E+00, E =  -7.82520578E-02, dEdr =   2.39556925E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.33539391E-01   1.33539391E-01   1.33539391E-01\natom   1.11428602E+00   1.11428602E+00   1.11428602E+00 Ne   0.00000000E+00   0.00000000E+00  -1.33539391E-01  -1.33539391E-01  -1.33539391E-01\nenergy  -7.58980573E-02\ncomment r =   1.93000000E+00, E =  -7.58980573E-02, dEdr =   2.31297011E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.28953134E-01   1.28953134E-01   1.28953134E-01\natom   1.12005952E+00   1.12005952E+00   1.12005952E+00 Ne   0.00000000E+00   0.00000000E+00  -1.28953134E-01  -1.28953134E-01  -1.28953134E-01\nenergy  -7.36250634E-02\ncomment r =   1.94000000E+00, E =  -7.36250634E-02, dEdr =   2.23353381E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.24541951E-01   1.24541951E-01   1.24541951E-01\natom   1.12583302E+00   1.12583302E+00   1.12583302E+00 Ne   0.00000000E+00   0.00000000E+00  -1.24541951E-01  -1.24541951E-01  -1.24541951E-01\nenergy  -7.14299790E-02\ncomment r =   1.95000000E+00, E =  -7.14299790E-02, dEdr =   2.15712986E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.20298629E-01   1.20298629E-01   1.20298629E-01\natom   1.13160653E+00   1.13160653E+00   1.13160653E+00 Ne   0.00000000E+00   0.00000000E+00  -1.20298629E-01  -1.20298629E-01  -1.20298629E-01\nenergy  -6.93098346E-02\ncomment r =   1.96000000E+00, E =  -6.93098346E-02, dEdr =   2.08363337E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.16216266E-01   1.16216266E-01   1.16216266E-01\natom   1.13738003E+00   1.13738003E+00   1.13738003E+00 Ne   0.00000000E+00   0.00000000E+00  -1.16216266E-01  -1.16216266E-01  -1.16216266E-01\nenergy  -6.72617830E-02\ncomment r =   1.97000000E+00, E =  -6.72617830E-02, dEdr =   2.01292477E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.12288255E-01   1.12288255E-01   1.12288255E-01\natom   1.14315353E+00   1.14315353E+00   1.14315353E+00 Ne   0.00000000E+00   0.00000000E+00  -1.12288255E-01  -1.12288255E-01  -1.12288255E-01\nenergy  -6.52830939E-02\ncomment r =   1.98000000E+00, E =  -6.52830939E-02, dEdr =   1.94488962E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.08508271E-01   1.08508271E-01   1.08508271E-01\natom   1.14892704E+00   1.14892704E+00   1.14892704E+00 Ne   0.00000000E+00   0.00000000E+00  -1.08508271E-01  -1.08508271E-01  -1.08508271E-01\nenergy  -6.33711491E-02\ncomment r =   1.99000000E+00, E =  -6.33711491E-02, dEdr =   1.87941839E-01\nend\nbegin\natom   0.00000000E+00   0.00000000E+00   0.00000000E+00 Ne   0.00000000E+00   0.00000000E+00   1.04870264E-01   1.04870264E-01   1.04870264E-01\natom   1.15470054E+00   1.15470054E+00   1.15470054E+00 Ne   0.00000000E+00   0.00000000E+00  -1.04870264E-01  -1.04870264E-01  -1.04870264E-01\nenergy  -6.15234375E-02\ncomment r =   2.00000000E+00, E =  -6.15234375E-02, dEdr =   1.81640625E-01\nend\n"
  },
  {
    "path": "examples/nnp-train/LJ/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              1              # Number of elements.\nelements                        Ne             # Specification of elements.\n#atom_energy                     Ne 0.0         # Free atom reference energy (Ne).\ncutoff_type                     2              # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      1              # Number of hidden layers.\nglobal_nodes_short              3              # Number of nodes in each hidden layer.\nglobal_activation_short         t l            # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    1.0            # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.167          # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               RMSEpa         # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# radial Ne Ne\nsymfunction_short Ne 2 Ne 1.000 0.00 3.00\nsymfunction_short Ne 2 Ne 1.000 0.25 3.00\nsymfunction_short Ne 2 Ne 1.000 0.50 3.00\nsymfunction_short Ne 2 Ne 1.000 0.75 3.00\nsymfunction_short Ne 2 Ne 1.000 1.00 3.00\n"
  },
  {
    "path": "examples/nnp-train/LJ/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   6.0871865837434718E-04   7.2815866278251790E-02   1.9093305172662212E-02   2.0241240265275205E-02\n         1          2   1.5544175511327358E-03   1.1277941989452710E-01   3.3134472337730189E-02   3.1972702944828152E-02\n         1          3   3.5029340302491388E-03   1.5415119007009570E-01   5.1275563979636354E-02   4.4402666633939228E-02\n         1          4   6.9664161692094993E-03   1.8594182841625700E-01   7.0845240019947853E-02   5.4073736544960498E-02\n         1          5   1.2226441157255801E-02   1.9793404599765610E-01   8.7507815525083174E-02   5.7502177573987671E-02\n"
  },
  {
    "path": "examples/nnp-train/QM9/input.data",
    "content": "begin\ncomment source_file_name=qm9/dsgdb9nsd_000001.xyz structure_number=1\natom -0.0126981359 1.0858041578 0.0080009958 C -0.535689 0.0 0.0 0.0 0.0\natom 0.002150416 -0.0060313176 0.0019761204 H 0.133921 0.0 0.0 0.0 0.0\natom 1.0117308433 1.4637511618 0.0002765748 H 0.133922 0.0 0.0 0.0 0.0\natom -0.540815069 1.4475266138 -0.8766437152 H 0.133923 0.0 0.0 0.0 0.0\natom -0.5238136345 1.4379326443 0.9063972942 H 0.133923 0.0 0.0 0.0 0.0\nenergy -40.47893\ncharge 0.0\nend\nbegin\ncomment source_file_name=qm9/dsgdb9nsd_001500.xyz structure_number=1500\natom 0.0182788081 1.4024971182 -0.0528273509 C -0.227658 0.0 0.0 0.0 0.0\natom -0.0053264627 -0.0058902362 0.0135796256 O -0.21262 0.0 0.0 0.0 0.0\natom 0.6165060004 -0.608937836 -1.0746697286 C -0.160405 0.0 0.0 0.0 0.0\natom 0.5566077334 -2.1249235866 -0.9416293144 C 0.229621 0.0 0.0 0.0 0.0\natom 0.0396286854 -2.7017209882 -0.016758342 O -0.255181 0.0 0.0 0.0 0.0\natom 1.1892210818 -2.8301355323 -2.0479128687 C 0.248321 0.0 0.0 0.0 0.0\natom 1.7146358394 -3.4031922406 -2.9667001421 C -0.428801 0.0 0.0 0.0 0.0\natom 1.0477068778 1.7933260047 -0.066785698 H 0.108234 0.0 0.0 0.0 0.0\natom -0.5052588574 1.7779083698 -0.9459333321 H 0.108229 0.0 0.0 0.0 0.0\natom -0.4903251948 1.7740600141 0.8390705515 H 0.137777 0.0 0.0 0.0 0.0\natom 0.1435056661 -0.3346848512 -2.0363804517 H 0.117397 0.0 0.0 0.0 0.0\natom 1.680195254 -0.3192247092 -1.1668661886 H 0.117402 0.0 0.0 0.0 0.0\natom 2.1748042983 -3.9242271966 -3.7711600701 H 0.217683 0.0 0.0 0.0 0.0\nenergy -344.41106\ncharge 0.0\nend\nbegin\ncomment source_file_name=qm9/dsgdb9nsd_003108.xyz structure_number=3108\natom 0.0403089664 -1.21485059 -0.0341318697 C -0.419172 0.0 0.0 0.0 0.0\natom 0.0333544303 -0.0107521502 -0.0103170084 C 0.172312 0.0 0.0 0.0 0.0\natom 0.0082994934 1.4098949156 0.0446952892 C 0.22448 0.0 0.0 0.0 0.0\natom 0.277306392 2.2837337811 -1.1626890247 C -0.313035 0.0 0.0 0.0 0.0\natom 1.17637449 2.4293890864 0.024311737 C -0.09492 0.0 0.0 0.0 0.0\natom 0.4920061461 3.2599759442 1.113427492 C -0.221631 0.0 0.0 0.0 0.0\natom -0.6976672966 2.2465425801 1.1313299148 C -0.289075 0.0 0.0 0.0 0.0\natom 0.0479152278 -2.2758792999 -0.0613632941 H 0.183009 0.0 0.0 0.0 0.0\natom 0.7012252939 1.7619299738 -2.0134805184 H 0.125361 0.0 0.0 0.0 0.0\natom -0.4298032851 3.0702385156 -1.4195857441 H 0.108251 0.0 0.0 0.0 0.0\natom 2.236060148 2.2140438585 -0.0362425101 H 0.099439 0.0 0.0 0.0 0.0\natom 1.0401638724 3.2648683722 2.0574615726 H 0.108678 0.0 0.0 0.0 0.0\natom 0.2565469696 4.2939709492 0.8412775756 H 0.099862 0.0 0.0 0.0 0.0\natom -1.6858588789 2.6296647622 0.8586314287 H 0.099318 0.0 0.0 0.0 0.0\natom -0.7754549991 1.7136799612 2.0801725198 H 0.117123 0.0 0.0 0.0 0.0\nenergy -271.323089\ncharge 0.0\nend\nbegin\ncomment source_file_name=qm9/dsgdb9nsd_004466.xyz structure_number=4466\natom 0.1396220836 1.5016932619 0.1086074424 C -0.498887 0.0 0.0 0.0 0.0\natom -0.0446729434 0.0347210783 0.0259566793 C 0.269055 0.0 0.0 0.0 0.0\natom -1.0905779488 -0.8149438212 -0.1392357263 C 0.178399 0.0 0.0 0.0 0.0\natom -2.4445079264 -0.5557432001 -0.3451764546 N -0.598771 0.0 0.0 0.0 0.0\natom -0.6399422628 -2.1370319384 -0.1568136527 N -0.426456 0.0 0.0 0.0 0.0\natom 0.6387609138 -2.0107459182 -0.0040660172 C 0.471261 0.0 0.0 0.0 0.0\natom 1.5554433112 -2.97576681 0.0527131274 O -0.401422 0.0 0.0 0.0 0.0\natom 1.1052803037 -0.7727321834 0.1158712873 O -0.206727 0.0 0.0 0.0 0.0\natom 0.7950256693 1.8819412841 -0.6849728504 H 0.137159 0.0 0.0 0.0 0.0\natom -0.828737223 1.9978074163 -0.0041701579 H 0.126843 0.0 0.0 0.0 0.0\natom 0.5682651583 1.8185976042 1.0678368528 H 0.132386 0.0 0.0 0.0 0.0\natom -2.7760797173 0.2762949088 0.1234173152 H 0.244663 0.0 0.0 0.0 0.0\natom -3.0097685976 -1.3543496684 -0.0883774578 H 0.252544 0.0 0.0 0.0 0.0\natom 1.0825505795 -3.8106937838 -0.0544033774 H 0.319954 0.0 0.0 0.0 0.0\nenergy -415.9009\ncharge 0.0\nend\nbegin\ncomment source_file_name=qm9/dsgdb9nsd_005743.xyz 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-2.4777600861 C -0.028637 0.0 0.0 0.0 0.0\natom 0.6345851602 2.1174961969 0.0143133728 H 0.123364 0.0 0.0 0.0 0.0\natom -0.9043697957 1.7986141185 -0.8120510635 H 0.131299 0.0 0.0 0.0 0.0\natom -0.8280134332 1.811828288 0.9646435117 H 0.106627 0.0 0.0 0.0 0.0\natom 0.6440422743 -0.2018486579 0.9220216246 H 0.068299 0.0 0.0 0.0 0.0\natom -1.7248338281 -0.3974194411 0.8111195536 H 0.283876 0.0 0.0 0.0 0.0\natom 2.9689462123 -0.4779116818 0.5462305326 H 0.139437 0.0 0.0 0.0 0.0\natom 3.8729659535 -1.4823584541 -0.6061660777 H 0.153908 0.0 0.0 0.0 0.0\natom 3.9149367465 0.277721429 -0.7476069978 H 0.150103 0.0 0.0 0.0 0.0\natom -0.851558333 -0.5973433634 -2.7686285342 H 0.13767 0.0 0.0 0.0 0.0\nenergy -439.087841\ncharge 0.0\nend\nbegin\ncomment source_file_name=qm9/dsgdb9nsd_126093.xyz structure_number=126093\natom -0.0367539717 1.6536015286 -0.1978777605 C -0.396886 0.0 0.0 0.0 0.0\natom 0.0193040758 0.147102198 -0.0223549731 C 0.03461 0.0 0.0 0.0 0.0\natom 0.8728716825 -0.4385398213 -1.0008681305 O -0.258008 0.0 0.0 0.0 0.0\natom 1.4818750264 -1.6141960253 -0.4900990483 C -0.170604 0.0 0.0 0.0 0.0\natom 1.5021547494 -1.373115678 1.0029402342 C 0.187266 0.0 0.0 0.0 0.0\natom 0.5897876628 -0.2861169334 1.3452589146 C 0.284505 0.0 0.0 0.0 0.0\natom 0.3065432856 0.1831182351 2.4224062794 O -0.348385 0.0 0.0 0.0 0.0\natom 2.7696821276 -2.594338985 2.6743361432 N -0.224094 0.0 0.0 0.0 0.0\natom 2.1841947658 -2.0397181444 1.8770115876 N 0.140155 0.0 0.0 0.0 0.0\natom 0.970587864 2.0772085236 -0.1634118886 H 0.129458 0.0 0.0 0.0 0.0\natom -0.4943517447 1.9134215063 -1.1555144589 H 0.128441 0.0 0.0 0.0 0.0\natom -0.6287948377 2.0868184061 0.6122365935 H 0.143904 0.0 0.0 0.0 0.0\natom -0.9956798581 -0.2822626182 -0.0955639063 H 0.101494 0.0 0.0 0.0 0.0\natom 0.895651583 -2.510554739 -0.7522475305 H 0.11528 0.0 0.0 0.0 0.0\natom 2.4771106893 -1.710379513 -0.9366731859 H 0.132864 0.0 0.0 0.0 0.0\nenergy -453.942786\ncharge 0.0\nend\nbegin\ncomment source_file_name=qm9/dsgdb9nsd_127366.xyz structure_number=127366\natom 0.0150159611 1.4686735036 0.0058475867 C -0.345472 0.0 0.0 0.0 0.0\natom -0.0181916668 0.0193860282 0.0362823828 N -0.177479 0.0 0.0 0.0 0.0\natom -0.1267812608 -0.8546247885 -1.0275886805 C 0.026892 0.0 0.0 0.0 0.0\natom -0.1301065951 -2.1201140184 -0.6850610095 N -0.241968 0.0 0.0 0.0 0.0\natom -0.0175157627 -2.0457071734 0.6702973105 N 0.101374 0.0 0.0 0.0 0.0\natom 0.0431976688 -2.9374797201 1.684144551 N -0.268001 0.0 0.0 0.0 0.0\natom 0.1486231072 -2.1035028338 2.7225268694 C 0.030658 0.0 0.0 0.0 0.0\natom 0.1604212283 -0.7565496183 2.4591217958 N -0.410491 0.0 0.0 0.0 0.0\natom 0.0522949563 -0.7844545652 1.1432212806 C 0.514295 0.0 0.0 0.0 0.0\natom 0.9513343121 1.8379741038 0.4326119658 H 0.165236 0.0 0.0 0.0 0.0\natom -0.0612514043 1.8002176109 -1.0307777205 H 0.150546 0.0 0.0 0.0 0.0\natom -0.8207158832 1.8816506869 0.5769936348 H 0.165228 0.0 0.0 0.0 0.0\natom -0.2014353507 -0.5092440148 -2.046332808 H 0.160118 0.0 0.0 0.0 0.0\natom 0.2212121496 -2.4883931409 3.7288043612 H 0.129066 0.0 0.0 0.0 0.0\nenergy -429.056153\ncharge 0.0\nend\nbegin\ncomment source_file_name=qm9/dsgdb9nsd_128820.xyz structure_number=128820\natom -0.2682024164 1.3628803104 -0.2757476969 C -0.22533 0.0 0.0 0.0 0.0\natom -0.2924715606 -0.0460486365 -0.3278681969 O -0.242854 0.0 0.0 0.0 0.0\natom 0.8998543979 -0.5921611473 -0.8782847016 C -0.193835 0.0 0.0 0.0 0.0\natom 0.7427775914 -2.0710323887 -0.9600934116 C 0.268764 0.0 0.0 0.0 0.0\natom 1.6939210952 -2.9324795145 -0.5989098967 N -0.273118 0.0 0.0 0.0 0.0\natom 1.1563069756 -4.1113793436 -0.8531254335 N -0.094467 0.0 0.0 0.0 0.0\natom -0.0921133877 -4.1094262589 -1.340153802 N -0.285175 0.0 0.0 0.0 0.0\natom -0.3734047113 -2.8101025191 -1.422003271 C 0.279785 0.0 0.0 0.0 0.0\natom -1.5606457443 -2.3098156521 -1.9307574688 N -0.602801 0.0 0.0 0.0 0.0\natom 0.553075785 1.7291881301 0.3587895863 H 0.111998 0.0 0.0 0.0 0.0\natom -0.1536071193 1.8067640312 -1.2770384647 H 0.109299 0.0 0.0 0.0 0.0\natom -1.2185480525 1.6903407015 0.152004469 H 0.129386 0.0 0.0 0.0 0.0\natom 1.0702877217 -0.1568863133 -1.8785417424 H 0.103801 0.0 0.0 0.0 0.0\natom 1.7731842092 -0.343725547 -0.2578253552 H 0.115888 0.0 0.0 0.0 0.0\natom 1.6513224898 -4.9693971534 -0.6809763156 H 0.288273 0.0 0.0 0.0 0.0\natom -2.3122538734 -2.9855282538 -1.9203723 H 0.25167 0.0 0.0 0.0 0.0\natom -1.8187617702 -1.439012325 -1.4850870084 H 0.258716 0.0 0.0 0.0 0.0\nenergy -451.317326\ncharge 0.0\nend\nbegin\ncomment source_file_name=qm9/dsgdb9nsd_130151.xyz structure_number=130151\natom -0.0919416655 1.3530581606 -0.0732725993 N -0.583573 0.0 0.0 0.0 0.0\natom -0.0077620925 -0.0240081635 -0.0177591003 C 0.386491 0.0 0.0 0.0 0.0\natom -1.0755797183 -0.8115846476 -0.0230606082 N -0.298748 0.0 0.0 0.0 0.0\natom -0.4922254459 -2.0482070129 -0.032630759 N -0.246169 0.0 0.0 0.0 0.0\natom 0.8489958444 -1.9489491113 -0.0182911679 C 0.367349 0.0 0.0 0.0 0.0\natom 1.7829013461 -3.1119867232 -0.0483289485 C -0.336816 0.0 0.0 0.0 0.0\natom 2.6054648141 -3.1613043339 -1.3505262689 C -0.058143 0.0 0.0 0.0 0.0\natom 3.4889306394 -4.2665986954 -1.3807360727 O -0.413305 0.0 0.0 0.0 0.0\natom 1.1955556048 -0.6693424433 -0.010181209 N -0.361568 0.0 0.0 0.0 0.0\natom 0.7070643998 1.8131197293 0.337276313 H 0.256528 0.0 0.0 0.0 0.0\natom -0.9715939297 1.718707288 0.2609159842 H 0.255988 0.0 0.0 0.0 0.0\natom -1.0695654288 -2.8720079166 -0.0326835577 H 0.27377 0.0 0.0 0.0 0.0\natom 2.4711283285 -3.0357046765 0.8024128218 H 0.122078 0.0 0.0 0.0 0.0\natom 1.2311887789 -4.0510796874 0.0636036518 H 0.111034 0.0 0.0 0.0 0.0\natom 1.9331076339 -3.2869002176 -2.2053183926 H 0.118878 0.0 0.0 0.0 0.0\natom 3.1290652919 -2.2052399703 -1.4821745659 H 0.12103 0.0 0.0 0.0 0.0\natom 4.1954132788 -4.0998435082 -0.7487746108 H 0.285175 0.0 0.0 0.0 0.0\nenergy -451.352759\ncharge 0.0\nend\nbegin\ncomment source_file_name=qm9/dsgdb9nsd_131426.xyz structure_number=131426\natom 0.1921560217 1.3819312449 0.2519275391 O -0.414513 0.0 0.0 0.0 0.0\natom 0.0707481088 0.0516965956 0.1487803248 C 0.481366 0.0 0.0 0.0 0.0\natom -0.1980070114 -0.5356236756 -0.9926882335 N -0.255749 0.0 0.0 0.0 0.0\natom -0.2382102934 -1.902136671 -0.6880077106 O -0.220723 0.0 0.0 0.0 0.0\natom 0.0097822061 -2.0711937138 0.625239083 C 0.439492 0.0 0.0 0.0 0.0\natom -0.0374092226 -3.4712054733 1.1315637814 C -0.387401 0.0 0.0 0.0 0.0\natom -1.4730446895 -3.9750110952 1.297887558 C 0.1588 0.0 0.0 0.0 0.0\natom -1.853776586 -4.5948132438 2.2526173669 O -0.222124 0.0 0.0 0.0 0.0\natom 0.2123487237 -0.8682382612 1.2244718536 C -0.438586 0.0 0.0 0.0 0.0\natom 0.0479035805 1.7605900877 -0.6259608532 H 0.31467 0.0 0.0 0.0 0.0\natom 0.4530486124 -4.1322106287 0.4041526798 H 0.156775 0.0 0.0 0.0 0.0\natom 0.4797785093 -3.5643481757 2.0880358492 H 0.147622 0.0 0.0 0.0 0.0\natom -2.1449735672 -3.7293133648 0.4476217963 H 0.105184 0.0 0.0 0.0 0.0\natom 0.4295211075 -0.6558700851 2.2569741553 H 0.135187 0.0 0.0 0.0 0.0\nenergy -473.828141\ncharge 0.0\nend\nbegin\ncomment source_file_name=qm9/dsgdb9nsd_132700.xyz structure_number=132700\natom 0.0680853169 1.3816216071 -0.1128715995 O -0.440854 0.0 0.0 0.0 0.0\natom 0.057971415 0.0259873016 -0.0675116287 C 0.257699 0.0 0.0 0.0 0.0\natom -0.0265403702 -0.7439194864 -1.2132047161 C -0.055815 0.0 0.0 0.0 0.0\natom -0.0380416733 -2.0875856867 -1.1838518194 N -0.31604 0.0 0.0 0.0 0.0\natom 0.036765383 -2.6245938192 0.0100897067 C 0.339384 0.0 0.0 0.0 0.0\natom 0.027060913 -3.944398089 0.0659224584 F -0.059395 0.0 0.0 0.0 0.0\natom 0.1218910773 -2.0132156338 1.1859748464 N -0.396164 0.0 0.0 0.0 0.0\natom 0.1316721158 -0.6941313361 1.1358148628 C 0.334147 0.0 0.0 0.0 0.0\natom 0.2156651802 0.0138142128 2.2786231285 O -0.429244 0.0 0.0 0.0 0.0\natom 0.1342603437 1.7141163039 0.7905969732 H 0.314495 0.0 0.0 0.0 0.0\natom -0.086993252 -0.2643772467 -2.1856848242 H 0.137115 0.0 0.0 0.0 0.0\natom 0.2583074007 -0.6191392675 3.0090584918 H 0.314672 0.0 0.0 0.0 0.0\nenergy -513.977601\ncharge 0.0\nend\n"
  },
  {
    "path": "examples/nnp-train/QM9/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\n#mean_energy  -2.3641783837344434E+01\n#conv_energy   1.8771325003590586E-01\n#conv_length   1.0000000000000000E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              5              # Number of elements.\nelements                        H C N O F      # Specification of elements.\n#atom_energy                     H  0.0         # Free atom reference energy (H).\n#atom_energy                     C  0.0         # Free atom reference energy (C).\n#atom_energy                     N  0.0         # Free atom reference energy (N).\n#atom_energy                     O  0.0         # Free atom reference energy (O).\n#atom_energy                     F  0.0         # Free atom reference energy (F).\ncutoff_type                     6 0.0          # Cutoff type (optional argument: shift parameter alpha).\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              10 50          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\n#use_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          100            # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.02315        # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               MAE            # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\nsymfunction_short  H   23     -1.50E+01  1.50E+01 p2\nsymfunction_short  H   23     -1.40E+01  1.40E+01 p2a\nsymfunction_short  H   23     -1.00E+01  1.00E+01 p2a\nsymfunction_short  H   23     -5.00E+00  5.00E+00 p2a\nsymfunction_short  H   23     -2.50E+00  7.50E+00 p2a\nsymfunction_short  H   23      0.00E+00  1.00E+01 p2a\nsymfunction_short  H   23      2.50E+00  1.25E+01 p2a\nsymfunction_short  H   23      5.00E+00  1.50E+01 p2a\n\nsymfunction_short  C   23     -1.50E+01  1.50E+01 p2\nsymfunction_short  C   23     -1.40E+01  1.40E+01 p2a\nsymfunction_short  C   23     -1.00E+01  1.00E+01 p2a\nsymfunction_short  C   23     -5.00E+00  5.00E+00 p2a\nsymfunction_short  C   23     -2.50E+00  7.50E+00 p2a\nsymfunction_short  C   23      0.00E+00  1.00E+01 p2a\nsymfunction_short  C   23      2.50E+00  1.25E+01 p2a\nsymfunction_short  C   23      5.00E+00  1.50E+01 p2a\n\nsymfunction_short  N   23     -1.50E+01  1.50E+01 p2\nsymfunction_short  N   23     -1.40E+01  1.40E+01 p2a\nsymfunction_short  N   23     -1.00E+01  1.00E+01 p2a\nsymfunction_short  N   23     -5.00E+00  5.00E+00 p2a\nsymfunction_short  N   23     -2.50E+00  7.50E+00 p2a\nsymfunction_short  N   23      0.00E+00  1.00E+01 p2a\nsymfunction_short  N   23      2.50E+00  1.25E+01 p2a\nsymfunction_short  N   23      5.00E+00  1.50E+01 p2a\n\nsymfunction_short  O   23     -1.50E+01  1.50E+01 p2\nsymfunction_short  O   23     -1.40E+01  1.40E+01 p2a\nsymfunction_short  O   23     -1.00E+01  1.00E+01 p2a\nsymfunction_short  O   23     -5.00E+00  5.00E+00 p2a\nsymfunction_short  O   23     -2.50E+00  7.50E+00 p2a\nsymfunction_short  O   23      0.00E+00  1.00E+01 p2a\nsymfunction_short  O   23      2.50E+00  1.25E+01 p2a\nsymfunction_short  O   23      5.00E+00  1.50E+01 p2a\n\nsymfunction_short  F   23     -1.50E+01  1.50E+01 p2\nsymfunction_short  F   23     -1.40E+01  1.40E+01 p2a\nsymfunction_short  F   23     -1.00E+01  1.00E+01 p2a\nsymfunction_short  F   23     -5.00E+00  5.00E+00 p2a\nsymfunction_short  F   23     -2.50E+00  7.50E+00 p2a\nsymfunction_short  F   23      0.00E+00  1.00E+01 p2a\nsymfunction_short  F   23      2.50E+00  1.25E+01 p2a\nsymfunction_short  F   23      5.00E+00  1.50E+01 p2a\n\nsymfunction_short  H   25  -1.50E+01  1.50E+01 -180.00  180.00 p2\nsymfunction_short  H   25  -1.50E+01  1.50E+01    0.00  360.00 p2\nsymfunction_short  H   25  -1.50E+01  1.50E+01    0.00  180.00 p2\nsymfunction_short  H   25  -1.50E+01  1.50E+01    0.00  110.00 p2\nsymfunction_short  H   25  -1.50E+01  1.50E+01   60.00  180.00 p2\nsymfunction_short  H   25  -1.50E+01  1.50E+01   49.10  169.10 p2\nsymfunction_short  H   24  -1.40E+01  1.40E+01 -180.00  180.00 p2a\nsymfunction_short  H   24  -1.40E+01  1.40E+01    0.00  360.00 p2a\nsymfunction_short  H   24  -1.40E+01  1.40E+01    0.00  180.00 p2a\nsymfunction_short  H   24  -1.40E+01  1.40E+01    0.00  110.00 p2a\nsymfunction_short  H   24  -1.40E+01  1.40E+01   60.00  180.00 p2a\nsymfunction_short  H   24  -1.40E+01  1.40E+01   49.10  169.10 p2a\nsymfunction_short  H   24  -1.00E+01  1.00E+01 -180.00  180.00 p2a\nsymfunction_short  H   24  -1.00E+01  1.00E+01    0.00  360.00 p2a\nsymfunction_short  H   24  -1.00E+01  1.00E+01    0.00  180.00 p2a\nsymfunction_short  H   24  -1.00E+01  1.00E+01    0.00  110.00 p2a\nsymfunction_short  H   24  -1.00E+01  1.00E+01   60.00  180.00 p2a\nsymfunction_short  H   24  -1.00E+01  1.00E+01   49.10  169.10 p2a\nsymfunction_short  H   24  -6.00E+00  6.00E+00 -180.00  180.00 p2a\nsymfunction_short  H   24  -6.00E+00  6.00E+00    0.00  360.00 p2a\nsymfunction_short  H   24  -6.00E+00  6.00E+00    0.00  180.00 p2a\nsymfunction_short  H   24  -6.00E+00  6.00E+00    0.00  110.00 p2a\nsymfunction_short  H   24  -6.00E+00  6.00E+00   60.00  180.00 p2a\nsymfunction_short  H   24  -6.00E+00  6.00E+00   49.10  169.10 p2a\nsymfunction_short  H   24   0.00E+00  1.00E+01 -180.00  180.00 p2a\nsymfunction_short  H   24   0.00E+00  1.00E+01    0.00  360.00 p2a\nsymfunction_short  H   24   0.00E+00  1.00E+01    0.00  180.00 p2a\nsymfunction_short  H   24   0.00E+00  1.00E+01    0.00  110.00 p2a\nsymfunction_short  H   24   0.00E+00  1.00E+01   60.00  180.00 p2a\nsymfunction_short  H   24   0.00E+00  1.00E+01   49.10  169.10 p2a\nsymfunction_short  H   24   2.50E+00  1.25E+01 -180.00  180.00 p2a\nsymfunction_short  H   24   2.50E+00  1.25E+01    0.00  360.00 p2a\nsymfunction_short  H   24   2.50E+00  1.25E+01    0.00  180.00 p2a\nsymfunction_short  H   24   2.50E+00  1.25E+01    0.00  110.00 p2a\nsymfunction_short  H   24   2.50E+00  1.25E+01   60.00  180.00 p2a\nsymfunction_short  H   24   2.50E+00  1.25E+01   49.10  169.10 p2a\nsymfunction_short  H   24   5.00E+00  1.50E+01 -180.00  180.00 p2a\nsymfunction_short  H   24   5.00E+00  1.50E+01    0.00  360.00 p2a\nsymfunction_short  H   24   5.00E+00  1.50E+01    0.00  180.00 p2a\nsymfunction_short  H   24   5.00E+00  1.50E+01    0.00  110.00 p2a\n# symfunction_short  H   24   5.00E+00  1.50E+01   60.00  180.00 p2a\nsymfunction_short  H   24   5.00E+00  1.50E+01   49.10  169.10 p2a\n\nsymfunction_short  C   25  -1.50E+01  1.50E+01 -180.00  180.00 p2\nsymfunction_short  C   25  -1.50E+01  1.50E+01    0.00  360.00 p2\nsymfunction_short  C   25  -1.50E+01  1.50E+01    0.00  180.00 p2\nsymfunction_short  C   25  -1.50E+01  1.50E+01    0.00  110.00 p2\nsymfunction_short  C   25  -1.50E+01  1.50E+01   60.00  180.00 p2\nsymfunction_short  C   25  -1.50E+01  1.50E+01   49.10  169.10 p2\nsymfunction_short  C   24  -1.40E+01  1.40E+01 -180.00  180.00 p2a\nsymfunction_short  C   24  -1.40E+01  1.40E+01    0.00  360.00 p2a\nsymfunction_short  C   24  -1.40E+01  1.40E+01    0.00  180.00 p2a\nsymfunction_short  C   24  -1.40E+01  1.40E+01    0.00  110.00 p2a\nsymfunction_short  C   24  -1.40E+01  1.40E+01   60.00  180.00 p2a\nsymfunction_short  C   24  -1.40E+01  1.40E+01   49.10  169.10 p2a\nsymfunction_short  C   24  -1.00E+01  1.00E+01 -180.00  180.00 p2a\nsymfunction_short  C   24  -1.00E+01  1.00E+01    0.00  360.00 p2a\nsymfunction_short  C   24  -1.00E+01  1.00E+01    0.00  180.00 p2a\nsymfunction_short  C   24  -1.00E+01  1.00E+01    0.00  110.00 p2a\nsymfunction_short  C   24  -1.00E+01  1.00E+01   60.00  180.00 p2a\nsymfunction_short  C   24  -1.00E+01  1.00E+01   49.10  169.10 p2a\nsymfunction_short  C   24  -6.00E+00  6.00E+00 -180.00  180.00 p2a\nsymfunction_short  C   24  -6.00E+00  6.00E+00    0.00  360.00 p2a\nsymfunction_short  C   24  -6.00E+00  6.00E+00    0.00  180.00 p2a\nsymfunction_short  C   24  -6.00E+00  6.00E+00    0.00  110.00 p2a\nsymfunction_short  C   24  -6.00E+00  6.00E+00   60.00  180.00 p2a\nsymfunction_short  C   24  -6.00E+00  6.00E+00   49.10  169.10 p2a\nsymfunction_short  C   24   0.00E+00  1.00E+01 -180.00  180.00 p2a\nsymfunction_short  C   24   0.00E+00  1.00E+01    0.00  360.00 p2a\nsymfunction_short  C   24   0.00E+00  1.00E+01    0.00  180.00 p2a\nsymfunction_short  C   24   0.00E+00  1.00E+01    0.00  110.00 p2a\nsymfunction_short  C   24   0.00E+00  1.00E+01   60.00  180.00 p2a\nsymfunction_short  C   24   0.00E+00  1.00E+01   49.10  169.10 p2a\nsymfunction_short  C   24   2.50E+00  1.25E+01 -180.00  180.00 p2a\nsymfunction_short  C   24   2.50E+00  1.25E+01    0.00  360.00 p2a\nsymfunction_short  C   24   2.50E+00  1.25E+01    0.00  180.00 p2a\nsymfunction_short  C   24   2.50E+00  1.25E+01    0.00  110.00 p2a\nsymfunction_short  C   24   2.50E+00  1.25E+01   60.00  180.00 p2a\nsymfunction_short  C   24   2.50E+00  1.25E+01   49.10  169.10 p2a\n# symfunction_short  C   24   5.00E+00  1.50E+01 -180.00  180.00 p2a\n# symfunction_short  C   24   5.00E+00  1.50E+01    0.00  360.00 p2a\n# symfunction_short  C   24   5.00E+00  1.50E+01    0.00  180.00 p2a\n# symfunction_short  C   24   5.00E+00  1.50E+01    0.00  110.00 p2a\n# symfunction_short  C   24   5.00E+00  1.50E+01   60.00  180.00 p2a\n# symfunction_short  C   24   5.00E+00  1.50E+01   49.10  169.10 p2a\n\nsymfunction_short  N   25  -1.50E+01  1.50E+01 -180.00  180.00 p2\nsymfunction_short  N   25  -1.50E+01  1.50E+01    0.00  360.00 p2\nsymfunction_short  N   25  -1.50E+01  1.50E+01    0.00  180.00 p2\nsymfunction_short  N   25  -1.50E+01  1.50E+01    0.00  110.00 p2\nsymfunction_short  N   25  -1.50E+01  1.50E+01   60.00  180.00 p2\nsymfunction_short  N   25  -1.50E+01  1.50E+01   49.10  169.10 p2\nsymfunction_short  N   24  -1.40E+01  1.40E+01 -180.00  180.00 p2a\nsymfunction_short  N   24  -1.40E+01  1.40E+01    0.00  360.00 p2a\nsymfunction_short  N   24  -1.40E+01  1.40E+01    0.00  180.00 p2a\nsymfunction_short  N   24  -1.40E+01  1.40E+01    0.00  110.00 p2a\nsymfunction_short  N   24  -1.40E+01  1.40E+01   60.00  180.00 p2a\nsymfunction_short  N   24  -1.40E+01  1.40E+01   49.10  169.10 p2a\nsymfunction_short  N   24  -1.00E+01  1.00E+01 -180.00  180.00 p2a\nsymfunction_short  N   24  -1.00E+01  1.00E+01    0.00  360.00 p2a\nsymfunction_short  N   24  -1.00E+01  1.00E+01    0.00  180.00 p2a\nsymfunction_short  N   24  -1.00E+01  1.00E+01    0.00  110.00 p2a\nsymfunction_short  N   24  -1.00E+01  1.00E+01   60.00  180.00 p2a\nsymfunction_short  N   24  -1.00E+01  1.00E+01   49.10  169.10 p2a\nsymfunction_short  N   24  -6.00E+00  6.00E+00 -180.00  180.00 p2a\nsymfunction_short  N   24  -6.00E+00  6.00E+00    0.00  360.00 p2a\nsymfunction_short  N   24  -6.00E+00  6.00E+00    0.00  180.00 p2a\nsymfunction_short  N   24  -6.00E+00  6.00E+00    0.00  110.00 p2a\nsymfunction_short  N   24  -6.00E+00  6.00E+00   60.00  180.00 p2a\nsymfunction_short  N   24  -6.00E+00  6.00E+00   49.10  169.10 p2a\nsymfunction_short  N   24   0.00E+00  1.00E+01 -180.00  180.00 p2a\nsymfunction_short  N   24   0.00E+00  1.00E+01    0.00  360.00 p2a\nsymfunction_short  N   24   0.00E+00  1.00E+01    0.00  180.00 p2a\nsymfunction_short  N   24   0.00E+00  1.00E+01    0.00  110.00 p2a\nsymfunction_short  N   24   0.00E+00  1.00E+01   60.00  180.00 p2a\nsymfunction_short  N   24   0.00E+00  1.00E+01   49.10  169.10 p2a\nsymfunction_short  N   24   2.50E+00  1.25E+01 -180.00  180.00 p2a\nsymfunction_short  N   24   2.50E+00  1.25E+01    0.00  360.00 p2a\nsymfunction_short  N   24   2.50E+00  1.25E+01    0.00  180.00 p2a\nsymfunction_short  N   24   2.50E+00  1.25E+01    0.00  110.00 p2a\nsymfunction_short  N   24   2.50E+00  1.25E+01   60.00  180.00 p2a\nsymfunction_short  N   24   2.50E+00  1.25E+01   49.10  169.10 p2a\n# symfunction_short  N   24   5.00E+00  1.50E+01 -180.00  180.00 p2a\n# symfunction_short  N   24   5.00E+00  1.50E+01    0.00  360.00 p2a\n# symfunction_short  N   24   5.00E+00  1.50E+01    0.00  180.00 p2a\n# symfunction_short  N   24   5.00E+00  1.50E+01    0.00  110.00 p2a\n# symfunction_short  N   24   5.00E+00  1.50E+01   60.00  180.00 p2a\n# symfunction_short  N   24   5.00E+00  1.50E+01   49.10  169.10 p2a\n\nsymfunction_short  O   25  -1.50E+01  1.50E+01 -180.00  180.00 p2\nsymfunction_short  O   25  -1.50E+01  1.50E+01    0.00  360.00 p2\nsymfunction_short  O   25  -1.50E+01  1.50E+01    0.00  180.00 p2\nsymfunction_short  O   25  -1.50E+01  1.50E+01    0.00  110.00 p2\nsymfunction_short  O   25  -1.50E+01  1.50E+01   60.00  180.00 p2\nsymfunction_short  O   25  -1.50E+01  1.50E+01   49.10  169.10 p2\nsymfunction_short  O   24  -1.40E+01  1.40E+01 -180.00  180.00 p2a\nsymfunction_short  O   24  -1.40E+01  1.40E+01    0.00  360.00 p2a\nsymfunction_short  O   24  -1.40E+01  1.40E+01    0.00  180.00 p2a\nsymfunction_short  O   24  -1.40E+01  1.40E+01    0.00  110.00 p2a\nsymfunction_short  O   24  -1.40E+01  1.40E+01   60.00  180.00 p2a\nsymfunction_short  O   24  -1.40E+01  1.40E+01   49.10  169.10 p2a\nsymfunction_short  O   24  -1.00E+01  1.00E+01 -180.00  180.00 p2a\nsymfunction_short  O   24  -1.00E+01  1.00E+01    0.00  360.00 p2a\nsymfunction_short  O   24  -1.00E+01  1.00E+01    0.00  180.00 p2a\nsymfunction_short  O   24  -1.00E+01  1.00E+01    0.00  110.00 p2a\nsymfunction_short  O   24  -1.00E+01  1.00E+01   60.00  180.00 p2a\nsymfunction_short  O   24  -1.00E+01  1.00E+01   49.10  169.10 p2a\nsymfunction_short  O   24  -6.00E+00  6.00E+00 -180.00  180.00 p2a\nsymfunction_short  O   24  -6.00E+00  6.00E+00    0.00  360.00 p2a\nsymfunction_short  O   24  -6.00E+00  6.00E+00    0.00  180.00 p2a\nsymfunction_short  O   24  -6.00E+00  6.00E+00    0.00  110.00 p2a\nsymfunction_short  O   24  -6.00E+00  6.00E+00   60.00  180.00 p2a\nsymfunction_short  O   24  -6.00E+00  6.00E+00   49.10  169.10 p2a\nsymfunction_short  O   24   0.00E+00  1.00E+01 -180.00  180.00 p2a\nsymfunction_short  O   24   0.00E+00  1.00E+01    0.00  360.00 p2a\nsymfunction_short  O   24   0.00E+00  1.00E+01    0.00  180.00 p2a\nsymfunction_short  O   24   0.00E+00  1.00E+01    0.00  110.00 p2a\nsymfunction_short  O   24   0.00E+00  1.00E+01   60.00  180.00 p2a\nsymfunction_short  O   24   0.00E+00  1.00E+01   49.10  169.10 p2a\nsymfunction_short  O   24   2.50E+00  1.25E+01 -180.00  180.00 p2a\nsymfunction_short  O   24   2.50E+00  1.25E+01    0.00  360.00 p2a\nsymfunction_short  O   24   2.50E+00  1.25E+01    0.00  180.00 p2a\nsymfunction_short  O   24   2.50E+00  1.25E+01    0.00  110.00 p2a\nsymfunction_short  O   24   2.50E+00  1.25E+01   60.00  180.00 p2a\nsymfunction_short  O   24   2.50E+00  1.25E+01   49.10  169.10 p2a\n# symfunction_short  O   24   5.00E+00  1.50E+01 -180.00  180.00 p2a\n# symfunction_short  O   24   5.00E+00  1.50E+01    0.00  360.00 p2a\n# symfunction_short  O   24   5.00E+00  1.50E+01    0.00  180.00 p2a\n# symfunction_short  O   24   5.00E+00  1.50E+01    0.00  110.00 p2a\n# symfunction_short  O   24   5.00E+00  1.50E+01   60.00  180.00 p2a\n# symfunction_short  O   24   5.00E+00  1.50E+01   49.10  169.10 p2a\n\nsymfunction_short  F   25  -1.50E+01  1.50E+01 -180.00  180.00 p2\nsymfunction_short  F   25  -1.50E+01  1.50E+01    0.00  360.00 p2\nsymfunction_short  F   25  -1.50E+01  1.50E+01    0.00  180.00 p2\nsymfunction_short  F   25  -1.50E+01  1.50E+01    0.00  110.00 p2\nsymfunction_short  F   25  -1.50E+01  1.50E+01   60.00  180.00 p2\nsymfunction_short  F   25  -1.50E+01  1.50E+01   49.10  169.10 p2\nsymfunction_short  F   24  -1.40E+01  1.40E+01 -180.00  180.00 p2a\nsymfunction_short  F   24  -1.40E+01  1.40E+01    0.00  360.00 p2a\nsymfunction_short  F   24  -1.40E+01  1.40E+01    0.00  180.00 p2a\nsymfunction_short  F   24  -1.40E+01  1.40E+01    0.00  110.00 p2a\nsymfunction_short  F   24  -1.40E+01  1.40E+01   60.00  180.00 p2a\nsymfunction_short  F   24  -1.40E+01  1.40E+01   49.10  169.10 p2a\nsymfunction_short  F   24  -1.00E+01  1.00E+01 -180.00  180.00 p2a\nsymfunction_short  F   24  -1.00E+01  1.00E+01    0.00  360.00 p2a\nsymfunction_short  F   24  -1.00E+01  1.00E+01    0.00  180.00 p2a\nsymfunction_short  F   24  -1.00E+01  1.00E+01    0.00  110.00 p2a\nsymfunction_short  F   24  -1.00E+01  1.00E+01   60.00  180.00 p2a\nsymfunction_short  F   24  -1.00E+01  1.00E+01   49.10  169.10 p2a\nsymfunction_short  F   24  -6.00E+00  6.00E+00 -180.00  180.00 p2a\nsymfunction_short  F   24  -6.00E+00  6.00E+00    0.00  360.00 p2a\nsymfunction_short  F   24  -6.00E+00  6.00E+00    0.00  180.00 p2a\nsymfunction_short  F   24  -6.00E+00  6.00E+00    0.00  110.00 p2a\nsymfunction_short  F   24  -6.00E+00  6.00E+00   60.00  180.00 p2a\nsymfunction_short  F   24  -6.00E+00  6.00E+00   49.10  169.10 p2a\nsymfunction_short  F   24   0.00E+00  1.00E+01 -180.00  180.00 p2a\nsymfunction_short  F   24   0.00E+00  1.00E+01    0.00  360.00 p2a\nsymfunction_short  F   24   0.00E+00  1.00E+01    0.00  180.00 p2a\nsymfunction_short  F   24   0.00E+00  1.00E+01    0.00  110.00 p2a\nsymfunction_short  F   24   0.00E+00  1.00E+01   60.00  180.00 p2a\nsymfunction_short  F   24   0.00E+00  1.00E+01   49.10  169.10 p2a\nsymfunction_short  F   24   2.50E+00  1.25E+01 -180.00  180.00 p2a\nsymfunction_short  F   24   2.50E+00  1.25E+01    0.00  360.00 p2a\nsymfunction_short  F   24   2.50E+00  1.25E+01    0.00  180.00 p2a\nsymfunction_short  F   24   2.50E+00  1.25E+01    0.00  110.00 p2a\nsymfunction_short  F   24   2.50E+00  1.25E+01   60.00  180.00 p2a\nsymfunction_short  F   24   2.50E+00  1.25E+01   49.10  169.10 p2a\n# symfunction_short  F   24   5.00E+00  1.50E+01 -180.00  180.00 p2a\n# symfunction_short  F   24   5.00E+00  1.50E+01    0.00  360.00 p2a\n# symfunction_short  F   24   5.00E+00  1.50E+01    0.00  180.00 p2a\n# symfunction_short  F   24   5.00E+00  1.50E+01    0.00  110.00 p2a\n# symfunction_short  F   24   5.00E+00  1.50E+01   60.00  180.00 p2a\n# symfunction_short  F   24   5.00E+00  1.50E+01   49.10  169.10 p2a\n\n"
  },
  {
    "path": "examples/nnp-train/QM9/input.nn.wacsf",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\n#mean_energy  -2.3641783837344434E+01\n#conv_energy   1.8771325003590586E-01\n#conv_length   1.0000000000000000E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              5              # Number of elements.\nelements                        H C N O F      # Specification of elements.\n#atom_energy                     H  0.0         # Free atom reference energy (H).\n#atom_energy                     C  0.0         # Free atom reference energy (C).\n#atom_energy                     N  0.0         # Free atom reference energy (N).\n#atom_energy                     O  0.0         # Free atom reference energy (O).\n#atom_energy                     F  0.0         # Free atom reference energy (F).\ncutoff_type                     6 0.0          # Cutoff type (optional argument: shift parameter alpha).\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              10 50          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\n#use_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          100            # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.02315        # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nmain_error_metric               MAE            # Main error metric for screen output (RMSEpa/RMSE/MAEpa/MAE).\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# wACSF set (26:6, \"best performing\"), https://doi.org/10.1063/1.5019667\n\n# Element H\nsymfunction_short H 12 6.3775510 7.5000000 8.00\nsymfunction_short H 12 6.3775510 7.2200000 8.00\nsymfunction_short H 12 6.3775510 6.9400000 8.00\nsymfunction_short H 12 6.3775510 6.6600000 8.00\nsymfunction_short H 12 6.3775510 6.3800000 8.00\nsymfunction_short H 12 6.3775510 6.1000000 8.00\nsymfunction_short H 12 6.3775510 5.8200000 8.00\nsymfunction_short H 12 6.3775510 5.5400000 8.00\nsymfunction_short H 12 6.3775510 5.2600000 8.00\nsymfunction_short H 12 6.3775510 4.9800000 8.00\nsymfunction_short H 12 6.3775510 4.7000000 8.00\nsymfunction_short H 12 6.3775510 4.4200000 8.00\nsymfunction_short H 12 6.3775510 4.1400000 8.00\nsymfunction_short H 12 6.3775510 3.8600000 8.00\nsymfunction_short H 12 6.3775510 3.5800000 8.00\nsymfunction_short H 12 6.3775510 3.3000000 8.00\nsymfunction_short H 12 6.3775510 3.0200000 8.00\nsymfunction_short H 12 6.3775510 2.7400000 8.00\nsymfunction_short H 12 6.3775510 2.4600000 8.00\nsymfunction_short H 12 6.3775510 2.1800000 8.00\nsymfunction_short H 12 6.3775510 1.9000000 8.00\nsymfunction_short H 12 6.3775510 1.6200000 8.00\nsymfunction_short H 12 6.3775510 1.3400000 8.00\nsymfunction_short H 12 6.3775510 1.0600000 8.00\nsymfunction_short H 12 6.3775510 0.7800000 8.00\nsymfunction_short H 12 6.3775510 0.5000000 8.00\n\nsymfunction_short H 13 0.08367770 0.0 -1.0 1.0 8.00\nsymfunction_short H 13 0.08367770 0.0  1.0 1.0 8.00\nsymfunction_short H 13 0.16857440 0.0 -1.0 1.0 8.00\nsymfunction_short H 13 0.16857440 0.0  1.0 1.0 8.00\nsymfunction_short H 13 0.50000000 0.0 -1.0 1.0 8.00\nsymfunction_short H 13 0.50000000 0.0  1.0 1.0 8.00\n\n# Element C\nsymfunction_short C 12 6.3775510 7.5000000 8.00\nsymfunction_short C 12 6.3775510 7.2200000 8.00\nsymfunction_short C 12 6.3775510 6.9400000 8.00\nsymfunction_short C 12 6.3775510 6.6600000 8.00\nsymfunction_short C 12 6.3775510 6.3800000 8.00\nsymfunction_short C 12 6.3775510 6.1000000 8.00\nsymfunction_short C 12 6.3775510 5.8200000 8.00\nsymfunction_short C 12 6.3775510 5.5400000 8.00\nsymfunction_short C 12 6.3775510 5.2600000 8.00\nsymfunction_short C 12 6.3775510 4.9800000 8.00\nsymfunction_short C 12 6.3775510 4.7000000 8.00\nsymfunction_short C 12 6.3775510 4.4200000 8.00\nsymfunction_short C 12 6.3775510 4.1400000 8.00\nsymfunction_short C 12 6.3775510 3.8600000 8.00\nsymfunction_short C 12 6.3775510 3.5800000 8.00\nsymfunction_short C 12 6.3775510 3.3000000 8.00\nsymfunction_short C 12 6.3775510 3.0200000 8.00\nsymfunction_short C 12 6.3775510 2.7400000 8.00\nsymfunction_short C 12 6.3775510 2.4600000 8.00\nsymfunction_short C 12 6.3775510 2.1800000 8.00\nsymfunction_short C 12 6.3775510 1.9000000 8.00\nsymfunction_short C 12 6.3775510 1.6200000 8.00\nsymfunction_short C 12 6.3775510 1.3400000 8.00\nsymfunction_short C 12 6.3775510 1.0600000 8.00\nsymfunction_short C 12 6.3775510 0.7800000 8.00\nsymfunction_short C 12 6.3775510 0.5000000 8.00\n\nsymfunction_short C 13 0.08367770 0.0 -1.0 1.0 8.00\nsymfunction_short C 13 0.08367770 0.0  1.0 1.0 8.00\nsymfunction_short C 13 0.16857440 0.0 -1.0 1.0 8.00\nsymfunction_short C 13 0.16857440 0.0  1.0 1.0 8.00\nsymfunction_short C 13 0.50000000 0.0 -1.0 1.0 8.00\nsymfunction_short C 13 0.50000000 0.0  1.0 1.0 8.00\n\n# Element N\nsymfunction_short N 12 6.3775510 7.5000000 8.00\nsymfunction_short N 12 6.3775510 7.2200000 8.00\nsymfunction_short N 12 6.3775510 6.9400000 8.00\nsymfunction_short N 12 6.3775510 6.6600000 8.00\nsymfunction_short N 12 6.3775510 6.3800000 8.00\nsymfunction_short N 12 6.3775510 6.1000000 8.00\nsymfunction_short N 12 6.3775510 5.8200000 8.00\nsymfunction_short N 12 6.3775510 5.5400000 8.00\nsymfunction_short N 12 6.3775510 5.2600000 8.00\nsymfunction_short N 12 6.3775510 4.9800000 8.00\nsymfunction_short N 12 6.3775510 4.7000000 8.00\nsymfunction_short N 12 6.3775510 4.4200000 8.00\nsymfunction_short N 12 6.3775510 4.1400000 8.00\nsymfunction_short N 12 6.3775510 3.8600000 8.00\nsymfunction_short N 12 6.3775510 3.5800000 8.00\nsymfunction_short N 12 6.3775510 3.3000000 8.00\nsymfunction_short N 12 6.3775510 3.0200000 8.00\nsymfunction_short N 12 6.3775510 2.7400000 8.00\nsymfunction_short N 12 6.3775510 2.4600000 8.00\nsymfunction_short N 12 6.3775510 2.1800000 8.00\nsymfunction_short N 12 6.3775510 1.9000000 8.00\nsymfunction_short N 12 6.3775510 1.6200000 8.00\nsymfunction_short N 12 6.3775510 1.3400000 8.00\nsymfunction_short N 12 6.3775510 1.0600000 8.00\nsymfunction_short N 12 6.3775510 0.7800000 8.00\nsymfunction_short N 12 6.3775510 0.5000000 8.00\n\nsymfunction_short N 13 0.08367770 0.0 -1.0 1.0 8.00\nsymfunction_short N 13 0.08367770 0.0  1.0 1.0 8.00\nsymfunction_short N 13 0.16857440 0.0 -1.0 1.0 8.00\nsymfunction_short N 13 0.16857440 0.0  1.0 1.0 8.00\nsymfunction_short N 13 0.50000000 0.0 -1.0 1.0 8.00\nsymfunction_short N 13 0.50000000 0.0  1.0 1.0 8.00\n\n# Element O\nsymfunction_short O 12 6.3775510 7.5000000 8.00\nsymfunction_short O 12 6.3775510 7.2200000 8.00\nsymfunction_short O 12 6.3775510 6.9400000 8.00\nsymfunction_short O 12 6.3775510 6.6600000 8.00\nsymfunction_short O 12 6.3775510 6.3800000 8.00\nsymfunction_short O 12 6.3775510 6.1000000 8.00\nsymfunction_short O 12 6.3775510 5.8200000 8.00\nsymfunction_short O 12 6.3775510 5.5400000 8.00\nsymfunction_short O 12 6.3775510 5.2600000 8.00\nsymfunction_short O 12 6.3775510 4.9800000 8.00\nsymfunction_short O 12 6.3775510 4.7000000 8.00\nsymfunction_short O 12 6.3775510 4.4200000 8.00\nsymfunction_short O 12 6.3775510 4.1400000 8.00\nsymfunction_short O 12 6.3775510 3.8600000 8.00\nsymfunction_short O 12 6.3775510 3.5800000 8.00\nsymfunction_short O 12 6.3775510 3.3000000 8.00\nsymfunction_short O 12 6.3775510 3.0200000 8.00\nsymfunction_short O 12 6.3775510 2.7400000 8.00\nsymfunction_short O 12 6.3775510 2.4600000 8.00\nsymfunction_short O 12 6.3775510 2.1800000 8.00\nsymfunction_short O 12 6.3775510 1.9000000 8.00\nsymfunction_short O 12 6.3775510 1.6200000 8.00\nsymfunction_short O 12 6.3775510 1.3400000 8.00\nsymfunction_short O 12 6.3775510 1.0600000 8.00\nsymfunction_short O 12 6.3775510 0.7800000 8.00\nsymfunction_short O 12 6.3775510 0.5000000 8.00\n\nsymfunction_short O 13 0.08367770 0.0 -1.0 1.0 8.00\nsymfunction_short O 13 0.08367770 0.0  1.0 1.0 8.00\nsymfunction_short O 13 0.16857440 0.0 -1.0 1.0 8.00\nsymfunction_short O 13 0.16857440 0.0  1.0 1.0 8.00\nsymfunction_short O 13 0.50000000 0.0 -1.0 1.0 8.00\nsymfunction_short O 13 0.50000000 0.0  1.0 1.0 8.00\n\n# Element F\nsymfunction_short F 12 6.3775510 7.5000000 8.0\nsymfunction_short F 12 6.3775510 7.2200000 8.0\nsymfunction_short F 12 6.3775510 6.9400000 8.0\nsymfunction_short F 12 6.3775510 6.6600000 8.0\nsymfunction_short F 12 6.3775510 6.3800000 8.0\nsymfunction_short F 12 6.3775510 6.1000000 8.0\nsymfunction_short F 12 6.3775510 5.8200000 8.0\nsymfunction_short F 12 6.3775510 5.5400000 8.0\nsymfunction_short F 12 6.3775510 5.2600000 8.0\nsymfunction_short F 12 6.3775510 4.9800000 8.0\nsymfunction_short F 12 6.3775510 4.7000000 8.0\nsymfunction_short F 12 6.3775510 4.4200000 8.0\nsymfunction_short F 12 6.3775510 4.1400000 8.0\nsymfunction_short F 12 6.3775510 3.8600000 8.0\nsymfunction_short F 12 6.3775510 3.5800000 8.0\nsymfunction_short F 12 6.3775510 3.3000000 8.0\nsymfunction_short F 12 6.3775510 3.0200000 8.0\nsymfunction_short F 12 6.3775510 2.7400000 8.0\nsymfunction_short F 12 6.3775510 2.4600000 8.0\nsymfunction_short F 12 6.3775510 2.1800000 8.0\nsymfunction_short F 12 6.3775510 1.9000000 8.0\nsymfunction_short F 12 6.3775510 1.6200000 8.0\nsymfunction_short F 12 6.3775510 1.3400000 8.0\nsymfunction_short F 12 6.3775510 1.0600000 8.0\nsymfunction_short F 12 6.3775510 0.7800000 8.0\nsymfunction_short F 12 6.3775510 0.5000000 8.0\n\nsymfunction_short F 13 0.08367770 0.0 -1.0 1.0 8.00\nsymfunction_short F 13 0.08367770 0.0  1.0 1.0 8.00\nsymfunction_short F 13 0.16857440 0.0 -1.0 1.0 8.00\nsymfunction_short F 13 0.16857440 0.0  1.0 1.0 8.00\nsymfunction_short F 13 0.50000000 0.0 -1.0 1.0 8.00\nsymfunction_short F 13 0.50000000 0.0  1.0 1.0 8.00\n\n"
  },
  {
    "path": "examples/potentials/Anisole_SCAN/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.7798465944668833E+00\nconv_energy   9.6165975309496139E+02\nconv_length   1.6441069294475543E+01\n###############################################################################\n\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              3              # Number of elements.\nelements                        C O H          # Specification of elements.\ncutoff_type                     6 0.0          # Cutoff type (optional argument: shift parameter alpha).\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              30 20          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                  987654321        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          30             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                   10.0            # Good to play with / Weight of force updates relative to energy updates.\nshort_energy_fraction           1.0000000       # Fraction of energy updates per epoch.\nshort_force_fraction            0.008057       # 0.0008057, could be 10 times larger / Fraction of force updates per epoch.\nshort_energy_error_threshold    0.000          # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.000          # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # increasing does rarely help / Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                    -1.0            # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               1              # fractional complete / Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\n# gradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\n# gradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\n# gradient_adam_eta               1.0E-3         # Adam parameter eta.\n# gradient_adam_beta1             0.9            # Adam parameter beta1.\n# gradient_adam_beta2             0.999          # Adam parameter beta2.\n# gradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n##########################################################################\n\nsymfunction_short C 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 C -1.40E+01 1.40E+01 p2a\nsymfunction_short C 20 C -1.20E+01 1.20E+01 p2a\nsymfunction_short C 20 C -1.00E+01 1.00E+01 p2a\nsymfunction_short C 20 C -8.00E+00 8.00E+00 p2a\nsymfunction_short C 20 C -6.00E+00 6.00E+00 p2a\nsymfunction_short C 20 C -5.00E+00 5.00E+00 p2a\nsymfunction_short C 20 C -2.50E+00 7.50E+00 p2a\nsymfunction_short C 20 C 0.00E+00 1.00E+01 p2a\nsymfunction_short C 20 C 2.50E+00 1.25E+01 p2a\nsymfunction_short C 20 C 5.00E+00 1.50E+01 p2a\n \nsymfunction_short C 20 O -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 O -1.40E+01 1.40E+01 p2a\nsymfunction_short C 20 O -1.20E+01 1.20E+01 p2a\nsymfunction_short C 20 O -1.00E+01 1.00E+01 p2a\nsymfunction_short C 20 O -8.00E+00 8.00E+00 p2a\nsymfunction_short C 20 O -6.00E+00 6.00E+00 p2a\nsymfunction_short C 20 O -5.00E+00 5.00E+00 p2a\nsymfunction_short C 20 O -2.50E+00 7.50E+00 p2a\nsymfunction_short C 20 O 0.00E+00 1.00E+01 p2a\nsymfunction_short C 20 O 2.50E+00 1.25E+01 p2a\nsymfunction_short C 20 O 5.00E+00 1.50E+01 p2a\n \nsymfunction_short C 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 H -1.40E+01 1.40E+01 p2a\nsymfunction_short C 20 H -1.20E+01 1.20E+01 p2a\nsymfunction_short C 20 H -1.00E+01 1.00E+01 p2a\nsymfunction_short C 20 H -8.00E+00 8.00E+00 p2a\nsymfunction_short C 20 H -6.00E+00 6.00E+00 p2a\nsymfunction_short C 20 H -5.00E+00 5.00E+00 p2a\nsymfunction_short C 20 H -2.50E+00 7.50E+00 p2a\nsymfunction_short C 20 H 0.00E+00 1.00E+01 p2a\nsymfunction_short C 20 H 2.50E+00 1.25E+01 p2a\nsymfunction_short C 20 H 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short O 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short O 20 C -1.40E+01 1.40E+01 p2a\nsymfunction_short O 20 C -1.20E+01 1.20E+01 p2a\nsymfunction_short O 20 C -1.00E+01 1.00E+01 p2a\nsymfunction_short O 20 C -8.00E+00 8.00E+00 p2a\nsymfunction_short O 20 C -6.00E+00 6.00E+00 p2a\nsymfunction_short O 20 C -5.00E+00 5.00E+00 p2a\nsymfunction_short O 20 C -2.50E+00 7.50E+00 p2a\nsymfunction_short O 20 C 0.00E+00 1.00E+01 p2a\nsymfunction_short O 20 C 2.50E+00 1.25E+01 p2a\nsymfunction_short O 20 C 5.00E+00 1.50E+01 p2a\n \nsymfunction_short O 20 O -1.50E+01 1.50E+01 p2\nsymfunction_short O 20 O -1.40E+01 1.40E+01 p2a\nsymfunction_short O 20 O -1.20E+01 1.20E+01 p2a\nsymfunction_short O 20 O -1.00E+01 1.00E+01 p2a\nsymfunction_short O 20 O -8.00E+00 8.00E+00 p2a\nsymfunction_short O 20 O -6.00E+00 6.00E+00 p2a\n# symfunction_short  O  280  O      -5.00E+00  5.00E+00\nsymfunction_short O 20 O -2.50E+00 7.50E+00 p2a\nsymfunction_short O 20 O 0.00E+00 1.00E+01 p2a\nsymfunction_short O 20 O 2.50E+00 1.25E+01 p2a\nsymfunction_short O 20 O 5.00E+00 1.50E+01 p2a\n \nsymfunction_short O 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short O 20 H -1.40E+01 1.40E+01 p2a\nsymfunction_short O 20 H -1.20E+01 1.20E+01 p2a\nsymfunction_short O 20 H -1.00E+01 1.00E+01 p2a\nsymfunction_short O 20 H -8.00E+00 8.00E+00 p2a\nsymfunction_short O 20 H -6.00E+00 6.00E+00 p2a\nsymfunction_short O 20 H -5.00E+00 5.00E+00 p2a\nsymfunction_short O 20 H -2.50E+00 7.50E+00 p2a\nsymfunction_short O 20 H 0.00E+00 1.00E+01 p2a\nsymfunction_short O 20 H 2.50E+00 1.25E+01 p2a\nsymfunction_short O 20 H 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short H 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 C -1.40E+01 1.40E+01 p2a\nsymfunction_short H 20 C -1.20E+01 1.20E+01 p2a\nsymfunction_short H 20 C -1.00E+01 1.00E+01 p2a\nsymfunction_short H 20 C -8.00E+00 8.00E+00 p2a\nsymfunction_short H 20 C -6.00E+00 6.00E+00 p2a\nsymfunction_short H 20 C -5.00E+00 5.00E+00 p2a\nsymfunction_short H 20 C -2.50E+00 7.50E+00 p2a\nsymfunction_short H 20 C 0.00E+00 1.00E+01 p2a\nsymfunction_short H 20 C 2.50E+00 1.25E+01 p2a\nsymfunction_short H 20 C 5.00E+00 1.50E+01 p2a\n \nsymfunction_short H 20 O -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 O -1.40E+01 1.40E+01 p2a\nsymfunction_short H 20 O -1.20E+01 1.20E+01 p2a\nsymfunction_short H 20 O -1.00E+01 1.00E+01 p2a\nsymfunction_short H 20 O -8.00E+00 8.00E+00 p2a\nsymfunction_short H 20 O -6.00E+00 6.00E+00 p2a\nsymfunction_short H 20 O -5.00E+00 5.00E+00 p2a\nsymfunction_short H 20 O -2.50E+00 7.50E+00 p2a\nsymfunction_short H 20 O 0.00E+00 1.00E+01 p2a\nsymfunction_short H 20 O 2.50E+00 1.25E+01 p2a\nsymfunction_short H 20 O 5.00E+00 1.50E+01 p2a\n \nsymfunction_short H 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 H -1.40E+01 1.40E+01 p2a\nsymfunction_short H 20 H -1.20E+01 1.20E+01 p2a\nsymfunction_short H 20 H -1.00E+01 1.00E+01 p2a\nsymfunction_short H 20 H -8.00E+00 8.00E+00 p2a\nsymfunction_short H 20 H -6.00E+00 6.00E+00 p2a\nsymfunction_short H 20 H -5.00E+00 5.00E+00 p2a\nsymfunction_short H 20 H -2.50E+00 7.50E+00 p2a\nsymfunction_short H 20 H 0.00E+00 1.00E+01 p2a\nsymfunction_short H 20 H 2.50E+00 1.25E+01 p2a\nsymfunction_short H 20 H 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short C 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short C 22 C O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C O -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C O -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 C O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short C 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short C 22 O O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 O O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 O O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 O O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 O O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 O O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 O O -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  C  890  O   O   -6.00E+00  -90.00   90.00  6.00E+00\n# symfunction_short  C  890  O   O   -6.00E+00   90.00  270.00  6.00E+00\nsymfunction_short C 22 O O -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 O O -6.00E+00 6.00E+00 0.00 120.00 p2a\n# symfunction_short  C  890  O   O   -6.00E+00   60.00  180.00  6.00E+00\nsymfunction_short C 22 O O -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 O O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short C 22 O H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 O H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 O H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 O H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 O H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 O H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 O H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 O H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 O H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short C 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \nsymfunction_short O 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C C -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C C -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short O 22 C O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 C O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 C O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 C O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 C O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 C O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C O -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  O  890  C   O   -6.00E+00  -90.00   90.00  6.00E+00\n# symfunction_short  O  890  C   O   -6.00E+00   90.00  270.00  6.00E+00\nsymfunction_short O 22 C O -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C O -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C O -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C O -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 C O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short O 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 C H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short O 22 O O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 O O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 O O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 O O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 O O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 O O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O -1.40E+01 1.40E+01 49.10 169.10 p2a\n# symfunction_short  O  890  O   O   -1.20E+01  -90.00   90.00  1.20E+01\nsymfunction_short O 22 O O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 O O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 O O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 O O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O -1.20E+01 1.20E+01 49.10 169.10 p2a\n# symfunction_short  O  890  O   O   -1.00E+01  -90.00   90.00  1.00E+01\n# symfunction_short  O  890  O   O   -1.00E+01   90.00  270.00  1.00E+01\nsymfunction_short O 22 O O -1.00E+01 1.00E+01 0.00 180.00 p2a\n# symfunction_short  O  890  O   O   -1.00E+01    0.00  120.00  1.00E+01\nsymfunction_short O 22 O O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O -1.00E+01 1.00E+01 49.10 169.10 p2a\n# symfunction_short  O  890  O   O   -8.00E+00  -90.00   90.00  8.00E+00\n# symfunction_short  O  890  O   O   -8.00E+00   90.00  270.00  8.00E+00\n# symfunction_short  O  890  O   O   -8.00E+00    0.00  180.00  8.00E+00\n# symfunction_short  O  890  O   O   -8.00E+00    0.00  120.00  8.00E+00\n# symfunction_short  O  890  O   O   -8.00E+00   60.00  180.00  8.00E+00\n# symfunction_short  O  890  O   O   -8.00E+00   49.10  169.10  8.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00  -90.00   90.00  6.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00   90.00  270.00  6.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00    0.00  180.00  6.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00    0.00  120.00  6.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00   60.00  180.00  6.00E+00\n# symfunction_short  O  890  O   O   -6.00E+00   49.10  169.10  6.00E+00\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 O O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short O 22 O H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 O H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 O H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 O H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 O H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 O H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 O H -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  O  890  O   H   -6.00E+00  -90.00   90.00  6.00E+00\n# symfunction_short  O  890  O   H   -6.00E+00   90.00  270.00  6.00E+00\n# symfunction_short  O  890  O   H   -6.00E+00    0.00  180.00  6.00E+00\n# symfunction_short  O  890  O   H   -6.00E+00    0.00  120.00  6.00E+00\n# symfunction_short  O  890  O   H   -6.00E+00   60.00  180.00  6.00E+00\n# symfunction_short  O  890  O   H   -6.00E+00   49.10  169.10  6.00E+00\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 O H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short O 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short O 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short O 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short O 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short O 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short O 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 H H -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  O  890  H   H   -6.00E+00  -90.00   90.00  6.00E+00\nsymfunction_short O 22 H H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short O 22 H H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short O 22 H H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short O 22 H H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short O 22 H H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short O 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \nsymfunction_short H 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short H 22 C O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C O -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C O -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 C O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short H 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short H 22 O O -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 O O -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 O O -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 O O -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 O O -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 O O -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 O O -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  H  890  O   O   -6.00E+00  -90.00   90.00  6.00E+00\n# symfunction_short  H  890  O   O   -6.00E+00   90.00  270.00  6.00E+00\nsymfunction_short H 22 O O -6.00E+00 6.00E+00 0.00 180.00 p2a\n# symfunction_short  H  890  O   O   -6.00E+00    0.00  120.00  6.00E+00\n# symfunction_short  H  890  O   O   -6.00E+00   60.00  180.00  6.00E+00\n# symfunction_short  H  890  O   O   -6.00E+00   49.10  169.10  6.00E+00\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 O O 5.00E+00 1.50E+01 49.10 169.10 p2a\n \nsymfunction_short H 22 O H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 O H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 O H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 O H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 O H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 O H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 O H -8.00E+00 8.00E+00 49.10 169.10 p2a\n# symfunction_short  H  890  O   H   -6.00E+00  -90.00   90.00  6.00E+00\nsymfunction_short H 22 O H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 O H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 O H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 O H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 O H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 O H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short H 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \n"
  },
  {
    "path": "examples/potentials/Anisole_SCAN/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0770318149875953E+01   1.9986398163731312E+01   1.5743821889794004E+01   1.1811294669196695E+00\n         1          2   7.8312775891892521E+00   1.9026924919587330E+01   1.4627464272348128E+01   1.3991210665860847E+00\n         1          3   5.2287534502987143E-01   3.8141380911012730E+00   2.1103743851065158E+00   4.9579949887052388E-01\n         1          4  -1.5543122344752192E-15   1.6579324287122832E-01   9.7841041210104777E-03   1.2416965578542126E-02\n         1          5   8.4632164887299410E-07   4.4379506330220853E-01   5.4373317731267461E-02   5.5899533822951500E-02\n         1          6   2.4394543912101829E-02   4.3142690427210102E+00   1.3623025761500003E+00   7.7237303355901965E-01\n         1          7   6.8706479057903946E-03   1.3131159448690370E+00   3.2700091023303485E-01   2.0503436165401862E-01\n         1          8   1.0764675633144916E-01   2.3291770324719794E+00   8.9267237397895693E-01   3.5317824974029721E-01\n         1          9   1.4002302154398407E+00   1.1823007840905614E+01   6.2160038099819497E+00   1.2813554811197465E+00\n         1         10   5.3477351451739341E-01   3.5853960625993455E+00   1.7886120377963679E+00   4.8170446482741447E-01\n         1         11   6.6938877197329925E+00   2.2780154923081366E+01   1.4782862949083480E+01   2.0707727502900801E+00\n         1         12   1.3710541859538115E+00   5.2505979592825911E+00   3.0846141976198549E+00   5.9443102844654661E-01\n         1         13   1.5294754831709664E+01   3.7168763545438878E+01   2.5581652815073703E+01   2.5858200899069512E+00\n         1         14   1.2477248736782487E-01   3.2139666520467502E-01   2.2970627086661496E-01   1.8189956271748162E-02\n         1         15   2.4905992117991849E-01   5.1266970165686565E-01   3.8621741665909887E-01   2.4695561666683425E-02\n         1         16   9.1801484475507888E-01   3.7779547390997159E+00   1.6779701612264089E+00   4.3215618195327871E-01\n         1         17   4.8661658599089908E-01   1.2464130664796027E+00   7.5090321062817023E-01   9.8266020690496919E-02\n         1         18   7.0400649123739278E-01   2.4455378972814081E+00   1.2721638193766069E+00   2.4653618676208328E-01\n         1         19   6.8332227390056133E-01   1.3437659977418182E+01   5.4176102967321000E+00   1.5869769209226949E+00\n         1         20   9.3159811724544406E-01   3.9761713203949642E+00   2.0763674220555082E+00   4.3227796058287543E-01\n         1         21   3.9381864829255417E+00   2.3315215132150293E+01   1.3615207680921213E+01   2.3955922018341669E+00\n         1         22   1.4629405570046021E+00   5.8816319844481075E+00   3.2515379213034152E+00   6.1714112456700509E-01\n         1         23   9.6939336001263943E+00   3.7833644465588371E+01   2.2462397581257605E+01   3.7382525941196265E+00\n         1         24  -1.7763568394002505E-15   2.3772083001581290E-02   4.5574528426809303E-04   8.4339525841937448E-04\n         1         25  -1.3322676295501878E-15   8.6562277422057909E-02   6.1653384914609685E-03   8.2740351239212282E-03\n         1         26  -1.7763568394002505E-15   1.4100891851342134E+00   2.5526522806996405E-01   2.5588897734458743E-01\n         1         27  -1.7763568394002505E-15   3.4737367978637013E-01   5.6028203142713374E-02   5.6676976983962048E-02\n         1         28  -1.7763568394002505E-15   7.0475929803101289E-01   1.5718079528286294E-01   1.2992173607677063E-01\n         1         29  -6.6613381477509392E-16   3.1532460601819374E+00   9.3536514194868059E-01   6.0612705388964983E-01\n         1         30   1.5217856355420611E-04   1.0734899430352809E+00   2.9802357783586103E-01   2.0608975869846163E-01\n         1         31   7.1599490789923115E-03   5.5610710668407730E+00   1.7639889122304782E+00   8.4913036627713445E-01\n         1         32   5.6970389119334053E-03   1.4409094458787184E+00   4.8152001401516226E-01   2.7249634580370724E-01\n         1         33   8.8369361932250423E-02   7.5425872037501200E+00   3.2324969019432173E+00   1.1371343181324518E+00\n         1         34   8.2462306757590866E+00   2.8131309654034975E+01   1.7583309322271525E+01   2.7005875435417090E+00\n         1         35   2.4810270446417945E+01   8.3490428787600052E+01   5.1620630730954467E+01   7.8229298428358893E+00\n         1         36   3.8213403872742390E+01   1.3399268389366674E+02   8.3246853700356624E+01   1.2511495098191897E+01\n         1         37   2.5021268785945132E+01   9.2397701025516398E+01   5.7272511119926826E+01   8.6213290037298904E+00\n         1         38   2.2382339587123724E+01   8.5219923089860103E+01   5.2534552017576075E+01   7.9141348319530103E+00\n         1         39   8.0370241695844733E+00   3.2601601950582371E+01   2.0057198216375767E+01   3.0702602026469581E+00\n         1         40   1.6931535944862880E+01   5.6926564890258909E+01   3.7240473570311671E+01   4.7996180186619348E+00\n         1         41   4.0370492753359905E+01   1.5410483087625499E+02   9.8248656902031058E+01   1.4373967265800120E+01\n         1         42   6.0192683916505828E+01   2.4432953738558845E+02   1.5662973142499033E+02   2.2959395052994211E+01\n         1         43   3.9262302330503424E+01   1.6810298743867904E+02   1.0706582546429206E+02   1.5831911907435323E+01\n         1         44   3.5116594977863414E+01   1.5265580990243916E+02   9.7952251583358944E+01   1.4450444578712318E+01\n         1         45   1.1673995895577544E+01   5.9724259491508924E+01   3.7109991415166355E+01   5.5768149391062281E+00\n         1         46   1.0023330902681222E+00   1.1018150106971305E+01   5.4389215137885794E+00   1.4347579555551704E+00\n         1         47   3.0023752082446449E+00   2.9319739423061648E+01   1.4454614912557457E+01   3.9515939375152818E+00\n         1         48   4.4790551699643633E+00   4.5130417192290643E+01   2.2620748561081665E+01   6.0983333793997243E+00\n         1         49   2.8443760013673307E+00   3.0439954665741482E+01   1.5282937103388720E+01   4.1299452901682825E+00\n         1         50   2.6787250892029832E+00   2.7767190694014843E+01   1.3997588949576697E+01   3.8079081624772653E+00\n         1         51   1.1234250425775465E+00   1.1440947317424198E+01   5.3542205933772751E+00   1.5089020912310827E+00\n         1         52   5.9623853546519481E+00   2.9745510915059722E+01   1.7393370201945430E+01   2.9639834287452183E+00\n         1         53   1.2452345268593449E+01   7.3038089055790920E+01   4.1894061392626533E+01   8.0818649939351612E+00\n         1         54   1.9214002650447274E+01   1.1662543448321061E+02   6.9572298302767308E+01   1.3706892801651017E+01\n         1         55   1.2503287178082664E+01   8.6095623597928807E+01   4.8965357813195126E+01   1.0090617512341291E+01\n         1         56   1.0722871603838465E+01   7.9870675361271097E+01   4.5142560174570939E+01   9.2847750886499298E+00\n         1         57   3.4010841446956124E+00   3.1639561628297159E+01   1.7370383938901863E+01   3.6947401150542811E+00\n         1         58   1.3457874073380038E+00   9.6584542522569308E+00   5.2617009319517640E+00   1.2486638117293218E+00\n         1         59   2.1097632571102398E+00   2.5263460375296415E+01   1.2916669268854649E+01   3.3676066832457940E+00\n         1         60   3.4708533375902597E+00   4.0514761912452641E+01   2.0609412772851503E+01   5.3780915323067608E+00\n         1         61   2.5075666662412552E+00   2.9767124572793993E+01   1.4135657918879614E+01   3.8360059105354818E+00\n         1         62   2.3978670830272164E+00   2.7910683974979150E+01   1.2975661589425545E+01   3.4995598981769214E+00\n         1         63   7.6458186209218426E-01   1.0060858125847639E+01   4.9882380253470195E+00   1.4276024237913671E+00\n         1         64   3.2259144583412377E-03   5.7339332488173567E-01   1.4306397927264281E-01   8.8608699648347597E-02\n         1         65   2.7736049077714441E-02   2.6579677980696803E+00   6.9754204374623163E-01   3.7478277834420881E-01\n         1         66   7.0684973204101331E-02   4.5755775380305019E+00   1.3150951302257565E+00   6.5981115172504401E-01\n         1         67   5.4367825162013592E-02   3.6111397565896737E+00   9.7985203575016511E-01   5.2184210313273549E-01\n         1         68   6.1841511600480764E-02   3.4094899831583714E+00   9.1239056796207818E-01   4.8747914093795097E-01\n         1         69   5.6402190304026059E-03   1.4520326469856797E+00   3.5598345619981375E-01   2.1568868274501576E-01\n         1         70  -6.2374004893334783E-18   4.3317346978946911E-03   2.1932430749888008E-04   2.9467086108696993E-04\n         1         71  -1.1438218586901202E-17   2.3046417967650654E-02   1.1706503041916693E-03   1.6449383128655502E-03\n         1         72  -3.9138868240349145E-19   5.3056544542124502E-02   1.2621828441503841E-03   2.0392994300200110E-03\n         1         73  -1.8491215289180094E-23   4.9023037230443725E-02   4.5924166028450257E-04   1.2247836523162992E-03\n         1         74  -7.2134845708393115E-17   4.9255603715700286E-02   4.2079293955527182E-04   1.2485277865039051E-03\n         1         75  -4.2323800755455422E-17   2.5137402943928397E-02   2.0864555207279317E-04   7.1148898235901220E-04\n         1         76   8.9418760595812121E-10   5.0831265062803034E-02   4.9834013413530900E-03   5.5395192451946924E-03\n         1         77   1.0494421437996694E-06   2.5431064818323201E-01   2.7068951090151679E-02   3.0556751563398481E-02\n         1         78   3.2179583527709046E-06   5.1623301660783016E-01   3.6689503056634064E-02   4.2619121691922564E-02\n         1         79   1.3841653842051163E-06   4.5440278667915651E-01   1.9920244367306647E-02   2.6621413667699337E-02\n         1         80   7.3093203434029042E-07   4.3093190644247298E-01   1.8927741650750510E-02   2.6300969752112893E-02\n         1         81   9.2637619487239718E-09   1.9615125468370415E-01   8.4498321711642902E-03   1.3345960877120564E-02\n         1         82   2.1774466101503638E-04   2.2602282086933029E-01   3.4328847199264614E-02   2.7445014317132668E-02\n         1         83   1.6082467432423297E-03   1.0278434179472808E+00   1.6349625516832617E-01   1.3337457064443639E-01\n         1         84   3.2647890377054492E-03   1.6668221261738243E+00   2.5666834994730897E-01   2.0246955310806941E-01\n         1         85   1.9390788768481782E-03   1.4187278825343281E+00   1.6566794865111717E-01   1.3365663685310258E-01\n         1         86   1.5910162593839004E-03   1.3071037552025035E+00   1.5698083210250496E-01   1.2894055829983656E-01\n         1         87   2.2948689179983427E-04   5.7296654270264336E-01   6.5298174626826785E-02   6.0121883495873406E-02\n         1         88   1.1327621784634290E-01   8.3045563652164383E+00   2.0943990569976267E+00   1.0218542897588423E+00\n         1         89   3.3370613510673158E-01   2.9453497292036595E+01   7.5877530824612389E+00   3.4109404950038580E+00\n         1         90   4.7988518927896195E-01   4.5660257302987425E+01   1.2637059872280588E+01   5.3778903087750551E+00\n         1         91   2.5775942414330383E-01   3.0532850369921658E+01   8.8551248167813821E+00   3.7434375700289295E+00\n         1         92   2.6123078884028328E-01   2.8390268043629735E+01   8.1706989431009660E+00   3.4173361669359688E+00\n         1         93   7.6890317232756175E-02   1.1503636136151936E+01   3.1270580184191670E+00   1.3684376161777125E+00\n         1         94   9.8619138473020306E-03   7.1512320230830972E-01   1.5929985005464631E-01   8.9061613834491737E-02\n         1         95   4.2708856676889201E-02   2.5945888498940120E+00   6.2928743842250778E-01   3.5749504062968335E-01\n         1         96   7.1382360407220194E-02   4.1294697970582952E+00   1.0318579765799314E+00   5.6205462834461606E-01\n         1         97   4.8485102483644640E-02   3.0682392304483188E+00   7.0270610075178364E-01   3.8109396274199092E-01\n         1         98   4.2982508668804750E-02   2.7812729531227500E+00   6.5835563695387112E-01   3.6057606040887158E-01\n         1         99   1.0305314920747077E-02   1.2836559468232112E+00   2.6314071553691487E-01   1.5792461750625936E-01\n         1        100   2.6795277697586091E+00   3.7483923873874772E+01   1.4558399796789585E+01   4.3217073571883597E+00\n         1        101   9.6861712985647603E+00   1.1079249709138742E+02   4.5755874983565917E+01   1.2920257848346751E+01\n         1        102   1.4602609037671213E+01   1.7421990484882818E+02   7.3729573762831834E+01   2.0668512730675921E+01\n         1        103   9.4814690533414847E+00   1.1973218870187333E+02   5.0597636079669449E+01   1.4253762328980228E+01\n         1        104   8.5058331373421225E+00   1.0943031578033759E+02   4.6341929165007045E+01   1.3106613048889903E+01\n         1        105   2.9741105811066335E+00   4.0793548760149861E+01   1.7629616989937688E+01   5.0598468249510669E+00\n         1        106   9.3198014095011453E-02   1.8646283811502087E+00   5.4440304534609596E-01   2.1781056048893171E-01\n         1        107   3.1864613522519958E-01   5.4161859740604319E+00   1.8888416360851201E+00   7.6264264692602912E-01\n         1        108   5.5570661971605728E-01   8.5383677428330902E+00   3.1087163360886203E+00   1.2110633017081061E+00\n         1        109   3.8217936156556126E-01   6.1354008965889211E+00   2.1460414184138812E+00   8.2878282155774807E-01\n         1        110   3.4386186649561573E-01   5.7027035595026847E+00   1.9916190831293090E+00   7.7329764916945687E-01\n         1        111   9.1490542162076582E-02   2.7215498328821832E+00   7.7880625409665438E-01   3.2395774171899855E-01\n         1        112   1.6531386252622308E+01   1.0152504027161164E+02   4.7514745292601489E+01   9.9017413881682721E+00\n         1        113   4.8968388988984174E+01   2.9121194650532118E+02   1.3829099779888946E+02   2.8230738162769132E+01\n         1        114   7.6329120816769134E+01   4.6466980123929432E+02   2.2086375515410890E+02   4.4968692071886515E+01\n         1        115   5.1249370212032915E+01   3.1827602373954085E+02   1.5126341884851288E+02   3.0888363761516239E+01\n         1        116   4.6913869832124554E+01   2.9009237025303764E+02   1.3864440478931155E+02   2.8310681193931000E+01\n         1        117   1.9597393807129524E+01   1.0986942732597737E+02   5.2931971015194144E+01   1.0858089969763240E+01\n         1        118   1.2152370911691392E-07   5.2265742615602455E-02   1.0069020600744980E-02   1.3036533397304307E-02\n         1        119   2.4459580901221437E-07   8.1328928871128969E-02   1.0725523562561625E-02   1.2871660148616289E-02\n         1        120   1.4821427439506633E-07   1.1443843270033990E-01   8.6493593302056828E-03   8.6311206056388784E-03\n         1        121  -5.6483120918067203E-16   1.0231106970138439E-01   3.9510452328287930E-03   6.6364854362518672E-03\n         1        122  -5.6690117799857142E-16   1.1135049197957866E-01   4.1740456396089243E-03   7.1315120163183083E-03\n         1        123  -1.0593587831838508E-16   8.5274708390060294E-02   1.7585622959728488E-03   4.4294017486752983E-03\n         1        124   2.0041898963602668E-03   3.0462458283923632E-01   7.6346878619169792E-02   7.8516570557692872E-02\n         1        125   3.7848514420379471E-03   4.4030055603436230E-01   1.0905601483159978E-01   6.7622411634581117E-02\n         1        126   2.7669441344468715E-03   6.3917475127430268E-01   1.2723446389170617E-01   6.4830615646937623E-02\n         1        127   2.9630171901262610E-06   5.6197480815094336E-01   7.6283777915212431E-02   6.0043336923884888E-02\n         1        128   2.7199277339843227E-06   5.8105656826759322E-01   7.4225051064060507E-02   6.1212009896402887E-02\n         1        129   2.5875766924341708E-08   3.8073237701940543E-01   2.8434007672895282E-02   3.3570355158285228E-02\n         1        130   3.7609816347695113E-02   7.7843858610943606E-01   2.4709999260446422E-01   1.5993842727120319E-01\n         1        131   7.6729087245930028E-02   1.4196809169059283E+00   4.6701056450601114E-01   1.5366501741456301E-01\n         1        132   8.2952905630474846E-02   2.4149650732222967E+00   6.8474455181594662E-01   2.5833742481719885E-01\n         1        133   3.5267352723956352E-03   2.0418281512541823E+00   4.6198911226251327E-01   2.3277456622475548E-01\n         1        134   3.3110006952649430E-03   2.0002611450545733E+00   4.3283126514287384E-01   2.2703716393230650E-01\n         1        135   3.8308693622682598E-04   9.4769342375777110E-01   1.6047567623294595E-01   1.1260598477272853E-01\n         1        136   3.1954782567957662E-01   1.5776925537844500E+01   5.7669983909176166E+00   2.0512915931859421E+00\n         1        137   7.5450753528668091E-01   4.7632674324532765E+01   1.3925376083334463E+01   5.9254825512190870E+00\n         1        138   8.2069958737773074E-01   7.4689567830423243E+01   2.3199352136795635E+01   9.6887177124693977E+00\n         1        139   3.2859444950928068E-01   5.2380898649259180E+01   1.6394041354593227E+01   6.9055195614356206E+00\n         1        140   3.1181469531260941E-01   4.4956056489679696E+01   1.4771842334102876E+01   6.1835885621115478E+00\n         1        141   7.9333979944650329E-02   1.7186788066409836E+01   5.3768531231560130E+00   2.3341680208180509E+00\n         1        142   1.9648714794188082E-01   1.5688995005843331E+00   6.6137286769311865E-01   2.3786089846268693E-01\n         1        143   5.1221895577866394E-01   4.1121186212903806E+00   1.5042117660025605E+00   3.9616174272653926E-01\n         1        144   4.3904635208661275E-01   6.7837815934718257E+00   2.4124794960172755E+00   7.6522053246854038E-01\n         1        145   8.1922434405018910E-02   5.2032404170208864E+00   1.6847841174678806E+00   6.3321490996819840E-01\n         1        146   7.7521108725653362E-02   4.9287301604198817E+00   1.5530434886712003E+00   5.9687334602637987E-01\n         1        147   1.5915564667138976E-02   1.9546030000174897E+00   5.7288136729457106E-01   2.6766251669505281E-01\n         1        148   8.4097101846191720E+00   7.5597518103614433E+01   3.3250725463031998E+01   7.9744345621289066E+00\n         1        149   1.6224043521765932E+01   2.0060910494258761E+02   8.6318270391028378E+01   2.2518359076840422E+01\n         1        150   2.8195767208650128E+01   3.0862826179464707E+02   1.3689887451533019E+02   3.5058142340561687E+01\n         1        151   2.0341009194300554E+01   2.0643261016892305E+02   9.2955071596663572E+01   2.3747396675826725E+01\n         1        152   1.7559393193182078E+01   1.8876524477375509E+02   8.5177200954685446E+01   2.1772971874490867E+01\n         1        153   4.1690097670032165E+00   7.4960766695340908E+01   3.2513713810941887E+01   8.4751165999800335E+00\n         1        154   7.2923008261745248E-01   3.2550080151893850E+00   1.6539163160612629E+00   3.7572399598979667E-01\n         1        155   1.5092301739014640E+00   9.3187091618107374E+00   4.1220216609884099E+00   9.8715306804584757E-01\n         1        156   1.5056613693099841E+00   1.6113832483161740E+01   6.7235072167829681E+00   1.8046438451129481E+00\n         1        157   6.4690411294584482E-01   1.1483604083382872E+01   4.6943319337704459E+00   1.3940979831078544E+00\n         1        158   5.9690450114477200E-01   1.0163227996675404E+01   4.2981940621687702E+00   1.2874338770256830E+00\n         1        159   1.1970829685362548E-01   3.9000889726093733E+00   1.5930689419664921E+00   5.3500368917553243E-01\n         1        160   2.9541673135164832E+01   1.7956505264559704E+02   9.4233007113744449E+01   1.9207833490125875E+01\n         1        161   7.8466958661931827E+01   4.8055826494351561E+02   2.4477082141349300E+02   5.0879432649094198E+01\n         1        162   1.2414941499339503E+02   7.6316847899069273E+02   3.8873584114390383E+02   7.9944611533586354E+01\n         1        163   8.0405677866192534E+01   5.2134615684113589E+02   2.6581721407254992E+02   5.4678262150570191E+01\n         1        164   7.4634807471521285E+01   4.7528202973617630E+02   2.4387092268516506E+02   5.0243814964774508E+01\n         1        165   2.8470350889835405E+01   1.7994297409160947E+02   9.2817237463201536E+01   1.9352816642770065E+01\n         1        166  -1.1848436914858111E-17   8.9009857217323338E-03   6.1293284923072671E-04   8.7168795335746069E-04\n         1        167  -1.2015749556800137E-17   1.0130173922777663E-02   5.8388995696158222E-04   8.6362698466414855E-04\n         1        168  -1.2985772917813876E-17   8.0997458075157038E-03   1.4029428054841033E-04   2.9729062311109806E-04\n         1        169  -1.2593053555347082E-17   7.0567169327866086E-03   6.5259189123179933E-05   2.2304815668721219E-04\n         1        170  -2.2588863879013769E-17   4.7778173753099855E-03   2.7876783979929873E-05   1.3165679419191833E-04\n         1        171  -2.7103098933058901E-16   2.3766710708078127E-02   2.9378222367593223E-03   3.4995128092543035E-03\n         1        172  -4.2027072196860628E-16   1.5114342726094493E-01   2.1351943012046463E-02   2.6619812702909914E-02\n         1        173  -5.2856472166402743E-16   1.8629785653965808E-01   2.2235896092200124E-02   2.7740024632666924E-02\n         1        174  -2.8953948008639497E-16   1.3609778207672604E-01   7.2828285816926739E-03   1.0528689064650917E-02\n         1        175  -1.7461686218799382E-16   1.2333659922841630E-01   4.9046842579432278E-03   8.2512114789903297E-03\n         1        176  -1.3984948167886373E-16   5.9646143074191083E-02   2.0972424057325518E-03   4.5178341862623242E-03\n         1        177  -1.1629224144565324E-16   1.1103865245242017E-01   1.7713789051717346E-02   1.7185175512937488E-02\n         1        178  -4.8768602191517616E-16   6.6396138628631540E-01   1.1228612736258256E-01   1.2242209111690140E-01\n         1        179  -1.1549643570420682E-15   8.6998487698736837E-01   1.3242193593986573E-01   1.3854018305683574E-01\n         1        180  -9.1661402142886631E-16   5.8311219891437838E-01   5.8472054251598245E-02   6.2268459395751138E-02\n         1        181  -8.4738455496057840E-16   5.6022160182620906E-01   4.7398091146176463E-02   5.2262347906107814E-02\n         1        182  -1.5216116031280500E-16   2.6728364211818134E-01   1.9456993348504866E-02   2.6451263797231766E-02\n         1        183  -5.5302595796431788E-16   4.6651873395875327E+00   7.6909735850328687E-01   6.1648173691501940E-01\n         1        184  -2.9027787117986680E-15   1.3804010329500246E+01   2.5968061245462728E+00   1.8636732831002352E+00\n         1        185  -3.6502171249638293E-15   1.7964105748489615E+01   4.0281018617082278E+00   2.7936885987751228E+00\n         1        186  -1.8431118408104498E-15   1.2277178752171039E+01   2.7103656977299622E+00   1.9407644882074722E+00\n         1        187  -1.3286955774162453E-15   1.2004442777720838E+01   2.5291743355617133E+00   1.8217269973617438E+00\n         1        188  -6.8905495876393187E-17   4.7710669452929295E+00   9.5557441333226800E-01   7.2784654846627661E-01\n         1        189   2.1638294884443980E-05   3.0376921083261915E-01   6.7693096069933539E-02   5.0988507447609063E-02\n         1        190   8.3544004308620990E-05   1.5512838067556292E+00   3.3173736784806074E-01   3.0129809262072244E-01\n         1        191   1.2713261653773589E-04   2.2523338664821662E+00   4.3528671080786330E-01   3.7255612924423231E-01\n         1        192   4.4610837853624061E-05   1.5405481366005049E+00   2.3290161226386707E-01   1.9375445777335393E-01\n         1        193   4.2696017045032018E-05   1.3939044550492212E+00   2.0320769767244087E-01   1.7020887190083797E-01\n         1        194   1.8481569575251545E-05   6.8977849059845231E-01   8.0839185639507441E-02   7.9608943152934750E-02\n         1        195   2.0507302384727047E-02   1.4428390047148968E+01   4.2471849773414512E+00   2.1473454583006570E+00\n         1        196   4.7418491980313074E-02   3.6914526365739619E+01   1.1181869993841593E+01   5.7047006671757163E+00\n         1        197   6.8070838738142861E-02   6.0435522001861777E+01   1.7601459785057873E+01   8.9045172962186800E+00\n         1        198   4.2721245114197233E-02   4.2564830351571736E+01   1.2017010394988983E+01   6.1287680557567921E+00\n         1        199   3.7321898107842456E-02   3.9115799781401520E+01   1.1015042064683902E+01   5.6427058826835390E+00\n         1        200   1.5705056992766524E-02   1.4218103757441645E+01   4.2287567914021258E+00   2.2335729792188630E+00\n         1        201   1.4695863642724398E-03   7.2132465108210375E-01   2.0672220383389153E-01   1.2189503966229270E-01\n         1        202   5.6141504233920723E-03   2.9220514545754477E+00   7.8862378714698200E-01   5.7107396151348511E-01\n         1        203   7.5366075204429317E-03   4.4494559564896230E+00   1.1146430967543648E+00   7.6131000191571485E-01\n         1        204   3.6789424554416628E-03   3.0317906856812291E+00   6.6636163644726731E-01   4.3808273253418528E-01\n         1        205   3.6466010608769508E-03   2.6903619267099073E+00   5.9812633097382728E-01   3.9425900259000507E-01\n         1        206   1.7070620138373745E-03   1.3608846201739351E+00   2.3340608455587861E-01   1.7352915593961865E-01\n         1        207   3.6155260424126623E-01   3.7017017531650090E+01   1.3540828477785897E+01   5.0609540678117044E+00\n         1        208   9.4909047785280287E-01   9.5162345183920010E+01   3.5022731034642987E+01   1.3025741382532960E+01\n         1        209   1.3837148347347041E+00   1.5056385241623857E+02   5.5790855562789964E+01   2.0567682439239288E+01\n         1        210   8.6723409361975856E-01   1.0527726240242093E+02   3.8260397354562485E+01   1.4119806037506219E+01\n         1        211   8.0076038099326297E-01   9.6583839881220953E+01   3.5107657641297479E+01   1.2970062214109774E+01\n         1        212   2.9548144546513727E-01   3.8363713918580679E+01   1.3352499746537719E+01   5.0005234769351636E+00\n         1        213  -4.3000975313373299E-16   1.4970235613521284E-02   3.3229490889538746E-03   2.6988336124648513E-03\n         1        214  -4.0598359456622110E-16   2.2396547721997718E-02   3.1659370389059524E-03   2.5832496518005264E-03\n         1        215  -4.0195162322780411E-16   2.4771250700016966E-02   1.6433500791575165E-03   1.3239952533196319E-03\n         1        216  -4.2579480156484828E-16   2.4704502988387264E-02   1.8155578163881223E-04   5.5134048902809112E-04\n         1        217  -4.0583805475647870E-16   2.4470190895643333E-02   1.8599919547246664E-04   6.2166053036710766E-04\n         1        218  -6.3909108264545264E-16   2.8875879499062604E-02   1.1925630027341996E-04   6.1250047851503693E-04\n         1        219   7.3255479742123241E-05   1.3189328703304892E-01   5.3000156366609132E-02   4.0042565542700401E-02\n         1        220   5.0679887366284870E-05   1.8827820705368936E-01   5.7677053995509944E-02   3.7530017711271887E-02\n         1        221   2.1267002843113076E-05   3.3804058224403977E-01   4.2369858543345983E-02   2.5407089634032827E-02\n         1        222   0.0000000000000000E+00   2.9512295332674587E-01   1.5006194900413047E-02   1.6895407912780058E-02\n         1        223  -2.7302858178001829E-19   2.5501513125914987E-01   1.4513950862696041E-02   1.8258963982074800E-02\n         1        224  -1.4581876722379970E-16   2.5862683019007265E-01   7.4645000848107207E-03   1.3899313891801929E-02\n         1        225   6.1062965959253904E-03   5.2024057158259585E-01   1.9918250626563580E-01   1.3557719423266895E-01\n         1        226   4.1814483428114233E-03   8.1776210105984470E-01   2.4841383263632225E-01   1.3014349079675774E-01\n         1        227   2.5590837051746342E-03   1.3199556561403507E+00   2.6095250096932399E-01   1.3707702905729788E-01\n         1        228   4.1186264653910376E-04   1.0458855587979277E+00   1.4268192048687262E-01   1.0668138184756649E-01\n         1        229   1.5457103733667005E-04   1.1118613205853334E+00   1.3875536593111648E-01   1.1277732870219868E-01\n         1        230   4.9021287046954801E-06   8.7753074270569575E-01   6.5340600383226491E-02   7.4741042881604297E-02\n         1        231   5.3451998165513936E-02   1.3722614207889087E+01   2.8110476150328205E+00   1.6452005325782018E+00\n         1        232   4.4434038916910244E-02   3.2607793048948054E+01   5.1612383538240021E+00   3.3027559240380091E+00\n         1        233   6.6893413720019723E-02   5.7945920745276460E+01   8.8058428750733633E+00   5.6088401648719994E+00\n         1        234   2.4239589213376406E-02   4.3327056370631851E+01   6.4014188927810398E+00   4.2792268578420281E+00\n         1        235   3.2025535247987014E-02   4.1615620921024224E+01   6.1329985990220219E+00   4.1066638222379863E+00\n         1        236   7.6381284733007828E-04   1.3111071878297237E+01   2.4987016271359206E+00   1.8233122722230599E+00\n         1        237   3.8927012875684681E-02   1.3601037242170322E+00   5.2191108385165441E-01   3.0233680993856527E-01\n         1        238   4.1091311635999279E-02   2.4330785717461167E+00   7.3130333326035568E-01   3.1907409070760351E-01\n         1        239   4.5319841202538971E-02   4.4901400842656169E+00   9.8149544150482171E-01   4.5746721636142462E-01\n         1        240   1.3490140904256312E-02   3.6928602344745114E+00   6.3640062962135868E-01   3.6508286936081719E-01\n         1        241   1.2598408948273783E-02   3.6172964439095692E+00   6.1453783808074280E-01   3.7403397674381633E-01\n         1        242   8.8826803100064064E-04   2.0295108836003597E+00   2.7046268016259550E-01   2.1814504494226578E-01\n         1        243   1.8759755379521450E+00   4.1774794902115673E+01   1.4528658438776793E+01   4.9750208746846702E+00\n         1        244   2.9542045694139185E+00   1.0899750956958944E+02   3.5926645693474185E+01   1.3258192891276828E+01\n         1        245   3.8304878966649492E+00   1.7792731663356429E+02   6.0915297522147412E+01   2.2007042956571190E+01\n         1        246   2.2789732056899221E+00   1.2645444370768000E+02   4.3349665806191290E+01   1.5814726283403534E+01\n         1        247   2.1294848951226468E+00   1.1913070248320449E+02   3.9699403435023406E+01   1.4312492268882965E+01\n         1        248   6.6756549939528098E-01   4.3693275919329992E+01   1.5055529966193294E+01   5.4585910288840953E+00\n         1        249   1.7722206788910308E-01   2.7040536880764821E+00   1.1573280402547617E+00   5.4092630771256778E-01\n         1        250   1.8412595675254104E-01   5.6141175802178500E+00   1.8623374306036700E+00   6.8510697112792673E-01\n         1        251   2.7260477341066441E-01   1.0824524222237070E+01   2.8439395662717581E+00   1.1275498049626269E+00\n         1        252   1.1354458880225779E-01   8.6505247088905648E+00   1.9653679014177534E+00   8.9589551275207047E-01\n         1        253   1.0904004720122391E-01   8.3979833194155873E+00   1.8728450533617604E+00   8.9159828736555979E-01\n         1        254   1.5420453962276939E-02   3.8791351746354166E+00   7.8294377734526877E-01   4.6500546676739390E-01\n         1        255   7.5661177794389554E+00   1.0137991761355863E+02   3.9975695133170987E+01   1.2470111894942587E+01\n         1        256   1.5749658322885811E+01   3.0212642568924912E+02   1.0501132337324783E+02   3.5927719146810936E+01\n         1        257   2.9359724892100107E+01   4.8206417334141508E+02   1.7034570441585672E+02   5.8182189299795354E+01\n         1        258   2.0394873343867829E+01   3.2654394940794083E+02   1.1718980461023428E+02   4.0215808756470835E+01\n         1        259   1.8616438114919038E+01   2.9920713076019598E+02   1.0728266208625732E+02   3.6894493238629785E+01\n         1        260   6.3867043023256223E+00   1.1669661054232476E+02   4.0664641161206035E+01   1.4261335462615461E+01\n         1        261  -2.1148880698555696E-17   9.7091160297992831E-03   1.1903931781245534E-03   1.6205253345015953E-03\n         1        262  -2.5961668340350929E-16   2.4734997461048732E-02   1.7937221884292947E-03   2.5404424424614411E-03\n         1        263  -4.8058010279700336E-16   2.5171551563703671E-02   1.0317986855025135E-03   1.4651469685379639E-03\n         1        264  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-1.0225638544993166E-15   1.3518273758444476E+01   1.9976102909659905E+00   1.6256331969142730E+00\n         1        281  -7.0972833662419045E-16   2.1568706622359496E+01   3.2228226140946572E+00   2.6686529734490865E+00\n         1        282  -2.6521067045062343E-16   1.5766092992197748E+01   2.3122045757250489E+00   2.0333564693392243E+00\n         1        283  -1.7635518551726226E-16   1.4684408153666491E+01   2.1478584141871915E+00   1.8606953439049330E+00\n         1        284  -6.2859702648111543E-19   5.2658939024659928E+00   8.1377805831736183E-01   7.7940575895957687E-01\n         1        285   9.8960743064583037E-05   5.8144130349883061E-01   1.5517155810119362E-01   1.2376205352778050E-01\n         1        286   7.0121008496359854E-05   1.3982261270486775E+00   2.8477555931360926E-01   1.9930619983507467E-01\n         1        287   8.2383214902720809E-05   2.1196618214372385E+00   3.4170901709766560E-01   2.3998228579228495E-01\n         1        288   3.8195204102453020E-05   1.4032576394796905E+00   1.9723596634074936E-01   1.6857030916332894E-01\n         1        289   3.7864902327405356E-05   1.2764188742268572E+00   1.8674153384592607E-01   1.6383800911802235E-01\n         1        290   8.6671479554384641E-06   9.4314124574518388E-01   7.9342689558002721E-02   9.4413814190556805E-02\n         1        291   1.4120258745390146E-02   1.4389927509398794E+01   4.1363670761429763E+00   2.1955971286058307E+00\n         1        292   5.1475185128733864E-02   3.6254220974183504E+01   9.9371214973091941E+00   5.3973477079602210E+00\n         1        293   8.1432721679340500E-02   5.7243352005477213E+01   1.6138993911944223E+01   8.6342018161577982E+00\n         1        294   5.3456264770985383E-02   4.0040748403411385E+01   1.1119609088266834E+01   6.0594409118378030E+00\n         1        295   5.2293397131346134E-02   3.6352980691073647E+01   1.0150769674881372E+01   5.5303562547169038E+00\n         1        296   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-1.6787227806912034E-16   2.8416073762637984E-02   1.9195361895907168E-04   8.9661390570185259E-04\n         1        313  -1.7764119777771352E-16   2.3061143546043241E-02   1.8584707364104362E-04   8.9586881650174780E-04\n         1        314  -1.6798416521647816E-16   2.1700798654479912E-02   2.0304653537784600E-04   9.5913144385747888E-04\n         1        315  -1.3115279964135579E-16   2.4994377220843599E-02   1.1894458114985284E-04   8.1381080336820203E-04\n         1        316  -1.3177061049622312E-16   1.0969027776753548E-02   4.1353049524839276E-05   2.2871261564803228E-04\n         1        317  -2.7528524562362418E-16   8.6160734040985468E-02   7.6680725990990197E-04   3.0018909236925470E-03\n         1        318  -1.7607390293398846E-16   1.1551389665952154E-01   2.6518922848760809E-03   7.0375825014900063E-03\n         1        319  -1.0668260541984058E-16   9.9960228837551082E-02   2.4649372574469413E-03   6.9402510559031464E-03\n         1        320  -3.2093507783452474E-16   9.4673589497312360E-02   2.5576869443322404E-03   7.2468336265971850E-03\n         1        321  -2.8370748783745319E-16   1.0712697552932823E-01   1.2733738927325931E-03   5.2506212094371877E-03\n         1        322  -8.6051851181298153E-16   4.5420110181390810E-01   5.4581891847823062E-03   2.0158458800118049E-02\n         1        323  -1.8681751270233328E-15   1.9917888667493993E+00   6.9835511204640821E-02   1.6009111758083816E-01\n         1        324  -1.1079320437943234E-15   3.1322870927148956E+00   1.9022511298576653E-01   3.3338776104754742E-01\n         1        325  -9.0841184779847062E-16   2.9716310154867553E+00   1.6528460399347120E-01   3.0743479555007097E-01\n         1        326  -8.4166320600932235E-16   2.9534923451991073E+00   1.6116910760723452E-01   2.9580274869961498E-01\n         1        327  -7.8406824003543401E-16   1.0734353587305678E+00   6.7310462169898985E-02   1.4749263482868955E-01\n         1        328  -2.3700324034380827E-17   3.1238223822295883E-02   4.2281682336613272E-04   1.2669934854046393E-03\n         1        329  -3.1429277342042671E-17   1.7964892540031832E-01   4.8995440882093578E-03   1.1306800548750053E-02\n         1        330   2.0315367224002399E-13   2.5915883489442870E-01   1.4000186208050179E-02   2.4929308631085445E-02\n         1        331   0.0000000000000000E+00   2.4832146503931771E-01   1.2351856455411007E-02   2.3870362876190803E-02\n         1        332  -5.2648558513060306E-17   2.6061724405948949E-01   1.2370962223237900E-02   2.4221783619927193E-02\n         1        333  -5.6327718287287329E-18   2.3775258680342709E-01   5.6287533989128691E-03   1.5540936232544943E-02\n         1        334  -3.6730021725519453E-17   1.3201013164099837E+00   7.6742756276333382E-02   1.1903134842705339E-01\n         1        335   1.2212607424253870E-09   6.2654746902195493E+00   4.9714276036925947E-01   5.9753396613820353E-01\n         1        336   1.2976299860715776E-05   9.4688087487172776E+00   9.5781990256922811E-01   1.0207757876830421E+00\n         1        337   0.0000000000000000E+00   6.1206499535430936E+00   7.1556713090341206E-01   7.8090968199806454E-01\n         1        338   0.0000000000000000E+00   5.7566375825879996E+00   6.5956730493035443E-01   7.2178388932463922E-01\n         1        339   0.0000000000000000E+00   2.5310664911090091E+00   2.4614721432697698E-01   3.0892643571172745E-01\n         1        340   1.9016804904533030E-11   6.2983136379773777E-02   2.2937122245780964E-03   4.3086590994617837E-03\n         1        341   1.0992400221986136E-07   3.0194362082612236E-01   1.9087324900981768E-02   2.9118716904287596E-02\n         1        342   1.9215740083786509E-06   5.2728199957353783E-01   4.6994041773351793E-02   6.0567186736187627E-02\n         1        343   2.2002678965637838E-06   4.9134578878640522E-01   3.9401883024866628E-02   5.5653072954543061E-02\n         1        344   2.6182889584095577E-06   5.1746262483342353E-01   3.8470812332549967E-02   5.5074739509189216E-02\n         1        345   7.4486927914759211E-08   3.9079422367154815E-01   1.6552509356257770E-02   3.1923037063115951E-02\n         1        346   6.8002073953750842E-05   3.1616218405733121E+00   4.4013684688592053E-01   4.0110277190282401E-01\n         1        347   1.0458786395398296E-04   1.1353558726643103E+01   2.0234626083246541E+00   1.5832818310176431E+00\n         1        348   2.1902474908233167E-03   1.8174385224697780E+01   3.4192601816925867E+00   2.5344409423211278E+00\n         1        349   1.6452087369477073E-03   1.3426053514568649E+01   2.3929457933775153E+00   1.8010448428971906E+00\n         1        350   1.3343644056231702E-03   1.2211023766237968E+01   2.1897069374449187E+00   1.6667009374665416E+00\n         1        351   2.1264107590565271E-04   5.2047173609919151E+00   8.2729312537611677E-01   6.9161629317817519E-01\n         2          1   1.2370111408686368E+01   2.1106915763222830E+01   1.6717102025540722E+01   1.1029074323103294E+00\n         2          2   7.9590730670167282E+00   1.7980151488989012E+01   1.3727152659455774E+01   1.3032121764937137E+00\n         2          3   6.5390904532813776E-01   3.6951604406790430E+00   2.0692239750973549E+00   4.5364075001243037E-01\n         2          4   5.5698361138611929E-05   8.2331148431728463E-01   2.6252145241898867E-01   1.8788755283563099E-01\n         2          5   6.9326147389832116E-03   1.2850588009647286E+00   4.4139133332468433E-01   3.0164276627384268E-01\n         2          6   6.9024945296797180E-01   4.4218717391819489E+00   1.9176801842587543E+00   5.8679724393795440E-01\n         2          7   1.4722010659422669E-01   2.2222264323186627E+00   8.5817509786076596E-01   4.3959747385550069E-01\n         2          8   5.7634876296928739E-01   3.2300100744155245E+00   1.4539015078589808E+00   4.8013631495471565E-01\n         2          9   1.6318561665780154E+00   1.2012366767060303E+01   6.1915546248366855E+00   1.4444237174830148E+00\n         2         10   1.2984520227451501E+00   4.5743572758519893E+00   2.3729913394920095E+00   4.9287073468277093E-01\n         2         11   7.4966735937289073E+00   2.3086817023360908E+01   1.5560237349624256E+01   2.0459722463495025E+00\n         2         12   2.3370275435840728E+00   6.2708271678021870E+00   3.7160433386324749E+00   5.2890775352150821E-01\n         2         13   1.5778594842220002E+01   3.6936429044044289E+01   2.5671311521437264E+01   2.6059122410147086E+00\n         2         14  -1.3322676295501878E-15   2.4206174037762840E-01   1.3427071432874801E-01   5.5929481041713178E-02\n         2         15   4.6605013387268635E-05   4.9852575174481706E-01   3.1835455461930129E-01   1.3020438481204638E-01\n         2         16   7.4877699205972759E-02   3.2426085664740025E+00   2.2456019325544858E+00   8.0611298862141512E-01\n         2         17   1.7735519611401962E-02   1.1491288268501287E+00   8.0970209186926678E-01   3.0693532610845292E-01\n         2         18   1.3128974617946443E-01   2.0501235897044916E+00   1.4409235566419056E+00   4.7462707730696974E-01\n         2         19   2.0922142594625068E+00   9.9468706601424852E+00   4.6429239824000899E+00   9.0672882127713683E-01\n         2         20   4.4655285022276237E-01   3.3670472299918202E+00   2.2368334298459787E+00   5.9416759710846012E-01\n         2         21   2.0067274419346290E+00   2.2286998738766798E+01   1.1297006129182956E+01   2.9016549001783871E+00\n         2         22   9.5221877526134946E-01   4.9451894437029633E+00   3.2907137868455658E+00   6.6536167808957503E-01\n         2         23   1.1008019389088860E+01   3.6633891119572553E+01   2.3355589023259903E+01   3.4846285068938907E+00\n         2         24  -1.1102230246251565E-15   1.4184055103230586E-01   2.1223720773868693E-02   3.4451115815381537E-02\n         2         25  -1.3322676295501878E-15   2.7105278307761815E-01   5.1147870492171212E-02   8.0375138915515093E-02\n         2         26  -1.7763568394002505E-15   1.5313628024466892E+00   3.5664546750150672E-01   4.1930548116329808E-01\n         2         27  -1.7763568394002505E-15   5.3871149107085148E-01   1.2887322630977524E-01   1.7285596573003989E-01\n         2         28   5.6915894155462610E-05   8.6243760615291798E-01   2.2095468251343731E-01   2.3772502411405563E-01\n         2         29   3.4088716392320917E-03   2.9964813469995333E+00   6.2879803932500045E-01   4.7454756857605707E-01\n         2         30   6.6483401614776394E-03   1.1293624006275655E+00   3.3754947964447080E-01   2.7728759222894234E-01\n         2         31   2.5055430516308652E-03   5.9666429106341701E+00   1.8798829121108092E+00   9.4500388056567175E-01\n         2         32   4.0455424107940452E-02   1.3581981583290548E+00   4.9713670074178296E-01   2.9898524444802016E-01\n         2         33   1.9056719306665537E-01   8.1743448797834670E+00   3.2919724019133016E+00   1.1569970627931025E+00\n         2         34   1.0490829605667448E+01   3.2448612403044457E+01   1.9864336724882346E+01   2.7329237836938267E+00\n         2         35   3.0916996476275806E+01   9.3633766733736877E+01   5.8173725811384259E+01   7.9357103300306848E+00\n         2         36   5.0148769557962339E+01   1.4839436783964052E+02   9.3772708667709765E+01   1.2568792091837715E+01\n         2         37   3.4923556542687706E+01   1.0174193955719564E+02   6.4649016164958468E+01   8.6123432880881765E+00\n         2         38   3.1884762870308919E+01   9.3596113140372367E+01   5.9054216602733867E+01   7.8774466072726099E+00\n         2         39   1.2683838878185455E+01   3.6742068700298070E+01   2.2560116110172320E+01   2.9685693144973246E+00\n         2         40   1.7853732273689396E+01   5.7757113928998344E+01   3.7575031479805006E+01   4.7910342647743276E+00\n         2         41   4.2360258940408322E+01   1.4984924237392428E+02   9.6046796610797671E+01   1.3775914996232904E+01\n         2         42   6.7969480916005480E+01   2.3814754540271986E+02   1.5468174157531126E+02   2.1767484452347421E+01\n         2         43   4.4717815990799956E+01   1.6490078753817681E+02   1.0644629268911434E+02   1.4895923631856354E+01\n         2         44   4.1094225400058754E+01   1.5189742447251245E+02   9.7865199416330142E+01   1.3637300540001899E+01\n         2         45   1.6274974825449913E+01   5.9490462642359553E+01   3.7832748751297572E+01   5.1890594385442883E+00\n         2         46   1.5047596186319243E+00   1.1697774055160188E+01   5.6797434538455205E+00   1.4168630115661052E+00\n         2         47   3.6830361630492998E+00   3.0215374864867016E+01   1.4716088343270338E+01   3.6604480950959903E+00\n         2         48   5.5607139336214892E+00   4.7736013797240012E+01   2.3475252722684814E+01   5.8884047333260678E+00\n         2         49   3.7009840431909118E+00   3.2692854767634401E+01   1.6178300828689416E+01   4.1510667558618897E+00\n         2         50   3.2449870535713017E+00   2.9804755175073776E+01   1.4727778893771768E+01   3.8010322545504605E+00\n         2         51   1.3597803459387674E+00   1.1422782820088740E+01   5.5784463850670996E+00   1.3617504771750930E+00\n         2         52   6.6050184344182057E+00   2.3520792686831065E+01   1.4196278130439875E+01   2.4463088137190776E+00\n         2         53   1.2089130198999424E+01   6.4506931261072893E+01   3.8291432040749498E+01   7.3781006144107986E+00\n         2         54   1.8995524141532911E+01   1.0812256532348557E+02   6.2697565304924836E+01   1.2212396939598225E+01\n         2         55   1.3031352981520142E+01   7.6505637761955512E+01   4.3573246145471565E+01   8.7370272853912017E+00\n         2         56   1.2058976049597680E+01   7.0516117446951156E+01   3.9647126201919960E+01   7.9467541550671301E+00\n         2         57   4.4421383058301185E+00   2.5360437591597645E+01   1.4763667743001324E+01   3.0523541754156258E+00\n         2         58   1.6296132905884495E+00   9.1003463508489695E+00   4.7692096792848124E+00   1.0757410587390290E+00\n         2         59   2.6724993575418190E+00   2.2860742795192284E+01   1.1720345863796613E+01   2.9343130143749234E+00\n         2         60   4.3591786493216675E+00   3.7192233430810369E+01   1.8979973070147150E+01   4.7466649398674097E+00\n         2         61   2.7805078715473970E+00   2.7366473294693094E+01   1.3110133248370786E+01   3.4237190980996175E+00\n         2         62   2.5098646642828655E+00   2.4873870399552292E+01   1.2056867407871897E+01   3.1528736324426050E+00\n         2         63   6.8021637891979148E-01   9.3119256580709084E+00   4.6849151296678357E+00   1.3091671420867326E+00\n         2         64   1.5204848098227860E-03   6.5950200588995445E-01   1.5351330864361537E-01   1.0034992913069611E-01\n         2         65   1.5573499703493487E-02   2.5652081003777707E+00   7.1693841284916737E-01   3.9315644805821581E-01\n         2         66   6.1600247347199370E-02   4.4598900277265319E+00   1.2784617108569720E+00   6.2967891396221942E-01\n         2         67   4.2864378734796690E-02   3.2119679036800406E+00   9.2398385530991922E-01   4.7388281403048294E-01\n         2         68   3.8944104810090356E-02   2.7606418422663275E+00   8.3482007635845501E-01   4.2930984594983962E-01\n         2         69   2.3148923429607078E-03   1.3515883499893624E+00   2.9340076046952596E-01   1.8233330868560657E-01\n         2         70  -3.8343165722002626E-16   1.2273920872761083E-02   6.8770333961471006E-05   2.3995420389576492E-04\n         2         71   8.5617156608656675E-13   1.1205905790113074E-01   5.2075973728551526E-03   8.8557803208937740E-03\n         2         72   7.0041457456641406E-08   5.0589966722753954E-01   5.8209286903255171E-02   1.3031003528391472E-01\n         2         73   2.8106581751314836E-11   5.2802377001603840E-01   6.1817266343333219E-02   1.4095015222995086E-01\n         2         74   9.4172528095885996E-08   5.0990792586616684E-01   5.7817887134402349E-02   1.3450127977190729E-01\n         2         75  -1.4997571384882273E-19   1.0293257670072954E-01   4.8555153663802988E-03   1.2225105358126320E-02\n         2         76   7.4066681231413311E-06   1.0528555834961313E-01   5.5518031061540605E-03   7.2112520617481366E-03\n         2         77   4.5392826401123435E-04   4.9702163745575723E-01   5.2848727978024417E-02   3.8086769729494624E-02\n         2         78   1.2470712591659463E-03   1.4500098978071343E+00   2.2741493530981596E-01   3.3075632063269833E-01\n         2         79   7.1850738477417667E-04   1.4548280617918981E+00   2.1944671796296303E-01   3.5202777526540829E-01\n         2         80   1.0427512552816083E-03   1.4086743548515410E+00   1.9309838486762501E-01   3.3940731514493649E-01\n         2         81   1.5316505699911688E-04   3.9170739576143243E-01   2.1690928391021241E-02   3.5951638124914538E-02\n         2         82   2.3226248027929980E-03   4.0659992967230246E-01   5.3837090521652087E-02   4.0925587509594595E-02\n         2         83   2.5108500941182360E-02   1.4626692013948281E+00   2.6569996271015145E-01   1.3967026247132786E-01\n         2         84   5.7226401547664188E-02   3.2631936005913977E+00   6.5763555812799035E-01   5.5826011511479856E-01\n         2         85   4.2129399962387695E-02   2.9152985915898517E+00   5.5493710174127275E-01   5.5249689475335928E-01\n         2         86   4.5090529564537220E-02   2.7890934485354242E+00   4.7691611927976857E-01   5.3407108975361495E-01\n         2         87   1.4465090111904569E-02   9.0063376561065744E-01   1.0171767821188143E-01   7.7884524062057633E-02\n         2         88   5.0830647099082707E-02   8.8733804165813375E+00   2.1914102288604869E+00   1.1831643328625014E+00\n         2         89   3.3869582455722153E-01   3.0264786460839161E+01   7.7756892916172973E+00   3.8603874071781519E+00\n         2         90   6.6087247809897265E-01   4.8130300813065347E+01   1.2721739742585562E+01   6.1253997018409194E+00\n         2         91   3.3466931646599773E-01   3.3401951454076382E+01   8.9028581289087434E+00   4.2662149632188902E+00\n         2         92   3.0024409868720120E-01   2.9456666352094416E+01   8.1173663820764439E+00   3.8522240089987516E+00\n         2         93   5.2767254489325274E-02   1.0482800211221702E+01   3.2189580132889946E+00   1.4648654836794395E+00\n         2         94   3.1444988560374837E-02   1.1413580776284868E+00   2.4362092810468247E-01   1.1839705939806393E-01\n         2         95   2.0698560158538329E-01   3.4665426737029224E+00   9.2623735419833431E-01   3.5855841513650888E-01\n         2         96   4.0637266706254599E-01   6.6198826316005954E+00   1.7831167036130755E+00   8.8257798470134108E-01\n         2         97   3.1839051103845656E-01   5.3726652161096364E+00   1.3597339867698643E+00   7.7949643213847009E-01\n         2         98   3.0639613382632469E-01   5.1215237594393423E+00   1.1882858358499524E+00   7.4559261772624819E-01\n         2         99   1.1549620642267347E-01   1.6857587926847877E+00   3.6716516487330109E-01   1.4841820434101499E-01\n         2        100   2.6789219942925810E+00   3.8339377458539474E+01   1.6259928339346143E+01   4.4950598220973026E+00\n         2        101   1.1068050063581769E+01   1.1562319725612882E+02   5.0727869667887454E+01   1.3542522508471061E+01\n         2        102   1.7525521953978522E+01   1.7994323447293985E+02   8.1618074462960749E+01   2.1603256718203220E+01\n         2        103   1.2279762752268180E+01   1.2363741101986318E+02   5.6020958578498025E+01   1.4872386219588417E+01\n         2        104   1.1480014998190741E+01   1.1226536447066910E+02   5.1259605154295464E+01   1.3639594665514641E+01\n         2        105   4.2037313527534490E+00   4.4833915487648014E+01   1.9496208299720774E+01   5.2386898305042022E+00\n         2        106   1.8892447412261551E-01   2.5211605759340014E+00   7.6037211994682374E-01   2.5467250652753382E-01\n         2        107   7.3893874127555204E-01   7.1374664222614959E+00   2.5676320015809524E+00   7.4985259589550979E-01\n         2        108   1.5202185447952643E+00   1.2465541601305318E+01   4.4687202861875406E+00   1.4221861677200898E+00\n         2        109   1.1326061194023906E+00   9.5284562527869436E+00   3.2337410445843329E+00   1.1179219868688535E+00\n         2        110   1.0032115750903061E+00   9.0981278933293961E+00   2.8808470288700398E+00   1.0507534671367857E+00\n         2        111   4.4555901532250702E-01   3.1244373336343108E+00   1.0238754016729235E+00   2.7051246115752403E-01\n         2        112   1.6650150598674831E+01   1.0173905973731840E+02   4.7873484114725450E+01   9.9940626651734075E+00\n         2        113   5.0383861869528367E+01   2.8528848194660964E+02   1.3908452190325804E+02   2.8601210822034794E+01\n         2        114   8.2696087352995278E+01   4.5781301896385105E+02   2.2232667856802766E+02   4.5571136636998510E+01\n         2        115   5.7650365416382378E+01   3.1459116718713244E+02   1.5230491482671894E+02   3.1318202467614771E+01\n         2        116   5.2969556775412457E+01   2.8821730855230101E+02   1.3955756962744783E+02   2.8738095158631932E+01\n         2        117   1.9907302404473956E+01   1.0781830096039809E+02   5.3239548507381066E+01   1.1040189292647714E+01\n         2        118  -2.6916037117720294E-19   9.2580862216124441E-03   2.2460153187443795E-03   1.2661728624613949E-03\n         2        119   4.6375051425780368E-06   2.4119571350881327E-02   1.5523595541206026E-03   1.1070405857839076E-03\n         2        120   5.1812853190775508E-05   1.7748531988237190E-01   7.9473166531189271E-02   4.9545065282283751E-02\n         2        121   4.1346394860205331E-05   1.9745052245942549E-01   9.4292453455491754E-02   5.9224268795783484E-02\n         2        122   3.4337801702531530E-05   1.9806736923054635E-01   1.0053335972932777E-01   6.2833827684229793E-02\n         2        123   1.7533292044559839E-06   6.3038619994557621E-02   2.3744448869216027E-02   1.4454259189452864E-02\n         2        124   1.2127688322655566E-05   1.0952733275438213E-01   5.1414745858739827E-02   2.5396079495490081E-02\n         2        125   1.9089148981614097E-03   2.4457303823757143E-01   4.9030864381825183E-02   1.8654004601577855E-02\n         2        126   2.7085815149184695E-02   8.5222594527800288E-01   3.5869650694760968E-01   1.6866740994183033E-01\n         2        127   2.8050655073247287E-02   8.6916230512082193E-01   3.9170581631674301E-01   2.0134924679505281E-01\n         2        128   2.5671227290251810E-02   8.8613741685603920E-01   4.3592837480514485E-01   2.2536177028057267E-01\n         2        129   1.2856998140145805E-03   3.2745656407759960E-01   1.6113859855472645E-01   7.5600080406566919E-02\n         2        130   4.0389828086697241E-03   4.7170215268649945E-01   2.3892835434657475E-01   9.6688517913066901E-02\n         2        131   3.3391544214664122E-02   1.3089212826311087E+00   3.5821022271621628E-01   1.1460121428745927E-01\n         2        132   2.5410063817101891E-01   2.6120326565931973E+00   1.1090729919467739E+00   3.2219731959315739E-01\n         2        133   2.2446123646543592E-01   2.3574403282348722E+00   1.0342709262745253E+00   3.5059377257582863E-01\n         2        134   1.9475560428125821E-01   2.3566472926187121E+00   1.1385011214293543E+00   4.1357562447740182E-01\n         2        135   2.2613172995687776E-02   9.8508691353374933E-01   5.3972204989204453E-01   2.0319473652572673E-01\n         2        136   9.8070945502725471E-01   1.3428145649127558E+01   4.9442940391552428E+00   1.6530857166611226E+00\n         2        137   1.4502769436558918E+00   3.8089689785352434E+01   1.1496370756286733E+01   4.0843916453868001E+00\n         2        138   1.9324192978892187E+00   6.2540030143559051E+01   1.9666274894986337E+01   7.1755571559548610E+00\n         2        139   5.8719863749961287E-01   4.6714340847352155E+01   1.3982101009035850E+01   5.4064455057326226E+00\n         2        140   4.9152445312688148E-01   4.1232311942801580E+01   1.2754045636311758E+01   5.0214764727091490E+00\n         2        141   8.3744836068373033E-02   1.5603532699915776E+01   4.7469013368485378E+00   2.1845964104586808E+00\n         2        142   6.5442705702925819E-02   1.4566102822849432E+00   7.3478130834920696E-01   2.1835599904057587E-01\n         2        143   3.0059391209111858E-01   3.8659547014509372E+00   1.4235637437371764E+00   3.7825905710091057E-01\n         2        144   9.6087791864551897E-01   6.4650213541971411E+00   3.0809713957801668E+00   7.0490623610497816E-01\n         2        145   7.9922576625002206E-01   5.2700248273371209E+00   2.5083436077885772E+00   6.0463743293223815E-01\n         2        146   6.5809905645336941E-01   5.1027774769420651E+00   2.6026757001835161E+00   6.7039781983059910E-01\n         2        147   1.1233144290602627E-01   2.2206040611599973E+00   1.2598148061956222E+00   3.7896533797681742E-01\n         2        148   4.3230481940948344E+00   7.0527362342118792E+01   2.9133364830006762E+01   8.6431941827054093E+00\n         2        149   8.8690638079805684E+00   1.8835544771727226E+02   7.4553505702010838E+01   2.4007885714500706E+01\n         2        150   1.4186728052316663E+01   3.0027555182137047E+02   1.1932592535007872E+02   3.7378064687139634E+01\n         2        151   9.8473291753004482E+00   2.0529221141215254E+02   8.1581087900498702E+01   2.5323400437240377E+01\n         2        152   8.6013923692890852E+00   1.8696883396210535E+02   7.4700093136459941E+01   2.3267400575834280E+01\n         2        153   3.0267945120084914E+00   7.0256031210577675E+01   2.8442640219823065E+01   8.9678175847195156E+00\n         2        154   3.3921820722647394E-01   3.4494340795167728E+00   1.8651383842515223E+00   4.1409375040266427E-01\n         2        155   1.1308362939738343E+00   9.0586120688475606E+00   4.1093243710060587E+00   9.2010297640064076E-01\n         2        156   2.4937186536904199E+00   1.4408494521675427E+01   7.6216832461340127E+00   1.5537129120056046E+00\n         2        157   1.8721576360833032E+00   1.0555668014925683E+01   5.7202559583691190E+00   1.1682679544032026E+00\n         2        158   1.6458627990678911E+00   1.0384542991606466E+01   5.6221986286363785E+00   1.1627675185266153E+00\n         2        159   3.4386095236273007E-01   4.5380473956281380E+00   2.5543879882736387E+00   6.0656594988754975E-01\n         2        160   4.1285646328038140E+01   1.9176484393483648E+02   9.8506461623465142E+01   1.9147257944556802E+01\n         2        161   1.0069294284593688E+02   5.0694163473841928E+02   2.5577257934003188E+02   5.1102419456965308E+01\n         2        162   1.5811362639640694E+02   7.8133890751357444E+02   4.0586284169715537E+02   8.0288193892869586E+01\n         2        163   1.0749058870590703E+02   5.2326779530723729E+02   2.7734176120314254E+02   5.4889817972537216E+01\n         2        164   1.0114308350571523E+02   4.7348822137414777E+02   2.5434956378477432E+02   5.0404822554215613E+01\n         2        165   3.5661991395485849E+01   1.7796549450952944E+02   9.6929082027756110E+01   1.9343176705527547E+01\n         2        166  -2.5494001516139498E-16   1.3191113410235776E-03   8.7211985226169567E-06   2.9330027830678834E-05\n         2        167  -5.0492320490329704E-16   4.7190960019697678E-02   1.9584637866019382E-03   4.1673893800176290E-03\n         2        168  -4.6890670706039519E-16   2.5353743852281613E-01   2.4406535653061619E-02   5.7839361349603727E-02\n         2        169  -3.9914313530512123E-16   2.7860015625068940E-01   2.6018079482324149E-02   6.2301078488400399E-02\n         2        170  -3.5037369872061447E-16   2.7389830500202123E-01   2.4415305830307207E-02   5.9057974644057529E-02\n         2        171  -2.4212370771499073E-17   4.3971611639061756E-02   1.9701382689985480E-03   5.0753817151005772E-03\n         2        172  -3.7951168900475239E-16   2.3705357271273226E-02   1.3946123406273338E-03   2.6132855458290108E-03\n         2        173  -4.2823166277308245E-16   2.0082277451533773E-01   2.0258147539834390E-02   2.4218229032522715E-02\n         2        174  -1.0619951948429922E-15   8.3642135780920246E-01   1.1484294749667777E-01   2.1762227217975760E-01\n         2        175  -1.0799867219897119E-15   8.8589836338618666E-01   1.1483490786260576E-01   2.3289582387235064E-01\n         2        176  -1.0722427499520293E-15   8.5488039950137606E-01   1.0352249822342323E-01   2.2099329718350288E-01\n         2        177  -1.1138652422279678E-15   1.5360705071016442E-01   9.4758627543343101E-03   1.9694823126490943E-02\n         2        178   1.8779425161118000E-06   1.2832710702693523E-01   1.6429742024520102E-02   2.2230563749590360E-02\n         2        179   3.2530659628354226E-05   5.4690230560778719E-01   9.4065382349243540E-02   9.8471518500877736E-02\n         2        180   4.7282706403794731E-05   1.7654919467068066E+00   2.9590914465165019E-01   4.2618780278779311E-01\n         2        181   2.6929795424016122E-05   1.7422128241014432E+00   2.6684417451143932E-01   4.3589189921444615E-01\n         2        182   1.5127892865727845E-05   1.6298760214031724E+00   2.3305689850532724E-01   4.1059365568972883E-01\n         2        183   2.4578044718036309E-05   3.2899165816559606E-01   3.5057248105119225E-02   4.3482426206068792E-02\n         2        184   2.1053261780298541E-03   4.2296446568574941E+00   5.9915048093706413E-01   5.3032213225190028E-01\n         2        185   7.9892624457163879E-03   1.3198907761370378E+01   1.7748794733517530E+00   1.5104096300717225E+00\n         2        186   1.1195305506846987E-02   1.7848904272832684E+01   2.5866839403712412E+00   2.0989424222577631E+00\n         2        187   7.0204701397032819E-03   1.1183911132708301E+01   1.7015265236411035E+00   1.3912543461337250E+00\n         2        188   4.2848987784550796E-03   9.6096503742581429E+00   1.5438248414422429E+00   1.2608950331548801E+00\n         2        189   1.8788792085643415E-04   4.5318930016521612E+00   6.8955374425644667E-01   6.1790343662567848E-01\n         2        190   7.1837531547354957E-04   3.8461163480833827E-01   7.6681439430651477E-02   7.1999303095500747E-02\n         2        191   6.4193745075507586E-03   1.4673401952647176E+00   2.9190900274982429E-01   2.4675747957419247E-01\n         2        192   9.4917520835970364E-03   3.1421860172666460E+00   6.5014999381271987E-01   6.9301324738529635E-01\n         2        193   5.5999553680636926E-03   2.8813005806952585E+00   5.2833381871048368E-01   6.5483660707235591E-01\n         2        194   3.3162917921341082E-03   2.7056337504667578E+00   4.6046579326078563E-01   6.0839360397683739E-01\n         2        195   2.9185681179858133E-03   6.0764038222466132E-01   1.1065922133253923E-01   8.5983124783962486E-02\n         2        196   5.5750725530591873E-03   1.9533650104690750E+01   4.8378012102681405E+00   2.5493843877900573E+00\n         2        197   1.3311540467677723E-02   4.8614736657886205E+01   1.2560227908621535E+01   6.6420278018307304E+00\n         2        198   2.4679215226359994E-02   7.9078150739060291E+01   1.9735262534925202E+01   1.0386157618046196E+01\n         2        199   1.8285711755099816E-02   5.5967108800381382E+01   1.3500468950091134E+01   7.1829041347555407E+00\n         2        200   1.6579574901830593E-02   5.1136391912905083E+01   1.2358009605099134E+01   6.6127608672613691E+00\n         2        201   6.5361744164033125E-03   1.7272121821397366E+01   4.6999965491309323E+00   2.5901658611492357E+00\n         2        202   1.1859819088534880E-02   8.4263185144825103E-01   2.3535958221348796E-01   1.5484805009439165E-01\n         2        203   4.9875006725589165E-02   2.8862392352523853E+00   7.3959983229967674E-01   4.7073828886630198E-01\n         2        204   7.1408304468075362E-02   5.1435235114689926E+00   1.3749047213482537E+00   1.0441093030221296E+00\n         2        205   4.5001480022145317E-02   4.4647499147632663E+00   1.0349814951966048E+00   9.0779705128558208E-01\n         2        206   2.9884620214659593E-02   4.2345995990742695E+00   9.1279213319137653E-01   8.3288667328417876E-01\n         2        207   2.3972101177354252E-02   1.1329866889957134E+00   2.8387537762228865E-01   1.5468025619680381E-01\n         2        208   6.7352094942232577E-01   3.7917353861056107E+01   1.3765426176022839E+01   5.1173334089323470E+00\n         2        209   2.0410610743667830E+00   9.7119458200248346E+01   3.5842850256247829E+01   1.3204661741118706E+01\n         2        210   3.3440775865141199E+00   1.5526910183288726E+02   5.7081085013758702E+01   2.0867703128760215E+01\n         2        211   2.1070911846325218E+00   1.1246431739152105E+02   3.9119580313743185E+01   1.4348101223999732E+01\n         2        212   1.9727073207583001E+00   1.0287113799433520E+02   3.5822328696989068E+01   1.3148239756186769E+01\n         2        213   7.7793884597979368E-01   3.7518032047949376E+01   1.3566767554690344E+01   5.0189002964557359E+00\n         2        214  -3.1611591744313104E-18   2.2056098909780729E-03   4.6947952971885805E-04   2.3374964101878135E-04\n         2        215  -1.0836468369828224E-18   9.2726851101144359E-03   6.7306069354257977E-04   3.5386118373610583E-04\n         2        216  -4.1317068003547389E-19   5.0112489764702839E-02   2.3617701860949310E-02   1.0031253789803336E-02\n         2        217  -4.1427570345589064E-18   5.8760470577606673E-02   2.7952724872908653E-02   1.1820158922369409E-02\n         2        218  -2.9264837085136436E-18   6.0819748395247231E-02   2.9151294082052047E-02   1.2319390329209472E-02\n         2        219  -3.0359165229561437E-18   2.2830932352789605E-02   6.0671890698357515E-03   3.0563112119906064E-03\n         2        220   3.1272861234208321E-06   6.2059491453399770E-02   2.9678798187126081E-02   1.2377204906071934E-02\n         2        221   2.0837646955958633E-06   1.1617651124679668E-01   4.7873078710262876E-02   2.0438540858565363E-02\n         2        222   1.0616059304349316E-06   3.1419648540967104E-01   1.6814635147208035E-01   7.0165699492299158E-02\n         2        223  -4.1356853943372865E-17   3.1096013283847429E-01   1.6776465912998181E-01   7.0072906643880287E-02\n         2        224  -3.1946742444925609E-17   3.1382204345890169E-01   1.6383849352612664E-01   6.8730463212520729E-02\n         2        225  -1.6927353802655058E-17   1.0857527321843860E-01   3.2529288030837225E-02   1.6493719723398560E-02\n         2        226   1.6660244065637251E-03   2.8394731819011121E-01   1.6741379427368022E-01   6.4663274354430075E-02\n         2        227   7.8915524824049233E-04   6.1794816645082651E-01   3.0113612325124756E-01   1.2330058281885389E-01\n         2        228   7.9823062233508183E-04   1.1631727611906499E+00   5.7706457738598982E-01   2.4076785431459399E-01\n         2        229   2.5922923448270803E-05   9.7847589078595043E-01   4.6754197624287303E-01   1.9865681870449436E-01\n         2        230   2.0058596855900044E-05   9.0665471627350003E-01   4.2604627095348019E-01   1.8394709549203109E-01\n         2        231   6.2437800243708238E-07   2.9089618340254197E-01   8.8919439031294137E-02   5.0601563609109348E-02\n         2        232   7.7079742115885685E-01   9.0473657627876136E+00   2.2674103097451783E+00   5.8702452070091393E-01\n         2        233   4.4721523457695361E-01   1.8587954891339198E+01   4.0012467570551378E+00   1.6427625976033298E+00\n         2        234   2.8277451643140106E-01   3.1310238734454462E+01   5.7580859002880516E+00   3.0355577439983707E+00\n         2        235   1.3580201515896806E-02   2.4661372388061636E+01   3.7825838339684124E+00   2.4648382785376586E+00\n         2        236   1.1760818380188618E-02   2.3893712165959506E+01   3.4972842584072334E+00   2.3058011008154442E+00\n         2        237   7.7084417791727230E-04   8.9996282482473902E+00   1.4040037966835337E+00   1.0325873874153799E+00\n         2        238   2.5408913205892402E-02   7.5189499699853890E-01   4.5389016423937756E-01   1.5498917894180189E-01\n         2        239   2.0473272420916191E-02   1.8911248332620583E+00   9.0534256741111585E-01   3.5046052589766341E-01\n         2        240   1.6011879384216245E-02   3.4564266849491569E+00   1.4636129575090517E+00   5.8524410762642998E-01\n         2        241   5.0958251057742140E-03   2.6800786459126251E+00   1.0575775288103657E+00   4.3846262403515318E-01\n         2        242   4.7244390327035313E-03   2.4411187589296506E+00   9.3371889989219214E-01   3.9389532195405802E-01\n         2        243   5.7280450023139027E-04   8.2951219597558568E-01   2.3204759978797024E-01   1.2431949163344429E-01\n         2        244   3.3609695572096487E-01   3.7898945558389869E+01   1.1367913893629229E+01   5.6173149401910658E+00\n         2        245   8.5749397668855221E-01   9.8679527165150134E+01   2.6093924990307269E+01   1.3742178722062768E+01\n         2        246   1.2117975615710617E+00   1.5890852876767158E+02   4.2176535732828427E+01   2.3014397369461758E+01\n         2        247   7.0273013876132817E-01   1.1895263373318599E+02   2.9153235781036077E+01   1.6574912154056843E+01\n         2        248   5.2088890824658263E-01   1.0772670616336991E+02   2.6661192011530410E+01   1.5018652139159339E+01\n         2        249   1.0908088976950713E-01   4.5084676144696040E+01   1.0391495708695533E+01   5.7117082324682267E+00\n         2        250   1.3981767047961852E-01   1.7220955722607805E+00   9.4123114128735996E-01   2.6282080294708166E-01\n         2        251   1.1747358138581923E-01   4.7211753874395939E+00   2.0989431405988741E+00   7.2633145973865332E-01\n         2        252   1.4542957538689177E-01   7.9023952906147699E+00   3.3123215526630894E+00   1.1812072053624671E+00\n         2        253   8.1634908239566678E-02   5.9819307764573733E+00   2.3104342026624924E+00   8.6206811911344550E-01\n         2        254   7.8987695950721262E-02   5.5692101626010899E+00   2.0399244873836482E+00   7.6962136796785297E-01\n         2        255   1.6640872417570830E-02   1.8559774438035899E+00   6.0389206280834706E-01   2.6165825666554204E-01\n         2        256   9.4961741753695339E+00   1.0348699505241775E+02   4.2701870068768898E+01   1.2181004686602527E+01\n         2        257   2.4384491793901525E+01   2.6925397637082625E+02   1.1246284975530376E+02   3.4043823114387372E+01\n         2        258   3.7810277720014675E+01   4.4882766312306950E+02   1.8349316899713617E+02   5.5471449432586390E+01\n         2        259   2.5151721817638144E+01   3.1421842816432235E+02   1.2669793054701798E+02   3.8496728034129767E+01\n         2        260   2.3362284921735235E+01   2.9033789869451289E+02   1.1613261160860596E+02   3.5341857374692843E+01\n         2        261   8.7687791503824339E+00   1.1012695134413345E+02   4.4006005476250138E+01   1.3897284984640002E+01\n         2        262  -3.1467633334010568E-17   2.1752762245976251E-03   1.7632341351685765E-04   2.0034343438611862E-04\n         2        263  -2.4365028993261572E-16   1.6285630874639839E-02   1.8793114982012770E-04   3.6276892134350065E-04\n         2        264  -4.6799327022854813E-16   9.3335798245309409E-02   7.9574640891394051E-03   1.9420381434809363E-02\n         2        265  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3.5751949316787665E-03   9.5518141113724955E+00   1.2642145092130928E+00   1.1127503863911330E+00\n         2        282   5.7506851098996304E-03   1.9672137062737729E+01   2.0541939003091487E+00   1.9687322163974863E+00\n         2        283   8.6533122447899073E-04   1.7133679566153205E+01   1.4382688717842733E+00   1.5031217215477679E+00\n         2        284   4.3008475783315231E-04   1.5127524169114215E+01   1.2716957099109780E+00   1.3303734070413826E+00\n         2        285   2.1227139819237377E-05   3.4492741112399705E+00   4.0019609048987398E-01   4.2765115819995964E-01\n         2        286   3.5195494114410681E-03   3.9345290687925893E-01   1.3823554726455087E-01   8.5871965796480043E-02\n         2        287   6.0305302019842393E-03   1.1653004873608499E+00   1.9011576084038950E-01   1.2614160793042037E-01\n         2        288   9.4402262132682151E-03   2.4396809932670638E+00   3.7051210977902277E-01   3.3544117075298185E-01\n         2        289   6.1995471635940336E-04   2.1952483991429004E+00   2.9785460830070321E-01   3.5608759025685754E-01\n         2        290   1.8747282258845145E-04   2.1513925099168079E+00   3.2436543041669968E-01   4.0945405314962702E-01\n         2        291   1.1954703033539322E-05   8.6546777829228638E-01   1.7065666269504576E-01   2.2056581908247369E-01\n         2        292   3.6558396396751715E-03   1.5288771885562616E+01   3.8571592215806736E+00   2.1871992540176795E+00\n         2        293   7.3332787771524521E-03   3.5412942117497835E+01   8.6714236823477382E+00   5.3828885408820257E+00\n         2        294   1.1616198716055457E-02   5.6262206544632789E+01   1.4167383117828665E+01   8.6333815651762489E+00\n         2        295   7.8735368684923600E-03   3.8191156716683231E+01   9.8302936607056957E+00   6.0901652544315450E+00\n         2        296   7.4300367047902818E-03   3.5947973198495191E+01   9.0683690563614618E+00   5.5694061789781104E+00\n         2        297   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-3.3708089626330151E-16   2.9782387354410061E-03   2.3151841233235869E-06   3.1257020530487835E-05\n         2        314  -5.7880265206462675E-16   4.4083484478076335E-02   3.0406422883091795E-05   3.4931242369601610E-04\n         2        315  -7.0455864885675093E-16   4.7476581574526250E-02   5.8533174838151352E-05   4.5070514338632259E-04\n         2        316  -4.5238432670633027E-16   1.8435666709758856E-02   4.2777699356617614E-05   2.9945958228646397E-04\n         2        317  -4.4941472137828128E-16   1.3766066109439083E-02   3.8028865094466531E-05   2.6640766451936952E-04\n         2        318  -4.4694751728115652E-16   1.6071672926534226E-02   1.9744790852316184E-05   2.8624418642841568E-04\n         2        319  -7.2970594384551471E-16   1.7822859853681875E-02   7.7641908064885219E-05   4.6145683843864101E-04\n         2        320  -5.3817449719545877E-16   1.4312837068816836E-01   7.2520123637357335E-04   3.0184869731706282E-03\n         2        321  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-5.0860966963475577E-17   1.3160756695064355E+00   8.3616355639794998E-02   1.3292807620494870E-01\n         2        338   0.0000000000000000E+00   7.8691978338880677E+00   5.7662482340920973E-01   7.1764852296083048E-01\n         2        339   2.3453455905980648E-14   1.1455384440973058E+01   1.1192569578455807E+00   1.2383682438427153E+00\n         2        340   8.4890366668183127E-15   7.0048424115669299E+00   8.3886205993113994E-01   9.3981977066076394E-01\n         2        341   1.8991275722811086E-19   6.6738171321656354E+00   7.7170095356179647E-01   8.6271562124626144E-01\n         2        342  -6.1581396050981082E-17   2.5154724997554911E+00   2.9290661853497441E-01   3.7490881932016229E-01\n         2        343   2.3101059266481205E-09   1.0927269785432800E-01   3.2932791030088971E-03   7.1140489741605521E-03\n         2        344   4.5766528264904676E-07   4.0007924938567041E-01   2.0274053816216366E-02   3.1313560956805091E-02\n         2        345   3.2762375058363147E-06   4.4574271242392144E-01   3.7994746982204737E-02   4.8443395533813639E-02\n         2        346   6.1058460184347876E-07   3.9611457655606058E-01   2.8077730795575698E-02   3.9051832396318584E-02\n         2        347   3.7946929031186537E-07   3.9768740443138967E-01   2.4553736471770348E-02   3.5240865537623366E-02\n         2        348   3.8241716229917413E-10   2.8457932605077785E-01   7.6929239539755626E-03   1.8283585653414088E-02\n         2        349   1.5468106269497946E-04   2.8250037168447713E+00   4.5107531572993054E-01   3.9707013413177150E-01\n         2        350   4.4410632959344994E-03   1.3749415464622384E+01   2.0813030883174131E+00   1.5974849823717563E+00\n         2        351   7.1744039058201934E-03   2.1819611489098019E+01   3.5421506237218621E+00   2.6098473059341334E+00\n         2        352   3.5849897794546122E-03   1.4274740807670216E+01   2.4911785100260588E+00   1.8711102535810242E+00\n         2        353   1.1176598997939084E-03   1.3579035524114536E+01   2.2890239088280673E+00   1.7380821604486389E+00\n         2        354   5.2654191488935248E-04   5.6823115705057061E+00   8.8236899310203076E-01   7.3421931441370680E-01\n         3          1   1.3071805784346152E+01   2.0292545185734930E+01   1.6882995080852130E+01   1.0655105617538705E+00\n         3          2   9.9765182803656725E+00   1.7560579858924843E+01   1.4484567825681484E+01   1.1797448908414465E+00\n         3          3   3.7476842557531798E-01   2.6090888274816648E+00   1.3373709754077781E+00   4.0215480267492371E-01\n         3          4   1.5126067246240549E-04   2.7550210187201163E-02   3.6459622741447447E-03   1.7248700707970148E-03\n         3          5   1.2636270118342230E-02   1.3605526229044529E-01   4.9322707931687755E-02   1.1053425734565546E-02\n         3          6   1.2852495011622809E+00   3.4478051674971857E+00   2.0421218245597124E+00   2.6308509719664530E-01\n         3          7   2.6844470118134167E-01   7.7061374240528513E-01   4.4822562514170677E-01   6.0138313519205580E-02\n         3          8   8.5907494948304386E-01   2.0143380797867536E+00   1.2574463622629037E+00   1.5086332057374569E-01\n         3          9   4.0174643136744654E+00   1.1702045618775839E+01   7.4829211355894429E+00   1.1692841556424693E+00\n         3         10   1.6224391508642264E+00   3.6490789385172282E+00   2.3841886226868865E+00   2.7231309702587847E-01\n         3         11   8.0525240937710763E+00   2.2249511251116687E+01   1.4111911297843834E+01   1.8888983698976862E+00\n         3         12   2.6182582663943448E+00   5.5659977631632360E+00   3.8521601121212963E+00   4.0547179825898150E-01\n         3         13   1.7621821049113890E+01   3.6116925453747250E+01   2.5859975215545752E+01   2.6240606986096155E+00\n         3         14   6.6738792002968617E-02   2.3340198427840619E-01   1.4856604541708091E-01   1.5731824116049436E-02\n         3         15   2.1388203197881983E-01   4.8331760786918410E-01   3.5803509344519840E-01   2.5316165204275626E-02\n         3         16   2.1347838695794144E+00   3.3252267877502395E+00   2.4965182725105479E+00   6.9172244500539895E-02\n         3         17   6.8066426419693915E-01   1.0751910408613734E+00   9.0211258416842688E-01   3.8475301986136995E-02\n         3         18   1.2560561407334521E+00   2.2299869852652252E+00   1.5466827775940608E+00   7.0606383660737460E-02\n         3         19   2.7258785527295872E+00   1.1462901191852431E+01   4.4015862752750046E+00   9.6608245597430398E-01\n         3         20   1.9772721944513978E+00   3.8285087930341293E+00   2.3628463575112950E+00   1.6186380503817893E-01\n         3         21   5.9892726046351346E+00   2.0144669481911937E+01   1.3159180384775656E+01   2.1810696445725015E+00\n         3         22   2.7366189682309017E+00   5.6963601219005735E+00   3.4799569051924801E+00   2.9900359865039955E-01\n         3         23   8.9026830217410033E+00   3.2676933215829663E+01   2.3043806813393111E+01   3.2575812437062370E+00\n         3         24  -1.1102230246251565E-15   8.9223563447500265E-03   1.1549612772429045E-05   1.6931045422369725E-04\n         3         25  -6.6613381477509392E-16   4.3546728478400043E-01   4.4753574847651084E-03   2.0697979316350677E-02\n         3         26  -1.3322676295501878E-15   9.2288536393856591E-02   1.1079051889191390E-03   4.4409301446067086E-03\n         3         27  -8.8817841970012523E-16   2.3533591873927895E-01   1.0980682908189982E-02   2.1300307171736345E-02\n         3         28  -4.4408920985006262E-16   1.7438237393069875E+00   2.5904183049130436E-01   3.2533312783901674E-01\n         3         29   1.5393273211650182E-07   3.9647049069742457E-01   4.6690499249910575E-02   5.3433635875517770E-02\n         3         30   1.7242501299049584E-03   4.4156685596793146E+00   1.4939772563656339E+00   8.1626722999049550E-01\n         3         31   1.3245700538102589E-03   5.8061179101105664E-01   1.2747445461717799E-01   9.8284283325590860E-02\n         3         32   5.3974076879932553E-01   6.3031854720847633E+00   3.1010467049135180E+00   1.0188243130078107E+00\n         3         33   1.1998378252668456E+01   2.9782617734245719E+01   2.0324164918275613E+01   2.6555386556494094E+00\n         3         34   3.6498988811560167E+01   8.5709876281842753E+01   5.9879220506397068E+01   7.6924529633825927E+00\n         3         35   5.7040302227725014E+01   1.3728485940570729E+02   9.5477039909035227E+01   1.2178535272171521E+01\n         3         36   3.7877632199676150E+01   9.4020428970973498E+01   6.5158940729141563E+01   8.3317484866471805E+00\n         3         37   3.4593433498302126E+01   8.7190633442845495E+01   5.9888600235959153E+01   7.6140541024697654E+00\n         3         38   1.3243358826686876E+01   3.3820779400325165E+01   2.2999308504641828E+01   2.9481657312076992E+00\n         3         39   2.3799404912326175E+01   5.4497963892317031E+01   3.9497979195335510E+01   4.5370439666742071E+00\n         3         40   5.7069039366939506E+01   1.4167169063644508E+02   1.0326156995918699E+02   1.3041950150377611E+01\n         3         41   8.9902345366406564E+01   2.2502577311803583E+02   1.6583183461643370E+02   2.0971855778967758E+01\n         3         42   5.9229472569544640E+01   1.5389295692752950E+02   1.1411166844155764E+02   1.4581847544551712E+01\n         3         43   5.4478703731238809E+01   1.4049039994405581E+02   1.0445853543751677E+02   1.3446797845077077E+01\n         3         44   2.1332966547201284E+01   5.4059375919033535E+01   3.9835038671556617E+01   5.1252339810096599E+00\n         3         45   1.2183280050775258E+00   7.1586990151861309E+00   3.7922087812509950E+00   1.2583297340011041E+00\n         3         46   2.7638293784244419E+00   1.8528681250151791E+01   9.6201127251722145E+00   3.2167258339293343E+00\n         3         47   4.2558485772658292E+00   3.0013625355257965E+01   1.5271317720563930E+01   4.9870384818805613E+00\n         3         48   2.8796740697842402E+00   2.1147943562175119E+01   1.0466504487121538E+01   3.4079397793952597E+00\n         3         49   2.6350395380078231E+00   1.9172699461941583E+01   9.5855447233012931E+00   3.1160758564828925E+00\n         3         50   9.4114712482971596E-01   7.3808125392913357E+00   3.6387717483890083E+00   1.2261752109985002E+00\n         3         51   9.8531275909188061E+00   2.5232981942809349E+01   1.6924187453577563E+01   2.3087628947089467E+00\n         3         52   1.8706907071227395E+01   6.1715521394906879E+01   4.0809134513040028E+01   6.9741292912831980E+00\n         3         53   3.0379205806778106E+01   1.0077309032477089E+02   6.8817988099368563E+01   1.1586408527436728E+01\n         3         54   2.1202627613019523E+01   7.4778215381282990E+01   4.8864270388588309E+01   8.6275808506486129E+00\n         3         55   1.9639999406553802E+01   6.9556051062131971E+01   4.4869916842590754E+01   7.8785036055707751E+00\n         3         56   6.2516111720199801E+00   2.5448825093753566E+01   1.6226459170983510E+01   3.0131797706373757E+00\n         3         57   9.1748290242091202E-01   6.6003753745611604E+00   2.9577741623998541E+00   9.5085938315072149E-01\n         3         58   2.6322197472080533E+00   1.7053111649859407E+01   8.0772641797987781E+00   2.7385799851448245E+00\n         3         59   3.8770419901281827E+00   2.6750506890358032E+01   1.3319048186016174E+01   4.4193935174549157E+00\n         3         60   2.4963999751771611E+00   1.8854778991897319E+01   9.2783280329862432E+00   3.1306936463872330E+00\n         3         61   2.3131423137043621E+00   1.7432155237681158E+01   8.5072474676779244E+00   2.8205235306972538E+00\n         3         62   9.3702893634815843E-01   6.5425088879665285E+00   3.1563445647390465E+00   1.0499149857157808E+00\n         3         63   1.0777023267829946E-03   2.1477867906145987E-01   5.5646380197854867E-02   4.0250894604743445E-02\n         3         64   1.9769790040215094E-02   1.2005711079226877E+00   2.9060038277536065E-01   2.0152737490504527E-01\n         3         65   4.3117189119923578E-02   2.2527600696158259E+00   5.3724628295453558E-01   3.5345294595452703E-01\n         3         66   2.9335696785015453E-02   1.6422502419640881E+00   3.9541072850471815E-01   2.7095036692311958E-01\n         3         67   2.7795378566643630E-02   1.5144256898213833E+00   3.6788926063195937E-01   2.5753904698896884E-01\n         3         68   4.7565343064947477E-03   7.0277076908358482E-01   1.4622739076932878E-01   1.1450510720452380E-01\n         3         69   3.9367032823867001E-05   3.6504818200479550E-03   7.1153664842585459E-04   2.9082789274275197E-04\n         3         70   3.5374341056771194E-05   4.6272990317393382E-03   5.6536157755917823E-04   3.4460959640911194E-04\n         3         71   1.8563513233959969E-07   3.3005973577681109E-03   1.1712337000889910E-04   2.3481062833764150E-04\n         3         72   1.5967330065250938E-07   3.4123239310143699E-03   1.1500106204227826E-04   2.2066166850347445E-04\n         3         73   6.5739753614947940E-08   1.6999056425241730E-03   5.1354081580895227E-05   8.5849400121204369E-05\n         3         74   5.5710246390615111E-03   4.1824892048856262E-02   1.6589399245100729E-02   2.5327417132429975E-03\n         3         75   1.4567077230449388E-02   1.2859960848022389E-01   5.0853144177989647E-02   1.2060089895468739E-02\n         3         76   1.7053769524795641E-02   1.8297247766002042E-01   5.2108859364447535E-02   1.9191228508818273E-02\n         3         77   2.4388647783237416E-03   1.1552581208076082E-01   2.1705268426303180E-02   1.4216487439468869E-02\n         3         78   3.0678679934307380E-03   1.1601393700887204E-01   2.1797243317817835E-02   1.3172897863250129E-02\n         3         79   3.0250992387144675E-04   5.0942029356123582E-02   1.0655334332601223E-02   6.0087886843150909E-03\n         3         80   5.7962833762863639E-02   2.5160972786221658E-01   1.0807654034344534E-01   1.7429458513088848E-02\n         3         81   1.5772216907628978E-01   8.4106202021993548E-01   3.6254701521284405E-01   8.1462236469850263E-02\n         3         82   1.8199222882333566E-01   1.2567666004936675E+00   4.5119570722177088E-01   1.3957316742960646E-01\n         3         83   5.0315220179236002E-02   8.6274169681156043E-01   2.4482421708730093E-01   1.0358595506238299E-01\n         3         84   7.2558646940725280E-02   8.6449094891986089E-01   2.3940314014817637E-01   9.4308892188051482E-02\n         3         85   5.8878027670777400E-03   3.5786570232309106E-01   1.0808404237052797E-01   4.1260825785928081E-02\n         3         86   6.4340139804662233E-01   8.9801104930092830E+00   2.8934962906308015E+00   1.0680953424295163E+00\n         3         87   2.3176190203817879E+00   2.8864688746615432E+01   1.1105631781889178E+01   3.7692432131691498E+00\n         3         88   4.3873152279477212E+00   4.4924535866888874E+01   1.8282999671620274E+01   6.0567909114308041E+00\n         3         89   2.9446638588375733E+00   3.2105607597588033E+01   1.2583846227674638E+01   4.2038747026842325E+00\n         3         90   2.9122062026409505E+00   2.9907581807462059E+01   1.1794840941195568E+01   3.8166715473615591E+00\n         3         91   5.8069976930128886E-01   1.1122689432135465E+01   4.6388661658990396E+00   1.4791826676933133E+00\n         3         92   1.8337961768192226E-01   8.0775030648697776E-01   3.5868925058912476E-01   6.9994707558929295E-02\n         3         93   5.3548539752919699E-01   2.7081313006654724E+00   1.2383805728966606E+00   2.8048787480273768E-01\n         3         94   7.1314796646991219E-01   4.1745549568637372E+00   1.7297798213450100E+00   4.7060646281128798E-01\n         3         95   3.1407390046052513E-01   2.9233299751898545E+00   1.0526602513197316E+00   3.4046481852505250E-01\n         3         96   3.4616342685507850E-01   2.8780546114124519E+00   1.0065197517610662E+00   3.0856065137705918E-01\n         3         97   4.8564120798129988E-02   1.1550363773206707E+00   4.2603371470398982E-01   1.2773077449038175E-01\n         3         98   3.8918550718611931E+00   3.3162642248295846E+01   1.3121481657216268E+01   3.6607822921407789E+00\n         3         99   1.2318690854382888E+01   1.0283170026060917E+02   4.1550939264614094E+01   1.1275093856631470E+01\n         3        100   2.0576068092032660E+01   1.6635381526136260E+02   6.7113956232172910E+01   1.8076639269107872E+01\n         3        101   1.4700359535260906E+01   1.1492909468963249E+02   4.6121053897673832E+01   1.2465631635176408E+01\n         3        102   1.3144717464854210E+01   1.0581370500353039E+02   4.2241557972809332E+01   1.1443414413294438E+01\n         3        103   4.9016935275761968E+00   3.9231078817365393E+01   1.6036332722087874E+01   4.4286394787557875E+00\n         3        104   4.7530900595918685E-01   1.9796668046899009E+00   9.3929084069675028E-01   1.9128514733374027E-01\n         3        105   1.2932639819348752E+00   6.3357608693574754E+00   3.1559844799065861E+00   6.7739371916514035E-01\n         3        106   1.9392641367260108E+00   9.9530583911043973E+00   4.7062187045181840E+00   1.1077329074173845E+00\n         3        107   1.1829125784279741E+00   6.9701786973659710E+00   3.0330768767501683E+00   7.8266913313933606E-01\n         3        108   1.1354145648192375E+00   6.7083075884741694E+00   2.8535828553866516E+00   7.0971962600787197E-01\n         3        109   2.3781394446602153E-01   2.6368513557574369E+00   1.1585161834191700E+00   2.8341300238744133E-01\n         3        110   2.2087210350635331E+01   9.6364923722368374E+01   4.8523078908917320E+01   1.0042992733783597E+01\n         3        111   6.4860150765213760E+01   2.7495440985458436E+02   1.4150506714631365E+02   2.8904617024969394E+01\n         3        112   1.0331499312183557E+02   4.3614358251925273E+02   2.2578201716335553E+02   4.6326143486596813E+01\n         3        113   7.0279968258143356E+01   2.9675351653885537E+02   1.5450651565524291E+02   3.1946765240437259E+01\n         3        114   6.4518026872682924E+01   2.7252962633390803E+02   1.4149277451816087E+02   2.9327180959503828E+01\n         3        115   2.4744531394138598E+01   1.0470779291799020E+02   5.4031635010324067E+01   1.1192700896519089E+01\n         3        116   6.2653640370759580E-04   1.7231546925243067E-02   5.8283368471957857E-03   1.4112126338704683E-03\n         3        117   8.5356164387468151E-04   2.4108911161528974E-02   5.5236556660806756E-03   1.6541297790929237E-03\n         3        118   2.1322127150788187E-03   3.6146691961077997E-02   8.8330834793400696E-03   2.7559267232903123E-03\n         3        119   1.6755388566639614E-03   3.7059156947251190E-02   7.0000824941341732E-03   2.4780211220025053E-03\n         3        120   1.8067877084444618E-03   3.6891139402244533E-02   7.2612812068355058E-03   2.4988818658075742E-03\n         3        121   2.7955531655141102E-04   1.3988422960301301E-02   3.0962204850476334E-03   1.3357627262048683E-03\n         3        122   4.6718149149442077E-02   1.8571788615868406E-01   1.1390595306603495E-01   1.2483455580519304E-02\n         3        123   5.6128722660603952E-02   2.9690097161389906E-01   1.3821691045850409E-01   2.4861039831718740E-02\n         3        124   1.0800618996201514E-01   5.3643044780924243E-01   2.2095980994699188E-01   4.4765906644182299E-02\n         3        125   7.8769693952300185E-02   4.4386643511727453E-01   1.6664715711068864E-01   3.9243173308709696E-02\n         3        126   7.5336187668895008E-02   4.0958468712635449E-01   1.6589847892139664E-01   3.7680813092072600E-02\n         3        127   1.1766527944291947E-02   1.6843591399025812E-01   7.0279481486079390E-02   2.0737784960339387E-02\n         3        128   2.8019592583653202E-01   6.3417325807172631E-01   4.4820767498535163E-01   3.1887074040955442E-02\n         3        129   3.2524512178621351E-01   1.4863048805800940E+00   7.0591085215065263E-01   1.1642113569954066E-01\n         3        130   6.1018914686401760E-01   2.4631742404973425E+00   1.1581771810114583E+00   2.1848009271387273E-01\n         3        131   4.5284824600463297E-01   1.9399179106010593E+00   8.5416076794164264E-01   1.8556877330835489E-01\n         3        132   3.7356266229242585E-01   1.7816109168170611E+00   8.2172552077541750E-01   1.7297915197321645E-01\n         3        133   6.2626975433098600E-02   6.6915137255842860E-01   3.4321774781194209E-01   8.5520741119141735E-02\n         3        134   2.1469295573562519E+00   1.4465415836392973E+01   5.1645199318702044E+00   1.4903576759670680E+00\n         3        135   3.8412181566448602E+00   4.5141035558109920E+01   1.3333939239524824E+01   4.2948891700850922E+00\n         3        136   6.7424262239501287E+00   7.4299371488025088E+01   2.2800202201850258E+01   7.2246469317123667E+00\n         3        137   5.1491423943959020E+00   5.1221531785172701E+01   1.6390403274785612E+01   5.2501468391851205E+00\n         3        138   4.4907944420124171E+00   4.4930284520215800E+01   1.4558905851676295E+01   4.8151125188427990E+00\n         3        139   1.0178864457726391E+00   1.5135589932805027E+01   5.3859768861699102E+00   1.8638722600424229E+00\n         3        140   8.0432728962985267E-01   1.7102513600202309E+00   1.0867779516132654E+00   9.0280814459307343E-02\n         3        141   9.6159265250432402E-01   4.8103827489353597E+00   2.1348913197495452E+00   3.6425921602128264E-01\n         3        142   1.7084417649305643E+00   7.4092811785119199E+00   3.5773961611243701E+00   6.6398249698545064E-01\n         3        143   1.3457269141321282E+00   5.1109992882397410E+00   2.6078501736896826E+00   5.3456356810942707E-01\n         3        144   1.0813000530584298E+00   4.6227388430668013E+00   2.4471347361699252E+00   4.9413783346142831E-01\n         3        145   2.2403726420577816E-01   1.7447071498035776E+00   9.8872357615456163E-01   2.1741728803391941E-01\n         3        146   1.1807594579584499E+01   6.1707123163009790E+01   3.1383226534353181E+01   7.1445351823063161E+00\n         3        147   2.4328500097255578E+01   1.6691981592255513E+02   7.9474239288725528E+01   1.9929100380852447E+01\n         3        148   3.4757038661686614E+01   2.6545455495746040E+02   1.2596440893565148E+02   3.1646233296290106E+01\n         3        149   2.1658989992534266E+01   1.8060632495368864E+02   8.5573280694602204E+01   2.1843160095999284E+01\n         3        150   1.9055198918632943E+01   1.6462924230387929E+02   7.8355482333199177E+01   2.0231713976013076E+01\n         3        151   6.8708333676079301E+00   6.5091803763614749E+01   2.9913972184408298E+01   7.9726323568214230E+00\n         3        152   1.6145334411406786E+00   3.8494651243030158E+00   2.3095565245620300E+00   2.5120473731385340E-01\n         3        153   2.4393247239995914E+00   1.1470868457962494E+01   5.2747729006052362E+00   8.9945436945399904E-01\n         3        154   4.2323202068494039E+00   1.8084866993175154E+01   8.8393759987557541E+00   1.5734112662360822E+00\n         3        155   3.0452753320770238E+00   1.2225283352972905E+01   6.3485827551911003E+00   1.2023612538364594E+00\n         3        156   2.6856263095546620E+00   1.0862615450252264E+01   5.8731455895047713E+00   1.1085527988499051E+00\n         3        157   6.9676721221208693E-01   3.8118017346494879E+00   2.3081357705259582E+00   4.5499790961181685E-01\n         3        158   3.9258146106068743E+01   1.6301144587542407E+02   9.7381905377217052E+01   1.7543009662125730E+01\n         3        159   9.2272239680418508E+01   4.1958807740895338E+02   2.5432093358186776E+02   4.6490336991228808E+01\n         3        160   1.3747233932343283E+02   6.5526182731209406E+02   4.0304658632233645E+02   7.3386147880135411E+01\n         3        161   8.9700517942741328E+01   4.4475332791432965E+02   2.7517465236137940E+02   5.0412563093232343E+01\n         3        162   8.1549925458314590E+01   4.0827712775089412E+02   2.5210856549934530E+02   4.6203983875104207E+01\n         3        163   3.3167556682665200E+01   1.5124871606629199E+02   9.6141546561292472E+01   1.7759614163649346E+01\n         3        164  -3.0775128425780430E-16   2.8956424726662368E-03   3.5229061710285188E-05   1.5427872911675736E-04\n         3        165  -3.9072364875383973E-16   1.8042551476390313E-02   2.0806517516575344E-04   8.7943770536477337E-04\n         3        166  -5.1781002647680079E-16   3.6727300885709586E-02   4.0199864462331955E-04   1.7251741594422618E-03\n         3        167  -4.3664583668461169E-16   3.0272036535488420E-02   3.0266042639421882E-04   1.3495987793993602E-03\n         3        168  -3.8578029218908534E-16   3.1440002708932373E-02   2.7068903633678868E-04   1.2194041372432149E-03\n         3        169  -2.2479901181416147E-16   1.1244266222617670E-02   7.6648565423891127E-05   3.8713002063569808E-04\n         3        170  -1.4326086843391004E-16   2.6911199389970938E-02   1.3922287829500099E-03   2.6901380455535409E-03\n         3        171  -1.8296564768592388E-16   1.4603024788637203E-01   5.9258162493008842E-03   1.2284061549278056E-02\n         3        172  -5.7662357137685567E-16   2.8007681985104566E-01   1.0442429212224697E-02   2.1663433325926625E-02\n         3        173  -5.5345559259688319E-16   2.0146782528604656E-01   7.5483793531863621E-03   1.6036214088098071E-02\n         3        174  -6.0198832920155626E-16   1.9466575797780675E-01   6.7849842569831622E-03   1.4482491519691176E-02\n         3        175  -3.7610845661031404E-16   7.2984212150041639E-02   2.1555688092182918E-03   5.1331258805085165E-03\n         3        176  -1.7588106345638890E-16   1.8283865021624053E+00   2.8566920344244656E-01   3.6639836554102817E-01\n         3        177  -1.3755864713011917E-15   6.3030903945064658E+00   8.6093702792754323E-01   1.1453277571424232E+00\n         3        178  -2.7901483901096170E-15   8.8125192582114007E+00   1.3397234537478397E+00   1.7343720637661202E+00\n         3        179  -2.1427450086068749E-15   6.1808673375181558E+00   9.1429196918765510E-01   1.1807664253900949E+00\n         3        180  -1.9335190688632992E-15   5.6527689334842552E+00   8.3553571030109364E-01   1.0724071369097863E+00\n         3        181  -5.0355366094046538E-16   2.1904784304648879E+00   3.1566483867754741E-01   4.2357602648982401E-01\n         3        182   5.8635704865177738E-08   1.1428530712795956E-01   1.4608589329276764E-02   1.6094775343114594E-02\n         3        183   1.8401866271028754E-07   4.7509632356779957E-01   4.8182740920951823E-02   5.9207821191203200E-02\n         3        184   2.8676164401796794E-07   8.7289504058207112E-01   8.0297919022305653E-02   9.7792663719474163E-02\n         3        185   1.9876080547958574E-07   6.2413461133170378E-01   5.6663485798587432E-02   7.0010145600832588E-02\n         3        186   1.6089532570922378E-07   5.6455151072807752E-01   5.1254967219483354E-02   6.3206402445097065E-02\n         3        187   3.8275108362551878E-08   2.2243267177574483E-01   1.7586913066705644E-02   2.3495545307587063E-02\n         3        188   4.0059887200286498E-03   1.0236957837544802E+01   3.5690489254071074E+00   2.0452926304181465E+00\n         3        189   1.0753265902465309E-02   2.5838382671009317E+01   9.0447690138210142E+00   5.2527636101021367E+00\n         3        190   1.7956633874559886E-02   4.1243556678903104E+01   1.4239458782769777E+01   8.1167474101856687E+00\n         3        191   1.2751047908716813E-02   2.8218687738346603E+01   9.7363077230281974E+00   5.5598674222623492E+00\n         3        192   1.1975102897218932E-02   2.5865268156845794E+01   8.9044550911709326E+00   5.0792840085598669E+00\n         3        193   5.2352497324445876E-03   9.4353553756823079E+00   3.3605600381049401E+00   1.9767743893744687E+00\n         3        194   8.7415756718665482E-04   3.1339491522301716E-01   7.4291738102471763E-02   5.6925192193623880E-02\n         3        195   2.1900802052770194E-03   1.0940024998703981E+00   2.1261358846198328E-01   1.7722647253021684E-01\n         3        196   3.6643202926095356E-03   1.9502353022483079E+00   3.4401220340994471E-01   2.8144828321486626E-01\n         3        197   2.6119808680144184E-03   1.3937363933099616E+00   2.3923301131571278E-01   1.9707766135232818E-01\n         3        198   2.3152207456855443E-03   1.2786661396761010E+00   2.1744133873836791E-01   1.7819511369961477E-01\n         3        199   4.0438427525894203E-04   4.8736348400465651E-01   7.8279272780132539E-02   6.8113354104469490E-02\n         3        200   2.5750747459732879E+00   2.7222273248034387E+01   1.2971739295751840E+01   4.6059116472185071E+00\n         3        201   5.8073869523123429E+00   6.9995730686027258E+01   3.3998816998704925E+01   1.1798590009309669E+01\n         3        202   9.2157559927294379E+00   1.1274089624906352E+02   5.4169446485663450E+01   1.8552186714793091E+01\n         3        203   6.1698128080850916E+00   7.8685071088231780E+01   3.7118450335570586E+01   1.2703402554364880E+01\n         3        204   5.6683759096458646E+00   7.2639712321633496E+01   3.3980544477347138E+01   1.1602323154100564E+01\n         3        205   2.6031912084080138E+00   2.7779751176706601E+01   1.2867989995398050E+01   4.4617877583934122E+00\n         3        206   3.2697131996451545E-05   2.6378276538800037E-03   6.7199829704598843E-04   2.2578482400275208E-04\n         3        207   7.5631858497720539E-05   1.2423570669886310E-02   9.7408366099742166E-04   8.2147049614567579E-04\n         3        208   8.1276842664877082E-03   5.2542930521788933E-02   2.6282028986897275E-02   4.2371958517669495E-03\n         3        209   8.3328580041482393E-03   5.6425729576885346E-02   3.0187847634923274E-02   4.4770182093267254E-03\n         3        210   1.0168729245279813E-02   5.7356930602515156E-02   3.1040826871205688E-02   4.6039201596387216E-03\n         3        211   3.0094814396890681E-05   2.7473117717514567E-02   5.6956064348821127E-03   3.0318129709524214E-03\n         3        212   1.0734824259029446E-02   6.2215165812276686E-02   3.3101700409816338E-02   4.4304701397625407E-03\n         3        213   1.0505702600875050E-02   1.1034398994909959E-01   3.4042882476841702E-02   8.2545899269826535E-03\n         3        214   7.4334358987337798E-02   3.3892182844030316E-01   1.7107270941307193E-01   2.1153723338952258E-02\n         3        215   6.5336809191059692E-02   3.0616112167973802E-01   1.7949981904397858E-01   1.8792500948255467E-02\n         3        216   9.1674926734591475E-02   2.7424225285848014E-01   1.8428283055843894E-01   1.7083335977145838E-02\n         3        217   1.9472092929856511E-04   1.5332777121438462E-01   4.1329043682018118E-02   1.8830865254551545E-02\n         3        218   8.8963265326237106E-02   2.5935177232330331E-01   1.6947239367085193E-01   1.4177438348010630E-02\n         3        219   8.8164679614018748E-02   6.8780824100878546E-01   1.9365699840772663E-01   3.8665333014925238E-02\n         3        220   2.7095883608694787E-01   1.5814175661300145E+00   5.3908214334681714E-01   8.4198609754666170E-02\n         3        221   2.2527456067220775E-01   1.3142139609533054E+00   5.0450040550697484E-01   7.7554644247827889E-02\n         3        222   2.6589593700839820E-01   1.1861531389950548E+00   5.0933789678874264E-01   6.9857234133993681E-02\n         3        223   1.7983369992475720E-03   3.8372011353875746E-01   1.3430301932554639E-01   5.1484940656047869E-02\n         3        224   1.1059019335103148E+00   9.8659764129996610E+00   1.9203233395248871E+00   7.4961112365738258E-01\n         3        225   1.4847361337204208E+00   2.2269553414967596E+01   3.7860037370042736E+00   1.6584091736313731E+00\n         3        226   1.3727897115817029E+00   4.0062753135945080E+01   5.6760407779255049E+00   3.1141414996150591E+00\n         3        227   3.1978964321447484E-01   3.0245578989153671E+01   3.6907803132083012E+00   2.5331790041762527E+00\n         3        228   2.4638460017603631E-01   2.9413248309849802E+01   3.3383703324655025E+00   2.3513897897640454E+00\n         3        229   2.9630136327664904E-02   1.1581039868541124E+01   1.1322731009332287E+00   9.0241420778106618E-01\n         3        230   3.1764591970994005E-01   8.9997249884563890E-01   4.8699086931297042E-01   3.7415935307412523E-02\n         3        231   3.1975532077832947E-01   2.2818553099967582E+00   6.4021767642270777E-01   1.3941542767636569E-01\n         3        232   7.3867957175300869E-01   4.7485625680297474E+00   1.3977138938709239E+00   2.9874473868411566E-01\n         3        233   5.4031884326134050E-01   3.8048229752764842E+00   1.1889042895373070E+00   2.6858418539254403E-01\n         3        234   5.8228542693342600E-01   3.5067053344009222E+00   1.1672353368073323E+00   2.4677834680067995E-01\n         3        235   3.2096214464731807E-02   9.3087719914818812E-01   3.3980000757332657E-01   1.1340581398017179E-01\n         3        236   3.4938935211865116E+00   3.0695240526639942E+01   1.3886065855839069E+01   4.4675185710920697E+00\n         3        237   6.4231524118637209E+00   7.9262009806797082E+01   3.3328315084147142E+01   1.1081081101232297E+01\n         3        238   1.0923137383219416E+01   1.3592262308209916E+02   5.6436610143560515E+01   1.8700321773412504E+01\n         3        239   6.3184712502113891E+00   1.0069516826110501E+02   4.0136544450107124E+01   1.3796393965570324E+01\n         3        240   5.3191611255827569E+00   9.1029183169967141E+01   3.6573861568744547E+01   1.2666050765260943E+01\n         3        241   1.2759090358542184E+00   3.2270527431922787E+01   1.3613613344904712E+01   5.2217132501491426E+00\n         3        242   8.0519136118659684E-01   2.2102940351105644E+00   1.1183590113685711E+00   1.0756544391484510E-01\n         3        243   8.3087850509451056E-01   5.2842849897717903E+00   1.7275496320649586E+00   3.9042824061406040E-01\n         3        244   1.7305295302897865E+00   1.0466454757896404E+01   3.3526145880551796E+00   7.8557123086721481E-01\n         3        245   1.3068624685786863E+00   8.2259926114154940E+00   2.6596638964419168E+00   6.7861373482783616E-01\n         3        246   1.2870353484677513E+00   7.7015843195954989E+00   2.5425187491159140E+00   6.2401626811390032E-01\n         3        247   1.7631198952733065E-01   2.3263502049460589E+00   7.9376489248038495E-01   2.4283433799790308E-01\n         3        248   9.0867824001203648E+00   8.0485956467869158E+01   4.2738291334737788E+01   1.0912391194019976E+01\n         3        249   1.8169908871521159E+01   2.1012862175095657E+02   1.0968486366895851E+02   2.9792359092096333E+01\n         3        250   2.2489794881396243E+01   3.5420108028233875E+02   1.7729477415271691E+02   4.9158689042876702E+01\n         3        251   1.2480196535139823E+01   2.5029610471446395E+02   1.2177726508141885E+02   3.4704954826044847E+01\n         3        252   1.1411346250800655E+01   2.3088200105996626E+02   1.1156380011427476E+02   3.2229221614494399E+01\n         3        253   5.7217542683103071E+00   8.6396315464252567E+01   4.2294910688687096E+01   1.3103287123206963E+01\n         3        254  -3.2773975569480938E-16   2.1447442200417132E-03   1.0119828147132442E-06   2.7423897154973828E-05\n         3        255  -3.6047495463912627E-16   3.0341677286782232E-03   3.5752709665374702E-06   5.4269337774467655E-05\n         3        256  -4.0270793892653777E-16   2.6483406784484184E-03   3.3794536693802627E-06   4.5759647026655676E-05\n         3        257  -4.2628941742518535E-16   2.2685322379359693E-03   3.0820218208106951E-06   3.9708758775674887E-05\n         3        258  -4.2873373632860711E-16   9.1003512280071440E-03   1.4897794248356281E-05   1.5250500610672663E-04\n         3        259  -1.1261745032298863E-15   5.8554793387908699E-02   2.5976942910112093E-04   1.3385083029844732E-03\n         3        260  -1.0083299962301777E-15   7.9578826052966165E-02   8.2327100123485758E-04   3.4690548888292481E-03\n         3        261  -1.1144931298590368E-15   6.9518999450832064E-02   7.5498463529483800E-04   3.2606637998928759E-03\n         3        262  -1.1634058081514093E-15   5.9759895625134757E-02   6.9583757683056805E-04   3.0451048181020252E-03\n         3        263  -2.9494688965407553E-16   1.2465857385767573E-02   1.7580610849245954E-04   7.7787529677283865E-04\n         3        264  -1.2477728111140212E-16   6.8436227755417495E-02   6.9700832561874382E-04   1.9137407189687510E-03\n         3        265  -3.9107201835958415E-16   2.8303081472611008E-01   5.2069746301960703E-03   1.1500093943178538E-02\n         3        266  -9.8485775570098949E-16   4.0113097805309528E-01   1.3439217996183658E-02   2.7621741281772763E-02\n         3        267  -8.4920795071881915E-16   3.1514167535087390E-01   1.1538340076691883E-02   2.5235009957941212E-02\n         3        268  -8.4323739566359950E-16   2.7468102831367447E-01   1.0605302531582927E-02   2.3563937221349709E-02\n         3        269  -3.2247164227979080E-16   7.3043620665020265E-02   3.1244687513743920E-03   7.2272344360553411E-03\n         3        270  -1.1823417791772494E-16   2.4247287087898184E+00   1.9392270959300970E-01   3.2820213967424283E-01\n         3        271  -5.4323712488909992E-16   5.3532211878454978E+00   4.2858229330890346E-01   6.1376242798427783E-01\n         3        272  -1.0844860785944083E-15   7.9386919100731141E+00   7.9253161356007051E-01   1.0503593720128770E+00\n         3        273  -8.6018042226012912E-16   5.2499651400177028E+00   5.9950827478080260E-01   8.2042352813123798E-01\n         3        274  -8.6458881926565691E-16   5.1408617680688451E+00   5.5638387205207984E-01   7.6867031119897877E-01\n         3        275  -8.7711231321440461E-16   2.1400405707354153E+00   2.0214426027202781E-01   3.2961328939677464E-01\n         3        276   4.4479365240249114E-08   2.1086008503487477E-01   8.5256964659873903E-03   1.1415405771673940E-02\n         3        277   2.4812051655587384E-07   7.5239192273064748E-01   3.8593414492823566E-02   4.7503414760012429E-02\n         3        278   3.0953429801891321E-07   1.1225745740607909E+00   8.4109702548192875E-02   1.0231345944226115E-01\n         3        279   1.6192460228885639E-07   8.2715009604378142E-01   6.7630259191043124E-02   8.9625775407566735E-02\n         3        280   1.0318591479768654E-07   7.3172722273513202E-01   6.1871785006430105E-02   8.2981361229504669E-02\n         3        281   8.1582984547041242E-09   2.1856535256040238E-01   1.9495438983860466E-02   2.7808680165757528E-02\n         3        282   4.5629679558248865E-03   1.2026740730782761E+01   3.5100487367055351E+00   2.0939166464846566E+00\n         3        283   1.2604526050270057E-02   3.0576168345064108E+01   8.1000483182910745E+00   5.1774224381423188E+00\n         3        284   1.9734520894264494E-02   4.9523830350229616E+01   1.3222957206475980E+01   8.0717436482540332E+00\n         3        285   1.3248056609838675E-02   3.4546480820458584E+01   9.1737647246003622E+00   5.5572017130914526E+00\n         3        286   1.1962573059349417E-02   3.0554688695127503E+01   8.4362126502853165E+00   5.0468927117410374E+00\n         3        287   5.1980855161655251E-03   1.1460518808903680E+01   3.1351409250053406E+00   1.9517109954111269E+00\n         3        288   5.5636368616198101E-04   4.7041825488507866E-01   4.7655576506132398E-02   4.0661124491805992E-02\n         3        289   2.3057413590377648E-03   1.5509771103139069E+00   1.6795357441007275E-01   1.3945032042678271E-01\n         3        290   3.5703756032694919E-03   2.3167493837806430E+00   3.2697116470910564E-01   2.7060675325036782E-01\n         3        291   1.6448601832993823E-03   1.6408812184341692E+00   2.4966729941857274E-01   2.2495216497313866E-01\n         3        292   1.2200564657208199E-03   1.4694771117408731E+00   2.2798143421561537E-01   2.0582726875614557E-01\n         3        293   4.9262332390579951E-04   4.6724608688069008E-01   7.5327620507255819E-02   7.1165647379917721E-02\n         3        294   1.1007878765033776E+00   2.7946175325109632E+01   1.2227471804665463E+01   4.5571114701800797E+00\n         3        295   2.3593456376136994E+00   7.6245027074676116E+01   3.0033820715525284E+01   1.1394282713910393E+01\n         3        296   4.6249701123897200E+00   1.1965266802200235E+02   4.7984784874994268E+01   1.7997173700650130E+01\n         3        297   3.5754319612643890E+00   8.0372970678573338E+01   3.2869155054656360E+01   1.2492882471346771E+01\n         3        298   3.6766112868651830E+00   7.1699639394051474E+01   3.0343831925300677E+01   1.1535117031331541E+01\n         3        299   1.4848792726072879E+00   2.9470880181117529E+01   1.1675345187452214E+01   4.6232672614899188E+00\n         3        300  -4.7560871347965801E-17   1.8327284650080094E-03   1.2646933605987180E-05   7.3403130263805210E-05\n         3        301  -4.5638678264011175E-17   2.0303834699724626E-03   1.2660605427638042E-05   7.8504930724904366E-05\n         3        302  -3.5412399071936617E-17   2.0007891374034794E-03   1.3605090688523725E-05   8.2288142870173126E-05\n         3        303  -5.9807940588296230E-17   2.5135521402326395E-02   1.5551833533781060E-04   1.2130518119413507E-03\n         3        304  -1.3468221305837976E-16   2.3050032554245023E-01   2.7116194116442150E-03   1.2531112386622901E-02\n         3        305  -3.0868531471921408E-16   6.8866302155125880E-01   1.0640129957363948E-02   4.1199678494024013E-02\n         3        306  -2.9163261466470822E-16   7.5839430849216016E-01   1.0159951948206352E-02   4.2369089794662980E-02\n         3        307  -2.2039022073357421E-16   7.4728523527420820E-01   1.0638094132775338E-02   4.3959819327677438E-02\n         3        308  -1.9098688330695927E-16   3.9919102123441580E-01   4.5680053059795290E-03   2.4018164130766496E-02\n         3        309  -1.4927054569349683E-17   5.4288060143951669E-03   1.2646124594880721E-04   3.4917625077484119E-04\n         3        310   0.0000000000000000E+00   1.5585417274844278E-02   3.9486990848092645E-04   1.0658555350373041E-03\n         3        311   0.0000000000000000E+00   1.7039639851509056E-02   3.5661737119803449E-04   1.0722969492159731E-03\n         3        312   0.0000000000000000E+00   1.6765634107290116E-02   3.6354432449997403E-04   1.1234112108672919E-03\n         3        313  -1.6874946464159030E-18   9.1465856708756992E-03   1.5271678756041579E-04   5.8704379061977623E-04\n         3        314  -7.6655367114397210E-16   6.3128931254110887E-01   4.6172806271438591E-02   8.5474619706774876E-02\n         3        315   6.7994130105837849E-17   3.1715634736016582E+00   3.2809747120755345E-01   4.5621415671956828E-01\n         3        316   2.9301464602148734E-07   5.7571549511923807E+00   6.5875204898820228E-01   7.8442966002571146E-01\n         3        317   2.6389037602795601E-07   4.4976121935612037E+00   5.0475908322295127E-01   6.1790286433623542E-01\n         3        318   1.6261811765265133E-07   4.2795420466560214E+00   4.7788920924137318E-01   5.9684317850444413E-01\n         3        319   0.0000000000000000E+00   1.7276650817778056E+00   1.8873727410404212E-01   2.7521743580783409E-01\n         3        320   7.8335248314188614E-11   3.6499757463674606E-03   1.7787909767522534E-04   3.4973829267240177E-04\n         3        321   3.3849207237937759E-08   2.3779041650772107E-02   1.5421769223248674E-03   2.5763170192341350E-03\n         3        322   1.8142915388567406E-07   5.7717883167940132E-02   3.7846054172045495E-03   6.2797228426095912E-03\n         3        323   1.7570652428813138E-07   6.0904566778856965E-02   3.1628360488713762E-03   5.8433085971484880E-03\n         3        324   1.7951302861338428E-07   5.9527449290661186E-02   3.1077168524934191E-03   5.9525480201561426E-03\n         3        325   2.7185832177170496E-08   3.4758679184872882E-02   1.2727481788324599E-03   3.0404858020360143E-03\n         3        326   3.6729299654012415E-04   2.6660410072146479E+00   3.6809792778420070E-01   3.3555332324089504E-01\n         3        327   1.7031335464568816E-02   7.5226104125868947E+00   1.7464646710982246E+00   1.2943455063438440E+00\n         3        328   6.0288306939422699E-02   1.3125400614483535E+01   3.0380350184825127E+00   2.0851125801436869E+00\n         3        329   3.1957087804619949E-02   1.0036474514483098E+01   2.1665861225215042E+00   1.5281150671522268E+00\n         3        330   2.5177921586288610E-02   9.3706637976168992E+00   1.9899469242603924E+00   1.4112096780264611E+00\n         3        331   9.8988167484363059E-04   3.1756759318717269E+00   7.8534243572036044E-01   6.2547885393945013E-01\n"
  },
  {
    "path": "examples/potentials/Anisole_SCAN/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.9749524986944524E+00 a         1     0     1     1     1\n -1.1727677476771443E+00 a         2     0     1     1     2\n  2.3670083874627159E+00 a         3     0     1     1     3\n  1.5350008890598528E+00 a         4     0     1     1     4\n -2.4991458866543339E+00 a         5     0     1     1     5\n -8.1048167707954342E+00 a         6     0     1     1     6\n -2.5122024995587542E+00 a         7     0     1     1     7\n -5.9184160196994329E+00 a         8     0     1     1     8\n  6.2405897016146570E+00 a         9     0     1     1     9\n  6.1011687863436442E-02 a        10     0     1     1    10\n  5.0370507950967633E+00 a        11     0     1     1    11\n -6.9388217299408588E+00 a        12     0     1     1    12\n -4.9243912303720512E+00 a        13     0     1     1    13\n -6.9840027709581705E+00 a        14     0     1     1    14\n  2.1815487728443553E-01 a        15     0     1     1    15\n -8.9983343757076675E+00 a        16     0     1     1    16\n -9.2862731322621155E+00 a        17     0     1     1    17\n  3.8416033169906152E+00 a        18     0     1     1    18\n -2.5373093635544275E-01 a        19     0     1     1    19\n  4.1105222124275249E+00 a        20     0     1     1    20\n  1.2844973733179619E+00 a        21     0     1     1    21\n -3.0634143478079601E+00 a        22     0     1     1    22\n -6.7997728833691147E+00 a        23     0     1     1    23\n  5.4005303860896410E+00 a        24     0     1     1    24\n  1.2540506323738827E+00 a        25     0     1     1    25\n  2.8350326218703645E+00 a        26     0     1     1    26\n  1.1168814583606019E+00 a        27     0     1     1    27\n  1.5315593736281889E+00 a        28     0     1     1    28\n  1.0286846439450088E+01 a        29     0     1     1    29\n -7.4750008131612091E+00 a        30     0     1     1    30\n -1.0459128443072387E+00 a        31     0     2     1     1\n  2.2016668904962180E+00 a        32     0     2     1     2\n -1.5034013149239440E+01 a        33     0     2     1     3\n -1.0584707585295450E-01 a        34     0     2     1     4\n -4.6247028380296547E+00 a        35     0     2     1     5\n  1.0992377487246067E+01 a        36     0     2     1     6\n  3.2909805579001836E+00 a        37     0     2     1     7\n -8.5144529541146046E+00 a        38     0     2     1     8\n -5.2514364793564958E+00 a        39     0     2     1     9\n -6.6926976061835477E+00 a        40     0     2     1    10\n -1.3123012288190221E+00 a        41     0     2     1    11\n  3.2389226200578323E+00 a        42     0     2     1    12\n -5.2909732571980967E+00 a        43     0     2     1    13\n -2.1376829600147609E-01 a        44     0     2     1    14\n -1.7239810378011997E+00 a        45     0     2     1    15\n -1.3105069462509715E+00 a        46     0     2     1    16\n -1.3068789187179304E+00 a        47     0     2     1    17\n  2.1543056322756007E+00 a        48     0     2     1    18\n  3.0911113639642647E+00 a        49     0     2     1    19\n  5.9213173902677085E-01 a        50     0     2     1    20\n -6.2844167812212079E+00 a        51     0     2     1    21\n -2.4883531796341982E+00 a        52     0     2     1    22\n -1.9120468016085304E+00 a        53     0     2     1    23\n -1.5017392146225348E+00 a        54     0     2     1    24\n -1.6738708882802966E+00 a        55     0     2     1    25\n -3.2885712224907260E+00 a        56     0     2     1    26\n  7.2452328630734453E+00 a        57     0     2     1    27\n  3.2784607839923883E+00 a        58     0     2     1    28\n  3.8243107317169431E+00 a        59     0     2     1    29\n -4.9623718979595992E+00 a        60     0     2     1    30\n -8.5296950293464024E-01 a        61     0     3     1     1\n  1.2473240592262670E-01 a        62     0     3     1     2\n  2.6085768101627078E+00 a        63     0     3     1     3\n -1.2758071049907285E+00 a        64     0     3     1     4\n -7.1390772098791082E+00 a        65     0     3     1     5\n -4.9960391246879494E+00 a        66     0     3     1     6\n  2.2882542591792583E+00 a        67     0     3     1     7\n  2.9181752383366186E+00 a        68     0     3     1     8\n  4.9096460756762426E+00 a        69     0     3     1     9\n  1.5793889008331435E+01 a        70     0     3     1    10\n  8.6165028726388613E+00 a        71     0     3     1    11\n -3.8911827041031031E+00 a        72     0     3     1    12\n  1.5433957974347541E+01 a        73     0     3     1    13\n -3.0705819276220442E-01 a        74     0     3     1    14\n -1.7156567467377482E+00 a        75     0     3     1    15\n -2.7821307962279564E+00 a        76     0     3     1    16\n  7.4560839875927281E+00 a        77     0     3     1    17\n -7.3244485727116464E+00 a        78     0     3     1    18\n  3.9404530211374622E+00 a        79     0     3     1    19\n -1.0370177555966073E+01 a        80     0     3     1    20\n  8.3251093503406857E+00 a        81     0     3     1    21\n  1.4812598567883057E+00 a        82     0     3     1    22\n -1.5477361444698505E+00 a        83     0     3     1    23\n -1.8220081234592883E-01 a        84     0     3     1    24\n  3.0688673637766910E+00 a        85     0     3     1    25\n -3.6247386887118775E+00 a        86     0     3     1    26\n -6.3432452417448970E-01 a        87     0     3     1    27\n -2.7759297384433865E+00 a        88     0     3     1    28\n  3.1919234130362124E+00 a        89     0     3     1    29\n -8.0091571843446250E+00 a        90     0     3     1    30\n  3.8344709043599310E+00 a        91     0     4     1     1\n -1.9300405913538296E-01 a        92     0     4     1     2\n -1.9823179747094428E+00 a        93     0     4     1     3\n  7.6781526810043921E-01 a        94     0     4     1     4\n  4.1636488412151005E+00 a        95     0     4     1     5\n  5.0741051344132275E+00 a        96     0     4     1     6\n -3.7045875657411163E+00 a        97     0     4     1     7\n -5.0704576825257046E+00 a        98     0     4     1     8\n  7.3445017709170788E+00 a        99     0     4     1     9\n -4.1595054128267550E-01 a       100     0     4     1    10\n  3.2792459325941299E+00 a       101     0     4     1    11\n -2.5663906959861453E+00 a       102     0     4     1    12\n -4.4689399606758551E+00 a       103     0     4     1    13\n -5.9904761371675541E-01 a       104     0     4     1    14\n -1.4535627754830140E+00 a       105     0     4     1    15\n -2.4782370306397374E+00 a       106     0     4     1    16\n -1.0573523001523624E+00 a       107     0     4     1    17\n -2.7218457913175982E+00 a       108     0     4     1    18\n -8.9951201806446979E-01 a       109     0     4     1    19\n  7.4431273344766975E+00 a       110     0     4     1    20\n  8.0904930305595695E+00 a       111     0     4     1    21\n -4.4013274261764721E+00 a       112     0     4     1    22\n -4.8902121989832068E+00 a       113     0     4     1    23\n -2.3283709503061019E+00 a       114     0     4     1    24\n  3.2065988350721724E+00 a       115     0     4     1    25\n  2.9299747435943084E+00 a       116     0     4     1    26\n -1.1061076405947587E+00 a       117     0     4     1    27\n  3.1074722061958737E+00 a       118     0     4     1    28\n -1.7659707266361965E-01 a       119     0     4     1    29\n -1.0797693094495223E+01 a       120     0     4     1    30\n  1.4221292413637004E+01 a       121     0     5     1     1\n  2.8432579806170679E+00 a       122     0     5     1     2\n  1.5785524951151102E+00 a       123     0     5     1     3\n -1.4644526889040106E+00 a       124     0     5     1     4\n -3.3289150025691456E+00 a       125     0     5     1     5\n -2.8438341877181283E+00 a       126     0     5     1     6\n  3.3314856043503482E+00 a       127     0     5     1     7\n 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1.7947485733618898E+00 a      1952     0    66     1     2\n  2.0959895299187772E-01 a      1953     0    66     1     3\n -6.0033698124291153E+00 a      1954     0    66     1     4\n  2.7048619888400065E+00 a      1955     0    66     1     5\n -9.2401278006473320E-01 a      1956     0    66     1     6\n  2.2970609315213792E+00 a      1957     0    66     1     7\n -3.9856707470005639E+00 a      1958     0    66     1     8\n -7.7588786083481889E+00 a      1959     0    66     1     9\n -3.2271977679020423E+00 a      1960     0    66     1    10\n  9.7203920306584148E+00 a      1961     0    66     1    11\n  8.2653327613231813E+00 a      1962     0    66     1    12\n  4.4631913563386734E+00 a      1963     0    66     1    13\n -3.6350317578683726E+00 a      1964     0    66     1    14\n  4.6316096619835045E+00 a      1965     0    66     1    15\n -2.7467169789066368E+00 a      1966     0    66     1    16\n -6.6574789436036612E+00 a      1967     0    66     1    17\n -1.5385535871292246E+00 a      1968     0    66     1    18\n  2.4473650361236926E-01 a      1969     0    66     1    19\n -1.0791127850009536E+01 a      1970     0    66     1    20\n  1.9644893545762492E+00 a      1971     0    66     1    21\n  1.9137157405673406E+00 a      1972     0    66     1    22\n  1.4746864615874236E+00 a      1973     0    66     1    23\n  1.9112012825013593E+00 a      1974     0    66     1    24\n  2.8073921461437262E-01 a      1975     0    66     1    25\n  8.2091986223370288E+00 a      1976     0    66     1    26\n -2.9403883811907647E+00 a      1977     0    66     1    27\n -5.3793413165501898E+00 a      1978     0    66     1    28\n -1.5450727803025233E+00 a      1979     0    66     1    29\n  5.0508009062519026E+00 a      1980     0    66     1    30\n  7.8536161605245436E-01 a      1981     0    67     1     1\n -2.6709168712707467E+00 a      1982     0    67     1     2\n -9.7260931210100559E+00 a      1983     0    67     1     3\n  3.3261616476390929E+00 a      1984     0    67     1     4\n  9.4686794460224954E-01 a      1985     0    67     1     5\n -3.1829794935510103E+00 a      1986     0    67     1     6\n -1.2745485150902964E+00 a      1987     0    67     1     7\n  2.7415529956496347E+00 a      1988     0    67     1     8\n  1.0416936232781232E+01 a      1989     0    67     1     9\n -3.4948346810260222E+00 a      1990     0    67     1    10\n -3.6972466821379948E+00 a      1991     0    67     1    11\n  5.4734513600827803E+00 a      1992     0    67     1    12\n  2.7666615871144429E-01 a      1993     0    67     1    13\n  1.8115784245712951E+00 a      1994     0    67     1    14\n -5.1364867929403335E+00 a      1995     0    67     1    15\n -6.0652859795628178E+00 a      1996     0    67     1    16\n  5.0942159216521974E+00 a      1997     0    67     1    17\n -2.9650891295409143E+00 a      1998     0    67     1    18\n -3.0341786355391638E+00 a      1999     0    67     1    19\n  3.7296534296465484E+00 a      2000     0    67     1    20\n -3.1405494615311662E+00 a      2001     0    67     1    21\n  1.2770074054823559E+00 a      2002     0    67     1    22\n -2.5845857098984553E+00 a      2003     0    67     1    23\n -6.4165587287534231E+00 a      2004     0    67     1    24\n  4.1448655661687619E+00 a      2005     0    67     1    25\n -7.7538037876528403E+00 a      2006     0    67     1    26\n  4.9618143048011104E-01 a      2007     0    67     1    27\n -1.5255690572718743E+00 a      2008     0    67     1    28\n  4.6683028122337555E-01 a      2009     0    67     1    29\n -3.1365879206426150E+00 a      2010     0    67     1    30\n  6.3282693610360141E+00 a      2011     0    68     1     1\n  1.2392099095198863E+00 a      2012     0    68     1     2\n  9.1746538030991012E+00 a      2013     0    68     1     3\n -5.9708841427319692E-01 a      2014     0    68     1     4\n -4.1104907669703661E-01 a      2015     0    68     1     5\n  2.5495064414901734E+00 a      2016     0    68     1     6\n -5.0523590635423945E+00 a      2017     0    68     1     7\n -3.1333654981583425E-01 a      2018     0    68     1     8\n -6.9992779295473166E+00 a      2019     0    68     1     9\n  1.0170006098975137E+00 a      2020     0    68     1    10\n -5.0261351178342233E+00 a      2021     0    68     1    11\n -6.8391330317858019E+00 a      2022     0    68     1    12\n  8.9762857799992926E+00 a      2023     0    68     1    13\n  4.3534340611862921E-01 a      2024     0    68     1    14\n  1.9974447147339027E+00 a      2025     0    68     1    15\n -2.4548722664283313E+00 a      2026     0    68     1    16\n  1.6253062784357770E+00 a      2027     0    68     1    17\n  1.6463814109756882E+00 a      2028     0    68     1    18\n  5.3912511671194148E+00 a      2029     0    68     1    19\n  2.6651909474065549E+00 a      2030     0    68     1    20\n -3.7598832707041372E+00 a      2031     0    68     1    21\n  1.4974387094926773E+00 a      2032     0    68     1    22\n  1.0082269273131633E+01 a      2033     0    68     1    23\n  1.1779490000724750E+00 a      2034     0    68     1    24\n -4.7148736936377658E+00 a      2035     0    68     1    25\n -1.3741753705419271E+00 a      2036     0    68     1    26\n  8.0374256732235523E+00 a      2037     0    68     1    27\n  3.6935306369121830E+00 a      2038     0    68     1    28\n -5.1321368081796026E-01 a      2039     0    68     1    29\n -5.1077642241291112E+00 a      2040     0    68     1    30\n  1.9807541165468572E+00 a      2041     0    69     1     1\n  2.5054025095227483E-01 a      2042     0    69     1     2\n -4.6444879546875328E-01 a      2043     0    69     1     3\n -4.8623212892192047E-01 a      2044     0    69     1     4\n  2.0999145547294251E+00 a      2045     0    69     1     5\n  1.7004704390605649E+00 a      2046     0    69     1     6\n -2.6404964045969797E+00 a      2047     0    69     1     7\n 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4.6020027621545241E+00 a      2128     0    71     1    28\n  2.8208943276438134E+00 a      2129     0    71     1    29\n  1.0462529186919253E+01 a      2130     0    71     1    30\n -2.2944939187288442E+00 a      2131     0    72     1     1\n -2.0130726368006697E+00 a      2132     0    72     1     2\n -1.6669130103052651E-01 a      2133     0    72     1     3\n  5.7237350789648911E-01 a      2134     0    72     1     4\n -4.0842150767513203E+00 a      2135     0    72     1     5\n -3.0665372331711800E+00 a      2136     0    72     1     6\n -1.5771148654488978E+00 a      2137     0    72     1     7\n  3.4778038388480392E+00 a      2138     0    72     1     8\n -2.2072463770283339E+00 a      2139     0    72     1     9\n  5.2879308581346984E-01 a      2140     0    72     1    10\n -4.2364229375964770E+00 a      2141     0    72     1    11\n -3.8332514720832642E+00 a      2142     0    72     1    12\n -3.4288325323236548E+00 a      2143     0    72     1    13\n 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3.6630341679761244E-02 a     10918     1    18     2    18\n -5.0792796520547974E-02 a     10919     1    18     2    19\n  7.0833040191672703E-01 a     10920     1    18     2    20\n  1.7356252860967805E-01 a     10921     1    19     2     1\n -1.7815086525976125E+00 a     10922     1    19     2     2\n -8.5816460549365176E-02 a     10923     1    19     2     3\n  1.6094148968262750E-01 a     10924     1    19     2     4\n -1.3189307761345115E+00 a     10925     1    19     2     5\n -7.9891068125627750E-03 a     10926     1    19     2     6\n  4.8789709767950856E-01 a     10927     1    19     2     7\n  3.2650073848671896E-01 a     10928     1    19     2     8\n  1.7941477416501972E-01 a     10929     1    19     2     9\n  1.4158343426706737E+00 a     10930     1    19     2    10\n -1.3210791372370589E-01 a     10931     1    19     2    11\n -6.0077674024177408E-01 a     10932     1    19     2    12\n -4.5795018704142820E-01 a     10933     1    19     2    13\n -4.6692096109717252E+00 a     10934     1    19     2    14\n -1.0735704417732042E+00 a     10935     1    19     2    15\n  3.5969529334416922E-01 a     10936     1    19     2    16\n  2.4722970647302156E-01 a     10937     1    19     2    17\n  2.6421944644497780E-01 a     10938     1    19     2    18\n  1.4568593605792513E-01 a     10939     1    19     2    19\n  8.6695627702796052E-01 a     10940     1    19     2    20\n -1.9961379955500044E-01 a     10941     1    20     2     1\n -2.6584678115753761E+00 a     10942     1    20     2     2\n  3.5037603966485020E-01 a     10943     1    20     2     3\n  6.4288054133549799E-01 a     10944     1    20     2     4\n  4.7063665047517633E-01 a     10945     1    20     2     5\n -1.0751711284345449E+00 a     10946     1    20     2     6\n -1.2484990492146704E+00 a     10947     1    20     2     7\n -3.0182723124311528E-01 a     10948     1    20     2     8\n  3.6230727024036902E-01 a     10949     1    20     2     9\n  1.9629680525407617E-01 a     10950     1    20     2    10\n -1.4971500547659333E-01 a     10951     1    20     2    11\n  1.4594159059341749E-01 a     10952     1    20     2    12\n -3.5312832189128124E-01 a     10953     1    20     2    13\n  2.6149503310347626E+00 a     10954     1    20     2    14\n -3.3944097071288581E+00 a     10955     1    20     2    15\n -6.1772432875414762E-01 a     10956     1    20     2    16\n -1.9228874002055532E+00 a     10957     1    20     2    17\n -3.4342371063763527E-01 a     10958     1    20     2    18\n  2.3730274475565197E-01 a     10959     1    20     2    19\n -1.6622100249507246E-01 a     10960     1    20     2    20\n  1.6538516439074280E-01 a     10961     1    21     2     1\n  8.4511755161776425E-01 a     10962     1    21     2     2\n -3.1494337922338445E-01 a     10963     1    21     2     3\n  1.3736966246950144E+00 a     10964     1    21     2     4\n  2.1776723730374942E-01 a     10965     1    21     2     5\n -4.2126548317296741E-01 a     10966     1    21     2     6\n -7.2244940578070238E-01 a     10967     1    21     2     7\n  2.7381961319773718E-01 a     10968     1    21     2     8\n -9.1465687668451520E-02 a     10969     1    21     2     9\n  3.1836333212979084E-01 a     10970     1    21     2    10\n  5.1775590130850431E-02 a     10971     1    21     2    11\n  4.1191453992266612E-02 a     10972     1    21     2    12\n -2.0731778833262227E+00 a     10973     1    21     2    13\n  1.8257149614219674E+00 a     10974     1    21     2    14\n -7.4426166913095881E-01 a     10975     1    21     2    15\n  3.8633210652992128E-01 a     10976     1    21     2    16\n  1.5511986191521196E-01 a     10977     1    21     2    17\n  6.2340655210495766E-01 a     10978     1    21     2    18\n -6.1453969750886905E-01 a     10979     1    21     2    19\n  8.4040227855261496E-01 a     10980     1    21     2    20\n -3.5696956583101297E-01 a     10981     1    22     2     1\n  8.0563377504006140E-01 a     10982     1    22     2     2\n  8.6025927668714897E-01 a     10983     1    22     2     3\n -4.1039262107675983E-01 a     10984     1    22     2     4\n -1.3528168969245764E+00 a     10985     1    22     2     5\n  4.0143993613758875E+00 a     10986     1    22     2     6\n  1.0779186199945607E+00 a     10987     1    22     2     7\n  6.1374726170127503E-01 a     10988     1    22     2     8\n  5.0210695810812223E-02 a     10989     1    22     2     9\n  1.5544826334084025E+00 a     10990     1    22     2    10\n  1.2867093433958943E-01 a     10991     1    22     2    11\n  1.3050512966266908E-01 a     10992     1    22     2    12\n  6.3797235523888962E-01 a     10993     1    22     2    13\n -1.1973484563321202E+00 a     10994     1    22     2    14\n  2.8052017234698639E+00 a     10995     1    22     2    15\n -2.1349379084553929E-01 a     10996     1    22     2    16\n -8.1369068958726906E-02 a     10997     1    22     2    17\n -4.0877427036235486E-01 a     10998     1    22     2    18\n  5.9646659477283509E-02 a     10999     1    22     2    19\n -1.8374682688422905E+00 a     11000     1    22     2    20\n -6.6525929481377333E-01 a     11001     1    23     2     1\n -2.8503045260742526E+00 a     11002     1    23     2     2\n  3.6400097287117419E-02 a     11003     1    23     2     3\n  1.0167603036316764E+00 a     11004     1    23     2     4\n -5.1981713699148002E-01 a     11005     1    23     2     5\n -8.9729817381079624E-01 a     11006     1    23     2     6\n  5.2196161272443087E-01 a     11007     1    23     2     7\n -5.6627120261110009E-01 a     11008     1    23     2     8\n  2.8799332952580542E-01 a     11009     1    23     2     9\n  9.6869505348576787E-02 a     11010     1    23     2    10\n -1.2106475521259337E-01 a     11011     1    23     2    11\n  1.2967038644479381E-01 a     11012     1    23     2    12\n -2.0208952253587387E+00 a     11013     1    23     2    13\n  1.5345434396474893E+00 a     11014     1    23     2    14\n -5.6402760746375535E-01 a     11015     1    23     2    15\n  7.5895764607096128E-01 a     11016     1    23     2    16\n -1.1658619688124652E+00 a     11017     1    23     2    17\n -6.2697131457677091E-01 a     11018     1    23     2    18\n -7.8394417563141361E-01 a     11019     1    23     2    19\n -1.9425570749291274E+00 a     11020     1    23     2    20\n -4.1605424796216171E-02 a     11021     1    24     2     1\n  2.9086371382185239E-01 a     11022     1    24     2     2\n  6.4266672226547084E-01 a     11023     1    24     2     3\n  3.3597457784610085E-01 a     11024     1    24     2     4\n  2.2440267680897974E+00 a     11025     1    24     2     5\n -2.8267672061048787E+00 a     11026     1    24     2     6\n  1.2539806417210586E-01 a     11027     1    24     2     7\n  3.3955070296327106E-01 a     11028     1    24     2     8\n  2.1206806870999271E-02 a     11029     1    24     2     9\n -1.3055929285183796E+00 a     11030     1    24     2    10\n -5.4977832772496911E-02 a     11031     1    24     2    11\n -9.8952779410743402E-02 a     11032     1    24     2    12\n -1.1871643558352938E+00 a     11033     1    24     2    13\n  1.7054266728729151E+00 a     11034     1    24     2    14\n  2.2436383768933106E+00 a     11035     1    24     2    15\n  8.8928672831608685E-02 a     11036     1    24     2    16\n -4.1793381018844172E-01 a     11037     1    24     2    17\n  6.0061801500315794E-02 a     11038     1    24     2    18\n -5.7122210995832112E-01 a     11039     1    24     2    19\n -2.9180648978698820E-01 a     11040     1    24     2    20\n  4.2388725382392761E-01 a     11041     1    25     2     1\n -2.6026140950249150E+00 a     11042     1    25     2     2\n  6.0233398456913023E-01 a     11043     1    25     2     3\n  1.3339099909248124E+00 a     11044     1    25     2     4\n  2.0797828929811355E+00 a     11045     1    25     2     5\n -3.2457788639776042E+00 a     11046     1    25     2     6\n -2.6390838224388316E+00 a     11047     1    25     2     7\n -1.3065567973540573E+00 a     11048     1    25     2     8\n  6.4780807701049337E-01 a     11049     1    25     2     9\n  1.3047302548549387E+00 a     11050     1    25     2    10\n -1.3348295921048384E-01 a     11051     1    25     2    11\n -5.6436219775635454E-01 a     11052     1    25     2    12\n -4.2150078563091391E+00 a     11053     1    25     2    13\n  3.9442115851796040E+00 a     11054     1    25     2    14\n  2.7507773655369379E+00 a     11055     1    25     2    15\n  8.4447977021750986E-01 a     11056     1    25     2    16\n  9.2677234375727435E-01 a     11057     1    25     2    17\n -1.6060645715140256E+00 a     11058     1    25     2    18\n -5.6297665187582979E-01 a     11059     1    25     2    19\n -1.1619762113838552E+00 a     11060     1    25     2    20\n -1.6527444394960217E-01 a     11061     1    26     2     1\n  3.7993995530148994E-01 a     11062     1    26     2     2\n -1.0259496009724096E+00 a     11063     1    26     2     3\n -6.0245974549209547E-02 a     11064     1    26     2     4\n -2.2632211432698259E+00 a     11065     1    26     2     5\n  6.9527443397655930E-01 a     11066     1    26     2     6\n -5.9966383116113520E-01 a     11067     1    26     2     7\n  9.3476592325536872E-02 a     11068     1    26     2     8\n  1.4348612198079621E-02 a     11069     1    26     2     9\n  6.5641206085959347E-01 a     11070     1    26     2    10\n  2.7966834633998992E-02 a     11071     1    26     2    11\n  1.6545050024914471E-01 a     11072     1    26     2    12\n  6.4845957215155581E-01 a     11073     1    26     2    13\n -9.8674438539031142E-02 a     11074     1    26     2    14\n  1.2136587580744669E-01 a     11075     1    26     2    15\n  4.2485713059291363E-01 a     11076     1    26     2    16\n  2.5888223077303336E+00 a     11077     1    26     2    17\n -1.7714315518617751E-01 a     11078     1    26     2    18\n -9.0610108805878242E-01 a     11079     1    26     2    19\n -2.0507960182098506E+00 a     11080     1    26     2    20\n  1.3171625927613156E-01 a     11081     1    27     2     1\n -8.0527161548753412E-01 a     11082     1    27     2     2\n -7.4436832488130211E-01 a     11083     1    27     2     3\n  1.4403926674814127E-01 a     11084     1    27     2     4\n  2.2166560063953424E+00 a     11085     1    27     2     5\n -1.9300401629753998E+00 a     11086     1    27     2     6\n -6.3480496063326808E-01 a     11087     1    27     2     7\n -6.9471569627674493E-02 a     11088     1    27     2     8\n -3.4862821594748067E-01 a     11089     1    27     2     9\n  7.7410936500885541E-01 a     11090     1    27     2    10\n  1.6903613196761885E-01 a     11091     1    27     2    11\n -7.8598979180250739E-01 a     11092     1    27     2    12\n -4.8259778613434712E-01 a     11093     1    27     2    13\n -1.7654655603858083E+00 a     11094     1    27     2    14\n -1.5238246042389547E+00 a     11095     1    27     2    15\n  4.1079414230333217E-01 a     11096     1    27     2    16\n  1.5052042974066839E+00 a     11097     1    27     2    17\n  9.2515589186416880E-01 a     11098     1    27     2    18\n  7.3659551418637936E-01 a     11099     1    27     2    19\n -1.4635683491502935E+00 a     11100     1    27     2    20\n  5.1654726550745378E-01 a     11101     1    28     2     1\n  1.3651433632169947E+00 a     11102     1    28     2     2\n -8.8337234847466695E-01 a     11103     1    28     2     3\n -7.0374144995301757E-02 a     11104     1    28     2     4\n  1.2651200744091082E+00 a     11105     1    28     2     5\n  1.6121255582700211E+00 a     11106     1    28     2     6\n  1.1027322263558608E+00 a     11107     1    28     2     7\n -3.3663905581833264E-01 a     11108     1    28     2     8\n  5.1644239772195268E-02 a     11109     1    28     2     9\n  8.1554791423286532E-01 a     11110     1    28     2    10\n -3.7227571126328338E-02 a     11111     1    28     2    11\n -4.1387271227819233E-01 a     11112     1    28     2    12\n -2.6005776608512057E+00 a     11113     1    28     2    13\n -8.9465432253632016E-01 a     11114     1    28     2    14\n -2.3310593605673615E+00 a     11115     1    28     2    15\n -2.3319567185688492E-01 a     11116     1    28     2    16\n -4.7097293258185138E-02 a     11117     1    28     2    17\n -6.8715198794572913E-02 a     11118     1    28     2    18\n -6.8655256253466568E-01 a     11119     1    28     2    19\n -8.2273389030700472E-02 a     11120     1    28     2    20\n -2.7629894352555007E-01 a     11121     1    29     2     1\n  1.5733596880615732E+00 a     11122     1    29     2     2\n -8.5838396901143019E-02 a     11123     1    29     2     3\n  1.4365906062224884E-01 a     11124     1    29     2     4\n -9.6027557188341905E-01 a     11125     1    29     2     5\n  1.7698549560320933E+00 a     11126     1    29     2     6\n  1.2825421476813752E+00 a     11127     1    29     2     7\n -1.2307294511050433E-01 a     11128     1    29     2     8\n  2.0758173525504223E-01 a     11129     1    29     2     9\n -8.4396524902691539E-01 a     11130     1    29     2    10\n  7.0135622629802075E-01 a     11131     1    29     2    11\n  7.8582947364924507E-02 a     11132     1    29     2    12\n -1.5953699759369271E+00 a     11133     1    29     2    13\n -1.2049932998645048E+00 a     11134     1    29     2    14\n -9.1645200676950389E-01 a     11135     1    29     2    15\n  1.6403563208734588E+00 a     11136     1    29     2    16\n -5.7618947144012511E-01 a     11137     1    29     2    17\n -3.0748290435239911E-01 a     11138     1    29     2    18\n  1.1530056611449119E-01 a     11139     1    29     2    19\n -2.0474086297437477E+00 a     11140     1    29     2    20\n  9.8228042408367286E-02 a     11141     1    30     2     1\n  5.2560694336138747E-01 a     11142     1    30     2     2\n  2.6256372138302436E-01 a     11143     1    30     2     3\n  8.8027633574760489E-01 a     11144     1    30     2     4\n  1.2713479794868694E+00 a     11145     1    30     2     5\n  1.2274271062410291E+00 a     11146     1    30     2     6\n -1.3005612172335508E+00 a     11147     1    30     2     7\n -5.0508651179865438E-01 a     11148     1    30     2     8\n -1.1270651055924877E-01 a     11149     1    30     2     9\n -2.4826737343557163E-03 a     11150     1    30     2    10\n -3.2745160642162596E-02 a     11151     1    30     2    11\n -3.5756581890613309E-01 a     11152     1    30     2    12\n -1.5421649753880264E+00 a     11153     1    30     2    13\n -8.2724545920372194E-01 a     11154     1    30     2    14\n -1.8544892764890102E+00 a     11155     1    30     2    15\n  4.5137551411729281E-02 a     11156     1    30     2    16\n -2.8324645317537556E+00 a     11157     1    30     2    17\n  6.4831455965679782E-03 a     11158     1    30     2    18\n -5.4121868534987416E-01 a     11159     1    30     2    19\n  2.5043173049551337E-01 a     11160     1    30     2    20\n -5.1349889638148960E-01 b     11161     2     1\n  3.6657380586403914E+00 b     11162     2     2\n -2.0307300651087949E+00 b     11163     2     3\n -5.8024576331296296E-01 b     11164     2     4\n -4.4100198758174908E-01 b     11165     2     5\n  1.2845063393558942E-01 b     11166     2     6\n  2.0578013120683822E+00 b     11167     2     7\n  1.0974625419406585E+00 b     11168     2     8\n -1.6897365970311475E+00 b     11169     2     9\n -4.0650350049641819E+00 b     11170     2    10\n -5.1369841178235278E+00 b     11171     2    11\n  1.3405121336832497E+00 b     11172     2    12\n  5.7450538265881823E+00 b     11173     2    13\n -6.4135481659424718E+00 b     11174     2    14\n  2.6216352022354590E+00 b     11175     2    15\n -2.3766711251604966E+00 b     11176     2    16\n -3.0898538462902096E+00 b     11177     2    17\n  1.5656661027987642E+00 b     11178     2    18\n -7.9284256386200465E+00 b     11179     2    19\n  1.1215139558987874E+01 b     11180     2    20\n  3.0707345728547603E-01 a     11181     2     1     3     1\n  1.1435572191425788E-02 a     11182     2     2     3     1\n  6.7457639421818941E-02 a     11183     2     3     3     1\n -1.2142552209035141E-01 a     11184     2     4     3     1\n -4.3696792203084100E-03 a     11185     2     5     3     1\n -1.0718748863557882E-03 a     11186     2     6     3     1\n  1.7376642249757011E-02 a     11187     2     7     3     1\n  1.2253750244800493E-01 a     11188     2     8     3     1\n  7.3540933053045243E-01 a     11189     2     9     3     1\n  2.6207686813745456E-03 a     11190     2    10     3     1\n  7.5957070673395355E-01 a     11191     2    11     3     1\n -4.7862590766954864E-02 a     11192     2    12     3     1\n -1.3132905931751402E-03 a     11193     2    13     3     1\n -4.8393630820568970E-03 a     11194     2    14     3     1\n -5.2779385306427800E-03 a     11195     2    15     3     1\n  5.6206260068789415E-01 a     11196     2    16     3     1\n -7.6169651994482633E-03 a     11197     2    17     3     1\n -5.9573269821951651E-02 a     11198     2    18     3     1\n  2.5812799989544479E+00 a     11199     2    19     3     1\n  3.4862067126539423E-03 a     11200     2    20     3     1\n  3.7106250300594783E+00 b     11201     3     1\n"
  },
  {
    "path": "examples/potentials/Anisole_SCAN/weights.006.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -8.0080144822938362E+00 a         1     0     1     1     1\n  2.2090435882245330E+00 a         2     0     1     1     2\n  1.0290693704206223E+01 a         3     0     1     1     3\n -2.8417139830274922E+00 a         4     0     1     1     4\n -2.8526241158413090E+00 a         5     0     1     1     5\n -9.4645546531270219E-01 a         6     0     1     1     6\n  6.1415566370839629E+00 a         7     0     1     1     7\n  2.1363851070147483E-01 a         8     0     1     1     8\n  3.2617069746963709E+00 a         9     0     1     1     9\n -1.4182211548670178E+00 a        10     0     1     1    10\n  2.3693590116344461E+00 a        11     0     1     1    11\n -9.9221711756408730E+00 a        12     0     1     1    12\n  7.2400551171497032E+00 a        13     0     1     1    13\n  3.6169275386382185E+00 a        14     0     1     1    14\n -7.7499761466918766E+00 a        15     0     1     1    15\n -8.0210653620027728E+00 a        16     0     1     1    16\n  1.4764781202734159E+01 a        17     0     1     1    17\n  3.6295756480079904E+00 a        18     0     1     1    18\n -9.9800220940048778E-01 a        19     0     1     1    19\n -8.9417148805152831E+00 a        20     0     1     1    20\n -2.0043699908613175E+00 a        21     0     1     1    21\n -4.2354066441247538E+00 a        22     0     1     1    22\n -2.1699482246785680E+00 a        23     0     1     1    23\n -5.3961515631073578E+00 a        24     0     1     1    24\n -6.3863026277481305E+00 a        25     0     1     1    25\n  1.9683476771876054E+00 a        26     0     1     1    26\n -2.4678358791451966E+00 a        27     0     1     1    27\n -2.9543614115730654E+00 a        28     0     1     1    28\n  1.7876871592822536E+00 a        29     0     1     1    29\n  4.9212749063860795E+00 a        30     0     1     1    30\n  1.2232210673279283E+01 a        31     0     2     1     1\n  2.2234640406788384E+00 a        32     0     2     1     2\n  2.7351745986105289E+00 a        33     0     2     1     3\n  1.6970146042135649E+01 a        34     0     2     1     4\n  7.4548210825054708E+00 a        35     0     2     1     5\n  1.6530956814050821E+01 a        36     0     2     1     6\n -6.0142405997336796E+00 a        37     0     2     1     7\n  1.8279819708033389E+00 a        38     0     2     1     8\n  1.0853195826121659E+01 a        39     0     2     1     9\n -6.9179658889049422E+00 a        40     0     2     1    10\n -1.5994297647508591E+00 a        41     0     2     1    11\n -4.2234425106452962E+00 a        42     0     2     1    12\n -8.7863042344507980E-01 a        43     0     2     1    13\n  1.2827967448991356E-01 a        44     0     2     1    14\n  8.9851668670358933E+00 a        45     0     2     1    15\n -7.9497422120021344E-01 a        46     0     2     1    16\n -4.7953859667281795E-01 a        47     0     2     1    17\n  3.9826550416012960E+00 a        48     0     2     1    18\n  7.0634136051966812E-01 a        49     0     2     1    19\n  1.4776961948906658E-01 a        50     0     2     1    20\n -5.4659569321985069E-01 a        51     0     2     1    21\n -1.2350049156730551E+00 a        52     0     2     1    22\n -4.6965060905626803E+00 a        53     0     2     1    23\n -1.3266788411411850E+00 a        54     0     2     1    24\n -7.1499990025827698E-01 a        55     0     2     1    25\n  7.3631503451048124E+00 a        56     0     2     1    26\n -3.7356137649714438E-01 a        57     0     2     1    27\n -1.7661859900775281E+00 a        58     0     2     1    28\n  3.1663704824029693E+00 a        59     0     2     1    29\n -6.1130719891691800E+00 a        60     0     2     1    30\n -1.9714017978728338E+00 a        61     0     3     1     1\n -1.3923278425298147E+00 a        62     0     3     1     2\n -9.8697683471843345E-01 a        63     0     3     1     3\n -7.1262652365963808E-01 a        64     0     3     1     4\n  9.5400275950841209E+00 a        65     0     3     1     5\n  8.6566030566285301E-01 a        66     0     3     1     6\n -1.4577949159722980E+00 a        67     0     3     1     7\n  1.9145227638310052E+00 a        68     0     3     1     8\n  1.0102518694345802E-01 a        69     0     3     1     9\n  8.3730751826762404E+00 a        70     0     3     1    10\n  1.2934817062433470E+00 a        71     0     3     1    11\n -7.2972061645521373E+00 a        72     0     3     1    12\n -6.9463656226862271E+00 a        73     0     3     1    13\n  3.2266910507204791E+00 a        74     0     3     1    14\n -6.7352174258563453E+00 a        75     0     3     1    15\n -6.1733813127176884E-01 a        76     0     3     1    16\n -3.0415277002146959E+00 a        77     0     3     1    17\n  3.7231122957607155E+00 a        78     0     3     1    18\n  8.0659351427534243E-01 a        79     0     3     1    19\n -4.2003427419630155E+00 a        80     0     3     1    20\n  3.7180335792394539E+00 a        81     0     3     1    21\n -1.0826907486576876E+00 a        82     0     3     1    22\n  4.4742316238978108E-01 a        83     0     3     1    23\n -3.6373590333193730E+00 a        84     0     3     1    24\n  1.2041213393086658E+00 a        85     0     3     1    25\n -3.6420223199326411E+00 a        86     0     3     1    26\n -3.3015813808266917E-02 a        87     0     3     1    27\n  2.1280403639259569E+00 a        88     0     3     1    28\n -3.9736837562465079E+00 a        89     0     3     1    29\n -4.8546639832441185E-01 a        90     0     3     1    30\n  5.2320718082075706E+00 a        91     0     4     1     1\n -8.8780125725376244E+00 a        92     0     4     1     2\n  4.5055017557061321E+00 a        93     0     4     1     3\n  3.2189948005008420E-02 a        94     0     4     1     4\n -6.9674283793363967E-01 a        95     0     4     1     5\n -4.9368938023767353E+00 a        96     0     4     1     6\n  9.8848239189178280E+00 a        97     0     4     1     7\n -8.4271360804483941E-01 a        98     0     4     1     8\n  1.3814708496581870E+01 a        99     0     4     1     9\n  3.4563008794579542E-01 a       100     0     4     1    10\n -1.1660179130342160E+01 a       101     0     4     1    11\n -3.6078324205347827E+00 a       102     0     4     1    12\n -1.0140943818455446E+01 a       103     0     4     1    13\n  3.3378874927013000E+00 a       104     0     4     1    14\n  1.0499040166073681E+00 a       105     0     4     1    15\n -7.9595288052838309E-01 a       106     0     4     1    16\n  4.0177970917741606E+00 a       107     0     4     1    17\n  1.4279057564434673E+01 a       108     0     4     1    18\n -6.6143506420987750E+00 a       109     0     4     1    19\n  6.5031679277173895E+00 a       110     0     4     1    20\n  8.4261623458506882E+00 a       111     0     4     1    21\n  6.5973670699895957E+00 a       112     0     4     1    22\n  1.7952236757057543E+00 a       113     0     4     1    23\n -4.0997307846352466E+00 a       114     0     4     1    24\n -7.1490342645013607E+00 a       115     0     4     1    25\n -3.8258530117236647E+00 a       116     0     4     1    26\n  1.4746764108933247E+01 a       117     0     4     1    27\n  1.3410884642563792E+01 a       118     0     4     1    28\n -4.9218470183282941E+00 a       119     0     4     1    29\n  2.4513490821111339E+00 a       120     0     4     1    30\n  3.1707232322979810E+00 a       121     0     5     1     1\n -5.5252362210164039E+00 a       122     0     5     1     2\n  4.8292808737997399E+00 a       123     0     5     1     3\n -1.7032006109102142E+00 a       124     0     5     1     4\n -3.2289525763128579E+00 a       125     0     5     1     5\n -5.2423765825138329E+00 a       126     0     5     1     6\n -7.1212017151819902E+00 a       127     0     5     1     7\n  3.1064862941893150E+00 a       128     0     5     1     8\n -4.5455982693018226E+00 a       129     0     5     1     9\n -1.7479603287029191E+00 a       130     0     5     1    10\n  9.0759137918162143E+00 a       131     0     5     1    11\n  2.9317524176534939E+00 a       132     0     5     1    12\n  3.0415352735528582E+00 a       133     0     5     1    13\n -3.9751923118222514E+00 a       134     0     5     1    14\n -9.3788894458025087E+00 a       135     0     5     1    15\n  1.7409434120762894E+00 a       136     0     5     1    16\n  2.4689108484712881E+00 a       137     0     5     1    17\n -3.6143831986559488E-01 a       138     0     5     1    18\n -9.0206010285339104E+00 a       139     0     5     1    19\n -3.1877193212757695E+00 a       140     0     5     1    20\n -1.2285170334331985E+00 a       141     0     5     1    21\n -6.4870668516790806E+00 a       142     0     5     1    22\n  2.7510935781920414E+00 a       143     0     5     1    23\n  1.9775510181580627E+00 a       144     0     5     1    24\n  1.0853157702741956E+00 a       145     0     5     1    25\n  5.8212943959309822E+00 a       146     0     5     1    26\n -1.7583290384967469E+01 a       147     0     5     1    27\n -8.4056337232549438E+00 a       148     0     5     1    28\n  2.5876247569103659E+00 a       149     0     5     1    29\n  4.3231252240823403E+00 a       150     0     5     1    30\n  3.1376841339809280E-01 a       151     0     6     1     1\n -4.0709405518169319E+00 a       152     0     6     1     2\n -9.0925283988613899E+00 a       153     0     6     1     3\n -8.1627333612751158E+00 a       154     0     6     1     4\n  6.8972209327054719E+00 a       155     0     6     1     5\n  6.0980595616682907E+00 a       156     0     6     1     6\n  8.4207708244030055E+00 a       157     0     6     1     7\n -3.6116814572330966E+00 a       158     0     6     1     8\n  1.1001805935188463E+01 a       159     0     6     1     9\n -9.1371431502944844E+00 a       160     0     6     1    10\n -1.7937957484714335E+00 a       161     0     6     1    11\n -1.2364603018198645E+01 a       162     0     6     1    12\n -6.7837986173810974E+00 a       163     0     6     1    13\n  7.5687054828742495E+00 a       164     0     6     1    14\n -1.0190046111263671E+01 a       165     0     6     1    15\n -1.8744230991177147E+00 a       166     0     6     1    16\n -5.0630008992543010E+00 a       167     0     6     1    17\n  3.0195621521490055E+00 a       168     0     6     1    18\n -1.6687355857311825E+01 a       169     0     6     1    19\n  2.0123528506264918E+00 a       170     0     6     1    20\n  1.2760730993527252E+00 a       171     0     6     1    21\n  3.1398227250523947E+00 a       172     0     6     1    22\n  5.2013611160693278E+00 a       173     0     6     1    23\n  3.9320637613434717E+00 a       174     0     6     1    24\n -7.0014488025663946E+00 a       175     0     6     1    25\n -3.5251046645010140E+00 a       176     0     6     1    26\n  7.2788988953483260E+00 a       177     0     6     1    27\n  5.1689065560904339E+00 a       178     0     6     1    28\n -1.3955318316854722E+01 a       179     0     6     1    29\n -5.6497312184518238E+00 a       180     0     6     1    30\n  1.0814323960244585E+00 a       181     0     7     1     1\n -3.6716853847794244E+00 a       182     0     7     1     2\n  1.4554998835752404E+00 a       183     0     7     1     3\n -5.3564841979605218E+00 a       184     0     7     1     4\n -1.7402501581840562E+00 a       185     0     7     1     5\n -2.2242597075361639E+00 a       186     0     7     1     6\n -9.1525009709232066E+00 a       187     0     7     1     7\n  2.2103822633840098E+00 a       188     0     7     1     8\n -9.6513004817900292E+00 a       189     0     7     1     9\n -2.5061749372792392E+00 a       190     0     7     1    10\n  8.2668806955377896E+00 a       191     0     7     1    11\n  7.4998353023785869E-01 a       192     0     7     1    12\n  3.8220834217640403E+00 a       193     0     7     1    13\n -3.0647929034661296E+00 a       194     0     7     1    14\n -6.7767820725873689E+00 a       195     0     7     1    15\n  1.7638123522437366E+00 a       196     0     7     1    16\n  7.7653012440164582E-01 a       197     0     7     1    17\n -2.8085376700842435E+00 a       198     0     7     1    18\n  2.0278077122949789E+01 a       199     0     7     1    19\n -6.6976054956098459E+00 a       200     0     7     1    20\n -1.0233671396856754E+00 a       201     0     7     1    21\n -5.6823195481636350E+00 a       202     0     7     1    22\n  3.3281140330170927E-01 a       203     0     7     1    23\n  3.8925713547823624E+00 a       204     0     7     1    24\n -9.7585882994033668E-01 a       205     0     7     1    25\n  2.6598156785563916E+00 a       206     0     7     1    26\n -1.0864032439151687E+01 a       207     0     7     1    27\n -1.2212311858007501E+01 a       208     0     7     1    28\n  3.6641150198755010E+00 a       209     0     7     1    29\n -6.5297673914992025E+00 a       210     0     7     1    30\n  7.2065877741791073E+00 a       211     0     8     1     1\n -1.4934468810542021E+00 a       212     0     8     1     2\n -1.1175905157698898E+00 a       213     0     8     1     3\n -6.0065196302021944E+00 a       214     0     8     1     4\n  2.3029180490095142E+00 a       215     0     8     1     5\n  7.8709629023473537E+00 a       216     0     8     1     6\n -8.3396870418766529E+00 a       217     0     8     1     7\n  3.4319790411440918E+00 a       218     0     8     1     8\n -3.6281451021775069E+00 a       219     0     8     1     9\n -8.8876497180545826E+00 a       220     0     8     1    10\n  1.3477583425742103E+00 a       221     0     8     1    11\n  7.8337033082206027E+00 a       222     0     8     1    12\n  1.3534588924822760E-01 a       223     0     8     1    13\n  1.3959326022966803E+00 a       224     0     8     1    14\n  7.8516531400221107E-02 a       225     0     8     1    15\n -2.6813521037869137E+00 a       226     0     8     1    16\n -5.4890399212610008E+00 a       227     0     8     1    17\n -1.2367627027213026E+00 a       228     0     8     1    18\n  1.1792011710392021E+00 a       229     0     8     1    19\n  7.3889251026795195E+00 a       230     0     8     1    20\n  1.4523546697818423E+01 a       231     0     8     1    21\n  5.4268567748008589E+00 a       232     0     8     1    22\n -9.1677080382550249E-02 a       233     0     8     1    23\n -6.6173313558278513E-01 a       234     0     8     1    24\n  2.6495031260502810E-01 a       235     0     8     1    25\n -7.2320391701040769E+00 a       236     0     8     1    26\n  3.3353742793897396E+00 a       237     0     8     1    27\n -3.9808124638288662E+00 a       238     0     8     1    28\n  1.1933602503592351E+01 a       239     0     8     1    29\n -2.7280035457924162E-01 a       240     0     8     1    30\n -1.4974192077932955E+00 a       241     0     9     1     1\n -3.1399413913766230E+00 a       242     0     9     1     2\n -4.7804686842986728E+00 a       243     0     9     1     3\n -2.4669931000577887E+00 a       244     0     9     1     4\n  1.8126118814773802E+00 a       245     0     9     1     5\n  8.9420503632153991E+00 a       246     0     9     1     6\n -4.1254671317101836E+00 a       247     0     9     1     7\n  4.5189392439920280E+00 a       248     0     9     1     8\n  2.9322130997519738E+00 a       249     0     9     1     9\n -6.9351385154902072E+00 a       250     0     9     1    10\n  2.2001836423725576E-01 a       251     0     9     1    11\n  5.2572281809236920E-01 a       252     0     9     1    12\n  1.4300774814682726E+00 a       253     0     9     1    13\n  1.6626196699620506E+00 a       254     0     9     1    14\n  2.9881082988407068E+00 a       255     0     9     1    15\n  1.1383880203445831E+00 a       256     0     9     1    16\n -2.1677741659287570E+00 a       257     0     9     1    17\n -2.0245180077142684E+00 a       258     0     9     1    18\n  1.5139561713816632E+00 a       259     0     9     1    19\n  6.3442472511664443E+00 a       260     0     9     1    20\n  1.0776520139267225E+00 a       261     0     9     1    21\n  1.1673586744086619E+00 a       262     0     9     1    22\n  1.8466915973942573E+00 a       263     0     9     1    23\n -6.9615582230009316E+00 a       264     0     9     1    24\n  4.1179782100364548E+00 a       265     0     9     1    25\n  8.7369485682727550E+00 a       266     0     9     1    26\n  1.5333886354589032E+00 a       267     0     9     1    27\n  8.6149069925912658E-01 a       268     0     9     1    28\n  6.5787757980455785E-01 a       269     0     9     1    29\n -2.5656337417677895E+00 a       270     0     9     1    30\n  6.5038664422540817E+00 a       271     0    10     1     1\n  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7.0459392131612972E+00 a      1936     0    65     1    16\n  3.1257238482760796E-01 a      1937     0    65     1    17\n -2.8910381512939685E+00 a      1938     0    65     1    18\n -7.0113563994536632E-01 a      1939     0    65     1    19\n  1.9926519484651284E+00 a      1940     0    65     1    20\n  2.5067187474014627E+00 a      1941     0    65     1    21\n  3.8182779698375704E+00 a      1942     0    65     1    22\n  1.1011238883856758E+00 a      1943     0    65     1    23\n -1.7668505853979874E+00 a      1944     0    65     1    24\n -1.0378446520542719E+00 a      1945     0    65     1    25\n  2.1078704737176812E+00 a      1946     0    65     1    26\n  1.1291371579020764E+00 a      1947     0    65     1    27\n -4.0066579204228442E-01 a      1948     0    65     1    28\n  2.3832532777375488E+00 a      1949     0    65     1    29\n -2.3375603262296654E+00 a      1950     0    65     1    30\n  4.9811558032609344E+00 a      1951     0    66     1     1\n -1.0255605361022960E+01 a      1952     0    66     1     2\n -1.6119099003074910E+00 a      1953     0    66     1     3\n -1.6307807602773852E+00 a      1954     0    66     1     4\n  1.1325490164429968E+00 a      1955     0    66     1     5\n -8.1171246020694117E+00 a      1956     0    66     1     6\n -3.3663567397237243E-01 a      1957     0    66     1     7\n  3.5184625271073006E-01 a      1958     0    66     1     8\n  2.4876146030781814E+00 a      1959     0    66     1     9\n  4.8978055549921438E+00 a      1960     0    66     1    10\n -4.9774088767988873E+00 a      1961     0    66     1    11\n -5.8187314095919636E+00 a      1962     0    66     1    12\n  1.1207791192940830E+01 a      1963     0    66     1    13\n  7.6882752808577388E+00 a      1964     0    66     1    14\n -1.4666307593295913E+00 a      1965     0    66     1    15\n -5.3030749227915119E-01 a      1966     0    66     1    16\n -1.2399480142659003E+00 a      1967     0    66     1    17\n  1.5713345976373119E+00 a      1968     0    66     1    18\n  1.6833971955154949E+00 a      1969     0    66     1    19\n -4.8841720912809077E+00 a      1970     0    66     1    20\n -5.0988893636415309E+00 a      1971     0    66     1    21\n -1.2018266037348024E+01 a      1972     0    66     1    22\n -1.7914240004373903E+00 a      1973     0    66     1    23\n -1.5077061460663705E+00 a      1974     0    66     1    24\n  4.1301320740417395E+00 a      1975     0    66     1    25\n  6.1109512581944903E-01 a      1976     0    66     1    26\n -1.5697958004616241E+00 a      1977     0    66     1    27\n -3.8712505922031069E+00 a      1978     0    66     1    28\n -4.2701227148846016E-01 a      1979     0    66     1    29\n  2.1652478470295371E+00 a      1980     0    66     1    30\n -9.6019282096973746E-01 a      1981     0    67     1     1\n  1.1377379687445819E+00 a      1982     0    67     1     2\n -7.1404703821928006E+00 a      1983     0    67     1     3\n  1.3426512952047063E+00 a      1984     0    67     1     4\n  6.2965705976427406E+00 a      1985     0    67     1     5\n  7.4633436120413221E-01 a      1986     0    67     1     6\n -9.0076352105389312E-01 a      1987     0    67     1     7\n -5.9355303577225271E-01 a      1988     0    67     1     8\n -4.0474245469647157E+00 a      1989     0    67     1     9\n -3.2493513972969903E+00 a      1990     0    67     1    10\n  4.3405640181410896E-02 a      1991     0    67     1    11\n -1.5803381282115860E+00 a      1992     0    67     1    12\n -6.5912860743201200E+00 a      1993     0    67     1    13\n -2.8025796618745478E+00 a      1994     0    67     1    14\n  2.9307522296599022E+00 a      1995     0    67     1    15\n -3.5989681060055405E+00 a      1996     0    67     1    16\n  1.4615411330688262E+00 a      1997     0    67     1    17\n -4.6443894692706538E+00 a      1998     0    67     1    18\n  5.1984677741146645E-01 a      1999     0    67     1    19\n  4.5029713466337631E+00 a      2000     0    67     1    20\n  1.6991462086827154E+00 a      2001     0    67     1    21\n  3.6982673335245759E+00 a      2002     0    67     1    22\n -4.3267313920534750E-01 a      2003     0    67     1    23\n  2.2363744614039232E+00 a      2004     0    67     1    24\n -3.4954121276940904E+00 a      2005     0    67     1    25\n -1.6899748619710084E+00 a      2006     0    67     1    26\n  5.5494847930104918E-01 a      2007     0    67     1    27\n  2.5752407445448062E+00 a      2008     0    67     1    28\n -2.4938859194049784E-01 a      2009     0    67     1    29\n  2.6615673287976527E-01 a      2010     0    67     1    30\n -4.1565547069969833E-01 a      2011     0    68     1     1\n  9.9058367091153432E+00 a      2012     0    68     1     2\n -2.2320885930751251E+00 a      2013     0    68     1     3\n -1.5201566097023014E+00 a      2014     0    68     1     4\n -1.9131268906634347E+00 a      2015     0    68     1     5\n  2.0050031250105977E+00 a      2016     0    68     1     6\n  7.4459925737901889E-01 a      2017     0    68     1     7\n  4.6179912915134622E+00 a      2018     0    68     1     8\n  2.0194072964686210E-01 a      2019     0    68     1     9\n  1.1836566557254549E+00 a      2020     0    68     1    10\n  3.7262670672160172E+00 a      2021     0    68     1    11\n  3.3077570991840992E+00 a      2022     0    68     1    12\n  4.1772416249066846E-01 a      2023     0    68     1    13\n  6.0117632144715509E+00 a      2024     0    68     1    14\n -1.6658721036765127E+00 a      2025     0    68     1    15\n  3.5156039717415788E+00 a      2026     0    68     1    16\n -1.0737198376068824E+00 a      2027     0    68     1    17\n -9.2079296108100206E-01 a      2028     0    68     1    18\n -1.5716606072121988E+00 a      2029     0    68     1    19\n -2.0575217452636467E+00 a      2030     0    68     1    20\n  5.2081717347392587E-02 a      2031     0    68     1    21\n  2.4987394136174816E+00 a      2032     0    68     1    22\n  2.5458377021865486E+00 a      2033     0    68     1    23\n  3.0776926027892486E+00 a      2034     0    68     1    24\n  4.6476913024032225E+00 a      2035     0    68     1    25\n  6.0202176126218832E-01 a      2036     0    68     1    26\n  5.4970802452372780E-01 a      2037     0    68     1    27\n -1.1102512030389236E+00 a      2038     0    68     1    28\n  3.3658749792248885E+00 a      2039     0    68     1    29\n -2.3416926280242318E+00 a      2040     0    68     1    30\n  1.3639146474347106E+00 a      2041     0    69     1     1\n  1.4599358927437662E+00 a      2042     0    69     1     2\n  1.6576068039363284E-01 a      2043     0    69     1     3\n  2.9319127788319284E+00 a      2044     0    69     1     4\n  7.4962477238828624E+00 a      2045     0    69     1     5\n -2.2528802393924270E+00 a      2046     0    69     1     6\n -9.9641230150479909E-01 a      2047     0    69     1     7\n -2.4739461585998472E+00 a      2048     0    69     1     8\n -1.3749072769086710E+00 a      2049     0    69     1     9\n  2.6588466252738687E+00 a      2050     0    69     1    10\n -1.5262033415023973E-01 a      2051     0    69     1    11\n -8.1739160540050015E-01 a      2052     0    69     1    12\n  1.0305781421203501E+00 a      2053     0    69     1    13\n  7.7778774212346502E-01 a      2054     0    69     1    14\n -2.2127646673830217E+00 a      2055     0    69     1    15\n  4.2409860972873377E+00 a      2056     0    69     1    16\n  1.1007065426481715E+00 a      2057     0    69     1    17\n -7.1770597354016830E-01 a      2058     0    69     1    18\n -4.1450901628849479E-01 a      2059     0    69     1    19\n  8.8434338787486563E-02 a      2060     0    69     1    20\n -3.9824459806182544E+00 a      2061     0    69     1    21\n -9.2536536811059877E-01 a      2062     0    69     1    22\n -1.9091501406627345E+00 a      2063     0    69     1    23\n -3.4821235723393178E+00 a      2064     0    69     1    24\n  4.6819195152073556E-02 a      2065     0    69     1    25\n  1.4328040854968258E+00 a      2066     0    69     1    26\n -2.9728350993648345E-02 a      2067     0    69     1    27\n  4.1199953171803672E-01 a      2068     0    69     1    28\n  4.4000628987590593E+00 a      2069     0    69     1    29\n  6.1350343648059635E-01 a      2070     0    69     1    30\n  4.0708257962887258E+00 a      2071     0    70     1     1\n  3.9202063651669783E+00 a      2072     0    70     1     2\n  9.5362247765065788E+00 a      2073     0    70     1     3\n  2.1152395867300964E+00 a      2074     0    70     1     4\n  8.9309959591702937E-01 a      2075     0    70     1     5\n -1.0580039524233880E+01 a      2076     0    70     1     6\n -5.2266675439055756E+00 a      2077     0    70     1     7\n  3.2819537926951350E+00 a      2078     0    70     1     8\n  2.2065581787546273E+00 a      2079     0    70     1     9\n  1.8018716794744649E+00 a      2080     0    70     1    10\n -5.3343732375093662E+00 a      2081     0    70     1    11\n  1.2371421981265385E+00 a      2082     0    70     1    12\n  3.1515260520007637E+00 a      2083     0    70     1    13\n -4.4432611590811284E+00 a      2084     0    70     1    14\n  1.6647206402438552E-01 a      2085     0    70     1    15\n  4.4880845869826418E+00 a      2086     0    70     1    16\n -5.9153458773746346E+00 a      2087     0    70     1    17\n -3.1758069345165296E+00 a      2088     0    70     1    18\n  1.5262827162325741E+00 a      2089     0    70     1    19\n  6.4577210984060471E+00 a      2090     0    70     1    20\n  2.5395777705129569E-01 a      2091     0    70     1    21\n  4.0330288509422720E+00 a      2092     0    70     1    22\n -1.7564368192694708E+00 a      2093     0    70     1    23\n  8.5276077086748980E+00 a      2094     0    70     1    24\n -2.1043314701911515E+00 a      2095     0    70     1    25\n  6.3585267532835582E-02 a      2096     0    70     1    26\n  9.7982038474276512E-01 a      2097     0    70     1    27\n -4.0051128278821775E+00 a      2098     0    70     1    28\n -4.2846508839209934E+00 a      2099     0    70     1    29\n  6.6851190879338711E+00 a      2100     0    70     1    30\n -1.3350087251983642E+00 a      2101     0    71     1     1\n  2.2594197973112857E+00 a      2102     0    71     1     2\n  3.0778642064694783E+00 a      2103     0    71     1     3\n -5.3196309372790758E+00 a      2104     0    71     1     4\n -7.3406328447172449E+00 a      2105     0    71     1     5\n  3.2340678439235671E+00 a      2106     0    71     1     6\n -3.2697468713521718E+00 a      2107     0    71     1     7\n -6.0265619745725019E+00 a      2108     0    71     1     8\n  1.1956545959983240E+00 a      2109     0    71     1     9\n  4.4578703162872744E+00 a      2110     0    71     1    10\n -5.3693106309717686E-01 a      2111     0    71     1    11\n  7.4579678352027845E-01 a      2112     0    71     1    12\n -8.3223649221812146E-01 a      2113     0    71     1    13\n -3.0576162316566529E+00 a      2114     0    71     1    14\n  8.3466268555069867E-01 a      2115     0    71     1    15\n  3.5299719802532104E-01 a      2116     0    71     1    16\n -1.3861621996516520E+00 a      2117     0    71     1    17\n -4.3586297990544187E+00 a      2118     0    71     1    18\n -6.4158698177666853E+00 a      2119     0    71     1    19\n -4.4540964060035106E+00 a      2120     0    71     1    20\n  4.7227294178052688E+00 a      2121     0    71     1    21\n  5.1675909675286524E+00 a      2122     0    71     1    22\n  6.0674715765237561E+00 a      2123     0    71     1    23\n -7.9671056146734456E+00 a      2124     0    71     1    24\n  3.1009050541030037E-01 a      2125     0    71     1    25\n -1.3065882002183768E+00 a      2126     0    71     1    26\n -4.2477514275733190E+00 a      2127     0    71     1    27\n -5.7822022353710212E-01 a      2128     0    71     1    28\n -3.0716820985662543E+00 a      2129     0    71     1    29\n -1.7423114762064926E+00 a      2130     0    71     1    30\n -7.8382241039678702E+00 a      2131     0    72     1     1\n  2.1379265203581523E+00 a      2132     0    72     1     2\n -6.2342760437491496E+00 a      2133     0    72     1     3\n -2.0893711290729203E-01 a      2134     0    72     1     4\n  3.3360337351986175E-01 a      2135     0    72     1     5\n -8.2734716406211515E+00 a      2136     0    72     1     6\n  3.1228828769936134E-01 a      2137     0    72     1     7\n  5.3647116471618572E-01 a      2138     0    72     1     8\n -3.5284637758761646E+00 a      2139     0    72     1     9\n  1.1502945792506158E+00 a      2140     0    72     1    10\n  1.1316499997608719E+01 a      2141     0    72     1    11\n -2.2260505012500658E+00 a      2142     0    72     1    12\n  2.4234375807778843E+00 a      2143     0    72     1    13\n  2.5716808588671660E+00 a      2144     0    72     1    14\n  1.0031502137056687E+01 a      2145     0    72     1    15\n  2.7726369031350551E+00 a      2146     0    72     1    16\n -9.6342379582257305E+00 a      2147     0    72     1    17\n -5.2207725695189633E-01 a      2148     0    72     1    18\n -6.7756294875987111E+00 a      2149     0    72     1    19\n -1.4753103832965206E+00 a      2150     0    72     1    20\n  4.9624887107326261E+00 a      2151     0    72     1    21\n -4.6977161784781103E+00 a      2152     0    72     1    22\n  1.2619426286001392E+01 a      2153     0    72     1    23\n -5.9131359858548382E-01 a      2154     0    72     1    24\n  8.4138216319651580E+00 a      2155     0    72     1    25\n  2.0032159198805868E+00 a      2156     0    72     1    26\n  2.0434146621766306E+01 a      2157     0    72     1    27\n -1.2070123856246218E-01 a      2158     0    72     1    28\n  3.3174226911137839E-01 a      2159     0    72     1    29\n 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1.7132888009358346E-01 a     11158     1    26     2     8\n  3.9640471772063490E+00 a     11159     1    26     2     9\n  2.7131493157059988E-01 a     11160     1    26     2    10\n  7.6150734189777902E-01 a     11161     1    26     2    11\n  1.3814191653975358E-01 a     11162     1    26     2    12\n -4.8788145360410784E-01 a     11163     1    26     2    13\n  6.1896448987212660E-01 a     11164     1    26     2    14\n -4.5134721875586627E-02 a     11165     1    26     2    15\n -3.3909377111217687E-01 a     11166     1    26     2    16\n  1.3587669314811954E+00 a     11167     1    26     2    17\n -2.6993270124690566E-01 a     11168     1    26     2    18\n -7.1054019494727294E-01 a     11169     1    26     2    19\n -8.2060913409987568E-01 a     11170     1    26     2    20\n  1.9357717962560703E+00 a     11171     1    27     2     1\n -2.4335076211157575E-01 a     11172     1    27     2     2\n -5.6489669485829319E-01 a     11173     1    27     2     3\n -6.1597526315008544E-01 a     11174     1    27     2     4\n  1.5278808340070069E-01 a     11175     1    27     2     5\n -1.9606652048657863E-01 a     11176     1    27     2     6\n -1.6572928535776312E+00 a     11177     1    27     2     7\n  2.3333251909020489E-01 a     11178     1    27     2     8\n -6.1495341416309648E-02 a     11179     1    27     2     9\n  5.1742082958223428E+00 a     11180     1    27     2    10\n -1.2265543313505489E-01 a     11181     1    27     2    11\n -1.5217657582113466E+00 a     11182     1    27     2    12\n -2.7007007985781395E-01 a     11183     1    27     2    13\n  2.9483608113433077E+00 a     11184     1    27     2    14\n  2.2871020024827948E+00 a     11185     1    27     2    15\n -1.5017394994581312E-01 a     11186     1    27     2    16\n -1.0796669297772064E+00 a     11187     1    27     2    17\n  1.3755269860560462E-01 a     11188     1    27     2    18\n  2.3603436568722394E-01 a     11189     1    27     2    19\n  9.5108154624825669E-01 a     11190     1    27     2    20\n -1.5488120836008454E+00 a     11191     1    28     2     1\n -5.5095745573888149E+00 a     11192     1    28     2     2\n  1.4210272748416470E+00 a     11193     1    28     2     3\n -4.2065676876208730E-01 a     11194     1    28     2     4\n -2.3332910790393009E+00 a     11195     1    28     2     5\n -3.8433306764348631E+00 a     11196     1    28     2     6\n  5.0781828410585588E+00 a     11197     1    28     2     7\n  5.2010767131458635E-01 a     11198     1    28     2     8\n -5.1410280311135237E-01 a     11199     1    28     2     9\n  4.8024697256838228E-01 a     11200     1    28     2    10\n -2.1854129485101890E+00 a     11201     1    28     2    11\n  8.5615632813308729E+00 a     11202     1    28     2    12\n -1.3044036186779409E-03 a     11203     1    28     2    13\n  9.1093108911146392E-01 a     11204     1    28     2    14\n  5.0430423419219723E+00 a     11205     1    28     2    15\n  1.2499175956754645E+00 a     11206     1    28     2    16\n  2.0364282895328567E-01 a     11207     1    28     2    17\n -3.2440215119148402E-01 a     11208     1    28     2    18\n  1.6563039262162016E-01 a     11209     1    28     2    19\n  9.9549316465737336E-01 a     11210     1    28     2    20\n -3.8280165383991099E-01 a     11211     1    29     2     1\n -2.6904461568026052E+00 a     11212     1    29     2     2\n  1.1266202052848859E+00 a     11213     1    29     2     3\n -4.2455328842719753E-01 a     11214     1    29     2     4\n  2.2421771938899289E+00 a     11215     1    29     2     5\n -4.4628143284606576E+00 a     11216     1    29     2     6\n  8.8711606620989913E-01 a     11217     1    29     2     7\n  1.7613360848928122E-01 a     11218     1    29     2     8\n  2.3384878915931213E+00 a     11219     1    29     2     9\n  1.3654466026401233E+00 a     11220     1    29     2    10\n  5.4573074028344681E-01 a     11221     1    29     2    11\n  7.0127278079529376E-01 a     11222     1    29     2    12\n -2.9667313414683355E-01 a     11223     1    29     2    13\n -6.2011650991871392E-01 a     11224     1    29     2    14\n -1.6897743207557703E+00 a     11225     1    29     2    15\n  1.4460018873476202E-01 a     11226     1    29     2    16\n  1.5425705550911477E+00 a     11227     1    29     2    17\n  1.1199015289181156E+00 a     11228     1    29     2    18\n -8.5974398027033938E-01 a     11229     1    29     2    19\n -3.4278385680228507E-01 a     11230     1    29     2    20\n -6.2512423886936952E-01 a     11231     1    30     2     1\n  5.6310002863349551E-01 a     11232     1    30     2     2\n  2.1017598857567945E+00 a     11233     1    30     2     3\n -1.2813157213009911E+00 a     11234     1    30     2     4\n -1.2476306233896500E-01 a     11235     1    30     2     5\n -6.0551583780043522E-02 a     11236     1    30     2     6\n  2.5543972431130766E+00 a     11237     1    30     2     7\n  1.2926942224400710E+00 a     11238     1    30     2     8\n  1.5877392725662114E+00 a     11239     1    30     2     9\n  1.7705548735253283E+00 a     11240     1    30     2    10\n  1.5201241139620603E+00 a     11241     1    30     2    11\n -2.5144525128236088E+00 a     11242     1    30     2    12\n -1.8551291092757534E+00 a     11243     1    30     2    13\n  3.3247977732255456E-02 a     11244     1    30     2    14\n  7.2975854204192159E-01 a     11245     1    30     2    15\n -2.3210161291255971E-01 a     11246     1    30     2    16\n -1.8199521801886045E+00 a     11247     1    30     2    17\n  3.5610896632038225E+00 a     11248     1    30     2    18\n -1.0797278981623819E+00 a     11249     1    30     2    19\n  5.3406039255950388E-01 a     11250     1    30     2    20\n -3.0442618105965300E+00 b     11251     2     1\n  1.2912549064721692E+00 b     11252     2     2\n -1.1766950443116373E+01 b     11253     2     3\n -8.1184926976465732E+00 b     11254     2     4\n  1.5391938866748854E+01 b     11255     2     5\n  5.5852513101020929E+00 b     11256     2     6\n  3.5241435858923493E+00 b     11257     2     7\n  8.5826790157816446E-01 b     11258     2     8\n -9.6310473003271717E+00 b     11259     2     9\n -9.1360843339705262E+00 b     11260     2    10\n -1.3938404148222991E+00 b     11261     2    11\n  2.8640222977365486E+00 b     11262     2    12\n  1.1438370425993079E+00 b     11263     2    13\n  5.5739608956829398E+00 b     11264     2    14\n  3.8424168101946363E+00 b     11265     2    15\n -9.8370245790869404E-01 b     11266     2    16\n  1.4724002144229171E+00 b     11267     2    17\n -3.1402198502618219E+00 b     11268     2    18\n  3.8340480278026927E+00 b     11269     2    19\n -1.2419165294071883E+00 b     11270     2    20\n -4.8209086798797129E-01 a     11271     2     1     3     1\n -6.6113516633439255E-03 a     11272     2     2     3     1\n -1.2616335960253163E-02 a     11273     2     3     3     1\n -3.3593347793028683E-01 a     11274     2     4     3     1\n -1.2096018555373318E-03 a     11275     2     5     3     1\n -1.8417852908408999E-02 a     11276     2     6     3     1\n  1.6023811570513833E-03 a     11277     2     7     3     1\n  4.9442311258794630E-01 a     11278     2     8     3     1\n  1.7558997875814261E-02 a     11279     2     9     3     1\n  9.7474984731094928E-03 a     11280     2    10     3     1\n  9.9143192341286882E-03 a     11281     2    11     3     1\n  2.7151274335435365E-03 a     11282     2    12     3     1\n -6.6767599223926466E-01 a     11283     2    13     3     1\n  9.5885808211704071E-01 a     11284     2    14     3     1\n  2.1482748192035842E-03 a     11285     2    15     3     1\n -3.2154973309140988E-01 a     11286     2    16     3     1\n -2.8130743222112981E-01 a     11287     2    17     3     1\n -7.7350220219195333E-03 a     11288     2    18     3     1\n  3.6363593349086065E-01 a     11289     2    19     3     1\n -4.7821766548453126E-01 a     11290     2    20     3     1\n  3.2467969014148550E+00 b     11291     3     1\n"
  },
  {
    "path": "examples/potentials/Anisole_SCAN/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -1.4892912926746951E+00 a         1     0     1     1     1\n  1.3786206112635062E+01 a         2     0     1     1     2\n  5.6935313569430752E+00 a         3     0     1     1     3\n -8.9265479837094954E+00 a         4     0     1     1     4\n  3.9445105420916344E+00 a         5     0     1     1     5\n -6.0852827471830535E+00 a         6     0     1     1     6\n -5.0021844069602128E+00 a         7     0     1     1     7\n -1.3014792773009494E+00 a         8     0     1     1     8\n -3.2783764688039492E+00 a         9     0     1     1     9\n -2.9070028724163777E+00 a        10     0     1     1    10\n -6.2298040928764005E+00 a        11     0     1     1    11\n -4.0669141239251578E+00 a        12     0     1     1    12\n -1.0743453391806076E+01 a        13     0     1     1    13\n -6.3243960696439752E+00 a        14     0     1     1    14\n -4.8128745937781163E+00 a        15     0     1     1    15\n  4.1935640172663682E+00 a        16     0     1     1    16\n -9.1937662981065351E+00 a        17     0     1     1    17\n  4.1217718130973182E+00 a        18     0     1     1    18\n  3.4695366930742546E+00 a        19     0     1     1    19\n  3.9296052289662371E+00 a        20     0     1     1    20\n -5.2397703048574362E+00 a        21     0     1     1    21\n  1.8239998764649912E+00 a        22     0     1     1    22\n -3.4201379933282072E+00 a        23     0     1     1    23\n  4.3150620390257100E+00 a        24     0     1     1    24\n -1.6968527725388069E-01 a        25     0     1     1    25\n -3.2546655458682348E+00 a        26     0     1     1    26\n -7.0567352851674094E+00 a        27     0     1     1    27\n -2.4322180077260529E+00 a        28     0     1     1    28\n -3.0097777128248078E+00 a        29     0     1     1    29\n  3.0092611618221414E+00 a        30     0     1     1    30\n  5.4050226263714668E-02 a        31     0     2     1     1\n -3.9566521169796331E+00 a        32     0     2     1     2\n -2.5929974799720101E+00 a        33     0     2     1     3\n -8.2748055115294648E+00 a        34     0     2     1     4\n -1.5281057523532721E-01 a        35     0     2     1     5\n -9.4878826507577880E+00 a        36     0     2     1     6\n -8.3001657733812029E-01 a        37     0     2     1     7\n -2.7292698728039180E+00 a        38     0     2     1     8\n  6.0948317967327599E+00 a        39     0     2     1     9\n -8.8447883302337651E+00 a        40     0     2     1    10\n -7.1673150173484128E+00 a        41     0     2     1    11\n -3.6694592471602645E+00 a        42     0     2     1    12\n -8.3647530422359928E+00 a        43     0     2     1    13\n -6.8528642150937360E+00 a        44     0     2     1    14\n -5.2730219181465880E+00 a        45     0     2     1    15\n  2.0385488482607759E+01 a        46     0     2     1    16\n -1.9474079278160563E+00 a        47     0     2     1    17\n  1.2470227393921414E+00 a        48     0     2     1    18\n -5.2915411198338349E+00 a        49     0     2     1    19\n  2.8066354839834600E+00 a        50     0     2     1    20\n  5.2597505725820746E+00 a        51     0     2     1    21\n  6.2081542925572659E+00 a        52     0     2     1    22\n -1.4022995282546884E+01 a        53     0     2     1    23\n -1.1626271124721386E+00 a        54     0     2     1    24\n  1.3108087549976558E+01 a        55     0     2     1    25\n  5.5138975173573908E+00 a        56     0     2     1    26\n  5.8791694872925326E+00 a        57     0     2     1    27\n  3.6009861384233020E+00 a        58     0     2     1    28\n -1.1839462340153907E-02 a        59     0     2     1    29\n  1.3319766534695956E+00 a        60     0     2     1    30\n -6.7660433402513442E+00 a        61     0     3     1     1\n  4.3608780137178362E+00 a        62     0     3     1     2\n  1.0141951311866718E+01 a        63     0     3     1     3\n  9.0909654849340049E-01 a        64     0     3     1     4\n  1.9773603721644442E+00 a        65     0     3     1     5\n  3.7363706457617962E-01 a        66     0     3     1     6\n -1.0141512583522317E+01 a        67     0     3     1     7\n  5.5729275218113786E-02 a        68     0     3     1     8\n  1.2168057294370614E+01 a        69     0     3     1     9\n -1.1337712428721204E+01 a        70     0     3     1    10\n  7.2000584957732086E+00 a        71     0     3     1    11\n  2.3674065995690863E+00 a        72     0     3     1    12\n  3.6338706996042522E+00 a        73     0     3     1    13\n  2.4996211333424907E+00 a        74     0     3     1    14\n -1.9237719645353630E+00 a        75     0     3     1    15\n -1.2686487845247347E+00 a        76     0     3     1    16\n -3.3405421019195045E+00 a        77     0     3     1    17\n -4.9225679371895241E+00 a        78     0     3     1    18\n  2.1471956527865927E+00 a        79     0     3     1    19\n -2.8470090817918980E+00 a        80     0     3     1    20\n -8.7537525820327016E+00 a        81     0     3     1    21\n  4.2052152897112713E-02 a        82     0     3     1    22\n  1.0554206269804212E+01 a        83     0     3     1    23\n  8.4334960068718556E-01 a        84     0     3     1    24\n  4.6456623168499478E-01 a        85     0     3     1    25\n -3.7341929322804193E+00 a        86     0     3     1    26\n  1.1166100409590300E+01 a        87     0     3     1    27\n -1.8304074401813091E+00 a        88     0     3     1    28\n -3.4162421319264036E+00 a        89     0     3     1    29\n -8.8446223367418284E+00 a        90     0     3     1    30\n  5.1517018108506081E+00 a        91     0     4     1     1\n  9.3719785146199470E+00 a        92     0     4     1     2\n -6.4859923110760391E+00 a        93     0     4     1     3\n -2.9145735164648828E-02 a        94     0     4     1     4\n -9.0964984469513999E-01 a        95     0     4     1     5\n -7.6632420422754055E-01 a        96     0     4     1     6\n -6.9662813937797141E+00 a        97     0     4     1     7\n -1.1863943203772700E+00 a        98     0     4     1     8\n  1.3801910489263394E+01 a        99     0     4     1     9\n  4.5909188179582188E+00 a       100     0     4     1    10\n  8.9977404234702938E+00 a       101     0     4     1    11\n  5.7070453974299928E-01 a       102     0     4     1    12\n  5.4226002069580681E-01 a       103     0     4     1    13\n -2.5367722645635289E+00 a       104     0     4     1    14\n -1.3857699734301572E+00 a       105     0     4     1    15\n -5.7013756288857909E-02 a       106     0     4     1    16\n -1.4368027811771402E+00 a       107     0     4     1    17\n  8.3816731936878242E-01 a       108     0     4     1    18\n  1.4678784316036095E+00 a       109     0     4     1    19\n -4.1527100241007684E+00 a       110     0     4     1    20\n  5.1767768330432942E+00 a       111     0     4     1    21\n  1.2374233720168766E+01 a       112     0     4     1    22\n  1.7099552809000343E-01 a       113     0     4     1    23\n -1.7689160474819472E+00 a       114     0     4     1    24\n -4.3389267533620837E+00 a       115     0     4     1    25\n  1.0153888198489649E+00 a       116     0     4     1    26\n  3.1586047332774623E+00 a       117     0     4     1    27\n -7.0799204300389018E-01 a       118     0     4     1    28\n  7.2905318443053799E-02 a       119     0     4     1    29\n -2.6312081929783937E+00 a       120     0     4     1    30\n  2.9032324820156008E+00 a       121     0     5     1     1\n -6.5829948892935031E+00 a       122     0     5     1     2\n -7.7859804150783116E+00 a       123     0     5     1     3\n -1.7511955910002459E+00 a       124     0     5     1     4\n -2.5236304821176812E+00 a       125     0     5     1     5\n  8.8212100270557092E-01 a       126     0     5     1     6\n  1.8663943553871987E+00 a       127     0     5     1     7\n  4.4621251519853340E+00 a       128     0     5     1     8\n -1.2828995467608618E+01 a       129     0     5     1     9\n  6.4895298984645757E+00 a       130     0     5     1    10\n -7.0589076693305524E+00 a       131     0     5     1    11\n  6.4896477306838811E+00 a       132     0     5     1    12\n -4.0406232044449855E+00 a       133     0     5     1    13\n -1.3017355324023098E+01 a       134     0     5     1    14\n  6.0659767711528598E+00 a       135     0     5     1    15\n -2.3649180443063686E+00 a       136     0     5     1    16\n -5.9481618503270104E+00 a       137     0     5     1    17\n  3.7557047742507179E+00 a       138     0     5     1    18\n  3.8172808434587804E+00 a       139     0     5     1    19\n -5.5423133628625552E+00 a       140     0     5     1    20\n -5.6583530647135865E+00 a       141     0     5     1    21\n  5.5199991232650971E+00 a       142     0     5     1    22\n -3.0185342028681408E+00 a       143     0     5     1    23\n  3.1893425914227974E-01 a       144     0     5     1    24\n  1.6695998202247160E+00 a       145     0     5     1    25\n -7.5748352488778936E+00 a       146     0     5     1    26\n  4.2742340878637348E+00 a       147     0     5     1    27\n  7.1874561981433480E+00 a       148     0     5     1    28\n  9.0156166591280655E+00 a       149     0     5     1    29\n  3.4525454706575744E+00 a       150     0     5     1    30\n  3.3886224695027702E+00 a       151     0     6     1     1\n  1.8500232409434996E+00 a       152     0     6     1     2\n -3.3161618425364087E-01 a       153     0     6     1     3\n -7.0839110885402397E+00 a       154     0     6     1     4\n -9.4359154287928657E+00 a       155     0     6     1     5\n -1.9004387972231009E+00 a       156     0     6     1     6\n  2.2439960013719573E+00 a       157     0     6     1     7\n -1.6326445836879746E+00 a       158     0     6     1     8\n -2.1380562643640938E-01 a       159     0     6     1     9\n 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3.1868788496979721E+00 a      1968     0    66     1    18\n -6.3659190318127709E-02 a      1969     0    66     1    19\n -6.0377257716237276E+00 a      1970     0    66     1    20\n -6.8243203372275811E+00 a      1971     0    66     1    21\n -6.6948377711010387E+00 a      1972     0    66     1    22\n  6.8216012932050099E+00 a      1973     0    66     1    23\n -3.1894637385052942E+00 a      1974     0    66     1    24\n  3.5411150231651729E+00 a      1975     0    66     1    25\n  5.1919686170075530E-01 a      1976     0    66     1    26\n -8.6688141282229463E+00 a      1977     0    66     1    27\n -3.2066106978209481E+00 a      1978     0    66     1    28\n  1.6856974114276784E+00 a      1979     0    66     1    29\n  2.6838966765315391E+00 a      1980     0    66     1    30\n -1.0066553546637930E+01 a      1981     0    67     1     1\n -3.2676051290292656E+00 a      1982     0    67     1     2\n  1.2155510343846935E+01 a      1983     0    67     1     3\n -1.2829331097051375E+01 a      1984     0    67     1     4\n -2.1156061552578707E+00 a      1985     0    67     1     5\n -2.8468743258091593E+00 a      1986     0    67     1     6\n  2.7883057967799503E+00 a      1987     0    67     1     7\n  3.5248571252324212E-01 a      1988     0    67     1     8\n  8.2328560343542474E+00 a      1989     0    67     1     9\n  6.1278186002327217E+00 a      1990     0    67     1    10\n -6.1048800664636884E+00 a      1991     0    67     1    11\n -3.1725308424634018E+00 a      1992     0    67     1    12\n -3.8122394155706947E+00 a      1993     0    67     1    13\n -4.4916199319312122E+00 a      1994     0    67     1    14\n -8.9932112925241299E+00 a      1995     0    67     1    15\n  2.3123441927071182E+00 a      1996     0    67     1    16\n -3.9442117527031226E+00 a      1997     0    67     1    17\n -5.5666173468889566E+00 a      1998     0    67     1    18\n -4.4609218885996551E+00 a      1999     0    67     1    19\n  4.4185559571327664E+00 a      2000     0    67     1    20\n  9.3695438691592727E+00 a      2001     0    67     1    21\n -1.3030397525450290E+01 a      2002     0    67     1    22\n -2.4239504740668081E+00 a      2003     0    67     1    23\n -3.1423441832096080E+00 a      2004     0    67     1    24\n  2.5299660757286152E-01 a      2005     0    67     1    25\n  4.0427964397263967E+00 a      2006     0    67     1    26\n  1.3763724422822603E+00 a      2007     0    67     1    27\n -5.9992514901502994E-03 a      2008     0    67     1    28\n  4.5074864598892574E+00 a      2009     0    67     1    29\n -3.2045029061682060E+00 a      2010     0    67     1    30\n -3.2143257614725926E+00 a      2011     0    68     1     1\n -5.9667639325500348E+00 a      2012     0    68     1     2\n  7.6704732439861143E+00 a      2013     0    68     1     3\n -1.3391711017500634E+00 a      2014     0    68     1     4\n -6.8834813921483695E+00 a      2015     0    68     1     5\n  1.2482065744870803E+00 a      2016     0    68     1     6\n -3.7149528581821984E+00 a      2017     0    68     1     7\n  8.8937416285610862E+00 a      2018     0    68     1     8\n -8.6285030480401770E-01 a      2019     0    68     1     9\n  4.7467826148241277E-01 a      2020     0    68     1    10\n  5.2246769221143881E+00 a      2021     0    68     1    11\n  9.1266091657688875E-01 a      2022     0    68     1    12\n -4.9986686226314916E+00 a      2023     0    68     1    13\n -5.8793718539428097E-01 a      2024     0    68     1    14\n -5.6750658893902690E+00 a      2025     0    68     1    15\n  6.4373522718012322E-01 a      2026     0    68     1    16\n -4.6294877231174114E+00 a      2027     0    68     1    17\n -1.0565047944668107E+01 a      2028     0    68     1    18\n  3.5598079529910787E+00 a      2029     0    68     1    19\n -3.8099476733873567E+00 a      2030     0    68     1    20\n  2.3275523704234948E+00 a      2031     0    68     1    21\n 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2.6935370197791564E-01 a     10438     1    24     2    18\n  5.4339448602431117E-01 a     10439     1    24     2    19\n -3.3214320527381641E-01 a     10440     1    24     2    20\n -2.2371482189750269E+00 a     10441     1    25     2     1\n -6.4427416395920156E-01 a     10442     1    25     2     2\n  6.6573975793408113E-01 a     10443     1    25     2     3\n  7.5312778884177844E-01 a     10444     1    25     2     4\n -2.1559323829494801E+00 a     10445     1    25     2     5\n  7.4284316734655062E-02 a     10446     1    25     2     6\n -2.3747413750097843E+00 a     10447     1    25     2     7\n -9.0314481774201361E-01 a     10448     1    25     2     8\n -1.5459304963438867E+00 a     10449     1    25     2     9\n  1.6781709126216608E+00 a     10450     1    25     2    10\n  2.1808372307962713E+00 a     10451     1    25     2    11\n  2.3033562064873219E+00 a     10452     1    25     2    12\n  4.8655757099423172E-02 a     10453     1    25     2    13\n  6.2292324283456757E-01 a     10454     1    25     2    14\n -1.0413071738047613E-01 a     10455     1    25     2    15\n -8.8198720103022987E-01 a     10456     1    25     2    16\n  1.8723432439746406E+00 a     10457     1    25     2    17\n -1.1653640353505037E+00 a     10458     1    25     2    18\n -8.0443880528711564E-01 a     10459     1    25     2    19\n  1.0788134708597794E+00 a     10460     1    25     2    20\n  1.6427933213312154E-01 a     10461     1    26     2     1\n -6.4407581990519169E-01 a     10462     1    26     2     2\n  1.0082942376833108E+00 a     10463     1    26     2     3\n -2.7009787589291412E-01 a     10464     1    26     2     4\n  8.7923639055035960E-02 a     10465     1    26     2     5\n -4.2963337870448520E-01 a     10466     1    26     2     6\n -1.7448182622459489E+00 a     10467     1    26     2     7\n -2.5849633320380621E+00 a     10468     1    26     2     8\n  7.3369429880103898E-01 a     10469     1    26     2     9\n  3.3863060227926722E-01 a     10470     1    26     2    10\n  1.3823116919031351E+00 a     10471     1    26     2    11\n  3.7082348939142307E-01 a     10472     1    26     2    12\n -9.7122697483857212E-01 a     10473     1    26     2    13\n  1.3588077534903265E+00 a     10474     1    26     2    14\n  1.2536591934077737E+00 a     10475     1    26     2    15\n -6.5398289409766430E-01 a     10476     1    26     2    16\n -3.0250643484764672E-01 a     10477     1    26     2    17\n -1.8386110581472255E+00 a     10478     1    26     2    18\n  3.7878798210665129E-02 a     10479     1    26     2    19\n  5.3962372220476895E-01 a     10480     1    26     2    20\n  2.0103193340822871E+00 a     10481     1    27     2     1\n -2.6625957144393770E-02 a     10482     1    27     2     2\n  3.0703454221413307E-01 a     10483     1    27     2     3\n -6.1118727756985880E-01 a     10484     1    27     2     4\n  1.7471139651180407E+00 a     10485     1    27     2     5\n  1.0867597011470271E+00 a     10486     1    27     2     6\n  1.5169298138532146E+00 a     10487     1    27     2     7\n -2.0970054897169952E+00 a     10488     1    27     2     8\n -5.0338365901425874E-01 a     10489     1    27     2     9\n  6.5781057678945820E-01 a     10490     1    27     2    10\n -1.3445806944440188E+00 a     10491     1    27     2    11\n -1.5995653873745411E-01 a     10492     1    27     2    12\n -1.5585365254131762E+00 a     10493     1    27     2    13\n -4.9733708869828813E-01 a     10494     1    27     2    14\n  7.6870147256530474E-01 a     10495     1    27     2    15\n  8.0606125442028509E-01 a     10496     1    27     2    16\n  2.7565408523353313E-01 a     10497     1    27     2    17\n -1.0351524780257726E+00 a     10498     1    27     2    18\n  1.6997154241973220E-01 a     10499     1    27     2    19\n  2.0407894244970546E+00 a     10500     1    27     2    20\n  1.5460500083022444E+00 a     10501     1    28     2     1\n -5.0534414393942417E-01 a     10502     1    28     2     2\n  2.2725214203984785E+00 a     10503     1    28     2     3\n  2.1115999129838121E+00 a     10504     1    28     2     4\n -5.6243438113246269E-01 a     10505     1    28     2     5\n  2.2390907510078542E+00 a     10506     1    28     2     6\n  2.4987683655889806E-01 a     10507     1    28     2     7\n -5.7892180882644972E-02 a     10508     1    28     2     8\n  1.4299556642380675E+00 a     10509     1    28     2     9\n  5.8755651222240279E-01 a     10510     1    28     2    10\n  6.5807698425641581E-01 a     10511     1    28     2    11\n  2.7678277714340277E-01 a     10512     1    28     2    12\n  1.6506852277292245E+00 a     10513     1    28     2    13\n -8.7012304541909036E-01 a     10514     1    28     2    14\n -2.8194790665587688E-01 a     10515     1    28     2    15\n -2.8146224884209650E+00 a     10516     1    28     2    16\n -1.3891189814709959E+00 a     10517     1    28     2    17\n  2.2060362536945735E-01 a     10518     1    28     2    18\n  3.1158814076123920E-01 a     10519     1    28     2    19\n  4.4023061538902084E+00 a     10520     1    28     2    20\n  1.3422233069068823E+00 a     10521     1    29     2     1\n  2.9130463113447735E-01 a     10522     1    29     2     2\n  1.9973609745350747E+00 a     10523     1    29     2     3\n -6.3695684991123447E-01 a     10524     1    29     2     4\n -2.1911021605422145E+00 a     10525     1    29     2     5\n  1.5121610496707201E+00 a     10526     1    29     2     6\n  1.7146817156558458E+00 a     10527     1    29     2     7\n  4.4558277583039863E-01 a     10528     1    29     2     8\n  3.1306635921011661E-01 a     10529     1    29     2     9\n -7.1280598071877171E-02 a     10530     1    29     2    10\n -1.2095644352398949E+00 a     10531     1    29     2    11\n -7.9856254561567275E-01 a     10532     1    29     2    12\n  1.4788943169403246E+00 a     10533     1    29     2    13\n  5.3864709925862553E-01 a     10534     1    29     2    14\n  2.6692909354021416E-01 a     10535     1    29     2    15\n -2.1972557880327068E-01 a     10536     1    29     2    16\n -1.0346990826109503E+00 a     10537     1    29     2    17\n -5.2468551112941708E-01 a     10538     1    29     2    18\n  1.8883380494637833E-01 a     10539     1    29     2    19\n  1.6256209131929505E-01 a     10540     1    29     2    20\n -6.0535890229810418E-01 a     10541     1    30     2     1\n  2.9108091077060988E-01 a     10542     1    30     2     2\n -1.0236084969791954E+00 a     10543     1    30     2     3\n  9.1548100019632317E-01 a     10544     1    30     2     4\n -1.0750615027977797E+00 a     10545     1    30     2     5\n  2.0224323574640075E+00 a     10546     1    30     2     6\n  1.0890527414115256E+00 a     10547     1    30     2     7\n -9.7595352526629015E-02 a     10548     1    30     2     8\n -1.8947793443664713E+00 a     10549     1    30     2     9\n -4.5225267715063172E-01 a     10550     1    30     2    10\n  2.7958930988576824E-01 a     10551     1    30     2    11\n -6.3626272279496920E-01 a     10552     1    30     2    12\n  3.0348025602065914E-01 a     10553     1    30     2    13\n -1.4232401974219648E+00 a     10554     1    30     2    14\n -3.0246284031444393E-01 a     10555     1    30     2    15\n  2.2479278585755805E-01 a     10556     1    30     2    16\n  4.0832628907054025E-01 a     10557     1    30     2    17\n -5.6014638423900830E-02 a     10558     1    30     2    18\n  1.5809428659510447E+00 a     10559     1    30     2    19\n  5.1196273083623844E-01 a     10560     1    30     2    20\n  9.9903466240451877E+00 b     10561     2     1\n -4.1513754444907152E+00 b     10562     2     2\n -1.9838813114644920E+00 b     10563     2     3\n  4.5766582065808570E-01 b     10564     2     4\n  5.4989694224725758E+00 b     10565     2     5\n -8.8054559208946381E-01 b     10566     2     6\n  2.7620887175618281E+00 b     10567     2     7\n  1.7075452939746377E+01 b     10568     2     8\n -1.7141928542414151E+00 b     10569     2     9\n  3.3832919102859358E+00 b     10570     2    10\n -1.7206432541048007E+00 b     10571     2    11\n -4.9391083488161129E+00 b     10572     2    12\n  1.0224034245647149E+00 b     10573     2    13\n  8.0221921498551048E+00 b     10574     2    14\n -3.7445302409888268E+00 b     10575     2    15\n -1.2661999609654199E+01 b     10576     2    16\n  7.0298962468109112E+00 b     10577     2    17\n  2.6181052048580669E+00 b     10578     2    18\n  8.4281364797389746E-01 b     10579     2    19\n  1.0664488944249935E+00 b     10580     2    20\n -1.0557065063045376E-03 a     10581     2     1     3     1\n  2.6701368355046244E+00 a     10582     2     2     3     1\n  8.5736458052644883E-03 a     10583     2     3     3     1\n  8.4425546814101884E-03 a     10584     2     4     3     1\n -2.0822056135789246E-02 a     10585     2     5     3     1\n -2.8153424057891551E-03 a     10586     2     6     3     1\n -8.8513610087836495E-03 a     10587     2     7     3     1\n  1.7504804692691420E-02 a     10588     2     8     3     1\n  1.1567408354269551E-02 a     10589     2     9     3     1\n  5.1459489281085202E-01 a     10590     2    10     3     1\n -6.2354041590818796E-03 a     10591     2    11     3     1\n  1.9068385143113643E-04 a     10592     2    12     3     1\n -7.4624623347023539E-03 a     10593     2    13     3     1\n -3.0897325872564704E-03 a     10594     2    14     3     1\n -2.5322813543927142E-01 a     10595     2    15     3     1\n  3.7586687158479909E-03 a     10596     2    16     3     1\n  1.6021186570534030E-03 a     10597     2    17     3     1\n -2.2330537566456452E-02 a     10598     2    18     3     1\n  1.6707153336643946E-01 a     10599     2    19     3     1\n  2.4731799846569105E-02 a     10600     2    20     3     1\n  4.6382812877716184E-01 b     10601     3     1\n"
  },
  {
    "path": "examples/potentials/Cu2S_PBE/input.nn",
    "content": "###############################################################################\n# HDNNP for copper sulfide Cu2S\n###############################################################################\n# Length unit     : Angstrom\n# Energy unit     : eV\n# Reference method: PBE\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.8640662064628053E+00\nconv_energy   7.3890846653659121E+00\nconv_length   6.1376931796181502E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type.\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          40             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   2              # Training parallelization used (0 = Serial, 1-4 = MSEKF implementations (4-fastest)).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2 10 1 15 2    # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 3\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.02315        # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               1              # Write energy comparison.\nwrite_trainforces               5              # Write force comparison.\nwrite_weights_epoch             1              # Write weights.\nwrite_neuronstats               5              # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\n# symfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\n# symfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n"
  },
  {
    "path": "examples/potentials/Cu2S_PBE/nnp-train.log.0000",
    "content": "\n*** SETUP: MPI ****************************************************************\n\nNumber of processors: 16\nProcess 1 of 16 (rank 0): n51-048.vsc3plus.xcat\nProcess 2 of 16 (rank 1): n51-048.vsc3plus.xcat\nProcess 3 of 16 (rank 2): n51-048.vsc3plus.xcat\nProcess 4 of 16 (rank 3): n51-048.vsc3plus.xcat\nProcess 5 of 16 (rank 4): n51-048.vsc3plus.xcat\nProcess 6 of 16 (rank 5): n51-048.vsc3plus.xcat\nProcess 7 of 16 (rank 6): n51-048.vsc3plus.xcat\nProcess 8 of 16 (rank 7): n51-048.vsc3plus.xcat\nProcess 9 of 16 (rank 8): n51-048.vsc3plus.xcat\nProcess 10 of 16 (rank 9): n51-048.vsc3plus.xcat\nProcess 11 of 16 (rank 10): n51-048.vsc3plus.xcat\nProcess 12 of 16 (rank 11): n51-048.vsc3plus.xcat\nProcess 13 of 16 (rank 12): n51-048.vsc3plus.xcat\nProcess 14 of 16 (rank 13): n51-048.vsc3plus.xcat\nProcess 15 of 16 (rank 14): n51-048.vsc3plus.xcat\nProcess 16 of 16 (rank 15): n51-048.vsc3plus.xcat\n*******************************************************************************\n\n*******************************************************************************\n\n   NNP LIBRARY v0.1.0\n   ------------------\n\nGit branch  : master\nGit revision: 7f7427e (7f7427e692ba496c08cde43f02c65ec58de915fa)\n\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 321 lines.\nFound 182 lines with keywords.\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is used.\nMean energy per atom     :  -3.8640662064628053E+00\nConversion factor energy :   7.3890846653659121E+00\nConversion factor length :   6.1376931796181502E+00\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  S ( 16)\nElement  1: Cu ( 29)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:   0.00000000E+00\nElement  1:   0.00000000E+00\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_POLY2 (6)\nx := (r - rc * alpha) / (rc - rc * alpha)\nf(x) = ((15 - 6x)x - 10)x^3 + 1\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  S :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  S  2  S    5.309E-02 9.207E+00         3.683E+01  6 0.00   105\n   2  S  2 Cu    5.309E-02 9.207E+00         3.683E+01  6 0.00   115\n   3  S  2  S    5.309E-02 1.228E+01         3.683E+01  6 0.00   106\n   4  S  2 Cu    5.309E-02 1.228E+01         3.683E+01  6 0.00   116\n   5  S  2  S    5.309E-02 1.534E+01         3.683E+01  6 0.00   107\n   6  S  2 Cu    5.309E-02 1.534E+01         3.683E+01  6 0.00   117\n   7  S  2 Cu    5.309E-02 1.841E+01         3.683E+01  6 0.00   118\n   8  S  3  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   163\n   9  S  3  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   176\n  10  S  3 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   189\n  11  S  3  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   164\n  12  S  3  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   177\n  13  S  3 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   190\n  14  S  3  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   165\n  15  S  3  S Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   178\n  16  S  3 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   191\n  17  S  3  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   166\n  18  S  3  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   179\n  19  S  3 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   192\n  20  S  3  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   159\n  21  S  3  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   172\n  22  S  3 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   185\n  23  S  3  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   160\n  24  S  3  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   173\n  25  S  3 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   186\n  26  S  3  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   161\n  27  S  3  S Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   174\n  28  S  3 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   187\n  29  S  3  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   162\n  30  S  3  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   175\n  31  S  3 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   188\n  32  S  3  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   155\n  33  S  3  S Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   168\n  34  S  3  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   156\n  35  S  3  S Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   169\n  36  S  3 Cu Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   182\n  37  S  3  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   158\n  38  S  3  S Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   171\n  39  S  9  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   251\n  40  S  9  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   264\n  41  S  9 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   277\n  42  S  9  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   252\n  43  S  9  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   265\n  44  S  9 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   278\n  45  S  9  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   253\n  46  S  9  S Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   266\n  47  S  9 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   279\n  48  S  9  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   254\n  49  S  9  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   267\n  50  S  9 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   280\n  51  S  9  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   247\n  52  S  9  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   260\n  53  S  9 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   273\n  54  S  9  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   248\n  55  S  9  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   261\n  56  S  9 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   274\n  57  S  9  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   249\n  58  S  9  S Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   262\n  59  S  9 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   275\n  60  S  9  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   250\n  61  S  9  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   263\n  62  S  9 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   276\n  63  S  9  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   243\n  64  S  9  S Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   256\n  65  S  9 Cu Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   269\n  66  S  9  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   244\n  67  S  9  S Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   257\n  68  S  9 Cu Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   270\n  69  S  9  S Cu 5.898E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   258\n  70  S  9  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   246\n  71  S  9  S Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   259\n  72  S  9 Cu Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   272\n-------------------------------------------------------------------------------\nShort range atomic symmetry functions element Cu :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1 Cu  2  S    5.309E-02 9.207E+00         3.683E+01  6 0.00   126\n   2 Cu  2  S    5.309E-02 1.228E+01         3.683E+01  6 0.00   127\n   3 Cu  2 Cu    5.309E-02 1.228E+01         3.683E+01  6 0.00   137\n   4 Cu  2  S    5.309E-02 1.534E+01         3.683E+01  6 0.00   128\n   5 Cu  2 Cu    5.309E-02 1.534E+01         3.683E+01  6 0.00   138\n   6 Cu  2  S    5.309E-02 1.841E+01         3.683E+01  6 0.00   129\n   7 Cu  2 Cu    5.309E-02 1.841E+01         3.683E+01  6 0.00   139\n   8 Cu  2  S    5.309E-02 2.455E+01         3.683E+01  6 0.00   131\n   9 Cu  2  S    5.309E-02 3.069E+01         3.683E+01  6 0.00   133\n  10 Cu  3  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   203\n  11 Cu  3  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   216\n  12 Cu  3 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   229\n  13 Cu  3  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   204\n  14 Cu  3  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   217\n  15 Cu  3 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   230\n  16 Cu  3  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   205\n  17 Cu  3 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   231\n  18 Cu  3  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   206\n  19 Cu  3  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   219\n  20 Cu  3 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   232\n  21 Cu  3  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   199\n  22 Cu  3  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   212\n  23 Cu  3 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   225\n  24 Cu  3  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   200\n  25 Cu  3  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   213\n  26 Cu  3 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   226\n  27 Cu  3  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   201\n  28 Cu  3 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   227\n  29 Cu  3  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   202\n  30 Cu  3  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   215\n  31 Cu  3 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   228\n  32 Cu  3  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   195\n  33 Cu  3  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   196\n  34 Cu  3  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   198\n  35 Cu  9  S  S 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   291\n  36 Cu  9  S Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   304\n  37 Cu  9 Cu Cu 4.388E-04 0.000E+00 -1  1.0 3.683E+01  6 0.00   317\n  38 Cu  9  S  S 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   292\n  39 Cu  9  S Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   305\n  40 Cu  9 Cu Cu 4.388E-04 0.000E+00  1  1.0 3.683E+01  6 0.00   318\n  41 Cu  9  S  S 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   293\n  42 Cu  9  S Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   306\n  43 Cu  9 Cu Cu 4.388E-04 0.000E+00 -1  6.0 3.683E+01  6 0.00   319\n  44 Cu  9  S  S 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   294\n  45 Cu  9  S Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   307\n  46 Cu  9 Cu Cu 4.388E-04 0.000E+00  1  6.0 3.683E+01  6 0.00   320\n  47 Cu  9  S  S 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   287\n  48 Cu  9  S Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   300\n  49 Cu  9 Cu Cu 1.084E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   313\n  50 Cu  9  S  S 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   288\n  51 Cu  9  S Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   301\n  52 Cu  9 Cu Cu 1.084E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   314\n  53 Cu  9  S  S 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   289\n  54 Cu  9  S Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   302\n  55 Cu  9 Cu Cu 1.084E-03 0.000E+00 -1  6.0 3.683E+01  6 0.00   315\n  56 Cu  9  S  S 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   290\n  57 Cu  9  S Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   303\n  58 Cu  9 Cu Cu 1.084E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   316\n  59 Cu  9  S  S 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   283\n  60 Cu  9  S Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   296\n  61 Cu  9 Cu Cu 5.898E-03 0.000E+00 -1  1.0 3.683E+01  6 0.00   309\n  62 Cu  9  S  S 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   284\n  63 Cu  9  S Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   297\n  64 Cu  9 Cu Cu 5.898E-03 0.000E+00  1  1.0 3.683E+01  6 0.00   310\n  65 Cu  9  S  S 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   286\n  66 Cu  9  S Cu 5.898E-03 0.000E+00  1  6.0 3.683E+01  6 0.00   299\n-------------------------------------------------------------------------------\nMinimum cutoff radius for element  S: 36.826159\nMinimum cutoff radius for element Cu: 36.826159\nMaximum cutoff radius (global)      : 36.826159\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function group index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  S :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  S  2  S            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 9.207E+00                 -  -    -   104    1    1  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   105    2    3  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   106    3    5  \n   2  S  2 Cu            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 9.207E+00                 -  -    -   114    1    2  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   115    2    4  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   116    3    6  \n   -  -  -  -    5.309E-02 1.841E+01                 -  -    -   117    4    7  \n   3  S  3  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   162    1    8 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   163    2   11 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   164    3   14 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   165    4   17 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   158    5   20 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   159    6   23 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   160    7   26 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   161    8   29 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   154    9   32 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   155   10   34 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   157   11   37 0\n   4  S  3  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   175    1    9 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   176    2   12 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   177    3   15 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   178    4   18 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   171    5   21 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   172    6   24 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   173    7   27 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   174    8   30 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   167    9   33 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   168   10   35 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   170   11   38 0\n   5  S  3 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   188    1   10 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   189    2   13 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   190    3   16 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   191    4   19 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   184    5   22 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   185    6   25 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   186    7   28 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   187    8   31 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   181    9   36 1\n   6  S  9  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   250    1   39 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   251    2   42 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   252    3   45 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   253    4   48 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   246    5   51 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   247    6   54 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   248    7   57 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   249    8   60 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   242    9   63 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   243   10   66 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   245   11   70 0\n   7  S  9  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   263    1   40 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   264    2   43 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   265    3   46 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   266    4   49 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   259    5   52 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   260    6   55 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   261    7   58 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   262    8   61 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   255    9   64 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   256   10   67 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  6.0         -  -    -   257   11   69 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   258   12   71 0\n   8  S  9 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   276    1   41 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   277    2   44 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   278    3   47 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   279    4   50 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   272    5   53 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   273    6   56 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   274    7   59 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   275    8   62 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   268    9   65 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   269   10   68 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   271   11   72 0\n-------------------------------------------------------------------------------\nShort range atomic symmetry function groups element Cu :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1 Cu  2  S            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 9.207E+00                 -  -    -   125    1    1  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   126    2    2  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   127    3    4  \n   -  -  -  -    5.309E-02 1.841E+01                 -  -    -   128    4    6  \n   -  -  -  -    5.309E-02 2.455E+01                 -  -    -   130    5    8  \n   -  -  -  -    5.309E-02 3.069E+01                 -  -    -   132    6    9  \n   2 Cu  2 Cu            *         *         3.683E+01  6 0.00     *    *    *  \n   -  -  -  -    5.309E-02 1.228E+01                 -  -    -   136    1    3  \n   -  -  -  -    5.309E-02 1.534E+01                 -  -    -   137    2    5  \n   -  -  -  -    5.309E-02 1.841E+01                 -  -    -   138    3    7  \n   3 Cu  3  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   202    1   10 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   203    2   13 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   204    3   16 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   205    4   18 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   198    5   21 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   199    6   24 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   200    7   27 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   201    8   29 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   194    9   32 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   195   10   33 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   197   11   34 0\n   4 Cu  3  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   215    1   11 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   216    2   14 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   218    3   19 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   211    4   22 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   212    5   25 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   214    6   30 0\n   5 Cu  3 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   228    1   12 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   229    2   15 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   230    3   17 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   231    4   20 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   224    5   23 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   225    6   26 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   226    7   28 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   227    8   31 0\n   6 Cu  9  S  S         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   290    1   35 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   291    2   38 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   292    3   41 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   293    4   44 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   286    5   47 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   287    6   50 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   288    7   53 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   289    8   56 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   282    9   59 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   283   10   62 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   285   11   65 0\n   7 Cu  9  S Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   303    1   36 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   304    2   39 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   305    3   42 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   306    4   45 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   299    5   48 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   300    6   51 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   301    7   54 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   302    8   57 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   295    9   60 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   296   10   63 0\n   -  -  -  -  - 5.898E-03 0.000E+00  1  6.0         -  -    -   298   11   66 0\n   8 Cu  9 Cu Cu         *         *  *    * 3.683E+01  6 0.00     *    *    * *\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  1.0         -  -    -   316    1   37 1\n   -  -  -  -  - 4.388E-04 0.000E+00  1  1.0         -  -    -   317    2   40 0\n   -  -  -  -  - 4.388E-04 0.000E+00 -1  6.0         -  -    -   318    3   43 0\n   -  -  -  -  - 4.388E-04 0.000E+00  1  6.0         -  -    -   319    4   46 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  1.0         -  -    -   312    5   49 1\n   -  -  -  -  - 1.084E-03 0.000E+00  1  1.0         -  -    -   313    6   52 0\n   -  -  -  -  - 1.084E-03 0.000E+00 -1  6.0         -  -    -   314    7   55 0\n   -  -  -  -  - 1.084E-03 0.000E+00  1  6.0         -  -    -   315    8   58 0\n   -  -  -  -  - 5.898E-03 0.000E+00 -1  1.0         -  -    -   308    9   61 1\n   -  -  -  -  - 5.898E-03 0.000E+00  1  1.0         -  -    -   309   10   64 0\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic short range NN for element  S :\nNumber of weights    :   2450\nNumber of biases     :     51\nNumber of connections:   2501\nArchitecture       72   25   25    1\n-------------------------------------------------------------------------------\n   1   G   p   p   l\n   2   G   p   p    \n   3   G   p   p    \n   4   G   p   p    \n   5   G   p   p    \n   6   G   p   p    \n   7   G   p   p    \n   8   G   p   p    \n   9   G   p   p    \n  10   G   p   p    \n  11   G   p   p    \n  12   G   p   p    \n  13   G   p   p    \n  14   G   p   p    \n  15   G   p   p    \n  16   G   p   p    \n  17   G   p   p    \n  18   G   p   p    \n  19   G   p   p    \n  20   G   p   p    \n  21   G   p   p    \n  22   G   p   p    \n  23   G   p   p    \n  24   G   p   p    \n  25   G   p   p    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n  37   G            \n  38   G            \n  39   G            \n  40   G            \n  41   G            \n  42   G            \n  43   G            \n  44   G            \n  45   G            \n  46   G            \n  47   G            \n  48   G            \n  49   G            \n  50   G            \n  51   G            \n  52   G            \n  53   G            \n  54   G            \n  55   G            \n  56   G            \n  57   G            \n  58   G            \n  59   G            \n  60   G            \n  61   G            \n  62   G            \n  63   G            \n  64   G            \n  65   G            \n  66   G            \n  67   G            \n  68   G            \n  69   G            \n  70   G            \n  71   G            \n  72   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element Cu :\nNumber of weights    :   2300\nNumber of biases     :     51\nNumber of connections:   2351\nArchitecture       66   25   25    1\n-------------------------------------------------------------------------------\n   1   G   p   p   l\n   2   G   p   p    \n   3   G   p   p    \n   4   G   p   p    \n   5   G   p   p    \n   6   G   p   p    \n   7   G   p   p    \n   8   G   p   p    \n   9   G   p   p    \n  10   G   p   p    \n  11   G   p   p    \n  12   G   p   p    \n  13   G   p   p    \n  14   G   p   p    \n  15   G   p   p    \n  16   G   p   p    \n  17   G   p   p    \n  18   G   p   p    \n  19   G   p   p    \n  20   G   p   p    \n  21   G   p   p    \n  22   G   p   p    \n  23   G   p   p    \n  24   G   p   p    \n  25   G   p   p    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n  31   G            \n  32   G            \n  33   G            \n  34   G            \n  35   G            \n  36   G            \n  37   G            \n  38   G            \n  39   G            \n  40   G            \n  41   G            \n  42   G            \n  43   G            \n  44   G            \n  45   G            \n  46   G            \n  47   G            \n  48   G            \n  49   G            \n  50   G            \n  51   G            \n  52   G            \n  53   G            \n  54   G            \n  55   G            \n  56   G            \n  57   G            \n  58   G            \n  59   G            \n  60   G            \n  61   G            \n  62   G            \n  63   G            \n  64   G            \n  65   G            \n  66   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALESIGMA (4)\nGs = Smin + (Smax - Smin) * (G - Gmean) / Gsigma\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  S :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  9.17E-08  7.06E-01  2.24E-02  9.64E-02  1.04E+01  0.00  1.00 4\n   2  2.64E-01  2.47E+00  1.04E+00  1.94E-01  5.15E+00  0.00  1.00 4\n   3  1.55E-05  1.42E+00  5.53E-02  2.15E-01  4.65E+00  0.00  1.00 4\n   4  1.41E+00  4.74E+00  3.10E+00  3.59E-01  2.79E+00  0.00  1.00 4\n   5  9.80E-04  1.95E+00  1.14E-01  2.29E-01  4.37E+00  0.00  1.00 4\n   6  2.22E+00  6.07E+00  3.88E+00  3.93E-01  2.54E+00  0.00  1.00 4\n   7  1.03E+00  5.14E+00  2.58E+00  4.38E-01  2.28E+00  0.00  1.00 4\n   8  4.85E-03  3.91E-01  4.76E-02  2.78E-02  3.60E+01  0.00  1.00 4\n   9  9.32E-02  2.83E+00  6.02E-01  3.19E-01  3.13E+00  0.00  1.00 4\n  10  6.72E-01  4.49E+00  2.20E+00  4.15E-01  2.41E+00  0.00  1.00 4\n  11  2.21E-02  8.66E-01  1.41E-01  7.58E-02  1.32E+01  0.00  1.00 4\n  12  8.42E-01  7.07E+00  2.90E+00  7.31E-01  1.37E+00  0.00  1.00 4\n  13  1.45E+00  9.65E+00  4.37E+00  8.38E-01  1.19E+00  0.00  1.00 4\n  14  2.43E-06  5.30E-02  2.81E-04  1.65E-03  6.05E+02  0.00  1.00 4\n  15  4.38E-04  3.34E-01  1.51E-02  3.64E-02  2.75E+01  0.00  1.00 4\n  16  1.87E-02  5.31E-01  1.93E-01  5.38E-02  1.86E+01  0.00  1.00 4\n  17  5.64E-03  2.71E-01  3.62E-02  2.22E-02  4.50E+01  0.00  1.00 4\n  18  5.82E-01  3.04E+00  1.54E+00  2.90E-01  3.45E+00  0.00  1.00 4\n  19  3.55E-01  2.89E+00  1.25E+00  2.61E-01  3.84E+00  0.00  1.00 4\n  20  1.31E-03  2.10E-01  1.65E-02  1.62E-02  6.18E+01  0.00  1.00 4\n  21  3.36E-02  1.60E+00  2.67E-01  1.92E-01  5.22E+00  0.00  1.00 4\n  22  3.53E-01  2.60E+00  1.20E+00  2.39E-01  4.19E+00  0.00  1.00 4\n  23  5.63E-03  4.83E-01  4.87E-02  4.56E-02  2.19E+01  0.00  1.00 4\n  24  3.56E-01  3.94E+00  1.35E+00  4.31E-01  2.32E+00  0.00  1.00 4\n  25  7.14E-01  5.41E+00  2.34E+00  4.75E-01  2.11E+00  0.00  1.00 4\n  26  6.03E-07  2.43E-02  1.04E-04  6.95E-04  1.44E+03  0.00  1.00 4\n  27  1.42E-04  1.88E-01  6.73E-03  1.89E-02  5.30E+01  0.00  1.00 4\n  28  7.67E-03  2.89E-01  9.68E-02  2.86E-02  3.50E+01  0.00  1.00 4\n  29  1.46E-03  1.28E-01  1.25E-02  1.22E-02  8.20E+01  0.00  1.00 4\n  30  2.43E-01  1.58E+00  7.31E-01  1.60E-01  6.24E+00  0.00  1.00 4\n  31  1.57E-01  1.50E+00  6.22E-01  1.39E-01  7.21E+00  0.00  1.00 4\n  32  8.03E-08  9.10E-03  1.18E-04  7.29E-04  1.37E+03  0.00  1.00 4\n  33  3.84E-05  4.69E-02  2.29E-03  6.35E-03  1.57E+02  0.00  1.00 4\n  34  2.51E-07  2.66E-02  3.52E-04  2.18E-03  4.59E+02  0.00  1.00 4\n  35  7.82E-04  1.21E-01  1.02E-02  1.56E-02  6.43E+01  0.00  1.00 4\n  36  6.08E-03  1.52E-01  4.53E-02  1.44E-02  6.93E+01  0.00  1.00 4\n  37  6.52E-08  6.90E-03  8.45E-05  5.18E-04  1.93E+03  0.00  1.00 4\n  38  5.10E-04  3.38E-02  5.05E-03  4.24E-03  2.36E+02  0.00  1.00 4\n  39  3.01E-01  3.92E+00  1.62E+00  3.61E-01  2.77E+00  0.00  1.00 4\n  40  2.92E+00  2.10E+01  1.07E+01  1.84E+00  5.42E-01  0.00  1.00 4\n  41  5.83E+00  3.32E+01  1.69E+01  2.84E+00  3.52E-01  0.00  1.00 4\n  42  2.90E-01  3.42E+00  1.35E+00  2.98E-01  3.35E+00  0.00  1.00 4\n  43  3.32E+00  2.00E+01  1.05E+01  1.84E+00  5.45E-01  0.00  1.00 4\n  44  5.60E+00  2.95E+01  1.47E+01  2.43E+00  4.11E-01  0.00  1.00 4\n  45  7.32E-02  1.42E+00  4.62E-01  1.06E-01  9.43E+00  0.00  1.00 4\n  46  7.44E-01  6.16E+00  3.09E+00  5.27E-01  1.90E+00  0.00  1.00 4\n  47  1.03E+00  9.55E+00  4.66E+00  8.82E-01  1.13E+00  0.00  1.00 4\n  48  5.34E-02  6.08E-01  2.01E-01  4.75E-02  2.11E+01  0.00  1.00 4\n  49  1.10E+00  5.34E+00  2.92E+00  4.91E-01  2.04E+00  0.00  1.00 4\n  50  9.37E-01  6.05E+00  2.81E+00  5.09E-01  1.97E+00  0.00  1.00 4\n  51  1.14E-01  2.31E+00  7.57E-01  2.08E-01  4.80E+00  0.00  1.00 4\n  52  1.43E+00  1.33E+01  5.88E+00  1.22E+00  8.22E-01  0.00  1.00 4\n  53  3.55E+00  2.13E+01  1.09E+01  1.88E+00  5.32E-01  0.00  1.00 4\n  54  1.10E-01  2.08E+00  6.31E-01  1.75E-01  5.70E+00  0.00  1.00 4\n  55  1.65E+00  1.24E+01  5.77E+00  1.19E+00  8.38E-01  0.00  1.00 4\n  56  3.33E+00  1.87E+01  9.22E+00  1.58E+00  6.34E-01  0.00  1.00 4\n  57  2.75E-02  9.17E-01  2.15E-01  6.17E-02  1.62E+01  0.00  1.00 4\n  58  3.62E-01  3.89E+00  1.71E+00  3.48E-01  2.87E+00  0.00  1.00 4\n  59  5.66E-01  6.16E+00  2.96E+00  5.90E-01  1.69E+00  0.00  1.00 4\n  60  2.02E-02  3.35E-01  9.30E-02  2.76E-02  3.62E+01  0.00  1.00 4\n  61  5.54E-01  3.19E+00  1.59E+00  3.05E-01  3.28E+00  0.00  1.00 4\n  62  5.38E-01  3.63E+00  1.66E+00  3.14E-01  3.19E+00  0.00  1.00 4\n  63  9.67E-05  1.49E-01  4.32E-03  8.27E-03  1.21E+02  0.00  1.00 4\n  64  1.20E-02  1.13E+00  1.28E-01  1.34E-01  7.47E+00  0.00  1.00 4\n  65  2.08E-01  1.86E+00  8.23E-01  1.78E-01  5.60E+00  0.00  1.00 4\n  66  8.79E-05  1.26E-01  4.40E-03  1.18E-02  8.46E+01  0.00  1.00 4\n  67  1.34E-02  8.78E-01  1.18E-01  1.13E-01  8.81E+00  0.00  1.00 4\n  68  1.77E-01  1.43E+00  6.21E-01  1.29E-01  7.73E+00  0.00  1.00 4\n  69  2.86E-03  3.73E-01  3.77E-02  3.72E-02  2.69E+01  0.00  1.00 4\n  70  1.59E-05  2.60E-02  7.25E-04  2.49E-03  4.02E+02  0.00  1.00 4\n  71  4.72E-03  1.60E-01  2.88E-02  1.94E-02  5.15E+01  0.00  1.00 4\n  72  1.53E-02  1.93E-01  6.97E-02  1.78E-02  5.62E+01  0.00  1.00 4\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element Cu :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  2.47E-02  1.51E+00  5.19E-01  1.23E-01  8.13E+00  0.00  1.00 4\n   2  2.50E-01  2.69E+00  1.55E+00  2.29E-01  4.37E+00  0.00  1.00 4\n   3  1.86E-03  3.82E+00  1.12E+00  3.99E-01  2.50E+00  0.00  1.00 4\n   4  6.93E-01  3.94E+00  1.94E+00  2.80E-01  3.57E+00  0.00  1.00 4\n   5  5.22E-02  5.98E+00  2.79E+00  6.88E-01  1.45E+00  0.00  1.00 4\n   6  3.47E-01  2.81E+00  1.29E+00  2.50E-01  3.99E+00  0.00  1.00 4\n   7  5.67E-01  6.01E+00  3.40E+00  5.38E-01  1.86E+00  0.00  1.00 4\n   8  8.22E-02  2.16E+00  9.59E-01  2.21E-01  4.53E+00  0.00  1.00 4\n   9  9.75E-02  8.05E-01  3.96E-01  7.28E-02  1.37E+01  0.00  1.00 4\n  10  7.56E-02  1.22E+00  4.24E-01  1.10E-01  9.07E+00  0.00  1.00 4\n  11  3.86E-01  3.42E+00  1.54E+00  2.98E-01  3.35E+00  0.00  1.00 4\n  12  1.27E-01  3.34E+00  9.07E-01  3.08E-01  3.25E+00  0.00  1.00 4\n  13  3.58E-02  2.31E+00  4.52E-01  2.05E-01  4.87E+00  0.00  1.00 4\n  14  1.74E+00  9.19E+00  5.03E+00  7.70E-01  1.30E+00  0.00  1.00 4\n  15  5.61E-01  6.92E+00  2.56E+00  7.04E-01  1.42E+00  0.00  1.00 4\n  16  2.73E-03  2.67E-01  6.84E-02  1.84E-02  5.43E+01  0.00  1.00 4\n  17  1.50E-04  2.89E-01  3.24E-02  2.15E-02  4.66E+01  0.00  1.00 4\n  18  9.70E-03  7.00E-01  7.45E-02  9.21E-02  1.09E+01  0.00  1.00 4\n  19  7.56E-01  3.87E+00  2.13E+00  2.95E-01  3.39E+00  0.00  1.00 4\n  20  2.30E-01  2.24E+00  8.48E-01  2.20E-01  4.54E+00  0.00  1.00 4\n  21  3.17E-02  6.93E-01  2.02E-01  6.20E-02  1.61E+01  0.00  1.00 4\n  22  1.63E-01  1.90E+00  8.13E-01  1.70E-01  5.88E+00  0.00  1.00 4\n  23  4.36E-02  1.85E+00  4.34E-01  1.65E-01  6.07E+00  0.00  1.00 4\n  24  1.18E-02  1.33E+00  2.02E-01  1.24E-01  8.08E+00  0.00  1.00 4\n  25  9.56E-01  5.16E+00  2.73E+00  4.50E-01  2.22E+00  0.00  1.00 4\n  26  2.13E-01  3.76E+00  1.23E+00  3.89E-01  2.57E+00  0.00  1.00 4\n  27  1.08E-03  1.62E-01  3.44E-02  1.03E-02  9.67E+01  0.00  1.00 4\n  28  4.15E-05  1.36E-01  1.35E-02  9.43E-03  1.06E+02  0.00  1.00 4\n  29  2.98E-03  3.97E-01  3.29E-02  5.36E-02  1.87E+01  0.00  1.00 4\n  30  4.09E-01  2.15E+00  1.13E+00  1.66E-01  6.04E+00  0.00  1.00 4\n  31  8.77E-02  1.12E+00  3.97E-01  1.16E-01  8.62E+00  0.00  1.00 4\n  32  2.00E-05  1.76E-02  1.42E-03  1.36E-03  7.35E+02  0.00  1.00 4\n  33  5.27E-06  4.46E-02  1.71E-03  4.26E-03  2.35E+02  0.00  1.00 4\n  34  8.83E-07  1.21E-02  4.19E-04  1.52E-03  6.60E+02  0.00  1.00 4\n  35  1.27E+00  8.93E+00  4.26E+00  5.94E-01  1.68E+00  0.00  1.00 4\n  36  4.30E+00  2.47E+01  1.43E+01  1.97E+00  5.08E-01  0.00  1.00 4\n  37  2.97E+00  2.58E+01  1.18E+01  2.36E+00  4.23E-01  0.00  1.00 4\n  38  4.87E-01  6.92E+00  2.94E+00  5.04E-01  1.98E+00  0.00  1.00 4\n  39  4.73E+00  2.48E+01  1.42E+01  1.97E+00  5.07E-01  0.00  1.00 4\n  40  2.79E+00  2.29E+01  1.03E+01  2.05E+00  4.87E-01  0.00  1.00 4\n  41  5.20E-01  3.06E+00  1.19E+00  2.26E-01  4.43E+00  0.00  1.00 4\n  42  1.07E+00  7.23E+00  3.99E+00  5.81E-01  1.72E+00  0.00  1.00 4\n  43  8.46E-01  7.53E+00  3.40E+00  7.11E-01  1.41E+00  0.00  1.00 4\n  44  7.08E-02  1.30E+00  3.18E-01  1.36E-01  7.34E+00  0.00  1.00 4\n  45  1.37E+00  6.40E+00  3.75E+00  5.02E-01  1.99E+00  0.00  1.00 4\n  46  6.40E-01  4.72E+00  1.99E+00  4.28E-01  2.34E+00  0.00  1.00 4\n  47  8.65E-01  6.12E+00  2.74E+00  4.06E-01  2.47E+00  0.00  1.00 4\n  48  2.53E+00  1.58E+01  8.79E+00  1.28E+00  7.81E-01  0.00  1.00 4\n  49  1.57E+00  1.61E+01  6.94E+00  1.58E+00  6.35E-01  0.00  1.00 4\n  50  2.45E-01  4.57E+00  1.78E+00  3.33E-01  3.00E+00  0.00  1.00 4\n  51  2.84E+00  1.57E+01  8.71E+00  1.28E+00  7.82E-01  0.00  1.00 4\n  52  1.48E+00  1.41E+01  5.96E+00  1.34E+00  7.46E-01  0.00  1.00 4\n  53  2.95E-01  2.16E+00  7.69E-01  1.64E-01  6.08E+00  0.00  1.00 4\n  54  6.12E-01  4.74E+00  2.44E+00  3.84E-01  2.61E+00  0.00  1.00 4\n  55  4.30E-01  4.73E+00  2.01E+00  4.76E-01  2.10E+00  0.00  1.00 4\n  56  3.34E-02  8.33E-01  1.73E-01  8.80E-02  1.14E+01  0.00  1.00 4\n  57  8.27E-01  3.95E+00  2.25E+00  3.13E-01  3.20E+00  0.00  1.00 4\n  58  3.12E-01  2.77E+00  1.11E+00  2.63E-01  3.80E+00  0.00  1.00 4\n  59  2.66E-02  5.68E-01  2.09E-01  4.91E-02  2.04E+01  0.00  1.00 4\n  60  7.25E-02  1.10E+00  4.58E-01  1.03E-01  9.67E+00  0.00  1.00 4\n  61  5.93E-03  1.25E+00  2.45E-01  1.10E-01  9.09E+00  0.00  1.00 4\n  62  3.60E-03  3.91E-01  8.91E-02  3.19E-02  3.14E+01  0.00  1.00 4\n  63  7.25E-02  1.09E+00  4.46E-01  1.02E-01  9.84E+00  0.00  1.00 4\n  64  5.47E-03  9.86E-01  1.95E-01  8.68E-02  1.15E+01  0.00  1.00 4\n  65  1.74E-04  5.69E-02  3.93E-03  6.00E-03  1.67E+02  0.00  1.00 4\n  66  2.10E-02  2.27E-01  9.55E-02  2.06E-02  4.86E+01  0.00  1.00 4\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 0\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** SETUP: RANDOM NUMBER GENERATOR ********************************************\n\nRandom number generator seed: 3\nSeed for rank 0: 3\nSeed for rank 1: 2365658986\nSeed for rank 2: 303761048\nSeed for rank 3: 3041471737\nSeed for rank 4: 3607553667\nSeed for rank 5: 1249426360\nSeed for rank 6: 521102280\nSeed for rank 7: 2193987840\nSeed for rank 8: 2445173525\nSeed for rank 9: 3835177981\nSeed for rank 10: 1877166739\nSeed for rank 11: 3849549514\nSeed for rank 12: 80522091\nSeed for rank 13: 539384825\nSeed for rank 14: 174507689\nSeed for rank 15: 890101386\nSeed for global RNG: 1064672149\n*******************************************************************************\n\n*** STRUCTURE DISTRIBUTION ****************************************************\n\nReading configurations from data file: input.data.\nTotal number of structures: 3965\nNumber of structures per processor: 247 (3) or 248 (13)\nDistributed 3965 structures, 118368544 bytes (112.89 MiB) transferred.\nNumber of local structures: 247\n*******************************************************************************\n\n*** DEFINE TRAINING/TEST SETS *************************************************\n\nDesired test set ratio      : 0.100000\nTotal number of energies    : 3965\nNumber of training energies : 3578\nNumber of test     energies : 387\nNumber of training forces   : 1545696\nNumber of test     forces   : 167184\nActual test set fraction    : 0.097604\n*******************************************************************************\n\n*** WRITE TRAINING/TEST SETS **************************************************\n\nWriting training/test set to files:\n - train.data\n - test.data\n*******************************************************************************\n\n*** WEIGHT INITIALIZATION *****************************************************\n\nInitial weights selected randomly in interval [-1.000000, 1.000000).\nWeights modified accoring to Glorot Bengio scheme.\nBiases set to zero.\n*******************************************************************************\n\n*** SETUP: TRAINING ***********************************************************\n\nForces will be used for training.\nForce update weight:   1.00E+01\nWeight update via Kalman filter selected: updaterType::UT_KALMANFILTER (1)\nMulti-stream Kalman filter training with non-blocking communication selected: ParallelMode::PM_MSEKFNB (2)\nNumber of streams       : 16\nStream of this processor: 0\nCombined updater for all elements selected: UpdateStrategy::US_COMBINED (0)\nNumber of weight updaters    : 1\nTotal fit parameters         : 4852\nSelection mode starting with epoch 0:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 0.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\nSelection mode starting with epoch 10:\nUpdate candidates selected according to error: SelectionMode::SM_SORT (1)\nSelection mode starting with epoch 15:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 0.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\n-------------------------------------------------------------------------------\nSymmetry function memory is reused (HIGH MEMORY USAGE!).\nTraining will be stopped after 40 epochs.\nEnergy comparison will be written every 1 epochs.\nForce comparison will be written every 5 epochs.\nWeights will be written every 1 epochs.\nNeuron statistics will be written every 5 epochs.\nTraining log with update information will be written to: train-log.out.\n-------------------------------------------------------------------------------\nFraction of energies used per epoch:    1.0000\nFraction of forces used per epoch  :    0.0232\nProjected energy updates per epoch :     224 (  9.1%)\nProjected forces updates per epoch :    2236 ( 90.9%)\nTotal projected updates per epoch  :    2460\nMulti-stream training uses 16 energies/forces per weight update.\nqtau is divided by number of projected updates per epoch.\netatau is divided by number of projected updates per epoch.\n-------------------------------------------------------------------------------\nCombined weight updater:\n-------------------------------------------------------------------------------\nKalmanType::KT_STANDARD (0)\nsizeState       = 4852\nsizeObservation = 16\nepsilon         =   1.0000E-02\nq0              =   1.0000E-02\nqtau            =   9.3575E-04\nqmin            =   1.0000E-06\neta0            =   1.0000E-02\netatau          =   9.3575E-04\netamax          =   1.0000E+00\nKalmanParallel::KP_NBCOMM (1)\nOpenMP threads used: 1\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** CALCULATE NEIGHBOR LISTS **************************************************\n\nCalculating neighbor lists for all structures.\nCutoff radius for neighbor lists: 36.826159\n*******************************************************************************\n\n*** TRAINING LOOP *************************************************************\n\nThe training loop output covers different RMSEs, update and\ntiming information. The following quantities are organized\naccording to the matrix scheme below:\n-------------------------------------------------------------------\nep ............ Epoch.\nEtrain_phys ... RMSE of training energies per atom (p. u.).\nEtest_phys .... RMSE of test     energies per atom (p. u.).\nEtrain_int .... RMSE of training energies per atom (i. u.).\nEtest_int ..... RMSE of test     energies per atom (i. u.).\nFtrain_phys ... RMSE of training forces (p. u.).\nFtest_phys .... RMSE of test     forces (p. u.).\nFtrain_int .... RMSE of training forces (i. u.).\nFtest_int ..... RMSE of test     forces (i. u.).\nE_count ....... Number of energy updates.\nF_count ....... Number of force  updates.\ncount ......... Total number of updates.\nt_train ....... Time for training (seconds).\nt_rmse ........ Time for RMSE calculation (seconds).\nt_epoch ....... Total time for this epoch (seconds).\nt_tot ......... Total time for all epochs (seconds).\nAbbreviations:\n  p. u. = physical units.\n  i. u. = internal units.\nNote: RMSEs in internal units (columns 5 + 6) are only present \n      if data set normalization is used.\n-------------------------------------------------------------------\n     1    2             3             4             5             6\nenergy   ep   Etrain_phys    Etest_phys    Etrain_int     Etest_int\nforces   ep   Ftrain_phys    Ftest_phys    Ftrain_int     Ftest_int\nupdate   ep       E_count       F_count         count\ntiming   ep       t_train        t_rmse       t_epoch         t_tot\n-------------------------------------------------------------------\nENERGY    0   1.91455E+00   1.85460E+00   1.41468E+01   1.37038E+01\nFORCES    0   3.95765E+00   3.81821E+00   4.76457E+00   4.59669E+00\nTIMING    0          0.00         36.72         36.84         36.84\n------\nENERGY    1   4.89186E-03   4.44070E-03   3.61464E-02   3.28127E-02\nFORCES    1   9.00338E-02   7.98956E-02   1.08390E-01   9.61853E-02\nUPDATE    1           223          2198          2421\nTIMING    1        591.73          2.88        594.74        631.57\n------\nENERGY    2   8.14646E-03   7.83106E-03   6.01949E-02   5.78643E-02\nFORCES    2   8.33764E-02   7.53830E-02   1.00376E-01   9.07526E-02\nUPDATE    2           223          2205          2428\nTIMING    2        581.29          2.88        584.28       1215.86\n------\nENERGY    3   1.46929E-03   1.41092E-03   1.08567E-02   1.04254E-02\nFORCES    3   7.14048E-02   6.44540E-02   8.59633E-02   7.75953E-02\nUPDATE    3           223          2304          2527\nTIMING    3        606.13          2.87        609.11       1824.97\n------\nENERGY    4   1.19764E-03   1.16880E-03   8.84947E-03   8.63635E-03\nFORCES    4   6.50925E-02   5.92062E-02   7.83639E-02   7.12775E-02\nUPDATE    4           223          2263          2486\nTIMING    4        594.00          2.86        596.98       2421.95\n------\nENERGY    5   3.46244E-03   3.20340E-03   2.55843E-02   2.36702E-02\nFORCES    5   6.32945E-02   5.82054E-02   7.61994E-02   7.00727E-02\nUPDATE    5           223          2168          2391\nTIMING    5        569.04          3.66        572.82       2994.77\n------\nENERGY    6   1.35889E-03   1.30765E-03   1.00410E-02   9.66235E-03\nFORCES    6   6.01682E-02   5.59752E-02   7.24357E-02   6.73878E-02\nUPDATE    6           223          2222          2445\nTIMING    6        582.19          2.88        585.18       3579.95\n------\nENERGY    7   1.10132E-03   1.06999E-03   8.13778E-03   7.90622E-03\nFORCES    7   6.09336E-02   5.61479E-02   7.33572E-02   6.75957E-02\nUPDATE    7           223          2220          2443\nTIMING    7        580.57          2.88        583.56       4163.52\n------\nENERGY    8   1.32085E-03   1.32122E-03   9.75985E-03   9.76257E-03\nFORCES    8   6.04221E-02   5.57148E-02   7.27413E-02   6.70743E-02\nUPDATE    8           223          2177          2400\nTIMING    8        570.35          2.87        573.33       4736.85\n------\nENERGY    9   1.21040E-03   1.20911E-03   8.94372E-03   8.93418E-03\nFORCES    9   6.07639E-02   5.61795E-02   7.31529E-02   6.76337E-02\nUPDATE    9           223          2219          2442\nTIMING    9        580.68          2.86        583.68       5320.52\n------\nINFO   Switching selection mode to SM_SORT (1).\nENERGY   10   1.58579E-03   1.73841E-03   1.17175E-02   1.28453E-02\nFORCES   10   6.52223E-02   6.36152E-02   7.85202E-02   7.65855E-02\nUPDATE   10           223          2275          2498\nTIMING   10        540.55          3.95        544.63       5865.15\n------\nENERGY   11   1.71933E-03   1.52765E-03   1.27043E-02   1.12880E-02\nFORCES   11   6.73072E-02   6.52751E-02   8.10303E-02   7.85838E-02\nUPDATE   11           223          2227          2450\nTIMING   11        530.01          3.05        533.20       6398.36\n------\nENERGY   12   1.91272E-03   2.18165E-03   1.41332E-02   1.61204E-02\nFORCES   12   7.01522E-02   6.84824E-02   8.44553E-02   8.24450E-02\nUPDATE   12           223          2267          2490\nTIMING   12        539.23          3.06        542.42       6940.78\n------\nENERGY   13   2.44192E-03   2.27489E-03   1.80435E-02   1.68094E-02\nFORCES   13   6.86417E-02   6.70474E-02   8.26368E-02   8.07175E-02\nUPDATE   13           223          2294          2517\nTIMING   13        545.08          3.01        548.22       7489.00\n------\nENERGY   14   2.26249E-03   2.34073E-03   1.67177E-02   1.72959E-02\nFORCES   14   6.90512E-02   6.75645E-02   8.31298E-02   8.13399E-02\nUPDATE   14           223          2288          2511\nTIMING   14        543.79          3.02        546.93       8035.93\n------\nINFO   Switching selection mode to SM_THRESHOLD (2).\nENERGY   15   1.06025E-03   1.07406E-03   7.83427E-03   7.93633E-03\nFORCES   15   5.73058E-02   5.50161E-02   6.89896E-02   6.62331E-02\nUPDATE   15           223          2238          2461\nTIMING   15        587.56          3.80        591.48       8627.41\n------\nENERGY   16   1.37488E-03   1.35568E-03   1.01591E-02   1.00172E-02\nFORCES   16   5.58823E-02   5.42190E-02   6.72759E-02   6.52735E-02\nUPDATE   16           223          2143          2366\nTIMING   16        560.83          2.88        563.83       9191.23\n------\nENERGY   17   1.27424E-03   1.31414E-03   9.41548E-03   9.71029E-03\nFORCES   17   5.58550E-02   5.41179E-02   6.72430E-02   6.51518E-02\nUPDATE   17           223          2203          2426\nTIMING   17        575.49          2.91        578.52       9769.76\n------\nENERGY   18   1.28910E-03   1.30698E-03   9.52530E-03   9.65742E-03\nFORCES   18   5.56228E-02   5.38312E-02   6.69636E-02   6.48066E-02\nUPDATE   18           223          2200          2423\nTIMING   18        574.57          2.86        577.55      10347.30\n------\nENERGY   19   1.12363E-03   1.14564E-03   8.30256E-03   8.46527E-03\nFORCES   19   5.62287E-02   5.43167E-02   6.76930E-02   6.53912E-02\nUPDATE   19           223          2220          2443\nTIMING   19        578.92          2.92        581.96      10929.26\n------\nENERGY   20   1.47923E-03   1.47152E-03   1.09301E-02   1.08732E-02\nFORCES   20   5.54920E-02   5.36308E-02   6.68061E-02   6.45654E-02\nUPDATE   20           223          2273          2496\nTIMING   20        591.90          3.68        595.70      11524.96\n------\nENERGY   21   1.11350E-03   1.16066E-03   8.22774E-03   8.57618E-03\nFORCES   21   5.66581E-02   5.41310E-02   6.82100E-02   6.51675E-02\nUPDATE   21           223          2273          2496\nTIMING   21        592.28          2.89        595.29      12120.25\n------\nENERGY   22   1.12267E-03   1.14775E-03   8.29551E-03   8.48081E-03\nFORCES   22   5.58592E-02   5.37209E-02   6.72481E-02   6.46739E-02\nUPDATE   22           223          2249          2472\nTIMING   22        586.16          2.92        589.20      12709.45\n------\nENERGY   23   1.26418E-03   1.27163E-03   9.34117E-03   9.39615E-03\nFORCES   23   5.56921E-02   5.34196E-02   6.70469E-02   6.43111E-02\nUPDATE   23           223          2228          2451\nTIMING   23        581.39          2.87        584.38      13293.83\n------\nENERGY   24   1.25106E-03   1.25941E-03   9.24418E-03   9.30589E-03\nFORCES   24   5.54962E-02   5.34614E-02   6.68111E-02   6.43615E-02\nUPDATE   24           223          2237          2460\nTIMING   24        583.31          2.99        586.42      13880.25\n------\nENERGY   25   1.31547E-03   1.31167E-03   9.72012E-03   9.69202E-03\nFORCES   25   5.55124E-02   5.35109E-02   6.68307E-02   6.44210E-02\nUPDATE   25           223          2204          2427\nTIMING   25        574.94          3.69        578.74      14458.99\n------\nENERGY   26   1.05830E-03   1.07179E-03   7.81984E-03   7.91958E-03\nFORCES   26   5.53964E-02   5.33895E-02   6.66909E-02   6.42749E-02\nUPDATE   26           223          2235          2458\nTIMING   26        583.34          2.92        586.38      15045.38\n------\nENERGY   27   1.06478E-03   1.07289E-03   7.86772E-03   7.92768E-03\nFORCES   27   5.57830E-02   5.35759E-02   6.71564E-02   6.44993E-02\nUPDATE   27           223          2185          2408\nTIMING   27        571.02          2.91        574.05      15619.42\n------\nENERGY   28   1.11424E-03   1.15456E-03   8.23318E-03   8.53116E-03\nFORCES   28   5.61240E-02   5.38066E-02   6.75669E-02   6.47770E-02\nUPDATE   28           223          2226          2449\nTIMING   28        580.99          2.92        584.02      16203.45\n------\nENERGY   29   1.19805E-03   1.25617E-03   8.85250E-03   9.28192E-03\nFORCES   29   5.56368E-02   5.33399E-02   6.69803E-02   6.42151E-02\nUPDATE   29           223          2177          2400\nTIMING   29        569.07          2.93        572.12      16775.57\n------\nENERGY   30   1.32401E-03   1.23619E-03   9.78320E-03   9.13429E-03\nFORCES   30   5.51757E-02   5.33361E-02   6.64253E-02   6.42106E-02\nUPDATE   30           223          2250          2473\nTIMING   30        586.74          3.70        590.56      17366.13\n------\nENERGY   31   1.21832E-03   1.31752E-03   9.00229E-03   9.73525E-03\nFORCES   31   5.54089E-02   5.34993E-02   6.67060E-02   6.44070E-02\nUPDATE   31           223          2223          2446\nTIMING   31        579.31          2.92        582.35      17948.48\n------\n"
  },
  {
    "path": "examples/potentials/Cu2S_PBE/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   9.1739161189824411E-08   7.0593095050533450E-01   2.2372649929284196E-02   9.6379208796011293E-02\n         1          2   2.6433999906765265E-01   2.4749666370750676E+00   1.0378805142792313E+00   1.9413782463770093E-01\n         1          3   1.5504686427401054E-05   1.4168627312588329E+00   5.5254915214857578E-02   2.1495058826125538E-01\n         1          4   1.4086411910634238E+00   4.7388215758712082E+00   3.1031877925923803E+00   3.5864448236496921E-01\n         1          5   9.8043626772015909E-04   1.9535901883323099E+00   1.1429456309160095E-01   2.2901461288065855E-01\n         1          6   2.2158364445227399E+00   6.0748308460582043E+00   3.8835182764170546E+00   3.9299243538518969E-01\n         1          7   1.0255080523534783E+00   5.1401074554660049E+00   2.5810215644603796E+00   4.3835591238870431E-01\n         1          8   4.8489829707261999E-03   3.9129781874325281E-01   4.7557455423079396E-02   2.7778419734655713E-02\n         1          9   9.3223803365223998E-02   2.8346930075434797E+00   6.0185719975366336E-01   3.1949957606875956E-01\n         1         10   6.7206749586119430E-01   4.4876923880381465E+00   2.1991872165248538E+00   4.1504796440380803E-01\n         1         11   2.2128378766968923E-02   8.6593017344520318E-01   1.4060436434125115E-01   7.5838421599526348E-02\n         1         12   8.4205124330445313E-01   7.0656885702864862E+00   2.9013712601439368E+00   7.3052821449417049E-01\n         1         13   1.4518778507164800E+00   9.6462711741708382E+00   4.3715329035264965E+00   8.3811671947643118E-01\n         1         14   2.4300884834352513E-06   5.3039215356450418E-02   2.8067394350178213E-04   1.6541693025921896E-03\n         1         15   4.3805855934107564E-04   3.3431366727997386E-01   1.5056637491023487E-02   3.6381498406602590E-02\n         1         16   1.8742403996648012E-02   5.3094282134884740E-01   1.9287359264197504E-01   5.3785992354357007E-02\n         1         17   5.6391705067135155E-03   2.7103176024192799E-01   3.6199336036120536E-02   2.2235092628611220E-02\n         1         18   5.8157340520125522E-01   3.0394483797974066E+00   1.5432926655352674E+00   2.9013849228704902E-01\n         1         19   3.5474335876025032E-01   2.8914948266501281E+00   1.2453633098426364E+00   2.6070492382053573E-01\n         1         20   1.3050150224953865E-03   2.0977615521049353E-01   1.6466279986318652E-02   1.6175233794254219E-02\n         1         21   3.3625763520090814E-02   1.6019727512861448E+00   2.6707302954572526E-01   1.9158906783856428E-01\n         1         22   3.5314748293148263E-01   2.5968432133168928E+00   1.2041087980295160E+00   2.3880745648555143E-01\n         1         23   5.6279184570511148E-03   4.8263719913200909E-01   4.8674878532957294E-02   4.5579012837321450E-02\n         1         24   3.5640890668898983E-01   3.9354254479681789E+00   1.3506519169134916E+00   4.3100694380807969E-01\n         1         25   7.1435545388184229E-01   5.4083380133399706E+00   2.3405335217844168E+00   4.7481787957091687E-01\n         1         26   6.0302894280955782E-07   2.4282702757490063E-02   1.0392381208153868E-04   6.9514343858439293E-04\n         1         27   1.4152015883516988E-04   1.8793440136817721E-01   6.7319944252965166E-03   1.8860146728064606E-02\n         1         28   7.6669273315039489E-03   2.8853650966579203E-01   9.6832241039761832E-02   2.8591400835791262E-02\n         1         29   1.4586287100215936E-03   1.2827520308122028E-01   1.2535333774723276E-02   1.2196652689168296E-02\n         1         30   2.4306078779227119E-01   1.5771292876622454E+00   7.3118666045976355E-01   1.6033491927751306E-01\n         1         31   1.5700215118676836E-01   1.4950427209078341E+00   6.2168623298528469E-01   1.3878720233016123E-01\n         1         32   8.0322135442977674E-08   9.1020506427165644E-03   1.1758299063219979E-04   7.2850621729108440E-04\n         1         33   3.8387499554503460E-05   4.6879099417593433E-02   2.2899299020297070E-03   6.3507919696978174E-03\n         1         34   2.5111603817039843E-07   2.6638155845094137E-02   3.5204871838944324E-04   2.1803344919789219E-03\n         1         35   7.8176366916082938E-04   1.2144199943350505E-01   1.0237823308897595E-02   1.5551953673898984E-02\n         1         36   6.0784771853405629E-03   1.5177813800129991E-01   4.5342256644197804E-02   1.4422755174681633E-02\n         1         37   6.5208235096380454E-08   6.8957085587219831E-03   8.4477914517405974E-05   5.1826403434160535E-04\n         1         38   5.1003186367566016E-04   3.3817704100212627E-02   5.0495259674331701E-03   4.2413701977289924E-03\n         1         39   3.0092380409832575E-01   3.9241027015819827E+00   1.6245850308330121E+00   3.6115017167195557E-01\n         1         40   2.9205060411645536E+00   2.0972699454192377E+01   1.0685030237788666E+01   1.8434608066664662E+00\n         1         41   5.8304225749625562E+00   3.3157582599900756E+01   1.6937338463410185E+01   2.8416990087236536E+00\n         1         42   2.8963706388516774E-01   3.4220973094358569E+00   1.3527222233246401E+00   2.9841578592458634E-01\n         1         43   3.3240856510350132E+00   1.9977206504626281E+01   1.0533032366441756E+01   1.8362183066460305E+00\n         1         44   5.5968160844972745E+00   2.9479500954936675E+01   1.4663357897716818E+01   2.4340402007751933E+00\n         1         45   7.3194532436105672E-02   1.4240027432637063E+00   4.6184059564430718E-01   1.0603619804309938E-01\n         1         46   7.4351404260172327E-01   6.1601360099088307E+00   3.0926623459215312E+00   5.2746971733324144E-01\n         1         47   1.0304047665725904E+00   9.5490875529313932E+00   4.6615470051220029E+00   8.8228607777747381E-01\n         1         48   5.3439780036913555E-02   6.0792049084128386E-01   2.0133541277710790E-01   4.7497199912796259E-02\n         1         49   1.0984946263275692E+00   5.3381605458179147E+00   2.9222626179881503E+00   4.9078113758325748E-01\n         1         50   9.3741001607568142E-01   6.0472356274080674E+00   2.8114797251218855E+00   5.0873676433244819E-01\n         1         51   1.1424085007079182E-01   2.3139492223359586E+00   7.5719953168832033E-01   2.0833570661709583E-01\n         1         52   1.4315113742496002E+00   1.3300925195398728E+01   5.8838374866614309E+00   1.2171600869775945E+00\n         1         53   3.5503714858105737E+00   2.1312715022502385E+01   1.0871674742056101E+01   1.8799426423890726E+00\n         1         54   1.0963309213378970E-01   2.0788696656585590E+00   6.3126459151902947E-01   1.7541529953806104E-01\n         1         55   1.6510272306266744E+00   1.2357046870783602E+01   5.7724472752012481E+00   1.1927743223366301E+00\n         1         56   3.3307522004182251E+00   1.8663597697385917E+01   9.2207406968320633E+00   1.5761279490996694E+00\n         1         57   2.7455727216146104E-02   9.1674320906634155E-01   2.1461170716720621E-01   6.1714021121502906E-02\n         1         58   3.6192386693953038E-01   3.8875893126984216E+00   1.7092032560335464E+00   3.4843371038350474E-01\n         1         59   5.6557210052590146E-01   6.1563972117346957E+00   2.9617726398537609E+00   5.9044611830216798E-01\n         1         60   2.0196364035104716E-02   3.3469617649847838E-01   9.3035775655912298E-02   2.7640180745065839E-02\n         1         61   5.5357670454431462E-01   3.1907980705952856E+00   1.5901399654465433E+00   3.0513520444755149E-01\n         1         62   5.3781344801473907E-01   3.6339755326587713E+00   1.6575261374157455E+00   3.1383714619102349E-01\n         1         63   9.6664268597268675E-05   1.4867672619417913E-01   4.3177785208556420E-03   8.2707901241799234E-03\n         1         64   1.2006437712525238E-02   1.1332481089585240E+00   1.2838035367153358E-01   1.3388538744183132E-01\n         1         65   2.0772479772511018E-01   1.8626169502984133E+00   8.2255201121385824E-01   1.7849382645365078E-01\n         1         66   8.7907438908811975E-05   1.2622839046469150E-01   4.4000149614673457E-03   1.1827043706432264E-02\n         1         67   1.3369106385547676E-02   8.7813896596785235E-01   1.1827747851010054E-01   1.1347348778532439E-01\n         1         68   1.7657303404092337E-01   1.4295433698727396E+00   6.2121356605669209E-01   1.2933064669650537E-01\n         1         69   2.8597998667575309E-03   3.7304172172637867E-01   3.7665097851475426E-02   3.7208167402427196E-02\n         1         70   1.5902143209986809E-05   2.6009225424800504E-02   7.2450937404019229E-04   2.4859888979869879E-03\n         1         71   4.7171431923273572E-03   1.6025670770457742E-01   2.8821358718588475E-02   1.9416774232856850E-02\n         1         72   1.5331295649388408E-02   1.9310943777686740E-01   6.9677412943044442E-02   1.7784064753732315E-02\n         2          1   2.4721472942648627E-02   1.5073065774351924E+00   5.1894025713961534E-01   1.2292746613848948E-01\n         2          2   2.4966843476303169E-01   2.6917832996745195E+00   1.5515938962961904E+00   2.2894178892035891E-01\n         2          3   1.8582961795319244E-03   3.8171243121869747E+00   1.1221679663414206E+00   3.9926224172528085E-01\n         2          4   6.9308990079045429E-01   3.9421018903882858E+00   1.9417591382085293E+00   2.7982355416028953E-01\n         2          5   5.2213352864915873E-02   5.9786240694290029E+00   2.7894744649522680E+00   6.8818475947171043E-01\n         2          6   3.4706330958249576E-01   2.8061894414477742E+00   1.2905107822301898E+00   2.5049917129048904E-01\n         2          7   5.6650782795607790E-01   6.0129804050995874E+00   3.4024808580901604E+00   5.3817898895468230E-01\n         2          8   8.2160472578002200E-02   2.1591157175155038E+00   9.5893716661004147E-01   2.2068746057755104E-01\n         2          9   9.7533565633843480E-02   8.0520717520847240E-01   3.9574121682754421E-01   7.2843087896835634E-02\n         2         10   7.5624736998622447E-02   1.2151161903363619E+00   4.2414909548153323E-01   1.1030205700397629E-01\n         2         11   3.8590027688988915E-01   3.4170303616374733E+00   1.5389187655267780E+00   2.9839201545750010E-01\n         2         12   1.2653139464575366E-01   3.3448693047411142E+00   9.0701446886275106E-01   3.0808232807716252E-01\n         2         13   3.5754079396564345E-02   2.3051636092543291E+00   4.5165801949286744E-01   2.0529180913687342E-01\n         2         14   1.7360244301899754E+00   9.1860981352526956E+00   5.0318013545245659E+00   7.7006828863188448E-01\n         2         15   5.6096556948092302E-01   6.9184291400548386E+00   2.5593433032311834E+00   7.0382259666666958E-01\n         2         16   2.7321455653550736E-03   2.6718628880300366E-01   6.8392239083035003E-02   1.8417271845608391E-02\n         2         17   1.4998879259624551E-04   2.8869834404308442E-01   3.2421219256901605E-02   2.1462316150937667E-02\n         2         18   9.6976148378458242E-03   6.9986551977156553E-01   7.4501947267367571E-02   9.2109247490457000E-02\n         2         19   7.5554776729931772E-01   3.8650650491408283E+00   2.1261658860729638E+00   2.9459249679651817E-01\n         2         20   2.2984860438624041E-01   2.2399640197541903E+00   8.4832685420611464E-01   2.2013029667841760E-01\n         2         21   3.1742242534198488E-02   6.9305314098138393E-01   2.0239450285654340E-01   6.2019223320811959E-02\n         2         22   1.6267388613945685E-01   1.8982342788109985E+00   8.1342448996901984E-01   1.7017885772188068E-01\n         2         23   4.3623299253776143E-02   1.8524213261728384E+00   4.3372964228967342E-01   1.6475284995752615E-01\n         2         24   1.1782155855406862E-02   1.3256780035707432E+00   2.0203673375826020E-01   1.2375770385162231E-01\n         2         25   9.5572013219445029E-01   5.1585503300832807E+00   2.7312178298449119E+00   4.5027566865612645E-01\n         2         26   2.1346552007948805E-01   3.7560054368796258E+00   1.2309867059977997E+00   3.8895981570570448E-01\n         2         27   1.0778454975081308E-03   1.6230009416534466E-01   3.4353839552470775E-02   1.0338804556484340E-02\n         2         28   4.1455680376600344E-05   1.3561930079689324E-01   1.3464607540962245E-02   9.4307016558753589E-03\n         2         29   2.9811923400491925E-03   3.9674788724187127E-01   3.2946560522656709E-02   5.3575100644579036E-02\n         2         30   4.0860996892032608E-01   2.1541090596644543E+00   1.1291055145629398E+00   1.6554701558125592E-01\n         2         31   8.7689965003411183E-02   1.1196100344004409E+00   3.9704096379805787E-01   1.1606734505235136E-01\n         2         32   2.0029888316796539E-05   1.7556653440553127E-02   1.4233102888664287E-03   1.3598121443903737E-03\n         2         33   5.2716716179610746E-06   4.4644993845652417E-02   1.7086280138653978E-03   4.2643079956046579E-03\n         2         34   8.8339290835669212E-07   1.2139204575362132E-02   4.1922038284938451E-04   1.5155281653507265E-03\n         2         35   1.2653672947005059E+00   8.9337925904902882E+00   4.2637335795708999E+00   5.9362291906692699E-01\n         2         36   4.3025897744283652E+00   2.4744209023066571E+01   1.4272525712868205E+01   1.9700222663219151E+00\n         2         37   2.9677470818795189E+00   2.5847640450705327E+01   1.1788593731598802E+01   2.3639335745006553E+00\n         2         38   4.8673248345854536E-01   6.9220258514917292E+00   2.9410791137038919E+00   5.0416378898015868E-01\n         2         39   4.7312413761643519E+00   2.4784350068345699E+01   1.4182436900763136E+01   1.9734981280505293E+00\n         2         40   2.7914940844674572E+00   2.2909604188642842E+01   1.0258913931047273E+01   2.0538117984713926E+00\n         2         41   5.1976352609600407E-01   3.0581982698648895E+00   1.1910833091075925E+00   2.2566892125976182E-01\n         2         42   1.0695804209866875E+00   7.2313250376604037E+00   3.9928775708897235E+00   5.8095727320582324E-01\n         2         43   8.4628209088378592E-01   7.5313801441068913E+00   3.3982729265620653E+00   7.1123273080942895E-01\n         2         44   7.0763463381880415E-02   1.2969398476188700E+00   3.1793764328087359E-01   1.3617384576811825E-01\n         2         45   1.3721123798749537E+00   6.3973513973729199E+00   3.7457022157866304E+00   5.0158792550110110E-01\n         2         46   6.3964342968618404E-01   4.7161013997028380E+00   1.9947659320351354E+00   4.2776493844298569E-01\n         2         47   8.6532747970285151E-01   6.1240088873304499E+00   2.7402018484921369E+00   4.0552538612845523E-01\n         2         48   2.5315105294788682E+00   1.5776758660822487E+01   8.7867531123795093E+00   1.2800885070636867E+00\n         2         49   1.5679508239487920E+00   1.6123025100421103E+01   6.9389600266532643E+00   1.5752331036924878E+00\n         2         50   2.4475421880204548E-01   4.5715135037651979E+00   1.7778621079614614E+00   3.3311384228682872E-01\n         2         51   2.8365798870360606E+00   1.5735394223700631E+01   8.7129345829426814E+00   1.2788947945672131E+00\n         2         52   1.4825266957775993E+00   1.4111085036729261E+01   5.9550381055833128E+00   1.3412575984240060E+00\n         2         53   2.9486345514961088E-01   2.1632897998459173E+00   7.6894782290828789E-01   1.6439255789853263E-01\n         2         54   6.1183454216254696E-01   4.7418024842673727E+00   2.4364672738977449E+00   3.8379810845509604E-01\n         2         55   4.2978046698724798E-01   4.7295979558909700E+00   2.0069121315341767E+00   4.7649159304923261E-01\n         2         56   3.3379248097225291E-02   8.3272635081969881E-01   1.7274845946125020E-01   8.7956031429209408E-02\n         2         57   8.2656009161897048E-01   3.9467471262168639E+00   2.2459243943426777E+00   3.1269124051179731E-01\n         2         58   3.1171589063801924E-01   2.7714452296122714E+00   1.1129251102859337E+00   2.6297335909685149E-01\n         2         59   2.6592109568248031E-02   5.6825603390221913E-01   2.0877471778793405E-01   4.9135988886466996E-02\n         2         60   7.2485536842319745E-02   1.1034806181844534E+00   4.5818934497666303E-01   1.0344323974312900E-01\n         2         61   5.9263838221524185E-03   1.2515028539804678E+00   2.4502825958578195E-01   1.1006546541667923E-01\n         2         62   3.5994334696395447E-03   3.9125406849266531E-01   8.9107610428087070E-02   3.1854933024728180E-02\n         2         63   7.2533340578499653E-02   1.0927078443379801E+00   4.4612155612487853E-01   1.0164232620041405E-01\n         2         64   5.4706332551405917E-03   9.8645463183530846E-01   1.9457952454956559E-01   8.6829363320211461E-02\n         2         65   1.7435002600794914E-04   5.6940854477051987E-02   3.9265019004702875E-03   5.9979210203388224E-03\n         2         66   2.1035187678847361E-02   2.2735828246294021E-01   9.5459655622289877E-02   2.0577872261152416E-02\n"
  },
  {
    "path": "examples/potentials/Cu2S_PBE/weights.016.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -3.5529535307974660E+00 a         1     0     1     1     1\n  7.2419212968357530E-02 a         2     0     1     1     2\n  6.6238167719007179E-01 a         3     0     1     1     3\n  1.3187085002852068E+00 a         4     0     1     1     4\n  8.0230438760649514E-01 a         5     0     1     1     5\n  8.3955862269426929E-01 a         6     0     1     1     6\n  6.0886672237242623E-01 a         7     0     1     1     7\n  1.8038521037244075E+00 a         8     0     1     1     8\n -9.4212226737513360E-01 a         9     0     1     1     9\n -5.1556581063883433E-01 a        10     0     1     1    10\n -1.1787308470438386E-01 a        11     0     1     1    11\n  2.7402309255936421E+00 a        12     0     1     1    12\n -1.4988157706430596E+00 a        13     0     1     1    13\n -1.4218948987030877E+00 a        14     0     1     1    14\n -3.1471248905197000E+00 a        15     0     1     1    15\n -2.7242744362012289E-01 a        16     0     1     1    16\n -1.4939110915197420E+00 a        17     0     1     1    17\n -4.5760625854044340E-01 a        18     0     1     1    18\n  1.8320965746572428E+00 a        19     0     1     1    19\n  1.4829292005742705E+00 a        20     0     1     1    20\n -4.7531481220841671E+00 a        21     0     1     1    21\n  6.9284365000837844E-01 a        22     0     1     1    22\n -1.4360334184866708E+00 a        23     0     1     1    23\n -6.9988606086712224E-01 a        24     0     1     1    24\n -2.6821117310359570E+00 a        25     0     1     1    25\n  1.2328185292695659E+00 a        26     0     2     1     1\n  6.8539081540980901E-02 a        27     0     2     1     2\n  1.1312525424757594E-01 a        28     0     2     1     3\n  3.3791299053992763E-01 a        29     0     2     1     4\n  1.3203780104475105E+00 a        30     0     2     1     5\n -1.4531712477250573E+00 a        31     0     2     1     6\n  2.4379072742488564E-01 a        32     0     2     1     7\n  7.2963026955779986E-01 a        33     0     2     1     8\n -1.2591734762557112E+00 a        34     0     2     1     9\n -4.7096176379988147E-01 a        35     0     2     1    10\n  1.1052943930835461E-01 a        36     0     2     1    11\n  1.2282514057948777E+00 a        37     0     2     1    12\n -5.8437787869506075E-01 a        38     0     2     1    13\n  1.4166787422902487E+00 a        39     0     2     1    14\n -1.6938650584717402E-01 a        40     0     2     1    15\n  2.3030826774815769E+00 a        41     0     2     1    16\n -1.4473769335578126E+00 a        42     0     2     1    17\n  4.0195075881174241E-01 a        43     0     2     1    18\n  1.1043558865793792E+00 a        44     0     2     1    19\n -3.4549061205961434E-01 a        45     0     2     1    20\n  8.1879232157423720E-01 a        46     0     2     1    21\n -2.7007345535606064E-01 a        47     0     2     1    22\n -8.2869143511169474E-01 a        48     0     2     1    23\n -2.9469119089022022E-01 a        49     0     2     1    24\n -5.7206441642229700E-01 a        50     0     2     1    25\n  7.7333844542414798E-01 a        51     0     3     1     1\n -2.8005034461966472E+00 a        52     0     3     1     2\n -2.0054154055351620E-01 a        53     0     3     1     3\n -2.3648818664674390E-01 a        54     0     3     1     4\n -6.4064022093719220E-01 a        55     0     3     1     5\n  6.9876341352721461E-01 a        56     0     3     1     6\n  1.2138517429043079E+00 a        57     0     3     1     7\n -1.0872828987358620E+00 a        58     0     3     1     8\n  2.4009903950784475E+00 a        59     0     3     1     9\n -7.1414550990900871E-01 a        60     0     3     1    10\n  4.8262298434516965E-01 a        61     0     3     1    11\n  1.2017235942575036E-01 a        62     0     3     1    12\n -5.0067742187524500E-01 a        63     0     3     1    13\n  1.6682617398315705E-01 a        64     0     3     1    14\n -1.9521789463955752E+00 a        65     0     3     1    15\n  1.3587159322569415E+00 a        66     0     3     1    16\n  1.9824040428450457E-01 a        67     0     3     1    17\n  5.0478176436946609E-01 a        68     0     3     1    18\n  1.7968971934667841E+00 a        69     0     3     1    19\n -2.6819167691107553E+00 a        70     0     3     1    20\n  3.1361294632323173E+00 a        71     0     3     1    21\n -7.2813429885436576E-01 a        72     0     3     1    22\n  7.9662962027149486E-01 a        73     0     3     1    23\n  5.3906067437318705E-01 a        74     0     3     1    24\n  1.8219650246428634E+00 a        75     0     3     1    25\n  5.8927722128305347E-02 a        76     0     4     1     1\n  3.4478358925805858E-01 a        77     0     4     1     2\n  2.1711984340886667E-01 a        78     0     4     1     3\n -7.5943721634464512E-01 a        79     0     4     1     4\n 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-2.9263488552138478E-01 a      1941     1     5     2    16\n  7.4326458357632263E-01 a      1942     1     5     2    17\n  4.2013924569516037E-01 a      1943     1     5     2    18\n -5.8280302654581832E-02 a      1944     1     5     2    19\n -3.2612804852919446E-02 a      1945     1     5     2    20\n  3.0897375192782450E-01 a      1946     1     5     2    21\n -3.4554814584389509E-01 a      1947     1     5     2    22\n  5.6462638020854716E-01 a      1948     1     5     2    23\n -2.2840636874785014E-01 a      1949     1     5     2    24\n -4.9669234553755076E-01 a      1950     1     5     2    25\n  1.1758939649783381E-01 a      1951     1     6     2     1\n  8.6738679928268236E-01 a      1952     1     6     2     2\n -8.2268243221940873E-01 a      1953     1     6     2     3\n -1.7656641024661676E-01 a      1954     1     6     2     4\n -7.3983486152494982E-01 a      1955     1     6     2     5\n  5.9385478664743296E-01 a      1956     1     6     2     6\n -4.2593570872866021E-01 a      1957     1     6     2     7\n -1.9801025124105215E-01 a      1958     1     6     2     8\n -4.6730416799726238E-01 a      1959     1     6     2     9\n  1.8116336463074925E-01 a      1960     1     6     2    10\n -7.5935659696139179E-01 a      1961     1     6     2    11\n -2.7885626460361607E-01 a      1962     1     6     2    12\n  2.2498372487170440E-01 a      1963     1     6     2    13\n -2.6922194278960770E-01 a      1964     1     6     2    14\n  8.2356834198746176E-02 a      1965     1     6     2    15\n -1.9959174200148408E+00 a      1966     1     6     2    16\n -9.1441649022992150E-02 a      1967     1     6     2    17\n -3.2893725936322316E-01 a      1968     1     6     2    18\n  8.4708812890909327E-02 a      1969     1     6     2    19\n -9.8738542155083330E-03 a      1970     1     6     2    20\n -1.5706979176219785E-01 a      1971     1     6     2    21\n -3.3385820430832114E-01 a      1972     1     6     2    22\n -8.1658461786034431E-01 a      1973     1     6     2    23\n  4.2826805041754107E-01 a      1974     1     6     2    24\n  6.7595378736221203E-03 a      1975     1     6     2    25\n -1.4858293771378450E-01 a      1976     1     7     2     1\n -4.8665064878920916E-01 a      1977     1     7     2     2\n  9.3147532658334302E-03 a      1978     1     7     2     3\n  2.2071434698840436E-01 a      1979     1     7     2     4\n -3.1521981986003578E+00 a      1980     1     7     2     5\n  1.4896102615333093E-01 a      1981     1     7     2     6\n  2.0639082326871608E-01 a      1982     1     7     2     7\n  1.4764434422173356E+00 a      1983     1     7     2     8\n -8.5415180586937678E-01 a      1984     1     7     2     9\n  2.0056826451387089E+00 a      1985     1     7     2    10\n -1.6035541337428121E+00 a      1986     1     7     2    11\n -1.0126746741541708E-01 a      1987     1     7     2    12\n  1.0176837892450277E+00 a      1988     1     7     2    13\n  5.8650237148957363E-01 a      1989     1     7     2    14\n  6.8764775335937489E-01 a      1990     1     7     2    15\n -1.6327881928548789E+00 a      1991     1     7     2    16\n -2.6588597247788198E-01 a      1992     1     7     2    17\n  1.9718370666773979E-01 a      1993     1     7     2    18\n  4.3601566297954825E-01 a      1994     1     7     2    19\n -2.7082844396133726E-01 a      1995     1     7     2    20\n  3.2206390922604272E-01 a      1996     1     7     2    21\n  5.0949702830703934E-03 a      1997     1     7     2    22\n -1.3049790188741632E+00 a      1998     1     7     2    23\n  4.2026808266723220E-01 a      1999     1     7     2    24\n -6.3063301866048659E-03 a      2000     1     7     2    25\n -2.6986778384233595E-01 a      2001     1     8     2     1\n  1.0472413049447822E+00 a      2002     1     8     2     2\n  2.1270075261563209E-01 a      2003     1     8     2     3\n  1.0059956884525167E-02 a      2004     1     8     2     4\n -5.6674331507128162E-01 a      2005     1     8     2     5\n -4.1069951508364727E-01 a      2006     1     8     2     6\n -5.7946760577066525E-01 a      2007     1     8     2     7\n -6.9320514952269952E-01 a      2008     1     8     2     8\n -2.6235771311219197E-01 a      2009     1     8     2     9\n -4.9114985182179943E-01 a      2010     1     8     2    10\n -6.4751077129371837E-01 a      2011     1     8     2    11\n  1.6623516048991380E-01 a      2012     1     8     2    12\n -1.3252784721447061E-01 a      2013     1     8     2    13\n  6.3617130518492077E-02 a      2014     1     8     2    14\n -7.9749770183388205E-02 a      2015     1     8     2    15\n  2.6810344620231513E-01 a      2016     1     8     2    16\n -1.0886590179511721E-01 a      2017     1     8     2    17\n -8.5635070249057671E-02 a      2018     1     8     2    18\n -8.5883419432118385E-02 a      2019     1     8     2    19\n  1.4001812857233212E-01 a      2020     1     8     2    20\n  2.4652559241660935E-01 a      2021     1     8     2    21\n -1.1705271450291483E-02 a      2022     1     8     2    22\n  5.1059887324814701E-01 a      2023     1     8     2    23\n -9.2777234250212143E-02 a      2024     1     8     2    24\n -6.6631934340703591E-01 a      2025     1     8     2    25\n  4.4575672600804567E-01 a      2026     1     9     2     1\n -6.7107163032432227E-01 a      2027     1     9     2     2\n -3.0179267369944862E-01 a      2028     1     9     2     3\n -1.3598496288690123E+00 a      2029     1     9     2     4\n -1.4940270248112404E+00 a      2030     1     9     2     5\n -2.2080339138801010E-02 a      2031     1     9     2     6\n -5.7301816910865744E-01 a      2032     1     9     2     7\n -1.0063124051587569E-01 a      2033     1     9     2     8\n -2.3012172042264027E+00 a      2034     1     9     2     9\n  1.0885556179246252E+00 a      2035     1     9     2    10\n -1.1526492907689538E+00 a      2036     1     9     2    11\n  3.9520279659304998E-02 a      2037     1     9     2    12\n  2.7509795088948047E-01 a      2038     1     9     2    13\n -3.2176987618681385E-01 a      2039     1     9     2    14\n  1.2152345255401775E+00 a      2040     1     9     2    15\n  6.7561788359563746E-01 a      2041     1     9     2    16\n  1.2756402711221351E-01 a      2042     1     9     2    17\n  4.2778010903937930E-02 a      2043     1     9     2    18\n  2.2524717454514478E-01 a      2044     1     9     2    19\n -5.9203499543104976E-01 a      2045     1     9     2    20\n  1.9472787318819443E-01 a      2046     1     9     2    21\n  2.6372584248809827E-01 a      2047     1     9     2    22\n -1.2605296128570485E+00 a      2048     1     9     2    23\n -4.2493619774884570E-02 a      2049     1     9     2    24\n -3.2689975704292223E-01 a      2050     1     9     2    25\n -5.0316442252296556E-01 a      2051     1    10     2     1\n -1.2776598471010672E+00 a      2052     1    10     2     2\n  3.2727687173561748E-01 a      2053     1    10     2     3\n -5.2750979806146270E-01 a      2054     1    10     2     4\n -5.2100917223171461E-01 a      2055     1    10     2     5\n  1.0271103871270988E+00 a      2056     1    10     2     6\n -1.3174585043808176E+00 a      2057     1    10     2     7\n  1.7860344423744762E-01 a      2058     1    10     2     8\n -3.1935218220133910E-01 a      2059     1    10     2     9\n  4.0624355231658738E-01 a      2060     1    10     2    10\n -8.4263015301232114E-01 a      2061     1    10     2    11\n -4.1311568727252523E-01 a      2062     1    10     2    12\n -2.0250507836832625E+00 a      2063     1    10     2    13\n -4.9669616476317113E-01 a      2064     1    10     2    14\n  1.4542353491363211E+00 a      2065     1    10     2    15\n -1.0829455537390682E-01 a      2066     1    10     2    16\n  3.0637661429549540E-01 a      2067     1    10     2    17\n  3.9830418172493465E-01 a      2068     1    10     2    18\n -1.6636558535137880E+00 a      2069     1    10     2    19\n  7.0498166711701593E-01 a      2070     1    10     2    20\n -3.8215339196853010E-01 a      2071     1    10     2    21\n -2.9475963780786207E-01 a      2072     1    10     2    22\n  1.2815404826499932E+00 a      2073     1    10     2    23\n  3.7464874577430729E-01 a      2074     1    10     2    24\n  6.7369985980501002E-01 a      2075     1    10     2    25\n  1.4787802212199200E-01 a      2076     1    11     2     1\n  2.3652422194864106E-01 a      2077     1    11     2     2\n -2.9319277439498237E-01 a      2078     1    11     2     3\n  8.1893235515044593E-01 a      2079     1    11     2     4\n -5.4251461750474061E-01 a      2080     1    11     2     5\n -7.9432325051447306E-01 a      2081     1    11     2     6\n  5.6741940214747433E-01 a      2082     1    11     2     7\n -1.9883538594217587E-01 a      2083     1    11     2     8\n  2.4059652163192724E-01 a      2084     1    11     2     9\n  9.0487535694630072E-01 a      2085     1    11     2    10\n  2.1500450010677571E-01 a      2086     1    11     2    11\n -8.8392848708160249E-02 a      2087     1    11     2    12\n  4.8911199216330936E-01 a      2088     1    11     2    13\n  3.8501747509679890E-01 a      2089     1    11     2    14\n  2.0880386832367939E-01 a      2090     1    11     2    15\n -1.2898150999726214E+00 a      2091     1    11     2    16\n -6.7684897098766336E-02 a      2092     1    11     2    17\n -1.3226797298228404E-01 a      2093     1    11     2    18\n -7.0860409533946489E-01 a      2094     1    11     2    19\n  2.0428970671759283E-01 a      2095     1    11     2    20\n  6.1788460934391509E-01 a      2096     1    11     2    21\n -1.5387742244322317E-02 a      2097     1    11     2    22\n -2.9187261106596285E-01 a      2098     1    11     2    23\n -2.7435985561202314E-01 a      2099     1    11     2    24\n -2.9893757922781268E-02 a      2100     1    11     2    25\n  1.4366492019663546E-01 a      2101     1    12     2     1\n -8.3708506447152686E-01 a      2102     1    12     2     2\n  8.4900741982625050E-01 a      2103     1    12     2     3\n -3.1763858239521897E-01 a      2104     1    12     2     4\n -8.5836557564984983E-02 a      2105     1    12     2     5\n  4.8971995238975233E-02 a      2106     1    12     2     6\n -8.6345064469884769E-01 a      2107     1    12     2     7\n -1.8877691890216164E+00 a      2108     1    12     2     8\n  4.7870208924774238E-01 a      2109     1    12     2     9\n -2.6803285718567860E-01 a      2110     1    12     2    10\n -8.3576740507701341E-01 a      2111     1    12     2    11\n -2.0233607775747742E-01 a      2112     1    12     2    12\n -2.0851336604971404E+00 a      2113     1    12     2    13\n  5.5710849793933925E-02 a      2114     1    12     2    14\n -2.5441709390192631E+00 a      2115     1    12     2    15\n  1.1056110845657674E+00 a      2116     1    12     2    16\n  4.1604534414542688E-01 a      2117     1    12     2    17\n -2.4025453894460813E-01 a      2118     1    12     2    18\n -4.8834369066457661E-01 a      2119     1    12     2    19\n  1.2885571052723108E-01 a      2120     1    12     2    20\n -5.4132000309146744E-01 a      2121     1    12     2    21\n -1.7269282812154974E-01 a      2122     1    12     2    22\n -5.8064851629878863E-03 a      2123     1    12     2    23\n -1.4394463497698487E-01 a      2124     1    12     2    24\n -4.2487948203957382E-01 a      2125     1    12     2    25\n  5.8675042735952393E-02 a      2126     1    13     2     1\n  1.7863972211172008E-01 a      2127     1    13     2     2\n  4.5741880103604365E-01 a      2128     1    13     2     3\n  9.1416506499137384E-01 a      2129     1    13     2     4\n -7.3674367315233913E-01 a      2130     1    13     2     5\n -3.0779431852369288E-01 a      2131     1    13     2     6\n -3.2999352842234286E-01 a      2132     1    13     2     7\n -5.4956662968530401E-01 a      2133     1    13     2     8\n -8.2136164243233878E-01 a      2134     1    13     2     9\n  1.2183161209162805E+00 a      2135     1    13     2    10\n -1.2314580021681576E-04 a      2136     1    13     2    11\n -1.0026980899080576E-01 a      2137     1    13     2    12\n -7.5923362473088618E-01 a      2138     1    13     2    13\n  8.7341315448514784E-02 a      2139     1    13     2    14\n  2.5889498070253123E+00 a      2140     1    13     2    15\n  3.2846563407201890E-01 a      2141     1    13     2    16\n  2.4140079639811293E-01 a      2142     1    13     2    17\n  6.6559640464078706E-01 a      2143     1    13     2    18\n -6.0228182791517193E-01 a      2144     1    13     2    19\n  5.0959148190761594E-01 a      2145     1    13     2    20\n -1.8343764259383200E-01 a      2146     1    13     2    21\n -2.0541935684248189E-01 a      2147     1    13     2    22\n  5.2020354314273987E-01 a      2148     1    13     2    23\n  2.8411193388383044E-01 a      2149     1    13     2    24\n  1.5031583886753237E+00 a      2150     1    13     2    25\n -1.5611135743074465E+00 a      2151     1    14     2     1\n -3.2360297425207724E-01 a      2152     1    14     2     2\n -2.8070095488766600E-01 a      2153     1    14     2     3\n -4.2682370987576490E-01 a      2154     1    14     2     4\n -8.0124669652434721E-01 a      2155     1    14     2     5\n  6.0916260028745439E-01 a      2156     1    14     2     6\n -1.3043834885545900E+00 a      2157     1    14     2     7\n -1.1114567839213945E+00 a      2158     1    14     2     8\n -7.6508338871898718E-01 a      2159     1    14     2     9\n  1.7394319780653198E+00 a      2160     1    14     2    10\n  6.1580012015667462E-01 a      2161     1    14     2    11\n -2.1501534971396988E-01 a      2162     1    14     2    12\n  8.1316399521310057E-01 a      2163     1    14     2    13\n -1.2944835426827954E+00 a      2164     1    14     2    14\n  3.6338934043065596E-02 a      2165     1    14     2    15\n -9.7464822438627852E-01 a      2166     1    14     2    16\n -2.4145501724766127E-01 a      2167     1    14     2    17\n -8.8876835360975071E-03 a      2168     1    14     2    18\n -5.8076528324547438E-01 a      2169     1    14     2    19\n -2.0411437917641737E+00 a      2170     1    14     2    20\n -4.2526015090964880E-01 a      2171     1    14     2    21\n  5.9996421373152897E-01 a      2172     1    14     2    22\n -3.6675255943507928E-02 a      2173     1    14     2    23\n  1.3185398858057240E-01 a      2174     1    14     2    24\n -2.0032286135136248E+00 a      2175     1    14     2    25\n  5.1591662327951759E-01 a      2176     1    15     2     1\n -2.5446052702797714E-03 a      2177     1    15     2     2\n -8.1769338860501051E-01 a      2178     1    15     2     3\n -6.8480492422848949E-01 a      2179     1    15     2     4\n  1.6061689254540090E+00 a      2180     1    15     2     5\n -3.6828605283363745E+00 a      2181     1    15     2     6\n -2.6949729107316758E+00 a      2182     1    15     2     7\n -8.7436479908358988E-01 a      2183     1    15     2     8\n -7.2537234627087488E-01 a      2184     1    15     2     9\n  1.7554101736285144E+00 a      2185     1    15     2    10\n -1.5729036376143151E+00 a      2186     1    15     2    11\n -4.7196403406815074E-01 a      2187     1    15     2    12\n  2.4686309706562368E+00 a      2188     1    15     2    13\n -8.1429048034865914E-01 a      2189     1    15     2    14\n  1.2457943097534157E+00 a      2190     1    15     2    15\n -1.8238343315299035E+00 a      2191     1    15     2    16\n -9.1710155695980261E-02 a      2192     1    15     2    17\n -1.7104412957602122E+00 a      2193     1    15     2    18\n  2.7030869802557012E-01 a      2194     1    15     2    19\n -1.7298684033912173E+00 a      2195     1    15     2    20\n -3.1058841915893948E-01 a      2196     1    15     2    21\n  1.8274844624858664E+00 a      2197     1    15     2    22\n -1.3513314668634027E+00 a      2198     1    15     2    23\n -1.1539080164302253E+00 a      2199     1    15     2    24\n  3.7623134982371026E-01 a      2200     1    15     2    25\n  3.8564708777748902E-01 a      2201     1    16     2     1\n -3.7485013341251339E-01 a      2202     1    16     2     2\n  3.0694902381634054E-01 a      2203     1    16     2     3\n -6.3820812530951954E-01 a      2204     1    16     2     4\n  6.1596951581411624E-02 a      2205     1    16     2     5\n  3.1823666483179947E-01 a      2206     1    16     2     6\n -1.7451214484287221E+00 a      2207     1    16     2     7\n  6.6928800449640258E-01 a      2208     1    16     2     8\n -1.1768614713311631E+00 a      2209     1    16     2     9\n -1.2657577834196381E+00 a      2210     1    16     2    10\n -3.0160201061177228E-01 a      2211     1    16     2    11\n -5.3877877406889563E-01 a      2212     1    16     2    12\n -8.6493612190989910E-01 a      2213     1    16     2    13\n -8.8460225776662071E-01 a      2214     1    16     2    14\n  1.9057948312439157E+00 a      2215     1    16     2    15\n -2.7200418390588271E-01 a      2216     1    16     2    16\n  1.9952889394862189E-01 a      2217     1    16     2    17\n  7.9321718120701656E-02 a      2218     1    16     2    18\n -7.5240700188026213E-02 a      2219     1    16     2    19\n  3.5188674964451849E-01 a      2220     1    16     2    20\n  4.4883278162576262E-01 a      2221     1    16     2    21\n  2.4951384292998435E-01 a      2222     1    16     2    22\n  1.6851679055279442E-01 a      2223     1    16     2    23\n -4.8371544786080266E-02 a      2224     1    16     2    24\n  8.1495784381186021E-01 a      2225     1    16     2    25\n -7.7932092504504180E-01 a      2226     1    17     2     1\n  8.4308356300312914E-01 a      2227     1    17     2     2\n  6.2801495977484001E-01 a      2228     1    17     2     3\n -1.6671863188240814E-02 a      2229     1    17     2     4\n  4.9617622666448757E-01 a      2230     1    17     2     5\n  2.8578791610744131E-01 a      2231     1    17     2     6\n  5.0261300134126208E-01 a      2232     1    17     2     7\n  4.2973672296612153E-01 a      2233     1    17     2     8\n  2.0605776991439645E-02 a      2234     1    17     2     9\n  3.1505912130803543E-01 a      2235     1    17     2    10\n -4.8141644197770223E-01 a      2236     1    17     2    11\n  6.5147019223382929E-01 a      2237     1    17     2    12\n  1.3223922139341173E-02 a      2238     1    17     2    13\n  1.3552951191767832E+00 a      2239     1    17     2    14\n -2.7683725661405684E-01 a      2240     1    17     2    15\n -1.4553982661789062E+00 a      2241     1    17     2    16\n  1.3934738472514663E-01 a      2242     1    17     2    17\n  6.5662014192387624E-02 a      2243     1    17     2    18\n  3.9097955051468730E-01 a      2244     1    17     2    19\n -1.5329149954135943E+00 a      2245     1    17     2    20\n -4.9182889227766408E-01 a      2246     1    17     2    21\n -8.4101247787721850E-02 a      2247     1    17     2    22\n  1.1079957740309260E-01 a      2248     1    17     2    23\n  1.2653734338244162E+00 a      2249     1    17     2    24\n  5.1889782109670390E-01 a      2250     1    17     2    25\n -3.5701303156391490E-01 a      2251     1    18     2     1\n -2.3369886700637788E-01 a      2252     1    18     2     2\n  1.8192889993017079E-02 a      2253     1    18     2     3\n -1.9089403601514085E-01 a      2254     1    18     2     4\n -2.2245213004847283E-01 a      2255     1    18     2     5\n -4.1704360216982245E-01 a      2256     1    18     2     6\n -5.9376327509449600E-01 a      2257     1    18     2     7\n  4.7700366121749904E-01 a      2258     1    18     2     8\n -2.4234013871626243E+00 a      2259     1    18     2     9\n -3.4319600817672740E+00 a      2260     1    18     2    10\n  1.4602063702387118E+00 a      2261     1    18     2    11\n -4.8017949262669966E-02 a      2262     1    18     2    12\n -2.5388955532842389E-01 a      2263     1    18     2    13\n -4.4955574787101665E-01 a      2264     1    18     2    14\n -5.9686971656068388E-01 a      2265     1    18     2    15\n  1.5329181413373798E+00 a      2266     1    18     2    16\n -1.7745540088419492E-01 a      2267     1    18     2    17\n -6.8356066126928808E-02 a      2268     1    18     2    18\n -5.7868883010994010E-01 a      2269     1    18     2    19\n -2.4958945618463482E-01 a      2270     1    18     2    20\n -8.8915588088891362E-01 a      2271     1    18     2    21\n  4.6796145878627105E-01 a      2272     1    18     2    22\n  3.7239838802427244E-01 a      2273     1    18     2    23\n  5.8825012698306467E-01 a      2274     1    18     2    24\n -2.5213870537746796E-01 a      2275     1    18     2    25\n -4.0945577957805229E-01 a      2276     1    19     2     1\n -6.3926426566269479E-01 a      2277     1    19     2     2\n -2.4803832950792159E-03 a      2278     1    19     2     3\n -9.5504254863097604E-01 a      2279     1    19     2     4\n  2.4385416954208063E-02 a      2280     1    19     2     5\n  1.8105456314263782E-01 a      2281     1    19     2     6\n -1.3959803913453275E+00 a      2282     1    19     2     7\n -1.4647235163838312E+00 a      2283     1    19     2     8\n -8.0598524282205181E-02 a      2284     1    19     2     9\n -6.8890711362406043E-01 a      2285     1    19     2    10\n  7.4049128505740025E-01 a      2286     1    19     2    11\n -1.8107652733146301E-01 a      2287     1    19     2    12\n  1.1180459617056233E-01 a      2288     1    19     2    13\n -9.7523288912192785E-01 a      2289     1    19     2    14\n  5.4031707452495070E-01 a      2290     1    19     2    15\n -8.6865875639635415E-01 a      2291     1    19     2    16\n -1.1736299949303194E-03 a      2292     1    19     2    17\n -2.1796832363882152E-01 a      2293     1    19     2    18\n -2.0197745129587785E-01 a      2294     1    19     2    19\n -2.0649260039989298E-01 a      2295     1    19     2    20\n -2.5945409305212930E-01 a      2296     1    19     2    21\n -5.3195384264402990E-01 a      2297     1    19     2    22\n  6.1477888542849975E-02 a      2298     1    19     2    23\n -6.9385778198627257E-01 a      2299     1    19     2    24\n  3.3845607119781312E-01 a      2300     1    19     2    25\n  4.0809678373584041E-02 a      2301     1    20     2     1\n  3.2924070883990825E-01 a      2302     1    20     2     2\n -3.9610966191553226E-01 a      2303     1    20     2     3\n -2.0132651897409879E+00 a      2304     1    20     2     4\n  2.4484241841952716E+00 a      2305     1    20     2     5\n  5.3570194814429040E-01 a      2306     1    20     2     6\n  3.9782963410556638E-01 a      2307     1    20     2     7\n  4.9250587897907255E-01 a      2308     1    20     2     8\n -9.0581905870919688E-01 a      2309     1    20     2     9\n  9.6720818758476146E-01 a      2310     1    20     2    10\n -2.4290730668752603E+00 a      2311     1    20     2    11\n  8.5170505147369346E-01 a      2312     1    20     2    12\n -2.1483680686887496E-01 a      2313     1    20     2    13\n  1.0883989821232398E+00 a      2314     1    20     2    14\n -4.2448276419305673E+00 a      2315     1    20     2    15\n  1.3220278308357323E+00 a      2316     1    20     2    16\n  2.0515176886377723E-01 a      2317     1    20     2    17\n  4.3773484307033583E-01 a      2318     1    20     2    18\n -1.3786340518033451E+00 a      2319     1    20     2    19\n -2.2372534223710475E-01 a      2320     1    20     2    20\n -2.7758118237942005E-02 a      2321     1    20     2    21\n -3.6463714150317883E-01 a      2322     1    20     2    22\n -1.4652346461706460E+00 a      2323     1    20     2    23\n -1.9948609569365011E-01 a      2324     1    20     2    24\n -1.2992922004186624E+00 a      2325     1    20     2    25\n -5.4234465116761910E-01 a      2326     1    21     2     1\n -1.1703464645203435E-01 a      2327     1    21     2     2\n  2.7846604110004280E-01 a      2328     1    21     2     3\n  4.2152065037688702E-01 a      2329     1    21     2     4\n -3.1812648076931704E-01 a      2330     1    21     2     5\n  2.5354733798445972E-01 a      2331     1    21     2     6\n  5.0508300555905372E-01 a      2332     1    21     2     7\n -1.8871360552404024E+00 a      2333     1    21     2     8\n -1.8179368004635235E+00 a      2334     1    21     2     9\n -9.1331416740862581E-01 a      2335     1    21     2    10\n  1.0900023434903663E+00 a      2336     1    21     2    11\n  8.9874047451855385E-02 a      2337     1    21     2    12\n -1.2847531299662041E+00 a      2338     1    21     2    13\n -7.4525540480534103E-01 a      2339     1    21     2    14\n  1.0535696198186528E+00 a      2340     1    21     2    15\n  7.8428574671901730E-01 a      2341     1    21     2    16\n  1.3814042929844125E-01 a      2342     1    21     2    17\n  6.9643061019999272E-02 a      2343     1    21     2    18\n  8.0359279616965651E-01 a      2344     1    21     2    19\n -5.6529681854842539E-01 a      2345     1    21     2    20\n -2.3488037904274034E-02 a      2346     1    21     2    21\n  2.1341829380240665E-01 a      2347     1    21     2    22\n -1.4102093313296238E-01 a      2348     1    21     2    23\n -1.6582794027459599E-01 a      2349     1    21     2    24\n -2.1114013691856662E-01 a      2350     1    21     2    25\n  2.4212589160209405E-01 a      2351     1    22     2     1\n  3.9327330796009152E-01 a      2352     1    22     2     2\n -3.6566016634832049E-01 a      2353     1    22     2     3\n  1.0287117668616212E+00 a      2354     1    22     2     4\n  1.6899708282115562E+00 a      2355     1    22     2     5\n  4.3429485581693034E-01 a      2356     1    22     2     6\n  1.7977381066015556E+00 a      2357     1    22     2     7\n  2.9196281691007775E-01 a      2358     1    22     2     8\n  8.9048235778413076E-01 a      2359     1    22     2     9\n -2.7029855626099626E+00 a      2360     1    22     2    10\n -9.9842398461553661E-01 a      2361     1    22     2    11\n  1.3261280174131618E-01 a      2362     1    22     2    12\n  7.8677628275123768E-01 a      2363     1    22     2    13\n -1.6176772224659823E+00 a      2364     1    22     2    14\n -2.9218429770545273E+00 a      2365     1    22     2    15\n -1.0470075932239322E+00 a      2366     1    22     2    16\n -6.2813242798639934E-01 a      2367     1    22     2    17\n -1.1926621420051280E+00 a      2368     1    22     2    18\n  5.6467524440711148E-01 a      2369     1    22     2    19\n  7.0550764585496206E-01 a      2370     1    22     2    20\n  6.7061497370680800E-01 a      2371     1    22     2    21\n  3.2149813491975643E-01 a      2372     1    22     2    22\n -6.5948083157745863E-01 a      2373     1    22     2    23\n  1.4878019494104766E-01 a      2374     1    22     2    24\n -1.4238392562512412E+00 a      2375     1    22     2    25\n -2.9244659427496789E+00 a      2376     1    23     2     1\n  1.1485640801249154E-01 a      2377     1    23     2     2\n  1.1880136805560255E-01 a      2378     1    23     2     3\n  1.9995339152108655E+00 a      2379     1    23     2     4\n -8.8052571584319517E-01 a      2380     1    23     2     5\n -7.6723479106454269E+00 a      2381     1    23     2     6\n -1.6775055426770660E-01 a      2382     1    23     2     7\n  1.1568877491878693E+00 a      2383     1    23     2     8\n -3.6248359285478049E-01 a      2384     1    23     2     9\n -1.0171667144821397E+00 a      2385     1    23     2    10\n -9.7885097010848721E-01 a      2386     1    23     2    11\n  1.7525905926099136E-01 a      2387     1    23     2    12\n  1.6667129102202356E+00 a      2388     1    23     2    13\n -6.3496168416867071E-01 a      2389     1    23     2    14\n -3.9752798317985540E+00 a      2390     1    23     2    15\n -3.0889419514464751E+00 a      2391     1    23     2    16\n -1.6580901185939814E-01 a      2392     1    23     2    17\n -3.0257630892267329E-01 a      2393     1    23     2    18\n  1.1693501120123342E+00 a      2394     1    23     2    19\n -4.4706334843197343E-01 a      2395     1    23     2    20\n  6.3453286866045877E-01 a      2396     1    23     2    21\n  1.9358044980890732E+00 a      2397     1    23     2    22\n  3.1113852281756920E+00 a      2398     1    23     2    23\n -1.9662951755400133E+00 a      2399     1    23     2    24\n -7.5262034829552482E-01 a      2400     1    23     2    25\n -1.0570204013747100E+00 a      2401     1    24     2     1\n  2.0242154350721828E-01 a      2402     1    24     2     2\n -6.1919254330906649E-02 a      2403     1    24     2     3\n -9.3075303350374716E-01 a      2404     1    24     2     4\n -9.4855833806427159E-01 a      2405     1    24     2     5\n  1.2813916759344554E-01 a      2406     1    24     2     6\n -2.0331973717312746E+00 a      2407     1    24     2     7\n  3.0837174823873076E-01 a      2408     1    24     2     8\n  3.7215037809188369E-02 a      2409     1    24     2     9\n  3.9279821894082573E-01 a      2410     1    24     2    10\n  1.1362819017641221E-01 a      2411     1    24     2    11\n -1.3856723422770947E-01 a      2412     1    24     2    12\n -9.0761795928204336E-01 a      2413     1    24     2    13\n -1.9312687936000594E+00 a      2414     1    24     2    14\n  2.4072402343893264E+00 a      2415     1    24     2    15\n -1.3575532169402038E+00 a      2416     1    24     2    16\n -5.0043337242109498E-01 a      2417     1    24     2    17\n  6.6622788206750017E-01 a      2418     1    24     2    18\n -2.7744853244980633E-01 a      2419     1    24     2    19\n -3.3208589628698015E-01 a      2420     1    24     2    20\n -6.5082760242357884E-01 a      2421     1    24     2    21\n -7.4238152455462947E-01 a      2422     1    24     2    22\n  3.5709111009352618E-01 a      2423     1    24     2    23\n  6.1990222796862571E-01 a      2424     1    24     2    24\n  1.1667603307669538E+00 a      2425     1    24     2    25\n  3.4874499133420743E-02 a      2426     1    25     2     1\n  4.6834087122092077E-01 a      2427     1    25     2     2\n -2.4278656264438364E-01 a      2428     1    25     2     3\n -4.7923572182631186E-01 a      2429     1    25     2     4\n  9.1932774354097346E-01 a      2430     1    25     2     5\n  6.9805008912145541E-03 a      2431     1    25     2     6\n -4.0244240337174698E-02 a      2432     1    25     2     7\n  2.3085018839417204E-01 a      2433     1    25     2     8\n  4.1477758640374958E-02 a      2434     1    25     2     9\n -2.9907893871952584E-01 a      2435     1    25     2    10\n  9.9861813798121868E-01 a      2436     1    25     2    11\n  6.1719473832720140E-01 a      2437     1    25     2    12\n  7.7349291753880958E-02 a      2438     1    25     2    13\n  1.9789467747705813E-01 a      2439     1    25     2    14\n -1.6963001394405985E+00 a      2440     1    25     2    15\n  1.6964283624354803E+00 a      2441     1    25     2    16\n -1.2412318165627852E-02 a      2442     1    25     2    17\n -3.0090042509304782E+00 a      2443     1    25     2    18\n -5.2854050109483008E-01 a      2444     1    25     2    19\n -4.0883552444931642E-01 a      2445     1    25     2    20\n -6.7332635048994605E-01 a      2446     1    25     2    21\n -1.9391822634747917E-02 a      2447     1    25     2    22\n  3.7493997817479574E-01 a      2448     1    25     2    23\n -3.1982153221239995E-01 a      2449     1    25     2    24\n -6.5908145380152439E-02 a      2450     1    25     2    25\n  3.6520581763320918E+00 b      2451     2     1\n  8.0350355841113590E+00 b      2452     2     2\n  1.0328413848960700E+00 b      2453     2     3\n  7.2118044450618859E+00 b      2454     2     4\n  1.6897857032469032E+00 b      2455     2     5\n -5.3128298088875221E+00 b      2456     2     6\n  1.1119283095513778E+01 b      2457     2     7\n  5.6335078037870667E-01 b      2458     2     8\n  3.1863573747908753E+00 b      2459     2     9\n -1.5027072914328254E+01 b      2460     2    10\n  4.2491825701309507E+00 b      2461     2    11\n  1.1953389718194374E+00 b      2462     2    12\n -3.7826613521070804E+00 b      2463     2    13\n  2.5804189796272916E+00 b      2464     2    14\n -1.8825899893966049E+01 b      2465     2    15\n  5.0689924546781171E+00 b      2466     2    16\n -4.2675620759638759E+00 b      2467     2    17\n -2.2492760679197388E+00 b      2468     2    18\n  3.5306849260434596E+00 b      2469     2    19\n -4.5612849025174862E+00 b      2470     2    20\n  2.5261284082068989E+00 b      2471     2    21\n  4.9997935137889167E+00 b      2472     2    22\n -1.0317047947417777E+01 b      2473     2    23\n -8.8894968314347089E+00 b      2474     2    24\n -2.4854869056932949E+00 b      2475     2    25\n  7.7377789653328519E-02 a      2476     2     1     3     1\n  3.8948596770158572E-01 a      2477     2     2     3     1\n  1.7977756447195445E-01 a      2478     2     3     3     1\n  6.2246542349685442E-02 a      2479     2     4     3     1\n -1.1775426437182669E-02 a      2480     2     5     3     1\n  7.4084231368981346E-02 a      2481     2     6     3     1\n -2.6739218038996107E-02 a      2482     2     7     3     1\n -1.4199418404546765E-01 a      2483     2     8     3     1\n -1.3644380226489719E-01 a      2484     2     9     3     1\n  4.2740071857011105E-02 a      2485     2    10     3     1\n -8.4658663941687990E-03 a      2486     2    11     3     1\n  1.8776930772068579E-01 a      2487     2    12     3     1\n -6.7008756457919524E-02 a      2488     2    13     3     1\n  4.7698142607044192E-02 a      2489     2    14     3     1\n -1.3372183470389412E-01 a      2490     2    15     3     1\n  4.0870498106272558E-02 a      2491     2    16     3     1\n  1.7572570907757842E-01 a      2492     2    17     3     1\n -1.6327794687227459E-01 a      2493     2    18     3     1\n -5.9707729641314558E-02 a      2494     2    19     3     1\n  1.0563906282310645E-01 a      2495     2    20     3     1\n  6.6231803238242182E-02 a      2496     2    21     3     1\n -2.7962585890502650E-01 a      2497     2    22     3     1\n  1.6032832788645526E-01 a      2498     2    23     3     1\n -1.0623041830538342E-01 a      2499     2    24     3     1\n  1.0896429147371821E-01 a      2500     2    25     3     1\n -1.3407810853851474E+00 b      2501     3     1\n"
  },
  {
    "path": "examples/potentials/Cu2S_PBE/weights.029.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -6.2446602207005186E-01 a         1     0     1     1     1\n  7.9109168478070069E-01 a         2     0     1     1     2\n  5.0258947941284748E-01 a         3     0     1     1     3\n  5.5154910097820120E-01 a         4     0     1     1     4\n  1.4505158314343458E+00 a         5     0     1     1     5\n -3.6571470924977034E-01 a         6     0     1     1     6\n  4.7092493582249750E-01 a         7     0     1     1     7\n  1.7219501990786370E+00 a         8     0     1     1     8\n -1.3599868727171069E-01 a         9     0     1     1     9\n  5.5171059902123576E-01 a        10     0     1     1    10\n -1.3239450297968971E+00 a        11     0     1     1    11\n  7.9289101991721189E-01 a        12     0     1     1    12\n -2.4436241907430895E-01 a        13     0     1     1    13\n  1.2669669007011655E+00 a        14     0     1     1    14\n -1.0859472353178850E+00 a        15     0     1     1    15\n  5.7149297331656246E-01 a        16     0     1     1    16\n  1.1787879403665555E+00 a        17     0     1     1    17\n  5.1959050316647970E-01 a        18     0     1     1    18\n -5.2070371830737283E-01 a        19     0     1     1    19\n -8.6539404799579653E-02 a        20     0     1     1    20\n -1.1403926908826987E+00 a        21     0     1     1    21\n  7.2846619332612425E-02 a        22     0     1     1    22\n -6.0675985144277489E-01 a        23     0     1     1    23\n  1.6628179166765720E+00 a        24     0     1     1    24\n  1.0538483108672489E+00 a        25     0     1     1    25\n -7.0622748176492056E-01 a        26     0     2     1     1\n  1.0910592071347260E+00 a        27     0     2     1     2\n  2.4631386883986663E+00 a        28     0     2     1     3\n  1.1474600047546029E+00 a        29     0     2     1     4\n -2.7984407189871603E+00 a        30     0     2     1     5\n  1.0533577807665364E-02 a        31     0     2     1     6\n -5.0292118189174440E-01 a        32     0     2     1     7\n -2.2761190415250261E+00 a        33     0     2     1     8\n -1.2187992237701142E+00 a        34     0     2     1     9\n  3.3724765156968588E-02 a        35     0     2     1    10\n -3.9421452238268578E-01 a        36     0     2     1    11\n  8.4824888999103987E-01 a        37     0     2     1    12\n -1.2466531728713620E-01 a        38     0     2     1    13\n  1.2079681252116843E+00 a        39     0     2     1    14\n -9.0112129189102541E-01 a        40     0     2     1    15\n  1.6824118679571578E+00 a        41     0     2     1    16\n  3.3935207339432649E-01 a        42     0     2     1    17\n -6.0996462596068590E-01 a        43     0     2     1    18\n  2.0533210855615880E-01 a        44     0     2     1    19\n -8.8645148744139757E-01 a        45     0     2     1    20\n -8.5393507862220064E-01 a        46     0     2     1    21\n -8.5526839185724302E-01 a        47     0     2     1    22\n  1.2489032362439190E+00 a        48     0     2     1    23\n  1.0938354906306260E+00 a        49     0     2     1    24\n -2.6473483803801245E-01 a        50     0     2     1    25\n -8.5878129366894407E-01 a        51     0     3     1     1\n  1.0564533358250394E+00 a        52     0     3     1     2\n  5.6697850343574663E-01 a        53     0     3     1     3\n  2.1086070474971215E+00 a        54     0     3     1     4\n  3.8166154557138393E-01 a        55     0     3     1     5\n -1.4247279770394652E-01 a        56     0     3     1     6\n -5.9572071020060458E-01 a        57     0     3     1     7\n -1.0694188993944764E-01 a        58     0     3     1     8\n  1.5066623963754497E+00 a        59     0     3     1     9\n  1.8089065761782133E-01 a        60     0     3     1    10\n -2.7214036058537823E+00 a        61     0     3     1    11\n  5.9806847727363321E-01 a        62     0     3     1    12\n -6.1642316248623163E-01 a        63     0     3     1    13\n  1.3696608481313977E+00 a        64     0     3     1    14\n -1.7104667782680838E+00 a        65     0     3     1    15\n  3.4174228333518369E-01 a        66     0     3     1    16\n  2.1950204328903058E+00 a        67     0     3     1    17\n  1.4819471011296372E+00 a        68     0     3     1    18\n  8.6419598086195182E-01 a        69     0     3     1    19\n -1.9807673916649222E+00 a        70     0     3     1    20\n -8.1754981466548049E-01 a        71     0     3     1    21\n  8.5183964054601424E-01 a        72     0     3     1    22\n -1.1265351050299546E+00 a        73     0     3     1    23\n  3.1023051337695745E-01 a        74     0     3     1    24\n  2.7440424392777945E+00 a        75     0     3     1    25\n  2.2960298979188901E-01 a        76     0     4     1     1\n  4.7699142503296446E-02 a        77     0     4     1     2\n  6.0155337022245625E-01 a        78     0     4     1     3\n -1.9439503692815557E-01 a        79     0     4     1     4\n -2.8605530154913746E-02 a        80     0     4     1     5\n  5.5983316423300188E-03 a        81     0     4     1     6\n  9.7519204826929984E-01 a        82     0     4     1     7\n  2.9668852740436547E-01 a        83     0     4     1     8\n  4.8725450035125151E-01 a        84     0     4     1     9\n  2.1326287630079049E-01 a        85     0     4     1    10\n -7.3554692603307470E-01 a        86     0     4     1    11\n  5.3315910230702435E-01 a        87     0     4     1    12\n -5.0172823432095809E-02 a        88     0     4     1    13\n  1.0865253078708168E+00 a        89     0     4     1    14\n -1.0261853156045440E+00 a        90     0     4     1    15\n  2.6512919821052433E-01 a        91     0     4     1    16\n  1.0812812614858249E+00 a        92     0     4     1    17\n  5.1028631925899315E-01 a        93     0     4     1    18\n -2.2599179332603903E-01 a        94     0     4     1    19\n  7.5088913825415021E-02 a        95     0     4     1    20\n -1.2364446472765618E+00 a        96     0     4     1    21\n  7.5326701143038222E-01 a        97     0     4     1    22\n -2.6515244091963569E-01 a        98     0     4     1    23\n  1.6838686308480304E+00 a        99     0     4     1    24\n  4.4492731774876376E-01 a       100     0     4     1    25\n -6.6099920232044096E-01 a       101     0     5     1     1\n  1.0089031054636115E-01 a       102     0     5     1     2\n  6.6342762904664385E-02 a       103     0     5     1     3\n  4.5542810443153381E-01 a       104     0     5     1     4\n -1.6657987380644132E-01 a       105     0     5     1     5\n -8.7555923451999446E-02 a       106     0     5     1     6\n -5.0759948537866628E-01 a       107     0     5     1     7\n  1.6763463093097672E-01 a       108     0     5     1     8\n -5.0802820857751363E-01 a       109     0     5     1     9\n  6.5721089961406787E-01 a       110     0     5     1    10\n -1.7250321983253045E+00 a       111     0     5     1    11\n  3.6248667744583185E-01 a       112     0     5     1    12\n -1.4187643709855371E-01 a       113     0     5     1    13\n  1.8277813268335372E-01 a       114     0     5     1    14\n -2.8759067553024059E-01 a       115     0     5     1    15\n  1.6396175797308257E-01 a       116     0     5     1    16\n  4.8459268505242964E-01 a       117     0     5     1    17\n  1.1485781012576022E+00 a       118     0     5     1    18\n  5.1100172835951252E-01 a       119     0     5     1    19\n -9.6969998866484486E-01 a       120     0     5     1    20\n  2.9282365167621466E-01 a       121     0     5     1    21\n  1.9454366730362621E-01 a       122     0     5     1    22\n  3.3723039867517968E-01 a       123     0     5     1    23\n -1.9892929243485494E-01 a       124     0     5     1    24\n -7.1822973746603158E-01 a       125     0     5     1    25\n -6.8064782973022775E-01 a       126     0     6     1     1\n  1.8829906173635458E-01 a       127     0     6     1     2\n  8.1479476506818194E-01 a       128     0     6     1     3\n  8.8277352960690048E-01 a       129     0     6     1     4\n -1.1427613588950543E+00 a       130     0     6     1     5\n  3.0159781113246154E-01 a       131     0     6     1     6\n -6.6588549790596940E-01 a       132     0     6     1     7\n -3.5003459927148434E-01 a       133     0     6     1     8\n -1.5345874997486508E+00 a       134     0     6     1     9\n -2.4240783711001435E-01 a       135     0     6     1    10\n  6.3947769766304896E-01 a       136     0     6     1    11\n  4.1352767758563735E-01 a       137     0     6     1    12\n -1.9019289044167662E-01 a       138     0     6     1    13\n  6.5802349593562548E-01 a       139     0     6     1    14\n -2.8846900299080136E-01 a       140     0     6     1    15\n  1.8044674812699533E+00 a       141     0     6     1    16\n -5.9916590668694536E-01 a       142     0     6     1    17\n  1.0233762388247421E-01 a       143     0     6     1    18\n -1.8293705219837877E-01 a       144     0     6     1    19\n -4.7618220713345544E-01 a       145     0     6     1    20\n -6.7585128250473714E-01 a       146     0     6     1    21\n -6.6619987727158803E-01 a       147     0     6     1    22\n  1.3937539584448881E+00 a       148     0     6     1    23\n  1.1804472226031208E+00 a       149     0     6     1    24\n -1.0475143437784208E-01 a       150     0     6     1    25\n -5.0310349062450688E-01 a       151     0     7     1     1\n  3.0549253527946091E-01 a       152     0     7     1     2\n  2.1639018141171862E-03 a       153     0     7     1     3\n  9.6581676298511743E-01 a       154     0     7     1     4\n  7.7874943618349207E-02 a       155     0     7     1     5\n  8.3859302793542922E-02 a       156     0     7     1     6\n  1.7299832669890869E-03 a       157     0     7     1     7\n  2.9262810015651336E-01 a       158     0     7     1     8\n  1.7542214681324636E-01 a       159     0     7     1     9\n -2.8526127268586043E-01 a       160     0     7     1    10\n -5.4990409523663197E-01 a       161     0     7     1    11\n  1.3450068091702161E-01 a       162     0     7     1    12\n -1.4756996153937790E-01 a       163     0     7     1    13\n  2.9311237452477523E-01 a       164     0     7     1    14\n -7.2084298548573761E-02 a       165     0     7     1    15\n -8.5149614730888945E-02 a       166     0     7     1    16\n  9.2949085965140277E-01 a       167     0     7     1    17\n -2.8847043946794215E-01 a       168     0     7     1    18\n  4.1186911885861338E-01 a       169     0     7     1    19\n -5.4169485090346026E-01 a       170     0     7     1    20\n -3.5243695639465118E-02 a       171     0     7     1    21\n  3.1341789027127781E-02 a       172     0     7     1    22\n -2.8786714994989410E-01 a       173     0     7     1    23\n  2.7315793972504460E-01 a       174     0     7     1    24\n  1.1716570530670567E+00 a       175     0     7     1    25\n -5.1036135947851669E-01 a       176     0     8     1     1\n -1.3740271110517560E-01 a       177     0     8     1     2\n  4.8958222402524031E-02 a       178     0     8     1     3\n  3.3177672494990651E-01 a       179     0     8     1     4\n -2.3856000868246988E-01 a       180     0     8     1     5\n  4.1214983538548872E-01 a       181     0     8     1     6\n -9.8286694614992598E-01 a       182     0     8     1     7\n -5.4107034590118536E-02 a       183     0     8     1     8\n -1.4324705358476875E-01 a       184     0     8     1     9\n -3.0823277006517974E-01 a       185     0     8     1    10\n  1.1094081849455624E+00 a       186     0     8     1    11\n  1.5831813220006527E-01 a       187     0     8     1    12\n -7.8050742477211929E-02 a       188     0     8     1    13\n  1.4147217795488959E-01 a       189     0     8     1    14\n -3.6482920722359169E-01 a       190     0     8     1    15\n  2.0010515781611065E+00 a       191     0     8     1    16\n -3.7164167894211825E-01 a       192     0     8     1    17\n -1.3125516149697244E-02 a       193     0     8     1    18\n -4.1954663172842910E-02 a       194     0     8     1    19\n -1.0331434570137119E-01 a       195     0     8     1    20\n -1.8011393958889632E-01 a       196     0     8     1    21\n  1.3088400236386397E-01 a       197     0     8     1    22\n  1.1923413887217991E+00 a       198     0     8     1    23\n  3.7781840918971593E-01 a       199     0     8     1    24\n -1.9294958159048309E-01 a       200     0     8     1    25\n -3.3392447645114481E-01 a       201     0     9     1     1\n  1.7014988701747677E-01 a       202     0     9     1     2\n -2.7070863493070599E-02 a       203     0     9     1     3\n  7.4604630341273778E-02 a       204     0     9     1     4\n -1.5102715752534066E-02 a       205     0     9     1     5\n  1.5720699324567589E-01 a       206     0     9     1     6\n -6.1974554587877762E-01 a       207     0     9     1     7\n  5.4891362413614087E-03 a       208     0     9     1     8\n  2.0919388011889421E-02 a       209     0     9     1     9\n -9.6391241772834951E-02 a       210     0     9     1    10\n  7.7306858668673450E-01 a       211     0     9     1    11\n  3.1255109436960182E-01 a       212     0     9     1    12\n  7.7005492614491439E-02 a       213     0     9     1    13\n -2.4607006332823117E-02 a       214     0     9     1    14\n -1.0454167793466912E-01 a       215     0     9     1    15\n  5.7967244318170463E-01 a       216     0     9     1    16\n -1.2093767067885464E-01 a       217     0     9     1    17\n -2.2544971455810286E-01 a       218     0     9     1    18\n  2.1029853185087000E-01 a       219     0     9     1    19\n -1.9601661095545145E-01 a       220     0     9     1    20\n -5.1292763498012379E-02 a       221     0     9     1    21\n  1.4590455721615306E-01 a       222     0     9     1    22\n  4.6964108851222075E-01 a       223     0     9     1    23\n  5.7481385069930169E-02 a       224     0     9     1    24\n -2.0098849633862609E-01 a       225     0     9     1    25\n  4.8244923506134771E+00 a       226     0    10     1     1\n  3.5108916592109578E+00 a       227     0    10     1     2\n  7.5139348670019617E+00 a       228     0    10     1     3\n -3.5578918915946471E+00 a       229     0    10     1     4\n  2.8386058903754559E+00 a       230     0    10     1     5\n  4.4207199746823003E+00 a       231     0    10     1     6\n -3.3412935119326561E+00 a       232     0    10     1     7\n -9.0971866563833217E+00 a       233     0    10     1     8\n -4.5268654758530369E+00 a       234     0    10     1     9\n -5.5872647360635401E+00 a       235     0    10     1    10\n -2.0635169275427789E+00 a       236     0    10     1    11\n -1.5340623877597045E+01 a       237     0    10     1    12\n -8.3715082878395020E+00 a       238     0    10     1    13\n -6.4817382472795639E+00 a       239     0    10     1    14\n -5.0809375777610395E+00 a       240     0    10     1    15\n -6.4689687360330987E+00 a       241     0    10     1    16\n  2.1416014963815999E+00 a       242     0    10     1    17\n  6.8940758724466367E+00 a       243     0    10     1    18\n -4.3648169145202758E+00 a       244     0    10     1    19\n  9.0382653292775696E+00 a       245     0    10     1    20\n -9.9166110945066848E+00 a       246     0    10     1    21\n -1.2044366652841560E+01 a       247     0    10     1    22\n  2.2720545079306909E+01 a       248     0    10     1    23\n -3.7379508213234649E+00 a       249     0    10     1    24\n -4.5209017693635660E+00 a       250     0    10     1    25\n  7.5183832154301431E+00 a       251     0    11     1     1\n -2.3203106234194992E+00 a       252     0    11     1     2\n  1.4841440810090241E+00 a       253     0    11     1     3\n  9.6482513939399706E-01 a       254     0    11     1     4\n -8.4297506087479601E-01 a       255     0    11     1     5\n -4.6990364184782007E-01 a       256     0    11     1     6\n -1.0961424660272627E+00 a       257     0    11     1     7\n -2.7374480650608306E+00 a       258     0    11     1     8\n  3.1380660893974572E+00 a       259     0    11     1     9\n  1.4968023108710922E+00 a       260     0    11     1    10\n  4.8431460218952400E-02 a       261     0    11     1    11\n -1.1491977088084576E+01 a       262     0    11     1    12\n -8.0416563043774918E+00 a       263     0    11     1    13\n -2.5360493765208667E+00 a       264     0    11     1    14\n  7.9109477782628268E-01 a       265     0    11     1    15\n -7.2962300446546091E-01 a       266     0    11     1    16\n -1.2513868916478101E+00 a       267     0    11     1    17\n -2.7011654742543052E+00 a       268     0    11     1    18\n  2.4531950654664225E+00 a       269     0    11     1    19\n -1.0070370759062769E+01 a       270     0    11     1    20\n  7.9155519637009908E+00 a       271     0    11     1    21\n 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1.6244338649202151E-02 a      1893     1     9     2    18\n  2.8159940956926782E-02 a      1894     1     9     2    19\n -7.3760105274932919E-01 a      1895     1     9     2    20\n  1.0604614152784235E-01 a      1896     1     9     2    21\n  1.3087759494518761E-01 a      1897     1     9     2    22\n  2.9873262087000452E-01 a      1898     1     9     2    23\n -7.5121649539691160E-01 a      1899     1     9     2    24\n -5.3923107796072600E-01 a      1900     1     9     2    25\n -9.4224670371027917E-03 a      1901     1    10     2     1\n  1.7582720220947401E-01 a      1902     1    10     2     2\n -4.3499560356818456E-02 a      1903     1    10     2     3\n  2.7310295785198496E-01 a      1904     1    10     2     4\n -1.4711568084768856E+00 a      1905     1    10     2     5\n -4.4204405689495387E-02 a      1906     1    10     2     6\n  6.0834648389602855E-02 a      1907     1    10     2     7\n -2.4139577578874571E+00 a      1908     1    10     2     8\n -3.2330445150185877E-01 a      1909     1    10     2     9\n -6.8558897710748834E-01 a      1910     1    10     2    10\n -2.6306695094273136E-01 a      1911     1    10     2    11\n -2.9406094777407277E+00 a      1912     1    10     2    12\n -1.0262257550335584E-01 a      1913     1    10     2    13\n -4.4889806212745592E-01 a      1914     1    10     2    14\n  1.2729127190479747E-01 a      1915     1    10     2    15\n -5.4339870455363115E-01 a      1916     1    10     2    16\n -4.3051833335864892E-01 a      1917     1    10     2    17\n  2.2774840440979685E-01 a      1918     1    10     2    18\n -4.6577095617807179E-01 a      1919     1    10     2    19\n  6.7677527850068725E-02 a      1920     1    10     2    20\n -5.4331229454547138E-02 a      1921     1    10     2    21\n -7.2517226150440761E-01 a      1922     1    10     2    22\n -1.1034679805264240E+00 a      1923     1    10     2    23\n -2.0195864669569050E+00 a      1924     1    10     2    24\n  3.4421830988038693E-01 a      1925     1    10     2    25\n  6.4169421416549660E-02 a      1926     1    11     2     1\n -1.5453028953359832E-01 a      1927     1    11     2     2\n -3.3937811286737152E-01 a      1928     1    11     2     3\n -2.7264685928399618E-02 a      1929     1    11     2     4\n -1.3046027284183024E+00 a      1930     1    11     2     5\n -2.7987570911040532E-01 a      1931     1    11     2     6\n -7.1818879614311160E-01 a      1932     1    11     2     7\n -1.1206386399096295E+00 a      1933     1    11     2     8\n  5.8589221854259044E-01 a      1934     1    11     2     9\n -3.7755430943908636E-01 a      1935     1    11     2    10\n -2.4227661602201420E-01 a      1936     1    11     2    11\n -6.6802170984862275E-01 a      1937     1    11     2    12\n -1.0335031399378087E+00 a      1938     1    11     2    13\n  2.7352884921752563E-01 a      1939     1    11     2    14\n -7.7644903482906286E-02 a      1940     1    11     2    15\n -1.2483161225817251E-01 a      1941     1    11     2    16\n -1.0076823380037454E-01 a      1942     1    11     2    17\n  1.8474479042673506E-02 a      1943     1    11     2    18\n  1.5921923675493641E-01 a      1944     1    11     2    19\n -8.6092467903913172E-01 a      1945     1    11     2    20\n  3.1597658763496336E-02 a      1946     1    11     2    21\n  1.2582027961569384E-01 a      1947     1    11     2    22\n  4.1552569278194468E-01 a      1948     1    11     2    23\n -1.8547083512843898E-01 a      1949     1    11     2    24\n -3.1841028886761663E-01 a      1950     1    11     2    25\n  1.8006197092716905E-01 a      1951     1    12     2     1\n -5.4024199178819454E-01 a      1952     1    12     2     2\n  3.3523776691134710E-01 a      1953     1    12     2     3\n  2.7560028312601675E-01 a      1954     1    12     2     4\n  8.6177633437044554E-01 a      1955     1    12     2     5\n  1.0087407297301751E+00 a      1956     1    12     2     6\n -1.2380927066334282E-01 a      1957     1    12     2     7\n -1.5229780941544174E-01 a      1958     1    12     2     8\n  2.9946743134146903E-01 a      1959     1    12     2     9\n  1.9819105447401073E+00 a      1960     1    12     2    10\n -8.0628486303151947E-01 a      1961     1    12     2    11\n -9.3151349622473523E-01 a      1962     1    12     2    12\n  1.5051328872455074E+00 a      1963     1    12     2    13\n -8.9627139441554438E-01 a      1964     1    12     2    14\n -3.1439437993199801E-02 a      1965     1    12     2    15\n  1.3701630178002484E+00 a      1966     1    12     2    16\n -2.9138443586057278E-01 a      1967     1    12     2    17\n -3.9087530619619010E-01 a      1968     1    12     2    18\n -2.2753042561066517E-01 a      1969     1    12     2    19\n -8.0931038915796594E-01 a      1970     1    12     2    20\n  1.2030804656668543E+00 a      1971     1    12     2    21\n -1.3389862350446610E-01 a      1972     1    12     2    22\n  4.8419262676478225E-01 a      1973     1    12     2    23\n  1.2108153439974718E+00 a      1974     1    12     2    24\n -1.9519966513619349E+00 a      1975     1    12     2    25\n -1.5047045953264607E-01 a      1976     1    13     2     1\n -6.5196314968694580E-01 a      1977     1    13     2     2\n -1.9444580576963033E-01 a      1978     1    13     2     3\n -3.0635873068371338E-03 a      1979     1    13     2     4\n  1.4891889558793558E+00 a      1980     1    13     2     5\n -2.7617795790820687E-01 a      1981     1    13     2     6\n  1.3155600760922213E+00 a      1982     1    13     2     7\n  1.6548881500952060E+00 a      1983     1    13     2     8\n  1.2939743974749243E+00 a      1984     1    13     2     9\n -8.8087806931438950E-01 a      1985     1    13     2    10\n -7.3026619095577089E-02 a      1986     1    13     2    11\n -6.7521271933403364E+00 a      1987     1    13     2    12\n  3.4361606414546986E-01 a      1988     1    13     2    13\n  8.7558578977526269E-01 a      1989     1    13     2    14\n -2.2881702674887253E-01 a      1990     1    13     2    15\n -6.2816527553206336E-01 a      1991     1    13     2    16\n -8.9317308141201190E-01 a      1992     1    13     2    17\n  9.7069680211539489E-01 a      1993     1    13     2    18\n -5.6927576536010438E-01 a      1994     1    13     2    19\n  8.2910381395357602E-01 a      1995     1    13     2    20\n -3.8934674186907103E-01 a      1996     1    13     2    21\n -1.0181364553104701E+00 a      1997     1    13     2    22\n -9.1002882788836370E-01 a      1998     1    13     2    23\n  2.1075571090156360E+00 a      1999     1    13     2    24\n  2.3017239447035212E-01 a      2000     1    13     2    25\n -3.5483123954045620E-01 a      2001     1    14     2     1\n -9.6047986054177317E-02 a      2002     1    14     2     2\n  3.3071183118138114E-01 a      2003     1    14     2     3\n  1.7705379181791761E-01 a      2004     1    14     2     4\n -1.2043718203406772E+00 a      2005     1    14     2     5\n -5.7806038919408154E-01 a      2006     1    14     2     6\n  6.5633162044623850E-01 a      2007     1    14     2     7\n -1.3450535190144031E-01 a      2008     1    14     2     8\n -1.2862521179205477E-01 a      2009     1    14     2     9\n -1.5177254021629161E-01 a      2010     1    14     2    10\n -2.9016357432381029E-01 a      2011     1    14     2    11\n  1.2793982277409728E+00 a      2012     1    14     2    12\n -3.7109006944139383E-01 a      2013     1    14     2    13\n -4.5064222698368622E-01 a      2014     1    14     2    14\n  3.9087439217392134E-02 a      2015     1    14     2    15\n -1.7890737007331405E+00 a      2016     1    14     2    16\n -3.5761366598992050E-01 a      2017     1    14     2    17\n  3.8280249413524364E-01 a      2018     1    14     2    18\n -3.4580266787944813E-01 a      2019     1    14     2    19\n -2.3102511719307051E-01 a      2020     1    14     2    20\n  6.1712210683785684E-02 a      2021     1    14     2    21\n -3.3548067811281668E-01 a      2022     1    14     2    22\n -7.9862203729164616E-01 a      2023     1    14     2    23\n -5.1952466530501407E-01 a      2024     1    14     2    24\n  2.5810393446929092E-01 a      2025     1    14     2    25\n -4.3558412131876484E-01 a      2026     1    15     2     1\n  1.1902629233075568E-01 a      2027     1    15     2     2\n  1.1747512026211912E-01 a      2028     1    15     2     3\n  1.5495247101048408E-02 a      2029     1    15     2     4\n -1.2065420500806932E+00 a      2030     1    15     2     5\n  3.3479165215501783E-01 a      2031     1    15     2     6\n  2.8245317600466197E-01 a      2032     1    15     2     7\n  6.6749992551384099E-02 a      2033     1    15     2     8\n -3.1396609925815760E-01 a      2034     1    15     2     9\n  3.0054714990159620E-01 a      2035     1    15     2    10\n  6.0483428643207637E-01 a      2036     1    15     2    11\n -1.2454958402656351E+00 a      2037     1    15     2    12\n  6.3389744137669779E-01 a      2038     1    15     2    13\n -5.9521423079842484E-01 a      2039     1    15     2    14\n  1.2019169256706089E-01 a      2040     1    15     2    15\n -1.1987245524864630E-01 a      2041     1    15     2    16\n -5.6896152994198784E-02 a      2042     1    15     2    17\n  2.8941200439853954E-01 a      2043     1    15     2    18\n  1.6309209946798925E-01 a      2044     1    15     2    19\n  8.7949523201494928E-01 a      2045     1    15     2    20\n  6.4769343609644300E-02 a      2046     1    15     2    21\n  4.8521193987474981E-01 a      2047     1    15     2    22\n  4.9988972941182691E-01 a      2048     1    15     2    23\n -2.3016622688408100E-01 a      2049     1    15     2    24\n -5.4074197586570194E-01 a      2050     1    15     2    25\n -4.8573302372386212E-01 a      2051     1    16     2     1\n -1.2895431219807293E-01 a      2052     1    16     2     2\n -3.6183115010678968E-01 a      2053     1    16     2     3\n -1.9197089311858578E-01 a      2054     1    16     2     4\n  1.6791441443786570E+00 a      2055     1    16     2     5\n  1.4524232953370153E+00 a      2056     1    16     2     6\n  8.1332800345877809E-01 a      2057     1    16     2     7\n -6.8993826377906453E-01 a      2058     1    16     2     8\n -6.4581623589215043E-01 a      2059     1    16     2     9\n -1.9086496482644792E+00 a      2060     1    16     2    10\n -7.6174424886678238E-01 a      2061     1    16     2    11\n -6.6106476479584952E-01 a      2062     1    16     2    12\n -6.5143307233530923E-01 a      2063     1    16     2    13\n  6.3145424574265796E-01 a      2064     1    16     2    14\n -2.3081494763260896E-01 a      2065     1    16     2    15\n  1.1456064040705682E-01 a      2066     1    16     2    16\n  1.6252315194690317E-01 a      2067     1    16     2    17\n -1.2291397585047813E-01 a      2068     1    16     2    18\n -6.7674808608296347E-02 a      2069     1    16     2    19\n  5.4942310825997287E-01 a      2070     1    16     2    20\n -1.0797615834794017E-01 a      2071     1    16     2    21\n  2.4950326732348715E-01 a      2072     1    16     2    22\n -7.9414639176233692E-01 a      2073     1    16     2    23\n  2.0544441738751792E-01 a      2074     1    16     2    24\n  1.8992443483722937E-01 a      2075     1    16     2    25\n -4.6582766497660771E-01 a      2076     1    17     2     1\n  2.9539156697999569E-01 a      2077     1    17     2     2\n -2.2097168205408066E-01 a      2078     1    17     2     3\n -1.4860622629638501E-01 a      2079     1    17     2     4\n -3.2498215361218613E-01 a      2080     1    17     2     5\n  3.4427076522021333E-01 a      2081     1    17     2     6\n  8.6586127926198697E-01 a      2082     1    17     2     7\n -1.1418000025514305E-01 a      2083     1    17     2     8\n -6.0056682073398004E-01 a      2084     1    17     2     9\n  2.0450736509644665E-01 a      2085     1    17     2    10\n -1.8519278941182027E-01 a      2086     1    17     2    11\n -1.4644629512368172E+00 a      2087     1    17     2    12\n -2.9378404760799470E-01 a      2088     1    17     2    13\n  5.5384788915605931E-01 a      2089     1    17     2    14\n -1.5004256050064771E-01 a      2090     1    17     2    15\n  3.2806846888851510E-01 a      2091     1    17     2    16\n  2.7598536643862270E-01 a      2092     1    17     2    17\n  4.1850888007058207E-01 a      2093     1    17     2    18\n -5.5362304975505497E-02 a      2094     1    17     2    19\n  2.6951266238898874E-01 a      2095     1    17     2    20\n -2.4264170360616094E-02 a      2096     1    17     2    21\n -1.8676465863061775E-01 a      2097     1    17     2    22\n -3.8787011654837039E-01 a      2098     1    17     2    23\n  3.4485637458118229E-01 a      2099     1    17     2    24\n -3.0786400824237545E-02 a      2100     1    17     2    25\n -1.4217762050351745E-01 a      2101     1    18     2     1\n -7.0998782591968046E-01 a      2102     1    18     2     2\n -9.6362930548428383E-01 a      2103     1    18     2     3\n  7.5180370041830813E-02 a      2104     1    18     2     4\n  9.3452511163166374E-01 a      2105     1    18     2     5\n  7.5072353982545093E-01 a      2106     1    18     2     6\n -1.4600462437868158E+00 a      2107     1    18     2     7\n -1.0484471284226574E-01 a      2108     1    18     2     8\n -1.5226425654047304E+00 a      2109     1    18     2     9\n -8.8296305768438263E-02 a      2110     1    18     2    10\n -3.6274389516383643E-01 a      2111     1    18     2    11\n  8.8349447132068071E-01 a      2112     1    18     2    12\n  3.6371290147774743E-01 a      2113     1    18     2    13\n -4.7916817706816656E-01 a      2114     1    18     2    14\n  1.3662341082955812E-01 a      2115     1    18     2    15\n  1.3172314297178116E+00 a      2116     1    18     2    16\n  3.4403068584860565E-02 a      2117     1    18     2    17\n  3.6061432566306936E-02 a      2118     1    18     2    18\n  4.5896212647717503E-02 a      2119     1    18     2    19\n -1.8589693017644275E+00 a      2120     1    18     2    20\n  1.5237137982152765E-01 a      2121     1    18     2    21\n -3.8234921593024973E-01 a      2122     1    18     2    22\n  3.5542438141750315E-02 a      2123     1    18     2    23\n -3.9944133636062124E-01 a      2124     1    18     2    24\n -6.5550378551330324E-01 a      2125     1    18     2    25\n  1.2816550559385723E-01 a      2126     1    19     2     1\n  3.5486759391369166E-02 a      2127     1    19     2     2\n  4.6182319454349319E-01 a      2128     1    19     2     3\n -5.5122652267036590E-03 a      2129     1    19     2     4\n -3.5080949888496260E+00 a      2130     1    19     2     5\n  7.1486948663206473E-01 a      2131     1    19     2     6\n -2.1201853030552007E+00 a      2132     1    19     2     7\n  7.2604028903282403E-01 a      2133     1    19     2     8\n  5.1081128242304719E-01 a      2134     1    19     2     9\n -4.9137504534121196E-01 a      2135     1    19     2    10\n -1.0472694822448174E+00 a      2136     1    19     2    11\n -1.3523763718593251E+00 a      2137     1    19     2    12\n  2.3568530190159431E-01 a      2138     1    19     2    13\n  5.9584736557607831E-01 a      2139     1    19     2    14\n -3.0079808992756946E-02 a      2140     1    19     2    15\n -1.5268283743999284E-01 a      2141     1    19     2    16\n  9.6122412178057212E-02 a      2142     1    19     2    17\n -1.0684936989401796E-01 a      2143     1    19     2    18\n -5.7716017213991798E-02 a      2144     1    19     2    19\n -2.1338482417439314E-01 a      2145     1    19     2    20\n -3.2012152562395965E-02 a      2146     1    19     2    21\n  6.6195535336631889E-02 a      2147     1    19     2    22\n -4.0717271079249823E-01 a      2148     1    19     2    23\n  4.3854075768154355E-01 a      2149     1    19     2    24\n  5.4824793644114189E-01 a      2150     1    19     2    25\n -1.6683810612646832E-01 a      2151     1    20     2     1\n  2.3322749612412674E-01 a      2152     1    20     2     2\n -4.4183715955442193E-01 a      2153     1    20     2     3\n -7.2076827728753526E-02 a      2154     1    20     2     4\n -5.9352383243727491E-01 a      2155     1    20     2     5\n -3.9339117998165263E-01 a      2156     1    20     2     6\n -5.4931274369409873E-02 a      2157     1    20     2     7\n -4.5548835587531822E-01 a      2158     1    20     2     8\n -6.5732706177413358E-01 a      2159     1    20     2     9\n -1.1236237633542311E-01 a      2160     1    20     2    10\n  1.1351566319349074E-02 a      2161     1    20     2    11\n -1.2386831457708261E+00 a      2162     1    20     2    12\n  4.5243628166561789E-01 a      2163     1    20     2    13\n -5.8831183211013338E-01 a      2164     1    20     2    14\n -8.3869411335455488E-02 a      2165     1    20     2    15\n -7.0984549162019170E-02 a      2166     1    20     2    16\n  3.3054811913793787E-02 a      2167     1    20     2    17\n  1.9644857020909354E-01 a      2168     1    20     2    18\n  1.5161782757226400E-01 a      2169     1    20     2    19\n -2.3505702805909551E-01 a      2170     1    20     2    20\n -1.7918789556131143E-01 a      2171     1    20     2    21\n  3.4990356667744421E-01 a      2172     1    20     2    22\n  6.4840494486623490E-01 a      2173     1    20     2    23\n -1.4478590661265617E-01 a      2174     1    20     2    24\n  2.1297816904812697E-01 a      2175     1    20     2    25\n  3.4493308448955345E-01 a      2176     1    21     2     1\n  3.5266855354427494E-02 a      2177     1    21     2     2\n -2.7754410875303576E-01 a      2178     1    21     2     3\n  4.6768620046741878E-02 a      2179     1    21     2     4\n -1.5769313809619548E-01 a      2180     1    21     2     5\n  1.3497835265205210E-01 a      2181     1    21     2     6\n -3.7341652004504744E-01 a      2182     1    21     2     7\n -3.0627556863254835E-01 a      2183     1    21     2     8\n -2.2925939617710103E-01 a      2184     1    21     2     9\n -3.8592084381092573E-01 a      2185     1    21     2    10\n  4.1234641447800625E-02 a      2186     1    21     2    11\n -9.5022250284578980E-01 a      2187     1    21     2    12\n -1.1125930303081784E+00 a      2188     1    21     2    13\n -5.3122650273704952E-01 a      2189     1    21     2    14\n  2.3060682491837362E-02 a      2190     1    21     2    15\n -1.5104224681786016E+00 a      2191     1    21     2    16\n  1.4753038731650985E-03 a      2192     1    21     2    17\n  1.5143866707297242E-02 a      2193     1    21     2    18\n  8.6090707736472302E-02 a      2194     1    21     2    19\n -6.2430761394861624E-02 a      2195     1    21     2    20\n -6.1308060604509992E-03 a      2196     1    21     2    21\n -1.4270727537208755E-01 a      2197     1    21     2    22\n  4.1134552752308873E-01 a      2198     1    21     2    23\n -6.8567787253466550E-01 a      2199     1    21     2    24\n -6.7206916205524492E-01 a      2200     1    21     2    25\n -1.5391019835641329E+00 a      2201     1    22     2     1\n  1.7206752534353434E-01 a      2202     1    22     2     2\n  6.7593465480848644E-02 a      2203     1    22     2     3\n -8.5997555363846803E-02 a      2204     1    22     2     4\n -9.6065684505879689E-01 a      2205     1    22     2     5\n  1.1113173657279094E+00 a      2206     1    22     2     6\n -3.0842014372062625E+00 a      2207     1    22     2     7\n -1.4384158041499902E+00 a      2208     1    22     2     8\n  1.1309101459634252E+00 a      2209     1    22     2     9\n  1.5105165505154550E-01 a      2210     1    22     2    10\n  3.0645396828385907E-01 a      2211     1    22     2    11\n  6.4601478772770526E-01 a      2212     1    22     2    12\n  4.8724111088572403E-01 a      2213     1    22     2    13\n -4.6620160034283531E-01 a      2214     1    22     2    14\n -4.8803479432276621E-02 a      2215     1    22     2    15\n -9.0430630054920480E-01 a      2216     1    22     2    16\n -6.9889480249312042E-01 a      2217     1    22     2    17\n -1.4468447857571731E+00 a      2218     1    22     2    18\n  2.3039464990726008E-01 a      2219     1    22     2    19\n  5.4576177723516872E-01 a      2220     1    22     2    20\n -7.8015018576137352E-02 a      2221     1    22     2    21\n -1.6133123661713483E-01 a      2222     1    22     2    22\n -1.8319296597374665E-01 a      2223     1    22     2    23\n  2.7253642896910552E-01 a      2224     1    22     2    24\n -1.1584411372851944E+00 a      2225     1    22     2    25\n -5.5424557394569851E-01 a      2226     1    23     2     1\n  7.0029876501251875E-01 a      2227     1    23     2     2\n  8.6637467798596698E-02 a      2228     1    23     2     3\n -7.8591217867498966E-02 a      2229     1    23     2     4\n -3.8578050693417802E+00 a      2230     1    23     2     5\n -1.5514902939375283E-02 a      2231     1    23     2     6\n  5.3013810166945474E-01 a      2232     1    23     2     7\n -6.0550270203294210E-01 a      2233     1    23     2     8\n  4.3671597358238062E-01 a      2234     1    23     2     9\n -3.5715147706396755E-01 a      2235     1    23     2    10\n  1.0882856270043771E-01 a      2236     1    23     2    11\n  1.7281037261210461E+00 a      2237     1    23     2    12\n -5.7515626421966193E-01 a      2238     1    23     2    13\n -1.3375042180867350E-01 a      2239     1    23     2    14\n -6.5503722712337037E-02 a      2240     1    23     2    15\n -2.2025191432304744E-02 a      2241     1    23     2    16\n -8.2655071054651752E-02 a      2242     1    23     2    17\n -2.1027511956094072E-01 a      2243     1    23     2    18\n  2.8902376330777999E-02 a      2244     1    23     2    19\n  1.3213999048426042E-01 a      2245     1    23     2    20\n -1.1460728829522189E-01 a      2246     1    23     2    21\n -5.8828720552246631E-02 a      2247     1    23     2    22\n -6.0152091553027887E-01 a      2248     1    23     2    23\n -7.1147789709956066E-01 a      2249     1    23     2    24\n  5.2100860083053230E-02 a      2250     1    23     2    25\n -1.4344935215141292E+00 a      2251     1    24     2     1\n  9.2746205501548851E-01 a      2252     1    24     2     2\n -7.7216665110619850E-02 a      2253     1    24     2     3\n -2.8798885399279067E-01 a      2254     1    24     2     4\n  3.7454428387915351E+00 a      2255     1    24     2     5\n -1.5625207926251825E+00 a      2256     1    24     2     6\n  3.6660395247444808E+00 a      2257     1    24     2     7\n  2.0253108718040456E+00 a      2258     1    24     2     8\n  1.6318897346220811E+00 a      2259     1    24     2     9\n  2.4800845209015692E+00 a      2260     1    24     2    10\n  1.4907673234653401E-01 a      2261     1    24     2    11\n -4.8613830479267428E-01 a      2262     1    24     2    12\n -6.2019617622102718E-01 a      2263     1    24     2    13\n  2.5952895630277122E+00 a      2264     1    24     2    14\n -4.5829312494493707E-01 a      2265     1    24     2    15\n -2.3487736500391203E+00 a      2266     1    24     2    16\n -3.0197296181118466E-01 a      2267     1    24     2    17\n -2.3095098659235344E-01 a      2268     1    24     2    18\n -3.3608639629945564E-01 a      2269     1    24     2    19\n  6.8582631891122880E-01 a      2270     1    24     2    20\n -5.0043316001326121E-01 a      2271     1    24     2    21\n  1.0373154633440593E-01 a      2272     1    24     2    22\n -1.6204291412423728E+00 a      2273     1    24     2    23\n  1.5638127191591980E+00 a      2274     1    24     2    24\n -2.3309635202853114E+00 a      2275     1    24     2    25\n  2.4489203274966312E-01 a      2276     1    25     2     1\n -2.1518661593071592E-01 a      2277     1    25     2     2\n -5.5802781061846052E-02 a      2278     1    25     2     3\n  4.8845808066633911E-02 a      2279     1    25     2     4\n -1.7557830120404228E-01 a      2280     1    25     2     5\n  2.7192371503339396E-01 a      2281     1    25     2     6\n  5.1576877441197089E-01 a      2282     1    25     2     7\n -2.5099882589234657E-01 a      2283     1    25     2     8\n  3.9307512202972061E-01 a      2284     1    25     2     9\n -1.1210987406922690E+00 a      2285     1    25     2    10\n -1.0439036996834390E-01 a      2286     1    25     2    11\n -4.6783720798261658E-01 a      2287     1    25     2    12\n -3.4722854444840895E-01 a      2288     1    25     2    13\n  3.6029120328851533E-01 a      2289     1    25     2    14\n -2.8984025140998956E-02 a      2290     1    25     2    15\n -2.4076394027143521E-02 a      2291     1    25     2    16\n -3.5643134150827477E-01 a      2292     1    25     2    17\n -8.0475176631190595E-02 a      2293     1    25     2    18\n -4.1056819128214495E-01 a      2294     1    25     2    19\n  7.9766759746990878E-02 a      2295     1    25     2    20\n -6.3351379628206916E-02 a      2296     1    25     2    21\n -6.6416236384591232E-01 a      2297     1    25     2    22\n  9.9799168900512741E-02 a      2298     1    25     2    23\n  3.6809534821907935E-01 a      2299     1    25     2    24\n  4.4938760583598990E-02 a      2300     1    25     2    25\n  1.2254169285344445E+00 b      2301     2     1\n -1.2971586668099495E+00 b      2302     2     2\n  1.5496818967172494E+00 b      2303     2     3\n -5.1016745940541508E+00 b      2304     2     4\n  1.0570990409883480E+01 b      2305     2     5\n -4.5156912340057982E+00 b      2306     2     6\n -5.3447216226080076E+00 b      2307     2     7\n  4.9121474463955411E-01 b      2308     2     8\n  1.8948035234025085E+00 b      2309     2     9\n  8.0589028128011697E-01 b      2310     2    10\n -1.7792287088770824E+00 b      2311     2    11\n  1.4582711867438684E+01 b      2312     2    12\n -1.7367556115635654E+00 b      2313     2    13\n -1.9740162795480241E+00 b      2314     2    14\n -2.4240966432157127E+00 b      2315     2    15\n -2.8599154334878940E+00 b      2316     2    16\n  4.0042881027206061E+00 b      2317     2    17\n -4.2248506318729575E+00 b      2318     2    18\n  4.0200826303003624E-02 b      2319     2    19\n -1.2474151269634015E+00 b      2320     2    20\n -9.2525707564953397E+00 b      2321     2    21\n  3.6900482337635778E+00 b      2322     2    22\n  1.2241959433351147E+01 b      2323     2    23\n -3.6270070547836308E+00 b      2324     2    24\n -9.9424710717210443E-02 b      2325     2    25\n -1.7929412362301902E-01 a      2326     2     1     3     1\n -7.9318720367251710E-02 a      2327     2     2     3     1\n -1.2245497150588677E-01 a      2328     2     3     3     1\n  2.6686957929803099E+00 a      2329     2     4     3     1\n  2.2208281256188907E-02 a      2330     2     5     3     1\n -1.3827880546853433E-01 a      2331     2     6     3     1\n  5.8883707570105491E-02 a      2332     2     7     3     1\n -1.8503473008958521E-01 a      2333     2     8     3     1\n  7.9941146090854662E-02 a      2334     2     9     3     1\n  6.0980780074337042E-02 a      2335     2    10     3     1\n  4.2898647862968903E-01 a      2336     2    11     3     1\n -1.6418700509588654E-02 a      2337     2    12     3     1\n  9.2626066276151567E-02 a      2338     2    13     3     1\n  1.6213121749951970E-01 a      2339     2    14     3     1\n  5.0025887501899446E-01 a      2340     2    15     3     1\n -9.3228633980085102E-02 a      2341     2    16     3     1\n -4.2506309509736678E-01 a      2342     2    17     3     1\n -2.8020236882301058E-01 a      2343     2    18     3     1\n  1.3369952476903810E+00 a      2344     2    19     3     1\n  7.6998543117290666E-02 a      2345     2    20     3     1\n  5.8165502415695283E+00 a      2346     2    21     3     1\n  4.9617644425128343E-01 a      2347     2    22     3     1\n  3.8051021746990116E-01 a      2348     2    23     3     1\n  1.1951241138280733E-01 a      2349     2    24     3     1\n  1.3087209279691459E-01 a      2350     2    25     3     1\n -2.6815621704168309E+00 b      2351     3     1\n"
  },
  {
    "path": "examples/potentials/DMABN_SCAN/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -3.6581036498775639E+00\nconv_energy   1.1608720067118788E+03\nconv_length   3.8128564085005848E+01\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              3              # Number of elements.\nelements                        C N H          # Specification of elements.\ncutoff_type                     6 0.0          # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\nrandom_seed 987654321\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\njacobian_mode                   1\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntask_batch_size_energy          1\ntask_batch_size_force           1\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints                5             # Write energy comparison.\nwrite_trainforces                5             # Write force comparison.\nwrite_weights_epoch              5             # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n## ####################\n## # GRADIENT DESCENT #\n## ####################\n## gradient_type                   0              # Gradient descent type (0 = Fixed step size).\n## gradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\nsymfunction_short C 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 C -1.30E+01 1.30E+01 p2\nsymfunction_short C 20 C -1.10E+01 1.10E+01 p2\nsymfunction_short C 20 C -9.00E+00 9.00E+00 p2\nsymfunction_short C 20 C -7.00E+00 7.00E+00 p2\nsymfunction_short C 20 C -5.00E+00 5.00E+00 p2\nsymfunction_short C 20 C -3.00E+00 3.00E+00 p2\nsymfunction_short C 20 C 0.00E+00 6.00E+00 p2\nsymfunction_short C 20 C 3.00E+00 9.00E+00 p2\nsymfunction_short C 20 C 6.00E+00 1.20E+01 p2\nsymfunction_short C 20 C 9.00E+00 1.50E+01 p2\n \nsymfunction_short C 20 N -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 N -1.30E+01 1.30E+01 p2\nsymfunction_short C 20 N -1.10E+01 1.10E+01 p2\nsymfunction_short C 20 N -9.00E+00 9.00E+00 p2\nsymfunction_short C 20 N -7.00E+00 7.00E+00 p2\nsymfunction_short C 20 N -5.00E+00 5.00E+00 p2\nsymfunction_short C 20 N -3.00E+00 3.00E+00 p2\nsymfunction_short C 20 N 0.00E+00 6.00E+00 p2\nsymfunction_short C 20 N 3.00E+00 9.00E+00 p2\nsymfunction_short C 20 N 6.00E+00 1.20E+01 p2\nsymfunction_short C 20 N 9.00E+00 1.50E+01 p2\n \nsymfunction_short C 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 H -1.30E+01 1.30E+01 p2\nsymfunction_short C 20 H -1.10E+01 1.10E+01 p2\nsymfunction_short C 20 H -9.00E+00 9.00E+00 p2\nsymfunction_short C 20 H -7.00E+00 7.00E+00 p2\nsymfunction_short C 20 H -5.00E+00 5.00E+00 p2\nsymfunction_short C 20 H -3.00E+00 3.00E+00 p2\nsymfunction_short C 20 H 0.00E+00 6.00E+00 p2\nsymfunction_short C 20 H 3.00E+00 9.00E+00 p2\nsymfunction_short C 20 H 6.00E+00 1.20E+01 p2\nsymfunction_short C 20 H 9.00E+00 1.50E+01 p2\n \n \nsymfunction_short N 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short N 20 C -1.30E+01 1.30E+01 p2\nsymfunction_short N 20 C -1.10E+01 1.10E+01 p2\nsymfunction_short N 20 C -9.00E+00 9.00E+00 p2\nsymfunction_short N 20 C -7.00E+00 7.00E+00 p2\nsymfunction_short N 20 C -5.00E+00 5.00E+00 p2\nsymfunction_short N 20 C -3.00E+00 3.00E+00 p2\nsymfunction_short N 20 C 0.00E+00 6.00E+00 p2\nsymfunction_short N 20 C 3.00E+00 9.00E+00 p2\nsymfunction_short N 20 C 6.00E+00 1.20E+01 p2\nsymfunction_short N 20 C 9.00E+00 1.50E+01 p2\n \nsymfunction_short N 20 N -1.50E+01 1.50E+01 p2\nsymfunction_short N 20 N -1.30E+01 1.30E+01 p2\n# symfunction_short  N   28  N      -1.10E+01  1.10E+01\n# symfunction_short  N   28  N      -9.00E+00  9.00E+00\n# symfunction_short  N   28  N      -7.00E+00  7.00E+00\n# symfunction_short  N   28  N      -5.00E+00  5.00E+00\n# symfunction_short  N   28  N      -3.00E+00  3.00E+00\n# symfunction_short  N   28  N       0.00E+00  6.00E+00\n# symfunction_short  N   28  N       3.00E+00  9.00E+00\n# symfunction_short  N   28  N       6.00E+00  1.20E+01\nsymfunction_short N 20 N 9.00E+00 1.50E+01 p2\n \nsymfunction_short N 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short N 20 H -1.30E+01 1.30E+01 p2\nsymfunction_short N 20 H -1.10E+01 1.10E+01 p2\nsymfunction_short N 20 H -9.00E+00 9.00E+00 p2\nsymfunction_short N 20 H -7.00E+00 7.00E+00 p2\nsymfunction_short N 20 H -5.00E+00 5.00E+00 p2\n# symfunction_short  N   28  H      -3.00E+00  3.00E+00\nsymfunction_short N 20 H 0.00E+00 6.00E+00 p2\nsymfunction_short N 20 H 3.00E+00 9.00E+00 p2\nsymfunction_short N 20 H 6.00E+00 1.20E+01 p2\nsymfunction_short N 20 H 9.00E+00 1.50E+01 p2\n \n \nsymfunction_short H 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 C -1.30E+01 1.30E+01 p2\nsymfunction_short H 20 C -1.10E+01 1.10E+01 p2\nsymfunction_short H 20 C -9.00E+00 9.00E+00 p2\nsymfunction_short H 20 C -7.00E+00 7.00E+00 p2\nsymfunction_short H 20 C -5.00E+00 5.00E+00 p2\nsymfunction_short H 20 C -3.00E+00 3.00E+00 p2\nsymfunction_short H 20 C 0.00E+00 6.00E+00 p2\nsymfunction_short H 20 C 3.00E+00 9.00E+00 p2\nsymfunction_short H 20 C 6.00E+00 1.20E+01 p2\nsymfunction_short H 20 C 9.00E+00 1.50E+01 p2\n \nsymfunction_short H 20 N -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 N -1.30E+01 1.30E+01 p2\nsymfunction_short H 20 N -1.10E+01 1.10E+01 p2\nsymfunction_short H 20 N -9.00E+00 9.00E+00 p2\nsymfunction_short H 20 N -7.00E+00 7.00E+00 p2\nsymfunction_short H 20 N -5.00E+00 5.00E+00 p2\n# symfunction_short  H   28  N      -3.00E+00  3.00E+00\nsymfunction_short H 20 N 0.00E+00 6.00E+00 p2\nsymfunction_short H 20 N 3.00E+00 9.00E+00 p2\nsymfunction_short H 20 N 6.00E+00 1.20E+01 p2\nsymfunction_short H 20 N 9.00E+00 1.50E+01 p2\n \nsymfunction_short H 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 H -1.30E+01 1.30E+01 p2\nsymfunction_short H 20 H -1.10E+01 1.10E+01 p2\nsymfunction_short H 20 H -9.00E+00 9.00E+00 p2\nsymfunction_short H 20 H -7.00E+00 7.00E+00 p2\nsymfunction_short H 20 H -5.00E+00 5.00E+00 p2\nsymfunction_short H 20 H -3.00E+00 3.00E+00 p2\nsymfunction_short H 20 H 0.00E+00 6.00E+00 p2\nsymfunction_short H 20 H 3.00E+00 9.00E+00 p2\nsymfunction_short H 20 H 6.00E+00 1.20E+01 p2\nsymfunction_short H 20 H 9.00E+00 1.50E+01 p2\n \n \nsymfunction_short C 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 C C -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 C C -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C C -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C C -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C C -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short C 22 C N -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C N -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C N -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C N -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C N -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 C N -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 C N -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C N -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C N -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C N -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 C N 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 C N 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C N 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short C 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 C H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 C H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short C 22 C H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \nsymfunction_short C 22 N N -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 N N -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 N N -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 N N -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 N N -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 N N -1.50E+01 1.50E+01 49.10 169.10 p2\n# symfunction_short  C   89  N   N   -1.30E+01  -90.00   90.00  1.30E+01\nsymfunction_short C 22 N N -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 N N -1.30E+01 1.30E+01 0.00 180.00 p2\n# symfunction_short  C   89  N   N   -1.30E+01    0.00  120.00  1.30E+01\nsymfunction_short C 22 N N -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 N N -1.30E+01 1.30E+01 49.10 169.10 p2\n# symfunction_short  C   89  N   N   -1.10E+01  -90.00   90.00  1.10E+01\nsymfunction_short C 22 N N -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 N N -1.10E+01 1.10E+01 0.00 180.00 p2\n# symfunction_short  C   89  N   N   -1.10E+01    0.00  120.00  1.10E+01\nsymfunction_short C 22 N N -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 N N -1.10E+01 1.10E+01 49.10 169.10 p2\n# symfunction_short  C   89  N   N   -9.00E+00  -90.00   90.00  9.00E+00\nsymfunction_short C 22 N N -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 N N -9.00E+00 9.00E+00 0.00 180.00 p2\n# symfunction_short  C   89  N   N   -9.00E+00    0.00  120.00  9.00E+00\nsymfunction_short C 22 N N -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 N N -9.00E+00 9.00E+00 49.10 169.10 p2\n# symfunction_short  C   89  N   N   -7.00E+00  -90.00   90.00  7.00E+00\n# symfunction_short  C   89  N   N   -7.00E+00   90.00  270.00  7.00E+00\n# symfunction_short  C   89  N   N   -7.00E+00    0.00  180.00  7.00E+00\n# symfunction_short  C   89  N   N   -7.00E+00    0.00  120.00  7.00E+00\n# symfunction_short  C   89  N   N   -7.00E+00   60.00  180.00  7.00E+00\n# symfunction_short  C   89  N   N   -7.00E+00   49.10  169.10  7.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00  -90.00   90.00  5.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00   90.00  270.00  5.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00    0.00  180.00  5.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00    0.00  120.00  5.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00   60.00  180.00  5.00E+00\n# symfunction_short  C   89  N   N   -5.00E+00   49.10  169.10  5.00E+00\n# symfunction_short  C   89  N   N    0.00E+00  -90.00   90.00  1.00E+01\nsymfunction_short C 22 N N 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 N N 0.00E+00 1.00E+01 0.00 180.00 p2\n# symfunction_short  C   89  N   N    0.00E+00    0.00  120.00  1.00E+01\nsymfunction_short C 22 N N 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 N N 0.00E+00 1.00E+01 49.10 169.10 p2\n# symfunction_short  C   89  N   N    2.50E+00  -90.00   90.00  1.25E+01\nsymfunction_short C 22 N N 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 N N 2.50E+00 1.25E+01 0.00 180.00 p2\n# symfunction_short  C   89  N   N    2.50E+00    0.00  120.00  1.25E+01\nsymfunction_short C 22 N N 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 N N 2.50E+00 1.25E+01 49.10 169.10 p2\n# symfunction_short  C   89  N   N    5.00E+00  -90.00   90.00  1.50E+01\nsymfunction_short C 22 N N 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 N N 5.00E+00 1.50E+01 0.00 180.00 p2\n# symfunction_short  C   89  N   N    5.00E+00    0.00  120.00  1.50E+01\nsymfunction_short C 22 N N 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 N N 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short C 22 N H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 N H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 N H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 N H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 N H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 N H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 N H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 N H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short C 22 N H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short C 22 N H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 N H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 N H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 N H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \nsymfunction_short C 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short C 22 H H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short C 22 H H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short C 22 H H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short C 22 H H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short C 22 H H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \n \nsymfunction_short N 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short N 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short N 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short N 22 C C -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short N 22 C C -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C C -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C C -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C C -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short N 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short N 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short N 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2\n# symfunction_short  N   89  C   C    5.00E+00   90.00  270.00  1.50E+01\nsymfunction_short N 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2\n# symfunction_short  N   89  C   C    5.00E+00   60.00  180.00  1.50E+01\n# symfunction_short  N   89  C   C    5.00E+00   49.10  169.10  1.50E+01\n \nsymfunction_short N 22 C N -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short N 22 C N -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short N 22 C N -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C N -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 C N -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 C N -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short N 22 C N -1.30E+01 1.30E+01 49.10 169.10 p2\n# symfunction_short  N   89  C   N   -1.10E+01  -90.00   90.00  1.10E+01\n# symfunction_short  N   89  C   N   -1.10E+01   90.00  270.00  1.10E+01\n# symfunction_short  N   89  C   N   -1.10E+01    0.00  180.00  1.10E+01\n# symfunction_short  N   89  C   N   -1.10E+01    0.00  120.00  1.10E+01\n# symfunction_short  N   89  C   N   -1.10E+01   60.00  180.00  1.10E+01\n# symfunction_short  N   89  C   N   -1.10E+01   49.10  169.10  1.10E+01\n# symfunction_short  N   89  C   N   -9.00E+00  -90.00   90.00  9.00E+00\n# symfunction_short  N   89  C   N   -9.00E+00   90.00  270.00  9.00E+00\n# symfunction_short  N   89  C   N   -9.00E+00    0.00  180.00  9.00E+00\n# symfunction_short  N   89  C   N   -9.00E+00    0.00  120.00  9.00E+00\n# symfunction_short  N   89  C   N   -9.00E+00   60.00  180.00  9.00E+00\n# symfunction_short  N   89  C   N   -9.00E+00   49.10  169.10  9.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00  -90.00   90.00  7.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00   90.00  270.00  7.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00    0.00  180.00  7.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00    0.00  120.00  7.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00   60.00  180.00  7.00E+00\n# symfunction_short  N   89  C   N   -7.00E+00   49.10  169.10  7.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00  -90.00   90.00  5.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00   90.00  270.00  5.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00    0.00  180.00  5.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00    0.00  120.00  5.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00   60.00  180.00  5.00E+00\n# symfunction_short  N   89  C   N   -5.00E+00   49.10  169.10  5.00E+00\n# symfunction_short  N   89  C   N    0.00E+00  -90.00   90.00  1.00E+01\n# symfunction_short  N   89  C   N    0.00E+00   90.00  270.00  1.00E+01\n# symfunction_short  N   89  C   N    0.00E+00    0.00  180.00  1.00E+01\n# symfunction_short  N   89  C   N    0.00E+00    0.00  120.00  1.00E+01\n# symfunction_short  N   89  C   N    0.00E+00   60.00  180.00  1.00E+01\n# symfunction_short  N   89  C   N    0.00E+00   49.10  169.10  1.00E+01\nsymfunction_short N 22 C N 2.50E+00 1.25E+01 -90.00 90.00 p2\n# symfunction_short  N   89  C   N    2.50E+00   90.00  270.00  1.25E+01\nsymfunction_short N 22 C N 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short N 22 C N 2.50E+00 1.25E+01 0.00 120.00 p2\n# symfunction_short  N   89  C   N    2.50E+00   60.00  180.00  1.25E+01\n# symfunction_short  N   89  C   N    2.50E+00   49.10  169.10  1.25E+01\nsymfunction_short N 22 C N 5.00E+00 1.50E+01 -90.00 90.00 p2\n# symfunction_short  N   89  C   N    5.00E+00   90.00  270.00  1.50E+01\nsymfunction_short N 22 C N 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C N 5.00E+00 1.50E+01 0.00 120.00 p2\n# symfunction_short  N   89  C   N    5.00E+00   60.00  180.00  1.50E+01\n# symfunction_short  N   89  C   N    5.00E+00   49.10  169.10  1.50E+01\n \nsymfunction_short N 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short N 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short N 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short N 22 C H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short N 22 C H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short N 22 C H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short N 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short N 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short N 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2\n# symfunction_short  N   89  C   H    5.00E+00   90.00  270.00  1.50E+01\nsymfunction_short N 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2\n# symfunction_short  N   89  C   H    5.00E+00   60.00  180.00  1.50E+01\nsymfunction_short N 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \n# symfunction_short  N   89  N   N   -1.50E+01  -90.00   90.00  1.50E+01\n# symfunction_short  N   89  N   N   -1.50E+01   90.00  270.00  1.50E+01\n# symfunction_short  N   89  N   N   -1.50E+01    0.00  180.00  1.50E+01\n# symfunction_short  N   89  N   N   -1.50E+01    0.00  120.00  1.50E+01\n# symfunction_short  N   89  N   N   -1.50E+01   60.00  180.00  1.50E+01\n# symfunction_short  N   89  N   N   -1.50E+01   49.10  169.10  1.50E+01\n# symfunction_short  N   89  N   N   -1.30E+01  -90.00   90.00  1.30E+01\n# symfunction_short  N   89  N   N   -1.30E+01   90.00  270.00  1.30E+01\n# symfunction_short  N   89  N   N   -1.30E+01    0.00  180.00  1.30E+01\n# symfunction_short  N   89  N   N   -1.30E+01    0.00  120.00  1.30E+01\n# symfunction_short  N   89  N   N   -1.30E+01   60.00  180.00  1.30E+01\n# symfunction_short  N   89  N   N   -1.30E+01   49.10  169.10  1.30E+01\n# symfunction_short  N   89  N   N   -1.10E+01  -90.00   90.00  1.10E+01\n# symfunction_short  N   89  N   N   -1.10E+01   90.00  270.00  1.10E+01\n# symfunction_short  N   89  N   N   -1.10E+01    0.00  180.00  1.10E+01\n# symfunction_short  N   89  N   N   -1.10E+01    0.00  120.00  1.10E+01\n# symfunction_short  N   89  N   N   -1.10E+01   60.00  180.00  1.10E+01\n# symfunction_short  N   89  N   N   -1.10E+01   49.10  169.10  1.10E+01\n# symfunction_short  N   89  N   N   -9.00E+00  -90.00   90.00  9.00E+00\n# symfunction_short  N   89  N   N   -9.00E+00   90.00  270.00  9.00E+00\n# symfunction_short  N   89  N   N   -9.00E+00    0.00  180.00  9.00E+00\n# symfunction_short  N   89  N   N   -9.00E+00    0.00  120.00  9.00E+00\n# symfunction_short  N   89  N   N   -9.00E+00   60.00  180.00  9.00E+00\n# symfunction_short  N   89  N   N   -9.00E+00   49.10  169.10  9.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00  -90.00   90.00  7.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00   90.00  270.00  7.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00    0.00  180.00  7.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00    0.00  120.00  7.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00   60.00  180.00  7.00E+00\n# symfunction_short  N   89  N   N   -7.00E+00   49.10  169.10  7.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00  -90.00   90.00  5.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00   90.00  270.00  5.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00    0.00  180.00  5.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00    0.00  120.00  5.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00   60.00  180.00  5.00E+00\n# symfunction_short  N   89  N   N   -5.00E+00   49.10  169.10  5.00E+00\n# symfunction_short  N   89  N   N    0.00E+00  -90.00   90.00  1.00E+01\n# symfunction_short  N   89  N   N    0.00E+00   90.00  270.00  1.00E+01\n# symfunction_short  N   89  N   N    0.00E+00    0.00  180.00  1.00E+01\n# symfunction_short  N   89  N   N    0.00E+00    0.00  120.00  1.00E+01\n# symfunction_short  N   89  N   N    0.00E+00   60.00  180.00  1.00E+01\n# symfunction_short  N   89  N   N    0.00E+00   49.10  169.10  1.00E+01\n# symfunction_short  N   89  N   N    2.50E+00  -90.00   90.00  1.25E+01\n# symfunction_short  N   89  N   N    2.50E+00   90.00  270.00  1.25E+01\n# symfunction_short  N   89  N   N    2.50E+00    0.00  180.00  1.25E+01\n# symfunction_short  N   89  N   N    2.50E+00    0.00  120.00  1.25E+01\n# symfunction_short  N   89  N   N    2.50E+00   60.00  180.00  1.25E+01\n# symfunction_short  N   89  N   N    2.50E+00   49.10  169.10  1.25E+01\n# symfunction_short  N   89  N   N    5.00E+00  -90.00   90.00  1.50E+01\n# symfunction_short  N   89  N   N    5.00E+00   90.00  270.00  1.50E+01\n# symfunction_short  N   89  N   N    5.00E+00    0.00  180.00  1.50E+01\n# symfunction_short  N   89  N   N    5.00E+00    0.00  120.00  1.50E+01\n# symfunction_short  N   89  N   N    5.00E+00   60.00  180.00  1.50E+01\n# symfunction_short  N   89  N   N    5.00E+00   49.10  169.10  1.50E+01\n \nsymfunction_short N 22 N H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short N 22 N H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short N 22 N H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 N H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 N H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 N H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short N 22 N H -1.30E+01 1.30E+01 49.10 169.10 p2\n# symfunction_short  N   89  N   H   -1.10E+01  -90.00   90.00  1.10E+01\n# symfunction_short  N   89  N   H   -1.10E+01   90.00  270.00  1.10E+01\n# symfunction_short  N   89  N   H   -1.10E+01    0.00  180.00  1.10E+01\n# symfunction_short  N   89  N   H   -1.10E+01    0.00  120.00  1.10E+01\n# symfunction_short  N   89  N   H   -1.10E+01   60.00  180.00  1.10E+01\n# symfunction_short  N   89  N   H   -1.10E+01   49.10  169.10  1.10E+01\n# symfunction_short  N   89  N   H   -9.00E+00  -90.00   90.00  9.00E+00\n# symfunction_short  N   89  N   H   -9.00E+00   90.00  270.00  9.00E+00\n# symfunction_short  N   89  N   H   -9.00E+00    0.00  180.00  9.00E+00\n# symfunction_short  N   89  N   H   -9.00E+00    0.00  120.00  9.00E+00\n# symfunction_short  N   89  N   H   -9.00E+00   60.00  180.00  9.00E+00\n# symfunction_short  N   89  N   H   -9.00E+00   49.10  169.10  9.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00  -90.00   90.00  7.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00   90.00  270.00  7.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00    0.00  180.00  7.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00    0.00  120.00  7.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00   60.00  180.00  7.00E+00\n# symfunction_short  N   89  N   H   -7.00E+00   49.10  169.10  7.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00  -90.00   90.00  5.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00   90.00  270.00  5.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00    0.00  180.00  5.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00    0.00  120.00  5.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00   60.00  180.00  5.00E+00\n# symfunction_short  N   89  N   H   -5.00E+00   49.10  169.10  5.00E+00\n# symfunction_short  N   89  N   H    0.00E+00  -90.00   90.00  1.00E+01\n# symfunction_short  N   89  N   H    0.00E+00   90.00  270.00  1.00E+01\n# symfunction_short  N   89  N   H    0.00E+00    0.00  180.00  1.00E+01\n# symfunction_short  N   89  N   H    0.00E+00    0.00  120.00  1.00E+01\n# symfunction_short  N   89  N   H    0.00E+00   60.00  180.00  1.00E+01\n# symfunction_short  N   89  N   H    0.00E+00   49.10  169.10  1.00E+01\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short N 22 N H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short N 22 N H 5.00E+00 1.50E+01 -90.00 90.00 p2\n# symfunction_short  N   89  N   H    5.00E+00   90.00  270.00  1.50E+01\nsymfunction_short N 22 N H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 N H 5.00E+00 1.50E+01 0.00 120.00 p2\n# symfunction_short  N   89  N   H    5.00E+00   60.00  180.00  1.50E+01\n# symfunction_short  N   89  N   H    5.00E+00   49.10  169.10  1.50E+01\n \n \nsymfunction_short N 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short N 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short N 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short N 22 H H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short N 22 H H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short N 22 H H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short N 22 H H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short N 22 H H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short N 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short N 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short N 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2\n# symfunction_short  N   89  H   H    5.00E+00   90.00  270.00  1.50E+01\nsymfunction_short N 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short N 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short N 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short N 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \n \nsymfunction_short H 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 C C -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 C C -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C C -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C C -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C C -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short H 22 C N -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C N -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C N -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C N -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C N -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 C N -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 C N -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C N -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C N -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C N -5.00E+00 5.00E+00 -90.00 90.00 p2\n# symfunction_short  H   89  C   N   -5.00E+00   90.00  270.00  5.00E+00\nsymfunction_short H 22 C N -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C N -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C N -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C N -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 C N 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 C N 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C N 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short H 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 C H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 C H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short H 22 C H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \nsymfunction_short H 22 N N -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 N N -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 N N -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 N N -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 N N -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 N N -1.50E+01 1.50E+01 49.10 169.10 p2\n# symfunction_short  H   89  N   N   -1.30E+01  -90.00   90.00  1.30E+01\nsymfunction_short H 22 N N -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 N N -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 N N -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 N N -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 N N -1.30E+01 1.30E+01 49.10 169.10 p2\n# symfunction_short  H   89  N   N   -1.10E+01  -90.00   90.00  1.10E+01\nsymfunction_short H 22 N N -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 N N -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 N N -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 N N -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 N N -1.10E+01 1.10E+01 49.10 169.10 p2\n# symfunction_short  H   89  N   N   -9.00E+00  -90.00   90.00  9.00E+00\n# symfunction_short  H   89  N   N   -9.00E+00   90.00  270.00  9.00E+00\nsymfunction_short H 22 N N -9.00E+00 9.00E+00 0.00 180.00 p2\n# symfunction_short  H   89  N   N   -9.00E+00    0.00  120.00  9.00E+00\nsymfunction_short H 22 N N -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 N N -9.00E+00 9.00E+00 49.10 169.10 p2\n# symfunction_short  H   89  N   N   -7.00E+00  -90.00   90.00  7.00E+00\n# symfunction_short  H   89  N   N   -7.00E+00   90.00  270.00  7.00E+00\n# symfunction_short  H   89  N   N   -7.00E+00    0.00  180.00  7.00E+00\n# symfunction_short  H   89  N   N   -7.00E+00    0.00  120.00  7.00E+00\n# symfunction_short  H   89  N   N   -7.00E+00   60.00  180.00  7.00E+00\n# symfunction_short  H   89  N   N   -7.00E+00   49.10  169.10  7.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00  -90.00   90.00  5.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00   90.00  270.00  5.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00    0.00  180.00  5.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00    0.00  120.00  5.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00   60.00  180.00  5.00E+00\n# symfunction_short  H   89  N   N   -5.00E+00   49.10  169.10  5.00E+00\n# symfunction_short  H   89  N   N    0.00E+00  -90.00   90.00  1.00E+01\nsymfunction_short H 22 N N 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 N N 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 N N 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 N N 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 N N 0.00E+00 1.00E+01 49.10 169.10 p2\n# symfunction_short  H   89  N   N    2.50E+00  -90.00   90.00  1.25E+01\nsymfunction_short H 22 N N 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 N N 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 N N 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 N N 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 N N 2.50E+00 1.25E+01 49.10 169.10 p2\n# symfunction_short  H   89  N   N    5.00E+00  -90.00   90.00  1.50E+01\nsymfunction_short H 22 N N 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 N N 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 N N 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 N N 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 N N 5.00E+00 1.50E+01 49.10 169.10 p2\n \nsymfunction_short H 22 N H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 N H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 N H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 N H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 N H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 N H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 N H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 N H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short H 22 N H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short H 22 N H -5.00E+00 5.00E+00 -90.00 90.00 p2\n# symfunction_short  H   89  N   H   -5.00E+00   90.00  270.00  5.00E+00\nsymfunction_short H 22 N H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short H 22 N H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short H 22 N H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short H 22 N H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 N H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 N H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 N H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \nsymfunction_short H 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 90.00 270.00 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 0.00 180.00 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 0.00 120.00 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 60.00 180.00 p2\nsymfunction_short H 22 H H -1.30E+01 1.30E+01 49.10 169.10 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 90.00 270.00 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 0.00 180.00 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 0.00 120.00 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 60.00 180.00 p2\nsymfunction_short H 22 H H -1.10E+01 1.10E+01 49.10 169.10 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 90.00 270.00 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 0.00 180.00 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 0.00 120.00 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 60.00 180.00 p2\nsymfunction_short H 22 H H -9.00E+00 9.00E+00 49.10 169.10 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 90.00 270.00 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 0.00 180.00 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 0.00 120.00 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 60.00 180.00 p2\nsymfunction_short H 22 H H -7.00E+00 7.00E+00 49.10 169.10 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 -90.00 90.00 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 90.00 270.00 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 0.00 180.00 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 0.00 120.00 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 60.00 180.00 p2\nsymfunction_short H 22 H H -5.00E+00 5.00E+00 49.10 169.10 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2\n \n \n \n"
  },
  {
    "path": "examples/potentials/DMABN_SCAN/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   0.0000000000000000E+00   8.9256522521687920E-03   2.1193691142807063E-05   2.8186351799893859E-04\n         1          2   0.0000000000000000E+00   9.0700888046097716E-01   2.8576381266700673E-01   2.1092873186201827E-01\n         1          3   3.0195033033699081E-02   3.7500074021719896E+00   1.8578479493308084E+00   9.1152666615775380E-01\n         1          4   6.6031505277643232E-02   2.0452529717163346E+00   1.0150425459608330E+00   5.0268744284813327E-01\n         1          5   3.2377304639348359E-01   3.2661719444302033E+00   1.8061799390235969E+00   7.5936163395571532E-01\n         1          6   2.4304331955263980E-01   5.7086975789220835E+00   2.5143121459887037E+00   9.5683418222321315E-01\n         1          7   6.8396772830898045E-01   4.2572589291083114E+00   2.7058959418894597E+00   9.7181375055539310E-01\n         1          8   6.9462380456302553E-01   6.5958770747160260E+00   3.1123984883562117E+00   1.2300024965727658E+00\n         1          9   1.2365227913043952E+00   5.1633496520728004E+00   3.6519600786058115E+00   1.0660271704060633E+00\n         1         10   2.0502650228337305E+00   5.9127524978644335E+00   4.5514758691484127E+00   1.0465915668934862E+00\n         1         11   0.0000000000000000E+00   4.8920182697896291E+00   1.4925322646477586E+00   1.2727208114747384E+00\n         1         12   1.9588702750826026E-02   3.5496915700992948E-01   1.7273156425717565E-01   4.8652622105060592E-02\n         1         13   4.6358856026644546E-01   9.6690906167814550E-01   6.9550684680044461E-01   7.4338483356896953E-02\n         1         14   7.1353898653629000E-01   3.1849472187417098E+00   1.6879270299619309E+00   7.3464774899133045E-01\n         1         15   8.0368406740490139E-01   2.0894662819874230E+00   1.3113934265207201E+00   3.3650418449605968E-01\n         1         16   1.2310809747155158E+00   3.3253654844084837E+00   2.1733230149165195E+00   5.7787407253961065E-01\n         1         17   1.5172411050519461E+00   5.2278787600105705E+00   3.4286565417505157E+00   6.8203135488140421E-01\n         1         18   1.8394036336993085E+00   4.6564347379688744E+00   3.1483480717046954E+00   7.7723626979967286E-01\n         1         19   9.9272922746128922E-01   3.6349130647862249E+00   2.4633466894021052E+00   5.8568318205296166E-01\n         1         20   2.5505066649359227E+00   5.7297731231465621E+00   4.0998993263923253E+00   8.7962087570568570E-01\n         1         21   3.3167631098840449E+00   6.5247442856998648E+00   4.9570066366846568E+00   8.8548204330098168E-01\n         1         22   0.0000000000000000E+00   2.5903496176917691E+00   1.0502460832108176E+00   6.8414700439823239E-01\n         1         23   0.0000000000000000E+00   1.8064536102326323E-01   3.5807532162519209E-02   3.6740814102621547E-02\n         1         24   0.0000000000000000E+00   9.7573019676424011E-01   5.0027604575569895E-01   3.5080285646510789E-01\n         1         25   0.0000000000000000E+00   5.1735495670069254E-01   2.4633689247568696E-01   1.5583037665319732E-01\n         1         26   1.3269946164258806E-02   7.1369334226933412E-01   4.6094245709230169E-01   1.9266971125633234E-01\n         1         27   2.4269803235760112E-02   1.1201422743902167E+00   4.8167090940876256E-01   3.3122216503046131E-01\n         1         28   1.8134224686757072E-01   8.2028423905705539E-01   6.3571039957431197E-01   1.4662055276562944E-01\n         1         29   0.0000000000000000E+00   1.7642468335508221E+00   3.0857098415949585E-01   4.3979869171000885E-01\n         1         30   4.7464601069293866E-01   9.2523509369006052E-01   7.8296448282118791E-01   6.4668569705626219E-02\n         1         31   7.6518946527721554E-01   1.1576282843693706E+00   9.0830683216051145E-01   4.9901597910281967E-02\n         1         32   0.0000000000000000E+00   9.9999987613656682E-01   1.8184832090165368E-01   2.5959166866523525E-01\n         1         33   0.0000000000000000E+00   2.4113158016025486E-02   4.8788699563846669E-03   4.6046591491055670E-03\n         1         34   0.0000000000000000E+00   1.2436276707645036E-01   2.5590225337958485E-02   2.4645414716438250E-02\n         1         35   0.0000000000000000E+00   1.9879405508320028E-01   2.6232883072168096E-02   2.7697748002688833E-02\n         1         36   0.0000000000000000E+00   1.3158829490748458E-01   8.6045336377654283E-03   1.5161496743767990E-02\n         1         37  -1.3213620967481957E-17   1.3875009458327800E-01   7.3915004909242367E-03   1.5719867803312585E-02\n         1         38   0.0000000000000000E+00   1.0428501305427620E-01   3.1018269296963262E-03   8.4057852991212094E-03\n         1         39   0.0000000000000000E+00   1.8610676045893954E-01   5.1707874664921820E-02   3.9484071181107978E-02\n         1         40   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1.5131104833674924E-01   7.2653078529240722E-01   3.3312243956074661E-01   8.0660084857515899E-02\n         3        150   6.1898490242672417E-02   3.2651093305998635E-01   1.3886755237398829E-01   3.5651372900497816E-02\n         3        151   0.0000000000000000E+00   1.5031053204378248E-02   1.9020118001833359E-03   2.2208604232359618E-03\n         3        152   0.0000000000000000E+00   6.4241302263013583E-02   5.1163399896796092E-03   7.8288521731106273E-03\n         3        153   0.0000000000000000E+00   5.2405091512168001E-01   2.0904800194072842E-01   2.1084918680293815E-01\n         3        154   0.0000000000000000E+00   6.1690299265384618E-01   2.4331345453505185E-01   2.4544812102548538E-01\n         3        155   0.0000000000000000E+00   6.5134520600413293E-01   2.5299712497946958E-01   2.5538741315708724E-01\n         3        156   0.0000000000000000E+00   1.8389263535977701E-01   5.0159125634532946E-02   5.3064424085919437E-02\n         3        157   8.7734262651493283E-02   3.5196973667162923E-01   2.0095697162308601E-01   6.3395415028838900E-02\n         3        158   2.9473194885637119E-05   5.3379709989904256E-01   1.7830178486140599E-01   1.7743241522941827E-01\n         3        159   1.0818297187750856E-05   1.9943903895152408E+00   8.4238911060042276E-01   8.4329837474336089E-01\n         3        160   0.0000000000000000E+00   2.1110251976520478E+00   8.7181286991137774E-01   8.7470226337795931E-01\n         3        161   0.0000000000000000E+00   2.1604234952467798E+00   8.9886590369767938E-01   9.0107000285735661E-01\n         3        162   0.0000000000000000E+00   7.5845301941020926E-01   2.4191219705372846E-01   2.5243569939496613E-01\n         3        163   5.0942647523115192E-01   1.1780505265479460E+00   8.0202708281168422E-01   1.4255860090335176E-01\n         3        164   4.6458845436134606E-02   1.5179103906171585E+00   6.0969749552074615E-01   5.1065962620097738E-01\n         3        165   1.7337927152011788E-02   3.9106341432939393E+00   1.6747672471758837E+00   1.6370186590575673E+00\n         3        166   0.0000000000000000E+00   3.9396694026417740E+00   1.5591498779303730E+00   1.5666305827896807E+00\n         3        167   0.0000000000000000E+00   4.0138344159306127E+00   1.6037920844796403E+00   1.6087180359905053E+00\n         3        168   0.0000000000000000E+00   1.5091893709735424E+00   5.0180822772966394E-01   5.2309052312605542E-01\n         3        169   2.5264361242029407E+00   5.8548795458333283E+00   4.0641393448548868E+00   1.0446504518677489E+00\n         3        170   7.5175412481206938E-01   6.0491915894633328E+00   2.7912046359913494E+00   1.6908607007556695E+00\n         3        171   3.1302661987763947E-01   7.3675356257548472E+00   3.3076133821917959E+00   2.8309557463925108E+00\n         3        172   0.0000000000000000E+00   5.6036572770595763E+00   2.0525279109461891E+00   2.0779545144509575E+00\n         3        173   0.0000000000000000E+00   5.4974091121215070E+00   2.1147903042361587E+00   2.1326037973653307E+00\n         3        174   0.0000000000000000E+00   2.4256329144693147E+00   7.8084033321832080E-01   8.1763163370647507E-01\n         3        175   1.3759613228806920E+00   2.6911206594478072E+00   1.9736723956634545E+00   3.2121410143533713E-01\n         3        176   2.1745134785617978E-01   2.9128177728750613E+00   1.2780220510262488E+00   9.1012167714547443E-01\n         3        177   8.4762323410835380E-02   6.1449273966047970E+00   2.6749047972120317E+00   2.5254668585911135E+00\n         3        178   0.0000000000000000E+00   5.8510814087087120E+00   2.3062870491808658E+00   2.3194820161549310E+00\n         3        179   0.0000000000000000E+00   5.9633131534037949E+00   2.3803153698686099E+00   2.3884251146339945E+00\n         3        180   0.0000000000000000E+00   2.3175610530139714E+00   7.7770513762542393E-01   8.1094980716443343E-01\n         3        181   4.4730762478889803E+00   7.6504678370803481E+00   5.8793945412588071E+00   9.3399157619631756E-01\n         3        182   1.9804489718609235E+00   3.2552843606719595E+00   2.5381448797134913E+00   1.7602861977611073E-01\n         3        183   8.3752582631440531E-01   1.5655828654525372E+00   1.2011454344168695E+00   1.1082134775619010E-01\n         3        184   0.0000000000000000E+00   7.1482854541392360E-02   1.0240183460962853E-02   1.2609394975938428E-02\n         3        185   0.0000000000000000E+00   6.4799546548227477E-02   7.9804834229192240E-03   1.1062346269159968E-02\n         3        186   0.0000000000000000E+00   2.5932958830711596E-02   2.5065133189365366E-03   3.7218599583779734E-03\n         3        187   2.8682537469179183E+00   4.5586270277181562E+00   3.6716587592274030E+00   3.8826629123545109E-01\n         3        188   5.3184311792544858E-01   4.3914873612678882E+00   2.0703862000918019E+00   1.2547229035506695E+00\n         3        189   2.1217569405740649E-01   8.2496983879554264E+00   3.6726138368838077E+00   3.3333622253574249E+00\n         3        190   0.0000000000000000E+00   7.5529308962971493E+00   2.9994280873825208E+00   3.0172473321835316E+00\n         3        191   0.0000000000000000E+00   7.7060637483862875E+00   3.1057048737624218E+00   3.1159618649139711E+00\n         3        192   0.0000000000000000E+00   3.0342146314538043E+00   1.0189917595919784E+00   1.0629602834829577E+00\n         3        193   4.7993545918739056E+00   6.4923299672576196E+00   5.6446922366399415E+00   3.4082468511190522E-01\n         3        194   9.3810638034054117E-01   5.7589295137162262E+00   2.8704304060002253E+00   1.5156759936085604E+00\n         3        195   3.7784683765045562E-01   1.0054429327614857E+01   4.5782769008045934E+00   4.0100324950405284E+00\n         3        196   0.0000000000000000E+00   8.9733432374080042E+00   3.6010953483361754E+00   3.6222580333144219E+00\n         3        197   0.0000000000000000E+00   9.1626804218457281E+00   3.7376383468626093E+00   3.7491152376275663E+00\n         3        198   0.0000000000000000E+00   3.6249203976033630E+00   1.2167389283522099E+00   1.2695832885263578E+00\n         3        199   9.8415463508333578E-01   4.4043442972666345E+00   2.7371207312831660E+00   1.0483965370947292E+00\n         3        200   1.7438426638874374E-01   1.2982238564110971E+00   6.4775313482199037E-01   3.7260415663336804E-01\n         3        201   6.8383908570577440E-02   5.4462129470807807E-01   2.6304941944840748E-01   1.5482948466171720E-01\n         3        202   0.0000000000000000E+00   1.6351180946724456E-02   1.5181531931493793E-04   1.0488631156613799E-03\n         3        203   0.0000000000000000E+00   3.4474491411356735E-03   3.0427540017497121E-05   2.1749249270905130E-04\n         3        204   0.0000000000000000E+00   1.4849489713062755E-03   1.2147034518224958E-05   8.8639816852757787E-05\n         3        205   0.0000000000000000E+00   9.1006878875634824E-03   5.8719849713919400E-04   1.1219726814402913E-03\n         3        206   0.0000000000000000E+00   3.8328410575109960E-03   1.4298808779026774E-04   3.3078835861347045E-04\n         3        207   0.0000000000000000E+00   5.4514407480856343E-03   1.8875186837256279E-04   5.0521558231940162E-04\n         3        208   0.0000000000000000E+00   4.6319172792174141E-03   1.5719271924057539E-04   4.5178163368523515E-04\n         3        209   0.0000000000000000E+00   5.0908507250858872E-03   1.6939430940113146E-04   4.8825464840686252E-04\n         3        210   0.0000000000000000E+00   1.3624519315845894E-03   4.1989553602825332E-05   1.2556040559165961E-04\n         3        211   3.7636176535169472E-02   2.0195226384691767E-01   9.8059091348624436E-02   2.8423962766891235E-02\n         3        212   2.7461282539233581E-03   8.1045334186492304E-02   2.0348307792322294E-02   1.2328297261465872E-02\n         3        213   9.7401278723618532E-04   1.0770429670003327E-01   2.7156647682140673E-02   2.5144020757316567E-02\n         3        214   0.0000000000000000E+00   8.9193114480282665E-02   2.2779791254796559E-02   2.4343066401206623E-02\n         3        215   0.0000000000000000E+00   9.8026414791324179E-02   2.4288791724394628E-02   2.6055936187046921E-02\n         3        216   0.0000000000000000E+00   3.3404009826364885E-02   5.6131949958147433E-03   6.5793910850868937E-03\n         3        217   4.8631071528394060E-01   2.0463726147038317E+00   1.0778097491661256E+00   2.8130780687997087E-01\n         3        218   2.4946208518389711E-02   2.5202590040394685E-01   8.4387437615384142E-02   3.8977600360448172E-02\n         3        219   8.8794973986827050E-03   9.2821403358363544E-02   3.0174377537242406E-02   1.3817948994681554E-02\n"
  },
  {
    "path": "examples/potentials/DMABN_SCAN/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  7.6700469000180993E-01 a         1     0     1     1     1\n -6.0190855511745439E-03 a         2     0     1     1     2\n  1.0579574412865869E-01 a         3     0     1     1     3\n  6.7860849664543998E-01 a         4     0     1     1     4\n -7.8540603665791453E-01 a         5     0     1     1     5\n  1.3824026004182208E-01 a         6     0     1     1     6\n  6.3652521971281995E-01 a         7     0     1     1     7\n -1.1617582936184434E+00 a         8     0     1     1     8\n  1.0412246142918693E+00 a         9     0     1     1     9\n -1.2111012669651891E-01 a        10     0     1     1    10\n  5.7258060862746840E-01 a        11     0     1     1    11\n -2.5396892476943000E-01 a        12     0     1     1    12\n -1.9004867051987739E-01 a        13     0     1     1    13\n -3.4437863452369655E-01 a        14     0     1     1    14\n -1.1799633122830752E-01 a        15     0     1     1    15\n  1.5393270030223383E-01 a        16     0     1     1    16\n -6.3117461493428867E-02 a        17     0     1     1    17\n  8.5244971293802119E-01 a        18     0     1     1    18\n -7.0952236524210532E-01 a        19     0     1     1    19\n -3.4936179293794121E+00 a        20     0     1     1    20\n -2.6021108832923017E+00 a        21     0     1     1    21\n -1.2555168264627528E-01 a        22     0     1     1    22\n  3.7216482784088190E-01 a        23     0     1     1    23\n  2.1187549376406092E+00 a        24     0     1     1    24\n -1.6686561352735790E-01 a        25     0     1     1    25\n -9.1280745890339099E-01 a        26     0     2     1     1\n  3.0058038824323080E-01 a        27     0     2     1     2\n -3.1540969172228928E+00 a        28     0     2     1     3\n  3.2518728481465846E+00 a        29     0     2     1     4\n  2.5836187348444450E-01 a        30     0     2     1     5\n  1.2741137607840769E+00 a        31     0     2     1     6\n -4.6999374266616529E+00 a        32     0     2     1     7\n  2.5821557721622462E-01 a        33     0     2     1     8\n -3.4057586353534068E+00 a        34     0     2     1     9\n -1.1679991249531785E+00 a        35     0     2     1    10\n  3.7240575295079732E+00 a        36     0     2     1    11\n -2.4505367049221589E+00 a        37     0     2     1    12\n -1.3269125640390420E+00 a        38     0     2     1    13\n  2.0902127876083121E+00 a        39     0     2     1    14\n  1.1065718846282944E+00 a        40     0     2     1    15\n  1.4521784863620670E+00 a        41     0     2     1    16\n  1.0750995737517113E+00 a        42     0     2     1    17\n -3.4551935017562427E+00 a        43     0     2     1    18\n  5.0011761901687208E+00 a        44     0     2     1    19\n -1.2898126752266825E-01 a        45     0     2     1    20\n  4.4142634003651571E+00 a        46     0     2     1    21\n -5.6463983139142737E-01 a        47     0     2     1    22\n  4.4523064792593150E+00 a        48     0     2     1    23\n  4.2163439716250979E+00 a        49     0     2     1    24\n  2.9396545157867378E+00 a        50     0     2     1    25\n  1.7129334812421519E+00 a        51     0     3     1     1\n  7.2207028228436654E-01 a        52     0     3     1     2\n -5.0478773527351306E+00 a        53     0     3     1     3\n -3.4662592395474046E+00 a        54     0     3     1     4\n -2.5613771784605910E+00 a        55     0     3     1     5\n  1.9002393446977156E-01 a        56     0     3     1     6\n -8.8534916137554021E-01 a        57     0     3     1     7\n -1.2744700008222004E-01 a        58     0     3     1     8\n -4.7875210111024753E+00 a        59     0     3     1     9\n  1.2053880957552976E+00 a        60     0     3     1    10\n  2.9038454829723679E+00 a        61     0     3     1    11\n  1.9062609794373869E-01 a        62     0     3     1    12\n -4.0773249272740770E+00 a        63     0     3     1    13\n -1.6580395575603668E+00 a        64     0     3     1    14\n -2.1580654480817363E+00 a        65     0     3     1    15\n  2.6953032697802182E+00 a        66     0     3     1    16\n -2.4920822346488030E+00 a        67     0     3     1    17\n -7.6126753162645566E-01 a        68     0     3     1    18\n -5.4322382951076076E-01 a        69     0     3     1    19\n -7.8818102509666943E-01 a        70     0     3     1    20\n  4.0139240274170507E-01 a        71     0     3     1    21\n -1.7334208016449146E+00 a        72     0     3     1    22\n -2.9961376241938287E+00 a        73     0     3     1    23\n -4.6215677876936212E+00 a        74     0     3     1    24\n  3.5806876920986191E-02 a        75     0     3     1    25\n -5.5626050365896376E+00 a        76     0     4     1     1\n -5.3045162064943803E+00 a        77     0     4     1     2\n  1.1613547361566459E+00 a        78     0     4     1     3\n -2.2993444984564109E+00 a        79     0     4     1     4\n 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2.3282405029562212E+00 a      2000     0    80     1    25\n -1.4650178497670969E+00 a      2001     0    81     1     1\n -1.2540727406267103E+00 a      2002     0    81     1     2\n  6.4296470829623109E-01 a      2003     0    81     1     3\n  1.9713949629332024E+00 a      2004     0    81     1     4\n  4.7985295138739575E-01 a      2005     0    81     1     5\n -5.8980630534280565E-01 a      2006     0    81     1     6\n -2.9379908360135554E+00 a      2007     0    81     1     7\n  2.5126008113420277E+00 a      2008     0    81     1     8\n  2.4425919680558699E+00 a      2009     0    81     1     9\n -1.7387808082006861E+00 a      2010     0    81     1    10\n -1.5375630809501493E+00 a      2011     0    81     1    11\n -7.1247019169760550E-01 a      2012     0    81     1    12\n  1.7007246528383648E+00 a      2013     0    81     1    13\n -1.3353281289218000E-01 a      2014     0    81     1    14\n  5.0013963301090081E-01 a      2015     0    81     1    15\n -1.9166936355178692E+00 a      2016     0    81     1    16\n  5.9435212333259289E+00 a      2017     0    81     1    17\n -1.0587473501745399E+00 a      2018     0    81     1    18\n -3.4931986826935124E+00 a      2019     0    81     1    19\n  9.9420020232258866E-01 a      2020     0    81     1    20\n -7.5064109651786143E-02 a      2021     0    81     1    21\n  6.3013213909829791E-01 a      2022     0    81     1    22\n -4.1489055307302819E-01 a      2023     0    81     1    23\n -2.5855264565527900E+00 a      2024     0    81     1    24\n -1.4785070884093898E+00 a      2025     0    81     1    25\n -1.5878846238762958E+00 a      2026     0    82     1     1\n -2.2419310549117601E+00 a      2027     0    82     1     2\n -3.2754001501772295E-02 a      2028     0    82     1     3\n  2.5561709636100898E+00 a      2029     0    82     1     4\n -4.8612337754981666E-01 a      2030     0    82     1     5\n -1.4608949543350769E+00 a      2031     0    82     1     6\n  3.7158719943990981E+00 a      2032     0    82     1     7\n  2.8309360345003216E+00 a      2033     0    82     1     8\n  1.5111748124718727E+00 a      2034     0    82     1     9\n  7.6268506487330001E-01 a      2035     0    82     1    10\n  1.5798625408381948E+00 a      2036     0    82     1    11\n -5.3023626154719461E-01 a      2037     0    82     1    12\n  1.0879214733151927E+00 a      2038     0    82     1    13\n  2.9107615666486946E+00 a      2039     0    82     1    14\n -2.9774893365477989E-01 a      2040     0    82     1    15\n -2.1067236835337231E+00 a      2041     0    82     1    16\n  2.7590328001820530E-01 a      2042     0    82     1    17\n  2.1515202032394365E+00 a      2043     0    82     1    18\n  1.0694007845216393E+00 a      2044     0    82     1    19\n -2.9272111276016566E+00 a      2045     0    82     1    20\n -3.1651564844030484E+00 a      2046     0    82     1    21\n  6.6758371633873725E-01 a      2047     0    82     1    22\n  4.8232195666591595E+00 a      2048     0    82     1    23\n -3.4700227080008972E+00 a      2049     0    82     1    24\n  4.8528925124466316E+00 a      2050     0    82     1    25\n  7.1763712610137675E-01 a      2051     0    83     1     1\n  1.2203387643953729E+00 a      2052     0    83     1     2\n  4.0717868078975422E-01 a      2053     0    83     1     3\n  1.3668949531636576E-01 a      2054     0    83     1     4\n  3.4097254572084357E-01 a      2055     0    83     1     5\n -1.4391398976333289E+00 a      2056     0    83     1     6\n -1.1760708995623901E+00 a      2057     0    83     1     7\n -7.1251851851676118E-01 a      2058     0    83     1     8\n  3.3639673728461061E+00 a      2059     0    83     1     9\n -5.0274539391369970E+00 a      2060     0    83     1    10\n -1.7298333803816022E+00 a      2061     0    83     1    11\n  4.3137775503680070E-01 a      2062     0    83     1    12\n  1.7848088456814126E-01 a      2063     0    83     1    13\n -3.5351223742800211E+00 a      2064     0    83     1    14\n -1.8343065720545388E+00 a      2065     0    83     1    15\n -2.6893707805711489E+00 a      2066     0    83     1    16\n  1.8927671710929608E+00 a      2067     0    83     1    17\n -1.2908120514153221E+00 a      2068     0    83     1    18\n -1.0643041430394038E+00 a      2069     0    83     1    19\n -1.5487041767070429E+00 a      2070     0    83     1    20\n  2.4289395950177077E+00 a      2071     0    83     1    21\n -1.6124853334308591E+00 a      2072     0    83     1    22\n -3.2559648389747693E+00 a      2073     0    83     1    23\n  2.5651747888754941E+00 a      2074     0    83     1    24\n -2.1165643210681577E+00 a      2075     0    83     1    25\n  9.6191916938139699E-01 a      2076     0    84     1     1\n -6.1730844693918618E-01 a      2077     0    84     1     2\n -3.5295337483719275E-01 a      2078     0    84     1     3\n  1.1133441506142641E+00 a      2079     0    84     1     4\n  1.4349697719117760E+00 a      2080     0    84     1     5\n -3.9285899094048865E-01 a      2081     0    84     1     6\n -7.2953169272674625E+00 a      2082     0    84     1     7\n -1.1233492660443229E+00 a      2083     0    84     1     8\n -3.7217034630145346E-01 a      2084     0    84     1     9\n -7.2310082424490396E-01 a      2085     0    84     1    10\n -5.1872605954942030E-01 a      2086     0    84     1    11\n  2.9424065352949019E-01 a      2087     0    84     1    12\n  1.1623580677931671E-01 a      2088     0    84     1    13\n  1.9579455255859468E+00 a      2089     0    84     1    14\n -1.2000417793074993E+00 a      2090     0    84     1    15\n  1.7523108904154485E+00 a      2091     0    84     1    16\n -6.5353579481864106E+00 a      2092     0    84     1    17\n -3.2094845633843638E+00 a      2093     0    84     1    18\n -3.4286762865463499E-01 a      2094     0    84     1    19\n  9.7852315545309498E-01 a      2095     0    84     1    20\n -3.8587535570545803E+00 a      2096     0    84     1    21\n  4.7082293832720300E-02 a      2097     0    84     1    22\n  1.6848181653955807E-01 a      2098     0    84     1    23\n  2.8008542421172309E+00 a      2099     0    84     1    24\n  3.0825453482166358E-02 a      2100     0    84     1    25\n -6.0772411369893187E-01 a      2101     0    85     1     1\n  4.1168518079911531E-01 a      2102     0    85     1     2\n  4.1610082855885838E-01 a      2103     0    85     1     3\n -7.0600851543623433E-01 a      2104     0    85     1     4\n -4.8734851283043473E-01 a      2105     0    85     1     5\n  7.9315070989830105E-01 a      2106     0    85     1     6\n  5.1881450447801472E+00 a      2107     0    85     1     7\n  7.8352094361541691E-01 a      2108     0    85     1     8\n  2.6453668485582871E-01 a      2109     0    85     1     9\n  4.0579625752594536E-02 a      2110     0    85     1    10\n  1.0415867237774370E+00 a      2111     0    85     1    11\n  1.1919458361815061E-01 a      2112     0    85     1    12\n  5.2121202706399729E-02 a      2113     0    85     1    13\n -1.2861601462825706E-01 a      2114     0    85     1    14\n  1.9206191784830207E-01 a      2115     0    85     1    15\n  1.7337365278602992E-01 a      2116     0    85     1    16\n  4.2199740955140674E+00 a      2117     0    85     1    17\n  3.8150628960736210E-01 a      2118     0    85     1    18\n -1.7944596151702514E+00 a      2119     0    85     1    19\n -1.7190777765294520E+00 a      2120     0    85     1    20\n  3.1041421015440389E+00 a      2121     0    85     1    21\n  4.0495625759685655E-01 a      2122     0    85     1    22\n -1.1009191347375953E+00 a      2123     0    85     1    23\n -3.8059282989541874E+00 a      2124     0    85     1    24\n  4.2771438993128227E-02 a      2125     0    85     1    25\n  8.8433021947755722E-02 a      2126     0    86     1     1\n  1.2961443988138391E-01 a      2127     0    86     1     2\n  3.1673331283177458E-01 a      2128     0    86     1     3\n -6.1616911146585927E-02 a      2129     0    86     1     4\n -4.1052393758817179E-01 a      2130     0    86     1     5\n -2.7783011975780242E-01 a      2131     0    86     1     6\n  3.4631102597554070E-01 a      2132     0    86     1     7\n -8.0885447634935514E-01 a      2133     0    86     1     8\n  1.4689495731434457E-01 a      2134     0    86     1     9\n  3.9087406731978458E-01 a      2135     0    86     1    10\n  7.2461210438336454E-01 a      2136     0    86     1    11\n  2.6672611436460037E-03 a      2137     0    86     1    12\n  5.0808453821032451E-01 a      2138     0    86     1    13\n -2.1448038444633485E-01 a      2139     0    86     1    14\n  1.1644628807255832E-01 a      2140     0    86     1    15\n  5.5053399973945139E-01 a      2141     0    86     1    16\n -1.3496575580524051E+00 a      2142     0    86     1    17\n  1.1055696865047069E+00 a      2143     0    86     1    18\n  2.3677271640531170E-01 a      2144     0    86     1    19\n -1.3211116750157847E+00 a      2145     0    86     1    20\n -2.8321102760624250E-01 a      2146     0    86     1    21\n  4.6895770962415755E-02 a      2147     0    86     1    22\n  1.9362804432961239E-01 a      2148     0    86     1    23\n -3.8923196175317731E-01 a      2149     0    86     1    24\n  8.7390040487394266E-02 a      2150     0    86     1    25\n  1.3877217796549755E+00 a      2151     0    87     1     1\n  2.3938754504426280E-01 a      2152     0    87     1     2\n  1.0723957183715729E+00 a      2153     0    87     1     3\n -1.6287197619163591E+00 a      2154     0    87     1     4\n  9.4890910576606502E-01 a      2155     0    87     1     5\n  8.4824905150740360E-01 a      2156     0    87     1     6\n  3.8187729058637299E-01 a      2157     0    87     1     7\n -2.2386437996951831E+00 a      2158     0    87     1     8\n -8.5890450030707055E-01 a      2159     0    87     1     9\n  1.6353396822470812E-01 a      2160     0    87     1    10\n  1.5936326008932595E+00 a      2161     0    87     1    11\n -2.3307479738598733E-01 a      2162     0    87     1    12\n  3.0569423480387541E+00 a      2163     0    87     1    13\n  1.4841529924902734E+00 a      2164     0    87     1    14\n -1.9976076146887580E+00 a      2165     0    87     1    15\n  1.3231893706948614E-01 a      2166     0    87     1    16\n  3.1237989538459114E+00 a      2167     0    87     1    17\n -3.7846189633027878E+00 a      2168     0    87     1    18\n -5.0664991507491819E-01 a      2169     0    87     1    19\n  1.8620417252482906E+00 a      2170     0    87     1    20\n -6.9778019325923235E-01 a      2171     0    87     1    21\n -1.2720276431113990E+00 a      2172     0    87     1    22\n  7.9187009935529495E-01 a      2173     0    87     1    23\n -4.0976789661527420E+00 a      2174     0    87     1    24\n -1.5920005703897966E+00 a      2175     0    87     1    25\n -5.4710750819724518E+00 a      2176     0    88     1     1\n -2.5182712714953670E+00 a      2177     0    88     1     2\n -2.0475769625578715E+00 a      2178     0    88     1     3\n -5.2466955426530086E+00 a      2179     0    88     1     4\n -2.0587850460408714E+00 a      2180     0    88     1     5\n -1.8900572344872828E+00 a      2181     0    88     1     6\n -1.8670324124693090E+00 a      2182     0    88     1     7\n -1.2104515071751876E+00 a      2183     0    88     1     8\n -3.4292917959609059E-01 a      2184     0    88     1     9\n -1.2855283846997585E+00 a      2185     0    88     1    10\n  7.5060098682922149E-01 a      2186     0    88     1    11\n  2.5989201739458445E+00 a      2187     0    88     1    12\n -1.8533290598040564E-01 a      2188     0    88     1    13\n -2.7900827816769618E+00 a      2189     0    88     1    14\n  1.7937482979090635E-01 a      2190     0    88     1    15\n  8.6304457040064386E-01 a      2191     0    88     1    16\n 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-6.1385624571003150E-01 a      8821     1    18     2    21\n  2.7455601936649154E-01 a      8822     1    18     2    22\n  1.5560613085371717E+00 a      8823     1    18     2    23\n  5.7347079987673588E-01 a      8824     1    18     2    24\n  3.9967783909592763E-01 a      8825     1    18     2    25\n -1.3686703128660744E+00 a      8826     1    19     2     1\n  4.1739731515905715E-01 a      8827     1    19     2     2\n  3.8790919208001506E-01 a      8828     1    19     2     3\n  1.9257306122971736E+00 a      8829     1    19     2     4\n -1.0936225663262797E+00 a      8830     1    19     2     5\n -7.3245692653847960E-01 a      8831     1    19     2     6\n  9.5216299112420200E-01 a      8832     1    19     2     7\n -8.4748892749880134E-01 a      8833     1    19     2     8\n -4.1100017645308001E-01 a      8834     1    19     2     9\n -1.6003532508137772E+00 a      8835     1    19     2    10\n -9.3027494613094985E-01 a      8836     1    19     2    11\n  7.8135228083574579E-02 a      8837     1    19     2    12\n  2.0816294728622523E-01 a      8838     1    19     2    13\n -6.6306719155139426E-01 a      8839     1    19     2    14\n  5.4976205960942781E-01 a      8840     1    19     2    15\n -1.9874946297684368E-01 a      8841     1    19     2    16\n  3.7842094311817216E+00 a      8842     1    19     2    17\n -7.1268365425790159E-01 a      8843     1    19     2    18\n  5.3998155097232114E-01 a      8844     1    19     2    19\n  1.1047621425547807E-01 a      8845     1    19     2    20\n -1.3524093589275060E-01 a      8846     1    19     2    21\n  1.9945760501794711E+00 a      8847     1    19     2    22\n  7.1371533413228294E-01 a      8848     1    19     2    23\n  7.2964282511905521E-01 a      8849     1    19     2    24\n  8.0051983901632640E-01 a      8850     1    19     2    25\n -5.1442659708492711E-02 a      8851     1    20     2     1\n -7.4159630562891876E-01 a      8852     1    20     2     2\n -5.8521986636073697E-01 a      8853     1    20     2     3\n -4.7260565371588265E-01 a      8854     1    20     2     4\n -3.5502988199681179E-01 a      8855     1    20     2     5\n -3.4307932070592306E-01 a      8856     1    20     2     6\n -7.9171164489046542E-01 a      8857     1    20     2     7\n -9.2365306511665668E-01 a      8858     1    20     2     8\n  1.9852746809138209E+00 a      8859     1    20     2     9\n -1.2221510079490165E+00 a      8860     1    20     2    10\n -5.1846661113933323E-01 a      8861     1    20     2    11\n -2.5397782202360081E-01 a      8862     1    20     2    12\n  4.4312588115066831E-01 a      8863     1    20     2    13\n -1.6557207716595115E+00 a      8864     1    20     2    14\n -3.4765799812999489E+00 a      8865     1    20     2    15\n  7.3192391182278072E-01 a      8866     1    20     2    16\n -7.9588932210418339E-01 a      8867     1    20     2    17\n -1.4631607896707796E-01 a      8868     1    20     2    18\n  1.9230037115588433E-01 a      8869     1    20     2    19\n  1.5616864766662508E-01 a      8870     1    20     2    20\n  1.0007305487489053E+00 a      8871     1    20     2    21\n  9.6387691277768994E-01 a      8872     1    20     2    22\n  4.4351256184842353E-01 a      8873     1    20     2    23\n -2.0566901428934767E+00 a      8874     1    20     2    24\n -3.2020739251068531E-01 a      8875     1    20     2    25\n -1.0063316371620552E+00 a      8876     1    21     2     1\n -5.6190451294698940E-01 a      8877     1    21     2     2\n -2.0321132316507260E+00 a      8878     1    21     2     3\n -1.2193425809207332E+00 a      8879     1    21     2     4\n  6.6811166815192713E-01 a      8880     1    21     2     5\n  1.1259910127701840E+00 a      8881     1    21     2     6\n  9.1232027828733442E-01 a      8882     1    21     2     7\n  2.9487103859470676E-02 a      8883     1    21     2     8\n -3.8739358476853442E-01 a      8884     1    21     2     9\n  6.1920125247456226E-01 a      8885     1    21     2    10\n  8.2348046453097534E-01 a      8886     1    21     2    11\n -3.7458988012124700E-01 a      8887     1    21     2    12\n -7.9031967197477049E-01 a      8888     1    21     2    13\n  2.5660428409501859E+00 a      8889     1    21     2    14\n -3.3276298104621321E-01 a      8890     1    21     2    15\n  1.7215908998336424E+00 a      8891     1    21     2    16\n  1.5903242954462844E+00 a      8892     1    21     2    17\n  1.9299746652775496E+00 a      8893     1    21     2    18\n -1.0644733102255930E+00 a      8894     1    21     2    19\n  7.7672217052890791E-01 a      8895     1    21     2    20\n -7.8796611698121233E-01 a      8896     1    21     2    21\n  1.8767759246216081E-01 a      8897     1    21     2    22\n -1.1889405011387266E+00 a      8898     1    21     2    23\n  1.0175693936875037E-01 a      8899     1    21     2    24\n  8.1062033901151753E-01 a      8900     1    21     2    25\n  1.2727943457845952E+00 a      8901     1    22     2     1\n -1.3284378742716152E+00 a      8902     1    22     2     2\n  1.2948635603082694E+00 a      8903     1    22     2     3\n -7.0355553111883151E-01 a      8904     1    22     2     4\n  6.0268419562018882E-01 a      8905     1    22     2     5\n -2.4527594727691188E-01 a      8906     1    22     2     6\n -1.7317344604546407E+00 a      8907     1    22     2     7\n  2.8757500010389028E+00 a      8908     1    22     2     8\n -2.9475265040968818E-01 a      8909     1    22     2     9\n  3.5375897192097554E+00 a      8910     1    22     2    10\n  1.0786695653485935E-01 a      8911     1    22     2    11\n  2.7844782831240669E+00 a      8912     1    22     2    12\n  2.2437465570939445E+00 a      8913     1    22     2    13\n -4.1120127829934938E-01 a      8914     1    22     2    14\n -6.7462483429309522E-02 a      8915     1    22     2    15\n -2.1326085756284270E+00 a      8916     1    22     2    16\n -6.0280683053460260E-01 a      8917     1    22     2    17\n -2.4176014813038398E+00 a      8918     1    22     2    18\n  4.3592836948755270E-01 a      8919     1    22     2    19\n  1.4222048524478563E+00 a      8920     1    22     2    20\n  1.4728096199503884E-01 a      8921     1    22     2    21\n -9.5680821567581759E-02 a      8922     1    22     2    22\n -3.5172680003125958E+00 a      8923     1    22     2    23\n -1.6277218240332745E+00 a      8924     1    22     2    24\n -1.0942602781793707E+00 a      8925     1    22     2    25\n  9.2659932366403785E-01 a      8926     1    23     2     1\n  1.6303760059822558E-01 a      8927     1    23     2     2\n -1.0177147331356582E+00 a      8928     1    23     2     3\n  9.3955059784358841E-01 a      8929     1    23     2     4\n  1.9744458820475230E-01 a      8930     1    23     2     5\n -1.9980190546908069E-01 a      8931     1    23     2     6\n -9.9694650484615333E-01 a      8932     1    23     2     7\n  2.6196652686114555E-02 a      8933     1    23     2     8\n -1.6635913885401774E-01 a      8934     1    23     2     9\n  1.7581266896915622E+00 a      8935     1    23     2    10\n  1.8863931340595905E-01 a      8936     1    23     2    11\n  4.5523936938389814E-01 a      8937     1    23     2    12\n -3.0635472260330240E-02 a      8938     1    23     2    13\n -9.2958704952957327E-01 a      8939     1    23     2    14\n -3.8860376031648775E-01 a      8940     1    23     2    15\n  6.1555023891468730E-01 a      8941     1    23     2    16\n -1.5920643255991653E+00 a      8942     1    23     2    17\n -2.5753018654581866E-01 a      8943     1    23     2    18\n  5.0870035393534585E-01 a      8944     1    23     2    19\n  6.2885048198225091E-01 a      8945     1    23     2    20\n -2.8731497944066753E-01 a      8946     1    23     2    21\n -5.0714910882177300E-01 a      8947     1    23     2    22\n  1.6452056418904384E+00 a      8948     1    23     2    23\n  3.3865129998232923E-01 a      8949     1    23     2    24\n -5.8231617120510015E-01 a      8950     1    23     2    25\n -3.1559266763370186E-01 a      8951     1    24     2     1\n  4.5899716445902566E-01 a      8952     1    24     2     2\n  1.7828266150148847E-01 a      8953     1    24     2     3\n  4.4738656629769717E-02 a      8954     1    24     2     4\n -6.2437585783096872E-01 a      8955     1    24     2     5\n  9.0545319451397141E-02 a      8956     1    24     2     6\n -1.6641054278112039E-01 a      8957     1    24     2     7\n -8.7496889903865749E-01 a      8958     1    24     2     8\n  1.0502079125306880E+00 a      8959     1    24     2     9\n -3.6890054980897746E-01 a      8960     1    24     2    10\n -1.7661396804175777E-01 a      8961     1    24     2    11\n -5.0373288543340422E-01 a      8962     1    24     2    12\n -3.2173606545851297E-01 a      8963     1    24     2    13\n -8.3565402814069367E-01 a      8964     1    24     2    14\n -6.0681797940330795E-01 a      8965     1    24     2    15\n  3.3474354717832383E-01 a      8966     1    24     2    16\n  5.8212400434953182E-01 a      8967     1    24     2    17\n -9.5734372280181990E-01 a      8968     1    24     2    18\n  1.3936206085232909E+00 a      8969     1    24     2    19\n -9.0491613558769102E-01 a      8970     1    24     2    20\n -3.0300620000312223E-01 a      8971     1    24     2    21\n -1.9406437913054916E-01 a      8972     1    24     2    22\n  1.4946774040594124E+00 a      8973     1    24     2    23\n  1.3214159472465539E+00 a      8974     1    24     2    24\n -9.4118201153245951E-01 a      8975     1    24     2    25\n  2.4828201016079139E+00 a      8976     1    25     2     1\n -1.5336081600324888E-01 a      8977     1    25     2     2\n  1.9935378418630993E+00 a      8978     1    25     2     3\n  8.4280830343488577E-01 a      8979     1    25     2     4\n -4.7381020709494298E-01 a      8980     1    25     2     5\n -5.4318049519129918E-01 a      8981     1    25     2     6\n  3.5173133189035743E+00 a      8982     1    25     2     7\n -1.0328349399773640E+00 a      8983     1    25     2     8\n -1.9794243128970941E+00 a      8984     1    25     2     9\n -7.7605495214067899E-01 a      8985     1    25     2    10\n -9.2624903244076984E-01 a      8986     1    25     2    11\n  1.0079789495216460E+00 a      8987     1    25     2    12\n  1.6533790133252002E+00 a      8988     1    25     2    13\n -2.2337682294795669E+00 a      8989     1    25     2    14\n -5.0067442796831474E-01 a      8990     1    25     2    15\n  4.2742263622482396E-01 a      8991     1    25     2    16\n -2.1956097193652049E+00 a      8992     1    25     2    17\n -6.2054829625087293E-01 a      8993     1    25     2    18\n  8.0066400242767621E-01 a      8994     1    25     2    19\n -3.6543535398183591E-01 a      8995     1    25     2    20\n  2.4104415414061398E-01 a      8996     1    25     2    21\n  6.2788190476165151E-01 a      8997     1    25     2    22\n -1.3283045798125370E-01 a      8998     1    25     2    23\n -1.2648200204715294E+00 a      8999     1    25     2    24\n  8.2510141236731366E-02 a      9000     1    25     2    25\n  1.6541342904122054E+00 b      9001     2     1\n  2.1516097515432766E+00 b      9002     2     2\n -3.0123423211724858E+00 b      9003     2     3\n  1.1493001537321035E+00 b      9004     2     4\n  2.8640046132633703E+00 b      9005     2     5\n -3.8132296134594825E+00 b      9006     2     6\n -6.4119544151905905E-02 b      9007     2     7\n -4.7281148978477727E+00 b      9008     2     8\n  3.9678729007605598E+00 b      9009     2     9\n -2.0982384210900347E+00 b      9010     2    10\n  6.3248691917373701E-01 b      9011     2    11\n -4.0259531419272934E+00 b      9012     2    12\n -3.6004309172211983E+00 b      9013     2    13\n  2.1803876248724952E-01 b      9014     2    14\n  2.9170132872739023E+00 b      9015     2    15\n -1.6063626922511116E+00 b      9016     2    16\n  3.1270717282106091E+00 b      9017     2    17\n  2.0963465008576657E-01 b      9018     2    18\n -7.0260248032579309E-01 b      9019     2    19\n -5.5948812707729623E-01 b      9020     2    20\n -3.8969204495339548E-02 b      9021     2    21\n -6.3964222775896662E-01 b      9022     2    22\n  2.7728079122349397E-01 b      9023     2    23\n -2.2073369872301689E+00 b      9024     2    24\n  1.4048995582501693E+00 b      9025     2    25\n  2.4639204051649602E-01 a      9026     2     1     3     1\n -1.3802884461836176E+00 a      9027     2     2     3     1\n  6.9007682276971327E-01 a      9028     2     3     3     1\n  9.5483111153964029E-01 a      9029     2     4     3     1\n  9.2152745054917562E-01 a      9030     2     5     3     1\n  5.0291661100596563E-01 a      9031     2     6     3     1\n -2.2997158340951313E-02 a      9032     2     7     3     1\n  7.9590684786984806E-02 a      9033     2     8     3     1\n -6.8570172993916545E-01 a      9034     2     9     3     1\n  2.5569182480462613E-02 a      9035     2    10     3     1\n -2.2657510485896107E-01 a      9036     2    11     3     1\n  6.1587847887954172E-01 a      9037     2    12     3     1\n  1.1286473488670512E+00 a      9038     2    13     3     1\n  3.8541249148011725E-01 a      9039     2    14     3     1\n  1.8631851860030546E-01 a      9040     2    15     3     1\n  2.6069265968724969E-01 a      9041     2    16     3     1\n -2.0037719275175982E-02 a      9042     2    17     3     1\n  1.0143788830600912E-02 a      9043     2    18     3     1\n  1.0899469593768871E+00 a      9044     2    19     3     1\n  1.0218132117205663E+00 a      9045     2    20     3     1\n  1.0363505575503407E+00 a      9046     2    21     3     1\n -2.7431224616661670E-01 a      9047     2    22     3     1\n -2.6607521294142733E-02 a      9048     2    23     3     1\n -1.5910341915720569E-01 a      9049     2    24     3     1\n -1.3394580706661012E+00 a      9050     2    25     3     1\n  2.7538766074480834E+00 b      9051     3     1\n"
  },
  {
    "path": "examples/potentials/DMABN_SCAN/weights.006.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  2.7383304992527409E+00 a         1     0     1     1     1\n -1.2621905738510548E+00 a         2     0     1     1     2\n -3.3755889009176978E+00 a         3     0     1     1     3\n -5.9860937814953550E+00 a         4     0     1     1     4\n -4.3640807985117025E+00 a         5     0     1     1     5\n -2.4479937808931078E+00 a         6     0     1     1     6\n  4.1920894805128917E-01 a         7     0     1     1     7\n  9.6391601838587571E-01 a         8     0     1     1     8\n  2.9854181934749375E+00 a         9     0     1     1     9\n  1.0342802096221779E+00 a        10     0     1     1    10\n  1.5333657099734965E+00 a        11     0     1     1    11\n -7.2097266357622503E-01 a        12     0     1     1    12\n -1.6660805257695439E+00 a        13     0     1     1    13\n -2.4552056422253328E+00 a        14     0     1     1    14\n  1.7994760339369671E+00 a        15     0     1     1    15\n  5.9783587475887146E-01 a        16     0     1     1    16\n -2.8574947541284695E-01 a        17     0     1     1    17\n  5.7972823073903157E-01 a        18     0     1     1    18\n  1.2620399224595726E+00 a        19     0     1     1    19\n  1.3897110359343479E+00 a        20     0     1     1    20\n -5.0851854756441117E-01 a        21     0     1     1    21\n -4.3547849098627820E+00 a        22     0     1     1    22\n -1.8668384881409912E+00 a        23     0     1     1    23\n  9.9767109922395347E-02 a        24     0     1     1    24\n -5.1685445048373762E+00 a        25     0     1     1    25\n -4.0057065605423183E+00 a        26     0     2     1     1\n  1.0520717198969416E+01 a        27     0     2     1     2\n  1.1844023063168900E+00 a        28     0     2     1     3\n  4.8266400620021095E+00 a        29     0     2     1     4\n  1.0976327036895519E+01 a        30     0     2     1     5\n -3.9537279878730291E-01 a        31     0     2     1     6\n 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1.7340176591681826E+00 a      1968     0    79     1    18\n -2.0351241139253999E+00 a      1969     0    79     1    19\n  1.8918718647814809E+00 a      1970     0    79     1    20\n  1.5816481268832807E+00 a      1971     0    79     1    21\n -1.3167792113863983E-01 a      1972     0    79     1    22\n -2.4463061293819170E+00 a      1973     0    79     1    23\n  8.2178073715823408E-01 a      1974     0    79     1    24\n -1.1028322046514376E+00 a      1975     0    79     1    25\n -4.6678228303017182E+00 a      1976     0    80     1     1\n  2.4232501556258468E+00 a      1977     0    80     1     2\n  4.4199901743062942E+00 a      1978     0    80     1     3\n -5.2351379806118870E-01 a      1979     0    80     1     4\n -1.5313206474807592E+00 a      1980     0    80     1     5\n -2.1690322793451733E+00 a      1981     0    80     1     6\n -2.4363668589285954E+00 a      1982     0    80     1     7\n  5.9685990028209637E-02 a      1983     0    80     1     8\n  5.3170431448847513E+00 a      1984     0    80     1     9\n -4.0755166520061170E+00 a      1985     0    80     1    10\n  4.4101859324201200E+00 a      1986     0    80     1    11\n -1.4141418401921917E+00 a      1987     0    80     1    12\n  1.1294025341881513E+00 a      1988     0    80     1    13\n  1.4205306286539932E-01 a      1989     0    80     1    14\n -1.6710920517056760E+00 a      1990     0    80     1    15\n  4.1282622720596229E-01 a      1991     0    80     1    16\n -1.3545903624825966E+00 a      1992     0    80     1    17\n -5.7202504713078162E-01 a      1993     0    80     1    18\n  2.3767078269054736E+00 a      1994     0    80     1    19\n  3.4037658536466693E+00 a      1995     0    80     1    20\n -8.0109282029988660E-01 a      1996     0    80     1    21\n  1.7142953101211482E+00 a      1997     0    80     1    22\n  5.8845248922551552E-01 a      1998     0    80     1    23\n -2.2292787354429024E+00 a      1999     0    80     1    24\n -1.0154907952249954E+00 a      2000     0    80     1    25\n -2.0685680896105598E+00 a      2001     0    81     1     1\n -1.3673919880269977E-01 a      2002     0    81     1     2\n  2.8976765507221889E+00 a      2003     0    81     1     3\n -2.2980014376168585E+00 a      2004     0    81     1     4\n  3.1299478654216681E+00 a      2005     0    81     1     5\n -1.0444799311073878E+00 a      2006     0    81     1     6\n -3.9414818305456176E+00 a      2007     0    81     1     7\n  3.3028524634162886E+00 a      2008     0    81     1     8\n  1.4101783343652088E-01 a      2009     0    81     1     9\n -1.7825128123693093E-01 a      2010     0    81     1    10\n  4.4846983887067928E+00 a      2011     0    81     1    11\n -1.4085820006717256E+00 a      2012     0    81     1    12\n -1.2018719206385144E+00 a      2013     0    81     1    13\n -5.7907652127642173E+00 a      2014     0    81     1    14\n -2.4711375044242843E+00 a      2015     0    81     1    15\n -7.0732307395162308E-01 a      2016     0    81     1    16\n  3.7457627167592233E-01 a      2017     0    81     1    17\n -1.8917354445115291E+00 a      2018     0    81     1    18\n -2.1848867582343496E+00 a      2019     0    81     1    19\n -6.1852317725461992E-01 a      2020     0    81     1    20\n  3.0689111870152366E+00 a      2021     0    81     1    21\n  2.9581136677359171E-01 a      2022     0    81     1    22\n  7.6628377437493045E-01 a      2023     0    81     1    23\n -1.8209697848550077E-01 a      2024     0    81     1    24\n -4.1689738692604505E+00 a      2025     0    81     1    25\n  3.9110830466641904E+00 a      2026     0    82     1     1\n -1.1712301085340124E+00 a      2027     0    82     1     2\n -6.0763985758325034E-02 a      2028     0    82     1     3\n -9.0665128017518870E-01 a      2029     0    82     1     4\n  1.8248219690665730E+00 a      2030     0    82     1     5\n  8.6993979328798610E-01 a      2031     0    82     1     6\n -3.6897593736905460E-01 a      2032     0    82     1     7\n  5.3083935136244165E-01 a      2033     0    82     1     8\n -1.5314038909794420E-01 a      2034     0    82     1     9\n  1.7677902185973464E+00 a      2035     0    82     1    10\n  2.4467669959048490E+00 a      2036     0    82     1    11\n  8.2834397033051943E-01 a      2037     0    82     1    12\n -2.4162608599290158E+00 a      2038     0    82     1    13\n -1.0726609155321805E+00 a      2039     0    82     1    14\n  4.4621441472249428E+00 a      2040     0    82     1    15\n  9.3249693507493880E-01 a      2041     0    82     1    16\n -2.5032079823706490E+00 a      2042     0    82     1    17\n  4.7305533947806272E-01 a      2043     0    82     1    18\n -1.7460582059461345E+00 a      2044     0    82     1    19\n -5.6640486642835175E-01 a      2045     0    82     1    20\n  1.5762175380816463E+00 a      2046     0    82     1    21\n  1.7808575442903285E+00 a      2047     0    82     1    22\n -3.6886996094663642E+00 a      2048     0    82     1    23\n -4.5135036811128249E+00 a      2049     0    82     1    24\n  4.6539208055168070E-02 a      2050     0    82     1    25\n -6.8101541046659753E-01 a      2051     0    83     1     1\n  1.6367869525297607E+00 a      2052     0    83     1     2\n  2.2551253117978436E+00 a      2053     0    83     1     3\n -2.8720005943700704E+00 a      2054     0    83     1     4\n -2.6309910998202559E+00 a      2055     0    83     1     5\n -1.0916211885512623E+00 a      2056     0    83     1     6\n -3.4298714806646119E-01 a      2057     0    83     1     7\n -3.3558482732776058E+00 a      2058     0    83     1     8\n -4.8917244503585664E+00 a      2059     0    83     1     9\n  1.7417477278187399E+00 a      2060     0    83     1    10\n  7.2259788319301521E-02 a      2061     0    83     1    11\n -1.6921237428597191E-01 a      2062     0    83     1    12\n -3.3205896295262507E+00 a      2063     0    83     1    13\n -1.2719724204430700E+00 a      2064     0    83     1    14\n  2.2710425203908664E+00 a      2065     0    83     1    15\n  2.5053973085214563E+00 a      2066     0    83     1    16\n -1.5058148067353272E-01 a      2067     0    83     1    17\n -4.4397546147842037E-01 a      2068     0    83     1    18\n  8.6448984386966854E-01 a      2069     0    83     1    19\n  1.7742768386961567E+00 a      2070     0    83     1    20\n  4.5527891082022602E+00 a      2071     0    83     1    21\n -7.0615230056202061E-01 a      2072     0    83     1    22\n -1.6584185055220644E+00 a      2073     0    83     1    23\n  4.4986030144511896E-01 a      2074     0    83     1    24\n  9.1770785145515410E-01 a      2075     0    83     1    25\n -3.8145712721259502E+00 a      2076     0    84     1     1\n -2.5145200601023086E+00 a      2077     0    84     1     2\n -4.2169929330264860E-01 a      2078     0    84     1     3\n  2.0689982362267694E+00 a      2079     0    84     1     4\n -4.0696272673038845E+00 a      2080     0    84     1     5\n -9.4738636185132852E-01 a      2081     0    84     1     6\n  1.2168554149082336E+00 a      2082     0    84     1     7\n -1.5528759736957551E+00 a      2083     0    84     1     8\n -1.9943907692858371E+00 a      2084     0    84     1     9\n  3.6744512555299208E-01 a      2085     0    84     1    10\n  1.7987095051339763E+00 a      2086     0    84     1    11\n  1.5611222442819459E+00 a      2087     0    84     1    12\n  2.9865536936203632E+00 a      2088     0    84     1    13\n -4.0976493578631414E+00 a      2089     0    84     1    14\n  1.2370566139116121E+00 a      2090     0    84     1    15\n -3.8804572309374097E-01 a      2091     0    84     1    16\n  9.9275502867032728E-01 a      2092     0    84     1    17\n  1.2428254086248287E+00 a      2093     0    84     1    18\n  1.1992135958422698E+00 a      2094     0    84     1    19\n -1.8339008369782659E+00 a      2095     0    84     1    20\n -2.7435501659103609E+00 a      2096     0    84     1    21\n -7.4511297332309423E-01 a      2097     0    84     1    22\n  4.7677246120773846E+00 a      2098     0    84     1    23\n -2.1345341164742409E+00 a      2099     0    84     1    24\n  2.8781512426503347E-01 a      2100     0    84     1    25\n  2.8749626042363141E-01 a      2101     0    85     1     1\n -1.7550151452179452E+00 a      2102     0    85     1     2\n -1.1401438613955355E+00 a      2103     0    85     1     3\n  1.8594458944558443E-02 a      2104     0    85     1     4\n  7.8426316340148106E-01 a      2105     0    85     1     5\n -4.2917358143104432E+00 a      2106     0    85     1     6\n -1.6626598727984204E-01 a      2107     0    85     1     7\n  3.0347190126450587E+00 a      2108     0    85     1     8\n  3.8113244528231188E-01 a      2109     0    85     1     9\n  6.9193073912482261E-01 a      2110     0    85     1    10\n -3.0914132510192673E+00 a      2111     0    85     1    11\n  4.4900896577440530E-01 a      2112     0    85     1    12\n  1.4695040752223913E+00 a      2113     0    85     1    13\n -9.6243633609541712E-01 a      2114     0    85     1    14\n  1.2616757289593470E+00 a      2115     0    85     1    15\n -5.4668539527328897E-01 a      2116     0    85     1    16\n  9.7729709435926504E-01 a      2117     0    85     1    17\n  1.6983940069576984E+00 a      2118     0    85     1    18\n -1.3412043780205507E-01 a      2119     0    85     1    19\n  1.2116678418643672E+00 a      2120     0    85     1    20\n -6.2474504988570745E-01 a      2121     0    85     1    21\n -7.5448642041665392E-01 a      2122     0    85     1    22\n -3.0044900436747661E+00 a      2123     0    85     1    23\n  1.7500089163787638E+00 a      2124     0    85     1    24\n  5.8563922935551971E-01 a      2125     0    85     1    25\n  3.4528390812414607E-03 a      2126     0    86     1     1\n  3.7478103237123833E-01 a      2127     0    86     1     2\n  1.1620162768842017E+00 a      2128     0    86     1     3\n  2.5456908897422310E+00 a      2129     0    86     1     4\n  3.9571688166703067E-01 a      2130     0    86     1     5\n  2.9241594404943116E+00 a      2131     0    86     1     6\n  1.7330197962186858E-01 a      2132     0    86     1     7\n -4.2898211583719803E+00 a      2133     0    86     1     8\n -5.3061575740670242E-01 a      2134     0    86     1     9\n -1.1133083446172420E+00 a      2135     0    86     1    10\n  1.6420908125966760E+00 a      2136     0    86     1    11\n -9.9958003981329435E-01 a      2137     0    86     1    12\n -3.0620116026877242E+00 a      2138     0    86     1    13\n -3.3319202920660613E+00 a      2139     0    86     1    14\n -3.2670834636460935E+00 a      2140     0    86     1    15\n  1.8881417119762106E-01 a      2141     0    86     1    16\n -3.9233035227926933E+00 a      2142     0    86     1    17\n  3.3588393104933084E-01 a      2143     0    86     1    18\n  7.6114016668792872E-01 a      2144     0    86     1    19\n  8.7277312886229530E-01 a      2145     0    86     1    20\n  5.4418287314896896E-01 a      2146     0    86     1    21\n  1.2764374069205566E+00 a      2147     0    86     1    22\n  7.7478718400336688E-01 a      2148     0    86     1    23\n -1.4310204684658627E+00 a      2149     0    86     1    24\n -1.7950279515762924E-01 a      2150     0    86     1    25\n -4.2828896266193744E-01 a      2151     0    87     1     1\n  2.5606837564546842E-01 a      2152     0    87     1     2\n -5.2073375822496692E-01 a      2153     0    87     1     3\n -3.0657626435895544E+00 a      2154     0    87     1     4\n -1.1312414537843978E+00 a      2155     0    87     1     5\n -1.6586429114011596E+00 a      2156     0    87     1     6\n  3.7038186963350062E-01 a      2157     0    87     1     7\n -1.3734474352300143E+00 a      2158     0    87     1     8\n -1.3389750407868268E+00 a      2159     0    87     1     9\n -2.4935565856071484E-01 a      2160     0    87     1    10\n  3.5561421263345239E-01 a      2161     0    87     1    11\n -2.7010466817496446E+00 a      2162     0    87     1    12\n  1.9941680200825993E+00 a      2163     0    87     1    13\n  1.5723648520993422E-01 a      2164     0    87     1    14\n -1.2742301274261532E+00 a      2165     0    87     1    15\n  5.8733687438643711E-01 a      2166     0    87     1    16\n -1.0650191091468435E+00 a      2167     0    87     1    17\n  1.7924605585713398E-02 a      2168     0    87     1    18\n  5.1839822861297069E-02 a      2169     0    87     1    19\n -1.9693727989714653E+00 a      2170     0    87     1    20\n -2.4770997045208540E-01 a      2171     0    87     1    21\n  6.8082243135466258E-01 a      2172     0    87     1    22\n -5.4878512229475385E-01 a      2173     0    87     1    23\n -1.2741616587757760E+00 a      2174     0    87     1    24\n  1.1890598336112055E+00 a      2175     0    87     1    25\n  1.1818051384143641E-01 a      2176     0    88     1     1\n -3.1956414290950930E-01 a      2177     0    88     1     2\n  4.9703933278633775E-02 a      2178     0    88     1     3\n -3.2471251480911971E+00 a      2179     0    88     1     4\n  1.3601985543292909E+00 a      2180     0    88     1     5\n -2.2636391624300090E+00 a      2181     0    88     1     6\n  4.7166466026724085E-01 a      2182     0    88     1     7\n  1.8088729523242837E+00 a      2183     0    88     1     8\n  1.2095942551927168E+00 a      2184     0    88     1     9\n  8.2176561111559254E-01 a      2185     0    88     1    10\n -1.4493679618775099E+00 a      2186     0    88     1    11\n  2.3830802132361684E+00 a      2187     0    88     1    12\n -2.2179193887778021E+00 a      2188     0    88     1    13\n -1.7405246050073773E+00 a      2189     0    88     1    14\n -8.6445468251123037E-01 a      2190     0    88     1    15\n -3.3763679771916855E-02 a      2191     0    88     1    16\n -1.5319499009641813E+00 a      2192     0    88     1    17\n  5.7777065366322700E-01 a      2193     0    88     1    18\n -7.9315810001182407E-01 a      2194     0    88     1    19\n  2.0604430718699693E-01 a      2195     0    88     1    20\n  3.8928166997046598E-01 a      2196     0    88     1    21\n -6.6495925851916812E-02 a      2197     0    88     1    22\n  2.7950668227176871E+00 a      2198     0    88     1    23\n -2.5137376412656337E-01 a      2199     0    88     1    24\n -1.3405404594487549E+00 a      2200     0    88     1    25\n  4.5668463088998168E-01 a      2201     0    89     1     1\n  2.1580926898980004E+00 a      2202     0    89     1     2\n  1.7771890240297945E+00 a      2203     0    89     1     3\n  2.1186847948902807E+00 a      2204     0    89     1     4\n -4.0188405081958276E+00 a      2205     0    89     1     5\n -1.0095389716469494E+00 a      2206     0    89     1     6\n  3.0666536981633052E-01 a      2207     0    89     1     7\n 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5.5019169428638304E-01 a      8741     1    16     2    16\n -3.4249669321966278E+00 a      8742     1    16     2    17\n -3.1423819742262493E-01 a      8743     1    16     2    18\n -1.3989925834700034E+00 a      8744     1    16     2    19\n  7.9747595510460012E-02 a      8745     1    16     2    20\n -2.3947459779644440E+00 a      8746     1    16     2    21\n  9.5085447424314828E-01 a      8747     1    16     2    22\n  7.7384832921845037E-01 a      8748     1    16     2    23\n -7.7706748030743056E-01 a      8749     1    16     2    24\n  1.0280647480895837E+00 a      8750     1    16     2    25\n  1.0434658577470174E-01 a      8751     1    17     2     1\n -1.5210367542796770E+00 a      8752     1    17     2     2\n -1.0511409072729181E+00 a      8753     1    17     2     3\n -8.0420729520108480E-02 a      8754     1    17     2     4\n  6.4968217814826673E-02 a      8755     1    17     2     5\n  3.7214481157037121E-01 a      8756     1    17     2     6\n -3.6290593720144504E-01 a      8757     1    17     2     7\n -3.4849606532490141E-01 a      8758     1    17     2     8\n  6.7753154237041380E-01 a      8759     1    17     2     9\n -6.3397018455628107E-01 a      8760     1    17     2    10\n  8.5615875927314167E-01 a      8761     1    17     2    11\n  2.8331563190589542E+00 a      8762     1    17     2    12\n  5.1311332097484763E-01 a      8763     1    17     2    13\n -1.8640833959223484E+00 a      8764     1    17     2    14\n -1.6376936554431791E+00 a      8765     1    17     2    15\n  8.6194139773843481E-01 a      8766     1    17     2    16\n  2.7635270649521970E-01 a      8767     1    17     2    17\n  5.1610611545474383E-01 a      8768     1    17     2    18\n -1.6901534840953572E+00 a      8769     1    17     2    19\n -1.3146911931860341E+00 a      8770     1    17     2    20\n  6.5398619578525818E-01 a      8771     1    17     2    21\n  1.8780797694651331E-02 a      8772     1    17     2    22\n -1.2828369138248208E+00 a      8773     1    17     2    23\n  9.2541808320774341E-02 a      8774     1    17     2    24\n  3.6303518963102227E-01 a      8775     1    17     2    25\n  1.7844985903242812E+00 a      8776     1    18     2     1\n -4.6129890164196059E+00 a      8777     1    18     2     2\n  2.4046876199252094E+00 a      8778     1    18     2     3\n  8.9653438214233472E-01 a      8779     1    18     2     4\n  4.0482512907985840E-01 a      8780     1    18     2     5\n -1.5730514515811844E+00 a      8781     1    18     2     6\n -6.6585765577360723E-01 a      8782     1    18     2     7\n -4.0462213699134464E-01 a      8783     1    18     2     8\n -3.9977943101636493E-01 a      8784     1    18     2     9\n  2.2656822423954361E+00 a      8785     1    18     2    10\n  1.1499354389613394E+00 a      8786     1    18     2    11\n -1.2172431946991304E+00 a      8787     1    18     2    12\n  4.1901408770896093E-01 a      8788     1    18     2    13\n  4.3427089800458729E-01 a      8789     1    18     2    14\n  1.0269601424509849E+00 a      8790     1    18     2    15\n -7.5150498608914884E-01 a      8791     1    18     2    16\n -4.8202117614779694E-01 a      8792     1    18     2    17\n -1.5707202564396059E+00 a      8793     1    18     2    18\n  1.7917477142510190E+00 a      8794     1    18     2    19\n  4.5744870242609467E-02 a      8795     1    18     2    20\n  1.2591705021360899E-01 a      8796     1    18     2    21\n  3.1058645950056174E-01 a      8797     1    18     2    22\n  6.6127437120545185E-01 a      8798     1    18     2    23\n  7.0752987239104925E-01 a      8799     1    18     2    24\n -1.1032145244624643E+00 a      8800     1    18     2    25\n  2.4736645223665268E-01 a      8801     1    19     2     1\n  9.2681189169842415E-01 a      8802     1    19     2     2\n -2.0334818442555287E+00 a      8803     1    19     2     3\n  1.2319425067894045E+00 a      8804     1    19     2     4\n  1.0091533129830501E+00 a      8805     1    19     2     5\n  1.3101348202655485E+00 a      8806     1    19     2     6\n  1.2876540568367965E+00 a      8807     1    19     2     7\n -1.9462858632592206E-01 a      8808     1    19     2     8\n -1.1321002224932226E-01 a      8809     1    19     2     9\n  2.0009983800607158E+00 a      8810     1    19     2    10\n -1.1250406545195766E+00 a      8811     1    19     2    11\n -3.4389214804685925E-01 a      8812     1    19     2    12\n -6.1934237276541171E-01 a      8813     1    19     2    13\n  1.7458791741771966E+00 a      8814     1    19     2    14\n  5.8398348877805295E-01 a      8815     1    19     2    15\n -1.7529217972599895E-01 a      8816     1    19     2    16\n  7.8292398741523173E-01 a      8817     1    19     2    17\n  1.8070936516818714E-01 a      8818     1    19     2    18\n -1.2635541271379785E-01 a      8819     1    19     2    19\n -2.1796249286352047E+00 a      8820     1    19     2    20\n  3.2949873711342698E-01 a      8821     1    19     2    21\n -3.2070057485432585E-01 a      8822     1    19     2    22\n  1.7582771382676135E-01 a      8823     1    19     2    23\n -9.7254898090562564E-02 a      8824     1    19     2    24\n  9.1997475286734465E-02 a      8825     1    19     2    25\n -6.6783776183946209E-02 a      8826     1    20     2     1\n -1.0367383620105466E+00 a      8827     1    20     2     2\n -5.0635918792281878E-03 a      8828     1    20     2     3\n -7.3965916311591906E-01 a      8829     1    20     2     4\n  2.4179220241745603E-01 a      8830     1    20     2     5\n -1.4269228450744231E-01 a      8831     1    20     2     6\n -3.2850401471105289E-01 a      8832     1    20     2     7\n  1.1122933376723334E+00 a      8833     1    20     2     8\n -1.7997830510951567E+00 a      8834     1    20     2     9\n -1.8459708986190904E+00 a      8835     1    20     2    10\n  1.0584103355904910E+00 a      8836     1    20     2    11\n  9.3322460571707055E-01 a      8837     1    20     2    12\n -1.8512482930987018E-01 a      8838     1    20     2    13\n  2.3378584402429589E-01 a      8839     1    20     2    14\n -9.6065536985668276E-02 a      8840     1    20     2    15\n  1.2925540670114162E+00 a      8841     1    20     2    16\n -1.8485906257217257E+00 a      8842     1    20     2    17\n -1.5575773892589289E+00 a      8843     1    20     2    18\n  7.4157846781092085E-01 a      8844     1    20     2    19\n  7.2127070991890707E-01 a      8845     1    20     2    20\n -7.5959033378675622E-01 a      8846     1    20     2    21\n  3.3496609798867005E-01 a      8847     1    20     2    22\n -2.2145380937668278E+00 a      8848     1    20     2    23\n  7.1192969230908501E-03 a      8849     1    20     2    24\n -6.7114288812328105E-01 a      8850     1    20     2    25\n -1.0305091984860848E+00 a      8851     1    21     2     1\n  2.4826611778875174E+00 a      8852     1    21     2     2\n  1.3946507521941012E+00 a      8853     1    21     2     3\n -5.0287223248530633E-01 a      8854     1    21     2     4\n  1.9156869390047898E-01 a      8855     1    21     2     5\n -4.7114962311982195E-01 a      8856     1    21     2     6\n  1.9295093167526289E+00 a      8857     1    21     2     7\n  7.5908911618125563E-01 a      8858     1    21     2     8\n  4.1508620015220143E-01 a      8859     1    21     2     9\n  2.7139861919273706E-01 a      8860     1    21     2    10\n -5.1747848415114824E-02 a      8861     1    21     2    11\n -4.2534958936829703E-01 a      8862     1    21     2    12\n -2.5013343826676743E-01 a      8863     1    21     2    13\n -1.4914098793330355E+00 a      8864     1    21     2    14\n  1.1014486192017088E+00 a      8865     1    21     2    15\n  5.2297193219530531E-02 a      8866     1    21     2    16\n -1.7355374204370299E-03 a      8867     1    21     2    17\n  3.8369929185181766E+00 a      8868     1    21     2    18\n -3.0386765892739476E-01 a      8869     1    21     2    19\n -1.7261659359399306E+00 a      8870     1    21     2    20\n  3.7217279809336568E-01 a      8871     1    21     2    21\n  5.4610462484717825E-01 a      8872     1    21     2    22\n -1.6224448942779552E+00 a      8873     1    21     2    23\n  5.0213577399174780E-01 a      8874     1    21     2    24\n -7.0732097446139827E-02 a      8875     1    21     2    25\n  1.4673260499285137E+00 a      8876     1    22     2     1\n  4.2206936772615000E-01 a      8877     1    22     2     2\n  2.7537348204858275E-01 a      8878     1    22     2     3\n -1.7000406019530814E+00 a      8879     1    22     2     4\n -1.5153756459296526E+00 a      8880     1    22     2     5\n -8.1109909640822964E-01 a      8881     1    22     2     6\n -5.6078705051847019E-02 a      8882     1    22     2     7\n -1.6799527003317505E+00 a      8883     1    22     2     8\n  1.2558538698546033E+00 a      8884     1    22     2     9\n  4.0831368770552778E-01 a      8885     1    22     2    10\n  1.5107306927745854E+00 a      8886     1    22     2    11\n  1.7029997111881162E-01 a      8887     1    22     2    12\n  1.3827695580182775E+00 a      8888     1    22     2    13\n  2.1753781312239062E+00 a      8889     1    22     2    14\n -8.6201548158296359E-01 a      8890     1    22     2    15\n  1.2574285160193052E-01 a      8891     1    22     2    16\n -1.5950997458440513E-01 a      8892     1    22     2    17\n -4.5967301121023257E-01 a      8893     1    22     2    18\n -1.1095793417769297E-01 a      8894     1    22     2    19\n  4.4972878475561323E-01 a      8895     1    22     2    20\n -7.7306000355928356E-02 a      8896     1    22     2    21\n -1.7994775304904129E+00 a      8897     1    22     2    22\n  2.8623812807247764E+00 a      8898     1    22     2    23\n -5.8448227655716700E-01 a      8899     1    22     2    24\n -6.5115472585496281E-01 a      8900     1    22     2    25\n  1.0804126172077615E+00 a      8901     1    23     2     1\n  1.7278844207552331E+00 a      8902     1    23     2     2\n -1.8724392983954325E+00 a      8903     1    23     2     3\n -5.1519709274830472E-01 a      8904     1    23     2     4\n -9.5700224499989023E-02 a      8905     1    23     2     5\n -7.3922304886884463E-02 a      8906     1    23     2     6\n -3.4891258604659168E+00 a      8907     1    23     2     7\n  4.7327597906818841E-01 a      8908     1    23     2     8\n  2.2479057735736037E+00 a      8909     1    23     2     9\n  6.2998477090336458E-01 a      8910     1    23     2    10\n  1.3167085613795646E+00 a      8911     1    23     2    11\n -3.2265075583916303E-01 a      8912     1    23     2    12\n  1.8724788870524902E+00 a      8913     1    23     2    13\n -2.4435132577249492E+00 a      8914     1    23     2    14\n -1.7478542009273379E-01 a      8915     1    23     2    15\n -4.6824993019357490E-02 a      8916     1    23     2    16\n -5.8782193412285866E-01 a      8917     1    23     2    17\n -1.6980349046664429E+00 a      8918     1    23     2    18\n  1.0090307154265397E+00 a      8919     1    23     2    19\n  2.3992459833659008E+00 a      8920     1    23     2    20\n -2.5882242228655639E-01 a      8921     1    23     2    21\n  8.2966907898332432E-01 a      8922     1    23     2    22\n -1.0153341195139198E+00 a      8923     1    23     2    23\n -3.1967790050681877E-01 a      8924     1    23     2    24\n  1.9652140445765414E+00 a      8925     1    23     2    25\n  2.6971244557131291E-01 a      8926     1    24     2     1\n -2.3371393725534917E+00 a      8927     1    24     2     2\n  1.3003866784238831E+00 a      8928     1    24     2     3\n  1.5276070521578917E+00 a      8929     1    24     2     4\n  1.9017330783851097E-01 a      8930     1    24     2     5\n -1.4480586853466553E+00 a      8931     1    24     2     6\n  3.0592993147395908E-01 a      8932     1    24     2     7\n -6.6806214353359616E-01 a      8933     1    24     2     8\n -1.7293599563129067E+00 a      8934     1    24     2     9\n  1.9559816846428027E-01 a      8935     1    24     2    10\n -1.4953667100058550E+00 a      8936     1    24     2    11\n -7.3952032796660086E-02 a      8937     1    24     2    12\n -1.2792957423746931E+00 a      8938     1    24     2    13\n  1.7330377638627557E+00 a      8939     1    24     2    14\n  1.0274437995229191E+00 a      8940     1    24     2    15\n -4.3050738658969223E-01 a      8941     1    24     2    16\n  3.0455018241551639E+00 a      8942     1    24     2    17\n  3.3381685022483398E-01 a      8943     1    24     2    18\n  9.3456436334264625E-01 a      8944     1    24     2    19\n -1.1286187411359493E-01 a      8945     1    24     2    20\n  2.8725180306121906E-01 a      8946     1    24     2    21\n  3.8260388557024128E-01 a      8947     1    24     2    22\n  1.2343929371229763E+00 a      8948     1    24     2    23\n  1.5315318181929878E+00 a      8949     1    24     2    24\n  6.7747115029120719E-01 a      8950     1    24     2    25\n -8.6361029803221201E-01 a      8951     1    25     2     1\n -2.7918967028663122E-01 a      8952     1    25     2     2\n  8.6566498777006196E-01 a      8953     1    25     2     3\n  1.5990278627428536E+00 a      8954     1    25     2     4\n  8.9477594499644675E-01 a      8955     1    25     2     5\n  2.1199698152453004E+00 a      8956     1    25     2     6\n -9.0881080226896638E-01 a      8957     1    25     2     7\n  2.2480927967666686E-01 a      8958     1    25     2     8\n -1.2653379923961772E+00 a      8959     1    25     2     9\n  1.0004197254928477E+00 a      8960     1    25     2    10\n  2.8786469197148674E-02 a      8961     1    25     2    11\n  1.0869851341574510E+00 a      8962     1    25     2    12\n -5.0453089645542337E-01 a      8963     1    25     2    13\n -5.8835771566201844E-01 a      8964     1    25     2    14\n  7.3047327465327361E-01 a      8965     1    25     2    15\n -7.9019625297211193E-01 a      8966     1    25     2    16\n -1.2239667028337129E+00 a      8967     1    25     2    17\n  2.1423737018196305E+00 a      8968     1    25     2    18\n -5.3641001364055763E-01 a      8969     1    25     2    19\n  9.3965720225372040E-01 a      8970     1    25     2    20\n -1.8946262533832001E-01 a      8971     1    25     2    21\n -7.2768411906009167E-01 a      8972     1    25     2    22\n -8.4009171005852501E-01 a      8973     1    25     2    23\n -9.6210895587692621E-02 a      8974     1    25     2    24\n  1.0294900253191936E+00 a      8975     1    25     2    25\n -6.1409827602752971E+00 b      8976     2     1\n -7.3435363751884586E-01 b      8977     2     2\n -5.4609281355163128E+00 b      8978     2     3\n -8.0445299479364107E-01 b      8979     2     4\n -2.7915603687780917E+00 b      8980     2     5\n -1.5869680305406451E+00 b      8981     2     6\n  5.1861639276596629E-02 b      8982     2     7\n -2.0170381000945410E+00 b      8983     2     8\n -1.3620725843388071E-01 b      8984     2     9\n -9.4490480827058398E-01 b      8985     2    10\n  3.7444987345693981E-01 b      8986     2    11\n -3.9673915726294515E+00 b      8987     2    12\n  9.0040768070585253E-01 b      8988     2    13\n  2.0652705054465290E+00 b      8989     2    14\n -1.6937755256917253E+00 b      8990     2    15\n  1.0928532409789391E+00 b      8991     2    16\n -4.2737789958368244E-01 b      8992     2    17\n  1.1600415930588150E+00 b      8993     2    18\n  1.7891861212833393E+00 b      8994     2    19\n  3.1373979554958009E-01 b      8995     2    20\n -5.9302439501067394E-01 b      8996     2    21\n  1.5705083345779005E+00 b      8997     2    22\n -2.2164103433440160E-01 b      8998     2    23\n  3.8312930277173701E-01 b      8999     2    24\n -3.1342349265758063E-01 b      9000     2    25\n  3.6304805461502632E-01 a      9001     2     1     3     1\n -6.5823799219877216E-03 a      9002     2     2     3     1\n -1.3121314208977258E-01 a      9003     2     3     3     1\n  7.1586566958173031E-02 a      9004     2     4     3     1\n -5.4372803926883717E-01 a      9005     2     5     3     1\n -4.2026697252852768E-01 a      9006     2     6     3     1\n -3.9435467280032055E-02 a      9007     2     7     3     1\n -2.5212591471480967E-03 a      9008     2     8     3     1\n  1.7449373076267763E-01 a      9009     2     9     3     1\n -6.0002877894158274E-04 a      9010     2    10     3     1\n  5.5300363498743121E-01 a      9011     2    11     3     1\n -3.5541446026866685E-01 a      9012     2    12     3     1\n  1.6102460198142304E-01 a      9013     2    13     3     1\n -5.5378817205560060E-01 a      9014     2    14     3     1\n -1.3701138428302488E+00 a      9015     2    15     3     1\n -9.0104042914602123E-01 a      9016     2    16     3     1\n -2.5611227485930576E-03 a      9017     2    17     3     1\n -1.3485021173759795E+00 a      9018     2    18     3     1\n  1.0024376080324708E+00 a      9019     2    19     3     1\n  1.4001790972679468E-02 a      9020     2    20     3     1\n  7.9429263074196277E-01 a      9021     2    21     3     1\n  5.9092476845946285E-01 a      9022     2    22     3     1\n  9.3204133982188275E-01 a      9023     2    23     3     1\n -8.2707424519823036E-01 a      9024     2    24     3     1\n  4.8028155477385344E-03 a      9025     2    25     3     1\n  2.4784889468279641E+00 b      9026     3     1\n"
  },
  {
    "path": "examples/potentials/DMABN_SCAN/weights.007.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -3.5369504107014866E+00 a         1     0     1     1     1\n  2.5396762681640106E+00 a         2     0     1     1     2\n  5.3737086807515388E-01 a         3     0     1     1     3\n  3.3181932998498191E+00 a         4     0     1     1     4\n  3.3981664467635913E+00 a         5     0     1     1     5\n  3.2465972875061313E+00 a         6     0     1     1     6\n -1.2403935054144948E+00 a         7     0     1     1     7\n  1.1307419369244407E+00 a         8     0     1     1     8\n  8.4866583151700026E-01 a         9     0     1     1     9\n  7.6140092891142785E-01 a        10     0     1     1    10\n  3.3739810113376794E+00 a        11     0     1     1    11\n -3.5028092681158909E+00 a        12     0     1     1    12\n  1.4745993853393073E+00 a        13     0     1     1    13\n  1.1081649365446951E+00 a        14     0     1     1    14\n -3.6522674441852532E-01 a        15     0     1     1    15\n  1.8013731727753872E+00 a        16     0     1     1    16\n  6.4473949657733931E-01 a        17     0     1     1    17\n -1.8897655255018206E+00 a        18     0     1     1    18\n -2.8797270652304743E+00 a        19     0     1     1    19\n  4.7358582495094304E+00 a        20     0     1     1    20\n  8.9497367876562617E-01 a        21     0     1     1    21\n -5.9979238386008715E-01 a        22     0     1     1    22\n -6.2029062408324993E+00 a        23     0     1     1    23\n  1.4841013053889547E+00 a        24     0     1     1    24\n -4.2337402404705848E-01 a        25     0     1     1    25\n -4.8423132565005034E-01 a        26     0     2     1     1\n -4.9549149754103644E-01 a        27     0     2     1     2\n  9.3104303701160596E-01 a        28     0     2     1     3\n  1.9540960757003016E+00 a        29     0     2     1     4\n  4.2376922693734755E+00 a        30     0     2     1     5\n -2.7271027313772609E+00 a        31     0     2     1     6\n  2.1582732186477331E+00 a        32     0     2     1     7\n -1.4332564004991794E-01 a        33     0     2     1     8\n -2.3619676627300470E-01 a        34     0     2     1     9\n  2.6898227423718629E-01 a        35     0     2     1    10\n  3.7452186602811608E+00 a        36     0     2     1    11\n -1.9374213998844403E+00 a        37     0     2     1    12\n  1.6164305649583353E+00 a        38     0     2     1    13\n  4.7856650305411037E+00 a        39     0     2     1    14\n  5.9317731612542834E-01 a        40     0     2     1    15\n -1.1748391855770293E+00 a        41     0     2     1    16\n -7.9204542293086622E-01 a        42     0     2     1    17\n  1.5991077119236101E+00 a        43     0     2     1    18\n -1.6410056375191431E+00 a        44     0     2     1    19\n  2.0394598945410802E-01 a        45     0     2     1    20\n  1.5177999824312389E+00 a        46     0     2     1    21\n -2.8449242418852638E-01 a        47     0     2     1    22\n  1.7158339717498070E+00 a        48     0     2     1    23\n -8.2576714725380340E-01 a        49     0     2     1    24\n -6.0384305773984115E-01 a        50     0     2     1    25\n -1.6615228926257042E+00 a        51     0     3     1     1\n  2.1019980813239825E-01 a        52     0     3     1     2\n  2.8976731747304645E+00 a        53     0     3     1     3\n  5.1591873279295344E+00 a        54     0     3     1     4\n  2.9578519581752793E+00 a        55     0     3     1     5\n  1.5922593170366808E+00 a        56     0     3     1     6\n  1.9708021381212191E+00 a        57     0     3     1     7\n  1.7522264377470143E-01 a        58     0     3     1     8\n -7.2744693304019725E-01 a        59     0     3     1     9\n  5.6864048834071079E-01 a        60     0     3     1    10\n  2.1185073757589721E+00 a        61     0     3     1    11\n  2.2137675460624312E-01 a        62     0     3     1    12\n  1.5004000701801765E+00 a        63     0     3     1    13\n  3.3376862065889976E+00 a        64     0     3     1    14\n  7.5809549958819689E-01 a        65     0     3     1    15\n  8.3661664872419966E-02 a        66     0     3     1    16\n  9.6849074314036177E-01 a        67     0     3     1    17\n  7.4521614669691527E-01 a        68     0     3     1    18\n -1.2359085834555514E+00 a        69     0     3     1    19\n  5.8994870842785452E-01 a        70     0     3     1    20\n -1.6261704189098432E+00 a        71     0     3     1    21\n -1.3407155465071025E-01 a        72     0     3     1    22\n -2.2788980414484157E+00 a        73     0     3     1    23\n  5.9726184489456058E-01 a        74     0     3     1    24\n  2.7859367291242004E-01 a        75     0     3     1    25\n  1.6137775622660802E-01 a        76     0     4     1     1\n  1.3265631948912675E+00 a        77     0     4     1     2\n  9.1699448746998968E-01 a        78     0     4     1     3\n  2.0710751376956007E+00 a        79     0     4     1     4\n  1.2834637068190666E+00 a        80     0     4     1     5\n  5.6200826316323416E-01 a        81     0     4     1     6\n  1.2004204723087921E+00 a        82     0     4     1     7\n  2.7128043760988069E-01 a        83     0     4     1     8\n  1.3788939740835870E+00 a        84     0     4     1     9\n  1.1459941982839992E+00 a        85     0     4     1    10\n  7.4814724037637714E-01 a        86     0     4     1    11\n -1.6336102315671188E+00 a        87     0     4     1    12\n  2.2724200714200466E+00 a        88     0     4     1    13\n  1.3718333545279562E+00 a        89     0     4     1    14\n -3.1593167113522957E-01 a        90     0     4     1    15\n -2.2482201609029254E-01 a        91     0     4     1    16\n  7.2124342076845493E-01 a        92     0     4     1    17\n  9.5786133504820736E-01 a        93     0     4     1    18\n -1.2888083614406223E+00 a        94     0     4     1    19\n  3.4331191220547419E-01 a        95     0     4     1    20\n  1.2942324858923577E+00 a        96     0     4     1    21\n  8.8022606716584051E-01 a        97     0     4     1    22\n -1.7667962687723222E+00 a        98     0     4     1    23\n -3.3512537310168961E-01 a        99     0     4     1    24\n  7.4812436846970098E-01 a       100     0     4     1    25\n -8.2360181611159022E-01 a       101     0     5     1     1\n  1.2389074587677156E+00 a       102     0     5     1     2\n -2.7480085413885793E+00 a       103     0     5     1     3\n -3.1859977838059073E+00 a       104     0     5     1     4\n  3.4141656815739330E+00 a       105     0     5     1     5\n -4.7732483562378158E+00 a       106     0     5     1     6\n  2.3523432138491729E+00 a       107     0     5     1     7\n  1.0301737280285617E+00 a       108     0     5     1     8\n  2.5492092219543898E+00 a       109     0     5     1     9\n  1.1077244960626917E+00 a       110     0     5     1    10\n -4.5045413443101001E+00 a       111     0     5     1    11\n -8.1186174547060952E-01 a       112     0     5     1    12\n  1.2533108018348613E+00 a       113     0     5     1    13\n -1.3372931909988894E+00 a       114     0     5     1    14\n  2.5296444014339325E-01 a       115     0     5     1    15\n  4.7724859575399980E+00 a       116     0     5     1    16\n  2.1403985985822938E+00 a       117     0     5     1    17\n  2.7779036863945872E-01 a       118     0     5     1    18\n -2.9996254051595863E+00 a       119     0     5     1    19\n -3.3842515391272281E+00 a       120     0     5     1    20\n -5.3379214596119260E+00 a       121     0     5     1    21\n -1.9817419047697455E+00 a       122     0     5     1    22\n -1.6726908270652059E+00 a       123     0     5     1    23\n -6.8556070871757424E-01 a       124     0     5     1    24\n -2.6142771202482811E+00 a       125     0     5     1    25\n  1.2259423853446638E+00 a       126     0     6     1     1\n -3.3394907579456745E-01 a       127     0     6     1     2\n  7.0880818803740619E-01 a       128     0     6     1     3\n  1.7666631896846139E+00 a       129     0     6     1     4\n  1.8355136403565278E+00 a       130     0     6     1     5\n -4.8623229625847975E-01 a       131     0     6     1     6\n  4.9653634068105418E-01 a       132     0     6     1     7\n -6.0359238857950592E-01 a       133     0     6     1     8\n  9.1810801996011204E-01 a       134     0     6     1     9\n  1.6854477406661306E+00 a       135     0     6     1    10\n  4.9418968882985015E-01 a       136     0     6     1    11\n -3.2675024782229021E+00 a       137     0     6     1    12\n  1.1399565063123112E+00 a       138     0     6     1    13\n  1.4998674747796750E+00 a       139     0     6     1    14\n  5.2978287848528494E-01 a       140     0     6     1    15\n  2.1264030434087960E-01 a       141     0     6     1    16\n -2.9555371696446975E-01 a       142     0     6     1    17\n  1.3892481175900235E+00 a       143     0     6     1    18\n -1.8904848855771703E-01 a       144     0     6     1    19\n  4.7200678300320503E-01 a       145     0     6     1    20\n  2.2951627198092424E+00 a       146     0     6     1    21\n  1.0946505322833169E+00 a       147     0     6     1    22\n -1.0486222160093548E+00 a       148     0     6     1    23\n -6.1341141372558450E-01 a       149     0     6     1    24\n  4.1037519088469276E-01 a       150     0     6     1    25\n  5.7581129827271060E-01 a       151     0     7     1     1\n -1.4179307877998559E+00 a       152     0     7     1     2\n -1.9653000433073284E+00 a       153     0     7     1     3\n -2.3286820920099810E-01 a       154     0     7     1     4\n  2.0836337836196188E+00 a       155     0     7     1     5\n -4.4582845471313820E-01 a       156     0     7     1     6\n -2.3377083089113473E+00 a       157     0     7     1     7\n -3.6643640174046543E-01 a       158     0     7     1     8\n  4.6784911178417268E+00 a       159     0     7     1     9\n  3.3022553293757512E-01 a       160     0     7     1    10\n -1.2959385768968392E+00 a       161     0     7     1    11\n  5.8499791887073926E-01 a       162     0     7     1    12\n  1.1531291281898310E+00 a       163     0     7     1    13\n -2.3054239228455762E+00 a       164     0     7     1    14\n  3.5247398928248069E-01 a       165     0     7     1    15\n  1.6146837084281047E+00 a       166     0     7     1    16\n  2.1203472491305080E+00 a       167     0     7     1    17\n -1.8361957578663717E+00 a       168     0     7     1    18\n -1.2340931627757279E-01 a       169     0     7     1    19\n -2.7461865270306909E+00 a       170     0     7     1    20\n -1.9189369712374460E+00 a       171     0     7     1    21\n  3.3180021245116675E+00 a       172     0     7     1    22\n -4.4281524647448239E-01 a       173     0     7     1    23\n  2.6549921115541699E+00 a       174     0     7     1    24\n -1.7328749320819510E+00 a       175     0     7     1    25\n  5.8066234918825999E-01 a       176     0     8     1     1\n -2.9916388302819075E-01 a       177     0     8     1     2\n  1.0762660131515738E+00 a       178     0     8     1     3\n  1.5814866457341863E+00 a       179     0     8     1     4\n  1.0966557619637038E+00 a       180     0     8     1     5\n -1.3814188779290431E+00 a       181     0     8     1     6\n  1.0160324863294588E+00 a       182     0     8     1     7\n -3.7624402488680214E-01 a       183     0     8     1     8\n -2.0001002057236408E-01 a       184     0     8     1     9\n  1.3580344299300324E+00 a       185     0     8     1    10\n  8.1967136445873057E-02 a       186     0     8     1    11\n -1.7657447391915786E+00 a       187     0     8     1    12\n  1.6828458992949018E+00 a       188     0     8     1    13\n  1.7108480693960313E+00 a       189     0     8     1    14\n -3.0102712245660512E-01 a       190     0     8     1    15\n  7.1462136054979974E-01 a       191     0     8     1    16\n  6.5357801443900077E-01 a       192     0     8     1    17\n  7.6949828410288423E-01 a       193     0     8     1    18\n  2.8130249680720304E-01 a       194     0     8     1    19\n -3.6094141127346091E-01 a       195     0     8     1    20\n  1.5315179724838315E+00 a       196     0     8     1    21\n  2.1869673147199932E-02 a       197     0     8     1    22\n -1.1839123219002545E+00 a       198     0     8     1    23\n  2.6273244631137654E-01 a       199     0     8     1    24\n -2.9786466533803396E-01 a       200     0     8     1    25\n -2.8423806276941194E-01 a       201     0     9     1     1\n  1.5182459071207557E+00 a       202     0     9     1     2\n  1.0117936185726237E+00 a       203     0     9     1     3\n  7.7597709991981445E-01 a       204     0     9     1     4\n  2.0044073175914647E+00 a       205     0     9     1     5\n -3.0051919474603433E-01 a       206     0     9     1     6\n  4.3862499672140409E-01 a       207     0     9     1     7\n  1.5378988336897817E-01 a       208     0     9     1     8\n -2.9340386492649256E-01 a       209     0     9     1     9\n  6.0369528188690535E-01 a       210     0     9     1    10\n  1.6080117634296287E+00 a       211     0     9     1    11\n -2.5781038542659074E+00 a       212     0     9     1    12\n  2.2856449746398799E+00 a       213     0     9     1    13\n  2.7908141156908557E+00 a       214     0     9     1    14\n  9.4397074903973854E-01 a       215     0     9     1    15\n -6.2441132967208157E-01 a       216     0     9     1    16\n  4.7604712301386415E-01 a       217     0     9     1    17\n  1.0794779806027370E+00 a       218     0     9     1    18\n  2.9326477859013628E-01 a       219     0     9     1    19\n -8.6447554836389762E-01 a       220     0     9     1    20\n  1.9534046462820254E+00 a       221     0     9     1    21\n  6.6171444006364522E-01 a       222     0     9     1    22\n -1.6190252598095867E+00 a       223     0     9     1    23\n -1.1214274320290180E-01 a       224     0     9     1    24\n -7.7873766708465475E-01 a       225     0     9     1    25\n  2.1922515273458129E-01 a       226     0    10     1     1\n  6.1900571403456073E-01 a       227     0    10     1     2\n  2.7917094717539399E-02 a       228     0    10     1     3\n  8.6391795720088593E-02 a       229     0    10     1     4\n  1.9807717572422867E+00 a       230     0    10     1     5\n  7.8352980726175070E-01 a       231     0    10     1     6\n -2.1062674455157371E+00 a       232     0    10     1     7\n  1.1749389745474137E+00 a       233     0    10     1     8\n -3.1676076872318992E+00 a       234     0    10     1     9\n  8.4269331764199137E-02 a       235     0    10     1    10\n -1.6865214268857009E+00 a       236     0    10     1    11\n  1.1857601578439116E+00 a       237     0    10     1    12\n  1.5839429394128990E+00 a       238     0    10     1    13\n -3.5128972887231069E-01 a       239     0    10     1    14\n -1.3594967627177972E+00 a       240     0    10     1    15\n -2.4697479144904406E+00 a       241     0    10     1    16\n -3.6717766821821001E+00 a       242     0    10     1    17\n -2.0739154619538267E+00 a       243     0    10     1    18\n -4.1906488461252320E-02 a       244     0    10     1    19\n  1.0143575179083719E+00 a       245     0    10     1    20\n -8.8332836755727784E-01 a       246     0    10     1    21\n -4.8443924636936542E-01 a       247     0    10     1    22\n -2.8628865345566710E+00 a       248     0    10     1    23\n  1.4055097902341183E+00 a       249     0    10     1    24\n -2.6195950322194257E+00 a       250     0    10     1    25\n  7.9679355222818660E-03 a       251     0    11     1     1\n  9.7108654234050007E-01 a       252     0    11     1     2\n  1.9025274067511575E+00 a       253     0    11     1     3\n -2.1464172477598469E+00 a       254     0    11     1     4\n  2.0402343485064454E+00 a       255     0    11     1     5\n  4.0734458067825621E+00 a       256     0    11     1     6\n  2.3918993125104877E+00 a       257     0    11     1     7\n -1.9685457336367871E+00 a       258     0    11     1     8\n -2.0227347565404374E-01 a       259     0    11     1     9\n  4.6255887685820225E+00 a       260     0    11     1    10\n  4.8015843576594086E-01 a       261     0    11     1    11\n  6.6042388553309872E-01 a       262     0    11     1    12\n  2.6415482859443125E+00 a       263     0    11     1    13\n -3.2484790365838556E-01 a       264     0    11     1    14\n -1.2441413248612294E-01 a       265     0    11     1    15\n -1.4328677961766330E+00 a       266     0    11     1    16\n  1.8974805922055420E+00 a       267     0    11     1    17\n  8.0751889634880961E-02 a       268     0    11     1    18\n  1.6950461845207432E+00 a       269     0    11     1    19\n  9.0709393644411440E-01 a       270     0    11     1    20\n -1.3112506094733818E+00 a       271     0    11     1    21\n  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5.6046563572575252E+00 a      1936     0    78     1    11\n -1.8518577275242660E+00 a      1937     0    78     1    12\n  2.2083687354038082E+00 a      1938     0    78     1    13\n  1.4772749737540514E+00 a      1939     0    78     1    14\n -6.4996310003107050E-01 a      1940     0    78     1    15\n -2.3938127460621770E+00 a      1941     0    78     1    16\n  3.0821423070618789E-02 a      1942     0    78     1    17\n -1.1242502355641322E+00 a      1943     0    78     1    18\n  2.5690001397520414E+00 a      1944     0    78     1    19\n  1.0597212178581785E+00 a      1945     0    78     1    20\n -1.2483110381506159E+00 a      1946     0    78     1    21\n -2.4451774558367654E+00 a      1947     0    78     1    22\n  3.4760189355277031E+00 a      1948     0    78     1    23\n  1.1324166100771771E+00 a      1949     0    78     1    24\n -3.7046827899093575E+00 a      1950     0    78     1    25\n  1.1699373183102337E+00 a      1951     0    79     1     1\n -3.4999560873525444E+00 a      1952     0    79     1     2\n -1.7390351072645140E+00 a      1953     0    79     1     3\n -1.9014825030221971E-01 a      1954     0    79     1     4\n  5.7650358587736328E-01 a      1955     0    79     1     5\n  2.0486641790637656E+00 a      1956     0    79     1     6\n -6.7958823453819983E-01 a      1957     0    79     1     7\n -2.8352920291014367E+00 a      1958     0    79     1     8\n  6.2981550936933450E-01 a      1959     0    79     1     9\n  1.1311526832523301E-01 a      1960     0    79     1    10\n -9.2556436631323447E-01 a      1961     0    79     1    11\n -4.5465118998353055E-01 a      1962     0    79     1    12\n -6.1742009139705756E-01 a      1963     0    79     1    13\n -3.1558668533585182E-01 a      1964     0    79     1    14\n  1.5544933740445883E+00 a      1965     0    79     1    15\n  1.2195499538184944E+00 a      1966     0    79     1    16\n  1.0787882024646700E+00 a      1967     0    79     1    17\n -3.3423787173372475E+00 a      1968     0    79     1    18\n  1.0208155259915410E+00 a      1969     0    79     1    19\n -1.8410958503935839E+00 a      1970     0    79     1    20\n -6.2746945231714091E-02 a      1971     0    79     1    21\n  5.3657939685807921E-01 a      1972     0    79     1    22\n  1.4300315820270415E+00 a      1973     0    79     1    23\n -3.7167617689817329E+00 a      1974     0    79     1    24\n -2.1429838428281855E+00 a      1975     0    79     1    25\n -1.2519762109713295E+00 a      1976     0    80     1     1\n  3.8729630184505159E-01 a      1977     0    80     1     2\n -1.8540880807827131E+00 a      1978     0    80     1     3\n -1.0123771318006507E+00 a      1979     0    80     1     4\n  4.9051784541708415E-02 a      1980     0    80     1     5\n -2.1307958330985479E+00 a      1981     0    80     1     6\n -3.5404974064714909E+00 a      1982     0    80     1     7\n  4.6106294456257899E+00 a      1983     0    80     1     8\n  1.4912768372807195E+00 a      1984     0    80     1     9\n  1.2802186526512287E+00 a      1985     0    80     1    10\n  6.4400545081208960E-01 a      1986     0    80     1    11\n  8.6631813625829068E-01 a      1987     0    80     1    12\n -4.1630204884292521E+00 a      1988     0    80     1    13\n  2.1063988437892589E+00 a      1989     0    80     1    14\n  4.0221327543926511E-01 a      1990     0    80     1    15\n  3.1015234889214921E-01 a      1991     0    80     1    16\n -2.0531955145315597E-01 a      1992     0    80     1    17\n -8.1858473501889906E-01 a      1993     0    80     1    18\n -8.0673716084881453E-01 a      1994     0    80     1    19\n -2.9576699686446806E-01 a      1995     0    80     1    20\n -1.7846332340852669E+00 a      1996     0    80     1    21\n  1.2099267750449125E+00 a      1997     0    80     1    22\n -8.0919743489400897E-01 a      1998     0    80     1    23\n  1.9049130779274256E-01 a      1999     0    80     1    24\n -9.0793975500887525E-01 a      2000     0    80     1    25\n  9.8963745848246865E-01 a      2001     0    81     1     1\n  2.8104679660715388E+00 a      2002     0    81     1     2\n -2.6054790077443801E+00 a      2003     0    81     1     3\n -1.2380577188709692E+00 a      2004     0    81     1     4\n -8.9929834535761907E-02 a      2005     0    81     1     5\n  6.9221895667354294E-01 a      2006     0    81     1     6\n  2.1608042149712410E+00 a      2007     0    81     1     7\n  2.5096979977441908E-01 a      2008     0    81     1     8\n  3.1730849834651051E+00 a      2009     0    81     1     9\n -7.8995284095423723E-01 a      2010     0    81     1    10\n  1.1126035261070453E+00 a      2011     0    81     1    11\n  1.2980698341277914E+00 a      2012     0    81     1    12\n -1.4032327815764938E+00 a      2013     0    81     1    13\n -3.3651065378404259E+00 a      2014     0    81     1    14\n -1.2267849824962915E+00 a      2015     0    81     1    15\n -2.7495438717997014E+00 a      2016     0    81     1    16\n -4.7924992408243228E-01 a      2017     0    81     1    17\n  8.4238072645860451E-01 a      2018     0    81     1    18\n -7.8568904218935232E-01 a      2019     0    81     1    19\n -1.6514634643985704E+00 a      2020     0    81     1    20\n -2.5454090166579846E+00 a      2021     0    81     1    21\n -2.2714608095042113E-01 a      2022     0    81     1    22\n  2.9381831994656129E+00 a      2023     0    81     1    23\n  2.2853762437093326E+00 a      2024     0    81     1    24\n  6.6483118474587855E-01 a      2025     0    81     1    25\n  3.4580309782497265E-01 a      2026     0    82     1     1\n -1.6636632039812640E+00 a      2027     0    82     1     2\n -2.8533769752620226E+00 a      2028     0    82     1     3\n -5.9149651290287686E-01 a      2029     0    82     1     4\n -4.0540275583290991E-01 a      2030     0    82     1     5\n  1.9010946749190749E+00 a      2031     0    82     1     6\n  7.7407306144684662E-02 a      2032     0    82     1     7\n  3.9010624748567930E+00 a      2033     0    82     1     8\n -1.6708679364183534E+00 a      2034     0    82     1     9\n -2.7676035062499371E-01 a      2035     0    82     1    10\n  7.7399167821432446E-01 a      2036     0    82     1    11\n  1.7957063897489960E+00 a      2037     0    82     1    12\n -1.4116110951123451E+00 a      2038     0    82     1    13\n -1.4719226446021707E+00 a      2039     0    82     1    14\n -5.3775393453060769E-03 a      2040     0    82     1    15\n  5.0644231906149972E-01 a      2041     0    82     1    16\n -1.1776936120017458E+00 a      2042     0    82     1    17\n  2.0114783069886752E+00 a      2043     0    82     1    18\n -8.8049187018897690E-01 a      2044     0    82     1    19\n -1.5574861174499643E+00 a      2045     0    82     1    20\n -4.6735711196880274E+00 a      2046     0    82     1    21\n  5.7151629930590691E+00 a      2047     0    82     1    22\n -3.0392760284472042E+00 a      2048     0    82     1    23\n  1.0088048147600619E+00 a      2049     0    82     1    24\n -6.0058245005557098E-01 a      2050     0    82     1    25\n -1.4129606335180411E+00 a      2051     0    83     1     1\n -2.3301200908584696E+00 a      2052     0    83     1     2\n  2.3025967782457131E+00 a      2053     0    83     1     3\n -1.1256867418364545E+00 a      2054     0    83     1     4\n -1.2567771423069003E+00 a      2055     0    83     1     5\n  9.7624692155149551E-01 a      2056     0    83     1     6\n  3.1512825691726691E+00 a      2057     0    83     1     7\n  3.4403643865901410E+00 a      2058     0    83     1     8\n  3.4470775987725171E+00 a      2059     0    83     1     9\n  1.0312923991922447E+00 a      2060     0    83     1    10\n -1.1384716373972918E+00 a      2061     0    83     1    11\n -3.4604865167681549E+00 a      2062     0    83     1    12\n  3.2983941553367444E+00 a      2063     0    83     1    13\n -5.2601160301318561E-01 a      2064     0    83     1    14\n  2.4779949688240781E+00 a      2065     0    83     1    15\n  4.6975829572898702E+00 a      2066     0    83     1    16\n -9.0176618086769467E-01 a      2067     0    83     1    17\n -1.8370204749211532E+00 a      2068     0    83     1    18\n -3.2701524271182052E+00 a      2069     0    83     1    19\n  2.0765788783194125E-01 a      2070     0    83     1    20\n  9.5711301178162317E-02 a      2071     0    83     1    21\n  2.5478903218124289E+00 a      2072     0    83     1    22\n -3.0133129094716313E+00 a      2073     0    83     1    23\n  9.3011985919731177E-01 a      2074     0    83     1    24\n  3.9604751874423534E+00 a      2075     0    83     1    25\n  2.8411853280969890E+00 a      2076     0    84     1     1\n  5.0273463665643914E-01 a      2077     0    84     1     2\n  2.2035261374112985E-01 a      2078     0    84     1     3\n  2.0156240764669140E+00 a      2079     0    84     1     4\n  4.1475081428715193E+00 a      2080     0    84     1     5\n  2.1556487762674350E+00 a      2081     0    84     1     6\n  6.2312917756599315E+00 a      2082     0    84     1     7\n -1.3392921201738335E+00 a      2083     0    84     1     8\n -2.8523130808420272E-01 a      2084     0    84     1     9\n  2.3329551247683065E+00 a      2085     0    84     1    10\n  3.7537528298794820E+00 a      2086     0    84     1    11\n  1.7837707693054017E+00 a      2087     0    84     1    12\n  1.3684487458348522E+00 a      2088     0    84     1    13\n  1.9431711446093884E+00 a      2089     0    84     1    14\n -5.3156670418548879E-01 a      2090     0    84     1    15\n -1.4536229184270499E+00 a      2091     0    84     1    16\n  5.3662653143135744E-02 a      2092     0    84     1    17\n  5.8081828243849620E-01 a      2093     0    84     1    18\n  1.4646786630828024E+00 a      2094     0    84     1    19\n -1.3363179633208813E+00 a      2095     0    84     1    20\n -5.6026357121489057E-01 a      2096     0    84     1    21\n  7.3848454338698821E-01 a      2097     0    84     1    22\n -1.2920055778703279E+00 a      2098     0    84     1    23\n  1.8873800747307370E+00 a      2099     0    84     1    24\n -4.2409929140803886E+00 a      2100     0    84     1    25\n -7.1505124959921940E-01 a      2101     0    85     1     1\n  9.6784383027406917E-01 a      2102     0    85     1     2\n  2.8007659467429702E-01 a      2103     0    85     1     3\n -6.9208309673234469E-01 a      2104     0    85     1     4\n -9.2380783441488867E-01 a      2105     0    85     1     5\n  1.0023159361464298E+00 a      2106     0    85     1     6\n  2.9670265572246851E-01 a      2107     0    85     1     7\n -8.8810942686575967E-01 a      2108     0    85     1     8\n -1.7014197875604595E+00 a      2109     0    85     1     9\n -3.6018130748246611E+00 a      2110     0    85     1    10\n  2.9651286565045361E+00 a      2111     0    85     1    11\n  4.4757353261205060E+00 a      2112     0    85     1    12\n  3.9020327185644005E-01 a      2113     0    85     1    13\n -5.1514191772100004E-01 a      2114     0    85     1    14\n  1.5898342921159506E-01 a      2115     0    85     1    15\n -2.8105429197212561E-01 a      2116     0    85     1    16\n  2.9824164584254373E+00 a      2117     0    85     1    17\n  7.9786950806819157E-01 a      2118     0    85     1    18\n  2.1979111636896290E-01 a      2119     0    85     1    19\n -2.9006550501959077E-01 a      2120     0    85     1    20\n -1.3298976020282940E+00 a      2121     0    85     1    21\n  1.9465186247481499E+00 a      2122     0    85     1    22\n  2.1220863316223597E+00 a      2123     0    85     1    23\n  3.3517647843148451E-01 a      2124     0    85     1    24\n  2.6807153716205151E-01 a      2125     0    85     1    25\n -2.6521357816115776E+00 a      2126     0    86     1     1\n  2.0611889401163226E+00 a      2127     0    86     1     2\n  2.0441483563792979E+00 a      2128     0    86     1     3\n -8.9437297819651418E-01 a      2129     0    86     1     4\n -2.4171924838075137E-01 a      2130     0    86     1     5\n -1.4289724372162758E+00 a      2131     0    86     1     6\n -7.5741278098496023E-01 a      2132     0    86     1     7\n  1.4295202066372050E+00 a      2133     0    86     1     8\n -2.6910235940166696E+00 a      2134     0    86     1     9\n -2.3598091945491380E+00 a      2135     0    86     1    10\n -4.3137581168416361E-01 a      2136     0    86     1    11\n  1.8481935739748611E-02 a      2137     0    86     1    12\n -1.9427976327121557E-01 a      2138     0    86     1    13\n  1.1846748160820451E+00 a      2139     0    86     1    14\n  3.9655077152763507E-01 a      2140     0    86     1    15\n  1.6336726766660348E+00 a      2141     0    86     1    16\n  1.1789111624737423E+00 a      2142     0    86     1    17\n  8.3965705138934588E-01 a      2143     0    86     1    18\n  1.1192330802581236E+00 a      2144     0    86     1    19\n  1.2087283642350153E+00 a      2145     0    86     1    20\n  1.4346753713148717E+00 a      2146     0    86     1    21\n  1.3204441487669138E+00 a      2147     0    86     1    22\n  5.1143133061864499E-01 a      2148     0    86     1    23\n -2.1721082405339806E-02 a      2149     0    86     1    24\n -3.5488330386313349E-01 a      2150     0    86     1    25\n  1.7775026745981628E+00 a      2151     0    87     1     1\n  9.4737384706948380E-01 a      2152     0    87     1     2\n  2.1936540431661764E+00 a      2153     0    87     1     3\n  2.4111833263225106E+00 a      2154     0    87     1     4\n  1.4403174726340995E-01 a      2155     0    87     1     5\n -3.3871270209548752E+00 a      2156     0    87     1     6\n  4.0713191577747274E+00 a      2157     0    87     1     7\n -1.6895043401279199E+00 a      2158     0    87     1     8\n -8.8532784776786755E-01 a      2159     0    87     1     9\n -3.5941705422798931E+00 a      2160     0    87     1    10\n  4.3580379730801138E+00 a      2161     0    87     1    11\n -2.4357414008432148E+00 a      2162     0    87     1    12\n  2.8866570553394704E+00 a      2163     0    87     1    13\n  3.9628703370211338E+00 a      2164     0    87     1    14\n -1.0298514567031141E+00 a      2165     0    87     1    15\n -1.8112724692644218E+00 a      2166     0    87     1    16\n -4.0989560502588834E-01 a      2167     0    87     1    17\n  6.4079561308084765E-01 a      2168     0    87     1    18\n -6.8136885379239329E-02 a      2169     0    87     1    19\n -9.9565494627090101E-01 a      2170     0    87     1    20\n  3.6949310057914588E+00 a      2171     0    87     1    21\n  7.8343270700304490E-01 a      2172     0    87     1    22\n  3.7452731766573906E+00 a      2173     0    87     1    23\n  1.5564428181259020E+00 a      2174     0    87     1    24\n  1.3555942151329516E+00 a      2175     0    87     1    25\n  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-3.2710984446723018E-01 a      6117     1    25     2    17\n  3.6170508884768859E-02 a      6118     1    25     2    18\n  5.2233141845527287E-01 a      6119     1    25     2    19\n -1.3550639878027124E+00 a      6120     1    25     2    20\n -5.7651450620355738E-01 a      6121     1    25     2    21\n  5.8634654596304436E-01 a      6122     1    25     2    22\n -4.6601560842664419E-01 a      6123     1    25     2    23\n  2.8887081075808779E-01 a      6124     1    25     2    24\n -1.2300760719234261E+00 a      6125     1    25     2    25\n -6.3156792037158438E-01 b      6126     2     1\n  1.8170046149112681E-01 b      6127     2     2\n  4.5688392926605031E-01 b      6128     2     3\n -1.6501891894738017E+00 b      6129     2     4\n  1.1975451814330686E-02 b      6130     2     5\n  5.7349917547685818E+00 b      6131     2     6\n  3.0878671525770407E-01 b      6132     2     7\n -1.7691453761290754E-01 b      6133     2     8\n -4.6323519485014647E-01 b      6134     2     9\n  1.6537646869123346E-01 b      6135     2    10\n -2.0387319322850002E+00 b      6136     2    11\n -1.6077917657058804E+00 b      6137     2    12\n -2.7441159559723682E+00 b      6138     2    13\n  7.5483249756142445E-01 b      6139     2    14\n  1.9116717641248275E+00 b      6140     2    15\n  9.6879186451292998E-01 b      6141     2    16\n  4.0148857566845964E-01 b      6142     2    17\n -1.9013439069607216E-02 b      6143     2    18\n  8.0421297285919979E-01 b      6144     2    19\n  6.3320812281530592E-01 b      6145     2    20\n  2.8332265792374489E+00 b      6146     2    21\n  2.5608177668550780E-01 b      6147     2    22\n  1.8708811112047341E-01 b      6148     2    23\n  2.9387553981500689E+00 b      6149     2    24\n -2.7119565740406868E+00 b      6150     2    25\n  1.5052923406415379E+00 a      6151     2     1     3     1\n  1.0384106893897140E+00 a      6152     2     2     3     1\n  1.1201956383242404E-01 a      6153     2     3     3     1\n -3.4308047261117157E-02 a      6154     2     4     3     1\n -5.1264188840114286E-02 a      6155     2     5     3     1\n  2.4273882407453127E+00 a      6156     2     6     3     1\n  1.4327238660510786E+00 a      6157     2     7     3     1\n  3.4306964791630151E-01 a      6158     2     8     3     1\n  7.5278391035421843E-01 a      6159     2     9     3     1\n -4.3555885246441058E-02 a      6160     2    10     3     1\n  5.9738115542131187E-01 a      6161     2    11     3     1\n -1.3052897656476148E-01 a      6162     2    12     3     1\n -3.0747547909748607E-01 a      6163     2    13     3     1\n -4.2785507608690176E-01 a      6164     2    14     3     1\n  3.4271657489943537E+00 a      6165     2    15     3     1\n  7.7143815952288031E-02 a      6166     2    16     3     1\n  6.4973849645688239E-02 a      6167     2    17     3     1\n  6.4993046699813084E-01 a      6168     2    18     3     1\n  5.6068219915368489E-01 a      6169     2    19     3     1\n  1.1274360992962646E+00 a      6170     2    20     3     1\n -3.0225908411317642E-01 a      6171     2    21     3     1\n  1.3204344784682329E+00 a      6172     2    22     3     1\n -4.5629598976386537E-01 a      6173     2    23     3     1\n  2.1232906349761507E-01 a      6174     2    24     3     1\n  1.5022971467852109E+00 a      6175     2    25     3     1\n  5.5077532151945463E-01 b      6176     3     1\n"
  },
  {
    "path": "examples/potentials/Ethylbenzene_SCAN/input.nn",
    "content": "###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.8547021561081563E+00\nconv_energy   6.2674740310100970E+03\nconv_length   9.4927514173056764E+01\n###############################################################################\n\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        C H          # Specification of elements.\ncutoff_type                     6 0.0          # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\nrandom_seed 987654321\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\njacobian_mode                   1\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntask_batch_size_energy          1\ntask_batch_size_force           1\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints                5             # Write energy comparison.\nwrite_trainforces                5             # Write force comparison.\nwrite_weights_epoch              5             # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n## ####################\n## # GRADIENT DESCENT #\n## ####################\n## gradient_type                   0              # Gradient descent type (0 = Fixed step size).\n## gradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\nsymfunction_short C 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 C -1.40E+01 1.40E+01 p2a\nsymfunction_short C 20 C -1.20E+01 1.20E+01 p2a\nsymfunction_short C 20 C -1.00E+01 1.00E+01 p2a\nsymfunction_short C 20 C -8.00E+00 8.00E+00 p2a\nsymfunction_short C 20 C -6.00E+00 6.00E+00 p2a\nsymfunction_short C 20 C -5.00E+00 5.00E+00 p2a\nsymfunction_short C 20 C -2.50E+00 7.50E+00 p2a\nsymfunction_short C 20 C 0.00E+00 1.00E+01 p2a\nsymfunction_short C 20 C 2.50E+00 1.25E+01 p2a\nsymfunction_short C 20 C 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short C 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short C 20 H -1.40E+01 1.40E+01 p2a\nsymfunction_short C 20 H -1.20E+01 1.20E+01 p2a\nsymfunction_short C 20 H -1.00E+01 1.00E+01 p2a\nsymfunction_short C 20 H -8.00E+00 8.00E+00 p2a\nsymfunction_short C 20 H -6.00E+00 6.00E+00 p2a\nsymfunction_short C 20 H -5.00E+00 5.00E+00 p2a\nsymfunction_short C 20 H -2.50E+00 7.50E+00 p2a\nsymfunction_short C 20 H 0.00E+00 1.00E+01 p2a\nsymfunction_short C 20 H 2.50E+00 1.25E+01 p2a\nsymfunction_short C 20 H 5.00E+00 1.50E+01 p2a\n \n \n \n \n \n \nsymfunction_short H 20 C -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 C -1.40E+01 1.40E+01 p2a\nsymfunction_short H 20 C -1.20E+01 1.20E+01 p2a\nsymfunction_short H 20 C -1.00E+01 1.00E+01 p2a\nsymfunction_short H 20 C -8.00E+00 8.00E+00 p2a\nsymfunction_short H 20 C -6.00E+00 6.00E+00 p2a\nsymfunction_short H 20 C -5.00E+00 5.00E+00 p2a\nsymfunction_short H 20 C -2.50E+00 7.50E+00 p2a\nsymfunction_short H 20 C 0.00E+00 1.00E+01 p2a\nsymfunction_short H 20 C 2.50E+00 1.25E+01 p2a\nsymfunction_short H 20 C 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short H 20 H -1.50E+01 1.50E+01 p2\nsymfunction_short H 20 H -1.40E+01 1.40E+01 p2a\nsymfunction_short H 20 H -1.20E+01 1.20E+01 p2a\nsymfunction_short H 20 H -1.00E+01 1.00E+01 p2a\nsymfunction_short H 20 H -8.00E+00 8.00E+00 p2a\nsymfunction_short H 20 H -6.00E+00 6.00E+00 p2a\nsymfunction_short H 20 H -5.00E+00 5.00E+00 p2a\nsymfunction_short H 20 H -2.50E+00 7.50E+00 p2a\nsymfunction_short H 20 H 0.00E+00 1.00E+01 p2a\nsymfunction_short H 20 H 2.50E+00 1.25E+01 p2a\nsymfunction_short H 20 H 5.00E+00 1.50E+01 p2a\n \n \nsymfunction_short C 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C C -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C C -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short C 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 C H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \n \n \nsymfunction_short C 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short C 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 H H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short C 22 H H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short C 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \n \n \n \n \n \n \n \n \n \n \nsymfunction_short H 22 C C -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C C -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C C -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C C -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 C C 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \nsymfunction_short H 22 C H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 C H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 C H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 C H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \n \n \nsymfunction_short H 22 H H -1.50E+01 1.50E+01 -90.00 90.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 90.00 270.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 0.00 120.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 60.00 180.00 p2\nsymfunction_short H 22 H H -1.50E+01 1.50E+01 49.10 169.10 p2\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.40E+01 1.40E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.20E+01 1.20E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H -1.00E+01 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 H H -8.00E+00 8.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 -90.00 90.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 90.00 270.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 0.00 180.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 0.00 120.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 60.00 180.00 p2a\nsymfunction_short H 22 H H -6.00E+00 6.00E+00 49.10 169.10 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 0.00E+00 1.00E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 2.50E+00 1.25E+01 49.10 169.10 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 -90.00 90.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 90.00 270.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 180.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 0.00 120.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 60.00 180.00 p2a\nsymfunction_short H 22 H H 5.00E+00 1.50E+01 49.10 169.10 p2a\n \n \n \n"
  },
  {
    "path": "examples/potentials/Ethylbenzene_SCAN/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.2546559757006401E+01   2.2343237809189908E+01   1.7734001143187928E+01   1.5596535256693718E+00\n         1          2   8.4533975944444197E+00   2.1378779062642725E+01   1.4885243204618567E+01   1.5871257822529075E+00\n         1          3   7.9657391793830357E-12   1.0513500116637253E-01   1.1261160053477924E-02   1.2038805389511614E-02\n         1          4   3.2997737249129688E-04   3.1113020951761805E-01   6.0626282023127649E-02   5.4291529654562604E-02\n         1          5   1.5720242124501316E-01   4.7256846191877742E+00   1.5556007191186063E+00   8.1649964464959968E-01\n         1          6   3.5752850090918997E-02   1.1592433021208004E+00   3.7312762322190912E-01   2.1349296622080433E-01\n         1          7   2.6206282443333084E-01   2.4378489559361651E+00   1.0449960051979448E+00   4.0805586442113517E-01\n         1          8   2.5821153643652530E+00   1.2794766759988073E+01   7.5130296376665928E+00   1.4891343054266262E+00\n         1          9   6.9778339100918063E-01   3.9769851182683120E+00   2.1015392604699823E+00   6.0101308833116851E-01\n         1         10   8.5324837037667152E+00   2.3546437703374927E+01   1.5918683552428156E+01   2.2759350502150575E+00\n         1         11   1.5119723535932765E+00   5.9038933591739546E+00   3.5934926372302365E+00   7.7524836078321291E-01\n         1         12   1.6580918248956802E+01   4.0274494709533137E+01   2.8547335650502522E+01   2.9444637993862446E+00\n         1         13   1.5221829849547830E-01   2.9838454964920813E-01   2.2872753891630551E-01   1.7508427448017064E-02\n         1         14   2.8906994167262723E-01   4.7884690846049305E-01   3.8897782076968046E-01   2.2160473442697660E-02\n         1         15   1.2372708366562235E+00   3.9050979054798409E+00   1.8736489455075844E+00   2.9250480103403287E-01\n         1         16   5.9435951834012546E-01   1.2554307977700960E+00   7.9127552044115068E-01   6.8871393296862454E-02\n         1         17   9.0641050046735971E-01   2.6629626722354978E+00   1.3745239054093017E+00   1.9158056413794630E-01\n         1         18   1.4518879387119599E+00   1.4304905990949930E+01   5.6516688787416589E+00   1.6455028258248543E+00\n         1         19   1.3082280042611956E+00   4.5267890533831912E+00   2.2297170718049215E+00   3.6884535265454182E-01\n         1         20   5.0222131059497048E+00   2.4997839839437475E+01   1.3374858966201369E+01   2.6607953227781573E+00\n         1         21   1.8771357878995758E+00   6.5988113977254068E+00   3.4362059203438395E+00   5.6597320336964529E-01\n         1         22   7.0153315416294948E+00   3.7193435117007851E+01   2.2751999873847460E+01   3.8708970076340701E+00\n         1         23   1.0466011331190366E+01   3.5920230473543590E+01   2.3123927695433384E+01   3.9744229289012516E+00\n         1         24   3.1407729274565483E+01   1.0401738843325803E+02   6.6105737514679220E+01   1.1722348997880802E+01\n         1         25   5.1953808005467771E+01   1.6792456174664284E+02   1.0568808481727804E+02   1.8738756250124165E+01\n         1         26   3.6631405125687685E+01   1.1595656018025753E+02   7.2461531813491845E+01   1.2897889522962057E+01\n         1         27   3.3368267044783970E+01   1.0752473124808681E+02   6.6428912601389229E+01   1.1798125884415610E+01\n         1         28   1.2739493368476229E+01   4.0384642180645791E+01   2.5361590401427087E+01   4.5573289045654350E+00\n         1         29   2.5373693987483545E+01   6.9415090420987568E+01   4.3712011981856847E+01   6.2170040677462817E+00\n         1         30   5.2707593124605211E+01   1.8922530072300341E+02   1.1262852164121868E+02   1.8663230872909676E+01\n         1         31   7.8477865443126134E+01   3.0064453633619149E+02   1.7885807885739868E+02   2.9661861098635576E+01\n         1         32   5.2065809714239450E+01   2.0502422468819088E+02   1.2199893212779403E+02   2.0375669964423579E+01\n         1         33   4.5700092472036665E+01   1.8735557891995970E+02   1.1163419548335656E+02   1.8581186681569751E+01\n         1         34   1.5522877800033205E+01   7.4164525762651607E+01   4.2340699411936740E+01   7.2297823507150341E+00\n         1         35   7.8464158105759463E+00   3.8593508365228693E+01   1.8693809315894406E+01   3.4511236204372473E+00\n         1         36   1.2488805050471340E+01   9.4608712603725749E+01   4.3630475935501650E+01   9.6608999490772263E+00\n         1         37   2.0905688982633144E+01   1.4542304333167073E+02   7.1757206248228655E+01   1.6219012471416441E+01\n         1         38   1.3334306098988312E+01   1.0043870807947989E+02   5.0336264423895003E+01   1.1872214246052058E+01\n         1         39   1.0616706120903871E+01   9.3332037497405821E+01   4.6435673854453121E+01   1.0906242354818291E+01\n         1         40   3.3889235540003240E+00   3.8661250616489326E+01   1.7854023513103343E+01   4.3946058502183885E+00\n         1         41  -6.4369109024905057E-19   1.6445624201060316E-03   2.1026341793914263E-04   3.2342937211760715E-04\n         1         42  -3.0594259008690694E-18   1.4548204566661713E-02   1.1690267211096135E-03   1.7696416796497026E-03\n         1         43   0.0000000000000000E+00   2.2146299805505150E-02   1.3206171560634047E-03   2.0430000265411921E-03\n         1         44   0.0000000000000000E+00   2.1769350304090843E-02   5.3236669988874650E-04   1.1336721414443791E-03\n         1         45   0.0000000000000000E+00   2.2179573493440123E-02   4.7053145108945078E-04   1.1199771849501501E-03\n         1         46  -5.1075201666984216E-20   1.3751905556960925E-02   2.1159854666204548E-04   6.4253806310641387E-04\n         1         47   1.5138498305898993E-09   3.4601506432543609E-02   5.5820465985605286E-03   6.1679672004732351E-03\n         1         48   4.0319148082154855E-07   2.4729939260894374E-01   3.4333405523974701E-02   3.7484843225019868E-02\n         1         49   6.5892911618642728E-05   3.8762882820672118E-01   4.9522386907086234E-02   5.1731428038941298E-02\n         1         50   4.0520506500407146E-05   3.1613431077511872E-01   2.9175465042555700E-02   3.1824568818230842E-02\n         1         51   7.2889364232276555E-05   3.0399333429488035E-01   2.5752715455774660E-02   2.9323673555592088E-02\n         1         52   7.5964116631821895E-06   1.4051223480825670E-01   1.0016118122947563E-02   1.3724531338194240E-02\n         1         53   2.6083280383815220E-04   1.9720923525963810E-01   4.8571046697338270E-02   3.5309409102935306E-02\n         1         54   1.7405381105677423E-03   1.1981040832923155E+00   2.4287411417687402E-01   1.9159260384263760E-01\n         1         55   1.4326896009393309E-02   1.8671439020136209E+00   3.7777694427533209E-01   2.8486518989755732E-01\n         1         56   9.1675664967257788E-03   1.4075238990124990E+00   2.4470099440134480E-01   1.8376648749543767E-01\n         1         57   1.0892682080305045E-02   1.3052542323371481E+00   2.1988645408623148E-01   1.6584404833108735E-01\n         1         58   2.6961280704837914E-03   5.7294615830939477E-01   8.4522654939658798E-02   7.0327655468921293E-02\n         1         59   1.1707643670648969E-01   1.0330736647842006E+01   3.3349411417241677E+00   1.4534416636890315E+00\n         1         60   6.6585679925327956E-01   3.4501206484900599E+01   1.1456585133335579E+01   4.7666638680566491E+00\n         1         61   1.7942187257523878E+00   5.4045045265068872E+01   1.8553637867128007E+01   7.5503799099127695E+00\n         1         62   1.5385445116634804E+00   3.7892479630869417E+01   1.2841571582300940E+01   5.2501272939742849E+00\n         1         63   1.5373743457312383E+00   3.4360077781694031E+01   1.1878879073033742E+01   4.8067539012628799E+00\n         1         64   3.5585890522366720E-01   1.2772059661863997E+01   4.6027601996319376E+00   1.9200552755526270E+00\n         1         65   1.3038743147928944E-02   6.9422755135590608E-01   2.3519400005093749E-01   1.2512682717514029E-01\n         1         66   4.3032557345656038E-02   3.1218800567276586E+00   9.4526224280026105E-01   5.5365072534674631E-01\n         1         67   1.2442752171322150E-01   5.2196904498452215E+00   1.4998834744787473E+00   8.4729854917684855E-01\n         1         68   1.1162428428665291E-01   3.7722287968065631E+00   1.0037234405334878E+00   5.5902038913904917E-01\n         1         69   1.1113265795097929E-01   3.4489359134464559E+00   9.1308827385426783E-01   5.0452452317000640E-01\n         1         70   2.8286725600118197E-02   1.4004804828845114E+00   3.5167817887335340E-01   2.0640060676515160E-01\n         1         71   5.1138317074537856E+00   3.8408583386156167E+01   1.7660916607978784E+01   5.2093955435920902E+00\n         1         72   1.1740412260770380E+01   1.1813132009555655E+02   5.3559485757544024E+01   1.5498044683406425E+01\n         1         73   2.1188885893761928E+01   1.8659768249020874E+02   8.5463658051982449E+01   2.4609398939388853E+01\n         1         74   1.6023736173052860E+01   1.2588472502903002E+02   5.8509954138677458E+01   1.6935780660511149E+01\n         1         75   1.5542020223539240E+01   1.1468417123203781E+02   5.3542121721487646E+01   1.5514411266286237E+01\n         1         76   5.9834467335821948E+00   4.3984776352145765E+01   2.0359290239956763E+01   5.9224789218961993E+00\n         1         77   1.0843183879261327E-01   1.9649083356940853E+00   7.8410690002076777E-01   3.1608658443848547E-01\n         1         78   3.3798141654953118E-01   7.1160077367799621E+00   2.7225603941172136E+00   1.1996295674152380E+00\n         1         79   6.8188585405689628E-01   1.1412736901892632E+01   4.3473203533704856E+00   1.8672364311395386E+00\n         1         80   5.3231985172948981E-01   8.0808755530800891E+00   2.9510288292586688E+00   1.2515450134677077E+00\n         1         81   5.1047498748418951E-01   7.3649724201198987E+00   2.6986190872095084E+00   1.1353596012211851E+00\n         1         82   1.6561515331608642E-01   3.0209402427485119E+00   1.0379945577551426E+00   4.5659228474100949E-01\n         1         83   1.9396576137726274E+01   1.1738270462212618E+02   6.0811510318833811E+01   1.2870031588463029E+01\n         1         84   5.7663979561925309E+01   3.3968122233158545E+02   1.7212634440434721E+02   3.5770059681399161E+01\n         1         85   9.0490555687510934E+01   5.4746918089807514E+02   2.7470169203553519E+02   5.6835563889013876E+01\n         1         86   6.0757449582961804E+01   3.7703552134824599E+02   1.8826530434821339E+02   3.9017425885292418E+01\n         1         87   5.5480625260864286E+01   3.4634635309186126E+02   1.7269270966410292E+02   3.5737227961495428E+01\n         1         88   2.2418158569423223E+01   1.3069209610677677E+02   6.5855319992476183E+01   1.3763805777572372E+01\n         1         89   6.8291768386302279E-06   4.5692362897072160E-02   1.1491556244128750E-02   1.2522994518719795E-02\n         1         90   3.9094665012918751E-05   6.1744697742903462E-02   1.3644802382262067E-02   1.3741588689588692E-02\n         1         91   8.1596582946310577E-05   7.5427689269542603E-02   1.0055060135684944E-02   8.5856309195793037E-03\n         1         92   5.3575581330211968E-06   6.8604085281111366E-02   3.6319441298786736E-03   5.5938777040247262E-03\n         1         93   1.4425248863717672E-10   7.8666813881625677E-02   3.7517153709747857E-03   6.1809571605660734E-03\n         1         94  -8.0199121749975099E-17   7.2820932459482124E-02   1.7766437372472479E-03   4.1742326617015294E-03\n         1         95   5.5238889362782635E-03   2.5423577295383643E-01   8.9747755711382007E-02   7.8959050907158962E-02\n         1         96   2.1025573200374400E-02   4.1668654441002573E-01   1.5866189499886491E-01   9.8203361747502674E-02\n         1         97   1.9521108096059205E-02   6.1755177873196987E-01   1.6855623801396627E-01   8.0388719255224853E-02\n         1         98   3.4598943291519533E-03   4.8081127846125432E-01   8.4878219104587954E-02   5.8432368294007178E-02\n         1         99   8.5481052618439912E-04   4.5378818811024479E-01   7.8076200643656529E-02   6.0270235641175098E-02\n         1        100   1.5278897977881127E-06   3.1665857321343238E-01   3.0913789230552390E-02   3.6083636380319258E-02\n         1        101   6.0834677215616792E-02   8.0305371730745989E-01   3.2072247931142600E-01   1.9322179093500697E-01\n         1        102   1.9268389929968716E-01   1.6524669998390960E+00   7.0324472205017641E-01   2.9409003155864499E-01\n         1        103   2.1839397540916058E-01   2.4912145973841411E+00   9.1524905062814998E-01   3.3478832429159400E-01\n         1        104   5.2018659555928333E-02   1.8874654408117970E+00   5.4044116642715201E-01   2.5400868369774227E-01\n         1        105   3.5777058427528693E-02   1.7269856440659204E+00   4.8822493127273076E-01   2.4958306356909724E-01\n         1        106   3.6215320801149663E-04   8.7635658412764095E-01   1.8235120644375449E-01   1.3132190067999697E-01\n         1        107   2.1469614121863585E+00   2.0067938031788668E+01   7.7181553635479245E+00   2.5082163361958334E+00\n         1        108   3.2549694396730158E+00   5.9716013387192788E+01   1.7798812010735400E+01   7.2017470234059617E+00\n         1        109   3.9022186224014557E+00   9.9893935055533944E+01   2.8867580275824842E+01   1.2083924159269603E+01\n         1        110   2.1699879972759231E+00   7.1064618648846121E+01   2.0088638513178967E+01   8.7041653231588736E+00\n         1        111   1.9725423479342221E+00   6.5969065958683387E+01   1.8215068524300133E+01   7.9276208496518050E+00\n         1        112   1.7337154312280542E-01   2.6532627150724423E+01   6.6627825533056129E+00   3.0488029632192832E+00\n         1        113   3.0059124074259214E-01   1.8881524806314889E+00   8.9199057962874051E-01   3.5672432212592342E-01\n         1        114   7.5715762980888879E-01   4.7383730227888607E+00   2.1351820494723821E+00   6.8400178231357667E-01\n         1        115   8.9086282881399370E-01   7.4024431256650223E+00   3.1058941095326023E+00   9.9009170213583575E-01\n         1        116   3.5629605177124080E-01   5.3290619858618271E+00   1.9918462501019505E+00   7.4882463586904424E-01\n         1        117   2.7527708908480003E-01   4.8836113782297863E+00   1.8028202373878723E+00   7.1212468988548061E-01\n         1        118   2.0317665170712696E-02   2.0730673952237932E+00   6.6740322283521603E-01   3.3348237160125521E-01\n         1        119   1.0762121714244833E+01   8.5229450756179205E+01   3.6378354200053579E+01   9.5238025847485233E+00\n         1        120   2.5634436949595980E+01   2.2627244268693886E+02   9.0883626593653062E+01   2.6253879824792651E+01\n         1        121   3.7425805926879939E+01   3.5087552674459414E+02   1.4407674920041597E+02   4.0959156277609033E+01\n         1        122   2.3402366325727481E+01   2.3667602760289907E+02   9.8035755217581539E+01   2.7835218603392494E+01\n         1        123   2.1296391111490021E+01   2.1938463551014155E+02   8.9860868406501837E+01   2.5551623188044751E+01\n         1        124   6.9867609399613571E+00   8.9616710526363960E+01   3.4370215372115659E+01   9.9600854612266065E+00\n         1        125   8.7102440233419709E-01   4.1040397864322014E+00   2.1756344460438970E+00   6.0610944709977910E-01\n         1        126   2.1511994534093253E+00   1.2048345775428094E+01   5.4233434070180557E+00   1.4571998117755525E+00\n         1        127   2.8832061507245244E+00   1.9276714424125018E+01   8.3149931696577593E+00   2.3415179301479534E+00\n         1        128   1.5507694501366269E+00   1.3183691937413567E+01   5.5312399978303235E+00   1.7327815384582925E+00\n         1        129   1.2609750691492845E+00   1.2115098814766556E+01   5.0232082869474093E+00   1.6148339712126116E+00\n         1        130   2.2629233104882596E-01   5.0921276254709724E+00   1.8674239535594823E+00   6.9586570453371910E-01\n         1        131   2.9123035386060792E+01   2.1758118583681599E+02   1.0841650166298422E+02   2.2722990748722687E+01\n         1        132   6.5437806204411146E+01   5.6172352346867615E+02   2.7547642443289425E+02   6.1109913288965330E+01\n         1        133   1.0319345904154332E+02   8.9665556308604278E+02   4.3852750107012287E+02   9.6373548529542262E+01\n         1        134   7.0427011246433949E+01   6.1733776372642399E+02   3.0019290695754040E+02   6.5888368282825169E+01\n         1        135   6.5777935741346582E+01   5.6942003017294769E+02   2.7545653271927392E+02   6.0429073803901879E+01\n         1        136   2.7576163061603197E+01   2.1564911647937311E+02   1.0509959479946249E+02   2.3195878466047024E+01\n         1        137   4.5655214708306935E-04   1.0497199613149117E-02   4.0238907069097725E-03   1.7361040614934269E-03\n         1        138   3.8253942946254776E-04   1.8681462878789627E-02   4.6023957976248156E-03   1.9840636301389656E-03\n         1        139   1.6766796315220145E-04   1.3842814029604213E-02   2.4125032793031746E-03   1.2022401720029332E-03\n         1        140  -4.6441097676199194E-16   9.0093640481115206E-03   1.4187754576004880E-04   4.0089063673459571E-04\n         1        141  -5.8327890528959447E-16   9.8306723832768377E-03   1.4970215131859577E-04   5.1987950687165760E-04\n         1        142  -4.0070117581484566E-16   2.0312556557895059E-02   1.1611439909679991E-04   5.5854342305950008E-04\n         1        143   1.9728612614413617E-02   1.1809140135903519E-01   6.5492438568020381E-02   2.3588306355076871E-02\n         1        144   1.7558727664990479E-02   2.2096391355234332E-01   8.4239787657303486E-02   2.9040789028782366E-02\n         1        145   9.6677676986976664E-03   2.9666191476308712E-01   5.7528121310560190E-02   2.5910730834023229E-02\n         1        146   1.1598805333232927E-07   2.1740786315523450E-01   1.4989244184272523E-02   1.6684457988440742E-02\n         1        147   8.6948487907996964E-08   2.3783447732788712E-01   1.3802653248513328E-02   1.8905675375065194E-02\n         1        148  -6.1682400176145661E-17   2.2383731619675554E-01   7.2201031068754740E-03   1.5060778731785322E-02\n         1        149   8.3695608151578504E-02   5.4210963633104847E-01   2.4434919399205207E-01   8.4228598874693333E-02\n         1        150   8.0272711798478447E-02   1.1707207183262294E+00   3.5199508525221868E-01   1.1839828045347257E-01\n         1        151   5.2642620224437900E-02   1.8978816142985209E+00   3.2910600021800857E-01   1.5150171819592734E-01\n         1        152   1.4926908288559926E-03   1.3520012399668215E+00   1.5101489599993984E-01   1.1546402993548585E-01\n         1        153   8.2380203749053758E-04   1.3285844235625062E+00   1.4057376160559620E-01   1.2339997290207937E-01\n         1        154   7.9577718651318891E-06   7.8014303016822961E-01   6.3752169597091526E-02   8.3467101142772157E-02\n         1        155   3.0991348875259678E-01   1.6060310320128451E+01   3.2520062681561059E+00   1.7736769690675145E+00\n         1        156   1.0950721707393307E-01   3.5428257048362582E+01   5.9069145745765148E+00   3.7865400920395573E+00\n         1        157   2.2194519998071627E-01   6.3030954964358415E+01   9.5841653354003284E+00   6.3241185459500180E+00\n         1        158   8.4692074756437405E-02   4.8420017540232273E+01   6.8015221967900947E+00   4.7608853224495302E+00\n         1        159   4.5878103526638833E-02   4.6249824100705112E+01   6.4116116380945423E+00   4.5659643847716360E+00\n         1        160   1.8768677406752028E-03   1.7409543159487839E+01   2.5338750243379593E+00   2.0551077290994968E+00\n         1        161   2.1098668855046537E-01   1.5171133688454141E+00   6.1897392760894332E-01   2.0945550588467904E-01\n         1        162   2.0495215327061578E-01   3.6711400558325704E+00   9.6812626549042646E-01   3.2791822226274536E-01\n         1        163   1.6612723766458456E-01   6.1405317769564967E+00   1.1586848699470682E+00   5.0889898759817009E-01\n         1        164   4.4741376100373868E-02   4.3983414728262993E+00   6.7715886867904485E-01   3.9866745137742698E-01\n         1        165   2.2693100754651755E-02   4.1363559280970135E+00   6.3444823651843074E-01   4.0698245521697540E-01\n         1        166   1.6603775956097327E-03   1.9245790728670908E+00   2.6944428144147459E-01   2.4302429439380327E-01\n         1        167   2.7332861680161717E+00   5.0896256962233331E+01   1.5147122699982654E+01   5.8628462970765085E+00\n         1        168   3.7886350444597068E+00   1.1734871916065721E+02   3.4345754450118861E+01   1.4595983735849568E+01\n         1        169   6.6046698868307603E+00   1.9947841636931801E+02   5.8240354061401895E+01   2.4477614231341263E+01\n         1        170   3.8914233089639390E+00   1.4431792553104302E+02   4.1621292209114685E+01   1.7777996637655356E+01\n         1        171   2.7018548415703805E+00   1.3587262880412180E+02   3.8416552492075752E+01   1.6270838644674612E+01\n         1        172   5.2372735138685278E-01   5.3918208091843574E+01   1.4664785399595678E+01   6.2186903657576122E+00\n         1        173   4.5877854702900894E-01   3.3549331057236649E+00   1.3310157711292494E+00   4.1564650392545216E-01\n         1        174   4.7696160169867141E-01   8.0901564907280665E+00   2.2832124287103612E+00   7.5181089020743275E-01\n         1        175   5.9823346357564844E-01   1.3647930676682734E+01   3.1923637690886180E+00   1.2498397126060981E+00\n         1        176   2.7334936636448992E-01   9.7912841348947595E+00   2.0736374345878046E+00   9.7174675873031324E-01\n         1        177   1.9713196483401321E-01   9.0580557428434698E+00   1.9406343352692832E+00   9.5734757552102723E-01\n         1        178   2.0849431259173590E-02   3.9074914478902456E+00   7.9380386690542104E-01   5.1450227679090677E-01\n         1        179   4.1658709074439422E+00   1.0314113975657527E+02   4.1870816671991676E+01   1.3343380563596151E+01\n         1        180   8.5655829127939640E+00   2.9029900497660361E+02   1.0719491225996300E+02   3.7280360147391207E+01\n         1        181   1.3923969009544516E+01   4.6712207142172917E+02   1.7451027569855944E+02   5.9971382453327621E+01\n         1        182   9.3578098551949083E+00   3.2100999642058457E+02   1.2054865315632786E+02   4.1449875854972809E+01\n         1        183   9.4662158704897070E+00   2.9108110726903089E+02   1.0999850509775632E+02   3.7892882585534082E+01\n         1        184   4.8167325246627959E+00   1.1002907165391024E+02   4.1577202220509250E+01   1.4860960635764441E+01\n         2          1   1.3776363591373302E+01   2.2957951972848651E+01   1.8606554005773212E+01   1.5073318700135985E+00\n         2          2   8.7199990012375146E+00   2.0454273577725090E+01   1.4022355297269060E+01   1.4746846180685842E+00\n         2          3   6.4814111526789731E-04   8.1213506707982974E-01   2.8590942364538185E-01   1.8651064349546770E-01\n         2          4   2.5059956987351750E-02   1.2667159798183374E+00   4.8622227596210038E-01   3.0236780811406250E-01\n         2          5   1.3470935864030293E+00   4.6296472882944428E+00   2.3420611818844792E+00   8.2275752986446493E-01\n         2          6   3.3422186968815737E-01   2.1786967394313095E+00   9.8909440055143860E-01   4.7679670377394512E-01\n         2          7   1.0576441794647604E+00   3.3869792746896885E+00   1.7181548817616268E+00   5.9905248168628600E-01\n         2          8   2.6878421392017882E+00   1.2692697538027918E+01   7.0645860984270739E+00   1.5787360497153005E+00\n         2          9   1.8203218195793918E+00   4.9717324173758648E+00   2.7871463397561520E+00   6.9347371462237362E-01\n         2         10   8.7475704232050866E+00   2.5173360646478670E+01   1.6718573707751705E+01   2.4840986758238208E+00\n         2         11   2.7382618384943500E+00   6.9453447160046098E+00   4.2952574004297990E+00   7.8111920208212704E-01\n         2         12   1.8851144037212421E+01   3.9011067373622524E+01   2.8439999842309334E+01   2.8973610223390494E+00\n         2         13   2.1938704604525072E-02   2.4278596181240208E-01   1.3966656398260360E-01   4.7743689190339902E-02\n         2         14   8.2453786654100192E-02   5.6813570538856517E-01   3.4226650459011293E-01   1.0383952107048113E-01\n         2         15   9.7738620935843368E-01   3.9576248397183154E+00   2.5040397514391461E+00   6.4045850733191390E-01\n         2         16   2.8758294162978215E-01   1.4088012487930615E+00   8.8731969282744738E-01   2.4352444127974410E-01\n         2         17   5.7309158143535921E-01   2.5570553746833258E+00   1.5740797410192757E+00   3.9814294951135115E-01\n         2         18   1.9196879204445652E+00   1.3516067305596030E+01   4.8492264697717165E+00   1.2284755250693586E+00\n         2         19   9.3819918019549753E-01   4.0321505810489775E+00   2.4224123294478863E+00   5.3249268478067002E-01\n         2         20   2.7189036470485117E+00   2.5764632658647479E+01   1.1363393780854373E+01   3.1435260622044825E+00\n         2         21   1.5272520603339936E+00   6.1065438911067842E+00   3.5214170867706738E+00   6.4225879456699486E-01\n         2         22   1.0536246615404965E+01   3.4812337399220780E+01   2.2784150253713509E+01   3.6647639767937608E+00\n         2         23   1.2985440522266781E+01   3.8374012290107089E+01   2.5288549463799669E+01   4.0687725377970283E+00\n         2         24   3.8903748971999491E+01   1.1099309074081349E+02   7.2623233195889412E+01   1.2041651588081979E+01\n         2         25   6.2500060925543018E+01   1.7759035930318592E+02   1.1638170889738701E+02   1.9277833770631165E+01\n         2         26   4.2888959474698424E+01   1.2257577626993633E+02   8.0042470615650984E+01   1.3275308071500660E+01\n         2         27   3.9506077892099192E+01   1.1212113281750891E+02   7.3172707144088449E+01   1.2106000881404475E+01\n         2         28   1.5793062344615720E+01   4.2971666278141029E+01   2.7893101020471658E+01   4.3702736918234084E+00\n         2         29   2.4802673249924243E+01   6.9017933881112768E+01   4.3389312830921035E+01   5.9495629405692609E+00\n         2         30   5.9618367367357486E+01   1.8443557117191736E+02   1.0871019873537360E+02   1.7910093269006353E+01\n         2         31   9.6575915089425990E+01   2.9719406014649456E+02   1.7551161719348224E+02   2.8196436429474836E+01\n         2         32   6.5473848476456752E+01   2.0584211888267521E+02   1.2123004518753439E+02   1.9222780522792540E+01\n         2         33   5.8982987051376384E+01   1.8992722621955798E+02   1.1142245394148748E+02   1.7399153370562129E+01\n         2         34   2.0605581937033215E+01   7.4209573187776883E+01   4.2817295904223712E+01   6.4911336102606061E+00\n         2         35   7.4456208890198781E+00   3.1906049388983991E+01   1.5563708404776683E+01   3.0388966016741130E+00\n         2         36   1.3812051897570651E+01   8.7424746821207094E+01   3.9435770596362822E+01   8.6976616818069363E+00\n         2         37   2.3453616215882981E+01   1.3834065405260489E+02   6.4996967466943119E+01   1.4497361586952412E+01\n         2         38   1.6838046182766828E+01   9.4686112773616316E+01   4.5511126916323065E+01   1.0554164051726149E+01\n         2         39   1.5270218684494301E+01   8.6019931901723126E+01   4.1524240495394437E+01   9.6207851983673027E+00\n         2         40   3.7653429920482191E+00   3.2997631116746184E+01   1.5272747297903418E+01   3.6428308941773397E+00\n         2         41  -2.0800952413783606E-16   2.9783467238342172E-03   8.6047052876964117E-05   1.7504994945839993E-04\n         2         42   9.2362942243410839E-05   9.5375046073687950E-02   8.4595739891389216E-03   1.2689979040796287E-02\n         2         43   1.4156944817621988E-04   4.9342300512255999E-01   7.2206254631782096E-02   1.3299354745310160E-01\n         2         44   8.3590548533974391E-05   5.3092175879535841E-01   7.4877946187766400E-02   1.4034038090021839E-01\n         2         45   7.5552134521690293E-05   5.1515723573033345E-01   6.8442671402915822E-02   1.3089060818694798E-01\n         2         46   0.0000000000000000E+00   6.4144708898461703E-02   4.9436206852273516E-03   1.0154308868373882E-02\n         2         47   1.4854099217966100E-05   6.1891989609639875E-02   8.4765092465489428E-03   8.3545162372741216E-03\n         2         48   1.3377824499372810E-02   4.4208760871679770E-01   8.7337893231215935E-02   6.6740831898821032E-02\n         2         49   2.8694583683801286E-02   1.5654365689397023E+00   3.2701527205384123E-01   4.1874818207502423E-01\n         2         50   1.7537273691342860E-02   1.5223378355083639E+00   3.0762936598079910E-01   4.2782455848808010E-01\n         2         51   1.5088319624021764E-02   1.4187167620570111E+00   2.7088803612965551E-01   4.0313134067579370E-01\n         2         52   5.8767973226431865E-04   2.4590915357590398E-01   3.5837588159585924E-02   4.9938185080239138E-02\n         2         53   3.2890211803067765E-03   3.5922289785658601E-01   7.8006264071889680E-02   5.5812221516648684E-02\n         2         54   9.8445057311949288E-02   1.5765263516542394E+00   4.2388573038514571E-01   2.4101985580778179E-01\n         2         55   2.5460515478681611E-01   3.8043361709366872E+00   1.0059336958797560E+00   8.6412903684893982E-01\n         2         56   1.9086933513449286E-01   3.2824189130985082E+00   8.3711809858829589E-01   8.2539366213035437E-01\n         2         57   1.3143884802675210E-01   3.0670111185000741E+00   7.2963128585573356E-01   7.8538854888319598E-01\n         2         58   3.4700789601495918E-02   7.3515802519785289E-01   1.6425977617278434E-01   1.3974695264052150E-01\n         2         59   3.7377796397893398E-01   9.2379553617057173E+00   2.9756886218548342E+00   1.4249861408764428E+00\n         2         60   1.2123099317454138E+00   3.3841363869788943E+01   1.0513008251336796E+01   4.9758240569983840E+00\n         2         61   1.7184623163577115E+00   5.3905134558728676E+01   1.6600840725833685E+01   7.7390649061672496E+00\n         2         62   1.1128939908099134E+00   3.6813730092768317E+01   1.1281878838968936E+01   5.2401517605507717E+00\n         2         63   1.0516915858050273E+00   3.2955289994218880E+01   1.0323906971470020E+01   4.7356552149701976E+00\n         2         64   5.3544541987168459E-01   1.2739587768489036E+01   4.1807757158013583E+00   1.7749578413961338E+00\n         2         65   4.2707247611989130E-02   1.0590721683720392E+00   3.3455245860743160E-01   1.7123423289240797E-01\n         2         66   3.5082973159644787E-01   4.1534680530596111E+00   1.3702422227098261E+00   6.0694836308784539E-01\n         2         67   8.7224764024501367E-01   8.3025130654234154E+00   2.6212650824198569E+00   1.5088064146196265E+00\n         2         68   6.1832207058833433E-01   6.3346372632766119E+00   1.9913552085863533E+00   1.3232799013388454E+00\n         2         69   5.0808746451269016E-01   5.8706203341426404E+00   1.7576701800087593E+00   1.2616960218012157E+00\n         2         70   2.3381764005597483E-01   1.7998107581680003E+00   5.3529525212717122E-01   2.7733529889238734E-01\n         2         71   4.8471321473736078E+00   4.4651897236891372E+01   1.9728055590722011E+01   5.9051897436620111E+00\n         2         72   1.4338569841046743E+01   1.3577974538230833E+02   5.9305312028115658E+01   1.7729217936081078E+01\n         2         73   2.5092175017592307E+01   2.1200359331886986E+02   9.4433246862732020E+01   2.7977584883020835E+01\n         2         74   1.8197893344543903E+01   1.4303827055879447E+02   6.4652918383034830E+01   1.9157517744434319E+01\n         2         75   1.6824995700405168E+01   1.3089165287629916E+02   5.9126852958279692E+01   1.7501776574132972E+01\n         2         76   5.6645849798224850E+00   5.0322748250689152E+01   2.2515595594225768E+01   6.7109304259830722E+00\n         2         77   2.3157469860024391E-01   2.5763181571942937E+00   1.0133756261850342E+00   3.7733256170682322E-01\n         2         78   1.0495359920129748E+00   8.9558307045087240E+00   3.5642278529303439E+00   1.2330623460930439E+00\n         2         79   2.1902201930704019E+00   1.6147363575960142E+01   6.1878848389164514E+00   2.4661300297146354E+00\n         2         80   1.6245497067506340E+00   1.1654335261310516E+01   4.4675196088161160E+00   1.9830693767990843E+00\n         2         81   1.3829442373224961E+00   1.0843027113070345E+01   4.0008461987199651E+00   1.8776603882077787E+00\n         2         82   6.4969878964138073E-01   3.7653419890324229E+00   1.3950056495229592E+00   4.8214978823104671E-01\n         2         83   2.5477934878676898E+01   1.1125290943670808E+02   6.0286552443623762E+01   1.2469629332334007E+01\n         2         84   7.3495535373271991E+01   3.1795727335908953E+02   1.7048363167330717E+02   3.5155467087667184E+01\n         2         85   1.1894965248416000E+02   5.1090686209467026E+02   2.7261259740474759E+02   5.6142269402976709E+01\n         2         86   8.0418668416325943E+01   3.5079811030509387E+02   1.8698900652479787E+02   3.8631419217085146E+01\n         2         87   7.2350287681903552E+01   3.2281587741926535E+02   1.7153812918881835E+02   3.5505300852010421E+01\n         2         88   2.5787725278712198E+01   1.2412317282454136E+02   6.5264680716321706E+01   1.3640785164101242E+01\n         2         89   5.2341035619083733E-04   8.8967640360901479E-03   2.8205313053402928E-03   1.3196552646362633E-03\n         2         90   2.7187703591868303E-04   3.6553280679833940E-02   4.1677799285378594E-03   4.4164048960438941E-03\n         2         91   5.0880015289545511E-03   2.2761283969577040E-01   1.0865510496573706E-01   4.3679199554560261E-02\n         2         92   4.2402439089947236E-03   2.4244184316279138E-01   1.2464346185249230E-01   4.8341452093109451E-02\n         2         93   4.7478809271539668E-03   2.3407790513972329E-01   1.2783705920455568E-01   4.7539688319504718E-02\n         2         94   2.4787974848261376E-03   4.9580895027098906E-02   2.4082866262788744E-02   1.1135660333080595E-02\n         2         95   2.5654050858959568E-02   1.6822857184470494E-01   6.9702831580278374E-02   2.7741393845116053E-02\n         2         96   2.2140931866466040E-02   2.7196778682998091E-01   8.4259207296709396E-02   4.5716757413234908E-02\n         2         97   2.0366880530198120E-01   1.1167725860096198E+00   5.2958585892848742E-01   1.7316732799250439E-01\n         2         98   1.6679852337100293E-01   1.1171594513417007E+00   5.5985613213438523E-01   1.8015605594313813E-01\n         2         99   1.7941533471921048E-01   1.0561238258776573E+00   5.8600056214151774E-01   1.5989411976702117E-01\n         2        100   2.5371138381238934E-02   2.7307525456475151E-01   1.6825135339362496E-01   5.6848316510319193E-02\n         2        101   1.7592581845260452E-01   7.1865274903905041E-01   3.2621725584219446E-01   1.0787968465080154E-01\n         2        102   1.9800851512877610E-01   1.5084242236143335E+00   5.2387856086323958E-01   2.0324810638344695E-01\n         2        103   9.7941648414195071E-01   3.2395281539184757E+00   1.5895662960002834E+00   4.2513107962706959E-01\n         2        104   9.8396910714038455E-01   2.9123883218531383E+00   1.4674048470067600E+00   3.8331769816002542E-01\n         2        105   1.0370877080943639E+00   2.6978769520099628E+00   1.5235353024082325E+00   2.9996278098110785E-01\n         2        106   1.1863209652235732E-01   9.1178931261902563E-01   5.8418752403428320E-01   1.6943033439055766E-01\n         2        107   1.8307424152062497E+00   2.0437917976337584E+01   6.0752728607426150E+00   2.3769972440138178E+00\n         2        108   4.0966689771516895E+00   6.2055800124979356E+01   1.4122478853724635E+01   5.5565586560638263E+00\n         2        109   4.5567449528614041E+00   1.0304260410387892E+02   2.3340653535370439E+01   9.4263869915278331E+00\n         2        110   1.6474340140541335E+00   7.1361001493979913E+01   1.6355694086262439E+01   6.9341722620372588E+00\n         2        111   1.6136778756652950E+00   6.3585920568925772E+01   1.4895460723207105E+01   6.4270980789089815E+00\n         2        112   3.1905601384379806E-01   2.0375770586228541E+01   5.6262630204553021E+00   2.7395671158907700E+00\n         2        113   5.1542385112864264E-01   1.9726700610269656E+00   9.6419872854352928E-01   2.4652131439439007E-01\n         2        114   7.7364039322841360E-01   4.7520409178938063E+00   1.8930544670448473E+00   5.6361111723022039E-01\n         2        115   2.1337507637326540E+00   8.2722107043034256E+00   4.1205893125139816E+00   1.0035896772124882E+00\n         2        116   1.8994552821336530E+00   6.5553092680717624E+00   3.3720727689203200E+00   8.0337971906483041E-01\n         2        117   2.0939144411929331E+00   5.9963101894806723E+00   3.3754750578718622E+00   6.5199844296118381E-01\n         2        118   3.0041211470459456E-01   2.2662831979447589E+00   1.4110287695441504E+00   3.5731595737294441E-01\n         2        119   6.3645295918998119E+00   8.7212967757256152E+01   3.2999251403539361E+01   1.0472571387848804E+01\n         2        120   1.1470464105459323E+01   2.3108019172751102E+02   7.9630918638296791E+01   2.8187908404727580E+01\n         2        121   2.1278468890529783E+01   3.5972769076286005E+02   1.2763304974564760E+02   4.3828684349843144E+01\n         2        122   1.5016319864502123E+01   2.4273095418898779E+02   8.7675054692177014E+01   2.9692307131959524E+01\n         2        123   1.3507978865763311E+01   2.2320662989797964E+02   8.0565386884466008E+01   2.7401351716692588E+01\n         2        124   5.5230004899537359E+00   8.8850729952253431E+01   3.1042037979064560E+01   1.0882449128654935E+01\n         2        125   1.1636119785202896E+00   4.5036402203019765E+00   2.3478796624434710E+00   4.8265993273892083E-01\n         2        126   2.3292981718935204E+00   1.2229027528558655E+01   5.1580281323875408E+00   1.2866312017459265E+00\n         2        127   4.6725406244153413E+00   2.0307004650689692E+01   9.6307942388527348E+00   2.1840849806647440E+00\n         2        128   3.5960466975756584E+00   1.4549561134118768E+01   7.2888067213445797E+00   1.6395125504091692E+00\n         2        129   3.7172419192939641E+00   1.3349831546287628E+01   7.0359035762346691E+00   1.4093840322206532E+00\n         2        130   7.9602109152306455E-01   5.2586961758272857E+00   2.9223324008128762E+00   6.3962019985531415E-01\n         2        131   4.2421478573481984E+01   2.1545181819624941E+02   1.0840530824286394E+02   2.1280742623483889E+01\n         2        132   9.6935173042244656E+01   5.6668783891883800E+02   2.7461268021164659E+02   5.7681929399081511E+01\n         2        133   1.5210882937768412E+02   8.8925741560567019E+02   4.3735048132336811E+02   9.1184415336723418E+01\n         2        134   1.0347513318466906E+02   6.0380074576797506E+02   2.9943882878430333E+02   6.2384768408519868E+01\n         2        135   9.3396073689498138E+01   5.5469398890179070E+02   2.7447701011688076E+02   5.7185345071924651E+01\n         2        136   3.4355694072592165E+01   2.1107653688670561E+02   1.0409634123431266E+02   2.2107043344353411E+01\n         2        137   2.4022363709054806E-07   1.4209115821242895E-03   4.6954629301672541E-04   2.4735563007031688E-04\n         2        138   6.3457185982437510E-08   5.4800912820231777E-03   6.6624277800292591E-04   3.7478772804472120E-04\n         2        139   2.3465461867642480E-08   8.4829701101682142E-02   2.7051666106326658E-02   1.7350673234620057E-02\n         2        140  -8.9797768154659563E-17   1.0092377361332103E-01   3.2037161939427482E-02   2.0673658576894762E-02\n         2        141  -7.9559883822224519E-17   1.0551261015470774E-01   3.3469879976410127E-02   2.1768973148138884E-02\n         2        142  -6.7366611645040197E-17   2.3242839120778132E-02   6.9921256402471878E-03   4.9169809307105456E-03\n         2        143   2.1062911326034371E-03   6.1447473859088206E-02   3.2877146410023129E-02   1.2804152045721986E-02\n         2        144   5.7157434811921156E-04   1.0661056388118885E-01   4.7620217324603080E-02   2.1615833409957323E-02\n         2        145   4.5170916276817753E-04   5.5075659510487152E-01   1.9155508169139884E-01   1.1198950107926528E-01\n         2        146   0.0000000000000000E+00   5.8821435134888034E-01   1.9609497371072843E-01   1.2336481024357500E-01\n         2        147   0.0000000000000000E+00   5.9426956377417672E-01   1.9667701555066086E-01   1.2916424776317159E-01\n         2        148  -7.1981824677217043E-17   1.6083012208762279E-01   4.4099885244901757E-02   3.6123732306916567E-02\n         2        149   3.1183844346484878E-02   3.3165377905314603E-01   1.9041656834773138E-01   6.5697318094721319E-02\n         2        150   1.7468703748095709E-02   8.9203887178036811E-01   3.0884291346297571E-01   1.3273333751276145E-01\n         2        151   1.1261065376785638E-02   1.9587562376845749E+00   6.4645669881307943E-01   3.2535127365086136E-01\n         2        152   3.5896493555871560E-04   1.7984970154113824E+00   5.4624534475215858E-01   3.1422371262402737E-01\n         2        153   3.2146558481187351E-04   1.7361200969750212E+00   5.2249399261790697E-01   3.2640477488401864E-01\n         2        154   1.9170802304639301E-05   5.1906530341340473E-01   1.3476576860610107E-01   1.2209998866602599E-01\n         2        155   8.1840259755860201E-01   1.5594249159894881E+01   2.5480147563845170E+00   9.4023878385982484E-01\n         2        156   4.7542569721655870E-01   3.3531589358968453E+01   4.6171453650268921E+00   2.6132171279273386E+00\n         2        157   3.0738894874348899E-01   5.7340549971175506E+01   6.6908487004451844E+00   4.5807701389511966E+00\n         2        158   6.3567156810183684E-02   4.5023216995322620E+01   4.3956044310167721E+00   3.5205232224344187E+00\n         2        159   5.2863448949719533E-02   4.2086094131093930E+01   4.0035851413359147E+00   3.1976205970551832E+00\n         2        160   6.4149968172717243E-03   1.8618075218843980E+01   1.4526833514225641E+00   1.2454636282220404E+00\n         2        161   1.4489452028832114E-01   1.0966593756356586E+00   5.3004356792959717E-01   1.5513127698684248E-01\n         2        162   1.0160574133187714E-01   3.1794557079835268E+00   9.5836851107842136E-01   3.8524701364310232E-01\n         2        163   7.6627314589045967E-02   5.4252913236855393E+00   1.6367931186779705E+00   7.1591678637586287E-01\n         2        164   2.2150001218022141E-02   4.0466331490957383E+00   1.2274854143268068E+00   6.0454284097536792E-01\n         2        165   1.8186823617799081E-02   3.7609945630553550E+00   1.1346293008253177E+00   6.0545850230785114E-01\n         2        166   3.1357228989072096E-03   1.2192894333018813E+00   3.2998396439263078E-01   2.6273445408423063E-01\n         2        167   5.9356688579077210E-01   5.2896811534252933E+01   1.2078900205515192E+01   6.4786720785965324E+00\n         2        168   7.8528450885121448E-01   1.2575672322168535E+02   2.5065916633656958E+01   1.4425120732404041E+01\n         2        169   1.5733945396317028E+00   2.1726161055496939E+02   4.2201295670647291E+01   2.4535911912158429E+01\n         2        170   1.2159121415855736E+00   1.5869487889684305E+02   3.0162630017512182E+01   1.7994902781170296E+01\n         2        171   9.7485945117709216E-01   1.4714352248898922E+02   2.8039385191222166E+01   1.6665425989282063E+01\n         2        172   5.7624328908054490E-01   5.2032605990435684E+01   1.1071136356893190E+01   6.5728652022350857E+00\n         2        173   3.8517869050529824E-01   2.6591072511076432E+00   1.1210065844709651E+00   2.6444065096677188E-01\n         2        174   3.7589446543088439E-01   7.5514221977898792E+00   2.2627973144563094E+00   8.2426976480805092E-01\n         2        175   3.8997673154004053E-01   1.2225782863663438E+01   3.6780385740373758E+00   1.4134595048547403E+00\n         2        176   1.8953769370358300E-01   8.5686057365350567E+00   2.6268076245223408E+00   1.0976078894743850E+00\n         2        177   1.7729708284564194E-01   7.7764375456882009E+00   2.3901076550888796E+00   1.0395830672085906E+00\n         2        178   3.5684992206404427E-02   2.7311579294234547E+00   7.5811964912914154E-01   4.4846628465095084E-01\n         2        179   7.4826693027104820E+00   9.9940754137346929E+01   4.2059453974550216E+01   1.2605635816476459E+01\n         2        180   1.7255242213055784E+01   2.6152979584973161E+02   1.0683124719178711E+02   3.4806498209133352E+01\n         2        181   3.1693079220817939E+01   4.0935023753583840E+02   1.7443471186787590E+02   5.5955565273310349E+01\n         2        182   2.4378595634715843E+01   2.7492475597054482E+02   1.2074254543255512E+02   3.8674324322101114E+01\n         2        183   2.3107639172579024E+01   2.4680054433882918E+02   1.0996855652172252E+02   3.5165587138237356E+01\n         2        184   7.3539876973635625E+00   9.7128322747635494E+01   4.1413102151684384E+01   1.3806641806589422E+01\n"
  },
  {
    "path": "examples/potentials/Ethylbenzene_SCAN/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -8.5559815049257306E+00 a         1     0     1     1     1\n  2.4455922401502130E+00 a         2     0     1     1     2\n  4.7522987330844790E+00 a         3     0     1     1     3\n -1.0544783349437394E+00 a         4     0     1     1     4\n  1.5860148045724824E+01 a         5     0     1     1     5\n  5.2740934002911546E+00 a         6     0     1     1     6\n -9.5856767902945546E+00 a         7     0     1     1     7\n  2.0208327915361588E+00 a         8     0     1     1     8\n -1.9221356432217263E-01 a         9     0     1     1     9\n  7.5509300171317122E+00 a        10     0     1     1    10\n  6.2488419702363194E+00 a        11     0     1     1    11\n  2.6500993233507542E+00 a        12     0     1     1    12\n -5.2976905163930770E+00 a        13     0     1     1    13\n -4.8296586807394855E+00 a        14     0     1     1    14\n  1.0750476036231758E+00 a        15     0     1     1    15\n -5.5679934068210435E-01 a        16     0     1     1    16\n  6.4518972784428490E+00 a        17     0     1     1    17\n -7.1327132812553842E+00 a        18     0     1     1    18\n -4.0392860056000508E+00 a        19     0     1     1    19\n  5.8010102453890440E+00 a        20     0     1     1    20\n -8.9590987302254632E+00 a        21     0     1     1    21\n  1.0731310874487839E+01 a        22     0     1     1    22\n  5.1548460695436893E-01 a        23     0     1     1    23\n  6.1343221569693815E+00 a        24     0     1     1    24\n  1.4235283083426873E+00 a        25     0     1     1    25\n -4.9169480836061492E+00 a        26     0     2     1     1\n -7.9769803801795396E+00 a        27     0     2     1     2\n -1.4353198359731416E+00 a        28     0     2     1     3\n  2.5859753346393188E+00 a        29     0     2     1     4\n  1.2998899000677383E+01 a        30     0     2     1     5\n -3.0058509859378448E+00 a        31     0     2     1     6\n  2.3428175954307708E+01 a        32     0     2     1     7\n -5.2965336655135999E+00 a        33     0     2     1     8\n  1.0429193716860453E+01 a        34     0     2     1     9\n  7.6452203557715643E+00 a        35     0     2     1    10\n  2.1156153724827798E+00 a        36     0     2     1    11\n -9.5104829181514425E+00 a        37     0     2     1    12\n -1.1260896921327607E+01 a        38     0     2     1    13\n -7.4313861462858000E-01 a        39     0     2     1    14\n -1.2099211359122032E+01 a        40     0     2     1    15\n -3.8078794322987894E+00 a        41     0     2     1    16\n  6.5263320236671598E+00 a        42     0     2     1    17\n -7.0181738280440555E+00 a        43     0     2     1    18\n  1.2754346067739859E+00 a        44     0     2     1    19\n -1.2160813658403619E+01 a        45     0     2     1    20\n  1.7046398372248357E+00 a        46     0     2     1    21\n -5.1466591039032084E+00 a        47     0     2     1    22\n -4.0322403609694053E+00 a        48     0     2     1    23\n  2.8446741865839238E+00 a        49     0     2     1    24\n -5.6755848432248941E+00 a        50     0     2     1    25\n  3.0569416997418963E-01 a        51     0     3     1     1\n -2.0339726363366561E+00 a        52     0     3     1     2\n  5.4275862953199927E-01 a        53     0     3     1     3\n  8.4247361446310143E-01 a        54     0     3     1     4\n -2.0096270087087298E+00 a        55     0     3     1     5\n  3.5457341879134208E+00 a        56     0     3     1     6\n  6.2493448144074373E+00 a        57     0     3     1     7\n  4.4367957430080218E-01 a        58     0     3     1     8\n  7.5249083597456607E+00 a        59     0     3     1     9\n -5.2983749425939477E+00 a        60     0     3     1    10\n -1.1447204380018845E+00 a        61     0     3     1    11\n  2.0371105291844023E+00 a        62     0     3     1    12\n  4.9460343173087198E+00 a        63     0     3     1    13\n -2.5324198443863527E-01 a        64     0     3     1    14\n -6.8210242278387163E+00 a        65     0     3     1    15\n  5.2913525991079347E-01 a        66     0     3     1    16\n -1.1858834803588463E+01 a        67     0     3     1    17\n  2.0281285870296055E+00 a        68     0     3     1    18\n -7.4323083735041240E-01 a        69     0     3     1    19\n -3.6630569048996651E+00 a        70     0     3     1    20\n  5.5559397845550196E+00 a        71     0     3     1    21\n -3.4351264830745003E+00 a        72     0     3     1    22\n  6.1768023469299504E-01 a        73     0     3     1    23\n  2.0749818921593999E+00 a        74     0     3     1    24\n -2.5626468655688139E+00 a        75     0     3     1    25\n -1.3202441000101630E+00 a        76     0     4     1     1\n  2.8538550305518856E-02 a        77     0     4     1     2\n -9.6019553345805086E-01 a        78     0     4     1     3\n  3.4022479966873895E+00 a        79     0     4     1     4\n  5.4968466118466992E+00 a        80     0     4     1     5\n -6.0087214708032732E+00 a        81     0     4     1     6\n -6.1882809075966945E+00 a        82     0     4     1     7\n -6.8184722309183643E-01 a        83     0     4     1     8\n -1.3375705013665093E+00 a        84     0     4     1     9\n  9.7521840098765082E+00 a        85     0     4     1    10\n  9.3680139667398663E+00 a        86     0     4     1    11\n  3.0574474852324185E+00 a        87     0     4     1    12\n -6.3422643036360196E+00 a        88     0     4     1    13\n -1.6227424970545004E+00 a        89     0     4     1    14\n  4.1353881168607126E-01 a        90     0     4     1    15\n  1.3316483852554977E+00 a        91     0     4     1    16\n  4.3136543409627164E+00 a        92     0     4     1    17\n  6.7723830444559008E+00 a        93     0     4     1    18\n  6.5621518357273692E+00 a        94     0     4     1    19\n  8.6800897939306132E-01 a        95     0     4     1    20\n -7.8877300531312589E-01 a        96     0     4     1    21\n -3.8698963042552945E+00 a        97     0     4     1    22\n -3.8319416333295337E+00 a        98     0     4     1    23\n  2.6260680834500723E+00 a        99     0     4     1    24\n  1.6251295723207098E+00 a       100     0     4     1    25\n -5.5735377514171125E-01 a       101     0     5     1     1\n  2.0051785182859159E+00 a       102     0     5     1     2\n  6.6962545646613005E+00 a       103     0     5     1     3\n  2.5425548387171437E+00 a       104     0     5     1     4\n -3.6794366823752940E+00 a       105     0     5     1     5\n  1.2030172764726759E+00 a       106     0     5     1     6\n  2.0203803082009184E+00 a       107     0     5     1     7\n  1.0689292000624320E+01 a       108     0     5     1     8\n -8.4440010346032490E-01 a       109     0     5     1     9\n -2.2600549082739501E+00 a       110     0     5     1    10\n -5.7875718744057583E+00 a       111     0     5     1    11\n  5.5007380754678952E+00 a       112     0     5     1    12\n  1.7024864471041243E+00 a       113     0     5     1    13\n -1.3032359113338730E+01 a       114     0     5     1    14\n -5.0066376932295418E+00 a       115     0     5     1    15\n  2.1400235856255891E+00 a       116     0     5     1    16\n  1.5291487496222489E+00 a       117     0     5     1    17\n  4.4059464236330657E+00 a       118     0     5     1    18\n  1.1144657471482894E+01 a       119     0     5     1    19\n -1.1090276935753343E+01 a       120     0     5     1    20\n -7.0209977418309144E+00 a       121     0     5     1    21\n  1.1634459160603861E+00 a       122     0     5     1    22\n -9.4122451424860731E+00 a       123     0     5     1    23\n  3.3283319340176551E+00 a       124     0     5     1    24\n -9.4962875505863149E+00 a       125     0     5     1    25\n -1.0753583381496806E+01 a       126     0     6     1     1\n -5.4609514294287917E+00 a       127     0     6     1     2\n -4.1128791813129792E+00 a       128     0     6     1     3\n -1.2980505992952660E+01 a       129     0     6     1     4\n -8.4319528116278004E+00 a       130     0     6     1     5\n  2.6916323811332741E+00 a       131     0     6     1     6\n  4.1173114753271172E+00 a       132     0     6     1     7\n  1.4517070606227620E+00 a       133     0     6     1     8\n -2.8477398086114674E+00 a       134     0     6     1     9\n  1.7355015630613344E+00 a       135     0     6     1    10\n  1.7250558320974116E+00 a       136     0     6     1    11\n -7.9970276305450856E+00 a       137     0     6     1    12\n -4.7779842556284198E+00 a       138     0     6     1    13\n -8.7207557780373648E+00 a       139     0     6     1    14\n -4.8205523949638431E+00 a       140     0     6     1    15\n  6.7245143009176700E-01 a       141     0     6     1    16\n  2.8340887554933003E-01 a       142     0     6     1    17\n  3.3497438610027888E+00 a       143     0     6     1    18\n  2.8804821120795681E+00 a       144     0     6     1    19\n -5.9041335162935935E+00 a       145     0     6     1    20\n -1.4848002578011865E+00 a       146     0     6     1    21\n -6.2591669115254245E-01 a       147     0     6     1    22\n  2.1192308145691118E+01 a       148     0     6     1    23\n  8.8285210993609908E-01 a       149     0     6     1    24\n -6.3130574310312175E+00 a       150     0     6     1    25\n -1.5704937470015987E+00 a       151     0     7     1     1\n  6.7611809515041987E-01 a       152     0     7     1     2\n  8.1559863031612867E+00 a       153     0     7     1     3\n  3.9270115239514021E+00 a       154     0     7     1     4\n  8.0365319137990561E+00 a       155     0     7     1     5\n  1.1408379765434110E-01 a       156     0     7     1     6\n -2.4154698368651717E+00 a       157     0     7     1     7\n -6.4185058527317249E+00 a       158     0     7     1     8\n -6.3530147117874556E+00 a       159     0     7     1     9\n -1.0300638522442572E+01 a       160     0     7     1    10\n -2.5171111984091286E+00 a       161     0     7     1    11\n  1.4346366450085095E+00 a       162     0     7     1    12\n -1.3304527621670990E+01 a       163     0     7     1    13\n  5.3440054715077174E+00 a       164     0     7     1    14\n -4.7752111845859284E+00 a       165     0     7     1    15\n  5.6996056931561228E+00 a       166     0     7     1    16\n -7.9407992418087998E+00 a       167     0     7     1    17\n -6.8536026180721965E+00 a       168     0     7     1    18\n -1.0711888650381090E+01 a       169     0     7     1    19\n  2.4505342833618038E-01 a       170     0     7     1    20\n -4.3922395588198606E+00 a       171     0     7     1    21\n  5.5178492498544873E-01 a       172     0     7     1    22\n -4.8792817141000047E+00 a       173     0     7     1    23\n -5.1325176047438585E+00 a       174     0     7     1    24\n -5.4022673676284061E+00 a       175     0     7     1    25\n -1.7450986580904615E+00 a       176     0     8     1     1\n -2.0857681787602300E+00 a       177     0     8     1     2\n  3.3767537084375467E+00 a       178     0     8     1     3\n -1.2182668398329699E+00 a       179     0     8     1     4\n -4.4813014658077348E+00 a       180     0     8     1     5\n  3.4420996861792021E+00 a       181     0     8     1     6\n  3.2454815776290897E+00 a       182     0     8     1     7\n -4.5227047921354613E+00 a       183     0     8     1     8\n  6.7799419181386513E+00 a       184     0     8     1     9\n -1.1903584323039825E+01 a       185     0     8     1    10\n -2.7223908495259308E+00 a       186     0     8     1    11\n -4.7321011194404500E-01 a       187     0     8     1    12\n -6.1092257950544511E+00 a       188     0     8     1    13\n  5.4895492716221366E+00 a       189     0     8     1    14\n -1.6338164188681257E+00 a       190     0     8     1    15\n  1.1277139003032529E+01 a       191     0     8     1    16\n -3.3604518374573411E-01 a       192     0     8     1    17\n  5.0324773412481543E+00 a       193     0     8     1    18\n  5.5190045818889044E-01 a       194     0     8     1    19\n -8.0739653112982630E+00 a       195     0     8     1    20\n  2.3182343608141337E-01 a       196     0     8     1    21\n -7.2752730220072390E+00 a       197     0     8     1    22\n -3.6054885240998058E-01 a       198     0     8     1    23\n -1.3142640398422461E+01 a       199     0     8     1    24\n  7.1465780543501847E+00 a       200     0     8     1    25\n  7.5183831819176081E+00 a       201     0     9     1     1\n  2.9478878274850411E+00 a       202     0     9     1     2\n -8.1539641377180487E+00 a       203     0     9     1     3\n  1.6331939279698631E+00 a       204     0     9     1     4\n  3.3670818176037733E+00 a       205     0     9     1     5\n -1.8919172818695511E+00 a       206     0     9     1     6\n  3.7866941325142678E+00 a       207     0     9     1     7\n -2.1688455257165606E+00 a       208     0     9     1     8\n -2.8769808982541201E+00 a       209     0     9     1     9\n -8.1245314227365206E+00 a       210     0     9     1    10\n  1.4805493121030247E+00 a       211     0     9     1    11\n  3.2509793154226454E+00 a       212     0     9     1    12\n  2.1041498098520948E+00 a       213     0     9     1    13\n  7.9799571475096975E+00 a       214     0     9     1    14\n -2.1949901731590886E+00 a       215     0     9     1    15\n -8.0908749194256935E-01 a       216     0     9     1    16\n -7.3129676794482235E+00 a       217     0     9     1    17\n -1.0319589334641524E+01 a       218     0     9     1    18\n -2.0389800124914292E+00 a       219     0     9     1    19\n  6.9525158971063590E+00 a       220     0     9     1    20\n  4.2115246519100769E+00 a       221     0     9     1    21\n  2.2370277559006819E+00 a       222     0     9     1    22\n -4.8393467643934969E+00 a       223     0     9     1    23\n -5.1214408194652217E+00 a       224     0     9     1    24\n  5.0160134560600929E+00 a       225     0     9     1    25\n  1.0638615105610261E+00 a       226     0    10     1     1\n  9.7818550481210265E-01 a       227     0    10     1     2\n -1.1563523862737251E+00 a       228     0    10     1     3\n  9.8453512388483189E-01 a       229     0    10     1     4\n -5.1528565685883754E+00 a       230     0    10     1     5\n -4.7337879400034666E+00 a       231     0    10     1     6\n  8.9788972890266692E+00 a       232     0    10     1     7\n  4.2652882359018096E-01 a       233     0    10     1     8\n -1.0302258172803562E+01 a       234     0    10     1     9\n  5.4999420894932536E+00 a       235     0    10     1    10\n  5.3923145094191502E+00 a       236     0    10     1    11\n -3.7232850508430002E+00 a       237     0    10     1    12\n -6.8970489437888620E+00 a       238     0    10     1    13\n -1.5840794804287139E+00 a       239     0    10     1    14\n  1.7169188089004842E-01 a       240     0    10     1    15\n  1.9648502314459890E+01 a       241     0    10     1    16\n -8.0744717790128995E+00 a       242     0    10     1    17\n -1.3433935923744658E-01 a       243     0    10     1    18\n  8.9210187496738076E+00 a       244     0    10     1    19\n -9.0342893458165907E+00 a       245     0    10     1    20\n  7.3462053868897463E+00 a       246     0    10     1    21\n -1.2703699286654917E+00 a       247     0    10     1    22\n -5.6864959717654184E-01 a       248     0    10     1    23\n -1.3644263450370872E+01 a       249     0    10     1    24\n  6.3185108276854578E+00 a       250     0    10     1    25\n  1.7047220426091605E+00 a       251     0    11     1     1\n -7.5015113906764616E-02 a       252     0    11     1     2\n -4.1380405892273213E+00 a       253     0    11     1     3\n  5.4695988995005540E-01 a       254     0    11     1     4\n -1.1278081605956256E+01 a       255     0    11     1     5\n  3.6090085862829835E-01 a       256     0    11     1     6\n  6.1879661688405774E+00 a       257     0    11     1     7\n  1.0482472293870837E+01 a       258     0    11     1     8\n -1.4635289295140994E-01 a       259     0    11     1     9\n -1.6705933901074963E+00 a       260     0    11     1    10\n  1.6804893710750135E+00 a       261     0    11     1    11\n -4.2124688096850349E+00 a       262     0    11     1    12\n  1.5883344670486316E+01 a       263     0    11     1    13\n  3.4013163945483607E+00 a       264     0    11     1    14\n  1.5496837480731045E+00 a       265     0    11     1    15\n -1.4898982067373119E+00 a       266     0    11     1    16\n  1.1818736714544111E+00 a       267     0    11     1    17\n -7.2587779385475129E+00 a       268     0    11     1    18\n  3.7418398478882966E+00 a       269     0    11     1    19\n  9.4909666560050141E+00 a       270     0    11     1    20\n  4.8822251465574400E+00 a       271     0    11     1    21\n  3.8343007691231787E+00 a       272     0    11     1    22\n  3.3507977123295727E+00 a       273     0    11     1    23\n -4.7784555511545879E+00 a       274     0    11     1    24\n  1.2313460849612209E+01 a       275     0    11     1    25\n  8.5469297882344544E-02 a       276     0    12     1     1\n -1.7985607003836032E-01 a       277     0    12     1     2\n  2.1156873293655036E+00 a       278     0    12     1     3\n -1.6810220192239533E+00 a       279     0    12     1     4\n -8.3646273469893000E+00 a       280     0    12     1     5\n -3.5599078542902398E+00 a       281     0    12     1     6\n  7.9528065619694921E-01 a       282     0    12     1     7\n -1.5005964907145810E+00 a       283     0    12     1     8\n -8.3713112710538198E+00 a       284     0    12     1     9\n  7.9893166136497511E+00 a       285     0    12     1    10\n  6.8328876094405384E+00 a       286     0    12     1    11\n  3.8718827991647267E+00 a       287     0    12     1    12\n  1.6016434828923782E+00 a       288     0    12     1    13\n  4.3197777296180071E+00 a       289     0    12     1    14\n  8.4689518622586828E+00 a       290     0    12     1    15\n -6.1406288315193187E+00 a       291     0    12     1    16\n -1.6164718716221598E+00 a       292     0    12     1    17\n -4.6079492966177513E+00 a       293     0    12     1    18\n  7.0589020945161538E+00 a       294     0    12     1    19\n  3.9902699890259017E+00 a       295     0    12     1    20\n -3.4302429028301744E+00 a       296     0    12     1    21\n  9.3558325285731865E+00 a       297     0    12     1    22\n  4.3035541883723460E-01 a       298     0    12     1    23\n -4.7392101275216820E+00 a       299     0    12     1    24\n  1.1777555495090788E-01 a       300     0    12     1    25\n -5.1599444770423126E+00 a       301     0    13     1     1\n  2.1491302342388305E+01 a       302     0    13     1     2\n  1.7258796601499700E+01 a       303     0    13     1     3\n  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1.9870719480852208E+00 a      1936     0    78     1    11\n -2.0321154226225011E+00 a      1937     0    78     1    12\n -4.9762884257090461E+00 a      1938     0    78     1    13\n -1.8046870228044856E+01 a      1939     0    78     1    14\n  2.0004359383504329E+00 a      1940     0    78     1    15\n -4.5714832083535590E+00 a      1941     0    78     1    16\n -3.1922595581752176E+00 a      1942     0    78     1    17\n -1.9030545311142664E+01 a      1943     0    78     1    18\n  3.4535593508521747E+00 a      1944     0    78     1    19\n  2.3092203210580666E+00 a      1945     0    78     1    20\n  2.3050834561966145E+00 a      1946     0    78     1    21\n  8.9391983102290489E+00 a      1947     0    78     1    22\n -6.2491226355717600E-01 a      1948     0    78     1    23\n -2.5112641641946833E+00 a      1949     0    78     1    24\n  6.5462790893286913E+00 a      1950     0    78     1    25\n  2.7772361693274923E+00 a      1951     0    79     1     1\n  1.1008932859225469E+00 a      1952     0    79     1     2\n  5.1394713480774197E+00 a      1953     0    79     1     3\n -6.8899012680035332E+00 a      1954     0    79     1     4\n  6.6378138553888348E+00 a      1955     0    79     1     5\n  3.8829030744033943E+00 a      1956     0    79     1     6\n -7.5090676818920432E+00 a      1957     0    79     1     7\n  2.1953105473271934E+00 a      1958     0    79     1     8\n -4.3231641521829340E+00 a      1959     0    79     1     9\n -1.9648053295801626E-01 a      1960     0    79     1    10\n  8.5225280099334064E+00 a      1961     0    79     1    11\n -2.2519772429179068E+00 a      1962     0    79     1    12\n  2.0877071686080018E+00 a      1963     0    79     1    13\n -5.3718900886827035E+00 a      1964     0    79     1    14\n  3.9682780334546339E+00 a      1965     0    79     1    15\n -5.4267302690686936E+00 a      1966     0    79     1    16\n  5.6249537611030593E+00 a      1967     0    79     1    17\n -2.6248724896874853E-01 a      1968     0    79     1    18\n  5.9282764098940541E+00 a      1969     0    79     1    19\n -2.1876693122171442E+00 a      1970     0    79     1    20\n -7.4045189778393414E+00 a      1971     0    79     1    21\n -1.1570611702898470E+00 a      1972     0    79     1    22\n  1.0519204361415867E-01 a      1973     0    79     1    23\n -5.1112178610584325E+00 a      1974     0    79     1    24\n -6.8045441043555730E+00 a      1975     0    79     1    25\n -3.9822500290250678E+00 a      1976     0    80     1     1\n  7.5393055145217964E+00 a      1977     0    80     1     2\n  1.0631946081157944E+01 a      1978     0    80     1     3\n -2.3657264322381288E+00 a      1979     0    80     1     4\n -5.2400086863654911E+00 a      1980     0    80     1     5\n -2.4924267722257039E+00 a      1981     0    80     1     6\n -1.4482203648300669E+00 a      1982     0    80     1     7\n -8.2507990895167840E+00 a      1983     0    80     1     8\n -2.9837948724493817E+00 a      1984     0    80     1     9\n  4.8047923027977752E+00 a      1985     0    80     1    10\n -3.4977814850738977E+00 a      1986     0    80     1    11\n -5.5266538738766713E-01 a      1987     0    80     1    12\n  2.2720375785361502E+00 a      1988     0    80     1    13\n  8.1155659544794378E+00 a      1989     0    80     1    14\n  1.5720298093394950E+01 a      1990     0    80     1    15\n  7.8920008837825684E+00 a      1991     0    80     1    16\n  8.0507098433621849E-01 a      1992     0    80     1    17\n  5.9185244874451151E+00 a      1993     0    80     1    18\n  2.5642424607541399E+00 a      1994     0    80     1    19\n -5.3442171958241929E+00 a      1995     0    80     1    20\n  5.0753912654216238E-01 a      1996     0    80     1    21\n -2.8532756294433184E+00 a      1997     0    80     1    22\n -4.5575543912850192E+00 a      1998     0    80     1    23\n -1.0326301296439699E+01 a      1999     0    80     1    24\n  1.7566566950260485E+00 a      2000     0    80     1    25\n  1.7968148866675133E+00 a      2001     0    81     1     1\n -2.8353407603544944E+00 a      2002     0    81     1     2\n -6.2809064144104001E+00 a      2003     0    81     1     3\n  1.7440412456468848E-01 a      2004     0    81     1     4\n  1.4735776942301784E-01 a      2005     0    81     1     5\n -1.4395670405482102E+00 a      2006     0    81     1     6\n  4.0729304076735318E+00 a      2007     0    81     1     7\n  5.0534537872499321E+00 a      2008     0    81     1     8\n  2.5277147126964650E-01 a      2009     0    81     1     9\n  3.6106926395649226E+00 a      2010     0    81     1    10\n  3.2273355219817446E+00 a      2011     0    81     1    11\n -1.0107090935910866E+01 a      2012     0    81     1    12\n  8.3523398519442882E+00 a      2013     0    81     1    13\n  8.3650159540184432E-01 a      2014     0    81     1    14\n  4.5453198949959788E+00 a      2015     0    81     1    15\n -8.2733085531604456E+00 a      2016     0    81     1    16\n  1.8397194357244531E-01 a      2017     0    81     1    17\n  6.3496792061827967E-01 a      2018     0    81     1    18\n  2.8727760317705937E+00 a      2019     0    81     1    19\n -4.4165925602418206E+00 a      2020     0    81     1    20\n  4.9032748494183593E+00 a      2021     0    81     1    21\n -9.6593330433473501E-01 a      2022     0    81     1    22\n  2.5823903430280120E+00 a      2023     0    81     1    23\n -4.3176804760716312E+00 a      2024     0    81     1    24\n  6.8415578724064083E+00 a      2025     0    81     1    25\n -7.0952354627464391E+00 a      2026     0    82     1     1\n -3.3805929128229444E+00 a      2027     0    82     1     2\n -5.5995925180536679E+00 a      2028     0    82     1     3\n  2.5410875611382560E+00 a      2029     0    82     1     4\n  3.5475693099544254E+00 a      2030     0    82     1     5\n -2.8396973568982302E+00 a      2031     0    82     1     6\n -2.7908053926657641E+00 a      2032     0    82     1     7\n  1.6772138719507588E+01 a      2033     0    82     1     8\n  6.4349275393852281E+00 a      2034     0    82     1     9\n  6.9847260931487458E+00 a      2035     0    82     1    10\n -3.8204886525794648E+00 a      2036     0    82     1    11\n -1.8465803707811859E+00 a      2037     0    82     1    12\n  9.9292201773087854E+00 a      2038     0    82     1    13\n -1.0935503791844912E+01 a      2039     0    82     1    14\n -3.8140726339991327E-01 a      2040     0    82     1    15\n  4.6540033524793589E+00 a      2041     0    82     1    16\n  1.4685057997665270E+00 a      2042     0    82     1    17\n  1.3830554099950021E+01 a      2043     0    82     1    18\n  6.2396568204822689E-01 a      2044     0    82     1    19\n -2.2755365047213876E+00 a      2045     0    82     1    20\n  1.2432619763584272E+00 a      2046     0    82     1    21\n  4.8275980504502005E+00 a      2047     0    82     1    22\n  2.4316903028913206E+00 a      2048     0    82     1    23\n  9.6668016270186623E+00 a      2049     0    82     1    24\n  1.8012613037724272E+00 a      2050     0    82     1    25\n  1.4172723208009139E+00 a      2051     0    83     1     1\n  1.2654490622972401E+00 a      2052     0    83     1     2\n -2.2970849224577479E+00 a      2053     0    83     1     3\n  4.0804115213357289E-01 a      2054     0    83     1     4\n  2.6004152586545830E+00 a      2055     0    83     1     5\n -7.1564843502605697E+00 a      2056     0    83     1     6\n -1.2295423536268091E+00 a      2057     0    83     1     7\n  7.5868943262656456E+00 a      2058     0    83     1     8\n  2.3782591543105407E+00 a      2059     0    83     1     9\n -1.2781424969935067E+01 a      2060     0    83     1    10\n -7.7751177599047621E+00 a      2061     0    83     1    11\n -5.3311133888918780E+00 a      2062     0    83     1    12\n -5.3122344469638900E+00 a      2063     0    83     1    13\n -5.8879482327874069E+00 a      2064     0    83     1    14\n -8.7608390301070105E-01 a      2065     0    83     1    15\n  2.4835128045713861E+00 a      2066     0    83     1    16\n  3.9512633914990278E+00 a      2067     0    83     1    17\n -4.7060617240652283E+00 a      2068     0    83     1    18\n -3.4766759657878882E-01 a      2069     0    83     1    19\n -9.0167460425013175E+00 a      2070     0    83     1    20\n  9.0775226142549670E+00 a      2071     0    83     1    21\n  9.1868627460771215E+00 a      2072     0    83     1    22\n  7.9634958142067808E-02 a      2073     0    83     1    23\n -5.6237588666689806E+00 a      2074     0    83     1    24\n -4.8745055833310511E+00 a      2075     0    83     1    25\n -1.0038948717066685E+01 a      2076     0    84     1     1\n -5.4069391881162887E-01 a      2077     0    84     1     2\n  2.0062972265574408E+00 a      2078     0    84     1     3\n -5.5007858591572778E-01 a      2079     0    84     1     4\n  6.2616034776869114E+00 a      2080     0    84     1     5\n  1.2278199722854149E+01 a      2081     0    84     1     6\n  7.5282270186139657E+00 a      2082     0    84     1     7\n -7.6278920181868139E+00 a      2083     0    84     1     8\n  2.6699324500683770E+00 a      2084     0    84     1     9\n -9.2015320919202388E+00 a      2085     0    84     1    10\n -4.4702379692661637E-01 a      2086     0    84     1    11\n  2.9150677780203389E+00 a      2087     0    84     1    12\n  2.2612920162108816E+00 a      2088     0    84     1    13\n  2.3917395308121221E+00 a      2089     0    84     1    14\n -5.1397696843441008E+00 a      2090     0    84     1    15\n -2.7891537471716541E+00 a      2091     0    84     1    16\n -1.9248230321271137E-01 a      2092     0    84     1    17\n  4.3777467145251485E+00 a      2093     0    84     1    18\n -1.1523775865932386E+01 a      2094     0    84     1    19\n  6.4275664273636695E+00 a      2095     0    84     1    20\n -1.1823974215133900E+01 a      2096     0    84     1    21\n -5.6595365159974982E+00 a      2097     0    84     1    22\n  5.1366266571893859E-01 a      2098     0    84     1    23\n -8.4421620077322679E+00 a      2099     0    84     1    24\n  3.9324980478328428E+00 a      2100     0    84     1    25\n  1.2424175267524284E+01 a      2101     0    85     1     1\n -8.9428378700895772E-01 a      2102     0    85     1     2\n -2.9641108341041664E+00 a      2103     0    85     1     3\n  5.8753114929334691E+00 a      2104     0    85     1     4\n -1.5433695699960004E-01 a      2105     0    85     1     5\n -8.4070230303250764E+00 a      2106     0    85     1     6\n  2.0711492597346819E+00 a      2107     0    85     1     7\n  4.5411716610154835E+00 a      2108     0    85     1     8\n -1.3959555631903160E+00 a      2109     0    85     1     9\n  3.5657376539548862E+00 a      2110     0    85     1    10\n  1.8558886237035148E+00 a      2111     0    85     1    11\n -1.4024833371639950E-01 a      2112     0    85     1    12\n -3.5428499997835501E+00 a      2113     0    85     1    13\n  6.0100997452714013E+00 a      2114     0    85     1    14\n -7.2660416239924706E+00 a      2115     0    85     1    15\n -3.5250723775375050E+00 a      2116     0    85     1    16\n  2.0997326349355254E+00 a      2117     0    85     1    17\n  6.3441144822116846E-01 a      2118     0    85     1    18\n  1.2954874069801255E+01 a      2119     0    85     1    19\n  3.3683349994453144E+00 a      2120     0    85     1    20\n  2.3511669514941334E+00 a      2121     0    85     1    21\n -1.6271896567050650E+00 a      2122     0    85     1    22\n -3.4921943473663442E-01 a      2123     0    85     1    23\n -3.7750437597088475E+00 a      2124     0    85     1    24\n  5.7492134315805643E+00 a      2125     0    85     1    25\n -5.3325376757363561E+00 a      2126     0    86     1     1\n -1.6336885681542390E+00 a      2127     0    86     1     2\n  1.2508425493150908E+00 a      2128     0    86     1     3\n -1.0193874788753815E+01 a      2129     0    86     1     4\n -8.2435696550600941E+00 a      2130     0    86     1     5\n -2.8488310804130643E+00 a      2131     0    86     1     6\n  4.8904882864392452E+00 a      2132     0    86     1     7\n  1.3503741849284790E+01 a      2133     0    86     1     8\n -1.4729846103640425E+00 a      2134     0    86     1     9\n  8.3687585264393949E+00 a      2135     0    86     1    10\n  1.0055163198213558E+01 a      2136     0    86     1    11\n  3.4077762794179662E+00 a      2137     0    86     1    12\n  3.9215206834612260E-01 a      2138     0    86     1    13\n  9.2197295642307248E-02 a      2139     0    86     1    14\n -5.5278256993762644E+00 a      2140     0    86     1    15\n  1.0736430974590759E+01 a      2141     0    86     1    16\n  1.6231889275526772E+00 a      2142     0    86     1    17\n  7.7011906034460997E+00 a      2143     0    86     1    18\n  2.7651889030914538E+00 a      2144     0    86     1    19\n -4.3522186925487167E+00 a      2145     0    86     1    20\n  2.6464861679117755E+00 a      2146     0    86     1    21\n -2.2466680328716482E-01 a      2147     0    86     1    22\n -3.8303615866467497E+00 a      2148     0    86     1    23\n -4.0115705224488059E+00 a      2149     0    86     1    24\n -3.3681290775818757E+00 a      2150     0    86     1    25\n  4.6634776346164966E+00 a      2151     0    87     1     1\n  1.6270769641856289E+00 a      2152     0    87     1     2\n -3.5104973497955333E-01 a      2153     0    87     1     3\n  6.7838113987278046E+00 a      2154     0    87     1     4\n  7.2638356016929215E+00 a      2155     0    87     1     5\n  4.7875706768887989E+00 a      2156     0    87     1     6\n -1.2887627940923290E+01 a      2157     0    87     1     7\n -1.7288995160777663E+01 a      2158     0    87     1     8\n -6.4553062296222832E+00 a      2159     0    87     1     9\n  6.1662177333147143E+00 a      2160     0    87     1    10\n  1.6284389485854529E+00 a      2161     0    87     1    11\n -4.0533349057327817E+00 a      2162     0    87     1    12\n  9.1949292089125159E+00 a      2163     0    87     1    13\n  1.0683792349446193E+00 a      2164     0    87     1    14\n  6.6733553028918040E+00 a      2165     0    87     1    15\n -1.8708794395875787E+00 a      2166     0    87     1    16\n  1.0200036088169178E+00 a      2167     0    87     1    17\n -3.9538308200098435E+00 a      2168     0    87     1    18\n -9.1427157730264561E+00 a      2169     0    87     1    19\n -6.1603286571475149E+00 a      2170     0    87     1    20\n -2.4329836934081142E+00 a      2171     0    87     1    21\n -1.1258212524176587E+01 a      2172     0    87     1    22\n  3.4259050868449745E+00 a      2173     0    87     1    23\n -6.4642154673806473E+00 a      2174     0    87     1    24\n -4.0010616737263810E-01 a      2175     0    87     1    25\n 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-3.2244435638916027E+00 a      5061     1    18     2    11\n  5.6754932834848108E-02 a      5062     1    18     2    12\n  9.2056603377778760E-03 a      5063     1    18     2    13\n -9.7496462054534716E-01 a      5064     1    18     2    14\n -5.2114791590354326E-01 a      5065     1    18     2    15\n -2.9808827977096968E+00 a      5066     1    18     2    16\n  8.6812203185660441E-01 a      5067     1    18     2    17\n -1.2510142565051938E-01 a      5068     1    18     2    18\n -2.7700258417164503E+00 a      5069     1    18     2    19\n  9.9431020569848172E-01 a      5070     1    18     2    20\n  1.4861986230420117E+00 a      5071     1    18     2    21\n  4.2803488451307219E+00 a      5072     1    18     2    22\n -5.1638986184331803E-01 a      5073     1    18     2    23\n  2.5717095726474910E+00 a      5074     1    18     2    24\n -1.0156524281129886E+00 a      5075     1    18     2    25\n  8.0817522913994089E-01 a      5076     1    19     2     1\n -1.1207738598192656E+00 a      5077     1    19     2     2\n -1.6696190303645468E+00 a      5078     1    19     2     3\n  1.1029039268162519E+00 a      5079     1    19     2     4\n -6.0389434565676323E+00 a      5080     1    19     2     5\n -7.3060573051571753E-01 a      5081     1    19     2     6\n -9.6904337766588500E-01 a      5082     1    19     2     7\n  8.7475200472869930E-01 a      5083     1    19     2     8\n  3.5703394120275622E-01 a      5084     1    19     2     9\n  7.8754833949028724E-01 a      5085     1    19     2    10\n  2.1337159086626634E+00 a      5086     1    19     2    11\n -2.0848630449388300E-01 a      5087     1    19     2    12\n  1.0938079379768909E-01 a      5088     1    19     2    13\n -1.9159420316016191E+00 a      5089     1    19     2    14\n  8.1968419185452401E-01 a      5090     1    19     2    15\n -8.0362614906119711E-01 a      5091     1    19     2    16\n  2.4636053131261999E+00 a      5092     1    19     2    17\n -8.5723203464409936E-01 a      5093     1    19     2    18\n -2.5715625544469236E+00 a      5094     1    19     2    19\n  7.8178385455533872E-01 a      5095     1    19     2    20\n -1.3352994195300782E+00 a      5096     1    19     2    21\n  2.6329796376706769E+00 a      5097     1    19     2    22\n  2.1760672950210571E+00 a      5098     1    19     2    23\n -2.1747200547607042E+00 a      5099     1    19     2    24\n -3.6640923211279408E-01 a      5100     1    19     2    25\n  3.1511869578037737E+00 a      5101     1    20     2     1\n -9.7615218476382222E-03 a      5102     1    20     2     2\n -3.7978034146089881E+00 a      5103     1    20     2     3\n  3.5385513719710211E+00 a      5104     1    20     2     4\n  6.3825414320145679E+00 a      5105     1    20     2     5\n  4.9513642117631240E-01 a      5106     1    20     2     6\n -4.7220016898267714E-01 a      5107     1    20     2     7\n  3.5523175424612914E+00 a      5108     1    20     2     8\n -4.0155910464813429E+00 a      5109     1    20     2     9\n -6.7816960805191795E-01 a      5110     1    20     2    10\n  2.8474201226715783E+00 a      5111     1    20     2    11\n  9.0929096525302078E-01 a      5112     1    20     2    12\n -2.4776121962228217E-01 a      5113     1    20     2    13\n -1.2735505460128325E+00 a      5114     1    20     2    14\n -3.0606132818625559E-01 a      5115     1    20     2    15\n  1.1725720798255974E+00 a      5116     1    20     2    16\n -5.3035661945148904E+00 a      5117     1    20     2    17\n -5.2390442942604043E+00 a      5118     1    20     2    18\n  9.1455379178731744E-01 a      5119     1    20     2    19\n -5.5427819719931923E+00 a      5120     1    20     2    20\n -1.3747643391659073E-01 a      5121     1    20     2    21\n  1.5115423807107053E+00 a      5122     1    20     2    22\n  8.9611936097922473E-01 a      5123     1    20     2    23\n -8.0509920495798548E-01 a      5124     1    20     2    24\n -4.0330719326684008E+00 a      5125     1    20     2    25\n  1.6004363527422369E+00 a      5126     1    21     2     1\n -3.4057934379229199E-01 a      5127     1    21     2     2\n -1.6471074820617013E+00 a      5128     1    21     2     3\n -1.2695306296023590E+00 a      5129     1    21     2     4\n  1.1671989840726993E+00 a      5130     1    21     2     5\n  5.0333073521920457E-01 a      5131     1    21     2     6\n  3.4735510561517851E+00 a      5132     1    21     2     7\n -1.9448615006400041E+00 a      5133     1    21     2     8\n  9.4671336113124949E-01 a      5134     1    21     2     9\n  5.8200370835875681E-01 a      5135     1    21     2    10\n -5.9262977866150761E+00 a      5136     1    21     2    11\n  6.7980696116865691E-02 a      5137     1    21     2    12\n -1.2482888616557203E-01 a      5138     1    21     2    13\n -7.4588543458861023E-01 a      5139     1    21     2    14\n  8.9238897174008858E-01 a      5140     1    21     2    15\n  1.8118920305522195E+00 a      5141     1    21     2    16\n  2.3827363812434887E+00 a      5142     1    21     2    17\n  8.9021534670549496E-01 a      5143     1    21     2    18\n  3.0298161953804397E+00 a      5144     1    21     2    19\n  2.7449696603173979E+00 a      5145     1    21     2    20\n  1.2719730937775531E+00 a      5146     1    21     2    21\n  2.7121325289774618E+00 a      5147     1    21     2    22\n  9.7998619269786891E-01 a      5148     1    21     2    23\n  3.5152666748715808E+00 a      5149     1    21     2    24\n  7.2639256397906304E-01 a      5150     1    21     2    25\n  3.8786317580510904E-01 a      5151     1    22     2     1\n  4.1431766406784853E-01 a      5152     1    22     2     2\n -1.7773489021342901E+00 a      5153     1    22     2     3\n  2.9686346262650518E-02 a      5154     1    22     2     4\n  6.4179804439566537E+00 a      5155     1    22     2     5\n  1.5659211447177285E-01 a      5156     1    22     2     6\n -3.7645216869478293E-01 a      5157     1    22     2     7\n  2.5925800945632216E+00 a      5158     1    22     2     8\n  2.5248886010279827E+00 a      5159     1    22     2     9\n  1.8114625993328564E+00 a      5160     1    22     2    10\n -9.0149397674712279E+00 a      5161     1    22     2    11\n -5.5385587174359971E-02 a      5162     1    22     2    12\n -1.6107074578350947E-01 a      5163     1    22     2    13\n -7.9308104512869082E-01 a      5164     1    22     2    14\n  2.2384868971120248E-01 a      5165     1    22     2    15\n -4.1184468379177180E-01 a      5166     1    22     2    16\n  1.0849002402293559E-01 a      5167     1    22     2    17\n -4.7987500778945191E-01 a      5168     1    22     2    18\n -2.2679690439890510E+00 a      5169     1    22     2    19\n  2.6345690965876090E+00 a      5170     1    22     2    20\n -2.7751942532008222E-01 a      5171     1    22     2    21\n  1.0268619970039047E+01 a      5172     1    22     2    22\n  1.4893635278433395E-01 a      5173     1    22     2    23\n  1.4227143851470730E-01 a      5174     1    22     2    24\n -1.5042838009093256E+00 a      5175     1    22     2    25\n -1.3355939919682664E+00 a      5176     1    23     2     1\n -2.2144508716901412E-01 a      5177     1    23     2     2\n  2.5997713625687595E+00 a      5178     1    23     2     3\n -1.7318950240483666E+00 a      5179     1    23     2     4\n -9.5091628980213816E-01 a      5180     1    23     2     5\n  1.1133773822338948E+00 a      5181     1    23     2     6\n -7.9577813502221567E-02 a      5182     1    23     2     7\n -1.8388390251277080E+00 a      5183     1    23     2     8\n  5.5929352010197864E-01 a      5184     1    23     2     9\n -1.1946805434431096E-01 a      5185     1    23     2    10\n -8.7264618366332924E-01 a      5186     1    23     2    11\n -1.1541160540958666E+00 a      5187     1    23     2    12\n  1.5656714273925130E+00 a      5188     1    23     2    13\n -7.3791117385890781E-02 a      5189     1    23     2    14\n  2.3955983106343531E-01 a      5190     1    23     2    15\n -1.8856249079760081E+00 a      5191     1    23     2    16\n -3.1482729046499052E+00 a      5192     1    23     2    17\n -1.8728562410856650E-01 a      5193     1    23     2    18\n -2.3683894268376497E+00 a      5194     1    23     2    19\n -1.0236970649186015E+00 a      5195     1    23     2    20\n -6.1950476011404243E-01 a      5196     1    23     2    21\n  1.9328772515255446E+00 a      5197     1    23     2    22\n -4.0552484852582236E+00 a      5198     1    23     2    23\n -3.9225587485999975E+00 a      5199     1    23     2    24\n -1.9947394385213868E-01 a      5200     1    23     2    25\n -4.3704749791359072E+00 a      5201     1    24     2     1\n  1.8787915296639122E-02 a      5202     1    24     2     2\n  5.4855213699962135E+00 a      5203     1    24     2     3\n -2.0001774899086429E+00 a      5204     1    24     2     4\n  3.0776769741503069E+00 a      5205     1    24     2     5\n  1.0866694787429930E-01 a      5206     1    24     2     6\n  1.5162064624690874E+00 a      5207     1    24     2     7\n  5.7137598874813484E+00 a      5208     1    24     2     8\n -2.0348536998309732E+00 a      5209     1    24     2     9\n -1.7394173179378547E+00 a      5210     1    24     2    10\n -7.4283419565582296E+00 a      5211     1    24     2    11\n -5.2762955285750555E-02 a      5212     1    24     2    12\n -1.7274346044059652E-01 a      5213     1    24     2    13\n -1.0419050294186168E-01 a      5214     1    24     2    14\n  1.2289760527975269E+00 a      5215     1    24     2    15\n  3.1274543350202659E+00 a      5216     1    24     2    16\n -6.0104880150504081E-01 a      5217     1    24     2    17\n -2.7046905251099869E+00 a      5218     1    24     2    18\n  1.0165961309731903E+00 a      5219     1    24     2    19\n -2.8243253828152994E+00 a      5220     1    24     2    20\n -2.7749144343156789E+00 a      5221     1    24     2    21\n -1.9245703775340668E+00 a      5222     1    24     2    22\n  5.9231071389482037E-01 a      5223     1    24     2    23\n -5.4690233253062264E+00 a      5224     1    24     2    24\n  1.3696049678759725E+00 a      5225     1    24     2    25\n  2.4357226368059322E+00 a      5226     1    25     2     1\n  1.6587565578760983E+00 a      5227     1    25     2     2\n  1.7197066660190599E+00 a      5228     1    25     2     3\n -1.7813605909515366E+00 a      5229     1    25     2     4\n -2.6171420111577968E+00 a      5230     1    25     2     5\n -2.9093749981786254E-01 a      5231     1    25     2     6\n -6.3694812287910108E-01 a      5232     1    25     2     7\n -4.1838484230148270E+00 a      5233     1    25     2     8\n -1.3114644901140601E-01 a      5234     1    25     2     9\n  6.3965614327051434E-01 a      5235     1    25     2    10\n  3.3558970148580813E-01 a      5236     1    25     2    11\n  3.0894458355433296E-01 a      5237     1    25     2    12\n  2.6857432259124497E-01 a      5238     1    25     2    13\n -4.2763308447273746E-01 a      5239     1    25     2    14\n  2.5256388068261366E-02 a      5240     1    25     2    15\n -1.7373289104656737E+00 a      5241     1    25     2    16\n -1.6010902904762014E+00 a      5242     1    25     2    17\n -1.4843504716535252E+00 a      5243     1    25     2    18\n -9.0399698420668317E-01 a      5244     1    25     2    19\n  1.0901933854756902E+00 a      5245     1    25     2    20\n -9.4420803683339616E-01 a      5246     1    25     2    21\n  3.3181848441236694E-01 a      5247     1    25     2    22\n  4.8310165776460140E-01 a      5248     1    25     2    23\n  2.0959433474371774E+00 a      5249     1    25     2    24\n -7.6535075511009698E-01 a      5250     1    25     2    25\n  2.3972689148636626E+00 b      5251     2     1\n  1.7154180017402040E-01 b      5252     2     2\n -5.5229867823392125E+00 b      5253     2     3\n  5.2616342734534960E-01 b      5254     2     4\n -1.0459668892134305E+01 b      5255     2     5\n -4.9240169341224718E+00 b      5256     2     6\n -3.0876746240972053E+00 b      5257     2     7\n -1.3619194046410812E+00 b      5258     2     8\n -1.1722074879829588E+01 b      5259     2     9\n  2.4868702377366771E+00 b      5260     2    10\n  1.5281225445127375E+00 b      5261     2    11\n  5.1943459822183702E-01 b      5262     2    12\n -6.0362400492902824E+00 b      5263     2    13\n -8.1513270116304071E-01 b      5264     2    14\n -4.9091965829559525E+00 b      5265     2    15\n  5.4383035515541478E-01 b      5266     2    16\n  1.1668928810435484E+00 b      5267     2    17\n  4.0101172502430344E+00 b      5268     2    18\n -8.2348953525181017E+00 b      5269     2    19\n -2.1463193168851635E+00 b      5270     2    20\n  5.8825775611798061E+00 b      5271     2    21\n  4.4741597846306069E+00 b      5272     2    22\n  9.4398394490750288E+00 b      5273     2    23\n  4.8558416975347685E+00 b      5274     2    24\n  1.3459518328767128E+01 b      5275     2    25\n -1.9641317243382372E-01 a      5276     2     1     3     1\n -1.4363721187863440E-01 a      5277     2     2     3     1\n -2.2575853398233182E-02 a      5278     2     3     3     1\n -1.5893554344107930E-01 a      5279     2     4     3     1\n  3.9290061853094492E-02 a      5280     2     5     3     1\n  3.0871348097189051E+00 a      5281     2     6     3     1\n  1.7050864514192923E-01 a      5282     2     7     3     1\n -3.0100747498387394E-02 a      5283     2     8     3     1\n  2.2665351135907555E-01 a      5284     2     9     3     1\n -2.0618778428614079E-01 a      5285     2    10     3     1\n  2.2450691698885042E-02 a      5286     2    11     3     1\n  1.3395018583777025E+00 a      5287     2    12     3     1\n  2.1759064697369035E+00 a      5288     2    13     3     1\n -5.3285490347452236E-01 a      5289     2    14     3     1\n  1.7560192941575337E+00 a      5290     2    15     3     1\n  2.2263668095263745E-02 a      5291     2    16     3     1\n -1.1089303526928738E-01 a      5292     2    17     3     1\n -1.2788396467490229E-01 a      5293     2    18     3     1\n  2.9730180868325084E-02 a      5294     2    19     3     1\n -1.9993534904303990E-02 a      5295     2    20     3     1\n  7.7910673578683076E-01 a      5296     2    21     3     1\n  3.8236672016762840E-03 a      5297     2    22     3     1\n -1.7389683319831688E+00 a      5298     2    23     3     1\n  2.7984518602650405E-02 a      5299     2    24     3     1\n -5.6807596349854765E-02 a      5300     2    25     3     1\n  1.1936191511085166E+01 b      5301     3     1\n"
  },
  {
    "path": "examples/potentials/Ethylbenzene_SCAN/weights.006.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -2.1697495595969407E+00 a         1     0     1     1     1\n -3.6698733385174749E+00 a         2     0     1     1     2\n -2.7618742921732444E+01 a         3     0     1     1     3\n  5.6385655464465438E+00 a         4     0     1     1     4\n  6.6552362998554928E+00 a         5     0     1     1     5\n -8.6811718844364414E+00 a         6     0     1     1     6\n  4.9217156963090432E+00 a         7     0     1     1     7\n -7.9801135158011549E-01 a         8     0     1     1     8\n -1.9125102590905214E+00 a         9     0     1     1     9\n  8.6811209997195409E+00 a        10     0     1     1    10\n  1.5324812732052255E+00 a        11     0     1     1    11\n -3.0465651002167654E-01 a        12     0     1     1    12\n -6.8972611589896204E-01 a        13     0     1     1    13\n  1.3389756685960588E+01 a        14     0     1     1    14\n  2.9931379991461449E-01 a        15     0     1     1    15\n  5.9523411091219369E+00 a        16     0     1     1    16\n -4.1349645544673272E+00 a        17     0     1     1    17\n -6.7028651496791172E+00 a        18     0     1     1    18\n -9.7792323168697379E+00 a        19     0     1     1    19\n -2.5735909159575980E+00 a        20     0     1     1    20\n -5.1681860291918849E+00 a        21     0     1     1    21\n -5.0623431085542885E+00 a        22     0     1     1    22\n  7.9782617850621680E+00 a        23     0     1     1    23\n -8.6866709540450646E+00 a        24     0     1     1    24\n -9.9535031749897058E+00 a        25     0     1     1    25\n -1.9455386834957047E+00 a        26     0     2     1     1\n -2.5918942174754189E+00 a        27     0     2     1     2\n  1.1822517686651599E+01 a        28     0     2     1     3\n  1.8709205874842080E+01 a        29     0     2     1     4\n  1.2236033610648279E+01 a        30     0     2     1     5\n  6.2061417070579594E+00 a        31     0     2     1     6\n -5.2697753868176260E+00 a        32     0     2     1     7\n  4.3403712837243784E+00 a        33     0     2     1     8\n  1.0346135337977957E+01 a        34     0     2     1     9\n  4.7866293229894090E+00 a        35     0     2     1    10\n -1.3260579040711664E+00 a        36     0     2     1    11\n -4.5200017402115424E+00 a        37     0     2     1    12\n -8.3762598704082549E+00 a        38     0     2     1    13\n -1.0469880750696952E+01 a        39     0     2     1    14\n -1.7254224419473587E+00 a        40     0     2     1    15\n -6.3727626650659124E+00 a        41     0     2     1    16\n -8.4216192969686410E-01 a        42     0     2     1    17\n  2.7327371894811185E+00 a        43     0     2     1    18\n  3.9665987626588102E+00 a        44     0     2     1    19\n  4.3560808937899145E+00 a        45     0     2     1    20\n  3.6156740459833978E+00 a        46     0     2     1    21\n -1.0492483980445360E+00 a        47     0     2     1    22\n  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3.2709328432650326E+00 a      1936     0    78     1    11\n  7.0476220626883919E+00 a      1937     0    78     1    12\n -5.3438908698635599E+00 a      1938     0    78     1    13\n -1.5528954690021710E+01 a      1939     0    78     1    14\n  9.0771118630025002E-02 a      1940     0    78     1    15\n  7.0014232541775065E+00 a      1941     0    78     1    16\n -9.3484986278633269E+00 a      1942     0    78     1    17\n -5.4531762670514317E+00 a      1943     0    78     1    18\n -5.9156058957189748E+00 a      1944     0    78     1    19\n  7.8253891579566623E+00 a      1945     0    78     1    20\n -4.4018215462645864E+00 a      1946     0    78     1    21\n -3.6233821598616234E+00 a      1947     0    78     1    22\n -1.3405627522790287E+00 a      1948     0    78     1    23\n  4.3964754740782261E+00 a      1949     0    78     1    24\n  2.8124127870740416E+00 a      1950     0    78     1    25\n -3.1552615857243738E-01 a      1951     0    79     1     1\n -6.9201464763502747E+00 a      1952     0    79     1     2\n  8.1709032994097406E+00 a      1953     0    79     1     3\n  6.7973157489406466E+00 a      1954     0    79     1     4\n  3.7772691526595334E+00 a      1955     0    79     1     5\n -3.6645210163559634E+00 a      1956     0    79     1     6\n -5.7585648354726029E+00 a      1957     0    79     1     7\n -3.6735810500536239E+00 a      1958     0    79     1     8\n -4.5309316850747399E+00 a      1959     0    79     1     9\n  3.2521043078215710E+00 a      1960     0    79     1    10\n  2.1046642638245392E+00 a      1961     0    79     1    11\n  1.2323152379063529E+01 a      1962     0    79     1    12\n  5.4812592642731550E+00 a      1963     0    79     1    13\n  1.2720848879446409E+01 a      1964     0    79     1    14\n -1.6258216880519054E+01 a      1965     0    79     1    15\n -4.8753114362892340E+00 a      1966     0    79     1    16\n  1.8783179544739944E+01 a      1967     0    79     1    17\n -1.7974347470977663E+00 a      1968     0    79     1    18\n -2.4646286412769427E+01 a      1969     0    79     1    19\n -1.5865821407567232E+01 a      1970     0    79     1    20\n -4.5230535111857844E+00 a      1971     0    79     1    21\n -8.1313341376072295E+00 a      1972     0    79     1    22\n  9.9124690467029286E-01 a      1973     0    79     1    23\n -8.4417081969164514E+00 a      1974     0    79     1    24\n  2.0427039418719795E+00 a      1975     0    79     1    25\n  6.7033466566285798E+00 a      1976     0    80     1     1\n  8.2242861485716734E+00 a      1977     0    80     1     2\n  6.9195806583718555E+00 a      1978     0    80     1     3\n -6.3691735687042232E+00 a      1979     0    80     1     4\n -2.8258906744554420E+00 a      1980     0    80     1     5\n  4.8216711196649964E+00 a      1981     0    80     1     6\n -2.3579008946172311E-01 a      1982     0    80     1     7\n -3.2995109016839835E-01 a      1983     0    80     1     8\n -1.5258569934947865E+01 a      1984     0    80     1     9\n -4.9214593092999737E+00 a      1985     0    80     1    10\n -1.9168513794976583E+01 a      1986     0    80     1    11\n -7.8253907975327630E+00 a      1987     0    80     1    12\n  2.0805197572312760E+01 a      1988     0    80     1    13\n -2.0136348375511279E-01 a      1989     0    80     1    14\n -1.0722415934205777E+01 a      1990     0    80     1    15\n  9.3258393178319192E+00 a      1991     0    80     1    16\n -6.2407291906097093E+00 a      1992     0    80     1    17\n -3.4079921931394206E+00 a      1993     0    80     1    18\n -1.9305342009692532E+00 a      1994     0    80     1    19\n -3.3259506864868480E+00 a      1995     0    80     1    20\n  6.4097975977911776E+00 a      1996     0    80     1    21\n -8.1072758192225560E+00 a      1997     0    80     1    22\n -2.5048448889005193E+00 a      1998     0    80     1    23\n -1.5220694885647783E+01 a      1999     0    80     1    24\n  5.2274960828283126E+00 a      2000     0    80     1    25\n -1.4243347078200361E+00 a      2001     0    81     1     1\n -1.0964671462628049E+01 a      2002     0    81     1     2\n  2.0150399089561808E+00 a      2003     0    81     1     3\n  8.8755273764421165E+00 a      2004     0    81     1     4\n -1.4769374490889529E+00 a      2005     0    81     1     5\n  1.3361156794288496E+00 a      2006     0    81     1     6\n  3.4839704111322320E+00 a      2007     0    81     1     7\n -1.2389969337556202E+01 a      2008     0    81     1     8\n  2.3076862076207036E+00 a      2009     0    81     1     9\n -8.2011027614464211E+00 a      2010     0    81     1    10\n  1.2796174161960991E+01 a      2011     0    81     1    11\n -4.9977822914032579E+00 a      2012     0    81     1    12\n -1.5566111207733790E+01 a      2013     0    81     1    13\n -1.2086443983441791E+01 a      2014     0    81     1    14\n  1.1435969100045966E+01 a      2015     0    81     1    15\n  5.9029453354603556E-01 a      2016     0    81     1    16\n  1.1963883008717800E-01 a      2017     0    81     1    17\n -6.4884181494454163E-01 a      2018     0    81     1    18\n -1.8429595951562030E+00 a      2019     0    81     1    19\n -3.2040783062032907E-01 a      2020     0    81     1    20\n  8.6850349699645495E+00 a      2021     0    81     1    21\n  4.2329106831563337E+00 a      2022     0    81     1    22\n  1.3419187081939459E+01 a      2023     0    81     1    23\n  5.5782241258714098E+00 a      2024     0    81     1    24\n  1.1050013375539850E+01 a      2025     0    81     1    25\n -4.9474790801113605E-01 a      2026     0    82     1     1\n  3.9645548923153773E+00 a      2027     0    82     1     2\n -1.4845303034569753E+01 a      2028     0    82     1     3\n -1.3469533681831251E+01 a      2029     0    82     1     4\n  8.8211724988018183E+00 a      2030     0    82     1     5\n  5.6962283855325060E+00 a      2031     0    82     1     6\n -7.9372230197475746E+00 a      2032     0    82     1     7\n -4.7279065224518080E+00 a      2033     0    82     1     8\n -4.8176310438319331E-01 a      2034     0    82     1     9\n  3.4184190630414317E+00 a      2035     0    82     1    10\n  1.8157129644893164E+00 a      2036     0    82     1    11\n -1.0788744308039704E+00 a      2037     0    82     1    12\n  2.3306724366883254E+00 a      2038     0    82     1    13\n  1.3451831418219440E+01 a      2039     0    82     1    14\n  5.5431970033223033E-01 a      2040     0    82     1    15\n  1.7171852736699689E+00 a      2041     0    82     1    16\n -1.1359908973424047E+00 a      2042     0    82     1    17\n -1.0284104796745149E+01 a      2043     0    82     1    18\n -7.9031200938787016E+00 a      2044     0    82     1    19\n  1.2602047024714105E+00 a      2045     0    82     1    20\n  1.1693824472606419E+01 a      2046     0    82     1    21\n  3.7325650995365072E+00 a      2047     0    82     1    22\n -8.2740795949735695E+00 a      2048     0    82     1    23\n -4.9261964714432960E+00 a      2049     0    82     1    24\n  1.2298814271432419E+00 a      2050     0    82     1    25\n -6.0795653082429113E-01 a      2051     0    83     1     1\n -6.5504958326154095E-01 a      2052     0    83     1     2\n -2.7579675896828717E+00 a      2053     0    83     1     3\n -2.4843669083440498E+00 a      2054     0    83     1     4\n  4.0073320391174878E+00 a      2055     0    83     1     5\n -2.9379903506880285E+00 a      2056     0    83     1     6\n  4.9132791879881932E+00 a      2057     0    83     1     7\n  4.6910077090565627E+00 a      2058     0    83     1     8\n -1.3349800065706807E+00 a      2059     0    83     1     9\n -5.9151370311355622E-01 a      2060     0    83     1    10\n  5.1759672239511278E+00 a      2061     0    83     1    11\n -1.0681326524023102E-01 a      2062     0    83     1    12\n -8.4348161316736214E-01 a      2063     0    83     1    13\n  2.2532225546106708E+00 a      2064     0    83     1    14\n  1.4058574177267378E+00 a      2065     0    83     1    15\n -1.1514517289411177E+00 a      2066     0    83     1    16\n -1.0747396887562696E-01 a      2067     0    83     1    17\n  2.2174635219570762E+00 a      2068     0    83     1    18\n -3.6468560131068126E+00 a      2069     0    83     1    19\n  2.8296291452914430E+00 a      2070     0    83     1    20\n -8.7829842862319263E-01 a      2071     0    83     1    21\n  2.6748062657577116E+00 a      2072     0    83     1    22\n  1.3855852423108328E+00 a      2073     0    83     1    23\n -3.6244308801488373E-01 a      2074     0    83     1    24\n  8.1479731385199088E+00 a      2075     0    83     1    25\n  3.1102915121257415E+00 a      2076     0    84     1     1\n -9.1044012081775524E-02 a      2077     0    84     1     2\n  1.0112002973877896E+01 a      2078     0    84     1     3\n  6.0138111981033437E-01 a      2079     0    84     1     4\n -4.1165090158213049E+00 a      2080     0    84     1     5\n  2.2080407009619440E+00 a      2081     0    84     1     6\n -4.5695298461408953E+00 a      2082     0    84     1     7\n  3.1694445151585833E+00 a      2083     0    84     1     8\n  3.5528329112528549E+00 a      2084     0    84     1     9\n -3.3630310467624285E+00 a      2085     0    84     1    10\n  1.8983692664923024E+00 a      2086     0    84     1    11\n -8.1181059099105513E-01 a      2087     0    84     1    12\n  8.4052322327041722E+00 a      2088     0    84     1    13\n -1.4911838543553297E+00 a      2089     0    84     1    14\n -5.5326420918847772E+00 a      2090     0    84     1    15\n -9.5987868115457925E-02 a      2091     0    84     1    16\n  3.1523788755289508E+00 a      2092     0    84     1    17\n  4.0201735077591376E+00 a      2093     0    84     1    18\n  8.0807216317065862E+00 a      2094     0    84     1    19\n -2.5334191401283590E+00 a      2095     0    84     1    20\n -3.0173259250892586E+00 a      2096     0    84     1    21\n -7.1789165689646657E+00 a      2097     0    84     1    22\n -9.8381570609539022E+00 a      2098     0    84     1    23\n  4.2000704304964565E+00 a      2099     0    84     1    24\n  1.7386150624886234E+00 a      2100     0    84     1    25\n -5.2092165362139164E+00 a      2101     0    85     1     1\n  5.5902421451457984E+00 a      2102     0    85     1     2\n  2.3693569541496631E+00 a      2103     0    85     1     3\n -8.0220670449386144E+00 a      2104     0    85     1     4\n -2.3865980224775813E+00 a      2105     0    85     1     5\n  2.1257980152867959E+00 a      2106     0    85     1     6\n  7.9122972753239047E+00 a      2107     0    85     1     7\n  3.5469003315420138E+00 a      2108     0    85     1     8\n -1.0871180389177118E+01 a      2109     0    85     1     9\n  7.9778733003390441E+00 a      2110     0    85     1    10\n  5.6040195674238031E+00 a      2111     0    85     1    11\n  2.5939528874486286E+00 a      2112     0    85     1    12\n -7.2154364980680787E+00 a      2113     0    85     1    13\n  1.0755117846890828E+01 a      2114     0    85     1    14\n  8.6148567064083803E+00 a      2115     0    85     1    15\n -8.0034015140884538E+00 a      2116     0    85     1    16\n -1.4614568467291086E+01 a      2117     0    85     1    17\n -9.8643799827336931E+00 a      2118     0    85     1    18\n -1.0858018793104169E+00 a      2119     0    85     1    19\n -2.0040784525251150E+00 a      2120     0    85     1    20\n  7.3099576628877108E+00 a      2121     0    85     1    21\n  3.4105121242322562E+00 a      2122     0    85     1    22\n  7.3338427323772679E+00 a      2123     0    85     1    23\n  1.5850206163363370E+00 a      2124     0    85     1    24\n  2.7808998120015671E-01 a      2125     0    85     1    25\n  4.7527171907452255E+00 a      2126     0    86     1     1\n  4.9909530668955711E+00 a      2127     0    86     1     2\n  6.6378218991612359E+00 a      2128     0    86     1     3\n  9.6473332865777266E+00 a      2129     0    86     1     4\n -3.8507802407579992E+00 a      2130     0    86     1     5\n  2.2248984205885951E+00 a      2131     0    86     1     6\n -5.2683295604656877E+00 a      2132     0    86     1     7\n -2.4483940052706124E+00 a      2133     0    86     1     8\n -3.8659280492756634E+00 a      2134     0    86     1     9\n -1.6543465037556258E+00 a      2135     0    86     1    10\n  8.8679999075250926E-01 a      2136     0    86     1    11\n  6.1908409549138685E+00 a      2137     0    86     1    12\n -1.1521239970381004E+01 a      2138     0    86     1    13\n -3.6300065106202064E+00 a      2139     0    86     1    14\n  4.2018799900451773E+00 a      2140     0    86     1    15\n  2.8527641569835054E+00 a      2141     0    86     1    16\n  2.1088447686634026E+00 a      2142     0    86     1    17\n  1.5344173197112843E+00 a      2143     0    86     1    18\n -1.7804816017306432E+01 a      2144     0    86     1    19\n  5.5544392756954633E+00 a      2145     0    86     1    20\n -8.8574238728528876E+00 a      2146     0    86     1    21\n -1.0406880706553459E-01 a      2147     0    86     1    22\n -1.1534798721004401E+01 a      2148     0    86     1    23\n  1.5207218608391602E+00 a      2149     0    86     1    24\n -4.1091964998211488E+00 a      2150     0    86     1    25\n -1.0186402081670147E+00 a      2151     0    87     1     1\n -6.6428062631968068E+00 a      2152     0    87     1     2\n -8.6184194410074326E+00 a      2153     0    87     1     3\n -4.3480323517218764E+00 a      2154     0    87     1     4\n -8.0396976612158131E+00 a      2155     0    87     1     5\n  3.6143059562750177E+00 a      2156     0    87     1     6\n  2.8609864497707643E-01 a      2157     0    87     1     7\n  1.6668447115313656E+00 a      2158     0    87     1     8\n  1.1876761041767219E+01 a      2159     0    87     1     9\n -4.9214466174142918E-01 a      2160     0    87     1    10\n -1.6698655682788561E+00 a      2161     0    87     1    11\n -2.9966475760892299E+00 a      2162     0    87     1    12\n  1.6698108317775983E+01 a      2163     0    87     1    13\n -9.0203423999209527E+00 a      2164     0    87     1    14\n -6.0424343156931366E+00 a      2165     0    87     1    15\n  1.5719150428186701E+00 a      2166     0    87     1    16\n  4.3359387761245820E+00 a      2167     0    87     1    17\n  4.2849823739190285E+00 a      2168     0    87     1    18\n  1.6606918544149362E+01 a      2169     0    87     1    19\n -5.8684651372907135E+00 a      2170     0    87     1    20\n  3.6820944805076539E+00 a      2171     0    87     1    21\n -7.0465520691919481E-01 a      2172     0    87     1    22\n  1.8923929120249083E+00 a      2173     0    87     1    23\n -3.9182076130728851E+00 a      2174     0    87     1    24\n  9.1808171767785467E+00 a      2175     0    87     1    25\n 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9.3005214901267674E-01 a      2192     0    88     1    17\n -1.5358575237234502E+00 a      2193     0    88     1    18\n -1.6379816507430847E+00 a      2194     0    88     1    19\n  4.0904622340138292E+00 a      2195     0    88     1    20\n -9.0672282030788864E-01 a      2196     0    88     1    21\n  4.2657029923479302E+00 a      2197     0    88     1    22\n  2.4051678008959789E+00 a      2198     0    88     1    23\n -1.8514393298887508E+00 a      2199     0    88     1    24\n -1.3064754649757739E+00 a      2200     0    88     1    25\n -1.1570535351866478E+00 a      2201     0    89     1     1\n  2.5190720570822394E+00 a      2202     0    89     1     2\n -8.0183848200116326E-01 a      2203     0    89     1     3\n  1.9656250905218693E+00 a      2204     0    89     1     4\n  2.4285227205294149E+00 a      2205     0    89     1     5\n -7.5716803848313852E+00 a      2206     0    89     1     6\n -3.8947530529509429E+00 a      2207     0    89     1     7\n  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4.8440745320704504E-01 a      5061     1    18     2    11\n  2.4196400821318615E+00 a      5062     1    18     2    12\n  1.2561093443190248E+00 a      5063     1    18     2    13\n -2.9968286845468701E+00 a      5064     1    18     2    14\n -5.0661381123937010E-01 a      5065     1    18     2    15\n  8.0528141780830217E-02 a      5066     1    18     2    16\n -3.0223935465223626E+00 a      5067     1    18     2    17\n -8.2745308569829013E-01 a      5068     1    18     2    18\n  4.2615111014798863E+00 a      5069     1    18     2    19\n -2.6017672909028128E-01 a      5070     1    18     2    20\n  2.7619340979278175E+00 a      5071     1    18     2    21\n  3.3999103765579202E+00 a      5072     1    18     2    22\n  2.3498547610543374E+00 a      5073     1    18     2    23\n -1.4937450638584623E-01 a      5074     1    18     2    24\n -2.1781140909068464E+00 a      5075     1    18     2    25\n  2.3914843200517351E+00 a      5076     1    19     2     1\n  1.0455542282854327E-01 a      5077     1    19     2     2\n  8.5162378879124634E-01 a      5078     1    19     2     3\n -1.0125549872796695E+00 a      5079     1    19     2     4\n  5.3094059612888900E-01 a      5080     1    19     2     5\n  1.8705690638176782E+00 a      5081     1    19     2     6\n  2.6410139403302633E-02 a      5082     1    19     2     7\n  6.3299972285806518E+00 a      5083     1    19     2     8\n -1.1274988753181696E+00 a      5084     1    19     2     9\n -2.1810863248314325E+00 a      5085     1    19     2    10\n -1.9526383223903618E-01 a      5086     1    19     2    11\n -4.6084639976860359E-01 a      5087     1    19     2    12\n -1.5696767227390840E-01 a      5088     1    19     2    13\n -5.8021907655654836E-01 a      5089     1    19     2    14\n  4.7855223010459896E-01 a      5090     1    19     2    15\n  1.7245485900428243E+00 a      5091     1    19     2    16\n -4.3965694793051737E+00 a      5092     1    19     2    17\n  4.8055451588736553E-01 a      5093     1    19     2    18\n  1.6654966879271607E+00 a      5094     1    19     2    19\n  8.6148872949636390E-01 a      5095     1    19     2    20\n  2.6237824230782687E+00 a      5096     1    19     2    21\n  3.2126471852367494E-01 a      5097     1    19     2    22\n  5.0916634918219439E-01 a      5098     1    19     2    23\n  2.5763309047566132E+00 a      5099     1    19     2    24\n -9.2430593765461833E-01 a      5100     1    19     2    25\n -2.8928059734317415E+00 a      5101     1    20     2     1\n  7.0274043408430875E-01 a      5102     1    20     2     2\n -2.2307321662927065E-01 a      5103     1    20     2     3\n  1.2633762286978281E+00 a      5104     1    20     2     4\n  8.7321261830110175E-01 a      5105     1    20     2     5\n -3.5321345599124149E-01 a      5106     1    20     2     6\n -1.4534942046688775E+00 a      5107     1    20     2     7\n  1.6966514616613639E+00 a      5108     1    20     2     8\n  1.6788206634847300E-01 a      5109     1    20     2     9\n -1.4804424281059547E-01 a      5110     1    20     2    10\n  1.4971215798232154E+00 a      5111     1    20     2    11\n -3.7905833836000911E+00 a      5112     1    20     2    12\n -7.0244149555063096E-01 a      5113     1    20     2    13\n  2.3844397284331209E+00 a      5114     1    20     2    14\n  1.5595465935415009E+00 a      5115     1    20     2    15\n  1.0281135710600786E+00 a      5116     1    20     2    16\n  2.2722144258901511E+00 a      5117     1    20     2    17\n  9.8619835543177448E-01 a      5118     1    20     2    18\n -1.7851253766014502E-01 a      5119     1    20     2    19\n  4.2929582243088499E-01 a      5120     1    20     2    20\n  5.3834318438123869E+00 a      5121     1    20     2    21\n -1.7468341791112680E+00 a      5122     1    20     2    22\n -7.7745316455823688E-01 a      5123     1    20     2    23\n  3.0533189331046606E+00 a      5124     1    20     2    24\n  2.1486228956063065E+00 a      5125     1    20     2    25\n -2.9520941261442850E+00 a      5126     1    21     2     1\n -4.0475968049997686E+00 a      5127     1    21     2     2\n  6.4080455106209333E-01 a      5128     1    21     2     3\n  1.3158039348064907E+00 a      5129     1    21     2     4\n -3.7485618801240603E+00 a      5130     1    21     2     5\n -4.4162445372564605E+00 a      5131     1    21     2     6\n -6.3888143153119072E+00 a      5132     1    21     2     7\n -4.2701085361779118E-01 a      5133     1    21     2     8\n -2.2151973192762178E+00 a      5134     1    21     2     9\n -2.7493567250277229E-01 a      5135     1    21     2    10\n -6.3889898839449122E-01 a      5136     1    21     2    11\n  1.8968253382625186E+00 a      5137     1    21     2    12\n  3.1756075095317610E-01 a      5138     1    21     2    13\n  3.0941058265394501E+00 a      5139     1    21     2    14\n  5.8697969632661184E+00 a      5140     1    21     2    15\n  1.9050715063517503E+00 a      5141     1    21     2    16\n -1.9464017063504508E+00 a      5142     1    21     2    17\n -2.1111211336475338E-01 a      5143     1    21     2    18\n  5.7085868840848528E-02 a      5144     1    21     2    19\n  3.5329271523558670E+00 a      5145     1    21     2    20\n -5.4821862523587344E+00 a      5146     1    21     2    21\n -1.3542101011539680E+00 a      5147     1    21     2    22\n  2.6436721301471328E-01 a      5148     1    21     2    23\n  6.8032372676081887E-01 a      5149     1    21     2    24\n  2.4022530182983681E+00 a      5150     1    21     2    25\n  1.0462360079460984E+00 a      5151     1    22     2     1\n -2.9133673855060467E+00 a      5152     1    22     2     2\n  1.4057233590237977E-01 a      5153     1    22     2     3\n -2.4422843597224220E+00 a      5154     1    22     2     4\n -7.2188673868224418E-01 a      5155     1    22     2     5\n  2.4279059742021105E+00 a      5156     1    22     2     6\n -9.6203184362686178E-01 a      5157     1    22     2     7\n  2.6553266385703691E+00 a      5158     1    22     2     8\n  5.8000509290644500E+00 a      5159     1    22     2     9\n  1.3224121985510022E+00 a      5160     1    22     2    10\n -3.0895419918307981E-01 a      5161     1    22     2    11\n -3.7059758018929512E+00 a      5162     1    22     2    12\n  2.7157047409042807E+00 a      5163     1    22     2    13\n  2.6753919937439929E-01 a      5164     1    22     2    14\n  5.2000576555087319E+00 a      5165     1    22     2    15\n  1.4334002491011191E-01 a      5166     1    22     2    16\n  7.6690584735559753E-01 a      5167     1    22     2    17\n  1.2582429417632357E+00 a      5168     1    22     2    18\n  1.2648510121373098E+00 a      5169     1    22     2    19\n -5.1022225582272507E-01 a      5170     1    22     2    20\n -3.2778206805469545E-01 a      5171     1    22     2    21\n -1.6164299080560121E+00 a      5172     1    22     2    22\n  9.6035891413738128E-01 a      5173     1    22     2    23\n -2.6962557528940034E+00 a      5174     1    22     2    24\n -2.0938489722277196E+00 a      5175     1    22     2    25\n  1.6518575073503858E+00 a      5176     1    23     2     1\n  4.3658450184850022E+00 a      5177     1    23     2     2\n -2.5401518657280614E-01 a      5178     1    23     2     3\n -2.4504179826318839E-01 a      5179     1    23     2     4\n -3.4868783621252492E-01 a      5180     1    23     2     5\n  1.4555776587858227E+00 a      5181     1    23     2     6\n  1.5853272764559438E+00 a      5182     1    23     2     7\n -5.8675763614240122E+00 a      5183     1    23     2     8\n -1.6997997195864469E+00 a      5184     1    23     2     9\n -2.1106851847693128E-01 a      5185     1    23     2    10\n  1.6245585133837133E+00 a      5186     1    23     2    11\n  2.9190907728672000E-01 a      5187     1    23     2    12\n -5.7466514930044887E-01 a      5188     1    23     2    13\n -1.7430345624300767E-02 a      5189     1    23     2    14\n  4.9178429567984011E-01 a      5190     1    23     2    15\n  7.7747359709116115E-01 a      5191     1    23     2    16\n -1.6828815269108388E+00 a      5192     1    23     2    17\n -2.9115191301502330E-01 a      5193     1    23     2    18\n  1.5336318332595944E+00 a      5194     1    23     2    19\n  2.1593691934958442E-01 a      5195     1    23     2    20\n -1.6038780962530299E+00 a      5196     1    23     2    21\n -6.9217774348284977E-01 a      5197     1    23     2    22\n  4.9858337460902280E-01 a      5198     1    23     2    23\n -2.9315316694345874E+00 a      5199     1    23     2    24\n -3.4114963673083079E+00 a      5200     1    23     2    25\n  1.6159948742700294E+00 a      5201     1    24     2     1\n  1.9538889022302033E+00 a      5202     1    24     2     2\n  6.1674167093866084E-01 a      5203     1    24     2     3\n  1.0327317447856539E+00 a      5204     1    24     2     4\n -1.6900780267528923E-01 a      5205     1    24     2     5\n -3.5057834446708513E+00 a      5206     1    24     2     6\n  4.3326760228511798E+00 a      5207     1    24     2     7\n -1.3371636046820159E+00 a      5208     1    24     2     8\n -3.2620804519005846E+00 a      5209     1    24     2     9\n -8.5629517431219704E-01 a      5210     1    24     2    10\n  1.1396047853936935E+00 a      5211     1    24     2    11\n -3.0699843448768133E-01 a      5212     1    24     2    12\n  1.5502096355921691E+00 a      5213     1    24     2    13\n -4.8225198300929160E+00 a      5214     1    24     2    14\n -3.8035500339344770E+00 a      5215     1    24     2    15\n -5.5383100114316997E-01 a      5216     1    24     2    16\n -5.5491822403379745E+00 a      5217     1    24     2    17\n  1.2170174075705877E+00 a      5218     1    24     2    18\n -1.6336867517932618E-01 a      5219     1    24     2    19\n -7.9294813142514531E-01 a      5220     1    24     2    20\n -7.1185121793781322E-02 a      5221     1    24     2    21\n -9.7698453462965595E-01 a      5222     1    24     2    22\n -1.4393470783564390E+00 a      5223     1    24     2    23\n -5.9167064400372382E-01 a      5224     1    24     2    24\n  9.7317824998891256E-01 a      5225     1    24     2    25\n -4.5037125647766150E+00 a      5226     1    25     2     1\n  1.7342201313625112E+00 a      5227     1    25     2     2\n  2.5745263292505888E-01 a      5228     1    25     2     3\n  3.0696209941237368E-01 a      5229     1    25     2     4\n -3.8379160861118222E-01 a      5230     1    25     2     5\n -1.6105857805228472E+00 a      5231     1    25     2     6\n  4.4698744099323635E+00 a      5232     1    25     2     7\n -2.9072809458232971E+00 a      5233     1    25     2     8\n -1.4731578090968062E-01 a      5234     1    25     2     9\n -1.8114942725982350E+00 a      5235     1    25     2    10\n  5.3229967325635907E-01 a      5236     1    25     2    11\n -1.6379254367195222E+00 a      5237     1    25     2    12\n  2.4266944211015185E-01 a      5238     1    25     2    13\n -3.5213796362734140E-01 a      5239     1    25     2    14\n -1.1644993482843600E+00 a      5240     1    25     2    15\n -9.1812359409814059E-01 a      5241     1    25     2    16\n -1.7912955125000245E+00 a      5242     1    25     2    17\n -4.1145419625444735E-01 a      5243     1    25     2    18\n  5.1279253330210217E-01 a      5244     1    25     2    19\n -4.4420539859737653E+00 a      5245     1    25     2    20\n  4.8935218207857129E-01 a      5246     1    25     2    21\n -1.0087305715780823E-01 a      5247     1    25     2    22\n  3.4635196571238644E+00 a      5248     1    25     2    23\n -8.5901835392140988E+00 a      5249     1    25     2    24\n -7.3469206940454543E-02 a      5250     1    25     2    25\n -1.8968623344556221E+01 b      5251     2     1\n -1.4708853013907071E+01 b      5252     2     2\n  5.2978596628724262E-01 b      5253     2     3\n -3.7435713651300619E+00 b      5254     2     4\n  6.9856702871531731E+00 b      5255     2     5\n  1.7414508824044105E+01 b      5256     2     6\n -1.5842618204345399E+01 b      5257     2     7\n -4.1668753163883576E-01 b      5258     2     8\n  8.7515519935470376E+00 b      5259     2     9\n  1.1673985832592932E+01 b      5260     2    10\n -1.1352926377926842E+01 b      5261     2    11\n -1.3199219072527804E+00 b      5262     2    12\n  8.3888300959014295E+00 b      5263     2    13\n  5.9279056703625335E+00 b      5264     2    14\n -3.8557574089720243E+00 b      5265     2    15\n -6.2895740987834019E+00 b      5266     2    16\n -1.6400146977721028E+00 b      5267     2    17\n -2.7461918934879854E+00 b      5268     2    18\n -1.4681831636569228E+01 b      5269     2    19\n  3.3066235246921596E+00 b      5270     2    20\n -2.0184844840017395E+00 b      5271     2    21\n -8.4760440789134321E+00 b      5272     2    22\n  5.9471415023449401E+00 b      5273     2    23\n  3.8621261117828469E+00 b      5274     2    24\n -1.5510284202453818E+01 b      5275     2    25\n -4.0146066018808726E-02 a      5276     2     1     3     1\n -2.1886339110119467E-02 a      5277     2     2     3     1\n  1.6299800869966747E+00 a      5278     2     3     3     1\n -3.8094927893565743E-02 a      5279     2     4     3     1\n -4.3715386726556026E-02 a      5280     2     5     3     1\n -3.9996253667800984E-02 a      5281     2     6     3     1\n -2.0402369168021267E-01 a      5282     2     7     3     1\n -1.7698903647339524E-02 a      5283     2     8     3     1\n  5.2345326550665296E-02 a      5284     2     9     3     1\n -8.4199581437601811E-01 a      5285     2    10     3     1\n -1.6520818934194048E-01 a      5286     2    11     3     1\n -8.9103165812771078E-03 a      5287     2    12     3     1\n  2.0800889327069694E+00 a      5288     2    13     3     1\n -5.1329906860830339E-02 a      5289     2    14     3     1\n  3.4939565963684348E-04 a      5290     2    15     3     1\n -4.4741060685440343E-01 a      5291     2    16     3     1\n  4.6221038180404806E-03 a      5292     2    17     3     1\n -7.7263895612098357E-02 a      5293     2    18     3     1\n  2.3805530123397056E+00 a      5294     2    19     3     1\n  3.1825582373527540E-02 a      5295     2    20     3     1\n -2.4890197349882404E+00 a      5296     2    21     3     1\n  3.6317402132344614E+00 a      5297     2    22     3     1\n -9.5012372068264550E-01 a      5298     2    23     3     1\n -1.8599221791063287E-02 a      5299     2    24     3     1\n -3.7169855387561790E-02 a      5300     2    25     3     1\n  9.5489532092654468E+00 b      5301     3     1\n"
  },
  {
    "path": "examples/potentials/H2O_BLYP/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: BLYP\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5515845506575516E+01\nconv_energy   1.8804016272992857E+02\nconv_length   4.3812936604793364E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   4              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 5\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               25             # Write energy comparison.\nwrite_trainforces               25             # Write force comparison.\nwrite_weights_epoch                            # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/potentials/H2O_BLYP/nnp-train.log.0000",
    "content": "\n*** SETUP: MPI ****************************************************************\n\nNumber of processors: 16\nProcess 1 of 16 (rank 0): n41-014\nProcess 2 of 16 (rank 1): n41-014\nProcess 3 of 16 (rank 2): n41-014\nProcess 4 of 16 (rank 3): n41-014\nProcess 5 of 16 (rank 4): n41-014\nProcess 6 of 16 (rank 5): n41-014\nProcess 7 of 16 (rank 6): n41-014\nProcess 8 of 16 (rank 7): n41-014\nProcess 9 of 16 (rank 8): n41-014\nProcess 10 of 16 (rank 9): n41-014\nProcess 11 of 16 (rank 10): n41-014\nProcess 12 of 16 (rank 11): n41-014\nProcess 13 of 16 (rank 12): n41-014\nProcess 14 of 16 (rank 13): n41-014\nProcess 15 of 16 (rank 14): n41-014\nProcess 16 of 16 (rank 15): n41-014\n*******************************************************************************\n\n*******************************************************************************\n\n   NNP LIBRARY v0.1.0\n   ------------------\n\nGit branch  : master\nGit revision: ff23516 (ff235161e90cd94280c0df259129e8d4e5e07007)\n\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 167 lines.\nFound 102 lines with keywords.\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is used.\nMean energy per atom     :  -2.5515845506575516E+01\nConversion factor energy :   1.8804016272992857E+02\nConversion factor length :   4.3812936604793364E+00\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  H (  1)\nElement  1:  O (  8)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:   0.00000000E+00\nElement  1:   0.00000000E+00\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_TANHU (2)\nf(r) = tanh^3(1 - r/rc)\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  H  2  H    5.209E-05 0.000E+00         5.258E+01  2 0.00    98\n   2  H  2  O    5.209E-05 0.000E+00         5.258E+01  2 0.00   108\n   3  H  2  H    5.209E-04 0.000E+00         5.258E+01  2 0.00    99\n   4  H  2  O    5.209E-04 0.000E+00         5.258E+01  2 0.00   109\n   5  H  2  H    1.563E-03 0.000E+00         5.258E+01  2 0.00   100\n   6  H  2  O    1.563E-03 0.000E+00         5.258E+01  2 0.00   110\n   7  H  2  H    3.126E-03 0.000E+00         5.258E+01  2 0.00   101\n   8  H  2  O    3.126E-03 0.000E+00         5.258E+01  2 0.00   111\n   9  H  2  O    7.814E-03 3.943E+00         5.258E+01  2 0.00   112\n  10  H  2  H    7.814E-03 8.324E+00         5.258E+01  2 0.00   102\n  11  H  2  O    1.563E-02 3.943E+00         5.258E+01  2 0.00   113\n  12  H  2  H    1.563E-02 8.324E+00         5.258E+01  2 0.00   103\n  13  H  2  O    3.126E-02 3.943E+00         5.258E+01  2 0.00   114\n  14  H  2  H    3.126E-02 8.324E+00         5.258E+01  2 0.00   104\n  15  H  2  O    7.814E-02 3.943E+00         5.258E+01  2 0.00   115\n  16  H  2  H    7.814E-02 8.324E+00         5.258E+01  2 0.00   105\n  17  H  3  O  O 5.209E-05 0.000E+00 -1  4.0 5.258E+01  2 0.00   162\n  18  H  3  O  O 5.209E-05 0.000E+00  1  4.0 5.258E+01  2 0.00   161\n  19  H  3  H  O 5.209E-04 0.000E+00 -1  4.0 5.258E+01  2 0.00   152\n  20  H  3  H  O 5.209E-04 0.000E+00  1  4.0 5.258E+01  2 0.00   150\n  21  H  3  H  O 1.563E-03 0.000E+00 -1  1.0 5.258E+01  2 0.00   147\n  22  H  3  O  O 1.563E-03 0.000E+00 -1  1.0 5.258E+01  2 0.00   160\n  23  H  3  H  O 1.563E-03 0.000E+00  1  1.0 5.258E+01  2 0.00   145\n  24  H  3  O  O 1.563E-03 0.000E+00  1  1.0 5.258E+01  2 0.00   159\n  25  H  3  H  O 3.647E-03 0.000E+00 -1  1.0 5.258E+01  2 0.00   142\n  26  H  3  H  O 3.647E-03 0.000E+00  1  1.0 5.258E+01  2 0.00   140\n  27  H  3  H  O 1.042E-02 0.000E+00  1  1.0 5.258E+01  2 0.00   137\n-------------------------------------------------------------------------------\nShort range atomic symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  O  2  H    5.209E-05 0.000E+00         5.258E+01  2 0.00   117\n   2  O  2  O    5.209E-05 0.000E+00         5.258E+01  2 0.00   127\n   3  O  2  H    5.209E-04 0.000E+00         5.258E+01  2 0.00   118\n   4  O  2  O    5.209E-04 0.000E+00         5.258E+01  2 0.00   128\n   5  O  2  H    1.563E-03 0.000E+00         5.258E+01  2 0.00   119\n   6  O  2  O    1.563E-03 0.000E+00         5.258E+01  2 0.00   129\n   7  O  2  H    3.126E-03 0.000E+00         5.258E+01  2 0.00   120\n   8  O  2  O    3.126E-03 0.000E+00         5.258E+01  2 0.00   130\n   9  O  2  H    7.814E-03 3.943E+00         5.258E+01  2 0.00   121\n  10  O  2  O    7.814E-03 1.753E+01         5.258E+01  2 0.00   131\n  11  O  2  H    1.563E-02 3.943E+00         5.258E+01  2 0.00   122\n  12  O  2  O    1.563E-02 1.753E+01         5.258E+01  2 0.00   132\n  13  O  2  H    3.126E-02 3.943E+00         5.258E+01  2 0.00   123\n  14  O  2  O    3.126E-02 1.753E+01         5.258E+01  2 0.00   133\n  15  O  2  H    7.814E-02 3.943E+00         5.258E+01  2 0.00   124\n  16  O  2  O    7.814E-02 1.753E+01         5.258E+01  2 0.00   134\n  17  O  3  H  O 5.209E-05 0.000E+00 -1  4.0 5.258E+01  2 0.00   157\n  18  O  3  O  O 5.209E-05 0.000E+00 -1  4.0 5.258E+01  2 0.00   167\n  19  O  3  H  O 5.209E-05 0.000E+00  1  4.0 5.258E+01  2 0.00   156\n  20  O  3  O  O 5.209E-05 0.000E+00  1  4.0 5.258E+01  2 0.00   166\n  21  O  3  H  H 5.209E-04 0.000E+00 -1  4.0 5.258E+01  2 0.00   151\n  22  O  3  H  H 5.209E-04 0.000E+00  1  4.0 5.258E+01  2 0.00   149\n  23  O  3  H  H 1.563E-03 0.000E+00 -1  1.0 5.258E+01  2 0.00   146\n  24  O  3  H  O 1.563E-03 0.000E+00 -1  1.0 5.258E+01  2 0.00   155\n  25  O  3  O  O 1.563E-03 0.000E+00 -1  1.0 5.258E+01  2 0.00   165\n  26  O  3  H  H 1.563E-03 0.000E+00  1  1.0 5.258E+01  2 0.00   144\n  27  O  3  H  O 1.563E-03 0.000E+00  1  1.0 5.258E+01  2 0.00   154\n  28  O  3  O  O 1.563E-03 0.000E+00  1  1.0 5.258E+01  2 0.00   164\n  29  O  3  H  H 3.647E-03 0.000E+00 -1  1.0 5.258E+01  2 0.00   141\n  30  O  3  H  H 3.647E-03 0.000E+00  1  1.0 5.258E+01  2 0.00   139\n-------------------------------------------------------------------------------\nMinimum cutoff radius for element  H: 52.575524\nMinimum cutoff radius for element  O: 52.575524\nMaximum cutoff radius (global)      : 52.575524\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function group index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  H  2  H            *         *         5.258E+01  2 0.00     *    *    *  \n   -  -  -  -    5.209E-05 0.000E+00                 -  -    -    97    1    1  \n   -  -  -  -    5.209E-04 0.000E+00                 -  -    -    98    2    3  \n   -  -  -  -    1.563E-03 0.000E+00                 -  -    -    99    3    5  \n   -  -  -  -    3.126E-03 0.000E+00                 -  -    -   100    4    7  \n   -  -  -  -    7.814E-03 8.324E+00                 -  -    -   101    5   10  \n   -  -  -  -    1.563E-02 8.324E+00                 -  -    -   102    6   12  \n   -  -  -  -    3.126E-02 8.324E+00                 -  -    -   103    7   14  \n   -  -  -  -    7.814E-02 8.324E+00                 -  -    -   104    8   16  \n   2  H  2  O            *         *         5.258E+01  2 0.00     *    *    *  \n   -  -  -  -    5.209E-05 0.000E+00                 -  -    -   107    1    2  \n   -  -  -  -    5.209E-04 0.000E+00                 -  -    -   108    2    4  \n   -  -  -  -    1.563E-03 0.000E+00                 -  -    -   109    3    6  \n   -  -  -  -    3.126E-03 0.000E+00                 -  -    -   110    4    8  \n   -  -  -  -    7.814E-03 3.943E+00                 -  -    -   111    5    9  \n   -  -  -  -    1.563E-02 3.943E+00                 -  -    -   112    6   11  \n   -  -  -  -    3.126E-02 3.943E+00                 -  -    -   113    7   13  \n   -  -  -  -    7.814E-02 3.943E+00                 -  -    -   114    8   15  \n   3  H  3  H  O         *         *  *    * 5.258E+01  2 0.00     *    *    * *\n   -  -  -  -  - 5.209E-04 0.000E+00 -1  4.0         -  -    -   151    1   19 1\n   -  -  -  -  - 5.209E-04 0.000E+00  1  4.0         -  -    -   149    2   20 0\n   -  -  -  -  - 1.563E-03 0.000E+00 -1  1.0         -  -    -   146    3   21 1\n   -  -  -  -  - 1.563E-03 0.000E+00  1  1.0         -  -    -   144    4   23 0\n   -  -  -  -  - 3.647E-03 0.000E+00 -1  1.0         -  -    -   141    5   25 1\n   -  -  -  -  - 3.647E-03 0.000E+00  1  1.0         -  -    -   139    6   26 0\n   -  -  -  -  - 1.042E-02 0.000E+00  1  1.0         -  -    -   136    7   27 1\n   4  H  3  O  O         *         *  *    * 5.258E+01  2 0.00     *    *    * *\n   -  -  -  -  - 5.209E-05 0.000E+00 -1  4.0         -  -    -   161    1   17 1\n   -  -  -  -  - 5.209E-05 0.000E+00  1  4.0         -  -    -   160    2   18 0\n   -  -  -  -  - 1.563E-03 0.000E+00 -1  1.0         -  -    -   159    3   22 1\n   -  -  -  -  - 1.563E-03 0.000E+00  1  1.0         -  -    -   158    4   24 0\n-------------------------------------------------------------------------------\nShort range atomic symmetry function groups element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  O  2  H            *         *         5.258E+01  2 0.00     *    *    *  \n   -  -  -  -    5.209E-05 0.000E+00                 -  -    -   116    1    1  \n   -  -  -  -    5.209E-04 0.000E+00                 -  -    -   117    2    3  \n   -  -  -  -    1.563E-03 0.000E+00                 -  -    -   118    3    5  \n   -  -  -  -    3.126E-03 0.000E+00                 -  -    -   119    4    7  \n   -  -  -  -    7.814E-03 3.943E+00                 -  -    -   120    5    9  \n   -  -  -  -    1.563E-02 3.943E+00                 -  -    -   121    6   11  \n   -  -  -  -    3.126E-02 3.943E+00                 -  -    -   122    7   13  \n   -  -  -  -    7.814E-02 3.943E+00                 -  -    -   123    8   15  \n   2  O  2  O            *         *         5.258E+01  2 0.00     *    *    *  \n   -  -  -  -    5.209E-05 0.000E+00                 -  -    -   126    1    2  \n   -  -  -  -    5.209E-04 0.000E+00                 -  -    -   127    2    4  \n   -  -  -  -    1.563E-03 0.000E+00                 -  -    -   128    3    6  \n   -  -  -  -    3.126E-03 0.000E+00                 -  -    -   129    4    8  \n   -  -  -  -    7.814E-03 1.753E+01                 -  -    -   130    5   10  \n   -  -  -  -    1.563E-02 1.753E+01                 -  -    -   131    6   12  \n   -  -  -  -    3.126E-02 1.753E+01                 -  -    -   132    7   14  \n   -  -  -  -    7.814E-02 1.753E+01                 -  -    -   133    8   16  \n   3  O  3  H  H         *         *  *    * 5.258E+01  2 0.00     *    *    * *\n   -  -  -  -  - 5.209E-04 0.000E+00 -1  4.0         -  -    -   150    1   21 1\n   -  -  -  -  - 5.209E-04 0.000E+00  1  4.0         -  -    -   148    2   22 0\n   -  -  -  -  - 1.563E-03 0.000E+00 -1  1.0         -  -    -   145    3   23 1\n   -  -  -  -  - 1.563E-03 0.000E+00  1  1.0         -  -    -   143    4   26 0\n   -  -  -  -  - 3.647E-03 0.000E+00 -1  1.0         -  -    -   140    5   29 1\n   -  -  -  -  - 3.647E-03 0.000E+00  1  1.0         -  -    -   138    6   30 0\n   4  O  3  H  O         *         *  *    * 5.258E+01  2 0.00     *    *    * *\n   -  -  -  -  - 5.209E-05 0.000E+00 -1  4.0         -  -    -   156    1   17 1\n   -  -  -  -  - 5.209E-05 0.000E+00  1  4.0         -  -    -   155    2   19 0\n   -  -  -  -  - 1.563E-03 0.000E+00 -1  1.0         -  -    -   154    3   24 1\n   -  -  -  -  - 1.563E-03 0.000E+00  1  1.0         -  -    -   153    4   27 0\n   5  O  3  O  O         *         *  *    * 5.258E+01  2 0.00     *    *    * *\n   -  -  -  -  - 5.209E-05 0.000E+00 -1  4.0         -  -    -   166    1   18 1\n   -  -  -  -  - 5.209E-05 0.000E+00  1  4.0         -  -    -   165    2   20 0\n   -  -  -  -  - 1.563E-03 0.000E+00 -1  1.0         -  -    -   164    3   25 1\n   -  -  -  -  - 1.563E-03 0.000E+00  1  1.0         -  -    -   163    4   28 0\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic short range NN for element  H :\nNumber of weights    :   1325\nNumber of biases     :     51\nNumber of connections:   1376\nArchitecture       27   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  O :\nNumber of weights    :   1400\nNumber of biases     :     51\nNumber of connections:   1451\nArchitecture       30   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALECENTER (3)\nGs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  1.01E+00  9.50E+00  2.26E+00  7.29E-01  1.18E-01  0.00  1.00 3\n   2  6.86E-01  4.95E+00  1.32E+00  3.64E-01  2.35E-01  0.00  1.00 3\n   3  7.13E-01  7.06E+00  1.64E+00  5.42E-01  1.58E-01  0.00  1.00 3\n   4  5.30E-01  3.73E+00  1.02E+00  2.70E-01  3.12E-01  0.00  1.00 3\n   5  3.81E-01  4.11E+00  9.13E-01  3.14E-01  2.68E-01  0.00  1.00 3\n   6  3.62E-01  2.26E+00  6.54E-01  1.56E-01  5.27E-01  0.00  1.00 3\n   7  1.89E-01  2.22E+00  4.63E-01  1.66E-01  4.92E-01  0.00  1.00 3\n   8  2.67E-01  1.32E+00  4.30E-01  8.25E-02  9.53E-01  0.00  1.00 3\n   9  2.34E-01  9.47E-01  3.70E-01  5.32E-02  1.40E+00  0.00  1.00 3\n  10  2.22E-01  2.75E+00  5.52E-01  2.07E-01  3.95E-01  0.00  1.00 3\n  11  1.34E-01  5.64E-01  2.71E-01  2.67E-02  2.33E+00  0.00  1.00 3\n  12  1.21E-01  1.72E+00  3.02E-01  1.18E-01  6.25E-01  0.00  1.00 3\n  13  4.85E-02  3.59E-01  1.84E-01  2.02E-02  3.22E+00  0.00  1.00 3\n  14  2.70E-02  9.09E-01  1.48E-01  5.29E-02  1.13E+00  0.00  1.00 3\n  15  2.45E-03  2.85E-01  7.42E-02  1.89E-02  3.53E+00  0.00  1.00 3\n  16  2.24E-04  3.15E-01  4.19E-02  2.18E-02  3.17E+00  0.00  1.00 3\n  17  2.19E-04  1.38E-01  1.90E-02  9.69E-03  7.24E+00  0.00  1.00 3\n  18  4.49E-03  5.71E-01  2.50E-02  3.81E-02  1.77E+00  0.00  1.00 3\n  19  2.70E-04  2.17E-01  1.82E-02  1.40E-02  4.62E+00  0.00  1.00 3\n  20  5.14E-02  1.65E+00  1.50E-01  1.11E-01  6.24E-01  0.00  1.00 3\n  21  3.41E-03  3.15E-01  1.90E-02  2.02E-02  3.20E+00  0.00  1.00 3\n  22  1.31E-04  1.03E-01  6.88E-03  6.62E-03  9.76E+00  0.00  1.00 3\n  23  3.42E-02  9.07E-01  8.44E-02  5.82E-02  1.15E+00  0.00  1.00 3\n  24  4.12E-04  1.57E-01  4.94E-03  9.84E-03  6.40E+00  0.00  1.00 3\n  25  8.69E-04  5.91E-02  3.79E-03  3.27E-03  1.72E+01  0.00  1.00 3\n  26  8.70E-03  1.94E-01  2.48E-02  1.09E-02  5.40E+00  0.00  1.00 3\n  27  1.63E-04  9.82E-03  1.97E-03  5.59E-04  1.04E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  1.44E+00  9.89E+00  2.65E+00  7.27E-01  1.18E-01  0.00  1.00 3\n   2  3.85E-01  4.57E+00  9.62E-01  3.62E-01  2.39E-01  0.00  1.00 3\n   3  1.16E+00  7.45E+00  2.03E+00  5.39E-01  1.59E-01  0.00  1.00 3\n   4  2.45E-01  3.35E+00  6.60E-01  2.66E-01  3.22E-01  0.00  1.00 3\n   5  8.22E-01  4.50E+00  1.31E+00  3.09E-01  2.72E-01  0.00  1.00 3\n   6  9.38E-02  1.88E+00  3.12E-01  1.49E-01  5.60E-01  0.00  1.00 3\n   7  5.69E-01  2.61E+00  8.60E-01  1.61E-01  4.91E-01  0.00  1.00 3\n   8  2.29E-02  9.37E-01  1.17E-01  7.17E-02  1.09E+00  0.00  1.00 3\n   9  5.18E-01  1.86E+00  7.39E-01  9.87E-02  7.46E-01  0.00  1.00 3\n  10  1.10E-01  2.89E+00  4.88E-01  2.45E-01  3.60E-01  0.00  1.00 3\n  11  3.61E-01  1.08E+00  5.41E-01  4.61E-02  1.39E+00  0.00  1.00 3\n  12  2.83E-02  2.51E+00  3.40E-01  2.16E-01  4.02E-01  0.00  1.00 3\n  13  1.44E-01  6.55E-01  3.68E-01  3.15E-02  1.96E+00  0.00  1.00 3\n  14  2.18E-03  2.29E+00  2.01E-01  1.89E-01  4.37E-01  0.00  1.00 3\n  15  7.24E-03  4.20E-01  1.48E-01  2.78E-02  2.42E+00  0.00  1.00 3\n  16  1.40E-06  2.02E+00  6.53E-02  1.43E-01  4.96E-01  0.00  1.00 3\n  17  2.33E-03  3.43E-01  1.76E-02  2.19E-02  2.93E+00  0.00  1.00 3\n  18  2.07E-05  5.66E-02  1.07E-03  3.31E-03  1.77E+01  0.00  1.00 3\n  19  4.78E-02  2.95E+00  2.10E-01  2.04E-01  3.45E-01  0.00  1.00 3\n  20  1.03E-03  4.86E-01  1.33E-02  3.20E-02  2.06E+00  0.00  1.00 3\n  21  8.33E-03  2.69E-01  3.22E-02  1.70E-02  3.83E+00  0.00  1.00 3\n  22  1.43E-02  1.39E+00  7.86E-02  9.39E-02  7.28E-01  0.00  1.00 3\n  23  1.98E-02  4.11E-01  5.10E-02  2.55E-02  2.56E+00  0.00  1.00 3\n  24  6.28E-04  2.35E-01  7.68E-03  1.44E-02  4.27E+00  0.00  1.00 3\n  25  3.66E-06  3.54E-02  4.46E-04  2.02E-03  2.82E+01  0.00  1.00 3\n  26  1.70E-02  8.13E-01  5.24E-02  5.32E-02  1.26E+00  0.00  1.00 3\n  27  4.53E-03  7.77E-01  3.96E-02  5.05E-02  1.29E+00  0.00  1.00 3\n  28  1.76E-05  9.78E-02  1.27E-03  5.72E-03  1.02E+01  0.00  1.00 3\n  29  5.85E-03  1.02E-01  1.67E-02  5.51E-03  1.04E+01  0.00  1.00 3\n  30  3.47E-03  1.54E-01  1.19E-02  8.84E-03  6.64E+00  0.00  1.00 3\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 0\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** SETUP: RANDOM NUMBER GENERATOR ********************************************\n\nRandom number generator seed: 5\nSeed for rank 0: 5\nSeed for rank 1: 953453411\nSeed for rank 2: 236996814\nSeed for rank 3: 3739766767\nSeed for rank 4: 3570525885\nSeed for rank 5: 887852006\nSeed for rank 6: 1562238070\nSeed for rank 7: 3945403792\nSeed for rank 8: 4206684233\nSeed for rank 9: 2097710088\nSeed for rank 10: 385778404\nSeed for rank 11: 2627419879\nSeed for rank 12: 1703970750\nSeed for rank 13: 3289549211\nSeed for rank 14: 1521011312\nSeed for rank 15: 2226588318\nSeed for global RNG: 2090094288\n*******************************************************************************\n\n*** STRUCTURE DISTRIBUTION ****************************************************\n\nReading configurations from data file: input.data.\nNumber of structures per processor: 437 (12) or 438 (4)\nDistributed 6996 structures, 119566141 bytes (114.03 MiB) transferred.\nNumber of local structures: 437\n*******************************************************************************\n\n*** DEFINE TRAINING/TEST SETS *************************************************\n\nDesired test set ratio      : 0.100000\nTotal number of energies    : 6996\nNumber of training energies : 6305\nNumber of test     energies : 691\nNumber of training forces   : 1542816\nNumber of test     forces   : 178164\nActual test set fraction    : 0.098771\n*******************************************************************************\n\n*** WRITE TRAINING/TEST SETS **************************************************\n\nWriting training/test set to files:\n - train.data\n - test.data\n*******************************************************************************\n\n*** WEIGHT INITIALIZATION *****************************************************\n\nInitial weights selected randomly in interval [-1.000000, 1.000000).\nWeights modified accoring to Glorot Bengio scheme.\nBiases set to zero.\n*******************************************************************************\n\n*** SETUP: TRAINING ***********************************************************\n\nForces will be used for training.\nForce update weight:   1.00E+01\nWeight update via Kalman filter selected: updaterType::UT_KALMANFILTER (1)\nMulti-stream Kalman filter training, update on rank 0, partial X calculation selected: ParallelMode::PM_MSEKFR0PX (4)\nNumber of streams       : 16\nStream of this processor: 0\nCombined updater for all elements selected: UpdateStrategy::US_COMBINED (0)\nNumber of weight updaters    : 1\nTotal fit parameters         : 2827\nSelection mode starting with epoch 0:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 1.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\n-------------------------------------------------------------------------------\nSymmetry function memory is reused (HIGH MEMORY USAGE!).\nTraining will be stopped after 25 epochs.\nEnergy comparison will be written every 25 epochs.\nForce comparison will be written every 25 epochs.\nWeights will be written every 1 epochs.\nNeuron statistics will be written every 5 epochs.\nUp to epoch 10 neuron statistics will be written every epoch.\nTraining log with update information will be written to: train-log.out.\n-------------------------------------------------------------------------------\nFraction of energies used per epoch:    1.0000\nFraction of forces used per epoch  :    0.0410\nProjected energy updates per epoch :     394 (  9.1%)\nProjected forces updates per epoch :    3953 ( 90.9%)\nTotal projected updates per epoch  :    4348\nMulti-stream training uses 16 energies/forces per weight update.\nqtau is divided by number of projected updates per epoch.\netatau is divided by number of projected updates per epoch.\n-------------------------------------------------------------------------------\nCombined weight updater:\n-------------------------------------------------------------------------------\nKalmanType::KT_STANDARD (0)\nsizeState       = 2827\nsizeObservation = 16\nepsilon         =   1.0000E-02\nq0              =   1.0000E-02\nqtau            =   5.2950E-04\nqmin            =   1.0000E-06\neta0            =   1.0000E-02\netatau          =   5.2950E-04\netamax          =   1.0000E+00\nKalmanParallel::KP_PRECALCX (2)\nOpenMP threads used: 1\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** CALCULATE NEIGHBOR LISTS **************************************************\n\nCalculating neighbor lists for all structures.\nCutoff radius for neighbor lists: 52.575524\n*******************************************************************************\n\n*** TRAINING LOOP *************************************************************\n\nThe training loop output covers different RMSEs, update and\ntiming information. The following quantities are organized\naccording to the matrix scheme below:\n-------------------------------------------------------------------\nep ............ Epoch.\nEtrain_phys ... RMSE of training energies per atom (p. u.).\nEtest_phys .... RMSE of test     energies per atom (p. u.).\nEtrain_int .... RMSE of training energies per atom (i. u.).\nEtest_int ..... RMSE of test     energies per atom (i. u.).\nFtrain_phys ... RMSE of training forces (p. u.).\nFtest_phys .... RMSE of test     forces (p. u.).\nFtrain_int .... RMSE of training forces (i. u.).\nFtest_int ..... RMSE of test     forces (i. u.).\nE_count ....... Number of energy updates.\nF_count ....... Number of force  updates.\ncount ......... Total number of updates.\nt_train ....... Time for training (seconds).\nt_rmse ........ Time for RMSE calculation (seconds).\nt_epoch ....... Total time for this epoch (seconds).\nt_tot ......... Total time for all epochs (seconds).\nAbbreviations:\n  p. u. = physical units.\n  i. u. = internal units.\nNote: RMSEs in internal units (columns 5 + 6) are only present \n      if data set normalization is used.\n-------------------------------------------------------------------\n     1    2             3             4             5             6\nenergy   ep   Etrain_phys    Etest_phys    Etrain_int     Etest_int\nforces   ep   Ftrain_phys    Ftest_phys    Ftrain_int     Ftest_int\nupdate   ep       E_count       F_count         count\ntiming   ep       t_train        t_rmse       t_epoch         t_tot\n-------------------------------------------------------------------\nENERGY    0   5.64501E-03   5.48381E-03   1.06149E+00   1.03118E+00\nFORCES    0   2.32665E-02   2.29954E-02   9.98572E-01   9.86934E-01\nTIMING    0          0.00         28.18         28.21         28.21\n------\nENERGY    1   1.81745E-04   1.78337E-04   3.41753E-02   3.35346E-02\nFORCES    1   1.15042E-03   9.21371E-04   4.93749E-02   3.95442E-02\nUPDATE    1           394          3959          4353\nTIMING    1        527.73          2.30        530.07        558.28\n------\nENERGY    2   1.17305E-04   1.13609E-04   2.20581E-02   2.13630E-02\nFORCES    2   1.11241E-03   8.53843E-04   4.77432E-02   3.66460E-02\nUPDATE    2           394          4020          4414\nTIMING    2        521.30          2.38        523.73       1082.01\n------\nENERGY    3   4.33433E-05   4.56327E-05   8.15029E-03   8.58077E-03\nFORCES    3   7.87140E-04   7.62600E-04   3.37832E-02   3.27299E-02\nUPDATE    3           394          3921          4315\nTIMING    3        511.69          2.35        514.09       1596.09\n------\nENERGY    4   3.36917E-05   3.37009E-05   6.33539E-03   6.33712E-03\nFORCES    4   7.60688E-04   7.34464E-04   3.26479E-02   3.15224E-02\nUPDATE    4           394          3935          4329\nTIMING    4        502.66          2.35        505.04       2101.13\n------\nENERGY    5   3.12427E-05   3.13005E-05   5.87487E-03   5.88575E-03\nFORCES    5   7.60011E-04   7.29289E-04   3.26188E-02   3.13002E-02\nUPDATE    5           394          3853          4247\nTIMING    5        490.49          2.38        492.90       2594.03\n------\nENERGY    6   2.87315E-05   2.77802E-05   5.40267E-03   5.22380E-03\nFORCES    6   7.55247E-04   7.18001E-04   3.24144E-02   3.08158E-02\nUPDATE    6           394          3896          4290\nTIMING    6        497.47          2.32        499.84       3093.87\n------\nENERGY    7   3.78098E-05   3.82099E-05   7.10975E-03   7.18499E-03\nFORCES    7   7.52107E-04   7.13936E-04   3.22796E-02   3.06413E-02\nUPDATE    7           394          3871          4265\nTIMING    7        493.62          2.35        496.00       3589.87\n------\nENERGY    8   3.16121E-05   3.11651E-05   5.94434E-03   5.86029E-03\nFORCES    8   7.53299E-04   7.15397E-04   3.23307E-02   3.07040E-02\nUPDATE    8           394          3883          4277\nTIMING    8        494.83          2.36        497.24       4087.12\n------\nENERGY    9   2.73431E-05   2.63597E-05   5.14160E-03   4.95668E-03\nFORCES    9   7.50612E-04   7.12022E-04   3.22154E-02   3.05592E-02\nUPDATE    9           394          3983          4377\nTIMING    9        505.46          2.35        507.85       4594.97\n------\nENERGY   10   3.05266E-05   2.97829E-05   5.74023E-03   5.60038E-03\nFORCES   10   7.52922E-04   7.17458E-04   3.23146E-02   3.07925E-02\nUPDATE   10           394          3982          4376\nTIMING   10        507.00          2.36        509.43       5104.40\n------\nENERGY   11   3.08249E-05   3.07024E-05   5.79632E-03   5.77329E-03\nFORCES   11   7.47610E-04   7.09773E-04   3.20866E-02   3.04627E-02\nUPDATE   11           394          3867          4261\nTIMING   11        494.56          2.35        496.94       5601.33\n------\nENERGY   12   3.65846E-05   3.49186E-05   6.87938E-03   6.56611E-03\nFORCES   12   7.43012E-04   7.07559E-04   3.18892E-02   3.03676E-02\nUPDATE   12           394          3908          4302\nTIMING   12        496.77          2.34        499.16       6100.49\n------\nENERGY   13   2.83711E-05   2.72325E-05   5.33491E-03   5.12079E-03\nFORCES   13   7.42542E-04   7.03252E-04   3.18690E-02   3.01828E-02\nUPDATE   13           394          3977          4371\nTIMING   13        505.82          2.39        508.24       6608.73\n------\nENERGY   14   2.89850E-05   2.79327E-05   5.45035E-03   5.25246E-03\nFORCES   14   7.18957E-04   7.07199E-04   3.08568E-02   3.03522E-02\nUPDATE   14           394          3955          4349\nTIMING   14        502.65          2.33        505.02       7113.75\n------\nENERGY   15   2.97534E-05   2.87138E-05   5.59483E-03   5.39935E-03\nFORCES   15   7.34201E-04   7.16606E-04   3.15111E-02   3.07559E-02\nUPDATE   15           394          4027          4421\nTIMING   15        513.12          2.38        515.53       7629.28\n------\nENERGY   16   3.22106E-05   3.10058E-05   6.05689E-03   5.83033E-03\nFORCES   16   7.37440E-04   7.19146E-04   3.16501E-02   3.08650E-02\nUPDATE   16           394          3888          4282\nTIMING   16        496.11          2.32        498.49       8127.77\n------\nENERGY   17   2.71166E-05   2.75032E-05   5.09902E-03   5.17171E-03\nFORCES   17   7.20358E-04   7.11365E-04   3.09169E-02   3.05310E-02\nUPDATE   17           394          3967          4361\nTIMING   17        505.50          2.34        507.87       8635.64\n------\nENERGY   18   2.81760E-05   2.72741E-05   5.29822E-03   5.12862E-03\nFORCES   18   7.12364E-04   7.01432E-04   3.05739E-02   3.01047E-02\nUPDATE   18           394          3967          4361\nTIMING   18        505.20          2.33        507.56       9143.20\n------\nENERGY   19   2.92210E-05   2.82683E-05   5.49472E-03   5.31558E-03\nFORCES   19   7.12816E-04   7.02165E-04   3.05933E-02   3.01361E-02\nUPDATE   19           394          3824          4218\nTIMING   19        485.44          2.32        487.79       9630.99\n------\nENERGY   20   2.87423E-05   2.75263E-05   5.40471E-03   5.17606E-03\nFORCES   20   7.14948E-04   7.00924E-04   3.06848E-02   3.00829E-02\nUPDATE   20           394          3978          4372\nTIMING   20        506.27          2.35        508.66      10139.65\n------\nENERGY   21   2.61834E-05   2.51414E-05   4.92352E-03   4.72759E-03\nFORCES   21   7.10730E-04   7.00339E-04   3.05037E-02   3.00578E-02\nUPDATE   21           394          3921          4315\nTIMING   21        498.96          2.34        501.33      10640.98\n------\nENERGY   22   2.82076E-05   2.70340E-05   5.30416E-03   5.08348E-03\nFORCES   22   7.07262E-04   6.96179E-04   3.03549E-02   2.98792E-02\nUPDATE   22           394          3927          4321\nTIMING   22        500.48          2.35        502.86      11143.84\n------\nENERGY   23   2.64148E-05   2.55147E-05   4.96703E-03   4.79779E-03\nFORCES   23   7.12998E-04   7.03658E-04   3.06011E-02   3.02002E-02\nUPDATE   23           394          3865          4259\nTIMING   23        493.12          2.36        495.54      11639.37\n------\nENERGY   24   2.67754E-05   2.57539E-05   5.03485E-03   4.84276E-03\nFORCES   24   7.12279E-04   7.01254E-04   3.05702E-02   3.00970E-02\nUPDATE   24           394          3935          4329\nTIMING   24        500.84          2.34        503.21      12142.58\n------\nENERGY   25   2.63136E-05   2.58564E-05   4.94801E-03   4.86204E-03\nFORCES   25   7.08677E-04   6.97313E-04   3.04156E-02   2.99279E-02\nUPDATE   25           394          3883          4277\nTIMING   25        495.81          4.53        500.37      12642.96\n*******************************************************************************\n"
  },
  {
    "path": "examples/potentials/H2O_BLYP/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0139920811417777E+00   9.4977580910223161E+00   2.2603947375875837E+00   7.2917921615978920E-01\n         1          2   6.8639888681304784E-01   4.9504853613627828E+00   1.3238211075580624E+00   3.6434689365904976E-01\n         1          3   7.1341916857589449E-01   7.0591216814523277E+00   1.6440474597147767E+00   5.4236777436756145E-01\n         1          4   5.3022482894128020E-01   3.7334888482543862E+00   1.0164037225981479E+00   2.7047255535792897E-01\n         1          5   3.8068389663107222E-01   4.1085315343122639E+00   9.1344601272927439E-01   3.1366034245622826E-01\n         1          6   3.6209352253798233E-01   2.2581437871512726E+00   6.5376753757281358E-01   1.5558515057408684E-01\n         1          7   1.8919103878435897E-01   2.2208902755745816E+00   4.6347173198472152E-01   1.6558095671706519E-01\n         1          8   2.6704178695764308E-01   1.3165499962653218E+00   4.3006152417867660E-01   8.2524577564005289E-02\n         1          9   2.3432552582413180E-01   9.4744522639629492E-01   3.6965740609827991E-01   5.3217971488250207E-02\n         1         10   2.2248910067848976E-01   2.7541033700513253E+00   5.5215780526487013E-01   2.0687626999491870E-01\n         1         11   1.3374237955415058E-01   5.6384631031683308E-01   2.7069878187908808E-01   2.6696058605315133E-02\n         1         12   1.2079214864210941E-01   1.7204357571854254E+00   3.0249171900250166E-01   1.1773155627500735E-01\n         1         13   4.8458872613975142E-02   3.5942380169808319E-01   1.8386453271773848E-01   2.0155336184978227E-02\n         1         14   2.7024966891331988E-02   9.0926173158416757E-01   1.4826162886702932E-01   5.2882935044636349E-02\n         1         15   2.4543106515324568E-03   2.8537946241644740E-01   7.4223588075560523E-02   1.8915314556467201E-02\n         1         16   2.2422507599479186E-04   3.1547402145398790E-01   4.1860830002911242E-02   2.1825843780429340E-02\n         1         17   2.1854219731237961E-04   1.3831176227811709E-01   1.9018235302043045E-02   9.6923971515768016E-03\n         1         18   4.4901398644641138E-03   5.7051242285921910E-01   2.4964676138172499E-02   3.8058259818075438E-02\n         1         19   2.7002790915257668E-04   2.1672023165088039E-01   1.8218200796318008E-02   1.3981346922046915E-02\n         1         20   5.1394921007966061E-02   1.6534022015443939E+00   1.5020874224913386E-01   1.1090825110094138E-01\n         1         21   3.4073471604482270E-03   3.1549770082510104E-01   1.8995158449171292E-02   2.0234498359001558E-02\n         1         22   1.3121382132811785E-04   1.0256295213721282E-01   6.8811414313411836E-03   6.6213295919552058E-03\n         1         23   3.4213548306919424E-02   9.0691679969751671E-01   8.4412203692533147E-02   5.8153501743683181E-02\n         1         24   4.1201879956648322E-04   1.5669952770939763E-01   4.9421419783389660E-03   9.8425761308934545E-03\n         1         25   8.6889007793241658E-04   5.9139541103707262E-02   3.7908389775993868E-03   3.2747112446898418E-03\n         1         26   8.7040247660959361E-03   1.9376799602864136E-01   2.4817287521716011E-02   1.0864140676357050E-02\n         1         27   1.6279340881271008E-04   9.8215755603321513E-03   1.9671395959884683E-03   5.5886688381775725E-04\n         2          1   1.4434251644234051E+00   9.8852032214270888E+00   2.6476422151161225E+00   7.2733611282140742E-01\n         2          2   3.8469125433437429E-01   4.5675215892628467E+00   9.6237285318012755E-01   3.6163011396961459E-01\n         2          3   1.1626875062562141E+00   7.4474515009798354E+00   2.0328074451962936E+00   5.3924172771802847E-01\n         2          4   2.4544442341825734E-01   3.3538165775552784E+00   6.5956400271727467E-01   2.6643206569702149E-01\n         2          5   8.2185539958507070E-01   4.4967534692006161E+00   1.3075350751456283E+00   3.0877185488949693E-01\n         2          6   9.3831855817988905E-02   1.8807875512399708E+00   3.1156069171380063E-01   1.4873342201745832E-01\n         2          7   5.6949141690859717E-01   2.6055246326610249E+00   8.6012304835735376E-01   1.6131223998750543E-01\n         2          8   2.2912282514974191E-02   9.3743651884038204E-01   1.1654780379239377E-01   7.1678408993491011E-02\n         2          9   5.1802225563760551E-01   1.8578962133017354E+00   7.3931481219655926E-01   9.8654485822510019E-02\n         2         10   1.1030204988383335E-01   2.8912420471413585E+00   4.8849657684007453E-01   2.4463147994064272E-01\n         2         11   3.6148389791073926E-01   1.0810856874313730E+00   5.4139756375817627E-01   4.6101468386091610E-02\n         2         12   2.8337474251498265E-02   2.5147758585456526E+00   3.3964122119934642E-01   2.1619193868418723E-01\n         2         13   1.4352871952342247E-01   6.5503429041515959E-01   3.6772906543547762E-01   3.1517609332029878E-02\n         2         14   2.1788022334140573E-03   2.2905999993694444E+00   2.0139532391348280E-01   1.8915788338443079E-01\n         2         15   7.2421508479313512E-03   4.1980710681015926E-01   1.4844717615112094E-01   2.7811187931855667E-02\n         2         16   1.3956056202249898E-06   2.0180356614099630E+00   6.5342136725642444E-02   1.4287305968641703E-01\n         2         17   2.3287495045603364E-03   3.4319227826170262E-01   1.7551983209942983E-02   2.1924428510969138E-02\n         2         18   2.0739240662834366E-05   5.6568536355828418E-02   1.0700369320778326E-03   3.3111564867629351E-03\n         2         19   4.7750201291023343E-02   2.9504748026822152E+00   2.1009867916772967E-01   2.0427300874224696E-01\n         2         20   1.0305478833859403E-03   4.8594103803931116E-01   1.3292176987042218E-02   3.1957125525737824E-02\n         2         21   8.3254800586476871E-03   2.6943765261840680E-01   3.2239304730842452E-02   1.7014664077306434E-02\n         2         22   1.4327655039840001E-02   1.3871282089845993E+00   7.8601396584900854E-02   9.3943754383554540E-02\n         2         23   1.9759831791959868E-02   4.1063243161904089E-01   5.1049776649751279E-02   2.5482669251984523E-02\n         2         24   6.2800954285628337E-04   2.3505014002218594E-01   7.6849258089972819E-03   1.4430358808519245E-02\n         2         25   3.6565666316001445E-06   3.5430179480123003E-02   4.4591255295562061E-04   2.0163156897533333E-03\n         2         26   1.7014371172551671E-02   8.1334396068685844E-01   5.2357585491953053E-02   5.3157901970668157E-02\n         2         27   4.5259074808881496E-03   7.7679046586486111E-01   3.9608207829723338E-02   5.0520632412756790E-02\n         2         28   1.7574896842165177E-05   9.7757167085459881E-02   1.2660184900086847E-03   5.7177479736320756E-03\n         2         29   5.8469236684166098E-03   1.0205551990696606E-01   1.6728641743617885E-02   5.5063250273753549E-03\n         2         30   3.4729465399378763E-03   1.5400706357418056E-01   1.1879484755697552E-02   8.8441587523401827E-03\n"
  },
  {
    "path": "examples/potentials/H2O_BLYP/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -1.5291125647377135E+00 a         1     0     1     1     1\n  4.8941164600852849E+00 a         2     0     1     1     2\n -1.6469277518153746E+01 a         3     0     1     1     3\n  9.3464593610670370E+00 a         4     0     1     1     4\n -9.1766990158742079E+00 a         5     0     1     1     5\n -7.4138470381520953E+00 a         6     0     1     1     6\n  9.4372339261784632E-01 a         7     0     1     1     7\n  8.5526346644631381E+00 a         8     0     1     1     8\n  2.4843297941317153E+00 a         9     0     1     1     9\n  9.2051940446694114E-01 a        10     0     1     1    10\n  2.5950406367783190E+00 a        11     0     1     1    11\n  5.8577596799733218E+00 a        12     0     1     1    12\n  3.1009420794845419E+00 a        13     0     1     1    13\n -8.9791935296470342E+00 a        14     0     1     1    14\n -8.1751091176467146E+00 a        15     0     1     1    15\n -1.2619434052408995E+01 a        16     0     1     1    16\n -2.0717905810964456E+01 a        17     0     1     1    17\n -4.5863690679420133E+00 a        18     0     1     1    18\n  1.2729334422050142E+01 a        19     0     1     1    19\n  1.3756988839635900E+01 a        20     0     1     1    20\n  1.0727727778278526E+01 a        21     0     1     1    21\n  1.4204001623378012E+01 a        22     0     1     1    22\n  3.8516365427557107E+00 a        23     0     1     1    23\n  2.2773193332610373E+00 a        24     0     1     1    24\n  8.1032865253873236E+00 a        25     0     1     1    25\n  2.8416128403455621E+00 a        26     0     2     1     1\n  2.7517566180611825E+00 a        27     0     2     1     2\n  2.2140744553823630E+00 a        28     0     2     1     3\n -1.3745935938357789E+00 a        29     0     2     1     4\n  5.2246992458665416E+00 a        30     0     2     1     5\n  9.4791657865247725E+00 a        31     0     2     1     6\n  1.5523740885540910E-01 a        32     0     2     1     7\n -9.2405133690500225E+00 a        33     0     2     1     8\n -9.8757519660631079E+00 a        34     0     2     1     9\n  9.0790561831707806E-02 a        35     0     2     1    10\n -5.6399363562884837E+00 a        36     0     2     1    11\n  4.0991367982650813E+00 a        37     0     2     1    12\n -2.2824268140662554E+01 a        38     0     2     1    13\n  1.2108080338939310E+01 a        39     0     2     1    14\n  1.3482349498994678E+01 a        40     0     2     1    15\n  7.6391741299165554E+00 a        41     0     2     1    16\n  1.3508197164083491E+01 a        42     0     2     1    17\n  5.6693857166351478E+00 a        43     0     2     1    18\n -1.7535047188442874E+01 a        44     0     2     1    19\n -1.1526524532008924E+01 a        45     0     2     1    20\n -1.2397725073717010E+00 a        46     0     2     1    21\n -2.1789900574242743E+01 a        47     0     2     1    22\n  6.6603941660333881E+00 a        48     0     2     1    23\n  8.6913560716304410E+00 a        49     0     2     1    24\n -1.3169815880547517E+01 a        50     0     2     1    25\n -2.1293094665492185E+00 a        51     0     3     1     1\n -4.3535914299560270E+00 a        52     0     3     1     2\n  2.2512315123027285E+01 a        53     0     3     1     3\n -2.2015110854969091E+01 a        54     0     3     1     4\n  8.9635117687491395E+00 a        55     0     3     1     5\n  8.0699752599519350E+00 a        56     0     3     1     6\n  2.4268177618207241E+00 a        57     0     3     1     7\n -4.4462063091756168E+00 a        58     0     3     1     8\n -2.0794088859281387E-01 a        59     0     3     1     9\n  1.0532710811564059E+00 a        60     0     3     1    10\n -9.7190030919083288E+00 a        61     0     3     1    11\n -1.5674891463874149E+01 a        62     0     3     1    12\n  4.2902789397156853E-02 a        63     0     3     1    13\n  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-1.3491244842429613E+00 a      1125     1    17     2    25\n -1.0002081735332582E+00 a      1126     1    18     2     1\n  2.8874400554799196E-01 a      1127     1    18     2     2\n  1.4154408019397398E+00 a      1128     1    18     2     3\n -1.1030468517624148E+00 a      1129     1    18     2     4\n -7.8591403045834918E-01 a      1130     1    18     2     5\n -3.3121055220825579E-01 a      1131     1    18     2     6\n -1.0712676193221522E+00 a      1132     1    18     2     7\n  5.0691598659616677E-01 a      1133     1    18     2     8\n  6.9989931890287227E-01 a      1134     1    18     2     9\n  1.2701066463343078E+00 a      1135     1    18     2    10\n  5.7323332234760107E+00 a      1136     1    18     2    11\n -1.2205760234064544E+00 a      1137     1    18     2    12\n  2.8581963717542436E-01 a      1138     1    18     2    13\n -1.7152062802745360E-01 a      1139     1    18     2    14\n  6.3013399337299214E-01 a      1140     1    18     2    15\n  1.6032810237900064E+00 a      1141     1    18     2    16\n -1.8647290360209326E-01 a      1142     1    18     2    17\n -1.7552280630471995E+00 a      1143     1    18     2    18\n -1.6951526452572885E-01 a      1144     1    18     2    19\n -4.4310576767783283E-01 a      1145     1    18     2    20\n  5.7194777698718280E-01 a      1146     1    18     2    21\n -6.7964545250772068E-01 a      1147     1    18     2    22\n  1.1504718311537716E+00 a      1148     1    18     2    23\n  1.8257036893647574E-01 a      1149     1    18     2    24\n  1.4326883808776378E+00 a      1150     1    18     2    25\n  1.0095242455639231E+00 a      1151     1    19     2     1\n -3.5498084342300873E-01 a      1152     1    19     2     2\n -7.9428413334335826E-02 a      1153     1    19     2     3\n  4.1898410754671311E-01 a      1154     1    19     2     4\n  5.7708594136156965E-01 a      1155     1    19     2     5\n  3.4219888511005964E-02 a      1156     1    19     2     6\n  2.0188343094068171E-02 a      1157     1    19     2     7\n  3.7065388886596445E-01 a      1158     1    19     2     8\n  4.0493838279888189E-01 a      1159     1    19     2     9\n -8.7880396095680291E-01 a      1160     1    19     2    10\n -4.2964998195714266E+00 a      1161     1    19     2    11\n -4.8622128295651041E+00 a      1162     1    19     2    12\n -3.2205422261123601E-01 a      1163     1    19     2    13\n  1.0584833349789229E+00 a      1164     1    19     2    14\n -1.4768523757998540E+00 a      1165     1    19     2    15\n -8.2507826636001494E-02 a      1166     1    19     2    16\n  1.9285629582200401E+00 a      1167     1    19     2    17\n  7.8377063604115649E-01 a      1168     1    19     2    18\n  8.6133987821315805E-01 a      1169     1    19     2    19\n  7.9592312938402732E-01 a      1170     1    19     2    20\n -2.5571084159158464E-01 a      1171     1    19     2    21\n  6.2094886044249265E-01 a      1172     1    19     2    22\n  5.3204351131503980E-01 a      1173     1    19     2    23\n -3.5617867451003005E-01 a      1174     1    19     2    24\n -2.0865883598876050E-01 a      1175     1    19     2    25\n  5.6090217480110005E-01 a      1176     1    20     2     1\n -3.7236626036363962E-01 a      1177     1    20     2     2\n -7.5321160552803912E-01 a      1178     1    20     2     3\n -1.4300947825026233E+00 a      1179     1    20     2     4\n  4.4733116304615095E-01 a      1180     1    20     2     5\n  5.9791755069591515E-02 a      1181     1    20     2     6\n -8.2957708933977192E-01 a      1182     1    20     2     7\n  9.8699818003222917E-01 a      1183     1    20     2     8\n  7.3205249269496386E-01 a      1184     1    20     2     9\n -9.9725723754597517E-01 a      1185     1    20     2    10\n -8.2488628446232382E-01 a      1186     1    20     2    11\n  4.5610095255288158E-01 a      1187     1    20     2    12\n -1.7628107924627607E+00 a      1188     1    20     2    13\n -8.2186542845300609E-02 a      1189     1    20     2    14\n -3.6055995965540927E-01 a      1190     1    20     2    15\n -1.4535148754483196E+00 a      1191     1    20     2    16\n  1.9834827817089609E+00 a      1192     1    20     2    17\n  1.5590759923945524E-01 a      1193     1    20     2    18\n -1.8089019492132679E+00 a      1194     1    20     2    19\n -2.0320064387925313E-01 a      1195     1    20     2    20\n -6.5704555123077657E-01 a      1196     1    20     2    21\n  2.5903822688616551E-01 a      1197     1    20     2    22\n -1.0926766728373481E-01 a      1198     1    20     2    23\n -2.4387082164113663E-01 a      1199     1    20     2    24\n  1.8310568350376563E-01 a      1200     1    20     2    25\n -1.1443383178869819E+00 a      1201     1    21     2     1\n -4.8240031881640466E-01 a      1202     1    21     2     2\n -1.6025078168765597E-01 a      1203     1    21     2     3\n  4.6860285112985678E-01 a      1204     1    21     2     4\n -1.4943224734368399E+00 a      1205     1    21     2     5\n  6.0310645125947115E-01 a      1206     1    21     2     6\n  1.5342424590210779E+00 a      1207     1    21     2     7\n -9.1876841319494015E-02 a      1208     1    21     2     8\n -1.0723209686020214E+00 a      1209     1    21     2     9\n -3.1633937830955072E-01 a      1210     1    21     2    10\n -9.5799913987291610E-02 a      1211     1    21     2    11\n -2.4276918623217019E+00 a      1212     1    21     2    12\n -8.9031087169682444E-01 a      1213     1    21     2    13\n  4.1976311882324452E-01 a      1214     1    21     2    14\n  7.4176975569635295E-01 a      1215     1    21     2    15\n -2.4366032697083659E-01 a      1216     1    21     2    16\n -1.6720736967996235E+00 a      1217     1    21     2    17\n  6.1068748732900469E-02 a      1218     1    21     2    18\n  1.9512673698321090E+00 a      1219     1    21     2    19\n  6.2495016793255109E-01 a      1220     1    21     2    20\n -3.7646606875967575E-01 a      1221     1    21     2    21\n  7.4097922589831255E-01 a      1222     1    21     2    22\n -3.5112553870551799E-01 a      1223     1    21     2    23\n  6.4324641005764716E-01 a      1224     1    21     2    24\n  1.3386547726530193E-01 a      1225     1    21     2    25\n  1.0285452332062215E+00 a      1226     1    22     2     1\n  2.4434658677842605E-01 a      1227     1    22     2     2\n -9.6585182096114375E-01 a      1228     1    22     2     3\n  2.6806483614131288E-01 a      1229     1    22     2     4\n  3.8615386441793476E-01 a      1230     1    22     2     5\n  9.3970405934937040E-01 a      1231     1    22     2     6\n  4.5241367422967926E-01 a      1232     1    22     2     7\n  4.8536764991199000E-01 a      1233     1    22     2     8\n -6.2997571649537754E-01 a      1234     1    22     2     9\n -7.9936040474389480E-01 a      1235     1    22     2    10\n  8.1401534272780207E-01 a      1236     1    22     2    11\n  3.1280108687641361E-01 a      1237     1    22     2    12\n  2.6904590239033954E-01 a      1238     1    22     2    13\n -5.1144640856624757E-01 a      1239     1    22     2    14\n  6.7811492892143699E-01 a      1240     1    22     2    15\n  5.7108139585521922E-01 a      1241     1    22     2    16\n  1.1080703120399862E+00 a      1242     1    22     2    17\n  4.7670726832084065E-01 a      1243     1    22     2    18\n -4.5995519499609921E-01 a      1244     1    22     2    19\n -3.1782137707150487E-01 a      1245     1    22     2    20\n -3.3906554048771365E-01 a      1246     1    22     2    21\n -8.7969853712123491E-01 a      1247     1    22     2    22\n  2.2638773193566211E+00 a      1248     1    22     2    23\n -2.5836296258896285E-01 a      1249     1    22     2    24\n -8.1919752591959161E-01 a      1250     1    22     2    25\n -2.7014773844118425E+00 a      1251     1    23     2     1\n -7.1441002220235006E-01 a      1252     1    23     2     2\n -6.5036485079876993E-01 a      1253     1    23     2     3\n  7.1704403318494092E-01 a      1254     1    23     2     4\n  6.6326996093337454E-01 a      1255     1    23     2     5\n -4.0831021230041973E+00 a      1256     1    23     2     6\n -2.8684862549287655E+00 a      1257     1    23     2     7\n -7.2811828379705235E+00 a      1258     1    23     2     8\n -3.4833949995675884E+00 a      1259     1    23     2     9\n  5.6782119119186542E-02 a      1260     1    23     2    10\n -2.9482764928488443E+00 a      1261     1    23     2    11\n  6.5422977385931214E+00 a      1262     1    23     2    12\n  2.5342339602002040E-01 a      1263     1    23     2    13\n -4.5200246119372553E-02 a      1264     1    23     2    14\n  1.4304255659968039E+00 a      1265     1    23     2    15\n  1.3106496800862921E+00 a      1266     1    23     2    16\n -9.4988955758206439E-01 a      1267     1    23     2    17\n  5.0834093134680391E-01 a      1268     1    23     2    18\n -1.3936575354105005E+00 a      1269     1    23     2    19\n  8.7259901855077782E-01 a      1270     1    23     2    20\n -7.1579191946859666E-01 a      1271     1    23     2    21\n  6.7457806942142673E-01 a      1272     1    23     2    22\n -1.4469880866415772E+00 a      1273     1    23     2    23\n  5.4276508028551884E-01 a      1274     1    23     2    24\n  2.1582470198017671E+00 a      1275     1    23     2    25\n  2.8287775908733287E-01 a      1276     1    24     2     1\n -1.6704216601267869E+00 a      1277     1    24     2     2\n -1.9838503924852646E+00 a      1278     1    24     2     3\n  5.6723544039823492E-01 a      1279     1    24     2     4\n  2.8400578570174539E-01 a      1280     1    24     2     5\n  3.4744069274607328E+00 a      1281     1    24     2     6\n  7.8530295085587662E-02 a      1282     1    24     2     7\n  2.0792120025714032E+00 a      1283     1    24     2     8\n -3.5606074893224426E-01 a      1284     1    24     2     9\n -1.1122499039108911E+00 a      1285     1    24     2    10\n -8.4743164415355707E+00 a      1286     1    24     2    11\n -1.6299559460752531E+00 a      1287     1    24     2    12\n -5.5606401322839305E-01 a      1288     1    24     2    13\n  8.2966102067866276E-01 a      1289     1    24     2    14\n  9.8113447050164726E-01 a      1290     1    24     2    15\n -1.4170171193881071E+00 a      1291     1    24     2    16\n  1.0858854247471748E+00 a      1292     1    24     2    17\n  1.1271748129454626E+00 a      1293     1    24     2    18\n -3.8198288307381180E-02 a      1294     1    24     2    19\n -1.3223062528347609E-01 a      1295     1    24     2    20\n -2.1577871364654571E+00 a      1296     1    24     2    21\n -1.5769618283183986E+00 a      1297     1    24     2    22\n -3.0781877544146194E+00 a      1298     1    24     2    23\n -4.0850391768263439E-01 a      1299     1    24     2    24\n -5.8453687119858682E+00 a      1300     1    24     2    25\n  3.9816952277708484E-01 a      1301     1    25     2     1\n  1.1656391468336913E+00 a      1302     1    25     2     2\n  1.4923207516303356E+00 a      1303     1    25     2     3\n  6.8546428472474319E-01 a      1304     1    25     2     4\n -1.2018290790523090E+00 a      1305     1    25     2     5\n -7.3887071893846357E-01 a      1306     1    25     2     6\n  2.4086894160842498E-01 a      1307     1    25     2     7\n  2.2314977175886459E+00 a      1308     1    25     2     8\n -4.9317511194113461E-01 a      1309     1    25     2     9\n  5.1774269531307637E-01 a      1310     1    25     2    10\n  3.0831501653420368E+00 a      1311     1    25     2    11\n  9.8513850324030960E-01 a      1312     1    25     2    12\n -6.8115031076679322E-01 a      1313     1    25     2    13\n -1.1334077077421534E-02 a      1314     1    25     2    14\n  1.6103394399138287E+00 a      1315     1    25     2    15\n  6.5207098932143981E-01 a      1316     1    25     2    16\n -1.8192436739280649E-01 a      1317     1    25     2    17\n -7.9141679410261589E-01 a      1318     1    25     2    18\n -3.6584193301853174E-01 a      1319     1    25     2    19\n  5.5049201064094111E-01 a      1320     1    25     2    20\n -4.3362861886952719E-01 a      1321     1    25     2    21\n -2.1861922748081430E-01 a      1322     1    25     2    22\n  7.5853857293977867E-01 a      1323     1    25     2    23\n  5.4291221548244262E-01 a      1324     1    25     2    24\n  3.6561633682078098E-01 a      1325     1    25     2    25\n -4.0396728803408957E+00 b      1326     2     1\n  2.6343382465495226E+00 b      1327     2     2\n  2.2004917393474663E+00 b      1328     2     3\n -4.0972446791290871E+00 b      1329     2     4\n -1.7874175341790259E+00 b      1330     2     5\n -3.3525872795516842E-01 b      1331     2     6\n  1.4203207877473889E+00 b      1332     2     7\n  4.2081004453336099E+00 b      1333     2     8\n  4.0361490782145104E+00 b      1334     2     9\n -4.2977579408198858E+00 b      1335     2    10\n  8.2115738927880066E+00 b      1336     2    11\n  9.6833615154896009E+00 b      1337     2    12\n -3.8769073103950631E+00 b      1338     2    13\n -4.8294039065683342E-01 b      1339     2    14\n -5.2291425555689597E-01 b      1340     2    15\n -1.6877051122041389E+00 b      1341     2    16\n -3.4179794380380532E-02 b      1342     2    17\n -1.9962658102768114E+00 b      1343     2    18\n -2.5597431454969457E+00 b      1344     2    19\n -1.5109756638135570E+00 b      1345     2    20\n -6.3197184617712265E-01 b      1346     2    21\n -3.6805826525608869E+00 b      1347     2    22\n  3.3216344767691788E+00 b      1348     2    23\n -3.8817768483696309E+00 b      1349     2    24\n -4.9398994006048476E+00 b      1350     2    25\n -1.3858564841975924E+00 a      1351     2     1     3     1\n  1.3814083067655392E+00 a      1352     2     2     3     1\n -5.1946438339891154E-01 a      1353     2     3     3     1\n -1.3875503954089745E+00 a      1354     2     4     3     1\n -1.5317255631575561E+00 a      1355     2     5     3     1\n -1.0456495633347411E+00 a      1356     2     6     3     1\n -7.7201734796426036E-01 a      1357     2     7     3     1\n  4.1167891312221236E+00 a      1358     2     8     3     1\n  9.8434446339603243E-01 a      1359     2     9     3     1\n -9.9525894437711293E-01 a      1360     2    10     3     1\n  1.0013888508395108E-01 a      1361     2    11     3     1\n  2.1664425342990312E+00 a      1362     2    12     3     1\n -5.0675361856134780E+00 a      1363     2    13     3     1\n -1.2830087745571082E+00 a      1364     2    14     3     1\n  1.3955578297628246E+00 a      1365     2    15     3     1\n -1.3797184261989368E+00 a      1366     2    16     3     1\n  7.6413855696777355E-01 a      1367     2    17     3     1\n -2.0673807232977750E+00 a      1368     2    18     3     1\n -3.7942050094667299E+00 a      1369     2    19     3     1\n  9.9671409667826649E-01 a      1370     2    20     3     1\n -8.6861298476234827E-01 a      1371     2    21     3     1\n -1.9382885369487628E+00 a      1372     2    22     3     1\n  1.5836200651834991E+00 a      1373     2    23     3     1\n -6.3466789099515086E+00 a      1374     2    24     3     1\n -1.0471914942937510E+00 a      1375     2    25     3     1\n  1.1916165890588871E+01 b      1376     3     1\n"
  },
  {
    "path": "examples/potentials/H2O_BLYP/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.9442574313162528E-01 a         1     0     1     1     1\n -1.7117015148757753E+00 a         2     0     1     1     2\n -6.2994909353826856E+00 a         3     0     1     1     3\n  1.1627499433425228E+01 a         4     0     1     1     4\n -6.0219169637828420E+00 a         5     0     1     1     5\n -2.9223097250964734E+00 a         6     0     1     1     6\n  1.1702548523541207E+01 a         7     0     1     1     7\n -3.3114536763717579E+00 a         8     0     1     1     8\n -5.0711292392231639E+00 a         9     0     1     1     9\n  3.4429945526141261E+00 a        10     0     1     1    10\n  1.6718625920290851E+01 a        11     0     1     1    11\n  9.7363080135101754E-01 a        12     0     1     1    12\n  8.2993838599779546E-01 a        13     0     1     1    13\n  2.4900895467502608E+00 a        14     0     1     1    14\n  3.2680344169676723E-01 a        15     0     1     1    15\n -5.5066104008259060E+00 a        16     0     1     1    16\n -4.4481864397096382E+00 a        17     0     1     1    17\n  2.5653733215502430E+00 a        18     0     1     1    18\n  1.5826241018506206E+01 a        19     0     1     1    19\n -1.1217024562117681E+01 a        20     0     1     1    20\n -9.7815453171201998E+00 a        21     0     1     1    21\n  1.1852021936516874E+00 a        22     0     1     1    22\n  1.1921403232929260E+01 a        23     0     1     1    23\n  8.9046315642032692E+00 a        24     0     1     1    24\n  2.5840701626710079E+00 a        25     0     1     1    25\n -2.9868463405583594E+01 a        26     0     2     1     1\n  3.2913264409866763E+00 a        27     0     2     1     2\n -5.2588058407721636E+00 a        28     0     2     1     3\n -1.1208964560609063E+01 a        29     0     2     1     4\n  9.7379059423090037E+00 a        30     0     2     1     5\n -4.9659425953500769E+00 a        31     0     2     1     6\n -1.7267862502605237E+01 a        32     0     2     1     7\n -1.5410787530782722E+01 a        33     0     2     1     8\n  3.8461293613159326E+00 a        34     0     2     1     9\n  2.7740389628829334E+00 a        35     0     2     1    10\n -1.4099386838734130E+01 a        36     0     2     1    11\n -8.2401268623938406E-01 a        37     0     2     1    12\n -3.1237366192656717E+00 a        38     0     2     1    13\n -9.1323684221985104E+00 a        39     0     2     1    14\n -8.5412447633582875E+00 a        40     0     2     1    15\n  4.9379427089451751E+00 a        41     0     2     1    16\n  4.7761380020152142E+00 a        42     0     2     1    17\n -1.0884630161294250E+01 a        43     0     2     1    18\n  7.3595288421646563E+00 a        44     0     2     1    19\n -1.7290406607417498E+01 a        45     0     2     1    20\n  1.0432307361265176E+00 a        46     0     2     1    21\n -1.8769446744669867E+01 a        47     0     2     1    22\n 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-1.1262219375438566E-01 a      1365     1    24     2    15\n -3.1582693484295554E-01 a      1366     1    24     2    16\n  4.0100361950481962E-03 a      1367     1    24     2    17\n -1.4218849049567435E+00 a      1368     1    24     2    18\n  2.5644785070058679E-01 a      1369     1    24     2    19\n  2.9038239914755015E-01 a      1370     1    24     2    20\n -1.7744007965188949E-01 a      1371     1    24     2    21\n  3.2838898759142382E-01 a      1372     1    24     2    22\n  1.2521209680875831E+00 a      1373     1    24     2    23\n  1.1193370196367683E-01 a      1374     1    24     2    24\n  4.9934217467646452E-01 a      1375     1    24     2    25\n  2.4945454634534542E-01 a      1376     1    25     2     1\n -2.4360422519694352E-01 a      1377     1    25     2     2\n  1.3596260270669551E+00 a      1378     1    25     2     3\n  2.5526752958183323E+00 a      1379     1    25     2     4\n  7.7988411832119386E-01 a      1380     1    25     2     5\n -1.1249827847801064E+00 a      1381     1    25     2     6\n  4.1611687080031282E-02 a      1382     1    25     2     7\n -1.1273335561554958E+00 a      1383     1    25     2     8\n -4.3224419711878109E-01 a      1384     1    25     2     9\n  4.2782608288272783E-01 a      1385     1    25     2    10\n -9.7981361059106054E-01 a      1386     1    25     2    11\n  2.1023321625700742E-01 a      1387     1    25     2    12\n  5.2811546411998411E-01 a      1388     1    25     2    13\n -9.2430032591177713E-02 a      1389     1    25     2    14\n -4.9504777123728999E-01 a      1390     1    25     2    15\n -7.5280337007178266E-01 a      1391     1    25     2    16\n  2.0938148852138551E-02 a      1392     1    25     2    17\n  1.4588693359734921E+00 a      1393     1    25     2    18\n  3.1110547730065847E-02 a      1394     1    25     2    19\n  3.7810797917672284E-01 a      1395     1    25     2    20\n  5.7458253916760878E-03 a      1396     1    25     2    21\n -6.7584464301040059E-01 a      1397     1    25     2    22\n -7.1252042314383202E-01 a      1398     1    25     2    23\n -7.6470216017457360E-01 a      1399     1    25     2    24\n -1.5740348067896169E-02 a      1400     1    25     2    25\n -1.2954255697362553E+00 b      1401     2     1\n  2.4644717533752001E+00 b      1402     2     2\n -1.1415802744768326E+00 b      1403     2     3\n -2.8938885668753183E+00 b      1404     2     4\n  1.2839285155271736E+00 b      1405     2     5\n  2.1083211522389185E+00 b      1406     2     6\n -4.2825165337386836E-03 b      1407     2     7\n  8.5030042954199547E-01 b      1408     2     8\n -5.4765764357561784E+00 b      1409     2     9\n -1.8933572304353372E+00 b      1410     2    10\n -4.4211796909606882E+00 b      1411     2    11\n -2.7021723582324118E+00 b      1412     2    12\n -1.2622277306250835E+00 b      1413     2    13\n  2.3834607308938081E+00 b      1414     2    14\n  1.5656892864881724E+00 b      1415     2    15\n  1.7218755356741144E+00 b      1416     2    16\n -1.8598776624290176E+00 b      1417     2    17\n -1.4704026291792496E-01 b      1418     2    18\n  4.4769917039777223E+00 b      1419     2    19\n  1.9087284583063613E+00 b      1420     2    20\n  1.0425849398482315E-01 b      1421     2    21\n -3.8694704901059718E-01 b      1422     2    22\n -2.0011462884316207E+00 b      1423     2    23\n  3.2270378854078503E+00 b      1424     2    24\n  9.2006703755566233E-01 b      1425     2    25\n -1.4516422204273129E+00 a      1426     2     1     3     1\n -4.9306948525926858E-01 a      1427     2     2     3     1\n  2.8447514429482779E-01 a      1428     2     3     3     1\n -2.6982315523932010E-01 a      1429     2     4     3     1\n -1.6783914109884221E+00 a      1430     2     5     3     1\n  1.3496182204192317E+00 a      1431     2     6     3     1\n -4.0533286517218470E-01 a      1432     2     7     3     1\n  3.6460671322804217E-01 a      1433     2     8     3     1\n  1.4961419597870886E+00 a      1434     2     9     3     1\n -2.5521243957287272E+00 a      1435     2    10     3     1\n  6.3391408484442779E-01 a      1436     2    11     3     1\n  2.4317832405061535E+00 a      1437     2    12     3     1\n  1.8820633321879099E+00 a      1438     2    13     3     1\n -1.2756493427946596E+00 a      1439     2    14     3     1\n  2.9643721236427862E+00 a      1440     2    15     3     1\n  3.1131125310299739E+00 a      1441     2    16     3     1\n -1.7573409438803484E+00 a      1442     2    17     3     1\n -1.4924282697044071E+00 a      1443     2    18     3     1\n  1.2462595546192918E+00 a      1444     2    19     3     1\n -1.4506155638143481E+00 a      1445     2    20     3     1\n -3.0927203659829448E+00 a      1446     2    21     3     1\n  1.7719400948030060E+00 a      1447     2    22     3     1\n  1.0622947744308620E+00 a      1448     2    23     3     1\n  1.7209450679172542E+00 a      1449     2    24     3     1\n  1.8101203415419616E+00 a      1450     2    25     3     1\n  5.9580829451113164E+00 b      1451     3     1\n"
  },
  {
    "path": "examples/potentials/H2O_BLYP-D3/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: BLYP-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   4              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 4\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               25             # Write energy comparison.\nwrite_trainforces               25             # Write force comparison.\nwrite_weights_epoch                            # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/potentials/H2O_BLYP-D3/nnp-train.log.0000",
    "content": "\n*** SETUP: MPI ****************************************************************\n\nNumber of processors: 16\nProcess 1 of 16 (rank 0): n01-046\nProcess 2 of 16 (rank 1): n01-046\nProcess 3 of 16 (rank 2): n01-046\nProcess 4 of 16 (rank 3): n01-046\nProcess 5 of 16 (rank 4): n01-046\nProcess 6 of 16 (rank 5): n01-046\nProcess 7 of 16 (rank 6): n01-046\nProcess 8 of 16 (rank 7): n01-046\nProcess 9 of 16 (rank 8): n01-046\nProcess 10 of 16 (rank 9): n01-046\nProcess 11 of 16 (rank 10): n01-046\nProcess 12 of 16 (rank 11): n01-046\nProcess 13 of 16 (rank 12): n01-046\nProcess 14 of 16 (rank 13): n01-046\nProcess 15 of 16 (rank 14): n01-046\nProcess 16 of 16 (rank 15): n01-046\n*******************************************************************************\n\n*******************************************************************************\n\n   NNP LIBRARY v0.1.0\n   ------------------\n\nGit branch  : master\nGit revision: d2f83cd (d2f83cde386d59595aea395bfe3755dccebc195a)\n\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 167 lines.\nFound 102 lines with keywords.\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is used.\nMean energy per atom     :  -2.5521343547039809E+01\nConversion factor energy :   2.4265748255366972E+02\nConversion factor length :   5.8038448995319847E+00\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  H (  1)\nElement  1:  O (  8)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:   0.00000000E+00\nElement  1:   0.00000000E+00\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_TANHU (2)\nf(r) = tanh^3(1 - r/rc)\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  H  2  H    2.969E-05 0.000E+00         6.965E+01  2 0.00    98\n   2  H  2  O    2.969E-05 0.000E+00         6.965E+01  2 0.00   108\n   3  H  2  H    2.969E-04 0.000E+00         6.965E+01  2 0.00    99\n   4  H  2  O    2.969E-04 0.000E+00         6.965E+01  2 0.00   109\n   5  H  2  H    8.906E-04 0.000E+00         6.965E+01  2 0.00   100\n   6  H  2  O    8.906E-04 0.000E+00         6.965E+01  2 0.00   110\n   7  H  2  H    1.781E-03 0.000E+00         6.965E+01  2 0.00   101\n   8  H  2  O    1.781E-03 0.000E+00         6.965E+01  2 0.00   111\n   9  H  2  O    4.453E-03 5.223E+00         6.965E+01  2 0.00   112\n  10  H  2  H    4.453E-03 1.103E+01         6.965E+01  2 0.00   102\n  11  H  2  O    8.906E-03 5.223E+00         6.965E+01  2 0.00   113\n  12  H  2  H    8.906E-03 1.103E+01         6.965E+01  2 0.00   103\n  13  H  2  O    1.781E-02 5.223E+00         6.965E+01  2 0.00   114\n  14  H  2  H    1.781E-02 1.103E+01         6.965E+01  2 0.00   104\n  15  H  2  O    4.453E-02 5.223E+00         6.965E+01  2 0.00   115\n  16  H  2  H    4.453E-02 1.103E+01         6.965E+01  2 0.00   105\n  17  H  3  O  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   162\n  18  H  3  O  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   161\n  19  H  3  H  O 2.969E-04 0.000E+00 -1  4.0 6.965E+01  2 0.00   152\n  20  H  3  H  O 2.969E-04 0.000E+00  1  4.0 6.965E+01  2 0.00   150\n  21  H  3  H  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   147\n  22  H  3  O  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   160\n  23  H  3  H  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   145\n  24  H  3  O  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   159\n  25  H  3  H  O 2.078E-03 0.000E+00 -1  1.0 6.965E+01  2 0.00   142\n  26  H  3  H  O 2.078E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   140\n  27  H  3  H  O 5.937E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   137\n-------------------------------------------------------------------------------\nShort range atomic symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  O  2  H    2.969E-05 0.000E+00         6.965E+01  2 0.00   117\n   2  O  2  O    2.969E-05 0.000E+00         6.965E+01  2 0.00   127\n   3  O  2  H    2.969E-04 0.000E+00         6.965E+01  2 0.00   118\n   4  O  2  O    2.969E-04 0.000E+00         6.965E+01  2 0.00   128\n   5  O  2  H    8.906E-04 0.000E+00         6.965E+01  2 0.00   119\n   6  O  2  O    8.906E-04 0.000E+00         6.965E+01  2 0.00   129\n   7  O  2  H    1.781E-03 0.000E+00         6.965E+01  2 0.00   120\n   8  O  2  O    1.781E-03 0.000E+00         6.965E+01  2 0.00   130\n   9  O  2  H    4.453E-03 5.223E+00         6.965E+01  2 0.00   121\n  10  O  2  O    4.453E-03 2.322E+01         6.965E+01  2 0.00   131\n  11  O  2  H    8.906E-03 5.223E+00         6.965E+01  2 0.00   122\n  12  O  2  O    8.906E-03 2.322E+01         6.965E+01  2 0.00   132\n  13  O  2  H    1.781E-02 5.223E+00         6.965E+01  2 0.00   123\n  14  O  2  O    1.781E-02 2.322E+01         6.965E+01  2 0.00   133\n  15  O  2  H    4.453E-02 5.223E+00         6.965E+01  2 0.00   124\n  16  O  2  O    4.453E-02 2.322E+01         6.965E+01  2 0.00   134\n  17  O  3  H  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   157\n  18  O  3  O  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   167\n  19  O  3  H  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   156\n  20  O  3  O  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   166\n  21  O  3  H  H 2.969E-04 0.000E+00 -1  4.0 6.965E+01  2 0.00   151\n  22  O  3  H  H 2.969E-04 0.000E+00  1  4.0 6.965E+01  2 0.00   149\n  23  O  3  H  H 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   146\n  24  O  3  H  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   155\n  25  O  3  O  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   165\n  26  O  3  H  H 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   144\n  27  O  3  H  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   154\n  28  O  3  O  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   164\n  29  O  3  H  H 2.078E-03 0.000E+00 -1  1.0 6.965E+01  2 0.00   141\n  30  O  3  H  H 2.078E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   139\n-------------------------------------------------------------------------------\nMinimum cutoff radius for element  H: 69.646139\nMinimum cutoff radius for element  O: 69.646139\nMaximum cutoff radius (global)      : 69.646139\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function group index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  H  2  H            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -    97    1    1  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -    98    2    3  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -    99    3    5  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   100    4    7  \n   -  -  -  -    4.453E-03 1.103E+01                 -  -    -   101    5   10  \n   -  -  -  -    8.906E-03 1.103E+01                 -  -    -   102    6   12  \n   -  -  -  -    1.781E-02 1.103E+01                 -  -    -   103    7   14  \n   -  -  -  -    4.453E-02 1.103E+01                 -  -    -   104    8   16  \n   2  H  2  O            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   107    1    2  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   108    2    4  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   109    3    6  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   110    4    8  \n   -  -  -  -    4.453E-03 5.223E+00                 -  -    -   111    5    9  \n   -  -  -  -    8.906E-03 5.223E+00                 -  -    -   112    6   11  \n   -  -  -  -    1.781E-02 5.223E+00                 -  -    -   113    7   13  \n   -  -  -  -    4.453E-02 5.223E+00                 -  -    -   114    8   15  \n   3  H  3  H  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-04 0.000E+00 -1  4.0         -  -    -   151    1   19 1\n   -  -  -  -  - 2.969E-04 0.000E+00  1  4.0         -  -    -   149    2   20 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   146    3   21 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   144    4   23 0\n   -  -  -  -  - 2.078E-03 0.000E+00 -1  1.0         -  -    -   141    5   25 1\n   -  -  -  -  - 2.078E-03 0.000E+00  1  1.0         -  -    -   139    6   26 0\n   -  -  -  -  - 5.937E-03 0.000E+00  1  1.0         -  -    -   136    7   27 1\n   4  H  3  O  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   161    1   17 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   160    2   18 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   159    3   22 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   158    4   24 0\n-------------------------------------------------------------------------------\nShort range atomic symmetry function groups element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  O  2  H            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   116    1    1  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   117    2    3  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   118    3    5  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   119    4    7  \n   -  -  -  -    4.453E-03 5.223E+00                 -  -    -   120    5    9  \n   -  -  -  -    8.906E-03 5.223E+00                 -  -    -   121    6   11  \n   -  -  -  -    1.781E-02 5.223E+00                 -  -    -   122    7   13  \n   -  -  -  -    4.453E-02 5.223E+00                 -  -    -   123    8   15  \n   2  O  2  O            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   126    1    2  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   127    2    4  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   128    3    6  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   129    4    8  \n   -  -  -  -    4.453E-03 2.322E+01                 -  -    -   130    5   10  \n   -  -  -  -    8.906E-03 2.322E+01                 -  -    -   131    6   12  \n   -  -  -  -    1.781E-02 2.322E+01                 -  -    -   132    7   14  \n   -  -  -  -    4.453E-02 2.322E+01                 -  -    -   133    8   16  \n   3  O  3  H  H         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-04 0.000E+00 -1  4.0         -  -    -   150    1   21 1\n   -  -  -  -  - 2.969E-04 0.000E+00  1  4.0         -  -    -   148    2   22 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   145    3   23 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   143    4   26 0\n   -  -  -  -  - 2.078E-03 0.000E+00 -1  1.0         -  -    -   140    5   29 1\n   -  -  -  -  - 2.078E-03 0.000E+00  1  1.0         -  -    -   138    6   30 0\n   4  O  3  H  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   156    1   17 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   155    2   19 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   154    3   24 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   153    4   27 0\n   5  O  3  O  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   166    1   18 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   165    2   20 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   164    3   25 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   163    4   28 0\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic short range NN for element  H :\nNumber of weights    :   1325\nNumber of biases     :     51\nNumber of connections:   1376\nArchitecture       27   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  O :\nNumber of weights    :   1400\nNumber of biases     :     51\nNumber of connections:   1451\nArchitecture       30   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALECENTER (3)\nGs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  1.06E+00  9.50E+00  2.32E+00  6.03E-01  1.19E-01  0.00  1.00 3\n   2  6.78E-01  4.95E+00  1.35E+00  3.01E-01  2.34E-01  0.00  1.00 3\n   3  7.29E-01  7.06E+00  1.68E+00  4.50E-01  1.58E-01  0.00  1.00 3\n   4  5.14E-01  3.73E+00  1.04E+00  2.25E-01  3.11E-01  0.00  1.00 3\n   5  3.95E-01  4.10E+00  9.31E-01  2.63E-01  2.70E-01  0.00  1.00 3\n   6  3.58E-01  2.26E+00  6.61E-01  1.31E-01  5.27E-01  0.00  1.00 3\n   7  1.89E-01  2.22E+00  4.68E-01  1.40E-01  4.93E-01  0.00  1.00 3\n   8  2.67E-01  1.33E+00  4.31E-01  7.07E-02  9.45E-01  0.00  1.00 3\n   9  2.34E-01  9.60E-01  3.67E-01  4.74E-02  1.38E+00  0.00  1.00 3\n  10  2.22E-01  2.75E+00  5.53E-01  1.77E-01  3.96E-01  0.00  1.00 3\n  11  1.34E-01  5.76E-01  2.70E-01  2.46E-02  2.26E+00  0.00  1.00 3\n  12  1.21E-01  1.72E+00  3.01E-01  1.01E-01  6.27E-01  0.00  1.00 3\n  13  4.85E-02  3.74E-01  1.85E-01  1.95E-02  3.08E+00  0.00  1.00 3\n  14  2.70E-02  9.07E-01  1.49E-01  4.68E-02  1.14E+00  0.00  1.00 3\n  15  2.45E-03  2.85E-01  7.58E-02  1.87E-02  3.53E+00  0.00  1.00 3\n  16  2.24E-04  3.15E-01  4.40E-02  2.22E-02  3.17E+00  0.00  1.00 3\n  17  1.45E-04  1.40E-01  1.85E-02  8.59E-03  7.16E+00  0.00  1.00 3\n  18  4.21E-03  5.70E-01  2.45E-02  3.14E-02  1.77E+00  0.00  1.00 3\n  19  1.63E-04  2.18E-01  1.78E-02  1.19E-02  4.59E+00  0.00  1.00 3\n  20  4.81E-02  1.65E+00  1.50E-01  9.20E-02  6.25E-01  0.00  1.00 3\n  21  3.41E-03  3.19E-01  1.88E-02  1.68E-02  3.16E+00  0.00  1.00 3\n  22  1.31E-04  1.05E-01  6.68E-03  5.61E-03  9.49E+00  0.00  1.00 3\n  23  3.44E-02  9.07E-01  8.33E-02  4.84E-02  1.15E+00  0.00  1.00 3\n  24  4.93E-04  1.57E-01  4.74E-03  8.13E-03  6.39E+00  0.00  1.00 3\n  25  8.69E-04  6.09E-02  3.73E-03  2.74E-03  1.67E+01  0.00  1.00 3\n  26  8.70E-03  1.96E-01  2.45E-02  9.14E-03  5.33E+00  0.00  1.00 3\n  27  1.63E-04  9.82E-03  2.02E-03  5.53E-04  1.04E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  1.42E+00  9.89E+00  2.70E+00  6.01E-01  1.18E-01  0.00  1.00 3\n   2  3.96E-01  4.56E+00  9.90E-01  2.99E-01  2.40E-01  0.00  1.00 3\n   3  1.11E+00  7.45E+00  2.07E+00  4.48E-01  1.58E-01  0.00  1.00 3\n   4  2.61E-01  3.34E+00  6.78E-01  2.21E-01  3.24E-01  0.00  1.00 3\n   5  7.75E-01  4.49E+00  1.32E+00  2.59E-01  2.69E-01  0.00  1.00 3\n   6  9.71E-02  1.87E+00  3.18E-01  1.24E-01  5.64E-01  0.00  1.00 3\n   7  5.69E-01  2.60E+00  8.61E-01  1.37E-01  4.91E-01  0.00  1.00 3\n   8  2.66E-02  9.34E-01  1.17E-01  6.02E-02  1.10E+00  0.00  1.00 3\n   9  5.18E-01  1.86E+00  7.35E-01  8.59E-02  7.48E-01  0.00  1.00 3\n  10  1.21E-01  2.88E+00  4.95E-01  2.06E-01  3.62E-01  0.00  1.00 3\n  11  3.61E-01  1.08E+00  5.40E-01  4.13E-02  1.40E+00  0.00  1.00 3\n  12  3.62E-02  2.51E+00  3.35E-01  1.83E-01  4.05E-01  0.00  1.00 3\n  13  1.44E-01  6.51E-01  3.70E-01  3.03E-02  1.97E+00  0.00  1.00 3\n  14  2.89E-03  2.28E+00  1.92E-01  1.60E-01  4.39E-01  0.00  1.00 3\n  15  7.24E-03  4.20E-01  1.52E-01  2.78E-02  2.42E+00  0.00  1.00 3\n  16  1.99E-06  2.01E+00  5.82E-02  1.19E-01  4.97E-01  0.00  1.00 3\n  17  2.40E-03  3.39E-01  1.72E-02  1.82E-02  2.97E+00  0.00  1.00 3\n  18  2.24E-05  5.63E-02  9.49E-04  2.74E-03  1.78E+01  0.00  1.00 3\n  19  4.90E-02  2.95E+00  2.10E-01  1.69E-01  3.45E-01  0.00  1.00 3\n  20  1.37E-03  4.84E-01  1.29E-02  2.64E-02  2.07E+00  0.00  1.00 3\n  21  7.30E-03  2.68E-01  3.18E-02  1.44E-02  3.84E+00  0.00  1.00 3\n  22  1.56E-02  1.38E+00  7.83E-02  7.76E-02  7.31E-01  0.00  1.00 3\n  23  1.98E-02  4.09E-01  5.03E-02  2.15E-02  2.57E+00  0.00  1.00 3\n  24  8.02E-04  2.31E-01  7.36E-03  1.19E-02  4.34E+00  0.00  1.00 3\n  25  1.16E-05  3.54E-02  3.94E-04  1.66E-03  2.83E+01  0.00  1.00 3\n  26  1.79E-02  8.10E-01  5.18E-02  4.40E-02  1.26E+00  0.00  1.00 3\n  27  4.55E-03  7.71E-01  3.83E-02  4.19E-02  1.30E+00  0.00  1.00 3\n  28  3.69E-05  9.64E-02  1.12E-03  4.71E-03  1.04E+01  0.00  1.00 3\n  29  5.85E-03  1.01E-01  1.65E-02  4.73E-03  1.05E+01  0.00  1.00 3\n  30  3.47E-03  1.54E-01  1.17E-02  7.38E-03  6.64E+00  0.00  1.00 3\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 0\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** SETUP: RANDOM NUMBER GENERATOR ********************************************\n\nRandom number generator seed: 4\nSeed for rank 0: 4\nSeed for rank 1: 4153361530\nSeed for rank 2: 3868139694\nSeed for rank 3: 2350344631\nSeed for rank 4: 741720773\nSeed for rank 5: 4177647489\nSeed for rank 6: 3674863976\nSeed for rank 7: 3070111319\nSeed for rank 8: 2615787976\nSeed for rank 9: 2996722482\nSeed for rank 10: 2566484361\nSeed for rank 11: 928097338\nSeed for rank 12: 607583996\nSeed for rank 13: 4193066855\nSeed for rank 14: 964245613\nSeed for rank 15: 26758750\nSeed for global RNG: 2999692087\n*******************************************************************************\n\n*** STRUCTURE DISTRIBUTION ****************************************************\n\nReading configurations from data file: input.data.\nTotal number of structures: 7183\nNumber of structures per processor: 448 (1) or 449 (15)\nDistributed 7183 structures, 141224340 bytes (134.68 MiB) transferred.\nNumber of local structures: 448\n*******************************************************************************\n\n*** DEFINE TRAINING/TEST SETS *************************************************\n\nDesired test set ratio      : 0.100000\nTotal number of energies    : 7183\nNumber of training energies : 6443\nNumber of test     energies : 740\nNumber of training forces   : 1820538\nNumber of test     forces   : 212382\nActual test set fraction    : 0.103021\n*******************************************************************************\n\n*** WRITE TRAINING/TEST SETS **************************************************\n\nWriting training/test set to files:\n - train.data\n - test.data\n*******************************************************************************\n\n*** WEIGHT INITIALIZATION *****************************************************\n\nInitial weights selected randomly in interval [-1.000000, 1.000000).\nWeights modified accoring to Glorot Bengio scheme.\nBiases set to zero.\n*******************************************************************************\n\n*** SETUP: TRAINING ***********************************************************\n\nForces will be used for training.\nForce update weight:   1.00E+01\nWeight update via Kalman filter selected: updaterType::UT_KALMANFILTER (1)\nMulti-stream Kalman filter training, update on rank 0, partial X calculation selected: ParallelMode::PM_MSEKFR0PX (4)\nNumber of streams       : 16\nStream of this processor: 0\nCombined updater for all elements selected: UpdateStrategy::US_COMBINED (0)\nNumber of weight updaters    : 1\nTotal fit parameters         : 2827\nSelection mode starting with epoch 0:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 1.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\n-------------------------------------------------------------------------------\nSymmetry function memory is reused (HIGH MEMORY USAGE!).\nTraining will be stopped after 25 epochs.\nEnergy comparison will be written every 25 epochs.\nForce comparison will be written every 25 epochs.\nWeights will be written every 1 epochs.\nNeuron statistics will be written every 5 epochs.\nUp to epoch 10 neuron statistics will be written every epoch.\nTraining log with update information will be written to: train-log.out.\n-------------------------------------------------------------------------------\nFraction of energies used per epoch:    1.0000\nFraction of forces used per epoch  :    0.0410\nProjected energy updates per epoch :     403 (  7.9%)\nProjected forces updates per epoch :    4665 ( 92.1%)\nTotal projected updates per epoch  :    5068\nMulti-stream training uses 16 energies/forces per weight update.\nqtau is divided by number of projected updates per epoch.\netatau is divided by number of projected updates per epoch.\n-------------------------------------------------------------------------------\nCombined weight updater:\n-------------------------------------------------------------------------------\nKalmanType::KT_STANDARD (0)\nsizeState       = 2827\nsizeObservation = 16\nepsilon         =   1.0000E-02\nq0              =   1.0000E-02\nqtau            =   4.5424E-04\nqmin            =   1.0000E-06\neta0            =   1.0000E-02\netatau          =   4.5424E-04\netamax          =   1.0000E+00\nKalmanParallel::KP_PRECALCX (2)\nOpenMP threads used: 1\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** CALCULATE NEIGHBOR LISTS **************************************************\n\nCalculating neighbor lists for all structures.\nCutoff radius for neighbor lists: 69.646139\n*******************************************************************************\n\n*** TRAINING LOOP *************************************************************\n\nThe training loop output covers different RMSEs, update and\ntiming information. The following quantities are organized\naccording to the matrix scheme below:\n-------------------------------------------------------------------\nep ............ Epoch.\nEtrain_phys ... RMSE of training energies per atom (p. u.).\nEtest_phys .... RMSE of test     energies per atom (p. u.).\nEtrain_int .... RMSE of training energies per atom (i. u.).\nEtest_int ..... RMSE of test     energies per atom (i. u.).\nFtrain_phys ... RMSE of training forces (p. u.).\nFtest_phys .... RMSE of test     forces (p. u.).\nFtrain_int .... RMSE of training forces (i. u.).\nFtest_int ..... RMSE of test     forces (i. u.).\nE_count ....... Number of energy updates.\nF_count ....... Number of force  updates.\ncount ......... Total number of updates.\nt_train ....... Time for training (seconds).\nt_rmse ........ Time for RMSE calculation (seconds).\nt_epoch ....... Total time for this epoch (seconds).\nt_tot ......... Total time for all epochs (seconds).\nAbbreviations:\n  p. u. = physical units.\n  i. u. = internal units.\nNote: RMSEs in internal units (columns 5 + 6) are only present \n      if data set normalization is used.\n-------------------------------------------------------------------\n     1    2             3             4             5             6\nenergy   ep   Etrain_phys    Etest_phys    Etrain_int     Etest_int\nforces   ep   Ftrain_phys    Ftest_phys    Ftrain_int     Ftest_int\nupdate   ep       E_count       F_count         count\ntiming   ep       t_train        t_rmse       t_epoch         t_tot\n-------------------------------------------------------------------\nENERGY    0   4.74316E-03   4.38511E-03   1.15096E+00   1.06408E+00\nFORCES    0   2.27445E-02   2.20704E-02   9.50942E-01   9.22759E-01\nTIMING    0          0.00         37.89         37.93         37.93\n------\nENERGY    1   2.62332E-04   2.62021E-04   6.36568E-02   6.35815E-02\nFORCES    1   1.08684E-03   8.99384E-04   4.54404E-02   3.76031E-02\nUPDATE    1           402          4656          5058\nTIMING    1        762.66          3.45        766.15        804.07\n------\nENERGY    2   8.38518E-05   8.46794E-05   2.03473E-02   2.05481E-02\nFORCES    2   1.07842E-03   8.84302E-04   4.50886E-02   3.69725E-02\nUPDATE    2           402          4612          5014\nTIMING    2        724.94          3.45        728.43       1532.50\n------\nENERGY    3   8.42097E-05   8.37110E-05   2.04341E-02   2.03131E-02\nFORCES    3   8.61280E-04   8.12897E-04   3.60099E-02   3.39871E-02\nUPDATE    3           402          4664          5066\nTIMING    3        739.28          3.55        742.86       2275.37\n------\nENERGY    4   2.63719E-05   2.67312E-05   6.39933E-03   6.48652E-03\nFORCES    4   7.74160E-04   7.61705E-04   3.23675E-02   3.18467E-02\nUPDATE    4           402          4670          5072\nTIMING    4        727.20          3.45        730.68       3006.05\n------\nENERGY    5   3.33191E-05   3.42033E-05   8.08513E-03   8.29968E-03\nFORCES    5   7.72538E-04   7.57909E-04   3.22997E-02   3.16880E-02\nUPDATE    5           402          4627          5029\nTIMING    5        715.92          3.51        719.46       3725.51\n------\nENERGY    6   2.98267E-05   2.94716E-05   7.23766E-03   7.15151E-03\nFORCES    6   7.68153E-04   7.49247E-04   3.21163E-02   3.13259E-02\nUPDATE    6           402          4597          4999\nTIMING    6        712.98          3.56        716.58       4442.09\n------\nENERGY    7   2.95337E-05   2.91416E-05   7.16657E-03   7.07143E-03\nFORCES    7   7.79652E-04   7.50785E-04   3.25971E-02   3.13902E-02\nUPDATE    7           402          4607          5009\nTIMING    7        712.73          3.53        716.29       5158.37\n------\nENERGY    8   2.88773E-05   2.98206E-05   7.00730E-03   7.23619E-03\nFORCES    8   7.64684E-04   7.39267E-04   3.19713E-02   3.09086E-02\nUPDATE    8           402          4630          5032\nTIMING    8        718.40          3.53        721.97       5880.34\n------\nENERGY    9   2.83626E-05   2.90459E-05   6.88239E-03   7.04821E-03\nFORCES    9   7.64997E-04   7.41450E-04   3.19844E-02   3.09998E-02\nUPDATE    9           402          4644          5046\nTIMING    9        724.22          3.49        727.75       6608.09\n------\nENERGY   10   2.95650E-05   3.05936E-05   7.17417E-03   7.42376E-03\nFORCES   10   7.58510E-04   7.38462E-04   3.17131E-02   3.08749E-02\nUPDATE   10           402          4549          4951\nTIMING   10        703.83          3.56        707.42       7315.51\n------\nENERGY   11   2.95338E-05   3.09436E-05   7.16659E-03   7.50870E-03\nFORCES   11   7.44338E-04   7.39733E-04   3.11206E-02   3.09281E-02\nUPDATE   11           402          4635          5037\nTIMING   11        723.45          3.56        727.04       8042.54\n------\nENERGY   12   2.83085E-05   2.87754E-05   6.86926E-03   6.98256E-03\nFORCES   12   7.44941E-04   7.36262E-04   3.11458E-02   3.07829E-02\nUPDATE   12           402          4668          5070\nTIMING   12        727.26          3.53        730.82       8773.36\n------\nENERGY   13   2.66207E-05   2.69546E-05   6.45972E-03   6.54073E-03\nFORCES   13   7.43088E-04   7.37891E-04   3.10684E-02   3.08511E-02\nUPDATE   13           402          4609          5011\nTIMING   13        711.50          3.51        715.04       9488.40\n------\nENERGY   14   2.96513E-05   2.98100E-05   7.19510E-03   7.23362E-03\nFORCES   14   7.39924E-04   7.34894E-04   3.09361E-02   3.07257E-02\nUPDATE   14           402          4554          4956\nTIMING   14        705.11          3.52        708.67      10197.07\n------\nENERGY   15   2.81390E-05   2.91516E-05   6.82813E-03   7.07386E-03\nFORCES   15   7.39764E-04   7.32316E-04   3.09294E-02   3.06180E-02\nUPDATE   15           402          4622          5024\nTIMING   15        713.57          3.48        717.09      10914.16\n------\nENERGY   16   4.43979E-05   4.35776E-05   1.07735E-02   1.05744E-02\nFORCES   16   7.40744E-04   7.33618E-04   3.09704E-02   3.06724E-02\nUPDATE   16           402          4717          5119\nTIMING   16        724.00          3.52        727.56      11641.72\n------\nENERGY   17   3.02151E-05   3.06975E-05   7.33191E-03   7.44899E-03\nFORCES   17   7.37396E-04   7.33211E-04   3.08304E-02   3.06554E-02\nUPDATE   17           402          4631          5033\nTIMING   17        716.73          3.49        720.25      12361.97\n------\nENERGY   18   2.48654E-05   2.60136E-05   6.03378E-03   6.31240E-03\nFORCES   18   7.35427E-04   7.30967E-04   3.07480E-02   3.05616E-02\nUPDATE   18           402          4602          5004\nTIMING   18        713.13          3.53        716.69      13078.65\n------\nENERGY   19   3.46925E-05   3.52192E-05   8.41838E-03   8.54620E-03\nFORCES   19   7.37165E-04   7.31071E-04   3.08207E-02   3.05659E-02\nUPDATE   19           402          4737          5139\nTIMING   19        732.06          3.53        735.62      13814.27\n------\nENERGY   20   3.11669E-05   3.18542E-05   7.56287E-03   7.72966E-03\nFORCES   20   7.41466E-04   7.33439E-04   3.10005E-02   3.06649E-02\nUPDATE   20           402          4541          4943\nTIMING   20        700.41          3.48        703.93      14518.20\n------\nENERGY   21   2.92938E-05   2.99674E-05   7.10835E-03   7.27180E-03\nFORCES   21   7.38847E-04   7.29923E-04   3.08910E-02   3.05179E-02\nUPDATE   21           402          4732          5134\nTIMING   21        730.07          3.45        733.56      15251.76\n------\nENERGY   22   3.03189E-05   3.02054E-05   7.35710E-03   7.32956E-03\nFORCES   22   7.35929E-04   7.28697E-04   3.07690E-02   3.04667E-02\nUPDATE   22           402          4648          5050\nTIMING   22        719.58          3.54        723.15      15974.90\n------\nENERGY   23   3.15232E-05   3.13463E-05   7.64934E-03   7.60642E-03\nFORCES   23   7.38851E-04   7.28588E-04   3.08912E-02   3.04621E-02\nUPDATE   23           402          4679          5081\nTIMING   23        731.53          3.55        735.11      16710.02\n------\nENERGY   24   2.92991E-05   2.92885E-05   7.10965E-03   7.10708E-03\nFORCES   24   7.32441E-04   7.29420E-04   3.06232E-02   3.04969E-02\nUPDATE   24           402          4636          5038\nTIMING   24        715.92          3.48        719.44      17429.46\n------\nENERGY   25   2.74763E-05   2.77246E-05   6.66733E-03   6.72758E-03\nFORCES   25   7.33265E-04   7.30703E-04   3.06577E-02   3.05505E-02\nUPDATE   25           402          4674          5076\nTIMING   25        722.14          4.72        726.89      18156.35\n*******************************************************************************\n"
  },
  {
    "path": "examples/potentials/H2O_BLYP-D3/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0603925015903508E+00   9.4965695104242709E+00   2.3170049685689307E+00   6.0291714647628103E-01\n         1          2   6.7796114362233972E-01   4.9479235550030474E+00   1.3516388250000126E+00   3.0132099735988388E-01\n         1          3   7.2920094626195009E-01   7.0577178720222475E+00   1.6834256403163406E+00   4.5040991998204222E-01\n         1          4   5.1373593943747675E-01   3.7289832753466952E+00   1.0351608390526674E+00   2.2481295470908944E-01\n         1          5   3.9539412587303108E-01   4.1045353053466718E+00   9.3097859431809005E-01   2.6291145927474097E-01\n         1          6   3.5804940311939948E-01   2.2554909574121358E+00   6.6092691006837234E-01   1.3080089483157395E-01\n         1          7   1.8919103878435897E-01   2.2165691039158446E+00   4.6830619635729820E-01   1.4026352904964970E-01\n         1          8   2.6704178695764313E-01   1.3252854646485042E+00   4.3069258596333004E-01   7.0698192491763540E-02\n         1          9   2.3432552582413152E-01   9.5985894006838979E-01   3.6743404992714473E-01   4.7432783101305803E-02\n         1         10   2.2248910067848982E-01   2.7482551313965367E+00   5.5345454298508212E-01   1.7663490137583926E-01\n         1         11   1.3374237955415089E-01   5.7555780466104955E-01   2.6990104908476592E-01   2.4553366433103990E-02\n         1         12   1.2079214864210941E-01   1.7161109364147793E+00   3.0087930171836863E-01   1.0103080388436764E-01\n         1         13   4.8458872613975419E-02   3.7352302087895262E-01   1.8498122968279135E-01   1.9469353470254566E-02\n         1         14   2.7024966891331988E-02   9.0698364912022389E-01   1.4929129615023826E-01   4.6843428338165509E-02\n         1         15   2.4543106515324499E-03   2.8537946241644763E-01   7.5788154289220699E-02   1.8743382725519665E-02\n         1         16   2.2422507599479169E-04   3.1547402145398762E-01   4.4027433743690288E-02   2.2165000790726617E-02\n         1         17   1.4524293730525610E-04   1.3987663656796817E-01   1.8541276177581546E-02   8.5897803459035141E-03\n         1         18   4.2080717513700025E-03   5.7034297600008665E-01   2.4522940310061470E-02   3.1439097986530745E-02\n         1         19   1.6305025910327636E-04   2.1823891010342389E-01   1.7848825079488349E-02   1.1897287697748784E-02\n         1         20   4.8122777334757713E-02   1.6493827087912631E+00   1.4955099057474797E-01   9.2003659726696427E-02\n         1         21   3.4073471604482227E-03   3.1949935706417248E-01   1.8805456781529686E-02   1.6842354821495795E-02\n         1         22   1.3121382132811807E-04   1.0548685225563786E-01   6.6806675960028733E-03   5.6070276001321693E-03\n         1         23   3.4368790392673633E-02   9.0693310292685470E-01   8.3259827790813118E-02   4.8400449021875090E-02\n         1         24   4.9339421631383368E-04   1.5700081674231126E-01   4.7379508312007752E-03   8.1285241406418209E-03\n         1         25   8.6889007793241897E-04   6.0887424299026757E-02   3.7274728261119418E-03   2.7420717780802994E-03\n         1         26   8.7040247660959500E-03   1.9642380976240573E-01   2.4495829588748026E-02   9.1425450551432235E-03\n         1         27   1.6279340881271008E-04   9.8215755603321218E-03   2.0218337872835944E-03   5.5272429271132966E-04\n         2          1   1.4213173942028050E+00   9.8880797168258603E+00   2.7032776500000217E+00   6.0145820941271033E-01\n         2          2   3.9626412312240411E-01   4.5602057310279998E+00   9.9011971471334403E-01   2.9881807282219519E-01\n         2          3   1.1147542079507753E+00   7.4486797356298267E+00   2.0703216781053313E+00   4.4789475263082179E-01\n         2          4   2.6077700427526451E-01   3.3443529134675924E+00   6.7781131189606780E-01   2.2109836631906557E-01\n         2          5   7.7542789977433935E-01   4.4942980926886493E+00   1.3218538201367438E+00   2.5888079726637109E-01\n         2          6   9.7105511224524765E-02   1.8699303209493725E+00   3.1767556924901225E-01   1.2432228520760431E-01\n         2          7   5.6949141690859706E-01   2.6045669224158496E+00   8.6138517192666164E-01   1.3703773749638820E-01\n         2          8   2.6601842750007033E-02   9.3430041772439176E-01   1.1665200448782125E-01   6.0185708488699460E-02\n         2          9   5.1802225563760573E-01   1.8552023479780817E+00   7.3486809985428780E-01   8.5876030396493885E-02\n         2         10   1.2113017145954923E-01   2.8812140466572265E+00   4.9504101435735409E-01   2.0622429896628103E-01\n         2         11   3.6148389791073959E-01   1.0764120430823212E+00   5.3980209816953084E-01   4.1262168421262853E-02\n         2         12   3.6236770090556265E-02   2.5054369427892476E+00   3.3535257298920407E-01   1.8305183391386451E-01\n         2         13   1.4352871952342236E-01   6.5127467874628953E-01   3.6996245936558392E-01   3.0311284134343013E-02\n         2         14   2.8930088222220663E-03   2.2821550251861504E+00   1.9175061774741886E-01   1.5989990004596175E-01\n         2         15   7.2421508479313659E-03   4.1980710681015831E-01   1.5157630857844137E-01   2.7755706610422069E-02\n         2         16   1.9935928594021411E-06   2.0101845732691275E+00   5.8226524725683820E-02   1.1909948022748237E-01\n         2         17   2.3981466715180234E-03   3.3937328363658342E-01   1.7177516521957308E-02   1.8171589681212737E-02\n         2         18   2.2353202378351962E-05   5.6254857216768407E-02   9.4876832079353118E-04   2.7350161370484306E-03\n         2         19   4.8961770113527252E-02   2.9469388689388913E+00   2.1041312898870274E-01   1.6904744771318797E-01\n         2         20   1.3718340250504096E-03   4.8436598753884313E-01   1.2903929906682226E-02   2.6351492451304057E-02\n         2         21   7.3015106914034395E-03   2.6802931728263452E-01   3.1791963215924361E-02   1.4389810987548657E-02\n         2         22   1.5612522222278442E-02   1.3842296182273586E+00   7.8331245458022072E-02   7.7642427639231265E-02\n         2         23   1.9759831791959857E-02   4.0880719300669388E-01   5.0262236586601033E-02   2.1498340706973006E-02\n         2         24   8.0219871333972210E-04   2.3097036139855665E-01   7.3610238679051769E-03   1.1929555669354207E-02\n         2         25   1.1563074448517735E-05   3.5357205787985520E-02   3.9397225209918466E-04   1.6614079933457971E-03\n         2         26   1.7857311533439311E-02   8.1012195985805868E-01   5.1803047985741701E-02   4.4031121354354830E-02\n         2         27   4.5467862926627843E-03   7.7101781364420252E-01   3.8313449840909390E-02   4.1901527435650475E-02\n         2         28   3.6919908321672065E-05   9.6427393825001734E-02   1.1214329207115408E-03   4.7100825495531833E-03\n         2         29   5.8469236684166219E-03   1.0115946138898321E-01   1.6513920456563171E-02   4.7320953206681851E-03\n         2         30   3.4729465399378828E-03   1.5413543908561486E-01   1.1709381958296818E-02   7.3803079124397297E-03\n"
  },
  {
    "path": "examples/potentials/H2O_BLYP-D3/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  5.5599864293100154E-01 a         1     0     1     1     1\n  1.3588584603802865E+00 a         2     0     1     1     2\n -1.7657253702809668E+00 a         3     0     1     1     3\n -3.0137172032554118E+00 a         4     0     1     1     4\n  1.2718501176038558E+01 a         5     0     1     1     5\n  1.0658784435179641E+01 a         6     0     1     1     6\n  4.7653378361655987E+00 a         7     0     1     1     7\n  3.5441560243507713E+00 a         8     0     1     1     8\n -6.2649404896920844E+00 a         9     0     1     1     9\n -9.6306591560637589E-01 a        10     0     1     1    10\n  1.2105724219837044E+00 a        11     0     1     1    11\n -1.0180614617246246E+00 a        12     0     1     1    12\n -4.1744577460177510E+00 a        13     0     1     1    13\n  9.9009326139578384E+00 a        14     0     1     1    14\n -7.4128713630994101E+00 a        15     0     1     1    15\n  5.5855882851233343E+00 a        16     0     1     1    16\n  1.7906137568298583E+00 a        17     0     1     1    17\n -8.8248117940190529E-01 a        18     0     1     1    18\n  1.3163695873221192E+01 a        19     0     1     1    19\n -1.1524624036901658E+00 a        20     0     1     1    20\n  6.2822518025173446E+00 a        21     0     1     1    21\n  8.3435048944266992E+00 a        22     0     1     1    22\n -2.2091674040849405E+01 a        23     0     1     1    23\n  2.7971567668957040E+00 a        24     0     1     1    24\n -1.8990904999939666E+01 a        25     0     1     1    25\n -6.3829903560013008E+00 a        26     0     2     1     1\n -1.9020450610756285E+01 a        27     0     2     1     2\n  1.6254583216252265E+00 a        28     0     2     1     3\n  9.7431353960322831E+00 a        29     0     2     1     4\n  5.6048405982447251E+00 a        30     0     2     1     5\n -9.9546460285590754E+00 a        31     0     2     1     6\n -6.9219496784215346E+00 a        32     0     2     1     7\n -5.4629162556874027E+00 a        33     0     2     1     8\n  1.2510030026709750E+01 a        34     0     2     1     9\n -1.2451272715775904E+01 a        35     0     2     1    10\n -6.6399148989663752E+00 a        36     0     2     1    11\n  5.8499727027695512E+00 a        37     0     2     1    12\n -1.2315267427103485E+01 a        38     0     2     1    13\n -9.0871574209775012E+00 a        39     0     2     1    14\n  1.6011528765468853E+01 a        40     0     2     1    15\n -2.2166268288157585E+00 a        41     0     2     1    16\n  2.9497573412022695E+00 a        42     0     2     1    17\n  4.6240909615215360E+00 a        43     0     2     1    18\n -1.7341814124415439E+01 a        44     0     2     1    19\n -6.8212742968011844E+00 a        45     0     2     1    20\n -1.7117834195895615E+01 a        46     0     2     1    21\n -2.8068775869023663E+00 a        47     0     2     1    22\n  2.6487355645610844E+01 a        48     0     2     1    23\n  3.4600215228668212E+00 a        49     0     2     1    24\n  2.1667161046299668E+01 a        50     0     2     1    25\n  1.1753822406422733E+01 a        51     0     3     1     1\n  9.0191103966608246E+00 a        52     0     3     1     2\n  1.1365423561373154E+00 a        53     0     3     1     3\n -6.2991888814619132E+00 a        54     0     3     1     4\n -1.7746591411130215E+01 a        55     0     3     1     5\n -8.4190992356207470E+00 a        56     0     3     1     6\n -6.1634630048587233E+00 a        57     0     3     1     7\n  3.0261681810333756E+00 a        58     0     3     1     8\n  8.1279337310889748E+00 a        59     0     3     1     9\n  7.9905537069564936E+00 a        60     0     3     1    10\n  3.1033101013326259E+00 a        61     0     3     1    11\n -8.3773637777244829E+00 a        62     0     3     1    12\n  1.4529611536507751E+01 a        63     0     3     1    13\n -1.2477627091949106E+01 a        64     0     3     1    14\n  2.6872078792025795E+00 a        65     0     3     1    15\n -5.2499498003176814E+00 a        66     0     3     1    16\n -1.0835340663230330E+01 a        67     0     3     1    17\n  1.0640224898486743E+00 a        68     0     3     1    18\n -1.7094679701942237E+01 a        69     0     3     1    19\n  6.4713797670394628E+00 a        70     0     3     1    20\n -1.2472155229515347E+00 a        71     0     3     1    21\n -6.9145495294541339E+00 a        72     0     3     1    22\n  2.9261389428877870E+01 a        73     0     3     1    23\n -1.1563953934979175E+01 a        74     0     3     1    24\n  2.4008604999584421E+01 a        75     0     3     1    25\n  5.5571029511621328E-01 a        76     0     4     1     1\n  3.1434995863645007E+01 a        77     0     4     1     2\n -7.4074993440531838E+00 a        78     0     4     1     3\n -9.5035107143069091E+00 a        79     0     4     1     4\n -2.0653746425224870E+01 a        80     0     4     1     5\n  1.2252770408535392E+01 a        81     0     4     1     6\n  1.0666869707498133E+01 a        82     0     4     1     7\n  3.4538599065157216E-01 a        83     0     4     1     8\n -2.8262060829145106E+01 a        84     0     4     1     9\n  9.6514114518579976E+00 a        85     0     4     1    10\n  1.5086158842750820E+01 a        86     0     4     1    11\n -2.6610382959633143E+00 a        87     0     4     1    12\n  5.9497152256297472E+00 a        88     0     4     1    13\n  6.4951973077098746E+00 a        89     0     4     1    14\n -2.9446403704152743E+01 a        90     0     4     1    15\n -4.8778039393184311E+00 a        91     0     4     1    16\n  1.6194934964899470E+00 a        92     0     4     1    17\n -1.3044764121367846E+01 a        93     0     4     1    18\n  2.3624815515176351E+01 a        94     0     4     1    19\n  1.5622659379002510E+01 a        95     0     4     1    20\n  2.4446822896120153E+01 a        96     0     4     1    21\n -8.2894459996856700E+00 a        97     0     4     1    22\n -4.4389556605743394E+01 a        98     0     4     1    23\n  2.1923336071671407E+00 a        99     0     4     1    24\n -2.6202511161686395E+01 a       100     0     4     1    25\n -1.9200744146005405E+01 a       101     0     5     1     1\n -2.7986635817338659E+01 a       102     0     5     1     2\n  4.0622912768146957E+00 a       103     0     5     1     3\n  1.0231408639163856E+01 a       104     0     5     1     4\n  2.3268459946182599E+01 a       105     0     5     1     5\n -5.1877192271770571E+00 a       106     0     5     1     6\n  1.9031703869173391E+00 a       107     0     5     1     7\n -5.2986390926372611E+00 a       108     0     5     1     8\n  1.2943193300479279E+00 a       109     0     5     1     9\n -5.0299926534731769E+00 a       110     0     5     1    10\n -1.4764234322608004E+01 a       111     0     5     1    11\n  1.7121699066559881E+01 a       112     0     5     1    12\n -1.3574327496659699E+01 a       113     0     5     1    13\n  9.5084028953123383E+00 a       114     0     5     1    14\n  2.3454079669583965E+01 a       115     0     5     1    15\n -3.9749721714312192E+00 a       116     0     5     1    16\n  1.9255460515916099E+01 a       117     0     5     1    17\n  2.4116594912649401E+00 a       118     0     5     1    18\n  8.5265876050176708E+00 a       119     0     5     1    19\n -1.3523642583274066E+01 a       120     0     5     1    20\n -5.0052167359373305E+00 a       121     0     5     1    21\n -7.0694491789326730E-01 a       122     0     5     1    22\n -8.7852377723760195E+00 a       123     0     5     1    23\n  1.7180103123508008E+01 a       124     0     5     1    24\n -1.3700430724892353E+01 a       125     0     5     1    25\n  4.3164659776750947E+00 a       126     0     6     1     1\n -1.9396802003154889E+01 a       127     0     6     1     2\n  2.0436383612706454E+01 a       128     0     6     1     3\n  4.9834340944581488E+00 a       129     0     6     1     4\n  1.5300957137758534E+01 a       130     0     6     1     5\n -1.0494214426399600E+01 a       131     0     6     1     6\n -1.6574966401934628E+00 a       132     0     6     1     7\n -8.8240983349367124E+00 a       133     0     6     1     8\n  2.5455225932835390E+01 a       134     0     6     1     9\n -9.5880656938337500E-02 a       135     0     6     1    10\n -1.9781854762118204E+01 a       136     0     6     1    11\n -8.4120483976359655E+00 a       137     0     6     1    12\n  1.2887477329223413E+01 a       138     0     6     1    13\n  3.3140551021654137E+00 a       139     0     6     1    14\n  1.9400094371403000E+01 a       140     0     6     1    15\n  1.5547699411802887E+01 a       141     0     6     1    16\n -1.4123468939394890E+01 a       142     0     6     1    17\n  1.0791835209707560E+01 a       143     0     6     1    18\n -1.7630857847310764E+01 a       144     0     6     1    19\n -1.3827193048792136E+01 a       145     0     6     1    20\n -1.7965257787852973E+01 a       146     0     6     1    21\n  1.7343081734079671E+01 a       147     0     6     1    22\n  3.3239918460892760E+01 a       148     0     6     1    23\n -1.1889837896945874E+01 a       149     0     6     1    24\n  9.8345978545123831E+00 a       150     0     6     1    25\n  2.1793647719124397E+01 a       151     0     7     1     1\n  2.5628916814228663E+01 a       152     0     7     1     2\n -1.0394470454114446E+01 a       153     0     7     1     3\n -8.1922688924636482E+00 a       154     0     7     1     4\n -2.0889446435875929E+01 a       155     0     7     1     5\n  1.4422669604926513E+01 a       156     0     7     1     6\n -1.3953703139836400E+00 a       157     0     7     1     7\n  1.2540523690514489E+01 a       158     0     7     1     8\n -5.9238601886702034E+00 a       159     0     7     1     9\n  1.5636954496653581E+00 a       160     0     7     1    10\n  3.2224199461418358E+01 a       161     0     7     1    11\n -1.6935208477794188E+01 a       162     0     7     1    12\n -1.1235362267801358E+01 a       163     0     7     1    13\n -5.5701748953716672E+00 a       164     0     7     1    14\n -3.7738498498306335E+01 a       165     0     7     1    15\n  7.9271727499686770E+00 a       166     0     7     1    16\n -1.7038253210315936E+01 a       167     0     7     1    17\n -3.6189815984345231E-01 a       168     0     7     1    18\n  1.5701282083499133E+00 a       169     0     7     1    19\n  1.6403043277293357E+01 a       170     0     7     1    20\n  7.3822033597169510E+00 a       171     0     7     1    21\n  4.5542039832215258E+00 a       172     0     7     1    22\n -3.7013241050430792E+00 a       173     0     7     1    23\n -1.9131295520562990E+01 a       174     0     7     1    24\n  1.2343941217255285E+01 a       175     0     7     1    25\n 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-3.7937355301536480E-01 a      1269     1    23     2    19\n  1.2346357153777958E+00 a      1270     1    23     2    20\n -3.7611975995193569E+00 a      1271     1    23     2    21\n  3.0044764509818580E+00 a      1272     1    23     2    22\n  1.2286394226892239E+00 a      1273     1    23     2    23\n  4.5990726979695903E-02 a      1274     1    23     2    24\n -7.5235284354118037E-01 a      1275     1    23     2    25\n -5.1375384833428930E+00 a      1276     1    24     2     1\n -2.2055241062252748E+00 a      1277     1    24     2     2\n  7.3924971238313040E+00 a      1278     1    24     2     3\n  2.2625140786086297E+00 a      1279     1    24     2     4\n -7.8056802311548115E+00 a      1280     1    24     2     5\n  1.2059867035050489E+01 a      1281     1    24     2     6\n  1.0467817614074788E+00 a      1282     1    24     2     7\n  5.0190322420772677E+00 a      1283     1    24     2     8\n -8.9709383498100070E-01 a      1284     1    24     2     9\n  3.5231423132874813E+00 a      1285     1    24     2    10\n  1.2438882617855608E+01 a      1286     1    24     2    11\n -5.9170434838164443E+00 a      1287     1    24     2    12\n -2.3680140765237443E+00 a      1288     1    24     2    13\n  4.5864537169339430E+00 a      1289     1    24     2    14\n -1.2675884117813137E+00 a      1290     1    24     2    15\n  7.8468709633979367E-02 a      1291     1    24     2    16\n -2.3773481294988521E+00 a      1292     1    24     2    17\n  8.6459135618226739E+00 a      1293     1    24     2    18\n -9.2828931738942366E-01 a      1294     1    24     2    19\n  5.7014335995385732E+00 a      1295     1    24     2    20\n  1.1438994285141218E+01 a      1296     1    24     2    21\n -8.2713113404853491E+00 a      1297     1    24     2    22\n -2.5563149673506316E+00 a      1298     1    24     2    23\n  6.0461822230838429E+00 a      1299     1    24     2    24\n -7.6396081376118988E-02 a      1300     1    24     2    25\n -1.9984606682335995E+00 a      1301     1    25     2     1\n  1.9521438678388997E-01 a      1302     1    25     2     2\n  2.4682616020968910E+00 a      1303     1    25     2     3\n -1.8878930623582046E-01 a      1304     1    25     2     4\n -9.1881757175628931E-01 a      1305     1    25     2     5\n  1.9786700803029329E+00 a      1306     1    25     2     6\n -9.4413848290810243E-01 a      1307     1    25     2     7\n  2.1251619163837172E+00 a      1308     1    25     2     8\n  3.8955267416819328E-01 a      1309     1    25     2     9\n  1.3018107659419500E+00 a      1310     1    25     2    10\n  2.3087499774432989E+00 a      1311     1    25     2    11\n  2.5795115016945669E-01 a      1312     1    25     2    12\n -1.6666034812488459E+00 a      1313     1    25     2    13\n  2.0825473086891683E-01 a      1314     1    25     2    14\n  1.1805687132848151E+00 a      1315     1    25     2    15\n  1.1111307006896074E+00 a      1316     1    25     2    16\n -1.2643165542388365E-01 a      1317     1    25     2    17\n  6.8542763857622147E-01 a      1318     1    25     2    18\n  3.5068280826709353E-01 a      1319     1    25     2    19\n -1.6700280688212445E+00 a      1320     1    25     2    20\n  4.9734814091044943E-01 a      1321     1    25     2    21\n  4.1767341284761950E-01 a      1322     1    25     2    22\n  2.9323783248311658E-01 a      1323     1    25     2    23\n  2.2626834190168438E-01 a      1324     1    25     2    24\n -7.1660991988367040E-01 a      1325     1    25     2    25\n  1.3758637483672373E-01 b      1326     2     1\n  1.4421949322160369E+01 b      1327     2     2\n  9.0713261326603369E+00 b      1328     2     3\n  1.1511841249204544E+01 b      1329     2     4\n -7.7500988704229545E+00 b      1330     2     5\n  1.0396280766374817E+01 b      1331     2     6\n  6.1319634747306244E+00 b      1332     2     7\n  7.0297632346964081E+00 b      1333     2     8\n -3.0691873623395272E+00 b      1334     2     9\n  3.7785046189711471E+00 b      1335     2    10\n  1.6735187721597125E+01 b      1336     2    11\n -1.0523222070404145E+01 b      1337     2    12\n -2.7517320134642764E+00 b      1338     2    13\n  7.0959353950919049E+00 b      1339     2    14\n -1.0192582964129420E+01 b      1340     2    15\n  8.5318673177438171E+00 b      1341     2    16\n  9.7712264318032246E-02 b      1342     2    17\n  7.4631563981846085E+00 b      1343     2    18\n -1.1671953174503151E+00 b      1344     2    19\n -1.0866785992377450E+00 b      1345     2    20\n  2.6929892144398586E+01 b      1346     2    21\n -3.9871694383739880E+00 b      1347     2    22\n -7.1400875489517119E+00 b      1348     2    23\n  6.5431031297039173E+00 b      1349     2    24\n  6.0535596218419316E+00 b      1350     2    25\n  1.0813259629564518E+00 a      1351     2     1     3     1\n  1.8902818976135820E+00 a      1352     2     2     3     1\n  1.4796302591891799E+00 a      1353     2     3     3     1\n -1.3663303585560327E+00 a      1354     2     4     3     1\n -8.1132039841400672E-01 a      1355     2     5     3     1\n -1.4566723462700406E+00 a      1356     2     6     3     1\n -1.5645527193134390E+00 a      1357     2     7     3     1\n  9.9793248220673436E-01 a      1358     2     8     3     1\n  3.3789557318136407E+00 a      1359     2     9     3     1\n -1.5070870090324426E+00 a      1360     2    10     3     1\n  1.8458738216843664E+00 a      1361     2    11     3     1\n -1.9108593015744817E+00 a      1362     2    12     3     1\n  1.0915211625405057E+00 a      1363     2    13     3     1\n -9.3758728934857027E-01 a      1364     2    14     3     1\n  1.2651854295645006E+00 a      1365     2    15     3     1\n  1.4609042720604604E+00 a      1366     2    16     3     1\n  1.1202623176545652E+00 a      1367     2    17     3     1\n -2.5589140217786355E+00 a      1368     2    18     3     1\n  1.2651286370765947E+01 a      1369     2    19     3     1\n -3.8671862214850711E-01 a      1370     2    20     3     1\n  2.3139934553790695E+00 a      1371     2    21     3     1\n -1.2943576049687842E+00 a      1372     2    22     3     1\n  1.3215992744228617E+00 a      1373     2    23     3     1\n -1.2096599509980557E+00 a      1374     2    24     3     1\n  1.3032629853758171E+00 a      1375     2    25     3     1\n  1.1380307876755417E+01 b      1376     3     1\n"
  },
  {
    "path": "examples/potentials/H2O_BLYP-D3/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -6.5146095852365482E+00 a         1     0     1     1     1\n -5.3637914514036256E+00 a         2     0     1     1     2\n  7.0092912096726030E+00 a         3     0     1     1     3\n  2.2312256619476423E+00 a         4     0     1     1     4\n  5.5143475755302482E+00 a         5     0     1     1     5\n -6.8655157347425515E+00 a         6     0     1     1     6\n -5.1994721977384369E-02 a         7     0     1     1     7\n  2.4041165482729866E+01 a         8     0     1     1     8\n  9.8445774480518864E+00 a         9     0     1     1     9\n  1.5671779769792842E+01 a        10     0     1     1    10\n  3.5619635885363032E-01 a        11     0     1     1    11\n  8.7704696898613790E+00 a        12     0     1     1    12\n -1.6629112052146120E+00 a        13     0     1     1    13\n -1.9511501346762959E+01 a        14     0     1     1    14\n  8.8672960978158670E+00 a        15     0     1     1    15\n  1.1683569177593631E+01 a        16     0     1     1    16\n -5.2927572998046042E+00 a        17     0     1     1    17\n  1.2723741940206974E+01 a        18     0     1     1    18\n -2.9836783422089082E+00 a        19     0     1     1    19\n -3.2636891126777803E+00 a        20     0     1     1    20\n  7.6977163743665153E+00 a        21     0     1     1    21\n -1.1741793539960680E+01 a        22     0     1     1    22\n  7.2921462111598512E+00 a        23     0     1     1    23\n -8.2042823825928046E+00 a        24     0     1     1    24\n  1.4976559026427745E+01 a        25     0     1     1    25\n -4.8710228971752674E+00 a        26     0     2     1     1\n  3.6691249457695378E+00 a        27     0     2     1     2\n -1.7797784990614449E+01 a        28     0     2     1     3\n  1.7633345792588795E+01 a        29     0     2     1     4\n  6.6640632604141743E+00 a        30     0     2     1     5\n  1.1508336029373060E+01 a        31     0     2     1     6\n -5.4665048278000112E+00 a        32     0     2     1     7\n -1.2182042572761588E+01 a        33     0     2     1     8\n -1.3706748134547009E+01 a        34     0     2     1     9\n -2.8556673026738217E+01 a        35     0     2     1    10\n  5.3064108743791154E+00 a        36     0     2     1    11\n  1.4395151977763352E+00 a        37     0     2     1    12\n  5.6311932789676691E+00 a        38     0     2     1    13\n  9.2500309643076062E-01 a        39     0     2     1    14\n  9.2757356151148906E-01 a        40     0     2     1    15\n  6.7490299742362572E+00 a        41     0     2     1    16\n  4.0670851845710736E+00 a        42     0     2     1    17\n  3.8654277675197482E-02 a        43     0     2     1    18\n  1.8141990890097944E+01 a        44     0     2     1    19\n  1.2710130698868356E+01 a        45     0     2     1    20\n -2.4814167787239938E+01 a        46     0     2     1    21\n  9.4239999774205643E+00 a        47     0     2     1    22\n  1.3849456602411003E+01 a        48     0     2     1    23\n -3.1141650716652189E+00 a        49     0     2     1    24\n  6.8423634339613004E+00 a        50     0     2     1    25\n  7.9685346281352798E+00 a        51     0     3     1     1\n  8.2594673321293488E+00 a        52     0     3     1     2\n -5.0088647567502065E+00 a        53     0     3     1     3\n -8.1616776929214794E+00 a        54     0     3     1     4\n -5.6611566560356996E+00 a        55     0     3     1     5\n  1.1012717954947364E+00 a        56     0     3     1     6\n  2.9300652776369480E+00 a        57     0     3     1     7\n -3.7040704387828789E+01 a        58     0     3     1     8\n -1.2769006048802188E+01 a        59     0     3     1     9\n  4.7885654160442845E+00 a        60     0     3     1    10\n -5.0929299923921594E+00 a        61     0     3     1    11\n -1.1639878713586496E+01 a        62     0     3     1    12\n -3.2889336907795377E+00 a        63     0     3     1    13\n  2.0427413777561576E+01 a        64     0     3     1    14\n -1.5780307216101090E+01 a        65     0     3     1    15\n -2.9881260249106244E+01 a        66     0     3     1    16\n  7.6138079548634199E+00 a        67     0     3     1    17\n -2.1104911617782101E+01 a        68     0     3     1    18\n -4.1597786078632950E+00 a        69     0     3     1    19\n  1.7935761922169255E+00 a        70     0     3     1    20\n -3.6976953006020108E+00 a        71     0     3     1    21\n  1.5938522313427564E+01 a        72     0     3     1    22\n -1.7937382996886587E+01 a        73     0     3     1    23\n  2.5317018047944000E+01 a        74     0     3     1    24\n -1.7989815975783220E+01 a        75     0     3     1    25\n  1.7257755447520960E+01 a        76     0     4     1     1\n -5.6030020785676857E+00 a        77     0     4     1     2\n  3.0520432624869450E+01 a        78     0     4     1     3\n -3.0311533134087611E+01 a        79     0     4     1     4\n -1.8613856208555724E+01 a        80     0     4     1     5\n -1.5319496122976641E+01 a        81     0     4     1     6\n  5.8521396013476199E+00 a        82     0     4     1     7\n  2.4393627764526087E+01 a        83     0     4     1     8\n  2.2628512579548275E+01 a        84     0     4     1     9\n  2.1966852294187312E+01 a        85     0     4     1    10\n -1.5473649540693030E+01 a        86     0     4     1    11\n -4.6635217500711663E+00 a        87     0     4     1    12\n -6.5121498854704729E+00 a        88     0     4     1    13\n  1.9532123085522763E+01 a        89     0     4     1    14\n -5.2970288133961203E+00 a        90     0     4     1    15\n  1.0860404563105095E+00 a        91     0     4     1    16\n -2.9707465273114773E+00 a        92     0     4     1    17\n -6.2109749284394802E+00 a        93     0     4     1    18\n -3.0666285020292911E+01 a        94     0     4     1    19\n -1.8271362117369478E+01 a        95     0     4     1    20\n  3.1359789213918248E+01 a        96     0     4     1    21\n -1.1997997111092880E+01 a        97     0     4     1    22\n -2.4886730753412415E+01 a        98     0     4     1    23\n -2.3529458321250454E+00 a        99     0     4     1    24\n -2.0411420737440515E+01 a       100     0     4     1    25\n -1.1477683572733199E+01 a       101     0     5     1     1\n -1.0718993897029907E+01 a       102     0     5     1     2\n -2.3577560835558140E+00 a       103     0     5     1     3\n  3.1103559993688452E+00 a       104     0     5     1     4\n  8.9457064188712341E+00 a       105     0     5     1     5\n -1.3875157042948916E+00 a       106     0     5     1     6\n -8.4798242306447271E+00 a       107     0     5     1     7\n  1.4160278541312966E+01 a       108     0     5     1     8\n  2.9698902968493637E+00 a       109     0     5     1     9\n -2.3276318411264235E+01 a       110     0     5     1    10\n  1.7059940434203615E+01 a       111     0     5     1    11\n -1.0457806397794498E+00 a       112     0     5     1    12\n  6.9496367641789520E+00 a       113     0     5     1    13\n -7.2233286826354464E+00 a       114     0     5     1    14\n  1.2900998992975591E+01 a       115     0     5     1    15\n  2.6974122624415770E+01 a       116     0     5     1    16\n -4.5569426100976616E+00 a       117     0     5     1    17\n  2.2342358245238639E+01 a       118     0     5     1    18\n  1.8036381450727248E+01 a       119     0     5     1    19\n -6.5274747761291776E+00 a       120     0     5     1    20\n  1.4128206374102778E+01 a       121     0     5     1    21\n -1.1620802875331787E+01 a       122     0     5     1    22\n  1.9990531724420329E+01 a       123     0     5     1    23\n -2.4541761694461673E+01 a       124     0     5     1    24\n  8.6633398961125323E+00 a       125     0     5     1    25\n -1.8373952305168952E+01 a       126     0     6     1     1\n  1.4884588336491642E+01 a       127     0     6     1     2\n -2.2740164367923203E+01 a       128     0     6     1     3\n  2.7326838750986951E+01 a       129     0     6     1     4\n  4.9253687083746267E-01 a       130     0     6     1     5\n  1.6509426734279476E+01 a       131     0     6     1     6\n  3.1727401777570172E+00 a       132     0     6     1     7\n -2.3162688628524158E+01 a       133     0     6     1     8\n -1.6185366125427365E+01 a       134     0     6     1     9\n -6.0548005829540932E+00 a       135     0     6     1    10\n  1.6099492185320692E+01 a       136     0     6     1    11\n  1.1438066447389741E+00 a       137     0     6     1    12\n  2.6197228024715424E+00 a       138     0     6     1    13\n -2.8041484145531228E+01 a       139     0     6     1    14\n  7.2285182531536742E+00 a       140     0     6     1    15\n -1.5086744260130120E+01 a       141     0     6     1    16\n -2.7842515015108256E+00 a       142     0     6     1    17\n  9.3352419057443239E+00 a       143     0     6     1    18\n  2.0591423483400369E+01 a       144     0     6     1    19\n  2.3787024286512319E+00 a       145     0     6     1    20\n -2.1899403550259741E+01 a       146     0     6     1    21\n  8.8430115404006955E+00 a       147     0     6     1    22\n  1.7046575498624332E+01 a       148     0     6     1    23\n  1.4339589180893487E+01 a       149     0     6     1    24\n  2.0110760583307130E+01 a       150     0     6     1    25\n  6.4535851457180149E+00 a       151     0     7     1     1\n -5.7608807905124637E-01 a       152     0     7     1     2\n  1.0847398758634283E+00 a       153     0     7     1     3\n -7.9863649115680833E+00 a       154     0     7     1     4\n -1.2839456983675002E+00 a       155     0     7     1     5\n -2.1134185990289649E+00 a       156     0     7     1     6\n  1.1411572006134728E+01 a       157     0     7     1     7\n  2.0696479877273255E+00 a       158     0     7     1     8\n -1.2180935942288924E+00 a       159     0     7     1     9\n  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4.0677982013034103E-01 a      1253     1    20     2     3\n -5.6869165347938358E-02 a      1254     1    20     2     4\n  1.3708362399170841E+00 a      1255     1    20     2     5\n  2.4622983936793545E+00 a      1256     1    20     2     6\n -5.5255290582821743E+00 a      1257     1    20     2     7\n  8.1147195880290512E-01 a      1258     1    20     2     8\n  3.8226590587441849E+00 a      1259     1    20     2     9\n  1.6757628362739045E+00 a      1260     1    20     2    10\n -1.1786707132321166E+00 a      1261     1    20     2    11\n -1.0283375797785133E-01 a      1262     1    20     2    12\n  2.6539878181404575E+00 a      1263     1    20     2    13\n -5.0109087420338083E-01 a      1264     1    20     2    14\n  4.2476521772551101E-01 a      1265     1    20     2    15\n  7.2708655334897365E-01 a      1266     1    20     2    16\n  2.2499540460588494E+00 a      1267     1    20     2    17\n -7.9299928083407079E-01 a      1268     1    20     2    18\n  2.9054613359378485E+00 a      1269     1    20     2    19\n -2.9622239106403386E-01 a      1270     1    20     2    20\n -2.7395573852529429E+00 a      1271     1    20     2    21\n  1.2368302383500276E+00 a      1272     1    20     2    22\n -1.3341610821308172E+00 a      1273     1    20     2    23\n  1.3274930057347895E-01 a      1274     1    20     2    24\n -3.9032257083063199E-01 a      1275     1    20     2    25\n  8.0265236612396684E-01 a      1276     1    21     2     1\n  3.8371510317333424E-01 a      1277     1    21     2     2\n  1.8039273756994709E-01 a      1278     1    21     2     3\n -7.9177515405569954E-01 a      1279     1    21     2     4\n  2.4321876875823274E+00 a      1280     1    21     2     5\n -4.0690873688212792E-01 a      1281     1    21     2     6\n  7.5737495479285366E+00 a      1282     1    21     2     7\n -8.7229674965122883E-01 a      1283     1    21     2     8\n  4.6091381419408730E+00 a      1284     1    21     2     9\n  1.6238927320258667E-01 a      1285     1    21     2    10\n  7.0508008200962080E-01 a      1286     1    21     2    11\n  9.7536837193864279E-01 a      1287     1    21     2    12\n  1.4773267189750643E+00 a      1288     1    21     2    13\n  2.6332601397356409E-01 a      1289     1    21     2    14\n -1.0242988804706432E+00 a      1290     1    21     2    15\n -6.1682430106573227E-01 a      1291     1    21     2    16\n -1.9323457292552909E-01 a      1292     1    21     2    17\n  3.4955789303131057E-01 a      1293     1    21     2    18\n -1.4770140088981005E+00 a      1294     1    21     2    19\n -1.3581149611898353E+00 a      1295     1    21     2    20\n -1.8625326071867450E+00 a      1296     1    21     2    21\n -8.1701318009285789E-02 a      1297     1    21     2    22\n -3.4907764374010952E-01 a      1298     1    21     2    23\n -3.8946220194498993E-01 a      1299     1    21     2    24\n  3.2463904827173612E-01 a      1300     1    21     2    25\n -9.2215531843178422E-01 a      1301     1    22     2     1\n  6.3205059491434512E-01 a      1302     1    22     2     2\n  1.4262091236144845E+00 a      1303     1    22     2     3\n  1.1388524150907597E+00 a      1304     1    22     2     4\n  4.7113932542986174E-02 a      1305     1    22     2     5\n  3.7834400351930402E+00 a      1306     1    22     2     6\n -2.1655713494670432E+00 a      1307     1    22     2     7\n  3.3441406143606073E-01 a      1308     1    22     2     8\n  4.2911736812599584E-02 a      1309     1    22     2     9\n  3.2767577957464294E-01 a      1310     1    22     2    10\n  7.8153379453482247E-02 a      1311     1    22     2    11\n -2.5116426921798141E-01 a      1312     1    22     2    12\n -7.3755653125680698E-01 a      1313     1    22     2    13\n -2.0931105232995884E+00 a      1314     1    22     2    14\n -2.6929825059469399E-02 a      1315     1    22     2    15\n -1.6075813813157286E-02 a      1316     1    22     2    16\n -7.0825919750799193E-01 a      1317     1    22     2    17\n  2.2568246387670681E+00 a      1318     1    22     2    18\n  3.9588736030959587E-01 a      1319     1    22     2    19\n  4.2624612770735382E-01 a      1320     1    22     2    20\n -4.0958468641716111E-01 a      1321     1    22     2    21\n -6.3171558415345364E-01 a      1322     1    22     2    22\n -2.8044715589555813E+00 a      1323     1    22     2    23\n -1.0864190520960098E+00 a      1324     1    22     2    24\n -2.0344084696846618E+00 a      1325     1    22     2    25\n -2.1420934071828127E-01 a      1326     1    23     2     1\n -9.8928855125513915E-01 a      1327     1    23     2     2\n -1.6669737594410705E-01 a      1328     1    23     2     3\n -5.5264335713868229E-01 a      1329     1    23     2     4\n  5.0521334630749426E-01 a      1330     1    23     2     5\n  7.5607842666614622E-01 a      1331     1    23     2     6\n -2.6557620067795473E+00 a      1332     1    23     2     7\n -7.4154353359519720E-01 a      1333     1    23     2     8\n  1.0953745989813461E+00 a      1334     1    23     2     9\n -6.5977706842014094E-01 a      1335     1    23     2    10\n -2.9513942779700719E+00 a      1336     1    23     2    11\n -7.2761443095050726E-01 a      1337     1    23     2    12\n -4.1239283541872079E-01 a      1338     1    23     2    13\n -4.8752598731045388E-01 a      1339     1    23     2    14\n  1.2981229940516952E+00 a      1340     1    23     2    15\n  8.6865726346287442E-01 a      1341     1    23     2    16\n -1.8321287537010453E-01 a      1342     1    23     2    17\n  1.4693277183657811E+00 a      1343     1    23     2    18\n  9.9120089476350343E-02 a      1344     1    23     2    19\n  2.3698240958882402E-01 a      1345     1    23     2    20\n  1.1497545291328537E-01 a      1346     1    23     2    21\n  6.8744895454400629E-02 a      1347     1    23     2    22\n -2.3388918594008836E+00 a      1348     1    23     2    23\n -2.7995217409354278E-01 a      1349     1    23     2    24\n -2.6671192567481816E-01 a      1350     1    23     2    25\n  4.1579701164457133E-01 a      1351     1    24     2     1\n  1.9085919808345636E-01 a      1352     1    24     2     2\n -1.7036930756001745E+00 a      1353     1    24     2     3\n -9.5396064917158419E-01 a      1354     1    24     2     4\n  7.6770333026909554E-01 a      1355     1    24     2     5\n  6.5055769836332660E+00 a      1356     1    24     2     6\n  3.0254363580567945E-01 a      1357     1    24     2     7\n -2.9501544039160450E+00 a      1358     1    24     2     8\n  2.2743163985362425E+00 a      1359     1    24     2     9\n -8.9772278115791793E-01 a      1360     1    24     2    10\n -5.9327961976841062E+00 a      1361     1    24     2    11\n -2.4947344965200888E+00 a      1362     1    24     2    12\n  4.0408352274434550E-01 a      1363     1    24     2    13\n -8.8734359115183226E-01 a      1364     1    24     2    14\n  2.3800082987761373E+00 a      1365     1    24     2    15\n -4.6968293336912342E-01 a      1366     1    24     2    16\n  1.9863413476705900E+00 a      1367     1    24     2    17\n -2.0715974078643354E-01 a      1368     1    24     2    18\n  4.3130840960665511E+00 a      1369     1    24     2    19\n  2.2585960801946534E+00 a      1370     1    24     2    20\n  6.0258470358001759E-01 a      1371     1    24     2    21\n  8.5279532985660955E-01 a      1372     1    24     2    22\n -4.1961097675151509E+00 a      1373     1    24     2    23\n -6.6614246676873168E-01 a      1374     1    24     2    24\n  2.6973082910471597E+00 a      1375     1    24     2    25\n -1.1481141390670786E+00 a      1376     1    25     2     1\n -6.5599423591676631E-01 a      1377     1    25     2     2\n -1.0957346863951549E+00 a      1378     1    25     2     3\n  1.6311890074352331E-01 a      1379     1    25     2     4\n -2.4266980459995660E+00 a      1380     1    25     2     5\n  1.6282473857758801E+00 a      1381     1    25     2     6\n -3.3958510838850886E+00 a      1382     1    25     2     7\n  1.0064768107489113E+00 a      1383     1    25     2     8\n  2.4568872805360757E+00 a      1384     1    25     2     9\n -9.9177771797118452E-01 a      1385     1    25     2    10\n -3.9241063847110935E-01 a      1386     1    25     2    11\n -4.2801331792553887E-01 a      1387     1    25     2    12\n -2.4404209563233747E-01 a      1388     1    25     2    13\n -1.5585000830623963E-01 a      1389     1    25     2    14\n -3.9964675925959914E-01 a      1390     1    25     2    15\n  1.3411627072187479E-01 a      1391     1    25     2    16\n  1.3067235823245975E+00 a      1392     1    25     2    17\n -1.8746987271186907E-01 a      1393     1    25     2    18\n  1.9173149443775008E+00 a      1394     1    25     2    19\n  9.7013398783726446E-01 a      1395     1    25     2    20\n  1.1362171702208577E+00 a      1396     1    25     2    21\n  9.2420162373548401E-02 a      1397     1    25     2    22\n -2.1763035938687764E-01 a      1398     1    25     2    23\n -8.2208291395382393E-01 a      1399     1    25     2    24\n  4.4515124288156260E-01 a      1400     1    25     2    25\n  6.9143337917218195E-01 b      1401     2     1\n  1.0551696648380711E+00 b      1402     2     2\n -7.1284028042990686E+00 b      1403     2     3\n -3.0892516409710526E+00 b      1404     2     4\n  2.7076652984658640E+00 b      1405     2     5\n -1.2068988030476619E+01 b      1406     2     6\n  3.1518150807458762E+00 b      1407     2     7\n -3.6338872018257420E+00 b      1408     2     8\n  1.0436125597796881E+00 b      1409     2     9\n  2.7898789567425584E+00 b      1410     2    10\n -7.1859836949700107E-01 b      1411     2    11\n  3.4223120483061686E+00 b      1412     2    12\n -1.6577813338960852E+00 b      1413     2    13\n  3.9842415619541587E+00 b      1414     2    14\n  2.8868638398327349E+00 b      1415     2    15\n -1.9353594735856796E+00 b      1416     2    16\n -9.4660621922591864E-02 b      1417     2    17\n -2.5384177030817812E+00 b      1418     2    18\n -3.2323713375133587E+00 b      1419     2    19\n -2.4337638518380339E-01 b      1420     2    20\n  2.2472742663678882E+00 b      1421     2    21\n -1.8092011571500699E+00 b      1422     2    22\n  1.0762334579817698E+00 b      1423     2    23\n  1.7571177390200005E-01 b      1424     2    24\n  1.7009588578398132E+00 b      1425     2    25\n -1.3523661993776510E+00 a      1426     2     1     3     1\n -9.5836280529874152E-01 a      1427     2     2     3     1\n -1.8713779493642639E+00 a      1428     2     3     3     1\n -1.5637950872968045E+00 a      1429     2     4     3     1\n  1.5004245802213869E+00 a      1430     2     5     3     1\n  1.6826845143442204E+00 a      1431     2     6     3     1\n  4.6852223814437044E-01 a      1432     2     7     3     1\n -1.6801012476753752E+00 a      1433     2     8     3     1\n -9.3652242568390665E-02 a      1434     2     9     3     1\n  5.4546329088716918E+00 a      1435     2    10     3     1\n -2.1911301915378916E+00 a      1436     2    11     3     1\n  3.0940532177783333E+00 a      1437     2    12     3     1\n -3.5925104461479922E+00 a      1438     2    13     3     1\n  1.8278532967693084E+00 a      1439     2    14     3     1\n  1.5409914384095009E+00 a      1440     2    15     3     1\n -1.7316884368691656E+00 a      1441     2    16     3     1\n -1.1826684335808630E+00 a      1442     2    17     3     1\n  8.7282231998279702E-01 a      1443     2    18     3     1\n  3.9046276695423399E-01 a      1444     2    19     3     1\n -2.1658886655726262E+00 a      1445     2    20     3     1\n -1.1474306448805338E+00 a      1446     2    21     3     1\n  1.2719780007835249E+00 a      1447     2    22     3     1\n -5.1823650932486531E-01 a      1448     2    23     3     1\n -2.2807058809518646E+00 a      1449     2    24     3     1\n  8.0748470179562448E-01 a      1450     2    25     3     1\n  5.6901539382409432E+00 b      1451     3     1\n"
  },
  {
    "path": "examples/potentials/H2O_RPBE/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5518720818658409E+01\nconv_energy   1.8840152379924052E+02\nconv_length   4.5523277791142096E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   4              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 7\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               25             # Write energy comparison.\nwrite_trainforces               25             # Write force comparison.\nwrite_weights_epoch                            # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/potentials/H2O_RPBE/nnp-train.log.0000",
    "content": "\n*** SETUP: MPI ****************************************************************\n\nNumber of processors: 16\nProcess 1 of 16 (rank 0): n10-003\nProcess 2 of 16 (rank 1): n10-003\nProcess 3 of 16 (rank 2): n10-003\nProcess 4 of 16 (rank 3): n10-003\nProcess 5 of 16 (rank 4): n10-003\nProcess 6 of 16 (rank 5): n10-003\nProcess 7 of 16 (rank 6): n10-003\nProcess 8 of 16 (rank 7): n10-003\nProcess 9 of 16 (rank 8): n10-003\nProcess 10 of 16 (rank 9): n10-003\nProcess 11 of 16 (rank 10): n10-003\nProcess 12 of 16 (rank 11): n10-003\nProcess 13 of 16 (rank 12): n10-003\nProcess 14 of 16 (rank 13): n10-003\nProcess 15 of 16 (rank 14): n10-003\nProcess 16 of 16 (rank 15): n10-003\n*******************************************************************************\n\n*******************************************************************************\n\n   NNP LIBRARY v0.1.0\n   ------------------\n\nGit branch  : master\nGit revision: ff23516 (ff235161e90cd94280c0df259129e8d4e5e07007)\n\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 167 lines.\nFound 102 lines with keywords.\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is used.\nMean energy per atom     :  -2.5518720818658409E+01\nConversion factor energy :   1.8840152379924052E+02\nConversion factor length :   4.5523277791142096E+00\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  H (  1)\nElement  1:  O (  8)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:   0.00000000E+00\nElement  1:   0.00000000E+00\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_TANHU (2)\nf(r) = tanh^3(1 - r/rc)\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  H  2  H    4.825E-05 0.000E+00         5.463E+01  2 0.00    98\n   2  H  2  O    4.825E-05 0.000E+00         5.463E+01  2 0.00   108\n   3  H  2  H    4.825E-04 0.000E+00         5.463E+01  2 0.00    99\n   4  H  2  O    4.825E-04 0.000E+00         5.463E+01  2 0.00   109\n   5  H  2  H    1.448E-03 0.000E+00         5.463E+01  2 0.00   100\n   6  H  2  O    1.448E-03 0.000E+00         5.463E+01  2 0.00   110\n   7  H  2  H    2.895E-03 0.000E+00         5.463E+01  2 0.00   101\n   8  H  2  O    2.895E-03 0.000E+00         5.463E+01  2 0.00   111\n   9  H  2  O    7.238E-03 4.097E+00         5.463E+01  2 0.00   112\n  10  H  2  H    7.238E-03 8.649E+00         5.463E+01  2 0.00   102\n  11  H  2  O    1.448E-02 4.097E+00         5.463E+01  2 0.00   113\n  12  H  2  H    1.448E-02 8.649E+00         5.463E+01  2 0.00   103\n  13  H  2  O    2.895E-02 4.097E+00         5.463E+01  2 0.00   114\n  14  H  2  H    2.895E-02 8.649E+00         5.463E+01  2 0.00   104\n  15  H  2  O    7.238E-02 4.097E+00         5.463E+01  2 0.00   115\n  16  H  2  H    7.238E-02 8.649E+00         5.463E+01  2 0.00   105\n  17  H  3  O  O 4.825E-05 0.000E+00 -1  4.0 5.463E+01  2 0.00   162\n  18  H  3  O  O 4.825E-05 0.000E+00  1  4.0 5.463E+01  2 0.00   161\n  19  H  3  H  O 4.825E-04 0.000E+00 -1  4.0 5.463E+01  2 0.00   152\n  20  H  3  H  O 4.825E-04 0.000E+00  1  4.0 5.463E+01  2 0.00   150\n  21  H  3  H  O 1.448E-03 0.000E+00 -1  1.0 5.463E+01  2 0.00   147\n  22  H  3  O  O 1.448E-03 0.000E+00 -1  1.0 5.463E+01  2 0.00   160\n  23  H  3  H  O 1.448E-03 0.000E+00  1  1.0 5.463E+01  2 0.00   145\n  24  H  3  O  O 1.448E-03 0.000E+00  1  1.0 5.463E+01  2 0.00   159\n  25  H  3  H  O 3.378E-03 0.000E+00 -1  1.0 5.463E+01  2 0.00   142\n  26  H  3  H  O 3.378E-03 0.000E+00  1  1.0 5.463E+01  2 0.00   140\n  27  H  3  H  O 9.651E-03 0.000E+00  1  1.0 5.463E+01  2 0.00   137\n-------------------------------------------------------------------------------\nShort range atomic symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  O  2  H    4.825E-05 0.000E+00         5.463E+01  2 0.00   117\n   2  O  2  O    4.825E-05 0.000E+00         5.463E+01  2 0.00   127\n   3  O  2  H    4.825E-04 0.000E+00         5.463E+01  2 0.00   118\n   4  O  2  O    4.825E-04 0.000E+00         5.463E+01  2 0.00   128\n   5  O  2  H    1.448E-03 0.000E+00         5.463E+01  2 0.00   119\n   6  O  2  O    1.448E-03 0.000E+00         5.463E+01  2 0.00   129\n   7  O  2  H    2.895E-03 0.000E+00         5.463E+01  2 0.00   120\n   8  O  2  O    2.895E-03 0.000E+00         5.463E+01  2 0.00   130\n   9  O  2  H    7.238E-03 4.097E+00         5.463E+01  2 0.00   121\n  10  O  2  O    7.238E-03 1.821E+01         5.463E+01  2 0.00   131\n  11  O  2  H    1.448E-02 4.097E+00         5.463E+01  2 0.00   122\n  12  O  2  O    1.448E-02 1.821E+01         5.463E+01  2 0.00   132\n  13  O  2  H    2.895E-02 4.097E+00         5.463E+01  2 0.00   123\n  14  O  2  O    2.895E-02 1.821E+01         5.463E+01  2 0.00   133\n  15  O  2  H    7.238E-02 4.097E+00         5.463E+01  2 0.00   124\n  16  O  2  O    7.238E-02 1.821E+01         5.463E+01  2 0.00   134\n  17  O  3  H  O 4.825E-05 0.000E+00 -1  4.0 5.463E+01  2 0.00   157\n  18  O  3  O  O 4.825E-05 0.000E+00 -1  4.0 5.463E+01  2 0.00   167\n  19  O  3  H  O 4.825E-05 0.000E+00  1  4.0 5.463E+01  2 0.00   156\n  20  O  3  O  O 4.825E-05 0.000E+00  1  4.0 5.463E+01  2 0.00   166\n  21  O  3  H  H 4.825E-04 0.000E+00 -1  4.0 5.463E+01  2 0.00   151\n  22  O  3  H  H 4.825E-04 0.000E+00  1  4.0 5.463E+01  2 0.00   149\n  23  O  3  H  H 1.448E-03 0.000E+00 -1  1.0 5.463E+01  2 0.00   146\n  24  O  3  H  O 1.448E-03 0.000E+00 -1  1.0 5.463E+01  2 0.00   155\n  25  O  3  O  O 1.448E-03 0.000E+00 -1  1.0 5.463E+01  2 0.00   165\n  26  O  3  H  H 1.448E-03 0.000E+00  1  1.0 5.463E+01  2 0.00   144\n  27  O  3  H  O 1.448E-03 0.000E+00  1  1.0 5.463E+01  2 0.00   154\n  28  O  3  O  O 1.448E-03 0.000E+00  1  1.0 5.463E+01  2 0.00   164\n  29  O  3  H  H 3.378E-03 0.000E+00 -1  1.0 5.463E+01  2 0.00   141\n  30  O  3  H  H 3.378E-03 0.000E+00  1  1.0 5.463E+01  2 0.00   139\n-------------------------------------------------------------------------------\nMinimum cutoff radius for element  H: 54.627933\nMinimum cutoff radius for element  O: 54.627933\nMaximum cutoff radius (global)      : 54.627933\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function group index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  H  2  H            *         *         5.463E+01  2 0.00     *    *    *  \n   -  -  -  -    4.825E-05 0.000E+00                 -  -    -    97    1    1  \n   -  -  -  -    4.825E-04 0.000E+00                 -  -    -    98    2    3  \n   -  -  -  -    1.448E-03 0.000E+00                 -  -    -    99    3    5  \n   -  -  -  -    2.895E-03 0.000E+00                 -  -    -   100    4    7  \n   -  -  -  -    7.238E-03 8.649E+00                 -  -    -   101    5   10  \n   -  -  -  -    1.448E-02 8.649E+00                 -  -    -   102    6   12  \n   -  -  -  -    2.895E-02 8.649E+00                 -  -    -   103    7   14  \n   -  -  -  -    7.238E-02 8.649E+00                 -  -    -   104    8   16  \n   2  H  2  O            *         *         5.463E+01  2 0.00     *    *    *  \n   -  -  -  -    4.825E-05 0.000E+00                 -  -    -   107    1    2  \n   -  -  -  -    4.825E-04 0.000E+00                 -  -    -   108    2    4  \n   -  -  -  -    1.448E-03 0.000E+00                 -  -    -   109    3    6  \n   -  -  -  -    2.895E-03 0.000E+00                 -  -    -   110    4    8  \n   -  -  -  -    7.238E-03 4.097E+00                 -  -    -   111    5    9  \n   -  -  -  -    1.448E-02 4.097E+00                 -  -    -   112    6   11  \n   -  -  -  -    2.895E-02 4.097E+00                 -  -    -   113    7   13  \n   -  -  -  -    7.238E-02 4.097E+00                 -  -    -   114    8   15  \n   3  H  3  H  O         *         *  *    * 5.463E+01  2 0.00     *    *    * *\n   -  -  -  -  - 4.825E-04 0.000E+00 -1  4.0         -  -    -   151    1   19 1\n   -  -  -  -  - 4.825E-04 0.000E+00  1  4.0         -  -    -   149    2   20 0\n   -  -  -  -  - 1.448E-03 0.000E+00 -1  1.0         -  -    -   146    3   21 1\n   -  -  -  -  - 1.448E-03 0.000E+00  1  1.0         -  -    -   144    4   23 0\n   -  -  -  -  - 3.378E-03 0.000E+00 -1  1.0         -  -    -   141    5   25 1\n   -  -  -  -  - 3.378E-03 0.000E+00  1  1.0         -  -    -   139    6   26 0\n   -  -  -  -  - 9.651E-03 0.000E+00  1  1.0         -  -    -   136    7   27 1\n   4  H  3  O  O         *         *  *    * 5.463E+01  2 0.00     *    *    * *\n   -  -  -  -  - 4.825E-05 0.000E+00 -1  4.0         -  -    -   161    1   17 1\n   -  -  -  -  - 4.825E-05 0.000E+00  1  4.0         -  -    -   160    2   18 0\n   -  -  -  -  - 1.448E-03 0.000E+00 -1  1.0         -  -    -   159    3   22 1\n   -  -  -  -  - 1.448E-03 0.000E+00  1  1.0         -  -    -   158    4   24 0\n-------------------------------------------------------------------------------\nShort range atomic symmetry function groups element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  O  2  H            *         *         5.463E+01  2 0.00     *    *    *  \n   -  -  -  -    4.825E-05 0.000E+00                 -  -    -   116    1    1  \n   -  -  -  -    4.825E-04 0.000E+00                 -  -    -   117    2    3  \n   -  -  -  -    1.448E-03 0.000E+00                 -  -    -   118    3    5  \n   -  -  -  -    2.895E-03 0.000E+00                 -  -    -   119    4    7  \n   -  -  -  -    7.238E-03 4.097E+00                 -  -    -   120    5    9  \n   -  -  -  -    1.448E-02 4.097E+00                 -  -    -   121    6   11  \n   -  -  -  -    2.895E-02 4.097E+00                 -  -    -   122    7   13  \n   -  -  -  -    7.238E-02 4.097E+00                 -  -    -   123    8   15  \n   2  O  2  O            *         *         5.463E+01  2 0.00     *    *    *  \n   -  -  -  -    4.825E-05 0.000E+00                 -  -    -   126    1    2  \n   -  -  -  -    4.825E-04 0.000E+00                 -  -    -   127    2    4  \n   -  -  -  -    1.448E-03 0.000E+00                 -  -    -   128    3    6  \n   -  -  -  -    2.895E-03 0.000E+00                 -  -    -   129    4    8  \n   -  -  -  -    7.238E-03 1.821E+01                 -  -    -   130    5   10  \n   -  -  -  -    1.448E-02 1.821E+01                 -  -    -   131    6   12  \n   -  -  -  -    2.895E-02 1.821E+01                 -  -    -   132    7   14  \n   -  -  -  -    7.238E-02 1.821E+01                 -  -    -   133    8   16  \n   3  O  3  H  H         *         *  *    * 5.463E+01  2 0.00     *    *    * *\n   -  -  -  -  - 4.825E-04 0.000E+00 -1  4.0         -  -    -   150    1   21 1\n   -  -  -  -  - 4.825E-04 0.000E+00  1  4.0         -  -    -   148    2   22 0\n   -  -  -  -  - 1.448E-03 0.000E+00 -1  1.0         -  -    -   145    3   23 1\n   -  -  -  -  - 1.448E-03 0.000E+00  1  1.0         -  -    -   143    4   26 0\n   -  -  -  -  - 3.378E-03 0.000E+00 -1  1.0         -  -    -   140    5   29 1\n   -  -  -  -  - 3.378E-03 0.000E+00  1  1.0         -  -    -   138    6   30 0\n   4  O  3  H  O         *         *  *    * 5.463E+01  2 0.00     *    *    * *\n   -  -  -  -  - 4.825E-05 0.000E+00 -1  4.0         -  -    -   156    1   17 1\n   -  -  -  -  - 4.825E-05 0.000E+00  1  4.0         -  -    -   155    2   19 0\n   -  -  -  -  - 1.448E-03 0.000E+00 -1  1.0         -  -    -   154    3   24 1\n   -  -  -  -  - 1.448E-03 0.000E+00  1  1.0         -  -    -   153    4   27 0\n   5  O  3  O  O         *         *  *    * 5.463E+01  2 0.00     *    *    * *\n   -  -  -  -  - 4.825E-05 0.000E+00 -1  4.0         -  -    -   166    1   18 1\n   -  -  -  -  - 4.825E-05 0.000E+00  1  4.0         -  -    -   165    2   20 0\n   -  -  -  -  - 1.448E-03 0.000E+00 -1  1.0         -  -    -   164    3   25 1\n   -  -  -  -  - 1.448E-03 0.000E+00  1  1.0         -  -    -   163    4   28 0\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic short range NN for element  H :\nNumber of weights    :   1325\nNumber of biases     :     51\nNumber of connections:   1376\nArchitecture       27   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  O :\nNumber of weights    :   1400\nNumber of biases     :     51\nNumber of connections:   1451\nArchitecture       30   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALECENTER (3)\nGs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  3.44E-01  9.62E+00  2.17E+00  7.42E-01  1.08E-01  0.00  1.00 3\n   2  3.45E-01  5.00E+00  1.28E+00  3.71E-01  2.15E-01  0.00  1.00 3\n   3  2.85E-01  7.14E+00  1.58E+00  5.51E-01  1.46E-01  0.00  1.00 3\n   4  3.21E-01  3.77E+00  9.83E-01  2.75E-01  2.90E-01  0.00  1.00 3\n   5  2.18E-01  4.15E+00  8.74E-01  3.18E-01  2.55E-01  0.00  1.00 3\n   6  2.90E-01  2.27E+00  6.32E-01  1.58E-01  5.06E-01  0.00  1.00 3\n   7  1.59E-01  2.23E+00  4.41E-01  1.67E-01  4.83E-01  0.00  1.00 3\n   8  2.46E-01  1.32E+00  4.16E-01  8.46E-02  9.31E-01  0.00  1.00 3\n   9  2.39E-01  9.48E-01  3.59E-01  5.47E-02  1.41E+00  0.00  1.00 3\n  10  2.17E-01  2.76E+00  5.22E-01  2.09E-01  3.93E-01  0.00  1.00 3\n  11  1.51E-01  5.56E-01  2.67E-01  2.64E-02  2.47E+00  0.00  1.00 3\n  12  9.77E-02  1.73E+00  2.90E-01  1.18E-01  6.14E-01  0.00  1.00 3\n  13  6.54E-02  3.45E-01  1.85E-01  1.98E-02  3.57E+00  0.00  1.00 3\n  14  2.42E-02  9.13E-01  1.50E-01  5.35E-02  1.13E+00  0.00  1.00 3\n  15  2.92E-03  2.70E-01  7.67E-02  1.89E-02  3.75E+00  0.00  1.00 3\n  16  3.21E-04  2.88E-01  4.62E-02  2.40E-02  3.48E+00  0.00  1.00 3\n  17  5.04E-06  1.38E-01  1.70E-02  1.02E-02  7.22E+00  0.00  1.00 3\n  18  1.04E-05  5.83E-01  2.25E-02  3.82E-02  1.71E+00  0.00  1.00 3\n  19  1.10E-05  2.16E-01  1.63E-02  1.44E-02  4.63E+00  0.00  1.00 3\n  20  2.72E-02  1.69E+00  1.40E-01  1.12E-01  6.03E-01  0.00  1.00 3\n  21  2.76E-03  3.16E-01  1.76E-02  2.03E-02  3.19E+00  0.00  1.00 3\n  22  8.60E-08  1.03E-01  6.07E-03  6.72E-03  9.75E+00  0.00  1.00 3\n  23  2.96E-02  9.16E-01  7.88E-02  5.87E-02  1.13E+00  0.00  1.00 3\n  24  8.20E-08  1.58E-01  4.42E-03  9.92E-03  6.33E+00  0.00  1.00 3\n  25  6.37E-04  5.92E-02  3.62E-03  3.33E-03  1.71E+01  0.00  1.00 3\n  26  8.57E-03  1.94E-01  2.38E-02  1.11E-02  5.39E+00  0.00  1.00 3\n  27  2.12E-04  9.97E-03  2.06E-03  6.01E-04  1.03E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  7.48E-01  1.00E+01  2.56E+00  7.41E-01  1.08E-01  0.00  1.00 3\n   2  2.84E-02  4.62E+00  9.20E-01  3.67E-01  2.18E-01  0.00  1.00 3\n   3  6.77E-01  7.53E+00  1.97E+00  5.48E-01  1.46E-01  0.00  1.00 3\n   4  1.17E-02  3.39E+00  6.27E-01  2.70E-01  2.96E-01  0.00  1.00 3\n   5  5.93E-01  4.54E+00  1.26E+00  3.14E-01  2.54E-01  0.00  1.00 3\n   6  1.65E-03  1.89E+00  2.91E-01  1.51E-01  5.29E-01  0.00  1.00 3\n   7  5.23E-01  2.62E+00  8.33E-01  1.65E-01  4.78E-01  0.00  1.00 3\n   8  8.96E-05  9.36E-01  1.06E-01  7.24E-02  1.07E+00  0.00  1.00 3\n   9  5.19E-01  1.85E+00  7.18E-01  1.01E-01  7.49E-01  0.00  1.00 3\n  10  1.82E-04  2.91E+00  4.50E-01  2.48E-01  3.43E-01  0.00  1.00 3\n  11  3.53E-01  1.07E+00  5.34E-01  4.55E-02  1.39E+00  0.00  1.00 3\n  12  1.25E-06  2.53E+00  3.00E-01  2.18E-01  3.96E-01  0.00  1.00 3\n  13  1.60E-01  6.63E-01  3.71E-01  3.07E-02  1.99E+00  0.00  1.00 3\n  14  7.07E-11  2.30E+00  1.69E-01  1.89E-01  4.34E-01  0.00  1.00 3\n  15  9.56E-03  4.13E-01  1.53E-01  2.81E-02  2.48E+00  0.00  1.00 3\n  16  1.77E-23  2.04E+00  5.26E-02  1.43E-01  4.91E-01  0.00  1.00 3\n  17  6.31E-06  3.43E-01  1.59E-02  2.21E-02  2.91E+00  0.00  1.00 3\n  18  2.56E-09  5.63E-02  9.14E-04  3.37E-03  1.78E+01  0.00  1.00 3\n  19  4.04E-04  3.02E+00  1.93E-01  2.05E-01  3.31E-01  0.00  1.00 3\n  20  4.03E-06  4.99E-01  1.20E-02  3.20E-02  2.00E+00  0.00  1.00 3\n  21  3.77E-03  2.67E-01  2.99E-02  1.75E-02  3.79E+00  0.00  1.00 3\n  22  2.01E-03  1.42E+00  7.21E-02  9.41E-02  7.07E-01  0.00  1.00 3\n  23  1.86E-02  4.08E-01  4.76E-02  2.59E-02  2.57E+00  0.00  1.00 3\n  24  1.92E-07  2.33E-01  6.84E-03  1.46E-02  4.29E+00  0.00  1.00 3\n  25  4.90E-10  3.53E-02  4.06E-04  2.05E-03  2.83E+01  0.00  1.00 3\n  26  1.07E-02  8.22E-01  4.88E-02  5.34E-02  1.23E+00  0.00  1.00 3\n  27  2.91E-06  7.86E-01  3.51E-02  5.10E-02  1.27E+00  0.00  1.00 3\n  28  3.98E-09  9.84E-02  1.16E-03  5.80E-03  1.02E+01  0.00  1.00 3\n  29  5.99E-03  9.93E-02  1.60E-02  5.57E-03  1.07E+01  0.00  1.00 3\n  30  3.37E-03  1.55E-01  1.14E-02  8.99E-03  6.60E+00  0.00  1.00 3\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 0\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** SETUP: RANDOM NUMBER GENERATOR ********************************************\n\nRandom number generator seed: 7\nSeed for rank 0: 7\nSeed for rank 1: 327741615\nSeed for rank 2: 976413892\nSeed for rank 3: 3349725721\nSeed for rank 4: 1369975286\nSeed for rank 5: 1882953283\nSeed for rank 6: 4201435347\nSeed for rank 7: 3107259287\nSeed for rank 8: 1956722279\nSeed for rank 9: 4200432988\nSeed for rank 10: 1322904761\nSeed for rank 11: 2312822158\nSeed for rank 12: 1133316631\nSeed for rank 13: 2152296008\nSeed for rank 14: 372560217\nSeed for rank 15: 309457262\nSeed for global RNG: 1801189930\n*******************************************************************************\n\n*** STRUCTURE DISTRIBUTION ****************************************************\n\nReading configurations from data file: input.data.\nNumber of structures per processor: 453 (6) or 454 (10)\nDistributed 7258 structures, 123689687 bytes (117.96 MiB) transferred.\nNumber of local structures: 453\n*******************************************************************************\n\n*** DEFINE TRAINING/TEST SETS *************************************************\n\nDesired test set ratio      : 0.100000\nTotal number of energies    : 7258\nNumber of training energies : 6537\nNumber of test     energies : 721\nNumber of training forces   : 1572390\nNumber of test     forces   : 192114\nActual test set fraction    : 0.099339\n*******************************************************************************\n\n*** WRITE TRAINING/TEST SETS **************************************************\n\nWriting training/test set to files:\n - train.data\n - test.data\n*******************************************************************************\n\n*** WEIGHT INITIALIZATION *****************************************************\n\nInitial weights selected randomly in interval [-1.000000, 1.000000).\nWeights modified accoring to Glorot Bengio scheme.\nBiases set to zero.\n*******************************************************************************\n\n*** SETUP: TRAINING ***********************************************************\n\nForces will be used for training.\nForce update weight:   1.00E+01\nWeight update via Kalman filter selected: updaterType::UT_KALMANFILTER (1)\nMulti-stream Kalman filter training, update on rank 0, partial X calculation selected: ParallelMode::PM_MSEKFR0PX (4)\nNumber of streams       : 16\nStream of this processor: 0\nCombined updater for all elements selected: UpdateStrategy::US_COMBINED (0)\nNumber of weight updaters    : 1\nTotal fit parameters         : 2827\nSelection mode starting with epoch 0:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 1.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\n-------------------------------------------------------------------------------\nSymmetry function memory is reused (HIGH MEMORY USAGE!).\nTraining will be stopped after 25 epochs.\nEnergy comparison will be written every 25 epochs.\nForce comparison will be written every 25 epochs.\nWeights will be written every 1 epochs.\nNeuron statistics will be written every 5 epochs.\nUp to epoch 10 neuron statistics will be written every epoch.\nTraining log with update information will be written to: train-log.out.\n-------------------------------------------------------------------------------\nFraction of energies used per epoch:    1.0000\nFraction of forces used per epoch  :    0.0410\nProjected energy updates per epoch :     409 (  9.2%)\nProjected forces updates per epoch :    4029 ( 90.8%)\nTotal projected updates per epoch  :    4438\nMulti-stream training uses 16 energies/forces per weight update.\nqtau is divided by number of projected updates per epoch.\netatau is divided by number of projected updates per epoch.\n-------------------------------------------------------------------------------\nCombined weight updater:\n-------------------------------------------------------------------------------\nKalmanType::KT_STANDARD (0)\nsizeState       = 2827\nsizeObservation = 16\nepsilon         =   1.0000E-02\nq0              =   1.0000E-02\nqtau            =   5.1872E-04\nqmin            =   1.0000E-06\neta0            =   1.0000E-02\netatau          =   5.1872E-04\netamax          =   1.0000E+00\nKalmanParallel::KP_PRECALCX (2)\nOpenMP threads used: 1\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** CALCULATE NEIGHBOR LISTS **************************************************\n\nCalculating neighbor lists for all structures.\nCutoff radius for neighbor lists: 54.627933\n*******************************************************************************\n\n*** TRAINING LOOP *************************************************************\n\nThe training loop output covers different RMSEs, update and\ntiming information. The following quantities are organized\naccording to the matrix scheme below:\n-------------------------------------------------------------------\nep ............ Epoch.\nEtrain_phys ... RMSE of training energies per atom (p. u.).\nEtest_phys .... RMSE of test     energies per atom (p. u.).\nEtrain_int .... RMSE of training energies per atom (i. u.).\nEtest_int ..... RMSE of test     energies per atom (i. u.).\nFtrain_phys ... RMSE of training forces (p. u.).\nFtest_phys .... RMSE of test     forces (p. u.).\nFtrain_int .... RMSE of training forces (i. u.).\nFtest_int ..... RMSE of test     forces (i. u.).\nE_count ....... Number of energy updates.\nF_count ....... Number of force  updates.\ncount ......... Total number of updates.\nt_train ....... Time for training (seconds).\nt_rmse ........ Time for RMSE calculation (seconds).\nt_epoch ....... Total time for this epoch (seconds).\nt_tot ......... Total time for all epochs (seconds).\nAbbreviations:\n  p. u. = physical units.\n  i. u. = internal units.\nNote: RMSEs in internal units (columns 5 + 6) are only present \n      if data set normalization is used.\n-------------------------------------------------------------------\n     1    2             3             4             5             6\nenergy   ep   Etrain_phys    Etest_phys    Etrain_int     Etest_int\nforces   ep   Ftrain_phys    Ftest_phys    Ftrain_int     Ftest_int\nupdate   ep       E_count       F_count         count\ntiming   ep       t_train        t_rmse       t_epoch         t_tot\n-------------------------------------------------------------------\nENERGY    0   5.11284E-03   3.31443E-03   9.63266E-01   6.24444E-01\nFORCES    0   2.43124E-02   2.50591E-02   1.00619E+00   1.03709E+00\nTIMING    0          0.00         28.61         28.64         28.64\n------\nENERGY    1   2.32112E-04   2.11221E-04   4.37302E-02   3.97943E-02\nFORCES    1   9.08384E-04   8.99678E-04   3.75942E-02   3.72339E-02\nUPDATE    1           408          3989          4397\nTIMING    1        488.10          2.26        490.39        519.04\n------\nENERGY    2   7.22540E-05   6.87879E-05   1.36128E-02   1.29597E-02\nFORCES    2   8.96036E-04   8.69566E-04   3.70831E-02   3.59876E-02\nUPDATE    2           408          4060          4468\nTIMING    2        481.82          2.28        484.13       1003.17\n------\nENERGY    3   3.30955E-05   3.14121E-05   6.23525E-03   5.91810E-03\nFORCES    3   7.59854E-04   7.62972E-04   3.14471E-02   3.15762E-02\nUPDATE    3           408          3868          4276\nTIMING    3        461.55          2.29        463.87       1467.04\n------\nENERGY    4   3.42202E-05   3.10360E-05   6.44714E-03   5.84724E-03\nFORCES    4   7.27662E-04   7.34262E-04   3.01149E-02   3.03880E-02\nUPDATE    4           408          4063          4471\nTIMING    4        478.34          2.29        480.67       1947.71\n------\nENERGY    5   3.09231E-05   2.89950E-05   5.82595E-03   5.46270E-03\nFORCES    5   7.19574E-04   7.22875E-04   2.97801E-02   2.99167E-02\nUPDATE    5           408          3950          4358\nTIMING    5        465.33          2.32        467.68       2415.39\n------\nENERGY    6   3.54836E-05   3.35687E-05   6.68516E-03   6.32439E-03\nFORCES    6   7.12779E-04   7.20079E-04   2.94989E-02   2.98010E-02\nUPDATE    6           408          4013          4421\nTIMING    6        470.91          2.34        473.28       2888.67\n------\nENERGY    7   3.03115E-05   2.99190E-05   5.71073E-03   5.63678E-03\nFORCES    7   7.13508E-04   7.20645E-04   2.95290E-02   2.98244E-02\nUPDATE    7           408          4013          4421\nTIMING    7        472.06          2.32        474.41       3363.09\n------\nENERGY    8   2.62911E-05   2.59198E-05   4.95328E-03   4.88332E-03\nFORCES    8   7.13227E-04   7.20274E-04   2.95174E-02   2.98091E-02\nUPDATE    8           408          4078          4486\nTIMING    8        478.21          2.32        480.56       3843.65\n------\nENERGY    9   2.78768E-05   2.74107E-05   5.25203E-03   5.16421E-03\nFORCES    9   7.02125E-04   7.11625E-04   2.90580E-02   2.94511E-02\nUPDATE    9           408          4018          4426\nTIMING    9        471.94          2.32        474.29       4317.94\n------\nENERGY   10   3.38611E-05   3.29423E-05   6.37948E-03   6.20637E-03\nFORCES   10   7.57695E-04   7.23856E-04   3.13578E-02   2.99573E-02\nUPDATE   10           408          4042          4450\nTIMING   10        474.02          2.30        476.35       4794.29\n------\nENERGY   11   3.11800E-05   3.09504E-05   5.87435E-03   5.83111E-03\nFORCES   11   6.98004E-04   7.06789E-04   2.88874E-02   2.92510E-02\nUPDATE   11           408          3991          4399\nTIMING   11        472.67          2.29        475.00       5269.29\n------\nENERGY   12   3.56976E-05   3.53036E-05   6.72548E-03   6.65124E-03\nFORCES   12   7.01723E-04   7.11682E-04   2.90413E-02   2.94535E-02\nUPDATE   12           408          4073          4481\nTIMING   12        475.70          2.28        478.01       5747.30\n------\nENERGY   13   2.91678E-05   2.77003E-05   5.49527E-03   5.21878E-03\nFORCES   13   6.98421E-04   7.07914E-04   2.89047E-02   2.92975E-02\nUPDATE   13           408          4037          4445\nTIMING   13        474.99          2.29        477.32       6224.62\n------\nENERGY   14   2.60211E-05   2.60839E-05   4.90241E-03   4.91425E-03\nFORCES   14   6.94284E-04   7.05119E-04   2.87335E-02   2.91819E-02\nUPDATE   14           408          4046          4454\nTIMING   14        475.52          2.29        477.84       6702.46\n------\nENERGY   15   2.76044E-05   2.77069E-05   5.20072E-03   5.22002E-03\nFORCES   15   6.94453E-04   7.04699E-04   2.87405E-02   2.91645E-02\nUPDATE   15           408          3889          4297\nTIMING   15        457.37          2.29        459.69       7162.15\n------\nENERGY   16   2.75078E-05   2.80643E-05   5.18251E-03   5.28737E-03\nFORCES   16   7.00424E-04   7.10398E-04   2.89876E-02   2.94003E-02\nUPDATE   16           408          3863          4271\nTIMING   16        454.32          2.31        456.66       7618.81\n------\nENERGY   17   2.79587E-05   2.75696E-05   5.26747E-03   5.19415E-03\nFORCES   17   6.88807E-04   6.99348E-04   2.85068E-02   2.89430E-02\nUPDATE   17           408          3907          4315\nTIMING   17        458.26          2.29        460.58       8079.39\n------\nENERGY   18   3.67039E-05   3.62841E-05   6.91508E-03   6.83597E-03\nFORCES   18   6.90684E-04   7.00952E-04   2.85845E-02   2.90094E-02\nUPDATE   18           408          4041          4449\nTIMING   18        475.08          2.28        477.39       8556.79\n------\nENERGY   19   2.82210E-05   2.85948E-05   5.31689E-03   5.38729E-03\nFORCES   19   6.91687E-04   7.02204E-04   2.86260E-02   2.90613E-02\nUPDATE   19           408          4077          4485\nTIMING   19        477.49          2.29        479.81       9036.60\n------\nENERGY   20   3.10641E-05   3.07822E-05   5.85252E-03   5.79941E-03\nFORCES   20   6.92776E-04   7.03079E-04   2.86710E-02   2.90975E-02\nUPDATE   20           408          4180          4588\nTIMING   20        486.82          2.28        489.14       9525.74\n------\nENERGY   21   2.52104E-05   2.56410E-05   4.74968E-03   4.83081E-03\nFORCES   21   6.89703E-04   7.02466E-04   2.85439E-02   2.90721E-02\nUPDATE   21           408          4001          4409\nTIMING   21        468.68          2.31        471.02       9996.76\n------\nENERGY   22   2.81115E-05   2.69695E-05   5.29624E-03   5.08109E-03\nFORCES   22   6.92767E-04   7.05060E-04   2.86707E-02   2.91795E-02\nUPDATE   22           408          4055          4463\nTIMING   22        474.92          2.27        477.22      10473.98\n------\nENERGY   23   2.62003E-05   2.60107E-05   4.93618E-03   4.90046E-03\nFORCES   23   6.89922E-04   7.00276E-04   2.85529E-02   2.89814E-02\nUPDATE   23           408          4076          4484\nTIMING   23        476.69          2.24        478.96      10952.93\n------\nENERGY   24   3.23055E-05   3.05217E-05   6.08640E-03   5.75033E-03\nFORCES   24   6.86600E-04   6.98834E-04   2.84154E-02   2.89218E-02\nUPDATE   24           408          3958          4366\nTIMING   24        464.42          2.24        466.69      11419.63\n------\nENERGY   25   2.87481E-05   2.83048E-05   5.41619E-03   5.33267E-03\nFORCES   25   6.88272E-04   7.00905E-04   2.84847E-02   2.90075E-02\nUPDATE   25           408          4004          4412\nTIMING   25        469.27          3.57        472.88      11892.51\n*******************************************************************************\n"
  },
  {
    "path": "examples/potentials/H2O_RPBE/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   3.4361916657281655E-01   9.6166419119419100E+00   2.1748938205013815E+00   7.4191537350143255E-01\n         1          2   3.4529815436471312E-01   5.0028559321574209E+00   1.2804622920635331E+00   3.7071908637882900E-01\n         1          3   2.8520969887279690E-01   7.1427942966219833E+00   1.5793173662073601E+00   5.5089665606785165E-01\n         1          4   3.2106553524354248E-01   3.7661771168267735E+00   9.8302452767030468E-01   2.7493168206863750E-01\n         1          5   2.1847521231954450E-01   4.1469832401668656E+00   8.7356549550189477E-01   3.1799617245982070E-01\n         1          6   2.9005448794053190E-01   2.2678239402766067E+00   6.3211068767406797E-01   1.5843713831593564E-01\n         1          7   1.5918983206892320E-01   2.2292652677252818E+00   4.4111837121817354E-01   1.6746450287127876E-01\n         1          8   2.4633535429997927E-01   1.3208742362468955E+00   4.1644010985653657E-01   8.4618882074047566E-02\n         1          9   2.3871167441164690E-01   9.4751160662053013E-01   3.5914192368456149E-01   5.4745363609973736E-02\n         1         10   2.1652029474256546E-01   2.7596216013647377E+00   5.2188946540215375E-01   2.0883824915382329E-01\n         1         11   1.5067117763308999E-01   5.5599270746969265E-01   2.6705603669763078E-01   2.6376911892691524E-02\n         1         12   9.7653543774030530E-02   1.7265405335201478E+00   2.8990244629916084E-01   1.1771952395941644E-01\n         1         13   6.5409396084418633E-02   3.4521757733971214E-01   1.8533634716653088E-01   1.9775928443295971E-02\n         1         14   2.4184019750917187E-02   9.1293170125596157E-01   1.4963205627085510E-01   5.3539509680440162E-02\n         1         15   2.9202821602466616E-03   2.6979289245531668E-01   7.6738984090206838E-02   1.8938717481778840E-02\n         1         16   3.2145385719803388E-04   2.8780215825669969E-01   4.6238660370711539E-02   2.3962334337404946E-02\n         1         17   5.0392116747274588E-06   1.3848731138266301E-01   1.7020481224750382E-02   1.0169953682386894E-02\n         1         18   1.0425744959269357E-05   5.8319173651547451E-01   2.2542533637215204E-02   3.8158386232402343E-02\n         1         19   1.0951118212822256E-05   2.1613962298381931E-01   1.6279905267385222E-02   1.4368183768220794E-02\n         1         20   2.7226867767020099E-02   1.6851617426880208E+00   1.3952230537109159E-01   1.1164326068924128E-01\n         1         21   2.7649487017544112E-03   3.1637071808861683E-01   1.7613747259739253E-02   2.0338310598344466E-02\n         1         22   8.6041113770643713E-08   1.0258348935693720E-01   6.0738398643095850E-03   6.7161946735046175E-03\n         1         23   2.9580298017842507E-02   9.1618560879938982E-01   7.8768837751373832E-02   5.8691541702176615E-02\n         1         24   8.1998395094105461E-08   1.5785966980407007E-01   4.4192213837265810E-03   9.9187977374992995E-03\n         1         25   6.3691481700312361E-04   5.9225627251012963E-02   3.6207977466753321E-03   3.3285565254801124E-03\n         1         26   8.5719260938176087E-03   1.9426085555380745E-01   2.3781897053519751E-02   1.1059437239915933E-02\n         1         27   2.1228022180417685E-04   9.9652427991033278E-03   2.0643892927967276E-03   6.0091382870397926E-04\n         2          1   7.4846323117439106E-01   1.0005711988560005E+01   2.5609245841270658E+00   7.4052854972999604E-01\n         2          2   2.8392799730020232E-02   4.6195409357987103E+00   9.1994396468770367E-01   3.6736041790976043E-01\n         2          3   6.7685342163101270E-01   7.5323544094345039E+00   1.9660490553406171E+00   5.4848444066384971E-01\n         2          4   1.1679710302485411E-02   3.3862131032504501E+00   6.2716450389037237E-01   2.7017344295584866E-01\n         2          5   5.9315564577324476E-01   4.5356481255168566E+00   1.2642213753481335E+00   3.1436043504428773E-01\n         2          6   1.6454718489766968E-03   1.8909877539194524E+00   2.9130816377975016E-01   1.5054185740505774E-01\n         2          7   5.2283356591555663E-01   2.6154328621607870E+00   8.3288021971307002E-01   1.6495240221433055E-01\n         2          8   8.9551627260546967E-05   9.3641034200657924E-01   1.0579949198861999E-01   7.2445732966072485E-02\n         2          9   5.1853195813177000E-01   1.8545341781448565E+00   7.1828384736912010E-01   1.0111710195641380E-01\n         2         10   1.8186844343484924E-04   2.9121456897811351E+00   4.5000976037755164E-01   2.4764503945970923E-01\n         2         11   3.5263905013513863E-01   1.0714592032613124E+00   5.3411207339525857E-01   4.5487441246439289E-02\n         2         12   1.2543484979231332E-06   2.5277642768509319E+00   3.0041142012990529E-01   2.1789986008284259E-01\n         2         13   1.5980022688828241E-01   6.6348817066386456E-01   3.7067269433306532E-01   3.0732108926417149E-02\n         2         14   7.0744532503554468E-11   2.3030057819082543E+00   1.6936053010502419E-01   1.8915868497783078E-01\n         2         15   9.5641036809349898E-03   4.1268754969500288E-01   1.5347796818041393E-01   2.8128837590643170E-02\n         2         16   1.7690275765523711E-23   2.0367068825281991E+00   5.2646616242243434E-02   1.4348700224919952E-01\n         2         17   6.3111206149137360E-06   3.4335400617385070E-01   1.5865526632271986E-02   2.2142642023896247E-02\n         2         18   2.5552203440925303E-09   5.6319316766205309E-02   9.1405773700959075E-04   3.3672812653005994E-03\n         2         19   4.0351137759319072E-04   3.0182597583971473E+00   1.9315623539110352E-01   2.0465521972428208E-01\n         2         20   4.0328722130386186E-06   4.9878800454061339E-01   1.2013813367896062E-02   3.2010383773991527E-02\n         2         21   3.7690363389962459E-03   2.6739582842775927E-01   2.9869420207849526E-02   1.7527727008027703E-02\n         2         22   2.0137524879322152E-03   1.4167796508898467E+00   7.2079317299346926E-02   9.4149907344989042E-02\n         2         23   1.8598283950705813E-02   4.0756378297923923E-01   4.7604388030601137E-02   2.5907486520071691E-02\n         2         24   1.9207201186160953E-07   2.3324050667069188E-01   6.8357503188617623E-03   1.4581378561320199E-02\n         2         25   4.8981212395007644E-10   3.5285772934088619E-02   4.0637862454730861E-04   2.0506561263012924E-03\n         2         26   1.0669838570041895E-02   8.2245409953473092E-01   4.8778196980512126E-02   5.3362532927491997E-02\n         2         27   2.9131522960331733E-06   7.8557031440100344E-01   3.5136494673282705E-02   5.1003823182777887E-02\n         2         28   3.9791661804285895E-09   9.8448068666706065E-02   1.1566771916965517E-03   5.8048429433103519E-03\n         2         29   5.9914984257891119E-03   9.9251766407842459E-02   1.5978405684497654E-02   5.5709962202180304E-03\n         2         30   3.3703767074221838E-03   1.5478537567691841E-01   1.1424289115697409E-02   8.9873423743960790E-03\n"
  },
  {
    "path": "examples/potentials/H2O_RPBE/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -9.1143913304911983E+00 a         1     0     1     1     1\n  7.1337760328721667E-01 a         2     0     1     1     2\n -5.7748613150534407E+00 a         3     0     1     1     3\n  1.0850639783007801E+00 a         4     0     1     1     4\n -1.0260659816523784E+01 a         5     0     1     1     5\n -1.2811971318150503E+00 a         6     0     1     1     6\n  5.5886913912483056E+00 a         7     0     1     1     7\n -7.9388405531724819E+00 a         8     0     1     1     8\n  1.1262820481786660E+01 a         9     0     1     1     9\n  8.9443626756653529E+00 a        10     0     1     1    10\n  3.1675484182177822E+00 a        11     0     1     1    11\n -2.6141155104283254E+01 a        12     0     1     1    12\n -6.0500623843897596E+00 a        13     0     1     1    13\n  1.8946982199503002E+00 a        14     0     1     1    14\n  1.2578839877176113E+01 a        15     0     1     1    15\n  7.3769307178107457E-01 a        16     0     1     1    16\n  8.4234881165673485E+00 a        17     0     1     1    17\n  2.7820635048589720E-01 a        18     0     1     1    18\n -6.5776118717549688E+00 a        19     0     1     1    19\n  2.5833138711474435E+00 a        20     0     1     1    20\n  6.6472423084087078E+00 a        21     0     1     1    21\n  2.0253727900732130E+00 a        22     0     1     1    22\n  1.5709370986391862E+00 a        23     0     1     1    23\n -1.8747709266736472E+00 a        24     0     1     1    24\n -1.9234262413744815E+01 a        25     0     1     1    25\n  1.2694021167495222E+01 a        26     0     2     1     1\n -9.8516927111118910E+00 a        27     0     2     1     2\n  7.4521111471876909E+00 a        28     0     2     1     3\n  1.1814112100017807E+01 a        29     0     2     1     4\n  1.2651166432245091E+01 a        30     0     2     1     5\n  1.7163065578207994E+00 a        31     0     2     1     6\n  2.7257767723523068E+00 a        32     0     2     1     7\n -3.7932084710569409E+00 a        33     0     2     1     8\n -1.5668318556426462E+01 a        34     0     2     1     9\n -3.1155716549649703E+00 a        35     0     2     1    10\n -9.7953996251491873E+00 a        36     0     2     1    11\n  2.9348329629948854E+01 a        37     0     2     1    12\n -1.0794040861830019E+00 a        38     0     2     1    13\n -7.9618258579850503E+00 a        39     0     2     1    14\n -8.9590585751802276E+00 a        40     0     2     1    15\n  1.0063282974973005E+00 a        41     0     2     1    16\n  6.4338769362774890E+00 a        42     0     2     1    17\n -1.2643063616314767E+00 a        43     0     2     1    18\n  5.8694289979095826E+00 a        44     0     2     1    19\n -5.7173733498639576E+00 a        45     0     2     1    20\n -9.8112393475471347E+00 a        46     0     2     1    21\n -7.0997344443364225E+00 a        47     0     2     1    22\n  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-1.2230475787629426E-01 a      1109     1    17     2     9\n -1.7766371313365034E-01 a      1110     1    17     2    10\n  2.7721560797268427E+00 a      1111     1    17     2    11\n  7.4501940187038096E-02 a      1112     1    17     2    12\n  5.3395830479703171E-02 a      1113     1    17     2    13\n -3.5492648989802061E-01 a      1114     1    17     2    14\n  5.0398363549275649E-01 a      1115     1    17     2    15\n  1.1885403311070930E+00 a      1116     1    17     2    16\n  4.7191374826793775E-01 a      1117     1    17     2    17\n -4.0579861015739999E-01 a      1118     1    17     2    18\n -2.5388466874489768E-01 a      1119     1    17     2    19\n -4.6795645688477144E-01 a      1120     1    17     2    20\n -1.5355955812292335E-01 a      1121     1    17     2    21\n  5.7567669645543018E-01 a      1122     1    17     2    22\n -1.7282101847715994E+00 a      1123     1    17     2    23\n -2.6507003958106674E+00 a      1124     1    17     2    24\n  6.1066104707664304E-01 a      1125     1    17     2    25\n  7.7540540324573906E+00 a      1126     1    18     2     1\n -3.7347356979968138E+00 a      1127     1    18     2     2\n -6.3500123093304695E-01 a      1128     1    18     2     3\n  4.3631875323082242E-01 a      1129     1    18     2     4\n -1.6547213485208521E+00 a      1130     1    18     2     5\n -2.6897866553791245E+00 a      1131     1    18     2     6\n -3.2014645282877918E+00 a      1132     1    18     2     7\n -2.1548647095530078E+00 a      1133     1    18     2     8\n  1.8021360660785644E+00 a      1134     1    18     2     9\n -3.6872184110137690E-01 a      1135     1    18     2    10\n  8.3102909743186815E-01 a      1136     1    18     2    11\n  1.7504926054633483E+00 a      1137     1    18     2    12\n -1.0922144575838399E+00 a      1138     1    18     2    13\n -2.3210838290346261E+00 a      1139     1    18     2    14\n  1.1608577604900376E+00 a      1140     1    18     2    15\n  5.4513222628158020E-01 a      1141     1    18     2    16\n -1.3082019093526220E+00 a      1142     1    18     2    17\n  1.9682601067403451E+00 a      1143     1    18     2    18\n  9.1840427945528813E-01 a      1144     1    18     2    19\n  1.6729538094977803E+00 a      1145     1    18     2    20\n  1.9514627479321187E+00 a      1146     1    18     2    21\n  1.3021464734305730E+00 a      1147     1    18     2    22\n  5.4145064432429297E+00 a      1148     1    18     2    23\n  3.1809138097883234E+00 a      1149     1    18     2    24\n  2.7939556798911331E+00 a      1150     1    18     2    25\n -9.4646764580613246E-02 a      1151     1    19     2     1\n  1.0160388467788467E-01 a      1152     1    19     2     2\n  3.6596359043959337E-01 a      1153     1    19     2     3\n  9.1615960705827615E-01 a      1154     1    19     2     4\n -1.2297734584424278E+00 a      1155     1    19     2     5\n -4.8122049493112123E-01 a      1156     1    19     2     6\n  4.4093924564057885E-01 a      1157     1    19     2     7\n -2.5492033157352028E+00 a      1158     1    19     2     8\n -1.4774004717921563E-01 a      1159     1    19     2     9\n  5.7805659181467117E-01 a      1160     1    19     2    10\n  3.5075826824619211E-01 a      1161     1    19     2    11\n  3.6627130733452151E-01 a      1162     1    19     2    12\n -1.7376231678091394E+00 a      1163     1    19     2    13\n  4.4169564170393294E-01 a      1164     1    19     2    14\n  1.0157216676234275E+00 a      1165     1    19     2    15\n -1.1240038073166908E-01 a      1166     1    19     2    16\n -3.0991174601967195E+00 a      1167     1    19     2    17\n  1.7008072040292781E+00 a      1168     1    19     2    18\n -1.6593864749295031E+00 a      1169     1    19     2    19\n -1.0550384582054625E-01 a      1170     1    19     2    20\n -3.2142768338015293E-01 a      1171     1    19     2    21\n  1.0117352568471173E-01 a      1172     1    19     2    22\n  1.9853602334130092E+00 a      1173     1    19     2    23\n  1.3997073686003441E+00 a      1174     1    19     2    24\n  2.9117796217637570E+00 a      1175     1    19     2    25\n -4.5764753306962114E-01 a      1176     1    20     2     1\n -9.9891583313822530E-01 a      1177     1    20     2     2\n -5.1899573526722464E-01 a      1178     1    20     2     3\n -2.0567536492989977E+00 a      1179     1    20     2     4\n  9.2352993174625033E-04 a      1180     1    20     2     5\n  2.5540489726669571E+00 a      1181     1    20     2     6\n -7.6341773585261519E-01 a      1182     1    20     2     7\n  2.3160576984664356E+00 a      1183     1    20     2     8\n  6.0901481267781610E-01 a      1184     1    20     2     9\n  1.2668445551264709E+00 a      1185     1    20     2    10\n -1.9419173240401806E+00 a      1186     1    20     2    11\n -6.9456390863435447E-01 a      1187     1    20     2    12\n  6.4143514881624264E-01 a      1188     1    20     2    13\n -6.7523840606955088E-01 a      1189     1    20     2    14\n  1.7060682681007883E-01 a      1190     1    20     2    15\n -8.6856242988024346E-01 a      1191     1    20     2    16\n  2.3673702458697710E+00 a      1192     1    20     2    17\n -3.2896597513188691E-01 a      1193     1    20     2    18\n  5.1483584590046283E-01 a      1194     1    20     2    19\n  7.6283189486490477E-01 a      1195     1    20     2    20\n  5.3126050517483481E-01 a      1196     1    20     2    21\n  2.4156101559153187E-01 a      1197     1    20     2    22\n  1.8659940946568193E-01 a      1198     1    20     2    23\n -4.8951004359865896E-01 a      1199     1    20     2    24\n -3.6955021845427987E+00 a      1200     1    20     2    25\n  3.3026951503002977E-01 a      1201     1    21     2     1\n  7.0085692638464550E-02 a      1202     1    21     2     2\n  1.5350691308185720E+00 a      1203     1    21     2     3\n  1.1399777563268440E+01 a      1204     1    21     2     4\n -1.4217252444130857E+00 a      1205     1    21     2     5\n  1.2527106528056411E+00 a      1206     1    21     2     6\n -1.5196779747644091E+00 a      1207     1    21     2     7\n  9.5752871668915926E-02 a      1208     1    21     2     8\n -4.0061418161332302E-01 a      1209     1    21     2     9\n -1.0608632679355677E-01 a      1210     1    21     2    10\n  2.6130566666465588E-01 a      1211     1    21     2    11\n -1.5952333462368868E+00 a      1212     1    21     2    12\n -2.2407020474877495E+00 a      1213     1    21     2    13\n -6.7299305613294869E-01 a      1214     1    21     2    14\n -1.0452111276516422E-01 a      1215     1    21     2    15\n -5.7081790052659655E-02 a      1216     1    21     2    16\n  5.9832663213416667E-02 a      1217     1    21     2    17\n  6.7058028411858006E-01 a      1218     1    21     2    18\n -1.4106293179367038E+00 a      1219     1    21     2    19\n -7.0812356901514795E-01 a      1220     1    21     2    20\n  3.4501537653459025E-01 a      1221     1    21     2    21\n  6.5446998920641974E-01 a      1222     1    21     2    22\n  3.0247903680236377E+00 a      1223     1    21     2    23\n -1.6407070736435441E+00 a      1224     1    21     2    24\n -7.7725075526767613E+00 a      1225     1    21     2    25\n -2.8878530004591241E+00 a      1226     1    22     2     1\n -1.8698056165949102E+00 a      1227     1    22     2     2\n  4.4924020661855041E-01 a      1228     1    22     2     3\n -2.2767544595359457E+00 a      1229     1    22     2     4\n -3.5203493490546314E+00 a      1230     1    22     2     5\n -1.5448845050104911E+00 a      1231     1    22     2     6\n -1.8711260461891439E+00 a      1232     1    22     2     7\n  1.7915140285640574E+00 a      1233     1    22     2     8\n  2.1702350088264535E-01 a      1234     1    22     2     9\n -1.6234033665035481E+00 a      1235     1    22     2    10\n -1.8272803877438288E+00 a      1236     1    22     2    11\n  8.7748384221966891E-01 a      1237     1    22     2    12\n  8.2026308658672886E-01 a      1238     1    22     2    13\n  7.0525549974537904E-01 a      1239     1    22     2    14\n  1.9642126710202101E+00 a      1240     1    22     2    15\n -2.8076656872726771E+00 a      1241     1    22     2    16\n  1.6471776166977137E+00 a      1242     1    22     2    17\n -1.2264587534374354E+00 a      1243     1    22     2    18\n  7.9477289887119074E-01 a      1244     1    22     2    19\n  1.7601454958853162E+00 a      1245     1    22     2    20\n  4.6411919084624126E-01 a      1246     1    22     2    21\n  5.7099382178715574E-01 a      1247     1    22     2    22\n -8.1530683478962396E-01 a      1248     1    22     2    23\n  2.9156642967618962E-01 a      1249     1    22     2    24\n -1.2526998124140987E+00 a      1250     1    22     2    25\n  1.0478264278181887E-01 a      1251     1    23     2     1\n  3.9608457353426207E-01 a      1252     1    23     2     2\n -1.2882292956436900E-01 a      1253     1    23     2     3\n  1.1091267211759670E+00 a      1254     1    23     2     4\n -6.2459439469257272E-01 a      1255     1    23     2     5\n  9.1229401452426417E-01 a      1256     1    23     2     6\n  2.3757654865086547E-01 a      1257     1    23     2     7\n -1.5619107257264000E+00 a      1258     1    23     2     8\n  1.1216556938513151E+00 a      1259     1    23     2     9\n  7.4093306485379359E-02 a      1260     1    23     2    10\n -6.1035293144195681E-02 a      1261     1    23     2    11\n  7.9495775758148723E-01 a      1262     1    23     2    12\n -1.1412488529723912E+00 a      1263     1    23     2    13\n -1.0116655466000819E-01 a      1264     1    23     2    14\n -4.5418748411664689E-01 a      1265     1    23     2    15\n  6.1440293007431523E-01 a      1266     1    23     2    16\n -1.8325049827486390E+00 a      1267     1    23     2    17\n -8.3037107885868891E-02 a      1268     1    23     2    18\n  4.1048970459244100E-01 a      1269     1    23     2    19\n -7.4083051840981318E-01 a      1270     1    23     2    20\n  2.2684747303480707E-01 a      1271     1    23     2    21\n -1.6657074727719456E-01 a      1272     1    23     2    22\n  6.0817271713677801E-01 a      1273     1    23     2    23\n  6.2317468332614229E-02 a      1274     1    23     2    24\n  9.4826301215571840E-01 a      1275     1    23     2    25\n  1.7828219847177271E+00 a      1276     1    24     2     1\n -5.6402037085176671E-01 a      1277     1    24     2     2\n  5.0090814553239371E-01 a      1278     1    24     2     3\n  4.6643369374498498E+00 a      1279     1    24     2     4\n  4.5768439782483448E+00 a      1280     1    24     2     5\n  1.6073879968363912E+01 a      1281     1    24     2     6\n  2.8877098949089530E-01 a      1282     1    24     2     7\n -3.3565646725402574E+00 a      1283     1    24     2     8\n  1.8100417343132675E+00 a      1284     1    24     2     9\n  6.7461680565843309E+00 a      1285     1    24     2    10\n -7.7343382865417878E+00 a      1286     1    24     2    11\n  4.9979223672006894E+00 a      1287     1    24     2    12\n -1.0848541560697336E+00 a      1288     1    24     2    13\n  5.2479810290094298E+00 a      1289     1    24     2    14\n -1.9981826587599492E+00 a      1290     1    24     2    15\n -2.6969923727338534E+00 a      1291     1    24     2    16\n -1.9404419550513365E+00 a      1292     1    24     2    17\n  1.4791992914782730E+00 a      1293     1    24     2    18\n -2.3874704344249218E+00 a      1294     1    24     2    19\n  2.9468808712680268E+00 a      1295     1    24     2    20\n -1.4855192943853226E+00 a      1296     1    24     2    21\n -1.3424006004146218E+00 a      1297     1    24     2    22\n  7.9949421059344745E+00 a      1298     1    24     2    23\n -4.8093133168450750E+00 a      1299     1    24     2    24\n -1.6597466852564802E+00 a      1300     1    24     2    25\n -1.0910586276756113E+00 a      1301     1    25     2     1\n -3.4433502201076144E-01 a      1302     1    25     2     2\n -6.6285126682363404E-01 a      1303     1    25     2     3\n -4.7482749805494090E-01 a      1304     1    25     2     4\n -6.5245880008824353E-01 a      1305     1    25     2     5\n  2.6409758431487827E-02 a      1306     1    25     2     6\n -5.2948039292524962E-01 a      1307     1    25     2     7\n -8.3458707657186038E-01 a      1308     1    25     2     8\n  2.4858998111555999E-01 a      1309     1    25     2     9\n  3.5871106772312616E-01 a      1310     1    25     2    10\n -7.3676136442800622E-01 a      1311     1    25     2    11\n -5.9425437706499373E-01 a      1312     1    25     2    12\n -1.0199143185186738E-01 a      1313     1    25     2    13\n -1.6180272746809008E+00 a      1314     1    25     2    14\n -1.2358827926463216E+00 a      1315     1    25     2    15\n -1.1191208495389962E+00 a      1316     1    25     2    16\n  1.9964316170681046E-01 a      1317     1    25     2    17\n  1.1406020683721997E-01 a      1318     1    25     2    18\n  2.2598447256515386E-02 a      1319     1    25     2    19\n  3.1030356270689763E-01 a      1320     1    25     2    20\n  1.8259747404299365E+00 a      1321     1    25     2    21\n -6.0540468896917365E-01 a      1322     1    25     2    22\n -1.5682830593662460E+00 a      1323     1    25     2    23\n  4.3947973342355762E-01 a      1324     1    25     2    24\n  3.1324829154084771E-01 a      1325     1    25     2    25\n -2.4279561882134963E+00 b      1326     2     1\n  6.4544771292908134E+00 b      1327     2     2\n  3.1751523607344467E-01 b      1328     2     3\n  4.1646451924597958E+00 b      1329     2     4\n -2.5505795783784428E+00 b      1330     2     5\n  1.5118415683213509E+01 b      1331     2     6\n  5.3264683151142889E-01 b      1332     2     7\n -3.4845667923485748E+00 b      1333     2     8\n -3.7224368826418797E+00 b      1334     2     9\n  1.3774457931632972E+01 b      1335     2    10\n -1.4848429288599934E+01 b      1336     2    11\n -2.5774099661328576E-01 b      1337     2    12\n  7.8644553237853676E-01 b      1338     2    13\n  8.5293687544107897E+00 b      1339     2    14\n -1.4623603002169225E+00 b      1340     2    15\n -1.4339071278876411E-01 b      1341     2    16\n  5.6722952511658919E-01 b      1342     2    17\n  2.9786494266751422E+00 b      1343     2    18\n -7.9846855691597938E+00 b      1344     2    19\n -1.2955913074824352E+00 b      1345     2    20\n -4.7974825361781406E+00 b      1346     2    21\n -6.1626840379483527E-01 b      1347     2    22\n  7.0515771425272211E-01 b      1348     2    23\n  4.0152920252762936E+00 b      1349     2    24\n -1.2433016957401415E+01 b      1350     2    25\n -3.3763339972210327E-01 a      1351     2     1     3     1\n  1.8938721616986220E+00 a      1352     2     2     3     1\n  8.7017936816667285E-01 a      1353     2     3     3     1\n  1.2971932946441780E+00 a      1354     2     4     3     1\n  4.1239553295611076E-01 a      1355     2     5     3     1\n -8.1737814804844422E-01 a      1356     2     6     3     1\n  1.3270657878134318E+00 a      1357     2     7     3     1\n -2.9556400913726261E-02 a      1358     2     8     3     1\n -2.0033836586675555E+00 a      1359     2     9     3     1\n  2.7255276248424019E+00 a      1360     2    10     3     1\n -4.2675239937851188E+00 a      1361     2    11     3     1\n -1.3918585258658327E+00 a      1362     2    12     3     1\n  8.0720851022768825E-01 a      1363     2    13     3     1\n  9.2170489192675709E-01 a      1364     2    14     3     1\n -3.7459111327023207E+00 a      1365     2    15     3     1\n  1.0657447005945400E+00 a      1366     2    16     3     1\n  1.1430249300083657E+00 a      1367     2    17     3     1\n -5.7830350135338193E-01 a      1368     2    18     3     1\n -9.0667957757811291E+00 a      1369     2    19     3     1\n -1.7467765897861225E+00 a      1370     2    20     3     1\n -2.8513695807952795E+00 a      1371     2    21     3     1\n -1.1467297140066941E+00 a      1372     2    22     3     1\n -4.0421959785178985E-01 a      1373     2    23     3     1\n  1.2278189643341817E+00 a      1374     2    24     3     1\n -1.4668941896730936E+00 a      1375     2    25     3     1\n -2.2553111235809182E+00 b      1376     3     1\n"
  },
  {
    "path": "examples/potentials/H2O_RPBE/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  9.2167172324771818E-01 a         1     0     1     1     1\n -7.3761497085562517E+00 a         2     0     1     1     2\n  1.1127282913615522E+00 a         3     0     1     1     3\n -2.4094364164935527E+01 a         4     0     1     1     4\n  1.9103539628018809E+00 a         5     0     1     1     5\n -5.7653210148774967E+00 a         6     0     1     1     6\n  7.3896026849525027E+00 a         7     0     1     1     7\n -8.9213391406127176E+00 a         8     0     1     1     8\n -4.0363734989605896E-02 a         9     0     1     1     9\n -1.5171556083137716E+01 a        10     0     1     1    10\n  6.6401350637616989E+00 a        11     0     1     1    11\n  1.0126536115567911E+01 a        12     0     1     1    12\n -9.6931479678689154E+00 a        13     0     1     1    13\n  4.8330689152905366E+00 a        14     0     1     1    14\n -6.8861900140476848E+00 a        15     0     1     1    15\n  6.8596301963562079E+00 a        16     0     1     1    16\n  4.3381497633208497E+00 a        17     0     1     1    17\n -4.9120077799499740E-01 a        18     0     1     1    18\n  7.9576995637313850E+00 a        19     0     1     1    19\n  4.0298121933325435E+00 a        20     0     1     1    20\n  1.0428416239698983E+01 a        21     0     1     1    21\n  7.8708117145760434E+00 a        22     0     1     1    22\n  4.8220699175316968E+00 a        23     0     1     1    23\n  7.7457693986107023E-01 a        24     0     1     1    24\n  2.3342413143954763E+00 a        25     0     1     1    25\n -3.2538137265621776E+00 a        26     0     2     1     1\n -2.2368418504430196E+01 a        27     0     2     1     2\n -1.4902218793761694E+01 a        28     0     2     1     3\n  1.7346801182368282E+01 a        29     0     2     1     4\n -1.5031080262438339E+01 a        30     0     2     1     5\n  2.2834891609570609E+00 a        31     0     2     1     6\n  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3.0342474432120031E-01 a      1365     1    24     2    15\n -2.8857948487391507E+00 a      1366     1    24     2    16\n -5.8085697830056127E-01 a      1367     1    24     2    17\n  1.1652474063604386E+00 a      1368     1    24     2    18\n -3.9375758169632863E-01 a      1369     1    24     2    19\n  4.2642622922963580E-01 a      1370     1    24     2    20\n -1.8868759254858047E+00 a      1371     1    24     2    21\n -1.0781825920191586E+00 a      1372     1    24     2    22\n  2.8942665011097934E-02 a      1373     1    24     2    23\n -9.1282576891400916E-02 a      1374     1    24     2    24\n -7.0197950741613824E-01 a      1375     1    24     2    25\n -1.0596314018581634E+00 a      1376     1    25     2     1\n  7.8352013856585412E-01 a      1377     1    25     2     2\n  1.0201782726274788E+00 a      1378     1    25     2     3\n  7.5869945049729215E-01 a      1379     1    25     2     4\n  1.9924744402907538E-01 a      1380     1    25     2     5\n -5.4567682506877879E-01 a      1381     1    25     2     6\n -4.7406425211733071E-02 a      1382     1    25     2     7\n -1.4767921688142591E+00 a      1383     1    25     2     8\n  2.1969814985799236E+00 a      1384     1    25     2     9\n  1.9911687452716058E+00 a      1385     1    25     2    10\n -5.4631316581663714E-01 a      1386     1    25     2    11\n -7.9038032138953940E-01 a      1387     1    25     2    12\n  8.9352955425693970E-01 a      1388     1    25     2    13\n  5.8860062995810345E-03 a      1389     1    25     2    14\n  9.6715840869568093E-01 a      1390     1    25     2    15\n -2.0270846881892139E+00 a      1391     1    25     2    16\n -7.3347254950651114E-02 a      1392     1    25     2    17\n -1.9619684693418662E+00 a      1393     1    25     2    18\n -9.2545429072479979E-01 a      1394     1    25     2    19\n -6.7146993930714305E-01 a      1395     1    25     2    20\n -2.1368616653845982E+00 a      1396     1    25     2    21\n -2.3765335491113776E-01 a      1397     1    25     2    22\n  4.5635596445069265E-01 a      1398     1    25     2    23\n -1.6464783154858758E+00 a      1399     1    25     2    24\n -1.6117339813757062E-01 a      1400     1    25     2    25\n -1.2676204890377714E+00 b      1401     2     1\n  1.0175307537035044E+01 b      1402     2     2\n -2.4186136412128554E+00 b      1403     2     3\n  6.7625959084009835E-01 b      1404     2     4\n  2.6764989079255641E+00 b      1405     2     5\n  5.6208563788517241E-01 b      1406     2     6\n  1.4419629797841917E+00 b      1407     2     7\n  3.7610722092635593E+00 b      1408     2     8\n  4.6442544243220327E+00 b      1409     2     9\n  1.3225214292916407E+00 b      1410     2    10\n -5.1605936748044696E+00 b      1411     2    11\n -6.5083410786388046E-02 b      1412     2    12\n -3.4188619412189194E+00 b      1413     2    13\n  2.5419018411274386E+00 b      1414     2    14\n -3.1264666016857832E+00 b      1415     2    15\n  3.6751596850235715E+00 b      1416     2    16\n -9.3611333776451977E-01 b      1417     2    17\n  2.4702526203659922E+00 b      1418     2    18\n -6.7568223613165335E-01 b      1419     2    19\n  3.6011177846754263E+00 b      1420     2    20\n  1.3020827139180135E+01 b      1421     2    21\n -1.2444302304415715E+00 b      1422     2    22\n -4.0719497700382430E+00 b      1423     2    23\n  6.1268171973991938E+00 b      1424     2    24\n -3.3340736838029233E-01 b      1425     2    25\n  1.8725783671947995E+00 a      1426     2     1     3     1\n  1.2433158001377529E+00 a      1427     2     2     3     1\n -1.2050289229557187E+00 a      1428     2     3     3     1\n  1.1341511117988448E+00 a      1429     2     4     3     1\n -2.1530533139933259E+00 a      1430     2     5     3     1\n  2.7111001781394817E-01 a      1431     2     6     3     1\n  2.1276921145830321E+00 a      1432     2     7     3     1\n  1.6728812399573947E+00 a      1433     2     8     3     1\n -5.7393520729739644E-01 a      1434     2     9     3     1\n -8.6612493534116797E-01 a      1435     2    10     3     1\n  3.6704272198050808E-01 a      1436     2    11     3     1\n  1.4844301814434364E+00 a      1437     2    12     3     1\n -1.4673213224407924E+00 a      1438     2    13     3     1\n  1.9282982669120732E+00 a      1439     2    14     3     1\n -7.2456251089623747E-01 a      1440     2    15     3     1\n  4.6657213796245850E-01 a      1441     2    16     3     1\n  1.8468480987974154E+00 a      1442     2    17     3     1\n  9.6988144177195057E-01 a      1443     2    18     3     1\n  1.7952005467874474E+00 a      1444     2    19     3     1\n  2.0122713228923459E+00 a      1445     2    20     3     1\n -4.6278663453374724E-01 a      1446     2    21     3     1\n  1.9816389379738466E+00 a      1447     2    22     3     1\n -3.5172056099403766E+00 a      1448     2    23     3     1\n  2.1445346973109483E+00 a      1449     2    24     3     1\n  1.6336911049106368E+00 a      1450     2    25     3     1\n -1.1276555618647039E+00 b      1451     3     1\n"
  },
  {
    "path": "examples/potentials/H2O_RPBE-D3/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   4              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 2\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               25             # Write energy comparison.\nwrite_trainforces               25             # Write force comparison.\nwrite_weights_epoch                            # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/potentials/H2O_RPBE-D3/nnp-train.log.0000",
    "content": "\n*** SETUP: MPI ****************************************************************\n\nNumber of processors: 16\nProcess 1 of 16 (rank 0): n18-040\nProcess 2 of 16 (rank 1): n18-040\nProcess 3 of 16 (rank 2): n18-040\nProcess 4 of 16 (rank 3): n18-040\nProcess 5 of 16 (rank 4): n18-040\nProcess 6 of 16 (rank 5): n18-040\nProcess 7 of 16 (rank 6): n18-040\nProcess 8 of 16 (rank 7): n18-040\nProcess 9 of 16 (rank 8): n18-040\nProcess 10 of 16 (rank 9): n18-040\nProcess 11 of 16 (rank 10): n18-040\nProcess 12 of 16 (rank 11): n18-040\nProcess 13 of 16 (rank 12): n18-040\nProcess 14 of 16 (rank 13): n18-040\nProcess 15 of 16 (rank 14): n18-040\nProcess 16 of 16 (rank 15): n18-040\n*******************************************************************************\n\n*******************************************************************************\n\n   NNP LIBRARY v0.1.0\n   ------------------\n\nGit branch  : master\nGit revision: d2f83cd (d2f83cde386d59595aea395bfe3755dccebc195a)\n\n*******************************************************************************\n\n*** SETUP: SETTINGS FILE ******************************************************\n\nSettings file name: input.nn\nRead 167 lines.\nFound 102 lines with keywords.\n*******************************************************************************\n\n*** SETUP: NORMALIZATION ******************************************************\n\nData set normalization is used.\nMean energy per atom     :  -2.5521343547039809E+01\nConversion factor energy :   2.4265748255366972E+02\nConversion factor length :   5.8038448995319847E+00\n*******************************************************************************\n\n*** SETUP: ELEMENT MAP ********************************************************\n\nNumber of element strings found: 2\nElement  0:  H (  1)\nElement  1:  O (  8)\n*******************************************************************************\n\n*** SETUP: ELEMENTS ***********************************************************\n\nNumber of elements is consistent: 2\nAtomic energy offsets per element:\nElement  0:   0.00000000E+00\nElement  1:   0.00000000E+00\n*******************************************************************************\n\n*** SETUP: CUTOFF FUNCTIONS ***************************************************\n\nParameter alpha for inner cutoff: 0.000000\nInner cutoff = Symmetry function cutoff * alpha\nEqual cutoff function type for all symmetry functions:\nCutoffFunction::CT_TANHU (2)\nf(r) = tanh^3(1 - r/rc)\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTIONS *************************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\n\nShort range atomic symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  H  2  H    2.969E-05 0.000E+00         6.965E+01  2 0.00    98\n   2  H  2  O    2.969E-05 0.000E+00         6.965E+01  2 0.00   108\n   3  H  2  H    2.969E-04 0.000E+00         6.965E+01  2 0.00    99\n   4  H  2  O    2.969E-04 0.000E+00         6.965E+01  2 0.00   109\n   5  H  2  H    8.906E-04 0.000E+00         6.965E+01  2 0.00   100\n   6  H  2  O    8.906E-04 0.000E+00         6.965E+01  2 0.00   110\n   7  H  2  H    1.781E-03 0.000E+00         6.965E+01  2 0.00   101\n   8  H  2  O    1.781E-03 0.000E+00         6.965E+01  2 0.00   111\n   9  H  2  O    4.453E-03 5.223E+00         6.965E+01  2 0.00   112\n  10  H  2  H    4.453E-03 1.103E+01         6.965E+01  2 0.00   102\n  11  H  2  O    8.906E-03 5.223E+00         6.965E+01  2 0.00   113\n  12  H  2  H    8.906E-03 1.103E+01         6.965E+01  2 0.00   103\n  13  H  2  O    1.781E-02 5.223E+00         6.965E+01  2 0.00   114\n  14  H  2  H    1.781E-02 1.103E+01         6.965E+01  2 0.00   104\n  15  H  2  O    4.453E-02 5.223E+00         6.965E+01  2 0.00   115\n  16  H  2  H    4.453E-02 1.103E+01         6.965E+01  2 0.00   105\n  17  H  3  O  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   162\n  18  H  3  O  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   161\n  19  H  3  H  O 2.969E-04 0.000E+00 -1  4.0 6.965E+01  2 0.00   152\n  20  H  3  H  O 2.969E-04 0.000E+00  1  4.0 6.965E+01  2 0.00   150\n  21  H  3  H  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   147\n  22  H  3  O  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   160\n  23  H  3  H  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   145\n  24  H  3  O  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   159\n  25  H  3  H  O 2.078E-03 0.000E+00 -1  1.0 6.965E+01  2 0.00   142\n  26  H  3  H  O 2.078E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   140\n  27  H  3  H  O 5.937E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   137\n-------------------------------------------------------------------------------\nShort range atomic symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n-------------------------------------------------------------------------------\n   1  O  2  H    2.969E-05 0.000E+00         6.965E+01  2 0.00   117\n   2  O  2  O    2.969E-05 0.000E+00         6.965E+01  2 0.00   127\n   3  O  2  H    2.969E-04 0.000E+00         6.965E+01  2 0.00   118\n   4  O  2  O    2.969E-04 0.000E+00         6.965E+01  2 0.00   128\n   5  O  2  H    8.906E-04 0.000E+00         6.965E+01  2 0.00   119\n   6  O  2  O    8.906E-04 0.000E+00         6.965E+01  2 0.00   129\n   7  O  2  H    1.781E-03 0.000E+00         6.965E+01  2 0.00   120\n   8  O  2  O    1.781E-03 0.000E+00         6.965E+01  2 0.00   130\n   9  O  2  H    4.453E-03 5.223E+00         6.965E+01  2 0.00   121\n  10  O  2  O    4.453E-03 2.322E+01         6.965E+01  2 0.00   131\n  11  O  2  H    8.906E-03 5.223E+00         6.965E+01  2 0.00   122\n  12  O  2  O    8.906E-03 2.322E+01         6.965E+01  2 0.00   132\n  13  O  2  H    1.781E-02 5.223E+00         6.965E+01  2 0.00   123\n  14  O  2  O    1.781E-02 2.322E+01         6.965E+01  2 0.00   133\n  15  O  2  H    4.453E-02 5.223E+00         6.965E+01  2 0.00   124\n  16  O  2  O    4.453E-02 2.322E+01         6.965E+01  2 0.00   134\n  17  O  3  H  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   157\n  18  O  3  O  O 2.969E-05 0.000E+00 -1  4.0 6.965E+01  2 0.00   167\n  19  O  3  H  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   156\n  20  O  3  O  O 2.969E-05 0.000E+00  1  4.0 6.965E+01  2 0.00   166\n  21  O  3  H  H 2.969E-04 0.000E+00 -1  4.0 6.965E+01  2 0.00   151\n  22  O  3  H  H 2.969E-04 0.000E+00  1  4.0 6.965E+01  2 0.00   149\n  23  O  3  H  H 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   146\n  24  O  3  H  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   155\n  25  O  3  O  O 8.906E-04 0.000E+00 -1  1.0 6.965E+01  2 0.00   165\n  26  O  3  H  H 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   144\n  27  O  3  H  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   154\n  28  O  3  O  O 8.906E-04 0.000E+00  1  1.0 6.965E+01  2 0.00   164\n  29  O  3  H  H 2.078E-03 0.000E+00 -1  1.0 6.965E+01  2 0.00   141\n  30  O  3  H  H 2.078E-03 0.000E+00  1  1.0 6.965E+01  2 0.00   139\n-------------------------------------------------------------------------------\nMinimum cutoff radius for element  H: 69.646139\nMinimum cutoff radius for element  O: 69.646139\nMaximum cutoff radius (global)      : 69.646139\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\nAbbreviations:\n--------------\nind .... Symmetry function group index.\nec ..... Central atom element.\nty ..... Symmetry function type.\ne1 ..... Neighbor 1 element.\ne2 ..... Neighbor 2 element.\neta .... Gaussian width eta.\nrs ..... Shift distance of Gaussian.\nla ..... Angle prefactor lambda.\nzeta ... Angle term exponent zeta.\nrc ..... Cutoff radius.\nct ..... Cutoff type.\nca ..... Cutoff alpha.\nln ..... Line number in settings file.\nmi ..... Member index.\nsfi .... Symmetry function index.\ne ...... Recalculate exponential term.\n\nShort range atomic symmetry function groups element  H :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  H  2  H            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -    97    1    1  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -    98    2    3  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -    99    3    5  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   100    4    7  \n   -  -  -  -    4.453E-03 1.103E+01                 -  -    -   101    5   10  \n   -  -  -  -    8.906E-03 1.103E+01                 -  -    -   102    6   12  \n   -  -  -  -    1.781E-02 1.103E+01                 -  -    -   103    7   14  \n   -  -  -  -    4.453E-02 1.103E+01                 -  -    -   104    8   16  \n   2  H  2  O            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   107    1    2  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   108    2    4  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   109    3    6  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   110    4    8  \n   -  -  -  -    4.453E-03 5.223E+00                 -  -    -   111    5    9  \n   -  -  -  -    8.906E-03 5.223E+00                 -  -    -   112    6   11  \n   -  -  -  -    1.781E-02 5.223E+00                 -  -    -   113    7   13  \n   -  -  -  -    4.453E-02 5.223E+00                 -  -    -   114    8   15  \n   3  H  3  H  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-04 0.000E+00 -1  4.0         -  -    -   151    1   19 1\n   -  -  -  -  - 2.969E-04 0.000E+00  1  4.0         -  -    -   149    2   20 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   146    3   21 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   144    4   23 0\n   -  -  -  -  - 2.078E-03 0.000E+00 -1  1.0         -  -    -   141    5   25 1\n   -  -  -  -  - 2.078E-03 0.000E+00  1  1.0         -  -    -   139    6   26 0\n   -  -  -  -  - 5.937E-03 0.000E+00  1  1.0         -  -    -   136    7   27 1\n   4  H  3  O  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   161    1   17 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   160    2   18 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   159    3   22 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   158    4   24 0\n-------------------------------------------------------------------------------\nShort range atomic symmetry function groups element  O :\n-------------------------------------------------------------------------------\n ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n-------------------------------------------------------------------------------\n   1  O  2  H            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   116    1    1  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   117    2    3  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   118    3    5  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   119    4    7  \n   -  -  -  -    4.453E-03 5.223E+00                 -  -    -   120    5    9  \n   -  -  -  -    8.906E-03 5.223E+00                 -  -    -   121    6   11  \n   -  -  -  -    1.781E-02 5.223E+00                 -  -    -   122    7   13  \n   -  -  -  -    4.453E-02 5.223E+00                 -  -    -   123    8   15  \n   2  O  2  O            *         *         6.965E+01  2 0.00     *    *    *  \n   -  -  -  -    2.969E-05 0.000E+00                 -  -    -   126    1    2  \n   -  -  -  -    2.969E-04 0.000E+00                 -  -    -   127    2    4  \n   -  -  -  -    8.906E-04 0.000E+00                 -  -    -   128    3    6  \n   -  -  -  -    1.781E-03 0.000E+00                 -  -    -   129    4    8  \n   -  -  -  -    4.453E-03 2.322E+01                 -  -    -   130    5   10  \n   -  -  -  -    8.906E-03 2.322E+01                 -  -    -   131    6   12  \n   -  -  -  -    1.781E-02 2.322E+01                 -  -    -   132    7   14  \n   -  -  -  -    4.453E-02 2.322E+01                 -  -    -   133    8   16  \n   3  O  3  H  H         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-04 0.000E+00 -1  4.0         -  -    -   150    1   21 1\n   -  -  -  -  - 2.969E-04 0.000E+00  1  4.0         -  -    -   148    2   22 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   145    3   23 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   143    4   26 0\n   -  -  -  -  - 2.078E-03 0.000E+00 -1  1.0         -  -    -   140    5   29 1\n   -  -  -  -  - 2.078E-03 0.000E+00  1  1.0         -  -    -   138    6   30 0\n   4  O  3  H  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   156    1   17 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   155    2   19 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   154    3   24 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   153    4   27 0\n   5  O  3  O  O         *         *  *    * 6.965E+01  2 0.00     *    *    * *\n   -  -  -  -  - 2.969E-05 0.000E+00 -1  4.0         -  -    -   166    1   18 1\n   -  -  -  -  - 2.969E-05 0.000E+00  1  4.0         -  -    -   165    2   20 0\n   -  -  -  -  - 8.906E-04 0.000E+00 -1  1.0         -  -    -   164    3   25 1\n   -  -  -  -  - 8.906E-04 0.000E+00  1  1.0         -  -    -   163    4   28 0\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: NEURAL NETWORKS ****************************************************\n\nNormalize neurons (all elements): 0\n-------------------------------------------------------------------------------\nAtomic short range NN for element  H :\nNumber of weights    :   1325\nNumber of biases     :     51\nNumber of connections:   1376\nArchitecture       27   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n-------------------------------------------------------------------------------\nAtomic short range NN for element  O :\nNumber of weights    :   1400\nNumber of biases     :     51\nNumber of connections:   1451\nArchitecture       30   25   25    1\n-------------------------------------------------------------------------------\n   1   G   t   t   l\n   2   G   t   t    \n   3   G   t   t    \n   4   G   t   t    \n   5   G   t   t    \n   6   G   t   t    \n   7   G   t   t    \n   8   G   t   t    \n   9   G   t   t    \n  10   G   t   t    \n  11   G   t   t    \n  12   G   t   t    \n  13   G   t   t    \n  14   G   t   t    \n  15   G   t   t    \n  16   G   t   t    \n  17   G   t   t    \n  18   G   t   t    \n  19   G   t   t    \n  20   G   t   t    \n  21   G   t   t    \n  22   G   t   t    \n  23   G   t   t    \n  24   G   t   t    \n  25   G   t   t    \n  26   G            \n  27   G            \n  28   G            \n  29   G            \n  30   G            \n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\nEqual scaling type for all symmetry functions:\nScaling type::ST_SCALECENTER (3)\nGs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\nSmin = 0.000000\nSmax = 1.000000\nSymmetry function scaling statistics from file: scaling.data\n-------------------------------------------------------------------------------\n\nAbbreviations:\n--------------\nind ..... Symmetry function index.\nmin ..... Minimum symmetry function value.\nmax ..... Maximum symmetry function value.\nmean .... Mean symmetry function value.\nsigma ... Standard deviation of symmetry function values.\nsf ...... Scaling factor for derivatives.\nSmin .... Desired minimum scaled symmetry function value.\nSmax .... Desired maximum scaled symmetry function value.\nt ....... Scaling type.\n\nScaling data for symmetry functions element  H :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  1.09E+00  9.62E+00  2.27E+00  6.79E-01  1.17E-01  0.00  1.00 3\n   2  7.33E-01  5.00E+00  1.33E+00  3.39E-01  2.34E-01  0.00  1.00 3\n   3  7.60E-01  7.14E+00  1.65E+00  5.08E-01  1.57E-01  0.00  1.00 3\n   4  5.48E-01  3.77E+00  1.02E+00  2.54E-01  3.11E-01  0.00  1.00 3\n   5  4.01E-01  4.15E+00  9.09E-01  2.98E-01  2.67E-01  0.00  1.00 3\n   6  3.62E-01  2.27E+00  6.49E-01  1.48E-01  5.25E-01  0.00  1.00 3\n   7  1.89E-01  2.23E+00  4.57E-01  1.60E-01  4.90E-01  0.00  1.00 3\n   8  2.67E-01  1.32E+00  4.24E-01  8.05E-02  9.49E-01  0.00  1.00 3\n   9  2.45E-01  9.48E-01  3.62E-01  5.30E-02  1.42E+00  0.00  1.00 3\n  10  2.22E-01  2.76E+00  5.39E-01  2.01E-01  3.94E-01  0.00  1.00 3\n  11  1.47E-01  5.56E-01  2.68E-01  2.62E-02  2.45E+00  0.00  1.00 3\n  12  9.91E-02  1.73E+00  2.96E-01  1.16E-01  6.14E-01  0.00  1.00 3\n  13  6.51E-02  3.45E-01  1.85E-01  1.97E-02  3.57E+00  0.00  1.00 3\n  14  3.17E-02  9.13E-01  1.50E-01  5.35E-02  1.13E+00  0.00  1.00 3\n  15  2.92E-03  2.65E-01  7.65E-02  1.88E-02  3.82E+00  0.00  1.00 3\n  16  3.21E-04  2.87E-01  4.58E-02  2.33E-02  3.49E+00  0.00  1.00 3\n  17  2.47E-04  1.38E-01  1.77E-02  9.75E-03  7.23E+00  0.00  1.00 3\n  18  5.10E-03  5.83E-01  2.39E-02  3.78E-02  1.73E+00  0.00  1.00 3\n  19  3.23E-04  2.16E-01  1.71E-02  1.40E-02  4.63E+00  0.00  1.00 3\n  20  4.96E-02  1.69E+00  1.45E-01  1.10E-01  6.11E-01  0.00  1.00 3\n  21  3.41E-03  3.16E-01  1.84E-02  2.01E-02  3.20E+00  0.00  1.00 3\n  22  1.31E-04  1.03E-01  6.37E-03  6.61E-03  9.76E+00  0.00  1.00 3\n  23  3.38E-02  9.16E-01  8.13E-02  5.79E-02  1.13E+00  0.00  1.00 3\n  24  4.17E-04  1.58E-01  4.66E-03  9.86E-03  6.35E+00  0.00  1.00 3\n  25  7.35E-04  5.92E-02  3.70E-03  3.31E-03  1.71E+01  0.00  1.00 3\n  26  8.98E-03  1.94E-01  2.41E-02  1.10E-02  5.40E+00  0.00  1.00 3\n  27  2.12E-04  8.78E-03  2.06E-03  5.88E-04  1.17E+02  0.00  1.00 3\n-------------------------------------------------------------------------------\nScaling data for symmetry functions element  O :\n-------------------------------------------------------------------------------\n ind       min       max      mean     sigma        sf  Smin  Smax t\n-------------------------------------------------------------------------------\n   1  1.51E+00  1.00E+01  2.65E+00  6.78E-01  1.18E-01  0.00  1.00 3\n   2  4.44E-01  4.62E+00  9.66E-01  3.37E-01  2.39E-01  0.00  1.00 3\n   3  1.19E+00  7.53E+00  2.03E+00  5.06E-01  1.58E-01  0.00  1.00 3\n   4  2.76E-01  3.39E+00  6.59E-01  2.50E-01  3.21E-01  0.00  1.00 3\n   5  8.06E-01  4.54E+00  1.30E+00  2.94E-01  2.68E-01  0.00  1.00 3\n   6  1.05E-01  1.89E+00  3.07E-01  1.42E-01  5.60E-01  0.00  1.00 3\n   7  5.69E-01  2.62E+00  8.48E-01  1.57E-01  4.89E-01  0.00  1.00 3\n   8  2.33E-02  9.36E-01  1.11E-01  6.98E-02  1.10E+00  0.00  1.00 3\n   9  5.14E-01  1.85E+00  7.25E-01  9.80E-02  7.46E-01  0.00  1.00 3\n  10  1.11E-01  2.91E+00  4.75E-01  2.34E-01  3.57E-01  0.00  1.00 3\n  11  3.53E-01  1.07E+00  5.35E-01  4.52E-02  1.39E+00  0.00  1.00 3\n  12  3.04E-02  2.53E+00  3.17E-01  2.10E-01  4.00E-01  0.00  1.00 3\n  13  1.60E-01  6.63E-01  3.70E-01  3.08E-02  1.99E+00  0.00  1.00 3\n  14  2.78E-03  2.30E+00  1.77E-01  1.86E-01  4.35E-01  0.00  1.00 3\n  15  9.56E-03  3.91E-01  1.53E-01  2.79E-02  2.62E+00  0.00  1.00 3\n  16  3.75E-06  2.04E+00  5.41E-02  1.43E-01  4.91E-01  0.00  1.00 3\n  17  2.47E-03  3.43E-01  1.67E-02  2.19E-02  2.93E+00  0.00  1.00 3\n  18  1.74E-05  5.63E-02  9.55E-04  3.36E-03  1.78E+01  0.00  1.00 3\n  19  5.48E-02  3.02E+00  2.04E-01  2.01E-01  3.37E-01  0.00  1.00 3\n  20  1.38E-03  4.99E-01  1.28E-02  3.18E-02  2.01E+00  0.00  1.00 3\n  21  6.69E-03  2.67E-01  3.09E-02  1.71E-02  3.84E+00  0.00  1.00 3\n  22  1.70E-02  1.42E+00  7.63E-02  9.29E-02  7.14E-01  0.00  1.00 3\n  23  1.98E-02  4.08E-01  4.88E-02  2.55E-02  2.58E+00  0.00  1.00 3\n  24  5.28E-04  2.33E-01  7.21E-03  1.45E-02  4.30E+00  0.00  1.00 3\n  25  1.11E-05  3.53E-02  4.25E-04  2.05E-03  2.83E+01  0.00  1.00 3\n  26  1.60E-02  8.22E-01  5.08E-02  5.28E-02  1.24E+00  0.00  1.00 3\n  27  3.99E-03  7.86E-01  3.69E-02  5.05E-02  1.28E+00  0.00  1.00 3\n  28  4.05E-05  9.84E-02  1.21E-03  5.79E-03  1.02E+01  0.00  1.00 3\n  29  6.04E-03  9.93E-02  1.62E-02  5.52E-03  1.07E+01  0.00  1.00 3\n  30  2.96E-03  1.55E-01  1.16E-02  8.94E-03  6.59E+00  0.00  1.00 3\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\nEqual symmetry function statistics for all elements.\nCollect min/max/mean/sigma                        : 0\nCollect extrapolation warnings                    : 0\nWrite extrapolation warnings immediately to stderr: 0\nHalt on any extrapolation warning                 : 0\n*******************************************************************************\n\n*** SETUP: RANDOM NUMBER GENERATOR ********************************************\n\nRandom number generator seed: 2\nSeed for rank 0: 2\nSeed for rank 1: 1872583848\nSeed for rank 2: 794921487\nSeed for rank 3: 111352301\nSeed for rank 4: 4000937544\nSeed for rank 5: 2360782358\nSeed for rank 6: 4070471979\nSeed for rank 7: 1869695442\nSeed for rank 8: 2081981515\nSeed for rank 9: 1805465960\nSeed for rank 10: 1376693511\nSeed for rank 11: 1418777250\nSeed for rank 12: 663257521\nSeed for rank 13: 878959199\nSeed for rank 14: 3001592395\nSeed for rank 15: 2659748565\nSeed for global RNG: 515183663\n*******************************************************************************\n\n*** STRUCTURE DISTRIBUTION ****************************************************\n\nReading configurations from data file: input.data.\nTotal number of structures: 7241\nNumber of structures per processor: 452 (7) or 453 (9)\nDistributed 7241 structures, 123519504 bytes (117.80 MiB) transferred.\nNumber of local structures: 452\n*******************************************************************************\n\n*** DEFINE TRAINING/TEST SETS *************************************************\n\nDesired test set ratio      : 0.100000\nTotal number of energies    : 7241\nNumber of training energies : 6533\nNumber of test     energies : 708\nNumber of training forces   : 1596654\nNumber of test     forces   : 169290\nActual test set fraction    : 0.097777\n*******************************************************************************\n\n*** WRITE TRAINING/TEST SETS **************************************************\n\nWriting training/test set to files:\n - train.data\n - test.data\n*******************************************************************************\n\n*** WEIGHT INITIALIZATION *****************************************************\n\nInitial weights selected randomly in interval [-1.000000, 1.000000).\nWeights modified accoring to Glorot Bengio scheme.\nBiases set to zero.\n*******************************************************************************\n\n*** SETUP: TRAINING ***********************************************************\n\nForces will be used for training.\nForce update weight:   1.00E+01\nWeight update via Kalman filter selected: updaterType::UT_KALMANFILTER (1)\nMulti-stream Kalman filter training, update on rank 0, partial X calculation selected: ParallelMode::PM_MSEKFR0PX (4)\nNumber of streams       : 16\nStream of this processor: 0\nCombined updater for all elements selected: UpdateStrategy::US_COMBINED (0)\nNumber of weight updaters    : 1\nTotal fit parameters         : 2827\nSelection mode starting with epoch 0:\nUpdate candidates chosen randomly above RMSE threshold: SelectionMode::SM_THRESHOLD (2)\nEnergy threshold: 1.00 * RMSE(Energy)\nForce  threshold: 1.00 * RMSE(Force)\nMaximum number of update candidate trials: 3\n-------------------------------------------------------------------------------\nSymmetry function memory is reused (HIGH MEMORY USAGE!).\nTraining will be stopped after 25 epochs.\nEnergy comparison will be written every 25 epochs.\nForce comparison will be written every 25 epochs.\nWeights will be written every 1 epochs.\nNeuron statistics will be written every 5 epochs.\nUp to epoch 10 neuron statistics will be written every epoch.\nTraining log with update information will be written to: train-log.out.\n-------------------------------------------------------------------------------\nFraction of energies used per epoch:    1.0000\nFraction of forces used per epoch  :    0.0410\nProjected energy updates per epoch :     408 (  9.1%)\nProjected forces updates per epoch :    4091 ( 90.9%)\nTotal projected updates per epoch  :    4500\nMulti-stream training uses 16 energies/forces per weight update.\nqtau is divided by number of projected updates per epoch.\netatau is divided by number of projected updates per epoch.\n-------------------------------------------------------------------------------\nCombined weight updater:\n-------------------------------------------------------------------------------\nKalmanType::KT_STANDARD (0)\nsizeState       = 2827\nsizeObservation = 16\nepsilon         =   1.0000E-02\nq0              =   1.0000E-02\nqtau            =   5.1159E-04\nqmin            =   1.0000E-06\neta0            =   1.0000E-02\netatau          =   5.1159E-04\netamax          =   1.0000E+00\nKalmanParallel::KP_PRECALCX (2)\nOpenMP threads used: 1\n-------------------------------------------------------------------------------\n*******************************************************************************\n\n*** CALCULATE NEIGHBOR LISTS **************************************************\n\nCalculating neighbor lists for all structures.\nCutoff radius for neighbor lists: 69.646139\n*******************************************************************************\n\n*** TRAINING LOOP *************************************************************\n\nThe training loop output covers different RMSEs, update and\ntiming information. The following quantities are organized\naccording to the matrix scheme below:\n-------------------------------------------------------------------\nep ............ Epoch.\nEtrain_phys ... RMSE of training energies per atom (p. u.).\nEtest_phys .... RMSE of test     energies per atom (p. u.).\nEtrain_int .... RMSE of training energies per atom (i. u.).\nEtest_int ..... RMSE of test     energies per atom (i. u.).\nFtrain_phys ... RMSE of training forces (p. u.).\nFtest_phys .... RMSE of test     forces (p. u.).\nFtrain_int .... RMSE of training forces (i. u.).\nFtest_int ..... RMSE of test     forces (i. u.).\nE_count ....... Number of energy updates.\nF_count ....... Number of force  updates.\ncount ......... Total number of updates.\nt_train ....... Time for training (seconds).\nt_rmse ........ Time for RMSE calculation (seconds).\nt_epoch ....... Total time for this epoch (seconds).\nt_tot ......... Total time for all epochs (seconds).\nAbbreviations:\n  p. u. = physical units.\n  i. u. = internal units.\nNote: RMSEs in internal units (columns 5 + 6) are only present \n      if data set normalization is used.\n-------------------------------------------------------------------\n     1    2             3             4             5             6\nenergy   ep   Etrain_phys    Etest_phys    Etrain_int     Etest_int\nforces   ep   Ftrain_phys    Ftest_phys    Ftrain_int     Ftest_int\nupdate   ep       E_count       F_count         count\ntiming   ep       t_train        t_rmse       t_epoch         t_tot\n-------------------------------------------------------------------\nENERGY    0   3.72115E-03   3.81895E-03   9.02965E-01   9.26696E-01\nFORCES    0   2.34072E-02   2.29953E-02   9.78649E-01   9.61428E-01\nTIMING    0          0.00         30.72         30.75         30.75\n------\nENERGY    1   5.27269E-05   5.44783E-05   1.27946E-02   1.32196E-02\nFORCES    1   9.78255E-04   9.47430E-04   4.09006E-02   3.96118E-02\nUPDATE    1           408          4076          4484\nTIMING    1        547.67          2.61        550.32        581.07\n------\nENERGY    2   9.56678E-05   8.86669E-05   2.32145E-02   2.15157E-02\nFORCES    2   8.94076E-04   8.74898E-04   3.73811E-02   3.65793E-02\nUPDATE    2           408          4082          4490\nTIMING    2        525.97          2.71        528.71       1109.78\n------\nENERGY    3   3.38638E-05   3.30619E-05   8.21730E-03   8.02272E-03\nFORCES    3   7.89628E-04   7.69554E-04   3.30142E-02   3.21749E-02\nUPDATE    3           408          3997          4405\nTIMING    3        517.62          2.69        520.35       1630.13\n------\nENERGY    4   2.69193E-05   2.55573E-05   6.53218E-03   6.20168E-03\nFORCES    4   7.54758E-04   7.38703E-04   3.15563E-02   3.08850E-02\nUPDATE    4           408          4143          4551\nTIMING    4        530.61          2.66        533.30       2163.43\n------\nENERGY    5   3.67487E-05   3.57290E-05   8.91736E-03   8.66991E-03\nFORCES    5   7.34764E-04   7.34122E-04   3.07203E-02   3.06935E-02\nUPDATE    5           408          3987          4395\nTIMING    5        508.88          2.63        511.54       2674.97\n------\nENERGY    6   3.05092E-05   3.02791E-05   7.40328E-03   7.34745E-03\nFORCES    6   7.24954E-04   7.21860E-04   3.03102E-02   3.01808E-02\nUPDATE    6           408          4077          4485\nTIMING    6        520.66          2.68        523.37       3198.34\n------\nENERGY    7   4.44131E-05   4.29940E-05   1.07772E-02   1.04328E-02\nFORCES    7   7.19542E-04   7.18822E-04   3.00839E-02   3.00538E-02\nUPDATE    7           408          4151          4559\nTIMING    7        529.47          2.71        532.21       3730.55\n------\nENERGY    8   3.55360E-05   3.40692E-05   8.62307E-03   8.26716E-03\nFORCES    8   7.22773E-04   7.20229E-04   3.02190E-02   3.01126E-02\nUPDATE    8           408          4151          4559\nTIMING    8        527.71          2.63        530.38       4260.93\n------\nENERGY    9   2.65646E-05   2.57801E-05   6.44610E-03   6.25574E-03\nFORCES    9   7.14881E-04   7.12744E-04   2.98890E-02   2.97997E-02\nUPDATE    9           408          4051          4459\nTIMING    9        515.96          2.67        518.66       4779.59\n------\nENERGY   10   2.74199E-05   2.62896E-05   6.65364E-03   6.37936E-03\nFORCES   10   7.14391E-04   7.12126E-04   2.98685E-02   2.97738E-02\nUPDATE   10           408          4054          4462\nTIMING   10        519.13          2.76        521.92       5301.51\n------\nENERGY   11   2.74124E-05   2.69574E-05   6.65184E-03   6.54141E-03\nFORCES   11   7.15474E-04   7.13003E-04   2.99138E-02   2.98105E-02\nUPDATE   11           408          3931          4339\nTIMING   11        501.49          2.65        504.17       5805.68\n------\nENERGY   12   2.87293E-05   2.82820E-05   6.97137E-03   6.86285E-03\nFORCES   12   7.14605E-04   7.12197E-04   2.98775E-02   2.97768E-02\nUPDATE   12           408          4122          4530\nTIMING   12        526.86          2.66        529.54       6335.22\n------\nENERGY   13   2.50400E-05   2.41467E-05   6.07614E-03   5.85937E-03\nFORCES   13   7.12309E-04   7.11631E-04   2.97815E-02   2.97531E-02\nUPDATE   13           408          4009          4417\nTIMING   13        511.79          2.72        514.54       6849.76\n------\nENERGY   14   3.27553E-05   3.21490E-05   7.94833E-03   7.80119E-03\nFORCES   14   7.11961E-04   7.10919E-04   2.97669E-02   2.97234E-02\nUPDATE   14           408          4132          4540\nTIMING   14        526.43          2.68        529.14       7378.90\n------\nENERGY   15   3.24771E-05   3.11575E-05   7.88081E-03   7.56061E-03\nFORCES   15   7.07100E-04   7.05472E-04   2.95637E-02   2.94956E-02\nUPDATE   15           408          4053          4461\nTIMING   15        515.38          2.65        518.06       7896.96\n------\nENERGY   16   3.12976E-05   3.18343E-05   7.59461E-03   7.72483E-03\nFORCES   16   7.10094E-04   7.07533E-04   2.96889E-02   2.95818E-02\nUPDATE   16           408          4104          4512\nTIMING   16        523.43          2.71        526.17       8423.13\n------\nENERGY   17   2.70985E-05   2.73839E-05   6.57565E-03   6.64491E-03\nFORCES   17   7.07123E-04   7.06332E-04   2.95647E-02   2.95316E-02\nUPDATE   17           408          4021          4429\nTIMING   17        513.31          2.67        516.01       8939.14\n------\nENERGY   18   3.09332E-05   2.91548E-05   7.50617E-03   7.07463E-03\nFORCES   18   7.05834E-04   7.04317E-04   2.95108E-02   2.94473E-02\nUPDATE   18           408          4079          4487\nTIMING   18        521.91          2.66        524.60       9463.74\n------\nENERGY   19   3.26598E-05   3.28139E-05   7.92515E-03   7.96254E-03\nFORCES   19   7.05070E-04   7.01846E-04   2.94788E-02   2.93440E-02\nUPDATE   19           408          4033          4441\nTIMING   19        514.32          2.69        517.05       9980.78\n------\nENERGY   20   2.60466E-05   2.47333E-05   6.32039E-03   6.00173E-03\nFORCES   20   7.06028E-04   7.04603E-04   2.95189E-02   2.94593E-02\nUPDATE   20           408          4026          4434\nTIMING   20        568.05          2.67        570.75      10551.53\n------\nENERGY   21   2.80412E-05   2.81732E-05   6.80440E-03   6.83644E-03\nFORCES   21   7.11965E-04   7.11953E-04   2.97671E-02   2.97666E-02\nUPDATE   21           408          4012          4420\nTIMING   21        518.97          2.80        521.80      11073.33\n------\nENERGY   22   2.64661E-05   2.60412E-05   6.42221E-03   6.31908E-03\nFORCES   22   7.14539E-04   7.13341E-04   2.98747E-02   2.98246E-02\nUPDATE   22           408          4038          4446\nTIMING   22        520.31          2.72        523.07      11596.40\n------\nENERGY   23   3.66545E-05   3.65880E-05   8.89450E-03   8.87835E-03\nFORCES   23   7.05732E-04   7.05303E-04   2.95065E-02   2.94886E-02\nUPDATE   23           408          4078          4486\nTIMING   23        526.46          3.31        529.80      12126.21\n------\nENERGY   24   3.00251E-05   2.86382E-05   7.28581E-03   6.94926E-03\nFORCES   24   7.05073E-04   7.02898E-04   2.94790E-02   2.93880E-02\nUPDATE   24           408          3989          4397\nTIMING   24        515.17          2.68        517.87      12644.08\n------\nENERGY   25   3.24461E-05   3.15622E-05   7.87329E-03   7.65879E-03\nFORCES   25   7.06710E-04   7.05342E-04   2.95474E-02   2.94902E-02\nUPDATE   25           408          4053          4461\nTIMING   25        523.39          3.60        527.02      13171.10\n*******************************************************************************\n"
  },
  {
    "path": "examples/potentials/H2O_RPBE-D3/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "examples/potentials/H2O_RPBE-D3/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.2539155865352127E+00 a         1     0     1     1     1\n  2.2490365890661286E+00 a         2     0     1     1     2\n  4.9361851928374572E+00 a         3     0     1     1     3\n -2.3971991574908125E+00 a         4     0     1     1     4\n -1.8596992303156465E+00 a         5     0     1     1     5\n  3.8287764168815897E+00 a         6     0     1     1     6\n  7.4523181738636106E+00 a         7     0     1     1     7\n  6.0971861116881998E+00 a         8     0     1     1     8\n -8.7239359226117639E+00 a         9     0     1     1     9\n -1.8255232070184267E+01 a        10     0     1     1    10\n -7.8065643887610179E+00 a        11     0     1     1    11\n  1.4247237398130265E+01 a        12     0     1     1    12\n -3.2217879518334338E+00 a        13     0     1     1    13\n -5.7395252086520712E+00 a        14     0     1     1    14\n  2.0353040522911576E+00 a        15     0     1     1    15\n  7.7520578160630560E+00 a        16     0     1     1    16\n  2.9357257867412252E+00 a        17     0     1     1    17\n -2.9719860930100790E+00 a        18     0     1     1    18\n  8.9245382590288980E+00 a        19     0     1     1    19\n  6.6848134049442169E+00 a        20     0     1     1    20\n -2.2992719903495891E+00 a        21     0     1     1    21\n -1.4401533482181721E+01 a        22     0     1     1    22\n -2.0574070545285186E+00 a        23     0     1     1    23\n -6.3544667277888678E+00 a        24     0     1     1    24\n  3.9668360525851707E+00 a        25     0     1     1    25\n  1.0930597297534963E+01 a        26     0     2     1     1\n  3.0058866618169424E+00 a        27     0     2     1     2\n -4.9950943102999927E+00 a        28     0     2     1     3\n -1.9930957240687266E+00 a        29     0     2     1     4\n  1.6790893133342006E+00 a        30     0     2     1     5\n -4.5254006136507128E+00 a        31     0     2     1     6\n -9.6165021729265252E+00 a        32     0     2     1     7\n -8.7465722730176285E+00 a        33     0     2     1     8\n  1.5506950040431201E+01 a        34     0     2     1     9\n  2.1903342918227118E+01 a        35     0     2     1    10\n -1.0685216745153280E+01 a        36     0     2     1    11\n -2.5859690636594280E+01 a        37     0     2     1    12\n -3.2423603491405122E+00 a        38     0     2     1    13\n  5.3753900550878555E+00 a        39     0     2     1    14\n -3.0291935617567991E+00 a        40     0     2     1    15\n -1.3534893178408465E+01 a        41     0     2     1    16\n -5.7625138055631471E+00 a        42     0     2     1    17\n  1.0216765318459601E+01 a        43     0     2     1    18\n -1.4416012930050949E+01 a        44     0     2     1    19\n -4.7226757471872144E-01 a        45     0     2     1    20\n  7.8981385188798026E+00 a        46     0     2     1    21\n  1.2202710023744410E+00 a        47     0     2     1    22\n  8.0560891210932120E+00 a        48     0     2     1    23\n  4.5972445013263297E-01 a        49     0     2     1    24\n  1.3374237019728858E+01 a        50     0     2     1    25\n -1.0644910441621166E+01 a        51     0     3     1     1\n -5.6098794516515920E+00 a        52     0     3     1     2\n -1.0236653403367724E+01 a        53     0     3     1     3\n  1.3552139405799508E+00 a        54     0     3     1     4\n  1.3201025058567883E+00 a        55     0     3     1     5\n  1.6531266759009673E+00 a        56     0     3     1     6\n -1.0303768926395865E+01 a        57     0     3     1     7\n  1.9927521303470008E-01 a        58     0     3     1     8\n  8.1216226663758366E+00 a        59     0     3     1     9\n  2.1349555016157687E+01 a        60     0     3     1    10\n  1.0105416692705148E+01 a        61     0     3     1    11\n -1.1444993918278378E+01 a        62     0     3     1    12\n  2.9861675555209538E-01 a        63     0     3     1    13\n  9.3552992513120543E+00 a        64     0     3     1    14\n -2.2844869025933630E+00 a        65     0     3     1    15\n -3.8047300595857316E+00 a        66     0     3     1    16\n -3.0512161452147448E+00 a        67     0     3     1    17\n  2.7887340590896472E+00 a        68     0     3     1    18\n -1.5988439945122812E+01 a        69     0     3     1    19\n -1.6917164763280326E+01 a        70     0     3     1    20\n  3.2170907488709326E+00 a        71     0     3     1    21\n  2.1641888770160929E+01 a        72     0     3     1    22\n  3.2604671723420497E+00 a        73     0     3     1    23\n  1.5230689068493776E+01 a        74     0     3     1    24\n -1.4713830039823366E+01 a        75     0     3     1    25\n -2.3544214523969775E+00 a        76     0     4     1     1\n -5.8299691629399382E+00 a        77     0     4     1     2\n  1.7168784391956539E+01 a        78     0     4     1     3\n  1.0050003860864617E+01 a        79     0     4     1     4\n  3.5168903759752812E+00 a        80     0     4     1     5\n -4.4828111046589010E+00 a        81     0     4     1     6\n  1.8299193380051442E+01 a        82     0     4     1     7\n  6.9717289110204188E+00 a        83     0     4     1     8\n -2.0364082994445859E+01 a        84     0     4     1     9\n -3.5062338388300589E+01 a        85     0     4     1    10\n  1.8010375764887119E+01 a        86     0     4     1    11\n  4.2133659287179640E+01 a        87     0     4     1    12\n  1.1988736553417061E+01 a        88     0     4     1    13\n -1.2351529706885179E+01 a        89     0     4     1    14\n  5.4139212296285057E+00 a        90     0     4     1    15\n  1.6705967069968899E+01 a        91     0     4     1    16\n  8.3219076874511639E+00 a        92     0     4     1    17\n -1.8555777504879448E+01 a        93     0     4     1    18\n  3.1433889377775369E+01 a        94     0     4     1    19\n  6.7043459658252780E-01 a        95     0     4     1    20\n -1.3837570456349678E+01 a        96     0     4     1    21\n  5.0298368971353791E-01 a        97     0     4     1    22\n -2.2656240789613065E+01 a        98     0     4     1    23\n -2.4243684644962626E+00 a        99     0     4     1    24\n -2.8280330035212309E+01 a       100     0     4     1    25\n  4.2306100814115322E+00 a       101     0     5     1     1\n  9.9770374716830084E+00 a       102     0     5     1     2\n  2.0487048112933808E+00 a       103     0     5     1     3\n -1.3702212470739978E+00 a       104     0     5     1     4\n  2.8131124422603837E+00 a       105     0     5     1     5\n  3.2845640151619522E-03 a       106     0     5     1     6\n  2.4065616021196026E+00 a       107     0     5     1     7\n -1.0461000723401572E+01 a       108     0     5     1     8\n -1.0180720750329515E+01 a       109     0     5     1     9\n -8.8668996772076660E+00 a       110     0     5     1    10\n  6.5256092481271502E+00 a       111     0     5     1    11\n -6.9831054240027211E+00 a       112     0     5     1    12\n  4.0892074148312876E+00 a       113     0     5     1    13\n -5.1951354450201128E+00 a       114     0     5     1    14\n  1.6657989141753051E+00 a       115     0     5     1    15\n -7.3542511663155619E+00 a       116     0     5     1    16\n  5.1573102842565115E+00 a       117     0     5     1    17\n  3.4929930175122172E+00 a       118     0     5     1    18\n  2.5382184218789963E+00 a       119     0     5     1    19\n  2.0045179007481050E+01 a       120     0     5     1    20\n -1.6165269676512768E+00 a       121     0     5     1    21\n  2.4869117790922393E+00 a       122     0     5     1    22\n  6.0131560843540068E+00 a       123     0     5     1    23\n -1.2231651850388728E+01 a       124     0     5     1    24\n  3.5372450187997345E+01 a       125     0     5     1    25\n -1.0433252604911765E+01 a       126     0     6     1     1\n -2.3715834640656657E+00 a       127     0     6     1     2\n -1.8239608965373137E+01 a       128     0     6     1     3\n -3.6510816169583777E+00 a       129     0     6     1     4\n -1.7632327653119535E+01 a       130     0     6     1     5\n  1.0040509177650593E+01 a       131     0     6     1     6\n -1.5407385349225459E+01 a       132     0     6     1     7\n -7.0553605774310779E-01 a       133     0     6     1     8\n  1.3204892207903583E+01 a       134     0     6     1     9\n  2.9596389655595953E+01 a       135     0     6     1    10\n -2.0620173259628203E+01 a       136     0     6     1    11\n -3.0803380363815094E+01 a       137     0     6     1    12\n -1.4917676387082279E+01 a       138     0     6     1    13\n  9.6935054799166185E+00 a       139     0     6     1    14\n  4.6937319413252743E+00 a       140     0     6     1    15\n -5.0263591258131060E+00 a       141     0     6     1    16\n -9.7243575590712439E+00 a       142     0     6     1    17\n  1.5625340951727363E+01 a       143     0     6     1    18\n -2.8266776356585389E+01 a       144     0     6     1    19\n  2.5386057418612946E+00 a       145     0     6     1    20\n  1.6302330128073283E+01 a       146     0     6     1    21\n -8.5166226512297030E+00 a       147     0     6     1    22\n  2.5040570504752605E+01 a       148     0     6     1    23\n -8.5008658358878897E-01 a       149     0     6     1    24\n  2.0458930574550632E+01 a       150     0     6     1    25\n  7.8529627796707677E+00 a       151     0     7     1     1\n -4.5279242985866821E+00 a       152     0     7     1     2\n  4.7942839133231594E+00 a       153     0     7     1     3\n -6.2431002330064649E+00 a       154     0     7     1     4\n  4.3358077462982054E+00 a       155     0     7     1     5\n -6.8037589596444281E+00 a       156     0     7     1     6\n  1.8980667946224101E+00 a       157     0     7     1     7\n  1.9802532239433695E+01 a       158     0     7     1     8\n  8.4826746941006572E+00 a       159     0     7     1     9\n  4.3614399548619884E+00 a       160     0     7     1    10\n -1.6073795583709572E+01 a       161     0     7     1    11\n  1.6345358363876109E+01 a       162     0     7     1    12\n -8.4662611499242502E+00 a       163     0     7     1    13\n  8.0952183951712298E-01 a       164     0     7     1    14\n -1.1658877435292819E+01 a       165     0     7     1    15\n  1.3236001648494756E+01 a       166     0     7     1    16\n -1.2875720369407999E+01 a       167     0     7     1    17\n -2.0324369268053388E+00 a       168     0     7     1    18\n  1.0874203669721311E+01 a       169     0     7     1    19\n -1.7284078771261807E+01 a       170     0     7     1    20\n -2.9714643625232693E+00 a       171     0     7     1    21\n -1.9329510057793893E+01 a       172     0     7     1    22\n -1.0307360045133033E+01 a       173     0     7     1    23\n  4.2080100442235366E+00 a       174     0     7     1    24\n -3.8428801618815640E+01 a       175     0     7     1    25\n 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-6.0004075552166369E-01 a      1269     1    23     2    19\n  8.6767695096505049E-01 a      1270     1    23     2    20\n  1.7471709925670367E-01 a      1271     1    23     2    21\n  6.3494817986861019E-01 a      1272     1    23     2    22\n  7.9839233743975266E-02 a      1273     1    23     2    23\n -8.7497499907984810E-01 a      1274     1    23     2    24\n -2.1279336414401262E-01 a      1275     1    23     2    25\n -1.0628518357816100E+01 a      1276     1    24     2     1\n -3.4149879843865938E-01 a      1277     1    24     2     2\n -4.0534872173827868E-01 a      1278     1    24     2     3\n  1.0980204380257913E-01 a      1279     1    24     2     4\n  1.8376924276804879E-01 a      1280     1    24     2     5\n  8.5047887536146360E-01 a      1281     1    24     2     6\n  4.3913590571042438E-01 a      1282     1    24     2     7\n  2.7167430357232609E+00 a      1283     1    24     2     8\n  2.9682659556600960E-01 a      1284     1    24     2     9\n -1.6032245851281013E+00 a      1285     1    24     2    10\n -6.7567048640865046E-01 a      1286     1    24     2    11\n -1.5253382251900995E+00 a      1287     1    24     2    12\n -6.7540631566041298E-01 a      1288     1    24     2    13\n -1.4565321192168545E+00 a      1289     1    24     2    14\n -1.3315414628143039E+00 a      1290     1    24     2    15\n  1.2552098425264056E+00 a      1291     1    24     2    16\n -1.1701558601459501E+00 a      1292     1    24     2    17\n  2.1967564647703792E+00 a      1293     1    24     2    18\n  3.6767594091430167E-01 a      1294     1    24     2    19\n  1.4791781996464841E+00 a      1295     1    24     2    20\n -2.4597335939693896E+00 a      1296     1    24     2    21\n  1.8222789722776007E+00 a      1297     1    24     2    22\n -2.4818384588216302E+00 a      1298     1    24     2    23\n -1.3359962912345340E+00 a      1299     1    24     2    24\n -1.6060924344568878E-02 a      1300     1    24     2    25\n -1.1558703878945702E+00 a      1301     1    25     2     1\n  5.5859771317693908E-02 a      1302     1    25     2     2\n -1.9275021348316721E+00 a      1303     1    25     2     3\n  4.2881321046205173E-01 a      1304     1    25     2     4\n  6.6308764508018558E-01 a      1305     1    25     2     5\n -2.5357661809360188E-01 a      1306     1    25     2     6\n  7.7965409617466697E-01 a      1307     1    25     2     7\n -1.9470416731652336E+00 a      1308     1    25     2     8\n  2.0923659915641873E-01 a      1309     1    25     2     9\n  8.9211452410465542E-01 a      1310     1    25     2    10\n -1.9807939822570442E-01 a      1311     1    25     2    11\n -5.0922943173038127E-01 a      1312     1    25     2    12\n  1.3378430979044107E+00 a      1313     1    25     2    13\n -6.8964614083753073E-01 a      1314     1    25     2    14\n  7.6939619343191556E-01 a      1315     1    25     2    15\n -1.5783243312480257E+00 a      1316     1    25     2    16\n  2.3586020281744577E+00 a      1317     1    25     2    17\n -5.1641666185758928E-01 a      1318     1    25     2    18\n  1.0291540870545792E+00 a      1319     1    25     2    19\n  1.5269830348487650E+00 a      1320     1    25     2    20\n -2.8987700591417855E+00 a      1321     1    25     2    21\n  9.0207337792476916E-01 a      1322     1    25     2    22\n  1.9890049402284911E+00 a      1323     1    25     2    23\n  3.9387622927433424E-01 a      1324     1    25     2    24\n  9.9397126232482103E-01 a      1325     1    25     2    25\n  2.5306467041996967E+00 b      1326     2     1\n  3.1633393474977245E+00 b      1327     2     2\n -1.1644295509710691E+00 b      1328     2     3\n -5.7686722641223600E+00 b      1329     2     4\n  2.0065022303893989E+00 b      1330     2     5\n -5.9106057000795840E+00 b      1331     2     6\n -1.1326093285804056E+01 b      1332     2     7\n -3.9025063397327071E+00 b      1333     2     8\n  4.4520505166676267E+00 b      1334     2     9\n -1.7352681951318241E+00 b      1335     2    10\n -2.1518912430432668E+00 b      1336     2    11\n  5.0463376560082969E+00 b      1337     2    12\n -2.2614514173852837E-01 b      1338     2    13\n -4.1454590614747211E+00 b      1339     2    14\n  1.6688417293495756E+00 b      1340     2    15\n -5.8649976938793378E+00 b      1341     2    16\n -3.8350084459541849E+00 b      1342     2    17\n  1.3730477223722950E+00 b      1343     2    18\n  1.8506935712854127E+00 b      1344     2    19\n  5.7362757779153428E+00 b      1345     2    20\n  7.2901484895568780E+00 b      1346     2    21\n  3.9773783666446022E-01 b      1347     2    22\n -6.1298011242151409E+00 b      1348     2    23\n  9.9698755072742991E+00 b      1349     2    24\n  1.1801564149295556E+00 b      1350     2    25\n  1.2704098997067026E+01 a      1351     2     1     3     1\n  1.5947733940307620E+00 a      1352     2     2     3     1\n -1.6022927057878529E+00 a      1353     2     3     3     1\n -1.5507258540777733E+00 a      1354     2     4     3     1\n  1.8696884022727636E+00 a      1355     2     5     3     1\n -8.2051908880071633E-01 a      1356     2     6     3     1\n  9.4325719092522542E-01 a      1357     2     7     3     1\n  2.4098435369626174E+00 a      1358     2     8     3     1\n  1.4100759633042474E+00 a      1359     2     9     3     1\n -1.4613034838529613E+00 a      1360     2    10     3     1\n  1.0296574685193380E+00 a      1361     2    11     3     1\n  1.2413851904356363E+00 a      1362     2    12     3     1\n -6.3168181712211169E-01 a      1363     2    13     3     1\n  7.6424175125347729E+00 a      1364     2    14     3     1\n -1.3477038299214714E+00 a      1365     2    15     3     1\n -1.6064659765754943E+00 a      1366     2    16     3     1\n -8.9624380518145874E-01 a      1367     2    17     3     1\n -1.0509865792522375E+00 a      1368     2    18     3     1\n  8.1847872933853638E-01 a      1369     2    19     3     1\n  1.2845504810303034E+00 a      1370     2    20     3     1\n -5.1879822944368881E-01 a      1371     2    21     3     1\n -7.2018714033119180E-01 a      1372     2    22     3     1\n  5.9870832883780798E+00 a      1373     2    23     3     1\n -6.0589155387470683E-01 a      1374     2    24     3     1\n  5.0177609140285355E+00 a      1375     2    25     3     1\n  9.7386086372975722E+00 b      1376     3     1\n"
  },
  {
    "path": "examples/potentials/H2O_RPBE-D3/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -4.2252995889643252E-01 a         1     0     1     1     1\n -6.0555645962054347E+00 a         2     0     1     1     2\n  1.4040722027928377E+01 a         3     0     1     1     3\n -2.7041370011942618E+00 a         4     0     1     1     4\n -3.8202743208058858E+00 a         5     0     1     1     5\n -3.3612643261393358E+00 a         6     0     1     1     6\n -2.0418101025905258E+00 a         7     0     1     1     7\n  7.5707237340996727E+00 a         8     0     1     1     8\n -5.8098755815926548E+00 a         9     0     1     1     9\n -6.0966886893925210E-01 a        10     0     1     1    10\n  5.8061564015115206E+00 a        11     0     1     1    11\n -1.5509339733099867E+00 a        12     0     1     1    12\n  1.9747395485200818E+00 a        13     0     1     1    13\n  4.5260782279680539E-01 a        14     0     1     1    14\n  9.9210415760283279E+00 a        15     0     1     1    15\n -6.5078831481547121E+00 a        16     0     1     1    16\n -3.4768832871318085E+00 a        17     0     1     1    17\n -1.9463994340943838E+00 a        18     0     1     1    18\n -3.4186058699290269E+00 a        19     0     1     1    19\n  1.2263643166698479E+00 a        20     0     1     1    20\n -5.9171161834436594E+00 a        21     0     1     1    21\n  1.8436267358458363E+00 a        22     0     1     1    22\n -2.3139530616378448E+00 a        23     0     1     1    23\n -1.7228542411478951E+01 a        24     0     1     1    24\n  2.2888610253215895E+00 a        25     0     1     1    25\n  8.0819405565169262E+00 a        26     0     2     1     1\n  8.0066409422078735E+00 a        27     0     2     1     2\n -2.8439251469462398E+01 a        28     0     2     1     3\n -1.1146087290797917E+01 a        29     0     2     1     4\n -7.5292172093563314E+00 a        30     0     2     1     5\n -4.0783685663337641E+00 a        31     0     2     1     6\n -4.4130406528599337E+00 a        32     0     2     1     7\n  1.0563249167508673E+01 a        33     0     2     1     8\n  1.0933105521974941E+01 a        34     0     2     1     9\n -1.1646509907117448E+01 a        35     0     2     1    10\n -7.5007478428041727E+00 a        36     0     2     1    11\n  7.7790182254249176E+00 a        37     0     2     1    12\n  1.1567034492555623E+01 a        38     0     2     1    13\n -4.2051741520233508E+00 a        39     0     2     1    14\n  3.1165306119132130E+00 a        40     0     2     1    15\n  1.6385645103485370E+01 a        41     0     2     1    16\n  2.6440539124381655E+00 a        42     0     2     1    17\n -3.9524518111687827E+00 a        43     0     2     1    18\n -8.7912410635652076E+00 a        44     0     2     1    19\n  4.3903318583813933E+00 a        45     0     2     1    20\n  3.3748047065442632E-01 a        46     0     2     1    21\n -6.6858946327311741E-01 a        47     0     2     1    22\n  5.4447187026310928E+00 a        48     0     2     1    23\n  1.9966018946508100E+01 a        49     0     2     1    24\n -1.7414420670154115E+01 a        50     0     2     1    25\n -3.9418657694849879E-01 a        51     0     3     1     1\n  9.1804829174186846E+00 a        52     0     3     1     2\n -1.0485089041850278E+01 a        53     0     3     1     3\n  8.9380499555048889E+00 a        54     0     3     1     4\n  1.0758607876097068E+01 a        55     0     3     1     5\n  7.2881492125393788E+00 a        56     0     3     1     6\n  8.2627077997774609E+00 a        57     0     3     1     7\n -1.2523613158520124E+01 a        58     0     3     1     8\n  4.5963999046141870E+00 a        59     0     3     1     9\n  8.2776469521184293E+00 a        60     0     3     1    10\n -2.1354371687617113E+00 a        61     0     3     1    11\n -9.0381751821938234E+00 a        62     0     3     1    12\n -1.2209592338152297E+00 a        63     0     3     1    13\n  4.7653671372245672E+00 a        64     0     3     1    14\n -1.7909124818088952E+01 a        65     0     3     1    15\n  3.2182917515973237E+00 a        66     0     3     1    16\n -2.3712750109800793E+00 a        67     0     3     1    17\n  4.6394007836500366E+00 a        68     0     3     1    18\n  2.3761984937954490E+00 a        69     0     3     1    19\n -1.0484832585147684E+01 a        70     0     3     1    20\n  1.2317970755621140E+01 a        71     0     3     1    21\n -1.5014054499447769E+00 a        72     0     3     1    22\n -1.1215435083480425E+00 a        73     0     3     1    23\n  8.9428653321614355E+00 a        74     0     3     1    24\n  1.2636165742848842E+00 a        75     0     3     1    25\n -1.3406492086741725E+01 a        76     0     4     1     1\n -1.0241053204283523E+01 a        77     0     4     1     2\n  4.3016369326050899E+01 a        78     0     4     1     3\n  2.0170433813810671E+01 a        79     0     4     1     4\n  1.3209328101408278E+01 a        80     0     4     1     5\n  1.2456789467161695E+01 a        81     0     4     1     6\n  4.3498515722861573E+00 a        82     0     4     1     7\n -2.1948185511490657E+01 a        83     0     4     1     8\n -1.5329558038416376E+01 a        84     0     4     1     9\n  1.4173337432869845E+01 a        85     0     4     1    10\n  5.6040631650516088E+00 a        86     0     4     1    11\n -9.7646834958548663E+00 a        87     0     4     1    12\n -1.3810669587629080E+01 a        88     0     4     1    13\n -1.5274915717855073E+00 a        89     0     4     1    14\n -1.3662043326477198E+01 a        90     0     4     1    15\n -2.5095635769057225E+01 a        91     0     4     1    16\n  5.4033548590960638E+00 a        92     0     4     1    17\n  1.1047593171711565E+01 a        93     0     4     1    18\n  1.9404912122904062E+01 a        94     0     4     1    19\n  2.4043652449872512E+00 a        95     0     4     1    20\n -3.3818087825635010E+00 a        96     0     4     1    21\n -4.9505657938825802E+00 a        97     0     4     1    22\n  6.2159614529590854E+00 a        98     0     4     1    23\n -1.9315299866781363E+01 a        99     0     4     1    24\n  2.4149549923763363E+01 a       100     0     4     1    25\n  2.2633190213689671E+00 a       101     0     5     1     1\n -1.1275056403465689E+01 a       102     0     5     1     2\n  1.2588751117785917E+00 a       103     0     5     1     3\n -1.7399288116611554E+01 a       104     0     5     1     4\n -1.8915392010979964E+01 a       105     0     5     1     5\n -6.5088880348621911E+00 a       106     0     5     1     6\n -8.7022768117985532E+00 a       107     0     5     1     7\n  9.5716939158219958E+00 a       108     0     5     1     8\n  6.7173652175539926E+00 a       109     0     5     1     9\n -1.0675975211687946E+01 a       110     0     5     1    10\n -9.8676303718126039E+00 a       111     0     5     1    11\n  2.2213929552875065E+01 a       112     0     5     1    12\n -3.9036053816020080E+00 a       113     0     5     1    13\n -1.0319098765495239E+01 a       114     0     5     1    14\n  2.0443220229254024E+01 a       115     0     5     1    15\n -1.4108663925115768E+00 a       116     0     5     1    16\n  8.2741724462704607E+00 a       117     0     5     1    17\n -5.3497533478370061E+00 a       118     0     5     1    18\n  1.0188467515179238E+00 a       119     0     5     1    19\n  3.3447636806848529E+00 a       120     0     5     1    20\n -6.3209134939668381E+00 a       121     0     5     1    21\n  7.0841649292282804E+00 a       122     0     5     1    22\n -1.3545092924552248E+01 a       123     0     5     1    23\n -1.0559922896741500E+00 a       124     0     5     1    24\n -1.6720809451360648E+00 a       125     0     5     1    25\n  2.8772403595811382E+00 a       126     0     6     1     1\n  6.6056181351338488E+00 a       127     0     6     1     2\n -2.1395393088585266E+01 a       128     0     6     1     3\n -1.6735909985964671E+01 a       129     0     6     1     4\n -4.4466039540570526E+00 a       130     0     6     1     5\n -1.9134274750411421E+01 a       131     0     6     1     6\n  7.4840405517853625E+00 a       132     0     6     1     7\n  1.5375004378912831E+01 a       133     0     6     1     8\n -3.2781218210557539E-01 a       134     0     6     1     9\n  5.1424696656729978E+00 a       135     0     6     1    10\n  2.4028588442306344E+00 a       136     0     6     1    11\n  1.6576032835324068E+00 a       137     0     6     1    12\n -1.8331489599850683E+00 a       138     0     6     1    13\n  1.5714883034771246E+01 a       139     0     6     1    14\n  1.3932522318533026E+01 a       140     0     6     1    15\n  3.0252340531342401E+01 a       141     0     6     1    16\n -2.0172838001093005E+01 a       142     0     6     1    17\n -1.3208548828817202E+01 a       143     0     6     1    18\n -1.1333313633908213E+01 a       144     0     6     1    19\n -2.2075367220543007E-01 a       145     0     6     1    20\n  5.4183716265511874E+00 a       146     0     6     1    21\n  4.4469214579975294E+00 a       147     0     6     1    22\n -1.7974421141420628E+01 a       148     0     6     1    23\n  1.3331466657294333E+01 a       149     0     6     1    24\n -1.0273470133062483E+01 a       150     0     6     1    25\n -1.3893961251032516E+00 a       151     0     7     1     1\n  4.8442398001659086E+00 a       152     0     7     1     2\n -1.4036072623897150E+01 a       153     0     7     1     3\n  1.9115742411572878E+01 a       154     0     7     1     4\n  1.7609386484170951E+01 a       155     0     7     1     5\n  7.6541742060341660E+00 a       156     0     7     1     6\n  2.6652782695389745E+00 a       157     0     7     1     7\n -4.1794554937287582E+00 a       158     0     7     1     8\n -1.1905203283691870E+01 a       159     0     7     1     9\n  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-1.2648655109330131E+00 a      1253     1    20     2     3\n -4.3905910522706337E-01 a      1254     1    20     2     4\n  4.2887555555714030E-01 a      1255     1    20     2     5\n  1.3300944280643934E+00 a      1256     1    20     2     6\n  1.0988390404457922E+00 a      1257     1    20     2     7\n  2.3801051936039075E+00 a      1258     1    20     2     8\n  1.1789379212300943E-01 a      1259     1    20     2     9\n  3.9144297908957699E+00 a      1260     1    20     2    10\n  5.5000952527940228E-01 a      1261     1    20     2    11\n  2.4087943927489916E-01 a      1262     1    20     2    12\n -3.7997171313505251E-01 a      1263     1    20     2    13\n -5.4744714104500347E-01 a      1264     1    20     2    14\n  8.9095280999944937E-01 a      1265     1    20     2    15\n -8.7130940035564164E-01 a      1266     1    20     2    16\n  3.7900358553306007E-01 a      1267     1    20     2    17\n  2.1342515402584987E+00 a      1268     1    20     2    18\n  1.2475880574414706E+00 a      1269     1    20     2    19\n  7.8956439485340524E-01 a      1270     1    20     2    20\n  4.6968348528891219E+00 a      1271     1    20     2    21\n  2.4464240930319816E+00 a      1272     1    20     2    22\n -5.7785142905302376E+00 a      1273     1    20     2    23\n -2.3074149497856417E-01 a      1274     1    20     2    24\n -2.6800082940155296E+00 a      1275     1    20     2    25\n -3.2729577955630704E+00 a      1276     1    21     2     1\n -1.2928637501931926E+00 a      1277     1    21     2     2\n -2.2664219916515152E-01 a      1278     1    21     2     3\n  6.8197406796553048E-02 a      1279     1    21     2     4\n  2.2800043902454539E-01 a      1280     1    21     2     5\n -1.4547709606717896E+00 a      1281     1    21     2     6\n -8.9797316703694119E-02 a      1282     1    21     2     7\n -7.9615421262219899E-01 a      1283     1    21     2     8\n -2.5074736863647562E-01 a      1284     1    21     2     9\n -3.2383137185187805E-01 a      1285     1    21     2    10\n -7.7486670060442631E-01 a      1286     1    21     2    11\n -1.7378145875987788E-01 a      1287     1    21     2    12\n  1.7001762592878558E+00 a      1288     1    21     2    13\n -1.7033999809142997E+00 a      1289     1    21     2    14\n  3.7961258225336264E-01 a      1290     1    21     2    15\n  6.0929689839357426E-01 a      1291     1    21     2    16\n -1.9171250145280534E+00 a      1292     1    21     2    17\n -1.6594854242769004E+00 a      1293     1    21     2    18\n -2.8219229087100910E+00 a      1294     1    21     2    19\n -4.3902463688638738E-01 a      1295     1    21     2    20\n -1.1744026035352828E+00 a      1296     1    21     2    21\n  3.9648025457334164E+00 a      1297     1    21     2    22\n -1.3587513635268793E+00 a      1298     1    21     2    23\n  3.9463311556495906E-02 a      1299     1    21     2    24\n -4.6280624473662763E-01 a      1300     1    21     2    25\n  8.3725910272757709E+00 a      1301     1    22     2     1\n  1.2030400911595496E+00 a      1302     1    22     2     2\n  5.2723639396495003E-01 a      1303     1    22     2     3\n  2.4863416823271995E+00 a      1304     1    22     2     4\n  5.0656775645932173E-01 a      1305     1    22     2     5\n  7.8889662692367113E-01 a      1306     1    22     2     6\n  2.7467021112668549E-01 a      1307     1    22     2     7\n  3.5551997281423904E+00 a      1308     1    22     2     8\n -6.9074567194666425E-01 a      1309     1    22     2     9\n  9.2831069742658789E-01 a      1310     1    22     2    10\n -2.7305664188353734E-01 a      1311     1    22     2    11\n -1.6732686793215996E+00 a      1312     1    22     2    12\n -1.2508123463191103E+00 a      1313     1    22     2    13\n  1.4253551144285490E+00 a      1314     1    22     2    14\n -1.2730453204508483E+00 a      1315     1    22     2    15\n -5.6234386233504563E-01 a      1316     1    22     2    16\n  4.7348930208036427E-01 a      1317     1    22     2    17\n  1.4228359329011722E+00 a      1318     1    22     2    18\n -3.0896237212805277E-02 a      1319     1    22     2    19\n -7.7625773033108136E-01 a      1320     1    22     2    20\n  5.1571228251110171E-02 a      1321     1    22     2    21\n -1.5781774955827834E+00 a      1322     1    22     2    22\n -1.7313703986673430E+00 a      1323     1    22     2    23\n -1.3316987118953665E+00 a      1324     1    22     2    24\n -7.0760527312605037E-01 a      1325     1    22     2    25\n -8.1466385165616928E-01 a      1326     1    23     2     1\n  6.8912340727205368E-01 a      1327     1    23     2     2\n  8.4582890184800619E-01 a      1328     1    23     2     3\n  3.8163700575566650E-01 a      1329     1    23     2     4\n -6.6556600373886232E-01 a      1330     1    23     2     5\n -1.3399458536680564E+00 a      1331     1    23     2     6\n -1.7425009694107033E-01 a      1332     1    23     2     7\n -2.6104662248332646E+00 a      1333     1    23     2     8\n -1.9788280313555501E-01 a      1334     1    23     2     9\n -4.6341960827595043E+00 a      1335     1    23     2    10\n -4.1560774205921192E-01 a      1336     1    23     2    11\n -1.3453315295733928E-01 a      1337     1    23     2    12\n  5.9251987079212687E-01 a      1338     1    23     2    13\n  1.3014540212114664E-01 a      1339     1    23     2    14\n  2.4962768316839337E-01 a      1340     1    23     2    15\n  3.3868458734074913E-01 a      1341     1    23     2    16\n -2.1103970517135956E-01 a      1342     1    23     2    17\n -2.7311756320323316E-01 a      1343     1    23     2    18\n  7.7825779463422798E-02 a      1344     1    23     2    19\n -1.5510879185574573E+00 a      1345     1    23     2    20\n -3.3731285186903501E+00 a      1346     1    23     2    21\n  1.5012690395440691E+00 a      1347     1    23     2    22\n -1.4938786629136067E+00 a      1348     1    23     2    23\n  1.5155834326942672E-01 a      1349     1    23     2    24\n  2.2135367884980521E+00 a      1350     1    23     2    25\n  7.6092107307961931E-01 a      1351     1    24     2     1\n  2.5019321183393825E-02 a      1352     1    24     2     2\n  2.4714648764760871E-01 a      1353     1    24     2     3\n -4.2700090187223255E-01 a      1354     1    24     2     4\n  1.9684439924637190E-01 a      1355     1    24     2     5\n -1.6150658390090172E-01 a      1356     1    24     2     6\n -8.4941771549071021E-01 a      1357     1    24     2     7\n  3.2616941337700417E-01 a      1358     1    24     2     8\n -6.0235251095177200E-01 a      1359     1    24     2     9\n  2.0073315297316108E+00 a      1360     1    24     2    10\n  6.8678637919958119E-01 a      1361     1    24     2    11\n -1.4709309602563259E+00 a      1362     1    24     2    12\n -7.3119546383323997E-01 a      1363     1    24     2    13\n  5.9624465461749732E-01 a      1364     1    24     2    14\n  1.1965703107989687E+00 a      1365     1    24     2    15\n -4.8078015734066326E-01 a      1366     1    24     2    16\n  2.8731897539798784E-01 a      1367     1    24     2    17\n  2.8943049077679879E+00 a      1368     1    24     2    18\n  4.4309374097560666E-01 a      1369     1    24     2    19\n -5.2571668466848664E-01 a      1370     1    24     2    20\n  2.6293009755349539E+00 a      1371     1    24     2    21\n  1.1166360248787797E+00 a      1372     1    24     2    22\n  1.4367909042068954E+00 a      1373     1    24     2    23\n  1.2263949730702137E+00 a      1374     1    24     2    24\n -1.5658327417588482E+00 a      1375     1    24     2    25\n -3.0524380712257440E+00 a      1376     1    25     2     1\n -1.6248402538917406E-01 a      1377     1    25     2     2\n  5.3725239557723847E-01 a      1378     1    25     2     3\n -3.1435543583372311E-01 a      1379     1    25     2     4\n  8.0294309812719877E-01 a      1380     1    25     2     5\n -3.3745709161028831E-01 a      1381     1    25     2     6\n  2.9618139473335392E-01 a      1382     1    25     2     7\n -1.3606606680314999E+00 a      1383     1    25     2     8\n  2.9886863438452965E-01 a      1384     1    25     2     9\n  3.4365095196288835E+00 a      1385     1    25     2    10\n  2.8778063903425566E-01 a      1386     1    25     2    11\n -5.2312889094867954E-01 a      1387     1    25     2    12\n  4.5730896273705224E-01 a      1388     1    25     2    13\n -8.8949447500584955E-01 a      1389     1    25     2    14\n -8.1389897744929640E-01 a      1390     1    25     2    15\n -4.0077086298379117E-01 a      1391     1    25     2    16\n  7.2544627916775950E-01 a      1392     1    25     2    17\n -9.8029709488119798E-01 a      1393     1    25     2    18\n  8.5017837869712165E-01 a      1394     1    25     2    19\n -2.9795775527520296E-01 a      1395     1    25     2    20\n  1.1940911570260535E+00 a      1396     1    25     2    21\n -4.1259772504588357E-02 a      1397     1    25     2    22\n  1.0619824936744515E+00 a      1398     1    25     2    23\n -6.5325825341918264E-01 a      1399     1    25     2    24\n  3.7575240210802421E+00 a      1400     1    25     2    25\n -1.0787018434494783E+01 b      1401     2     1\n -8.4067078142086771E-01 b      1402     2     2\n  9.3201271110229211E-01 b      1403     2     3\n -1.8318272256547821E+00 b      1404     2     4\n -2.1732436845179119E+00 b      1405     2     5\n -2.6390929073478930E+00 b      1406     2     6\n  3.7489748853957300E-01 b      1407     2     7\n -2.3789675524866163E+00 b      1408     2     8\n  2.7252644932624959E+00 b      1409     2     9\n  2.5100559841854970E+00 b      1410     2    10\n -2.4897033671113025E-01 b      1411     2    11\n  2.6913296692082476E+00 b      1412     2    12\n  5.8162695990329221E+00 b      1413     2    13\n -1.5170700889568940E+00 b      1414     2    14\n  4.2121259244130220E+00 b      1415     2    15\n  2.2987725066596130E+00 b      1416     2    16\n -7.1493650128731911E-01 b      1417     2    17\n -3.9961443472349811E-01 b      1418     2    18\n  7.8083705485664430E+00 b      1419     2    19\n -4.0462773256448170E-01 b      1420     2    20\n -1.4333029489891109E+00 b      1421     2    21\n -4.9517224038431467E+00 b      1422     2    22\n  1.0702867307710989E+01 b      1423     2    23\n -9.7535853921453985E-01 b      1424     2    24\n  5.3161969295054172E+00 b      1425     2    25\n -5.1941647295982207E-01 a      1426     2     1     3     1\n -7.7346657642095373E-01 a      1427     2     2     3     1\n  1.4003893583106508E+00 a      1428     2     3     3     1\n  8.9188080044914464E-01 a      1429     2     4     3     1\n -2.0147808233792022E+00 a      1430     2     5     3     1\n -1.8131831735812174E+00 a      1431     2     6     3     1\n  3.3217884596641700E+00 a      1432     2     7     3     1\n -1.2675289031787327E+00 a      1433     2     8     3     1\n -1.2791140359120716E+00 a      1434     2     9     3     1\n  1.9731828075446340E+00 a      1435     2    10     3     1\n -2.3928332883234411E+00 a      1436     2    11     3     1\n -1.1755085043375486E+00 a      1437     2    12     3     1\n  2.6525670286472951E+00 a      1438     2    13     3     1\n -2.4861988521743901E+00 a      1439     2    14     3     1\n  1.2534500349238071E+00 a      1440     2    15     3     1\n  2.8804282010183990E+00 a      1441     2    16     3     1\n -2.0327745898215275E+00 a      1442     2    17     3     1\n -1.1760164122204946E+00 a      1443     2    18     3     1\n -9.9841804355412322E-01 a      1444     2    19     3     1\n -1.8663330516323837E+00 a      1445     2    20     3     1\n  6.3266049836286531E-01 a      1446     2    21     3     1\n  1.2025500357718348E+00 a      1447     2    22     3     1\n  1.1367820678861495E-01 a      1448     2    23     3     1\n -2.6481374255863193E+00 a      1449     2    24     3     1\n  5.2166795947347921E-01 a      1450     2    25     3     1\n  4.8693043186011655E+00 b      1451     3     1\n"
  },
  {
    "path": "examples/pynnp/prediction/example-simple.py",
    "content": "#!/bin/env python\n\nfrom __future__ import absolute_import\nfrom __future__ import print_function\nimport pynnp\n\n# Initialize NNP prediction mode.\np = pynnp.Prediction()\n\n# Read settings and setup NNP.\np.setup()\n\n# Read in structure.\np.readStructureFromFile()\n\n# Predict energies and forces.\np.predict()\n\n# Shortcut for structure container.\ns = p.structure\n\nprint(\"------------\")\nprint(\"Structure 1:\")\nprint(\"------------\")\nprint(\"numAtoms           : \", s.numAtoms)\nprint(\"numAtomsPerElement : \", s.numAtomsPerElement)\nprint(\"------------\")\nprint(\"Energy (Ref) : \", s.energyRef)\nprint(\"Energy (NNP) : \", s.energy)\nprint(\"------------\")\nfor atom in s.atoms:\n    print(atom.index, atom.element, p.elementMap[atom.element], atom.f.r)\n"
  },
  {
    "path": "examples/pynnp/prediction/example-verbose.py",
    "content": "#!/bin/env python\n\nfrom __future__ import absolute_import\nfrom __future__ import print_function\nimport pynnp\n\n# Initialize NNP setup (symmetry functions only).\nm = pynnp.Mode()\nm.initialize()\nm.loadSettingsFile(\"input.nn\")\nm.setupNormalization()\nuseNormalization = m.useNormalization()\nmeanEnergy = m.getMeanEnergy()\nconvEnergy = m.getConvEnergy()\nconvLength = m.getConvLength()\nm.setupElementMap()\nm.setupElements()\nm.setupCutoff()\nm.setupSymmetryFunctions()\nm.setupSymmetryFunctionMemory() # comment out when compiled with N2P2_FULL_SFD_MEMORY\nm.setupSymmetryFunctionCache() # comment out when compiled with N2P2_NO_SF_CACHE\nm.setupSymmetryFunctionGroups()\nm.setupNeuralNetwork()\nm.setupSymmetryFunctionScaling(\"scaling.data\")\nm.setupNeuralNetworkWeights(\"weights.%03zu.data\")\nm.setupSymmetryFunctionStatistics(True, True, True, False)\n\n# Initialize NNP structure data container.\ns = pynnp.Structure()\ns.setElementMap(m.elementMap)\n\n# Read in data via Structure member function.\ns.readFromFile(\"input.data\")\nm.removeEnergyOffset(s);\n# If normalization is used, convert structure data.\nif useNormalization:\n    s.toNormalizedUnits(meanEnergy, convEnergy, convLength)\n\n# Retrieve cutoff radius form NNP setup.\ncutoffRadius = m.getMaxCutoffRadius()\nprint(\"Cutoff radius = \", cutoffRadius / convLength)\n\n# Calculate neighbor list.\ns.calculateNeighborList(cutoffRadius)\n\n# Calculate symmetry functions for all atoms (use groups).\n#m.calculateSymmetryFunctions(s, False)\nm.calculateSymmetryFunctionGroups(s, True)\n\n# Calculate atomic neural networks.\nm.calculateAtomicNeuralNetworks(s, True)\n\n# Sum up potential energy.\nm.calculateEnergy(s)\n\n# Collect force contributions.\nm.calculateForces(s)\n\n# If normalization is used, convert structure data back to physical units.\nif useNormalization:\n    s.toPhysicalUnits(meanEnergy, convEnergy, convLength)\nm.addEnergyOffset(s, False);\nm.addEnergyOffset(s, True);\n\nprint(\"------------\")\nprint(\"Structure 1:\")\nprint(\"------------\")\nprint(\"numAtoms           : \", s.numAtoms)\nprint(\"numAtomsPerElement : \", s.numAtomsPerElement)\nprint(\"------------\")\nprint(\"Energy (Ref) : \", s.energyRef)\nprint(\"Energy (NNP) : \", s.energy)\nprint(\"------------\")\nfor atom in s.atoms:\n    print(atom.index, atom.element, m.elementMap[atom.element], atom.f.r)\n"
  },
  {
    "path": "examples/pynnp/prediction/input.data",
    "content": "begin\nlattice         17.007526000         0.000000000         0.000000000\nlattice          0.000000000        14.728517000         0.000000000\nlattice          0.000000000         0.000000000        13.885701000\natom          -0.004100346        -0.049554341        -0.016880525 O         -0.217594850         0.000000000         0.000008033        -0.000542100        -0.000410159\natom           1.492583556         0.873520660         0.644659612 H          0.109115980         0.000000000         0.000252683         0.000204913         0.000200704\natom          15.503581693         0.881917393         0.626419599 H          0.109022510         0.000000000        -0.000246170         0.000266375         0.000134107\natom           8.498589062         0.043176894         0.025537700 O         -0.218598620         0.000000000         0.000007022         0.000533358         0.000361666\natom           8.491160360        12.981354552         0.599284097 H          0.108512460         0.000000000        -0.000021290        -0.000392627         0.000011916\natom           8.499220060        -0.027896059        12.033864819 H          0.108863030         0.000000000        -0.000013989        -0.000096456        -0.000378365\natom           4.277295961         7.375744190        -0.020977565 O         -0.217668440         0.000000000         0.000481532         0.000277410        -0.000334794\natom           4.228769952         5.619750841         0.645799003 H          0.109194280         0.000000000        -0.000204917        -0.000343797         0.000111773\natom           2.727070736         8.215583168         0.628405228 H          0.109614200         0.000000000        -0.000319730         0.000099148         0.000189655\natom          12.695333412         7.352384758         0.005785717 O         -0.218143300         0.000000000        -0.000450159        -0.000281280         0.000354495\natom          14.242870010         8.239469758         0.596217904 H          0.109580130         0.000000000         0.000294128         0.000216700         0.000038584\natom          12.778339040         7.376230719        12.014619869 H          0.108920890         0.000000000         0.000114545         0.000025595        -0.000401701\natom           4.207316271         2.472274106         1.730280339 O         -0.218226050         0.000000000        -0.000399123         0.000255904        -0.000358453\natom           5.753769376         1.579438121         1.146854142 H          0.109643110         0.000000000         0.000325083        -0.000161344         0.000011977\natom           4.273576735         2.443254491         3.607928163 H          0.108727520         0.000000000         0.000071433        -0.000054918         0.000382490\natom          12.785533813         2.440390743         1.750614490 O         -0.218082980         0.000000000         0.000427353        -0.000251532         0.000427749\natom          11.239414149         1.594814897         1.097275480 H          0.109329000         0.000000000        -0.000279583        -0.000112864        -0.000214875\natom          12.723757442         4.198100588         1.090903929 H          0.109228610         0.000000000        -0.000075451         0.000366986        -0.000205847\natom          -0.018578236         9.770351711         1.708133696 O         -0.218614930         0.000000000        -0.000025913        -0.000553474        -0.000376021\natom          -0.010260267        11.560893239         1.136272074 H          0.108730400         0.000000000        -0.000011992         0.000402432        -0.000005430\natom          -0.000506333         9.839684113         3.585501292 H          0.108889010         0.000000000         0.000011475         0.000114173         0.000376410\natom           8.490139095         9.870825493         1.754768788 O         -0.217517160         0.000000000        -0.000010864         0.000508765         0.000409113\natom           6.989329978         8.936839686         1.118083555 H          0.109024080         0.000000000        -0.000232184        -0.000247149        -0.000123829\natom           9.985789204         8.951322868         1.084417558 H          0.108989940         0.000000000         0.000239204        -0.000184120        -0.000209689\natom           4.288957423         2.432358217         6.928761652 O         -0.217798740         0.000000000         0.000443754        -0.000261449        -0.000368781\natom           2.737000282         1.601557704         7.586976741 H          0.108802260         0.000000000        -0.000360352        -0.000072537         0.000185428\natom           4.247153698         4.190556631         7.588952827 H          0.109226820         0.000000000        -0.000080628         0.000340162         0.000172008\natom          12.808113128         2.466327516         6.957766376 O         -0.218477540         0.000000000         0.000421514    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4.170973911         7.255862676         8.559486899 O         -0.215164050         0.000000000        -0.000467542        -0.000194129        -0.000349729\natom           4.215465922         7.284069255        10.441736999 H          0.107425280         0.000000000         0.000075706         0.000022811         0.000358015\natom           5.726519830         8.147218060         7.985735721 H          0.107963420         0.000000000         0.000388071         0.000060390        -0.000045681\natom          12.569404113         7.294087165         8.583451572 O         -0.215120610         0.000000000        -0.000532768         0.000284872         0.000337051\natom          12.623430736         5.529809370         7.928182547 H          0.107798330         0.000000000         0.000109416        -0.000341090        -0.000214683\natom          14.127416559         8.132713204         7.938887070 H          0.107728160         0.000000000         0.000396288         0.000052784        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8.354981093        12.752717700         0.610914227 H          0.106812980         0.000000000        -0.000033686        -0.000422773        -0.000080872\natom           8.369715362        -0.014688708        11.814421920 H          0.107127810         0.000000000        -0.000064232        -0.000147586        -0.000382486\natom           4.209551326         7.262350993        -0.022244872 O         -0.214206040         0.000000000         0.000399251         0.000241606        -0.000441413\natom           4.161083841         5.499453341         0.641417636 H          0.107373970         0.000000000        -0.000078789        -0.000309787         0.000200290\natom           2.652266386         8.104075824         0.623481925 H          0.107689920         0.000000000        -0.000288023         0.000135969         0.000246296\natom          12.482850316         7.234554145         0.008496303 O         -0.214630680         0.000000000        -0.000461889        -0.000291876         0.000377122\natom          14.037257108         8.120781568         0.599819816 H          0.107619210         0.000000000         0.000234880         0.000293877         0.000048318\natom          12.560246841         7.256619738        11.790854637 H          0.107141510         0.000000000         0.000187165        -0.000002489        -0.000364300\natom           4.135445551         2.434921952         1.699023213 O         -0.214713810         0.000000000        -0.000403684         0.000298912        -0.000382033\natom           5.689105561         1.545022318         1.113039045 H          0.107713310         0.000000000         0.000290336        -0.000244647        -0.000009852\natom           4.198672816         2.407407371         3.582248034 H          0.106929550         0.000000000         0.000060257        -0.000027175         0.000358194\natom          12.591407194         2.401063108         1.724190792 O         -0.214537290         0.000000000         0.000374317    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8.429854833         0.027627681         8.568151727 O         -0.214467930         0.000000000         0.000463859         0.000286373         0.000364515\natom           6.868148124         0.863757391         7.926739383 H          0.107378890         0.000000000        -0.000362933         0.000078746        -0.000026637\natom           8.382027682        12.758380642         7.904705631 H          0.107318890         0.000000000        -0.000048782        -0.000296910        -0.000220122\natom           4.153971215         7.226312615         8.525006505 O         -0.214267830         0.000000000        -0.000448055        -0.000184528        -0.000334325\natom           4.197465659         7.254358190        10.408717269 H          0.106982030         0.000000000         0.000053509         0.000013318         0.000350110\natom           5.710205580         8.118967601         7.950403457 H          0.107503910         0.000000000         0.000376534         0.000043539        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1.502456014         0.869655018         0.636608926 H          0.106863550         0.000000000         0.000283022         0.000032550         0.000289690\natom          15.162002156         0.874413537         0.623740137 H          0.106829690         0.000000000        -0.000253165         0.000310329        -0.000102272\natom           8.331817927         0.053636357         0.032689085 O         -0.213853600         0.000000000         0.000037505         0.000529599         0.000367348\natom           8.321203034        12.694231343         0.612301702 H          0.106376910         0.000000000        -0.000034768        -0.000412203        -0.000084739\natom           8.337317899        -0.013102963        11.758575093 H          0.106680670         0.000000000        -0.000077141        -0.000141032        -0.000373197\natom           4.191642997         7.233685834        -0.022228167 O         -0.213316940         0.000000000         0.000369962         0.000227641        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0.000000000        -0.000036315        -0.000525739        -0.000370407\natom          -0.014158394        11.363755474         1.090424184 H          0.106523040         0.000000000        -0.000002995         0.000408633         0.000089940\natom          -0.008408940         9.632432743         3.552234839 H          0.106660160         0.000000000         0.000108074         0.000147098         0.000350968\natom           8.315198657         9.684764547         1.728093567 O         -0.213036250         0.000000000        -0.000003177         0.000443521         0.000332348\natom           6.807771454         8.751782241         1.085539904 H          0.106837360         0.000000000        -0.000286432        -0.000267190         0.000069300\natom           9.817930570         8.761084152         1.059757484 H          0.106785820         0.000000000         0.000264161        -0.000038663        -0.000259530\natom           4.213155468         2.381402701         6.788646142 O         -0.213317830         0.000000000         0.000392275        -0.000237791        -0.000440666\natom           2.658197896         1.539889558         7.445737411 H          0.106598040         0.000000000        -0.000326813        -0.000004659         0.000251544\natom           4.168424501         4.147330340         7.447632636 H          0.106909410         0.000000000        -0.000007016         0.000297568         0.000217645\natom          12.567413362         2.417030669         6.820894959 O         -0.213855690         0.000000000         0.000450879         0.000281471         0.000373034\natom          12.502611483         2.396108983         4.936405269 H          0.106575660         0.000000000        -0.000187555         0.000024429        -0.000362658\natom          11.005551903         1.532416485         7.400456912 H          0.106527440         0.000000000        -0.000318298        -0.000259485        -0.000086607\natom          -0.024750686         9.592792962         6.773717288 O         -0.213761650         0.000000000        -0.000437704        -0.000277756        -0.000466434\natom           0.018706738        11.357009455         7.438833883 H          0.106799140         0.000000000        -0.000009877         0.000293459         0.000235961\natom           1.532597332         8.755726874         7.430305871 H          0.106544730         0.000000000         0.000352499         0.000008776         0.000234862\natom           8.302565385         9.652540769         6.832719711 O         -0.213994980         0.000000000        -0.000419469         0.000330436         0.000371920\natom           8.343465254         9.618397956         4.947877984 H          0.106603650         0.000000000         0.000084175        -0.000147262        -0.000358192\natom           9.860139282         8.751815916         7.398594549 H          0.106429370         0.000000000         0.000323002        -0.000242629        -0.000088387\natom           0.055135760        -0.034617588         8.485824095 O         -0.213237150         0.000000000         0.000448963        -0.000210671        -0.000337012\natom          -0.006459178         0.003436221        10.370283474 H          0.106701150         0.000000000        -0.000089645         0.000153547         0.000356524\natom          15.173440761         0.860032042         7.895699273 H          0.106930160         0.000000000        -0.000352090         0.000003142        -0.000092677\natom           8.397558603         0.028311667         8.534536563 O         -0.213562630         0.000000000         0.000436351         0.000276868         0.000345630\natom           6.835085365         0.865806440         7.892390854 H          0.106936450         0.000000000        -0.000355884         0.000087930         0.000006494\natom           8.349424013        12.699247223         7.871726511 H          0.106877150         0.000000000        -0.000012850        -0.000287657        -0.000222178\natom           4.137300166         7.196989926         8.490761269 O         -0.213379700         0.000000000        -0.000431926        -0.000176204        -0.000324942\natom           4.179712212         7.224870489        10.375978749 H          0.106535580         0.000000000         0.000030386         0.000002884         0.000342168\natom           5.694305973         8.090841732         7.915246107 H          0.107046200         0.000000000         0.000366300         0.000027737        -0.000073201\natom          12.466962086         7.234666338         8.515161883 O         -0.213343460         0.000000000        -0.000479922         0.000262552         0.000300962\natom          12.522076833         5.467098889         7.860408999 H          0.106893390         0.000000000         0.000032504        -0.000317225        -0.000223327\natom          14.026416733         8.076389391         7.869571203 H          0.106839990         0.000000000         0.000390767         0.000072857         0.000062792\nenergy       -1225.21898133\ncharge           0.00000000\nend\nbegin\nlattice         16.603359000         0.000000000         0.000000000\nlattice          0.000000000        14.378506000         0.000000000\nlattice          0.000000000         0.000000000        13.555721000\natom          -0.000503310        -0.057687325        -0.023071117 O         -0.212151150         0.000000000         0.000010587        -0.000435752        -0.000312992\natom           1.504895196         0.870101806         0.636314053 H          0.106414470         0.000000000         0.000289918        -0.000003147         0.000292181\natom          15.094557759         0.874963901         0.623653985 H          0.106393210         0.000000000        -0.000259626         0.000301813        -0.000143021\natom           8.299023812         0.054063719         0.032694622 O         -0.212953440         0.000000000         0.000039179         0.000515614         0.000356475\natom           8.287553609        12.635639198         0.613414183 H          0.105943850         0.000000000        -0.000035722        -0.000401948        -0.000088551\natom           8.304981362        -0.011808293        11.702579508 H          0.106235580         0.000000000        -0.000089623        -0.000134339        -0.000363714\natom           4.173443689         7.204929836        -0.022004574 O         -0.212448030         0.000000000         0.000348310         0.000217748        -0.000436167\natom           4.126655642         5.438746763         0.641569834 H          0.106483350         0.000000000        -0.000014625        -0.000288022         0.000201356\natom           2.613530349         8.048524683         0.623850875 H          0.106779850         0.000000000        -0.000247246         0.000163085         0.000235516\natom          12.379799042         7.178176740         0.008967789 O         -0.212880480         0.000000000        -0.000424955        -0.000285393         0.000353862\natom          13.937087382         8.065084843         0.601539164 H          0.106696130         0.000000000         0.000176739         0.000310721         0.000089064\natom          12.455595120         7.198586650        11.679160700 H          0.106257690         0.000000000         0.000186329        -0.000028136        -0.000342062\natom           4.103050488         2.415576279         1.684959589 O         -0.212949070         0.000000000        -0.000369241         0.000293003        -0.000363537\natom           5.659510694         1.525524163         1.096846739 H          0.106789260         0.000000000         0.000243628        -0.000251942        -0.000042038\natom           4.164997275         2.388749596         3.571241987 H          0.106047760         0.000000000         0.000018446        -0.000002189         0.000338324\natom          12.493041419         2.382731915         1.709564351 O         -0.212770590         0.000000000         0.000322269        -0.000206057         0.000522503\natom          10.936319600         1.532089374         1.063485838 H          0.106578140         0.000000000        -0.000189205        -0.000200548        -0.000265621\natom          12.428042990         4.150894647         1.053702292 H          0.106502830         0.000000000         0.000077131         0.000287447        -0.000285520\natom          -0.027467035         9.529340782         1.661161079 O         -0.212974310         0.000000000        -0.000037341        -0.000509657        -0.000359883\natom          -0.014690938        11.326741657         1.082908706 H          0.106085650         0.000000000        -0.000001115         0.000396626         0.000093529\natom          -0.009482834         9.592918402         3.547193277 H          0.106210170         0.000000000         0.000121409         0.000140625         0.000340350\natom           8.280286460         9.646643766         1.721822606 O         -0.212152580         0.000000000        -0.000001115         0.000422173         0.000310736\natom           6.771336498         8.713480991         1.078635582 H          0.106401550         0.000000000        -0.000294820        -0.000255556         0.000104453\natom           9.784701477         8.722598824         1.053393265 H          0.106345480         0.000000000         0.000269658        -0.000010164        -0.000257087\natom           4.197273398         2.371888271         6.761541103 O         -0.212444630         0.000000000         0.000372948        -0.000227635        -0.000436442\natom           2.641486520         1.528552695         7.418689914 H          0.106160270         0.000000000        -0.000318561        -0.000001655         0.000247943\natom           4.152522872         4.139453282         7.420552390 H          0.106453370         0.000000000         0.000021064         0.000284978         0.000216489\natom          12.518623434         2.406847105         6.793147696 O         -0.212962590         0.000000000         0.000439986         0.000275651         0.000366644\natom          12.454423111         2.386571177         4.907101118 H          0.106134580         0.000000000        -0.000189281         0.000040632        -0.000351654\natom          10.955625985         1.521734582         7.373894545 H          0.106088340         0.000000000        -0.000304940        -0.000260831        -0.000090894\natom          -0.025040306         9.553498813         6.746392927 O         -0.212873260         0.000000000        -0.000420072        -0.000268929        -0.000459563\natom           0.018592731        11.319454495         7.411304279 H          0.106349350         0.000000000        -0.000040489         0.000284067         0.000235606\natom           1.533293205         8.714935154         7.403115643 H          0.106108940         0.000000000         0.000346555         0.000014494         0.000227115\natom           8.269116498         9.614335045         6.806071684 O         -0.213092890         0.000000000        -0.000402425         0.000323442         0.000360166\natom           8.308893567         9.580921666         4.919677093 H          0.106169750         0.000000000         0.000070256        -0.000155475        -0.000347681\natom           9.827603775         8.712372818         7.372603504 H          0.105994450         0.000000000         0.000309426        -0.000241197        -0.000092140\natom           0.055921357        -0.035572448         8.451364639 O         -0.212353680         0.000000000         0.000436932        -0.000197769        -0.000323344\natom          -0.005072251         0.002101413        10.337375313 H          0.106264430         0.000000000        -0.000077349         0.000160113         0.000345628\natom          15.106728011         0.860209260         7.860132267 H          0.106480770         0.000000000        -0.000343875        -0.000018063        -0.000109136\natom           8.365151314         0.028750612         8.500746807 O         -0.212664370         0.000000000         0.000411456         0.000266553         0.000327815\natom           6.801813281         0.867642233         7.858014773 H          0.106497200         0.000000000        -0.000348575         0.000097277         0.000037293\natom           8.316864393        12.640088463         7.838446339 H          0.106438190         0.000000000         0.000021437        -0.000277368        -0.000222892\natom           4.120891278         7.167889355         8.456745634 O         -0.212489100         0.000000000        -0.000416097        -0.000168059        -0.000309184\natom           4.162103632         7.195551939        10.343532494 H          0.106098760         0.000000000         0.000007239        -0.000008088         0.000328110\natom           5.678780268         8.062825430         7.880282888 H          0.106595110         0.000000000         0.000355504         0.000012362        -0.000086469\natom          12.416548448         7.204989703         8.481188805 O         -0.212466090         0.000000000        -0.000455718         0.000250945         0.000282753\natom          12.471902567         5.435751472         7.826533714 H          0.106446420         0.000000000        -0.000001768        -0.000305284        -0.000225435\natom          13.976865717         8.048250162         7.835201131 H          0.106400660         0.000000000         0.000387338         0.000083824         0.000101114\nenergy       -1225.21777128\ncharge           0.00000000\nend\n"
  },
  {
    "path": "examples/pynnp/prediction/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   4              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 2\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               25             # Write energy comparison.\nwrite_trainforces               25             # Write force comparison.\nwrite_weights_epoch                            # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/pynnp/prediction/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "examples/pynnp/prediction/weights.001.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n  1.2539155865352127E+00 a         1     0     1     1     1\n  2.2490365890661286E+00 a         2     0     1     1     2\n  4.9361851928374572E+00 a         3     0     1     1     3\n -2.3971991574908125E+00 a         4     0     1     1     4\n -1.8596992303156465E+00 a         5     0     1     1     5\n  3.8287764168815897E+00 a         6     0     1     1     6\n  7.4523181738636106E+00 a         7     0     1     1     7\n  6.0971861116881998E+00 a         8     0     1     1     8\n -8.7239359226117639E+00 a         9     0     1     1     9\n -1.8255232070184267E+01 a        10     0     1     1    10\n -7.8065643887610179E+00 a        11     0     1     1    11\n  1.4247237398130265E+01 a        12     0     1     1    12\n -3.2217879518334338E+00 a        13     0     1     1    13\n -5.7395252086520712E+00 a        14     0     1     1    14\n  2.0353040522911576E+00 a        15     0     1     1    15\n  7.7520578160630560E+00 a        16     0     1     1    16\n  2.9357257867412252E+00 a        17     0     1     1    17\n -2.9719860930100790E+00 a        18     0     1     1    18\n  8.9245382590288980E+00 a        19     0     1     1    19\n  6.6848134049442169E+00 a        20     0     1     1    20\n -2.2992719903495891E+00 a        21     0     1     1    21\n -1.4401533482181721E+01 a        22     0     1     1    22\n -2.0574070545285186E+00 a        23     0     1     1    23\n -6.3544667277888678E+00 a        24     0     1     1    24\n  3.9668360525851707E+00 a        25     0     1     1    25\n  1.0930597297534963E+01 a        26     0     2     1     1\n  3.0058866618169424E+00 a        27     0     2     1     2\n -4.9950943102999927E+00 a        28     0     2     1     3\n -1.9930957240687266E+00 a        29     0     2     1     4\n  1.6790893133342006E+00 a        30     0     2     1     5\n -4.5254006136507128E+00 a        31     0     2     1     6\n -9.6165021729265252E+00 a        32     0     2     1     7\n -8.7465722730176285E+00 a        33     0     2     1     8\n  1.5506950040431201E+01 a        34     0     2     1     9\n  2.1903342918227118E+01 a        35     0     2     1    10\n -1.0685216745153280E+01 a        36     0     2     1    11\n -2.5859690636594280E+01 a        37     0     2     1    12\n -3.2423603491405122E+00 a        38     0     2     1    13\n  5.3753900550878555E+00 a        39     0     2     1    14\n -3.0291935617567991E+00 a        40     0     2     1    15\n -1.3534893178408465E+01 a        41     0     2     1    16\n -5.7625138055631471E+00 a        42     0     2     1    17\n  1.0216765318459601E+01 a        43     0     2     1    18\n -1.4416012930050949E+01 a        44     0     2     1    19\n -4.7226757471872144E-01 a        45     0     2     1    20\n  7.8981385188798026E+00 a        46     0     2     1    21\n  1.2202710023744410E+00 a        47     0     2     1    22\n  8.0560891210932120E+00 a        48     0     2     1    23\n  4.5972445013263297E-01 a        49     0     2     1    24\n  1.3374237019728858E+01 a        50     0     2     1    25\n -1.0644910441621166E+01 a        51     0     3     1     1\n -5.6098794516515920E+00 a        52     0     3     1     2\n -1.0236653403367724E+01 a        53     0     3     1     3\n  1.3552139405799508E+00 a        54     0     3     1     4\n  1.3201025058567883E+00 a        55     0     3     1     5\n  1.6531266759009673E+00 a        56     0     3     1     6\n -1.0303768926395865E+01 a        57     0     3     1     7\n  1.9927521303470008E-01 a        58     0     3     1     8\n  8.1216226663758366E+00 a        59     0     3     1     9\n  2.1349555016157687E+01 a        60     0     3     1    10\n  1.0105416692705148E+01 a        61     0     3     1    11\n -1.1444993918278378E+01 a        62     0     3     1    12\n  2.9861675555209538E-01 a        63     0     3     1    13\n  9.3552992513120543E+00 a        64     0     3     1    14\n -2.2844869025933630E+00 a        65     0     3     1    15\n -3.8047300595857316E+00 a        66     0     3     1    16\n -3.0512161452147448E+00 a        67     0     3     1    17\n  2.7887340590896472E+00 a        68     0     3     1    18\n -1.5988439945122812E+01 a        69     0     3     1    19\n -1.6917164763280326E+01 a        70     0     3     1    20\n  3.2170907488709326E+00 a        71     0     3     1    21\n  2.1641888770160929E+01 a        72     0     3     1    22\n  3.2604671723420497E+00 a        73     0     3     1    23\n  1.5230689068493776E+01 a        74     0     3     1    24\n -1.4713830039823366E+01 a        75     0     3     1    25\n -2.3544214523969775E+00 a        76     0     4     1     1\n -5.8299691629399382E+00 a        77     0     4     1     2\n  1.7168784391956539E+01 a        78     0     4     1     3\n  1.0050003860864617E+01 a        79     0     4     1     4\n  3.5168903759752812E+00 a        80     0     4     1     5\n -4.4828111046589010E+00 a        81     0     4     1     6\n  1.8299193380051442E+01 a        82     0     4     1     7\n  6.9717289110204188E+00 a        83     0     4     1     8\n -2.0364082994445859E+01 a        84     0     4     1     9\n -3.5062338388300589E+01 a        85     0     4     1    10\n  1.8010375764887119E+01 a        86     0     4     1    11\n  4.2133659287179640E+01 a        87     0     4     1    12\n  1.1988736553417061E+01 a        88     0     4     1    13\n -1.2351529706885179E+01 a        89     0     4     1    14\n  5.4139212296285057E+00 a        90     0     4     1    15\n  1.6705967069968899E+01 a        91     0     4     1    16\n  8.3219076874511639E+00 a        92     0     4     1    17\n -1.8555777504879448E+01 a        93     0     4     1    18\n  3.1433889377775369E+01 a        94     0     4     1    19\n  6.7043459658252780E-01 a        95     0     4     1    20\n -1.3837570456349678E+01 a        96     0     4     1    21\n  5.0298368971353791E-01 a        97     0     4     1    22\n -2.2656240789613065E+01 a        98     0     4     1    23\n -2.4243684644962626E+00 a        99     0     4     1    24\n -2.8280330035212309E+01 a       100     0     4     1    25\n  4.2306100814115322E+00 a       101     0     5     1     1\n  9.9770374716830084E+00 a       102     0     5     1     2\n  2.0487048112933808E+00 a       103     0     5     1     3\n -1.3702212470739978E+00 a       104     0     5     1     4\n  2.8131124422603837E+00 a       105     0     5     1     5\n  3.2845640151619522E-03 a       106     0     5     1     6\n  2.4065616021196026E+00 a       107     0     5     1     7\n -1.0461000723401572E+01 a       108     0     5     1     8\n -1.0180720750329515E+01 a       109     0     5     1     9\n -8.8668996772076660E+00 a       110     0     5     1    10\n  6.5256092481271502E+00 a       111     0     5     1    11\n -6.9831054240027211E+00 a       112     0     5     1    12\n  4.0892074148312876E+00 a       113     0     5     1    13\n -5.1951354450201128E+00 a       114     0     5     1    14\n  1.6657989141753051E+00 a       115     0     5     1    15\n -7.3542511663155619E+00 a       116     0     5     1    16\n  5.1573102842565115E+00 a       117     0     5     1    17\n  3.4929930175122172E+00 a       118     0     5     1    18\n  2.5382184218789963E+00 a       119     0     5     1    19\n  2.0045179007481050E+01 a       120     0     5     1    20\n -1.6165269676512768E+00 a       121     0     5     1    21\n  2.4869117790922393E+00 a       122     0     5     1    22\n  6.0131560843540068E+00 a       123     0     5     1    23\n -1.2231651850388728E+01 a       124     0     5     1    24\n  3.5372450187997345E+01 a       125     0     5     1    25\n -1.0433252604911765E+01 a       126     0     6     1     1\n -2.3715834640656657E+00 a       127     0     6     1     2\n -1.8239608965373137E+01 a       128     0     6     1     3\n -3.6510816169583777E+00 a       129     0     6     1     4\n -1.7632327653119535E+01 a       130     0     6     1     5\n  1.0040509177650593E+01 a       131     0     6     1     6\n -1.5407385349225459E+01 a       132     0     6     1     7\n -7.0553605774310779E-01 a       133     0     6     1     8\n  1.3204892207903583E+01 a       134     0     6     1     9\n  2.9596389655595953E+01 a       135     0     6     1    10\n -2.0620173259628203E+01 a       136     0     6     1    11\n -3.0803380363815094E+01 a       137     0     6     1    12\n -1.4917676387082279E+01 a       138     0     6     1    13\n  9.6935054799166185E+00 a       139     0     6     1    14\n  4.6937319413252743E+00 a       140     0     6     1    15\n -5.0263591258131060E+00 a       141     0     6     1    16\n -9.7243575590712439E+00 a       142     0     6     1    17\n  1.5625340951727363E+01 a       143     0     6     1    18\n -2.8266776356585389E+01 a       144     0     6     1    19\n  2.5386057418612946E+00 a       145     0     6     1    20\n  1.6302330128073283E+01 a       146     0     6     1    21\n -8.5166226512297030E+00 a       147     0     6     1    22\n  2.5040570504752605E+01 a       148     0     6     1    23\n -8.5008658358878897E-01 a       149     0     6     1    24\n  2.0458930574550632E+01 a       150     0     6     1    25\n  7.8529627796707677E+00 a       151     0     7     1     1\n -4.5279242985866821E+00 a       152     0     7     1     2\n  4.7942839133231594E+00 a       153     0     7     1     3\n -6.2431002330064649E+00 a       154     0     7     1     4\n  4.3358077462982054E+00 a       155     0     7     1     5\n -6.8037589596444281E+00 a       156     0     7     1     6\n  1.8980667946224101E+00 a       157     0     7     1     7\n  1.9802532239433695E+01 a       158     0     7     1     8\n  8.4826746941006572E+00 a       159     0     7     1     9\n  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-4.6552795168897604E-01 a      1221     1    21     2    21\n  1.1611386377657384E+00 a      1222     1    21     2    22\n -1.2972265245341139E+00 a      1223     1    21     2    23\n  1.8117173751313085E+00 a      1224     1    21     2    24\n  1.0433495561237927E+00 a      1225     1    21     2    25\n  1.5410314634266913E+00 a      1226     1    22     2     1\n  6.6201420998527072E-01 a      1227     1    22     2     2\n  1.1189293597068475E+00 a      1228     1    22     2     3\n -1.1536147566508355E+00 a      1229     1    22     2     4\n -8.4859080711662893E-01 a      1230     1    22     2     5\n  3.7903158089014494E-01 a      1231     1    22     2     6\n -2.6461659405296234E+00 a      1232     1    22     2     7\n  2.2472472042954434E+00 a      1233     1    22     2     8\n -9.2281733258289744E-01 a      1234     1    22     2     9\n  8.7312141982063785E-01 a      1235     1    22     2    10\n -4.3593190134289528E-01 a      1236     1    22     2    11\n  5.1912574126564559E-01 a      1237     1    22     2    12\n -5.9029854481930821E-01 a      1238     1    22     2    13\n -7.2255183403800793E-01 a      1239     1    22     2    14\n  4.1024670935059383E-02 a      1240     1    22     2    15\n  2.0425371936604741E-01 a      1241     1    22     2    16\n -1.0394832812330597E+00 a      1242     1    22     2    17\n  4.7202219372950349E-01 a      1243     1    22     2    18\n -1.9958648332222221E-03 a      1244     1    22     2    19\n -1.4664186611455649E-02 a      1245     1    22     2    20\n  1.0689476163444707E+00 a      1246     1    22     2    21\n  8.4484833020425232E-01 a      1247     1    22     2    22\n -1.4147373614558330E+00 a      1248     1    22     2    23\n  1.9187324467269602E+00 a      1249     1    22     2    24\n  1.5330124676330812E+00 a      1250     1    22     2    25\n  2.3019050197742894E+00 a      1251     1    23     2     1\n -1.3828322911066271E-01 a      1252     1    23     2     2\n -2.3555430378419923E-01 a      1253     1    23     2     3\n -1.3434989779696097E-01 a      1254     1    23     2     4\n  3.7852663531566189E-01 a      1255     1    23     2     5\n  9.8266847359694973E-02 a      1256     1    23     2     6\n  3.2721968443206462E-01 a      1257     1    23     2     7\n -3.7061171550241617E-01 a      1258     1    23     2     8\n  2.2862436245090851E+00 a      1259     1    23     2     9\n  1.7674065728047832E+00 a      1260     1    23     2    10\n -5.2627257197444939E-02 a      1261     1    23     2    11\n  9.4094481148145870E-01 a      1262     1    23     2    12\n  1.0616552648143298E+00 a      1263     1    23     2    13\n -1.6065739188681796E-01 a      1264     1    23     2    14\n  1.6833160475834315E+00 a      1265     1    23     2    15\n -5.5679530352182072E-01 a      1266     1    23     2    16\n  4.2170082515325280E-01 a      1267     1    23     2    17\n  1.8142946234467967E+00 a      1268     1    23     2    18\n -6.0004075552166369E-01 a      1269     1    23     2    19\n  8.6767695096505049E-01 a      1270     1    23     2    20\n  1.7471709925670367E-01 a      1271     1    23     2    21\n  6.3494817986861019E-01 a      1272     1    23     2    22\n  7.9839233743975266E-02 a      1273     1    23     2    23\n -8.7497499907984810E-01 a      1274     1    23     2    24\n -2.1279336414401262E-01 a      1275     1    23     2    25\n -1.0628518357816100E+01 a      1276     1    24     2     1\n -3.4149879843865938E-01 a      1277     1    24     2     2\n -4.0534872173827868E-01 a      1278     1    24     2     3\n  1.0980204380257913E-01 a      1279     1    24     2     4\n  1.8376924276804879E-01 a      1280     1    24     2     5\n  8.5047887536146360E-01 a      1281     1    24     2     6\n  4.3913590571042438E-01 a      1282     1    24     2     7\n  2.7167430357232609E+00 a      1283     1    24     2     8\n  2.9682659556600960E-01 a      1284     1    24     2     9\n -1.6032245851281013E+00 a      1285     1    24     2    10\n -6.7567048640865046E-01 a      1286     1    24     2    11\n -1.5253382251900995E+00 a      1287     1    24     2    12\n -6.7540631566041298E-01 a      1288     1    24     2    13\n -1.4565321192168545E+00 a      1289     1    24     2    14\n -1.3315414628143039E+00 a      1290     1    24     2    15\n  1.2552098425264056E+00 a      1291     1    24     2    16\n -1.1701558601459501E+00 a      1292     1    24     2    17\n  2.1967564647703792E+00 a      1293     1    24     2    18\n  3.6767594091430167E-01 a      1294     1    24     2    19\n  1.4791781996464841E+00 a      1295     1    24     2    20\n -2.4597335939693896E+00 a      1296     1    24     2    21\n  1.8222789722776007E+00 a      1297     1    24     2    22\n -2.4818384588216302E+00 a      1298     1    24     2    23\n -1.3359962912345340E+00 a      1299     1    24     2    24\n -1.6060924344568878E-02 a      1300     1    24     2    25\n -1.1558703878945702E+00 a      1301     1    25     2     1\n  5.5859771317693908E-02 a      1302     1    25     2     2\n -1.9275021348316721E+00 a      1303     1    25     2     3\n  4.2881321046205173E-01 a      1304     1    25     2     4\n  6.6308764508018558E-01 a      1305     1    25     2     5\n -2.5357661809360188E-01 a      1306     1    25     2     6\n  7.7965409617466697E-01 a      1307     1    25     2     7\n -1.9470416731652336E+00 a      1308     1    25     2     8\n  2.0923659915641873E-01 a      1309     1    25     2     9\n  8.9211452410465542E-01 a      1310     1    25     2    10\n -1.9807939822570442E-01 a      1311     1    25     2    11\n -5.0922943173038127E-01 a      1312     1    25     2    12\n  1.3378430979044107E+00 a      1313     1    25     2    13\n -6.8964614083753073E-01 a      1314     1    25     2    14\n  7.6939619343191556E-01 a      1315     1    25     2    15\n -1.5783243312480257E+00 a      1316     1    25     2    16\n  2.3586020281744577E+00 a      1317     1    25     2    17\n -5.1641666185758928E-01 a      1318     1    25     2    18\n  1.0291540870545792E+00 a      1319     1    25     2    19\n  1.5269830348487650E+00 a      1320     1    25     2    20\n -2.8987700591417855E+00 a      1321     1    25     2    21\n  9.0207337792476916E-01 a      1322     1    25     2    22\n  1.9890049402284911E+00 a      1323     1    25     2    23\n  3.9387622927433424E-01 a      1324     1    25     2    24\n  9.9397126232482103E-01 a      1325     1    25     2    25\n  2.5306467041996967E+00 b      1326     2     1\n  3.1633393474977245E+00 b      1327     2     2\n -1.1644295509710691E+00 b      1328     2     3\n -5.7686722641223600E+00 b      1329     2     4\n  2.0065022303893989E+00 b      1330     2     5\n -5.9106057000795840E+00 b      1331     2     6\n -1.1326093285804056E+01 b      1332     2     7\n -3.9025063397327071E+00 b      1333     2     8\n  4.4520505166676267E+00 b      1334     2     9\n -1.7352681951318241E+00 b      1335     2    10\n -2.1518912430432668E+00 b      1336     2    11\n  5.0463376560082969E+00 b      1337     2    12\n -2.2614514173852837E-01 b      1338     2    13\n -4.1454590614747211E+00 b      1339     2    14\n  1.6688417293495756E+00 b      1340     2    15\n -5.8649976938793378E+00 b      1341     2    16\n -3.8350084459541849E+00 b      1342     2    17\n  1.3730477223722950E+00 b      1343     2    18\n  1.8506935712854127E+00 b      1344     2    19\n  5.7362757779153428E+00 b      1345     2    20\n  7.2901484895568780E+00 b      1346     2    21\n  3.9773783666446022E-01 b      1347     2    22\n -6.1298011242151409E+00 b      1348     2    23\n  9.9698755072742991E+00 b      1349     2    24\n  1.1801564149295556E+00 b      1350     2    25\n  1.2704098997067026E+01 a      1351     2     1     3     1\n  1.5947733940307620E+00 a      1352     2     2     3     1\n -1.6022927057878529E+00 a      1353     2     3     3     1\n -1.5507258540777733E+00 a      1354     2     4     3     1\n  1.8696884022727636E+00 a      1355     2     5     3     1\n -8.2051908880071633E-01 a      1356     2     6     3     1\n  9.4325719092522542E-01 a      1357     2     7     3     1\n  2.4098435369626174E+00 a      1358     2     8     3     1\n  1.4100759633042474E+00 a      1359     2     9     3     1\n -1.4613034838529613E+00 a      1360     2    10     3     1\n  1.0296574685193380E+00 a      1361     2    11     3     1\n  1.2413851904356363E+00 a      1362     2    12     3     1\n -6.3168181712211169E-01 a      1363     2    13     3     1\n  7.6424175125347729E+00 a      1364     2    14     3     1\n -1.3477038299214714E+00 a      1365     2    15     3     1\n -1.6064659765754943E+00 a      1366     2    16     3     1\n -8.9624380518145874E-01 a      1367     2    17     3     1\n -1.0509865792522375E+00 a      1368     2    18     3     1\n  8.1847872933853638E-01 a      1369     2    19     3     1\n  1.2845504810303034E+00 a      1370     2    20     3     1\n -5.1879822944368881E-01 a      1371     2    21     3     1\n -7.2018714033119180E-01 a      1372     2    22     3     1\n  5.9870832883780798E+00 a      1373     2    23     3     1\n -6.0589155387470683E-01 a      1374     2    24     3     1\n  5.0177609140285355E+00 a      1375     2    25     3     1\n  9.7386086372975722E+00 b      1376     3     1\n"
  },
  {
    "path": "examples/pynnp/prediction/weights.008.data",
    "content": "################################################################################\n# Neural network connection values (weights and biases).\n################################################################################\n# Col  Name       Description\n################################################################################\n# 1    connection Neural network connection value.\n# 2    t          Connection type (a = weight, b = bias).\n# 3    index      Index enumerating weights.\n# 4    l_s        Starting point layer (end point layer for biases).\n# 5    n_s        Starting point neuron in starting layer (end point neuron for biases).\n# 6    l_e        End point layer.\n# 7    n_e        End point neuron in end layer.\n################################################################################\n#                      1 2         3     4     5     6     7\n#             connection t     index   l_s   n_s   l_e   n_e\n############################################################\n -4.2252995889643252E-01 a         1     0     1     1     1\n -6.0555645962054347E+00 a         2     0     1     1     2\n  1.4040722027928377E+01 a         3     0     1     1     3\n -2.7041370011942618E+00 a         4     0     1     1     4\n -3.8202743208058858E+00 a         5     0     1     1     5\n -3.3612643261393358E+00 a         6     0     1     1     6\n -2.0418101025905258E+00 a         7     0     1     1     7\n  7.5707237340996727E+00 a         8     0     1     1     8\n -5.8098755815926548E+00 a         9     0     1     1     9\n -6.0966886893925210E-01 a        10     0     1     1    10\n  5.8061564015115206E+00 a        11     0     1     1    11\n -1.5509339733099867E+00 a        12     0     1     1    12\n  1.9747395485200818E+00 a        13     0     1     1    13\n  4.5260782279680539E-01 a        14     0     1     1    14\n  9.9210415760283279E+00 a        15     0     1     1    15\n -6.5078831481547121E+00 a        16     0     1     1    16\n -3.4768832871318085E+00 a        17     0     1     1    17\n -1.9463994340943838E+00 a        18     0     1     1    18\n -3.4186058699290269E+00 a        19     0     1     1    19\n  1.2263643166698479E+00 a        20     0     1     1    20\n -5.9171161834436594E+00 a        21     0     1     1    21\n  1.8436267358458363E+00 a        22     0     1     1    22\n -2.3139530616378448E+00 a        23     0     1     1    23\n -1.7228542411478951E+01 a        24     0     1     1    24\n  2.2888610253215895E+00 a        25     0     1     1    25\n  8.0819405565169262E+00 a        26     0     2     1     1\n  8.0066409422078735E+00 a        27     0     2     1     2\n -2.8439251469462398E+01 a        28     0     2     1     3\n -1.1146087290797917E+01 a        29     0     2     1     4\n -7.5292172093563314E+00 a        30     0     2     1     5\n -4.0783685663337641E+00 a        31     0     2     1     6\n -4.4130406528599337E+00 a        32     0     2     1     7\n  1.0563249167508673E+01 a        33     0     2     1     8\n  1.0933105521974941E+01 a        34     0     2     1     9\n -1.1646509907117448E+01 a        35     0     2     1    10\n -7.5007478428041727E+00 a        36     0     2     1    11\n  7.7790182254249176E+00 a        37     0     2     1    12\n  1.1567034492555623E+01 a        38     0     2     1    13\n -4.2051741520233508E+00 a        39     0     2     1    14\n  3.1165306119132130E+00 a        40     0     2     1    15\n  1.6385645103485370E+01 a        41     0     2     1    16\n  2.6440539124381655E+00 a        42     0     2     1    17\n -3.9524518111687827E+00 a        43     0     2     1    18\n -8.7912410635652076E+00 a        44     0     2     1    19\n  4.3903318583813933E+00 a        45     0     2     1    20\n  3.3748047065442632E-01 a        46     0     2     1    21\n -6.6858946327311741E-01 a        47     0     2     1    22\n  5.4447187026310928E+00 a        48     0     2     1    23\n  1.9966018946508100E+01 a        49     0     2     1    24\n -1.7414420670154115E+01 a        50     0     2     1    25\n -3.9418657694849879E-01 a        51     0     3     1     1\n  9.1804829174186846E+00 a        52     0     3     1     2\n -1.0485089041850278E+01 a        53     0     3     1     3\n  8.9380499555048889E+00 a        54     0     3     1     4\n  1.0758607876097068E+01 a        55     0     3     1     5\n  7.2881492125393788E+00 a        56     0     3     1     6\n  8.2627077997774609E+00 a        57     0     3     1     7\n -1.2523613158520124E+01 a        58     0     3     1     8\n  4.5963999046141870E+00 a        59     0     3     1     9\n  8.2776469521184293E+00 a        60     0     3     1    10\n -2.1354371687617113E+00 a        61     0     3     1    11\n -9.0381751821938234E+00 a        62     0     3     1    12\n -1.2209592338152297E+00 a        63     0     3     1    13\n  4.7653671372245672E+00 a        64     0     3     1    14\n -1.7909124818088952E+01 a        65     0     3     1    15\n  3.2182917515973237E+00 a        66     0     3     1    16\n -2.3712750109800793E+00 a        67     0     3     1    17\n  4.6394007836500366E+00 a        68     0     3     1    18\n  2.3761984937954490E+00 a        69     0     3     1    19\n -1.0484832585147684E+01 a        70     0     3     1    20\n  1.2317970755621140E+01 a        71     0     3     1    21\n -1.5014054499447769E+00 a        72     0     3     1    22\n -1.1215435083480425E+00 a        73     0     3     1    23\n  8.9428653321614355E+00 a        74     0     3     1    24\n  1.2636165742848842E+00 a        75     0     3     1    25\n -1.3406492086741725E+01 a        76     0     4     1     1\n -1.0241053204283523E+01 a        77     0     4     1     2\n  4.3016369326050899E+01 a        78     0     4     1     3\n  2.0170433813810671E+01 a        79     0     4     1     4\n  1.3209328101408278E+01 a        80     0     4     1     5\n  1.2456789467161695E+01 a        81     0     4     1     6\n  4.3498515722861573E+00 a        82     0     4     1     7\n -2.1948185511490657E+01 a        83     0     4     1     8\n -1.5329558038416376E+01 a        84     0     4     1     9\n  1.4173337432869845E+01 a        85     0     4     1    10\n  5.6040631650516088E+00 a        86     0     4     1    11\n -9.7646834958548663E+00 a        87     0     4     1    12\n -1.3810669587629080E+01 a        88     0     4     1    13\n -1.5274915717855073E+00 a        89     0     4     1    14\n -1.3662043326477198E+01 a        90     0     4     1    15\n -2.5095635769057225E+01 a        91     0     4     1    16\n  5.4033548590960638E+00 a        92     0     4     1    17\n  1.1047593171711565E+01 a        93     0     4     1    18\n  1.9404912122904062E+01 a        94     0     4     1    19\n  2.4043652449872512E+00 a        95     0     4     1    20\n -3.3818087825635010E+00 a        96     0     4     1    21\n -4.9505657938825802E+00 a        97     0     4     1    22\n  6.2159614529590854E+00 a        98     0     4     1    23\n -1.9315299866781363E+01 a        99     0     4     1    24\n  2.4149549923763363E+01 a       100     0     4     1    25\n  2.2633190213689671E+00 a       101     0     5     1     1\n -1.1275056403465689E+01 a       102     0     5     1     2\n  1.2588751117785917E+00 a       103     0     5     1     3\n -1.7399288116611554E+01 a       104     0     5     1     4\n -1.8915392010979964E+01 a       105     0     5     1     5\n -6.5088880348621911E+00 a       106     0     5     1     6\n -8.7022768117985532E+00 a       107     0     5     1     7\n  9.5716939158219958E+00 a       108     0     5     1     8\n  6.7173652175539926E+00 a       109     0     5     1     9\n -1.0675975211687946E+01 a       110     0     5     1    10\n -9.8676303718126039E+00 a       111     0     5     1    11\n  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-1.2648655109330131E+00 a      1253     1    20     2     3\n -4.3905910522706337E-01 a      1254     1    20     2     4\n  4.2887555555714030E-01 a      1255     1    20     2     5\n  1.3300944280643934E+00 a      1256     1    20     2     6\n  1.0988390404457922E+00 a      1257     1    20     2     7\n  2.3801051936039075E+00 a      1258     1    20     2     8\n  1.1789379212300943E-01 a      1259     1    20     2     9\n  3.9144297908957699E+00 a      1260     1    20     2    10\n  5.5000952527940228E-01 a      1261     1    20     2    11\n  2.4087943927489916E-01 a      1262     1    20     2    12\n -3.7997171313505251E-01 a      1263     1    20     2    13\n -5.4744714104500347E-01 a      1264     1    20     2    14\n  8.9095280999944937E-01 a      1265     1    20     2    15\n -8.7130940035564164E-01 a      1266     1    20     2    16\n  3.7900358553306007E-01 a      1267     1    20     2    17\n  2.1342515402584987E+00 a      1268     1    20     2    18\n  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-3.2383137185187805E-01 a      1285     1    21     2    10\n -7.7486670060442631E-01 a      1286     1    21     2    11\n -1.7378145875987788E-01 a      1287     1    21     2    12\n  1.7001762592878558E+00 a      1288     1    21     2    13\n -1.7033999809142997E+00 a      1289     1    21     2    14\n  3.7961258225336264E-01 a      1290     1    21     2    15\n  6.0929689839357426E-01 a      1291     1    21     2    16\n -1.9171250145280534E+00 a      1292     1    21     2    17\n -1.6594854242769004E+00 a      1293     1    21     2    18\n -2.8219229087100910E+00 a      1294     1    21     2    19\n -4.3902463688638738E-01 a      1295     1    21     2    20\n -1.1744026035352828E+00 a      1296     1    21     2    21\n  3.9648025457334164E+00 a      1297     1    21     2    22\n -1.3587513635268793E+00 a      1298     1    21     2    23\n  3.9463311556495906E-02 a      1299     1    21     2    24\n -4.6280624473662763E-01 a      1300     1    21     2    25\n  8.3725910272757709E+00 a      1301     1    22     2     1\n  1.2030400911595496E+00 a      1302     1    22     2     2\n  5.2723639396495003E-01 a      1303     1    22     2     3\n  2.4863416823271995E+00 a      1304     1    22     2     4\n  5.0656775645932173E-01 a      1305     1    22     2     5\n  7.8889662692367113E-01 a      1306     1    22     2     6\n  2.7467021112668549E-01 a      1307     1    22     2     7\n  3.5551997281423904E+00 a      1308     1    22     2     8\n -6.9074567194666425E-01 a      1309     1    22     2     9\n  9.2831069742658789E-01 a      1310     1    22     2    10\n -2.7305664188353734E-01 a      1311     1    22     2    11\n -1.6732686793215996E+00 a      1312     1    22     2    12\n -1.2508123463191103E+00 a      1313     1    22     2    13\n  1.4253551144285490E+00 a      1314     1    22     2    14\n -1.2730453204508483E+00 a      1315     1    22     2    15\n -5.6234386233504563E-01 a      1316     1    22     2    16\n  4.7348930208036427E-01 a      1317     1    22     2    17\n  1.4228359329011722E+00 a      1318     1    22     2    18\n -3.0896237212805277E-02 a      1319     1    22     2    19\n -7.7625773033108136E-01 a      1320     1    22     2    20\n  5.1571228251110171E-02 a      1321     1    22     2    21\n -1.5781774955827834E+00 a      1322     1    22     2    22\n -1.7313703986673430E+00 a      1323     1    22     2    23\n -1.3316987118953665E+00 a      1324     1    22     2    24\n -7.0760527312605037E-01 a      1325     1    22     2    25\n -8.1466385165616928E-01 a      1326     1    23     2     1\n  6.8912340727205368E-01 a      1327     1    23     2     2\n  8.4582890184800619E-01 a      1328     1    23     2     3\n  3.8163700575566650E-01 a      1329     1    23     2     4\n -6.6556600373886232E-01 a      1330     1    23     2     5\n -1.3399458536680564E+00 a      1331     1    23     2     6\n -1.7425009694107033E-01 a      1332     1    23     2     7\n -2.6104662248332646E+00 a      1333     1    23     2     8\n -1.9788280313555501E-01 a      1334     1    23     2     9\n -4.6341960827595043E+00 a      1335     1    23     2    10\n -4.1560774205921192E-01 a      1336     1    23     2    11\n -1.3453315295733928E-01 a      1337     1    23     2    12\n  5.9251987079212687E-01 a      1338     1    23     2    13\n  1.3014540212114664E-01 a      1339     1    23     2    14\n  2.4962768316839337E-01 a      1340     1    23     2    15\n  3.3868458734074913E-01 a      1341     1    23     2    16\n -2.1103970517135956E-01 a      1342     1    23     2    17\n -2.7311756320323316E-01 a      1343     1    23     2    18\n  7.7825779463422798E-02 a      1344     1    23     2    19\n -1.5510879185574573E+00 a      1345     1    23     2    20\n -3.3731285186903501E+00 a      1346     1    23     2    21\n  1.5012690395440691E+00 a      1347     1    23     2    22\n -1.4938786629136067E+00 a      1348     1    23     2    23\n  1.5155834326942672E-01 a      1349     1    23     2    24\n  2.2135367884980521E+00 a      1350     1    23     2    25\n  7.6092107307961931E-01 a      1351     1    24     2     1\n  2.5019321183393825E-02 a      1352     1    24     2     2\n  2.4714648764760871E-01 a      1353     1    24     2     3\n -4.2700090187223255E-01 a      1354     1    24     2     4\n  1.9684439924637190E-01 a      1355     1    24     2     5\n -1.6150658390090172E-01 a      1356     1    24     2     6\n -8.4941771549071021E-01 a      1357     1    24     2     7\n  3.2616941337700417E-01 a      1358     1    24     2     8\n -6.0235251095177200E-01 a      1359     1    24     2     9\n  2.0073315297316108E+00 a      1360     1    24     2    10\n  6.8678637919958119E-01 a      1361     1    24     2    11\n -1.4709309602563259E+00 a      1362     1    24     2    12\n -7.3119546383323997E-01 a      1363     1    24     2    13\n  5.9624465461749732E-01 a      1364     1    24     2    14\n  1.1965703107989687E+00 a      1365     1    24     2    15\n -4.8078015734066326E-01 a      1366     1    24     2    16\n  2.8731897539798784E-01 a      1367     1    24     2    17\n  2.8943049077679879E+00 a      1368     1    24     2    18\n  4.4309374097560666E-01 a      1369     1    24     2    19\n -5.2571668466848664E-01 a      1370     1    24     2    20\n  2.6293009755349539E+00 a      1371     1    24     2    21\n  1.1166360248787797E+00 a      1372     1    24     2    22\n  1.4367909042068954E+00 a      1373     1    24     2    23\n  1.2263949730702137E+00 a      1374     1    24     2    24\n -1.5658327417588482E+00 a      1375     1    24     2    25\n -3.0524380712257440E+00 a      1376     1    25     2     1\n -1.6248402538917406E-01 a      1377     1    25     2     2\n  5.3725239557723847E-01 a      1378     1    25     2     3\n -3.1435543583372311E-01 a      1379     1    25     2     4\n  8.0294309812719877E-01 a      1380     1    25     2     5\n -3.3745709161028831E-01 a      1381     1    25     2     6\n  2.9618139473335392E-01 a      1382     1    25     2     7\n -1.3606606680314999E+00 a      1383     1    25     2     8\n  2.9886863438452965E-01 a      1384     1    25     2     9\n  3.4365095196288835E+00 a      1385     1    25     2    10\n  2.8778063903425566E-01 a      1386     1    25     2    11\n -5.2312889094867954E-01 a      1387     1    25     2    12\n  4.5730896273705224E-01 a      1388     1    25     2    13\n -8.8949447500584955E-01 a      1389     1    25     2    14\n -8.1389897744929640E-01 a      1390     1    25     2    15\n -4.0077086298379117E-01 a      1391     1    25     2    16\n  7.2544627916775950E-01 a      1392     1    25     2    17\n -9.8029709488119798E-01 a      1393     1    25     2    18\n  8.5017837869712165E-01 a      1394     1    25     2    19\n -2.9795775527520296E-01 a      1395     1    25     2    20\n  1.1940911570260535E+00 a      1396     1    25     2    21\n -4.1259772504588357E-02 a      1397     1    25     2    22\n  1.0619824936744515E+00 a      1398     1    25     2    23\n -6.5325825341918264E-01 a      1399     1    25     2    24\n  3.7575240210802421E+00 a      1400     1    25     2    25\n -1.0787018434494783E+01 b      1401     2     1\n -8.4067078142086771E-01 b      1402     2     2\n  9.3201271110229211E-01 b      1403     2     3\n -1.8318272256547821E+00 b      1404     2     4\n -2.1732436845179119E+00 b      1405     2     5\n -2.6390929073478930E+00 b      1406     2     6\n  3.7489748853957300E-01 b      1407     2     7\n -2.3789675524866163E+00 b      1408     2     8\n  2.7252644932624959E+00 b      1409     2     9\n  2.5100559841854970E+00 b      1410     2    10\n -2.4897033671113025E-01 b      1411     2    11\n  2.6913296692082476E+00 b      1412     2    12\n  5.8162695990329221E+00 b      1413     2    13\n -1.5170700889568940E+00 b      1414     2    14\n  4.2121259244130220E+00 b      1415     2    15\n  2.2987725066596130E+00 b      1416     2    16\n -7.1493650128731911E-01 b      1417     2    17\n -3.9961443472349811E-01 b      1418     2    18\n  7.8083705485664430E+00 b      1419     2    19\n -4.0462773256448170E-01 b      1420     2    20\n -1.4333029489891109E+00 b      1421     2    21\n -4.9517224038431467E+00 b      1422     2    22\n  1.0702867307710989E+01 b      1423     2    23\n -9.7535853921453985E-01 b      1424     2    24\n  5.3161969295054172E+00 b      1425     2    25\n -5.1941647295982207E-01 a      1426     2     1     3     1\n -7.7346657642095373E-01 a      1427     2     2     3     1\n  1.4003893583106508E+00 a      1428     2     3     3     1\n  8.9188080044914464E-01 a      1429     2     4     3     1\n -2.0147808233792022E+00 a      1430     2     5     3     1\n -1.8131831735812174E+00 a      1431     2     6     3     1\n  3.3217884596641700E+00 a      1432     2     7     3     1\n -1.2675289031787327E+00 a      1433     2     8     3     1\n -1.2791140359120716E+00 a      1434     2     9     3     1\n  1.9731828075446340E+00 a      1435     2    10     3     1\n -2.3928332883234411E+00 a      1436     2    11     3     1\n -1.1755085043375486E+00 a      1437     2    12     3     1\n  2.6525670286472951E+00 a      1438     2    13     3     1\n -2.4861988521743901E+00 a      1439     2    14     3     1\n  1.2534500349238071E+00 a      1440     2    15     3     1\n  2.8804282010183990E+00 a      1441     2    16     3     1\n -2.0327745898215275E+00 a      1442     2    17     3     1\n -1.1760164122204946E+00 a      1443     2    18     3     1\n -9.9841804355412322E-01 a      1444     2    19     3     1\n -1.8663330516323837E+00 a      1445     2    20     3     1\n  6.3266049836286531E-01 a      1446     2    21     3     1\n  1.2025500357718348E+00 a      1447     2    22     3     1\n  1.1367820678861495E-01 a      1448     2    23     3     1\n -2.6481374255863193E+00 a      1449     2    24     3     1\n  5.2166795947347921E-01 a      1450     2    25     3     1\n  4.8693043186011655E+00 b      1451     3     1\n"
  },
  {
    "path": "examples/pynnp/symfunc-only/example.ipynb",
    "content": "{\n \"cells\": [\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 1,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"# To capture the NNP library stdout output we have two possible options:\\n\",\n    \"#\\n\",\n    \"# 1.) Install \\\"wurlitzer\\\" available via pip or github.com/minrk/wurlitzer\\n\",\n    \"#     > pip install wurlitzer\\n\",\n    \"#     and load as extension\\n\",\n    \"#     > %load_ext wurlitzer\\n\",\n    \"#\\n\",\n    \"# 2.) Silence the library output (which will otherwise go to Jupyter server shell)\\n\",\n    \"#     > nnp = pynnp.Mode()\\n\",\n    \"#     > nnp.log.writeToStdout = False\\n\",\n    \"#     > ... do initialization ...\\n\",\n    \"#     and recall the log later:\\n\",\n    \"#     > for line in nnp.log.getLog():\\n\",\n    \"#     >     sys.stdout.write(line)\\n\",\n    \"#\\n\",\n    \"# Option 1.) is obviously more comfortable and will also capture output to stderr.\\n\",\n    \"%load_ext wurlitzer\\n\",\n    \"import pynnp\\n\",\n    \"from sys import stdout as so\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 2,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"# Create instance of NNP setup.                               \\n\",\n    \"nnp = pynnp.Mode()\\n\",\n    \"\\n\",\n    \"# Turn off output to stdout (for Option 2.) described above).\\n\",\n    \"#nnp.log.writeToStdout = False\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 3,\n   \"metadata\": {\n    \"scrolled\": false\n   },\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"\\n\",\n      \"*******************************************************************************\\n\",\n      \"\\n\",\n      \"   NNP LIBRARY v2.0.0\\n\",\n      \"   ------------------\\n\",\n      \"\\n\",\n      \"Git branch  : master\\n\",\n      \"Git revision: e7a2975 (e7a29759d35de1e94b09bf88b270a76e20f41323)\\n\",\n      \"\\n\",\n      \"*******************************************************************************\\n\",\n      \"\\n\",\n      \"*** SETUP: SETTINGS FILE ******************************************************\\n\",\n      \"\\n\",\n      \"Settings file name: input.nn\\n\",\n      \"Read 175 lines.\\n\",\n      \"Found 102 lines with keywords.\\n\",\n      \"*******************************************************************************\\n\",\n      \"\\n\",\n      \"*** SETUP: ELEMENT MAP ********************************************************\\n\",\n      \"\\n\",\n      \"Number of element strings found: 2\\n\",\n      \"Element  0:  H (  1)\\n\",\n      \"Element  1:  O (  8)\\n\",\n      \"*******************************************************************************\\n\",\n      \"\\n\",\n      \"*** SETUP: ELEMENTS ***********************************************************\\n\",\n      \"\\n\",\n      \"Number of elements is consistent: 2\\n\",\n      \"Atomic energy offsets per element:\\n\",\n      \"Element  0:   0.00000000E+00\\n\",\n      \"Element  1:   0.00000000E+00\\n\",\n      \"Energy offsets are automatically subtracted from reference energies.\\n\",\n      \"*******************************************************************************\\n\",\n      \"\\n\",\n      \"*** SETUP: CUTOFF FUNCTIONS ***************************************************\\n\",\n      \"\\n\",\n      \"Parameter alpha for inner cutoff: 0.000000\\n\",\n      \"Inner cutoff = Symmetry function cutoff * alpha\\n\",\n      \"Equal cutoff function type for all symmetry functions:\\n\",\n      \"CutoffFunction::CT_TANHU (2)\\n\",\n      \"f(r) = tanh^3(1 - r/rc)\\n\",\n      \"*******************************************************************************\\n\",\n      \"\\n\",\n      \"*** SETUP: SYMMETRY FUNCTIONS *************************************************\\n\",\n      \"\\n\",\n      \"Abbreviations:\\n\",\n      \"--------------\\n\",\n      \"ind .... Symmetry function index.\\n\",\n      \"ec ..... Central atom element.\\n\",\n      \"ty ..... Symmetry function type.\\n\",\n      \"e1 ..... Neighbor 1 element.\\n\",\n      \"e2 ..... Neighbor 2 element.\\n\",\n      \"eta .... Gaussian width eta.\\n\",\n      \"rs ..... Shift distance of Gaussian.\\n\",\n      \"la ..... Angle prefactor lambda.\\n\",\n      \"zeta ... Angle term exponent zeta.\\n\",\n      \"rc ..... Cutoff radius.\\n\",\n      \"ct ..... Cutoff type.\\n\",\n      \"ca ..... Cutoff alpha.\\n\",\n      \"ln ..... Line number in settings file.\\n\",\n      \"\\n\",\n      \"Short range atomic symmetry functions element  H :\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \" ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \"   1  H  2  H    1.000E-03 0.000E+00         1.200E+01  2 0.00   106\\n\",\n      \"   2  H  2  O    1.000E-03 0.000E+00         1.200E+01  2 0.00   116\\n\",\n      \"   3  H  2  H    1.000E-02 0.000E+00         1.200E+01  2 0.00   107\\n\",\n      \"   4  H  2  O    1.000E-02 0.000E+00         1.200E+01  2 0.00   117\\n\",\n      \"   5  H  2  H    3.000E-02 0.000E+00         1.200E+01  2 0.00   108\\n\",\n      \"   6  H  2  O    3.000E-02 0.000E+00         1.200E+01  2 0.00   118\\n\",\n      \"   7  H  2  H    6.000E-02 0.000E+00         1.200E+01  2 0.00   109\\n\",\n      \"   8  H  2  O    6.000E-02 0.000E+00         1.200E+01  2 0.00   119\\n\",\n      \"   9  H  2  O    1.500E-01 9.000E-01         1.200E+01  2 0.00   120\\n\",\n      \"  10  H  2  H    1.500E-01 1.900E+00         1.200E+01  2 0.00   110\\n\",\n      \"  11  H  2  O    3.000E-01 9.000E-01         1.200E+01  2 0.00   121\\n\",\n      \"  12  H  2  H    3.000E-01 1.900E+00         1.200E+01  2 0.00   111\\n\",\n      \"  13  H  2  O    6.000E-01 9.000E-01         1.200E+01  2 0.00   122\\n\",\n      \"  14  H  2  H    6.000E-01 1.900E+00         1.200E+01  2 0.00   112\\n\",\n      \"  15  H  2  O    1.500E+00 9.000E-01         1.200E+01  2 0.00   123\\n\",\n      \"  16  H  2  H    1.500E+00 1.900E+00         1.200E+01  2 0.00   113\\n\",\n      \"  17  H  3  O  O 1.000E-03 0.000E+00 -1  4.0 1.200E+01  2 0.00   170\\n\",\n      \"  18  H  3  O  O 1.000E-03 0.000E+00  1  4.0 1.200E+01  2 0.00   169\\n\",\n      \"  19  H  3  H  O 1.000E-02 0.000E+00 -1  4.0 1.200E+01  2 0.00   160\\n\",\n      \"  20  H  3  H  O 1.000E-02 0.000E+00  1  4.0 1.200E+01  2 0.00   158\\n\",\n      \"  21  H  3  H  O 3.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   155\\n\",\n      \"  22  H  3  O  O 3.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   168\\n\",\n      \"  23  H  3  H  O 3.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   153\\n\",\n      \"  24  H  3  O  O 3.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   167\\n\",\n      \"  25  H  3  H  O 7.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   150\\n\",\n      \"  26  H  3  H  O 7.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   148\\n\",\n      \"  27  H  3  H  O 2.000E-01 0.000E+00  1  1.0 1.200E+01  2 0.00   145\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \"Short range atomic symmetry functions element  O :\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \" ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \"   1  O  2  H    1.000E-03 0.000E+00         1.200E+01  2 0.00   125\\n\",\n      \"   2  O  2  O    1.000E-03 0.000E+00         1.200E+01  2 0.00   135\\n\",\n      \"   3  O  2  H    1.000E-02 0.000E+00         1.200E+01  2 0.00   126\\n\",\n      \"   4  O  2  O    1.000E-02 0.000E+00         1.200E+01  2 0.00   136\\n\",\n      \"   5  O  2  H    3.000E-02 0.000E+00         1.200E+01  2 0.00   127\\n\",\n      \"   6  O  2  O    3.000E-02 0.000E+00         1.200E+01  2 0.00   137\\n\",\n      \"   7  O  2  H    6.000E-02 0.000E+00         1.200E+01  2 0.00   128\\n\",\n      \"   8  O  2  O    6.000E-02 0.000E+00         1.200E+01  2 0.00   138\\n\",\n      \"   9  O  2  H    1.500E-01 9.000E-01         1.200E+01  2 0.00   129\\n\",\n      \"  10  O  2  O    1.500E-01 4.000E+00         1.200E+01  2 0.00   139\\n\",\n      \"  11  O  2  H    3.000E-01 9.000E-01         1.200E+01  2 0.00   130\\n\",\n      \"  12  O  2  O    3.000E-01 4.000E+00         1.200E+01  2 0.00   140\\n\",\n      \"  13  O  2  H    6.000E-01 9.000E-01         1.200E+01  2 0.00   131\\n\",\n      \"  14  O  2  O    6.000E-01 4.000E+00         1.200E+01  2 0.00   141\\n\",\n      \"  15  O  2  H    1.500E+00 9.000E-01         1.200E+01  2 0.00   132\\n\",\n      \"  16  O  2  O    1.500E+00 4.000E+00         1.200E+01  2 0.00   142\\n\",\n      \"  17  O  3  H  O 1.000E-03 0.000E+00 -1  4.0 1.200E+01  2 0.00   165\\n\",\n      \"  18  O  3  O  O 1.000E-03 0.000E+00 -1  4.0 1.200E+01  2 0.00   175\\n\",\n      \"  19  O  3  H  O 1.000E-03 0.000E+00  1  4.0 1.200E+01  2 0.00   164\\n\",\n      \"  20  O  3  O  O 1.000E-03 0.000E+00  1  4.0 1.200E+01  2 0.00   174\\n\",\n      \"  21  O  3  H  H 1.000E-02 0.000E+00 -1  4.0 1.200E+01  2 0.00   159\\n\",\n      \"  22  O  3  H  H 1.000E-02 0.000E+00  1  4.0 1.200E+01  2 0.00   157\\n\",\n      \"  23  O  3  H  H 3.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   154\\n\",\n      \"  24  O  3  H  O 3.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   163\\n\",\n      \"  25  O  3  O  O 3.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   173\\n\",\n      \"  26  O  3  H  H 3.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   152\\n\",\n      \"  27  O  3  H  O 3.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   162\\n\",\n      \"  28  O  3  O  O 3.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   172\\n\",\n      \"  29  O  3  H  H 7.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   149\\n\",\n      \"  30  O  3  H  H 7.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   147\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \"Minimum cutoff radius for element  H: 12.000000\\n\",\n      \"Minimum cutoff radius for element  O: 12.000000\\n\",\n      \"Maximum cutoff radius (global)      : 12.000000\\n\",\n      \"*******************************************************************************\\n\",\n      \"\\n\",\n      \"*** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\\n\",\n      \"\\n\",\n      \"Abbreviations:\\n\",\n      \"--------------\\n\",\n      \"ind .... Symmetry function group index.\\n\",\n      \"ec ..... Central atom element.\\n\",\n      \"ty ..... Symmetry function type.\\n\",\n      \"e1 ..... Neighbor 1 element.\\n\",\n      \"e2 ..... Neighbor 2 element.\\n\",\n      \"eta .... Gaussian width eta.\\n\",\n      \"rs ..... Shift distance of Gaussian.\\n\",\n      \"la ..... Angle prefactor lambda.\\n\",\n      \"zeta ... Angle term exponent zeta.\\n\",\n      \"rc ..... Cutoff radius.\\n\",\n      \"ct ..... Cutoff type.\\n\",\n      \"ca ..... Cutoff alpha.\\n\",\n      \"ln ..... Line number in settings file.\\n\",\n      \"mi ..... Member index.\\n\",\n      \"sfi .... Symmetry function index.\\n\",\n      \"e ...... Recalculate exponential term.\\n\",\n      \"\\n\",\n      \"Short range atomic symmetry function groups element  H :\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \" ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \"   1  H  2  H            *         *         1.200E+01  2 0.00     *    *    *  \\n\",\n      \"   -  -  -  -    1.000E-03 0.000E+00                 -  -    -   105    1    1  \\n\",\n      \"   -  -  -  -    1.000E-02 0.000E+00                 -  -    -   106    2    3  \\n\",\n      \"   -  -  -  -    3.000E-02 0.000E+00                 -  -    -   107    3    5  \\n\",\n      \"   -  -  -  -    6.000E-02 0.000E+00                 -  -    -   108    4    7  \\n\",\n      \"   -  -  -  -    1.500E-01 1.900E+00                 -  -    -   109    5   10  \\n\",\n      \"   -  -  -  -    3.000E-01 1.900E+00                 -  -    -   110    6   12  \\n\",\n      \"   -  -  -  -    6.000E-01 1.900E+00                 -  -    -   111    7   14  \\n\",\n      \"   -  -  -  -    1.500E+00 1.900E+00                 -  -    -   112    8   16  \\n\",\n      \"   2  H  2  O            *         *         1.200E+01  2 0.00     *    *    *  \\n\",\n      \"   -  -  -  -    1.000E-03 0.000E+00                 -  -    -   115    1    2  \\n\",\n      \"   -  -  -  -    1.000E-02 0.000E+00                 -  -    -   116    2    4  \\n\",\n      \"   -  -  -  -    3.000E-02 0.000E+00                 -  -    -   117    3    6  \\n\",\n      \"   -  -  -  -    6.000E-02 0.000E+00                 -  -    -   118    4    8  \\n\",\n      \"   -  -  -  -    1.500E-01 9.000E-01                 -  -    -   119    5    9  \\n\",\n      \"   -  -  -  -    3.000E-01 9.000E-01                 -  -    -   120    6   11  \\n\",\n      \"   -  -  -  -    6.000E-01 9.000E-01                 -  -    -   121    7   13  \\n\",\n      \"   -  -  -  -    1.500E+00 9.000E-01                 -  -    -   122    8   15  \\n\",\n      \"   3  H  3  H  O         *         *  *    * 1.200E+01  2 0.00     *    *    * *\\n\",\n      \"   -  -  -  -  - 1.000E-02 0.000E+00 -1  4.0         -  -    -   159    1   19 1\\n\",\n      \"   -  -  -  -  - 1.000E-02 0.000E+00  1  4.0         -  -    -   157    2   20 0\\n\",\n      \"   -  -  -  -  - 3.000E-02 0.000E+00 -1  1.0         -  -    -   154    3   21 1\\n\",\n      \"   -  -  -  -  - 3.000E-02 0.000E+00  1  1.0         -  -    -   152    4   23 0\\n\",\n      \"   -  -  -  -  - 7.000E-02 0.000E+00 -1  1.0         -  -    -   149    5   25 1\\n\",\n      \"   -  -  -  -  - 7.000E-02 0.000E+00  1  1.0         -  -    -   147    6   26 0\\n\",\n      \"   -  -  -  -  - 2.000E-01 0.000E+00  1  1.0         -  -    -   144    7   27 1\\n\",\n      \"   4  H  3  O  O         *         *  *    * 1.200E+01  2 0.00     *    *    * *\\n\",\n      \"   -  -  -  -  - 1.000E-03 0.000E+00 -1  4.0         -  -    -   169    1   17 1\\n\",\n      \"   -  -  -  -  - 1.000E-03 0.000E+00  1  4.0         -  -    -   168    2   18 0\\n\",\n      \"   -  -  -  -  - 3.000E-02 0.000E+00 -1  1.0         -  -    -   167    3   22 1\\n\",\n      \"   -  -  -  -  - 3.000E-02 0.000E+00  1  1.0         -  -    -   166    4   24 0\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \"Short range atomic symmetry function groups element  O :\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \" ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \"   1  O  2  H            *         *         1.200E+01  2 0.00     *    *    *  \\n\",\n      \"   -  -  -  -    1.000E-03 0.000E+00                 -  -    -   124    1    1  \\n\",\n      \"   -  -  -  -    1.000E-02 0.000E+00                 -  -    -   125    2    3  \\n\",\n      \"   -  -  -  -    3.000E-02 0.000E+00                 -  -    -   126    3    5  \\n\",\n      \"   -  -  -  -    6.000E-02 0.000E+00                 -  -    -   127    4    7  \\n\",\n      \"   -  -  -  -    1.500E-01 9.000E-01                 -  -    -   128    5    9  \\n\",\n      \"   -  -  -  -    3.000E-01 9.000E-01                 -  -    -   129    6   11  \\n\",\n      \"   -  -  -  -    6.000E-01 9.000E-01                 -  -    -   130    7   13  \\n\",\n      \"   -  -  -  -    1.500E+00 9.000E-01                 -  -    -   131    8   15  \\n\",\n      \"   2  O  2  O            *         *         1.200E+01  2 0.00     *    *    *  \\n\",\n      \"   -  -  -  -    1.000E-03 0.000E+00                 -  -    -   134    1    2  \\n\",\n      \"   -  -  -  -    1.000E-02 0.000E+00                 -  -    -   135    2    4  \\n\",\n      \"   -  -  -  -    3.000E-02 0.000E+00                 -  -    -   136    3    6  \\n\",\n      \"   -  -  -  -    6.000E-02 0.000E+00                 -  -    -   137    4    8  \\n\",\n      \"   -  -  -  -    1.500E-01 4.000E+00                 -  -    -   138    5   10  \\n\",\n      \"   -  -  -  -    3.000E-01 4.000E+00                 -  -    -   139    6   12  \\n\",\n      \"   -  -  -  -    6.000E-01 4.000E+00                 -  -    -   140    7   14  \\n\",\n      \"   -  -  -  -    1.500E+00 4.000E+00                 -  -    -   141    8   16  \\n\",\n      \"   3  O  3  H  H         *         *  *    * 1.200E+01  2 0.00     *    *    * *\\n\",\n      \"   -  -  -  -  - 1.000E-02 0.000E+00 -1  4.0         -  -    -   158    1   21 1\\n\",\n      \"   -  -  -  -  - 1.000E-02 0.000E+00  1  4.0         -  -    -   156    2   22 0\\n\",\n      \"   -  -  -  -  - 3.000E-02 0.000E+00 -1  1.0         -  -    -   153    3   23 1\\n\",\n      \"   -  -  -  -  - 3.000E-02 0.000E+00  1  1.0         -  -    -   151    4   26 0\\n\",\n      \"   -  -  -  -  - 7.000E-02 0.000E+00 -1  1.0         -  -    -   148    5   29 1\\n\",\n      \"   -  -  -  -  - 7.000E-02 0.000E+00  1  1.0         -  -    -   146    6   30 0\\n\",\n      \"   4  O  3  H  O         *         *  *    * 1.200E+01  2 0.00     *    *    * *\\n\",\n      \"   -  -  -  -  - 1.000E-03 0.000E+00 -1  4.0         -  -    -   164    1   17 1\\n\",\n      \"   -  -  -  -  - 1.000E-03 0.000E+00  1  4.0         -  -    -   163    2   19 0\\n\",\n      \"   -  -  -  -  - 3.000E-02 0.000E+00 -1  1.0         -  -    -   162    3   24 1\\n\",\n      \"   -  -  -  -  - 3.000E-02 0.000E+00  1  1.0         -  -    -   161    4   27 0\\n\",\n      \"   5  O  3  O  O         *         *  *    * 1.200E+01  2 0.00     *    *    * *\\n\",\n      \"   -  -  -  -  - 1.000E-03 0.000E+00 -1  4.0         -  -    -   174    1   18 1\\n\",\n      \"   -  -  -  -  - 1.000E-03 0.000E+00  1  4.0         -  -    -   173    2   20 0\\n\",\n      \"   -  -  -  -  - 3.000E-02 0.000E+00 -1  1.0         -  -    -   172    3   25 1\\n\",\n      \"   -  -  -  -  - 3.000E-02 0.000E+00  1  1.0         -  -    -   171    4   28 0\\n\",\n      \"-------------------------------------------------------------------------------\\n\",\n      \"*******************************************************************************\\n\",\n      \"\\n\",\n      \"*** SETUP: SYMMETRY FUNCTION SCALING ******************************************\\n\",\n      \"\\n\",\n      \"No scaling for symmetry functions.\\n\",\n      \"*******************************************************************************\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Run initialization steps (symmetry functions only).\\n\",\n    \"nnp.initialize()                                                                  \\n\",\n    \"nnp.loadSettingsFile(\\\"input.nn\\\")                                                  \\n\",\n    \"nnp.setupElementMap()                                                             \\n\",\n    \"nnp.setupElements()                                                               \\n\",\n    \"nnp.setupCutoff()                                                                 \\n\",\n    \"nnp.setupSymmetryFunctions()                                                      \\n\",\n    \"nnp.setupSymmetryMemory() # comment out when compiled with N2P2_FULL_SFD_MEMORY   \\n\",\n    \"nnp.setupSymmetryCache() # comment out when compiled with N2P2_NO_SF_CACHE        \\n\",\n    \"nnp.setupSymmetryFunctionGroups()\\n\",\n    \"# Either use symmetry function scaling...\\n\",\n    \"#nnp.setupSymmetryFunctionScaling(\\\"scaling.data\\\")                                  \\n\",\n    \"#nnp.setupSymmetryFunctionStatistics(False, False, True, False)\\n\",\n    \"# ... or calculate raw values.\\n\",\n    \"nnp.setupSymmetryFunctionScalingNone()\\n\",\n    \"\\n\",\n    \"# Print log file (for Option 2.) described above).\\n\",\n    \"#for line in m.log.getLog():\\n\",\n    \"#    so.write(line)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 4,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"# Create an empty structure.\\n\",\n    \"struct = pynnp.Structure()\\n\",\n    \"\\n\",\n    \"# Tell the structure which elements are to be expected,\\n\",\n    \"# i.e. pass the ElementMap from the NNP setup instance.\\n\",\n    \"# Note: this step is required!\\n\",\n    \"struct.setElementMap(nnp.elementMap)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 5,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"Number of atoms:  24\\n\",\n      \"Number of atoms per element: \\n\",\n      \"H :  16\\n\",\n      \"O :  8\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Read in configuration from file.\\n\",\n    \"# WARNING: Do not read repeatedly as this will pile up atoms!\\n\",\n    \"struct.readFromFile(\\\"input.data.1\\\")\\n\",\n    \"\\n\",\n    \"# Print some information:\\n\",\n    \"print(\\\"Number of atoms: \\\", struct.numAtoms)\\n\",\n    \"print(\\\"Number of atoms per element: \\\")\\n\",\n    \"for (i, n) in enumerate(struct.numAtomsPerElement):\\n\",\n    \"    print(nnp.elementMap[i], \\\": \\\", n)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 6,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"Cutoff radius =  12.0\\n\",\n      \"Atom    0 (O ): 142 neighbors\\n\",\n      \"Atom    1 (O ): 142 neighbors\\n\",\n      \"Atom    2 (O ): 142 neighbors\\n\",\n      \"Atom    3 (O ): 142 neighbors\\n\",\n      \"Atom    4 (O ): 142 neighbors\\n\",\n      \"Atom    5 (O ): 142 neighbors\\n\",\n      \"Atom    6 (O ): 142 neighbors\\n\",\n      \"Atom    7 (O ): 142 neighbors\\n\",\n      \"Atom    8 (H ): 127 neighbors\\n\",\n      \"Atom    9 (H ): 127 neighbors\\n\",\n      \"Atom   10 (H ): 127 neighbors\\n\",\n      \"Atom   11 (H ): 127 neighbors\\n\",\n      \"Atom   12 (H ): 127 neighbors\\n\",\n      \"Atom   13 (H ): 127 neighbors\\n\",\n      \"Atom   14 (H ): 127 neighbors\\n\",\n      \"Atom   15 (H ): 128 neighbors\\n\",\n      \"Atom   16 (H ): 127 neighbors\\n\",\n      \"Atom   17 (H ): 127 neighbors\\n\",\n      \"Atom   18 (H ): 128 neighbors\\n\",\n      \"Atom   19 (H ): 127 neighbors\\n\",\n      \"Atom   20 (H ): 127 neighbors\\n\",\n      \"Atom   21 (H ): 127 neighbors\\n\",\n      \"Atom   22 (H ): 127 neighbors\\n\",\n      \"Atom   23 (H ): 127 neighbors\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Retrieve cutoff radius form NNP setup.                                        \\n\",\n    \"cutoffRadius = nnp.getMaxCutoffRadius()                                           \\n\",\n    \"print(\\\"Cutoff radius = \\\", cutoffRadius)                                         \\n\",\n    \"                                                                                \\n\",\n    \"# Calculate neighbor list.                                                      \\n\",\n    \"struct.calculateNeighborList(cutoffRadius)\\n\",\n    \"\\n\",\n    \"# Show some information about neighbor list.\\n\",\n    \"for atom in struct.atoms:\\n\",\n    \"    print(\\\"Atom {0:4d} ({1:2s}): {2:3d} neighbors\\\".format(atom.index, nnp.elementMap[atom.element], atom.numNeighbors))\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 7,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"[3.0979046907343974, 1.18994287347951, 2.3374571003048064, 0.8149627350606994, 1.4183860085998368, 0.365071888883069, 0.8566908159542491, 0.11517221925856677, 0.6816891712438031, 0.5470457335903648, 0.5140233759056304, 0.2789086480393483, 0.3795853440912408, 0.08424583073547427, 0.16736514762008486, 0.0037220328749432313, 0.017450677340565067, 0.0005024982243135199, 0.2321654300938664, 0.015056415734351522, 0.02580794766232825, 0.08085925995465679, 0.04351493344073904, 0.00607693892348457, 0.0003358516494455779, 0.048211127016197244, 0.029932837634662226, 0.000989359235199765, 0.01398246084208952, 0.010175918586600824]\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Calculate symmetry functions for all atoms (using groups is generally faster).\\n\",\n    \"#nnp.calculateSymmetryFunctions(s, False)\\n\",\n    \"nnp.calculateSymmetryFunctionGroups(struct, False)\\n\",\n    \"                                                                                \\n\",\n    \"# Retrieve symmetry functions of atom with index 0.\\n\",\n    \"# Symmetry functions sort order is provided in the library output\\n\",\n    \"# of the setupSymmetryFunctions() method (see above).\\n\",\n    \"print(struct.atoms[0].G)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 8,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"CPU times: user 15.6 ms, sys: 0 ns, total: 15.6 ms\\n\",\n      \"Wall time: 15.6 ms\\n\",\n      \"[2.86649377277164, 1.6229466695415529, 2.0623976954260583, 1.2201970615555326, 1.0990912879196195, 0.7414354094663689, 0.5115930320848044, 0.45659991006210426, 0.3768515741861182, 0.5650265555940194, 0.278675620398098, 0.2635626900178468, 0.19573039002565443, 0.12387824509705335, 0.0866044486663157, 0.03509025803430324, 0.02230215047551002, 0.031993442362933104, 0.019395663617398876, 0.1728751811637228, 0.01879781449053553, 0.007054820572245642, 0.08605197074485345, 0.004730188232226057, 0.003192176127904365, 0.022823231470083947, 0.0017684369314133184]\\n\"\n     ]\n    }\n   ],\n   \"source\": [\n    \"# Repeat the procedure for another structure.\\n\",\n    \"\\n\",\n    \"# First reset the structure, this will erase all data except for the ElementMap.\\n\",\n    \"struct.reset()\\n\",\n    \"\\n\",\n    \"struct.readFromFile(\\\"input.data.2\\\")\\n\",\n    \"struct.calculateNeighborList(cutoffRadius)\\n\",\n    \"%time nnp.calculateSymmetryFunctionGroups(struct, False)\\n\",\n    \"print(struct.atoms[0].G)\"\n   ]\n  }\n ],\n \"metadata\": {\n  \"anaconda-cloud\": {},\n  \"kernelspec\": {\n   \"display_name\": \"Python 3\",\n   \"language\": \"python\",\n   \"name\": \"python3\"\n  },\n  \"language_info\": {\n   \"codemirror_mode\": {\n    \"name\": \"ipython\",\n    \"version\": 3\n   },\n   \"file_extension\": \".py\",\n   \"mimetype\": \"text/x-python\",\n   \"name\": \"python\",\n   \"nbconvert_exporter\": \"python\",\n   \"pygments_lexer\": \"ipython3\",\n   \"version\": \"3.6.8\"\n  }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 2\n}\n"
  },
  {
    "path": "examples/pynnp/symfunc-only/example.py",
    "content": "#!/bin/env python\n\nfrom __future__ import absolute_import\nfrom __future__ import print_function\nimport pynnp\n\n# Initialize NNP setup (symmetry functions only).\nm = pynnp.Mode()\nm.initialize()\nm.loadSettingsFile(\"input.nn\")\nm.setupElementMap()\nm.setupElements()\nm.setupCutoff()\nm.setupSymmetryFunctions()\nm.setupSymmetryFunctionMemory() # comment out when compiled with N2P2_FULL_SFD_MEMORY\nm.setupSymmetryFunctionCache() # comment out when compiled with N2P2_NO_SF_CACHE\nm.setupSymmetryFunctionGroups()\n# Either use symmetry function scaling...\n#m.setupSymmetryFunctionScaling(\"scaling.data\")\n#m.setupSymmetryFunctionStatistics(False, False, True, False)\n# ... or calculate raw values.\nm.setupSymmetryFunctionScalingNone()\n\n# Initialize NNP structure data container.\ns = pynnp.Structure()\ns.setElementMap(m.elementMap)\n\n# Read in data via Structure member function.\ns.readFromFile(\"input.data.1\")\n\n# Retrieve cutoff radius form NNP setup.\ncutoffRadius = m.getMaxCutoffRadius()\nprint(\"Cutoff radius = \", cutoffRadius)\n\n# Calculate neighbor list.\ns.calculateNeighborList(cutoffRadius)\n\n# Calculate symmetry functions for all atoms (use groups).\n#m.calculateSymmetryFunctions(s, False)\nm.calculateSymmetryFunctionGroups(s, False)\n\n# Loop over atoms, symmetry function values are stored in \"G\" member.\nprint(\"------------\")\nprint(\"Structure 1:\")\nprint(\"------------\")\nprint(\"numAtoms           : \", s.numAtoms)\nprint(\"numAtomsPerElement : \", s.numAtomsPerElement)\nprint(\"------------\")\nfor atom in s.atoms:\n    print(atom.index, atom.element, m.elementMap[atom.element], len(atom.G), atom.G[0])\n\n####################################################\n# Let's do the same thing for another configuration.\n####################################################\n\n# Reseting a structure clears everything but the element map.\ns.reset()\n\ns.readFromFile(\"input.data.2\")\ns.calculateNeighborList(cutoffRadius)\nm.calculateSymmetryFunctionGroups(s, False)\nprint(\"------------\")\nprint(\"Structure 2:\")\nprint(\"------------\")\nprint(\"numAtoms           : \", s.numAtoms)\nprint(\"numAtomsPerElement : \", s.numAtomsPerElement)\nprint(\"------------\")\nfor atom in s.atoms:\n    print(atom.index, atom.element, m.elementMap[atom.element], len(atom.G), atom.G[0])\n"
  },
  {
    "path": "examples/pynnp/symfunc-only/input.data.1",
    "content": "begin\nlattice             9.716666            0.000000            0.000000\nlattice             0.000000            9.716666            0.000000\nlattice             0.000000            0.000000           14.129322\natom          -0.006589478         0.009994765         3.257579222 O      -0.240244      0.000000     -0.000411      0.001926      0.009947\natom           0.001719651         4.858527487         6.808015088 O      -0.242134      0.000000     -0.020804      0.000443      0.013399\natom           4.823418251         0.026257755         7.310958337 O      -0.239876      0.000000      0.000770     -0.040620      0.001369\natom           4.828375005         4.830119223         3.792500430 O      -0.241319      0.000000      0.016998      0.000707     -0.006202\natom           4.811588561         4.853771044        10.349414279 O      -0.242113      0.000000      0.000848      0.021624      0.014391\natom           4.879237004         9.697362130        13.917547437 O      -0.240743      0.000000      0.000740     -0.001655     -0.025347\natom           9.668488993         4.832887673        14.364881694 O      -0.243392      0.000000      0.000278     -0.007567     -0.001733\natom           9.674477538         9.765201435        10.883700539 O      -0.239044      0.000000      0.021521     -0.002604     -0.026971\natom           0.045436593         1.442192310         4.437320594 H       0.119710      0.000000     -0.000443      0.000689     -0.005578\natom           4.870619849         3.359643371        11.439214100 H       0.120474      0.000000      0.000354      0.004548      0.001447\natom          -1.507714810         4.848579965         7.962623092 H       0.121814      0.000000      0.017411     -0.000244     -0.013773\natom           6.274666133         0.011485760        15.061633442 H       0.120400      0.000000      0.017450      0.000380      0.011962\natom           4.886338597         1.423960225         6.185947235 H       0.117144      0.000000      0.000233      0.021847     -0.015970\natom           0.032102680         3.374638354        -0.921449723 H       0.119301      0.000000     -0.001328      0.005873      0.003979\natom           6.294290946         4.843158338         2.612777955 H       0.122547      0.000000     -0.011758     -0.000275      0.009212\natom          -1.486236174        -0.043061206        -4.420296045 H       0.118414      0.000000      0.004767      0.001510      0.005612\natom           4.860581620         6.364494300        11.527454897 H       0.124276      0.000000     -0.000699     -0.025134     -0.015070\natom           9.691025876         8.297431672        18.560825584 H       0.119064      0.000000      0.000666     -0.002807     -0.003734\natom           3.425343505         9.758370073        14.980433768 H       0.120952      0.000000     -0.018566      0.000266      0.012555\natom          11.144424266         4.857796163        22.102914526 H       0.117229      0.000000      0.002828     -0.000161      0.001269\natom           9.692463958         6.303535490        13.260655697 H       0.119168      0.000000      0.000179      0.001868     -0.002312\natom           4.906481196         8.234564238         6.155131459 H       0.125091      0.000000     -0.002115      0.017327      0.014659\natom          11.189203234         9.693945504         9.690663048 H       0.123457      0.000000     -0.024905      0.001809      0.020449\natom           3.361888366         4.876052814         2.690360692 H       0.119954      0.000000     -0.004013      0.000251     -0.003560\nenergy          -612.577467\ncharge             0.000000\nend\n"
  },
  {
    "path": "examples/pynnp/symfunc-only/input.data.2",
    "content": "begin\nlattice            15.866107            0.000000            0.000000\nlattice            -0.002748           15.735538            0.000000\nlattice             0.001330           -0.006648            7.617187\natom          14.485083441        16.367565106         8.726065192 H       0.110185      0.000000     -0.009273      0.003171      0.003439\natom          15.150615012        14.412427222         6.484308653 H       0.122758      0.000000      0.011748      0.024537      0.025975\natom           4.418859852         3.612910236         2.186880760 H       0.118755      0.000000      0.032202      0.009635     -0.029215\natom           6.708122235         5.305105853         1.785546235 H       0.099468      0.000000      0.034002      0.043049      0.027982\natom           5.518856640         9.109027792         5.909958294 H       0.114566      0.000000     -0.010895      0.008840      0.008117\natom           3.593510300        11.305682220         5.224796240 H       0.114547      0.000000      0.009643     -0.020520      0.028030\natom           9.130311786        13.163168467         0.192759700 H       0.121056      0.000000      0.006699     -0.009370      0.007559\natom          11.300171776        11.333066252        -0.225304577 H       0.115910      0.000000      0.019554     -0.008807     -0.019218\natom          13.358044662         6.509927680         7.399030948 H       0.109629      0.000000      0.002400      0.003455     -0.001317\natom          11.458812458         4.393475151         8.078850744 H       0.113064      0.000000      0.007977      0.019262     -0.025243\natom           0.799282660         6.622336194         2.950082865 H       0.115910      0.000000     -0.000312     -0.001274     -0.000185\natom           1.411408659         8.520927780         0.784374604 H       0.112250      0.000000      0.002917      0.001678     -0.000995\natom          10.309896311         1.179261381         3.549226440 H       0.123139      0.000000      0.037192      0.029997     -0.003888\natom          12.297227582         3.414343405         4.279689027 H       0.100311      0.000000     -0.002902      0.011923      0.018648\natom           4.264331216        12.325771906         1.381841992 H       0.110007      0.000000     -0.000959      0.019252      0.028178\natom           2.546210436        14.436296362         2.087054048 H       0.097556      0.000000     -0.058628      0.037230     -0.024176\natom           9.462601360         7.242771322         4.810267642 H       0.109554      0.000000      0.011105      0.000481      0.003663\natom           8.641025593         9.272577984         2.708691043 H       0.108641      0.000000      0.009652      0.001935     -0.000029\natom          14.582311778        10.366164818         3.888780125 H       0.100133      0.000000      0.030616     -0.041034     -0.025757\natom          12.392456588        12.151864121         3.446476321 H       0.109288      0.000000      0.010570     -0.004408      0.010173\natom           3.333580258         4.318451104         5.934868673 H       0.102730      0.000000      0.108589      0.035753      0.117863\natom           1.144779535         2.445170520         5.464241643 H       0.125965      0.000000      0.022327      0.024075      0.000305\natom           6.561318803        -0.622194464         4.739246037 H       0.106331      0.000000     -0.082070     -0.037379     -0.061276\natom           7.086116744         1.277328758         6.801270652 H       0.122839      0.000000      0.007224     -0.003916     -0.007392\natom          15.889991440        15.794467636         7.682304786 O      -0.217751      0.000000     -0.006549     -0.029298     -0.035838\natom           5.854266153         4.085498803         0.860386978 O      -0.233984      0.000000     -0.067046     -0.056123      0.004627\natom           4.065832415        10.068362760         6.711485949 O      -0.215261      0.000000      0.002429      0.016184     -0.039381\natom          10.135298775        11.803082900         1.071463801 O      -0.204152      0.000000     -0.026960      0.023093      0.005602\natom          11.908333129         5.649432987         6.613539515 O      -0.216790      0.000000     -0.006785     -0.022360      0.032095\natom           0.033720286         7.935412915         1.880391627 O      -0.219139      0.000000     -0.001721     -0.003952     -0.000084\natom          11.907654717         2.219943422         2.954242153 O      -0.228377      0.000000     -0.036909     -0.042461     -0.017200\natom           3.905878373        13.655332715         2.829334986 O      -0.232383      0.000000      0.060738     -0.064492     -0.002388\natom           8.081199674         7.874790477         3.778512672 O      -0.231720      0.000000     -0.024489     -0.003252      0.000764\natom          13.713834879        11.648027031         4.720985606 O      -0.240425      0.000000     -0.040418      0.051417      0.021912\natom           2.235947519         3.919512753         4.809562774 O      -0.225917      0.000000     -0.130658     -0.059274     -0.120920\natom           7.835091094        -0.054533738         5.682592025 O      -0.218515      0.000000      0.078990      0.042955      0.069569\nenergy          -918.835853\ncharge             0.000000\nend\n"
  },
  {
    "path": "examples/pynnp/symfunc-only/input.nn",
    "content": "###############################################################################\n# HDNNP for water H2O\n###############################################################################\n# Length unit     : Bohr\n# Energy unit     : Ha\n# Reference method: RPBE-D3\n###############################################################################\n\n###############################################################################\n# DATA SET NORMALIZATION\n###############################################################################\n# This section was automatically added by nnp-norm.\nmean_energy  -2.5521343547039809E+01\nconv_energy   2.4265748255366972E+02\nconv_length   5.8038448995319847E+00\n###############################################################################\n\n###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\nnumber_of_elements              2              # Number of elements.\nelements                        H O            # Specification of elements.\n#atom_energy                     H -0.45890771  # Free atom reference energy (H).\n#atom_energy                     O -74.94518524 # Free atom reference energy (O).\ncutoff_type                     2              # Cutoff type.\nscale_symmetry_functions                       # Scale all symmetry functions with min/max values.\n#scale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\ncenter_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              25 25          # Number of nodes in each hidden layer.\nglobal_activation_short         t t l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\nepochs                          25             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   4              # Training parallelization used (0 = Serial, 1 = Multi-stream, 2 = MS with PMO).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\nrandom_seed 2\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nuse_short_forces                               # Use forces for training.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.041          # Fraction of force updates per epoch.\nshort_energy_error_threshold    1.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#repeated_energy_update                         # After force update perform energy update for corresponding structure.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               25             # Write energy comparison.\nwrite_trainforces               25             # Write force comparison.\nwrite_weights_epoch                            # Write weights.\nwrite_neuronstats               5 10           # Write neuron statistics.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\ngradient_type                   0              # Gradient descent type (0 = Fixed step size).\ngradient_eta                    1.0E-4         # Gradient descent parameter eta (fixed step size).\n############################\n# KALMAN FILTER (STANDARD) #\n############################\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# Wide Angular symmetry function (type 9):\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff>\n\n# radial H H\nsymfunction_short H 2 H 0.001 0.0 12.00\nsymfunction_short H 2 H 0.01  0.0 12.00\nsymfunction_short H 2 H 0.03  0.0 12.00\nsymfunction_short H 2 H 0.06  0.0 12.00\nsymfunction_short H 2 H 0.15  1.9 12.00\nsymfunction_short H 2 H 0.30  1.9 12.00\nsymfunction_short H 2 H 0.60  1.9 12.00\nsymfunction_short H 2 H 1.50  1.9 12.00\n\n# radial H O / O H\nsymfunction_short H 2 O 0.001 0.0 12.00\nsymfunction_short H 2 O 0.01  0.0 12.00\nsymfunction_short H 2 O 0.03  0.0 12.00\nsymfunction_short H 2 O 0.06  0.0 12.00\nsymfunction_short H 2 O 0.15  0.9 12.00\nsymfunction_short H 2 O 0.30  0.9 12.00\nsymfunction_short H 2 O 0.60  0.9 12.00\nsymfunction_short H 2 O 1.50  0.9 12.00\n\nsymfunction_short O 2 H 0.001 0.0 12.00\nsymfunction_short O 2 H 0.01  0.0 12.00\nsymfunction_short O 2 H 0.03  0.0 12.00\nsymfunction_short O 2 H 0.06  0.0 12.00\nsymfunction_short O 2 H 0.15  0.9 12.00\nsymfunction_short O 2 H 0.30  0.9 12.00\nsymfunction_short O 2 H 0.60  0.9 12.00\nsymfunction_short O 2 H 1.50  0.9 12.00\n\n# radial O O\nsymfunction_short O 2 O 0.001 0.0 12.00\nsymfunction_short O 2 O 0.01  0.0 12.00\nsymfunction_short O 2 O 0.03  0.0 12.00\nsymfunction_short O 2 O 0.06  0.0 12.00\nsymfunction_short O 2 O 0.15  4.0 12.00\nsymfunction_short O 2 O 0.30  4.0 12.00\nsymfunction_short O 2 O 0.60  4.0 12.00\nsymfunction_short O 2 O 1.50  4.0 12.00\n\n# angular\nsymfunction_short H 3 O H 0.2  1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.07  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.07 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.07 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.03  1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03  1.0 1.0  12.00000\nsymfunction_short O 3 H H 0.03 -1.0 1.0  12.00000\nsymfunction_short H 3 O H 0.03 -1.0 1.0  12.00000\n\nsymfunction_short O 3 H H 0.01  1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01  1.0 4.0  12.00000\nsymfunction_short O 3 H H 0.01 -1.0 4.0  12.00000\nsymfunction_short H 3 O H 0.01 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O H 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O H 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O H 0.001 -1.0 4.0  12.00000\n\nsymfunction_short H 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short H 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short H 3 O O 0.001 -1.0 4.0  12.00000\n\nsymfunction_short O 3 O O 0.03  1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.03 -1.0 1.0   12.00000\nsymfunction_short O 3 O O 0.001  1.0 4.0  12.00000\nsymfunction_short O 3 O O 0.001 -1.0 4.0  12.00000\n"
  },
  {
    "path": "examples/pynnp/symfunc-only/scaling.data",
    "content": "################################################################################\n# Symmetry function scaling data.\n################################################################################\n# Col  Name     Description\n################################################################################\n# 1    e_index  Element index.\n# 2    sf_index Symmetry function index.\n# 3    sf_min   Symmetry function minimum.\n# 4    sf_max   Symmetry function maximum.\n# 5    sf_mean  Symmetry function mean.\n# 6    sf_sigma Symmetry function sigma.\n#########################################################################################################################\n#        1          2                        3                        4                        5                        6\n#  e_index   sf_index                   sf_min                   sf_max                  sf_mean                 sf_sigma\n#########################################################################################################################\n         1          1   1.0882016636170764E+00   9.6166419119419064E+00   2.2691752247542194E+00   6.7883526611658462E-01\n         1          2   7.3274438904180561E-01   5.0028559321574191E+00   1.3272332317543580E+00   3.3936750181780473E-01\n         1          3   7.6010783783215696E-01   7.1427942966219815E+00   1.6470726712825305E+00   5.0771115927383836E-01\n         1          4   5.4842285884800812E-01   3.7661771168267726E+00   1.0163698211361718E+00   2.5362958053787776E-01\n         1          5   4.0080665126604625E-01   4.1469832401668629E+00   9.0925040981537897E-01   2.9758019277508319E-01\n         1          6   3.6209352253798227E-01   2.2678239402766054E+00   6.4931154122889623E-01   1.4835420345383032E-01\n         1          7   1.8919103878435897E-01   2.2292652677252804E+00   4.5693857051003817E-01   1.5976079618578123E-01\n         1          8   2.6704178695764313E-01   1.3208742362468955E+00   4.2395636902644862E-01   8.0492394978461931E-02\n         1          9   2.4513099752055156E-01   9.4751160662053002E-01   3.6244199023263673E-01   5.2993540556109331E-02\n         1         10   2.2248910067848982E-01   2.7596216013647377E+00   5.3891576898130766E-01   2.0137334230483950E-01\n         1         11   1.4743601726548086E-01   5.5599270746969276E-01   2.6773972195910817E-01   2.6188094566404998E-02\n         1         12   9.9110926426029380E-02   1.7265405335201480E+00   2.9553976311554875E-01   1.1619768775752932E-01\n         1         13   6.5093699123904267E-02   3.4521757733971170E-01   1.8521249136783141E-01   1.9741155185936318E-02\n         1         14   3.1653527247865069E-02   9.1293170125596168E-01   1.5025164684953513E-01   5.3480187368038674E-02\n         1         15   2.9202821602466694E-03   2.6453981776124141E-01   7.6525296616004684E-02   1.8780956137549487E-02\n         1         16   3.2145385719803329E-04   2.8696425565429240E-01   4.5792284631233672E-02   2.3263495133568998E-02\n         1         17   2.4693757528509622E-04   1.3848731138266304E-01   1.7693289653297604E-02   9.7460303038080908E-03\n         1         18   5.0992836797990751E-03   5.8319173651547385E-01   2.3851656540978389E-02   3.7790771891778152E-02\n         1         19   3.2282960174310170E-04   2.1613962298381925E-01   1.7072560754702336E-02   1.4026518665786077E-02\n         1         20   4.9647513277769700E-02   1.6851617426880194E+00   1.4541325969622534E-01   1.0954306125703028E-01\n         1         21   3.4073471604482227E-03   3.1637071808861689E-01   1.8422597685566724E-02   2.0125274191649719E-02\n         1         22   1.3121382132811807E-04   1.0258348935693713E-01   6.3684016949344113E-03   6.6071626858835051E-03\n         1         23   3.3813162813665906E-02   9.1618560879938926E-01   8.1266384503339575E-02   5.7918502576695730E-02\n         1         24   4.1708500446352870E-04   1.5785966980407021E-01   4.6646981268568697E-03   9.8630700614506465E-03\n         1         25   7.3528900917695290E-04   5.9225627251013026E-02   3.7042174075139758E-03   3.3118079036492621E-03\n         1         26   8.9828333062972592E-03   1.9426085555380754E-01   2.4093377110646338E-02   1.0980657457661532E-02\n         1         27   2.1228022180417653E-04   8.7777813240869640E-03   2.0550705761547970E-03   5.8802103858137246E-04\n         2          1   1.5142595331454245E+00   1.0005711988559998E+01   2.6544664635087183E+00   6.7806617585688911E-01\n         2          2   4.4366445360926199E-01   4.6195409357987076E+00   9.6587051599896101E-01   3.3688559575009042E-01\n         2          3   1.1907810568758714E+00   7.5323544094345003E+00   2.0327396422723472E+00   5.0607867531004169E-01\n         2          4   2.7576036468694687E-01   3.3862131032504492E+00   6.5929732667024776E-01   2.5004687333979903E-01\n         2          5   8.0580777590695674E-01   4.5356481255168557E+00   1.2986230824577940E+00   2.9449908325462404E-01\n         2          6   1.0517053799863604E-01   1.8909877539194515E+00   3.0673921331641835E-01   1.4198497108573313E-01\n         2          7   5.6949141690859706E-01   2.6154328621607852E+00   8.4791273805289546E-01   1.5714071578589769E-01\n         2          8   2.3251646720171416E-02   9.3641034200657891E-01   1.1140979781150941E-01   6.9796654369842781E-02\n         2          9   5.1354161698115419E-01   1.8545341781448565E+00   7.2488398046527269E-01   9.8011511620611044E-02\n         2         10   1.1057465545812291E-01   2.9121456897811342E+00   4.7474421797982730E-01   2.3441807910092233E-01\n         2         11   3.5269317308496489E-01   1.0714592032613128E+00   5.3547944391821678E-01   4.5179661104166338E-02\n         2         12   3.0424313539726355E-02   2.5277642768509305E+00   3.1652845366685045E-01   2.1026891409654727E-01\n         2         13   1.5980022688828247E-01   6.6348817066386512E-01   3.7042498273566293E-01   3.0753700953611234E-02\n         2         14   2.7781847150922931E-03   2.3030057819082539E+00   1.7737800292869690E-01   1.8600239464755819E-01\n         2         15   9.5641036809349829E-03   3.9085233064570807E-01   1.5305059323200970E-01   2.7862233984302390E-02\n         2         16   3.7500170432292374E-06   2.0367068825281995E+00   5.4144316535640342E-02   1.4305857218443538E-01\n         2         17   2.4726232100491033E-03   3.4335400617385042E-01   1.6684597803376652E-02   2.1902951351570905E-02\n         2         18   1.7405672406959600E-05   5.6319316766205302E-02   9.5478184601751693E-04   3.3588039002222358E-03\n         2         19   5.4785372164647961E-02   3.0182597583971442E+00   2.0392031625072374E-01   2.0088721011517138E-01\n         2         20   1.3795234987637416E-03   4.9878800454061323E-01   1.2788265359933434E-02   3.1829452602194934E-02\n         2         21   6.6852772684814245E-03   2.6739582842775905E-01   3.0851859894574358E-02   1.7089886758420030E-02\n         2         22   1.7021399438214336E-02   1.4167796508898451E+00   7.6274174813506748E-02   9.2852504206357669E-02\n         2         23   1.9759831791959857E-02   4.0756378297923890E-01   4.8843503112397949E-02   2.5474332458885439E-02\n         2         24   5.2768632746659245E-04   2.3324050667069166E-01   7.2057238727819412E-03   1.4495435261027742E-02\n         2         25   1.1144879740881719E-05   3.5285772934088612E-02   4.2545240948261025E-04   2.0471375111485984E-03\n         2         26   1.6013752685265073E-02   8.2245409953473059E-01   5.0845479076508403E-02   5.2802834522172923E-02\n         2         27   3.9898424495541764E-03   7.8557031440100300E-01   3.6926675414383096E-02   5.0474458307624794E-02\n         2         28   4.0523818189746699E-05   9.8448068666705968E-02   1.2119235889230262E-03   5.7945700128174639E-03\n         2         29   6.0374649986214514E-03   9.9251766407842473E-02   1.6156539248049700E-02   5.5245068674135743E-03\n         2         30   2.9595491075765732E-03   1.5478537567691833E-01   1.1641055270110553E-02   8.9415193910804703E-03\n"
  },
  {
    "path": "include/.gitignore",
    "content": ""
  },
  {
    "path": "lib/.gitignore",
    "content": ""
  },
  {
    "path": "src/application/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=../..\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# GENERAL SETTINGS\n###############################################################################\n# Default compiler, may be overridden by master makefile or command line.\nCOMP=gnu\n\n# Default build mode, may be overridden by master makefile or command line.\n# Possible modes are \"static\", \"shared\" and \"test\".\nMODE=static\n\n# Include global (project-wide) settings.\ninclude $(PROJECT_DIR)/src/makefile.$(COMP)\n\n\n###############################################################################\n# PROJECT COMPILER AND FLAGS\n###############################################################################\n# Include directories and linking flags are target specific (see below).\nCC=$(PROJECT_CC)\nMPICC=$(PROJECT_MPICC)\nCFLAGS=$(PROJECT_CFLAGS)\nOPTIONS+=$(PROJECT_OPTIONS)\nDEBUG=$(PROJECT_DEBUG)\nifeq ($(MODE), test)\n\tDEBUG+= $(PROJECT_TEST)\nendif\n\n\n###############################################################################\n# APPLICATION TYPES\n###############################################################################\n# Applications which require only libnnp:\nAPP_CORE=nnp-convert \\\n         nnp-cutoff \\\n         nnp-dist \\\n         nnp-predict \\\n         nnp-prune \\\n         nnp-select \\\n         nnp-symfunc\n\n# Applications which require libnnp and libnnptrain\n# but do not use class Training (only Dataset):\nAPP_DATASET=nnp-atomenv \\\n            nnp-checkf \\\n            nnp-comp2 \\\n            nnp-dataset \\\n            nnp-norm \\\n            nnp-scaling\n\n# Applications which require libnnp and libnnptrain:\nAPP_TRAINING=nnp-checkdw \\\n             nnp-norm2 \\\n             nnp-train\n\n# All applications together.\nAPP=$(APP_CORE) $(APP_DATASET) $(APP_TRAINING)\n\n# Targets for cleaning.\nCLEAN_APP=$(patsubst %, clean-%, $(APP))\n\n\n###############################################################################\n# RULES\n###############################################################################\n.PHONY: all $(CLEAN_APP) list-libnnp list-libnnptrain list-all\n\nall: $(APP_CORE) $(APP_DATASET) $(APP_TRAINING)\n\n# Applications which require only libnnp:\n$(APP_CORE): INCLUDES=-I./ -I$(PROJECT_INCLUDE)/ -I$(PROJECT_EIGEN)\nifeq ($(MODE), shared)\n$(APP_CORE): LDFLAGS=-L$(PROJECT_LIB) -lnnp\nelse\n$(APP_CORE): LDFLAGS=$(PROJECT_LIB)/libnnp.a\nendif\n$(APP_CORE):\n\t$(CC) $(CFLAGS) $(DEBUG) $(INCLUDES) $(OPTIONS) -o $@.o -c $@.cpp\n\t$(CC) $(CFLAGS) $(DEBUG) $(OPTIONS) -o $@ $@.o $(LDFLAGS)\n\tcp $@ $(PROJECT_BIN)/\n\n# Applications which require libnnp and libnnptrain\n# but do not use class Training (only Dataset):\n$(APP_DATASET): INCLUDES=-I./ -I$(PROJECT_INCLUDE)/ -I$(PROJECT_GSL) -I$(PROJECT_EIGEN)\nifeq ($(MODE), shared)\n$(APP_DATASET): LDFLAGS=-L$(PROJECT_LIB) -lnnptrain -lnnp -lgsl $(PROJECT_LDFLAGS_BLAS)\nelse\n$(APP_DATASET): LDFLAGS=$(PROJECT_LIB)/libnnptrain.a $(PROJECT_LIB)/libnnp.a -lgsl $(PROJECT_LDFLAGS_BLAS)\nendif\n$(APP_DATASET):\n\t$(MPICC) $(CFLAGS) $(DEBUG) $(INCLUDES) $(OPTIONS) -o $@.o -c $@.cpp\n\t$(MPICC) $(CFLAGS) $(DEBUG) $(OPTIONS) -o $@ $@.o $(LDFLAGS)\n\tcp $@ $(PROJECT_BIN)/\n\n# Applications which require libnnp and libnnptrain, requires Eigen.\n$(APP_TRAINING): INCLUDES=-I./ -I$(PROJECT_INCLUDE)/ -I$(PROJECT_GSL) -I$(PROJECT_EIGEN)\nifeq ($(MODE), shared)\n$(APP_TRAINING): LDFLAGS=-L$(PROJECT_LIB) -lnnptrain -lnnp -lgsl $(PROJECT_LDFLAGS_BLAS)\nelse\n$(APP_TRAINING): LDFLAGS=$(PROJECT_LIB)/libnnptrain.a $(PROJECT_LIB)/libnnp.a -lgsl $(PROJECT_LDFLAGS_BLAS)\nendif\n$(APP_TRAINING): nnp-train.cpp\n\t$(MPICC) $(CFLAGS) $(DEBUG) $(INCLUDES) $(OPTIONS) -o $@.o -c $@.cpp\n\t$(MPICC) $(CFLAGS) $(DEBUG) $(OPTIONS) -o $@ $@.o $(LDFLAGS)\n\tcp $@ $(PROJECT_BIN)/\n\n# Clean everything.\nclean: $(CLEAN_APP)\n\n# Clean rules for all applications.\n$(CLEAN_APP): EXE=$(patsubst clean-%,%,$@)\n$(CLEAN_APP):\n\t$(RM) $(EXE).gcno $(EXE).gcda $(EXE).o $(EXE)\n\t$(RM) $(PROJECT_BIN)/$(EXE)\n\nlist-libnnp:\n\t@echo $(APP_CORE)\n\nlist-libnnptrain:\n\t@echo $(APP_DATASET) $(APP_TRAINING)\n\nlist-all:\n\t@echo $(APP_CORE) $(APP_DATASET) $(APP_TRAINING)\n"
  },
  {
    "path": "src/application/nnp-atomenv.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Dataset.h\"\n#include \"mpi-extra.h\"\n#include \"utility.h\"\n#include <mpi.h>\n#include <cstdlib>\n#include <iostream>\n#include <fstream>\n#include <string>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    bool   useForces = false;\n    int    numProcs  = 0;\n    int    myRank    = 0;\n    ofstream myLog;\n\n    if (argc < 3)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <nbins> <ncutij> \\n\"\n             << \"       <nbins> ... Number of symmetry function\"\n                \" histogram bins.\\n\"\n             << \"       <ncutij> ... Maximum number of neighbor symmetry \"\n                \"functions written (for each element combination).\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\"\n             << \"       - input.nn (NNP settings)\\n\"\n             << \"       - scaling.data (symmetry function scaling data)\\n\";\n        return 1;\n    }\n\n    size_t numBins = (size_t)atoi(argv[1]);\n\n    MPI_Init(&argc, &argv);\n    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);\n    MPI_Comm_rank(MPI_COMM_WORLD, &myRank);\n\n    Dataset dataset;\n    myLog.open(strpr(\"nnp-atomenv.log.%04d\", myRank).c_str());\n    if (myRank != 0) dataset.log.writeToStdout = false;\n    dataset.log.registerStreamPointer(&myLog);\n    dataset.setupMPI();\n    dataset.initialize();\n    dataset.loadSettingsFile();\n    dataset.setupGeneric();\n    dataset.setupSymmetryFunctionScaling();\n    dataset.setupSymmetryFunctionStatistics(true, false, true, false);\n    dataset.setupRandomNumberGenerator();\n    dataset.distributeStructures(false);\n    if (dataset.useNormalization()) dataset.toNormalizedUnits();\n\n    size_t n = dataset.getNumElements();\n    if ((size_t)argc - 2 != n * n)\n    {\n        throw runtime_error(\"ERROR: Wrong number of neighbor cutoffs.\\n\");\n    }\n    vector<vector<size_t> > neighCutoff(n);\n    size_t count = 0;\n    for (size_t i = 0; i < n; ++i)\n    {\n        neighCutoff.at(i).resize(n, 0);\n        for (size_t j = 0; j < n; ++j)\n        {\n            neighCutoff.at(i).at(j) = atof(argv[count+2]);\n            count++;\n        }\n    }\n    useForces = dataset.settingsKeywordExists(\"use_short_forces\");\n\n    dataset.log << \"\\n\";\n    dataset.log << \"*** CALCULATING SYMMETRY FUNCTIONS ******\"\n                   \"**************************************\\n\";\n    dataset.log << \"\\n\";\n\n    for (vector<Structure>::iterator it = dataset.structures.begin();\n         it != dataset.structures.end(); ++it)\n    {\n        it->calculateNeighborList(dataset.getMaxCutoffRadius());\n#ifdef N2P2_NO_SF_GROUPS\n        dataset.calculateSymmetryFunctions((*it), useForces);\n#else\n        dataset.calculateSymmetryFunctionGroups((*it), useForces);\n#endif\n        // Clear unneccessary memory, don't use these structures after these\n        // operations unless you know what you do!\n        for (vector<Atom>::iterator it2 = it->atoms.begin();\n             it2 != it->atoms.end(); ++it2)\n        {\n            it2->numNeighborsUnique = 0;\n            it2->neighborsUnique.clear();\n            vector<size_t>(it2->neighborsUnique).swap(it2->neighborsUnique);\n\n            it2->dEdG.clear();\n            vector<double>(it2->dEdG).swap(it2->dEdG);\n\n#ifdef N2P2_FULL_SFD_MEMORY\n            it2->dGdxia.clear();\n            vector<double>(it2->dGdxia).swap(it2->dGdxia);\n#endif\n\n            if (!useForces)\n            {\n                it2->dGdr.clear();\n                vector<Vec3D>(it2->dGdr).swap(it2->dGdr);\n            }\n        }\n    }\n    dataset.log << \"*****************************************\"\n                   \"**************************************\\n\";\n\n    dataset.collectSymmetryFunctionStatistics();\n    dataset.writeSymmetryFunctionHistograms(numBins,\n                                            \"sf-scaled.%03zu.%04zu.histo\");\n    dataset.writeNeighborHistogram();\n    dataset.sortNeighborLists();\n    dataset.writeNeighborLists();\n    dataset.writeAtomicEnvironmentFile(neighCutoff, useForces);\n\n    myLog.close();\n\n    MPI_Finalize();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-checkdw.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Training.h\"\n#include \"mpi-extra.h\"\n#include \"utility.h\"\n#include <mpi.h>\n#include <algorithm>\n#include <cmath>\n#include <cstdlib>\n#include <fstream>\n#include <iostream>\n#include <map>\n#include <string>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    int                    warning = 0;\n    int                    numProcs = 0;\n    int                    myRank = 0;\n    size_t                 stage = 0;\n    double                 delta = 0.0;\n    ofstream               myLog;\n    ofstream               outFileSummary;\n    map<string, double>    meanAbsError;\n    map<string, double>    maxAbsError;\n    map<string, string>    outFilesNames;\n    map<string, ofstream*> outFiles;\n\n    if (argc < 2 || argc > 3)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <stage> <<delta>>\\n\"\n             << \"       <stage> ..... Training stage (irrelevant for NNPs \"\n                \"with only one stage).\\n\"\n             << \"       <<delta>> ... (optional) Displacement for central \"\n                \"difference (default: 1.0e-4).\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\"\n             << \"       - input.nn (NNP settings)\\n\"\n             << \"       - scaling.data (symmetry function scaling data)\\n\"\n             << \"       - \\\"weights.%%03d.data\\\" (weights files)\\n\";\n        return 1;\n    }\n\n    MPI_Init(&argc, &argv);\n    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);\n    MPI_Comm_rank(MPI_COMM_WORLD, &myRank);\n\n    stage = (size_t)atoi(argv[1]);\n    if (argc == 3) delta = atof(argv[2]);\n    else delta = 1.0E-4;\n\n    Training training;\n    if (myRank != 0) training.log.writeToStdout = false;\n    myLog.open(strpr(\"nnp-checkdw.log.%04d\", myRank).c_str());\n    training.log.registerStreamPointer(&myLog);\n    training.setupMPI();\n    training.initialize();\n    training.loadSettingsFile();\n    training.setStage(stage);\n    training.setupGeneric();\n    bool normalize = training.useNormalization();\n    training.setupSymmetryFunctionScaling();\n    training.setupSymmetryFunctionStatistics(false, false, true, false);\n    training.setupNeuralNetworkWeights();\n    training.distributeStructures(false);\n    if (normalize) training.toNormalizedUnits();\n    auto pk = training.setupNumericDerivCheck();\n\n    training.log << \"\\n\";\n    training.log << \"*** ANALYTIC/NUMERIC WEIGHT DERIVATIVES C\"\n                    \"HECK *********************************\\n\";\n    training.log << \"\\n\";\n    training.log << strpr(\"Delta for symmetric difference quotient: %11.3E\\n\",\n                         delta);\n\n    string fileName = \"checkdw-summary.out\";\n    training.log << strpr(\"Per-structure summary of analytic/numeric \"\n                         \"weight derivative comparison\\n\"\n                         \"will be written to \\\"%s\\\"\\n\",\n                         fileName.c_str());\n    fileName += strpr(\".%04d\", myRank);\n    outFileSummary.open(fileName.c_str());\n    if (myRank == 0)\n    {\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(strpr(\"Per-structure summary of analytic vs. numeric \"\n                              \"weight derivative comparison (delta = %11.3E).\",\n                              delta));\n        colSize.push_back(10);\n        colName.push_back(\"struct\");\n        colInfo.push_back(\"Structure index.\");\n        colSize.push_back(10);\n        colName.push_back(\"numAtoms\");\n        colInfo.push_back(\"Number of atoms in structure.\");\n        for (auto k : pk)\n        {\n            colSize.push_back(16);\n            colName.push_back(\"MAE_\" + k);\n            colInfo.push_back(\"Mean over all absolute differences between \"\n                              \"analytic and numeric weight derivatives for \"\n                              \"property \\\"\" + k + \"\\\".\");\n            colSize.push_back(16);\n            colName.push_back(\"maxAE_\" + k);\n            colInfo.push_back(\"Maximum over all absolute differences between \"\n                              \"analytic and numeric weight derivatives for \"\n                              \"property \\\"\" + k + \"\\\".\");\n        }\n        appendLinesToFile(outFileSummary,\n                          createFileHeader(title, colSize, colName, colInfo));\n    }\n\n    for (auto k : pk)\n    {\n        string fileName = \"checkdw-weights.\" + k + \".out\";\n        training.log << \"Individual analytic/numeric weight derivatives for \"\n                        \"property \\\"\" + k + \"\\\"\\nwill be written to \\\"\"\n                        + fileName + \"\\\"\\n\";\n        outFilesNames[k] = fileName;\n        fileName += strpr(\".%04d\", myRank);\n        outFiles[k] = new ofstream();\n        outFiles.at(k)->open(fileName.c_str());\n        if (myRank == 0)\n        {\n            // File header.\n            vector<string> title;\n            vector<string> colName;\n            vector<string> colInfo;\n            vector<size_t> colSize;\n            title.push_back(strpr(\"Comparison of analytic and numeric weight \"\n                                  \"derivatives for property \\\"%s\\\" (delta = \"\n                                  \"%11.3E).\", k.c_str(), delta));\n            colSize.push_back(10);\n            colName.push_back(\"struct\");\n            colInfo.push_back(\"Structure index.\");\n            colSize.push_back(10);\n            colName.push_back(\"index\");\n            colInfo.push_back(\"Property index.\");\n            colSize.push_back(10);\n            colName.push_back(\"weight\");\n            colInfo.push_back(\"Weight index.\");\n            //colSize.push_back(10);\n            //colName.push_back(\"atom\");\n            //colInfo.push_back(\"Atom index (starting with 1).\");\n            //colSize.push_back(3);\n            //colName.push_back(\"xyz\");\n            //colInfo.push_back(\"Force component (0 = x, 1 = y, 2 = z).\");\n            colSize.push_back(24);\n            colName.push_back(\"analytic\");\n            colInfo.push_back(\"Analytic weight derivatives.\");\n            colSize.push_back(24);\n            colName.push_back(\"numeric\");\n            colInfo.push_back(\"Numeric weight derivatives.\");\n            appendLinesToFile(*(outFiles.at(k)),\n                              createFileHeader(title,\n                                               colSize,\n                                               colName,\n                                               colInfo));\n        }\n    }\n\n    training.log << \"\\n\";\n    training.log << \"                      |\";\n    for (auto k : pk) training.log << strpr(\" %33s |\", k.c_str());\n    training.log << \"\\n\";\n    training.log << \"                      |\";\n    for (auto k : pk) training.log << \" meanAbsError  maxAbsError verdict |\";\n    training.log << \"\\n\";\n    training.log << \"-----------------------\";\n    for (auto k : pk) training.log << \"------------------------------------\";\n    training.log << \"\\n\";\n\n\n    // Loop over all structures and compute symmetry functions and energies.\n    bool useForces = training.settingsKeywordExists(\"use_short_forces\");\n    for (auto& s : training.structures)\n    {\n        s.calculateNeighborList(training.getMaxCutoffRadius());\n#ifdef N2P2_NO_SF_GROUPS\n        training.calculateSymmetryFunctions(s, useForces);\n#else\n        training.calculateSymmetryFunctionGroups(s, useForces);\n#endif\n        training.log << strpr(\"Configuration %6zu: \", s.index + 1);\n        outFileSummary << strpr(\"%10zu %10zu\", s.index + 1, s.numAtoms);\n        for (auto k : pk)\n        {\n            vector<vector<double>> dPdc;\n            training.dPdc(k, s, dPdc);\n            vector<vector<double>> dPdcN;\n            training.dPdcN(k, s, dPdcN, delta);\n            meanAbsError[k] = 0.0;\n            maxAbsError[k] = 0.0;\n            size_t count = 0;\n            for (size_t i = 0; i < dPdc.size(); ++i)\n            {\n                for (size_t j = 0; j < dPdc.at(i).size(); ++j)\n                {\n                    *(outFiles.at(k)) << strpr(\"%10zu %10zu %10zu \"\n                                               \"%24.16E %24.16E\\n\",\n                                               s.index + 1,\n                                               i + 1,\n                                               j + 1,\n                                               dPdc.at(i).at(j),\n                                               dPdcN.at(i).at(j));\n                    outFiles.at(k)->flush();\n                    double const error = fabs(dPdc.at(i).at(j) -\n                                              dPdcN.at(i).at(j));\n                    meanAbsError.at(k) += error;\n                    maxAbsError.at(k) = max(error, maxAbsError.at(k));\n                    count++;\n                }\n            }\n            meanAbsError.at(k) /= count;\n            string swarn = \"OK\";\n            if (maxAbsError.at(k) > 100 * delta * delta)\n            {\n                swarn = \"WARN\";\n                warning++;\n            }\n            training.log << strpr(\"  %12.3E %12.3E %7s \",\n                                  meanAbsError.at(k),\n                                  maxAbsError.at(k),\n                                  swarn.c_str());\n            outFileSummary << strpr(\" %16.8E %16.8E\",\n                                    meanAbsError.at(k),\n                                    maxAbsError.at(k));\n        }\n        training.log << \"\\n\";\n        outFileSummary << \"\\n\";\n        s.reset();\n    }\n    if (normalize) training.toPhysicalUnits();\n\n    outFileSummary.close();\n    MPI_Barrier(MPI_COMM_WORLD);\n    if (myRank == 0) training.combineFiles(\"checkdw-summary.out\");\n\n    for (auto k : pk)\n    {\n        outFiles.at(k)->close();\n        delete outFiles.at(k);\n        MPI_Barrier(MPI_COMM_WORLD);\n        if (myRank == 0) training.combineFiles(outFilesNames.at(k));\n    }\n\n    MPI_Allreduce(MPI_IN_PLACE, &warning, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);\n    if (warning > 0)\n    {\n        training.log << \"\\n\";\n        training.log << \"IMPORTANT: Some warnings were issued. By default, this happens if the maximum\\n\"\n                        \"           absolute error (\\\"maxAbsError\\\") is higher than 100 * delta².\\n\"\n                        \"           However, this does NOT mean that analytic derivatives are incorrect!\\n\"\n                        \"           Repeat this analysis with a different delta and check whether\\n\"\n                        \"           the error scales with O(delta²). The prefactor for your system\\n\"\n                        \"           could be higher than 10, hence, as long as there is a O(delta²)\\n\"\n                        \"           scaling the analytic derivatives are probably correct.\\n\";\n    }\n\n    training.log << \"*****************************************\"\n                   \"**************************************\\n\";\n\n    myLog.close();\n\n    MPI_Finalize();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-checkf.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Dataset.h\"\n#include \"mpi-extra.h\"\n#include \"utility.h\"\n#include <mpi.h>\n#include <algorithm>\n#include <cmath>\n#include <cstdlib>\n#include <fstream>\n#include <iostream>\n#include <map>\n#include <string>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    int      numProcs = 0;\n    int      myRank = 0;\n    size_t   numOriginals = 0;\n    double   delta = 0.0;\n    ifstream dataFile;\n    ofstream myLog;\n    ofstream outFileForces;\n    ofstream outFileSummary;\n\n    if (argc > 2)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <<delta>>\\n\"\n             << \"       <<delta>> ... (optional) Displacement for central \"\n                \"difference (default: 1.0e-4).\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\"\n             << \"       - input.nn (NNP settings)\\n\"\n             << \"       - scaling.data (symmetry function scaling data)\\n\"\n             << \"       - \\\"weights.%%03d.data\\\" (weights files)\\n\";\n        return 1;\n    }\n\n    MPI_Init(&argc, &argv);\n    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);\n    MPI_Comm_rank(MPI_COMM_WORLD, &myRank);\n\n    if (argc == 2) delta = atof(argv[1]);\n    else delta = 1.0E-4;\n\n    Dataset dataset;\n    if (myRank != 0) dataset.log.writeToStdout = false;\n    myLog.open(strpr(\"nnp-checkf.log.%04d\", myRank).c_str());\n    dataset.log.registerStreamPointer(&myLog);\n    dataset.setupMPI();\n    dataset.initialize();\n    dataset.loadSettingsFile();\n    dataset.setupGeneric();\n    bool normalize = dataset.useNormalization();\n    dataset.setupSymmetryFunctionScaling();\n    dataset.setupSymmetryFunctionStatistics(false, false, false, false);\n    dataset.setupNeuralNetworkWeights();\n\n    dataset.log << \"\\n\";\n    dataset.log << \"*** ANALYTIC/NUMERIC FORCES CHECK *******\"\n                   \"**************************************\\n\";\n    dataset.log << \"\\n\";\n    dataset.log << strpr(\"Delta for symmetric difference quotient: %11.3E\\n\",\n                         delta);\n    if (myRank == 0)\n    {\n        string fileName = \"checkf-forces.out\";\n        dataset.log << strpr(\"Individual analytic/numeric forces will be \"\n                             \"written to \\\"%s\\\"\\n\", fileName.c_str());\n        outFileForces.open(fileName.c_str());\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(strpr(\"Comparison of analytic and numeric forces \"\n                              \"(delta = %11.3E).\", delta));\n        colSize.push_back(10);\n        colName.push_back(\"struct\");\n        colInfo.push_back(\"Structure index (starting with 1).\");\n        colSize.push_back(10);\n        colName.push_back(\"atom\");\n        colInfo.push_back(\"Atom index (starting with 1).\");\n        colSize.push_back(3);\n        colName.push_back(\"xyz\");\n        colInfo.push_back(\"Force component (0 = x, 1 = y, 2 = z).\");\n        colSize.push_back(24);\n        colName.push_back(\"F_analytic\");\n        colInfo.push_back(\"Force computed from analytic derivative of NNP \"\n                          \"energy.\");\n        colSize.push_back(24);\n        colName.push_back(\"F_numeric\");\n        colInfo.push_back(\"Force computed numerically from symmetric \"\n                          \"difference quotient.\");\n        appendLinesToFile(outFileForces,\n                          createFileHeader(title, colSize, colName, colInfo));\n\n        fileName = \"checkf-summary.out\";\n        dataset.log << strpr(\"Per-structure summary of analytic/numeric force \"\n                             \"comparison will be \\n\"\n                             \"written to \\\"%s\\\"\\n\",\n                             fileName.c_str());\n        outFileSummary.open(fileName.c_str());\n        // File header.\n        title.clear();\n        colName.clear();\n        colInfo.clear();\n        colSize.clear();\n        title.push_back(strpr(\"Per-structure summary of analytic vs. numeric \"\n                              \"force comparison (delta = %11.3E).\", delta));\n        colSize.push_back(10);\n        colName.push_back(\"struct\");\n        colInfo.push_back(\"Structure index (starting with 1).\");\n        colSize.push_back(16);\n        colName.push_back(\"numForces\");\n        colInfo.push_back(\"Number of forces in this structure\");\n        colSize.push_back(16);\n        colName.push_back(\"meanAbsError\");\n        colInfo.push_back(\"Mean over all absolute differences between \"\n                          \"analytic and numeric forces in this structure.\");\n        colSize.push_back(16);\n        colName.push_back(\"maxAbsError\");\n        colInfo.push_back(\"Maximum over all absolute differences between \"\n                          \"analytic and numeric forces in this structure.\");\n        appendLinesToFile(outFileSummary,\n                          createFileHeader(title, colSize, colName, colInfo));\n    }\n\n    // First, check how many originals are in \"input.data\".\n    if (myRank == 0)\n    {\n        string fileName = \"input.data\";\n        dataFile.open(fileName.c_str());\n        numOriginals = dataset.getNumStructures(dataFile);\n        dataset.log << strpr(\"Found %zu configurations in data file: %s.\\n\",\n                             numOriginals,\n                             fileName.c_str());\n        dataFile.clear();\n        dataFile.seekg(0);\n    }\n    MPI_Bcast(&numOriginals, 1, MPI_SIZE_T, 0, MPI_COMM_WORLD);\n    dataset.log << strpr(\"Starting loop over %zu configurations...\\n\",\n                          numOriginals);\n\n    if (myRank == 0)\n    {\n        dataset.log << \"\\n\";\n        dataset.log << strpr(\"                      %10s %12s %12s  verdict\\n\",\n                             \"numForces\", \"meanAbsError\", \"maxAbsError\");\n        dataset.log << \"-----------------------------------\"\n                       \"--------------------------------\\n\";\n    }\n\n    bool warning = false;\n    for (size_t is = 0; is < numOriginals; ++is)\n    {\n        // Read original, prepare and distribute modified copies.\n        Structure original;\n        original.setElementMap(dataset.elementMap);\n        if (myRank == 0) original.readFromFile(dataFile);\n        size_t numStructures = dataset.prepareNumericForces(original, delta);\n        if (normalize) dataset.toNormalizedUnits();\n\n        // Prepare arrays to collect central difference values and identifiers.\n        vector<double> allEnergies(numStructures - 1, 0.0);\n        vector<size_t> allAtoms(numStructures - 1, 0);\n        vector<size_t> allXYZ(numStructures - 1, 0);\n        vector<int> allSigns(numStructures - 1, 0);\n\n        // Loop over all structures and compute symmetry functions and energies.\n        for (auto& s : dataset.structures)\n        {\n            bool needForces = false;\n            if (s.comment == \"original\") needForces = true;\n            s.calculateNeighborList(dataset.getMaxCutoffRadius());\n#ifdef N2P2_NO_SF_GROUPS\n            dataset.calculateSymmetryFunctions(s, needForces);\n#else\n            dataset.calculateSymmetryFunctionGroups(s, needForces);\n#endif\n            dataset.calculateAtomicNeuralNetworks(s, needForces);\n            dataset.calculateEnergy(s);\n            if (needForces) dataset.calculateForces(s);\n            s.freeAtoms(true);\n        }\n        if (normalize) dataset.toPhysicalUnits();\n\n        // Loop over all structures collect energies and identifiers.\n        for (auto& s : dataset.structures)\n        {\n            // Skip for original structure.\n            if (s.comment == \"original\") continue;\n            // Store central difference values in arrays (locally on each\n            // processor, communicate later).\n            vector<string> lsplit = split(s.comment);\n            size_t count = atoi(lsplit.at(0).c_str());\n            size_t iAtom = atoi(lsplit.at(1).c_str());\n            size_t ixyz = atoi(lsplit.at(2).c_str());\n            int sign = atoi(lsplit.at(3).c_str());\n            allEnergies.at(count) = s.energy;\n            allAtoms.at(count) = iAtom;\n            allXYZ.at(count) = ixyz;\n            allSigns.at(count) = sign;\n        }\n\n        // Collect data on rank 0.\n        if (myRank == 0)\n        {\n            MPI_Reduce(MPI_IN_PLACE      , allEnergies.data(), numStructures - 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);\n            MPI_Reduce(MPI_IN_PLACE      , allAtoms.data()   , numStructures - 1, MPI_SIZE_T, MPI_SUM, 0, MPI_COMM_WORLD);\n            MPI_Reduce(MPI_IN_PLACE      , allXYZ.data()     , numStructures - 1, MPI_SIZE_T, MPI_SUM, 0, MPI_COMM_WORLD);\n            MPI_Reduce(MPI_IN_PLACE      , allSigns.data()   , numStructures - 1, MPI_INT   , MPI_SUM, 0, MPI_COMM_WORLD);\n        }\n        else\n        {\n            MPI_Reduce(allEnergies.data(), allEnergies.data(), numStructures - 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);\n            MPI_Reduce(allAtoms.data()   , allAtoms.data()   , numStructures - 1, MPI_SIZE_T, MPI_SUM, 0, MPI_COMM_WORLD);\n            MPI_Reduce(allXYZ.data()     , allXYZ.data()     , numStructures - 1, MPI_SIZE_T, MPI_SUM, 0, MPI_COMM_WORLD);\n            MPI_Reduce(allSigns.data()   , allSigns.data()   , numStructures - 1, MPI_INT   , MPI_SUM, 0, MPI_COMM_WORLD);\n        }\n\n        if (myRank == 0)\n        {\n            // Now temporarily store central difference energies in\n            // fRef(+delta) and f(-delta) of original structure.\n            for (size_t i = 0; i < numStructures - 1; ++i)\n            {\n                Atom& a = original.atoms.at(allAtoms.at(i));\n                if (allSigns.at(i) == 1)\n                {\n                    a.fRef[allXYZ.at(i)] = allEnergies.at(i);\n                }\n                else if (allSigns.at(i) == -1)\n                {\n                    a.f[allXYZ.at(i)] = allEnergies.at(i);\n                }\n            }\n\n            double maxAbsError = 0.0;\n            double meanAbsError = 0.0;\n            for (size_t i = 0; i < original.atoms.size(); ++i)\n            {\n                Atom const& ref = dataset.structures.at(0).atoms.at(i);\n                Atom& a = original.atoms.at(i);\n                for (size_t j = 0; j < 3; ++j)\n                {\n                    a.f[j] = - (a.fRef[j] - a.f[j]) / (2.0 * delta);\n                    a.fRef[j] = ref.f[j];\n                    double const error = fabs(a.f[j] - a.fRef[j]);\n                    meanAbsError += error;\n                    maxAbsError = max(error, maxAbsError);\n                    outFileForces << strpr(\"%10zu %10zu %3zu %24.16E \"\n                                           \"%24.16E\\n\",\n                                           is + 1,\n                                           i + 1,\n                                           j,\n                                           a.fRef[j],\n                                           a.f[j]);\n                }\n            }\n            size_t const numForces = 3 * original.atoms.size();\n            meanAbsError /= numForces;\n            dataset.log << strpr(\"Configuration %6zu: %10zu %12.3E %12.3E\",\n                                 is + 1, numForces, meanAbsError, maxAbsError);\n            outFileSummary << strpr(\"%10zu %16zu %16.8E %16.8E\\n\",\n                                    is + 1,\n                                    numForces,\n                                    meanAbsError,\n                                    maxAbsError);\n            if (maxAbsError > 10 * delta * delta)\n            {\n                dataset.log << \"  WARNING!\\n\";\n                warning = true;\n            }\n            else dataset.log << \"  OK.\\n\";\n        }\n    }\n\n    if (myRank == 0)\n    {\n        if (warning)\n        {\n            dataset.log << \"\\n\"; \n            dataset.log << \"IMPORTANT: Some warnings were issued. By default, this happens if the maximum\\n\"\n                           \"           absolute error (\\\"maxAbsError\\\") is higher than 10 * delta².\\n\"\n                           \"           However, this does NOT mean that analytic forces are incorrect!\\n\"\n                           \"           Repeat this analysis with a different delta and check whether\\n\"\n                           \"           the error scales with O(delta²). The prefactor for your system\\n\"\n                           \"           could be higher than 10, hence, as long as there is a O(delta²)\\n\"\n                           \"           scaling the analytic forces are probably correct.\\n\";\n        }\n        outFileForces.close();\n        outFileSummary.close();\n        dataFile.close();\n    }\n\n    dataset.log << \"*****************************************\"\n                   \"**************************************\\n\";\n\n    myLog.close();\n\n    MPI_Finalize();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-comp2.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Dataset.h\"\n#include \"Log.h\"\n#include \"utility.h\"\n#include <algorithm>\n#include <cmath>\n#include <cstddef>\n#include <iostream>\n#include <fstream>\n#include <stdexcept>\n#include <string>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    string   mode;\n    int      numProcs        = 0;\n    int      numProcsNNP     = 0;\n    int      numProcsData    = 0;\n    int      myRank          = 0;\n    int      myRankNNP       = 0;\n    int      myRankData      = 0;\n    int      myNNP           = 0;\n    int      myData          = 0;\n    int      numWorkers      = 0;\n    size_t   thresholdEW     = 0;\n    double   thresholdEnergy = 0.0;\n    double   thresholdForce  = 0.0;\n    string   elements;\n    ofstream myLog;\n\n    if (argc < 2)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <mode> <t_ew> <t_en <t_f> \"\n                \"<elem1 <elem2 ...>>\\n\"\n             << \"       <mode> ... Either compare 2 NNPs (compare) or apply\"\n                \" threshold to existing comparison data set (select).\\n\"\n             << \"       If <mode> is \\\"select\\\":\\n\"\n             << \"       <t_ew> ... Extrapolation warning threshold.\\n\"\n             << \"       <t_en> ... Energy per atom threshold.\\n\"\n             << \"       <t_f> .... Force threshold.\\n\"\n             << \"       <elem1 <elem2 ...>> ... Element strings in data set \"\n                \"(e.g. H O).\\n\"\n             << \"       Execute in directory with the data set file\\n\"\n             << \"       - input.data\\n\"\n             << \"       and 2 subdirectories\\n\"\n             << \"       - nnp-data-1\\n\"\n             << \"       - nnp-data-2\\n\"\n             << \"       each containing these NNP files:\\n\"\n             << \"       - input.nn (NNP settings)\\n\"\n             << \"       - scaling.data (symmetry function scaling data)\\n\"\n             << \"       - \\\"weights.%%03d.data\\\" (weights files)\\n\";\n        return 1;\n    }\n\n    mode = argv[1];\n    if (mode == \"compare\")\n    {\n    }\n    else if (mode == \"select\")\n    {\n        if (argc < 6)\n        {\n            throw runtime_error(\"ERROR: Wrong number of arguments.\\n\");\n        }\n        thresholdEW        = (size_t)atoi(argv[2]);\n        thresholdEnergy    = atof(argv[3]);\n        thresholdForce     = atof(argv[4]);\n        size_t numElements = argc - 5;\n        elements += argv[5];\n        for (size_t i = 6; i < numElements + 5; ++i)\n        {\n            elements += \" \";\n            elements += argv[i];\n        }\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown mode selected.\\n\");\n    }\n\n    MPI_Init(&argc, &argv);\n    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);\n    MPI_Comm_rank(MPI_COMM_WORLD, &myRank);\n\n    if ((mode == \"compare\") && (numProcs % 2 != 0))\n    {\n        throw runtime_error(\"ERROR: Please start with an even number of MPI\"\n                            \" processes.\\n\");\n    }\n    else if ((mode == \"select\") && (numProcs != 1))\n    {\n        throw runtime_error(\"ERROR: Please start with a single MPI \"\n                            \"processes.\\n\");\n    }\n\n    if (mode == \"compare\")\n    {\n        numWorkers = numProcs / 2;\n        MPI_Comm commNNP;\n        myNNP = myRank / numWorkers;\n        MPI_Comm_split(MPI_COMM_WORLD, myNNP, myRank, &commNNP);\n        MPI_Comm_size(commNNP, &numProcsNNP);\n        MPI_Comm_rank(commNNP, &myRankNNP);\n\n        MPI_Comm commData;\n        myData = myRankNNP % numWorkers;\n        MPI_Comm_split(MPI_COMM_WORLD, myData, myRank, &commData);\n        MPI_Comm_size(commData, &numProcsData);\n        MPI_Comm_rank(commData, &myRankData);\n\n        Dataset dataset;\n        if (myRank != 0) dataset.log.writeToStdout = false;\n        myLog.open(strpr(\"nnp-comp2.log.%1d.%04d\",\n                         myNNP + 1,\n                         myRankNNP).c_str());\n        dataset.log.registerStreamPointer(&myLog);\n\n        string dirNNP = strpr(\"nnp-data-%1d\", myNNP + 1); \n\n        dataset.log << \"\\n\";\n        dataset.log << \"*** 2-NNP COMPARISON INITIALIZATION *****\"\n                       \"**************************************\\n\";\n        dataset.log << \"\\n\";\n        dataset.log << strpr(\"Number of workers per NNP: %4d\\n\", numWorkers);\n        dataset.log << strpr(\"NNP  Id                  : %4d\\n\", myNNP);\n        dataset.log << strpr(\"Data Id                  : %4d\\n\", myData);\n        dataset.log << \"My NNP directory         : \" + dirNNP + \"\\n\";\n        dataset.log << \"\\n\";\n        dataset.log << \"Global Communicator:\\n\";\n        dataset.log << strpr(\"- numProcs: %4d\\n\", numProcs);\n        dataset.log << strpr(\"- myRank  : %4d\\n\", myRank);\n        dataset.log << \"\\n\";\n        dataset.log << \"NNP Communicator:\\n\";\n        dataset.log << strpr(\"- numProcs: %4d\\n\", numProcsNNP);\n        dataset.log << strpr(\"- myRank  : %4d\\n\", myRankNNP);\n        dataset.log << \"\\n\";\n        dataset.log << \"Data Communicator:\\n\";\n        dataset.log << strpr(\"- numProcs: %4d\\n\", numProcsData);\n        dataset.log << strpr(\"- myRank  : %4d\\n\", myRankData);\n        dataset.log << \"\\n\";\n        dataset.log << \"Starting NNP initialization...\\n\";\n        dataset.log << \"*****************************************\"\n                       \"**************************************\\n\";\n\n        dataset.setupMPI(&commNNP);\n        dataset.initialize();\n        dataset.loadSettingsFile(dirNNP + \"/input.nn\");\n        dataset.setupGeneric();\n        bool normalize = dataset.useNormalization();\n        bool useForces = dataset.settingsKeywordExists(\"use_short_forces\");\n        dataset.setupSymmetryFunctionScaling(dirNNP + \"/scaling.data\");\n        dataset.setupSymmetryFunctionStatistics(false, true, false, false);\n        dataset.setupNeuralNetworkWeights(dirNNP + \"/weights.%03d.data\");\n        dataset.distributeStructures(false);\n        if (normalize) dataset.toNormalizedUnits();\n\n        dataset.log << \"\\n\";\n        dataset.log << \"*** 2-NNP COMPARISON ********************\"\n                       \"**************************************\\n\";\n        dataset.log << \"\\n\";\n        if (useForces)\n        { \n            dataset.log << \"Calculating energies and forces for dataset.\\n\";\n        }\n        else\n        {\n            dataset.log << \"Calculating energies for dataset.\\n\";\n        }\n\n        for (vector<Structure>::iterator it = dataset.structures.begin();\n             it != dataset.structures.end(); ++it)\n        {\n            it->calculateNeighborList(dataset.getMaxCutoffRadius());\n#ifdef N2P2_NO_SF_GROUPS\n            dataset.calculateSymmetryFunctions((*it), useForces);\n#else\n            dataset.calculateSymmetryFunctionGroups((*it), useForces);\n#endif\n            dataset.calculateAtomicNeuralNetworks((*it), useForces);\n            dataset.calculateEnergy((*it));\n            if (useForces) dataset.calculateForces((*it));\n            if (normalize) dataset.convertToPhysicalUnits((*it));\n            dataset.addEnergyOffset((*it), true);\n            dataset.addEnergyOffset((*it), false);\n            // Store number of extrapolation warnings in unused\n            // \"numElementsPresent\" field.\n            it->clearNeighborList(); \n            it->numElementsPresent = dataset.getNumExtrapolationWarnings();\n            dataset.resetExtrapolationWarnings();\n        }\n\n        // Receive data from other NNP worker (rank 1 in data comm) and\n        // subtract results.\n        if (myRankData == 0)\n        {\n            ofstream myComparisonData;\n            myComparisonData.open(strpr(\"comp.data.%04d\", myRankNNP).c_str());\n            ofstream myDiff;\n            myDiff.open(strpr(\"diff.out.%04d\", myRankNNP).c_str());\n            if (myRankNNP == 0)\n            {\n                // File header.\n                vector<string> title;\n                vector<string> colName;\n                vector<string> colInfo;\n                vector<size_t> colSize;\n                title.push_back(\"2-NNP EW, energy and force comparison.\");\n                colSize.push_back(7);\n                colName.push_back(\"index\");\n                colInfo.push_back(\"Structure index.\");\n                colSize.push_back(10);\n                colName.push_back(\"nAtoms\");\n                colInfo.push_back(\"Number of atoms in structure.\");\n                colSize.push_back(10);\n                colName.push_back(\"EW_NNP1\");\n                colInfo.push_back(\"Extrapolation warnings issued by NNP 1.\");\n                colSize.push_back(10);\n                colName.push_back(\"EW_NNP2\");\n                colInfo.push_back(\"Extrapolation warnings issued by NNP 2.\");\n                colSize.push_back(16);\n                colName.push_back(\"E_NNP1\");\n                colInfo.push_back(\"Energy prediction of NNP 1.\");\n                colSize.push_back(16);\n                colName.push_back(\"E_NNP2\");\n                colInfo.push_back(\"Energy prediction of NNP 2.\");\n                colSize.push_back(16);\n                colName.push_back(\"FDiffMean\");\n                colInfo.push_back(\"Mean absolute force difference.\");\n                colSize.push_back(16);\n                colName.push_back(\"FDiffMax\");\n                colInfo.push_back(\"Maximum absolute force difference.\");\n                appendLinesToFile(myDiff,\n                                  createFileHeader(title,\n                                                   colSize,\n                                                   colName,\n                                                   colInfo));\n            }\n\n            for (vector<Structure>::iterator it = dataset.structures.begin();\n                 it != dataset.structures.end(); ++it)\n            {\n                vector<double> buffer;\n                size_t sizeBuffer = 2;\n                if (useForces) sizeBuffer += 3 * it->numAtoms;\n                buffer.resize(sizeBuffer, 0.0);\n                MPI_Recv(&(buffer.front()), buffer.size(), MPI_DOUBLE, 1, 0, commData, MPI_STATUS_IGNORE);\n                size_t count = 0;\n                double eNNP2 = buffer.at(count++);\n                size_t ewNNP2 = (size_t)buffer.at(count++);\n                double meanForceDiff = 0.0;\n                double maxForceDiff = 0.0;\n                it->energyRef = it->energy - eNNP2;\n                if (useForces)\n                {\n                    for (vector<Atom>::iterator it2 = it->atoms.begin();\n                         it2 != it->atoms.end(); ++it2)\n                    {\n                        for (size_t i = 0; i < 3; ++i)\n                        {\n                            it2->fRef[i] = it2->f[i] - buffer.at(count++);\n                            double const fAbsDiff = fabs(it2->fRef[i]);\n                            meanForceDiff += fAbsDiff;\n                            maxForceDiff = max(maxForceDiff, fAbsDiff);\n                        }\n                    }\n                    meanForceDiff /= 3 * it->numAtoms;\n                }\n                // Add EW sum to comment line.\n                myDiff << strpr(\"%7zu %10zu %10zu %10zu %16.8E %16.8E \"\n                                \"%16.8E %16.8E\\n\",\n                                it->index,\n                                it->numAtoms,\n                                it->numElementsPresent,\n                                ewNNP2,\n                                it->energy,\n                                eNNP2,\n                                meanForceDiff,\n                                maxForceDiff);\n                it->numElementsPresent += ewNNP2;\n                it->comment = strpr(\"EWSUM %zu \", it->numElementsPresent)\n                            + it->comment;\n                it->writeToFile(&myComparisonData);\n            }\n            myComparisonData.close();\n            myDiff.close();\n        }\n        // Send data to other NNP worker (rank 0 in data comm).\n        else if (myRankData == 1)\n        {\n            for (vector<Structure>::const_iterator it = dataset.structures.begin();\n                 it != dataset.structures.end(); ++it)\n            {\n                double ew = (double)it->numElementsPresent;\n                vector<double> buffer;\n                buffer.push_back(it->energy);\n                buffer.push_back(ew);\n                if (useForces)\n                {\n                    for (vector<Atom>::const_iterator it2 = it->atoms.begin();\n                         it2 != it->atoms.end(); ++it2)\n                    {\n                        buffer.push_back(it2->f[0]);\n                        buffer.push_back(it2->f[1]);\n                        buffer.push_back(it2->f[2]);\n                    }\n                }\n                MPI_Send(&(buffer.front()), buffer.size(), MPI_DOUBLE, 0, 0, commData);\n            }\n        }\n        \n        MPI_Barrier(MPI_COMM_WORLD);\n        if (myRank == 0)\n        {\n            dataset.log << \"Difference structures written to \\\"comp.data\\\".\\n\";\n            dataset.combineFiles(\"comp.data\");\n            dataset.log << \"Difference data collected in \\\"diff.out\\\".\\n\";\n            dataset.combineFiles(\"diff.out\");\n        }\n\n        MPI_Comm_free(&commNNP);\n        MPI_Comm_free(&commData);\n\n        dataset.log << \"*****************************************\"\n                       \"**************************************\\n\";\n    }\n    else if (mode == \"select\")\n    {\n        ofstream logFile;\n        logFile.open(\"nnp-comp2.log\");\n        Log log;\n        log.registerStreamPointer(&logFile);\n        log << \"\\n\";\n        log << \"*** 2-NNP COMPARISON SELECTION **********\"\n               \"**************************************\\n\";\n        log << \"\\n\";\n        log << strpr(\"Element string: %s\\n\", elements.c_str());\n        log << strpr(\"Threshold extrapolation warnings    : %d\\n\",\n                     thresholdEW);\n        log << strpr(\"Threshold energy difference per atom: %g\\n\",\n                     thresholdEnergy);\n        log << strpr(\"Threshold force difference          : %g\\n\",\n                     thresholdForce);\n        log << \"*****************************************\"\n               \"**************************************\\n\";\n\n        ofstream selectFile;\n        selectFile.open(\"select.out\");\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Selection results based on 2-NNP comparison.\");\n        colSize.push_back(7);\n        colName.push_back(\"index\");\n        colInfo.push_back(\"Structure index.\");\n        colSize.push_back(5);\n        colName.push_back(\"fAny\");\n        colInfo.push_back(\"Whether structure was selected.\");\n        colSize.push_back(5);\n        colName.push_back(\"fEW\");\n        colInfo.push_back(\"Structure selected due to extrapolation warning.\");\n        colSize.push_back(5);\n        colName.push_back(\"fE\");\n        colInfo.push_back(\"Structure selected due to energy difference.\");\n        colSize.push_back(5);\n        colName.push_back(\"fF\");\n        colInfo.push_back(\"Structure selected due to force difference.\");\n        colSize.push_back(10);\n        colName.push_back(\"nEW\");\n        colInfo.push_back(\"Number of extrapolation warnings (both NNPs \"\n                          \"combined).\");\n        colSize.push_back(10);\n        colName.push_back(\"nAtoms\");\n        colInfo.push_back(\"Number of atoms in structure.\");\n        colSize.push_back(16);\n        colName.push_back(\"Ediff\");\n        colInfo.push_back(\"Energy difference per atom.\");\n        colSize.push_back(10);\n        colName.push_back(\"nForce\");\n        colInfo.push_back(\"Number of forces exceeding threshold.\");\n        colSize.push_back(16);\n        colName.push_back(\"FDiffMean\");\n        colInfo.push_back(\"Mean absolute force difference.\");\n        colSize.push_back(16);\n        colName.push_back(\"FDiffMax\");\n        colInfo.push_back(\"Maximum absolute force difference.\");\n        appendLinesToFile(selectFile,\n                          createFileHeader(title, colSize, colName, colInfo));\n\n        ElementMap elementMap;\n        elementMap.registerElements(elements);\n\n        Structure structure;\n        structure.setElementMap(elementMap);\n\n        ifstream comparisonData;\n        comparisonData.open(\"comp.data\");\n\n        ofstream selectionData;\n        selectionData.open(\"comp-selection.data\");\n\n        size_t countEWHit      = 0;\n        size_t countEnergyHit  = 0;\n        size_t countForceHit   = 0;\n        size_t countStructures = 0;\n        size_t countSelected   = 0;\n        while (comparisonData.peek() != EOF)\n        {\n            bool flagEW          = false;\n            bool flagEnergy      = false;\n            bool flagForce       = false;\n            size_t countForce    = 0;\n            double meanForceDiff = 0.0;\n            double maxForceDiff  = 0.0;\n            structure.readFromFile(comparisonData);\n            structure.index = countStructures++;\n            Structure const& s = structure;\n            size_t countEW = (size_t)atoi(split(s.comment).at(1).c_str());\n            if (thresholdEW > 0 && countEW >= thresholdEW)\n            {\n                flagEW = true;\n                countEWHit++;\n            }\n            if (thresholdEnergy > 0 &&\n                fabs(s.energyRef) / s.numAtoms > thresholdEnergy)\n            {\n                flagEnergy = true;\n                countEnergyHit++;\n            }\n            if (thresholdForce > 0)\n            {\n                for (vector<Atom>::const_iterator it = s.atoms.begin();\n                     it != s.atoms.end(); ++it)\n                {\n                    for (size_t i = 0; i < 3; ++i)\n                    {\n                        double const fAbsDiff = fabs(it->fRef[i]);\n                        maxForceDiff = max(maxForceDiff, fAbsDiff);\n                        meanForceDiff += fAbsDiff;\n                        if (fAbsDiff > thresholdForce)\n                        {\n                            flagForce = true;\n                            countForce++;\n                        }\n                    }\n                } \n                meanForceDiff /= 3 * s.numAtoms;\n                if (flagForce) countForceHit++;\n            }\n            if (flagEW || flagEnergy || flagForce)\n            {\n                s.writeToFile(&selectionData);\n                countSelected++;\n                log << strpr(\"Structure %7zu selected.\\n\", structure.index);\n            }\n            selectFile << strpr(\"%7zu %5d %5d %5d %5d %10zu %10zu %16.8E \"\n                                \"%10zu %16.8E %16.8E\\n\",\n                                structure.index,\n                                (int)(flagEW || flagEnergy || flagForce),\n                                (int)flagEW,\n                                (int)flagEnergy,\n                                (int)flagForce,\n                                countEW,\n                                structure.numAtoms,\n                                structure.energyRef / structure.numAtoms,\n                                countForce,\n                                meanForceDiff,\n                                maxForceDiff);\n            structure.reset();\n        }\n        selectFile.close();\n\n        log << \"*****************************************\"\n               \"**************************************\\n\";\n        log << strpr(\"Total number of structures   : %7zu\\n\", countStructures);\n        log << strpr(\"Number of selected structures: %7zu (%6.2f %)\\n\",\n                     countSelected, countSelected * 100.0 / countStructures);\n        log << strpr(\"EW     threshold exceeded    : %7zu (%6.2f %)\\n\",\n                     countEWHit, countEWHit * 100.0 / countStructures);\n        log << strpr(\"Energy threshold exceeded    : %7zu (%6.2f %)\\n\",\n                     countEnergyHit, countEnergyHit * 100.0 / countStructures);\n        log << strpr(\"Force  threshold exceeded    : %7zu (%6.2f %)\\n\",\n                     countForceHit, countForceHit * 100.0 / countStructures);\n        log << \"Selected structures written to \\\"comp-selection.data\\\".\\n\";\n        log << \"*****************************************\"\n               \"**************************************\\n\";\n    }\n\n    MPI_Finalize();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-convert.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"ElementMap.h\"\n#include \"Log.h\"\n#include \"Structure.h\"\n#include \"utility.h\"\n#include <algorithm>\n#include <cmath>\n#include <cstdlib>\n#include <iostream>\n#include <fstream>\n#include <map>\n#include <string>\n#include <utility>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    if (argc < 3)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <format> <elem1 <elem2 ...>>\\n\"\n             << \"       <format> ... Structure file output format \"\n                \"(xyz/poscar).\\n\"\n             << \"       <elemN> .... Symbol for Nth element.\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\";\n        return 1;\n    }\n\n    ofstream logFile;\n    logFile.open(\"nnp-convert.log\");\n    Log log;\n    log.registerStreamPointer(&logFile);\n\n    log << \"\\n\";\n    log << \"*** NNP-CONVERT *************************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    string format = argv[1];\n    log << strpr(\"Requested file format  : %s\\n\", format.c_str());\n    string outputFileName;\n    string outputFileNamePrefix;\n    if (format == \"xyz\")\n    {\n        outputFileName = \"input.xyz\";\n        log << strpr(\"Output file name       : %s\\n\", outputFileName.c_str());\n    }\n    else if (format == \"poscar\")\n    {\n        outputFileNamePrefix = \"POSCAR\";\n        log << strpr(\"Output file name prefix: %s\\n\",\n                     outputFileNamePrefix.c_str());\n    }\n    else\n    {\n        log << \"ERROR: Unknown output file format.\\n\";\n        return 1;\n    }\n    size_t numElements = argc - 2;\n    log << strpr(\"Number of elements     : %zu\\n\", numElements);\n    string elements;\n    elements += argv[2];\n    for (size_t i = 3; i < numElements + 2; ++i)\n    {\n        elements += \" \";\n        elements += argv[i];\n    }\n    log << strpr(\"Element string         : %s\\n\", elements.c_str());\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    ElementMap elementMap;\n    elementMap.registerElements(elements);\n\n    ifstream inputFile;\n    inputFile.open(\"input.data\");\n    Structure structure;\n    structure.setElementMap(elementMap);\n\n    size_t countStructures = 0;\n    ofstream outputFile;\n    if (format == \"xyz\")\n    {\n        outputFile.open(outputFileName.c_str());\n    }\n\n    while (inputFile.peek() != EOF)\n    {\n        structure.readFromFile(inputFile);\n        if (format == \"xyz\")\n        {\n            structure.writeToFileXyz(&outputFile);\n        }\n        else if (format == \"poscar\")\n        {\n            outputFileName = strpr(\"%s_%d\",\n                                   outputFileNamePrefix.c_str(),\n                                   countStructures + 1);\n            outputFile.open(outputFileName.c_str());\n            structure.writeToFilePoscar(&outputFile, elements);\n            outputFile.close();\n        }\n        countStructures++;\n        log << strpr(\"Configuration %7zu: %7zu atoms\\n\",\n                     countStructures,\n                     structure.numAtoms);\n        structure.reset();\n    }\n\n    if (format == \"xyz\")\n    {\n        outputFile.close();\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n    logFile.close();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-cutoff.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"CutoffFunction.h\"\n#include \"Log.h\"\n#include \"Stopwatch.h\"\n#include \"utility.h\"\n#include <iostream> // std::cout\n#include <fstream>  // std::ofstream\n\nusing namespace std;\nusing namespace nnp;\n\nCutoffFunction fc;\nLog nnplog;\nofstream logFile;\nStopwatch swf;\nStopwatch swdf;\nStopwatch swfdf;\nsize_t p = 100000000;\ndouble d = 0.99999 / p;\ndouble tbf = 0.0;\ndouble tbdf = 0.0;\ndouble tbfdf = 0.0;\ndouble tlf = 0.0;\ndouble tldf = 0.0;\ndouble tlfdf = 0.0;\n\nvoid runTest(bool write)\n{\n    swf.reset();\n    swf.start();\n    for (size_t i = 0; i < p; ++i)\n    {\n        __asm__ __volatile__(\"\");\n    }\n    tlf = swf.stop();\n    if (write) nnplog << strpr(\" %10.2E %6.1f       \", tlf, tlf / tlf);\n\n    swdf.reset();\n    swdf.start();\n    for (size_t i = 0; i < p; ++i)\n    {\n        __asm__ __volatile__(\"\");\n    }\n    tldf = swdf.stop();\n    if (write) nnplog << strpr(\" %10.2E %6.1f       \", tldf, tldf / tldf);\n\n    swfdf.reset();\n    swfdf.start();\n    for (size_t i = 0; i < p; ++i)\n    {\n        __asm__ __volatile__(\"\");\n    }\n    tlfdf = swfdf.stop();\n    if (write) nnplog << strpr(\" %10.2E %6.1f        %10.2E %9.1f\\n\",\n                            tlfdf,\n                            tlfdf / tlfdf,\n                            tlfdf - (tlf + tldf),\n                            100.0 * tlfdf / (tlf + tldf));\n}\n\nvoid runTest(CutoffFunction::CutoffType cutoffType)\n{\n    fc.setCutoffType(cutoffType);\n\n    swf.reset();\n    swf.start();\n    for (size_t i = 0; i < p; ++i)\n    {\n        fc.f(i * d);\n    }\n    double tf = swf.stop();\n    if (cutoffType == CutoffFunction::CT_HARD) tbf = tf;\n    nnplog << strpr(\" %10.2E %6.1f %6.1f\", tf, tf / tlf, tf / tbf);\n\n    swdf.reset();\n    swdf.start();\n    for (size_t i = 0; i < p; ++i)\n    {\n        fc.df(i * d);\n    }\n    double tdf = swdf.stop();\n    if (cutoffType == CutoffFunction::CT_HARD) tbdf = tdf;\n    nnplog << strpr(\" %10.2E %6.1f %6.1f\", tdf, tdf / tldf, tdf / tbdf);\n\n    swfdf.reset();\n    swfdf.start();\n    for (size_t i = 0; i < p; ++i)\n    {\n        double f;\n        double df;\n        fc.fdf(i * d, f, df);\n    }\n    double tfdf = swfdf.stop();\n    if (cutoffType == CutoffFunction::CT_HARD) tbfdf = tfdf;\n\n    nnplog << strpr(\" %10.2E %6.1f %6.1f %10.2E %9.1f\\n\",\n                 tfdf,\n                 tfdf / tlfdf,\n                 tfdf / tbfdf,\n                 tfdf - (tf + tdf),\n                 100.0 * tfdf / (tf + tdf));\n}\n\nint main()\n{\n    logFile.open(\"nnp-cutoff.log\");\n    nnplog.registerStreamPointer(&logFile);\n\n    nnplog << \"-------------------------------------------------------------------------------------------------------------\\n\";\n    nnplog << \"Speed test tool for cutoff functions:\\n\";\n    nnplog << \"-------------------------------------------------------------------------------------------------------------\\n\";\n    nnplog << \"Column f     : Time for calling f   (no derivatives  ).\\n\";\n    nnplog << \"Column df    : Time for calling df  (only derivatives).\\n\";\n    nnplog << \"Column fdf   : Time for calling fdf (f and df at once).\\n\";\n    nnplog << \"Column compL : Time compared to LOOP ONLY.\\n\";\n    nnplog << \"Column compH : Time compared to CT_HARD.\\n\";\n    nnplog << \"Column diff  : Time difference between calling f + df (separately) and fdf.\\n\";\n    nnplog << \"Column ratio : Ratio time(fdf) / (time(f) + time(df)) in %.\\n\";\n    nnplog << \"-------------------------------------------------------------------------------------------------------------\\n\";\n    nnplog << \"CutoffType :       f [s]  compL  compH     df [s]  compL  compH     fdf[s]  compL  compH   diff [s] ratio [%]\\n\";\n    nnplog << \"-------------------------------------------------------------------------------------------------------------\\n\";\n\n    // Initialize...\n    runTest(false);\n\n    nnplog << \"LOOP ONLY  : \";\n    runTest(true);\n\n    fc.setCutoffRadius(1.0);\n\n    nnplog << \"CT_HARD    : \";\n    runTest(CutoffFunction::CT_HARD);\n\n    nnplog << \"CT_COS     : \";\n    fc.setCutoffParameter(0.0);\n    runTest(CutoffFunction::CT_COS);\n\n    nnplog << \"CT_TANHU   : \";\n    runTest(CutoffFunction::CT_TANHU);\n\n    nnplog << \"CT_TANH    : \";\n    runTest(CutoffFunction::CT_TANH);\n\n    nnplog << \"CT_EXP     : \";\n    fc.setCutoffParameter(0.0);\n    runTest(CutoffFunction::CT_EXP);\n\n    nnplog << \"CT_POLY1   : \";\n    fc.setCutoffParameter(0.0);\n    runTest(CutoffFunction::CT_POLY1);\n\n    nnplog << \"CT_POLY2   : \";\n    fc.setCutoffParameter(0.0);\n    runTest(CutoffFunction::CT_POLY2);\n\n    nnplog << \"CT_POLY3   : \";\n    fc.setCutoffParameter(0.0);\n    runTest(CutoffFunction::CT_POLY3);\n\n    nnplog << \"CT_POLY4   : \";\n    fc.setCutoffParameter(0.0);\n    runTest(CutoffFunction::CT_POLY4);\n\n    logFile.close();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-dataset.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Dataset.h\"\n#include \"mpi-extra.h\"\n#include \"utility.h\"\n#include <mpi.h>\n#include <algorithm>\n#include <cmath>\n#include <cstdlib>\n#include <fstream>\n#include <iostream>\n#include <map>\n#include <string>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    bool                shuffle         = false;\n    bool                useForces       = false;\n    bool                normalize       = false;\n    int                 numProcs        = 0;\n    int                 myRank          = 0;\n    size_t              countEnergy     = 0;\n    size_t              countForces     = 0;\n    map<string, double> errorEnergy;\n    map<string, double> errorForces;\n    string              fileName;\n    ofstream            fileEnergy;\n    ofstream            fileForces;\n    ofstream            fileOutputData;\n    ofstream            myLog;\n\n    errorEnergy[\"RMSEpa\"] = 0.0;\n    errorEnergy[\"RMSE\"] = 0.0;\n    errorEnergy[\"MAEpa\"] = 0.0;\n    errorEnergy[\"MAE\"] = 0.0;\n    errorForces[\"RMSE\"] = 0.0;\n    errorForces[\"MAE\"] = 0.0;\n\n    if (argc != 2)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <shuffle>\\n\"\n             << \"       <shuffle> ... Randomly distribute structures to MPI\"\n                \" processes (0/1 = no/yes).\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\"\n             << \"       - input.nn (NNP settings)\\n\"\n             << \"       - scaling.data (symmetry function scaling data)\\n\"\n             << \"       - \\\"weights.%%03d.data\\\" (weights files)\\n\";\n        return 1;\n    }\n\n    shuffle = (bool)atoi(argv[1]);\n\n    MPI_Init(&argc, &argv);\n    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);\n    MPI_Comm_rank(MPI_COMM_WORLD, &myRank);\n\n    Dataset dataset;\n    if (myRank != 0) dataset.log.writeToStdout = false;\n    myLog.open(strpr(\"nnp-dataset.log.%04d\", myRank).c_str());\n    dataset.log.registerStreamPointer(&myLog);\n    dataset.setupMPI();\n    dataset.initialize();\n    dataset.loadSettingsFile();\n    dataset.setupGeneric();\n    normalize = dataset.useNormalization();\n    dataset.setupSymmetryFunctionScaling();\n    dataset.setupSymmetryFunctionStatistics(false, false, true, false);\n    dataset.setupNeuralNetworkWeights();\n    if (shuffle) dataset.setupRandomNumberGenerator();\n    dataset.distributeStructures(shuffle);\n    if (normalize) dataset.toNormalizedUnits();\n\n    dataset.log << \"\\n\";\n    dataset.log << \"*** DATA SET PREDICTION *****************\"\n                   \"**************************************\\n\";\n    dataset.log << \"\\n\";\n\n    useForces = dataset.settingsKeywordExists(\"use_short_forces\");\n    if (useForces)\n    {\n        dataset.log << \"Energies and forces are predicted.\\n\";\n    }\n    else\n    {\n        dataset.log << \"Only energies are predicted.\\n\";\n    }\n\n    // Set up sensitivity vectors.\n    size_t numElements = dataset.getNumElements();\n    vector<size_t> numSymmetryFunctions = dataset.getNumSymmetryFunctions();\n    vector<size_t> count(numElements, 0);\n    vector<vector<double> > sensMean;\n    vector<vector<double> > sensMax;\n    sensMean.resize(numElements);\n    sensMax.resize(numElements);\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        sensMean.at(i).resize(numSymmetryFunctions.at(i), 0.0);\n        sensMax.at(i).resize(numSymmetryFunctions.at(i), 0.0);\n    }\n\n    // Set up error files for energy and forces RMSEs.\n    fileName = strpr(\"energy.comp.%04d\", myRank);\n    fileEnergy.open(fileName.c_str());\n\n    // File header.\n    if (myRank == 0)\n    {\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Energy comparison.\");\n        colSize.push_back(10);\n        colName.push_back(\"index\");\n        colInfo.push_back(\"Structure index.\");\n        colSize.push_back(10);\n        colName.push_back(\"N\");\n        colInfo.push_back(\"Number of atoms in structure.\");\n        colSize.push_back(16);\n        colName.push_back(\"Eref_phys\");\n        colInfo.push_back(\"Reference potential energy (physical units, \"\n                          \"atomic energy offsets added).\");\n        colSize.push_back(16);\n        colName.push_back(\"Ennp_phys\");\n        colInfo.push_back(\"NNP potential energy (physical units, \"\n                          \"atomic energy offsets added).\");\n        if (normalize)\n        {\n            colSize.push_back(16);\n            colName.push_back(\"Eref_int\");\n            colInfo.push_back(\"Reference potential energy (internal units).\");\n            colSize.push_back(16);\n            colName.push_back(\"Ennp_int\");\n            colInfo.push_back(\"NNP potential energy (internal units).\");\n        }\n        appendLinesToFile(fileEnergy,\n                          createFileHeader(title, colSize, colName, colInfo));\n    }\n    if (useForces)\n    {\n        fileName = strpr(\"forces.comp.%04d\", myRank);\n        fileForces.open(fileName.c_str());\n\n        // File header.\n        if (myRank == 0)\n        {\n            vector<string> title;\n            vector<string> colName;\n            vector<string> colInfo;\n            vector<size_t> colSize;\n            title.push_back(\"Force comparison.\");\n            colSize.push_back(10);\n            colName.push_back(\"index_s\");\n            colInfo.push_back(\"Structure index.\");\n            colSize.push_back(10);\n            colName.push_back(\"index_a\");\n            colInfo.push_back(\"Atom index (x, y, z components in consecutive \"\n                              \"lines).\");\n            colSize.push_back(16);\n            colName.push_back(\"Fref_phys\");\n            colInfo.push_back(\"Reference force (physical units).\");\n            colSize.push_back(16);\n            colName.push_back(\"Fnnp_phys\");\n            colInfo.push_back(\"NNP force (physical units).\");\n            if (normalize)\n            {\n                colSize.push_back(16);\n                colName.push_back(\"Fref_int\");\n                colInfo.push_back(\"Reference force (internal units).\");\n                colSize.push_back(16);\n                colName.push_back(\"Fnnp_int\");\n                colInfo.push_back(\"NNP force (internal units).\");\n            }\n            appendLinesToFile(fileForces,\n                              createFileHeader(title,\n                                               colSize,\n                                               colName,\n                                               colInfo));\n        }\n    }\n\n    // Open output.data file.\n    fileName = strpr(\"output.data.%04d\", myRank);\n    fileOutputData.open(fileName.c_str());\n\n    for (vector<Structure>::iterator it = dataset.structures.begin();\n         it != dataset.structures.end(); ++it)\n    {\n        // Set derivatives argument to true in any case to fill dEdG vectors\n        // in atom storage.\n        dataset.evaluateNNP((*it), useForces, true);\n\n        // Loop over atoms, collect sensitivity data and clear memory.\n        for (vector<Atom>::iterator it2 = it->atoms.begin();\n             it2 != it->atoms.end(); ++it2)\n        {\n            // Collect sensitivity data.\n            size_t const& e = it2->element;\n            count.at(e)++;\n            for (size_t i = 0; i < numSymmetryFunctions.at(e); ++i)\n            {\n                double const& s = it2->dEdG.at(i);\n                sensMean.at(e).at(i) += s * s;\n                sensMax.at(e).at(i) = max(sensMax.at(e).at(i), abs(s));\n            }\n            // Clear unnecessary memory (neighbor list and others), energies\n            // and forces are still stored. Don't use these structures after\n            // these operations unless you know what you do!\n            it2->numNeighborsUnique = 0;\n            it2->neighborsUnique.clear();\n            vector<size_t>(it2->neighborsUnique).swap(it2->neighborsUnique);\n\n            it2->numNeighborsPerElement.clear();\n            vector<size_t>(it2->numNeighborsPerElement).swap(\n                                                  it2->numNeighborsPerElement);\n\n            it2->G.clear();\n            vector<double>(it2->G).swap(it2->G);\n\n            it2->dEdG.clear();\n            vector<double>(it2->dEdG).swap(it2->dEdG);\n\n#ifdef N2P2_FULL_SFD_MEMORY\n            it2->dGdxia.clear();\n            vector<double>(it2->dGdxia).swap(it2->dGdxia);\n#endif\n\n            it2->dGdr.clear();\n            vector<Vec3D>(it2->dGdr).swap(it2->dGdr);\n\n            it2->numNeighbors = 0;\n            it2->neighbors.clear();\n            vector<Atom::Neighbor>(it2->neighbors).swap(it2->neighbors);\n\n            it2->hasNeighborList = false;\n            it2->hasSymmetryFunctions = false;\n            it2->hasSymmetryFunctionDerivatives = false;\n        }\n        it->hasNeighborList = false;\n        it->hasSymmetryFunctions = false;\n        it->hasSymmetryFunctionDerivatives = false;\n        it->updateError(\"energy\", errorEnergy, countEnergy);\n        fileEnergy << strpr(\"%10zu %10zu\", it->index, it->numAtoms);\n        if (normalize)\n        {\n            fileEnergy << strpr(\" %16.8E %16.8E %16.8E %16.8E\\n\",\n                                dataset.physicalEnergy(*it, true)\n                                + dataset.getEnergyOffset(*it),\n                                dataset.physicalEnergy(*it, false)\n                                + dataset.getEnergyOffset(*it),\n                                it->energyRef,\n                                it->energy);\n        }\n        else\n        {\n            fileEnergy << strpr(\" %16.8E %16.8E\\n\",\n                                dataset.getEnergyWithOffset(*it, true),\n                                dataset.getEnergyWithOffset(*it, false));\n        }\n        if (useForces)\n        {\n            it->updateError(\"force\", errorForces, countForces);\n            for (vector<Atom>::const_iterator it2 = it->atoms.begin();\n                 it2 != it->atoms.end(); ++it2)\n            {\n                for (size_t i = 0; i < 3; ++i)\n                {\n                    fileForces << strpr(\"%10zu %10zu\",\n                                        it2->indexStructure,\n                                        it2->index);\n                    if (normalize)\n                    {\n                        fileForces << strpr(\n                                       \" %16.8E %16.8E\",\n                                       dataset.physical(\"force\", it2->fRef[i]),\n                                       dataset.physical(\"force\", it2->f[i]));\n                    }\n                    fileForces << strpr(\" %16.8E %16.8E\\n\",\n                                        it2->fRef[i],\n                                        it2->f[i]);\n                }\n            }\n        }\n        if (normalize)\n        {\n            it->toPhysicalUnits(dataset.getMeanEnergy(),\n                                dataset.getConvEnergy(),\n                                dataset.getConvLength(),\n                                dataset.getConvCharge());\n        }\n        dataset.addEnergyOffset(*it, false);\n        it->writeToFile(&fileOutputData, false);\n    }\n\n    fileEnergy.close();\n    if (useForces) fileForces.close();\n    fileOutputData.close();\n    MPI_Barrier(MPI_COMM_WORLD);\n\n    if (myRank == 0)\n    {\n        fileName = \"energy.comp\";\n        dataset.combineFiles(fileName);\n        if (useForces)\n        {\n            fileName = \"forces.comp\";\n            dataset.combineFiles(fileName);\n        }\n        fileName = \"output.data\";\n        dataset.combineFiles(fileName);\n    }\n\n    dataset.collectError(\"energy\", errorEnergy, countEnergy);\n    if (useForces) dataset.collectError(\"force\", errorForces, countForces);\n\n    if (myRank == 0)\n    {\n        if (useForces)\n        {\n            dataset.log << \"Energy and force comparison in files:\\n\";\n            dataset.log << \" - energy.comp\\n\";\n            dataset.log << \" - forces.comp\\n\";\n        }\n        else\n        {\n            dataset.log << \"Energy comparison in file:\\n\";\n            dataset.log << \" - energy.comp\\n\";\n        }\n        dataset.log << \"Predicted data set in \\\"output.data\\\"\\n\";\n    }\n    dataset.log << \"Error metrics for energies and forces:\\n\";\n    dataset.log << \"-----------------------------------------\"\n                   \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n    dataset.log << \"                      physical units                          \";\n    if (normalize)\n    {\n        dataset.log << \" |                    internal units                            \";\n    }\n    dataset.log << \"\\n\";\n    dataset.log << strpr(\"       %13s %13s %13s %13s\",\n                         \"RMSEpa\", \"RMSE\", \"MAEpa\", \"MAE\");\n    if (normalize)\n    {\n        dataset.log << strpr(\" | %13s %13s %13s %13s\",\n                             \"RMSEpa\", \"RMSE\", \"MAEpa\", \"MAE\");\n    }\n    dataset.log << \"\\n\";\n    dataset.log << \"ENERGY\";\n    if (normalize)\n    {\n        dataset.log << strpr(\n                          \" %13.5E %13.5E %13.5E %13.5E |\",\n                          dataset.physical(\"energy\", errorEnergy.at(\"RMSEpa\")),\n                          dataset.physical(\"energy\", errorEnergy.at(\"RMSE\")),\n                          dataset.physical(\"energy\", errorEnergy.at(\"MAEpa\")),\n                          dataset.physical(\"energy\", errorEnergy.at(\"MAE\")));\n    }\n    dataset.log << strpr(\" %13.5E %13.5E %13.5E %13.5E\\n\",\n                         errorEnergy.at(\"RMSEpa\"),\n                         errorEnergy.at(\"RMSE\"),\n                         errorEnergy.at(\"MAEpa\"),\n                         errorEnergy.at(\"MAE\"));\n    if (useForces)\n    {\n        dataset.log << \"FORCES\";\n        if (normalize)\n        {\n            dataset.log << strpr(\n                         \" %13s %13.5E %13s %13.5E |\", \"\",\n                         dataset.physical(\"force\", errorForces.at(\"RMSE\")), \"\",\n                         dataset.physical(\"force\", errorForces.at(\"MAE\")));\n        }\n        dataset.log << strpr(\" %13s %13.5E %13s %13.5E\\n\", \"\",\n                             errorForces.at(\"RMSE\"), \"\",\n                             errorForces.at(\"MAE\"));\n    }\n    dataset.log << \"-----------------------------------------\"\n                   \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n    dataset.log << \"*****************************************\"\n                   \"**************************************\\n\";\n\n    dataset.log << \"\\n\";\n    dataset.log << \"*** SENSITIVITY ANALYSIS ****************\"\n                   \"**************************************\\n\";\n    dataset.log << \"\\n\";\n\n    // Combine sensititvity data from all procs.\n    if (myRank == 0)\n    {\n        dataset.log << \"Writing sensitivity analysis data to files:\\n\";\n        MPI_Reduce(MPI_IN_PLACE, &(count.front()), numElements, MPI_SIZE_T, MPI_SUM, 0, MPI_COMM_WORLD);\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            size_t const& n = numSymmetryFunctions.at(i);\n            double sensMeanSum = 0.0;\n            double sensMaxSum = 0.0;\n            MPI_Reduce(MPI_IN_PLACE, &(sensMean.at(i).front()), n, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);\n            MPI_Reduce(MPI_IN_PLACE, &(sensMax.at(i).front() ), n, MPI_DOUBLE, MPI_MAX, 0, MPI_COMM_WORLD);\n            for (size_t j = 0; j < numSymmetryFunctions.at(i); ++j)\n            {\n                sensMean.at(i).at(j) = sqrt(sensMean.at(i).at(j)\n                                            / count.at(i));\n                sensMeanSum += sensMean.at(i).at(j);\n                sensMaxSum += sensMax.at(i).at(j);\n            }\n            ofstream sensFile;\n            string sensFileName = strpr(\"sensitivity.%03d.out\",\n                                        dataset.elementMap.atomicNumber(i));\n            dataset.log << strpr(\" - %s\\n\", sensFileName.c_str());\n            sensFile.open(sensFileName.c_str());\n\n            // File header.\n            vector<string> title;\n            vector<string> colName;\n            vector<string> colInfo;\n            vector<size_t> colSize;\n            title.push_back(strpr(\"Sensitivity analysis for element %2s.\",\n                                   dataset.elementMap[i].c_str()));\n            colSize.push_back(10);\n            colName.push_back(\"index\");\n            colInfo.push_back(\"Symmetry function index.\");\n            colSize.push_back(16);\n            colName.push_back(\"sens_msa_norm\");\n            colInfo.push_back(\"Mean square average sensitivity (normalized, \"\n                              \"sum = 100%).\");\n            colSize.push_back(16);\n            colName.push_back(\"sens_max_norm\");\n            colInfo.push_back(\"Maximum sensitivity (normalized, sum = 100%).\");\n            colSize.push_back(16);\n            colName.push_back(\"sens_msa_phys\");\n            colInfo.push_back(\"Mean square average sensitivity (physical \"\n                              \"energy units).\");\n            colSize.push_back(16);\n            colName.push_back(\"sens_max_phys\");\n            colInfo.push_back(\"Maximum sensitivity (physical energy units).\");\n            if (normalize)\n            {\n                colSize.push_back(16);\n                colName.push_back(\"sens_msa_int\");\n                colInfo.push_back(\"Mean square average sensitivity (internal \"\n                                  \"units).\");\n                colSize.push_back(16);\n                colName.push_back(\"sens_max_int\");\n                colInfo.push_back(\"Maximum sensitivity (internal units).\");\n            }\n            appendLinesToFile(sensFile,\n                              createFileHeader(title,\n                                               colSize,\n                                               colName,\n                                               colInfo));\n\n            for (size_t j = 0; j < numSymmetryFunctions.at(i); ++j)\n            {\n                sensFile << strpr(\"%10d\", j + 1);\n                sensFile << strpr(\" %16.8E %16.8E\",\n                                  sensMean.at(i).at(j) / sensMeanSum * 100.0,\n                                  sensMax.at(i).at(j) / sensMaxSum * 100.0);\n                if (normalize)\n                {\n                    sensFile << strpr(\" %16.8E %16.8E\",\n                                      dataset.physical(\"energy\",\n                                                       sensMean.at(i).at(j)),\n                                      dataset.physical(\"energy\",\n                                                       sensMax.at(i).at(j)));\n                }\n                sensFile << strpr(\" %16.8E %16.8E\\n\",\n                                  sensMean.at(i).at(j),\n                                  sensMax.at(i).at(j));\n            }\n            sensFile.close();\n        }\n    }\n    else\n    {\n        MPI_Reduce(&(count.front()), &(count.front()), numElements, MPI_SIZE_T, MPI_SUM, 0, MPI_COMM_WORLD);\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            size_t const& n = numSymmetryFunctions.at(i);\n            MPI_Reduce(&(sensMean.at(i).front()), &(sensMean.at(i).front()), n, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);\n            MPI_Reduce(&(sensMax.at(i).front() ), &(sensMax.at(i).front() ), n, MPI_DOUBLE, MPI_MAX, 0, MPI_COMM_WORLD);\n        }\n    }\n\n    dataset.log << \"*****************************************\"\n                   \"**************************************\\n\";\n\n    myLog.close();\n\n    MPI_Finalize();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-dist.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"ElementMap.h\"\n#include \"Log.h\"\n#include \"Structure.h\"\n#include \"utility.h\"\n#include <algorithm>\n#include <cmath>\n#include <cstdlib>\n#include <iostream>\n#include <fstream>\n#include <limits>\n#include <map>\n#include <string>\n#include <utility>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    if (argc < 4)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <rcut> <nbin> <adf> <elem1 \"\n             << \"<elem2 <elem3...>>>\\n\"\n             << \"       <rcut> .... Cutoff radius.\\n\"\n             << \"       <nbin> .... Number of histogram bins.\\n\"\n             << \"       <adf> ..... Calculate angle distribution (0/1).\\n\"\n             << \"       <elemN> ... Symbol for Nth element.\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\";\n        return 1;\n    }\n\n    ofstream logFile;\n    logFile.open(\"nnp-dist.log\");\n    Log log;\n    log.registerStreamPointer(&logFile);\n\n    log << \"\\n\";\n    log << \"*** NNP-DIST ****************************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    size_t numElements = argc - 4;\n    log << strpr(\"Number of elements: %zu\\n\", numElements);\n    string elements;\n    elements += argv[4];\n    for (size_t i = 5; i < numElements + 4; ++i)\n    {\n        elements += \" \";\n        elements += argv[i];\n    }\n    log << strpr(\"Element string    : %s\\n\", elements.c_str());\n    double cutoffRadius = atof(argv[1]);\n    log << strpr(\"Cutoff radius     : %f\\n\", cutoffRadius);\n    size_t numBins = (size_t)atoi(argv[2]);\n    log << strpr(\"Histogram bins    : %zu\\n\", numBins);\n    bool calcAdf = (bool)atoi(argv[3]);\n    log << strpr(\"Calculate ADF     : %d\\n\", calcAdf);\n\n    double minCellLength = numeric_limits<double>::max();\n    double maxCellLength = 0.0;\n    vector<size_t> periodicStructures;\n    vector<vector<double>> cellLengths(3);\n\n    size_t numRdf = numElements * (numElements + 1);\n    numRdf /= 2;\n    log << strpr(\"Number of RDFs    : %zu\\n\", numRdf); \n    size_t numAdf = 0;\n    if (calcAdf)\n    {\n        numAdf = numElements * numElements * (numElements + 1);\n        numAdf /= 2;\n    }\n    log << strpr(\"Number of ADFs    : %zu\\n\", numAdf); \n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    ElementMap elementMap;\n    elementMap.registerElements(elements);\n\n    double dr = cutoffRadius / numBins;\n    map<pair<size_t, size_t>, vector<double>* > rhist;\n    map<pair<size_t, size_t>, vector<double>* > rdf;\n    double da = 180.0 / numBins;\n    vector<map<pair<size_t, size_t>, vector<double>* > > ahist(numElements);\n    vector<map<pair<size_t, size_t>, vector<double>* > > adf(numElements);\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        for (size_t j = i; j < numElements; ++j)\n        {\n            pair<size_t, size_t> e(i, j);\n            rhist[e] = new vector<double>(numBins, 0);\n            rdf  [e] = new vector<double>(numBins, 0.0);\n            if (i != j)\n            {\n                rhist[make_pair(j, i)] = rhist[e];\n                rdf  [make_pair(j, i)] = rdf  [e];\n            }\n        }\n    }\n    if (calcAdf)\n    {\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            for (size_t j = 0; j < numElements; ++j)\n            {\n                for (size_t k = j; k < numElements; ++k)\n                {\n                    pair<size_t, size_t> e(j, k);\n                    ahist.at(i)[e] = new vector<double>(numBins, 0);\n                    adf.at(i)  [e] = new vector<double>(numBins, 0.0);\n                    if (j != k)\n                    {\n                        ahist.at(i)[make_pair(k, j)] = ahist.at(i)[e];\n                        adf.at(i)  [make_pair(k, j)] = adf.at(i)  [e];\n                    }\n                }\n            }\n        }\n    }\n\n    ifstream inputFile;\n    inputFile.open(\"input.data\");\n    Structure structure;\n    structure.setElementMap(elementMap);\n\n    size_t countStructures = 0;\n    size_t countPeriodicStructures = 0;\n    vector<double> numberDensity(numElements, 0.0);\n    while (inputFile.peek() != EOF)\n    {\n        structure.readFromFile(inputFile);\n        structure.calculateNeighborList(cutoffRadius);\n        if (structure.isPeriodic)\n        {\n            periodicStructures.push_back(countStructures);\n            for (size_t i = 0; i < 3; ++i)\n            {\n                cellLengths.at(i).push_back(structure.box[i].norm());\n            }\n        }\n        for (vector<Atom>::const_iterator it = structure.atoms.begin();\n             it != structure.atoms.end(); ++it)\n        {\n            for (size_t j = 0; j < it->numNeighbors; ++j)\n            {\n                size_t const ei = it->element;\n                Atom::Neighbor const& nj = it->neighbors.at(j);\n                size_t const ej = nj.element;\n                double const rij = nj.d;\n                pair<size_t, size_t> e(ei, ej);\n                if (ei == ej)\n                {\n                    rhist[e]->at((size_t)floor(rij / dr)) += 1.0;\n                }\n                else\n                {\n                    rhist[e]->at((size_t)floor(rij / dr)) += 0.5;\n                }\n                if (calcAdf)\n                {\n                    for (size_t k = j + 1; k < it->numNeighbors; ++k)\n                    {\n                        Atom::Neighbor const& nk = it->neighbors.at(k);\n                        size_t const ek = nk.element;\n                        e = make_pair(ej, ek);\n                        double theta = nj.dr * nk.dr / (nj.d * nk.d);\n                        // Use first bin for 0 degree angle and catch problems\n                        // with rounding errors.\n                        if (theta >= 1.0)\n                        {\n                            ahist.at(ei)[e]->at(0) += 1.0;\n                        }\n                        // Use last bin for 180 degree angle and catch problems\n                        // with rounding errors.\n                        else if (theta <= -1.0)\n                        {\n                            ahist.at(ei)[e]->at(numBins - 1) += 1.0;\n                        }\n                        else\n                        {\n                            theta = acos(theta) * 180.0 / M_PI;\n                            ahist.at(ei)[e]\n                                ->at((size_t)floor(theta / da)) += 1.0;\n                        }\n                    }\n                }\n            }\n        }\n        countStructures++;\n        if (structure.isPeriodic) countPeriodicStructures++;\n        double const volume = structure.volume;\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            size_t const nni = structure.numAtomsPerElement.at(i);\n            if (structure.isPeriodic)\n            {\n                numberDensity.at(i) += nni / volume;\n            }\n            for (size_t j = i; j < numElements; ++j)\n            {\n                size_t const nnj = structure.numAtomsPerElement.at(j);\n                if (nni == 0 || nnj == 0) continue;\n                pair<size_t, size_t> e(i, j);\n                for (size_t n = 0; n < numBins; ++n)\n                {\n                    double r = (n + 0.5) * dr;\n                    if (structure.isPeriodic)\n                    {\n                        rhist[e]->at(n) *= volume / (nni * nnj);\n                    }\n                    rdf[e]->at(n) += rhist[e]->at(n)\n                                   / (4.0 * M_PI * r * r * dr);\n                }\n                rhist[e]->clear();\n                rhist[e]->resize(numBins, 0.0);\n            }\n        }\n        if (calcAdf)\n        {\n            for (size_t i = 0; i < numElements; ++i)\n            {\n                for (size_t j = 0; j < numElements; ++j)\n                {\n                    for (size_t k = j; k < numElements; ++k)\n                    {\n                        pair<size_t, size_t> e(j, k);\n                        double countAngles = 0.0;\n                        for (size_t n = 0; n < numBins; ++n)\n                        {\n                            countAngles += ahist.at(i)[e]->at(n);\n                        }\n                        if (countAngles > 0)\n                        {\n                            for (size_t n = 0; n < numBins; ++n)\n                            {\n                                adf.at(i)[e]->at(n) += ahist.at(i)[e]->at(n)\n                                                     / countAngles / da;\n                            }\n                        }\n                        ahist.at(i)[e]->clear();\n                        ahist.at(i)[e]->resize(numBins, 0.0);\n                    }\n                }\n            }\n        }\n        log << strpr(\"Configuration %7zu: %7zu atoms\\n\",\n                     countStructures,\n                     structure.numAtoms);\n        structure.reset();\n    }\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n    log << strpr(\"Number of          structures: %9zu\\n\", countStructures);\n    log << strpr(\"Number of periodic structures: %9zu\\n\",\n                 countPeriodicStructures);\n    bool calcCn = false;\n    if (countStructures == countPeriodicStructures) calcCn = true;\n    if (calcCn)\n    {\n        vector<double>::const_iterator minnd = min_element(\n                                   numberDensity.begin(), numberDensity.end());\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            log << strpr(\"Number density (ratio) of element %2s: %16.8E \"\n                         \"(%.2f)\\n\", elementMap[i].c_str(),\n                         numberDensity.at(i), numberDensity.at(i) / (*minnd));\n        }\n    }\n\n    ofstream outputFile;\n    if (countPeriodicStructures > 0)\n    {\n        outputFile.open(\"cell-lengths.out\");\n\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Unit cell vector lengths for each periodic \"\n                        \"structure.\");\n        colSize.push_back(10);\n        colName.push_back(\"index\");\n        colInfo.push_back(\"Index of periodic structure in data set \"\n                          \"(starting with 1).\");\n        colSize.push_back(16);\n        colName.push_back(\"norm(A)\");\n        colInfo.push_back(\"Norm of 1st unit cell vector.\");\n        colSize.push_back(16);\n        colName.push_back(\"norm(B)\");\n        colInfo.push_back(\"Norm of 2nd unit cell vector.\");\n        colSize.push_back(16);\n        colName.push_back(\"norm(C)\");\n        colInfo.push_back(\"Norm of 3rd unit cell vector.\");\n\n        appendLinesToFile(outputFile,\n                          createFileHeader(title,\n                                           colSize,\n                                           colName,\n                                           colInfo));\n\n        for (size_t i = 0; i < periodicStructures.size(); ++i)\n        {\n            outputFile << strpr(\"%10zu %16.8E %16.8E %16.8E\\n\",\n                                periodicStructures.at(i) + 1,\n                                cellLengths.at(0).at(i),\n                                cellLengths.at(1).at(i),\n                                cellLengths.at(2).at(i));\n            for (size_t j = 0; j < 3; ++j)\n            {\n                minCellLength = min(minCellLength, cellLengths.at(j).at(i));\n                maxCellLength = max(maxCellLength, cellLengths.at(j).at(i));\n            }\n        }\n\n        outputFile.close();\n\n        log << strpr(\"Minimum unit cell vector length     : %16.8E\\n\",\n                     minCellLength);\n        log << strpr(\"Maximum unit cell vector length     : %16.8E\\n\",\n                     maxCellLength);\n    }\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        for (size_t j = i; j < numElements; ++j)\n        {\n            pair<size_t, size_t> e(i, j);\n            string fileName = strpr(\"rdf_%s_%s.out\",\n                                    elementMap[i].c_str(),\n                                    elementMap[j].c_str());\n            log << strpr(\"Writing RDF for element combination (%2s/%2s) \"\n                         \"to file %s.\\n\",\n                         elementMap[i].c_str(),\n                         elementMap[j].c_str(),\n                         fileName.c_str());\n            outputFile.open(fileName.c_str());\n\n            // File header.\n            vector<string> title;\n            vector<string> colName;\n            vector<string> colInfo;\n            vector<size_t> colSize;\n            title.push_back(strpr(\"Radial distribution function for element \"\n                                  \"combination %2s-%2s.\",\n                                   elementMap[i].c_str(),\n                                   elementMap[j].c_str()));\n            colSize.push_back(16);\n            colName.push_back(\"dist_bin_l\");\n            colInfo.push_back(\"Distance, left bin limit.\");\n            colSize.push_back(16);\n            colName.push_back(\"dist_bin_r\");\n            colInfo.push_back(\"Distance, right bin limit.\");\n            colSize.push_back(16);\n            colName.push_back(\"rdf\");\n            colInfo.push_back(\"Radial distribution function, standard \"\n                              \"normalization (-> 1 for r -> inf)\");\n            colSize.push_back(16);\n            colName.push_back(\"rdf_max1\");\n            colInfo.push_back(\"Radial distribution function, maximum \"\n                              \"normalized to 1.\");\n            if (calcCn)\n            {\n                colSize.push_back(16);\n                colName.push_back(\"cn\");\n                colInfo.push_back(\"Coordination number.\");\n            }\n            appendLinesToFile(outputFile,\n                              createFileHeader(title,\n                                               colSize,\n                                               colName,\n                                               colInfo));\n\n            vector<double> cn(rdf[e]->size(), 0.0);\n            double integral = 0.0;\n            double const pre = 4.0 * M_PI * dr * 0.5\n                             / countStructures / countStructures;\n            double maxRdf = *max_element(rdf[e]->begin(), rdf[e]->end());\n            for (size_t n = 0; n < numBins; ++n)\n            {\n                double const low = n * dr;\n                double const center = (n + 0.5) * dr;\n                double const high = (n + 1) * dr;\n                outputFile << strpr(\"%16.8E %16.8E %16.8E %16.8E\",\n                                    low,\n                                    high,\n                                    rdf[e]->at(n) / countStructures,\n                                    rdf[e]->at(n) / maxRdf);\n                if (calcCn)\n                {\n                    if (n > 0)\n                    {\n                        integral += pre * center * center * numberDensity.at(j)\n                                  * (rdf[e]->at(n-1) + rdf[e]->at(n));\n                    }\n                    outputFile << strpr(\" %16.8E\", integral);\n                }\n                outputFile << '\\n';\n            }\n            outputFile.close();\n            delete rdf  [e];\n            delete rhist[e];\n        }\n    }\n    if (calcAdf)\n    {\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            for (size_t j = 0; j < numElements; ++j)\n            {\n                for (size_t k = j; k < numElements; ++k)\n                {\n                    pair<size_t, size_t> e(j, k);\n                    string fileName = strpr(\"adf_%s_%s_%s.out\",\n                                            elementMap[i].c_str(),\n                                            elementMap[j].c_str(),\n                                            elementMap[k].c_str());\n                    log << strpr(\"Writing ADF for element combination \"\n                                 \"(%2s/%2s/%2s) to file %s.\\n\",\n                                 elementMap[i].c_str(),\n                                 elementMap[j].c_str(),\n                                 elementMap[k].c_str(),\n                                 fileName.c_str());\n                    outputFile.open(fileName.c_str());\n\n                    // File header.\n                    vector<string> title;\n                    vector<string> colName;\n                    vector<string> colInfo;\n                    vector<size_t> colSize;\n                    title.push_back(strpr(\"Angular distribution function for \"\n                                          \"element combination %2s-%2s-%2s.\",\n                                          elementMap[i].c_str(),\n                                          elementMap[j].c_str(),\n                                          elementMap[k].c_str()));\n                    colSize.push_back(16);\n                    colName.push_back(\"angle_bin_l\");\n                    colInfo.push_back(\"Angle [degree], left bin limit.\");\n                    colSize.push_back(16);\n                    colName.push_back(\"angle_bin_r\");\n                    colInfo.push_back(\"Angle [degree], right bin limit.\");\n                    colSize.push_back(16);\n                    colName.push_back(\"adf\");\n                    colInfo.push_back(\"Angular distribution function, \"\n                                      \"probability normalization \"\n                                      \"(integral = 1)\");\n                    colSize.push_back(16);\n                    colName.push_back(\"adf_max1\");\n                    colInfo.push_back(\"Angular distribution function, maximum \"\n                                      \"normalized to 1.\");\n                    appendLinesToFile(outputFile,\n                                      createFileHeader(title,\n                                                       colSize,\n                                                       colName,\n                                                       colInfo));\n\n                    double maxAdf = *max_element(adf.at(i)[e]->begin(),\n                                                 adf.at(i)[e]->end());\n                    for (size_t n = 0; n < numBins; ++n)\n                    {\n                        double const low = n * da;\n                        double const high = (n + 1) * da;\n                        outputFile << strpr(\"%16.8E %16.8E %16.8E %16.8E\\n\",\n                                            low,\n                                            high,\n                                            adf.at(i)[e]->at(n)\n                                            / countStructures,\n                                            adf.at(i)[e]->at(n) / maxAdf);\n                    }\n                    outputFile.close();\n                    delete adf.at(i)  [e];\n                    delete ahist.at(i)[e];\n                }\n            }\n        }\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n    logFile.close();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-norm.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Dataset.h\"\n#include \"mpi-extra.h\"\n#include \"utility.h\"\n#include <mpi.h>\n#include <cmath>\n#include <cstdlib>\n#include <iostream>\n#include <fstream>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    int      numProcs    = 0;\n    int      myRank      = 0;\n    ofstream myLog;\n\n    if (argc != 1)\n    {\n        cout << \"USAGE: \" << argv[0] << \"\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\"\n             << \"       - input.nn (NNP settings)\\n\";\n        return 1;\n    }\n\n    MPI_Init(&argc, &argv);\n    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);\n    MPI_Comm_rank(MPI_COMM_WORLD, &myRank);\n\n    Dataset dataset;\n    if (myRank != 0) dataset.log.writeToStdout = false;\n    myLog.open(strpr(\"nnp-norm.log.%04d\", myRank).c_str());\n    dataset.log.registerStreamPointer(&myLog);\n    dataset.setupMPI();\n    dataset.initialize();\n    dataset.loadSettingsFile();\n    dataset.setupElementMap();\n    dataset.setupElements();\n    dataset.distributeStructures(false);\n\n    dataset.log << \"\\n\";\n    dataset.log << \"*** DATA SET NORMALIZATION **************\"\n                   \"**************************************\\n\";\n    dataset.log << \"\\n\";\n\n    if (dataset.settingsKeywordExists(\"mean_energy\") ||\n        dataset.settingsKeywordExists(\"conv_energy\") ||\n        dataset.settingsKeywordExists(\"conv_length\") ||\n        dataset.settingsKeywordExists(\"conv_charge\"))\n    {\n        throw runtime_error(\"ERROR: Normalization keywords found in settings, \"\n                            \"please remove them first.\\n\");\n    }\n\n    ofstream fileEvsV;\n    fileEvsV.open(strpr(\"evsv.dat.%04d\", myRank).c_str());\n\n    // File header.\n    vector<string> title;\n    vector<string> colName;\n    vector<string> colInfo;\n    vector<size_t> colSize;\n    title.push_back(\"Energy vs. volume comparison.\");\n    colSize.push_back(16);\n    colName.push_back(\"V_atom\");\n    colInfo.push_back(\"Volume per atom.\");\n    colSize.push_back(16);\n    colName.push_back(\"Eref_atom\");\n    colInfo.push_back(\"Reference energy per atom.\");\n    colSize.push_back(10);\n    colName.push_back(\"N\");\n    colInfo.push_back(\"Number of atoms.\");\n    colSize.push_back(16);\n    colName.push_back(\"V\");\n    colInfo.push_back(\"Volume of structure.\");\n    colSize.push_back(16);\n    colName.push_back(\"Eref\");\n    colInfo.push_back(\"Reference energy of structure.\");\n    colSize.push_back(16);\n    colName.push_back(\"Eref_offset\");\n    colInfo.push_back(\"Reference energy of structure (including offset).\");\n    appendLinesToFile(fileEvsV,\n                      createFileHeader(title, colSize, colName, colInfo));\n\n    size_t numAtomsTotal = 0;\n    size_t numStructures = 0;\n    double meanEnergyPerAtom = 0.0;\n    double sigmaEnergyPerAtom = 0.0;\n    double meanForce = 0.0;\n    double sigmaForce = 0.0;\n    double maxAbsCharge = 0.0;\n    for (vector<Structure>::const_iterator it = dataset.structures.begin();\n         it != dataset.structures.end(); ++it)\n    {\n        numStructures++;\n        numAtomsTotal += it->numAtoms;\n        meanEnergyPerAtom += it->energyRef / it->numAtoms;\n        fileEvsV << strpr(\"%16.8E %16.8E %10zu %16.8E %16.8E %16.8E\\n\",\n                          it->volume / it->numAtoms,\n                          it->energyRef / it->numAtoms,\n                          it->numAtoms,\n                          it->volume,\n                          it->energyRef,\n                          dataset.getEnergyWithOffset(*it, true));\n        for (vector<Atom>::const_iterator it2 = it->atoms.begin();\n             it2 != it->atoms.end(); ++it2)\n        {\n            meanForce += it2->fRef[0] + it2->fRef[1] + it2->fRef[2];\n            double absChargeRef = abs(it2->chargeRef);\n            if (abs(it2->chargeRef) > maxAbsCharge)\n                maxAbsCharge = absChargeRef;\n        }\n    }\n    fileEvsV.flush();\n    fileEvsV.close();\n    MPI_Barrier(MPI_COMM_WORLD);\n    dataset.log << \"Writing energy/atom vs. volume/atom data \"\n                << \"to \\\"evsv.dat\\\".\\n\";\n    if (myRank == 0) dataset.combineFiles(\"evsv.dat\");\n    MPI_Allreduce(MPI_IN_PLACE, &numStructures    , 1, MPI_SIZE_T, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &numAtomsTotal    , 1, MPI_SIZE_T, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &meanEnergyPerAtom, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &meanForce        , 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &maxAbsCharge     , 1, MPI_DOUBLE, MPI_MAX, MPI_COMM_WORLD);\n    meanEnergyPerAtom /= numStructures;\n    meanForce /= 3 * numAtomsTotal;\n    for (vector<Structure>::const_iterator it = dataset.structures.begin();\n         it != dataset.structures.end(); ++it)\n    {\n        double ediff = it->energyRef / it->numAtoms - meanEnergyPerAtom;\n        sigmaEnergyPerAtom += ediff * ediff;\n        for (vector<Atom>::const_iterator it2 = it->atoms.begin();\n             it2 != it->atoms.end(); ++it2)\n        {\n            double fdiff = it2->fRef[0] - meanForce;\n            sigmaForce += fdiff * fdiff;\n            fdiff = it2->fRef[1] - meanForce;\n            sigmaForce += fdiff * fdiff;\n            fdiff = it2->fRef[2] - meanForce;\n            sigmaForce += fdiff * fdiff;\n        }\n    }\n    MPI_Allreduce(MPI_IN_PLACE, &sigmaEnergyPerAtom, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &sigmaForce        , 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    sigmaEnergyPerAtom = sqrt(sigmaEnergyPerAtom / (numStructures - 1));\n    sigmaForce = sqrt(sigmaForce / (3 * numAtomsTotal - 1));\n    dataset.log << \"\\n\";\n    dataset.log << strpr(\"Total number of structures: %zu\\n\", numStructures);\n    dataset.log << strpr(\"Total number of atoms     : %zu\\n\", numAtomsTotal);\n    dataset.log << strpr(\"Mean/sigma energy per atom: %16.8E +/- %16.8E\\n\",\n                         meanEnergyPerAtom,\n                         sigmaEnergyPerAtom);\n    dataset.log << strpr(\"Mean/sigma force          : %16.8E +/- %16.8E\\n\",\n                         meanForce,\n                         sigmaForce);\n    double convEnergy = 1.0 / sigmaEnergyPerAtom;\n    double convLength = sigmaForce / sigmaEnergyPerAtom;\n    double convCharge = 1.0;\n    if (maxAbsCharge > 0)\n        convCharge = 1.0 / maxAbsCharge;\n    dataset.log << strpr(\"Conversion factor energy  : %24.16E\\n\", convEnergy);\n    dataset.log << strpr(\"Conversion factor length  : %24.16E\\n\", convLength);\n    dataset.log << strpr(\"Conversion factor charge  : %24.16E\\n\", convCharge);\n\n    ofstream fileCfg;\n    fileCfg.open(strpr(\"output.data.%04d\", myRank).c_str());\n    for (vector<Structure>::iterator it = dataset.structures.begin();\n         it != dataset.structures.end(); ++it)\n    {\n        it->energyRef = (it->energyRef - meanEnergyPerAtom * it->numAtoms)\n                      * convEnergy;\n        it->chargeRef *= convCharge;\n        it->box[0] *= convLength;\n        it->box[1] *= convLength;\n        it->box[2] *= convLength;\n        for (vector<Atom>::iterator it2 = it->atoms.begin();\n             it2 != it->atoms.end(); ++it2)\n        {\n            it2->r *= convLength;\n            it2->fRef *= convEnergy / convLength;\n            it2->chargeRef *= convCharge;\n        }\n        it->writeToFile(&fileCfg);\n    }\n    fileCfg.flush();\n    fileCfg.close();\n    MPI_Barrier(MPI_COMM_WORLD);\n    dataset.log << \"\\n\";\n    dataset.log << \"Writing converted data file to \\\"output.data\\\".\\n\";\n    dataset.log << \"WARNING: This data set is provided for debugging \"\n                   \"purposes only and is NOT intended for training.\\n\";\n    if (myRank == 0) dataset.combineFiles(\"output.data\");\n\n    if (myRank == 0)\n    {\n        dataset.log << \"\\n\";\n        dataset.log << \"Writing backup of original settings file to \"\n                       \"\\\"input.nn.bak\\\".\\n\";\n        ofstream fileSettings;\n        fileSettings.open(\"input.nn.bak\");\n        dataset.writeSettingsFile(&fileSettings);\n        fileSettings.close();\n\n        dataset.log << \"\\n\";\n        dataset.log << \"Writing extended settings file to \\\"input.nn\\\".\\n\";\n        dataset.log << \"Use this settings file for normalized training.\\n\";\n        fileSettings.open(\"input.nn\");\n        fileSettings << \"#########################################\"\n                        \"######################################\\n\";\n        fileSettings << \"# DATA SET NORMALIZATION\\n\";\n        fileSettings << \"#########################################\"\n                        \"######################################\\n\";\n        fileSettings << strpr(\"mean_energy %24.16E # nnp-norm\\n\",\n                              meanEnergyPerAtom);\n        fileSettings << strpr(\"conv_energy %24.16E # nnp-norm\\n\",\n                              convEnergy);\n        fileSettings << strpr(\"conv_length %24.16E # nnp-norm\\n\",\n                              convLength);\n        fileSettings << strpr(\"conv_charge %24.16E\\n # nnp-norm\\n\",\n                              convCharge);\n        fileSettings << \"#########################################\"\n                        \"######################################\\n\";\n        fileSettings << \"\\n\";\n        dataset.writeSettingsFile(&fileSettings);\n        fileSettings.close();\n    }\n\n    dataset.log << \"*****************************************\"\n                   \"**************************************\\n\";\n\n    myLog.close();\n\n    MPI_Finalize();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-norm2.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Training.h\"\n#include \"mpi-extra.h\"\n#include \"utility.h\"\n#include <mpi.h>\n#include <cmath>\n#include <cstdlib>\n#include <iostream>\n#include <fstream>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    int      numProcs = 0;\n    int      myRank   = 0;\n    size_t   stage    = 0;\n    ofstream myLog;\n\n    if (argc > 2)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <stage>\\n\"\n             << \"       <stage> ... Training stage (only required if training\"\n                \" is a multi-stage process.\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\"\n             << \"       - input.nn (NNP settings)\\n\"\n             << \"       - scaling.data (symmetry function scaling data)\\n\"\n             << \"       - \\\"weights(e).%%03d.data\\\" (weights files)\\n\";\n        return 1;\n    }\n\n    string suffix = \"\";\n    if (argc > 1)\n    {\n        stage = (size_t)atoi(argv[1]);\n        suffix = strpr(\".stage-%zu\", stage);\n    }\n\n    MPI_Init(&argc, &argv);\n    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);\n    MPI_Comm_rank(MPI_COMM_WORLD, &myRank);\n\n    Training training;\n    if (myRank != 0) training.log.writeToStdout = false;\n    myLog.open((strpr(\"nnp-norm2.log.%04d\", myRank) + suffix).c_str());\n    training.log.registerStreamPointer(&myLog);\n    training.setupMPI();\n    training.initialize();\n    training.loadSettingsFile();\n    training.setStage(stage);\n    training.setupGeneric();\n    training.setupSymmetryFunctionScaling();\n    training.setupSymmetryFunctionStatistics(false, false, false, false);\n\n    auto nnpType = training.getNnpType();\n    if ( (nnpType == Training::NNPType::HDNNP_4G ||\n          nnpType == Training::NNPType::HDNNP_Q) && stage == 1)\n    {\n        throw runtime_error(\"ERROR: Normalization of charges not yet \"\n                            \"implemented\\n.\");\n    }\n\n    if (training.settingsKeywordExists(\"mean_energy\") ||\n        training.settingsKeywordExists(\"conv_energy\") ||\n        training.settingsKeywordExists(\"conv_length\"))\n    {\n        throw runtime_error(\"ERROR: Normalization keywords found in settings, \"\n                            \"please remove them first.\\n\");\n    }\n\n    if (!training.settingsKeywordExists(\"use_short_forces\"))\n    {\n        throw runtime_error(\"ERROR: Normalization is only possible if forces \"\n                            \"are used (keyword \\\"use_short_forces\\\").\\n\");\n    }\n\n    // Need RNG for initial random weights.\n    training.setupRandomNumberGenerator();\n\n    // Distribute structures to MPI processes.\n    training.distributeStructures(false);\n\n    // Initialize weights and biases for neural networks.\n    training.initializeWeights();\n\n    training.writeWeights(\"short\", \"weights.%03zu.norm\");\n    if ( (nnpType == Training::NNPType::HDNNP_4G ||\n          nnpType == Training::NNPType::HDNNP_Q) && stage == 2)\n    {\n        training.writeWeights(\"charge\", \"weightse.%03zu.norm\");\n    }\n\n    training.log << \"\\n\";\n    training.log << \"*** DATA SET NORMALIZATION **************\"\n                    \"**************************************\\n\";\n    training.log << \"\\n\";\n\n    ofstream fileEvsV;\n    fileEvsV.open(strpr(\"evsv.dat.%04d\", myRank).c_str());\n    if (myRank == 0)\n    {\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Energy vs. volume comparison.\");\n        colSize.push_back(16);\n        colName.push_back(\"V_atom\");\n        colInfo.push_back(\"Volume per atom.\");\n        colSize.push_back(16);\n        colName.push_back(\"Eref_atom\");\n        colInfo.push_back(\"Reference energy per atom.\");\n        colSize.push_back(10);\n        colName.push_back(\"N\");\n        colInfo.push_back(\"Number of atoms.\");\n        colSize.push_back(16);\n        colName.push_back(\"V\");\n        colInfo.push_back(\"Volume of structure.\");\n        colSize.push_back(16);\n        colName.push_back(\"Eref\");\n        colInfo.push_back(\"Reference energy of structure.\");\n        colSize.push_back(16);\n        colName.push_back(\"Eref_offset\");\n        colInfo.push_back(\"Reference energy of structure (including offset).\");\n        appendLinesToFile(fileEvsV,\n                          createFileHeader(title, colSize, colName, colInfo));\n    }\n\n    size_t numAtomsTotal         = 0;\n    size_t numStructures         = 0;\n    double meanEnergyPerAtomRef  = 0.0;\n    double meanEnergyPerAtomNnp  = 0.0;\n    double sigmaEnergyPerAtomRef = 0.0;\n    double sigmaEnergyPerAtomNnp = 0.0;\n    double meanForceRef          = 0.0;\n    double meanForceNnp          = 0.0;\n    double sigmaForceRef         = 0.0;\n    double sigmaForceNnp         = 0.0;\n    training.log << \"Computing initial prediction for all structures...\\n\";\n    for (auto& s : training.structures)\n    {\n        // File output for evsv.dat.\n        fileEvsV << strpr(\"%16.8E %16.8E %10zu %16.8E %16.8E %16.8E\\n\",\n                          s.volume / s.numAtoms,\n                          s.energyRef / s.numAtoms,\n                          s.numAtoms,\n                          s.volume,\n                          s.energyRef,\n                          training.getEnergyWithOffset(s, true));\n        s.calculateNeighborList(training.getMaxCutoffRadius());\n#ifdef N2P2_NO_SF_GROUPS\n        training.calculateSymmetryFunctions(s, true);\n#else\n        training.calculateSymmetryFunctionGroups(s, true);\n#endif\n        training.calculateAtomicNeuralNetworks(s, true);\n        training.calculateEnergy(s);\n        training.calculateForces(s);\n        s.clearNeighborList();\n\n        numStructures++;\n        numAtomsTotal += s.numAtoms;\n        meanEnergyPerAtomRef += s.energyRef / s.numAtoms;\n        meanEnergyPerAtomNnp += s.energy    / s.numAtoms;\n        for (auto& a : s.atoms)\n        {\n            meanForceRef += a.fRef[0] + a.fRef[1] + a.fRef[2];\n            meanForceNnp += a.f   [0] + a.f   [1] + a.f   [2];\n        }\n    }\n\n    fileEvsV.flush();\n    fileEvsV.close();\n    MPI_Barrier(MPI_COMM_WORLD);\n    training.log << \"Writing energy/atom vs. volume/atom data \"\n                 << \"to \\\"evsv.dat\\\".\\n\";\n    if (myRank == 0) training.combineFiles(\"evsv.dat\");\n    MPI_Allreduce(MPI_IN_PLACE, &numStructures       , 1, MPI_SIZE_T, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &numAtomsTotal       , 1, MPI_SIZE_T, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &meanEnergyPerAtomRef, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &meanEnergyPerAtomNnp, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &meanForceRef        , 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &meanForceNnp        , 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    meanEnergyPerAtomRef /= numStructures;\n    meanEnergyPerAtomNnp /= numStructures;\n    meanForceRef /= 3 * numAtomsTotal;\n    meanForceNnp /= 3 * numAtomsTotal;\n    for (auto const& s : training.structures)\n    {\n        double ediffRef = s.energyRef / s.numAtoms - meanEnergyPerAtomRef;\n        double ediffNnp = s.energy    / s.numAtoms - meanEnergyPerAtomNnp;\n        sigmaEnergyPerAtomRef += ediffRef * ediffRef;\n        sigmaEnergyPerAtomNnp += ediffNnp * ediffNnp;\n        for (auto const& a : s.atoms)\n        {\n            double fdiffRef = a.fRef[0] - meanForceRef;\n            double fdiffNnp = a.f   [0] - meanForceNnp;\n            sigmaForceRef += fdiffRef * fdiffRef;\n            sigmaForceNnp += fdiffNnp * fdiffNnp;\n            fdiffRef = a.fRef[1] - meanForceRef;\n            fdiffNnp = a.f   [1] - meanForceNnp;\n            sigmaForceRef += fdiffRef * fdiffRef;\n            sigmaForceNnp += fdiffNnp * fdiffNnp;\n            fdiffRef = a.fRef[2] - meanForceRef;\n            fdiffNnp = a.f   [2] - meanForceNnp;\n            sigmaForceRef += fdiffRef * fdiffRef;\n            sigmaForceNnp += fdiffNnp * fdiffNnp;\n        }\n    }\n    MPI_Allreduce(MPI_IN_PLACE, &sigmaEnergyPerAtomRef, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &sigmaEnergyPerAtomNnp, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &sigmaForceRef        , 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &sigmaForceNnp        , 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    sigmaEnergyPerAtomRef = sqrt(sigmaEnergyPerAtomRef / (numStructures - 1));\n    sigmaEnergyPerAtomNnp = sqrt(sigmaEnergyPerAtomNnp / (numStructures - 1));\n    sigmaForceRef = sqrt(sigmaForceRef / (3 * numAtomsTotal - 1));\n    sigmaForceNnp = sqrt(sigmaForceNnp / (3 * numAtomsTotal - 1));\n    training.log << \"\\n\";\n    training.log << strpr(\"Total number of structures : %zu\\n\", numStructures);\n    training.log << strpr(\"Total number of atoms      : %zu\\n\", numAtomsTotal);\n    training.log << \"----------------------------------\\n\";\n    training.log << \"Reference data statistics:\\n\";\n    training.log << \"----------------------------------\\n\";\n    training.log << strpr(\"Mean/sigma energy per atom : %16.8E +/- %16.8E\\n\",\n                         meanEnergyPerAtomRef,\n                         sigmaEnergyPerAtomRef);\n    training.log << strpr(\"Mean/sigma force           : %16.8E +/- %16.8E\\n\",\n                         meanForceRef,\n                         sigmaForceRef);\n    training.log << \"----------------------------------\\n\";\n    training.log << \"Initial NNP prediction statistics:\\n\";\n    training.log << \"----------------------------------\\n\";\n    training.log << strpr(\"Mean/sigma energy per atom : %16.8E +/- %16.8E\\n\",\n                         meanEnergyPerAtomNnp,\n                         sigmaEnergyPerAtomNnp);\n    training.log << strpr(\"Mean/sigma force           : %16.8E +/- %16.8E\\n\",\n                         meanForceNnp,\n                         sigmaForceNnp);\n    training.log << \"----------------------------------\\n\";\n    double convEnergy = sigmaForceNnp / sigmaForceRef;\n    double convLength = sigmaForceNnp;\n    training.log << strpr(\"Conversion factor energy   : %24.16E\\n\", convEnergy);\n    training.log << strpr(\"Conversion factor length   : %24.16E\\n\", convLength);\n\n    //ofstream fileCfg;\n    //fileCfg.open(strpr(\"output.data.%04d\", myRank).c_str());\n    //for (vector<Structure>::iterator it = training.structures.begin();\n    //     it != training.structures.end(); ++it)\n    //{\n    //    it->energyRef = (it->energyRef - meanEnergyPerAtom * it->numAtoms)\n    //                  * convEnergy;\n    //    it->box[0] *= convLength;\n    //    it->box[1] *= convLength;\n    //    it->box[2] *= convLength;\n    //    for (vector<Atom>::iterator it2 = it->atoms.begin();\n    //         it2 != it->atoms.end(); ++it2)\n    //    {\n    //        it2->r *= convLength;\n    //        it2->fRef *= convEnergy / convLength;\n    //    }\n    //    it->writeToFile(&fileCfg);\n    //}\n    //fileCfg.flush();\n    //fileCfg.close();\n    //MPI_Barrier(MPI_COMM_WORLD);\n    //training.log << \"\\n\";\n    //training.log << \"Writing converted data file to \\\"output.data\\\".\\n\";\n    //training.log << \"WARNING: This data set is provided for debugging \"\n    //               \"purposes only and is NOT intended for training.\\n\";\n    //if (myRank == 0) training.combineFiles(\"output.data\");\n\n    if (myRank == 0)\n    {\n        training.log << \"\\n\";\n        training.log << \"Writing backup of original settings file to \"\n                       \"\\\"input.nn.bak\\\".\\n\";\n        ofstream fileSettings;\n        fileSettings.open(\"input.nn.bak\");\n        training.writeSettingsFile(&fileSettings);\n        fileSettings.close();\n\n        training.log << \"\\n\";\n        training.log << \"Writing extended settings file to \\\"input.nn\\\".\\n\";\n        training.log << \"Use this settings file for normalized training.\\n\";\n        fileSettings.open(\"input.nn\");\n        fileSettings << \"#########################################\"\n                        \"######################################\\n\";\n        fileSettings << \"# DATA SET NORMALIZATION\\n\";\n        fileSettings << \"#########################################\"\n                        \"######################################\\n\";\n        fileSettings << strpr(\"mean_energy %24.16E # nnp-norm2\\n\",\n                              meanEnergyPerAtomRef);\n        fileSettings << strpr(\"conv_energy %24.16E # nnp-norm2\\n\", convEnergy);\n        fileSettings << strpr(\"conv_length %24.16E # nnp-norm2\\n\", convLength);\n        fileSettings << \"#########################################\"\n                        \"######################################\\n\";\n        fileSettings << \"\\n\";\n        training.writeSettingsFile(&fileSettings);\n        fileSettings.close();\n    }\n\n    training.log << \"*****************************************\"\n                    \"**************************************\\n\";\n\n    myLog.close();\n\n    MPI_Finalize();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-predict.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Atom.h\"\n#include \"Prediction.h\"\n#include \"Structure.h\"\n#include \"utility.h\"\n#include <cstdlib>\n#include <iostream>\n#include <fstream>\n#include <string>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    bool structureInfo = false;\n\n    if (argc != 2)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <info>\\n\"\n             << \"       <info> ... Write structure information for debugging \"\n                \"to \\\"structure.out (0/1)\\\".\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\"\n             << \"       - input.nn (NNP settings)\\n\"\n             << \"       - scaling.data (symmetry function scaling data)\\n\"\n             << \"       - \\\"weights.%%03d.data\\\" (weights files)\\n\";\n        return 1;\n    }\n\n    structureInfo = (bool)atoi(argv[1]);\n\n    ofstream logFile;\n    logFile.open(\"nnp-predict.log\");\n    Prediction prediction;\n    prediction.log.registerStreamPointer(&logFile);\n    prediction.setup();\n    prediction.log << \"\\n\";\n    prediction.log << \"*** PREDICTION **************************\"\n                      \"**************************************\\n\";\n    prediction.log << \"\\n\";\n    prediction.log << \"Reading structure file...\\n\";\n    prediction.readStructureFromFile(\"input.data\");\n    Structure& s = prediction.structure;\n    prediction.log << strpr(\"Structure contains %d atoms (%d elements).\\n\",\n                            s.numAtoms, s.numElements);\n    prediction.log << \"Calculating NNP prediction...\\n\";\n    prediction.predict();\n    prediction.log << \"\\n\";\n    prediction.logEwaldCutoffs();\n    prediction.log << \"-----------------------------------------\"\n                      \"--------------------------------------\\n\";\n    prediction.log << strpr(\"NNP         total energy: %16.8E\\n\",\n                            prediction.structure.energy);\n    if (prediction.getNnpType() == Mode::NNPType::HDNNP_4G)\n    {\n        prediction.log << strpr(\"NNP electrostatic energy: %16.8E\\n\",\n                                prediction.structure.energyElec);\n        prediction.log << \"\\n\";\n        prediction.log << \"NNP charges:\\n\";\n        for (auto const& a : s.atoms)\n        {\n            prediction.log << strpr(\"%10zu %2s %16.8E\\n\",\n                                    a.index + 1,\n                                    prediction.elementMap[a.element].c_str(),\n                                    a.charge);\n        }\n        prediction.log << strpr(\"NNP total charge: %16.8E (ref: %16.8E)\\n\",\n                          s.charge, s.chargeRef);\n    }\n    prediction.log << \"\\n\";\n    prediction.log << \"NNP forces:\\n\";\n    for (vector<Atom>::const_iterator it = s.atoms.begin();\n         it != s.atoms.end(); ++it)\n    {\n        prediction.log << strpr(\"%10zu %2s %16.8E %16.8E %16.8E\\n\",\n                                it->index + 1,\n                                prediction.elementMap[it->element].c_str(),\n                                it->element,\n                                it->f[0],\n                                it->f[1],\n                                it->f[2]);\n    }\n    prediction.log << \"-----------------------------------------\"\n                      \"--------------------------------------\\n\";\n    prediction.log << \"Writing output files...\\n\";\n    prediction.log << \" - energy.out\\n\";\n    ofstream file;\n    file.open(\"energy.out\");\n\n    // File header.\n    vector<string> title;\n    vector<string> colName;\n    vector<string> colInfo;\n    vector<size_t> colSize;\n    title.push_back(\"Energy comparison.\");\n    colSize.push_back(10);\n    colName.push_back(\"conf\");\n    colInfo.push_back(\"Configuration index (starting with 1).\");\n    colSize.push_back(10);\n    colName.push_back(\"natoms\");\n    colInfo.push_back(\"Number of atoms in configuration.\");\n    colSize.push_back(24);\n    colName.push_back(\"Eref\");\n    colInfo.push_back(\"Reference potential energy.\");\n    colSize.push_back(24);\n    colName.push_back(\"Ennp\");\n    colInfo.push_back(\"Potential energy predicted by NNP.\");\n    colSize.push_back(24);\n    colName.push_back(\"Ediff\");\n    colInfo.push_back(\"Difference in energy per atom between reference and \"\n                      \"NNP prediction.\");\n    colSize.push_back(24);\n    colName.push_back(\"E_offset\");\n    colInfo.push_back(\"Sum of atomic offset energies \"\n                      \"(included in column Ennp).\");\n    appendLinesToFile(file,\n                      createFileHeader(title, colSize, colName, colInfo));\n\n    file << strpr(\"%10zu %10zu %24.16E %24.16E %24.16E %24.16E\\n\",\n                  s.index + 1,\n                  s.numAtoms,\n                  s.energyRef,\n                  s.energy,\n                  (s.energyRef - s.energy) / s.numAtoms,\n                  prediction.getEnergyOffset(s));\n    file.close();\n\n    prediction.log << \" - nnatoms.out\\n\";\n    file.open(\"nnatoms.out\");\n\n    // File header.\n    title.clear();\n    colName.clear();\n    colInfo.clear();\n    colSize.clear();\n    title.push_back(\"Energy contributions calculated from NNP.\");\n    colSize.push_back(10);\n    colName.push_back(\"conf\");\n    colInfo.push_back(\"Configuration index (starting with 1).\");\n    colSize.push_back(10);\n    colName.push_back(\"index\");\n    colInfo.push_back(\"Atom index (starting with 1).\");\n    colSize.push_back(3);\n    colName.push_back(\"Z\");\n    colInfo.push_back(\"Nuclear charge of atom.\");\n    colSize.push_back(24);\n    colName.push_back(\"Qref\");\n    colInfo.push_back(\"Reference atomic charge.\");\n    colSize.push_back(24);\n    colName.push_back(\"Qnnp\");\n    colInfo.push_back(\"NNP atomic charge.\");\n    colSize.push_back(24);\n    colName.push_back(\"Eref_atom\");\n    colInfo.push_back(\"Reference atomic energy contribution.\");\n    colSize.push_back(24);\n    colName.push_back(\"Ennp_atom\");\n    colInfo.push_back(\"Atomic energy contribution (physical units, no mean \"\n                      \"or offset energy added).\");\n    appendLinesToFile(file,\n                      createFileHeader(title, colSize, colName, colInfo));\n\n    for (vector<Atom>::const_iterator it = s.atoms.begin();\n         it != s.atoms.end(); ++it)\n    {\n        file << strpr(\"%10zu %10zu %3zu %24.16E %24.16E %24.16E %24.16E\\n\",\n                      s.index + 1,\n                      it->index + 1,\n                      prediction.elementMap.atomicNumber(it->element),\n                      it->chargeRef,\n                      it->charge,\n                      0.0,\n                      it->energy);\n    }\n    file.close();\n\n    prediction.log << \" - nnforces.out\\n\";\n    file.open(\"nnforces.out\");\n\n    // File header.\n    title.clear();\n    colName.clear();\n    colInfo.clear();\n    colSize.clear();\n    title.push_back(\"Atomic force comparison (ordered by atom index).\");\n    colSize.push_back(10);\n    colName.push_back(\"conf\");\n    colInfo.push_back(\"Configuration index (starting with 1).\");\n    colSize.push_back(10);\n    colName.push_back(\"index\");\n    colInfo.push_back(\"Atom index (starting with 1).\");\n    colSize.push_back(24);\n    colName.push_back(\"fxRef\");\n    colInfo.push_back(\"Reference force in x direction.\");\n    colSize.push_back(24);\n    colName.push_back(\"fyRef\");\n    colInfo.push_back(\"Reference force in y direction.\");\n    colSize.push_back(24);\n    colName.push_back(\"fzRef\");\n    colInfo.push_back(\"Reference force in z direction.\");\n    colSize.push_back(24);\n    colName.push_back(\"fx\");\n    colInfo.push_back(\"Force in x direction.\");\n    colSize.push_back(24);\n    colName.push_back(\"fy\");\n    colInfo.push_back(\"Force in y direction.\");\n    colSize.push_back(24);\n    colName.push_back(\"fz\");\n    colInfo.push_back(\"Force in z direction.\");\n    appendLinesToFile(file,\n                      createFileHeader(title, colSize, colName, colInfo));\n\n    for (vector<Atom>::const_iterator it = s.atoms.begin();\n         it != s.atoms.end(); ++it)\n    {\n        file << strpr(\"%10zu %10zu %24.16E %24.16E %24.16E %24.16E %24.16E \"\n                      \"%24.16E\\n\",\n                      s.index + 1,\n                      it->index + 1,\n                      it->fRef[0],\n                      it->fRef[1],\n                      it->fRef[2],\n                      it->f[0],\n                      it->f[1],\n                      it->f[2]);\n    }\n    file.close();\n\n    prediction.log << \"Writing structure with NNP prediction \"\n                      \"to \\\"output.data\\\".\\n\";\n    file.open(\"output.data\");\n    prediction.structure.writeToFile(&file, false);\n    file.close();\n\n    if (structureInfo)\n    {\n        prediction.log << \"Writing detailed structure information to \"\n                          \"\\\"structure.out\\\".\\n\";\n        file.open(\"structure.out\");\n        vector<string> info = prediction.structure.info();\n        appendLinesToFile(file, info);\n        file.close();\n    }\n\n    prediction.log << \"Finished.\\n\";\n    prediction.log << \"*****************************************\"\n                      \"**************************************\\n\";\n    logFile.close();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-prune.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Mode.h\"\n#include \"utility.h\"\n#include <cstdlib>\n#include <iostream>\n#include <fstream>\n#include <stdexcept>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    double threshold;\n    string pruneMode;\n\n    if (!(argc == 3 || argc == 4))\n    {\n        cout << \"USAGE: \" << argv[0] << \" <mode> <threshold> <<sensmode>>\\n\"\n             << \"       <mode> ........ Use scaling data \\\"range\\\" or \"\n                \"sensitivity analysis data \\\"sensitivity\\\".\\n\"\n             << \"       <threshold> ... Prune symmetry function lines in \"\n                \"settings file below this threshold.\\n\"\n             << \"       <sensmode> .... If <mode> is sensitivity, select mean \"\n                \"square average or maximum sensitivity (msa/max).\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.nn (NNP settings)\\n\"\n             << \"       - sensitivity.???.out (Data for sensitivity mode).\\n\";\n        return 1;\n    }\n\n    pruneMode = argv[1];\n    if (! (pruneMode == \"range\" || pruneMode == \"sensitivity\"))\n    {\n        throw invalid_argument(\"ERROR: Unknown pruning mode.\\n\");\n    }\n    threshold = atof(argv[2]);\n\n    ofstream logFile;\n    logFile.open(\"nnp-prune.log\");\n    Mode mode;\n    mode.log.registerStreamPointer(&logFile);\n    mode.initialize();\n    mode.loadSettingsFile();\n    mode.setupGeneric();\n    if (pruneMode == \"range\")\n    {\n        mode.setupSymmetryFunctionScaling();\n    }\n\n    mode.log << \"\\n\";\n    mode.log << \"*** PRUNE SYMMETRY FUNCTIONS ************\"\n                \"**************************************\\n\";\n    mode.log << \"\\n\";\n\n    vector<size_t> prune;\n    if (pruneMode == \"range\")\n    {\n        mode.log << \"Pruning symmetry functions according to their range.\\n\";\n        mode.log << strpr(\"Symmetry function threshold for pruning |Gmax - \"\n                          \"Gmin| < %10.2E\\n\", threshold);\n        prune = mode.pruneSymmetryFunctionsRange(threshold);\n        mode.log << strpr(\"Number of symmetry functions to be pruned: %zu\\n\",\n                          prune.size());\n        mode.writePrunedSettingsFile(prune, \"output-prune-range.nn\");\n        mode.log << \"Pruned settings file written to: output-prune-range.nn\\n\";\n    }\n    else if (pruneMode == \"sensitivity\")\n    {\n        if (argc != 4)\n        {\n            throw invalid_argument(\"ERROR: Please select sensitivity mode.\\n\");\n        }\n        string sensMode = argv[3];\n        size_t column = 0;\n        if (sensMode == \"msa\")\n        {\n            column = 1;\n            mode.log << strpr(\"Pruning symmetry functions below mean square \"\n                              \"average sensitivity threshold: %10.2E.\\n\",\n                              threshold);\n        }\n        else if (sensMode == \"max\")\n        {\n            column = 2;\n            mode.log << strpr(\"Pruning symmetry functions below maximum \"\n                              \"sensitivity threshold: %10.2E.\\n\",\n                              threshold);\n        }\n        else\n        {\n            throw invalid_argument(\"ERROR: Unknown sensitivity mode.\\n\");\n        }\n        vector<vector<double> > sensitivity;\n        size_t numElements = mode.getNumElements();\n        vector<size_t> numSymmetryFunctions = mode.getNumSymmetryFunctions();\n        sensitivity.resize(numElements);\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            ifstream sensFile;\n            string sensFileName = strpr(\"sensitivity.%03d.out\",\n                                        mode.elementMap.atomicNumber(i));\n            sensFile.open(sensFileName.c_str());\n            string line;\n            vector<string> lines;\n            while (getline(sensFile, line))\n            {\n                if (line.at(0) != '#')\n                {\n                    lines.push_back(line);\n                }\n            }\n            if (lines.size() != numSymmetryFunctions.at(i))\n            {\n                throw range_error(strpr(\"ERROR: Inconsistent sensistivity\"\n                                        \" data file \\\"%s\\\".\\n\",\n                                        sensFileName.c_str()));\n            }\n            for (size_t j = 0; j < numSymmetryFunctions.at(i); ++j)\n            {\n                vector<string> split = nnp::split(reduce(lines.at(j)));\n                double s = atof(split.at(column).c_str()); \n                sensitivity.at(i).push_back(s);\n            }\n            sensFile.close();\n        }\n        prune = mode.pruneSymmetryFunctionsSensitivity(threshold, sensitivity);\n        mode.log << strpr(\"Number of symmetry functions to be pruned: %zu\\n\",\n                          prune.size());\n        mode.writePrunedSettingsFile(prune, \"output-prune-sensitivity.nn\");\n        mode.log << \"Pruned settings file written to: \"\n                    \"output-prune-sensitivity.nn\\n\";\n    }\n\n    mode.log << \"*****************************************\"\n                \"**************************************\\n\";\n    logFile.close();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-scaling.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Dataset.h\"\n#include \"mpi-extra.h\"\n#include \"utility.h\"\n#include <mpi.h>\n#include <cstdlib>\n#include <iostream>\n#include <fstream>\n#include <string>\n#include <vector>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    bool   useForces = false;\n    int    numProcs  = 0;\n    int    myRank    = 0;\n    long   memory    = 0;\n    size_t count     = 0;\n    ofstream myLog;\n\n    if (argc != 2)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <nbins>\\n\"\n             << \"       <nbins> ... Number of symmetry function\"\n                \" histogram bins.\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\"\n             << \"       - input.nn (NNP settings)\\n\";\n        return 1;\n    }\n\n    size_t numBins = (size_t)atoi(argv[1]);\n\n    MPI_Init(&argc, &argv);\n    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);\n    MPI_Comm_rank(MPI_COMM_WORLD, &myRank);\n\n    Dataset dataset;\n    myLog.open(strpr(\"nnp-scaling.log.%04d\", myRank).c_str());\n    if (myRank != 0) dataset.log.writeToStdout = false;\n    dataset.log.registerStreamPointer(&myLog);\n    dataset.setupMPI();\n    dataset.initialize();\n    dataset.loadSettingsFile();\n    // TODO: is there a better way than setting initial_hardness true? stage is\n    // not accessible here.\n    dataset.setupGeneric(\"\", true);\n    dataset.setupSymmetryFunctionScalingNone();\n    dataset.setupSymmetryFunctionStatistics(true, false, false, false);\n    dataset.setupRandomNumberGenerator();\n    dataset.distributeStructures(true);\n    if (dataset.useNormalization()) dataset.toNormalizedUnits();\n    useForces = dataset.settingsKeywordExists(\"use_short_forces\");\n\n    dataset.log << \"\\n\";\n    dataset.log << \"*** CALCULATING SYMMETRY FUNCTIONS ******\"\n                   \"**************************************\\n\";\n    dataset.log << \"\\n\";\n\n    dataset.log << \"Check the log files of all (!) MPI processes\"\n                   \" for warnings in this section!\\n\";\n\n    for (vector<Structure>::iterator it = dataset.structures.begin();\n         it != dataset.structures.end(); ++it)\n    {\n        it->calculateNeighborList(dataset.getMaxCutoffRadius());\n#ifdef N2P2_NO_SF_GROUPS\n        dataset.calculateSymmetryFunctions((*it), useForces);\n#else\n        dataset.calculateSymmetryFunctionGroups((*it), useForces);\n#endif\n        memory += dataset.calculateBufferSize((*it));\n        count++;\n        // Clear unneccessary memory (neighbor list and others), leave only\n        // numNeighbors and symmetry functions (G) for histogram calculation.\n        // Don't use these structures after these operations unless you know\n        // what you do!\n        for (vector<Atom>::iterator it2 = it->atoms.begin();\n             it2 != it->atoms.end(); ++it2)\n        {\n            it2->numNeighborsUnique = 0;\n            it2->neighborsUnique.clear();\n            vector<size_t>(it2->neighborsUnique).swap(it2->neighborsUnique);\n\n            it2->numNeighborsPerElement.clear();\n            vector<size_t>(it2->numNeighborsPerElement).swap(\n                                                  it2->numNeighborsPerElement);\n\n            it2->dEdG.clear();\n            vector<double>(it2->dEdG).swap(it2->dEdG);\n\n#ifdef N2P2_FULL_SFD_MEMORY\n            it2->dGdxia.clear();\n            vector<double>(it2->dGdxia).swap(it2->dGdxia);\n#endif\n\n            it2->dGdr.clear();\n            vector<Vec3D>(it2->dGdr).swap(it2->dGdr);\n\n            // Leave this for the histogram.\n            //it2->numNeighbors = 0;\n            it2->neighbors.clear();\n            vector<Atom::Neighbor>(it2->neighbors).swap(it2->neighbors);\n        }\n    }\n    dataset.log << \"*****************************************\"\n                   \"**************************************\\n\";\n\n    dataset.collectSymmetryFunctionStatistics();\n    dataset.writeSymmetryFunctionScaling();\n    dataset.writeNeighborHistogram();\n    dataset.writeSymmetryFunctionHistograms(numBins);\n    dataset.writeSymmetryFunctionFile();\n\n    dataset.log << \"\\n\";\n    dataset.log << \"*** MEMORY USAGE ESTIMATION *************\"\n                   \"**************************************\\n\";\n    dataset.log << \"\\n\";\n    dataset.log << \"Estimated memory usage for training (keyword\"\n                   \" \\\"memorize_symfunc_results\\\":\\n\";\n    if (useForces)\n    {\n        dataset.log << \"Valid for training of energies and forces.\\n\";\n    }\n    else\n    {\n        dataset.log << \"Valid for training of energies only.\\n\";\n    }\n    dataset.log << strpr(\"Memory for local structures  : \"\n                         \"%15ld bytes (%.2f MiB = %.2f GiB).\\n\",\n                         memory,\n                         memory / 1024. / 1024.,\n                         memory / 1024. / 1024. / 1024.);\n    MPI_Allreduce(MPI_IN_PLACE, &memory, 1, MPI_LONG  , MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &count , 1, MPI_SIZE_T, MPI_SUM, MPI_COMM_WORLD);\n    dataset.log << strpr(\"Memory for all structures    : \"\n                         \"%15ld bytes (%.2f MiB = %.2f GiB).\\n\",\n                         memory,\n                         memory / 1024. / 1024.,\n                         memory / 1024. / 1024. / 1024.);\n    dataset.log << strpr(\"Average memory per structure : \"\n                         \"%15.0f bytes (%.2f MiB).\\n\",\n                         memory / (double)count,\n                         memory / (double)count / 1024. / 1024.);\n    dataset.log << \"*****************************************\"\n                   \"**************************************\\n\";\n\n    myLog.close();\n\n    MPI_Finalize();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-select.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Log.h\"\n#include \"utility.h\"\n#include <cstddef>  // std::size_t\n#include <cstdlib>  // srand, rand\n#include <cstring>  // strcmp\n#include <iostream> // std::cout\n#include <fstream>  // std::ofstream\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    if (argc < 3)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <mode> <arg1 <arg2>>\\n\"\n             << \"       <mode> ... Choose selection mode (random/interval).\\n\"\n             << \"       Arguments for mode \\\"random\\\":\\n\"\n             << \"         <arg1> ... Ratio of selected structures \"\n             << \"(1.0 equals 100 %).\\n\"\n             << \"         <arg2> ... Seed for random number generator \"\n             << \"(integer).\\n\"\n             << \"       Arguments for mode \\\"interval\\\":\\n\"\n             << \"         <arg1> ... Select structures in this interval \"\n             << \"(integer).\\n\"\n             << \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.data (structure file)\\n\";\n        return 1;\n    }\n\n    bool mode = false; // 0 = random, 1 = interval.\n    bool writeStructure = false;\n    size_t countStructures = 0;\n    size_t countSelected = 0;\n    size_t interval = 10;\n    int seed = 10;\n    double ratio = 1.0;\n\n    Log log;\n    ifstream inputFile;\n    ofstream outputFile;\n    ofstream rejectFile;\n    ofstream logFile;\n\n    logFile.open(\"nnp-select.log\");\n    log.registerStreamPointer(&logFile);\n\n    log << \"\\n\";\n    log << \"*** NNP-SELECT **************************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    if (strcmp(argv[1], \"random\") == 0)\n    {\n        mode = false;\n        if (argc != 4)\n        {\n            throw invalid_argument(\"ERROR: Wrong number of arguments.\\n\");\n        }\n        ratio = atof(argv[2]);\n        seed = atoi(argv[3]);\n        srand(seed);\n        log << strpr(\"Selecting randomly %.2f %% of all structures.\\n\",\n                     ratio * 100.0);\n        log << strpr(\"Random number generator seed: %d.\\n\", seed);\n    }\n    else if (strcmp(argv[1], \"interval\") == 0)\n    {\n        mode = true; \n        if (argc != 3)\n        {\n            throw invalid_argument(\"ERROR: Wrong number of arguments.\\n\");\n        }\n        interval = (size_t)atoi(argv[2]);\n        log << strpr(\"Selecting every %d structure.\\n\", interval);\n    }\n    else\n    {\n        throw invalid_argument(\"ERROR: Unknown selection mode.\\n\");\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    inputFile.open(\"input.data\");\n    outputFile.open(\"output.data\");\n    rejectFile.open(\"reject.data\");\n    string line;\n    while (getline(inputFile, line))\n    {\n        if (split(reduce(line)).at(0) == \"begin\")\n        {\n            if (mode)\n            {\n                if (countStructures % interval == 0) writeStructure = true; \n                else writeStructure = false;\n            }\n            else\n            {\n                if ((double)rand() / RAND_MAX <= ratio) writeStructure = true;\n                else writeStructure = false;\n            }\n            countStructures++; \n            if (writeStructure)\n            {\n                log << strpr(\"Structure %7d selected.\\n\", countStructures);\n                countSelected++;\n            }\n        }\n        if (writeStructure)\n        {\n            outputFile << line << '\\n';\n        }\n        else\n        {\n            rejectFile << line << '\\n';\n        }\n    }\n    inputFile.close();\n    outputFile.close();\n    rejectFile.close();\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n    log << strpr(\"Total    structures           : %7d\\n\", countStructures);\n    log << strpr(\"Selected structures           : %7d\\n\", countSelected);\n    log << strpr(\"Selected structures percentage: %.3f %%\\n\",\n                 countSelected / (double)countStructures * 100.0);\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n    logFile.close();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-symfunc.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SetupAnalysis.h\"\n#include \"utility.h\"\n#include <cstdlib>\n#include <iostream>\n#include <fstream>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    size_t numPoints = 0;\n    ofstream logFile;\n\n    if (argc != 2)\n    {\n        cout << \"USAGE: \" << argv[0] << \" <npoints>\\n\"\n                \"        <npoints> ... Number of data points in symmetry\"\n                \" function files.\\n\"\n                \"       Execute in directory with these NNP files present:\\n\"\n             << \"       - input.nn (NNP settings)\\n\";\n        return 1;\n    }\n\n    numPoints = atof(argv[1]);\n    \n    logFile.open(\"nnp-symfunc.log\");\n    SetupAnalysis setupAnalysis;\n    setupAnalysis.log.registerStreamPointer(&logFile);\n\n    setupAnalysis.initialize();\n    setupAnalysis.loadSettingsFile();\n    setupAnalysis.setupElementMap();\n    setupAnalysis.setupElements();\n    setupAnalysis.setupCutoff();\n    setupAnalysis.setupSymmetryFunctions();\n\n    setupAnalysis.writeSymmetryFunctionShape(numPoints);\n\n    logFile.close();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/application/nnp-train.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Training.h\"\n#include \"utility.h\"\n#include <mpi.h>\n#include <cstddef> // std::size_t\n#include <cstdlib> // atoi\n#include <fstream>\n#include <string>\n\nusing namespace std;\nusing namespace nnp;\n\nint main(int argc, char* argv[])\n{\n    int numProcs = 0;\n    int myRank   = 0;\n    size_t stage = 0;\n    ofstream myLog;\n\n    string suffix = \"\";\n    if (argc > 1)\n    {\n        stage = (size_t)atoi(argv[1]);\n        suffix = strpr(\".stage-%zu\", stage);\n    }\n\n    MPI_Init(&argc, &argv);\n    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);\n    MPI_Comm_rank(MPI_COMM_WORLD, &myRank);\n\n    // Basic setup.\n    Training training;\n    if (myRank != 0) training.log.writeToStdout = false;\n\n    myLog.open((strpr(\"nnp-train.log.%04d\", myRank) + suffix).c_str());\n    training.log.registerStreamPointer(&myLog);\n    training.setupMPI();\n    training.initialize();\n    training.loadSettingsFile();\n    training.setStage(stage);\n    // If initial-weights-based normalization is enabled skip normalization\n    // setup here.\n    training.setupGeneric(\n        \"\",\n        training.settingsKeywordExists(\"normalize_data_set\"),\n        stage == 1\n    );\n    training.setupSymmetryFunctionScaling();\n    training.setupSymmetryFunctionStatistics(false, false, false, false);\n    training.setupRandomNumberGenerator();\n\n    // Distribute structures to MPI processes.\n    training.distributeStructures(true);\n\n    // Randomly select training/test set and write them to separate files\n    // (train.data/test.data, same format as input.data).\n    training.selectSets();\n    training.writeSetsToFiles();\n\n    // Initialize weights and biases for neural networks.\n    training.initializeWeights();\n\n    // Run data set normalization if keyword present.\n    if (training.settingsKeywordExists(\"normalize_data_set\"))\n    {\n        training.dataSetNormalization();\n    }\n\n    // Switch to normalized units, convert all structures.\n    if (training.useNormalization()) training.toNormalizedUnits();\n\n    // General training settings and weight update routine.\n    training.setupTraining();\n\n    // Calculate neighbor lists for all structures.\n    training.calculateNeighborLists();\n\n    // The main training loop.\n    training.loop();\n\n    myLog.close();\n\n    MPI_Finalize();\n\n    return 0;\n}\n"
  },
  {
    "path": "src/doc/doxygen/Doxyfile",
    "content": "# Doxyfile 1.9.2\n\n# This file describes the settings to be used by the documentation system\n# doxygen (www.doxygen.org) for a project.\n#\n# All text after a double hash (##) is considered a comment and is placed in\n# front of the TAG it is preceding.\n#\n# All text after a single hash (#) is considered a comment and will be ignored.\n# The format is:\n# TAG = value [value, ...]\n# For lists, items can also be appended using:\n# TAG += value [value, ...]\n# Values that contain spaces should be placed between quotes (\\\" \\\").\n\n#---------------------------------------------------------------------------\n# Project related configuration options\n#---------------------------------------------------------------------------\n\n# This tag specifies the encoding used for all characters in the configuration\n# file that follow. The default is UTF-8 which is also the encoding used for all\n# text before the first occurrence of this tag. Doxygen uses libiconv (or the\n# iconv built into libc) for the transcoding. See\n# https://www.gnu.org/software/libiconv/ for the list of possible encodings.\n# The default value is: UTF-8.\n\nDOXYFILE_ENCODING      = UTF-8\n\n# The PROJECT_NAME tag is a single word (or a sequence of words surrounded by\n# double-quotes, unless you are using Doxywizard) that should identify the\n# project for which the documentation is generated. This name is used in the\n# title of most generated pages and in a few other places.\n# The default value is: My Project.\n\nPROJECT_NAME           = \"n2p2 - A neural network potential package\"\n\n# The PROJECT_NUMBER tag can be used to enter a project or revision number. This\n# could be handy for archiving the generated documentation or if some version\n# control system is used.\n\nPROJECT_NUMBER         =\n\n# Using the PROJECT_BRIEF tag one can provide an optional one line description\n# for a project that appears at the top of each page and should give viewer a\n# quick idea about the purpose of the project. Keep the description short.\n\nPROJECT_BRIEF          =\n\n# With the PROJECT_LOGO tag one can specify a logo or an icon that is included\n# in the documentation. The maximum height of the logo should not exceed 55\n# pixels and the maximum width should not exceed 200 pixels. Doxygen will copy\n# the logo to the output directory.\n\nPROJECT_LOGO           =\n\n# The OUTPUT_DIRECTORY tag is used to specify the (relative or absolute) path\n# into which the generated documentation will be written. If a relative path is\n# entered, it will be relative to the location where doxygen was started. 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By setting PYTHON_DOCSTRING to NO the\n# doxygen's special commands can be used and the contents of the docstring\n# documentation blocks is shown as doxygen documentation.\n# The default value is: YES.\n\nPYTHON_DOCSTRING       = YES\n\n# If the INHERIT_DOCS tag is set to YES then an undocumented member inherits the\n# documentation from any documented member that it re-implements.\n# The default value is: YES.\n\nINHERIT_DOCS           = YES\n\n# If the SEPARATE_MEMBER_PAGES tag is set to YES then doxygen will produce a new\n# page for each member. If set to NO, the documentation of a member will be part\n# of the file/class/namespace that contains it.\n# The default value is: NO.\n\nSEPARATE_MEMBER_PAGES  = NO\n\n# The TAB_SIZE tag can be used to set the number of spaces in a tab. Doxygen\n# uses this value to replace tabs by spaces in code fragments.\n# Minimum value: 1, maximum value: 16, default value: 4.\n\nTAB_SIZE               = 4\n\n# This tag can be used to specify a number of aliases that act as commands in\n# the documentation. An alias has the form:\n# name=value\n# For example adding\n# \"sideeffect=@par Side Effects:^^\"\n# will allow you to put the command \\sideeffect (or @sideeffect) in the\n# documentation, which will result in a user-defined paragraph with heading\n# \"Side Effects:\". Note that you cannot put \\n's in the value part of an alias\n# to insert newlines (in the resulting output). You can put ^^ in the value part\n# of an alias to insert a newline as if a physical newline was in the original\n# file. When you need a literal { or } or , in the value part of an alias you\n# have to escape them by means of a backslash (\\), this can lead to conflicts\n# with the commands \\{ and \\} for these it is advised to use the version @{ and\n# @} or use a double escape (\\\\{ and \\\\})\n\nALIASES                =\n\n# Set the OPTIMIZE_OUTPUT_FOR_C tag to YES if your project consists of C sources\n# only. Doxygen will then generate output that is more tailored for C. For\n# instance, some of the names that are used will be different. The list of all\n# members will be omitted, etc.\n# The default value is: NO.\n\nOPTIMIZE_OUTPUT_FOR_C  = NO\n\n# Set the OPTIMIZE_OUTPUT_JAVA tag to YES if your project consists of Java or\n# Python sources only. Doxygen will then generate output that is more tailored\n# for that language. For instance, namespaces will be presented as packages,\n# qualified scopes will look different, etc.\n# The default value is: NO.\n\nOPTIMIZE_OUTPUT_JAVA   = NO\n\n# Set the OPTIMIZE_FOR_FORTRAN tag to YES if your project consists of Fortran\n# sources. Doxygen will then generate output that is tailored for Fortran.\n# The default value is: NO.\n\nOPTIMIZE_FOR_FORTRAN   = NO\n\n# Set the OPTIMIZE_OUTPUT_VHDL tag to YES if your project consists of VHDL\n# sources. Doxygen will then generate output that is tailored for VHDL.\n# The default value is: NO.\n\nOPTIMIZE_OUTPUT_VHDL   = NO\n\n# Set the OPTIMIZE_OUTPUT_SLICE tag to YES if your project consists of Slice\n# sources only. Doxygen will then generate output that is more tailored for that\n# language. For instance, namespaces will be presented as modules, types will be\n# separated into more groups, etc.\n# The default value is: NO.\n\nOPTIMIZE_OUTPUT_SLICE  = NO\n\n# Doxygen selects the parser to use depending on the extension of the files it\n# parses. With this tag you can assign which parser to use for a given\n# extension. Doxygen has a built-in mapping, but you can override or extend it\n# using this tag. The format is ext=language, where ext is a file extension, and\n# language is one of the parsers supported by doxygen: IDL, Java, JavaScript,\n# Csharp (C#), C, C++, Lex, D, PHP, md (Markdown), Objective-C, Python, Slice,\n# VHDL, Fortran (fixed format Fortran: FortranFixed, free formatted Fortran:\n# FortranFree, unknown formatted Fortran: Fortran. In the later case the parser\n# tries to guess whether the code is fixed or free formatted code, this is the\n# default for Fortran type files). For instance to make doxygen treat .inc files\n# as Fortran files (default is PHP), and .f files as C (default is Fortran),\n# use: inc=Fortran f=C.\n#\n# Note: For files without extension you can use no_extension as a placeholder.\n#\n# Note that for custom extensions you also need to set FILE_PATTERNS otherwise\n# the files are not read by doxygen. When specifying no_extension you should add\n# * to the FILE_PATTERNS.\n#\n# Note see also the list of default file extension mappings.\n\nEXTENSION_MAPPING      = pyx=Python \\\n                         pxd=Python\n\n# If the MARKDOWN_SUPPORT tag is enabled then doxygen pre-processes all comments\n# according to the Markdown format, which allows for more readable\n# documentation. See https://daringfireball.net/projects/markdown/ for details.\n# The output of markdown processing is further processed by doxygen, so you can\n# mix doxygen, HTML, and XML commands with Markdown formatting. Disable only in\n# case of backward compatibilities issues.\n# The default value is: YES.\n\nMARKDOWN_SUPPORT       = YES\n\n# When the TOC_INCLUDE_HEADINGS tag is set to a non-zero value, all headings up\n# to that level are automatically included in the table of contents, even if\n# they do not have an id attribute.\n# Note: This feature currently applies only to Markdown headings.\n# Minimum value: 0, maximum value: 99, default value: 5.\n# This tag requires that the tag MARKDOWN_SUPPORT is set to YES.\n\nTOC_INCLUDE_HEADINGS   = 5\n\n# When enabled doxygen tries to link words that correspond to documented\n# classes, or namespaces to their corresponding documentation. Such a link can\n# be prevented in individual cases by putting a % sign in front of the word or\n# globally by setting AUTOLINK_SUPPORT to NO.\n# The default value is: YES.\n\nAUTOLINK_SUPPORT       = YES\n\n# If you use STL classes (i.e. std::string, std::vector, etc.) but do not want\n# to include (a tag file for) the STL sources as input, then you should set this\n# tag to YES in order to let doxygen match functions declarations and\n# definitions whose arguments contain STL classes (e.g. func(std::string);\n# versus func(std::string) {}). This also make the inheritance and collaboration\n# diagrams that involve STL classes more complete and accurate.\n# The default value is: NO.\n\nBUILTIN_STL_SUPPORT    = YES\n\n# If you use Microsoft's C++/CLI language, you should set this option to YES to\n# enable parsing support.\n# The default value is: NO.\n\nCPP_CLI_SUPPORT        = NO\n\n# Set the SIP_SUPPORT tag to YES if your project consists of sip (see:\n# https://www.riverbankcomputing.com/software/sip/intro) sources only. Doxygen\n# will parse them like normal C++ but will assume all classes use public instead\n# of private inheritance when no explicit protection keyword is present.\n# The default value is: NO.\n\nSIP_SUPPORT            = NO\n\n# For Microsoft's IDL there are propget and propput attributes to indicate\n# getter and setter methods for a property. Setting this option to YES will make\n# doxygen to replace the get and set methods by a property in the documentation.\n# This will only work if the methods are indeed getting or setting a simple\n# type. If this is not the case, or you want to show the methods anyway, you\n# should set this option to NO.\n# The default value is: YES.\n\nIDL_PROPERTY_SUPPORT   = YES\n\n# If member grouping is used in the documentation and the DISTRIBUTE_GROUP_DOC\n# tag is set to YES then doxygen will reuse the documentation of the first\n# member in the group (if any) for the other members of the group. By default\n# all members of a group must be documented explicitly.\n# The default value is: NO.\n\nDISTRIBUTE_GROUP_DOC   = NO\n\n# If one adds a struct or class to a group and this option is enabled, then also\n# any nested class or struct is added to the same group. By default this option\n# is disabled and one has to add nested compounds explicitly via \\ingroup.\n# The default value is: NO.\n\nGROUP_NESTED_COMPOUNDS = NO\n\n# Set the SUBGROUPING tag to YES to allow class member groups of the same type\n# (for instance a group of public functions) to be put as a subgroup of that\n# type (e.g. under the Public Functions section). Set it to NO to prevent\n# subgrouping. Alternatively, this can be done per class using the\n# \\nosubgrouping command.\n# The default value is: YES.\n\nSUBGROUPING            = YES\n\n# When the INLINE_GROUPED_CLASSES tag is set to YES, classes, structs and unions\n# are shown inside the group in which they are included (e.g. using \\ingroup)\n# instead of on a separate page (for HTML and Man pages) or section (for LaTeX\n# and RTF).\n#\n# Note that this feature does not work in combination with\n# SEPARATE_MEMBER_PAGES.\n# The default value is: NO.\n\nINLINE_GROUPED_CLASSES = NO\n\n# When the INLINE_SIMPLE_STRUCTS tag is set to YES, structs, classes, and unions\n# with only public data fields or simple typedef fields will be shown inline in\n# the documentation of the scope in which they are defined (i.e. file,\n# namespace, or group documentation), provided this scope is documented. If set\n# to NO, structs, classes, and unions are shown on a separate page (for HTML and\n# Man pages) or section (for LaTeX and RTF).\n# The default value is: NO.\n\nINLINE_SIMPLE_STRUCTS  = NO\n\n# When TYPEDEF_HIDES_STRUCT tag is enabled, a typedef of a struct, union, or\n# enum is documented as struct, union, or enum with the name of the typedef. So\n# typedef struct TypeS {} TypeT, will appear in the documentation as a struct\n# with name TypeT. When disabled the typedef will appear as a member of a file,\n# namespace, or class. And the struct will be named TypeS. This can typically be\n# useful for C code in case the coding convention dictates that all compound\n# types are typedef'ed and only the typedef is referenced, never the tag name.\n# The default value is: NO.\n\nTYPEDEF_HIDES_STRUCT   = NO\n\n# The size of the symbol lookup cache can be set using LOOKUP_CACHE_SIZE. This\n# cache is used to resolve symbols given their name and scope. Since this can be\n# an expensive process and often the same symbol appears multiple times in the\n# code, doxygen keeps a cache of pre-resolved symbols. If the cache is too small\n# doxygen will become slower. If the cache is too large, memory is wasted. The\n# cache size is given by this formula: 2^(16+LOOKUP_CACHE_SIZE). The valid range\n# is 0..9, the default is 0, corresponding to a cache size of 2^16=65536\n# symbols. At the end of a run doxygen will report the cache usage and suggest\n# the optimal cache size from a speed point of view.\n# Minimum value: 0, maximum value: 9, default value: 0.\n\nLOOKUP_CACHE_SIZE      = 0\n\n# The NUM_PROC_THREADS specifies the number threads doxygen is allowed to use\n# during processing. When set to 0 doxygen will based this on the number of\n# cores available in the system. You can set it explicitly to a value larger\n# than 0 to get more control over the balance between CPU load and processing\n# speed. At this moment only the input processing can be done using multiple\n# threads. Since this is still an experimental feature the default is set to 1,\n# which effectively disables parallel processing. Please report any issues you\n# encounter. Generating dot graphs in parallel is controlled by the\n# DOT_NUM_THREADS setting.\n# Minimum value: 0, maximum value: 32, default value: 1.\n\nNUM_PROC_THREADS       = 1\n\n#---------------------------------------------------------------------------\n# Build related configuration options\n#---------------------------------------------------------------------------\n\n# If the EXTRACT_ALL tag is set to YES, doxygen will assume all entities in\n# documentation are documented, even if no documentation was available. Private\n# class members and static file members will be hidden unless the\n# EXTRACT_PRIVATE respectively EXTRACT_STATIC tags are set to YES.\n# Note: This will also disable the warnings about undocumented members that are\n# normally produced when WARNINGS is set to YES.\n# The default value is: NO.\n\nEXTRACT_ALL            = YES\n\n# If the EXTRACT_PRIVATE tag is set to YES, all private members of a class will\n# be included in the documentation.\n# The default value is: NO.\n\nEXTRACT_PRIVATE        = YES\n\n# If the EXTRACT_PRIV_VIRTUAL tag is set to YES, documented private virtual\n# methods of a class will be included in the documentation.\n# The default value is: NO.\n\nEXTRACT_PRIV_VIRTUAL   = NO\n\n# If the EXTRACT_PACKAGE tag is set to YES, all members with package or internal\n# scope will be included in the documentation.\n# The default value is: NO.\n\nEXTRACT_PACKAGE        = NO\n\n# If the EXTRACT_STATIC tag is set to YES, all static members of a file will be\n# included in the documentation.\n# The default value is: NO.\n\nEXTRACT_STATIC         = YES\n\n# If the EXTRACT_LOCAL_CLASSES tag is set to YES, classes (and structs) defined\n# locally in source files will be included in the documentation. If set to NO,\n# only classes defined in header files are included. Does not have any effect\n# for Java sources.\n# The default value is: YES.\n\nEXTRACT_LOCAL_CLASSES  = YES\n\n# This flag is only useful for Objective-C code. If set to YES, local methods,\n# which are defined in the implementation section but not in the interface are\n# included in the documentation. If set to NO, only methods in the interface are\n# included.\n# The default value is: NO.\n\nEXTRACT_LOCAL_METHODS  = NO\n\n# If this flag is set to YES, the members of anonymous namespaces will be\n# extracted and appear in the documentation as a namespace called\n# 'anonymous_namespace{file}', where file will be replaced with the base name of\n# the file that contains the anonymous namespace. By default anonymous namespace\n# are hidden.\n# The default value is: NO.\n\nEXTRACT_ANON_NSPACES   = NO\n\n# If this flag is set to YES, the name of an unnamed parameter in a declaration\n# will be determined by the corresponding definition. By default unnamed\n# parameters remain unnamed in the output.\n# The default value is: YES.\n\nRESOLVE_UNNAMED_PARAMS = YES\n\n# If the HIDE_UNDOC_MEMBERS tag is set to YES, doxygen will hide all\n# undocumented members inside documented classes or files. If set to NO these\n# members will be included in the various overviews, but no documentation\n# section is generated. This option has no effect if EXTRACT_ALL is enabled.\n# The default value is: NO.\n\nHIDE_UNDOC_MEMBERS     = NO\n\n# If the HIDE_UNDOC_CLASSES tag is set to YES, doxygen will hide all\n# undocumented classes that are normally visible in the class hierarchy. If set\n# to NO, these classes will be included in the various overviews. This option\n# has no effect if EXTRACT_ALL is enabled.\n# The default value is: NO.\n\nHIDE_UNDOC_CLASSES     = NO\n\n# If the HIDE_FRIEND_COMPOUNDS tag is set to YES, doxygen will hide all friend\n# declarations. If set to NO, these declarations will be included in the\n# documentation.\n# The default value is: NO.\n\nHIDE_FRIEND_COMPOUNDS  = NO\n\n# If the HIDE_IN_BODY_DOCS tag is set to YES, doxygen will hide any\n# documentation blocks found inside the body of a function. If set to NO, these\n# blocks will be appended to the function's detailed documentation block.\n# The default value is: NO.\n\nHIDE_IN_BODY_DOCS      = NO\n\n# The INTERNAL_DOCS tag determines if documentation that is typed after a\n# \\internal command is included. If the tag is set to NO then the documentation\n# will be excluded. Set it to YES to include the internal documentation.\n# The default value is: NO.\n\nINTERNAL_DOCS          = NO\n\n# With the correct setting of option CASE_SENSE_NAMES doxygen will better be\n# able to match the capabilities of the underlying filesystem. In case the\n# filesystem is case sensitive (i.e. it supports files in the same directory\n# whose names only differ in casing), the option must be set to YES to properly\n# deal with such files in case they appear in the input. For filesystems that\n# are not case sensitive the option should be be set to NO to properly deal with\n# output files written for symbols that only differ in casing, such as for two\n# classes, one named CLASS and the other named Class, and to also support\n# references to files without having to specify the exact matching casing. On\n# Windows (including Cygwin) and MacOS, users should typically set this option\n# to NO, whereas on Linux or other Unix flavors it should typically be set to\n# YES.\n# The default value is: system dependent.\n\nCASE_SENSE_NAMES       = YES\n\n# If the HIDE_SCOPE_NAMES tag is set to NO then doxygen will show members with\n# their full class and namespace scopes in the documentation. If set to YES, the\n# scope will be hidden.\n# The default value is: NO.\n\nHIDE_SCOPE_NAMES       = NO\n\n# If the HIDE_COMPOUND_REFERENCE tag is set to NO (default) then doxygen will\n# append additional text to a page's title, such as Class Reference. If set to\n# YES the compound reference will be hidden.\n# The default value is: NO.\n\nHIDE_COMPOUND_REFERENCE= NO\n\n# If the SHOW_HEADERFILE tag is set to YES then the documentation for a class\n# will show which file needs to be included to use the class.\n# The default value is: YES.\n\nSHOW_HEADERFILE        = YES\n\n# If the SHOW_INCLUDE_FILES tag is set to YES then doxygen will put a list of\n# the files that are included by a file in the documentation of that file.\n# The default value is: YES.\n\nSHOW_INCLUDE_FILES     = YES\n\n# If the SHOW_GROUPED_MEMB_INC tag is set to YES then Doxygen will add for each\n# grouped member an include statement to the documentation, telling the reader\n# which file to include in order to use the member.\n# The default value is: NO.\n\nSHOW_GROUPED_MEMB_INC  = NO\n\n# If the FORCE_LOCAL_INCLUDES tag is set to YES then doxygen will list include\n# files with double quotes in the documentation rather than with sharp brackets.\n# The default value is: NO.\n\nFORCE_LOCAL_INCLUDES   = NO\n\n# If the INLINE_INFO tag is set to YES then a tag [inline] is inserted in the\n# documentation for inline members.\n# The default value is: YES.\n\nINLINE_INFO            = YES\n\n# If the SORT_MEMBER_DOCS tag is set to YES then doxygen will sort the\n# (detailed) documentation of file and class members alphabetically by member\n# name. If set to NO, the members will appear in declaration order.\n# The default value is: YES.\n\nSORT_MEMBER_DOCS       = NO\n\n# If the SORT_BRIEF_DOCS tag is set to YES then doxygen will sort the brief\n# descriptions of file, namespace and class members alphabetically by member\n# name. If set to NO, the members will appear in declaration order. Note that\n# this will also influence the order of the classes in the class list.\n# The default value is: NO.\n\nSORT_BRIEF_DOCS        = NO\n\n# If the SORT_MEMBERS_CTORS_1ST tag is set to YES then doxygen will sort the\n# (brief and detailed) documentation of class members so that constructors and\n# destructors are listed first. If set to NO the constructors will appear in the\n# respective orders defined by SORT_BRIEF_DOCS and SORT_MEMBER_DOCS.\n# Note: If SORT_BRIEF_DOCS is set to NO this option is ignored for sorting brief\n# member documentation.\n# Note: If SORT_MEMBER_DOCS is set to NO this option is ignored for sorting\n# detailed member documentation.\n# The default value is: NO.\n\nSORT_MEMBERS_CTORS_1ST = NO\n\n# If the SORT_GROUP_NAMES tag is set to YES then doxygen will sort the hierarchy\n# of group names into alphabetical order. If set to NO the group names will\n# appear in their defined order.\n# The default value is: NO.\n\nSORT_GROUP_NAMES       = NO\n\n# If the SORT_BY_SCOPE_NAME tag is set to YES, the class list will be sorted by\n# fully-qualified names, including namespaces. If set to NO, the class list will\n# be sorted only by class name, not including the namespace part.\n# Note: This option is not very useful if HIDE_SCOPE_NAMES is set to YES.\n# Note: This option applies only to the class list, not to the alphabetical\n# list.\n# The default value is: NO.\n\nSORT_BY_SCOPE_NAME     = NO\n\n# If the STRICT_PROTO_MATCHING option is enabled and doxygen fails to do proper\n# type resolution of all parameters of a function it will reject a match between\n# the prototype and the implementation of a member function even if there is\n# only one candidate or it is obvious which candidate to choose by doing a\n# simple string match. By disabling STRICT_PROTO_MATCHING doxygen will still\n# accept a match between prototype and implementation in such cases.\n# The default value is: NO.\n\nSTRICT_PROTO_MATCHING  = NO\n\n# The GENERATE_TODOLIST tag can be used to enable (YES) or disable (NO) the todo\n# list. This list is created by putting \\todo commands in the documentation.\n# The default value is: YES.\n\nGENERATE_TODOLIST      = YES\n\n# The GENERATE_TESTLIST tag can be used to enable (YES) or disable (NO) the test\n# list. This list is created by putting \\test commands in the documentation.\n# The default value is: YES.\n\nGENERATE_TESTLIST      = YES\n\n# The GENERATE_BUGLIST tag can be used to enable (YES) or disable (NO) the bug\n# list. This list is created by putting \\bug commands in the documentation.\n# The default value is: YES.\n\nGENERATE_BUGLIST       = YES\n\n# The GENERATE_DEPRECATEDLIST tag can be used to enable (YES) or disable (NO)\n# the deprecated list. This list is created by putting \\deprecated commands in\n# the documentation.\n# The default value is: YES.\n\nGENERATE_DEPRECATEDLIST= YES\n\n# The ENABLED_SECTIONS tag can be used to enable conditional documentation\n# sections, marked by \\if <section_label> ... \\endif and \\cond <section_label>\n# ... \\endcond blocks.\n\nENABLED_SECTIONS       =\n\n# The MAX_INITIALIZER_LINES tag determines the maximum number of lines that the\n# initial value of a variable or macro / define can have for it to appear in the\n# documentation. If the initializer consists of more lines than specified here\n# it will be hidden. Use a value of 0 to hide initializers completely. The\n# appearance of the value of individual variables and macros / defines can be\n# controlled using \\showinitializer or \\hideinitializer command in the\n# documentation regardless of this setting.\n# Minimum value: 0, maximum value: 10000, default value: 30.\n\nMAX_INITIALIZER_LINES  = 30\n\n# Set the SHOW_USED_FILES tag to NO to disable the list of files generated at\n# the bottom of the documentation of classes and structs. If set to YES, the\n# list will mention the files that were used to generate the documentation.\n# The default value is: YES.\n\nSHOW_USED_FILES        = YES\n\n# Set the SHOW_FILES tag to NO to disable the generation of the Files page. This\n# will remove the Files entry from the Quick Index and from the Folder Tree View\n# (if specified).\n# The default value is: YES.\n\nSHOW_FILES             = YES\n\n# Set the SHOW_NAMESPACES tag to NO to disable the generation of the Namespaces\n# page. This will remove the Namespaces entry from the Quick Index and from the\n# Folder Tree View (if specified).\n# The default value is: YES.\n\nSHOW_NAMESPACES        = YES\n\n# The FILE_VERSION_FILTER tag can be used to specify a program or script that\n# doxygen should invoke to get the current version for each file (typically from\n# the version control system). Doxygen will invoke the program by executing (via\n# popen()) the command command input-file, where command is the value of the\n# FILE_VERSION_FILTER tag, and input-file is the name of an input file provided\n# by doxygen. Whatever the program writes to standard output is used as the file\n# version. For an example see the documentation.\n\nFILE_VERSION_FILTER    =\n\n# The LAYOUT_FILE tag can be used to specify a layout file which will be parsed\n# by doxygen. The layout file controls the global structure of the generated\n# output files in an output format independent way. To create the layout file\n# that represents doxygen's defaults, run doxygen with the -l option. You can\n# optionally specify a file name after the option, if omitted DoxygenLayout.xml\n# will be used as the name of the layout file. See also section \"Changing the\n# layout of pages\" for information.\n#\n# Note that if you run doxygen from a directory containing a file called\n# DoxygenLayout.xml, doxygen will parse it automatically even if the LAYOUT_FILE\n# tag is left empty.\n\nLAYOUT_FILE            =\n\n# The CITE_BIB_FILES tag can be used to specify one or more bib files containing\n# the reference definitions. This must be a list of .bib files. The .bib\n# extension is automatically appended if omitted. This requires the bibtex tool\n# to be installed. See also https://en.wikipedia.org/wiki/BibTeX for more info.\n# For LaTeX the style of the bibliography can be controlled using\n# LATEX_BIB_STYLE. To use this feature you need bibtex and perl available in the\n# search path. See also \\cite for info how to create references.\n\nCITE_BIB_FILES         =\n\n#---------------------------------------------------------------------------\n# Configuration options related to warning and progress messages\n#---------------------------------------------------------------------------\n\n# The QUIET tag can be used to turn on/off the messages that are generated to\n# standard output by doxygen. If QUIET is set to YES this implies that the\n# messages are off.\n# The default value is: NO.\n\nQUIET                  = NO\n\n# The WARNINGS tag can be used to turn on/off the warning messages that are\n# generated to standard error (stderr) by doxygen. If WARNINGS is set to YES\n# this implies that the warnings are on.\n#\n# Tip: Turn warnings on while writing the documentation.\n# The default value is: YES.\n\nWARNINGS               = YES\n\n# If the WARN_IF_UNDOCUMENTED tag is set to YES then doxygen will generate\n# warnings for undocumented members. If EXTRACT_ALL is set to YES then this flag\n# will automatically be disabled.\n# The default value is: YES.\n\nWARN_IF_UNDOCUMENTED   = YES\n\n# If the WARN_IF_DOC_ERROR tag is set to YES, doxygen will generate warnings for\n# potential errors in the documentation, such as documenting some parameters in\n# a documented function twice, or documenting parameters that don't exist or\n# using markup commands wrongly.\n# The default value is: YES.\n\nWARN_IF_DOC_ERROR      = YES\n\n# If WARN_IF_INCOMPLETE_DOC is set to YES, doxygen will warn about incomplete\n# function parameter documentation. If set to NO, doxygen will accept that some\n# parameters have no documentation without warning.\n# The default value is: YES.\n\nWARN_IF_INCOMPLETE_DOC = YES\n\n# This WARN_NO_PARAMDOC option can be enabled to get warnings for functions that\n# are documented, but have no documentation for their parameters or return\n# value. If set to NO, doxygen will only warn about wrong parameter\n# documentation, but not about the absence of documentation. If EXTRACT_ALL is\n# set to YES then this flag will automatically be disabled. See also\n# WARN_IF_INCOMPLETE_DOC\n# The default value is: NO.\n\nWARN_NO_PARAMDOC       = NO\n\n# If the WARN_AS_ERROR tag is set to YES then doxygen will immediately stop when\n# a warning is encountered. If the WARN_AS_ERROR tag is set to FAIL_ON_WARNINGS\n# then doxygen will continue running as if WARN_AS_ERROR tag is set to NO, but\n# at the end of the doxygen process doxygen will return with a non-zero status.\n# Possible values are: NO, YES and FAIL_ON_WARNINGS.\n# The default value is: NO.\n\nWARN_AS_ERROR          = NO\n\n# The WARN_FORMAT tag determines the format of the warning messages that doxygen\n# can produce. The string should contain the $file, $line, and $text tags, which\n# will be replaced by the file and line number from which the warning originated\n# and the warning text. Optionally the format may contain $version, which will\n# be replaced by the version of the file (if it could be obtained via\n# FILE_VERSION_FILTER)\n# The default value is: $file:$line: $text.\n\nWARN_FORMAT            = \"$file:$line: $text\"\n\n# The WARN_LOGFILE tag can be used to specify a file to which warning and error\n# messages should be written. If left blank the output is written to standard\n# error (stderr).\n\nWARN_LOGFILE           =\n\n#---------------------------------------------------------------------------\n# Configuration options related to the input files\n#---------------------------------------------------------------------------\n\n# The INPUT tag is used to specify the files and/or directories that contain\n# documented source files. You may enter file names like myfile.cpp or\n# directories like /usr/src/myproject. Separate the files or directories with\n# spaces. See also FILE_PATTERNS and EXTENSION_MAPPING\n# Note: If this tag is empty the current directory is searched.\n\nINPUT                  = ../../application \\\n                         ../../libnnp \\\n                         ../../libnnpif \\\n                         ../../libnnptrain \\\n                         ../../interface\n\n# This tag can be used to specify the character encoding of the source files\n# that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses\n# libiconv (or the iconv built into libc) for the transcoding. See the libiconv\n# documentation (see:\n# https://www.gnu.org/software/libiconv/) for the list of possible encodings.\n# The default value is: UTF-8.\n\nINPUT_ENCODING         = UTF-8\n\n# If the value of the INPUT tag contains directories, you can use the\n# FILE_PATTERNS tag to specify one or more wildcard patterns (like *.cpp and\n# *.h) to filter out the source-files in the directories.\n#\n# Note that for custom extensions or not directly supported extensions you also\n# need to set EXTENSION_MAPPING for the extension otherwise the files are not\n# read by doxygen.\n#\n# Note the list of default checked file patterns might differ from the list of\n# default file extension mappings.\n#\n# If left blank the following patterns are tested:*.c, *.cc, *.cxx, *.cpp,\n# *.c++, *.java, *.ii, *.ixx, *.ipp, *.i++, *.inl, *.idl, *.ddl, *.odl, *.h,\n# *.hh, *.hxx, *.hpp, *.h++, *.l, *.cs, *.d, *.php, *.php4, *.php5, *.phtml,\n# *.inc, *.m, *.markdown, *.md, *.mm, *.dox (to be provided as doxygen C\n# comment), *.py, *.pyw, *.f90, *.f95, *.f03, *.f08, *.f18, *.f, *.for, *.vhd,\n# *.vhdl, *.ucf, *.qsf and *.ice.\n\nFILE_PATTERNS          = *.cpp \\\n                         *.h \\\n                         *.py \\\n                         *.pyx \\\n                         *.pxd \\\n                         *.md\n\n# The RECURSIVE tag can be used to specify whether or not subdirectories should\n# be searched for input files as well.\n# The default value is: NO.\n\nRECURSIVE              = YES\n\n# The EXCLUDE tag can be used to specify files and/or directories that should be\n# excluded from the INPUT source files. This way you can easily exclude a\n# subdirectory from a directory tree whose root is specified with the INPUT tag.\n#\n# Note that relative paths are relative to the directory from which doxygen is\n# run.\n\nEXCLUDE                = ../../interface/lammps-hdnnp\n\n# The EXCLUDE_SYMLINKS tag can be used to select whether or not files or\n# directories that are symbolic links (a Unix file system feature) are excluded\n# from the input.\n# The default value is: NO.\n\nEXCLUDE_SYMLINKS       = NO\n\n# If the value of the INPUT tag contains directories, you can use the\n# EXCLUDE_PATTERNS tag to specify one or more wildcard patterns to exclude\n# certain files from those directories.\n#\n# Note that the wildcards are matched against the file with absolute path, so to\n# exclude all test directories for example use the pattern */test/*\n\nEXCLUDE_PATTERNS       =\n\n# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names\n# (namespaces, classes, functions, etc.) that should be excluded from the\n# output. The symbol name can be a fully qualified name, a word, or if the\n# wildcard * is used, a substring. Examples: ANamespace, AClass,\n# AClass::ANamespace, ANamespace::*Test\n#\n# Note that the wildcards are matched against the file with absolute path, so to\n# exclude all test directories use the pattern */test/*\n\nEXCLUDE_SYMBOLS        =\n\n# The EXAMPLE_PATH tag can be used to specify one or more files or directories\n# that contain example code fragments that are included (see the \\include\n# command).\n\nEXAMPLE_PATH           =\n\n# If the value of the EXAMPLE_PATH tag contains directories, you can use the\n# EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp and\n# *.h) to filter out the source-files in the directories. If left blank all\n# files are included.\n\nEXAMPLE_PATTERNS       =\n\n# If the EXAMPLE_RECURSIVE tag is set to YES then subdirectories will be\n# searched for input files to be used with the \\include or \\dontinclude commands\n# irrespective of the value of the RECURSIVE tag.\n# The default value is: NO.\n\nEXAMPLE_RECURSIVE      = NO\n\n# The IMAGE_PATH tag can be used to specify one or more files or directories\n# that contain images that are to be included in the documentation (see the\n# \\image command).\n\nIMAGE_PATH             = ./\n\n# The INPUT_FILTER tag can be used to specify a program that doxygen should\n# invoke to filter for each input file. Doxygen will invoke the filter program\n# by executing (via popen()) the command:\n#\n# <filter> <input-file>\n#\n# where <filter> is the value of the INPUT_FILTER tag, and <input-file> is the\n# name of an input file. Doxygen will then use the output that the filter\n# program writes to standard output. If FILTER_PATTERNS is specified, this tag\n# will be ignored.\n#\n# Note that the filter must not add or remove lines; it is applied before the\n# code is scanned, but not when the output code is generated. If lines are added\n# or removed, the anchors will not be placed correctly.\n#\n# Note that for custom extensions or not directly supported extensions you also\n# need to set EXTENSION_MAPPING for the extension otherwise the files are not\n# properly processed by doxygen.\n\nINPUT_FILTER           =\n\n# The FILTER_PATTERNS tag can be used to specify filters on a per file pattern\n# basis. Doxygen will compare the file name with each pattern and apply the\n# filter if there is a match. The filters are a list of the form: pattern=filter\n# (like *.cpp=my_cpp_filter). See INPUT_FILTER for further information on how\n# filters are used. If the FILTER_PATTERNS tag is empty or if none of the\n# patterns match the file name, INPUT_FILTER is applied.\n#\n# Note that for custom extensions or not directly supported extensions you also\n# need to set EXTENSION_MAPPING for the extension otherwise the files are not\n# properly processed by doxygen.\n\nFILTER_PATTERNS        =\n\n# If the FILTER_SOURCE_FILES tag is set to YES, the input filter (if set using\n# INPUT_FILTER) will also be used to filter the input files that are used for\n# producing the source files to browse (i.e. when SOURCE_BROWSER is set to YES).\n# The default value is: NO.\n\nFILTER_SOURCE_FILES    = NO\n\n# The FILTER_SOURCE_PATTERNS tag can be used to specify source filters per file\n# pattern. A pattern will override the setting for FILTER_PATTERN (if any) and\n# it is also possible to disable source filtering for a specific pattern using\n# *.ext= (so without naming a filter).\n# This tag requires that the tag FILTER_SOURCE_FILES is set to YES.\n\nFILTER_SOURCE_PATTERNS =\n\n# If the USE_MDFILE_AS_MAINPAGE tag refers to the name of a markdown file that\n# is part of the input, its contents will be placed on the main page\n# (index.html). This can be useful if you have a project on for instance GitHub\n# and want to reuse the introduction page also for the doxygen output.\n\nUSE_MDFILE_AS_MAINPAGE = ./README.md\n\n#---------------------------------------------------------------------------\n# Configuration options related to source browsing\n#---------------------------------------------------------------------------\n\n# If the SOURCE_BROWSER tag is set to YES then a list of source files will be\n# generated. Documented entities will be cross-referenced with these sources.\n#\n# Note: To get rid of all source code in the generated output, make sure that\n# also VERBATIM_HEADERS is set to NO.\n# The default value is: NO.\n\nSOURCE_BROWSER         = YES\n\n# Setting the INLINE_SOURCES tag to YES will include the body of functions,\n# classes and enums directly into the documentation.\n# The default value is: NO.\n\nINLINE_SOURCES         = YES\n\n# Setting the STRIP_CODE_COMMENTS tag to YES will instruct doxygen to hide any\n# special comment blocks from generated source code fragments. Normal C, C++ and\n# Fortran comments will always remain visible.\n# The default value is: YES.\n\nSTRIP_CODE_COMMENTS    = YES\n\n# If the REFERENCED_BY_RELATION tag is set to YES then for each documented\n# entity all documented functions referencing it will be listed.\n# The default value is: NO.\n\nREFERENCED_BY_RELATION = YES\n\n# If the REFERENCES_RELATION tag is set to YES then for each documented function\n# all documented entities called/used by that function will be listed.\n# The default value is: NO.\n\nREFERENCES_RELATION    = YES\n\n# If the REFERENCES_LINK_SOURCE tag is set to YES and SOURCE_BROWSER tag is set\n# to YES then the hyperlinks from functions in REFERENCES_RELATION and\n# REFERENCED_BY_RELATION lists will link to the source code. Otherwise they will\n# link to the documentation.\n# The default value is: YES.\n\nREFERENCES_LINK_SOURCE = NO\n\n# If SOURCE_TOOLTIPS is enabled (the default) then hovering a hyperlink in the\n# source code will show a tooltip with additional information such as prototype,\n# brief description and links to the definition and documentation. Since this\n# will make the HTML file larger and loading of large files a bit slower, you\n# can opt to disable this feature.\n# The default value is: YES.\n# This tag requires that the tag SOURCE_BROWSER is set to YES.\n\nSOURCE_TOOLTIPS        = YES\n\n# If the USE_HTAGS tag is set to YES then the references to source code will\n# point to the HTML generated by the htags(1) tool instead of doxygen built-in\n# source browser. The htags tool is part of GNU's global source tagging system\n# (see https://www.gnu.org/software/global/global.html). You will need version\n# 4.8.6 or higher.\n#\n# To use it do the following:\n# - Install the latest version of global\n# - Enable SOURCE_BROWSER and USE_HTAGS in the configuration file\n# - Make sure the INPUT points to the root of the source tree\n# - Run doxygen as normal\n#\n# Doxygen will invoke htags (and that will in turn invoke gtags), so these\n# tools must be available from the command line (i.e. in the search path).\n#\n# The result: instead of the source browser generated by doxygen, the links to\n# source code will now point to the output of htags.\n# The default value is: NO.\n# This tag requires that the tag SOURCE_BROWSER is set to YES.\n\nUSE_HTAGS              = NO\n\n# If the VERBATIM_HEADERS tag is set the YES then doxygen will generate a\n# verbatim copy of the header file for each class for which an include is\n# specified. Set to NO to disable this.\n# See also: Section \\class.\n# The default value is: YES.\n\nVERBATIM_HEADERS       = YES\n\n#---------------------------------------------------------------------------\n# Configuration options related to the alphabetical class index\n#---------------------------------------------------------------------------\n\n# If the ALPHABETICAL_INDEX tag is set to YES, an alphabetical index of all\n# compounds will be generated. Enable this if the project contains a lot of\n# classes, structs, unions or interfaces.\n# The default value is: YES.\n\nALPHABETICAL_INDEX     = YES\n\n# In case all classes in a project start with a common prefix, all classes will\n# be put under the same header in the alphabetical index. The IGNORE_PREFIX tag\n# can be used to specify a prefix (or a list of prefixes) that should be ignored\n# while generating the index headers.\n# This tag requires that the tag ALPHABETICAL_INDEX is set to YES.\n\nIGNORE_PREFIX          =\n\n#---------------------------------------------------------------------------\n# Configuration options related to the HTML output\n#---------------------------------------------------------------------------\n\n# If the GENERATE_HTML tag is set to YES, doxygen will generate HTML output\n# The default value is: YES.\n\nGENERATE_HTML          = YES\n\n# The HTML_OUTPUT tag is used to specify where the HTML docs will be put. If a\n# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of\n# it.\n# The default directory is: html.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_OUTPUT            = html\n\n# The HTML_FILE_EXTENSION tag can be used to specify the file extension for each\n# generated HTML page (for example: .htm, .php, .asp).\n# The default value is: .html.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_FILE_EXTENSION    = .html\n\n# The HTML_HEADER tag can be used to specify a user-defined HTML header file for\n# each generated HTML page. If the tag is left blank doxygen will generate a\n# standard header.\n#\n# To get valid HTML the header file that includes any scripts and style sheets\n# that doxygen needs, which is dependent on the configuration options used (e.g.\n# the setting GENERATE_TREEVIEW). It is highly recommended to start with a\n# default header using\n# doxygen -w html new_header.html new_footer.html new_stylesheet.css\n# YourConfigFile\n# and then modify the file new_header.html. See also section \"Doxygen usage\"\n# for information on how to generate the default header that doxygen normally\n# uses.\n# Note: The header is subject to change so you typically have to regenerate the\n# default header when upgrading to a newer version of doxygen. For a description\n# of the possible markers and block names see the documentation.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_HEADER            =\n\n# The HTML_FOOTER tag can be used to specify a user-defined HTML footer for each\n# generated HTML page. If the tag is left blank doxygen will generate a standard\n# footer. See HTML_HEADER for more information on how to generate a default\n# footer and what special commands can be used inside the footer. See also\n# section \"Doxygen usage\" for information on how to generate the default footer\n# that doxygen normally uses.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_FOOTER            =\n\n# The HTML_STYLESHEET tag can be used to specify a user-defined cascading style\n# sheet that is used by each HTML page. It can be used to fine-tune the look of\n# the HTML output. If left blank doxygen will generate a default style sheet.\n# See also section \"Doxygen usage\" for information on how to generate the style\n# sheet that doxygen normally uses.\n# Note: It is recommended to use HTML_EXTRA_STYLESHEET instead of this tag, as\n# it is more robust and this tag (HTML_STYLESHEET) will in the future become\n# obsolete.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_STYLESHEET        =\n\n# The HTML_EXTRA_STYLESHEET tag can be used to specify additional user-defined\n# cascading style sheets that are included after the standard style sheets\n# created by doxygen. Using this option one can overrule certain style aspects.\n# This is preferred over using HTML_STYLESHEET since it does not replace the\n# standard style sheet and is therefore more robust against future updates.\n# Doxygen will copy the style sheet files to the output directory.\n# Note: The order of the extra style sheet files is of importance (e.g. the last\n# style sheet in the list overrules the setting of the previous ones in the\n# list). For an example see the documentation.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_EXTRA_STYLESHEET  = ./theme.css\n\n# The HTML_EXTRA_FILES tag can be used to specify one or more extra images or\n# other source files which should be copied to the HTML output directory. Note\n# that these files will be copied to the base HTML output directory. Use the\n# $relpath^ marker in the HTML_HEADER and/or HTML_FOOTER files to load these\n# files. In the HTML_STYLESHEET file, use the file name only. Also note that the\n# files will be copied as-is; there are no commands or markers available.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_EXTRA_FILES       =\n\n# The HTML_COLORSTYLE_HUE tag controls the color of the HTML output. Doxygen\n# will adjust the colors in the style sheet and background images according to\n# this color. Hue is specified as an angle on a color-wheel, see\n# https://en.wikipedia.org/wiki/Hue for more information. For instance the value\n# 0 represents red, 60 is yellow, 120 is green, 180 is cyan, 240 is blue, 300\n# purple, and 360 is red again.\n# Minimum value: 0, maximum value: 359, default value: 220.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_COLORSTYLE_HUE    = 220\n\n# The HTML_COLORSTYLE_SAT tag controls the purity (or saturation) of the colors\n# in the HTML output. For a value of 0 the output will use gray-scales only. A\n# value of 255 will produce the most vivid colors.\n# Minimum value: 0, maximum value: 255, default value: 100.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_COLORSTYLE_SAT    = 100\n\n# The HTML_COLORSTYLE_GAMMA tag controls the gamma correction applied to the\n# luminance component of the colors in the HTML output. Values below 100\n# gradually make the output lighter, whereas values above 100 make the output\n# darker. The value divided by 100 is the actual gamma applied, so 80 represents\n# a gamma of 0.8, The value 220 represents a gamma of 2.2, and 100 does not\n# change the gamma.\n# Minimum value: 40, maximum value: 240, default value: 80.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_COLORSTYLE_GAMMA  = 80\n\n# If the HTML_TIMESTAMP tag is set to YES then the footer of each generated HTML\n# page will contain the date and time when the page was generated. Setting this\n# to YES can help to show when doxygen was last run and thus if the\n# documentation is up to date.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_TIMESTAMP         = YES\n\n# If the HTML_DYNAMIC_MENUS tag is set to YES then the generated HTML\n# documentation will contain a main index with vertical navigation menus that\n# are dynamically created via JavaScript. If disabled, the navigation index will\n# consists of multiple levels of tabs that are statically embedded in every HTML\n# page. Disable this option to support browsers that do not have JavaScript,\n# like the Qt help browser.\n# The default value is: YES.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_DYNAMIC_MENUS     = YES\n\n# If the HTML_DYNAMIC_SECTIONS tag is set to YES then the generated HTML\n# documentation will contain sections that can be hidden and shown after the\n# page has loaded.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_DYNAMIC_SECTIONS  = NO\n\n# With HTML_INDEX_NUM_ENTRIES one can control the preferred number of entries\n# shown in the various tree structured indices initially; the user can expand\n# and collapse entries dynamically later on. Doxygen will expand the tree to\n# such a level that at most the specified number of entries are visible (unless\n# a fully collapsed tree already exceeds this amount). So setting the number of\n# entries 1 will produce a full collapsed tree by default. 0 is a special value\n# representing an infinite number of entries and will result in a full expanded\n# tree by default.\n# Minimum value: 0, maximum value: 9999, default value: 100.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_INDEX_NUM_ENTRIES = 100\n\n# If the GENERATE_DOCSET tag is set to YES, additional index files will be\n# generated that can be used as input for Apple's Xcode 3 integrated development\n# environment (see:\n# https://developer.apple.com/xcode/), introduced with OSX 10.5 (Leopard). To\n# create a documentation set, doxygen will generate a Makefile in the HTML\n# output directory. Running make will produce the docset in that directory and\n# running make install will install the docset in\n# ~/Library/Developer/Shared/Documentation/DocSets so that Xcode will find it at\n# startup. See https://developer.apple.com/library/archive/featuredarticles/Doxy\n# genXcode/_index.html for more information.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nGENERATE_DOCSET        = NO\n\n# This tag determines the name of the docset feed. A documentation feed provides\n# an umbrella under which multiple documentation sets from a single provider\n# (such as a company or product suite) can be grouped.\n# The default value is: Doxygen generated docs.\n# This tag requires that the tag GENERATE_DOCSET is set to YES.\n\nDOCSET_FEEDNAME        = \"Doxygen generated docs\"\n\n# This tag specifies a string that should uniquely identify the documentation\n# set bundle. This should be a reverse domain-name style string, e.g.\n# com.mycompany.MyDocSet. Doxygen will append .docset to the name.\n# The default value is: org.doxygen.Project.\n# This tag requires that the tag GENERATE_DOCSET is set to YES.\n\nDOCSET_BUNDLE_ID       = org.doxygen.Project\n\n# The DOCSET_PUBLISHER_ID tag specifies a string that should uniquely identify\n# the documentation publisher. This should be a reverse domain-name style\n# string, e.g. com.mycompany.MyDocSet.documentation.\n# The default value is: org.doxygen.Publisher.\n# This tag requires that the tag GENERATE_DOCSET is set to YES.\n\nDOCSET_PUBLISHER_ID    = org.doxygen.Publisher\n\n# The DOCSET_PUBLISHER_NAME tag identifies the documentation publisher.\n# The default value is: Publisher.\n# This tag requires that the tag GENERATE_DOCSET is set to YES.\n\nDOCSET_PUBLISHER_NAME  = Publisher\n\n# If the GENERATE_HTMLHELP tag is set to YES then doxygen generates three\n# additional HTML index files: index.hhp, index.hhc, and index.hhk. The\n# index.hhp is a project file that can be read by Microsoft's HTML Help Workshop\n# on Windows. In the beginning of 2021 Microsoft took the original page, with\n# a.o. the download links, offline the HTML help workshop was already many years\n# in maintenance mode). You can download the HTML help workshop from the web\n# archives at Installation executable (see:\n# http://web.archive.org/web/20160201063255/http://download.microsoft.com/downlo\n# ad/0/A/9/0A939EF6-E31C-430F-A3DF-DFAE7960D564/htmlhelp.exe).\n#\n# The HTML Help Workshop contains a compiler that can convert all HTML output\n# generated by doxygen into a single compiled HTML file (.chm). Compiled HTML\n# files are now used as the Windows 98 help format, and will replace the old\n# Windows help format (.hlp) on all Windows platforms in the future. Compressed\n# HTML files also contain an index, a table of contents, and you can search for\n# words in the documentation. The HTML workshop also contains a viewer for\n# compressed HTML files.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nGENERATE_HTMLHELP      = NO\n\n# The CHM_FILE tag can be used to specify the file name of the resulting .chm\n# file. You can add a path in front of the file if the result should not be\n# written to the html output directory.\n# This tag requires that the tag GENERATE_HTMLHELP is set to YES.\n\nCHM_FILE               =\n\n# The HHC_LOCATION tag can be used to specify the location (absolute path\n# including file name) of the HTML help compiler (hhc.exe). If non-empty,\n# doxygen will try to run the HTML help compiler on the generated index.hhp.\n# The file has to be specified with full path.\n# This tag requires that the tag GENERATE_HTMLHELP is set to YES.\n\nHHC_LOCATION           =\n\n# The GENERATE_CHI flag controls if a separate .chi index file is generated\n# (YES) or that it should be included in the main .chm file (NO).\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTMLHELP is set to YES.\n\nGENERATE_CHI           = NO\n\n# The CHM_INDEX_ENCODING is used to encode HtmlHelp index (hhk), content (hhc)\n# and project file content.\n# This tag requires that the tag GENERATE_HTMLHELP is set to YES.\n\nCHM_INDEX_ENCODING     =\n\n# The BINARY_TOC flag controls whether a binary table of contents is generated\n# (YES) or a normal table of contents (NO) in the .chm file. Furthermore it\n# enables the Previous and Next buttons.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTMLHELP is set to YES.\n\nBINARY_TOC             = NO\n\n# The TOC_EXPAND flag can be set to YES to add extra items for group members to\n# the table of contents of the HTML help documentation and to the tree view.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTMLHELP is set to YES.\n\nTOC_EXPAND             = NO\n\n# If the GENERATE_QHP tag is set to YES and both QHP_NAMESPACE and\n# QHP_VIRTUAL_FOLDER are set, an additional index file will be generated that\n# can be used as input for Qt's qhelpgenerator to generate a Qt Compressed Help\n# (.qch) of the generated HTML documentation.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nGENERATE_QHP           = NO\n\n# If the QHG_LOCATION tag is specified, the QCH_FILE tag can be used to specify\n# the file name of the resulting .qch file. The path specified is relative to\n# the HTML output folder.\n# This tag requires that the tag GENERATE_QHP is set to YES.\n\nQCH_FILE               =\n\n# The QHP_NAMESPACE tag specifies the namespace to use when generating Qt Help\n# Project output. For more information please see Qt Help Project / Namespace\n# (see:\n# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#namespace).\n# The default value is: org.doxygen.Project.\n# This tag requires that the tag GENERATE_QHP is set to YES.\n\nQHP_NAMESPACE          = org.doxygen.Project\n\n# The QHP_VIRTUAL_FOLDER tag specifies the namespace to use when generating Qt\n# Help Project output. For more information please see Qt Help Project / Virtual\n# Folders (see:\n# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#virtual-folders).\n# The default value is: doc.\n# This tag requires that the tag GENERATE_QHP is set to YES.\n\nQHP_VIRTUAL_FOLDER     = doc\n\n# If the QHP_CUST_FILTER_NAME tag is set, it specifies the name of a custom\n# filter to add. For more information please see Qt Help Project / Custom\n# Filters (see:\n# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#custom-filters).\n# This tag requires that the tag GENERATE_QHP is set to YES.\n\nQHP_CUST_FILTER_NAME   =\n\n# The QHP_CUST_FILTER_ATTRS tag specifies the list of the attributes of the\n# custom filter to add. For more information please see Qt Help Project / Custom\n# Filters (see:\n# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#custom-filters).\n# This tag requires that the tag GENERATE_QHP is set to YES.\n\nQHP_CUST_FILTER_ATTRS  =\n\n# The QHP_SECT_FILTER_ATTRS tag specifies the list of the attributes this\n# project's filter section matches. Qt Help Project / Filter Attributes (see:\n# https://doc.qt.io/archives/qt-4.8/qthelpproject.html#filter-attributes).\n# This tag requires that the tag GENERATE_QHP is set to YES.\n\nQHP_SECT_FILTER_ATTRS  =\n\n# The QHG_LOCATION tag can be used to specify the location (absolute path\n# including file name) of Qt's qhelpgenerator. If non-empty doxygen will try to\n# run qhelpgenerator on the generated .qhp file.\n# This tag requires that the tag GENERATE_QHP is set to YES.\n\nQHG_LOCATION           =\n\n# If the GENERATE_ECLIPSEHELP tag is set to YES, additional index files will be\n# generated, together with the HTML files, they form an Eclipse help plugin. To\n# install this plugin and make it available under the help contents menu in\n# Eclipse, the contents of the directory containing the HTML and XML files needs\n# to be copied into the plugins directory of eclipse. The name of the directory\n# within the plugins directory should be the same as the ECLIPSE_DOC_ID value.\n# After copying Eclipse needs to be restarted before the help appears.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nGENERATE_ECLIPSEHELP   = NO\n\n# A unique identifier for the Eclipse help plugin. When installing the plugin\n# the directory name containing the HTML and XML files should also have this\n# name. Each documentation set should have its own identifier.\n# The default value is: org.doxygen.Project.\n# This tag requires that the tag GENERATE_ECLIPSEHELP is set to YES.\n\nECLIPSE_DOC_ID         = org.doxygen.Project\n\n# If you want full control over the layout of the generated HTML pages it might\n# be necessary to disable the index and replace it with your own. The\n# DISABLE_INDEX tag can be used to turn on/off the condensed index (tabs) at top\n# of each HTML page. A value of NO enables the index and the value YES disables\n# it. Since the tabs in the index contain the same information as the navigation\n# tree, you can set this option to YES if you also set GENERATE_TREEVIEW to YES.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nDISABLE_INDEX          = NO\n\n# The GENERATE_TREEVIEW tag is used to specify whether a tree-like index\n# structure should be generated to display hierarchical information. If the tag\n# value is set to YES, a side panel will be generated containing a tree-like\n# index structure (just like the one that is generated for HTML Help). For this\n# to work a browser that supports JavaScript, DHTML, CSS and frames is required\n# (i.e. any modern browser). Windows users are probably better off using the\n# HTML help feature. Via custom style sheets (see HTML_EXTRA_STYLESHEET) one can\n# further fine tune the look of the index (see \"Fine-tuning the output\"). As an\n# example, the default style sheet generated by doxygen has an example that\n# shows how to put an image at the root of the tree instead of the PROJECT_NAME.\n# Since the tree basically has the same information as the tab index, you could\n# consider setting DISABLE_INDEX to YES when enabling this option.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nGENERATE_TREEVIEW      = YES\n\n# When both GENERATE_TREEVIEW and DISABLE_INDEX are set to YES, then the\n# FULL_SIDEBAR option determines if the side bar is limited to only the treeview\n# area (value NO) or if it should extend to the full height of the window (value\n# YES). Setting this to YES gives a layout similar to\n# https://docs.readthedocs.io with more room for contents, but less room for the\n# project logo, title, and description. If either GENERATOR_TREEVIEW or\n# DISABLE_INDEX is set to NO, this option has no effect.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nFULL_SIDEBAR           = NO\n\n# The ENUM_VALUES_PER_LINE tag can be used to set the number of enum values that\n# doxygen will group on one line in the generated HTML documentation.\n#\n# Note that a value of 0 will completely suppress the enum values from appearing\n# in the overview section.\n# Minimum value: 0, maximum value: 20, default value: 4.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nENUM_VALUES_PER_LINE   = 4\n\n# If the treeview is enabled (see GENERATE_TREEVIEW) then this tag can be used\n# to set the initial width (in pixels) of the frame in which the tree is shown.\n# Minimum value: 0, maximum value: 1500, default value: 250.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nTREEVIEW_WIDTH         = 250\n\n# If the EXT_LINKS_IN_WINDOW option is set to YES, doxygen will open links to\n# external symbols imported via tag files in a separate window.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nEXT_LINKS_IN_WINDOW    = NO\n\n# If the HTML_FORMULA_FORMAT option is set to svg, doxygen will use the pdf2svg\n# tool (see https://github.com/dawbarton/pdf2svg) or inkscape (see\n# https://inkscape.org) to generate formulas as SVG images instead of PNGs for\n# the HTML output. These images will generally look nicer at scaled resolutions.\n# Possible values are: png (the default) and svg (looks nicer but requires the\n# pdf2svg or inkscape tool).\n# The default value is: png.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nHTML_FORMULA_FORMAT    = png\n\n# Use this tag to change the font size of LaTeX formulas included as images in\n# the HTML documentation. When you change the font size after a successful\n# doxygen run you need to manually remove any form_*.png images from the HTML\n# output directory to force them to be regenerated.\n# Minimum value: 8, maximum value: 50, default value: 10.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nFORMULA_FONTSIZE       = 14\n\n# Use the FORMULA_TRANSPARENT tag to determine whether or not the images\n# generated for formulas are transparent PNGs. Transparent PNGs are not\n# supported properly for IE 6.0, but are supported on all modern browsers.\n#\n# Note that when changing this option you need to delete any form_*.png files in\n# the HTML output directory before the changes have effect.\n# The default value is: YES.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nFORMULA_TRANSPARENT    = YES\n\n# The FORMULA_MACROFILE can contain LaTeX \\newcommand and \\renewcommand commands\n# to create new LaTeX commands to be used in formulas as building blocks. See\n# the section \"Including formulas\" for details.\n\nFORMULA_MACROFILE      =\n\n# Enable the USE_MATHJAX option to render LaTeX formulas using MathJax (see\n# https://www.mathjax.org) which uses client side JavaScript for the rendering\n# instead of using pre-rendered bitmaps. Use this if you do not have LaTeX\n# installed or if you want to formulas look prettier in the HTML output. When\n# enabled you may also need to install MathJax separately and configure the path\n# to it using the MATHJAX_RELPATH option.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nUSE_MATHJAX            = YES\n\n# With MATHJAX_VERSION it is possible to specify the MathJax version to be used.\n# Note that the different versions of MathJax have different requirements with\n# regards to the different settings, so it is possible that also other MathJax\n# settings have to be changed when switching between the different MathJax\n# versions.\n# Possible values are: MathJax_2 and MathJax_3.\n# The default value is: MathJax_2.\n# This tag requires that the tag USE_MATHJAX is set to YES.\n\nMATHJAX_VERSION        = MathJax_2\n\n# When MathJax is enabled you can set the default output format to be used for\n# the MathJax output. For more details about the output format see MathJax\n# version 2 (see:\n# http://docs.mathjax.org/en/v2.7-latest/output.html) and MathJax version 3\n# (see:\n# http://docs.mathjax.org/en/latest/web/components/output.html).\n# Possible values are: HTML-CSS (which is slower, but has the best\n# compatibility. This is the name for Mathjax version 2, for MathJax version 3\n# this will be translated into chtml), NativeMML (i.e. MathML. Only supported\n# for NathJax 2. For MathJax version 3 chtml will be used instead.), chtml (This\n# is the name for Mathjax version 3, for MathJax version 2 this will be\n# translated into HTML-CSS) and SVG.\n# The default value is: HTML-CSS.\n# This tag requires that the tag USE_MATHJAX is set to YES.\n\nMATHJAX_FORMAT         = HTML-CSS\n\n# When MathJax is enabled you need to specify the location relative to the HTML\n# output directory using the MATHJAX_RELPATH option. The destination directory\n# should contain the MathJax.js script. For instance, if the mathjax directory\n# is located at the same level as the HTML output directory, then\n# MATHJAX_RELPATH should be ../mathjax. The default value points to the MathJax\n# Content Delivery Network so you can quickly see the result without installing\n# MathJax. However, it is strongly recommended to install a local copy of\n# MathJax from https://www.mathjax.org before deployment. The default value is:\n# - in case of MathJax version 2: https://cdn.jsdelivr.net/npm/mathjax@2\n# - in case of MathJax version 3: https://cdn.jsdelivr.net/npm/mathjax@3\n# This tag requires that the tag USE_MATHJAX is set to YES.\n\nMATHJAX_RELPATH        =\n\n# The MATHJAX_EXTENSIONS tag can be used to specify one or more MathJax\n# extension names that should be enabled during MathJax rendering. For example\n# for MathJax version 2 (see\n# https://docs.mathjax.org/en/v2.7-latest/tex.html#tex-and-latex-extensions):\n# MATHJAX_EXTENSIONS = TeX/AMSmath TeX/AMSsymbols\n# For example for MathJax version 3 (see\n# http://docs.mathjax.org/en/latest/input/tex/extensions/index.html):\n# MATHJAX_EXTENSIONS = ams\n# This tag requires that the tag USE_MATHJAX is set to YES.\n\nMATHJAX_EXTENSIONS     = TeX/AMSmath TeX/AMSsymbols\n\n# The MATHJAX_CODEFILE tag can be used to specify a file with javascript pieces\n# of code that will be used on startup of the MathJax code. See the MathJax site\n# (see:\n# http://docs.mathjax.org/en/v2.7-latest/output.html) for more details. For an\n# example see the documentation.\n# This tag requires that the tag USE_MATHJAX is set to YES.\n\nMATHJAX_CODEFILE       =\n\n# When the SEARCHENGINE tag is enabled doxygen will generate a search box for\n# the HTML output. The underlying search engine uses javascript and DHTML and\n# should work on any modern browser. Note that when using HTML help\n# (GENERATE_HTMLHELP), Qt help (GENERATE_QHP), or docsets (GENERATE_DOCSET)\n# there is already a search function so this one should typically be disabled.\n# For large projects the javascript based search engine can be slow, then\n# enabling SERVER_BASED_SEARCH may provide a better solution. It is possible to\n# search using the keyboard; to jump to the search box use <access key> + S\n# (what the <access key> is depends on the OS and browser, but it is typically\n# <CTRL>, <ALT>/<option>, or both). Inside the search box use the <cursor down\n# key> to jump into the search results window, the results can be navigated\n# using the <cursor keys>. Press <Enter> to select an item or <escape> to cancel\n# the search. The filter options can be selected when the cursor is inside the\n# search box by pressing <Shift>+<cursor down>. Also here use the <cursor keys>\n# to select a filter and <Enter> or <escape> to activate or cancel the filter\n# option.\n# The default value is: YES.\n# This tag requires that the tag GENERATE_HTML is set to YES.\n\nSEARCHENGINE           = YES\n\n# When the SERVER_BASED_SEARCH tag is enabled the search engine will be\n# implemented using a web server instead of a web client using JavaScript. There\n# are two flavors of web server based searching depending on the EXTERNAL_SEARCH\n# setting. When disabled, doxygen will generate a PHP script for searching and\n# an index file used by the script. When EXTERNAL_SEARCH is enabled the indexing\n# and searching needs to be provided by external tools. See the section\n# \"External Indexing and Searching\" for details.\n# The default value is: NO.\n# This tag requires that the tag SEARCHENGINE is set to YES.\n\nSERVER_BASED_SEARCH    = NO\n\n# When EXTERNAL_SEARCH tag is enabled doxygen will no longer generate the PHP\n# script for searching. Instead the search results are written to an XML file\n# which needs to be processed by an external indexer. Doxygen will invoke an\n# external search engine pointed to by the SEARCHENGINE_URL option to obtain the\n# search results.\n#\n# Doxygen ships with an example indexer (doxyindexer) and search engine\n# (doxysearch.cgi) which are based on the open source search engine library\n# Xapian (see:\n# https://xapian.org/).\n#\n# See the section \"External Indexing and Searching\" for details.\n# The default value is: NO.\n# This tag requires that the tag SEARCHENGINE is set to YES.\n\nEXTERNAL_SEARCH        = NO\n\n# The SEARCHENGINE_URL should point to a search engine hosted by a web server\n# which will return the search results when EXTERNAL_SEARCH is enabled.\n#\n# Doxygen ships with an example indexer (doxyindexer) and search engine\n# (doxysearch.cgi) which are based on the open source search engine library\n# Xapian (see:\n# https://xapian.org/). See the section \"External Indexing and Searching\" for\n# details.\n# This tag requires that the tag SEARCHENGINE is set to YES.\n\nSEARCHENGINE_URL       =\n\n# When SERVER_BASED_SEARCH and EXTERNAL_SEARCH are both enabled the unindexed\n# search data is written to a file for indexing by an external tool. With the\n# SEARCHDATA_FILE tag the name of this file can be specified.\n# The default file is: searchdata.xml.\n# This tag requires that the tag SEARCHENGINE is set to YES.\n\nSEARCHDATA_FILE        = searchdata.xml\n\n# When SERVER_BASED_SEARCH and EXTERNAL_SEARCH are both enabled the\n# EXTERNAL_SEARCH_ID tag can be used as an identifier for the project. This is\n# useful in combination with EXTRA_SEARCH_MAPPINGS to search through multiple\n# projects and redirect the results back to the right project.\n# This tag requires that the tag SEARCHENGINE is set to YES.\n\nEXTERNAL_SEARCH_ID     =\n\n# The EXTRA_SEARCH_MAPPINGS tag can be used to enable searching through doxygen\n# projects other than the one defined by this configuration file, but that are\n# all added to the same external search index. Each project needs to have a\n# unique id set via EXTERNAL_SEARCH_ID. The search mapping then maps the id of\n# to a relative location where the documentation can be found. The format is:\n# EXTRA_SEARCH_MAPPINGS = tagname1=loc1 tagname2=loc2 ...\n# This tag requires that the tag SEARCHENGINE is set to YES.\n\nEXTRA_SEARCH_MAPPINGS  =\n\n#---------------------------------------------------------------------------\n# Configuration options related to the LaTeX output\n#---------------------------------------------------------------------------\n\n# If the GENERATE_LATEX tag is set to YES, doxygen will generate LaTeX output.\n# The default value is: YES.\n\nGENERATE_LATEX         = NO\n\n# The LATEX_OUTPUT tag is used to specify where the LaTeX docs will be put. If a\n# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of\n# it.\n# The default directory is: latex.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_OUTPUT           = latex\n\n# The LATEX_CMD_NAME tag can be used to specify the LaTeX command name to be\n# invoked.\n#\n# Note that when not enabling USE_PDFLATEX the default is latex when enabling\n# USE_PDFLATEX the default is pdflatex and when in the later case latex is\n# chosen this is overwritten by pdflatex. For specific output languages the\n# default can have been set differently, this depends on the implementation of\n# the output language.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_CMD_NAME         = latex\n\n# The MAKEINDEX_CMD_NAME tag can be used to specify the command name to generate\n# index for LaTeX.\n# Note: This tag is used in the Makefile / make.bat.\n# See also: LATEX_MAKEINDEX_CMD for the part in the generated output file\n# (.tex).\n# The default file is: makeindex.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nMAKEINDEX_CMD_NAME     = makeindex\n\n# The LATEX_MAKEINDEX_CMD tag can be used to specify the command name to\n# generate index for LaTeX. In case there is no backslash (\\) as first character\n# it will be automatically added in the LaTeX code.\n# Note: This tag is used in the generated output file (.tex).\n# See also: MAKEINDEX_CMD_NAME for the part in the Makefile / make.bat.\n# The default value is: makeindex.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_MAKEINDEX_CMD    = makeindex\n\n# If the COMPACT_LATEX tag is set to YES, doxygen generates more compact LaTeX\n# documents. This may be useful for small projects and may help to save some\n# trees in general.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nCOMPACT_LATEX          = NO\n\n# The PAPER_TYPE tag can be used to set the paper type that is used by the\n# printer.\n# Possible values are: a4 (210 x 297 mm), letter (8.5 x 11 inches), legal (8.5 x\n# 14 inches) and executive (7.25 x 10.5 inches).\n# The default value is: a4.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nPAPER_TYPE             = a4\n\n# The EXTRA_PACKAGES tag can be used to specify one or more LaTeX package names\n# that should be included in the LaTeX output. The package can be specified just\n# by its name or with the correct syntax as to be used with the LaTeX\n# \\usepackage command. To get the times font for instance you can specify :\n# EXTRA_PACKAGES=times or EXTRA_PACKAGES={times}\n# To use the option intlimits with the amsmath package you can specify:\n# EXTRA_PACKAGES=[intlimits]{amsmath}\n# If left blank no extra packages will be included.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nEXTRA_PACKAGES         = {amsmath}\n\n# The LATEX_HEADER tag can be used to specify a user-defined LaTeX header for\n# the generated LaTeX document. The header should contain everything until the\n# first chapter. If it is left blank doxygen will generate a standard header. It\n# is highly recommended to start with a default header using\n# doxygen -w latex new_header.tex new_footer.tex new_stylesheet.sty\n# and then modify the file new_header.tex. See also section \"Doxygen usage\" for\n# information on how to generate the default header that doxygen normally uses.\n#\n# Note: Only use a user-defined header if you know what you are doing!\n# Note: The header is subject to change so you typically have to regenerate the\n# default header when upgrading to a newer version of doxygen. The following\n# commands have a special meaning inside the header (and footer): For a\n# description of the possible markers and block names see the documentation.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_HEADER           =\n\n# The LATEX_FOOTER tag can be used to specify a user-defined LaTeX footer for\n# the generated LaTeX document. The footer should contain everything after the\n# last chapter. If it is left blank doxygen will generate a standard footer. See\n# LATEX_HEADER for more information on how to generate a default footer and what\n# special commands can be used inside the footer. See also section \"Doxygen\n# usage\" for information on how to generate the default footer that doxygen\n# normally uses. Note: Only use a user-defined footer if you know what you are\n# doing!\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_FOOTER           =\n\n# The LATEX_EXTRA_STYLESHEET tag can be used to specify additional user-defined\n# LaTeX style sheets that are included after the standard style sheets created\n# by doxygen. Using this option one can overrule certain style aspects. Doxygen\n# will copy the style sheet files to the output directory.\n# Note: The order of the extra style sheet files is of importance (e.g. the last\n# style sheet in the list overrules the setting of the previous ones in the\n# list).\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_EXTRA_STYLESHEET =\n\n# The LATEX_EXTRA_FILES tag can be used to specify one or more extra images or\n# other source files which should be copied to the LATEX_OUTPUT output\n# directory. Note that the files will be copied as-is; there are no commands or\n# markers available.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_EXTRA_FILES      =\n\n# If the PDF_HYPERLINKS tag is set to YES, the LaTeX that is generated is\n# prepared for conversion to PDF (using ps2pdf or pdflatex). The PDF file will\n# contain links (just like the HTML output) instead of page references. This\n# makes the output suitable for online browsing using a PDF viewer.\n# The default value is: YES.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nPDF_HYPERLINKS         = YES\n\n# If the USE_PDFLATEX tag is set to YES, doxygen will use the engine as\n# specified with LATEX_CMD_NAME to generate the PDF file directly from the LaTeX\n# files. Set this option to YES, to get a higher quality PDF documentation.\n#\n# See also section LATEX_CMD_NAME for selecting the engine.\n# The default value is: YES.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nUSE_PDFLATEX           = YES\n\n# If the LATEX_BATCHMODE tag is set to YES, doxygen will add the \\batchmode\n# command to the generated LaTeX files. This will instruct LaTeX to keep running\n# if errors occur, instead of asking the user for help.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_BATCHMODE        = NO\n\n# If the LATEX_HIDE_INDICES tag is set to YES then doxygen will not include the\n# index chapters (such as File Index, Compound Index, etc.) in the output.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_HIDE_INDICES     = NO\n\n# The LATEX_BIB_STYLE tag can be used to specify the style to use for the\n# bibliography, e.g. plainnat, or ieeetr. See\n# https://en.wikipedia.org/wiki/BibTeX and \\cite for more info.\n# The default value is: plain.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_BIB_STYLE        = plain\n\n# If the LATEX_TIMESTAMP tag is set to YES then the footer of each generated\n# page will contain the date and time when the page was generated. Setting this\n# to NO can help when comparing the output of multiple runs.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_TIMESTAMP        = NO\n\n# The LATEX_EMOJI_DIRECTORY tag is used to specify the (relative or absolute)\n# path from which the emoji images will be read. If a relative path is entered,\n# it will be relative to the LATEX_OUTPUT directory. If left blank the\n# LATEX_OUTPUT directory will be used.\n# This tag requires that the tag GENERATE_LATEX is set to YES.\n\nLATEX_EMOJI_DIRECTORY  =\n\n#---------------------------------------------------------------------------\n# Configuration options related to the RTF output\n#---------------------------------------------------------------------------\n\n# If the GENERATE_RTF tag is set to YES, doxygen will generate RTF output. The\n# RTF output is optimized for Word 97 and may not look too pretty with other RTF\n# readers/editors.\n# The default value is: NO.\n\nGENERATE_RTF           = NO\n\n# The RTF_OUTPUT tag is used to specify where the RTF docs will be put. If a\n# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of\n# it.\n# The default directory is: rtf.\n# This tag requires that the tag GENERATE_RTF is set to YES.\n\nRTF_OUTPUT             = rtf\n\n# If the COMPACT_RTF tag is set to YES, doxygen generates more compact RTF\n# documents. This may be useful for small projects and may help to save some\n# trees in general.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_RTF is set to YES.\n\nCOMPACT_RTF            = NO\n\n# If the RTF_HYPERLINKS tag is set to YES, the RTF that is generated will\n# contain hyperlink fields. The RTF file will contain links (just like the HTML\n# output) instead of page references. This makes the output suitable for online\n# browsing using Word or some other Word compatible readers that support those\n# fields.\n#\n# Note: WordPad (write) and others do not support links.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_RTF is set to YES.\n\nRTF_HYPERLINKS         = NO\n\n# Load stylesheet definitions from file. Syntax is similar to doxygen's\n# configuration file, i.e. a series of assignments. You only have to provide\n# replacements, missing definitions are set to their default value.\n#\n# See also section \"Doxygen usage\" for information on how to generate the\n# default style sheet that doxygen normally uses.\n# This tag requires that the tag GENERATE_RTF is set to YES.\n\nRTF_STYLESHEET_FILE    =\n\n# Set optional variables used in the generation of an RTF document. Syntax is\n# similar to doxygen's configuration file. A template extensions file can be\n# generated using doxygen -e rtf extensionFile.\n# This tag requires that the tag GENERATE_RTF is set to YES.\n\nRTF_EXTENSIONS_FILE    =\n\n#---------------------------------------------------------------------------\n# Configuration options related to the man page output\n#---------------------------------------------------------------------------\n\n# If the GENERATE_MAN tag is set to YES, doxygen will generate man pages for\n# classes and files.\n# The default value is: NO.\n\nGENERATE_MAN           = NO\n\n# The MAN_OUTPUT tag is used to specify where the man pages will be put. If a\n# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of\n# it. A directory man3 will be created inside the directory specified by\n# MAN_OUTPUT.\n# The default directory is: man.\n# This tag requires that the tag GENERATE_MAN is set to YES.\n\nMAN_OUTPUT             = man\n\n# The MAN_EXTENSION tag determines the extension that is added to the generated\n# man pages. In case the manual section does not start with a number, the number\n# 3 is prepended. The dot (.) at the beginning of the MAN_EXTENSION tag is\n# optional.\n# The default value is: .3.\n# This tag requires that the tag GENERATE_MAN is set to YES.\n\nMAN_EXTENSION          = .3\n\n# The MAN_SUBDIR tag determines the name of the directory created within\n# MAN_OUTPUT in which the man pages are placed. If defaults to man followed by\n# MAN_EXTENSION with the initial . removed.\n# This tag requires that the tag GENERATE_MAN is set to YES.\n\nMAN_SUBDIR             =\n\n# If the MAN_LINKS tag is set to YES and doxygen generates man output, then it\n# will generate one additional man file for each entity documented in the real\n# man page(s). These additional files only source the real man page, but without\n# them the man command would be unable to find the correct page.\n# The default value is: NO.\n# This tag requires that the tag GENERATE_MAN is set to YES.\n\nMAN_LINKS              = NO\n\n#---------------------------------------------------------------------------\n# Configuration options related to the XML output\n#---------------------------------------------------------------------------\n\n# If the GENERATE_XML tag is set to YES, doxygen will generate an XML file that\n# captures the structure of the code including all documentation.\n# The default value is: NO.\n\nGENERATE_XML           = YES\n\n# The XML_OUTPUT tag is used to specify where the XML pages will be put. If a\n# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of\n# it.\n# The default directory is: xml.\n# This tag requires that the tag GENERATE_XML is set to YES.\n\nXML_OUTPUT             = xml\n\n# If the XML_PROGRAMLISTING tag is set to YES, doxygen will dump the program\n# listings (including syntax highlighting and cross-referencing information) to\n# the XML output. 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  },
  {
    "path": "src/doc/doxygen/README.md",
    "content": "n2p2 - API documentation\n========================\n\nThis is the `n2p2` API documentation using Doxygen.\n\nThe remaining docs are located [here](../index.html).\n"
  },
  {
    "path": "src/doc/doxygen/makefile",
    "content": "#!/bin/make -f\n\nDOXYGEN_VERSION = \"Release_1_13_2\"\nTHEME_VERSION = \"v2.0.3\"\n\ndoc: doxygen theme.css\n\t./doxygen\n\nclean: clean-doxygen clean-theme\n\t$(RM) -r ../../../doc/doxygen/html\n\t$(RM) -r ../../../doc/doxygen/xml\n\ndoxygen:\n\tgit clone https://github.com/doxygen/doxygen.git src-doxygen\n\tcd src-doxygen && \\\n\tgit checkout ${DOXYGEN_VERSION} && \\\n\tmkdir build && \\\n\tcd build && \\\n\tcmake -G \"Unix Makefiles\" -DCMAKE_BUILD_TYPE=Release .. && \\\n\t$(MAKE) -j $(CORES) && \\\n\tcp bin/doxygen ../..\n\nclean-doxygen:\n\t$(RM) -r src-doxygen doxygen\n\ntheme.css:\n\tgit clone https://github.com/jothepro/doxygen-awesome-css.git src-theme\n\tcd src-theme && \\\n\tgit checkout ${THEME_VERSION} && \\\n\tcp doxygen-awesome.css ../theme.css\n\nclean-theme:\n\t$(RM) -r src-theme theme.css\n"
  },
  {
    "path": "src/doc/sphinx/Makefile",
    "content": "# Minimal makefile for Sphinx documentation\n#\n\n# You can set these variables from the command line.\nSPHINXOPTS    =\nSPHINXBUILD   = sphinx-build\nSPHINXPROJ    = n2p2-Aneuralnetworkpotentialpackage\nSOURCEDIR     = source\nBUILDDIR      = ../../../doc/sphinx/\n\n# Put it first so that \"make\" without argument is like \"make help\".\nhelp:\n\t@$(SPHINXBUILD) -M help \"$(SOURCEDIR)\" \"$(BUILDDIR)\" $(SPHINXOPTS) $(O)\n\n.PHONY: help Makefile clean\n\nclean:\n\t#rm -rf $(SOURCEDIR)/doxyoutput/ $(SOURCEDIR)/doc-exhale/\n\t@$(SPHINXBUILD) -M clean \"$(SOURCEDIR)\" \"$(BUILDDIR)\" $(SPHINXOPTS) $(O)\n\n# Catch-all target: route all unknown targets to Sphinx using the new\n# \"make mode\" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).\n%: Makefile\n\t@$(SPHINXBUILD) -M $@ \"$(SOURCEDIR)\" \"$(BUILDDIR)\" $(SPHINXOPTS) $(O)\n"
  },
  {
    "path": "src/doc/sphinx/source/about/authors.rst",
    "content": ".. _authors:\n\n.. include:: ../../../../../AUTHORS.rst\n"
  },
  {
    "path": "src/doc/sphinx/source/about/changelog.rst",
    "content": ".. _changelog:\n\n.. include:: ../../../../../CHANGELOG.rst\n"
  },
  {
    "path": "src/doc/sphinx/source/about/how_to_cite.rst",
    "content": ".. _how_to_cite:\n\nHow to cite\n===========\n\nSoftware citation\n-----------------\n\nThe software *n2p2* has its own `DOI <http://doi.org>`__ number which can be used for citations:\n\n|badge| ... `<https://doi.org/10.5281/zenodo.1344446>`__\n\nThis DOI always points to the latest release version of *n2p2*. If you prefer to\ncite a specific version please follow the above link which contains a list of\nDOIs for each version.\n\nScientific publications\n-----------------------\n\nPlease cite the following papers in your published work:\n\n*  **General citation for n2p2 and the LAMMPS interface**\n\n   Singraber, A.; Behler, J.; Dellago, C. Library-Based LAMMPS Implementation of\n   High-Dimensional Neural Network Potentials. J. Chem. Theory Comput. 2019, 15\n   (3), 1827–1840. `<https://doi.org/10.1021/acs.jctc.8b00770>`__\n\n*  **If you used the NNP training features of n2p2**\n\n   Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C. Parallel Multistream\n   Training of High-Dimensional Neural Network Potentials. J. Chem. Theory\n   Comput. 2019, 15 (5), 3075–3092.\n   `<https://doi.org/10.1021/acs.jctc.8b01092>`__\n\n*  **For any usage of** :ref:`polynomial symmetry functions <polynomial_sf>`\n\n   Bircher, M. P.; Singraber, A.; Dellago, C. Improved Description of Atomic\n   Environments Using Low-Cost Polynomial Functions with Compact Support.\n   arXiv:2010.14414 [cond-mat, physics:physics] 2020.\n   `<https://arxiv.org/abs/2010.14414>`__\n\n.. |badge| image:: https://zenodo.org/badge/142296892.svg\n   :target: https://zenodo.org/badge/latestdoi/142296892\n   :alt: 10.5281/zenodo.1344446\n"
  },
  {
    "path": "src/doc/sphinx/source/about/license.rst",
    "content": ".. _license:\n\nLicense\n=======\n\nThis software is licensed under the `GNU General Public License version 3 or any later version (GPL-3.0-or-later) <https://www.gnu.org/licenses/gpl.txt>`__.\n"
  },
  {
    "path": "src/doc/sphinx/source/api/cutoff_functions.rst",
    "content": ".. _cutoff_functions:\n\nCutoff functions\n================\n\n.. doxygenenum:: nnp::CutoffFunction::CutoffType\n"
  },
  {
    "path": "src/doc/sphinx/source/api/memory_layout.rst",
    "content": ".. _memory_layout:\n\nMemory layout\n=============\n\nConfiguration storage\n---------------------\n\n.. doxygenstruct:: nnp::Atom\n   :members: index, element, energy, charge, r, f, fRef, G, dEdG, dGdr, neighbors\n\n.. doxygenstruct:: nnp::Atom::Neighbor\n   :members: index, element, d, dr, dGdr\n\n.. doxygenstruct:: nnp::Structure\n   :members: index, energy, energyRef, chargeRef, box, atoms\n\n.. doxygenclass:: nnp::Dataset\n   :members: structures\n\nHelper classes and functions\n----------------------------\n\n.. doxygenclass:: nnp::ElementMap\n   :members: operator[]\n\n.. doxygenstruct:: nnp::Vec3D\n   :members: r, norm, norm2, normalize, cross\n\n.. doxygenfunction:: nnp::split\n\n.. doxygenfunction:: nnp::strpr\n"
  },
  {
    "path": "src/doc/sphinx/source/api/neural_network.rst",
    "content": ".. _neural_network:\n\nNeural network\n==============\n\n.. doxygenenum:: nnp::NeuralNetwork::ActivationFunction\n"
  },
  {
    "path": "src/doc/sphinx/source/api/symmetry_function_scaling.rst",
    "content": ".. _symmetry_function_scaling:\n\nSymmetry function scaling\n=========================\n\n.. doxygenenum:: nnp::SymFnc::ScalingType\n"
  },
  {
    "path": "src/doc/sphinx/source/api/symmetry_function_types.rst",
    "content": ".. _symmetry_function_types:\n\nSymmetry function types\n=======================\n\nBehler and Parrinello PRL 2007\n------------------------------\n\n.. doxygenclass:: nnp::SymFncExpRad\n.. doxygenclass:: nnp::SymFncExpAngn\n\nBehler JCP 2011\n---------------\n\n.. doxygenclass:: nnp::SymFncExpAngw\n\nGastegger et al. JCP 2018\n-------------------------\n\n.. doxygenclass:: nnp::SymFncExpRadWeighted\n.. doxygenclass:: nnp::SymFncExpAngnWeighted\n\nBircher et al. arXiv 2020\n-------------------------\n\n.. doxygenclass:: nnp::SymFncCompRad\n.. doxygenclass:: nnp::SymFncCompAngn\n.. doxygenclass:: nnp::SymFncCompAngw\n.. doxygenclass:: nnp::SymFncCompRadWeighted\n.. doxygenclass:: nnp::SymFncCompAngnWeighted\n.. doxygenclass:: nnp::SymFncCompAngwWeighted\n.. doxygenfunction:: nnp::SymFncBaseComp::setCompactFunction\n.. doxygenenum:: nnp::CoreFunction::Type\n"
  },
  {
    "path": "src/doc/sphinx/source/conf.py",
    "content": "# -*- coding: utf-8 -*-\n#\n# n2p2 - A neural network potential package documentation build configuration file, created by\n# sphinx-quickstart on Tue Jan 29 14:37:49 2019.\n#\n# This file is execfile()d with the current directory set to its\n# containing dir.\n#\n# Note that not all possible configuration values are present in this\n# autogenerated file.\n#\n# All configuration values have a default; values that are commented out\n# serve to show the default.\n\n# If extensions (or modules to document with autodoc) are in another directory,\n# add these directories to sys.path here. If the directory is relative to the\n# documentation root, use os.path.abspath to make it absolute, like shown here.\n#\n# import os\n# import sys\n# sys.path.insert(0, os.path.abspath('.'))\n\nimport sphinx_rtd_theme\n\n# -- General configuration ------------------------------------------------\n\n# If your documentation needs a minimal Sphinx version, state it here.\n#\n# needs_sphinx = '1.0'\n\n# Add any Sphinx extension module names here, as strings. They can be\n# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom\n# ones.\nextensions = [\n    'breathe',\n#    'exhale',\n    'sphinx.ext.mathjax',\n    'sphinx_rtd_theme'\n]\n\n# Setup the breathe extension\nbreathe_projects = {\n    \"n2p2\": \"../../../../doc/doxygen/xml\"\n}\n\nbreathe_default_project = \"n2p2\"\n\n## From https://exhale.readthedocs.io/en/latest/usage.html#customizing-breathe-output\n#from exhale import utils\n#def specificationsForKind(kind):\n#    '''\n#    For a given input ``kind``, return the list of reStructuredText specifications\n#    for the associated Breathe directive.\n#    '''\n#    # Change the defaults for .. doxygenclass:: and .. doxygenstruct::\n#    if kind == \"class\" or kind == \"struct\":\n#        return [\n#          \":members:\",\n#          \":protected-members:\",\n#          \":private-members:\",\n#          \":undoc-members:\"\n#        ]\n#    # Change the defaults for .. doxygenenum::\n#    elif kind == \"enum\":\n#        return [\":no-link:\"]\n#    # An empty list signals to Exhale to use the defaults\n#    else:\n#        return []\n\n## Setup the exhale extension\n#exhale_args = {\n#    # These arguments are required\n#    \"containmentFolder\":     \"./doc-exhale\",\n#    \"rootFileName\":          \"root.rst\",\n#    \"rootFileTitle\":         \"n2p2 code documentation\",\n#    \"doxygenStripFromPath\":  \"..\",\n#    # Suggested optional arguments\n#    \"createTreeView\":        True,\n#    # TIP: if using the sphinx-bootstrap-theme, you need\n#    # \"treeViewIsBootstrap\": True,\n#    \"exhaleExecutesDoxygen\": True,\n#    \"exhaleDoxygenStdin\":    \"INPUT = ../../../libnnp\\n\"\n#                             \"INPUT += ../../../libnnpif\\n\" \n#                             \"INPUT += ../../../libnnptrain\\n\" \n#                             \"XML_PROGRAMLISTING     = YES\\n\"\n#                             \"EXTRACT_ALL            = YES\\n\"\n#                             \"EXTRACT_PRIVATE        = YES\\n\"\n#                             \"EXTRACT_STATIC         = YES\\n\"\n#                             \"EXTRACT_LOCAL_CLASSES  = YES\\n\",\n#    \"customSpecificationsMapping\": utils.makeCustomSpecificationsMapping(specificationsForKind)\n#\n#}\n\n## Tell sphinx what the primary language being documented is.\nprimary_domain = 'cpp'\n\n## Tell sphinx what the pygments highlight language should be.\nhighlight_language = 'cpp'\n\n# Add any paths that contain templates here, relative to this directory.\ntemplates_path = ['_templates']\n\n# The suffix(es) of source filenames.\n# You can specify multiple suffix as a list of string:\n#\n# source_suffix = ['.rst', '.md']\nsource_suffix = '.rst'\n\n# The master toctree document.\nmaster_doc = 'index'\n\n# General information about the project.\nproject = u'n2p2 - A neural network potential package'\ncopyright = u'2024, Andreas Singraber'\nauthor = u'Andreas Singraber'\n\n# The version info for the project you're documenting, acts as replacement for\n# |version| and |release|, also used in various other places throughout the\n# built documents.\n#\n# The short X.Y version.\nwith open('../../../libnnp/version.h') as f:\n    for line in f:\n        if 'N2P2_GIT_VERSION' in line:\n            version = line.split()[2]\n#version = u'1.0.0'\n# The full version, including alpha/beta/rc tags.\n#release = u'1.0.0'\nrelease = version\n\n# The language for content autogenerated by Sphinx. Refer to documentation\n# for a list of supported languages.\n#\n# This is also used if you do content translation via gettext catalogs.\n# Usually you set \"language\" from the command line for these cases.\nlanguage = 'en'\n\n# List of patterns, relative to source directory, that match files and\n# directories to ignore when looking for source files.\n# This patterns also effect to html_static_path and html_extra_path\nexclude_patterns = []\n\n# The name of the Pygments (syntax highlighting) style to use.\npygments_style = 'sphinx'\n\n# If true, `todo` and `todoList` produce output, else they produce nothing.\ntodo_include_todos = False\n\n\n# -- Options for HTML output ----------------------------------------------\n\n# The theme to use for HTML and HTML Help pages.  See the documentation for\n# a list of builtin themes.\n#\nhtml_theme = 'sphinx_rtd_theme'\n\n# Theme options are theme-specific and customize the look and feel of a theme\n# further.  For a list of options available for each theme, see the\n# documentation.\n#\n# html_theme_options = {}\nhtml_theme_options = {\n    'canonical_url': '',\n    #'analytics_id': 'UA-XXXXXXX-1',  #  Provided by Google in your dashboard\n    'logo_only': False,\n    'display_version': True,\n    'prev_next_buttons_location': 'bottom',\n    'style_external_links': False,\n    #'vcs_pageview_mode': '',\n    # Toc options\n    'collapse_navigation': True,\n    'sticky_navigation': True,\n    'navigation_depth': -1,\n    'includehidden': True,\n    'titles_only': False\n}\n\n# Add any paths that contain custom static files (such as style sheets) here,\n# relative to this directory. They are copied after the builtin static files,\n# so a file named \"default.css\" will overwrite the builtin \"default.css\".\n#html_static_path = ['_static']\n\n\n# -- Options for HTMLHelp output ------------------------------------------\n\n# Output file base name for HTML help builder.\nhtmlhelp_basename = 'n2p2-Aneuralnetworkpotentialpackagedoc'\n\n\n# -- Options for LaTeX output ---------------------------------------------\n\nlatex_elements = {\n    # The paper size ('letterpaper' or 'a4paper').\n    #\n    # 'papersize': 'letterpaper',\n\n    # The font size ('10pt', '11pt' or '12pt').\n    #\n    # 'pointsize': '10pt',\n\n    # Additional stuff for the LaTeX preamble.\n    #\n    # 'preamble': '',\n\n    # Latex figure (float) alignment\n    #\n    # 'figure_align': 'htbp',\n}\n\n# Grouping the document tree into LaTeX files. List of tuples\n# (source start file, target name, title,\n#  author, documentclass [howto, manual, or own class]).\nlatex_documents = [\n    (master_doc, 'n2p2-Aneuralnetworkpotentialpackage.tex', u'n2p2 - A neural network potential package Documentation',\n     u'Andreas Singraber', 'manual'),\n]\n\n\n# -- Options for manual page output ---------------------------------------\n\n# One entry per manual page. List of tuples\n# (source start file, name, description, authors, manual section).\nman_pages = [\n    (master_doc, 'n2p2-aneuralnetworkpotentialpackage', u'n2p2 - A neural network potential package Documentation',\n     [author], 1)\n]\n\n\n# -- Options for Texinfo output -------------------------------------------\n\n# Grouping the document tree into Texinfo files. List of tuples\n# (source start file, target name, title, author,\n#  dir menu entry, description, category)\ntexinfo_documents = [\n    (master_doc, 'n2p2-Aneuralnetworkpotentialpackage', u'n2p2 - A neural network potential package Documentation',\n     author, 'n2p2-Aneuralnetworkpotentialpackage', 'One line description of project.',\n     'Miscellaneous'),\n]\n\n\n\n"
  },
  {
    "path": "src/doc/sphinx/source/helper.rst",
    "content": ""
  },
  {
    "path": "src/doc/sphinx/source/index.rst",
    "content": ".. n2p2 - A neural network potential package documentation master file, created by\n   sphinx-quickstart on Tue Jan 29 14:37:49 2019.\n   You can adapt this file completely to your liking, but it should at least\n   contain the root `toctree` directive.\n\nWelcome to the documentation of n2p2!\n=====================================\n\nThis repository (obtain source code `here\n<https://github.com/CompPhysVienna/n2p2>`__) provides ready-to-use software for\nhigh-dimensional neural network potentials in computational physics and\nchemistry.  The methodology behind the Behler-Parinello neural network\npotentials was first described here:\n\n`J. Behler and M. Parrinello, Phys. Rev. Lett. 98, 146401 (2007)\n<https://doi.org/10.1103/PhysRevLett.98.146401>`__\n\nThis package contains software that will allow you to use existing neural\nnetwork potential parameterizations to predict energies and forces (with\nstandalone tools but also in conjunction with the MD software `LAMMPS\n<http://lammps.sandia.gov>`__). In addition it is possible to train new neural\nnetwork potentials with the provided training tools.\n\nDocumentation\n=============\n\n.. warning::\n\n   Unfortunately many parts of the documentation are still unfinished and will\n   be completed little by little. If you have specific questions, consider to\n   ask on GitHub (file an issue) and I will update the corresponding docs as\n   quickly as possible.\n\nThis package uses automatic documentation generation via `Doxygen\n<http://www.doxygen.nl>`__, `Sphinx <http://www.sphinx-doc.org>`__ and `Breathe\n<https://breathe.readthedocs.io/en/latest/#>`__. An online version of the\ndocumentation which is automatically updated with the main repository can be\nfound `here <https://compphysvienna.github.io/n2p2>`__.\n\n.. note::\n\n   The online documentation describes the ``master`` branch of the *n2p2*\n   repository and not the release versions.\n\n.. This package uses automatic documentation generation via `Doxygen\n.. <http://www.doxygen.nl>`__, `Sphinx <http://www.sphinx-doc.org>`__\n.. and `Exhale <https://github.com/svenevs/exhale>`__. An online version of the\n.. documentation which is automatically updated with the main repository can be\n.. found `here <https://compphysvienna.github.io/n2p2>`__.\n\nAPI documentation\n-----------------\n\nMost parts of the C++ code are documented in the header files via Doxygen\nannotations. The information written in the source files is automatically\nextracted by `Doxygen` and presented in a separate API documentation page\navailable `here <doxygen/index.html>`__.\n\n.. Most parts of the C++ code are documented in the header files via Doxygen\n.. annotations. The information written in the source files is automatically\n.. extracted by `Exhale` (which uses `Doxygen`) and integrated into this\n.. documentation (see `API` section on the left). However, because\n.. this documentation and also `Exhale` is still under development some things may\n.. not work as expected. As a fallback option the unaltered Doxygen API\n.. documentation is also available `here <doxygen/index.html>`__.\n\nPurpose\n=======\n\nThis repository provides applications for multiple purposes. Depending on your\ntask at hand you may only need individual parts and do not need to compile all\ncomponents (see components table below). As a new user you may find yourself in\none of these three possible scenarios:\n\nPrediction with existing neural network potential\n-------------------------------------------------\n\nIf you have a working neural network potential setup (i.e. a settings file with\nnetwork and symmetry function parameters, weight files and a scaling file)\nready and want to predict energies and forces for a single structure you only\nneed these components:\n\n* :ref:`libnnp <libnnp>`\n* :ref:`nnp-predict`\n\nMolecular dynamics simulation\n-----------------------------\n\nSimilarly, if you have a working neural network potential setup and would like\nto run an MD simulation with an external MD software (LAMMPS or CabanaMD), these\ncomponents are required:\n\n* :ref:`libnnp <libnnp>`\n* `libnnpif`\n* :ref:`lammps-hdnnp <if_lammps>` (for LAMMPS)\n\nTraining a new neural network potential\n---------------------------------------\n\nTo train a completely new neural network potential the following parts are required:\n\n* :ref:`libnnp <libnnp>`\n* `libnnptrain`\n* :ref:`nnp-scaling`\n* :ref:`nnp-train`\n\nAdditional, though not strictly required tools, are also quite useful:\n\n* `nnp-comp2`\n* :ref:`nnp-convert`\n* `nnp-dataset`\n* `nnp-dist`\n* :ref:`nnp-norm`\n* :ref:`nnp-prune`\n* :ref:`nnp-select`\n* `nnp-symfunc`\n\nRough guidelines for NNP training are provided :ref:`here <training>`.\n\nExamples\n========\n\nApplications\n------------\n\nMinimal working examples for each application can be found in the corresponding\nsubdirectory in ``examples``, e.g. ``examples/nnp-train``.\n\nTraining data sets and single configurations (for testing)\n----------------------------------------------------------\n\nSmall data sets for testing purposes can be found in\n``examples/configuration-sets`` and single configurations are provided in\n``configuration-single``.\n\nTraining data sets (full size)\n------------------------------\nActual full size data sets may be rather large and are therefore hosted elsewhere:\n\n+-------------+--------------+\n| System      | Link         |\n+=============+==============+\n| |H2O| [1]_  | |h2o_data|_  |\n+-------------+--------------+\n| |Cu2S| [2]_ | |cu2s_data|_ |\n+-------------+--------------+\n\nNNP potentials ready for use\n----------------------------\n\nWorking pre-trained NNP potentials are located in ``examples/potentials``.\n\n\nKeywords\n========\n\nThe setup of a neural network potential (network topology, symmetry function\nparameters,...) is stored in a simple text file with keyword-argument pairs. A\nlist of keywords is provided :ref:`here <keywords>`.\n\n\n.. toctree::\n   :hidden:\n\n   Overview<self>\n\n.. toctree::\n   :hidden:\n   :caption: Topics\n\n   topics/build\n   topics/descriptors\n   topics/keywords\n   topics/cfg_file\n   topics/training\n   topics/units\n\n.. toctree::\n   :hidden:\n   :caption: Interfaces\n\n   interfaces/if_lammps\n   interfaces/if_cabanamd\n\n.. toctree::\n   :hidden:\n   :caption: Tools\n\n   tools/libnnp\n   tools/nnp-atomenv\n   tools/nnp-checkf\n   tools/nnp-convert\n   tools/nnp-norm\n   tools/nnp-predict\n   tools/nnp-prune\n   tools/nnp-select\n   tools/nnp-scaling\n   tools/nnp-train\n\n.. toctree::\n   :hidden:\n   :caption: Miscellaneous\n\n   misc/cabanamd_build_example\n   misc/cg_descriptor_analysis\n\n.. toctree::\n   :hidden:\n   :caption: API\n\n   api/neural_network\n   api/cutoff_functions\n   api/symmetry_function_types\n   api/symmetry_function_scaling\n   api/memory_layout\n\n..    doc-exhale/root\n\n.. toctree::\n   :hidden:\n   :caption: About\n\n   about/authors\n   about/how_to_cite\n   about/license\n   about/changelog\n\n.. |H2O| replace:: H\\ :sub:`2`\\ O\n\n.. |Cu2S| replace:: Cu\\ :sub:`2`\\ S\n\n.. |h2o_data| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.2634098.svg\n.. _h2o_data: https://doi.org/10.5281/zenodo.2634098\n\n.. |cu2s_data| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.2603918.svg\n.. _cu2s_data: https://doi.org/10.5281/zenodo.2603918\n\n.. [1] Morawietz, T.; Singraber, A.; Dellago, C.; Behler, J. How van Der Waals\n   Interactions Determine the Unique Properties of Water. Proc. Natl. Acad. Sci.\n   U. S. A. 2016, 113 (30), 8368–8373. https://doi.org/10.1073/pnas.1602375113\n\n.. [2] Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C. Parallel\n   Multistream Training of High-Dimensional Neural Network Potentials. J. Chem.\n   Theory Comput. 2019, 15 (5), 3075–3092. https://doi.org/10.1021/acs.jctc.8b01092\n"
  },
  {
    "path": "src/doc/sphinx/source/interfaces/if_cabanamd.rst",
    "content": ".. _if_cabanamd:\n\nCabanaMD interface\n==================\n\nPurpose\n-------\nThe CabanaMD interface adds the neural network potential method in a proxy\napplication which uses the Cabana particle library. `Cabana\n<https://github.com/ECP-copa/Cabana>`_ uses the `Kokkos\n<https://github.com/kokkos/kokkos>`_ programming model to run on multi-core CPUs\nand GPUs; `CabanaMD <https://github.com/ECP-copa/CabanaMD>`_ provides a simple\nMD code to explore performance with Cabana and Kokkos. The Cabana version of\nn2p2 reimplements a small part of the neural network potential to enable\nsimulations on the GPU [1]_.\n\n\nBuild instructions\n------------------\n\nGo to the ``src`` directory and compile with the CabanaMD interface enabled:\n\n.. code-block:: none\n\n   cd src\n   make libnnpif INTERFACES=CabanaMD\n\nAlternatively, set the ``INTERFACES`` variable in the master makefile\n(``src/makefile``) to ``CabanaMD`` and just run in the ``src`` directory:\n\n.. code-block:: none\n\n   make libnnpif\n\nFor dynamic linking add the argument ``MODE=shared``.\n\n.. note::\n   If dynamic linking (\\ ``make libnnpif MODE=shared``\\ ) is used, you need to make the NNP\n   libraries visibile in your system, e.g. add this line in your ``.bashrc``\\ :\n\n   .. code-block:: none\n\n      export LD_LIBRARY_PATH=<path-to-n2p2>/lib:${LD_LIBRARY_PATH}\n\nThis completes the necessary steps on the n2p2 side, further instructions on how\nto build CabandaMD together with this interface are provided `here\n<https://github.com/ECP-copa/CabanaMD/wiki>`__.\n\n\nUsage\n-----\n\nSee `here <https://github.com/ECP-copa/CabanaMD/wiki>`__ for building and running\nCabanaMD after building n2p2 (with the CabanaMD interface).\n\n.. [1] Desai, S.; Reeve, S. T.; Belak, J. F. Implementing a Neural Network\n   Interatomic Model with Performance Portability for Emerging Exascale\n   Architectures. `arXiv:2002.00054 <https://arxiv.org/abs/2002.00054>`__\n   [cond-mat, physics:physics] 2020\n"
  },
  {
    "path": "src/doc/sphinx/source/interfaces/if_lammps.rst",
    "content": ".. _if_lammps:\n\nLAMMPS interface\n================\n\nPurpose\n-------\n\nThe LAMMPS interface adds the neural network potential method in LAMMPS. Hence,\none can use a previously fitted NNP to predict energies and forces and use\nLAMMPS to propagate an MD simulation. LAMMPS parallelization via MPI is\nfully supported.\n\nBuild instructions\n------------------\n\nThe recommended way to build LAMMPS together with n2p2 is using the LAMMPS\npackage management and build system. If you are new to LAMMPS, please start with\nthe basics of the LAMMPS build system which are described\n`here <https://docs.lammps.org/Build.html>`__. Specific instructions for the\nLAMMPS + n2p2 build can be found here:\n\n* `LAMMPS Packages with extra build options: ML-HDNNP <https://docs.lammps.org/Build_extras.html#ml-hdnnp>`__\n* `LAMMPS Packages details: ML-HDNNP <https://docs.lammps.org/Packages_details.html#pkg-ml-hdnnp>`__\n\nFor example, these commands will build LAMMPS with n2p2 support following the\ntraditional makefile method:\n\n.. code-block:: shell\n\n   cd /path/to/lammps/src\n\n   # Enable ML-HDNNP package:\n   make yes-ml-hdnnp\n\n   # Automatically download and build n2p2:\n   make lib-hdnnp args=\"-b\"\n   # Alternatively, use existing n2p2 installation:\n   # (follow instructions in <path-to-lammps>/lib/hdnnp/README)\n   # make lib-hdnnp args=\"-p path/to/n2p2\n\n   # Build LAMMPS for desired target, for example:\n   make mpi -j\n\nAlternatively, the CMake build commands may look like this:\n\n.. code-block:: shell\n\n   cd path/to/lammps\n   mkdir build; cd build\n   cmake ../cmake -D PKG_ML-HDNNP=yes -D DOWNLOAD_N2P2=yes\n   cmake --build . -j\n\nUsage\n-----\n\nThe neural network potential method is introduced in the context of a pair style\nnamed ``hdnnp``. LAMMPS comes with a large collection of these pair styles, e.g. for\na LJ or Tersoff potential, look\n`here <https://docs.lammps.org/Commands_pair.html>`__ for more information. The\nsetup of a ``hdnnp`` pair style is done by issuing two commands: ``pair_style`` and\n``pair_coeff``. See the `pair style hdnnp\n<https://docs.lammps.org/pair_hdnnp.html>`__ documentation page for a detailed\ndescription.\n\nDevelopment build\n-----------------\n\n.. danger::\n\n   This is not the recommended way to build LAMMPS + n2p2, please consider using\n   the LAMMPS package and build system as described above! The development build\n   usually does not offer any benefit. Instead, it may include unstable or\n   untested additions, or may even not compile at all.\n\nFor the development build the main makefile provides the compilation target\n``lammps-hdnnp`` which will automatically download LAMMPS (from the `GitHub\nreleases page <https://github.com/lammps/lammps/releases>`__) into the\n``interface`` directory, unpack it to ``lammps-hdnnp``, add the necessary n2p2\nfiles to it and compile the LAMMPS ``mpi`` target. Finally, the binary\n``lmp_mpi`` will be copied to the n2p2 ``bin`` directory. Hence, compiling\nLAMMPS with NNP support is as easy as typing\n\nThe LAMMPS version which will be downloaded is determined in\n``src/interface/makefile``. Close to the top there is a variable ``LAMMPS_VERSION``\nwhich contains the LAMMPS version string, e.g. ``stable_29Aug2024``. This\ndefault value can be changed in the makefile or also on the command-line if\ndesired:\n\n.. code-block:: none\n\n   make LAMMPS_VERSION=stable_2Aug2023 lammps-hdnnp -j\n\nThe development build will perform the following actions:\n\n1. If not present, download the LAMMPS source tarball from GitHub.\n2. Unpack the LAMMPS source code.\n3. Link the necessary folders and files to the ``lammps-hdnnp/lib/hdnnp``\n   directory.\n4. Copy the contents of n2p2's ``src/LAMMPS/src/ML-HDNNP`` folder to the LAMMPS\n   ML-HDNNP package folder.\n5. Modify the LAMMPS ``mpi`` target makefile to contain compiler flags from\n   n2p2.\n6. Enable the ML-HDNNP package with ``make yes-ml-hdnnp``.\n7. Compile the LAMMPS ``mpi`` target.\n8. Copy the executable ``lmp_mpi`` to n2p2's ``bin`` directory.\n\nSince in step 4 the LAMMPS-distributed ``hdnnp`` pair style files are replaced\nwith the ones located in n2p2, this build may not be identical to the\nrecommended way of installing LAMMPS + n2p2 described above.\n\n.. note::\n\n   The automatic compilation will only work on Unix-like systems as it relies on\n   tools such as ``wget``, ``sed`` and ``tar``.\n\nTo remove the developer build run ``make clean-lammps-hdnnp``. However, this\nwill not delete the downloaded LAMMPS tarballs in the ``src/interface``\ndirectory so they can be reused for the next build. Please delete them\nmanually if desired.\n\n.. important::\n\n   During development be aware that the **copied** files in the LAMMPS ``src``\n   or ``src/ML-HDNNP`` directories are not managed by git. Be sure to transfer\n   modifications back to n2p2's ``src/interface/LAMMPS/src/ML-HDNNP`` directory\n   before cleaning!\n\nNote on older development builds\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nPrevious versions of n2p2 (before 2.3.0) had a similar automatic development\nbuild with **older** pair style source code files (pre-dating the `merge request\n<https://github.com/lammps/lammps/pull/2626>`__ for the official LAMMPS repo).\nThe most obvious difference is that the pair style name was ``nnp`` and not\n``hdnnp``. This version of the LAMMPS interface is not supported anymore. For\nfuture installations please always try to use the recommended build method\ndescribed at the top of this page.\n\nLAMMPS script files using the ``nnp`` pair style require three minor modifications\nto be converted to the official ``hdnpp`` version:\n\n1. Replace the pair style name.\n2. The element mapping previously entered via the ``emap`` keyword is now listed\n   in the ``pair_coeff`` line in the usual LAMMPS style.\n3. The cutoff radius is moved from the ``pair_coeff`` line to the first\n   (mandatory) argument of the ``pair_style`` line.\n\nHere is an example:\n\n.. code-block:: shell\n\n   # Old nnp pair style lines:\n   pair_style nnp showew no showewsum 100 maxew 1000 resetew yes emap \"1:H,2:O\"\n   pair_coeff * * 6.01\n\n   # Corresponding hdnnp pair style lines:\n   pair_style hdnnp 6.01 showew no showewsum 100 maxew 1000 resetew yes\n   pair_coeff * * H O\n\nPlease consult the `pair style hdnnp\n<https://docs.lammps.org/pair_hdnnp.html>`__ documentation page for details. The\ndocumentation for the old ``nnp`` pair style is kept in the n2p2 repository\nhere: ``src/doc/sphinx/source/old/pair_nnp.rst``.\n"
  },
  {
    "path": "src/doc/sphinx/source/misc/cabanamd_build_example.rst",
    "content": ".. _cabanamd_build_example:\n\nCabanaMD GPU build example\n==========================\n\n.. warning::\n\n   This is not a fully tested installation guide but rather a collection of\n   build instructions that worked for a specific system at a certain point in\n   time. They are kept here only as a reference, for your own build please refer\n   to the current build instructions of the individual software packages.\n\nSystem specifications\n---------------------\n\n-  CPU: ``Intel(R) Core(TM) i7-7800X (6/12 cores/threads)``\n-  RAM: ``32GB``\n-  OS: ``Linux Mint 19.3``\n-  GPU: ``GeForce GTX 1060 6GB (GP106, Pascal architecture)``\n-  CUDA version: ``11.0``\n-  CUDA capability: ``6.1``\n-  GPU driver: ``450.51.06``\n\nBuild steps\n-----------\n\nIn order to have all packages in one place please first create a working directory for\nthese instructions (e.g. ``CabanaMD-Setup``) and ``cd`` there.\n\nOn this particular system it was required to build a CUDA-aware MPI. Create a\nfile ``build_openmpi.sh``, copy these commands and execute it (or go through the\ncommands one by one):\n\n.. code-block:: bash\n\n   #!/bin/bash\n\n   wget https://download.open-mpi.org/release/open-mpi/v4.1/openmpi-4.1.0.tar.gz\n   tar -xvzf openmpi-4.1.0.tar.gz\n   mv openmpi-4.1.0 openmpi\n   \n   cd openmpi\n   mkdir build\n   ./configure --prefix=`pwd`/build --with-cuda=/usr/local/cuda-11.0 && \\\n   make all -j && \\\n   make install\n   cd ..\n\nAfter successful compilation you should see binaries in ``openmpi/build/bin/``.\nBe sure to set the path to your CUDA installation correctly in the\n``./configure`` line.\n\nNext, we download `Kokkos <https://github.com/kokkos/kokkos>`__ and compile it.\nCreate and execute a file ``build_kokkos.sh`` with this content:\n\n.. code-block:: bash\n\n   #!/bin/bash\n\n   git clone git@github.com:kokkos/kokkos.git\n   export COMPILER=`pwd`/kokkos/bin/nvcc_wrapper\n   export ARCH=sm_61\n   # CAUTION: Also set the flag (-D Kokkos_ARCH_PASCAL61=On)\n   cd kokkos\n   git checkout 3.2.00\n   mkdir build\n   cd build\n   cmake ../ \\\n    -D CMAKE_CXX_COMPILER=${COMPILER} \\\n    -D CMAKE_CXX_FLAGS=-arch=${ARCH} \\\n    -D CMAKE_INSTALL_PREFIX=./install \\\n    -D Kokkos_CUDA_DIR=/usr/local/cuda-11.0/ \\\n    -D Kokkos_ENABLE_SERIAL=On \\\n    -D Kokkos_ENABLE_OPENMP=On \\\n    -D Kokkos_ENABLE_CUDA=On \\\n    -D Kokkos_ENABLE_CUDA_LAMBDA=On \\\n    -D Kokkos_ENABLE_CUDA_UVM=On \\\n    -D Kokkos_ARCH_PASCAL61=On \\\n    -D Kokkos_ENABLE_HWLOC=On &&\n   make install -j\n   cd ../..\n\nMake sure to set the ``ARCH`` and ``Kokkos_ARCH_???`` correctly for your GPU\n(see `docs <https://github.com/kokkos/kokkos/blob/master/BUILD.md>`__). This\nshould create a directory ``kokkos/build/install`` where you can find libraries\nand headers in the ``lib`` and ``include`` subfolder, respectively.\n\nNow we install `Cabana <https://github.com/ECP-copa/Cabana>`__, create\n``build_Cabana.sh``, fill in below commands and execute it:\n\n.. code-block:: bash\n\n   #!/bin/bash\n\n   git clone git@github.com:ECP-copa/Cabana.git\n   cd Cabana\n   # No specific version is specified in the docs, only \"master\". If that does not\n   # work at a later point in time use this line to get a commit that worked:\n   git checkout 5c2503aa72c3e3cb4db34ea52e41a2ac446e5719\n   export ARCH=sm_61\n   export OPENMPI_BUILD_DIR=`pwd`/../openmpi/build\n   export KOKKOS_SRC_DIR=`pwd`/../kokkos\n   export KOKKOS_INSTALL_DIR=${KOKKOS_SRC_DIR}/build/install\n   mkdir build\n   cd build\n   cmake ../ \\\n    -D CMAKE_BUILD_TYPE=\"Release\" \\\n    -D CMAKE_PREFIX_PATH=\"${OPENMPI_BUILD_DIR};${KOKKOS_INSTALL_DIR}\" \\\n    -D CMAKE_INSTALL_PREFIX=`pwd`/install \\\n    -D CMAKE_CXX_COMPILER=${KOKKOS_SRC_DIR}/bin/nvcc_wrapper \\\n    -D CMAKE_CXX_FLAGS=-arch=${ARCH} \\\n    -D MPI_CXX_COMPILER=${OPENMPI_BUILD_DIR}/bin/mpic++ \\\n    -D Cabana_REQUIRE_CUDA=On \\\n    -D Cabana_ENABLE_MPI=On \\\n    -D Cabana_ENABLE_TESTING=OFF \\\n    -D Cabana_ENABLE_EXAMPLES=OFF && \\\n   make install -j\n   cd ../..\n\nAgain, check that the ``ARCH`` variable is set correctly. Since we have excluded\nthe tests and examples (``Cabana_ENABLE_TESTING=OFF`` and\n``Cabana_ENABLE_EXAMPLES=OFF``) this will not compile anything but create some\nheaders in ``build/install/include``.\n\nThe last step before we get to CabanaMD is to set up n2p2, create\n``build_n2p2.sh`` with the follwing lines and execute:\n\n.. code-block:: bash\n\n   #!/bin/bash\n\n   git clone https://github.com/CompPhysVienna/n2p2\n   cd n2p2\n   git checkout v2.0.1\n   cd src\n   make libnnpif -j\n   cd ../..\n\nNow there should be headers in ``n2p2/include``.\n\nFinally, compile `CabanaMD <https://github.com/ECP-copa/CabanaMD>`__, create a\nfile ``build_CabanaMD.sh``, fill it with this content and execute (check again\nthe ``ARCH`` variable):\n\n.. code-block:: bash\n\n   #!/bin/bash\n\n   git clone git@github.com:ECP-copa/CabanaMD.git\n   cd CabanaMD\n   # No specific version is specified in the docs, only \"master\". If that does not\n   # work at a later point in time use this line to get a commit that worked:\n   git checkout 15fa51c03a388c6c7f59dbbd4e21ecc3e5c7459b\n   export ARCH=sm_61\n   export OPENMPI_BUILD_DIR=`pwd`/../openmpi/build\n   export KOKKOS_SRC_DIR=`pwd`/../kokkos\n   export CABANA_DIR=`pwd`/../Cabana/build/install\n   export N2P2_DIR=`pwd`/../n2p2\n   mkdir build\n   cd build\n   cmake ../ \\\n    -D CMAKE_BUILD_TYPE=\"Release\" \\\n    -D CMAKE_PREFIX_PATH=\"${OPENMPI_BUILD_DIR};${CABANA_DIR}\" \\\n    -D CMAKE_INSTALL_PREFIX=`pwd`/install \\\n    -D CMAKE_CXX_COMPILER=${KOKKOS_SRC_DIR}/bin/nvcc_wrapper \\\n    -D CMAKE_CXX_FLAGS=-arch=${ARCH} \\\n    -D MPI_CXX_COMPILER=${OPENMPI_BUILD_DIR}/bin/mpic++ \\\n    -D Cabana_ENABLE_MPI=On \\\n    -D N2P2_DIR=${N2P2_DIR} \\\n    -D CabanaMD_VECTORLENGTH=32 \\\n    -D CabanaMD_ENABLE_NNP=On \\\n    -D CabanaMD_MAXSYMMFUNC_NNP=30 \\\n    -D CabanaMD_VECTORLENGTH_NNP=1 \\\n    -D CabanaMD_ENABLE_TESTING=OFF && \\\n   make -j\n   cd ../..\n\nIf successful you will now find the CabanaMD executable ``cbnMD`` in\n``CabanaMD/build/bin/``.\n\nRunning an example on the GPU\n-----------------------------\nFinally, we can test it on the GPU with the provided NNP example. Create\n``test_CabanaMD_GPU_NNP.sh`` with below content and execute:\n\n.. code-block:: bash\n   \n   #!/bin/bash\n\n   cd CabanaMD\n   build/bin/cbnMD -il input/in.nnp --device-type CUDA\n   mv cabanaMD.out ..\n   mv cabanaMD.err ..\n   cd ..\n\nYou should see the (slightly modified) n2p2 library output and in the output\nfile ``cabanaMD.out`` you will find some information about your GPU and the\nperformed timesteps as in:\n\n.. code-block:: none\n\n   Read input file.\n   macro  KOKKOS_ENABLE_CUDA      : defined\n   macro  CUDA_VERSION          = 11000 = version 11.0\n   Kokkos::Cuda[ 0 ] GeForce GTX 1060 6GB capability 6.1, Total Global Memory: 5.927 G, Shared Memory per Block: 48 K : Selected\n   Using: SystemVectorLength: 32 System:1AoSoA\n   Using: SystemNNPVectorLength: 1 NNPSystem:1AoSoA\n   Using: Force:NNPCabana Neighbor:CabanaVerletFull Comm:CabanaMPI Binning:CabanaLinkedCell Integrator:NVE\n   Atoms: 108 108\n   Created atoms.\n   \n   #Timestep Temperature PotE ETot Time Atomsteps/s\n   0 600.000000 -5.780009 -5.703171 0.00 0.00e+00\n   10 577.114210 -5.777077 -5.703170 0.50 2.14e+03\n   20 512.839729 -5.768845 -5.703169 0.97 2.32e+03\n   30 418.982352 -5.756824 -5.703168 1.43 2.35e+03\n   40 312.732989 -5.743216 -5.703167 1.90 2.31e+03\n   50 213.508287 -5.730508 -5.703165 2.36 2.33e+03\n   60 138.634903 -5.720919 -5.703165 2.83 2.30e+03\n   70 99.064735 -5.715851 -5.703164 3.29 2.34e+03\n   80 96.861148 -5.715569 -5.703165 3.76 2.28e+03\n   90 125.599583 -5.719251 -5.703166 4.23 2.32e+03\n   100 173.352777 -5.725367 -5.703167 4.70 2.29e+03\n   \n   #Procs Atoms | Time T_Force T_Neigh T_Comm T_Int T_Other |\n   1 108 | 4.70 4.31 0.00 0.38 0.00 0.00 | PERFORMANCE\n   1 108 | 1.00 0.92 0.00 0.08 0.00 0.00 | FRACTION\n   \n   #Steps/s Atomsteps/s Atomsteps/(proc*s)\n   2.13e+01 2.30e+03 2.30e+03\n\nYou can check your GPU utilization with the ``nvidia-smi`` tool, run ``watch\nnvidia-smi`` in another shell. The executable ``cbnMD`` should be\nlisted under ``Processes``:\n\n.. code-block:: none\n\n   +-----------------------------------------------------------------------------+\n   | NVIDIA-SMI 450.51.06    Driver Version: 450.51.06    CUDA Version: 11.0     |\n   |-------------------------------+----------------------+----------------------+\n   | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n   | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n   |                               |                      |               MIG M. |\n   |===============================+======================+======================|\n   |   0  GeForce GTX 106...  On   | 00000000:65:00.0 Off |                  N/A |\n   |  0%   49C    P2    33W / 200W |    476MiB /  6069MiB |     96%      Default |\n   |                               |                      |                  N/A |\n   +-------------------------------+----------------------+----------------------+\n   \n   +-----------------------------------------------------------------------------+\n   | Processes:                                                                  |\n   |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n   |        ID   ID                                                   Usage      |\n   |=============================================================================|\n   |    0   N/A  N/A      1385      G   /usr/lib/xorg/Xorg                224MiB |\n   |    0   N/A  N/A      2402      G   cinnamon                           48MiB |\n   |    0   N/A  N/A     10163      C   build/bin/cbnMD                    71MiB |\n   +-----------------------------------------------------------------------------+\n"
  },
  {
    "path": "src/doc/sphinx/source/misc/cg_descriptor_analysis.rst",
    "content": ".. _cg_descriptor_analysis:\n\nDescriptor analysis/Coarse-graining\n===================================\n\n.. warning::\n\n   The following procedures and analyses should be considered experimental. They\n   are not well-tested and there is no related peer-reviewed publication.\n\nThis short tutorial shows how to prepare and run a descriptor analysis which can\nbe useful when creating a coarse-grained (CG) model based on neural network\npotentials. The steps outlined here correspond to the subfolders of the\n``examples/coarse-graining`` directory in the repository. The descriptor\nanalysis itself is described in detail inside the Jupyter notebook\n``step-3_cluster-analysis/analyze-descriptors.ipynb``.\n\n.. note::\n\n   The tools ``nnp-atomenv`` and ``nnp-scaling`` need to be compiled to follow\n   the steps presented in this tutorial.\n\nStep 0 (optional): Coarse-grained data set\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\n\n.. note::\n\n   This step is optional, the descriptor analysis may also yield insights if\n   applied directly to the full, atomistic description of the system.\n\nFirst, we need to create a data set which contains the coarse-grained\ndescription of the original structures. In the example (directory\n``step-0_cg-data-set``) we start with a data set of bulk water (``input.data``)\nwhere we apply the following coarse-graining strategy: for each oxygen atom we\nidentify the two closest hydrogen neighbors and compute then the center of mass\ncoordinates of all molecules via\n\n.. math::\n\n   \\vec{R} = \\vec{r}_O - \\frac{2 m_H \\left(\\Delta \\vec{r}_{OH_1} + \\Delta \\vec{r}_{OH_2} \\right)}{m_O + 2 m_H},\n\nwhere :math:`\\Delta \\vec{r}_{jk} = \\vec{r}_j - \\vec{r}_k`. The force acting on\nthe center of mass is then just the sum of all forces in each molecule.\n\n.. figure:: ./water-full-cg.jpeg\n   :width: 250\n   :align: center\n   :alt: Water molecule with center of mass position.\n\n   A water molecule and its coarse-grained (center of mass) representation (turquoise sphere).\n\nAn example C++ code is provided to perform this conversion in ``nnp-cgdata.cpp``\nmaking use of the ``libnnp`` library. To build the executable just run ``make``\n(``libnnp`` needs to be compiled beforehand in the main ``src`` directory). Then\nrun the executable with an appropriate cutoff radius for the neighbor list as\nthe only argument:\n\n.. code-block:: none\n\n   ./nnp-cgdata 2.3\n\nHere, we use a cutoff of 2.3 bohr which ensures that the two closest hydrogen\nneighbors are found for each oxygen atom. This will create the file\n``output.data`` which contains the desired coarse-grained center of mass\nparticles representing the water molecules.\n\n.. hint::\n\n   The \"element symbol\" of the CG particles in this example is ``Cm``. Normally,\n   this would correspond to the element Curium but here we use it to abbreviate\n   \"center of mass\".\n\nThe ``nnp-cgdata.cpp`` code demonstrates the usage of the C++ API to manipulate\ndatasets of configurations. Of course such a task can also be performed with\nexternal software.\n\nStep 1: Create symmetry function set\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\n\nThis step is common to regular NNP training with *n2p2*: for a given data set we\nneed to prepare an appropriate symmetry function set and compute the scaling\ndata. Please see also :ref:`this section <symfunc_setup>` for further\ninformation. For this example, an ``input.nn`` file is already prepared in\n``step-1_scaling-data`` which contains symmetry function definitions for our\ncoarse-grained description of water:\n\n.. code-block:: none\n\n   ...\n   symfunction_short Cm 2 Cm 0.30  4.0 12.00\n   symfunction_short Cm 2 Cm 0.60  4.0 12.00\n   symfunction_short Cm 2 Cm 1.50  4.0 12.00\n   symfunction_short Cm 3 Cm Cm 0.03  1.0 1.0   12.00000\n   symfunction_short Cm 3 Cm Cm 0.03 -1.0 1.0   12.00000\n   ...\n\nTogether with the data set file ``input.data`` (file is provided, it is the\n``output.data`` of step 0 above) we can proceed to compute the symmetry\nfunctions statistics:\n\n.. code-block:: bash\n\n   mpirun -np 4 ../../../bin/nnp-scaling 500\n\nWe can safely ignore (or delete) the output files ``sf.???.????.histo``, we only\nrequire the ``scaling.data`` file for the next steps.\n\nStep 2: Generate atomic environment data\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\n\nNext, in order to feed the descriptor analysis Jupyter notebook in the final\nstep, we need to prepare atomic environment data for our system. Please read the\n:ref:`description <nnp-atomenv>` of the tool ``nnp-atomenv`` for a detailed\nexplanation how this data is constructed. The required files from the previous\nsteps are prepared in the ``step-2_atomic-env`` directory. For the\ncoarse-graining example we use the command\n\n.. code-block:: bash\n\n   ../../../bin/nnp-atomenv 500 4\n\nwhere the second argument determines the maximum number of neighbor particles\nconsidered for the atomic environment data. Again, we can ignore all output\nfiles except ``atomic-env.dGdx`` which we use in the final step.\n\nStep 3: Analyze descriptors\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\n\nFinally, everything is ready to start the Jupyter notebook\n``analyze-descriptors.ipynb`` which carries out the actual descriptor analysis. The\nnotebook and necessary files are provided in ``step-3_cluster-analysis``. After\nstarting Jupyter with\n\n.. code-block:: bash\n\n   jupyter notebook analyze-descriptors.ipynb\n\nwe can run all cells which may take a while. All further steps of the descriptor\nanalysis are described in the notebook's comment cells.\n\n.. figure:: ./jupyter-notebook.jpeg\n   :width: 600\n   :alt: Preview of the Jupyter notebook.\n"
  },
  {
    "path": "src/doc/sphinx/source/old/pair_nnp.rst",
    "content": ".. _pair_nnp:\n\nLAMMPS NNP pair style\n=====================\n\npair_style nnp command\n----------------------\n\nSyntax\n^^^^^^\n\n.. code-block:: none\n\n   pair_style nnp keyword value ...\n\n* zero or more keyword/value pairs may be appended\n\n* keyword = *dir* or *showew* or *showewsum* or *maxew* or *resetew* or *cflength* or *cfenergy*\n\n* value depends on the preceding keyword:\n\n  *  *emap* value = mapping\n\n      mapping = Element mapping from LAMMPS atom types to n2p2 elements\n\n  *  *dir* value = directory\n\n      directory = Path to NNP configuration files\n\n  *   *showew* value = *yes* or *no*\n\n  *   *showewsum* value = summary\n\n       summary = Write EW summary every this many timesteps (*0* turns summary off)\n\n  *   *maxew* value = threshold\n\n       threshold = Maximum number of EWs allowed\n\n  *   *resetew* value = *yes* or *no*\n\n  *   *cflength* value = length\n\n       length = Length unit conversion factor\n\n  *   *cfenergy* value = energy\n\n       energy = Energy unit conversion factor\n\nExamples\n^^^^^^^^\n\n.. code-block:: none\n\n   pair_style nnp showew yes showewsum 100 maxew 1000 resetew yes cflength 1.8897261328 cfenergy 0.0367493254 emap \"1:H,2:O\"\n\n   pair_style nnp dir \"./\" showewsum 10000\n\n   pair_coeff * * 6.01\n\n.. warning::\n\n   Only use a single `pair_style nnp` line in your LAMMPS script.\n\nDescription\n^^^^^^^^^^^\n\nThis pair style adds an interaction based on the high-dimensional neural network\npotential method [1]_. These potentials must\nbe carefully trained to reproduce the potential energy surface in the desired\nphase-space region prior to their usage in an MD simulation. This pair style\nuses an interface to the NNP library [2]_ [3]_, see the documentation\nthere for more information.\n\nThe maximum cutoff radius of all symmetry functions is the only argument of the\n*pair_coeff* command which should be invoked with asterisk wild-cards only:\n\n.. code-block:: none\n\n   pair_coeff * * cutoff\n\n.. note::\n\n   The cutoff must be given in LAMMPS length units, even if the neural network\n   potential has been trained using a different unit system (see remarks about the\n   *cflength* and *cfenergy* keywords below for details).\n\nThe numeric value may be slightly larger than the actual maximum symmetry\nfunction cutoff radius (to account for rounding errors when converting units),\nbut must not be smaller.\n\n----\n\nIf provided, the keyword *emap* determines the mapping from LAMMPS atom types to\nn2p2 elements. The format is a comma-separated list of ``atom type:element``\npairs, e.g. ``\"1:Cu,2:Zn\"`` will map atom types 1 and 2 to elements Cu and Zn,\nrespectively. Atom types not present in the list will be completely ignored by\nthe NNP. The keyword *emap* is mandatory in a \"hybrid\" setup (see `pair_hybrid\n<https://lammps.sandia.gov/doc/pair_hybrid.html>`__) with \"extra\" atom types in\nthe simulation which are not handled by the NNP.\n\n.. warning::\n\n   Without an explicit mapping it is by default assumed that the atom type\n   specifications in LAMMPS configuration files are consistent with the ordering\n   of elements in the NNP library. Thus, without the *emap* keyword present\n   atom types must be sorted in order of ascending atomic number, e.g. the only\n   correct mapping for a configuration containing hydrogen, oxygen and zinc\n   atoms would be:\n   \n   +---------+---------------+-------------+\n   | Element | Atomic number | LAMMPS type |\n   +=========+===============+=============+\n   |       H |             1 |           1 |\n   +---------+---------------+-------------+\n   |       O |             8 |           2 |\n   +---------+---------------+-------------+\n   |      Zn |            30 |           3 |\n   +---------+---------------+-------------+\n\nUse the *dir* keyword to specify the directory containing the NNP configuration\nfiles. The directory must contain \"input.nn\" with neural network\nand symmetry function setup, \"scaling.data\" with symmetry function scaling data\nand \"weights.???.data\" with weight parameters for each element.\n\nThe keyword *showew* can be used to turn on/off the display of extrapolation\nwarnings (EWs) which are issued whenever a symmetry function value is out of\nbounds defined by minimum/maximum values in \"scaling.data\". An extrapolation\nwarning may look like this:\n\n.. code-block:: none\n\n   ### NNP EXTRAPOLATION WARNING ### STRUCTURE:      0 ATOM:       119 ELEMENT: Cu SYMFUNC:   32 TYPE:  3 VALUE:  2.166E-02 MIN:  2.003E-05 MAX:  1.756E-02\n\nstating that the value 2.166E-02 of symmetry function 32 of :ref:`type 3\n(angular narrow)<symfunction_short>`, element Cu (see the log file for a symmetry\nfunction listing) was out of bounds (maximum in \"scaling.data\" is 1.756E-02) for\natom 119. Here, the atom index refers to the LAMMPS tag (global index) and the\nstructure index is used to print out the MPI rank the atom belongs to.\n\n.. note::\n\n   The *showew* keyword should only be set to *yes* for debugging purposes.\n   Extrapolation warnings may add lots of overhead as they are communicated each\n   timestep. Also, if the simulation is run in a phase-space region where the NNP\n   was not correctly trained, lots of extrapolation warnings may clog log files and\n   the console. In a production run use *showewsum* instead.\n\nThe keyword *showewsum* can be used to get an overview of extrapolation warnings\noccurring during an MD simulation. The argument specifies the interval at which\nextrapolation warning summaries are displayed and logged. An EW summary may look\nlike this:\n\n.. code-block:: none\n\n   ### NNP EW SUMMARY ### TS:        100 EW         11 EWPERSTEP  1.100E-01\n\nHere, at timestep 100 the occurrence of 11 extrapolation warnings since the last\nsummary is reported, which corresponds to an EW rate of 0.11 per timestep.\nSetting *showewsum* to 0 deactivates the EW summaries.\n\nA maximum number of allowed extrapolation warnings can be specified with the\n*maxew* keyword. If the number of EWs exceeds the *maxew* argument the\nsimulation is stopped. Note however that this is merely an approximate threshold\nsince the check is only performed at the end of each timestep and each MPI\nprocess counts individually to minimize communication overhead.\n\nThe keyword *resetew* alters the behavior of the above mentioned *maxew*\nthreshold. If *resetew* is set to *yes* the threshold is applied on a\nper-timestep basis and the internal EW counters are reset at the beginning of\neach timestep. With *resetew* set to *no* the counters accumulate EWs along the\nwhole trajectory.\n\nIf the training of a neural network potential has been performed with different\nphysical units for length and energy than those set in LAMMPS, it is still\npossible to use the potential when the unit conversion factors are provided via\nthe *cflength* and *cfenergy* keywords. If for example, the NNP was\nparameterized with Bohr and Hartree training data and symmetry function\nparameters (i.e. distances and energies in \"input.nn\" are given in Bohr and\nHartree) but LAMMPS is set to use *metal* units (Angstrom and eV) the correct\nconversion factors are:\n\n.. code-block:: none\n\n   cflength 1.8897261328\n\n   cfenergy 0.0367493254\n\nThus, arguments of *cflength* and *cfenergy* are the multiplicative factors\nrequired to convert lengths and energies given in LAMMPS units to respective\nquantities in native NNP units (1 Angstrom = 1.8897261328 Bohr, 1 eV =\n0.0367493254 Hartree).\n\n----\n\nRestrictions\n^^^^^^^^^^^^\n\nPlease report bugs and feature requests to the `n2p2 GitHub issue page\n<https://github.com/CompPhysVienna/n2p2/issues>`__.\n\nRelated commands\n^^^^^^^^^^^^^^^^\n\n`pair_coeff <https://lammps.sandia.gov/doc/pair_coeff.html>`__\n\n`pair_hybrid <https://lammps.sandia.gov/doc/pair_hybrid.html>`__\n\n`units <https://lammps.sandia.gov/doc/units.html>`__\n\nDefault\n^^^^^^^\n\nThe default options are *dir* = \"nnp/\", *showew* = yes, *showewsum* = 0, *maxew*\n= 0, *resetew* = no, *cflength* = 1.0, *cfenergy* = 1.0. The default atom type\nmapping is determined automatically according to ascending atomic number of\npresent elements (see above).\n\n----\n\n.. [1] Behler, J.; Parrinello, M. Generalized Neural-Network Representation of\n   High-Dimensional Potential-Energy Surfaces. Phys. Rev. Lett. 2007, 98 (14),\n   146401. https://doi.org/10.1103/PhysRevLett.98.146401\n\n.. [2] https://github.com/CompPhysVienna/n2p2\n\n.. [3] Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C. Parallel\n   Multistream Training of High-Dimensional Neural Network Potentials. J. Chem.\n   Theory Comput. 2019, 15 (5), 3075–3092. https://doi.org/10.1021/acs.jctc.8b01092\n"
  },
  {
    "path": "src/doc/sphinx/source/tools/libnnp.rst",
    "content": ".. _libnnp:\n\nThe libnnp core library\n=======================\n\n.. warning::\n\n   Documentation under construction...\n\nThe ``libnnp`` library provides all the basic ingredients for HDNNP generation or\napplication. For instance, it contains classes for symmetry functions, a neural\nnetwork class and data storage classes. Furthermore, a top-level class\n(nnp::Mode) combines all these building blocks to form a working HDNNP setup.\nMost of the provided tools and the :ref:`LAMMPS interface <if_lammps>` make use of\nthis Mode class and its setup methods. Consequently, the screen and log output\nwill often look similar. This page will walk you through the library output as\nproduced by the :ref:`nnp-predict` example for RPBE-D3 water (see\n``examples/nnp-predict/H2O_RPBE-D3`` directory).\n\nThe initial output section (corresponding to :func:`nnp::Mode::initialize`)\nis simply stating the current version, git branch and commit ID (if available).\nIf the library was compiled with OpenMP support, the number of used threads is\nalso provided (see :ref:`Parallelization <parallelization>`).\n\n.. code-block:: none\n\n   *******************************************************************************\n\n      NNP LIBRARY v2.0.0\n      ------------------\n\n   Git branch  : master\n   Git revision: 7b42366 (7b423664b02ff4e4979301b4a136ac3221f46be2)\n\n   Number of OpenMP threads: 2\n   *******************************************************************************\n\nThe next section (:func:`nnp::Mode::loadSettingsFile`) names which settings file is\nused and how many keywords (see :ref:`Keywords <keywords>`) were found. If\nproblems (unknown or multiply defined keywords) occur, warnings will be issued\nin this section.\n\n.. code-block:: none\n\n   *** SETUP: SETTINGS FILE ******************************************************\n\n   Settings file name: input.nn\n   Read 167 lines.\n   Found 102 lines with keywords.\n   *******************************************************************************\n\nIf data set normalization is used (see the corresponding tool :ref:`nnp-norm`\nand :ref:`here <units>`) this section lists the required quantities to convert\nto normalized (internal) units.\n\n.. code-block:: none\n\n   *** SETUP: NORMALIZATION ******************************************************\n\n   Data set normalization is used.\n   Mean energy per atom     :  -2.5521343547039809E+01\n   Conversion factor energy :   2.4265748255366972E+02\n   Conversion factor length :   5.8038448995319847E+00\n   *******************************************************************************\n\n.. code-block:: none\n\n   *** SETUP: ELEMENT MAP ********************************************************\n\n   Number of element strings found: 2\n   Element  0:  H (  1)\n   Element  1:  O (  8)\n   *******************************************************************************\n\n.. code-block:: none\n\n   *** SETUP: ELEMENTS ***********************************************************\n\n   Number of elements is consistent: 2\n   Atomic energy offsets per element:\n   Element  0:   0.00000000E+00\n   Element  1:   0.00000000E+00\n   Energy offsets are automatically subtracted from reference energies.\n   *******************************************************************************\n\n.. code-block:: none\n\n   *** SETUP: CUTOFF FUNCTIONS ***************************************************\n\n   Parameter alpha for inner cutoff: 0.000000\n   Inner cutoff = Symmetry function cutoff * alpha\n   Equal cutoff function type for all symmetry functions:\n   CutoffFunction::CT_TANHU (2)\n   f(r) = tanh^3(1 - r/rc)\n   *******************************************************************************\n\n.. code-block:: none\n\n   *** SETUP: SYMMETRY FUNCTIONS *************************************************\n\n   Abbreviations:\n   --------------\n   ind .... Symmetry function index.\n   ec ..... Central atom element.\n   ty ..... Symmetry function type.\n   e1 ..... Neighbor 1 element.\n   e2 ..... Neighbor 2 element.\n   eta .... Gaussian width eta.\n   rs ..... Shift distance of Gaussian.\n   la ..... Angle prefactor lambda.\n   zeta ... Angle term exponent zeta.\n   rc ..... Cutoff radius.\n   ct ..... Cutoff type.\n   ca ..... Cutoff alpha.\n   ln ..... Line number in settings file.\n\n   Short range atomic symmetry functions element  H :\n   -------------------------------------------------------------------------------\n    ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n   -------------------------------------------------------------------------------\n      1  H  2  H    1.000E-03 0.000E+00         1.200E+01  2 0.00    98\n      2  H  2  O    1.000E-03 0.000E+00         1.200E+01  2 0.00   108\n      3  H  2  H    1.000E-02 0.000E+00         1.200E+01  2 0.00    99\n      4  H  2  O    1.000E-02 0.000E+00         1.200E+01  2 0.00   109\n      5  H  2  H    3.000E-02 0.000E+00         1.200E+01  2 0.00   100\n      6  H  2  O    3.000E-02 0.000E+00         1.200E+01  2 0.00   110\n      7  H  2  H    6.000E-02 0.000E+00         1.200E+01  2 0.00   101\n      8  H  2  O    6.000E-02 0.000E+00         1.200E+01  2 0.00   111\n      9  H  2  O    1.500E-01 9.000E-01         1.200E+01  2 0.00   112\n     10  H  2  H    1.500E-01 1.900E+00         1.200E+01  2 0.00   102\n     11  H  2  O    3.000E-01 9.000E-01         1.200E+01  2 0.00   113\n     12  H  2  H    3.000E-01 1.900E+00         1.200E+01  2 0.00   103\n     13  H  2  O    6.000E-01 9.000E-01         1.200E+01  2 0.00   114\n     14  H  2  H    6.000E-01 1.900E+00         1.200E+01  2 0.00   104\n     15  H  2  O    1.500E+00 9.000E-01         1.200E+01  2 0.00   115\n     16  H  2  H    1.500E+00 1.900E+00         1.200E+01  2 0.00   105\n     17  H  3  O  O 1.000E-03 0.000E+00 -1  4.0 1.200E+01  2 0.00   162\n     18  H  3  O  O 1.000E-03 0.000E+00  1  4.0 1.200E+01  2 0.00   161\n     19  H  3  H  O 1.000E-02 0.000E+00 -1  4.0 1.200E+01  2 0.00   152\n     20  H  3  H  O 1.000E-02 0.000E+00  1  4.0 1.200E+01  2 0.00   150\n     21  H  3  H  O 3.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   147\n     22  H  3  O  O 3.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   160\n     23  H  3  H  O 3.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   145\n     24  H  3  O  O 3.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   159\n     25  H  3  H  O 7.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   142\n     26  H  3  H  O 7.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   140\n     27  H  3  H  O 2.000E-01 0.000E+00  1  1.0 1.200E+01  2 0.00   137\n   -------------------------------------------------------------------------------\n   Short range atomic symmetry functions element  O :\n   -------------------------------------------------------------------------------\n    ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln\n   -------------------------------------------------------------------------------\n      1  O  2  H    1.000E-03 0.000E+00         1.200E+01  2 0.00   117\n      2  O  2  O    1.000E-03 0.000E+00         1.200E+01  2 0.00   127\n      3  O  2  H    1.000E-02 0.000E+00         1.200E+01  2 0.00   118\n      4  O  2  O    1.000E-02 0.000E+00         1.200E+01  2 0.00   128\n      5  O  2  H    3.000E-02 0.000E+00         1.200E+01  2 0.00   119\n      6  O  2  O    3.000E-02 0.000E+00         1.200E+01  2 0.00   129\n      7  O  2  H    6.000E-02 0.000E+00         1.200E+01  2 0.00   120\n      8  O  2  O    6.000E-02 0.000E+00         1.200E+01  2 0.00   130\n      9  O  2  H    1.500E-01 9.000E-01         1.200E+01  2 0.00   121\n     10  O  2  O    1.500E-01 4.000E+00         1.200E+01  2 0.00   131\n     11  O  2  H    3.000E-01 9.000E-01         1.200E+01  2 0.00   122\n     12  O  2  O    3.000E-01 4.000E+00         1.200E+01  2 0.00   132\n     13  O  2  H    6.000E-01 9.000E-01         1.200E+01  2 0.00   123\n     14  O  2  O    6.000E-01 4.000E+00         1.200E+01  2 0.00   133\n     15  O  2  H    1.500E+00 9.000E-01         1.200E+01  2 0.00   124\n     16  O  2  O    1.500E+00 4.000E+00         1.200E+01  2 0.00   134\n     17  O  3  H  O 1.000E-03 0.000E+00 -1  4.0 1.200E+01  2 0.00   157\n     18  O  3  O  O 1.000E-03 0.000E+00 -1  4.0 1.200E+01  2 0.00   167\n     19  O  3  H  O 1.000E-03 0.000E+00  1  4.0 1.200E+01  2 0.00   156\n     20  O  3  O  O 1.000E-03 0.000E+00  1  4.0 1.200E+01  2 0.00   166\n     21  O  3  H  H 1.000E-02 0.000E+00 -1  4.0 1.200E+01  2 0.00   151\n     22  O  3  H  H 1.000E-02 0.000E+00  1  4.0 1.200E+01  2 0.00   149\n     23  O  3  H  H 3.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   146\n     24  O  3  H  O 3.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   155\n     25  O  3  O  O 3.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   165\n     26  O  3  H  H 3.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   144\n     27  O  3  H  O 3.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   154\n     28  O  3  O  O 3.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   164\n     29  O  3  H  H 7.000E-02 0.000E+00 -1  1.0 1.200E+01  2 0.00   141\n     30  O  3  H  H 7.000E-02 0.000E+00  1  1.0 1.200E+01  2 0.00   139\n   -------------------------------------------------------------------------------\n   Minimum cutoff radius for element  H: 12.000000\n   Minimum cutoff radius for element  O: 12.000000\n   Maximum cutoff radius (global)      : 12.000000\n   *******************************************************************************\n\n.. code-block:: none\n\n   *** SETUP: SYMMETRY FUNCTION GROUPS *******************************************\n\n   Abbreviations:\n   --------------\n   ind .... Symmetry function group index.\n   ec ..... Central atom element.\n   ty ..... Symmetry function type.\n   e1 ..... Neighbor 1 element.\n   e2 ..... Neighbor 2 element.\n   eta .... Gaussian width eta.\n   rs ..... Shift distance of Gaussian.\n   la ..... Angle prefactor lambda.\n   zeta ... Angle term exponent zeta.\n   rc ..... Cutoff radius.\n   ct ..... Cutoff type.\n   ca ..... Cutoff alpha.\n   ln ..... Line number in settings file.\n   mi ..... Member index.\n   sfi .... Symmetry function index.\n   e ...... Recalculate exponential term.\n\n   Short range atomic symmetry function groups element  H :\n   -------------------------------------------------------------------------------\n    ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n   -------------------------------------------------------------------------------\n      1  H  2  H            *         *         1.200E+01  2 0.00     *    *    *  \n      -  -  -  -    1.000E-03 0.000E+00                 -  -    -    97    1    1  \n      -  -  -  -    1.000E-02 0.000E+00                 -  -    -    98    2    3  \n      -  -  -  -    3.000E-02 0.000E+00                 -  -    -    99    3    5  \n      -  -  -  -    6.000E-02 0.000E+00                 -  -    -   100    4    7  \n      -  -  -  -    1.500E-01 1.900E+00                 -  -    -   101    5   10  \n      -  -  -  -    3.000E-01 1.900E+00                 -  -    -   102    6   12  \n      -  -  -  -    6.000E-01 1.900E+00                 -  -    -   103    7   14  \n      -  -  -  -    1.500E+00 1.900E+00                 -  -    -   104    8   16  \n      2  H  2  O            *         *         1.200E+01  2 0.00     *    *    *  \n      -  -  -  -    1.000E-03 0.000E+00                 -  -    -   107    1    2  \n      -  -  -  -    1.000E-02 0.000E+00                 -  -    -   108    2    4  \n      -  -  -  -    3.000E-02 0.000E+00                 -  -    -   109    3    6  \n      -  -  -  -    6.000E-02 0.000E+00                 -  -    -   110    4    8  \n      -  -  -  -    1.500E-01 9.000E-01                 -  -    -   111    5    9  \n      -  -  -  -    3.000E-01 9.000E-01                 -  -    -   112    6   11  \n      -  -  -  -    6.000E-01 9.000E-01                 -  -    -   113    7   13  \n      -  -  -  -    1.500E+00 9.000E-01                 -  -    -   114    8   15  \n      3  H  3  H  O         *         *  *    * 1.200E+01  2 0.00     *    *    * *\n      -  -  -  -  - 1.000E-02 0.000E+00 -1  4.0         -  -    -   151    1   19 1\n      -  -  -  -  - 1.000E-02 0.000E+00  1  4.0         -  -    -   149    2   20 0\n      -  -  -  -  - 3.000E-02 0.000E+00 -1  1.0         -  -    -   146    3   21 1\n      -  -  -  -  - 3.000E-02 0.000E+00  1  1.0         -  -    -   144    4   23 0\n      -  -  -  -  - 7.000E-02 0.000E+00 -1  1.0         -  -    -   141    5   25 1\n      -  -  -  -  - 7.000E-02 0.000E+00  1  1.0         -  -    -   139    6   26 0\n      -  -  -  -  - 2.000E-01 0.000E+00  1  1.0         -  -    -   136    7   27 1\n      4  H  3  O  O         *         *  *    * 1.200E+01  2 0.00     *    *    * *\n      -  -  -  -  - 1.000E-03 0.000E+00 -1  4.0         -  -    -   161    1   17 1\n      -  -  -  -  - 1.000E-03 0.000E+00  1  4.0         -  -    -   160    2   18 0\n      -  -  -  -  - 3.000E-02 0.000E+00 -1  1.0         -  -    -   159    3   22 1\n      -  -  -  -  - 3.000E-02 0.000E+00  1  1.0         -  -    -   158    4   24 0\n   -------------------------------------------------------------------------------\n   Short range atomic symmetry function groups element  O :\n   -------------------------------------------------------------------------------\n    ind ec ty e1 e2       eta        rs la zeta        rc ct   ca    ln   mi  sfi e\n   -------------------------------------------------------------------------------\n      1  O  2  H            *         *         1.200E+01  2 0.00     *    *    *  \n      -  -  -  -    1.000E-03 0.000E+00                 -  -    -   116    1    1  \n      -  -  -  -    1.000E-02 0.000E+00                 -  -    -   117    2    3  \n      -  -  -  -    3.000E-02 0.000E+00                 -  -    -   118    3    5  \n      -  -  -  -    6.000E-02 0.000E+00                 -  -    -   119    4    7  \n      -  -  -  -    1.500E-01 9.000E-01                 -  -    -   120    5    9  \n      -  -  -  -    3.000E-01 9.000E-01                 -  -    -   121    6   11  \n      -  -  -  -    6.000E-01 9.000E-01                 -  -    -   122    7   13  \n      -  -  -  -    1.500E+00 9.000E-01                 -  -    -   123    8   15  \n      2  O  2  O            *         *         1.200E+01  2 0.00     *    *    *  \n      -  -  -  -    1.000E-03 0.000E+00                 -  -    -   126    1    2  \n      -  -  -  -    1.000E-02 0.000E+00                 -  -    -   127    2    4  \n      -  -  -  -    3.000E-02 0.000E+00                 -  -    -   128    3    6  \n      -  -  -  -    6.000E-02 0.000E+00                 -  -    -   129    4    8  \n      -  -  -  -    1.500E-01 4.000E+00                 -  -    -   130    5   10  \n      -  -  -  -    3.000E-01 4.000E+00                 -  -    -   131    6   12  \n      -  -  -  -    6.000E-01 4.000E+00                 -  -    -   132    7   14  \n      -  -  -  -    1.500E+00 4.000E+00                 -  -    -   133    8   16  \n      3  O  3  H  H         *         *  *    * 1.200E+01  2 0.00     *    *    * *\n      -  -  -  -  - 1.000E-02 0.000E+00 -1  4.0         -  -    -   150    1   21 1\n      -  -  -  -  - 1.000E-02 0.000E+00  1  4.0         -  -    -   148    2   22 0\n      -  -  -  -  - 3.000E-02 0.000E+00 -1  1.0         -  -    -   145    3   23 1\n      -  -  -  -  - 3.000E-02 0.000E+00  1  1.0         -  -    -   143    4   26 0\n      -  -  -  -  - 7.000E-02 0.000E+00 -1  1.0         -  -    -   140    5   29 1\n      -  -  -  -  - 7.000E-02 0.000E+00  1  1.0         -  -    -   138    6   30 0\n      4  O  3  H  O         *         *  *    * 1.200E+01  2 0.00     *    *    * *\n      -  -  -  -  - 1.000E-03 0.000E+00 -1  4.0         -  -    -   156    1   17 1\n      -  -  -  -  - 1.000E-03 0.000E+00  1  4.0         -  -    -   155    2   19 0\n      -  -  -  -  - 3.000E-02 0.000E+00 -1  1.0         -  -    -   154    3   24 1\n      -  -  -  -  - 3.000E-02 0.000E+00  1  1.0         -  -    -   153    4   27 0\n      5  O  3  O  O         *         *  *    * 1.200E+01  2 0.00     *    *    * *\n      -  -  -  -  - 1.000E-03 0.000E+00 -1  4.0         -  -    -   166    1   18 1\n      -  -  -  -  - 1.000E-03 0.000E+00  1  4.0         -  -    -   165    2   20 0\n      -  -  -  -  - 3.000E-02 0.000E+00 -1  1.0         -  -    -   164    3   25 1\n      -  -  -  -  - 3.000E-02 0.000E+00  1  1.0         -  -    -   163    4   28 0\n   -------------------------------------------------------------------------------\n   *******************************************************************************\n\n.. code-block:: none\n\n   *** SETUP: NEURAL NETWORKS ****************************************************\n\n   Normalize neurons (all elements): 0\n   -------------------------------------------------------------------------------\n   Atomic short range NN for element  H :\n   Number of weights    :   1325\n   Number of biases     :     51\n   Number of connections:   1376\n   Architecture       27   25   25    1\n   -------------------------------------------------------------------------------\n      1   G   t   t   l\n      2   G   t   t\n      3   G   t   t\n      4   G   t   t\n      5   G   t   t\n      6   G   t   t\n      7   G   t   t\n      8   G   t   t\n      9   G   t   t\n     10   G   t   t\n     11   G   t   t\n     12   G   t   t\n     13   G   t   t\n     14   G   t   t\n     15   G   t   t\n     16   G   t   t\n     17   G   t   t\n     18   G   t   t\n     19   G   t   t\n     20   G   t   t\n     21   G   t   t\n     22   G   t   t\n     23   G   t   t\n     24   G   t   t\n     25   G   t   t\n     26   G\n     27   G\n   -------------------------------------------------------------------------------\n   Atomic short range NN for element  O :\n   Number of weights    :   1400\n   Number of biases     :     51\n   Number of connections:   1451\n   Architecture       30   25   25    1\n   -------------------------------------------------------------------------------\n      1   G   t   t   l\n      2   G   t   t\n      3   G   t   t\n      4   G   t   t\n      5   G   t   t\n      6   G   t   t\n      7   G   t   t\n      8   G   t   t\n      9   G   t   t\n     10   G   t   t\n     11   G   t   t\n     12   G   t   t\n     13   G   t   t\n     14   G   t   t\n     15   G   t   t\n     16   G   t   t\n     17   G   t   t\n     18   G   t   t\n     19   G   t   t\n     20   G   t   t\n     21   G   t   t\n     22   G   t   t\n     23   G   t   t\n     24   G   t   t\n     25   G   t   t\n     26   G\n     27   G\n     28   G\n     29   G\n     30   G\n   -------------------------------------------------------------------------------\n   *******************************************************************************\n\n.. code-block:: none\n\n   *** SETUP: SYMMETRY FUNCTION SCALING ******************************************\n\n   Equal scaling type for all symmetry functions:\n   Scaling type::ST_SCALECENTER (3)\n   Gs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\n   Smin = 0.000000\n   Smax = 1.000000\n   Symmetry function scaling statistics from file: scaling.data\n   -------------------------------------------------------------------------------\n\n   Abbreviations:\n   --------------\n   ind ..... Symmetry function index.\n   min ..... Minimum symmetry function value.\n   max ..... Maximum symmetry function value.\n   mean .... Mean symmetry function value.\n   sigma ... Standard deviation of symmetry function values.\n   sf ...... Scaling factor for derivatives.\n   Smin .... Desired minimum scaled symmetry function value.\n   Smax .... Desired maximum scaled symmetry function value.\n   t ....... Scaling type.\n\n   Scaling data for symmetry functions element  H :\n   -------------------------------------------------------------------------------\n    ind       min       max      mean     sigma        sf  Smin  Smax t\n   -------------------------------------------------------------------------------\n      1  1.09E+00  9.62E+00  2.27E+00  6.79E-01  1.17E-01  0.00  1.00 3\n      2  7.33E-01  5.00E+00  1.33E+00  3.39E-01  2.34E-01  0.00  1.00 3\n      3  7.60E-01  7.14E+00  1.65E+00  5.08E-01  1.57E-01  0.00  1.00 3\n      4  5.48E-01  3.77E+00  1.02E+00  2.54E-01  3.11E-01  0.00  1.00 3\n      5  4.01E-01  4.15E+00  9.09E-01  2.98E-01  2.67E-01  0.00  1.00 3\n      6  3.62E-01  2.27E+00  6.49E-01  1.48E-01  5.25E-01  0.00  1.00 3\n      7  1.89E-01  2.23E+00  4.57E-01  1.60E-01  4.90E-01  0.00  1.00 3\n      8  2.67E-01  1.32E+00  4.24E-01  8.05E-02  9.49E-01  0.00  1.00 3\n      9  2.45E-01  9.48E-01  3.62E-01  5.30E-02  1.42E+00  0.00  1.00 3\n     10  2.22E-01  2.76E+00  5.39E-01  2.01E-01  3.94E-01  0.00  1.00 3\n     11  1.47E-01  5.56E-01  2.68E-01  2.62E-02  2.45E+00  0.00  1.00 3\n     12  9.91E-02  1.73E+00  2.96E-01  1.16E-01  6.14E-01  0.00  1.00 3\n     13  6.51E-02  3.45E-01  1.85E-01  1.97E-02  3.57E+00  0.00  1.00 3\n     14  3.17E-02  9.13E-01  1.50E-01  5.35E-02  1.13E+00  0.00  1.00 3\n     15  2.92E-03  2.65E-01  7.65E-02  1.88E-02  3.82E+00  0.00  1.00 3\n     16  3.21E-04  2.87E-01  4.58E-02  2.33E-02  3.49E+00  0.00  1.00 3\n     17  2.47E-04  1.38E-01  1.77E-02  9.75E-03  7.23E+00  0.00  1.00 3\n     18  5.10E-03  5.83E-01  2.39E-02  3.78E-02  1.73E+00  0.00  1.00 3\n     19  3.23E-04  2.16E-01  1.71E-02  1.40E-02  4.63E+00  0.00  1.00 3\n     20  4.96E-02  1.69E+00  1.45E-01  1.10E-01  6.11E-01  0.00  1.00 3\n     21  3.41E-03  3.16E-01  1.84E-02  2.01E-02  3.20E+00  0.00  1.00 3\n     22  1.31E-04  1.03E-01  6.37E-03  6.61E-03  9.76E+00  0.00  1.00 3\n     23  3.38E-02  9.16E-01  8.13E-02  5.79E-02  1.13E+00  0.00  1.00 3\n     24  4.17E-04  1.58E-01  4.66E-03  9.86E-03  6.35E+00  0.00  1.00 3\n     25  7.35E-04  5.92E-02  3.70E-03  3.31E-03  1.71E+01  0.00  1.00 3\n     26  8.98E-03  1.94E-01  2.41E-02  1.10E-02  5.40E+00  0.00  1.00 3\n     27  2.12E-04  8.78E-03  2.06E-03  5.88E-04  1.17E+02  0.00  1.00 3\n   -------------------------------------------------------------------------------\n   Scaling data for symmetry functions element  O :\n   -------------------------------------------------------------------------------\n    ind       min       max      mean     sigma        sf  Smin  Smax t\n   -------------------------------------------------------------------------------\n      1  1.51E+00  1.00E+01  2.65E+00  6.78E-01  1.18E-01  0.00  1.00 3\n      2  4.44E-01  4.62E+00  9.66E-01  3.37E-01  2.39E-01  0.00  1.00 3\n      3  1.19E+00  7.53E+00  2.03E+00  5.06E-01  1.58E-01  0.00  1.00 3\n      4  2.76E-01  3.39E+00  6.59E-01  2.50E-01  3.21E-01  0.00  1.00 3\n      5  8.06E-01  4.54E+00  1.30E+00  2.94E-01  2.68E-01  0.00  1.00 3\n      6  1.05E-01  1.89E+00  3.07E-01  1.42E-01  5.60E-01  0.00  1.00 3\n      7  5.69E-01  2.62E+00  8.48E-01  1.57E-01  4.89E-01  0.00  1.00 3\n      8  2.33E-02  9.36E-01  1.11E-01  6.98E-02  1.10E+00  0.00  1.00 3\n      9  5.14E-01  1.85E+00  7.25E-01  9.80E-02  7.46E-01  0.00  1.00 3\n     10  1.11E-01  2.91E+00  4.75E-01  2.34E-01  3.57E-01  0.00  1.00 3\n     11  3.53E-01  1.07E+00  5.35E-01  4.52E-02  1.39E+00  0.00  1.00 3\n     12  3.04E-02  2.53E+00  3.17E-01  2.10E-01  4.00E-01  0.00  1.00 3\n     13  1.60E-01  6.63E-01  3.70E-01  3.08E-02  1.99E+00  0.00  1.00 3\n     14  2.78E-03  2.30E+00  1.77E-01  1.86E-01  4.35E-01  0.00  1.00 3\n     15  9.56E-03  3.91E-01  1.53E-01  2.79E-02  2.62E+00  0.00  1.00 3\n     16  3.75E-06  2.04E+00  5.41E-02  1.43E-01  4.91E-01  0.00  1.00 3\n     17  2.47E-03  3.43E-01  1.67E-02  2.19E-02  2.93E+00  0.00  1.00 3\n     18  1.74E-05  5.63E-02  9.55E-04  3.36E-03  1.78E+01  0.00  1.00 3\n     19  5.48E-02  3.02E+00  2.04E-01  2.01E-01  3.37E-01  0.00  1.00 3\n     20  1.38E-03  4.99E-01  1.28E-02  3.18E-02  2.01E+00  0.00  1.00 3\n     21  6.69E-03  2.67E-01  3.09E-02  1.71E-02  3.84E+00  0.00  1.00 3\n     22  1.70E-02  1.42E+00  7.63E-02  9.29E-02  7.14E-01  0.00  1.00 3\n     23  1.98E-02  4.08E-01  4.88E-02  2.55E-02  2.58E+00  0.00  1.00 3\n     24  5.28E-04  2.33E-01  7.21E-03  1.45E-02  4.30E+00  0.00  1.00 3\n     25  1.11E-05  3.53E-02  4.25E-04  2.05E-03  2.83E+01  0.00  1.00 3\n     26  1.60E-02  8.22E-01  5.08E-02  5.28E-02  1.24E+00  0.00  1.00 3\n     27  3.99E-03  7.86E-01  3.69E-02  5.05E-02  1.28E+00  0.00  1.00 3\n     28  4.05E-05  9.84E-02  1.21E-03  5.79E-03  1.02E+01  0.00  1.00 3\n     29  6.04E-03  9.93E-02  1.62E-02  5.52E-03  1.07E+01  0.00  1.00 3\n     30  2.96E-03  1.55E-01  1.16E-02  8.94E-03  6.59E+00  0.00  1.00 3\n   -------------------------------------------------------------------------------\n   *******************************************************************************\n\n.. code-block:: none\n\n   *** SETUP: NEURAL NETWORK WEIGHTS *********************************************\n\n   Weight file name format: weights.%03zu.data\n   Weight file for element  H: weights.001.data\n   Weight file for element  O: weights.008.data\n   *******************************************************************************\n\n.. code-block:: none\n\n   *** SETUP: SYMMETRY FUNCTION STATISTICS ***************************************\n\n   Equal symmetry function statistics for all elements.\n   Collect min/max/mean/sigma                        : 0\n   Collect extrapolation warnings                    : 0\n   Write extrapolation warnings immediately to stderr: 1\n   Halt on any extrapolation warning                 : 0\n   *******************************************************************************\n"
  },
  {
    "path": "src/doc/sphinx/source/tools/nnp-atomenv.rst",
    "content": ".. _nnp-atomenv:\n\nnnp-atomenv\n===========\n\nThis tool creates files which contain atomic environment data in the form of\nsymmetry functions and their derivatives for further processing. In the context\nof high-dimensional neural network potentials symmetry functions act as a local\nenvironment descriptors and determine the energy contribution of each atom.\nHowever, a more detailed description of each atom's surroundings can be provided\nif we include also symmetry functions of close-by neighbors. In particular,\nconsidering the HDNNP expression for forces,\n\n.. math::\n   F_{i,\\alpha} = - \\sum_{j=0}^{N_\\text{atoms}} \\sum_{k=0}^{N_\\text{sym.func.}}\n   \\frac{\\partial E_j}{\\partial G_{j,k}} \\frac{\\partial G_{j,k}}{\\partial x_{i,\n   \\alpha}},\n\nit becomes clear that not only the symmetry function derivatives of the central\natom :math:`i` but also those of neighboring atoms are relevant. Hence, if we\nconstruct a per-atom vector describing the local environment we can add the\nneighbor's symmetry function (derivatives) to the each atom's own list. Note\nhowever, that in order to make these environment vectors comparable the total\nnumber of entries must be identical for all atoms of the same species.  Also, it\nis crucial that the data order is consistent. To make such an environment vector\nunambiguous we therefore fix the number of neighbors and arrange their\ncontributions according to their distance to the central atom. In practice, the\ntool ``nnp-atomenv`` writes the symmetry functions to ``atomic-env.G`` in the\nfollowing way (one atom per row):\n\n.. math::\n   S(i) \\quad \\vec{G}_{i} \\quad \\vec{G}_{n^{S_1}(i, 1)} \\quad \\ldots \\quad\n   \\vec{G}_{n^{S_1}(i, c_{S(i)S_1})} \\quad \\vec{G}_{n^{S_2}(i, 1)}\n   \\quad \\ldots \\quad \\vec{G}_{n^{S_2}(i, c_{S(i)S_2})} \\quad \\ldots,\n\nwhere\n\n  * :math:`S(i)` ... Element string of atom :math:`i`, e.g. ``H``,\n\n  * :math:`\\vec{G}_{i}` ... Symmetry functions of atom :math:`i` as a row vector,\n\n  * :math:`S_j` ... Element string of the :math:`j` th element (sorted according\n    to atomic number), e.g. :math:`S_2 =` ``O`` in water,\n\n  * :math:`n^{S_j}(i, k)` ... a function returning the index of the :math:`k` th\n    nearest neighbor (sorted according to distance) of atom :math:`i` and of element\n    :math:`S_j`.\n\n  * :math:`c_{AB}` ... the maximum amount of neighbors of element `B` given\n    central atom `A` considered (neighbor cutoff).\n\nSimilarly, the symmetry function derivatives in :math:`x`, :math:`y` and :math:`z` direction are\nwritten to ``atomic-env.dGdx``, ``atomic-env.dGdy`` and ``atomic-env.dGdz``,\nrespectively:\n\n.. math::\n\n   S(i) \\quad \\frac{\\partial \\vec{G}_{i}}{\\partial x_{i, \\alpha}} \\quad\n   \\frac{\\partial \\vec{G}_{n^{S_1}(i, 1)}}{\\partial x_{i, \\alpha}} \\quad \\ldots\n   \\quad \\frac{\\partial \\vec{G}_{n^{S_1}(i, c_{S(i)S_1})}}{\\partial\n   x_{i, \\alpha}} \\quad \\frac{\\partial \\vec{G}_{n^{S_2}(i, 1)}}{\\partial x_{i,\n   \\alpha}} \\quad \\ldots \\quad \\frac{\\partial \\vec{G}_{n^{S_2}(i,\n   c_{S(i)S_2})}}{\\partial x_{i, \\alpha}} \\quad \\ldots,\n\nwhere :math:`\\alpha = \\{0, 1, 2\\}` and :math:`x_{i, 0} = x_i, x_{i, 1} = y_i, x_{i, 2} = z_i`.\n\nRequirements:\n-------------\n\nA data set with multiple configurations, a settings file and the symmetry\nfunction scaling data is required:\n\n* ``input.data``\n* ``input.nn``\n* ``scaling.data``\n\nUsage:\n------\n\n.. code-block:: none\n\n   mpirun -np <np> nnp-atomenv <nbins> <ncutij>\n\nwhere\n\n.. code-block:: none\n\n   <np> ....... Number of MPI processes to use.\n   <nbins> .... Number of symmetry function histogram bins.\n   <ncutij> ... Maximum number of neighbor symmetry functions written (for each element combination).\n\nThe ``<nbins>`` parameter determines how many bins will be used for writing out\nsymmetry function histograms (output files ``sf-scaled.XXX.YYYY.histo``). Unlike\nthe tool :ref:`nnp-scaling` the histograms contain data from the scaled symmetry\nfunctions. This output is unrelated to the atomic environment vector files.\n\nThe ``<ncutij>`` command line parameters determine for each element combination\nhow many of the closest neighbors are included in the environment vector output.\nHere, ``i`` is the central atom's element and ``j`` is the neighbor's element,\nsorted according to increasing atomic number. Hence, the ``<ncutij>`` parameter\ndetermine the length of the atomic environment descriptor vector. If set to zero\nfor all elements the output files will just contain the symmetry functions (and\ntheir derivatives) for each atom (one atom per line, columns correspond to\ndifferent symmetry functions).\n\nConsider for example a water data set where you want to extract the symmetry\nfunction information from the first (and second) neighbor shell. First, extract\nthe number of nearest neighbors from the radial distribution function and use\nthem when calling ``nnp-atomenv``:\n\n.. code-block:: none\n\n   mpirun -np 4 nnp-atomenv 500 6 2 4 4\n\nSince elements are always sorted according to their atomic number the neighbor\ncutoffs here are read in this order:\n\n.. code-block:: none\n\n   mpirun -np 4 nnp-atomenv 500 HH HO OH OO\n\nor in words:\n\n  * central atom H: print out information from 6 closest H and 2 closest O neighbors\n  * central atom O: print out information from 4 closest H and 4 closest O neighbors\n\n.. warning::\n\n   Do not run the ``nnp-atomenv`` tool on large data sets as it will create HUGE\n   files!\n\nSample screen output:\n---------------------\n\n.. code-block:: none\n\n   *** SYMMETRY FUNCTION HISTOGRAMS **********************************************\n   \n   Writing histograms with 500 bins.\n   *******************************************************************************\n   \n   *** NEIGHBOR HISTOGRAMS *******************************************************\n   \n   Minimum number of neighbors: 80\n   Mean    number of neighbors: 103.1\n   Maximum number of neighbors: 120\n   Neighbor histogram file: neighbors.histo.\n   *******************************************************************************\n   \n   *** NEIGHBOR LIST *************************************************************\n   \n   Sorting neighbor lists according to element and distance.\n   *******************************************************************************\n   \n   *** NEIGHBOR LIST *************************************************************\n   \n   Writing neighbor lists to file: neighbor-list.data.\n   *******************************************************************************\n   \n   *** ATOMIC ENVIRONMENT ********************************************************\n   \n   Preparing symmetry functions for atomic environment file(s).\n   Maximum number of  H neighbors for central  H atoms: 6\n   Maximum number of  O neighbors for central  H atoms: 2\n   Maximum number of  H neighbors for central  O atoms: 4\n   Maximum number of  O neighbors for central  O atoms: 4\n   Combining atomic environment file: atomic-env.G.\n   Combining atomic environment file: atomic-env.dGdx.\n   Combining atomic environment file: atomic-env.dGdy.\n   Combining atomic environment file: atomic-env.dGdz.\n   *******************************************************************************\n\nFile output:\n------------\n\n*  ``atomic-env.G``: Symmetry function values of each atom and its closest\n   neighbors.\n\n*  ``atomic-env.dGd[xyz]``: Symmetry function derivatives of atoms and neighbors\n   `x`, `y`, and `z` - direction.\n\n*  ``neighbor-list.data``: File containing the neighbor list of all atoms. First\n   line is the number of atoms. Each following line contains the neighbor list of\n   one atom. The first column is the atomic number, then follows the number of\n   neighbors of each element. Then starts the list of neighbor indices.\n\n*  ``neighbors.histo``: A histogram of the neighbor count.\n\n*  ``sf-scaled.XXX.YYYY.histo``: Histograms of all symmetry functions, similar\n   to the output of :ref:`nnp-scaling` but for the scaled symmetry functions.\n"
  },
  {
    "path": "src/doc/sphinx/source/tools/nnp-checkf.rst",
    "content": ".. _nnp-checkf:\n\nnnp-checkf\n==========\n\nThis tool is useful for debugging as it computes numeric forces via the\nsymmetric difference quotient (central difference) and compares it to the\nanalytic forces obtained directly from n2p2's prediction. Parallelization via\nMPI is supported and it can process multiple configurations in the input file.\n\nRequirements:\n-------------\n\nThe HDNNP setup, symmetry function scaling data and weight parameters are\nrequired in the usual files. The data file ``input.data`` may contain multiple\nconfigurations.\n\n* ``input.data``\n* ``input.nn``\n* ``scaling.data``\n* ``weights.???.data``\n\nUsage:\n------\n\n.. code-block:: none\n\n   mpirun -np <np> nnp-checkf <<delta>>\n\nwhere\n\n.. code-block:: none\n\n   <np> ........ Number of MPI processes to use.\n   <<delta>> ... (optional) Displacement for central difference (default: 1.0e-4).\n\nThe ``<<delta>>`` parameter determines the position displacement of atoms used\nfor the central difference approximation of the forces. If no value is provided\nthe default is :math:`\\delta = 10^{-4}`.\n\nSample screen output:\n---------------------\n\n.. code-block:: none\n\n   *** ANALYTIC/NUMERIC FORCES CHECK *********************************************\n   \n   Delta for symmetric difference quotient:   1.000E-04\n   Individual analytic/numeric forces will be written to \"checkf-forces.out\"\n   Per-structure summary of analytic/numeric force comparison will be\n   written to \"checkf-summary.out\"\n   Found 3 configurations in data file: input.data.\n   Starting loop over 3 configurations...\n   \n                          numForces meanAbsError  maxAbsError  verdict\n   -------------------------------------------------------------------\n   Configuration      1:        144    7.168E-10    2.984E-09  OK.\n   Configuration      2:        144    8.215E-10    3.212E-09  OK.\n   Configuration      3:        144    7.254E-10    2.459E-09  OK.\n   *******************************************************************************\n\nFile output:\n------------\n\n*  ``checkf-forces.out``: Comparison of analytic/numeric values, each force one\n   line.\n\n*  ``checkf-summary.out``: Per-structure accumulated comparison (same as screen\n   output).\n\nExamples:\n---------\n\n* Run on 4 cores and override default :math:`\\delta` value:\n\n  .. code-block:: none\n\n     mpirun -np 4 nnp-checkf 1.0E-3\n\n"
  },
  {
    "path": "src/doc/sphinx/source/tools/nnp-convert.rst",
    "content": ".. _nnp-convert:\n\nnnp-convert\n===========\n\nThe ``nnp-convert`` tool converts a given ``input.data`` set file (see \n:ref:`format <cfg_file>`) into a different file format. Currently, the following\nfile formats are supported:\n\n#. `Extended <http://libatoms.github.io/QUIP/io.html#module-ase.io.extxyz>`_ XYZ,\n#. VASP POSCAR.\n\nRequirements:\n-------------\nA configuration file named ``input.data`` needs to be present.\n\nUsage:\n------\n\n.. code-block:: none\n\n   nnp-convert <format> <elem1 <elem2 ...>>\n               <format> ... Structure file output format (xyz/poscar).\n               <elemN> .... Symbol for Nth element.\n\nUnfortunately, the element symbols present in the configuration file are not\nautomatically determined and must be provided via the command line (separated by\nspaces). For XYZ files the order is not important.  \n\n.. warning::\n\n   The order of elements given via the command line arguments is critical for\n   POSCAR output as the atoms will be sorted according to this list. Hence, the\n   order should match the one determined by the POTCAR file.\n\nSample screen output:\n---------------------\n\n.. code-block:: none\n\n   *** NNP-CONVERT ***************************************************************\n\n   Requested file format  : poscar\n   Output file name prefix: POSCAR\n   Number of elements     : 2\n   Element string         : Cu S\n   *******************************************************************************\n   Configuration       1:     144 atoms\n   Configuration       2:     144 atoms\n   Configuration       3:     144 atoms\n   Configuration       4:     144 atoms\n   Configuration       5:     144 atoms\n   Configuration       6:     144 atoms\n   Configuration       7:     144 atoms\n   Configuration       8:     144 atoms\n   Configuration       9:     144 atoms\n   Configuration      10:     144 atoms\n   Configuration      11:     144 atoms\n   Configuration      12:     144 atoms\n   Configuration      13:     144 atoms\n   Configuration      14:     144 atoms\n   Configuration      15:     144 atoms\n   Configuration      16:     144 atoms\n   Configuration      17:     144 atoms\n   Configuration      18:     144 atoms\n   Configuration      19:     144 atoms\n   Configuration      20:     144 atoms\n   *******************************************************************************\n\nFile output:\n------------\n\n* Main output depends on the chosen target file format:\n\n  #. XYZ: ``input.xyz`` An XYZ file with all configurations in ``input.data``.\n  #. POSCAR: For each configuration a separate file with prefix ``POSCAR_`` is written.\n\n* ``nnp-convert.log`` : Log file (copy of screen output).\n\nExamples:\n---------\n\n* Convert to XYZ:\n\n  .. code-block:: none\n\n     nnp-convert xyz S Cu\n\n* Convert to POSCAR:\n\n  .. code-block:: none\n\n     nnp-convert poscar Cu S\n\n"
  },
  {
    "path": "src/doc/sphinx/source/tools/nnp-norm.rst",
    "content": ".. _nnp-norm:\n\nnnp-norm\n========\n\n.. warning::\n\n   The use of this tool is not recommended any more because the data set\n   normalization can now be performed on-the-fly during training with the\n   keyword :ref:`normalize_data_set`.\n\nThis is a helper tool for the :ref:`training procedure <training>` which enables\nan optional data set normalization. Please have a look at this :ref:`explanation\n<units>` why normalization may help to achieve consistent training results.\nA full description of the procedure is provided in section 3.1 in [1]_. In\nshort, the normalization is achieved by subtracting a mean energy per atom and\nconverting energy and length units in such way that the energies per atom and the\nforces have unit standard deviation. In practice, this requires three numbers\nwhich are  computed from statistical characteristics of the data set:\n\n1. mean energy per atom (keyword ``mean_energy``)\n\n2. energy unit conversion factor (keyword ``conv_energy``)\n\n3. length unit conversion factor (keyword ``conv_length``)\n   \nHowever, this tool will not actually apply the normalization to the data set but\nrather store the above numbers as keyword-value pairs in an additional header of\nthe settings file. Other n2p2 tools will read them in, confirm the activation of\nthe normalization in the log file and automatically apply unit conversion\non-the-fly. No additional intervention by the user is required!\n\nRequirements:\n-------------\n\nA data set with multiple configurations and a basic settings file are required:\n\n* ``input.data``\n* ``input.nn``\n\nA working symmetry function setup in the settings file is not required, only\nbasic information about elements is needed.\n\nUsage:\n------\n\n.. code-block:: none\n\n   nnp-norm\n\nSample screen output:\n---------------------\n\n.. code-block:: none\n\n   *** DATA SET NORMALIZATION ****************************************************\n   \n   Writing energy/atom vs. volume/atom data to \"evsv.dat\".\n   \n   Total number of structures: 20\n   Total number of atoms     : 2064\n   Mean/sigma energy per atom:  -2.33538240E-01 +/-   1.17415619E-03\n   Mean/sigma force          :  -8.55943153E-12 +/-   2.67687948E-02\n   Conversion factor energy  :   8.5167544626563699E+02\n   Conversion factor length  :   2.2798325235535355E+01\n   \n   Writing converted data file to \"output.data\".\n   WARNING: This data set is provided for debugging purposes only and is NOT intended for training.\n   \n   Writing backup of original settings file to \"input.nn.bak\".\n   \n   Writing extended settings file to \"input.nn\".\n   \n   Use this settings file for normalized training.\n   *******************************************************************************\n\nFile output:\n------------\n\n* ``input.nn``: The settings file with additional normalization header.\n\n* ``input.nn.bak``: A backup of the original settings file without normalization keywords.\n\n* ``evsv.dat``: Energies, volumes and atom numbers of all configurations in the\n  data set.\n\n* ``output.data``: The data set with normalization applied, only for debugging\n  purposes.\n\n.. [1] Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C. Parallel\n   Multistream Training of High-Dimensional Neural Network Potentials. J. Chem.\n   Theory Comput. 2019, 15 (5), 3075–3092. https://doi.org/10.1021/acs.jctc.8b01092\n"
  },
  {
    "path": "src/doc/sphinx/source/tools/nnp-predict.rst",
    "content": ".. _nnp-predict:\n\nnnp-predict\n===========\n\nThis is a simple tool to predict energies and forces of a single configuration,\ngiven an existing HDNNP parameterization.\n\nRequirements:\n-------------\n\nThe HDNNP setup, symmetry function scaling data and weight parameters are\nrequired in the usual files:\n\n* ``input.data``\n* ``input.nn``\n* ``scaling.data``\n* ``weights.???.data``\n\nUsage:\n------\n\n.. code-block:: none\n\n   nnp-predict <info>\n               <info> ... Write structure information for debugging to \"structure.out\" (0/1)\n\nThe tool will output the resulting potential energy and atomic forces on the\nscreen and in files (see sections below). Enabling the additional debugging\noutput to is usually not necessary. The file \"structure.out\" contains basically\nthe entire content of the ``Structure`` and ``Atom`` instances, i.e. the full\nneighbor lists and symmetry function derivatives of all atoms.\n\n.. warning::\n\n   Depending on the configuration the \"structure.out\" debugging file can be\n   huge.\n\nSample screen output:\n---------------------\n\n.. code-block:: none\n\n   *** PREDICTION ****************************************************************\n   \n   Reading structure file...\n   Structure contains 144 atoms (2 elements).\n   Calculating NNP prediction...\n   \n   -------------------------------------------------------------------------------\n   NNP energy:  -5.73656032E+02\n   \n   NNP forces:\n            1  S  -1.40007861E-01   2.74032613E-02  -5.96150479E-03\n            2  S   1.39972905E-01   2.73894285E-02   5.93808974E-03\n            3  S   1.39988541E-01  -2.73969011E-02   6.02337848E-03\n            4  S  -1.39985315E-01  -2.73976741E-02  -6.01454763E-03\n            5  S  -1.34194641E-01  -3.09539812E-02   3.93006430E-02\n            .\n            .\n            .\n          140 Cu   4.22986438E-02  -1.77295621E-02   3.63706424E-02\n          141 Cu  -3.57169850E-02   7.57362417E-02   1.68472680E-03\n          142 Cu   3.57606444E-02   7.57328191E-02  -1.65808098E-03\n          143 Cu   3.57294618E-02  -7.57352222E-02  -1.67173728E-03\n          144 Cu  -3.57158597E-02  -7.57244307E-02   1.68265914E-03\n   -------------------------------------------------------------------------------\n   Writing output files...\n    - energy.out\n    - nnatoms.out\n    - nnforces.out\n   Writing structure with NNP prediction to \"output.data\".\n   Finished.\n   *******************************************************************************\n\nFile output:\n------------\n\n* ``energy.out``: Contains the potential energy predicted by the NNP.\n\n* ``nnforces.out``: Contains the atomic forces predicted by the NNP.\n\n* ``nnatoms.out``: Contains the atomic energy contributions to the total\n  potential energy.\n\n* ``output.data``: Contains the configuration just like in the ``input.data``\n  file but with NNP energy and force predictions inserted.\n\nExamples:\n---------\n\n* Write out additional structure information file:\n\n  .. code-block:: none\n\n     nnp-predict 1\n"
  },
  {
    "path": "src/doc/sphinx/source/tools/nnp-prune.rst",
    "content": ".. _nnp-prune:\n\nnnp-prune\n=========\n\nThe tool ``nnp-prune`` is used to identify and remove symmetry functions that have\nlittle effect on the training performance. There are two modes of operation:\n\nPrune before training\n^^^^^^^^^^^^^^^^^^^^^\n\nHere, symmetry functions are discarded if their range (i.e. maximum - minimum\nvalue over the entire data set) is below a provided threshold. The first step\nis to calculate all symmetry functions with :ref:`nnp-scaling`:\n\n.. code-block:: bash\n\n   mpirun -np 4 nnp-scaling 500\n\nThis will produce the file ``scaling.data`` where minimum, maximum, mean and sigma\nvalues are stored. Then, in the same directory call for example\n\n.. code-block:: bash\n\n   nnp-prune range 1.0E-4\n\nto eliminate all symmetry functions with range below :math:`10^{-4}`. The resulting\nsettings file is called ``output-prune-range.nn``. It is an exact copy of\n``input.nn`` but all lines with pruned symmetry functions are commented out. If\nthe result is reasonable, rename the file to ``input.nn`` and start over with the\ntraining process (note: do not forget to calculate ``scaling.data`` again with\n:ref:`nnp-scaling`).\n\nPrune after training\n^^^^^^^^^^^^^^^^^^^^\n\nAfter a neural network potential has been fitted with ``nnp-train`` it is possible\nto identify unnecessary symmetry functions with a so-called sensitivity\nanalysis. Here, the derivatives of the output neuron with respect to the input\nlayer neurons, i.e. the symmetry functions, are averaged over the whole data.\nThis analysis is automatically performed by ``nnp-dataset`` and the results are\nstored in files like ``sensitivity.008.out`` (for the oxygen neural network):\n\n.. code-block:: bash\n\n   mpirun -np 4 nnp-dataset 1\n\nWith the sensitivity data ready, use the pruning tool to automatically remove\nsymmetry functions with a sensitivity below the threshold:\n\n.. code-block:: bash\n\n   nnp-prune sensitivity 0.5 max\n\nHere, the threshold is set to 0.5% where 100% is equal to the total sum of all\nsensitivities. The resulting settings file is called\n``output-prune-sensitivity.nn`` and is again an exact copy of ``input.nn``,\nonly with commented pruned symmetry function lines.\n"
  },
  {
    "path": "src/doc/sphinx/source/tools/nnp-scaling.rst",
    "content": ".. _nnp-scaling:\n\nnnp-scaling\n===========\n\n.. warning::\n   Documentation under construction...\n\nThis tool calculates all symmetry functions for a given dataset (\\ ``input.data``\\ ),\nstores scaling information and computes neighbor and symmetry function\nhistograms. It is a prerequisite for training with ``nnp-train``. ``nnp-scaling``\ncan be called with MPI parallelization and requires an additional command line\nargument, e.g.\n\n.. code-block:: none\n\n   mpirun -np 4 nnp-scaling 500\n\nThis will randomly distribute the given structures to 4 cores (for load\nbalancing). The scaling parameters (minimum, maximum, mean and sigma) of\nsymmetry functions are written to ``scaling.data``. Histograms showing the\nsymmetry function value distributions are provided in separate files (e.g.\n``sf.008.0003.histo`` will contain the histogram for symmetry function 3 for\noxygen atoms). In the above example, the command line parameter ``nbin`` is set\nto 500 which determines the number of bins for symmetry function histograms.\nIn addition, a neighbor histogram is written to ``neighbors.histo``. The screen\noutput contains a useful section about memory requirements during training,\ne.g.\n\n.. code-block:: none\n\n   *** MEMORY USAGE ESTIMATION ***************************************************\n\n   Estimated memory usage for training (keyword \"memorize_symfunc_results\":\n   Valid for training of energies and forces.\n   Memory for local structures  :     12459839800 bytes (11882.63 MiB = 11.60 GiB).\n   Memory for all structures    :     49526892170 bytes (47232.53 MiB = 46.13 GiB).\n   Average memory per structure :         6839786 bytes (6.52 MiB).\n   *******************************************************************************\n\nWhile ``nnp-scaling`` itself will not use a lot of RAM memory, training speed with\n``nnp-train`` can be significantly increased if intermediate symmetry function\nresults can be stored and reused. This will usually require a large amount of\nmemory and the above lines present a rough estimate of the minimum usage. In\npractice at least 10% more memory should be expected.\n"
  },
  {
    "path": "src/doc/sphinx/source/tools/nnp-select.rst",
    "content": ".. _nnp-select:\n\nnnp-select\n==========\n\nThe ``nnp-select`` tool extracts a small subset from a larger training data set,\ne.g. for testing purposes. The initial set ``input.data`` is expected to be\nlocated in the current working directory. Two different modes of operation are\nsupported: selecting structures\n\n#. randomly with given seed, or\n#. at regular intervals.\n\nUsage:\n------\n\n.. code-block:: none\n\n   nnp-select <mode> <arg1 <arg2>>\n              <mode> ... Choose selection mode (random/interval).\n              Arguments for mode \"random\":\n                <arg1> ... Ratio of selected structures (1.0 equals 100 %).\n                <arg2> ... Seed for random number generator (integer).\n              Arguments for mode \"interval\":\n                <arg1> ... Select structures in this interval (integer).\n              Execute in directory with these NNP files present:\n              - input.data (structure file)\n\nSample screen output:\n---------------------\n\n.. code-block:: none\n\n   *** NNP-SELECT ****************************************************************\n\n   Selecting every 3 structure.\n   *******************************************************************************\n   Structure       1 selected.\n   Structure       4 selected.\n   Structure       7 selected.\n   Structure      10 selected.\n   Structure      13 selected.\n   Structure      16 selected.\n   *******************************************************************************\n   Total    structures           :      16\n   Selected structures           :       6\n   Selected structures percentage: 37.500 %\n   *******************************************************************************\n\nFile output:\n------------\n\n* ``output.data``\\ : The requested subset of training structures.\n* ``reject.data``\\ : The rejected configurations, i.e. all data minus ``output.data``.\n* ``nnp-select.log`` : Log file (copy of screen output).\n\nExamples:\n---------\n\n* \n  Select randomly 10% of the original set with random seed 123:\n\n  .. code-block:: none\n\n     nnp-select random 0.1 123\n\n* \n  Select every 20th structure from original set (starting with structure 1):\n\n  .. code-block:: none\n\n     nnp-select interval 20\n\n"
  },
  {
    "path": "src/doc/sphinx/source/tools/nnp-train.rst",
    "content": ".. _nnp-train:\n\nnnp-train\n=========\n\n.. warning::\n\n   Documentation in progress...\n\nThis tool implements the actual training procedure for a given data set. It is\nable to train both 2G and 4G [1]_ neural networks (NN). In the latter case the\ntraining procedure consists of two training stages. Stage 1 needs to be done\nfirst. It is the training of the charge NNs. After this is finished one can go\nto stage 2 which consists of training the short-ranged NNs by fitting the data\nto energy and forces.\n\nRequirements:\n-------------\n* ``input.data``\n* ``input.nn``\n* ``scaling.data``\n\nAdditionally for stage 2 in the 4G case:\n\n* ``hardness.???.data``\n* ``weightse.???.data``\n\nUsage:\n-----------\n\nWhen training a 2G NN the following command will train a NN with the given\ntopology in ``input.nn`` for the given data set with 4 MPI tasks\n\n.. code-block:: none\n\n   mpirun -np 4 nnp-train\n\nIf one has specified a 4G NN the command is\n\n.. code-block:: none\n\n   mpirun -np 4 nnp-train <n>\n\nwhere ``<n>`` is the stage (1 or 2). After finishing stage 1 one has to choose\nthe NN architecture of the preferred training epoch. Usually one picks the epoch\nwith the lowest RMSE in the training set but there may be reasons to deviate\nfrom that rule. After deciding for epoch ``<m>`` one has to rename the files\n``hardness.???.<m>.out`` and ``weightse.???.<m>.out`` to ``hardness.???.data``\nand ``weightse.???.data``, respectively.\nWhen the training is finished (after stage 2 with the 4G NN or after the\ntraining with the 2G NN) it is again necessary to pick an epoch ``<m>`` of this\nrun and rename the files ``weights.???.<m>.out`` to ``weights.???.data``.\n\nSample screen output:\n---------------------\n\nA typical stage 1 training with a 4G network looks like this:\n\n.. code-block:: none\n\n   .\n   .\n   .\n   *** TRAINING LOOP *************************************************************\n\n   The training loop output covers different errors, update and\n   timing information. The following quantities are organized\n   according to the matrix scheme below:\n   -------------------------------------------------------------------\n   ep ........ Epoch.\n   Q_count ... Number of charge updates.\n   Q_train ... RMSE of training charges.\n   Q_test .... RMSE of test     charges.\n   Q_pt ...... Percentage of time for charge updates w.r.t. to t_train.\n   count ..... Total number of updates.\n   train ..... Percentage of time for training.\n   error ..... Percentage of time for error calculation.\n   other ..... Percentage of time for other purposes.\n   epoch ..... Total time for this epoch (seconds).\n   total ..... Total time for all epochs (seconds).\n   -------------------------------------------------------------------\n   charge     ep  Q_count       Q_train        Q_test    Q_pt\n   timing     ep    count  train  error  other      epoch      total\n   -------------------------------------------------------------------\n   CHARGE      0        0   2.30301E-01   2.75350E-01     0.0\n   TIMING      0        0    0.0   58.3   41.7       0.09       0.09\n   ------\n   CHARGE      1        4   1.64420E-02   1.25118E-02   100.0\n   TIMING      1        4   92.8    3.8    3.3       0.41       0.49\n   ------\n   CHARGE      2        4   8.13293E-03   4.64616E-03   100.0\n   TIMING      2        4   91.7    4.5    3.9       0.34       0.83\n   ------\n   .\n   .\n   .\n   ------\n   CHARGE     10        4   3.41430E-03   2.22138E-03   100.0\n   TIMING     10        4   90.0    5.0    5.0       0.38       3.65\n   -------------------------------------------------------------------------------\n   TIMING Training loop finished: 3.65 seconds.\n   *******************************************************************************\n\nWhereas 2G NN training or stage 2 training with 4G NN produces something similar\nto this:\n\n.. code-block:: none\n\n   .\n   .\n   .\n   *** TRAINING LOOP *************************************************************\n   \n   The training loop output covers different errors, update and\n   timing information. The following quantities are organized\n   according to the matrix scheme below:\n   -------------------------------------------------------------------\n   ep ........ Epoch.\n   E_count ... Number of energy updates.\n   E_train ... RMSE of training energies per atom.\n   E_test .... RMSE of test     energies per atom.\n   E_pt ...... Percentage of time for energy updates w.r.t. to t_train.\n   F_count ... Number of force updates.\n   F_train ... RMSE of training forces.\n   F_test .... RMSE of test     forces.\n   F_pt ...... Percentage of time for force updates w.r.t. to t_train.\n   count ..... Total number of updates.\n   train ..... Percentage of time for training.\n   error ..... Percentage of time for error calculation.\n   other ..... Percentage of time for other purposes.\n   epoch ..... Total time for this epoch (seconds).\n   total ..... Total time for all epochs (seconds).\n   -------------------------------------------------------------------\n   energy     ep  E_count       E_train        E_test    E_pt\n   force      ep  F_count       F_train        F_test    F_pt\n   timing     ep    count  train  error  other      epoch      total\n   -------------------------------------------------------------------\n   ENERGY      0        0   1.80089E-02   1.72559E-02     0.0\n   FORCE       0        0   1.76247E-01   1.93256E-01     0.0\n   TIMING      0        0    0.0   82.9   17.1       0.12       0.12\n   ------\n   ENERGY      1        4   5.48098E-05   2.99658E-05    15.5\n   FORCE       1       16   3.97965E-03   3.93252E-03    84.5\n   TIMING      1       20   95.4    3.5    1.1       1.21       1.33\n   ------\n   ENERGY      2        4   1.62363E-05   8.82677E-06    14.1\n   FORCE       2       16   3.15635E-03   2.18593E-03    85.9\n   TIMING      2       20   95.2    3.6    1.1       1.23       2.56\n   ------\n   .\n   .\n   .\n   ------\n   ENERGY     10        4   2.47602E-05   8.54473E-06    14.2\n   FORCE      10       16   8.73691E-03   1.41630E-02    85.8\n   TIMING     10       20   94.5    4.0    1.5       1.23      12.35\n   -------------------------------------------------------------------------------\n   TIMING Training loop finished: 12.35 seconds.\n   *******************************************************************************\n\nFile output:\n------------\n\nAlways generated:\n^^^^^^^^^^^^^^^^^\n\nIn the following ``[...]`` is a part of the filename that only exists in 4G training.\n\n* ``learning-curve.out[.stage-<n>]``: Contains the errors of the NN after each\n  epoch for all quantities that are used for this training.\n\n* ``test.data``: Contains the data that is only used for testing but not for\n  training (formatted like ``input.data``).\n\n* ``train.data``: Contains the data that is only used for training but not for\n  testing (formatted like ``input.data``).\n\n* ``updater.???.out[.stage-<n>]``: Contains informations about the optimization\n  algorithm that was used for training the NN.\n\n* ``timing.out[.stage-<n>]``: Contains information about the time needed for\n  individual tasks in the training procedure (e.g. update and error\n  calculation).\n\nOptional:\n^^^^^^^^^\n\nIn 4G stage 1 (if ``write_weights_epoch`` is set non-zero):\n\n* ``hardness.???.??????.out``\n* ``weightse.???.??????.out``\n\nIn 2G and 4G stage 2 (if ``write_weights_epoch`` is set non-zero):\n\n* ``weights.???.??????.out``\n\nIn 4G stage 1 (if ``write_traincharges`` is set non-zero):\n\n* ``traincharges.??????.out``: Contains a comparison between the reference charges\n  and the predicted charges for the data used in the training after the epoch\n  denoted by ``??????``.\n\n* ``testcharges.??????.out``: Contains a comparison between the reference charges\n  and the predicted charges for the data used for testing after the epoch\n  denoted by ``??????``.\n\n\nIn 2G or 4G stage 2 (if ``write_trainpoints`` is set non-zero):\n\n* ``trainpoints.??????.out``: Contains a comparison between the reference energies\n  and the predicted energies for the data used in the training after the epoch\n  denoted by ``??????``.\n\n* ``testpoints.??????.out``: Contains a comparison between the reference\n  energies and the predicted energies for the data used for testing after the epoch\n  denoted by ``??????``.\n\nIn 2G or 4G stage 2 (if ``write_trainforces`` is set non-zero):\n\n* ``trainforces.??????.out``: Contains a comparison between the reference forces\n  and the predicted forces for the data used in the training after the epoch\n  denoted by ``??????``.\n\n* ``testforces.??????.out``: Contains a comparison between the reference\n  forces and the predicted forces for the data used for testing after the epoch\n  denoted by ``??????``.\n\n\n.. [1] Ko, T. W.; Finkler, J. A.; Goedecker, S.; Behler, J. A Fourth-Generation High-Dimensional Neural Network Potential with Accurate Electrostatics Including Non-Local Charge Transfer. Nature Communications 2021, 12 (1), 398. https://doi.org/10.1038/s41467-020-20427-2.\n"
  },
  {
    "path": "src/doc/sphinx/source/topics/build.rst",
    "content": ".. _build:\n\nBuild instructions\n==================\n\nCode structure\n--------------\n\nThis package contains multiple components with varying interdependencies and\ndependencies on third-party libraries. You may not need to build all\ncomponents, this depends on the intended use. The following table lists all\ncomponents and their respective requirements (follow the links for more\ninformation).\n\n+---------------------------------+------------------------------+------------------------------------------------------+\n| Component                       | Requirements                 | Function                                             |\n+=================================+==============================+======================================================+\n| :ref:`libnnp <libnnp>`          | C++11 compiler (icpc, g++)   | NNP core library (NN, SF, Structure, ...)            |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| libnnpif                        | libnnp, MPI                  | Interfaces to other software (LAMMPS, ...)           |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| libnnptrain                     | libnnp, MPI, GSL, Eigen 3.3+ | Dataset and training routines (Kalman, ...).         |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| :ref:`nnp-convert`              | libnnp                       | Convert between structure file formats.              |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| nnp-cutoff                      | libnnp                       | Test speed of different cutoff functions.            |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| nnp-dist                        | libnnp                       | Calculate radial and angular distribution functions. |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| :ref:`nnp-predict`              | libnnp                       | Predict energy and forces for one structure.         |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| :ref:`nnp-prune`                | libnnp                       | Prune symmetry functions.                            |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| :ref:`nnp-select`               | libnnp                       | Select subset from data set.                         |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| nnp-symfunc                     | libnnp                       | Symmetry function shape from settings file.          |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| :ref:`nnp-atomenv`              | libnnptrain                  | Write atomic environment data to files.              |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| nnp-checkdw                     | libnnptrain                  | Check analytic vs. numeric weight derivatives.       |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| :ref:`nnp-checkf`               | libnnptrain                  | Check analytic vs. numeric forces.                   |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| nnp-comp2                       | libnnptrain                  | Compare prediction of 2 NNPs for data set.           |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| nnp-dataset                     | libnnptrain                  | Calculate energies and forces for a whole data set.  |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| :ref:`nnp-norm`                 | libnnptrain                  | Calculate normalization factors for data set.        |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| :ref:`nnp-scaling`              | libnnptrain                  | Calculate symmetry function values for data set.     |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| nnp-train                       | libnnptrain                  | Train a neural network potential.                    |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| :ref:`lammps-hdnnp <if_lammps>` | libnnpif                     | Pair style ``hdnnp`` for LAMMPS                      |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| pynnp                           | libnnp, python, cython       | Python interface to NNP library.                     |\n+---------------------------------+------------------------------+------------------------------------------------------+\n| doc                             | Sphinx, Doxygen, Breathe     | Documentation.                                       |\n+---------------------------------+------------------------------+------------------------------------------------------+\n\nDependencies\n------------\n\nIn order to compile n2p2 the following packages/libraries are needed\n\n    * **make**\n    * **C++ Compiler** (Makefiles are provided for GNU, Intel and LLVM)\n    * **Eigen**\n    * **MPI** Implementation (e.g. OpenMPI)\n    * **BLAS** Implementation\n    * **GNU Scientific Library** (GSL).\n\nIf the compiler can't find Eigen although it is installed, you may need to\ncreate a symlink to the directory the compiler is looking for. This is\nexplained here: https://eigen.tuxfamily.org/dox/GettingStarted.html.\n\nFor example on **Ubuntu** one can run\n\n.. code-block:: bash\n\n    apt install build-essential libeigen3-dev libopenmpi-dev libblas-dev libgsl-dev\n\n\nThe master makefile\n-------------------\n\nA master makefile is provided in the ``src`` directory which provides targets\nfor all individual components.  For instance, compiling the interface library\n``libnnpif`` requires only to type\n\n.. code-block:: bash\n\n   make libnnpif\n\nin the ``src`` directory. Similarly, to build the application ``nnp-predict``\nrun\n\n.. code-block:: bash\n\n   make nnp-predict\n\nIf an application depends on libraries, these will be built in advance\nautomatically. Compiled binaries will be copied to the ``bin`` path (relative to\nthe root directory), whereas libraries can be found in the ``lib`` folder.  To\nclean up individual components use\n\n.. code-block:: bash\n\n   make clean-<component>\n\nor to clean everything (except documentation) use\n\n.. code-block:: bash\n\n   make clean\n\nBy default, all libraries and applications will be built for static linking,\ni.e ``.a`` versions of libraries and statically built versions of executables\nare created. If dynamic linking is preferred use the ``MODE=shared`` switch as\nadditional argument of the make command:\n\n.. code-block:: bash\n\n   make MODE=shared nnp-predict\n\nThis will build ``.so`` versions of libraries and executables which require\ndynamic linking at runtime. Do not forget to point your linker to the ``lib``\ndirectory, e.g. correctly set the environment variable ``LD_LIBRARY_PATH``.\n\nThere are three different choices for the ``MODE`` switch: \n\n   * ``static`` (*default*): This is the default which is used when no mode is\n     explicitly set at the command line. Static build of libraries and\n     applications.\n\n   * ``shared``: Use for dynamic linking, creates ``.so`` versions of libraries.\n\n   * ``test``: Special builds for CI tests and coverage reports.\n\nCurrently the build process has been tested with two different compilers, the\nGNU compiler g++ 5.4 (``gnu``) and the Intel compiler 17 (``intel``). It is\npossible to switch between them via the ``COMP`` variable, e.g.\n\n.. code-block:: bash\n\n   make libnnp COMP=intel\n\nIf you need to change compiler variables and paths have a look at the\ncorresponding makefiles containing global build parameters:\n\n.. code-block:: bash\n\n   src/makefile.gnu\n   src/makefile.intel\n\nYou can also create new parameter makefiles based on the above and change the\nfile name suffix according to your target:\n\n.. code-block:: bash\n\n   src/makefile.<target>\n   make libnnp COMP=<target>\n\n.. note::\n\n   In contrast to earlier versions it is now safe to use the `-j` switch to\n   enable parallel compilation. By default only a single processor is used. For\n   instance, in order to use 4 processors to build all components type:\n\n   .. code-block:: bash\n   \n      make -j 4\n\nIndividual component makefiles\n------------------------------\n\nIt is also possible to invoke individual makefiles for each component manually.\nJust switch to the corresponding folder and use ``make MODE=<mode>\nCOMP=<target>``. The global build parameters will be used from the\n``src/makefile.<target>`` file.\n\nProject-wide compilation options\n--------------------------------\n\nEach of the build parameter makefiles ``src/makefile.<target>`` contains a\nsection at the end which allows to enable/disable certain options at compile\ntime:\n\nSymmetry function groups\n^^^^^^^^^^^^^^^^^^^^^^^^\n\n**Flag:** ``-DN2P2_NO_SF_GROUPS`` (default: *disabled*)\n\nIf this flag is set the symmetry function group feature will be disabled\neverywhere. This will result in a much worse performance but may be useful for\ndebugging and development purposes. Note that disabling symmetry function groups\nwill not change results, please see details in this publication [1]_.\n\nImproved symmetry function derivative memory\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n**Flag:** ``-DN2P2_FULL_SFD_MEMORY`` (default: *disabled*)\n\nBy default *n2p2* reduces the memory usage when multiple elements are present by\neliminating storage for symmetry function derivatives which are zero by\ndefinition. This happens whenever a symmetry function is only sensitive to\nneighbors of certain (and not all) elements. Then, there is no space required\nfor derivatives with respect to neighbors of all other elements and hence a\nsignificant amount of memory allocation can be avoided. The actual benefit\ndepends on the symmetry function setup, as a rough estimate expect about 30 to\n50% reduction. This feature is particularly useful for training of large data\nsets when symmetry function derivatives are stored in memory (keyword\n``memorize_symfunc_results``).\n\nHowever, for debugging and development purposes (see e.g. `this\ndiscussion <https://github.com/CompPhysVienna/n2p2/issues/68>`__) it can be\nhelpful to keep the naive, full symmetry function derivative memory allocation.\nThis can be achieved by enabling the flag ``-DN2P2_FULL_SFD_MEMORY``. Only in\nthis case there is a one-to-one correspondance between the list of symmetry\nfunctions in the :ref:`libnnp <libnnp>` output and the symmetry function\nderivative vectors in :cpp:member:`nnp::Atom::Neighbor::dGdr`.\n\nNormally, i.e. when ``-DN2P2_FULL_SFD_MEMORY`` is **disabled**, an additional\nsection in the :ref:`libnnp <libnnp>` output will displayed after the ``SETUP:\nSYMMETRY FUNCTIONS`` section, which indicates the amount of still required\nmemory for symmetry function derivatives. Here is how the output looks like for\nthe RPBE-D3 water example (``examples/nnp-predict/H2O_RPBE-D3``):\n\n.. code-block:: none\n\n   *** SETUP: SYMMETRY FUNCTION MEMORY *******************************************\n\n   Symmetry function derivatives memory table for element  H :\n   -------------------------------------------------------------------------------\n   Relevant symmetry functions for neighbors with element:\n   -  H:   15 of   27 ( 55.6 %)\n   -  O:   19 of   27 ( 70.4 %)\n   -------------------------------------------------------------------------------\n   Symmetry function derivatives memory table for element  O :\n   -------------------------------------------------------------------------------\n   Relevant symmetry functions for neighbors with element:\n   -  H:   18 of   30 ( 60.0 %)\n   -  O:   16 of   30 ( 53.3 %)\n   -------------------------------------------------------------------------------\n   *******************************************************************************\n\nBenchmarking the training program and the LAMMPS interface with the same\nsystem gives the following results: \n\n+---------------------------------+-------------+------------+------------+\n| ``-DN2P2_FULL_SFD_MEMORY``      | *enabled*   | *disabled* | difference |\n+=================================+=============+============+============+\n| Training (memory)               | 55.2 GB     | 37.8 GB    | -31.5 %    |\n+---------------------------------+-------------+------------+------------+\n| MD with LAMMPS (memory)         | 725.6 MB    | 500.0 MB   | -31.1 %    |\n+---------------------------------+-------------+------------+------------+\n| MD with LAMMPS (speed)          | 33.82 s     | 34.14 s    |  +0.9 %    |\n+---------------------------------+-------------+------------+------------+\n\nGiven the significant reduction in memory and the negligible impact on speed\nthe improved memory layout is used by default (``-DN2P2_FULL_SFD_MEMORY``\ndisabled).\n\n.. [1] Singraber, A.; Behler, J.; Dellago, C. Library-Based LAMMPS\n   Implementation of High-Dimensional Neural Network Potentials. J. Chem. Theory\n   Comput. 2019, 15 (3), 1827–1840. https://doi.org/10.1021/acs.jctc.8b00770\n"
  },
  {
    "path": "src/doc/sphinx/source/topics/cfg_file.rst",
    "content": ".. _cfg_file:\n\nConfiguration file format\n=========================\n\nAtomic configurations are stored on disk by NNP applications in a simple ASCII\nfile. Data sets with training structures need to be provided in the same format.\nThe file name for input configurations is usually ``input.data``. A configuration\nfile may contain multiple structures, each enclosed by the ``begin`` and ``end``\nkeywords. The lines in between must begin with one of the following keywords:\n\n\n* ``atom``\n* ``lattice``\n* ``comment``\n* ``energy``\n* ``charge``\n\nHere is a sample layout:\n\n.. code-block:: none\n\n   begin\n   comment <comment>\n   lattice <ax> <ay> <az>\n   lattice <bx> <by> <bz>\n   lattice <cx> <cy> <cz>\n   atom <x1> <y1> <z1> <e1> <c1> <n1> <fx1> <fy1> <fz1> \n   atom <x2> <y2> <z2> <e2> <c2> <n2> <fx2> <fy2> <fz2> \n   ...\n   atom <xn> <yn> <zn> <en> <cn> <nn> <fxn> <fyn> <fzn> \n   energy <energy>\n   charge <charge>\n   end\n   begin\n   ...\n   end\n   ...\n   begin\n   ...\n   end\n\nwhere the arguments of the keywords are:\n\n\n* ``<comment>`` : comment line\n* ``<ax>``... ``<cz>`` : box vectors :math:`\\vec{\\mathbf{a}}, \\vec{\\mathbf{b}}, \\vec{\\mathbf{c}}` (see :func:`nnp::Structure::calculateInverseBox`).\n* ``<x1>``... ``<zn>`` : atom coordinates of ``n`` atoms\n* ``<e1>``... ``<en>`` : atom element string (e.g. Cd, S)\n* ``<c1>``... ``<cn>`` : not (yet) used, reserved for atom charge in case of long range neural network (to be implemented)\n* ``<n1>``... ``<nn>`` : not used\n* ``<fx1>``... ``<fzn>`` : force components of ``n`` atoms\n* ``<energy>`` : total potential energy\n* ``<charge>`` : total charge (for long range neural network only)\n\nThe ``lattice`` section must be omitted for non-periodic structures. It is\npossible to mix periodic and non-periodic structures. Also, configurations may\ncontain different numbers of atoms. If atoms in a periodic structure are\ninitially outside of the simulation box they will be automatically mapped back\ninto the box (see :func:`nnp::Structure::remap`). Here is an example\nconfiguration file with 3 structures, 2 periodic and 1 non-periodic:\n\n.. code-block:: none\n\n   begin\n   comment This periodic structure contains 2 Cd and 2 S atoms.\n   lattice 1.0 0.0 0.0\n   lattice 0.0 1.0 0.0\n   lattice 0.0 0.0 1.0\n   atom 0.1 0.2 0.3 Cd -0.1 0.0 -0.1 -0.3  0.1\n   atom 0.2 0.4 0.8 Cd -0.1 0.0 -0.2  0.6 -0.6\n   atom 0.7 0.2 0.7 S   0.1 0.0 -0.8 -0.1  0.1\n   atom 0.1 0.1 0.4 S   0.1 0.0  1.1 -0.2  0.4\n   energy 123.456\n   charge 0.0\n   end\n   begin\n   comment This non-periodic structure contains 1 Cd and 2 S atoms.\n   atom 0.9 0.1 0.8 Cd -0.1 0.0 -0.3 -0.3  0.1\n   atom 0.7 0.2 0.2 S   0.1 0.0 -0.8  0.1  0.3\n   atom 0.6 0.9 0.4 S   0.1 0.0  1.1  0.2 -0.4\n   energy 1337.00\n   charge 0.0\n   end\n   begin\n   comment This periodic structure contains 3 Cd and 3 S atoms.\n   lattice 2.0 0.0 0.0\n   lattice 1.0 2.0 0.0\n   lattice 1.0 1.0 2.0\n   atom 1.9 0.2 1.7 S   0.1 0.0  0.4 -0.1 -0.2\n   atom 1.1 0.2 0.5 Cd -0.1 0.0 -0.1 -0.3  0.2\n   atom 0.2 1.4 0.8 Cd -0.1 0.0 -0.2  0.8  0.5\n   atom 0.9 0.2 1.7 S   0.1 0.0 -0.7 -0.3 -0.6\n   atom 0.8 1.2 0.1 Cd -0.1 0.0 -0.2  0.1  0.5\n   atom 0.1 0.1 0.4 S   0.1 0.0  0.8 -0.2 -0.4\n   energy 543.210\n   charge 0.0\n   end\n\nManual train/test set definition\n--------------------------------\n\nSince n2p2 version 2.3.0 it is possible to manually assign structures to the\ntraining or test set already in the ``input.data`` file. Just add the string\n``set=train`` or ``set=test`` right after the structure start marker ``begin``.\nFor example:\n\n.. code-block:: none\n\n   begin set=train\n   lattice 1.0 0.0 0.0\n   lattice 0.0 1.0 0.0\n   lattice 0.0 0.0 1.0\n   atom 0.1 0.2 0.3 Cd -0.1 0.0 -0.1 -0.3  0.1\n   atom 0.1 0.1 0.4 S   0.1 0.0  1.1 -0.2  0.4\n   energy 123.456\n   charge 0.0\n   end\n   begin set=test\n   lattice 1.0 0.0 0.0\n   lattice 0.0 1.0 0.0\n   lattice 0.0 0.0 1.0\n   atom 0.1 0.2 0.3 Cd -0.1 0.0 -0.1 -0.3  0.1\n   atom 0.1 0.1 0.4 S   0.1 0.0  1.1 -0.2  0.4\n   energy 123.456\n   charge 0.0\n   end\n\nThis assignment takes precedence over the usual random split performed by\n``nnp-train``. Structures which are not labelled with the ``set=`` method will\nstill be assigned randomly to training/test sets according to the\n``test_fraction`` keyword.\n"
  },
  {
    "path": "src/doc/sphinx/source/topics/descriptors.rst",
    "content": ".. _descriptors:\n\nAtomic environment descriptors\n==============================\n\nMultiple atomic environment descriptors (symmetry functions) are already\nimplemented. Use them via the ``symfunction_short`` keyword (see\n:ref:`this<keywords>` page).\n\nOriginal atom-centered symmetry functions\n-----------------------------------------\n\nTaken from the original 2007 paper\n\n`J. Behler and M. Parrinello, Phys. Rev. Lett. 98, 146401 (2007)\n<https://doi.org/10.1103/PhysRevLett.98.146401>`_\n\nthese are the basic radial and angular symmetry functions:\n\n\n* Radial symmetry function (:cpp:class:`nnp::SymFncExpRad`):\n\n  .. math::\n\n     G^2_i = \\sum_{j \\neq i} \\mathrm{e}^{-\\eta(r_{ij} - r_s)^2} f_c(r_{ij})\n\n* Angular symmetry function (:cpp:class:`nnp::SymFncExpAngn`):\n\n  .. math::\n\n     G^3_i = 2^{1-\\zeta} \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n             \\left( 1 + \\lambda \\cos \\theta_{ijk} \\right)^\\zeta\n             \\mathrm{e}^{-\\eta( r_{ij}^2 + r_{ik}^2 + r_{jk}^2 ) }\n             f_c(r_{ij}) f_c(r_{ik}) f_c(r_{jk})\n\nAtom-centered symmetry functions (continued)\n--------------------------------------------\n\nIn 2011 more symmetry functions were presented here:\n\n`J. Behler, J. Chem. Phys. 134, 074106 (2011) <http://dx.doi.org/10.1063/1.3553717>`_\n\nAmongst others a variant of the above angular symmetry function was introduced:\n\n\n* Modified angular symmetry function (:cpp:class:`nnp::SymFncExpAngw`, for\n  historic reasons the type number here is 9):\n\n  .. math::\n\n     G^9_i = 2^{1-\\zeta} \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n             \\left( 1 + \\lambda \\cos \\theta_{ijk} \\right)^\\zeta\n             \\mathrm{e}^{-\\eta( r_{ij}^2 + r_{ik}^2 ) } f_c(r_{ij}) f_c(r_{ik})\n\n.. note::\n\n   The implementation of both angular symmetry functions described above also\n   supports an additional shift parameter :math:`r_s` in the exponential function\n   (analogous to the radial symmetry function or the weighted symmetry functions\n   below). Specifying the shift parameter is optional, omitting it will reproduce\n   the formulae given above.\n\nWeighted atom-centered symmetry functions\n-----------------------------------------\n\nIn 2018 an approach to overcome limitiations for systems with many different\natom species was put forward here:\n\n`M. Gastegger, L. Schwiedrzik, M. Bittermann, F. Berzsenyi and P. Marquetand,\nJ. Chem. Phys. 148, 241709 (2018) <https://doi.org/10.1063/1.5019667>`_\n\nHere two variants of the original symmetry functions were presented:\n\n\n* Weighted radial symmetry function (:cpp:class:`nnp::SymFncExpRadWeighted`)\n\n  .. math::\n\n     G^{12}_i = \\sum_{j \\neq i} Z_j \\,\n                \\mathrm{e}^{-\\eta(r_{ij} - r_s)^2}\n                f_c(r_{ij})\n\n* Weighted angular symmetry function (:cpp:class:`nnp::SymFncExpAngnWeighted`)\n\n  .. math::\n\n     G^{13}_i = 2^{1-\\zeta} \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n                Z_j Z_k \\,\n                \\left( 1 + \\lambda \\cos \\theta_{ijk} \\right)^\\zeta\n                \\mathrm{e}^{-\\eta \\left[\n                (r_{ij} - r_s)^2 + (r_{ik} - r_s)^2 + (r_{jk} - r_s)^2 \\right] }\n                f_c(r_{ij}) f_c(r_{ik}) f_c(r_{jk})\n\n.. _polynomial_sf:\n\nLow-cost polynomial symmetry functions with compact support\n-----------------------------------------------------------\n\nIn 2020 a new set of computationally efficient symmetry functions was proposed\nhere:\n\n`Bircher, M. P.; Singraber, A.; Dellago, C., arXiv:2010.14414 [cond-mat,\nphysics:physics] (2020). <http://arxiv.org/abs/2010.14414>`__\n\nIn contrast to the above definitions these **polynomial** symmetry functions do\nnot require the computation of expensive exponential terms because they are\nbased solely on polynomial window functions in the radial and angular domain. As\nshown in the publication a significant increase in performance ensues without\nsacrificing descriptive power. Furthermore, they are well suited to describe\ncomplex atomic environments because their angular sensitivity can be easily\ncontrolled via the free hyperparameters. The following variants of polynomial\nsymmetry functions are implemented (here :math:`C(x, x_\\text{low},\nx_\\text{high})` is a function with compact support :math:`\\left[x_\\text{low},\nx_\\text{high}\\right]`):\n\n* Radial symmetry function (:cpp:class:`nnp::SymFncCompRad`)\n\n  .. math::\n\n     G^{20}_i = \\sum_{\\substack{j \\neq i}} C(r_{ij}, r_l, r_c)\n\n* Angular symmetry function, narrow variant (:cpp:class:`nnp::SymFncCompAngn`)\n\n  .. math::\n\n     G^{21}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}} C(r_{ij}, r_l, r_c)\n                C(r_{ik}, r_l, r_c) C(r_{jk}, r_l, r_c)\n                C(\\theta_{ijk}, \\theta_l, \\theta_r)\n\n* Angular symmetry function, wide variant (:cpp:class:`nnp::SymFncCompAngw`)\n\n  .. math::\n\n     G^{22}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}} C(r_{ij}, r_l, r_c)\n                C(r_{ik}, r_l, r_c) C(\\theta_{ijk}, \\theta_l, \\theta_r)\n\n* Weighted radial symmetry function (:cpp:class:`nnp::SymFncCompRadWeighted`)\n\n  .. math::\n\n     G^{23}_i = \\sum_{\\substack{j \\neq i}} Z_j C(r_{ij}, r_l, r_c)\n\n* Weighted angular symmetry function, narrow variant\n  (:cpp:class:`nnp::SymFncCompAngnWeighted`)\n\n  .. math::\n\n     G^{24}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}} Z_j Z_k\n                C(r_{ij}, r_l, r_c) C(r_{ik}, r_l, r_c)\n                C(r_{jk}, r_l, r_c) C(\\theta_{ijk}, \\theta_l, \\theta_r),\n\n* Weighted angular symmetry function, wide variant\n  (:cpp:class:`nnp::SymFncCompAngwWeighted`)\n\n  .. math::\n\n     G^{25}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}} Z_j Z_k\n                C(r_{ij}, r_l, r_c) C(r_{ik}, r_l, r_c)\n                C(\\theta_{ijk}, \\theta_l, \\theta_r),\n"
  },
  {
    "path": "src/doc/sphinx/source/topics/keywords.rst",
    "content": ".. _keywords:\n\n.. include:: ../helper.rst\n\nNNP configuration: keywords\n===========================\n\n.. warning::\n\n   Documentation under construction...\n\nThe NNP settings file (usually named ``input.nn``\\ ) contains the setup of neural\nnetworks and symmetry functions. Each line may contain a single keyword with no,\none or multiple arguments. Keywords and arguments are separated by at least one\nwhitespace. Lines or part of lines can be commented out with the symbol \"#\",\neverything right of \"#\" will be ignored. The order of keywords is not\nimportant, most keywords may only appear once (exceptions: ``symfunction_short``\nand ``atom_energy``\\ ). Here is the list of available keywords (if no usage\ninformation is provided, then the keyword does not support any arguments).\n\nGeneral NNP keywords\n--------------------\n\nThese keywords provide the basic setup for a neural network potential.\nTherefore, they are mandatory for most NNP applications and a minimal example\nsetup file would contain at least:\n\n.. code-block:: none\n\n   number_of_elements 1\n   elements H\n   global_hidden_layers_short 2\n   global_nodes_short 10 10\n   global_activation_short t t l\n   cutoff_type 1\n   symfunction_short ...\n   ...\n\nThese commands will set up a neural network potential for hydrogen atoms (2\nhidden layers with 10 neurons each, hyperbolic tangent activation function) and\nthe cosine cutoff function for all symmetry functions. Of course, further\nsymmetry functions need to be specified by adding multiple lines starting with\nthe ``symfunction_short`` keyword.\n\n----\n\n``number_of_elements``\n^^^^^^^^^^^^^^^^^^^^^^\n\nDefines the number of elements the neural network potential is designed for.\n\n**Usage:**\n   ``number_of_elements <integer>``\n\n**Examples**:\n   ``number_of_elements 3``\n\n----\n\n``elements``\n^^^^^^^^^^^^\n\n**Usage**:\n   ``elements <string(s)>``\n\n**Examples**:\n   ``elements O H Zn``\n\nThis keyword defines all elements via a list of element symbols. The number of\nitems provided has to be consistent with the argument of the\n``number_of_elements`` keyword. The order of the items is not important,\nelements are automatically sorted according to their atomic number. The list\n`nnp::ElementMap::knownElements\n<../doxygen/classnnp_1_1ElementMap.html#ad0295785b2db8268cfc175b835046a1e>`__\ncontains a list of recognized element symbols.\n\n----\n\n``atom_energy``\n^^^^^^^^^^^^^^^\n\n**Usage**:\n   ``atom_energy <string> <float>``\n\n**Examples**:\n   ``atom_energy O -74.94518524``\n\nDefinition of atomic reference energy. Shifts the total potential energy by\nthe given value for each atom of the specified type. The first argument is the\nelement symbol, the second parameter is the shift energy.\n\n----\n\n``global_hidden_layers_short``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n**Usage**:\n   ``global_hidden_layers_short <integer>``\n\n**Examples**:\n   ``global_hidden_layers_short 3``\n\nSets the number of hidden layers for neural networks of all elements.\n\n----\n\n``global_nodes_short``\n^^^^^^^^^^^^^^^^^^^^^^\n\n**Usage**:\n   ``global_nodes_short <integer(s)>``\n\n**Examples**:\n   ``global_nodes_short 15 10 5``\n\nSets the number of neurons in the hidden layers of neural networks of all\nelements. The number of integer arguments has to be consistent with the\nargument of the ``global_hidden_layers_short`` keyword. Note: The number of\ninput layer neurons is determined by the number of symmetry functions and there\nis always only a single output neuron.\n\n----\n\n``global_activation_short``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n**Usage**:\n   ``global_activation_short <chars>``\n\n**Examples**:\n   ``global_activation_short t t t l``\n\nSets the activation function per layer for hidden layers and output layers\nof neural networks of all elements. The number of integer arguments has to\nbe consistent with the argument of the ``global_hidden_layers_short`` keyword\n(i.e. number of hidden layers + 1). Activation functions are chosen via\nsingle characters from the following table (see also\n:cpp:enum:`nnp::NeuralNetwork::ActivationFunction`).\n\n.. list-table::\n   :header-rows: 1\n\n   * - Character\n     - Activation function type\n   * - l\n     - :cpp:enumerator:`nnp::NeuralNetwork::AF_IDENTITY`\n   * - t\n     - :cpp:enumerator:`nnp::NeuralNetwork::AF_TANH`\n   * - s\n     - :cpp:enumerator:`nnp::NeuralNetwork::AF_LOGISTIC`\n   * - p\n     - :cpp:enumerator:`nnp::NeuralNetwork::AF_SOFTPLUS`\n   * - r\n     - :cpp:enumerator:`nnp::NeuralNetwork::AF_RELU`\n   * - g\n     - :cpp:enumerator:`nnp::NeuralNetwork::AF_GAUSSIAN`\n   * - c\n     - :cpp:enumerator:`nnp::NeuralNetwork::AF_COS`\n   * - S\n     - :cpp:enumerator:`nnp::NeuralNetwork::AF_REVLOGISTIC`\n   * - e\n     - :cpp:enumerator:`nnp::NeuralNetwork::AF_EXP`\n   * - h\n     - :cpp:enumerator:`nnp::NeuralNetwork::AF_HARMONIC`\n\n\n----\n\n``normalize_nodes``\n^^^^^^^^^^^^^^^^^^^\n\nActivates normalized neural network propagation, i.e. the weighted sum of\nconnected neuron values is divided by the number of incoming connections\nbefore the activation function is applied. Thus, the default formula to calculate the neuron\n\n.. math::\n\n   y^{k}_{i} = f_a \\left( b^{k}_{i} + \\sum_{j=1}^{n_l} a^{lk}_{ji} \\, y^{l}_{j} \\right),\n\nis modified according to:\n\n.. math::\n\n   y^{k}_{i} = f_a \\left( \\frac{b^{k}_{i} + \\sum_{j=1}^{n_l} a^{lk}_{ji} \\, y^{l}_{j}}{n_l} \\right).\n\n----\n\n``cutoff_type``\n^^^^^^^^^^^^^^^^^^^\n\n**Usage**:\n   ``cutoff_type <integer> <<float>>``\n\n**Examples**:\n   ``cutoff_type 2 0.5``\n\n   ``cutoff_type 7``\n\nDefines the cutoff function type used for all symmetry functions. The first\nargument determines the functional form, see\n:cpp:enum:`nnp::CutoffFunction::CutoffType` for all available options. Use one\nof the following integer numbers to select the cutoff type. The second argument\nis optional and sets the parameter :math:`\\alpha`. If not provided, the default\nvalue is :math:`\\alpha = 0.0`.\n\n.. list-table::\n   :header-rows: 1\n\n   * - Cutoff #\n     - Cutoff type\n   * - 0\n     - :cpp:enumerator:`nnp::CutoffFunction::CT_HARD`\n   * - 1\n     - :cpp:enumerator:`nnp::CutoffFunction::CT_COS`\n   * - 2\n     - :cpp:enumerator:`nnp::CutoffFunction::CT_TANHU`\n   * - 3\n     - :cpp:enumerator:`nnp::CutoffFunction::CT_TANH`\n   * - 4\n     - :cpp:enumerator:`nnp::CutoffFunction::CT_EXP`\n   * - 5\n     - :cpp:enumerator:`nnp::CutoffFunction::CT_POLY1`\n   * - 6\n     - :cpp:enumerator:`nnp::CutoffFunction::CT_POLY2`\n   * - 7\n     - :cpp:enumerator:`nnp::CutoffFunction::CT_POLY3`\n   * - 8\n     - :cpp:enumerator:`nnp::CutoffFunction::CT_POLY4`\n\n\n----\n\n``center_symmetry_functions``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n``scale_symmetry_functions``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n``scale_symmetry_functions_sigma``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nCombining these keywords determines how the symmetry functions are scaled\nbefore they are used as input for the neural network. See\n:cpp:enum:`nnp::SymFnc::ScalingType` and the following table for allowed\ncombinations:\n\n.. list-table::\n   :header-rows: 1\n\n   * - Keywords present\n     - Scaling type\n   * - ``None``\n     - :cpp:enumerator:`nnp::SymFnc::ST_NONE`\n   * - ``scale_symmetry_functions``\n     - :cpp:enumerator:`nnp::SymFnc::ST_SCALE`\n   * - ``center_symmetry_functions``\n     - :cpp:enumerator:`nnp::SymFnc::ST_CENTER`\n   * - ``scale_symmetry_functions`` + ``center_symmetry_functions``\n     - :cpp:enumerator:`nnp::SymFnc::ST_SCALECENTER`\n   * - ``scale_symmetry_functions_sigma``\n     - :cpp:enumerator:`nnp::SymFnc::ST_SCALESIGMA`\n\n\n----\n\n``scale_min_short``\n^^^^^^^^^^^^^^^^^^^\n\n``scale_max_short``\n^^^^^^^^^^^^^^^^^^^\n\n**Usage**:\n   ``scale_min_short <float>``\n\n   ``scale_max_short <float>``\n\n**Examples**:\n   ``scale_min_short 0.0``\n\n   ``scale_max_short 1.0``\n\nSet minimum :math:`S_{\\min}` and maximum :math:`S_{\\max}` for symmetry function\nscaling. See :cpp:enumerator:`nnp::SymmetryFunction::ScalingType`.\n\n----\n\n.. _symfunction_short:\n\n``symfunction_short``\n^^^^^^^^^^^^^^^^^^^^^\n\n**Usage**:\n   ``symfunction_short <string> <integer> ...``\n\n**Examples**:\n   ``symfunction_short H 2 H 0.01 0.0 12.0``\n\n   ``symfunction_short H 3 O H 0.2 -1.0 4.0 12.0``\n\n   ``symfunction_short O 9 H H 0.1  1.0 8.0 16.0``\n\n   ``symfunction_short H 12 0.01 0.0 12.0``\n\n   ``symfunction_short O 13 0.1 0.2 1.0 8.0 16.0``\n\nDefines a symmetry function for a specific element. The first argument is the\nelement symbol, the second sets the type. The remaining parameters depend on\nthe symmetry function type, follow the links in the right column of the table\nand look for the detailed description of the class.\n\n.. list-table::\n   :header-rows: 1\n\n   * - Type integer\n     - Symmetry function type\n   * - 2\n     - :cpp:class:`nnp::SymFncExpRad`\n   * - 3\n     - :cpp:class:`nnp::SymFncExpAngn`\n   * - 9\n     - :cpp:class:`nnp::SymFncExpAngw`\n   * - 12\n     - :cpp:class:`nnp::SymFncExpRadWeighted`\n   * - 13\n     - :cpp:class:`nnp::SymFncExpAngnWeighted`\n   * - 20\n     - :cpp:class:`nnp::SymFncCompRad`\n   * - 21\n     - :cpp:class:`nnp::SymFncCompAngn`\n   * - 22\n     - :cpp:class:`nnp::SymFncCompAngw`\n   * - 23\n     - :cpp:class:`nnp::SymFncCompRadWeighted`\n   * - 24\n     - :cpp:class:`nnp::SymFncCompAngnWeighted`\n   * - 25\n     - :cpp:class:`nnp::SymFncCompAngwWeighted`\n\n----\n\n``ewald_truncation_error_method``\n^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nIn 4G the Ewald summation is used if periodic boundary conditions are applied.\nBoth the reciprocal and the real space sum need to be truncated. For this, two\ndifferent schemes are available. This defines the behaviour of ``ewald_prec``.\n\n**Usage**:\n   ``ewald_truncation_error_method <mode>``\n\n**Examples**:\n   ``ewald_truncation_error_method 1``\n\n\n*  ``0``: *default*, **Method by Jackson & Catlow**\n\n    This method is based on the idea to truncate all terms that are smaller in\n    magnitude than a certain threshold [3]_. It is the method used in *RuNNer*.\n\n*  ``1``: **Method by Kolafa & Perram**\n\n    Statistical assumptions are made of the material to incorporate cancelling\n    effects of the energy contributions [4]_. It is the recommended method.\n\n``ewald_prec``\n^^^^^^^^^^^^^^\n\nDepending on the mode in ``ewald_truncation_error_method`` this keyword has\ndifferent meanings. The parameter ``<threshold>`` determines the cutoff radii in\nreal and reciprocal space. For both methods a smaller threshold leads to\nincreased radii and thus to a degrade in performance. Also the memory footprint\ncan become quite noticeable for very small values.\n\n.. warning::\n\n    If n2p2 crashes in 4G mode because it needs more memory than available on\n    the machine, it may be related to the ``<threshold>`` parameter. This can\n    be tested by increasing its value considerably.\n\n* If ``ewald_truncation_error_method 0``\n\n    **Usage**:\n        ``ewald_prec <threshold>``\n\n    ``<threshold>`` is a dimensionless parameter that controls the accuracy of\n    the Ewald summation. Typical values are in the range of ``1.e-2`` to\n    ``1.e-7``.\n\n* If ``ewald_truncation_error_method 1``\n\n    **Usage**:\n        ``ewald_prec <threshold> <max charge> <<real space cutoff>>``\n\n    ``<threshold>`` loosely corresponds to the standard deviation of the\n    electrostatic force error one would like to achieve and has to be given in\n    the same units as the forces in the training data. However, the methods\n    tends to overestimate the actual error, so one may test the accuracy for\n    different values. Choosing values that are orders of magnitude smaller than\n    the RMSE of the short-range force errors does not make sense.\n    ``<max charge>`` should be the maximum charge (in magnitude) that appears during\n    training. This does not have to be very precise but should be given in the\n    same units as in the training data. :ref:`nnp-norm` outputs this quantity.\n    The default is ``1.``.\n\n    It is important to note that this method has two different modes.\n    ``<<real space cutoff>>`` is an optional parameter. It fixes the real space\n    cutoff in the Ewald summation and adjusts the Ewald parameter and the\n    reciprocal space cutoff accordingly such that the specified ``<threshold>``\n    is still satisfied. If ``<<real space cutoff>>`` is chosen unreasonably\n    small, the truncation error estimate may not be reliable anymore and\n    a warning is given. This mode is useful when n2p2 is used in combination\n    with other programs like LAMMPS, since they often expect a fixed cutoff\n    during the simulation. If ``<<real space cutoff>>`` is not specified, an\n    optimal combination of the real and reciprocal space cutoff is computed.\n    However, \"optimal\" refers to the computational effort inside n2p2. If used\n    in combination with other programs like LAMMPS, it will not be optimal in\n    general. Also note that the optimal cutoffs may change during the\n    simulation since they depend on factors like simulation cell volume, number\n    of atoms etc. In general we recommend the optimal choice of the cutoffs\n    only if n2p2 is used as a standalone tool. If it is used in the interface\n    mode, a good choice is to set ``<<real space cutoff>>`` to the symmetry\n    function cutoff. This choice may also decrease the memory footprint.\n\n\nTraining-specific keywords\n--------------------------\n\nThe following keywords are solely used for training with :ref:`nnp-train`. All\nother tools and interfaces will ignore these keywords.\n\n----\n\n``selection_mode``\n^^^^^^^^^^^^^^^^^^\n\n**Usage**:\n   ``selection_mode <integer> <<pairs of integers>>``\n\n**Examples**:\n   ``selection_mode 0``\n\n   ``selection_mode 2 15 1 20 2``\n\nSets the scheme to select energy and force candidates during training (first\ninteger argument, mandatory). If only one argument is given the chosen mode is\nused for the entire training. The optional pairs of integers allow to switch the\nselection mode during training. The first integer of each pair determines the\nepoch when to switch while the second denotes the selection mode to switch to.\nHence, the above example means: Start the training with selection mode ``2``,\nthen after 15 epochs switch to mode ``1`` and finally at epoch 20 switch back to\nmode ``2`` until training is completed. There are three selection modes\nimplemented:\n\n*  ``0``: **Random selection**\n\n   Select training candidates randomly.\n\n*  ``1``: **Sort by RMSE**\n\n   At the beginning of each epoch all training candidates are sorted according\n   to their current RMSE. Throughout the epoch this list is then processed\n   sequentially in order of descending RMSE, i.e. from highest to lowest\n   error. This selection scheme can be helpful to decrease the error of\n   outlier forces when used in conjunction with the optional selection mode\n   switching (see above).\n\n*  ``2``: **Random selection with threshold**\n\n   Select training candidates randomly but use the choice only for training if\n   the current error is above a threshold. Otherwise, select another candidate.\n   The threshold can be set for energies and forces separately with the keywords\n   ``short_energy_error_threshold`` and ``short_force_error_threshold`` and is\n   expressed in terms of the last epochs RMSE, e.g.\n   ``short_energy_error_threshold 1.5`` means a threshold of :math:`1.5 \\times\n   RMSE`. Training candidates are selected randomly until the threshold condition\n   is fulfilled or a the number of trial choices (keyword\n   ``rmse_threshold_trials``) is exceeded. If even in the latter case no\n   candidate above the threshold is found, the candidate with the highest error\n   so far is used. This selection scheme is a variation of the adaptive process\n   described by Blank and Brown [1]_ and is described here [2]_.\n\n----\n\n``main_error_metric``\n^^^^^^^^^^^^^^^^^^^^^\n\n**Usage**:\n   ``main_error_metric <string>``\n\n**Examples**:\n   ``main_error_metric RMSEpa``\n\n   ``main_error_metric MAE``\n\nSelects the error metric to display on the screen during training. Four variants\nare available:\n\n* ``RMSEpa``: RMSE of energies per atom, RMSE of forces.\n\n* ``RMSE``: RMSE of energies, RMSE of forces.\n\n* ``MAEpa``: MAE of energies per atom, MAE of forces.\n\n* ``MAE``: MAE of energies, MAE of forces.\n\nIf this keyword is omitted the default value is ``RMSEpa``. The keyword does not\ninfluence the output in the ``learning-curve.out`` file. There, all error metrics\nare written.\n\n----\n\n.. _normalize_data_set:\n\n``normalize_data_set``\n^^^^^^^^^^^^^^^^^^^^^^\n\n**Usage**:\n   ``normalize_data_set <string>``\n\n**Examples**:\n   ``normalize_data_set ref``\n\n   ``normalize_data_set force``\n\nEnables automatic data set normalization (see also :ref:`units`) as a\npre-processing step during training with :ref:`nnp-train`. If this keyword is\npresent, an additional calculation will be performed after the initialization of\nweights. The file and screen output will contain a corresponding section ``DATA\nSET NORMALIZATION`` summarizing the results of the data set normalization step.\nThree different modes of normalization can be selected:\n\n*  ``stats-only`` : **No or manually provided normalization, compute only statistics**\n\n   This option will trigger a calculation of statistics: mean and standard\n   deviation of reference energies and forces will be computed. Also, a first\n   prediction with the (randomly) initialized NN weights will be executed.\n   Finally, statistics for these energy and force predictions will be collected\n   and printed to screen. If present, already given normalization data (keywords\n   ``mean_energy``, ``conv_energy`` and ``conv_length``) in the ``input.nn``\n   file will be read and applied.\n\n*  ``ref`` : **Normalization based on reference energies and forces**\n\n   Energy and force statistics are computed as in mode ``stats-only``. The mean\n   and standard deviation of reference energies and forces are used to compute\n   three numbers for normalization: (1) the mean energy per atom, (2) a\n   conversion factor for energies , and (3) a conversion factor for lengths .\n   These are computed in such way that the normalized (indicated by :math:`^*`)\n   data satisfies:\n\n   .. math::\n\n      \\left<e^*_\\text{ref}\\right> = 0 \\quad \\text{and} \\quad\n      \\sigma_{e^*_\\text{ref}} = \\sigma_{F^*_\\text{ref}} = 1,\n\n   i.e., the mean reference energy per atom vanishes and there is unity standard\n   deviation of reference energies per atom and forces. As the training run\n   continues all necessary quantities are automatically converted to this\n   normalized unit system.\n\n   .. important::\n\n      The three numbers (1), (2) and (3) are automatically written to the first\n      lines of ``input.nn`` as arguments of the keywords ``mean_energy``,\n      ``conv_energy`` and ``conv_length``, respectively. They are read in and\n      normalization is applied by other tools if necessary. No additional user\n      interaction is required. In particular, it is **not** required to convert\n      settings in ``input.nn`` (e.g. cutoff radii, some symmetry function\n      parameters), nor the configuration data in ``input.data``. All unit\n      conversion will be handled internally.\n\n*  ``force`` : **Normalization based on reference and predicted forces (recommended)**\n\n   Same procedure as in mode ``ref`` but the normalization with respect to\n   standard deviation of energies per atom is omitted. Instead, the standard\n   deviation of **predicted** forces is set to unity:\n\n   .. math::\n\n      \\left<e^*_\\text{ref}\\right> = 0 \\quad \\text{and} \\quad\n      \\sigma_{F^*_\\text{NNP}} = \\sigma_{F^*_\\text{ref}} = 1,\n\n   The prediction is carried out with the previously (randomly) initialized\n   neural network weights. Usually this normalization procedure results in a\n   very uniform distribution of data points in the initial\n   reference-vs-prediction plot of the forces (see the files\n   ``train/testforces.000000.out``). This seems to be a good starting point for\n   the HDNNP training often resulting in lower force errors than the ``ref``\n   mode.\n\n.. [1] Blank, T. B.; Brown, S. D. Adaptive, Global, Extended Kalman Filters for\n   Training Feedforward Neural Networks. J. Chemom. 1994, 8 (6), 391–407.\n   https://doi.org/10.1002/cem.1180080605\n\n.. [2] Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C. Parallel\n   Multistream Training of High-Dimensional Neural Network Potentials. J. Chem.\n   Theory Comput. 2019, 15 (5), 3075–3092. https://doi.org/10.1021/acs.jctc.8b01092\n\n.. [3] Jackson, R. A.; Catlow, C. R. A. Computer Simulation Studies of Zeolite\n   Structure. Molecular Simulation 1988, 1 (4), 207–224.\n   https://doi.org/10.1080/08927028808080944.\n\n.. [4] Kolafa, J.; Perram, J. W. Cutoff Errors in the Ewald Summation Formulae\n   for Point Charge Systems. Molecular Simulation 1992, 9 (5), 351–368.\n   https://doi.org/10.1080/08927029208049126.\n"
  },
  {
    "path": "src/doc/sphinx/source/topics/training.rst",
    "content": ".. _training:\n\nNNP training procedure\n======================\n\n.. warning::\n\n   This part of the documentation is incomplete!\n\nCreating a new high-dimensional neural network potential from scratch is\nusually a multi-step iterative procedure which includes\n\n* data set generation/augmentation,\n* selection/refinement/pruning of symmetry function parameters,\n* experimenting with neural network topology/settings,\n* the actual neural network training, i.e. optimizing the weight parameters.\n\nTools are ready-made for most of these tasks and can be combined to generate a\nnew NNP from scratch. Here is a rough guideline of the individual steps from a\nset of configurations to an initial NN potential. However, be aware that\ncreating a reliable NNP usually requires repeated data set refining and adequate\ntesting before it is ready for production!\n\nStep 1: Data set\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\n\nPrepare a data set (name the file ``input.data``) in the file format described\n:ref:`here <cfg_file>`. Unfortunately there's no simple recipe how to create a\n\"good\" set of configurations, you will find more hints in the literature. As a\nstarting point you could try with some (100+) configurations taken from an *ab\ninitio* MD simulation.\n\nStep 2: Prepare settings file\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\nPrepare a settings file (name the file ``input.nn``): Use the recommended file\n`here\n<https://github.com/CompPhysVienna/n2p2/blob/master/examples/input.nn.recommended>`__\nand change the settings in the \"GENERAL NNP SETTINGS\" section according to\nyour system.\n\nStep 3 (**optional**): Data set normalization\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\n.. note::\n\n   This step is usually not necessary any more because data set normalization is\n   handled on-the-fly during training with the keyword\n   :ref:`normalize_data_set`.\n\nAs explained :ref:`here <units>` it may be useful to ensure that training is\nindependent of the chosen unit system. With ``input.nn`` and ``input.data``\npresent run the tool :ref:`nnp-norm` which implements a normalization procedure\n(see chapter 3.1 in [1]_) for this purpose. This will write an additional header\nto the settings file ``input.nn`` with three new keyword-value pairs. These will\ninstruct other n2p2 tools to enable the data set normalization during runtime.\nWhenever the data set is changed, do not forget to repeat this step.\n\n.. important::\n\n   Besides the addition of the normalization header no other actions are required\n   to enable data set normalization for all other steps below. In particular,\n   neither the data set nor other unit system dependent settings (e.g. cutoff\n   radii, some symmetry function parameters) need to be converted manually. Any\n   unit conversion will be handled internally and no user intervention is\n   necessary.\n\n.. _symfunc_setup:\n\nStep 4: Symmetry function setup\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\n\nChange the symmetry function definitions in the \"SYMMETRY FUNCTIONS\" section of\nthe ``input.nn`` file.. again this not a trivial task, please find more\ninformation in the literature [2]_ [3]_ [4]_. See also the description of the\n``symfunction_short`` keyword :ref:`here <keywords>`.\n\n.. note::\n\n   There is a very useful standalone Python tool written by Florian Buchner (see\n   his `pull request <https://github.com/CompPhysVienna/n2p2/pull/15>`__) which\n   allows to create sets of symmetry function lines following the guidelines\n   given in [3]_ and [4]_. To use it, just copy the file `sfparamgen.py\n   <https://github.com/flobuch/n2p2/blob/symfunc_paramgen/tools/python/symfunc_paramgen/src/sfparamgen.py>`__\n   to a local directory and follow the instructions given in this `Jupyter\n   notebook\n   <https://github.com/flobuch/n2p2/blob/symfunc_paramgen/tools/python/symfunc_paramgen/examples/example.ipynb>`__.\n\n\nStep 5: Compute symmetry function statistics\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\n\nWith the files ``input.data`` and ``input.nn`` ready in the same directoy, run\nthe tool ``nnp-scaling`` (supports MPI parallelization). This will compute all\nsymmetry functions for all atoms once and store statistics about them in a\nthird file (``scaling.data``) required for training.\n\nStep 6: NNP Training\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\n\nRun the actual training program ``nnp-train``, preferably in parallel via:\n``mpirun -np 16 nnp-train`` Be aware of the memory footprint which is estimated\nin the previous step (see end of log file or screen output).\n\nStep 7: Collect weight files\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\nUpon training weight files are created for each epoch ``weights.???.<epoch>``.\nSelect an epoch with satisfying RMSE and rename the corresponding weight\nfiles to ``weights.???.data`` (``???`` is the atomic number of elements\noccurring).\n\nStep 8: Prediction and MD simulation\n\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\n\nTry the potential by predicting energies and forces for a new configuration:\nCollect the files from training (``input.nn``, ``scaling.data`` and\n``weights.???``) in a folder together with a single configuration (named again\n``input.data``) and run the tool ``nnp-predict``. Alternatively, try to run a MD\nsimulation with LAMMPS (see setup instructions :ref:`here <if_lammps>`).\n\nPlease also have a look at the ``examples`` directory which provides working\nexample setups for each tool. If there are problems don't hesitate to ask\nagain...\n\n.. [1] Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C. Parallel\n   Multistream Training of High-Dimensional Neural Network Potentials. J. Chem.\n   Theory Comput. 2019, 15 (5), 3075–3092. https://doi.org/10.1021/acs.jctc.8b01092\n\n.. [2] Behler, J. Atom-Centered Symmetry Functions for Constructing\n   High-Dimensional Neural Network Potentials. J. Chem. Phys. 2011, 134 (7),\n   074106. https://doi.org/10.1063/1.3553717\n\n.. [3] Imbalzano, G.; Anelli, A.; Giofré, D.; Klees, S.; Behler, J.; Ceriotti,\n   M. Automatic Selection of Atomic Fingerprints and Reference Configurations for\n   Machine-Learning Potentials. J. Chem. Phys. 2018, 148 (24), 241730.\n   https://doi.org/10.1063/1.5024611\n\n.. [4] Gastegger, M.; Schwiedrzik, L.; Bittermann, M.; Berzsenyi, F.;\n   Marquetand, P. WACSF—Weighted Atom-Centered Symmetry Functions as Descriptors in\n   Machine Learning Potentials. J. Chem. Phys. 2018, 148 (24), 241709.\n   https://doi.org/10.1063/1.5019667\n"
  },
  {
    "path": "src/doc/sphinx/source/topics/units.rst",
    "content": ".. _units:\n\nUnits\n=====\n\nIn principle the library and all applications are agnostic to a specific system\nof physical units. This means that numeric values in input files are processed\nunaltered. Hence, it is the user's responsibility to provide data in a\nconsistent way. For instance, the same length units must be used in training\nconfigurations (see :ref:`configuration file format<cfg_file>`) and in the\n:ref:`definition of symmetry functions<descriptors>` (mind that some parameters,\ne.g. :math:`\\eta, r_c`, need to be given in length units).\n\n.. warning::\n\n   Note that unit conversion may be required if an existing neural network\n   potential is used to drive an MD simulation in LAMMPS. If the LAMMPS units\n   (see command `units <https://lammps.sandia.gov/doc/units.html>`__) are not\n   matching with those used during NNP training, appropriate conversion factors\n   need to be provided. See the `pair_style hdnnp reference\n   <https://docs.lammps.org/pair_hdnnp.html>`__ for further details.\n\nNormalizing the data set: \"internal\" units\n------------------------------------------\n\nProcessing data sets unaltered potentially introduces a dependence of training\nresults on the chosen unit system, i.e. if the same data set would be set up\nwith different physical unit systems, it is unclear whether the training would\nconverge to comparable errors. To avoid this problem an additional\npre-processing of the training data can be performed with the keyword\n:ref:`normalize_data_set` (recommended) or the tool :ref:`nnp-norm`. Both will\ndetermine conversion factors for a reduced \"internal\" unit system and add them\nto the settings file. Other tools will recognize the corresponding\n:ref:`keywords <keywords>` and automatically perform the conversion to\n\"internal\" units. No additional intervention of the user is necessary and\nquantities are usually converted back to physical units for screen or file\noutput.\n\n.. note::\n\n   Sometimes quantities are provided also in internal units (for debugging\n   purposes). If this is the case it will be explicitly mentioned in the screen\n   output or in the file header. The default output of all tools is given in the\n   original physical unit system.\n\nFor further details see the :ref:`keyword description <normalize_data_set>`, the\n:ref:`tool description <nnp-norm>` and a recent publication [1]_.\n\n.. important::\n\n   The described data set normalization step is **optional**, you are not\n   required to perform it. It is also not guaranteed that the quality of\n   training will increase in all cases.\n\n.. [1] Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C. Parallel\n   Multistream Training of High-Dimensional Neural Network Potentials. J. Chem.\n   Theory Comput. 2019, 15 (5), 3075–3092. https://doi.org/10.1021/acs.jctc.8b01092\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/Install.sh",
    "content": "# Install/unInstall package files in LAMMPS\n# mode = 0/1/2 for uninstall/install/update\n\nmode=$1\n\n# enforce using portable C locale\nLC_ALL=C\nexport LC_ALL\n\n# arg1 = file, arg2 = file it depends on\n\naction () {\n  if (test $mode = 0) then\n    rm -f ../$1\n  elif (! cmp -s $1 ../$1) then\n    if (test -z \"$2\" || test -e ../$2) then\n      cp $1 ..\n      if (test $mode = 2) then\n        echo \"  updating src/$1\"\n      fi\n    fi\n  elif (test -n \"$2\") then\n    if (test ! -e ../$2) then\n      rm -f ../$1\n    fi\n  fi\n}\n\n# all package files with no dependencies\n\nfor file in *.cpp *.h; do\n  test -f ${file} && action $file\ndone\n\n# edit 2 Makefile.package files to include/exclude package info\n\nif (test $1 = 1) then\n\n  if (test -e ../Makefile.package) then\n    sed -i -e 's/[^ \\t]*hdnnp[^ \\t]* //g' ../Makefile.package\n    sed -i -e 's|^PKG_INC =[ \\t]*|&-I../../lib/hdnnp/includelink |' ../Makefile.package\n    sed -i -e 's|^PKG_PATH =[ \\t]*|&-L../../lib/hdnnp/liblink |' ../Makefile.package\n    sed -i -e 's|^PKG_SYSINC =[ \\t]*|&$(hdnnp_SYSINC) |' ../Makefile.package\n    sed -i -e 's|^PKG_SYSLIB =[ \\t]*|&$(hdnnp_SYSLIB) |' ../Makefile.package\n    sed -i -e 's|^PKG_SYSPATH =[ \\t]*|&$(hdnnp_SYSPATH) |' ../Makefile.package\n  fi\n\n  if (test -e ../Makefile.package.settings) then\n    sed -i -e '/^[ \\t]*include.*hdnnp.*$/d' ../Makefile.package.settings\n    # multiline form needed for BSD sed on Macs\n    sed -i -e '4 i \\\ninclude ..\\/..\\/lib\\/hdnnp\\/Makefile.lammps\n' ../Makefile.package.settings\n  fi\n\nelif (test $1 = 0) then\n\n  if (test -e ../Makefile.package) then\n    sed -i -e 's/[^ \\t]*hdnnp[^ \\t]* //g' ../Makefile.package\n  fi\n\n  if (test -e ../Makefile.package.settings) then\n    sed -i -e '/^[ \\t]*include.*hdnnp.*$/d' ../Makefile.package.settings\n  fi\n\nfi\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/README",
    "content": "This package implements the \"pair_style hdnnp\" command which can be used in a\nLAMMPS input script. This pair style allows to use pre-trained high-dimensional\nneural network potentials[1] via an interface to the n2p2 library\n(https://github.com/CompPhysVienna/n2p2)[2].\n\nPlease see the main documentation for the \"pair_style hdnnp\" command for further\ndetails on how the pair style is used. An example is provided in the\n\"examples/PACKAGES/hdnnp\" directory of LAMMPS.\n\nThe ML-HDNNP package requires the external library n2p2 which must be\ndownloaded and compiled before starting the build process of LAMMPS. A\nguideline on how to build n2p2 is presented in \"lib/hdnnp/README\". This package\nsupports the LAMMPS build process via CMake and traditional makefiles, please\nsee the LAMMPS manual section on building with external libraries for more\ndetails.\n\nThis package was created by Andreas Singraber, please ask questions/report bugs\non the n2p2 Github issues page (https://github.com/CompPhysVienna/n2p2/issues).\n\n[1] Behler, J.; Parrinello, M. Generalized Neural-Network Representation of\nHigh-Dimensional Potential-Energy Surfaces.  Phys. Rev. Lett.  2007, 98 (14),\n146401. https://doi.org/10.1103/PhysRevLett.98.146401\n\n[2] Singraber, A.; Behler, J.; Dellago, C. Library-Based\nLAMMPS Implementation of High-Dimensional Neural Network Potentials. J. Chem.\nTheory Comput. 2019, 15 (3), 1827-1840. https://doi.org/10.1021/acs.jctc.8b00770\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/fix_hdnnp.cpp",
    "content": "/* ----------------------------------------------------------------------\n   LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator\n   http://lammps.sandia.gov, Sandia National Laboratories\n   Steve Plimpton, sjplimp@sandia.gov\n\n   Copyright (2003) Sandia Corporation.  Under the terms of Contract\n   DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains\n   certain rights in this software.  This software is distributed under\n   the GNU General Public License.\n\n   See the README file in the top-level LAMMPS directory.\n------------------------------------------------------------------------- */\n\n#include \"fix_hdnnp.h\"\n#include \"pair_hdnnp_4g.h\"\n#include <iostream>\n#include <gsl/gsl_multimin.h>\n#include <mpi.h>\n#include <cmath>\n#include <cstring>\n#include \"pair_hdnnp.h\"\n#include \"kspace_hdnnp.h\"\n#include \"atom.h\"\n#include \"comm.h\"\n#include \"domain.h\" // check for periodicity\n#include \"neighbor.h\"\n#include \"neigh_list.h\"\n#include \"neigh_request.h\"\n#include \"update.h\"\n#include \"force.h\"\n#include \"group.h\"\n#include \"pair.h\"\n#include \"memory.h\"\n#include \"error.h\"\n#include \"utils.h\"\n#include <chrono> //time\n\nusing namespace LAMMPS_NS;\nusing namespace FixConst;\nusing namespace std::chrono;\nusing namespace nnp;\n\n#define EV_TO_KCAL_PER_MOL 14.4\n#define SQR(x) ((x)*(x))\n#define CUBE(x) ((x)*(x)*(x))\n#define MIN_NBRS 100\n#define SAFE_ZONE      1.2\n#define DANGER_ZONE    0.90\n#define MIN_CAP        50\n\n\nFixHDNNP::FixHDNNP(LAMMPS *lmp, int narg, char **arg) :\n        Fix(lmp, narg, arg),\n        hdnnp         (nullptr),\n        kspacehdnnp   (nullptr),\n        list          (nullptr),\n        pertype_option(nullptr),\n        hdnnpflag     (0      ),\n        kspaceflag    (0      ),\n        ngroup        (0      ),\n        periodic      (false  ),\n        qRef          (0.0    ),\n        Q             (nullptr),\n        type_all      (nullptr),\n        type_loc      (nullptr),\n        qall          (nullptr),\n        qall_loc      (nullptr),\n        dEdQ_all      (nullptr),\n        dEdQ_loc      (nullptr),\n        xx            (nullptr),\n        xy            (nullptr),\n        xz            (nullptr),\n        xx_loc        (nullptr),\n        xy_loc        (nullptr),\n        xz_loc        (nullptr)\n\n{\n    if (narg<9 || narg>11) error->all(FLERR,\"Illegal fix hdnnp command\");\n\n    nevery = utils::inumeric(FLERR,arg[3],false,lmp);\n    if (nevery <= 0) error->all(FLERR,\"Illegal fix hdnnp command\");\n\n    int len = strlen(arg[8]) + 1;\n    pertype_option = new char[len];\n    strcpy(pertype_option,arg[8]);\n\n    hdnnp = nullptr;\n    kspacehdnnp = nullptr;\n    hdnnp = (PairHDNNP4G *) force->pair_match(\"^hdnnp/4g\",0);\n    kspacehdnnp = (KSpaceHDNNP *) force->kspace_match(\"^hdnnp\",0);\n\n    hdnnp->chi = nullptr;\n    hdnnp->hardness = nullptr;\n    hdnnp->sigmaSqrtPi = nullptr;\n    hdnnp->gammaSqrt2 = nullptr;\n    hdnnp->screening_info = nullptr;\n\n    // User-defined minimization parameters used in pair_hdnnp as well\n    // TODO: read only on proc 0 and then Bcast ?\n    hdnnp->grad_tol = utils::numeric(FLERR,arg[4],false,lmp); //tolerance for gradient check\n    hdnnp->min_tol = utils::numeric(FLERR,arg[5],false,lmp); //tolerance\n    hdnnp->step = utils::numeric(FLERR,arg[6],false,lmp); //initial hdnnp->step size\n    hdnnp->maxit = utils::inumeric(FLERR,arg[7],false,lmp); //maximum number of iterations\n    hdnnp->minim_init_style = utils::inumeric(FLERR,arg[10],false,lmp); //initialization style\n\n    // TODO: check these initializations and allocations\n    int natoms = atom->natoms;\n\n    // TODO: these are not necessary in case of periodic systems\n    memory->create(xx,atom->natoms,\"fix_hdnnp:xx\");\n    memory->create(xy,atom->natoms,\"fix_hdnnp:xy\");\n    memory->create(xz,atom->natoms,\"fix_hdnnp:xz\");\n    memory->create(xx_loc,atom->natoms,\"fix_hdnnp:xx_loc\");\n    memory->create(xy_loc,atom->natoms,\"fix_hdnnp:xy_loc\");\n    memory->create(xz_loc,atom->natoms,\"fix_hdnnp:xz_loc\");\n    memory->create(type_loc,atom->natoms,\"fix_hdnnp:type_loc\");\n    memory->create(type_all,atom->natoms,\"fix_hdnnp:type_all\");\n    \n}\n\n/* ---------------------------------------------------------------------- */\n\nFixHDNNP::~FixHDNNP()\n{\n    if (copymode) return;\n\n    delete[] pertype_option;\n    \n    memory->destroy(hdnnp->chi);\n    memory->destroy(hdnnp->hardness);\n    memory->destroy(hdnnp->sigmaSqrtPi);\n    memory->destroy(hdnnp->gammaSqrt2);\n\n    memory->destroy(qall);\n    memory->destroy(qall_loc);\n    memory->destroy(dEdQ_loc);\n    memory->destroy(dEdQ_all);\n    \n    memory->destroy(xx);\n    memory->destroy(xy);\n    memory->destroy(xz);\n    memory->destroy(xx_loc);\n    memory->destroy(xy_loc);\n    memory->destroy(xz_loc);\n    memory->destroy(type_loc);\n    memory->destroy(type_all);\n    \n}\n\nvoid FixHDNNP::post_constructor()\n{\n    pertype_parameters(pertype_option);\n\n}\n\nint FixHDNNP::setmask()\n{\n    int mask = 0;\n    mask |= PRE_FORCE;\n    mask |= PRE_FORCE_RESPA;\n    mask |= MIN_PRE_FORCE;\n    return mask;\n}\n\nvoid FixHDNNP::init()\n{\n    if (!atom->q_flag)\n        error->all(FLERR,\"Fix hdnnp requires atom attribute q\");\n\n    ngroup = group->count(igroup);\n    if (ngroup == 0) error->all(FLERR,\"Fix hdnnp group has no atoms\");\n\n    // need a half neighbor list w/ Newton off and ghost neighbors\n    // built whenever re-neighboring occurs\n\n    //int irequest = neighbor->request(this,instance_me);\n    //neighbor->requests[irequest]->pair = 0;\n    //neighbor->requests[irequest]->fix = 1;\n    //neighbor->requests[irequest]->newton = 2;\n    //neighbor->requests[irequest]->ghost = 1;\n\n    isPeriodic();\n\n    //if (periodic) neighbor->add_request(this, NeighConst::REQ_DEFAULT);\n    //else neighbor->add_request(this, NeighConst::REQ_FULL);\n    neighbor->add_request(this, NeighConst::REQ_FULL |\n                                NeighConst::REQ_GHOST |\n                                NeighConst::REQ_NEWTON_OFF);\n\n    // TODO : do we really need a full NL in periodic cases ?\n    //if (periodic) { // periodic : full neighborlist\n    //    neighbor->requests[irequest]->half = 0;\n    //    neighbor->requests[irequest]->full = 1;\n    //}\n\n    allocate_QEq();\n}\n\nvoid FixHDNNP::pertype_parameters(char *arg)\n{\n    if (strcmp(arg,\"hdnnp\") == 0) {\n        hdnnpflag = 1;\n        Pair *pair = force->pair_match(\"hdnnp\",0);\n        if (pair == NULL) error->all(FLERR,\"No pair hdnnp for fix hdnnp\");\n    }\n}\n\n// Allocate QEq arrays\nvoid FixHDNNP::allocate_QEq()\n{\n    int ne = atom->ntypes;\n    memory->create(hdnnp->chi,atom->natoms,\"qeq:hdnnp->chi\");\n    memory->create(hdnnp->hardness,ne,\"qeq:hdnnp->hardness\");\n    memory->create(hdnnp->sigmaSqrtPi,ne,\"qeq:hdnnp->sigmaSqrtPi\");\n    memory->create(hdnnp->gammaSqrt2,ne,ne,\"qeq:hdnnp->gammaSqrt2\");\n    memory->create(hdnnp->screening_info,4,\"qeq:screening\");\n    memory->create(qall,atom->natoms,\"qeq:qall\");\n    memory->create(qall_loc,atom->natoms,\"qeq:qall_loc\");\n    memory->create(dEdQ_loc,atom->natoms,\"qeq:dEdQ_loc\");\n    memory->create(dEdQ_all,atom->natoms,\"qeq:dEdQ_all\");\n    \n    // Initialization\n    for (int i =0; i < atom->natoms; i++){\n        hdnnp->chi[i] = 0.0;\n    }\n    for (int i = 0; i < ne; i++){\n\thdnnp->hardness[i] = 0.0;\n\thdnnp->sigmaSqrtPi[i] = 0.0;\n\tfor (int j = 0; j < ne; j++){\n\t\thdnnp->gammaSqrt2[i][j] = 0.0;\n\t}\n    }\n    for (int i = 0; i < 4; i++){\n\t    hdnnp->screening_info[i] = 0.0;\n    }\n}\n\n// Deallocate QEq arrays\nvoid FixHDNNP::deallocate_QEq() {\n\n    memory->destroy(hdnnp->chi);\n    memory->destroy(hdnnp->hardness);\n    memory->destroy(hdnnp->sigmaSqrtPi);\n    memory->destroy(hdnnp->gammaSqrt2);\n    memory->destroy(hdnnp->screening_info);\n    memory->destroy(qall);\n    memory->destroy(qall_loc);\n    memory->destroy(dEdQ_loc);\n    memory->destroy(dEdQ_all);\n\n}\n\nvoid FixHDNNP::init_list(int /*id*/, NeighList *ptr)\n{\n    list = ptr;\n}\n\nvoid FixHDNNP::setup_pre_force(int vflag)\n{\n    pre_force(vflag);\n}\n\nvoid FixHDNNP::min_setup_pre_force(int vflag)\n{\n    setup_pre_force(vflag);\n}\n\nvoid FixHDNNP::min_pre_force(int vflag)\n{\n    pre_force(vflag);\n}\n\n// Main calculation routine, runs before pair->compute at each timehdnnp->step\nvoid FixHDNNP::pre_force(int /*vflag*/) {\n\n    double *q = atom->q;\n    double Qtot_loc = 0.0;\n    int n = atom->nlocal;\n    int j,jmap;\n\n    //deallocate_QEq();\n    //allocate_QEq();\n    \n    if(periodic) {\n        //force->kspace->setup();\n\tkspacehdnnp->ewald_sfexp();\n    }\n    \n    // Calculate atomic electronegativities \\Chi_i\n    calculate_electronegativities();\n    \n    // Calculate the current total charge\n    for (int i = 0; i < n; i++) {\n        //std::cout << q[i] << '\\n';\n        Qtot_loc += q[i];\n    }\n    MPI_Allreduce(&Qtot_loc,&qRef,1,MPI_DOUBLE,MPI_SUM,world);\n\n    //TODO\n    calculate_erfc_terms();\n    \n    std::chrono::steady_clock::time_point begin = std::chrono::steady_clock::now();\n    // Minimize QEq energy and calculate atomic charges\n    calculate_QEqCharges();\n    std::chrono::steady_clock::time_point end = std::chrono::steady_clock::now();\n    //std::cout << \"iQEq time (s) = \" << std::chrono::duration_cast<std::chrono::microseconds>(end - begin).count() / 1000000.0 << std::endl;\n\n}\n\nvoid FixHDNNP::calculate_electronegativities()\n{\n    // Run first set of atomic NNs\n    process_first_network();\n\n    // Read QEq arrays from n2p2 into LAMMPS\n    hdnnp->interface.getQEqParams(hdnnp->chi,hdnnp->hardness,hdnnp->sigmaSqrtPi,hdnnp->gammaSqrt2,qRef);\n\n    // Read screening function information from n2p2 into LAMMPS\n    hdnnp->interface.getScreeningInfo(hdnnp->screening_info); //TODO: read function type\n}\n\n// Runs interface.process for electronegativities\nvoid FixHDNNP::process_first_network()\n{\n    if(hdnnp->interface.getNnpType() == InterfaceLammps::NNPType::HDNNP_4G)\n    {\n        // Set number of local atoms and add element.\n        hdnnp->interface.setLocalAtoms(atom->nlocal,atom->type);\n\n        // Set tags of local atoms.\n        hdnnp->interface.setLocalTags(atom->tag);\n\n        // Transfer local neighbor list to HDNNP interface.\n        hdnnp->transferNeighborList();\n\n        // Run the first NN for electronegativities\n        hdnnp->interface.process();\n    }\n    else{ //TODO\n        error->all(FLERR,\"This fix style can only be used with a 4G-HDNNP.\");\n    }\n}\n\n// This routine is called once. Complementary error function terms are calculated and stored\nvoid FixHDNNP::calculate_erfc_terms()\n{\n    int i,j,jmap;\n    int nlocal = atom->nlocal;\n    int *tag = atom->tag;\n    int *type = atom->type;\n\n    double **x = atom->x;\n    double eta;\n\n    int maxnumneigh = 0;\n    // TODO is this already available in LAMMPS ?\n    for (int i = 0; i < nlocal; i++)\n    {\n      int nneigh = list->numneigh[i];\n      if (nneigh > maxnumneigh) maxnumneigh = nneigh;\n    }\n    \n    //maxnumneigh = 100000;\n    // allocate and initialize\n    memory->create(hdnnp->erfc_val,nlocal+1,maxnumneigh+1,\"fix_hdnnp:erfc_val\");\n\n    for (int i = 0; i < nlocal; i++){\n        for (int j = 0; j < maxnumneigh; j++)\t\t\n            hdnnp->erfc_val[i][j] = 0.0;\n    }\n\n    if (periodic)\n    {\n        eta = 1 / kspacehdnnp->g_ewald; // LAMMPS truncation\n        double sqrt2eta = (sqrt(2.0) * eta);\n        for (i = 0; i < nlocal; i++)\n        {\n            for (int jj = 0; jj < list->numneigh[i]; ++jj) {\n                j = list->firstneigh[i][jj];\n                j &= NEIGHMASK;\n                jmap = atom->map(tag[j]);\n                double const dx = x[i][0] - x[j][0];\n                double const dy = x[i][1] - x[j][1];\n                double const dz = x[i][2] - x[j][2];\n                double const rij = sqrt(SQR(dx) + SQR(dy) + SQR(dz)) * hdnnp->cflength;\n                hdnnp->erfc_val[i][jj] = (erfc(rij/sqrt2eta) - erfc(rij/hdnnp->gammaSqrt2[type[i]-1][type[jmap]-1])) / rij;\n            }\n        }\n    }\n}\n\n// QEq energy function, $E_{QEq}$\ndouble FixHDNNP::QEq_f(const gsl_vector *v)\n{\n    int i,j,jmap;\n    int *tag = atom->tag;\n    int *type = atom->type;\n    int nlocal = atom->nlocal;\n    int nall = atom->natoms;\n\n    double **x = atom->x;\n    double *q = atom->q;\n\n    double E_qeq_loc,E_qeq;\n    double E_elec_loc,E_scr_loc,E_scr;\n    double E_real,E_recip,E_self; // for periodic examples\n    double iiterm,ijterm;\n\n    double eta;\n\n    if(periodic) eta = 1 / kspacehdnnp->g_ewald; // LAMMPS truncation\n\n    E_qeq = 0.0;\n    E_qeq_loc = 0.0;\n    E_scr = 0.0;\n    E_scr_loc = 0.0;\n    hdnnp->E_elec = 0.0;\n\n    if (periodic)\n    {\n        double sqrt2eta = (sqrt(2.0) * eta);\n        E_recip = 0.0;\n        E_real = 0.0;\n        E_self = 0.0;\n        for (i = 0; i < nlocal; i++) // over local atoms\n        {\n            double const qi = gsl_vector_get(v, tag[i]-1);\n            double qi2 = qi * qi;\n            // Self term\n            E_self += qi2 * (1 / (2.0 * hdnnp->sigmaSqrtPi[type[i]-1]) - 1 / (sqrt(2.0 * M_PI) * eta));\n            E_qeq_loc += hdnnp->chi[i] * qi + 0.5 * hdnnp->hardness[type[i]-1] * qi2;\n            E_scr -= qi2 / (2.0 * hdnnp->sigmaSqrtPi[type[i]-1]); // self screening term TODO:parallel ?\n            // Real Term\n            // TODO: we loop over the full neighbor list, could this be optimized ?\n            for (int jj = 0; jj < list->numneigh[i]; ++jj) {\n                j = list->firstneigh[i][jj];\n                j &= NEIGHMASK;\n                jmap = atom->map(tag[j]);\n                double const qj = gsl_vector_get(v, tag[j]-1); // mapping based on tags\n                double const dx = x[i][0] - x[j][0];\n                double const dy = x[i][1] - x[j][1];\n                double const dz = x[i][2] - x[j][2];\n                double const rij = sqrt(SQR(dx) + SQR(dy) + SQR(dz)) * hdnnp->cflength;\n                //double erfcRij = (erfc(rij / sqrt2eta) - erfc(rij / hdnnp->gammaSqrt2[type[i]-1][type[jmap]-1])) / rij;\n                //double real = 0.5 * qi * qj * erfcRij;\n                double real = 0.5 * qi * qj * hdnnp->erfc_val[i][jj];\n                E_real += real;\n                if (rij <= hdnnp->screening_info[2]) {\n                    E_scr += 0.5 * qi * qj *\n                            erf(rij/hdnnp->gammaSqrt2[type[i]-1][type[jmap]-1])*(hdnnp->screening_f(rij) - 1) / rij;\n                }\n            }\n        }\n        // Reciprocal Term\n        if (kspacehdnnp->ewaldflag) // Ewald Sum\n        {\n            // Calls the charge equilibration energy calculation routine in the KSpace base class\n            // Returns reciprocal energy\n            E_recip = kspacehdnnp->compute_ewald_eqeq(v);\n        }\n        else if (kspacehdnnp->pppmflag) // PPPM\n        {\n            //TODO: add contributions to Eqeq for PPPM style\n            kspacehdnnp->particle_map();\n            kspacehdnnp->make_rho_qeq(v); // map my particle charge onto my local 3d density grid\n            E_recip = kspacehdnnp->compute_pppm_eqeq(); // TODO: WIP\n        }\n        hdnnp->E_elec = E_real + E_self; // do not add E_recip, it is already global\n        E_qeq_loc += hdnnp->E_elec;\n    }else\n    {\n        // first loop over local atoms\n        for (i = 0; i < nlocal; i++) {\n            double const qi = gsl_vector_get(v,tag[i]-1);\n            double qi2 = qi * qi;\n            // add i terms\n            iiterm = qi2 * (1 / (2.0 * hdnnp->sigmaSqrtPi[type[i]-1]) + (0.5 * hdnnp->hardness[type[i]-1]));\n            E_qeq_loc += iiterm + hdnnp->chi[i] * qi;\n            hdnnp->E_elec += iiterm;\n            E_scr -= iiterm; //TODO parallel ?\n            // Looping over all atoms (parallelization of necessary arrays has been done beforehand)\n            for (j = 0; j < nall; j++) {\n                double const qj = gsl_vector_get(v, j);\n                double const dx = xx[j] - x[i][0];\n                double const dy = xy[j] - x[i][1];\n                double const dz = xz[j] - x[i][2];\n                double const rij = sqrt(SQR(dx) + SQR(dy) + SQR(dz)) * hdnnp->cflength;\n                if (rij != 0.0) //TODO check\n                {\n                    ijterm = (erf(rij / hdnnp->gammaSqrt2[type[i]-1][type_all[j]-1]) / rij);\n                    E_qeq_loc += 0.5 * ijterm * qi * qj;\n                    hdnnp->E_elec += ijterm;\n                    if(rij <= hdnnp->screening_info[2]) {\n                        E_scr += ijterm * (hdnnp->screening_f(rij) - 1);\n                    }\n                }\n            }\n        }\n    }\n\n    //TODO: add communication steps for E_elec !!!\n    hdnnp->E_elec = hdnnp->E_elec + E_scr; // add screening energy\n\n    MPI_Allreduce(&E_qeq_loc,&E_qeq,1,MPI_DOUBLE,MPI_SUM,world); // MPI_SUM of local QEQ contributions\n\n    if (periodic) E_qeq += E_recip; // adding already all-reduced reciprocal part now\n\n    //fprintf(stderr, \"Erecip = %24.16E\\n\", E_recip);\n    return E_qeq;\n}\n\n// QEq energy function - wrapper\ndouble FixHDNNP::QEq_f_wrap(const gsl_vector *v, void *params)\n{\n    return static_cast<FixHDNNP*>(params)->QEq_f(v);\n}\n\n// QEq energy gradient, $\\partial E_{QEq} / \\partial Q_i$\nvoid FixHDNNP::QEq_df(const gsl_vector *v, gsl_vector *dEdQ)\n{\n    int i,j,jmap;\n    int nlocal = atom->nlocal;\n    int nall = atom->natoms;\n    int *tag = atom->tag;\n    int *type = atom->type;\n\n    double **x = atom->x;\n    double *q = atom->q;\n\n    double grad;\n    double grad_sum_loc;\n    double grad_sum;\n    double grad_recip; // reciprocal space contribution to the gradient\n    double grad_i;\n    double jsum; //summation over neighbors & kspace respectively\n    double recip_sum;\n\n    double eta;\n\n    if (periodic) eta = 1 / kspacehdnnp->g_ewald; // LAMMPS truncation\n\n\n    grad_sum = 0.0;\n    grad_sum_loc = 0.0;\n    if (periodic)\n    {\n        double sqrt2eta = (sqrt(2.0) * eta);\n        for (i = 0; i < nlocal; i++) // over local atoms\n        {\n            double const qi = gsl_vector_get(v,tag[i]-1);\n            // Reciprocal contribution\n            if (kspacehdnnp->ewaldflag)\n            {\n                grad_recip = 0.0;\n                for (int k = 0; k < kspacehdnnp->kcount; k++) // over k-space\n                {\n                    grad_recip += 2.0 * kspacehdnnp->kcoeff[k] *\n                            (kspacehdnnp->sf_real[k] * kspacehdnnp->sfexp_rl[k][i] +\n                             kspacehdnnp->sf_im[k] *   kspacehdnnp->sfexp_im[k][i]);\n                }\n            }\n            else if (kspacehdnnp->pppmflag)\n            {\n                //TODO: calculate dEdQ_i for a given local atom i\n                grad_recip = kspacehdnnp->compute_pppm_dEdQ(i);\n            }\n            // Real contribution - over neighbors\n            jsum = 0.0;\n            for (int jj = 0; jj < list->numneigh[i]; ++jj) {\n                j = list->firstneigh[i][jj];\n                j &= NEIGHMASK;\n                double const qj = gsl_vector_get(v, tag[j]-1);\n                //jmap = atom->map(tag[j]);\n                //double const dx = x[i][0] - x[j][0];\n                //double const dy = x[i][1] - x[j][1];\n                //double const dz = x[i][2] - x[j][2];\n                //double const rij = sqrt(SQR(dx) + SQR(dy) + SQR(dz)) * hdnnp->cflength;\n                //double erfcRij = (erfc(rij / sqrt2eta) - erfc(rij / hdnnp->gammaSqrt2[type[i]-1][type[jmap]-1]));\n                //jsum += qj * erfcRij / rij;\n                jsum += qj * hdnnp->erfc_val[i][jj];\n            }\n            grad = jsum + grad_recip + hdnnp->chi[i] + hdnnp->hardness[type[i]-1]*qi +\n                   qi * (1/(hdnnp->sigmaSqrtPi[type[i]-1])- 2/(eta * sqrt(2.0 * M_PI)));\n            grad_sum_loc += grad;\n            dEdQ_loc[tag[i]-1] = grad; // fill gradient array based on tags instead of local IDs\n        }\n    }else\n    {\n        // first loop over local atoms\n        for (i = 0; i < nlocal; i++) { // TODO: indices\n            double const qi = gsl_vector_get(v,tag[i]-1);\n            // second loop over 'all' atoms\n            jsum = 0.0;\n            // Looping over all atoms (parallelization of necessary arrays has been done beforehand)\n            for (j = 0; j < nall; j++) {\n                {\n                    double const qj = gsl_vector_get(v, j);\n                    double const dx = xx[j] - x[i][0];\n                    double const dy = xy[j] - x[i][1];\n                    double const dz = xz[j] - x[i][2];\n                    double const rij = sqrt(SQR(dx) + SQR(dy) + SQR(dz)) * hdnnp->cflength;\n                    if (rij != 0.0) jsum += qj * erf(rij / hdnnp->gammaSqrt2[type[i]-1][type_all[j]-1]) / rij;\n                }\n            }\n            grad = hdnnp->chi[i] + hdnnp->hardness[type[i]-1]*qi + qi/(hdnnp->sigmaSqrtPi[type[i]-1]) + jsum;\n            grad_sum_loc += grad;\n            dEdQ_loc[tag[i]-1] = grad;\n            //gsl_vector_set(dEdQ,i,grad);\n        }\n    }\n\n    MPI_Allreduce(dEdQ_loc,dEdQ_all,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n    MPI_Allreduce(&grad_sum_loc,&grad_sum,1,MPI_DOUBLE,MPI_SUM,world);\n\n    // Gradient projection\n    for (i = 0; i < nall; i++){\n        grad_i = dEdQ_all[i];\n        gsl_vector_set(dEdQ,i,grad_i - (grad_sum)/nall);\n    }\n}\n\n// QEq energy gradient - wrapper\nvoid FixHDNNP::QEq_df_wrap(const gsl_vector *v, void *params, gsl_vector *df)\n{\n    static_cast<FixHDNNP*>(params)->QEq_df(v, df);\n}\n\n// QEq f*df, $E_{QEq} * (\\partial E_{QEq} / \\partial Q_i)$\nvoid FixHDNNP::QEq_fdf(const gsl_vector *v, double *f, gsl_vector *df)\n{\n    *f = QEq_f(v);\n    QEq_df(v, df);\n}\n\n// QEq f*df - wrapper\nvoid FixHDNNP::QEq_fdf_wrap(const gsl_vector *v, void *params, double *E, gsl_vector *df)\n{\n    static_cast<FixHDNNP*>(params)->QEq_fdf(v, E, df);\n}\n\n// Main minimization routine\nvoid FixHDNNP::calculate_QEqCharges()\n{\n    size_t iter = 0;\n    int status;\n    int i,j;\n    int nsize;\n    int nlocal;\n    int *tag = atom->tag;\n\n    double *q = atom->q;\n    double qsum_it;\n    double gradsum;\n    double qi;\n    double df,alpha;\n\n    nsize = atom->natoms; // total number of atoms\n    nlocal = atom->nlocal; // total number of atoms\n\n    gsl_vector *Q; // charge vector\n    QEq_minimizer.n = nsize; // it should be n_all in the future\n    QEq_minimizer.f = &QEq_f_wrap; // function pointer f(x)\n    QEq_minimizer.df = &QEq_df_wrap; // function pointer df(x)\n    QEq_minimizer.fdf = &QEq_fdf_wrap;\n    QEq_minimizer.params = this;\n\n    //fprintf(stderr, \"q[%d] = %24.16E\\n\", atom->tag[0], q[0]);\n\n    // Allocation\n    //memory->create(qall,atom->natoms,\"qeq:qall\");\n    //memory->create(qall_loc,atom->natoms,\"qeq:qall_loc\");\n    //memory->create(dEdQ_loc,atom->natoms,\"qeq:dEdQ_loc\");\n    //memory->create(dEdQ_all,atom->natoms,\"qeq:dEdQ_all\");\n    \n    // Initialization\n    for (int i =0; i < atom->natoms; i++){\n        qall[i] = 0.0;\n        qall_loc[i] = 0.0;\n        dEdQ_loc[i] = 0.0;\n        dEdQ_all[i] = 0.0;\n    }\n\n    for (int i = 0; i < atom->nlocal; i++) {\n        qall_loc[tag[i] - 1] = q[i];\n    }\n\n    MPI_Allreduce(qall_loc,qall,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n\n    if (!periodic) // we need global position arrays in nonperiodic systems\n    {\n        // Initialize global arrays\n        for (int i = 0; i < atom->natoms; i++){\n            type_loc[i] = 0;\n            xx_loc[i] = 0.0;\n            xy_loc[i] = 0.0;\n            xz_loc[i] = 0.0;\n            xx[i] = 0.0;\n            xy[i] = 0.0;\n            xz[i] = 0.0;\n        }\n\n        // Create global sparse arrays here\n        for (int i = 0; i < atom->nlocal; i++){\n            xx_loc[tag[i]-1] = atom->x[i][0];\n            xy_loc[tag[i]-1] = atom->x[i][1];\n            xz_loc[tag[i]-1] = atom->x[i][2];\n            type_loc[tag[i]-1] = atom->type[i];\n        }\n        MPI_Allreduce(xx_loc,xx,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n        MPI_Allreduce(xy_loc,xy,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n        MPI_Allreduce(xz_loc,xz,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n        MPI_Allreduce(type_loc,type_all,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n    }\n\n\n    // Set the initial guess vector \n    Q = gsl_vector_alloc(nsize);\n    for (i = 0; i < nsize; i++)\n    {\n\tif (hdnnp->minim_init_style == 0)\n\t{\n\t    gsl_vector_set(Q, i, 0.0);\n\t}else if (hdnnp->minim_init_style == 1)\n\t{\n\t    gsl_vector_set(Q, i, qall[i]);   \n\t}else\n\t{\n\t    error->all(FLERR,\"Invalid minimization style. Allowed values are 0 and 1.\");\n\t}\n    }\n\n    //memory->destroy(qall);\n    //memory->destroy(qall_loc);\n\n    // TODO: is bfgs2 standard ?\n    T = gsl_multimin_fdfminimizer_vector_bfgs2;\n    s = gsl_multimin_fdfminimizer_alloc(T, nsize);\n    gsl_multimin_fdfminimizer_set(s, &QEq_minimizer, Q, hdnnp->step, hdnnp->min_tol); // tol = 0 might be expensive ???\n    do\n    {\n        //fprintf(stderr, \"eqeq-iter %zu\\n\", iter);\n        iter++;\n        qsum_it = 0.0;\n        gradsum = 0.0;\n        status = gsl_multimin_fdfminimizer_iterate(s);\n        // Projection (enforcing constraints)\n        // TODO: could this be done more efficiently ?\n        for(i = 0; i < nsize; i++) {\n            qsum_it = qsum_it + gsl_vector_get(s->x, i); // total charge after the minimization hdnnp->step\n        }\n        for(i = 0; i < nsize; i++) {\n            qi = gsl_vector_get(s->x,i);\n            gsl_vector_set(s->x,i, qi - (qsum_it-qRef)/nsize); // charge projection\n        }\n        status = gsl_multimin_test_gradient(s->gradient, hdnnp->grad_tol); // check for convergence\n\n        // TODO: dump also iteration time ?\n        //if (status == GSL_SUCCESS) printf (\"Minimum charge distribution is found at iteration : %zu\\n\", iter);\n    }\n    while (status == GSL_CONTINUE && iter < hdnnp->maxit);\n\n    // Read calculated atomic charges back into local arrays for further calculations\n    for (int i = 0; i < atom->nlocal; i++){\n        q[i] = gsl_vector_get(s->x,tag[i]-1);\n    }\n\n    // Deallocation\n    gsl_multimin_fdfminimizer_free(s);\n    gsl_vector_free(Q);\n    //memory->destroy(dEdQ_loc);\n    //memory->destroy(dEdQ_all);\n}\n\n// Check if the system is periodic\nvoid FixHDNNP::isPeriodic()\n{\n    if (domain->nonperiodic == 0) periodic = true;\n    else                          periodic = false;\n}\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/fix_hdnnp.h",
    "content": "/* -*- c++ -*- ----------------------------------------------------------\n   LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator\n   http://lammps.sandia.gov, Sandia National Laboratories\n   Steve Plimpton, sjplimp@sandia.gov\n\n   Copyright (2003) Sandia Corporation.  Under the terms of Contract\n   DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains\n   certain rights in this software.  This software is distributed under\n   the GNU General Public License.\n\n   See the README file in the top-level LAMMPS directory.\n------------------------------------------------------------------------- */\n#ifdef FIX_CLASS\n\nFixStyle(hdnnp,FixHDNNP)\n\n#else\n\n#ifndef LMP_FIX_HDNNP_H\n#define LMP_FIX_HDNNP_H\n\n#include <gsl/gsl_multimin.h>\n#include \"fix.h\"\n#include \"InterfaceLammps.h\"\n\n\nnamespace LAMMPS_NS {\n\n    class FixHDNNP : public Fix {\n        friend class PairHDNNP4G;\n    public:\n        FixHDNNP(class LAMMPS *, int, char **);\n        ~FixHDNNP();\n\n        int setmask();\n        virtual void post_constructor();\n        virtual void init();\n        void init_list(int,class NeighList *);\n        void setup_pre_force(int);\n        virtual void pre_force(int);\n\n        void min_setup_pre_force(int);\n        void min_pre_force(int);\n\n    protected:\n\n        class PairHDNNP4G *hdnnp; // interface to HDNNP pair_style\n        class KSpaceHDNNP *kspacehdnnp; // interface to HDNNP kspace_style\n        class NeighList *list;\n        char *pertype_option;\n\n        int hdnnpflag;\n        int kspaceflag; // 0:Ewald Sum, 1:PPPM\n        int ngroup;\n\n        bool periodic; // true if periodic\n        double qRef; // total reference charge of the system\n        double *Q;\n\n        virtual void pertype_parameters(char*);\n        void isPeriodic(); // check for periodicity\n        void calculate_electronegativities(); // calculates electronegatives via running first set of NNs\n        void process_first_network(); // interfaces to n2p2 and runs first NN\n        void allocate_QEq(); // allocates QEq arrays\n        void deallocate_QEq(); // deallocates QEq arrays\n\n        /// QEq energy minimization via gsl library\n\n        gsl_multimin_function_fdf QEq_minimizer; // minimizer object\n        const gsl_multimin_fdfminimizer_type *T;\n        gsl_multimin_fdfminimizer *s;\n\n        double QEq_f(const gsl_vector*); // f : QEq energy as a function of atomic charges\n        void QEq_df(const gsl_vector*, gsl_vector*); // df : Gradient of QEq energy with respect to atomic charges\n        void QEq_fdf(const gsl_vector*, double*, gsl_vector*); // f * df\n\n        static double QEq_f_wrap(const gsl_vector*, void*); // wrapper of f\n        static void QEq_df_wrap(const gsl_vector*, void*, gsl_vector*); // wrapper of df\n        static void QEq_fdf_wrap(const gsl_vector*, void*, double*, gsl_vector*); // wrapper of f * df\n\n        void calculate_QEqCharges(); // main function where minimization happens\n\n        void calculate_erfc_terms(); // loops over neighbors of local atoms and calculates erfc terms\n                                     // these consume the most time. Storing them speeds up calculations\n\n        /// Global storage\n        int *type_all,*type_loc;\n        double *qall,*qall_loc;\n        double *dEdQ_all,*dEdQ_loc; // gradient of the charge equilibration energy wrt charges\n        double *xx,*xy,*xz; // global positions (here only for nonperiodic case)\n        double *xx_loc,*xy_loc,*xz_loc; // sparse local positions (here only for nonperiodic case)\n\n\n        /* Matrix Approach (DEPRECATED and to be deleted)\n        int nevery,hdnnpflag;\n        int n, N, m_fill;\n        int n_cap, m_cap;\n        int pack_flag;\n        bigint ngroup;\n        int nprev;\n        double **Q_hist;\n        double *p, *q, *r, *d;\n        virtual int pack_forward_comm(int, int *, double *, int, int *);\n        virtual void unpack_forward_comm(int, int, double *);\n        virtual int pack_reverse_comm(int, int, double *);\n        virtual void unpack_reverse_comm(int, int *, double *);\n        virtual double memory_usage();\n        virtual void grow_arrays(int);\n        virtual void copy_arrays(int, int, int);\n        virtual int pack_exchange(int, double *);\n        virtual int unpack_exchange(int, double *);\n\n        virtual double parallel_norm( double*, int );\n        virtual double parallel_dot( double*, double*, int );\n        virtual double parallel_vector_acc( double*, int );\n\n        virtual void vector_sum(double*,double,double*,double,double*,int);\n        virtual void vector_add(double*, double, double*,int);*/\n\n    };\n\n}\n\n#endif\n#endif\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/kspace_hdnnp.cpp",
    "content": "/* ----------------------------------------------------------------------\n   LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator\n   https://lammps.sandia.gov/, Sandia National Laboratories\n   Steve Plimpton, sjplimp@sandia.gov\n\n   Copyright (2003) Sandia Corporation.  Under the terms of Contract\n   DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains\n   certain rights in this software.  This software is distributed under\n   the GNU General Public License.\n\n   See the README file in the top-level LAMMPS directory.\n------------------------------------------------------------------------- */\n\n#include \"kspace_hdnnp.h\"\n\n#include \"angle.h\"\n#include \"atom.h\"\n#include \"bond.h\"\n#include \"comm.h\"\n#include \"domain.h\"\n#include \"error.h\"\n#include \"fft3d_wrap.h\"\n#include \"force.h\"\n#include \"grid3d.h\"\n#include \"math_const.h\"\n#include \"math_special.h\"\n#include \"memory.h\"\n#include \"neighbor.h\"\n#include \"pair.h\"\n#include \"remap_wrap.h\"\n#include \"fix_hdnnp.h\"\n#include \"pair_hdnnp_4g.h\"\n\n#include <cmath>\n#include <cstring>\n#include <iostream>\n\nusing namespace LAMMPS_NS;\nusing namespace MathConst;\nusing namespace MathSpecial;\nusing namespace std;\n\n#define MAXORDER 7\n#define OFFSET 16384\n#define LARGE 10000.0\n#define SMALL 0.00001\n#define EPS_HOC 1.0e-7\n\nenum{REVERSE_RHO};\nenum{FORWARD_IK,FORWARD_AD,FORWARD_IK_PERATOM,FORWARD_AD_PERATOM};\n\n#ifdef FFT_SINGLE\n#define ZEROF 0.0f\n#define ONEF  1.0f\n#else\n#define ZEROF 0.0\n#define ONEF  1.0\n#endif\n\n/* ---------------------------------------------------------------------- */\n\nKSpaceHDNNP::KSpaceHDNNP(LAMMPS *lmp) : KSpace(lmp),\n      kxvecs(nullptr), kyvecs(nullptr), kzvecs(nullptr), kcoeff(nullptr), ug(nullptr), eg(nullptr), vg(nullptr),\n      ek(nullptr), sfexp_rl(nullptr), sfexp_im(nullptr), sf_real(nullptr), sf_im(nullptr),\n      sfexp_rl_all(nullptr),sfexp_im_all(nullptr),\n      cs(nullptr), sn(nullptr), factors(nullptr),\n      density_brick(nullptr), vdx_brick(nullptr),\n      vdy_brick(nullptr), vdz_brick(nullptr),u_brick(nullptr), v0_brick(nullptr), v1_brick(nullptr),\n      v2_brick(nullptr), v3_brick(nullptr),v4_brick(nullptr), v5_brick(nullptr), greensfn(nullptr),\n      fkx(nullptr), fky(nullptr), fkz(nullptr), density_fft(nullptr), work1(nullptr),\n      work2(nullptr), gf_b(nullptr), rho1d(nullptr),\n      rho_coeff(nullptr), drho1d(nullptr), drho_coeff(nullptr),\n      sf_precoeff1(nullptr), sf_precoeff2(nullptr), sf_precoeff3(nullptr),\n      sf_precoeff4(nullptr), sf_precoeff5(nullptr), sf_precoeff6(nullptr),\n      acons(nullptr), fft1(nullptr), fft2(nullptr), remap(nullptr), gc(nullptr),\n      gc_buf1(nullptr), gc_buf2(nullptr), part2grid(nullptr), boxlo(nullptr)\n{\n    hdnnp = nullptr;\n    hdnnp = (PairHDNNP4G *) force->pair_match(\"^hdnnp/4g\",0);\n\n    ewaldflag = pppmflag = 0; // TODO check\n\n    eflag_global = 1; // calculate global energy\n\n    //// EWALD\n    kewaldflag = 0;\n    kmax_created = 0;\n\n    kmax = 0;\n    kxvecs = kyvecs = kzvecs = nullptr;\n    kcoeff = nullptr;\n    ug = nullptr;\n    eg = vg = nullptr;\n    ek = nullptr;\n\n    sfexp_rl = sfexp_im = nullptr;\n    sf_im = sf_real = nullptr;\n    sfexp_rl_all = sfexp_im_all = nullptr;\n    cs = sn = nullptr;\n\n    kcount = 0;\n\n    //// PPPM\n    peratom_allocate_flag = 0;\n    //group_allocate_flag = 0;\n\n    group_group_enable = 1;\n    triclinic = domain->triclinic;\n\n    //TODO: add a flag-check for these initializations\n    nfactors = 3;\n    factors = new int[nfactors];\n    factors[0] = 2;\n    factors[1] = 3;\n    factors[2] = 5;\n\n    MPI_Comm_rank(world,&me);\n    MPI_Comm_size(world,&nprocs);\n\n    nfft_both = 0;\n    nxhi_in = nxlo_in = nxhi_out = nxlo_out = 0;\n    nyhi_in = nylo_in = nyhi_out = nylo_out = 0;\n    nzhi_in = nzlo_in = nzhi_out = nzlo_out = 0;\n\n    density_brick = vdx_brick = vdy_brick = vdz_brick = nullptr;\n    vx_brick = vy_brick = vz_brick = nullptr;\n    density_fft = nullptr;\n    u_brick = nullptr;\n    v0_brick = v1_brick = v2_brick = v3_brick = v4_brick = v5_brick = nullptr;\n    greensfn = nullptr;\n    work1 = work2 = nullptr;\n    vg = nullptr;\n    fkx = fky = fkz = nullptr;\n\n    sf_precoeff1 = sf_precoeff2 = sf_precoeff3 =\n    sf_precoeff4 = sf_precoeff5 = sf_precoeff6 = nullptr;\n\n    gf_b = nullptr;\n    rho1d = rho_coeff = drho1d = drho_coeff = nullptr;\n\n    fft1 = fft2 = nullptr;\n    remap = nullptr;\n    gc = nullptr;\n    gc_buf1 = gc_buf2 = nullptr;\n\n    nmax = 0;\n    part2grid = nullptr;\n\n    // define acons coefficients for estimation of kspace errors\n    // see JCP 109, pg 7698 for derivation of coefficients\n    // higher order coefficients may be computed if needed\n\n    memory->create(acons,8,7,\"pppm:acons\");\n    acons[1][0] = 2.0 / 3.0;\n    acons[2][0] = 1.0 / 50.0;\n    acons[2][1] = 5.0 / 294.0;\n    acons[3][0] = 1.0 / 588.0;\n    acons[3][1] = 7.0 / 1440.0;\n    acons[3][2] = 21.0 / 3872.0;\n    acons[4][0] = 1.0 / 4320.0;\n    acons[4][1] = 3.0 / 1936.0;\n    acons[4][2] = 7601.0 / 2271360.0;\n    acons[4][3] = 143.0 / 28800.0;\n    acons[5][0] = 1.0 / 23232.0;\n    acons[5][1] = 7601.0 / 13628160.0;\n    acons[5][2] = 143.0 / 69120.0;\n    acons[5][3] = 517231.0 / 106536960.0;\n    acons[5][4] = 106640677.0 / 11737571328.0;\n    acons[6][0] = 691.0 / 68140800.0;\n    acons[6][1] = 13.0 / 57600.0;\n    acons[6][2] = 47021.0 / 35512320.0;\n    acons[6][3] = 9694607.0 / 2095994880.0;\n    acons[6][4] = 733191589.0 / 59609088000.0;\n    acons[6][5] = 326190917.0 / 11700633600.0;\n    acons[7][0] = 1.0 / 345600.0;\n    acons[7][1] = 3617.0 / 35512320.0;\n    acons[7][2] = 745739.0 / 838397952.0;\n    acons[7][3] = 56399353.0 / 12773376000.0;\n    acons[7][4] = 25091609.0 / 1560084480.0;\n    acons[7][5] = 1755948832039.0 / 36229939200000.0;\n    acons[7][6] = 4887769399.0 / 37838389248.0;\n}\n\n/* ---------------------------------------------------------------------- */\n\nvoid KSpaceHDNNP::settings(int narg, char **arg)\n{\n    if (narg < 2) error->all(FLERR,\"Illegal kspace_style hdnnp command\"); // we have two params, not one (style + FP)\n\n    if (strcmp(arg[0],\"pppm\") == 0) pppmflag = 1;\n    else if (strcmp(arg[0],\"ewald\") == 0) ewaldflag = 1;\n    else error->all(FLERR,\"Illegal kspace_style hdnnp command\");\n\n    accuracy_relative = fabs(utils::numeric(FLERR,arg[1],false,lmp));\n}\n\n/* ----------------------------------------------------------------------\n   free all memory\n------------------------------------------------------------------------- */\n\nKSpaceHDNNP::~KSpaceHDNNP()\n{\n    if (pppmflag)\n    {\n        deallocate();\n        if (copymode) return;\n        delete [] factors;\n        //if (peratom_allocate_flag) deallocate_peratom();\n        //if (group_allocate_flag) deallocate_groups();\n        memory->destroy(part2grid);\n        memory->destroy(acons);\n    }\n    else if (ewaldflag)\n    {\n        deallocate();\n        //if (group_allocate_flag) deallocate_groups();\n        memory->destroy(ek);\n\t//memory->destroy(acons);\n        memory->destroy3d_offset(cs,-kmax_created);\n        memory->destroy3d_offset(sn,-kmax_created);\n    }\n}\n\n/* ----------------------------------------------------------------------\n   called once before run\n------------------------------------------------------------------------- */\n\nvoid KSpaceHDNNP::init()\n{\n    // Make initializations based on the selected k-space style\n    if (pppmflag)\n    {\n        if (me == 0) utils::logmesg(lmp,\"PPPM initialization ...\\n\");\n\n        // TODO: add other error handlings in LAMMPS\n\n        if (order < 2 || order > MAXORDER)\n            error->all(FLERR,fmt::format(\"PPPM order cannot be < 2 or > {}\",MAXORDER));\n\n        // compute two charge force (?)\n        two_charge();\n\n        triclinic = domain->triclinic;\n\n        // extract short-range Coulombic cutoff from pair style\n        cutoff = hdnnp->maxCutoffRadius;\n\n        // compute qsum & qsqsum and warn if not charge-neutral\n        scale = 1.0;\n        qqrd2e = force->qqrd2e;\n        qsum_qsq();\n        natoms_original = atom->natoms;\n\n        if (accuracy_absolute >= 0.0) accuracy = accuracy_absolute;\n        else accuracy = accuracy_relative * two_charge_force;\n\n        // free all arrays previously allocated\n        deallocate();\n\n        //if (peratom_allocate_flag) deallocate_peratom();\n        //if (group_allocate_flag) deallocate_groups();\n\n        Grid3d *gctmp = nullptr;\n        int iteration = 0;\n\n        while (order >= minorder) {\n            if (iteration && me == 0)\n                error->warning(FLERR, \"Reducing PPPM order b/c stencil extends \"\n                                      \"beyond nearest neighbor processor\");\n\n            //compute_gf_denom(); //TODO: stagger ?\n            set_grid_global();\n            set_grid_local();\n            // overlap not allowed\n\n            gctmp = new Grid3d(lmp, world, nx_pppm, ny_pppm, nz_pppm,\n                               nxlo_in, nxhi_in, nylo_in, nyhi_in, nzlo_in, nzhi_in,\n                               nxlo_out, nxhi_out, nylo_out, nyhi_out, nzlo_out, nzhi_out);\n\n            int tmp1, tmp2;\n            gctmp->setup_comm(tmp1, tmp2);\n            if (gctmp->ghost_adjacent()) break;\n            delete gctmp;\n\n            order--;\n            iteration++;\n        }\n\n        if (order < minorder) error->all(FLERR,\"PPPM order < minimum allowed order\");\n        if (!overlap_allowed && !gctmp->ghost_adjacent())\n            error->all(FLERR,\"PPPM grid stencil extends \"\n                             \"beyond nearest neighbor processor\");\n        if (gctmp) delete gctmp;\n\n        // adjust g_ewald TODO(kspace_modify)\n        if (!gewaldflag) adjust_gewald();\n\n        // calculate the final accuracy\n        double estimated_accuracy = final_accuracy();\n\n        // print stats\n        int ngrid_max,nfft_both_max;\n        MPI_Allreduce(&ngrid,&ngrid_max,1,MPI_INT,MPI_MAX,world);\n        MPI_Allreduce(&nfft_both,&nfft_both_max,1,MPI_INT,MPI_MAX,world);\n\n        if (me == 0) {\n            std::string mesg = fmt::format(\"  G vector (1/distance) = {:.8g}\\n\",g_ewald);\n            mesg += fmt::format(\"  grid = {} {} {}\\n\",nx_pppm,ny_pppm,nz_pppm);\n            mesg += fmt::format(\"  stencil order = {}\\n\",order);\n            mesg += fmt::format(\"  estimated absolute RMS force accuracy = {:.8g}\\n\",\n                                estimated_accuracy);\n            mesg += fmt::format(\"  estimated relative force accuracy = {:.8g}\\n\",\n                                estimated_accuracy/two_charge_force);\n            mesg += \"  using \" LMP_FFT_PREC \" precision \" LMP_FFT_LIB \"\\n\";\n            mesg += fmt::format(\"  3d grid and FFT values/proc = {} {}\\n\",\n                                ngrid_max,nfft_both_max);\n            utils::logmesg(lmp,mesg);\n        }\n\n        // allocate K-space dependent memory\n        // don't invoke allocate peratom() or group(), will be allocated when needed\n        allocate();\n\n        // pre-compute Green's function denomiator expansion\n        // pre-compute 1d charge distribution coefficients\n        // (differentiation_flag == 0)\n        compute_gf_denom();\n        compute_rho_coeff();\n    }\n    else if (ewaldflag)\n    {\n        if (comm->me == 0) utils::logmesg(lmp,\"Ewald initialization ...\\n\");\n\n        // error check\n        //triclinic_check();\n        if (domain->dimension == 2)\n            error->all(FLERR,\"Cannot use Ewald with 2d simulation\");\n        if (!atom->q_flag) error->all(FLERR,\"Kspace style requires atom attribute q\");\n        if (slabflag == 0 && domain->nonperiodic > 0)\n            error->all(FLERR,\"Cannot use non-periodic boundaries with Ewald\");\n\n        //TODO: no slab yet\n\n        // compute two charge force TODO:check\n        two_charge();\n\n        // extract short-range Coulombic cutoff from pair style\n        triclinic = domain->triclinic;\n\n        // extract short-range Coulombic cutoff from pair style\n        cutoff = hdnnp->maxCutoffRadius;\n\n        // compute qsum & qsqsum and warn if not charge-neutral TODO:check\n        scale = 1.0;\n        qqrd2e = force->qqrd2e;\n        qsum_qsq();\n        natoms_original = atom->natoms;\n\n        // Via the method in RuNNer (umgekehrt)\n        // LAMMPS uses a different methodology to calculate g_ewald\n        accuracy = accuracy_relative;\n        g_ewald = sqrt(-2.0 * log(accuracy)) / (cutoff*hdnnp->cflength);\n\n        // setup Ewald coefficients\n        setup();\n    }\n}\n\n/* ----------------------------------------------------------------------\n   adjust coeffs, called initially and whenever volume has changed\n------------------------------------------------------------------------- */\n\nvoid KSpaceHDNNP::setup()\n{\n    if (pppmflag)\n    {\n        // TODO: trcilinic & slab\n        // perform some checks to avoid illegal boundaries with read_data\n\n        if (slabflag == 0 && domain->nonperiodic > 0)\n            error->all(FLERR,\"Cannot use non-periodic boundaries with PPPM\");\n        if (slabflag) {\n            if (domain->xperiodic != 1 || domain->yperiodic != 1 ||\n                domain->boundary[2][0] != 1 || domain->boundary[2][1] != 1)\n                error->all(FLERR,\"Incorrect boundaries with slab PPPM\");\n        }\n\n        int i,j,k,n;\n        double *prd;\n\n        // volume-dependent factors\n        // adjust z dimension for 2d slab PPPM\n        // z dimension for 3d PPPM is zprd since slab_volfactor = 1.0\n\n        //triclinic = 0 TODO:check\n\n        // WARNING: Immediately convert to HDNNP units!\n        // volume-dependent factors\n        prd = domain->prd;\n        double xprd = prd[0] * hdnnp->cflength;\n        double yprd = prd[1] * hdnnp->cflength;\n        double zprd = prd[2] * hdnnp->cflength;\n        volume = xprd * yprd * zprd;\n\n        delxinv = nx_pppm/xprd;\n        delyinv = ny_pppm/yprd;\n        delzinv = nz_pppm/zprd;\n\n        delvolinv = delxinv*delyinv*delzinv;\n\n        double unitkx = (MY_2PI/xprd);\n        double unitky = (MY_2PI/yprd);\n        double unitkz = (MY_2PI/zprd);\n\n        // fkx,fky,fkz for my FFT grid pts\n\n        double per;\n\n        for (i = nxlo_fft; i <= nxhi_fft; i++) {\n            per = i - nx_pppm*(2*i/nx_pppm);\n            fkx[i] = unitkx*per;\n        }\n\n        for (i = nylo_fft; i <= nyhi_fft; i++) {\n            per = i - ny_pppm*(2*i/ny_pppm);\n            fky[i] = unitky*per;\n        }\n\n        for (i = nzlo_fft; i <= nzhi_fft; i++) {\n            per = i - nz_pppm*(2*i/nz_pppm);\n            fkz[i] = unitkz*per;\n        }\n\n        // virial coefficients TODO\n\n        /*double sqk,vterm;\n\n        n = 0;\n        for (k = nzlo_fft; k <= nzhi_fft; k++) {\n            for (j = nylo_fft; j <= nyhi_fft; j++) {\n                for (i = nxlo_fft; i <= nxhi_fft; i++) {\n                    sqk = fkx[i]*fkx[i] + fky[j]*fky[j] + fkz[k]*fkz[k];\n                    if (sqk == 0.0) {\n                        vg[n][0] = 0.0;\n                        vg[n][1] = 0.0;\n                        vg[n][2] = 0.0;\n                        vg[n][3] = 0.0;\n                        vg[n][4] = 0.0;\n                        vg[n][5] = 0.0;\n                    } else {\n                        vterm = -2.0 * (1.0/sqk + 0.25/(g_ewald*g_ewald));\n                        vg[n][0] = 1.0 + vterm*fkx[i]*fkx[i];\n                        vg[n][1] = 1.0 + vterm*fky[j]*fky[j];\n                        vg[n][2] = 1.0 + vterm*fkz[k]*fkz[k];\n                        vg[n][3] = vterm*fkx[i]*fky[j];\n                        vg[n][4] = vterm*fkx[i]*fkz[k];\n                        vg[n][5] = vterm*fky[j]*fkz[k];\n                    }\n                    n++;\n                }\n            }\n        }*/\n\n        compute_gf_ik(); // diff option 'ik' is selected\n    }\n    else if (ewaldflag)\n    {\n        // WARNING: Immediately convert to HDNNP units!\n        // volume-dependent factors\n        double const xprd = domain->xprd * hdnnp->cflength;\n        double const yprd = domain->yprd * hdnnp->cflength;\n        double const zprd = domain->zprd * hdnnp->cflength;\n        volume = xprd * yprd * zprd;\n\n        //TODO: slab feature\n\n        unitk[0] = 2.0*MY_PI/xprd;\n        unitk[1] = 2.0*MY_PI/yprd;\n        unitk[2] = 2.0*MY_PI/zprd;\n\n        // Get k-space resolution via the method in RuNNer\n        ewald_recip_cutoff = sqrt(-2.0 * log(accuracy)) * g_ewald;\n        //ewald_real_cutoff = sqrt(-2.0 * log(accuracy)) / g_ewald;\n        ewald_real_cutoff = cutoff * hdnnp->cflength; // we skip the calculation\n\n        //std::cout << \"recip cut:\" << ewald_recip_cutoff << '\\n';\n        //std::cout << \"real cut: \" << ewald_real_cutoff << '\\n';\n        //std::cout << \"eta: \" << 1 / g_ewald << '\\n';\n\n        int kmax_old = kmax;\n        kxmax = kymax = kzmax = 1;\n\n        ewald_pbc(ewald_recip_cutoff); // get kxmax, kymax and kzmax\n        gsqmx = ewald_recip_cutoff * ewald_recip_cutoff;\n\n        kmax = MAX(kxmax,kymax);\n        kmax = MAX(kmax,kzmax);\n        kmax3d = 4*kmax*kmax*kmax + 6*kmax*kmax + 3*kmax;\n\n        // size change ?\n        kxmax_orig = kxmax;\n        kymax_orig = kymax;\n        kzmax_orig = kzmax;\n\n\t//allocate();\n        // if size has grown, reallocate k-dependent and nlocal-dependent arrays\n        if (kmax > kmax_old) {\n            deallocate();\n            allocate();\n            memory->destroy(ek);\n            memory->destroy3d_offset(cs,-kmax_created);\n            memory->destroy3d_offset(sn,-kmax_created);\n            nmax = atom->nmax;\n            memory->create(ek,nmax,3,\"ewald:ek\");\n            memory->create3d_offset(cs,-kmax,kmax,3,nmax,\"ewald:cs\");\n            memory->create3d_offset(sn,-kmax,kmax,3,nmax,\"ewald:sn\");\n            kmax_created = kmax;\n        }\n\n        // pre-compute Ewald coefficients and structure factor arrays\n        ewald_coeffs();\n        //ewald_sfexp();\n    }\n}\n\n// compute RMS accuracy for a dimension TODO: do we need this ?\ndouble KSpaceHDNNP::rms(int km, double prd, bigint natoms, double q2)\n{\n\n    if (natoms == 0) natoms = 1;   // avoid division by zero\n    double value = 2.0*q2*g_ewald/prd *\n                   sqrt(1.0/(MY_PI*km*natoms)) *\n                   exp(-MY_PI*MY_PI*km*km/(g_ewald*g_ewald*prd*prd));\n\n    return value;\n}\n\n// Calculate Ewald coefficients\nvoid KSpaceHDNNP::ewald_coeffs()\n{\n    int k,l,m;\n    double sqk,vterm;\n    double preu = 4.0*M_PI/volume;\n    double etasq;\n\n    etasq = 1.0 / (g_ewald*g_ewald); // LAMMPS truncation (RuNNer truncations has been removed)\n\n    kcount = 0;\n\n    // (k,0,0), (0,l,0), (0,0,m)\n\n    for (m = 1; m <= kmax; m++) {\n        sqk = (m*unitk[0]) * (m*unitk[0]);\n        if (sqk <= gsqmx) {\n            //fprintf(stderr, \"sqk 1x = %24.16E, m %d\\n\", sqrt(sqk), m);\n            kxvecs[kcount] = m;\n            kyvecs[kcount] = 0;\n            kzvecs[kcount] = 0;\n            kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n            kcount++;\n        }\n        sqk = (m*unitk[1]) * (m*unitk[1]);\n        if (sqk <= gsqmx) {\n            //fprintf(stderr, \"sqk 1y = %24.16E, m %d\\n\", sqrt(sqk), m);\n            kxvecs[kcount] = 0;\n            kyvecs[kcount] = m;\n            kzvecs[kcount] = 0;\n            kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n            kcount++;\n        }\n        sqk = (m*unitk[2]) * (m*unitk[2]);\n        if (sqk <= gsqmx) {\n            //fprintf(stderr, \"sqk 1z = %24.16E, m %d\\n\", sqrt(sqk), m);\n            kxvecs[kcount] = 0;\n            kyvecs[kcount] = 0;\n            kzvecs[kcount] = m;\n            kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n            kcount++;\n        }\n    }\n\n    // 1 = (k,l,0), 2 = (k,-l,0)\n\n    for (k = 1; k <= kxmax; k++) {\n        for (l = 1; l <= kymax; l++) {\n            sqk = (unitk[0]*k) * (unitk[0]*k) + (unitk[1]*l) * (unitk[1]*l);\n            if (sqk <= gsqmx) {\n                //fprintf(stderr, \"sqk 2 = %24.16E, k %d  l %d\\n\", sqrt(sqk), k, l);\n                kxvecs[kcount] = k;\n                kyvecs[kcount] = l;\n                kzvecs[kcount] = 0;\n                kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n                kcount++;\n\n                //fprintf(stderr, \"sqk 2 = %24.16E, k %d -l %d\\n\", sqrt(sqk), k, l);\n                kxvecs[kcount] = k;\n                kyvecs[kcount] = -l;\n                kzvecs[kcount] = 0;\n                kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n                kcount++;;\n            }\n        }\n    }\n\n    // 1 = (0,l,m), 2 = (0,l,-m)\n\n    for (l = 1; l <= kymax; l++) {\n        for (m = 1; m <= kzmax; m++) {\n            sqk = (unitk[1]*l) * (unitk[1]*l) + (unitk[2]*m) * (unitk[2]*m);\n            if (sqk <= gsqmx) {\n                //fprintf(stderr, \"sqk 3 = %24.16E, l %d  m %d\\n\", sqrt(sqk), l, m);\n                kxvecs[kcount] = 0;\n                kyvecs[kcount] = l;\n                kzvecs[kcount] = m;\n                kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n                kcount++;\n\n                //fprintf(stderr, \"sqk 3 = %24.16E, l %d -m %d\\n\", sqrt(sqk), l, m);\n                kxvecs[kcount] = 0;\n                kyvecs[kcount] = l;\n                kzvecs[kcount] = -m;\n                kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n                kcount++;\n            }\n        }\n    }\n\n    // 1 = (k,0,m), 2 = (k,0,-m)\n\n    for (k = 1; k <= kxmax; k++) {\n        for (m = 1; m <= kzmax; m++) {\n            sqk = (unitk[0]*k) * (unitk[0]*k) + (unitk[2]*m) * (unitk[2]*m);\n            if (sqk <= gsqmx) {\n                //fprintf(stderr, \"sqk 4 = %24.16E, k %d  m %d\\n\", sqrt(sqk), k, m);\n                kxvecs[kcount] = k;\n                kyvecs[kcount] = 0;\n                kzvecs[kcount] = m;\n                kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n                kcount++;\n\n                //fprintf(stderr, \"sqk 4 = %24.16E, k %d -m %d\\n\", sqrt(sqk), k, m);\n                kxvecs[kcount] = k;\n                kyvecs[kcount] = 0;\n                kzvecs[kcount] = -m;\n                kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n                kcount++;\n            }\n        }\n    }\n\n    // 1 = (k,l,m), 2 = (k,-l,m), 3 = (k,l,-m), 4 = (k,-l,-m)\n\n    for (k = 1; k <= kxmax; k++) {\n        for (l = 1; l <= kymax; l++) {\n            for (m = 1; m <= kzmax; m++) {\n                sqk = (unitk[0]*k) * (unitk[0]*k) + (unitk[1]*l) * (unitk[1]*l) +\n                      (unitk[2]*m) * (unitk[2]*m);\n                if (sqk <= gsqmx) {\n                    //fprintf(stderr, \"sqk 5 = %24.16E, k %d  l %d  m %d\\n\", sqrt(sqk), k, l, m);\n                    kxvecs[kcount] = k;\n                    kyvecs[kcount] = l;\n                    kzvecs[kcount] = m;\n                    kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n                    kcount++;\n\n                    //fprintf(stderr, \"sqk 5 = %24.16E, k %d -l %d  m %d\\n\", sqrt(sqk), k, l, m);\n                    kxvecs[kcount] = k;\n                    kyvecs[kcount] = -l;\n                    kzvecs[kcount] = m;\n                    kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n                    kcount++;\n\n                    //fprintf(stderr, \"sqk 5 = %24.16E, k %d  l %d -m %d\\n\", sqrt(sqk), k, l, m);\n                    kxvecs[kcount] = k;\n                    kyvecs[kcount] = l;\n                    kzvecs[kcount] = -m;\n                    kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n                    kcount++;\n\n                    //fprintf(stderr, \"sqk 5 = %24.16E, k %d -l %d -m %d\\n\", sqrt(sqk), k, l, m);\n                    kxvecs[kcount] = k;\n                    kyvecs[kcount] = -l;\n                    kzvecs[kcount] = -m;\n                    kcoeff[kcount] = preu*exp(-0.5*sqk*etasq)/sqk;\n                    kcount++;\n                }\n            }\n        }\n    }\n}\n\n// Calculate Ewald structure factors\nvoid KSpaceHDNNP::ewald_sfexp()\n{\n    int i,k,l,m,n,ic;\n    double sqk,clpm,slpm;\n\n    double **x = atom->x;\n    int nlocal = atom->nlocal;\n    double cflength;\n\n    n = 0;\n    cflength = hdnnp->cflength; // RuNNer truncation (conversion required)\n\n    // (k,0,0), (0,l,0), (0,0,m)\n\n    for (ic = 0; ic < 3; ic++) {\n        sqk = unitk[ic]*unitk[ic];\n        if (sqk <= gsqmx) {\n            for (i = 0; i < nlocal; i++) {\n                cs[0][ic][i] = 1.0;\n                sn[0][ic][i] = 0.0;\n                cs[1][ic][i] = cos(unitk[ic]*x[i][ic]*cflength);\n                sn[1][ic][i] = sin(unitk[ic]*x[i][ic]*cflength);\n                cs[-1][ic][i] = cs[1][ic][i];\n                sn[-1][ic][i] = -sn[1][ic][i];\n                sfexp_rl[n][i] = cs[1][ic][i];\n                sfexp_im[n][i] = sn[1][ic][i];\n            }\n            n++;\n        }\n    }\n\n    for (m = 2; m <= kmax; m++) {\n        for (ic = 0; ic < 3; ic++) {\n            sqk = m*unitk[ic] * m*unitk[ic];\n            if (sqk <= gsqmx) {\n                for (i = 0; i < nlocal; i++) {\n                    cs[m][ic][i] = cs[m-1][ic][i]*cs[1][ic][i] -\n                                   sn[m-1][ic][i]*sn[1][ic][i];\n                    sn[m][ic][i] = sn[m-1][ic][i]*cs[1][ic][i] +\n                                   cs[m-1][ic][i]*sn[1][ic][i];\n                    cs[-m][ic][i] = cs[m][ic][i];\n                    sn[-m][ic][i] = -sn[m][ic][i];\n                    sfexp_rl[n][i] = cs[m][ic][i];\n                    sfexp_im[n][i] = sn[m][ic][i];\n                }\n                n++;\n            }\n        }\n    }\n\n    // 1 = (k,l,0), 2 = (k,-l,0)\n\n    for (k = 1; k <= kxmax; k++) {\n        for (l = 1; l <= kymax; l++) {\n            sqk = (k*unitk[0] * k*unitk[0]) + (l*unitk[1] * l*unitk[1]);\n            if (sqk <= gsqmx) {\n                for (i = 0; i < nlocal; i++) {\n                    sfexp_rl[n][i] = (cs[k][0][i]*cs[l][1][i] - sn[k][0][i]*sn[l][1][i]);\n                    sfexp_im[n][i] = (sn[k][0][i]*cs[l][1][i] + cs[k][0][i]*sn[l][1][i]);\n                }\n                n++;\n                for (i = 0; i < nlocal; i++) {\n                    sfexp_rl[n][i] = (cs[k][0][i]*cs[l][1][i] + sn[k][0][i]*sn[l][1][i]);\n                    sfexp_im[n][i] = (sn[k][0][i]*cs[l][1][i] - cs[k][0][i]*sn[l][1][i]);\n                }\n                n++;\n            }\n        }\n    }\n\n    // 1 = (0,l,m), 2 = (0,l,-m)\n\n    for (l = 1; l <= kymax; l++) {\n        for (m = 1; m <= kzmax; m++) {\n            sqk = (l*unitk[1] * l*unitk[1]) + (m*unitk[2] * m*unitk[2]);\n            if (sqk <= gsqmx) {\n                for (i = 0; i < nlocal; i++) {\n                    sfexp_rl[n][i] = (cs[l][1][i]*cs[m][2][i] - sn[l][1][i]*sn[m][2][i]);\n                    sfexp_im[n][i] = (sn[l][1][i]*cs[m][2][i] + cs[l][1][i]*sn[m][2][i]);\n                }\n                n++;\n                for (i = 0; i < nlocal; i++) {\n                    sfexp_rl[n][i] = (cs[l][1][i]*cs[m][2][i] + sn[l][1][i]*sn[m][2][i]);\n                    sfexp_im[n][i] = (sn[l][1][i]*cs[m][2][i] - cs[l][1][i]*sn[m][2][i]);\n                }\n                n++;\n            }\n        }\n    }\n\n    // 1 = (k,0,m), 2 = (k,0,-m)\n\n    for (k = 1; k <= kxmax; k++) {\n        for (m = 1; m <= kzmax; m++) {\n            sqk = (k*unitk[0] * k*unitk[0]) + (m*unitk[2] * m*unitk[2]);\n            if (sqk <= gsqmx) {\n                for (i = 0; i < nlocal; i++) {\n                    sfexp_rl[n][i] = (cs[k][0][i]*cs[m][2][i] - sn[k][0][i]*sn[m][2][i]);\n                    sfexp_im[n][i] = (sn[k][0][i]*cs[m][2][i] + cs[k][0][i]*sn[m][2][i]);\n                }\n                n++;\n                for (i = 0; i < nlocal; i++) {\n                    sfexp_rl[n][i] = (cs[k][0][i]*cs[m][2][i] + sn[k][0][i]*sn[m][2][i]);\n                    sfexp_im[n][i] = (sn[k][0][i]*cs[m][2][i] - cs[k][0][i]*sn[m][2][i]);\n                }\n                n++;\n            }\n        }\n    }\n\n    // 1 = (k,l,m), 2 = (k,-l,m), 3 = (k,l,-m), 4 = (k,-l,-m)\n\n    for (k = 1; k <= kxmax; k++) {\n        for (l = 1; l <= kymax; l++) {\n            for (m = 1; m <= kzmax; m++) {\n                sqk = (k*unitk[0] * k*unitk[0]) + (l*unitk[1] * l*unitk[1]) +\n                      (m*unitk[2] * m*unitk[2]);\n                if (sqk <= gsqmx) {\n                    for (i = 0; i < nlocal; i++) {\n                        clpm = cs[l][1][i]*cs[m][2][i] - sn[l][1][i]*sn[m][2][i];\n                        slpm = sn[l][1][i]*cs[m][2][i] + cs[l][1][i]*sn[m][2][i];\n                        sfexp_rl[n][i] = (cs[k][0][i]*clpm - sn[k][0][i]*slpm);\n                        sfexp_im[n][i] = (sn[k][0][i]*clpm + cs[k][0][i]*slpm);\n                    }\n                    n++;\n                    for (i = 0; i < nlocal; i++) {\n                        clpm = cs[l][1][i]*cs[m][2][i] + sn[l][1][i]*sn[m][2][i];\n                        slpm = -sn[l][1][i]*cs[m][2][i] + cs[l][1][i]*sn[m][2][i];\n                        sfexp_rl[n][i] = (cs[k][0][i]*clpm - sn[k][0][i]*slpm);\n                        sfexp_im[n][i] = (sn[k][0][i]*clpm + cs[k][0][i]*slpm);\n                    }\n                    n++;\n                    for (i = 0; i < nlocal; i++) {\n                        clpm = cs[l][1][i]*cs[m][2][i] + sn[l][1][i]*sn[m][2][i];\n                        slpm = sn[l][1][i]*cs[m][2][i] - cs[l][1][i]*sn[m][2][i];\n                        sfexp_rl[n][i] = (cs[k][0][i]*clpm - sn[k][0][i]*slpm);\n                        sfexp_im[n][i] = (sn[k][0][i]*clpm + cs[k][0][i]*slpm);\n                    }\n                    n++;\n                    for (i = 0; i < nlocal; i++) {\n                        clpm = cs[l][1][i]*cs[m][2][i] - sn[l][1][i]*sn[m][2][i];\n                        slpm = -sn[l][1][i]*cs[m][2][i] - cs[l][1][i]*sn[m][2][i];\n                        sfexp_rl[n][i] = (cs[k][0][i]*clpm - sn[k][0][i]*slpm);\n                        sfexp_im[n][i] = (sn[k][0][i]*clpm + cs[k][0][i]*slpm);\n                    }\n                    n++;\n                }\n            }\n        }\n    }\n\n}\n\n// Compute E_QEQ (recip) in PPPM TODO:WIP\ndouble KSpaceHDNNP::compute_pppm_eqeq()\n{\n\n    // all procs communicate density values from their ghost cells\n    //   to fully sum contribution in their 3d bricks\n    // remap from 3d decomposition to FFT decomposition\n\n    gc->reverse_comm(Grid3d::KSPACE,this,REVERSE_RHO,1,sizeof(FFT_SCALAR),\n                     gc_buf1,gc_buf2,MPI_FFT_SCALAR);\n    brick2fft();\n\n    // compute potential V(r) on my FFT grid and\n    //   portion of e_long on this proc's FFT grid\n    // return potentials 3d brick decomposition\n\n    std::cout << energy << '\\n';\n    poisson();\n\n    std::cout << energy << '\\n';\n    exit(0);\n\n    // all procs communicate E-field values\n    // to fill ghost cells surrounding their 3d bricks\n    // TODO check\n    // differentiation_flag == 0\n\n    gc->forward_comm(Grid3d::KSPACE,this,FORWARD_IK,3,sizeof(FFT_SCALAR),\n                     gc_buf1,gc_buf2,MPI_FFT_SCALAR);\n\n    // sum global energy across procs and add in volume-dependent term\n\n    const double qscale = qqrd2e * scale;\n\n    if (eflag_global) {\n        double energy_all;\n        MPI_Allreduce(&energy, &energy_all, 1, MPI_DOUBLE, MPI_SUM, world);\n        energy = energy_all;\n\n        energy *= 0.5 * volume;\n        energy -= g_ewald * qsqsum / MY_PIS +\n                  MY_PI2 * qsum * qsum / (g_ewald * g_ewald * volume);\n        energy *= qscale;\n    }\n\n    std::cout << \"here\" << '\\n';\n    //std::cout << qscale << '\\n';\n    std::cout << MY_PIS << '\\n';\n    std::cout << MY_PI2 << '\\n';\n    //std::cout << qsum << '\\n';\n    //std::cout << g_ewald << '\\n';\n    //std::cout << energy << '\\n';\n    exit(0);\n\n    return energy;\n}\n\n// Returns dE_qeq/dQ_i in PPPM for a given local atom i (inx)\ndouble KSpaceHDNNP::compute_pppm_dEdQ(int inx)\n{\n    int i,l,m,n,nx,ny,nz,mx,my,mz;\n    FFT_SCALAR dx,dy,dz,x0,y0,z0;\n    FFT_SCALAR dEdQx,dEdQy,dEdQz;\n\n    // loop over my charges, interpolate dEdQ from nearby grid points\n    // (nx,ny,nz) = global coords of grid pt to \"lower left\" of charge\n    // (dx,dy,dz) = distance to \"lower left\" grid pt\n    // (mx,my,mz) = global coords of moving stencil pt\n    // ek = 3 components of E-field on particle\n\n    double *q = atom->q;\n    double **x = atom->x;\n    double **f = atom->f;\n\n    double dEdQ;\n\n    int nlocal = atom->nlocal;\n\n    nx = part2grid[inx][0];\n    ny = part2grid[inx][1];\n    nz = part2grid[inx][2];\n    dx = nx + shiftone - (x[inx][0] - boxlo[0]) * delxinv;\n    dy = ny + shiftone - (x[inx][1] - boxlo[1]) * delyinv;\n    dz = nz + shiftone - (x[inx][2] - boxlo[2]) * delzinv;\n\n    compute_rho1d(dx, dy, dz);\n\n    dEdQx = dEdQy = dEdQz = ZEROF;\n    for (n = nlower; n <= nupper; n++) {\n        mz = n + nz;\n        z0 = rho1d[2][n];\n        for (m = nlower; m <= nupper; m++) {\n            my = m + ny;\n            y0 = z0 * rho1d[1][m];\n            for (l = nlower; l <= nupper; l++) {\n                mx = l + nx;\n                x0 = y0 * rho1d[0][l];\n                dEdQx -= x0 * vx_brick[mz][my][mx];\n                dEdQy -= x0 * vy_brick[mz][my][mx];\n                dEdQz -= x0 * vz_brick[mz][my][mx];\n            }\n        }\n    }\n\n    dEdQ = sqrt(dEdQx*dEdQx + dEdQy*dEdQy + dEdQz*dEdQz);\n\n    std::cout << dEdQ << '\\n';\n\n\n    /*for (i = 0; i < nlocal; i++) {\n        nx = part2grid[i][0];\n        ny = part2grid[i][1];\n        nz = part2grid[i][2];\n        dx = nx + shiftone - (x[i][0] - boxlo[0]) * delxinv;\n        dy = ny + shiftone - (x[i][1] - boxlo[1]) * delyinv;\n        dz = nz + shiftone - (x[i][2] - boxlo[2]) * delzinv;\n\n        compute_rho1d(dx, dy, dz);\n\n        dEdQx = dEdQy = dEdQz = ZEROF;\n        for (n = nlower; n <= nupper; n++) {\n            mz = n + nz;\n            z0 = rho1d[2][n];\n            for (m = nlower; m <= nupper; m++) {\n                my = m + ny;\n                y0 = z0 * rho1d[1][m];\n                for (l = nlower; l <= nupper; l++) {\n                    mx = l + nx;\n                    x0 = y0 * rho1d[0][l];\n                    dEdQx -= x0 * vx_brick[mz][my][mx];\n                    dEdQy -= x0 * vy_brick[mz][my][mx];\n                    dEdQz -= x0 * vz_brick[mz][my][mx];\n                }\n            }\n        }\n    }*/\n\n    return dEdQ;\n}\n\n// Compute E_QEQ (recip) in Ewald\ndouble KSpaceHDNNP::compute_ewald_eqeq(const gsl_vector *v)\n{\n    int i;\n    int nlocal = atom->nlocal;\n    int *tag = atom->tag;\n    double E_recip;\n\n\n    E_recip = 0.0;\n    for (int k = 0; k < kcount; k++) // over k-space\n    {\n        //fprintf(stderr, \"kcoeff[%d] = %24.16E\\n\", k, hdnnp->kcoeff[k]);\n        double sf_real_loc = 0.0;\n        double sf_im_loc = 0.0;\n        sf_real[k] = 0.0;\n        sf_im[k] = 0.0;\n        // TODO: this loop over all atoms can be replaced by a MPIallreduce ?\n        for (i = 0; i < nlocal; i++)\n        {\n            double const qi = gsl_vector_get(v,tag[i]-1);\n            sf_real_loc += qi * sfexp_rl[k][i];\n            sf_im_loc += qi * sfexp_im[k][i];\n        }\n        //fprintf(stderr, \"sfexp %d : %24.16E\\n\", k, hdnnp->kcoeff[k] * (pow(sf_real,2) + pow(sf_im,2)));\n        MPI_Allreduce(&(sf_real_loc),&(sf_real[k]),1,MPI_DOUBLE,MPI_SUM,world);\n        MPI_Allreduce(&(sf_im_loc),&(sf_im[k]),1,MPI_DOUBLE,MPI_SUM,world);\n        E_recip += kcoeff[k] * (pow(sf_real[k],2) + pow(sf_im[k],2));\n    }\n\n    return E_recip;\n}\n\n// TODO: this is called after the force->pair->compute calculations in verlet.cpp\n// therefore we cannot make use of it as it is\nvoid KSpaceHDNNP::compute(int eflag, int vflag)\n{\n    // Carry out k-space computations based on the selected method\n    if (pppmflag)\n    {\n\n    }\n    else if (ewaldflag)\n    {\n\n    }\n}\n\nvoid KSpaceHDNNP::allocate()\n{\n    // Make allocations based on the selected K-space method\n    if (pppmflag)\n    {\n        memory->create3d_offset(density_brick,nzlo_out,nzhi_out,nylo_out,nyhi_out,\n                                nxlo_out,nxhi_out,\"pppm:density_brick\");\n\n        memory->create(density_fft,nfft_both,\"pppm:density_fft\");\n        memory->create(greensfn,nfft_both,\"pppm:greensfn\");\n        memory->create(work1,2*nfft_both,\"pppm:work1\");\n        memory->create(work2,2*nfft_both,\"pppm:work2\");\n        //memory->create(vg,nfft_both,6,\"pppm:vg\"); // TODO virial\n\n        // triclinic = 0 TODO: triclinic systems ?\n        memory->create1d_offset(fkx,nxlo_fft,nxhi_fft,\"pppm:fkx\");\n        memory->create1d_offset(fky,nylo_fft,nyhi_fft,\"pppm:fky\");\n        memory->create1d_offset(fkz,nzlo_fft,nzhi_fft,\"pppm:fkz\");\n\n        // differentiation_flag = 0\n        /*memory->create3d_offset(vdx_brick,nzlo_out,nzhi_out,nylo_out,nyhi_out,\n                                nxlo_out,nxhi_out,\"pppm:vdx_brick\");\n        memory->create3d_offset(vdy_brick,nzlo_out,nzhi_out,nylo_out,nyhi_out,\n                                nxlo_out,nxhi_out,\"pppm:vdy_brick\");\n        memory->create3d_offset(vdz_brick,nzlo_out,nzhi_out,nylo_out,nyhi_out,\n                                nxlo_out,nxhi_out,\"pppm:vdz_brick\");*/\n\n        memory->create3d_offset(vx_brick,nzlo_out,nzhi_out,nylo_out,nyhi_out,\n                                nxlo_out,nxhi_out,\"pppm:vx_brick\");\n        memory->create3d_offset(vy_brick,nzlo_out,nzhi_out,nylo_out,nyhi_out,\n                                nxlo_out,nxhi_out,\"pppm:vy_brick\");\n        memory->create3d_offset(vz_brick,nzlo_out,nzhi_out,nylo_out,nyhi_out,\n                                nxlo_out,nxhi_out,\"pppm:vz_brick\");\n\n        // summation coeffs\n        order_allocated = order;\n        memory->create(gf_b,order,\"pppm:gf_b\");\n        memory->create2d_offset(rho1d,3,-order/2,order/2,\"pppm:rho1d\");\n        memory->create2d_offset(drho1d,3,-order/2,order/2,\"pppm:drho1d\");\n        memory->create2d_offset(rho_coeff,order,(1-order)/2,order/2,\"pppm:rho_coeff\");\n        memory->create2d_offset(drho_coeff,order,(1-order)/2,order/2,\n                                \"pppm:drho_coeff\");\n\n        // create 2 FFTs and a Remap\n        // 1st FFT keeps data in FFT decomposition\n        // 2nd FFT returns data in 3d brick decomposition\n        // remap takes data from 3d brick to FFT decomposition\n\n        int tmp;\n\n        fft1 = new FFT3d(lmp,world,nx_pppm,ny_pppm,nz_pppm,\n                         nxlo_fft,nxhi_fft,nylo_fft,nyhi_fft,nzlo_fft,nzhi_fft,\n                         nxlo_fft,nxhi_fft,nylo_fft,nyhi_fft,nzlo_fft,nzhi_fft,\n                         0,0,&tmp,collective_flag);\n\n        fft2 = new FFT3d(lmp,world,nx_pppm,ny_pppm,nz_pppm,\n                         nxlo_fft,nxhi_fft,nylo_fft,nyhi_fft,nzlo_fft,nzhi_fft,\n                         nxlo_in,nxhi_in,nylo_in,nyhi_in,nzlo_in,nzhi_in,\n                         0,0,&tmp,collective_flag);\n\n        remap = new Remap(lmp,world,\n                          nxlo_in,nxhi_in,nylo_in,nyhi_in,nzlo_in,nzhi_in,\n                          nxlo_fft,nxhi_fft,nylo_fft,nyhi_fft,nzlo_fft,nzhi_fft,\n                          1,0,0,FFT_PRECISION,collective_flag);\n\n        // create ghost grid object for rho and electric field communication\n        // also create 2 bufs for ghost grid cell comm, passed to GridComm methods\n\n        gc = new Grid3d(lmp,world,nx_pppm,ny_pppm,nz_pppm,\n                        nxlo_in,nxhi_in,nylo_in,nyhi_in,nzlo_in,nzhi_in,\n                        nxlo_out,nxhi_out,nylo_out,nyhi_out,nzlo_out,nzhi_out);\n\n        gc->setup_comm(ngc_buf1,ngc_buf2);\n        npergrid = 3;\n\n        memory->create(gc_buf1,npergrid*ngc_buf1,\"pppm:gc_buf1\");\n        memory->create(gc_buf2,npergrid*ngc_buf2,\"pppm:gc_buf2\");\n    }\n    else if (ewaldflag)\n    {\n       \n\t//kxvecs = new int[kmax3d];\n  \t//kyvecs = new int[kmax3d];\n  \t//kzvecs = new int[kmax3d];\n \t//kcoeff = new int[kmax3d];\n\n\t//sf_real = new double[kmax3d];\n  \t//sf_im = new double[kmax3d];\n\t\n\t//for(int i = 0; i < kmax3d; ++i){\n    \t//\tsfexp_rl[i] = new int[nloc];\n    \t//\tsfexp_im[i] = new int[nloc];\n\t//}\n\t\n\tmemory->create(kxvecs,kmax3d,\"ewald:kxvecs\");\n\tmemory->create(kyvecs,kmax3d,\"ewald:kyvecs\");\n        memory->create(kzvecs,kmax3d,\"ewald:kzvecs\");\n        memory->create(kcoeff,kmax3d,\"ewald:kcoeff\");\n\n\tmemory->create(sfexp_rl,kmax3d,atom->natoms,\"ewald:sfexp_rl\");\n        memory->create(sfexp_im,kmax3d,atom->natoms,\"ewald:sfexp_im\");\n        memory->create(sf_real,kmax3d,\"ewald:sf_rl\");\n        memory->create(sf_im,kmax3d,\"ewald:sf_im\");\n\t\n\t//memory->create(eg,kmax3d,3,\"ewald:eg\");\n        //memory->create(vg,kmax3d,6,\"ewald:vg\"); // TODO: might be required for pressure\n\n    }\n}\n\nvoid KSpaceHDNNP::deallocate()\n{\n    // Make deallocations based on the selected K-space method\n    if (pppmflag)\n    {\n        memory->destroy3d_offset(density_brick,nzlo_out,nylo_out,nxlo_out);\n\n        // differentiation_flag = 0\n        /*memory->destroy3d_offset(vdx_brick,nzlo_out,nylo_out,nxlo_out);\n        memory->destroy3d_offset(vdy_brick,nzlo_out,nylo_out,nxlo_out);\n        memory->destroy3d_offset(vdz_brick,nzlo_out,nylo_out,nxlo_out);*/\n\n        memory->destroy3d_offset(vx_brick,nzlo_out,nylo_out,nxlo_out);\n        memory->destroy3d_offset(vy_brick,nzlo_out,nylo_out,nxlo_out);\n        memory->destroy3d_offset(vz_brick,nzlo_out,nylo_out,nxlo_out);\n\n        memory->destroy(density_fft);\n        memory->destroy(greensfn);\n        memory->destroy(work1);\n        memory->destroy(work2);\n        memory->destroy(vg);\n\n        memory->destroy1d_offset(fkx,nxlo_fft);\n        memory->destroy1d_offset(fky,nylo_fft);\n        memory->destroy1d_offset(fkz,nzlo_fft);\n\n        memory->destroy(gf_b);\n\n        memory->destroy2d_offset(rho1d,-order_allocated/2);\n        memory->destroy2d_offset(drho1d,-order_allocated/2);\n        memory->destroy2d_offset(rho_coeff,(1-order_allocated)/2);\n        memory->destroy2d_offset(drho_coeff,(1-order_allocated)/2);\n\n        delete fft1;\n        delete fft2;\n        delete remap;\n        delete gc;\n        memory->destroy(gc_buf1);\n        memory->destroy(gc_buf2);\n    }\n    else if (ewaldflag)\n    {\n        \n\t//delete [] kxvecs;\n  \t//delete [] kyvecs;\n  \t//delete [] kzvecs;\n\t//delete [] kcoeff;\n\t//delete [] sf_real;\n\t//delete [] sf_im;\n\n\t//for(int i = 0; i < kmax3d; ++i) {\n    \t//\tdelete [] sfexp_rl[i];\n\t//\tdelete [] sfexp_im[i];\n\t//}\n\t//delete [] sfexp_rl;\n\t//delete [] sfexp_im;\n        \n\tmemory->destroy(kxvecs);\n\tmemory->destroy(kyvecs);\n\tmemory->destroy(kzvecs);\n\tmemory->destroy(kcoeff);\n\t\n\tmemory->destroy(sf_real);\n        memory->destroy(sf_im);\n\tmemory->destroy(sfexp_rl);\n        memory->destroy(sfexp_im);\n\t\n\t//memory->destroy(ek);\n        //memory->destroy3d_offset(cs,-kmax_created);\n        //memory->destroy3d_offset(sn,-kmax_created);\n\n        //memory->destroy(eg);\n        //memory->destroy(vg);\n    }\n}\n\n// Maps atoms to corresponding grid points\nvoid KSpaceHDNNP::particle_map()\n{\n    int nx,ny,nz;\n\n    double **x = atom->x;\n    int nlocal = atom->nlocal;\n\n    int flag = 0;\n\n    // if atom count has changed, update qsum and qsqsum\n\n    if (atom->natoms != natoms_original) {\n        qsum_qsq();\n        natoms_original = atom->natoms;\n    }\n\n    // return if there are no charges\n\n    if (qsqsum == 0.0) return;\n\n    boxlo = domain->boxlo; //triclinic = 0\n\n    if (!std::isfinite(boxlo[0]) || !std::isfinite(boxlo[1]) || !std::isfinite(boxlo[2]))\n        error->one(FLERR,\"Non-numeric box dimensions - simulation unstable\");\n\n    if (atom->nmax > nmax) {\n        memory->destroy(part2grid);\n        nmax = atom->nmax;\n        memory->create(part2grid,nmax,3,\"kspacehdnnp:part2grid\");\n    }\n\n    for (int i = 0; i < nlocal; i++) {\n\n        // (nx,ny,nz) = global coords of grid pt to \"lower left\" of charge\n        // current particle coord can be outside global and local box\n        // add/subtract OFFSET to avoid int(-0.75) = 0 when want it to be -1\n\n        nx = static_cast<int> ((x[i][0]-boxlo[0])*delxinv+shift) - OFFSET;\n        ny = static_cast<int> ((x[i][1]-boxlo[1])*delyinv+shift) - OFFSET;\n        nz = static_cast<int> ((x[i][2]-boxlo[2])*delzinv+shift) - OFFSET;\n\n\n        // check that entire stencil around nx,ny,nz will fit in my 3d brick\n\n        if (nx+nlower < nxlo_out || nx+nupper > nxhi_out ||\n            ny+nlower < nylo_out || ny+nupper > nyhi_out ||\n            nz+nlower < nzlo_out || nz+nupper > nzhi_out)\n            flag = 1;\n    }\n    if (flag) error->one(FLERR,\"Out of range atoms - cannot compute PPPM\");\n}\n\nvoid KSpaceHDNNP::make_rho_qeq(const gsl_vector *v)\n{\n    int l,m,n,nx,ny,nz,mx,my,mz;\n    FFT_SCALAR dx,dy,dz,x0,y0,z0;\n\n    int *tag = atom->tag;\n\n    // clear 3d density array\n\n    memset(&(density_brick[nzlo_out][nylo_out][nxlo_out]),0,\n           ngrid*sizeof(FFT_SCALAR));\n\n    // loop over my charges, add their contribution to nearby grid points\n    // (nx,ny,nz) = global coords of grid pt to \"lower left\" of charge\n    // (dx,dy,dz) = distance to \"lower left\" grid pt\n    // (mx,my,mz) = global coords of moving stencil pt\n\n    double **x = atom->x;\n    int nlocal = atom->nlocal;\n\n    for (int i = 0; i < nlocal; i++) {\n        //TODO:conversion ?\n        nx = part2grid[i][0];\n        ny = part2grid[i][1];\n        nz = part2grid[i][2];\n        dx = (nx+shiftone - (x[i][0]-boxlo[0])*delxinv) * hdnnp->cflength;\n        dy = (ny+shiftone - (x[i][1]-boxlo[1])*delyinv) * hdnnp->cflength;\n        dz = (nz+shiftone - (x[i][2]-boxlo[2])*delzinv) * hdnnp->cflength;\n\n        compute_rho1d(dx,dy,dz);\n\n        double const qi = gsl_vector_get(v, tag[i]-1);\n\n        //z0 = delvolinv * q[i];\n        z0 = delvolinv * qi;\n        for (n = nlower; n <= nupper; n++) {\n            mz = n+nz;\n            y0 = z0*rho1d[2][n];\n            for (m = nlower; m <= nupper; m++) {\n                my = m+ny;\n                x0 = y0*rho1d[1][m];\n                for (l = nlower; l <= nupper; l++) {\n                    mx = l+nx;\n                    density_brick[mz][my][mx] += x0*rho1d[0][l];\n                }\n            }\n        }\n    }\n}\n\nvoid KSpaceHDNNP::compute_rho1d(const FFT_SCALAR &dx, const FFT_SCALAR &dy, const FFT_SCALAR &dz)\n{\n    int k,l;\n    FFT_SCALAR r1,r2,r3;\n\n    for (k = (1-order)/2; k <= order/2; k++) {\n        r1 = r2 = r3 = ZEROF;\n        std::cout << r1 << '\\n';\n        std::cout << r2 << '\\n';\n        for (l = order-1; l >= 0; l--) {\n            std::cout << l << '\\n';\n            r1 = rho_coeff[l][k] + r1*dx;\n            std::cout << \"aaau\" << '\\n';\n            exit(0);\n            r2 = rho_coeff[l][k] + r2*dy;\n            r3 = rho_coeff[l][k] + r3*dz;\n        }\n        rho1d[0][k] = r1;\n        rho1d[1][k] = r2;\n        rho1d[2][k] = r3;\n    }\n}\n\n// Poission solver in PPPM\nvoid KSpaceHDNNP::poisson()\n{\n    int i,j,k,n;\n    double eng;\n\n    // transform charge density (r -> k)\n\n    n = 0;\n    for (i = 0; i < nfft; i++) {\n        work1[n++] = density_fft[i];\n        work1[n++] = ZEROF;\n    }\n\n    fft1->compute(work1,work1,1);\n\n    // global energy and virial contribution\n\n    double scaleinv = 1.0/(nx_pppm*ny_pppm*nz_pppm);\n    double s2 = scaleinv*scaleinv;\n\n    if (eflag_global || vflag_global) {\n        if (vflag_global) {\n            n = 0;\n            for (i = 0; i < nfft; i++) {\n                eng = s2 * greensfn[i] * (work1[n]*work1[n] + work1[n+1]*work1[n+1]);\n                for (j = 0; j < 6; j++) virial[j] += eng*vg[i][j];\n                if (eflag_global) energy += eng;\n                n += 2;\n            }\n        } else {\n            n = 0;\n            for (i = 0; i < nfft; i++) {\n                //std::cout << \"Green\" << greensfn[i] << '\\n';\n                //std::cout << \"S2\" << s2 << '\\n';\n                //std::cout << \"Par\" << (work1[n]*work1[n] + work1[n+1]*work1[n+1]) << '\\n';\n                energy += s2 * greensfn[i] * (work1[n]*work1[n] + work1[n+1]*work1[n+1]);\n                n += 2;\n            }\n        }\n    }\n\n\n    // scale by 1/total-grid-pts to get rho(k)\n    // multiply by Green's function to get V(k)\n\n    n = 0;\n    for (i = 0; i < nfft; i++) {\n        work1[n++] *= scaleinv * greensfn[i];\n        work1[n++] *= scaleinv * greensfn[i];\n    }\n\n    // extra FFTs for per-atom energy/virial\n    //if (evflag_atom) poisson_peratom(); // TODO: do we need ?\n\n    // compute V(r) in each of 3 dims by transformimg V(k)\n    // FFT leaves data in 3d brick decomposition\n    // copy it into inner portion of vx,vy,vz arrays\n\n    // x direction\n\n    n = 0;\n    for (k = nzlo_fft; k <= nzhi_fft; k++)\n        for (j = nylo_fft; j <= nyhi_fft; j++)\n            for (i = nxlo_fft; i <= nxhi_fft; i++) {\n                work2[n] = work1[n+1];\n                work2[n+1] = work1[n];\n                n += 2;\n            }\n\n    fft2->compute(work2,work2,-1);\n\n    n = 0;\n    for (k = nzlo_in; k <= nzhi_in; k++)\n        for (j = nylo_in; j <= nyhi_in; j++)\n            for (i = nxlo_in; i <= nxhi_in; i++) {\n                vx_brick[k][j][i] = work2[n];\n                n += 2;\n            }\n\n    // y direction\n\n    n = 0;\n    for (k = nzlo_fft; k <= nzhi_fft; k++)\n        for (j = nylo_fft; j <= nyhi_fft; j++)\n            for (i = nxlo_fft; i <= nxhi_fft; i++) {\n                work2[n] = work1[n+1];\n                work2[n+1] = work1[n];\n                n += 2;\n            }\n\n    fft2->compute(work2,work2,-1);\n\n    n = 0;\n    for (k = nzlo_in; k <= nzhi_in; k++)\n        for (j = nylo_in; j <= nyhi_in; j++)\n            for (i = nxlo_in; i <= nxhi_in; i++) {\n                vy_brick[k][j][i] = work2[n];\n                n += 2;\n            }\n\n    // z direction gradient\n\n    n = 0;\n    for (k = nzlo_fft; k <= nzhi_fft; k++)\n        for (j = nylo_fft; j <= nyhi_fft; j++)\n            for (i = nxlo_fft; i <= nxhi_fft; i++) {\n                work2[n] = work1[n+1];\n                work2[n+1] = work1[n];\n                n += 2;\n            }\n\n    fft2->compute(work2,work2,-1);\n\n    n = 0;\n    for (k = nzlo_in; k <= nzhi_in; k++)\n        for (j = nylo_in; j <= nyhi_in; j++)\n            for (i = nxlo_in; i <= nxhi_in; i++) {\n                vz_brick[k][j][i] = work2[n];\n                n += 2;\n            }\n}\n\n//remap density from 3d brick decomposition to FFT decomposition\nvoid KSpaceHDNNP::brick2fft()\n{\n    int n,ix,iy,iz;\n\n    // copy grabs inner portion of density from 3d brick\n    // remap could be done as pre-stage of FFT,\n    //   but this works optimally on only double values, not complex values\n\n    n = 0;\n    for (iz = nzlo_in; iz <= nzhi_in; iz++)\n        for (iy = nylo_in; iy <= nyhi_in; iy++)\n            for (ix = nxlo_in; ix <= nxhi_in; ix++)\n                density_fft[n++] = density_brick[iz][iy][ix];\n\n    remap->perform(density_fft,density_fft,work1);\n}\n\nvoid KSpaceHDNNP::set_grid_local()\n{\n    // global indices of PPPM grid range from 0 to N-1\n    // nlo_in,nhi_in = lower/upper limits of the 3d sub-brick of\n    //   global PPPM grid that I own without ghost cells\n    // for slab PPPM, assign z grid as if it were not extended\n    // both non-tiled and tiled proc layouts use 0-1 fractional sumdomain info\n\n    if (comm->layout != Comm::LAYOUT_TILED) {\n        nxlo_in = static_cast<int> (comm->xsplit[comm->myloc[0]] * nx_pppm);\n        nxhi_in = static_cast<int> (comm->xsplit[comm->myloc[0]+1] * nx_pppm) - 1;\n\n        nylo_in = static_cast<int> (comm->ysplit[comm->myloc[1]] * ny_pppm);\n        nyhi_in = static_cast<int> (comm->ysplit[comm->myloc[1]+1] * ny_pppm) - 1;\n\n        nzlo_in = static_cast<int> (comm->zsplit[comm->myloc[2]] * nz_pppm);\n        nzhi_in = static_cast<int> (comm->zsplit[comm->myloc[2]+1] * nz_pppm) - 1;\n\n    } else {\n        nxlo_in = static_cast<int> (comm->mysplit[0][0] * nx_pppm);\n        nxhi_in = static_cast<int> (comm->mysplit[0][1] * nx_pppm) - 1;\n\n        nylo_in = static_cast<int> (comm->mysplit[1][0] * ny_pppm);\n        nyhi_in = static_cast<int> (comm->mysplit[1][1] * ny_pppm) - 1;\n\n        nzlo_in = static_cast<int> (comm->mysplit[2][0] * nz_pppm);\n        nzhi_in = static_cast<int> (comm->mysplit[2][1] * nz_pppm) - 1;\n    }\n\n\n    // nlower,nupper = stencil size for mapping particles to PPPM grid\n    //TODO: conversion ?\n    nlower = -(order-1)/2;\n    nupper = order/2;\n\n    // shift values for particle <-> grid mapping\n    // add/subtract OFFSET to avoid int(-0.75) = 0 when want it to be -1\n    //TODO: conversion ?\n    if (order % 2) shift = OFFSET + 0.5;\n    else shift = OFFSET;\n    if (order % 2) shiftone = 0.0;\n    else shiftone = 0.5;\n\n    // nlo_out,nhi_out = lower/upper limits of the 3d sub-brick of\n    //   global PPPM grid that my particles can contribute charge to\n    // effectively nlo_in,nhi_in + ghost cells\n    // nlo,nhi = global coords of grid pt to \"lower left\" of smallest/largest\n    //           position a particle in my box can be at\n    // dist[3] = particle position bound = subbox + skin/2.0 + qdist\n    //   qdist = offset due to TIP4P fictitious charge\n    //   convert to triclinic if necessary\n    // nlo_out,nhi_out = nlo,nhi + stencil size for particle mapping\n    // for slab PPPM, assign z grid as if it were not extended\n\n    double *prd,*sublo,*subhi;\n\n    // triclinic  = 0, no slab\n    prd = domain->prd;\n    boxlo = domain->boxlo;\n    sublo = domain->sublo;\n    subhi = domain->subhi;\n\n    // Unit conversions for n2p2\n    boxlo[0] = boxlo[0] * hdnnp->cflength;\n    boxlo[1] = boxlo[1] * hdnnp->cflength;\n    boxlo[2] = boxlo[2] * hdnnp->cflength;\n\n    sublo[0] = sublo[0] * hdnnp->cflength;\n    sublo[1] = sublo[1] * hdnnp->cflength;\n    sublo[2] = sublo[2] * hdnnp->cflength;\n\n    subhi[0] = subhi[0] * hdnnp->cflength;\n    subhi[1] = subhi[1] * hdnnp->cflength;\n    subhi[2] = subhi[2] * hdnnp->cflength;\n\n    double xprd = prd[0] * hdnnp->cflength;\n    double yprd = prd[1] * hdnnp->cflength;\n    double zprd = prd[2] * hdnnp->cflength;\n\n    double dist[3] = {0.0,0.0,0.0};\n    double cuthalf = 0.5*neighbor->skin * hdnnp->cflength;\n    dist[0] = dist[1] = dist[2] = cuthalf;\n\n    int nlo,nhi;\n    nlo = nhi = 0;\n\n    nlo = static_cast<int> ((sublo[0]-dist[0]-boxlo[0]) *\n                            nx_pppm/xprd + shift) - OFFSET;\n    nhi = static_cast<int> ((subhi[0]+dist[0]-boxlo[0]) *\n                            nx_pppm/xprd + shift) - OFFSET;\n    nxlo_out = nlo + nlower;\n    nxhi_out = nhi + nupper;\n\n    nlo = static_cast<int> ((sublo[1]-dist[1]-boxlo[1]) *\n                            ny_pppm/yprd + shift) - OFFSET;\n    nhi = static_cast<int> ((subhi[1]+dist[1]-boxlo[1]) *\n                            ny_pppm/yprd + shift) - OFFSET;\n    nylo_out = nlo + nlower;\n    nyhi_out = nhi + nupper;\n\n    nlo = static_cast<int> ((sublo[2]-dist[2]-boxlo[2]) *\n                            nz_pppm/zprd + shift) - OFFSET;\n    nhi = static_cast<int> ((subhi[2]+dist[2]-boxlo[2]) *\n                            nz_pppm/zprd + shift) - OFFSET;\n    nzlo_out = nlo + nlower;\n    nzhi_out = nhi + nupper;\n\n    // x-pencil decomposition of FFT mesh\n    // global indices range from 0 to N-1\n    // each proc owns entire x-dimension, clumps of columns in y,z dimensions\n    // npey_fft,npez_fft = # of procs in y,z dims\n    // if nprocs is small enough, proc can own 1 or more entire xy planes,\n    //   else proc owns 2d sub-blocks of yz plane\n    // me_y,me_z = which proc (0-npe_fft-1) I am in y,z dimensions\n    // nlo_fft,nhi_fft = lower/upper limit of the section\n    //   of the global FFT mesh that I own in x-pencil decomposition\n\n    int npey_fft,npez_fft;\n    if (nz_pppm >= nprocs) {\n        npey_fft = 1;\n        npez_fft = nprocs;\n    } else procs2grid2d(nprocs,ny_pppm,nz_pppm,&npey_fft,&npez_fft);\n\n    int me_y = me % npey_fft;\n    int me_z = me / npey_fft;\n\n    nxlo_fft = 0;\n    nxhi_fft = nx_pppm - 1;\n    nylo_fft = me_y*ny_pppm/npey_fft;\n    nyhi_fft = (me_y+1)*ny_pppm/npey_fft - 1;\n    nzlo_fft = me_z*nz_pppm/npez_fft;\n    nzhi_fft = (me_z+1)*nz_pppm/npez_fft - 1;\n\n    // ngrid = count of PPPM grid pts owned by this proc, including ghosts\n\n    ngrid = (nxhi_out-nxlo_out+1) * (nyhi_out-nylo_out+1) *\n            (nzhi_out-nzlo_out+1);\n\n    // count of FFT grids pts owned by this proc, without ghosts\n    // nfft = FFT points in x-pencil FFT decomposition on this proc\n    // nfft_brick = FFT points in 3d brick-decomposition on this proc\n    // nfft_both = greater of 2 values\n\n    nfft = (nxhi_fft-nxlo_fft+1) * (nyhi_fft-nylo_fft+1) *\n           (nzhi_fft-nzlo_fft+1);\n    int nfft_brick = (nxhi_in-nxlo_in+1) * (nyhi_in-nylo_in+1) *\n                     (nzhi_in-nzlo_in+1);\n    nfft_both = MAX(nfft,nfft_brick);\n}\n\n/* ----------------------------------------------------------------------\n   set global size of PPPM grid = nx,ny,nz_pppm\n   used for charge accumulation, FFTs, and electric field interpolation\n------------------------------------------------------------------------- */\nvoid KSpaceHDNNP::set_grid_global()\n{\n    // use xprd,yprd,zprd (even if triclinic, and then scale later)\n    // adjust z dimension for 2d slab PPPM\n    // 3d PPPM just uses zprd since slab_volfactor = 1.0\n\n    double xprd = domain->xprd * hdnnp->cflength;\n    double yprd = domain->yprd * hdnnp->cflength;\n    double zprd = domain->zprd * hdnnp->cflength;\n    //double zprd_slab = zprd*slab_volfactor;\n\n    // make initial g_ewald estimate\n    // based on desired accuracy and real space cutoff\n    // fluid-occupied volume used to estimate real-space error\n    // zprd used rather than zprd_slab\n\n    double h;\n    bigint natoms = atom->natoms;\n\n    // TODO: check this, we can also use 'kspace_modify' to pick gewald\n    if (!gewaldflag) {\n        if (accuracy <= 0.0)\n            error->all(FLERR, \"KSpace accuracy must be > 0\");\n        if (q2 == 0.0)\n            error->all(FLERR, \"Must use kspace_modify gewald for uncharged system\");\n        g_ewald = accuracy * sqrt(natoms * cutoff * xprd * yprd * zprd) / (2.0 * q2);\n        if (g_ewald >= 1.0) g_ewald = (1.35 - 0.15 * log(accuracy)) / cutoff;\n        else g_ewald = sqrt(-log(g_ewald)) / cutoff;\n    }\n\n    // set optimal nx_pppm,ny_pppm,nz_pppm based on order and accuracy\n    // nz_pppm uses extended zprd_slab instead of zprd\n    // reduce it until accuracy target is met\n\n    if (!gridflag) { // gridflag = 0 if there is no kspace_modify command\n\n        // differentiation_flag = 0 & stagger_flag = 0 TODO\n        double err;\n        h_x = h_y = h_z = 1.0/g_ewald;\n\n        nx_pppm = static_cast<int> (xprd/h_x) + 1;\n        ny_pppm = static_cast<int> (yprd/h_y) + 1;\n        nz_pppm = static_cast<int> (zprd/h_z) + 1;\n\n        err = estimate_ik_error(h_x,xprd,natoms);\n        while (err > accuracy) {\n            err = estimate_ik_error(h_x,xprd,natoms);\n            nx_pppm++;\n            h_x = xprd/nx_pppm;\n        }\n\n        err = estimate_ik_error(h_y,yprd,natoms);\n        while (err > accuracy) {\n            err = estimate_ik_error(h_y,yprd,natoms);\n            ny_pppm++;\n            h_y = yprd/ny_pppm;\n        }\n\n        err = estimate_ik_error(h_z,zprd,natoms);\n        while (err > accuracy) {\n            err = estimate_ik_error(h_z,zprd,natoms);\n            nz_pppm++;\n            h_z = zprd/nz_pppm;\n        }\n    }\n\n    // boost grid size until it is factorable\n\n    while (!factorable(nx_pppm)) nx_pppm++;\n    while (!factorable(ny_pppm)) ny_pppm++;\n    while (!factorable(nz_pppm)) nz_pppm++;\n\n    // triclinic = 0\n    h_x = xprd/nx_pppm;\n    h_y = yprd/ny_pppm;\n    h_z = zprd/nz_pppm;\n\n\n    if (nx_pppm >= OFFSET || ny_pppm >= OFFSET || nz_pppm >= OFFSET)\n        error->all(FLERR,\"PPPM grid is too large\");\n}\n\nvoid KSpaceHDNNP::compute_rho_coeff()\n{\n    int j,k,l,m;\n    FFT_SCALAR s;\n\n    FFT_SCALAR **a;\n    memory->create2d_offset(a,order,-order,order,\"pppm:a\");\n\n    for (k = -order; k <= order; k++)\n        for (l = 0; l < order; l++)\n            a[l][k] = 0.0;\n\n    a[0][0] = 1.0;\n    for (j = 1; j < order; j++) {\n        for (k = -j; k <= j; k += 2) {\n            s = 0.0;\n            for (l = 0; l < j; l++) {\n                a[l+1][k] = (a[l][k+1]-a[l][k-1]) / (l+1);\n#ifdef FFT_SINGLE\n                s += powf(0.5,(float) l+1) *\n          (a[l][k-1] + powf(-1.0,(float) l) * a[l][k+1]) / (l+1);\n#else\n                s += pow(0.5,(double) l+1) *\n                     (a[l][k-1] + pow(-1.0,(double) l) * a[l][k+1]) / (l+1);\n#endif\n            }\n            a[0][k] = s;\n        }\n    }\n\n    m = (1-order)/2;\n    for (k = -(order-1); k < order; k += 2) {\n        for (l = 0; l < order; l++)\n            rho_coeff[l][m] = a[l][k];\n        for (l = 1; l < order; l++)\n            drho_coeff[l-1][m] = l*a[l][k];\n        m++;\n    }\n\n    memory->destroy2d_offset(a,-order);\n}\n\n// pre-compute modified (Hockney-Eastwood) Coulomb Green's function\nvoid KSpaceHDNNP::compute_gf_ik()\n{\n    const double * const prd = domain->prd;\n    //TODO: conversion ?\n    const double xprd = prd[0] * hdnnp->cflength;\n    const double yprd = prd[1] * hdnnp->cflength;\n    const double zprd = prd[2] * hdnnp->cflength;\n\n    const double unitkx = (MY_2PI/xprd);\n    const double unitky = (MY_2PI/yprd);\n    const double unitkz = (MY_2PI/zprd);\n\n    double snx,sny,snz;\n    double argx,argy,argz,wx,wy,wz,sx,sy,sz,qx,qy,qz;\n    double sum1,dot1,dot2;\n    double numerator,denominator;\n    double sqk;\n\n    int k,l,m,n,nx,ny,nz,kper,lper,mper;\n\n    const int nbx = static_cast<int> ((g_ewald*xprd/(MY_PI*nx_pppm)) *\n                                      pow(-log(EPS_HOC),0.25));\n    const int nby = static_cast<int> ((g_ewald*yprd/(MY_PI*ny_pppm)) *\n                                      pow(-log(EPS_HOC),0.25));\n    const int nbz = static_cast<int> ((g_ewald*zprd/(MY_PI*nz_pppm)) *\n                                      pow(-log(EPS_HOC),0.25));\n    const int twoorder = 2*order;\n\n    n = 0;\n    for (m = nzlo_fft; m <= nzhi_fft; m++) {\n        mper = m - nz_pppm*(2*m/nz_pppm);\n        snz = square(sin(0.5*unitkz*mper*zprd/nz_pppm));\n\n        for (l = nylo_fft; l <= nyhi_fft; l++) {\n            lper = l - ny_pppm*(2*l/ny_pppm);\n            sny = square(sin(0.5*unitky*lper*yprd/ny_pppm));\n\n            for (k = nxlo_fft; k <= nxhi_fft; k++) {\n                kper = k - nx_pppm*(2*k/nx_pppm);\n                snx = square(sin(0.5*unitkx*kper*xprd/nx_pppm));\n\n                sqk = square(unitkx*kper) + square(unitky*lper) + square(unitkz*mper);\n\n                if (sqk != 0.0) {\n                    numerator = 12.5663706/sqk;\n                    denominator = gf_denom(snx,sny,snz);\n                    sum1 = 0.0;\n\n                    for (nx = -nbx; nx <= nbx; nx++) {\n                        qx = unitkx*(kper+nx_pppm*nx);\n                        sx = exp(-0.25*square(qx/g_ewald));\n                        argx = 0.5*qx*xprd/nx_pppm;\n                        wx = powsinxx(argx,twoorder);\n\n                        for (ny = -nby; ny <= nby; ny++) {\n                            qy = unitky*(lper+ny_pppm*ny);\n                            sy = exp(-0.25*square(qy/g_ewald));\n                            argy = 0.5*qy*yprd/ny_pppm;\n                            wy = powsinxx(argy,twoorder);\n\n                            for (nz = -nbz; nz <= nbz; nz++) {\n                                qz = unitkz*(mper+nz_pppm*nz);\n                                sz = exp(-0.25*square(qz/g_ewald));\n                                argz = 0.5*qz*zprd/nz_pppm;\n                                wz = powsinxx(argz,twoorder);\n\n                                dot1 = unitkx*kper*qx + unitky*lper*qy + unitkz*mper*qz;\n                                dot2 = qx*qx+qy*qy+qz*qz;\n                                sum1 += (dot1/dot2) * sx*sy*sz * wx*wy*wz;\n                            }\n                        }\n                    }\n                    greensfn[n++] = numerator*sum1/denominator;\n                } else greensfn[n++] = 0.0;\n            }\n        }\n    }\n}\n\n/* ----------------------------------------------------------------------\n   calculate the final estimate of the accuracy\n------------------------------------------------------------------------- */\n\ndouble KSpaceHDNNP::final_accuracy()\n{\n    double xprd = domain->xprd;\n    double yprd = domain->yprd;\n    double zprd = domain->zprd;\n    bigint natoms = atom->natoms;\n    if (natoms == 0) natoms = 1; // avoid division by zero\n\n    double df_kspace = compute_df_kspace();\n    double q2_over_sqrt = q2 / sqrt(natoms*cutoff*xprd*yprd*zprd);\n    double df_rspace = 2.0 * q2_over_sqrt * exp(-g_ewald*g_ewald*cutoff*cutoff);\n    double df_table = estimate_table_accuracy(q2_over_sqrt,df_rspace);\n    double estimated_accuracy = sqrt(df_kspace*df_kspace + df_rspace*df_rspace +\n                                     df_table*df_table);\n\n    return estimated_accuracy;\n}\n\n/* ----------------------------------------------------------------------\n   compute estimated kspace force error\n------------------------------------------------------------------------- */\n\ndouble KSpaceHDNNP::compute_df_kspace()\n{\n    double xprd = domain->xprd;\n    double yprd = domain->yprd;\n    double zprd = domain->zprd;\n    bigint natoms = atom->natoms;\n    double df_kspace = 0.0;\n\n    //differentiation_flag = 0\n    double lprx = estimate_ik_error(h_x,xprd,natoms);\n    double lpry = estimate_ik_error(h_y,yprd,natoms);\n    double lprz = estimate_ik_error(h_z,zprd,natoms);\n    df_kspace = sqrt(lprx*lprx + lpry*lpry + lprz*lprz) / sqrt(3.0);\n\n    return df_kspace;\n}\n\n/* ----------------------------------------------------------------------\n   estimate kspace force error for ik method\n------------------------------------------------------------------------- */\n\ndouble KSpaceHDNNP::estimate_ik_error(double h, double prd, bigint natoms)\n{\n    double sum = 0.0;\n    if (natoms == 0) return 0.0;\n    for (int m = 0; m < order; m++)\n        sum += acons[order][m] * pow(h*g_ewald,2.0*m);\n    double value = q2 * pow(h*g_ewald,(double)order) *\n                   sqrt(g_ewald*prd*sqrt(MY_2PI)*sum/natoms) / (prd*prd);\n\n    return value;\n}\n\nvoid KSpaceHDNNP::procs2grid2d(int nprocs, int nx, int ny, int *px, int *py)\n{\n    // loop thru all possible factorizations of nprocs\n    // surf = surface area of largest proc sub-domain\n    // innermost if test minimizes surface area and surface/volume ratio\n\n    int bestsurf = 2 * (nx + ny);\n    int bestboxx = 0;\n    int bestboxy = 0;\n\n    int boxx,boxy,surf,ipx,ipy;\n\n    ipx = 1;\n    while (ipx <= nprocs) {\n        if (nprocs % ipx == 0) {\n            ipy = nprocs/ipx;\n            boxx = nx/ipx;\n            if (nx % ipx) boxx++;\n            boxy = ny/ipy;\n            if (ny % ipy) boxy++;\n            surf = boxx + boxy;\n            if (surf < bestsurf ||\n                (surf == bestsurf && boxx*boxy > bestboxx*bestboxy)) {\n                bestsurf = surf;\n                bestboxx = boxx;\n                bestboxy = boxy;\n                *px = ipx;\n                *py = ipy;\n            }\n        }\n        ipx++;\n    }\n}\n\n// pre-compute Green's function denominator expansion coeffs, Gamma(2n)\nvoid KSpaceHDNNP::compute_gf_denom()\n{\n    int k,l,m;\n\n    for (l = 1; l < order; l++) gf_b[l] = 0.0;\n    gf_b[0] = 1.0;\n\n    for (m = 1; m < order; m++) {\n        for (l = m; l > 0; l--)\n            gf_b[l] = 4.0 * (gf_b[l]*(l-m)*(l-m-0.5)-gf_b[l-1]*(l-m-1)*(l-m-1));\n        gf_b[0] = 4.0 * (gf_b[0]*(l-m)*(l-m-0.5));\n    }\n\n    bigint ifact = 1;\n    for (k = 1; k < 2*order; k++) ifact *= k;\n    double gaminv = 1.0/ifact;\n    for (l = 0; l < order; l++) gf_b[l] *= gaminv;\n}\n\nint KSpaceHDNNP::factorable(int n)\n{\n    int i;\n\n    while (n > 1) {\n        for (i = 0; i < nfactors; i++) {\n            if (n % factors[i] == 0) {\n                n /= factors[i];\n                break;\n            }\n        }\n        if (i == nfactors) return 0;\n    }\n\n    return 1;\n}\n\n/* ----------------------------------------------------------------------\n   adjust the g_ewald parameter to near its optimal value\n   using a Newton-Raphson solver\n------------------------------------------------------------------------- */\n\nvoid KSpaceHDNNP::adjust_gewald()\n{\n    double dx;\n\n    for (int i = 0; i < LARGE; i++) {\n        dx = newton_raphson_f() / derivf();\n        g_ewald -= dx;\n        if (fabs(newton_raphson_f()) < SMALL) return;\n    }\n    error->all(FLERR, \"Could not compute g_ewald\");\n}\n\n/* ----------------------------------------------------------------------\n   calculate f(x) using Newton-Raphson solver\n------------------------------------------------------------------------- */\n\ndouble KSpaceHDNNP::newton_raphson_f()\n{\n    double xprd = domain->xprd;\n    double yprd = domain->yprd;\n    double zprd = domain->zprd;\n    bigint natoms = atom->natoms;\n\n    double df_rspace = 2.0*q2*exp(-g_ewald*g_ewald*cutoff*cutoff) /\n                       sqrt(natoms*cutoff*xprd*yprd*zprd);\n\n    double df_kspace = compute_df_kspace();\n\n    return df_rspace - df_kspace;\n}\n\n/* ----------------------------------------------------------------------\n   calculate numerical derivative f'(x) using forward difference\n   [f(x + h) - f(x)] / h\n------------------------------------------------------------------------- */\n\ndouble KSpaceHDNNP::derivf()\n{\n    double h = 0.000001;  //Derivative step-size\n    double df,f1,f2,g_ewald_old;\n\n    f1 = newton_raphson_f();\n    g_ewald_old = g_ewald;\n    g_ewald += h;\n    f2 = newton_raphson_f();\n    g_ewald = g_ewald_old;\n    df = (f2 - f1)/h;\n\n    return df;\n}\n\n// Calculate Ewald eta param (original method in RuNNer - JACKSON_CATLOW)\nvoid KSpaceHDNNP::calculate_ewald_eta(int mflag)\n{\n    ewald_eta = 1.0 / sqrt(2.0 * M_PI);\n\n    //TODO: check\n    if (mflag == 0) ewald_eta *= pow(volume * volume / atom->natoms, 1.0 / 6.0); // regular Ewald eta\n    else            ewald_eta *= pow(volume, 1.0 / 3.0); // matrix approach\n\n}\n\n// Calculate Ewald eta param (efficient method - KOLAFA_PARRAM)\nvoid KSpaceHDNNP::calculate_ewald_eta_efficient()\n{\n    // Ratio of computing times for one real space and k space iteration.\n    double TrOverTk = 3.676; // TODO: should it be hardcoded ?\n\n    // Unit Conversion (in KOLAFA-PERRAM method precision has unit of a force) TODO:check\n    double fourPiEps = 1.0;\n\n    /*precision *= convEnergy / convLength;\n    ewaldMaxCharge *= convCharge;\n    fourPiEps = pow(convCharge, 2) / (convLength * convEnergy);*/\n\n    // Initial approximation\n    double eta0 = pow(1 / TrOverTk * pow(volume, 2) / pow(2 * M_PI, 3),1.0 / 6.0);\n\n    // Selfconsistent calculation of eta\n    ewald_eta = eta0;\n    s_ewald = 0.0; // TODO: check\n    double relError = 1.0;\n    while (relError > 0.01)\n    {\n        // Calculates S\n        double y = accuracy * sqrt(ewald_eta / sqrt(2)) * fourPiEps;\n        y /= 2 * sqrt(atom->natoms * 1.0 / volume) * pow(ewald_max_charge, 2);\n\n        double relYError = 1.0;\n        if (s_ewald <= 0.0)\n            s_ewald = 0.5;\n        double step = s_ewald;\n        while (abs(step) / s_ewald > 0.01 || relYError > 0.01)\n        {\n            step = 2 * s_ewald / (4 * pow(s_ewald,2) + 1);\n            step *= 1 -  sqrt(s_ewald) * y / exp(-pow(s_ewald,2));\n            if (s_ewald <= -step)\n            {\n                s_ewald /= 2;\n                step = 1.0;\n            }\n            else\n                s_ewald += step;\n            relYError = (exp(-pow(s_ewald,2)) / sqrt(s_ewald) - y) / y;\n        }\n\n        double newEta = eta0 * pow((1 + 1 / (2 * pow(s_ewald, 2))), 1.0 / 6.0);\n        relError = abs(newEta - ewald_eta) / ewald_eta;\n        ewald_eta = newEta;\n    }\n\n    ewald_eta = max(ewald_eta, ewald_max_sigma);\n}\n\n// Generate k-space grid in Ewald Sum (RuNNer)\nvoid KSpaceHDNNP::ewald_pbc(double rcut)\n{\n    double proja = fabs(unitk[0]);\n    double projb = fabs(unitk[1]);\n    double projc = fabs(unitk[2]);\n    kxmax = 0;\n    kymax = 0;\n    kzmax = 0;\n    while (kxmax * proja <= rcut) kxmax++;\n    while (kymax * projb <= rcut) kymax++;\n    while (kzmax * projc <= rcut) kzmax++;\n\n    return;\n}\n\n\n\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/kspace_hdnnp.h",
    "content": "/* -*- c++ -*- ----------------------------------------------------------\n   LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator\n   http://lammps.sandia.gov, Sandia National Laboratories\n   Steve Plimpton, sjplimp@sandia.gov\n\n   Copyright (2003) Sandia Corporation.  Under the terms of Contract\n   DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains\n   certain rights in this software.  This software is distributed under\n   the GNU General Public License.\n\n   See the README file in the top-level LAMMPS directory.\n------------------------------------------------------------------------- */\n\n#ifdef KSPACE_CLASS\n\nKSpaceStyle(hdnnp,KSpaceHDNNP)\n\n#else\n\n#ifndef LMP_KSPACE_HDNNP_H\n#define LMP_KSPACE_HDNNP_H\n\n#include <gsl/gsl_multimin.h>\n#include \"kspace.h\"\n#include \"grid3d.h\"\n\n#if defined(FFT_FFTW3)\n#define LMP_FFT_LIB \"FFTW3\"\n#elif defined(FFT_MKL)\n#define LMP_FFT_LIB \"MKL FFT\"\n#elif defined(FFT_CUFFT)\n#define LMP_FFT_LIB \"cuFFT\"\n#else\n#define LMP_FFT_LIB \"KISS FFT\"\n#endif\n\n#ifdef FFT_SINGLE\ntypedef float FFT_SCALAR;\n#define LMP_FFT_PREC \"single\"\n#define MPI_FFT_SCALAR MPI_FLOAT\n#else\n\ntypedef double FFT_SCALAR;\n#define LMP_FFT_PREC \"double\"\n#define MPI_FFT_SCALAR MPI_DOUBLE\n#endif\n\n#include \"InterfaceLammps.h\"\n\n\nnamespace LAMMPS_NS {\n\n    class KSpaceHDNNP : public KSpace {\n        friend class PairHDNNP4G;\n        friend class FixHDNNP;\n    public:\n        KSpaceHDNNP(class LAMMPS *);\n        ~KSpaceHDNNP();\n\n        virtual void settings(int, char **);\n        virtual void init();\n        virtual void setup();\n        //virtual void setup_grid();\n        virtual void compute(int, int);\n        //virtual int timing_1d(int, double &);\n        //virtual int timing_3d(int, double &);\n        //virtual double memory_usage();\n\n    protected:\n\n        class PairHDNNP4G *hdnnp; // interface to HDNNP pair_style\n\n        int ewaldflag,pppmflag;\n\n        int triclinic;               // domain settings, orthog or triclinic\n\n        double cutoff;\n        double gsqmx;\n\n        //// EWALD SUM\n        int kewaldflag; // O if no kspace_modify\n\n        double unitk[3];\n        int *kxvecs,*kyvecs,*kzvecs;\n        int kxmax_orig,kymax_orig,kzmax_orig,kmax_created;\n        int kxmax,kymax,kzmax,kmax,kmax3d;\n        int kcount;\n\n        int ewald_truncation_method; // truncation method (RuNNer)\n\n        double ewald_eta;\n        double s_ewald;\n        double ewald_recip_cutoff;\n        double ewald_real_cutoff;\n\n        double ewald_max_charge;\n        double ewald_max_sigma;\n\n        double *ug;\n        double **eg,**vg;\n        double **ek;\n\n        double *kcoeff;\n        double **sfexp_rl,**sfexp_im;\n        double *sf_real, *sf_im;\n        double *sfexp_rl_all,*sfexp_im_all; // structure factors after communications ?\n        double ***cs,***sn; // cosine and sine grid\n\n        void calculate_ewald_eta(int);\n        void calculate_ewald_eta_efficient();\n\n        void ewald_coeffs();\n        void ewald_sfexp();\n\n        void ewald_pbc(double); // TODO: this is from RuNNer\n\n        double rms(int, double, bigint, double);\n\n        double compute_ewald_eqeq(const gsl_vector*);\n\n        //// PPPM\n\n        int me,nprocs;\n        int nfactors;\n        int *factors;\n\n        double volume;\n        double delxinv,delyinv,delzinv,delvolinv;\n        double h_x,h_y,h_z;\n        double shift,shiftone;\n        int peratom_allocate_flag;\n        int nxlo_in,nylo_in,nzlo_in,nxhi_in,nyhi_in,nzhi_in;\n        int nxlo_out,nylo_out,nzlo_out,nxhi_out,nyhi_out,nzhi_out;\n        int nxlo_ghost,nxhi_ghost,nylo_ghost,nyhi_ghost,nzlo_ghost,nzhi_ghost;\n        int nxlo_fft,nylo_fft,nzlo_fft,nxhi_fft,nyhi_fft,nzhi_fft;\n        int nlower,nupper;\n        int ngrid,nfft,nfft_both;\n\n        FFT_SCALAR ***density_brick;\n        FFT_SCALAR ***vdx_brick,***vdy_brick,***vdz_brick;\n        FFT_SCALAR ***vx_brick,***vy_brick,***vz_brick;\n        FFT_SCALAR ***u_brick;\n        FFT_SCALAR ***v0_brick,***v1_brick,***v2_brick;\n        FFT_SCALAR ***v3_brick,***v4_brick,***v5_brick;\n        double *greensfn;\n        double *fkx,*fky,*fkz;\n        FFT_SCALAR *density_fft;\n        FFT_SCALAR *work1,*work2;\n\n        double *gf_b;\n        FFT_SCALAR **rho1d,**rho_coeff,**drho1d,**drho_coeff;\n        double *sf_precoeff1, *sf_precoeff2, *sf_precoeff3;\n        double *sf_precoeff4, *sf_precoeff5, *sf_precoeff6;\n        double sf_coeff[6];          // coefficients for calculating ad self-forces\n        double **acons;\n\n        // FFTs and grid communication\n\n        class FFT3d *fft1,*fft2;\n        class Remap *remap;\n        class Grid3d *gc;\n\n        FFT_SCALAR *gc_buf1,*gc_buf2;\n        int ngc_buf1,ngc_buf2,npergrid;\n\n        int **part2grid;             // storage for particle -> grid mapping\n        int nmax;\n\n        double *boxlo;\n\n        virtual void set_grid_global();\n        void set_grid_local();\n        void adjust_gewald();\n        virtual double newton_raphson_f();\n        double derivf();\n        double final_accuracy();\n\n        virtual void allocate();\n        //virtual void allocate_peratom();\n        virtual void deallocate();\n        //virtual void deallocate_peratom();\n\n\n        int factorable(int);\n        double compute_df_kspace();\n        double estimate_ik_error(double, double, bigint);\n        //virtual double compute_qopt();\n        virtual void compute_gf_denom();\n        virtual void compute_gf_ik();\n\n\n        void make_rho_qeq(const gsl_vector*); // charge density (rho) / charge\n        virtual void particle_map();\n        double compute_pppm_eqeq();\n        double compute_pppm_dEdQ(int);\n\n        //virtual void make_rho();\n\n        virtual void brick2fft();\n\n        virtual void poisson(); // Poisson solver for P3M (differentiation_flag == 0)\n\n        /*void compute_sf_precoeff();\n\n        virtual void fieldforce();\n        virtual void fieldforce_ik();\n        virtual void fieldforce_ad();\n\n        virtual void poisson_peratom();\n        virtual void fieldforce_peratom();*/\n        void procs2grid2d(int,int,int,int *, int*);\n        void compute_rho1d(const FFT_SCALAR &, const FFT_SCALAR &, const FFT_SCALAR &);\n        //void compute_drho1d(const FFT_SCALAR &, const FFT_SCALAR &,const FFT_SCALAR &);\n        void compute_rho_coeff();\n\n\n        // grid communication\n        /*\n        virtual void pack_forward_grid(int, void *, int, int *);\n        virtual void unpack_forward_grid(int, void *, int, int *);\n        virtual void pack_reverse_grid(int, void *, int, int *);\n        virtual void unpack_reverse_grid(int, void *, int, int *);\n\n        // triclinic\n\n        void setup_triclinic();\n        void compute_gf_ik_triclinic();\n        void poisson_ik_triclinic();\n        void poisson_groups_triclinic();\n\n        // group-group interactions\n\n        virtual void allocate_groups();\n        virtual void deallocate_groups();\n        virtual void make_rho_groups(int, int, int);\n        virtual void poisson_groups(int);\n        virtual void slabcorr_groups(int,int,int);*/\n\n/* ----------------------------------------------------------------------\n   denominator for Hockney-Eastwood Green's function\n     of x,y,z = sin(kx*deltax/2), etc\n\n            inf                 n-1\n   S(n,k) = Sum  W(k+pi*j)**2 = Sum b(l)*(z*z)**l\n           j=-inf               l=0\n\n          = -(z*z)**n /(2n-1)! * (d/dx)**(2n-1) cot(x)  at z = sin(x)\n   gf_b = denominator expansion coeffs\n------------------------------------------------------------------------- */\n\n        inline double gf_denom(const double &x, const double &y,\n                               const double &z) const {\n            double sx,sy,sz;\n            sz = sy = sx = 0.0;\n            for (int l = order-1; l >= 0; l--) {\n                sx = gf_b[l] + sx*x;\n                sy = gf_b[l] + sy*y;\n                sz = gf_b[l] + sz*z;\n            }\n            double s = sx*sy*sz;\n            return s*s;\n        };\n\n\n    };\n\n}\n\n#endif\n#endif\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/pair_hdnnp.cpp",
    "content": "/* -*- c++ -*- ----------------------------------------------------------\n   LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator\n   https://www.lammps.org/ Sandia National Laboratories\n   LAMMPS development team: developers@lammps.org\n\n   Copyright (2003) Sandia Corporation.  Under the terms of Contract\n   DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains\n   certain rights in this software.  This software is distributed under\n   the GNU General Public License.\n\n   This file initially came from n2p2 (https://github.com/CompPhysVienna/n2p2)\n   Copyright (2018) Andreas Singraber (University of Vienna)\n\n   See the README file in the top-level LAMMPS directory.\n------------------------------------------------------------------------- */\n\n/* ----------------------------------------------------------------------\n   Contributing author: Andreas Singraber\n------------------------------------------------------------------------- */\n\n#include \"pair_hdnnp.h\"\n\n#include \"atom.h\"\n#include \"citeme.h\"\n#include \"comm.h\"\n#include \"error.h\"\n#include \"memory.h\"\n#include \"neigh_list.h\"\n#include \"neighbor.h\"\n#include \"update.h\"\n\n#include <cstring>\n\n#include \"InterfaceLammps.h\"    // n2p2 interface header\n\nusing namespace LAMMPS_NS;\n\nstatic const char cite_user_hdnnp_package[] =\n    \"ML-HDNNP package: doi:10.1021/acs.jctc.8b00770\\n\\n\"\n    \"@Article{Singraber19,\\n\"\n    \" author = {Singraber, Andreas and Behler, J{\\\"o}rg and Dellago, Christoph},\\n\"\n    \" title = {Library-Based {LAMMPS} Implementation of High-Dimensional\\n\"\n    \"    Neural Network Potentials},\\n\"\n    \" year = {2019},\\n\"\n    \" month = mar,\\n\"\n    \" volume = {15},\\n\"\n    \" pages = {1827--1840},\\n\"\n    \" doi = {10.1021/acs.jctc.8b00770},\\n\"\n    \" journal = {J.~Chem.\\\\ Theory Comput.},\\n\"\n    \" number = {3}\\n\"\n    \"}\\n\\n\";\n\n/* ---------------------------------------------------------------------- */\n\nPairHDNNP::PairHDNNP(LAMMPS *lmp) : Pair(lmp)\n{\n  if (lmp->citeme) lmp->citeme->add(cite_user_hdnnp_package);\n\n  single_enable = 0;    // 1 if single() routine exists\n  restartinfo = 0;      // 1 if pair style writes restart info\n  one_coeff = 1;        // 1 if allows only one coeff * * call\n  manybody_flag = 1;    // 1 if a manybody potential\n  unit_convert_flag =\n      0;    // TODO: Check possible values. value != 0 indicates support for unit conversion.\n  reinitflag = 0;    // 1 if compatible with fix adapt and alike\n\n  interface = new nnp::InterfaceLammps();\n}\n\n/* ---------------------------------------------------------------------- */\n\nPairHDNNP::~PairHDNNP()\n{\n  delete interface;\n  memory->destroy(setflag);\n  memory->destroy(cutsq);\n}\n\n/* ---------------------------------------------------------------------- */\n\nvoid PairHDNNP::compute(int eflag, int vflag)\n{\n  ev_init(eflag, vflag);\n\n  // Set number of local atoms and add element.\n  interface->setLocalAtoms(atom->nlocal, atom->type);\n  // Transfer tags separately. Interface::setLocalTags is overloaded internally\n  // to work with both -DLAMMPS_SMALLBIG (tagint = int) and -DLAMMPS_BIGBIG\n  // (tagint = int64_t)\n  interface->setLocalTags(atom->tag);\n\n  // Transfer local neighbor list to n2p2 interface.\n  transferNeighborList();\n\n  // Compute symmetry functions, atomic neural networks and add up energy.\n  interface->process();\n\n  // Do all stuff related to extrapolation warnings.\n  if (showew || showewsum > 0 || maxew >= 0) { handleExtrapolationWarnings(); }\n\n  // Calculate forces of local and ghost atoms.\n  interface->getForces(atom->f);\n\n  // Add energy contribution to total energy.\n  if (eflag_global)\n    ev_tally(0, 0, atom->nlocal, 1, interface->getEnergy(), 0.0, 0.0, 0.0, 0.0, 0.0);\n\n  // Add atomic energy if requested (CAUTION: no physical meaning!).\n  if (eflag_atom)\n    for (int i = 0; i < atom->nlocal; ++i) eatom[i] = interface->getAtomicEnergy(i);\n\n  // If virial needed calculate via F dot r.\n  if (vflag_fdotr) virial_fdotr_compute();\n}\n\n/* ----------------------------------------------------------------------\n   global settings\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP::settings(int narg, char **arg)\n{\n  int iarg = 0;\n\n  if (narg < 1) error->all(FLERR, \"Illegal pair_style command\");\n\n  maxCutoffRadius = utils::numeric(FLERR, arg[0], false, lmp);\n  iarg++;\n\n  // default settings\n  directory = utils::strdup(\"hdnnp/\");\n  showew = true;\n  showewsum = 0;\n  maxew = 0;\n  resetew = false;\n  cflength = 1.0;\n  cfenergy = 1.0;\n  numExtrapolationWarningsTotal = 0;\n  numExtrapolationWarningsSummary = 0;\n\n  while (iarg < narg) {\n    // set HDNNP directory\n    if (strcmp(arg[iarg], \"dir\") == 0) {\n      if (iarg + 2 > narg) error->all(FLERR, \"Illegal pair_style command\");\n      delete[] directory;\n      directory = utils::strdup(arg[iarg + 1]);\n      iarg += 2;\n      // show extrapolation warnings\n    } else if (strcmp(arg[iarg], \"showew\") == 0) {\n      if (iarg + 2 > narg) error->all(FLERR, \"Illegal pair_style command\");\n      showew = utils::logical(FLERR, arg[iarg + 1], false, lmp) == 1;\n      iarg += 2;\n      // show extrapolation warning summary\n    } else if (strcmp(arg[iarg], \"showewsum\") == 0) {\n      if (iarg + 2 > narg) error->all(FLERR, \"Illegal pair_style command\");\n      showewsum = utils::inumeric(FLERR, arg[iarg + 1], false, lmp);\n      iarg += 2;\n      // maximum allowed extrapolation warnings\n    } else if (strcmp(arg[iarg], \"maxew\") == 0) {\n      if (iarg + 2 > narg) error->all(FLERR, \"Illegal pair_style command\");\n      maxew = utils::inumeric(FLERR, arg[iarg + 1], false, lmp);\n      iarg += 2;\n      // reset extrapolation warning counter\n    } else if (strcmp(arg[iarg], \"resetew\") == 0) {\n      if (iarg + 2 > narg) error->all(FLERR, \"Illegal pair_style command\");\n      resetew = utils::logical(FLERR, arg[iarg + 1], false, lmp) == 1;\n      iarg += 2;\n      // length unit conversion factor\n    } else if (strcmp(arg[iarg], \"cflength\") == 0) {\n      if (iarg + 2 > narg) error->all(FLERR, \"Illegal pair_style command\");\n      cflength = utils::numeric(FLERR, arg[iarg + 1], false, lmp);\n      iarg += 2;\n      // energy unit conversion factor\n    } else if (strcmp(arg[iarg], \"cfenergy\") == 0) {\n      if (iarg + 2 > narg) error->all(FLERR, \"Illegal pair_style command\");\n      cfenergy = utils::numeric(FLERR, arg[iarg + 1], false, lmp);\n      iarg += 2;\n    } else\n      error->all(FLERR, \"Illegal pair_style command\");\n  }\n}\n\n/* ----------------------------------------------------------------------\n   set coeffs for one or more type pairs\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP::coeff(int narg, char **arg)\n{\n  int n = atom->ntypes;\n\n  if (!allocated) allocate();\n\n  if (narg != 2 + n) error->all(FLERR, \"Incorrect args for pair coefficients\");\n\n  if (strcmp(arg[0], \"*\") != 0 || strcmp(arg[1], \"*\") != 0)\n    error->all(FLERR, \"Incorrect args for pair coefficients\");\n\n  int *map = new int[n + 1];\n  for (int i = 0; i < n; i++) map[i] = 0;\n\n  emap = \"\";\n  for (int i = 2; i < narg; i++) {\n    if (strcmp(arg[i], \"NULL\") != 0) {\n      if (!emap.empty()) emap += \",\";\n      emap += std::to_string(i - 1) + \":\" + arg[i];\n      map[i - 1] = 1;\n    }\n  }\n\n  int count = 0;\n  for (int i = 1; i <= n; i++)\n    for (int j = i; j <= n; j++)\n      if (map[i] > 0 && map[j] > 0) {\n        setflag[i][j] = 1;\n        count++;\n      }\n\n  if (count == 0) error->all(FLERR, \"Incorrect args for pair coefficients\");\n\n  delete[] map;\n}\n\n/* ----------------------------------------------------------------------\n   init specific to this pair style\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP::init_style()\n{\n  neighbor->add_request(this, NeighConst::REQ_FULL);\n\n  // Return immediately if HDNNP setup is already completed.\n  if (interface->isInitialized()) return;\n\n  // Activate screen and logfile output only for rank 0.\n  if (comm->me == 0) {\n    if (lmp->screen != nullptr) interface->log.registerCFilePointer(&(lmp->screen));\n    if (lmp->logfile != nullptr) interface->log.registerCFilePointer(&(lmp->logfile));\n  }\n\n  // Initialize interface on all processors.\n  interface->initialize(directory, emap.c_str(), showew, resetew, showewsum, maxew, cflength,\n                        cfenergy, maxCutoffRadius, atom->ntypes, comm->me);\n\n  // LAMMPS cutoff radius (given via pair_coeff) should not be smaller than\n  // maximum symmetry function cutoff radius.\n  if (maxCutoffRadius < interface->getMaxCutoffRadius())\n    error->all(FLERR, \"Inconsistent cutoff radius\");\n}\n\n/* ----------------------------------------------------------------------\n   init for one type pair i,j and corresponding j,i\n------------------------------------------------------------------------- */\n\ndouble PairHDNNP::init_one(int, int)\n{\n  return maxCutoffRadius;\n}\n\n/* ----------------------------------------------------------------------\n   allocate all arrays\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP::allocate()\n{\n  allocated = 1;\n  int n = atom->ntypes;\n\n  memory->create(setflag, n + 1, n + 1, \"pair:setflag\");\n  for (int i = 1; i <= n; i++)\n    for (int j = i; j <= n; j++) setflag[i][j] = 0;\n\n  memory->create(cutsq, n + 1, n + 1, \"pair:cutsq\");    // TODO: Is this required?\n}\n\nvoid PairHDNNP::transferNeighborList()\n{\n  // Transfer neighbor list to n2p2.\n  double rc2 = maxCutoffRadius * maxCutoffRadius;\n  for (int ii = 0; ii < list->inum; ++ii) {\n    int i = list->ilist[ii];\n    for (int jj = 0; jj < list->numneigh[i]; ++jj) {\n      int j = list->firstneigh[i][jj];\n      j &= NEIGHMASK;\n      double dx = atom->x[i][0] - atom->x[j][0];\n      double dy = atom->x[i][1] - atom->x[j][1];\n      double dz = atom->x[i][2] - atom->x[j][2];\n      double d2 = dx * dx + dy * dy + dz * dz;\n      if (d2 <= rc2) { interface->addNeighbor(i, j, atom->tag[j], atom->type[j], dx, dy, dz, d2); }\n    }\n  }\n}\n\nvoid PairHDNNP::handleExtrapolationWarnings()\n{\n  // Get number of extrapolation warnings for local atoms.\n  long numCurrentEW = (long) interface->getNumExtrapolationWarnings();\n\n  // Update (or set, resetew == true) total warnings counter.\n  if (resetew)\n    numExtrapolationWarningsTotal = numCurrentEW;\n  else\n    numExtrapolationWarningsTotal += numCurrentEW;\n\n  // Update warnings summary counter.\n  if (showewsum > 0) { numExtrapolationWarningsSummary += numCurrentEW; }\n\n  // If requested write extrapolation warnings.\n  // Requires communication of all symmetry functions statistics entries to\n  // rank 0.\n  if (showew > 0) {\n    // First collect an overview of extrapolation warnings per process.\n    long *numEWPerProc = nullptr;\n    if (comm->me == 0) numEWPerProc = new long[comm->nprocs];\n    MPI_Gather(&numCurrentEW, 1, MPI_LONG, numEWPerProc, 1, MPI_LONG, 0, world);\n\n    if (comm->me == 0) {\n      for (int i = 1; i < comm->nprocs; i++) {\n        if (numEWPerProc[i] > 0) {\n          long bs = 0;\n          MPI_Status ms;\n          // Get buffer size.\n          MPI_Recv(&bs, 1, MPI_LONG, i, 0, world, &ms);\n          auto buf = new char[bs];\n          // Receive buffer.\n          MPI_Recv(buf, bs, MPI_BYTE, i, 0, world, &ms);\n          interface->extractEWBuffer(buf, bs);\n          delete[] buf;\n        }\n      }\n      interface->writeExtrapolationWarnings();\n    } else if (numCurrentEW > 0) {\n      // Get desired buffer length for all extrapolation warning entries.\n      long bs = interface->getEWBufferSize();\n      // Allocate and fill buffer.\n      auto buf = new char[bs];\n      interface->fillEWBuffer(buf, bs);\n      // Send buffer size and buffer.\n      MPI_Send(&bs, 1, MPI_LONG, 0, 0, world);\n      MPI_Send(buf, bs, MPI_BYTE, 0, 0, world);\n      delete[] buf;\n    }\n\n    if (comm->me == 0) delete[] numEWPerProc;\n  }\n\n  // If requested gather number of warnings to display summary.\n  if (showewsum > 0 && update->ntimestep % showewsum == 0) {\n    long globalEW = 0;\n    // Communicate the sum over all processors to proc 0.\n    MPI_Reduce(&numExtrapolationWarningsSummary, &globalEW, 1, MPI_LONG, MPI_SUM, 0, world);\n    // Write to screen or logfile.\n    if (comm->me == 0)\n      utils::logmesg(lmp, \"### NNP EW SUMMARY ### TS: {:10d} EW {:10d} EWPERSTEP {:10.3e}\\n\",\n                     update->ntimestep, globalEW, double(globalEW) / showewsum);\n    // Reset summary counter.\n    numExtrapolationWarningsSummary = 0;\n  }\n\n  // Stop if maximum number of extrapolation warnings is exceeded.\n  if (numExtrapolationWarningsTotal > maxew) {\n    error->one(FLERR, \"Too many extrapolation warnings\");\n  }\n\n  // Reset internal extrapolation warnings counters.\n  interface->clearExtrapolationWarnings();\n}\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/pair_hdnnp.h",
    "content": "/* -*- c++ -*- ----------------------------------------------------------\n   LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator\n   https://www.lammps.org/ Sandia National Laboratories\n   LAMMPS development team: developers@lammps.org\n\n   Copyright (2003) Sandia Corporation.  Under the terms of Contract\n   DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains\n   certain rights in this software.  This software is distributed under\n   the GNU General Public License.\n\n   This file initially came from n2p2 (https://github.com/CompPhysVienna/n2p2)\n   Copyright (2018) Andreas Singraber (University of Vienna)\n\n   See the README file in the top-level LAMMPS directory.\n------------------------------------------------------------------------- */\n\n/* ----------------------------------------------------------------------\n   Contributing author: Andreas Singraber\n------------------------------------------------------------------------- */\n\n#ifdef PAIR_CLASS\n// clang-format off\nPairStyle(hdnnp,PairHDNNP);\n// clang-format on\n#else\n\n#ifndef LMP_PAIR_HDNNP_H\n#define LMP_PAIR_HDNNP_H\n\n#include \"pair.h\"\n\nnamespace nnp {\nclass InterfaceLammps;\n}\n\nnamespace LAMMPS_NS {\n\nclass PairHDNNP : public Pair {\n\n public:\n  PairHDNNP(class LAMMPS *);\n  ~PairHDNNP() override;\n  void compute(int, int) override;\n  void settings(int, char **) override;\n  void coeff(int, char **) override;\n  void init_style() override;\n  double init_one(int, int) override;\n\n protected:\n  virtual void allocate();\n  void transferNeighborList();\n  void handleExtrapolationWarnings();\n\n  bool showew;\n  bool resetew;\n  int showewsum;\n  int maxew;\n  long numExtrapolationWarningsTotal;\n  long numExtrapolationWarningsSummary;\n  double cflength;\n  double cfenergy;\n  double maxCutoffRadius;\n  char *directory;\n  std::string emap;\n  nnp::InterfaceLammps *interface;\n};\n\n}    // namespace LAMMPS_NS\n\n#endif\n#endif\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/pair_hdnnp_4g.cpp",
    "content": "/* -*- c++ -*- ----------------------------------------------------------\n   LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator\n   https://www.lammps.org/ Sandia National Laboratories\n   LAMMPS development team: developers@lammps.org\n\n   Copyright (2003) Sandia Corporation.  Under the terms of Contract\n   DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains\n   certain rights in this software.  This software is distributed under\n   the GNU General Public License.\n\n   This file initially came from n2p2 (https://github.com/CompPhysVienna/n2p2)\n   Copyright (2018) Andreas Singraber (University of Vienna)\n\n   See the README file in the top-level LAMMPS directory.\n------------------------------------------------------------------------- */\n\n/* ----------------------------------------------------------------------\n   Contributing authors: Emir Kocer\n                         Andreas Singraber\n------------------------------------------------------------------------- */\n\n#include <mpi.h>\n#include <iostream>\n#include <cmath>\n#include <string.h>\n#include <stdlib.h>  //exit(0);\n#include <vector>\n#include \"pair_hdnnp_4g.h\"\n#include \"atom.h\"\n#include \"comm.h\"\n#include \"force.h\"\n#include \"kspace.h\"\n#include \"neighbor.h\"\n#include \"neigh_list.h\"\n#include \"neigh_request.h\"\n#include \"memory.h\"\n#include \"error.h\"\n#include \"update.h\"\n#include \"domain.h\" //periodicity\n#include \"fix_hdnnp.h\"\n#include \"kspace_hdnnp.h\"\n#include <chrono> //time\n#include <thread>\n\nusing namespace LAMMPS_NS;\nusing namespace std::chrono;\nusing namespace nnp;\nusing namespace std;\n\n#define SQR(x) ((x)*(x))\n\n/* ---------------------------------------------------------------------- */\n\nPairHDNNP4G::PairHDNNP4G(LAMMPS *lmp) : Pair(lmp),\n    kspacehdnnp                    (nullptr),\n    periodic                       (false  ),\n    showew                         (false  ),\n    resetew                        (false  ),\n    showewsum                      (0      ),\n    maxew                          (0      ),\n    numExtrapolationWarningsTotal  (0      ),\n    numExtrapolationWarningsSummary(0      ),\n    cflength                       (0.0    ),\n    cfenergy                       (0.0    ),\n    maxCutoffRadius                (0.0    ),\n    directory                      (nullptr),\n    emap                           (nullptr),\n    list                           (nullptr),\n    chi                            (nullptr),\n    hardness                       (nullptr),\n    sigmaSqrtPi                    (nullptr),\n    gammaSqrt2                     (nullptr),\n    dEdQ                           (nullptr),\n    forceLambda                    (nullptr),\n    grad_tol                       (0.0    ),\n    min_tol                        (0.0    ),\n    step                           (0.0    ),\n    maxit                          (0      ),\n    minim_init_style               (0      ),\n    T                              (nullptr),\n    s                              (nullptr),\n    E_elec                         (0.0    ),\n    kcoeff_sum                     (0.0    ),\n    type_all                       (nullptr),\n    type_loc                       (nullptr),\n    dEdLambda_loc                  (nullptr),\n    dEdLambda_all                  (nullptr),\n    qall_loc                       (nullptr),\n    qall                           (nullptr),\n    xx                             (nullptr),\n    xy                             (nullptr),\n    xz                             (nullptr),\n    xx_loc                         (nullptr),\n    xy_loc                         (nullptr),\n    xz_loc                         (nullptr),\n    forceLambda_loc                (nullptr),\n    forceLambda_all                (nullptr),\n    erfc_val                       (nullptr),\n    kcos                           (nullptr),\n    ksinx                          (nullptr),\n    ksiny                          (nullptr),\n    ksinz                          (nullptr),\n    screening_info                 (nullptr)\n{\n\n    MPI_Comm_rank(world,&me);\n    MPI_Comm_size(world,&nprocs);\n}\n\n/* ----------------------------------------------------------------------\n   check if allocated, since class can be destructed when incomplete\n------------------------------------------------------------------------- */\n\nPairHDNNP4G::~PairHDNNP4G()\n{\n}\n\nvoid PairHDNNP4G::compute(int eflag, int vflag)\n{\n  if(eflag || vflag) ev_setup(eflag,vflag);\n  else evflag = vflag_fdotr = eflag_global = eflag_atom = 0;\n\n  if (interface.getNnpType() == InterfaceLammps::NNPType::HDNNP_2G)\n  {\n      // Set number of local atoms and add element.\n      interface.setLocalAtoms(atom->nlocal,atom->type);\n\n      // Set tags of local atoms.\n      interface.setLocalTags(atom->tag);\n\n      // Transfer local neighbor list to NNP interface.\n      transferNeighborList();\n\n      // Compute symmetry functions, atomic neural networks and add up energy.\n      interface.process();\n\n      // Do all stuff related to extrapolation warnings.\n      if(showew == true || showewsum > 0 || maxew >= 0) {\n          handleExtrapolationWarnings();\n      }\n\n      // get short-range forces of local and ghost atoms.\n      interface.getForces(atom->f);\n\n  }\n  else if (interface.getNnpType() == InterfaceLammps::NNPType::HDNNP_4G)\n  {\n      // Transfer charges into n2p2 before running second set of NNs\n      transferCharges();\n\n      // Add electrostatic energy contribution to the total energy before conversion TODO:check\n      interface.addElectrostaticEnergy(E_elec);\n\n      // Run second set of NNs for the short range contributions\n      interface.process();\n\n      // Get short-range forces of local and ghost atoms.\n      interface.getForces(atom->f);\n\n      // Initialize global arrays\n      for (int i =0; i < atom->natoms; i++){\n          qall[i] = 0.0;\n          qall_loc[i] = 0.0;\n          dEdLambda_all[i] = 0.0;\n          dEdLambda_loc[i] = 0.0;\n          forceLambda[i] = 0.0;\n          dEdQ[i] = 0.0;\n          forceLambda_loc[i] = 0.0;\n          forceLambda_all[i] = 0.0;\n          xx_loc[i] = 0.0;\n          xy_loc[i] = 0.0;\n          xz_loc[i] = 0.0;\n          xx[i] = 0.0;\n          xy[i] = 0.0;\n          xz[i] = 0.0;\n          type_loc[i] = 0;\n          type_all[i] = 0;\n      }\n\n      // Create global sparse arrays here\n      for (int i = 0; i < atom->nlocal; i++){\n          qall_loc[atom->tag[i]-1] = atom->q[i]; // global charge vector on each proc\n          xx_loc[atom->tag[i]-1] = atom->x[i][0];\n          xy_loc[atom->tag[i]-1] = atom->x[i][1];\n          xz_loc[atom->tag[i]-1] = atom->x[i][2];\n          type_loc[atom->tag[i]-1] = atom->type[i];\n      }\n\n      // Communicate atomic charges and positions\n      MPI_Allreduce(qall_loc,qall,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n      MPI_Allreduce(type_loc,type_all,atom->natoms,MPI_INT,MPI_SUM,world);\n      MPI_Allreduce(xx_loc,xx,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n      MPI_Allreduce(xy_loc,xy,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n      MPI_Allreduce(xz_loc,xz,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n\n      //TODO: it did not work when they were in the constructor as they are in FixHDNNP, check\n      if (periodic){\n          kspacehdnnp = nullptr;\n          kspacehdnnp = (KSpaceHDNNP *) force->kspace_match(\"^hdnnp\",0);\n      }\n\n      // Calculates and stores k-space terms for speedup\n      calculate_kspace_terms();\n\n      // Calculate dEelecdQ and add pEelecpr contribution to the total force vector\n      calculateElecDerivatives(dEdQ,atom->f); // TODO: calculate fElec separately ?\n\n      // Read dEdG array from n2p2\n      interface.getdEdQ(dEdQ);\n\n      // Calculate lambda vector that is necessary for optimized force calculation\n      calculateForceLambda(); // TODO: lambdaElec & f_elec ?\n\n      // Communicate forceLambda\n      for (int i = 0; i < atom->nlocal; i++){\n          forceLambda_loc[atom->tag[i]-1] = forceLambda[i];\n      }\n      for (int i = 0; i < atom->natoms; i++){\n          forceLambda_all[i] = 0.0;\n      }\n      MPI_Allreduce(forceLambda_loc,forceLambda_all,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n\n      // Add electrostatic contributions and calculate final force vector\n      calculateElecForce(atom->f);\n\n      // TODO check\n      memory->destroy(erfc_val);\n      \n      // Do all stuff related to extrapolation warnings.\n      if(showew == true || showewsum > 0 || maxew >= 0) {\n          handleExtrapolationWarnings();\n      }\n  }\n  // Add energy contribution to total energy.\n  if (eflag_global)\n     ev_tally(0,0,atom->nlocal,1,interface.getEnergy(),0.0,0.0,0.0,0.0,0.0);\n\n  // Add atomic energy if requested (CAUTION: no physical meaning!).\n  if (eflag_atom)\n    for (int i = 0; i < atom->nlocal; ++i)\n      eatom[i] = interface.getAtomicEnergy(i);\n\n  // If virial needed calculate via F dot r.\n  if (vflag_fdotr) virial_fdotr_compute();\n}\n\n/* ----------------------------------------------------------------------\n   global settings\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP4G::settings(int narg, char **arg)\n{\n  int iarg = 0;\n\n  if (narg == 0) error->all(FLERR,\"Illegal pair_style command\");\n\n  // default settings\n  int len = strlen(\"nnp/\") + 1;\n  directory = new char[len];\n  strcpy(directory,\"nnp/\");\n  showew = true;\n  showewsum = 0;\n  maxew = 0;\n  resetew = false;\n  cflength = 1.0;\n  cfenergy = 1.0;\n  len = strlen(\"\") + 1;\n  emap = new char[len];\n  strcpy(emap,\"\");\n  numExtrapolationWarningsTotal = 0;\n  numExtrapolationWarningsSummary = 0;\n\n  while(iarg < narg) {\n    // set NNP directory\n    if (strcmp(arg[iarg],\"dir\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      delete[] directory;\n      len = strlen(arg[iarg+1]) + 2;\n      directory = new char[len];\n      sprintf(directory, \"%s/\", arg[iarg+1]);\n      iarg += 2;\n    // element mapping\n    } else if (strcmp(arg[iarg],\"emap\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      delete[] emap;\n      len = strlen(arg[iarg+1]) + 1;\n      emap = new char[len];\n      sprintf(emap, \"%s\", arg[iarg+1]);\n      iarg += 2;\n    // show extrapolation warnings\n    } else if (strcmp(arg[iarg],\"showew\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      if (strcmp(arg[iarg+1],\"yes\") == 0)\n        showew = true;\n      else if (strcmp(arg[iarg+1],\"no\") == 0)\n        showew = false;\n      else\n        error->all(FLERR,\"Illegal pair_style command\");\n      iarg += 2;\n    // show extrapolation warning summary\n    } else if (strcmp(arg[iarg],\"showewsum\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      showewsum = utils::inumeric(FLERR,arg[iarg+1],false,lmp);\n      iarg += 2;\n    // maximum allowed extrapolation warnings\n    } else if (strcmp(arg[iarg],\"maxew\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      maxew = utils::inumeric(FLERR,arg[iarg+1],false,lmp);\n      iarg += 2;\n    // reset extrapolation warning counter\n    } else if (strcmp(arg[iarg],\"resetew\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      if (strcmp(arg[iarg+1],\"yes\") == 0)\n        resetew = true;\n      else if (strcmp(arg[iarg+1],\"no\") == 0)\n        resetew = false;\n      else\n        error->all(FLERR,\"Illegal pair_style command\");\n      iarg += 2;\n    // length unit conversion factor\n    } else if (strcmp(arg[iarg],\"cflength\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      cflength = utils::numeric(FLERR,arg[iarg+1],false,lmp);\n      iarg += 2;\n    // energy unit conversion factor\n    } else if (strcmp(arg[iarg],\"cfenergy\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      cfenergy = utils::numeric(FLERR,arg[iarg+1],false,lmp);\n      iarg += 2;\n    } else error->all(FLERR,\"Illegal pair_style command\");\n  }\n}\n\n/* ----------------------------------------------------------------------\n   set coeffs for one or more type pairs\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP4G::coeff(int narg, char **arg)\n{\n  if (!allocated) allocate();\n\n  if (narg != 3) error->all(FLERR,\"Incorrect args for pair coefficients\");\n\n  int ilo,ihi,jlo,jhi;\n\n  utils::bounds(FLERR,arg[0],1,atom->ntypes,ilo,ihi,error);\n  utils::bounds(FLERR,arg[1],1,atom->ntypes,jlo,jhi,error);\n\n  maxCutoffRadius = utils::numeric(FLERR,arg[2],false,lmp); // this the cutoff specified via pair_coeff in the input\n\n  // TODO: Check how this flag is set.\n  int count = 0;\n  for(int i=ilo; i<=ihi; i++) {\n    for(int j=MAX(jlo,i); j<=jhi; j++) {\n      setflag[i][j] = 1;\n      count++;\n    }\n  }\n\n  if (count == 0) error->all(FLERR,\"Incorrect args for pair coefficients\");\n}\n\n/* ----------------------------------------------------------------------\n   init specific to this pair style\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP4G::init_style()\n{\n  //int irequest = neighbor->request((void *) this);\n  //neighbor->requests[irequest]->pair = 1;\n  //neighbor->requests[irequest]->half = 0;\n  //neighbor->requests[irequest]->full = 1;\n  neighbor->add_request(this, NeighConst::REQ_FULL);\n\n  // Return immediately if NNP setup is already completed.\n  if (interface.isInitialized()) return;\n\n  // Activate screen and logfile output only for rank 0.\n  if (comm->me == 0) {\n    if (lmp->screen != NULL)\n      interface.log.registerCFilePointer(&(lmp->screen));\n    if (lmp->logfile != NULL)\n      interface.log.registerCFilePointer(&(lmp->logfile));\n  }\n\n  ///TODO: add nnpType\n  // Initialize interface on all processors.\n  interface.initialize(directory,\n                       emap,\n                       showew,\n                       resetew,\n                       showewsum,\n                       maxew,\n                       cflength,\n                       cfenergy,\n                       maxCutoffRadius,\n                       atom->ntypes,\n                       comm->me);\n  // LAMMPS cutoff radius (given via pair_coeff) should not be smaller than\n  // maximum symmetry function cutoff radius.\n  if (maxCutoffRadius < interface.getMaxCutoffRadius())\n    error->all(FLERR,\"Inconsistent cutoff radius\");\n\n    if (interface.getNnpType() == InterfaceLammps::NNPType::HDNNP_4G)\n    {\n        isPeriodic(); // check for periodicity here\n    }\n}\n\n/* ----------------------------------------------------------------------\n   init neighbor list(TODO: check this)\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP4G::init_list(int /*id*/, NeighList *ptr)\n{\n    list = ptr;\n}\n\n/* ----------------------------------------------------------------------\n   init for one type pair i,j and corresponding j,i\n------------------------------------------------------------------------- */\n\ndouble PairHDNNP4G::init_one(int i, int j)\n{\n  // TODO: Check how this actually works for different cutoffs.\n  return maxCutoffRadius;\n}\n\n/* ----------------------------------------------------------------------\n   proc 0 writes to restart file\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP4G::write_restart(FILE *fp)\n{\n    return;\n}\n\n/* ----------------------------------------------------------------------\n   proc 0 reads from restart file, bcasts\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP4G::read_restart(FILE *fp)\n{\n    return;\n}\n\n/* ----------------------------------------------------------------------\n   proc 0 writes to restart file\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP4G::write_restart_settings(FILE *fp)\n{\n    return;\n}\n\n/* ----------------------------------------------------------------------\n   proc 0 reads from restart file, bcasts\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP4G::read_restart_settings(FILE *fp)\n{\n    return;\n}\n\n/* ----------------------------------------------------------------------\n   allocate all arrays\n------------------------------------------------------------------------- */\n\nvoid PairHDNNP4G::allocate()\n{\n  allocated = 1;\n  int n = atom->ntypes;\n  int natoms = atom->natoms;\n  int nlocal = atom->nlocal;\n\n\n\n  memory->create(setflag,n+1,n+1,\"pair:setflag\");\n  for (int i = 1; i <= n; i++)\n    for (int j = i; j <= n; j++)\n      setflag[i][j] = 0;\n\n  memory->create(cutsq,n+1,n+1,\"pair:cutsq\");\n\n  // TODO: add an if and initialize only for 4G\n  // Allocate and initialize 4G-related arrays\n  dEdQ = nullptr;\n  forceLambda = nullptr;\n  memory->create(dEdQ,natoms+1,\"pair:dEdQ\");\n  memory->create(forceLambda,natoms+1,\"pair:forceLambda\");\n  memory->create(dEdLambda_loc,natoms,\"pair_nnp:dEdLambda_loc\");\n  memory->create(dEdLambda_all,natoms,\"pair_nnp:dEdLambda_all\");\n  memory->create(qall_loc,natoms,\"pair_nnp:qall_loc\");\n  memory->create(qall,natoms,\"pair_nnp:qall\");\n  memory->create(type_loc,natoms,\"pair_nnp:type_loc\");\n  memory->create(type_all,natoms,\"pair_nnp:type_all\");\n  memory->create(xx,natoms,\"pair_nnp:xx\");\n  memory->create(xy,natoms,\"pair_nnp:xy\");\n  memory->create(xz,natoms,\"pair_nnp:xz\");\n  memory->create(xx_loc,natoms,\"pair_nnp:xx_loc\");\n  memory->create(xy_loc,natoms,\"pair_nnp:xy_loc\");\n  memory->create(xz_loc,natoms,\"pair_nnp:xz_loc\");\n  memory->create(forceLambda_loc,natoms,\"pair_nnp:forceLambda_loc\");\n  memory->create(forceLambda_all,natoms,\"pair_nnp:forceLambda_all\");\n  \n  /*memory->create(kcos,nlocal,natoms,\"pair_nnp:kcos\");\n  memory->create(ksinx,nlocal,natoms,\"pair_nnp:ksinx\");\n  memory->create(ksiny,nlocal,natoms,\"pair_nnp:ksiny\");\n  memory->create(ksinz,nlocal,natoms,\"pair_nnp:ksinz\");*/\n\n  for (int i = 0; i < natoms+1; i++)\n  {\n      forceLambda[i] = 0.0;\n      dEdQ[i] = 0.0;\n  }\n\n    /*for (int i = 0; i < nlocal; i++)\n    {\n        for (int j = 0; j < natoms; j++)\n        {\n            kcos[i][j] = 0.0;\n            ksinx[i][j] = 0.0;\n            ksiny[i][j] = 0.0;\n            ksinz[i][j] = 0.0;\n        }\n    }*/\n\n}\n\n// Transfers neighbor lists to n2p2\nvoid PairHDNNP4G::transferNeighborList()\n{\n  // Transfer neighbor list to NNP.\n  double rc2 = maxCutoffRadius * maxCutoffRadius;\n  for (int ii = 0; ii < list->inum; ++ii) {\n    int i = list->ilist[ii];\n    for (int jj = 0; jj < list->numneigh[i]; ++jj) {\n      int j = list->firstneigh[i][jj];\n      j &= NEIGHMASK;\n      double dx = atom->x[i][0] - atom->x[j][0];\n      double dy = atom->x[i][1] - atom->x[j][1];\n      double dz = atom->x[i][2] - atom->x[j][2];\n      double d2 = dx * dx + dy * dy + dz * dz;\n      if (d2 <= rc2) {\n        interface.addNeighbor(i,j,atom->tag[j],atom->type[j],dx,dy,dz,d2);\n      }\n    }\n  }\n}\n\nvoid PairHDNNP4G::handleExtrapolationWarnings()\n{\n  // Get number of extrapolation warnings for local atoms.\n  // TODO: Is the conversion from std::size_t to long ok?\n  long numCurrentEW = (long)interface.getNumExtrapolationWarnings();\n\n  // Update (or set, resetew == true) total warnings counter.\n  if (resetew) numExtrapolationWarningsTotal = numCurrentEW;\n  else numExtrapolationWarningsTotal += numCurrentEW;\n\n  // Update warnings summary counter.\n  if(showewsum > 0) {\n    numExtrapolationWarningsSummary += numCurrentEW;\n  }\n\n  // If requested write extrapolation warnings.\n  // Requires communication of all symmetry functions statistics entries to\n  // rank 0.\n  if(showew > 0) {\n    // First collect an overview of extrapolation warnings per process.\n    long* numEWPerProc = NULL;\n    if(comm->me == 0) numEWPerProc = new long[comm->nprocs];\n    MPI_Gather(&numCurrentEW, 1, MPI_LONG, numEWPerProc, 1, MPI_LONG, 0, world);\n\n    if(comm->me == 0) {\n      for(int i=1;i<comm->nprocs;i++) {\n        if(numEWPerProc[i] > 0) {\n          long bs = 0;\n          MPI_Status ms;\n          // Get buffer size.\n          MPI_Recv(&bs, 1, MPI_LONG, i, 0, world, &ms);\n          char* buf = new char[bs];\n          // Receive buffer.\n          MPI_Recv(buf, bs, MPI_BYTE, i, 0, world, &ms);\n          interface.extractEWBuffer(buf, bs);\n          delete[] buf;\n        }\n      }\n      interface.writeExtrapolationWarnings();\n    }\n    else if(numCurrentEW > 0) {\n      // Get desired buffer length for all extrapolation warning entries.\n      long bs = interface.getEWBufferSize();\n      // Allocate and fill buffer.\n      char* buf = new char[bs];\n      interface.fillEWBuffer(buf, bs);\n      // Send buffer size and buffer.\n      MPI_Send(&bs, 1, MPI_LONG, 0, 0, world);\n      MPI_Send(buf, bs, MPI_BYTE, 0, 0, world);\n      delete[] buf;\n    }\n\n    if(comm->me == 0) delete[] numEWPerProc;\n  }\n\n  // If requested gather number of warnings to display summary.\n  if(showewsum > 0 && update->ntimestep % showewsum == 0) {\n    long globalEW = 0;\n    // Communicate the sum over all processors to proc 0.\n    MPI_Reduce(&numExtrapolationWarningsSummary,\n               &globalEW, 1, MPI_LONG, MPI_SUM, 0, world);\n    // Write to screen or logfile.\n    if(comm->me == 0) {\n      if(screen) {\n        fprintf(screen,\n                \"### NNP EW SUMMARY ### TS: %10ld EW %10ld EWPERSTEP %10.3e\\n\",\n                update->ntimestep,\n                globalEW,\n                double(globalEW) / showewsum);\n      }\n      if(logfile) {\n        fprintf(logfile,\n                \"### NNP EW SUMMARY ### TS: %10ld EW %10ld EWPERSTEP %10.3e\\n\",\n                update->ntimestep,\n                globalEW,\n                double(globalEW) / showewsum);\n      }\n    }\n    // Reset summary counter.\n    numExtrapolationWarningsSummary = 0;\n  }\n\n  // Stop if maximum number of extrapolation warnings is exceeded.\n  if (numExtrapolationWarningsTotal > maxew) {\n    error->one(FLERR,\"Too many extrapolation warnings\");\n  }\n\n  // Reset internal extrapolation warnings counters.\n  interface.clearExtrapolationWarnings();\n}\n\n// Write atomic charges into n2p2\nvoid PairHDNNP4G::transferCharges()\n{\n    for (int i = 0; i < atom->nlocal; ++i) {\n        interface.addCharge(i,atom->q[i]);\n    }\n}\n\n// forceLambda function\ndouble PairHDNNP4G::forceLambda_f(const gsl_vector *v)\n{\n    int i,j,jmap;\n    int *type = atom->type;\n    int nlocal = atom->nlocal;\n    int *tag = atom->tag;\n    int nall = atom->natoms;\n\n    double **x = atom->x;\n    double E_real, E_recip, E_self;\n    double E_lambda,E_lambda_loc;\n    double iiterm,ijterm;\n\n    double eta;\n\n    if (periodic) eta = 1 / kspacehdnnp->g_ewald; // LAMMPS truncation\n\n    E_lambda = 0.0;\n    E_lambda_loc = 0.0;\n    if (periodic)\n    {\n        double sqrt2eta = (sqrt(2.0) * eta);\n        E_recip = 0.0;\n        E_real = 0.0;\n        E_self = 0.0;\n        for (i = 0; i < nlocal; i++) // over local atoms\n        {\n            double const lambda_i = gsl_vector_get(v, tag[i]-1);\n            double lambda_i2 = lambda_i * lambda_i;\n\n            // Self interactionsterm\n            E_self += lambda_i2 * (1 / (2.0 * sigmaSqrtPi[type[i]-1]) - 1 / (sqrt(2.0 * M_PI) * eta));\n            E_lambda_loc += dEdQ[i] * lambda_i + 0.5 * hardness[type[i]-1] * lambda_i2;\n\n            // Real space\n            // TODO: we loop over the full neighbor list, could this be optimized ?\n            for (int jj = 0; jj < list->numneigh[i]; ++jj) {\n                j = list->firstneigh[i][jj];\n                j &= NEIGHMASK;\n                double const lambda_j = gsl_vector_get(v, tag[j]-1);\n                //jmap = atom->map(tag[j]);\n                //double const dx = x[i][0] - x[j][0];\n                //double const dy = x[i][1] - x[j][1];\n                //double const dz = x[i][2] - x[j][2];\n                //double const rij = sqrt(SQR(dx) + SQR(dy) + SQR(dz)) * cflength;\n                //double erfcRij = (erfc(rij / sqrt2eta) - erfc(rij / gammaSqrt2[type[i]-1][type[jmap]-1])) / rij;\n                //double real = 0.5 * lambda_i * lambda_j * erfcRij;\n                double real = 0.5 * lambda_i * lambda_j * erfc_val[i][jj];\n                E_real += real;\n            }\n        }\n        // Reciprocal space\n        for (int k = 0; k < kspacehdnnp->kcount; k++) // over k-space\n        {\n            double sf_real_loc = 0.0;\n            double sf_im_loc = 0.0;\n            kspacehdnnp->sf_real[k] = 0.0;\n            kspacehdnnp->sf_im[k] = 0.0;\n            for (i = 0; i < nlocal; i++) //TODO: check\n            {\n                double const lambda_i = gsl_vector_get(v,tag[i]-1);\n                sf_real_loc += lambda_i * kspacehdnnp->sfexp_rl[k][i];\n                sf_im_loc += lambda_i * kspacehdnnp->sfexp_im[k][i];\n            }\n            MPI_Allreduce(&(sf_real_loc),&(kspacehdnnp->sf_real[k]),1,MPI_DOUBLE,MPI_SUM,world);\n            MPI_Allreduce(&(sf_im_loc),&(kspacehdnnp->sf_im[k]),1,MPI_DOUBLE,MPI_SUM,world);\n            E_recip += kspacehdnnp->kcoeff[k] * (pow(kspacehdnnp->sf_real[k],2) + pow(kspacehdnnp->sf_im[k],2));\n        }\n        E_lambda_loc += E_real + E_self;\n    }else\n    {\n        // first loop over local atoms\n        for (i = 0; i < nlocal; i++) {\n            double const lambda_i = gsl_vector_get(v,i);\n            // add i terms here\n            iiterm = lambda_i * lambda_i / (2.0 * sigmaSqrtPi[type[i]-1]);\n            E_lambda += iiterm + dEdQ[i]*lambda_i + 0.5*hardness[type[i]-1]*lambda_i*lambda_i;\n            // second loop over 'all' atoms\n            for (j = i + 1; j < nall; j++) {\n                double const lambda_j = gsl_vector_get(v, j);\n                double const dx = x[j][0] - x[i][0];\n                double const dy = x[j][1] - x[i][1];\n                double const dz = x[j][2] - x[i][2];\n                double const rij = sqrt(SQR(dx) + SQR(dy) + SQR(dz)) * cflength;\n                ijterm = lambda_i * lambda_j * (erf(rij / gammaSqrt2[type[i]-1][type[j]-1]) / rij);\n                E_lambda += ijterm;\n            }\n        }\n    }\n\n    MPI_Allreduce(&E_lambda_loc,&E_lambda,1,MPI_DOUBLE,MPI_SUM,world); // MPI_SUM of local QEQ contributions\n    E_lambda += E_recip; // adding already all-reduced reciprocal part\n\n    return E_lambda;\n}\n\n// forceLambda function - wrapper\ndouble PairHDNNP4G::forceLambda_f_wrap(const gsl_vector *v, void *params)\n{\n    return static_cast<PairHDNNP4G*>(params)->forceLambda_f(v);\n}\n\n// forceLambda gradient\nvoid PairHDNNP4G::forceLambda_df(const gsl_vector *v, gsl_vector *dEdLambda)\n{\n    int i,j,jmap;\n    int nlocal = atom->nlocal;\n    int nall = atom->natoms;\n    int *tag = atom->tag;\n    int *type = atom->type;\n\n    double **x = atom->x;\n    double val;\n    double grad;\n    double grad_sum,grad_sum_loc,grad_i;\n    double local_sum;\n\n    double eta;\n\n    if (periodic) eta = 1 / kspacehdnnp->g_ewald; // LAMMPS truncation\n\n    grad_sum = 0.0;\n    grad_sum_loc = 0.0;\n    if (periodic)\n    {\n        double sqrt2eta = (sqrt(2.0) * eta);\n        for (i = 0; i < nlocal; i++) // over local atoms\n        {\n            double const lambda_i = gsl_vector_get(v,tag[i]-1);\n\n            // Reciprocal space\n            double ksum = 0.0;\n            for (int k = 0; k < kspacehdnnp->kcount; k++) // over k-space\n            {\n                ksum += 2.0 * kspacehdnnp->kcoeff[k] *\n                        (kspacehdnnp->sf_real[k] * kspacehdnnp->sfexp_rl[k][i] +\n                         kspacehdnnp->sf_im[k] * kspacehdnnp->sfexp_im[k][i]);\n            }\n\n            // Real space\n            double jsum = 0.0;\n            for (int jj = 0; jj < list->numneigh[i]; ++jj) {\n                j = list->firstneigh[i][jj];\n                j &= NEIGHMASK;\n                double const lambda_j = gsl_vector_get(v, tag[j]-1);\n                //jmap = atom->map(tag[j]);\n                //double const dx = x[i][0] - x[j][0];\n                //double const dy = x[i][1] - x[j][1];\n                //double const dz = x[i][2] - x[j][2];\n                //double const rij = sqrt(SQR(dx) + SQR(dy) + SQR(dz)) * cflength;\n                //double erfcRij = (erfc(rij / sqrt2eta) - erfc(rij / gammaSqrt2[type[i]-1][type[jmap]-1]));\n                //jsum += lambda_j * erfcRij / rij;\n                jsum += lambda_j * erfc_val[i][jj];\n            }\n            grad = jsum + ksum + dEdQ[i] + hardness[type[i]-1]*lambda_i +\n                   lambda_i * (1/(sigmaSqrtPi[type[i]-1])- 2/(eta * sqrt(2.0 * M_PI)));\n            grad_sum_loc += grad;\n            dEdLambda_loc[tag[i]-1] = grad; // fill gradient array based on tags instead of local IDs\n        }\n    }else\n    {\n        // first loop over local atoms\n        for (i = 0; i < nlocal; i++) { // TODO: indices\n            double const lambda_i = gsl_vector_get(v,i);\n            local_sum = 0.0;\n            // second loop over 'all' atoms\n            for (j = 0; j < nall; j++) {\n                if (j != i) {\n                    double const lambda_j = gsl_vector_get(v, j);\n                    double const dx = x[j][0] - x[i][0];\n                    double const dy = x[j][1] - x[i][1];\n                    double const dz = x[j][2] - x[i][2];\n                    double const rij = sqrt(SQR(dx) + SQR(dy) + SQR(dz)) * cflength;\n                    local_sum += lambda_j * erf(rij / gammaSqrt2[type[i]-1][type[j]-1]) / rij;\n                }\n            }\n            val = dEdQ[i] + hardness[type[i]-1]*lambda_i +\n                  lambda_i/(sigmaSqrtPi[type[i]-1]) + local_sum;\n            grad_sum = grad_sum + val;\n            gsl_vector_set(dEdLambda,i,val);\n        }\n    }\n\n    MPI_Allreduce(dEdLambda_loc,dEdLambda_all,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n    MPI_Allreduce(&grad_sum_loc,&grad_sum,1,MPI_DOUBLE,MPI_SUM,world);\n\n    // Gradient projection //TODO: communication ?\n    for (i = 0; i < nall; i++){\n        grad_i = dEdLambda_all[i];\n        gsl_vector_set(dEdLambda,i,grad_i - (grad_sum)/nall);\n    }\n\n}\n\n// forceLambda gradient - wrapper\nvoid PairHDNNP4G::forceLambda_df_wrap(const gsl_vector *v, void *params, gsl_vector *df)\n{\n    static_cast<PairHDNNP4G*>(params)->forceLambda_df(v, df);\n}\n\n// forceLambda f*df\nvoid PairHDNNP4G::forceLambda_fdf(const gsl_vector *v, double *f, gsl_vector *df)\n{\n    *f = forceLambda_f(v);\n    forceLambda_df(v, df);\n}\n\n// forceLambda f*df - wrapper\nvoid PairHDNNP4G::forceLambda_fdf_wrap(const gsl_vector *v, void *params, double *f, gsl_vector *df)\n{\n    static_cast<PairHDNNP4G*>(params)->forceLambda_fdf(v, f, df);\n}\n\n// Calculate forcelambda vector $\\lambda_i$ that is required for optimized force calculation\nvoid PairHDNNP4G::calculateForceLambda()\n{\n    size_t iter = 0;\n    int i,j;\n    int nsize,status;\n    int nlocal;\n\n    double psum_it;\n    double gradsum;\n    double lambda_i;\n\n    nsize = atom->natoms; // total number of atoms\n    nlocal = atom->nlocal; // total number of atoms\n\n    gsl_vector *x; // charge vector in our case\n\n    forceLambda_minimizer.n = nsize;\n    forceLambda_minimizer.f = &forceLambda_f_wrap;\n    forceLambda_minimizer.df = &forceLambda_df_wrap;\n    forceLambda_minimizer.fdf = &forceLambda_fdf_wrap;\n    forceLambda_minimizer.params = this;\n\n    for (int i =0; i < atom->natoms; i++) {\n        dEdLambda_all[i] = 0.0;\n        dEdLambda_loc[i] = 0.0;\n        forceLambda_loc[i] = 0.0;\n        forceLambda_all[i] = 0.0;\n    }\n\n    // Communicate forceLambda\n    for (int i = 0; i < atom->nlocal; i++){\n        forceLambda_loc[atom->tag[i]-1] = forceLambda[i];\n    }\n    MPI_Allreduce(forceLambda_loc,forceLambda_all,atom->natoms,MPI_DOUBLE,MPI_SUM,world);\n\n\n    // TODO : check\n    x = gsl_vector_alloc(nsize);\n    for (i = 0; i < nsize; i++) {\n        gsl_vector_set(x,i,forceLambda_all[i]);\n    }\n\n    T = gsl_multimin_fdfminimizer_vector_bfgs2;\n    s = gsl_multimin_fdfminimizer_alloc(T, nsize);\n\n    gsl_multimin_fdfminimizer_set(s, &forceLambda_minimizer, x, step, min_tol); // TODO would tol = 0 be expensive ??\n    do\n    {\n        iter++;\n        psum_it = 0.0;\n        status = gsl_multimin_fdfminimizer_iterate(s);\n\n        // Projection\n        for(i = 0; i < nsize; i++) {\n            psum_it = psum_it + gsl_vector_get(s->x, i);\n        }\n        for(i = 0; i < nsize; i++) {\n            lambda_i = gsl_vector_get(s->x,i);\n            gsl_vector_set(s->x,i, lambda_i - psum_it/nsize); // projection\n        }\n\n        status = gsl_multimin_test_gradient(s->gradient, grad_tol);\n\n        //if (status == GSL_SUCCESS) printf (\"Minimum forceLambda is found at iteration: %zu\\n\",iter);\n\n    }\n    while (status == GSL_CONTINUE && iter < maxit);\n\n    // Read charges before deallocating x\n    for (i = 0; i < nlocal; i++) {\n        forceLambda[i] = gsl_vector_get(s->x,atom->tag[i]-1);\n    }\n\n    gsl_multimin_fdfminimizer_free(s);\n    gsl_vector_free(x);\n}\n\nvoid PairHDNNP4G::calculate_kspace_terms()\n{\n    int i,j,k;\n    int nlocal = atom->nlocal;\n    int nall = atom->natoms;\n\n    double **x = atom->x;\n    double dx,dy,dz;\n    double kdum_cos,kdum_sinx,kdum_siny,kdum_sinz;\n\n    // This term is used in dEdQ calculation and can be calculated beforehand\n    for (k = 0; k < kspacehdnnp->kcount; k++)\n    {\n        kcoeff_sum += 2 * kspacehdnnp->kcoeff[k];\n    }\n\n    for (i = 0; i < nlocal; i++)\n    {\n        for (j = 0; j < nall; j++)\n        {\n            kdum_cos = 0.0;\n            kdum_sinx = 0.0;\n            kdum_siny = 0.0;\n            kdum_sinz = 0.0;\n\n            /*dx = x[i][0] - xx[j];\n            dy = x[i][1] - xy[j];\n            dz = x[i][2] - xz[j];\n\n            for (int k = 0; k < kspacehdnnp->kcount; k++) {\n                double kx = kspacehdnnp->kxvecs[k] * kspacehdnnp->unitk[0];\n                double ky = kspacehdnnp->kyvecs[k] * kspacehdnnp->unitk[1];\n                double kz = kspacehdnnp->kzvecs[k] * kspacehdnnp->unitk[2];\n                double kdr = (dx * kx + dy * ky + dz * kz) * cflength;\n\n                    // Cos term\n                    if (dx != 0.0) kdum_cos += 2.0 * kspacehdnnp->kcoeff[k] * cos(kdr);\n\n                    // Sin terms\n                    double sinkdr = sin(kdr);\n                    kdum_sinx -= 2.0 * kspacehdnnp->kcoeff[k] * sinkdr * kx;\n                    kdum_siny -= 2.0 * kspacehdnnp->kcoeff[k] * sinkdr * ky;\n                    kdum_sinz -= 2.0 * kspacehdnnp->kcoeff[k] * sinkdr * kz;\n            }\n            kcos[i][j] = kdum_cos;\n            ksinx[i][j] = kdum_sinx;\n            ksiny[i][j] = kdum_siny;\n            ksinz[i][j] = kdum_sinz;*/\n        }\n    }\n}\n\n// Calculate $dEelec/dQ_i$ and add one part of the $\\partial Eelec/\\partial Q_i$ contribution to the total force vector\nvoid PairHDNNP4G::calculateElecDerivatives(double *dEelecdQ, double **f)\n{\n    int i,j,jmap;\n    int nlocal = atom->nlocal;\n    int nall = atom->natoms;\n    int *tag = atom->tag;\n    int *type = atom->type;\n\n    double **x = atom->x;\n    double *q = atom->q;\n    double qi,qj;\n    double dx,dy,dz;\n    double rij,rij2,erfrij;\n    double gams2;\n    double sij,tij;\n    double fsrij,dfsrij; // corrections due to screening\n\n    double eta;\n\n    if (periodic) eta = 1 / kspacehdnnp->g_ewald; // LAMMPS truncation (RuNNer truncation has been removed)\n\n    for (i = 0; i < nlocal; i++)\n    {\n        qi = q[i];\n        if (periodic)\n        {\n            double sqrt2eta = (sqrt(2.0) * eta);\n            double ksum = 0.0;\n            for (j = 0; j < nall; j++)\n            {\n                double Aij = 0.0;\n                qj = qall[j];\n                dx = x[i][0] - xx[j];\n                dy = x[i][1] - xy[j];\n                dz = x[i][2] - xz[j];\n                // Reciprocal part\n                for (int k = 0; k < kspacehdnnp->kcount; k++) {\n                    double kdr = (dx * kspacehdnnp->kxvecs[k] * kspacehdnnp->unitk[0] +\n                                  dy * kspacehdnnp->kyvecs[k] * kspacehdnnp->unitk[1] +\n                                  dz * kspacehdnnp->kzvecs[k] * kspacehdnnp->unitk[2]) * cflength;\n                    if (dx != 0.0) Aij += 2.0 * kspacehdnnp->kcoeff[k] * cos(kdr);\n                }\n                dEelecdQ[i] += qj * Aij;\n                //dEelecdQ[i] += qj * kcos[i][j];\n            }\n            // Add remaining k-space contributions here\n            dEelecdQ[i] += qi * (kcoeff_sum - 2 / (sqrt2eta * sqrt(M_PI)));\n\n            // Real space\n            for (int jj = 0; jj < list->numneigh[i]; ++jj) {\n                j = list->firstneigh[i][jj];\n                j &= NEIGHMASK;\n                jmap = atom->map(tag[j]);\n                qj = qall[tag[j]-1];\n                dx = x[i][0] - x[j][0];\n                dy = x[i][1] - x[j][1];\n                dz = x[i][2] - x[j][2];\n                rij2 = SQR(dx) + SQR(dy) + SQR(dz);\n                rij = sqrt(rij2) * cflength;\n\n                gams2 = gammaSqrt2[type[i]-1][type[jmap]-1];\n\n                //double Aij = (erfc(rij / sqrt2eta) - erfc(rij / gams2)) / rij;\n                double Aij = erfc_val[i][jj];\n\n                dEelecdQ[i] += qj * Aij; // Add Aij contribution regardless of screening\n\n                if (rij < screening_info[2])\n                {\n                    erfrij = erf(rij / gams2);\n                    fsrij = screening_f(rij);\n                    dfsrij = screening_df(rij);\n\n                    sij = erfrij * (fsrij - 1) / rij;\n\n                    tij = (2 / (sqrt(M_PI)*gams2) * exp(- pow(rij / gams2,2)) *\n                           (fsrij - 1) + erfrij*dfsrij - erfrij*(fsrij-1)/rij) / rij2;\n\n                    dEelecdQ[i] += qj * (sij); // Add sij contributions if inside screening cutoff\n\n                    f[i][0] -= 0.5 * (qi * qj * dx * tij) / cfenergy;\n                    f[i][1] -= 0.5 * (qi * qj * dy * tij) / cfenergy;\n                    f[i][2] -= 0.5 * (qi * qj * dz * tij) / cfenergy;\n\n                    f[j][0] += 0.5 * (qi * qj * dx * tij) / cfenergy;\n                    f[j][1] += 0.5 * (qi * qj * dy * tij) / cfenergy;\n                    f[j][2] += 0.5 * (qi * qj * dz * tij) / cfenergy;\n                }\n            }\n        }else\n        {\n            for (j = 0; j < nall; j++)\n            {\n                // Retrieve position, type and charge from global arrays\n                //TODO check\n                dx = x[i][0] - xx[j];\n                dy = x[i][1] - xy[j];\n                dz = x[i][2] - xz[j];\n                qj = qall[j];\n                rij2 = SQR(dx) + SQR(dy) + SQR(dz);\n                rij = sqrt(rij2) * cflength;\n\n                if (rij != 0.0)\n                {\n                    gams2 = gammaSqrt2[type[i]-1][type_all[j]-1];\n\n                    erfrij = erf(rij / gams2);\n                    fsrij = screening_f(rij);\n                    dfsrij = screening_df(rij);\n\n                    sij = erfrij * (fsrij - 1) / rij;\n                    tij = (2 / (sqrt(M_PI)*gams2) * exp(- pow(rij / gams2,2)) *\n                           (fsrij - 1) + erfrij*dfsrij - erfrij*(fsrij-1)/rij) / rij2;\n\n                    dEelecdQ[i] += qj * ((erfrij/rij) + sij);\n                    f[i][0] -= qi * qj * dx * tij;\n                    f[i][1] -= qi * qj * dy * tij;\n                    f[i][2] -= qi * qj * dz * tij;\n                }\n            }\n        }\n    }\n    kcoeff_sum = 0.0; // re-initialize to 0.0 here\n}\n\n// Calculate electrostatic forces and add to atomic force vectors\n// TODO: clean-up & non-periodic\nvoid PairHDNNP4G::calculateElecForce(double **f)\n{\n\n    int i,j,k;\n    int nlocal = atom->nlocal;\n    int nall = atom->natoms;\n    int *tag = atom->tag;\n    int *type = atom->type;\n\n    double rij;\n    double qi,qj,qk;\n    double *q = atom->q;\n    double **x = atom->x;\n    double delr,gams2;\n    double dx,dy,dz;\n\n    double eta;\n\n    if (periodic) eta = 1 / kspacehdnnp->g_ewald; // LAMMPS truncation\n\n    // lambda_i * dChidr contributions are added into the force vectors in n2p2\n    interface.getForcesChi(forceLambda_all, atom->f);\n\n    for (i = 0; i < nlocal; i++) {\n        qi = q[i];\n        double lambdai = forceLambda[i];\n        if (periodic) {\n            double sqrt2eta = (sqrt(2.0) * eta);\n            double dAdrx = 0.0;\n            double dAdry = 0.0;\n            double dAdrz = 0.0;\n\n            // Real space\n            for (int jj = 0; jj < list->numneigh[i]; ++jj) {\n                k = list->firstneigh[i][jj];\n                k &= NEIGHMASK;\n                int jmap = atom->map(tag[k]);\n                qk = qall[tag[k]-1];\n                double lambdak = forceLambda_all[tag[k]-1];\n                dx = x[i][0] - x[k][0];\n                dy = x[i][1] - x[k][1];\n                dz = x[i][2] - x[k][2];\n                double rij2 = SQR(dx) + SQR(dy) + SQR(dz);\n                rij = sqrt(rij2) * cflength;\n\n                if (rij < kspacehdnnp->ewald_real_cutoff) {\n                    gams2 = gammaSqrt2[type[i]- 1][type[jmap]-1];\n                    //delr = (2 / sqrt(M_PI) * (-exp(-pow(rij / sqrt2eta, 2))\n                    //                          / sqrt2eta + exp(-pow(rij / gams2, 2)) / gams2)\n                    //        - 1 / rij * (erfc(rij / sqrt2eta) - erfc(rij / gams2))) / rij2;\n                    delr = (2 / sqrt(M_PI) * (-exp(-pow(rij / sqrt2eta, 2))\n                                              / sqrt2eta + exp(-pow(rij / gams2, 2)) / gams2)\n                            - erfc_val[i][jj]) / rij2;\n                    dAdrx = dx * delr;\n                    dAdry = dy * delr;\n                    dAdrz = dz * delr;\n\n                    // Contributions to the local atom i\n                    f[i][0] -= 0.5 * (lambdai * qk + lambdak * qi) * dAdrx / cfenergy;\n                    f[i][1] -= 0.5 * (lambdai * qk + lambdak * qi) * dAdry / cfenergy;\n                    f[i][2] -= 0.5 * (lambdai * qk + lambdak * qi) * dAdrz / cfenergy;\n\n                    // Contributions to the neighbors of the local atom i\n                    f[k][0] += 0.5 * (lambdai * qk + lambdak * qi) * dAdrx / cfenergy;\n                    f[k][1] += 0.5 * (lambdai * qk + lambdak * qi) * dAdry / cfenergy;\n                    f[k][2] += 0.5 * (lambdai * qk + lambdak * qi) * dAdrz / cfenergy;\n\n                    // Contributions to the local atom i (pEelecpr)\n                    f[i][0] -= (0.5 * qk * dAdrx * qi) / cfenergy;\n                    f[i][1] -= (0.5 * qk * dAdry * qi) / cfenergy;\n                    f[i][2] -= (0.5 * qk * dAdrz * qi) / cfenergy;\n\n                    f[k][0] += (0.5 * qk * dAdrx * qi) / cfenergy;\n                    f[k][1] += (0.5 * qk * dAdry * qi) / cfenergy;\n                    f[k][2] += (0.5 * qk * dAdrz * qi) / cfenergy;\n                }\n            }\n            // Reciprocal space\n            for (j = 0; j < nall; j++){\n                qj = qall[j];\n                double lambdaj = forceLambda_all[j];\n                dx = x[i][0] - xx[j];\n                dy = x[i][1] - xy[j];\n                dz = x[i][2] - xz[j];\n                double ksx = 0;\n                double ksy = 0;\n                double ksz = 0;\n                for (int kk = 0; kk < kspacehdnnp->kcount; kk++) {\n                    double kx = kspacehdnnp->kxvecs[kk] * kspacehdnnp->unitk[0];\n                    double ky = kspacehdnnp->kyvecs[kk] * kspacehdnnp->unitk[1];\n                    double kz = kspacehdnnp->kzvecs[kk] * kspacehdnnp->unitk[2];\n                    double kdr = (dx * kx + dy * ky + dz * kz) * cflength;\n                    ksx -= 2.0 * kspacehdnnp->kcoeff[kk] * sin(kdr) * kx;\n                    ksy -= 2.0 * kspacehdnnp->kcoeff[kk] * sin(kdr) * ky;\n                    ksz -= 2.0 * kspacehdnnp->kcoeff[kk] * sin(kdr) * kz;\n                }\n                dAdrx = ksx;\n                dAdry = ksy;\n                dAdrz = ksz;\n                //dAdrx = ksinx[i][j];\n                //dAdry = ksiny[i][j];\n                //dAdrz = ksinz[i][j];\n\n                // Contributions to the local atom i\n                f[i][0] -= (lambdai * qj + lambdaj * qi) * dAdrx * (cflength/cfenergy);\n                f[i][1] -= (lambdai * qj + lambdaj * qi) * dAdry * (cflength/cfenergy);\n                f[i][2] -= (lambdai * qj + lambdaj * qi) * dAdrz * (cflength/cfenergy);\n\n                // pEelecpr\n                f[i][0] -= (qj * dAdrx * qi) * (cflength/cfenergy);\n                f[i][1] -= (qj * dAdry * qi) * (cflength/cfenergy);\n                f[i][2] -= (qj * dAdrz * qi) * (cflength/cfenergy);\n\n                // Contributions to the neighbors of the local atom i\n                /*f[k][0] += (lambdai * qj + lambdaj * qi) * dAdrx * (cflength/cfenergy);\n                f[k][1] += (lambdai * qj + lambdaj * qi) * dAdry * (cflength/cfenergy);\n                f[k][2] += (lambdai * qj + lambdaj * qi) * dAdrz * (cflength/cfenergy);*/\n\n                /*f[k][0] += (qj * dAdrx * qi) * (cflength/cfenergy);\n                f[k][1] += (qj * dAdry * qi) * (cflength/cfenergy);\n                f[k][2] += (qj * dAdrz * qi) * (cflength/cfenergy);*/\n            }\n        } else {\n            // Over all atoms in the system\n            for (j = 0; j < nall; j++) {\n                double jt0 = 0;\n                double jt1 = 0;\n                double jt2 = 0;\n                //qj = q[j];\n                qj = qall[j];\n                if (i == j) {\n                    // We have to loop over all atoms once again to calculate dAdrQ terms\n                    for (k = 0; k < nall; k++) {\n                        //qk = q[k];\n                        qk = qall[k];\n                        //dx = x[i][0] - x[k][0];\n                        dx = x[i][0] - xx[k];\n                        //dy = x[i][1] - x[k][1];\n                        dy = x[i][1] - xy[k];\n                        //dz = x[i][2] - x[k][2];\n                        dz = x[i][2] - xz[k];\n                        double rij2 = SQR(dx) + SQR(dy) + SQR(dz);\n                        rij = sqrt(rij2) * cflength;\n\n                        if (rij != 0.0)\n                        {\n                            //gams2 = gammaSqrt2[type[i]-1][type[k]-1];\n                            gams2 = gammaSqrt2[type[i]-1][type_all[k]-1];\n                            delr = (2 / (sqrt(M_PI) * gams2) * exp(-pow(rij / gams2, 2)) - erf(rij / gams2) / rij);\n\n                            jt0 += (dx / rij2) * delr * qk;\n                            jt1 += (dy / rij2) * delr * qk;\n                            jt2 += (dz / rij2) * delr * qk;\n                        }\n                    }\n                } else {\n                    //TODO\n                    //dx = x[i][0] - x[j][0];\n                    dx = x[i][0] - xx[j];\n                    //dy = x[i][1] - x[j][1];\n                    dy = x[i][1] - xy[j];\n                    //dz = x[i][2] - x[j][2];\n                    dz = x[i][2] - xz[j];\n                    double rij2 = SQR(dx) + SQR(dy) + SQR(dz);\n                    rij = sqrt(rij2) * cflength;\n\n                    //gams2 = gammaSqrt2[type[i]-1][type[j]-1];\n                    gams2 = gammaSqrt2[type[i]-1][type_all[j]-1];\n                    delr = (2 / (sqrt(M_PI) * gams2) * exp(-pow(rij / gams2, 2)) - erf(rij / gams2) / rij);\n\n                    jt0 = (dx / rij2) * delr * qi;\n                    jt1 = (dy / rij2) * delr * qi;\n                    jt2 = (dz / rij2) * delr * qi;\n                }\n                f[i][0] -= (forceLambda_all[j] * (jt0) + 0.5 * qj * jt0) / cfenergy;\n                f[i][1] -= (forceLambda_all[j] * (jt1) + 0.5 * qj * jt1) / cfenergy;\n                f[i][2] -= (forceLambda_all[j] * (jt2) + 0.5 * qj * jt2) / cfenergy;\n            }\n        }\n    }\n}\n\n// Calculate screening function\n// TODO : add other function types\ndouble PairHDNNP4G::screening_f(double r)\n{\n    double x;\n\n    if (r >= screening_info[2]) return 1.0;\n    else if (r <= screening_info[1]) return 0.0;\n    else\n    {\n        x = (r-screening_info[1])*screening_info[3];\n        return 1.0 - 0.5*(cos(M_PI*x)+1);\n    }\n}\n\n// Calculate derivative of the screening function\n// TODO : add other function types\ndouble PairHDNNP4G::screening_df(double r) {\n\n    double x;\n\n    if (r >= screening_info[2] || r <= screening_info[1]) return 0.0;\n    else {\n        x = (r - screening_info[1]) * screening_info[3];\n        return -screening_info[3] * (-M_PI_2 * sin(M_PI * x));\n    }\n}\n\n// Check for periodicity\nvoid PairHDNNP4G::isPeriodic()\n{\n    if (domain->nonperiodic == 0) periodic = true;\n    else                          periodic = false;\n}\n\n\n\n\n\n\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/pair_hdnnp_4g.h",
    "content": "/* -*- c++ -*- ----------------------------------------------------------\n   LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator\n   https://www.lammps.org/ Sandia National Laboratories\n   LAMMPS development team: developers@lammps.org\n\n   Copyright (2003) Sandia Corporation.  Under the terms of Contract\n   DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains\n   certain rights in this software.  This software is distributed under\n   the GNU General Public License.\n\n   This file initially came from n2p2 (https://github.com/CompPhysVienna/n2p2)\n   Copyright (2018) Andreas Singraber (University of Vienna)\n\n   See the README file in the top-level LAMMPS directory.\n------------------------------------------------------------------------- */\n\n/* ----------------------------------------------------------------------\n   Contributing authors: Emir Kocer\n                         Andreas Singraber\n------------------------------------------------------------------------- */\n\n#ifdef PAIR_CLASS\n// clang-format off\nPairStyle(hdnnp/4g,PairHDNNP4G)\n// clang-format on\n#else\n\n#ifndef LMP_PAIR_HDNNP4G_H\n#define LMP_PAIR_HDNNP4G_H\n\n#include \"pair.h\"\n#include \"InterfaceLammps.h\"\n#include <gsl/gsl_multimin.h>\n\nnamespace LAMMPS_NS {\n\nclass PairHDNNP4G : public Pair {\n    friend class FixHDNNP;\n    friend class KSpaceHDNNP;\n public:\n\n  PairHDNNP4G(class LAMMPS *);\n  virtual ~PairHDNNP4G();\n  virtual void compute(int, int);\n  virtual void settings(int, char **);\n  virtual void coeff(int, char **);\n  virtual void init_style();\n  virtual double init_one(int, int);\n  void init_list(int,class NeighList *);\n  virtual void write_restart(FILE *);\n  virtual void read_restart(FILE *);\n  virtual void write_restart_settings(FILE *);\n  virtual void read_restart_settings(FILE *);\n\n\nprotected:\n\n    class KSpaceHDNNP *kspacehdnnp; // interface to HDNNP kspace_style\n\n    int me,nprocs;\n    bool periodic;\n    bool showew;\n    bool resetew;\n    int showewsum;\n    int maxew;\n    long numExtrapolationWarningsTotal;\n    long numExtrapolationWarningsSummary;\n    double cflength;\n    double cfenergy;\n    double maxCutoffRadius;\n    char* directory;\n    char* emap;\n    class NeighList *list;\n\n    nnp::InterfaceLammps interface;\n\n    double *chi,*hardness,*sigmaSqrtPi,**gammaSqrt2; // QEq arrays\n    double *dEdQ,*forceLambda;\n    double grad_tol,min_tol,step; // user-defined minimization parameters\n    int maxit;\n    int minim_init_style; // initialization style for the minimization algorithm, 0: from zero or 1: from the final step\n\n    virtual void allocate();\n    void transferNeighborList();\n    void isPeriodic();\n\n    void transferCharges();\n    void handleExtrapolationWarnings();\n\n    void deallocateQEq();\n\n    // Minimization Setup for Force Lambda\n    const gsl_multimin_fdfminimizer_type *T;\n    gsl_multimin_fdfminimizer *s;\n\n    gsl_multimin_function_fdf forceLambda_minimizer;\n\n    double forceLambda_f(const gsl_vector*);\n    void forceLambda_df(const gsl_vector*, gsl_vector*);\n    void forceLambda_fdf(const gsl_vector*, double*, gsl_vector*);\n    static double forceLambda_f_wrap(const gsl_vector*, void*);\n    static void forceLambda_df_wrap(const gsl_vector*, void*, gsl_vector*);\n    static void forceLambda_fdf_wrap(const gsl_vector*, void*, double*, gsl_vector*);\n\n    double E_elec;\n    double kcoeff_sum; // used in dEdQ calculation\n\n    int nmax;\n\n    int *type_all,*type_loc;\n    double *dEdLambda_loc,*dEdLambda_all;\n    double *qall_loc,*qall;\n    double *xx,*xy,*xz; // global positions\n    double *xx_loc,*xy_loc,*xz_loc; // sparse local positions\n    double *forceLambda_loc,*forceLambda_all;\n\n    double **erfc_val;\n    double **kcos,**ksinx,**ksiny,**ksinz;\n\n    void calculateForceLambda();\n    void calculateElecDerivatives(double*,double**);\n    void calculateElecForce(double**);\n    void calculate_kspace_terms();\n\n\n    // Screening\n    double *screening_info;\n    double screening_f(double);\n    double screening_df(double);\n\n};\n\n}\n\n#endif\n#endif\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/pair_hdnnp_develop.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include <mpi.h>\n#include <string.h>\n#include \"pair_hdnnp_develop.h\"\n#include \"atom.h\"\n#include \"domain.h\"\n#include \"comm.h\"\n#include \"neighbor.h\"\n#include \"neigh_list.h\"\n#include \"neigh_request.h\"\n#include \"memory.h\"\n#include \"error.h\"\n#include \"force.h\"\n#include \"update.h\"\n#include \"utils.h\"\n\n#include <stdexcept>\n//TODO:  remove later\n#include <iostream>\n\n#include \"InterfaceLammps.h\"    // n2p2 interface header\n\nusing namespace LAMMPS_NS;\nusing namespace std;\n\n\n/* ---------------------------------------------------------------------- */\n\nPairHDNNPDevelop::PairHDNNPDevelop(LAMMPS *lmp) : PairHDNNP(lmp) {}\n\n/* ---------------------------------------------------------------------- */\n\nvoid PairHDNNPDevelop::compute(int eflag, int vflag)\n{\n  if(eflag || vflag) ev_setup(eflag,vflag);\n  else evflag = vflag_fdotr = eflag_global = eflag_atom = 0;\n\n  // Set number of local atoms and add index and element.\n  interface->setLocalAtoms(atom->nlocal, atom->type);\n  // Transfer tags separately. Interface::setLocalTags is overloaded internally\n  // to work with both -DLAMMPS_SMALLBIG (tagint = int) and -DLAMMPS_BIGBIG\n  // (tagint = int64_t)\n  interface->setLocalTags(atom->tag);\n\n\n  // Also set absolute atom positions.\n  interface->setLocalAtomPositions(atom->x);\n\n  // Set Box vectors if system is periodic in all 3 dims.\n  if(domain->nonperiodic == 0)\n  {\n      interface->setBoxVectors(domain->boxlo,\n                               domain->boxhi,\n                               domain->xy,\n                               domain->xz,\n                               domain->yz);\n  }\n\n  updateNeighborlistCutoff();\n\n  // Transfer local neighbor list to NNP interface. Has to be called after\n  // setBoxVectors if structure is periodic!\n  transferNeighborList(maxCutoffRadiusNeighborList);\n\n  // Compute symmetry functions, atomic neural networks and add up energy.\n  interface->processDevelop();\n\n  // Do all stuff related to extrapolation warnings.\n  if(showew == true || showewsum > 0 || maxew >= 0) {\n    handleExtrapolationWarnings();\n  }\n\n  // Calculate forces of local and ghost atoms.\n  interface->getForcesDevelop(atom->f);\n\n  // Transfer charges LAMMPS. Does nothing if nnpType != 4G.\n  interface->getCharges(atom->q);\n\n  // Add energy contribution to total energy.\n  if (eflag_global)\n     ev_tally(0,0,atom->nlocal,1,interface->getEnergy(),0.0,0.0,0.0,0.0,0.0);\n\n  // Add atomic energy if requested (CAUTION: no physical meaning!).\n  if (eflag_atom)\n    for (int i = 0; i < atom->nlocal; ++i)\n      eatom[i] = interface->getAtomicEnergy(i);\n\n  // If virial needed calculate via F dot r.\n  if (vflag_fdotr) virial_fdotr_compute();\n\n    //interface.writeToFile(\"md_run.data\", true);\n}\n\n/* ----------------------------------------------------------------------\n   init specific to this pair style\n------------------------------------------------------------------------- */\n\nvoid PairHDNNPDevelop::init_style()\n{\n  if (comm->nprocs > 1) {\n    throw runtime_error(\"ERROR: Pair style \\\"nnp/develop\\\" can only be used \"\n                        \"with a single MPI task.\\n\");\n  }\n\n  if(domain->dimension != 3)\n    throw runtime_error(\"ERROR: Only 3d systems can be used!\");\n\n  if (!(domain->xperiodic == domain->yperiodic\n     && domain->yperiodic == domain->zperiodic))\n    throw runtime_error(\"ERROR: System must be either aperiodic or periodic \"\n                        \"in all 3 dimmensions!\");\n\n  // Required for charge equilibration scheme.\n  if (atom->map_style == Atom::MAP_NONE)\n      throw runtime_error(\"ERROR: pair style requires atom map yes\");\n\n  PairHDNNP::init_style();\n\n\n  maxCutoffRadiusNeighborList = maxCutoffRadius;\n\n  interface->setGlobalStructureStatus(true);\n}\n\n\ndouble PairHDNNPDevelop::init_one(int i, int j)\n{\n    //cutsq[i][j] = cutsq[j][i] = pow(maxCutoffRadiusNeighborList,2);\n    return maxCutoffRadiusNeighborList;\n}\n\n\nvoid PairHDNNPDevelop::transferNeighborList(double const cutoffRadius)\n{\n  // Transfer neighbor list to NNP.\n  double rc2 = cutoffRadius * cutoffRadius;\n  interface->allocateNeighborlists(list->numneigh);\n#ifdef _OPENMP\n  #pragma omp parallel for\n#endif\n  for (int ii = 0; ii < list->inum; ++ii) {\n    int i = list->ilist[ii];\n    for (int jj = 0; jj < list->numneigh[i]; ++jj) {\n      int j = list->firstneigh[i][jj];\n      j &= NEIGHMASK;\n      double dx = atom->x[i][0] - atom->x[j][0];\n      double dy = atom->x[i][1] - atom->x[j][1];\n      double dz = atom->x[i][2] - atom->x[j][2];\n      double d2 = dx * dx + dy * dy + dz * dz;\n      if (d2 <= rc2) {\n        if (!interface->getGlobalStructureStatus())\n          // atom->tag[j] will be implicitly converted to int64_t internally.\n          interface->addNeighbor(i,j,atom->tag[j],atom->type[j],dx,dy,dz,d2);\n        else\n          interface->addNeighbor(i,j,atom->map(atom->tag[j]),atom->type[j],dx,dy,dz,d2);\n      }\n    }\n  }\n  interface->finalizeNeighborList();\n}\n\n\nvoid PairHDNNPDevelop::updateNeighborlistCutoff()\n{\n    double maxCutoffRadiusOverall = interface->getMaxCutoffRadiusOverall();\n    if(maxCutoffRadiusOverall > maxCutoffRadiusNeighborList)\n    {\n        // TODO: Increase slightly to compensate for rounding errors?\n        utils::logmesg(lmp, fmt::format(\"WARNING: Cutoff too small, need at \"\n                                        \"least: {}\\n\", maxCutoffRadiusOverall));\n\n        //maxCutoffRadiusNeighborList = maxCutoffRadiusOverall;\n        //reinit();\n\n        //mixed_flag = 1;\n        //for (int i = 1; i <= atom->ntypes; i++)\n        //{\n        //    for (int j = i; j <= atom->ntypes; j++)\n        //    {\n        //        if ((i != j) && setflag[i][j]) mixed_flag = 0;\n        //        cutsq[i][j] = cutsq[j][i] = pow(maxCutoffRadiusNeighborList, 2);\n        //    }\n        //}\n        //cutforce = MAX(cutforce, maxCutoffRadiusNeighborList);\n\n        //neighbor->init();\n        //neighbor->build(0);\n    }\n}\n\n\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/pair_hdnnp_develop.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifdef PAIR_CLASS\n// clang-format off\nPairStyle(hdnnp/develop,PairHDNNPDevelop)\n// clang-format on\n#else\n\n#ifndef LMP_PAIR_HDNNP_DEVELOP_H\n#define LMP_PAIR_HDNNP_DEVELOP_H\n\n#include \"pair_hdnnp.h\"\n\nnamespace LAMMPS_NS {\n\nclass PairHDNNPDevelop : public PairHDNNP {\n\n public:\n  PairHDNNPDevelop(class LAMMPS *);\n  void compute(int, int) override;\n  void init_style() override;\n  double init_one(int i, int j) override;\n\n protected:\n  /// Keeps track of the maximum cutoff radius that was used for the neighbor\n  /// list.\n  double maxCutoffRadiusNeighborList;\n\n  void transferNeighborList(double const cutoffRadius);\n  /// Update neighborlist if maxCutoffRadiusNeighborList has changed.\n  void updateNeighborlistCutoff();\n\n};\n\n}    // namespace LAMMPS_NS\n\n#endif\n#endif\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/pair_hdnnp_external.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include <mpi.h>\n#include <cstdlib>\n#include <fstream>\n#include <string.h>\n#include <vector>\n#include \"pair_hdnnp_external.h\"\n#include \"atom.h\"\n#include \"comm.h\"\n#include \"domain.h\"\n#include \"force.h\"\n#include \"memory.h\"\n#include \"error.h\"\n#include \"update.h\"\n#include \"Atom.h\" // nnp::Atom\n#include \"utility.h\" // nnp::\n\nusing namespace LAMMPS_NS;\nusing namespace std;\n\n/* ---------------------------------------------------------------------- */\n\nPairHDNNPExternal::PairHDNNPExternal(LAMMPS *lmp) : Pair(lmp)\n{\n}\n\n/* ----------------------------------------------------------------------\n   check if allocated, since class can be destructed when incomplete\n------------------------------------------------------------------------- */\n\nPairHDNNPExternal::~PairHDNNPExternal()\n{\n}\n\n/* ---------------------------------------------------------------------- */\n\nvoid PairHDNNPExternal::compute(int eflag, int vflag)\n{\n  if(eflag || vflag) ev_setup(eflag,vflag);\n  else evflag = vflag_fdotr = eflag_global = eflag_atom = 0;\n\n  // Clear structure completely.\n  structure.reset();\n\n  // Set simulation box.\n  if (domain->nonperiodic < 2) structure.isPeriodic = true;\n  else structure.isPeriodic = false;\n  if (structure.isPeriodic) structure.isTriclinic = (bool)domain->triclinic;\n  structure.box[0][0] = domain->h[0] * cflength;\n  structure.box[0][1] = 0.0;\n  structure.box[0][2] = 0.0;\n  structure.box[1][0] = domain->h[5] * cflength;\n  structure.box[1][1] = domain->h[1] * cflength;\n  structure.box[1][2] = 0.0;\n  structure.box[2][0] = domain->h[4] * cflength;\n  structure.box[2][1] = domain->h[3] * cflength;\n  structure.box[2][2] = domain->h[2] * cflength;\n\n  // Fill structure with atoms.\n  for (int i = 0; i < atom->nlocal; ++i)\n  {\n    structure.atoms.push_back(nnp::Atom());\n    nnp::Atom& a = structure.atoms.back();\n    a.r[0] = atom->x[i][0] * cflength;\n    a.r[1] = atom->x[i][1] * cflength;\n    a.r[2] = atom->x[i][2] * cflength;\n    a.element = atom->type[i] - 1;\n    structure.numAtoms++;\n  }\n\n  // Write \"input.data\" file to disk.\n  structure.writeToFile(string(directory) + \"input.data\");\n\n  // Run external command and throw away stdout output.\n  string com = \"cd \" + string(directory) + \"; \" + string(command) + \" > external.out\";\n  system(com.c_str());\n\n  // Read back in total potential energy.\n  ifstream f;\n  f.open(string(directory) + \"energy.out\");\n  if (!f.is_open()) error->all(FLERR,\"Could not open energy output file\");\n  string line;\n  double energy = 0.0;\n  getline(f, line); // Ignore first line, RuNNer and n2p2 have header here.\n  while (getline(f, line))\n  {\n    if ((line.size() > 0) && (line.at(0) != '#')) // Ignore n2p2 header.\n    {\n      // 4th columns contains NNP energy.\n      sscanf(line.c_str(), \"%*s %*s %*s %lf\", &energy);\n    }\n  }\n  f.close();\n  energy /= cfenergy;\n\n  // Add energy contribution to total energy.\n  if (eflag_global)\n     ev_tally(0,0,atom->nlocal,1,energy,0.0,0.0,0.0,0.0,0.0);\n\n  // Read back in forces.\n  f.open(string(directory) + \"nnforces.out\");\n  if (!f.is_open()) error->all(FLERR,\"Could not open force output file\");\n  int c = 0;\n  double const cfforce = cfenergy / cflength;\n  getline(f, line); // Ignore first line, RuNNer and n2p2 have header here.\n  while (getline(f, line))\n  {\n    if ((line.size() > 0) && (line.at(0) != '#')) // Ignore n2p2 header.\n    {\n      if (c > atom->nlocal - 1) error->all(FLERR,\"Too many atoms in force file.\");\n      double fx;\n      double fy;\n      double fz;\n      sscanf(line.c_str(), \"%*s %*s %*s %*s %*s %lf %lf %lf\", &fx, &fy, &fz);\n      atom->f[c][0] = fx / cfforce;\n      atom->f[c][1] = fy / cfforce;\n      atom->f[c][2] = fz / cfforce;\n      c++;\n    }\n  }\n\n  f.close();\n\n  // If virial needed calculate via F dot r.\n  // TODO: Pressure calculation is probably wrong anyway, tell user only to use\n  // in NVE, NVT ensemble.\n  if (vflag_fdotr) virial_fdotr_compute();\n}\n\n/* ----------------------------------------------------------------------\n   global settings\n------------------------------------------------------------------------- */\n\nvoid PairHDNNPExternal::settings(int narg, char **arg)\n{\n  int iarg = 0;\n\n  // elements list is mandatory\n  if (narg < 1) error->all(FLERR,\"Illegal pair_style command\");\n\n  // element list, mandatory\n  int len = strlen(arg[iarg]) + 1;\n  elements = new char[len];\n  sprintf(elements, \"%s\", arg[iarg]);\n  iarg++;\n  em.registerElements(elements);\n  vector<FILE*> fp;\n  if (screen) fp.push_back(screen);\n  if (logfile) fp.push_back(logfile);\n  structure.setElementMap(em);\n\n  // default settings\n  len = strlen(\"hdnnp/\") + 1;\n  directory = new char[len];\n  strcpy(directory,\"hdnnp/\");\n  len = strlen(\"nnp-predict 0\") + 1;\n  command = new char[len];\n  strcpy(command,\"nnp-predict 0\");\n  cflength = 1.0;\n  cfenergy = 1.0;\n\n  while(iarg < narg) {\n    // set NNP directory\n    if (strcmp(arg[iarg],\"dir\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      delete[] directory;\n      len = strlen(arg[iarg+1]) + 2;\n      directory = new char[len];\n      sprintf(directory, \"%s/\", arg[iarg+1]);\n      iarg += 2;\n    // set external prediction command\n    } else if (strcmp(arg[iarg],\"command\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      delete[] command;\n      len = strlen(arg[iarg+1]) + 1;\n      command = new char[len];\n      sprintf(command, \"%s\", arg[iarg+1]);\n      iarg += 2;\n    // length unit conversion factor\n    } else if (strcmp(arg[iarg],\"cflength\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      cflength = utils::numeric(FLERR,arg[iarg+1],false,lmp);\n      iarg += 2;\n    // energy unit conversion factor\n    } else if (strcmp(arg[iarg],\"cfenergy\") == 0) {\n      if (iarg+2 > narg)\n        error->all(FLERR,\"Illegal pair_style command\");\n      cfenergy = utils::numeric(FLERR,arg[iarg+1],false,lmp);\n      iarg += 2;\n    } else error->all(FLERR,\"Illegal pair_style command\");\n  }\n\n  for (auto f : fp)\n  {\n      fprintf(f, \"*****************************************\"\n                 \"**************************************\\n\");\n      fprintf(f, \"pair_style hdnnp/external settings:\\n\");\n      fprintf(f, \"-----------------------------------\\n\");\n      fprintf(f, \"elements = %s\\n\", elements);\n      fprintf(f, \"dir      = %s\\n\", directory);\n      fprintf(f, \"command  = %s\\n\", command);\n      fprintf(f, \"cflength = %16.8E\\n\", cflength);\n      fprintf(f, \"cfenergy = %16.8E\\n\", cfenergy);\n      fprintf(f, \"*****************************************\"\n                 \"**************************************\\n\");\n      fprintf(f, \"CAUTION: Explicit element mapping is not available for hdnnp/external,\\n\");\n      fprintf(f, \"         please carefully check whether this map between LAMMPS\\n\");\n      fprintf(f, \"         atom types and element strings is correct:\\n\");\n      fprintf(f, \"---------------------------\\n\");\n      fprintf(f, \"LAMMPS type  |  NNP element\\n\");\n      fprintf(f, \"---------------------------\\n\");\n      int lammpsNtypes = em.size();\n      for (int i = 0; i < lammpsNtypes; ++i)\n      {\n          fprintf(f, \"%11d <-> %2s (%3zu)\\n\",\n                  i, em[i].c_str(), em.atomicNumber(i));\n      }\n      fprintf(f, \"*****************************************\"\n                 \"**************************************\\n\");\n  }\n}\n\n/* ----------------------------------------------------------------------\n   set coeffs for one or more type pairs\n------------------------------------------------------------------------- */\n\nvoid PairHDNNPExternal::coeff(int narg, char **arg)\n{\n  if (!allocated) allocate();\n\n  if (narg != 3) error->all(FLERR,\"Incorrect args for pair coefficients\");\n\n  int ilo,ihi,jlo,jhi;\n\n  utils::bounds(FLERR,arg[0],1,atom->ntypes,ilo,ihi,error);\n  utils::bounds(FLERR,arg[1],1,atom->ntypes,jlo,jhi,error);\n\n  maxCutoffRadius = utils::numeric(FLERR,arg[2],false,lmp);\n\n  // TODO: Check how this flag is set.\n  int count = 0;\n  for(int i=ilo; i<=ihi; i++) {\n    for(int j=MAX(jlo,i); j<=jhi; j++) {\n      setflag[i][j] = 1;\n      count++;\n    }\n  }\n\n  if (count == 0) error->all(FLERR,\"Incorrect args for pair coefficients\");\n}\n\n/* ----------------------------------------------------------------------\n   init specific to this pair style\n------------------------------------------------------------------------- */\n\nvoid PairHDNNPExternal::init_style()\n{\n  if (comm->nprocs > 1)\n  {\n    error->all(FLERR,\"MPI is not supported for this pair_style\");\n  }\n}\n\n/* ----------------------------------------------------------------------\n   init for one type pair i,j and corresponding j,i\n------------------------------------------------------------------------- */\n\ndouble PairHDNNPExternal::init_one(int i, int j)\n{\n  // TODO: Check how this actually works for different cutoffs.\n  return maxCutoffRadius;\n}\n\n/* ----------------------------------------------------------------------\n   allocate all arrays\n------------------------------------------------------------------------- */\n\nvoid PairHDNNPExternal::allocate()\n{\n  allocated = 1;\n  int n = atom->ntypes;\n\n  memory->create(setflag,n+1,n+1,\"pair:setflag\");\n  for (int i = 1; i <= n; i++)\n    for (int j = i; j <= n; j++)\n      setflag[i][j] = 0;\n\n  memory->create(cutsq,n+1,n+1,\"pair:cutsq\");\n}\n"
  },
  {
    "path": "src/interface/LAMMPS/src/ML-HDNNP/pair_hdnnp_external.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifdef PAIR_CLASS\n// clang-format off\nPairStyle(hdnnp/external,PairHDNNPExternal);\n// clang-format on\n#else\n\n#ifndef LMP_PAIR_HDNNP_EXTERNAL_H\n#define LMP_PAIR_HDNNP_EXTERNAL_H\n\n#include \"pair.h\"\n#include \"ElementMap.h\"\n#include \"Structure.h\"\n\nnamespace LAMMPS_NS {\n\nclass PairHDNNPExternal : public Pair {\n\n public:\n  PairHDNNPExternal(class LAMMPS *);\n  ~PairHDNNPExternal() override;\n  void compute(int, int) override;\n  void settings(int, char **) override;\n  void coeff(int, char **) override;\n  void init_style() override;\n  double init_one(int, int) override;\n\n protected:\n  virtual void allocate();\n\n  double cflength;\n  double cfenergy;\n  double maxCutoffRadius;\n  char* directory;\n  char* elements;\n  char* command;\n  nnp::ElementMap em;\n  nnp::Structure structure;\n};\n\n}    // namespace LAMMPS_NS\n\n#endif\n#endif\n"
  },
  {
    "path": "src/interface/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=../..\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# GENERAL SETTINGS\n###############################################################################\n# Default compiler, may be overridden by master makefile or command line.\nCOMP=gnu\n\n# Default build mode, may be overridden by master makefile or command line.\n# Possible modes are \"static\" and \"test\".\nMODE=static\n\n# LAMMPS version string\nLAMMPS_VERSION=stable_29Aug2024\n\n# Include global (project-wide) settings.\ninclude $(PROJECT_DIR)/src/makefile.$(COMP)\n\n\n###############################################################################\n# RULES\n###############################################################################\n.PHONY: all lammps-hdnnp clean-lammps-hdnnp clean-lammps-hdnnp-keep-file\n\nall: lammps-hdnnp\n\nclean: clean-lammps-hdnnp\n\n################\n# lammps-hdnnp #\n################\nLAMMPS_DEBUG := $(filter-out -pedantic-errors,$(PROJECT_DEBUG))\nlammps-hdnnp:\n\tif [ ! -e $(LAMMPS_VERSION).tar.gz ]; then \\\n\t\twget https://github.com/lammps/lammps/archive/$(LAMMPS_VERSION).tar.gz; \\\n\tfi\n\ttar -xzf $(LAMMPS_VERSION).tar.gz && mv lammps-$(LAMMPS_VERSION) lammps-hdnnp\n\tln -s $(PROJECT_DIR)/../../../include/ lammps-hdnnp/lib/hdnnp/includelink\n\tln -s $(PROJECT_DIR)/../../../lib/ lammps-hdnnp/lib/hdnnp/liblink\n\tln -s $(PROJECT_DIR)/../../../lib/Makefile.lammps-extra lammps-hdnnp/lib/hdnnp/Makefile.lammps\n\tcp -r ./LAMMPS/src/ML-HDNNP/* lammps-hdnnp/src/ML-HDNNP/\n\t@sed -i.bak \"s;^CC .*$$;CC      =       $(PROJECT_MPICC);\" lammps-hdnnp/src/MAKE/Makefile.mpi\n\t@sed -i.bak \"s;^CCFLAGS .*$$;CCFLAGS =       $(PROJECT_CFLAGS) $(PROJECT_CFLAGS_MPI) -I$(PROJECT_EIGEN);\" lammps-hdnnp/src/MAKE/Makefile.mpi\n\t@sed -i.bak \"s;^LINK .*$$;LINK =          $(PROJECT_MPICC);\" lammps-hdnnp/src/MAKE/Makefile.mpi\n\t@sed -i.bak \"s;^LINKFLAGS .*$$;LINKFLAGS =     $(PROJECT_CFLAGS) $(PROJECT_CFLAGS_MPI);\" lammps-hdnnp/src/MAKE/Makefile.mpi\n\tif [ \"$(MODE)\" = \"test\" ]; then \\\n\t\tsed -i.bak \"/^CCFLAGS =/   s;$$; $(LAMMPS_DEBUG) $(PROJECT_TEST);\" lammps-hdnnp/src/MAKE/Makefile.mpi; \\\n\t\tsed -i.bak \"/^LINKFLAGS =/ s;$$; $(LAMMPS_DEBUG) $(PROJECT_TEST);\" lammps-hdnnp/src/MAKE/Makefile.mpi; \\\n\tfi\n\t@rm lammps-hdnnp/src/MAKE/Makefile.mpi.bak\n\tcd lammps-hdnnp/src/ && $(MAKE) yes-ml-hdnnp && $(MAKE) yes-kspace && $(MAKE) yes-molecule && $(MAKE) mpi\n\tcp lammps-hdnnp/src/lmp_mpi $(PROJECT_BIN)/\n\nclean-lammps-hdnnp:\n\t$(RM) -r lammps-hdnnp\n\t$(RM) $(LAMMPS_VERSION).tar.gz\n\t$(RM) $(PROJECT_BIN)/lmp_mpi\n\nclean-lammps-hdnnp-keep-file:\n\t$(RM) -r lammps-hdnnp\n\t$(RM) $(PROJECT_BIN)/lmp_mpi\n"
  },
  {
    "path": "src/libnnp/Atom.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Atom.h\"\n#include \"utility.h\"\n#include <cinttypes> // PRId64\n#include <cmath>     // fabs\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::range_error\n\nusing namespace std;\nusing namespace nnp;\n\nAtom::Atom() : hasNeighborList               (false),\n               NeighborListIsSorted          (false),\n               hasSymmetryFunctions          (false),\n               hasSymmetryFunctionDerivatives(false),\n               useChargeNeuron               (false),\n               index                         (0    ),\n               indexStructure                (0    ),\n               tag                           (0    ),\n               element                       (0    ),\n               numNeighbors                  (0    ),\n               numNeighborsUnique            (0    ),\n               numSymmetryFunctions          (0    ),\n               energy                        (0.0  ),\n               dEelecdQ                      (0.0  ),\n               chi                           (0.0  ),\n               charge                        (0.0  ),\n               chargeRef                     (0.0  )\n{\n}\n\n#ifdef N2P2_FULL_SFD_MEMORY\nvoid Atom::collectDGdxia(size_t indexAtom,\n                         size_t indexComponent,\n                         double maxCutoffRadius)\n{\n    for (size_t i = 0; i < dGdxia.size(); i++)\n    {\n        dGdxia[i] = 0.0;\n    }\n    for (size_t i = 0; i < getStoredMinNumNeighbors(maxCutoffRadius); i++)\n    {\n        if (neighbors[i].index == indexAtom)\n        {\n            for (size_t j = 0; j < numSymmetryFunctions; ++j)\n            {\n                dGdxia[j] += neighbors[i].dGdr[j][indexComponent];\n            }\n        }\n    }\n    if (index == indexAtom)\n    {\n        for (size_t i = 0; i < numSymmetryFunctions; ++i)\n        {\n            dGdxia[i] += dGdr[i][indexComponent];\n        }\n    }\n\n    return;\n}\n#endif\n\nvoid Atom::toNormalizedUnits(double convEnergy,\n                             double convLength,\n                             double convCharge)\n{\n    energy *= convEnergy;\n    r *= convLength;\n    f *= convEnergy / convLength;\n    fRef *= convEnergy / convLength;\n    charge *= convCharge;\n    chargeRef *= convCharge;\n    if (hasSymmetryFunctionDerivatives)\n    {\n        for (size_t i = 0; i < numSymmetryFunctions; ++i)\n        {\n            dEdG.at(i) *= convEnergy;\n            dGdr.at(i) /= convLength;\n#ifdef N2P2_FULL_SFD_MEMORY\n            dGdxia.at(i) /= convLength;\n#endif\n        }\n        // Take care of extra charge neuron.\n        if (useChargeNeuron)\n            dEdG.at(numSymmetryFunctions) *= convEnergy / convCharge;\n    }\n\n    if (hasNeighborList)\n    {\n        for (vector<Neighbor>::iterator it = neighbors.begin();\n             it != neighbors.end(); ++it)\n        {\n            it->d *= convLength;\n            it->dr *= convLength;\n            if (hasSymmetryFunctionDerivatives)\n            {\n                for (size_t i = 0; i < dGdr.size(); ++i)\n                {\n                    dGdr.at(i) /= convLength;\n                }\n            }\n        }\n    }\n\n    return;\n}\n\nvoid Atom::toPhysicalUnits(double convEnergy,\n                           double convLength,\n                           double convCharge)\n{\n    energy /= convEnergy;\n    r /= convLength;\n    f /= convEnergy / convLength;\n    fRef /= convEnergy / convLength;\n    charge /= convCharge;\n    chargeRef /= convCharge;\n    if (hasSymmetryFunctionDerivatives)\n    {\n        for (size_t i = 0; i < numSymmetryFunctions; ++i)\n        {\n            dEdG.at(i) /= convEnergy;\n            dGdr.at(i) *= convLength;\n#ifdef N2P2_FULL_SFD_MEMORY\n            dGdxia.at(i) *= convLength;\n#endif\n        }\n        // Take care of extra charge neuron.\n        if (useChargeNeuron)\n            dEdG.at(numSymmetryFunctions) /= convEnergy / convCharge;\n    }\n\n    if (hasNeighborList)\n    {\n        for (vector<Neighbor>::iterator it = neighbors.begin();\n             it != neighbors.end(); ++it)\n        {\n            it->d /= convLength;\n            it->dr /= convLength;\n            if (hasSymmetryFunctionDerivatives)\n            {\n                for (size_t i = 0; i < dGdr.size(); ++i)\n                {\n                    dGdr.at(i) *= convLength;\n                }\n            }\n        }\n    }\n\n    return;\n}\n\nvoid Atom::allocate(bool all, double const maxCutoffRadius)\n{\n    if (numSymmetryFunctions == 0)\n    {\n        throw range_error(\"ERROR: Number of symmetry functions set to\"\n                          \"zero, cannot allocate.\\n\");\n    }\n\n    // Clear all symmetry function related vectors (also for derivatives).\n    G.clear();\n    dEdG.clear();\n    dQdG.clear();\n    dChidG.clear();\n#ifdef N2P2_FULL_SFD_MEMORY\n    dGdxia.clear();\n#endif\n    dGdr.clear();\n\n    // Don't need any allocation of neighbors outside the symmetry function\n    // cutoff.\n    size_t const numSymFuncNeighbors = getStoredMinNumNeighbors(maxCutoffRadius);\n    for (size_t i = 0; i < numSymFuncNeighbors; ++i)\n    {\n        Neighbor& n = neighbors.at(i);\n#ifndef N2P2_NO_SF_CACHE\n        n.cache.clear();\n#endif\n        n.dGdr.clear();\n    }\n\n    // Reset status of symmetry functions and derivatives.\n    hasSymmetryFunctions           = false;\n    hasSymmetryFunctionDerivatives = false;\n\n    // Resize vectors (derivatives only if requested).\n    G.resize(numSymmetryFunctions, 0.0);\n    if (all)\n    {\n#ifndef N2P2_FULL_SFD_MEMORY\n        if (numSymmetryFunctionDerivatives.size() == 0)\n        {\n            throw range_error(\"ERROR: Number of symmetry function derivatives\"\n                              \" unset, cannot allocate.\\n\");\n        }\n#endif\n        if (useChargeNeuron) dEdG.resize(numSymmetryFunctions + 1, 0.0);\n        else                 dEdG.resize(numSymmetryFunctions, 0.0);\n        dQdG.resize(numSymmetryFunctions, 0.0);\n        dChidG.resize(numSymmetryFunctions,0.0);\n#ifdef N2P2_FULL_SFD_MEMORY\n        dGdxia.resize(numSymmetryFunctions, 0.0);\n#endif\n        dGdr.resize(numSymmetryFunctions);\n    }\n    for (size_t i = 0; i < numSymFuncNeighbors; ++i)\n    {\n        Neighbor& n = neighbors.at(i);\n#ifndef N2P2_NO_SF_CACHE\n        n.cache.resize(cacheSizePerElement.at(n.element),\n                         -numeric_limits<double>::max());\n#endif\n        if (all)\n        {\n#ifndef N2P2_FULL_SFD_MEMORY\n            n.dGdr.resize(numSymmetryFunctionDerivatives.at(n.element));\n#else\n            n.dGdr.resize(numSymmetryFunctions);\n#endif\n        }\n    }\n\n    return;\n}\n\nvoid Atom::free(bool all, double const maxCutoffRadius)\n{\n    size_t const numSymFuncNeighbors = getStoredMinNumNeighbors(maxCutoffRadius);\n    if (all)\n    {\n        G.clear();\n        vector<double>(G).swap(G);\n        hasSymmetryFunctions = false;\n\n#ifndef N2P2_NO_SF_CACHE\n        for (size_t i = 0; i < numSymFuncNeighbors; ++i)\n        {\n            Neighbor& n = neighbors.at(i);\n            n.cache.clear();\n            vector<double>(n.cache).swap(n.cache);\n        }\n#endif\n    }\n\n    dEdG.clear();\n    vector<double>(dEdG).swap(dEdG);\n    dQdG.clear();\n    vector<double>(dQdG).swap(dQdG);\n    dChidG.clear();\n    vector<double>(dChidG).swap(dChidG);\n#ifdef N2P2_FULL_SFD_MEMORY\n    dGdxia.clear();\n    vector<double>(dGdxia).swap(dGdxia);\n#endif\n    dGdr.clear();\n    vector<Vec3D>(dGdr).swap(dGdr);\n\n    for (size_t i = 0; i < numSymFuncNeighbors; ++i)\n    {\n        Neighbor& n = neighbors.at(i);\n        n.dGdr.clear();\n        vector<Vec3D>(n.dGdr).swap(n.dGdr);\n    }\n    hasSymmetryFunctionDerivatives = false;\n\n    return;\n}\n\nvoid Atom::clearNeighborList()\n{\n    clearNeighborList(numNeighborsPerElement.size());\n\n    return;\n}\n\nvoid Atom::clearNeighborList(size_t const numElements)\n{\n    free(true);\n    numNeighbors = 0;\n    numNeighborsPerElement.resize(numElements, 0);\n    numNeighborsUnique = 0;\n    neighborsUnique.clear();\n    vector<size_t>(neighborsUnique).swap(neighborsUnique);\n    neighbors.clear();\n    vector<Atom::Neighbor>(neighbors).swap(neighbors);\n    hasNeighborList = false;\n\n    return;\n}\n\nsize_t Atom::calculateNumNeighbors(double const cutoffRadius) const\n{\n    // neighborCutoffs map is only constructed when the neighbor list is sorted.\n    if (unorderedMapContainsKey(neighborCutoffs, cutoffRadius))\n        return neighborCutoffs.at(cutoffRadius);\n    else\n    {\n        size_t numNeighborsLocal = 0;\n\n        for (vector<Neighbor>::const_iterator it = neighbors.begin();\n             it != neighbors.end(); ++it)\n        {\n            if (it->d <= cutoffRadius)\n            {\n                numNeighborsLocal++;\n            }\n        }\n\n        return numNeighborsLocal;\n    }\n}\n\nsize_t Atom::getStoredMinNumNeighbors(double const cutoffRadius) const\n{\n     // neighborCutoffs map is only constructed when the neighbor list is sorted.\n    if (unorderedMapContainsKey(neighborCutoffs, cutoffRadius))\n        return neighborCutoffs.at(cutoffRadius);\n    else\n    {\n        return numNeighbors;\n    }\n}\n\nbool Atom::isNeighbor(size_t index) const\n{\n    for (auto const& n : neighbors) if (n.index == index) return true;\n\n    return false;\n}\n\nvoid Atom::updateError(string const&        property,\n                       map<string, double>& error,\n                       size_t&              count) const\n{\n    if (property == \"force\")\n    {\n        count += 3;\n        error.at(\"RMSE\") += (fRef - f).norm2();\n        error.at(\"MAE\") += (fRef - f).l1norm();\n    }\n    else if (property == \"charge\")\n    {\n        count++;\n        error.at(\"RMSE\") += (chargeRef - charge) * (chargeRef - charge);\n        error.at(\"MAE\") += fabs(chargeRef - charge);\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown property for error update.\\n\");\n    }\n\n    return;\n}\n\nVec3D Atom::calculateSelfForceShort() const\n{\n    Vec3D selfForce{};\n    for (size_t i = 0; i < numSymmetryFunctions; ++i)\n    {\n        selfForce -= dEdG.at(i) * dGdr.at(i);\n    }\n    return selfForce;\n}\n\nVec3D Atom::calculatePairForceShort(Neighbor const&             neighbor,\n                                    vector<vector<size_t> >\n                                    const *const                tableFull) const\n{\n    Vec3D pairForce{};\n#ifndef N2P2_FULL_SFD_MEMORY\n    if (!tableFull) throw runtime_error(\n                \"ERROR: tableFull must not be null pointer\");\n    vector<size_t> const& table = tableFull->at(neighbor.element);\n    for (size_t i = 0; i < neighbor.dGdr.size(); ++i)\n    {\n        pairForce -= dEdG.at(table.at(i)) * neighbor.dGdr.at(i);\n    }\n#else\n    for (size_t i = 0; i < numSymmetryFunctions; ++i)\n    {\n        pairForce -= dEdG.at(i) * neighbor.dGdr.at(i);\n    }\n#endif\n    return pairForce;\n}\n\nVec3D Atom::calculateDChidr(size_t const atomIndexOfR,\n                            double const maxCutoffRadius,\n                            vector<vector<size_t> > const *const tableFull) const\n{\n#ifndef N2P2_FULL_SFD_MEMORY\n    if (!tableFull) throw runtime_error(\n                \"ERROR: tableFull must not be null pointer\");\n#endif\n    Vec3D dChidr{};\n    // need to add this case because the loop over the neighbors\n    // does not include the contribution dChi_i/dr_i.\n    if (atomIndexOfR == index)\n    {\n        for (size_t k = 0; k < numSymmetryFunctions; ++k)\n        {\n            dChidr += dChidG.at(k) * dGdr.at(k);\n        }\n    }\n\n    size_t numNeighbors = getStoredMinNumNeighbors(maxCutoffRadius);\n    for (size_t m = 0; m < numNeighbors; ++m)\n    {\n        Atom::Neighbor const& n = neighbors.at(m);\n\t// atomIndexOfR must not be larger than ~max(int64_t)/2.\n        if (n.tag == (int64_t)atomIndexOfR)\n        {\n#ifndef N2P2_FULL_SFD_MEMORY\n            vector<size_t> const& table = tableFull->at(n.element);\n            for (size_t k = 0; k < n.dGdr.size(); ++k)\n            {\n                dChidr += dChidG.at(table.at(k)) * n.dGdr.at(k);\n            }\n#else\n            for (size_t k = 0; k < numSymmetryFunctions; ++k)\n            {\n                dChidr += dChidG.at(k) * n.dGdr.at(k);\n            }\n#endif\n        }\n    }\n    return dChidr;\n}\n\nvector<string> Atom::getForcesLines() const\n{\n    vector<string> v;\n    for (size_t i = 0; i < 3; ++i)\n    {\n        v.push_back(strpr(\"%10zu %10zu %16.8E %16.8E\\n\",\n                          indexStructure,\n                          index,\n                          fRef[i],\n                          f[i]));\n    }\n\n    return v;\n}\n\nstring Atom::getChargeLine() const\n{\n    return strpr(\"%10zu %10zu %16.8E %16.8E\\n\",\n                 indexStructure,\n                 index,\n                 chargeRef,\n                 charge);\n}\n\nvector<string> Atom::info() const\n{\n    vector<string> v;\n\n    v.push_back(strpr(\"********************************\\n\"));\n    v.push_back(strpr(\"ATOM                            \\n\"));\n    v.push_back(strpr(\"********************************\\n\"));\n    v.push_back(strpr(\"hasNeighborList                : %d\\n\", hasNeighborList));\n    v.push_back(strpr(\"hasSymmetryFunctions           : %d\\n\", hasSymmetryFunctions));\n    v.push_back(strpr(\"hasSymmetryFunctionDerivatives : %d\\n\", hasSymmetryFunctionDerivatives));\n    v.push_back(strpr(\"useChargeNeuron                : %d\\n\", useChargeNeuron));\n    v.push_back(strpr(\"index                          : %d\\n\", index));\n    v.push_back(strpr(\"indexStructure                 : %d\\n\", indexStructure));\n    v.push_back(strpr(\"tag                            : %\" PRId64 \"\\n\", tag));\n    v.push_back(strpr(\"element                        : %d\\n\", element));\n    v.push_back(strpr(\"numNeighbors                   : %d\\n\", numNeighbors));\n    v.push_back(strpr(\"numNeighborsUnique             : %d\\n\", numNeighborsUnique));\n    v.push_back(strpr(\"numSymmetryFunctions           : %d\\n\", numSymmetryFunctions));\n    v.push_back(strpr(\"energy                         : %16.8E\\n\", energy));\n    v.push_back(strpr(\"chi                            : %16.8E\\n\", chi));\n    v.push_back(strpr(\"charge                         : %16.8E\\n\", charge));\n    v.push_back(strpr(\"chargeRef                      : %16.8E\\n\", chargeRef));\n    v.push_back(strpr(\"r                              : %16.8E %16.8E %16.8E\\n\", r[0], r[1], r[2]));\n    v.push_back(strpr(\"f                              : %16.8E %16.8E %16.8E\\n\", f[0], f[1], f[2]));\n    v.push_back(strpr(\"fRef                           : %16.8E %16.8E %16.8E\\n\", fRef[0], fRef[1], fRef[2]));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"neighborsUnique            [*] : %d\\n\", neighborsUnique.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < neighborsUnique.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %d\\n\", i, neighborsUnique.at(i)));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"numNeighborsPerElement     [*] : %d\\n\", numNeighborsPerElement.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < numNeighborsPerElement.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %d\\n\", i, numNeighborsPerElement.at(i)));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"numSymmetryFunctionDeriv.  [*] : %d\\n\", numSymmetryFunctionDerivatives.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < numSymmetryFunctionDerivatives.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %d\\n\", i, numSymmetryFunctionDerivatives.at(i)));\n    }\n#ifndef N2P2_NO_SF_CACHE\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"cacheSizePerElement        [*] : %d\\n\", cacheSizePerElement.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < cacheSizePerElement.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %d\\n\", i, cacheSizePerElement.at(i)));\n    }\n#endif\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"G                          [*] : %d\\n\", G.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < G.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %16.8E\\n\", i, G.at(i)));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"dEdG                       [*] : %d\\n\", dEdG.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < dEdG.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %16.8E\\n\", i, dEdG.at(i)));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"dQdG                       [*] : %d\\n\", dQdG.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < dQdG.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %16.8E\\n\", i, dQdG.at(i)));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n#ifdef N2P2_FULL_SFD_MEMORY\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"dGdxia                     [*] : %d\\n\", dGdxia.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < dGdxia.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %16.8E\\n\", i, dGdxia.at(i)));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n#endif\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"dGdr                       [*] : %d\\n\", dGdr.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < dGdr.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %16.8E %16.8E %16.8E\\n\", i, dGdr.at(i)[0], dGdr.at(i)[1], dGdr.at(i)[2]));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"neighbors                  [*] : %d\\n\", neighbors.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < neighbors.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  :\\n\", i));\n        vector<string> vn = neighbors[i].info();\n        v.insert(v.end(), vn.begin(), vn.end());\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"********************************\\n\"));\n\n    return v;\n}\n\nAtom::Neighbor::Neighbor() : index      (0                      ),\n                             tag        (0                      ),\n                             element    (0                      ),\n                             d          (0.0                    )\n{\n}\n\nbool Atom::Neighbor::operator==(Atom::Neighbor const& rhs) const\n{\n    if (element != rhs.element) return false;\n    if (d       != rhs.d      ) return false;\n    return true;\n}\n\nbool Atom::Neighbor::operator<(Atom::Neighbor const& rhs) const\n{\n    // sorting according to elements deactivated\n    // TODO: resolve this issue for nnp-sfclust\n    // TODO: this breaks pynnp CI tests in test_Neighbor.py\n    //if      (element < rhs.element) return true;\n    //else if (element > rhs.element) return false;\n    if      (d       < rhs.d      ) return true;\n    else if (d       > rhs.d      ) return false;\n    return false;\n}\n\nvector<string> Atom::Neighbor::info() const\n{\n    vector<string> v;\n\n    v.push_back(strpr(\"********************************\\n\"));\n    v.push_back(strpr(\"NEIGHBOR                        \\n\"));\n    v.push_back(strpr(\"********************************\\n\"));\n    v.push_back(strpr(\"index                          : %d\\n\", index));\n    v.push_back(strpr(\"tag                            : %\" PRId64 \"\\n\", tag));\n    v.push_back(strpr(\"element                        : %d\\n\", element));\n    v.push_back(strpr(\"d                              : %16.8E\\n\", d));\n    v.push_back(strpr(\"dr                             : %16.8E %16.8E %16.8E\\n\", dr[0], dr[1], dr[2]));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n#ifndef N2P2_NO_SF_CACHE\n    v.push_back(strpr(\"cache                      [*] : %d\\n\", cache.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < cache.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %16.8E\\n\", i, cache.at(i)));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n#endif\n    v.push_back(strpr(\"dGdr                       [*] : %d\\n\", dGdr.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < dGdr.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %16.8E %16.8E %16.8E\\n\", i, dGdr.at(i)[0], dGdr.at(i)[1], dGdr.at(i)[2]));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"********************************\\n\"));\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/Atom.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef ATOM_H\n#define ATOM_H\n\n#include \"Vec3D.h\"\n#include <cstddef>          // std::size_t\n#include <cstdint>          // int64_t\n#include <map>              // std::map\n#include <unordered_map>    // std::unordered_map\n#include <string>           // std::string\n#include <vector>           // std::vector\n\nnamespace nnp\n{\n\n/// Storage for a single atom.\nstruct Atom\n{\n    /// Struct to store information on neighbor atoms.\n    struct Neighbor\n    {\n        /// Index of neighbor atom.\n        std::size_t                index;\n        /// Tag of neighbor atom.\n        int64_t                    tag;\n        /// %Element index of neighbor atom.\n        std::size_t                element;\n        /// Distance to neighbor atom.\n        double                     d;\n        /// Distance vector to neighbor atom.\n        Vec3D                      dr;\n#ifndef N2P2_NO_SF_CACHE\n        /// Symmetry function cache (e.g. for cutoffs, compact functions).\n        std::vector<double>        cache;\n#endif\n        /** Derivatives of symmetry functions with respect to neighbor\n         * coordinates.\n         *\n         * May be empty, only filled when needed. Contains\n         * @f$ \\frac{\\partial G_i}{\\partial \\alpha_j} @f$, where @f$G_i@f$ is\n         * a symmetry function of atom @f$i@f$ and @f$\\alpha_j@f$ is a\n         * coordinate @f$ \\alpha = x,y,z @f$ of neighbor atom @f$ j @f$,\n         * necessary for force calculation.\n         */\n        std::vector<Vec3D>         dGdr;\n\n        /** Neighbor constructor, initialize to zero.\n         */\n        Neighbor();\n        /** Overload == operator.\n         */\n        bool                     operator==(Neighbor const& rhs) const;\n        /** Overload != operator.\n         */\n        bool                     operator!=(Neighbor const& rhs) const;\n        /** Overload < operator.\n         */\n        bool                     operator<(Neighbor const& rhs) const;\n        /** Overload > operator.\n         */\n        bool                     operator>(Neighbor const& rhs) const;\n        /** Overload <= operator.\n         */\n        bool                     operator<=(Neighbor const& rhs) const;\n        /** Overload >= operator.\n         */\n        bool                     operator>=(Neighbor const& rhs) const;\n        /** Get atom information as a vector of strings.\n         *\n         * @return Lines with atom information.\n         */\n        std::vector<std::string> info() const;\n    };\n\n    /// If the neighbor list has been calculated for this atom.\n    bool                     hasNeighborList;\n    /// If the neighbor list is sorted by distance.\n    bool                     NeighborListIsSorted;\n    /// If symmetry function values are saved for this atom.\n    bool                     hasSymmetryFunctions;\n    /// If symmetry function derivatives are saved for this atom.\n    bool                     hasSymmetryFunctionDerivatives;\n    /// If an additional charge neuron in the short-range NN is present.\n    bool                     useChargeNeuron;\n    /// Index number of this atom.\n    std::size_t              index;\n    /// Index number of structure this atom belongs to.\n    std::size_t              indexStructure;\n    /// Tag number of this atom.\n    int64_t                  tag;\n    /// %Element index of this atom.\n    std::size_t              element;\n    /// Total number of neighbors.\n    std::size_t              numNeighbors;\n    /// Number of unique neighbor indices (don't count multiple PBC images).\n    std::size_t              numNeighborsUnique;\n    /// Number of symmetry functions used to describe the atom environment.\n    std::size_t              numSymmetryFunctions;\n    /// Atomic energy determined by neural network.\n    double                   energy;\n    /// Derivative of electrostatic energy with respect to this atom's charge.\n    double                   dEelecdQ;\n    /// Atomic electronegativity determined by neural network.\n    double                   chi;\n    /// Atomic charge determined by neural network.\n    double                   charge;\n    /// Atomic reference charge.\n    double                   chargeRef;\n    /// Cartesian coordinates\n    Vec3D                    r;\n    /// Force vector calculated by neural network.\n    Vec3D                    f;\n    /// Force vector resulting from electrostatics.\n    Vec3D                    fElec;\n    /// Reference force vector from data set.\n    Vec3D                    fRef;\n    /// Partial derivative of electrostatic energy with respect to this atom's\n    /// coordinates.\n    Vec3D                    pEelecpr;\n    /// List of unique neighbor indices (don't count multiple PBC images).\n    std::vector<std::size_t> neighborsUnique;\n    /// Number of neighbors per element.\n    std::vector<std::size_t> numNeighborsPerElement;\n    /// Number of neighbor atom symmetry function derivatives per element.\n    std::vector<std::size_t> numSymmetryFunctionDerivatives;\n#ifndef N2P2_NO_SF_CACHE\n    /// Cache size for each element.\n    std::vector<std::size_t> cacheSizePerElement;\n#endif\n    /// Symmetry function values\n    std::vector<double>      G;\n    /// Derivative of atomic energy with respect to symmetry functions. Also\n    /// contains dEdQ in the last element if HDNNP-4G is used.\n    std::vector<double>      dEdG;\n    /// Derivative of atomic charge with respect to symmetry functions.\n    std::vector<double>      dQdG;\n    /// Derivative of electronegativity with respect to symmetry functions.\n    std::vector<double>      dChidG;\n#ifdef N2P2_FULL_SFD_MEMORY\n    /// Derivative of symmetry functions with respect to one specific atom\n    /// coordinate.\n    std::vector<double>      dGdxia;\n#endif\n    /// Derivative of symmetry functions with respect to this atom's\n    /// coordinates.\n    std::vector<Vec3D>       dGdr;\n    /// Derivative of charges with respect to this atom's coordinates.\n    std::vector<Vec3D>       dQdr;\n    /// If dQdr has been calculated for respective components.\n    //bool                    hasdQdr[3];\n    /// Derivative of A-matrix with respect to this atom's coordinates\n    /// contracted with the charges.\n    std::vector<Vec3D>       dAdrQ;\n    /// Neighbor array (maximum number defined in macros.h.\n    std::vector<Neighbor>    neighbors;\n    /// Map stores number of neighbors needed for the corresponding cut-off.\n    std::unordered_map<double, size_t> neighborCutoffs;\n\n    /** Atom constructor, initialize to zero.\n     */\n    Atom();\n#ifdef N2P2_FULL_SFD_MEMORY\n    /** Collect derivative of symmetry functions with repect to one atom's\n     * coordinate.\n     *\n     * @param[in] indexAtom The index @f$i@f$ of the atom requested.\n     * @param[in] indexComponent The component @f$\\alpha@f$ of the atom\n     *                           requested.\n     * @param[in] maxCutoffRadius Maximum symmetry function cutoff.\n     *\n     * This calculates an array of derivatives\n     * @f[\n     *   \\left(\\frac{\\partial G_1}{\\partial x_{i,\\alpha}}, \\ldots,\n     *   \\frac{\\partial G_n}{\\partial x_{i,\\alpha}}\\right),\n     *\n     * @f]\n     * where @f$\\{G_j\\}_{j=1,\\ldots,n}@f$ are the symmetry functions for this\n     * atom and @f$x_{i,\\alpha}@f$ is the @f$\\alpha@f$-component of the\n     * position of atom @f$i@f$. The result is stored in #dGdxia.\n     */\n    void                     collectDGdxia(std::size_t indexAtom,\n                                           std::size_t indexComponent,\n                                           double maxCutoffRadius);\n#endif\n    /** Switch to normalized length, energy and charge units.\n     *\n     * @param[in] convEnergy Multiplicative energy unit conversion factor.\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     * @param[in] convCharge Multiplicative charge unit conversion factor.\n     */\n    void                     toNormalizedUnits(double convEnergy,\n                                               double convLength,\n                                               double convCharge);\n    /** Switch to physical length, energy and charge units.\n     *\n     * @param[in] convEnergy Multiplicative energy unit conversion factor.\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     * @param[in] convCharge Multiplicative charge unit conversion factor.\n     */\n    void                     toPhysicalUnits(double convEnergy,\n                                             double convLength,\n                                             double convCharge);\n    /** Allocate vectors related to symmetry functions (#G, #dEdG).\n     *\n     * @param[in] all If `true` allocate also vectors corresponding to\n     *                derivatives of symmetry functions (#dEdG, #dGdr, #dGdxia\n     *                and Neighbor::dGdr, neighbors must be present). If\n     *                `false` allocate only #G.\n     * @param[in] maxCutoffRadius Maximum cutoff radius of symmetry functions.\n     *\n     * Warning: #numSymmetryFunctions and #numSymmetryFunctionDerivatives need\n     * to be set first (the latter only in case of argument all == true.\n     */\n    void                     allocate(bool         all,\n                                      double const maxCutoffRadius = 0.0);\n    /** Free vectors related to symmetry functions, opposite of #allocate().\n     *\n     * @param[in] all If `true` free all vectors (#G, #dEdG, #dGdr, #dGdxia\n     *                and Neighbor::dGdr) otherwise free only #dEdG, #dGdr,\n     *                #dGdxia and Neighbor::dGdr.\n     * @param[in] maxCutoffRadius Maximum cutoff radius of symmetry functions.\n     */\n    void                     free(bool all, double const maxCutoffRadius = 0.0);\n    /** Clear neighbor list.\n     *\n     * @note Also clears symmetry function data.\n     */\n    void                     clearNeighborList();\n    /** Clear neighbor list and change number of elements.\n     *\n     * @param[in] numElements Number of elements present.\n     *\n     * @note Also clears symmetry function data. The number of elements is\n     * necessary to allocate the #numNeighborsPerElement vector. Use the\n     * overloaded version clearNeighborList() if the number of elements stays\n     * the same.\n     */\n    void                     clearNeighborList(std::size_t const numElements);\n    /** Calculate number of neighbors for a given cutoff radius.\n     *\n     * @param[in] cutoffRadius Desired cutoff radius.\n     *\n     * This function assumes that the neighbor list has already been calculated\n     * for a large cutoff radius and now the number of neighbor atoms for a\n     * smaller cutoff is requested.\n     */\n    std::size_t              calculateNumNeighbors(double const cutoffRadius) const;\n    /** Return needed number of neighbors for a given cutoff radius from\n     *                  neighborCutoffs map. If it isn't setup, return number\n     *                  of all neighbors in list.\n     * @param[in]   cutoffRadius Desired cutoff radius.\n     * @return Integer with the number of neighbors corresponding to the cutoff\n     *                  radius.\n     */\n    std::size_t              getStoredMinNumNeighbors(\n                                             double const cutoffRadius) const;\n    /** Return whether atom is a neighbor.\n     *\n     * @param[in] index Index of atom in question.\n     *\n     * @return `True` if atom is neighbor of this atom.\n     */\n    bool                     isNeighbor(std::size_t index) const;\n    /** Update property error metrics with data from this atom.\n     *\n     * @param[in] property One of \"force\" or \"charge\".\n     * @param[in,out] error Input error metric map to be updated.\n     * @param[in,out] count Input counter to be updated.\n     */\n    void                     updateError(\n                                   std::string const&             property,\n                                   std::map<std::string, double>& error,\n                                   std::size_t&                   count) const;\n    /** Calculate force resulting from gradient of this atom's\n     *  (short-ranged) energy contribution with respect to this atom's\n     *  coordinate.\n     *  @return calculated force vector.\n     */\n    Vec3D                    calculateSelfForceShort() const;\n     /** Calculate force resulting from gradient of this atom's (short-ranged)\n     *  energy contribution with respect to neighbor's coordinate.\n     *\n     * @param[in] neighbor Neighbor of which the gradient is considered.\n     * @param[in] tableFull Pointer to ymmetry function table if it is used.\n     * @return calculated force vector.\n     */\n    Vec3D                    calculatePairForceShort(\n                                    Neighbor const&  neighbor,\n                                    std::vector<std::vector <std::size_t> >\n                                    const *const     tableFull = nullptr) const;\n    /** Calculate dChi/dr of this atom's Chi with respect to the coordinates\n     *  of the given atom.\n     *\n     * @param[in] atomIndexOfR Index of the atom corresponding to the coordinates r.\n     * @param[in] maxCutoffRadius Largest cut-off of the symmetry functions.\n     * @param[in] tableFull Pointer to symmetry function table if it is used.\n     * @return 3D Vector containing the derivative dChi/dr.\n     */\n    Vec3D                    calculateDChidr(\n                                    size_t const     atomIndexOfR,\n                                    double const     maxCutoffRadius,\n                                    std::vector<std::vector<size_t> >\n                                    const *const     tableFull = nullptr) const;\n    /** Get reference and NN forces for this atoms.\n     *\n     * @return Vector of strings with #indexStructure, #index, #fRef, #f\n     * values.\n     */\n    std::vector<std::string> getForcesLines() const;\n    /** Get reference and NN charge for this atoms.\n     *\n     * @return Line with #indexStructure, #index, #chargeRef, #charge values.\n     */\n    std::string              getChargeLine() const;\n    /** Get atom information as a vector of strings.\n     *\n     * @return Lines with atom information.\n     */\n    std::vector<std::string> info() const;\n};\n\ninline bool Atom::Neighbor::operator!=(Atom::Neighbor const& rhs) const\n{\n    return !((*this) == rhs);\n}\n\ninline bool Atom::Neighbor::operator>(Atom::Neighbor const& rhs) const\n{\n    return rhs < (*this);\n}\n\ninline bool Atom::Neighbor::operator<=(Atom::Neighbor const& rhs) const\n{\n    return !((*this) > rhs);\n}\n\ninline bool Atom::Neighbor::operator>=(Atom::Neighbor const& rhs) const\n{\n    return !((*this) < rhs);\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/CompactFunction.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"CompactFunction.h\"\n#include <stdexcept>\n\nusing namespace std;\nusing namespace nnp;\n\nCompactFunction::CompactFunction() : center    (0.0  ),\n                                     width     (0.0  ),\n                                     left      (0.0  ),\n                                     right     (0.0  ),\n                                     scale     (0.0  )\n{\n    core.setType(CoreFunction::Type::POLY2);\n}\n\n#ifndef N2P2_NO_ASYM_POLY\nbool CompactFunction::getAsymmetric() const\n{\n    return core.getAsymmetric();\n}\n\nvoid CompactFunction::setAsymmetric(bool asymmetric)\n{\n    core.setAsymmetric(asymmetric);\n\n    return;\n}\n#endif\n\nvoid CompactFunction::setCenterWidth(double center, double width)\n{\n    if (width <= 0.0)\n    {\n        throw invalid_argument(\"ERROR: Width <= 0.\\n\");\n    }\n\n    this->center = center;\n    this->width  = width;\n    this->left   = center - width;\n    this->right  = center + width;\n    this->scale  = 1.0 / width;\n\n    return;\n}\n\nvoid CompactFunction::setLeftRight(double left, double right)\n{\n    if (left >= right)\n    {\n        throw invalid_argument(\"ERROR: Left >= Right.\\n\");\n    }\n\n    this->left   = left;\n    this->right  = right;\n    this->center = (right + left) / 2.0;\n    this->width  = (right - left) / 2.0;\n    this->scale  = 1.0 / width;\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/CompactFunction.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef COMPACTFUNCTION_H\n#define COMPACTFUNCTION_H\n\n#include \"CoreFunction.h\"\n\nnamespace nnp\n{\n\n/// A general function with compact support.\nclass CompactFunction\n{\npublic:\n    /** Constructor, initializes to #CoreFunction::Type::POLY2.\n     */\n    CompactFunction();\n    /** Set type.\n     *\n     * @param[in] type Type of core function to use.\n     */\n    void               setCoreFunction(CoreFunction::Type const type);\n    /** Set center and width.\n     *\n     * @param[in] center Center of compact function.\n     * @param[in] width Width of compact function.\n     *\n     * @note Either use setCenterWidth() or setLeftRight() to initialize.\n     */\n    void               setCenterWidth(double center, double width);\n    /** Set left and right boundary.\n     *\n     * @param[in] left Left boundary of compact function.\n     * @param[in] right Right boundary of compact function.\n     *\n     * @note Either use setCenterWidth() or setLeftRight() to initialize.\n     */\n    void               setLeftRight(double left, double right);\n    /** Getter for #type.\n     *\n     * @return Type used.\n     */\n    CoreFunction::Type getCoreFunctionType() const;\n#ifndef N2P2_NO_ASYM_POLY\n    /** Set asymmetric property in core function.\n     *\n     * @param[in] asymmetric Whether asymmetry should be activated.\n     */\n    void               setAsymmetric(bool asymmetric);\n    /** Check if asymmetry is enabled in core function.\n     *\n     * @return Whether asymmetry is activated.\n     */\n    bool               getAsymmetric() const;\n#endif\n    /** Getter for #center.\n     *\n     * @return Center of compact function.\n     */\n    double             getCenter() const;\n    /** Getter for #width.\n     *\n     * @return Width of compact function.\n     */\n    double             getWidth() const;\n    /** Getter for #left.\n     *\n     * @return Left boundary of compact function.\n     */\n    double             getLeft() const;\n    /** Getter for #right.\n     *\n     * @return Right boundary of compact function.\n     */\n    double             getRight() const;\n    /** Compact function @f$f_c@f$.\n     *\n     * @param[in] a Function argument.\n     * @return Function value.\n     */\n    double             f(double a) const;\n    /** Derivative of compact function @f$\\frac{d f_c}{d a}@f$.\n     *\n     * @param[in] a Function argument.\n     * @return Value of function derivative.\n     */\n    double             df(double a) const;\n    /** Calculate compact function and derivative at once.\n     *\n     * @param[in] a Function argument.\n     * @param[out] fa Cutoff function value.\n     * @param[out] dfa Value of cutoff function derivative.\n     */\n    void               fdf(double a, double& fa, double& dfa) const;\n\nprivate:\n    /// Center of compact function.\n    double       center;\n    /// Width of compact function.\n    double       width;\n    /// Left boundary of compact function.\n    double       left;\n    /// Right boundary of compact function.\n    double       right;\n    /// Inverse width.\n    double       scale;\n    /// Core function to be used on either side of compact function.\n    CoreFunction core;\n\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline void CompactFunction::setCoreFunction(CoreFunction::Type const type)\n{\n    core.setType(type);\n\n    return;\n}\n\ninline CoreFunction::Type CompactFunction::getCoreFunctionType() const\n{\n    return core.getType();\n}\n\ninline double CompactFunction::getCenter() const { return center; }\ninline double CompactFunction::getWidth() const { return width; }\ninline double CompactFunction::getLeft() const { return left; }\ninline double CompactFunction::getRight() const { return right; }\n\ninline double CompactFunction::f(double a) const\n{\n    a = (a - center) * scale;\n    return core.f(std::abs(a));\n}\n\ninline double CompactFunction::df(double a) const\n{\n    a = (a - center) * scale;\n    return copysign(scale * core.df(std::abs(a)), a);\n}\n\ninline void CompactFunction::fdf(double a, double& fa, double& dfa) const\n{\n    a = (a - center) * scale;\n    core.fdf(std::abs(a), fa, dfa);\n    dfa *= copysign(scale, a);\n\n    return;\n}\n\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/CoreFunction.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"CoreFunction.h\"\n#include \"utility.h\"\n#include <stdexcept>\n\nusing namespace std;\nusing namespace nnp;\n\ndouble const CoreFunction::PI = 4.0 * atan(1.0);\ndouble const CoreFunction::PI_2 = 2.0 * atan(1.0);\ndouble const CoreFunction::E = exp(1.0);\n\nCoreFunction::CoreFunction() : type      (Type::POLY2            ),\n#ifndef N2P2_NO_ASYM_POLY\n                               asymmetric(false                  ),\n#endif\n                               fPtr      (&CoreFunction::  fPOLY2),\n                               dfPtr     (&CoreFunction:: dfPOLY2),\n                               fdfPtr    (&CoreFunction::fdfPOLY2)\n{\n}\n\nvoid CoreFunction::setType(Type const type)\n{\n    this->type = type;\n\n    if (type == Type::COS)\n    {\n          fPtr = &CoreFunction::  fCOS;\n         dfPtr = &CoreFunction:: dfCOS;\n        fdfPtr = &CoreFunction::fdfCOS;\n    }\n    else if (type == Type::POLY1)\n    {\n          fPtr = &CoreFunction::  fPOLY1;\n         dfPtr = &CoreFunction:: dfPOLY1;\n        fdfPtr = &CoreFunction::fdfPOLY1;\n    }\n    else if (type == Type::POLY2)\n    {\n          fPtr = &CoreFunction::  fPOLY2;\n         dfPtr = &CoreFunction:: dfPOLY2;\n        fdfPtr = &CoreFunction::fdfPOLY2;\n    }\n    else if (type == Type::POLY3)\n    {\n          fPtr = &CoreFunction::  fPOLY3;\n         dfPtr = &CoreFunction:: dfPOLY3;\n        fdfPtr = &CoreFunction::fdfPOLY3;\n    }\n    else if (type == Type::POLY4)\n    {\n          fPtr = &CoreFunction::  fPOLY4;\n         dfPtr = &CoreFunction:: dfPOLY4;\n        fdfPtr = &CoreFunction::fdfPOLY4;\n    }\n    else if (type == Type::EXP)\n    {\n          fPtr = &CoreFunction::  fEXP;\n         dfPtr = &CoreFunction:: dfEXP;\n        fdfPtr = &CoreFunction::fdfEXP;\n    }\n    else\n    {\n        throw invalid_argument(\"ERROR: Unknown core function.\\n\");\n    }\n\n    return;\n}\n\nvoid CoreFunction::setType(string const typeString)\n{\n    CoreFunction::Type t;\n\n    if      (typeString == \"c\")  t = CoreFunction::Type::COS;\n    else if (typeString == \"p1\") t = CoreFunction::Type::POLY1;\n    else if (typeString == \"p2\") t = CoreFunction::Type::POLY2;\n    else if (typeString == \"p3\") t = CoreFunction::Type::POLY3;\n    else if (typeString == \"p4\") t = CoreFunction::Type::POLY4;\n    else if (typeString == \"e\")  t = CoreFunction::Type::EXP;\n    else\n    {\n        throw invalid_argument(\"ERROR: Unknown CoreFunction type.\\n\");\n    }\n\n    setType(t);\n\n    return;\n}\n\nvector<string> CoreFunction::info() const\n{\n    vector<string> v;\n\n    if (type == Type::COS)\n    {\n        v.push_back(strpr(\"CoreFunction::Type::COS (%d):\\n\", type));\n        v.push_back(\"f(x) := 1/2 * (cos(pi*x) + 1)\\n\");\n    }\n    else if (type == Type::POLY1)\n    {\n        v.push_back(strpr(\"CoreFunction::Type::POLY1 (%d):\\n\", type));\n        v.push_back(\"f(x) := (2x - 3)x^2 + 1\\n\");\n    }\n    else if (type == Type::POLY2)\n    {\n        v.push_back(strpr(\"CoreFunction::Type::POLY2 (%d):\\n\", type));\n        v.push_back(\"f(x) := ((15 - 6x)x - 10)x^3 + 1\\n\");\n    }\n    else if (type == Type::POLY3)\n    {\n        v.push_back(strpr(\"CoreFunction::Type::POLY3 (%d):\\n\", type));\n        v.push_back(\"f(x) := (x(x(20x - 70) + 84) - 35)x^4 + 1\\n\");\n    }\n    else if (type == Type::POLY4)\n    {\n        v.push_back(strpr(\"CoreFunction::Type::POLY4 (%d):\\n\", type));\n        v.push_back(\"f(x) := (x(x((315 - 70x)x - 540) + 420) - 126)x^5 + 1\\n\");\n    }\n    else if (type == Type::EXP)\n    {\n        v.push_back(strpr(\"CoreFunction::Type::EXP (%d):\\n\", type));\n        v.push_back(\"f(x) := exp(-1 / 1 - x^2)\\n\");\n    }\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/CoreFunction.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef COREFUNCTION_H\n#define COREFUNCTION_H\n\n#include <cmath>\n#include <string>\n#include <vector>\n\nnamespace nnp\n{\n\nclass CoreFunction\n{\npublic:\n    /// List of available function types.\n    enum class Type\n    {\n        /** @f$f(x) = \\frac{1}{2} \\left[ \\cos (\\pi x) + 1\\right] @f$\n         */\n        COS,\n        /** @f$f(x) = (2x - 3)x^2 + 1@f$\n         */\n        POLY1,\n        /** @f$f(x) = ((15 - 6x)x - 10) x^3 + 1@f$\n         */\n        POLY2,\n        /** @f$f(x) = (x(x(20x - 70) + 84) - 35)x^4 + 1@f$\n         */\n        POLY3,\n        /** @f$f(x) = (x(x((315 - 70x)x - 540) + 420) - 126)x^5 + 1@f$\n         */\n        POLY4,\n        /** @f$f(x) = e^{1 - \\frac{1}{1 - x^2}}@f$\n         */\n        EXP\n    };\n\n    /** Constructor, initializes to #Type::POLY2.\n     */\n    CoreFunction();\n    /** Set function type.\n     *\n     * @param[in] type Type of core function used.\n     */\n    void                     setType(Type const type);\n    /** Set function type.\n     *\n     * @param[in] typeString Type (string version) of core function used.\n     */\n    void                     setType(std::string const typeString);\n    /** Getter for #type.\n     *\n     * @return Type used.\n     */\n    Type                     getType() const;\n#ifndef N2P2_NO_ASYM_POLY\n    /** Set asymmetric property.\n     *\n     * @param[in] asymmetric Whether asymmetry should be activated.\n     */\n    void                     setAsymmetric(bool asymmetric);\n    /** Getter for #asymmetric.\n     *\n     * @return Whether asymmetry is activated.\n     */\n    bool                     getAsymmetric() const;\n#endif\n    /** Calculate function value @f$f(x)@f$.\n     *\n     * @param[in] x Function argument.\n     * @return Function value.\n     */\n    double                   f(double x) const;\n    /** Calculate derivative of function at argument @f$\\frac{df(x)}{dx}@f$.\n     *\n     * @param[in] x Function argument.\n     * @return Function derivative value.\n     */\n    double                   df(double x) const;\n    /** Calculate function and derivative at once.\n     *\n     * @param[in] x Function argument.\n     * @param[out] fx Function value.\n     * @param[out] dfx Derivative value.\n     */\n    void                     fdf(double x, double& fx, double& dfx) const;\n    /** Get string with formula of compact function.\n     *\n     * @return Information string.\n     */\n    std::vector<std::string> info() const;\n\nprivate:\n    static double const PI;\n    static double const PI_2;\n    static double const E;\n    /// Core function type.\n    Type                type;\n#ifndef N2P2_NO_ASYM_POLY\n    /// Enables asymmetry modification (use with polynomials).\n    bool                asymmetric;\n#endif\n    /// Function pointer to f.\n    double     (CoreFunction::*fPtr)(double x) const;\n    /// Function pointer to df.\n    double     (CoreFunction::*dfPtr)(double x) const;\n    /// Function pointer to fdf.\n    void       (CoreFunction::*fdfPtr)(double  x,\n                                       double& fx,\n                                       double& dfx) const;\n\n    // Individual functions.\n    double   fCOS(double x) const;\n    double  dfCOS(double x) const;\n    void   fdfCOS(double x, double& fx, double& dfx) const;\n\n    double   fPOLY1(double x) const;\n    double  dfPOLY1(double x) const;\n    void   fdfPOLY1(double x, double& fx, double& dfx) const;\n\n    double   fPOLY2(double x) const;\n    double  dfPOLY2(double x) const;\n    void   fdfPOLY2(double x, double& fx, double& dfx) const;\n\n    double   fPOLY3(double x) const;\n    double  dfPOLY3(double x) const;\n    void   fdfPOLY3(double x, double& fx, double& dfx) const;\n\n    double   fPOLY4(double x) const;\n    double  dfPOLY4(double x) const;\n    void   fdfPOLY4(double x, double& fx, double& dfx) const;\n\n    double   fEXP(double x) const;\n    double  dfEXP(double x) const;\n    void   fdfEXP(double x, double& fx, double& dfx) const;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline CoreFunction::Type CoreFunction::getType() const { return type; }\n\n#ifndef N2P2_NO_ASYM_POLY\ninline void CoreFunction::setAsymmetric(bool asymmetric)\n{\n    this->asymmetric = asymmetric;\n\n    return;\n}\n\ninline bool CoreFunction::getAsymmetric() const { return asymmetric; }\n#endif\n\ninline double CoreFunction::f(double x) const\n{\n#ifndef N2P2_NO_ASYM_POLY\n    if (asymmetric) x = (2.0 - x) * x;\n#endif\n    return (this->*fPtr)(x);\n}\n\ninline double CoreFunction::df(double x) const\n{\n#ifndef N2P2_NO_ASYM_POLY\n    if (asymmetric) return (2.0 - 2.0 * x) * (this->*dfPtr)((2.0 - x) * x);\n    else return (this->*dfPtr)(x);\n#else\n    return (this->*dfPtr)(x);\n#endif\n}\n\ninline void CoreFunction::fdf(double x, double& fx, double& dfx) const\n{\n#ifndef N2P2_NO_ASYM_POLY\n    if (asymmetric)\n    {\n        (this->*fdfPtr)((2.0 - x) * x, fx, dfx);\n        dfx *= 2.0 - 2.0 * x;\n    }\n    else (this->*fdfPtr)(x, fx, dfx);\n#else\n    (this->*fdfPtr)(x, fx, dfx);\n#endif\n    return;\n}\n\ninline double CoreFunction::fCOS(double x) const\n{\n    return 0.5 * (cos(PI * x) + 1.0);\n}\n\ninline double CoreFunction::dfCOS(double x) const\n{\n    return -PI_2 * sin(PI * x);\n}\n\ninline void CoreFunction::fdfCOS(double x, double& fx, double& dfx) const\n{\n    double const temp = cos(PI * x);\n    fx = 0.5 * (temp + 1.0);\n    dfx = -0.5 * PI * sqrt(1.0 - temp * temp);\n    return;\n}\n\ninline double CoreFunction::fPOLY1(double x) const\n{\n    return (2.0 * x - 3.0) * x * x + 1.0;\n}\n\ninline double CoreFunction::dfPOLY1(double x) const\n{\n    return x * (6.0 * x - 6.0);\n}\n\ninline void CoreFunction::fdfPOLY1(double x, double& fx, double& dfx) const\n{\n    fx = (2.0 * x - 3.0) * x * x + 1.0;\n    dfx = x * (6.0 * x - 6.0);\n    return;\n}\n\ninline double CoreFunction::fPOLY2(double x) const\n{\n    return ((15.0 - 6.0 * x) * x - 10.0) * x * x * x + 1.0;\n}\n\ninline double CoreFunction::dfPOLY2(double x) const\n{\n    return x * x * ((60.0 - 30.0 * x) * x - 30.0);\n}\n\ninline void CoreFunction::fdfPOLY2(double x, double& fx, double& dfx) const\n{\n    double const x2 = x * x;\n    fx = ((15.0 - 6.0 * x) * x - 10.0) * x * x2 + 1.0;\n    dfx = x2 * ((60.0 - 30.0 * x) * x - 30.0);\n    return;\n}\n\ninline double CoreFunction::fPOLY3(double x) const\n{\n    double const x2 = x * x;\n    return (x * (x * (20.0 * x - 70.0) + 84.0) - 35.0) * x2 * x2 + 1.0;\n}\n\ninline double CoreFunction::dfPOLY3(double x) const\n{\n    return x * x * x * (x * (x * (140.0 * x - 420.0) + 420.0) - 140.0);\n}\n\ninline void CoreFunction::fdfPOLY3(double x, double& fx, double& dfx) const\n{\n    double const x2 = x * x;\n    fx = (x * (x * (20.0 * x - 70.0) + 84.0) - 35.0) * x2 * x2 + 1.0;\n    dfx = x2 * x * (x * (x * (140.0 * x - 420.0) + 420.0) - 140.0);\n    return;\n}\n\ninline double CoreFunction::fPOLY4(double x) const\n{\n    double const x2 = x * x;\n    return (x * (x * ((315.0 - 70.0 * x) * x - 540.0) + 420.0) - 126.0) *\n           x2 * x2 * x + 1.0;\n}\n\ninline double CoreFunction::dfPOLY4(double x) const\n{\n    double const x2 = x * x;\n    return x2 * x2 *\n           (x * (x * ((2520.0 - 630.0 * x) * x - 3780.0) + 2520.0) - 630.0);\n}\n\ninline void CoreFunction::fdfPOLY4(double x, double& fx, double& dfx) const\n{\n    double x4 = x * x;\n    x4 *= x4;\n    fx = (x * (x * ((315.0 - 70.0 * x) * x - 540.0) + 420.0) - 126.0) *\n         x * x4 + 1.0;\n    dfx = x4 *\n          (x * (x * ((2520.0 - 630.0 * x) * x - 3780.0) + 2520.0) - 630.0);\n    return;\n}\n\ninline double CoreFunction::fEXP(double x) const\n{\n    return E * exp(1.0 / (x * x - 1.0));\n}\n\ninline double CoreFunction::dfEXP(double x) const\n{\n    double const temp = 1.0 / (x * x - 1.0);\n    return -2.0 * E * x * temp * temp * exp(temp);\n}\n\ninline void CoreFunction::fdfEXP(double x, double& fc, double& dfc) const\n{\n    double const temp = 1.0 / (x * x - 1.0);\n    double const temp2 = exp(temp);\n    fc = E * temp2;\n    dfc = -2.0 * E * x * temp * temp * temp2;\n    return;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/CutoffFunction.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"CutoffFunction.h\"\n#include <stdexcept>\n#include <cmath>  // cos, sin, tanh, exp, pow\n#include <limits> // std::numeric_limits\n\nusing namespace std;\nusing namespace nnp;\n\ndouble const CutoffFunction::PI = 4.0 * atan(1.0);\ndouble const CutoffFunction::PI_2 = 2.0 * atan(1.0);\ndouble const CutoffFunction::E = exp(1.0);\ndouble const CutoffFunction::TANH_PRE = pow((E + 1 / E) / (E - 1 / E), 3);\n\nCutoffFunction::CutoffFunction() : cutoffType(CT_HARD                 ),\n                                   rc        (0.0                     ),\n                                   rcinv     (0.0                     ),\n                                   rci       (0.0                     ),\n                                   alpha     (0.0                     ),\n                                   iw        (0.0                     ),\n                                   fPtr      (&CutoffFunction::  fHARD),\n                                   dfPtr     (&CutoffFunction:: dfHARD),\n                                   fdfPtr    (&CutoffFunction::fdfHARD)\n{\n}\n\nvoid CutoffFunction::setCutoffType(CutoffType const cutoffType)\n{\n    this->cutoffType = cutoffType;\n\n    if (cutoffType == CT_HARD)\n    {\n          fPtr = &CutoffFunction::  fHARD;\n         dfPtr = &CutoffFunction:: dfHARD;\n        fdfPtr = &CutoffFunction::fdfHARD;\n    }\n    else if (cutoffType == CT_COS)\n    {\n          fPtr = &CutoffFunction::  fCOS;\n         dfPtr = &CutoffFunction:: dfCOS;\n        fdfPtr = &CutoffFunction::fdfCOS;\n    }\n    else if (cutoffType == CT_TANHU)\n    {\n          fPtr = &CutoffFunction::  fTANHU;\n         dfPtr = &CutoffFunction:: dfTANHU;\n        fdfPtr = &CutoffFunction::fdfTANHU;\n    }\n    else if (cutoffType == CT_TANH)\n    {\n          fPtr = &CutoffFunction::  fTANH;\n         dfPtr = &CutoffFunction:: dfTANH;\n        fdfPtr = &CutoffFunction::fdfTANH;\n    }\n    else if (cutoffType == CT_POLY1 ||\n             cutoffType == CT_POLY2 ||\n             cutoffType == CT_POLY3 ||\n             cutoffType == CT_POLY4 ||\n             cutoffType == CT_EXP)\n    {\n        using CFT = CoreFunction::Type;\n        if      (cutoffType == CT_POLY1) core.setType(CFT::POLY1);\n        else if (cutoffType == CT_POLY2) core.setType(CFT::POLY2);\n        else if (cutoffType == CT_POLY3) core.setType(CFT::POLY3);\n        else if (cutoffType == CT_POLY4) core.setType(CFT::POLY4);\n        else if (cutoffType == CT_EXP)   core.setType(CFT::EXP);\n\n          fPtr = &CutoffFunction::  fCORE;\n         dfPtr = &CutoffFunction:: dfCORE;\n        fdfPtr = &CutoffFunction::fdfCORE;\n    }\n    else\n    {\n        throw invalid_argument(\"ERROR: Unknown cutoff type.\\n\");\n    }\n\n    return;\n}\n\nvoid CutoffFunction::setCutoffRadius(double const cutoffRadius)\n{\n    rc = cutoffRadius;\n    rcinv = 1.0 / cutoffRadius;\n    return;\n}\n\nvoid CutoffFunction::setCutoffParameter(double const alpha)\n{\n    if (alpha < 0.0 || alpha >= 1.0)\n    {\n        throw invalid_argument(\"ERROR: 0 <= alpha < 1.0 is required.\\n\");\n    }\n    this->alpha = alpha;\n    rci = rc * alpha;\n    iw = 1.0 / (rc - rci);\n    return;\n}\n\ndouble CutoffFunction::fCOS(double r) const\n{\n    if (r < rci) return 1.0;\n    double const x = (r - rci) * iw;\n    return 0.5 * (cos(PI * x) + 1.0);\n}\n\ndouble CutoffFunction::dfCOS(double r) const\n{\n    if (r < rci) return 0.0;\n    double const x = (r - rci) * iw;\n    return -PI_2 * iw * sin(PI * x);\n}\n\nvoid CutoffFunction::fdfCOS(double r, double& fc, double& dfc) const\n{\n    if (r < rci)\n    {\n        fc = 1.0;\n        dfc = 0.0;\n        return;\n    }\n    double const x = (r - rci) * iw;\n    double const temp = cos(PI * x);\n    fc = 0.5 * (temp + 1.0);\n    dfc = -0.5 * iw * PI * sqrt(1.0 - temp * temp);\n    return;\n}\n\ndouble CutoffFunction::fTANHU(double r) const\n{\n    double const temp = tanh(1.0 - r * rcinv);\n    return temp * temp * temp;\n}\n\ndouble CutoffFunction::dfTANHU(double r) const\n{\n    double temp = tanh(1.0 - r * rcinv);\n    temp *= temp;\n    return 3.0 * temp * (temp - 1.0) * rcinv;\n}\n\nvoid CutoffFunction::fdfTANHU(double r, double& fc, double& dfc) const\n{\n    double const temp = tanh(1.0 - r * rcinv);\n    double const temp2 = temp * temp;\n    fc = temp * temp2;\n    dfc = 3.0 * temp2 * (temp2 - 1.0) * rcinv;\n    return;\n}\n\ndouble CutoffFunction::fTANH(double r) const\n{\n    double const temp = tanh(1.0 - r * rcinv);\n    return TANH_PRE * temp * temp * temp;\n}\n\ndouble CutoffFunction::dfTANH(double r) const\n{\n    double temp = tanh(1.0 - r * rcinv);\n    temp *= temp;\n    return 3.0 * TANH_PRE * temp * (temp - 1.0) * rcinv;\n}\n\nvoid CutoffFunction::fdfTANH(double r, double& fc, double& dfc) const\n{\n    double const temp = tanh(1.0 - r * rcinv);\n    double const temp2 = temp * temp;\n    fc = TANH_PRE * temp * temp2;\n    dfc = 3.0 * TANH_PRE * temp2 * (temp2 - 1.0) * rcinv;\n    return;\n}\n\ndouble CutoffFunction::fCORE(double r) const\n{\n    if (r < rci) return 1.0;\n    double const x = (r - rci) * iw;\n    return core.f(x);\n}\n\ndouble CutoffFunction::dfCORE(double r) const\n{\n    if (r < rci) return 0.0;\n    double const x = (r - rci) * iw;\n    return iw * core.df(x);\n}\n\nvoid CutoffFunction::fdfCORE(double r, double& fc, double& dfc) const\n{\n    if (r < rci)\n    {\n        fc = 1.0;\n        dfc = 0.0;\n        return;\n    }\n    double const x = (r - rci) * iw;\n    core.fdf(x, fc, dfc);\n    dfc *= iw;\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/CutoffFunction.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef CUTOFFFUNCTION_H\n#define CUTOFFFUNCTION_H\n\n#include \"CoreFunction.h\"\n\nnamespace nnp\n{\n\nclass CutoffFunction\n{\npublic:\n    /** List of available cutoff function types.\n     *\n     * Most cutoff types allow the definition of an inner cutoff\n     * @f$ r_{ci} := \\alpha \\, r_c@f$. Then the cutoff is equal to @f$1@f$ up\n     * to the inner cutoff:\n     *\n     * @f$ f_c(r) =\n     * \\begin{cases}\n     * 1, & \\text{for } 0 \\le r < r_{ci} \\\\\n     * f(x), & \\text{for } r_{ci} \\le r < r_c \\text{ where }\n     * x := \\frac{r - r_{ci}}{r_c - r_{ci}} \\\\\n     * 0 & \\text{for } r \\geq r_c\n     * \\end{cases} @f$\n     */\n    enum CutoffType\n    {\n        /** @f$f(x) = 1@f$\n         */\n        CT_HARD,\n        /** @f$f(x) = \\frac{1}{2} \\left[ \\cos (\\pi x) + 1\\right] @f$\n         */\n        CT_COS,\n        /** @f$f_c(r) = \\tanh^3 \\left(1 - \\frac{r}{r_c} \\right) @f$\n         */\n        CT_TANHU,\n        /** @f$f_c(r) = c \\tanh^3 \\left(1 - \\frac{r}{r_c} \\right),\\,\n         *  f(0) = 1 @f$\n         */\n        CT_TANH,\n        /** @f$f(x) = e^{1 - \\frac{1}{1 - x^2}}@f$\n         */\n        CT_EXP,\n        /** @f$f(x) = (2x - 3)x^2 + 1@f$\n         */\n        CT_POLY1,\n        /** @f$f(x) = ((15 - 6x)x - 10) x^3 + 1@f$\n         */\n        CT_POLY2,\n        /** @f$f(x) = (x(x(20x - 70) + 84) - 35)x^4 + 1@f$\n         */\n        CT_POLY3,\n        /** @f$f(x) = (x(x((315 - 70x)x - 540) + 420) - 126)x^5 + 1@f$\n         */\n        CT_POLY4\n    };\n\n    /** Constructor, initializes to ´CT_HARD´.\n     */\n    CutoffFunction();\n    /** Set cutoff type.\n     *\n     * @param[in] cutoffType Type of cutoff used.\n     */\n    void       setCutoffType(CutoffType const cutoffType);\n    /** Getter for #cutoffType.\n     *\n     * @return CutoffType used.\n     */\n    CutoffType getCutoffType() const;\n    /** Set cutoff radius.\n     *\n     * @param[in] cutoffRadius Cutoff radius @f$r_c@f$.\n     */\n    void       setCutoffRadius(double const cutoffRadius);\n    /** Getter for #rc.\n     *\n     * @return Cutoff radius used.\n     */\n    double     getCutoffRadius() const;\n    /** Set parameter for polynomial cutoff function (CT_POLY).\n     *\n     * @param[in] alpha Width parameter @f$\\alpha@f$.\n     */\n    void       setCutoffParameter(double const alpha);\n    /** Getter for #alpha.\n     *\n     * @return Cutoff parameter used.\n     */\n    double     getCutoffParameter() const;\n    /** Cutoff function @f$f_c@f$.\n     *\n     * @param[in] r Distance.\n     * @return Cutoff function value.\n     */\n    double     f(double r) const;\n    /** Derivative of cutoff function @f$\\frac{d f_c}{d r}@f$.\n     *\n     * @param[in] r Distance.\n     * @return Value of cutoff function derivative.\n     */\n    double     df(double r) const;\n    /** Calculate cutoff function @f$f_c@f$ and derivative\n     * @f$\\frac{d f_c}{d r}@f$.\n     *\n     * @param[in] r Distance.\n     * @param[out] fc Cutoff function value.\n     * @param[out] dfc Value of cutoff function derivative.\n     */\n    void       fdf(double r, double& fc, double& dfc) const;\n\nprivate:\n    static double const PI;\n    static double const PI_2;\n    static double const E;\n    static double const TANH_PRE;\n\n    /// Cutoff function type.\n    CutoffType   cutoffType;\n    /// Outer cutoff radius @f$r_c@f$.\n    double       rc;\n    /// Inverse cutoff radius @f$\\frac{1}{r_c}@f$.\n    double       rcinv;\n    /// Inner cutoff for cutoff function types which allow shifting.\n    double       rci;\n    /// Cutoff function parameter for `CT_POLYn` and `CT_EXP` @f$\\alpha@f$.\n    double       alpha;\n    /// Inverse width of cutoff function @f$\\frac{1}{r_c - r_{ci}}@f$.\n    double       iw;\n    /// Core functions used by POLYN, if any.\n    CoreFunction core;\n    /// Function pointer to f.\n    double       (CutoffFunction::*fPtr)(double r) const;\n    /// Function pointer to df.\n    double       (CutoffFunction::*dfPtr)(double r) const;\n    /// Function pointer to fdf.\n    void         (CutoffFunction::*fdfPtr)(double  r,\n                                           double& fc,\n                                           double& dfc) const;\n\n    // Individual cutoff functions.\n    double   fHARD (double r) const;\n    double  dfHARD (double r) const;\n    void   fdfHARD (double r, double& fc, double& dfc) const;\n\n    double   fCOS  (double r) const;\n    double  dfCOS  (double r) const;\n    void   fdfCOS  (double r, double& fc, double& dfc) const;\n\n    double   fTANHU(double r) const;\n    double  dfTANHU(double r) const;\n    void   fdfTANHU(double r, double& fc, double& dfc) const;\n\n    double   fTANH (double r) const;\n    double  dfTANH (double r) const;\n    void   fdfTANH (double r, double& fc, double& dfc) const;\n\n    double   fCORE (double r) const;\n    double  dfCORE (double r) const;\n    void   fdfCORE (double r, double& fc, double& dfc) const;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline CutoffFunction::CutoffType CutoffFunction::getCutoffType() const\n{\n    return cutoffType;\n}\n\ninline double CutoffFunction::getCutoffRadius() const\n{\n    return rc;\n}\n\ninline double CutoffFunction::getCutoffParameter() const\n{\n    return alpha;\n}\n\ninline double CutoffFunction::f(double r) const\n{\n    if (r >= rc) return 0.0;\n    return (this->*fPtr)(r);\n}\n\ninline double CutoffFunction::df(double r) const\n{\n    if (r >= rc) return 0.0;\n    return (this->*dfPtr)(r);\n}\n\ninline void CutoffFunction::fdf(double r, double& fc, double& dfc) const\n{\n    if (r >= rc)\n    {\n        fc = 0.0;\n        dfc = 0.0;\n        return;\n    }\n    (this->*fdfPtr)(r, fc, dfc);\n    return;\n}\n\ninline double CutoffFunction::fHARD(double /*r*/) const\n{\n    return 1.0;\n}\n\ninline double CutoffFunction::dfHARD(double /*r*/) const\n{\n    return 0.0;\n}\n\ninline void CutoffFunction::fdfHARD(double /*r*/,\n                                    double& fc,\n                                    double& dfc) const\n{\n    fc = 1.0;\n    dfc = 0.0;\n    return;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/Element.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Atom.h\"\n#include \"Element.h\"\n#include \"NeuralNetwork.h\"\n#include \"SymFnc.h\"\n#include \"SymFncBaseCutoff.h\"\n#include \"SymFncExpRad.h\"\n#include \"SymFncCompRad.h\"\n#include \"SymFncExpAngn.h\"\n#include \"SymFncExpAngw.h\"\n#include \"SymFncCompAngw.h\"\n#include \"SymFncCompAngn.h\"\n#include \"SymFncExpRadWeighted.h\"\n#include \"SymFncExpAngnWeighted.h\"\n#include \"SymFncCompRadWeighted.h\"\n#include \"SymFncCompAngnWeighted.h\"\n#include \"SymFncCompAngwWeighted.h\"\n#include \"SymGrp.h\"\n#include \"SymGrpExpRad.h\"\n#include \"SymGrpCompRad.h\"\n#include \"SymGrpExpAngn.h\"\n#include \"SymGrpExpAngw.h\"\n#include \"SymGrpCompAngw.h\"\n#include \"SymGrpCompAngn.h\"\n#include \"SymGrpExpRadWeighted.h\"\n#include \"SymGrpExpAngnWeighted.h\"\n#include \"SymGrpCompRadWeighted.h\"\n#include \"SymGrpCompAngnWeighted.h\"\n#include \"SymGrpCompAngwWeighted.h\"\n#include \"utility.h\"\n#include <iostream>  // std::cerr\n#include <cinttypes> // PRId64\n#include <cstdlib>   // atoi\n#include <algorithm> // std::sort, std::min, std::max\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nElement::Element(size_t const index, ElementMap const& elementMap) :\n    elementMap         (elementMap                    ),\n    index              (index                         ),\n    atomicNumber       (elementMap.atomicNumber(index)),\n    atomicEnergyOffset (0.0                           ),\n    hardness           (0.0                           ),\n    qsigma             (0.0                           ),\n    symbol             (elementMap.symbol(index)      )\n{\n}\n\nElement::~Element()\n{\n    clearSymmetryFunctions();\n}\n\nvoid Element::clearSymmetryFunctions()\n{\n    for (auto& s : symmetryFunctions) delete s;\n    symmetryFunctions.clear();\n    for (auto& s : symmetryFunctionGroups) delete s;\n    symmetryFunctionGroups.clear();\n\n    return;\n}\n\nvoid Element::addSymmetryFunction(string const& parameters,\n                                  size_t const& lineNumber)\n{\n    vector<string> args = split(reduce(parameters));\n    size_t         type = (size_t)atoi(args.at(1).c_str());\n\n    if (type == 2)\n    {\n        symmetryFunctions.push_back(new SymFncExpRad(elementMap));\n    }\n    else if (type == 3)\n    {\n        symmetryFunctions.push_back(new SymFncExpAngn(elementMap));\n    }\n    else if (type == 9)\n    {\n        symmetryFunctions.push_back(new SymFncExpAngw(elementMap));\n    }\n    else if (type == 12)\n    {\n        symmetryFunctions.push_back(new SymFncExpRadWeighted(elementMap));\n    }\n    else if (type == 13)\n    {\n        symmetryFunctions.push_back(new SymFncExpAngnWeighted(elementMap));\n    }\n    else if (type == 20)\n    {\n        symmetryFunctions.push_back(new SymFncCompRad(elementMap));\n    }\n    else if (type == 21)\n    {\n        symmetryFunctions.push_back(new SymFncCompAngn(elementMap));\n    }\n    else if (type == 22)\n    {\n        symmetryFunctions.push_back(new SymFncCompAngw(elementMap));\n    }\n    else if (type == 23)\n    {\n        symmetryFunctions.push_back(new SymFncCompRadWeighted(elementMap));\n    }\n    else if (type == 24)\n    {\n        symmetryFunctions.push_back(new SymFncCompAngnWeighted(elementMap));\n    }\n    else if (type == 25)\n    {\n        symmetryFunctions.push_back(new SymFncCompAngwWeighted(elementMap));\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown symmetry function type.\\n\");\n    }\n\n    symmetryFunctions.back()->setParameters(parameters);\n    symmetryFunctions.back()->setLineNumber(lineNumber);\n\n    return;\n}\n\nvoid Element::changeLengthUnitSymmetryFunctions(double convLength)\n{\n    for (vector<SymFnc*>::iterator it = symmetryFunctions.begin();\n         it != symmetryFunctions.end(); ++it)\n    {\n        (*it)->changeLengthUnit(convLength);\n    }\n\n    return;\n}\n\nvoid Element::sortSymmetryFunctions()\n{\n    sort(symmetryFunctions.begin(),\n         symmetryFunctions.end(),\n         comparePointerTargets<SymFnc>);\n\n    for (size_t i = 0; i < symmetryFunctions.size(); ++i)\n    {\n        symmetryFunctions.at(i)->setIndex(i);\n    }\n\n    return;\n}\n\nvector<string> Element::infoSymmetryFunctionParameters() const\n{\n    vector<string> v;\n\n    for (vector<SymFnc*>::const_iterator\n         sf = symmetryFunctions.begin(); sf != symmetryFunctions.end(); ++sf)\n    {\n        v.push_back((*sf)->parameterLine());\n    }\n\n    return v;\n}\n\nvector<string> Element::infoSymmetryFunctionScaling() const\n{\n    vector<string> v;\n\n    for (vector<SymFnc*>::const_iterator\n         sf = symmetryFunctions.begin(); sf != symmetryFunctions.end(); ++sf)\n    {\n        v.push_back((*sf)->scalingLine());\n    }\n\n    return v;\n}\n\nvoid Element::setupSymmetryFunctionGroups()\n{\n    for (vector<SymFnc*>::const_iterator\n         sf = symmetryFunctions.begin(); sf != symmetryFunctions.end(); ++sf)\n    {\n        bool createNewGroup = true;\n        for (vector<SymGrp*>::const_iterator\n             sfg = symmetryFunctionGroups.begin();\n             sfg != symmetryFunctionGroups.end(); ++sfg)\n        {\n            if ((*sfg)->addMember((*sf)))\n            {\n                createNewGroup = false;\n                break;\n            }\n        }\n        if (createNewGroup)\n        {\n            if ((*sf)->getType() == 2)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpExpRad(elementMap));\n            }\n            else if ((*sf)->getType() == 3)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpExpAngn(elementMap));\n            }\n            else if ((*sf)->getType() == 9)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpExpAngw(elementMap));\n            }\n            else if ((*sf)->getType() == 12)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpExpRadWeighted(elementMap));\n            }\n            else if ((*sf)->getType() == 13)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpExpAngnWeighted(elementMap));\n            }\n            else if ((*sf)->getType() == 20)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpCompRad(elementMap));\n            }\n            else if ((*sf)->getType() == 21)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpCompAngn(elementMap));\n            }\n            else if ((*sf)->getType() == 22)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpCompAngw(elementMap));\n            }\n            else if ((*sf)->getType() == 23)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpCompRadWeighted(elementMap));\n            }\n            else if ((*sf)->getType() == 24)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpCompAngnWeighted(elementMap));\n            }\n            else if ((*sf)->getType() == 25)\n            {\n                symmetryFunctionGroups.push_back((SymGrp*)\n                    new SymGrpCompAngwWeighted(elementMap));\n            }\n            else\n            {\n                throw runtime_error(\"ERROR: Unknown symmetry function group\"\n                                    \" type.\\n\");\n            }\n            symmetryFunctionGroups.back()->addMember(*sf);\n        }\n    }\n\n    sort(symmetryFunctionGroups.begin(),\n         symmetryFunctionGroups.end(),\n         comparePointerTargets<SymGrp>);\n\n    for (size_t i = 0; i < symmetryFunctionGroups.size(); ++i)\n    {\n        symmetryFunctionGroups.at(i)->sortMembers();\n        symmetryFunctionGroups.at(i)->setIndex(i);\n    }\n\n    return;\n}\n\nvoid Element::setupSymmetryFunctionMemory()\n{\n    symmetryFunctionTable.clear();\n    symmetryFunctionTable.resize(elementMap.size());\n    for (auto const& s : symmetryFunctions)\n    {\n        for (size_t i = 0; i < elementMap.size(); ++i)\n        {\n            if (s->checkRelevantElement(i))\n            {\n                s->setIndexPerElement(i, symmetryFunctionTable.at(i).size());\n                symmetryFunctionTable.at(i).push_back(s->getIndex());\n            }\n        }\n    }\n    symmetryFunctionNumTable.clear();\n    for (size_t i = 0; i < elementMap.size(); ++i)\n    {\n        symmetryFunctionNumTable.push_back(symmetryFunctionTable.at(i).size());\n    }\n\n    return;\n}\n\nvector<string> Element::infoSymmetryFunctionGroups() const\n{\n    vector<string> v;\n\n    for (vector<SymGrp*>::const_iterator\n         it = symmetryFunctionGroups.begin();\n         it != symmetryFunctionGroups.end(); ++it)\n    {\n        vector<string> lines = (*it)->parameterLines();\n        v.insert(v.end(), lines.begin(), lines.end());\n    }\n\n    return v;\n}\n\nvoid Element::setCutoffFunction(CutoffFunction::CutoffType const cutoffType,\n                                double const                     cutoffAlpha)\n{\n    for (vector<SymFnc*>::const_iterator\n         it = symmetryFunctions.begin(); it != symmetryFunctions.end(); ++it)\n    {\n        SymFncBaseCutoff* sfcb = dynamic_cast<SymFncBaseCutoff*>(*it);\n        if (sfcb != nullptr)\n        {\n            sfcb->setCutoffFunction(cutoffType, cutoffAlpha);\n        }\n    }\n\n    return;\n}\n\nvoid Element::setScalingNone() const\n{\n    for (size_t i = 0; i < symmetryFunctions.size(); ++i)\n    {\n        string scalingLine = strpr(\"%d %d 0.0 0.0 0.0 0.0\",\n                                   symmetryFunctions.at(i)->getEc(),\n                                   i + 1);\n        symmetryFunctions.at(i)->setScalingType(SymFnc::ST_NONE,\n                                                scalingLine,\n                                                0.0,\n                                                0.0);\n    }\n    for (size_t i = 0; i < symmetryFunctionGroups.size(); ++i)\n    {\n        symmetryFunctionGroups.at(i)->setScalingFactors();\n    }\n    \n    return;\n}\n\nvoid Element::setScaling(SymFnc::ScalingType scalingType,\n                         vector<string> const&         statisticsLine,\n                         double                        Smin,\n                         double                        Smax) const\n{\n    for (size_t i = 0; i < symmetryFunctions.size(); ++i)\n    {\n        symmetryFunctions.at(i)->setScalingType(scalingType,\n                                                statisticsLine.at(i),\n                                                Smin,\n                                                Smax);\n    }\n    for (size_t i = 0; i < symmetryFunctionGroups.size(); ++i)\n    {\n        symmetryFunctionGroups.at(i)->setScalingFactors();\n    }\n\n    return;\n}\n\nsize_t Element::getMinNeighbors() const\n{\n    size_t minNeighbors = 0;\n\n    for (vector<SymFnc*>::const_iterator\n         it = symmetryFunctions.begin(); it != symmetryFunctions.end(); ++it)\n    {\n        minNeighbors = max((*it)->getMinNeighbors(), minNeighbors);\n    }\n\n    return minNeighbors;\n}\n\ndouble Element::getMinCutoffRadius() const\n{\n    double minCutoffRadius = numeric_limits<double>::max();\n\n    // MPB: Hack to work with negative radii\n    //      Exploit the fact that all allowed symmetry functions are either\n    //      defined for a domain > 0 or have to be symmetric around 0.\n\n    for (vector<SymFnc*>::const_iterator\n         it = symmetryFunctions.begin(); it != symmetryFunctions.end(); ++it)\n    {\n        minCutoffRadius = min((*it)->getRc(), minCutoffRadius);\n    }\n\n    return minCutoffRadius;\n}\n\ndouble Element::getMaxCutoffRadius() const\n{\n    double maxCutoffRadius = 0.0;\n\n    for (vector<SymFnc*>::const_iterator\n         it = symmetryFunctions.begin(); it != symmetryFunctions.end(); ++it)\n    {\n        maxCutoffRadius = max((*it)->getRc(), maxCutoffRadius);\n    }\n\n    return maxCutoffRadius;\n}\n\nvoid Element::getCutoffRadii(std::vector<double>& cutoffs) const\n{\n    for (auto const& sf : symmetryFunctions)\n    {\n        double rc = sf->getRc();\n        if (!vectorContains(cutoffs,rc)) cutoffs.push_back(rc);\n    }\n}\n\nvoid Element::calculateSymmetryFunctions(Atom&      atom,\n                                         bool const derivatives) const\n{\n    for (vector<SymFnc*>::const_iterator\n         it = symmetryFunctions.begin();\n         it != symmetryFunctions.end(); ++it)\n    {\n        (*it)->calculate(atom, derivatives);\n    }\n\n    return;\n}\n\nvoid Element::calculateSymmetryFunctionGroups(Atom&      atom,\n                                              bool const derivatives) const\n{\n    for (vector<SymGrp*>::const_iterator\n         it = symmetryFunctionGroups.begin();\n         it != symmetryFunctionGroups.end(); ++it)\n    {\n        (*it)->calculate(atom, derivatives);\n    }\n\n    return;\n}\n\nsize_t Element::updateSymmetryFunctionStatistics(Atom const& atom)\n{\n    size_t countExtrapolationWarnings = 0;\n    double epsilon = 1000.0 * numeric_limits<double>::epsilon();\n\n    if (atom.element != index)\n    {\n        throw runtime_error(\"ERROR: Atom has a different element index.\\n\");\n    }\n\n    if (atom.numSymmetryFunctions != symmetryFunctions.size())\n    {\n        throw runtime_error(\"ERROR: Number of symmetry functions\"\n                            \" does not match.\\n\");\n    }\n\n    for (size_t i = 0; i < atom.G.size(); ++i)\n    {\n        double const Gmin = symmetryFunctions.at(i)->getGmin();\n        double const Gmax = symmetryFunctions.at(i)->getGmax();\n        double const value = symmetryFunctions.at(i)->unscale(atom.G.at(i));\n        size_t const sfindex = symmetryFunctions.at(i)->getIndex();\n        size_t const type = symmetryFunctions.at(i)->getType();\n        if (statistics.collectStatistics)\n        {\n            statistics.addValue(sfindex, atom.G.at(i));\n        }\n\n        // Avoid \"fake\" EWs at the boundaries.\n        if (value + epsilon < Gmin || value - epsilon > Gmax)\n        {\n            countExtrapolationWarnings++;\n            if (statistics.collectExtrapolationWarnings)\n            {\n                statistics.addExtrapolationWarning(sfindex,\n                                                   type,\n                                                   value,\n                                                   Gmin,\n                                                   Gmax,\n                                                   symbol,\n                                                   atom.indexStructure,\n                                                   atom.tag);\n            }\n            if (statistics.writeExtrapolationWarnings)\n            {\n                cerr << strpr(\"### NNP EXTRAPOLATION WARNING ### \"\n                              \"STRUCTURE: %6zu ATOM: %9\" PRId64 \" ELEMENT: \"\n                              \"%2s SYMFUNC: %4zu TYPE: %2zu VALUE: %10.3E \"\n                              \"MIN: %10.3E MAX: %10.3E\\n\",\n                              atom.indexStructure,\n                              atom.tag,\n                              symbol.c_str(),\n                              sfindex + 1,\n                              type,\n                              value,\n                              Gmin,\n                              Gmax);\n            }\n            if (statistics.stopOnExtrapolationWarnings)\n            {\n                throw out_of_range(\n                        strpr(\"### NNP EXTRAPOLATION WARNING ### \"\n                              \"STRUCTURE: %6zu ATOM: %9\" PRId64 \" ELEMENT: \"\n                              \"%2s SYMFUNC: %4zu TYPE: %2zu VALUE: %10.3E \"\n                              \"MIN: %10.3E MAX: %10.3E\\n\"\n                              \"ERROR: Symmetry function value out of range.\\n\",\n                              atom.indexStructure,\n                              atom.tag,\n                              symbol.c_str(),\n                              sfindex + 1,\n                              type,\n                              value,\n                              Gmin,\n                              Gmax));\n            }\n        }\n    }\n\n    return countExtrapolationWarnings;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvoid Element::setCacheIndices(vector<vector<SFCacheList>> cacheLists)\n{\n    this->cacheLists = cacheLists;\n    for (size_t i = 0; i < cacheLists.size(); ++i)\n    {\n        for (size_t j = 0; j < cacheLists.at(i).size(); ++j)\n        {\n            SFCacheList const& c = cacheLists.at(i).at(j);\n            for (size_t k = 0; k < c.indices.size(); ++k)\n            {\n                SymFnc*& sf = symmetryFunctions.at(c.indices.at(k));\n                sf->addCacheIndex(c.element, j, c.identifier);\n            }\n        }\n    }\n\n    return;\n}\n\nvector<size_t> Element::getCacheSizes() const\n{\n    vector<size_t> cacheSizes;\n    for (auto const& c : cacheLists)\n    {\n        cacheSizes.push_back(c.size());\n    }\n\n    return cacheSizes;\n}\n#endif\n"
  },
  {
    "path": "src/libnnp/Element.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef ELEMENT_H\n#define ELEMENT_H\n\n#include \"CutoffFunction.h\"\n#include \"ElementMap.h\"\n#include \"NeuralNetwork.h\"\n#include \"SymFnc.h\"\n#include \"SymFncStatistics.h\"\n#include <cstddef> // std::size_t\n#include <map>     // std::map\n#include <string>  // std::string\n#include <utility> // std::pair\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass SymGrp;\n\n/// Contains element-specific data.\nclass Element\n{\npublic:\n\n#ifndef N2P2_NO_SF_CACHE\n    /// List of symmetry functions corresponding to one cache identifier.\n    struct SFCacheList\n    {\n        /// Neighbor element index.\n        std::size_t              element;\n        /// Cache identifier string.\n        std::string              identifier;\n        /// Symmetry function indices for this cache.\n        std::vector<std::size_t> indices;\n    };\n#endif\n\n    /** Default constructor\n     */\n    Element() {}\n    /** Constructor using index.\n     */\n    Element(std::size_t const index, ElementMap const& elementMap);\n    /** Destructor.\n     *\n     * Necessary because of #symmetryFunctions vector of pointers.\n     */\n    virtual ~Element();\n    /** Clear all symmetry functions and groups.\n     */\n    void                     clearSymmetryFunctions();\n    /** Set #atomicEnergyOffset.\n     */\n    void                     setAtomicEnergyOffset(double atomicEnergyOffset);\n    /** Set #hardness.\n     */\n    void                     setHardness(double hardness);\n    /** Set #qsigma.\n     */\n    void                     setQsigma(double qsigma);\n    /** Get #index.\n     */\n    std::size_t              getIndex() const;\n    /** Get #atomicNumber.\n     */\n    std::size_t              getAtomicNumber() const;\n    /** Get #atomicEnergyOffset.\n     */\n    double                   getAtomicEnergyOffset() const;\n    /** Get #hardness.\n     */\n    double                   getHardness() const;\n    /** Get #qsigma.\n     */\n    double                   getQsigma() const;\n    /** Get #symbol.\n     */\n    std::string              getSymbol() const;\n    /** Add one symmetry function.\n     *\n     * @param[in] parameters String containing settings for symmetry function.\n     * @param[in] lineNumber Line number of symmetry function in settings file.\n     */\n    void                     addSymmetryFunction(\n                                                std::string const& parameters,\n                                                std::size_t const& lineNumber);\n    /** Change length unit for all symmetry functions.\n     *\n     * @param[in] convLength Length unit conversion factor.\n     */\n    void                     changeLengthUnitSymmetryFunctions(\n                                                            double convLength);\n    /** Sort all symmetry function.\n     */\n    void                     sortSymmetryFunctions();\n    /** Print symmetry function parameter value information.\n     */\n    std::vector<std::string> infoSymmetryFunctionParameters() const;\n    /** Print symmetry function parameter names and values.\n     */\n    std::vector<std::string> infoSymmetryFunction(std::size_t index) const;\n    /** Print symmetry function scaling information.\n     */\n    std::vector<std::string> infoSymmetryFunctionScaling() const;\n    /** Set up symmetry function groups.\n     */\n    void                     setupSymmetryFunctionGroups();\n    /** Extract relevant symmetry function combinations for derivative memory.\n     */\n    void                     setupSymmetryFunctionMemory();\n    /** Print symmetry function group info.\n     */\n    std::vector<std::string> infoSymmetryFunctionGroups() const;\n    /** Set cutoff function for all symmetry functions.\n     *\n     * @param[in] cutoffType Type of cutoff function.\n     * @param[in] cutoffAlpha Cutoff parameter for all functions.\n     */\n    void                     setCutoffFunction(\n                                 CutoffFunction::CutoffType const cutoffType,\n                                 double const                     cutoffAlpha);\n    /** Set no scaling of symmetry function.\n     *\n     * Still scaling factors need to be initialized.\n     */\n    void                     setScalingNone() const;\n    /** Set scaling of all symmetry functions.\n     *\n     * @param[in] scalingType Type of scaling, see SymFnc::ScalingType.\n     * @param[in] statisticsLine Vector of strings containing statistics for\n     *                           all symmetry functions.\n     * @param[in] minS Minimum for scaling range.\n     * @param[in] maxS Maximum for scaling range.\n     */\n    void                     setScaling(\n                                SymFnc::ScalingType             scalingType,\n                                std::vector<std::string> const& statisticsLine,\n                                double                          minS,\n                                double                          maxS) const;\n    /** Get number of symmetry functions.\n     *\n     * @return Number of symmetry functions.\n     */\n    std::size_t              numSymmetryFunctions() const;\n    /** Get maximum of required minimum number of neighbors for all symmetry\n     * functions for this element.\n     *\n     * @return Minimum number of neighbors required.\n     */\n    std::size_t              getMinNeighbors() const;\n    /** Get minimum cutoff radius of all symmetry functions.\n     *\n     * @return Minimum cutoff radius.\n     */\n    double                   getMinCutoffRadius() const;\n    /** Get maximum cutoff radius of all symmetry functions.\n     *\n     * @return Maximum cutoff radius.\n     */\n    double                   getMaxCutoffRadius() const;\n    /** Get all different cutoff radii belonging to this element.\n     *\n     * @param[in] cutoffs Vector to append the result.\n     */\n    void                    getCutoffRadii(std::vector<double>& cutoffs) const;\n    /** Get number of relevant symmetry functions per element.\n     *\n     * @return #symmetryFunctionNumTable\n     */\n    std::vector<\n    std::size_t> const&      getSymmetryFunctionNumTable() const;\n    /** Get symmetry function element relevance table.\n     *\n     * @return #symmetryFunctionTable\n     */\n    std::vector<std::vector<\n    std::size_t>> const&     getSymmetryFunctionTable() const;\n    /** Calculate symmetry functions.\n     *\n     * @param[in] atom Atom whose symmetry functions are calculated.\n     * @param[in] derivatives If symmetry function derivatives will be\n     *                        calculated.\n     */\n    void                     calculateSymmetryFunctions(\n                                                 Atom&      atom,\n                                                 bool const derivatives) const;\n    /** Calculate symmetry functions via groups.\n     *\n     * @param[in] atom Atom whose symmetry functions are calculated.\n     * @param[in] derivatives If symmetry function derivatives will be\n     *                        calculated.\n     */\n    void                     calculateSymmetryFunctionGroups(\n                                                Atom&       atom,\n                                                bool const  derivatives) const;\n    /** Update symmetry function statistics.\n     *\n     * @param[in] atom Atom with symmetry function values.\n     *\n     * @return Number of extrapolation warnings encountered.\n     *\n     * This function checks also for extrapolation warnings.\n     */\n    std::size_t              updateSymmetryFunctionStatistics(\n                                                             Atom const& atom);\n    /** Get symmetry function instance.\n     *\n     * @param[in] index Symmetry function index.\n     *\n     * @return Symmetry function object.\n     */\n    SymFnc const&            getSymmetryFunction(std::size_t index) const;\n#ifndef N2P2_NO_SF_CACHE\n    /** Set cache indices for all symmetry functions of this element.\n     *\n     * @param[in] cacheLists List of cache identifier strings and corresponding\n     *                       SF indices for each neighbor element.\n     */\n    void                     setCacheIndices(\n                                         std::vector<\n                                         std::vector<SFCacheList>> cacheLists);\n    /** Get cache sizes for each neighbor atom element.\n     *\n     * @return Vector with cache sizes.\n     */\n    std::vector<std::size_t> getCacheSizes() const;\n#endif\n\n    /// Neural networks for this element.\n    std::map<std::string, NeuralNetwork> neuralNetworks;\n    /// Symmetry function statistics.\n    SymFncStatistics                     statistics;\n\nprotected:\n    /// Copy of element map.\n    ElementMap                            elementMap;\n    /// Global index of this element.\n    std::size_t                           index;\n    /// Atomic number of this element.\n    std::size_t                           atomicNumber;\n    /// Offset energy for every atom of this element.\n    double                                atomicEnergyOffset;\n    /// Atomic hardness for global charge equilibration.\n    double                                hardness;\n    /// Gaussian width of charge distribution.\n    double                                qsigma;\n    /// Element symbol.\n    std::string                           symbol;\n    /// Number of relevant symmetry functions for each neighbor element.\n    std::vector<std::size_t>              symmetryFunctionNumTable;\n    /// List of symmetry function indices relevant for each neighbor element.\n    std::vector<std::vector<std::size_t>> symmetryFunctionTable;\n#ifndef N2P2_NO_SF_CACHE\n    /// Symmetry function cache lists.\n    std::vector<std::vector<SFCacheList>> cacheLists;\n#endif\n    /// Vector of pointers to symmetry functions.\n    std::vector<SymFnc*>                  symmetryFunctions;\n    /// Vector of pointers to symmetry function groups.\n    std::vector<SymGrp*>                  symmetryFunctionGroups;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline void Element::setAtomicEnergyOffset(double atomicEnergyOffset)\n{\n    this->atomicEnergyOffset = atomicEnergyOffset;\n\n    return;\n}\n\ninline void Element::setHardness(double hardness)\n{\n    this->hardness = hardness;\n\n    return;\n}\n\ninline void Element::setQsigma(double qsigma)\n{\n    this->qsigma = qsigma;\n\n    return;\n}\n\ninline size_t Element::getIndex() const\n{\n    return index;\n}\n\ninline size_t Element::getAtomicNumber() const\n{\n    return atomicNumber;\n}\n\ninline double Element::getAtomicEnergyOffset() const\n{\n    return atomicEnergyOffset;\n}\n\ninline double Element::getHardness() const\n{\n    return hardness;\n}\n\ninline double Element::getQsigma() const\n{\n    return qsigma;\n}\n\ninline std::string Element::getSymbol() const\n{\n    return symbol;\n}\n\ninline std::vector<std::size_t> const&\nElement::getSymmetryFunctionNumTable() const\n{\n    return symmetryFunctionNumTable;\n}\n\ninline std::vector<std::vector<std::size_t>> const&\nElement::getSymmetryFunctionTable() const\n{\n    return symmetryFunctionTable;\n}\n\ninline\nstd::vector<std::string> Element::infoSymmetryFunction(std::size_t index) const\n{\n    return symmetryFunctions.at(index)->parameterInfo();\n}\n\ninline size_t Element::numSymmetryFunctions() const\n{\n    return symmetryFunctions.size();\n}\n\ninline SymFnc const& Element::getSymmetryFunction(\n                                                       std::size_t index) const\n{\n    return *(symmetryFunctions.at(index));\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/ElementMap.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nstring const ElementMap::knownElements[] = {\n\"H\" , \"He\", \"Li\", \"Be\", \"B\" , \"C\" , \"N\" , \"O\" , \"F\" , \"Ne\", \"Na\", \"Mg\", \"Al\",\n\"Si\", \"P\" , \"S\" , \"Cl\", \"Ar\", \"K\" , \"Ca\", \"Sc\", \"Ti\", \"V\" , \"Cr\", \"Mn\", \"Fe\",\n\"Co\", \"Ni\", \"Cu\", \"Zn\", \"Ga\", \"Ge\", \"As\", \"Se\", \"Br\", \"Kr\", \"Rb\", \"Sr\", \"Y\" ,\n\"Zr\", \"Nb\", \"Mo\", \"Tc\", \"Ru\", \"Rh\", \"Pd\", \"Ag\", \"Cd\", \"In\", \"Sn\", \"Sb\", \"Te\",\n\"I\" , \"Xe\", \"Cs\", \"Ba\", \"La\", \"Ce\", \"Pr\", \"Nd\", \"Pm\", \"Sm\", \"Eu\", \"Gd\", \"Tb\",\n\"Dy\", \"Ho\", \"Er\", \"Tm\", \"Yb\", \"Lu\", \"Hf\", \"Ta\", \"W\" , \"Re\", \"Os\", \"Ir\", \"Pt\",\n\"Au\", \"Hg\", \"Tl\", \"Pb\", \"Bi\", \"Po\", \"At\", \"Rn\", \"Fr\", \"Ra\", \"Ac\", \"Th\", \"Pa\",\n\"U\" , \"Np\", \"Pu\", \"Am\", \"Cm\", \"Bk\", \"Cf\", \"Es\", \"Fm\", \"Md\", \"No\"\n};\n\nsize_t ElementMap::registerElements(string const& elementLine)\n{\n    vector<string> elements = split(reduce(elementLine));\n\n    sort(elements.begin(), elements.end(), compareAtomicNumber);\n\n    if (!forwardMap.empty())\n    {\n        throw runtime_error(\"ERROR: Element map not empty.\\n\");\n    }\n\n    for (size_t i = 0; i < elements.size(); i++)\n    {\n        forwardMap[elements[i]] = i;\n        reverseMap[i] = elements[i];\n    }\n\n    return forwardMap.size();\n}\n\nstring ElementMap::getElementsString() const\n{\n    string elements = \"\";\n\n    if (size() == 0) return elements;\n    elements += symbol(0);\n    if (size() == 1) return elements;\n    for (size_t i = 1; i < size(); ++i)\n    {\n        elements += strpr(\" %s\", symbol(i).c_str());\n    }\n\n    return elements;\n}\n\nsize_t ElementMap::index(string const& symbol) const\n{\n    return safeFind(forwardMap, symbol);\n}\n\nstring ElementMap::symbol(size_t const index) const\n{\n    return safeFind(reverseMap, index);\n}\n\nvoid ElementMap::deregisterElements()\n{\n    forwardMap.clear();\n    reverseMap.clear();\n\n    return;\n}\n\nsize_t ElementMap::atomicNumber(string const& symbol)\n{\n    size_t numKnownElements = sizeof(knownElements) / sizeof(*knownElements);\n\n    for (size_t i = 0; i < numKnownElements; i++)\n    {\n        if (knownElements[i] == symbol)\n        {\n            return i + 1;\n        }\n    }\n\n    throw runtime_error(\"ERROR: Element \\\"\" + symbol + \"\\\" unknown.\\n\");\n\n    return 0;\n}\n\nstring ElementMap::symbolFromAtomicNumber(size_t atomicNumber)\n{\n    size_t numKnownElements = sizeof(knownElements) / sizeof(*knownElements);\n\n    if (atomicNumber >= numKnownElements)\n    {\n        throw runtime_error(strpr(\"ERROR: Only the first %zu elements are \"\n                                  \"known to this library.\\n\",\n                                  numKnownElements));\n    }\n    else if (atomicNumber == 0)\n    {\n        throw runtime_error(\"ERROR: Invalid atomic number.\\n\");\n    }\n\n    atomicNumber--;\n    return knownElements[atomicNumber];\n}\n\nvector<string> ElementMap::info() const\n{\n    vector<string> v;\n\n    v.push_back(strpr(\"********************************\\n\"));\n    v.push_back(strpr(\"ELEMENT MAP                     \\n\"));\n    v.push_back(strpr(\"********************************\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"forwardMap                 [*] : %d\\n\", forwardMap.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (map<string, size_t>::const_iterator it = forwardMap.begin();\n         it != forwardMap.end(); ++it)\n    {\n        v.push_back(strpr(\"%29s  : %d\\n\", it->first.c_str(), it->second));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"reverseMap                 [*] : %d\\n\", reverseMap.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (map<size_t, string>::const_iterator it = reverseMap.begin();\n         it != reverseMap.end(); ++it)\n    {\n        v.push_back(strpr(\"%29d  : %s\\n\", it->first, it->second.c_str()));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"********************************\\n\"));\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/ElementMap.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef ELEMENTMAP_H\n#define ELEMENTMAP_H\n\n#include <cstddef> // std::size_t\n#include <map>     // std::map\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/// Contains element map.\nclass ElementMap\n{\npublic:\n    /** Overload [] operator for index search.\n     *\n     * @param[in] index Element index.\n     * @return Symbol of element in map.\n     */\n    std::string              operator[](std::size_t const index) const;\n    /** Overload [] operator for symbol search.\n     *\n     * @param[in] symbol Element symbol.\n     * @return Index of element in map.\n     */\n    std::size_t              operator[](std::string const symbol) const;\n    /** Get element map size.\n     *\n     * @return Number of elements registered.\n     */\n    std::size_t              size() const;\n    /** Get sorted list of elements in one string (space separated).\n     *\n     * @return Element string.\n     */\n    std::string              getElementsString() const;\n    /** Get index of given element.\n     *\n     * @param[in] symbol Element symbol.\n     * @return Element index.\n     */\n    std::size_t              index(std::string const& symbol) const;\n    /** Get element symbol for given element index.\n     *\n     * @param[in] index Element index.\n     * @return Element symbol.\n     */\n    std::string              symbol(std::size_t const index) const;\n    /** Get atomic number from element index.\n     *\n     * @param[in] index Element index in map.\n     * @return Atomic number (proton number Z) of element.\n     */\n    std::size_t              atomicNumber(std::size_t index) const;\n    /** Extract all elements and store in element map.\n     *\n     * @param[in] elementLine String containing all elements, e.g.\n     *                        \"Cd S Zn\", separated by whitespaces.\n     * @return Number of registered elements.\n     *\n     * Sorts all elements according to their atomic number and populates\n     * #forwardMap and #reverseMap with the symbol and the corresponding\n     * index number.\n     */\n    std::size_t              registerElements(std::string const& elementLine);\n    /** Clear element map.\n     */\n    void                     deregisterElements();\n    /** Get element symbol from atomic number.\n     *\n     * @param[in] atomicNumber Atomic number of element.\n     * @return Element symbol.\n     */\n    static std::string       symbolFromAtomicNumber(\n                                               std::size_t const atomicNumber);\n    /** Get atomic number from element string.\n     *\n     * @param[in] symbol Element symbol (e.g. \"He\" for Helium).\n     * @return Atomic number (proton number Z) of element.\n     */\n    static std::size_t       atomicNumber(std::string const& symbol);\n    /** Get map information as a vector of strings.\n     *\n     * @return Lines with map information.\n     */\n    std::vector<std::string> info() const;\n\nprivate:\n    /// Map of elements present and corresponding index number.\n    std::map<std::string, std::size_t> forwardMap;\n    /// Reverse element map.\n    std::map<std::size_t, std::string> reverseMap;\n    /// List of element symbols (e.g. \"He\" for Helium).\n    static std::string const           knownElements[];\n\n    /** Check if arguments are sorted according to atomic number.\n     *\n     * @param[in] symbol1 Element symbol 1.\n     * @param[in] symbol2 Element symbol 2.\n     * @return `true` if atomic number of element 1 is smaller than atomic\n     *         number of element 2, `false` otherwise.\n     *\n     * Used for sorting in #registerElements().\n     */\n    static bool compareAtomicNumber(std::string const& symbol1,\n                                    std::string const& symbol2);\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline std::string ElementMap::operator[](std::size_t const index) const\n{\n    return symbol(index);\n}\n\ninline std::size_t ElementMap::operator[](std::string const symbol) const\n{\n    return index(symbol);\n}\n\ninline std::size_t ElementMap::size() const\n{\n    return forwardMap.size();\n}\n\ninline std::size_t ElementMap::atomicNumber(std::size_t index) const\n{\n    return atomicNumber(symbol(index));\n}\n\ninline bool ElementMap::compareAtomicNumber(std::string const& symbol1,\n                                            std::string const& symbol2)\n{\n    return atomicNumber(symbol1) < atomicNumber(symbol2);\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/ErfcBuf.cpp",
    "content": "//\n// Created by philipp on 5/23/22.\n//\n\n#include \"ErfcBuf.h\"\n\nusing namespace std;\nusing namespace nnp;\n\nvoid ErfcBuf::reset(std::vector<Atom> const& atoms, size_t const valuesPerPair)\n{\n    f.resize(atoms.size());\n    for(size_t i = 0; i < atoms.size(); ++i)\n    {\n        f[i].resize(atoms[i].numNeighbors * valuesPerPair);\n        fill(f[i].begin(), f[i].end(), -1.0);\n    }\n    numValuesPerPair = valuesPerPair;\n}\n\ndouble ErfcBuf::getf(const size_t atomIndex,\n                     const size_t neighIndex,\n                     const size_t valIndex,\n                     const double x)\n{\n    size_t j = neighIndex * numValuesPerPair + valIndex;\n    if (f.at(atomIndex).at(j) == -1.0)\n    {\n        f[atomIndex][j] = erfc(x);\n    }\n    return f[atomIndex][j];\n}"
  },
  {
    "path": "src/libnnp/ErfcBuf.h",
    "content": "//\n// Created by philipp on 5/23/22.\n//\n\n#ifndef N2P2_ERFCBUF_H\n#define N2P2_ERFCBUF_H\n\n#include \"Atom.h\"\n#include <vector>\n\n\nnamespace nnp\n{\n    /// Helper class to store previously calculated values of erfc() that are\n    /// needed during the charge equilibration.\n    struct ErfcBuf\n    {\n        /** Resizes and resets the storage array to fit the current structure.\n         *\n         * @param[in] atoms Vector of atoms of the structure.\n         * @param[in] valuesPerPair Number of values that are stored for each\n         * neighbor pair (intended use is for erfc(rij...)).\n         */\n        void reset(std::vector<Atom> const& atoms, size_t const valuesPerPair);\n        /** Either returns already stored value erfc(x) or calculates it if not\n         *  yet stored.\n         * @param[in] atomIndex Index of atom.\n         * @param[in] neighIndex Index of neighbor of this atom.\n         * @param[in] valIndex Index corresponds to the value that is requested,\n         *                      see numValuesPerPair.\n         * @param[in] x Corresponds to erfc(x). Only used when result is not\n         *              stored yet.\n         */\n        double getf(size_t const atomIndex,\n                    size_t const neighIndex,\n                    size_t const valIndex,\n                    double const x);\n\n        /// 2d vector to store already calculated results. Elements set to -1\n        /// indicate that this value has not been calculated yet.\n        std::vector<std::vector<double>> f;\n        /// Typically one needs erfc(a_i * rij), where the number of a_i's\n        /// correspond to numValuesPerPair.\n        size_t numValuesPerPair = 1;\n    };\n\n} // nnp\n\n#endif //N2P2_ERFCBUF_H\n"
  },
  {
    "path": "src/libnnp/EwaldSetup.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"EwaldSetup.h\"\n#include \"EwaldTruncKolafaFixR.h\"\n#include \"EwaldTruncKolafaOptEta.h\"\n#include \"EwaldTruncJackson.h\"\n#include \"utility.h\"\n#include <stdexcept> // std::runtime_error\n#include <memory>    // std::make_unique\n\nusing namespace nnp;\nusing namespace std;\n\n\nEwaldSetup::EwaldSetup() : params     (                                ),\n                           truncMethod(EWALDTruncMethod::JACKSON_CATLOW),\n                           GlobSett   (                                ),\n                           truncImpl  (nullptr                         )\n{\n}\n\nvoid EwaldSetup::readFromArgs(vector<string> const& args)\n{\n    bool argConsistent = false;\n    if (truncMethod ==\n        EWALDTruncMethod::JACKSON_CATLOW)\n        argConsistent = (args.size() == 1);\n    else\n        argConsistent = (args.size() >= 1 && args.size() <= 3);\n\n    if (!argConsistent)\n        throw runtime_error(\"ERROR: Number of arguments for ewald_prec is \"\n                            \"not consistent with \"\n                            \"ewald_truncation_error_method.\");\n\n    GlobSett.precision = atof(args.at(0).c_str());\n    if (GlobSett.precision <= 0.0)\n        throw runtime_error(\"ERROR: Ewald precision must be positive.\");\n\n    if (truncMethod == EWALDTruncMethod::JACKSON_CATLOW)\n    {\n        truncImpl.reset(new EwaldTruncJackson{});\n    }\n    else\n    {\n        if (args.size() >= 2)\n            GlobSett.maxCharge = atof(args.at(1).c_str());\n        if (args.size() == 2)\n        {\n            truncImpl.reset(new EwaldTruncKolafaOptEta{});\n        }\n        if (args.size() == 3)\n        {\n            params.rCut = atof(args.at(2).c_str());\n            truncImpl.reset(new EwaldTruncKolafaFixR{});\n        }\n    }\n}\n\nvoid EwaldSetup::toNormalizedUnits(double const convEnergy,\n                                   double const convLength)\n{\n    if (truncMethod == EWALDTruncMethod::KOLAFA_PERRAM)\n    {\n        // in KOLAFA_PERRAM method precision has unit of a force.\n        GlobSett.precision *= convEnergy / convLength;\n        GlobSett.fourPiEps /= convLength * convEnergy;\n        // GlobSett.maxQSigma is already normalized\n        params = params.toNormalizedUnits(convLength);\n        // Other variables are already normalized.\n    }\n}\n\nvoid EwaldSetup::calculateParameters(double const volume, size_t const numAtoms)\n{\n    if (truncImpl == nullptr)\n        throw runtime_error(\"ERROR: Undefined Ewald truncation method.\");\n    EwaldStructureData sData{volume, numAtoms};\n    truncImpl->calculateParameters(GlobSett, sData, params);\n}\nvoid EwaldSetup::logEwaldCutoffs(Log& log, double const lengthConversion) const\n{\n    if (!publishedNewCutoffs())\n    {\n        EwaldParameters ewaldParams = params.toPhysicalUnits(lengthConversion);\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        log << \"Ewald parameters for this structure changed:\\n\";\n        log << strpr(\"Real space cutoff:         %16.8E\\n\",\n                     ewaldParams.rCut);\n        log << strpr(\"Reciprocal space cutoff:   %16.8E\\n\",\n                     ewaldParams.kCut);\n        log << strpr(\"Ewald screening parameter: %16.8E\\n\",\n                     ewaldParams.eta);\n        if (!isEstimateReliable())\n            log << strpr(\"WARNING: Ewald truncation error estimate may not be \"\n                         \"reliable, better compare it\\n\"\n                         \"         with high accuracy settings.\\n\");\n    }\n}\nbool EwaldSetup::publishedNewCutoffs() const\n{\n    return truncImpl->publishedNewCutoffs();\n}\nbool EwaldSetup::isEstimateReliable() const\n{\n    return truncImpl->isEstimateReliable(GlobSett, params);\n}\n"
  },
  {
    "path": "src/libnnp/EwaldSetup.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef EWALDSETUP_H\n#define EWALDSETUP_H\n\n//#include \"Vec3D.h\"\n#include \"IEwaldTrunc.h\"\n#include \"Log.h\"\n#include <string>\n#include <vector>\n#include <memory>\n\n\nnamespace nnp {\nenum class EWALDTruncMethod {\n    /// Method 0: Used by RuNNer (DOI: 10.1080/08927028808080944).\n    JACKSON_CATLOW,\n    /// Method 1: Optimized in n2p2 (DOI: 10.1080/08927029208049126).\n    KOLAFA_PERRAM\n};\n\n/// Setup data for Ewald summation.\nclass EwaldSetup {\npublic:\n    EwaldParameters params;\n    /// Default constructor.\n    EwaldSetup();\n    void setTruncMethod(EWALDTruncMethod const m);\n    EWALDTruncMethod getTruncMethod() const {return truncMethod;};\n    double getMaxCharge() const {return GlobSett.maxCharge;};\n    double getPrecision() const {return GlobSett.precision;};\n    double getMaxQSigma() const {return GlobSett.maxQSigma;};\n\n    /** Setter for maximum width of charges.\n     *\n     * @param maxWidth Maximum width of gaussian charges.\n     */\n    void setMaxQSigma(double const maxWidth);\n    /** Setup parameters from argument vector.\n     *\n     * @param[in] args Vector containing arguments of input file.\n     */\n    void readFromArgs(std::vector<std::string> const& args);\n\n    /** Convert cutoff parameters to normalized units.\n     *\n     * @param convEnergy Conversion factor for energy.\n     * @param convLength Conversion factor for length.\n     */\n    void toNormalizedUnits(double const convEnergy,\n                           double const convLength);\n    /** Compute eta, rCut and kCut.\n    *\n    * @param[in] newVolume Volume of the real space cell.\n    * @param[in] newNumAtoms Number of atoms in system.\n    */\n    void calculateParameters(double const newVolume, size_t const newNumAtoms);\n    /** Use after Ewald summation!\n     *\n     * @return\n     */\n    void logEwaldCutoffs(Log& log, double const lengthConversion) const;\n\nprivate:\n    /// Method for determining real and k space cutoffs.\n    EWALDTruncMethod truncMethod;\n    EwaldGlobalSettings GlobSett;\n\n    std::unique_ptr<IEwaldTrunc> truncImpl;\n\n    bool publishedNewCutoffs() const;\n    bool isEstimateReliable() const;\n};\n\ninline void EwaldSetup::setMaxQSigma(double const maxWidth)\n{\n    GlobSett.maxQSigma = maxWidth;\n}\n\ninline void EwaldSetup::setTruncMethod(EWALDTruncMethod const m)\n{\n    truncMethod = m;\n}\n\n}\n#endif //EWALDSETUP_H\n"
  },
  {
    "path": "src/libnnp/EwaldTruncJackson.cpp",
    "content": "//\n// Created by philipp on 2/17/23.\n//\n\n#include \"EwaldTruncJackson.h\"\n#include <cmath>\n#include <stdexcept>\n\nnamespace nnp\n{\n    void\n    EwaldTruncJackson::calculateParameters(EwaldGlobalSettings const& settings,\n                                           EwaldStructureData const& sData,\n                                           EwaldParameters &params)\n    {\n        double V = sData.getVolume();\n        newCutoffs = (V != volume);\n        if (!newCutoffs) return;\n        newCutoffsWerePublished = false;\n        volume = V;\n\n        if ( settings.precision >= 1.0 )\n            throw std::runtime_error(\"ERROR: Ewald truncation method 0 \"\n                                     \"(Jackson) requires precision < 1.0\");\n        params.eta = calculateEta();\n        if ( params.eta <= 0.0 )\n            throw std::runtime_error(\"ERROR: Ewald screening parameter eta is \"\n                                     \"not positive, is the unit cell volume \"\n                                     \"correct?\");\n        params.rCut = calculateRCut(params.eta, settings.precision);\n        params.kCut = calculateKCut(params.eta, settings.precision);\n        return;\n    }\n\n    bool EwaldTruncJackson::publishedNewCutoffs()\n    {\n        bool answer = newCutoffsWerePublished;\n        newCutoffsWerePublished = true;\n        return answer;\n    }\n\n    double EwaldTruncJackson::calculateEta() const\n    {\n        // Matrix version of eta.\n        return 1.0 / sqrt(2.0 * M_PI) * pow(volume, 1.0 / 3.0);\n    }\n\n    double EwaldTruncJackson::calculateRCut(double const eta,\n                                            double const prec) const\n    {\n        return sqrt(-2.0 * log(prec)) * eta;\n    }\n\n    double EwaldTruncJackson::calculateKCut(double const eta,\n                                            double const prec) const\n    {\n        return sqrt(-2.0 * log(prec)) / eta;\n    }\n} // nnp"
  },
  {
    "path": "src/libnnp/EwaldTruncJackson.h",
    "content": "//\n// Created by philipp on 2/17/23.\n//\n\n#ifndef N2P2_EWALDTRUNCJACKSON_H\n#define N2P2_EWALDTRUNCJACKSON_H\n\n#include \"IEwaldTrunc.h\"\nnamespace nnp\n{\n    class EwaldTruncJackson : public IEwaldTrunc\n    {\n    public:\n        void calculateParameters(EwaldGlobalSettings const& settings,\n                                 EwaldStructureData const& sData,\n                                 EwaldParameters &params) override;\n        bool publishedNewCutoffs() override;\n        virtual bool isEstimateReliable(\n                EwaldGlobalSettings const&,\n                EwaldParameters const&) const override {return true;};\n    private:\n        bool newCutoffs = true;\n        bool newCutoffsWerePublished = false;\n        double volume = 0.0;\n\n        double calculateEta() const;\n        double calculateRCut(double const eta, double const prec) const;\n        double calculateKCut(double const eta, double const prec) const;\n\n    };\n\n} // nnp\n\n#endif //N2P2_EWALDTRUNCJACKSON_H\n"
  },
  {
    "path": "src/libnnp/EwaldTruncKolafaFixR.cpp",
    "content": "//\n// Created by philipp on 2/17/23.\n//\n\n#include \"EwaldTruncKolafaFixR.h\"\n#include <stdexcept>\n\nusing namespace std;\n\nnamespace nnp\n{\n    void EwaldTruncKolafaFixR::calculateParameters(EwaldGlobalSettings const& settings,\n                                                   EwaldStructureData const& sData,\n                                                   EwaldParameters &params)\n    {\n        size_t N = sData.getNumAtoms();\n        double V = sData.getVolume();\n\n        newCutoffs = (V != volume || N != numAtoms);\n        if (!newCutoffs) return;\n        newCutoffsWerePublished = false;\n\n        volume = V;\n        fourPiEps = settings.fourPiEps;\n        numAtoms = N;\n        double rCut = params.rCut;\n        if (rCut == 0.0)\n            throw std::runtime_error(\"ERROR: Real space cutoff of Ewald \"\n                                     \"summation cannot be zero.\");\n\n        calculateC(settings.maxCharge);\n        params.eta = calculateEta(rCut, settings.precision);\n        params.kCut = calculateKCut(params.eta, settings.precision);\n        return;\n    }\n    bool EwaldTruncKolafaFixR::publishedNewCutoffs()\n    {\n        bool answer = newCutoffsWerePublished;\n        newCutoffsWerePublished = true;\n        return answer;\n    }\n    bool EwaldTruncKolafaFixR::isEstimateReliable(\n            EwaldGlobalSettings const& settings,\n            EwaldParameters const& params) const\n    {\n        return params.eta >= settings.maxQSigma;\n    }\n\n    double EwaldTruncKolafaFixR::calculateEta(double const rCut,\n                                              double const prec) const\n    {\n        double x = sqrt(rCut/2) * prec / C;\n        if (x >= 1.0)\n            throw runtime_error(\"ERROR: Bad Ewald precision settings, try a \"\n                                \"smaller value.\");\n        return rCut / sqrt(-2 * log(x));\n    }\n\n    double EwaldTruncKolafaFixR::calculateKCut(double const eta,\n                                               double const prec) const\n    {\n        double constexpr acceptError = 1.e-10;\n        double relXError = 1.0;\n        double relYError = 1.0;\n        double y = eta * prec / (sqrt(2) * C);\n\n        double kCut = 1.0/eta;\n        double kCutOld;\n        while (relXError > acceptError || relYError > acceptError)\n        {\n            kCutOld = kCut;\n            kCut -= 2 * kCut / (1 + 2*pow(kCut * eta,2.0))\n                    * (-1 + sqrt(kCut) * exp(pow(kCut * eta,2.0)/2) * y);\n            // If kCut becomes negative, start with smaller value.\n            if (kCut <= 0)\n            {\n                kCut = kCutOld / 2;\n                continue;\n            }\n\n            relXError = abs((kCut - kCutOld) / kCut);\n            relYError = abs((1/sqrt(kCut)\n                        * exp(-pow(kCut * eta,2.0) / 2) - y) / y);\n        }\n        return kCut;\n    }\n\n    void EwaldTruncKolafaFixR::calculateC(const double qMax)\n    {\n        C = 2 * pow(qMax,2.0) * sqrt(numAtoms/volume) / fourPiEps;\n    }\n\n} // nnp"
  },
  {
    "path": "src/libnnp/EwaldTruncKolafaFixR.h",
    "content": "//\n// Created by philipp on 2/17/23.\n//\n\n#ifndef N2P2_EWALDTRUNCKOLAFAFIXR_H\n#define N2P2_EWALDTRUNCKOLAFAFIXR_H\n\n#include \"IEwaldTrunc.h\"\n#include <cmath>\n\nnamespace nnp\n{\n    class EwaldTruncKolafaFixR : public IEwaldTrunc\n    {\n    public:\n        void calculateParameters(EwaldGlobalSettings const& settings,\n                                 EwaldStructureData const& sData,\n                                 EwaldParameters &params) override;\n        bool publishedNewCutoffs() override;\n        bool isEstimateReliable(\n                EwaldGlobalSettings const& settings,\n                EwaldParameters const& params) const override;\n\n    private:\n        double volume = 0.0;\n        double fourPiEps = 1.0;\n        std::size_t numAtoms = 0;\n        bool newCutoffs = true;\n        bool newCutoffsWerePublished = false;\n\n        double C = 0.0;\n\n        double calculateEta(double const rCut, double const prec) const;\n        double calculateKCut(double const eta, double const prec) const;\n        void calculateC(double const qMax);\n    };\n\n\n} // nnp\n\n#endif //N2P2_EWALDTRUNCKOLAFAFIXR_H\n"
  },
  {
    "path": "src/libnnp/EwaldTruncKolafaOptEta.cpp",
    "content": "//\n// Created by philipp on 2/17/23.\n//\n\n#include \"EwaldTruncKolafaOptEta.h\"\n#include <cmath>\n#include <algorithm>\n\nusing namespace std;\n\nnamespace nnp\n{\n    // Ratio of computing times for one real space and k space iteration.\n    double constexpr TrOverTk = 3.676;\n\n    void EwaldTruncKolafaOptEta::calculateParameters(\n            const EwaldGlobalSettings &settings,\n            const EwaldStructureData &sData, EwaldParameters &params)\n    {\n        size_t N = sData.getNumAtoms();\n        double V = sData.getVolume();\n        newCutoffs = (volume != V || numAtoms != N);\n        if (!newCutoffs) return;\n        newCutoffsWerePublished = false;\n\n        volume = V;\n        numAtoms = N;\n        prec = settings.precision;\n        fourPiEps = settings.fourPiEps;\n\n        calculateC(settings.maxCharge);\n        calculateEta();\n\n        eta = std::max(eta,settings.maxQSigma);\n        params.eta = eta;\n        params.rCut = calculateRCut();\n        params.kCut = calculateKCut();\n    }\n    bool EwaldTruncKolafaOptEta::publishedNewCutoffs()\n    {\n        bool answer = newCutoffsWerePublished;\n        newCutoffsWerePublished = true;\n        return answer;\n    }\n\n    void EwaldTruncKolafaOptEta::calculateEta()\n    {\n        double constexpr acceptError = 1.e-10;\n\n        // Initial approximation\n        double eta0 = pow(1 / TrOverTk * pow(volume, 2.0)\n                    / pow(2 * M_PI, 3.0), 1.0 / 6.0);\n\n        // Selfconsistent calculation of eta\n        eta = eta0;\n        double oldEta;\n        double relError = 1.0;\n        s = 1.0;\n        while (relError > acceptError)\n        {\n            calculateS();\n            oldEta = eta;\n            eta = eta0 * pow((1 + 1 / (2 * pow(s, 2))), 1.0 / 6.0);\n            relError = abs(oldEta - eta) / eta;\n        }\n    }\n    double EwaldTruncKolafaOptEta::calculateRCut()\n    {\n        return sqrt(2)*eta*s;\n    }\n\n    double EwaldTruncKolafaOptEta::calculateKCut()\n    {\n        return sqrt(2)*s / eta;\n    }\n\n    void EwaldTruncKolafaOptEta::calculateS()\n    {\n        double constexpr acceptError = 1.e-10;\n        double relXError = 1.0;\n        double relYError = 1.0;\n        double y = prec / C * sqrt(eta/2);\n\n        if (s <= 0.0) s = 0.5;\n\n        double step;\n        while (relXError > acceptError || relYError > acceptError)\n        {\n            step = 2*s / (4*pow(s,2.0) + 1)\n                   * (1 - sqrt(s) / exp(-pow(s,2.0)) * y);\n\n            // If s would become negative, try smaller start value.\n            if (s <= -step)\n            {\n                s /= 2;\n                step = 1.0;\n                continue;\n            }\n            s += step;\n            relYError = abs((exp(-pow(s,2.0)) / sqrt(s) - y) / y);\n            relXError = abs(step/s);\n        }\n    }\n\n    void EwaldTruncKolafaOptEta::calculateC(double const qMax)\n    {\n        C = pow(2, 3.0/4) * pow(qMax,2.0) * sqrt(numAtoms/volume) / fourPiEps;\n    }\n} // nnp\n"
  },
  {
    "path": "src/libnnp/EwaldTruncKolafaOptEta.h",
    "content": "//\n// Created by philipp on 2/17/23.\n//\n\n#ifndef N2P2_EWALDTRUNCKOLAFAOPTETA_H\n#define N2P2_EWALDTRUNCKOLAFAOPTETA_H\n\n#include \"IEwaldTrunc.h\"\n\nnamespace nnp\n{\n\n    class EwaldTruncKolafaOptEta : public IEwaldTrunc\n    {\n    public:\n        void calculateParameters(EwaldGlobalSettings const& settings,\n                                 EwaldStructureData const& sData,\n                                 EwaldParameters &params) override;\n        bool publishedNewCutoffs() override;\n        virtual bool isEstimateReliable(\n                EwaldGlobalSettings const& ,\n                EwaldParameters const& ) const override { return true; };\n    private:\n        bool newCutoffs = true;\n        bool newCutoffsWerePublished = false;\n        double C = 0.0;\n        double s = 1.0;\n        double eta = 1.0;\n        double prec = 1.e-6;\n        double volume = 0.0;\n        double fourPiEps = 1.0;\n        std::size_t numAtoms = 0;\n\n        void calculateEta();\n        double calculateRCut();\n        double calculateKCut();\n        void calculateS();\n        void calculateC(double const qMax);\n    };\n\n} // nnp\n\n#endif //N2P2_EWALDTRUNCKOLAFAOPTETA_H\n"
  },
  {
    "path": "src/libnnp/IEwaldTrunc.h",
    "content": "//\n// Created by philipp on 2/17/23.\n//\n\n#ifndef N2P2_IEWALDTRUNC_H\n#define N2P2_IEWALDTRUNC_H\n\n#include <cstddef>        // std::size_t\n\nnamespace nnp\n{\n    struct EwaldGlobalSettings\n    {\n        double precision = 1.0E-6;\n        double maxCharge = 1.0;\n        double maxQSigma = 1.0;\n        /// Multiplicative constant \\f$ 4 \\pi \\varepsilon_0 \\f$.\n        /// Value depends on unit system (e.g. normalization).\n        double fourPiEps = 1.0;\n    };\n\n    class EwaldStructureData\n    {\n    public:\n        EwaldStructureData(double const V, std::size_t const N)\n                : volume{V}, numAtoms{N}\n        {};\n        ~EwaldStructureData() = default;\n\n        double getVolume() const { return volume; };\n        std::size_t getNumAtoms() const { return numAtoms; };\n    private:\n        double volume = 0.0;\n        std::size_t numAtoms = 0;\n    };\n\n    struct EwaldParameters\n    {\n        /// Width of the gaussian screening charges.\n        double eta = 0.0;\n        /// Cutoff in real space.\n        double rCut = 0.0;\n        /// Cutoff in reciprocal space.\n        double kCut = 0.0;\n\n        EwaldParameters() = default;\n        EwaldParameters(double oEta, double oRCut, double oKCut)\n                : eta{oEta}, rCut{oRCut}, kCut{oKCut}\n        {}\n\n        EwaldParameters toPhysicalUnits(double const convLength) const\n        {\n            return EwaldParameters{eta / convLength,\n                                   rCut / convLength,\n                                   kCut * convLength};\n        }\n        EwaldParameters toNormalizedUnits(double const convLength) const\n        {\n            return toPhysicalUnits(1/convLength);\n        }\n    };\n\n    class IEwaldTrunc\n    {\n    public:\n        virtual void calculateParameters(EwaldGlobalSettings const& settings,\n                                         EwaldStructureData const& sData,\n                                         EwaldParameters &params) = 0;\n        virtual bool publishedNewCutoffs() = 0;\n        virtual bool isEstimateReliable(\n                EwaldGlobalSettings const& settings,\n                EwaldParameters const& params) const = 0;\n        virtual ~IEwaldTrunc() = default;\n    };\n}\n#endif //N2P2_IEWALDTRUNC_H\n"
  },
  {
    "path": "src/libnnp/ISettings.h",
    "content": "//\n// Created by philipp on 2/21/23.\n//\n\n#ifndef N2P2_ISETTINGS_H\n#define N2P2_ISETTINGS_H\n\n#include \"Key.h\"\n\nnamespace nnp\n{\n    namespace settings\n    {\n        class ISettings\n        {\n        public:\n            virtual bool keywordExists(Key const& key,\n                                       bool const exact = false) const = 0;\n            virtual std::string getValue(Key const& key) const = 0;\n        };\n    }\n}\n\n#endif //N2P2_ISETTINGS_H\n"
  },
  {
    "path": "src/libnnp/Key.h",
    "content": "//\n// Created by philipp on 2/21/23.\n//\n\n#ifndef N2P2_KEY_H\n#define N2P2_KEY_H\n\n#include <string>\n#include <vector>\n#include <iterator>\n\nnamespace nnp\n{\n    namespace settings\n    {\n        /// Keyword properties.\n        class Key\n        {\n        public:\n            std::string getMainKeyword() const\n            {\n                return keywords.at(0);\n            }\n            /// Whether this keyword has no alternative definitions or spellings.\n            bool hasUniqueKeyword() const {return (keywords.size() == 1);}\n            void addAlternative(std::string word) {keywords.push_back(word);};\n            void setDescription(std::string text) {description = text;};\n\n            std::vector<std::string>::const_iterator begin() const\n            {\n                return keywords.begin();\n            }\n            std::vector<std::string>::const_iterator end() const\n            {\n                return keywords.end();\n            }\n\n        private:\n            /// A short description of the keyword.\n            std::string              description;\n            /// Alternative keywords (first entry is main name).\n            std::vector<std::string> keywords;\n        };\n    }\n}\n#endif //N2P2_KEY_H\n"
  },
  {
    "path": "src/libnnp/Kspace.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n\n#include \"Kspace.h\"\n#include <iostream>\n#include <fstream>\n\nusing namespace std;\nusing namespace nnp;\n\n\nKvector::Kvector() : k     (Vec3D()),\n                     knorm2(0.0    ),\n                     coeff (0.0    )\n{\n}\n\nKvector::Kvector(Vec3D v) : k     (v       ),\n                            knorm2(v.norm()),\n                            coeff (0.0     )\n{\n}\n\nKspaceGrid::KspaceGrid() : eta   (0.0),\n                           kCut  (0.0),\n                           volume(0.0),\n                           pre   (0.0)\n{\n}\n\nvoid KspaceGrid::setup(Vec3D box[3], EwaldSetup& ewaldSetup)\n{\n    volume = fabs(box[0] * (box[1].cross(box[2])));\n    pre = 2.0 * M_PI / volume;\n\n    kbox[0] = pre * box[1].cross(box[2]);\n    kbox[1] = pre * box[2].cross(box[0]);\n    kbox[2] = pre * box[0].cross(box[1]);\n\n    eta = ewaldSetup.params.eta;\n    kCut = ewaldSetup.params.kCut;\n\n    // Compute box copies required in each direction.\n    calculatePbcCopies(kCut);\n\n    double halfSphere = 1; // TODO\n    if (halfSphere)\n    {\n        // Compute k-grid (only half sphere because of symmetry).\n        for (int i = 0; i <= n[0]; ++i)\n        {\n            int sj = -n[1];\n            if (i == 0) sj = 0;\n            for (int j = sj; j <= n[1]; ++j)\n            {\n                int sk = -n[2];\n                if (i == 0 && j == 0) sk = 0;\n                for (int k = sk; k <= n[2]; ++k)\n                {\n                    if (i == 0 && j == 0 && k == 0) continue;\n                    Vec3D kv = i * kbox[0] + j * kbox[1] + k * kbox[2];\n                    double knorm2 = kv.norm2();\n                    if (kv.norm2() < kCut * kCut)\n                    {\n                        //fprintf(stderr, \"sqk = %24.16E\\n\", kv.norm());\n                        kvectors.push_back(kv);\n                        kvectors.back().knorm2 = knorm2; // TODO: Necessary?\n                        kvectors.back().coeff = exp(-0.5 * eta * eta * knorm2)\n                                              * 2.0 * pre / knorm2;\n                    }\n                }\n            }\n        }\n    }\n    else\n    {\n        // Compute full k-grid.\n        for (int i = -n[0]; i <= n[0]; ++i)\n        {\n            for (int j = -n[1]; j <= n[1]; ++j)\n            {\n                for (int k = -n[2]; k <= n[2]; ++k)\n                {\n                    if (i == 0 && j == 0 && k == 0) continue;\n                    Vec3D kv = i * kbox[0] + j * kbox[1] + k * kbox[2];\n                    double knorm2 = kv.norm2();\n                    if (kv.norm2() < kCut * kCut)\n                    {\n                        kvectors.push_back(kv);\n                        kvectors.back().knorm2 = knorm2; // TODO: Necessary?\n                        kvectors.back().coeff = exp(-0.5 * eta * eta * knorm2)\n                                              * 2.0 * pre / knorm2;\n                    }\n                }\n            }\n        }\n    }\n}\n\nvoid KspaceGrid::calculatePbcCopies(double cutoffRadius)\n{\n    Vec3D axb;\n    Vec3D axc;\n    Vec3D bxc;\n\n    axb = kbox[0].cross(kbox[1]).normalize();\n    axc = kbox[0].cross(kbox[2]).normalize();\n    bxc = kbox[1].cross(kbox[2]).normalize();\n\n    double proja = fabs(kbox[0] * bxc);\n    double projb = fabs(kbox[1] * axc);\n    double projc = fabs(kbox[2] * axb);\n\n    n[0] = 0;\n    n[1] = 0;\n    n[2] = 0;\n    while (n[0] * proja <= cutoffRadius) n[0]++;\n    while (n[1] * projb <= cutoffRadius) n[1]++;\n    while (n[2] * projc <= cutoffRadius) n[2]++;\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/Kspace.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef KSPACE_H\n#define KSPACE_H\n\n#include \"Vec3D.h\"\n#include \"EwaldSetup.h\"\n#include <vector> // std::vector\n\nnamespace nnp\n{\nenum class KSPACESolver {\n    /// Solver 0: Ewald summation.\n    EWALD_SUM,\n    /// Solver 1: PPPM.\n    PPPM,\n    /// Solver 2: Ewald summation in LAMMPS.\n    EWALD_SUM_LAMMPS\n};\nclass Kvector\n{\npublic:\n    /// A single k-vector (as Vec3D).\n    Vec3D  k;\n    /// Square of norm of k-vector.\n    double knorm2;\n    /// Precomputed coefficient for Ewald summation.\n    double coeff;\n\n    /// Constructor.\n    Kvector();\n    /// Constructor with Vec3D.\n    Kvector(Vec3D v);\n};\n\nclass KspaceGrid\n{\npublic:\n    /// Method for calculating the reciprocal part.\n    KSPACESolver         kspaceSolver;\n    /// Ewald summation eta parameter.\n    double               eta;\n    /// Cutoff in reciprocal space.\n    double               kCut;\n    /// Cutoff in real space.\n    double               rCut;\n    /// Volume of real box.\n    double               volume;\n    /// Ewald sum prefactor @f$\\frac{2\\pi}{V}@f$.\n    double               pre;\n    /// Required box copies in each box vector direction.\n    int                  n[3];\n    /// Reciprocal box vectors.\n    Vec3D                kbox[3];\n    /// Vector containing all k-vectors.\n    std::vector<Kvector> kvectors;\n    \n    /// Constructor.\n    KspaceGrid();\n    /** Set up reciprocal box vectors and eta.\n     *\n     * @param[in] box Real box vectors.\n     * @param[in] ewaldSetup Settings of ewald summation.\n     */\n    void setup(Vec3D box[3], EwaldSetup& ewaldSetup);\n\nprivate:\n    /** Compute box copies in each direction.\n     *\n     * @param[in] cutoffRadius Cutoff radius.\n     *\n     * TODO: This is code copy from Structure class!\n     */\n    void calculatePbcCopies(double cutoffRadius);\n};\n\n}\n\n#endif\n\n"
  },
  {
    "path": "src/libnnp/Log.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Log.h\"\n#include <iostream> // std::cout\n\nusing namespace std;\nusing namespace nnp;\n\nLog::Log() : writeToStdout(true ),\n             silent       (false)\n{\n}\n\nLog& Log::operator<<(string const& entry)\n{\n    addLogEntry(entry);\n    return *this;\n}\n\nLog& Log::operator<<(vector<string> const& entries)\n{\n    addMultipleLogEntries(entries);\n    return *this;\n}\n\nvoid Log::addLogEntry(string const& entry)\n{\n    if (silent) return;\n    memory.push_back(entry);\n\n    if (writeToStdout)\n    {\n        cout << entry;\n        cout.flush();\n    }\n\n    for (vector<FILE**>::const_iterator it = cFilePointers.begin();\n         it != cFilePointers.end(); ++it)\n    {\n        if ((**it) != 0)\n        {\n            fprintf((**it), \"%s\", entry.c_str());\n            fflush((**it));\n        }\n    }\n\n    for (vector<ofstream*>::const_iterator it = streamPointers.begin();\n         it != streamPointers.end(); ++it)\n    {\n        if ((**it).is_open())\n        {\n            (**it) << entry;\n            (**it).flush();\n        }\n    }\n\n    return;\n}\n\nvoid Log::addMultipleLogEntries(vector<string> const& entries)\n{\n    for (vector<string>::const_iterator it = entries.begin();\n         it != entries.end(); ++it)\n    {\n        addLogEntry(*it);\n    }\n\n    return;\n}\n\nvoid Log::registerCFilePointer(FILE** const& filePointer)\n{\n    cFilePointers.push_back(filePointer);\n    return;\n}\n\nvoid Log::registerStreamPointer(ofstream* const& streamPointer)\n{\n    streamPointers.push_back(streamPointer);\n    return;\n}\n\nvector<string> Log::getLog() const\n{\n    return memory;\n}\n"
  },
  {
    "path": "src/libnnp/Log.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef LOG_H\n#define LOG_H\n\n#include <cstdio>  // FILE\n#include <fstream> // std::ofstream\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/** Logging class for library output.\n *\n * Log entries are saved in internal memory and may be redirected to multiple\n * destinations: existing C-style FILE pointer or existing C++ stream.\n */\nclass Log\n{\npublic:\n    /** Constructor.\n     *\n     * Default output to stdout.\n     */\n    Log();\n    /** Overload << operator.\n     *\n     * @param[in] entry New log entry.\n     *\n     * @return Reference to log itself.\n     */\n    Log&                     operator<<(std::string const& entry);\n    /** Overload << operator.\n     *\n     * @param[in] entries Vector with log entries.\n     *\n     * @return Reference to log itself.\n     */\n    Log&                     operator<<(\n                                      std::vector<std::string> const& entries);\n    /** Add string as new log entry.\n     *\n     * @param[in] entry New log entry.\n     */\n    void                     addLogEntry(std::string const& entry);\n    /** Add multiple log entries at once.\n     *\n     * @param[in] entries Vector with log entries.\n     */\n    void                     addMultipleLogEntries(\n                                      std::vector<std::string> const& entries);\n    /** Register new C-style FILE* pointer for output.\n     *\n     * @param[in] filePointer Address of C-style file pointer (FILE*).\n     */\n    void                     registerCFilePointer(FILE** const& filePointer);\n    /** Register new C++ ofstream pointer.\n     *\n     * @param[in] streamPointer Address of C++ ofstream pointer.\n     */\n    void                     registerStreamPointer(\n                                          std::ofstream* const& streamPointer);\n    /** Get complete log memory.\n     *\n     * @return Log memory.\n     */\n    std::vector<std::string> getLog() const;\n\n    /// Turn on/off output to stdout.\n    bool writeToStdout;\n    /// Completely silence output.\n    bool silent;\n\nprivate:\n    /// Memory with all log entries.\n    std::vector<std::string>    memory;\n    /// Storage for C-style FILE* pointers.\n    std::vector<FILE**>         cFilePointers;\n    /// Storage for C++ ofstream pointers.\n    std::vector<std::ofstream*> streamPointers;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/Mode.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Mode.h\"\n#include \"NeuralNetwork.h\"\n#include \"utility.h\"\n#include \"version.h\"\n#include <cmath>\n#ifdef _OPENMP\n#include <omp.h>\n#endif\n#include <Eigen/QR>\n#include <algorithm> // std::min, std::max, std::remove_if\n#include <cstdlib>   // atoi, atof\n#include <fstream>   // std::ifstream\n#ifndef N2P2_NO_SF_CACHE\n#include <map>       // std::multimap\n#endif\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n#include <utility>   // std::piecewise_construct, std::forward_as_tuple\n\nusing namespace std;\nusing namespace nnp;\nusing namespace Eigen;\n\nMode::Mode() : nnpType                   (NNPType::HDNNP_2G),\n               normalize                 (false            ),\n               checkExtrapolationWarnings(false            ),\n               numElements               (0                ),\n               maxCutoffRadius           (0.0              ),\n               cutoffAlpha               (0.0              ),\n               meanEnergy                (0.0              ),\n               convEnergy                (1.0              ),\n               convLength                (1.0              ),\n               convCharge                (1.0              ),\n               fourPiEps                 (1.0              ),\n               ewaldSetup                {},\n               kspaceGrid                {}\n{\n}\n\nvoid Mode::initialize()\n{\n    log << \"\\n\";\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n    log << \"WELCOME TO n²p², A SOFTWARE PACKAGE FOR NEURAL NETWORK \"\n           \"POTENTIALS!\\n\";\n    log << \"-------------------------------------------------------\"\n           \"-----------\\n\";\n    log << \"\\n\";\n    log << \"n²p² version  (from git): \" N2P2_GIT_VERSION \"\\n\";\n    log << \"             (version.h): \" N2P2_VERSION \"\\n\";\n    log << \"------------------------------------------------------------\\n\";\n    log << \"Git branch              : \" N2P2_GIT_BRANCH \"\\n\";\n    log << \"Git revision            : \" N2P2_GIT_REV \"\\n\";\n    log << \"Compile date/time       : \" __DATE__ \" \" __TIME__ \"\\n\";\n    log << \"------------------------------------------------------------\\n\";\n    log << \"\\n\";\n    log << \"Features/Flags:\\n\";\n    log << \"------------------------------------------------------------\\n\";\n    log << \"Symmetry function groups     : \";\n#ifndef N2P2_NO_SF_GROUPS\n    log << \"enabled\\n\";\n#else\n    log << \"disabled\\n\";\n#endif\n    log << \"Symmetry function cache      : \";\n#ifndef N2P2_NO_SF_CACHE\n    log << \"enabled\\n\";\n#else\n    log << \"disabled\\n\";\n#endif\n    log << \"Timing function available    : \";\n#ifndef N2P2_NO_TIME\n    log << \"available\\n\";\n#else\n    log << \"disabled\\n\";\n#endif\n    log << \"Asymmetric polynomial SFs    : \";\n#ifndef N2P2_NO_ASYM_POLY\n    log << \"available\\n\";\n#else\n    log << \"disabled\\n\";\n#endif\n    log << \"SF low neighbor number check : \";\n#ifndef N2P2_NO_NEIGH_CHECK\n    log << \"enabled\\n\";\n#else\n    log << \"disabled\\n\";\n#endif\n    log << \"SF derivative memory layout  : \";\n#ifndef N2P2_FULL_SFD_MEMORY\n    log << \"reduced\\n\";\n#else\n    log << \"full\\n\";\n#endif\n    log << \"MPI explicitly disabled      : \";\n#ifndef N2P2_NO_MPI\n    log << \"no\\n\";\n#else\n    log << \"yes\\n\";\n#endif\n#ifdef _OPENMP\n    log << strpr(\"OpenMP threads               : %d\\n\", omp_get_max_threads());\n#endif\n    log << \"------------------------------------------------------------\\n\";\n    log << \"\\n\";\n\n    log << \"Please cite the following papers when publishing results \"\n           \"obtained with n²p²:\\n\";\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    log << \" * General citation for n²p² and the LAMMPS interface:\\n\";\n    log << \"\\n\";\n    log << \" Singraber, A.; Behler, J.; Dellago, C.\\n\";\n    log << \" Library-Based LAMMPS Implementation of High-Dimensional\\n\";\n    log << \" Neural Network Potentials.\\n\";\n    log << \" J. Chem. Theory Comput. 2019 15 (3), 1827–1840.\\n\";\n    log << \" https://doi.org/10.1021/acs.jctc.8b00770\\n\";\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    log << \" * Additionally, if you use the NNP training features of n²p²:\\n\";\n    log << \"\\n\";\n    log << \" Singraber, A.; Morawietz, T.; Behler, J.; Dellago, C.\\n\";\n    log << \" Parallel Multistream Training of High-Dimensional Neural\\n\";\n    log << \" Network Potentials.\\n\";\n    log << \" J. Chem. Theory Comput. 2019, 15 (5), 3075–3092.\\n\";\n    log << \" https://doi.org/10.1021/acs.jctc.8b01092\\n\";\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    log << \" * Additionally, if polynomial symmetry functions are used:\\n\";\n    log << \"\\n\";\n    log << \" Bircher, M. P.; Singraber, A.; Dellago, C.\\n\";\n    log << \" Improved Description of Atomic Environments Using Low-Cost\\n\";\n    log << \" Polynomial Functions with Compact Support.\\n\";\n    log << \" arXiv:2010.14414 [cond-mat, physics:physics] 2020.\\n\";\n    log << \" https://arxiv.org/abs/2010.14414\\n\";\n\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::loadSettingsFile(string const& fileName)\n{\n    log << \"\\n\";\n    log << \"*** SETUP: SETTINGS FILE ****************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    size_t numCriticalProblems = settings.loadFile(fileName);\n    log << settings.info();\n    if (numCriticalProblems > 0)\n    {\n        throw runtime_error(strpr(\"ERROR: %zu critical problem(s) were found \"\n                                  \"in settings file.\\n\", numCriticalProblems));\n    }\n\n    if (settings.keywordExists(\"nnp_type\"))\n    {\n        string nnpTypeString = settings[\"nnp_type\"];\n        if      (nnpTypeString == \"2G-HDNNP\") nnpType = NNPType::HDNNP_2G;\n        else if (nnpTypeString == \"4G-HDNNP\") nnpType = NNPType::HDNNP_4G;\n        else if (nnpTypeString == \"Q-HDNNP\")  nnpType = NNPType::HDNNP_Q;\n        else nnpType = (NNPType)atoi(settings[\"nnp_type\"].c_str());\n    }\n\n    if (nnpType == NNPType::HDNNP_2G)\n    {\n        log << \"This settings file defines a short-range NNP (2G-HDNNP).\\n\";\n    }\n    else if (nnpType == NNPType::HDNNP_4G)\n    {\n        log << \"This settings file defines a NNP with electrostatics and\\n\"\n               \"non-local charge transfer (4G-HDNNP).\\n\";\n    }\n    else if (nnpType == NNPType::HDNNP_Q)\n    {\n        log << \"This settings file defines a short-range NNP similar to\\n\"\n               \"4G-HDNNP with additional charge NN but with neither\\n\"\n               \"electrostatics nor global charge equilibration\\n\"\n               \"(method by M. Bircher).\\n\";\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown NNP type.\\n\");\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::setupGeneric(string const& nnpDir,\n                        bool skipNormalize,\n                        bool initialHardness)\n{\n    if (!skipNormalize) setupNormalization();\n    setupElementMap();\n    setupElements();\n    if (nnpType == NNPType::HDNNP_4G)\n        setupElectrostatics(initialHardness, nnpDir);\n    setupCutoff();\n    setupSymmetryFunctions();\n    setupCutoffMatrix();\n#ifndef N2P2_FULL_SFD_MEMORY\n    setupSymmetryFunctionMemory(false);\n#endif\n#ifndef N2P2_NO_SF_CACHE\n    setupSymmetryFunctionCache();\n#endif\n#ifndef N2P2_NO_SF_GROUPS\n    setupSymmetryFunctionGroups();\n#endif\n    setupNeuralNetwork();\n\n    return;\n}\n\nvoid Mode::setupNormalization(bool standalone)\n{\n    if (standalone)\n    {\n    log << \"\\n\";\n    log << \"*** SETUP: NORMALIZATION ****************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n    }\n\n    if (settings.keywordExists(\"mean_energy\") &&\n        settings.keywordExists(\"conv_energy\") &&\n        settings.keywordExists(\"conv_length\"))\n    {\n        normalize = true;\n        meanEnergy = atof(settings[\"mean_energy\"].c_str());\n        convEnergy = atof(settings[\"conv_energy\"].c_str());\n        convLength = atof(settings[\"conv_length\"].c_str());\n\n        log << \"Data set normalization is used.\\n\";\n        log << strpr(\"Mean energy per atom     : %24.16E\\n\", meanEnergy);\n        log << strpr(\"Conversion factor energy : %24.16E\\n\", convEnergy);\n        log << strpr(\"Conversion factor length : %24.16E\\n\", convLength);\n        if (settings.keywordExists(\"conv_charge\"))\n        {\n            convCharge = atof(settings[\"conv_charge\"].c_str());\n            log << strpr(\"Conversion factor charge : %24.16E\\n\",\n                         convCharge);\n        }\n        if (settings.keywordExists(\"atom_energy\"))\n        {\n            log << \"\\n\";\n            log << \"Atomic energy offsets are used in addition to\"\n                   \" data set normalization.\\n\";\n            log << \"Offsets will be subtracted from reference energies BEFORE\"\n                   \" normalization is applied.\\n\";\n        }\n    }\n    else if ((!settings.keywordExists(\"mean_energy\")) &&\n             (!settings.keywordExists(\"conv_energy\")) &&\n             (!settings.keywordExists(\"conv_length\")) &&\n             (!settings.keywordExists(\"conv_charge\")))\n    {\n        normalize = false;\n        log << \"Data set normalization is not used.\\n\";\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Incorrect usage of normalization\"\n                            \" keywords.\\n\"\n                            \"       Use all or none of \\\"mean_energy\\\", \\\"conv_energy\\\"\"\n                            \" and \\\"conv_length\\\".\\n\");\n    }\n\n    if (standalone)\n    {\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n    }\n\n    return;\n}\n\nvoid Mode::setupElementMap()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: ELEMENT MAP ******************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    elementMap.registerElements(settings[\"elements\"]);\n    log << strpr(\"Number of element strings found: %d\\n\", elementMap.size());\n    for (size_t i = 0; i < elementMap.size(); ++i)\n    {\n        log << strpr(\"Element %2zu: %2s (%3zu)\\n\", i, elementMap[i].c_str(),\n                     elementMap.atomicNumber(i));\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::setupElements()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: ELEMENTS *********************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    numElements = (size_t)atoi(settings[\"number_of_elements\"].c_str());\n    if (numElements != elementMap.size())\n    {\n        throw runtime_error(\"ERROR: Inconsistent number of elements.\\n\");\n    }\n    log << strpr(\"Number of elements is consistent: %zu\\n\", numElements);\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        elements.push_back(Element(i, elementMap));\n    }\n\n    if (settings.keywordExists(\"atom_energy\"))\n    {\n        settings::Settings::KeyRange r = settings.getValues(\"atom_energy\");\n        for (settings::Settings::KeyMap::const_iterator it = r.first;\n             it != r.second; ++it)\n        {\n            vector<string> args    = split(reduce(it->second.first));\n            size_t         element = elementMap[args.at(0)];\n            elements.at(element).\n                setAtomicEnergyOffset(atof(args.at(1).c_str()));\n        }\n    }\n    log << \"Atomic energy offsets per element:\\n\";\n    for (size_t i = 0; i < elementMap.size(); ++i)\n    {\n        log << strpr(\"Element %2zu: %16.8E\\n\",\n                     i, elements.at(i).getAtomicEnergyOffset());\n    }\n    log << \"Energy offsets are automatically subtracted from reference \"\n           \"energies.\\n\";\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::setupElectrostatics(bool   initialHardness,\n                               string directoryPrefix,\n                               string fileNameFormat)\n{\n    log << \"\\n\";\n    log << \"*** SETUP: ELECTROSTATICS ***************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    // Atomic hardness.\n    if (initialHardness)\n    {\n        settings::Settings::KeyRange r = settings.getValues(\"initial_hardness\");\n        for (settings::Settings::KeyMap::const_iterator it = r.first;\n             it != r.second; ++it)\n        {\n            vector<string> args    = split(reduce(it->second.first));\n            size_t         element = elementMap[args.at(0)];\n            double hardness = atof(args.at(1).c_str());\n            if (normalize) hardness = normalized(\"hardness\", hardness);\n            elements.at(element).setHardness(hardness);\n        }\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            double hardness = elements.at(i).getHardness();\n            if (normalize) hardness = physical(\"hardness\", hardness);\n            log << strpr(\"Initial atomic hardness for element %2s: %16.8E\\n\",\n                         elements.at(i).getSymbol().c_str(),\n                         hardness);\n        }\n    }\n    else\n    {\n        string actualFileNameFormat = directoryPrefix + fileNameFormat;\n        log << strpr(\"Atomic hardness file name format: %s\\n\",\n                     actualFileNameFormat.c_str());\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            string fileName = strpr(actualFileNameFormat.c_str(),\n                                    elements.at(i).getAtomicNumber());\n            log << strpr(\"Atomic hardness for element %2s from file %s: \",\n                         elements.at(i).getSymbol().c_str(),\n                         fileName.c_str());\n            vector<double> const data = readColumnsFromFile(fileName,\n                                                            {0}).at(0);\n            if (data.size() != 1)\n            {\n                throw runtime_error(\"ERROR: Atomic hardness data is \"\n                                    \"inconsistent.\\n\");\n            }\n            double hardness = data.at(0);\n            if (normalize) hardness = normalized(\"hardness\", hardness);\n            elements.at(i).setHardness(hardness);\n            if (normalize) hardness = physical(\"hardness\", hardness);\n            log << strpr(\"%16.8E\\n\", hardness);\n        }\n    }\n    log << \"\\n\";\n\n    // Gaussian width of charges.\n    double maxQsigma = 0.0;\n    settings::Settings::KeyRange r = settings.getValues(\"fixed_gausswidth\");\n    for (settings::Settings::KeyMap::const_iterator it = r.first;\n         it != r.second; ++it)\n    {\n        vector<string> args    = split(reduce(it->second.first));\n        size_t         element = elementMap[args.at(0)];\n        double qsigma = atof(args.at(1).c_str());\n        if (normalize) qsigma *= convLength;\n        elements.at(element).setQsigma(qsigma);\n\n        maxQsigma = max(qsigma, maxQsigma);\n    }\n    log << \"Gaussian width of charge distribution per element:\\n\";\n    for (size_t i = 0; i < elementMap.size(); ++i)\n    {\n        double qsigma = elements.at(i).getQsigma();\n        if (normalize) qsigma /= convLength;\n        log << strpr(\"Element %2zu: %16.8E\\n\",\n                     i, qsigma);\n    }\n    log << \"\\n\";\n\n    // K-Space Solver\n    if (settings.keywordExists(\"kspace_solver\"))\n    {\n        string kspace_solver_string = settings[\"kspace_solver\"];\n        if (kspace_solver_string == \"ewald\")\n        {\n            kspaceGrid.kspaceSolver = KSPACESolver::EWALD_SUM;\n        }\n        else if (kspace_solver_string == \"pppm\")\n        {\n            kspaceGrid.kspaceSolver = KSPACESolver::PPPM;\n        }\n        else if (kspace_solver_string == \"ewald_lammps\")\n        {\n            kspaceGrid.kspaceSolver = KSPACESolver::EWALD_SUM_LAMMPS;\n        }\n    }\n    else kspaceGrid.kspaceSolver = KSPACESolver::EWALD_SUM;\n\n    // Ewald truncation error method.\n    if (settings.keywordExists(\"ewald_truncation_error_method\"))\n    {\n        string truncation_method_string =\n            settings[\"ewald_truncation_error_method\"];\n        if (truncation_method_string == \"0\")\n        {\n            ewaldSetup.setTruncMethod(EWALDTruncMethod::JACKSON_CATLOW);\n        }\n        else if (truncation_method_string == \"1\")\n        {\n            ewaldSetup.setTruncMethod(EWALDTruncMethod::KOLAFA_PERRAM);\n        }\n    }\n    else ewaldSetup.setTruncMethod(EWALDTruncMethod::JACKSON_CATLOW);\n\n    // Ewald precision.\n    if (settings.keywordExists(\"ewald_prec\"))\n    {\n        vector<string> args = split(settings[\"ewald_prec\"]);\n        ewaldSetup.readFromArgs(args);\n        ewaldSetup.setMaxQSigma(maxQsigma);\n        if (normalize) ewaldSetup.toNormalizedUnits(convEnergy, convLength);\n    }\n    else if (ewaldSetup.getTruncMethod() == EWALDTruncMethod::KOLAFA_PERRAM)\n    {\n        throw runtime_error(\"ERROR: ewald_truncation_error_method 1 requires \"\n                            \"ewald_prec.\");\n    }\n    log << strpr(\"Ewald truncation error method: %16d\\n\",\n                 ewaldSetup.getTruncMethod());\n    log << strpr(\"Ewald precision:               %16.8E\\n\",\n                 ewaldSetup.getPrecision());\n    if (ewaldSetup.getTruncMethod() == EWALDTruncMethod::KOLAFA_PERRAM)\n    {\n        log << strpr(\"Ewald expected maximum charge: %16.8E\\n\",\n                     ewaldSetup.getMaxCharge());\n    }\n    log << \"\\n\";\n\n    // 4 * pi * epsilon\n    if (settings.keywordExists(\"four_pi_epsilon\"))\n        fourPiEps = atof(settings[\"four_pi_epsilon\"].c_str());\n    if (normalize)\n        fourPiEps *= pow(convCharge, 2) / (convLength * convEnergy);\n\n    // Screening function.\n    if (settings.keywordExists(\"screen_electrostatics\"))\n    {\n        vector<string> args = split(settings[\"screen_electrostatics\"]);\n        double inner = atof(args.at(0).c_str());\n        double outer = atof(args.at(1).c_str());\n        string type = \"c\"; // Default core function is cosine.\n        if (args.size() > 2) type = args.at(2); \n        screeningFunction.setInnerOuter(inner, outer);\n        screeningFunction.setCoreFunction(type);\n        for (auto s : screeningFunction.info()) log << s;\n        if (normalize) screeningFunction.changeLengthUnits(convLength);\n    }\n    else\n    {\n\t    // Set screening function in such way that it will always be 1.0.\n\t    // This may not be very efficient, may optimize later.\n        screeningFunction.setInnerOuter(-2.0, -1.0);\n\t    log << \"Screening function not used.\\n\";\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::setupCutoff()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: CUTOFF FUNCTIONS *************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    vector<string> args = split(settings[\"cutoff_type\"]);\n\n    cutoffType = (CutoffFunction::CutoffType) atoi(args.at(0).c_str());\n    if (args.size() > 1)\n    {\n        cutoffAlpha = atof(args.at(1).c_str());\n        if (0.0 < cutoffAlpha && cutoffAlpha >= 1.0)\n        {\n            throw invalid_argument(\"ERROR: 0 <= alpha < 1.0 is required.\\n\");\n        }\n    }\n    log << strpr(\"Parameter alpha for inner cutoff: %f\\n\", cutoffAlpha);\n    log << \"Inner cutoff = Symmetry function cutoff * alpha\\n\";\n\n    log << \"Equal cutoff function type for all symmetry functions:\\n\";\n    if (cutoffType == CutoffFunction::CT_COS)\n    {\n        log << strpr(\"CutoffFunction::CT_COS (%d)\\n\", cutoffType);\n        log << \"x := (r - rc * alpha) / (rc - rc * alpha)\\n\";\n        log << \"f(x) = 1/2 * (cos(pi*x) + 1)\\n\";\n    }\n    else if (cutoffType == CutoffFunction::CT_TANHU)\n    {\n        log << strpr(\"CutoffFunction::CT_TANHU (%d)\\n\", cutoffType);\n        log << \"f(r) = tanh^3(1 - r/rc)\\n\";\n        if (cutoffAlpha > 0.0)\n        {\n            log << \"WARNING: Inner cutoff parameter not used in combination\"\n                   \" with this cutoff function.\\n\";\n        }\n    }\n    else if (cutoffType == CutoffFunction::CT_TANH)\n    {\n        log << strpr(\"CutoffFunction::CT_TANH (%d)\\n\", cutoffType);\n        log << \"f(r) = c * tanh^3(1 - r/rc), f(0) = 1\\n\";\n        if (cutoffAlpha > 0.0)\n        {\n            log << \"WARNING: Inner cutoff parameter not used in combination\"\n                   \" with this cutoff function.\\n\";\n        }\n    }\n    else if (cutoffType == CutoffFunction::CT_POLY1)\n    {\n        log << strpr(\"CutoffFunction::CT_POLY1 (%d)\\n\", cutoffType);\n        log << \"x := (r - rc * alpha) / (rc - rc * alpha)\\n\";\n        log << \"f(x) = (2x - 3)x^2 + 1\\n\";\n    }\n    else if (cutoffType == CutoffFunction::CT_POLY2)\n    {\n        log << strpr(\"CutoffFunction::CT_POLY2 (%d)\\n\", cutoffType);\n        log << \"x := (r - rc * alpha) / (rc - rc * alpha)\\n\";\n        log << \"f(x) = ((15 - 6x)x - 10)x^3 + 1\\n\";\n    }\n    else if (cutoffType == CutoffFunction::CT_POLY3)\n    {\n        log << strpr(\"CutoffFunction::CT_POLY3 (%d)\\n\", cutoffType);\n        log << \"x := (r - rc * alpha) / (rc - rc * alpha)\\n\";\n        log << \"f(x) = (x(x(20x - 70) + 84) - 35)x^4 + 1\\n\";\n    }\n    else if (cutoffType == CutoffFunction::CT_POLY4)\n    {\n        log << strpr(\"CutoffFunction::CT_POLY4 (%d)\\n\", cutoffType);\n        log << \"x := (r - rc * alpha) / (rc - rc * alpha)\\n\";\n        log << \"f(x) = (x(x((315 - 70x)x - 540) + 420) - 126)x^5 + 1\\n\";\n    }\n    else if (cutoffType == CutoffFunction::CT_EXP)\n    {\n        log << strpr(\"CutoffFunction::CT_EXP (%d)\\n\", cutoffType);\n        log << \"x := (r - rc * alpha) / (rc - rc * alpha)\\n\";\n        log << \"f(x) = exp(-1 / 1 - x^2)\\n\";\n    }\n    else if (cutoffType == CutoffFunction::CT_HARD)\n    {\n        log << strpr(\"CutoffFunction::CT_HARD (%d)\\n\", cutoffType);\n        log << \"f(r) = 1\\n\";\n        log << \"WARNING: Hard cutoff used!\\n\";\n    }\n    else\n    {\n        throw invalid_argument(\"ERROR: Unknown cutoff type.\\n\");\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::setupSymmetryFunctions()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: SYMMETRY FUNCTIONS ***********\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    settings::Settings::KeyRange r = settings.getValues(\"symfunction_short\");\n    for (settings::Settings::KeyMap::const_iterator it = r.first; it != r.second; ++it)\n    {\n        vector<string> args    = split(reduce(it->second.first));\n        size_t         element = elementMap[args.at(0)];\n\n        elements.at(element).addSymmetryFunction(it->second.first,\n                                                 it->second.second);\n    }\n\n    log << \"Abbreviations:\\n\";\n    log << \"--------------\\n\";\n    log << \"ind .... Symmetry function index.\\n\";\n    log << \"ec ..... Central atom element.\\n\";\n    log << \"tp ..... Symmetry function type.\\n\";\n    log << \"sbtp ... Symmetry function subtype (e.g. cutoff type).\\n\";\n    log << \"e1 ..... Neighbor 1 element.\\n\";\n    log << \"e2 ..... Neighbor 2 element.\\n\";\n    log << \"eta .... Gaussian width eta.\\n\";\n    log << \"rs/rl... Shift distance of Gaussian or left cutoff radius \"\n           \"for polynomial.\\n\";\n    log << \"angl.... Left cutoff angle for polynomial.\\n\";\n    log << \"angr.... Right cutoff angle for polynomial.\\n\";\n    log << \"la ..... Angle prefactor lambda.\\n\";\n    log << \"zeta ... Angle term exponent zeta.\\n\";\n    log << \"rc ..... Cutoff radius / right cutoff radius for polynomial.\\n\";\n    log << \"a ...... Free parameter alpha (e.g. cutoff alpha).\\n\";\n    log << \"ln ..... Line number in settings file.\\n\";\n    log << \"\\n\";\n    maxCutoffRadius = 0.0;\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        if (normalize) it->changeLengthUnitSymmetryFunctions(convLength);\n        it->sortSymmetryFunctions();\n        maxCutoffRadius = max(it->getMaxCutoffRadius(), maxCutoffRadius);\n        it->setCutoffFunction(cutoffType, cutoffAlpha);\n        log << strpr(\"Short range atomic symmetry functions element %2s :\\n\",\n                     it->getSymbol().c_str());\n        log << \"--------------------------------------------------\"\n               \"-----------------------------------------------\\n\";\n        log << \" ind ec tp sbtp e1 e2       eta      rs/rl         \"\n               \"rc   angl   angr la zeta    a    ln\\n\";\n        log << \"--------------------------------------------------\"\n               \"-----------------------------------------------\\n\";\n        log << it->infoSymmetryFunctionParameters();\n        log << \"--------------------------------------------------\"\n               \"-----------------------------------------------\\n\";\n    }\n    minNeighbors.clear();\n    minNeighbors.resize(numElements, 0);\n    minCutoffRadius.clear();\n    minCutoffRadius.resize(numElements, maxCutoffRadius);\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        minNeighbors.at(i) = elements.at(i).getMinNeighbors();\n        minCutoffRadius.at(i) = elements.at(i).getMinCutoffRadius();\n        log << strpr(\"Minimum cutoff radius for element %2s: %f\\n\",\n                     elements.at(i).getSymbol().c_str(),\n                     minCutoffRadius.at(i) / convLength);\n    }\n    log << strpr(\"Maximum cutoff radius (global)      : %f\\n\",\n                 maxCutoffRadius / convLength);\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::setupSymmetryFunctionScalingNone()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: SYMMETRY FUNCTION SCALING ****\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << \"No scaling for symmetry functions.\\n\";\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        it->setScalingNone();\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::setupSymmetryFunctionScaling(string const& fileName)\n{\n    log << \"\\n\";\n    log << \"*** SETUP: SYMMETRY FUNCTION SCALING ****\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << \"Equal scaling type for all symmetry functions:\\n\";\n    if (   ( settings.keywordExists(\"scale_symmetry_functions\" ))\n        && (!settings.keywordExists(\"center_symmetry_functions\")))\n    {\n        scalingType = SymFnc::ST_SCALE;\n        log << strpr(\"Scaling type::ST_SCALE (%d)\\n\", scalingType);\n        log << \"Gs = Smin + (Smax - Smin) * (G - Gmin) / (Gmax - Gmin)\\n\";\n    }\n    else if (   (!settings.keywordExists(\"scale_symmetry_functions\" ))\n             && ( settings.keywordExists(\"center_symmetry_functions\")))\n    {\n        scalingType = SymFnc::ST_CENTER;\n        log << strpr(\"Scaling type::ST_CENTER (%d)\\n\", scalingType);\n        log << \"Gs = G - Gmean\\n\";\n    }\n    else if (   ( settings.keywordExists(\"scale_symmetry_functions\" ))\n             && ( settings.keywordExists(\"center_symmetry_functions\")))\n    {\n        scalingType = SymFnc::ST_SCALECENTER;\n        log << strpr(\"Scaling type::ST_SCALECENTER (%d)\\n\", scalingType);\n        log << \"Gs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\\n\";\n    }\n    else if (settings.keywordExists(\"scale_symmetry_functions_sigma\"))\n    {\n        scalingType = SymFnc::ST_SCALESIGMA;\n        log << strpr(\"Scaling type::ST_SCALESIGMA (%d)\\n\", scalingType);\n        log << \"Gs = Smin + (Smax - Smin) * (G - Gmean) / Gsigma\\n\";\n    }\n    else\n    {\n        scalingType = SymFnc::ST_NONE;\n        log << strpr(\"Scaling type::ST_NONE (%d)\\n\", scalingType);\n        log << \"Gs = G\\n\";\n        log << \"WARNING: No symmetry function scaling!\\n\";\n    }\n\n    double Smin = 0.0;\n    double Smax = 0.0;\n    if (scalingType == SymFnc::ST_SCALE ||\n        scalingType == SymFnc::ST_SCALECENTER ||\n        scalingType == SymFnc::ST_SCALESIGMA)\n    {\n        if (settings.keywordExists(\"scale_min_short\"))\n        {\n            Smin = atof(settings[\"scale_min_short\"].c_str());\n        }\n        else\n        {\n            log << \"WARNING: Keyword \\\"scale_min_short\\\" not found.\\n\";\n            log << \"         Default value for Smin = 0.0.\\n\";\n            Smin = 0.0;\n        }\n\n        if (settings.keywordExists(\"scale_max_short\"))\n        {\n            Smax = atof(settings[\"scale_max_short\"].c_str());\n        }\n        else\n        {\n            log << \"WARNING: Keyword \\\"scale_max_short\\\" not found.\\n\";\n            log << \"         Default value for Smax = 1.0.\\n\";\n            Smax = 1.0;\n        }\n\n        log << strpr(\"Smin = %f\\n\", Smin);\n        log << strpr(\"Smax = %f\\n\", Smax);\n    }\n\n    log << strpr(\"Symmetry function scaling statistics from file: %s\\n\",\n                 fileName.c_str());\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    ifstream file;\n    file.open(fileName.c_str());\n    if (!file.is_open())\n    {\n        throw runtime_error(\"ERROR: Could not open file: \\\"\" + fileName\n                            + \"\\\".\\n\");\n    }\n    string line;\n    vector<string> lines;\n    while (getline(file, line))\n    {\n        if (line.at(0) != '#') lines.push_back(line);\n    }\n    file.close();\n\n    log << \"\\n\";\n    log << \"Abbreviations:\\n\";\n    log << \"--------------\\n\";\n    log << \"ind ..... Symmetry function index.\\n\";\n    log << \"min ..... Minimum symmetry function value.\\n\";\n    log << \"max ..... Maximum symmetry function value.\\n\";\n    log << \"mean .... Mean symmetry function value.\\n\";\n    log << \"sigma ... Standard deviation of symmetry function values.\\n\";\n    log << \"sf ...... Scaling factor for derivatives.\\n\";\n    log << \"Smin .... Desired minimum scaled symmetry function value.\\n\";\n    log << \"Smax .... Desired maximum scaled symmetry function value.\\n\";\n    log << \"t ....... Scaling type.\\n\";\n    log << \"\\n\";\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        it->setScaling(scalingType, lines, Smin, Smax);\n        log << strpr(\"Scaling data for symmetry functions element %2s :\\n\",\n                     it->getSymbol().c_str());\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        log << \" ind       min       max      mean     sigma        sf  Smin  Smax t\\n\";\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        log << it->infoSymmetryFunctionScaling();\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        lines.erase(lines.begin(), lines.begin() + it->numSymmetryFunctions());\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::setupSymmetryFunctionGroups()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: SYMMETRY FUNCTION GROUPS *****\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << \"Abbreviations:\\n\";\n    log << \"--------------\\n\";\n    log << \"ind .... Symmetry function index.\\n\";\n    log << \"ec ..... Central atom element.\\n\";\n    log << \"tp ..... Symmetry function type.\\n\";\n    log << \"sbtp ... Symmetry function subtype (e.g. cutoff type).\\n\";\n    log << \"e1 ..... Neighbor 1 element.\\n\";\n    log << \"e2 ..... Neighbor 2 element.\\n\";\n    log << \"eta .... Gaussian width eta.\\n\";\n    log << \"rs/rl... Shift distance of Gaussian or left cutoff radius \"\n           \"for polynomial.\\n\";\n    log << \"angl.... Left cutoff angle for polynomial.\\n\";\n    log << \"angr.... Right cutoff angle for polynomial.\\n\";\n    log << \"la ..... Angle prefactor lambda.\\n\";\n    log << \"zeta ... Angle term exponent zeta.\\n\";\n    log << \"rc ..... Cutoff radius / right cutoff radius for polynomial.\\n\";\n    log << \"a ...... Free parameter alpha (e.g. cutoff alpha).\\n\";\n    log << \"ln ..... Line number in settings file.\\n\";\n    log << \"mi ..... Member index.\\n\";\n    log << \"sfi .... Symmetry function index.\\n\";\n    log << \"e ...... Recalculate exponential term.\\n\";\n    log << \"\\n\";\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        it->setupSymmetryFunctionGroups();\n        log << strpr(\"Short range atomic symmetry function groups \"\n                     \"element %2s :\\n\", it->getSymbol().c_str());\n        log << \"------------------------------------------------------\"\n               \"----------------------------------------------------\\n\";\n        log << \" ind ec tp sbtp e1 e2       eta      rs/rl         \"\n               \"rc   angl   angr la zeta    a    ln   mi  sfi e\\n\";\n        log << \"------------------------------------------------------\"\n               \"----------------------------------------------------\\n\";\n        log << it->infoSymmetryFunctionGroups();\n        log << \"------------------------------------------------------\"\n               \"----------------------------------------------------\\n\";\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::setupSymmetryFunctionMemory(bool verbose)\n{\n    log << \"\\n\";\n    log << \"*** SETUP: SYMMETRY FUNCTION MEMORY *****\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    for (auto& e : elements)\n    {\n        e.setupSymmetryFunctionMemory();\n        vector<size_t> symmetryFunctionNumTable\n            = e.getSymmetryFunctionNumTable();\n        vector<vector<size_t>> symmetryFunctionTable\n            = e.getSymmetryFunctionTable();\n        log << strpr(\"Symmetry function derivatives memory table \"\n                     \"for element %2s :\\n\", e.getSymbol().c_str());\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        log << \"Relevant symmetry functions for neighbors with element:\\n\";\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            log << strpr(\"- %2s: %4zu of %4zu (%5.1f %)\\n\",\n                         elementMap[i].c_str(),\n                         symmetryFunctionNumTable.at(i),\n                         e.numSymmetryFunctions(),\n                         (100.0 * symmetryFunctionNumTable.at(i))\n                         / e.numSymmetryFunctions());\n            if (verbose)\n            {\n                log << \"-----------------------------------------\"\n                       \"--------------------------------------\\n\";\n                for (auto isf : symmetryFunctionTable.at(i))\n                {\n                    SymFnc const& sf = e.getSymmetryFunction(isf);\n                    log << sf.parameterLine();\n                }\n                log << \"-----------------------------------------\"\n                       \"--------------------------------------\\n\";\n            }\n        }\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n    }\n    if (verbose)\n    {\n        for (auto& e : elements)\n        {\n            log << strpr(\"%2s - symmetry function per-element index table:\\n\",\n                         e.getSymbol().c_str());\n            log << \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n            log << \" ind\";\n            for (size_t i = 0; i < numElements; ++i)\n            {\n                log << strpr(\" %4s\", elementMap[i].c_str());\n            }\n            log << \"\\n\";\n            log << \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n            for (size_t i = 0; i < e.numSymmetryFunctions(); ++i)\n            {\n                SymFnc const& sf = e.getSymmetryFunction(i);\n                log << strpr(\"%4zu\", sf.getIndex() + 1);\n                vector<size_t> indexPerElement = sf.getIndexPerElement();\n                for (auto ipe : sf.getIndexPerElement())\n                {\n                    if (ipe == numeric_limits<size_t>::max())\n                    {\n                        log << strpr(\"     \");\n                    }\n                    else\n                    {\n                        log << strpr(\" %4zu\", ipe + 1);\n                    }\n                }\n                log << \"\\n\";\n            }\n            log << \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n        }\n\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvoid Mode::setupSymmetryFunctionCache(bool verbose)\n{\n    log << \"\\n\";\n    log << \"*** SETUP: SYMMETRY FUNCTION CACHE ******\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        using SFCacheList = Element::SFCacheList;\n        vector<vector<SFCacheList>> cacheLists(numElements);\n        Element& e = elements.at(i);\n        for (size_t j = 0; j < e.numSymmetryFunctions(); ++j)\n        {\n            SymFnc const& s = e.getSymmetryFunction(j);\n            for (auto identifier : s.getCacheIdentifiers())\n            {\n                size_t ne = atoi(split(identifier)[0].c_str());\n                bool unknown = true;\n                for (auto& c : cacheLists.at(ne))\n                {\n                    if (identifier == c.identifier)\n                    {\n                        c.indices.push_back(s.getIndex());\n                        unknown = false;\n                        break;\n                    }\n                }\n                if (unknown)\n                {\n                    cacheLists.at(ne).push_back(SFCacheList());\n                    cacheLists.at(ne).back().element = ne;\n                    cacheLists.at(ne).back().identifier = identifier;\n                    cacheLists.at(ne).back().indices.push_back(s.getIndex());\n                }\n            }\n        }\n        if (verbose)\n        {\n            log << strpr(\"Multiple cache identifiers for element %2s:\\n\\n\",\n                         e.getSymbol().c_str());\n        }\n        double cacheUsageMean = 0.0;\n        size_t cacheCount = 0;\n        for (size_t j = 0; j < numElements; ++j)\n        {\n            if (verbose)\n            {\n                log << strpr(\"Neighbor %2s:\\n\", elementMap[j].c_str());\n            }\n            vector<SFCacheList>& c = cacheLists.at(j);\n            c.erase(remove_if(c.begin(),\n                              c.end(),\n                              [](SFCacheList l)\n                              {\n                                  return l.indices.size() <= 1;\n                              }), c.end());\n            cacheCount += c.size();\n            for (size_t k = 0; k < c.size(); ++k)\n            {\n                cacheUsageMean += c.at(k).indices.size();\n                if (verbose)\n                {\n                    log << strpr(\"Cache %zu, Identifier \\\"%s\\\", \"\n                                 \"Symmetry functions\",\n                                 k, c.at(k).identifier.c_str());\n                    for (auto si : c.at(k).indices)\n                    {\n                        log << strpr(\" %zu\", si);\n                    }\n                    log << \"\\n\";\n                }\n            }\n        }\n        e.setCacheIndices(cacheLists);\n        //for (size_t j = 0; j < e.numSymmetryFunctions(); ++j)\n        //{\n        //    SymFnc const& sf = e.getSymmetryFunction(j);\n        //    auto indices = sf.getCacheIndices();\n        //    size_t count = 0;\n        //    for (size_t k = 0; k < numElements; ++k)\n        //    {\n        //        count += indices.at(k).size();\n        //    }\n        //    if (count > 0)\n        //    {\n        //        log << strpr(\"SF %4zu:\\n\", sf.getIndex());\n        //    }\n        //    for (size_t k = 0; k < numElements; ++k)\n        //    {\n        //        if (indices.at(k).size() > 0)\n        //        {\n        //            log << strpr(\"- Neighbor %2s:\", elementMap[k].c_str());\n        //            for (size_t l = 0; l < indices.at(k).size(); ++l)\n        //            {\n        //                log << strpr(\" %zu\", indices.at(k).at(l));\n        //            }\n        //            log << \"\\n\";\n        //        }\n        //    }\n        //}\n        cacheUsageMean /= cacheCount;\n        log << strpr(\"Element %2s: in total %zu caches, \"\n                     \"used %3.2f times on average.\\n\",\n                     e.getSymbol().c_str(), cacheCount, cacheUsageMean);\n        if (verbose)\n        {\n            log << \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n        }\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n#endif\n\nvoid Mode::setupSymmetryFunctionStatistics(bool collectStatistics,\n                                           bool collectExtrapolationWarnings,\n                                           bool writeExtrapolationWarnings,\n                                           bool stopOnExtrapolationWarnings)\n{\n    log << \"\\n\";\n    log << \"*** SETUP: SYMMETRY FUNCTION STATISTICS *\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << \"Equal symmetry function statistics for all elements.\\n\";\n    log << strpr(\"Collect min/max/mean/sigma                        : %d\\n\",\n                 (int)collectStatistics);\n    log << strpr(\"Collect extrapolation warnings                    : %d\\n\",\n                 (int)collectExtrapolationWarnings);\n    log << strpr(\"Write extrapolation warnings immediately to stderr: %d\\n\",\n                 (int)writeExtrapolationWarnings);\n    log << strpr(\"Halt on any extrapolation warning                 : %d\\n\",\n                 (int)stopOnExtrapolationWarnings);\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        it->statistics.collectStatistics = collectStatistics;\n        it->statistics.collectExtrapolationWarnings =\n                                                  collectExtrapolationWarnings;\n        it->statistics.writeExtrapolationWarnings = writeExtrapolationWarnings;\n        it->statistics.stopOnExtrapolationWarnings =\n                                                   stopOnExtrapolationWarnings;\n    }\n\n    checkExtrapolationWarnings = collectStatistics\n                              || collectExtrapolationWarnings\n                              || writeExtrapolationWarnings\n                              || stopOnExtrapolationWarnings;\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n    return;\n}\n\nvoid Mode::setupCutoffMatrix()\n{\n    double rCutScreen = screeningFunction.getOuter();\n    cutoffs.resize(numElements);\n    for(auto const& e : elements)\n    {\n        e.getCutoffRadii(cutoffs.at(e.getIndex()));\n        if ( rCutScreen > 0 &&\n             !vectorContains(cutoffs.at(e.getIndex()), rCutScreen) )\n        {\n            cutoffs.at(e.getIndex()).push_back(rCutScreen);\n        }\n    }\n}\n\nvoid Mode::setupNeuralNetwork()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: NEURAL NETWORKS **************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    string id;\n\n    // Some NNP types require extra NNs.\n    if (nnpType == NNPType::HDNNP_4G)\n    {\n        id = \"elec\";\n        nnk.push_back(id);\n        nns[id].id = id;\n        nns.at(id).name = \"electronegativity\";\n        nns.at(id).weightFileFormat = \"weightse.%03zu.data\";\n        nns.at(id).keywordSuffix = \"_electrostatic\";\n        nns.at(id).keywordSuffix2 = \"_charge\";\n    }\n    else if(nnpType == NNPType::HDNNP_Q)\n    {\n        id = \"elec\";\n        nnk.push_back(id);\n        nns[id].id = id;\n        nns.at(id).name = \"charge\";\n        nns.at(id).weightFileFormat = \"weightse.%03zu.data\";\n        nns.at(id).keywordSuffix = \"_electrostatic\";\n        nns.at(id).keywordSuffix2 = \"_charge\";\n    }\n\n    // All NNP types contain a short range NN.\n    id = \"short\";\n    nnk.push_back(id);\n    nns[id].id = id;\n    nns.at(id).name = \"short range\";\n    nns.at(id).weightFileFormat = \"weights.%03zu.data\";\n    nns.at(id).keywordSuffix = \"_short\";\n    nns.at(id).keywordSuffix2 = \"_short\";\n\n    // Loop over all NNs and set global properties.\n    for (auto& k : nnk)\n    {\n        // Each elements number of hidden layers.\n        size_t globalNumHiddenLayers = 0;\n        // Abbreviation for current NN.\n        NNSetup& nn = nns.at(k);\n        // Set size of NN topology vector.\n        nn.topology.resize(numElements);\n        // First, check for global number of hidden layers.\n        string keyword = \"global_hidden_layers\" + nn.keywordSuffix;\n        if (settings.keywordExists(keyword))\n        {\n            globalNumHiddenLayers = atoi(settings[keyword].c_str());\n            for (auto& t : nn.topology)\n            {\n                t.numLayers = globalNumHiddenLayers + 2;\n            }\n        }\n        // Now, check for per-element number of hidden layers.\n        keyword = \"element_hidden_layers\" + nn.keywordSuffix;\n        if (settings.keywordExists(keyword))\n        {\n            settings::Settings::KeyRange r = settings.getValues(keyword);\n            for (settings::Settings::KeyMap::const_iterator it = r.first;\n                 it != r.second; ++it)\n            {\n                vector<string> args = split(reduce(it->second.first));\n                size_t const e = elementMap[args.at(0)];\n                size_t const n = atoi(args.at(1).c_str());\n                nn.topology.at(e).numLayers = n + 2;\n            }\n        }\n        // Check whether user has set all NN's number of layers correctly.\n        for (auto& t : nn.topology)\n        {\n            if (t.numLayers == 0)\n            {\n                throw runtime_error(\"ERROR: Number of neural network hidden \"\n                                    \"layers unset for some elements.\\n\");\n            }\n        }\n        // Finally, allocate NN topologies data.\n        for (auto& t : nn.topology)\n        {\n            t.numNeuronsPerLayer.resize(t.numLayers, 0);\n            t.activationFunctionsPerLayer.resize(t.numLayers,\n                                                 NeuralNetwork::AF_UNSET);\n        }\n\n        // Now read global number of neurons and activation functions.\n        vector<string> globalNumNeuronsPerHiddenLayer;\n        keyword = \"global_nodes\" + nn.keywordSuffix;\n        if (settings.keywordExists(keyword))\n        {\n            globalNumNeuronsPerHiddenLayer = split(reduce(settings[keyword]));\n            if (globalNumHiddenLayers != globalNumNeuronsPerHiddenLayer.size())\n            {\n                throw runtime_error(strpr(\"ERROR: Inconsistent global NN \"\n                                          \"topology keyword \\\"%s\\\".\\n\",\n                                          keyword.c_str()));\n            }\n        }\n        vector<string> globalActivationFunctions;\n        keyword = \"global_activation\" + nn.keywordSuffix;\n        if (settings.keywordExists(keyword))\n        {\n            globalActivationFunctions = split(reduce(settings[keyword]));\n            if (globalNumHiddenLayers != globalActivationFunctions.size() - 1)\n            {\n                throw runtime_error(strpr(\"ERROR: Inconsistent global NN \"\n                                          \"topology keyword \\\"%s\\\".\\n\",\n                                          keyword.c_str()));\n            }\n        }\n        // Set global number of neurons and activation functions if provided.\n        bool globalNumNeurons = (globalNumNeuronsPerHiddenLayer.size() != 0);\n        bool globalActivation = (globalActivationFunctions.size() != 0);\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            NNSetup::Topology& t = nn.topology.at(i);\n            size_t const nsf = elements.at(i).numSymmetryFunctions();\n            // Set input layer. Number of input layer neurons depends on NNP\n            // type and NN purpose.\n            if (nnpType == NNPType::HDNNP_2G)\n            {\n                // Can assume NN id is \"short\".\n                t.numNeuronsPerLayer.at(0) = nsf;\n            }\n            else if (nnpType == NNPType::HDNNP_4G ||\n                     nnpType == NNPType::HDNNP_Q)\n            {\n                // NN with id \"elec\" requires only SFs.\n                if (k == \"elec\") t.numNeuronsPerLayer.at(0) = nsf;\n                // \"short\" NN needs extra charge neuron.\n                else if (k == \"short\") t.numNeuronsPerLayer.at(0) = nsf + 1;\n            }\n            // Set dummy input neuron activation function.\n            t.activationFunctionsPerLayer.at(0) = NeuralNetwork::AF_IDENTITY;\n            // Set output layer. Assume single output neuron.\n            t.numNeuronsPerLayer.at(t.numLayers - 1) = 1;\n            // If this element's NN does not use the global number of hidden\n            // layers it makes no sense to set the global number of hidden\n            // neurons or activation functions. Hence, skip the settings here,\n            // appropriate settings should follow later in the per-element\n            // section.\n            if ((size_t)t.numLayers != globalNumHiddenLayers + 2) continue;\n            for (int j = 1; j < t.numLayers; ++j)\n            {\n                if ((j == t.numLayers - 1) && globalActivation)\n                {\n                    t.activationFunctionsPerLayer.at(j) = activationFromString(\n                        globalActivationFunctions.at(t.numLayers - 2));\n                }\n                else\n                {\n                    if (globalNumNeurons)\n                    {\n                        t.numNeuronsPerLayer.at(j) = atoi(\n                            globalNumNeuronsPerHiddenLayer.at(j - 1).c_str());\n                    }\n                    if (globalActivation)\n                    {\n                        t.activationFunctionsPerLayer.at(j) =\n                            activationFromString(\n                                globalActivationFunctions.at(j - 1));\n                    }\n                }\n            }\n        }\n        // Override global number of neurons with per-element keyword.\n        keyword = \"element_nodes\" + nn.keywordSuffix;\n        if (settings.keywordExists(keyword))\n        {\n            settings::Settings::KeyRange r = settings.getValues(keyword);\n            for (settings::Settings::KeyMap::const_iterator it = r.first;\n                 it != r.second; ++it)\n            {\n                vector<string> args = split(reduce(it->second.first));\n                size_t e = elementMap[args.at(0)];\n                size_t n = args.size() - 1;\n                NNSetup::Topology& t = nn.topology.at(e);\n                if ((size_t)t.numLayers != n + 2)\n                {\n                    throw runtime_error(strpr(\"ERROR: Inconsistent per-element\"\n                                              \" NN topology keyword \\\"%s\\\".\\n\",\n                                              keyword.c_str()));\n                }\n                for (int j = 1; j < t.numLayers - 2; ++j)\n                {\n                    t.numNeuronsPerLayer.at(j) = atoi(args.at(j).c_str());\n                }\n            }\n        }\n        // Override global activation functions with per-element keyword.\n        keyword = \"element_activation\" + nn.keywordSuffix;\n        if (settings.keywordExists(keyword))\n        {\n            settings::Settings::KeyRange r = settings.getValues(keyword);\n            for (settings::Settings::KeyMap::const_iterator it = r.first;\n                 it != r.second; ++it)\n            {\n                vector<string> args = split(reduce(it->second.first));\n                size_t e = elementMap[args.at(0)];\n                size_t n = args.size() - 1;\n                NNSetup::Topology& t = nn.topology.at(e);\n                if ((size_t)t.numLayers != n + 1)\n                {\n                    throw runtime_error(strpr(\"ERROR: Inconsistent per-element\"\n                                              \" NN topology keyword \\\"%s\\\".\\n\",\n                                              keyword.c_str()));\n                }\n                for (int j = 1; j < t.numLayers - 1; ++j)\n                {\n                    t.activationFunctionsPerLayer.at(j) =\n                        activationFromString(args.at(j).c_str());\n                }\n            }\n        }\n\n        // Finally check everything for any unset NN property.\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            NNSetup::Topology const& t = nn.topology.at(i);\n            for (int j = 0; j < t.numLayers; ++j)\n            {\n                if (t.numNeuronsPerLayer.at(j) == 0)\n                {\n                    throw runtime_error(strpr(\n                              \"ERROR: NN \\\"%s\\\", element %2s: number of \"\n                              \"neurons for layer %d unset.\\n\",\n                              nn.id.c_str(),\n                              elements.at(i).getSymbol().c_str(),\n                              j));\n                }\n                if (t.activationFunctionsPerLayer.at(j)\n                        == NeuralNetwork::AF_UNSET)\n                {\n                    throw runtime_error(strpr(\n                              \"ERROR: NN \\\"%s\\\", element %2s: activation \"\n                              \"functions for layer %d unset.\\n\",\n                              nn.id.c_str(),\n                              elements.at(i).getSymbol().c_str(),\n                              j));\n                }\n            }\n        }\n    }\n\n\n    bool normalizeNeurons = settings.keywordExists(\"normalize_nodes\");\n    log << strpr(\"Normalize neurons (all elements): %d\\n\",\n                 (int)normalizeNeurons);\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n\n    // Finally, allocate all neural networks.\n    for (auto& k : nnk)\n    {\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            Element& e = elements.at(i);\n            NNSetup::Topology const& t = nns.at(k).topology.at(i);\n            e.neuralNetworks.emplace(\n                                    piecewise_construct,\n                                    forward_as_tuple(k),\n                                    forward_as_tuple(\n                                        t.numLayers,\n                                        t.numNeuronsPerLayer.data(),\n                                        t.activationFunctionsPerLayer.data()));\n            e.neuralNetworks.at(k).setNormalizeNeurons(normalizeNeurons);\n            log << strpr(\"Atomic %s NN for \"\n                         \"element %2s :\\n\",\n                         nns.at(k).name.c_str(),\n                         e.getSymbol().c_str());\n            log << e.neuralNetworks.at(k).info();\n            log << \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n        }\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::setupNeuralNetworkWeights(map<string, string> fileNameFormats)\n{\n    setupNeuralNetworkWeights(\"\", fileNameFormats);\n    return;\n}\n\nvoid Mode::setupNeuralNetworkWeights(string              directoryPrefix,\n                                     map<string, string> fileNameFormats)\n{\n    log << \"\\n\";\n    log << \"*** SETUP: NEURAL NETWORK WEIGHTS *******\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    for (auto k : nnk)\n    {\n        string actualFileNameFormat;\n        if (fileNameFormats.find(k) != fileNameFormats.end())\n        {\n            actualFileNameFormat = fileNameFormats.at(k);\n        }\n        else actualFileNameFormat = nns.at(k).weightFileFormat;\n        actualFileNameFormat = directoryPrefix + actualFileNameFormat;\n        log << strpr(\"%s weight file name format: %s\\n\",\n                     cap(nns.at(k).name).c_str(),\n                     actualFileNameFormat.c_str());\n        readNeuralNetworkWeights(k, actualFileNameFormat);\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Mode::calculateSymmetryFunctions(Structure& structure,\n                                      bool const derivatives)\n{\n    // Skip calculation for whole structure if results are already saved.\n    if (structure.hasSymmetryFunctionDerivatives) return;\n    if (structure.hasSymmetryFunctions && !derivatives) return;\n\n    Atom* a = NULL;\n    Element* e = NULL;\n#ifdef _OPENMP\n    #pragma omp parallel for private (a, e)\n#endif\n    for (size_t i = 0; i < structure.atoms.size(); ++i)\n    {\n        // Pointer to atom.\n        a = &(structure.atoms.at(i));\n\n        // Skip calculation for individual atom if results are already saved.\n        if (a->hasSymmetryFunctionDerivatives) continue;\n        if (a->hasSymmetryFunctions && !derivatives) continue;\n\n        // Inform atom if extra charge neuron is present in short-range NN.\n        if (nnpType == NNPType::HDNNP_4G ||\n            nnpType == NNPType::HDNNP_Q) a->useChargeNeuron = true;\n\n        // Get element of atom and set number of symmetry functions.\n        e = &(elements.at(a->element));\n        a->numSymmetryFunctions = e->numSymmetryFunctions();\n        if (derivatives)\n        {\n            a->numSymmetryFunctionDerivatives\n                = e->getSymmetryFunctionNumTable();\n        }\n#ifndef N2P2_NO_SF_CACHE\n        a->cacheSizePerElement = e->getCacheSizes();\n#endif\n\n#ifndef N2P2_NO_NEIGH_CHECK\n        // Check if atom has low number of neighbors.\n        size_t numNeighbors = a->calculateNumNeighbors(\n                minCutoffRadius.at(e->getIndex()));\n        if (numNeighbors < minNeighbors.at(e->getIndex()))\n        {\n            log << strpr(\"WARNING: Structure %6zu Atom %6zu : %zu \"\n                         \"neighbors.\\n\",\n                         a->indexStructure,\n                         a->index,\n                         numNeighbors);\n        }\n#endif\n\n        // Allocate symmetry function data vectors in atom.\n        a->allocate(derivatives, maxCutoffRadius);\n\n        // Calculate symmetry functions (and derivatives).\n        e->calculateSymmetryFunctions(*a, derivatives);\n\n        // Remember that symmetry functions of this atom have been calculated.\n        a->hasSymmetryFunctions = true;\n        if (derivatives) a->hasSymmetryFunctionDerivatives = true;\n    }\n\n    // If requested, check extrapolation warnings or update statistics.\n    // Needed to shift this out of the loop above to make it thread-safe.\n    if (checkExtrapolationWarnings)\n    {\n        for (size_t i = 0; i < structure.atoms.size(); ++i)\n        {\n            a = &(structure.atoms.at(i));\n            e = &(elements.at(a->element));\n            e->updateSymmetryFunctionStatistics(*a);\n        }\n    }\n\n    // Remember that symmetry functions of this structure have been calculated.\n    structure.hasSymmetryFunctions = true;\n    if (derivatives) structure.hasSymmetryFunctionDerivatives = true;\n\n    return;\n}\n\nvoid Mode::calculateSymmetryFunctionGroups(Structure& structure,\n                                           bool const derivatives)\n{\n    // Skip calculation for whole structure if results are already saved.\n    if (structure.hasSymmetryFunctionDerivatives) return;\n    if (structure.hasSymmetryFunctions && !derivatives) return;\n\n    Atom* a = NULL;\n    Element* e = NULL;\n#ifdef _OPENMP\n    #pragma omp parallel for private (a, e)\n#endif\n    for (size_t i = 0; i < structure.atoms.size(); ++i)\n    {\n        // Pointer to atom.\n        a = &(structure.atoms.at(i));\n\n        // Skip calculation for individual atom if results are already saved.\n        if (a->hasSymmetryFunctionDerivatives) continue;\n        if (a->hasSymmetryFunctions && !derivatives) continue;\n\n        // Inform atom if extra charge neuron is present in short-range NN.\n        if (nnpType == NNPType::HDNNP_4G ||\n            nnpType == NNPType::HDNNP_Q) a->useChargeNeuron = true;\n\n        // Get element of atom and set number of symmetry functions.\n        e = &(elements.at(a->element));\n        a->numSymmetryFunctions = e->numSymmetryFunctions();\n        if (derivatives)\n        {\n            a->numSymmetryFunctionDerivatives\n                = e->getSymmetryFunctionNumTable();\n        }\n#ifndef N2P2_NO_SF_CACHE\n        a->cacheSizePerElement = e->getCacheSizes();\n#endif\n\n#ifndef N2P2_NO_NEIGH_CHECK\n        // Check if atom has low number of neighbors.\n        size_t numNeighbors = a->calculateNumNeighbors(\n                minCutoffRadius.at(e->getIndex()));\n        if (numNeighbors < minNeighbors.at(e->getIndex()))\n        {\n            log << strpr(\"WARNING: Structure %6zu Atom %6zu : %zu \"\n                         \"neighbors.\\n\",\n                         a->indexStructure,\n                         a->index,\n                         numNeighbors);\n        }\n#endif\n\n        // Allocate symmetry function data vectors in atom.\n        a->allocate(derivatives, maxCutoffRadius);\n\n        // Calculate symmetry functions (and derivatives).\n        e->calculateSymmetryFunctionGroups(*a, derivatives);\n\n        // Remember that symmetry functions of this atom have been calculated.\n        a->hasSymmetryFunctions = true;\n        if (derivatives) a->hasSymmetryFunctionDerivatives = true;\n    }\n\n    // If requested, check extrapolation warnings or update statistics.\n    // Needed to shift this out of the loop above to make it thread-safe.\n    if (checkExtrapolationWarnings)\n    {\n        for (size_t i = 0; i < structure.atoms.size(); ++i)\n        {\n            a = &(structure.atoms.at(i));\n            e = &(elements.at(a->element));\n            e->updateSymmetryFunctionStatistics(*a);\n        }\n    }\n\n    // Remember that symmetry functions of this structure have been calculated.\n    structure.hasSymmetryFunctions = true;\n    if (derivatives) structure.hasSymmetryFunctionDerivatives = true;\n\n    return;\n}\n\nvoid Mode::calculateAtomicNeuralNetworks(Structure& structure,\n                                         bool const derivatives,\n                                         string id)\n{\n    if (id == \"\") id = nnk.front();\n\n    if (nnpType == NNPType::HDNNP_2G)\n    {\n        for (vector<Atom>::iterator it = structure.atoms.begin();\n             it != structure.atoms.end(); ++it)\n        {\n            NeuralNetwork& nn = elements.at(it->element)\n                                .neuralNetworks.at(id);\n            nn.setInput(&((it->G).front()));\n            nn.propagate();\n            if (derivatives)\n            {\n                nn.calculateDEdG(&((it->dEdG).front()));\n            }\n            nn.getOutput(&(it->energy));\n        }\n    }\n    else if (nnpType == NNPType::HDNNP_4G)\n    {\n        if (id == \"elec\")\n        {\n            for (auto& a : structure.atoms)\n            {\n                NeuralNetwork& nn = elements.at(a.element)\n                                    .neuralNetworks.at(id);\n                nn.setInput(&((a.G).front()));\n                nn.propagate();\n                if (derivatives)\n                {\n                    // Calculation of dEdG is identical to dChidG\n                    nn.calculateDEdG(&((a.dChidG).front()));\n                    if (normalize)\n                    {\n                        for (auto& dChidGi : a.dChidG)\n                            dChidGi = normalized(\"negativity\", dChidGi);\n                    }\n                }\n                nn.getOutput(&(a.chi));\n                //log << strpr(\"Atom %5zu (%2s) chi: %24.16E\\n\",\n                //             a.index, elementMap[a.element].c_str(), a.chi);\n                if (normalize) a.chi = normalized(\"negativity\", a.chi);\n            }\n        }\n        else if (id == \"short\")\n        {\n            for (auto& a : structure.atoms)\n            {\n                NeuralNetwork& nn = elements.at(a.element)\n                                    .neuralNetworks.at(id);\n                // TODO: This part should simplify with improved NN class.\n                for (size_t i = 0; i < a.G.size(); ++i)\n                {\n                    nn.setInput(i, a.G.at(i));\n                }\n                // Set additional charge neuron.\n                nn.setInput(a.G.size(), a.charge);\n                nn.propagate();\n                if (derivatives)\n                {\n                    // last element of vector dEdG is dEdQ\n                    nn.calculateDEdG(&((a.dEdG).front()));\n                }\n                nn.getOutput(&(a.energy));\n                //log << strpr(\"Atom %5zu (%2s) energy: %24.16E\\n\",\n                //             a.index, elementMap[a.element].c_str(), a.energy);\n            }\n        }\n    }\n    else if (nnpType == NNPType::HDNNP_Q)\n    {\n        // Ignore ID, both NNs are computed here.\n        for (vector<Atom>::iterator it = structure.atoms.begin();\n             it != structure.atoms.end(); ++it)\n        {\n            // First the charge NN.\n            NeuralNetwork& nnCharge = elements.at(it->element)\n                                      .neuralNetworks.at(\"elec\");\n            nnCharge.setInput(&((it->G).front()));\n            nnCharge.propagate();\n            if (derivatives)\n            {\n                nnCharge.calculateDEdG(&((it->dQdG).front()));\n            }\n            nnCharge.getOutput(&(it->charge));\n\n            // Now the short-range NN (have to set input neurons individually).\n            NeuralNetwork& nnShort = elements.at(it->element)\n                                     .neuralNetworks.at(\"short\");\n            // TODO: This part should simplify with improved NN class.\n            for (size_t i = 0; i < it->G.size(); ++i)\n            {\n                nnShort.setInput(i, it->G.at(i));\n            }\n            // Set additional charge neuron.\n            nnShort.setInput(it->G.size(), it->charge);\n            nnShort.propagate();\n            if (derivatives)\n            {\n                nnShort.calculateDEdG(&((it->dEdG).front()));\n            }\n            nnShort.getOutput(&(it->energy));\n        }\n    }\n\n    return;\n}\n\n// TODO: Make this const?\nvoid Mode::chargeEquilibration( Structure& structure,\n                                bool const derivativesElec)\n{\n    Structure& s = structure;\n\n    // Prepare hardness vector and precalculate gamma(i, j).\n    VectorXd hardness(numElements);\n    MatrixXd gammaSqrt2(numElements, numElements);\n    VectorXd sigmaSqrtPi(numElements);\n    // In case of natural units and no normalization\n    double fourPiEps = 1;\n    // In case of natural units but with normalization. Other units currently\n    // not supported.\n    if (normalize) fourPiEps = pow(convCharge, 2) / (convLength * convEnergy);\n\n    fourPiEps = 1;\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        hardness(i) = elements.at(i).getHardness();\n        double const iSigma = elements.at(i).getQsigma();\n        sigmaSqrtPi(i) = sqrt(M_PI) * iSigma;\n        for (size_t j = 0; j < numElements; ++j)\n        {\n            double const jSigma = elements.at(j).getQsigma();\n            gammaSqrt2(i, j) = sqrt(2.0 * (iSigma * iSigma + jSigma * jSigma));\n        }\n    }\n\n    s.calculateElectrostaticEnergy(ewaldSetup,\n                                   hardness,\n                                   gammaSqrt2,\n                                   sigmaSqrtPi,\n                                   screeningFunction,\n                                   fourPiEps,\n                                   erfcBuf);\n\n    // TODO: leave these 2 functions here or move it to e.g. forces? Needs to be\n    // executed after calculateElectrostaticEnergy.\n    if (derivativesElec)\n    {\n        s.calculateDAdrQ(ewaldSetup, gammaSqrt2, fourPiEps, erfcBuf);\n        s.calculateElectrostaticEnergyDerivatives(hardness,\n                                                  gammaSqrt2,\n                                                  sigmaSqrtPi,\n                                                  screeningFunction,\n                                                  fourPiEps);\n    }\n\n    return;\n}\n\nvoid Mode::calculateEnergy(Structure& structure) const\n{\n    // Loop over all atoms and add atomic contributions to total energy.\n    structure.energy = 0.0;\n    structure.energyShort = 0.0;\n    for (vector<Atom>::iterator it = structure.atoms.begin();\n         it != structure.atoms.end(); ++it)\n    {\n        structure.energyShort += it->energy;\n    }\n    structure.energy = structure.energyShort + structure.energyElec;\n\n    //cout << strpr(\"Electrostatic energy: %24.16E\\n\", structure.energyElec);\n    //cout << strpr(\"Short-range   energy: %24.16E\\n\", structure.energyShort);\n    //cout << strpr(\"Sum           energy: %24.16E\\n\", structure.energy);\n    //cout << strpr(\"Offset        energy: %24.16E\\n\", getEnergyOffset(structure));\n    //cout << \"---------------------\\n\";\n    //cout << strpr(\"Total         energy: %24.16E\\n\", structure.energy + getEnergyOffset(structure));\n    //cout << strpr(\"Reference     energy: %24.16E\\n\", structure.energyRef + getEnergyOffset(structure));\n    //cout << \"---------------------\\n\";\n    //cout << \"without offset:      \\n\";\n    //cout << strpr(\"Total         energy: %24.16E\\n\", structure.energy);\n    //cout << strpr(\"Reference     energy: %24.16E\\n\", structure.energyRef);\n\n    return;\n}\n\nvoid Mode::calculateCharge(Structure& structure) const\n{\n    // Loop over all atoms and add atomic charge contributions to total charge.\n    structure.charge = 0.0;\n    for (vector<Atom>::iterator it = structure.atoms.begin();\n         it != structure.atoms.end(); ++it)\n    {\n        //log << strpr(\"Atom %5zu (%2s) q: %24.16E\\n\",\n        //             it->index, elementMap[it->element].c_str(), it->charge);\n        structure.charge += it->charge;\n    }\n\n    //log << \"---------------------\\n\";\n    //log << strpr(\"Total         charge: %24.16E\\n\", structure.charge);\n    //log << strpr(\"Reference     charge: %24.16E\\n\", structure.chargeRef);\n\n    return;\n}\n\nvoid Mode::calculateForces(Structure& structure) const\n{\n    if (nnpType == NNPType::HDNNP_Q)\n    {\n        throw runtime_error(\"WARNING: Forces are not implemented yet.\\n\");\n        return;\n    }\n\n    // Loop over all atoms, center atom i (ai).\n#ifdef _OPENMP\n    #pragma omp parallel\n    {\n    #pragma omp for\n#endif\n    for (size_t i = 0; i < structure.atoms.size(); ++i) {\n        // Set pointer to atom.\n        Atom &ai = structure.atoms.at(i);\n\n        // Reset forces.\n        ai.f = Vec3D{};\n\n        // First add force contributions from atom i itself (gradient of\n        // atomic energy E_i).\n        ai.f += ai.calculateSelfForceShort();\n\n        // Now loop over all neighbor atoms j of atom i. These may hold\n        // non-zero derivatives of their symmetry functions with respect to\n        // atom i's coordinates. Some atoms may appear multiple times in the\n        // neighbor list because of periodic boundary conditions. To avoid\n        // that the same contributions are added multiple times use the\n        // \"unique neighbor\" list. This list contains also the central atom\n        // index as first entry and hence also adds contributions of periodic\n        // images of the central atom (happens when cutoff radii larger than\n        // cell vector lengths are used, but this is already considered in the\n        // self-interaction).\n        for (vector<size_t>::const_iterator it = ai.neighborsUnique.begin() + 1;\n             it != ai.neighborsUnique.end(); ++it)\n        {\n            // Define shortcut for atom j (aj).\n            Atom &aj = structure.atoms.at(*it);\n#ifndef N2P2_FULL_SFD_MEMORY\n            vector<vector<size_t>> const& tableFull\n                = elements.at(aj.element).getSymmetryFunctionTable();\n#endif\n            // Loop over atom j's neighbors (n), atom i should be one of them.\n            // TODO: Could implement maxCutoffRadiusSymFunc for each element and\n            //       use this instead of maxCutoffRadius.\n            size_t const numNeighbors =\n                aj.getStoredMinNumNeighbors(maxCutoffRadius);\n            for (size_t k = 0; k < numNeighbors; ++k) {\n                Atom::Neighbor const &n = aj.neighbors[k];\n                // If atom j's neighbor is atom i add force contributions.\n                if (n.index == ai.index)\n                {\n#ifndef N2P2_FULL_SFD_MEMORY\n                    ai.f += aj.calculatePairForceShort(n, &tableFull);\n#else\n                    ai.f += aj.calculatePairForceShort(n);\n#endif\n                }\n            }\n        }\n    }\n\n    if (nnpType == NNPType::HDNNP_4G)\n    {\n        Structure &s = structure;\n\n        VectorXd lambdaTotal = s.calculateForceLambdaTotal();\n        VectorXd lambdaElec = s.calculateForceLambdaElec();\n\n#ifdef _OPENMP\n        #pragma omp for\n#endif\n        // OpenMP 4.0 doesn't support range based loops\n        for (size_t i = 0; i < s.numAtoms; ++i)\n        {\n            auto &ai = s.atoms[i];\n            ai.f -= ai.pEelecpr;\n            ai.fElec = -ai.pEelecpr;\n\n            for (size_t j = 0; j < s.numAtoms; ++j)\n            {\n                Atom const &aj = s.atoms.at(j);\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                vector<vector<size_t> > const &tableFull\n                        = elements.at(aj.element).getSymmetryFunctionTable();\n                Vec3D dChidr = aj.calculateDChidr(ai.index,\n                                                  maxCutoffRadius,\n                                                  &tableFull);\n#else\n                Vec3D dChidr = aj.calculateDChidr(ai.index,\n                                                  maxCutoffRadius);\n#endif\n                ai.f -= lambdaTotal(j) * (ai.dAdrQ[j] + dChidr);\n                ai.fElec -= lambdaElec(j) * (ai.dAdrQ[j] + dChidr);\n            }\n        }\n    }\n#ifdef _OPENMP\n    }\n#endif\n    return;\n}\n\n\nvoid Mode::evaluateNNP(Structure& structure, bool useForces, bool useDEdG)\n{\n    useDEdG = (useForces || useDEdG);\n    if (nnpType == NNPType::HDNNP_4G)\n    {\n        structure.calculateMaxCutoffRadiusOverall(\n            ewaldSetup,\n            screeningFunction.getOuter(),\n            maxCutoffRadius);\n        structure.calculateNeighborList(maxCutoffRadius, cutoffs);\n    }\n    // TODO: For the moment sort neighbors only for 4G-HDNNPs (breaks some\n    //       CI tests because of small numeric changes).\n    else structure.calculateNeighborList(maxCutoffRadius, false);\n\n#ifdef N2P2_NO_SF_GROUPS\n    calculateSymmetryFunctions(structure, true);\n#else\n    calculateSymmetryFunctionGroups(structure, useForces);\n#endif\n\n    // Needed if useForces == false but sensitivity data is requested.\n    if (useDEdG && !useForces)\n    {\n        // Manually allocate dEdG vectors.\n        for (auto& a : structure.atoms)\n        {\n            if (nnpType == NNPType::HDNNP_4G)\n            {\n                a.dEdG.resize(a.numSymmetryFunctions + 1, 0.0);\n                a.dChidG.resize(a.numSymmetryFunctions, 0.0);\n            }\n            else\n                a.dEdG.resize(a.numSymmetryFunctions, 0.0);\n        }\n    }\n\n    calculateAtomicNeuralNetworks(structure, useDEdG);\n    if (nnpType == NNPType::HDNNP_4G)\n    {\n        chargeEquilibration(structure, useForces);\n        calculateAtomicNeuralNetworks(structure, useDEdG, \"short\");\n    }\n    calculateEnergy(structure);\n    if (nnpType == NNPType::HDNNP_4G ||\n        nnpType == NNPType::HDNNP_Q)\n        calculateCharge(structure);\n    if (useForces) calculateForces(structure);\n}\n\nvoid Mode::addEnergyOffset(Structure& structure, bool ref)\n{\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        if (ref)\n        {\n            structure.energyRef += structure.numAtomsPerElement.at(i)\n                                   * elements.at(i).getAtomicEnergyOffset();\n        }\n        else\n        {\n            structure.energy += structure.numAtomsPerElement.at(i)\n                              * elements.at(i).getAtomicEnergyOffset();\n        }\n    }\n\n    return;\n}\n\nvoid Mode::removeEnergyOffset(Structure& structure, bool ref)\n{\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        if (ref)\n        {\n            structure.energyRef -= structure.numAtomsPerElement.at(i)\n                                 * elements.at(i).getAtomicEnergyOffset();\n        }\n        else\n        {\n            structure.energy -= structure.numAtomsPerElement.at(i)\n                              * elements.at(i).getAtomicEnergyOffset();\n        }\n    }\n\n    return;\n}\n\ndouble Mode::getEnergyOffset(Structure const& structure) const\n{\n    double result = 0.0;\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        result += structure.numAtomsPerElement.at(i)\n                * elements.at(i).getAtomicEnergyOffset();\n    }\n\n    return result;\n}\n\ndouble Mode::getEnergyWithOffset(Structure const& structure, bool ref) const\n{\n    double result;\n    if (ref) result = structure.energyRef;\n    else     result = structure.energy;\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        result += structure.numAtomsPerElement.at(i)\n                * elements.at(i).getAtomicEnergyOffset();\n    }\n\n    return result;\n}\n\ndouble Mode::normalized(string const& property, double value) const\n{\n    if      (property == \"energy\") return value * convEnergy;\n    else if (property == \"force\") return value * convEnergy / convLength;\n    else if (property == \"charge\") return value * convCharge;\n    else if (property == \"hardness\")\n        return value * convEnergy / pow(convCharge, 2);\n    else if (property == \"negativity\") return value * convEnergy / convCharge;\n    else throw runtime_error(\"ERROR: Unknown property to convert to \"\n                             \"normalized units.\\n\");\n}\n\ndouble Mode::normalizedEnergy(Structure const& structure, bool ref) const\n{\n    if (ref)\n    {\n        return (structure.energyRef - structure.numAtoms * meanEnergy)\n               * convEnergy;\n    }\n    else\n    {\n        return (structure.energy - structure.numAtoms * meanEnergy)\n               * convEnergy;\n    }\n}\n\ndouble Mode::physical(string const& property, double value) const\n{\n    if      (property == \"energy\") return value / convEnergy;\n    else if (property == \"force\") return value * convLength / convEnergy;\n    else if (property == \"charge\") return value / convCharge;\n    else if (property == \"hardness\")\n        return value / (convEnergy / pow(convCharge, 2));\n    else if (property == \"negativity\") return value * convCharge / convEnergy;\n    else throw runtime_error(\"ERROR: Unknown property to convert to physical \"\n                             \"units.\\n\");\n}\n\ndouble Mode::physicalEnergy(Structure const& structure, bool ref) const\n{\n    if (ref)\n    {\n        return structure.energyRef / convEnergy + structure.numAtoms\n               * meanEnergy;\n    }\n    else\n    {\n        return structure.energy / convEnergy + structure.numAtoms * meanEnergy;\n    }\n}\n\nvoid Mode::convertToNormalizedUnits(Structure& structure) const\n{\n    structure.toNormalizedUnits(meanEnergy, convEnergy, convLength, convCharge);\n\n    return;\n}\n\nvoid Mode::convertToPhysicalUnits(Structure& structure) const\n{\n    structure.toPhysicalUnits(meanEnergy, convEnergy, convLength, convCharge);\n\n    return;\n}\n\nvoid Mode::logEwaldCutoffs()\n{\n    if (nnpType != NNPType::HDNNP_4G) return;\n    ewaldSetup.logEwaldCutoffs(log, convLength);\n}\n\nvoid Mode::resetExtrapolationWarnings()\n{\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        it->statistics.resetExtrapolationWarnings();\n    }\n\n    return;\n}\n\nsize_t Mode::getNumExtrapolationWarnings() const\n{\n    size_t numExtrapolationWarnings = 0;\n\n    for (vector<Element>::const_iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        numExtrapolationWarnings +=\n            it->statistics.countExtrapolationWarnings();\n    }\n\n    return numExtrapolationWarnings;\n}\n\nvector<size_t> Mode::getNumSymmetryFunctions() const\n{\n    vector<size_t> v;\n\n    for (vector<Element>::const_iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        v.push_back(it->numSymmetryFunctions());\n    }\n\n    return v;\n}\n\nbool Mode::settingsKeywordExists(std::string const& keyword) const\n{\n    return settings.keywordExists(keyword);\n}\n\nstring Mode::settingsGetValue(std::string const& keyword) const\n{\n    return settings.getValue(keyword);\n}\n\n\nvoid Mode::writePrunedSettingsFile(vector<size_t> prune, string fileName) const\n{\n    ofstream file(fileName.c_str());\n    vector<string> settingsLines = settings.getSettingsLines();\n    for (size_t i = 0; i < settingsLines.size(); ++i)\n    {\n        if (find(prune.begin(), prune.end(), i) != prune.end())\n        {\n            file << \"# \";\n        }\n        file << settingsLines.at(i) << '\\n';\n    }\n    file.close();\n\n    return;\n}\n\nvoid Mode::writeSettingsFile(ofstream* const& file) const\n{\n    settings.writeSettingsFile(file);\n\n    return;\n}\n\nvector<size_t> Mode::pruneSymmetryFunctionsRange(double threshold)\n{\n    vector<size_t> prune;\n\n    // Check if symmetry functions have low range.\n    for (vector<Element>::const_iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        for (size_t i = 0; i < it->numSymmetryFunctions(); ++i)\n        {\n            SymFnc const& s = it->getSymmetryFunction(i);\n            if (fabs(s.getGmax() - s.getGmin()) < threshold)\n            {\n                prune.push_back(it->getSymmetryFunction(i).getLineNumber());\n            }\n        }\n    }\n\n    return prune;\n}\n\nvector<size_t> Mode::pruneSymmetryFunctionsSensitivity(\n                                           double                  threshold,\n                                           vector<vector<double> > sensitivity)\n{\n    vector<size_t> prune;\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        for (size_t j = 0; j < elements.at(i).numSymmetryFunctions(); ++j)\n        {\n            if (sensitivity.at(i).at(j) < threshold)\n            {\n                prune.push_back(\n                        elements.at(i).getSymmetryFunction(j).getLineNumber());\n            }\n        }\n    }\n\n    return prune;\n}\n\nvoid Mode::readNeuralNetworkWeights(string const& id,\n                                    string const& fileNameFormat)\n{\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        string fileName = strpr(fileNameFormat.c_str(),\n                                it->getAtomicNumber());\n        log << strpr(\"Setting weights for element %2s from file: %s\\n\",\n                     it->getSymbol().c_str(),\n                     fileName.c_str());\n        vector<double> weights = readColumnsFromFile(fileName,\n                                                     vector<size_t>(1, 0)\n                                                    ).at(0);\n        NeuralNetwork& nn = it->neuralNetworks.at(id);\n        nn.setConnections(&(weights.front()));\n    }\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/Mode.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef MODE_H\n#define MODE_H\n\n#include \"CutoffFunction.h\"\n#include \"Element.h\"\n#include \"ElementMap.h\"\n#include \"ErfcBuf.h\"\n#include \"EwaldSetup.h\"\n#include \"Kspace.h\"\n#include \"Log.h\"\n#include \"ScreeningFunction.h\"\n#include \"Settings.h\"\n#include \"Structure.h\"\n#include \"SymFnc.h\"\n#include <cstddef> // std::size_t\n#include <map>     // std::map\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/** Base class for all NNP applications.\n *\n * This top-level class is the anchor point for existing and future\n * applications. It contains functions to set up an existing neural network\n * potential and calculate energies and forces for configurations given as\n * Structure. A minimal setup requires some consecutive functions calls as this\n * minimal example shows:\n *\n * ```\n * Mode mode;\n * mode.initialize();\n * mode.loadSettingsFile();\n * mode.setupElementMap();\n * mode.setupElements();\n * mode.setupCutoff();\n * mode.setupSymmetryFunctions();\n * mode.setupSymmetryFunctionGroups();\n * mode.setupSymmetryFunctionStatistics(false, false, true, false);\n * mode.setupNeuralNetwork();\n * ```\n * To load weights and scaling information from files add these lines:\n * ```\n * mode.setupSymmetryFunctionScaling();\n * mode.setupNeuralNetworkWeights();\n * ```\n * The NNP is now ready! If we load a structure from a data file:\n * ```\n * Structure structure;\n * ifstream file;\n * file.open(\"input.data\");\n * structure.setupElementMap(mode.elementMap);\n * structure.readFromFile(file);\n * file.close();\n * ```\n * we can finally predict the energy and forces from the neural network\n * potential:\n * ```\n * structure.calculateNeighborList(mode.getMaxCutoffRadius());\n * mode.calculateSymmetryFunctionGroups(structure, true);\n * mode.calculateAtomicNeuralNetworks(structure, true);\n * mode.calculateEnergy(structure);\n * mode.calculateForces(structure);\n * cout << structure.energy << '\\n';\n * ```\n * The resulting potential energy is stored in Structure::energy, the forces\n * on individual atoms are located within the Structure::atoms vector in\n * Atom::f.\n */\nclass Mode\n{\npublic:\n    enum class NNPType\n    {\n        /// Short range NNP (2G-HDNNP).\n        HDNNP_2G = 2,\n        /// NNP with electrostatics and non-local charge transfer (4G-HDNNP).\n        HDNNP_4G = 4,\n        /** Short range NNP with charge NN, no electrostatics/Qeq (M. Bircher).\n         *\n         * This is a simplified version of a 4G-HDNNP. Two neural networks are\n         * used: the first one predicts atomic charges, which will be used for\n         * the second NN as additional input neuron. There is no electrostatic\n         * energy and no global charge equilibration as in 4G-HDNNP.\n         */\n        HDNNP_Q = 10\n    };\n\n    Mode();\n    /** Write welcome message with version information.\n     */\n    void                     initialize();\n    /** Open settings file and load all keywords into memory.\n     *\n     * @param[in] fileName Settings file name.\n     */\n    void                     loadSettingsFile(std::string const& fileName\n                                                                 = \"input.nn\");\n    /** Combine multiple setup routines and provide a basic NNP setup.\n     *\n     * @param[in] nnpDir Optional directory where NNP files reside.\n     * @param[in] skipNormalize Whether to skip normalization setup.\n     * @param[in] initialHardness Signalizes to use initial hardness in NN\n     *                  settings.\n     *\n     * Sets up elements, symmetry functions, symmetry function groups, neural\n     * networks. No symmetry function scaling data is read, no weights are set.\n     */\n    void                     setupGeneric(std::string const& nnpDir = \"\",\n                                          bool               skipNormalize = false,\n                                          bool               initialHardness = false);\n    /** Set up normalization.\n     *\n     * @param[in] standalone Whether to write section header and footer.\n     *\n     * If the keywords `mean_energy`, `conv_length` and\n     * `conv_length` are present, the provided conversion factors are used to\n     * internally use a different unit system.\n     */\n    void                     setupNormalization(bool standalone = true);\n    /** Set up the element map.\n     *\n     * Uses keyword `elements`. This function should follow immediately after\n     * settings are loaded via loadSettingsFile().\n     */\n    virtual void             setupElementMap();\n    /** Set up all Element instances.\n     *\n     * Uses keywords `number_of_elements` and `atom_energy`. This function\n     * should follow immediately after setupElementMap().\n     */\n    virtual void             setupElements();\n    /** Set up cutoff function for all symmetry functions.\n     *\n     * Uses keyword `cutoff_type`. Cutoff parameters are read from settings\n     * keywords and stored internally. As soon as setupSymmetryFunctions() is\n     * called the settings are restored and used for all symmetry functions.\n     * Thus, this function must be called before setupSymmetryFunctions().\n     */\n    void                     setupCutoff();\n    /** Set up all symmetry functions.\n     *\n     * Uses keyword `symfunction_short`. Reads all symmetry functions from\n     * settings and automatically assigns them to the correct element.\n     */\n    virtual void             setupSymmetryFunctions();\n    /** Set up \"empy\" symmetry function scaling.\n     *\n     * Does not use any keywords. Sets no scaling for all symmetry functions.\n     * Call after setupSymmetryFunctions(). Alternatively set scaling via\n     * setupSymmetryFunctionScaling().\n     */\n    void                     setupSymmetryFunctionScalingNone();\n    /** Set up symmetry function scaling from file.\n     *\n     * @param[in] fileName Scaling file name.\n     *\n     * Uses keywords `scale_symmetry_functions`, `center_symmetry_functions`,\n     * `scale_symmetry_functions_sigma`, `scale_min_short` and\n     * `scale_max_short`. Reads in scaling information and sets correct scaling\n     * behavior for all symmetry functions. Call after\n     * setupSymmetryFunctions().\n     */\n    virtual void             setupSymmetryFunctionScaling(\n                                 std::string const& fileName = \"scaling.data\");\n    /** Set up symmetry function groups.\n     *\n     * Does not use any keywords. Call after setupSymmetryFunctions() and\n     * ensure that correct scaling behavior has already been set.\n     */\n    virtual void             setupSymmetryFunctionGroups();\n#ifndef N2P2_NO_SF_CACHE\n    /** Set up symmetry function cache.\n     *\n     * @param[in] verbose If true, print more cache information.\n     *\n     * Searches symmetry functions for identical cutoff functions or compact\n     * function (i.e. all cachable stuff) and sets up a caching index.\n     */\n    virtual void             setupSymmetryFunctionCache(bool verbose = false);\n#endif\n    /** Extract required memory dimensions for symmetry function derivatives.\n     *\n     * @param[in] verbose If true, print all symmetry function lines.\n     *\n     * Call after symmetry functions have been set up and sorted.\n     */\n    void                     setupSymmetryFunctionMemory(bool verbose = false);\n    /** Set up symmetry function statistics collection.\n     *\n     * @param[in] collectStatistics Whether statistics (min, max, mean, sigma)\n     *                              is collected.\n     * @param[in] collectExtrapolationWarnings Whether extrapolation warnings\n     *                                         are logged.\n     * @param[in] writeExtrapolationWarnings Write extrapolation warnings\n     *                                       immediately when they occur.\n     * @param[in] stopOnExtrapolationWarnings Throw error immediately when\n     *                                        an extrapolation warning occurs.\n     *\n     * Does not use any keywords. Calling this setup function is not required,\n     * by default no statistics collection is enabled (all arguments `false`).\n     * Call after setupElements().\n     */\n    void                     setupSymmetryFunctionStatistics(\n                                             bool collectStatistics,\n                                             bool collectExtrapolationWarnings,\n                                             bool writeExtrapolationWarnings,\n                                             bool stopOnExtrapolationWarnings);\n    /** Setup matrix storing all symmetry function cut-offs for each element.\n     */\n    void                     setupCutoffMatrix();\n    /** Set up neural networks for all elements.\n     *\n     * Uses keywords `global_hidden_layers_short`, `global_nodes_short`,\n     * `global_activation_short`, `normalize_nodes`. Call after\n     * setupSymmetryFunctions(), only then the number of input layer neurons is\n     * known.\n     */\n    virtual void             setupNeuralNetwork();\n    /** Set up neural network weights from files with given name format.\n     *\n     * @param[in] fileNameFormats Map of NN ids to format for weight file\n     *                            names. Must contain a placeholder \"%zu\" for\n     *                            the element atomic number. Map keys are\n     *                            \"short\", \"elec\". Map argument may be\n     *                            ommitted, then default name formats are used.\n     *\n     * Does not use any keywords. The weight files should contain one weight\n     * per line, see NeuralNetwork::setConnections() for the correct order.\n     */\n    virtual void             setupNeuralNetworkWeights(\n                                 std::map<std::string,\n                                          std::string> fileNameFormats =\n                                 std::map<std::string,\n                                          std::string>());\n    /** Set up neural network weights from files with given name format.\n     *\n     * @param[in] directoryPrefix Directory prefix which is applied to all\n     *                            fileNameFormats.\n     * @param[in] fileNameFormats Map of NN ids to format for weight file\n     *                            names. Must contain a placeholder \"%zu\" for\n     *                            the element atomic number. Map keys are\n     *                            \"short\", \"elec\". Map argument may be\n     *                            ommitted, then default name formats are used.\n     *\n     * Does not use any keywords. The weight files should contain one weight\n     * per line, see NeuralNetwork::setConnections() for the correct order.\n     */\n    virtual void             setupNeuralNetworkWeights(\n                                 std::string           directoryPrefix,\n                                 std::map<std::string,\n                                          std::string> fileNameFormats =\n                                 std::map<std::string,\n                                          std::string>());\n    /** Set up electrostatics related stuff (hardness, screening, ...).\n     *\n     * @param[in] initialHardness Use initial hardness from keyword in settings\n     *                            file (useful for training).\n     * @param[in] directoryPrefix Directory prefix which is applied to\n     *                            fileNameFormat.\n     * @param[in] fileNameFormat Name format of file containing atomic\n     *                           hardness data.\n     */\n    virtual void             setupElectrostatics(bool initialHardness =\n                                                 false,\n                                                 std::string directoryPrefix =\n                                                 \"\",\n                                                 std::string fileNameFormat =\n                                                 \"hardness.%03zu.data\");\n    /** Calculate all symmetry functions for all atoms in given structure.\n     *\n     * @param[in] structure Input structure.\n     * @param[in] derivatives If `true` calculate also derivatives of symmetry\n     *                        functions.\n     *\n     * This function should be replaced by calculateSymmetryFunctionGroups()\n     * whenever possible. Results are stored in Atom::G. If derivatives are\n     * calculated, additional results are stored in Atom::dGdr and\n     * Atom::Neighbor::dGdr.\n     */\n    void                     calculateSymmetryFunctions(\n                                                       Structure& structure,\n                                                       bool const derivatives);\n    /** Calculate all symmetry function groups for all atoms in given\n     * structure.\n     *\n     * @param[in] structure Input structure.\n     * @param[in] derivatives If `true` calculate also derivatives of symmetry\n     *                        functions.\n     *\n     * This function replaces calculateSymmetryFunctions() when symmetry\n     * function groups are enabled (faster, default behavior). Results are\n     * stored in Atom::G. If derivatives are calculated, additional results are\n     * stored in Atom::dGdr and Atom::Neighbor::dGdr.\n     */\n    void                     calculateSymmetryFunctionGroups(\n                                                       Structure& structure,\n                                                       bool const derivatives);\n    // /** Calculate a single atomic neural network for a given atom and nn type.\n    // *\n    // * @param[in] nnId Neural network identifier, e.g. \"short\", \"charge\".\n    // * @param[in] atom Input atom.\n    // * @param[in] derivatives If `true` calculate also derivatives of neural\n    // *                        networks with respect to input layer neurons\n    // *                        (required for force calculation).\n    // *\n    // * The atomic energy and charge is stored in Atom::energy and Atom::charge,\n    // * respectively. If derivatives are calculated the results are stored in\n    // * Atom::dEdG or Atom::dQdG.\n    // */\n    //void                     calculateAtomicNeuralNetwork(\n    //                                           std::string const& nnId,\n    //                                           Atom&              atom,\n    //                                           bool const         derivatives);\n    /** Calculate atomic neural networks for all atoms in given structure.\n     *\n     * @param[in] structure Input structure.\n     * @param[in] derivatives If `true` calculate also derivatives of neural\n     *                        networks with respect to input layer neurons\n     *                        (required for force calculation).\n     * @param[in] id Neural network ID to use. If empty, the first entry\n     *                        nnk.front() is used.\n     */\n    void                     calculateAtomicNeuralNetworks(\n                                           Structure&  structure,\n                                           bool const  derivatives,\n                                           std::string id = \"\");\n    /** Perform global charge equilibration method.\n     *\n     * @param[in] structure Input structure.\n     * @param[in] derivativesElec Turn on/off calculation of dElecdQ and\n     *                          pElecpr (Typically needed for elecstrosttic\n     *                          forces).\n     */\n    void                     chargeEquilibration(\n                                                Structure& structure,\n                                                bool const derivativesElec);\n    /** Calculate potential energy for a given structure.\n     *\n     * @param[in] structure Input structure.\n     *\n     * Sum up potential energy from atomic energy contributions. Result is\n     * stored in Structure::energy.\n     */\n    void                     calculateEnergy(Structure& structure) const;\n    /** Calculate total charge for a given structure.\n     *\n     * @param[in] structure Input structure.\n     *\n     * Sum up charge from atomic charge contributions. Result is\n     * stored in Structure::charge.\n     */\n    void                     calculateCharge(Structure& structure) const;\n    /** Calculate forces for all atoms in given structure.\n     *\n     * @param[in] structure Input structure.\n     *\n     * Combine intermediate results from symmetry function and neural network\n     * computation to atomic forces. Results are stored in Atom::f.\n     */\n    void                     calculateForces(Structure& structure) const;\n    /** Evaluate neural network potential (includes total energy, optionally\n     *  forces and in some cases charges.\n     *  @param[in] structure Input structure.\n     *  @param[in] useForces If true, calculate forces too.\n     *  @param[in] useDEdG If true, calculate dE/dG too.\n     */\n    void                     evaluateNNP(Structure& structure,\n                                         bool useForces = true,\n                                         bool useDEdG = true);\n    /** Add atomic energy offsets to reference energy.\n     *\n     * @param[in] structure Input structure.\n     * @param[in] ref If true, use reference energy, otherwise use NN energy.\n     */\n    void                     addEnergyOffset(Structure& structure,\n                                             bool       ref = true);\n    /** Remove atomic energy offsets from reference energy.\n     *\n     * @param[in] structure Input structure.\n     * @param[in] ref If true, use reference energy, otherwise use NN energy.\n     *\n     * This function should be called immediately after structures are read in.\n     */\n    void                     removeEnergyOffset(Structure& structure,\n                                                bool       ref = true);\n    /** Get atomic energy offset for given structure.\n     *\n     * @param[in] structure Input structure.\n     *\n     * @return Summed atomic energy offsets for structure.\n     */\n    double                   getEnergyOffset(Structure const& structure) const;\n    /** Add atomic energy offsets and return energy.\n     *\n     * @param[in] structure Input structure.\n     * @param[in] ref If true, use reference energy, otherwise use NN energy.\n     *\n     * @return Reference or NNP energy with energy offsets added.\n     *\n     * @note If normalization is used, ensure that structure energy is already\n     * in physical units.\n     */\n    double                   getEnergyWithOffset(\n                                            Structure const& structure,\n                                            bool             ref = true) const;\n    /** Apply normalization to given property.\n     *\n     * @param[in] property One of \"energy\", \"force\", \"charge\", \"hardness\"\n     *                     \"negativity\".\n     * @param[in] value Input property value in physical units.\n     *\n     * @return Property in normalized units.\n     */\n    double                   normalized(std::string const& property,\n                                        double             value) const;\n    /** Apply normalization to given energy of structure.\n     *\n     * @param[in] structure Input structure with energy in physical units.\n     * @param[in] ref If true, use reference energy, otherwise use NN energy.\n     *\n     * @return Energy in normalized units.\n     */\n    double                   normalizedEnergy(\n                                            Structure const& structure,\n                                            bool             ref = true) const;\n    /** Undo normalization for a given property.\n     *\n     * @param[in] property One of \"energy\", \"force\", \"charge\", \"hardness\",\n     *                     \"negativity\".\n     * @param[in] value Input property value in normalized units.\n     *\n     * @return Property in physical units.\n     */\n    double                   physical(std::string const& property,\n                                      double             value) const;\n    /** Undo normalization for a given energy of structure.\n     *\n     * @param[in] structure Input structure with energy in normalized units.\n     * @param[in] ref If true, use reference energy, otherwise use NN energy.\n     *\n     * @return Energy in physical units.\n     */\n    double                   physicalEnergy(Structure const& structure,\n                                            bool             ref = true) const;\n    /** Convert one structure to normalized units.\n     *\n     * @param[in,out] structure Input structure.\n     */\n    void                     convertToNormalizedUnits(\n                                                   Structure& structure) const;\n    /** Convert one structure to physical units.\n     *\n     * @param[in,out] structure Input structure.\n     */\n    void                     convertToPhysicalUnits(\n                                                   Structure& structure) const;\n    /** Logs Ewald params whenever they change.\n     *\n     */\n    void                     logEwaldCutoffs();\n    /** Count total number of extrapolation warnings encountered for all\n     * elements and symmetry functions.\n     *\n     * @return Number of extrapolation warnings.\n     */\n    std::size_t              getNumExtrapolationWarnings() const;\n    /** Erase all extrapolation warnings and reset counters.\n     */\n    void                     resetExtrapolationWarnings();\n    /** Getter for Mode::nnpType.\n     *\n     * @return HDNNP type (2G, 4G,..) that was set up.\n     */\n    NNPType                  getNnpType() const;\n    /** Getter for Mode::meanEnergy.\n     *\n     * @return Mean energy per atom.\n     */\n    double                   getMeanEnergy() const;\n    /** Getter for Mode::convEnergy.\n     *\n     * @return Energy unit conversion factor.\n     */\n    double                   getConvEnergy() const;\n    /** Getter for Mode::convLength.\n     *\n     * @return Length unit conversion factor.\n     */\n    double                   getConvLength() const;\n    /** Getter for Mode::convCharge.\n     *\n     * @return Charge unit conversion factor.\n     */\n    double                   getConvCharge() const;\n    /** Getter for Mode::ewaldSetup.precision.\n     *\n     * @return Ewald precision in 4G-HDNNPs.\n     *\n     */\n    double                   getEwaldPrecision() const;\n    /** Getter for Mode::ewaldSetup.maxCharge.\n     *\n     * @return Ewald max charge if specified in 4G-HDNNPs.\n     *\n     */\n    double                   getEwaldMaxCharge() const;\n    /** Getter for Mode::ewaldSetup.maxQsigma.\n     *\n     * @return Ewald max sigma parameter in 4G-HDNNPs.\n     *\n     */\n    double                   getEwaldMaxSigma() const;\n    /** Getter for Mode::ewaldSetup.truncMethod.\n     *\n     * @return Ewald truncation method in 4G-HDNNPs.\n     *\n     */\n    EWALDTruncMethod         getEwaldTruncationMethod() const;\n    /** Getter for Mode::kspaceSolver.\n     *\n     * @return K-space solver to be used in 4G-HDNNPs.\n     *\n     */\n    KSPACESolver             kspaceSolver() const;\n    /** Getter for Mode::maxCutoffRadius.\n     *\n     * @return Maximum cutoff radius of all symmetry functions.\n     *\n     * The maximum cutoff radius is determined by setupSymmetryFunctions().\n     */\n    double                   getMaxCutoffRadius() const;\n    /** Getter for Mode::numElements.\n     *\n     * @return Number of elements defined.\n     *\n     * The number of elements is determined by setupElements().\n     */\n    std::size_t              getNumElements() const;\n    /** Getter for Mode::screeningFunction.\n     *\n     * @return Copy of screening function instance.\n     */\n    ScreeningFunction        getScreeningFunction() const;\n    /** Get number of symmetry functions per element.\n     *\n     * @return Vector with number of symmetry functions for each element.\n     */\n    std::vector<std::size_t> getNumSymmetryFunctions() const;\n    /** Check if normalization is enabled.\n     *\n     * @return Value of #normalize.\n     */\n    bool                     useNormalization() const;\n    /** Check if keyword was found in settings file.\n     *\n     * @param[in] keyword Keyword for which value is requested.\n     *\n     * @return `true` if keyword exists, `false` otherwise.\n     */\n    bool                     settingsKeywordExists(\n                                             std::string const& keyword) const;\n    /** Get value for given keyword in Settings instance.\n     *\n     * @param[in] keyword Keyword for which value is requested.\n     *\n     * @return Value string corresponding to keyword.\n     */\n    std::string              settingsGetValue(\n                                             std::string const& keyword) const;\n    /** Prune symmetry functions according to their range and write settings\n     * file.\n     *\n     * @param[in] threshold Symmetry functions with range (max - min) smaller\n     *                      than this threshold will be pruned.\n     *\n     * @return List of line numbers with symmetry function to be removed.\n     */\n    std::vector<std::size_t> pruneSymmetryFunctionsRange(double threshold);\n    /** Prune symmetry functions with sensitivity analysis data.\n     *\n     * @param[in] threshold Symmetry functions with sensitivity lower than this\n     *                      threshold will be pruned.\n     * @param[in] sensitivity Sensitivity data for each element and symmetry\n     *                        function.\n     *\n     * @return List of line numbers with symmetry function to be removed.\n     */\n    std::vector<std::size_t> pruneSymmetryFunctionsSensitivity(\n                                            double threshold,\n                                            std::vector<\n                                            std::vector<double> > sensitivity);\n    /** Copy settings file but comment out lines provided.\n     *\n     * @param[in] prune List of line numbers to comment out.\n     * @param[in] fileName Output file name.\n     */\n    void                     writePrunedSettingsFile(\n                                              std::vector<std::size_t> prune,\n                                              std::string              fileName\n                                                          = \"output.nn\") const;\n    /** Write complete settings file.\n     *\n     * @param[in,out] file Settings file.\n     */\n    void                     writeSettingsFile(\n                                             std::ofstream* const& file) const;\n\n    /// Global element map, populated by setupElementMap().\n    ElementMap elementMap;\n    /// Global log file.\n    Log        log;\n\nprotected:\n    /// Setup data for one neural network.\n    struct NNSetup\n    {\n        struct Topology\n        {\n            /// Number of NN layers (including input and output layer).\n            int                                numLayers;\n            /// Number of neurons per layer.\n            std::vector<int>                   numNeuronsPerLayer;\n            /// Activation function type per layer.\n            std::vector<\n            NeuralNetwork::ActivationFunction> activationFunctionsPerLayer;\n\n            /// Constructor.\n            Topology() : numLayers(0) {};\n        };\n\n        /// NN identifier, e.g. \"short\", \"charge\",...\n        std::string           id;\n        /// Description string for log output, e.g. \"electronegativity\".\n        std::string           name;\n        /// Format for weight files.\n        std::string           weightFileFormat;\n        /// Suffix for keywords (NN topology related).\n        std::string           keywordSuffix;\n        /// Suffix for some other keywords (weight file loading related).\n        std::string           keywordSuffix2;\n        /// Per-element NN topology.\n        std::vector<Topology> topology;\n    };\n\n\n    NNPType                    nnpType;\n    bool                       normalize;\n    bool                       checkExtrapolationWarnings;\n    std::size_t                numElements;\n    std::vector<std::size_t>   minNeighbors;\n    std::vector<double>        minCutoffRadius;\n    double                     maxCutoffRadius;\n    double                     cutoffAlpha;\n    double                     meanEnergy;\n    double                     convEnergy;\n    double                     convLength;\n    double                     convCharge;\n    double                     fourPiEps;\n    EwaldSetup                 ewaldSetup;\n    KspaceGrid                 kspaceGrid;\n    settings::Settings         settings;\n    SymFnc::ScalingType        scalingType;\n    CutoffFunction::CutoffType cutoffType;\n    ScreeningFunction          screeningFunction;\n    std::vector<Element>       elements;\n    std::vector<std::string>   nnk;\n    std::map<\n    std::string, NNSetup>      nns;\n    /// Matrix storing all symmetry function cut-offs for all elements.\n    std::vector<\n    std::vector<double>>       cutoffs;\n    ErfcBuf                    erfcBuf;\n\n    /** Read in weights for a specific type of neural network.\n     *\n     * @param[in] id Actual network type to initialize (\"short\" or \"elec\").\n     * @param[in] fileNameFormat Weights file name format.\n     */\n    void readNeuralNetworkWeights(std::string const& id,\n                                  std::string const& fileName);\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline Mode::NNPType Mode::getNnpType() const\n{\n    return nnpType;\n}\n\ninline double Mode::getMeanEnergy() const\n{\n    return meanEnergy;\n}\n\ninline double Mode::getConvEnergy() const\n{\n    return convEnergy;\n}\n\ninline double Mode::getConvLength() const\n{\n    return convLength;\n}\n\ninline double Mode::getConvCharge() const\n{\n    return convCharge;\n}\n\ninline double Mode::getMaxCutoffRadius() const\n{\n    return maxCutoffRadius;\n}\n\ninline std::size_t Mode::getNumElements() const\n{\n    return numElements;\n}\n\ninline double Mode::getEwaldPrecision() const\n{\n    return ewaldSetup.getPrecision();\n}\n\ninline double Mode::getEwaldMaxCharge() const\n{\n    return ewaldSetup.getMaxCharge();\n}\n\ninline double Mode::getEwaldMaxSigma() const\n{\n    return ewaldSetup.getMaxQSigma();\n}\n\ninline EWALDTruncMethod Mode::getEwaldTruncationMethod() const\n{\n    return ewaldSetup.getTruncMethod();\n}\n\ninline KSPACESolver Mode::kspaceSolver() const\n{\n    return kspaceGrid.kspaceSolver;\n}\n\ninline bool Mode::useNormalization() const\n{\n    return normalize;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/NeuralNetwork.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"NeuralNetwork.h\"\n#include \"utility.h\"\n#include <algorithm> // std::min, std::max\n#include <cmath>     // sqrt, pow, tanh\n#include <cstdio>    // fprintf, stderr\n#include <cstdlib>   // exit, EXIT_FAILURE, rand, srand\n#include <limits>    // std::numeric_limits\n\n#define EXP_LIMIT 35.0\n\nusing namespace std;\nusing namespace nnp;\n\nNeuralNetwork::\nNeuralNetwork(int                              numLayers,\n              int const* const&                numNeuronsPerLayer,\n              ActivationFunction const* const& activationFunctionsPerLayer)\n{\n    // check number of layers\n    this->numLayers = numLayers;\n    if (numLayers < 3)\n    {\n        fprintf(stderr,\n                \"ERROR: Neural network must have at least three layers\\n\");\n        exit(EXIT_FAILURE);\n    }\n    numHiddenLayers = numLayers - 2;\n\n    // do not normalize neurons by default\n    normalizeNeurons = false;\n\n    // allocate layers and populate with neurons\n    layers = new Layer[numLayers];\n    inputLayer = &layers[0];\n    outputLayer = &layers[numLayers-1];\n    allocateLayer(*inputLayer,\n                  0,\n                  numNeuronsPerLayer[0],\n                  activationFunctionsPerLayer[0]);\n    for (int i = 1; i < numLayers; i++)\n    {\n        allocateLayer(layers[i],\n                      numNeuronsPerLayer[i-1],\n                      numNeuronsPerLayer[i],\n                      activationFunctionsPerLayer[i]);\n    }\n\n    // count connections\n    numWeights     = 0;\n    numBiases      = 0;\n    numConnections = 0;\n    for (int i = 1; i < numLayers; i++)\n    {\n        numBiases  += layers[i].numNeurons;\n        numWeights += layers[i].numNeurons * layers[i].numNeuronsPrevLayer;\n    }\n    numConnections = numWeights + numBiases;\n\n    // calculate weight and bias offsets for each layer\n    weightOffset = new int[numLayers-1];\n    weightOffset[0] = 0;\n    for (int i = 1; i < numLayers-1; i++)\n    {\n        weightOffset[i] = weightOffset[i-1] +\n                          (layers[i-1].numNeurons + 1) * layers[i].numNeurons;\n    }\n    biasOffset = new int[numLayers-1];\n    for (int i = 0; i < numLayers-1; i++)\n    {\n        biasOffset[i] = weightOffset[i] +\n                        layers[i+1].numNeurons * layers[i].numNeurons;\n    }\n    biasOnlyOffset = new int[numLayers-1];\n    biasOnlyOffset[0] = 0;\n    for (int i = 1; i < numLayers-1; i++)\n    {\n        biasOnlyOffset[i] = biasOnlyOffset[i-1] + layers[i].numNeurons;\n    }\n}\n\nNeuralNetwork::~NeuralNetwork()\n{\n    for (int i = 0; i < numLayers; i++)\n    {\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            delete[] layers[i].neurons[j].weights;\n        }\n        delete[] layers[i].neurons;\n    }\n    delete[] layers;\n    delete[] weightOffset;\n    delete[] biasOffset;\n    delete[] biasOnlyOffset;\n}\n\nvoid NeuralNetwork::setNormalizeNeurons(bool normalizeNeurons)\n{\n    this->normalizeNeurons = normalizeNeurons;\n\n    return;\n}\n\nint NeuralNetwork::getNumNeurons() const\n{\n    int count = 0;\n\n    for (int i = 0; i < numLayers; i++)\n    {\n        count += layers[i].numNeurons;\n    }\n\n    return count;\n}\n\nint NeuralNetwork::getNumConnections() const\n{\n    return numConnections;\n}\n\nint NeuralNetwork::getNumWeights() const\n{\n    return numWeights;\n}\n\nint NeuralNetwork::getNumBiases() const\n{\n    return numBiases;\n}\n\nvoid NeuralNetwork::setConnections(double const* const& connections)\n{\n    int count = 0;\n\n    for (int i = 1; i < numLayers; i++)\n    {\n        for (int j = 0; j < layers[i].numNeuronsPrevLayer; j++)\n        {\n            for (int k = 0; k < layers[i].numNeurons; k++)\n            {\n                layers[i].neurons[k].weights[j] = connections[count];\n                count++;\n            }\n        }\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            layers[i].neurons[j].bias = connections[count];\n            count++;\n        }\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::getConnections(double* connections) const\n{\n    int count = 0;\n\n    for (int i = 1; i < numLayers; i++)\n    {\n        for (int j = 0; j < layers[i].numNeuronsPrevLayer; j++)\n        {\n            for (int k = 0; k < layers[i].numNeurons; k++)\n            {\n                connections[count] = layers[i].neurons[k].weights[j] ;\n                count++;\n            }\n        }\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            connections[count] = layers[i].neurons[j].bias;\n            count++;\n        }\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::initializeConnectionsRandomUniform(unsigned int seed)\n{\n    double* connections = new double[numConnections];\n\n    srand(seed);\n    for (int i = 0; i < numConnections; i++)\n    {\n        connections[i] = -1.0 + 2.0 * (double)rand() / RAND_MAX;\n    }\n\n    setConnections(connections);\n\n    delete[] connections;\n\n    return;\n}\n\nvoid NeuralNetwork::modifyConnections(ModificationScheme modificationScheme)\n{\n    if (modificationScheme == MS_ZEROBIAS)\n    {\n        for (int i = 0; i < numLayers; i++)\n        {\n            for (int j = 0; j < layers[i].numNeurons; j++)\n            {\n                layers[i].neurons[j].bias = 0.0;\n            }\n        }\n    }\n    else if (modificationScheme == MS_ZEROOUTPUTWEIGHTS)\n    {\n        for (int i = 0; i < outputLayer->numNeurons; i++)\n        {\n            for (int j = 0; j < outputLayer->numNeuronsPrevLayer; j++)\n            {\n                outputLayer->neurons[i].weights[j] = 0.0;\n            }\n        }\n    }\n    else if (modificationScheme == MS_FANIN)\n    {\n        for (int i = 1; i < numLayers; i++)\n        {\n            if(layers[i].activationFunction == AF_TANH)\n            {\n                for (int j = 0; j < layers[i].numNeurons; j++)\n                {\n                    for (int k = 0; k < layers[i].numNeuronsPrevLayer; k++)\n                    {\n                        layers[i].neurons[j].weights[k] /=\n                                           sqrt(layers[i].numNeuronsPrevLayer);\n                    }\n                }\n            }\n        }\n    }\n    else if (modificationScheme == MS_GLOROTBENGIO)\n    {\n        for (int i = 1; i < numLayers; i++)\n        {\n            if(layers[i].activationFunction == AF_TANH)\n            {\n                for (int j = 0; j < layers[i].numNeurons; j++)\n                {\n                    for (int k = 0; k < layers[i].numNeuronsPrevLayer; k++)\n                    {\n                        layers[i].neurons[j].weights[k] *= sqrt(6.0 / (\n                                             layers[i].numNeuronsPrevLayer\n                                           + layers[i].numNeurons));\n                    }\n                }\n            }\n        }\n    }\n    else if (modificationScheme == MS_NGUYENWIDROW)\n    {\n        double beta   = 0.0;\n        double sum    = 0.0;\n        double weight = 0.0;\n\n        for (int i = 1; i < numLayers-1; i++)\n        {\n            beta = 0.7 * pow(layers[i].numNeurons,\n                             1.0 / double(layers[i].numNeuronsPrevLayer));\n            for (int j = 0; j < layers[i].numNeurons; j++)\n            {\n                sum = 0.0;\n                for (int k = 0; k < layers[i].numNeuronsPrevLayer; k++)\n                {\n                    weight = layers[i].neurons[j].weights[k];\n                    sum += weight * weight;\n                }\n                sum = sqrt(sum);\n                for (int k = 0; k < layers[i].numNeuronsPrevLayer; k++)\n                {\n                    layers[i].neurons[j].weights[k] *= beta / sum;\n                    if (layers[i].activationFunction == AF_TANH)\n                    {\n                        layers[i].neurons[j].weights[k] *= 2.0;\n                    }\n                }\n                layers[i].neurons[j].bias *= beta;\n                if (layers[i].activationFunction == AF_TANH)\n                {\n                    layers[i].neurons[j].bias *= 2.0;\n                }\n            }\n        }\n        for (int i = 0; i < outputLayer->numNeurons; i++)\n        {\n            outputLayer->neurons[0].weights[i] *= 0.5;\n        }\n    }\n    else\n    {\n        fprintf(stderr, \"ERROR: Incorrect modifyConnections call.\\n\");\n        exit(EXIT_FAILURE);\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::modifyConnections(ModificationScheme modificationScheme,\n                                      double parameter1,\n                                      double parameter2)\n{\n    if (modificationScheme == MS_PRECONDITIONOUTPUT)\n    {\n        double mean  = parameter1;\n        double sigma = parameter2;\n\n        for (int i = 0; i < outputLayer->numNeurons; i++)\n        {\n            for (int j = 0; j < outputLayer->numNeuronsPrevLayer; j++)\n            {\n                outputLayer->neurons[i].weights[j] *= sigma;\n            }\n            outputLayer->neurons[i].bias += mean;\n        }\n    }\n    else\n    {\n        fprintf(stderr, \"ERROR: Incorrect modifyConnections call.\\n\");\n        exit(EXIT_FAILURE);\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::setInput(size_t const index, double const value) const\n{\n    Neuron& n = inputLayer->neurons[index];\n    n.count++;\n    n.value = value;\n    n.min  = min(value, n.min);\n    n.max  = max(value, n.max);\n    n.sum  += value;\n    n.sum2 += value * value;\n\n    return;\n}\n\nvoid NeuralNetwork::setInput(double const* const& input) const\n{\n    for (int i = 0; i < inputLayer->numNeurons; i++)\n    {\n        // TODO: replace by calling setInput from above\n        // also, for 4G we need charges\n        double const& value = input[i];\n        Neuron& n = inputLayer->neurons[i];\n        n.count++;\n        n.value = value;\n        n.min  = min(value, n.min);\n        n.max  = max(value, n.max);\n        n.sum  += value;\n        n.sum2 += value * value;\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::getOutput(double* output) const\n{\n    for (int i = 0; i < outputLayer->numNeurons; i++)\n    {\n        output[i] = outputLayer->neurons[i].value;\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::propagate()\n{\n    for (int i = 1; i < numLayers; i++)\n    {\n        propagateLayer(layers[i], layers[i-1]);\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::calculateDEdG(double *dEdG) const\n{\n    double** inner = new double*[numHiddenLayers];\n    double** outer = new double*[numHiddenLayers];\n\n    for (int i = 0; i < numHiddenLayers; i++)\n    {\n        inner[i] = new double[layers[i+1].numNeurons];\n        outer[i] = new double[layers[i+2].numNeurons];\n    }\n\n    for (int k = 0; k < layers[0].numNeurons; k++)\n    {\n        for (int i = 0; i < layers[1].numNeurons; i++)\n        {\n            inner[0][i] = layers[1].neurons[i].weights[k]\n                        * layers[1].neurons[i].dfdx;\n            if (normalizeNeurons) inner[0][i] /= layers[0].numNeurons;\n        }\n        for (int l = 1; l < numHiddenLayers+1; l++)\n        {\n            for (int i2 = 0; i2 < layers[l+1].numNeurons; i2++)\n            {\n                outer[l-1][i2] = 0.0;\n                for (int i1 = 0; i1 < layers[l].numNeurons; i1++)\n                {\n                    outer[l-1][i2] += layers[l+1].neurons[i2].weights[i1]\n                                    * inner[l-1][i1];\n                }\n                outer[l-1][i2] *= layers[l+1].neurons[i2].dfdx;\n                if (normalizeNeurons) outer[l-1][i2] /= layers[l].numNeurons;\n                if (l < numHiddenLayers) inner[l][i2] = outer[l-1][i2];\n            }\n        }\n        dEdG[k] = outer[numHiddenLayers-1][0];\n    }\n\n    for (int i = 0; i < numHiddenLayers; i++)\n    {\n        delete[] inner[i];\n        delete[] outer[i];\n    }\n    delete[] inner;\n    delete[] outer;\n\n    return;\n}\n\nvoid NeuralNetwork::calculateDEdc(double* dEdc) const\n{\n    int count = 0;\n\n    for (int i = 0; i < numConnections; i++)\n    {\n        dEdc[i] = 0.0;\n    }\n\n    for (int i = 0; i < outputLayer->numNeurons; i++)\n    {\n        dEdc[biasOffset[numLayers-2]+i] = outputLayer->neurons[i].dfdx;\n        if (normalizeNeurons)\n        {\n            dEdc[biasOffset[numLayers-2]+i] /=\n                outputLayer->numNeuronsPrevLayer;\n        }\n    }\n\n    for (int i = numLayers-2; i >= 0; i--)\n    {\n        count = 0;\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            for (int k = 0; k < layers[i+1].numNeurons; k++)\n            {\n                dEdc[weightOffset[i]+count] = dEdc[biasOffset[i]+k]\n                                            * layers[i].neurons[j].value;\n                count++;\n                if (i >= 1)\n                {\n                    dEdc[biasOffset[i-1]+j] += dEdc[biasOffset[i]+k]\n                        * layers[i+1].neurons[k].weights[j]\n                        * layers[i].neurons[j].dfdx;\n                }\n            }\n            if (normalizeNeurons && i >= 1)\n            {\n                dEdc[biasOffset[i-1]+j] /= layers[i].numNeuronsPrevLayer;\n            }\n        }\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::calculateDFdc(double*              dFdc,\n                                  double const* const& dGdxyz) const\n{\n    double* dEdb    = new double[numBiases];\n    double* d2EdGdc = new double[numConnections];\n\n    for (int i = 0; i < numBiases; i++)\n    {\n        dEdb[i] = 0.0;\n    }\n    for (int i = 0; i < numConnections; i++)\n    {\n        dFdc[i]    = 0.0;\n        d2EdGdc[i] = 0.0;\n    }\n\n    calculateDEdb(dEdb);\n    for (int i = 0; i < layers[0].numNeurons; i++)\n    {\n        for (int j = 0; j < numConnections; j++)\n        {\n            d2EdGdc[j] = 0.0;\n        }\n        calculateDxdG(i);\n        calculateD2EdGdc(i, dEdb, d2EdGdc);\n        for (int j = 0; j < numConnections; j++)\n        {\n            // Note: F = - dE / dx !!\n            //           ^\n            dFdc[j] -= d2EdGdc[j] * dGdxyz[i];\n        }\n    }\n\n    delete[] dEdb;\n    delete[] d2EdGdc;\n\n    return;\n}\n\nvoid NeuralNetwork::writeConnections(std::ofstream& file) const\n{\n    // File header.\n    vector<string> title;\n    vector<string> colName;\n    vector<string> colInfo;\n    vector<size_t> colSize;\n    title.push_back(\"Neural network connection values (weights and biases).\");\n    colSize.push_back(24);\n    colName.push_back(\"connection\");\n    colInfo.push_back(\"Neural network connection value.\");\n    colSize.push_back(1);\n    colName.push_back(\"t\");\n    colInfo.push_back(\"Connection type (a = weight, b = bias).\");\n    colSize.push_back(9);\n    colName.push_back(\"index\");\n    colInfo.push_back(\"Index enumerating weights.\");\n    colSize.push_back(5);\n    colName.push_back(\"l_s\");\n    colInfo.push_back(\"Starting point layer (end point layer for biases).\");\n    colSize.push_back(5);\n    colName.push_back(\"n_s\");\n    colInfo.push_back(\"Starting point neuron in starting layer (end point \"\n                      \"neuron for biases).\");\n    colSize.push_back(5);\n    colName.push_back(\"l_e\");\n    colInfo.push_back(\"End point layer.\");\n    colSize.push_back(5);\n    colName.push_back(\"n_e\");\n    colInfo.push_back(\"End point neuron in end layer.\");\n    appendLinesToFile(file,\n                      createFileHeader(title, colSize, colName, colInfo));\n\n    int count = 0;\n    for (int i = 1; i < numLayers; i++)\n    {\n        for (int j = 0; j < layers[i].numNeuronsPrevLayer; j++)\n        {\n            for (int k = 0; k < layers[i].numNeurons; k++)\n            {\n                count++;\n                file << strpr(\"%24.16E a %9d %5d %5d %5d %5d\\n\",\n                              layers[i].neurons[k].weights[j],\n                              count,\n                              i - 1,\n                              j + 1,\n                              i,\n                              k + 1);\n            }\n        }\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            count++;\n            file << strpr(\"%24.16E b %9d %5d %5d\\n\",\n                          layers[i].neurons[j].bias,\n                          count,\n                          i,\n                          j + 1);\n        }\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::calculateDEdb(double* dEdb) const\n{\n    for (int i = 0; i < outputLayer->numNeurons; i++)\n    {\n        dEdb[biasOnlyOffset[numLayers-2]+i] = outputLayer->neurons[i].dfdx;\n        if (normalizeNeurons)\n        {\n            dEdb[biasOnlyOffset[numLayers-2]+i] /=\n                outputLayer->numNeuronsPrevLayer;\n        }\n    }\n\n    for (int i = numLayers-2; i >= 0; i--)\n    {\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            for (int k = 0; k < layers[i+1].numNeurons; k++)\n            {\n                if (i >= 1)\n                {\n                    dEdb[biasOnlyOffset[i-1]+j] += dEdb[biasOnlyOffset[i]+k]\n                        * layers[i+1].neurons[k].weights[j]\n                        * layers[i].neurons[j].dfdx;\n                }\n            }\n            if (normalizeNeurons && i >= 1)\n            {\n                dEdb[biasOnlyOffset[i-1]+j] /= layers[i].numNeuronsPrevLayer;\n            }\n        }\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::calculateDxdG(int index) const\n{\n    for (int i = 0; i < layers[1].numNeurons; i++)\n    {\n        layers[1].neurons[i].dxdG = layers[1].neurons[i].weights[index];\n        if (normalizeNeurons)\n        {\n            layers[1].neurons[i].dxdG /= layers[1].numNeuronsPrevLayer;\n        }\n    }\n    for (int i = 2; i < numLayers; i++)\n    {\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            layers[i].neurons[j].dxdG = 0.0;\n            for (int k = 0; k < layers[i-1].numNeurons; k++)\n            {\n                layers[i].neurons[j].dxdG += layers[i].neurons[j].weights[k]\n                                           * layers[i-1].neurons[k].dfdx\n                                           * layers[i-1].neurons[k].dxdG;\n            }\n            if (normalizeNeurons)\n            {\n                layers[i].neurons[j].dxdG /= layers[i].numNeuronsPrevLayer;\n            }\n        }\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::calculateD2EdGdc(int                  index,\n                                     double const* const& dEdb,\n                                     double*              d2EdGdc) const\n{\n    int count = 0;\n\n    for (int i = 0; i < outputLayer->numNeurons; i++)\n    {\n        d2EdGdc[biasOffset[numLayers-2]+i] = outputLayer->neurons[i].d2fdx2\n                                           * outputLayer->neurons[i].dxdG;\n        if (normalizeNeurons)\n        {\n            d2EdGdc[biasOffset[numLayers-2]+i] /=\n                outputLayer->numNeuronsPrevLayer;\n        }\n    }\n\n    for (int i = numLayers-2; i >= 0; i--)\n    {\n        count = 0;\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            for (int k = 0; k < layers[i+1].numNeurons; k++)\n            {\n                if (i == 0)\n                {\n                    d2EdGdc[weightOffset[i]+count] =\n                        d2EdGdc[biasOffset[i]+k] * layers[i].neurons[j].value;\n                    if (j == index)\n                    {\n                        d2EdGdc[weightOffset[i]+count] +=\n                            dEdb[biasOnlyOffset[i]+k];\n                    }\n                }\n                else\n                {\n                    d2EdGdc[weightOffset[i]+count] =\n                        d2EdGdc[biasOffset[i]+k] * layers[i].neurons[j].value\n                      + dEdb[biasOnlyOffset[i]+k] * layers[i].neurons[j].dfdx\n                      * layers[i].neurons[j].dxdG;\n                }\n                count++;\n                if (i >= 1)\n                {\n                    d2EdGdc[biasOffset[i-1]+j] +=\n                        layers[i+1].neurons[k].weights[j]\n                      * (d2EdGdc[biasOffset[i]+k] * layers[i].neurons[j].dfdx\n                      + dEdb[biasOnlyOffset[i]+k]\n                      * layers[i].neurons[j].d2fdx2\n                      * layers[i].neurons[j].dxdG);\n                }\n            }\n            if (normalizeNeurons && i >= 1)\n            {\n                d2EdGdc[biasOffset[i-1]+j] /= layers[i].numNeuronsPrevLayer;\n            }\n        }\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::allocateLayer(Layer&             layer,\n                                  int                numNeuronsPrevLayer,\n                                  int                numNeurons,\n                                  ActivationFunction activationFunction)\n{\n    layer.numNeurons          = numNeurons;\n    layer.numNeuronsPrevLayer = numNeuronsPrevLayer;\n    layer.activationFunction  = activationFunction;\n\n    layer.neurons = new Neuron[layer.numNeurons];\n    for (int i = 0; i < layer.numNeurons; i++)\n    {\n        layer.neurons[i].x      = 0.0;\n        layer.neurons[i].value  = 0.0;\n        layer.neurons[i].dfdx   = 0.0;\n        layer.neurons[i].d2fdx2 = 0.0;\n        layer.neurons[i].bias   = 0.0;\n        layer.neurons[i].dxdG   = 0.0;\n        layer.neurons[i].count  = 0;\n        layer.neurons[i].min    =  numeric_limits<double>::max();\n        layer.neurons[i].max    = -numeric_limits<double>::max();\n        layer.neurons[i].sum    = 0.0;\n        layer.neurons[i].sum2   = 0.0;\n        if (layer.numNeuronsPrevLayer > 0)\n        {\n            layer.neurons[i].weights = new double[layer.numNeuronsPrevLayer];\n            for (int j = 0; j < layer.numNeuronsPrevLayer; j++)\n            {\n                layer.neurons[i].weights[j] = 0.0;\n            }\n        }\n        else\n        {\n            layer.neurons[i].weights = 0;\n        }\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::propagateLayer(Layer& layer, Layer& layerPrev)\n{\n    double dtmp = 0.0;\n\n    for (int i = 0; i < layer.numNeurons; i++)\n    {\n        dtmp = 0.0;\n        for (int j = 0; j < layer.numNeuronsPrevLayer; j++)\n        {\n            dtmp += layer.neurons[i].weights[j] * layerPrev.neurons[j].value;\n        }\n        dtmp += layer.neurons[i].bias;\n        if (normalizeNeurons)\n        {\n            dtmp /= layer.numNeuronsPrevLayer;\n        }\n\n        layer.neurons[i].x = dtmp;\n        if (layer.activationFunction == AF_IDENTITY)\n        {\n            layer.neurons[i].value  = dtmp;\n            layer.neurons[i].dfdx   = 1.0;\n            layer.neurons[i].d2fdx2 = 0.0;\n        }\n        else if (layer.activationFunction == AF_TANH)\n        {\n            dtmp = tanh(dtmp);\n            layer.neurons[i].value  = dtmp;\n            layer.neurons[i].dfdx   = 1.0 - dtmp * dtmp;\n            layer.neurons[i].d2fdx2 = -2.0 * dtmp * (1.0 - dtmp * dtmp);\n        }\n        else if (layer.activationFunction == AF_LOGISTIC)\n        {\n            if (dtmp > EXP_LIMIT)\n            {\n                layer.neurons[i].value  = 1.0;\n                layer.neurons[i].dfdx   = 0.0;\n                layer.neurons[i].d2fdx2 = 0.0;\n            }\n            else if (dtmp < -EXP_LIMIT)\n            {\n                layer.neurons[i].value  = 0.0;\n                layer.neurons[i].dfdx   = 0.0;\n                layer.neurons[i].d2fdx2 = 0.0;\n            }\n            else\n            {\n                dtmp = 1.0 / (1.0 + exp(-dtmp));\n                layer.neurons[i].value  = dtmp;\n                layer.neurons[i].dfdx   = dtmp * (1.0 - dtmp);\n                layer.neurons[i].d2fdx2 = dtmp * (1.0 - dtmp)\n                                        * (1.0 - 2.0 * dtmp);\n            }\n        }\n        else if (layer.activationFunction == AF_SOFTPLUS)\n        {\n            if (dtmp > EXP_LIMIT)\n            {\n                layer.neurons[i].value  = dtmp;\n                layer.neurons[i].dfdx   = 1.0;\n                layer.neurons[i].d2fdx2 = 0.0;\n            }\n            else if (dtmp < -EXP_LIMIT)\n            {\n                layer.neurons[i].value  = 0.0;\n                layer.neurons[i].dfdx   = 0.0;\n                layer.neurons[i].d2fdx2 = 0.0;\n            }\n            else\n            {\n                dtmp = exp(dtmp);\n                layer.neurons[i].value  = log(1.0 + dtmp);\n                dtmp = 1.0 / (1.0 + 1.0 / dtmp);\n                layer.neurons[i].dfdx   = dtmp;\n                layer.neurons[i].d2fdx2 = dtmp * (1.0 - dtmp);\n            }\n        }\n        else if (layer.activationFunction == AF_RELU)\n        {\n            if (dtmp > 0.0)\n            {\n                layer.neurons[i].value  = dtmp;\n                layer.neurons[i].dfdx   = 1.0;\n                layer.neurons[i].d2fdx2 = 0.0;\n            }\n            else\n            {\n                layer.neurons[i].value  = 0.0;\n                layer.neurons[i].dfdx   = 0.0;\n                layer.neurons[i].d2fdx2 = 0.0;\n            }\n        }\n        else if (layer.activationFunction == AF_GAUSSIAN)\n        {\n            double const tmpexp = exp(-0.5 * dtmp * dtmp);\n            layer.neurons[i].value  = tmpexp;\n            layer.neurons[i].dfdx   = -dtmp * tmpexp;\n            layer.neurons[i].d2fdx2 = (dtmp * dtmp - 1.0) * tmpexp;\n        }\n        else if (layer.activationFunction == AF_COS)\n        {\n            double const tmpcos = cos(dtmp);\n            layer.neurons[i].value  = tmpcos;\n            layer.neurons[i].dfdx   = -sin(dtmp);\n            layer.neurons[i].d2fdx2 = -tmpcos;\n        }\n        else if (layer.activationFunction == AF_REVLOGISTIC)\n        {\n            dtmp = 1.0 / (1.0 + exp(-dtmp));\n            layer.neurons[i].value  = 1.0 - dtmp;\n            layer.neurons[i].dfdx   = dtmp * (dtmp - 1.0);\n            layer.neurons[i].d2fdx2 = dtmp * (dtmp - 1.0) * (1.0 - 2.0 * dtmp);\n        }\n        else if (layer.activationFunction == AF_EXP)\n        {\n            dtmp = exp(-dtmp);\n            layer.neurons[i].value  = dtmp;\n            layer.neurons[i].dfdx   = -dtmp;\n            layer.neurons[i].d2fdx2 = dtmp;\n        }\n        else if (layer.activationFunction == AF_HARMONIC)\n        {\n            layer.neurons[i].value  = dtmp * dtmp;\n            layer.neurons[i].dfdx   = 2.0 * dtmp;\n            layer.neurons[i].d2fdx2 = 2.0;\n        }\n        layer.neurons[i].count++;\n        dtmp = layer.neurons[i].x;\n        layer.neurons[i].min  = min(dtmp, layer.neurons[i].min);\n        layer.neurons[i].max  = max(dtmp, layer.neurons[i].max);\n        layer.neurons[i].sum  += dtmp;\n        layer.neurons[i].sum2 += dtmp * dtmp;\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::resetNeuronStatistics()\n{\n    for (int i = 0; i < numLayers; i++)\n    {\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            layers[i].neurons[j].count = 0;\n            layers[i].neurons[j].min   =  numeric_limits<double>::max();\n            layers[i].neurons[j].max   = -numeric_limits<double>::max();\n            layers[i].neurons[j].sum   = 0.0;\n            layers[i].neurons[j].sum2  = 0.0;\n        }\n    }\n\n    return;\n}\n\nvoid NeuralNetwork::getNeuronStatistics(long*   count,\n                                        double* min,\n                                        double* max,\n                                        double* sum,\n                                        double* sum2) const\n{\n    int iNeuron = 0;\n\n    for (int i = 0; i < numLayers; i++)\n    {\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            count[iNeuron] = layers[i].neurons[j].count;\n            min  [iNeuron] = layers[i].neurons[j].min;\n            max  [iNeuron] = layers[i].neurons[j].max;\n            sum  [iNeuron] = layers[i].neurons[j].sum;\n            sum2 [iNeuron] = layers[i].neurons[j].sum2;\n            iNeuron++;\n        }\n    }\n\n    return;\n}\n\n/*\nvoid NeuralNetwork::writeStatus(int element, int epoch)\n{\n    char  fName[LSTR] = \"\";\n    FILE* fpn         = NULL;\n    FILE* fpw         = NULL;\n\n    for (int i = 0; i < numLayers; i++)\n    {\n        sprintf(fName, \"nn.neurons.%03d.%1d.%06d\", element, i, epoch);\n        fpn = fopen(fName, \"a\");\n        if (fpn == NULL)\n        {\n            fprintf(stderr, \"ERROR: Could not open file: %s.\\n\", fName);\n            exit(EXIT_FAILURE);\n        }\n        sprintf(fName, \"nn.weights.%03d.%1d.%06d\", element, i, epoch);\n        fpw = fopen(fName, \"a\");\n        if (fpw == NULL)\n        {\n            fprintf(stderr, \"ERROR: Could not open file: %s.\\n\", fName);\n            exit(EXIT_FAILURE);\n        }\n        for (int j = 0; j < layers[i].numNeurons; j++)\n        {\n            fprintf(fpn, \"%4d %.8f %.8f %.8f %.8f %.8f %.8f\\n\", j, layers[i].neurons[j].x,\n                    layers[i].neurons[j].value, layers[i].neurons[j].dfdx, layers[i].neurons[j].d2fdx2,\n                    layers[i].neurons[j].bias, layers[i].neurons[j].dxdG);\n            for (int k = 0; k < layers[i].numNeuronsPrevLayer; k++)\n            {\n                fprintf(fpw, \"%4d %4d %.8f\\n\", j, k, layers[i].neurons[j].weights[k]);\n            }\n        }\n        fclose(fpn);\n        fclose(fpw);\n    }\n\n    return;\n\n}\n*/\n\nlong NeuralNetwork::getMemoryUsage()\n{\n    long mem        = sizeof(*this);\n    int  numNeurons = getNumNeurons();\n\n    mem += (numLayers - 1) * sizeof(int); // weightOffset\n    mem += (numLayers - 1) * sizeof(int); // biasOffset\n    mem += (numLayers - 1) * sizeof(int); // biasOnlyOffset\n    mem += numLayers  * sizeof(Layer);    // layers\n    mem += numNeurons * sizeof(Neuron);   // neurons\n    mem += numWeights * sizeof(double);   // weights\n\n    return mem;\n}\n\nvector<string> NeuralNetwork::info() const\n{\n    vector<string> v;\n    int maxNeurons = 0;\n\n    v.push_back(strpr(\"Number of weights    : %6zu\\n\", numWeights));\n    v.push_back(strpr(\"Number of biases     : %6zu\\n\", numBiases));\n    v.push_back(strpr(\"Number of connections: %6zu\\n\", numConnections));\n    v.push_back(strpr(\"Architecture    \"));\n    for (int i = 0; i < numLayers; ++i)\n    {\n        maxNeurons = max(layers[i].numNeurons, maxNeurons);\n        v.push_back(strpr(\" %4d\", layers[i].numNeurons));\n    }\n    v.push_back(\"\\n\");\n    v.push_back(\"-----------------------------------------\"\n                \"--------------------------------------\\n\");\n\n    for (int i = 0; i < maxNeurons; ++i)\n    {\n        v.push_back(strpr(\"%4d\", i + 1));\n        string s = \"\";\n        for (int j = 0; j < numLayers; ++j)\n        {\n            if (i < layers[j].numNeurons)\n            {\n                if (j == 0)\n                {\n                    s += strpr(\" %3s\", \"G\");\n                }\n                else if (layers[j].activationFunction == AF_IDENTITY)\n                {\n                    s += strpr(\" %3s\", \"l\");\n                }\n                else if (layers[j].activationFunction == AF_TANH)\n                {\n                    s += strpr(\" %3s\", \"t\");\n                }\n                else if (layers[j].activationFunction == AF_LOGISTIC)\n                {\n                    s += strpr(\" %3s\", \"s\");\n                }\n                else if (layers[j].activationFunction == AF_SOFTPLUS)\n                {\n                    s += strpr(\" %3s\", \"p\");\n                }\n                else if (layers[j].activationFunction == AF_RELU)\n                {\n                    s += strpr(\" %3s\", \"r\");\n                }\n                else if (layers[j].activationFunction == AF_GAUSSIAN)\n                {\n                    s += strpr(\" %3s\", \"g\");\n                }\n                else if (layers[j].activationFunction == AF_COS)\n                {\n                    s += strpr(\" %3s\", \"c\");\n                }\n                else if (layers[j].activationFunction == AF_REVLOGISTIC)\n                {\n                    s += strpr(\" %3s\", \"S\");\n                }\n                else if (layers[j].activationFunction == AF_EXP)\n                {\n                    s += strpr(\" %3s\", \"e\");\n                }\n                else if (layers[j].activationFunction == AF_HARMONIC)\n                {\n                    s += strpr(\" %3s\", \"h\");\n                }\n            }\n            else\n            {\n                s += \"    \";\n            }\n        }\n        v.push_back(s += \"\\n\");\n    }\n\n    return v;\n}\n\nNeuralNetwork::ActivationFunction nnp::activationFromString(string c)\n{\n    NeuralNetwork::ActivationFunction a;\n\n    if      (c == \"l\") a = NeuralNetwork::AF_IDENTITY;\n    else if (c == \"t\") a = NeuralNetwork::AF_TANH;\n    else if (c == \"s\") a = NeuralNetwork::AF_LOGISTIC;\n    else if (c == \"p\") a = NeuralNetwork::AF_SOFTPLUS;\n    else if (c == \"r\") a = NeuralNetwork::AF_RELU;\n    else if (c == \"g\") a = NeuralNetwork::AF_GAUSSIAN;\n    else if (c == \"c\") a = NeuralNetwork::AF_COS;\n    else if (c == \"S\") a = NeuralNetwork::AF_REVLOGISTIC;\n    else if (c == \"e\") a = NeuralNetwork::AF_EXP;\n    else if (c == \"h\") a = NeuralNetwork::AF_HARMONIC;\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown activation function.\\n\");\n    }\n\n    return a;\n}\n"
  },
  {
    "path": "src/libnnp/NeuralNetwork.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef NEURALNETWORK_H\n#define NEURALNETWORK_H\n\n#include <fstream>   // std::ofstream\n#include <string>    // std::string\n#include <vector>    // std::vector\n\nnamespace nnp\n{\n\n/// This class implements a feed-forward neural network.\nclass NeuralNetwork\n{\npublic:\n    /// List of available activation function types.\n    enum ActivationFunction\n    {\n        /// Unset activation function.\n        AF_UNSET,\n        /// @f$f_a(x) = x@f$\n        AF_IDENTITY,\n        /// @f$f_a(x) = \\tanh(x)@f$\n        AF_TANH,\n        /// @f$f_a(x) = 1 / (1 + \\mathrm{e}^{-x})@f$\n        AF_LOGISTIC,\n        /// @f$f_a(x) = \\ln (1 + \\mathrm{e}^x)@f$\n        AF_SOFTPLUS,\n        /// @f$f_a(x) = \\max(0, x)@f$ (NOT recommended for HDNNPs!)\n        AF_RELU,\n        /// @f$f_a(x) = \\mathrm{e}^{-x^2 / 2}@f$\n        AF_GAUSSIAN,\n        /// @f$f_a(x) = \\cos (x)@f$\n        AF_COS,\n        /// @f$f_a(x) = 1 - 1 / (1 + \\mathrm{e}^{-x})@f$\n        AF_REVLOGISTIC,\n        /// @f$f_a(x) = \\mathrm{e}^{-x}@f$\n        AF_EXP,\n        /// @f$f_a(x) = x^2@f$\n        AF_HARMONIC\n    };\n\n    /// List of available connection modification schemes.\n    enum ModificationScheme\n    {\n        /// Set all bias values to zero.\n        MS_ZEROBIAS,\n        /// Set all weights connecting to the output layer to zero.\n        MS_ZEROOUTPUTWEIGHTS,\n        /** Normalize weights via number of neuron inputs (fan-in).\n         *\n         * If initial weights are uniformly distributed in\n         * @f$\\left[-1, 1\\right]@f$ they will be scaled to be in\n         * @f$\\left[\\frac{-1}{\\sqrt{n_\\text{in}}},\n         * \\frac{1}{\\sqrt{n_\\text{in}}}\\right]@f$, where @f$n_\\text{in}@f$ is\n         * the number of incoming weights of a neuron (if activation\n         * function is of type #AF_TANH).\n         */\n        MS_FANIN,\n        /** Normalize connections according to Glorot and Bengio.\n         *\n         * If initial weights are uniformly distributed in\n         * @f$\\left[-1, 1\\right]@f$ they will be scaled to be in\n         * @f$\\left[-\\sqrt{\\frac{6}{n_\\text{in} + n_\\text{out}}},\n         * \\sqrt{\\frac{6}{n_\\text{in} + n_\\text{out}}}\\right]@f$, where\n         * @f$n_\\text{in}@f$ and @f$n_\\text{out}@f$ are the number of incoming\n         * and outgoing weights of a neuron, respectively (if activation\n         * function is of type #AF_TANH).\n         *\n         * For details see:\n         *  - X. Glorot and Y. Bengio, \"Understanding the difficulty of\n         *    training deep feedforward neural networks\", International\n         *    conference on artificial intelligence and statistics. 2010.\n         */\n        MS_GLOROTBENGIO,\n        /** Initialize connections according to Nguyen-Widrow scheme.\n         *\n         * For details see:\n         *  - D. Nguyen and B. Widrow, Improving the learning speed of 2-layer\n         *    neural networks by choosing initial values of the adaptive\n         *    weights, Proceedings of the International Joint Conference on\n         *    Neural networks (IJCNN), pages 21-26, San Diego, 1990\n         *  - T. Morawietz, Entwicklung eines effizienten Potentials für das\n         *    Wasser-Dimer basierend auf künstlichen neuronalen Netzen,\n         *    Master's thesis, pages 24-28, Bochum, 2010\n         */\n        MS_NGUYENWIDROW,\n        /** Apply preconditioning to output layer connections.\n         *\n         * Multiply weights connecting to output neurons with @f$\\sigma@f$ and\n         * add \"mean\" to biases.\n         *\n         * Call #modifyConnections with two additional arguments:\n         * #modifyConnections(NeuralNetwork::MS_PRECONDITIONOUTPUT,\n         * mean, sigma);\n         */\n        MS_PRECONDITIONOUTPUT\n    };\n\n    /** Neural network class constructor.\n     *\n     * @param[in] numLayers Total number of layers (including in- and\n     *            output layer).\n     * @param[in] numNeuronsPerLayer Array with number of neurons per layer.\n     * @param[in] activationFunctionsPerLayer Array with activation function\n     *            type per layer (note: input layer activation function is\n     *            is mandatory although it is never used).\n     */\n    NeuralNetwork(\n                int                              numLayers,\n                int const* const&                numNeuronsPerLayer,\n                ActivationFunction const* const& activationFunctionsPerLayer);\n    ~NeuralNetwork();\n    // Prevent copying.\n    //NeuralNetwork(const NeuralNetwork&) = delete;\n    //NeuralNetwork(NeuralNetwork&&) = delete;\n    /** Turn on/off neuron normalization.\n     *\n     * @param[in] normalizeNeurons true or false (default: false).\n     */\n    void                     setNormalizeNeurons(bool normalizeNeurons);\n    /** Return total number of neurons.\n     *\n     *  Includes input and output layer.\n     */\n    int                      getNumNeurons() const;\n    /** Return total number of connections.\n     *\n     *  Connections are all weights and biases.\n     */\n    int                      getNumConnections() const;\n    /** Return number of weights.\n     */\n    int                      getNumWeights() const;\n    /** Return number of biases.\n     */\n    int                      getNumBiases() const;\n    /** Set neural network weights and biases.\n     *\n     * @param[in] connections One-dimensional array with neural network\n     *                        connections in the following order:\n     *            @f[\n     *              \\underbrace{\n     *                \\overbrace{\n     *                  a^{01}_{00}, \\ldots, a^{01}_{0m_1},\n     *                  a^{01}_{10}, \\ldots, a^{01}_{1m_1},\n     *                  \\ldots,\n     *                  a^{01}_{n_00}, \\ldots, a^{01}_{n_0m_1},\n     *                }^{\\text{Weights}}\n     *                \\overbrace{\n     *                  b^{1}_{0}, \\ldots, b^{1}_{m_1}\n     *                }^{\\text{Biases}}\n     *              }_{\\text{Layer } 0 \\rightarrow 1},\n     *              \\underbrace{\n     *                a^{12}_{00}, \\ldots, b^{2}_{m_2}\n     *              }_{\\text{Layer } 1 \\rightarrow 2},\n     *              \\ldots,\n     *              \\underbrace{\n     *                a^{p-1,p}_{00}, \\ldots, b^{p}_{m_p}\n     *              }_{\\text{Layer } p-1 \\rightarrow p}\n     *            @f]\n     *            where @f$a^{i-1, i}_{jk}@f$ is the weight connecting neuron\n     *            @f$j@f$ in layer @f$i-1@f$ to neuron @f$k@f$ in layer\n     *            @f$i@f$ and @f$b^{i}_{k}@f$ is the bias assigned to neuron\n     *            @f$k@f$ in layer @f$i@f$.\n     */\n    void                     setConnections(double const* const& connections);\n    /** Get neural network weights and biases.\n     *\n     * @param[out] connections One-dimensional array with neural network\n     *                         connections (same order as described in\n     *                         #setConnections())\n     */\n    void                     getConnections(double* connections) const;\n    /** Initialize connections with random numbers.\n     *\n     * @param[in] seed Random number generator seed.\n     *\n     * Weights are initialized with random values in the @f$[-1, 1]@f$\n     * interval. The C standard library rand() function is used.\n     */\n    void                     initializeConnectionsRandomUniform(\n                                                            unsigned int seed);\n    /** Change connections according to a given modification scheme.\n     *\n     * @param[in] modificationScheme Defines how the connections are modified.\n     *                               See #ModificationScheme for possible\n     *                               options.\n     */\n    void                     modifyConnections(\n                                        ModificationScheme modificationScheme);\n    /** Change connections according to a given modification scheme.\n     *\n     * @param[in] modificationScheme Defines how the connections are modified.\n     *                               See #ModificationScheme for possible\n     *                               options.\n     * @param[in] parameter1 Additional parameter (see #ModificationScheme).\n     * @param[in] parameter2 Additional parameter (see #ModificationScheme).\n     */\n    void                     modifyConnections(\n                                         ModificationScheme modificationScheme,\n                                         double             parameter1,\n                                         double             parameter2);\n    /** Set neural network input layer node values.\n     *\n     * @param[in] input Input layer node values.\n     */\n    void                     setInput(double const* const& input) const;\n    /** Set neural network input layer node values.\n     *\n     * @param[in] index Index of neuron to set.\n     * @param[in] value Input layer neuron value.\n     */\n    void                     setInput(std::size_t const index,\n                                      double const      value) const;\n    /** Get neural network output layer node values.\n     *\n     * @param[out] output Output layer node values.\n     */\n    void                     getOutput(double* output) const;\n    /** Propagate input information through all layers.\n     *\n     * With the input data set by #setInput() this will calculate all remaining\n     * neuron values, the output in the last layer is acccessible via\n     * #getOutput().\n     */\n    void                     propagate();\n    /** Calculate derivative of output neuron with respect to input neurons.\n     *\n     * @param[out] dEdG Array containing derivative (length is number of input\n     *                  neurons).\n     *\n     * __CAUTION__: This works only for neural networks with a single output\n     * neuron!\n     *\n     * Returns @f$\\left(\\frac{dE}{dG_i}\\right)_{i=1,\\ldots,N}@f$, where\n     * @f$E@f$ is the output neuron and @f$\\left(G_i\\right)_{i=1,\\ldots,N}@f$\n     * are the @f$N@f$ input neurons.\n     */\n    void                     calculateDEdG(double* dEdG) const;\n    /** Calculate derivative of output neuron with respect to connections.\n     *\n     * @param[out] dEdc Array containing derivative (length is number of\n     *                  connections, see #getNumConnections()).\n     *\n     * __CAUTION__: This works only for neural networks with a single output\n     * neuron!\n     *\n     * Returns @f$\\left(\\frac{dE}{dc_i}\\right)_{i=1,\\ldots,N}@f$, where\n     * @f$E@f$ is the output neuron and @f$\\left(c_i\\right)_{i=1,\\ldots,N}@f$\n     * are the @f$N@f$ connections (weights and biases) of the neural network.\n     * See #setConnections() for details on the order of weights an biases.\n     */\n    void                     calculateDEdc(double* dEdc) const;\n    /** Calculate \"second\" derivative of output with respect to connections.\n     *\n     * @param[out] dFdc Array containing derivative (length is number of\n     *                  connections, see #getNumConnections()).\n     * @param[in] dGdxyz Array containing derivative of input neurons with\n     *                   respect to coordinates @f$\\frac{\\partial G_j}\n     *                   {\\partial x_{l, \\gamma}}@f$.\n     *\n     * __CAUTION__: This works only for neural networks with a single output\n     * neuron!\n     *\n     * In the context of the neural network potentials this function is used to\n     * calculate derivatives of forces (or force contributions) with respect to\n     * connections. The force component\n     * @f$\\gamma@f$ (where @f$\\gamma@f$ is one of @f$x,y,z@f$)  of\n     * particle @f$l@f$ is\n     * @f[\n     *   F_{l, \\gamma} = - \\frac{\\partial}{\\partial x_{l, \\gamma}} \\sum_i^{N}\n     *   E_i = - \\sum_i^N \\sum_j^M \\frac{\\partial E_i}{\\partial G_j}\n     *   \\frac{\\partial G_j}{\\partial x_{l, \\gamma}},\n     * @f]\n     * where @f$N@f$ is the number of particles in the system and @f$M@f$ is\n     * the number of symmetry functions (number of input neurons). Hence the\n     * derivative of @f$F_{l, \\gamma}@f$ with respect to the neural network\n     * connection @f$c_n@f$ is\n     * @f[\n     *   \\frac{\\partial}{\\partial c_n} F_{l, \\gamma} = - \\sum_i^N \\sum_j^M\n     *   \\frac{\\partial^2 E_i}{\\partial c_n \\partial G_j}\n     *   \\frac{\\partial G_j}{\\partial x_{l, \\gamma}}.\n     * @f]\n     * Thus, with given @f$\\frac{\\partial G_j}{\\partial x_{l, \\gamma}}@f$ this\n     * function calculates\n     * @f[\n     *   \\sum_j^M \\frac{\\partial^2 E}{\\partial c_n \\partial G_j}\n     *   \\frac{\\partial G_j}{\\partial x_{l, \\gamma}}\n     * @f]\n     * for the current network status and returns it via the output array.\n     */\n    void                     calculateDFdc(double*              dFdc,\n                                           double const* const& dGdxyz) const;\n    /** Write connections to file.\n     *\n     * @param[in,out] file File stream to write to.\n     */\n    void                     writeConnections(std::ofstream& file) const;\n    /** Return gathered neuron statistics.\n     *\n     * @param[out] count Number of neuron output value calculations.\n     * @param[out] min   Minimum neuron value encountered.\n     * @param[out] max   Maximum neuron value encountered.\n     * @param[out] sum   Sum of all neuron values encountered.\n     * @param[out] sum2  Sum of squares of all neuron values encountered.\n     *\n     * __CAUTION__: This works only for neural networks with a single output\n     * neuron!\n     *\n     * When neuron values are calculated (e.g. when #propagate() is called)\n     * statistics about encountered values are automatically gathered. The\n     * internal counters can be reset calling #resetNeuronStatistics(). Neuron\n     * values are ordered layer by layer:\n     * @f[\n     *   \\underbrace{y^0_1, \\ldots, y^0_{N_0}}_\\text{Input layer},\n     *   \\underbrace{y^1_1, \\ldots, y^1_{N_1}}_{\\text{Hidden Layer } 1},\n     *   \\ldots,\n     *   \\underbrace{y^p_1, \\ldots, y^p_{N_p}}_\\text{Output layer},\n     * @f]\n     * where @f$y^m_i@f$ is neuron @f$i@f$ in layer @f$m@f$ and @f$N_m@f$ is\n     * the total number of neurons in this layer.\n     */\n    void                     getNeuronStatistics(long*   count,\n                                                 double* min,\n                                                 double* max,\n                                                 double* sum,\n                                                 double* sum2) const;\n    /** Reset neuron statistics.\n     *\n     * Counters and summation variables for neuron statistics are reset.\n     */\n    void                     resetNeuronStatistics();\n    //void   writeStatus(int, int);\n    long                     getMemoryUsage();\n    /** Print neural network architecture.\n     */\n    std::vector<std::string> info() const;\n\nprivate:\n    /// A single neuron.\n    typedef struct\n    {\n        /// How often the value of this neuron has been evaluated.\n        long    count;\n        /// %Neuron value before application of activation function.\n        double  x;\n        /// %Neuron value.\n        double  value;\n        /// Derivative of activation function with respect to its argument\n        /// \\f$ \\frac{\\partial f_a}{\\partial x} \\f$.\n        double  dfdx;\n        /// Second derivative of activation function with respect to its\n        /// argument \\f$ \\frac{\\partial^2 f_a}{\\partial x^2} \\f$.\n        double  d2fdx2;\n        /// Bias value assigned to this neuron (if this is neuron \\f$ y_i^n \\f$\n        /// this bias value is \\f$ b_{i}^{n} \\f$).\n        double  bias;\n        /// Derivative of neuron value before application of activation\n        /// function with respect to input layer neurons\n        /// \\f$ \\frac{\\partial x}{\\partial G} \\f$.\n        double  dxdG;\n        /// Minimum neuron value over data set (neuron statistics).\n        double  min;\n        /// Maximum neuron value over data set (neuron statistics).\n        double  max;\n        /// Sum of neuron values over data set (neuron statistics).\n        double  sum;\n        /// Sum of squared neuron values over data set (neuron statistics).\n        double  sum2;\n        /// NN weights assigned to neuron.\n        /// If this is neuron @f$i@f$ in layer @f$n@f$, \\f$ y_i^n \\f$,\n        /// these weights are \\f$ \\left\\{ a_{ji}^{n-1, n}\n        /// \\right\\}_{j=1,\\ldots,N_n} \\f$.\n        double* weights;\n    } Neuron;\n\n    /// One neural network layer.\n    typedef struct\n    {\n        /// Number of neurons in this layer \\f$ N_n \\f$.\n        int                numNeurons;\n        /// Number of neurons in previous layer \\f$ N_{n-1} \\f$.\n        int                numNeuronsPrevLayer;\n        /// Common activation function for all neurons in this layer.\n        ActivationFunction activationFunction;\n        /// Array of neurons in this layer.\n        Neuron*            neurons;\n    } Layer;\n\n    /// If neurons are normalized.\n    bool   normalizeNeurons;\n    /// Number of NN weights only.\n    int    numWeights;\n    /// Number of NN biases only.\n    int    numBiases;\n    /// Number of NN connections (weights + biases).\n    int    numConnections;\n    /// Total number of layers (includes input and output layers).\n    int    numLayers;\n    /// Number of hidden layers.\n    int    numHiddenLayers;\n    /// Offset adress of weights per layer in combined weights+bias array.\n    int*   weightOffset;\n    /// Offset adress of biases per layer in combined weights+bias array.\n    int*   biasOffset;\n    /// Offset adress of biases per layer in bias only array.\n    int*   biasOnlyOffset;\n    /// Pointer to input layer.\n    Layer* inputLayer;\n    /// Pointer to output layer.\n    Layer* outputLayer;\n    /// Neural network layers.\n    Layer* layers;\n\n    /** Calculate derivative of output neuron with respect to biases.\n     *\n     * @param[out] dEdb Array containing derivatives (length is number of\n     *                  biases).\n     *\n     * __CAUTION__: This works only for neural networks with a single output\n     * neuron!\n     *\n     * Similar to #calculateDEdc() but includes only biases. Used internally\n     * by #calculateDFdc().\n     */\n    void   calculateDEdb(double* dEdb) const;\n    /** Calculate derivative of neuron values before activation function with\n     * respect to input neuron.\n     *\n     * @param[in] index Index of input neuron the derivative will be\n     *                  calculated for.\n     *\n     * No output, derivatives are internally saved for each neuron in\n     * Neuron::dxdG. Used internally by #calculateDFdc().\n     */\n    void   calculateDxdG(int index) const;\n    /** Calculate second derivative of output neuron with respect to input\n     * neuron and connections.\n     *\n     * @param[in] index Index of input neuron the derivative will be\n     *                  calculated for.\n     * @param[in] dEdb Derivatives of output neuron with respect to biases. See\n     *                 #calculateDEdb().\n     * @param[out] d2EdGdc Array containing the derivatives (ordered as\n     *                     described in #setConnections()).\n     *\n     * __CAUTION__: This works only for neural networks with a single output\n     * neuron!\n     *\n     * Used internally by #calculateDFdc().\n     */\n    void   calculateD2EdGdc(int                  index,\n                            double const* const& dEdb,\n                            double*              d2EdGdc) const;\n    /** Allocate a single layer.\n     *\n     * @param[in,out] layer Neural network layer to allocate.\n     * @param[in] numNeuronsPrevLayer Number of neurons in the previous layer.\n     * @param[in] numNeurons Number of neurons in this layer.\n     * @param[in] activationFunction Activation function to use for all neurons\n     *                               in this layer.\n     *\n     * This function is internally called by the constructor to allocate all\n     * neurons layer by layer.\n     */\n    void   allocateLayer(Layer&             layer,\n                         int                numNeuronsPrevLayer,\n                         int                numNeurons,\n                         ActivationFunction activationFunction);\n    /** Propagate information from one layer to the next.\n     *\n     * @param[in,out] layer %Neuron values in this layer will be calculated.\n     * @param[in] layerPrev %Neuron values in this layer will be used as input.\n     *\n     * This function is internally looped by #propagate().\n     */\n    void   propagateLayer(Layer& layer, Layer& layerPrev);\n};\n\n/** Convert string to activation function.\n *\n * @param[in] letter String representing activation function.\n *\n * @return Activation corresponding to string.\n */\nNeuralNetwork::ActivationFunction activationFromString(std::string c);\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/Prediction.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Prediction.h\"\n#include \"Stopwatch.h\"\n#include <fstream>   // std::ifstream\n#include <iostream>\n#include <map>       // std::map\n#include <stdexcept> // std::runtime_error\n#include \"utility.h\"\n\nusing namespace std;\nusing namespace nnp;\n\nPrediction::Prediction() : Mode(),\n                           fileNameSettings        (\"input.nn\"          ),\n                           fileNameScaling         (\"scaling.data\"      ),\n                           formatWeightsFilesShort (\"weights.%03zu.data\" ),\n                           formatWeightsFilesCharge(\"weightse.%03zu.data\")\n{\n}\n\nvoid Prediction::setup()\n{\n    initialize();\n    loadSettingsFile(fileNameSettings);\n    setupGeneric();\n    setupSymmetryFunctionScaling(fileNameScaling);\n    map<string, string> formatWeights {\n        {\"short\", formatWeightsFilesShort},\n        {\"elec\", formatWeightsFilesCharge}\n    };\n    setupNeuralNetworkWeights(formatWeights);\n    setupSymmetryFunctionStatistics(false, false, true, false);\n}\n\nvoid Prediction::readStructureFromFile(string const& fileName)\n{\n    ifstream file;\n    file.open(fileName.c_str());\n    structure.reset();\n    structure.setElementMap(elementMap);\n    structure.readFromFile(fileName);\n    removeEnergyOffset(structure);\n    if (normalize)\n    {\n        structure.toNormalizedUnits(meanEnergy, convEnergy, convLength, convCharge);\n    }\n    file.close();\n\n    return;\n}\n\nvoid Prediction::predict()\n{\n    evaluateNNP(structure);\n    if (normalize)\n    {\n        structure.toPhysicalUnits(meanEnergy, convEnergy, convLength, convCharge);\n    }\n    addEnergyOffset(structure, false);\n    addEnergyOffset(structure, true);\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/Prediction.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef PREDICTION_H\n#define PREDICTION_H\n\n#include \"Mode.h\"\n#include \"Structure.h\"\n#include <string> // std::string\n\nnamespace nnp\n{\n\nclass Prediction : public Mode\n{\npublic:\n    Prediction();\n    void readStructureFromFile(std::string const& fileName = \"input.data\");\n    void setup();\n    void predict();\n\n    std::string fileNameSettings;\n    std::string fileNameScaling;\n    std::string formatWeightsFilesShort;\n    std::string formatWeightsFilesCharge;\n    Structure   structure;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/ScreeningFunction.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2021 Andreas Singraber\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"ScreeningFunction.h\"\n#include \"utility.h\"\n#include <stdexcept>\n\nusing namespace std;\nusing namespace nnp;\n\nScreeningFunction::ScreeningFunction() : inner(0.0),\n                                         outer(0.0),\n                                         scale(0.0)\n{\n    core.setType(CoreFunction::Type::POLY2);\n}\n\nvoid ScreeningFunction::setInnerOuter(double inner, double outer)\n{\n    if (inner >= outer)\n    {\n        throw invalid_argument(\"ERROR: Inner radius of transition region >= \"\n                               \"outer radius.\\n\");\n    }\n\n    this->inner  = inner;\n    this->outer  = outer;\n    this->scale  = 1.0 / (outer - inner);\n\n    return;\n}\n\nvoid ScreeningFunction::changeLengthUnits(double const conv)\n{\n    inner *= conv;\n    outer *= conv;\n    scale /= conv;\n}\nvector<string> ScreeningFunction::info() const\n{\n    vector<string> v;\n\n    v.push_back(\"Screening function information:\\n\");\n    v.push_back(strpr(\"Inner radius : %16.8E\\n\", inner));\n    v.push_back(strpr(\"Outer radius : %16.8E\\n\", outer));\n    v.push_back(\"Transition region functional form:\\n\");\n    v.push_back(\"x     := (r - inner) / (outer - inner)\\n\");\n    v.push_back(\"fs(x) := 1 - f(x)\\n\");\n    vector<string> ci = core.info();\n    v.insert(v.end(), ci.begin(), ci.end());\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/ScreeningFunction.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2021 Andreas Singraber\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SCREENINGFUNCTION_H\n#define SCREENINGFUNCTION_H\n\n#include \"CoreFunction.h\"\n\nnamespace nnp\n{\n\n/// A screening functions for use with electrostatics.\nclass ScreeningFunction\n{\npublic:\n    /** Constructor, initializes to #CoreFunction::Type::POLY2.\n     */\n    ScreeningFunction();\n    /** Set functional form of transition region.\n     *\n     * @param[in] type Type of core function to use.\n     */\n    void                     setCoreFunction(CoreFunction::Type const type);\n    /** Set functional form of transition region.\n     *\n     * @param[in] typeString Type (string version) of core function to use.\n     */\n    void                     setCoreFunction(std::string const type);\n    /** Set inner and outer limit of transition region.\n     *\n     * @param[in] inner Inner radius where transition region begins.\n     * @param[in] outer Outer radius where transition region ends.\n     *\n     */\n    void                     setInnerOuter(double inner, double outer);\n    /** Getter for #type.\n     *\n     * @return Type used.\n     */\n    CoreFunction::Type       getCoreFunctionType() const;\n    /** Getter for #inner.\n     *\n     * @return Inner radius where transition region starts.\n     */\n    double                   getInner() const;\n    /** Getter for #outer.\n     *\n     * @return Outer radius where transition region ends.\n     */\n    double                   getOuter() const;\n    /** Change length units of screening function.\n     *\n     * @param conv Multiplicative conversion factor.\n     */\n    void                     changeLengthUnits(double const conv);\n    /** Screening function @f$f_\\text{screen}@f$.\n     *\n     * @param[in] r Radius argument.\n     *\n     * @return Function value.\n     */\n    double                   f(double r) const;\n    /** Derivative of screening function @f$\\frac{d f_\\text{screen}}{d r}@f$.\n     *\n     * @param[in] r Radius argument.\n     *\n     * @return Value of function derivative.\n     */\n    double                   df(double r) const;\n    /** Calculate screening function and derivative at once.\n     *\n     * @param[in] r Radius argument.\n     * @param[out] fr Screening function value.\n     * @param[out] dfr Value of screening function derivative.\n     */\n    void                     fdf(double r, double& fr, double& dfr) const;\n    /** Get string with information of screening function.\n     *\n     * @return Information string.\n     */\n    std::vector<std::string> info() const;\n\n\nprivate:\n    /// Inner radius where transition region starts.\n    double       inner;\n    /// Outer radius where transition region ends.\n    double       outer;\n    /// Inverse width.\n    double       scale;\n    /// Core function to be used in the transition region.\n    CoreFunction core;\n\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline void ScreeningFunction::setCoreFunction(CoreFunction::Type const type)\n{\n    core.setType(type);\n\n    return;\n}\n\ninline void ScreeningFunction::setCoreFunction(std::string const typeString)\n{\n    core.setType(typeString);\n\n    return;\n}\n\ninline CoreFunction::Type ScreeningFunction::getCoreFunctionType() const\n{\n    return core.getType();\n}\n\ninline double ScreeningFunction::getInner() const { return inner; }\ninline double ScreeningFunction::getOuter() const { return outer; }\n\ninline double ScreeningFunction::f(double r) const\n{\n    if      (r >= outer) return 1.0;\n    else if (r <= inner) return 0.0;\n    else return 1.0 - core.f((r - inner) * scale);\n}\n\ninline double ScreeningFunction::df(double r) const\n{\n    if (r >= outer || r <= inner) return 0.0;\n    else return -scale * core.df((r - inner) * scale);\n}\n\ninline void ScreeningFunction::fdf(double r, double& fr, double& dfr) const\n{\n    if (r >= outer)\n    {\n        fr = 1.0;\n        dfr = 0.0;\n    }\n    else if (r <= inner)\n    {\n        fr = 0.0;\n        dfr = 0.0;\n    }\n    else\n    {\n        core.fdf((r - inner) * scale, fr, dfr);\n        fr = 1.0 - fr;\n        dfr = -scale * dfr;\n    }\n\n    return;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/Settings.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Settings.h\"\n#include \"utility.h\"\n#include <fstream>   // std::ifstream\n#include <stdexcept> // std::runtime_error\n#include <tuple>     // std::tie\n\nusing namespace std;\nusing namespace nnp;\nusing namespace settings;\n\nmap<string, shared_ptr<settings::Key>> const createKnownKeywordsMap()\n{\n    // Main keyword names and descriptions.\n    map<string, string> m;\n    // Alternative names.\n    map<string, vector<string>> a;\n    // Complete keyword map to return.\n    map<string, shared_ptr<settings::Key>> r;\n\n    // Required for prediction.\n    m[\"number_of_elements\"                 ] = \"\";\n    m[\"elements\"                           ] = \"\";\n    m[\"atom_energy\"                        ] = \"\";\n    m[\"cutoff_type\"                        ] = \"\";\n    m[\"symfunction_short\"                  ] = \"\";\n    m[\"scale_symmetry_functions\"           ] = \"\";\n    m[\"scale_min_short\"                    ] = \"\";\n    m[\"scale_max_short\"                    ] = \"\";\n    m[\"center_symmetry_functions\"          ] = \"\";\n    m[\"scale_symmetry_functions_sigma\"     ] = \"\";\n    m[\"global_hidden_layers_short\"         ] = \"\";\n    m[\"global_hidden_layers_electrostatic\" ] = \"\";\n    m[\"global_nodes_short\"                 ] = \"\";\n    m[\"global_nodes_electrostatic\"         ] = \"\";\n    m[\"global_activation_short\"            ] = \"\";\n    m[\"global_activation_electrostatic\"    ] = \"\";\n    m[\"element_hidden_layers_short\"        ] = \"\";\n    m[\"element_hidden_layers_electrostatic\"] = \"\";\n    m[\"element_nodes_short\"                ] = \"\";\n    m[\"element_nodes_electrostatic\"        ] = \"\";\n    m[\"element_activation_short\"           ] = \"\";\n    m[\"element_activation_electrostatic\"   ] = \"\";\n    m[\"normalize_nodes\"                    ] = \"\";\n    m[\"mean_energy\"                        ] = \"\";\n    m[\"conv_length\"                        ] = \"\";\n    m[\"conv_energy\"                        ] = \"\";\n    m[\"conv_charge\"                        ] = \"\";\n    m[\"nnp_type\"                           ] = \"\";\n    m[\"fixed_gausswidth\"                   ] = \"\";\n    m[\"ewald_truncation_error_method\"      ] = \"\";\n    m[\"kspace_solver\"                      ] = \"\";\n    m[\"ewald_prec\"                         ] = \"\";\n    m[\"screen_electrostatics\"              ] = \"\";\n    m[\"four_pi_epsilon\"                    ] = \"\";\n\n    // Training keywords.\n    m[\"random_seed\"                        ] = \"\";\n    m[\"test_fraction\"                      ] = \"\";\n    m[\"epochs\"                             ] = \"\";\n    m[\"normalize_data_set\"                 ] = \"\";\n    m[\"use_short_forces\"                   ] = \"\";\n    m[\"rmse_threshold\"                     ] = \"\";\n    m[\"rmse_threshold_energy\"              ] = \"\";\n    m[\"rmse_threshold_force\"               ] = \"\";\n    m[\"rmse_threshold_charge\"              ] = \"\";\n    m[\"rmse_threshold_trials\"              ] = \"\";\n    m[\"rmse_threshold_trials_energy\"       ] = \"\";\n    m[\"rmse_threshold_trials_force\"        ] = \"\";\n    m[\"rmse_threshold_trials_charge\"       ] = \"\";\n    m[\"energy_fraction\"                    ] = \"\";\n    m[\"force_fraction\"                     ] = \"\";\n    m[\"force_energy_ratio\"                 ] = \"\";\n    m[\"charge_fraction\"                    ] = \"\";\n    m[\"use_old_weights_short\"              ] = \"\";\n    m[\"use_old_weights_charge\"             ] = \"\";\n    m[\"weights_min\"                        ] = \"\";\n    m[\"weights_max\"                        ] = \"\";\n    m[\"initial_hardness\"                   ] = \"\";\n    m[\"nguyen_widrow_weights_short\"        ] = \"\";\n    m[\"nguyen_widrow_weights_charge\"       ] = \"\";\n    m[\"precondition_weights\"               ] = \"\";\n    m[\"main_error_metric\"                  ] = \"\";\n    m[\"write_trainpoints\"                  ] = \"\";\n    m[\"write_trainforces\"                  ] = \"\";\n    m[\"write_traincharges\"                 ] = \"\";\n    m[\"write_weights_epoch\"                ] = \"\";\n    m[\"write_neuronstats\"                  ] = \"\";\n    m[\"write_trainlog\"                     ] = \"\";\n    m[\"repeated_energy_update\"             ] = \"\";\n    m[\"updater_type\"                       ] = \"\";\n    m[\"parallel_mode\"                      ] = \"\";\n    m[\"jacobian_mode\"                      ] = \"\";\n    m[\"update_strategy\"                    ] = \"\";\n    m[\"selection_mode\"                     ] = \"\";\n    m[\"selection_mode_energy\"              ] = \"\";\n    m[\"selection_mode_force\"               ] = \"\";\n    m[\"selection_mode_charge\"              ] = \"\";\n    m[\"task_batch_size_energy\"             ] = \"\";\n    m[\"task_batch_size_force\"              ] = \"\";\n    m[\"task_batch_size_charge\"             ] = \"\";\n    m[\"gradient_type\"                      ] = \"\";\n    m[\"gradient_eta\"                       ] = \"\";\n    m[\"gradient_adam_eta\"                  ] = \"\";\n    m[\"gradient_adam_beta1\"                ] = \"\";\n    m[\"gradient_adam_beta2\"                ] = \"\";\n    m[\"gradient_adam_epsilon\"              ] = \"\";\n    m[\"kalman_type\"                        ] = \"\";\n    m[\"kalman_epsilon\"                     ] = \"\";\n    m[\"kalman_eta\"                         ] = \"\";\n    m[\"kalman_etatau\"                      ] = \"\";\n    m[\"kalman_etamax\"                      ] = \"\";\n    m[\"kalman_q0\"                          ] = \"\";\n    m[\"kalman_qtau\"                        ] = \"\";\n    m[\"kalman_qmin\"                        ] = \"\";\n    m[\"kalman_lambda_short\"                ] = \"\";\n    m[\"kalman_nue_short\"                   ] = \"\";\n    m[\"memorize_symfunc_results\"           ] = \"\";\n    m[\"force_weight\"                       ] = \"\";\n\n    // Alternative keyword names.\n    a[\"nnp_type\"             ] = {\"nnp_generation\", \"nnp_type_gen\", \"nnp_gen\"};\n    a[\"rmse_threshold_energy\"] = {\"short_energy_error_threshold\"};\n    a[\"rmse_threshold_force\" ] = {\"short_force_error_threshold\"};\n    a[\"energy_fraction\"      ] = {\"short_energy_fraction\"};\n    a[\"force_fraction\"       ] = {\"short_force_fraction\"};\n    a[\"symfunction_short\"    ] = {\"symfunction\"};\n\n    for (auto im : m)\n    {\n        // Check if keyword was already inserted.\n        if (r.find(im.first) != r.end())\n        {\n            throw runtime_error(\"ERROR: Multiple definition of keyword.\\n\");\n        }\n        // Insert new shared pointer to a Key object.\n        r[im.first] = make_shared<settings::Key>();\n        // Add main keyword as first entry in alternatives list.\n        r.at(im.first)->addAlternative(im.first);\n        // Add description text.\n        r.at(im.first)->setDescription(im.second);\n        // Check if alternative keywords exist.\n        if (a.find(im.first) != a.end())\n        {\n            // Loop over all alternative keywords.\n            for (auto alt : a.at(im.first))\n            {\n                // Check if alternative keyword is already inserted.\n                if (r.find(alt) != r.end())\n                {\n                    throw runtime_error(\"ERROR: Multiple definition of \"\n                                        \"alternative keyword.\\n\");\n                }\n                // Set map entry, i.e. shared pointer, to Key object.\n                r[alt] = r.at(im.first);\n                // Add alternative keyword to list.\n                r[alt]->addAlternative(alt);\n            }\n        }\n    }\n\n    return r;\n}\n\nSettings::KeywordList Settings::knownKeywords = createKnownKeywordsMap();\n\nstring Settings::operator[](string const& keyword) const\n{\n    return getValue(keyword);\n}\n\n\nsize_t Settings::loadFile(string const& fileName)\n{\n    this->fileName = fileName;\n\n    readFile();\n    return parseLines();\n}\nbool Settings::keywordExists(Key const& key,\n                             bool const exact) const\n{\n    return keywordExists(key.getMainKeyword(), exact);\n}\nbool Settings::keywordExists(string const& keyword, bool exact) const\n{\n    if (knownKeywords.find(keyword) == knownKeywords.end())\n    {\n        throw runtime_error(\"ERROR: Not in the list of allowed keyword: \\\"\" +\n                            keyword + \"\\\".\\n\");\n    }\n    if (exact || knownKeywords.at(keyword)->hasUniqueKeyword())\n    {\n        return (contents.find(keyword) != contents.end());\n    }\n    else\n    {\n        for (auto alternative : *knownKeywords.at(keyword))\n        {\n            if (contents.find(alternative) != contents.end()) return true;\n        }\n    }\n\n    return false;\n}\n\nstring Settings::keywordCheck(string const& keyword) const\n{\n    bool exists = keywordExists(keyword, false);\n    bool unique = knownKeywords.at(keyword)->hasUniqueKeyword();\n    if (!exists)\n    {\n        if (unique)\n        {\n            throw std::runtime_error(\"ERROR: Keyword \\\"\" + keyword\n                                     + \"\\\" not found.\\n\");\n        }\n        else\n        {\n            throw std::runtime_error(\"ERROR: Neither keyword \\\"\" + keyword\n                                     + \"\\\" nor alternative keywords found.\\n\");\n        }\n    }\n\n    bool exact = keywordExists(keyword, true);\n    if (!exact)\n    {\n        for (auto const& alt : *knownKeywords.at(keyword))\n        {\n            if (contents.find(alt) != contents.end()) return alt;\n        }\n    }\n\n    return keyword;\n}\n\nstring Settings::getValue(Key const& key) const\n{\n    return contents.find(key.getMainKeyword())->second.first;\n}\n\nstring Settings::getValue(string const& keyword) const\n{\n    return contents.find(keywordCheck(keyword))->second.first;\n}\n\nSettings::KeyRange Settings::getValues(string const& keyword) const\n{\n    return contents.equal_range(keywordCheck(keyword));\n}\n\nvector<string> Settings::info() const\n{\n    return log;\n}\n\nvector<string> Settings::getSettingsLines() const\n{\n    return lines;\n}\n\nvoid Settings::readFile()\n{\n    ifstream file;\n    string   line;\n\n    log.push_back(strpr(\"Settings file name: %s\\n\", fileName.c_str()));\n    file.open(fileName.c_str());\n    if (!file.is_open())\n    {\n        throw runtime_error(\"ERROR: Could not open file: \\\"\" + fileName\n                            + \"\\\".\\n\");\n    }\n\n    while (getline(file, line))\n    {\n        lines.push_back(line);\n    }\n\n    file.close();\n\n    log.push_back(strpr(\"Read %zu lines.\\n\", lines.size()));\n\n    return;\n}\n\nvoid Settings::writeSettingsFile(ofstream* const&           file,\n                                 map<size_t, string> const& replacements) const\n{\n    if (!file->is_open())\n    {\n        runtime_error(\"ERROR: Could not write to file.\\n\");\n    }\n\n    size_t i = 0;\n    for (auto const& l : lines)\n    {\n        if (replacements.find(i) != replacements.end())\n        {\n            (*file) << replacements.at(i);\n        }\n        else (*file) << l << '\\n';\n        i++;\n    }\n\n    return;\n}\n\nsize_t Settings::parseLines()\n{\n    for (size_t i = 0; i < lines.size(); ++i)\n    {\n        string line = lines.at(i);\n\n        // ignore empty and comment lines\n        if (line.empty())\n        {\n            continue;\n        }\n        // check for empty lines in Windows format\n        if (line == \"\\r\")\n        {\n            continue;\n        }\n        if (line.find('#') != string::npos)\n        {\n            line.erase(line.find('#'));\n        }\n        if (line.find('!') != string::npos)\n        {\n            line.erase(line.find('!'));\n        }\n        if (line.find_first_not_of(' ') == string::npos)\n        {\n            continue;\n        }\n\n        // remove leading and trailing whitespaces and trim separating spaces\n        line = reduce(line);\n\n        // find separator position\n        size_t const separatorPosition = line.find_first_of(\" \");\n        string key;\n        pair<string, size_t> value;\n\n        if (separatorPosition == string::npos)\n        {\n            // first check for single keyword without value\n            key = line;\n            value = pair<string, size_t>(\"\", i);\n        }\n        else\n        {\n            // one or more arguments\n            key = line.substr(0, separatorPosition);\n            value = pair<string, size_t>(line.erase(0, separatorPosition + 1),\n                                         i);\n        }\n\n        contents.insert(pair<string, pair<string, size_t> >(key, value));\n    }\n\n    size_t numProblems = 0;\n    size_t numCritical = 0;\n    tie(numProblems, numCritical) = sanityCheck();\n    if (numProblems > 0)\n    {\n        log.push_back(strpr(\"WARNING: %zu problems detected (%zu critical).\\n\",\n                            numProblems, numCritical));\n    }\n\n    log.push_back(strpr(\"Found %zu lines with keywords.\\n\", contents.size()));\n\n    return numCritical;\n}\n\npair<size_t, size_t> Settings::sanityCheck()\n{\n    size_t countProblems = 0;\n    size_t countCritical = 0;\n\n    // check for unknown keywords\n    for (multimap<string, pair<string, size_t> >::const_iterator\n         it = contents.begin(); it != contents.end(); ++it)\n    {\n        if (knownKeywords.find((*it).first) == knownKeywords.end())\n        {\n            countProblems++;\n            log.push_back(strpr(\n                \"WARNING: Unknown keyword \\\"%s\\\" at line %zu.\\n\",\n                (*it).first.c_str(),\n                (*it).second.second + 1));\n        }\n    }\n\n    // check for multiple instances of known keywords (with exceptions)\n    for (KeywordList::const_iterator it = knownKeywords.begin();\n         it != knownKeywords.end(); ++it)\n    {\n        if (contents.count((*it).first) > 1\n            && (*it).first != \"symfunction\"\n            && (*it).first != \"symfunction_short\"\n            && (*it).first != \"atom_energy\"\n            && (*it).first != \"element_nodes_short\"\n            && (*it).first != \"fixed_gausswidth\"\n            && (*it).first != \"initial_hardness\")\n        {\n            countProblems++;\n            countCritical++;\n            log.push_back(strpr(\n                \"WARNING (CRITICAL): Multiple instances of \\\"%s\\\" detected.\\n\",\n                (*it).first.c_str()));\n        }\n    }\n\n    // Check for usage of multiple keyword versions.\n    for (KeywordList::const_iterator it = knownKeywords.begin();\n         it != knownKeywords.end(); ++it)\n    {\n        if (it->second->hasUniqueKeyword()) continue;\n        vector<string> duplicates;\n        for (auto keyword : *it->second)\n        {\n            if (contents.find(keyword) != contents.end())\n            {\n                duplicates.push_back(keyword);\n            }\n        }\n        if (duplicates.size() > 1)\n        {\n            countProblems++;\n            countCritical++;\n            log.push_back(strpr(\n                \"WARNING (CRITICAL): Multiple alternative versions of keyword \"\n                \"\\\"%s\\\" detected:.\\n\", (*it).first.c_str()));\n            for (auto d : duplicates)\n            {\n                log.push_back(strpr(\n                    \"                    - \\\"%s\\\"\\n\", d.c_str()));\n            }\n        }\n    }\n\n    return make_pair(countProblems, countCritical);\n}\n"
  },
  {
    "path": "src/libnnp/Settings.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SETTINGS_H\n#define SETTINGS_H\n\n#include \"Key.h\"\n#include \"ISettings.h\"\n#include <cstddef> // std::size_t\n#include <fstream> // std::ofstream\n#include <map>     // std::multimap\n#include <memory>  // std::shared_ptr\n#include <string>  // std::string\n#include <utility> // std::pair\n#include <vector>  // std::vector\n\nnamespace nnp\n{\nnamespace settings\n{\n\n\n/// Reads and analyzes settings file and stores parameters.\nclass Settings : public ISettings\n{\npublic:\n\n    typedef std::multimap<std::string,\n                          std::pair<std::string, std::size_t> > KeyMap;\n    typedef std::pair<KeyMap::const_iterator,\n                      KeyMap::const_iterator>                   KeyRange;\n    typedef std::map<std::string,\n                     std::shared_ptr<Key>> const                KeywordList;\n\n    /** Overload [] operator.\n     *\n     * @param[in] keyword Keyword string.\n     * @return Value string corresponding to keyword.\n     *\n     * Internally calls #getValue().\n     */\n    std::string              operator[](std::string const& keyword) const;\n    /** Load a file with settings.\n     *\n     * @param[in] fileName Name of file containing settings.\n     *\n     * @return Number of critical problems detected.\n     */\n    std::size_t              loadFile(\n                                     std::string const& fileName = \"input.nn\");\n    bool                     keywordExists(Key const&  key,\n                                           bool const exact = false) const override;\n    /** Check if keyword is present in settings file.\n     *\n     * @param[in] keyword Keyword string.\n     * @param[in] exact If `True` check only for exact spelling, no\n     *                  alternative keywords allowed.\n     *\n     * @return `True` if keyword exists, `False` otherwise.\n     *\n     * @note This throws an error if the keyword is not in the list of known\n     *       keywords.\n     */\n    bool                     keywordExists(\n                                       std::string const& keyword,\n                                       bool               exact = false) const;\n    /** Check for keyword and alternatives, throw exception if not present.\n     *\n     * @param[in] keyword Original keyword for which alternatives should be\n     *                    searched.\n     *\n     * @return Keyword or alternative found in file contents.\n     */\n    std::string              keywordCheck(std::string const& keyword) const;\n    std::string              getValue(Key const& key) const override;\n    /** Get value for given keyword.\n     *\n     * @param[in] keyword Keyword string.\n     *\n     * @return Value string corresponding to keyword.\n     *\n     * If keyword is present multiple times only the value of the first\n     * keyword-value pair is returned (use #getValues() instead).\n     */\n    std::string              getValue(std::string const& keyword) const;\n    /** Get all keyword-value pairs for given keyword.\n     *\n     * @param[in] keyword Keyword string.\n     *\n     * @return Pair with begin and end values for iteration.\n     *\n     * Useful if keyword appears multiple times. Returns a pair representing\n     * begin and end for an iterator over all corresponding keyword-value\n     * pairs. Use like this:\n     * ```\n     * Settings* s = new Settings(\"input.nn\");\n     * Settings::KeyRange r = s->getValues(\"symfunction_short\");\n     * for (Settings::KeyMap::const_iterator i = r.first; i != r.second; i++)\n     * {\n     *     cout << \"keyword: \" << i->first\n     *          << \" value: \" << i->second.first\n     *          << \" line : \" << i->second.second << \"\\n\";\n     * }\n     * ```\n     */\n    KeyRange                 getValues(std::string const& keyword) const;\n    /** Get logged information about settings file.\n     *\n     * @return Vector with log lines.\n     */\n    std::vector<std::string> info() const;\n    /** Get complete settings file.\n     *\n     * @return Vector with settings file lines.\n     */\n    std::vector<std::string> getSettingsLines() const;\n    /** Write complete settings file.\n     *\n     * @param[in,out] file Settings file.\n     * @param[in] replacements Map of line numbers with alternative content.\n     */\n    void                     writeSettingsFile(\n                                 std::ofstream* const&        file,\n                                 std::map<std::size_t,\n                                          std::string> const& replacements\n                                                                  = {}) const;\n\nprivate:\n    /// Vector of all lines in settings file.\n    std::vector<std::string>                        lines;\n    /// Vector with log lines.\n    std::vector<std::string>                        log;\n    /// Map containing all keyword-value pairs.\n    KeyMap                                          contents;\n    /// Map containing all known keywords and a description.\n    static KeywordList                              knownKeywords;\n    /// %Settings file name.\n    std::string                                     fileName;\n\n    /** Read file once and save all lines in #lines vector.\n     */\n    void                      readFile();\n    /** Parse lines and create #contents map.\n     *\n     * @return Number of critical problems detected.\n     */\n    std::size_t               parseLines();\n    /** Check if all keywords are in known-keywords database and for\n     * duplicates.\n     *\n     * @return Number of detected/critical problems.\n     */\n    std::pair<\n    std::size_t, std::size_t> sanityCheck();\n};\n\n}\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SetupAnalysis.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SetupAnalysis.h\"\n#include \"utility.h\"\n#include <cmath> // M_PI\n\nusing namespace std;\nusing namespace nnp;\n\nvoid SetupAnalysis::writeSymmetryFunctionShape(size_t       numPoints,\n                                               string const fileNameFormat)\n{\n    log << \"\\n\";\n    log << \"*** ANALYSIS: SYMMETRY FUNCTION SHAPE ***\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << strpr(\"Symmetry function file name format: %s\\n\",\n                 fileNameFormat.c_str());\n    log << strpr(\"Number of points                  : %zu\\n\", numPoints);\n    double dr = getMaxCutoffRadius() / numPoints;\n    log << strpr(\"Distance step                     : %f\\n\", dr);\n    double da = M_PI / numPoints;\n    log << strpr(\"Angle step (radians)              : %f\\n\", da);\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        Element const& e = elements.at(i);\n        for (size_t j = 0; j < e.numSymmetryFunctions(); ++j)\n        {\n            SymFnc const& s = e.getSymmetryFunction(j);\n            ofstream file;\n            file.open(strpr(fileNameFormat.c_str(),\n                            e.getAtomicNumber(),\n                            j + 1).c_str());\n            vector<string> info = e.infoSymmetryFunction(s.getIndex());\n            for (vector<string>::const_iterator it = info.begin();\n                 it != info.end(); ++it)\n            {\n                file << strpr(\"#SFINFO %s\\n\", it->c_str());\n            }\n\n            // File header.\n            vector<string> title;\n            vector<string> colName;\n            vector<string> colInfo;\n            vector<size_t> colSize;\n            title.push_back(\"Symmetry function shape.\");\n            colSize.push_back(16);\n            colName.push_back(\"distance\");\n            colInfo.push_back(\"Distance from center.\");\n            colSize.push_back(16);\n            colName.push_back(\"sf_radial\");\n            colInfo.push_back(\"Radial part of symmetry function at given \"\n                              \"distance.\");\n            colSize.push_back(16);\n            colName.push_back(\"angle\");\n            colInfo.push_back(\"Angle in degrees.\");\n            colSize.push_back(16);\n            colName.push_back(\"sf_angular\");\n            colInfo.push_back(\"Angular part of symmetry function at given \"\n                              \"angle.\");\n            appendLinesToFile(file,\n                              createFileHeader(title,\n                                               colSize,\n                                               colName,\n                                               colInfo));\n\n            for (size_t k = 0; k < numPoints + 1; ++k)\n            {\n                file << strpr(\"%16.8E %16.8E %16.8E %16.8E\\n\",\n                              k * dr,\n                              s.calculateRadialPart(k * dr),\n                              k * da,\n                              s.calculateAngularPart(k * da));\n            }\n            file.close();\n        }\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SetupAnalysis.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SETUPANALYSIS_H\n#define SETUPANALYSIS_H\n\n#include \"Mode.h\"\n#include <string> // std::string\n\nnamespace nnp\n{\n\nclass SetupAnalysis : public Mode\n{\npublic:\n    /** Write radial and angular part of symmetry functions to file.\n     *\n     * @param[in] numPoints Number of symmetry function points to plot.\n     * @param[in] fileNameFormat File name with place holder for element and\n     *                           symmetry function number.\n     */\n    void writeSymmetryFunctionShape(std::size_t       numPoints,\n                                    std::string const fileNameFormat\n                                        = \"sf.%03zu.%04zu.out\");\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/Stopwatch.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include <cstdio>\n#include \"Stopwatch.h\"\n\nusing namespace nnp;\n\nconst double Stopwatch::NSEC = 1E-9;\n\nStopwatch::Stopwatch()\n{\n    state        = STOPPED;\n    timeTotal    = 0.0;\n    timeLoop     = 0.0;\n#ifdef N2P2_NO_TIME\n    //fprintf(stderr, \"WARNING: Stopwatch is using dummy implementation.\\n\");\n#elif __linux__\n    time.tv_sec  = 0;\n    time.tv_nsec = 0;\n#elif __MACH__\n    time         = 0;\n#endif\n\n}\n\nvoid Stopwatch::start(bool newLoop)\n{\n    if (state == STOPPED)\n    {\n#ifdef N2P2_NO_TIME\n#elif __linux__\n        clock_gettime(CLOCK_MONOTONIC, &time);\n#elif __MACH__\n        time = mach_absolute_time();\n#endif\n        if (newLoop) timeLoop = 0.0;\n        state = RUNNING;\n    }\n    else\n    {\n        fprintf(stderr,\n                \"WARNING: Unable to start clock, clock already running.\\n\");\n    }\n\n    return;\n}\n\ndouble Stopwatch::stop()\n{\n    stopTime();\n\n    return getTotal();\n}\n\ndouble Stopwatch::loop()\n{\n    stopTime();\n\n    return getLoop();\n}\n\nvoid Stopwatch::reset()\n{\n    state        = STOPPED;\n    timeTotal    = 0.0;\n    timeLoop     = 0.0;\n#ifdef N2P2_NO_TIME\n#elif __linux__\n    time.tv_sec  = 0;\n    time.tv_nsec = 0;\n#elif __MACH__\n    time         = 0;\n#endif\n\n    return;\n}\n\nvoid Stopwatch::stopTime()\n{\n    double timeInterval = updateTime();\n    timeLoop += timeInterval;\n    timeTotal += timeInterval;\n    state = STOPPED;\n\n    return;\n}\n\ndouble Stopwatch::updateTime()\n{\n    if (state == RUNNING)\n    {\n#ifdef N2P2_NO_TIME\n        return 1.0;\n#elif __linux__\n        time_t   secLast  = time.tv_sec;\n        long     nsecLast = time.tv_nsec;\n\n        clock_gettime(CLOCK_MONOTONIC, &time);\n        return (double)(time.tv_sec  - secLast)\n             + (double)(time.tv_nsec - nsecLast) * NSEC;\n#elif __MACH__\n        uint64_t                         lastTime = time;\n        uint64_t                         time     = mach_absolute_time();\n        static mach_timebase_info_data_t info     = {0, 0};\n\n        if (info.denom == 0) mach_timebase_info(&info);\n        return ((time - lastTime) * (info.numer / info.denom)) * NSEC;\n#endif\n    }\n    else\n    {\n        fprintf(stderr,\n                \"WARNING: Unable to update time, clock not running.\\n\");\n        return 0.0;\n    }\n}\n"
  },
  {
    "path": "src/libnnp/Stopwatch.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef STOPWATCH_H\n#define STOPWATCH_H\n\n#if !(defined(__linux__) || defined(__MACH__))\n#pragma message(\"WARNING: Platform not supported.\")\n#define N2P2_NO_TIME\n#endif\n\n#ifdef N2P2_NO_TIME\n#pragma message(\"WARNING: Compiling dummy Stopwatch class (-DN2P2_NO_TIME).\")\n#endif\n\n#include <ctime>\n#ifdef __MACH__\n#include <mach/mach_time.h>\n#endif\n\nnamespace nnp\n{\n\n/// Implements a simple stopwatch on different platforms.\nclass Stopwatch\n{\n\npublic:\n    Stopwatch();\n    /** Start the stopwatch.\n     *\n     * @param[in] resetLoop Optional. If `true` reset loop time, i.e. this\n     *                      start() call is then also the beginning of a new\n     *                      loop. Use `false` if you want to accumulate further\n     *                      time in the loop timer. Default: `true`.\n     */\n    void                      start(bool newLoop = true);\n    /// Stop and return total time.\n    double                    stop();\n    /// Stop and return loop time.\n    double                    loop();\n    /// Return total time elapsed (of a stopped watch).\n    double                    getTotal() const {return timeTotal;};\n    /// Return time elapsed in last loop interval (of a stopped watch).\n    double                    getLoop() const {return timeLoop;};\n    /// Reset stopwatch (total and loop time zero, clock not running).\n    void                      reset();\n\nprivate:\n    enum State\n    {\n        STOPPED,\n        RUNNING\n    };\n\n    State               state;\n    bool                resetLoop;\n    static const double NSEC;\n    double              timeTotal;\n    double              timeLoop;\n#ifdef N2P2_NO_TIME\n#elif __linux__\n    timespec            time;\n#elif __MACH__\n    uint64_t            time;\n#endif\n\n    void                stopTime();\n    double              updateTime();\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/Structure.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Kspace.h\"\n#include \"Structure.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <Eigen/Dense> // MatrixXd, VectorXd\n#include <algorithm>   // std::max\n#include <cmath>       // fabs, erf\n#include <cstdlib>     // atof\n#include <limits>      // std::numeric_limits\n#include <stdexcept>   // std::runtime_error\n#include <string>      // std::getline\n#include <iostream>\n\nusing namespace std;\nusing namespace nnp;\nusing namespace Eigen;\n\n\nStructure::Structure() :\n    isPeriodic                    (false     ),\n    isTriclinic                   (false     ),\n    hasNeighborList               (false     ),\n    NeighborListIsSorted          (false     ),\n    hasSymmetryFunctions          (false     ),\n    hasSymmetryFunctionDerivatives(false     ),\n    index                         (0         ),\n    numAtoms                      (0         ),\n    numElements                   (0         ),\n    numElementsPresent            (0         ),\n    energy                        (0.0       ),\n    energyRef                     (0.0       ),\n    energyShort                   (0.0       ),\n    energyElec                    (0.0       ),\n    hasCharges                    (false     ),\n    charge                        (0.0       ),\n    chargeRef                     (0.0       ),\n    volume                        (0.0       ),\n    maxCutoffRadiusOverall        (0.0       ),\n    sampleType                    (ST_UNKNOWN),\n    comment                       (\"\"        ),\n    hasAMatrix                    (false     )\n{\n    for (size_t i = 0; i < 3; i++)\n    {\n        pbc[i] = 0;\n        box[i][0] = 0.0;\n        box[i][1] = 0.0;\n        box[i][2] = 0.0;\n        invbox[i][0] = 0.0;\n        invbox[i][1] = 0.0;\n        invbox[i][2] = 0.0;\n    }\n}\n\nvoid Structure::setElementMap(ElementMap const& elementMap)\n{\n    this->elementMap = elementMap;\n    numElements = elementMap.size();\n    numAtomsPerElement.resize(numElements, 0);\n\n    return;\n}\n\nvoid Structure::addAtom(Atom const& atom, string const& element)\n{\n    atoms.push_back(Atom());\n    atoms.back() = atom;\n    // The number of elements may have changed.\n    atoms.back().numNeighborsPerElement.resize(elementMap.size(), 0);\n    atoms.back().clearNeighborList();\n    atoms.back().index                = numAtoms;\n    atoms.back().indexStructure       = index;\n    atoms.back().element              = elementMap[element];\n    atoms.back().numSymmetryFunctions = 0;\n    numAtoms++;\n    numAtomsPerElement[elementMap[element]]++;\n\n    return;\n}\n\nvoid Structure::readFromFile(string const fileName)\n{\n    ifstream file;\n\n    file.open(fileName.c_str());\n    if (!file.is_open())\n    {\n        throw runtime_error(\"ERROR: Could not open file: \\\"\" + fileName\n                            + \"\\\".\\n\");\n    }\n    readFromFile(file);\n    file.close();\n\n    return;\n}\n\nvoid Structure::readFromFile(ifstream& file)\n{\n    string         line;\n    vector<string> lines;\n    vector<string> splitLine;\n\n    // read first line, should be keyword \"begin\".\n    getline(file, line);\n    lines.push_back(line);\n    splitLine = split(reduce(line));\n    if (splitLine.at(0) != \"begin\")\n    {\n        throw runtime_error(\"ERROR: Unexpected file content, expected\"\n                            \" \\\"begin\\\" keyword.\\n\");\n    }\n\n    while (getline(file, line))\n    {\n        lines.push_back(line);\n        splitLine = split(reduce(line));\n        if (splitLine.at(0) == \"end\") break;\n    }\n\n    readFromLines(lines);\n\n    return;\n}\n\n\nvoid Structure::readFromLines(vector<string> const& lines)\n{\n    size_t         iBoxVector = 0;\n    vector<string> splitLine;\n\n    // read first line, should be keyword \"begin\".\n    splitLine = split(reduce(lines.at(0)));\n    if (splitLine.at(0) != \"begin\")\n    {\n        throw runtime_error(\"ERROR: Unexpected line content, expected\"\n                            \" \\\"begin\\\" keyword.\\n\");\n    }\n\n    for (vector<string>::const_iterator line = lines.begin();\n         line != lines.end(); ++line)\n    {\n        splitLine = split(reduce(*line));\n        if (splitLine.at(0) == \"begin\")\n        {\n            if (splitLine.size() > 1)\n            {\n                for (vector<string>::const_iterator word =\n                     splitLine.begin() + 1; word != splitLine.end(); ++word)\n                {\n                    if      (*word == \"set=train\") sampleType = ST_TRAINING;\n                    else if (*word == \"set=test\") sampleType = ST_TEST;\n                    else\n                    {\n                        throw runtime_error(\"ERROR: Unknown keyword in \"\n                                            \"structure specification, check \"\n                                            \"\\\"begin\\\" arguments.\\n\");\n                    }\n                }\n            }\n        }\n        else if (splitLine.at(0) == \"comment\")\n        {\n            size_t position = line->find(\"comment\");\n            string tmpLine = *line;\n            comment = tmpLine.erase(position, splitLine.at(0).length() + 1);\n        }\n        else if (splitLine.at(0) == \"lattice\")\n        {\n            if (iBoxVector > 2)\n            {\n                throw runtime_error(\"ERROR: Too many box vectors.\\n\");\n            }\n            box[iBoxVector][0] = atof(splitLine.at(1).c_str());\n            box[iBoxVector][1] = atof(splitLine.at(2).c_str());\n            box[iBoxVector][2] = atof(splitLine.at(3).c_str());\n            iBoxVector++;\n            if (iBoxVector == 3)\n            {\n                isPeriodic = true;\n                if (box[0][1] > numeric_limits<double>::min() ||\n                    box[0][2] > numeric_limits<double>::min() ||\n                    box[1][0] > numeric_limits<double>::min() ||\n                    box[1][2] > numeric_limits<double>::min() ||\n                    box[2][0] > numeric_limits<double>::min() ||\n                    box[2][1] > numeric_limits<double>::min())\n                {\n                    isTriclinic = true;\n                }\n                calculateInverseBox();\n                calculateVolume();\n            }\n        }\n        else if (splitLine.at(0) == \"atom\")\n        {\n            atoms.push_back(Atom());\n            atoms.back().index          = numAtoms;\n            atoms.back().indexStructure = index;\n            atoms.back().tag            = numAtoms; // Implicit conversion!\n            atoms.back().r[0]           = atof(splitLine.at(1).c_str());\n            atoms.back().r[1]           = atof(splitLine.at(2).c_str());\n            atoms.back().r[2]           = atof(splitLine.at(3).c_str());\n            atoms.back().element        = elementMap[splitLine.at(4)];\n            atoms.back().chargeRef      = atof(splitLine.at(5).c_str());\n            atoms.back().fRef[0]        = atof(splitLine.at(7).c_str());\n            atoms.back().fRef[1]        = atof(splitLine.at(8).c_str());\n            atoms.back().fRef[2]        = atof(splitLine.at(9).c_str());\n            atoms.back().numNeighborsPerElement.resize(numElements, 0);\n            numAtoms++;\n            numAtomsPerElement[elementMap[splitLine.at(4)]]++;\n        }\n        else if (splitLine.at(0) == \"energy\")\n        {\n            energyRef = atof(splitLine[1].c_str());\n        }\n        else if (splitLine.at(0) == \"charge\")\n        {\n            chargeRef = atof(splitLine[1].c_str());\n        }\n        else if (splitLine.at(0) == \"end\")\n        {\n            if (!(iBoxVector == 0 || iBoxVector == 3))\n            {\n                throw runtime_error(\"ERROR: Strange number of box vectors.\\n\");\n            }\n            if (isPeriodic &&\n                abs(chargeRef) > 10*std::numeric_limits<double>::epsilon())\n            {\n                throw runtime_error(\"ERROR: In structure with index \"\n                                    + to_string(index)\n                                    + \"; if PBCs are applied, the\\n\"\n                                    \"simulation cell has to be neutrally \"\n                                    \"charged.\\n\");\n            }\n            break;\n        }\n        else\n        {\n            throw runtime_error(\"ERROR: Unexpected file content, \"\n                                \"unknown keyword \\\"\" + splitLine.at(0) +\n                                \"\\\".\\n\");\n        }\n    }\n\n    for (size_t i = 0; i < numElements; i++)\n    {\n        if (numAtomsPerElement[i] > 0)\n        {\n            numElementsPresent++;\n        }\n    }\n\n    if (isPeriodic) remap();\n\n    return;\n}\n\nvoid Structure::calculateMaxCutoffRadiusOverall(\n                                            EwaldSetup& ewaldSetup,\n                                            double rcutScreen,\n                                            double maxCutoffRadius)\n{\n    maxCutoffRadiusOverall = max(rcutScreen, maxCutoffRadius);\n    if (isPeriodic)\n    {\n        ewaldSetup.calculateParameters(volume, numAtoms);\n        maxCutoffRadiusOverall = max(maxCutoffRadiusOverall,\n                                     ewaldSetup.params.rCut);\n    }\n}\n\nvoid Structure::calculateNeighborList(\n                                        double      cutoffRadius,\n                                        bool        sortByDistance)\n{\n    cutoffRadius = max( cutoffRadius, maxCutoffRadiusOverall );\n    //cout << \"CUTOFF: \" << cutoffRadius << \"\\n\";\n\n    if (isPeriodic)\n    {\n        calculatePbcCopies(cutoffRadius, pbc);\n        // Use square of cutoffRadius (faster).\n        cutoffRadius *= cutoffRadius;\n\n#ifdef _OPENMP\n        #pragma omp parallel for\n#endif\n        for (size_t i = 0; i < numAtoms; i++)\n        {\n            // Count atom i as unique neighbor.\n            atoms[i].neighborsUnique.push_back(i);\n            atoms[i].numNeighborsUnique++;\n            for (size_t j = 0; j < numAtoms; j++)\n            {\n                for (int bc0 = -pbc[0]; bc0 <= pbc[0]; bc0++)\n                {\n                    for (int bc1 = -pbc[1]; bc1 <= pbc[1]; bc1++)\n                    {\n                        for (int bc2 = -pbc[2]; bc2 <= pbc[2]; bc2++)\n                        {\n                            if (!(i == j && bc0 == 0 && bc1 == 0 && bc2 == 0))\n                            {\n                                Vec3D dr = atoms[i].r - atoms[j].r\n                                         + bc0 * box[0]\n                                         + bc1 * box[1]\n                                         + bc2 * box[2];\n                                if (dr.norm2() <= cutoffRadius)\n                                {\n                                    atoms[i].neighbors.\n                                        push_back(Atom::Neighbor());\n                                    atoms[i].neighbors.\n                                        back().index = j;\n                                    atoms[i].neighbors.\n                                        back().tag = j; // Implicit conversion!\n                                    atoms[i].neighbors.\n                                        back().element = atoms[j].element;\n                                    atoms[i].neighbors.\n                                        back().d = dr.norm();\n                                    atoms[i].neighbors.\n                                        back().dr = dr;\n                                    atoms[i].numNeighborsPerElement[\n                                        atoms[j].element]++;\n                                    atoms[i].numNeighbors++;\n                                    // Count atom j only once as unique\n                                    // neighbor.\n                                    if (atoms[i].neighborsUnique.back() != j &&\n                                        i != j)\n                                    {\n                                        atoms[i].neighborsUnique.push_back(j);\n                                        atoms[i].numNeighborsUnique++;\n                                    }\n                                }\n                            }\n                        }\n                    }\n                }\n            }\n            atoms[i].hasNeighborList = true;\n        }\n    }\n    else\n    {\n        // Use square of cutoffRadius (faster).\n        cutoffRadius *= cutoffRadius;\n\n#ifdef _OPENMP\n        #pragma omp parallel for\n#endif\n        for (size_t i = 0; i < numAtoms; i++)\n        {\n            // Count atom i as unique neighbor.\n            atoms[i].neighborsUnique.push_back(i);\n            atoms[i].numNeighborsUnique++;\n            for (size_t j = 0; j < numAtoms; j++)\n            {\n                if (i != j)\n                {\n                    Vec3D dr = atoms[i].r - atoms[j].r;\n                    if (dr.norm2() <= cutoffRadius)\n                    {\n                        atoms[i].neighbors.push_back(Atom::Neighbor());\n                        atoms[i].neighbors.back().index   = j;\n                        atoms[i].neighbors.back().tag     = j; // Impl. conv.!\n                        atoms[i].neighbors.back().element = atoms[j].element;\n                        atoms[i].neighbors.back().d       = dr.norm();\n                        atoms[i].neighbors.back().dr      = dr;\n                        atoms[i].numNeighborsPerElement[atoms[j].element]++;\n                        atoms[i].numNeighbors++;\n                        atoms[i].neighborsUnique.push_back(j);\n                        atoms[i].numNeighborsUnique++;\n                    }\n                }\n            }\n            atoms[i].hasNeighborList = true;\n        }\n    }\n\n    hasNeighborList = true;\n\n    if (sortByDistance) sortNeighborList();\n\n    return;\n}\n\nvoid Structure::calculateNeighborList(double                cutoffRadius,\n                                      std::vector<\n                                      std::vector<double>>& cutoffs)\n{\n    calculateNeighborList(cutoffRadius, true);\n    setupNeighborCutoffMap(cutoffs);\n}\n\nvoid Structure::sortNeighborList()\n{\n#ifdef _OPENMP\n        #pragma omp parallel for\n#endif\n    for (size_t i = 0; i < numAtoms; ++i)\n    {\n        sort(atoms[i].neighbors.begin(), atoms[i].neighbors.end());\n        //TODO: maybe sort neighborsUnique too?\n        atoms[i].NeighborListIsSorted = true;\n    }\n    NeighborListIsSorted = true;\n}\n\nvoid Structure::setupNeighborCutoffMap(vector<\n                                       vector<double>> cutoffs)\n{\n    if ( !NeighborListIsSorted )\n        throw runtime_error(\"NeighborCutoffs map needs a sorted neighbor list\");\n\n    for ( auto& elementCutoffs : cutoffs )\n    {\n        if ( maxCutoffRadiusOverall > 0 &&\n             !vectorContains(elementCutoffs, maxCutoffRadiusOverall))\n        {\n            elementCutoffs.push_back(maxCutoffRadiusOverall);\n        }\n\n        if ( !is_sorted(elementCutoffs.begin(), elementCutoffs.end()) )\n        {\n            sort(elementCutoffs.begin(), elementCutoffs.end());\n        }\n    }\n\n    // Loop over all atoms in this structure and create its neighborCutoffs map\n    for( auto& a : atoms )\n    {\n        size_t const eIndex = a.element;\n        vector<double> const& elementCutoffs = cutoffs.at(eIndex);\n        size_t in = 0;\n        size_t ic = 0;\n\n        while( in < a.numNeighbors && ic < elementCutoffs.size() )\n        {\n            Atom::Neighbor const& n = a.neighbors[in];\n            // If neighbor distance is higher than current \"desired cutoff\"\n            // then add neighbor cutoff.\n            // Attention: a step in the neighbor list could jump over multiple\n            // params -> don't increment neighbor index\n            if( n.d > elementCutoffs[ic] )\n            {\n                a.neighborCutoffs.emplace( elementCutoffs.at(ic), in );\n                ++ic;\n            }\n            else if ( in == a.numNeighbors - 1 )\n            {\n                a.neighborCutoffs.emplace( elementCutoffs.at(ic), a.numNeighbors );\n                ++ic;\n            }\n            else ++in;\n        }\n    }\n}\n\nsize_t Structure::getMaxNumNeighbors() const\n{\n    size_t maxNumNeighbors = 0;\n\n    for(vector<Atom>::const_iterator it = atoms.begin();\n        it != atoms.end(); ++it)\n    {\n        maxNumNeighbors = max(maxNumNeighbors, it->numNeighbors);\n    }\n\n    return maxNumNeighbors;\n}\n\nvoid Structure::calculatePbcCopies(double cutoffRadius, int (&pbc)[3])\n{\n    Vec3D axb;\n    Vec3D axc;\n    Vec3D bxc;\n\n    axb = box[0].cross(box[1]).normalize();\n    axc = box[0].cross(box[2]).normalize();\n    bxc = box[1].cross(box[2]).normalize();\n\n    double proja = fabs(box[0] * bxc);\n    double projb = fabs(box[1] * axc);\n    double projc = fabs(box[2] * axb);\n\n    pbc[0] = 0;\n    pbc[1] = 0;\n    pbc[2] = 0;\n    while (pbc[0] * proja <= cutoffRadius)\n    {\n        pbc[0]++;\n    }\n    while (pbc[1] * projb <= cutoffRadius)\n    {\n        pbc[1]++;\n    }\n    while (pbc[2] * projc <= cutoffRadius)\n    {\n        pbc[2]++;\n    }\n\n    return;\n}\n\nvoid Structure::calculateInverseBox()\n{\n    double invdet = box[0][0] * box[1][1] * box[2][2]\n                  + box[1][0] * box[2][1] * box[0][2]\n                  + box[2][0] * box[0][1] * box[1][2]\n                  - box[2][0] * box[1][1] * box[0][2]\n                  - box[0][0] * box[2][1] * box[1][2]\n                  - box[1][0] * box[0][1] * box[2][2];\n    invdet = 1.0 / invdet;\n\n    invbox[0][0] = box[1][1] * box[2][2] - box[2][1] * box[1][2];\n    invbox[0][1] = box[2][1] * box[0][2] - box[0][1] * box[2][2];\n    invbox[0][2] = box[0][1] * box[1][2] - box[1][1] * box[0][2];\n    invbox[0] *= invdet;\n\n    invbox[1][0] = box[2][0] * box[1][2] - box[1][0] * box[2][2];\n    invbox[1][1] = box[0][0] * box[2][2] - box[2][0] * box[0][2];\n    invbox[1][2] = box[1][0] * box[0][2] - box[0][0] * box[1][2];\n    invbox[1] *= invdet;\n\n    invbox[2][0] = box[1][0] * box[2][1] - box[2][0] * box[1][1];\n    invbox[2][1] = box[2][0] * box[0][1] - box[0][0] * box[2][1];\n    invbox[2][2] = box[0][0] * box[1][1] - box[1][0] * box[0][1];\n    invbox[2] *= invdet;\n\n    return;\n}\n\n// TODO: Not needed anymore, should we keep it?\nbool Structure::canMinimumImageConventionBeApplied(double cutoffRadius)\n{\n    Vec3D axb;\n    Vec3D axc;\n    Vec3D bxc;\n\n    axb = box[0].cross(box[1]).normalize();\n    axc = box[0].cross(box[2]).normalize();\n    bxc = box[1].cross(box[2]).normalize();\n\n    double proj[3];\n    proj[0] = fabs(box[0] * bxc);\n    proj[1] = fabs(box[1] * axc);\n    proj[2] = fabs(box[2] * axb);\n\n    double minProj = *min_element(proj, proj+3);\n    return (cutoffRadius < minProj / 2.0);\n}\n\nVec3D Structure::applyMinimumImageConvention(Vec3D const& dr)\n{\n    Vec3D ds = invbox * dr;\n    Vec3D dsNINT;\n\n    for (size_t i=0; i<3; ++i)\n    {\n        dsNINT[i] = round(ds[i]);\n    }\n    Vec3D drMin = box * (ds - dsNINT);\n\n    return drMin;\n}\n\nvoid Structure::calculateVolume()\n{\n    volume = fabs(box[0] * (box[1].cross(box[2])));\n\n    return;\n}\n\ndouble Structure::calculateElectrostaticEnergy(\n                                            EwaldSetup&              ewaldSetup,\n                                            VectorXd                 hardness,\n                                            MatrixXd                 gammaSqrt2,\n                                            VectorXd                 sigmaSqrtPi,\n                                            ScreeningFunction const& fs,\n                                            double const             fourPiEps,\n                                            ErfcBuf&                 erfcBuf)\n{\n    A.resize(numAtoms + 1, numAtoms + 1);\n    A.setZero();\n    VectorXd b(numAtoms + 1);\n    VectorXd hardnessJ(numAtoms);\n    VectorXd Q;\n    erfcBuf.reset(atoms, 2);\n\n#ifdef _OPENMP\n#pragma omp parallel\n    {\n#endif\n    if (isPeriodic)\n    {\n#ifdef _OPENMP\n#pragma omp single\n        {\n#endif\n        if (!NeighborListIsSorted)\n        {\n            throw runtime_error(\"ERROR: Neighbor list needs to \"\n                                \"be sorted for Ewald summation!\\n\");\n        }\n\n        // Should always happen already before neighborlist construction.\n        //ewaldSetup.calculateParameters(volume, numAtoms);\n#ifdef _OPENMP\n        }\n#endif\n        KspaceGrid grid;\n        grid.setup(box, ewaldSetup);\n        double const rcutReal = ewaldSetup.params.rCut;\n        //fprintf(stderr, \"CAUTION: rcutReal = %f\\n\", rcutReal);\n        double const sqrt2eta = sqrt(2.0) * ewaldSetup.params.eta;\n\n#ifdef _OPENMP\n        #pragma omp for schedule(dynamic)\n#endif\n        for (size_t i = 0; i < numAtoms; ++i)\n        {\n            Atom const &ai = atoms.at(i);\n            size_t const ei = ai.element;\n\n            // diagonal including self interaction\n            A(i, i) += hardness(ei)\n                       + (1.0 / sigmaSqrtPi(ei) - 2 / (sqrt2eta * sqrt(M_PI)))\n                         / fourPiEps;\n\n            hardnessJ(i) = hardness(ei);\n            b(i) = -ai.chi;\n\n            // real part\n            size_t const numNeighbors = ai.getStoredMinNumNeighbors(rcutReal);\n            for (size_t k = 0; k < numNeighbors; ++k)\n            {\n                auto const &n = ai.neighbors[k];\n                size_t j = n.tag;\n                if (j < i) continue;\n\n                double const rij = n.d;\n                size_t const ej = n.element;\n\n                double erfcSqrt2Eta = erfcBuf.getf(i, k, 0, rij / sqrt2eta);\n                double erfcGammaSqrt2 =\n                            erfcBuf.getf(i, k, 1, rij / gammaSqrt2(ei, ej));\n\n                A(i, j) += (erfcSqrt2Eta - erfcGammaSqrt2) / (rij * fourPiEps);\n            }\n            // reciprocal part\n            for (size_t j = i; j < numAtoms; ++j)\n            {\n                Atom const &aj = atoms.at(j);\n                for (auto const &gv: grid.kvectors)\n                {\n                    // Multiply by 2 because our grid is only a half-sphere\n                    // Vec3D const dr = applyMinimumImageConvention(ai.r - aj.r);\n                    Vec3D const dr = ai.r - aj.r;\n                    A(i, j) += 2 * gv.coeff * cos(gv.k * dr) / fourPiEps;\n                    //A(i, j) += 2 * gv.coeff * cos(gv.k * (ai.r - aj.r));\n                }\n                A(j, i) = A(i, j);\n            }\n        }\n    }\n    else\n    {\n#ifdef _OPENMP\n#pragma omp for schedule(dynamic)\n#endif\n        for (size_t i = 0; i < numAtoms; ++i)\n        {\n            Atom const &ai = atoms.at(i);\n            size_t const ei = ai.element;\n\n            A(i, i) = hardness(ei) + 1.0 / (sigmaSqrtPi(ei) * fourPiEps);\n            hardnessJ(i) = hardness(ei);\n            b(i) = -ai.chi;\n            for (size_t j = i + 1; j < numAtoms; ++j)\n            {\n                Atom const &aj = atoms.at(j);\n                size_t const ej = aj.element;\n                double const rij = (ai.r - aj.r).norm();\n\n                A(i, j) = erf(rij / gammaSqrt2(ei, ej)) / (rij * fourPiEps);\n                A(j, i) = A(i, j);\n\n            }\n        }\n    }\n#ifdef _OPENMP\n#pragma omp single\n    {\n#endif\n    A.col(numAtoms).setOnes();\n    A.row(numAtoms).setOnes();\n    A(numAtoms, numAtoms) = 0.0;\n    hasAMatrix = true;\n    b(numAtoms) = chargeRef;\n#ifdef _OPENMP\n    }\n#endif\n    //TODO: sometimes only recalculation of A matrix is needed, because\n    //      Qs are stored.\n    Q = A.colPivHouseholderQr().solve(b);\n#ifdef _OPENMP\n    #pragma omp for nowait\n#endif\n    for (size_t i = 0; i < numAtoms; ++i)\n    {\n        atoms.at(i).charge = Q(i);\n    }\n#ifdef _OPENMP\n    } // end of parallel region\n#endif\n\n    lambda = Q(numAtoms);\n    hasCharges = true;\n    double error = (A * Q - b).norm() / b.norm();\n\n    // We need matrix E not A, which only differ by the hardness terms along the diagonal\n    energyElec = 0.5 * Q.head(numAtoms).transpose()\n               * (A.topLeftCorner(numAtoms, numAtoms) -\n                MatrixXd(hardnessJ.asDiagonal())) * Q.head(numAtoms);\n    energyElec += calculateScreeningEnergy(gammaSqrt2, sigmaSqrtPi, fs, fourPiEps);\n\n    return error;\n}\n\ndouble Structure::calculateScreeningEnergy(\n                                        MatrixXd                 gammaSqrt2,\n                                        VectorXd                 sigmaSqrtPi,\n                                        ScreeningFunction const& fs,\n                                        double const             fourPiEps)\n\n{\n    double energyScreen = 0;\n    double const rcutScreen = fs.getOuter();\n\n#ifdef _OPENMP\n    #pragma omp parallel\n    {\n        double localEnergyScreen = 0;\n#endif\n        if (isPeriodic)\n        {\n#ifdef _OPENMP\n            #pragma omp for schedule(dynamic)\n#endif\n            for (size_t i = 0; i < numAtoms; ++i)\n            {\n                Atom const& ai = atoms.at(i);\n                size_t const ei = ai.element;\n                double const Qi = ai.charge;\n#ifdef _OPENMP\n                localEnergyScreen +=  -Qi * Qi\n                                   / (2 * sigmaSqrtPi(ei) * fourPiEps);\n#else\n                energyScreen +=  -Qi * Qi\n                              / (2 * sigmaSqrtPi(ei) * fourPiEps);\n#endif\n\n                size_t const numNeighbors = ai.getStoredMinNumNeighbors(rcutScreen);\n                for (size_t k = 0; k < numNeighbors; ++k)\n                {\n                    auto const& n = ai.neighbors[k];\n                    size_t const j = n.tag;\n                    if (j < i) continue;\n                    double const rij = n.d;\n                    size_t const ej = n.element;\n                    //TODO: Maybe add charge to neighbor class?\n                    double const Qj = atoms.at(j).charge;\n#ifdef _OPENMP\n                    localEnergyScreen += Qi * Qj * erf(rij / gammaSqrt2(ei, ej))\n                                    * (fs.f(rij) - 1) / (rij * fourPiEps);\n#else\n                    energyScreen += Qi * Qj * erf(rij / gammaSqrt2(ei, ej))\n                                    * (fs.f(rij) - 1) / (rij * fourPiEps);\n#endif\n\n               }\n            }\n        }\n        else\n        {\n#ifdef _OPENMP\n            #pragma omp for schedule(dynamic)\n#endif\n            for (size_t i = 0; i < numAtoms; ++i)\n            {\n                Atom const& ai = atoms.at(i);\n                size_t const ei = ai.element;\n                double const Qi = ai.charge;\n#ifdef _OPENMP\n                localEnergyScreen +=  -Qi * Qi\n                                   / (2 * sigmaSqrtPi(ei) * fourPiEps);\n#else\n                energyScreen +=  -Qi * Qi\n                              / (2 * sigmaSqrtPi(ei) * fourPiEps);\n#endif\n\n                for (size_t j = i + 1; j < numAtoms; ++j)\n                {\n                    Atom const& aj = atoms.at(j);\n                    double const Qj = aj.charge;\n                    double const rij = (ai.r - aj.r).norm();\n                    if ( rij < rcutScreen )\n                    {\n#ifdef _OPENMP\n                        localEnergyScreen += Qi * Qj * A(i, j) * (fs.f(rij) - 1);\n#else\n                        energyScreen += Qi * Qj * A(i, j) * (fs.f(rij) - 1);\n#endif\n                    }\n                }\n            }\n        }\n#ifdef _OPENMP\n        #pragma omp atomic\n        energyScreen += localEnergyScreen;\n    }\n#endif\n    //cout << \"energyScreen = \" << energyScreen << endl;\n    return energyScreen;\n}\n\n\nvoid Structure::calculateDAdrQ(EwaldSetup&  ewaldSetup,\n                               MatrixXd     gammaSqrt2,\n                               double const fourPiEps,\n                               ErfcBuf&     erfcBuf)\n{\n\n#ifdef _OPENMP\n    vector<Vec3D> dAdrQDiag(numAtoms);\n    #pragma omp parallel\n    {\n\n    #pragma omp declare reduction(vec_Vec3D_plus : std::vector<Vec3D> : \\\n                  std::transform(omp_out.begin(), omp_out.end(), omp_in.begin(), omp_out.begin(), std::plus<Vec3D>())) \\\n                  initializer(omp_priv = decltype(omp_orig)(omp_orig.size()))\n    #pragma omp for\n#endif\n    // TODO: This initialization loop could probably be avoid, maybe use\n    // default constructor?\n    for (size_t i = 0; i < numAtoms; ++i)\n    {\n        Atom &ai = atoms.at(i);\n        // dAdrQ(numAtoms+1,:) entries are zero\n        ai.dAdrQ.resize(numAtoms + 1);\n    }\n\n    if (isPeriodic)\n    {\n        // TODO: We need same Kspace grid as in calculateScreeningEnergy, should\n        // we cache it for reuse? Note that we can't calculate dAdrQ already in\n        // the loops of calculateElectrostaticEnergy because at this point we don't\n        // have the charges.\n\n        KspaceGrid grid;\n        grid.setup(box, ewaldSetup);\n        double rcutReal = ewaldSetup.params.rCut;\n        double const sqrt2eta = sqrt(2.0) * ewaldSetup.params.eta;\n\n#ifdef _OPENMP\n        // This way of parallelization slightly changes the result because of\n        // numerical errors.\n        #pragma omp for reduction(vec_Vec3D_plus : dAdrQDiag) schedule(dynamic)\n#endif\n        for (size_t i = 0; i < numAtoms; ++i)\n        {\n            Atom &ai = atoms.at(i);\n            size_t const ei = ai.element;\n            double const Qi = ai.charge;\n\n            // real part\n            size_t const numNeighbors = ai.getStoredMinNumNeighbors(rcutReal);\n            for (size_t k = 0; k < numNeighbors; ++k)\n            {\n                auto const &n = ai.neighbors[k];\n                size_t j = n.tag;\n                //if (j < i) continue;\n                if (j <= i) continue;\n\n                double const rij = n.d;\n                Atom &aj = atoms.at(j);\n                size_t const ej = aj.element;\n                double const Qj = aj.charge;\n\n                double erfcSqrt2Eta = erfcBuf.getf(i, k, 0, rij / sqrt2eta);\n                double erfcGammaSqrt2 =\n                        erfcBuf.getf(i, k, 1, rij / gammaSqrt2(ei, ej));\n\n                Vec3D dAijdri;\n                dAijdri = n.dr / pow(rij, 2)\n                          * (2 / sqrt(M_PI) * (-exp(-pow(rij / sqrt2eta, 2))\n                          / sqrt2eta + exp(-pow(rij / gammaSqrt2(ei, ej), 2))\n                          / gammaSqrt2(ei, ej)) - 1 / rij\n                          * (erfcSqrt2Eta - erfcGammaSqrt2));\n                dAijdri /= fourPiEps;\n                // Make use of symmetry: dA_{ij}/dr_i = dA_{ji}/dr_i\n                // = -dA_{ji}/dr_j = -dA_{ij}/dr_j\n                ai.dAdrQ[i] += dAijdri * Qj;\n                ai.dAdrQ[j] += dAijdri * Qi;\n                aj.dAdrQ[i] -= dAijdri * Qj;\n#ifdef _OPENMP\n                dAdrQDiag[j] -= dAijdri * Qi;\n#else\n                aj.dAdrQ[j] -= dAijdri * Qi;\n#endif\n            }\n\n            // reciprocal part\n            for (size_t j = i + 1; j < numAtoms; ++j)\n            {\n                Atom &aj = atoms.at(j);\n                double const Qj = aj.charge;\n                Vec3D dAijdri;\n                for (auto const &gv: grid.kvectors)\n                {\n                    // Multiply by 2 because our grid is only a half-sphere\n                    //Vec3D const dr = applyMinimumImageConvention(ai.r - aj.r);\n                    Vec3D const dr = ai.r - aj.r;\n                    dAijdri -= 2 * gv.coeff * sin(gv.k * dr) * gv.k;\n                }\n                dAijdri /= fourPiEps;\n\n                ai.dAdrQ[i] += dAijdri * Qj;\n                ai.dAdrQ[j] += dAijdri * Qi;\n                aj.dAdrQ[i] -= dAijdri * Qj;\n#ifdef _OPENMP\n                dAdrQDiag[j] -= dAijdri * Qi;\n#else\n                aj.dAdrQ[j] -= dAijdri * Qi;\n#endif\n            }\n        }\n\n    } else\n    {\n#ifdef _OPENMP\n        #pragma omp for reduction(vec_Vec3D_plus : dAdrQDiag) schedule(dynamic)\n#endif\n        for (size_t i = 0; i < numAtoms; ++i)\n        {\n            Atom &ai = atoms.at(i);\n            size_t const ei = ai.element;\n            double const Qi = ai.charge;\n\n            for (size_t j = i + 1; j < numAtoms; ++j)\n            {\n                Atom &aj = atoms.at(j);\n                size_t const ej = aj.element;\n                double const Qj = aj.charge;\n\n                double rij = (ai.r - aj.r).norm();\n                Vec3D dAijdri;\n                dAijdri = (ai.r - aj.r) / pow(rij, 2)\n                          * (2 / (sqrt(M_PI) * gammaSqrt2(ei, ej))\n                             * exp(-pow(rij / gammaSqrt2(ei, ej), 2))\n                             - erf(rij / gammaSqrt2(ei, ej)) / rij);\n                dAijdri /= fourPiEps;\n                // Make use of symmetry: dA_{ij}/dr_i = dA_{ji}/dr_i\n                // = -dA_{ji}/dr_j = -dA_{ij}/dr_j\n                ai.dAdrQ[i] += dAijdri * Qj;\n                ai.dAdrQ[j] = dAijdri * Qi;\n                aj.dAdrQ[i] = -dAijdri * Qj;\n#ifdef _OPENMP\n                dAdrQDiag[j] -= dAijdri * Qi;\n#else\n                aj.dAdrQ[j] -= dAijdri * Qi;\n#endif\n            }\n        }\n    }\n#ifdef _OPENMP\n    #pragma omp for\n    for (size_t i = 0; i < numAtoms; ++i)\n    {\n        Atom& ai = atoms[i];\n        ai.dAdrQ[i] += dAdrQDiag[i];\n    }\n    }\n#endif\n    return;\n}\n\nvoid Structure::calculateDQdChi(vector<Eigen::VectorXd> &dQdChi)\n{\n    dQdChi.clear();\n    dQdChi.reserve(numAtoms);\n    for (size_t i = 0; i < numAtoms; ++i)\n    {\n        // Including Lagrange multiplier equation.\n        VectorXd b(numAtoms+1);\n        b.setZero();\n        b(i) = -1.;\n        dQdChi.push_back(A.colPivHouseholderQr().solve(b).head(numAtoms));\n    }\n    return;\n}\n\nvoid Structure::calculateDQdJ(vector<Eigen::VectorXd> &dQdJ)\n{\n    dQdJ.clear();\n    dQdJ.reserve(numElements);\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        // Including Lagrange multiplier equation.\n        VectorXd b(numAtoms+1);\n        b.setZero();\n        for (size_t j = 0; j < numAtoms; ++j)\n        {\n            Atom const &aj = atoms.at(j);\n            if (i == aj.element) b(j) = -aj.charge;\n        }\n        dQdJ.push_back(A.colPivHouseholderQr().solve(b).head(numAtoms));\n    }\n    return;\n}\n\nvoid Structure::calculateDQdr(  vector<size_t> const&   atomIndices,\n                                vector<size_t> const&   compIndices,\n                                double const            maxCutoffRadius,\n                                vector<Element> const&  elements)\n{\n    if (atomIndices.size() != compIndices.size())\n        throw runtime_error(\"ERROR: In calculation of dQ/dr both atom index and\"\n                            \" component index must be specified.\");\n    for (size_t i = 0; i < atomIndices.size(); ++i)\n    {\n        Atom& a = atoms.at(atomIndices[i]);\n        if ( a.dAdrQ.size() == 0 )\n            throw runtime_error(\"ERROR: dAdrQ needs to be calculated before \"\n                                \"calculating dQdr\");\n        a.dQdr.resize(numAtoms);\n\n        // b stores (-dChidr - dAdrQ), last element for charge conservation.\n        VectorXd b(numAtoms + 1);\n        b.setZero();\n        for (size_t j = 0; j < numAtoms; ++j)\n        {\n            Atom const& aj = atoms.at(j);\n\n#ifndef N2P2_FULL_SFD_MEMORY\n            vector<vector<size_t> > const *const tableFull\n                    = &(elements.at(aj.element).getSymmetryFunctionTable());\n#else\n            vector<vector<size_t> > const *const tableFull = nullptr;\n#endif\n            b(j) -= aj.calculateDChidr(atomIndices[i],\n                                       maxCutoffRadius,\n                                       tableFull)[compIndices[i]];\n            b(j) -= a.dAdrQ.at(j)[compIndices[i]];\n        }\n        VectorXd dQdr = A.colPivHouseholderQr().solve(b).head(numAtoms);\n        for (size_t j = 0; j < numAtoms; ++j)\n        {\n            a.dQdr.at(j)[compIndices[i]] = dQdr(j);\n        }\n    }\n    return;\n}\n\n\nvoid Structure::calculateElectrostaticEnergyDerivatives(\n                                        Eigen::VectorXd          hardness,\n                                        Eigen::MatrixXd          gammaSqrt2,\n                                        VectorXd                 sigmaSqrtPi,\n                                        ScreeningFunction const& fs,\n                                        double const             fourPiEps)\n{\n    // Reset in case structure is used again (e.g. during training)\n    for (Atom &ai : atoms)\n    {\n        ai.pEelecpr = Vec3D{};\n        ai.dEelecdQ = 0.0;\n    }\n\n    double rcutScreen = fs.getOuter();\n    for (size_t i = 0; i < numAtoms; ++i)\n    {\n        Atom& ai = atoms.at(i);\n        size_t const ei = ai.element;\n        double const Qi = ai.charge;\n\n        // TODO: This loop could be reduced by making use of symmetry, j>=i or\n        // so\n        for (size_t j = 0; j < numAtoms; ++j)\n        {\n            Atom& aj = atoms.at(j);\n            double const Qj = aj.charge;\n\n            ai.pEelecpr += 0.5 * Qj * ai.dAdrQ[j];\n            // Diagonal terms contain self-interaction --> screened\n            if (i != j) ai.dEelecdQ += Qj * A(i,j);\n            else if (isPeriodic)\n            {\n                ai.dEelecdQ += Qi * (A(i,i) - hardness(ei)\n                                - 1 / (sigmaSqrtPi(ei) * fourPiEps));\n            }\n        }\n\n        if (isPeriodic)\n        {\n            for (auto const& ajN : ai.neighbors)\n            {\n                size_t j = ajN.tag;\n                Atom& aj = atoms.at(j);\n                if (j < i) continue;\n                double const rij = ajN.d;\n\n                if (rij >= rcutScreen) break;\n\n                size_t const ej = aj.element;\n                double const Qj = atoms.at(j).charge;\n\n                double erfRij = erf(rij / gammaSqrt2(ei,ej));\n                double fsRij = fs.f(rij);\n\n                // corrections due to screening\n                Vec3D Tij = Qi * Qj * ajN.dr / pow(rij,2)\n                                * (2 / (sqrt(M_PI) * gammaSqrt2(ei,ej))\n                                * exp(- pow(rij / gammaSqrt2(ei,ej),2))\n                                * (fsRij - 1) + erfRij * fs.df(rij) - erfRij\n                                * (fsRij - 1) / rij);\n                Tij /= fourPiEps;\n                ai.pEelecpr += Tij;\n                aj.pEelecpr -= Tij;\n\n                double Sij = erfRij * (fsRij - 1) / rij;\n                Sij /= fourPiEps;\n                ai.dEelecdQ += Qj * Sij;\n                aj.dEelecdQ += Qi * Sij;\n            }\n        }\n        else\n        {\n            for (size_t j = i + 1; j < numAtoms; ++j)\n            {\n                Atom& aj = atoms.at(j);\n                double const rij = (ai.r - aj.r).norm();\n                if (rij >= rcutScreen) continue;\n\n                size_t const ej = aj.element;\n                double const Qj = atoms.at(j).charge;\n\n                double erfRij = erf(rij / gammaSqrt2(ei,ej));\n                double fsRij = fs.f(rij);\n\n                // corrections due to screening\n                Vec3D Tij = Qi * Qj * (ai.r - aj.r) / pow(rij,2)\n                                * (2 / (sqrt(M_PI) * gammaSqrt2(ei,ej))\n                                * exp(- pow(rij / gammaSqrt2(ei,ej),2))\n                                * (fsRij - 1) + erfRij * fs.df(rij) - erfRij\n                                * (fsRij - 1) / rij);\n                Tij /= fourPiEps;\n                ai.pEelecpr += Tij;\n                aj.pEelecpr -= Tij;\n\n                double Sij = erfRij * (fsRij - 1) / rij;\n                Sij /= fourPiEps;\n                ai.dEelecdQ += Qj * Sij;\n                aj.dEelecdQ += Qi * Sij;\n            }\n        }\n    }\n   return;\n}\n\nVectorXd const Structure::calculateForceLambdaTotal() const\n{\n    VectorXd dEdQ(numAtoms+1);\n    for (size_t i = 0; i < numAtoms; ++i)\n    {\n        Atom const& ai = atoms.at(i);\n        dEdQ(i) = ai.dEelecdQ + ai.dEdG.back();\n    }\n    dEdQ(numAtoms) = 0;\n    VectorXd const lambdaTotal = A.colPivHouseholderQr().solve(-dEdQ);\n    return lambdaTotal;\n}\n\nVectorXd const Structure::calculateForceLambdaElec() const\n{\n    VectorXd dEelecdQ(numAtoms+1);\n    for (size_t i = 0; i < numAtoms; ++i)\n    {\n        Atom const& ai = atoms.at(i);\n        dEelecdQ(i) = ai.dEelecdQ;\n    }\n    dEelecdQ(numAtoms) = 0;\n    VectorXd const lambdaElec = A.colPivHouseholderQr().solve(-dEelecdQ);\n    return lambdaElec;\n}\n\nvoid Structure::remap()\n{\n    for (vector<Atom>::iterator it = atoms.begin(); it != atoms.end(); ++it)\n    {\n        remap((*it));\n    }\n    return;\n}\n\nvoid Structure::remap(Atom& atom)\n{\n    Vec3D f = atom.r[0] * invbox[0]\n            + atom.r[1] * invbox[1]\n            + atom.r[2] * invbox[2];\n\n    // Quick and dirty... there may be a more elegant way!\n    if (f[0] > 1.0) f[0] -= (int)f[0];\n    if (f[1] > 1.0) f[1] -= (int)f[1];\n    if (f[2] > 1.0) f[2] -= (int)f[2];\n\n    if (f[0] < 0.0) f[0] += 1.0 - (int)f[0];\n    if (f[1] < 0.0) f[1] += 1.0 - (int)f[1];\n    if (f[2] < 0.0) f[2] += 1.0 - (int)f[2];\n\n    if (f[0] == 1.0) f[0] = 0.0;\n    if (f[1] == 1.0) f[1] = 0.0;\n    if (f[2] == 1.0) f[2] = 0.0;\n\n    atom.r = f[0] * box[0]\n           + f[1] * box[1]\n           + f[2] * box[2];\n\n    return;\n}\n\nvoid Structure::toNormalizedUnits(double meanEnergy,\n                                  double convEnergy,\n                                  double convLength,\n                                  double convCharge)\n{\n    if (isPeriodic)\n    {\n        box[0] *= convLength;\n        box[1] *= convLength;\n        box[2] *= convLength;\n        invbox[0] /= convLength;\n        invbox[1] /= convLength;\n        invbox[2] /= convLength;\n    }\n\n    energyRef = (energyRef - numAtoms * meanEnergy) * convEnergy;\n    energy = (energy - numAtoms * meanEnergy) * convEnergy;\n    chargeRef *= convCharge;\n    charge *= convCharge;\n    volume *= convLength * convLength * convLength;\n\n    for (vector<Atom>::iterator it = atoms.begin(); it != atoms.end(); ++it)\n    {\n        it->toNormalizedUnits(convEnergy, convLength, convCharge);\n    }\n\n    return;\n}\n\nvoid Structure::toPhysicalUnits(double meanEnergy,\n                                double convEnergy,\n                                double convLength,\n                                double convCharge)\n{\n    if (isPeriodic)\n    {\n        box[0] /= convLength;\n        box[1] /= convLength;\n        box[2] /= convLength;\n        invbox[0] *= convLength;\n        invbox[1] *= convLength;\n        invbox[2] *= convLength;\n    }\n\n    energyRef = energyRef / convEnergy + numAtoms * meanEnergy;\n    energy = energy / convEnergy + numAtoms * meanEnergy;\n    chargeRef /= convCharge;\n    charge /= convCharge;\n    volume /= convLength * convLength * convLength;\n\n    for (vector<Atom>::iterator it = atoms.begin(); it != atoms.end(); ++it)\n    {\n        it->toPhysicalUnits(convEnergy, convLength, convCharge);\n    }\n\n    return;\n}\n\nvoid Structure::freeAtoms(bool all, double const maxCutoffRadius)\n{\n    for (vector<Atom>::iterator it = atoms.begin(); it != atoms.end(); ++it)\n    {\n        it->free(all, maxCutoffRadius);\n    }\n    if (all) hasSymmetryFunctions = false;\n    hasSymmetryFunctionDerivatives = false;\n\n    return;\n}\n\nvoid Structure::reset()\n{\n    isPeriodic                     = false     ;\n    isTriclinic                    = false     ;\n    hasNeighborList                = false     ;\n    hasSymmetryFunctions           = false     ;\n    hasSymmetryFunctionDerivatives = false     ;\n    index                          = 0         ;\n    numAtoms                       = 0         ;\n    numElementsPresent             = 0         ;\n    energy                         = 0.0       ;\n    energyRef                      = 0.0       ;\n    charge                         = 0.0       ;\n    chargeRef                      = 0.0       ;\n    volume                         = 0.0       ;\n    sampleType                     = ST_UNKNOWN;\n    comment                        = \"\"        ;\n\n    for (size_t i = 0; i < 3; ++i)\n    {\n        pbc[i] = 0;\n        for (size_t j = 0; j < 3; ++j)\n        {\n            box[i][j] = 0.0;\n            invbox[i][j] = 0.0;\n        }\n    }\n\n    numElements = elementMap.size();\n    numAtomsPerElement.clear();\n    numAtomsPerElement.resize(numElements, 0);\n    atoms.clear();\n    vector<Atom>(atoms).swap(atoms);\n\n    return;\n}\n\nvoid Structure::clearNeighborList()\n{\n    for (size_t i = 0; i < numAtoms; i++)\n    {\n        Atom& a = atoms.at(i);\n        // This may have changed if atoms are added via addAtoms().\n        a.numNeighborsPerElement.resize(numElements, 0);\n        a.clearNeighborList();\n    }\n    hasNeighborList = false;\n    hasSymmetryFunctions = false;\n    hasSymmetryFunctionDerivatives = false;\n\n    return;\n}\n\nvoid Structure::clearElectrostatics(bool clearDQdr)\n{\n    A.resize(0,0);\n    hasAMatrix = false;\n    for (auto& a : atoms)\n    {\n        vector<Vec3D>().swap(a.dAdrQ);\n        if (clearDQdr)\n        {\n            vector<Vec3D>().swap(a.dQdr);\n        }\n    }\n}\n\nvoid Structure::updateError(string const&        property,\n                            map<string, double>& error,\n                            size_t&              count) const\n{\n    if (property == \"energy\")\n    {\n        count++;\n        double diff = energyRef - energy;\n        error.at(\"RMSEpa\") += diff * diff / (numAtoms * numAtoms);\n        error.at(\"RMSE\") += diff * diff;\n        diff = fabs(diff);\n        error.at(\"MAEpa\") += diff / numAtoms;\n        error.at(\"MAE\") += diff;\n    }\n    else if (property == \"force\" || property == \"charge\")\n    {\n        for (vector<Atom>::const_iterator it = atoms.begin();\n             it != atoms.end(); ++it)\n        {\n            it->updateError(property, error, count);\n        }\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown property for error update.\\n\");\n    }\n\n    return;\n}\n\nstring Structure::getEnergyLine() const\n{\n    return strpr(\"%10zu %16.8E %16.8E\\n\",\n                 index,\n                 energyRef / numAtoms,\n                 energy / numAtoms);\n}\n\nvector<string> Structure::getForcesLines() const\n{\n    vector<string> v;\n    for (vector<Atom>::const_iterator it = atoms.begin();\n         it != atoms.end(); ++it)\n    {\n        vector<string> va = it->getForcesLines();\n        v.insert(v.end(), va.begin(), va.end());\n    }\n\n    return v;\n}\n\nvector<string> Structure::getChargesLines() const\n{\n    vector<string> v;\n    for (vector<Atom>::const_iterator it = atoms.begin();\n         it != atoms.end(); ++it)\n    {\n        v.push_back(it->getChargeLine());\n    }\n\n    return v;\n}\n\nvoid Structure::writeToFile(string const fileName,\n                            bool const   ref,\n                            bool const   append) const\n{\n    ofstream file;\n\n    if (append)\n    {\n        file.open(fileName.c_str(), ofstream::app);\n    }\n    else\n    {\n        file.open(fileName.c_str());\n    }\n    if (!file.is_open())\n    {\n        throw runtime_error(\"ERROR: Could not open file: \\\"\" + fileName\n                            + \"\\\".\\n\");\n    }\n    writeToFile(&file, ref );\n    file.close();\n\n    return;\n}\n\nvoid Structure::writeToFile(ofstream* const& file, bool const ref) const\n{\n    if (!file->is_open())\n    {\n        runtime_error(\"ERROR: Cannot write to file, file is not open.\\n\");\n    }\n\n    (*file) << \"begin\\n\";\n    (*file) << strpr(\"comment %s\\n\", comment.c_str());\n    if (isPeriodic)\n    {\n        for (size_t i = 0; i < 3; ++i)\n        {\n            (*file) << strpr(\"lattice %24.16E %24.16E %24.16E\\n\",\n                             box[i][0], box[i][1], box[i][2]);\n        }\n    }\n    for (vector<Atom>::const_iterator it = atoms.begin();\n         it != atoms.end(); ++it)\n    {\n        if (ref)\n        {\n            (*file) << strpr(\"atom %24.16E %24.16E %24.16E %2s %24.16E %24.16E\"\n                             \" %24.16E %24.16E %24.16E\\n\",\n                             it->r[0],\n                             it->r[1],\n                             it->r[2],\n                             elementMap[it->element].c_str(),\n                             it->chargeRef,\n                             0.0,\n                             it->fRef[0],\n                             it->fRef[1],\n                             it->fRef[2]);\n        }\n        else\n        {\n            (*file) << strpr(\"atom %24.16E %24.16E %24.16E %2s %24.16E %24.16E\"\n                             \" %24.16E %24.16E %24.16E\\n\",\n                             it->r[0],\n                             it->r[1],\n                             it->r[2],\n                             elementMap[it->element].c_str(),\n                             it->charge,\n                             0.0,\n                             it->f[0],\n                             it->f[1],\n                             it->f[2]);\n\n        }\n    }\n    if (ref) (*file) << strpr(\"energy %24.16E\\n\", energyRef);\n    else     (*file) << strpr(\"energy %24.16E\\n\", energy);\n    if (ref) (*file) << strpr(\"charge %24.16E\\n\", chargeRef);\n    else     (*file) << strpr(\"charge %24.16E\\n\", charge);\n    (*file) << strpr(\"end\\n\");\n\n    return;\n}\n\nvoid Structure::writeToFileXyz(ofstream* const& file) const\n{\n    if (!file->is_open())\n    {\n        runtime_error(\"ERROR: Could not write to file.\\n\");\n    }\n\n    (*file) << strpr(\"%d\\n\", numAtoms);\n    if (isPeriodic)\n    {\n        (*file) << \"Lattice=\\\"\";\n        (*file) << strpr(\"%24.16E %24.16E %24.16E \"   ,\n                         box[0][0], box[0][1], box[0][2]);\n        (*file) << strpr(\"%24.16E %24.16E %24.16E \"   ,\n                         box[1][0], box[1][1], box[1][2]);\n        (*file) << strpr(\"%24.16E %24.16E %24.16E\\\"\\n\",\n                         box[2][0], box[2][1], box[2][2]);\n    }\n    else\n    {\n        (*file) << \"\\n\";\n    }\n    for (vector<Atom>::const_iterator it = atoms.begin();\n         it != atoms.end(); ++it)\n    {\n        (*file) << strpr(\"%-2s %24.16E %24.16E %24.16E\\n\",\n                         elementMap[it->element].c_str(),\n                         it->r[0],\n                         it->r[1],\n                         it->r[2]);\n    }\n\n    return;\n}\n\nvoid Structure::writeToFilePoscar(ofstream* const& file) const\n{\n    writeToFilePoscar(file, elementMap.getElementsString());\n\n    return;\n}\n\nvoid Structure::writeToFilePoscar(ofstream* const& file,\n                                  string const elements) const\n{\n    if (!file->is_open())\n    {\n        runtime_error(\"ERROR: Could not write to file.\\n\");\n    }\n\n    vector<string> ve = split(elements);\n    vector<size_t> elementOrder;\n    for (size_t i = 0; i < ve.size(); ++i)\n    {\n        elementOrder.push_back(elementMap[ve.at(i)]);\n    }\n    if (elementOrder.size() != elementMap.size())\n    {\n        runtime_error(\"ERROR: Inconsistent element declaration.\\n\");\n    }\n\n    (*file) << strpr(\"%s, \", comment.c_str());\n    (*file) << strpr(\"ATOM=%s\", elementMap[elementOrder.at(0)].c_str());\n    for (size_t i = 1; i < elementOrder.size(); ++i)\n    {\n        (*file) << strpr(\" %s\", elementMap[elementOrder.at(i)].c_str());\n    }\n    (*file) << \"\\n\";\n    (*file) << \"1.0\\n\";\n    if (isPeriodic)\n    {\n        (*file) << strpr(\"%24.16E %24.16E %24.16E\\n\",\n                         box[0][0], box[0][1], box[0][2]);\n        (*file) << strpr(\"%24.16E %24.16E %24.16E\\n\",\n                         box[1][0], box[1][1], box[1][2]);\n        (*file) << strpr(\"%24.16E %24.16E %24.16E\\n\",\n                         box[2][0], box[2][1], box[2][2]);\n    }\n    else\n    {\n        runtime_error(\"ERROR: Writing non-periodic structure to POSCAR file \"\n                      \"is not implemented.\\n\");\n    }\n    (*file) << strpr(\"%d\", numAtomsPerElement.at(elementOrder.at(0)));\n    for (size_t i = 1; i < numAtomsPerElement.size(); ++i)\n    {\n        (*file) << strpr(\" %d\", numAtomsPerElement.at(elementOrder.at(i)));\n    }\n    (*file) << \"\\n\";\n    (*file) << \"Cartesian\\n\";\n    for (size_t i = 0; i < elementOrder.size(); ++i)\n    {\n        for (vector<Atom>::const_iterator it = atoms.begin();\n             it != atoms.end(); ++it)\n        {\n            if (it->element == elementOrder.at(i))\n            {\n                (*file) << strpr(\"%24.16E %24.16E %24.16E\\n\",\n                                 it->r[0],\n                                 it->r[1],\n                                 it->r[2]);\n            }\n        }\n    }\n\n    return;\n}\n\nvector<string> Structure::info() const\n{\n    vector<string> v;\n\n    v.push_back(strpr(\"********************************\\n\"));\n    v.push_back(strpr(\"STRUCTURE                       \\n\"));\n    v.push_back(strpr(\"********************************\\n\"));\n    vector<string> vm = elementMap.info();\n    v.insert(v.end(), vm.begin(), vm.end());\n    v.push_back(strpr(\"index                          : %d\\n\", index));\n    v.push_back(strpr(\"isPeriodic                     : %d\\n\", isPeriodic        ));\n    v.push_back(strpr(\"isTriclinic                    : %d\\n\", isTriclinic       ));\n    v.push_back(strpr(\"hasNeighborList                : %d\\n\", hasNeighborList   ));\n    v.push_back(strpr(\"hasSymmetryFunctions           : %d\\n\", hasSymmetryFunctions));\n    v.push_back(strpr(\"hasSymmetryFunctionDerivatives : %d\\n\", hasSymmetryFunctionDerivatives));\n    v.push_back(strpr(\"numAtoms                       : %d\\n\", numAtoms          ));\n    v.push_back(strpr(\"numElements                    : %d\\n\", numElements       ));\n    v.push_back(strpr(\"numElementsPresent             : %d\\n\", numElementsPresent));\n    v.push_back(strpr(\"pbc                            : %d %d %d\\n\", pbc[0], pbc[1], pbc[2]));\n    v.push_back(strpr(\"energy                         : %16.8E\\n\", energy        ));\n    v.push_back(strpr(\"energyRef                      : %16.8E\\n\", energyRef     ));\n    v.push_back(strpr(\"charge                         : %16.8E\\n\", charge        ));\n    v.push_back(strpr(\"chargeRef                      : %16.8E\\n\", chargeRef     ));\n    v.push_back(strpr(\"volume                         : %16.8E\\n\", volume        ));\n    v.push_back(strpr(\"sampleType                     : %d\\n\", (int)sampleType));\n    v.push_back(strpr(\"comment                        : %s\\n\", comment.c_str()   ));\n    v.push_back(strpr(\"box[0]                         : %16.8E %16.8E %16.8E\\n\", box[0][0], box[0][1], box[0][2]));\n    v.push_back(strpr(\"box[1]                         : %16.8E %16.8E %16.8E\\n\", box[1][0], box[1][1], box[1][2]));\n    v.push_back(strpr(\"box[2]                         : %16.8E %16.8E %16.8E\\n\", box[2][0], box[2][1], box[2][2]));\n    v.push_back(strpr(\"invbox[0]                      : %16.8E %16.8E %16.8E\\n\", invbox[0][0], invbox[0][1], invbox[0][2]));\n    v.push_back(strpr(\"invbox[1]                      : %16.8E %16.8E %16.8E\\n\", invbox[1][0], invbox[1][1], invbox[1][2]));\n    v.push_back(strpr(\"invbox[2]                      : %16.8E %16.8E %16.8E\\n\", invbox[2][0], invbox[2][1], invbox[2][2]));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"numAtomsPerElement         [*] : %d\\n\", numAtomsPerElement.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < numAtomsPerElement.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  : %d\\n\", i, numAtomsPerElement.at(i)));\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"atoms                      [*] : %d\\n\", atoms.size()));\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    for (size_t i = 0; i < atoms.size(); ++i)\n    {\n        v.push_back(strpr(\"%29d  :\\n\", i));\n        vector<string> va = atoms[i].info();\n        v.insert(v.end(), va.begin(), va.end());\n    }\n    v.push_back(strpr(\"--------------------------------\\n\"));\n    v.push_back(strpr(\"********************************\\n\"));\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/Structure.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef STRUCTURE_H\n#define STRUCTURE_H\n\n#include \"Atom.h\"\n#include \"Element.h\"\n#include \"ElementMap.h\"\n#include \"ErfcBuf.h\"\n#include \"EwaldSetup.h\"\n#include \"ScreeningFunction.h\"\n#include \"Vec3D.h\"\n#include <Eigen/Core> // MatrixXd, VectorXd\n#include <cstddef>    // std::size_t\n#include <fstream>    // std::ofstream\n#include <map>        // std::map\n#include <string>     // std::string\n#include <vector>     // std::vector\n\nnamespace nnp\n{\n\n/// Storage for one atomic configuration.\nstruct Structure\n{\n    /** Enumerates different sample types (e.g. training or test set).\n     */\n    enum SampleType\n    {\n        /** Sample type not assigned yet.\n         */\n        ST_UNKNOWN,\n        /** Structure is part of the training set.\n         */\n        ST_TRAINING,\n        /** Structure is part of validation set (currently unused).\n         */\n        ST_VALIDATION,\n        /** Structure is part of the test set.\n         */\n        ST_TEST\n    };\n\n    /// Copy of element map provided as constructor argument.\n    ElementMap               elementMap;\n    /// If periodic boundary conditions apply.\n    bool                     isPeriodic;\n    /// If the simulation box is triclinic.\n    bool                     isTriclinic;\n    /// If the neighbor list has been calculated.\n    bool                     hasNeighborList;\n    /// If the neighbor list has been sorted by distance.\n    bool                     NeighborListIsSorted;\n    /// If symmetry function values are saved for each atom.\n    bool                     hasSymmetryFunctions;\n    /// If symmetry function derivatives are saved for each atom.\n    bool                     hasSymmetryFunctionDerivatives;\n    /// Index number of this structure.\n    std::size_t              index;\n    /// Total number of atoms present in this structure.\n    std::size_t              numAtoms;\n    /// Global number of elements (all structures).\n    std::size_t              numElements;\n    /// Number of elements present in this structure.\n    std::size_t              numElementsPresent;\n    /// Number of PBC images necessary in each direction for max cut-off.\n    int                      pbc[3];\n    /// Potential energy determined by neural network.\n    double                   energy;\n    /// Reference potential energy.\n    double                   energyRef;\n    // TODO: MPI_Pack\n    /// Short-range part of the potential energy predicted by NNP.\n    double                   energyShort;\n    // TODO: MPI_Pack\n    /// Electrostatics part of the potential energy predicted by NNP.\n    double                   energyElec;\n    /// If all charges of this structure have been calculated (and stay the\n    /// same, e.g. for stage 2).\n    bool                     hasCharges;\n    /// Charge determined by neural network potential.\n    double                   charge;\n    /// Reference charge.\n    double                   chargeRef;\n    /// Simulation box volume.\n    double                   volume;\n    /// Maximum cut-off radius with respect to symmetry functions, screening\n    /// function and Ewald summation.\n    double                   maxCutoffRadiusOverall;\n    // TODO: MPI_Pack\n    /// Lagrange multiplier used for charge equilibration.\n    double                   lambda;\n    /// Sample type (training or test set).\n    SampleType               sampleType;\n    /// Structure comment.\n    std::string              comment;\n    /// Simulation box vectors.\n    Vec3D                    box[3];\n    /// Inverse simulation box vectors.\n    Vec3D                    invbox[3];\n    /// Global charge equilibration matrix A'.\n    Eigen::MatrixXd          A;\n    /// If A matrix of this structure is currently stored.\n    bool                     hasAMatrix;\n    /// Number of atoms of each element in this structure.\n    std::vector<std::size_t> numAtomsPerElement;\n    /// Vector of all atoms in this structure.\n    std::vector<Atom>        atoms;\n\n    /** Constructor, initializes to zero.\n     */\n    Structure();\n    /** Set element map of structure.\n     *\n     * @param[in] elementMap Reference to a map containing all possible\n     *                       (symbol, index)-pairs (see ElementMap).\n     */\n    void                     setElementMap(ElementMap const& elementMap);\n    /** Add a single atom to structure.\n     *\n     * @param[in] atom Atom to insert.\n     * @param[in] element Element string of new atom.\n     *\n     * @note Be sure to set the element map properly before adding atoms. This\n     * function will only keep the atom's coordinates, energy, charge, tag and\n     * forces, all other members will be cleared or reset (in particular, the\n     * neighbor list and symmetry function data will be deleted).\n     */\n    void                     addAtom(Atom const&        atom,\n                                     std::string const& element);\n    /** Read configuration from file.\n     *\n     * @param[in] fileName Input file name.\n     *\n     * Reads the first configuration found in the input file.\n     */\n    void                     readFromFile(std::string const fileName\n                                                            = \"input.data\");\n    /** Read configuration from file.\n     *\n     * @param[in] file Input file stream (already opened).\n     *\n     * Expects that a file with configurations is open, first keyword on first\n     * line should be `begin`. Reads until keyword is `end`.\n     */\n    void                     readFromFile(std::ifstream& file);\n    /** Read configuration from lines.\n     *\n     * @param[in] lines One configuration in form of a vector of strings.\n     *\n     * Read the configuration from a vector of strings.\n     */\n    void                     readFromLines(std::vector<\n                                           std::string> const& lines);\n    /** Calculate maximal cut-off if cut-off of screening and real part Ewald\n     * summation are also considered.\n     *\n     * @param[in] ewaldSetup Settings of Ewald summation.\n     * @param[in] rcutScreen Cut-off for Screening of the electrostatic\n     *                         interaction.\n     * @param[in] maxCutoffRadius maximal cut-off of symmetry functions.\n     */\n    void                     calculateMaxCutoffRadiusOverall(\n                                            EwaldSetup& ewaldSetup,\n                                            double      rcutScreen,\n                                            double      maxCutoffRadius);\n    /** Calculate neighbor list for all atoms.\n     *\n     * @param[in] cutoffRadius Atoms are neighbors if there distance is smaller\n     *                         than the cutoff radius.\n     * @param[in] sortByDistance Sort neighborlist from nearest to farthest neighbor.\n     *\n     */\n    void                     calculateNeighborList(\n                                 double  cutoffRadius,\n                                 bool    sortByDistance = false);\n    /** Calculate neighbor list for all atoms and setup neighbor cut-off map.\n     *\n     * @param[in] cutoffRadius Atoms are neighbors if there distance is smaller\n     *                         than the cutoff radius.\n     * @param[in] cutoffs Vector of all needed cutoffs (needed for cut-off map\n     *                         construction).\n     * @return Maximum of {maxCutoffRadius, rcutScreen, rCut}.\n     */\n    void                     calculateNeighborList(\n                                 double  cutoffRadius,\n                                 std::vector<\n                                 std::vector<double>>& cutoffs);\n    /** Sort all neighbor lists of this structure with respect to the distance.\n     */\n    void                     sortNeighborList();\n    /** Set up a neighbor cut-off map which gives the index (value) of the last needed\n     *  neighbor corresponding to a specific cut-off (key).\n     * @param[in] cutoffs Vector of all needed symmetry function cutoffs. Note\n     *                          that a local copy gets extended with\n     *                          maxCutoffRadiusOverall.\n     */\n    void                     setupNeighborCutoffMap(std::vector<\n                                                    std::vector<double>> cutoffs);\n    /** Calculate required PBC copies.\n     *\n     * @param[in] cutoffRadius Cutoff radius for neighbor list.\n     * @param[in] pbc Array for storing the result.\n     *\n     * Called by #calculateNeighborList().\n     */\n    void                     calculatePbcCopies(double cutoffRadius, int (&pbc)[3]);\n    /** Calculate inverse box.\n     *\n     * Simulation box looks like this:\n     *\n     * @f[\n     * h =\n     * \\begin{pmatrix}\n     * \\phantom{a_x} & \\phantom{b_x} & \\phantom{c_x} \\\\\n     * \\vec{\\mathbf{a}} & \\vec{\\mathbf{b}} & \\vec{\\mathbf{c}} \\\\\n     * \\phantom{a_z} & \\phantom{b_z} & \\phantom{c_z} \\\\\n     * \\end{pmatrix} =\n     * \\begin{pmatrix}\n     * a_x & b_x & c_x \\\\\n     * a_y & b_y & c_y \\\\\n     * a_z & b_z & c_z \\\\\n     * \\end{pmatrix},\n     * @f]\n     *\n     * where @f$\\vec{\\mathbf{a}} = @f$ `box[0]`, @f$\\vec{\\mathbf{b}} = @f$\n     * `box[1]` and @f$\\vec{\\mathbf{c}} = @f$ `box[2]`. Thus, indices are\n     * column first, row second:\n     *\n     * @f[\n     * h =\n     * \\begin{pmatrix}\n     * \\texttt{box[0][0]} & \\texttt{box[1][0]} & \\texttt{box[2][0]} \\\\\n     * \\texttt{box[0][1]} & \\texttt{box[1][1]} & \\texttt{box[2][1]} \\\\\n     * \\texttt{box[0][2]} & \\texttt{box[1][2]} & \\texttt{box[2][2]} \\\\\n     * \\end{pmatrix}.\n     * @f]\n     *\n     * The inverse box matrix (same scheme as above but with `invbox`) can be\n     * used to calculate fractional coordinates:\n     *\n     * @f[\n     * \\begin{pmatrix}\n     * f_0 \\\\ f_1 \\\\ f_2\n     * \\end{pmatrix} = h^{-1} \\; \\vec{\\mathbf{r}}.\n     * @f]\n     */\n    void                     calculateInverseBox();\n    /** Check if cut-off radius is small enough to apply minimum image\n    * convention.\n    *\n    * @param[in] cutoffRadius cut-off radius for which condition should be\n    * checked.\n    */\n    bool                     canMinimumImageConventionBeApplied(double cutoffRadius);\n    /** Calculate distance between two atoms in the minimum image convention.\n     *\n     * @param[in] dr Distance vector between two atoms of the same box.\n     *\n     */\n    Vec3D                    applyMinimumImageConvention(Vec3D const& dr);\n    /** Calculate volume from box vectors.\n     */\n    void                     calculateVolume();\n    /** Compute electrostatic energy with global charge equilibration.\n     *\n     * @param[in] ewaldSetup Settings of Ewald summation.\n     * @param[in] hardness Vector containing the hardness of all elements.\n     * @param[in] gammaSqrt2 Matrix combining gamma with prefactor.\n     *                  @f$ \\text{gammaSqrt2}_{ij} = \\sqrt{2} \\gamma_{ij} \n     *                          = \\sqrt{2} \\sqrt{(\\sigma_i^2 + \\sigma_j^2)} @f$\n     * @param[in] sigmaSqrtPi Vector combining sigma with prefactor,\n     *                  @f$ \\text{sigmaSqrtPi}_i = \\sqrt{\\pi} \\sigma_i @f$\n     * @param[in] fs Screening function.\n     * @param[in] fourPiEps @f$ \\text{fourPiEps} = 4 \\pi \\varepsilon_0 @f$.\n     *                  Value depends on unit system (e.g. normalization).\n     * @param[in] erfcBuf helper object to avoid repeated calculation of erfc().\n     */\n    double                   calculateElectrostaticEnergy(\n                                            EwaldSetup&              ewaldSetup,\n                                            Eigen::VectorXd          hardness,\n                                            Eigen::MatrixXd          gammaSqrt2,\n                                            Eigen::VectorXd          sigmaSqrtPi,\n                                            ScreeningFunction const& fs,\n                                            double const             fourPiEps,\n                                            ErfcBuf&                 erfcBuf);\n    /** Calculate screening energy which needs to be added (!) to the\n     * electrostatic energy in order to remove contributions in the short range\n     * domain.\n     * @param[in] gammaSqrt2 Matrix combining gamma with prefactor.\n     *                  @f$ \\text{gammaSqrt2}_{ij} = \\sqrt{2} \\gamma_{ij}\n     *                          = \\sqrt{2} \\sqrt{(\\sigma_i^2 + \\sigma_j^2)} @f$\n     * @param[in] sigmaSqrtPi Vector combining sigma with prefactor,\n     *                  @f$ \\text{sigmaSqrtPi}_i = \\sqrt{\\pi} \\sigma_i @f$\n     *\n     * @param[in] fs Screening function.\n     * @param[in] fourPiEps @f$ \\text{fourPiEps} = 4 \\pi \\varepsilon_0 @f$.\n                            Value depends on unit system (e.g. normalization).\n     */\n    double                   calculateScreeningEnergy(  \n                                            Eigen::MatrixXd          gammaSqrt2,\n                                            Eigen::VectorXd          sigmaSqrtPi,\n                                            ScreeningFunction const& fs,\n                                            double const             fourPiEps);\n    /** Calculates derivative of A-matrix with respect to the atoms positions and\n     * contract it with Q. \n     * @param[in] ewaldSetup Settings of Ewald summation.\n     * @param[in] gammaSqrt2 Matrix combining gamma with prefactor.\n     *                  @f$ \\text{gammaSqrt2}_{ij} = \\sqrt{2} \\gamma_{ij} \n     *                          = \\sqrt{2} \\sqrt{(\\sigma_i^2 + \\sigma_j^2)} @f$\n     * @param[in] fourPiEps @f$ \\text{fourPiEps} = 4 \\pi \\varepsilon_0 @f$.\n                            Value depends on unit system (e.g. normalization).\n     * @param[in] erfcBuf helper object to avoid repeated calculation of erfc().\n     */\n    void                     calculateDAdrQ(\n                                        EwaldSetup&     ewaldSetup,\n                                        Eigen::MatrixXd gammaSqrt2,\n                                        double const    fourPiEps,\n                                        ErfcBuf&        erfcBuf);\n    /** Calculates derivative of the charges with respect to electronegativities.\n     *  @param[in] dQdChi vector to store the result. dQdChi[i](j) represents the\n     *  derivative for the i-th electronegativity and the j-th charge.\n     */\n    void                     calculateDQdChi(std::vector<Eigen::VectorXd> &dQdChi);\n    /** Calculates derivative of the charges with respect to atomic hardness.\n     *  @param[in] dQdJ vector to store the result. dQdJ[i](j) represents the\n     *  derivative for the i-th hardness and the j-th charge.\n     */\n    void                     calculateDQdJ(std::vector<Eigen::VectorXd> &dQdJ);\n    /** Calculates derivative of the charges with respect to the atom's\n     * position.\n     * @param[in] atomIndices Vector containing indices of atoms for which the\n     *                      derivative should be calculated.\n     * @param[in] compIndices Vector containing indices of vector components\n     *                        for which the derivative should be calculated.\n     * @param[in] maxCutoffRadius Max. cutoff radius of symmetry functions.\n     * @param[in] elements Vector containing all elements (needed for symmetry\n     *                     function table).\n     */\n    void                    calculateDQdr(\n                                std::vector<size_t> const&  atomsIndices,\n                                std::vector<size_t> const&  compIndices,\n                                double const                maxCutoffRadius,\n                                std::vector<Element> const& elements);\n     /** Calculates partial derivatives of electrostatic Energy with respect\n     * to atom's coordinates and charges.\n     * @param[in] hardness Vector containing the hardness of all elements.\n     * @param[in] gammaSqrt2 Matrix combining gamma with prefactor.\n     *                  @f$ \\text{gammaSqrt2}_{ij} = \\sqrt{2} \\gamma_{ij} \n     *                          = \\sqrt{2} \\sqrt{(\\sigma_i^2 + \\sigma_j^2)} @f$\n     * @param[in] sigmaSqrtPi Vector combining sigma with prefactor,\n     *                  @f$ \\text{sigmaSqrtPi}_i = \\sqrt{\\pi} \\sigma_i @f$\n     * @param[in] fs Screening function.\n     * @param[in] fourPiEps @f$ \\text{fourPiEps} = 4 \\pi \\varepsilon_0 @f$.\n                            Value depends on unit system (e.g. normalization).\n     */\n    void                     calculateElectrostaticEnergyDerivatives(\n                                        Eigen::VectorXd          hardness,\n                                        Eigen::MatrixXd          gammaSqrt2,\n                                        Eigen::VectorXd          sigmaSqrtPi,\n                                        ScreeningFunction const& fs,\n                                        double const             fourPiEps);\n    /** Calculate lambda_total vector which is needed for the total force\n     *  calculation in 4G NN.\n     */\n    Eigen::VectorXd const calculateForceLambdaTotal() const;\n    /** Calculate lambda_elec vector which is needed for the electrostatic\n     *  force calculation in 4G NN.\n     */\n    Eigen::VectorXd const calculateForceLambdaElec() const;\n    /** Translate all atoms back into box if outside.\n     */\n    void                     remap();\n    /** Translate atom back into box if outside.\n     *\n     * @param[in,out] atom Atom to be remapped.\n     */\n    void                     remap(Atom& atom);\n    /** Normalize structure, shift energy and change energy, length and charge\n     *  unit.\n     *\n     * @param[in] meanEnergy Mean energy per atom (in old units).\n     * @param[in] convEnergy Multiplicative energy unit conversion factor.\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     * @param[in] convCharge Multiplicative charge unit conversion factor.\n     */\n    void                     toNormalizedUnits(double meanEnergy,\n                                               double convEnergy,\n                                               double convLength,\n                                               double convCharge);\n    /** Switch to physical units, shift energy and change energy, length and\n     *  charge unit.\n     *\n     * @param[in] meanEnergy Mean energy per atom (in old units).\n     * @param[in] convEnergy Multiplicative energy unit conversion factor.\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     * @param[in] convCharge Multiplicative charge unit conversion factor.\n     */\n    void                     toPhysicalUnits(double meanEnergy,\n                                             double convEnergy,\n                                             double convLength,\n                                             double convCharge);\n    /** Find maximum number of neighbors.\n     *\n     * @return Maximum numbor of neighbors of all atoms in this structure.\n     */\n    std::size_t              getMaxNumNeighbors() const;\n    /** Free symmetry function memory for all atoms, see free() in Atom class.\n     *\n     * @param[in] all See description in Atom.\n     * @param[in] maxCutoffRadius Maximum cutoff radius of symmetry functions.\n     */\n    void                     freeAtoms(bool         all,\n                                       double const maxCutoffRadius = 0.0);\n    /** Reset everything but #elementMap.\n     */\n    void                     reset();\n    /** Clear neighbor list of all atoms.\n     */\n    void                     clearNeighborList();\n    /** Clear A-matrix, dAdrQ and optionally dQdr\n     * @param[in] clearDqdr Specify if dQdr should also be cleared.\n     */\n    void                     clearElectrostatics(bool clearDQdr = false);\n    /** Update property error metrics with this structure.\n     *\n     * @param[in] property One of \"energy\", \"force\" or \"charge\".\n     * @param[in,out] error Input error metric map to be updated.\n     * @param[in,out] count Input counter to be updated.\n     *\n     * The \"energy\" error metric map stores temporary sums for the following\n     * metrics:\n     *\n     * key \"RMSEpa\": RMSE of energy per atom\n     * key \"RMSE\"  : RMSE of energy\n     * key \"MAEpa\" : MAE  of energy per atom\n     * key \"MAE\"   : MAE  of energy\n     *\n     * The \"force\" error metric map stores temporary sums for the following\n     * metrics:\n     *\n     * key \"RMSE\"  : RMSE of forces\n     * key \"MAE\"   : MAE  of forces\n     *\n     * The \"charge\" error metric map stores temporary sums for the following\n     * metrics:\n     *\n     * key \"RMSE\"  : RMSE of charges\n     * key \"MAE\"   : MAE  of charges\n     */\n    void                     updateError(\n                                   std::string const&             property,\n                                   std::map<std::string, double>& error,\n                                   std::size_t&                   count) const;\n    /** Get reference and NN energy.\n     *\n     * @return String with #index, #energyRef and #energy values.\n     */\n    std::string              getEnergyLine() const;\n    /** Get reference and NN forces for all atoms.\n     *\n     * @return Vector of strings with force comparison.\n     */\n    std::vector<std::string> getForcesLines() const;\n    /** Get reference and NN charges for all atoms.\n     *\n     * @return Vector of strings with charge comparison.\n     */\n    std::vector<std::string> getChargesLines() const;\n    /** Write configuration to file.\n     *\n     * @param[in,out] fileName Ouptut file name.\n     * @param[in] ref If true, write reference energy and forces, if false,\n     *                write NNP results instead.\n     * @param[in] append If true, append to existing file.\n     */\n    void                     writeToFile(\n                                     std::string const fileName =\"output.data\",\n                                     bool const        ref = true,\n                                     bool const        append = false) const;\n    /** Write configuration to file.\n     *\n     * @param[in,out] file Ouptut file.\n     * @param[in] ref If true, write reference energy and forces, if false,\n     *                write NNP results instead.\n     */\n    void                     writeToFile(\n                                       std::ofstream* const& file,\n                                       bool const            ref = true) const;\n    /** Write configuration to xyz file.\n     *\n     * @param[in,out] file xyz output file.\n     */\n    void                     writeToFileXyz(std::ofstream* const& file) const;\n    /** Write configuration to POSCAR file.\n     *\n     * @param[in,out] file POSCAR output file.\n     *\n     * @warning Elements in POTCAR file must be ordered according to\n     *          periodic table.\n     */\n    void                     writeToFilePoscar(\n                                             std::ofstream* const& file) const;\n    /** Write configuration to POSCAR file.\n     *\n     * @param[in,out] file POSCAR output file.\n     * @param[in,out] elements User-defined order of elements, e.g. \"Zn O Cu\".\n     */\n    void                     writeToFilePoscar(\n                                         std::ofstream* const& file,\n                                         std::string const     elements) const;\n    /** Get structure information as a vector of strings.\n     *\n     * @return Lines with structure information.\n     */\n    std::vector<std::string> info() const;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFnc.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFnc.h\"\n#include \"utility.h\"\n#include <cstdlib>   // atof, atoi\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error, std::out_of_range\n\nusing namespace std;\nusing namespace nnp;\n\nsize_t const SymFnc::sfinfoWidth = 12;\n\nSymFnc::PrintFormat const SymFnc::printFormat = initializePrintFormat();\n\nSymFnc::PrintOrder const SymFnc::printOrder = initializePrintOrder();\n\nvector<string> SymFnc::parameterInfo() const\n{\n    vector<string> v;\n    string s;\n    size_t w = sfinfoWidth;\n\n    s = \"lineNumber\";\n    v.push_back(strpr((pad(s, w) + \"%zu\"   ).c_str(), lineNumber + 1));\n    s = \"index\";\n    v.push_back(strpr((pad(s, w) + \"%zu\"   ).c_str(), index + 1));\n    s = \"type\";\n    v.push_back(strpr((pad(s, w) + \"%zu\"   ).c_str(), type));\n    s = \"ec\";\n    v.push_back(strpr((pad(s, w) + \"%s\"    ).c_str(), elementMap[ec].c_str()));\n    s = \"rc\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), rc / convLength));\n\n    return v;\n}\n\nvoid SymFnc::setScalingType(ScalingType scalingType,\n                            string      statisticsLine,\n                            double      Smin,\n                            double      Smax)\n{\n    this->scalingType = scalingType;\n\n    vector<string> s = split(reduce(statisticsLine));\n    if (((size_t)atoi(s.at(0).c_str()) != ec + 1) &&\n        ((size_t)atoi(s.at(1).c_str()) != index + 1))\n    {\n        throw runtime_error(\"ERROR: Inconsistent scaling statistics.\\n\");\n    }\n    Gmin       = atof(s.at(2).c_str());\n    Gmax       = atof(s.at(3).c_str());\n    Gmean      = atof(s.at(4).c_str());\n    // Older versions may not supply sigma.\n    if (s.size() > 5)\n    {\n        Gsigma = atof(s.at(5).c_str());\n    }\n    this->Smin = Smin;\n    this->Smax = Smax;\n\n    if(scalingType == ST_NONE)\n    {\n        scalingFactor = 1.0;\n    }\n    else if (scalingType == ST_SCALE)\n    {\n        scalingFactor = (Smax - Smin) / (Gmax - Gmin);\n    }\n    else if (scalingType == ST_CENTER)\n    {\n        scalingFactor = 1.0;\n    }\n    else if (scalingType == ST_SCALECENTER)\n    {\n        scalingFactor = (Smax - Smin) / (Gmax - Gmin);\n    }\n    else if (scalingType == ST_SCALESIGMA)\n    {\n        scalingFactor = (Smax - Smin) / Gsigma;\n    }\n\n    return;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvector<string> SymFnc::getCacheIdentifiers() const\n{\n    return vector<string>();\n}\n\nvoid SymFnc::addCacheIndex(size_t element,\n                           size_t cacheIndex,\n                           string cacheIdentifier)\n{\n    // Check if provided cache identifier is identical to the originally\n    // supplied one.\n    vector<vector<string>> identifiersPerElement(elementMap.size());\n    for (string id : getCacheIdentifiers())\n    {\n        size_t ne = atoi(split(id)[0].c_str());\n        identifiersPerElement.at(ne).push_back(id);\n    }\n    size_t current = cacheIndices.at(element).size();\n    if (identifiersPerElement.at(element).at(current) != cacheIdentifier)\n    {\n        throw runtime_error(strpr(\"ERROR: Cache identifiers do no match:\\n\"\n                                  \"%s\\n\"\n                                  \"    !=\\n\"\n                                  \"%s\\n\",\n                                  identifiersPerElement.at(element)\n                                  .at(current).c_str(),\n                                  cacheIdentifier.c_str()));\n    }\n    cacheIndices.at(element).push_back(cacheIndex);\n\n    return;\n}\n#endif\n\nSymFnc::SymFnc(size_t type, ElementMap const& elementMap) :\n    type         (type      ),\n    elementMap   (elementMap),\n    index        (0         ),\n    ec           (0         ),\n    minNeighbors (0         ),\n    Smin         (0.0       ),\n    Smax         (0.0       ),\n    Gmin         (0.0       ),\n    Gmax         (0.0       ),\n    Gmean        (0.0       ),\n    Gsigma       (0.0       ),\n    rc           (0.0       ),\n    scalingFactor(1.0       ),\n    convLength   (1.0       ),\n    scalingType  (ST_NONE   )\n{\n    // Add standard parameter IDs to set.\n    parameters.insert(\"index\");\n    parameters.insert(\"ec\");\n    parameters.insert(\"type\");\n    parameters.insert(\"rc\");\n    parameters.insert(\"lineNumber\");\n\n    // Initialize per-element index vector, use max to indicate\n    // \"uninitialized\" state.\n    indexPerElement.resize(elementMap.size(), numeric_limits<size_t>::max());\n\n#ifndef N2P2_NO_SF_CACHE\n    // Initialize cache indices vector.\n    cacheIndices.resize(elementMap.size(), vector<size_t>());\n#endif\n}\n\ndouble SymFnc::scale(double value) const\n{\n    if (scalingType == ST_NONE)\n    {\n        return value;\n    }\n    else if (scalingType == ST_SCALE)\n    {\n        return Smin + scalingFactor * (value - Gmin);\n    }\n    else if (scalingType == ST_CENTER)\n    {\n        return value - Gmean;\n    }\n    else if (scalingType == ST_SCALECENTER)\n    {\n        return Smin + scalingFactor * (value - Gmean);\n    }\n    else if (scalingType == ST_SCALESIGMA)\n    {\n        return Smin + scalingFactor * (value - Gmean);\n    }\n    else\n    {\n        return 0.0;\n    }\n}\n\ndouble SymFnc::unscale(double value) const\n{\n    if (scalingType == ST_NONE)\n    {\n        return value;\n    }\n    else if (scalingType == ST_SCALE)\n    {\n        return (value - Smin) / scalingFactor + Gmin;\n    }\n    else if (scalingType == ST_CENTER)\n    {\n        return value + Gmean;\n    }\n    else if (scalingType == ST_SCALECENTER)\n    {\n        return (value - Smin) / scalingFactor + Gmean;\n    }\n    else if (scalingType == ST_SCALESIGMA)\n    {\n        return (value - Smin) / scalingFactor + Gmean;\n    }\n    else\n    {\n        return 0.0;\n    }\n}\n\nstring SymFnc::scalingLine() const\n{\n    return strpr(\"%4zu %9.2E %9.2E %9.2E %9.2E %9.2E %5.2f %5.2f %d\\n\",\n                 index + 1,\n                 Gmin,\n                 Gmax,\n                 Gmean,\n                 Gsigma,\n                 scalingFactor,\n                 Smin,\n                 Smax,\n                 scalingType);\n}\n\nSymFnc::PrintFormat const SymFnc::initializePrintFormat()\n{\n    PrintFormat pf;\n\n    pf[\"index\"]       = make_pair(\"%4zu\"  , string(4,  ' '));\n    pf[\"ec\"]          = make_pair(\"%2s\"   , string(2,  ' '));\n    pf[\"type\"]        = make_pair(\"%2zu\"  , string(2,  ' '));\n    pf[\"subtype\"]     = make_pair(\"%4s\"   , string(4,  ' '));\n    pf[\"e1\"]          = make_pair(\"%2s\"   , string(2,  ' '));\n    pf[\"e2\"]          = make_pair(\"%2s\"   , string(2,  ' '));\n    pf[\"eta\"]         = make_pair(\"%9.3E\" , string(9,  ' '));\n    pf[\"rs/rl\"]       = make_pair(\"%10.3E\", string(10, ' '));\n    pf[\"rc\"]          = make_pair(\"%10.3E\", string(10, ' '));\n    pf[\"angleLeft\"]   = make_pair(\"%6.1f\" , string(6,  ' '));\n    pf[\"angleRight\"]  = make_pair(\"%6.1f\" , string(6,  ' '));\n    pf[\"lambda\"]      = make_pair(\"%2.0f\" , string(2,  ' '));\n    pf[\"zeta\"]        = make_pair(\"%4.1f\" , string(4,  ' '));\n    pf[\"alpha\"]       = make_pair(\"%4.2f\" , string(4,  ' '));\n    pf[\"lineNumber\"]  = make_pair(\"%5zu\"  , string(5,  ' '));\n\n    return pf;\n}\n\nSymFnc::PrintOrder const SymFnc::initializePrintOrder()\n{\n    vector<string> po;\n\n    po.push_back(\"index\"     );\n    po.push_back(\"ec\"        );\n    po.push_back(\"type\"      );\n    po.push_back(\"subtype\"   );\n    po.push_back(\"e1\"        );\n    po.push_back(\"e2\"        );\n    po.push_back(\"eta\"       );\n    po.push_back(\"rs/rl\"     );\n    po.push_back(\"rc\"        );\n    po.push_back(\"angleLeft\" );\n    po.push_back(\"angleRight\");\n    po.push_back(\"lambda\"    );\n    po.push_back(\"zeta\"      );\n    po.push_back(\"alpha\"     );\n    po.push_back(\"lineNumber\");\n\n    return po;\n}\n\nstring SymFnc::getPrintFormat() const\n{\n    string s;\n\n    for (PrintOrder::const_iterator it = printOrder.begin();\n         it != printOrder.end(); ++it)\n    {\n        // If parameter is present add format string.\n        if (parameters.find(*it) != parameters.end())\n        {\n            s += safeFind(printFormat, (*it)).first + ' ';\n        }\n        // Else add just enough empty spaces.\n        else \n        {\n            s += safeFind(printFormat, (*it)).second + ' ';\n        }\n    }\n    // Remove extra space at the end.\n    if (s.size () > 0)  s.resize (s.size () - 1);\n    s += '\\n';\n\n    return s;\n}\n\n"
  },
  {
    "path": "src/libnnp/SymFnc.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNC_H\n#define SYMFNC_H\n\n#include \"ElementMap.h\"\n#include <cstddef> // std::size_t\n#include <map>     // std::map\n#include <set>     // std::set\n#include <string>  // std::string\n#include <utility> // std::pair\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass SymFncStatistics;\n\n/** Symmetry function base class.\n *\n * Actual symmetry functions derive from this class. Provides common\n * functionality, e.g. scaling behavior.\n */\nclass SymFnc\n{\npublic:\n    /// List of available scaling types.\n    enum ScalingType\n    {\n        /** @f$G_\\text{scaled} = G@f$\n         */\n        ST_NONE,\n        /** @f$G_\\text{scaled} = S_\\text{min} + \\left(S_\\text{max} -\n         * S_\\text{min}\\right) \\cdot \\frac{G - G_\\text{min}}\n         * {G_\\text{max} - G_\\text{min}} @f$\n         */\n        ST_SCALE,\n        /** @f$G_\\text{scaled} = G - \\left<G\\right>@f$\n         */\n        ST_CENTER,\n        /** @f$G_\\text{scaled} = S_\\text{min} + \\left(S_\\text{max} -\n         * S_\\text{min}\\right) \\cdot \\frac{G - \\left<G\\right>}\n         * {G_\\text{max} - G_\\text{min}} @f$\n         */\n        ST_SCALECENTER,\n        /** @f$G_\\text{scaled} = S_\\text{min} + \\left(S_\\text{max} -\n         * S_\\text{min}\\right) \\cdot \\frac{G - \\left<G\\right>}{\\sigma_G} @f$\n         */\n        ST_SCALESIGMA\n    };\n\n    /** Virtual destructor\n     */\n    virtual             ~SymFnc() {};\n    /** Overload == operator.\n     */\n    virtual bool        operator==(SymFnc const& rhs) const = 0;\n    /** Overload < operator.\n     */\n    virtual bool        operator<(SymFnc const& rhs) const = 0;\n    /** Overload != operator.\n     */\n    bool                operator!=(SymFnc const& rhs) const;\n    /** Overload > operator.\n     */\n    bool                operator>(SymFnc const& rhs) const;\n    /** Overload <= operator.\n     */\n    bool                operator<=(SymFnc const& rhs) const;\n    /** Overload >= operator.\n     */\n    bool                operator>=(SymFnc const& rhs) const;\n    /** Set parameters.\n     *\n     * @param[in] parameterString String containing all parameters for this\n     *                            symmetry function.\n     */\n    virtual void        setParameters(std::string const& parameterString) = 0;\n    /** Change length unit.\n     *\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     *\n     * @note This will permanently change all symmetry function parameters with\n     * dimension length. For convenience, some member functions for printing\n     * (getSettingsLine(), parameterLine(), calculateRadialPart() and\n     * calculateAngularPart()) will temporarily undo this change. In contrast,\n     * the member getter functions, e.g. getRc(), will return the internally\n     * stored values.\n     */\n    virtual void        changeLengthUnit(double convLength) = 0;\n    /** Get settings file line from currently set parameters.\n     *\n     * @return Settings file string (\"symfunction_short ...\").\n     */\n    virtual std::string getSettingsLine() const = 0;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void        calculate(Atom&      atom,\n                                  bool const derivatives) const = 0;\n    /** Give symmetry function parameters in one line.\n     *\n     * @return String containing symmetry function parameter values.\n     */\n    virtual std::string parameterLine() const = 0;\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual std::vector<std::string>\n                        parameterInfo() const;\n    /** Set symmetry function scaling type.\n     *\n     * @param[in] scalingType Desired symmetry function scaling type.\n     * @param[in] statisticsLine String containing symmetry function statistics\n     *                           (\"min max mean sigma\").\n     * @param[in] Smin Minimum for scaling range @f$S_\\text{min}@f$.\n     * @param[in] Smax Maximum for scaling range @f$S_\\text{max}@f$.\n     */\n    void                setScalingType(ScalingType scalingType,\n                                       std::string statisticsLine,\n                                       double      Smin,\n                                       double      Smax);\n    /** Apply symmetry function scaling and/or centering.\n     *\n     * @param[in] value Raw symmetry function value.\n     * @return Scaled symmetry function value.\n     */\n    double              scale(double value) const;\n    /** Undo symmetry function scaling and/or centering.\n     *\n     * @param[in] value Scaled symmetry function value.\n     * @return Raw symmetry function value.\n     */\n    double              unscale(double value) const;\n    /** Get private #type member variable.\n     */\n    std::size_t         getType() const;\n    /** Get private #index member variable.\n     */\n    std::size_t         getIndex() const;\n    /** Get private #lineNumber member variable.\n     */\n    std::size_t         getLineNumber() const;\n    /** Get private #ec member variable.\n     */\n    std::size_t         getEc() const;\n    /** Get private #minNeighbors member variable.\n     */\n    std::size_t         getMinNeighbors() const;\n    /** Get private #rc member variable.\n     */\n    double              getRc() const;\n    /** Get private #Gmin member variable.\n     */\n    double              getGmin() const;\n    /** Get private #Gmax member variable.\n     */\n    double              getGmax() const;\n    /** Get private #scalingFactor member variable.\n     */\n    double              getScalingFactor() const;\n    /** Get private #convLength member variable.\n     */\n    double              getConvLength() const;\n    /** Get private #parameters member variable.\n     */\n    std::set<\n    std::string>        getParameters() const;\n    /** Get private #indexPerElement member variable.\n     */\n    std::vector<\n    std::size_t>        getIndexPerElement() const;\n    /** Set private #index member variable.\n     *\n     * @param[in] index Symmetry function index.\n     */\n    void                setIndex(std::size_t index);\n    /** Set private #indexPerElement member variable.\n     *\n     * @param[in] elementIndex Element index.\n     * @param[in] index Symmetry function index.\n     */\n    void                setIndexPerElement(std::size_t elementIndex,\n                                           std::size_t index);\n    /** Set line number.\n     *\n     * @param[in] lineNumber Line number in settings file.\n     */\n    void                setLineNumber(std::size_t lineNumber);\n    /** Get string with scaling information.\n     *\n     * @return Scaling information string.\n     */\n    std::string         scalingLine() const;\n    /** Calculate (partial) symmetry function value for one given distance.\n     *\n     * @param[in] distance Distance between two atoms.\n     * @return Symmetry function value.\n     *\n     * @note This function is not used for actual calculations but only for\n     * plotting symmetry functions. Derived classes should implement a\n     * meaningful symmetry function value for visualization.\n     */\n    virtual double      calculateRadialPart(double distance) const = 0;\n    /** Calculate (partial) symmetry function value for one given angle.\n     *\n     * @param[in] angle Angle between triplet of atoms (in radians).\n     * @return Symmetry function value.\n     *\n     * @note This function is not used for actual calculations but only for\n     * plotting symmetry functions. Derived classes should implement a\n     * meaningful symmetry function value for visualization.\n     */\n    virtual double      calculateAngularPart(double angle) const = 0;\n    /** Check whether symmetry function is relevant for given element.\n     *\n     * @param[in] index Index of given element.\n     * @return True if symmetry function is sensitive to given element, false\n     *         otherwise.\n     */\n    virtual bool        checkRelevantElement(std::size_t index) const = 0;\n#ifndef N2P2_NO_SF_CACHE\n    /** Get unique cache identifiers.\n     *\n     * @return Vector of string identifying the type of cache this symmetry\n     *         function requires.\n     */\n    virtual std::vector<\n    std::string>        getCacheIdentifiers() const;\n    /** Add one cache index for given neighbor element and check identifier.\n     *\n     * @param[in] element Index of neighbor atom element.\n     * @param[in] cacheIndex Cache index in Atom::Neighbor.\n     * @param[in] cacheIdentifier Cache identifier for checking.\n     */\n    void                addCacheIndex(std::size_t element,\n                                      std::size_t cacheIndex,\n                                      std::string cacheIdentifier);\n    /// Getter for #cacheIndices.\n    std::vector<std::vector<\n    std::size_t>>       getCacheIndices() const;\n#endif\n\nprotected:\n    typedef std::map<std::string,\n                     std::pair<std::string, std::string> > PrintFormat;\n    typedef std::vector<std::string>                       PrintOrder;\n    /// Symmetry function type.\n    std::size_t                type;\n    /// Copy of element map.\n    ElementMap                 elementMap;\n    /// Symmetry function index (per element).\n    std::size_t                index;\n    /// Line number.\n    std::size_t                lineNumber;\n    /// Element index of center atom.\n    std::size_t                ec;\n    /// Minimum number of neighbors required.\n    std::size_t                minNeighbors;\n    /// Minimum for scaling range.\n    double                     Smin;\n    /// Maximum for scaling range.\n    double                     Smax;\n    /// Minimum unscaled symmetry function value.\n    double                     Gmin;\n    /// Maximum unscaled symmetry function value.\n    double                     Gmax;\n    /// Mean unscaled symmetry function value.\n    double                     Gmean;\n    /// Sigma of unscaled symmetry function values.\n    double                     Gsigma;\n    /// Cutoff radius @f$r_c@f$.\n    double                     rc;\n    /// Scaling factor.\n    double                     scalingFactor;\n    /// Data set normalization length conversion factor.\n    double                     convLength;\n    /// Symmetry function scaling type used by this symmetry function.\n    ScalingType                scalingType;\n    /// Set with symmetry function parameter IDs (lookup for printing).\n    std::set<std::string>      parameters;\n    /// Per-element index for derivative memory in Atom::Neighbor::dGdr arrays.\n    std::vector<std::size_t>   indexPerElement;\n#ifndef N2P2_NO_SF_CACHE\n    /// Cache indices for each element.\n    std::vector<\n    std::vector<std::size_t>>  cacheIndices;\n#endif\n    /// Width of the SFINFO parameter description field (see #parameterInfo()).\n    static std::size_t const   sfinfoWidth;\n    /// Map of parameter format strings and empty strings.\n    static PrintFormat const   printFormat;\n    /// Vector of parameters in order of printing.\n    static PrintOrder const    printOrder;\n\n    /** Constructor, initializes #type.\n     */\n    SymFnc(std::size_t type, ElementMap const&);\n    /** Initialize static print format map for all possible parameters.\n     */\n    static PrintFormat const initializePrintFormat();\n    /** Initialize static print order vector for all possible parameters.\n     */\n    static PrintOrder const  initializePrintOrder();\n    /** Generate format string for symmetry function parameter printing.\n     *\n     * @return C-Style format string.\n     */\n    std::string              getPrintFormat() const;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline bool SymFnc::operator!=(SymFnc const& rhs) const\n{\n    return !((*this) == rhs);\n}\n\ninline bool SymFnc::operator>(SymFnc const& rhs) const\n{\n    return rhs < (*this);\n}\n\ninline bool SymFnc::operator<=(SymFnc const& rhs) const\n{\n    return !((*this) > rhs);\n}\n\ninline bool SymFnc::operator>=(SymFnc const& rhs) const\n{\n    return !((*this) < rhs);\n}\n\ninline std::size_t SymFnc::getType() const { return type; }\ninline std::size_t SymFnc::getEc() const { return ec; }\ninline std::size_t SymFnc::getIndex() const { return index; }\ninline std::size_t SymFnc::getLineNumber() const { return lineNumber; }\ninline std::size_t SymFnc::getMinNeighbors() const { return minNeighbors; }\ninline double SymFnc::getRc() const { return rc; }\ninline double SymFnc::getGmin() const { return Gmin; }\ninline double SymFnc::getGmax() const { return Gmax; }\ninline double SymFnc::getScalingFactor() const { return scalingFactor; }\ninline double SymFnc::getConvLength() const { return convLength; }\n\ninline void SymFnc::setIndex(std::size_t index)\n{\n    this->index = index;\n    return;\n}\n\ninline void SymFnc::setLineNumber(std::size_t lineNumber)\n{\n    this->lineNumber = lineNumber;\n    return;\n}\n\ninline std::set<std::string> SymFnc::getParameters() const\n{\n    return parameters;\n}\n\ninline std::vector<std::size_t> SymFnc::getIndexPerElement() const\n{\n    return indexPerElement;\n}\n\ninline void SymFnc::setIndexPerElement(std::size_t elementIndex,\n                                       std::size_t index)\n{\n    indexPerElement.at(elementIndex) = index;\n    return;\n}\n\n#ifndef N2P2_NO_SF_CACHE\ninline std::vector<std::vector<std::size_t>> SymFnc::getCacheIndices() const\n{\n    return cacheIndices;\n}\n#endif\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncBaseComp.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncBaseComp.h\"\n#include \"utility.h\"\n#include <string>\n\nusing namespace std;\nusing namespace nnp;\n\nvector<string> SymFncBaseComp::parameterInfo() const\n{\n    vector<string> v = SymFnc::parameterInfo();\n    string s;\n    size_t w = sfinfoWidth;\n\n    s = \"subtype\";\n    v.push_back(strpr((pad(s, w) + \"%s\"    ).c_str(), subtype.c_str()));\n    s = \"rl\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), rl / convLength));\n\n    return v;\n}\n\nvoid SymFncBaseComp::setCompactFunction(string subtype)\n{\n    if (subtype.size() < 1 || subtype.size() > 3)\n    {\n        throw runtime_error(strpr(\"ERROR: Invalid compact function type \"\n                                  \"specification: \\\"%s\\\".\\n\",\n                                  subtype.c_str()));\n    }\n\n    using CFT = CoreFunction::Type;\n    // Check for polynomials.\n    if (subtype.front() == 'p')\n    {\n        if      (subtype.at(1) == '1') cr.setCoreFunction(CFT::POLY1);\n        else if (subtype.at(1) == '2') cr.setCoreFunction(CFT::POLY2);\n        else if (subtype.at(1) == '3') cr.setCoreFunction(CFT::POLY3);\n        else if (subtype.at(1) == '4') cr.setCoreFunction(CFT::POLY4);\n        else\n        {\n            throw runtime_error(strpr(\"ERROR: Invalid polynom type: \\\"%s\\\".\\n\",\n                                      subtype.c_str()));\n        }\n        if (subtype.size() == 3)\n        {\n            if (subtype.at(2) == 'a')\n            {\n#ifndef N2P2_NO_ASYM_POLY\n                asymmetric = true;\n                cr.setAsymmetric(true);\n#else\n                throw runtime_error(\"ERROR: Compiled without support for \"\n                                    \"asymmetric polynomial symmetry functions \"\n                                    \"(-DN2P2_NO_ASYM_POLY).\\n\");\n#endif\n            }\n            else\n            {\n                throw runtime_error(strpr(\"ERROR: Invalid polynom specifier: \"\n                                          \"\\\"%s\\\".\\n\", subtype.c_str()));\n            }\n        }\n    }\n    else if (subtype.front() == 'e')\n    {\n        cr.setCoreFunction(CFT::EXP);\n    }\n    else\n    {\n        throw runtime_error(strpr(\"ERROR: Unknown compact SF type: \\\"%s\\\".\\n\",\n                                  subtype.c_str()));\n    }\n\n    return;\n}\n\nSymFncBaseComp::SymFncBaseComp(size_t type,\n                               ElementMap const& elementMap) :\n    SymFnc(type, elementMap),\n    asymmetric(false),\n    rl        (0.0  ),\n    subtype   (\"\"   )\n{\n    // Add compact-related parameter IDs to set.\n    parameters.insert(\"rs/rl\");\n    parameters.insert(\"subtype\");\n}\n"
  },
  {
    "path": "src/libnnp/SymFncBaseComp.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCBASECOMP_H\n#define SYMFNCBASECOMP_H\n\n#include \"SymFnc.h\"\n#include \"CompactFunction.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/// Symmetry function base class for SFs with compact support.\nclass SymFncBaseComp : public SymFnc\n{\npublic:\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual\n    std::vector<std::string> parameterInfo() const;\n    /** Set radial compact function.\n     *\n     * @param[in] subtype Core function specification.\n     *\n     * The subtype argument determines which CoreFunction::Type is used to\n     * generate the CompactFunction used by symmetry functions. The following\n     * strings are accepted (without the apostrophes):\n     * - \"e\": CoreFunction::Type::EXP\n     * - \"pN\", where \"N\" is one of \"1,2,3,4\", corresponding to the\n     *    polynomial CoreFunction::Type POLYN, respectively. \"pN\" can\n     *    be followed by the letter \"a\", which will enable the asymmetric\n     *    version of the compact function, i.e. @f$2x - x^2@f$ is used as\n     *    argument. Examples: \"p2\", \"p3a\", \"p4\".\n     */\n    void                     setCompactFunction(std::string subtype);\n    /** Get private #subtype member variable.\n     */\n    std::string              getSubtype() const;\n    /** Get private #rl member variable.\n     */\n    double                   getRl() const;\n\nprotected:\n    /// If asymmetric version of polynomials should be used.\n    bool            asymmetric;\n    /// Lower bound of compact function, @f$r_{l}@f$.\n    double          rl;\n    /// Subtype string (specifies e.g. polynom type).\n    std::string     subtype;\n    /// Compact function for radial part.\n    CompactFunction cr;\n\n    /** Constructor, initializes #type.\n     */\n    SymFncBaseComp(std::size_t type, ElementMap const&);\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline std::string SymFncBaseComp::getSubtype() const { return subtype; }\ninline double SymFncBaseComp::getRl() const { return rl; }\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncBaseCompAng.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncBaseCompAng.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp, pow, cos\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncBaseCompAng::\nSymFncBaseCompAng(size_t type, ElementMap const& elementMap) :\n    SymFncBaseComp(type, elementMap),\n    e1               (0  ),\n    e2               (0  ),\n    angleLeft        (0.0),\n    angleRight       (0.0),\n    angleLeftRadians (0.0),\n    angleRightRadians(0.0)\n{\n    minNeighbors = 2;\n    parameters.insert(\"e1\");\n    parameters.insert(\"e2\");\n    parameters.insert(\"angleLeft\");\n    parameters.insert(\"angleRight\");\n}\n\nvoid SymFncBaseCompAng::setParameters(string const& parameterString)\n{\n    vector<string> splitLine = split(reduce(parameterString));\n\n    if (type != (size_t)atoi(splitLine.at(1).c_str()))\n    {\n        throw runtime_error(\"ERROR: Incorrect symmetry function type.\\n\");\n    }\n\n    ec         = elementMap[splitLine.at(0)];\n    e1         = elementMap[splitLine.at(2)];\n    e2         = elementMap[splitLine.at(3)];\n    rl         = atof(splitLine.at(4).c_str());\n    rc         = atof(splitLine.at(5).c_str());\n    angleLeft  = atof(splitLine.at(6).c_str());\n    angleRight = atof(splitLine.at(7).c_str());\n    subtype    = splitLine.at(8);\n\n    if (e1 > e2)\n    {\n        size_t tmp = e1;\n        e1         = e2;\n        e2         = tmp;\n    }\n\n    // Radial part.\n    if (rl > rc)\n    {\n        throw runtime_error(\"ERROR: Lower radial boundary >= upper \"\n                            \"radial boundary.\\n\");\n    }\n    //if (rl < 0.0 && abs(rl + rc) > numeric_limits<double>::epsilon())\n    //{\n    //    throw runtime_error(\"ERROR: Radial function not symmetric \"\n    //                        \"w.r.t. origin.\\n\");\n    //}\n   \n    setCompactFunction(subtype);\n    cr.setLeftRight(rl,rc);\n\n    // Angular part.\n    if (angleLeft >= angleRight)\n    {\n        throw runtime_error(\"ERROR: Left angle boundary right of or equal to \"\n                            \"right angle boundary.\\n\");\n    }\n\n    double const center = (angleLeft + angleRight) / 2.0;\n    if ( (angleLeft  <   0.0 && center != 0.0) ||\n         (angleRight > 180.0 && center != 180.0) )\n    {\n        throw runtime_error(\"ERROR: Angle boundary out of [0,180] and \"\n                            \"center of angular function /= 0 or /= 180.\\n\");\n    }\n    if (angleRight - angleLeft > 360.0)\n    {\n        throw runtime_error(\"ERROR: Periodic symmetry function cannot spread \"\n                            \"over domain > 360 degrees\\n\");\n    }\n\n    ca.setCoreFunction(cr.getCoreFunctionType());\n    angleLeftRadians = angleLeft * M_PI / 180.0;\n    angleRightRadians = angleRight * M_PI / 180.0;\n    ca.setLeftRight(angleLeftRadians, angleRightRadians);\n\n    return;\n}\n\nvoid SymFncBaseCompAng::changeLengthUnit(double convLength)\n{\n    this->convLength = convLength;\n    rc *= convLength;\n    rl *= convLength;\n\n    cr.setLeftRight(rl,rc);\n\n    return;\n}\n\nstring SymFncBaseCompAng::getSettingsLine() const\n{\n    string s = strpr(\"symfunction_short %2s %2zu %2s %2s %16.8E %16.8E \"\n                     \"%16.8E %16.8E %s\\n\",\n                     elementMap[ec].c_str(),\n                     type,\n                     elementMap[e1].c_str(),\n                     elementMap[e2].c_str(),\n                     rl / convLength,\n                     rc / convLength,\n                     angleLeft,\n                     angleRight,\n                     subtype.c_str());\n\n    return s;\n}\n\nstring SymFncBaseCompAng::parameterLine() const\n{\n    return strpr(getPrintFormat().c_str(),\n                 index + 1,\n                 elementMap[ec].c_str(),\n                 type,\n                 subtype.c_str(),\n                 elementMap[e1].c_str(),\n                 elementMap[e2].c_str(),\n                 rl / convLength,\n                 rc / convLength,\n                 angleLeft,\n                 angleRight,\n                 lineNumber + 1);\n}\n\nvector<string> SymFncBaseCompAng::parameterInfo() const\n{\n    vector<string> v = SymFncBaseComp::parameterInfo();\n    string s;\n    size_t w = sfinfoWidth;\n\n    s = \"e1\";\n    v.push_back(strpr((pad(s, w) + \"%s\"    ).c_str(), elementMap[e1].c_str()));\n    s = \"e2\";\n    v.push_back(strpr((pad(s, w) + \"%s\"    ).c_str(), elementMap[e2].c_str()));\n    s = \"angleLeft\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), angleLeft));\n    s = \"angleRight\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), angleRight));\n\n    return v;\n}\n\ndouble SymFncBaseCompAng::calculateRadialPart(double distance) const\n{\n    double const& r = distance * convLength;\n\n    return cr.f(r);\n}\n\ndouble SymFncBaseCompAng::calculateAngularPart(double angle) const\n{\n    return ca.f(angle);\n}\n\nbool SymFncBaseCompAng::checkRelevantElement(size_t index) const\n{\n    if (index == e1 || index == e2) return true;\n    else return false;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvector<string> SymFncBaseCompAng::getCacheIdentifiers() const\n{\n    vector<string> v;\n    string s(\"\");\n\n    s += subtype;\n    s += \" \";\n    s += strpr(\"rl = %16.8E\", rl / convLength);\n    s += \" \";\n    s += strpr(\"rc = %16.8E\", rc / convLength);\n\n    v.push_back(strpr(\"%zu f \", e1) + s);\n    v.push_back(strpr(\"%zu df \", e1) + s);\n    if (e1 != e2) v.push_back(strpr(\"%zu f \", e2) + s);\n    if (e1 != e2) v.push_back(strpr(\"%zu df \", e2) + s);\n\n    return v;\n}\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncBaseCompAng.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCBASECOMPANG_H\n#define SYMFNCBASECOMPANG_H\n\n#include \"SymFncBaseComp.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/// Intermediate symmetry function class for angular SFs with compact support.\nclass SymFncBaseCompAng : public SymFncBaseComp\n{\npublic:\n    /** Set symmetry function parameters.\n     *\n     * @param[in] parameterString String containing angular symmetry function\n     *                            parameters.\n     */\n    virtual void        setParameters(std::string const& parameterString);\n    /** Change length unit.\n     *\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     */\n    virtual void        changeLengthUnit(double convLength);\n    /** Get settings file line from currently set parameters.\n     *\n     * @return Settings file string (\"symfunction_short ...\").\n     */\n    virtual std::string getSettingsLine() const;\n    // Core fcts\n    void                getCompactAngle(double const x,\n                                        double&      fx,\n                                        double&      dfx) const;\n    void                getCompactRadial(double const x,\n                                         double&      fx,\n                                         double&      dfx) const;\n    /** Give symmetry function parameters in one line.\n     *\n     * @return String containing symmetry function parameter values.\n     */\n    virtual std::string parameterLine() const;\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual std::vector<\n    std::string>        parameterInfo() const;\n    /** Get private #e1 member variable.\n     */\n    std::size_t         getE1() const;\n    /** Get private #e2 member variable.\n     */\n    std::size_t         getE2() const;\n    /** Get private #angleLeft member variable.\n     */\n    double              getAngleLeft() const;\n    /** Get private #angleRight member variable.\n     */\n    double              getAngleRight() const;\n    /** Calculate (partial) symmetry function value for one given distance.\n     *\n     * @param[in] distance Distance between two atoms.\n     * @return @f$\\left(e^{-\\eta r^2} f_c(r)\\right)^2@f$\n     */\n    virtual double      calculateRadialPart(double distance) const;\n    /** Calculate (partial) symmetry function value for one given angle.\n     *\n     * @param[in] angle Angle between triplet of atoms (in radians).\n     * @return @f$1@f$\n     */\n    virtual double      calculateAngularPart(double angle) const;\n    /** Check whether symmetry function is relevant for given element.\n     *\n     * @param[in] index Index of given element.\n     * @return True if symmetry function is sensitive to given element, false\n     *         otherwise.\n     */\n    virtual bool        checkRelevantElement(std::size_t index) const;\n#ifndef N2P2_NO_SF_CACHE\n    /** Get unique cache identifiers.\n     *\n     * @return Vector of string identifying the type of cache this symmetry\n     *         function requires.\n     */\n    virtual std::vector<\n    std::string>        getCacheIdentifiers() const;\n#endif\n\nprotected:\n    /// Element index of neighbor atom 1.\n    std::size_t     e1;\n    /// Element index of neighbor atom 2.\n    std::size_t     e2;\n    /// Left angle boundary.\n    double          angleLeft;\n    /// Right angle boundary.\n    double          angleRight;\n    /// Left angle boundary in radians.\n    double          angleLeftRadians;\n    /// Right angle boundary in radians.\n    double          angleRightRadians;\n    /// Compact function member for angular part.\n    CompactFunction ca;\n\n    /** Constructor, initializes #type.\n     */\n    SymFncBaseCompAng(std::size_t type, ElementMap const&);\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline std::size_t SymFncBaseCompAng::getE1() const { return e1; }\ninline std::size_t SymFncBaseCompAng::getE2() const { return e2; }\ninline double SymFncBaseCompAng::getAngleLeft() const { return angleLeft; }\ninline double SymFncBaseCompAng::getAngleRight() const { return angleRight; }\n\ninline void SymFncBaseCompAng::getCompactAngle(double const x,\n                                               double&      fx,\n                                               double&      dfx) const\n{\n    ca.fdf(x, fx, dfx);\n    return;\n}\n\ninline void SymFncBaseCompAng::getCompactRadial(double const x,\n                                                double&      fx,\n                                                double&      dfx) const\n{\n    cr.fdf(x, fx, dfx);\n    return;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncBaseCompAngWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncBaseCompAngWeighted.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp, pow, cos\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncBaseCompAngWeighted::\nSymFncBaseCompAngWeighted(size_t type, ElementMap const& elementMap) :\n    SymFncBaseComp(type, elementMap),\n    angleLeft        (0.0),\n    angleRight       (0.0),\n    angleLeftRadians (0.0),\n    angleRightRadians(0.0)\n{\n    minNeighbors = 2;\n    parameters.insert(\"angleLeft\");\n    parameters.insert(\"angleRight\");\n}\n\nvoid SymFncBaseCompAngWeighted::setParameters(string const& parameterString)\n{\n    vector<string> splitLine = split(reduce(parameterString));\n\n    if (type != (size_t)atoi(splitLine.at(1).c_str()))\n    {\n        throw runtime_error(\"ERROR: Incorrect symmetry function type.\\n\");\n    }\n\n    ec         = elementMap[splitLine.at(0)];\n    rl         = atof(splitLine.at(2).c_str());\n    rc         = atof(splitLine.at(3).c_str());\n    angleLeft  = atof(splitLine.at(4).c_str());\n    angleRight = atof(splitLine.at(5).c_str());\n    subtype    = splitLine.at(6);\n\n    // Radial part.\n    if (rl > rc)\n    {\n        throw runtime_error(\"ERROR: Lower radial boundary >= upper \"\n                            \"radial boundary.\\n\");\n    }\n    //if (rl < 0.0 && abs(rl + rc) > numeric_limits<double>::epsilon())\n    //{\n    //    throw runtime_error(\"ERROR: Radial function not symmetric \"\n    //                        \"w.r.t. origin.\\n\");\n    //}\n   \n    setCompactFunction(subtype);\n    cr.setLeftRight(rl,rc);\n\n    // Angular part.\n    if (angleLeft >= angleRight)\n    {\n        throw runtime_error(\"ERROR: Left angle boundary right of or equal to \"\n                            \"right angle boundary.\\n\");\n    }\n\n    double const center = (angleLeft + angleRight) / 2.0;\n    if ( (angleLeft  <   0.0 && center != 0.0) ||\n         (angleRight > 180.0 && center != 180.0) )\n    {\n        throw runtime_error(\"ERROR: Angle boundary out of [0,180] and \"\n                            \"center of angular function /= 0 or /= 180.\\n\");\n    }\n    if (angleRight - angleLeft > 360.0)\n    {\n        throw runtime_error(\"ERROR: Periodic symmetry function cannot spread \"\n                            \"over domain > 360 degrees\\n\");\n    }\n\n    ca.setCoreFunction(cr.getCoreFunctionType());\n    angleLeftRadians = angleLeft * M_PI / 180.0;\n    angleRightRadians = angleRight * M_PI / 180.0;\n    ca.setLeftRight(angleLeftRadians, angleRightRadians);\n\n    return;\n}\n\nvoid SymFncBaseCompAngWeighted::changeLengthUnit(double convLength)\n{\n    this->convLength = convLength;\n    rc *= convLength;\n    rl *= convLength;\n\n    cr.setLeftRight(rl,rc);\n\n    return;\n}\n\nstring SymFncBaseCompAngWeighted::getSettingsLine() const\n{\n    string s = strpr(\"symfunction_short %2s %2zu %16.8E %16.8E \"\n                     \"%16.8E %16.8E %s\\n\",\n                     elementMap[ec].c_str(),\n                     type,\n                     rl / convLength,\n                     rc / convLength,\n                     angleLeft,\n                     angleRight,\n                     subtype.c_str());\n\n    return s;\n}\n\nstring SymFncBaseCompAngWeighted::parameterLine() const\n{\n    return strpr(getPrintFormat().c_str(),\n                 index + 1,\n                 elementMap[ec].c_str(),\n                 type,\n                 subtype.c_str(),\n                 rl / convLength,\n                 rc / convLength,\n                 angleLeft,\n                 angleRight,\n                 lineNumber + 1);\n}\n\nvector<string> SymFncBaseCompAngWeighted::parameterInfo() const\n{\n    vector<string> v = SymFncBaseComp::parameterInfo();\n    string s;\n    size_t w = sfinfoWidth;\n\n    s = \"angleLeft\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), angleLeft));\n    s = \"angleRight\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), angleRight));\n\n    return v;\n}\n\ndouble SymFncBaseCompAngWeighted::calculateRadialPart(double distance) const\n{\n    double const& r = distance * convLength;\n\n    return cr.f(r);\n}\n\ndouble SymFncBaseCompAngWeighted::calculateAngularPart(double angle) const\n{\n    return ca.f(angle);\n}\n\nbool SymFncBaseCompAngWeighted::checkRelevantElement(size_t /*index*/) const\n{\n    return true;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvector<string> SymFncBaseCompAngWeighted::getCacheIdentifiers() const\n{\n    vector<string> v;\n    string s(\"\");\n\n    s += subtype;\n    s += \" \";\n    s += strpr(\"rl = %16.8E\", rl / convLength);\n    s += \" \";\n    s += strpr(\"rc = %16.8E\", rc / convLength);\n\n    for (size_t i = 0; i < elementMap.size(); ++i)\n    {\n        v.push_back(strpr(\"%zu f \", i) + s);\n        v.push_back(strpr(\"%zu df \", i) + s);\n    }\n\n    return v;\n}\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncBaseCompAngWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCBASECOMPANGWEIGHTED_H\n#define SYMFNCBASECOMPANGWEIGHTED_H\n\n#include \"SymFncBaseComp.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/// Intermediate symmetry function class for weighted angular compact SFs.\nclass SymFncBaseCompAngWeighted : public SymFncBaseComp\n{\npublic:\n    /** Set symmetry function parameters.\n     *\n     * @param[in] parameterString String containing weighted angular symmetry\n     *                            function parameters.\n     */\n    virtual void        setParameters(std::string const& parameterString);\n    /** Change length unit.\n     *\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     */\n    virtual void        changeLengthUnit(double convLength);\n    /** Get settings file line from currently set parameters.\n     *\n     * @return Settings file string (\"symfunction_short ...\").\n     */\n    virtual std::string getSettingsLine() const;\n    // Core fcts\n    void                getCompactAngle(double const x,\n                                        double&      fx,\n                                        double&      dfx) const;\n    void                getCompactRadial(double const x,\n                                         double&      fx,\n                                         double&      dfx) const;\n    /** Give symmetry function parameters in one line.\n     *\n     * @return String containing symmetry function parameter values.\n     */\n    virtual std::string parameterLine() const;\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual std::vector<\n    std::string>        parameterInfo() const;\n    /** Get private #angleLeft member variable.\n     */\n    double              getAngleLeft() const;\n    /** Get private #angleRight member variable.\n     */\n    double              getAngleRight() const;\n    /** Calculate (partial) symmetry function value for one given distance.\n     *\n     * @param[in] distance Distance between two atoms.\n     * @return @f$\\left(e^{-\\eta r^2} f_c(r)\\right)^2@f$\n     */\n    virtual double      calculateRadialPart(double distance) const;\n    /** Calculate (partial) symmetry function value for one given angle.\n     *\n     * @param[in] angle Angle between triplet of atoms (in radians).\n     * @return @f$1@f$\n     */\n    virtual double      calculateAngularPart(double angle) const;\n    /** Check whether symmetry function is relevant for given element.\n     *\n     * @param[in] index Index of given element.\n     * @return True if symmetry function is sensitive to given element, false\n     *         otherwise.\n     */\n    virtual bool        checkRelevantElement(std::size_t index) const;\n#ifndef N2P2_NO_SF_CACHE\n    /** Get unique cache identifiers.\n     *\n     * @return Vector of string identifying the type of cache this symmetry\n     *         function requires.\n     */\n    virtual std::vector<\n    std::string>        getCacheIdentifiers() const;\n#endif\n\nprotected:\n    /// Left angle boundary.\n    double          angleLeft;\n    /// Right angle boundary.\n    double          angleRight;\n    /// Left angle boundary in radians.\n    double          angleLeftRadians;\n    /// Right angle boundary in radians.\n    double          angleRightRadians;\n    /// Compact function member for angular part.\n    CompactFunction ca;\n\n    /** Constructor, initializes #type.\n     */\n    SymFncBaseCompAngWeighted(std::size_t type, ElementMap const&);\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline double SymFncBaseCompAngWeighted::getAngleLeft() const\n{\n    return angleLeft;\n}\n\ninline double SymFncBaseCompAngWeighted::getAngleRight() const\n{\n    return angleRight;\n}\n\ninline void SymFncBaseCompAngWeighted::getCompactAngle(double const x,\n                                                       double&      fx,\n                                                       double&      dfx) const\n{\n    ca.fdf(x, fx, dfx);\n    return;\n}\n\ninline void SymFncBaseCompAngWeighted::getCompactRadial(double const x,\n                                                        double&      fx,\n                                                        double&      dfx) const\n{\n    cr.fdf(x, fx, dfx);\n    return;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncBaseCutoff.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncBaseCutoff.h\"\n#include \"utility.h\"\n#include <string>\n\nusing namespace std;\nusing namespace nnp;\n\nvector<string> SymFncBaseCutoff::parameterInfo() const\n{\n    vector<string> v = SymFnc::parameterInfo();\n    string s;\n    size_t w = sfinfoWidth;\n\n    s = \"subtype\";\n    v.push_back(strpr((pad(s, w) + \"%s\"    ).c_str(), subtype.c_str()));\n    s = \"alpha\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), cutoffAlpha));\n\n    return v;\n}\n\nvoid SymFncBaseCutoff::setCutoffFunction(\n                                        CutoffFunction::CutoffType cutoffType,\n                                        double                     cutoffAlpha)\n{\n    this->cutoffType = cutoffType;\n    this->cutoffAlpha = cutoffAlpha;\n    fc.setCutoffType(cutoffType);\n    fc.setCutoffParameter(cutoffAlpha);\n    this->subtype = string(\"ct\") + strpr(\"%d\", static_cast<int>(cutoffType));\n\n    return;\n}\n\nSymFncBaseCutoff::SymFncBaseCutoff(size_t type,\n                                     ElementMap const& elementMap) :\n    SymFnc(type, elementMap),\n    cutoffAlpha  (0.0                    ),\n    subtype      (\"ct0\"                  ),\n    cutoffType   (CutoffFunction::CT_HARD)\n{\n    // Add cutoff-related parameter IDs to set.\n    parameters.insert(\"subtype\");\n    parameters.insert(\"alpha\");\n}\n"
  },
  {
    "path": "src/libnnp/SymFncBaseCutoff.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCBASECUTOFF_H\n#define SYMFNCBASECUTOFF_H\n\n#include \"SymFnc.h\"\n#include \"CutoffFunction.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/// Intermediate class for SFs based on cutoff functions.\nclass SymFncBaseCutoff : public SymFnc\n{\npublic:\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual\n    std::vector<std::string> parameterInfo() const;\n    /** Set cutoff function type and parameter.\n     *\n     * @param[in] cutoffType Desired cutoff function for this symmetry\n     *                       function.\n     * @param[in] cutoffAlpha Cutoff function parameter @f$\\alpha@f$.\n     */\n    void                     setCutoffFunction(CutoffFunction::\n                                          CutoffType cutoffType,\n                                          double     cutoffAlpha);\n    /** Get private #cutoffAlpha member variable.\n     */\n    double                   getCutoffAlpha() const;\n    /** Get private #subtype member variable.\n     */\n    std::string              getSubtype() const;\n    /** Get private #cutoffType member variable.\n     */\n    CutoffFunction::\n    CutoffType               getCutoffType() const;\n\nprotected:\n    /// Cutoff parameter @f$\\alpha@f$.\n    double                     cutoffAlpha;\n    /// Subtype string (specifies cutoff type).\n    std::string                subtype;\n    /// Cutoff function used by this symmetry function.\n    CutoffFunction             fc;\n    /// Cutoff type used by this symmetry function.\n    CutoffFunction::CutoffType cutoffType;\n\n    /** Constructor, initializes #type.\n     */\n    SymFncBaseCutoff(std::size_t type, ElementMap const&);\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline double SymFncBaseCutoff::getCutoffAlpha() const { return cutoffAlpha; }\ninline std::string SymFncBaseCutoff::getSubtype() const { return subtype; } \n\ninline CutoffFunction::CutoffType SymFncBaseCutoff::getCutoffType() const\n{\n    return cutoffType;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncBaseExpAng.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncBaseExpAng.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp, pow, cos\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncBaseExpAng::SymFncBaseExpAng(size_t type, ElementMap const& elementMap) :\n    SymFncBaseCutoff(type, elementMap),\n    useIntegerPow(false),\n    e1           (0    ),\n    e2           (0    ),\n    zetaInt      (0    ),\n    lambda       (0.0  ),\n    eta          (0.0  ),\n    zeta         (0.0  ),\n    rs           (0.0  )\n{\n    minNeighbors = 2;\n    parameters.insert(\"e1\");\n    parameters.insert(\"e2\");\n    parameters.insert(\"eta\");\n    parameters.insert(\"zeta\");\n    parameters.insert(\"lambda\");\n    parameters.insert(\"rs/rl\");\n}\n\nvoid SymFncBaseExpAng::setParameters(string const& parameterString)\n{\n    vector<string> splitLine = split(reduce(parameterString));\n\n    if (type != (size_t)atoi(splitLine.at(1).c_str()))\n    {\n        throw runtime_error(\"ERROR: Incorrect symmetry function type.\\n\");\n    }\n\n    ec     = elementMap[splitLine.at(0)];\n    e1     = elementMap[splitLine.at(2)];\n    e2     = elementMap[splitLine.at(3)];\n    eta    = atof(splitLine.at(4).c_str());\n    lambda = atof(splitLine.at(5).c_str());\n    zeta   = atof(splitLine.at(6).c_str());\n    rc     = atof(splitLine.at(7).c_str());\n    // Shift parameter is optional.\n    if (splitLine.size() > 8)\n    {\n        rs = atof(splitLine.at(8).c_str());\n    }\n\n    fc.setCutoffRadius(rc);\n    fc.setCutoffParameter(cutoffAlpha);\n\n    if (e1 > e2)\n    {\n        size_t tmp = e1;\n        e1         = e2;\n        e2         = tmp;\n    }\n\n    zetaInt = round(zeta);\n    if (fabs(zeta - zetaInt) <= numeric_limits<double>::min())\n    {\n        useIntegerPow = true;\n    }\n    else\n    {\n        useIntegerPow = false;\n    }\n\n    return;\n}\n\nvoid SymFncBaseExpAng::changeLengthUnit(double convLength)\n{\n    this->convLength = convLength;\n    eta /= convLength * convLength;\n    rc *= convLength;\n    rs *= convLength;\n\n    fc.setCutoffRadius(rc);\n    fc.setCutoffParameter(cutoffAlpha);\n\n    return;\n}\n\nstring SymFncBaseExpAng::getSettingsLine() const\n{\n    string s = strpr(\"symfunction_short %2s %2zu %2s %2s %16.8E %16.8E \"\n                     \"%16.8E %16.8E %16.8E\\n\",\n                     elementMap[ec].c_str(),\n                     type,\n                     elementMap[e1].c_str(),\n                     elementMap[e2].c_str(),\n                     eta * convLength * convLength,\n                     lambda,\n                     zeta,\n                     rc / convLength,\n                     rs / convLength);\n\n    return s;\n}\n\nstring SymFncBaseExpAng::parameterLine() const\n{\n    return strpr(getPrintFormat().c_str(),\n                 index + 1,\n                 elementMap[ec].c_str(),\n                 type,\n                 subtype.c_str(),\n                 elementMap[e1].c_str(),\n                 elementMap[e2].c_str(),\n                 eta * convLength * convLength,\n                 rs / convLength,\n                 rc / convLength,\n                 lambda,\n                 zeta,\n                 cutoffAlpha,\n                 lineNumber + 1);\n}\n\nvector<string> SymFncBaseExpAng::parameterInfo() const\n{\n    vector<string> v = SymFncBaseCutoff::parameterInfo();\n    string s;\n    size_t w = sfinfoWidth;\n\n    s = \"e1\";\n    v.push_back(strpr((pad(s, w) + \"%s\"    ).c_str(), elementMap[e1].c_str()));\n    s = \"e2\";\n    v.push_back(strpr((pad(s, w) + \"%s\"    ).c_str(), elementMap[e2].c_str()));\n    s = \"eta\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(),\n                      eta * convLength * convLength));\n    s = \"lambda\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), lambda));\n    s = \"zeta\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), zeta));\n    s = \"rs\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), rs / convLength));\n\n    return v;\n}\n\ndouble SymFncBaseExpAng::calculateRadialPart(double distance) const\n{\n    double const& r = distance * convLength;\n    double const p = exp(-eta * (r - rs) * (r - rs)) * fc.f(r);\n\n    return p;\n}\n\ndouble SymFncBaseExpAng::calculateAngularPart(double angle) const\n{\n    return 2.0 * pow((1.0 + lambda * cos(angle)) / 2.0, zeta);\n}\n\nbool SymFncBaseExpAng::checkRelevantElement(size_t index) const\n{\n    if (index == e1 || index == e2) return true;\n    else return false;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvector<string> SymFncBaseExpAng::getCacheIdentifiers() const\n{\n    vector<string> v;\n    string s(\"\");\n\n    s += subtype;\n    s += \" \";\n    s += strpr(\"alpha = %16.8E\", cutoffAlpha);\n    s += \" \";\n    s += strpr(\"rc = %16.8E\", rc / convLength);\n\n    v.push_back(strpr(\"%zu f \", e1) + s);\n    v.push_back(strpr(\"%zu df \", e1) + s);\n    if (e1 != e2) v.push_back(strpr(\"%zu f \", e2) + s);\n    if (e1 != e2) v.push_back(strpr(\"%zu df \", e2) + s);\n\n    return v;\n}\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncBaseExpAng.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCBASEEXPANG_H\n#define SYMFNCBASEEXPANG_H\n\n#include \"SymFncBaseCutoff.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/// Intermediate class for angular SFs based on cutoffs and exponentials.\nclass SymFncBaseExpAng : public SymFncBaseCutoff\n{\npublic:\n    /** Set symmetry function parameters.\n     *\n     * @param[in] parameterString String containing angular symmetry function\n     *                            parameters.\n     */\n    virtual void        setParameters(std::string const& parameterString);\n    /** Change length unit.\n     *\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     */\n    virtual void        changeLengthUnit(double convLength);\n    /** Get settings file line from currently set parameters.\n     *\n     * @return Settings file string (\"symfunction_short ...\").\n     */\n    virtual std::string getSettingsLine() const;\n    /** Give symmetry function parameters in one line.\n     *\n     * @return String containing symmetry function parameter values.\n     */\n    virtual std::string parameterLine() const;\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual std::vector<\n    std::string>        parameterInfo() const;\n    /** Calculate (partial) symmetry function value for one given distance.\n     *\n     * @param[in] distance Distance between two atoms.\n     * @return @f$\\left(e^{-\\eta r^2} f_c(r)\\right)@f$\n     */\n    virtual double      calculateRadialPart(double distance) const;\n    /** Calculate (partial) symmetry function value for one given angle.\n     *\n     * @param[in] angle Angle between triplet of atoms (in radians).\n     * @return @f$1@f$\n     */\n    virtual double      calculateAngularPart(double angle) const;\n    /** Check whether symmetry function is relevant for given element.\n     *\n     * @param[in] index Index of given element.\n     * @return True if symmetry function is sensitive to given element, false\n     *         otherwise.\n     */\n    virtual bool        checkRelevantElement(std::size_t index) const;\n#ifndef N2P2_NO_SF_CACHE\n    /** Get unique cache identifiers.\n     *\n     * @return Vector of string identifying the type of cache this symmetry\n     *         function requires.\n     */\n    virtual std::vector<\n    std::string>        getCacheIdentifiers() const;\n#endif\n    /** Get private #useIntegerPow member variable.\n     */\n    bool                getUseIntegerPow() const;\n    /** Get private #e1 member variable.\n     */\n    std::size_t         getE1() const;\n    /** Get private #e2 member variable.\n     */\n    std::size_t         getE2() const;\n    /** Get private #zetaInt member variable.\n     */\n    int                 getZetaInt() const;\n    /** Get private #lambda member variable.\n     */\n    double              getLambda() const;\n    /** Get private #eta member variable.\n     */\n    double              getEta() const;\n    /** Get private #zeta member variable.\n     */\n    double              getZeta() const;\n    /** Get private #rs member variable.\n     */\n    double              getRs() const;\n\nprotected:\n    /// Whether to use integer version of power function (faster).\n    bool        useIntegerPow;\n    /// Element index of neighbor atom 1.\n    std::size_t e1;\n    /// Element index of neighbor atom 2.\n    std::size_t e2;\n    /// Integer version of @f$\\zeta@f$.\n    int         zetaInt;\n    /// Cosine shift factor.\n    double      lambda;\n    /// Width @f$\\eta@f$ of gaussian.\n    double      eta;\n    /// Exponent @f$\\zeta@f$ of cosine term.\n    double      zeta;\n    /// Shift @f$r_s@f$ of gaussian.\n    double      rs;\n\n    /** Constructor, initializes #type.\n     */\n    SymFncBaseExpAng(std::size_t type, ElementMap const&);\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline bool SymFncBaseExpAng::getUseIntegerPow() const { return useIntegerPow; }\ninline std::size_t SymFncBaseExpAng::getE1() const { return e1; }\ninline std::size_t SymFncBaseExpAng::getE2() const { return e2; }\ninline int SymFncBaseExpAng::getZetaInt() const { return zetaInt; }\ninline double SymFncBaseExpAng::getLambda() const { return lambda; }\ninline double SymFncBaseExpAng::getEta() const { return eta; }\ninline double SymFncBaseExpAng::getZeta() const { return zeta; }\ninline double SymFncBaseExpAng::getRs() const { return rs; }\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncCompAngn.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncCompAngn.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp, pow, cos\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncCompAngn::\nSymFncCompAngn(ElementMap const& elementMap) :\n    SymFncBaseCompAng(21, elementMap)\n{\n}\n\nbool SymFncCompAngn::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncCompAngn const& c = dynamic_cast<SymFncCompAngn const&>(rhs);\n    if (subtype     != c.getSubtype()) return false;\n    if (e1          != c.e1          ) return false;\n    if (e2          != c.e2          ) return false;\n    if (rc          != c.rc          ) return false;\n    if (rl          != c.rl          ) return false;\n    if (angleLeft   != c.angleLeft   ) return false;\n    if (angleRight  != c.angleRight  ) return false;\n    return true;\n}\n\nbool SymFncCompAngn::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncCompAngn const& c = dynamic_cast<SymFncCompAngn const&>(rhs);\n    if      (subtype     < c.getSubtype()) return true;\n    else if (subtype     > c.getSubtype()) return false;\n    if      (e1          < c.e1          ) return true;\n    else if (e1          > c.e1          ) return false;\n    if      (e2          < c.e2          ) return true;\n    else if (e2          > c.e2          ) return false;\n    if      (rc          < c.rc          ) return true;\n    else if (rc          > c.rc          ) return false;\n    if      (rl          < c.rl          ) return true;\n    else if (rl          > c.rl          ) return false;\n    if      (angleLeft   < c.angleLeft   ) return true;\n    else if (angleLeft   > c.angleLeft   ) return false;\n    if      (angleRight  < c.angleRight  ) return true;\n    else if (angleRight  > c.angleRight  ) return false;\n    return false;\n}\n\nvoid SymFncCompAngn::calculate(Atom& atom, bool const derivatives) const\n{\n    double r2l = 0.0;\n    if (rl > 0.0) r2l = rl * rl;\n    double r2c = rc * rc;\n    double result = 0.0;\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n        if ((e1 == nej || e2 == nej) && rij < rc && rij > rl)\n        {\n            double radij;\n            double dradij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) cr.fdf(rij, radij, dradij);\n            else\n            {\n                double& crad = nj.cache[cacheIndices[nej][0]];\n                double& cdrad = nj.cache[cacheIndices[nej][1]];\n                if (crad < 0) cr.fdf(rij, crad, cdrad);\n                radij = crad;\n                dradij = cdrad;\n            }\n#else\n            cr.fdf(rij, radij, dradij);\n#endif\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                if ((e1 == nej && e2 == nek) ||\n                    (e2 == nej && e1 == nek))\n                {\n                    double const rik = nk.d;\n                    if (rik < rc && rik > rl)\n                    {\n                        // Energy calculation.\n                        Vec3D drij = nj.dr;\n                        Vec3D drik = nk.dr;\n                        Vec3D drjk = nk.dr - nj.dr;\n                        double rjk = drjk.norm2();\n                        if (rjk >= r2c || rjk <= r2l) continue;\n                        rjk = sqrt(rjk);\n \n                        double radik;\n                        double dradik;\n#ifndef N2P2_NO_SF_CACHE\n                        if (cacheIndices[nek].size() == 0)\n                        {\n                            cr.fdf(rik, radik, dradik);\n                        }\n                        else\n                        {\n                            double& crad = nk.cache[cacheIndices[nek][0]];\n                            double& cdrad = nk.cache[cacheIndices[nek][1]];\n                            if (crad < 0) cr.fdf(rik, crad, cdrad);\n                            radik = crad;\n                            dradik = cdrad;\n                        }\n#else\n                        cr.fdf(rik, radik, dradik);\n#endif\n                        double radjk;\n                        double dradjk;\n                        cr.fdf(rjk, radjk, dradjk);\n\n                        double costijk = drij * drik;\n                        double rinvijik = 1.0 / rij / rik;\n                        costijk *= rinvijik;\n\n                        // By definition, our polynomial is zero at 0 and 180 deg.\n                        // Therefore, skip the whole rest which might yield some NaN\n                        if (costijk <= -1.0 || costijk >= 1.0) continue;\n \n                        // Regroup later: Get acos(cos)\n                        double const acostijk = acos(costijk);\n                        // Only go on if we are within our compact support\n                        if (acostijk < angleLeftRadians ||\n                            acostijk > angleRightRadians) continue;\n                        double ang  = 0.0;\n                        double dang = 0.0;\n                        ca.fdf(acostijk, ang, dang);\n\n                        double const rad  = radij * radik * radjk; // product of cutoff fcts\n                        result += rad * ang;\n\n                        // Force calculation.\n                        if (!derivatives) continue;\n\n                        double const dacostijk = -1.0\n                                               / sqrt(1.0 - costijk * costijk);\n                        dang *= dacostijk;\n                        double const rinvij = rinvijik * rik;\n                        double const rinvik = rinvijik * rij;\n                        double const rinvjk = 1.0 / rjk;\n                        double phiijik = rinvij * (rinvik - rinvij*costijk);\n                        double phiikij = rinvik * (rinvij - rinvik*costijk);\n                        double psiijik = rinvijik; // careful: sign flip w.r.t. notes due to nj.dGd...\n                        phiijik *= dang;\n                        phiikij *= dang;\n                        psiijik *= dang;\n\n                        // Cutoff function might be a divide by zero, but we screen that case before\n                        double const chiij =  rinvij * dradij *  radik *  radjk;\n                        double const chiik =  rinvik *  radij * dradik *  radjk;\n                        double const chijk = -rinvjk *  radij *  radik * dradjk;\n\n                        // rijs/rij due to the shifted radial part of the Gaussian                        \n                        double const p1 = rad * phiijik +  ang * chiij;\n                        double const p2 = rad * phiikij +  ang * chiik;\n                        double const p3 = rad * psiijik +  ang * chijk;\n                        drij *= p1 * scalingFactor;\n                        drik *= p2 * scalingFactor;\n                        drjk *= p3 * scalingFactor;\n\n                        // Save force contributions in Atom storage.\n                        atom.dGdr[index] += drij + drik;\n#ifndef N2P2_FULL_SFD_MEMORY\n                        nj.dGdr[indexPerElement[nej]] -= drij + drjk;\n                        nk.dGdr[indexPerElement[nek]] -= drik - drjk;\n#else\n                        nj.dGdr[index] -= drij + drjk;\n                        nk.dGdr[index] -= drik - drjk;\n#endif\n                    } // rik <= rc\n                } // elem\n            } // k\n        } // rij <= rc\n    } // j\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymFncCompAngn.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCCOMPANGN_H\n#define SYMFNCCOMPANGN_H\n\n#include \"SymFncBaseCompAng.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Narrow angular symmetry function with compact support (type 21)\n *\n * @f[\n   G^{21}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n              C(r_{ij}, r_l, r_c)\n              C(r_{ik}, r_l, r_c)\n              C(r_{jk}, r_l, r_c)\n              C(\\theta_{ijk}, \\theta_l, \\theta_r),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$.\n *\n * Parameter string:\n * ```\n * <element-central> 21 <element-neighbor1> <element-neighbor2> <rlow> <rcutoff> <left> <right> <subtype>\n * ```\n * where\n * - `<element-central> .....` element symbol of central atom\n * - `<element-neighbor1> ...` element symbol of neighbor atom 1\n * - `<element-neighbor2> ...` element symbol of neighbor atom 2\n * - `<rlow> ................` low radius boundary @f$r_{l}@f$\n * - `<rcutoff> .............` high radius boundary @f$r_{c}@f$\n * - `<left> ................` left angle boundary @f$\\theta_l@f$\n * - `<right> ...............` right angle boundary @f$\\theta_r@f$\n * - `<subtype> .............` compact function specifier\n *\n * See the description of SymFncBaseComp::setCompactFunction() for possible\n * values of the `<subtype>` argument.\n *\n * @note If `<subtype>` specifies an asymmetric version of a polynomial core\n * function the asymmetry only applies to the radial parts, i.e. \"p2a\" sets\n * a \"p2a\" radial compact function and a \"p2\" angular compact function.\n */\nclass SymFncCompAngn : public SymFncBaseCompAng\n{\npublic:\n    /** Constructor, sets type = 21\n    */\n    SymFncCompAngn(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymFnc const& rhs) const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncCompAngnWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncCompAngnWeighted.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp, pow, cos\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncCompAngnWeighted::\nSymFncCompAngnWeighted(ElementMap const& elementMap) :\n    SymFncBaseCompAngWeighted(24, elementMap)\n{\n}\n\nbool SymFncCompAngnWeighted::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncCompAngnWeighted const& c =\n        dynamic_cast<SymFncCompAngnWeighted const&>(rhs);\n    if (subtype     != c.getSubtype()) return false;\n    if (rc          != c.rc          ) return false;\n    if (rl          != c.rl          ) return false;\n    if (angleLeft   != c.angleLeft   ) return false;\n    if (angleRight  != c.angleRight  ) return false;\n    return true;\n}\n\nbool SymFncCompAngnWeighted::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncCompAngnWeighted const& c =\n        dynamic_cast<SymFncCompAngnWeighted const&>(rhs);\n    if      (subtype     < c.getSubtype()) return true;\n    else if (subtype     > c.getSubtype()) return false;\n    if      (rc          < c.rc          ) return true;\n    else if (rc          > c.rc          ) return false;\n    if      (rl          < c.rl          ) return true;\n    else if (rl          > c.rl          ) return false;\n    if      (angleLeft   < c.angleLeft   ) return true;\n    else if (angleLeft   > c.angleLeft   ) return false;\n    if      (angleRight  < c.angleRight  ) return true;\n    else if (angleRight  > c.angleRight  ) return false;\n    return false;\n}\n\nvoid SymFncCompAngnWeighted::calculate(Atom& atom, bool const derivatives) const\n{\n    double r2l = 0.0;\n    if (rl > 0.0) r2l = rl * rl;\n    double r2c = rc * rc;\n    double result = 0.0;\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n        if (rij < rc && rij > rl)\n        {\n            double radij;\n            double dradij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) cr.fdf(rij, radij, dradij);\n            else\n            {\n                double& crad = nj.cache[cacheIndices[nej][0]];\n                double& cdrad = nj.cache[cacheIndices[nej][1]];\n                if (crad < 0) cr.fdf(rij, crad, cdrad);\n                radij = crad;\n                dradij = cdrad;\n            }\n#else\n            cr.fdf(rij, radij, dradij);\n#endif\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                double const rik = nk.d;\n                if (rik < rc && rik > rl)\n                {\n                    // Energy calculation.\n                    Vec3D drij = nj.dr;\n                    Vec3D drik = nk.dr;\n                    Vec3D drjk = nk.dr - nj.dr;\n                    double rjk = drjk.norm2();\n                    if (rjk >= r2c || rjk <= r2l) continue;\n                    rjk = sqrt(rjk);\n \n                    double radik;\n                    double dradik;\n#ifndef N2P2_NO_SF_CACHE\n                    if (cacheIndices[nek].size() == 0)\n                    {\n                        cr.fdf(rik, radik, dradik);\n                    }\n                    else\n                    {\n                        double& crad = nk.cache[cacheIndices[nek][0]];\n                        double& cdrad = nk.cache[cacheIndices[nek][1]];\n                        if (crad < 0) cr.fdf(rik, crad, cdrad);\n                        radik = crad;\n                        dradik = cdrad;\n                    }\n#else\n                    cr.fdf(rik, radik, dradik);\n#endif\n                    double radjk;\n                    double dradjk;\n                    cr.fdf(rjk, radjk, dradjk);\n\n                    double costijk = drij * drik;\n                    double rinvijik = 1.0 / rij / rik;\n                    costijk *= rinvijik;\n\n                    // By definition, our polynomial is zero at 0 and 180 deg.\n                    // Therefore, skip the whole rest which might yield some NaN\n                    if (costijk <= -1.0 || costijk >= 1.0) continue;\n \n                    // Regroup later: Get acos(cos)\n                    double const acostijk = acos(costijk);\n                    // Only go on if we are within our compact support\n                    if (acostijk < angleLeftRadians ||\n                        acostijk > angleRightRadians) continue;\n                    double ang  = 0.0;\n                    double dang = 0.0;\n                    ca.fdf(acostijk, ang, dang);\n\n                    double const rad  = radij * radik * radjk; // product of cutoff fcts\n                    ang *= elementMap.atomicNumber(nej)\n                         * elementMap.atomicNumber(nek);\n                    result += rad * ang;\n\n                    // Force calculation.\n                    if (!derivatives) continue;\n\n                    double const dacostijk = -1.0\n                                           / sqrt(1.0 - costijk * costijk);\n                    dang *= dacostijk\n                          * elementMap.atomicNumber(nej)\n                          * elementMap.atomicNumber(nek);\n                    double const rinvij = rinvijik * rik;\n                    double const rinvik = rinvijik * rij;\n                    double const rinvjk = 1.0 / rjk;\n                    double phiijik = rinvij * (rinvik - rinvij * costijk);\n                    double phiikij = rinvik * (rinvij - rinvik * costijk);\n                    double psiijik = rinvijik; // careful: sign flip w.r.t. notes due to nj.dGd...\n                    phiijik *= dang;\n                    phiikij *= dang;\n                    psiijik *= dang;\n\n                    // Cutoff function might be a divide by zero, but we screen that case before\n                    double const chiij =  rinvij * dradij *  radik *  radjk;\n                    double const chiik =  rinvik *  radij * dradik *  radjk;\n                    double const chijk = -rinvjk *  radij *  radik * dradjk;\n\n                    // rijs/rij due to the shifted radial part of the Gaussian                        \n                    double const p1 = rad * phiijik +  ang * chiij;\n                    double const p2 = rad * phiikij +  ang * chiik;\n                    double const p3 = rad * psiijik +  ang * chijk;\n                    drij *= p1 * scalingFactor;\n                    drik *= p2 * scalingFactor;\n                    drjk *= p3 * scalingFactor;\n\n                    // Save force contributions in Atom storage.\n                    atom.dGdr[index] += drij + drik;\n#ifndef N2P2_FULL_SFD_MEMORY\n                    nj.dGdr[indexPerElement[nej]] -= drij + drjk;\n                    nk.dGdr[indexPerElement[nek]] -= drik - drjk;\n#else\n                    nj.dGdr[index] -= drij + drjk;\n                    nk.dGdr[index] -= drik - drjk;\n#endif\n                } // rik <= rc\n            } // k\n        } // rij <= rc\n    } // j\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymFncCompAngnWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCCOMPANGNWEIGHTED_H\n#define SYMFNCCOMPANGNWEIGHTED_H\n\n#include \"SymFncBaseCompAngWeighted.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Weighted narrow angular symmetry function with compact support (type 24)\n *\n * @f[\n   G^{24}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n              Z_j Z_k\n              C(r_{ij}, r_l, r_c)\n              C(r_{ik}, r_l, r_c)\n              C(r_{jk}, r_l, r_c)\n              C(\\theta_{ijk}, \\theta_l, \\theta_r),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$. @f$Z_j@f$ is defined\n * as the atomic number of the neighbor atom @f$j@f$.\n *\n * Parameter string:\n * ```\n * <element-central> 24 <rlow> <rcutoff> <left> <right> <subtype>\n * ```\n * where\n * - `<element-central> .....` element symbol of central atom\n * - `<rlow> ................` low radius boundary @f$r_{l}@f$\n * - `<rcutoff> .............` high radius boundary @f$r_{c}@f$\n * - `<left> ................` left angle boundary @f$\\theta_l@f$\n * - `<right> ...............` right angle boundary @f$\\theta_r@f$\n * - `<subtype> .............` compact function specifier\n *\n * See the description of SymFncBaseComp::setCompactFunction() for possible\n * values of the `<subtype>` argument.\n *\n * @note If `<subtype>` specifies an asymmetric version of a polynomial core\n * function the asymmetry only applies to the radial parts, i.e. \"p2a\" sets\n * a \"p2a\" radial compact function and a \"p2\" angular compact function.\n */\nclass SymFncCompAngnWeighted : public SymFncBaseCompAngWeighted\n{\npublic:\n    /** Constructor, sets type = 24\n    */\n    SymFncCompAngnWeighted(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymFnc const& rhs) const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncCompAngw.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncCompAngw.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp, pow, cos\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncCompAngw::\nSymFncCompAngw(ElementMap const& elementMap) :\n    SymFncBaseCompAng(22, elementMap)\n{\n}\n\nbool SymFncCompAngw::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncCompAngw const& c = dynamic_cast<SymFncCompAngw const&>(rhs);\n    if (subtype     != c.getSubtype()) return false;\n    if (e1          != c.e1          ) return false;\n    if (e2          != c.e2          ) return false;\n    if (rc          != c.rc          ) return false;\n    if (rl          != c.rl          ) return false;\n    if (angleLeft   != c.angleLeft   ) return false;\n    if (angleRight  != c.angleRight  ) return false;\n    return true;\n}\n\nbool SymFncCompAngw::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncCompAngw const& c = dynamic_cast<SymFncCompAngw const&>(rhs);\n    if      (subtype     < c.getSubtype()) return true;\n    else if (subtype     > c.getSubtype()) return false;\n    if      (e1          < c.e1          ) return true;\n    else if (e1          > c.e1          ) return false;\n    if      (e2          < c.e2          ) return true;\n    else if (e2          > c.e2          ) return false;\n    if      (rc          < c.rc          ) return true;\n    else if (rc          > c.rc          ) return false;\n    if      (rl          < c.rl          ) return true;\n    else if (rl          > c.rl          ) return false;\n    if      (angleLeft   < c.angleLeft   ) return true;\n    else if (angleLeft   > c.angleLeft   ) return false;\n    if      (angleRight  < c.angleRight  ) return true;\n    else if (angleRight  > c.angleRight  ) return false;\n    return false;\n}\n\nvoid SymFncCompAngw::calculate(Atom& atom, bool const derivatives) const\n{\n    double       result = 0.0;\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n        if ((e1 == nej || e2 == nej) && rij < rc && rij > rl)\n        {\n            double radij;\n            double dradij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) cr.fdf(rij, radij, dradij);\n            else\n            {\n                double& crad = nj.cache[cacheIndices[nej][0]];\n                double& cdrad = nj.cache[cacheIndices[nej][1]];\n                if (crad < 0) cr.fdf(rij, crad, cdrad);\n                radij = crad;\n                dradij = cdrad;\n            }\n#else\n            cr.fdf(rij, radij, dradij);\n#endif\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                if ((e1 == nej && e2 == nek) ||\n                    (e2 == nej && e1 == nek))\n                {\n                    double const rik = nk.d;\n                    if (rik < rc && rik > rl)\n                    {\n                        // Energy calculation.\n                        double radik;\n                        double dradik;\n#ifndef N2P2_NO_SF_CACHE\n                        if (cacheIndices[nek].size() == 0)\n                        {\n                            cr.fdf(rik, radik, dradik);\n                        }\n                        else\n                        {\n                            double& crad = nk.cache[cacheIndices[nek][0]];\n                            double& cdrad = nk.cache[cacheIndices[nek][1]];\n                            if (crad < 0) cr.fdf(rik, crad, cdrad);\n                            radik = crad;\n                            dradik = cdrad;\n                        }\n#else\n                        cr.fdf(rik, radik, dradik);\n#endif\n\n                        Vec3D drij = nj.dr;\n                        Vec3D drik = nk.dr;\n                        Vec3D drjk = drik - drij;\n                        double costijk = drij * drik;\n                        double rinvijik = 1.0 / rij / rik;\n                        costijk *= rinvijik;\n\n                        // By definition, our polynomial is zero at 0 and 180 deg.\n                        // Therefore, skip the whole rest which might yield some NaN\n                        if (costijk <= -1.0 || costijk >= 1.0) continue;\n \n                        // Regroup later: Get acos(cos)\n                        double const acostijk = acos(costijk);\n                        // Only go on if we are within our compact support\n                        if (acostijk < angleLeftRadians ||\n                            acostijk > angleRightRadians) continue;\n                        double ang  = 0.0;\n                        double dang = 0.0;\n                        ca.fdf(acostijk, ang, dang);\n\n                        double const rad  = radij * radik; // product of cutoff fcts\n                        result += rad * ang;\n\n                        // Force calculation.\n                        if (!derivatives) continue;\n\n                        double const dacostijk = -1.0\n                                               / sqrt(1.0 - costijk * costijk);\n                        dang *= dacostijk;\n\n                        double const rinvij = rinvijik * rik;\n                        double const rinvik = rinvijik * rij;\n                        double phiijik = rinvij * (rinvik - rinvij * costijk);\n                        double phiikij = rinvik * (rinvij - rinvik * costijk);\n                        double psiijik = rinvijik; // careful: sign flip w.r.t. notes due to nj.dGd...\n                        phiijik *= dang;\n                        phiikij *= dang;\n                        psiijik *= dang;\n\n                        // Cutoff function might be a divide by zero, but we screen that case before\n                        double const chiij = rinvij * radik * dradij;\n                        double const chiik = rinvik * radij * dradik;\n\n                        // rijs/rij due to the shifted radial part of the Gaussian                        \n                        double const p1 = rad * phiijik +  ang * chiij;\n                        double const p2 = rad * phiikij +  ang * chiik;\n                        double const p3 = rad * psiijik;\n                        drij *= p1 * scalingFactor;\n                        drik *= p2 * scalingFactor;\n                        drjk *= p3 * scalingFactor;\n\n                        // Save force contributions in Atom storage.\n                        atom.dGdr[index] += drij + drik;\n#ifndef N2P2_FULL_SFD_MEMORY\n                        nj.dGdr[indexPerElement[nej]] -= drij + drjk;\n                        nk.dGdr[indexPerElement[nek]] -= drik - drjk;\n#else\n                        nj.dGdr[index] -= drij + drjk;\n                        nk.dGdr[index] -= drik - drjk;\n#endif\n                    } // rik <= rc\n                } // elem\n            } // k\n        } // rij <= rc\n    } // j\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymFncCompAngw.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCCOMPANGW_H\n#define SYMFNCCOMPANGW_H\n\n#include \"SymFncBaseCompAng.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Wide angular symmetry function with compact support (type 22)\n *\n * @f[\n   G^{22}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n              C(r_{ij}, r_l, r_c)\n              C(r_{ik}, r_l, r_c)\n              C(\\theta_{ijk}, \\theta_l, \\theta_r),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$.\n *\n * Parameter string:\n * ```\n * <element-central> 22 <element-neighbor1> <element-neighbor2> <rlow> <rcutoff> <left> <right> <subtype>\n * ```\n * where\n * - `<element-central> .....` element symbol of central atom\n * - `<element-neighbor1> ...` element symbol of neighbor atom 1\n * - `<element-neighbor2> ...` element symbol of neighbor atom 2\n * - `<rlow> ................` low radius boundary @f$r_{l}@f$\n * - `<rcutoff> .............` high radius boundary @f$r_{c}@f$\n * - `<left> ................` left angle boundary @f$\\theta_l@f$\n * - `<right> ...............` right angle boundary @f$\\theta_r@f$\n * - `<subtype> .............` compact function specifier\n *\n * See the description of SymFncBaseComp::setCompactFunction() for possible\n * values of the `<subtype>` argument.\n *\n * @note If `<subtype>` specifies an asymmetric version of a polynomial core\n * function the asymmetry only applies to the radial parts, i.e. \"p2a\" sets\n * a \"p2a\" radial compact function and a \"p2\" angular compact function.\n */\nclass SymFncCompAngw : public SymFncBaseCompAng\n{\npublic:\n    /** Constructor, sets type = 22\n     */\n    SymFncCompAngw(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool        operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool        operator<(SymFnc const& rhs) const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void        calculate(Atom& atom, bool const derivatives) const;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncCompAngwWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncCompAngwWeighted.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp, pow, cos\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncCompAngwWeighted::\nSymFncCompAngwWeighted(ElementMap const& elementMap) :\n    SymFncBaseCompAngWeighted(25, elementMap)\n{\n}\n\nbool SymFncCompAngwWeighted::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncCompAngwWeighted const& c =\n        dynamic_cast<SymFncCompAngwWeighted const&>(rhs);\n    if (subtype     != c.getSubtype()) return false;\n    if (rc          != c.rc          ) return false;\n    if (rl          != c.rl          ) return false;\n    if (angleLeft   != c.angleLeft   ) return false;\n    if (angleRight  != c.angleRight  ) return false;\n    return true;\n}\n\nbool SymFncCompAngwWeighted::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncCompAngwWeighted const& c =\n        dynamic_cast<SymFncCompAngwWeighted const&>(rhs);\n    if      (subtype     < c.getSubtype()) return true;\n    else if (subtype     > c.getSubtype()) return false;\n    if      (rc          < c.rc          ) return true;\n    else if (rc          > c.rc          ) return false;\n    if      (rl          < c.rl          ) return true;\n    else if (rl          > c.rl          ) return false;\n    if      (angleLeft   < c.angleLeft   ) return true;\n    else if (angleLeft   > c.angleLeft   ) return false;\n    if      (angleRight  < c.angleRight  ) return true;\n    else if (angleRight  > c.angleRight  ) return false;\n    return false;\n}\n\nvoid SymFncCompAngwWeighted::calculate(Atom& atom, bool const derivatives) const\n{\n    double result = 0.0;\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n        if (rij < rc && rij > rl)\n        {\n            double radij;\n            double dradij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) cr.fdf(rij, radij, dradij);\n            else\n            {\n                double& crad = nj.cache[cacheIndices[nej][0]];\n                double& cdrad = nj.cache[cacheIndices[nej][1]];\n                if (crad < 0) cr.fdf(rij, crad, cdrad);\n                radij = crad;\n                dradij = cdrad;\n            }\n#else\n            cr.fdf(rij, radij, dradij);\n#endif\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                double const rik = nk.d;\n                if (rik < rc && rik > rl)\n                {\n                    // Energy calculation.\n                    double radik;\n                    double dradik;\n#ifndef N2P2_NO_SF_CACHE\n                    if (cacheIndices[nek].size() == 0)\n                    {\n                        cr.fdf(rik, radik, dradik);\n                    }\n                    else\n                    {\n                        double& crad = nk.cache[cacheIndices[nek][0]];\n                        double& cdrad = nk.cache[cacheIndices[nek][1]];\n                        if (crad < 0) cr.fdf(rik, crad, cdrad);\n                        radik = crad;\n                        dradik = cdrad;\n                    }\n#else\n                    cr.fdf(rik, radik, dradik);\n#endif\n\n                    Vec3D drij = nj.dr;\n                    Vec3D drik = nk.dr;\n                    Vec3D drjk = nk.dr - nj.dr;\n                    double costijk = drij * drik;\n                    double rinvijik = 1.0 / rij / rik;\n                    costijk *= rinvijik;\n\n                    // By definition, our polynomial is zero at 0 and 180 deg.\n                    // Therefore, skip the whole rest which might yield some NaN\n                    if (costijk <= -1.0 || costijk >= 1.0) continue;\n \n                    // Regroup later: Get acos(cos)\n                    double const acostijk = acos(costijk);\n                    // Only go on if we are within our compact support\n                    if (acostijk < angleLeftRadians ||\n                        acostijk > angleRightRadians) continue;\n                    double ang  = 0.0;\n                    double dang = 0.0;\n                    ca.fdf(acostijk, ang, dang);\n\n                    double const rad  = radij * radik; // product of cutoff fcts\n                    ang *= elementMap.atomicNumber(nej)\n                         * elementMap.atomicNumber(nek);\n                    result += rad * ang;\n\n                    // Force calculation.\n                    if (!derivatives) continue;\n\n                    double const dacostijk = -1.0\n                                           / sqrt(1.0 - costijk * costijk);\n                    dang *= dacostijk\n                          * elementMap.atomicNumber(nej)\n                          * elementMap.atomicNumber(nek);\n                    double const rinvij = rinvijik * rik;\n                    double const rinvik = rinvijik * rij;\n                    double phiijik = rinvij * (rinvik - rinvij * costijk);\n                    double phiikij = rinvik * (rinvij - rinvik * costijk);\n                    double psiijik = rinvijik; // careful: sign flip w.r.t. notes due to nj.dGd...\n                    phiijik *= dang;\n                    phiikij *= dang;\n                    psiijik *= dang;\n\n                    // Cutoff function might be a divide by zero, but we screen that case before\n                    double const chiij = rinvij * radik * dradij;\n                    double const chiik = rinvik * radij * dradik;\n\n                    // rijs/rij due to the shifted radial part of the Gaussian                        \n                    double const p1 = rad * phiijik +  ang * chiij;\n                    double const p2 = rad * phiikij +  ang * chiik;\n                    double const p3 = rad * psiijik;\n                    drij *= p1 * scalingFactor;\n                    drik *= p2 * scalingFactor;\n                    drjk *= p3 * scalingFactor;\n\n                    // Save force contributions in Atom storage.\n                    atom.dGdr[index] += drij + drik;\n#ifndef N2P2_FULL_SFD_MEMORY\n                    nj.dGdr[indexPerElement[nej]] -= drij + drjk;\n                    nk.dGdr[indexPerElement[nek]] -= drik - drjk;\n#else\n                    nj.dGdr[index] -= drij + drjk;\n                    nk.dGdr[index] -= drik - drjk;\n#endif\n                } // rik <= rc\n            } // k\n        } // rij <= rc\n    } // j\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymFncCompAngwWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCCOMPANGWWEIGHTED_H\n#define SYMFNCCOMPANGWWEIGHTED_H\n\n#include \"SymFncBaseCompAngWeighted.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Weighted wide angular symmetry function with compact support (type 25)\n *\n * @f[\n   G^{25}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n              Z_j Z_k\n              C(r_{ij}, r_l, r_c)\n              C(r_{ik}, r_l, r_c)\n              C(\\theta_{ijk}, \\theta_l, \\theta_r),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$. @f$Z_j@f$ is defined\n * as the atomic number of the neighbor atom @f$j@f$.\n *\n * Parameter string:\n * ```\n * <element-central> 25 <rlow> <rcutoff> <left> <right> <subtype>\n * ```\n * where\n * - `<element-central> .....` element symbol of central atom\n * - `<rlow> ................` low radius boundary @f$r_{l}@f$\n * - `<rcutoff> .............` high radius boundary @f$r_{c}@f$\n * - `<left> ................` left angle boundary @f$\\theta_l@f$\n * - `<right> ...............` right angle boundary @f$\\theta_r@f$\n * - `<subtype> .............` compact function specifier\n *\n * See the description of SymFncBaseComp::setCompactFunction() for possible\n * values of the `<subtype>` argument.\n *\n * @note If `<subtype>` specifies an asymmetric version of a polynomial core\n * function the asymmetry only applies to the radial parts, i.e. \"p2a\" sets\n * a \"p2a\" radial compact function and a \"p2\" angular compact function.\n */\nclass SymFncCompAngwWeighted : public SymFncBaseCompAngWeighted\n{\npublic:\n    /** Constructor, sets type = 25\n    */\n    SymFncCompAngwWeighted(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymFnc const& rhs) const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncCompRad.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncCompRad.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncCompRad::SymFncCompRad(ElementMap const& elementMap) :\n    SymFncBaseComp(20, elementMap),\n    e1(0)\n{\n    minNeighbors = 1;\n    parameters.insert(\"e1\");\n}\n\nbool SymFncCompRad::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncCompRad const& c = dynamic_cast<SymFncCompRad const&>(rhs);\n    if (subtype     != c.getSubtype()) return false;\n    if (e1          != c.e1          ) return false;\n    if (rc          != c.rc          ) return false;\n    if (rl          != c.rl          ) return false;\n    return true;\n}\n\nbool SymFncCompRad::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncCompRad const& c = dynamic_cast<SymFncCompRad const&>(rhs);\n    if      (subtype     < c.getSubtype()) return true;\n    else if (subtype     > c.getSubtype()) return false;\n    if      (e1          < c.e1          ) return true;\n    else if (e1          > c.e1          ) return false;\n    if      (rc          < c.rc          ) return true;\n    else if (rc          > c.rc          ) return false;\n    if      (rl          < c.rl          ) return true;\n    else if (rl          > c.rl          ) return false;\n    return false;\n}\n\nvoid SymFncCompRad::setParameters(string const& parameterString)\n{\n    vector<string> splitLine = split(reduce(parameterString));\n\n    if (type != (size_t)atoi(splitLine.at(1).c_str()))\n    {\n        throw runtime_error(\"ERROR: Incorrect symmetry function type.\\n\");\n    }\n\n    ec      = elementMap[splitLine.at(0)];\n    e1      = elementMap[splitLine.at(2)];\n    rl      = atof(splitLine.at(3).c_str());\n    rc      = atof(splitLine.at(4).c_str());\n    subtype = splitLine.at(5);\n\n    if (rl > rc)\n    {\n        throw runtime_error(\"ERROR: Lower radial boundary >= upper \"\n                            \"radial boundary.\\n\");\n    }\n    //if (rl < 0.0 && abs(rl + rc) > numeric_limits<double>::epsilon())\n    //{\n    //    throw runtime_error(\"ERROR: Radial function not symmetric \"\n    //                        \"w.r.t. origin.\\n\");\n    //}\n\n    setCompactFunction(subtype);\n    cr.setLeftRight(rl, rc);\n\n    return;\n}\n\nvoid SymFncCompRad::changeLengthUnit(double convLength)\n{\n    this->convLength = convLength;\n    rl *= convLength;\n    rc *= convLength;\n\n    cr.setLeftRight(rl, rc);\n\n    return;\n}\n\nstring SymFncCompRad::getSettingsLine() const\n{\n    string s = strpr(\"symfunction_short %2s %2zu %2s %16.8E %16.8E %s\\n\",\n                     elementMap[ec].c_str(),\n                     type,\n                     elementMap[e1].c_str(),\n                     rl / convLength,\n                     rc / convLength,\n                     subtype.c_str());\n\n    return s;\n}\n\nvoid SymFncCompRad::calculate(Atom& atom, bool const derivatives) const\n{\n    double result = 0.0;\n#ifndef N2P2_NO_SF_CACHE\n    bool unique = true;\n    size_t c0 = 0;\n    size_t c1 = 0;\n    if (cacheIndices.at(e1).size() > 0)\n    {\n        unique = false;\n        c0 = cacheIndices.at(e1).at(0);\n        c1 = cacheIndices.at(e1).at(1);\n    }\n#endif\n\n    for (size_t j = 0; j < atom.numNeighbors; ++j)\n    {\n        Atom::Neighbor& n = atom.neighbors[j];\n        if (e1 == n.element && n.d > rl && n.d < rc)\n        {\n            // Energy calculation.\n            double const rij = n.d;\n\n            double rad;\n            double drad;\n            double r = rij;\n#ifndef N2P2_NO_SF_CACHE\n            if (unique) cr.fdf(r, rad, drad);\n            else\n            {\n                double& crad = n.cache[c0];\n                double& cdrad = n.cache[c1];\n                if (crad < 0) cr.fdf(r, crad, cdrad);\n                rad = crad;\n                drad = cdrad;\n            }\n#else\n            cr.fdf(r, rad, drad);\n#endif\n            result += rad;\n\n            // Force calculation.\n            if (!derivatives) continue;\n            double const p1 = scalingFactor * drad / rij;\n            Vec3D dij = p1 * n.dr;\n            // Save force contributions in Atom storage.\n            atom.dGdr[index] += dij;\n#ifndef N2P2_FULL_SFD_MEMORY\n            n.dGdr[indexPerElement[e1]] -= dij;\n#else\n            n.dGdr[index] -= dij;\n#endif\n        }\n    }\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n\nstring SymFncCompRad::parameterLine() const\n{\n    return strpr(getPrintFormat().c_str(),\n                 index + 1,\n                 elementMap[ec].c_str(),\n                 type,\n                 subtype.c_str(),\n                 elementMap[e1].c_str(),\n                 rl / convLength,\n                 rc / convLength,\n                 lineNumber + 1);\n}\n\nvector<string> SymFncCompRad::parameterInfo() const\n{\n    vector<string> v = SymFncBaseComp::parameterInfo();\n    string s;\n    size_t w = sfinfoWidth;\n\n    s = \"e1\";\n    v.push_back(strpr((pad(s, w) + \"%s\").c_str(), elementMap[e1].c_str()));\n\n    return v;\n}\n\ndouble SymFncCompRad::calculateRadialPart(double distance) const\n{\n    double const& r = distance * convLength;\n\n    return cr.f(r);\n}\n\ndouble SymFncCompRad::calculateAngularPart(double /* angle */) const\n{\n    return 1.0;\n}\n\nbool SymFncCompRad::checkRelevantElement(size_t index) const\n{\n    if (index == e1) return true;\n    else return false;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvector<string> SymFncCompRad::getCacheIdentifiers() const\n{\n    vector<string> v;\n    string s(\"\");\n\n    s += subtype;\n    s += \" \";\n    s += strpr(\"rl = %16.8E\", rl / convLength);\n    s += \" \";\n    s += strpr(\"rc = %16.8E\", rc / convLength);\n\n    v.push_back(strpr(\"%zu f \", e1) + s);\n    v.push_back(strpr(\"%zu df \", e1) + s);\n\n    return v;\n}\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncCompRad.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCCOMPRAD_H\n#define SYMFNCCOMPRAD_H\n\n#include \"SymFncBaseComp.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Radial symmetry function with compact support (type 20)\n *\n * @f[\n   G^{20}_i = \\sum_{\\substack{j \\neq i}}\n              C(r_{ij}, r_l, r_c),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$.\n *\n * Parameter string:\n * ```\n * <element-central> 20 <element-neighbor> <rlow> <rcutoff> <subtype>\n * ```\n * where\n * - `<element-central> ....` element symbol of central atom\n * - `<element-neighbor> ...` element symbol of neighbor atom\n * - `<rlow> ...............` low radius boundary @f$r_{l}@f$\n * - `<rcutoff> ............` high radius boundary @f$r_{c}@f$\n * - `<subtype> ............` compact function specifier\n *\n * See the description of SymFncBaseComp::setCompactFunction() for possible\n * values of the `<subtype>` argument.\n */\nclass SymFncCompRad : public SymFncBaseComp\n{\npublic:\n    /** Constructor, sets type = 20\n     */\n    SymFncCompRad(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool        operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool        operator<(SymFnc const& rhs) const;\n    /** Set symmetry function parameters.\n     *\n     * @param[in] parameterString String containing radial symmetry function\n     *                            parameters.\n     */\n    virtual void        setParameters(std::string const& parameterString);\n    /** Change length unit.\n     *\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     */\n    virtual void        changeLengthUnit(double convLength);\n    /** Get settings file line from currently set parameters.\n     *\n     * @return Settings file string (\"symfunction_short ...\").\n     */\n    virtual std::string getSettingsLine() const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void        calculate(Atom& atom, bool const derivatives) const;\n    // Access core fct. for groups\n    void                getCompactOnly(double const x,\n                                       double&      fx,\n                                       double&      dfx) const;\n    /** Give symmetry function parameters in one line.\n     *\n     * @return String containing symmetry function parameter values.\n     */\n    virtual std::string parameterLine() const;\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual std::vector<\n    std::string>        parameterInfo() const;\n    /** Get private #e1 member variable.\n     */\n    std::size_t         getE1() const;\n    /** Calculate (partial) symmetry function value for one given distance.\n     *\n     * @param[in] distance Distance between two atoms.\n     * @return @f$ e^{-\\eta (r - r_s)^2} f_c(r)@f$\n     */\n    virtual double      calculateRadialPart(double distance) const;\n    /** Calculate (partial) symmetry function value for one given angle.\n     *\n     * @param[in] angle Angle between triplet of atoms (in radians).\n     * @return @f$1@f$\n     */\n    virtual double      calculateAngularPart(double angle) const;\n    /** Check whether symmetry function is relevant for given element.\n     *\n     * @param[in] index Index of given element.\n     * @return True if symmetry function is sensitive to given element, false\n     *         otherwise.\n     */\n    virtual bool        checkRelevantElement(std::size_t index) const;\n#ifndef N2P2_NO_SF_CACHE\n    /** Get unique cache identifiers.\n     *\n     * @return Vector of string identifying the type of cache this symmetry\n     *         function requires.\n     */\n    virtual std::vector<\n    std::string>        getCacheIdentifiers() const;\n#endif\n\nprivate:\n    /// Element index of neighbor atom.\n    std::size_t e1;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline std::size_t SymFncCompRad::getE1() const { return e1; }\n\ninline void SymFncCompRad::getCompactOnly(double const x,\n                                          double&      fx,\n                                          double&      dfx) const\n{\n    cr.fdf(x, fx, dfx);\n    return;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncCompRadWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncCompRadWeighted.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncCompRadWeighted::SymFncCompRadWeighted(ElementMap const& elementMap) :\n    SymFncBaseComp(23, elementMap)\n{\n    minNeighbors = 1;\n}\n\nbool SymFncCompRadWeighted::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncCompRadWeighted const& c\n        = dynamic_cast<SymFncCompRadWeighted const&>(rhs);\n    if (subtype     != c.getSubtype()) return false;\n    if (rc          != c.rc          ) return false;\n    if (rl          != c.rl          ) return false;\n    return true;\n}\n\nbool SymFncCompRadWeighted::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncCompRadWeighted const& c\n        = dynamic_cast<SymFncCompRadWeighted const&>(rhs);\n    if      (subtype     < c.getSubtype()) return true;\n    else if (subtype     > c.getSubtype()) return false;\n    if      (rc          < c.rc          ) return true;\n    else if (rc          > c.rc          ) return false;\n    if      (rl          < c.rl          ) return true;\n    else if (rl          > c.rl          ) return false;\n    return false;\n}\n\nvoid SymFncCompRadWeighted::setParameters(string const& parameterString)\n{\n    vector<string> splitLine = split(reduce(parameterString));\n\n    if (type != (size_t)atoi(splitLine.at(1).c_str()))\n    {\n        throw runtime_error(\"ERROR: Incorrect symmetry function type.\\n\");\n    }\n\n    ec      = elementMap[splitLine.at(0)];\n    rl      = atof(splitLine.at(2).c_str());\n    rc      = atof(splitLine.at(3).c_str());\n    subtype = splitLine.at(4);\n\n    if (rl > rc)\n    {\n        throw runtime_error(\"ERROR: Lower radial boundary >= upper \"\n                            \"radial boundary.\\n\");\n    }\n    //if (rl < 0.0 && abs(rl + rc) > numeric_limits<double>::epsilon())\n    //{\n    //    throw runtime_error(\"ERROR: Radial function not symmetric \"\n    //                        \"w.r.t. origin.\\n\");\n    //}\n\n    setCompactFunction(subtype);\n    cr.setLeftRight(rl,rc);\n\n    return;\n}\n\nvoid SymFncCompRadWeighted::changeLengthUnit(double convLength)\n{\n    this->convLength = convLength;\n    rl *= convLength;\n    rc *= convLength;\n\n    cr.setLeftRight(rl, rc);\n\n    return;\n}\n\nstring SymFncCompRadWeighted::getSettingsLine() const\n{\n    string s = strpr(\"symfunction_short %2s %2zu %16.8E %16.8E %s\\n\",\n                     elementMap[ec].c_str(),\n                     type,\n                     rl / convLength,\n                     rc / convLength,\n                     subtype.c_str());\n\n    return s;\n}\n\nvoid SymFncCompRadWeighted::calculate(Atom& atom, bool const derivatives) const\n{\n    double result = 0.0;\n\n    for (size_t j = 0; j < atom.numNeighbors; ++j)\n    {\n        Atom::Neighbor& n = atom.neighbors[j];\n        if (n.d > rl && n.d < rc)\n        {\n            // Energy calculation.\n            size_t const ne = n.element;\n            double const rij = n.d;\n\n            double rad;\n            double drad;\n            double r = rij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[ne].size() == 0) cr.fdf(r, rad, drad);\n            else\n            {\n                double& crad = n.cache[cacheIndices[ne][0]];\n                double& cdrad = n.cache[cacheIndices[ne][1]];\n                if (crad < 0) cr.fdf(r, crad, cdrad);\n                rad = crad;\n                drad = cdrad;\n            }\n#else\n            cr.fdf(r, rad, drad);\n#endif\n            result += rad * elementMap.atomicNumber(ne);\n\n            // Force calculation.\n            if (!derivatives) continue;\n            double const p1 = scalingFactor * elementMap.atomicNumber(ne)\n                            * drad / rij;\n            Vec3D dij = p1 * n.dr;\n            // Save force contributions in Atom storage.\n            atom.dGdr[index] += dij;\n#ifndef N2P2_FULL_SFD_MEMORY\n            n.dGdr[indexPerElement[ne]] -= dij;\n#else\n            n.dGdr[index] -= dij;\n#endif\n        }\n    }\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n\nstring SymFncCompRadWeighted::parameterLine() const\n{\n    return strpr(getPrintFormat().c_str(),\n                 index + 1,\n                 elementMap[ec].c_str(),\n                 type,\n                 subtype.c_str(),\n                 rl / convLength,\n                 rc / convLength,\n                 lineNumber + 1);\n}\n\nvector<string> SymFncCompRadWeighted::parameterInfo() const\n{\n    vector<string> v = SymFncBaseComp::parameterInfo();\n\n    return v;\n}\n\ndouble SymFncCompRadWeighted::calculateRadialPart(double distance) const\n{\n    double const& r = distance * convLength;\n\n    return cr.f(r);\n}\n\ndouble SymFncCompRadWeighted::calculateAngularPart(double /* angle */) const\n{\n    return 1.0;\n}\n\nbool SymFncCompRadWeighted::checkRelevantElement(size_t /*index*/) const\n{\n    return true;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvector<string> SymFncCompRadWeighted::getCacheIdentifiers() const\n{\n    vector<string> v;\n    string s(\"\");\n\n    s += subtype;\n    s += \" \";\n    s += strpr(\"rl = %16.8E\", rl / convLength);\n    s += \" \";\n    s += strpr(\"rc = %16.8E\", rc / convLength);\n\n    for (size_t i = 0; i < elementMap.size(); ++i)\n    {\n        v.push_back(strpr(\"%zu f \", i) + s);\n        v.push_back(strpr(\"%zu df \", i) + s);\n    }\n\n    return v;\n}\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncCompRadWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCCOMPRADWEIGHTED_H\n#define SYMFNCCOMPRADWEIGHTED_H\n\n#include \"SymFncBaseComp.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Weighted radial symmetry function with compact support (type 23)\n *\n * @f[\n   G^{23}_i = \\sum_{\\substack{j \\neq i}}\n              Z_j\n              C(r_{ij}, r_l, r_c),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$. @f$Z_j@f$ is defined\n * as the atomic number of the neighbor atom @f$j@f$.\n *\n * Parameter string:\n * ```\n * <element-central> 23 <rlow> <rcutoff> <subtype>\n * ```\n * where\n * - `<element-central> ....` element symbol of central atom\n * - `<rlow> ................` low radius boundary @f$r_{l}@f$\n * - `<rcutoff> .............` high radius boundary @f$r_{c}@f$\n * - `<subtype> ............` compact function specifier\n *\n * See the description of SymFncBaseComp::setCompactFunction() for possible\n * values of the `<subtype>` argument.\n */\nclass SymFncCompRadWeighted : public SymFncBaseComp\n{\npublic:\n    /** Constructor, sets type = 23\n     */\n    SymFncCompRadWeighted(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool        operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool        operator<(SymFnc const& rhs) const;\n    /** Set symmetry function parameters.\n     *\n     * @param[in] parameterString String containing weighted radial symmetry\n     *                            function parameters.\n     */\n    virtual void        setParameters(std::string const& parameterString);\n    /** Change length unit.\n     *\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     */\n    virtual void        changeLengthUnit(double convLength);\n    /** Get settings file line from currently set parameters.\n     *\n     * @return Settings file string (\"symfunction_short ...\").\n     */\n    virtual std::string getSettingsLine() const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void        calculate(Atom& atom, bool const derivatives) const;\n    // Access core fct. for groups\n    void                getCompactOnly(double const x,\n                                       double&      fx,\n                                       double&      dfx) const;\n    /** Give symmetry function parameters in one line.\n     *\n     * @return String containing symmetry function parameter values.\n     */\n    virtual std::string parameterLine() const;\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual std::vector<\n    std::string>        parameterInfo() const;\n    /** Calculate (partial) symmetry function value for one given distance.\n     *\n     * @param[in] distance Distance between two atoms.\n     * @return @f$ e^{-\\eta (r - r_s)^2} f_c(r)@f$\n     */\n    virtual double      calculateRadialPart(double distance) const;\n    /** Calculate (partial) symmetry function value for one given angle.\n     *\n     * @param[in] angle Angle between triplet of atoms (in radians).\n     * @return @f$1@f$\n     */\n    virtual double      calculateAngularPart(double angle) const;\n    /** Check whether symmetry function is relevant for given element.\n     *\n     * @param[in] index Index of given element.\n     * @return True if symmetry function is sensitive to given element, false\n     *         otherwise.\n     */\n    virtual bool        checkRelevantElement(std::size_t index) const;\n#ifndef N2P2_NO_SF_CACHE\n    /** Get unique cache identifiers.\n     *\n     * @return Vector of string identifying the type of cache this symmetry\n     *         function requires.\n     */\n    virtual std::vector<\n    std::string>        getCacheIdentifiers() const;\n#endif\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline void SymFncCompRadWeighted::getCompactOnly(double const x,\n                                                  double&      fx,\n                                                  double&      dfx) const\n{\n    cr.fdf(x, fx, dfx);\n    return;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncExpAngn.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncExpAngn.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp, pow, cos\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncExpAngn::SymFncExpAngn(ElementMap const& elementMap) :\n    SymFncBaseExpAng(3, elementMap)\n{\n}\n\nbool SymFncExpAngn::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncExpAngn const& c = dynamic_cast<SymFncExpAngn const&>(rhs);\n    if (cutoffType  != c.cutoffType ) return false;\n    if (cutoffAlpha != c.cutoffAlpha) return false;\n    if (rc          != c.rc         ) return false;\n    if (eta         != c.eta        ) return false;\n    if (zeta        != c.zeta       ) return false;\n    if (lambda      != c.lambda     ) return false;\n    if (e1          != c.e1         ) return false;\n    if (e2          != c.e2         ) return false;\n    return true;\n}\n\nbool SymFncExpAngn::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncExpAngn const& c = dynamic_cast<SymFncExpAngn const&>(rhs);\n    if      (cutoffType  < c.cutoffType ) return true;\n    else if (cutoffType  > c.cutoffType ) return false;\n    if      (cutoffAlpha < c.cutoffAlpha) return true;\n    else if (cutoffAlpha > c.cutoffAlpha) return false;\n    if      (rc          < c.rc         ) return true;\n    else if (rc          > c.rc         ) return false;\n    if      (eta         < c.eta        ) return true;\n    else if (eta         > c.eta        ) return false;\n    if      (rs          < c.rs         ) return true;\n    else if (rs          > c.rs         ) return false;\n    if      (zeta        < c.zeta       ) return true;\n    else if (zeta        > c.zeta       ) return false;\n    if      (lambda      < c.lambda     ) return true;\n    else if (lambda      > c.lambda     ) return false;\n    if      (e1          < c.e1         ) return true;\n    else if (e1          > c.e1         ) return false;\n    if      (e2          < c.e2         ) return true;\n    else if (e2          > c.e2         ) return false;\n    return false;\n}\n\nvoid SymFncExpAngn::calculate(Atom& atom, bool const derivatives) const\n{\n    double const pnorm  = pow(2.0, 1.0 - zeta);\n    double const pzl    = zeta * lambda;\n    double const rc2    = rc * rc;\n    double       result = 0.0;\n\n    //size_t numNeighbors = atom.numNeighbors;\n    size_t numNeighbors = atom.getStoredMinNumNeighbors(rc);\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n        if ((e1 == nej || e2 == nej) && rij < rc)\n        {\n            double const r2ij   = rij * rij;\n\n            // Calculate cutoff function and derivative.\n            double pfcij;\n            double pdfcij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) fc.fdf(rij, pfcij, pdfcij);\n            else\n            {\n                double& cfc = nj.cache[cacheIndices[nej][0]];\n                double& cdfc = nj.cache[cacheIndices[nej][1]];\n                if (cfc < 0) fc.fdf(rij, cfc, cdfc);\n                pfcij = cfc;\n                pdfcij = cdfc;\n            }\n#else\n            fc.fdf(rij, pfcij, pdfcij);\n#endif\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                if ((e1 == nej && e2 == nek) ||\n                    (e2 == nej && e1 == nek))\n                {\n                    double const rik = nk.d;\n                    if (rik < rc)\n                    {\n                        Vec3D drjk = nk.dr - nj.dr;\n                        double rjk = drjk.norm2();;\n                        if (rjk < rc2)\n                        {\n                            // Energy calculation.\n                            double pfcik;\n                            double pdfcik;\n#ifndef N2P2_NO_SF_CACHE\n                            if (cacheIndices[nej].size() == 0)\n                            {\n                                fc.fdf(rik, pfcik, pdfcik);\n                            }\n                            else\n                            {\n                                double& cfc = nk.cache[cacheIndices[nek][0]];\n                                double& cdfc = nk.cache[cacheIndices[nek][1]];\n                                if (cfc < 0) fc.fdf(rik, cfc, cdfc);\n                                pfcik = cfc;\n                                pdfcik = cdfc;\n                            }\n#else\n                            fc.fdf(rik, pfcik, pdfcik);\n#endif\n                            rjk = sqrt(rjk);\n                            double pfcjk;\n                            double pdfcjk;\n                            fc.fdf(rjk, pfcjk, pdfcjk);\n\n                            Vec3D drij = nj.dr;\n                            Vec3D drik = nk.dr;\n                            double costijk = drij * drik;;\n                            double rinvijik = 1.0 / rij / rik;\n                            costijk *= rinvijik;\n\n                            double const pfc = pfcij * pfcik * pfcjk;\n                            double const r2ik = rik * rik;\n                            double const rijs = rij - rs;\n                            double const riks = rik - rs;\n                            double const rjks = rjk - rs;\n                            double const pexp = exp(-eta * (rijs * rijs +\n                                                            riks * riks +\n                                                            rjks * rjks));\n                            double const plambda = 1.0 + lambda * costijk;\n                            double       fg = pexp;\n                            if (plambda <= 0.0) fg = 0.0;\n                            else\n                            {\n                                if (useIntegerPow)\n                                {\n                                    fg *= pow_int(plambda, zetaInt - 1);\n                                }\n                                else\n                                {\n                                    fg *= pow(plambda, zeta - 1.0);\n                                }\n                            }\n                            result += fg * plambda * pfc;\n\n                            // Force calculation.\n                            if (!derivatives) continue;\n                            fg       *= pnorm;\n                            rinvijik *= pzl;\n                            costijk  *= pzl;\n                            double const p2etapl = 2.0 * eta * plambda;\n                            double const p1 = fg * (pfc * (rinvijik - costijk\n                                            / r2ij - p2etapl * rijs / rij)\n                                            + pfcik * pfcjk * pdfcij * plambda\n                                            / rij);\n                            double const p2 = fg * (pfc * (rinvijik - costijk\n                                            / r2ik - p2etapl * riks / rik)\n                                            + pfcij * pfcjk * pdfcik * plambda\n                                            / rik);\n                            double const p3 = fg * (pfc * (rinvijik + p2etapl\n                                            * rjks / rjk) - pfcij * pfcik\n                                            * pdfcjk * plambda / rjk);\n                            drij *= p1 * scalingFactor;\n                            drik *= p2 * scalingFactor;\n                            drjk *= p3 * scalingFactor;\n\n                            // Save force contributions in Atom storage.\n                            atom.dGdr[index] += drij + drik;\n#ifndef N2P2_FULL_SFD_MEMORY\n                            nj.dGdr[indexPerElement[nej]] -= drij + drjk;\n                            nk.dGdr[indexPerElement[nek]] -= drik - drjk;\n#else\n                            nj.dGdr[index] -= drij + drjk;\n                            nk.dGdr[index] -= drik - drjk;\n#endif\n                        } // rjk <= rc\n                    } // rik <= rc\n                } // elem\n            } // k\n        } // rij <= rc\n    } // j\n    result *= pnorm;\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymFncExpAngn.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCEXPANGN_H\n#define SYMFNCEXPANGN_H\n\n#include \"SymFncBaseExpAng.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Angular symmetry function (type 3)\n *\n * @f[\n   G^3_i = 2^{1-\\zeta} \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n           \\left( 1 + \\lambda \\cos \\theta_{ijk} \\right)^\\zeta\n           \\mathrm{e}^{-\\eta( (r_{ij}-r_s)^2 + (r_{ik}-r_s)^2\n           + (r_{jk}-r_s)^2 ) }\n           f_c(r_{ij}) f_c(r_{ik}) f_c(r_{jk}) \n * @f]\n * Parameter string:\n * ```\n * <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>>\n * ```\n * where\n * - `<element-central> .....` element symbol of central atom\n * - `<element-neighbor1> ...` element symbol of neighbor atom 1\n * - `<element-neighbor2> ...` element symbol of neighbor atom 2\n * - `<eta> .................` @f$\\eta@f$ \n * - `<lambda> ..............` @f$\\lambda@f$ \n * - `<zeta> ................` @f$\\zeta@f$ \n * - `<rcutoff> .............` @f$r_c@f$\n * - `<<rshift>> ............` @f$r_s@f$ (optional, default @f$r_s = 0@f$)\n */\nclass SymFncExpAngn : public SymFncBaseExpAng\n{\npublic:\n    /** Constructor, sets type = 3\n     */\n    SymFncExpAngn(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymFnc const& rhs) const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncExpAngnWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncExpAngnWeighted.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp, pow, cos\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncExpAngnWeighted::SymFncExpAngnWeighted(ElementMap const& elementMap) :\n    SymFncBaseCutoff(13, elementMap),\n    useIntegerPow(false),\n    zetaInt      (0    ),\n    eta          (0.0  ),\n    rs           (0.0  ),\n    lambda       (0.0  ),\n    zeta         (0.0  )\n{\n    minNeighbors = 2;\n    parameters.insert(\"rs/rl\");\n    parameters.insert(\"eta\");\n    parameters.insert(\"zeta\");\n    parameters.insert(\"lambda\");\n}\n\nbool SymFncExpAngnWeighted::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncExpAngnWeighted const& c =\n        dynamic_cast<SymFncExpAngnWeighted const&>(rhs);\n    if (cutoffType  != c.cutoffType ) return false;\n    if (cutoffAlpha != c.cutoffAlpha) return false;\n    if (rc          != c.rc         ) return false;\n    if (eta         != c.eta        ) return false;\n    if (rs          != c.rs         ) return false;\n    if (zeta        != c.zeta       ) return false;\n    if (lambda      != c.lambda     ) return false;\n    return true;\n}\n\nbool SymFncExpAngnWeighted::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncExpAngnWeighted const& c =\n        dynamic_cast<SymFncExpAngnWeighted const&>(rhs);\n    if      (cutoffType  < c.cutoffType ) return true;\n    else if (cutoffType  > c.cutoffType ) return false;\n    if      (cutoffAlpha < c.cutoffAlpha) return true;\n    else if (cutoffAlpha > c.cutoffAlpha) return false;\n    if      (rc          < c.rc         ) return true;\n    else if (rc          > c.rc         ) return false;\n    if      (eta         < c.eta        ) return true;\n    else if (eta         > c.eta        ) return false;\n    if      (rs          < c.rs         ) return true;\n    else if (rs          > c.rs         ) return false;\n    if      (zeta        < c.zeta       ) return true;\n    else if (zeta        > c.zeta       ) return false;\n    if      (lambda      < c.lambda     ) return true;\n    else if (lambda      > c.lambda     ) return false;\n    return false;\n}\n\nvoid SymFncExpAngnWeighted::setParameters(string const& parameterString)\n{\n    vector<string> splitLine = split(reduce(parameterString));\n\n    if (type != (size_t)atoi(splitLine.at(1).c_str()))\n    {\n        throw runtime_error(\"ERROR: Incorrect symmetry function type.\\n\");\n    }\n\n    ec     = elementMap[splitLine.at(0)];\n    eta    = atof(splitLine.at(2).c_str());\n    rs     = atof(splitLine.at(3).c_str());\n    lambda = atof(splitLine.at(4).c_str());\n    zeta   = atof(splitLine.at(5).c_str());\n    rc     = atof(splitLine.at(6).c_str());\n\n    fc.setCutoffRadius(rc);\n    fc.setCutoffParameter(cutoffAlpha);\n\n    zetaInt = round(zeta);\n    if (fabs(zeta - zetaInt) <= numeric_limits<double>::min())\n    {\n        useIntegerPow = true;\n    }\n    else\n    {\n        useIntegerPow = false;\n    }\n\n    return;\n}\n\nvoid SymFncExpAngnWeighted::changeLengthUnit(double convLength)\n{\n    this->convLength = convLength;\n    eta /= convLength * convLength;\n    rs *= convLength;\n    rc *= convLength;\n\n    fc.setCutoffRadius(rc);\n    fc.setCutoffParameter(cutoffAlpha);\n\n    return;\n}\n\nstring SymFncExpAngnWeighted::getSettingsLine() const\n{\n    string s = strpr(\"symfunction_short %2s %2zu %16.8E %16.8E %16.8E \"\n                     \"%16.8E %16.8E\\n\",\n                     elementMap[ec].c_str(),\n                     type,\n                     eta * convLength * convLength,\n                     rs / convLength,\n                     lambda,\n                     zeta,\n                     rc / convLength);\n\n    return s;\n}\n\nvoid SymFncExpAngnWeighted::calculate(Atom& atom, bool const derivatives) const\n{\n    double const pnorm  = pow(2.0, 1.0 - zeta);\n    double const pzl    = zeta * lambda;\n    double const rc2    = rc * rc;\n    double       result = 0.0;\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n        if (rij < rc)\n        {\n            double const r2ij   = rij * rij;\n\n            // Calculate cutoff function and derivative.\n            double pfcij;\n            double pdfcij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) fc.fdf(rij, pfcij, pdfcij);\n            else\n            {\n                double& cfc = nj.cache[cacheIndices[nej][0]];\n                double& cdfc = nj.cache[cacheIndices[nej][1]];\n                if (cfc < 0) fc.fdf(rij, cfc, cdfc);\n                pfcij = cfc;\n                pdfcij = cdfc;\n            }\n#else\n            fc.fdf(rij, pfcij, pdfcij);\n#endif\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                double const rik = nk.d;\n                if (rik < rc)\n                {\n                    Vec3D drjk = nk.dr - nj.dr;\n                    double rjk = drjk.norm2();;\n                    if (rjk < rc2)\n                    {\n                        // Energy calculation.\n                        double pfcik;\n                        double pdfcik;\n#ifndef N2P2_NO_SF_CACHE\n                        if (cacheIndices[nej].size() == 0)\n                        {\n                            fc.fdf(rik, pfcik, pdfcik);\n                        }\n                        else\n                        {\n                            double& cfc = nk.cache[cacheIndices[nek][0]];\n                            double& cdfc = nk.cache[cacheIndices[nek][1]];\n                            if (cfc < 0) fc.fdf(rik, cfc, cdfc);\n                            pfcik = cfc;\n                            pdfcik = cdfc;\n                        }\n#else\n                        fc.fdf(rik, pfcik, pdfcik);\n#endif\n                        rjk = sqrt(rjk);\n                        double pfcjk;\n                        double pdfcjk;\n                        fc.fdf(rjk, pfcjk, pdfcjk);\n\n                        Vec3D drij = nj.dr;\n                        Vec3D drik = nk.dr;\n                        double costijk = drij * drik;;\n                        double rinvijik = 1.0 / rij / rik;\n                        costijk *= rinvijik;\n\n                        double const pfc = pfcij * pfcik * pfcjk;\n                        double const r2ik = rik * rik;\n                        double const rijs = rij - rs;\n                        double const riks = rik - rs;\n                        double const rjks = rjk - rs;\n                        double const pexp = elementMap.atomicNumber(nej)\n                                          * elementMap.atomicNumber(nek)\n                                          * exp(-eta * (rijs * rijs +\n                                                        riks * riks +\n                                                        rjks * rjks));\n                        double const plambda = 1.0 + lambda * costijk;\n                        double       fg = pexp;\n                        if (plambda <= 0.0) fg = 0.0;\n                        else\n                        {\n                            if (useIntegerPow)\n                            {\n                                fg *= pow_int(plambda, zetaInt - 1);\n                            }\n                            else\n                            {\n                                fg *= pow(plambda, zeta - 1.0);\n                            }\n                        }\n                        result += fg * plambda * pfc;\n\n                        // Force calculation.\n                        if (!derivatives) continue;\n                        fg       *= pnorm;\n                        rinvijik *= pzl;\n                        costijk  *= pzl;\n                        double const p2etapl = 2.0 * eta * plambda;\n                        double const p1 = fg * (pfc * (rinvijik - costijk\n                                        / r2ij - p2etapl * rijs / rij) + pfcik\n                                        * pfcjk * pdfcij * plambda / rij);\n                        double const p2 = fg * (pfc * (rinvijik - costijk\n                                        / r2ik - p2etapl * riks / rik) + pfcij\n                                        * pfcjk * pdfcik * plambda / rik);\n                        double const p3 = fg * (pfc * (rinvijik + p2etapl\n                                        * rjks / rjk) - pfcij * pfcik * pdfcjk\n                                        * plambda / rjk);\n                        drij *= p1 * scalingFactor;\n                        drik *= p2 * scalingFactor;\n                        drjk *= p3 * scalingFactor;\n\n                        // Save force contributions in Atom storage.\n                        atom.dGdr[index] += drij + drik;\n#ifndef N2P2_FULL_SFD_MEMORY\n                        nj.dGdr[indexPerElement[nj.element]] -= drij + drjk;\n                        nk.dGdr[indexPerElement[nk.element]] -= drik - drjk;\n#else\n                        nj.dGdr[index] -= drij + drjk;\n                        nk.dGdr[index] -= drik - drjk;\n#endif\n                    } // rjk <= rc\n                } // rik <= rc\n            } // k\n        } // rij <= rc\n    } // j\n    result *= pnorm;\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n\nstring SymFncExpAngnWeighted::parameterLine() const\n{\n    return strpr(getPrintFormat().c_str(),\n                 index + 1,\n                 elementMap[ec].c_str(),\n                 type,\n                 subtype.c_str(),\n                 eta * convLength * convLength,\n                 rs / convLength,\n                 rc / convLength,\n                 lambda,\n                 zeta,\n                 cutoffAlpha,\n                 lineNumber + 1);\n}\n\nvector<string> SymFncExpAngnWeighted::parameterInfo() const\n{\n    vector<string> v = SymFncBaseCutoff::parameterInfo();\n    string s;\n    size_t w = sfinfoWidth;\n\n    s = \"eta\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(),\n                      eta * convLength * convLength));\n    s = \"lambda\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), lambda));\n    s = \"zeta\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), zeta));\n    s = \"rs\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), rs / convLength));\n\n    return v;\n}\n\ndouble SymFncExpAngnWeighted::calculateRadialPart(double distance) const\n{\n    double const& r = distance * convLength;\n    double const p = exp(-eta * (r - rs) * (r - rs)) * fc.f(r);\n\n    return p * p * p;\n}\n\ndouble SymFncExpAngnWeighted::calculateAngularPart(double angle) const\n{\n    return 2.0 * pow((1.0 + lambda * cos(angle)) / 2.0, zeta);\n}\n\nbool SymFncExpAngnWeighted::checkRelevantElement(size_t /*index*/) const\n{\n    return true;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvector<string> SymFncExpAngnWeighted::getCacheIdentifiers() const\n{\n    vector<string> v;\n    string s(\"\");\n\n    s += subtype;\n    s += \" \";\n    s += strpr(\"alpha = %16.8E\", cutoffAlpha);\n    s += \" \";\n    s += strpr(\"rc = %16.8E\", rc / convLength);\n\n    for (size_t i = 0; i < elementMap.size(); ++i)\n    {\n        v.push_back(strpr(\"%zu f \", i) + s);\n        v.push_back(strpr(\"%zu df \", i) + s);\n    }\n\n    return v;\n}\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncExpAngnWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCEXPANGNWEIGHTED_H\n#define SYMFNCEXPANGNWEIGHTED_H\n\n#include \"SymFncBaseCutoff.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Weighted angular symmetry function (type 13)\n *\n * @f[\n   G^{13}_i = 2^{1-\\zeta} \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n              Z_j Z_k \\,\n              \\left( 1 + \\lambda \\cos \\theta_{ijk} \\right)^\\zeta\n              \\mathrm{e}^{-\\eta \\left[\n              (r_{ij} - r_s)^2 + (r_{ik} - r_s)^2 + (r_{jk} - r_s)^2 \\right] }\n              f_c(r_{ij}) f_c(r_{ik}) f_c(r_{jk}) \n * @f]\n * Parameter string:\n * ```\n * <element-central> 13 <eta> <rshift> <lambda> <zeta> <rcutoff>\n * ```\n * where\n * - `<element-central> .....` element symbol of central atom\n * - `<eta> .................` @f$\\eta@f$ \n * - `<rshift> ..............` @f$r_s@f$ \n * - `<lambda> ..............` @f$\\lambda@f$ \n * - `<zeta> ................` @f$\\zeta@f$ \n * - `<rcutoff> .............` @f$r_c@f$\n */\nclass SymFncExpAngnWeighted : public SymFncBaseCutoff\n{\npublic:\n    /** Constructor, sets type = 13\n     */\n    SymFncExpAngnWeighted(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool        operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool        operator<(SymFnc const& rhs) const;\n    /** Set symmetry function parameters.\n     *\n     * @param[in] parameterString String containing weighted angular symmetry\n     *                            function parameters.\n     */\n    virtual void        setParameters(std::string const& parameterString);\n    /** Change length unit.\n     *\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     */\n    virtual void        changeLengthUnit(double convLength);\n    /** Get settings file line from currently set parameters.\n     *\n     * @return Settings file string (\"symfunction_short ...\").\n     */\n    virtual std::string getSettingsLine() const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void        calculate(Atom& atom, bool const derivatives) const;\n    /** Give symmetry function parameters in one line.\n     *\n     * @return String containing symmetry function parameter values.\n     */\n    virtual std::string parameterLine() const;\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual std::vector<\n    std::string>        parameterInfo() const;\n    /** Get private #useIntegerPow member variable.\n     */\n    bool                getUseIntegerPow() const;\n    /** Get private #zetaInt member variable.\n     */\n    int                 getZetaInt() const;\n    /** Get private #eta member variable.\n     */\n    double              getEta() const;\n    /** Get private #rs member variable.\n     */\n    double              getRs() const;\n    /** Get private #lambda member variable.\n     */\n    double              getLambda() const;\n    /** Get private #zeta member variable.\n     */\n    double              getZeta() const;\n    /** Calculate (partial) symmetry function value for one given distance.\n     *\n     * @param[in] distance Distance between two atoms.\n     * @return @f$\\left(e^{-\\eta (r - r_s)^2} f_c(r)\\right)^3@f$\n     */\n    virtual double      calculateRadialPart(double distance) const;\n    /** Calculate (partial) symmetry function value for one given angle.\n     *\n     * @param[in] angle Angle between triplet of atoms (in radians).\n     * @return @f$1@f$\n     */\n    virtual double      calculateAngularPart(double angle) const;\n    /** Check whether symmetry function is relevant for given element.\n     *\n     * @param[in] index Index of given element.\n     * @return True if symmetry function is sensitive to given element, false\n     *         otherwise.\n     */\n    virtual bool        checkRelevantElement(std::size_t index) const;\n#ifndef N2P2_NO_SF_CACHE\n    /** Get unique cache identifiers.\n     *\n     * @return Vector of string identifying the type of cache this symmetry\n     *         function requires.\n     */\n    virtual std::vector<\n    std::string>        getCacheIdentifiers() const;\n#endif\n\nprivate:\n    /// Whether to use integer version of power function (faster).\n    bool   useIntegerPow;\n    /// Integer version of @f$\\zeta@f$.\n    int    zetaInt;\n    /// Width @f$\\eta@f$ of gaussian.\n    double eta;\n    /// Shift @f$r_s@f$ of gaussian.\n    double rs;\n    /// Cosine shift factor.\n    double lambda;\n    /// Exponent @f$\\zeta@f$ of cosine term.\n    double zeta;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline bool SymFncExpAngnWeighted::getUseIntegerPow() const\n{\n    return useIntegerPow;\n}\n\ninline int SymFncExpAngnWeighted::getZetaInt() const { return zetaInt; }\ninline double SymFncExpAngnWeighted::getEta() const { return eta; }\ninline double SymFncExpAngnWeighted::getRs() const { return rs; }\ninline double SymFncExpAngnWeighted::getLambda() const { return lambda; }\ninline double SymFncExpAngnWeighted::getZeta() const { return zeta; }\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncExpAngw.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncExpAngw.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp, pow, cos\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncExpAngw::SymFncExpAngw(ElementMap const& elementMap) :\n    SymFncBaseExpAng(9, elementMap)\n{\n}\n\nbool SymFncExpAngw::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncExpAngw const& c = dynamic_cast<SymFncExpAngw const&>(rhs);\n    if (cutoffType  != c.cutoffType ) return false;\n    if (cutoffAlpha != c.cutoffAlpha) return false;\n    if (rc          != c.rc         ) return false;\n    if (eta         != c.eta        ) return false;\n    if (zeta        != c.zeta       ) return false;\n    if (lambda      != c.lambda     ) return false;\n    if (e1          != c.e1         ) return false;\n    if (e2          != c.e2         ) return false;\n    return true;\n}\n\nbool SymFncExpAngw::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncExpAngw const& c = dynamic_cast<SymFncExpAngw const&>(rhs);\n    if      (cutoffType  < c.cutoffType ) return true;\n    else if (cutoffType  > c.cutoffType ) return false;\n    if      (cutoffAlpha < c.cutoffAlpha) return true;\n    else if (cutoffAlpha > c.cutoffAlpha) return false;\n    if      (rc          < c.rc         ) return true;\n    else if (rc          > c.rc         ) return false;\n    if      (eta         < c.eta        ) return true;\n    else if (eta         > c.eta        ) return false;\n    if      (rs          < c.rs         ) return true;\n    else if (rs          > c.rs         ) return false;\n    if      (zeta        < c.zeta       ) return true;\n    else if (zeta        > c.zeta       ) return false;\n    if      (lambda      < c.lambda     ) return true;\n    else if (lambda      > c.lambda     ) return false;\n    if      (e1          < c.e1         ) return true;\n    else if (e1          > c.e1         ) return false;\n    if      (e2          < c.e2         ) return true;\n    else if (e2          > c.e2         ) return false;\n    return false;\n}\n\nvoid SymFncExpAngw::calculate(Atom& atom, bool const derivatives) const\n{\n    double const pnorm  = pow(2.0, 1.0 - zeta);\n    double const pzl    = zeta * lambda;\n    double       result = 0.0;\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n        if ((e1 == nej || e2 == nej) && rij < rc)\n        {\n            double const r2ij   = rij * rij;\n\n            // Calculate cutoff function and derivative.\n            double pfcij;\n            double pdfcij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) fc.fdf(rij, pfcij, pdfcij);\n            else\n            {\n                double& cfc = nj.cache[cacheIndices[nej][0]];\n                double& cdfc = nj.cache[cacheIndices[nej][1]];\n                if (cfc < 0) fc.fdf(rij, cfc, cdfc);\n                pfcij = cfc;\n                pdfcij = cdfc;\n            }\n#else\n            fc.fdf(rij, pfcij, pdfcij);\n#endif\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                if ((e1 == nej && e2 == nek) ||\n                    (e2 == nej && e1 == nek))\n                {\n                    double const rik = nk.d;\n                    if (rik < rc)\n                    {\n                        // Energy calculation.\n                        double pfcik;\n                        double pdfcik;\n#ifndef N2P2_NO_SF_CACHE\n                        if (cacheIndices[nej].size() == 0)\n                        {\n                            fc.fdf(rik, pfcik, pdfcik);\n                        }\n                        else\n                        {\n                            double& cfc = nk.cache[cacheIndices[nek][0]];\n                            double& cdfc = nk.cache[cacheIndices[nek][1]];\n                            if (cfc < 0) fc.fdf(rik, cfc, cdfc);\n                            pfcik = cfc;\n                            pdfcik = cdfc;\n                        }\n#else\n                        fc.fdf(rik, pfcik, pdfcik);\n#endif\n                        Vec3D drij = nj.dr;\n                        Vec3D drik = nk.dr;\n                        Vec3D drjk = drik - drij;\n                        double costijk = drij * drik;;\n                        double rinvijik = 1.0 / rij / rik;\n                        costijk *= rinvijik;\n\n                        double const pfc = pfcij * pfcik;\n                        double const r2ik = rik * rik;\n                        double const rijs = rij - rs;\n                        double const riks = rik - rs;\n                        double const pexp = exp(-eta * (rijs * rijs\n                                                      + riks * riks));\n                        double const plambda = 1.0 + lambda * costijk;\n                        double       fg = pexp;\n                        if (plambda <= 0.0) fg = 0.0;\n                        else\n                        {\n                            if (useIntegerPow)\n                            {\n                                fg *= pow_int(plambda, zetaInt - 1);\n                            }\n                            else\n                            {\n                                fg *= pow(plambda, zeta - 1.0);\n                            }\n                        }\n                        result += fg * plambda * pfc;\n\n                        // Force calculation.\n                        if (!derivatives) continue;\n                        fg       *= pnorm;\n                        rinvijik *= pzl;\n                        costijk  *= pzl;\n                        double const p2etapl = 2.0 * eta * plambda;\n                        double const p1 = fg * (pfc * (rinvijik - costijk\n                                        / r2ij - p2etapl * rijs / rij) + pfcik\n                                        * pdfcij * plambda / rij);\n                        double const p2 = fg * (pfc * (rinvijik - costijk\n                                        / r2ik - p2etapl * riks / rik) + pfcij\n                                        * pdfcik * plambda / rik);\n                        double const p3 = fg * pfc * rinvijik;\n                        drij *= p1 * scalingFactor;\n                        drik *= p2 * scalingFactor;\n                        drjk *= p3 * scalingFactor;\n\n                        // Save force contributions in Atom storage.\n                        atom.dGdr[index] += drij + drik;\n#ifndef N2P2_FULL_SFD_MEMORY\n                        nj.dGdr[indexPerElement[nej]] -= drij + drjk;\n                        nk.dGdr[indexPerElement[nek]] -= drik - drjk;\n#else\n                        nj.dGdr[index] -= drij + drjk;\n                        nk.dGdr[index] -= drik - drjk;\n#endif\n                    } // rik <= rc\n                } // elem\n            } // k\n        } // rij <= rc\n    } // j\n    result *= pnorm;\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymFncExpAngw.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCEXPANGW_H\n#define SYMFNCEXPANGW_H\n\n#include \"SymFncBaseExpAng.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Angular symmetry function (type 9)\n *\n * @f[\n   G^9_i = 2^{1-\\zeta} \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n           \\left( 1 + \\lambda \\cos \\theta_{ijk} \\right)^\\zeta\n           \\mathrm{e}^{-\\eta( (r_{ij}-r_s)^2 + (r_{ik}-r_s)^2 ) }\n           f_c(r_{ij}) f_c(r_{ik}) \n * @f]\n * Parameter string:\n * ```\n * <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>>\n * ```\n * where\n * - `<element-central> .....` element symbol of central atom\n * - `<element-neighbor1> ...` element symbol of neighbor atom 1\n * - `<element-neighbor2> ...` element symbol of neighbor atom 2\n * - `<eta> .................` @f$\\eta@f$ \n * - `<lambda> ..............` @f$\\lambda@f$ \n * - `<zeta> ................` @f$\\zeta@f$ \n * - `<rcutoff> .............` @f$r_c@f$\n * - `<<rshift>> ............` @f$r_s@f$ (optional, default @f$r_s = 0@f$)\n */\nclass SymFncExpAngw : public SymFncBaseExpAng\n{\npublic:\n    /** Constructor, sets type = 9\n     */\n    SymFncExpAngw(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymFnc const& rhs) const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncExpRad.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncExpRad.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncExpRad::SymFncExpRad(ElementMap const& elementMap) :\n    SymFncBaseCutoff(2, elementMap),\n    e1              (0  ),\n    eta             (0.0),\n    rs              (0.0)\n{\n    minNeighbors = 1;\n    parameters.insert(\"e1\");\n    parameters.insert(\"eta\");\n    parameters.insert(\"rs/rl\");\n}\n\nbool SymFncExpRad::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncExpRad const& c = dynamic_cast<SymFncExpRad const&>(rhs);\n    if (cutoffType  != c.cutoffType ) return false;\n    if (cutoffAlpha != c.cutoffAlpha) return false;\n    if (rc          != c.rc         ) return false;\n    if (eta         != c.eta        ) return false;\n    if (rs          != c.rs         ) return false;\n    if (e1          != c.e1         ) return false;\n    return true;\n}\n\nbool SymFncExpRad::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncExpRad const& c = dynamic_cast<SymFncExpRad const&>(rhs);\n    if      (cutoffType  < c.cutoffType ) return true;\n    else if (cutoffType  > c.cutoffType ) return false;\n    if      (cutoffAlpha < c.cutoffAlpha) return true;\n    else if (cutoffAlpha > c.cutoffAlpha) return false;\n    if      (rc          < c.rc         ) return true;\n    else if (rc          > c.rc         ) return false;\n    if      (eta         < c.eta        ) return true;\n    else if (eta         > c.eta        ) return false;\n    if      (rs          < c.rs         ) return true;\n    else if (rs          > c.rs         ) return false;\n    if      (e1          < c.e1         ) return true;\n    else if (e1          > c.e1         ) return false;\n    return false;\n}\n\nvoid SymFncExpRad::setParameters(string const& parameterString)\n{\n    vector<string> splitLine = split(reduce(parameterString));\n\n    if (type != (size_t)atoi(splitLine.at(1).c_str()))\n    {\n        throw runtime_error(\"ERROR: Incorrect symmetry function type.\\n\");\n    }\n\n    ec   = elementMap[splitLine.at(0)];\n    e1   = elementMap[splitLine.at(2)];\n    eta  = atof(splitLine.at(3).c_str());\n    rs   = atof(splitLine.at(4).c_str());\n    rc   = atof(splitLine.at(5).c_str());\n\n    fc.setCutoffRadius(rc);\n    fc.setCutoffParameter(cutoffAlpha);\n\n    return;\n}\n\nvoid SymFncExpRad::changeLengthUnit(double convLength)\n{\n    this->convLength = convLength;\n    eta /= convLength * convLength;\n    rs *= convLength;\n    rc *= convLength;\n\n    fc.setCutoffRadius(rc);\n    fc.setCutoffParameter(cutoffAlpha);\n\n    return;\n}\n\nstring SymFncExpRad::getSettingsLine() const\n{\n    string s = strpr(\"symfunction_short %2s %2zu %2s %16.8E %16.8E %16.8E\\n\",\n                     elementMap[ec].c_str(),\n                     type,\n                     elementMap[e1].c_str(),\n                     eta * convLength * convLength,\n                     rs / convLength,\n                     rc / convLength);\n\n    return s;\n}\n\nvoid SymFncExpRad::calculate(Atom& atom, bool const derivatives) const\n{\n    double result = 0.0;\n#ifndef N2P2_NO_SF_CACHE\n    bool unique = true;\n    size_t c0 = 0;\n    size_t c1 = 0;\n    if (cacheIndices.at(e1).size() > 0)\n    {\n        unique = false;\n        c0 = cacheIndices.at(e1).at(0);\n        c1 = cacheIndices.at(e1).at(1);\n    }\n#endif\n\n    for (size_t j = 0; j < atom.getStoredMinNumNeighbors(rc); ++j)\n    {\n        Atom::Neighbor& n = atom.neighbors[j];\n        if (e1 == n.element && n.d < rc)\n        {\n            // Energy calculation.\n            double const rij = n.d;\n            double const pexp = exp(-eta * (rij - rs) * (rij - rs));\n\n            // Calculate cutoff function and derivative.\n            double pfc;\n            double pdfc;\n#ifndef N2P2_NO_SF_CACHE\n            if (unique) fc.fdf(rij, pfc, pdfc);\n            else\n            {\n                double& cfc = n.cache[c0];\n                double& cdfc = n.cache[c1];\n                if (cfc < 0) fc.fdf(rij, cfc, cdfc);\n                pfc = cfc;\n                pdfc = cdfc;\n            }\n#else\n            fc.fdf(rij, pfc, pdfc);\n#endif\n            result += pexp * pfc;\n            // Force calculation.\n            if (!derivatives) continue;\n            double const p1 = scalingFactor\n                * (pdfc - 2.0 * eta * (rij - rs)\n                * pfc) * pexp / rij;\n            Vec3D dij = p1 * n.dr;\n            // Save force contributions in Atom storage.\n            atom.dGdr[index] += dij;\n#ifndef N2P2_FULL_SFD_MEMORY\n            n.dGdr[indexPerElement[e1]] -= dij;\n#else\n            n.dGdr[index] -= dij;\n#endif\n        }\n    }\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n\nstring SymFncExpRad::parameterLine() const\n{\n    return strpr(getPrintFormat().c_str(),\n                 index + 1,\n                 elementMap[ec].c_str(),\n                 type,\n                 subtype.c_str(),\n                 elementMap[e1].c_str(),\n                 eta * convLength * convLength,\n                 rs / convLength,\n                 rc / convLength,\n                 cutoffAlpha,\n                 lineNumber + 1);\n}\n\nvector<string> SymFncExpRad::parameterInfo() const\n{\n    vector<string> v = SymFncBaseCutoff::parameterInfo();\n    string s;\n    size_t w = sfinfoWidth;\n\n    s = \"e1\";\n    v.push_back(strpr((pad(s, w) + \"%s\"    ).c_str(), elementMap[e1].c_str()));\n    s = \"eta\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(),\n                      eta * convLength * convLength));\n    s = \"rs\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), rs / convLength));\n\n    return v;\n}\n\ndouble SymFncExpRad::calculateRadialPart(double distance) const\n{\n    double const& r = distance * convLength;\n\n    return exp(-eta * (r - rs) * (r - rs)) * fc.f(r);\n}\n\ndouble SymFncExpRad::calculateAngularPart(double /* angle */) const\n{\n    return 1.0;\n}\n\nbool SymFncExpRad::checkRelevantElement(size_t index) const\n{\n    if (index == e1) return true;\n    else return false;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvector<string> SymFncExpRad::getCacheIdentifiers() const\n{\n    vector<string> v;\n    string s(\"\");\n\n    s += subtype;\n    s += \" \";\n    s += strpr(\"alpha = %16.8E\", cutoffAlpha);\n    s += \" \";\n    s += strpr(\"rc = %16.8E\", rc / convLength);\n\n    v.push_back(strpr(\"%zu f \", e1) + s);\n    v.push_back(strpr(\"%zu df \", e1) + s);\n\n    return v;\n}\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncExpRad.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCEXPRAD_H\n#define SYMFNCEXPRAD_H\n\n#include \"SymFncBaseCutoff.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Radial symmetry function (type 2)\n *\n * @f[\n * G^2_i = \\sum_{j \\neq i} \\mathrm{e}^{-\\eta(r_{ij} - r_\\mathrm{s})^2}\n *         f_c(r_{ij}) \n * @f]\n * Parameter string:\n * ```\n * <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n * ```\n * where\n * - `<element-central> ....` element symbol of central atom\n * - `<element-neighbor> ...` element symbol of neighbor atom\n * - `<eta> ................` @f$\\eta@f$ \n * - `<rshift> .............` @f$r_\\mathrm{s}@f$\n * - `<rcutoff> ............` @f$r_c@f$\n */\nclass SymFncExpRad : public SymFncBaseCutoff\n{\npublic:\n    /** Constructor, sets type = 2\n     */\n    SymFncExpRad(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool        operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool        operator<(SymFnc const& rhs) const;\n    /** Set symmetry function parameters.\n     *\n     * @param[in] parameterString String containing radial symmetry function\n     *                            parameters.\n     */\n    virtual void        setParameters(std::string const& parameterString);\n    /** Change length unit.\n     *\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     */\n    virtual void        changeLengthUnit(double convLength);\n    /** Get settings file line from currently set parameters.\n     *\n     * @return Settings file string (\"symfunction_short ...\").\n     */\n    virtual std::string getSettingsLine() const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void        calculate(Atom& atom, bool const derivatives) const;\n    /** Give symmetry function parameters in one line.\n     *\n     * @return String containing symmetry function parameter values.\n     */\n    virtual std::string parameterLine() const;\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual std::vector<\n    std::string>        parameterInfo() const;\n    /** Get private #e1 member variable.\n     */\n    std::size_t         getE1() const;\n    /** Get private #eta member variable.\n     */\n    double              getEta() const;\n    /** Get private #rs member variable.\n     */\n    double              getRs() const;\n    /** Calculate (partial) symmetry function value for one given distance.\n     *\n     * @param[in] distance Distance between two atoms.\n     * @return @f$ e^{-\\eta (r - r_s)^2} f_c(r)@f$\n     */\n    virtual double      calculateRadialPart(double distance) const;\n    /** Calculate (partial) symmetry function value for one given angle.\n     *\n     * @param[in] angle Angle between triplet of atoms (in radians).\n     * @return @f$1@f$\n     */\n    virtual double      calculateAngularPart(double angle) const;\n    /** Check whether symmetry function is relevant for given element.\n     *\n     * @param[in] index Index of given element.\n     * @return True if symmetry function is sensitive to given element, false\n     *         otherwise.\n     */\n    virtual bool        checkRelevantElement(std::size_t index) const;\n#ifndef N2P2_NO_SF_CACHE\n    /** Get unique cache identifiers.\n     *\n     * @return Vector of string identifying the type of cache this symmetry\n     *         function requires.\n     */\n    virtual std::vector<\n    std::string>        getCacheIdentifiers() const;\n#endif\n\nprivate:\n    /// Element index of neighbor atom.\n    std::size_t e1;\n    /// Width @f$\\eta@f$ of gaussian.\n    double      eta;\n    /// Shift @f$r_s@f$ of gaussian.\n    double      rs;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline std::size_t SymFncExpRad::getE1() const { return e1; }\ninline double SymFncExpRad::getEta() const { return eta; }\ninline double SymFncExpRad::getRs() const { return rs; }\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncExpRadWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncExpRadWeighted.h\"\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"utility.h\"\n#include \"Vec3D.h\"\n#include <cstdlib>   // atof, atoi\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncExpRadWeighted::SymFncExpRadWeighted(ElementMap const& elementMap) :\n    SymFncBaseCutoff(12, elementMap),\n    eta             (0.0),\n    rs              (0.0)\n{\n    minNeighbors = 1;\n    parameters.insert(\"eta\");\n    parameters.insert(\"rs/rl\");\n}\n\nbool SymFncExpRadWeighted::operator==(SymFnc const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymFncExpRadWeighted const& c =\n        dynamic_cast<SymFncExpRadWeighted const&>(rhs);\n    if (cutoffType  != c.cutoffType ) return false;\n    if (cutoffAlpha != c.cutoffAlpha) return false;\n    if (rc          != c.rc         ) return false;\n    if (eta         != c.eta        ) return false;\n    if (rs          != c.rs         ) return false;\n    return true;\n}\n\nbool SymFncExpRadWeighted::operator<(SymFnc const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymFncExpRadWeighted const& c =\n        dynamic_cast<SymFncExpRadWeighted const&>(rhs);\n    if      (cutoffType  < c.cutoffType ) return true;\n    else if (cutoffType  > c.cutoffType ) return false;\n    if      (cutoffAlpha < c.cutoffAlpha) return true;\n    else if (cutoffAlpha > c.cutoffAlpha) return false;\n    if      (rc          < c.rc         ) return true;\n    else if (rc          > c.rc         ) return false;\n    if      (eta         < c.eta        ) return true;\n    else if (eta         > c.eta        ) return false;\n    if      (rs          < c.rs         ) return true;\n    else if (rs          > c.rs         ) return false;\n    return false;\n}\n\nvoid SymFncExpRadWeighted::setParameters(string const& parameterString)\n{\n    vector<string> splitLine = split(reduce(parameterString));\n\n    if (type != (size_t)atoi(splitLine.at(1).c_str()))\n    {\n        throw runtime_error(\"ERROR: Incorrect symmetry function type.\\n\");\n    }\n\n    ec   = elementMap[splitLine.at(0)];\n    eta  = atof(splitLine.at(2).c_str());\n    rs   = atof(splitLine.at(3).c_str());\n    rc   = atof(splitLine.at(4).c_str());\n\n    fc.setCutoffRadius(rc);\n    fc.setCutoffParameter(cutoffAlpha);\n\n    return;\n}\n\nvoid SymFncExpRadWeighted::changeLengthUnit(double convLength)\n{\n    this->convLength = convLength;\n    eta /= convLength * convLength;\n    rs *= convLength;\n    rc *= convLength;\n\n    fc.setCutoffRadius(rc);\n    fc.setCutoffParameter(cutoffAlpha);\n\n    return;\n}\n\nstring SymFncExpRadWeighted::getSettingsLine() const\n{\n    string s = strpr(\"symfunction_short %2s %2zu %16.8E %16.8E %16.8E\\n\",\n                     elementMap[ec].c_str(),\n                     type,\n                     eta * convLength * convLength,\n                     rs / convLength,\n                     rc / convLength);\n\n    return s;\n}\n\nvoid SymFncExpRadWeighted::calculate(Atom& atom, bool const derivatives) const\n{\n    double result = 0.0;\n\n    for (size_t j = 0; j < atom.numNeighbors; ++j)\n    {\n        Atom::Neighbor& n = atom.neighbors[j];\n        if (n.d < rc)\n        {\n            // Energy calculation.\n            size_t const ne = n.element;\n            double const rij = n.d;\n            double const pexp = elementMap.atomicNumber(n.element)\n                              * exp(-eta * (rij - rs) * (rij - rs));\n\n            // Calculate cutoff function and derivative.\n            double pfc;\n            double pdfc;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[ne].size() == 0) fc.fdf(rij, pfc, pdfc);\n            else\n            {\n                double& cfc = n.cache[cacheIndices[ne][0]];\n                double& cdfc = n.cache[cacheIndices[ne][1]];\n                if (cfc < 0) fc.fdf(rij, cfc, cdfc);\n                pfc = cfc;\n                pdfc = cdfc;\n            }\n#else\n            fc.fdf(rij, pfc, pdfc);\n#endif\n            result += pexp * pfc;\n            // Force calculation.\n            if (!derivatives) continue;\n            double const p1 = scalingFactor\n                * (pdfc - 2.0 * eta * (rij - rs)\n                * pfc) * pexp / rij;\n            Vec3D dij = p1 * n.dr;\n            // Save force contributions in Atom storage.\n            atom.dGdr[index] += dij;\n#ifndef N2P2_FULL_SFD_MEMORY\n            n.dGdr[indexPerElement[ne]] -= dij;\n#else\n            n.dGdr[index] -= dij;\n#endif\n        }\n    }\n\n    atom.G[index] = scale(result);\n\n    return;\n}\n\nstring SymFncExpRadWeighted::parameterLine() const\n{\n    return strpr(getPrintFormat().c_str(),\n                 index + 1,\n                 elementMap[ec].c_str(),\n                 type,\n                 subtype.c_str(),\n                 eta * convLength * convLength,\n                 rs / convLength,\n                 rc / convLength,\n                 cutoffAlpha,\n                 lineNumber + 1);\n}\n\nvector<string> SymFncExpRadWeighted::parameterInfo() const\n{\n    vector<string> v = SymFncBaseCutoff::parameterInfo();\n    string s;\n    size_t w = sfinfoWidth;\n\n    s = \"eta\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(),\n                      eta * convLength * convLength));\n    s = \"rs\";\n    v.push_back(strpr((pad(s, w) + \"%14.8E\").c_str(), rs / convLength));\n\n    return v;\n}\n\ndouble SymFncExpRadWeighted::calculateRadialPart(double distance) const\n{\n    double const& r = distance * convLength;\n\n    return exp(-eta * (r - rs) * (r - rs)) * fc.f(r);\n}\n\ndouble SymFncExpRadWeighted::calculateAngularPart(double /* angle */) const\n{\n    return 1.0;\n}\n\nbool SymFncExpRadWeighted::checkRelevantElement(size_t /*index*/) const\n{\n    return true;\n}\n\n#ifndef N2P2_NO_SF_CACHE\nvector<string> SymFncExpRadWeighted::getCacheIdentifiers() const\n{\n    vector<string> v;\n    string s(\"\");\n\n    s += subtype;\n    s += \" \";\n    s += strpr(\"alpha = %16.8E\", cutoffAlpha);\n    s += \" \";\n    s += strpr(\"rc = %16.8E\", rc / convLength);\n\n    for (size_t i = 0; i < elementMap.size(); ++i)\n    {\n        v.push_back(strpr(\"%zu f \", i) + s);\n        v.push_back(strpr(\"%zu df \", i) + s);\n    }\n\n    return v;\n}\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncExpRadWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCEXPRADWEIGHTED_H\n#define SYMFNCEXPRADWEIGHTED_H\n\n#include \"SymFncBaseCutoff.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\n\n/** Weighted radial symmetry function (type 12)\n *\n * @f[\n * G^{12}_i = \\sum_{j \\neq i} Z_j \\,\n *            \\mathrm{e}^{-\\eta(r_{ij} - r_\\mathrm{s})^2}\n *            f_c(r_{ij}) \n * @f]\n * Parameter string:\n * ```\n * <element-central> 12 <eta> <rshift> <rcutoff>\n * ```\n * where\n * - `<element-central> ....` element symbol of central atom\n * - `<eta> ................` @f$\\eta@f$ \n * - `<rshift> .............` @f$r_\\mathrm{s}@f$\n * - `<rcutoff> ............` @f$r_c@f$\n */\nclass SymFncExpRadWeighted : public SymFncBaseCutoff\n{\npublic:\n    /** Constructor, sets type = 12\n     */\n    SymFncExpRadWeighted(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool        operator==(SymFnc const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool        operator<(SymFnc const& rhs) const;\n    /** Set symmetry function parameters.\n     *\n     * @param[in] parameterString String containing weighted radial symmetry\n     *                            function parameters.\n     */\n    virtual void        setParameters(std::string const& parameterString);\n    /** Change length unit.\n     *\n     * @param[in] convLength Multiplicative length unit conversion factor.\n     */\n    virtual void        changeLengthUnit(double convLength);\n    /** Get settings file line from currently set parameters.\n     *\n     * @return Settings file string (\"symfunction_short ...\").\n     */\n    virtual std::string getSettingsLine() const;\n    /** Calculate symmetry function for one atom.\n     *\n     * @param[in,out] atom Atom for which the symmetry function is caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void        calculate(Atom& atom, bool const derivatives) const;\n    /** Give symmetry function parameters in one line.\n     *\n     * @return String containing symmetry function parameter values.\n     */\n    virtual std::string parameterLine() const;\n    /** Get description with parameter names and values.\n     *\n     * @return Vector of parameter description strings.\n     */\n    virtual std::vector<\n    std::string>        parameterInfo() const;\n    /** Get private #eta member variable.\n     */\n    double              getEta() const;\n    /** Get private #rs member variable.\n     */\n    double              getRs() const;\n    /** Calculate (partial) symmetry function value for one given distance.\n     *\n     * @param[in] distance Distance between two atoms.\n     * @return @f$ e^{-\\eta (r - r_s)^2} f_c(r)@f$\n     */\n    virtual double      calculateRadialPart(double distance) const;\n    /** Calculate (partial) symmetry function value for one given angle.\n     *\n     * @param[in] angle Angle between triplet of atoms (in radians).\n     * @return @f$1@f$\n     */\n    virtual double      calculateAngularPart(double angle) const;\n    /** Check whether symmetry function is relevant for given element.\n     *\n     * @param[in] index Index of given element.\n     * @return True if symmetry function is sensitive to given element, false\n     *         otherwise.\n     */\n    virtual bool        checkRelevantElement(std::size_t index) const;\n#ifndef N2P2_NO_SF_CACHE\n    /** Get unique cache identifiers.\n     *\n     * @return Vector of string identifying the type of cache this symmetry\n     *         function requires.\n     */\n    virtual std::vector<\n    std::string>        getCacheIdentifiers() const;\n#endif\n\nprivate:\n    /// Width @f$\\eta@f$ of gaussian.\n    double eta;\n    /// Shift @f$r_s@f$ of gaussian.\n    double rs;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline double SymFncExpRadWeighted::getEta() const { return eta; }\ninline double SymFncExpRadWeighted::getRs() const { return rs; }\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymFncStatistics.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymFncStatistics.h\"\n#include <algorithm> // std::min, std::max\n#include <limits>    // std::numeric_limits\n#include \"utility.h\"\n\nusing namespace std;\nusing namespace nnp;\n\nSymFncStatistics::Container::Container() :\n    count  (0                             ),\n    countEW(0                             ),\n    type   (0                             ),\n    min    ( numeric_limits<double>::max()),\n    max    (-numeric_limits<double>::max()),\n    Gmin   (0.0                           ),\n    Gmax   (0.0                           ),\n    sum    (0.0                           ),\n    sum2   (0.0                           ),\n    element(\"\"                            )\n{\n}\n\nvoid SymFncStatistics::Container::reset()\n{\n    resetStatistics();\n    resetExtrapolationWarnings();\n\n    return;\n}\n\nvoid SymFncStatistics::Container::resetStatistics()\n{\n    count = 0;\n    min   =  numeric_limits<double>::max();\n    max   = -numeric_limits<double>::max();\n    sum   = 0.0;\n    sum2  = 0.0;\n\n    return;\n}\n\nvoid SymFncStatistics::Container::resetExtrapolationWarnings()\n{\n    countEW = 0;\n    Gmin = 0.0;\n    Gmax = 0.0;\n    type = 0;\n    element = \"\";\n    indexStructureEW.clear();\n    indexAtomEW.clear();\n    valueEW.clear();\n\n    return;\n}\n\nSymFncStatistics::SymFncStatistics() :\n    collectStatistics           (false),\n    collectExtrapolationWarnings(false),\n    writeExtrapolationWarnings  (false),\n    stopOnExtrapolationWarnings (false)\n{\n}\n\nvoid SymFncStatistics::addValue(size_t index, double value)\n{\n    data[index].count++;\n    data[index].sum += value;\n    data[index].sum2 += value * value;\n    data[index].min = min(data[index].min, value);\n    data[index].max = max(data[index].max, value);\n\n    return;\n}\n\nvoid SymFncStatistics::addExtrapolationWarning(size_t index,\n                                               size_t type,\n                                               double value,\n                                               double Gmin,\n                                               double Gmax,\n                                               string element,\n                                               size_t indexStructure,\n                                               size_t indexAtom)\n{\n    data[index].countEW++;\n    data[index].Gmin = Gmin;\n    data[index].Gmax = Gmax;\n    data[index].type = type;\n    data[index].element = element;\n    data[index].valueEW.push_back(value);\n    data[index].indexStructureEW.push_back(indexStructure);\n    data[index].indexAtomEW.push_back(indexAtom);\n\n    return;\n}\n\nvector<string> SymFncStatistics::getExtrapolationWarningLines() const\n{\n    vector<string> vs;\n    for (map<size_t, Container>::const_iterator it = data.begin();\n         it != data.end(); ++it)\n    {\n        SymFncStatistics::Container const& d = it->second;\n        for (size_t i = 0; i < d.valueEW.size(); ++i)\n        {\n            vs.push_back(strpr(\"### NNP EXTRAPOLATION WARNING ### \"\n                               \"STRUCTURE: %6zu ATOM: %9zu ELEMENT: %2s \"\n                               \"SYMFUNC: %4zu TYPE: %2zu VALUE: %10.3E \"\n                               \"MIN: %10.3E MAX: %10.3E\\n\",\n                               d.indexStructureEW[i],\n                               d.indexAtomEW[i],\n                               d.element.c_str(),\n                               it->first + 1,\n                               d.type,\n                               d.valueEW[i],\n                               d.Gmin,\n                               d.Gmax));\n        }\n    }\n\n    return vs;\n}\n\nsize_t SymFncStatistics::countExtrapolationWarnings() const\n{\n    size_t n = 0;\n\n    for (map<size_t, Container>::const_iterator it = data.begin();\n         it != data.end(); ++it)\n    {\n        n += it->second.countEW;\n    }\n\n    return n;\n}\n\nvoid SymFncStatistics::resetStatistics()\n{\n    for (map<size_t, Container>::iterator it = data.begin();\n         it != data.end(); ++it)\n    {\n        it->second.resetStatistics();\n    }\n\n    return;\n}\n\nvoid SymFncStatistics::resetExtrapolationWarnings()\n{\n    for (map<size_t, Container>::iterator it = data.begin();\n         it != data.end(); ++it)\n    {\n        it->second.resetExtrapolationWarnings();\n    }\n\n    return;\n}\n\nvoid SymFncStatistics::clear()\n{\n    data.clear();\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymFncStatistics.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMFNCSTATISTICS\n#define SYMFNCSTATISTICS\n\n#include <cstddef> // std::size_t\n#include <map>     // std::map\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nclass SymFncStatistics\n{\npublic:\n    /** Struct containing statistics gathered during symmetry function\n     * calculation.\n     */\n    struct Container\n    {\n        /// Counts total number of symmetry function evaluations.\n        std::size_t              count;\n        /// Counts extrapolation warnings.\n        std::size_t              countEW;\n        /// Symmetry function type.\n        std::size_t              type;\n        /// Minimum symmetry function value encountered.\n        double                   min;\n        /// Maximum symmetry function value encountered.\n        double                   max;\n        /// Minimum symmetry function from scaling data.\n        double                   Gmin;\n        /// Maximum symmetry function from scaling data.\n        double                   Gmax;\n        /// Sum of symmetry function values (to compute mean).\n        double                   sum;\n        /// Sum of squared symmetry function values (to compute sigma).\n        double                   sum2;\n        /// Element string of central atom of symmetry function.\n        std::string              element;\n        /// Structure indices for which extrapolation warnings occured.\n        std::vector<std::size_t> indexStructureEW;\n        /// Atom indices for which extrapolation warnings occured.\n        std::vector<std::size_t> indexAtomEW;\n        /// Out-of-bounds values causing extrapolation warnings.\n        std::vector<double>      valueEW;\n\n        /** Constructor, initializes contents to zero.\n         *\n         * Except min, max which are initialized to largest positive and\n         * negative double values, respectively.\n         */\n        Container();\n        /** Reset all values.\n         */\n        void reset();\n        /** Reset only statistics.\n         */\n        void resetStatistics();\n        /** Reset only extrapolation warnings.\n         */\n        void resetExtrapolationWarnings();\n    };\n\n    /// Whether statistics are gathered.\n    bool                             collectStatistics;\n    /// Whether extrapolation warnings are logged.\n    bool                             collectExtrapolationWarnings;\n    /// Whether to write out extrapolation warnings immediately as they occur.\n    bool                             writeExtrapolationWarnings;\n    /// Whether to raise an exception in case of extrapolation warnings.\n    bool                             stopOnExtrapolationWarnings;\n    /// Map for all symmetry functions containing all gathered information.\n    std::map<std::size_t, Container> data;\n\n    /** Constructor, initializes bool variables.\n     *\n     * Defaults are #collectStatistics = `false`, #collectExtrapolationWarnings\n     * = `false`, #writeExtrapolationWarnings = `false`,\n     * #stopOnExtrapolationWarnings = `false`.\n     */\n    SymFncStatistics();\n    /** Update symmetry function statistics with one value.\n     *\n     * @param[in] index Symmetry function index.\n     * @param[in] value Symmetry function value.\n     */\n    void         addValue(std::size_t index, double value);\n    /** Add extrapolation warning entry.\n     *\n     * @param[in] index Symmetry function index.\n     * @param[in] type Symmetry function type.\n     * @param[in] value Unscaled symmetry function value.\n     * @param[in] Gmin Minimum symmetry function value from scaling data.\n     * @param[in] Gmax Maximum symmetry function value from scaling data.\n     * @param[in] element Symmetry function element string.\n     * @param[in] indexStructure Index of structure of affected atom.\n     * @param[in] indexAtom Index of affected atom.\n     */\n    void         addExtrapolationWarning(std::size_t index,\n                                         std::size_t type,\n                                         double      value,\n                                         double      Gmin,\n                                         double      Gmax,\n                                         std::string element,\n                                         std::size_t indexStructure,\n                                         std::size_t indexAtom);\n    /** Get lines with extrapolation warnings.\n     *\n     * @return Extrapolation warning lines.\n     */\n    std::vector<\n    std::string> getExtrapolationWarningLines() const;\n    /** Count total number of extrapolation warnings.\n     *\n     * @return Sum of extrapolation warnings for all symmetry functions.\n     */\n    std::size_t  countExtrapolationWarnings() const;\n    /** Reset statistics for all symmetry functions at once.\n     */\n    void         resetStatistics();\n    /** Reset extrapolation warnings for all symmetry functions at once.\n     */\n    void         resetExtrapolationWarnings();\n    /** Completely erase database.\n     */\n    void         clear();\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrp.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrp.h\"\n#include \"utility.h\"\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrp::PrintFormat const SymGrp::printFormat = initializePrintFormat();\n\nSymGrp::PrintOrder const SymGrp::printOrder = initializePrintOrder();\n\nSymGrp::SymGrp(size_t type, ElementMap const& elementMap) :\n    type       (type      ),\n    elementMap (elementMap),\n    index      (0         ),\n    ec         (0         ),\n    convLength (1.0       )\n{\n    // Add standard common parameter IDs to set.\n    parametersCommon.insert(\"index\");\n    parametersCommon.insert(\"type\");\n    parametersCommon.insert(\"ec\");\n\n    // Add standard member parameter IDs to set.\n    parametersMember.insert(\"lineNumber\");\n    parametersMember.insert(\"mindex\");\n    parametersMember.insert(\"sfindex\");\n}\n\nSymGrp::PrintFormat const SymGrp::initializePrintFormat()\n{\n    PrintFormat pf;\n\n    pf[\"index\"]       = make_pair(\"%4zu\"  , string(4,  ' '));\n    pf[\"ec\"]          = make_pair(\"%2s\"   , string(2,  ' '));\n    pf[\"type\"]        = make_pair(\"%2zu\"  , string(2,  ' '));\n    pf[\"subtype\"]     = make_pair(\"%4s\"   , string(4,  ' '));\n    pf[\"e1\"]          = make_pair(\"%2s\"   , string(2,  ' '));\n    pf[\"e2\"]          = make_pair(\"%2s\"   , string(2,  ' '));\n    pf[\"eta\"]         = make_pair(\"%9.3E\" , string(9,  ' '));\n    pf[\"rs/rl\"]       = make_pair(\"%10.3E\", string(10, ' '));\n    pf[\"rc\"]          = make_pair(\"%10.3E\", string(10, ' '));\n    pf[\"angleLeft\"]   = make_pair(\"%6.1f\" , string(6,  ' '));\n    pf[\"angleRight\"]  = make_pair(\"%6.1f\" , string(6,  ' '));\n    pf[\"lambda\"]      = make_pair(\"%2.0f\" , string(2,  ' '));\n    pf[\"zeta\"]        = make_pair(\"%4.1f\" , string(4,  ' '));\n    pf[\"alpha\"]       = make_pair(\"%4.2f\" , string(4,  ' '));\n    pf[\"lineNumber\"]  = make_pair(\"%5zu\"  , string(5,  ' '));\n    pf[\"mindex\"]      = make_pair(\"%4zu\"  , string(4,  ' '));\n    pf[\"sfindex\"]     = make_pair(\"%4zu\"  , string(4,  ' '));\n    pf[\"calcexp\"]     = make_pair(\"%1d\"   , string(1,  ' '));\n\n    return pf;\n}\n\nSymGrp::PrintOrder const SymGrp::initializePrintOrder()\n{\n    vector<string> po;\n\n    po.push_back(\"index\"     );\n    po.push_back(\"ec\"        );\n    po.push_back(\"type\"      );\n    po.push_back(\"subtype\"   );\n    po.push_back(\"e1\"        );\n    po.push_back(\"e2\"        );\n    po.push_back(\"eta\"       );\n    po.push_back(\"rs/rl\"     );\n    po.push_back(\"rc\"        );\n    po.push_back(\"angleLeft\" );\n    po.push_back(\"angleRight\");\n    po.push_back(\"lambda\"    );\n    po.push_back(\"zeta\"      );\n    po.push_back(\"alpha\"     );\n    po.push_back(\"lineNumber\");\n    po.push_back(\"mindex\"    );\n    po.push_back(\"sfindex\"   );\n    po.push_back(\"calcexp\"   );\n\n    return po;\n}\n\nstring SymGrp::getPrintFormatCommon() const\n{\n    string s;\n\n    for (PrintOrder::const_iterator it = printOrder.begin();\n         it != printOrder.end(); ++it)\n    {\n        // If common parameter is present add format string.\n        if (parametersCommon.find(*it) != parametersCommon.end())\n        {\n            s += safeFind(printFormat, (*it)).first + ' ';\n        }\n        // Else if member parameter is present add star marker.\n        else if (parametersMember.find(*it) != parametersMember.end())\n        {\n            string t = safeFind(printFormat, (*it)).second;\n            if (t.size () > 0)  t.resize (t.size () - 1);\n            t += '*';\n            s += t + ' ';\n        }\n        // Else add just enough empty spaces.\n        else \n        {\n            s += safeFind(printFormat, (*it)).second + ' ';\n        }\n    }\n    // Remove extra space at the end.\n    if (s.size () > 0)  s.resize (s.size () - 1);\n    s += '\\n';\n\n    return s;\n}\n\nstring SymGrp::getPrintFormatMember() const\n{\n    string s;\n\n    for (PrintOrder::const_iterator it = printOrder.begin();\n         it != printOrder.end(); ++it)\n    {\n        // If common parameter is present add format string.\n        if (parametersMember.find(*it) != parametersMember.end())\n        {\n            s += safeFind(printFormat, (*it)).first + ' ';\n        }\n        // Else if member parameter is present add star marker.\n        else if (parametersCommon.find(*it) != parametersCommon.end())\n        {\n            string t = safeFind(printFormat, (*it)).second;\n            if (t.size () > 0)  t.resize (t.size () - 1);\n            t += '-';\n            s += t + ' ';\n        }\n        // Else add just enough empty spaces.\n        else \n        {\n            s += safeFind(printFormat, (*it)).second + ' ';\n        }\n    }\n    // Remove extra space at the end.\n    if (s.size () > 0)  s.resize (s.size () - 1);\n    s += '\\n';\n\n    return s;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrp.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRP_H\n#define SYMGRP_H\n\n#include \"ElementMap.h\"\n#include <cstddef> // std::size_t\n#include <set>     // std::set\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass SymFnc;\n\nclass SymGrp\n{\npublic:\n    /** Virtual destructor.\n     */\n    virtual ~SymGrp() {};\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const = 0;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const = 0;\n    /** Overload != operator.\n     */\n    bool         operator!=(SymGrp const& rhs) const;\n    /** Overload > operator.\n     */\n    bool         operator>(SymGrp const& rhs) const;\n    /** Overload <= operator.\n     */\n    bool         operator<=(SymGrp const& rhs) const;\n    /** Overload >= operator.\n     */\n    bool         operator>=(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to the members vector.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction) = 0;\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers() = 0;\n    /** Fill #scalingFactors with values from member symmetry functions.\n     */\n    virtual void setScalingFactors() = 0;\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const = 0;\n    /** Give symmetry function group parameters on multiple lines.\n     *\n     * @return Vector of string containing symmetry function parameters lines.\n     */\n    virtual std::vector<std::string>\n                 parameterLines() const = 0;\n    /** Set private #index member variable.\n     *\n     * @param[in] index Index number of symmetry function group.\n     */\n    void         setIndex(std::size_t index);\n    /** Get private #index member variable.\n     */\n    std::size_t  getIndex() const;\n    /** Get private #type member variable.\n     */\n    std::size_t  getType() const;\n    /** Get private #ec member variable.\n     */\n    std::size_t  getEc() const;\n\nprotected:\n    typedef std::map<std::string,\n                     std::pair<std::string, std::string> > PrintFormat;\n    typedef std::vector<std::string>                       PrintOrder;\n    /// Symmetry function type.\n    std::size_t                            type;\n    /// Copy of element map.\n    ElementMap                             elementMap;\n    /// Symmetry function group index.\n    std::size_t                            index;\n    /// Element index of center atom (common feature).\n    std::size_t                            ec;\n    /// Data set normalization length conversion factor.\n    double                                 convLength;\n    /// Vector containing indices of all member symmetry functions.\n    std::vector<size_t>                    memberIndex;\n    /// Scaling factors of all member symmetry functions.\n    std::vector<double>                    scalingFactors;\n    /// Set of common parameters IDs.\n    std::set<std::string>                  parametersCommon;\n    /// Set of common parameters IDs.\n    std::set<std::string>                  parametersMember;\n    /// Vector containing per-element indices of all member symmetry functions.\n    std::vector<std::vector<std::size_t> > memberIndexPerElement;\n    /// Map of parameter format strings and empty strings.\n    static PrintFormat const               printFormat;\n    /// Vector of parameters in order of printing.\n    static PrintOrder const                printOrder;\n\n    /** Constructor, sets type.\n     *\n     * @param[in] type Type of symmetry functions grouped.\n     * @param[in] elementMap Element Map used.\n     */\n    SymGrp(std::size_t type, ElementMap const& elementMap);\n    /** Initialize static print format map for all possible parameters.\n     */\n    static PrintFormat const initializePrintFormat();\n    /** Initialize static print order vector for all possible parameters.\n     */\n    static PrintOrder const  initializePrintOrder();\n    /** Get common parameter line format string.\n     *\n     * @return C-style format string.\n     */\n    std::string              getPrintFormatCommon() const;\n    /** Get member parameter line format string.\n     *\n     * @return C-style format string.\n     */\n    std::string              getPrintFormatMember() const;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline bool SymGrp::operator!=(SymGrp const& rhs) const\n{\n    return !((*this) == rhs);\n}\n\ninline bool SymGrp::operator>(SymGrp const& rhs) const\n{\n    return rhs < (*this);\n}\n\ninline bool SymGrp::operator<=(SymGrp const& rhs) const\n{\n    return !((*this) > rhs);\n}\n\ninline bool SymGrp::operator>=(SymGrp const& rhs) const\n{\n    return !((*this) < rhs);\n}\n\ninline void SymGrp::setIndex(size_t index)\n{\n    this->index = index;\n    return;\n}\n\ninline std::size_t SymGrp::getIndex() const { return index; }\ninline std::size_t SymGrp::getType() const { return type; }\ninline std::size_t SymGrp::getEc() const { return ec; }\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpBaseComp.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpBaseComp.h\"\n#include \"utility.h\"\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrpBaseComp::SymGrpBaseComp(size_t type, ElementMap const& elementMap) :\n    SymGrp(type, elementMap),\n    rmin(0.0),\n    rmax(0.0)\n{\n    parametersCommon.insert(\"rs/rl\");\n    parametersCommon.insert(\"rc\");\n\n    parametersMember.insert(\"subtype\");\n    parametersMember.insert(\"rs/rl\");\n    parametersMember.insert(\"rc\");\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpBaseComp.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPBASECOMP_H\n#define SYMGRPBASECOMP_H\n\n#include \"SymGrp.h\"\n#include \"CutoffFunction.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nclass SymGrpBaseComp : public SymGrp\n{\npublic:\n    /// Getter for #rmin.\n    double getRmin() const;\n    /// Getter for #rmax.\n    double getRmax() const;\n\nprotected:\n    /// Minimum radius within group.\n    double rmin;\n    /// Maximum radius within group.\n    double rmax;\n\n    /** Constructor, sets type.\n     *\n     * @param[in] type Type of symmetry functions grouped.\n     * @param[in] elementMap Element Map used.\n     */\n    SymGrpBaseComp(std::size_t type, ElementMap const& elementMap);\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline double SymGrpBaseComp::getRmin() const\n{\n    return rmin;\n}\n\ninline double SymGrpBaseComp::getRmax() const\n{\n    return rmax;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpBaseCompAng.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpBaseCompAng.h\"\n#include \"SymFncBaseCompAng.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\nusing namespace std;\nusing namespace nnp;\n\nSymGrpBaseCompAng::\nSymGrpBaseCompAng(size_t type, ElementMap const& elementMap) :\n    SymGrpBaseComp(type, elementMap),\n    e1(0),\n    e2(0)\n{\n    parametersCommon.insert(\"e1\");\n    parametersCommon.insert(\"e2\");\n\n    parametersMember.insert(\"angleLeft\");\n    parametersMember.insert(\"angleRight\");\n    parametersMember.insert(\"calcexp\");\n}\n\nvoid SymGrpBaseCompAng::setScalingFactors()\n{\n    vector<SymFncBaseCompAng const*> members = getMembers();\n    scalingFactors.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        scalingFactors.at(i) = members[i]->getScalingFactor();\n    }\n\n    return;\n}\n\nvector<string> SymGrpBaseCompAng::parameterLines() const\n{\n    vector<string> v;\n    vector<SymFncBaseCompAng const*> members = getMembers();\n\n    v.push_back(strpr(getPrintFormatCommon().c_str(),\n                      index + 1,\n                      elementMap[ec].c_str(),\n                      type,\n                      elementMap[e1].c_str(),\n                      elementMap[e2].c_str(),\n                      rmin / convLength,\n                      rmax / convLength));\n\n    for (size_t i = 0; i < members.size(); ++i)\n    {\n        v.push_back(strpr(getPrintFormatMember().c_str(),\n                          members[i]->getSubtype().c_str(),\n                          members[i]->getRl() / convLength,\n                          members[i]->getRc() / convLength,\n                          members[i]->getAngleLeft(),\n                          members[i]->getAngleRight(),\n                          members[i]->getLineNumber() + 1,\n                          i + 1,\n                          members[i]->getIndex() + 1,\n                          calculateComp[i]));\n    }\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpBaseCompAng.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPBASECOMPANG_H\n#define SYMGRPBASECOMPANG_H\n\n#include \"SymGrpBaseComp.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nclass ElementMap;\nclass SymFncBaseCompAng;\n\nclass SymGrpBaseCompAng : public SymGrpBaseComp\n{\npublic:\n    /** Fill #scalingFactors with values from member symmetry functions.\n     */\n    virtual void                     setScalingFactors();\n    /** Give symmetry function group parameters on multiple lines.\n     *\n     * @return Vector of string containing symmetry function parameters lines.\n     */\n    virtual std::vector<std::string> parameterLines() const;\n\nprotected:\n    /** Constructor, sets type.\n     *\n     * @param[in] type Type of symmetry functions grouped.\n     * @param[in] elementMap Element Map used.\n     */\n    SymGrpBaseCompAng(std::size_t type, ElementMap const& elementMap);\n    /** Get symmetry function members.\n     *\n     * @return Vector of pointers casted to base class.\n     */\n    virtual std::vector<SymFncBaseCompAng const*> getMembers() const = 0;\n\n    /// Element index of neighbor atom 1 (common feature).\n    std::size_t                e1;\n    /// Element index of neighbor atom 2 (common feature).\n    std::size_t                e2;\n    /// Vector indicating whether compact function needs to be recalculated.\n    std::vector<bool>          calculateComp;\n    /// Member rl.\n    std::vector<double>        mrl;\n    /// Member rc.\n    std::vector<double>        mrc;\n    /// Member angleLeft.\n    std::vector<double>        mal;\n    /// Member angleRight.\n    std::vector<double>        mar;\n#ifndef N2P2_NO_SF_CACHE\n    /// Member cache indices for actual neighbor element.\n    std::vector<std::vector<\n    std::vector<std::size_t>>> mci;\n#endif\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpBaseCompAngWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpBaseCompAngWeighted.h\"\n#include \"SymFncBaseCompAngWeighted.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\nusing namespace std;\nusing namespace nnp;\n\nSymGrpBaseCompAngWeighted::\nSymGrpBaseCompAngWeighted(size_t type, ElementMap const& elementMap) :\n    SymGrpBaseComp(type, elementMap)\n{\n    parametersMember.insert(\"angleLeft\");\n    parametersMember.insert(\"angleRight\");\n    parametersMember.insert(\"calcexp\");\n}\n\nvoid SymGrpBaseCompAngWeighted::setScalingFactors()\n{\n    vector<SymFncBaseCompAngWeighted const*> members = getMembers();\n    scalingFactors.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        scalingFactors.at(i) = members[i]->getScalingFactor();\n    }\n\n    return;\n}\n\nvector<string> SymGrpBaseCompAngWeighted::parameterLines() const\n{\n    vector<string> v;\n    vector<SymFncBaseCompAngWeighted const*> members = getMembers();\n\n    v.push_back(strpr(getPrintFormatCommon().c_str(),\n                      index + 1,\n                      elementMap[ec].c_str(),\n                      type,\n                      rmin / convLength,\n                      rmax / convLength));\n\n    for (size_t i = 0; i < members.size(); ++i)\n    {\n        v.push_back(strpr(getPrintFormatMember().c_str(),\n                          members[i]->getSubtype().c_str(),\n                          members[i]->getRl() / convLength,\n                          members[i]->getRc() / convLength,\n                          members[i]->getAngleLeft(),\n                          members[i]->getAngleRight(),\n                          members[i]->getLineNumber() + 1,\n                          i + 1,\n                          members[i]->getIndex() + 1,\n                          calculateComp[i]));\n    }\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpBaseCompAngWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPBASECOMPANGWEIGHTED_H\n#define SYMGRPBASECOMPANGWEIGHTED_H\n\n#include \"SymGrpBaseComp.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nclass ElementMap;\nclass SymFncBaseCompAngWeighted;\n\nclass SymGrpBaseCompAngWeighted : public SymGrpBaseComp\n{\npublic:\n    /** Fill #scalingFactors with values from member symmetry functions.\n     */\n    virtual void                     setScalingFactors();\n    /** Give symmetry function group parameters on multiple lines.\n     *\n     * @return Vector of string containing symmetry function parameters lines.\n     */\n    virtual std::vector<std::string> parameterLines() const;\n\nprotected:\n    /** Constructor, sets type.\n     *\n     * @param[in] type Type of symmetry functions grouped.\n     * @param[in] elementMap Element Map used.\n     */\n    SymGrpBaseCompAngWeighted(std::size_t type, ElementMap const& elementMap);\n    /** Get symmetry function members.\n     *\n     * @return Vector of pointers casted to base class.\n     */\n    virtual\n    std::vector<SymFncBaseCompAngWeighted const*> getMembers() const = 0;\n\n    /// Vector indicating whether compact function needs to be recalculated.\n    std::vector<bool>          calculateComp;\n    /// Member rl.\n    std::vector<double>        mrl;\n    /// Member rc.\n    std::vector<double>        mrc;\n    /// Member angleLeft.\n    std::vector<double>        mal;\n    /// Member angleRight.\n    std::vector<double>        mar;\n#ifndef N2P2_NO_SF_CACHE\n    /// Member cache indices for actual neighbor element.\n    std::vector<std::vector<\n    std::vector<std::size_t>>> mci;\n#endif\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpBaseCutoff.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpBaseCutoff.h\"\n#include \"utility.h\"\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrpBaseCutoff::SymGrpBaseCutoff(size_t type, ElementMap const& elementMap) :\n    SymGrp(type, elementMap),\n    rc         (0.0                    ),\n    cutoffAlpha(0.0                    ),\n    subtype    (\"ct0\"                  ),\n    cutoffType (CutoffFunction::CT_HARD)\n{\n    // Add standard common parameter IDs to set.\n    parametersCommon.insert(\"subtype\");\n    parametersCommon.insert(\"rc\");\n    parametersCommon.insert(\"alpha\");\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpBaseCutoff.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPBASECUTOFF_H\n#define SYMGRPBASECUTOFF_H\n\n#include \"SymGrp.h\"\n#include \"CutoffFunction.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nclass SymGrpBaseCutoff : public SymGrp\n{\npublic:\n    /// Get private #rc member variable.\n    double getRc() const;\n\nprotected:\n    /// Cutoff radius @f$r_c@f$ (common feature).\n    double                     rc;\n    /// Cutoff function parameter @f$\\alpha@f$ (common feature).\n    double                     cutoffAlpha;\n    /// Subtype string (specifies cutoff type) (common feature).\n    std::string                subtype;\n    /// Cutoff function used by this symmetry function group.\n    CutoffFunction             fc;\n    /// Cutoff type used by this symmetry function group (common feature).\n    CutoffFunction::CutoffType cutoffType;\n\n    /** Constructor, sets type.\n     *\n     * @param[in] type Type of symmetry functions grouped.\n     * @param[in] elementMap Element Map used.\n     */\n    SymGrpBaseCutoff(std::size_t type, ElementMap const& elementMap);\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpBaseExpAng.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpBaseExpAng.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncBaseExpAng.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrpBaseExpAng::SymGrpBaseExpAng(size_t type, ElementMap const& elementMap) :\n    SymGrpBaseCutoff(type, elementMap),\n    e1(0),\n    e2(0)\n{\n    parametersCommon.insert(\"e1\");\n    parametersCommon.insert(\"e2\");\n\n    parametersMember.insert(\"eta\");\n    parametersMember.insert(\"rs/rl\");\n    parametersMember.insert(\"lambda\");\n    parametersMember.insert(\"zeta\");\n    parametersMember.insert(\"calcexp\");\n}\n\nvoid SymGrpBaseExpAng::setScalingFactors()\n{\n    vector<SymFncBaseExpAng const*> members = getMembers();\n\n    scalingFactors.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        scalingFactors.at(i) = members[i]->getScalingFactor();\n        factorNorm.at(i) *= scalingFactors.at(i);\n    }\n\n    return;\n}\n\nvector<string> SymGrpBaseExpAng::parameterLines() const\n{\n    vector<string> v;\n    vector<SymFncBaseExpAng const*> members = getMembers();\n\n    v.push_back(strpr(getPrintFormatCommon().c_str(),\n                      index + 1,\n                      elementMap[ec].c_str(),\n                      type,\n                      subtype.c_str(),\n                      elementMap[e1].c_str(),\n                      elementMap[e2].c_str(),\n                      rc / convLength,\n                      cutoffAlpha));\n\n    for (size_t i = 0; i < members.size(); ++i)\n    {\n        v.push_back(strpr(getPrintFormatMember().c_str(),\n                          members[i]->getEta() * convLength * convLength,\n                          members[i]->getRs() / convLength,\n                          members[i]->getLambda(),\n                          members[i]->getZeta(),\n                          members[i]->getLineNumber() + 1,\n                          i + 1,\n                          members[i]->getIndex() + 1,\n                          (int)calculateExp[i]));\n    }\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpBaseExpAng.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPBASEEXPANG_H\n#define SYMGRPBASEEXPANG_H\n\n#include \"SymGrpBaseCutoff.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nclass ElementMap;\nclass SymFncBaseExpAng;\n\nclass SymGrpBaseExpAng : public SymGrpBaseCutoff\n{\npublic:\n    /** Fill #scalingFactors with values from member symmetry functions.\n     */\n    virtual void                     setScalingFactors();\n    /** Give symmetry function group parameters on multiple lines.\n     *\n     * @return Vector of string containing symmetry function parameters lines.\n     */\n    virtual std::vector<std::string> parameterLines() const;\n\nprotected:\n    /** Constructor, sets type.\n     *\n     * @param[in] type Type of symmetry functions grouped.\n     * @param[in] elementMap Element Map used.\n     */\n    SymGrpBaseExpAng(std::size_t type, ElementMap const& elementMap);\n    /** Get symmetry function members.\n     *\n     * @return Vector of pointers casted to base class.\n     */\n    virtual std::vector<SymFncBaseExpAng const*> getMembers() const = 0;\n\n    /// Element index of neighbor atom 1 (common feature).\n    std::size_t         e1;\n    /// Element index of neighbor atom 2 (common feature).\n    std::size_t         e2;\n    /// Vector indicating whether exponential term needs to be calculated.\n    std::vector<bool>   calculateExp;\n    /// Vector containing precalculated normalizing factor for each zeta.\n    std::vector<double> factorNorm;\n    /// Vector containing precalculated normalizing factor for derivatives.\n    std::vector<double> factorDeriv;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<bool>   useIntegerPow;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<int>    zetaInt;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double> eta;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double> zeta;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double> lambda;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double> zetaLambda;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double> rs;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpCompAngn.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpCompAngn.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncCompAngn.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\nusing namespace std;\nusing namespace nnp;\n\nSymGrpCompAngn::\nSymGrpCompAngn(ElementMap const& elementMap) :\n    SymGrpBaseCompAng(21, elementMap)\n{\n}\n\nbool SymGrpCompAngn::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymGrpCompAngn const& c = dynamic_cast<SymGrpCompAngn const&>(rhs);\n    if (e1 != c.e1) return false;\n    if (e2 != c.e2) return false;\n    return true;\n}\n\nbool SymGrpCompAngn::operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymGrpCompAngn const& c = dynamic_cast<SymGrpCompAngn const&>(rhs);\n    if      (e1 < c.e1) return true;\n    else if (e1 > c.e1) return false;\n    if      (e2 < c.e2) return true;\n    else if (e2 > c.e2) return false;\n    return false;\n}\n\nbool SymGrpCompAngn::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncCompAngn const* sf =\n        dynamic_cast<SymFncCompAngn const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        ec          = sf->getEc();\n        e1          = sf->getE1();\n        e2          = sf->getE2();\n        convLength  = sf->getConvLength();\n    }\n\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getE1()          != e1         ) return false;\n    if (sf->getE2()          != e2         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    if (sf->getRl() <= 0.0) rmin = 0.0;\n    else rmin = min( rmin, sf->getRl() );\n    rmax = max( rmax, sf->getRc() );\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpCompAngn::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncCompAngn const>);\n\n    mrl.resize(members.size(), 0.0);\n    mrc.resize(members.size(), 0.0);\n    mal.resize(members.size(), 0.0);\n    mar.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        mrl.at(i) = members[i]->getRl();\n        mrc.at(i) = members[i]->getRc();\n        mal.at(i) = members[i]->getAngleLeft() * M_PI / 180.0;\n        mar.at(i) = members[i]->getAngleRight() * M_PI / 180.0;\n        memberIndex.push_back(members[i]->getIndex());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n        if (i == 0)\n        {\n            calculateComp.push_back(true);\n        }\n        else\n        {\n            if ( members[i - 1]->getRc() != members[i]->getRc() ||\n                 members[i - 1]->getRl() != members[i]->getRl() )\n            {\n                calculateComp.push_back(true);\n            }\n            else\n            {\n                calculateComp.push_back(false);\n            }\n        }\n    }\n\n#ifndef N2P2_NO_SF_CACHE\n    mci.resize(members.size());\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        mci.at(k) = members.at(k)->getCacheIndices();\n    }\n#endif\n\n    return;\n}\n\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minimized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpCompAngn::calculate(Atom& atom, bool const derivatives) const\n{\n    double* result = new double[members.size()];\n    double* radij  = new double[members.size()];\n    double* dradij = new double[members.size()];\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        result[l] = 0.0;\n        radij[l]  = 0.0;\n        dradij[l] = 0.0;\n    }\n\n    double r2min = rmin * rmin;\n    double r2max = rmax * rmax;\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n\n        if ((e1 == nej || e2 == nej) && rij < rmax && rij > rmin)\n        {\n            // Precalculate the radial part for ij\n            // Supposedly saves quite a number of operations\n            for (size_t l = 0; l < members.size(); ++l)\n            {\n                if (rij > mrl[l] && rij < mrc[l])\n                {\n                    SymFncCompAngn const& sf = *(members[l]);\n#ifndef N2P2_NO_SF_CACHE\n                    if (mci[l][nej].size() == 0)\n                    {\n                        sf.getCompactRadial(rij, radij[l], dradij[l]);\n                    }\n                    else\n                    {\n                        double& crad = nj.cache[mci[l][nej][0]];\n                        double& cdrad = nj.cache[mci[l][nej][1]];\n                        if (crad < 0) sf.getCompactRadial(rij, crad, cdrad);\n                        radij[l] = crad;\n                        dradij[l] = cdrad;\n                    }\n#else\n                    sf.getCompactRadial(rij, radij[l], dradij[l]);\n#endif\n                }\n                else radij[l] = 0.0;\n            }\n\n            // SIMPLE EXPRESSIONS:\n            //Vec3D drij(atom.neighbors[j].dr);\n            double const* const dr1 = nj.dr.r;\n\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                if ((e1 == nej && e2 == nek) ||\n                    (e2 == nej && e1 == nek))\n                {\n                    double const rik = nk.d;\n                    if (rik < rmax && rik > rmin)\n                    {\n                        // SIMPLE EXPRESSIONS:\n                        //Vec3D drik(atom.neighbors[k].dr);\n                        //Vec3D drjk = drik - drij;\n                        double const* const dr2 = nk.dr.r;\n                        double const dr30 = dr2[0] - dr1[0];\n                        double const dr31 = dr2[1] - dr1[1];\n                        double const dr32 = dr2[2] - dr1[2];\n\n                        double rjk = dr30 * dr30\n                                   + dr31 * dr31\n                                   + dr32 * dr32;\n                        if ((rjk >= r2max) || (rjk <= r2min)) continue;\n                        rjk = sqrt(rjk);\n\n                        // Energy calculation.\n                        double const rinvijik = 1.0 / (rij * rik);\n                        double const costijk = (dr1[0] * dr2[0] +\n                                                dr1[1] * dr2[1] +\n                                                dr1[2] * dr2[2]) * rinvijik;\n\n                        // By definition, our polynomial is zero at 0 and 180 deg.\n                        // Therefore, skip the whole rest which might yield some NaN\n                        if (costijk <= -1.0 || costijk >= 1.0) continue;\n\n                        double const acostijk = acos(costijk);\n\n                        double const rinvij   = rinvijik * rik;\n                        double const rinvik   = rinvijik * rij;\n                        double const rinvjk   = 1.0 / rjk;\n                        double const phiijik0 = rinvij\n                                              * (rinvik - rinvij * costijk);\n                        double const phiikij0 = rinvik\n                                              * (rinvij - rinvik * costijk);\n                        double dacostijk = 0.0;\n                        if (derivatives)\n                        {\n                            dacostijk = -1.0 / sqrt(1.0 - costijk * costijk);\n                        }\n\n                        bool skip = false;\n                        double ang;\n                        double dang;\n                        double radik;\n                        double dradik;\n                        double radjk;\n                        double dradjk;\n\n                        for (size_t l = 0; l < members.size(); ++l)\n                        {\n                            // Break conditions.\n                            if (radij[l] == 0.0 ||\n                                rik <= mrl[l] || rik >= mrc[l] ||\n                                rjk <= mrl[l] || rjk >= mrc[l] ||\n                                acostijk <= mal[l] || acostijk >= mar[l])\n                            {\n                                // Record if skipped.\n                                skip = true;\n                                continue;\n                            }\n\n                            SymFncCompAngn const& sf = *(members[l]);\n#ifndef N2P2_NO_SF_CACHE\n                            if (mci[l][nek].size() == 0)\n                            {\n                                sf.getCompactRadial(rik, radik, dradik);\n                            }\n                            else\n                            {\n                                double& crad = nk.cache[mci[l][nek][0]];\n                                double& cdrad = nk.cache[mci[l][nek][1]];\n                                if (crad < 0) sf.getCompactRadial(rik, crad, cdrad);\n                                radik = crad;\n                                dradik = cdrad;\n                            }\n#else\n                            sf.getCompactRadial(rik, radik, dradik);\n#endif\n                            // Calculate anyway if skipped previously.\n                            if (calculateComp[l] || skip)\n                            {\n                                sf.getCompactRadial(rjk, radjk, dradjk);\n                                skip = false;\n                            }\n\n                            sf.getCompactAngle(acostijk, ang, dang);\n\n                            double rad = radij[l] * radik * radjk;\n                            result[l] += rad * ang;\n            \n                            // Force calculation.\n                            if (!derivatives) continue;\n\n                            dang *= dacostijk;\n                            double const phiijik = phiijik0 * dang;\n                            double const phiikij = phiikij0 * dang;\n                            double const psiijik = rinvijik * dang;\n\n                            double const chiij =  rinvij * dradij[l]\n                                               *  radik  * radjk;\n                            double const chiik =  rinvik * radij[l]\n                                               *  dradik * radjk;\n                            double const chijk = -rinvjk * radij[l]\n                                               *  radik  * dradjk;\n\n                            double p1;\n                            double p2;\n                            double p3;\n\n                            if (dang != 0.0 && rad != 0.0)\n                            {\n                                rad  *= scalingFactors[l];\n                                ang  *= scalingFactors[l];\n                                p1 = rad * phiijik +  ang * chiij;\n                                p2 = rad * phiikij +  ang * chiik;\n                                p3 = rad * psiijik +  ang * chijk;\n                            }\n                            else if (ang != 0.0)\n                            {\n                                ang *= scalingFactors[l];\n\n                                p1 = ang * chiij;\n                                p2 = ang * chiik;\n                                p3 = ang * chijk;\n                            }\n                            else continue;\n\n                            // SIMPLE EXPRESSIONS:\n                            // Save force contributions in Atom storage.\n                            //atom.dGdr[memberIndex[l]] += p1 * drij\n                            //                           + p2 * drik;\n                            //atom.neighbors[j].\n                            //    dGdr[memberIndex[l]] -= p1 * drij\n                            //                          + p3 * drjk;\n                            //atom.neighbors[k].\n                            //    dGdr[memberIndex[l]] -= p2 * drik\n                            //                          - p3 * drjk;\n\n                            double const p1drijx = p1 * dr1[0];\n                            double const p1drijy = p1 * dr1[1];\n                            double const p1drijz = p1 * dr1[2];\n\n                            double const p2drikx = p2 * dr2[0];\n                            double const p2driky = p2 * dr2[1];\n                            double const p2drikz = p2 * dr2[2];\n\n                            double const p3drjkx = p3 * dr30;\n                            double const p3drjky = p3 * dr31;\n                            double const p3drjkz = p3 * dr32;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            size_t li = memberIndex[l];\n#else\n                            size_t const li = memberIndex[l];\n#endif\n                            double* dGdr = atom.dGdr[li].r;\n                            dGdr[0] += p1drijx + p2drikx;\n                            dGdr[1] += p1drijy + p2driky;\n                            dGdr[2] += p1drijz + p2drikz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            li = memberIndexPerElement[l][nej];\n#endif\n                            dGdr = nj.dGdr[li].r;\n                            dGdr[0] -= p1drijx + p3drjkx;\n                            dGdr[1] -= p1drijy + p3drjky;\n                            dGdr[2] -= p1drijz + p3drjkz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            li = memberIndexPerElement[l][nek];\n#endif\n                            dGdr = nk.dGdr[li].r;\n                            dGdr[0] -= p2drikx - p3drjkx;\n                            dGdr[1] -= p2driky - p3drjky;\n                            dGdr[2] -= p2drikz - p3drjkz;\n                        } // l\n                    } // rik <= rc\n                } // elem\n            } // k\n        } // rij <= rc\n    } // j\n\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        atom.G[memberIndex[l]] = members[l]->scale(result[l]);\n    }\n\n    delete[] result;\n    delete[] radij;\n    delete[] dradij;\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpCompAngn.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPCOMPANGN_H\n#define SYMGRPCOMPANGN_H\n\n#include \"SymGrpBaseCompAng.h\"\n#include \"SymFncCompAngn.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\n\n/** Narrow angular symmetry function with compact support (type 21)\n *\n * @f[\n   G^{21}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n              C(r_{ij}, r_l, r_c)\n              C(r_{ik}, r_l, r_c)\n              C(r_{jk}, r_l, r_c)\n              C(\\theta_{ijk}, \\theta_l, \\theta_r),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$.\n *\n * Common features:\n * - element of central atom\n * - element of neighbor atom 1\n * - element of neighbor atom 2\n */\nclass SymGrpCompAngn : public SymGrpBaseCompAng\n{\npublic:\n    /** Constructor, sets type = 21\n     */\n    SymGrpCompAngn(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n\nprivate:\n    /** Get symmetry function members.\n     *\n     * @return Vector of pointers casted to base class.\n     */\n    virtual std::vector<SymFncBaseCompAng const*> getMembers() const;\n\n    /// Vector of all group member pointers.\n    std::vector<SymFncCompAngn const*> members;\n};\n\ninline std::vector<SymFncBaseCompAng const*> SymGrpCompAngn::getMembers() const\n{\n    std::vector<SymFncBaseCompAng const*> cast;\n\n    for (auto p : members)\n    {\n        cast.push_back(dynamic_cast<SymFncBaseCompAng const*>(p));\n    }\n\n    return cast;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpCompAngnWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpCompAngnWeighted.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncCompAngnWeighted.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\nusing namespace std;\nusing namespace nnp;\n\nSymGrpCompAngnWeighted::\nSymGrpCompAngnWeighted(ElementMap const& elementMap) :\n    SymGrpBaseCompAngWeighted(24, elementMap)\n{\n}\n\nbool SymGrpCompAngnWeighted::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    return true;\n}\n\nbool SymGrpCompAngnWeighted::operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    return false;\n}\n\nbool SymGrpCompAngnWeighted::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncCompAngnWeighted const* sf =\n        dynamic_cast<SymFncCompAngnWeighted const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        ec          = sf->getEc();\n        convLength  = sf->getConvLength();\n    }\n\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    if (sf->getRl() <= 0.0) rmin = 0.0;\n    else rmin = min( rmin, sf->getRl() );\n    rmax = max( rmax, sf->getRc() );\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpCompAngnWeighted::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncCompAngnWeighted const>);\n\n    mrl.resize(members.size(), 0.0);\n    mrc.resize(members.size(), 0.0);\n    mal.resize(members.size(), 0.0);\n    mar.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        mrl.at(i) = members[i]->getRl();\n        mrc.at(i) = members[i]->getRc();\n        mal.at(i) = members[i]->getAngleLeft() * M_PI / 180.0;\n        mar.at(i) = members[i]->getAngleRight() * M_PI / 180.0;\n        memberIndex.push_back(members[i]->getIndex());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n        if (i == 0)\n        {\n            calculateComp.push_back(true);\n        }\n        else\n        {\n            if ( members[i - 1]->getRc() != members[i]->getRc() ||\n                 members[i - 1]->getRl() != members[i]->getRl() )\n            {\n                calculateComp.push_back(true);\n            }\n            else\n            {\n                calculateComp.push_back(false);\n            }\n        }\n    }\n\n#ifndef N2P2_NO_SF_CACHE\n    mci.resize(members.size());\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        mci.at(k) = members.at(k)->getCacheIndices();\n    }\n#endif\n\n    return;\n}\n\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minimized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpCompAngnWeighted::\ncalculate(Atom& atom, bool const derivatives) const\n{\n    double* result = new double[members.size()];\n    double* radij  = new double[members.size()];\n    double* dradij = new double[members.size()];\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        result[l] = 0.0;\n        radij[l]  = 0.0;\n        dradij[l] = 0.0;\n    }\n\n    double r2min = rmin * rmin;\n    double r2max = rmax * rmax;\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n\n        if (rij < rmax && rij > rmin)\n        {\n            // Precalculate the radial part for ij\n            // Supposedly saves quite a number of operations\n            for (size_t l = 0; l < members.size(); ++l)\n            {\n                if (rij > mrl[l] && rij < mrc[l])\n                {\n                    SymFncCompAngnWeighted const& sf = *(members[l]);\n#ifndef N2P2_NO_SF_CACHE\n                    if (mci[l][nej].size() == 0)\n                    {\n                        sf.getCompactRadial(rij, radij[l], dradij[l]);\n                    }\n                    else\n                    {\n                        double& crad = nj.cache[mci[l][nej][0]];\n                        double& cdrad = nj.cache[mci[l][nej][1]];\n                        if (crad < 0) sf.getCompactRadial(rij, crad, cdrad);\n                        radij[l] = crad;\n                        dradij[l] = cdrad;\n                    }\n#else\n                    sf.getCompactRadial(rij, radij[l], dradij[l]);\n#endif\n                }\n                else radij[l] = 0.0;\n            }\n\n            // SIMPLE EXPRESSIONS:\n            //Vec3D drij(atom.neighbors[j].dr);\n            double const* const dr1 = nj.dr.r;\n\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                double const rik = nk.d;\n                if (rik < rmax && rik > rmin)\n                {\n                    // SIMPLE EXPRESSIONS:\n                    //Vec3D drik(atom.neighbors[k].dr);\n                    //Vec3D drjk = drik - drij;\n                    double const* const dr2 = nk.dr.r;\n                    double const dr30 = dr2[0] - dr1[0];\n                    double const dr31 = dr2[1] - dr1[1];\n                    double const dr32 = dr2[2] - dr1[2];\n\n                    double rjk = dr30 * dr30\n                               + dr31 * dr31\n                               + dr32 * dr32;\n                    if ((rjk >= r2max) || (rjk <= r2min)) continue;\n                    rjk = sqrt(rjk);\n\n                    // Energy calculation.\n                    double const rinvijik = 1.0 / (rij * rik);\n                    double const costijk = (dr1[0] * dr2[0] +\n                                            dr1[1] * dr2[1] +\n                                            dr1[2] * dr2[2]) * rinvijik;\n\n                    // By definition, our polynomial is zero at 0 and 180 deg.\n                    // Therefore, skip the whole rest which might yield some NaN\n                    if (costijk <= -1.0 || costijk >= 1.0) continue;\n\n                    double const acostijk = acos(costijk);\n\n                    double const rinvij   = rinvijik * rik;\n                    double const rinvik   = rinvijik * rij;\n                    double const rinvjk   = 1.0 / rjk;\n                    double const phiijik0 = rinvij\n                                          * (rinvik - rinvij * costijk);\n                    double const phiikij0 = rinvik\n                                          * (rinvij - rinvik * costijk);\n                    double dacostijk = 0.0;\n                    if (derivatives)\n                    {\n                        dacostijk = -1.0 / sqrt(1.0 - costijk * costijk);\n                    }\n\n                    bool skip = false;\n                    double ang;\n                    double dang;\n                    double radik;\n                    double dradik;\n                    double radjk;\n                    double dradjk;\n\n                    for (size_t l = 0; l < members.size(); ++l)\n                    {\n                        // Break conditions.\n                        if (radij[l] == 0.0 ||\n                            rik <= mrl[l] || rik >= mrc[l] ||\n                            rjk <= mrl[l] || rjk >= mrc[l] ||\n                            acostijk <= mal[l] || acostijk >= mar[l])\n                        {\n                            // Record if skipped.\n                            skip = true;\n                            continue;\n                        }\n\n                        SymFncCompAngnWeighted const& sf = *(members[l]);\n#ifndef N2P2_NO_SF_CACHE\n                        if (mci[l][nek].size() == 0)\n                        {\n                            sf.getCompactRadial(rik, radik, dradik);\n                        }\n                        else\n                        {\n                            double& crad = nk.cache[mci[l][nek][0]];\n                            double& cdrad = nk.cache[mci[l][nek][1]];\n                            if (crad < 0) sf.getCompactRadial(rik, crad, cdrad);\n                            radik = crad;\n                            dradik = cdrad;\n                        }\n#else\n                        sf.getCompactRadial(rik, radik, dradik);\n#endif\n                        // Calculate anyway if skipped previously.\n                        if (calculateComp[l] || skip)\n                        {\n                            sf.getCompactRadial(rjk, radjk, dradjk);\n                            skip = false;\n                        }\n\n                        sf.getCompactAngle(acostijk, ang, dang);\n\n                        double const z = elementMap.atomicNumber(nej)\n                                       * elementMap.atomicNumber(nek);\n                        ang *= z;\n                        double rad = radij[l] * radik * radjk;\n                        result[l] += rad * ang;\n            \n                        // Force calculation.\n                        if (!derivatives) continue;\n\n                        dang *= dacostijk;\n                        double const phiijik = phiijik0 * dang;\n                        double const phiikij = phiikij0 * dang;\n                        double const psiijik = rinvijik * dang;\n\n                        double const chiij =  rinvij * dradij[l]\n                                           *  radik  * radjk;\n                        double const chiik =  rinvik * radij[l]\n                                           *  dradik * radjk;\n                        double const chijk = -rinvjk * radij[l]\n                                           *  radik  * dradjk;\n\n                        double p1;\n                        double p2;\n                        double p3;\n\n                        if (dang != 0.0 && rad != 0.0)\n                        {\n                            rad  *= scalingFactors[l] * z;\n                            ang  *= scalingFactors[l];\n                            p1 = rad * phiijik +  ang * chiij;\n                            p2 = rad * phiikij +  ang * chiik;\n                            p3 = rad * psiijik +  ang * chijk;\n                        }\n                        else if (ang != 0.0)\n                        {\n                            ang *= scalingFactors[l];\n\n                            p1 = ang * chiij;\n                            p2 = ang * chiik;\n                            p3 = ang * chijk;\n                        }\n                        else continue;\n\n                        // SIMPLE EXPRESSIONS:\n                        // Save force contributions in Atom storage.\n                        //atom.dGdr[memberIndex[l]] += p1 * drij\n                        //                           + p2 * drik;\n                        //atom.neighbors[j].\n                        //    dGdr[memberIndex[l]] -= p1 * drij\n                        //                          + p3 * drjk;\n                        //atom.neighbors[k].\n                        //    dGdr[memberIndex[l]] -= p2 * drik\n                        //                          - p3 * drjk;\n\n                        double const p1drijx = p1 * dr1[0];\n                        double const p1drijy = p1 * dr1[1];\n                        double const p1drijz = p1 * dr1[2];\n\n                        double const p2drikx = p2 * dr2[0];\n                        double const p2driky = p2 * dr2[1];\n                        double const p2drikz = p2 * dr2[2];\n\n                        double const p3drjkx = p3 * dr30;\n                        double const p3drjky = p3 * dr31;\n                        double const p3drjkz = p3 * dr32;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                        size_t li = memberIndex[l];\n#else\n                        size_t const li = memberIndex[l];\n#endif\n                        double* dGdr = atom.dGdr[li].r;\n                        dGdr[0] += p1drijx + p2drikx;\n                        dGdr[1] += p1drijy + p2driky;\n                        dGdr[2] += p1drijz + p2drikz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                        li = memberIndexPerElement[l][nej];\n#endif\n                        dGdr = nj.dGdr[li].r;\n                        dGdr[0] -= p1drijx + p3drjkx;\n                        dGdr[1] -= p1drijy + p3drjky;\n                        dGdr[2] -= p1drijz + p3drjkz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                        li = memberIndexPerElement[l][nek];\n#endif\n                        dGdr = nk.dGdr[li].r;\n                        dGdr[0] -= p2drikx - p3drjkx;\n                        dGdr[1] -= p2driky - p3drjky;\n                        dGdr[2] -= p2drikz - p3drjkz;\n                    } // l\n                } // rik <= rc\n            } // k\n        } // rij <= rc\n    } // j\n\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        atom.G[memberIndex[l]] = members[l]->scale(result[l]);\n    }\n\n    delete[] result;\n    delete[] radij;\n    delete[] dradij;\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpCompAngnWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPCOMPANGNWEIGHTED_H\n#define SYMGRPCOMPANGNWEIGHTED_H\n\n#include \"SymGrpBaseCompAngWeighted.h\"\n#include \"SymFncCompAngnWeighted.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\n\n/** Weighted narrow angular symmetry function with compact support (type 24)\n *\n * @f[\n   G^{24}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n              Z_j Z_k\n              C(r_{ij}, r_l, r_c)\n              C(r_{ik}, r_l, r_c)\n              C(r_{jk}, r_l, r_c)\n              C(\\theta_{ijk}, \\theta_l, \\theta_r),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$. @f$Z_j@f$ is defined\n * as the atomic number of the neighbor atom @f$j@f$.\n *\n * Common features:\n * - element of central atom\n */\nclass SymGrpCompAngnWeighted : public SymGrpBaseCompAngWeighted\n{\npublic:\n    /** Constructor, sets type = 24\n     */\n    SymGrpCompAngnWeighted(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n\nprivate:\n    /** Get symmetry function members.\n     *\n     * @return Vector of pointers casted to base class.\n     */\n    virtual std::vector<SymFncBaseCompAngWeighted const*> getMembers() const;\n\n    /// Vector of all group member pointers.\n    std::vector<SymFncCompAngnWeighted const*> members;\n};\n\ninline std::vector<SymFncBaseCompAngWeighted const*>\n                                     SymGrpCompAngnWeighted::getMembers() const\n{\n    std::vector<SymFncBaseCompAngWeighted const*> cast;\n\n    for (auto p : members)\n    {\n        cast.push_back(dynamic_cast<SymFncBaseCompAngWeighted const*>(p));\n    }\n\n    return cast;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpCompAngw.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpCompAngw.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncCompAngw.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\nusing namespace std;\nusing namespace nnp;\n\nSymGrpCompAngw::\nSymGrpCompAngw(ElementMap const& elementMap) :\n    SymGrpBaseCompAng(22, elementMap)\n{\n}\n\nbool SymGrpCompAngw::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymGrpCompAngw const& c = dynamic_cast<SymGrpCompAngw const&>(rhs);\n    if (e1 != c.e1) return false;\n    if (e2 != c.e2) return false;\n    return true;\n}\n\nbool SymGrpCompAngw::operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymGrpCompAngw const& c = dynamic_cast<SymGrpCompAngw const&>(rhs);\n    if      (e1 < c.e1) return true;\n    else if (e1 > c.e1) return false;\n    if      (e2 < c.e2) return true;\n    else if (e2 > c.e2) return false;\n    return false;\n}\n\nbool SymGrpCompAngw::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncCompAngw const* sf =\n        dynamic_cast<SymFncCompAngw const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        ec          = sf->getEc();\n        e1          = sf->getE1();\n        e2          = sf->getE2();\n        convLength  = sf->getConvLength();\n    }\n\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getE1()          != e1         ) return false;\n    if (sf->getE2()          != e2         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    if (sf->getRl() <= 0.0) rmin = 0.0;\n    else rmin = min( rmin, sf->getRl() );\n    rmax = max( rmax, sf->getRc() );\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpCompAngw::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncCompAngw const>);\n\n    mrl.resize(members.size(), 0.0);\n    mrc.resize(members.size(), 0.0);\n    mal.resize(members.size(), 0.0);\n    mar.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        mrl.at(i) = members[i]->getRl();\n        mrc.at(i) = members[i]->getRc();\n        mal.at(i) = members[i]->getAngleLeft() * M_PI / 180.0;\n        mar.at(i) = members[i]->getAngleRight() * M_PI / 180.0;\n        memberIndex.push_back(members[i]->getIndex());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n        calculateComp.push_back(true);\n    }\n\n#ifndef N2P2_NO_SF_CACHE\n    mci.resize(members.size());\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        mci.at(k) = members.at(k)->getCacheIndices();\n    }\n#endif\n\n    return;\n}\n\n// TODO: Check if untested optimizations work correctly!\n// TODO: Eventually change SF ordering, so angular compact function can be\n//       cached.\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minimized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpCompAngw::calculate(Atom& atom, bool const derivatives) const\n{\n    double* result = new double[members.size()];\n    double* radij  = new double[members.size()];\n    double* dradij = new double[members.size()];\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        result[l] = 0.0;\n        radij[l]  = 0.0;\n        dradij[l] = 0.0;\n    }\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n\n        if ((e1 == nej || e2 == nej) && rij < rmax && rij > rmin)\n        {\n            // Precalculate the radial part for ij\n            // Supposedly saves quite a number of operations\n            for (size_t l = 0; l < members.size(); ++l)\n            {\n                if (rij > mrl[l] && rij < mrc[l])\n                {\n                    SymFncCompAngw const& sf = *(members[l]);\n#ifndef N2P2_NO_SF_CACHE\n                    if (mci[l][nej].size() == 0)\n                    {\n                        sf.getCompactRadial(rij, radij[l], dradij[l]);\n                    }\n                    else\n                    {\n                        double& crad = nj.cache[mci[l][nej][0]];\n                        double& cdrad = nj.cache[mci[l][nej][1]];\n                        if (crad < 0) sf.getCompactRadial(rij, crad, cdrad);\n                        radij[l] = crad;\n                        dradij[l] = cdrad;\n                    }\n#else\n                    sf.getCompactRadial(rij, radij[l], dradij[l]);\n#endif\n                }\n                else radij[l] = 0.0;\n            }\n\n            // SIMPLE EXPRESSIONS:\n            //Vec3D drij(atom.neighbors[j].dr);\n            double const* const dr1 = nj.dr.r;\n\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                if ((e1 == nej && e2 == nek) ||\n                    (e2 == nej && e1 == nek))\n                {\n                    double const rik = nk.d;\n                    if (rik < rmax && rik > rmin)\n                    {\n                        // SIMPLE EXPRESSIONS:\n                        //Vec3D drik(atom.neighbors[k].dr);\n                        //Vec3D drjk = drik - drij;\n                        double const* const dr2 = nk.dr.r;\n                        double const dr30 = dr2[0] - dr1[0];\n                        double const dr31 = dr2[1] - dr1[1];\n                        double const dr32 = dr2[2] - dr1[2];\n\n                        // Energy calculation.\n                        double const rinvijik = 1.0 / (rij * rik);\n                        double const costijk = (dr1[0] * dr2[0] +\n                                                dr1[1] * dr2[1] +\n                                                dr1[2] * dr2[2]) * rinvijik;\n\n                        // By definition, our polynomial is zero at 0 and 180 deg.\n                        // Therefore, skip the whole rest which might yield some NaN\n                        if (costijk <= -1.0 || costijk >= 1.0) continue;\n\n                        double const acostijk = acos(costijk);\n\n                        double const rinvij   = rinvijik * rik;\n                        double const rinvik   = rinvijik * rij;\n                        double const phiijik0 = rinvij\n                                              * (rinvik - rinvij * costijk);\n                        double const phiikij0 = rinvik\n                                              * (rinvij - rinvik * costijk);\n                        double dacostijk = 0.0;\n                        if (derivatives)\n                        {\n                            dacostijk = -1.0 / sqrt(1.0 - costijk * costijk);\n                        }\n\n                        double ang;\n                        double dang;\n                        double radik;\n                        double dradik;\n\n                        for (size_t l = 0; l < members.size(); ++l)\n                        {\n                            // Break conditions.\n                            if (radij[l] == 0.0 ||\n                                rik <= mrl[l] || rik >= mrc[l] ||\n                                acostijk <= mal[l] || acostijk >= mar[l])\n                            {\n                                continue;\n                            }\n\n                            SymFncCompAngw const& sf = *(members[l]);\n#ifndef N2P2_NO_SF_CACHE\n                            if (mci[l][nek].size() == 0)\n                            {\n                                sf.getCompactRadial(rik, radik, dradik);\n                            }\n                            else\n                            {\n                                double& crad = nk.cache[mci[l][nek][0]];\n                                double& cdrad = nk.cache[mci[l][nek][1]];\n                                if (crad < 0) sf.getCompactRadial(rik, crad, cdrad);\n                                radik = crad;\n                                dradik = cdrad;\n                            }\n#else\n                            sf.getCompactRadial(rik, radik, dradik);\n#endif\n                            sf.getCompactAngle(acostijk, ang, dang);\n\n                            double rad = radij[l] * radik;\n                            result[l] += rad * ang;\n            \n                            // Force calculation.\n                            if (!derivatives) continue;\n\n                            dang *= dacostijk;\n                            double const phiijik = phiijik0 * dang;\n                            double const phiikij = phiikij0 * dang;\n                            double const psiijik = rinvijik * dang;\n\n                            double const chiij = rinvij * radik    * dradij[l];\n                            double const chiik = rinvik * radij[l] * dradik;\n\n                            double p1;\n                            double p2;\n                            double p3;\n\n                            if (dang != 0.0 && rad != 0.0)\n                            {\n                                rad  *= scalingFactors[l];\n                                ang  *= scalingFactors[l];\n                                p1 = rad * phiijik +  ang * chiij;\n                                p2 = rad * phiikij +  ang * chiik;\n                                p3 = rad * psiijik;\n                            }\n                            else if (ang != 0.0)\n                            {\n                                ang *= scalingFactors[l];\n\n                                p1 = ang * chiij;\n                                p2 = ang * chiik;\n                                p3 = 0.0;\n                            }\n                            else continue;\n\n                            // SIMPLE EXPRESSIONS:\n                            // Save force contributions in Atom storage.\n                            //atom.dGdr[memberIndex[l]] += p1 * drij\n                            //                           + p2 * drik;\n                            //atom.neighbors[j].\n                            //    dGdr[memberIndex[l]] -= p1 * drij\n                            //                          + p3 * drjk;\n                            //atom.neighbors[k].\n                            //    dGdr[memberIndex[l]] -= p2 * drik\n                            //                          - p3 * drjk;\n\n                            double const p1drijx = p1 * dr1[0];\n                            double const p1drijy = p1 * dr1[1];\n                            double const p1drijz = p1 * dr1[2];\n\n                            double const p2drikx = p2 * dr2[0];\n                            double const p2driky = p2 * dr2[1];\n                            double const p2drikz = p2 * dr2[2];\n\n                            double const p3drjkx = p3 * dr30;\n                            double const p3drjky = p3 * dr31;\n                            double const p3drjkz = p3 * dr32;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            size_t li = memberIndex[l];\n#else\n                            size_t const li = memberIndex[l];\n#endif\n                            double* dGdr = atom.dGdr[li].r;\n                            dGdr[0] += p1drijx + p2drikx;\n                            dGdr[1] += p1drijy + p2driky;\n                            dGdr[2] += p1drijz + p2drikz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            li = memberIndexPerElement[l][nej];\n#endif\n                            dGdr = nj.dGdr[li].r;\n                            dGdr[0] -= p1drijx + p3drjkx;\n                            dGdr[1] -= p1drijy + p3drjky;\n                            dGdr[2] -= p1drijz + p3drjkz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            li = memberIndexPerElement[l][nek];\n#endif\n                            dGdr = nk.dGdr[li].r;\n                            dGdr[0] -= p2drikx - p3drjkx;\n                            dGdr[1] -= p2driky - p3drjky;\n                            dGdr[2] -= p2drikz - p3drjkz;\n                        } // l\n                    } // rik <= rc\n                } // elem\n            } // k\n        } // rij <= rc\n    } // j\n\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        atom.G[memberIndex[l]] = members[l]->scale(result[l]);\n    }\n\n    delete[] result;\n    delete[] radij;\n    delete[] dradij;\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpCompAngw.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPCOMPANGW_H\n#define SYMGRPCOMPANGW_H\n\n#include \"SymGrpBaseCompAng.h\"\n#include \"SymFncCompAngw.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\n\n/** Wide angular symmetry function with compact support (type 22)\n *\n * @f[\n   G^{22}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n              C(r_{ij}, r_l, r_c)\n              C(r_{ik}, r_l, r_c)\n              C(\\theta_{ijk}, \\theta_l, \\theta_r),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$.\n *\n * Common features:\n * - element of central atom\n * - element of neighbor atom 1\n * - element of neighbor atom 2\n */\nclass SymGrpCompAngw : public SymGrpBaseCompAng\n{\npublic:\n    /** Constructor, sets type = 22\n     */\n    SymGrpCompAngw(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n\nprivate:\n    /** Get symmetry function members.\n     *\n     * @return Vector of pointers casted to base class.\n     */\n    virtual std::vector<SymFncBaseCompAng const*> getMembers() const;\n\n    /// Vector of all group member pointers.\n    std::vector<SymFncCompAngw const*> members;\n};\n\ninline std::vector<SymFncBaseCompAng const*> SymGrpCompAngw::getMembers() const\n{\n    std::vector<SymFncBaseCompAng const*> cast;\n\n    for (auto p : members)\n    {\n        cast.push_back(dynamic_cast<SymFncBaseCompAng const*>(p));\n    }\n\n    return cast;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpCompAngwWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpCompAngwWeighted.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncCompAngwWeighted.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\nusing namespace std;\nusing namespace nnp;\n\nSymGrpCompAngwWeighted::\nSymGrpCompAngwWeighted(ElementMap const& elementMap) :\n    SymGrpBaseCompAngWeighted(25, elementMap)\n{\n}\n\nbool SymGrpCompAngwWeighted::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    return true;\n}\n\nbool SymGrpCompAngwWeighted::operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    return false;\n}\n\nbool SymGrpCompAngwWeighted::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncCompAngwWeighted const* sf =\n        dynamic_cast<SymFncCompAngwWeighted const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        ec          = sf->getEc();\n        convLength  = sf->getConvLength();\n    }\n\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    if (sf->getRl() <= 0.0) rmin = 0.0;\n    else rmin = min( rmin, sf->getRl() );\n    rmax = max( rmax, sf->getRc() );\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpCompAngwWeighted::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncCompAngwWeighted const>);\n\n    mrl.resize(members.size(), 0.0);\n    mrc.resize(members.size(), 0.0);\n    mal.resize(members.size(), 0.0);\n    mar.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        mrl.at(i) = members[i]->getRl();\n        mrc.at(i) = members[i]->getRc();\n        mal.at(i) = members[i]->getAngleLeft() * M_PI / 180.0;\n        mar.at(i) = members[i]->getAngleRight() * M_PI / 180.0;\n        memberIndex.push_back(members[i]->getIndex());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n        calculateComp.push_back(true);\n    }\n\n#ifndef N2P2_NO_SF_CACHE\n    mci.resize(members.size());\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        mci.at(k) = members.at(k)->getCacheIndices();\n    }\n#endif\n\n    return;\n}\n\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minimized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpCompAngwWeighted::\ncalculate(Atom& atom, bool const derivatives) const\n{\n    double* result = new double[members.size()];\n    double* radij  = new double[members.size()];\n    double* dradij = new double[members.size()];\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        result[l] = 0.0;\n        radij[l]  = 0.0;\n        dradij[l] = 0.0;\n    }\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n\n        if (rij < rmax && rij > rmin)\n        {\n            // Precalculate the radial part for ij\n            // Supposedly saves quite a number of operations\n            for (size_t l = 0; l < members.size(); ++l)\n            {\n                if (rij > mrl[l] && rij < mrc[l])\n                {\n                    SymFncCompAngwWeighted const& sf = *(members[l]);\n#ifndef N2P2_NO_SF_CACHE\n                    if (mci[l][nej].size() == 0)\n                    {\n                        sf.getCompactRadial(rij, radij[l], dradij[l]);\n                    }\n                    else\n                    {\n                        double& crad = nj.cache[mci[l][nej][0]];\n                        double& cdrad = nj.cache[mci[l][nej][1]];\n                        if (crad < 0) sf.getCompactRadial(rij, crad, cdrad);\n                        radij[l] = crad;\n                        dradij[l] = cdrad;\n                    }\n#else\n                    sf.getCompactRadial(rij, radij[l], dradij[l]);\n#endif\n                }\n                else radij[l] = 0.0;\n            }\n\n            // SIMPLE EXPRESSIONS:\n            //Vec3D drij(atom.neighbors[j].dr);\n            double const* const dr1 = nj.dr.r;\n\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                double const rik = nk.d;\n                if (rik < rmax && rik > rmin)\n                {\n                    // SIMPLE EXPRESSIONS:\n                    //Vec3D drik(atom.neighbors[k].dr);\n                    //Vec3D drjk = drik - drij;\n                    double const* const dr2 = nk.dr.r;\n                    double const dr30 = dr2[0] - dr1[0];\n                    double const dr31 = dr2[1] - dr1[1];\n                    double const dr32 = dr2[2] - dr1[2];\n\n                    // Energy calculation.\n                    double const rinvijik = 1.0 / (rij * rik);\n                    double const costijk = (dr1[0] * dr2[0] +\n                                            dr1[1] * dr2[1] +\n                                            dr1[2] * dr2[2]) * rinvijik;\n\n                    // By definition, our polynomial is zero at 0 and 180 deg.\n                    // Therefore, skip the whole rest which might yield some NaN\n                    if (costijk <= -1.0 || costijk >= 1.0) continue;\n\n                    double const acostijk = acos(costijk);\n\n                    double const rinvij   = rinvijik * rik;\n                    double const rinvik   = rinvijik * rij;\n                    double const phiijik0 = rinvij\n                                          * (rinvik - rinvij * costijk);\n                    double const phiikij0 = rinvik\n                                          * (rinvij - rinvik * costijk);\n                    double dacostijk = 0.0;\n                    if (derivatives)\n                    {\n                        dacostijk = -1.0 / sqrt(1.0 - costijk * costijk);\n                    }\n\n                    double ang;\n                    double dang;\n                    double radik;\n                    double dradik;\n\n                    for (size_t l = 0; l < members.size(); ++l)\n                    {\n                        // Break conditions.\n                        if (radij[l] == 0.0 ||\n                            rik <= mrl[l] || rik >= mrc[l] ||\n                            acostijk <= mal[l] || acostijk >= mar[l])\n                        {\n                            continue;\n                        }\n\n                        SymFncCompAngwWeighted const& sf = *(members[l]);\n#ifndef N2P2_NO_SF_CACHE\n                        if (mci[l][nek].size() == 0)\n                        {\n                            sf.getCompactRadial(rik, radik, dradik);\n                        }\n                        else\n                        {\n                            double& crad = nk.cache[mci[l][nek][0]];\n                            double& cdrad = nk.cache[mci[l][nek][1]];\n                            if (crad < 0) sf.getCompactRadial(rik, crad, cdrad);\n                            radik = crad;\n                            dradik = cdrad;\n                        }\n#else\n                        sf.getCompactRadial(rik, radik, dradik);\n#endif\n                        sf.getCompactAngle(acostijk, ang, dang);\n\n                        double const z = elementMap.atomicNumber(nej)\n                                       * elementMap.atomicNumber(nek);\n                        ang *= z;\n                        double rad = radij[l] * radik;\n                        result[l] += rad * ang;\n            \n                        // Force calculation.\n                        if (!derivatives) continue;\n\n                        dang *= dacostijk;\n                        double const phiijik = phiijik0 * dang;\n                        double const phiikij = phiikij0 * dang;\n                        double const psiijik = rinvijik * dang;\n\n                        double const chiij =  rinvij * dradij[l] *  radik;\n                        double const chiik =  rinvik * radij[l] *  dradik;\n\n                        double p1;\n                        double p2;\n                        double p3;\n\n                        if (dang != 0.0 && rad != 0.0)\n                        {\n                            rad  *= scalingFactors[l] * z;\n                            ang  *= scalingFactors[l];\n                            p1 = rad * phiijik +  ang * chiij;\n                            p2 = rad * phiikij +  ang * chiik;\n                            p3 = rad * psiijik;\n                        }\n                        else if (ang != 0.0)\n                        {\n                            ang *= scalingFactors[l];\n\n                            p1 = ang * chiij;\n                            p2 = ang * chiik;\n                            p3 = 0.0;\n                        }\n                        else continue;\n\n                        // SIMPLE EXPRESSIONS:\n                        // Save force contributions in Atom storage.\n                        //atom.dGdr[memberIndex[l]] += p1 * drij\n                        //                           + p2 * drik;\n                        //atom.neighbors[j].\n                        //    dGdr[memberIndex[l]] -= p1 * drij\n                        //                          + p3 * drjk;\n                        //atom.neighbors[k].\n                        //    dGdr[memberIndex[l]] -= p2 * drik\n                        //                          - p3 * drjk;\n\n                        double const p1drijx = p1 * dr1[0];\n                        double const p1drijy = p1 * dr1[1];\n                        double const p1drijz = p1 * dr1[2];\n\n                        double const p2drikx = p2 * dr2[0];\n                        double const p2driky = p2 * dr2[1];\n                        double const p2drikz = p2 * dr2[2];\n\n                        double const p3drjkx = p3 * dr30;\n                        double const p3drjky = p3 * dr31;\n                        double const p3drjkz = p3 * dr32;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                        size_t li = memberIndex[l];\n#else\n                        size_t const li = memberIndex[l];\n#endif\n                        double* dGdr = atom.dGdr[li].r;\n                        dGdr[0] += p1drijx + p2drikx;\n                        dGdr[1] += p1drijy + p2driky;\n                        dGdr[2] += p1drijz + p2drikz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                        li = memberIndexPerElement[l][nej];\n#endif\n                        dGdr = nj.dGdr[li].r;\n                        dGdr[0] -= p1drijx + p3drjkx;\n                        dGdr[1] -= p1drijy + p3drjky;\n                        dGdr[2] -= p1drijz + p3drjkz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                        li = memberIndexPerElement[l][nek];\n#endif\n                        dGdr = nk.dGdr[li].r;\n                        dGdr[0] -= p2drikx - p3drjkx;\n                        dGdr[1] -= p2driky - p3drjky;\n                        dGdr[2] -= p2drikz - p3drjkz;\n                    } // l\n                } // rik <= rc\n            } // k\n        } // rij <= rc\n    } // j\n\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        atom.G[memberIndex[l]] = members[l]->scale(result[l]);\n    }\n\n    delete[] result;\n    delete[] radij;\n    delete[] dradij;\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpCompAngwWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPCOMPANGWWEIGHTED_H\n#define SYMGRPCOMPANGWWEIGHTED_H\n\n#include \"SymGrpBaseCompAngWeighted.h\"\n#include \"SymFncCompAngwWeighted.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\n\n/** Weighted wide angular symmetry function with compact support (type 25)\n *\n * @f[\n   G^{25}_i = \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n              Z_j Z_k\n              C(r_{ij}, r_l, r_c)\n              C(r_{ik}, r_l, r_c)\n              C(\\theta_{ijk}, \\theta_l, \\theta_r),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$. @f$Z_j@f$ is defined\n * as the atomic number of the neighbor atom @f$j@f$.\n *\n * Common features:\n * - element of central atom\n */\nclass SymGrpCompAngwWeighted : public SymGrpBaseCompAngWeighted\n{\npublic:\n    /** Constructor, sets type = 25\n     */\n    SymGrpCompAngwWeighted(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n\nprivate:\n    /** Get symmetry function members.\n     *\n     * @return Vector of pointers casted to base class.\n     */\n    virtual std::vector<SymFncBaseCompAngWeighted const*> getMembers() const;\n\n    /// Vector of all group member pointers.\n    std::vector<SymFncCompAngwWeighted const*> members;\n};\n\ninline std::vector<SymFncBaseCompAngWeighted const*>\n                                     SymGrpCompAngwWeighted::getMembers() const\n{\n    std::vector<SymFncBaseCompAngWeighted const*> cast;\n\n    for (auto p : members)\n    {\n        cast.push_back(dynamic_cast<SymFncBaseCompAngWeighted const*>(p));\n    }\n\n    return cast;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpCompRad.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpCompRad.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncCompRad.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrpCompRad::\nSymGrpCompRad(ElementMap const& elementMap) :\n    SymGrpBaseComp(20, elementMap),\n    e1(0)\n{\n    parametersCommon.insert(\"e1\");\n}\n\nbool SymGrpCompRad::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymGrpCompRad const& c = dynamic_cast<SymGrpCompRad const&>(rhs);\n    if (e1 != c.e1) return false;\n    return true;\n}\n\nbool SymGrpCompRad::operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymGrpCompRad const& c = dynamic_cast<SymGrpCompRad const&>(rhs);\n    if      (e1 < c.e1) return true;\n    else if (e1 > c.e1) return false;\n    return false;\n}\n\nbool SymGrpCompRad::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncCompRad const* sf =\n        dynamic_cast<SymFncCompRad const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        ec          = sf->getEc();\n        e1          = sf->getE1();\n        convLength  = sf->getConvLength();\n    }\n\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getE1()          != e1         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    if (sf->getRl() <= 0.0) rmin = 0.0;\n    else rmin = min( rmin, sf->getRl() );\n    rmax = max( rmax, sf->getRc() );\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpCompRad::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncCompRad const>);\n\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        memberIndex.push_back(members[i]->getIndex());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n    }\n\n    mrl.resize(members.size(), 0.0);\n    mrc.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        mrl.at(i) = members[i]->getRl();\n        mrc.at(i) = members[i]->getRc();\n    }\n\n#ifndef N2P2_NO_SF_CACHE\n    mci.resize(members.size());\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        mci.at(k) = members.at(k)->getCacheIndices()[e1];\n    }\n#endif\n\n    return;\n}\n\nvoid SymGrpCompRad::setScalingFactors()\n{\n    scalingFactors.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        scalingFactors.at(i) = members[i]->getScalingFactor();\n    }\n\n    return;\n}\n\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minimized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpCompRad::calculate(Atom& atom, bool const derivatives) const\n{\n    double* result = new double[members.size()];\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        result[k] = 0.0;\n    }\n\n    for (size_t j = 0; j < atom.numNeighbors; ++j)\n    {\n        Atom::Neighbor& n = atom.neighbors[j];\n        double const rij = n.d;\n        if (e1 == n.element && rij < rmax && rij > rmin)\n        {\n            // Energy calculation.\n            double const* const d1 = n.dr.r;\n            for (size_t k = 0; k < members.size(); ++k)\n            {\n                SymFncCompRad const& sf = *(members[k]);\n                if (rij <= mrl[k] || rij >= mrc[k]) continue;\n                double rad;\n                double drad;\n#ifndef N2P2_NO_SF_CACHE\n                if (mci[k].size() == 0) sf.getCompactOnly(rij, rad, drad);\n                else\n                {\n                    double& crad = n.cache[mci[k][0]];\n                    double& cdrad = n.cache[mci[k][1]];\n                    if (crad < 0) sf.getCompactOnly(rij, crad, cdrad);\n                    rad = crad;\n                    drad = cdrad;\n                }\n#else\n                sf.getCompactOnly(rij, rad, drad);\n#endif\n                result[k] += rad;\n\n                // Force calculation.\n                if (!derivatives || drad == 0.0) continue;\n                drad *= scalingFactors[k] / rij;\n                // SIMPLE EXPRESSIONS:\n                //Vec3D const dij = p1 * atom.neighbors[j].dr;\n                double const p1drijx = drad * d1[0];\n                double const p1drijy = drad * d1[1];\n                double const p1drijz = drad * d1[2];\n\n                // Save force contributions in Atom storage.\n#ifndef N2P2_FULL_SFD_MEMORY\n                size_t ki = memberIndex[k];\n#else\n                size_t const ki = memberIndex[k];\n#endif\n                // SIMPLE EXPRESSIONS:\n                //atom.dGdr[ki]              += dij;\n                //atom.neighbors[j].dGdr[ki] -= dij;\n\n                double* dGdr = atom.dGdr[ki].r;\n                dGdr[0] += p1drijx;\n                dGdr[1] += p1drijy;\n                dGdr[2] += p1drijz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                ki = memberIndexPerElement[k][e1];\n#endif\n                dGdr = n.dGdr[ki].r;\n                dGdr[0] -= p1drijx;\n                dGdr[1] -= p1drijy;\n                dGdr[2] -= p1drijz;\n            }\n        }\n    }\n\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        atom.G[memberIndex[k]] = members[k]->scale(result[k]);\n    }\n\n    delete[] result;\n\n    return;\n}\n\nvector<string> SymGrpCompRad::parameterLines() const\n{\n    vector<string> v;\n\n    v.push_back(strpr(getPrintFormatCommon().c_str(),\n                      index + 1,\n                      elementMap[ec].c_str(),\n                      type,\n                      elementMap[e1].c_str(),\n                      rmin / convLength,\n                      rmax / convLength));\n\n    for (size_t i = 0; i < members.size(); ++i)\n    {\n        v.push_back(strpr(getPrintFormatMember().c_str(),\n                          members[i]->getSubtype().c_str(),\n                          members[i]->getRl() / convLength,\n                          members[i]->getRc() / convLength,\n                          members[i]->getLineNumber() + 1,\n                          i + 1,\n                          members[i]->getIndex() + 1));\n    }\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpCompRad.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPCOMPRAD_H\n#define SYMGRPCOMPRAD_H\n\n#include \"SymGrpBaseComp.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\nclass SymFncCompRad;\n\n/** Radial symmetry function with compact support (type 20)\n *\n * @f[\n   G^{20}_i = \\sum_{\\substack{j \\neq i}}\n              C(r_{ij}, r_l, r_c),\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$.\n *\n * Common features:\n * - element of central atom\n * - element of neighbor atom\n */\nclass SymGrpCompRad : public SymGrpBaseComp\n{\npublic:\n    /** Constructor, sets type = 20\n     */\n    SymGrpCompRad(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Fill #scalingFactors with values from member symmetry functions.\n     */\n    virtual void setScalingFactors();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n    /** Give symmetry function group parameters on multiple lines.\n     *\n     * @return Vector of string containing symmetry function parameters lines.\n     */\n    virtual std::vector<std::string>\n                 parameterLines() const;\n\nprivate:\n    /// Element index of neighbor atom (common feature).\n    std::size_t                           e1;\n    /// Vector of all group member pointers.\n    std::vector<SymFncCompRad const*>     members;\n    /// Member rl.\n    std::vector<double>                   mrl;\n    /// Member rc.\n    std::vector<double>                   mrc;\n#ifndef N2P2_NO_SF_CACHE\n    /// Member cache indices for actual neighbor element.\n    std::vector<std::vector<std::size_t>> mci;\n#endif\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpCompRadWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpCompRadWeighted.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncCompRadWeighted.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrpCompRadWeighted::\nSymGrpCompRadWeighted(ElementMap const& elementMap) :\n    SymGrpBaseComp(23, elementMap)\n{\n}\n\nbool SymGrpCompRadWeighted::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    return true;\n}\n\nbool SymGrpCompRadWeighted::operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    return false;\n}\n\nbool SymGrpCompRadWeighted::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncCompRadWeighted const* sf =\n        dynamic_cast<SymFncCompRadWeighted const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        ec          = sf->getEc();\n        convLength  = sf->getConvLength();\n    }\n\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    if (sf->getRl() <= 0.0) rmin = 0.0;\n    else rmin = min( rmin, sf->getRl() );\n    rmax = max( rmax, sf->getRc() );\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpCompRadWeighted::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncCompRadWeighted const>);\n\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        memberIndex.push_back(members[i]->getIndex());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n    }\n\n    mrl.resize(members.size(), 0.0);\n    mrc.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        mrl.at(i) = members[i]->getRl();\n        mrc.at(i) = members[i]->getRc();\n    }\n\n    return;\n}\n\nvoid SymGrpCompRadWeighted::setScalingFactors()\n{\n    scalingFactors.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        scalingFactors.at(i) = members[i]->getScalingFactor();\n    }\n\n    return;\n}\n\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minimized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpCompRadWeighted::calculate(Atom& atom, bool const derivatives) const\n{\n    double* result = new double[members.size()];\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        result[k] = 0.0;\n    }\n\n    for (size_t j = 0; j < atom.numNeighbors; ++j)\n    {\n        Atom::Neighbor& n = atom.neighbors[j];\n        double const rij = n.d;\n        if (rij < rmax && rij > rmin)\n        {\n            // Energy calculation.\n            double const* const d1 = n.dr.r;\n            size_t const        ne = n.element;\n            for (size_t k = 0; k < members.size(); ++k)\n            {\n                SymFncCompRadWeighted const& sf = *(members[k]);\n                if (rij <= mrl[k] || rij >= mrc[k]) continue;\n                double rad;\n                double drad;\n#ifndef N2P2_NO_SF_CACHE\n                auto ci = sf.getCacheIndices();\n                if (ci[ne].size() == 0) sf.getCompactOnly(rij, rad, drad);\n                else\n                {\n                    double& crad = n.cache[ci[ne][0]];\n                    double& cdrad = n.cache[ci[ne][1]];\n                    if (crad < 0) sf.getCompactOnly(rij, crad, cdrad);\n                    rad = crad;\n                    drad = cdrad;\n                }\n#else\n                sf.getCompactOnly(rij, rad, drad);\n#endif\n                result[k] += elementMap.atomicNumber(ne) * rad;\n\n                // Force calculation.\n                if (!derivatives || drad == 0.0) continue;\n                drad *= elementMap.atomicNumber(ne) * scalingFactors[k] / rij;\n                // SIMPLE EXPRESSIONS:\n                //Vec3D const dij = p1 * atom.neighbors[j].dr;\n                double const p1drijx = drad * d1[0];\n                double const p1drijy = drad * d1[1];\n                double const p1drijz = drad * d1[2];\n\n                // Save force contributions in Atom storage.\n#ifndef N2P2_FULL_SFD_MEMORY\n                size_t ki = memberIndex[k];\n#else\n                size_t const ki = memberIndex[k];\n#endif\n                // SIMPLE EXPRESSIONS:\n                //atom.dGdr[ki]              += dij;\n                //atom.neighbors[j].dGdr[ki] -= dij;\n\n                double* dGdr = atom.dGdr[ki].r;\n                dGdr[0] += p1drijx;\n                dGdr[1] += p1drijy;\n                dGdr[2] += p1drijz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                ki = memberIndexPerElement[k][ne];\n#endif\n                dGdr = n.dGdr[ki].r;\n                dGdr[0] -= p1drijx;\n                dGdr[1] -= p1drijy;\n                dGdr[2] -= p1drijz;\n            }\n        }\n    }\n\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        atom.G[memberIndex[k]] = members[k]->scale(result[k]);\n    }\n\n    delete[] result;\n\n    return;\n}\n\nvector<string> SymGrpCompRadWeighted::parameterLines() const\n{\n    vector<string> v;\n\n    v.push_back(strpr(getPrintFormatCommon().c_str(),\n                      index + 1,\n                      elementMap[ec].c_str(),\n                      type,\n                      rmin / convLength,\n                      rmax / convLength));\n\n    for (size_t i = 0; i < members.size(); ++i)\n    {\n        v.push_back(strpr(getPrintFormatMember().c_str(),\n                          members[i]->getSubtype().c_str(),\n                          members[i]->getRl() / convLength,\n                          members[i]->getRc() / convLength,\n                          members[i]->getLineNumber() + 1,\n                          i + 1,\n                          members[i]->getIndex() + 1));\n    }\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpCompRadWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Martin P. Bircher\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPCOMPRADWEIGHTED_H\n#define SYMGRPCOMPRADWEIGHTED_H\n\n#include \"SymGrpBaseComp.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\nclass SymFncCompRadWeighted;\n\n/** Weighted radial symmetry function with compact support (type 23)\n *\n * @f[\n   G^{23}_i = \\sum_{\\substack{j \\neq i}}\n              Z_j\n              C(r_{ij}, r_l, r_c)\n * @f]\n * where @f$C(x, x_\\text{low}, x_\\text{high})@f$ is a function with compact\n * support @f$\\left[x_\\text{low}, x_\\text{high}\\right]@f$. @f$Z_j@f$ is defined\n * as the atomic number of the neighbor atom @f$j@f$.\n *\n * Common features:\n * - element of central atom\n */\nclass SymGrpCompRadWeighted : public SymGrpBaseComp\n{\npublic:\n    /** Constructor, sets type = 23\n     */\n    SymGrpCompRadWeighted(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Fill #scalingFactors with values from member symmetry functions.\n     */\n    virtual void setScalingFactors();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n    /** Give symmetry function group parameters on multiple lines.\n     *\n     * @return Vector of string containing symmetry function parameters lines.\n     */\n    virtual std::vector<std::string>\n                 parameterLines() const;\n\nprivate:\n    /// Vector of all group member pointers.\n    std::vector<SymFncCompRadWeighted const*> members;\n    /// Member rl.\n    std::vector<double>                       mrl;\n    /// Member rc.\n    std::vector<double>                       mrc;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpExpAngn.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpExpAngn.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncExpAngn.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrpExpAngn::SymGrpExpAngn(ElementMap const& elementMap) :\n    SymGrpBaseExpAng(3, elementMap)\n{\n}\n\nbool SymGrpExpAngn::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymGrpExpAngn const& c = dynamic_cast<SymGrpExpAngn const&>(rhs);\n    if (cutoffType  != c.cutoffType ) return false;\n    if (cutoffAlpha != c.cutoffAlpha) return false;\n    if (rc          != c.rc         ) return false;\n    if (e1          != c.e1         ) return false;\n    if (e2          != c.e2         ) return false;\n    return true;\n}\n\nbool SymGrpExpAngn:: operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymGrpExpAngn const& c = dynamic_cast<SymGrpExpAngn const&>(rhs);\n    if      (cutoffType  < c.cutoffType ) return true;\n    else if (cutoffType  > c.cutoffType ) return false;\n    if      (cutoffAlpha < c.cutoffAlpha) return true;\n    else if (cutoffAlpha > c.cutoffAlpha) return false;\n    if      (rc          < c.rc         ) return true;\n    else if (rc          > c.rc         ) return false;\n    if      (e1          < c.e1         ) return true;\n    else if (e1          > c.e1         ) return false;\n    if      (e2          < c.e2         ) return true;\n    else if (e2          > c.e2         ) return false;\n    return false;\n}\n\nbool SymGrpExpAngn::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncExpAngn const* sf =\n        dynamic_cast<SymFncExpAngn const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        cutoffType  = sf->getCutoffType();\n        subtype     = sf->getSubtype();\n        cutoffAlpha = sf->getCutoffAlpha();\n        ec          = sf->getEc();\n        rc          = sf->getRc();\n        e1          = sf->getE1();\n        e2          = sf->getE2();\n        convLength  = sf->getConvLength();\n\n        fc.setCutoffType(cutoffType);\n        fc.setCutoffRadius(rc);\n        fc.setCutoffParameter(cutoffAlpha);\n    }\n\n    if (sf->getCutoffType()  != cutoffType ) return false;\n    if (sf->getCutoffAlpha() != cutoffAlpha) return false;\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getRc()          != rc         ) return false;\n    if (sf->getE1()          != e1         ) return false;\n    if (sf->getE2()          != e2         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpExpAngn::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncExpAngn const>);\n\n    // Members are now sorted with eta changing the slowest.\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        factorNorm.push_back(pow(2.0, 1.0 - members[i]->getZeta()));\n        factorDeriv.push_back(2.0 * members[i]->getEta() /\n                              members[i]->getZeta() / members[i]->getLambda());\n        if (i == 0)\n        {\n            calculateExp.push_back(true);\n        }\n        else\n        {\n            if ( members[i - 1]->getEta() != members[i]->getEta() ||\n                 members[i - 1]->getRs()  != members[i]->getRs() )\n            {\n                calculateExp.push_back(true);\n            }\n            else\n            {\n                calculateExp.push_back(false);\n            }\n        }\n        useIntegerPow.push_back(members[i]->getUseIntegerPow());\n        memberIndex.push_back(members[i]->getIndex());\n        zetaInt.push_back(members[i]->getZetaInt());\n        eta.push_back(members[i]->getEta());\n        rs.push_back(members[i]->getRs());\n        zeta.push_back(members[i]->getZeta());\n        lambda.push_back(members[i]->getLambda());\n        zetaLambda.push_back(members[i]->getZeta() * members[i]->getLambda());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n    }\n\n    return;\n}\n\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minimized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpExpAngn::calculate(Atom& atom, bool const derivatives) const\n{\n#ifndef N2P2_NO_SF_CACHE\n    // Can use cache indices of any member because this group is defined via\n    // identical symmetry function type, neighbors and cutoff functions.\n    auto cacheIndices = members.at(0)->getCacheIndices();\n#endif\n    double* result = new double[members.size()];\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        result[l] = 0.0;\n    }\n\n    double const rc2 = rc * rc;\n    //size_t numNeighbors = atom.numNeighbors;\n    size_t numNeighbors = atom.getStoredMinNumNeighbors(rc);\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n        if ((e1 == nej || e2 == nej) && rij < rc)\n        {\n            double const r2ij = rij * rij;\n\n            // Calculate cutoff function and derivative.\n            double pfcij;\n            double pdfcij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) fc.fdf(rij, pfcij, pdfcij);\n            else\n            {\n                double& cfc = nj.cache[cacheIndices[nej][0]];\n                double& cdfc = nj.cache[cacheIndices[nej][1]];\n                if (cfc < 0) fc.fdf(rij, cfc, cdfc);\n                pfcij = cfc;\n                pdfcij = cdfc;\n            }\n#else\n            fc.fdf(rij, pfcij, pdfcij);\n#endif\n            // SIMPLE EXPRESSIONS:\n            //Vec3D const drij(atom.neighbors[j].dr);\n            //double const* const dr1 = drij.r;\n            double const* const dr1 = nj.dr.r;\n\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                if ((e1 == nej && e2 == nek) ||\n                    (e2 == nej && e1 == nek))\n                {\n                    double const rik = nk.d;\n                    if (rik < rc)\n                    {\n                        // SIMPLE EXPRESSIONS:\n                        //Vec3D const drjk(atom.neighbors[k].dr\n                        //               - atom.neighbors[j].dr);\n                        //double rjk = drjk.norm2();\n                        double const* const dr2 = nk.dr.r;\n                        double dr3[3];\n                        dr3[0] = dr2[0] - dr1[0];\n                        dr3[1] = dr2[1] - dr1[1];\n                        dr3[2] = dr2[2] - dr1[2];\n                        double rjk = dr3[0] * dr3[0]\n                                   + dr3[1] * dr3[1]\n                                   + dr3[2] * dr3[2];\n                        if (rjk < rc2)\n                        {\n                            // Energy calculation.\n                            double pfcik;\n                            double pdfcik;\n#ifndef N2P2_NO_SF_CACHE\n                            if (cacheIndices[nek].size() == 0)\n                            {\n                                fc.fdf(rik, pfcik, pdfcik);\n                            }\n                            else\n                            {\n                                double& cfc = nk.cache[cacheIndices[nek][0]];\n                                double& cdfc = nk.cache[cacheIndices[nek][1]];\n                                if (cfc < 0) fc.fdf(rik, cfc, cdfc);\n                                pfcik = cfc;\n                                pdfcik = cdfc;\n                            }\n#else\n                            fc.fdf(rik, pfcik, pdfcik);\n#endif\n                            rjk = sqrt(rjk);\n\n                            double pfcjk;\n                            double pdfcjk;\n                            fc.fdf(rjk, pfcjk, pdfcjk);\n\n                            // SIMPLE EXPRESSIONS:\n                            //Vec3D const drik(atom.neighbors[k].dr);\n                            //double const* const dr2 = drik.r;\n                            //double const* const dr3 = drjk.r;\n                            double const rinvijik = 1.0 / rij / rik;\n                            // SIMPLE EXPRESSIONS:\n                            //double const costijk = (drij * drik) * rinvijik;\n                            double const costijk = (dr1[0] * dr2[0] +\n                                                    dr1[1] * dr2[1] +\n                                                    dr1[2] * dr2[2]) * rinvijik;\n                            double const pfc = pfcij * pfcik * pfcjk;\n                            double const r2ik = rik * rik;\n                            double const r2sum = r2ij + r2ik + rjk * rjk;\n                            double const pr1 = pfcik * pfcjk * pdfcij / rij;\n                            double const pr2 = pfcij * pfcjk * pdfcik / rik;\n                            double const pr3 = pfcij * pfcik * pdfcjk / rjk;\n                            double vexp = 0.0;\n                            double rijs = 0.0;\n                            double riks = 0.0;\n                            double rjks = 0.0;\n                            for (size_t l = 0; l < members.size(); ++l)\n                            {\n                                if (calculateExp[l])\n                                {\n                                    if (rs[l] > 0.0)\n                                    {\n                                        rijs = rij - rs[l];\n                                        riks = rik - rs[l];\n                                        rjks = rjk - rs[l];\n                                        vexp = exp(-eta[l] * (rijs * rijs\n                                                            + riks * riks\n                                                            + rjks * rjks));\n                                    }\n                                    else\n                                    {\n                                        vexp = exp(-eta[l] * r2sum);\n                                    }\n                                }\n                                double const plambda = 1.0\n                                                     + lambda[l] * costijk;\n                                double fg = vexp;\n                                if (plambda <= 0.0) fg = 0.0;\n                                else\n                                {\n                                    if (useIntegerPow[l])\n                                    {\n                                        fg *= pow_int(plambda, zetaInt[l] - 1);\n                                    }\n                                    else\n                                    {\n                                        fg *= pow(plambda, zeta[l] - 1.0);\n                                    }\n                                }\n                                result[l] += fg * plambda * pfc;\n\n                                // Force calculation.\n                                if (!derivatives) continue;\n                                fg *= factorNorm[l];\n                                double const pfczl = pfc * zetaLambda[l];\n                                double const p2etapl = plambda * factorDeriv[l];\n                                double p1;\n                                double p2;\n                                double p3;\n                                if (rs[l] > 0.0)\n                                {\n                                    p1 = fg * (pfczl * (rinvijik\n                                       - costijk / r2ij - p2etapl\n                                       * rijs / rij) + pr1 * plambda);\n                                    p2 = fg * (pfczl * (rinvijik\n                                       - costijk / r2ik - p2etapl\n                                       * riks / rik) + pr2 * plambda);\n                                    p3 = fg * (pfczl * (rinvijik\n                                       + p2etapl * rjks / rjk)\n                                       - pr3 * plambda);\n                                }\n                                else\n                                {\n                                    p1 = fg * (pfczl * (rinvijik - costijk\n                                       / r2ij - p2etapl) + pr1 * plambda);\n                                    p2 = fg * (pfczl * (rinvijik - costijk\n                                       / r2ik - p2etapl) + pr2 * plambda);\n                                    p3 = fg * (pfczl * (rinvijik + p2etapl)\n                                       - pr3 * plambda);\n                                }\n\n                                // Save force contributions in Atom storage.\n                                //\n                                // SIMPLE EXPRESSIONS:\n                                //size_t const li = members[l]->getIndex();\n                                //atom.dGdr[li] += p1 * drij + p2 * drik;\n                                //atom.neighbors[j].dGdr[li] -= p1 * drij\n                                //                            + p3 * drjk;\n                                //atom.neighbors[k].dGdr[li] -= p2 * drik\n                                //                            - p3 * drjk;\n\n                                double const p1drijx = p1 * dr1[0];\n                                double const p1drijy = p1 * dr1[1];\n                                double const p1drijz = p1 * dr1[2];\n\n                                double const p2drikx = p2 * dr2[0];\n                                double const p2driky = p2 * dr2[1];\n                                double const p2drikz = p2 * dr2[2];\n\n                                double const p3drjkx = p3 * dr3[0];\n                                double const p3drjky = p3 * dr3[1];\n                                double const p3drjkz = p3 * dr3[2];\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                                size_t li = memberIndex[l];\n#else\n                                size_t const li = memberIndex[l];\n#endif\n                                double* dGdr = atom.dGdr[li].r;\n                                dGdr[0] += p1drijx + p2drikx;\n                                dGdr[1] += p1drijy + p2driky;\n                                dGdr[2] += p1drijz + p2drikz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                                li = memberIndexPerElement[l][nej];\n#endif\n                                dGdr = nj.dGdr[li].r;\n                                dGdr[0] -= p1drijx + p3drjkx;\n                                dGdr[1] -= p1drijy + p3drjky;\n                                dGdr[2] -= p1drijz + p3drjkz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                                li = memberIndexPerElement[l][nek];\n#endif\n                                dGdr = nk.dGdr[li].r;\n                                dGdr[0] -= p2drikx - p3drjkx;\n                                dGdr[1] -= p2driky - p3drjky;\n                                dGdr[2] -= p2drikz - p3drjkz;\n                            } // l\n                        } // rjk <= rc\n                    } // rik <= rc\n                } // elem\n            } // k\n        } // rij <= rc\n    } // j\n\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        result[l] *= factorNorm[l] / scalingFactors[l];\n        atom.G[memberIndex[l]] = members[l]->scale(result[l]);\n    }\n\n    delete[] result;\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpExpAngn.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPEXPANGN_H\n#define SYMGRPEXPANGN_H\n\n#include \"SymGrpBaseExpAng.h\"\n#include \"SymFncExpAngn.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\n\n/** Angular symmetry function group (type 3)\n *\n * @f[\n   G^3_i = 2^{1-\\zeta} \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n           \\left( 1 + \\lambda \\cos \\theta_{ijk} \\right)^\\zeta\n           \\mathrm{e}^{-\\eta( (r_{ij}-r_s)^2 + (r_{ik}-r_s)^2\n           + (r_{jk}-r_s)^2 ) }\n           f_c(r_{ij}) f_c(r_{ik}) f_c(r_{jk}) \n * @f]\n * Common features:\n * - element of central atom\n * - element of neighbor atom 1\n * - element of neighbor atom 2\n * - cutoff type\n * - @f$r_c@f$\n * - @f$\\alpha@f$\n */\nclass SymGrpExpAngn : public SymGrpBaseExpAng\n{\npublic:\n    /** Constructor, sets type = 3\n     */\n    SymGrpExpAngn(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n\nprivate:\n    /** Get symmetry function members.\n     *\n     * @return Vector of pointers casted to base class.\n     */\n    virtual std::vector<SymFncBaseExpAng const*> getMembers() const;\n\n    /// Vector of all group member pointers.\n    std::vector<SymFncExpAngn const*> members;\n};\n\ninline std::vector<SymFncBaseExpAng const*> SymGrpExpAngn::getMembers() const\n{\n    std::vector<SymFncBaseExpAng const*> cast;\n\n    for (auto p : members)\n    {\n        cast.push_back(dynamic_cast<SymFncBaseExpAng const*>(p));\n    }\n\n    return cast;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpExpAngnWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpExpAngnWeighted.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncExpAngnWeighted.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrpExpAngnWeighted::SymGrpExpAngnWeighted(ElementMap const& elementMap) :\n    SymGrpBaseCutoff(13, elementMap)\n{\n    parametersMember.insert(\"eta\");\n    parametersMember.insert(\"rs/rl\");\n    parametersMember.insert(\"lambda\");\n    parametersMember.insert(\"zeta\");\n    parametersMember.insert(\"mindex\");\n    parametersMember.insert(\"sfindex\");\n    parametersMember.insert(\"calcexp\");\n}\n\nbool SymGrpExpAngnWeighted::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymGrpExpAngnWeighted const& c =\n        dynamic_cast<SymGrpExpAngnWeighted const&>(rhs);\n    if (cutoffType  != c.cutoffType ) return false;\n    if (cutoffAlpha != c.cutoffAlpha) return false;\n    if (rc          != c.rc         ) return false;\n    return true;\n}\n\nbool SymGrpExpAngnWeighted::operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymGrpExpAngnWeighted const& c =\n        dynamic_cast<SymGrpExpAngnWeighted const&>(rhs);\n    if      (cutoffType  < c.cutoffType ) return true;\n    else if (cutoffType  > c.cutoffType ) return false;\n    if      (cutoffAlpha < c.cutoffAlpha) return true;\n    else if (cutoffAlpha > c.cutoffAlpha) return false;\n    if      (rc          < c.rc         ) return true;\n    else if (rc          > c.rc         ) return false;\n    return false;\n}\n\nbool SymGrpExpAngnWeighted::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncExpAngnWeighted const* sf =\n        dynamic_cast<SymFncExpAngnWeighted const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        cutoffType  = sf->getCutoffType();\n        subtype     = sf->getSubtype();\n        cutoffAlpha = sf->getCutoffAlpha();\n        ec          = sf->getEc();\n        rc          = sf->getRc();\n        convLength  = sf->getConvLength();\n\n        fc.setCutoffType(cutoffType);\n        fc.setCutoffRadius(rc);\n        fc.setCutoffParameter(cutoffAlpha);\n    }\n\n    if (sf->getCutoffType()  != cutoffType ) return false;\n    if (sf->getCutoffAlpha() != cutoffAlpha) return false;\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getRc()          != rc         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpExpAngnWeighted::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncExpAngnWeighted const>);\n\n    // Members are now sorted with eta changing the slowest.\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        factorNorm.push_back(pow(2.0, 1.0 - members[i]->getZeta()));\n        factorDeriv.push_back(2.0 * members[i]->getEta() /\n                              members[i]->getZeta() / members[i]->getLambda());\n        if (i == 0)\n        {\n            calculateExp.push_back(true);\n        }\n        else\n        {\n            if ( members[i - 1]->getEta() != members[i]->getEta() ||\n                 members[i - 1]->getRs()  != members[i]->getRs() )\n            {\n                calculateExp.push_back(true);\n            }\n            else\n            {\n                calculateExp.push_back(false);\n            }\n        }\n        useIntegerPow.push_back(members[i]->getUseIntegerPow());\n        memberIndex.push_back(members[i]->getIndex());\n        zetaInt.push_back(members[i]->getZetaInt());\n        eta.push_back(members[i]->getEta());\n        rs.push_back(members[i]->getRs());\n        lambda.push_back(members[i]->getLambda());\n        zeta.push_back(members[i]->getZeta());\n        zetaLambda.push_back(members[i]->getZeta() * members[i]->getLambda());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n    }\n\n    return;\n}\n\nvoid SymGrpExpAngnWeighted::setScalingFactors()\n{\n    scalingFactors.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        scalingFactors.at(i) = members[i]->getScalingFactor();\n        factorNorm.at(i) *= scalingFactors.at(i);\n    }\n\n    return;\n}\n\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minimized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpExpAngnWeighted::calculate(Atom& atom, bool const derivatives) const\n{\n#ifndef N2P2_NO_SF_CACHE\n    // Can use cache indices of any member because this group is defined via\n    // identical symmetry function type and cutoff functions.\n    auto cacheIndices = members.at(0)->getCacheIndices();\n#endif\n    double* result = new double[members.size()];\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        result[l] = 0.0;\n    }\n\n    double const rc2 = rc * rc;\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n        if (rij < rc)\n        {\n            double const r2ij = rij * rij;\n\n            // Calculate cutoff function and derivative.\n            double pfcij;\n            double pdfcij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) fc.fdf(rij, pfcij, pdfcij);\n            else\n            {\n                double& cfc = nj.cache[cacheIndices[nej][0]];\n                double& cdfc = nj.cache[cacheIndices[nej][1]];\n                if (cfc < 0) fc.fdf(rij, cfc, cdfc);\n                pfcij = cfc;\n                pdfcij = cdfc;\n            }\n#else\n            fc.fdf(rij, pfcij, pdfcij);\n#endif\n            // SIMPLE EXPRESSIONS:\n            //Vec3D const drij(atom.neighbors[j].dr);\n            //double const* const dr1 = drij.r;\n            double const* const dr1 = nj.dr.r;\n\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                double const rik = nk.d;\n                if (rik < rc)\n                {\n                    // SIMPLE EXPRESSIONS:\n                    //Vec3D const drjk(atom.neighbors[k].dr\n                    //               - atom.neighbors[j].dr);\n                    //double rjk = drjk.norm2();\n                    double const* const dr2 = nk.dr.r;\n                    double dr3[3];\n                    dr3[0] = dr2[0] - dr1[0];\n                    dr3[1] = dr2[1] - dr1[1];\n                    dr3[2] = dr2[2] - dr1[2];\n                    double rjk = dr3[0] * dr3[0]\n                               + dr3[1] * dr3[1]\n                               + dr3[2] * dr3[2];\n                    if (rjk < rc2)\n                    {\n                        // Energy calculation.\n                        double pfcik;\n                        double pdfcik;\n#ifndef N2P2_NO_SF_CACHE\n                        if (cacheIndices[nej].size() == 0)\n                        {\n                            fc.fdf(rik, pfcik, pdfcik);\n                        }\n                        else\n                        {\n                            double& cfc = nk.cache[cacheIndices[nek][0]];\n                            double& cdfc = nk.cache[cacheIndices[nek][1]];\n                            if (cfc < 0) fc.fdf(rik, cfc, cdfc);\n                            pfcik = cfc;\n                            pdfcik = cdfc;\n                        }\n#else\n                        fc.fdf(rik, pfcik, pdfcik);\n#endif\n                        rjk = sqrt(rjk);\n\n                        double pfcjk;\n                        double pdfcjk;\n                        fc.fdf(rjk, pfcjk, pdfcjk);\n\n                        // SIMPLE EXPRESSIONS:\n                        //Vec3D const drik(atom.neighbors[k].dr);\n                        //double const* const dr2 = drik.r;\n                        //double const* const dr3 = drjk.r;\n                        double const rinvijik = 1.0 / rij / rik;\n                        // SIMPLE EXPRESSIONS:\n                        //double const costijk = (drij * drik) * rinvijik;\n                        double const costijk = (dr1[0] * dr2[0] +\n                                                dr1[1] * dr2[1] +\n                                                dr1[2] * dr2[2]) * rinvijik;\n                        double const z = elementMap.atomicNumber(nej)\n                                       * elementMap.atomicNumber(nek);\n                        double const pfc = z * pfcij * pfcik * pfcjk;\n                        double const r2ik = rik * rik;\n                        double const pr1 = z * pfcik * pfcjk * pdfcij / rij;\n                        double const pr2 = z * pfcij * pfcjk * pdfcik / rik;\n                        double const pr3 = z * pfcij * pfcik * pdfcjk / rjk;\n                        double vexp = 0.0;\n                        double rijs = 0.0;\n                        double riks = 0.0;\n                        double rjks = 0.0;\n\n                        for (size_t l = 0; l < members.size(); ++l)\n                        {\n                            if (calculateExp[l])\n                            {\n                                rijs = rij - rs[l];\n                                riks = rik - rs[l];\n                                rjks = rjk - rs[l];\n                                double const r2sum = rijs * rijs\n                                                   + riks * riks\n                                                   + rjks * rjks;\n                                vexp = exp(-eta[l] * r2sum);\n                            }\n                            double const plambda = 1.0\n                                                 + lambda[l] * costijk;\n                            double fg = vexp;\n                            if (plambda <= 0.0) fg = 0.0;\n                            else\n                            {\n                                if (useIntegerPow[l])\n                                {\n                                    fg *= pow_int(plambda, zetaInt[l] - 1);\n                                }\n                                else\n                                {\n                                    fg *= pow(plambda, zeta[l] - 1.0);\n                                }\n                            }\n                            result[l] += fg * plambda * pfc;\n\n                            // Force calculation.\n                            if (!derivatives) continue;\n                            fg *= factorNorm[l];\n                            double const pfczl = pfc * zetaLambda[l];\n                            double const p2etapl = plambda * factorDeriv[l];\n                            double const p1 = fg * (pfczl * (rinvijik - costijk\n                                            / r2ij - p2etapl * rijs / rij)\n                                            + pr1 * plambda);\n                            double const p2 = fg * (pfczl * (rinvijik - costijk\n                                            / r2ik - p2etapl * riks / rik)\n                                            + pr2 * plambda);\n                            double const p3 = fg * (pfczl * (rinvijik + p2etapl\n                                            * rjks / rjk) - pr3 * plambda);\n\n                            // Save force contributions in Atom storage.\n                            //\n                            // SIMPLE EXPRESSIONS:\n                            //size_t const li = members[l]->getIndex();\n                            //atom.dGdr[li] += p1 * drij + p2 * drik;\n                            //atom.neighbors[j].dGdr[li] -= p1 * drij\n                            //                            + p3 * drjk;\n                            //atom.neighbors[k].dGdr[li] -= p2 * drik\n                            //                            - p3 * drjk;\n\n                            double const p1drijx = p1 * dr1[0];\n                            double const p1drijy = p1 * dr1[1];\n                            double const p1drijz = p1 * dr1[2];\n\n                            double const p2drikx = p2 * dr2[0];\n                            double const p2driky = p2 * dr2[1];\n                            double const p2drikz = p2 * dr2[2];\n\n                            double const p3drjkx = p3 * dr3[0];\n                            double const p3drjky = p3 * dr3[1];\n                            double const p3drjkz = p3 * dr3[2];\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            size_t li = memberIndex[l];\n#else\n                            size_t const li = memberIndex[l];\n#endif\n                            double* dGdr = atom.dGdr[li].r;\n                            dGdr[0] += p1drijx + p2drikx;\n                            dGdr[1] += p1drijy + p2driky;\n                            dGdr[2] += p1drijz + p2drikz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            li = memberIndexPerElement[l][nej];\n#endif\n                            dGdr = nj.dGdr[li].r;\n                            dGdr[0] -= p1drijx + p3drjkx;\n                            dGdr[1] -= p1drijy + p3drjky;\n                            dGdr[2] -= p1drijz + p3drjkz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            li = memberIndexPerElement[l][nek];\n#endif\n                            dGdr = nk.dGdr[li].r;\n                            dGdr[0] -= p2drikx - p3drjkx;\n                            dGdr[1] -= p2driky - p3drjky;\n                            dGdr[2] -= p2drikz - p3drjkz;\n                        } // l\n                    } // rjk <= rc\n                } // rik <= rc\n            } // k\n        } // rij <= rc\n    } // j\n\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        result[l] *= factorNorm[l] / scalingFactors[l];\n        atom.G[memberIndex[l]] = members[l]->scale(result[l]);\n    }\n\n    delete[] result;\n\n    return;\n}\n\nvector<string> SymGrpExpAngnWeighted::parameterLines() const\n{\n    vector<string> v;\n\n    v.push_back(strpr(getPrintFormatCommon().c_str(),\n                      index + 1,\n                      elementMap[ec].c_str(),\n                      type,\n                      subtype.c_str(),\n                      rc / convLength,\n                      cutoffAlpha));\n\n    for (size_t i = 0; i < members.size(); ++i)\n    {\n        v.push_back(strpr(getPrintFormatMember().c_str(),\n                          members[i]->getEta() * convLength * convLength,\n                          members[i]->getRs() / convLength,\n                          members[i]->getLambda(),\n                          members[i]->getZeta(),\n                          members[i]->getLineNumber() + 1,\n                          i + 1,\n                          members[i]->getIndex() + 1,\n                          (int)calculateExp[i]));\n    }\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpExpAngnWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPEXPANGNWEIGHTED_H\n#define SYMGRPEXPANGNWEIGHTED_H\n\n#include \"SymGrpBaseCutoff.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\nclass SymFncExpAngnWeighted;\n\n/** Weighted angular symmetry function group (type 13)\n *\n * @f[\n   G^{13}_i = 2^{1-\\zeta} \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n              Z_j Z_k \\,\n              \\left( 1 + \\lambda \\cos \\theta_{ijk} \\right)^\\zeta\n              \\mathrm{e}^{-\\eta \\left[\n              (r_{ij} - r_s)^2 + (r_{ik} - r_s)^2 + (r_{jk} - r_s)^2 \\right] }\n              f_c(r_{ij}) f_c(r_{ik}) f_c(r_{jk}) \n * @f]\n * Common features:\n * - element of central atom\n * - cutoff type\n * - @f$r_c@f$\n * - @f$\\alpha@f$\n */\nclass SymGrpExpAngnWeighted : public SymGrpBaseCutoff\n{\npublic:\n    /** Constructor, sets type = 13\n     */\n    SymGrpExpAngnWeighted(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Fill #scalingFactors with values from member symmetry functions.\n     */\n    virtual void setScalingFactors();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n    /** Give symmetry function group parameters on multiple lines.\n     *\n     * @return Vector of string containing symmetry function parameters lines.\n     */\n    virtual std::vector<std::string>\n                 parameterLines() const;\n\nprivate:\n    /// Vector of all group member pointers.\n    std::vector<SymFncExpAngnWeighted const*> members;\n    /// Vector indicating whether exponential term needs to be calculated.\n    std::vector<bool>                         calculateExp;\n    /// Vector containing precalculated normalizing factor for each zeta.\n    std::vector<double>                       factorNorm;\n    /// Vector containing precalculated normalizing factor for derivatives.\n    std::vector<double>                       factorDeriv;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<bool>                         useIntegerPow;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<int>                          zetaInt;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double>                       eta;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double>                       rs;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double>                       lambda;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double>                       zeta;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double>                       zetaLambda;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpExpAngw.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpExpAngw.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncExpAngw.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrpExpAngw::SymGrpExpAngw(ElementMap const& elementMap) :\n    SymGrpBaseExpAng(9, elementMap)\n{\n}\n\nbool SymGrpExpAngw::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymGrpExpAngw const& c = dynamic_cast<SymGrpExpAngw const&>(rhs);\n    if (cutoffType  != c.cutoffType ) return false;\n    if (cutoffAlpha != c.cutoffAlpha) return false;\n    if (rc          != c.rc         ) return false;\n    if (e1          != c.e1         ) return false;\n    if (e2          != c.e2         ) return false;\n    return true;\n}\n\nbool SymGrpExpAngw::operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymGrpExpAngw const& c = dynamic_cast<SymGrpExpAngw const&>(rhs);\n    if      (cutoffType  < c.cutoffType ) return true;\n    else if (cutoffType  > c.cutoffType ) return false;\n    if      (cutoffAlpha < c.cutoffAlpha) return true;\n    else if (cutoffAlpha > c.cutoffAlpha) return false;\n    if      (rc          < c.rc         ) return true;\n    else if (rc          > c.rc         ) return false;\n    if      (e1          < c.e1         ) return true;\n    else if (e1          > c.e1         ) return false;\n    if      (e2          < c.e2         ) return true;\n    else if (e2          > c.e2         ) return false;\n    return false;\n}\n\nbool SymGrpExpAngw::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncExpAngw const* sf =\n        dynamic_cast<SymFncExpAngw const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        cutoffType  = sf->getCutoffType();\n        subtype     = sf->getSubtype();\n        cutoffAlpha = sf->getCutoffAlpha();\n        ec          = sf->getEc();\n        rc          = sf->getRc();\n        e1          = sf->getE1();\n        e2          = sf->getE2();\n        convLength  = sf->getConvLength();\n\n        fc.setCutoffType(cutoffType);\n        fc.setCutoffRadius(rc);\n        fc.setCutoffParameter(cutoffAlpha);\n    }\n\n    if (sf->getCutoffType()  != cutoffType ) return false;\n    if (sf->getCutoffAlpha() != cutoffAlpha) return false;\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getRc()          != rc         ) return false;\n    if (sf->getE1()          != e1         ) return false;\n    if (sf->getE2()          != e2         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpExpAngw::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncExpAngw const>);\n\n    // Members are now sorted with eta changing the slowest.\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        factorNorm.push_back(pow(2.0, 1.0 - members[i]->getZeta()));\n        factorDeriv.push_back(2.0 * members[i]->getEta() /\n                              members[i]->getZeta() / members[i]->getLambda());\n        if (i == 0)\n        {\n            calculateExp.push_back(true);\n        }\n        else\n        {\n            if ( members[i - 1]->getEta() != members[i]->getEta() ||\n                 members[i - 1]->getRs()  != members[i]->getRs() )\n            {\n                calculateExp.push_back(true);\n            }\n            else\n            {\n                calculateExp.push_back(false);\n            }\n        }\n        useIntegerPow.push_back(members[i]->getUseIntegerPow());\n        memberIndex.push_back(members[i]->getIndex());\n        zetaInt.push_back(members[i]->getZetaInt());\n        eta.push_back(members[i]->getEta());\n        rs.push_back(members[i]->getRs());\n        zeta.push_back(members[i]->getZeta());\n        lambda.push_back(members[i]->getLambda());\n        zetaLambda.push_back(members[i]->getZeta() * members[i]->getLambda());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n    }\n\n    return;\n}\n\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minimized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpExpAngw::calculate(Atom& atom, bool const derivatives) const\n{\n#ifndef N2P2_NO_SF_CACHE\n    // Can use cache indices of any member because this group is defined via\n    // identical symmetry function type, neighbors and cutoff functions.\n    auto cacheIndices = members.at(0)->getCacheIndices();\n#endif\n    double* result = new double[members.size()];\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        result[l] = 0.0;\n    }\n\n    size_t numNeighbors = atom.numNeighbors;\n    // Prevent problematic condition in loop test below (j < numNeighbors - 1).\n    if (numNeighbors == 0) numNeighbors = 1;\n\n    for (size_t j = 0; j < numNeighbors - 1; j++)\n    {\n        Atom::Neighbor& nj = atom.neighbors[j];\n        size_t const nej = nj.element;\n        double const rij = nj.d;\n        if ((e1 == nej || e2 == nej) && rij < rc)\n        {\n            double const r2ij = rij * rij;\n\n            // Calculate cutoff function and derivative.\n            double pfcij;\n            double pdfcij;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) fc.fdf(rij, pfcij, pdfcij);\n            else\n            {\n                double& cfc = nj.cache[cacheIndices[nej][0]];\n                double& cdfc = nj.cache[cacheIndices[nej][1]];\n                if (cfc < 0) fc.fdf(rij, cfc, cdfc);\n                pfcij = cfc;\n                pdfcij = cdfc;\n            }\n#else\n            fc.fdf(rij, pfcij, pdfcij);\n#endif\n            // SIMPLE EXPRESSIONS:\n            //Vec3D drij(atom.neighbors[j].dr);\n            double const* const dr1 = nj.dr.r;\n\n            for (size_t k = j + 1; k < numNeighbors; k++)\n            {\n                Atom::Neighbor& nk = atom.neighbors[k];\n                size_t const nek = nk.element;\n                if ((e1 == nej && e2 == nek) ||\n                    (e2 == nej && e1 == nek))\n                {\n                    double const rik = nk.d;\n                    if (rik < rc)\n                    {\n                        // SIMPLE EXPRESSIONS:\n                        //Vec3D drik(atom.neighbors[k].dr);\n                        //Vec3D drjk = drik - drij;\n                        double const* const dr2 = nk.dr.r;\n                        double const dr30 = dr2[0] - dr1[0];\n                        double const dr31 = dr2[1] - dr1[1];\n                        double const dr32 = dr2[2] - dr1[2];\n\n                        // Energy calculation.\n                        double pfcik;\n                        double pdfcik;\n#ifndef N2P2_NO_SF_CACHE\n                        if (cacheIndices[nek].size() == 0)\n                        {\n                            fc.fdf(rik, pfcik, pdfcik);\n                        }\n                        else\n                        {\n                            double& cfc = nk.cache[cacheIndices[nek][0]];\n                            double& cdfc = nk.cache[cacheIndices[nek][1]];\n                            if (cfc < 0) fc.fdf(rik, cfc, cdfc);\n                            pfcik = cfc;\n                            pdfcik = cdfc;\n                        }\n#else\n                        fc.fdf(rik, pfcik, pdfcik);\n#endif\n                        double const rinvijik = 1.0 / rij / rik;\n                        // SIMPLE EXPRESSIONS:\n                        //double const costijk = drij * drik * rinvijik;\n                        double const costijk = (dr1[0] * dr2[0] +\n                                                dr1[1] * dr2[1] +\n                                                dr1[2] * dr2[2]) * rinvijik;\n                        double const pfc = pfcij * pfcik;\n                        double const r2ik = rik * rik;\n                        double const r2sum = r2ij + r2ik;\n                        double const pr1 = pfcik * pdfcij / rij;\n                        double const pr2 = pfcij * pdfcik / rik;\n                        double vexp = 0.0;\n                        double rijs = 0.0;\n                        double riks = 0.0;\n\n                        for (size_t l = 0; l < members.size(); ++l)\n                        {\n                            if (calculateExp[l])\n                            {\n                                if (rs[l] > 0.0)\n                                {\n                                    rijs = rij - rs[l];\n                                    riks = rik - rs[l];\n                                    vexp = exp(-eta[l] * (rijs * rijs\n                                                        + riks * riks));\n                                }\n                                else\n                                {\n                                    vexp = exp(-eta[l] * r2sum);\n                                }\n                            }\n                            double const plambda = 1.0 + lambda[l] * costijk;\n                            double fg = vexp;\n                            if (plambda <= 0.0) fg = 0.0;\n                            else\n                            {\n                                if (useIntegerPow[l])\n                                {\n                                    fg *= pow_int(plambda, zetaInt[l] - 1);\n                                }\n                                else\n                                {\n                                    fg *= pow(plambda, zeta[l] - 1.0);\n                                }\n                            }\n                            result[l] += fg * plambda * pfc;\n\n                            // Force calculation.\n                            if (!derivatives) continue;\n                            fg *= factorNorm[l];\n                            double const pfczl = pfc * zetaLambda[l];\n                            double const p2etapl = plambda * factorDeriv[l];\n                            double p1;\n                            double p2;\n                            if (rs[l] > 0)\n                            {\n                                p1 = fg * (pfczl * (rinvijik\n                                   - costijk / r2ij - p2etapl\n                                   * rijs / rij) + pr1 * plambda);\n                                p2 = fg * (pfczl * (rinvijik\n                                   - costijk / r2ik - p2etapl\n                                   * riks / rik) + pr2 * plambda);\n                            }\n                            else\n                            {\n                                p1 = fg * (pfczl * (rinvijik - costijk / r2ij\n                                   - p2etapl) + pr1 * plambda);\n                                p2 = fg * (pfczl * (rinvijik - costijk / r2ik\n                                   - p2etapl) + pr2 * plambda);\n\n                            }\n                            double const p3 = fg * pfczl * rinvijik;\n\n                            // SIMPLE EXPRESSIONS:\n                            // Save force contributions in Atom storage.\n                            //atom.dGdr[memberIndex[l]] += p1 * drij\n                            //                           + p2 * drik;\n                            //atom.neighbors[j].\n                            //    dGdr[memberIndex[l]] -= p1 * drij\n                            //                          + p3 * drjk;\n                            //atom.neighbors[k].\n                            //    dGdr[memberIndex[l]] -= p2 * drik\n                            //                          - p3 * drjk;\n\n                            double const p1drijx = p1 * dr1[0];\n                            double const p1drijy = p1 * dr1[1];\n                            double const p1drijz = p1 * dr1[2];\n\n                            double const p2drikx = p2 * dr2[0];\n                            double const p2driky = p2 * dr2[1];\n                            double const p2drikz = p2 * dr2[2];\n\n                            double const p3drjkx = p3 * dr30;\n                            double const p3drjky = p3 * dr31;\n                            double const p3drjkz = p3 * dr32;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            size_t li = memberIndex[l];\n#else\n                            size_t const li = memberIndex[l];\n#endif\n                            double* dGdr = atom.dGdr[li].r;\n                            dGdr[0] += p1drijx + p2drikx;\n                            dGdr[1] += p1drijy + p2driky;\n                            dGdr[2] += p1drijz + p2drikz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            li = memberIndexPerElement[l][nej];\n#endif\n                            dGdr = nj.dGdr[li].r;\n                            dGdr[0] -= p1drijx + p3drjkx;\n                            dGdr[1] -= p1drijy + p3drjky;\n                            dGdr[2] -= p1drijz + p3drjkz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                            li = memberIndexPerElement[l][nek];\n#endif\n                            dGdr = nk.dGdr[li].r;\n                            dGdr[0] -= p2drikx - p3drjkx;\n                            dGdr[1] -= p2driky - p3drjky;\n                            dGdr[2] -= p2drikz - p3drjkz;\n                        } // l\n                    } // rik <= rc\n                } // elem\n            } // k\n        } // rij <= rc\n    } // j\n\n    for (size_t l = 0; l < members.size(); ++l)\n    {\n        result[l] *= factorNorm[l] / scalingFactors[l];\n        atom.G[memberIndex[l]] = members[l]->scale(result[l]);\n    }\n\n    delete[] result;\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnp/SymGrpExpAngw.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPEXPANGW_H\n#define SYMGRPEXPANGW_H\n\n#include \"SymGrpBaseExpAng.h\"\n#include \"SymFncExpAngw.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\n\n/** Angular symmetry function group (type 3)\n *\n * @f[\n   G^9_i = 2^{1-\\zeta} \\sum_{\\substack{j,k\\neq i \\\\ j < k}}\n           \\left( 1 + \\lambda \\cos \\theta_{ijk} \\right)^\\zeta\n           \\mathrm{e}^{-\\eta( (r_{ij}-r_s)^2 + (r_{ik}-r_s)^2 ) }\n           f_c(r_{ij}) f_c(r_{ik}) \n * @f]\n * Common features:\n * - element of central atom\n * - element of neighbor atom 1\n * - element of neighbor atom 2\n * - cutoff type\n * - @f$r_c@f$\n * - @f$\\alpha@f$\n */\nclass SymGrpExpAngw : public SymGrpBaseExpAng\n{\npublic:\n    /** Constructor, sets type = 3\n     */\n    SymGrpExpAngw(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n\nprivate:\n    /** Get symmetry function members.\n     *\n     * @return Vector of pointers casted to base class.\n     */\n    virtual std::vector<SymFncBaseExpAng const*> getMembers() const;\n\n    /// Vector of all group member pointers.\n    std::vector<SymFncExpAngw const*> members;\n};\n\ninline std::vector<SymFncBaseExpAng const*> SymGrpExpAngw::getMembers() const\n{\n    std::vector<SymFncBaseExpAng const*> cast;\n\n    for (auto p : members)\n    {\n        cast.push_back(dynamic_cast<SymFncBaseExpAng const*>(p));\n    }\n\n    return cast;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpExpRad.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpExpRad.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncExpRad.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrpExpRad::SymGrpExpRad(ElementMap const& elementMap) :\n    SymGrpBaseCutoff(2, elementMap),\n    e1(0)\n{\n    parametersCommon.insert(\"e1\");\n\n    parametersMember.insert(\"eta\");\n    parametersMember.insert(\"rs/rl\");\n    parametersMember.insert(\"mindex\");\n    parametersMember.insert(\"sfindex\");\n}\n\nbool SymGrpExpRad::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymGrpExpRad const& c = dynamic_cast<SymGrpExpRad const&>(rhs);\n    if (cutoffType  != c.cutoffType ) return false;\n    if (cutoffAlpha != c.cutoffAlpha) return false;\n    if (rc          != c.rc         ) return false;\n    if (e1          != c.e1         ) return false;\n    return true;\n}\n\nbool SymGrpExpRad::operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymGrpExpRad const& c = dynamic_cast<SymGrpExpRad const&>(rhs);\n    if      (cutoffType  < c.cutoffType ) return true;\n    else if (cutoffType  > c.cutoffType ) return false;\n    if      (cutoffAlpha < c.cutoffAlpha) return true;\n    else if (cutoffAlpha > c.cutoffAlpha) return false;\n    if      (rc          < c.rc         ) return true;\n    else if (rc          > c.rc         ) return false;\n    if      (e1          < c.e1         ) return true;\n    else if (e1          > c.e1         ) return false;\n    return false;\n}\n\nbool SymGrpExpRad::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncExpRad const* sf =\n        dynamic_cast<SymFncExpRad const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        cutoffType  = sf->getCutoffType();\n        subtype     = sf->getSubtype();\n        cutoffAlpha = sf->getCutoffAlpha();\n        ec          = sf->getEc();\n        rc          = sf->getRc();\n        e1          = sf->getE1();\n        convLength  = sf->getConvLength();\n\n        fc.setCutoffType(cutoffType);\n        fc.setCutoffRadius(rc);\n        fc.setCutoffParameter(cutoffAlpha);\n    }\n\n    if (sf->getCutoffType()  != cutoffType ) return false;\n    if (sf->getCutoffAlpha() != cutoffAlpha) return false;\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getRc()          != rc         ) return false;\n    if (sf->getE1()          != e1         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpExpRad::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncExpRad const>);\n\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        memberIndex.push_back(members[i]->getIndex());\n        eta.push_back(members[i]->getEta());\n        rs.push_back(members[i]->getRs());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n    }\n\n    return;\n}\n\nvoid SymGrpExpRad::setScalingFactors()\n{\n    scalingFactors.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        scalingFactors.at(i) = members[i]->getScalingFactor();\n    }\n\n    return;\n}\n\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minmized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpExpRad::calculate(Atom& atom, bool const derivatives) const\n{\n#ifndef N2P2_NO_SF_CACHE\n    // Can use cache indices of any member because this group is defined via\n    // identical symmetry function type, neighbors and cutoff functions.\n    auto cacheIndices = members.at(0)->getCacheIndices();\n    bool unique = true;\n    size_t c0 = 0;\n    size_t c1 = 0;\n    if (cacheIndices.at(e1).size() > 0)\n    {\n        unique = false;\n        c0 = cacheIndices.at(e1).at(0);\n        c1 = cacheIndices.at(e1).at(1);\n    }\n#endif\n    double* result = new double[members.size()];\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        result[k] = 0.0;\n    }\n\n    for (size_t j = 0; j < atom.getStoredMinNumNeighbors(rc); ++j)\n    {\n        Atom::Neighbor& n = atom.neighbors[j];\n        if (e1 == n.element && n.d < rc)\n        {\n            // Energy calculation.\n            double const rij = n.d;\n\n            // Calculate cutoff function and derivative.\n            double pfc;\n            double pdfc;\n#ifndef N2P2_NO_SF_CACHE\n            if (unique) fc.fdf(rij, pfc, pdfc);\n            else\n            {\n                double& cfc = n.cache[c0];\n                double& cdfc = n.cache[c1];\n                if (cfc < 0) fc.fdf(rij, cfc, cdfc);\n                pfc = cfc;\n                pdfc = cdfc;\n            }\n#else\n            fc.fdf(rij, pfc, pdfc);\n#endif\n            double const* const d1 = n.dr.r;\n            for (size_t k = 0; k < members.size(); ++k)\n            {\n                double pexp = exp(-eta[k] * (rij - rs[k]) * (rij - rs[k]));\n                result[k] += pexp * pfc;\n                // Force calculation.\n                if (!derivatives) continue;\n                double const p1 = scalingFactors[k] * (pdfc - 2.0 * eta[k]\n                                * (rij - rs[k]) * pfc) * pexp / rij;\n                // SIMPLE EXPRESSIONS:\n                //Vec3D const dij = p1 * atom.neighbors[j].dr;\n                double const p1drijx = p1 * d1[0];\n                double const p1drijy = p1 * d1[1];\n                double const p1drijz = p1 * d1[2];\n\n                // Save force contributions in Atom storage.\n#ifndef N2P2_FULL_SFD_MEMORY\n                size_t ki = memberIndex[k];\n#else\n                size_t const ki = memberIndex[k];\n#endif\n                // SIMPLE EXPRESSIONS:\n                //atom.dGdr[ki]              += dij;\n                //atom.neighbors[j].dGdr[ki] -= dij;\n\n                double* dGdr = atom.dGdr[ki].r;\n                dGdr[0] += p1drijx;\n                dGdr[1] += p1drijy;\n                dGdr[2] += p1drijz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                ki = memberIndexPerElement[k][e1];\n#endif\n                dGdr = n.dGdr[ki].r;\n                dGdr[0] -= p1drijx;\n                dGdr[1] -= p1drijy;\n                dGdr[2] -= p1drijz;\n            }\n        }\n    }\n\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        atom.G[memberIndex[k]] = members[k]->scale(result[k]);\n    }\n\n    delete[] result;\n\n    return;\n}\n\nvector<string> SymGrpExpRad::parameterLines() const\n{\n    vector<string> v;\n\n    v.push_back(strpr(getPrintFormatCommon().c_str(),\n                      index + 1,\n                      elementMap[ec].c_str(),\n                      type,\n                      subtype.c_str(),\n                      elementMap[e1].c_str(),\n                      rc / convLength,\n                      cutoffAlpha));\n\n    for (size_t i = 0; i < members.size(); ++i)\n    {\n        v.push_back(strpr(getPrintFormatMember().c_str(),\n                          members[i]->getEta() * convLength * convLength,\n                          members[i]->getRs() / convLength,\n                          members[i]->getLineNumber() + 1,\n                          i + 1,\n                          members[i]->getIndex() + 1));\n    }\n\n    return v;\n}\n\n"
  },
  {
    "path": "src/libnnp/SymGrpExpRad.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPEXPRAD_H\n#define SYMGRPEXPRAD_H\n\n#include \"SymGrpBaseCutoff.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\nclass SymFncExpRad;\n\n/** Radial symmetry function group (type 2)\n *\n * @f[\n * G^2_i = \\sum_{j \\neq i} \\mathrm{e}^{-\\eta(r_{ij} - r_\\mathrm{s})^2}\n *         f_c(r_{ij}) \n * @f]\n * Common features:\n * - element of central atom\n * - element of neighbor atom\n * - cutoff type\n * - @f$r_c@f$\n * - @f$\\alpha@f$\n */\nclass SymGrpExpRad : public SymGrpBaseCutoff\n{\npublic:\n    /** Constructor, sets type = 2\n     */\n    SymGrpExpRad(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Fill #scalingFactors with values from member symmetry functions.\n     */\n    virtual void setScalingFactors();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n    /** Give symmetry function group parameters on multiple lines.\n     *\n     * @return Vector of string containing symmetry function parameters lines.\n     */\n    virtual std::vector<std::string>\n                 parameterLines() const;\n\nprivate:\n    /// Element index of neighbor atom (common feature).\n    std::size_t                      e1;\n    /// Vector of all group member pointers.\n    std::vector<SymFncExpRad const*> members;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double>              eta;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double>              rs;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/SymGrpExpRadWeighted.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"SymGrpExpRadWeighted.h\"\n#include \"Atom.h\"\n#include \"SymFnc.h\"\n#include \"SymFncExpRadWeighted.h\"\n#include \"Vec3D.h\"\n#include \"utility.h\"\n#include <algorithm> // std::sort\n#include <cmath>     // exp\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\nusing namespace nnp;\n\nSymGrpExpRadWeighted::SymGrpExpRadWeighted(ElementMap const& elementMap) :\n    SymGrpBaseCutoff(12, elementMap)\n{\n    parametersMember.insert(\"eta\");\n    parametersMember.insert(\"rs/rl\");\n    parametersMember.insert(\"mindex\");\n    parametersMember.insert(\"sfindex\");\n}\n\nbool SymGrpExpRadWeighted::operator==(SymGrp const& rhs) const\n{\n    if (ec   != rhs.getEc()  ) return false;\n    if (type != rhs.getType()) return false;\n    SymGrpExpRadWeighted const& c =\n        dynamic_cast<SymGrpExpRadWeighted const&>(rhs);\n    if (cutoffType  != c.cutoffType ) return false;\n    if (cutoffAlpha != c.cutoffAlpha) return false;\n    if (rc          != c.rc         ) return false;\n    return true;\n}\n\nbool SymGrpExpRadWeighted::operator<(SymGrp const& rhs) const\n{\n    if      (ec   < rhs.getEc()  ) return true;\n    else if (ec   > rhs.getEc()  ) return false;\n    if      (type < rhs.getType()) return true;\n    else if (type > rhs.getType()) return false;\n    SymGrpExpRadWeighted const& c =\n        dynamic_cast<SymGrpExpRadWeighted const&>(rhs);\n    if      (cutoffType  < c.cutoffType ) return true;\n    else if (cutoffType  > c.cutoffType ) return false;\n    if      (cutoffAlpha < c.cutoffAlpha) return true;\n    else if (cutoffAlpha > c.cutoffAlpha) return false;\n    if      (rc          < c.rc         ) return true;\n    else if (rc          > c.rc         ) return false;\n    return false;\n}\n\nbool SymGrpExpRadWeighted::addMember(SymFnc const* const symmetryFunction)\n{\n    if (symmetryFunction->getType() != type) return false;\n\n    SymFncExpRadWeighted const* sf =\n        dynamic_cast<SymFncExpRadWeighted const*>(symmetryFunction);\n\n    if (members.empty())\n    {\n        cutoffType  = sf->getCutoffType();\n        subtype     = sf->getSubtype();\n        cutoffAlpha = sf->getCutoffAlpha();\n        ec          = sf->getEc();\n        rc          = sf->getRc();\n        convLength  = sf->getConvLength();\n\n        fc.setCutoffType(cutoffType);\n        fc.setCutoffRadius(rc);\n        fc.setCutoffParameter(cutoffAlpha);\n    }\n\n    if (sf->getCutoffType()  != cutoffType ) return false;\n    if (sf->getCutoffAlpha() != cutoffAlpha) return false;\n    if (sf->getEc()          != ec         ) return false;\n    if (sf->getRc()          != rc         ) return false;\n    if (sf->getConvLength()  != convLength )\n    {\n        throw runtime_error(\"ERROR: Unable to add symmetry function members \"\n                            \"with different conversion factors.\\n\");\n    }\n\n    members.push_back(sf);\n\n    return true;\n}\n\nvoid SymGrpExpRadWeighted::sortMembers()\n{\n    sort(members.begin(),\n         members.end(),\n         comparePointerTargets<SymFncExpRadWeighted const>);\n\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        memberIndex.push_back(members[i]->getIndex());\n        eta.push_back(members[i]->getEta());\n        rs.push_back(members[i]->getRs());\n        memberIndexPerElement.push_back(members[i]->getIndexPerElement());\n    }\n\n    return;\n}\n\nvoid SymGrpExpRadWeighted::setScalingFactors()\n{\n    scalingFactors.resize(members.size(), 0.0);\n    for (size_t i = 0; i < members.size(); i++)\n    {\n        scalingFactors.at(i) = members[i]->getScalingFactor();\n    }\n\n    return;\n}\n\n// Depending on chosen symmetry functions this function may be very\n// time-critical when predicting new structures (e.g. in MD simulations). Thus,\n// lots of optimizations were used sacrificing some readablity. Vec3D\n// operations have been rewritten in simple C array style and the use of\n// temporary objects has been minmized. Some of the originally coded\n// expressions are kept in comments marked with \"SIMPLE EXPRESSIONS:\".\nvoid SymGrpExpRadWeighted::calculate(Atom& atom, bool const derivatives) const\n{\n#ifndef N2P2_NO_SF_CACHE\n    // Can use cache indices of any member because this group is defined via\n    // identical symmetry function type and cutoff functions.\n    auto cacheIndices = members.at(0)->getCacheIndices();\n#endif\n    double* result = new double[members.size()];\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        result[k] = 0.0;\n    }\n\n    for (size_t j = 0; j < atom.numNeighbors; ++j)\n    {\n        Atom::Neighbor& n = atom.neighbors[j];\n        if (n.d < rc)\n        {\n            // Energy calculation.\n            double const rij = n.d;\n            size_t const nej = n.element;\n\n            // Calculate cutoff function and derivative.\n            double pfc;\n            double pdfc;\n#ifndef N2P2_NO_SF_CACHE\n            if (cacheIndices[nej].size() == 0) fc.fdf(rij, pfc, pdfc);\n            else\n            {\n                double& cfc = n.cache[cacheIndices[nej][0]];\n                double& cdfc = n.cache[cacheIndices[nej][1]];\n                if (cfc < 0) fc.fdf(rij, cfc, cdfc);\n                pfc = cfc;\n                pdfc = cdfc;\n            }\n#else\n            fc.fdf(rij, pfc, pdfc);\n#endif\n            double const* const d1 = n.dr.r;\n            for (size_t k = 0; k < members.size(); ++k)\n            {\n                double pexp = elementMap.atomicNumber(nej)\n                            * exp(-eta[k] * (rij - rs[k]) * (rij - rs[k]));\n                result[k] += pexp * pfc;\n                // Force calculation.\n                if (!derivatives) continue;\n                double const p1 = scalingFactors[k] * (pdfc - 2.0 * eta[k]\n                                * (rij - rs[k]) * pfc) * pexp / rij;\n                // SIMPLE EXPRESSIONS:\n                //Vec3D const dij = p1 * atom.neighbors[j].dr;\n                double const p1drijx = p1 * d1[0];\n                double const p1drijy = p1 * d1[1];\n                double const p1drijz = p1 * d1[2];\n\n                // Save force contributions in Atom storage.\n#ifndef N2P2_FULL_SFD_MEMORY\n                size_t ki = memberIndex[k];\n#else\n                size_t const ki = memberIndex[k];\n#endif\n                // SIMPLE EXPRESSIONS:\n                //atom.dGdr[ki]              += dij;\n                //atom.neighbors[j].dGdr[ki] -= dij;\n\n                double* dGdr = atom.dGdr[ki].r;\n                dGdr[0] += p1drijx;\n                dGdr[1] += p1drijy;\n                dGdr[2] += p1drijz;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                ki = memberIndexPerElement[k][nej];\n#endif\n                dGdr = n.dGdr[ki].r;\n                dGdr[0] -= p1drijx;\n                dGdr[1] -= p1drijy;\n                dGdr[2] -= p1drijz;\n            }\n        }\n    }\n\n    for (size_t k = 0; k < members.size(); ++k)\n    {\n        atom.G[memberIndex[k]] = members[k]->scale(result[k]);\n    }\n\n    delete[] result;\n\n    return;\n}\n\nvector<string> SymGrpExpRadWeighted::parameterLines() const\n{\n    vector<string> v;\n\n    v.push_back(strpr(getPrintFormatCommon().c_str(),\n                      index + 1,\n                      elementMap[ec].c_str(),\n                      type,\n                      subtype.c_str(),\n                      rc / convLength,\n                      cutoffAlpha));\n\n    for (size_t i = 0; i < members.size(); ++i)\n    {\n        v.push_back(strpr(getPrintFormatMember().c_str(),\n                          members[i]->getEta() * convLength * convLength,\n                          members[i]->getRs() / convLength,\n                          members[i]->getLineNumber() + 1,\n                          i + 1,\n                          members[i]->getIndex() + 1));\n    }\n\n    return v;\n}\n\n"
  },
  {
    "path": "src/libnnp/SymGrpExpRadWeighted.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef SYMGRPEXPRADWEIGHTED_H\n#define SYMGRPEXPRADWEIGHTED_H\n\n#include \"SymGrpBaseCutoff.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nstruct Atom;\nclass ElementMap;\nclass SymFnc;\nclass SymFncExpRadWeighted;\n\n/** Weighted radial symmetry function group (type 12)\n *\n * @f[\n * G^{12}_i = \\sum_{j \\neq i} Z_j \\mathrm{e}^{-\\eta(r_{ij} - r_\\mathrm{s})^2}\n *            f_c(r_{ij}) \n * @f]\n * Common features:\n * - element of central atom\n * - cutoff type\n * - @f$r_c@f$\n * - @f$\\alpha@f$\n */\nclass SymGrpExpRadWeighted : public SymGrpBaseCutoff\n{\npublic:\n    /** Constructor, sets type = 12\n     */\n    SymGrpExpRadWeighted(ElementMap const& elementMap);\n    /** Overload == operator.\n     */\n    virtual bool operator==(SymGrp const& rhs) const;\n    /** Overload < operator.\n     */\n    virtual bool operator<(SymGrp const& rhs) const;\n    /** Potentially add a member to group.\n     *\n     * @param[in] symmetryFunction Candidate symmetry function.\n     * @return If addition was successful.\n     *\n     * If symmetry function is compatible with common feature list its pointer\n     * will be added to #members.\n     */\n    virtual bool addMember(SymFnc const* const symmetryFunction);\n    /** Sort member symmetry functions.\n     *\n     * Also allocate and precalculate additional stuff.\n     */\n    virtual void sortMembers();\n    /** Fill #scalingFactors with values from member symmetry functions.\n     */\n    virtual void setScalingFactors();\n    /** Calculate all symmetry functions of this group for one atom.\n     *\n     * @param[in,out] atom Atom for which symmetry functions are caluclated.\n     * @param[in] derivatives If also symmetry function derivatives will be\n     *                        calculated and saved.\n     */\n    virtual void calculate(Atom& atom, bool const derivatives) const;\n    /** Give symmetry function group parameters on multiple lines.\n     *\n     * @return Vector of string containing symmetry function parameters lines.\n     */\n    virtual std::vector<std::string>\n                 parameterLines() const;\n\nprivate:\n    /// Vector of all group member pointers.\n    std::vector<SymFncExpRadWeighted const*> members;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double>                      eta;\n    /// Vector containing values of all member symmetry functions.\n    std::vector<double>                      rs;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/Vec3D.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef VEC3D_H\n#define VEC3D_H\n\n#include <cstddef>   // std::size_t\n#include <utility>   // std::move\n#include <cmath>     // sqrt\n#include <stdexcept> // std::runtime_error\n\nnamespace nnp\n{\n\n/// Vector in 3 dimensional real space.\nstruct Vec3D\n{\n    /// cartesian coordinates.\n    double r[3];\n\n    /** Constructor, initializes to zero.\n     */\n    Vec3D();\n    /** Constructor, with initialization of coordinates.\n     */\n    Vec3D(double x, double y, double z);\n    /** Copy constructor.\n     */\n    Vec3D(Vec3D const& source);\n    /** Move constructor.\n     */\n    Vec3D(Vec3D&& source);\n    /** Overload = operator.\n     *\n     * @return Vector with copied data.\n     */\n    Vec3D&        operator=(Vec3D const& rhs);\n    /** Overload += operator to implement in-place vector addition.\n     *\n     * @return Replace original vector with sum of two vectors.\n     */\n    Vec3D&        operator+=(Vec3D const& v);\n    /** Overload -= operator to implement in-place vector subtraction.\n     *\n     * @return Replace original vector with original minus given.\n     */\n    Vec3D&        operator-=(Vec3D const& v);\n    /** Overload *= operator to implement multiplication with scalar.\n     *\n     * @return Original vector multiplied with scalar.\n     */\n    Vec3D&        operator*=(double const a);\n    /** Overload /= operator to implement division by scalar.\n     *\n     * @return Original vector divided by scalar.\n     */\n    Vec3D&        operator/=(double const a);\n    /** Overload * operator to implement scalar product.\n     *\n     * @return Scalar product of two vectors.\n     */\n    double        operator*(Vec3D const& v) const;\n    /** Overload * operator to implement (left) multiplication with a matrix\n     * defined as Vec3D A[3]. By convention A[i][j] gives the element of j-th\n     * row and i-th column.\n     *\n     * @return Original vector multiplied with a matrix.\n     */\n    Vec3D&        operator*=(Vec3D const  (& A) [3]);\n    /** Overload [] operator to return coordinate by index.\n     *\n     * @return x,y or z when index is 0, 1 or 2, respectively.\n     */\n    double&       operator[](std::size_t const index);\n    /** Overload [] operator to return coordinate by index (const version).\n     *\n     * @return x,y or z when index is 0, 1 or 2, respectively.\n     */\n    double const& operator[](std::size_t const index) const;\n    /** Compare if vectors are equal.\n     *\n     * @return `True` if all components are equal, `false` else.\n     */\n    bool          operator==(Vec3D const& rhs) const;\n    /** Compare if vectors are not equal.\n     *\n     * @return `False` if all components are equal, `false` else.\n     */\n    bool          operator!=(Vec3D const& rhs) const;\n    /** Calculate norm of vector.\n     *\n     * @return Norm of vector.\n     */\n    double        norm() const;\n    /** Calculate square of norm of vector.\n     *\n     * @return Square of norm of vector.\n     */\n    double        norm2() const;\n    /** Calculate l1 norm of vector (taxicab metric).\n     *\n     * @return L1-norm of vector.\n     */\n    double        l1norm() const;\n    /** Normalize vector, norm equals 1.0 afterwards.\n     */\n    Vec3D&        normalize();\n    /** Cross product, argument vector is second in product.\n     *\n     * @return Cross product of two vectors.\n     */\n    Vec3D         cross(Vec3D const& v) const;\n};\n\n/** Overload + operator to implement vector addition.\n *\n * @return Sum of two vectors.\n */\nVec3D operator+(Vec3D lhs, Vec3D const& rhs);\n/** Overload - operator to implement vector subtraction.\n *\n * @return Difference between two vectors.\n */\nVec3D operator-(Vec3D lhs, Vec3D const& rhs);\n/** Overload - operator to implement vector sign change.\n *\n * @return Negative vector.\n */\nVec3D operator-(Vec3D v);\n/** Overload * operator to implement multiplication with scalar.\n *\n * @return Vector multiplied with scalar.\n */\nVec3D operator*(Vec3D v, double const a);\n/** Overload * operator to implement (left) multiplication with a matrix.\n *\n * @return Vector multiplied with a matrix.\n */\nVec3D operator*(Vec3D const  (& A) [3], Vec3D v);\n/** Overload / operator to implement division by scalar.\n *\n * @return Vector divided by scalar.\n */\nVec3D operator/(Vec3D v, double const a);\n/** Overload * operator to implement multiplication with scalar (scalar first).\n *\n * @return Vector multiplied with scalar.\n */\nVec3D operator*(double const a, Vec3D v);\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline Vec3D::Vec3D()\n{\n    r[0] = 0.0;\n    r[1] = 0.0;\n    r[2] = 0.0;\n}\n\ninline Vec3D::Vec3D(double x, double y, double z)\n{\n    r[0] = x;\n    r[1] = y;\n    r[2] = z;\n}\n\ninline Vec3D::Vec3D(Vec3D const& source)\n{\n    r[0] = source.r[0];\n    r[1] = source.r[1];\n    r[2] = source.r[2];\n}\n\ninline Vec3D::Vec3D(Vec3D&& source)\n{\n    r[0] = std::move(source.r[0]);\n    r[1] = std::move(source.r[1]);\n    r[2] = std::move(source.r[2]);\n}\n\ninline Vec3D& Vec3D::operator=(Vec3D const& rhs)\n{\n    r[0] = rhs.r[0];\n    r[1] = rhs.r[1];\n    r[2] = rhs.r[2];\n\n    return *this;\n}\n\ninline Vec3D& Vec3D::operator+=(Vec3D const& rhs)\n{\n    r[0] += rhs.r[0];\n    r[1] += rhs.r[1];\n    r[2] += rhs.r[2];\n\n    return *this;\n}\n\ninline Vec3D& Vec3D::operator-=(Vec3D const& rhs)\n{\n    r[0] -= rhs.r[0];\n    r[1] -= rhs.r[1];\n    r[2] -= rhs.r[2];\n\n    return *this;\n}\n\ninline Vec3D& Vec3D::operator*=(double const a)\n{\n    r[0] *= a;\n    r[1] *= a;\n    r[2] *= a;\n\n    return *this;\n}\n\ninline Vec3D& Vec3D::operator*=(Vec3D const  (& A) [3])\n{\n    Vec3D w;\n    for (size_t i=0; i<3; ++i)\n    {\n        for (size_t j=0; j<3; ++j)\n        {\n            w.r[i] += A[j][i] * r[j];\n        }\n    }\n    *this = w;\n    return *this;\n}\n\ninline Vec3D& Vec3D::operator/=(double const a)\n{\n    *this *= 1.0 / a;\n\n    return *this;\n}\n\ninline double Vec3D::operator*(Vec3D const& v) const\n{\n    return r[0] * v.r[0] + r[1] * v.r[1] + r[2] * v.r[2];\n}\n\n\n// Doxygen requires namespace prefix for arguments...\ninline double& Vec3D::operator[](std::size_t const index)\n{\n    if (index < 3) return r[index];\n    else\n    {\n        throw std::runtime_error(\"ERROR: 3D vector has only three\"\n                                 \" components.\\n\");\n    }\n}\n\n// Doxygen requires namespace prefix for arguments...\ninline double const& Vec3D::operator[](std::size_t const index) const\n{\n    if (index < 3) return r[index];\n    else\n    {\n        throw std::runtime_error(\"ERROR: 3D vector has only three\"\n                                 \" components.\\n\");\n    }\n}\n\ninline bool Vec3D::operator==(Vec3D const& rhs) const\n{\n    if (r[0] != rhs.r[0]) return false;\n    if (r[1] != rhs.r[1]) return false;\n    if (r[2] != rhs.r[2]) return false;\n    return true;\n}\n\ninline bool Vec3D::operator!=(Vec3D const& rhs) const\n{\n    return !(*this == rhs);\n}\n\ninline double Vec3D::norm() const\n{\n    return sqrt(r[0] * r[0] + r[1] * r[1] + r[2] * r[2]);\n}\n\ninline double Vec3D::norm2() const\n{\n    return r[0] * r[0] + r[1] * r[1] + r[2] * r[2];\n}\n\ninline double Vec3D::l1norm() const\n{\n    return fabs(r[0]) + fabs(r[1]) + fabs(r[2]);\n}\n\ninline Vec3D& Vec3D::normalize()\n{\n    double n = norm();\n    r[0] /= n;\n    r[1] /= n;\n    r[2] /= n;\n\n    return *this;\n}\n\ninline Vec3D Vec3D::cross(Vec3D const& v) const\n{\n    Vec3D w;\n\n    w.r[0] = r[1] * v.r[2] - r[2] * v.r[1];\n    w.r[1] = r[2] * v.r[0] - r[0] * v.r[2];\n    w.r[2] = r[0] * v.r[1] - r[1] * v.r[0];\n\n    return w;\n}\n\ninline Vec3D operator+(Vec3D lhs, Vec3D const& rhs)\n{\n    return lhs += rhs;\n}\n\ninline Vec3D operator-(Vec3D lhs, Vec3D const& rhs)\n{\n    return lhs -= rhs;\n}\n\ninline Vec3D operator-(Vec3D v)\n{\n    v *= -1.0;\n    return v;\n}\n\ninline Vec3D operator*(Vec3D v, double const a)\n{\n    return v *= a;\n}\n\ninline Vec3D operator/(Vec3D v, double const a)\n{\n    return v /= a;\n}\n\ninline Vec3D operator*(double const a, Vec3D v)\n{\n    return v *= a;\n}\n\ninline Vec3D operator*(Vec3D const  (& A) [3], Vec3D v)\n{\n    return v *= A;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=../..\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# GENERAL SETTINGS\n###############################################################################\n# Default compiler, may be overridden by master makefile or command line.\nCOMP=gnu\n\n# Default build mode, may be overridden by master makefile or command line.\n# Possible modes are \"static\", \"shared\" and \"test\".\nMODE=static\n\n# Include global (project-wide) settings.\ninclude $(PROJECT_DIR)/src/makefile.$(COMP)\n\n\n###############################################################################\n# LIBRARY NAME\n###############################################################################\nNAME=nnp\nLIB=lib$(NAME)\n\n\n###############################################################################\n# PROJECT COMPILER AND FLAGS\n###############################################################################\nCC=$(PROJECT_CC)\nMPICC=$(PROJECT_MPICC)\nCFLAGS=$(PROJECT_CFLAGS)\nOPTIONS+=$(PROJECT_OPTIONS)\nDEBUG=$(PROJECT_DEBUG)\nifeq ($(MODE), test)\nDEBUG+= $(PROJECT_TEST)\nendif\nAR=$(PROJECT_AR)\nARFLAGS=$(PROJECT_ARFLAGS)\n\n# Extra include paths for compiling.\nINCLUDES=-I./ -I$(PROJECT_EIGEN)\n\n\n###############################################################################\n# DEFINE SOURCES AND HEADERS\n###############################################################################\nSRC=$(wildcard *.cpp)\nHEADERS=$(wildcard *.h)\nOBJ=$(SRC:.cpp=.o)\n\n\n###############################################################################\n# RULES\n###############################################################################\n.PHONY: all headers version clean rebuild\n\nifeq ($(MODE), shared)\nall: headers $(LIB).so\nelse\nall: headers $(LIB).a\nendif\n\nheaders: version\n\tcp $(HEADERS) $(PROJECT_INCLUDE)\n\nversion:\n\t@$(eval GIT_VERSION = $(shell git describe --tags --always))\n\t@sed -i.bak -E \"s?(N2P2_GIT_VERSION) .*?\\1 \\\"$(GIT_VERSION)\\\"?\" version.h\n\t@$(eval GIT_REV = $(shell git rev-parse HEAD))\n\t@sed -i.bak -E \"s?(N2P2_GIT_REV) .*?\\1 \\\"$(GIT_REV)\\\"?\" version.h\n\t@$(eval GIT_BRANCH = $(shell git rev-parse --abbrev-ref HEAD))\n\t@sed -i.bak -E \"s?(N2P2_GIT_BRANCH) .*?\\1 \\\"$(GIT_BRANCH)\\\"?\" version.h\n\t@rm version.h.bak\n\n$(LIB).so: CFLAGS+= -fPIC\n$(LIB).so: $(OBJ)\n\t$(CC) $(CFLAGS) $(DEBUG) $(OPTIONS) -o $@ $+ -shared\n\tcp $@ $(PROJECT_LIB)\n\n$(LIB).a: $(OBJ)\n\t$(AR) $(ARFLAGS) $@ $+\n\tcp $@ $(PROJECT_LIB)\n\n%.o: %.cpp\n\t$(CC) $(CFLAGS) $(DEBUG) $(INCLUDES) $(OPTIONS) -o $@ -c $<\n\nclean: clean-version clean-headers\n\t$(RM) $(OBJ)\n\t$(RM) *.gcno *.gcda $(LIB).so $(LIB).a\n\t$(RM) $(PROJECT_LIB)/$(LIB).so $(PROJECT_LIB)/$(LIB).a\n\nclean-version:\n\t@sed -i.bak -E \"s?(N2P2_GIT_VERSION) .*?\\1 \\\"\\\"?\" version.h\n\t@sed -i.bak -E \"s?(N2P2_GIT_REV) .*?\\1 \\\"\\\"?\" version.h\n\t@sed -i.bak -E \"s?(N2P2_GIT_BRANCH) .*?\\1 \\\"\\\"?\" version.h\n\t@rm version.h.bak\n\nclean-headers:\n\tcd $(PROJECT_INCLUDE) && $(RM) $(HEADERS)\n\nrebuild: clean all\n"
  },
  {
    "path": "src/libnnp/mpi-extra.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include <mpi.h>\n#include <cstdint>\n#include <climits>\n\n#if SIZE_MAX == UCHAR_MAX\n   #define MPI_SIZE_T MPI_UNSIGNED_CHAR\n#elif SIZE_MAX == USHRT_MAX\n   #define MPI_SIZE_T MPI_UNSIGNED_SHORT\n#elif SIZE_MAX == UINT_MAX\n   #define MPI_SIZE_T MPI_UNSIGNED\n#elif SIZE_MAX == ULONG_MAX\n   #define MPI_SIZE_T MPI_UNSIGNED_LONG\n#elif SIZE_MAX == ULLONG_MAX\n   #define MPI_SIZE_T MPI_UNSIGNED_LONG_LONG\n#else\n   #error \"No matching MPI data type for size_t.\"\n#endif\n"
  },
  {
    "path": "src/libnnp/utility.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"utility.h\"\n#include <algorithm> // std::max\n#include <cstdio>    // vsprintf\n#include <cstdarg>   // va_list, va_start, va_end\n#include <iomanip>   // std::setw\n#include <limits>    // std::numeric_limits\n#include <sstream>   // std::istringstream\n#include <stdexcept> // std::runtime_error\n\n#define STRPR_MAXBUF 1024\n\nusing namespace std;\n\nnamespace nnp\n{\n\nvector<string> split(string const& input, char delimiter)\n{\n    vector<string> parts;\n    stringstream ss;\n\n    ss.str(input);\n    string item;\n    while (getline(ss, item, delimiter)) {\n        parts.push_back(item);\n    }\n\n    return parts;\n}\n\nstring trim(string const& line, string const& whitespace)\n{\n    size_t const begin = line.find_first_not_of(whitespace);\n    if (begin == string::npos)\n    {\n        return \"\";\n    }\n    size_t const end = line.find_last_not_of(whitespace);\n    size_t const range = end - begin + 1;\n\n    return line.substr(begin, range);\n}\n\nstring reduce(string const& line,\n              string const& whitespace,\n              string const& fill)\n{\n    string result = trim(line, whitespace);\n\n    size_t begin = result.find_first_of(whitespace);\n    while (begin != string::npos)\n    {\n        size_t const end = result.find_first_not_of(whitespace, begin);\n        size_t const range = end - begin;\n        result.replace(begin, range, fill);\n        size_t const newBegin = begin + fill.length();\n        begin = result.find_first_of(whitespace, newBegin);\n    }\n\n    return result;\n}\n\nstring pad(string const& input, size_t num, char fill, bool right)\n{\n    string result = input;\n\n    if (input.size() >= num) return result;\n\n    string pad(num - input.size(), fill);\n    if (right) return result + pad;\n    else return pad + result;\n}\n\nstring strpr(const char* format, ...)\n{\n    char buffer[STRPR_MAXBUF];\n\n    va_list args;\n    va_start(args, format);\n    vsprintf(buffer, format, args);\n    va_end(args);\n\n    string s(buffer);\n\n    return s;\n}\n\nstring cap(string word)\n{\n    word[0] = toupper(word[0]);\n\n    return word;\n}\n\nvector<string> createFileHeader(vector<string> const& title,\n                                vector<size_t> const& colSize,\n                                vector<string> const& colName,\n                                vector<string> const& colInfo,\n                                char           const& commentChar)\n{\n    size_t const stdWidth = 80;\n    vector<string> h;\n    if (!(colSize.size() == colName.size() &&\n          colName.size() == colInfo.size()))\n    {\n        throw runtime_error(\"ERROR: Could not create file header, column sizes\"\n                            \" are not equal.\\n\");\n    }\n    size_t numCols = colSize.size();\n\n    // Separator line definition.\n    string sepLine(stdWidth, commentChar);\n    sepLine += '\\n';\n    // Start string.\n    string startStr(1, commentChar);\n\n    // Add title lines.\n    h.push_back(sepLine);\n    for (vector<string>::const_iterator it = title.begin();\n         it != title.end(); ++it)\n    {\n        h.push_back(startStr + ' ' + (*it) + '\\n');\n    }\n    h.push_back(sepLine);\n\n    // Determine maximum width of names.\n    size_t widthNames = 0;\n    for (vector<string>::const_iterator it = colName.begin();\n         it != colName.end(); ++it)\n    {\n        widthNames = max(widthNames, it->size());\n    }\n\n    // Column description section.\n    stringstream s;\n    s << startStr << ' '\n      << left << setw(4) << \"Col\" << ' '\n      << left << setw(widthNames) << \"Name\" << ' '\n      << left << \"Description\\n\";\n    h.push_back(s.str());\n    h.push_back(sepLine);\n    for (size_t i = 0; i < numCols; ++i)\n    {\n        s.clear();\n        s.str(string());\n        s << startStr << ' '\n          << left << setw(4) << i + 1 << ' '\n          << left << setw(widthNames) << colName.at(i) << ' '\n          << colInfo.at(i) << '\\n';\n        h.push_back(s.str());\n    }\n\n    // Determine total data width.\n    size_t widthData = 0;\n    for (vector<size_t>::const_iterator it = colSize.begin();\n         it != colSize.end(); ++it)\n    {\n        widthData += (*it) + 1;\n    }\n    widthData -= 1;\n\n    if (widthData > stdWidth)\n    {\n        // Long separator line.\n        h.push_back(string(widthData, commentChar) + \"\\n\");\n    }\n    else\n    {\n        h.push_back(sepLine);\n    }\n\n    // Write column number.\n    s.clear();\n    s.str(string());\n    s << startStr;\n    for (size_t i = 0; i < numCols; ++i)\n    {\n        size_t n = colSize.at(i);\n        if (i == 0) n -= 2;\n        s << ' ' << right << setw(n) << i + 1;\n    }\n    s << '\\n';\n    h.push_back(s.str());\n\n    // Write column name.\n    s.clear();\n    s.str(string());\n    s << startStr;\n    for (size_t i = 0; i < numCols; ++i)\n    {\n        size_t n = colSize.at(i);\n        if (i == 0) n -= 2;\n        string name = colName.at(i);\n        if (name.size() > n)\n        {\n            name.erase(n, string::npos);\n        }\n        s << ' ' << right << setw(n) << name;\n    }\n    s << '\\n';\n    h.push_back(s.str());\n\n    // Long separator line.\n    h.push_back(string(widthData, commentChar) + \"\\n\");\n\n    return h;\n}\n\nvoid appendLinesToFile(ofstream& file, vector<string> const lines)\n{\n    for (vector<string>::const_iterator it = lines.begin();\n         it != lines.end(); ++it)\n    {\n        file << (*it);\n    }\n\n    return;\n}\n\nvoid appendLinesToFile(FILE* const& file, vector<string> const lines)\n{\n    for (vector<string>::const_iterator it = lines.begin();\n         it != lines.end(); ++it)\n    {\n        fprintf(file, \"%s\", it->c_str());\n    }\n\n    return;\n}\n\nmap<size_t, vector<double>> readColumnsFromFile(string         fileName,\n                                                vector<size_t> columns,\n                                                char           comment)\n{\n    map<size_t, vector<double>> result;\n\n    sort(columns.begin(), columns.end());\n    for (auto col : columns)\n    {\n        result[col] = vector<double>();\n    }\n\n    ifstream file;\n    file.open(fileName.c_str());\n    if (!file.is_open())\n    {\n        throw runtime_error(\"ERROR: Could not open file: \\\"\" + fileName\n                            + \"\\\".\\n\");\n    }\n    string line;\n    while (getline(file, line))\n    {\n        if (line.size() == 0) continue;\n        if (line.at(0) != comment)\n        {\n            vector<string> splitLine = split(reduce(line));\n            for (auto col : columns)\n            {\n                if (col >= splitLine.size())\n                {\n                    result[col].push_back(\n                        std::numeric_limits<double>::quiet_NaN());\n                }\n                else\n                {\n                    result[col].push_back(atof(splitLine.at(col).c_str()));\n                }\n            }\n        }\n    }\n    file.close();\n\n    return result;\n}\n\ndouble pow_int(double x, int n)\n{\n    // Need an unsigned integer for bit-shift divison.\n    unsigned int m;\n\n    // If negative exponent, take the inverse of x and change sign of n.\n    if (n < 0)\n    {\n        x = 1.0 / x;\n        m = -n;\n    }\n    else m = n;\n\n    // Exponentiation by squaring, \"fast exponentiation algorithm\"\n    double result = 1.0;\n    do\n    {\n        if (m & 1) result *= x;\n        // Division by 2.\n        m >>= 1;\n        x *= x;\n    }\n    while (m);\n\n    return result;\n}\n\n}\n"
  },
  {
    "path": "src/libnnp/utility.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef UTILITY_H\n#define UTILITY_H\n\n#include <cstdio>           // FILE\n#include <fstream>          // std::ofstream\n#include <map>              // std::map\n#include <sstream>          // std::stringstream\n#include <stdexcept>        // std::range_error\n#include <string>           // std::string\n#include <vector>           // std::vector\n#include <unordered_map>    // std::unordered_map\n#include <algorithm>        // std::find\n\nnamespace nnp\n{\n\n/** Split string at each delimiter.\n *\n * @param[in] input Input string.\n * @param[in] delimiter Delimiter character (default ' ').\n * @return Vector containing the string parts.\n */\nstd::vector<std::string> split(std::string const& input,\n                               char               delimiter = ' ');\n/** Remove leading and trailing whitespaces from string.\n *\n * @param[in] line Input string.\n * @param[in] whitespace All characters identified as whitespace (default:\n *                       \" \\t\").\n * @return String without leading and trailing whitespaces.\n */\nstd::string              trim(std::string const& line,\n                              std::string const& whitespace = \" \\t\");\n/** Replace multiple whitespaces with fill.\n *\n * @param[in] line Input string.\n * @param[in] whitespace All characters identified as whitespace (default:\n *                       \" \\t\").\n * @param[in] fill Replacement character (default: \" \").\n * @return String with fill replacements.\n *\n * Calls #trim() at the beginning.\n */\nstd::string              reduce(std::string const& line,\n                                std::string const& whitespace = \" \\t\",\n                                std::string const& fill = \" \");\n/** Pad string to given length with fill character.\n *\n * @param[in] input Input string.\n * @param[in] num Desired width of padded string.\n * @param[in] fill Padding character.\n * @param[in] right If true, pad right. Pad left otherwise.\n *\n * @return String padded to desired length or original string if length of old\n *         string is not shorter than desired length.\n */\nstd::string              pad(std::string const& input,\n                             std::size_t        num,\n                             char               fill = ' ',\n                             bool               right = true);\n/** String version of printf function.\n */\nstd::string              strpr(const char* format, ...);\n/** Capitalize first letter of word.\n *\n * @param[in] word String to capitalize.\n *\n * @return Input string with first letter in capital letters.\n */\nstd::string              cap(std::string word);\n/** Generate output file header with info section and column labels.\n *\n * @param[in] title Multiple lines of title text.\n * @param[in] colLength Length of the individual columns.\n * @param[in] colName Names of the individual columns.\n * @param[in] colInfo Description of the individual columns.\n * @param[in] commentChar Character used for starting each line and to create\n *                        separator lines.\n *\n * @return Vector of strings, one entry per line.\n */\nstd::vector<std::string> createFileHeader(\n                            std::vector<std::string> const& title,\n                            std::vector<std::size_t> const& colLength,\n                            std::vector<std::string> const& colName,\n                            std::vector<std::string> const& colInfo,\n                            char const&                     commentChar = '#');\n/** Append multiple lines of strings to open file stream.\n *\n * @param[in,out] file File stream to append lines to.\n * @param[in] lines Vector of strings with line content.\n *\n */\nvoid                     appendLinesToFile(\n                                         std::ofstream&                 file,\n                                         std::vector<std::string> const lines);\n/** Append multiple lines of strings to open file pointer.\n *\n * @param[in,out] file File pointer.\n * @param[in] lines Vector of strings with line content.\n *\n */\nvoid                     appendLinesToFile(\n                                         FILE* const&                   file,\n                                         std::vector<std::string> const lines);\n/** Read multiple columns of data from file.\n *\n * @param[in] fileName Name of data file.\n * @param[in] columns Vector with column indices of interest (starting with 0).\n * @param[in] comment Lines starting with comment sign are ignored.\n *\n * @return Map from column index to vector of data.\n  */\nstd::map<std::size_t,\n         std::vector<double>>\n                         readColumnsFromFile(\n                                       std::string fileName,\n                                       std::vector<std::size_t> columns,\n                                       char                     comment = '#');\n/** Safely access map entry.\n *\n * @param[in] stdMap Map to search in.\n * @param[in] key Key requested.\n *\n * The .at() member function of maps is available only for C++11.\n */\ntemplate<typename K, typename V>\nV const&                 safeFind(std::map<K, V> const&           stdMap,\n                                  typename\n                                  std::map<K, V>::key_type const& key)\n{\n    if (stdMap.find(key) == stdMap.end())\n    {\n        std::stringstream message;\n        message << \"ERROR: No map entry found for key \\\"\";\n        message << key;\n        message << \"\\\".\\n\";\n        throw std::range_error(message.str());\n    }\n    return stdMap.find(key)->second;\n}\n\n/** Test if vector contains specified value.\n *\n * @param[in] stdVec Vector to search in.\n * @param[in] value Value to search for.\n * @return `True` if value is located in vector.\n */\ntemplate<typename T>\nbool                    vectorContains(std::vector<T> const& stdVec,\n                                       T value)\n{\n    return (std::find(stdVec.begin(), stdVec.end(), value) != stdVec.end());\n}\n/** Test if unordered map contains specified key.\n *\n * @param[in] stdMap Map to search in.\n * @param[in] key Key to search for.\n * @return `True` if key is located in map.\n */\n\ntemplate<typename T, typename U>\nbool                    unorderedMapContainsKey(\n                                    std::unordered_map<T, U> const& stdMap,\n                                    T key)\n{\n    return ( stdMap.find(key) != stdMap.end() );\n}\n\n/** Compare pointer targets\n *\n * @param[in] lhs Pointer to left side of comparison.\n * @param[in] rhs Pointer to right side of comparison.\n * @return `True` if dereferenced `lhs` < dereferenced `rhs`, `False`\n *         otherwise.\n */\ntemplate<typename T>\nbool                     comparePointerTargets(T* lhs, T* rhs)\n{\n    return ((*lhs) < (*rhs));\n}\n\n/** Integer version of power function, \"fast exponentiation algorithm\".\n *\n * @param[in] x Base number.\n * @param[in] n Integer exponent.\n *\n * @return x^n\n */\ndouble                   pow_int(double x, int n);\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnp/version.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef VERSION_H\n#define VERSION_H\n\n#define N2P2_VERSION \"v2.3.0\"\n#define N2P2_GIT_VERSION \"\"\n#define N2P2_GIT_REV \"\"\n#define N2P2_GIT_BRANCH \"\"\n\n#endif\n"
  },
  {
    "path": "src/libnnpif/CabanaMD/ElementCabana.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Saaketh Desai and Sam Reeve\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef ELEMENT_CABANA_H\n#define ELEMENT_CABANA_H\n\n#include \"typesCabana.h\"\n\n#include \"CutoffFunction.h\"\n#include \"Element.h\"\n#include \"utility.h\"\n\n#include <cstddef> // size_t\n#include <string>  // string\n#include <vector>  // vector\n\nnamespace nnp\n{\n\n/// Derived Cabana class for element-specific data.\nclass ElementCabana : public Element\n{\n  public:\n    /** Constructor using index.\n     */\n    ElementCabana( std::size_t const index );\n    /** Destructor.\n     */\n    ~ElementCabana();\n\n    /** Add one symmetry function.\n     *\n     * @param[in] parameters String containing settings for symmetry function.\n     * @param[in] lineNumber Line number of symmetry function in settings file.\n     * @param[in] attype Atom type.\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] convLength Length unit conversion factor.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     */\n    template <class t_SF, class h_t_int>\n    void addSymmetryFunction( std::string const &parameters,\n                              std::vector<std::string> elementStrings,\n                              int attype, t_SF SF, double convLength,\n                              h_t_int h_numSFperElem );\n    /** Change length unit for all symmetry functions.\n     *\n     * @param[in] convLength Length unit conversion factor.\n     */\n    void changeLengthUnitSymmetryFunctions( double convLength );\n    /** Sort all symmetry function.\n     *\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     * @param[in] attype Atom type.\n     */\n    template <class t_SF, class h_t_int>\n    void sortSymmetryFunctions( t_SF SF, h_t_int h_numSFperElem, int attype );\n    /** Print symmetry function parameter value information.\n     *\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] attype Atom type.\n     * @param[in] index1 First symmetry function index.\n     * @param[in] index2 Second symmetry function index.\n     */\n    template <class t_SF>\n    bool compareSF( t_SF SF, int attype, int index1, int index2 );\n    /** Print symmetry function parameter value information.\n     *\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] attype Atom type.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     */\n    template <class t_SF, class h_t_int>\n    std::vector<std::string>\n    infoSymmetryFunctionParameters( t_SF SF, int attype,\n                                    h_t_int h_numSFperElem ) const;\n    /** Print symmetry function scaling information.\n     *\n     * @param[in] scalingType Type of scaling see\n     *                        SymmetryFunction::ScalingType.\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] SFscaling Kokkos host View of symmetry function scaling.\n     * @param[in] attype Atom type.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     */\n    template <class t_SF, class t_SFscaling, class h_t_int>\n    std::vector<std::string>\n    infoSymmetryFunctionScaling( ScalingType scalingType,\n                                 t_SF SF, t_SFscaling SFscaling,\n                                 int attype,\n                                 h_t_int h_numSFperElem ) const;\n    /** Set up symmetry function groups.\n     *\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] SFGmemberlist Kokkos host View of symmetry function groups.\n     * @param[in] attype Atom type.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     * @param[in] h_numSFGperElem Kokkos host View of number of symmetry\n     *                            function groups per element.\n     * @param[in] maxSFperElem Maximum number of symmetry functions per element.\n     */\n    template <class t_SF, class t_SFGmemberlist, class h_t_int>\n    void setupSymmetryFunctionGroups( t_SF SF, t_SFGmemberlist SFGmemberlist,\n                                      int attype, h_t_int h_numSFperElem,\n                                      h_t_int h_numSFGperElem,\n                                      int maxSFperElem );\n    /** Print symmetry function group info.\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] SFGmemberlist Kokkos host View of symmetry function groups.\n     * @param[in] attype Atom type.\n     * @param[in] h_numSFGperElem Kokkos host View of number of symmetry\n     *                            function groups per element.\n     */\n    template <class t_SF, class t_SFGmemberlist, class h_t_int>\n    std::vector<std::string>\n    infoSymmetryFunctionGroups( t_SF SF, t_SFGmemberlist SFGmemberlist,\n                                int attype, h_t_int h_numSFGperElem ) const;\n    /** Set cutoff function for all symmetry functions.\n     *\n     * @param[in] cutoffType Type of cutoff function.\n     * @param[in] cutoffAlpha Cutoff parameter for all functions.\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] attype Atom type.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     */\n    template <class t_SF, class h_t_int>\n    void setCutoffFunction( CutoffFunction::CutoffType const cutoffType,\n                            double const cutoffAlpha, t_SF SF, int attype,\n                            h_t_int h_numSFperElem );\n    /** Set scaling of all symmetry functions.\n     *\n     * @param[in] scalingType Type of scaling, see\n     *                        SymmetryFunction::ScalingType.\n     * @param[in] statisticsLine Vector of strings containing statistics for\n     *                           all symmetry functions.\n     * @param[in] minS Minimum for scaling range.\n     * @param[in] maxS Maximum for scaling range.\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] SFscaling Kokkos host View of symmetry function scaling.\n     * @param[in] attype Atom type.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     */\n    template <class t_SF, class t_SFscaling, class h_t_int>\n    void setScaling( ScalingType scalingType,\n                     std::vector<std::string> const &statisticsLine,\n                     double minS, double maxS, t_SF SF,\n                     t_SFscaling SFscaling, int attype,\n                     h_t_int h_numSFperElem ) const;\n    /** Get number of symmetry functions.\n     *\n     * @param[in] attype Atom type.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     *\n     * @return Number of symmetry functions.\n     */\n    template <class h_t_int>\n    std::size_t numSymmetryFunctions( int attype, h_t_int h_numSFperElem ) const;\n    /** Get maximum of required minimum number of neighbors for all symmetry\n     * functions for this element.\n     *\n     * @param[in] attype Atom type.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     * @param[in] nSF Number of symmetry function for this type.\n     *\n     * @return Minimum number of neighbors required.\n     */\n    template <class t_SF>\n    std::size_t getMinNeighbors( int attype, t_SF SF, int nSF ) const;\n    /** Get minimum cutoff radius of all symmetry functions.\n     *\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] attype Atom type.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     *\n     * @return Minimum cutoff radius.\n     */\n    template <class t_SF, class h_t_int>\n    double getMinCutoffRadius( t_SF SF, int attype,\n                               h_t_int h_numSFperElem ) const;\n    /** Get maximum cutoff radius of all symmetry functions.\n     *\n     * @param[in] SF Kokkos host View of symmetry functions.\n     * @param[in] attype Atom type.\n     * @param[in] h_numSFperElem Kokkos host View of number of symmetry\n     *                           functions per element.\n     *\n     * @return Maximum cutoff radius.\n     */\n    template <class t_SF, class h_t_int>\n    double getMaxCutoffRadius( t_SF SF, int attype,\n                               h_t_int h_numSFperElem ) const;\n\n    /* Update symmetry function statistics.\n     *\n     */\n    // void                     updateSymmetryFunctionStatistics(\n\n    /// Symmetry function statistics.\n    // SymmetryFunctionStatistics statistics;\n\n    /** Set scaling type of one symmetry function\n     *\n     * @param[in] scalingType Type of scaling, see\n     *                        SymmetryFunction::ScalingType.\n     * @param[in] statisticsLine Output string for this symmetry function.\n     * @param[in] Smin Minimum for scaling range.\n     * @param[in] Smax Maximum for scaling range.\n     * @param[in] SFscaling Kokkos host View of symmetry function scaling.\n     * @param[in] attype Atom type.\n     * @param[in] k Symmetry function index.\n     */\n    template <class t_SFscaling>\n    inline void setScalingType( ScalingType scalingType,\n                                std::string statisticsLine,\n                                double Smin, double Smax,\n                                t_SFscaling SFscaling,\n                                int attype, int k ) const;\n    /** Print scaling for one symmetry function.\n     *\n     * @param[in] scalingType Type of scaling, see\n     *                        SymmetryFunction::ScalingType.\n     * @param[in] SFscaling Kokkos host View of symmetry function scaling.\n     * @param[in] attype Atom type.\n     * @param[in] k Symmetry function index.\n     */\n    template <class t_SFscaling>\n    inline std::string scalingLine( ScalingType scalingType,\n                                    t_SFscaling SFscaling,\n                                    int attype, int k ) const;\n    /** Unscale one symmetry function.\n     *\n     * @param[in] attype Atom type.\n     * @param[in] value Unscaled symmetry function value.\n     * @param[in] k Symmetry function index.\n     * @param[in] SFscaling Kokkos host View of symmetry function scaling.\n     */\n    template <class t_SFscaling>\n    inline double unscale( int attype, double value, int k,\n                           t_SFscaling SFscaling );\n\n  private:\n    using Element::index;\n    using Element::atomicNumber;\n    using Element::atomicEnergyOffset;\n    using Element::symbol;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ntemplate <class h_t_int>\ninline std::size_t\nElementCabana::numSymmetryFunctions( int attype,\n                                     h_t_int h_numSFperElem ) const\n{\n    return h_numSFperElem( attype );\n}\n\ntemplate <class t_SFscaling>\ninline void\nElementCabana::setScalingType( ScalingType scalingType,\n                               std::string statisticsLine, double Smin,\n                               double Smax, t_SFscaling SFscaling,\n                               int attype, int k ) const\n{\n    double Gmin, Gmax, Gmean, Gsigma = 0, scalingFactor = 0;\n    std::vector<std::string> s = split( reduce( statisticsLine ) );\n\n    Gmin = atof( s.at( 2 ).c_str() );\n    Gmax = atof( s.at( 3 ).c_str() );\n    Gmean = atof( s.at( 4 ).c_str() );\n    SFscaling( attype, k, 0 ) = Gmin;\n    SFscaling( attype, k, 1 ) = Gmax;\n    SFscaling( attype, k, 2 ) = Gmean;\n\n    // Older versions may not supply sigma.\n    if ( s.size() > 5 )\n        Gsigma = atof( s.at( 5 ).c_str() );\n    SFscaling( attype, k, 3 ) = Gsigma;\n\n    SFscaling( attype, k, 4 ) = Smin;\n    SFscaling( attype, k, 5 ) = Smax;\n    SFscaling( attype, k, 7 ) = scalingType;\n\n    if ( scalingType == ST_NONE )\n        scalingFactor = 1.0;\n    else if ( scalingType == ST_SCALE )\n        scalingFactor = ( Smax - Smin ) / ( Gmax - Gmin );\n    else if ( scalingType == ST_CENTER )\n        scalingFactor = 1.0;\n    else if ( scalingType == ST_SCALECENTER )\n        scalingFactor = ( Smax - Smin ) / ( Gmax - Gmin );\n    else if ( scalingType == ST_SCALESIGMA )\n        scalingFactor = ( Smax - Smin ) / Gsigma;\n    SFscaling( attype, k, 6 ) = scalingFactor;\n\n    return;\n}\n\ntemplate <class t_SFscaling>\ninline std::string\nElementCabana::scalingLine( ScalingType scalingType,\n                            t_SFscaling SFscaling, int attype,\n                            int k ) const\n{\n    return strpr( \"%4zu %9.2E %9.2E %9.2E %9.2E %9.2E %5.2f %5.2f %d\\n\",\n                  k + 1, SFscaling( attype, k, 0 ),\n                  SFscaling( attype, k, 1 ), SFscaling( attype, k, 2 ),\n                  SFscaling( attype, k, 3 ), SFscaling( attype, k, 6 ),\n                  SFscaling( attype, k, 4 ), SFscaling( attype, k, 5 ),\n                  scalingType );\n}\n\ntemplate <class t_SFscaling>\ninline double ElementCabana::unscale( int attype, double value, int k,\n                                      t_SFscaling SFscaling )\n{\n    double scalingType = SFscaling( attype, k, 7 );\n    double scalingFactor = SFscaling( attype, k, 6 );\n    double Gmin = SFscaling( attype, k, 0 );\n    // double Gmax = SFscaling(attype,k,1);\n    double Gmean = SFscaling( attype, k, 2 );\n    // double Gsigma = SFscaling(attype,k,3);\n    double Smin = SFscaling( attype, k, 4 );\n    // double Smax = SFscaling(attype,k,5);\n\n    if ( scalingType == 0.0 )\n    {\n        return value;\n    }\n    else if ( scalingType == 1.0 )\n    {\n        return ( value - Smin ) / scalingFactor + Gmin;\n    }\n    else if ( scalingType == 2.0 )\n    {\n        return value + Gmean;\n    }\n    else if ( scalingType == 3.0 )\n    {\n        return ( value - Smin ) / scalingFactor + Gmean;\n    }\n    else if ( scalingType == 4.0 )\n    {\n        return ( value - Smin ) / scalingFactor + Gmean;\n    }\n    else\n    {\n        return 0.0;\n    }\n}\n\n}\n\n#include \"ElementCabana_impl.h\"\n\n#endif\n"
  },
  {
    "path": "src/libnnpif/CabanaMD/ElementCabana_impl.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Saaketh Desai and Sam Reeve\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"utility.h\"\n\n#include <algorithm> // std::sort, std::min, std::max\n#include <cstdlib>   // atoi\n#include <iostream>  // std::cerr\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n\nusing namespace std;\n\nnamespace nnp\n{\n\nElementCabana::ElementCabana( size_t const _index )\n    : Element()\n{\n    index = _index;\n    atomicEnergyOffset = 0.0;\n    neuralNetwork = NULL;\n}\n\nElementCabana::~ElementCabana() {}\n\ntemplate <class t_SF, class h_t_int>\nvoid ElementCabana::addSymmetryFunction( string const &parameters,\n                                         vector<string> elementStrings, int attype,\n                                         t_SF SF, double convLength,\n                                         h_t_int h_numSFperElem )\n{\n    vector<string> args = split( reduce( parameters ) );\n    size_t type = (size_t)atoi( args.at( 1 ).c_str() );\n    const char *estring;\n    int el = 0;\n\n    vector<string> splitLine = split( reduce( parameters ) );\n    if ( type == 2 )\n    {\n        estring = splitLine.at( 0 ).c_str();\n        for ( size_t i = 0; i < elementStrings.size(); ++i )\n        {\n            if ( strcmp( elementStrings[i].c_str(), estring ) == 0 )\n                el = i;\n        }\n        SF( attype, h_numSFperElem( attype ), 0 ) = el;   // ec\n        SF( attype, h_numSFperElem( attype ), 1 ) = type; // type\n\n        estring = splitLine.at( 2 ).c_str();\n        for ( size_t i = 0; i < elementStrings.size(); ++i )\n        {\n            if ( strcmp( elementStrings[i].c_str(), estring ) == 0 )\n                el = i;\n        }\n        SF( attype, h_numSFperElem( attype ), 2 ) = el; // e1\n        // set e2 to arbit high number for ease in creating groups\n        SF( attype, h_numSFperElem( attype ), 3 ) = 100000; // e2\n\n        SF( attype, h_numSFperElem( attype ), 4 ) =\n            atof( splitLine.at( 3 ).c_str() ) /\n            ( convLength * convLength ); // eta\n        SF( attype, h_numSFperElem( attype ), 8 ) =\n            atof( splitLine.at( 4 ).c_str() ) * convLength; // rs\n        SF( attype, h_numSFperElem( attype ), 7 ) =\n            atof( splitLine.at( 5 ).c_str() ) * convLength; // rc\n\n        SF( attype, h_numSFperElem( attype ), 13 ) = h_numSFperElem( attype );\n        h_numSFperElem( attype )++;\n    }\n\n    else if ( type == 3 )\n    {\n        if ( type != (size_t)atoi( splitLine.at( 1 ).c_str() ) )\n            throw runtime_error( \"ERROR: Incorrect symmetry function type.\\n\" );\n        estring = splitLine.at( 0 ).c_str();\n        for ( size_t i = 0; i < elementStrings.size(); ++i )\n        {\n            if ( strcmp( elementStrings[i].c_str(), estring ) == 0 )\n                el = i;\n        }\n        SF( attype, h_numSFperElem( attype ), 0 ) = el;   // ec\n        SF( attype, h_numSFperElem( attype ), 1 ) = type; // type\n\n        estring = splitLine.at( 2 ).c_str();\n        for ( size_t i = 0; i < elementStrings.size(); ++i )\n        {\n            if ( strcmp( elementStrings[i].c_str(), estring ) == 0 )\n                el = i;\n        }\n        SF( attype, h_numSFperElem( attype ), 2 ) = el; // e1\n\n        estring = splitLine.at( 3 ).c_str();\n        for ( size_t i = 0; i < elementStrings.size(); ++i )\n        {\n            if ( strcmp( elementStrings[i].c_str(), estring ) == 0 )\n                el = i;\n        }\n\n        SF( attype, h_numSFperElem( attype ), 3 ) = el; // e2\n        SF( attype, h_numSFperElem( attype ), 4 ) =\n            atof( splitLine.at( 4 ).c_str() ) /\n            ( convLength * convLength ); // eta\n        SF( attype, h_numSFperElem( attype ), 5 ) =\n            atof( splitLine.at( 5 ).c_str() ); // lambda\n        SF( attype, h_numSFperElem( attype ), 6 ) =\n            atof( splitLine.at( 6 ).c_str() ); // zeta\n        SF( attype, h_numSFperElem( attype ), 7 ) =\n            atof( splitLine.at( 7 ).c_str() ) * convLength; // rc\n        // Shift parameter is optional.\n        if ( splitLine.size() > 8 )\n            SF( attype, h_numSFperElem( attype ), 8 ) =\n                atof( splitLine.at( 8 ).c_str() ) * convLength; // rs\n\n        T_INT e1 = SF( attype, h_numSFperElem( attype ), 2 );\n        T_INT e2 = SF( attype, h_numSFperElem( attype ), 3 );\n        if ( e1 > e2 )\n        {\n            size_t tmp = e1;\n            e1 = e2;\n            e2 = tmp;\n        }\n        SF( attype, h_numSFperElem( attype ), 2 ) = e1;\n        SF( attype, h_numSFperElem( attype ), 3 ) = e2;\n\n        T_FLOAT zeta = SF( attype, h_numSFperElem( attype ), 6 );\n        T_INT zetaInt = round( zeta );\n        if ( fabs( zeta - zetaInt ) <= numeric_limits<double>::min() )\n            SF( attype, h_numSFperElem( attype ), 9 ) = 1;\n        else\n            SF( attype, h_numSFperElem( attype ), 9 ) = 0;\n\n        SF( attype, h_numSFperElem( attype ), 13 ) = h_numSFperElem( attype );\n        h_numSFperElem( attype )++;\n    }\n    // TODO: Add this later\n    else if ( type == 9 )\n    {\n    }\n    else if ( type == 12 )\n    {\n    }\n    else if ( type == 13 )\n    {\n    }\n    else\n    {\n        throw runtime_error( \"ERROR: Unknown symmetry function type.\\n\" );\n    }\n\n    return;\n}\n\ntemplate <class t_SF, class h_t_int>\nvoid ElementCabana::sortSymmetryFunctions( t_SF SF, h_t_int h_numSFperElem,\n                                           int attype )\n{\n    int size = h_numSFperElem( attype );\n    h_t_int h_SFsort( \"SortSort\", size );\n    for ( int i = 0; i < size; ++i )\n        h_SFsort( i ) = i;\n\n    // naive insertion sort\n    int i, j, tmp;\n    for ( i = 1; i < size; ++i )\n    {\n        j = i;\n        // explicit condition for sort\n        while ( j > 0 &&\n                compareSF( SF, attype, h_SFsort( j - 1 ), h_SFsort( j ) ) )\n        {\n            tmp = h_SFsort( j );\n            h_SFsort( j ) = h_SFsort( j - 1 );\n            h_SFsort( j - 1 ) = tmp;\n            --j;\n        }\n    }\n\n    int tmpindex;\n    for ( int i = 0; i < size; ++i )\n    {\n        SF( attype, i, 13 ) = h_SFsort( i );\n        tmpindex = SF( attype, i, 13 );\n        SF( attype, tmpindex, 14 ) = i;\n    }\n\n    return;\n}\n\ntemplate <class t_SF>\nbool ElementCabana::compareSF( t_SF SF, int attype, int index1, int index2 )\n{\n    if ( SF( attype, index2, 0 ) < SF( attype, index1, 0 ) )\n        return true; // ec\n    else if ( SF( attype, index2, 0 ) > SF( attype, index1, 0 ) )\n        return false;\n\n    if ( SF( attype, index2, 1 ) < SF( attype, index1, 1 ) )\n        return true; // type\n    else if ( SF( attype, index2, 1 ) > SF( attype, index1, 1 ) )\n        return false;\n\n    if ( SF( attype, index2, 11 ) < SF( attype, index1, 11 ) )\n        return true; // cutofftype\n    else if ( SF( attype, index2, 11 ) > SF( attype, index1, 11 ) )\n        return false;\n\n    if ( SF( attype, index2, 12 ) < SF( attype, index1, 12 ) )\n        return true; // cutoffalpha\n    else if ( SF( attype, index2, 12 ) > SF( attype, index1, 12 ) )\n        return false;\n\n    if ( SF( attype, index2, 7 ) < SF( attype, index1, 7 ) )\n        return true; // rc\n    else if ( SF( attype, index2, 7 ) > SF( attype, index1, 7 ) )\n        return false;\n\n    if ( SF( attype, index2, 4 ) < SF( attype, index1, 4 ) )\n        return true; // eta\n    else if ( SF( attype, index2, 4 ) > SF( attype, index1, 4 ) )\n        return false;\n\n    if ( SF( attype, index2, 8 ) < SF( attype, index1, 8 ) )\n        return true; // rs\n    else if ( SF( attype, index2, 8 ) > SF( attype, index1, 8 ) )\n        return false;\n\n    if ( SF( attype, index2, 6 ) < SF( attype, index1, 6 ) )\n        return true; // zeta\n    else if ( SF( attype, index2, 6 ) > SF( attype, index1, 6 ) )\n        return false;\n\n    if ( SF( attype, index2, 5 ) < SF( attype, index1, 5 ) )\n        return true; // lambda\n    else if ( SF( attype, index2, 5 ) > SF( attype, index1, 5 ) )\n        return false;\n\n    if ( SF( attype, index2, 2 ) < SF( attype, index1, 2 ) )\n        return true; // e1\n    else if ( SF( attype, index2, 2 ) > SF( attype, index1, 2 ) )\n        return false;\n\n    if ( SF( attype, index2, 3 ) < SF( attype, index1, 3 ) )\n        return true; // e2\n    else if ( SF( attype, index2, 3 ) > SF( attype, index1, 3 ) )\n        return false;\n\n    else\n        return false;\n}\n\ntemplate <class t_SF, class h_t_int>\nvector<string>\nElementCabana::infoSymmetryFunctionParameters( t_SF SF, int attype,\n                                               h_t_int h_numSFperElem ) const\n{\n    vector<string> v;\n    string pushstring = \"\";\n    int index;\n    float writestring;\n    for ( int i = 0; i < h_numSFperElem( attype ); ++i )\n    {\n        index = SF( attype, i, 13 );\n        // TODO: improve function\n        for ( int j = 1; j < 12; ++j )\n        {\n            writestring = SF( attype, index, j );\n            pushstring += to_string( writestring ) + \" \";\n        }\n        pushstring += \"\\n\";\n    }\n    v.push_back( pushstring );\n\n    return v;\n}\n\ntemplate <class t_SF, class t_SFscaling, class h_t_int>\nvector<string>\nElementCabana::infoSymmetryFunctionScaling( ScalingType scalingType, t_SF SF,\n                                      t_SFscaling SFscaling, int attype,\n                                      h_t_int h_numSFperElem ) const\n{\n    vector<string> v;\n    int index;\n    for ( int k = 0; k < h_numSFperElem( attype ); ++k )\n    {\n        index = SF( attype, k, 13 );\n        v.push_back( scalingLine( scalingType, SFscaling, attype, index ) );\n    }\n    return v;\n}\n\ntemplate <class t_SF, class t_SFGmemberlist, class h_t_int>\nvoid ElementCabana::setupSymmetryFunctionGroups( t_SF SF,\n                                                 t_SFGmemberlist SFGmemberlist,\n                                                 int attype, h_t_int h_numSFperElem,\n                                                 h_t_int h_numSFGperElem,\n                                                 int maxSFperElem )\n{\n    int num_group = h_numSFperElem.extent( 0 );\n    h_t_int h_numGR( \"RadialCounter\", num_group );\n    h_t_int h_numGA( \"AngularCounter\", num_group );\n    int SFindex;\n    for ( int k = 0; k < h_numSFperElem( attype ); ++k )\n    {\n        bool createNewGroup = true;\n        SFindex = SF( attype, k, 13 );\n        for ( int l = 0; l < h_numSFGperElem( attype ); ++l )\n        {\n            if ( ( SF( attype, SFindex, 0 ) ==\n                   SF( attype, SFGmemberlist( attype, l, 0 ),\n                       0 ) ) && // same ec\n                 ( SF( attype, SFindex, 2 ) ==\n                   SF( attype, SFGmemberlist( attype, l, 0 ),\n                       2 ) ) && // same e1\n                 ( SF( attype, SFindex, 3 ) ==\n                   SF( attype, SFGmemberlist( attype, l, 0 ),\n                       3 ) ) && // same e2\n                 ( SF( attype, SFindex, 7 ) ==\n                   SF( attype, SFGmemberlist( attype, l, 0 ),\n                       7 ) ) && // same rc\n                 ( SF( attype, SFindex, 11 ) ==\n                   SF( attype, SFGmemberlist( attype, l, 0 ),\n                       11 ) ) && // same cutoffType\n                 ( SF( attype, SFindex, 12 ) ==\n                   SF( attype, SFGmemberlist( attype, l, 0 ),\n                       12 ) ) ) // same cutoffAlpha\n            {\n                createNewGroup = false;\n                if ( SF( attype, SFindex, 1 ) == 2 )\n                {\n                    SFGmemberlist( attype, l, h_numGR( l ) ) = SFindex;\n                    h_numGR( l )++;\n                    SFGmemberlist( attype, l, maxSFperElem )++;\n                    break;\n                }\n\n                else if ( SF( attype, SFindex, 1 ) == 3 )\n                {\n                    SFGmemberlist( attype, l, h_numGA( l ) ) = SFindex;\n                    h_numGA( l )++;\n                    SFGmemberlist( attype, l, maxSFperElem )++;\n                    break;\n                }\n            }\n        }\n\n        if ( createNewGroup )\n        {\n            int l = h_numSFGperElem( attype );\n            h_numSFGperElem( attype )++;\n            if ( SF( attype, SFindex, 1 ) == 2 )\n            {\n                SFGmemberlist( attype, l, 0 ) = SFindex;\n                if ( l >= (int)h_numGR.extent( 0 ) )\n                    Kokkos::resize( h_numGR, l+1 );\n                h_numGR( l ) = 1;\n                SFGmemberlist( attype, l, maxSFperElem )++;\n            }\n            else if ( SF( attype, SFindex, 1 ) == 3 )\n            {\n                SFGmemberlist( attype, l, 0 ) = SFindex;\n                if ( l >= (int)h_numGA.extent( 0 ) )\n                    Kokkos::resize( h_numGA, l+1 );\n                h_numGA( l ) = 1;\n                SFGmemberlist( attype, l, maxSFperElem )++;\n            }\n        }\n    }\n\n    return;\n}\n\ntemplate <class t_SF, class t_SFGmemberlist, class h_t_int>\nvector<string>\nElementCabana::infoSymmetryFunctionGroups( t_SF SF, t_SFGmemberlist SFGmemberlist,\n                                           int attype, h_t_int h_numSFGperElem ) const\n{\n    vector<string> v;\n    string pushstring = \"\";\n    for ( int groupIndex = 0; groupIndex < h_numSFGperElem( attype );\n          ++groupIndex )\n    {\n        // TODO: improve function\n        for ( int j = 0; j < 8; ++j )\n            pushstring +=\n                to_string(\n                    SF( attype, SFGmemberlist( attype, groupIndex, 0 ), j ) ) +\n                \" \";\n        pushstring += \"\\n\";\n    }\n    v.push_back( pushstring );\n\n    return v;\n}\n\ntemplate <class t_SF, class h_t_int>\nvoid ElementCabana::setCutoffFunction( CutoffFunction::CutoffType const cutoffType,\n                                       double const cutoffAlpha, t_SF SF, int attype,\n                                       h_t_int h_numSFperElem )\n{\n    for ( int k = 0; k < h_numSFperElem( attype ); ++k )\n    {\n        SF( attype, k, 10 ) = cutoffType;\n        SF( attype, k, 11 ) = cutoffAlpha;\n    }\n    return;\n}\n\ntemplate <class t_SF, class t_SFscaling, class h_t_int>\nvoid ElementCabana::setScaling( ScalingType scalingType,\n                                vector<string> const &statisticsLine, double Smin,\n                                double Smax, t_SF SF, t_SFscaling SFscaling,\n                                int attype, h_t_int h_numSFperElem ) const\n{\n    int index;\n    for ( int k = 0; k < h_numSFperElem( attype ); ++k )\n    {\n        index = SF( attype, k, 13 );\n        setScalingType( scalingType, statisticsLine.at( k ), Smin, Smax,\n                        SFscaling, attype, index );\n    }\n    // TODO: groups\n    // for (int k = 0; k < h_numSFperElem(attype); ++k)\n    //    setScalingFactors(SF,attype,k);\n\n    return;\n}\n\ntemplate <class t_SF>\nsize_t ElementCabana::getMinNeighbors( int attype, t_SF SF, int nSF ) const\n{\n    // get max number of minNeighbors\n    size_t global_minNeighbors = 0;\n    size_t minNeighbors = 0;\n    int SFtype;\n    for ( int k = 0; k < nSF; ++k )\n    {\n        SFtype = SF( attype, k, 1 );\n        if ( SFtype == 2 )\n            minNeighbors = 1;\n        else if ( SFtype == 3 )\n            minNeighbors = 2;\n        global_minNeighbors = max( minNeighbors, global_minNeighbors );\n    }\n\n    return global_minNeighbors;\n}\n\ntemplate <class t_SF, class h_t_int>\ndouble ElementCabana::getMinCutoffRadius( t_SF SF, int attype,\n                                          h_t_int h_numSFperElem ) const\n{\n    double minCutoffRadius = numeric_limits<double>::max();\n\n    for ( int k = 0; k < h_numSFperElem( attype ); ++k )\n        minCutoffRadius = min( SF( attype, k, 7 ), minCutoffRadius );\n\n    return minCutoffRadius;\n}\n\ntemplate <class t_SF, class h_t_int>\ndouble ElementCabana::getMaxCutoffRadius( t_SF SF, int attype,\n                                          h_t_int h_numSFperElem ) const\n{\n    double maxCutoffRadius = 0.0;\n\n    for ( int k = 0; k < h_numSFperElem( attype ); ++k )\n        maxCutoffRadius = max( SF( attype, k, 7 ), maxCutoffRadius );\n\n    return maxCutoffRadius;\n}\n\n// TODO:add functionality\n/*\nvoid ElementCabana::updateSymmetryFunctionStatistics\n*/\n\n}\n"
  },
  {
    "path": "src/libnnpif/CabanaMD/ModeCabana.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Saaketh Desai and Sam Reeve\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef MODE_CABANA_H\n#define MODE_CABANA_H\n\n#include \"./ElementCabana.h\"\n#include \"typesCabana.h\"\n\n#include <Cabana_Core.hpp>\n#include <Kokkos_Core.hpp>\n\n#include \"CutoffFunction.h\"\n#include \"Log.h\"\n#include \"Mode.h\"\n#include \"Settings.h\"\n\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/** Derived Cabana main NNP class.\n *\n * The main n2p2 functions for computing energies and forces are replaced\n * to use the Kokkos and Cabana libraries. Most setup functions are\n * overridden; some are replaced as needed to work within device kernels.\n */\ntemplate <class t_device>\nclass ModeCabana : public Mode\n{\n\n public:\n    using Mode::Mode;\n\n    // Kokkos settings\n    using device_type = t_device;\n    using exe_space = typename device_type::execution_space;\n    using memory_space = typename device_type::memory_space;\n    typedef typename exe_space::array_layout layout;\n    using host_space = Kokkos::HostSpace;\n\n    // Per-type Kokkos::Views\n    using d_t_mass = Kokkos::View<T_V_FLOAT *, memory_space>;\n    using h_t_mass = Kokkos::View<T_V_FLOAT *, layout, host_space>;\n    using d_t_int = Kokkos::View<T_INT *, memory_space>;\n    using h_t_int = Kokkos::View<T_INT *, layout, host_space>;\n\n    // SymmetryFunctionTypes Kokkos::Views\n    using d_t_SF = Kokkos::View<T_FLOAT * * [15], memory_space>;\n    using t_SF = Kokkos::View<T_FLOAT * * [15], layout, host_space>;\n    using d_t_SFscaling = Kokkos::View<T_FLOAT * * [8], memory_space>;\n    using t_SFscaling = Kokkos::View<T_FLOAT * * [8], layout, host_space>;\n    using d_t_SFGmemberlist = Kokkos::View<T_INT ***, memory_space>;\n    using t_SFGmemberlist = Kokkos::View<T_INT ***, layout, host_space>;\n\n    // NN Kokkos::Views\n    using d_t_bias = Kokkos::View<T_FLOAT ***, memory_space>;\n    using t_bias = Kokkos::View<T_FLOAT ***, layout, host_space>;\n    using d_t_weights = Kokkos::View<T_FLOAT ****, memory_space>;\n    using t_weights = Kokkos::View<T_FLOAT ****, layout, host_space>;\n    using d_t_NN = Kokkos::View<T_FLOAT ***, memory_space>;\n\n    /** Set up the element map.\n     *\n     * Uses keyword `elements`. This function should follow immediately after\n     * settings are loaded via loadSettingsFile().\n     */\n    void setupElementMap() override;\n    /** Set up all Element instances.\n     *\n     * Uses keywords `number_of_elements` and `atom_energy`. This function\n     * should follow immediately after setupElementMap().\n     */\n    void setupElements() override;\n    /** Set up all symmetry functions.\n     *\n     * Uses keyword `symfunction_short`. Reads all symmetry functions from\n     * settings and automatically assigns them to the correct element.\n     */\n    void setupSymmetryFunctions() override;\n    /** Set up symmetry function scaling from file.\n     *\n     * @param[in] fileName Scaling file name.\n     *\n     * Uses keywords `scale_symmetry_functions`, `center_symmetry_functions`,\n     * `scale_symmetry_functions_sigma`, `scale_min_short` and\n     * `scale_max_short`. Reads in scaling information and sets correct scaling\n     * behavior for all symmetry functions. Call after\n     * setupSymmetryFunctions().\n     */\n    void setupSymmetryFunctionScaling(\n             std::string const &fileName = \"scaling.data\") override;\n    /** Set up symmetry function groups.\n     *\n     * Does not use any keywords. Call after setupSymmetryFunctions() and\n     * ensure that correct scaling behavior has already been set.\n     */\n    void setupSymmetryFunctionGroups() override;\n    /** Set up neural networks for all elements.\n     *\n     * Uses keywords `global_hidden_layers_short`, `global_nodes_short`,\n     * `global_activation_short`, `normalize_nodes`. Call after\n     * setupSymmetryFunctions(), only then the number of input layer neurons is\n     * known.\n     */\n    void setupNeuralNetwork() override;\n    /** Set up neural network weights from files.\n     *\n     * @param[in] fileNameFormat Format for weights file name. The string must\n     *                           contain one placeholder for the atomic number.\n     *\n     * Does not use any keywords. The weight files should contain one weight\n     * per line, see NeuralNetwork::setConnections() for the correct order.\n     */\n    void setupNeuralNetworkWeights(\n        std::string const &fileNameFormat = \"weights.%03zu.data\") override;\n\n    /* Compute cutoff for a single atom pair.\n     *\n     * @param[in] cutoffType Cutoff type.\n     * @param[in] fc Cutoff function value.\n     * @param[in] dfc Derivative of cutoff function.\n     * @param[in] r Atom separation distance.\n     * @param[in] rc Cutoff radius.\n     * @param[in] derivative If the cutoff derivative should be computed.\n     *\n     * Callable within device kernel.\n     */\n    KOKKOS_INLINE_FUNCTION\n    void compute_cutoff(CutoffFunction::CutoffType cutoffType, double cutoffAlpha,\n                        double &fc, double &dfc, double r, double rc,\n                        bool derivative) const;\n    /*\n     * Scale one symmetry function.\n     *\n     * @param[in] attype Atom type.\n     * @param[in] value Scaled symmetry function value.\n     * @param[in] k Symmetry function index.\n     * @param[in] SFscaling Kokkos host View of symmetry function scaling.\n     *\n     * Callable within device kernel.\n     */\n    KOKKOS_INLINE_FUNCTION\n    double scale(int attype, double value, int k, d_t_SFscaling SFscaling) const;\n\n    /** Calculate forces for all atoms in given structure.\n     *\n     * @param[in] x Cabana slice of atom positions.\n     * @param[in] f Cabana slice of atom forces.\n     * @param[in] type Cabana slice of atom types.\n     * @param[in] dEdG Cabana slice of the derivative of energy with respect\n                       to symmetry functions per atom.\n     * @param[in] N_local Number of atoms.\n     * @param[in] neigh_op Cabana tag for neighbor parallelism.\n     * @param[in] angle_op Cabana tag for angular parallelism.\n     *\n     * Combine intermediate results from symmetry function and neural network\n     * computation to atomic forces. Results are stored in f.\n     */\n    template <class t_slice_x, class t_slice_f, class t_slice_type,\n              class t_slice_dEdG, class t_neigh_list, class t_neigh_parallel,\n              class t_angle_parallel>\n    void calculateForces(t_slice_x x, t_slice_f f, t_slice_type type,\n                         t_slice_dEdG dEdG, t_neigh_list neigh_list, int N_local,\n                         t_neigh_parallel neigh_op, t_angle_parallel angle_op);\n\n    /** Calculate atomic neural networks for all atoms in given structure.\n     *\n     * @param[in] type Cabana slice of atom types.\n     * @param[in] G Cabana slice of symmetry functions per atom.\n     * @param[in] dEdG Cabana slice of the derivative of energy with respect\n                       to symmetry functions per atom.\n     * @param[in] E Cabana slice of energy per atom.\n     * @param[in] N_local Number of atoms.\n     *\n     * The atomic energy is stored in E.\n     */\n    template <class t_slice_type, class t_slice_G, class t_slice_dEdG,\n              class t_slice_E>\n    void calculateAtomicNeuralNetworks(t_slice_type type, t_slice_G G,\n                                       t_slice_dEdG dEdG, t_slice_E E,\n                                       int N_local);\n\n    /** Calculate all symmetry function groups for all atoms in given\n     * structure.\n     *\n     * @param[in] x Cabana slice of atom positions.\n     * @param[in] type Cabana slice of atom types.\n     * @param[in] G Cabana slice of symmetry functions per atom.\n     * @param[in] neigh_list Cabana neighbor list.\n     * @param[in] N_local Number of atoms.\n     * @param[in] neigh_op Cabana tag for neighbor parallelism.\n     * @param[in] angle_op Cabana tag for angular parallelism.\n     *\n     * Note there is no calculateSymmetryFunctions() within this derived class.\n     * Results are stored in G.\n     */\n    template <class t_slice_x, class t_slice_type, class t_slice_G,\n              class t_neigh_list, class t_neigh_parallel, class t_angle_parallel>\n    void calculateSymmetryFunctionGroups(t_slice_x x, t_slice_type type,\n                                         t_slice_G G, t_neigh_list neigh_list,\n                                         int N_local, t_neigh_parallel neigh_op,\n                                         t_angle_parallel angle_op);\n\n    using Mode::log;\n\n    /// list of element symbols in order of periodic table\n    // (duplicated from ElementMap)\n    std::vector<std::string> knownElements = {\n        \"H\",  \"He\", \"Li\", \"Be\", \"B\",  \"C\",  \"N\",  \"O\",  \"F\",  \"Ne\", \"Na\", \"Mg\",\n        \"Al\", \"Si\", \"P\",  \"S\",  \"Cl\", \"Ar\", \"K\",  \"Ca\", \"Sc\", \"Ti\", \"V\",  \"Cr\",\n        \"Mn\", \"Fe\", \"Co\", \"Ni\", \"Cu\", \"Zn\", \"Ga\", \"Ge\", \"As\", \"Se\", \"Br\", \"Kr\",\n        \"Rb\", \"Sr\", \"Y\",  \"Zr\", \"Nb\", \"Mo\", \"Tc\", \"Ru\", \"Rh\", \"Pd\", \"Ag\", \"Cd\",\n        \"In\", \"Sn\", \"Sb\", \"Te\", \"I\",  \"Xe\", \"Cs\", \"Ba\", \"La\", \"Ce\", \"Pr\", \"Nd\",\n        \"Pm\", \"Sm\", \"Eu\", \"Gd\", \"Tb\", \"Dy\", \"Ho\", \"Er\", \"Tm\", \"Yb\", \"Lu\", \"Hf\",\n        \"Ta\", \"W\",  \"Re\", \"Os\", \"Ir\", \"Pt\", \"Au\", \"Hg\", \"Tl\", \"Pb\", \"Bi\", \"Po\",\n        \"At\", \"Rn\", \"Fr\", \"Ra\", \"Ac\", \"Th\", \"Pa\", \"U\",  \"Np\", \"Pu\", \"Am\", \"Cm\",\n        \"Bk\", \"Cf\", \"Es\", \"Fm\", \"Md\", \"No\"};\n\n    // Symmetry function Kokkos::Views\n    d_t_SF d_SF;\n    t_SF SF;\n    d_t_SFGmemberlist d_SFGmemberlist;\n    t_SFGmemberlist SFGmemberlist;\n    d_t_SFscaling d_SFscaling;\n    t_SFscaling SFscaling;\n\n    // NN Kokkos::Views\n    d_t_bias bias;\n    d_t_weights weights;\n    t_bias h_bias;\n    t_weights h_weights;\n    int numLayers, numHiddenLayers, maxNeurons;\n    d_t_int numNeuronsPerLayer;\n    h_t_int h_numNeuronsPerLayer;\n    d_t_int AF;\n    h_t_int h_AF;\n\n    // Per type Kokkos::Views\n    h_t_mass atomicEnergyOffset;\n    h_t_int h_numSFperElem;\n    d_t_int numSFperElem;\n    h_t_int h_numSFGperElem;\n    d_t_int numSFGperElem;\n    int maxSFperElem;\n\n    using Mode::numElements;\n    using Mode::minNeighbors;\n    using Mode::minCutoffRadius;\n    using Mode::maxCutoffRadius;\n    using Mode::cutoffAlpha;\n    double meanEnergy;\n    using Mode::convEnergy;\n    using Mode::convLength;\n    ScalingType scalingType;\n    using Mode::settings;\n    using Mode::cutoffType;\n    std::vector<ElementCabana> elements;\n    std::vector<std::string> elementStrings;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ntemplate <class t_device>\nKOKKOS_INLINE_FUNCTION void\nModeCabana<t_device>::compute_cutoff(CutoffFunction::CutoffType cutoffType,\n                                     double cutoffAlpha, double &fc, double &dfc,\n                                     double r, double rc, bool derivative) const\n{\n    double temp;\n    if (cutoffType == CutoffFunction::CT_TANHU) {\n        temp = tanh(1.0 - r / rc);\n        fc = temp * temp * temp;\n        if (derivative)\n            dfc = 3.0 * temp * temp * (temp * temp - 1.0) / rc;\n    }\n\n    if (cutoffType == CutoffFunction::CT_COS) {\n\n        double rci = rc * cutoffAlpha;\n        double iw = 1.0 / (rc - rci);\n        double PI = 4.0 * atan(1.0);\n        if (r < rci) {\n            fc = 1.0;\n            dfc = 0.0;\n        } else {\n            temp = cos(PI * (r - rci) * iw);\n            fc = 0.5 * (temp + 1.0);\n            if (derivative)\n                dfc = -0.5 * iw * PI * sqrt(1.0 - temp * temp);\n        }\n    }\n}\n\ntemplate <class t_device>\nKOKKOS_INLINE_FUNCTION double\nModeCabana<t_device>::scale(int attype, double value, int k,\n                            d_t_SFscaling SFscaling_) const\n{\n    double scalingType = SFscaling_(attype, k, 7);\n    double scalingFactor = SFscaling_(attype, k, 6);\n    double Gmin = SFscaling_(attype, k, 0);\n    // double Gmax = SFscaling_(attype,k,1);\n    double Gmean = SFscaling_(attype, k, 2);\n    // double Gsigma = SFscaling_(attype,k,3);\n    double Smin = SFscaling_(attype, k, 4);\n    // double Smax = SFscaling_(attype,k,5);\n\n    if (scalingType == 0.0) {\n        return value;\n    } else if (scalingType == 1.0) {\n        return Smin + scalingFactor * (value - Gmin);\n    } else if (scalingType == 2.0) {\n        return value - Gmean;\n    } else if (scalingType == 3.0) {\n        return Smin + scalingFactor * (value - Gmean);\n    } else if (scalingType == 4.0) {\n        return Smin + scalingFactor * (value - Gmean);\n    } else {\n        return 0.0;\n    }\n}\n\n}\n\n#include \"ModeCabana_impl.h\"\n\n#endif\n"
  },
  {
    "path": "src/libnnpif/CabanaMD/ModeCabana_impl.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Saaketh Desai and Sam Reeve\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"utility.h\"\n\n#include <algorithm> // std::min, std::max\n#include <cstdlib>   // atoi, atof\n#include <fstream>   // std::ifstream\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n#include <string>\n\nusing namespace std;\n\nnamespace nnp\n{\n\n// TODO: call base, then copy to Views\ntemplate <class t_device>\nvoid ModeCabana<t_device>::setupElementMap()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: ELEMENT MAP ******************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    elementStrings = split( reduce( settings[\"elements\"] ) );\n\n    log << strpr( \"Number of element strings found: %d\\n\",\n                       elementStrings.size() );\n    for ( size_t i = 0; i < elementStrings.size(); ++i )\n    {\n        log << strpr( \"Element %2zu: %2s\\n\", i,\n                           elementStrings[i].c_str() );\n    }\n    // resize to match number of element types\n    numElements = elementStrings.size();\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\ntemplate <class t_device>\nvoid ModeCabana<t_device>::setupElements()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: ELEMENTS *********************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    numElements = (size_t)atoi( settings[\"number_of_elements\"].c_str() );\n    atomicEnergyOffset =\n        h_t_mass( \"Mode::atomicEnergyOffset\", numElements );\n    if ( numElements != elementStrings.size() )\n    {\n        throw runtime_error( \"ERROR: Inconsistent number of elements.\\n\" );\n    }\n    log << strpr( \"Number of elements is consistent: %zu\\n\", numElements );\n\n    for ( size_t i = 0; i < numElements; ++i )\n    {\n        elements.push_back( ElementCabana( i ) );\n    }\n\n    if ( settings.keywordExists( \"atom_energy\" ) )\n    {\n        Settings::KeyRange r = settings.getValues( \"atom_energy\" );\n        for ( Settings::KeyMap::const_iterator it = r.first;\n              it != r.second; ++it )\n        {\n            vector<string> args = split( reduce( it->second.first ) );\n            const char *estring = args.at( 0 ).c_str();\n            for ( size_t i = 0; i < elementStrings.size(); ++i )\n            {\n                if ( strcmp( elementStrings[i].c_str(), estring ) == 0 )\n                    atomicEnergyOffset( i ) = atof( args.at( 1 ).c_str() );\n            }\n        }\n    }\n\n    log << \"Atomic energy offsets per element:\\n\";\n    for ( size_t i = 0; i < elementStrings.size(); ++i )\n    {\n        log << strpr( \"Element %2zu: %16.8E\\n\", i,\n                           atomicEnergyOffset( i ) );\n    }\n\n    log << \"Energy offsets are automatically subtracted from reference \"\n           \"energies.\\n\";\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\ntemplate <class t_device>\nvoid ModeCabana<t_device>::setupSymmetryFunctions()\n{\n    maxSFperElem = 0;\n    h_numSFperElem =\n        h_t_int( \"Mode::numSymmetryFunctionsPerElement\", numElements );\n    log << \"\\n\";\n    log << \"*** SETUP: SYMMETRY FUNCTIONS ***********\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    // Only count SF per element; parse and add later\n    Settings::KeyRange r = settings.getValues( \"symfunction_short\" );\n    for ( Settings::KeyMap::const_iterator it = r.first; it != r.second;\n          ++it )\n    {\n        vector<string> args = split( reduce( it->second.first ) );\n        int type = 0;\n        const char *estring = args.at( 0 ).c_str();\n        for ( size_t i = 0; i < elementStrings.size(); ++i )\n        {\n            if ( strcmp( elementStrings[i].c_str(), estring ) == 0 )\n                type = i;\n        }\n        h_numSFperElem( type )++;\n\n        if ( h_numSFperElem( type ) > maxSFperElem )\n            maxSFperElem = h_numSFperElem( type );\n    }\n    Kokkos::deep_copy( h_numSFperElem, 0 );\n\n    // setup SF host views\n    // create device mirrors if needed below\n    SF = t_SF( \"SymmetryFunctions\", numElements, maxSFperElem );\n    SFscaling = t_SFscaling( \"SFscaling\", numElements, maxSFperElem );\n    // +1 to store size of memberlist\n    SFGmemberlist = t_SFGmemberlist( \"SFGmemberlist\", numElements,\n                                     maxSFperElem + 1, maxSFperElem + 1 );\n\n    r = settings.getValues( \"symfunction_short\" );\n    for ( Settings::KeyMap::const_iterator it = r.first; it != r.second;\n          ++it )\n    {\n        vector<string> args = split( reduce( it->second.first ) );\n        int type = 0;\n        const char *estring = args.at( 0 ).c_str();\n        for ( size_t i = 0; i < elementStrings.size(); ++i )\n        {\n            if ( strcmp( elementStrings[i].c_str(), estring ) == 0 )\n                type = i;\n        }\n        elements.at( type ).addSymmetryFunction( it->second.first,\n                                                 elementStrings, type, SF,\n                                                 convLength, h_numSFperElem );\n    }\n\n    log << \"Abbreviations:\\n\";\n    log << \"--------------\\n\";\n    log << \"ind .... Symmetry function index.\\n\";\n    log << \"ec ..... Central atom element.\\n\";\n    log << \"ty ..... Symmetry function type.\\n\";\n    log << \"e1 ..... Neighbor 1 element.\\n\";\n    log << \"e2 ..... Neighbor 2 element.\\n\";\n    log << \"eta .... Gaussian width eta.\\n\";\n    log << \"rs ..... Shift distance of Gaussian.\\n\";\n    log << \"la ..... Angle prefactor lambda.\\n\";\n    log << \"zeta ... Angle term exponent zeta.\\n\";\n    log << \"rc ..... Cutoff radius.\\n\";\n    log << \"ct ..... Cutoff type.\\n\";\n    log << \"ca ..... Cutoff alpha.\\n\";\n    log << \"ln ..... Line number in settings file.\\n\";\n    log << \"\\n\";\n    maxCutoffRadius = 0.0;\n\n    for ( vector<ElementCabana>::iterator it = elements.begin(); it != elements.end();\n          ++it )\n    {\n        int attype = it->getIndex();\n        it->sortSymmetryFunctions( SF, h_numSFperElem, attype );\n        maxCutoffRadius =\n            max( it->getMaxCutoffRadius( SF, attype, h_numSFperElem ),\n                 maxCutoffRadius );\n        it->setCutoffFunction( cutoffType, cutoffAlpha, SF, attype,\n                               h_numSFperElem );\n        log << strpr(\n            \"Short range atomic symmetry functions element %2s :\\n\",\n            it->getSymbol().c_str() );\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        log << \" ind ec ty e1 e2       eta        rs la \"\n               \"zeta        rc ct   ca    ln\\n\";\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        log << it->infoSymmetryFunctionParameters( SF, attype, h_numSFperElem );\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n    }\n    minNeighbors.resize( numElements, 0 );\n    minCutoffRadius.resize( numElements, maxCutoffRadius );\n    for ( size_t i = 0; i < numElements; ++i )\n    {\n        int attype = elements.at( i ).getIndex();\n        int nSF = h_numSFperElem( attype );\n        minNeighbors.at( i ) =\n            elements.at( i ).getMinNeighbors( attype, SF, nSF );\n        minCutoffRadius.at( i ) =\n            elements.at( i ).getMinCutoffRadius( SF, attype, h_numSFperElem );\n        log << strpr( \"Minimum cutoff radius for element %2s: %f\\n\",\n                           elements.at( i ).getSymbol().c_str(),\n                           minCutoffRadius.at( i ) / convLength );\n    }\n    log << strpr( \"Maximum cutoff radius (global)      : %f\\n\",\n                       maxCutoffRadius / convLength );\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    numSFperElem =\n        Kokkos::create_mirror_view_and_copy( memory_space(), h_numSFperElem );\n\n    return;\n}\n\n// TODO: call base, then copy to View\ntemplate <class t_device>\nvoid ModeCabana<t_device>::setupSymmetryFunctionScaling( string const &fileName )\n{\n    log << \"\\n\";\n    log << \"*** SETUP: SYMMETRY FUNCTION SCALING ****\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << \"Equal scaling type for all symmetry functions:\\n\";\n    if ( ( settings.keywordExists( \"scale_symmetry_functions\" ) ) &&\n         ( !settings.keywordExists( \"center_symmetry_functions\" ) ) )\n    {\n        scalingType = ST_SCALE;\n        log << strpr( \"Scaling type::ST_SCALE (%d)\\n\", scalingType );\n        log << \"Gs = Smin + (Smax - Smin) * (G - Gmin) / (Gmax - Gmin)\\n\";\n    }\n    else if ( ( !settings.keywordExists( \"scale_symmetry_functions\" ) ) &&\n              ( settings.keywordExists( \"center_symmetry_functions\" ) ) )\n    {\n        scalingType = ST_CENTER;\n        log << strpr( \"Scaling type::ST_CENTER (%d)\\n\", scalingType );\n        log << \"Gs = G - Gmean\\n\";\n    }\n    else if ( ( settings.keywordExists( \"scale_symmetry_functions\" ) ) &&\n              ( settings.keywordExists( \"center_symmetry_functions\" ) ) )\n    {\n        scalingType = ST_SCALECENTER;\n        log << strpr( \"Scaling type::ST_SCALECENTER (%d)\\n\", scalingType );\n        log << \"Gs = Smin + (Smax - Smin) * (G - Gmean) / (Gmax - Gmin)\\n\";\n    }\n    else if ( settings.keywordExists( \"scale_symmetry_functions_sigma\" ) )\n    {\n        scalingType = ST_SCALESIGMA;\n        log << strpr( \"Scaling type::ST_SCALESIGMA (%d)\\n\", scalingType );\n        log << \"Gs = Smin + (Smax - Smin) * (G - Gmean) / Gsigma\\n\";\n    }\n    else\n    {\n        scalingType = ST_NONE;\n        log << strpr( \"Scaling type::ST_NONE (%d)\\n\", scalingType );\n        log << \"Gs = G\\n\";\n        log << \"WARNING: No symmetry function scaling!\\n\";\n    }\n\n    double Smin = 0.0;\n    double Smax = 0.0;\n    if ( scalingType == ST_SCALE || scalingType == ST_SCALECENTER ||\n         scalingType == ST_SCALESIGMA )\n    {\n        if ( settings.keywordExists( \"scale_min_short\" ) )\n        {\n            Smin = atof( settings[\"scale_min_short\"].c_str() );\n        }\n        else\n        {\n            log << \"WARNING: Keyword \\\"scale_min_short\\\" not found.\\n\";\n            log << \"         Default value for Smin = 0.0.\\n\";\n            Smin = 0.0;\n        }\n\n        if ( settings.keywordExists( \"scale_max_short\" ) )\n        {\n            Smax = atof( settings[\"scale_max_short\"].c_str() );\n        }\n        else\n        {\n            log << \"WARNING: Keyword \\\"scale_max_short\\\" not found.\\n\";\n            log << \"         Default value for Smax = 1.0.\\n\";\n            Smax = 1.0;\n        }\n\n        log << strpr( \"Smin = %f\\n\", Smin );\n        log << strpr( \"Smax = %f\\n\", Smax );\n    }\n\n    log << strpr( \"Symmetry function scaling statistics from file: %s\\n\",\n                       fileName.c_str() );\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    ifstream file;\n    file.open( fileName.c_str() );\n    if ( !file.is_open() )\n    {\n        throw runtime_error( \"ERROR: Could not open file: \\\"\" + fileName +\n                             \"\\\".\\n\" );\n    }\n    string line;\n    vector<string> lines;\n    while ( getline( file, line ) )\n    {\n        if ( line.at( 0 ) != '#' )\n            lines.push_back( line );\n    }\n    file.close();\n\n    log << \"\\n\";\n    log << \"Abbreviations:\\n\";\n    log << \"--------------\\n\";\n    log << \"ind ..... Symmetry function index.\\n\";\n    log << \"min ..... Minimum symmetry function value.\\n\";\n    log << \"max ..... Maximum symmetry function value.\\n\";\n    log << \"mean .... Mean symmetry function value.\\n\";\n    log << \"sigma ... Standard deviation of symmetry function values.\\n\";\n    log << \"sf ...... Scaling factor for derivatives.\\n\";\n    log << \"Smin .... Desired minimum scaled symmetry function value.\\n\";\n    log << \"Smax .... Desired maximum scaled symmetry function value.\\n\";\n    log << \"t ....... Scaling type.\\n\";\n    log << \"\\n\";\n    for ( vector<ElementCabana>::iterator it = elements.begin(); it != elements.end();\n          ++it )\n    {\n        int attype = it->getIndex();\n        it->setScaling( scalingType, lines, Smin, Smax, SF, SFscaling, attype,\n                        h_numSFperElem );\n        log << strpr(\n            \"Scaling data for symmetry functions element %2s :\\n\",\n            it->getSymbol().c_str() );\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        log << \" ind       min       max      mean     sigma        sf  Smin  \"\n               \"Smax t\\n\";\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        log << it->infoSymmetryFunctionScaling( scalingType, SF, SFscaling,\n                                                attype, h_numSFperElem );\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        lines.erase( lines.begin(),\n                     lines.begin() +\n                         it->numSymmetryFunctions( attype, h_numSFperElem ) );\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    d_SF = Kokkos::create_mirror_view_and_copy( memory_space(), SF );\n    d_SFscaling =\n        Kokkos::create_mirror_view_and_copy( memory_space(), SFscaling );\n    d_SFGmemberlist =\n        Kokkos::create_mirror_view_and_copy( memory_space(), SFGmemberlist );\n\n    return;\n}\n\ntemplate <class t_device>\nvoid ModeCabana<t_device>::setupSymmetryFunctionGroups()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: SYMMETRY FUNCTION GROUPS *****\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << \"Abbreviations:\\n\";\n    log << \"--------------\\n\";\n    log << \"ind .... Symmetry function group index.\\n\";\n    log << \"ec ..... Central atom element.\\n\";\n    log << \"ty ..... Symmetry function type.\\n\";\n    log << \"e1 ..... Neighbor 1 element.\\n\";\n    log << \"e2 ..... Neighbor 2 element.\\n\";\n    log << \"eta .... Gaussian width eta.\\n\";\n    log << \"rs ..... Shift distance of Gaussian.\\n\";\n    log << \"la ..... Angle prefactor lambda.\\n\";\n    log << \"zeta ... Angle term exponent zeta.\\n\";\n    log << \"rc ..... Cutoff radius.\\n\";\n    log << \"ct ..... Cutoff type.\\n\";\n    log << \"ca ..... Cutoff alpha.\\n\";\n    log << \"ln ..... Line number in settings file.\\n\";\n    log << \"mi ..... Member index.\\n\";\n    log << \"sfi .... Symmetry function index.\\n\";\n    log << \"e ...... Recalculate exponential term.\\n\";\n    log << \"\\n\";\n\n    h_numSFGperElem =\n        h_t_int( \"Mode::numSymmetryFunctionGroupsPerElement\", numElements );\n\n    for ( vector<ElementCabana>::iterator it = elements.begin(); it != elements.end();\n          ++it )\n    {\n        int attype = it->getIndex();\n        it->setupSymmetryFunctionGroups( SF, SFGmemberlist, attype,\n                                         h_numSFperElem, h_numSFGperElem,\n                                         maxSFperElem );\n        log << strpr( \"Short range atomic symmetry function groups \"\n                           \"element %2s :\\n\",\n                           it->getSymbol().c_str() );\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        log << \" ind ec ty e1 e2       eta        rs la \"\n               \"zeta        rc ct   ca    ln   mi  sfi e\\n\";\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n        log << it->infoSymmetryFunctionGroups( SF, SFGmemberlist, attype,\n                                               h_numSFGperElem );\n        log << \"-----------------------------------------\"\n               \"--------------------------------------\\n\";\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    numSFGperElem =\n        Kokkos::create_mirror_view_and_copy( memory_space(), h_numSFGperElem );\n\n    return;\n}\n\ntemplate <class t_device>\nvoid ModeCabana<t_device>::setupNeuralNetwork()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: NEURAL NETWORKS **************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    numLayers = 2 + atoi( settings[\"global_hidden_layers_short\"].c_str() );\n    numHiddenLayers = numLayers - 2;\n\n    h_numNeuronsPerLayer = h_t_int( \"Mode::numNeuronsPerLayer\", numLayers );\n    h_AF = h_t_int( \"Mode::ActivationFunctions\", numLayers );\n\n    vector<string> numNeuronsPerHiddenLayer =\n        split( reduce( settings[\"global_nodes_short\"] ) );\n    vector<string> activationFunctions =\n        split( reduce( settings[\"global_activation_short\"] ) );\n\n    for ( int i = 0; i < numLayers; i++ )\n    {\n        if ( i == 0 )\n            h_AF( i ) = 0;\n        else if ( i == numLayers - 1 )\n        {\n            h_numNeuronsPerLayer( i ) = 1;\n            h_AF( i ) = 0;\n        }\n        else\n        {\n            h_numNeuronsPerLayer( i ) =\n                atoi( numNeuronsPerHiddenLayer.at( i - 1 ).c_str() );\n            h_AF( i ) = 1; // TODO: hardcoded atoi(activationFunctions.at(i-1));\n        }\n    }\n\n    // TODO: add normalization of neurons\n    bool normalizeNeurons = settings.keywordExists( \"normalize_nodes\" );\n    log << strpr( \"Normalize neurons (all elements): %d\\n\",\n                       (int)normalizeNeurons );\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n\n    for ( vector<ElementCabana>::iterator it = elements.begin(); it != elements.end();\n          ++it )\n    {\n        int attype = it->getIndex();\n        h_numNeuronsPerLayer( 0 ) =\n            it->numSymmetryFunctions( attype, h_numSFperElem );\n        log << strpr( \"Atomic short range NN for \"\n                           \"element %2s :\\n\",\n                           it->getSymbol().c_str() );\n\n        int numWeights = 0, numBiases = 0, numConnections = 0;\n        for ( int j = 1; j < numLayers; ++j )\n        {\n            numWeights +=\n                h_numNeuronsPerLayer( j - 1 ) * h_numNeuronsPerLayer( j );\n            numBiases += h_numNeuronsPerLayer( j );\n        }\n        numConnections = numWeights + numBiases;\n        log << strpr( \"Number of weights    : %6zu\\n\", numWeights );\n        log << strpr( \"Number of biases     : %6zu\\n\", numBiases );\n        log << strpr( \"Number of connections: %6zu\\n\", numConnections );\n        log << strpr( \"Architecture    \" );\n        for ( int j = 0; j < numLayers; ++j )\n            log << strpr( \" %4d\", h_numNeuronsPerLayer( j ) );\n\n        log << \"\\n-----------------------------------------\"\n               \"--------------------------------------\\n\";\n    }\n\n    // initialize Views\n    maxNeurons = 0;\n    for ( int j = 0; j < numLayers; ++j )\n        maxNeurons = max( maxNeurons, h_numNeuronsPerLayer( j ) );\n\n    h_bias = t_bias( \"Mode::biases\", numElements, numLayers, maxNeurons );\n    h_weights = t_weights( \"Mode::weights\", numElements, numLayers,\n                           maxNeurons, maxNeurons );\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\ntemplate <class t_device>\nvoid ModeCabana<t_device>::setupNeuralNetworkWeights( string const &fileNameFormat )\n{\n    log << \"\\n\";\n    log << \"*** SETUP: NEURAL NETWORK WEIGHTS *******\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << strpr( \"Weight file name format: %s\\n\",\n                       fileNameFormat.c_str() );\n    int count = 0;\n    int AN = 0;\n    for ( vector<ElementCabana>::iterator it = elements.begin(); it != elements.end();\n          ++it )\n    {\n        const char *estring = elementStrings[count].c_str();\n        for ( size_t i = 0; i < knownElements.size(); ++i )\n        {\n            if ( strcmp( knownElements[i].c_str(), estring ) == 0 )\n            {\n                AN = i + 1;\n                break;\n            }\n        }\n\n        string fileName = strpr( fileNameFormat.c_str(), AN );\n        log << strpr( \"Weight file for element %2s: %s\\n\",\n                           elementStrings[count].c_str(), fileName.c_str() );\n        ifstream file;\n        file.open( fileName.c_str() );\n        if ( !file.is_open() )\n        {\n            throw runtime_error( \"ERROR: Could not open file: \\\"\" + fileName +\n                                 \"\\\".\\n\" );\n        }\n        string line;\n        int attype = it->getIndex();\n        int layer, start, end;\n        while ( getline( file, line ) )\n        {\n            if ( line.at( 0 ) != '#' )\n            {\n                vector<string> splitLine = split( reduce( line ) );\n                if ( strcmp( splitLine.at( 1 ).c_str(), \"a\" ) == 0 )\n                {\n                    layer = atoi( splitLine.at( 3 ).c_str() );\n                    start = atoi( splitLine.at( 4 ).c_str() ) - 1;\n                    end = atoi( splitLine.at( 6 ).c_str() ) - 1;\n                    h_weights( attype, layer, end, start ) =\n                        atof( splitLine.at( 0 ).c_str() );\n                }\n                else if ( strcmp( splitLine.at( 1 ).c_str(), \"b\" ) == 0 )\n                {\n                    layer = atoi( splitLine.at( 3 ).c_str() ) - 1;\n                    start = atoi( splitLine.at( 4 ).c_str() ) - 1;\n                    h_bias( attype, layer, start ) =\n                        atof( splitLine.at( 0 ).c_str() );\n                }\n            }\n        }\n        file.close();\n        count += 1;\n    }\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    bias = Kokkos::create_mirror_view_and_copy( memory_space(), h_bias );\n    weights = Kokkos::create_mirror_view_and_copy( memory_space(), h_weights );\n    AF = Kokkos::create_mirror_view_and_copy( memory_space(), h_AF );\n    numNeuronsPerLayer = Kokkos::create_mirror_view_and_copy(\n        memory_space(), h_numNeuronsPerLayer );\n\n    return;\n}\n\ntemplate <class t_device>\ntemplate <class t_slice_x, class t_slice_type, class t_slice_G,\n          class t_neigh_list, class t_neigh_parallel, class t_angle_parallel>\nvoid ModeCabana<t_device>::calculateSymmetryFunctionGroups(\n    t_slice_x x, t_slice_type type, t_slice_G G, t_neigh_list neigh_list,\n    int N_local, t_neigh_parallel neigh_op_tag, t_angle_parallel angle_op_tag )\n{\n    Cabana::deep_copy( G, 0.0 );\n\n    Kokkos::RangePolicy<exe_space> policy( 0, N_local );\n\n    // Create local copies for lambda\n    auto numSFGperElem_ = numSFGperElem;\n    auto SFGmemberlist_ = d_SFGmemberlist;\n    auto SF_ = d_SF;\n    auto SFscaling_ = d_SFscaling;\n    auto maxSFperElem_ = maxSFperElem;\n    auto convLength_ = convLength;\n    auto cutoffType_ = cutoffType;\n    auto cutoffAlpha_ = cutoffAlpha;\n\n    auto calc_radial_symm_op = KOKKOS_LAMBDA( const int i, const int j )\n    {\n        double pfcij = 0.0;\n        double pdfcij = 0.0;\n        double eta, rs;\n        size_t nej;\n        int memberindex, globalIndex;\n        double rij, r2ij;\n        T_F_FLOAT dxij, dyij, dzij;\n\n        int attype = type( i );\n        for ( int groupIndex = 0; groupIndex < numSFGperElem_( attype );\n              ++groupIndex )\n        {\n            if ( SF_( attype, SFGmemberlist_( attype, groupIndex, 0 ), 1 ) ==\n                 2 )\n            {\n                size_t memberindex0 = SFGmemberlist_( attype, groupIndex, 0 );\n                size_t e1 = SF_( attype, memberindex0, 2 );\n                double rc = SF_( attype, memberindex0, 7 );\n                size_t size =\n                    SFGmemberlist_( attype, groupIndex, maxSFperElem_ );\n\n                nej = type( j );\n                dxij = ( x( i, 0 ) - x( j, 0 ) ) * CFLENGTH * convLength_;\n                dyij = ( x( i, 1 ) - x( j, 1 ) ) * CFLENGTH * convLength_;\n                dzij = ( x( i, 2 ) - x( j, 2 ) ) * CFLENGTH * convLength_;\n                r2ij = dxij * dxij + dyij * dyij + dzij * dzij;\n                rij = sqrt( r2ij );\n                if ( e1 == nej && rij < rc )\n                {\n                    compute_cutoff( cutoffType_, cutoffAlpha_, pfcij, pdfcij,\n                                    rij, rc, false );\n                    for ( size_t k = 0; k < size; ++k )\n                    {\n                        memberindex = SFGmemberlist_( attype, groupIndex, k );\n                        globalIndex = SF_( attype, memberindex, 14 );\n                        eta = SF_( attype, memberindex, 4 );\n                        rs = SF_( attype, memberindex, 8 );\n                        G( i, globalIndex ) +=\n                            exp( -eta * ( rij - rs ) * ( rij - rs ) ) * pfcij;\n                    }\n                }\n            }\n        }\n    };\n    Cabana::neighbor_parallel_for(\n        policy, calc_radial_symm_op, neigh_list, Cabana::FirstNeighborsTag(),\n        neigh_op_tag, \"Mode::calculateRadialSymmetryFunctionGroups\" );\n    Kokkos::fence();\n\n    auto calc_angular_symm_op =\n        KOKKOS_LAMBDA( const int i, const int j, const int k )\n    {\n        double pfcij = 0.0, pdfcij = 0.0;\n        double pfcik = 0.0, pdfcik = 0.0;\n        double pfcjk = 0.0, pdfcjk = 0.0;\n        size_t nej, nek;\n        int memberindex, globalIndex;\n        double rij, r2ij, rik, r2ik, rjk, r2jk;\n        T_F_FLOAT dxij, dyij, dzij, dxik, dyik, dzik, dxjk, dyjk, dzjk;\n        double eta, rs, lambda, zeta;\n\n        int attype = type( i );\n        for ( int groupIndex = 0; groupIndex < numSFGperElem_( attype );\n              ++groupIndex )\n        {\n            if ( SF_( attype, SFGmemberlist_( attype, groupIndex, 0 ), 1 ) ==\n                 3 )\n            {\n                size_t memberindex0 = SFGmemberlist_( attype, groupIndex, 0 );\n                size_t e1 = SF_( attype, memberindex0, 2 );\n                size_t e2 = SF_( attype, memberindex0, 3 );\n                double rc = SF_( attype, memberindex0, 7 );\n                size_t size =\n                    SFGmemberlist_( attype, groupIndex, maxSFperElem_ );\n\n                nej = type( j );\n                dxij = ( x( i, 0 ) - x( j, 0 ) ) * CFLENGTH * convLength_;\n                dyij = ( x( i, 1 ) - x( j, 1 ) ) * CFLENGTH * convLength_;\n                dzij = ( x( i, 2 ) - x( j, 2 ) ) * CFLENGTH * convLength_;\n                r2ij = dxij * dxij + dyij * dyij + dzij * dzij;\n                rij = sqrt( r2ij );\n                if ( ( e1 == nej || e2 == nej ) && rij < rc )\n                {\n                    // Calculate cutoff function and derivative.\n                    compute_cutoff( cutoffType_, cutoffAlpha_, pfcij, pdfcij,\n                                    rij, rc, false );\n\n                    nek = type( k );\n\n                    if ( ( e1 == nej && e2 == nek ) ||\n                         ( e2 == nej && e1 == nek ) )\n                    {\n                        dxik =\n                            ( x( i, 0 ) - x( k, 0 ) ) * CFLENGTH * convLength_;\n                        dyik =\n                            ( x( i, 1 ) - x( k, 1 ) ) * CFLENGTH * convLength_;\n                        dzik =\n                            ( x( i, 2 ) - x( k, 2 ) ) * CFLENGTH * convLength_;\n                        r2ik = dxik * dxik + dyik * dyik + dzik * dzik;\n                        rik = sqrt( r2ik );\n                        if ( rik < rc )\n                        {\n                            dxjk = dxik - dxij;\n                            dyjk = dyik - dyij;\n                            dzjk = dzik - dzij;\n                            r2jk = dxjk * dxjk + dyjk * dyjk + dzjk * dzjk;\n                            if ( r2jk < rc * rc )\n                            {\n                                // Energy calculation.\n                                compute_cutoff( cutoffType_, cutoffAlpha_,\n                                                pfcik, pdfcik, rik, rc, false );\n\n                                rjk = sqrt( r2jk );\n                                compute_cutoff( cutoffType_, cutoffAlpha_,\n                                                pfcjk, pdfcjk, rjk, rc, false );\n\n                                double const rinvijik = 1.0 / rij / rik;\n                                double const costijk =\n                                    ( dxij * dxik + dyij * dyik +\n                                      dzij * dzik ) *\n                                    rinvijik;\n                                double vexp = 0.0, rijs = 0.0, riks = 0.0,\n                                       rjks = 0.0;\n                                for ( size_t l = 0; l < size; ++l )\n                                {\n                                    globalIndex =\n                                        SF_( attype,\n                                              SFGmemberlist_( attype,\n                                                               groupIndex, l ),\n                                              14 );\n                                    memberindex = SFGmemberlist_(\n                                        attype, groupIndex, l );\n                                    eta = SF_( attype, memberindex, 4 );\n                                    lambda = SF_( attype, memberindex, 5 );\n                                    zeta = SF_( attype, memberindex, 6 );\n                                    rs = SF_( attype, memberindex, 8 );\n                                    if ( rs > 0.0 )\n                                    {\n                                        rijs = rij - rs;\n                                        riks = rik - rs;\n                                        rjks = rjk - rs;\n                                        vexp = exp( -eta * ( rijs * rijs +\n                                                             riks * riks +\n                                                             rjks * rjks ) );\n                                    }\n                                    else\n                                        vexp = exp( -eta *\n                                                    ( r2ij + r2ik + r2jk ) );\n                                    double const plambda =\n                                        1.0 + lambda * costijk;\n                                    double fg = vexp;\n                                    if ( plambda <= 0.0 )\n                                        fg = 0.0;\n                                    else\n                                        fg *= pow( plambda, ( zeta - 1.0 ) );\n                                    G( i, globalIndex ) +=\n                                        fg * plambda * pfcij * pfcik * pfcjk;\n                                } // l\n                            }     // rjk <= rc\n                        }         // rik <= rc\n                    }             // elem\n                }                 // rij <= rc\n            }\n        }\n    };\n    Cabana::neighbor_parallel_for(\n        policy, calc_angular_symm_op, neigh_list, Cabana::SecondNeighborsTag(),\n        angle_op_tag, \"Mode::calculateAngularSymmetryFunctionGroups\" );\n    Kokkos::fence();\n\n    auto scale_symm_op = KOKKOS_LAMBDA( const int i )\n    {\n        int attype = type( i );\n\n        int memberindex0;\n        int memberindex, globalIndex;\n        double raw_value = 0.0;\n        for ( int groupIndex = 0; groupIndex < numSFGperElem_( attype );\n              ++groupIndex )\n        {\n            memberindex0 = SFGmemberlist_( attype, groupIndex, 0 );\n\n            size_t size = SFGmemberlist_( attype, groupIndex, maxSFperElem_ );\n            for ( size_t k = 0; k < size; ++k )\n            {\n                globalIndex = SF_(\n                    attype, SFGmemberlist_( attype, groupIndex, k ), 14 );\n                memberindex = SFGmemberlist_( attype, groupIndex, k );\n\n                if ( SF_( attype, memberindex0, 1 ) == 2 )\n                    raw_value = G( i, globalIndex );\n                else if ( SF_( attype, memberindex0, 1 ) == 3 )\n                    raw_value =\n                        G( i, globalIndex ) *\n                        pow( 2, ( 1 - SF_( attype, memberindex, 6 ) ) );\n\n                G( i, globalIndex ) =\n                    scale( attype, raw_value, memberindex, SFscaling_ );\n            }\n        }\n    };\n    Kokkos::parallel_for( \"Mode::scaleSymmetryFunctionGroups\", policy,\n                          scale_symm_op );\n    Kokkos::fence();\n}\n\ntemplate <class t_device>\ntemplate <class t_slice_type, class t_slice_G, class t_slice_dEdG,\n          class t_slice_E>\nvoid ModeCabana<t_device>::calculateAtomicNeuralNetworks( \n    t_slice_type type, t_slice_G G, t_slice_dEdG dEdG, t_slice_E E, int N_local )\n{\n    auto NN = d_t_NN( \"Mode::NN\", N_local, numLayers, maxNeurons );\n    auto dfdx = d_t_NN( \"Mode::dfdx\", N_local, numLayers, maxNeurons );\n    auto inner = d_t_NN( \"Mode::inner\", N_local, numHiddenLayers, maxNeurons );\n    auto outer = d_t_NN( \"Mode::outer\", N_local, numHiddenLayers, maxNeurons );\n\n    Kokkos::RangePolicy<exe_space> policy( 0, N_local );\n\n    // Create local copies for lambda\n    auto numSFperElem_ = numSFperElem;\n    auto numNeuronsPerLayer_ = numNeuronsPerLayer;\n    auto numLayers_ = numLayers;\n    auto numHiddenLayers_ = numHiddenLayers;\n    auto AF_ = AF;\n    auto weights_ = weights;\n    auto bias_ = bias;\n\n    auto calc_nn_op = KOKKOS_LAMBDA( const int atomindex )\n    {\n        int attype = type( atomindex );\n        // set input layer of NN\n        int layer_0, layer_lminusone;\n        layer_0 = (int)numSFperElem_( attype );\n\n        for ( int k = 0; k < layer_0; ++k )\n            NN( atomindex, 0, k ) = G( atomindex, k );\n        // forward propagation\n        for ( int l = 1; l < numLayers_; l++ )\n        {\n            if ( l == 1 )\n                layer_lminusone = layer_0;\n            else\n                layer_lminusone = numNeuronsPerLayer_( l - 1 );\n            double dtmp;\n            for ( int i = 0; i < numNeuronsPerLayer_( l ); i++ )\n            {\n                dtmp = 0.0;\n                for ( int j = 0; j < layer_lminusone; j++ )\n                    dtmp += weights_( attype, l - 1, i, j ) *\n                            NN( atomindex, l - 1, j );\n                dtmp += bias_( attype, l - 1, i );\n                if ( AF_( l ) == 0 )\n                {\n                    NN( atomindex, l, i ) = dtmp;\n                    dfdx( atomindex, l, i ) = 1.0;\n                }\n                else if ( AF_( l ) == 1 )\n                {\n                    dtmp = tanh( dtmp );\n                    NN( atomindex, l, i ) = dtmp;\n                    dfdx( atomindex, l, i ) = 1.0 - dtmp * dtmp;\n                }\n            }\n        }\n\n        E( atomindex ) = NN( atomindex, numLayers_ - 1, 0 );\n\n        // derivative of network w.r.t NN inputs\n        for ( int k = 0; k < numNeuronsPerLayer_( 0 ); k++ )\n        {\n            for ( int i = 0; i < numNeuronsPerLayer_( 1 ); i++ )\n                inner( atomindex, 0, i ) =\n                    weights_( attype, 0, i, k ) * dfdx( atomindex, 1, i );\n\n            for ( int l = 1; l < numHiddenLayers_ + 1; l++ )\n            {\n                for ( int i2 = 0; i2 < numNeuronsPerLayer_( l + 1 ); i2++ )\n                {\n                    outer( atomindex, l - 1, i2 ) = 0.0;\n\n                    for ( int i1 = 0; i1 < numNeuronsPerLayer_( l ); i1++ )\n                        outer( atomindex, l - 1, i2 ) +=\n                            weights_( attype, l, i2, i1 ) *\n                            inner( atomindex, l - 1, i1 );\n                    outer( atomindex, l - 1, i2 ) *=\n                        dfdx( atomindex, l + 1, i2 );\n\n                    if ( l < numHiddenLayers_ )\n                        inner( atomindex, l, i2 ) =\n                            outer( atomindex, l - 1, i2 );\n                }\n            }\n            dEdG( atomindex, k ) = outer( atomindex, numHiddenLayers_ - 1, 0 );\n        }\n    };\n    Kokkos::parallel_for( \"Mode::calculateAtomicNeuralNetworks\", policy,\n                          calc_nn_op );\n    Kokkos::fence();\n}\n\ntemplate <class t_device>\ntemplate <class t_slice_x, class t_slice_f, class t_slice_type,\n          class t_slice_dEdG, class t_neigh_list, class t_neigh_parallel,\n          class t_angle_parallel>\nvoid ModeCabana<t_device>::calculateForces( \n    t_slice_x x, t_slice_f f_a, t_slice_type type, t_slice_dEdG dEdG,\n    t_neigh_list neigh_list, int N_local, t_neigh_parallel neigh_op_tag,\n    t_angle_parallel angle_op_tag )\n{\n    double convForce_ = convLength / convEnergy;\n\n    Kokkos::RangePolicy<exe_space> policy( 0, N_local );\n\n    // Create local copies for lambda\n    auto numSFGperElem_ = numSFGperElem;\n    auto SFGmemberlist_ = d_SFGmemberlist;\n    auto SF_ = d_SF;\n    auto SFscaling_ = d_SFscaling;\n    auto maxSFperElem_ = maxSFperElem;\n    auto convLength_ = convLength;\n    auto cutoffType_ = cutoffType;\n    auto cutoffAlpha_ = cutoffAlpha;\n\n    auto calc_radial_force_op = KOKKOS_LAMBDA( const int i, const int j )\n    {\n        double pfcij = 0.0;\n        double pdfcij = 0.0;\n        double rij, r2ij;\n        T_F_FLOAT dxij, dyij, dzij;\n        double eta, rs;\n        int memberindex, globalIndex;\n\n        int attype = type( i );\n\n        for ( int groupIndex = 0; groupIndex < numSFGperElem_( attype );\n              ++groupIndex )\n        {\n            if ( SF_( attype, SFGmemberlist_( attype, groupIndex, 0 ), 1 ) ==\n                 2 )\n            {\n                size_t memberindex0 = SFGmemberlist_( attype, groupIndex, 0 );\n                size_t e1 = SF_( attype, memberindex0, 2 );\n                double rc = SF_( attype, memberindex0, 7 );\n                size_t size =\n                    SFGmemberlist_( attype, groupIndex, maxSFperElem_ );\n\n                size_t nej = type( j );\n                dxij = ( x( i, 0 ) - x( j, 0 ) ) * CFLENGTH * convLength_;\n                dyij = ( x( i, 1 ) - x( j, 1 ) ) * CFLENGTH * convLength_;\n                dzij = ( x( i, 2 ) - x( j, 2 ) ) * CFLENGTH * convLength_;\n                r2ij = dxij * dxij + dyij * dyij + dzij * dzij;\n                rij = sqrt( r2ij );\n                if ( e1 == nej && rij < rc )\n                {\n                    // Energy calculation.\n                    // Calculate cutoff function and derivative.\n                    compute_cutoff( cutoffType_, cutoffAlpha_, pfcij, pdfcij,\n                                    rij, rc, true );\n                    for ( size_t k = 0; k < size; ++k )\n                    {\n                        globalIndex = SF_(\n                            attype, SFGmemberlist_( attype, groupIndex, k ),\n                            14 );\n                        memberindex = SFGmemberlist_( attype, groupIndex, k );\n                        eta = SF_( attype, memberindex, 4 );\n                        rs = SF_( attype, memberindex, 8 );\n                        double pexp = exp( -eta * ( rij - rs ) * ( rij - rs ) );\n                        // Force calculation.\n                        double const p1 =\n                            SFscaling_( attype, memberindex, 6 ) *\n                            ( pdfcij - 2.0 * eta * ( rij - rs ) * pfcij ) *\n                            pexp / rij;\n                        f_a( i, 0 ) -= ( dEdG( i, globalIndex ) *\n                                         ( p1 * dxij ) * CFFORCE * convForce_ );\n                        f_a( i, 1 ) -= ( dEdG( i, globalIndex ) *\n                                         ( p1 * dyij ) * CFFORCE * convForce_ );\n                        f_a( i, 2 ) -= ( dEdG( i, globalIndex ) *\n                                         ( p1 * dzij ) * CFFORCE * convForce_ );\n\n                        f_a( j, 0 ) += ( dEdG( i, globalIndex ) *\n                                         ( p1 * dxij ) * CFFORCE * convForce_ );\n                        f_a( j, 1 ) += ( dEdG( i, globalIndex ) *\n                                         ( p1 * dyij ) * CFFORCE * convForce_ );\n                        f_a( j, 2 ) += ( dEdG( i, globalIndex ) *\n                                         ( p1 * dzij ) * CFFORCE * convForce_ );\n                    }\n                }\n            }\n        }\n    };\n    Cabana::neighbor_parallel_for( policy, calc_radial_force_op, neigh_list,\n                                   Cabana::FirstNeighborsTag(), neigh_op_tag,\n                                   \"Mode::calculateRadialForces\" );\n    Kokkos::fence();\n\n    auto calc_angular_force_op =\n        KOKKOS_LAMBDA( const int i, const int j, const int k )\n    {\n        double pfcij = 0.0;\n        double pdfcij = 0.0;\n        double pfcik, pdfcik, pfcjk, pdfcjk;\n        size_t nej, nek;\n        double rij, r2ij, rik, r2ik, rjk, r2jk;\n        T_F_FLOAT dxij, dyij, dzij, dxik, dyik, dzik, dxjk, dyjk, dzjk;\n        double eta, rs, lambda, zeta;\n        int memberindex, globalIndex;\n\n        int attype = type( i );\n        for ( int groupIndex = 0; groupIndex < numSFGperElem_( attype );\n              ++groupIndex )\n        {\n            if ( SF_( attype, SFGmemberlist_( attype, groupIndex, 0 ), 1 ) ==\n                 3 )\n            {\n                size_t memberindex0 = SFGmemberlist_( attype, groupIndex, 0 );\n                size_t e1 = SF_( attype, memberindex0, 2 );\n                size_t e2 = SF_( attype, memberindex0, 3 );\n                double rc = SF_( attype, memberindex0, 7 );\n                size_t size =\n                    SFGmemberlist_( attype, groupIndex, maxSFperElem_ );\n\n                nej = type( j );\n                dxij = ( x( i, 0 ) - x( j, 0 ) ) * CFLENGTH * convLength_;\n                dyij = ( x( i, 1 ) - x( j, 1 ) ) * CFLENGTH * convLength_;\n                dzij = ( x( i, 2 ) - x( j, 2 ) ) * CFLENGTH * convLength_;\n                r2ij = dxij * dxij + dyij * dyij + dzij * dzij;\n                rij = sqrt( r2ij );\n                if ( ( e1 == nej || e2 == nej ) && rij < rc )\n                {\n                    // Calculate cutoff function and derivative.\n                    compute_cutoff( cutoffType_, cutoffAlpha_, pfcij, pdfcij,\n                                    rij, rc, true );\n\n                    nek = type( k );\n                    if ( ( e1 == nej && e2 == nek ) ||\n                         ( e2 == nej && e1 == nek ) )\n                    {\n                        dxik =\n                            ( x( i, 0 ) - x( k, 0 ) ) * CFLENGTH * convLength_;\n                        dyik =\n                            ( x( i, 1 ) - x( k, 1 ) ) * CFLENGTH * convLength_;\n                        dzik =\n                            ( x( i, 2 ) - x( k, 2 ) ) * CFLENGTH * convLength_;\n                        r2ik = dxik * dxik + dyik * dyik + dzik * dzik;\n                        rik = sqrt( r2ik );\n                        if ( rik < rc )\n                        {\n                            dxjk = dxik - dxij;\n                            dyjk = dyik - dyij;\n                            dzjk = dzik - dzij;\n                            r2jk = dxjk * dxjk + dyjk * dyjk + dzjk * dzjk;\n                            if ( r2jk < rc * rc )\n                            {\n                                // Energy calculation.\n                                compute_cutoff( cutoffType_, cutoffAlpha_,\n                                                pfcik, pdfcik, rik, rc, true );\n                                rjk = sqrt( r2jk );\n\n                                compute_cutoff( cutoffType_, cutoffAlpha_,\n                                                pfcjk, pdfcjk, rjk, rc, true );\n\n                                double const rinvijik = 1.0 / rij / rik;\n                                double const costijk =\n                                    ( dxij * dxik + dyij * dyik +\n                                      dzij * dzik ) *\n                                    rinvijik;\n                                double const pfc = pfcij * pfcik * pfcjk;\n                                double const r2sum = r2ij + r2ik + r2jk;\n                                double const pr1 = pfcik * pfcjk * pdfcij / rij;\n                                double const pr2 = pfcij * pfcjk * pdfcik / rik;\n                                double const pr3 = pfcij * pfcik * pdfcjk / rjk;\n                                double vexp = 0.0, rijs = 0.0, riks = 0.0,\n                                       rjks = 0.0;\n                                for ( size_t l = 0; l < size; ++l )\n                                {\n                                    globalIndex =\n                                        SF_( attype,\n                                              SFGmemberlist_( attype,\n                                                               groupIndex, l ),\n                                              14 );\n                                    memberindex = SFGmemberlist_(\n                                        attype, groupIndex, l );\n                                    rs = SF_( attype, memberindex, 8 );\n                                    eta = SF_( attype, memberindex, 4 );\n                                    lambda = SF_( attype, memberindex, 5 );\n                                    zeta = SF_( attype, memberindex, 6 );\n                                    if ( rs > 0.0 )\n                                    {\n                                        rijs = rij - rs;\n                                        riks = rik - rs;\n                                        rjks = rjk - rs;\n                                        vexp = exp( -eta * ( rijs * rijs +\n                                                             riks * riks +\n                                                             rjks * rjks ) );\n                                    }\n                                    else\n                                        vexp = exp( -eta * r2sum );\n\n                                    double const plambda =\n                                        1.0 + lambda * costijk;\n                                    double fg = vexp;\n                                    if ( plambda <= 0.0 )\n                                        fg = 0.0;\n                                    else\n                                        fg *= pow( plambda, ( zeta - 1.0 ) );\n\n                                    fg *= pow( 2, ( 1 - zeta ) ) *\n                                          SFscaling_( attype, memberindex, 6 );\n                                    double const pfczl = pfc * zeta * lambda;\n                                    double factorDeriv =\n                                        2.0 * eta / zeta / lambda;\n                                    double const p2etapl =\n                                        plambda * factorDeriv;\n                                    double p1, p2, p3;\n                                    if ( rs > 0.0 )\n                                    {\n                                        p1 = fg *\n                                             ( pfczl *\n                                                   ( rinvijik - costijk / r2ij -\n                                                     p2etapl * rijs / rij ) +\n                                               pr1 * plambda );\n                                        p2 = fg *\n                                             ( pfczl *\n                                                   ( rinvijik - costijk / r2ik -\n                                                     p2etapl * riks / rik ) +\n                                               pr2 * plambda );\n                                        p3 =\n                                            fg *\n                                            ( pfczl * ( rinvijik +\n                                                        p2etapl * rjks / rjk ) -\n                                              pr3 * plambda );\n                                    }\n                                    else\n                                    {\n                                        p1 = fg * ( pfczl * ( rinvijik -\n                                                              costijk / r2ij -\n                                                              p2etapl ) +\n                                                    pr1 * plambda );\n                                        p2 = fg * ( pfczl * ( rinvijik -\n                                                              costijk / r2ik -\n                                                              p2etapl ) +\n                                                    pr2 * plambda );\n                                        p3 = fg *\n                                             ( pfczl * ( rinvijik + p2etapl ) -\n                                               pr3 * plambda );\n                                    }\n                                    f_a( i, 0 ) -= ( dEdG( i, globalIndex ) *\n                                                     ( p1 * dxij + p2 * dxik ) *\n                                                     CFFORCE * convForce_ );\n                                    f_a( i, 1 ) -= ( dEdG( i, globalIndex ) *\n                                                     ( p1 * dyij + p2 * dyik ) *\n                                                     CFFORCE * convForce_ );\n                                    f_a( i, 2 ) -= ( dEdG( i, globalIndex ) *\n                                                     ( p1 * dzij + p2 * dzik ) *\n                                                     CFFORCE * convForce_ );\n\n                                    f_a( j, 0 ) += ( dEdG( i, globalIndex ) *\n                                                     ( p1 * dxij + p3 * dxjk ) *\n                                                     CFFORCE * convForce_ );\n                                    f_a( j, 1 ) += ( dEdG( i, globalIndex ) *\n                                                     ( p1 * dyij + p3 * dyjk ) *\n                                                     CFFORCE * convForce_ );\n                                    f_a( j, 2 ) += ( dEdG( i, globalIndex ) *\n                                                     ( p1 * dzij + p3 * dzjk ) *\n                                                     CFFORCE * convForce_ );\n\n                                    f_a( k, 0 ) += ( dEdG( i, globalIndex ) *\n                                                     ( p2 * dxik - p3 * dxjk ) *\n                                                     CFFORCE * convForce_ );\n                                    f_a( k, 1 ) += ( dEdG( i, globalIndex ) *\n                                                     ( p2 * dyik - p3 * dyjk ) *\n                                                     CFFORCE * convForce_ );\n                                    f_a( k, 2 ) += ( dEdG( i, globalIndex ) *\n                                                     ( p2 * dzik - p3 * dzjk ) *\n                                                     CFFORCE * convForce_ );\n                                } // l\n                            }     // rjk <= rc\n                        }         // rik <= rc\n                    }             // elem\n                }                 // rij <= rc\n            }\n        }\n    };\n    Cabana::neighbor_parallel_for( policy, calc_angular_force_op, neigh_list,\n                                   Cabana::SecondNeighborsTag(), angle_op_tag,\n                                   \"Mode::calculateAngularForces\" );\n    Kokkos::fence();\n\n    return;\n}\n\n}\n"
  },
  {
    "path": "src/libnnpif/CabanaMD/typesCabana.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n// Copyright (C) 2020 Saaketh Desai and Sam Reeve\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef TYPESCABANAMD_H\n#define TYPESCABANAMD_H\n\nconstexpr double CFLENGTH = 1.889726;\nconstexpr double CFENERGY = 0.036749;\nconstexpr double CFFORCE = CFLENGTH / CFENERGY;\n\n// Extracted from SymmetryFunction class\nenum ScalingType {\n    ST_NONE,\n    ST_SCALE,\n    ST_CENTER,\n    ST_SCALECENTER,\n    ST_SCALESIGMA\n};\n\n#endif // TYPES_H\n"
  },
  {
    "path": "src/libnnpif/LAMMPS/InterfaceLammps.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef N2P2_NO_MPI\n#include <mpi.h>\n#include \"mpi-extra.h\"\n#endif\n#include \"InterfaceLammps.h\"\n#include \"Atom.h\"\n#include \"Element.h\"\n#include \"utility.h\"\n#include <Eigen/Dense>\n#include <cmath>\n#include <string>\n#include <iostream>\n#include <limits>\n//#include <stdexcept>\n\n#define TOLCUTOFF 1.0E-2\n\nusing namespace std;\nusing namespace nnp;\nusing namespace Eigen;\n\nInterfaceLammps::InterfaceLammps() : myRank             (0    ),\n                                     initialized        (false),\n                                     hasGlobalStructure (false),\n                                     showew             (true ),\n                                     resetew            (false),\n                                     showewsum          (0    ),\n                                     maxew              (0    ),\n                                     cflength           (1.0  ),\n                                     cfenergy           (1.0  ),\n                                     isElecDone         (false)\n{\n}\n\nvoid InterfaceLammps::initialize(char const* const& directory,\n                                 char const* const& emap,\n                                 bool               showew,\n                                 bool               resetew,\n                                 int                showewsum,\n                                 int                maxew,\n                                 double             cflength,\n                                 double             cfenergy,\n                                 double             lammpsCutoff,\n                                 int                lammpsNtypes,\n                                 int                myRank)\n{\n    this->emap = emap;\n    this->showew = showew;\n    this->resetew = resetew;\n    this->showewsum = showewsum;\n    this->maxew = maxew;\n    this->cflength = cflength;\n    this->cfenergy = cfenergy;\n    this->myRank = myRank;\n    log.writeToStdout = false;\n    string dir(directory);\n    char const separator = '/';\n    if (dir.back() != separator) dir += separator;\n    Mode::initialize();\n    loadSettingsFile(dir + \"input.nn\");\n    setupGeneric(dir);\n    setupSymmetryFunctionScaling(dir + \"scaling.data\");\n    bool collectStatistics = false;\n    bool collectExtrapolationWarnings = false;\n    bool writeExtrapolationWarnings = false;\n    bool stopOnExtrapolationWarnings = false;\n    if (showew == true || showewsum > 0 || maxew >= 0)\n    {\n        collectExtrapolationWarnings = true;\n    }\n    setupSymmetryFunctionStatistics(collectStatistics,\n                                    collectExtrapolationWarnings,\n                                    writeExtrapolationWarnings,\n                                    stopOnExtrapolationWarnings);\n    setupNeuralNetworkWeights(dir);\n\n    log << \"\\n\";\n    log << \"*** SETUP: LAMMPS INTERFACE *************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    if (showew)\n    {\n        log << \"Individual extrapolation warnings will be shown.\\n\";\n    }\n    else\n    {\n        log << \"Individual extrapolation warnings will not be shown.\\n\";\n    }\n\n    if (showewsum != 0)\n    {\n        log << strpr(\"Extrapolation warning summary will be shown every %d\"\n                     \" timesteps.\\n\", showewsum);\n    }\n    else\n    {\n        log << \"Extrapolation warning summary will not be shown.\\n\";\n    }\n\n    if (maxew != 0)\n    {\n        log << strpr(\"The simulation will be stopped when %d extrapolation\"\n                     \" warnings are exceeded.\\n\", maxew);\n    }\n    else\n    {\n        log << \"No extrapolation warning limit set.\\n\";\n    }\n\n    if (resetew)\n    {\n        log << \"Extrapolation warning counter is reset every time step.\\n\";\n    }\n    else\n    {\n        log << \"Extrapolation warnings are accumulated over all time steps.\\n\";\n    }\n\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    log << \"CAUTION: If the LAMMPS unit system differs from the one used\\n\";\n    log << \"         during NN training, appropriate conversion factors\\n\";\n    log << \"         must be provided (see keywords cflength and cfenergy).\\n\";\n    log << \"\\n\";\n    log << strpr(\"Length unit conversion factor: %24.16E\\n\", cflength);\n    log << strpr(\"Energy unit conversion factor: %24.16E\\n\", cfenergy);\n    double sfCutoff = getMaxCutoffRadius();\n    log << \"\\n\";\n    log << \"Checking consistency of cutoff radii (in LAMMPS units):\\n\";\n    log << strpr(\"LAMMPS Cutoff (via pair_coeff)  : %11.3E\\n\", lammpsCutoff);\n    log << strpr(\"Maximum symmetry function cutoff: %11.3E\\n\", sfCutoff);\n    if (lammpsCutoff < sfCutoff)\n    {\n        throw runtime_error(\"ERROR: LAMMPS cutoff via pair_coeff keyword is\"\n                            \" smaller than maximum symmetry function\"\n                            \" cutoff.\\n\");\n    }\n    else if (fabs(sfCutoff - lammpsCutoff) / lammpsCutoff > TOLCUTOFF)\n    {\n        log << \"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\\n\";\n        log << \"WARNING: Potential length units mismatch!\\n\";\n        log << \"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\\n\";\n    }\n    else\n    {\n        log << \"Cutoff radii are consistent.\\n\";\n    }\n\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    log << \"Element mapping string from LAMMPS to n2p2: \\\"\"\n           + this->emap + \"\\\"\\n\";\n    // Create default element mapping.\n    if (this->emap == \"\")\n    {\n        if (elementMap.size() != (size_t)lammpsNtypes)\n        {\n            throw runtime_error(strpr(\"ERROR: No element mapping given and \"\n                                      \"number of LAMMPS atom types (%d) and \"\n                                      \"NNP elements (%zu) does not match.\\n\",\n                                      lammpsNtypes, elementMap.size()));\n        }\n        log << \"Element mapping string empty, creating default mapping.\\n\";\n        for (int i = 0; i < lammpsNtypes; ++i)\n        {\n            mapTypeToElement[i + 1] = i;\n            mapElementToType[i] = i + 1;\n        }\n    }\n    // Read element mapping from pair_style argument.\n    else\n    {\n        vector<string> emapSplit = split(reduce(trim(this->emap), \" \\t\", \"\"),\n                                         ',');\n        if (elementMap.size() < emapSplit.size())\n        {\n            throw runtime_error(strpr(\"ERROR: Element mapping is inconsistent,\"\n                                      \" NNP elements: %zu,\"\n                                      \" emap elements: %zu.\\n\",\n                                      elementMap.size(),\n                                      emapSplit.size()));\n        }\n        for (string s : emapSplit)\n        {\n            vector<string> typeString = split(s, ':');\n            if (typeString.size() != 2)\n            {\n                throw runtime_error(strpr(\"ERROR: Invalid element mapping \"\n                                          \"string: \\\"%s\\\".\\n\", s.c_str()));\n            }\n            int t = stoi(typeString.at(0));\n            if (t > lammpsNtypes)\n            {\n                throw runtime_error(strpr(\"ERROR: LAMMPS type \\\"%d\\\" not \"\n                                          \"present, there are only %d types \"\n                                          \"defined.\\n\", t, lammpsNtypes));\n            }\n            size_t e = elementMap[typeString.at(1)];\n            mapTypeToElement[t] = e;\n            mapElementToType[e] = t;\n        }\n    }\n    log << \"\\n\";\n    log << \"CAUTION: Please ensure that this mapping between LAMMPS\\n\";\n    log << \"         atom types and NNP elements is consistent:\\n\";\n    log << \"\\n\";\n    log << \"---------------------------\\n\";\n    log << \"LAMMPS type  |  NNP element\\n\";\n    log << \"---------------------------\\n\";\n    for (int i = 1; i <= lammpsNtypes; ++i)\n    {\n        if (mapTypeToElement.find(i) != mapTypeToElement.end())\n        {\n            size_t e = mapTypeToElement.at(i);\n            log << strpr(\"%11d <-> %2s (%3zu)\\n\",\n                         i,\n                         elementMap[e].c_str(),\n                         elementMap.atomicNumber(e));\n            ignoreType[i] = false;\n        }\n        else\n        {\n            log << strpr(\"%11d <-> --\\n\", i);\n            ignoreType[i] = true;\n\n        }\n    }\n    log << \"---------------------------\\n\";\n    log << \"\\n\";\n    log << \"NNP setup for LAMMPS completed.\\n\";\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    structure.setElementMap(elementMap);\n\n    initialized = true;\n}\n\nvoid InterfaceLammps::setGlobalStructureStatus(bool const status)\n{\n    hasGlobalStructure = status;\n}\n\nbool InterfaceLammps::getGlobalStructureStatus()\n{\n    return hasGlobalStructure;\n}\n\nvoid InterfaceLammps::setLocalAtoms(int              numAtomsLocal,\n                                    int const* const atomType)\n{\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        structure.numAtomsPerElement[i] = 0;\n    }\n    structure.index                          = myRank;\n    structure.numAtoms                       = 0;\n    structure.hasNeighborList                = false;\n    structure.hasSymmetryFunctions           = false;\n    structure.hasSymmetryFunctionDerivatives = false;\n    structure.energy                         = 0.0;\n    structure.atoms.clear();\n    indexMap.clear();\n    structure.atoms.reserve(numAtomsLocal);\n    indexMap.resize(numAtomsLocal, numeric_limits<size_t>::max());\n    for (int i = 0; i < numAtomsLocal; i++)\n    {\n        if (ignoreType[atomType[i]]) continue;\n        indexMap.at(i) = structure.numAtoms;\n        structure.numAtoms++;\n        structure.atoms.push_back(Atom());\n        Atom& a = structure.atoms.back();\n        a.index                          = i;\n        a.indexStructure                 = myRank;\n        a.element                        = mapTypeToElement[atomType[i]];\n        a.numNeighbors                   = 0;\n        a.hasSymmetryFunctions           = false;\n        a.hasSymmetryFunctionDerivatives = false;\n        a.neighbors.clear();\n        a.numNeighborsPerElement.clear();\n        a.numNeighborsPerElement.resize(numElements, 0);\n        structure.numAtomsPerElement[a.element]++;\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::setLocalAtomPositions(double const* const* const atomPos)\n{\n    for (size_t i = 0; i < structure.numAtoms; ++i)\n    {\n        Atom& a = structure.atoms.at(i);\n        a.r[0] = atomPos[i][0] * cflength;\n        a.r[1] = atomPos[i][1] * cflength;\n        a.r[2] = atomPos[i][2] * cflength;\n        if (normalize)\n        {\n            a.r[0] *= convLength;\n            a.r[1] *= convLength;\n            a.r[2] *= convLength;\n        }\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::setLocalTags(int const* const atomTag)\n{\n    for (size_t i = 0; i < structure.atoms.size(); i++)\n    {\n        // Implicit conversion from int to int64_t!\n        structure.atoms.at(i).tag = atomTag[i];\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::setLocalTags(int64_t const* const atomTag)\n{\n    for (size_t i = 0; i < structure.atoms.size(); i++)\n    {\n        structure.atoms.at(i).tag = atomTag[i];\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::setBoxVectors(double const* boxlo,\n                                    double const* boxhi,\n                                    double const  xy,\n                                    double const  xz,\n                                    double const  yz)\n{\n    structure.isPeriodic = true;\n\n    // Box vector a\n    structure.box[0][0] = boxhi[0] - boxlo[0];\n    structure.box[0][1] = 0;\n    structure.box[0][2] = 0;\n\n    // Box vector b\n    structure.box[1][0] = xy;\n    structure.box[1][1] = boxhi[1] - boxlo[1];\n    structure.box[1][2] = 0;\n\n    // Box vector c\n    structure.box[2][0] = xz;\n    structure.box[2][1] = yz;\n    structure.box[2][2] = boxhi[2] - boxlo[2];\n\n    // LAMMPS may set triclinic = 1 even if the following condition is not\n    // satisfied.\n    if (structure.box[0][1] > numeric_limits<double>::min() ||\n        structure.box[0][2] > numeric_limits<double>::min() ||\n        structure.box[1][0] > numeric_limits<double>::min() ||\n        structure.box[1][2] > numeric_limits<double>::min() ||\n        structure.box[2][0] > numeric_limits<double>::min() ||\n        structure.box[2][1] > numeric_limits<double>::min())\n    {\n        structure.isTriclinic = true;\n    }\n\n    for(size_t i = 0; i < 3; ++i)\n    {\n        structure.box[i] *= cflength;\n        if (normalize) structure.box[i] *= convLength;\n    }\n\n    structure.calculateInverseBox();\n    structure.calculateVolume();\n    //cout << \"Box vectors: \\n\";\n    //for(size_t i = 0; i < 3; ++i)\n    //{\n    //    for(size_t j = 0; j < 3; ++j)\n    //    {\n    //        cout << structure.box[i][j] / convLength << \" \";\n    //    }\n    //    cout << endl;\n    //}\n\n}\n\nvoid InterfaceLammps::allocateNeighborlists(int const* const numneigh)\n{\n    for(size_t i = 0; i < structure.numAtoms; ++i)\n    {\n        auto& a = structure.atoms.at(i);\n        a.neighbors.reserve(numneigh[i]);\n    }\n}\n\nvoid InterfaceLammps::addNeighbor(int     i,\n                                  int     j,\n                                  int64_t tag,\n                                  int     type,\n                                  double  dx,\n                                  double  dy,\n                                  double  dz,\n                                  double  d2)\n{\n    if (ignoreType[type] ||\n        indexMap.at(i) == numeric_limits<size_t>::max()) return;\n    Atom& a = structure.atoms[indexMap.at(i)];\n    a.numNeighbors++;\n    a.neighbors.push_back(Atom::Neighbor());\n    a.numNeighborsPerElement.at(mapTypeToElement[type])++;\n    Atom::Neighbor& n = a.neighbors.back();\n\n    n.index = j;\n    n.tag = tag;\n    n.element = mapTypeToElement[type];\n    n.dr[0]   = dx * cflength;\n    n.dr[1]   = dy * cflength;\n    n.dr[2]   = dz * cflength;\n    n.d       = sqrt(d2) * cflength;\n    if (normalize)\n    {\n        n.dr *= convLength;\n        n.d  *= convLength;\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::finalizeNeighborList()\n{\n    if (nnpType == NNPType::HDNNP_4G)\n    {\n        for (auto& a : structure.atoms)\n        {\n            a.hasNeighborList = true;\n        }\n        // Ewald summation cut-off depends on box vectors.\n        structure.calculateMaxCutoffRadiusOverall(\n                                            ewaldSetup,\n                                            screeningFunction.getOuter(),\n                                            maxCutoffRadius);\n        structure.sortNeighborList();\n        structure.setupNeighborCutoffMap(cutoffs);\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::process() //TODO : add comments\n{\n#ifdef N2P2_NO_SF_GROUPS\n    calculateSymmetryFunctions(structure, true);\n#else\n    calculateSymmetryFunctionGroups(structure, true);\n#endif\n    if (nnpType == NNPType::HDNNP_2G)\n    {\n        calculateAtomicNeuralNetworks(structure, true);\n        calculateEnergy(structure);\n        if (normalize)\n        {\n            structure.energy = physicalEnergy(structure, false);\n        }\n        addEnergyOffset(structure, false);\n    }\n    else if (nnpType == NNPType::HDNNP_4G)\n    {\n        if (!isElecDone)\n        {\n            calculateAtomicNeuralNetworks(structure, true, \"elec\");\n            isElecDone = true;\n        } else\n        {\n            calculateAtomicNeuralNetworks(structure, true, \"short\");\n            isElecDone = false;\n            calculateEnergy(structure);\n            if (normalize)\n            {\n                structure.energy = physicalEnergy(structure, false);\n            }\n            addEnergyOffset(structure, false);\n        }\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::processDevelop()\n{\n#ifdef N2P2_NO_SF_GROUPS\n    calculateSymmetryFunctions(structure, true);\n#else\n    calculateSymmetryFunctionGroups(structure, true);\n#endif\n    calculateAtomicNeuralNetworks(structure, true, \"\");\n    if (nnpType == NNPType::HDNNP_4G)\n    {\n        chargeEquilibration(structure, true);\n        calculateAtomicNeuralNetworks(structure, true, \"short\");\n        ewaldSetup.logEwaldCutoffs(log, convLength * cflength);\n    }\n    calculateEnergy(structure);\n    if (nnpType == NNPType::HDNNP_4G ||\n        nnpType == NNPType::HDNNP_Q) calculateCharge(structure);\n    if (normalize)\n    {\n        structure.energy = physicalEnergy(structure, false);\n    }\n    addEnergyOffset(structure, false);\n\n    return;\n}\n\ndouble InterfaceLammps::getMaxCutoffRadius() const\n{\n    if (normalize) return maxCutoffRadius / convLength / cflength;\n    else return maxCutoffRadius / cflength;\n}\n\ndouble InterfaceLammps::getMaxCutoffRadiusOverall()\n{\n    double cutoff = 0;\n    if(nnpType == NNPType::HDNNP_4G)\n    {\n        structure.calculateMaxCutoffRadiusOverall(\n                                        ewaldSetup,\n                                        screeningFunction.getOuter(),\n                                        maxCutoffRadius);\n        cutoff = structure.maxCutoffRadiusOverall / cflength;\n        if (normalize) cutoff /= convLength;\n    }\n    else cutoff = getMaxCutoffRadius();\n    return cutoff;\n}\n\ndouble InterfaceLammps::getEnergy() const\n{\n    return structure.energy / cfenergy;\n}\n\ndouble InterfaceLammps::getAtomicEnergy(int index) const\n{\n    Atom const& a = structure.atoms.at(index);\n    Element const& e = elements.at(a.element);\n\n    if (normalize)\n    {\n        return (physical(\"energy\", a.energy)\n                + meanEnergy\n                + e.getAtomicEnergyOffset()) / cfenergy;\n    }\n    else\n    {\n        return (a.energy + e.getAtomicEnergyOffset()) / cfenergy;\n    }\n}\n\nvoid InterfaceLammps::getQEqParams(double* const& atomChi, double* const& atomJ,\n                     double* const& sigmaSqrtPi, double *const *const& gammaSqrt2, double& qRef) const\n{\n    for (size_t i = 0; i < structure.atoms.size(); ++i) {\n        Atom const& a = structure.atoms.at(i);\n        size_t const ia = a.index;\n        atomChi[ia] = a.chi;\n    }\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        double const iSigma = elements.at(i).getQsigma();\n        atomJ[i] = elements.at(i).getHardness();\n        sigmaSqrtPi[i] = sqrt(M_PI) * iSigma;\n        for (size_t j = 0; j < numElements; j++)\n        {\n            double const jSigma = elements.at(j).getQsigma();\n            gammaSqrt2[i][j] = sqrt(2.0 * (iSigma * iSigma + jSigma * jSigma));\n        }\n    }\n    qRef = structure.chargeRef;\n}\n\nvoid InterfaceLammps::getdEdQ(double* const& dEtotdQ) const\n{\n    Atom const* ai = NULL;\n    for (size_t i = 0; i < structure.atoms.size(); ++i)\n    {\n        ai = &(structure.atoms.at(i));\n        size_t const ia = ai->index;\n        dEtotdQ[ia] += ai->dEdG.back();\n    }\n}\n\nvoid InterfaceLammps::getdChidxyz(int ind,\n        double *const &dChidx, double *const &dChidy, double *const &dChidz) const\n{\n    Atom const &ai = structure.atoms.at(ind);\n\n    for (size_t j = 0; j < structure.numAtoms; ++j) {\n        Atom const &aj = structure.atoms.at(j);\n#ifndef NNP_FULL_SFD_MEMORY\n        vector <vector<size_t>> const &tableFull\n                = elements.at(aj.element).getSymmetryFunctionTable();\n#endif\n        Vec3D dChi;\n        // need to add this case because the loop over the neighbors\n        // does not include the contribution dChi_i/dr_i.\n        if (ai.index == j) {\n            for (size_t k = 0; k < aj.numSymmetryFunctions; ++k) {\n                dChi += aj.dChidG.at(k) * aj.dGdr.at(k);\n            }\n        }\n\n        for (auto const &n : aj.neighbors) {\n            if (n.d > maxCutoffRadius) break;\n            if (n.index == ai.index) {\n#ifndef NNP_FULL_SFD_MEMORY\n                vector <size_t> const &table = tableFull.at(n.element);\n                for (size_t k = 0; k < n.dGdr.size(); ++k) {\n                    dChi += aj.dChidG.at(table.at(k)) * n.dGdr.at(k);\n                }\n#else\n                for (size_t k = 0; k < aj.numSymmetryFunctions; ++k)\n                        {\n                            dChi += aj.dChidG.at(k) * n.dGdr.at(k);\n                        }\n#endif\n                }\n            }\n        dChidx[j] = dChi[0];\n        dChidy[j] = dChi[1];\n        dChidz[j] = dChi[2];\n        }\n}\n\nvoid InterfaceLammps::addCharge(int index, double Q)\n{\n    Atom& a = structure.atoms.at(index);\n    a.charge = Q;\n    //log << strpr(\"Atom %5zu (%2s) q: %24.16E\\n\",\n    //             a.tag, elementMap[a.element].c_str(), a.charge);\n}\n\nvoid InterfaceLammps::getScreeningInfo(double* const& screenInfo) const\n{\n    screenInfo[0] = (double) screeningFunction.getCoreFunctionType(); //TODO: this does not work atm\n    screenInfo[1] = screeningFunction.getInner();\n    screenInfo[2] = screeningFunction.getOuter();\n    screenInfo[3] = 1.0 / (screenInfo[2] - screenInfo[1]); // scale\n}\n\ndouble InterfaceLammps::getEwaldPrec() const\n{\n    return Mode::getEwaldPrecision();\n}\n\nvoid InterfaceLammps::setElecDone()\n{\n    if (isElecDone) isElecDone = false;\n}\n\nvoid InterfaceLammps::addElectrostaticEnergy(double eElec)\n{\n    structure.energyElec = eElec;\n}\n\nvoid InterfaceLammps::getForces(double* const* const& atomF) const {\n    double const cfforce = cflength / cfenergy;\n    double convForce = 1.0;\n    if (normalize) {\n        convForce = convLength / convEnergy;\n    }\n\n    // Loop over all local atoms. Neural network and Symmetry function\n    // derivatives are saved in the dEdG arrays of atoms and dGdr arrays of\n    // atoms and their neighbors. These are now summed up to the force\n    // contributions of local and ghost atoms.\n    Atom const *a = NULL;\n\n    for (size_t i = 0; i < structure.atoms.size(); ++i) {\n        // Set pointer to atom.\n        a = &(structure.atoms.at(i));\n\n#ifndef NNP_FULL_SFD_MEMORY\n        vector <vector<size_t>> const &tableFull\n                = elements.at(a->element).getSymmetryFunctionTable();\n#endif\n        // Loop over all neighbor atoms. Some are local, some are ghost atoms.\n        for (vector<Atom::Neighbor>::const_iterator n = a->neighbors.begin();\n             n != a->neighbors.end(); ++n) {\n            // Temporarily save the neighbor index. Note: this is the index for\n            // the LAMMPS force array.\n            size_t const in = n->index;\n            // Now loop over all symmetry functions and add force contributions\n            // (local + ghost atoms).\n#ifndef NNP_FULL_SFD_MEMORY\n            vector <size_t> const &table = tableFull.at(n->element);\n            for (size_t s = 0; s < n->dGdr.size(); ++s)\n            {\n                double const dEdG = a->dEdG[table.at(s)] * cfforce * convForce;\n#else\n            for (size_t s = 0; s < a->numSymmetryFunctions; ++s)\n            {\n                double const dEdG = a->dEdG[s] * cfforce * convForce;\n#endif\n                double const *const dGdr = n->dGdr[s].r;\n                atomF[in][0] -= dEdG * dGdr[0];\n                atomF[in][1] -= dEdG * dGdr[1];\n                atomF[in][2] -= dEdG * dGdr[2];\n            }\n        }\n        // Temporarily save the atom index. Note: this is the index for\n        // the LAMMPS force array.\n        size_t const ia = a->index;\n        // Loop over all symmetry functions and add force contributions (local\n        // atoms).\n        for (size_t s = 0; s < a->numSymmetryFunctions; ++s)\n        {\n            double const dEdG = a->dEdG[s] * cfforce * convForce;\n            double const *const dGdr = a->dGdr[s].r;\n            atomF[ia][0] -= dEdG * dGdr[0];\n            atomF[ia][1] -= dEdG * dGdr[1];\n            atomF[ia][2] -= dEdG * dGdr[2];\n        }\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::getForcesDevelop(double* const* const& atomF) const\n{\n    double const cfforce = cflength / cfenergy;\n    double convForce = 1.0;\n    if (normalize)\n    {\n        convForce = convLength / convEnergy;\n    }\n\n    // Loop over all local atoms. Neural network and Symmetry function\n    // derivatives are saved in the dEdG arrays of atoms and dGdr arrays of\n    // atoms and their neighbors. These are now summed up to the force\n    // contributions of local and ghost atoms.\n    for (auto const& a : structure.atoms)\n    {\n        size_t const ia = a.index;\n        Vec3D selfForce = a.calculateSelfForceShort();\n        selfForce *= cfforce * convForce;\n        // TODO: ia is not the right index when some atom types are excluded / ignored\n        //       (see use of indexmap)\n        add3DVecToArray(atomF[ia], selfForce);\n\n#ifndef N2P2_FULL_SFD_MEMORY\n        vector<vector<size_t> > const& tableFull\n            = elements.at(a.element).getSymmetryFunctionTable();\n#endif\n        // Loop over all neighbor atoms. Some are local, some are ghost atoms.\n\n        //for (auto const& n : a.neighbors)\n        size_t const numNeighbors = a.getStoredMinNumNeighbors(maxCutoffRadius);\n#ifdef _OPENMP\n        #pragma omp parallel for\n#endif\n        for (size_t k = 0; k < numNeighbors; ++k)\n        {\n            Atom::Neighbor const& n = a.neighbors[k];\n            // Temporarily save the neighbor index. Note: this is the index for\n            // the LAMMPS force array.\n            size_t const in = n.index;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n            Vec3D pairForce = a.calculatePairForceShort(n, &tableFull);\n#else\n            Vec3D pairForce = a.calculatePairForceShort(n);\n#endif\n            pairForce *= cfforce * convForce;\n            add3DVecToArray(atomF[in], pairForce);\n        }\n    }\n\n    // Comment: Will not work with multiple MPI tasks but this routine will\n    //          probably be obsolete when Emir's solution is finished.\n    if (nnpType == NNPType::HDNNP_4G)\n    {\n        Structure const& s = structure;\n        VectorXd lambdaTotal = s.calculateForceLambdaTotal();\n\n#ifdef _OPENMP\n        #pragma omp parallel for\n#endif\n        // OpenMP 4.0 doesn't support range based loops\n        for (size_t i = 0; i < s.numAtoms; ++i)\n        {\n            auto const& ai = s.atoms[i];\n            add3DVecToArray(atomF[i], -ai.pEelecpr * cfforce * convForce);\n\n            for (auto const& aj : s.atoms)\n            {\n                size_t const j = aj.index;\n\n#ifndef N2P2_FULL_SFD_MEMORY\n                vector<vector<size_t> > const& tableFull\n                        = elements.at(aj.element).getSymmetryFunctionTable();\n                Vec3D dChidr = aj.calculateDChidr(ai.index,\n                                                  maxCutoffRadius,\n                                                  &tableFull);\n#else\n                Vec3D dChidr = aj.calculateDChidr(ai.index,\n                                                  maxCutoffRadius);\n#endif\n\n                Vec3D remainingForce = -lambdaTotal(j) * (ai.dAdrQ[j] + dChidr);\n                add3DVecToArray(atomF[i], remainingForce * cfforce * convForce);\n\n            }\n        }\n    }\n    return;\n}\n\nvoid InterfaceLammps::getForcesChi(double const* const&  lambda,\n                                   double* const* const& atomF) const {\n    double const cfforce = cflength / cfenergy;\n    double convForce = 1.0;\n    if (normalize) {\n        convForce = convLength / convEnergy;\n    }\n\n    // Loop over all local atoms. Neural network and Symmetry function\n    // derivatives are saved in the dEdG arrays of atoms and dGdr arrays of\n    // atoms and their neighbors. These are now summed up to the force\n    // contributions of local and ghost atoms.\n    Atom const *a = NULL;\n\n    for (size_t i = 0; i < structure.atoms.size(); ++i) {\n        // Set pointer to atom.\n        a = &(structure.atoms.at(i));\n\n        // Temporarily save the atom index. Note: this is the index for\n        // the LAMMPS force array.\n        size_t const ia = a->index;\n        // Also save tag - 1 which is the correct position in lambda array.\n        size_t const ta = a->tag - 1;\n\n#ifndef NNP_FULL_SFD_MEMORY\n        vector <vector<size_t>> const &tableFull\n                = elements.at(a->element).getSymmetryFunctionTable();\n#endif\n        // Loop over all neighbor atoms. Some are local, some are ghost atoms.\n        for (vector<Atom::Neighbor>::const_iterator n = a->neighbors.begin();\n             n != a->neighbors.end(); ++n) {\n            // Temporarily save the neighbor index. Note: this is the index for\n            // the LAMMPS force array.\n            size_t const in = n->index;\n            // Also save tag - 1 which is the correct position in lambda array.\n            size_t const tn = n->tag - 1;\n            //std::cout << \"Chi : \" << a->chi << '\\t' << \"nei :\" << n->index << '\\n';\n            // Now loop over all symmetry functions and add force contributions\n            // (local + ghost atoms).\n#ifndef NNP_FULL_SFD_MEMORY\n            vector <size_t> const &table = tableFull.at(n->element);\n            for (size_t s = 0; s < n->dGdr.size(); ++s)\n            {\n                double const dChidG = a->dChidG[table.at(s)]\n                                    * cfforce * convForce;\n#else\n            for (size_t s = 0; s < a->numSymmetryFunctions; ++s)\n            {\n                double const dChidG = a->dChidG[s] * cfforce * convForce;\n#endif\n                double const *const dGdr = n->dGdr[s].r;\n                atomF[in][0] -= lambda[ta] * dChidG * dGdr[0];\n                atomF[in][1] -= lambda[ta] * dChidG * dGdr[1];\n                atomF[in][2] -= lambda[ta] * dChidG * dGdr[2];\n            }\n        }\n        // Loop over all symmetry functions and add force contributions (local\n        // atoms).\n        for (size_t s = 0; s < a->numSymmetryFunctions; ++s)\n        {\n            double const dChidG = a->dChidG[s] * cfforce * convForce;\n            double const *const dGdr = a->dGdr[s].r;\n            atomF[ia][0] -= lambda[ta] * dChidG * dGdr[0];\n            atomF[ia][1] -= lambda[ta] * dChidG * dGdr[1];\n            atomF[ia][2] -= lambda[ta] * dChidG * dGdr[2];\n        }\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::getCharges(double* const& atomQ) const\n{\n    if (nnpType != NNPType::HDNNP_4G) return;\n    if (!atomQ) return;\n\n    Structure const& s = structure;\n#ifdef _OPENMP\n    #pragma omp parallel for\n#endif\n    for (size_t i = 0; i < s.numAtoms; ++i)\n    {\n        atomQ[i] = s.atoms[i].charge;\n    }\n\n    return;\n}\n\nlong InterfaceLammps::getEWBufferSize() const\n{\n    long bs = 0;\n#ifndef N2P2_NO_MPI\n    int ss = 0; // size_t size.\n    int ds = 0; // double size.\n    int cs = 0; // char size.\n    MPI_Pack_size(1, MPI_SIZE_T, MPI_COMM_WORLD, &ss);\n    MPI_Pack_size(1, MPI_DOUBLE, MPI_COMM_WORLD, &ds);\n    MPI_Pack_size(1, MPI_CHAR  , MPI_COMM_WORLD, &cs);\n\n    for (vector<Element>::const_iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        map<size_t, SymFncStatistics::Container> const& m\n            = it->statistics.data;\n        bs += ss; // n.\n        for (map<size_t, SymFncStatistics::Container>::const_iterator\n             it2 = m.begin(); it2 != m.end(); ++it2)\n        {\n            bs += ss; // index   (it2->first).\n            bs += ss; // countEW (it2->second.countEW).\n            bs += ss; // type    (it2->second.type).\n            bs += ds; // Gmin    (it2->second.Gmin).\n            bs += ds; // Gmax    (it2->second.Gmax).\n            bs += ss; // element.length() (it2->second.element.length()).\n            bs += (it2->second.element.length() + 1) * cs; // element.\n            size_t countEW = it2->second.countEW;\n            bs += countEW * ss; // indexStructureEW.\n            bs += countEW * ss; // indexAtomEW.\n            bs += countEW * ds; // valueEW.\n        }\n    }\n#endif\n    return bs;\n}\n\nvoid InterfaceLammps::fillEWBuffer(char* const& buf, int bs) const\n{\n#ifndef N2P2_NO_MPI\n    int p = 0;\n    for (vector<Element>::const_iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        map<size_t, SymFncStatistics::Container> const& m =\n            it->statistics.data;\n        size_t n = m.size();\n        MPI_Pack((void *) &(n), 1, MPI_SIZE_T, buf, bs, &p, MPI_COMM_WORLD);\n        for (map<size_t, SymFncStatistics::Container>::const_iterator\n             it2 = m.begin(); it2 != m.end(); ++it2)\n        {\n            MPI_Pack((void *) &(it2->first                          ),       1, MPI_SIZE_T, buf, bs, &p, MPI_COMM_WORLD);\n            size_t countEW = it2->second.countEW;\n            MPI_Pack((void *) &(countEW                             ),       1, MPI_SIZE_T, buf, bs, &p, MPI_COMM_WORLD);\n            MPI_Pack((void *) &(it2->second.type                    ),       1, MPI_SIZE_T, buf, bs, &p, MPI_COMM_WORLD);\n            MPI_Pack((void *) &(it2->second.Gmin                    ),       1, MPI_DOUBLE, buf, bs, &p, MPI_COMM_WORLD);\n            MPI_Pack((void *) &(it2->second.Gmax                    ),       1, MPI_DOUBLE, buf, bs, &p, MPI_COMM_WORLD);\n            // it2->element\n            size_t ts = it2->second.element.length() + 1;\n            MPI_Pack((void *) &ts                                    ,       1, MPI_SIZE_T, buf, bs, &p, MPI_COMM_WORLD);\n            MPI_Pack((void *) it2->second.element.c_str()            ,      ts, MPI_CHAR  , buf, bs, &p, MPI_COMM_WORLD);\n            MPI_Pack((void *) &(it2->second.indexStructureEW.front()), countEW, MPI_SIZE_T, buf, bs, &p, MPI_COMM_WORLD);\n            MPI_Pack((void *) &(it2->second.indexAtomEW.front()     ), countEW, MPI_SIZE_T, buf, bs, &p, MPI_COMM_WORLD);\n            MPI_Pack((void *) &(it2->second.valueEW.front()         ), countEW, MPI_DOUBLE, buf, bs, &p, MPI_COMM_WORLD);\n        }\n    }\n#endif\n    return;\n}\n\nvoid InterfaceLammps::extractEWBuffer(char const* const& buf, int bs)\n{\n#ifndef N2P2_NO_MPI\n    int p = 0;\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        size_t n = 0;\n        MPI_Unpack((void *) buf, bs, &p, &(n), 1, MPI_SIZE_T, MPI_COMM_WORLD);\n        for (size_t i = 0; i < n; ++i)\n        {\n            size_t index = 0;\n            MPI_Unpack((void *) buf, bs, &p, &(index), 1, MPI_SIZE_T, MPI_COMM_WORLD);\n            SymFncStatistics::Container& d = it->statistics.data[index];\n            size_t countEW = 0;\n            MPI_Unpack((void *) buf, bs, &p, &(countEW                      ),       1, MPI_SIZE_T, MPI_COMM_WORLD);\n            MPI_Unpack((void *) buf, bs, &p, &(d.type                       ),       1, MPI_SIZE_T, MPI_COMM_WORLD);\n            MPI_Unpack((void *) buf, bs, &p, &(d.Gmin                       ),       1, MPI_DOUBLE, MPI_COMM_WORLD);\n            MPI_Unpack((void *) buf, bs, &p, &(d.Gmax                       ),       1, MPI_DOUBLE, MPI_COMM_WORLD);\n            // d.element\n            size_t ts = 0;\n            MPI_Unpack((void *) buf, bs, &p, &ts                             ,       1, MPI_SIZE_T, MPI_COMM_WORLD);\n            char* element = new char[ts];\n            MPI_Unpack((void *) buf, bs, &p, element                         ,      ts, MPI_CHAR  , MPI_COMM_WORLD);\n            d.element = element;\n            delete[] element;\n            // indexStructureEW.\n            d.indexStructureEW.resize(d.countEW + countEW);\n            MPI_Unpack((void *) buf, bs, &p, &(d.indexStructureEW[d.countEW]), countEW, MPI_SIZE_T, MPI_COMM_WORLD);\n            // indexAtomEW.\n            d.indexAtomEW.resize(d.countEW + countEW);\n            MPI_Unpack((void *) buf, bs, &p, &(d.indexAtomEW[d.countEW]     ), countEW, MPI_SIZE_T, MPI_COMM_WORLD);\n            // valueEW.\n            d.valueEW.resize(d.countEW + countEW);\n            MPI_Unpack((void *) buf, bs, &p, &(d.valueEW[d.countEW]         ), countEW, MPI_DOUBLE, MPI_COMM_WORLD);\n\n            d.countEW += countEW;\n        }\n    }\n#endif\n    return;\n}\n\nvoid InterfaceLammps::writeExtrapolationWarnings()\n{\n    for (vector<Element>::const_iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        vector<string> vs = it->statistics.getExtrapolationWarningLines();\n        for (vector<string>::const_iterator it2 = vs.begin();\n             it2 != vs.end(); ++it2)\n        {\n            log << (*it2);\n        }\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::clearExtrapolationWarnings()\n{\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        it->statistics.clear();\n    }\n\n    return;\n}\n\nvoid InterfaceLammps::writeToFile(string const fileName,\n                                  bool const   append)\n{\n    structure.toPhysicalUnits(meanEnergy, convEnergy, convLength, convCharge);\n    structure.writeToFile(fileName, false, append);\n    structure.toNormalizedUnits(meanEnergy, convEnergy, convLength, convCharge);\n}\n\nvoid InterfaceLammps::add3DVecToArray(double *const & arr, Vec3D const& v) const\n{\n    arr[0] += v[0];\n    arr[1] += v[1];\n    arr[2] += v[2];\n}\n"
  },
  {
    "path": "src/libnnpif/LAMMPS/InterfaceLammps.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef INTERFACELAMMPS_H\n#define INTERFACELAMMPS_H\n\n#include \"Mode.h\"\n#include \"Structure.h\"\n#include <map>     // std::map\n#include <cstddef> // std::size_t\n#include <cstdint> // int64_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\nclass InterfaceLammps : public Mode\n{\npublic:\n    InterfaceLammps();\n\n    /** Initialize the LAMMPS interface.\n     *\n     * @param[in] directory Directory containing NNP data files (weights,\n     *                      scaling, settings).\n     * @param[in] emap Element mapping from LAMMPS to n2p2.\n     * @param[in] showew If detailed extrapolation warnings for all atoms are\n     *                   shown.\n     * @param[in] resetew If extrapolation warnings counter is reset every\n     *                    timestep.\n     * @param[in] showewsum Show number of warnings every this many timesteps.\n     * @param[in] maxew Abort simulation if more than this many warnings are\n     *                  encountered.\n     * @param[in] cflength Length unit conversion factor.\n     * @param[in] cfenergy Energy unit conversion factor.\n     * @param[in] lammpsCutoff Cutoff radius from LAMMPS (via pair_coeff).\n     * @param[in] lammpsNtypes Number of atom types in LAMMPS.\n     * @param[in] myRank MPI process rank (passed on to structure index).\n     */\n    void   initialize(char const* const& directory,\n                      char const* const& emap,\n                      bool               showew,\n                      bool               resetew,\n                      int                showewsum,\n                      int                maxew,\n                      double             cflength,\n                      double             cfenergy,\n                      double             lammpsCutoff,\n                      int                lammpsNtypes,\n                      int                myRank);\n    /** Specify whether n2p2 knows about global structure or only local\n     * structure.\n     * @param[in] status true if n2p2 has global structure.\n     */\n    void    setGlobalStructureStatus(bool const status);\n    /// Check if n2p2 knows about global structure.\n    bool    getGlobalStructureStatus();\n    /** (Re)set #structure to contain only local LAMMPS atoms.\n     *\n     * @param[in] numAtomsLocal Number of local atoms.\n     * @param[in] atomType LAMMPS atom type.\n     */\n    void   setLocalAtoms(int              numAtomsLocal,\n                         int const* const atomType);\n    /** Set absolute atom positions from LAMMPS (nnp/develop only).\n     *\n     * @param[in] atomPos Atom coordinate array in LAMMPS units.\n     */\n    void   setLocalAtomPositions(double const* const* const atomPos);\n    /** Set atom tags (int version, -DLAMMPS_SMALLBIG).\n     *\n     * @param[in] atomTag LAMMPS atom tag.\n     */\n    void   setLocalTags(int const* const atomTag);\n    /** Set atom tags (int64_t version, -DLAMMPS_BIGBIG).\n     *\n     * @param[in] atomTag LAMMPS atom tag.\n     */\n    void   setLocalTags(int64_t const* const atomTag);\n    /** Set box vectors of structure stored in LAMMPS (nnp/develop only).\n     *\n     * @param[in] boxlo Array containing coordinates of origin xlo, ylo, zlo.\n     * @param[in] boxhi Array containing coordinates xhi, yhi, zhi.\n     * @param[in] xy Tilt factor for box vector b.\n     * @param[in] xz First tilt factor for box vector c.\n     * @param[in] yz Second tilt factor for box vector c.\n     */\n    void   setBoxVectors(double const* boxlo,\n                         double const* boxhi,\n                         double const  xy,\n                         double const  xz,\n                         double const  yz);\n    /** Allocate neighbor lists.\n     *\n     * @param[in] numneigh Array containing number of neighbors for each local atom.\n     */\n    void   allocateNeighborlists(int const* const numneigh);\n    /** Add one neighbor to atom (int64_t version, -DLAMMPS_BIGBIG).\n     *\n     * @param[in] i Local atom index.\n     * @param[in] j Neighbor atom index.\n     * @param[in] tag Neighbor atom tag.\n     * @param[in] type Neighbor atom type.\n     * @param[in] dx Neighbor atom distance in x direction.\n     * @param[in] dy Neighbor atom distance in y direction.\n     * @param[in] dz Neighbor atom distance in z direction.\n     * @param[in] d2 Square of neighbor atom distance.\n     *\n     * If -DLAMMPS_SMALLBIG implicit conversion is applied for tag.\n     */\n    void   addNeighbor(int     i,\n                       int     j,\n                       int64_t tag,\n                       int     type,\n                       double  dx,\n                       double  dy,\n                       double  dz,\n                       double  d2);\n    /** Sorts neighbor list and creates cutoff map if necessary. If structure is\n     * periodic, this function needs to be called after setBoxVectors!\n     */\n    void   finalizeNeighborList();\n    /** Calculate symmetry functions, atomic neural networks and sum of local\n     * energy contributions.\n     */\n    void   process();\n    /** Calculate symmetry functions, atomic neural networks and sum of local\n     * energy contributions (development version for \"hdnnp/develop\" pair style).\n     */\n    void   processDevelop();\n    /** Return sum of local energy contributions.\n     *\n     * @return Sum of local energy contributions.\n     */\n    double getEnergy() const;\n    /** Return energy contribution of one atom.\n     *\n     * @param[in] index Atom index.\n     *\n     * @return energy contribution of atom with given index.\n     *\n     * @attention These atomic contributions are not physical!\n     */\n    double getAtomicEnergy(int index) const;\n    /** Adds electrostatic energy contribution to the total structure energy\n     *\n     * @param[in] electrostatic energy (calculated in LAMMPS).\n     *\n     */\n    void addElectrostaticEnergy(double energy);\n    /** Calculate forces and add to LAMMPS atomic force arrays.\n     *\n     * @param[in,out] atomF LAMMPS force array for local and ghost atoms.\n     */\n    void   getForces(double* const* const& atomF) const;\n    /** Calculate forces and add to LAMMPS atomic force arrays (development version for\n     * \"hdnnp/develop\" pair style).\n     *\n     * @param[in,out] atomF LAMMPS force array for local and ghost atoms.\n     */\n    void   getForcesDevelop(double* const* const& atomF) const;\n    /** Calculate chi-term for forces and add to LAMMPS atomic force arrays.\n     *\n     * @param[in,out] atomF LAMMPS force array for local and ghost atoms.\n     */\n    void   getForcesChi(double const* const&  lambda,\n                        double* const* const& atomF) const;\n    /** Transfer charges (in units of e) to LAMMPS atomic charge vector. Call\n     *  after getAtomicEnergy().\n     *\n     * @param[in,out] atomQ LAMMPS charge vector.\n     */\n    void   getCharges(double* const& atomQ) const;\n    /** Check if this interface is correctly initialized.\n     *\n     * @return `True` if initialized, `False` otherwise.\n     */\n    bool   isInitialized() const;\n    /** Get largest cutoff of symmetry functions.\n     *\n     * @return Largest cutoff of all symmetry functions.\n     */\n    double getMaxCutoffRadius() const;\n    /** Get Ewald precision parameter.\n     *\n     * @return Ewald precision parameter.\n     */\n    double getEwaldPrec() const;\n    /** Get largest cutoff including structure specific cutoff and screening\n     *  cutoff.\n     *\n     * @return Largest cutoff of all symmetry functions and structure specific\n     *                  cutoff and screening cutoff.\n     */\n    double getMaxCutoffRadiusOverall();\n    /** Calculate buffer size for extrapolation warning communication.\n     *\n     * @return Buffer size.\n     */\n    long   getEWBufferSize() const;\n    /** Fill provided buffer with extrapolation warning entries.\n     *\n     * @param[in,out] buf Communication buffer to fill.\n     * @param[in] bs Buffer size.\n     */\n    void   fillEWBuffer(char* const& buf, int bs) const;\n    /** Extract given buffer to symmetry function statistics class.\n     *\n     * @param[in] buf Buffer with extrapolation warnings data.\n     * @param[in] bs Buffer size.\n     */\n    void   extractEWBuffer(char const* const& buf, int bs);\n    /** Write extrapolation warnings to log.\n     */\n    void   writeExtrapolationWarnings();\n    /** Clear extrapolation warnings storage.\n     */\n    void   clearExtrapolationWarnings();\n    /** Read atomic charges from LAMMPS into n2p2.\n     */\n    void   addCharge(int index, double Q);\n    /** Write QEq arrays from n2p2 to LAMMPS.\n     *\n     * @param[in] atomChi Electronegativities.\n     * @param[in] atomJ Atomic hardness.\n     * @param[in] atomSigma Gaussian width.\n     * @param[in] qRef Reference charge of the structure.\n     */\n    void   getQEqParams(double* const&        atomChi,\n                        double* const&        atomJ,\n                        double* const&        sigmaSqrtPi,\n                        double *const *const& gammaSqrt2,\n                        double& qRef) const;\n    /** Write the derivative of total energy with respect to atomic charges\n     * from n2p2 into LAMMPS.\n     *\n     * @param[in] dEtotdQ Derivative of the total energy w.r.t. atomic charge.\n     */\n    void   getdEdQ(double* const& dEtotdQ) const;\n    /** Read screening function information from n2p2 into LAMMPS.\n     *\n     * @param[in] rScreen Array that contains screening radii.\n     */\n    void   getScreeningInfo(double* const& rScreen) const;\n    /** Transfer spatial derivatives of atomic electronegativities.\n     *\n     * @param[in] tag Atom of interest\n     * @param dChidx\n     * @param dChidy\n     * @param dChidz\n     */\n    void   getdChidxyz(int            tag,\n                       double* const& dChidx,\n                       double* const& dChidy,\n                       double* const& dChidz) const;\n    /** Set isElecDone true after running the first NN in 4G-HDNNPs.\n     */\n    void   setElecDone();\n    /** Write current structure to file in units used in training data.\n     *\n     * @param fileName File name of the output structure file.\n     * @param append true if structure should be appended to existing file.\n     */\n    void   writeToFile(std::string const fileName,\n                       bool const        append);\n    /** Add a Vec3D vector to a 3D array in place.\n     *\n     * @param[in,out] arr Array which is edited in place.\n     * @param[in] v Vector which is added to arr.\n     */\n    void   add3DVecToArray(double *const & arr, Vec3D const& v) const;\n\nprotected:\n    /// Process rank.\n    int                        myRank;\n    /// Initialization state.\n    bool                       initialized;\n    /// Whether n2p2 knows about the global structure or only a local part.\n    bool                       hasGlobalStructure;\n    /// Corresponds to LAMMPS `showew` keyword.\n    bool                       showew;\n    /// Corresponds to LAMMPS `resetew` keyword.\n    bool                       resetew;\n    /// Corresponds to LAMMPS `showewsum` keyword.\n    int                        showewsum;\n    /// Corresponds to LAMMPS `maxew` keyword.\n    int                        maxew;\n    /// Corresponds to LAMMPS `cflength` keyword.\n    double                     cflength;\n    /// Corresponds to LAMMPS `cfenergy` keyword.\n    double                     cfenergy;\n    /// Corresponds to LAMMPS `map` keyword.\n    std::string                emap;\n    /// Map from LAMMPS index to n2p2 atom index.\n    std::vector<size_t>        indexMap;\n    /// True if atoms of this LAMMPS type will be ignored.\n    std::map<int, bool>        ignoreType;\n    /// Map from LAMMPS type to n2p2 element index.\n    std::map<int, std::size_t> mapTypeToElement;\n    /// Map from n2p2 element index to LAMMPS type.\n    std::map<std::size_t, int> mapElementToType;\n    /// Structure containing local atoms.\n    Structure                  structure;\n    /// True if first NN is calculated\n    bool                       isElecDone;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline bool InterfaceLammps::isInitialized() const\n{\n    return initialized;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnpif/LAMMPS/Makefile.lammps",
    "content": "# Settings that the LAMMPS build will import when this package library is used\n\nhdnnp_SYSINC =\nhdnnp_SYSLIB = -lnnpif -lnnp\nhdnnp_SYSPATH =\n"
  },
  {
    "path": "src/libnnpif/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=../..\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# GENERAL SETTINGS\n###############################################################################\n# Default compiler, may be overridden by master makefile or command line.\nCOMP=gnu\n\n# Default build mode, may be overridden by master makefile or command line.\n# Possible modes are \"static\", \"shared\" and \"test\".\nMODE=static\n\n# Include global (project-wide) settings.\ninclude $(PROJECT_DIR)/src/makefile.$(COMP)\n\n\n###############################################################################\n# INTERFACE LIBRARY OPTIONS\n###############################################################################\n\n# Default interfaces compiled into libnnpif, may be overridden by master\n# makefile or command line. Provide a space-separated list of the following\n# available options:\n#    * LAMMPS\n#    * CabanaMD\nINTERFACES=LAMMPS CabanaMD\n\n\n###############################################################################\n# LIBRARY NAME\n###############################################################################\nNAME=nnpif\nLIB=lib$(NAME)\n\n\n###############################################################################\n# PROJECT COMPILER AND FLAGS\n###############################################################################\nCC=$(PROJECT_CC)\nifneq (,$(findstring N2P2_NO_MPI,${PROJECT_OPTIONS}))\nMPICC=${PROJECT_CC}\nCFLAGS=${PROJECT_CFLAGS}\nelse\nMPICC=${PROJECT_MPICC}\nCFLAGS=${PROJECT_CFLAGS} ${PROJECT_CFLAGS_MPI}\nendif\nOPTIONS+=$(PROJECT_OPTIONS)\nDEBUG=$(PROJECT_DEBUG)\nifeq ($(MODE), test)\nDEBUG+= $(PROJECT_TEST)\nendif\nAR=$(PROJECT_AR)\nARFLAGS=$(PROJECT_ARFLAGS)\n\n# Extra include paths for compiling.\nINCLUDES=-I./ -I$(PROJECT_INCLUDE)/ -I$(PROJECT_EIGEN)\n\n\n###############################################################################\n# DEFINE SOURCES AND HEADERS\n###############################################################################\n\n$(info The following interfaces were selected: $(INTERFACES))\nIF=LAMMPS\nifneq ($(filter $(IF),$(INTERFACES)),)\nSRC:=$(SRC) $(wildcard $(IF)/*.cpp)\nHEADERS:=$(HEADERS) $(wildcard $(IF)/*.h)\nendif\n\nIF=CabanaMD\nifneq ($(filter $(IF),$(INTERFACES)),)\nSRC:=$(SRC) $(wildcard $(IF)/*.cpp)\nHEADERS:=$(HEADERS) $(wildcard $(IF)/*.h)\nendif\n\nOBJ=$(SRC:.cpp=.o)\n\n\n###############################################################################\n# RULES\n###############################################################################\n.PHONY: all \\\n\theaders \\\n\tlammps-prep \\\n\tlammps-mf \\\n\tlammps-cmake \\\n\tclean rebuild\n\nifeq ($(MODE), shared)\nall: headers lammps-prep $(LIB).so\nelse\nall: headers lammps-prep $(LIB).a\nendif\n\nheaders:\n\tcp $(HEADERS) $(PROJECT_INCLUDE)\n\nLAMMPS_OPTIONS := $(filter -DN2P2_%,$(OPTIONS))\nlammps-prep: lammps-mf lammps-cmake\n\nlammps-mf:\n\tcp LAMMPS/Makefile.lammps $(PROJECT_LIB)/Makefile.lammps-extra\n\t@sed -i.bak -E \"s,(hdnnp_SYSINC =).*,\\1 $(LAMMPS_OPTIONS),\" $(PROJECT_LIB)/Makefile.lammps-extra\n\t@sed -i.bak -E \"s,(hdnnp_SYSLIB =.*),\\1 $(PROJECT_LDFLAGS_BLAS),\" $(PROJECT_LIB)/Makefile.lammps-extra\n\t@rm $(PROJECT_LIB)/Makefile.lammps-extra.bak\n\nlammps-cmake:\n\t$(RM) -f $(PROJECT_LIB)/lammps-extra.cmake\n\ttouch $(PROJECT_LIB)/lammps-extra.cmake\n\tfor flag in $(LAMMPS_OPTIONS); do \\\n\t\techo \"target_compile_definitions(lammps PRIVATE $${flag})\" >> $(PROJECT_LIB)/lammps-extra.cmake; \\\n\tdone\n\n$(LIB).so: CFLAGS+= -fPIC\n$(LIB).so: $(OBJ)\n\t$(MPICC) $(CFLAGS) $(DEBUG) $(OPTIONS) -o $@ $+ -shared\n\tcp $@ $(PROJECT_LIB)\n\n$(LIB).a: $(OBJ)\n\t$(AR) $(ARFLAGS) $@ $+\n\tcp $@ $(PROJECT_LIB)\n\n%.o: %.cpp\n\t$(MPICC) $(CFLAGS) $(DEBUG) $(INCLUDES) $(OPTIONS) -o $@ -c $<\n\nclean: clean-headers clean-lammps-prep\n\t$(RM) $(OBJ)\n\t$(RM) $(OBJ:.o=.gcno) $(OBJ:.o=.gcda) $(LIB).so $(LIB).a\n\t$(RM) $(PROJECT_LIB)/$(LIB).so $(PROJECT_LIB)/$(LIB).a\n\nclean-headers:\n\tcd $(PROJECT_INCLUDE) && $(RM) $(notdir $(HEADERS))\n\nclean-lammps-prep:\n\t$(RM) $(PROJECT_LIB)/Makefile.lammps-extra\n\t$(RM) $(PROJECT_LIB)/lammps-extra.cmake\n\nrebuild: clean all\n"
  },
  {
    "path": "src/libnnptrain/Dataset.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Dataset.h\"\n#include \"SymFnc.h\"\n#include \"mpi-extra.h\"\n#include \"utility.h\"\n#include <algorithm> // std::max, std::find, std::find_if, std::sort, std::fill\n#include <cmath>     // sqrt, fabs\n#include <cstdint>   // int64_t\n#include <cstdlib>   // atoi\n#include <cstdio>    // fprintf, fopen, fclose, remove\n#include <iostream>  // std::ios::binary\n#include <fstream>   // std::ifstream, std::ofstream\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error\n#include <gsl/gsl_histogram.h>\n#include <gsl/gsl_rng.h>\n\nusing namespace std;\nusing namespace nnp;\n\nDataset::Dataset() : Mode(),\n                     myRank       (0   ),\n                     numProcs     (0   ),\n                     numStructures(0   ),\n                     myName       (\"\"  ),\n                     rng          (NULL),\n                     rngGlobal    (NULL)\n{\n}\n\nDataset::~Dataset()\n{\n    if (rng != NULL) gsl_rng_free(rng);\n    if (rngGlobal != NULL) gsl_rng_free(rngGlobal);\n}\n\nvoid Dataset::setupMPI()\n{\n    MPI_Comm tmpComm;\n    MPI_Comm_dup(MPI_COMM_WORLD, &tmpComm);\n    setupMPI(&tmpComm);\n    MPI_Comm_free(&tmpComm);\n\n    return;\n}\n\nvoid Dataset::setupMPI(MPI_Comm* communicator)\n{\n    log << \"\\n\";\n    log << \"*** SETUP: MPI **************************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    int        bufferSize = 0;\n    char       line[MPI_MAX_PROCESSOR_NAME];\n    MPI_Status ms;\n\n    MPI_Comm_dup(*communicator, &comm);\n    MPI_Comm_rank(comm, &myRank);\n    MPI_Comm_size(comm, &numProcs);\n    MPI_Get_processor_name(line, &bufferSize);\n    myName = line;\n\n    log << strpr(\"Number of processors: %d\\n\", numProcs);\n    log << strpr(\"Process %d of %d (rank %d): %s\\n\",\n                 myRank + 1,\n                 numProcs,\n                 myRank,\n                 myName.c_str());\n    for (int i = 1; i < numProcs; ++i)\n    {\n        if (myRank == 0)\n        {\n            MPI_Recv(&bufferSize, 1, MPI_INT, i, 0, comm, &ms);\n            MPI_Recv(line, bufferSize, MPI_CHAR, i, 0, comm, &ms);\n            log << strpr(\"Process %d of %d (rank %d): %s\\n\",\n                         i + 1,\n                         numProcs,\n                         i,\n                         line);\n        }\n        else if (myRank == i)\n        {\n            MPI_Send(&bufferSize, 1, MPI_INT, 0, 0, comm);\n            MPI_Send(line, bufferSize, MPI_CHAR, 0, 0, comm);\n        }\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Dataset::setupRandomNumberGenerator()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: RANDOM NUMBER GENERATOR ******\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    // Get random seed from settings file.\n    unsigned long seed = atoi(settings[\"random_seed\"].c_str());\n    unsigned long seedGlobal = 0;\n\n    if (myRank == 0)\n    {\n        log << strpr(\"Random number generator seed: %d\\n\", seed);\n        if (seed == 0)\n        {\n            log << \"WARNING: Seed set to 0. This is a special value for the \"\n                   \"gsl_rng_set() routine (see GSL docs).\\n\";\n        }\n        // Initialize personal RNG of process 0 with the given seed.\n        rng = gsl_rng_alloc(gsl_rng_mt19937);\n        gsl_rng_set(rng, seed);\n        log << strpr(\"Seed for rank %d: %lu\\n\", 0, seed);\n        for (int i = 1; i < numProcs; ++i)\n        {\n            // Get new seeds for all remaining processes with the RNG.\n            seed = gsl_rng_get(rng);\n            log << strpr(\"Seed for rank %d: %lu\\n\", i, seed);\n            MPI_Send(&seed, 1, MPI_UNSIGNED_LONG, i, 0, comm);\n        }\n        // Set seed for global RNG.\n        seedGlobal = gsl_rng_get(rng);\n    }\n    else\n    {\n        // Receive seed for personal RNG.\n        MPI_Status ms;\n        MPI_Recv(&seed, 1, MPI_UNSIGNED_LONG, 0, 0, comm, &ms);\n        log << strpr(\"Seed for rank %d: %lu\\n\", myRank, seed);\n        rng = gsl_rng_alloc(gsl_rng_taus);\n        gsl_rng_set(rng, seed);\n    }\n    // Rank 0 broadcasts global seed.\n    MPI_Bcast(&seedGlobal, 1, MPI_UNSIGNED_LONG, 0, comm);\n    log << strpr(\"Seed for global RNG: %lu\\n\", seedGlobal);\n    // All processes initialize global RNG.\n    rngGlobal = gsl_rng_alloc(gsl_rng_taus);\n    gsl_rng_set(rngGlobal, seedGlobal);\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nint Dataset::calculateBufferSize(Structure const& structure) const\n{\n    int              bs   = 0;         // Send buffer size.\n    int              is   = 0;         // int size.\n    int              i64s = 0;         // int64_t size.\n    int              ss   = 0;         // size_t size.\n    int              ds   = 0;         // double size.\n    int              cs   = 0;         // char size.\n    Structure const& s   = structure; // Shortcut for structure.\n\n    MPI_Pack_size(1, MPI_INT    , comm, &is  );\n    MPI_Pack_size(1, MPI_INT64_T, comm, &i64s);\n    MPI_Pack_size(1, MPI_SIZE_T , comm, &ss  );\n    MPI_Pack_size(1, MPI_DOUBLE , comm, &ds  );\n    MPI_Pack_size(1, MPI_CHAR   , comm, &cs  );\n\n    // Structure\n    bs += 5 * cs + 4 * ss + 4 * is + 5 * ds;\n    // Structure.comment\n    bs += ss;\n    bs += (s.comment.length() + 1) * cs;\n    // Structure.box\n    bs += 9 * ds;\n    // Structure.invbox\n    bs += 9 * ds;\n    // Structure.numAtomsPerElement\n    bs += ss;\n    bs += s.numAtomsPerElement.size() * ss;\n    // Structure.atoms\n    bs += ss;\n    bs += s.atoms.size() * (4 * cs + 6 * ss + i64s + 4 * ds + 3 * 3 * ds);\n    for (vector<Atom>::const_iterator it = s.atoms.begin();\n         it != s.atoms.end(); ++it)\n    {\n        // Atom.neighborsUnique\n        bs += ss;\n        bs += it->neighborsUnique.size() * ss;\n        // Atom.numNeighborsPerElement\n        bs += ss;\n        bs += it->numNeighborsPerElement.size() * ss;\n        // Atom.numSymmetryFunctionDerivatives\n        bs += ss;\n        bs += it->numSymmetryFunctionDerivatives.size() * ss;\n#ifndef N2P2_NO_SF_CACHE\n        // Atom.cacheSizePerElement\n        bs += ss;\n        bs += it->cacheSizePerElement.size() * ss;\n#endif\n        // Atom.G\n        bs += ss;\n        bs += it->G.size() * ds;\n        // Atom.dEdG\n        bs += ss;\n        bs += it->dEdG.size() * ds;\n        // Atom.dQdG\n        bs += ss;\n        bs += it->dQdG.size() * ds;\n#ifdef N2P2_FULL_SFD_MEMORY\n        // Atom.dGdxia\n        bs += ss;\n        bs += it->dGdxia.size() * ds;\n#endif\n        // Atom.dGdr\n        bs += ss;\n        bs += it->dGdr.size() * 3 * ds;\n        // Atom.neighbors\n        bs += ss;\n        for (vector<Atom::Neighbor>::const_iterator it2 =\n             it->neighbors.begin(); it2 != it->neighbors.end(); ++it2)\n        {\n            // Neighbor\n            bs += 2 * ss + i64s + ds + 3 * ds;\n#ifndef N2P2_NO_SF_CACHE\n            // Neighbor.cache\n            bs += ss;\n            bs += it2->cache.size() * ds;\n#endif\n            // Neighbor.dGdr\n            bs += ss;\n            bs += it2->dGdr.size() * 3 * ds;\n        }\n    }\n\n    return bs;\n}\n\nint Dataset::sendStructure(Structure const& structure, int dest) const\n{\n    unsigned char*   buf = 0;         // Send buffer.\n    int              bs  = 0;         // Send buffer size.\n    int              p   = 0;         // Send buffer position.\n    int              ts  = 0;         // Size for temporary stuff.\n    Structure const& s   = structure; // Shortcut for structure.\n\n    bs = calculateBufferSize(s);\n    buf = new unsigned char[bs];\n\n    // Structure\n    MPI_Pack(&(s.isPeriodic                    ), 1, MPI_CHAR  , buf, bs, &p, comm);\n    MPI_Pack(&(s.isTriclinic                   ), 1, MPI_CHAR  , buf, bs, &p, comm);\n    MPI_Pack(&(s.hasNeighborList               ), 1, MPI_CHAR  , buf, bs, &p, comm);\n    MPI_Pack(&(s.hasSymmetryFunctions          ), 1, MPI_CHAR  , buf, bs, &p, comm);\n    MPI_Pack(&(s.hasSymmetryFunctionDerivatives), 1, MPI_CHAR  , buf, bs, &p, comm);\n    MPI_Pack(&(s.index                         ), 1, MPI_SIZE_T, buf, bs, &p, comm);\n    MPI_Pack(&(s.numAtoms                      ), 1, MPI_SIZE_T, buf, bs, &p, comm);\n    MPI_Pack(&(s.numElements                   ), 1, MPI_SIZE_T, buf, bs, &p, comm);\n    MPI_Pack(&(s.numElementsPresent            ), 1, MPI_SIZE_T, buf, bs, &p, comm);\n    MPI_Pack(&(s.pbc                           ), 3, MPI_INT   , buf, bs, &p, comm);\n    MPI_Pack(&(s.energy                        ), 1, MPI_DOUBLE, buf, bs, &p, comm);\n    MPI_Pack(&(s.energyRef                     ), 1, MPI_DOUBLE, buf, bs, &p, comm);\n    MPI_Pack(&(s.charge                        ), 1, MPI_DOUBLE, buf, bs, &p, comm);\n    MPI_Pack(&(s.chargeRef                     ), 1, MPI_DOUBLE, buf, bs, &p, comm);\n    MPI_Pack(&(s.volume                        ), 1, MPI_DOUBLE, buf, bs, &p, comm);\n    MPI_Pack(&(s.sampleType                    ), 1, MPI_INT   , buf, bs, &p, comm);\n\n    // Strucuture.comment\n    ts = s.comment.length() + 1;\n    MPI_Pack(&ts, 1, MPI_SIZE_T, buf, bs, &p, comm);\n    MPI_Pack(s.comment.c_str(), ts, MPI_CHAR, buf, bs, &p, comm);\n\n    // Structure.box\n    for (size_t i = 0; i < 3; ++i)\n    {\n        MPI_Pack(s.box[i].r, 3, MPI_DOUBLE, buf, bs, &p, comm);\n    }\n\n    // Structure.invbox\n    for (size_t i = 0; i < 3; ++i)\n    {\n        MPI_Pack(s.invbox[i].r, 3, MPI_DOUBLE, buf, bs, &p, comm);\n    }\n\n    // Structure.numAtomsPerElement\n    ts = s.numAtomsPerElement.size();\n    MPI_Pack(&ts, 1, MPI_SIZE_T, buf, bs, &p, comm);\n    if (ts > 0)\n    {\n        MPI_Pack(&(s.numAtomsPerElement.front()), ts, MPI_SIZE_T, buf, bs, &p, comm);\n    }\n\n    // Structure.atoms\n    ts = s.atoms.size();\n    MPI_Pack(&ts, 1, MPI_SIZE_T, buf, bs, &p, comm);\n    if (ts > 0)\n    {\n        for (vector<Atom>::const_iterator it = s.atoms.begin();\n             it != s.atoms.end(); ++it)\n        {\n            // Atom\n            MPI_Pack(&(it->hasNeighborList               ), 1, MPI_CHAR,    buf, bs, &p, comm);\n            MPI_Pack(&(it->hasSymmetryFunctions          ), 1, MPI_CHAR,    buf, bs, &p, comm);\n            MPI_Pack(&(it->hasSymmetryFunctionDerivatives), 1, MPI_CHAR,    buf, bs, &p, comm);\n            MPI_Pack(&(it->useChargeNeuron               ), 1, MPI_CHAR,    buf, bs, &p, comm);\n            MPI_Pack(&(it->index                         ), 1, MPI_SIZE_T,  buf, bs, &p, comm);\n            MPI_Pack(&(it->indexStructure                ), 1, MPI_SIZE_T,  buf, bs, &p, comm);\n            MPI_Pack(&(it->tag                           ), 1, MPI_INT64_T, buf, bs, &p, comm);\n            MPI_Pack(&(it->element                       ), 1, MPI_SIZE_T,  buf, bs, &p, comm);\n            MPI_Pack(&(it->numNeighbors                  ), 1, MPI_SIZE_T,  buf, bs, &p, comm);\n            MPI_Pack(&(it->numNeighborsUnique            ), 1, MPI_SIZE_T,  buf, bs, &p, comm);\n            MPI_Pack(&(it->numSymmetryFunctions          ), 1, MPI_SIZE_T,  buf, bs, &p, comm);\n            MPI_Pack(&(it->energy                        ), 1, MPI_DOUBLE,  buf, bs, &p, comm);\n            MPI_Pack(&(it->chi                           ), 1, MPI_DOUBLE,  buf, bs, &p, comm);\n            MPI_Pack(&(it->charge                        ), 1, MPI_DOUBLE,  buf, bs, &p, comm);\n            MPI_Pack(&(it->chargeRef                     ), 1, MPI_DOUBLE,  buf, bs, &p, comm);\n            MPI_Pack(&(it->r.r                           ), 3, MPI_DOUBLE,  buf, bs, &p, comm);\n            MPI_Pack(&(it->f.r                           ), 3, MPI_DOUBLE,  buf, bs, &p, comm);\n            MPI_Pack(&(it->fRef.r                        ), 3, MPI_DOUBLE,  buf, bs, &p, comm);\n\n            // Atom.neighborsUnique\n            size_t ts2 = it->neighborsUnique.size();\n            MPI_Pack(&ts2, 1, MPI_SIZE_T, buf, bs, &p, comm);\n            if (ts2 > 0)\n            {\n                MPI_Pack(&(it->neighborsUnique.front()), ts2, MPI_SIZE_T, buf, bs, &p, comm);\n            }\n\n            // Atom.numNeighborsPerElement\n            ts2 = it->numNeighborsPerElement.size();\n            MPI_Pack(&ts2, 1, MPI_SIZE_T, buf, bs, &p, comm);\n            if (ts2 > 0)\n            {\n                MPI_Pack(&(it->numNeighborsPerElement.front()), ts2, MPI_SIZE_T, buf, bs, &p, comm);\n            }\n\n            // Atom.numSymmetryFunctionDerivatives\n            ts2 = it->numSymmetryFunctionDerivatives.size();\n            MPI_Pack(&ts2, 1, MPI_SIZE_T, buf, bs, &p, comm);\n            if (ts2 > 0)\n            {\n                MPI_Pack(&(it->numSymmetryFunctionDerivatives.front()), ts2, MPI_SIZE_T, buf, bs, &p, comm);\n            }\n\n#ifndef N2P2_NO_SF_CACHE\n            // Atom.cacheSizePerElement\n            ts2 = it->cacheSizePerElement.size();\n            MPI_Pack(&ts2, 1, MPI_SIZE_T, buf, bs, &p, comm);\n            if (ts2 > 0)\n            {\n                MPI_Pack(&(it->cacheSizePerElement.front()), ts2, MPI_SIZE_T, buf, bs, &p, comm);\n            }\n#endif\n\n            // Atom.G\n            ts2 = it->G.size();\n            MPI_Pack(&ts2, 1, MPI_SIZE_T, buf, bs, &p, comm);\n            if (ts2 > 0)\n            {\n                MPI_Pack(&(it->G.front()), ts2, MPI_DOUBLE, buf, bs, &p, comm);\n            }\n\n            // Atom.dEdG\n            ts2 = it->dEdG.size();\n            MPI_Pack(&ts2, 1, MPI_SIZE_T, buf, bs, &p, comm);\n            if (ts2 > 0)\n            {\n                MPI_Pack(&(it->dEdG.front()), ts2, MPI_DOUBLE, buf, bs, &p, comm);\n            }\n\n            // Atom.dQdG\n            ts2 = it->dQdG.size();\n            MPI_Pack(&ts2, 1, MPI_SIZE_T, buf, bs, &p, comm);\n            if (ts2 > 0)\n            {\n                MPI_Pack(&(it->dQdG.front()), ts2, MPI_DOUBLE, buf, bs, &p, comm);\n            }\n\n#ifdef N2P2_FULL_SFD_MEMORY\n            // Atom.dGdxia\n            ts2 = it->dGdxia.size();\n            MPI_Pack(&ts2, 1, MPI_SIZE_T, buf, bs, &p, comm);\n            if (ts2 > 0)\n            {\n                MPI_Pack(&(it->dGdxia.front()), ts2, MPI_DOUBLE, buf, bs, &p, comm);\n            }\n#endif\n\n            // Atom.dGdr\n            ts2 = it->dGdr.size();\n            MPI_Pack(&ts2, 1, MPI_SIZE_T, buf, bs, &p, comm);\n            if (ts2 > 0)\n            {\n                for (vector<Vec3D>::const_iterator it2 = it->dGdr.begin();\n                     it2 != it->dGdr.end(); ++it2)\n                {\n                    MPI_Pack(it2->r, 3, MPI_DOUBLE, buf, bs, &p, comm);\n                }\n            }\n\n            // Atom.neighbors\n            ts2 = it->neighbors.size();\n            MPI_Pack(&ts2, 1, MPI_SIZE_T, buf, bs, &p, comm);\n            if (ts2 > 0)\n            {\n                for (vector<Atom::Neighbor>::const_iterator it2 =\n                     it->neighbors.begin(); it2 != it->neighbors.end(); ++it2)\n                {\n                    // Neighbor\n                    MPI_Pack(&(it2->index      ), 1, MPI_SIZE_T , buf, bs, &p, comm);\n                    MPI_Pack(&(it2->tag        ), 1, MPI_INT64_T, buf, bs, &p, comm);\n                    MPI_Pack(&(it2->element    ), 1, MPI_SIZE_T , buf, bs, &p, comm);\n                    MPI_Pack(&(it2->d          ), 1, MPI_DOUBLE , buf, bs, &p, comm);\n                    MPI_Pack(  it2->dr.r        , 3, MPI_DOUBLE , buf, bs, &p, comm);\n\n                    size_t ts3 = 0;\n#ifndef N2P2_NO_SF_CACHE\n                    // Neighbor.cache\n                    ts3 = it2->cache.size();\n                    MPI_Pack(&ts3, 1, MPI_SIZE_T, buf, bs, &p, comm);\n                    if (ts3 > 0)\n                    {\n                        MPI_Pack(&(it2->cache.front()), ts3, MPI_DOUBLE, buf, bs, &p, comm);\n                    }\n#endif\n\n                    // Neighbor.dGdr\n                    ts3 = it2->dGdr.size();\n                    MPI_Pack(&ts3, 1, MPI_SIZE_T, buf, bs, &p, comm);\n                    if (ts3 > 0)\n                    {\n                        for (vector<Vec3D>::const_iterator it3 =\n                             it2->dGdr.begin(); it3 != it2->dGdr.end(); ++it3)\n                        {\n                            MPI_Pack(it3->r, 3, MPI_DOUBLE, buf, bs, &p, comm);\n                        }\n                    }\n                }\n            }\n        }\n    }\n\n    MPI_Send(&bs, 1, MPI_INT, dest, 0, comm);\n    MPI_Send(buf, bs, MPI_PACKED, dest, 0, comm);\n\n    delete[] buf;\n\n    return bs;\n}\n\nint Dataset::recvStructure(Structure* const structure, int src)\n{\n    unsigned char*   buf = 0;         // Receive buffer.\n    int              bs  = 0;         // Receive buffer size.\n    int              p   = 0;         // Receive buffer position.\n    int              ts  = 0;         // Size for temporary stuff.\n    Structure* const s   = structure; // Shortcut for structure.\n    MPI_Status       ms;\n\n    // Receive buffer size and extract source.\n    MPI_Recv(&bs, 1, MPI_INT, src, 0, comm, &ms);\n    src = ms.MPI_SOURCE;\n\n    buf = new unsigned char[bs];\n\n    MPI_Recv(buf, bs, MPI_PACKED, src, 0, comm, &ms);\n\n    // Structure\n    MPI_Unpack(buf, bs, &p, &(s->isPeriodic                    ), 1, MPI_CHAR  , comm);\n    MPI_Unpack(buf, bs, &p, &(s->isTriclinic                   ), 1, MPI_CHAR  , comm);\n    MPI_Unpack(buf, bs, &p, &(s->hasNeighborList               ), 1, MPI_CHAR  , comm);\n    MPI_Unpack(buf, bs, &p, &(s->hasSymmetryFunctions          ), 1, MPI_CHAR  , comm);\n    MPI_Unpack(buf, bs, &p, &(s->hasSymmetryFunctionDerivatives), 1, MPI_CHAR  , comm);\n    MPI_Unpack(buf, bs, &p, &(s->index                         ), 1, MPI_SIZE_T, comm);\n    MPI_Unpack(buf, bs, &p, &(s->numAtoms                      ), 1, MPI_SIZE_T, comm);\n    MPI_Unpack(buf, bs, &p, &(s->numElements                   ), 1, MPI_SIZE_T, comm);\n    MPI_Unpack(buf, bs, &p, &(s->numElementsPresent            ), 1, MPI_SIZE_T, comm);\n    MPI_Unpack(buf, bs, &p, &(s->pbc                           ), 3, MPI_INT   , comm);\n    MPI_Unpack(buf, bs, &p, &(s->energy                        ), 1, MPI_DOUBLE, comm);\n    MPI_Unpack(buf, bs, &p, &(s->energyRef                     ), 1, MPI_DOUBLE, comm);\n    MPI_Unpack(buf, bs, &p, &(s->charge                        ), 1, MPI_DOUBLE, comm);\n    MPI_Unpack(buf, bs, &p, &(s->chargeRef                     ), 1, MPI_DOUBLE, comm);\n    MPI_Unpack(buf, bs, &p, &(s->volume                        ), 1, MPI_DOUBLE, comm);\n    MPI_Unpack(buf, bs, &p, &(s->sampleType                    ), 1, MPI_INT   , comm);\n\n    // Strucuture.comment\n    ts = 0;\n    MPI_Unpack(buf, bs, &p, &ts, 1, MPI_SIZE_T, comm);\n    char* comment = new char[ts];\n    MPI_Unpack(buf, bs, &p, comment, ts, MPI_CHAR, comm);\n    s->comment = comment;\n    delete[] comment;\n\n    // Structure.box\n    for (size_t i = 0; i < 3; ++i)\n    {\n        MPI_Unpack(buf, bs, &p, s->box[i].r, 3, MPI_DOUBLE, comm);\n    }\n\n    // Structure.invbox\n    for (size_t i = 0; i < 3; ++i)\n    {\n        MPI_Unpack(buf, bs, &p, s->invbox[i].r, 3, MPI_DOUBLE, comm);\n    }\n\n    // Structure.numAtomsPerElement\n    ts = 0;\n    MPI_Unpack(buf, bs, &p, &ts, 1, MPI_SIZE_T, comm);\n    if (ts > 0)\n    {\n        s->numAtomsPerElement.clear();\n        s->numAtomsPerElement.resize(ts, 0);\n        MPI_Unpack(buf, bs, &p, &(s->numAtomsPerElement.front()), ts, MPI_SIZE_T, comm);\n    }\n\n    // Structure.atoms\n    ts = 0;\n    MPI_Unpack(buf, bs, &p, &ts, 1, MPI_SIZE_T, comm);\n    if (ts > 0)\n    {\n        s->atoms.clear();\n        s->atoms.resize(ts);\n        for (vector<Atom>::iterator it = s->atoms.begin();\n             it != s->atoms.end(); ++it)\n        {\n            // Atom\n            MPI_Unpack(buf, bs, &p, &(it->hasNeighborList               ), 1, MPI_CHAR,    comm);\n            MPI_Unpack(buf, bs, &p, &(it->hasSymmetryFunctions          ), 1, MPI_CHAR,    comm);\n            MPI_Unpack(buf, bs, &p, &(it->hasSymmetryFunctionDerivatives), 1, MPI_CHAR,    comm);\n            MPI_Unpack(buf, bs, &p, &(it->useChargeNeuron               ), 1, MPI_CHAR,    comm);\n            MPI_Unpack(buf, bs, &p, &(it->index                         ), 1, MPI_SIZE_T,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->indexStructure                ), 1, MPI_SIZE_T,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->tag                           ), 1, MPI_INT64_T, comm);\n            MPI_Unpack(buf, bs, &p, &(it->element                       ), 1, MPI_SIZE_T,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->numNeighbors                  ), 1, MPI_SIZE_T,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->numNeighborsUnique            ), 1, MPI_SIZE_T,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->numSymmetryFunctions          ), 1, MPI_SIZE_T,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->energy                        ), 1, MPI_DOUBLE,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->chi                           ), 1, MPI_DOUBLE,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->charge                        ), 1, MPI_DOUBLE,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->chargeRef                     ), 1, MPI_DOUBLE,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->r.r                           ), 3, MPI_DOUBLE,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->f.r                           ), 3, MPI_DOUBLE,  comm);\n            MPI_Unpack(buf, bs, &p, &(it->fRef.r                        ), 3, MPI_DOUBLE,  comm);\n\n            // Atom.neighborsUnique\n            size_t ts2 = 0;\n            MPI_Unpack(buf, bs, &p, &ts2, 1, MPI_SIZE_T, comm);\n            if (ts2 > 0)\n            {\n                it->neighborsUnique.clear();\n                it->neighborsUnique.resize(ts2, 0);\n                MPI_Unpack(buf, bs, &p, &(it->neighborsUnique.front()), ts2, MPI_SIZE_T, comm);\n            }\n\n            // Atom.numNeighborsPerElement\n            ts2 = 0;\n            MPI_Unpack(buf, bs, &p, &ts2, 1, MPI_SIZE_T, comm);\n            if (ts2 > 0)\n            {\n                it->numNeighborsPerElement.clear();\n                it->numNeighborsPerElement.resize(ts2, 0);\n                MPI_Unpack(buf, bs, &p, &(it->numNeighborsPerElement.front()), ts2, MPI_SIZE_T, comm);\n            }\n\n            // Atom.numSymmetryFunctionDerivatives\n            ts2 = 0;\n            MPI_Unpack(buf, bs, &p, &ts2, 1, MPI_SIZE_T, comm);\n            if (ts2 > 0)\n            {\n                it->numSymmetryFunctionDerivatives.clear();\n                it->numSymmetryFunctionDerivatives.resize(ts2, 0);\n                MPI_Unpack(buf, bs, &p, &(it->numSymmetryFunctionDerivatives.front()), ts2, MPI_SIZE_T, comm);\n            }\n\n#ifndef N2P2_NO_SF_CACHE\n            // Atom.cacheSizePerElement\n            ts2 = 0;\n            MPI_Unpack(buf, bs, &p, &ts2, 1, MPI_SIZE_T, comm);\n            if (ts2 > 0)\n            {\n                it->cacheSizePerElement.clear();\n                it->cacheSizePerElement.resize(ts2, 0);\n                MPI_Unpack(buf, bs, &p, &(it->cacheSizePerElement.front()), ts2, MPI_SIZE_T, comm);\n            }\n#endif\n\n            // Atom.G\n            ts2 = 0;\n            MPI_Unpack(buf, bs, &p, &ts2, 1, MPI_SIZE_T, comm);\n            if (ts2 > 0)\n            {\n                it->G.clear();\n                it->G.resize(ts2, 0.0);\n                MPI_Unpack(buf, bs, &p, &(it->G.front()), ts2, MPI_DOUBLE, comm);\n            }\n\n            // Atom.dEdG\n            ts2 = 0;\n            MPI_Unpack(buf, bs, &p, &ts2, 1, MPI_SIZE_T, comm);\n            if (ts2 > 0)\n            {\n                it->dEdG.clear();\n                it->dEdG.resize(ts2, 0.0);\n                MPI_Unpack(buf, bs, &p, &(it->dEdG.front()), ts2, MPI_DOUBLE, comm);\n            }\n\n            // Atom.dQdG\n            ts2 = 0;\n            MPI_Unpack(buf, bs, &p, &ts2, 1, MPI_SIZE_T, comm);\n            if (ts2 > 0)\n            {\n                it->dQdG.clear();\n                it->dQdG.resize(ts2, 0.0);\n                MPI_Unpack(buf, bs, &p, &(it->dQdG.front()), ts2, MPI_DOUBLE, comm);\n            }\n\n#ifdef N2P2_FULL_SFD_MEMORY\n            // Atom.dGdxia\n            ts2 = 0;\n            MPI_Unpack(buf, bs, &p, &ts2, 1, MPI_SIZE_T, comm);\n            if (ts2 > 0)\n            {\n                it->dGdxia.clear();\n                it->dGdxia.resize(ts2, 0.0);\n                MPI_Unpack(buf, bs, &p, &(it->dGdxia.front()), ts2, MPI_DOUBLE, comm);\n            }\n#endif\n\n            // Atom.dGdr\n            ts2 = 0;\n            MPI_Unpack(buf, bs, &p, &ts2, 1, MPI_SIZE_T, comm);\n            if (ts2 > 0)\n            {\n                it->dGdr.clear();\n                it->dGdr.resize(ts2);\n                for (vector<Vec3D>::iterator it2 = it->dGdr.begin();\n                     it2 != it->dGdr.end(); ++it2)\n                {\n                    MPI_Unpack(buf, bs, &p, it2->r, 3, MPI_DOUBLE, comm);\n                }\n            }\n\n            // Atom.neighbors\n            ts2 = 0;\n            MPI_Unpack(buf, bs, &p, &ts2, 1, MPI_SIZE_T, comm);\n            if (ts2 > 0)\n            {\n                it->neighbors.clear();\n                it->neighbors.resize(ts2);\n                for (vector<Atom::Neighbor>::iterator it2 =\n                     it->neighbors.begin(); it2 != it->neighbors.end(); ++it2)\n                {\n                    // Neighbor\n                    MPI_Unpack(buf, bs, &p, &(it2->index      ), 1, MPI_SIZE_T , comm);\n                    MPI_Unpack(buf, bs, &p, &(it2->tag        ), 1, MPI_INT64_T, comm);\n                    MPI_Unpack(buf, bs, &p, &(it2->element    ), 1, MPI_SIZE_T , comm);\n                    MPI_Unpack(buf, bs, &p, &(it2->d          ), 1, MPI_DOUBLE , comm);\n                    MPI_Unpack(buf, bs, &p,   it2->dr.r        , 3, MPI_DOUBLE , comm);\n\n                    size_t ts3 = 0;\n#ifndef N2P2_NO_SF_CACHE\n                    // Neighbor.cache\n                    ts3 = 0;\n                    MPI_Unpack(buf, bs, &p, &ts3, 1, MPI_SIZE_T, comm);\n                    if (ts3 > 0)\n                    {\n                        it2->cache.clear();\n                        it2->cache.resize(ts3, 0.0);\n                        MPI_Unpack(buf, bs, &p, &(it2->cache.front()), ts3, MPI_DOUBLE, comm);\n                    }\n#endif\n\n                    // Neighbor.dGdr\n                    ts3 = 0;\n                    MPI_Unpack(buf, bs, &p, &ts3, 1, MPI_SIZE_T, comm);\n                    if (ts3 > 0)\n                    {\n                        it2->dGdr.clear();\n                        it2->dGdr.resize(ts3);\n                        for (vector<Vec3D>::iterator it3 = it2->dGdr.begin();\n                             it3 != it2->dGdr.end(); ++it3)\n                        {\n                            MPI_Unpack(buf, bs, &p, it3->r, 3, MPI_DOUBLE, comm);\n                        }\n                    }\n                }\n            }\n        }\n    }\n\n    delete[] buf;\n\n    return bs;\n}\n\nsize_t Dataset::getNumStructures(ifstream& dataFile)\n{\n    size_t count = 0;\n    string line;\n    vector<string> splitLine;\n\n    while (getline(dataFile, line))\n    {\n        splitLine = split(reduce(line));\n        if (!splitLine.empty() && splitLine.at(0) == \"begin\") count++;\n    }\n\n    return count;\n}\n\nint Dataset::distributeStructures(bool          randomize,\n                                  bool          excludeRank0,\n                                  string const& fileName)\n{\n    log << \"\\n\";\n    log << \"*** STRUCTURE DISTRIBUTION **************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    ifstream dataFile;\n    vector<size_t> numStructuresPerProc;\n\n    if (excludeRank0)\n    {\n        log << \"No structures will be distributed to rank 0.\\n\";\n        if (numProcs == 1)\n        {\n            throw runtime_error(\"ERROR: Can not distribute structures, \"\n                                \"at least 2 MPI tasks are required.\\n\");\n        }\n    }\n    size_t numReceivers = numProcs;\n    if (excludeRank0) numReceivers--;\n\n    if (myRank == 0)\n    {\n        log << strpr(\"Reading configurations from data file: %s.\\n\",\n                     fileName.c_str());\n        dataFile.open(fileName.c_str());\n        numStructures = getNumStructures(dataFile);\n        log << strpr(\"Total number of structures: %zu\\n\", numStructures);\n        dataFile.clear();\n        dataFile.seekg(0);\n    }\n    MPI_Bcast(&numStructures, 1, MPI_SIZE_T, 0, comm);\n    if (numStructures < numReceivers)\n    {\n        throw runtime_error(\"ERROR: More receiving processors than \"\n                            \"structures.\\n\");\n    }\n\n    numStructuresPerProc.resize(numProcs, 0);\n    if (myRank == 0)\n    {\n        size_t quotient = numStructures / numReceivers;\n        size_t remainder = numStructures % numReceivers;\n        for (size_t i = 0; i < (size_t) numProcs; i++)\n        {\n            if (i != 0 || (!excludeRank0))\n            {\n                numStructuresPerProc.at(i) = quotient;\n                if (remainder > 0 && i > 0 && i <= remainder)\n                {\n                    numStructuresPerProc.at(i)++;\n                }\n            }\n        }\n        if (remainder == 0)\n        {\n            log << strpr(\"Number of structures per processor: %d\\n\", quotient);\n        }\n        else\n        {\n            log << strpr(\"Number of structures per\"\n                         \" processor: %d (%d) or %d (%d)\\n\",\n                         quotient,\n                         numReceivers - remainder,\n                         quotient + 1,\n                         remainder);\n        }\n    }\n    MPI_Bcast(&(numStructuresPerProc.front()), numProcs, MPI_SIZE_T, 0, comm);\n\n    int bytesTransferred = 0;\n    size_t numMyStructures = numStructuresPerProc.at(myRank);\n    if (myRank == 0)\n    {\n        size_t countStructures = 0;\n        vector<size_t> countStructuresPerProc;\n\n        countStructuresPerProc.resize(numProcs, 0);\n\n        if (randomize)\n        {\n            while (countStructures < numStructures)\n            {\n                int proc = gsl_rng_uniform_int(rng, numProcs);\n                if (countStructuresPerProc.at(proc)\n                    < numStructuresPerProc.at(proc))\n                {\n                    if (proc == 0)\n                    {\n                        structures.push_back(Structure());\n                        structures.back().setElementMap(elementMap);\n                        structures.back().index = countStructures;\n                        structures.back().readFromFile(dataFile);\n                        removeEnergyOffset(structures.back());\n                    }\n                    else\n                    {\n                        Structure tmpStructure;\n                        tmpStructure.setElementMap(elementMap);\n                        tmpStructure.index = countStructures;\n                        tmpStructure.readFromFile(dataFile);\n                        removeEnergyOffset(tmpStructure);\n                        bytesTransferred += sendStructure(tmpStructure, proc);\n                    }\n                    countStructuresPerProc.at(proc)++;\n                    countStructures++;\n                }\n            }\n        }\n        else\n        {\n            for (int proc = 0; proc < numProcs; ++proc)\n            {\n                for (size_t i = 0; i < numStructuresPerProc.at(proc); ++i)\n                {\n                    if (proc == 0)\n                    {\n                        structures.push_back(Structure());\n                        structures.back().setElementMap(elementMap);\n                        structures.back().index = countStructures;\n                        structures.back().readFromFile(dataFile);\n                        removeEnergyOffset(structures.back());\n                    }\n                    else\n                    {\n                        Structure tmpStructure;\n                        tmpStructure.setElementMap(elementMap);\n                        tmpStructure.index = countStructures;\n                        tmpStructure.readFromFile(dataFile);\n                        removeEnergyOffset(tmpStructure);\n                        bytesTransferred += sendStructure(tmpStructure, proc);\n                    }\n                    countStructuresPerProc.at(proc)++;\n                    countStructures++;\n                }\n            }\n        }\n        dataFile.close();\n    }\n    else\n    {\n        for (size_t i = 0; i < numMyStructures; i++)\n        {\n            structures.push_back(Structure());\n            structures.back().setElementMap(elementMap);\n            bytesTransferred += recvStructure(&(structures.back()), 0);\n        }\n    }\n\n    log << strpr(\"Distributed %zu structures,\"\n                 \" %d bytes (%.2f MiB) transferred.\\n\",\n                 numStructures,\n                 bytesTransferred,\n                 bytesTransferred / 1024. / 1024.);\n    log << strpr(\"Number of local structures: %zu\\n\", structures.size());\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return bytesTransferred;\n}\n\nsize_t Dataset::prepareNumericForces(Structure& original, double delta)\n{\n    // Be sure that structure memory is cleared.\n    vector<Structure>().swap(structures);\n\n    // Send original to all processors.\n    for (int p = 1; p < numProcs; ++p)\n    {\n        if (myRank == 0) sendStructure(original, p);\n        else if (myRank == p) recvStructure(&original, 0);\n    }\n\n    vector<size_t> numStructuresPerProc(numProcs, 0);\n    // Number of structures that need to be calculated:\n    // - Original structure +\n    // - Two times for each force component.\n    numStructures = 1 + 6 * original.numAtoms;\n    size_t quotient = numStructures / numProcs;\n    size_t remainder = numStructures % numProcs;\n    for (size_t i = 0; i < (size_t) numProcs; i++)\n    {\n        numStructuresPerProc.at(i) = quotient;\n        if (remainder > 0 && i < remainder) numStructuresPerProc.at(i)++;\n    }\n\n    // Rank 0 needs an unaltered version.\n    if (myRank == 0)\n    {\n        structures.push_back(original);\n        structures.back().setElementMap(elementMap);\n        structures.back().comment = \"original\";\n    }\n    // Now make as many copies as each processor needs.\n    size_t count = 0;\n    size_t iAtom = 0;\n    size_t ixyz = 0;\n    int sign = 0;\n    for (int p = 0; p < numProcs; ++p)\n    {\n        size_t istart = 0;\n        if (p == 0) istart = 1;\n        for (size_t i = istart; i < numStructuresPerProc.at(p); ++i)\n        {\n            iAtom = count / 6;\n            ixyz = count % 3;\n            sign = 2 * ((count % 6) / 3) - 1;\n            if (p == myRank)\n            {\n                structures.push_back(original);\n                Structure& s = structures.back();\n                s.setElementMap(elementMap);\n                // Write identifiers to comment field.\n                s.comment = strpr(\"%zu %zu %zu %d\", count, iAtom, ixyz, sign);\n                // Modify atom position.\n                s.atoms.at(iAtom).r[ixyz] += sign * delta;\n                if (s.isPeriodic) s.remap(s.atoms.at(iAtom));\n            }\n            count++;\n        }\n    }\n\n    return numStructures;\n}\n\nvoid Dataset::toNormalizedUnits()\n{\n    for (vector<Structure>::iterator it = structures.begin();\n         it != structures.end(); ++it)\n    {\n        it->toNormalizedUnits(meanEnergy, convEnergy, convLength, convCharge);\n    }\n\n    return;\n}\n\nvoid Dataset::toPhysicalUnits()\n{\n    for (vector<Structure>::iterator it = structures.begin();\n         it != structures.end(); ++it)\n    {\n        it->toPhysicalUnits(meanEnergy, convEnergy, convLength, convCharge);\n    }\n\n    return;\n}\n\nvoid Dataset::collectSymmetryFunctionStatistics()\n{\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        // If no atoms of this element exist on this proc, create empty\n        // statistics.\n        if (it->statistics.data.size() == 0)\n        {\n            log << strpr(\"WARNING: No statistics for element %zu (%2s) found, \"\n                         \"process %d has no corresponding atoms, creating \"\n                         \"empty statistics.\\n\",\n                         it->getIndex(),\n                         it->getSymbol().c_str(),\n                         myRank);\n        }\n        for (size_t i = 0; i < it->numSymmetryFunctions(); ++i)\n        {\n            SymFncStatistics::Container& c = it->statistics.data[i];\n            MPI_Allreduce(MPI_IN_PLACE, &(c.count), 1, MPI_SIZE_T, MPI_SUM, comm);\n            MPI_Allreduce(MPI_IN_PLACE, &(c.min  ), 1, MPI_DOUBLE, MPI_MIN, comm);\n            MPI_Allreduce(MPI_IN_PLACE, &(c.max  ), 1, MPI_DOUBLE, MPI_MAX, comm);\n            MPI_Allreduce(MPI_IN_PLACE, &(c.sum  ), 1, MPI_DOUBLE, MPI_SUM, comm);\n            MPI_Allreduce(MPI_IN_PLACE, &(c.sum2 ), 1, MPI_DOUBLE, MPI_SUM, comm);\n        }\n    }\n\n    return;\n}\n\nvoid Dataset::writeSymmetryFunctionScaling(string const& fileName)\n{\n    log << \"\\n\";\n    log << \"*** SYMMETRY FUNCTION SCALING ***********\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    if (myRank == 0)\n    {\n        log << strpr(\"Writing symmetry function scaling file: %s.\\n\",\n                     fileName.c_str());\n        ofstream sFile;\n        sFile.open(fileName.c_str());\n\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Symmetry function scaling data.\");\n        colSize.push_back(10);\n        colName.push_back(\"e_index\");\n        colInfo.push_back(\"Element index.\");\n        colSize.push_back(10);\n        colName.push_back(\"sf_index\");\n        colInfo.push_back(\"Symmetry function index.\");\n        colSize.push_back(24);\n        colName.push_back(\"sf_min\");\n        colInfo.push_back(\"Symmetry function minimum.\");\n        colSize.push_back(24);\n        colName.push_back(\"sf_max\");\n        colInfo.push_back(\"Symmetry function maximum.\");\n        colSize.push_back(24);\n        colName.push_back(\"sf_mean\");\n        colInfo.push_back(\"Symmetry function mean.\");\n        colSize.push_back(24);\n        colName.push_back(\"sf_sigma\");\n        colInfo.push_back(\"Symmetry function sigma.\");\n        appendLinesToFile(sFile,\n                          createFileHeader(title, colSize, colName, colInfo));\n\n        log << \"\\n\";\n        log << \"Abbreviations:\\n\";\n        log << \"--------------\\n\";\n        log << \"ind ...... Symmetry function index.\\n\";\n        log << \"min ...... Minimum symmetry function value.\\n\";\n        log << \"max ...... Maximum symmetry function value.\\n\";\n        log << \"mean ..... Mean symmetry function value.\\n\";\n        log << \"sigma .... Standard deviation of symmetry function values.\\n\";\n        log << \"spread ... (max - min) / sigma.\\n\";\n        log << \"\\n\";\n        for (vector<Element>::const_iterator it = elements.begin();\n             it != elements.end(); ++it)\n        {\n            log << strpr(\"Scaling data for symmetry functions element %2s :\\n\",\n                         it->getSymbol().c_str());\n            log << \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n            log << \" ind       min       max      mean     sigma    spread\\n\";\n            log << \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n            for (size_t i = 0; i < it->numSymmetryFunctions(); ++i)\n            {\n                SymFncStatistics::Container const& c\n                    = it->statistics.data.at(i);\n                size_t n = c.count;\n                double const mean = c.sum / n;\n                double const sigma = sqrt((c.sum2 - c.sum * c.sum / n)\n                                          / (n - 1));\n                double const spread = (c.max - c.min) / sigma;\n                sFile << strpr(\"%10d %10d %24.16E %24.16E %24.16E %24.16E\\n\",\n                               it->getIndex() + 1,\n                               i + 1,\n                               c.min,\n                               c.max,\n                               mean,\n                               sigma);\n                log << strpr(\"%4zu %9.2E %9.2E %9.2E %9.2E %9.2E\\n\",\n                             i + 1,\n                             c.min,\n                             c.max,\n                             mean,\n                             sigma,\n                             spread);\n            }\n            log << \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n        }\n        // Finally decided to remove this legacy line...\n        //sFile << strpr(\"%f %f\\n\", 0.0, 0.0);\n        sFile.close();\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Dataset::writeSymmetryFunctionHistograms(size_t numBins,\n                                              string fileNameFormat)\n{\n    log << \"\\n\";\n    log << \"*** SYMMETRY FUNCTION HISTOGRAMS ********\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    // Initialize histograms.\n    numBins--;\n    vector<vector<gsl_histogram*> > histograms;\n    for (vector<Element>::const_iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        histograms.push_back(vector<gsl_histogram*>());\n        for (size_t i = 0; i < it->numSymmetryFunctions(); ++i)\n        {\n            double l = safeFind(it->statistics.data, i).min;\n            double h = safeFind(it->statistics.data, i).max;\n            if (l < h)\n            {\n                // Add an extra bin at the end to cover complete range.\n                h += (h - l) / numBins;\n                histograms.back().push_back(gsl_histogram_alloc(numBins + 1));\n                gsl_histogram_set_ranges_uniform(histograms.back().back(),\n                                                 l,\n                                                 h);\n            }\n            else\n            {\n                // Use nullptr so signalize non-existing histogram.\n                histograms.back().push_back(nullptr);\n                log << strpr(\"WARNING: Symmetry function min equals max, \"\n                             \"ommitting histogram (Element %2s SF %4zu \"\n                             \"(line %4zu).\\n\",\n                             it->getSymbol().c_str(),\n                             i,\n                             it->getSymmetryFunction(i).getLineNumber() + 1);\n            }\n        }\n    }\n\n    // Increment histograms with symmetry function values.\n    for (vector<Structure>::const_iterator it = structures.begin();\n         it != structures.end(); ++it)\n    {\n        for (vector<Atom>::const_iterator it2 = it->atoms.begin();\n             it2 != it->atoms.end(); ++it2)\n        {\n            size_t e = it2->element;\n            vector<gsl_histogram*>& h = histograms.at(e);\n            for (size_t s = 0; s < it2->G.size(); ++s)\n            {\n                if (h.at(s) == nullptr) continue;\n                gsl_histogram_increment(h.at(s), it2->G.at(s));\n            }\n        }\n    }\n\n    // Collect histograms from all processes.\n    for (vector<vector<gsl_histogram*> >::const_iterator it =\n         histograms.begin(); it != histograms.end(); ++it)\n    {\n        for (vector<gsl_histogram*>::const_iterator it2 = it->begin();\n             it2 != it->end(); ++it2)\n        {\n            if ((*it2) == nullptr) continue;\n            MPI_Allreduce(MPI_IN_PLACE, (*it2)->bin, numBins + 1, MPI_DOUBLE, MPI_SUM, comm);\n        }\n    }\n\n    // Write histogram to file.\n    if (myRank == 0)\n    {\n        log << strpr(\"Writing histograms with %zu bins.\\n\", numBins + 1);\n        for (size_t e = 0; e < elements.size(); ++e)\n        {\n            for (size_t s = 0; s < elements.at(e).numSymmetryFunctions(); ++s)\n            {\n                gsl_histogram*& h = histograms.at(e).at(s);\n                if (h == nullptr) continue;\n                FILE* fp = 0;\n                string fileName = strpr(fileNameFormat.c_str(),\n                                        elementMap.atomicNumber(e),\n                                        s + 1);\n                fp = fopen(fileName.c_str(), \"w\");\n                if (fp == 0)\n                {\n                    throw runtime_error(strpr(\"ERROR: Could not open file:\"\n                                              \" %s.\\n\", fileName.c_str()));\n                }\n                vector<string> info = elements.at(e).infoSymmetryFunction(s);\n                for (vector<string>::const_iterator it = info.begin();\n                     it != info.end(); ++it)\n                {\n                    fprintf(fp, \"#SFINFO %s\\n\", it->c_str());\n                }\n                SymFncStatistics::Container const& c\n                    = elements.at(e).statistics.data.at(s);\n                size_t n = c.count;\n                fprintf(fp, \"#SFINFO min         %15.8E\\n\", c.min);\n                fprintf(fp, \"#SFINFO max         %15.8E\\n\", c.max);\n                fprintf(fp, \"#SFINFO mean        %15.8E\\n\", c.sum / n);\n                fprintf(fp, \"#SFINFO sigma       %15.8E\\n\",\n                        sqrt(1.0 / (n - 1) * (c.sum2 - c.sum * c.sum / n)));\n\n                // File header.\n                vector<string> title;\n                vector<string> colName;\n                vector<string> colInfo;\n                vector<size_t> colSize;\n                title.push_back(\"Symmetry function histogram.\");\n                colSize.push_back(16);\n                colName.push_back(\"symfunc_l\");\n                colInfo.push_back(\"Symmetry function value, left bin limit.\");\n                colSize.push_back(16);\n                colName.push_back(\"symfunc_r\");\n                colInfo.push_back(\"Symmetry function value, right bin limit.\");\n                colSize.push_back(16);\n                colName.push_back(\"hist\");\n                colInfo.push_back(\"Histogram count.\");\n                appendLinesToFile(fp,\n                                  createFileHeader(title,\n                                                   colSize,\n                                                   colName,\n                                                   colInfo));\n\n                gsl_histogram_fprintf(fp, h, \"%16.8E\", \"%16.8E\");\n                fflush(fp);\n                fclose(fp);\n                fp = 0;\n            }\n        }\n    }\n\n    for (vector<vector<gsl_histogram*> >::const_iterator it =\n         histograms.begin(); it != histograms.end(); ++it)\n    {\n        for (vector<gsl_histogram*>::const_iterator it2 = it->begin();\n             it2 != it->end(); ++it2)\n        {\n            if ((*it2) == nullptr) continue;\n            gsl_histogram_free(*it2);\n        }\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Dataset::writeSymmetryFunctionFile(string fileName)\n{\n    log << \"\\n\";\n    log << \"*** SYMMETRY FUNCTION FILE **************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    // Create empty file.\n    log << strpr(\"Writing symmetry functions to file: %s\\n\", fileName.c_str());\n    if (myRank == 0)\n    {\n        ofstream file;\n        file.open(fileName.c_str());\n        file.close();\n    }\n    MPI_Barrier(comm);\n\n    // Prepare structure iterator.\n    vector<Structure>::const_iterator it = structures.begin();\n    // Loop over all structures (on each proc the local structures are stored\n    // with increasing index).\n    for (size_t i = 0; i < numStructures; ++i)\n    {\n        // If this proc holds structure with matching index,\n        // open file and write symmetry functions.\n        if (it != structures.end() && i == it->index)\n        {\n            ofstream file;\n            file.open(fileName.c_str(), ios_base::app);\n            file << strpr(\"%6zu\\n\", it->numAtoms);\n            // Loop over atoms.\n            for (vector<Atom>::const_iterator it2 = it->atoms.begin();\n                 it2 != it->atoms.end(); ++it2)\n            {\n                // Loop over symmetry functions.\n                file << strpr(\"%3zu \", elementMap.atomicNumber(it2->element));\n                for (vector<double>::const_iterator it3 = it2->G.begin();\n                     it3 != it2->G.end(); ++it3)\n                {\n                    file << strpr(\" %14.10f\", *it3);\n                }\n                file << '\\n';\n            }\n            // There is no charge NN, so first and last entry is zero.\n            double energy = 0.0;\n            if (normalize) energy = physicalEnergy(*it);\n            else energy = it->energyRef;\n            energy += getEnergyOffset(*it);\n            energy /= it->numAtoms;\n            file << strpr(\" %19.10f %19.10f %19.10f %19.10f\\n\",\n                          0.0, energy, energy, 0.0);\n            file.flush();\n            file.close();\n            // Iterate to next structure.\n            ++it;\n        }\n        MPI_Barrier(comm);\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nsize_t Dataset::writeNeighborHistogram(string const& fileNameHisto,\n                                       string const& fileNameStructure)\n{\n    log << \"\\n\";\n    log << \"*** NEIGHBOR STATISTICS/HISTOGRAM *******\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    ofstream statFile;\n    string fileNameLocal = strpr(\"%s.%04d\", fileNameStructure.c_str(), myRank);\n    statFile.open(fileNameLocal.c_str());\n    if (myRank == 0)\n    {\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Neighbor statistics for each structure.\");\n        colSize.push_back(10);\n        colName.push_back(\"struct\");\n        colInfo.push_back(\"Index of structure (starting with 1).\");\n        colSize.push_back(10);\n        colName.push_back(\"natoms\");\n        colInfo.push_back(\"Number of atoms in structure.\");\n        colSize.push_back(10);\n        colName.push_back(\"min\");\n        colInfo.push_back(\"Minimum number of neighbors over all atoms.\");\n        colSize.push_back(10);\n        colName.push_back(\"max\");\n        colInfo.push_back(\"Maximum number of neighbors over all atoms.\");\n        colSize.push_back(16);\n        colName.push_back(\"mean\");\n        colInfo.push_back(\"Mean number of neighbors over all atoms.\");\n        appendLinesToFile(statFile,\n                          createFileHeader(title, colSize, colName, colInfo));\n    }\n\n    // Compute per-structure statistics and prepare histogram boundaries.\n    size_t numAtomsGlobal = 0;\n    size_t minNeighborsGlobal = numeric_limits<size_t>::max();\n    size_t maxNeighborsGlobal = 0;\n    double meanNeighborsGlobal = 0.0;\n    for (auto const& s : structures)\n    {\n    size_t minNeighbors = numeric_limits<size_t>::max();\n    size_t maxNeighbors = 0;\n    double meanNeighbors = 0.0;\n        for (auto const& a : s.atoms)\n    {\n            size_t const n = a.numNeighbors;\n            minNeighbors = min(minNeighbors, n);\n            maxNeighbors = max(maxNeighbors, n);\n            meanNeighbors += n;\n        }\n        numAtomsGlobal += s.numAtoms;\n        minNeighborsGlobal = min(minNeighborsGlobal, minNeighbors);\n        maxNeighborsGlobal = max(maxNeighborsGlobal, maxNeighbors);\n        meanNeighborsGlobal += meanNeighbors;\n        statFile << strpr(\"%10zu %10zu %10zu %10zu %16.8E\\n\",\n                          s.index + 1,\n                          s.numAtoms,\n                          minNeighbors,\n                          maxNeighbors,\n                          meanNeighbors / s.numAtoms);\n    }\n    statFile.flush();\n    statFile.close();\n    MPI_Allreduce(MPI_IN_PLACE, &numAtomsGlobal     , 1, MPI_SIZE_T, MPI_SUM, comm);\n    MPI_Allreduce(MPI_IN_PLACE, &minNeighborsGlobal , 1, MPI_SIZE_T, MPI_MIN, comm);\n    MPI_Allreduce(MPI_IN_PLACE, &maxNeighborsGlobal , 1, MPI_SIZE_T, MPI_MAX, comm);\n    MPI_Allreduce(MPI_IN_PLACE, &meanNeighborsGlobal, 1, MPI_DOUBLE, MPI_SUM, comm);\n    log << strpr(\"Minimum number of neighbors: %d\\n\", minNeighborsGlobal);\n    log << strpr(\"Mean    number of neighbors: %.1f\\n\",\n                 meanNeighborsGlobal / numAtomsGlobal);\n    log << strpr(\"Maximum number of neighbors: %d\\n\", maxNeighborsGlobal);\n\n    // Calculate neighbor histogram.\n    gsl_histogram* histNeighbors = NULL;\n    histNeighbors = gsl_histogram_alloc(maxNeighborsGlobal + 1);\n    gsl_histogram_set_ranges_uniform(histNeighbors,\n                                     -0.5,\n                                     maxNeighborsGlobal + 0.5);\n    for (vector<Structure>::const_iterator it = structures.begin();\n         it != structures.end(); ++it)\n    {\n        for (vector<Atom>::const_iterator it2 = it->atoms.begin();\n             it2 != it->atoms.end(); ++it2)\n        {\n            gsl_histogram_increment(histNeighbors, it2->numNeighbors);\n        }\n    }\n    MPI_Allreduce(MPI_IN_PLACE, histNeighbors->bin, maxNeighborsGlobal + 1, MPI_DOUBLE, MPI_SUM, comm);\n\n    // Write histogram to file.\n    if (myRank == 0)\n    {\n        log << strpr(\"Neighbor histogram file: %s.\\n\", fileNameHisto.c_str());\n        FILE* fp = 0;\n        fp = fopen(fileNameHisto.c_str(), \"w\");\n        if (fp == 0)\n        {\n            throw runtime_error(strpr(\"ERROR: Could not open file: %s.\\n\",\n                                      fileNameHisto.c_str()));\n        }\n\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Neighbor count histogram.\");\n        colSize.push_back(9);\n        colName.push_back(\"neigh_l\");\n        colInfo.push_back(\"Number of neighbors, left bin limit.\");\n        colSize.push_back(9);\n        colName.push_back(\"neigh_r\");\n        colInfo.push_back(\"Number of neighbors, right bin limit.\");\n        colSize.push_back(16);\n        colName.push_back(\"hist\");\n        colInfo.push_back(\"Histogram count.\");\n        appendLinesToFile(fp,\n                          createFileHeader(title, colSize, colName, colInfo));\n\n        gsl_histogram_fprintf(fp, histNeighbors, \"%9.1f\", \"%16.8E\");\n        fflush(fp);\n        fclose(fp);\n        fp = 0;\n    }\n\n    MPI_Barrier(comm);\n    if (myRank == 0)\n    {\n        log << strpr(\"Combining per-structure neighbor statistics file: %s.\\n\",\n                     fileNameStructure.c_str());\n        combineFiles(fileNameStructure);\n    }\n\n    gsl_histogram_free(histNeighbors);\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return maxNeighborsGlobal;\n}\n\nvoid Dataset::sortNeighborLists()\n{\n    log << \"\\n\";\n    log << \"*** NEIGHBOR LIST ***********************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << \"Sorting neighbor lists according to element and distance.\\n\";\n\n    for (vector<Structure>::iterator it = structures.begin();\n         it != structures.end(); ++it)\n    {\n        for (vector<Atom>::iterator it2 = it->atoms.begin();\n             it2 != it->atoms.end(); ++it2)\n        {\n            sort(it2->neighbors.begin(), it2->neighbors.end());\n        }\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\nvoid Dataset::writeNeighborLists(string const& fileName)\n{\n    log << \"\\n\";\n    log << \"*** NEIGHBOR LIST ***********************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    string fileNameLocal = strpr(\"%s.%04d\", fileName.c_str(), myRank);\n    ofstream fileLocal;\n    fileLocal.open(fileNameLocal.c_str());\n\n    for (vector<Structure>::const_iterator it = structures.begin();\n         it != structures.end(); ++it)\n    {\n        fileLocal << strpr(\"%zu\\n\", it->numAtoms);\n        for (vector<Atom>::const_iterator it2 = it->atoms.begin();\n             it2 != it->atoms.end(); ++it2)\n        {\n            fileLocal << strpr(\"%zu\", elementMap.atomicNumber(it2->element));\n            for (size_t i = 0; i < numElements; ++i)\n            {\n                fileLocal << strpr(\" %zu\", it2->numNeighborsPerElement.at(i));\n            }\n            for (vector<Atom::Neighbor>::const_iterator it3\n                 = it2->neighbors.begin(); it3 != it2->neighbors.end(); ++it3)\n            {\n                fileLocal << strpr(\" %zu\", it3->index);\n            }\n            fileLocal << '\\n';\n        }\n    }\n\n    fileLocal.flush();\n    fileLocal.close();\n    MPI_Barrier(comm);\n\n    log << strpr(\"Writing neighbor lists to file: %s.\\n\", fileName.c_str());\n\n    if (myRank == 0) combineFiles(fileName);\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Dataset::writeAtomicEnvironmentFile(\n                                        vector<vector<size_t> > neighCutoff,\n                                        bool                    derivatives,\n                                        string const&           fileNamePrefix)\n{\n    log << \"\\n\";\n    log << \"*** ATOMIC ENVIRONMENT ******************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    string const fileNamePrefixG    = strpr(\"%s.G\"   , fileNamePrefix.c_str());\n    string const fileNamePrefixdGdx = strpr(\"%s.dGdx\", fileNamePrefix.c_str());\n    string const fileNamePrefixdGdy = strpr(\"%s.dGdy\", fileNamePrefix.c_str());\n    string const fileNamePrefixdGdz = strpr(\"%s.dGdz\", fileNamePrefix.c_str());\n\n    string const fileNameLocalG    = strpr(\"%s.%04d\",\n                                           fileNamePrefixG.c_str(), myRank);\n    string const fileNameLocaldGdx = strpr(\"%s.%04d\",\n                                           fileNamePrefixdGdx.c_str(), myRank);\n    string const fileNameLocaldGdy = strpr(\"%s.%04d\",\n                                           fileNamePrefixdGdy.c_str(), myRank);\n    string const fileNameLocaldGdz = strpr(\"%s.%04d\",\n                                           fileNamePrefixdGdz.c_str(), myRank);\n\n    ofstream fileLocalG;\n    ofstream fileLocaldGdx;\n    ofstream fileLocaldGdy;\n    ofstream fileLocaldGdz;\n\n    fileLocalG.open(fileNameLocalG.c_str());\n    if (derivatives)\n    {\n        fileLocaldGdx.open(fileNameLocaldGdx.c_str());\n        fileLocaldGdy.open(fileNameLocaldGdy.c_str());\n        fileLocaldGdz.open(fileNameLocaldGdz.c_str());\n    }\n\n    log << \"Preparing symmetry functions for atomic environment file(s).\\n\";\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        for (size_t j = 0; j < numElements; ++j)\n        {\n            log << strpr(\"Maximum number of %2s neighbors for central %2s \"\n                         \"atoms: %zu\\n\",\n                         elementMap[j].c_str(),\n                         elementMap[i].c_str(),\n                         neighCutoff.at(i).at(j));\n        }\n    }\n\n    vector<size_t> neighCount(numElements, 0);\n    for (vector<Structure>::const_iterator its = structures.begin();\n         its != structures.end(); ++its)\n    {\n        for (vector<Atom>::const_iterator ita = its->atoms.begin();\n             ita != its->atoms.end(); ++ita)\n        {\n            size_t const ea = ita->element;\n            for (size_t i = 0; i < numElements; ++i)\n            {\n                if (ita->numNeighborsPerElement.at(i)\n                    < neighCutoff.at(ea).at(i))\n                {\n                    throw runtime_error(strpr(\n                        \"ERROR: Not enough neighbor atoms, cannot create \"\n                        \"atomic environment file. Reduce neighbor cutoff for \"\n                        \"element %2s.\\n\", elementMap[i].c_str()).c_str());\n                }\n            }\n            fileLocalG << strpr(\"%2s\", elementMap[ita->element].c_str());\n            fileLocaldGdx << strpr(\"%2s\", elementMap[ita->element].c_str());\n            fileLocaldGdy << strpr(\"%2s\", elementMap[ita->element].c_str());\n            fileLocaldGdz << strpr(\"%2s\", elementMap[ita->element].c_str());\n            // Write atom's own symmetry functions (and derivatives).\n            for (vector<double>::const_iterator it = ita->G.begin();\n                 it != ita->G.end(); ++it)\n            {\n                fileLocalG << strpr(\" %16.8E\", (*it));\n            }\n            if (derivatives)\n            {\n                for (vector<Vec3D>::const_iterator it = ita->dGdr.begin();\n                     it != ita->dGdr.end(); ++it)\n                {\n                    fileLocaldGdx << strpr(\" %16.8E\", (*it)[0]);\n                    fileLocaldGdy << strpr(\" %16.8E\", (*it)[1]);\n                    fileLocaldGdz << strpr(\" %16.8E\", (*it)[2]);\n                }\n            }\n            // Write symmetry functions of neighbors\n            for (vector<Atom::Neighbor>::const_iterator itn\n                 = ita->neighbors.begin(); itn != ita->neighbors.end(); ++itn)\n            {\n                size_t const i = itn->index;\n                size_t const en = itn->element;\n                if (neighCount.at(en) < neighCutoff.at(ea).at(en))\n                {\n                    // Look up symmetry function at Atom instance of neighbor.\n                    Atom const& a = its->atoms.at(i);\n                    for (vector<double>::const_iterator it = a.G.begin();\n                         it != a.G.end(); ++it)\n                    {\n                        fileLocalG << strpr(\" %16.8E\", (*it));\n                    }\n                    // Log derivatives directly from Neighbor instance.\n                    if (derivatives)\n                    {\n                        // Find atom in neighbor list of neighbor atom.\n                        vector<Atom::Neighbor>::const_iterator itan = find_if(\n                            a.neighbors.begin(), a.neighbors.end(),\n                            [&ita](Atom::Neighbor const& n)\n                            {\n                                return n.index == ita->index;\n                            });\n                        for (vector<Vec3D>::const_iterator it\n                             = itan->dGdr.begin();\n                             it != itan->dGdr.end(); ++it)\n                        {\n                            fileLocaldGdx << strpr(\" %16.8E\", (*it)[0]);\n                            fileLocaldGdy << strpr(\" %16.8E\", (*it)[1]);\n                            fileLocaldGdz << strpr(\" %16.8E\", (*it)[2]);\n                        }\n                    }\n                    neighCount.at(en)++;\n                }\n            }\n            fileLocalG << '\\n';\n            if (derivatives)\n            {\n                fileLocaldGdx << '\\n';\n                fileLocaldGdy << '\\n';\n                fileLocaldGdz << '\\n';\n            }\n            // Reset neighbor counter.\n            fill(neighCount.begin(), neighCount.end(), 0);\n        }\n    }\n\n    fileLocalG.flush();\n    fileLocalG.close();\n    if (derivatives)\n    {\n        fileLocaldGdx.flush();\n        fileLocaldGdx.close();\n        fileLocaldGdy.flush();\n        fileLocaldGdy.close();\n        fileLocaldGdz.flush();\n        fileLocaldGdz.close();\n    }\n    MPI_Barrier(comm);\n\n    if (myRank == 0)\n    {\n        log << strpr(\"Combining atomic environment file: %s.\\n\",\n                     fileNamePrefixG.c_str());\n        combineFiles(fileNamePrefixG);\n        if (derivatives)\n        {\n            log << strpr(\"Combining atomic environment file: %s.\\n\",\n                         fileNamePrefixdGdx.c_str());\n            combineFiles(fileNamePrefixdGdx);\n            log << strpr(\"Combining atomic environment file: %s.\\n\",\n                         fileNamePrefixdGdy.c_str());\n            combineFiles(fileNamePrefixdGdy);\n            log << strpr(\"Combining atomic environment file: %s.\\n\",\n                         fileNamePrefixdGdz.c_str());\n            combineFiles(fileNamePrefixdGdz);\n        }\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Dataset::collectError(string const&        property,\n                           map<string, double>& error,\n                           size_t&              count) const\n{\n    if (property == \"energy\")\n    {\n        MPI_Allreduce(MPI_IN_PLACE, &count               , 1, MPI_SIZE_T, MPI_SUM, comm);\n        MPI_Allreduce(MPI_IN_PLACE, &(error.at(\"RMSEpa\")), 1, MPI_DOUBLE, MPI_SUM, comm);\n        MPI_Allreduce(MPI_IN_PLACE, &(error.at(\"RMSE\"))  , 1, MPI_DOUBLE, MPI_SUM, comm);\n        MPI_Allreduce(MPI_IN_PLACE, &(error.at(\"MAEpa\")) , 1, MPI_DOUBLE, MPI_SUM, comm);\n        MPI_Allreduce(MPI_IN_PLACE, &(error.at(\"MAE\"))   , 1, MPI_DOUBLE, MPI_SUM, comm);\n        error.at(\"RMSEpa\") = sqrt(error.at(\"RMSEpa\") / count);\n        error.at(\"RMSE\") = sqrt(error.at(\"RMSE\") / count);\n        error.at(\"MAEpa\") = error.at(\"MAEpa\") / count;\n        error.at(\"MAE\") = error.at(\"MAE\") / count;\n    }\n    else if (property == \"force\" || property == \"charge\")\n    {\n        MPI_Allreduce(MPI_IN_PLACE, &count             , 1, MPI_SIZE_T, MPI_SUM, comm);\n        MPI_Allreduce(MPI_IN_PLACE, &(error.at(\"RMSE\")), 1, MPI_DOUBLE, MPI_SUM, comm);\n        MPI_Allreduce(MPI_IN_PLACE, &(error.at(\"MAE\")) , 1, MPI_DOUBLE, MPI_SUM, comm);\n        error.at(\"RMSE\") = sqrt(error.at(\"RMSE\") / count);\n        error.at(\"MAE\") = error.at(\"MAE\") / count;\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown property for error collection.\\n\");\n    }\n\n    return;\n}\n\nvoid Dataset::combineFiles(string filePrefix) const\n{\n    ofstream combinedFile(filePrefix.c_str(), ios::binary);\n    if (!combinedFile.is_open())\n    {\n        throw runtime_error(strpr(\"ERROR: Could not open file: %s.\\n\",\n                                  filePrefix.c_str()));\n    }\n    for (int i = 0; i < numProcs; ++i)\n    {\n        string procFileName = strpr(\"%s.%04d\", filePrefix.c_str(), i);\n        ifstream procFile(procFileName.c_str(), ios::binary);\n        if (!procFile.is_open())\n        {\n            throw runtime_error(strpr(\"ERROR: Could not open file: %s.\\n\",\n                                      procFileName.c_str()));\n        }\n        // If file is empty, do not get rdbuf, otherwise combined file will be\n        // closed!\n        if (procFile.peek() != ifstream::traits_type::eof())\n        {\n            combinedFile << procFile.rdbuf();\n        }\n        procFile.close();\n        remove(procFileName.c_str());\n    }\n    combinedFile.close();\n\n    return;\n}\n"
  },
  {
    "path": "src/libnnptrain/Dataset.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef DATASET_H\n#define DATASET_H\n\n#include <mpi.h>\n#include \"Mode.h\"\n#include \"Structure.h\"\n#include <cstddef> // std::size_t\n#include <fstream> // std::ifstream\n#include <map>     // std::map\n#include <string>  // std::string\n#include <vector>  // std::vector\n#include <gsl/gsl_rng.h>\n\nnamespace nnp\n{\n\n///Collect and process large data sets.\nclass Dataset : public Mode\n{\npublic:\n    /** Constructor, initialize members.\n     */\n    Dataset();\n    /** Destructor.\n     */\n    ~Dataset();\n    /** Initialize MPI with MPI_COMM_WORLD.\n     */\n    void        setupMPI();\n    /** Initialize MPI with given communicator.\n     *\n     * @param[in] communicator Provided communicator which should be used.\n     */\n    void        setupMPI(MPI_Comm* communicator);\n    /** Initialize random number generator.\n     *\n     * CAUTION: MPI communicator required, call #setupMPI() before!\n     */\n    void        setupRandomNumberGenerator();\n    /** Get number of structures in data file.\n     *\n     * @param[inout] dataFile Data file name.\n     *\n     * @return Number of structures.\n     */\n    std::size_t getNumStructures(std::ifstream& dataFile);\n    /** Calculate buffer size required to communicate structure via MPI\n     *\n     * @param[in] structure Input structure.\n     *\n     * @return Buffer size in bytes.\n     */\n    int         calculateBufferSize(Structure const& structure) const;\n    /** Send one structure to destination process.\n     *\n     * @param[in] structure Source structure.\n     * @param[in] dest MPI rank of destination process.\n     *\n     * @return Number of bytes sent.\n     */\n    int         sendStructure(Structure const& structure, int dest) const;\n    /** Receive one structure from source process.\n     *\n     * @param[in] structure Source structure.\n     * @param[in] src MPI rank of source process.\n     *\n     * @return Number of bytes received.\n     */\n    int         recvStructure(Structure* structure, int src);\n    /** Read data file and distribute structures among processors.\n     *\n     * @param[in] randomize If `true` randomly distribute structures, otherwise\n     *                      they are distributed in order.\n     * @param[in] excludeRank0 If `true` no structures are distributed to MPI\n     *                         process with rank 0.\n     * @param[in] fileName Data file name, e.g. \"input.data\".\n     *\n     * @return Number of bytes transferred.\n     */\n    int         distributeStructures(bool               randomize,\n                                     bool               excludeRank0 = false,\n                                     std::string const& fileName\n                                         = \"input.data\");\n    /** Prepare numeric force check for a single structure.\n     *\n     * @param[inout] original The structure under investigation.\n     * @param[in] delta Central difference delta for positions\n     *\n     * @return Number of structures distributed (= 1 + 6 * numAtoms).\n     *\n     * Distributes copies of original structure among all processors and\n     * modifies positions for central difference.\n     */\n    std::size_t prepareNumericForces(Structure& original, double delta);\n    /** Switch all structures to normalized units.\n     */\n    void        toNormalizedUnits();\n    /** Switch all structures to physical units.\n     */\n    void        toPhysicalUnits();\n    /** Collect symmetry function statistics from all processors.\n     */\n    void        collectSymmetryFunctionStatistics();\n    /** Write symmetry function scaling values to file.\n     *\n     * @param[in] fileName Scaling data file name (e.g. \"scaling.data\").\n     */\n    void        writeSymmetryFunctionScaling(std::string const& fileName\n                                                 = \"scaling.data\");\n    /** Calculate and write symmetry function histograms.\n     *\n     * @param[in] numBins Number of histogram bins used.\n     * @param[in] fileNameFormat Format for histogram file names, must include\n     *                           placeholders for element and symmetry function\n     *                           number.\n     */\n    void        writeSymmetryFunctionHistograms(std::size_t numBins,\n                                                std::string fileNameFormat\n                                                    = \"sf.%03zu.%04zu.histo\");\n    /** Write symmetry function legacy file (\"function.data\").\n     *\n     * @param[in] fileName File name for symmetry function file.\n     */\n    void        writeSymmetryFunctionFile(std::string fileName\n                                              = \"function.data\");\n    /** Calculate and write neighbor histogram and per-structure statistics.\n     *\n     * @param[in] fileNameHisto Name of histogram file.\n     * @param[in] fileNameStructure Name of per-structure file.\n     *\n     * @return Maximum number of neighbors.\n     */\n    std::size_t writeNeighborHistogram(std::string const& fileNameHisto\n                                           = \"neighbors.histo\",\n                                       std::string const& fileNameStructure\n                                           = \"neighbors.out\");\n    /** Sort all neighbor lists according to element and distance.\n     */\n    void        sortNeighborLists();\n    /** Write neighbor list file.\n     *\n     * @param[in] fileName Name for neighbor list file.\n     */\n    void        writeNeighborLists(std::string const& fileName\n                                       = \"neighbor-list.data\");\n    /** Write atomic environment file.\n     *\n     * @param[in] neighCutoff Maximum number of neighbor to consider (for each\n     *                        element combination).\n     * @param[in] derivatives If true, write separate files for derivates.\n     * @param[in] fileNamePrefix Prefix for atomic environment files.\n     *\n     * This file is used for symmetry function clustering analysis.\n     */\n    void        writeAtomicEnvironmentFile(\n                                        std::vector<std::vector<\n                                        std::size_t> >           neighCutoff,\n                                        bool                     derivatives,\n                                        std::string const &      fileNamePrefix\n                                             = \"atomic-env\");\n    /** Collect error metrics of a property over all MPI procs.\n     *\n     * @param[in] property One of \"energy\", \"force\" or \"charge\".\n     * @param[in,out] error Metric sums of this proc (in), global metric (out).\n     * @param[in,out] count Count for this proc (in), global count (out).\n     */\n    void        collectError(std::string const&             property,\n                             std::map<std::string, double>& error,\n                             std::size_t&                   count) const;\n    /** Combine individual MPI proc files to one.\n     *\n     * @param[in] filePrefix File prefix without the \".0001\" suffix.\n     *\n     * CAUTION: Make sure files are completely written and closed.\n     */\n    void        combineFiles(std::string filePrefix) const;\n\n    /// All structures in this dataset.\n    std::vector<Structure> structures;\n\nprotected:\n    /// My process ID.\n    int         myRank;\n    /// Total number of MPI processors.\n    int         numProcs;\n    /// Total number of structures in dataset.\n    std::size_t numStructures;\n    /// My processor name.\n    std::string myName;\n    /// Global MPI communicator.\n    MPI_Comm    comm;\n    /// GSL random number generator (different seed for each MPI process).\n    gsl_rng*    rng;\n    /// Global GSL random number generator (equal seed for each MPI process).\n    gsl_rng*    rngGlobal;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnptrain/GradientDescent.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"GradientDescent.h\"\n#include \"utility.h\"\n#include <cstddef>\n#include <cmath>\n\nusing namespace std;\nusing namespace nnp;\n\nGradientDescent::GradientDescent(size_t const      sizeState,\n                                 DescentType const type) :\n    Updater(sizeState),\n    eta     (0.0        ),\n    beta1   (0.0        ),\n    beta2   (0.0        ),\n    epsilon (0.0        ),\n    beta1t  (0.0        ),\n    beta2t  (0.0        ),\n    state   (NULL       ),\n    error   (NULL       ),\n    gradient(NULL       )\n{\n    if (!(type == DT_FIXED ||\n          type == DT_ADAM))\n    {\n        throw runtime_error(\"ERROR: Unknown GradientDescent type.\\n\");\n    }\n\n    if (sizeState < 1)\n    {\n        throw runtime_error(\"ERROR: Wrong GradientDescent dimensions.\\n\");\n    }\n\n    this->type = type;\n\n    if (type == DT_ADAM)\n    {\n        m.resize(sizeState, 0.0);\n        v.resize(sizeState, 0.0);\n    }\n}\n\nvoid GradientDescent::setState(double* state)\n{\n    this->state = state;\n\n    return;\n}\n\nvoid GradientDescent::setError(double const* const error,\n                               size_t const /* size */)\n{\n    this->error = error;\n\n    return;\n}\n\nvoid GradientDescent::setJacobian(double const* const jacobian,\n                                  size_t const        /* columns*/)\n{\n    this->gradient = jacobian;\n\n    return;\n}\n\nvoid GradientDescent::update()\n{\n    if (type == DT_FIXED)\n    {\n        for (std::size_t i = 0; i < sizeState; ++i)\n        {\n            state[i] -= eta * (*error) * -gradient[i];\n        }\n    }\n    else if (type == DT_ADAM)\n    {\n        for (std::size_t i = 0; i < sizeState; ++i)\n        {\n            double const g = (*error) * -gradient[i];\n            m[i] = beta1 * m[i] + (1.0 - beta1) * g;\n            v[i] = beta2 * v[i] + (1.0 - beta2) * g * g;\n\n            // Standard implementation\n            // (Algorithm 1 in publication).\n            //double const mhat = m[i] / (1.0 - beta1t);\n            //double const vhat = v[i] / (1.0 - beta2t);\n            //state[i] -= eta * mhat / (sqrt(vhat) + epsilon);\n            \n            // Faster (?) alternative\n            // (see last paragraph in Section 2 of publication).\n            // This is actually only marginally faster\n            // (less statements, but two sqrt() calls)!\n            eta = eta0 * sqrt(1 - beta2t) / (1 - beta1t); \n            state[i] -= eta * m[i] / (sqrt(v[i]) + epsilon);\n        }\n\n        // Update betas.\n        beta1t *= beta1;\n        beta2t *= beta2;\n    }\n\n    return;\n}\n\nvoid GradientDescent::setParametersFixed(double const eta)\n{\n    this->eta = eta;\n\n    return;\n}\n\nvoid GradientDescent::setParametersAdam(double const eta,\n                                        double const beta1,\n                                        double const beta2,\n                                        double const epsilon)\n{\n    this->eta     = eta;\n    this->beta1   = beta1;\n    this->beta2   = beta2;\n    this->epsilon = epsilon;\n\n    eta0   = eta;\n    beta1t = beta1;\n    beta2t = beta2;\n\n    return;\n}\n\nstring GradientDescent::status(size_t epoch) const\n{\n    string s = strpr(\"%10zu %16.8E\", epoch, eta);\n\n    if (type == DT_ADAM)\n    {\n        double meanm = 0.0;\n        double meanv = 0.0;\n        for (std::size_t i = 0; i < sizeState; ++i)\n        {\n            meanm += abs(m[i]);\n            meanv += abs(v[i]);\n        }\n        meanm /= sizeState;\n        meanv /= sizeState;\n        s += strpr(\" %16.8E %16.8E %16.8E %16.8E\",\n                   beta1t, beta2t, meanm, meanv);\n    }\n    s += '\\n';\n\n    return s;\n}\n\nvector<string> GradientDescent::statusHeader() const\n{\n    vector<string> header;\n\n    vector<string> title;\n    vector<string> colName;\n    vector<string> colInfo;\n    vector<size_t> colSize;\n    title.push_back(\"Gradient descent status report.\");\n    colSize.push_back(10);\n    colName.push_back(\"epoch\");\n    colInfo.push_back(\"Training epoch.\");\n    colSize.push_back(16);\n    colName.push_back(\"eta\");\n    colInfo.push_back(\"Step size.\");\n    if (type == DT_ADAM)\n    {\n        colSize.push_back(16);\n        colName.push_back(\"beta1t\");\n        colInfo.push_back(\"Decay rate 1 to the power of t.\");\n        colSize.push_back(16);\n        colName.push_back(\"beta2t\");\n        colInfo.push_back(\"Decay rate 2 to the power of t.\");\n        colSize.push_back(16);\n        colName.push_back(\"mag_m\");\n        colInfo.push_back(\"Mean of absolute first momentum (m).\");\n        colSize.push_back(16);\n        colName.push_back(\"mag_v\");\n        colInfo.push_back(\"Mean of absolute second momentum (v).\");\n    }\n    header = createFileHeader(title, colSize, colName, colInfo);\n\n    return header;\n}\n\nvector<string> GradientDescent::info() const\n{\n    vector<string> v;\n\n    if (type == DT_FIXED)\n    {\n        v.push_back(strpr(\"GradientDescentType::DT_FIXED (%d)\\n\", type));\n        v.push_back(strpr(\"sizeState       = %zu\\n\", sizeState));\n        v.push_back(strpr(\"eta             = %12.4E\\n\", eta));\n    }\n    else if (type == DT_ADAM)\n    {\n        v.push_back(strpr(\"GradientDescentType::DT_ADAM (%d)\\n\", type));\n        v.push_back(strpr(\"sizeState       = %zu\\n\", sizeState));\n        v.push_back(strpr(\"eta             = %12.4E\\n\", eta));\n        v.push_back(strpr(\"beta1           = %12.4E\\n\", beta1));\n        v.push_back(strpr(\"beta2           = %12.4E\\n\", beta2));\n        v.push_back(strpr(\"epsilon         = %12.4E\\n\", epsilon));\n    }\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnptrain/GradientDescent.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef GRADIENTDESCENT_H\n#define GRADIENTDESCENT_H\n\n#include \"Updater.h\"\n#include <cstddef> // std::size_t\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/// Weight updates based on simple gradient descent methods.\nclass GradientDescent : public Updater\n{\npublic:\n    /// Enumerate different gradient descent variants.\n    enum DescentType\n    {\n        /// Fixed step size.\n        DT_FIXED,\n        /// Adaptive moment estimation (Adam).\n        DT_ADAM\n    };\n\n    /** %GradientDescent class constructor.\n     *\n     * @param[in] sizeState Number of neural network connections (weights\n     *                      and biases).\n     * @param[in] type Descent type used for step size.\n     */\n    GradientDescent(std::size_t const sizeState, DescentType const type);\n    /** Destructor\n     */\n    virtual ~GradientDescent() {};\n    /** Set pointer to current state.\n     *\n     * @param[in,out] state Pointer to state vector (weights vector), will be\n     *                      changed in-place upon calling update().\n     */\n    void                     setState(double* state);\n    /** Set pointer to current error vector.\n     *\n     * @param[in] error Pointer to error (difference between reference and\n     *                  neural network potential output).\n     * @param[in] size Number of error vector entries.\n     */\n    void                     setError(double const* const error,\n                                      std::size_t const   size = 1);\n    /** Set pointer to current Jacobi matrix.\n     *\n     * @param[in] jacobian Derivatives of error with respect to weights.\n     * @param[in] columns Number of gradients provided.\n     *\n     * @note\n     * If there are @f$m@f$ errors and @f$n@f$ weights, the Jacobi matrix\n     * is a @f$n \\times m@f$ matrix stored in column-major order.\n     */\n    void                     setJacobian(double const* const jacobian,\n                                         std::size_t const   columns = 1);\n    /** Perform connection update.\n     *\n     * Update the connections via steepest descent method.\n     */\n    void                     update();\n    /** Set parameters for fixed step gradient descent algorithm.\n     *\n     * @param[in] eta Step size = ratio of gradient subtracted from current\n     *                weights.\n     */\n    void                     setParametersFixed(double const eta);\n    /** Set parameters for Adam algorithm.\n     *\n     * @param[in] eta Step size (corresponds to @f$\\alpha@f$ in Adam\n     *                publication).\n     * @param[in] beta1 Decay rate 1 (first moment).\n     * @param[in] beta2 Decay rate 2 (second moment).\n     * @param[in] epsilon Small scalar.\n     */\n    void                     setParametersAdam(double const eta,\n                                               double const beta1,\n                                               double const beta2,\n                                               double const epsilon);\n    /** Status report.\n     *\n     * @param[in] epoch Current epoch.\n     *\n     * @return Line with current status information.\n     */\n    std::string              status(std::size_t epoch) const;\n    /** Header for status report file.\n     *\n     * @return Vector with header lines.\n     */\n    std::vector<std::string> statusHeader() const;\n    /** Information about gradient descent settings.\n     *\n     * @return Vector with info lines.\n     */\n    std::vector<std::string> info() const;\n\nprivate:\n    DescentType         type;\n    /// Learning rate @f$\\eta@f$.\n    double              eta;\n    /// Decay rate 1 (Adam).\n    double              beta1;\n    /// Decay rate 2 (Adam).\n    double              beta2;\n    /// Small scalar.\n    double              epsilon;\n    /// Initial learning rate.\n    double              eta0;\n    /// Decay rate 1 to the power of t (Adam).\n    double              beta1t;\n    /// Decay rate 2 to the power of t (Adam).\n    double              beta2t;\n    /// State vector pointer.\n    double*             state;\n    /// Error pointer (single double value).\n    double const*       error;\n    /// Gradient vector pointer.\n    double const*       gradient;\n    /// First moment estimate (Adam).\n    std::vector<double> m;\n    /// Second moment estimate (Adam).\n    std::vector<double> v;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnptrain/KalmanFilter.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"KalmanFilter.h\"\n#include \"utility.h\"\n#include <Eigen/LU>\n#include <iostream>\n#include <stdexcept>\n\nusing namespace Eigen;\nusing namespace std;\nusing namespace nnp;\n\nKalmanFilter::KalmanFilter(size_t const sizeState,\n                           KalmanType const type) :\n    Updater(sizeState),\n    sizeObservation(0   ),\n    numUpdates     (0   ),\n    epsilon        (0.0 ),\n    q              (0.0 ),\n    q0             (0.0 ),\n    qtau           (0.0 ),\n    qmin           (0.0 ),\n    eta            (0.0 ),\n    eta0           (0.0 ),\n    etatau         (0.0 ),\n    etamax         (0.0 ),\n    lambda         (0.0 ),\n    nu             (0.0 ),\n    gamma          (0.0 ),\n    w              (NULL),\n    xi             (NULL),\n    H              (NULL)\n{\n    if (!(type == KT_STANDARD ||\n          type == KT_FADINGMEMORY))\n    {\n        throw runtime_error(\"ERROR: Unknown Kalman filter type.\\n\");\n    }\n\n    if (sizeState < 1)\n    {\n        throw runtime_error(\"ERROR: Wrong Kalman filter dimensions.\\n\");\n    }\n\n    this->type            = type;\n    sizeObservation = 1;\n\n    w  = new Map<VectorXd      >(0, sizeState);\n    xi = new Map<VectorXd const>(0, sizeObservation);\n    H  = new Map<MatrixXd const>(0, sizeState, sizeObservation);\n    P.resize(sizeState, sizeState);\n    P.setIdentity();\n    // Prevent problems with unallocated K when log starts.\n    K.resize(sizeState, sizeObservation);\n    K.setZero();\n}\n\nKalmanFilter::~KalmanFilter()\n{\n}\n\nvoid KalmanFilter::setSizeObservation(size_t const size)\n{\n    sizeObservation = size;\n\n    return;\n}\n\nvoid KalmanFilter::setState(double* state)\n{\n    new (w) Map<VectorXd>(state, sizeState);\n\n    return;\n}\n\nvoid KalmanFilter::setError(double const* const error)\n{\n    setError(error, sizeObservation);\n\n    return;\n}\n\nvoid KalmanFilter::setError(double const* const error, size_t const size)\n{\n    new (xi) Map<VectorXd const>(error, size);\n\n    return;\n}\n\nvoid KalmanFilter::setJacobian(double const* const jacobian)\n{\n    setJacobian(jacobian, sizeObservation);\n\n    return;\n}\n\nvoid KalmanFilter::setJacobian(double const* const jacobian,\n                               size_t const columns)\n{\n    new (H) Map<MatrixXd const>(jacobian, sizeState, columns);\n\n    return;\n}\n\nvoid KalmanFilter::update()\n{\n    update(sizeObservation);\n\n    return;\n}\n\nvoid KalmanFilter::update(size_t const sizeObservation)\n{\n    sw[prefix].start(timingReset);\n\n    X.resize(sizeState, sizeObservation);\n\n    // Calculate temporary result.\n    // X = P . H\n    X = P.selfadjointView<Lower>() * (*H);\n\n    // Calculate scaling matrix.\n    // A = H^T . X\n    MatrixXd A = H->transpose() * X;\n\n    // Increase learning rate.\n    // eta(n) = eta(0) * exp(n * tau)\n    if (type == KT_STANDARD && eta < etamax) eta *= exp(etatau);\n\n    // Add measurement noise.\n    // A = A + R\n    if (type == KT_STANDARD)\n    {\n        A.diagonal() += VectorXd::Constant(sizeObservation, 1.0 / eta);\n    }\n    else if (type == KT_FADINGMEMORY)\n    {\n        A.diagonal() += VectorXd::Constant(sizeObservation, lambda);\n    }\n\n    // Calculate Kalman gain matrix.\n    // K = X . A^-1\n    K.resize(sizeState, sizeObservation);\n    K = X * A.inverse();\n\n    // Update error covariance matrix.\n    // P = P - K . X^T\n    P.noalias() -= K * X.transpose();\n\n    // Apply forgetting factor.\n    if (type == KT_FADINGMEMORY)\n    {\n        P *= 1.0 / lambda;\n    }\n    // Add process noise.\n    // P = P + Q\n    P.diagonal() += VectorXd::Constant(sizeState, q);\n\n    //double numAcc = (P - P.transpose()).cwiseAbs().maxCoeff();\n    //cout << \"Max. deviation of symmetric form of P: \" << numAcc << endl;\n\n    // Update state vector.\n    // w =  w + K . xi\n    (*w) += K * (*xi);\n\n    // Anneal process noise.\n    // q(n) = q(0) * exp(-n * tau)\n    if (q > qmin) q *= exp(-qtau);\n\n    // Update forgetting factor.\n    if (type == KT_FADINGMEMORY)\n    {\n        lambda = nu * lambda + 1.0 - nu;\n        gamma = 1.0 / (1.0 + lambda / gamma);\n    }\n\n    numUpdates++;\n\n    if (timingReset) timingReset = false;\n    sw[prefix].stop();\n\n    return;\n}\n\nvoid KalmanFilter::setParametersStandard(double const epsilon,\n                                         double const q0,\n                                         double const qtau,\n                                         double const qmin,\n                                         double const eta0,\n                                         double const etatau,\n                                         double const etamax)\n{\n    this->epsilon = epsilon;\n    this->q0      = q0     ;\n    this->qtau    = qtau   ;\n    this->qmin    = qmin   ;\n    this->eta0    = eta0   ;\n    this->etatau  = etatau ;\n    this->etamax  = etamax ;\n\n    q = q0;\n    eta = eta0;\n    P /= epsilon;\n\n    return;\n}\n\nvoid KalmanFilter::setParametersFadingMemory(double const epsilon,\n                                             double const q0,\n                                             double const qtau,\n                                             double const qmin,\n                                             double const lambda,\n                                             double const nu)\n{\n    this->epsilon = epsilon;\n    this->q0      = q0     ;\n    this->qtau    = qtau   ;\n    this->qmin    = qmin   ;\n    this->lambda  = lambda ;\n    this->nu      = nu     ;\n\n    q = q0;\n    P /= epsilon;\n    gamma = 1.0;\n\n    return;\n}\n\nstring KalmanFilter::status(size_t epoch) const\n{\n\n    double Pasym = 0.5 * (P - P.transpose()).array().abs().mean();\n    double Pdiag = P.diagonal().array().abs().sum();\n    double Poffdiag = (P.array().abs().sum() - Pdiag)\n                    / (sizeState * (sizeState - 1));\n    Pdiag /= sizeState;\n    double Kmean = K.array().abs().mean();\n\n    string s = strpr(\"%10zu %10zu %16.8E %16.8E %16.8E %16.8E %16.8E\",\n                     epoch, numUpdates, Pdiag, Poffdiag, Pasym, Kmean, q);\n    if (type == KT_STANDARD)\n    {\n        s += strpr(\" %16.8E\", eta);\n    }\n    else if (type == KT_FADINGMEMORY)\n    {\n        s += strpr(\" %16.8E %16.8E\", lambda, numUpdates * gamma);\n    }\n    s += '\\n';\n\n    return s;\n}\n\nvector<string> KalmanFilter::statusHeader() const\n{\n    vector<string> header;\n\n    vector<string> title;\n    vector<string> colName;\n    vector<string> colInfo;\n    vector<size_t> colSize;\n    title.push_back(\"Kalman filter status report.\");\n    colSize.push_back(10);\n    colName.push_back(\"epoch\");\n    colInfo.push_back(\"Training epoch.\");\n    colSize.push_back(10);\n    colName.push_back(\"nupdates\");\n    colInfo.push_back(\"Number of updates performed.\");\n    colSize.push_back(16);\n    colName.push_back(\"Pdiag\");\n    colInfo.push_back(\"Mean of absolute diagonal values of error covariance \"\n                      \"matrix P.\");\n    colSize.push_back(16);\n    colName.push_back(\"Poffdiag\");\n    colInfo.push_back(\"Mean of absolute off-diagonal values of error \"\n                      \"covariance matrix P.\");\n    colSize.push_back(16);\n    colName.push_back(\"Pasym\");\n    colInfo.push_back(\"Asymmetry of P, i.e. mean of absolute values of \"\n                      \"asymmetric part 0.5*(P - P^T).\");\n    colSize.push_back(16);\n    colName.push_back(\"Kmean\");\n    colInfo.push_back(\"Mean of abolute compontents of Kalman gain matrix K.\");\n    colSize.push_back(16);\n    colName.push_back(\"q\");\n    colInfo.push_back(\"Magnitude of process noise (= diagonal entries of Q).\");\n    if (type == KT_STANDARD)\n    {\n        colSize.push_back(16);\n        colName.push_back(\"eta\");\n        colInfo.push_back(\"Learning rate.\");\n    }\n    else if (type == KT_FADINGMEMORY)\n    {\n        colSize.push_back(16);\n        colName.push_back(\"lambda\");\n        colInfo.push_back(\"Forgetting factor for fading memory KF.\");\n        colSize.push_back(16);\n        colName.push_back(\"kgamma\");\n        colInfo.push_back(\"Forgetting gain k * gamma(k).\");\n    }\n    header = createFileHeader(title, colSize, colName, colInfo);\n\n    return header;\n}\n\nvector<string> KalmanFilter::info() const\n{\n    vector<string> v;\n\n    if (type == KT_STANDARD)\n    {\n        v.push_back(strpr(\"KalmanType::KT_STANDARD (%d)\\n\", type));\n        v.push_back(strpr(\"sizeState       = %zu\\n\", sizeState));\n        v.push_back(strpr(\"sizeObservation = %zu\\n\", sizeObservation));\n        v.push_back(strpr(\"epsilon         = %12.4E\\n\", epsilon));\n        v.push_back(strpr(\"q0              = %12.4E\\n\", q0     ));\n        v.push_back(strpr(\"qtau            = %12.4E\\n\", qtau   ));\n        v.push_back(strpr(\"qmin            = %12.4E\\n\", qmin   ));\n        v.push_back(strpr(\"eta0            = %12.4E\\n\", eta0   ));\n        v.push_back(strpr(\"etatau          = %12.4E\\n\", etatau ));\n        v.push_back(strpr(\"etamax          = %12.4E\\n\", etamax ));\n    }\n    else if (type == KT_FADINGMEMORY)\n    {\n        v.push_back(strpr(\"KalmanType::KT_FADINGMEMORY (%d)\\n\", type));\n        v.push_back(strpr(\"sizeState       = %zu\\n\", sizeState));\n        v.push_back(strpr(\"sizeObservation = %zu\\n\", sizeObservation));\n        v.push_back(strpr(\"epsilon         = %12.4E\\n\", epsilon));\n        v.push_back(strpr(\"q0              = %12.4E\\n\", q0     ));\n        v.push_back(strpr(\"qtau            = %12.4E\\n\", qtau   ));\n        v.push_back(strpr(\"qmin            = %12.4E\\n\", qmin   ));\n        v.push_back(strpr(\"lambda          = %12.4E\\n\", lambda));\n        v.push_back(strpr(\"nu              = %12.4E\\n\", nu    ));\n    }\n    v.push_back(strpr(\"OpenMP threads used: %d\\n\", nbThreads()));\n\n    return v;\n}\n"
  },
  {
    "path": "src/libnnptrain/KalmanFilter.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef KALMANFILTER_H\n#define KALMANFILTER_H\n\n#include <mpi.h>\n#include \"Updater.h\"\n#include <Eigen/Core>\n#include <cstddef>\n#include <string>\n#include <vector>\n\nnamespace nnp\n{\n\n/// Implementation of the Kalman filter method.\nclass KalmanFilter : public Updater\n{\npublic:\n    /// Enumerate different Kalman filter types.\n    enum KalmanType\n    {\n        /// Regular Kalman filter.\n        KT_STANDARD,\n        /// Kalman filtering with fading memory modification.\n        KT_FADINGMEMORY\n    };\n\n    /** Kalman filter class constructor.\n     *\n     * @param[in] sizeState Size of the state vector #w.\n     * @param[in] type Kalman filter type (see #KalmanType).\n     */\n    KalmanFilter(std::size_t const sizeState,\n                 KalmanType const  type);\n    /** Destructor.\n     */\n    virtual ~KalmanFilter();\n    /** Set observation vector size.\n     *\n     * @param[in] size Size of the observation vector.\n     *\n     * If the size of the observation vector is known in advance it can be set\n     * here.\n     */\n    void                     setSizeObservation(\n                                            std::size_t const sizeObservation);\n    /** Set pointer to current state.\n     *\n     * @param[in,out] state Pointer to state vector (weights vector), will be\n     *                      changed in-place upon calling update().\n     */\n    void                     setState(double* state);\n    /** Set pointer to current error vector.\n     *\n     * @param[in] error Pointer to error (difference between reference and\n     *                  neural network potential output).\n     */\n    void                     setError(double const* const error);\n    /** Set pointer to current error vector.\n     *\n     * @param[in] error Pointer to error (difference between reference and\n     *                  neural network potential output).\n     * @param[in] size Number of error vector entries.\n     */\n    void                     setError(double const* const error,\n                                      std::size_t const   size);\n    /** Set pointer to current Jacobi matrix.\n     *\n     * @param[in] jacobian Derivatives of error with respect to weights.\n     */\n    void                     setJacobian(double const* const jacobian);\n    /** Set pointer to current Jacobi matrix.\n     *\n     * @param[in] jacobian Derivatives of error with respect to weights.\n     * @param[in] columns Number of gradients provided.\n     *\n     * @note\n     * If there are @f$m@f$ errors and @f$n@f$ weights, the Jacobi matrix\n     * is a @f$n \\times m@f$ matrix stored in column-major order.\n     */\n    void                     setJacobian(double const* const jacobian,\n                                         std::size_t const   columns);\n    /** Update error covariance matrix and state vector.\n     */\n    void                     update();\n    /** Update error covariance matrix and state vector.\n     *\n     * @param[in] sizeObservation Size of the observation vector.\n     */\n    void                     update(std::size_t const sizeObservation);\n    /** Set parameters for standard Kalman filter.\n     *\n     * @param[in] epsilon Error covariance initialization parameter\n     *                    @f$\\epsilon@f$.\n     * @param[in] q0 Process noise initial value @f$q_0@f$.\n     * @param[in] qtau Process noise exponential decay parameter\n     *                 @f$q_{\\tau}@f$.\n     * @param[in] qmin Process noise minimum value @f$q_{\\text{min}}@f$.\n     * @param[in] eta0 Initial learning rate @f$\\eta_0@f$.\n     * @param[in] etatau Learning rate exponential increase parameter\n     *                   @f$\\eta_{\\tau}@f$.\n     * @param[in] etamax Learning rate maximum value @f$\\eta_{\\text{max}}@f$.\n     */\n    void                     setParametersStandard(double const epsilon,\n                                                   double const q0,\n                                                   double const qtau,\n                                                   double const qmin,\n                                                   double const eta0,\n                                                   double const etatau,\n                                                   double const etamax);\n    /** Set parameters for fading memory Kalman filter.\n     *\n     * @param[in] epsilon Error covariance initialization parameter\n     *                    @f$\\epsilon@f$.\n     * @param[in] q0 Process noise initial value @f$q_0@f$.\n     * @param[in] qtau Process noise exponential decay parameter\n     *                 @f$q_{\\tau}@f$.\n     * @param[in] qmin Process noise minimum value @f$q_{\\text{min}}@f$.\n     * @param[in] lambda Forgetting factor @f$\\lambda@f$.\n     * @param[in] nu Fading memory parameter @f$\\nu@f$.\n     */\n    void                     setParametersFadingMemory(double const epsilon,\n                                                       double const q0,\n                                                       double const qtau,\n                                                       double const qmin,\n                                                       double const lambda,\n                                                       double const nu);\n    /** Status report.\n     *\n     * @param[in] epoch Current epoch.\n     *\n     * @return Line with current status information.\n     */\n    std::string              status(std::size_t epoch) const;\n    /** Header for status report file.\n     *\n     * @return Vector with header lines.\n     */\n    std::vector<std::string> statusHeader() const;\n    /** Information about Kalman filter settings.\n     *\n     * @return Vector with info lines.\n     */\n    std::vector<std::string> info() const;\n    /** Getter for #type.\n     */\n    KalmanType               getType() const;\n    /** Getter for #sizeObservation.\n     */\n    std::size_t              getSizeObservation() const;\n    /** Getter for #numUpdates.\n     */\n    std::size_t              getNumUpdates() const;\n    /** Getter for #eta.\n     */\n    double                   getEta() const;\n    /** Getter for #epsilon.\n     */\n    double                   getEpsilon() const;\n    /** Getter for #q0.\n     */\n    double                   getQ0() const;\n    /** Getter for #qtau.\n     */\n    double                   getQtau() const;\n    /** Getter for #qmin.\n     */\n    double                   getQmin() const;\n    /** Getter for #lambda.\n     */\n    double                   getLambda() const;\n    /** Getter for #nu.\n     */\n    double                   getNu() const;\n    /** Getter for #gamma.\n     */\n    double                   getGamma() const;\n\nprivate:\n    /// Kalman filter type.\n    KalmanType                         type;\n    /// Size of observation (measurement) vector.\n    std::size_t                        sizeObservation;\n    /// Total number of updates performed.\n    std::size_t                        numUpdates;\n    /// Error covariance initialization parameter @f$\\epsilon@f$.\n    double                             epsilon;\n    /// Process noise @f$q@f$.\n    double                             q;\n    /// Process noise initial value @f$q_0@f$.\n    double                             q0;\n    /// Process noise exponential decay parameter @f$q_{\\tau}@f$.\n    double                             qtau;\n    /// Process noise minimum value @f$q_{\\text{min}}@f$.\n    double                             qmin;\n    /// Learning rate @f$\\eta@f$.\n    double                             eta;\n    /// Learning rate initial value @f$\\eta_0@f$.\n    double                             eta0;\n    /// Learning rate exponential increase parameter @f$\\eta_{\\tau}@f$.\n    double                             etatau;\n    /// Learning rate maximum value @f$\\eta_{\\text{max}}@f$.\n    double                             etamax;\n    /// Forgetting factor for fading memory Kalman filter.\n    double                             lambda;\n    /// Parameter for fading memory Kalman filter.\n    double                             nu;\n    /// Forgetting gain factor gamma for fading memory Kalman filter.\n    double                             gamma;\n    /// State vector.\n    Eigen::Map<Eigen::VectorXd>*       w;\n    /// Error vector.\n    Eigen::Map<Eigen::VectorXd const>* xi;\n    /// Derivative matrix.\n    Eigen::Map<Eigen::MatrixXd const>* H;\n    /// Error covariance matrix.\n    Eigen::MatrixXd                    P;\n    /// Kalman gain matrix.\n    Eigen::MatrixXd                    K;\n    /// Intermediate result X = P . H.\n    Eigen::MatrixXd                    X;\n};\n\n//////////////////////////////////\n// Inlined function definitions //\n//////////////////////////////////\n\ninline KalmanFilter::KalmanType KalmanFilter::getType() const\n{\n    return type;\n}\n\ninline std::size_t KalmanFilter::getSizeObservation() const\n{\n    return sizeObservation;\n}\n\ninline std::size_t KalmanFilter::getNumUpdates() const\n{\n    return numUpdates;\n}\n\ninline double KalmanFilter::getEta() const\n{\n    return eta;\n}\n\ninline double KalmanFilter::getEpsilon() const\n{\n    return epsilon;\n}\n\ninline double KalmanFilter::getQ0() const\n{\n    return q0;\n}\n\ninline double KalmanFilter::getQtau() const\n{\n    return qtau;\n}\n\ninline double KalmanFilter::getQmin() const\n{\n    return qmin;\n}\n\ninline double KalmanFilter::getLambda() const\n{\n    return lambda;\n}\n\ninline double KalmanFilter::getNu() const\n{\n    return nu;\n}\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnptrain/Training.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Training.h\"\n#include \"Eigen/src/Core/Matrix.h\"\n#include \"GradientDescent.h\"\n#include \"KalmanFilter.h\"\n#include \"NeuralNetwork.h\"\n#include \"utility.h\"\n#include \"mpi-extra.h\"\n#ifdef _OPENMP\n#include <omp.h>\n#endif\n#include <algorithm> // std::sort, std::fill, std::find\n#include <cmath>     // fabs\n#include <cstdlib>   // atoi\n#include <gsl/gsl_rng.h>\n#include <limits>    // std::numeric_limits\n#include <stdexcept> // std::runtime_error, std::range_error\n#include <utility>   // std::piecewise_construct, std::forward_as_tuple\n\nusing namespace std;\nusing namespace nnp;\n\nTraining::Training() : Dataset(),\n                       updaterType                (UT_GD          ),\n                       parallelMode               (PM_TRAIN_RK0   ),\n                       jacobianMode               (JM_SUM         ),\n                       updateStrategy             (US_COMBINED    ),\n                       hasUpdaters                (false          ),\n                       hasStructures              (false          ),\n                       useForces                  (false          ),\n                       repeatedEnergyUpdates      (false          ),\n                       freeMemory                 (false          ),\n                       writeTrainingLog           (false          ),\n                       stage                      (0              ),\n                       numUpdaters                (0              ),\n                       numEpochs                  (0              ),\n                       epoch                      (0              ),\n                       writeWeightsEvery          (0              ),\n                       writeWeightsAlways         (0              ),\n                       writeNeuronStatisticsEvery (0              ),\n                       writeNeuronStatisticsAlways(0              ),\n                       numWeights                 (0              ),\n                       forceWeight                (0.0            ),\n                       trainingLogFileName        (\"train-log.out\")\n{\n    sw[\"setup\"].start();\n}\n\nTraining::~Training()\n{\n    for (vector<Updater*>::iterator it = updaters.begin();\n         it != updaters.end(); ++it)\n    {\n        if (updaterType == UT_GD)\n        {\n            delete dynamic_cast<GradientDescent*>(*it);\n        }\n        else if (updaterType == UT_KF)\n        {\n            delete dynamic_cast<KalmanFilter*>(*it);\n        }\n    }\n\n    if (trainingLog.is_open()) trainingLog.close();\n}\n\nvoid Training::selectSets()\n{\n    log << \"\\n\";\n    log << \"*** DEFINE TRAINING/TEST SETS ***********\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    vector<string> pCheck = {\"force\", \"charge\"};\n    bool check = false;\n    for (auto k : pk)\n    {\n        check |= (find(pCheck.begin(), pCheck.end(), k) != pCheck.end());\n    }\n    vector<size_t> numAtomsPerElement(numElements, 0);\n\n    double testSetFraction = atof(settings[\"test_fraction\"].c_str());\n    log << strpr(\"Desired test set ratio      : %f\\n\", testSetFraction);\n    if (structures.size() > 0) hasStructures = true;\n    else hasStructures = false;\n\n    string k;\n    for (size_t i = 0; i < structures.size(); ++i)\n    {\n        Structure& s = structures.at(i);\n        // Only select set if not already determined.\n        if (s.sampleType == Structure::ST_UNKNOWN)\n        {\n            double const r = gsl_rng_uniform(rng);\n            if (r < testSetFraction) s.sampleType = Structure::ST_TEST;\n            else                     s.sampleType = Structure::ST_TRAINING;\n        }\n        if (s.sampleType == Structure::ST_TEST)\n        {\n            size_t const& na = s.numAtoms;\n            k = \"energy\"; if (p.exists(k)) p[k].numTestPatterns++;\n            k = \"force\";  if (p.exists(k)) p[k].numTestPatterns += 3 * na;\n            if (nnpType == NNPType::HDNNP_4G)\n            {\n                k = \"charge\"; if (p.exists(k)) p[k].numTestPatterns++;\n            }\n            else\n            {\n                k = \"charge\"; if (p.exists(k)) p[k].numTestPatterns += na;\n            }\n        }\n        else if (s.sampleType == Structure::ST_TRAINING)\n        {\n            for (size_t j = 0; j < numElements; ++j)\n            {\n                numAtomsPerElement.at(j) += s.numAtomsPerElement.at(j);\n            }\n\n            k = \"energy\";\n            if (p.exists(k))\n            {\n                p[k].numTrainPatterns++;\n                p[k].updateCandidates.push_back(UpdateCandidate());\n                p[k].updateCandidates.back().s = i;\n            }\n            k = \"force\";\n            if (p.exists(k))\n            {\n                p[k].numTrainPatterns += 3 * s.numAtoms;\n\n                if (nnpType == NNPType::HDNNP_4G)\n                {\n                    p[k].updateCandidates.push_back(UpdateCandidate());\n                    p[k].updateCandidates.back().s = i;\n                }\n                for (auto &ai : s.atoms)\n                {\n                    for (size_t j = 0; j < 3; ++j)\n                    {\n                        if (nnpType != NNPType::HDNNP_4G)\n                        {\n                            p[k].updateCandidates.push_back(UpdateCandidate());\n                            p[k].updateCandidates.back().s = i;\n                        }\n                        p[k].updateCandidates.back().subCandidates\n                            .push_back(SubCandidate());\n                        p[k].updateCandidates.back().subCandidates\n                            .back().a = ai.index;\n                        p[k].updateCandidates.back().subCandidates\n                            .back().c = j;\n                    }\n                }\n            }\n            k = \"charge\";\n            if (p.exists(k))\n            {\n                if (nnpType == NNPType::HDNNP_4G)\n                {\n                    p[k].numTrainPatterns++;\n                    p[k].updateCandidates.push_back(UpdateCandidate());\n                    p[k].updateCandidates.back().s = i;\n                }\n                else\n                {\n                    p[k].numTrainPatterns += s.numAtoms;\n                    for (vector<Atom>::const_iterator it = s.atoms.begin();\n                         it != s.atoms.end(); ++it)\n                    {\n                        p[k].updateCandidates.push_back(UpdateCandidate());\n                        p[k].updateCandidates.back().s = i;\n                        p[k].updateCandidates.back().subCandidates\n                            .push_back(SubCandidate());\n                        p[k].updateCandidates.back().subCandidates.back().a\n                            = it->index;\n                    }\n                }\n\n            }\n        }\n        else\n        {\n            log << strpr(\"WARNING: Structure %zu not assigned to either \"\n                         \"training or test set.\\n\", s.index);\n        }\n    }\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        if (hasStructures && (numAtomsPerElement.at(i) == 0))\n        {\n            log << strpr(\"WARNING: Process %d has no atoms of element \"\n                         \"%d (%2s).\\n\",\n                         myRank,\n                         i,\n                         elementMap[i].c_str());\n        }\n    }\n    for (auto k : pk)\n    {\n        MPI_Allreduce(MPI_IN_PLACE, &(p[k].numTrainPatterns), 1, MPI_SIZE_T, MPI_SUM, comm);\n        MPI_Allreduce(MPI_IN_PLACE, &(p[k].numTestPatterns) , 1, MPI_SIZE_T, MPI_SUM, comm);\n        double sum = p[k].numTrainPatterns + p[k].numTestPatterns;\n        log << \"Training/test split of data set for property \\\"\" + k + \"\\\":\\n\";\n        log << strpr(\"- Total    patterns : %.0f\\n\", sum);\n        log << strpr(\"- Training patterns : %d\\n\", p[k].numTrainPatterns);\n        log << strpr(\"- Test     patterns : %d\\n\", p[k].numTestPatterns);\n        log << strpr(\"- Test set fraction : %f\\n\", p[k].numTestPatterns / sum);\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Training::writeSetsToFiles()\n{\n    log << \"\\n\";\n    log << \"*** WRITE TRAINING/TEST SETS ************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    string fileName = strpr(\"train.data.%04d\", myRank);\n    ofstream fileTrain;\n    fileTrain.open(fileName.c_str());\n    if (!fileTrain.is_open())\n    {\n        runtime_error(strpr(\"ERROR: Could not open file %s\\n\",\n                            fileName.c_str()));\n    }\n    fileName = strpr(\"test.data.%04d\", myRank);\n    ofstream fileTest;\n    fileTest.open(fileName.c_str());\n    if (!fileTest.is_open())\n    {\n        runtime_error(strpr(\"ERROR: Could not open file %s\\n\",\n                            fileName.c_str()));\n    }\n    for (vector<Structure>::iterator it = structures.begin();\n         it != structures.end(); ++it)\n    {\n        // Energy offsets are already subtracted at this point.\n        // Here, we quickly add them again to provide consistent data sets.\n        addEnergyOffset(*it);\n        if (it->sampleType == Structure::ST_TRAINING)\n        {\n            it->writeToFile(&fileTrain);\n        }\n        else if (it->sampleType == Structure::ST_TEST)\n        {\n            it->writeToFile(&fileTest);\n        }\n        // Subtract energy offsets again.\n        removeEnergyOffset(*it);\n    }\n    fileTrain.flush();\n    fileTrain.close();\n    fileTest.flush();\n    fileTest.close();\n    MPI_Barrier(comm);\n    if (myRank == 0)\n    {\n        log << \"Writing training/test set to files:\\n\";\n        log << \" - train.data\\n\";\n        log << \" - test.data\\n\";\n        fileName = \"train.data\";\n        combineFiles(fileName);\n        fileName = \"test.data\";\n        combineFiles(fileName);\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Training::initializeWeights()\n{\n    log << \"\\n\";\n    log << \"*** WEIGHT INITIALIZATION ***************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    if (settings.keywordExists(\"nguyen_widrow_weights_short\") &&\n        settings.keywordExists(\"precondition_weights\"))\n    {\n        throw runtime_error(\"ERROR: Nguyen Widrow and preconditioning weights\"\n                            \" initialization are incompatible\\n\");\n    }\n\n    // Training stage 2 requires electrostatics NN weights from file.\n    if ((nnpType == NNPType::HDNNP_4G && stage == 2) ||\n        (nnpType == NNPType::HDNNP_Q  && stage == 2))\n    {\n        log << \"Setting up \" + nns.at(\"elec\").name + \" neural networks:\\n\";\n        readNeuralNetworkWeights(\"elec\", nns.at(\"elec\").weightFileFormat);\n    }\n\n    // Currently trained NN weights may be read from file or randomized.\n    NNSetup const& nn = nns.at(nnId);\n    log << \"Setting up \" + nn.name + \" neural networks:\\n\";\n    if (settings.keywordExists(\"use_old_weights\" + nn.keywordSuffix2))\n    {\n        log << \"Reading old weights from files.\\n\";\n        readNeuralNetworkWeights(nnId, nn.weightFileFormat);\n    }\n    else randomizeNeuralNetworkWeights(nnId);\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Training::initializeWeightsMemory(UpdateStrategy updateStrategy)\n{\n    this->updateStrategy = updateStrategy;\n    numWeights= 0;\n    if (updateStrategy == US_COMBINED)\n    {\n        log << strpr(\"Combined updater for all elements selected: \"\n                     \"UpdateStrategy::US_COMBINED (%d)\\n\", updateStrategy);\n        numUpdaters = 1;\n        log << strpr(\"Number of weight updaters    : %zu\\n\", numUpdaters);\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            weightsOffset.push_back(numWeights);\n            numWeights += elements.at(i).neuralNetworks.at(nnId)\n                          .getNumConnections();\n            // sqrt of Hardness of element is included in weights vector\n            if (nnpType == NNPType::HDNNP_4G && stage == 1) numWeights ++;\n        }\n        weights.resize(numUpdaters);\n        weights.at(0).resize(numWeights, 0.0);\n        numWeightsPerUpdater.push_back(numWeights);\n        log << strpr(\"Total fit parameters         : %zu\\n\", numWeights);\n    }\n    else if (updateStrategy == US_ELEMENT)\n    {\n        log << strpr(\"Separate updaters for elements selected: \"\n                     \"UpdateStrategy::US_ELEMENT (%d)\\n\", updateStrategy);\n        numUpdaters = numElements;\n        log << strpr(\"Number of weight updaters    : %zu\\n\", numUpdaters);\n        weights.resize(numUpdaters);\n        for (size_t i = 0; i < numUpdaters; ++i)\n        {\n            size_t n = elements.at(i).neuralNetworks.at(nnId)\n                       .getNumConnections();\n            weights.at(i).resize(n, 0.0);\n            numWeightsPerUpdater.push_back(n);\n            log << strpr(\"Fit parameters for element %2s: %zu\\n\",\n                         elements.at(i).getSymbol().c_str(),\n                         n);\n        }\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown update strategy.\\n\");\n    }\n\n    return;\n}\n\nvoid Training::setStage(size_t stage)\n{\n    this->stage = stage;\n\n    // NNP of type HDNNP_2G trains <properties> -> <network>:\n    //   \"energy\" (optionally: \"force\") -> \"short\"\n    if (nnpType == NNPType::HDNNP_2G)\n    {\n        pk.push_back(\"energy\");\n        if (settings.keywordExists(\"use_short_forces\")) pk.push_back(\"force\");\n        nnId = \"short\";\n    }\n    // NNP of type HDNNP_4G or HDNNP_Q trains <properties> -> <network>:\n    // * stage 1: \"charge\" -> \"elec\"\n    // * stage 2: \"energy\" (optionally: \"force\") -> \"short\"\n    else if (nnpType == NNPType::HDNNP_4G ||\n             nnpType == NNPType::HDNNP_Q)\n    {\n        if (stage == 1)\n        {\n            pk.push_back(\"charge\");\n            nnId = \"elec\";\n        }\n        else if (stage == 2)\n        {\n            pk.push_back(\"energy\");\n            if (settings.keywordExists(\"use_short_forces\"))\n            {\n                pk.push_back(\"force\");\n            }\n            nnId = \"short\";\n        }\n        else\n        {\n            throw runtime_error(strpr(\"ERROR: No or incorrect training stage \"\n                                      \"specified: %zu (must be 1 or 2).\\n\",\n                                      stage));\n        }\n    }\n\n    // Initialize all training properties which will be used.\n    auto initP = [this](string key) {p.emplace(piecewise_construct,\n                                               forward_as_tuple(key),\n                                               forward_as_tuple(key));\n                 };\n    for (auto k : pk) initP(k);\n\n    return;\n}\n\nvoid Training::dataSetNormalization()\n{\n    log << \"\\n\";\n    log << \"*** DATA SET NORMALIZATION **************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << \"Computing statistics from reference data and initial \"\n           \"prediction...\\n\";\n    log << \"\\n\";\n\n    bool useForcesLocal = settings.keywordExists(\"use_short_forces\");\n\n    if ( (nnpType == NNPType::HDNNP_4G || nnpType == NNPType::HDNNP_Q) &&\n          stage == 1)\n    {\n        throw runtime_error(\"ERROR: Normalization of charges not yet \"\n                            \"implemented\\n.\");\n    }\n    writeWeights(\"short\", \"weights.%03zu.norm\");\n    if ( (nnpType == NNPType::HDNNP_4G || nnpType == NNPType::HDNNP_Q) &&\n          stage == 2)\n    {\n        writeWeights(\"elec\", \"weightse.%03zu.norm\");\n    }\n\n    ofstream fileEvsV;\n    fileEvsV.open(strpr(\"evsv.dat.%04d\", myRank).c_str());\n    if (myRank == 0)\n    {\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Energy vs. volume comparison.\");\n        colSize.push_back(16);\n        colName.push_back(\"V_atom\");\n        colInfo.push_back(\"Volume per atom.\");\n        colSize.push_back(16);\n        colName.push_back(\"Eref_atom\");\n        colInfo.push_back(\"Reference energy per atom.\");\n        colSize.push_back(10);\n        colName.push_back(\"N\");\n        colInfo.push_back(\"Number of atoms.\");\n        colSize.push_back(16);\n        colName.push_back(\"V\");\n        colInfo.push_back(\"Volume of structure.\");\n        colSize.push_back(16);\n        colName.push_back(\"Eref\");\n        colInfo.push_back(\"Reference energy of structure.\");\n        colSize.push_back(16);\n        colName.push_back(\"Eref_offset\");\n        colInfo.push_back(\"Reference energy of structure (including offset).\");\n        appendLinesToFile(fileEvsV,\n                          createFileHeader(title, colSize, colName, colInfo));\n    }\n\n    size_t numAtomsTotal         = 0;\n    size_t numStructures         = 0;\n    double meanEnergyPerAtomRef  = 0.0;\n    double meanEnergyPerAtomNnp  = 0.0;\n    double sigmaEnergyPerAtomRef = 0.0;\n    double sigmaEnergyPerAtomNnp = 0.0;\n    double meanForceRef          = 0.0;\n    double meanForceNnp          = 0.0;\n    double sigmaForceRef         = 0.0;\n    double sigmaForceNnp         = 0.0;\n    for (auto& s : structures)\n    {\n        // File output for evsv.dat.\n        fileEvsV << strpr(\"%16.8E %16.8E %10zu %16.8E %16.8E %16.8E\\n\",\n                          s.volume / s.numAtoms,\n                          s.energyRef / s.numAtoms,\n                          s.numAtoms,\n                          s.volume,\n                          s.energyRef,\n                          getEnergyWithOffset(s, true));\n        s.calculateNeighborList(maxCutoffRadius);\n        // TODO: handle 4G case\n#ifdef N2P2_NO_SF_GROUPS\n        calculateSymmetryFunctions(s, true);\n#else\n        calculateSymmetryFunctionGroups(s, true);\n#endif\n        calculateAtomicNeuralNetworks(s, true);\n        calculateEnergy(s);\n        if (useForcesLocal) calculateForces(s);\n        s.clearNeighborList();\n\n        numStructures++;\n        numAtomsTotal += s.numAtoms;\n        meanEnergyPerAtomRef += s.energyRef / s.numAtoms;\n        meanEnergyPerAtomNnp += s.energy    / s.numAtoms;\n        for (auto& a : s.atoms)\n        {\n            meanForceRef += a.fRef[0] + a.fRef[1] + a.fRef[2];\n            meanForceNnp += a.f   [0] + a.f   [1] + a.f   [2];\n        }\n    }\n\n    fileEvsV.flush();\n    fileEvsV.close();\n    MPI_Barrier(MPI_COMM_WORLD);\n    log << \"Writing energy/atom vs. volume/atom data to \\\"evsv.dat\\\".\\n\";\n    if (myRank == 0) combineFiles(\"evsv.dat\");\n    MPI_Allreduce(MPI_IN_PLACE, &numStructures       , 1, MPI_SIZE_T, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &numAtomsTotal       , 1, MPI_SIZE_T, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &meanEnergyPerAtomRef, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &meanEnergyPerAtomNnp, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &meanForceRef        , 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &meanForceNnp        , 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    meanEnergyPerAtomRef /= numStructures;\n    meanEnergyPerAtomNnp /= numStructures;\n    meanForceRef /= 3 * numAtomsTotal;\n    meanForceNnp /= 3 * numAtomsTotal;\n    for (auto const& s : structures)\n    {\n        double ediffRef = s.energyRef / s.numAtoms - meanEnergyPerAtomRef;\n        double ediffNnp = s.energy    / s.numAtoms - meanEnergyPerAtomNnp;\n        sigmaEnergyPerAtomRef += ediffRef * ediffRef;\n        sigmaEnergyPerAtomNnp += ediffNnp * ediffNnp;\n        for (auto const& a : s.atoms)\n        {\n            double fdiffRef = a.fRef[0] - meanForceRef;\n            double fdiffNnp = a.f   [0] - meanForceNnp;\n            sigmaForceRef += fdiffRef * fdiffRef;\n            sigmaForceNnp += fdiffNnp * fdiffNnp;\n            fdiffRef = a.fRef[1] - meanForceRef;\n            fdiffNnp = a.f   [1] - meanForceNnp;\n            sigmaForceRef += fdiffRef * fdiffRef;\n            sigmaForceNnp += fdiffNnp * fdiffNnp;\n            fdiffRef = a.fRef[2] - meanForceRef;\n            fdiffNnp = a.f   [2] - meanForceNnp;\n            sigmaForceRef += fdiffRef * fdiffRef;\n            sigmaForceNnp += fdiffNnp * fdiffNnp;\n        }\n    }\n    MPI_Allreduce(MPI_IN_PLACE, &sigmaEnergyPerAtomRef, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &sigmaEnergyPerAtomNnp, 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &sigmaForceRef        , 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    MPI_Allreduce(MPI_IN_PLACE, &sigmaForceNnp        , 1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD);\n    sigmaEnergyPerAtomRef = sqrt(sigmaEnergyPerAtomRef / (numStructures - 1));\n    sigmaEnergyPerAtomNnp = sqrt(sigmaEnergyPerAtomNnp / (numStructures - 1));\n    sigmaForceRef = sqrt(sigmaForceRef / (3 * numAtomsTotal - 1));\n    sigmaForceNnp = sqrt(sigmaForceNnp / (3 * numAtomsTotal - 1));\n    log << \"\\n\";\n    log << strpr(\"Total number of structures : %zu\\n\", numStructures);\n    log << strpr(\"Total number of atoms      : %zu\\n\", numAtomsTotal);\n    log << \"----------------------------------\\n\";\n    log << \"Reference data statistics:\\n\";\n    log << \"----------------------------------\\n\";\n    log << strpr(\"Mean/sigma energy per atom : %16.8E   / %16.8E\\n\",\n                 meanEnergyPerAtomRef,\n                 sigmaEnergyPerAtomRef);\n    log << strpr(\"Mean/sigma force           : %16.8E   / %16.8E\\n\",\n                 meanForceRef,\n                 sigmaForceRef);\n    log << \"----------------------------------\\n\";\n    log << \"Initial NNP prediction statistics:\\n\";\n    log << \"----------------------------------\\n\";\n    log << strpr(\"Mean/sigma energy per atom : %16.8E   / %16.8E\\n\",\n                 meanEnergyPerAtomNnp,\n                 sigmaEnergyPerAtomNnp);\n    log << strpr(\"Mean/sigma force           : %16.8E   / %16.8E\\n\",\n                 meanForceNnp,\n                 sigmaForceNnp);\n    log << \"----------------------------------\\n\";\n    // Now set conversion quantities of Mode class.\n    if (settings[\"normalize_data_set\"] == \"stats-only\")\n    {\n        log << \"Data set statistics computation completed, now make up for \\n\";\n        log << \"initially skipped normalization setup...\\n\";\n        log << \"\\n\";\n        setupNormalization(false);\n    }\n    else if (settings[\"normalize_data_set\"] == \"ref\")\n    {\n        log << \"Normalization based on standard deviation of reference data \"\n               \"selected:\\n\";\n        log << \"\\n\";\n        log << \"  mean(e_ref) = 0, sigma(e_ref) = sigma(F_ref) = 1\\n\";\n        log << \"\\n\";\n        meanEnergy = meanEnergyPerAtomRef;\n        convEnergy = 1.0 / sigmaEnergyPerAtomRef;\n        if (useForcesLocal) convLength = sigmaForceRef / sigmaEnergyPerAtomRef;\n        else convLength = 1.0;\n        normalize = true;\n    }\n    else if (settings[\"normalize_data_set\"] == \"force\")\n    {\n        if (!useForcesLocal)\n        {\n            throw runtime_error(\"ERROR: Selected normalization mode only \"\n                                \"possible when forces are available.\\n\");\n        }\n        log << \"Normalization based on standard deviation of reference forces \"\n               \"and their\\n\";\n        log << \"initial prediction selected:\\n\";\n        log << \"\\n\";\n        log << \"  mean(e_ref) = 0, sigma(F_NNP) = sigma(F_ref) = 1\\n\";\n        log << \"\\n\";\n        meanEnergy = meanEnergyPerAtomRef;\n        convEnergy = sigmaForceNnp / sigmaForceRef;\n        convLength = sigmaForceNnp;\n        normalize = true;\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown data set normalization mode.\\n\");\n    }\n\n    if (settings[\"normalize_data_set\"] != \"stats-only\")\n    {\n        log << \"Final conversion data:\\n\";\n        log << strpr(\"Mean ref. energy per atom = %24.16E\\n\", meanEnergy);\n        log << strpr(\"Conversion factor energy  = %24.16E\\n\", convEnergy);\n        log << strpr(\"Conversion factor length  = %24.16E\\n\", convLength);\n        log << \"----------------------------------\\n\";\n    }\n\n    if ((myRank == 0) &&\n        (settings[\"normalize_data_set\"] != \"stats-only\"))\n    {\n        log << \"\\n\";\n        log << \"Writing backup of original settings file to \"\n               \"\\\"input.nn.bak\\\".\\n\";\n        ofstream fileSettings;\n        fileSettings.open(\"input.nn.bak\");\n        writeSettingsFile(&fileSettings);\n        fileSettings.close();\n\n        log << \"\\n\";\n        log << \"Writing normalization data to settings file \\\"input.nn\\\".\\n\";\n        string n1 = strpr(\"mean_energy %24.16E # nnp-train\\n\",\n                          meanEnergyPerAtomRef);\n        string n2 = strpr(\"conv_energy %24.16E # nnp-train\\n\",\n                          convEnergy);\n        string n3 = strpr(\"conv_length %24.16E # nnp-train\\n\",\n                          convLength);\n        // Check for existing normalization header and record line numbers\n        // to replace.\n        auto lines = settings.getSettingsLines();\n        map<size_t, string> replace;\n        for (size_t i = 0; i < lines.size(); ++i)\n        {\n            vector<string> sl = split(lines.at(i));\n            if (sl.size() > 0)\n            {\n                if (sl.at(0) == \"mean_energy\") replace[i] = n1;\n                if (sl.at(0) == \"conv_energy\") replace[i] = n2;\n                if (sl.at(0) == \"conv_length\") replace[i] = n3;\n            }\n        }\n        if (!replace.empty())\n        {\n            log << \"WARNING: Preexisting normalization data was found and \"\n                   \"replaced in original \\\"input.nn\\\" file.\\n\";\n        }\n\n        fileSettings.open(\"input.nn\");\n        if (replace.empty())\n        {\n            fileSettings << \"#########################################\"\n                            \"######################################\\n\";\n            fileSettings << \"# DATA SET NORMALIZATION\\n\";\n            fileSettings << \"#########################################\"\n                            \"######################################\\n\";\n            fileSettings << n1;\n            fileSettings << n2;\n            fileSettings << n3;\n            fileSettings << \"#########################################\"\n                            \"######################################\\n\";\n            fileSettings << \"\\n\";\n        }\n        settings.writeSettingsFile(&fileSettings, replace);\n        fileSettings.close();\n    }\n\n    // Now make up for left-out normalization setup, need to repeat entire\n    // symmetry function setup.\n    log << \"\\n\";\n    if (normalize)\n    {\n        log << \"Silently repeating symmetry function setup...\\n\";\n        log.silent = true;\n        for (auto& e : elements) e.clearSymmetryFunctions();\n        setupSymmetryFunctions();\n#ifndef N2P2_FULL_SFD_MEMORY\n        setupSymmetryFunctionMemory(false);\n#endif\n#ifndef N2P2_NO_SF_CACHE\n        setupSymmetryFunctionCache();\n#endif\n#ifndef N2P2_NO_SF_GROUPS\n        setupSymmetryFunctionGroups();\n#endif\n        setupSymmetryFunctionScaling();\n        setupSymmetryFunctionStatistics(false, false, false, false);\n        log.silent = false;\n    }\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Training::setupTraining()\n{\n    log << \"\\n\";\n    log << \"*** SETUP: TRAINING *********************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    if (nnpType == NNPType::HDNNP_4G ||\n        nnpType == NNPType::HDNNP_Q)\n    {\n        log << strpr(\"Running stage %zu of training: \", stage);\n        if      (stage == 1) log << \"electrostatic NN fitting.\\n\";\n        else if (stage == 2) log << \"short-range NN fitting.\\n\";\n        else throw runtime_error(\"\\nERROR: Unknown training stage.\\n\");\n    }\n\n    if ( nnpType == NNPType::HDNNP_2G ||\n        (nnpType == NNPType::HDNNP_4G && stage == 2) ||\n        (nnpType == NNPType::HDNNP_Q  && stage == 2))\n    {\n        useForces = settings.keywordExists(\"use_short_forces\");\n        if (useForces)\n        {\n            log << \"Forces will be used for training.\\n\";\n            if (settings.keywordExists(\"force_weight\"))\n            {\n                forceWeight = atof(settings[\"force_weight\"].c_str());\n            }\n            else\n            {\n                log << \"WARNING: Force weight not set, using default value.\\n\";\n                forceWeight = 1.0;\n            }\n            log << strpr(\"Force update weight: %10.2E\\n\", forceWeight);\n        }\n        else\n        {\n            log << \"Only energies will be used for training.\\n\";\n        }\n    }\n    log << \"Training will act on \\\"\" << nns.at(nnId).name\n        << \"\\\" neural networks.\\n\";\n\n    if (settings.keywordExists(\"main_error_metric\"))\n    {\n        string k;\n        if (settings[\"main_error_metric\"] == \"RMSEpa\")\n        {\n            k = \"energy\"; if (p.exists(k)) p[k].displayMetric = \"RMSEpa\";\n            k = \"force\";  if (p.exists(k)) p[k].displayMetric = \"RMSE\";\n            k = \"charge\"; if (p.exists(k)) p[k].displayMetric = \"RMSE\";\n        }\n        else if (settings[\"main_error_metric\"] == \"RMSE\")\n        {\n            k = \"energy\"; if (p.exists(k)) p[k].displayMetric = \"RMSE\";\n            k = \"force\";  if (p.exists(k)) p[k].displayMetric = \"RMSE\";\n            k = \"charge\"; if (p.exists(k)) p[k].displayMetric = \"RMSE\";\n        }\n        else if (settings[\"main_error_metric\"] == \"MAEpa\")\n        {\n            k = \"energy\"; if (p.exists(k)) p[k].displayMetric = \"MAEpa\";\n            k = \"force\";  if (p.exists(k)) p[k].displayMetric = \"MAE\";\n            k = \"charge\"; if (p.exists(k)) p[k].displayMetric = \"MAE\";\n        }\n        else if (settings[\"main_error_metric\"] == \"MAE\")\n        {\n            k = \"energy\"; if (p.exists(k)) p[k].displayMetric = \"MAE\";\n            k = \"force\";  if (p.exists(k)) p[k].displayMetric = \"MAE\";\n            k = \"charge\"; if (p.exists(k)) p[k].displayMetric = \"MAE\";\n        }\n        else\n        {\n            throw runtime_error(\"ERROR: Unknown error metric.\\n\");\n        }\n    }\n    else\n    {\n        string k;\n        k = \"energy\"; if (p.exists(k)) p[k].displayMetric = \"RMSEpa\";\n        k = \"force\";  if (p.exists(k)) p[k].displayMetric = \"RMSE\";\n        k = \"charge\"; if (p.exists(k)) p[k].displayMetric = \"RMSE\";\n    }\n\n    updaterType = (UpdaterType)atoi(settings[\"updater_type\"].c_str());\n    if (updaterType == UT_GD)\n    {\n        log << strpr(\"Weight update via gradient descent selected: \"\n                     \"updaterType::UT_GD (%d)\\n\",\n                     updaterType);\n    }\n    else if (updaterType == UT_KF)\n    {\n        log << strpr(\"Weight update via Kalman filter selected: \"\n                     \"updaterType::UT_KF (%d)\\n\",\n                     updaterType);\n    }\n    else if (updaterType == UT_LM)\n    {\n        throw runtime_error(\"ERROR: LM algorithm not yet implemented.\\n\");\n        log << strpr(\"Weight update via Levenberg-Marquardt algorithm \"\n                     \"selected: updaterType::UT_LM (%d)\\n\",\n                     updaterType);\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown updater type.\\n\");\n    }\n\n    parallelMode = (ParallelMode)atoi(settings[\"parallel_mode\"].c_str());\n    //if (parallelMode == PM_DATASET)\n    //{\n    //    log << strpr(\"Serial training selected: \"\n    //                 \"ParallelMode::PM_DATASET (%d)\\n\",\n    //                 parallelMode);\n    //}\n    if (parallelMode == PM_TRAIN_RK0)\n    {\n        log << strpr(\"Parallel training (rank 0 updates) selected: \"\n                     \"ParallelMode::PM_TRAIN_RK0 (%d)\\n\",\n                     parallelMode);\n    }\n    else if (parallelMode == PM_TRAIN_ALL)\n    {\n        log << strpr(\"Parallel training (all ranks update) selected: \"\n                     \"ParallelMode::PM_TRAIN_ALL (%d)\\n\",\n                     parallelMode);\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown parallelization mode.\\n\");\n    }\n\n    jacobianMode = (JacobianMode)atoi(settings[\"jacobian_mode\"].c_str());\n    if (jacobianMode == JM_SUM)\n    {\n        log << strpr(\"Gradient summation only selected: \"\n                     \"JacobianMode::JM_SUM (%d)\\n\", jacobianMode);\n        log << \"No Jacobi matrix, gradients of all training candidates are \"\n               \"summed up instead.\\n\";\n    }\n    else if (jacobianMode == JM_TASK)\n    {\n        log << strpr(\"Per-task Jacobian selected: \"\n                     \"JacobianMode::JM_TASK (%d)\\n\",\n                     jacobianMode);\n        log << \"One Jacobi matrix row per MPI task is stored, within each \"\n               \"task gradients are summed up.\\n\";\n    }\n    else if (jacobianMode == JM_FULL)\n    {\n        log << strpr(\"Full Jacobian selected: \"\n                     \"JacobianMode::JM_FULL (%d)\\n\",\n                     jacobianMode);\n        log << \"Each update candidate generates one Jacobi matrix \"\n               \"row entry.\\n\";\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown Jacobian mode.\\n\");\n    }\n\n    if (updaterType == UT_GD && jacobianMode != JM_SUM)\n    {\n        throw runtime_error(\"ERROR: Gradient descent methods can only be \"\n                            \"combined with Jacobian mode JM_SUM.\\n\");\n    }\n\n    if (updateStrategy == US_ELEMENT && nnpType != NNPType::HDNNP_2G)\n    {\n        throw runtime_error(\"ERROR: US_ELEMENT only implemented for \"\n                            \"HDNNP_2G.\\n\");\n    }\n\n    updateStrategy = (UpdateStrategy)atoi(settings[\"update_strategy\"].c_str());\n    // This section is pushed into a separate function because it's needed also\n    // for testing purposes.\n    initializeWeightsMemory(updateStrategy);\n    // Now it is possible to fill the weights arrays with weight parameters\n    // from the neural network.\n    getWeights();\n\n    // Set up update candidate selection modes.\n    setupSelectionMode(\"all\");\n    for (auto k : pk) setupSelectionMode(k);\n\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    repeatedEnergyUpdates = settings.keywordExists(\"repeated_energy_update\");\n    if (useForces && repeatedEnergyUpdates)\n    {\n        throw runtime_error(\"ERROR: Repeated energy updates are not correctly\"\n                            \" implemented at the moment.\\n\");\n        //log << \"After each force update an energy update for the\\n\";\n        //log << \"corresponding structure will be performed.\\n\";\n    }\n\n    freeMemory = !(settings.keywordExists(\"memorize_symfunc_results\"));\n    if (freeMemory)\n    {\n        log << \"Symmetry function memory is cleared after each calculation.\\n\";\n    }\n    else\n    {\n        log << \"Symmetry function memory is reused (HIGH MEMORY USAGE!).\\n\";\n    }\n\n    numEpochs = (size_t)atoi(settings[\"epochs\"].c_str());\n    log << strpr(\"Training will be stopped after %zu epochs.\\n\", numEpochs);\n\n    // Set up how often comparison output files should be written.\n    for (auto k : pk) setupFileOutput(k);\n    // Set up how often weight files should be written.\n    setupFileOutput(\"weights_epoch\");\n    // Set up how often neuron statistics files should be written.\n    setupFileOutput(\"neuronstats\");\n\n    // Prepare training log header.\n    writeTrainingLog = settings.keywordExists(\"write_trainlog\");\n    if (writeTrainingLog && myRank == 0)\n    {\n        if (nnpType == NNPType::HDNNP_4G ||\n            nnpType == NNPType::HDNNP_Q)\n        {\n            trainingLogFileName += strpr(\".stage-%zu\", stage);\n        }\n        log << strpr(\"Training log with update information will be written to:\"\n                     \" %s.\\n\", trainingLogFileName.c_str());\n        trainingLog.open(trainingLogFileName.c_str());\n\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Detailed information on each weight update.\");\n        colSize.push_back(3);\n        colName.push_back(\"U\");\n        colInfo.push_back(\"Update type (E = energy, F = force, Q = charge).\");\n        colSize.push_back(5);\n        colName.push_back(\"epoch\");\n        colInfo.push_back(\"Current training epoch.\");\n        colSize.push_back(10);\n        colName.push_back(\"count\");\n        colInfo.push_back(\"Update counter (Multiple lines with identical count\"\n                          \" for multi-streaming!).\");\n        colSize.push_back(5);\n        colName.push_back(\"proc\");\n        colInfo.push_back(\"MPI process providing this update candidate.\");\n        colSize.push_back(3);\n        colName.push_back(\"tl\");\n        colInfo.push_back(\"Threshold loop counter.\");\n        colSize.push_back(10);\n        colName.push_back(\"rmse_frac\");\n        colInfo.push_back(\"Update candidates error divided by this \"\n                          \"epochs RMSE.\");\n        colSize.push_back(10);\n        colName.push_back(\"s_ind_g\");\n        colInfo.push_back(\"Global structure index.\");\n        colSize.push_back(5);\n        colName.push_back(\"s_ind\");\n        colInfo.push_back(\"Local structure index on this MPI process.\");\n        colSize.push_back(5);\n        colName.push_back(\"a_ind\");\n        colInfo.push_back(\"Atom index.\");\n        colSize.push_back(2);\n        colName.push_back(\"c\");\n        colInfo.push_back(\"Force component (0 = x, 1 = y, 2 = z).\");\n        appendLinesToFile(trainingLog,\n                          createFileHeader(title, colSize, colName, colInfo));\n    }\n\n    // Compute number of updates and properties per update.\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    for (auto k : pk) setupUpdatePlan(k);\n    if (p.exists(\"energy\") && p.exists(\"force\"))\n    {\n        Property& pe = p[\"energy\"];\n        Property& pf = p[\"force\"];\n        log << strpr(\"Energy to force ratio                        : \"\n                     \"     1 : %5.1f\\n\",\n                     static_cast<double>(\n                         pf.numUpdates * pf.patternsPerUpdateGlobal)\n                         / (pe.numUpdates * pe.patternsPerUpdateGlobal));\n        log << strpr(\"Energy to force percentages                  : \"\n                     \"%5.1f%% : %5.1f%%\\n\",\n                     pe.numUpdates * pe.patternsPerUpdateGlobal * 100.0 /\n                     (pe.numUpdates * pe.patternsPerUpdateGlobal\n                     + pf.numUpdates * pf.patternsPerUpdateGlobal),\n                     pf.numUpdates * pf.patternsPerUpdateGlobal * 100.0 /\n                     (pe.numUpdates * pe.patternsPerUpdateGlobal\n                     + pf.numUpdates * pf.patternsPerUpdateGlobal));\n    }\n    double totalUpdates = 0.0;\n    for (auto k : pk) totalUpdates += p[k].numUpdates;\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n\n    // Allocate error and Jacobian arrays.\n    for (auto k : pk) allocateArrays(k);\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n\n    // Set up new C++11 random number generator (TODO: move it!).\n    rngGlobalNew.seed(gsl_rng_get(rngGlobal));\n    rngNew.seed(gsl_rng_get(rng));\n\n    // Updater setup.\n    GradientDescent::DescentType descentType = GradientDescent::DT_FIXED;\n    if (updaterType == UT_GD)\n    {\n        descentType = (GradientDescent::DescentType)\n                      atoi(settings[\"gradient_type\"].c_str());\n    }\n    KalmanFilter::KalmanType kalmanType = KalmanFilter::KT_STANDARD;\n    if (updaterType == UT_KF)\n    {\n        kalmanType = (KalmanFilter::KalmanType)\n                     atoi(settings[\"kalman_type\"].c_str());\n    }\n\n    for (size_t i = 0; i < numUpdaters; ++i)\n    {\n        if ( (myRank == 0) || (parallelMode == PM_TRAIN_ALL) )\n        {\n            if (updaterType == UT_GD)\n            {\n                updaters.push_back(\n                    (Updater*)new GradientDescent(numWeightsPerUpdater.at(i),\n                                                  descentType));\n            }\n            else if (updaterType == UT_KF)\n            {\n                updaters.push_back(\n                    (Updater*)new KalmanFilter(numWeightsPerUpdater.at(i),\n                                               kalmanType));\n            }\n            updaters.back()->setState(&(weights.at(i).front()));\n            updaters.back()->setupTiming(strpr(\"wupd%zu\", i));\n            updaters.back()->resetTimingLoop();\n        }\n    }\n    if (updaters.size() > 0) hasUpdaters = true;\n    else hasUpdaters = false;\n\n    if (hasUpdaters && updaterType == UT_GD)\n    {\n        if (descentType == GradientDescent::DT_FIXED)\n        {\n            double const eta = atof(settings[\"gradient_eta\"].c_str());\n            for (size_t i = 0; i < numUpdaters; ++i)\n            {\n                GradientDescent* u =\n                    dynamic_cast<GradientDescent*>(updaters.at(i));\n                u->setParametersFixed(eta);\n            }\n        }\n        if (descentType == GradientDescent::DT_ADAM)\n        {\n            double const eta = atof(settings[\"gradient_adam_eta\"].c_str());\n            double const beta1 = atof(settings[\"gradient_adam_beta1\"].c_str());\n            double const beta2 = atof(settings[\"gradient_adam_beta2\"].c_str());\n            double const eps = atof(settings[\"gradient_adam_epsilon\"].c_str());\n            for (size_t i = 0; i < numUpdaters; ++i)\n            {\n                GradientDescent* u =\n                    dynamic_cast<GradientDescent*>(updaters.at(i));\n                u->setParametersAdam(eta, beta1, beta2, eps);\n            }\n        }\n    }\n    else if (hasUpdaters && updaterType == UT_KF)\n    {\n        if (kalmanType == KalmanFilter::KT_STANDARD)\n        {\n            double const epsilon = atof(settings[\"kalman_epsilon\"].c_str());\n            double const q0      = atof(settings[\"kalman_q0\"     ].c_str());\n            double const qtau    = atof(settings[\"kalman_qtau\"   ].c_str())\n                                 / totalUpdates;\n            log << \"qtau is divided by number \"\n                   \"of projected updates per epoch.\\n\";\n            double const qmin    = atof(settings[\"kalman_qmin\"   ].c_str());\n            double const eta0    = atof(settings[\"kalman_eta\"    ].c_str());\n            double etatau  = 1.0;\n            double etamax  = eta0;\n            if (settings.keywordExists(\"kalman_etatau\") &&\n                settings.keywordExists(\"kalman_etamax\"))\n            {\n                etatau = atof(settings[\"kalman_etatau\"].c_str())\n                       / totalUpdates;\n                log << \"etatau is divided by number \"\n                       \"of projected updates per epoch.\\n\";\n                etamax = atof(settings[\"kalman_etamax\"].c_str());\n            }\n            for (size_t i = 0; i < updaters.size(); ++i)\n            {\n                KalmanFilter* u = dynamic_cast<KalmanFilter*>(updaters.at(i));\n                u->setParametersStandard(epsilon,\n                                         q0,\n                                         qtau,\n                                         qmin,\n                                         eta0,\n                                         etatau,\n                                         etamax);\n            }\n        }\n        else if (kalmanType == KalmanFilter::KT_FADINGMEMORY)\n        {\n            double const epsilon = atof(settings[\"kalman_epsilon\"].c_str());\n            double const q0      = atof(settings[\"kalman_q0\"     ].c_str());\n            double const qtau    = atof(settings[\"kalman_qtau\"   ].c_str())\n                                 / totalUpdates;\n            log << \"qtau is divided by number \"\n                   \"of projected updates per epoch.\\n\";\n            double const qmin   = atof(settings[\"kalman_qmin\"].c_str());\n            double const lambda =\n                                 atof(settings[\"kalman_lambda_short\"].c_str());\n            //double const nu =\n            //       pow(atof(settings[\"kalman_nue_short\"].c_str()), numProcs);\n            //log << \"nu is exponentiated with the number of streams.\\n\";\n            double const nu = atof(settings[\"kalman_nue_short\"].c_str());\n            for (size_t i = 0; i < updaters.size(); ++i)\n            {\n                KalmanFilter* u = dynamic_cast<KalmanFilter*>(updaters.at(i));\n                u->setParametersFadingMemory(epsilon,\n                                             q0,\n                                             qtau,\n                                             qmin,\n                                             lambda,\n                                             nu);\n            }\n        }\n    }\n\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    for (size_t i = 0; i < updaters.size(); ++i)\n    {\n            if (updateStrategy == US_COMBINED)\n            {\n                log << strpr(\"Combined weight updater:\\n\");\n            }\n            else if (updateStrategy == US_ELEMENT)\n            {\n                log << strpr(\"Weight updater for element %2s :\\n\",\n                             elements.at(i).getSymbol().c_str());\n            }\n            log << \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n            log << updaters.at(i)->info();\n            if (updaterType == UT_KF)\n            {\n                log << \"Note: During training loop the actual observation\\n\";\n                log << \"      size corresponds to error vector size:\\n\";\n                for (auto k : pk)\n                {\n                    log << strpr(\"sizeObservation = %zu (%s updates)\\n\",\n                                 p[k].error.at(i).size(), k.c_str());\n                }\n            }\n            log << \"-----------------------------------------\"\n                   \"--------------------------------------\\n\";\n    }\n\n    log << strpr(\"TIMING Finished setup: %.2f seconds.\\n\",\n                 sw[\"setup\"].stop());\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvector<string> Training::setupNumericDerivCheck()\n{\n    log << \"\\n\";\n    log << \"*** SETUP WEIGHT DERIVATIVES CHECK ******\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n    log << \"Weight derivatives will be checked for these properties:\\n\";\n    for (auto k : pk) log << \" - \" + p[k].plural + \"\\n\";\n    log << \"\\n\";\n\n    if (nnpType == NNPType::HDNNP_2G)\n    {\n        nnId = \"short\";\n        readNeuralNetworkWeights(nnId, \"weights.%03zu.data\");\n    }\n    else if ( (nnpType == NNPType::HDNNP_4G || nnpType == NNPType::HDNNP_Q) &&\n               stage == 1)\n    {\n        nnId = \"elec\";\n        readNeuralNetworkWeights(nnId, \"weightse.%03zu.data\");\n    }\n    else if ( (nnpType == NNPType::HDNNP_4G || nnpType == NNPType::HDNNP_Q) &&\n               stage == 2)\n    {\n        nnId = \"short\";\n        readNeuralNetworkWeights(\"elec\", \"weightse.%03zu.data\");\n        readNeuralNetworkWeights(nnId, \"weights.%03zu.data\");\n    }\n    initializeWeightsMemory();\n    getWeights();\n\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return pk;\n}\n\nvoid Training::calculateNeighborLists()\n{\n    sw[\"nl\"].start();\n    log << \"\\n\";\n    log << \"*** CALCULATE NEIGHBOR LISTS ************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n\n#ifdef _OPENMP\n    int num_threads = omp_get_max_threads();\n    omp_set_num_threads(1);\n    log << strpr(\"Temporarily disabling OpenMP parallelization: %d threads.\\n\",\n                 omp_get_max_threads());\n#endif\n    log << \"Calculating neighbor lists for all structures.\\n\";\n    double maxCutoffRadiusPhys = maxCutoffRadius;\n    if (normalize) maxCutoffRadiusPhys = maxCutoffRadius / convLength;\n    // TODO: may not actually be cutoff (ewald real space cutoff is often\n    // larger)\n    if (nnpType != NNPType::HDNNP_4G)\n        log << strpr(\"Cutoff radius for neighbor lists: %f\\n\",\n                 maxCutoffRadiusPhys);\n    double maxCutoffRadiusAllStructures = 0.0;\n    for (vector<Structure>::iterator it = structures.begin();\n         it != structures.end(); ++it)\n    {\n        // List only needs to be sorted for 4G\n        if (nnpType == NNPType::HDNNP_4G)\n        {\n            it->calculateMaxCutoffRadiusOverall(\n                                            ewaldSetup,\n                                            screeningFunction.getOuter(),\n                                            maxCutoffRadius);\n            it->calculateNeighborList(maxCutoffRadius,cutoffs);\n\n            if (it->maxCutoffRadiusOverall > maxCutoffRadiusAllStructures)\n                maxCutoffRadiusAllStructures = it->maxCutoffRadiusOverall;\n        }\n        else\n        {\n            it->calculateNeighborList(maxCutoffRadius);\n        }\n    }\n    if (normalize) maxCutoffRadiusAllStructures /= convLength;\n    if (nnpType == NNPType::HDNNP_4G)\n        log << strpr(\"Largest cutoff radius for neighbor lists: %f\\n\",\n                     maxCutoffRadiusAllStructures);\n#ifdef _OPENMP\n    omp_set_num_threads(num_threads);\n    log << strpr(\"Restoring OpenMP parallelization: max. %d threads.\\n\",\n                 omp_get_max_threads());\n#endif\n\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    log << strpr(\"TIMING Finished neighbor lists: %.2f seconds.\\n\",\n                 sw[\"nl\"].stop());\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Training::calculateError(\n                             map<string, pair<string, string>> const fileNames)\n{\n#ifdef _OPENMP\n    int num_threads = omp_get_max_threads();\n    omp_set_num_threads(1);\n#endif\n    vector<string> write;\n    for (auto i : fileNames)\n    {\n        if (i.second.first.size() == 0 || i.second.second.size() == 0)\n        {\n            throw runtime_error(\"ERROR: No filename provided for comparison \"\n                                \"files.\\n\");\n        }\n        write.push_back(i.first);\n    }\n    auto doWrite = [&write](string key){\n                       return find(write.begin(),\n                                   write.end(),\n                                   key) != write.end();\n                   };\n\n\n    map<string, size_t> countTrain;\n    map<string, size_t> countTest;\n    for (auto k : pk) countTrain[k] = 0;\n    for (auto k : pk) countTest[k]  = 0;\n\n    map<string, ofstream> filesTrain;\n    map<string, ofstream> filesTest;\n\n    // Reset current error metrics.\n    for (auto k : pk)\n    {\n        for (auto& m : p[k].errorTrain) m.second = 0.0;\n        for (auto& m : p[k].errorTest) m.second = 0.0;\n    }\n\n    for (auto k : write)\n    {\n        filesTrain[k].open(strpr(\"%s.%04d\",\n                                 fileNames.at(k).first.c_str(),\n                                 myRank).c_str());\n        filesTest[k].open(strpr(\"%s.%04d\",\n                                fileNames.at(k).second.c_str(),\n                                myRank).c_str());\n        // File header.\n        vector<string> header;\n        if (myRank == 0)\n        {\n            vector<string> title;\n            vector<string> colName;\n            vector<string> colInfo;\n            vector<size_t> colSize;\n            if (k == \"energy\")\n            {\n                title.push_back(\"Energy comparison.\");\n                colSize.push_back(10);\n                colName.push_back(\"index\");\n                colInfo.push_back(\"Structure index.\");\n                colSize.push_back(16);\n                colName.push_back(\"Eref\");\n                colInfo.push_back(\"Reference potential energy per atom \"\n                                  \"(training units).\");\n                colSize.push_back(16);\n                colName.push_back(\"Ennp\");\n                colInfo.push_back(\"NNP potential energy per atom \"\n                                  \"(training units).\");\n            }\n            else if (k == \"force\")\n            {\n                title.push_back(\"Force comparison.\");\n                colSize.push_back(10);\n                colName.push_back(\"index_s\");\n                colInfo.push_back(\"Structure index.\");\n                colSize.push_back(10);\n                colName.push_back(\"index_a\");\n                colInfo.push_back(\"Atom index (x, y, z components in \"\n                                  \"consecutive lines).\");\n                colSize.push_back(16);\n                colName.push_back(\"Fref\");\n                colInfo.push_back(\"Reference force (training units).\");\n                colSize.push_back(16);\n                colName.push_back(\"Fnnp\");\n                colInfo.push_back(\"NNP force (training units).\");\n            }\n            else if (k == \"charge\")\n            {\n                title.push_back(\"Charge comparison.\");\n                colSize.push_back(10);\n                colName.push_back(\"index_s\");\n                colInfo.push_back(\"Structure index.\");\n                colSize.push_back(10);\n                colName.push_back(\"index_a\");\n                colInfo.push_back(\"Atom index.\");\n                colSize.push_back(16);\n                colName.push_back(\"Qref\");\n                colInfo.push_back(\"Reference charge.\");\n                colSize.push_back(16);\n                colName.push_back(\"Qnnp\");\n                colInfo.push_back(\"NNP charge.\");\n            }\n            header = createFileHeader(title, colSize, colName, colInfo);\n            appendLinesToFile(filesTrain.at(k), header);\n            appendLinesToFile(filesTest.at(k), header);\n        }\n    }\n\n    for (vector<Structure>::iterator it = structures.begin();\n         it != structures.end(); ++it)\n    {\n#ifdef N2P2_NO_SF_GROUPS\n        calculateSymmetryFunctions((*it), useForces);\n#else\n        calculateSymmetryFunctionGroups((*it), useForces);\n#endif\n        // TODO: Can we use evaluateNNP?\n        if ( nnpType == Mode::NNPType::HDNNP_4G )\n        {\n            if ( stage == 1 )\n            {\n                calculateAtomicNeuralNetworks((*it), useForces, nnId);\n                chargeEquilibration((*it), false);\n            }\n            else\n            {\n                if ( !it->hasCharges || (!it->hasAMatrix && useForces) )\n                {\n                    calculateAtomicNeuralNetworks((*it), useForces,\n                                                    \"elec\");\n                    chargeEquilibration((*it), useForces);\n                }\n                calculateAtomicNeuralNetworks((*it), useForces, \"short\");\n                calculateEnergy((*it));\n                if (useForces) calculateForces((*it));\n            }\n        }\n        else\n        {\n            calculateAtomicNeuralNetworks((*it), useForces, nnId);\n            calculateEnergy((*it));\n            if (useForces) calculateForces((*it));\n        }\n\n        for (auto k : pk)\n        {\n            map<string, double>* error = nullptr;\n            size_t* count = nullptr;\n            ofstream* file = nullptr;\n            if (it->sampleType == Structure::ST_TRAINING)\n            {\n                error = &(p[k].errorTrain);\n                count = &(countTrain.at(k));\n                if (doWrite(k)) file = &(filesTrain.at(k));\n            }\n            else if (it->sampleType == Structure::ST_TEST)\n            {\n                error = &(p[k].errorTest);\n                count = &(countTest.at(k));\n                if (doWrite(k)) file = &(filesTest.at(k));\n            }\n\n            it->updateError(k, *error, *count);\n            if (doWrite(k))\n            {\n                if      (k == \"energy\") (*file) << it->getEnergyLine();\n                else if (k == \"force\")\n                {\n                    for (auto l : it->getForcesLines()) (*file) << l;\n                }\n                else if (k == \"charge\")\n                {\n                    for (auto l : it->getChargesLines()) (*file) << l;\n                }\n            }\n        }\n        if (freeMemory) it->freeAtoms(true, maxCutoffRadius);\n        it->clearElectrostatics();\n    }\n\n    for (auto k : pk)\n    {\n        collectError(k, p[k].errorTrain, countTrain.at(k));\n        collectError(k, p[k].errorTest, countTest.at(k));\n        if (doWrite(k))\n        {\n            filesTrain.at(k).close();\n            filesTest.at(k).close();\n            MPI_Barrier(comm);\n            if (myRank == 0)\n            {\n                combineFiles(fileNames.at(k).first);\n                combineFiles(fileNames.at(k).second);\n            }\n        }\n    }\n\n#ifdef _OPENMP\n    omp_set_num_threads(num_threads);\n#endif\n\n    return;\n}\n\nvoid Training::calculateErrorEpoch()\n{\n    // Check whether property comparison files should be written for\n    // this epoch.\n    map<string, pair<string, string>> fileNames;\n\n    for (auto const& ip : p)\n    {\n        string const& k = ip.first; // key\n        Property const& d = ip.second; // data\n        if (d.writeCompEvery > 0 &&\n            (epoch % d.writeCompEvery == 0 || epoch <= d.writeCompAlways))\n        {\n            string middle;\n            if      (k == \"energy\") middle = \"points\";\n            else if (k == \"force\" ) middle = \"forces\";\n            else if (k == \"charge\") middle = \"charges\";\n            fileNames[k] = make_pair(strpr(\"train%s.%06zu.out\",\n                                           middle.c_str(), epoch),\n                                     strpr(\"test%s.%06zu.out\",\n                                           middle.c_str(), epoch));\n        }\n    }\n\n    // Calculate errors and write comparison files.\n    calculateError(fileNames);\n\n    return;\n}\n\nvoid Training::calculateChargeErrorVec( Structure const &s,\n                                        Eigen::VectorXd &cVec,\n                                        double          &cNorm)\n{\n    cVec.resize(s.numAtoms);\n    for (size_t i = 0; i < s.numAtoms; ++i)\n    {\n        cVec(i) = s.atoms.at(i).charge - s.atoms.at(i).chargeRef;\n    }\n    cNorm = cVec.norm();\n    return;\n}\n\nvoid Training::printHeader()\n{\n    string metric = \"?\";\n    string peratom = \"\";\n\n    log << \"The training loop output covers different errors, update and\\n\";\n    log << \"timing information. The following quantities are organized\\n\";\n    log << \"according to the matrix scheme below:\\n\";\n    log << \"-------------------------------------------------------------------\\n\";\n    log << \"ep ........ Epoch.\\n\";\n    for (auto k : pk)\n    {\n        string const& pmetric = p[k].displayMetric;\n        if      (pmetric.find(\"RMSE\") != pmetric.npos) metric = \"RMSE\";\n        else if (pmetric.find(\"MAE\")  != pmetric.npos) metric = \"MAE\";\n        if      (pmetric.find(\"pa\") != pmetric.npos) peratom = \" per atom\";\n        else peratom = \"\";\n        log << p[k].tiny << \"_count ... Number of \" << k << \" updates.\\n\";\n        log << p[k].tiny << \"_train ... \" << metric << \" of training \"\n            << p[k].plural << peratom << \".\\n\";\n        log << p[k].tiny << \"_test .... \" << metric << \" of test     \"\n            << p[k].plural << peratom << \".\\n\";\n        //log << p[k].tiny << \"_time ........ Time for \" << k << \" updates \"\n        //                 << \"(seconds).\\n\";\n        log << p[k].tiny << \"_pt ...... Percentage of time for \" << k <<\n                            \" updates w.r.t. to t_train.\\n\";\n    }\n    log << \"count ..... Total number of updates.\\n\";\n    log << \"train ..... Percentage of time for training.\\n\";\n    log << \"error ..... Percentage of time for error calculation.\\n\";\n    log << \"other ..... Percentage of time for other purposes.\\n\";\n    log << \"epoch ..... Total time for this epoch (seconds).\\n\";\n    log << \"total ..... Total time for all epochs (seconds).\\n\";\n    log << \"-------------------------------------------------------------------\\n\";\n    for (auto k : pk)\n    {\n        log << strpr(\"%-6s\", k.c_str())\n            << strpr(\"  %5s\", \"ep\")\n            << strpr(\"  %7s\", (p[k].tiny + \"_count\").c_str())\n            << strpr(\"   %11s\", (p[k].tiny + \"_train\").c_str())\n            << strpr(\"   %11s\", (p[k].tiny + \"_test\").c_str())\n            << strpr(\"   %5s\", (p[k].tiny + \"_pt\").c_str())\n            << \"\\n\";\n    }\n    log << strpr(\"%-6s\", \"timing\")\n        << strpr(\"  %5s\", \"ep\")\n        << strpr(\"  %7s\", \"count\")\n        << strpr(\"  %5s\", \"train\")\n        << strpr(\"  %5s\", \"error\")\n        << strpr(\"  %5s\", \"other\")\n        << strpr(\"  %9s\", \"epoch\")\n        << strpr(\"  %9s\", \"total\")\n        << \"\\n\";\n    log << \"-------------------------------------------------------------------\\n\";\n\n    return;\n}\n\nvoid Training::printEpoch()\n{\n    double timeLoop = sw[\"loop\"].getLoop();\n    double timeTrain = sw[\"train\"].getLoop();\n    size_t totalUpdates = 0;\n    for (auto k : pk)\n    {\n        totalUpdates += p[k].countUpdates;\n        double timeProp = sw[k].getLoop();\n        string caps = k;\n        for (auto& c : caps) c = toupper(c);\n        log << strpr(\"%-6s\", caps.c_str());\n        log << strpr(\"  %5zu\", epoch);\n        log << strpr(\"  %7zu\", p[k].countUpdates);\n        if (normalize)\n        {\n            log << strpr(\"   %11.5E   %11.5E\",\n                         physical(k, p[k].errorTrain.at(p[k].displayMetric)),\n                         physical(k, p[k].errorTest.at(p[k].displayMetric)));\n        }\n        else\n        {\n            log << strpr(\"   %11.5E   %11.5E\",\n                         p[k].errorTrain.at(p[k].displayMetric),\n                         p[k].errorTest.at(p[k].displayMetric));\n        }\n        if (epoch == 0) log << strpr(\"   %5.1f\", 0.0);\n        else log << strpr(\"   %5.1f\", timeProp / timeTrain * 100.0);\n        log << \"\\n\";\n    }\n    double timeOther = timeLoop;\n    timeOther -= sw[\"error\"].getLoop();\n    timeOther -= sw[\"train\"].getLoop();\n    log << strpr(\"%-6s\", \"TIMING\");\n    log << strpr(\"  %5zu\", epoch);\n    log << strpr(\"  %7zu\", totalUpdates);\n    log << strpr(\"  %5.1f\", sw[\"train\"].getLoop() / timeLoop * 100.0);\n    log << strpr(\"  %5.1f\", sw[\"error\"].getLoop() / timeLoop * 100.0);\n    log << strpr(\"  %5.1f\", timeOther / timeLoop * 100.0);\n    log << strpr(\"  %9.2f\", sw[\"loop\"].getLoop());\n    log << strpr(\"  %9.2f\", sw[\"loop\"].getTotal());\n    log << \"\\n\";\n\n    return;\n}\n\nvoid Training::writeWeights(string const& nnName,\n                            string const& fileNameFormat) const\n{\n    ofstream file;\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        string fileName = strpr(fileNameFormat.c_str(),\n                                elements.at(i).getAtomicNumber());\n        file.open(fileName.c_str());\n        elements.at(i).neuralNetworks.at(nnName).writeConnections(file);\n        file.close();\n    }\n\n    return;\n}\n\nvoid Training::writeWeightsEpoch() const\n{\n    if (writeWeightsEvery > 0 &&\n        (epoch % writeWeightsEvery == 0 || epoch <= writeWeightsAlways))\n    {\n        string weightFileFormat = strpr(\".%%03zu.%06d.out\", epoch);\n        if ( nnpType == NNPType::HDNNP_2G ||\n            (nnpType == NNPType::HDNNP_4G && stage == 2) ||\n            (nnpType == NNPType::HDNNP_Q  && stage == 2))\n        {\n            weightFileFormat = \"weights\" + weightFileFormat;\n        }\n        else if ((nnpType == NNPType::HDNNP_4G && stage == 1) ||\n                 (nnpType == NNPType::HDNNP_Q  && stage == 1))\n        {\n            weightFileFormat = \"weightse\" + weightFileFormat;\n        }\n        writeWeights(nnId, weightFileFormat);\n    }\n\n    return;\n}\n\nvoid Training::writeHardness(string const& fileNameFormat) const\n{\n    ofstream file;\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        string fileName = strpr(fileNameFormat.c_str(),\n                                elements.at(i).getAtomicNumber());\n        file.open(fileName.c_str());\n        double hardness = elements.at(i).getHardness();\n        if (normalize) hardness = physical(\"hardness\", hardness);\n        file << hardness << endl;\n        file.close();\n    }\n\n    return;\n}\n\nvoid Training::writeHardnessEpoch() const\n{\n    if (writeWeightsEvery > 0 &&\n        (epoch % writeWeightsEvery == 0 || epoch <= writeWeightsAlways) &&\n        nnpType == NNPType::HDNNP_4G && stage == 1)\n    {\n        string hardnessFileFormat = strpr(\".%%03zu.%06d.out\", epoch);\n        hardnessFileFormat = \"hardness\" + hardnessFileFormat;\n        writeHardness(hardnessFileFormat);\n    }\n\n    return;\n}\n\nvoid Training::writeLearningCurve(bool append, string const fileName) const\n{\n    ofstream file;\n    string fileNameActual = fileName;\n    if (nnpType == NNPType::HDNNP_4G ||\n        nnpType == NNPType::HDNNP_Q)\n    {\n        fileNameActual += strpr(\".stage-%zu\", stage);\n    }\n\n    if (append) file.open(fileNameActual.c_str(), ofstream::app);\n    else\n    {\n        file.open(fileNameActual.c_str());\n\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Learning curves for training properties:\");\n        for (auto k : pk)\n        {\n            title.push_back(\" * \" + p[k].plural);\n        }\n        colSize.push_back(10);\n        colName.push_back(\"epoch\");\n        colInfo.push_back(\"Current epoch.\");\n\n        map<string, string> text;\n        text[\"RMSEpa\"] = \"RMSE of %s %s per atom\";\n        text[\"RMSE\"]   = \"RMSE of %s %s\";\n        text[\"MAEpa\"]  = \"MAE of %s %s per atom\";\n        text[\"MAE\"]    = \"MAE of %s %s\";\n\n        for (auto k : pk)\n        {\n            for (auto m : p[k].errorMetrics)\n            {\n                colSize.push_back(16);\n                colName.push_back(m + \"_\" + p[k].tiny + \"train_pu\");\n                colInfo.push_back(strpr(\n                                       (text[m] + \" (physical units)\").c_str(),\n                                       \"training\",\n                                       p[k].plural.c_str()));\n                colSize.push_back(16);\n                colName.push_back(m + \"_\" + p[k].tiny + \"test_pu\");\n                colInfo.push_back(strpr(\n                                       (text[m] + \" (physical units)\").c_str(),\n                                       \"test\",\n                                       p[k].plural.c_str()));\n            }\n        }\n        if (normalize)\n        {\n            for (auto k : pk)\n            {\n                // Internal units only for energies, forces and charges.\n                if (!(k == \"energy\" || k == \"force\" || k == \"charge\")) continue;\n                for (auto m : p[k].errorMetrics)\n                {\n                    colSize.push_back(16);\n                    colName.push_back(m + \"_\" + p[k].tiny + \"train_iu\");\n                    colInfo.push_back(strpr(\n                                       (text[m] + \" (training units)\").c_str(),\n                                       \"training\",\n                                       p[k].plural.c_str()));\n                    colSize.push_back(16);\n                    colName.push_back(m + \"_\" + p[k].tiny + \"test_iu\");\n                    colInfo.push_back(strpr(\n                                       (text[m] + \" (training units)\").c_str(),\n                                       \"test\",\n                                       p[k].plural.c_str()));\n                }\n            }\n        }\n        appendLinesToFile(file,\n                          createFileHeader(title, colSize, colName, colInfo));\n    }\n\n    file << strpr(\"%10zu\", epoch);\n    if (normalize)\n    {\n        for (auto k : pk)\n        {\n            if (!(k == \"energy\" || k == \"force\" || k == \"charge\")) continue;\n            for (auto m : p[k].errorMetrics)\n            {\n                file << strpr(\" %16.8E %16.8E\",\n                              physical(k, p[k].errorTrain.at(m)),\n                              physical(k, p[k].errorTest.at(m)));\n            }\n        }\n    }\n    for (auto k : pk)\n    {\n        for (auto m : p[k].errorMetrics)\n        {\n            file << strpr(\" %16.8E %16.8E\",\n                          p[k].errorTrain.at(m),\n                          p[k].errorTest.at(m));\n        }\n    }\n    file << \"\\n\";\n    file.flush();\n    file.close();\n\n    return;\n}\n\nvoid Training::writeNeuronStatistics(string const& id,\n                                     string const& fileName) const\n{\n    ofstream file;\n    if (myRank == 0)\n    {\n        file.open(fileName.c_str());\n\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Statistics for individual neurons of network \\\"\"\n                        + id + \"\\\" gathered during RMSE calculation.\");\n        colSize.push_back(10);\n        colName.push_back(\"element\");\n        colInfo.push_back(\"Element index.\");\n        colSize.push_back(10);\n        colName.push_back(\"neuron\");\n        colInfo.push_back(\"Neuron number.\");\n        colSize.push_back(10);\n        colName.push_back(\"count\");\n        colInfo.push_back(\"Number of neuron value computations.\");\n        colSize.push_back(16);\n        colName.push_back(\"min\");\n        colInfo.push_back(\"Minimum neuron value encounterd.\");\n        colSize.push_back(16);\n        colName.push_back(\"max\");\n        colInfo.push_back(\"Maximum neuron value encounterd.\");\n        colSize.push_back(16);\n        colName.push_back(\"mean\");\n        colInfo.push_back(\"Mean neuron value.\");\n        colSize.push_back(16);\n        colName.push_back(\"sigma\");\n        colInfo.push_back(\"Standard deviation of neuron value.\");\n        appendLinesToFile(file,\n                          createFileHeader(title, colSize, colName, colInfo));\n    }\n\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        size_t n = elements.at(i).neuralNetworks.at(id).getNumNeurons();\n        vector<long>   count(n, 0);\n        vector<double> min(n, 0.0);\n        vector<double> max(n, 0.0);\n        vector<double> mean(n, 0.0);\n        vector<double> sigma(n, 0.0);\n        elements.at(i).neuralNetworks.at(id).\n            getNeuronStatistics(&(count.front()),\n                                &(min.front()),\n                                &(max.front()),\n                                &(mean.front()),\n                                &(sigma.front()));\n        // Collect statistics from all processors on proc 0.\n        if (myRank == 0)\n        {\n            MPI_Reduce(MPI_IN_PLACE, &(count.front()), n, MPI_LONG  , MPI_SUM, 0, comm);\n            MPI_Reduce(MPI_IN_PLACE, &(min.front())  , n, MPI_DOUBLE, MPI_MIN, 0, comm);\n            MPI_Reduce(MPI_IN_PLACE, &(max.front())  , n, MPI_DOUBLE, MPI_MAX, 0, comm);\n            MPI_Reduce(MPI_IN_PLACE, &(mean.front()) , n, MPI_DOUBLE, MPI_SUM, 0, comm);\n            MPI_Reduce(MPI_IN_PLACE, &(sigma.front()), n, MPI_DOUBLE, MPI_SUM, 0, comm);\n        }\n        else\n        {\n            MPI_Reduce(&(count.front()), &(count.front()), n, MPI_LONG  , MPI_SUM, 0, comm);\n            MPI_Reduce(&(min.front())  , &(min.front())  , n, MPI_DOUBLE, MPI_MIN, 0, comm);\n            MPI_Reduce(&(max.front())  , &(max.front())  , n, MPI_DOUBLE, MPI_MAX, 0, comm);\n            MPI_Reduce(&(mean.front()) , &(mean.front()) , n, MPI_DOUBLE, MPI_SUM, 0, comm);\n            MPI_Reduce(&(sigma.front()), &(sigma.front()), n, MPI_DOUBLE, MPI_SUM, 0, comm);\n        }\n        if (myRank == 0)\n        {\n            for (size_t j = 0; j < n; ++j)\n            {\n                size_t m = count.at(j);\n                sigma.at(j) = sqrt((m * sigma.at(j) - mean.at(j) * mean.at(j))\n                            / (m * (m - 1)));\n                mean.at(j) /= m;\n                file << strpr(\"%10d %10d %10d %16.8E %16.8E %16.8E %16.8E\\n\",\n                              i + 1,\n                              j + 1,\n                              count[j],\n                              min[j],\n                              max[j],\n                              mean[j],\n                              sigma[j]);\n            }\n        }\n    }\n\n    if (myRank == 0)\n    {\n        file.close();\n    }\n\n    return;\n}\n\nvoid Training::writeNeuronStatisticsEpoch() const\n{\n    if (writeNeuronStatisticsEvery > 0 &&\n        (epoch % writeNeuronStatisticsEvery == 0\n        || epoch <= writeNeuronStatisticsAlways))\n    {\n        string fileName = strpr(\"neuron-stats.%s.%06zu.out\",\n                                nnId.c_str(), epoch);\n        if (nnpType == NNPType::HDNNP_4G ||\n            nnpType == NNPType::HDNNP_Q)\n        {\n            fileName += strpr(\".stage-%zu\", stage);\n        }\n        writeNeuronStatistics(nnId, fileName);\n    }\n\n    return;\n}\n\nvoid Training::resetNeuronStatistics()\n{\n    for (vector<Element>::iterator it = elements.begin();\n         it != elements.end(); ++it)\n    {\n        for (auto& nn : it->neuralNetworks) nn.second.resetNeuronStatistics();\n    }\n    return;\n}\n\nvoid Training::writeUpdaterStatus(bool         append,\n                                  string const fileNameFormat) const\n{\n    ofstream file;\n    string fileNameFormatActual = fileNameFormat;\n    if (nnpType == NNPType::HDNNP_4G ||\n        nnpType == NNPType::HDNNP_Q)\n    {\n        fileNameFormatActual += strpr(\".stage-%zu\", stage);\n    }\n\n    for (size_t i = 0; i < numUpdaters; ++i)\n    {\n        string fileName;\n        if (updateStrategy == US_COMBINED)\n        {\n            fileName = strpr(fileNameFormatActual.c_str(), 0);\n        }\n        else if (updateStrategy == US_ELEMENT)\n        {\n            fileName = strpr(fileNameFormatActual.c_str(),\n                             elementMap.atomicNumber(i));\n        }\n        if (append) file.open(fileName.c_str(), ofstream::app);\n        else\n        {\n            file.open(fileName.c_str());\n            appendLinesToFile(file, updaters.at(i)->statusHeader());\n        }\n        file << updaters.at(i)->status(epoch);\n        file.close();\n    }\n\n    return;\n}\n\nvoid Training::sortUpdateCandidates(string const& property)\n{\n    // Update error for all structures.\n    for (auto& uc : p[property].updateCandidates)\n    {\n        if (property == \"energy\")\n        {\n            Structure const& s = structures.at(uc.s);\n            uc.error = fabs((s.energyRef - s.energy) / s.numAtoms);\n        }\n        else if (property == \"force\")\n        {\n            Structure const& s = structures.at(uc.s);\n            uc.error = 0.0;\n            for (auto &sc : uc.subCandidates)\n            {\n                Atom const& ai = s.atoms.at(sc.a);\n                sc.error = fabs(ai.fRef[sc.c] - ai.f[sc.c]);\n                uc.error += sc.error;\n            }\n            uc.error /= uc.subCandidates.size();\n        }\n        else if (property == \"charge\")\n        {\n            Structure const& s = structures.at(uc.s);\n            uc.error = 0.0;\n            for (auto const& a : s.atoms)\n            {\n                uc.error = fabs(a.chargeRef - a.charge);\n            }\n            uc.error /= s.numAtoms;\n        }\n    }\n    // Sort update candidates list.\n    sort(p[property].updateCandidates.begin(),\n         p[property].updateCandidates.end());\n\n    for (auto &uc : p[property].updateCandidates)\n    {\n        if (uc.subCandidates.size() > 0)\n            sort(uc.subCandidates.begin(),\n                uc.subCandidates.end());\n    }\n\n    // Reset current position.\n    p[property].posUpdateCandidates = 0;\n    for (auto &uc : p[property].updateCandidates)\n    {\n        uc.posSubCandidates = 0;\n    }\n\n    return;\n}\n\nvoid Training::shuffleUpdateCandidates(string const& property)\n{\n    shuffle(p[property].updateCandidates.begin(),\n            p[property].updateCandidates.end(),\n            rngNew);\n\n    for (auto &uc : p[property].updateCandidates)\n    {\n        if (uc.subCandidates.size() > 0)\n            shuffle(uc.subCandidates.begin(),\n                uc.subCandidates.end(),\n                rngNew);\n    }\n\n    // Reset current position.\n    p[property].posUpdateCandidates = 0;\n     for (auto &uc : p[property].updateCandidates)\n    {\n        uc.posSubCandidates = 0;\n    }\n\n    return;\n}\n\nvoid Training::setEpochSchedule()\n{\n    // Clear epoch schedule.\n    epochSchedule.clear();\n    vector<int>(epochSchedule).swap(epochSchedule);\n\n    // Grow schedule vector by each property's number of desired updates.\n    // Fill this array looping in reverse direction for backward compatibility.\n    //for (size_t i = 0; i < pk.size(); ++i)\n    for (int i = pk.size() - 1; i >= 0; --i)\n    {\n        epochSchedule.insert(epochSchedule.end(), p[pk.at(i)].numUpdates, i);\n    }\n\n    // Return if there is only a single training property.\n    if (pk.size() == 1) return;\n\n    // Now shuffle the schedule to get a random sequence.\n    shuffle(epochSchedule.begin(), epochSchedule.end(), rngGlobalNew);\n\n    //for (size_t i = 0; i < epochSchedule.size(); ++i)\n    //{\n    //    log << strpr(\"%zu %zu\\n\", i, epochSchedule.at(i));\n    //}\n\n    return;\n}\n\nvoid Training::checkSelectionMode()\n{\n    for (auto k : pk)\n    {\n        if (p[k].selectionModeSchedule.find(epoch)\n            != p[k].selectionModeSchedule.end())\n        {\n            p[k].selectionMode = p[k].selectionModeSchedule[epoch];\n            if (epoch != 0)\n            {\n                string message = \"INFO   Switching selection mode for \"\n                                 \"property \\\"\" + k + \"\\\" to \";\n                if (p[k].selectionMode == SM_RANDOM)\n                {\n                    message += strpr(\"SM_RANDOM (%d).\\n\", p[k].selectionMode);\n                }\n                else if (p[k].selectionMode == SM_SORT)\n                {\n                    message += strpr(\"SM_SORT (%d).\\n\", p[k].selectionMode);\n                }\n                else if (p[k].selectionMode == SM_THRESHOLD)\n                {\n                    message += strpr(\"SM_THRESHOLD (%d).\\n\",\n                                     p[k].selectionMode);\n                }\n                log << message;\n            }\n        }\n    }\n\n    return;\n}\n\nvoid Training::loop()\n{\n    sw[\"loop\"].start();\n    log << \"\\n\";\n    log << \"*** TRAINING LOOP ***********************\"\n           \"**************************************\\n\";\n    log << \"\\n\";\n    printHeader();\n\n    // Calculate initial RMSE and write comparison files.\n    sw[\"error\"].start();\n    calculateErrorEpoch();\n    sw[\"error\"].stop();\n\n    // Write initial weights to files.\n    if (myRank == 0) writeWeightsEpoch();\n\n    // Write initial hardness to files (checks for corresponding type and\n    // stage)\n    if (myRank == 0) writeHardnessEpoch();\n\n    // Write learning curve.\n    if (myRank == 0) writeLearningCurve(false);\n\n    // Write updater status to file.\n    if (myRank == 0) writeUpdaterStatus(false);\n\n    // Write neuron statistics.\n    writeNeuronStatisticsEpoch();\n\n    // Print timing information.\n    sw[\"loop\"].stop();\n    printEpoch();\n\n    // Check if training should be continued.\n    while (advance())\n    {\n        sw[\"loop\"].start();\n\n        // Increment epoch counter.\n        epoch++;\n        log << \"------\\n\";\n\n        // Reset update counters.\n        for (auto k : pk) p[k].countUpdates = 0;\n\n        // Check if selection mode should be changed in this epoch.\n        checkSelectionMode();\n\n        // Sort or shuffle update candidates.\n        for (auto k : pk)\n        {\n            if (p[k].selectionMode == SM_SORT) sortUpdateCandidates(k);\n            else shuffleUpdateCandidates(k);\n        }\n\n        // Determine epoch update schedule.\n        setEpochSchedule();\n\n        // Perform property updates according to schedule.\n        sw[\"train\"].start();\n        for (auto i : epochSchedule)\n        {\n            string property = pk.at(i);\n            update(property);\n            p[property].countUpdates++;\n        }\n        sw[\"train\"].stop();\n\n        // Reset neuron statistics.\n        resetNeuronStatistics();\n\n        // Calculate errors and write comparison files.\n        sw[\"error\"].start();\n        calculateErrorEpoch();\n        sw[\"error\"].stop();\n\n        // Write weights to files.\n        if (myRank == 0) writeWeightsEpoch();\n\n        // Write hardness to files (checks for corresponding type and stage).\n        if (myRank == 0) writeHardnessEpoch();\n\n        // Append to learning curve.\n        if (myRank == 0) writeLearningCurve(true);\n\n        // Write updater status to file.\n        if (myRank == 0) writeUpdaterStatus(true);\n\n        // Write neuron statistics.\n        writeNeuronStatisticsEpoch();\n\n        // Print error overview and timing information.\n        sw[\"loop\"].stop();\n        printEpoch();\n\n        if (myRank == 0) writeTimingData(epoch != 1);\n    }\n\n    log << \"-----------------------------------------\"\n           \"--------------------------------------\\n\";\n    log << strpr(\"TIMING Training loop finished: %.2f seconds.\\n\",\n                 sw[\"loop\"].getTotal());\n    log << \"*****************************************\"\n           \"**************************************\\n\";\n\n    return;\n}\n\nvoid Training::update(string const& property)\n{\n    // Shortcuts.\n    string const& k = property; // Property key.\n    Property& pu = p[k]; // Update property.\n    // Start watch for error and jacobian computation, reset loop timer if\n    // first update in this epoch.\n    bool newLoop = pu.countUpdates == 0;\n    sw[k].start(newLoop);\n    sw[k + \"_err\"].start(newLoop);\n\n#ifdef _OPENMP\n    int num_threads = omp_get_max_threads();\n    omp_set_num_threads(1);\n#endif\n\n    ///////////////////////////////////////////////////////////////////////////\n    // PART 1: Find update candidate, compute error fractions and derivatives\n    ///////////////////////////////////////////////////////////////////////////\n\n    size_t batchSize = pu.taskBatchSize;\n    if (batchSize == 0) batchSize = pu.patternsPerUpdate;\n    bool derivatives = false;\n    if (k == \"force\") derivatives = true;\n\n    vector<size_t> thresholdLoopCount(batchSize, 0);\n    vector<double> currentRmseFraction(batchSize, 0.0);\n\n    bool useSubCandidates = (k == \"force\" && nnpType == NNPType::HDNNP_4G);\n\n    // Either consider only UpdateCandidates or SubCandidates\n    vector<size_t> currentUpdateCandidates(batchSize, 0);\n\n    for (size_t i = 0; i < numUpdaters; ++i)\n    {\n        fill(pu.error.at(i).begin(), pu.error.at(i).end(), 0.0);\n        fill(pu.jacobian.at(i).begin(), pu.jacobian.at(i).end(), 0.0);\n    }\n\n    // Loop over (mini-)batch size.\n    for (size_t b = 0; b < batchSize; ++b)\n    {\n        UpdateCandidate* c = NULL; // Actual current update candidate.\n        SubCandidate* sC = NULL; // Actual current sub candidate.\n        size_t* posCandidates = NULL; // position of sub or update candidate.\n        size_t indexBest = 0; // Index of best update candidate so far.\n        double rmseFractionBest = 0.0; // RMSE of best update candidate so far.\n\n        // For SM_THRESHOLD need to loop until candidate's RMSE is above\n        // threshold. Other modes don't loop here.\n        size_t trials = 1;\n        if (pu.selectionMode == SM_THRESHOLD) trials = pu.rmseThresholdTrials;\n        size_t il = 0;\n        for (il = 0; il < trials; ++il)\n        {\n            // Restart position index if necessary.\n            if (pu.posUpdateCandidates >= pu.updateCandidates.size())\n            {\n                pu.posUpdateCandidates = 0;\n            }\n            //log << strpr(\"pos %zu b %zu size %zu\\n\", pu.posUpdateCandidates, b, currentUpdateCandidates.size());\n            // Set current update candidate.\n            c = &(pu.updateCandidates.at(pu.posUpdateCandidates));\n\n            if (c->posSubCandidates >= c->subCandidates.size())\n                c->posSubCandidates = 0;\n            // Shortcut for position counter of interest.\n            if (useSubCandidates)\n            {\n                posCandidates = &(c->posSubCandidates);\n                sC = &(c->subCandidates.at(c->posSubCandidates));\n            }\n            else\n            {\n                posCandidates = &(pu.posUpdateCandidates);\n                if (c->subCandidates.size() > 0)\n                    sC = &(c->subCandidates.front());\n            }\n\n            // Keep update candidates (for logging later).\n            currentUpdateCandidates.at(b) = *posCandidates;\n\n            // Shortcut for current structure.\n            Structure& s = structures.at(c->s);\n            // Calculate symmetry functions (if results are already stored\n            // these functions will return immediately).\n#ifdef NOSFGROUPS\n            calculateSymmetryFunctions(s, derivatives);\n#else\n            calculateSymmetryFunctionGroups(s, derivatives);\n#endif\n            // For SM_THRESHOLD calculate RMSE of update candidate.\n            if (pu.selectionMode == SM_THRESHOLD)\n            {\n                if (k == \"energy\")\n                {\n                    if (nnpType == NNPType::HDNNP_2G)\n                    {\n                        calculateAtomicNeuralNetworks(s, derivatives);\n                        calculateEnergy(s);\n                        currentRmseFraction.at(b) =\n                            fabs(s.energyRef - s.energy)\n                            / (s.numAtoms * pu.errorTrain.at(\"RMSEpa\"));\n                    }\n                    // Assume stage 2.\n                    else if (nnpType == NNPType::HDNNP_4G)\n                    {\n                        if (!s.hasCharges)\n                        {\n                            calculateAtomicNeuralNetworks(s, derivatives, \"elec\");\n                            chargeEquilibration(s, derivatives);\n                        }\n                        calculateAtomicNeuralNetworks(s, derivatives, \"short\");\n                        calculateEnergy(s);\n                        currentRmseFraction.at(b) = fabs(s.energyRef - s.energy)\n                                                  / (s.numAtoms\n                                                     * pu.errorTrain.at(\"RMSEpa\"));\n                    }\n                    else if (nnpType == NNPType::HDNNP_Q)\n                    {\n                        // TODO: Reuse already present charge-NN data and\n                        // compute only short-NN energy contributions.\n                        throw runtime_error(\"ERROR: Not implemented.\\n\");\n                    }\n                }\n                else if (k == \"force\")\n                {\n                    if (nnpType == NNPType::HDNNP_2G)\n                    {\n                        calculateAtomicNeuralNetworks(s, derivatives);\n                        calculateForces(s);\n                        Atom const& a = s.atoms.at(sC->a);\n                        currentRmseFraction.at(b) =\n                            fabs(a.fRef[sC->c]\n                                    - a.f[sC->c])\n                            / pu.errorTrain.at(\"RMSE\");\n                    }\n                    // Assume stage 2.\n                    else if (nnpType == NNPType::HDNNP_4G)\n                    {\n                        if (!s.hasAMatrix)\n                        {\n                            calculateAtomicNeuralNetworks(s, derivatives, \"elec\");\n                            chargeEquilibration(s, derivatives);\n                        }\n                        calculateAtomicNeuralNetworks(s, derivatives, \"short\");\n                        calculateForces(s);\n                        Atom const& a = s.atoms.at(sC->a);\n                        currentRmseFraction.at(b) =\n                            fabs(a.fRef[sC->c]\n                                    - a.f[sC->c])\n                            / pu.errorTrain.at(\"RMSE\");\n                    }\n                    else if (nnpType == NNPType::HDNNP_Q)\n                    {\n                        // TODO: Reuse already present charge-NN data and\n                        // compute only short-NN force contributions.\n                        throw runtime_error(\"ERROR: Not implemented.\\n\");\n                    }\n                }\n                else if (k == \"charge\")\n                {\n                    // Assume stage 1.\n                    if (nnpType == NNPType::HDNNP_4G)\n                    {\n                        calculateAtomicNeuralNetworks(s, derivatives, \"\");\n                        chargeEquilibration(s, false);\n                        Eigen::VectorXd QError;\n                        double QErrorNorm;\n                        calculateChargeErrorVec(s, QError, QErrorNorm);\n                        currentRmseFraction.at(b) =\n                            QErrorNorm / sqrt(s.numAtoms)\n                            / pu.errorTrain.at(\"RMSE\");\n                    }\n                    else if (nnpType == NNPType::HDNNP_Q)\n                    {\n                        // Compute only charge-NN\n                        Atom& a = s.atoms.at(sC->a);\n                        NeuralNetwork& nn =\n                            elements.at(a.element).neuralNetworks.at(nnId);\n                        nn.setInput(&(a.G.front()));\n                        nn.propagate();\n                        nn.getOutput(&(a.charge));\n                        currentRmseFraction.at(b) =\n                            fabs(a.chargeRef - a.charge)\n                            / pu.errorTrain.at(\"RMSE\");\n                    }\n                }\n                // If force RMSE is above threshold stop loop immediately.\n                if (currentRmseFraction.at(b) > pu.rmseThreshold)\n                {\n                    // Increment position in update candidate list.\n                    (*posCandidates)++;\n                    break;\n                }\n                // If loop continues, free memory and remember best candidate\n                // so far.\n                if (freeMemory)\n                {\n                    s.freeAtoms(true, maxCutoffRadius);\n                }\n                if (!useSubCandidates) s.clearElectrostatics();\n\n                if (currentRmseFraction.at(b) > rmseFractionBest)\n                {\n                    rmseFractionBest = currentRmseFraction.at(b);\n                    indexBest = *posCandidates;\n                }\n                // Increment position in update candidate list.\n                (*posCandidates)++;\n            }\n            // Break loop for all selection modes but SM_THRESHOLD.\n            else if (pu.selectionMode == SM_RANDOM ||\n                     pu.selectionMode == SM_SORT)\n            {\n                // Increment position in update candidate list.\n                (*posCandidates)++;\n                break;\n            }\n        }\n        thresholdLoopCount.at(b) = il;\n\n        // If loop was not stopped because of a proper update candidate found\n        // (RMSE above threshold) use best candidate during iteration.\n        if (pu.selectionMode == SM_THRESHOLD && il == trials)\n        {\n            // Set best candidate.\n            currentUpdateCandidates.at(b) = indexBest;\n            currentRmseFraction.at(b) = rmseFractionBest;\n            // Need to calculate the symmetry functions again, maybe results\n            // were not stored.\n            Structure& s = structures.at(c->s);\n#ifdef N2P2_NO_SF_GROUPS\n            calculateSymmetryFunctions(s, derivatives);\n#else\n            calculateSymmetryFunctionGroups(s, derivatives);\n#endif\n        }\n\n        // If new update candidate, determine number of subcandidates needed\n        // before going to next candidate.\n        if (useSubCandidates)\n        {\n            if (pu.countGroupedSubCand == 0)\n            {\n                pu.numGroupedSubCand = static_cast<size_t>(\n                                c->subCandidates.size() * pu.epochFraction);\n                MPI_Allreduce(  MPI_IN_PLACE, &(pu.numGroupedSubCand), 1,\n                                MPI_INT, MPI_MIN, comm);\n                //if (myRank == 0)\n                //    cout << \"group size: \" << pu.numGroupedSubCand << endl;\n            }\n            pu.countGroupedSubCand++;\n        }\n\n        ///////////////////////////////////////////////////////////////////////\n        // PART 2: Compute error vector and Jacobian\n        ///////////////////////////////////////////////////////////////////////\n\n        Structure& s = structures.at(c->s);\n        // Temporary storage for derivative contributions of atoms (dXdc stores\n        // dEdc, dFdc or dQdc for energy, force or charge update, respectively.\n        vector<vector<double>> dXdc;\n        dXdc.resize(numElements);\n        // Temporary storage vector for charge errors in structure\n        Eigen::VectorXd QError;\n        QError.resize(s.numAtoms);\n        double QErrorNorm = 0;\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            size_t n = elements.at(i).neuralNetworks.at(nnId)\n                       .getNumConnections();\n            dXdc.at(i).resize(n, 0.0);\n        }\n        // Precalculate offset in Jacobian array.\n        size_t iu = 0;\n        vector<size_t> offset(numElements, 0);\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            if (updateStrategy == US_ELEMENT) iu = i;\n            else iu = 0;\n            if (parallelMode == PM_TRAIN_ALL && jacobianMode != JM_SUM)\n            {\n                // Offset from multiple streams/tasks\n                offset.at(i) += pu.offsetPerTask.at(myRank)\n                              * numWeightsPerUpdater.at(iu);\n                //log << strpr(\"%zu os 1: %zu \", i, offset.at(i));\n            }\n            if (jacobianMode == JM_FULL)\n            {\n                // Offset from batch training (multiple contributions from\n                // single stream/task\n                offset.at(i) += b * numWeightsPerUpdater.at(iu);\n                //log << strpr(\"%zu os 2: %zu \", i, offset.at(i));\n            }\n            if (updateStrategy == US_COMBINED)\n            {\n                // Offset from multiple elements in contribution from single\n                // stream/task\n                offset.at(i) += weightsOffset.at(i);\n                //log << strpr(\"%zu os 3: %zu\", i, offset.at(i));\n            }\n            //log << strpr(\" %zu final os: %zu\\n\", i, offset.at(i));\n        }\n        // Now compute Jacobian.\n        if (k == \"energy\")\n        {\n            if (nnpType == NNPType::HDNNP_2G || nnpType == NNPType::HDNNP_4G)\n            {\n                if (nnpType == NNPType::HDNNP_4G && !s.hasCharges)\n                {\n                   calculateAtomicNeuralNetworks(s, derivatives, \"elec\");\n                   chargeEquilibration(s, derivatives);\n                }\n                // Loop over atoms and calculate atomic energy contributions.\n                for (vector<Atom>::iterator it = s.atoms.begin();\n                     it != s.atoms.end(); ++it)\n                {\n                    size_t i = it->element;\n                    NeuralNetwork& nn = elements.at(i).neuralNetworks.at(nnId);\n\n                    // TODO: This part should simplify with improved NN class.\n                    for (size_t j = 0; j < it->G.size(); ++j)\n                    {\n                        nn.setInput(j, it->G.at(j));\n                    }\n                    if (nnpType == NNPType::HDNNP_4G)\n                        nn.setInput(it->G.size(), it->charge);\n                    nn.propagate();\n                    nn.getOutput(&(it->energy));\n                    // Compute derivative of output node with respect to all\n                    // neural network connections (weights + biases).\n                    nn.calculateDEdc(&(dXdc.at(i).front()));\n                    // Finally sum up Jacobian.\n                    if (updateStrategy == US_ELEMENT) iu = i;\n                    else iu = 0;\n                    for (size_t j = 0; j < dXdc.at(i).size(); ++j)\n                    {\n                        pu.jacobian.at(iu).at(offset.at(i) + j) +=\n                            dXdc.at(i).at(j);\n                    }\n                }\n            }\n            // Assume stage 2.\n            else if (nnpType == NNPType::HDNNP_Q)\n            {\n                // TODO: Lots of stuff.\n                throw runtime_error(\"ERROR: Not implemented.\\n\");\n            }\n        }\n        else if (k == \"force\")\n        {\n            if (nnpType == NNPType::HDNNP_2G || nnpType == NNPType::HDNNP_4G )\n            {\n                if (nnpType == NNPType::HDNNP_4G)\n                {\n                    if (!s.hasAMatrix)\n                    {\n                       calculateAtomicNeuralNetworks(s, derivatives, \"elec\");\n                       chargeEquilibration(s, derivatives);\n                    }\n                    s.calculateDQdr(vector<size_t>{sC->a},\n                                    vector<size_t>{sC->c},\n                                    maxCutoffRadius,\n                                    elements);\n                }\n\n                // Loop over atoms and calculate atomic energy contributions.\n                for (vector<Atom>::iterator it = s.atoms.begin();\n                     it != s.atoms.end(); ++it)\n                {\n                    // For force update save derivative of symmetry function\n                    // with respect to coordinate.\n#ifndef N2P2_FULL_SFD_MEMORY\n                    collectDGdxia((*it), sC->a, sC->c);\n\n                    if (nnpType == NNPType::HDNNP_4G)\n                    {\n                        double dQdxia = s.atoms.at(sC->a).dQdr.at(it->index)[sC->c];\n                        dGdxia.back() = dQdxia;\n                    }\n#else\n                    it->collectDGdxia(sC->a, sC->c, maxCutoffRadius);\n                    if (nnpType == NNPType::HDNNP_4G)\n                    {\n                        double dQdxia = s.atoms.at(sC->a).dQdr.at(it->index)[sC->c];\n                        it->dGdxia.resize(it->G.size() + 1);\n                        it->dGdxia.back() = dQdxia;\n                    }\n#endif\n                    size_t i = it->element;\n                    NeuralNetwork& nn = elements.at(i).neuralNetworks.at(nnId);\n                    // TODO: This part should simplify with improved NN class.\n                    for (size_t j = 0; j < it->G.size(); ++j)\n                    {\n                        nn.setInput(j, it->G.at(j));\n                    }\n                    if (nnpType == NNPType::HDNNP_4G)\n                        nn.setInput(it->G.size(), it->charge);\n                    nn.propagate();\n                    if (derivatives) nn.calculateDEdG(&((it->dEdG).front()));\n                    nn.getOutput(&(it->energy));\n\n                    // Compute derivative of output node with respect to all\n                    // neural network connections (weights + biases).\n#ifndef N2P2_FULL_SFD_MEMORY\n                    nn.calculateDFdc(&(dXdc.at(i).front()),\n                                     &(dGdxia.front()));\n#else\n                    nn.calculateDFdc(&(dXdc.at(i).front()),\n                                     &(it->dGdxia.front()));\n#endif\n                    // Finally sum up Jacobian.\n                    if (updateStrategy == US_ELEMENT) iu = i;\n                    else iu = 0;\n                    for (size_t j = 0; j < dXdc.at(i).size(); ++j)\n                    {\n                        pu.jacobian.at(iu).at(offset.at(i) + j) +=\n                            dXdc.at(i).at(j);\n                    }\n                }\n\n            }\n            // Assume stage 2.\n            else if (nnpType == NNPType::HDNNP_Q)\n            {\n                // TODO: Lots of stuff.\n                throw runtime_error(\"ERROR: Not implemented.\\n\");\n            }\n        }\n        else if (k == \"charge\")\n        {\n            // Assume stage 1.\n            if (nnpType == NNPType::HDNNP_4G)\n            {\n\n                // Vector for storing all atoms dChi/dc\n                vector<vector<double>> dChidc;\n                dChidc.resize(s.numAtoms);\n                for (size_t k = 0; k < s.numAtoms; ++k)\n                {\n                    Atom& ak = s.atoms.at(k);\n                    size_t n = elements.at(ak.element).neuralNetworks.at(nnId)\n                               .getNumConnections();\n                    dChidc.at(k).resize(n, 0.0);\n\n                    NeuralNetwork& nn =\n                        elements.at(ak.element).neuralNetworks.at(nnId);\n                    nn.setInput(&(ak.G.front()));\n                    nn.propagate();\n                    nn.getOutput(&(ak.chi));\n                    // Compute derivative of output node with respect to all\n                    // neural network connections (weights + biases).\n                    nn.calculateDEdc(&(dChidc.at(k).front()));\n                    if (normalize)\n                    {\n                        ak.chi = normalized(\"negativity\", ak.chi);\n                        for (auto& dChidGi : ak.dChidG)\n                            dChidGi = normalized(\"negativity\", dChidGi);\n                        for (auto& dChidci : dChidc.at(k))\n                            dChidci = normalized(\"negativity\", dChidci);\n                    }\n\n                }\n                chargeEquilibration(s, false);\n\n                vector<Eigen::VectorXd> dQdChi;\n                s.calculateDQdChi(dQdChi);\n                vector<Eigen::VectorXd> dQdJ;\n                s.calculateDQdJ(dQdJ);\n\n                calculateChargeErrorVec(s, QError, QErrorNorm);\n\n                if (QErrorNorm != 0)\n                {\n                    // Finally sum up Jacobian.\n                    for (size_t i = 0; i < s.numAtoms; ++i)\n                    {\n                        // weights\n                        for (size_t k = 0; k < s.numAtoms; ++k)\n                        {\n                            size_t l = s.atoms.at(k).element;\n                            for (size_t j = 0; j < dChidc.at(k).size(); ++j)\n                            {\n                                // 1 / QErrorNorm * (Q-Qref) * dQ/dChi * dChi/dc\n                                pu.jacobian.at(0).at(offset.at(l) + j) +=\n                                    1.0 / QErrorNorm * QError(i)\n                                    * dQdChi.at(k)(i) * dChidc.at(k).at(j);\n                            }\n                        }\n                        // hardness (actually h, where J=h^2)\n                        for (size_t k = 0; k < numElements; ++k)\n                        {\n                            size_t n = elements.at(k).neuralNetworks.at(nnId)\n                                       .getNumConnections();\n                            pu.jacobian.at(0).at(offset.at(k) + n) +=\n                                        1.0 / QErrorNorm\n                                        * QError(i) * dQdJ.at(k)(i) * 2\n                                        * sqrt(elements.at(k).getHardness());\n                        }\n                    }\n                }\n            }\n\n            else if (nnpType == NNPType::HDNNP_Q)\n            {\n                // Shortcut to selected atom.\n                Atom& a = s.atoms.at(sC->a);\n                size_t i = a.element;\n                NeuralNetwork& nn = elements.at(i).neuralNetworks.at(nnId);\n                nn.setInput(&(a.G.front()));\n                nn.propagate();\n                nn.getOutput(&(a.charge));\n                // Compute derivative of output node with respect to all\n                // neural network connections (weights + biases).\n                nn.calculateDEdc(&(dXdc.at(i).front()));\n                // Finally sum up Jacobian.\n                if (updateStrategy == US_ELEMENT) iu = i;\n                else iu = 0;\n                for (size_t j = 0; j < dXdc.at(i).size(); ++j)\n                {\n                    pu.jacobian.at(iu).at(offset.at(i) + j) +=\n                        dXdc.at(i).at(j);\n                }\n            }\n        }\n\n        // Sum up total potential energy or calculate force.\n        if (k == \"energy\")\n        {\n            calculateEnergy(s);\n            currentRmseFraction.at(b) = fabs(s.energyRef - s.energy)\n                                      / (s.numAtoms\n                                         * pu.errorTrain.at(\"RMSEpa\"));\n        }\n        else if (k == \"force\")\n        {\n            calculateForces(s);\n            Atom const& a = s.atoms.at(sC->a);\n            currentRmseFraction.at(b) = fabs(a.fRef[sC->c] - a.f[sC->c])\n                                      / pu.errorTrain.at(\"RMSE\");\n        }\n        else if (k == \"charge\")\n        {\n            if (nnpType == NNPType::HDNNP_4G)\n            {\n                currentRmseFraction.at(b) = QErrorNorm / sqrt(s.numAtoms)\n                                            / pu.errorTrain.at(\"RMSE\");\n            }\n            else\n            {\n                Atom const& a = s.atoms.at(sC->a);\n                currentRmseFraction.at(b) = fabs(a.chargeRef - a.charge)\n                                          / pu.errorTrain.at(\"RMSE\");\n            }\n        }\n\n        // Now symmetry function memory is not required any more for this\n        // update.\n        if (freeMemory) s.freeAtoms(true, maxCutoffRadius);\n        if (nnpType == NNPType::HDNNP_4G && !useSubCandidates)\n            s.clearElectrostatics();\n\n        // Precalculate offset in error array.\n        size_t offset2 = 0;\n        if (parallelMode == PM_TRAIN_ALL && jacobianMode != JM_SUM)\n        {\n            offset2 += pu.offsetPerTask.at(myRank);\n            //log << strpr(\"os 4: %zu \", offset2);\n        }\n        if (jacobianMode == JM_FULL)\n        {\n            offset2 += b;\n            //log << strpr(\"os 5: %zu \", offset2);\n        }\n        //log << strpr(\" final os: %zu\\n\", offset2);\n\n\n        // Compute error vector (depends on update strategy).\n        if (updateStrategy == US_COMBINED)\n        {\n            if (k == \"energy\")\n            {\n                pu.error.at(0).at(offset2) += s.energyRef - s.energy;\n            }\n            else if (k == \"force\")\n            {\n                Atom const& a = s.atoms.at(sC->a);\n                pu.error.at(0).at(offset2) +=  a.fRef[sC->c] - a.f[sC->c];\n            }\n            else if (k == \"charge\")\n            {\n                if (nnpType == NNPType::HDNNP_4G)\n                    pu.error.at(0).at(offset2) = -QErrorNorm;\n                else\n                {\n                    Atom const& a = s.atoms.at(sC->a);\n                    pu.error.at(0).at(offset2) += a.chargeRef - a.charge;\n                }\n            }\n        }\n        else if (updateStrategy == US_ELEMENT)\n        {\n            for (size_t i = 0; i < numUpdaters; ++i)\n            {\n                if (k == \"energy\")\n                {\n                    pu.error.at(i).at(offset2) += (s.energyRef - s.energy)\n                                               * s.numAtomsPerElement.at(i)\n                                               / s.numAtoms;\n                }\n                else if (k == \"force\")\n                {\n                    Atom const& a = s.atoms.at(sC->a);\n                    pu.error.at(i).at(offset2) += (a.fRef[sC->c] - a.f[sC->c])\n                                               * a.numNeighborsPerElement.at(i)\n                                               / a.numNeighbors;\n                }\n                else if (k == \"charge\")\n                {\n                    if (nnpType == NNPType::HDNNP_4G)\n                    {\n                        throw runtime_error(\"ERROR: US_ELEMENT not implemented\"\n                                \" for HDNNP_4G.\\n\");\n                    }\n                    Atom const& a = s.atoms.at(sC->a);\n                    pu.error.at(i).at(offset2) += a.chargeRef - a.charge;\n                }\n            }\n        }\n    }\n\n    // Apply force update weight to error and Jacobian.\n    if (k == \"force\")\n    {\n        for (size_t i = 0; i < numUpdaters; ++i)\n        {\n            for (size_t j = 0; j < pu.error.at(i).size(); ++j)\n            {\n                pu.error.at(i).at(j) *= forceWeight;\n            }\n            for (size_t j = 0; j < pu.jacobian.at(i).size(); ++j)\n            {\n                pu.jacobian.at(i).at(j) *= forceWeight;\n            }\n        }\n    }\n    sw[k + \"_err\"].stop();\n\n    ///////////////////////////////////////////////////////////////////////\n    // PART 3: Communicate error and Jacobian.\n    ///////////////////////////////////////////////////////////////////////\n\n    sw[k + \"_com\"].start(newLoop);\n    if (jacobianMode == JM_SUM)\n    {\n        if (parallelMode == PM_TRAIN_RK0)\n        {\n            for (size_t i = 0; i < numUpdaters; ++i)\n            {\n                if (myRank == 0) MPI_Reduce(MPI_IN_PLACE             , &(pu.error.at(i).front()), 1, MPI_DOUBLE, MPI_SUM, 0, comm);\n                else             MPI_Reduce(&(pu.error.at(i).front()), &(pu.error.at(i).front()), 1, MPI_DOUBLE, MPI_SUM, 0, comm);\n                if (myRank == 0) MPI_Reduce(MPI_IN_PLACE                , &(pu.jacobian.at(i).front()), numWeightsPerUpdater.at(i), MPI_DOUBLE, MPI_SUM, 0, comm);\n                else             MPI_Reduce(&(pu.jacobian.at(i).front()), &(pu.jacobian.at(i).front()), numWeightsPerUpdater.at(i), MPI_DOUBLE, MPI_SUM, 0, comm);\n            }\n        }\n        else if (parallelMode == PM_TRAIN_ALL)\n        {\n            for (size_t i = 0; i < numUpdaters; ++i)\n            {\n                MPI_Allreduce(MPI_IN_PLACE, &(pu.error.at(i).front()), 1, MPI_DOUBLE, MPI_SUM, comm);\n                MPI_Allreduce(MPI_IN_PLACE, &(pu.jacobian.at(i).front()), numWeightsPerUpdater.at(i), MPI_DOUBLE, MPI_SUM, comm);\n            }\n        }\n    }\n    else if (jacobianMode == JM_TASK)\n    {\n        if (parallelMode == PM_TRAIN_RK0)\n        {\n            for (size_t i = 0; i < numUpdaters; ++i)\n            {\n                if (myRank == 0) MPI_Gather(MPI_IN_PLACE             , 1, MPI_DOUBLE, &(pu.error.at(i).front()),  1, MPI_DOUBLE, 0, comm);\n                else             MPI_Gather(&(pu.error.at(i).front()), 1, MPI_DOUBLE, NULL                     ,  1, MPI_DOUBLE, 0, comm);\n                if (myRank == 0) MPI_Gather(MPI_IN_PLACE                , numWeightsPerUpdater.at(i), MPI_DOUBLE, &(pu.jacobian.at(i).front()), numWeightsPerUpdater.at(i), MPI_DOUBLE, 0, comm);\n                else             MPI_Gather(&(pu.jacobian.at(i).front()), numWeightsPerUpdater.at(i), MPI_DOUBLE, NULL                        , numWeightsPerUpdater.at(i), MPI_DOUBLE, 0, comm);\n            }\n        }\n        else if (parallelMode == PM_TRAIN_ALL)\n        {\n            for (size_t i = 0; i < numUpdaters; ++i)\n            {\n                MPI_Allgather(MPI_IN_PLACE, 1, MPI_DOUBLE, &(pu.error.at(i).front()),  1, MPI_DOUBLE, comm);\n                MPI_Allgather(MPI_IN_PLACE, numWeightsPerUpdater.at(i), MPI_DOUBLE, &(pu.jacobian.at(i).front()), numWeightsPerUpdater.at(i), MPI_DOUBLE, comm);\n            }\n        }\n    }\n    else if (jacobianMode == JM_FULL)\n    {\n        if (parallelMode == PM_TRAIN_RK0)\n        {\n            for (size_t i = 0; i < numUpdaters; ++i)\n            {\n                if (myRank == 0) MPI_Gatherv(MPI_IN_PLACE             , 0                          , MPI_DOUBLE, &(pu.error.at(i).front()), &(pu.errorsPerTask.front()), &(pu.offsetPerTask.front()), MPI_DOUBLE, 0, comm);\n                else             MPI_Gatherv(&(pu.error.at(i).front()), pu.errorsPerTask.at(myRank), MPI_DOUBLE, NULL                     , NULL                       , NULL                       , MPI_DOUBLE, 0, comm);\n                if (myRank == 0) MPI_Gatherv(MPI_IN_PLACE                , 0                                 , MPI_DOUBLE, &(pu.jacobian.at(i).front()), &(pu.weightsPerTask.at(i).front()), &(pu.offsetJacobian.at(i).front()), MPI_DOUBLE, 0, comm);\n                else             MPI_Gatherv(&(pu.jacobian.at(i).front()), pu.weightsPerTask.at(i).at(myRank), MPI_DOUBLE, NULL                        , NULL                              , NULL                              , MPI_DOUBLE, 0, comm);\n            }\n        }\n        else if (parallelMode == PM_TRAIN_ALL)\n        {\n            for (size_t i = 0; i < numUpdaters; ++i)\n            {\n                MPI_Allgatherv(MPI_IN_PLACE, 0, MPI_DOUBLE, &(pu.error.at(i).front()), &(pu.errorsPerTask.front()), &(pu.offsetPerTask.front()), MPI_DOUBLE, comm);\n                MPI_Allgatherv(MPI_IN_PLACE, 0, MPI_DOUBLE, &(pu.jacobian.at(i).front()), &(pu.weightsPerTask.at(i).front()), &(pu.offsetJacobian.at(i).front()), MPI_DOUBLE, comm);\n            }\n        }\n    }\n    sw[k + \"_com\"].stop();\n\n    ///////////////////////////////////////////////////////////////////////\n    // PART 4: Perform weight update and apply new weights.\n    ///////////////////////////////////////////////////////////////////////\n\n    sw[k + \"_upd\"].start(newLoop);\n#ifdef _OPENMP\n    omp_set_num_threads(num_threads);\n#endif\n    // Loop over all updaters.\n    for (size_t i = 0; i < updaters.size(); ++i)\n    {\n        updaters.at(i)->setError(&(pu.error.at(i).front()),\n                                 pu.error.at(i).size());\n        updaters.at(i)->setJacobian(&(pu.jacobian.at(i).front()),\n                                    pu.error.at(i).size());\n        if (updaterType == UT_KF)\n        {\n            KalmanFilter* kf = dynamic_cast<KalmanFilter*>(updaters.at(i));\n            kf->setSizeObservation(pu.error.at(i).size());\n        }\n        updaters.at(i)->update();\n    }\n    countUpdates++;\n\n    // Redistribute weights to all MPI tasks.\n    if (parallelMode == PM_TRAIN_RK0)\n    {\n        for (size_t i = 0; i < numUpdaters; ++i)\n        {\n            MPI_Bcast(&(weights.at(i).front()), weights.at(i).size(), MPI_DOUBLE, 0, comm);\n        }\n    }\n\n    // Set new weights in neural networks.\n    setWeights();\n    sw[k + \"_upd\"].stop();\n\n    ///////////////////////////////////////////////////////////////////////\n    // PART 5: Communicate candidates and RMSE fractions and write log.\n    ///////////////////////////////////////////////////////////////////////\n\n    sw[k + \"_log\"].start(newLoop);\n    if (writeTrainingLog)\n    {\n        vector<int>    procUpdateCandidate;\n        vector<size_t> indexStructure;\n        vector<size_t> indexStructureGlobal;\n        vector<size_t> indexAtom;\n        vector<size_t> indexCoordinate;\n\n        vector<int> currentUpdateCandidatesPerTask;\n        vector<int> currentUpdateCandidatesOffset;\n        int myCurrentUpdateCandidates = currentUpdateCandidates.size();\n\n        if (myRank == 0)\n        {\n            currentUpdateCandidatesPerTask.resize(numProcs, 0);\n            currentUpdateCandidatesPerTask.at(0) = myCurrentUpdateCandidates;\n        }\n        if (myRank == 0) MPI_Gather(MPI_IN_PLACE                , 1, MPI_INT, &(currentUpdateCandidatesPerTask.front()),  1, MPI_INT, 0, comm);\n        else             MPI_Gather(&(myCurrentUpdateCandidates), 1, MPI_INT, NULL                                     ,  1, MPI_INT, 0, comm);\n\n        if (myRank == 0)\n        {\n            int totalUpdateCandidates = 0;\n            for (size_t i = 0; i < currentUpdateCandidatesPerTask.size(); ++i)\n            {\n                currentUpdateCandidatesOffset.push_back(totalUpdateCandidates);\n                totalUpdateCandidates += currentUpdateCandidatesPerTask.at(i);\n            }\n            procUpdateCandidate.resize(totalUpdateCandidates, 0);\n            indexStructure.resize(totalUpdateCandidates, 0);\n            indexStructureGlobal.resize(totalUpdateCandidates, 0);\n            indexAtom.resize(totalUpdateCandidates, 0);\n            indexCoordinate.resize(totalUpdateCandidates, 0);\n            // Increase size of this vectors (only rank 0).\n            currentRmseFraction.resize(totalUpdateCandidates, 0.0);\n            thresholdLoopCount.resize(totalUpdateCandidates, 0.0);\n        }\n        else\n        {\n            procUpdateCandidate.resize(myCurrentUpdateCandidates, 0);\n            indexStructure.resize(myCurrentUpdateCandidates, 0);\n            indexStructureGlobal.resize(myCurrentUpdateCandidates, 0);\n            indexAtom.resize(myCurrentUpdateCandidates, 0);\n            indexCoordinate.resize(myCurrentUpdateCandidates, 0);\n        }\n        for (int i = 0; i < myCurrentUpdateCandidates; ++i)\n        {\n            procUpdateCandidate.at(i) = myRank;\n            UpdateCandidate* c = NULL;\n            SubCandidate* sC = NULL;\n            if (useSubCandidates)\n            {\n                c = &(pu.updateCandidates.at(pu.posUpdateCandidates));\n                sC = &(c->subCandidates.at(currentUpdateCandidates.at(i)));\n            }\n            else\n            {\n                c = &(pu.updateCandidates.at(currentUpdateCandidates.at(i)));\n                if (c->subCandidates.size() > 0)\n                    sC = &(c->subCandidates.front());\n            }\n            indexStructure.at(i) = c->s;\n            indexStructureGlobal.at(i) = structures.at(c->s).index;\n            if (useSubCandidates)\n            {\n                indexAtom.at(i) = sC->a;\n                indexCoordinate.at(i) = sC->c;\n            }\n        }\n        if (myRank == 0)\n        {\n            MPI_Gatherv(MPI_IN_PLACE, 0, MPI_DOUBLE, &(currentRmseFraction.front()) , &(currentUpdateCandidatesPerTask.front()), &(currentUpdateCandidatesOffset.front()), MPI_DOUBLE, 0, comm);\n            MPI_Gatherv(MPI_IN_PLACE, 0, MPI_SIZE_T, &(thresholdLoopCount.front())  , &(currentUpdateCandidatesPerTask.front()), &(currentUpdateCandidatesOffset.front()), MPI_SIZE_T, 0, comm);\n            MPI_Gatherv(MPI_IN_PLACE, 0, MPI_INT   , &(procUpdateCandidate.front()) , &(currentUpdateCandidatesPerTask.front()), &(currentUpdateCandidatesOffset.front()), MPI_INT   , 0, comm);\n            MPI_Gatherv(MPI_IN_PLACE, 0, MPI_SIZE_T, &(indexStructure.front())      , &(currentUpdateCandidatesPerTask.front()), &(currentUpdateCandidatesOffset.front()), MPI_SIZE_T, 0, comm);\n            MPI_Gatherv(MPI_IN_PLACE, 0, MPI_SIZE_T, &(indexStructureGlobal.front()), &(currentUpdateCandidatesPerTask.front()), &(currentUpdateCandidatesOffset.front()), MPI_SIZE_T, 0, comm);\n            MPI_Gatherv(MPI_IN_PLACE, 0, MPI_SIZE_T, &(indexAtom.front())           , &(currentUpdateCandidatesPerTask.front()), &(currentUpdateCandidatesOffset.front()), MPI_SIZE_T, 0, comm);\n            MPI_Gatherv(MPI_IN_PLACE, 0, MPI_SIZE_T, &(indexCoordinate.front())     , &(currentUpdateCandidatesPerTask.front()), &(currentUpdateCandidatesOffset.front()), MPI_SIZE_T, 0, comm);\n        }\n        else\n        {\n            MPI_Gatherv(&(currentRmseFraction.front()) , myCurrentUpdateCandidates, MPI_DOUBLE, NULL, NULL, NULL, MPI_DOUBLE, 0, comm);\n            MPI_Gatherv(&(thresholdLoopCount.front())  , myCurrentUpdateCandidates, MPI_SIZE_T, NULL, NULL, NULL, MPI_SIZE_T, 0, comm);\n            MPI_Gatherv(&(procUpdateCandidate.front()) , myCurrentUpdateCandidates, MPI_INT   , NULL, NULL, NULL, MPI_INT   , 0, comm);\n            MPI_Gatherv(&(indexStructure.front())      , myCurrentUpdateCandidates, MPI_SIZE_T, NULL, NULL, NULL, MPI_SIZE_T, 0, comm);\n            MPI_Gatherv(&(indexStructureGlobal.front()), myCurrentUpdateCandidates, MPI_SIZE_T, NULL, NULL, NULL, MPI_SIZE_T, 0, comm);\n            MPI_Gatherv(&(indexAtom.front())           , myCurrentUpdateCandidates, MPI_SIZE_T, NULL, NULL, NULL, MPI_SIZE_T, 0, comm);\n            MPI_Gatherv(&(indexCoordinate.front())     , myCurrentUpdateCandidates, MPI_SIZE_T, NULL, NULL, NULL, MPI_SIZE_T, 0, comm);\n        }\n\n        if (myRank == 0)\n        {\n            for (size_t i = 0; i < procUpdateCandidate.size(); ++i)\n            {\n                if (k == \"energy\")\n                {\n                    addTrainingLogEntry(procUpdateCandidate.at(i),\n                                        thresholdLoopCount.at(i),\n                                        currentRmseFraction.at(i),\n                                        indexStructureGlobal.at(i),\n                                        indexStructure.at(i));\n                }\n                else if (k == \"force\")\n                {\n                    addTrainingLogEntry(procUpdateCandidate.at(i),\n                                        thresholdLoopCount.at(i),\n                                        currentRmseFraction.at(i),\n                                        indexStructureGlobal.at(i),\n                                        indexStructure.at(i),\n                                        indexAtom.at(i),\n                                        indexCoordinate.at(i));\n                }\n                else if (k == \"charge\")\n                {\n                    addTrainingLogEntry(procUpdateCandidate.at(i),\n                                        thresholdLoopCount.at(i),\n                                        currentRmseFraction.at(i),\n                                        indexStructureGlobal.at(i),\n                                        indexStructure.at(i),\n                                        indexAtom.at(i));\n                }\n            }\n        }\n    }\n    sw[k + \"_log\"].stop();\n\n    // Need to go to next update candidate after numGroupedSubCand is reached.\n    if (pu.countGroupedSubCand >= pu.numGroupedSubCand && useSubCandidates)\n    {\n        pu.countGroupedSubCand = 0;\n        pu.numGroupedSubCand = 0;\n        UpdateCandidate& c = pu.updateCandidates.at(pu.posUpdateCandidates);\n        structures.at(c.s).clearElectrostatics(true);\n        pu.posUpdateCandidates++;\n    }\n\n    sw[k].stop();\n\n    return;\n}\n\ndouble Training::getSingleWeight(size_t element, size_t index)\n{\n    getWeights();\n\n    return weights.at(element).at(index);\n}\n\nvoid Training::setSingleWeight(size_t element, size_t index, double value)\n{\n    weights.at(element).at(index) = value;\n    setWeights();\n\n    return;\n}\n\nvector<\nvector<double>> Training::calculateWeightDerivatives(Structure* structure)\n{\n    Structure& s = *structure;\n#ifdef N2P2_NO_SF_GROUPS\n    calculateSymmetryFunctions(s, false);\n#else\n    calculateSymmetryFunctionGroups(s, false);\n#endif\n\n    vector<vector<double> > dEdc;\n    vector<vector<double> > dedc;\n    dEdc.resize(numElements);\n    dedc.resize(numElements);\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        size_t n = elements.at(i).neuralNetworks.at(\"short\")\n                   .getNumConnections();\n        dEdc.at(i).resize(n, 0.0);\n        dedc.at(i).resize(n, 0.0);\n    }\n    for (vector<Atom>::iterator it = s.atoms.begin();\n         it != s.atoms.end(); ++it)\n    {\n        size_t i = it->element;\n        NeuralNetwork& nn = elements.at(i).neuralNetworks.at(\"short\");\n        nn.setInput(&((it->G).front()));\n        nn.propagate();\n        nn.getOutput(&(it->energy));\n        nn.calculateDEdc(&(dedc.at(i).front()));\n        for (size_t j = 0; j < dedc.at(i).size(); ++j)\n        {\n            dEdc.at(i).at(j) += dedc.at(i).at(j);\n        }\n    }\n\n    return dEdc;\n}\n\n// Doxygen requires namespace prefix for arguments...\nvector<\nvector<double>> Training::calculateWeightDerivatives(Structure*  structure,\n                                                      std::size_t atom,\n                                                      std::size_t component)\n{\n    Structure& s = *structure;\n#ifdef N2P2_NO_SF_GROUPS\n    calculateSymmetryFunctions(s, true);\n#else\n    calculateSymmetryFunctionGroups(s, true);\n#endif\n    // TODO: Is charge equilibration necessary here?\n\n    vector<vector<double> > dFdc;\n    vector<vector<double> > dfdc;\n    dFdc.resize(numElements);\n    dfdc.resize(numElements);\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        size_t n = elements.at(i).neuralNetworks.at(\"short\")\n                   .getNumConnections();\n        dFdc.at(i).resize(n, 0.0);\n        dfdc.at(i).resize(n, 0.0);\n    }\n    for (vector<Atom>::iterator it = s.atoms.begin();\n         it != s.atoms.end(); ++it)\n    {\n#ifndef N2P2_FULL_SFD_MEMORY\n        collectDGdxia((*it), atom, component);\n#else\n        it->collectDGdxia(atom, component, maxCutoffRadius);\n#endif\n        size_t i = it->element;\n        NeuralNetwork& nn = elements.at(i).neuralNetworks.at(\"short\");\n        nn.setInput(&((it->G).front()));\n        // TODO: what about charge neuron for 4G?\n        nn.propagate();\n        nn.getOutput(&(it->energy));\n#ifndef N2P2_FULL_SFD_MEMORY\n        nn.calculateDFdc(&(dfdc.at(i).front()), &(dGdxia.front()));\n#else\n        nn.calculateDFdc(&(dfdc.at(i).front()), &(it->dGdxia.front()));\n#endif\n        for (size_t j = 0; j < dfdc.at(i).size(); ++j)\n        {\n            dFdc.at(i).at(j) += dfdc.at(i).at(j);\n        }\n    }\n\n    return dFdc;\n}\n\nvoid Training::setTrainingLogFileName(string fileName)\n{\n    trainingLogFileName = fileName;\n\n    return;\n}\n\nsize_t Training::getNumConnections(string id) const\n{\n    size_t n = 0;\n    for (auto const& e : elements)\n    {\n        n += e.neuralNetworks.at(id).getNumConnections();\n    }\n\n    return n;\n}\n\nvector<size_t> Training::getNumConnectionsPerElement(string id) const\n{\n    vector<size_t> npe;\n    for (auto const& e : elements)\n    {\n        npe.push_back(e.neuralNetworks.at(id).getNumConnections());\n    }\n\n    return npe;\n}\n\nvector<size_t> Training::getConnectionOffsets(string id) const\n{\n    vector<size_t> offset;\n    size_t n = 0;\n    for (auto const& e : elements)\n    {\n        offset.push_back(n);\n        n += e.neuralNetworks.at(id).getNumConnections();\n    }\n\n    return offset;\n}\n\nvoid Training::dPdc(string                  property,\n                    Structure&              structure,\n                    vector<vector<double>>& dPdc)\n{\n    auto npe = getNumConnectionsPerElement();\n    auto off = getConnectionOffsets();\n    dPdc.clear();\n\n    if (property == \"energy\")\n    {\n        dPdc.resize(1);\n        dPdc.at(0).resize(getNumConnections(), 0.0);\n        for (auto const& a : structure.atoms)\n        {\n            size_t e = a.element;\n            NeuralNetwork& nn = elements.at(e).neuralNetworks.at(nnId);\n            nn.setInput(a.G.data());\n            nn.propagate();\n            vector<double> tmp(npe.at(e), 0.0);\n            nn.calculateDEdc(tmp.data());\n            for (size_t j = 0; j < tmp.size(); ++j)\n            {\n                dPdc.at(0).at(off.at(e) + j) += tmp.at(j);\n            }\n        }\n    }\n    else if (property == \"force\")\n    {\n        dPdc.resize(3 * structure.numAtoms);\n        size_t count = 0;\n        for (size_t ia = 0; ia < structure.numAtoms; ++ia)\n        {\n            for (size_t ixyz = 0; ixyz < 3; ++ixyz)\n            {\n                dPdc.at(count).resize(getNumConnections(), 0.0);\n                for (auto& a : structure.atoms)\n                {\n#ifndef N2P2_FULL_SFD_MEMORY\n                    collectDGdxia(a, ia, ixyz);\n#else\n                    a.collectDGdxia(ia, ixyz);\n#endif\n                    size_t e = a.element;\n                    NeuralNetwork& nn = elements.at(e).neuralNetworks.at(nnId);\n                    nn.setInput(a.G.data());\n                    nn.propagate();\n                    nn.calculateDEdG(a.dEdG.data());\n                    nn.getOutput(&(a.energy));\n                    vector<double> tmp(npe.at(e), 0.0);\n#ifndef N2P2_FULL_SFD_MEMORY\n                    nn.calculateDFdc(tmp.data(), dGdxia.data());\n#else\n                    nn.calculateDFdc(tmp.data(), a.dGdxia.data());\n#endif\n                    for (size_t j = 0; j < tmp.size(); ++j)\n                    {\n                        dPdc.at(count).at(off.at(e) + j) += tmp.at(j);\n                    }\n                }\n                count++;\n            }\n        }\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Weight derivatives not implemented for \"\n                            \"property \\\"\" + property + \"\\\".\\n\");\n    }\n\n    return;\n}\n\nvoid Training::dPdcN(string                  property,\n                     Structure&              structure,\n                     vector<vector<double>>& dPdc,\n                     double                  delta)\n{\n    auto npe = getNumConnectionsPerElement();\n    auto off = getConnectionOffsets();\n    dPdc.clear();\n\n    if (property == \"energy\")\n    {\n        dPdc.resize(1);\n        for (size_t ie = 0; ie < numElements; ++ie)\n        {\n            for (size_t ic = 0; ic < npe.at(ie); ++ic)\n            {\n                size_t const o = off.at(ie) + ic;\n                double const w = weights.at(0).at(o);\n\n                weights.at(0).at(o) += delta;\n                setWeights();\n                calculateAtomicNeuralNetworks(structure, false);\n                calculateEnergy(structure);\n                double energyHigh = structure.energy;\n\n                weights.at(0).at(o) -= 2.0 * delta;\n                setWeights();\n                calculateAtomicNeuralNetworks(structure, false);\n                calculateEnergy(structure);\n                double energyLow = structure.energy;\n\n                dPdc.at(0).push_back((energyHigh - energyLow) / (2.0 * delta));\n                weights.at(0).at(o) = w;\n            }\n        }\n    }\n    else if (property == \"force\")\n    {\n        size_t count = 0;\n        dPdc.resize(3 * structure.numAtoms);\n        for (size_t ia = 0; ia < structure.numAtoms; ++ia)\n        {\n            for (size_t ixyz = 0; ixyz < 3; ++ixyz)\n            {\n                for (size_t ie = 0; ie < numElements; ++ie)\n                {\n                    for (size_t ic = 0; ic < npe.at(ie); ++ic)\n                    {\n                        size_t const o = off.at(ie) + ic;\n                        double const w = weights.at(0).at(o);\n\n                        weights.at(0).at(o) += delta;\n                        setWeights();\n                        calculateAtomicNeuralNetworks(structure, true);\n                        calculateForces(structure);\n                        double forceHigh = structure.atoms.at(ia).f[ixyz];\n\n                        weights.at(0).at(o) -= 2.0 * delta;\n                        setWeights();\n                        calculateAtomicNeuralNetworks(structure, true);\n                        calculateForces(structure);\n                        double forceLow = structure.atoms.at(ia).f[ixyz];\n\n                        dPdc.at(count).push_back((forceHigh - forceLow)\n                                                 / (2.0 * delta));\n                        weights.at(0).at(o) = w;\n                    }\n                }\n                count++;\n            }\n        }\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Numeric weight derivatives not \"\n                            \"implemented for property \\\"\"\n                            + property + \"\\\".\\n\");\n    }\n\n    return;\n}\n\nbool Training::advance() const\n{\n    if (epoch < numEpochs) return true;\n    else return false;\n}\n\nvoid Training::getWeights()\n{\n    if (updateStrategy == US_COMBINED)\n    {\n        size_t pos = 0;\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            NeuralNetwork const& nn = elements.at(i).neuralNetworks.at(nnId);\n            nn.getConnections(&(weights.at(0).at(pos)));\n            pos += nn.getNumConnections();\n            // Leave slot for sqrt of hardness\n            if (nnpType == NNPType::HDNNP_4G && stage == 1)\n            {\n                // TODO: check that hardness is positive?\n                weights.at(0).at(pos) = sqrt(elements.at(i).getHardness());\n                pos ++;\n            }\n        }\n    }\n    else if (updateStrategy == US_ELEMENT)\n    {\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            NeuralNetwork const& nn = elements.at(i).neuralNetworks.at(nnId);\n            nn.getConnections(&(weights.at(i).front()));\n        }\n    }\n\n    return;\n}\n\nvoid Training::setWeights()\n{\n    if (updateStrategy == US_COMBINED)\n    {\n        size_t pos = 0;\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            NeuralNetwork& nn = elements.at(i).neuralNetworks.at(nnId);\n            nn.setConnections(&(weights.at(0).at(pos)));\n            pos += nn.getNumConnections();\n            // hardness\n            if (nnpType == NNPType::HDNNP_4G && stage == 1)\n            {\n                elements.at(i).setHardness(pow(weights.at(0).at(pos),2));\n                pos ++;\n            }\n        }\n    }\n    else if (updateStrategy == US_ELEMENT)\n    {\n        for (size_t i = 0; i < numElements; ++i)\n        {\n            NeuralNetwork& nn = elements.at(i).neuralNetworks.at(nnId);\n            nn.setConnections(&(weights.at(i).front()));\n        }\n    }\n\n    return;\n}\n\n// Doxygen requires namespace prefix for arguments...\nvoid Training::addTrainingLogEntry(int                 proc,\n                                   std::size_t         il,\n                                   double              f,\n                                   std::size_t         isg,\n                                   std::size_t         is)\n{\n    string s = strpr(\"  E %5zu %10zu %5d %3zu %10.2E %10zu %5zu\\n\",\n                     epoch, countUpdates, proc, il + 1, f, isg, is);\n    trainingLog << s;\n\n    return;\n}\n\n// Doxygen requires namespace prefix for arguments...\nvoid Training::addTrainingLogEntry(int                 proc,\n                                   std::size_t         il,\n                                   double              f,\n                                   std::size_t         isg,\n                                   std::size_t         is,\n                                   std::size_t         ia,\n                                   std::size_t         ic)\n{\n    string s = strpr(\"  F %5zu %10zu %5d %3zu %10.2E %10zu %5zu %5zu %2zu\\n\",\n                     epoch, countUpdates, proc, il + 1, f, isg, is, ia, ic);\n    trainingLog << s;\n\n    return;\n}\n\n// Doxygen requires namespace prefix for arguments...\nvoid Training::addTrainingLogEntry(int                 proc,\n                                   std::size_t         il,\n                                   double              f,\n                                   std::size_t         isg,\n                                   std::size_t         is,\n                                   std::size_t         ia)\n{\n    string s = strpr(\"  Q %5zu %10zu %5d %3zu %10.2E %10zu %5zu %5zu\\n\",\n                     epoch, countUpdates, proc, il + 1, f, isg, is, ia);\n    trainingLog << s;\n\n    return;\n}\n\n#ifndef N2P2_FULL_SFD_MEMORY\nvoid Training::collectDGdxia(Atom const& atom,\n                             size_t      indexAtom,\n                             size_t      indexComponent)\n{\n    size_t const nsf = atom.numSymmetryFunctions;\n\n    // Reset dGdxia array.\n    dGdxia.clear();\n    vector<double>(dGdxia).swap(dGdxia);\n    if (nnpType == NNPType::HDNNP_4G)\n        dGdxia.resize(nsf+1, 0.0);\n    else\n        dGdxia.resize(nsf, 0.0);\n\n    vector<vector<size_t> > const& tableFull\n        = elements.at(atom.element).getSymmetryFunctionTable();\n\n    // TODO: Check if maxCutoffRadius is needed here\n    for (size_t i = 0; i < atom.numNeighbors; i++)\n    {\n        if (atom.neighbors[i].index == indexAtom)\n        {\n            Atom::Neighbor const& n = atom.neighbors[i];\n            vector<size_t> const& table = tableFull.at(n.element);\n            for (size_t j = 0; j < n.dGdr.size(); ++j)\n            {\n                dGdxia[table.at(j)] += n.dGdr[j][indexComponent];\n            }\n        }\n    }\n    if (atom.index == indexAtom)\n    {\n        for (size_t i = 0; i < nsf; ++i)\n        {\n            dGdxia[i] += atom.dGdr[i][indexComponent];\n        }\n    }\n\n    return;\n}\n#endif\n\nvoid Training::randomizeNeuralNetworkWeights(string const& id)\n{\n    string keywordNW = \"nguyen_widrow_weights\" + nns.at(id).keywordSuffix2;\n\n    double minWeights = atof(settings[\"weights_min\"].c_str());\n    double maxWeights = atof(settings[\"weights_max\"].c_str());\n    log << strpr(\"Initial weights selected randomly in interval \"\n                 \"[%f, %f).\\n\", minWeights, maxWeights);\n    vector<double> w;\n    for (size_t i = 0; i < numElements; ++i)\n    {\n        NeuralNetwork& nn = elements.at(i).neuralNetworks.at(id);\n        w.resize(nn.getNumConnections(), 0);\n        for (size_t j = 0; j < w.size(); ++j)\n        {\n            w.at(j) = minWeights + gsl_rng_uniform(rngGlobal)\n                    * (maxWeights - minWeights);\n        }\n        nn.setConnections(&(w.front()));\n    }\n    if (settings.keywordExists(keywordNW))\n    {\n        log << \"Weights modified according to Nguyen Widrow scheme.\\n\";\n        for (vector<Element>::iterator it = elements.begin();\n             it != elements.end(); ++it)\n        {\n            NeuralNetwork& nn = it->neuralNetworks.at(id);\n            nn.modifyConnections(NeuralNetwork::MS_NGUYENWIDROW);\n        }\n    }\n    else if (settings.keywordExists(\"precondition_weights\"))\n    {\n        throw runtime_error(\"ERROR: Preconditioning of weights not yet\"\n                            \" implemented.\\n\");\n    }\n    else\n    {\n        log << \"Weights modified accoring to Glorot Bengio scheme.\\n\";\n        //log << \"Weights connected to output layer node set to zero.\\n\";\n        log << \"Biases set to zero.\\n\";\n        for (vector<Element>::iterator it = elements.begin();\n             it != elements.end(); ++it)\n        {\n            NeuralNetwork& nn = it->neuralNetworks.at(id);\n            nn.modifyConnections(NeuralNetwork::MS_GLOROTBENGIO);\n            //nn->modifyConnections(NeuralNetwork::MS_ZEROOUTPUTWEIGHTS);\n            nn.modifyConnections(NeuralNetwork::MS_ZEROBIAS);\n        }\n    }\n\n    return;\n}\n\nvoid Training::setupSelectionMode(string const& property)\n{\n    bool all = (property == \"all\");\n    bool isProperty = (find(pk.begin(), pk.end(), property) != pk.end());\n    if (!(all || isProperty))\n    {\n        throw runtime_error(\"ERROR: Unknown property for selection mode\"\n                            \" setup.\\n\");\n    }\n\n    if (all)\n    {\n        if (!(settings.keywordExists(\"selection_mode\") ||\n              settings.keywordExists(\"rmse_threshold\") ||\n              settings.keywordExists(\"rmse_threshold_trials\"))) return;\n        log << \"Global selection mode settings:\\n\";\n    }\n    else\n    {\n        if (!(settings.keywordExists(\"selection_mode_\" + property) ||\n              settings.keywordExists(\"rmse_threshold_\" + property) ||\n              settings.keywordExists(\"rmse_threshold_trials_\"\n                                     + property))) return;\n        log << \"Selection mode settings specific to property \\\"\"\n            << property << \"\\\":\\n\";\n    }\n    string keyword;\n    if (all) keyword = \"selection_mode\";\n    else keyword = \"selection_mode_\" + property;\n\n    if (settings.keywordExists(keyword))\n    {\n        map<size_t, SelectionMode> schedule;\n        vector<string> args = split(settings[keyword]);\n        if (args.size() % 2 != 1)\n        {\n            throw runtime_error(\"ERROR: Incorrect selection mode format.\\n\");\n        }\n        schedule[0] = (SelectionMode)atoi(args.at(0).c_str());\n        for (size_t i = 1; i < args.size(); i = i + 2)\n        {\n            schedule[(size_t)atoi(args.at(i).c_str())] =\n                (SelectionMode)atoi(args.at(i + 1).c_str());\n        }\n        for (map<size_t, SelectionMode>::const_iterator it = schedule.begin();\n             it != schedule.end(); ++it)\n        {\n            log << strpr(\"- Selection mode starting with epoch %zu:\\n\",\n                         it->first);\n            if (it->second == SM_RANDOM)\n            {\n                log << strpr(\"  Random selection of update candidates: \"\n                             \"SelectionMode::SM_RANDOM (%d)\\n\", it->second);\n            }\n            else if (it->second == SM_SORT)\n            {\n                log << strpr(\"  Update candidates selected according to error: \"\n                             \"SelectionMode::SM_SORT (%d)\\n\", it->second);\n            }\n            else if (it->second == SM_THRESHOLD)\n            {\n                log << strpr(\"  Update candidates chosen randomly above RMSE \"\n                             \"threshold: SelectionMode::SM_THRESHOLD (%d)\\n\",\n                             it->second);\n            }\n            else\n            {\n                throw runtime_error(\"ERROR: Unknown selection mode.\\n\");\n            }\n        }\n        if (all)\n        {\n            for (auto& i : p)\n            {\n                i.second.selectionModeSchedule = schedule;\n                i.second.selectionMode = schedule[0];\n            }\n        }\n        else\n        {\n            p[property].selectionModeSchedule = schedule;\n            p[property].selectionMode = schedule[0];\n        }\n    }\n\n    if (all) keyword = \"rmse_threshold\";\n    else keyword = \"rmse_threshold_\" + property;\n    if (settings.keywordExists(keyword))\n    {\n        double t = atof(settings[keyword].c_str());\n        log << strpr(\"- RMSE selection threshold: %.2f * RMSE\\n\", t);\n        if (all) for (auto& i : p) i.second.rmseThreshold = t;\n        else p[property].rmseThreshold = t;\n    }\n\n    if (all) keyword = \"rmse_threshold_trials\";\n    else keyword = \"rmse_threshold_trials_\" + property;\n    if (settings.keywordExists(keyword))\n    {\n        size_t t = atoi(settings[keyword].c_str());\n        log << strpr(\"- RMSE selection trials   : %zu\\n\", t);\n        if (all) for (auto& i : p) i.second.rmseThresholdTrials = t;\n        else p[property].rmseThresholdTrials = t;\n    }\n\n    return;\n}\n\nvoid Training::setupFileOutput(string const& type)\n{\n    string keyword = \"write_\";\n    bool isProperty = (find(pk.begin(), pk.end(), type) != pk.end());\n    if      (type == \"energy\"       ) keyword += \"trainpoints\";\n    else if (type == \"force\"        ) keyword += \"trainforces\";\n    else if (type == \"charge\"       ) keyword += \"traincharges\";\n    else if (type == \"weights_epoch\") keyword += type;\n    else if (type == \"neuronstats\"  ) keyword += type;\n    else\n    {\n        throw runtime_error(\"ERROR: Invalid type for file output setup.\\n\");\n    }\n\n    // Check how often energy comparison files should be written.\n    if (settings.keywordExists(keyword))\n    {\n        size_t* writeEvery = nullptr;\n        size_t* writeAlways = nullptr;\n        string message;\n        if (isProperty)\n        {\n            writeEvery = &(p[type].writeCompEvery);\n            writeAlways = &(p[type].writeCompAlways);\n            message = \"Property \\\"\" + type + \"\\\" comparison\";\n            message.at(0) = toupper(message.at(0));\n        }\n        else if (type == \"weights_epoch\")\n        {\n            writeEvery = &writeWeightsEvery;\n            writeAlways = &writeWeightsAlways;\n            message = \"Weight\";\n        }\n        else if (type == \"neuronstats\")\n        {\n            writeEvery = &writeNeuronStatisticsEvery;\n            writeAlways = &writeNeuronStatisticsAlways;\n            message = \"Neuron statistics\";\n        }\n\n        *writeEvery = 1;\n        vector<string> v = split(reduce(settings[keyword]));\n        if (v.size() == 1) *writeEvery = (size_t)atoi(v.at(0).c_str());\n        else if (v.size() == 2)\n        {\n            *writeEvery = (size_t)atoi(v.at(0).c_str());\n            *writeAlways = (size_t)atoi(v.at(1).c_str());\n        }\n        log << strpr((message\n                      + \" files will be written every %zu epochs.\\n\").c_str(),\n                     *writeEvery);\n        if (*writeAlways > 0)\n        {\n            log << strpr((message\n                          + \" files will always be written up to epoch \"\n                            \"%zu.\\n\").c_str(), *writeAlways);\n        }\n    }\n\n    return;\n}\n\nvoid Training::setupUpdatePlan(string const& property)\n{\n    bool isProperty = (find(pk.begin(), pk.end(), property) != pk.end());\n    if (!isProperty)\n    {\n        throw runtime_error(\"ERROR: Unknown property for update plan\"\n                            \" setup.\\n\");\n    }\n\n    // Actual property modified here.\n    Property& pa = p[property];\n    string keyword = property + \"_fraction\";\n\n    // Override force fraction if keyword \"energy_force_ratio\" is provided.\n    if (property == \"force\" &&\n        p.exists(\"energy\") &&\n        settings.keywordExists(\"force_energy_ratio\"))\n    {\n        double const ratio = atof(settings[\"force_energy_ratio\"].c_str());\n        if (settings.keywordExists(keyword))\n        {\n            log << \"WARNING: Given force fraction is ignored because \"\n                   \"force/energy ratio is provided.\\n\";\n        }\n        log << strpr(\"Desired force/energy update ratio              : %.6f\\n\",\n                     ratio);\n        log << \"----------------------------------------------\\n\";\n        pa.epochFraction = (p[\"energy\"].numTrainPatterns * ratio)\n                         / p[\"force\"].numTrainPatterns;\n    }\n    // Default action = read \"<property>_fraction\" keyword.\n    else\n    {\n    pa.epochFraction = atof(settings[keyword].c_str());\n    }\n\n    keyword = \"task_batch_size_\" + property;\n    pa.taskBatchSize = (size_t)atoi(settings[keyword].c_str());\n    if (pa.taskBatchSize == 0)\n    {\n        pa.patternsPerUpdate =\n            static_cast<size_t>(pa.updateCandidates.size() * pa.epochFraction);\n        pa.numUpdates = 1;\n    }\n    else\n    {\n        pa.patternsPerUpdate = pa.taskBatchSize;\n        pa.numUpdates =\n            static_cast<size_t>((pa.numTrainPatterns * pa.epochFraction)\n                                / pa.taskBatchSize / numProcs);\n    }\n    pa.patternsPerUpdateGlobal = pa.patternsPerUpdate;\n    MPI_Allreduce(MPI_IN_PLACE, &(pa.patternsPerUpdateGlobal), 1, MPI_SIZE_T, MPI_SUM, comm);\n    pa.errorsPerTask.resize(numProcs, 0);\n    if (jacobianMode == JM_FULL)\n    {\n        pa.errorsPerTask.at(myRank) = static_cast<int>(pa.patternsPerUpdate);\n    }\n    else\n    {\n        pa.errorsPerTask.at(myRank) = 1;\n    }\n    MPI_Allgather(MPI_IN_PLACE, 1, MPI_INT, &(pa.errorsPerTask.front()), 1, MPI_INT, comm);\n    if (jacobianMode == JM_FULL)\n    {\n        pa.weightsPerTask.resize(numUpdaters);\n        for (size_t i = 0; i < numUpdaters; ++i)\n        {\n            pa.weightsPerTask.at(i).resize(numProcs, 0);\n            for (int j = 0; j < numProcs; ++j)\n            {\n                pa.weightsPerTask.at(i).at(j) = pa.errorsPerTask.at(j)\n                                              * numWeightsPerUpdater.at(i);\n            }\n        }\n    }\n    pa.numErrorsGlobal = 0;\n    for (size_t i = 0; i < pa.errorsPerTask.size(); ++i)\n    {\n        pa.offsetPerTask.push_back(pa.numErrorsGlobal);\n        pa.numErrorsGlobal += pa.errorsPerTask.at(i);\n    }\n    pa.offsetJacobian.resize(numUpdaters);\n    for (size_t i = 0; i < numUpdaters; ++i)\n    {\n        for (size_t j = 0; j < pa.offsetPerTask.size(); ++j)\n        {\n            pa.offsetJacobian.at(i).push_back(pa.offsetPerTask.at(j) *\n                                              numWeightsPerUpdater.at(i));\n        }\n    }\n    log << \"Update plan for property \\\"\" + property + \"\\\":\\n\";\n    log << strpr(\"- Per-task batch size                          : %zu\\n\",\n                 pa.taskBatchSize);\n    log << strpr(\"- Fraction of patterns used per epoch          : %.6f\\n\",\n                 pa.epochFraction);\n    if (pa.numUpdates == 0)\n    {\n        log << \"WARNING: No updates are planned for this property.\";\n    }\n    log << strpr(\"- Updates per epoch                            : %zu\\n\",\n                 pa.numUpdates);\n    log << strpr(\"- Patterns used per update (rank %3d / global) : \"\n                 \"%10zu / %zu\\n\",\n                 myRank, pa.patternsPerUpdate, pa.patternsPerUpdateGlobal);\n    log << \"----------------------------------------------\\n\";\n\n    return;\n}\n\nvoid Training::allocateArrays(string const& property)\n{\n    bool isProperty = (find(pk.begin(), pk.end(), property) != pk.end());\n    if (!isProperty)\n    {\n        throw runtime_error(\"ERROR: Unknown property for array allocation.\\n\");\n    }\n\n    log << \"Allocating memory for \" + property +\n           \" error vector and Jacobian.\\n\";\n    Property& pa = p[property];\n    pa.error.resize(numUpdaters);\n    pa.jacobian.resize(numUpdaters);\n    for (size_t i = 0; i < numUpdaters; ++i)\n    {\n        size_t size = 1;\n        if (( parallelMode == PM_TRAIN_ALL ||\n              (parallelMode == PM_TRAIN_RK0 && myRank == 0)) &&\n            jacobianMode != JM_SUM)\n        {\n            size *= pa.numErrorsGlobal;\n        }\n        else if ((parallelMode == PM_TRAIN_RK0 && myRank != 0) &&\n                 jacobianMode != JM_SUM)\n        {\n            size *= pa.errorsPerTask.at(myRank);\n        }\n        pa.error.at(i).resize(size, 0.0);\n        pa.jacobian.at(i).resize(size * numWeightsPerUpdater.at(i), 0.0);\n        log << strpr(\"Updater %3zu:\\n\", i);\n        log << strpr(\" - Error    size: %zu\\n\", pa.error.at(i).size());\n        log << strpr(\" - Jacobian size: %zu\\n\", pa.jacobian.at(i).size());\n    }\n    log << \"----------------------------------------------\\n\";\n\n    return;\n}\n\nvoid Training::writeTimingData(bool append, string const fileName)\n{\n    ofstream file;\n    string fileNameActual = fileName;\n    if (nnpType == NNPType::HDNNP_4G ||\n        nnpType == NNPType::HDNNP_Q)\n    {\n        fileNameActual += strpr(\".stage-%zu\", stage);\n    }\n\n    vector<string> sub = {\"_err\", \"_com\", \"_upd\", \"_log\"};\n    if (append) file.open(fileNameActual.c_str(), ofstream::app);\n    else\n    {\n        file.open(fileNameActual.c_str());\n\n        // File header.\n        vector<string> title;\n        vector<string> colName;\n        vector<string> colInfo;\n        vector<size_t> colSize;\n        title.push_back(\"Timing data for training loop.\");\n        colSize.push_back(10);\n        colName.push_back(\"epoch\");\n        colInfo.push_back(\"Current epoch.\");\n        colSize.push_back(11);\n        colName.push_back(\"train\");\n        colInfo.push_back(\"Time for training.\");\n        colSize.push_back(7);\n        colName.push_back(\"ptrain\");\n        colInfo.push_back(\"Time for training (percentage of loop).\");\n        colSize.push_back(11);\n        colName.push_back(\"error\");\n        colInfo.push_back(\"Time for error calculation.\");\n        colSize.push_back(7);\n        colName.push_back(\"perror\");\n        colInfo.push_back(\"Time for error calculation (percentage of loop).\");\n        colSize.push_back(11);\n        colName.push_back(\"epoch\");\n        colInfo.push_back(\"Time for this epoch.\");\n        colSize.push_back(11);\n        colName.push_back(\"total\");\n        colInfo.push_back(\"Total time for all epochs.\");\n        for (auto k : pk)\n        {\n            colSize.push_back(11);\n            colName.push_back(p[k].tiny + \"train\");\n            colInfo.push_back(\"\");\n            colSize.push_back(7);\n            colName.push_back(p[k].tiny + \"ptrain\");\n            colInfo.push_back(\"\");\n        }\n        for (auto s : sub)\n        {\n            for (auto k : pk)\n            {\n                colSize.push_back(11);\n                colName.push_back(p[k].tiny + s);\n                colInfo.push_back(\"\");\n                colSize.push_back(7);\n                colName.push_back(p[k].tiny + \"p\" + s);\n                colInfo.push_back(\"\");\n            }\n        }\n        appendLinesToFile(file,\n                          createFileHeader(title, colSize, colName, colInfo));\n    }\n\n    double timeLoop = sw[\"loop\"].getLoop();\n    file << strpr(\"%10zu\", epoch);\n    file << strpr(\" %11.3E\", sw[\"train\"].getLoop());\n    file << strpr(\" %7.3f\", sw[\"train\"].getLoop() / timeLoop);\n    file << strpr(\" %11.3E\", sw[\"error\"].getLoop());\n    file << strpr(\" %7.3f\", sw[\"error\"].getLoop() / timeLoop);\n    file << strpr(\" %11.3E\", timeLoop);\n    file << strpr(\" %11.3E\", sw[\"loop\"].getTotal());\n\n    for (auto k : pk)\n    {\n        file << strpr(\" %11.3E\", sw[k].getLoop());\n        file << strpr(\" %7.3f\", sw[k].getLoop() / sw[\"train\"].getLoop());\n    }\n    for (auto s : sub)\n    {\n        for (auto k : pk)\n        {\n            file << strpr(\" %11.3E\", sw[k + s].getLoop());\n            file << strpr(\" %7.3f\", sw[k + s].getLoop() / sw[k].getLoop());\n        }\n    }\n    file << \"\\n\";\n\n    file.flush();\n    file.close();\n\n    return;\n}\n\nTraining::Property::Property(string const& property) :\n    property               (property ),\n    displayMetric          (\"\"       ),\n    tiny                   (\"\"       ),\n    plural                 (\"\"       ),\n    selectionMode          (SM_RANDOM),\n    numTrainPatterns       (0        ),\n    numTestPatterns        (0        ),\n    taskBatchSize          (0        ),\n    writeCompEvery         (0        ),\n    writeCompAlways        (0        ),\n    posUpdateCandidates    (0        ),\n    numGroupedSubCand      (0        ),\n    countGroupedSubCand    (0        ),\n    rmseThresholdTrials    (0        ),\n    countUpdates           (0        ),\n    numUpdates             (0        ),\n    patternsPerUpdate      (0        ),\n    patternsPerUpdateGlobal(0        ),\n    numErrorsGlobal        (0        ),\n    epochFraction          (0.0      ),\n    rmseThreshold          (0.0      )\n{\n    if (property == \"energy\")\n    {\n        tiny = \"E\";\n        plural = \"energies\";\n        errorMetrics = {\"RMSEpa\", \"RMSE\", \"MAEpa\", \"MAE\"};\n    }\n    else if (property == \"force\")\n    {\n        tiny = \"F\";\n        plural = \"forces\";\n        errorMetrics = {\"RMSE\", \"MAE\"};\n    }\n    else if (property == \"charge\")\n    {\n        tiny = \"Q\";\n        plural = \"charges\";\n        errorMetrics = {\"RMSE\", \"MAE\"};\n    }\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown training property.\\n\");\n    }\n\n    // Set up error metrics\n    for (auto m : errorMetrics)\n    {\n        errorTrain[m] = 0.0;\n        errorTest[m] = 0.0;\n    }\n    displayMetric = errorMetrics.at(0);\n}\n"
  },
  {
    "path": "src/libnnptrain/Training.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef TRAINING_H\n#define TRAINING_H\n\n#include \"Atom.h\"\n#include \"Dataset.h\"\n#include \"Stopwatch.h\"\n#include \"Updater.h\"\n#include <cstddef> // std::size_t\n#include <fstream> // std::ofstream\n#include <map>     // std::map\n#include <random>  // std::mt19937_64\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/// Training methods.\nclass Training : public Dataset\n{\npublic:\n    /// Type of update routine.\n    enum UpdaterType\n    {\n        /// Simple gradient descent methods.\n        UT_GD,\n        /// Kalman filter-based methods.\n        UT_KF,\n        /// Levenberg-Marquardt algorithm.\n        UT_LM\n    };\n\n    /** Training parallelization mode.\n     *\n     * This mode determines if and how individual MPI tasks contribute to\n     * parallel training. Note that in all cases the data set gets distributed\n     * among the MPI processes and RMSE computation is always parallelized.\n     */\n    enum ParallelMode\n    {\n        /** No training parallelization, only data set distribution.\n         *\n         * Data set is distributed via MPI, but for each weight update only\n         * a single task is active, selects energy/force update candidates,\n         * computes errors and gradients, and updates weights.\n         */\n        //PM_DATASET,\n        /** Parallel gradient computation, update on rank 0.\n         *\n         * Data set is distributed via MPI, each tasks selects energy/force\n         * update candidates, and computes errors and gradients, which are\n         * collected on rank 0. Weight update is carried out on rank 0 and new\n         * weights are redistributed to all tasks.\n         */\n        PM_TRAIN_RK0,\n        /** Parallel gradient computation, update on each task.\n         *\n         * Data set is distributed via MPI, each tasks selects energy/force\n         * update candidates, and computes errors and gradients, which are\n         * collected on all MPI tasks. Identical weight updates are carried out\n         * on each task. This mode is ideal if the update routine itself is\n         * parallelized.\n         */\n        PM_TRAIN_ALL\n    };\n\n    /// Jacobian matrix preparation mode.\n    enum JacobianMode\n    {\n        /// No Jacobian, sum up contributions from update candidates.\n        JM_SUM,\n        /// Prepare one Jacobian entry for each task, sum up within tasks.\n        JM_TASK,\n        /// Prepare full Jacobian matrix.\n        JM_FULL\n    };\n\n    /// Update strategies available for Training.\n    enum UpdateStrategy\n    {\n        /// One combined updater for all elements.\n        US_COMBINED,\n        /// Separate updaters for individual elements.\n        US_ELEMENT\n    };\n\n    /// How update candidates are selected during Training.\n    enum SelectionMode\n    {\n        /// Select candidates randomly.\n        SM_RANDOM,\n        /// Sort candidates according to their RMSE and pick worst first.\n        SM_SORT,\n        /// Select candidates randomly with RMSE above threshold.\n        SM_THRESHOLD\n    };\n\n    /// Constructor.\n    Training();\n    /// Destructor, updater vector needs to be cleaned.\n    ~Training();\n    /** Randomly select training and test set structures.\n     *\n     * Also fills training candidates lists.\n     */\n    void                  selectSets();\n    /** Write training and test set to separate files (train.data and\n     * test.data, same format as input.data).\n     */\n    void                  writeSetsToFiles();\n    /** Initialize weights for all elements.\n     */\n    void                  initializeWeights();\n    /** Initialize weights vector according to update strategy.\n     *\n     * @param[in] updateStrategy Determines the shape of the weights array.\n     */\n    void                  initializeWeightsMemory(UpdateStrategy updateStrategy\n                                                      = US_COMBINED);\n    /** Set training stage (if multiple stages are needed for NNP type).\n     *\n     * @param[in] stage Training stage to set.\n     */\n    void                  setStage(std::size_t stage);\n    /** Apply normalization based on initial weights prediction.\n     */\n    void                  dataSetNormalization();\n    /** General training settings and setup of weight update routine.\n     */\n    void                  setupTraining();\n    /** Set up numeric weight derivatives check.\n     */\n    std::vector<\n    std::string>          setupNumericDerivCheck();\n    /** Calculate neighbor lists for all structures.\n     */\n    void                  calculateNeighborLists();\n    /** Calculate error metrics for all structures.\n     *\n     * @param[in] fileNames Map of properties to file names for training/test\n     *                      comparison files.\n     *\n     * If fileNames map is empty, no files will be written.\n     */\n    void                  calculateError(\n                                   std::map<std::string,\n                                   std::pair<\n                                   std::string, std::string>> const fileNames);\n    /** Calculate error metrics per epoch for all structures with file names\n     * used in training loop.\n     *\n     * Also write training curve to file.\n     */\n    void                  calculateErrorEpoch();\n    /** Calculate vector of charge errors in one structure.\n     *\n     * @param[in] s Structure of interest.\n     * @param[in] cVec Vector to store result of charge errors.\n     * @param[in] cNorm Euclidean norm of the error vector.\n     */\n    void                  calculateChargeErrorVec( Structure const &s,\n                                                   Eigen::VectorXd &cVec,\n                                                   double          &cNorm);\n    /** Print training loop header on screen.\n     */\n    void                  printHeader();\n    /** Print preferred error metric and timing information on screen.\n     */\n    void                  printEpoch();\n    /** Write weights to files (one file for each element).\n     *\n     * @param[in] nnName Identifier for neural network.\n     * @param[in] fileNameFormat String with file name format.\n     */\n    void                  writeWeights(\n                                      std::string const& nnName,\n                                      std::string const& fileNameFormat) const;\n    /** Write weights to files during training loop.\n     */\n    void                  writeWeightsEpoch() const;\n    /** Write hardness to files (one file for each element).\n     *\n     * @param[in] fileNameFormat String with file name format.\n     */\n    void                  writeHardness(\n                                      std::string const& fileNameFormat) const;\n    /** Write hardness to files during training loop.\n     */\n    void                  writeHardnessEpoch() const;\n\n    /** Write current RMSEs and epoch information to file.\n     *\n     * @param[in] append If true, append to file, otherwise create new file.\n     * @param[in] fileName File name for learning curve file.\n     */\n    void                  writeLearningCurve(bool              append,\n                                             std::string const fileName\n                                                 = \"learning-curve.out\") const;\n    /** Write neuron statistics collected since last invocation.\n     *\n     * @param[in] nnName Identifier of neural network to process.\n     * @param[in] fileName File name for statistics file.\n     */\n    void                  writeNeuronStatistics(\n                                            std::string const& nnName,\n                                            std::string const& fileName) const;\n    /** Write neuron statistics during training loop.\n     */\n    void                  writeNeuronStatisticsEpoch() const;\n    /** Reset neuron statistics for all elements.\n     */\n    void                  resetNeuronStatistics();\n    /** Write updater information to file.\n     *\n     * @param[in] append If true, append to file, otherwise create new file.\n     * @param[in] fileNameFormat String with file name format.\n     */\n    void                  writeUpdaterStatus(bool              append,\n                                             std::string const fileNameFormat\n                                                 = \"updater.%03zu.out\") const;\n    /** Sort update candidates with descending RMSE.\n     *\n     * @param[in] property Training property.\n     */\n    void                  sortUpdateCandidates(std::string const& property);\n    /** Shuffle update candidates.\n     *\n     * @param[in] property Training property.\n     */\n    void                  shuffleUpdateCandidates(std::string const& property);\n    /** Check if selection mode should be changed.\n     */\n    void                  checkSelectionMode();\n    /** Execute main training loop.\n     */\n    void                  loop();\n    /** Select energies/forces schedule for one epoch.\n     */\n    void                  setEpochSchedule();\n    /** Perform one update.\n     *\n     * @param[in] property Training property to use for update.\n     */\n    void                  update(std::string const& property);\n    /** Get a single weight value.\n     *\n     * @param[in] element Element index of weight.\n     * @param[in] index Weight index.\n     *\n     * @return Weight value.\n     *\n     * Note: This function is implemented for testing purposes and works\n     * correctly only with update strategy #US_ELEMENT.\n     */\n    double                getSingleWeight(std::size_t element,\n                                          std::size_t index);\n    /** Set a single weight value.\n     *\n     * @param[in] element Element index of weight.\n     * @param[in] index Weight index.\n     * @param[in] value Weight value.\n     *\n     * Note: This function is implemented for testing purposes and works\n     * correctly only with update strategy #US_ELEMENT.\n     */\n    void                  setSingleWeight(std::size_t element,\n                                          std::size_t index,\n                                          double      value);\n    /** Calculate derivatives of energy with respect to weights.\n     *\n     * @param[in,out] structure Structure to process.\n     *\n     * @return Vector with derivatives of energy with respect to weights (per\n     *         element).\n     *\n     * @note This function is implemented for testing purposes.\n     */\n    std::vector<\n    std::vector<double> > calculateWeightDerivatives(Structure* structure);\n    /** Calculate derivatives of force with respect to weights.\n     *\n     * @param[in,out] structure Structure to process.\n     * @param[in] atom Atom index.\n     * @param[in] component x, y or z-component of force (0, 1, 2).\n     *\n     * @return Vector with derivatives of force with respect to weights (per\n     *         element).\n     *\n     * @note This function is implemented for testing purposes.\n     */\n    std::vector<\n    std::vector<double> > calculateWeightDerivatives(Structure*  structure,\n                                                     std::size_t atom,\n                                                     std::size_t component);\n    /** Set training log file name\n     *\n     * @param[in] fileName File name for training log.\n     */\n    void                  setTrainingLogFileName(std::string fileName);\n    /** Get total number of NN connections.\n     *\n     * @param[in] id NN ID to use (e.g. \"short\").\n     *\n     * @return Sum of all NN weights + biases for all elements\n     */\n    std::size_t           getNumConnections(std::string id = \"short\") const;\n    /** Get number of NN connections for each element.\n     *\n     * @param[in] id NN ID to use (e.g. \"short\").\n     *\n     * @return Vector containing number of connections for each element.\n     */\n    std::vector<\n    std::size_t>          getNumConnectionsPerElement(\n                                               std::string id = \"short\") const;\n    /** Get offsets of NN connections for each element.\n     *\n     * @param[in] id NN ID to use (e.g. \"short\").\n     *\n     * @return Vector containing offsets for each element.\n     */\n    std::vector<\n    std::size_t>          getConnectionOffsets(std::string id = \"short\") const;\n    /** Compute derivatives of property with respect to weights.\n     *\n     * @param[in] property Training property for which derivatives should be\n     *                     computed.\n     * @param[in] structure The structure under investigation.\n     * @param[inout] dEdc Weight derivative array (first index = property,\n     *                    second index = weight).\n     */\n    void                  dPdc(std::string                       property,\n                               Structure&                        structure,\n                               std::vector<std::vector<double>>& dEdc);\n    /** Compute numeric derivatives of property with respect to weights.\n     *\n     * @param[in] property Training property for which derivatives should be\n     *                     computed.\n     * @param[in] structure The structure under investigation.\n     * @param[inout] dEdc Weight derivative array (first index = property,\n     *                    second index = weight).\n     * @param[in] delta Delta for central difference.\n     */\n    void                  dPdcN(\n                             std::string                       property,\n                             Structure&                        structure,\n                             std::vector<std::vector<double>>& dEdc,\n                             double                            delta = 1.0E-4);\n\nprivate:\n    /// Contains update candidate which is grouped with others to specific\n    /// parent update candidate (e.g. forces belonging to same structure).\n    struct SubCandidate\n    {\n        /// Atom index (only used for force candidates).\n        std::size_t a;\n        /// Component index (x,y,z -> 0,1,2, only used for force candidates).\n        std::size_t c;\n        /// Absolute value of error with respect to reference value.\n        double error;\n\n        /// Overload < operator to sort in \\em descending order.\n        bool operator<(SubCandidate const& rhs) const {\n            return this->error > rhs.error;\n        }\n    };\n    /// Contains location of one update candidate (energy or force).\n    struct UpdateCandidate\n    {\n        /// Structure index.\n        std::size_t s;\n        /// Absolute value of error with respect to reference value (in case of\n        /// subcandidates, average is taken)\n        double      error;\n        /// Current position in sub-candidate list (SM_SORT/_THRESHOLD).\n        std::size_t                  posSubCandidates;\n\n        /// Vector containing grouped candidates. If no grouping intended,\n        /// vector will contain only single entry.\n        std::vector<SubCandidate> subCandidates;\n\n        /// Overload < operator to sort in \\em descending order.\n        bool operator<(UpdateCandidate const& rhs) const {\n            return this->error > rhs.error;\n        }\n    };\n\n    /// Specific training quantity (e.g. energies, forces, charges).\n    struct Property\n    {\n        /// Constructor.\n        Property(std::string const& property);\n\n        /// Copy of identifier within Property map.\n        std::string                  property;\n        /// Error metric for display.\n        std::string                  displayMetric;\n        /// Tiny abbreviation string for property.\n        std::string                  tiny;\n        /// Plural string of property;\n        std::string                  plural;\n        /// Selection mode for update candidates.\n        SelectionMode                selectionMode;\n        /// Number of training patterns in set.\n        std::size_t                  numTrainPatterns;\n        /// Number of training patterns in set.\n        std::size_t                  numTestPatterns;\n        /// Batch size for each MPI task.\n        std::size_t                  taskBatchSize;\n        /// Write comparison every this many epochs.\n        std::size_t                  writeCompEvery;\n        /// Up to this epoch comparison is written every epoch.\n        std::size_t                  writeCompAlways;\n        /// Current position in update candidate list (SM_SORT/_THRESHOLD).\n        std::size_t                  posUpdateCandidates;\n        /// Number of subcandidates which are considered before changing the\n        /// update candidate.\n        std::size_t                  numGroupedSubCand;\n        /// Counter for number of used subcandidates belonging to same update\n        /// candidate.\n        std::size_t                  countGroupedSubCand;\n        /// Maximum trials for SM_THRESHOLD selection mode.\n        std::size_t                  rmseThresholdTrials;\n        /// Counter for updates per epoch.\n        std::size_t                  countUpdates;\n        /// Number of desired updates per epoch.\n        std::size_t                  numUpdates;\n        /// Patterns used per update.\n        std::size_t                  patternsPerUpdate;\n        /// Patterns used per update (summed over all MPI tasks).\n        std::size_t                  patternsPerUpdateGlobal;\n        /// Global number of errors per update.\n        std::size_t                  numErrorsGlobal;\n        /// Desired update fraction per epoch.\n        double                       epochFraction;\n        /// RMSE threshold for update candidates.\n        double                       rmseThreshold;\n        /// Errors per task for each update.\n        std::vector<int>             errorsPerTask;\n        /// Offset for combined error per task.\n        std::vector<int>             offsetPerTask;\n        /// Error metrics available for this property.\n        std::vector<std::string>     errorMetrics;\n        /// Current error metrics of training patterns.\n        std::map<\n        std::string, double>         errorTrain;\n        /// Current error metrics of test patterns.\n        std::map<\n        std::string, double>         errorTest;\n        /// Vector with indices of training patterns.\n        std::vector<UpdateCandidate> updateCandidates;\n        /// Weights per task per updater.\n        std::vector<\n        std::vector<int>>            weightsPerTask;\n        /// Stride for Jacobians per task per updater.\n        std::vector<\n        std::vector<int>>            offsetJacobian;\n        /// Global error vector (per updater).\n        std::vector<\n        std::vector<double>>         error;\n        /// Global Jacobian (per updater).\n        std::vector<\n        std::vector<double>>         jacobian;\n        /// Schedule for varying selection mode.\n        std::map<\n        std::size_t, SelectionMode>  selectionModeSchedule;\n    };\n\n    /// Map of all training properties.\n    struct PropertyMap : std::map<std::string, Property>\n    {\n        /// Overload [] operator to simplify access.\n        Property& operator[](std::string const& key) {return this->at(key);}\n        /// Overload [] operator to simplify access (const version).\n        Property const& operator[](std::string const& key) const\n        {\n            return this->at(key);\n        }\n        /// Check if property is present.\n        bool exists(std::string const& key)\n        {\n            return (this->find(key) != this->end());\n        }\n    };\n\n    /// Updater type used.\n    UpdaterType              updaterType;\n    /// Parallelization mode used.\n    ParallelMode             parallelMode;\n    /// Jacobian mode used.\n    JacobianMode             jacobianMode;\n    /// Update strategy used.\n    UpdateStrategy           updateStrategy;\n    /// If this rank performs weight updates.\n    bool                     hasUpdaters;\n    /// If this rank holds structure information.\n    bool                     hasStructures;\n    /// Use forces for training.\n    bool                     useForces;\n    /// After force update perform energy update for corresponding structure.\n    bool                     repeatedEnergyUpdates;\n    /// Free symmetry function memory after calculation.\n    bool                     freeMemory;\n    /// Whether training log file is written.\n    bool                     writeTrainingLog;\n    /// Training stage.\n    std::size_t              stage;\n    /// Number of updaters (depends on update strategy).\n    std::size_t              numUpdaters;\n    /// Number of epochs requested.\n    std::size_t              numEpochs;\n    /// Current epoch.\n    std::size_t              epoch;\n    /// Write weights every this many epochs.\n    std::size_t              writeWeightsEvery;\n    /// Up to this epoch weights are written every epoch.\n    std::size_t              writeWeightsAlways;\n    /// Write neuron statistics every this many epochs.\n    std::size_t              writeNeuronStatisticsEvery;\n    /// Up to this epoch neuron statistics are written every epoch.\n    std::size_t              writeNeuronStatisticsAlways;\n    /// Update counter (for all training quantities together).\n    std::size_t              countUpdates;\n    /// Total number of weights. If nnpType 4G also h = sqrt(J) (hardness) is\n    /// counted.\n    std::size_t              numWeights;\n    /// Force update weight.\n    double                   forceWeight;\n    /// File name for training log.\n    std::string              trainingLogFileName;\n    /// ID of neural network the training is working on.\n    std::string              nnId;\n    /// Training log file.\n    std::ofstream            trainingLog;\n    /// Update schedule epoch (stage 1: 0 = charge update; \n    ///                        stage 2: 0 = energy update, 1 = force update (optional)).\n    std::vector<int>         epochSchedule;\n    /// Number of weights per updater. If nnpType 4G also h = sqrt(J) is \n    /// counted during stage 1 training.\n    std::vector<std::size_t> numWeightsPerUpdater;\n    /// Offset of each element's weights in combined array. If nnpType 4G also \n    /// h = sqrt(J) is counted.\n    std::vector<std::size_t> weightsOffset;\n    /// Vector of actually used training properties.\n    std::vector<std::string> pk;\n#ifndef N2P2_FULL_SFD_MEMORY\n    /// Derivative of symmetry functions with respect to one specific atom\n    /// coordinate.\n    std::vector<double>      dGdxia;\n#endif\n    /// Neural network weights and biases for each element. If nnpType 4G also\n    ///  h = sqrt(J) included.\n    std::vector<\n    std::vector<double> >    weights;\n    /// Weight updater (combined or for each element).\n    std::vector<Updater*>    updaters;\n    /// Stopwatches for timing overview.\n    std::map<\n    std::string, Stopwatch>  sw;\n    /// Per-task random number generator.\n    std::mt19937_64          rngNew;\n    /// Global random number generator.\n    std::mt19937_64          rngGlobalNew;\n    /// Actual training properties.\n    PropertyMap              p;\n\n\n    /** Check if training loop should be continued.\n     *\n     * @return True if further training should be performed, false otherwise.\n     */\n    bool advance() const;\n    /** Get weights from neural network class.\n     */\n    void getWeights();\n    /** Set weights in neural network class.\n     */\n    void setWeights();\n    /** Write energy update data to training log file.\n     *\n     * @param[in] proc Processor which provided update candidate.\n     * @param[in] il Loop index of threshold loop.\n     * @param[in] f RMSE fraction of update candidate.\n     * @param[in] is Local structure index.\n     * @param[in] isg Global structure index.\n     */\n    void addTrainingLogEntry(int         proc,\n                             std::size_t il,\n                             double      f,\n                             std::size_t isg,\n                             std::size_t is);\n    /** Write force update data to training log file.\n     *\n     * @param[in] proc Processor which provided update candidate.\n     * @param[in] il Loop index of threshold loop.\n     * @param[in] f RMSE fraction of update candidate.\n     * @param[in] is Local structure index.\n     * @param[in] isg Global structure index.\n     * @param[in] ia Atom index.\n     * @param[in] ic Component index.\n     */\n    void addTrainingLogEntry(int         proc,\n                             std::size_t il,\n                             double      f,\n                             std::size_t isg,\n                             std::size_t is,\n                             std::size_t ia,\n                             std::size_t ic);\n    /** Write charge update data to training log file.\n     *\n     * @param[in] proc Processor which provided update candidate.\n     * @param[in] il Loop index of threshold loop.\n     * @param[in] f RMSE fraction of update candidate.\n     * @param[in] is Local structure index.\n     * @param[in] isg Global structure index.\n     * @param[in] ia Atom index.\n     */\n    void addTrainingLogEntry(int         proc,\n                             std::size_t il,\n                             double      f,\n                             std::size_t isg,\n                             std::size_t is,\n                             std::size_t ia);\n#ifndef N2P2_FULL_SFD_MEMORY\n    /** Collect derivative of symmetry functions with respect to one atom's\n     * coordinate.\n     *\n     * @param[in] atom The atom which owns the symmetry functions.\n     * @param[in] indexAtom The index @f$i@f$ of the atom requested.\n     * @param[in] indexComponent The component @f$\\alpha@f$ of the atom\n     *                           requested.\n     *\n     * This calculates an array of derivatives\n     * @f[\n     *   \\left(\\frac{\\partial G_1}{\\partial x_{i,\\alpha}}, \\ldots,\n     *   \\frac{\\partial G_n}{\\partial x_{i,\\alpha}}\\right),\n     *\n     * @f]\n     * where @f$\\{G_j\\}_{j=1,\\ldots,n}@f$ are the symmetry functions for this\n     * atom and @f$x_{i,\\alpha}@f$ is the @f$\\alpha@f$-component of the\n     * position of atom @f$i@f$. The result is stored in #dGdxia.\n     */\n    void collectDGdxia(Atom const& atom,\n                       std::size_t indexAtom,\n                       std::size_t indexComponent);\n#endif\n    /** Randomly initialize specificy neural network weights.\n     *\n     * @param[in] id Actual network type to initialize (\"short\" or \"elec\").\n     */\n    void randomizeNeuralNetworkWeights(std::string const& id);\n    /** Set selection mode for specific training property.\n     *\n     * @param[in] property Training property (uses corresponding keyword).\n     */\n    void setupSelectionMode(std::string const& property);\n    /** Set file output intervals for properties and other quantities.\n     *\n     * @param[in] type Training property or `weights` or `neuron-stats`.\n     */\n    void setupFileOutput(std::string const& type);\n    /** Set up how often properties are updated.\n     *\n     * @param[in] property Training property (uses corresponding keyword).\n     */\n    void setupUpdatePlan(std::string const& property);\n    /** Allocate error and Jacobian arrays for given property.\n     *\n     * @param[in] property Training property.\n     */\n    void allocateArrays(std::string const& property);\n    /** Write timing data for all clocks.\n     *\n     * @param[in] append If true, append to file, otherwise create new file.\n     * @param[in] fileName File name for timing data file.\n     */\n    void writeTimingData(bool              append,\n                         std::string const fileName = \"timing.out\");\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnptrain/Updater.cpp",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#include \"Updater.h\"\n\nusing namespace std;\nusing namespace nnp;\n\nUpdater::Updater(size_t const sizeState) : timing     (false    ),\n                                           timingReset(true     ),\n                                           sizeState  (sizeState),\n                                           prefix     (\"\"       )\n{\n}\n\nvoid Updater::setupTiming(string const& prefix)\n{\n    this->prefix = prefix;\n    timing = true;\n\n    return;\n}\n\nstd::map<std::string, Stopwatch> Updater::getTiming() const\n{\n    return sw;\n}\n\nvoid Updater::resetTimingLoop()\n{\n    timingReset = false;\n    return;\n}\n"
  },
  {
    "path": "src/libnnptrain/Updater.h",
    "content": "// n2p2 - A neural network potential package\n// Copyright (C) 2018 Andreas Singraber (University of Vienna)\n//\n// This program is free software: you can redistribute it and/or modify\n// it under the terms of the GNU General Public License as published by\n// the Free Software Foundation, either version 3 of the License, or\n// (at your option) any later version.\n//\n// This program is distributed in the hope that it will be useful,\n// but WITHOUT ANY WARRANTY; without even the implied warranty of\n// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n// GNU General Public License for more details.\n//\n// You should have received a copy of the GNU General Public License\n// along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n#ifndef UPDATER_H\n#define UPDATER_H\n\n#include \"Stopwatch.h\"\n\n#include <cstddef> // std::size_t\n#include <map>     // std::map\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nnamespace nnp\n{\n\n/// Base class for different weight update methods.\nclass Updater\n{\npublic:\n    /** Set pointer to current state.\n     *\n     * @param[in,out] state Pointer to state vector (weights vector), will be\n     *                      changed in-place upon calling update().\n     */\n    virtual void                     setState(double* state) = 0;\n    /** Set pointer to current error vector.\n     *\n     * @param[in] error Pointer to error (difference between reference and\n     *                  neural network potential output).\n     * @param[in] size Number of error vector entries.\n     */\n    virtual void                     setError(\n                                             double const* const error,\n                                             std::size_t const   size = 1) = 0;\n    /** Set pointer to current Jacobi matrix.\n     *\n     * @param[in] jacobian Derivatives of error with respect to weights.\n     * @param[in] columns Number of gradients provided.\n     *\n     * @note\n     * If there are @f$m@f$ errors and @f$n@f$ weights, the Jacobi matrix\n     * is a @f$n \\times m@f$ matrix stored in column-major order.\n     */\n    virtual void                     setJacobian(\n                                          double const* const jacobian,\n                                          std::size_t const   columns = 1) = 0;\n    /** Perform single update of state vector.\n     */\n    virtual void                     update() = 0;\n    /** Status report.\n     *\n     * @param[in] epoch Current epoch.\n     *\n     * @return Line with current status information.\n     */\n    virtual std::string              status(std::size_t epoch) const = 0;\n    /** Header for status report file.\n     *\n     * @return Vector with header lines.\n     */\n    virtual std::vector<std::string> statusHeader() const = 0;\n    /** Information about this updater.\n     *\n     * @return Vector of information lines.\n     */\n    virtual std::vector<std::string> info() const = 0;\n    /** Activate detailed timing.\n     *\n     * @param[in] prefix Prefix used for stopwatch map entries.\n     */\n    virtual void                     setupTiming(\n                                            std::string const& prefix = \"upd\");\n    /** Start a new timing loop (e.g. epoch).\n     */\n    virtual void                     resetTimingLoop();\n    /** Return timings gathered in stopwatch map.\n     *\n     * @return Stopwatch map.\n     */\n    virtual\n    std::map<std::string, Stopwatch> getTiming() const;\n\nprotected:\n    /** Constructor\n     *\n     * @param[in] sizeState Size of the state vector (number of parameters to\n     *                      optimize).\n     */\n    Updater(std::size_t const sizeState);\n\n    /// Whether detailed timing is enabled.\n    bool                             timing;\n    /// Internal loop timer reset switch.\n    bool                             timingReset;\n    /// Number of neural network connections (weights + biases).\n    std::size_t                      sizeState;\n    /// Prefix for timing stopwatches.\n    std::string                      prefix;\n    /// Stopwatch map for timing.\n    std::map<std::string, Stopwatch> sw;\n};\n\n}\n\n#endif\n"
  },
  {
    "path": "src/libnnptrain/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=../..\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# GENERAL SETTINGS\n###############################################################################\n# Default compiler, may be overridden by master makefile or command line.\nCOMP=gnu\n\n# Default build mode, may be overridden by master makefile or command line.\n# Possible modes are \"static\", \"shared\" and \"test\".\nMODE=static\n\n# Include global (project-wide) settings.\ninclude $(PROJECT_DIR)/src/makefile.$(COMP)\n\n\n###############################################################################\n# LIBRARY NAME\n###############################################################################\nNAME=nnptrain\nLIB=lib$(NAME)\n\n\n###############################################################################\n# PROJECT COMPILER AND FLAGS\n###############################################################################\nCC=$(PROJECT_CC)\nMPICC=$(PROJECT_MPICC)\nCFLAGS=$(PROJECT_CFLAGS) $(PROJECT_CFLAGS_MPI)\nOPTIONS+=$(PROJECT_OPTIONS)\nDEBUG=$(PROJECT_DEBUG)\nifeq ($(MODE), test)\nDEBUG+= $(PROJECT_TEST)\nendif\nAR=$(PROJECT_AR)\nARFLAGS=$(PROJECT_ARFLAGS)\n\n# Extra include paths for compiling.\nINCLUDES=-I./ -I$(PROJECT_INCLUDE)/ -I$(PROJECT_GSL) -I$(PROJECT_EIGEN)\n\n\n###############################################################################\n# DEFINE SOURCES AND HEADERS\n###############################################################################\nSRC=$(wildcard *.cpp)\nHEADERS=$(wildcard *.h)\nOBJ=$(SRC:.cpp=.o)\n\n\n###############################################################################\n# RULES\n###############################################################################\n.PHONY: all headers clean rebuild\n\nifeq ($(MODE), shared)\nall: headers $(LIB).so\nelse\nall: headers $(LIB).a\nendif\n\nheaders:\n\tcp $(HEADERS) $(PROJECT_INCLUDE)\n\n$(LIB).so: CFLAGS+= -fPIC\n$(LIB).so: $(OBJ)\n\t$(MPICC) $(CFLAGS) $(DEBUG) $(OPTIONS) -o $@ $+ -shared\n\tcp $@ $(PROJECT_LIB)\n\n$(LIB).a: $(OBJ)\n\t$(AR) $(ARFLAGS) $@ $+\n\tcp $@ $(PROJECT_LIB)\n\n%.o: %.cpp\n\t$(MPICC) $(CFLAGS) $(DEBUG) $(INCLUDES) $(OPTIONS) -o $@ -c $<\n\nclean: clean-headers\n\t$(RM) $(OBJ)\n\t$(RM) *.gcno *.gcda $(LIB).so $(LIB).a\n\t$(RM) $(PROJECT_LIB)/$(LIB).so $(PROJECT_LIB)/$(LIB).a\n\nclean-headers:\n\tcd $(PROJECT_INCLUDE) && $(RM) $(HEADERS)\n\nrebuild: clean all\n"
  },
  {
    "path": "src/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=..\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# GENERAL SETTINGS\n###############################################################################\n# Default compiler (gnu/intel/llvm).\nCOMP=gnu\n\n# Default build mode.\n# Possible modes are \"static\", \"shared\" and \"test\".\n# Note: For target \"pynnp\" there is no \"static\" mode, \"shared\" is automatically\n# used instead.\nMODE=static\n\n# Installation directory for binaries.\nINSTALL_BIN=$(HOME)/local/bin\n\n# Installation directory for libraries.\nINSTALL_LIB=$(HOME)/local/lib\n\n\n###############################################################################\n# INTERFACE LIBRARY OPTIONS\n###############################################################################\n\n# Select which interfaces should be compiled into libnnpif. Provide a\n# space-separated list of the following available options:\n#    * LAMMPS\n#    * CabanaMD\nINTERFACES=LAMMPS CabanaMD\n\n\n###############################################################################\n# APPLICATION TARGET NAMES\n###############################################################################\n\n# Variables should not contain \"entering directory...\", so we temporarily\n# disable it\nMAKEFLAGS_ORIGINAL:=$(MAKEFLAGS)\nMAKEFLAGS += --no-print-directory\n\n# Call makefile in \"application\" directory to list targets.\nAPP_LIBNNP:=$(shell cd application && $(MAKE) $(MFLAGS) list-libnnp)\nAPP_LIBNNPTRAIN:=$(shell cd application && $(MAKE) $(MFLAGS) list-libnnptrain)\nAPP:=$(shell cd application && $(MAKE) $(MFLAGS) list-all)\n\n# Targets for cleaning.\nCLEAN_APP=$(patsubst %, clean-%, $(APP))\n\nMAKEFLAGS:=$(MAKEFLAGS_ORIGINAL)\n\n###############################################################################\n# RULES\n###############################################################################\n.PHONY:\tall \\\n\tdoc \\\n\tdoc-sphinx \\\n\tdoc-doxygen \\\n\tlibnnp \\\n\tlibnnptrain \\\n\tlibnnpif \\\n\tlammps-hdnnp \\\n\tpynnp \\\n\tclean-doc \\\n\tclean-doc-sphinx \\\n\tclean-doc-doxygen \\\n\tclean-no-doc \\\n\tclean-libnnp \\\n\tclean-libnnptrain \\\n\tclean-libnnpif \\\n\tclean-lammps-hdnnp \\\n\tclean-pynnp \\\n\tinstall \\\n\tuninstall\n\nall: libnnp \\\n     libnnptrain \\\n     libnnpif \\\n     all-app\n\nclean: clean-libnnp \\\n       clean-libnnptrain \\\n       clean-libnnpif \\\n       clean-app \\\n       clean-lammps-hdnnp \\\n       clean-pynnp\n\nclean-all: clean \\\n           clean-doc\n\n################################\n# doc, doc-sphinx, doc-doxygen #\n################################\ndoc: doc-doxygen doc-sphinx\n\tcp -r ../doc/doxygen/html ../doc/sphinx/html/doxygen\n\nclean-doc: clean-doc-sphinx clean-doc-doxygen\n\ndoc-sphinx:\n\tcd doc/sphinx && $(MAKE) html\n\nclean-doc-sphinx:\n\tcd doc/sphinx && $(MAKE) clean\n\ndoc-doxygen:\n\tcd doc/doxygen && $(MAKE)\n\nclean-doc-doxygen:\n\tcd doc/doxygen && $(MAKE) clean\n\n##########\n# libnnp #\n##########\nlibnnp:\n\tcd libnnp && $(MAKE) COMP=$(COMP) MODE=$(MODE)\n\nclean-libnnp:\n\tcd libnnp && $(MAKE) clean\n\n###############\n# libnnptrain #\n###############\nlibnnptrain: libnnp\n\tcd $@ && $(MAKE) COMP=$(COMP) MODE=$(MODE)\n\nclean-libnnptrain: LIBDIR=$(subst clean-,,$@)\nclean-libnnptrain:\n\tcd $(LIBDIR) && $(MAKE) clean\n\n############\n# libnnpif #\n############\nlibnnpif: libnnp\n\tcd $@ && $(MAKE) COMP=$(COMP) MODE=$(MODE) INTERFACES=\"$(INTERFACES)\"\n\nclean-libnnpif: LIBDIR=$(subst clean-,,$@)\nclean-libnnpif:\n\tcd $(LIBDIR) && $(MAKE) INTERFACES=\"$(INTERFACES)\" clean\n\n####################\n# nnp applications #\n####################\n# All at once (parallel).\nall-app: libnnptrain\n\tcd application && $(MAKE) COMP=$(COMP) MODE=$(MODE)\n\nclean-app:\n\tcd application && $(MAKE) clean\n\n# Individual applications.\n$(APP_LIBNNP): libnnp\n\tcd application && $(MAKE) $@ COMP=$(COMP) MODE=$(MODE)\n\n$(APP_LIBNNPTRAIN): libnnptrain\n\tcd application && $(MAKE) $@ COMP=$(COMP) MODE=$(MODE)\n\n$(CLEAN_APP):\n\tcd application && $(MAKE) $@\n\n################\n# lammps-hdnnp #\n################\ndefine LAMMPS_NNP_WARNING\n##############################################################\n#           __      ___   ___ _  _ ___ _  _  ___             #\n#           \\ \\    / /_\\ | _ \\ \\| |_ _| \\| |/ __|            #\n#            \\ \\/\\/ / _ \\|   / .` || || .` | (_ |            #\n#             \\_/\\_/_/ \\_\\_|_\\_|\\_|___|_|\\_|\\___|            #\n#                                                            #\n# WARNING: This is a development build of LAMMPS + n2p2!     #\n#                                                            #\n# n2p2's makefile feature to build an automatically patched  #\n# version of LAMMPS is designed for development purposes and #\n# not guarantueed to work. The recommended way to build and  #\n# link LAMMPS with n2p2 is based on the build system of      #\n# LAMMPS and described here:                                 #\n#                                                            #\n# https://docs.lammps.org/Build_extras.html#ml-hdnnp         #\n#                                                            #\n##############################################################\nendef\n\nexport LAMMPS_NNP_WARNING\nlammps-hdnnp: libnnpif\n\t@echo \"$$LAMMPS_NNP_WARNING\"\n\tcd libnnpif && $(MAKE) lammps-mf\n\tcd interface && $(MAKE) $@ COMP=$(COMP) MODE=$(MODE)\n\t@echo \"$$LAMMPS_NNP_WARNING\"\n\nclean-lammps-hdnnp:\n\t#cd interface && $(MAKE) $@\n\tcd interface && $(MAKE) clean-lammps-hdnnp-keep-file\n\n#########\n# pynnp #\n#########\npynnp:\n\tcd pynnp && $(MAKE) MODE=$(MODE)\n\nclean-pynnp:\n\tcd pynnp && $(MAKE) clean\n\n##############################################\n# install (set links to install directories) #\n##############################################\nEXE=$(APP)\nDLIB=libnnp.so libnnpif.so libnnptrain.so\nSLIB=$(DLIB:.so=.a)\nPYLIB=$(wildcard $(PROJECT_LIB)/pynnp*.so)\ninstall:\n\t$(foreach exe, $(EXE), ln -s $(CURDIR)/$(PROJECT_BIN)/$(exe) $(INSTALL_BIN)/$(exe);)\n\t$(foreach dlib, $(DLIB), ln -s $(CURDIR)/$(PROJECT_LIB)/$(dlib) $(INSTALL_LIB)/$(dlib);)\n\t$(foreach slib, $(SLIB), ln -s $(CURDIR)/$(PROJECT_LIB)/$(slib) $(INSTALL_LIB)/$(slib);)\n\t$(foreach pylib, $(notdir $(PYLIB)), ln -s $(CURDIR)/$(PROJECT_LIB)/$(pylib) $(INSTALL_LIB)/$(pylib);)\n\nuninstall:\n\t$(foreach exe, $(EXE), rm $(INSTALL_BIN)/$(exe);)\n\t$(foreach dlib, $(DLIB), rm $(INSTALL_LIB)/$(dlib);)\n\t$(foreach slib, $(SLIB), rm $(INSTALL_LIB)/$(slib);)\n\t$(foreach pylib, $(notdir $(PYLIB)), rm $(INSTALL_LIB)/$(pylib);)\n"
  },
  {
    "path": "src/makefile.gnu",
    "content": "#!/bin/make -f\n\n###############################################################################\n# EXTERNAL LIBRARY PATHS\n###############################################################################\n# Enter here paths to GSL or EIGEN if they are not in your standard include\n# path. DO NOT completely remove the entry, leave at least \"./\".\nPROJECT_GSL=./\n#PROJECT_GSL=${HOME}/local/src/gsl-2.8/build/include\nPROJECT_EIGEN=/usr/include/eigen3/\n#PROJECT_EIGEN=${HOME}/local/src/eigen/\nPROJECT_BOOST=${BOOST_ROOT}\n\n###############################################################################\n# COMPILERS AND FLAGS\n###############################################################################\nPROJECT_CC=g++\nPROJECT_MPICC=mpic++\n# OpenMP parallelization is disabled by default, add flag \"-fopenmp\" to enable.\nPROJECT_CFLAGS=-O3 -march=native -std=c++11 #-fopenmp\nPROJECT_CFLAGS_MPI=-Wno-long-long\nPROJECT_DEBUG=-g -pedantic-errors -Wall -Wextra\nPROJECT_TEST=--coverage -fno-default-inline -fno-inline -fno-inline-small-functions -fno-elide-constructors\nPROJECT_AR=ar\nPROJECT_ARFLAGS=-rcsv\nPROJECT_CFLAGS_BLAS=\nPROJECT_LDFLAGS_BLAS=-lopenblas -lgsl -lgslcblas\n\n###############################################################################\n# COMPILE-TIME OPTIONS\n###############################################################################\n\n# Do not use symmetry function groups.\n#PROJECT_OPTIONS+= -DN2P2_NO_SF_GROUPS\n\n# Do not use symmetry function cache.\n#PROJECT_OPTIONS+= -DN2P2_NO_SF_CACHE\n\n# Disable asymmetric polynomial symmetry functions.\n#PROJECT_OPTIONS+= -DN2P2_NO_ASYM_POLY\n\n# Build with dummy Stopwatch class.\n#PROJECT_OPTIONS+= -DN2P2_NO_TIME\n\n# Disable check for low number of neighbors.\n#PROJECT_OPTIONS+= -DN2P2_NO_NEIGH_CHECK\n\n# Use alternative (older) memory layout for symmetry function derivatives.\n#PROJECT_OPTIONS+= -DN2P2_FULL_SFD_MEMORY\n\n# Compile without MPI support.\n#PROJECT_OPTIONS+= -DN2P2_NO_MPI\n\n# Use BLAS together with Eigen.\n#PROJECT_OPTIONS+= -DEIGEN_USE_BLAS\n\n# Disable all C++ asserts (also Eigen debugging).\n#PROJECT_OPTIONS+= -DNDEBUG\n\n# Use Intel MKL together with Eigen.\n#PROJECT_OPTIONS+= -DEIGEN_USE_MKL_ALL\n\n# Disable Eigen multi threading.\nPROJECT_OPTIONS+= -DEIGEN_DONT_PARALLELIZE\n"
  },
  {
    "path": "src/makefile.intel",
    "content": "#!/bin/make -f\n\n###############################################################################\n# EXTERNAL LIBRARY PATHS\n###############################################################################\n# Enter here paths to GSL or EIGEN if they are not in your standard include\n# path. DO NOT completely remove the entry, leave at least \"./\".\nPROJECT_GSL=./\nPROJECT_EIGEN=/usr/include/eigen3/\n\n###############################################################################\n# COMPILERS AND FLAGS\n###############################################################################\nPROJECT_CC=icpc\nPROJECT_MPICC=mpiicpc\n# OpenMP parallelization is disabled by default, add flag \"-qopenmp\" to enable.\nPROJECT_CFLAGS=-O3 -xHost -std=c++11 -ipo\nPROJECT_CFLAGS_MPI=-Wno-long-long\nPROJECT_DEBUG=-g -pedantic-errors -Wall -Wextra\nPROJECT_TEST= # Testing works only with gnu compiler\nPROJECT_AR=xiar\nPROJECT_ARFLAGS=-rcsv\nPROJECT_CFLAGS_BLAS=\n#PROJECT_LDFLAGS_BLAS=-lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -liomp5 -lpthread -lm -ldl\nPROJECT_LDFLAGS_BLAS=-lmkl_intel_lp64 -lmkl_sequential -lmkl_core -lpthread -lm -ldl\n\n###############################################################################\n# COMPILE-TIME OPTIONS\n###############################################################################\n\n# Do not use symmetry function groups.\n#PROJECT_OPTIONS+= -DN2P2_NO_SF_GROUPS\n\n# Do not use symmetry function cache.\n#PROJECT_OPTIONS+= -DN2P2_NO_SF_CACHE\n\n# Disable asymmetric polynomial symmetry functions.\n#PROJECT_OPTIONS+= -DN2P2_NO_ASYM_POLY\n\n# Build with dummy Stopwatch class.\n#PROJECT_OPTIONS+= -DN2P2_NO_TIME\n\n# Disable check for low number of neighbors.\n#PROJECT_OPTIONS+= -DN2P2_NO_NEIGH_CHECK\n\n# Use alternative (older) memory layout for symmetry function derivatives.\n#PROJECT_OPTIONS+= -DN2P2_FULL_SFD_MEMORY\n\n# Compile without MPI support.\n#PROJECT_OPTIONS+= -DN2P2_NO_MPI\n\n# Use BLAS together with Eigen.\n#PROJECT_OPTIONS+= -DEIGEN_USE_BLAS\n\n# Disable all C++ asserts (also Eigen debugging).\n#PROJECT_OPTIONS+= -DNDEBUG\n\n# Use Intel MKL together with Eigen.\nPROJECT_OPTIONS+= -DEIGEN_USE_MKL_ALL\n\n# Disable Eigen multi threading.\nPROJECT_OPTIONS+= -DEIGEN_DONT_PARALLELIZE\n"
  },
  {
    "path": "src/makefile.llvm",
    "content": "#!/bin/make -f\n\n###############################################################################\n# EXTERNAL LIBRARY PATHS\n###############################################################################\n# Enter here paths to GSL or EIGEN if they are not in your standard include\n# path. DO NOT completely remove the entry, leave at least \"./\".\nPROJECT_GSL=/usr/local/include/gsl\nPROJECT_EIGEN=/usr/local/include/eigen3\n\n###############################################################################\n# COMPILERS AND FLAGS\n###############################################################################\nPROJECT_CC=clang++\nPROJECT_MPICC=mpic++\n# OpenMP parallelization is disabled by default, add flags \"-fopenmp -lomp\" to enable.\nPROJECT_CFLAGS=-O3 -march=native -std=c++11 -Xpreprocessor\nPROJECT_CFLAGS_MPI=-Wno-long-long\nPROJECT_DEBUG=-g -pedantic-errors -Wall -Wextra\nPROJECT_TEST= # Testing works only with gnu compiler\nPROJECT_AR=ar\nPROJECT_ARFLAGS=-rcsv\nPROJECT_CFLAGS_BLAS=\nPROJECT_LDFLAGS_BLAS=-lblas\n\nPROJECT_OPTIONS=-I${HOME}/miniconda3/envs/n2p2/include/\n\n###############################################################################\n# COMPILE-TIME OPTIONS\n###############################################################################\n\n# Do not use symmetry function groups.\n#PROJECT_OPTIONS+= -DN2P2_NO_SF_GROUPS\n\n# Do not use symmetry function cache.\n#PROJECT_OPTIONS+= -DN2P2_NO_SF_CACHE\n\n# Disable asymmetric polynomial symmetry functions.\n#PROJECT_OPTIONS+= -DN2P2_NO_ASYM_POLY\n\n# Build with dummy Stopwatch class.\n#PROJECT_OPTIONS+= -DN2P2_NO_TIME\n\n# Disable check for low number of neighbors.\n#PROJECT_OPTIONS+= -DN2P2_NO_NEIGH_CHECK\n\n# Use alternative (older) memory layout for symmetry function derivatives.\n#PROJECT_OPTIONS+= -DN2P2_FULL_SFD_MEMORY\n\n# Compile without MPI support.\n#PROJECT_OPTIONS+= -DN2P2_NO_MPI\n\n# Use BLAS together with Eigen.\nPROJECT_OPTIONS+= -DEIGEN_USE_BLAS\n\n# Disable all C++ asserts (also Eigen debugging).\n#PROJECT_OPTIONS+= -DNDEBUG\n\n# Use Intel MKL together with Eigen.\n#PROJECT_OPTIONS+= -DEIGEN_USE_MKL_ALL\n\n# Disable Eigen multi threading.\nPROJECT_OPTIONS+= -DEIGEN_DONT_PARALLELIZE\n"
  },
  {
    "path": "src/pynnp/Atom.pyx",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\ncdef class Neighbor:\n    cdef pd_Atom.Neighbor* thisptr\n    cdef object owner\n\n    def __cinit__(self, empty=False):\n        if empty is True:\n            self.owner = False\n            return\n        self.thisptr = new pd_Atom.Neighbor()\n        self.owner = True\n    cdef set_ptr(self, pd_Atom.Neighbor* ptr, owner):\n        if self.owner is True:\n            del self.thisptr\n        self.thisptr = ptr\n        self.owner = owner\n    def __dealloc__(self):\n        if self.owner is True:\n            del self.thisptr\n    def __eq__(self, rhs):\n        cdef Neighbor rhs2 = <Neighbor?>rhs\n        return self.thisptr.eq(deref(rhs2.thisptr))\n    def __ne__(self, rhs):\n        cdef Neighbor rhs2 = <Neighbor?>rhs\n        return self.thisptr.ne(deref(rhs2.thisptr))\n    def __lt__(self, rhs):\n        cdef Neighbor rhs2 = <Neighbor?>rhs\n        return self.thisptr.lt(deref(rhs2.thisptr))\n    def __gt__(self, rhs):\n        cdef Neighbor rhs2 = <Neighbor?>rhs\n        return self.thisptr.gt(deref(rhs2.thisptr))\n    def __le__(self, rhs):\n        cdef Neighbor rhs2 = <Neighbor?>rhs\n        return self.thisptr.le(deref(rhs2.thisptr))\n    def __ge__(self, rhs):\n        cdef Neighbor rhs2 = <Neighbor?>rhs\n        return self.thisptr.ge(deref(rhs2.thisptr))\n\n    # index\n    @property\n    def index(self):\n        return deref(self.thisptr).index\n    @index.setter\n    def index(self, value):\n        deref(self.thisptr).index = value\n    # tag\n    @property\n    def tag(self):\n        return deref(self.thisptr).tag\n    @tag.setter\n    def tag(self, value):\n        deref(self.thisptr).tag = value\n    # element\n    @property\n    def element(self):\n        return deref(self.thisptr).element\n    @element.setter\n    def element(self, value):\n        deref(self.thisptr).element = value\n    # d\n    @property\n    def d(self):\n        return deref(self.thisptr).d\n    @d.setter\n    def d(self, value):\n        deref(self.thisptr).d = value\n    # dr\n    @property\n    def dr(self):\n        res = Vec3D(True)\n        res.set_ptr(&self.thisptr.dr, self)\n        return res\n    @dr.setter\n    def dr(self, Vec3D v):\n        deref(self.thisptr).dr = deref(v.thisptr)\n    # cache\n    @property\n    def cache(self):\n        return deref(self.thisptr).cache\n    @cache.setter\n    def cache(self, value):\n        deref(self.thisptr).cache = value\n    # dGdr\n    @property\n    def dGdr(self):\n        res = []\n        for i in range(self.thisptr.dGdr.size()):\n            e = Vec3D(True)\n            e.set_ptr(&self.thisptr.dGdr[i], self)\n            res += [e]\n        return res\n\ncdef class Atom:\n    cdef pd.Atom* thisptr\n    cdef object owner\n\n    def __cinit__(self, empty=False):\n        if empty is True:\n            self.owner = False\n            return\n        self.thisptr = new pd.Atom()\n        self.owner = True\n    cdef set_ptr(self, pd.Atom* ptr, owner):\n        if self.owner is True:\n            del self.thisptr\n        self.thisptr = ptr\n        self.owner = owner\n    def __dealloc__(self):\n        if self.owner is True:\n            del self.thisptr\n    def info(self):\n        return self.thisptr.info()\n\n    # hasNeighborList\n    @property\n    def hasNeighborList(self):\n        return deref(self.thisptr).hasNeighborList\n    @hasNeighborList.setter\n    def hasNeighborList(self, value):\n        deref(self.thisptr).hasNeighborList = value\n    # hasSymmetryFunctions\n    @property\n    def hasSymmetryFunctions(self):\n        return deref(self.thisptr).hasSymmetryFunctions\n    @hasSymmetryFunctions.setter\n    def hasSymmetryFunctions(self, value):\n        deref(self.thisptr).hasSymmetryFunctions = value\n    # hasSymmetryFunctionDerivatives\n    @property\n    def hasSymmetryFunctionDerivatives(self):\n        return deref(self.thisptr).hasSymmetryFunctionDerivatives\n    @hasSymmetryFunctionDerivatives.setter\n    def hasSymmetryFunctionDerivatives(self, value):\n        deref(self.thisptr).hasSymmetryFunctionDerivatives = value\n    # useChargeNeuron\n    @property\n    def useChargeNeuron(self):\n        return deref(self.thisptr).useChargeNeuron\n    @useChargeNeuron.setter\n    def useChargeNeuron(self, value):\n        deref(self.thisptr).useChargeNeuron = value\n    # index\n    @property\n    def index(self):\n        return deref(self.thisptr).index\n    @index.setter\n    def index(self, value):\n        deref(self.thisptr).index = value\n    # indexStructure\n    @property\n    def indexStructure(self):\n        return deref(self.thisptr).indexStructure\n    @indexStructure.setter\n    def indexStructure(self, value):\n        deref(self.thisptr).indexStructure = value\n    # tag\n    @property\n    def tag(self):\n        return deref(self.thisptr).tag\n    @tag.setter\n    def tag(self, value):\n        deref(self.thisptr).tag = value\n    # element\n    @property\n    def element(self):\n        return deref(self.thisptr).element\n    @element.setter\n    def element(self, value):\n        deref(self.thisptr).element = value\n    # numNeighbors\n    @property\n    def numNeighbors(self):\n        return deref(self.thisptr).numNeighbors\n    @numNeighbors.setter\n    def numNeighbors(self, value):\n        deref(self.thisptr).numNeighbors = value\n    # numNeighborsUnique\n    @property\n    def numNeighborsUnique(self):\n        return deref(self.thisptr).numNeighborsUnique\n    @numNeighborsUnique.setter\n    def numNeighborsUnique(self, value):\n        deref(self.thisptr).numNeighborsUnique = value\n    # numSymmetryFunctions\n    @property\n    def numSymmetryFunctions(self):\n        return deref(self.thisptr).numSymmetryFunctions\n    @numSymmetryFunctions.setter\n    def numSymmetryFunctions(self, value):\n        deref(self.thisptr).numSymmetryFunctions = value\n    # energy\n    @property\n    def energy(self):\n        return deref(self.thisptr).energy\n    @energy.setter\n    def energy(self, value):\n        deref(self.thisptr).energy = value\n    #charge\n    @property\n    def charge(self):\n        return deref(self.thisptr).charge\n    @charge.setter\n    def charge(self, value):\n        deref(self.thisptr).charge = value\n    #chargeRef\n    @property\n    def chargeRef(self):\n        return deref(self.thisptr).chargeRef\n    @chargeRef.setter\n    def chargeRef(self, value):\n        deref(self.thisptr).chargeRef = value\n    # r\n    @property\n    def r(self):\n        res = Vec3D(True)\n        res.set_ptr(&self.thisptr.r, self)\n        return res\n    @r.setter\n    def r(self, Vec3D v):\n        deref(self.thisptr).r = deref(v.thisptr)\n    # f\n    @property\n    def f(self):\n        res = Vec3D(True)\n        res.set_ptr(&self.thisptr.f, self)\n        return res\n    @f.setter\n    def f(self, Vec3D v):\n        deref(self.thisptr).f = deref(v.thisptr)\n    # fRef\n    @property\n    def fRef(self):\n        res = Vec3D(True)\n        res.set_ptr(&self.thisptr.fRef, self)\n        return res\n    @fRef.setter\n    def fRef(self, Vec3D v):\n        deref(self.thisptr).fRef = deref(v.thisptr)\n    # neighborsUnique\n    @property\n    def neighborsUnique(self):\n        return deref(self.thisptr).neighborsUnique\n    @neighborsUnique.setter\n    def neighborsUnique(self, value):\n        deref(self.thisptr).neighborsUnique = value\n    # numNeighborsPerElement\n    @property\n    def numNeighborsPerElement(self):\n        return deref(self.thisptr).numNeighborsPerElement\n    @numNeighborsPerElement.setter\n    def numNeighborsPerElement(self, value):\n        deref(self.thisptr).numNeighborsPerElement = value\n    # numSymmetryFunctionDerivatives\n    @property\n    def numSymmetryFunctionDerivatives(self):\n        return deref(self.thisptr).numSymmetryFunctionDerivatives\n    @numSymmetryFunctionDerivatives.setter\n    def numSymmetryFunctionDerivatives(self, value):\n        deref(self.thisptr).numSymmetryFunctionDerivatives = value\n    # cacheSizePerElement\n    @property\n    def cacheSizePerElement(self):\n        return deref(self.thisptr).cacheSizePerElement\n    @cacheSizePerElement.setter\n    def cacheSizePerElement(self, value):\n        deref(self.thisptr).cacheSizePerElement = value\n    # G\n    @property\n    def G(self):\n        return deref(self.thisptr).G\n    @G.setter\n    def G(self, value):\n        deref(self.thisptr).G = value\n    # dEdG\n    @property\n    def dEdG(self):\n        return deref(self.thisptr).dEdG\n    @dEdG.setter\n    def dEdG(self, value):\n        deref(self.thisptr).dEdG = value\n    # dQdG\n    @property\n    def dQdG(self):\n        return deref(self.thisptr).dQdG\n    @dQdG.setter\n    def dQdG(self, value):\n        deref(self.thisptr).dQdG = value\n    ## dGdxia\n    #@property\n    #def dGdxia(self):\n    #    return deref(self.thisptr).dGdxia\n    #@dGdxia.setter\n    #def dGdxia(self, value):\n    #    deref(self.thisptr).dGdxia = value\n    # dGdr\n    @property\n    def dGdr(self):\n        res = []\n        for i in range(self.thisptr.dGdr.size()):\n            e = Vec3D(True)\n            e.set_ptr(&self.thisptr.dGdr[i], self)\n            res += [e]\n        return res\n    # neighbors\n    @property\n    def neighbors(self):\n        res = []\n        for i in range(self.thisptr.neighbors.size()):\n            e =  Neighbor(True)\n            e.set_ptr(&self.thisptr.neighbors[i], self)\n            res += [e]\n        return res\n"
  },
  {
    "path": "src/pynnp/CutoffFunction.pyx",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\ncdef class CutoffFunction:\n    cdef pd.CutoffFunction* thisptr\n    cdef object owner\n    CT_HARD  = pd.CT_HARD\n    CT_COS   = pd.CT_COS\n    CT_TANHU = pd.CT_TANHU\n    CT_TANH  = pd.CT_TANH\n    CT_EXP   = pd.CT_EXP\n    CT_POLY1 = pd.CT_POLY1\n    CT_POLY2 = pd.CT_POLY2\n    CT_POLY3 = pd.CT_POLY3\n    CT_POLY4 = pd.CT_POLY4\n\n    def __cinit__(self, empty=False):\n        if empty is True:\n            self.owner = False\n            return\n        self.thisptr = new pd.CutoffFunction()\n        self.owner = True\n    cdef set_ptr(self, pd.CutoffFunction* ptr, owner):\n        if self.owner is True:\n            del self.thisptr\n        self.thisptr = ptr\n        self.owner = owner\n    def __dealloc__(self):\n        if self.owner is True:\n            del self.thisptr\n    def setCutoffType(self, cutoffType):\n        self.thisptr.setCutoffType(cutoffType)\n    def setCutoffRadius(self, cutoffRadius):\n        self.thisptr.setCutoffRadius(cutoffRadius)\n    def setCutoffParameter(self, alpha):\n        self.thisptr.setCutoffParameter(alpha)\n    def f(self, r):\n        return self.thisptr.f(r)\n    def df(self, r):\n        return self.thisptr.df(r)\n    def fdf(self, r):\n        cdef double fc = 0.0\n        cdef double dfc = 0.0\n        self.thisptr.fdf(r, fc, dfc)\n        return fc, dfc\n"
  },
  {
    "path": "src/pynnp/ElementMap.pyx",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\ncdef class ElementMap:\n    cdef pd.ElementMap* thisptr\n    cdef object owner\n\n    def __cinit__(self, empty=False):\n        if empty is True:\n            self.owner = False\n            return\n        self.thisptr = new pd.ElementMap()\n        self.owner = True\n    cdef set_ptr(self, pd.ElementMap* ptr, owner):\n        if self.owner is True:\n            del self.thisptr\n        self.thisptr = ptr\n        self.owner = owner\n    def __dealloc__(self):\n        if self.owner is True:\n            del self.thisptr\n    def __getitem__(self, item):\n        if isinstance(item, int):\n            # Implementing __getitem__() makes the class iterable.\n            # Need to stop iteration before C++ method throws an error.\n            if item >= self.size():\n                raise IndexError\n            return deref(self.thisptr)[<size_t>item]\n        elif isinstance(item, str):\n            return deref(self.thisptr)[<string>item]\n        else:\n            raise NotImplementedError\n    def size(self):\n        return self.thisptr.size()\n    def index(self, symbol):\n        return self.thisptr.index(symbol)\n    def symbol(self, index):\n        return self.thisptr.symbol(index)\n    def atomicNumber(self, other):\n        if type(other) is int:\n            return self.thisptr.atomicNumber(<int>other)\n        elif isinstance(other, basestring):\n            return self.thisptr.atomicNumber(<string>other)\n    def registerElements(self, elementLine):\n        return self.thisptr.registerElements(elementLine)\n    def deregisterElements(self):\n        self.thisptr.deregisterElements()\n    def symbolFromAtomicNumber(self, atomicNumber):\n        return self.thisptr.symbolFromAtomicNumber(atomicNumber)\n    def info(self):\n        return self.thisptr.info()\n"
  },
  {
    "path": "src/pynnp/Log.pyx",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\ncdef class Log:\n    cdef pd.Log* thisptr\n    cdef object owner\n\n    def __cinit__(self, empty=False):\n        if empty is True:\n            self.owner = False\n            return\n        self.thisptr = new pd.Log()\n        self.owner = True\n    cdef set_ptr(self, pd.Log* ptr, owner):\n        if self.owner is True:\n            del self.thisptr\n        self.thisptr = ptr\n        self.owner = owner\n    def __dealloc__(self):\n        if self.owner is True:\n            del self.thisptr\n    def addLogEntry(self, entry):\n        self.thisptr.addLogEntry(entry)\n    def getLog(self):\n        return self.thisptr.getLog()\n\n    # writeToStdout\n    @property\n    def writeToStdout(self):\n        return deref(self.thisptr).writeToStdout\n    @writeToStdout.setter\n    def writeToStdout(self, value):\n        deref(self.thisptr).writeToStdout = value\n"
  },
  {
    "path": "src/pynnp/Mode.pyx",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\ncdef class Mode:\n    cdef pd.Mode* thisptr\n\n    def __cinit__(self):\n        self.thisptr = new pd.Mode()\n    def __dealloc__(self):\n        del self.thisptr\n    def initialize(self):\n        self.thisptr.initialize()\n    def loadSettingsFile(self, fileName=\"input.nn\"):\n        self.thisptr.loadSettingsFile(fileName)\n    def setupGeneric(self):\n        self.thisptr.setupGeneric()\n    def setupNormalization(self):\n        self.thisptr.setupNormalization()\n    def setupElementMap(self):\n        self.thisptr.setupElementMap()\n    def setupElements(self):\n        self.thisptr.setupElements()\n    def setupCutoff(self):\n        self.thisptr.setupCutoff()\n    def setupSymmetryFunctions(self):\n        self.thisptr.setupSymmetryFunctions()\n    def setupSymmetryFunctionScalingNone(self):\n        self.thisptr.setupSymmetryFunctionScalingNone()\n    def setupSymmetryFunctionScaling(self, fileName=\"scaling.data\"):\n        self.thisptr.setupSymmetryFunctionScaling(fileName)\n    def setupSymmetryFunctionGroups(self):\n        self.thisptr.setupSymmetryFunctionGroups()\n    def setupSymmetryFunctionCache(self, verbose=False):\n        self.thisptr.setupSymmetryFunctionCache(verbose)\n    def setupSymmetryFunctionMemory(self, verbose=False):\n        self.thisptr.setupSymmetryFunctionMemory(verbose)\n    def setupSymmetryFunctionStatistics(self,\n                                        collectStatistics,\n                                        collectExtrapolationWarnings,\n                                        writeExtrapolationWarnings,\n                                        stopOnExtrapolationWarnings):\n        self.thisptr.setupSymmetryFunctionStatistics(\n                                                  collectStatistics,\n                                                  collectExtrapolationWarnings,\n                                                  writeExtrapolationWarnings,\n                                                  stopOnExtrapolationWarnings)\n    def setupNeuralNetwork(self):\n        self.thisptr.setupNeuralNetwork()\n    def setupNeuralNetworkWeights(self):\n        self.thisptr.setupNeuralNetworkWeights()\n    def calculateSymmetryFunctions(self, Structure structure, derivatives):\n        self.thisptr.calculateSymmetryFunctions(deref(structure.thisptr),\n                                                derivatives)\n    def calculateSymmetryFunctionGroups(self,\n                                        Structure structure,\n                                        derivatives):\n        self.thisptr.calculateSymmetryFunctionGroups(deref(structure.thisptr),\n                                                     derivatives)\n    def calculateAtomicNeuralNetworks(self, Structure structure, derivatives):\n        self.thisptr.calculateAtomicNeuralNetworks(deref(structure.thisptr),\n                                                   derivatives)\n    def calculateEnergy(self, Structure structure):\n        self.thisptr.calculateEnergy(deref(structure.thisptr))\n    def calculateForces(self, Structure structure):\n        self.thisptr.calculateForces(deref(structure.thisptr))\n    def addEnergyOffset(self, Structure structure, ref=True):\n        self.thisptr.addEnergyOffset(deref(structure.thisptr), ref)\n    def removeEnergyOffset(self, Structure structure, ref=True):\n        self.thisptr.removeEnergyOffset(deref(structure.thisptr), ref)\n    def getMaxCutoffRadius(self):\n        return self.thisptr.getMaxCutoffRadius()\n    def settingsKeywordExists(self, keyword):\n        return self.thisptr.settingsKeywordExists(keyword)\n    def settingsGetValue(self, keyword):\n        return self.thisptr.settingsGetValue(keyword)\n    def getMeanEnergy(self):\n        return self.thisptr.getMeanEnergy()\n    def getConvEnergy(self):\n        return self.thisptr.getConvEnergy()\n    def getConvLength(self):\n        return self.thisptr.getConvLength()\n    def getConvLength(self):\n        return self.thisptr.getConvLength()\n    def useNormalization(self):\n        return self.thisptr.useNormalization()\n\n    # log\n    property log:\n        def __get__(self):\n            r = Log()\n            thisptr = self.thisptr\n            r.set_ptr(&thisptr.log, self)\n            return r\n    # elementMap\n    property elementMap:\n        def __get__(self):\n            r = ElementMap()\n            thisptr = self.thisptr\n            r.set_ptr(&thisptr.elementMap, self)\n            return r\n"
  },
  {
    "path": "src/pynnp/Prediction.pyx",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\ncdef class Prediction(Mode):\n    cdef pd.Structure structure\n\n    def __cinit__(self):\n        if self.thisptr:\n            del self.thisptr\n        self.thisptr = new pd.Prediction()\n    def __dealloc__(self):\n        if self.thisptr:\n            del self.thisptr\n            self.thisptr = <pd.Mode*>0\n    def readStructureFromFile(self, fileName=\"input.data\"):\n        (<pd.Prediction*>self.thisptr).readStructureFromFile(fileName)\n    def setup(self):\n        (<pd.Prediction*>self.thisptr).setup()\n    def predict(self):\n        (<pd.Prediction*>self.thisptr).predict()\n\n    # fileNameSettings\n    @property\n    def fileNameSettings(self):\n        return deref(<pd.Prediction*>self.thisptr).fileNameSettings\n    @fileNameSettings.setter\n    def fileNameSettings(self, value):\n        deref(<pd.Prediction*>self.thisptr).fileNameSettings = value\n    # fileNameScaling\n    @property\n    def fileNameScaling(self):\n        return deref(<pd.Prediction*>self.thisptr).fileNameScaling\n    @fileNameScaling.setter\n    def fileNameScaling(self, value):\n        deref(<pd.Prediction*>self.thisptr).fileNameScaling = value\n    # formatWeightsFilesShort\n    @property\n    def formatWeightsFilesShort(self):\n        return deref(<pd.Prediction*>self.thisptr).formatWeightsFilesShort\n    @formatWeightsFilesShort.setter\n    def formatWeightsFilesShort(self, value):\n        deref(<pd.Prediction*>self.thisptr).formatWeightsFilesShort = value\n    # formatWeightsFilesCharge\n    @property\n    def formatWeightsFilesCharge(self):\n        return deref(<pd.Prediction*>self.thisptr).formatWeightsFilesCharge\n    @formatWeightsFilesCharge.setter\n    def formatWeightsFilesCharge(self, value):\n        deref(<pd.Prediction*>self.thisptr).formatWeightsFilesCharge = value\n    # structure\n    property structure:\n        def __get__(self):\n            r = Structure()\n            thisptr = <pd.Prediction*>self.thisptr\n            r.set_ptr(&thisptr.structure, self)\n            return r\n"
  },
  {
    "path": "src/pynnp/Settings.pyx",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\ncdef class Settings:\n    cdef pd.Settings* thisptr\n    cdef object owner\n\n    def __cinit__(self, empty=False):\n        if empty is True:\n            owner = False\n        self.thisptr = new pd.Settings()\n        owner = True\n    cdef set_ptr(self, pd.Settings* ptr, owner):\n        if self.owner is True:\n            del self.thisptr\n        self.thisptr = ptr\n        self.owner = owner\n    def __dealloc__(self):\n        if self.owner is True:\n            del self.thisptr\n    def __getitem__(self, keyword):\n        return deref(self.thisptr)[keyword]\n    def loadFile(self, fileName):\n        self.thisptr.loadFile(fileName)\n    def keywordExists(self, keyword):\n        return self.thisptr.keywordExists(keyword)\n    def getValue(self, keyword):\n        return self.thisptr.getValue(keyword)\n    def info(self):\n        return self.thisptr.info()\n    def getSettingsLines(self):\n        return self.thisptr.getSettingsLines()\n"
  },
  {
    "path": "src/pynnp/Structure.pyx",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\ncdef class Structure:\n    cdef pd.Structure* thisptr\n    cdef pd.Vec3D box\n    cdef pd.Vec3D invbox\n    cdef object owner\n    ST_UNKNOWN    = pd.ST_UNKNOWN\n    ST_TRAINING   = pd.ST_TRAINING\n    ST_VALIDATION = pd.ST_VALIDATION\n    ST_TEST       = pd.ST_TEST\n\n    def __cinit__(self, empty=False):\n        if empty is True:\n            self.owner = False\n            return\n        self.thisptr = new pd.Structure()\n        self.owner = True\n    cdef set_ptr(self, pd.Structure* ptr, owner):\n        if self.owner is True:\n            del self.thisptr\n        self.thisptr = ptr\n        self.owner = owner\n    def __dealloc__(self):\n        if self.owner is True:\n            del self.thisptr\n    def setElementMap(self, ElementMap elementMap):\n        self.thisptr.setElementMap(deref(elementMap.thisptr))\n    def addAtom(self, Atom atom, element):\n        if isinstance(element, str):\n            self.thisptr.addAtom(deref(atom.thisptr), element)\n        else:\n            raise NotImplementedError(\"ERROR: Element must be string.\")\n    def readFromFile(self, fileName=\"input.data\"):\n        self.thisptr.readFromFile(fileName)\n    def readFromLines(self, lines):\n        self.thisptr.readFromLines(lines)\n    def calculateNeighborList(self, cutoffRadius):\n        self.thisptr.calculateNeighborList(cutoffRadius)\n    def remap(self):\n        self.thisptr.remap()\n    def toNormalizedUnits(self, meanEnergy, convEnergy, convLength, convCharge):\n        self.thisptr.toNormalizedUnits(meanEnergy, convEnergy, convLength, convCharge)\n    def toPhysicalUnits(self, meanEnergy, convEnergy, convLength, convCharge):\n        self.thisptr.toPhysicalUnits(meanEnergy, convEnergy, convLength, convCharge)\n    def getMaxNumNeighbors(self):\n        return self.thisptr.getMaxNumNeighbors()\n    def reset(self):\n        self.thisptr.reset()\n    def clearNeighborList(self):\n        self.thisptr.clearNeighborList()\n    def writeToFile(self, fileName=\"output.data\", ref=True, append=False):\n        self.thisptr.writeToFile(fileName, ref, append)\n    def info(self):\n        return self.thisptr.info()\n\n    # elementMap\n    property elementMap:\n        def __get__(self):\n            r = ElementMap()\n            thisptr = self.thisptr\n            r.set_ptr(&thisptr.elementMap, self)\n            return r\n    # isPeriodic\n    @property\n    def isPeriodic(self):\n        return deref(self.thisptr).isPeriodic\n    @isPeriodic.setter\n    def isPeriodic(self, value):\n        deref(self.thisptr).isPeriodic = value\n    # isTriclinic\n    @property\n    def isTriclinic(self):\n        return deref(self.thisptr).isTriclinic\n    @isTriclinic.setter\n    def isTriclinic(self, value):\n        deref(self.thisptr).isTriclinic = value\n    # hasNeighborList\n    @property\n    def hasNeighborList(self):\n        return deref(self.thisptr).hasNeighborList\n    @hasNeighborList.setter\n    def hasNeighborList(self, value):\n        deref(self.thisptr).hasNeighborList = value\n    # hasSymmetryFunctions\n    @property\n    def hasSymmetryFunctions(self):\n        return deref(self.thisptr).hasSymmetryFunctions\n    @hasSymmetryFunctions.setter\n    def hasSymmetryFunctions(self, value):\n        deref(self.thisptr).hasSymmetryFunctions = value\n    # hasSymmetryFunctionDerivatives\n    @property\n    def hasSymmetryFunctionDerivatives(self):\n        return deref(self.thisptr).hasSymmetryFunctionDerivatives\n    @hasSymmetryFunctionDerivatives.setter\n    def hasSymmetryFunctionDerivatives(self, value):\n        deref(self.thisptr).hasSymmetryFunctionDerivatives = value\n    # index\n    @property\n    def index(self):\n        return deref(self.thisptr).index\n    @index.setter\n    def index(self, value):\n        deref(self.thisptr).index = value\n    # numAtoms\n    @property\n    def numAtoms(self):\n        return deref(self.thisptr).numAtoms\n    @numAtoms.setter\n    def numAtoms(self, value):\n        deref(self.thisptr).numAtoms = value\n    # numElements\n    @property\n    def numElements(self):\n        return deref(self.thisptr).numElements\n    @numElements.setter\n    def numElements(self, value):\n        deref(self.thisptr).numElements = value\n    # numElementsPresent\n    @property\n    def numElementsPresent(self):\n        return deref(self.thisptr).numElementsPresent\n    @numElementsPresent.setter\n    def numElementsPresent(self, value):\n        deref(self.thisptr).numElementsPresent = value\n    # pbc\n    @property\n    def pbc(self):\n        return deref(self.thisptr).pbc\n    @pbc.setter\n    def pbc(self, value):\n        deref(self.thisptr).pbc = value\n    # energy\n    @property\n    def energy(self):\n        return deref(self.thisptr).energy\n    @energy.setter\n    def energy(self, value):\n        deref(self.thisptr).energy = value\n    # energyRef\n    @property\n    def energyRef(self):\n        return deref(self.thisptr).energyRef\n    @energyRef.setter\n    def energyRef(self, value):\n        deref(self.thisptr).energyRef = value\n    # chargeRef\n    @property\n    def chargeRef(self):\n        return deref(self.thisptr).chargeRef\n    @chargeRef.setter\n    def chargeRef(self, value):\n        deref(self.thisptr).chargeRef = value\n    # volume\n    @property\n    def volume(self):\n        return deref(self.thisptr).volume\n    @volume.setter\n    def volume(self, value):\n        deref(self.thisptr).volume = value\n    # sampleType\n    @property\n    def sampleType(self):\n        return deref(self.thisptr).sampleType\n    @sampleType.setter\n    def sampleType(self, value):\n        deref(self.thisptr).sampleType = value\n    # comment\n    @property\n    def comment(self):\n        return deref(self.thisptr).comment\n    @comment.setter\n    def comment(self, value):\n        deref(self.thisptr).comment = value\n    # box\n    property box:\n        def __get__(self):\n            r = []\n            thisptr = self.thisptr\n            for i in range(3):\n                e = Vec3D()\n                e.set_ptr(&thisptr.box[i], self)\n                r = r + [e]\n            return r\n    # invbox\n    property invbox:\n        def __get__(self):\n            r = []\n            thisptr = self.thisptr\n            for i in range(3):\n                e = Vec3D()\n                e.set_ptr(&thisptr.invbox[i], self)\n                r = r + [e]\n            return r\n    # numAtomsPerElement\n    @property\n    def numAtomsPerElement(self):\n        return deref(self.thisptr).numAtomsPerElement\n    @numAtomsPerElement.setter\n    def numAtomsPerElement(self, value):\n        deref(self.thisptr).numAtomsPerElement = value\n    # atoms\n    property atoms:\n        def __get__(self):\n            r = []\n            thisptr = self.thisptr\n            for i in range(thisptr.atoms.size()):\n                e = Atom()\n                e.set_ptr(&thisptr.atoms[i], self)\n                r = r + [e]\n            return r\n"
  },
  {
    "path": "src/pynnp/Vec3D.pyx",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\ncdef class Vec3D:\n    cdef pd.Vec3D* thisptr\n    cdef object owner\n\n    def __cinit__(self, x=None, y=None, z=None):\n        cdef Vec3D v = <Vec3D>x\n        if x is True:\n            self.owner = False\n            return\n        elif x is not None and isinstance(x, Vec3D):\n            self.thisptr = new pd.Vec3D(deref(v.thisptr))\n        elif x is not None and y is not None and z is not None:\n            self.thisptr = new pd.Vec3D(x, y, z)\n        elif x is not None or y is not None or z is not None:\n            raise ValueError(\"ERROR: Wrong arguments, either set all \"\n                             \"components or none.\")\n        else:\n            self.thisptr = new pd.Vec3D()\n        self.owner = True\n    cdef set_ptr(self, pd.Vec3D* ptr, owner):\n        if self.owner is True:\n            del self.thisptr\n        self.thisptr = ptr\n        self.owner = owner\n    def __dealloc__(self):\n        if self.owner is True:\n            del self.thisptr\n    def __getitem__(self, item):\n        if item >= 3 or item < 0:\n            raise IndexError\n        return deref(self.thisptr).r[<size_t>item]\n    def __setitem__(self, item, value):\n        if item >= 3 or item < 0:\n            raise IndexError\n        deref(self.thisptr).r[<size_t>item] = value\n    def __str__(self):\n        return \"x: {0:f} y: {1:f} z: {2:f}\".format(*(deref(self.thisptr).r))\n    def __iadd__(self, Vec3D v):\n        self.thisptr.iadd(deref(v.thisptr))\n        return self\n    def __isub__(self, Vec3D v):\n        self.thisptr.isub(deref(v.thisptr))\n        return self\n    def __imul__(self, a):\n        self.thisptr.imul(a)\n        return self\n    def __itruediv__(self, a):\n        self.thisptr.itruediv(a)\n        return self\n    def __mul__(ls, rs):\n        if isinstance(ls, Vec3D) and isinstance(rs, Vec3D):\n            return ls.mul_Vec3D(rs)\n        elif isinstance(ls, Vec3D) and isinstance(rs, float):\n            return ls.mul_rfloat(rs)\n        else:\n            return NotImplemented\n    def __rmul__(rs, ls):\n        if isinstance(ls, float) and isinstance(rs, Vec3D):\n            return rs.mul_lfloat(ls)\n        else:\n            return NotImplemented\n    def mul_Vec3D(Vec3D self, Vec3D v):\n        return self.thisptr.mul_vec3d(deref(v.thisptr))\n    def mul_rfloat(Vec3D self, a):\n        cdef Vec3D res = Vec3D()\n        res.thisptr[0] = pd.mul_d(deref(self.thisptr), a)\n        return res\n    def mul_lfloat(Vec3D self, a):\n        cdef Vec3D res = Vec3D()\n        res.thisptr[0] = pd.d_mul(a, deref(self.thisptr))\n        return res\n    def __eq__(self, Vec3D rhs):\n        return self.thisptr.eq(deref(rhs.thisptr))\n    def __ne__(self, Vec3D rhs):\n        return self.thisptr.ne(deref(rhs.thisptr))\n    def norm(self):\n        return self.thisptr.norm()\n    def norm2(self):\n        return self.thisptr.norm2()\n    def normalize(self):\n        self.thisptr.normalize()\n        return self\n    def cross(self, Vec3D v):\n        cdef Vec3D res = Vec3D()\n        res.thisptr[0] = self.thisptr.cross(deref(v.thisptr))\n        return res\n    def __add__(Vec3D self, Vec3D rhs):\n        cdef Vec3D res = Vec3D()\n        res.thisptr[0] = pd.add(deref(self.thisptr), deref(rhs.thisptr))\n        return res\n    def __sub__(Vec3D self, Vec3D rhs):\n        cdef Vec3D res = Vec3D()\n        res.thisptr[0] = pd.sub(deref(self.thisptr), deref(rhs.thisptr))\n        return res\n    def __neg__(Vec3D self):\n        cdef Vec3D res = Vec3D()\n        res.thisptr[0] = pd.neg(deref(self.thisptr))\n        return res\n    def __truediv__(self, a):\n        if isinstance(a, float):\n            return self.div_float(a)\n        else:\n            return NotImplemented\n    def div_float(Vec3D self, a):\n        cdef Vec3D res = Vec3D()\n        res.thisptr[0] = pd.div_d(deref(self.thisptr), a)\n        return res\n\n    # r\n    @property\n    def r(self):\n        return deref(self.thisptr).r\n    @r.setter\n    def r(self, value):\n        deref(self.thisptr).r = value\n"
  },
  {
    "path": "src/pynnp/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=../..\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# GENERAL SETTINGS\n###############################################################################\n# Default compiler, may be overridden by master makefile or command line.\nCOMP=gnu\n\n# Default build mode, may be overridden command line.\n# Possible modes are \"shared\" and \"test\".\nMODE=shared\n# Override \"static\" mode from main makefile.\nifeq ($(MODE), static)\noverride MODE=shared\nendif\n\n# Include global (project-wide) settings.\ninclude $(PROJECT_DIR)/src/makefile.$(COMP)\n\n###############################################################################\n# RULES\n###############################################################################\n.PHONY: all setup-py clean-setup-py clean\n\nifeq ($(MODE), shared)\nall: setup-py\n\tpython3 setup.py build_ext --inplace\n\tcp pynnp*.so $(PROJECT_LIB)\nelse\nall: setup-py\n\tpython3 setup-test.py build_ext --inplace --define CYTHON_TRACE\n\tcp pynnp*.so $(PROJECT_LIB)\nendif\n\nsetup-py:\n\t@sed -i.bak -E \"s,(includes =).*,\\1 [\\\"$(PROJECT_EIGEN)\\\"],\" setup.py\n\t@rm setup.py.bak\n\t@sed -i.bak -E \"s,(includes =).*,\\1 [\\\"$(PROJECT_EIGEN)\\\"],\" setup-test.py\n\t@rm setup-test.py.bak\n\nclean: clean-setup-py\n\t$(RM) pynnp.cpp pynnp*.so\n\t$(RM) -r build\n\t$(RM) $(PROJECT_LIB)/pynnp*.so\n\t$(RM) ./*.html\n\nclean-setup-py:\n\t@sed -i.bak -E \"s,(includes =).*,\\1 [],\" setup.py\n\t@rm setup.py.bak\n\t@sed -i.bak -E \"s,(includes =).*,\\1 [],\" setup-test.py\n\t@rm setup-test.py.bak\n"
  },
  {
    "path": "src/pynnp/pynnp.pyx",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\nfrom cython.operator cimport dereference as deref\nfrom libcpp.string cimport string\ncimport pynnp_dec as pd\n# Nested subclasses require this construction:\nfrom pynnp_dec cimport Atom as pd_Atom\n\ninclude \"CutoffFunction.pyx\"\ninclude \"ElementMap.pyx\"\ninclude \"Log.pyx\"\ninclude \"Settings.pyx\"\ninclude \"Vec3D.pyx\"\ninclude \"Atom.pyx\"\ninclude \"Structure.pyx\"\ninclude \"Mode.pyx\"\ninclude \"Prediction.pyx\"\n\n###############################################################################\n# DatasetReader\n###############################################################################\nclass DatasetReader:\n    def __init__(self, file_name, elements):\n        self.file_name = file_name\n        self._element_map = ElementMap()\n        self._element_map.registerElements(elements)\n        self._f = open(self.file_name, \"r\")\n\n    def __iter__(self):\n        if(self._f.closed):\n            self._f = open(self.file_name, \"r\")\n        return self\n\n    def __next__(self):\n        line = self._f.readline()\n        if len(line) < 1:\n            self._f.close()\n            raise StopIteration\n        lines = [line.rstrip(\"\\r\\n\")]\n        for line in self._f:\n            lines.append(line.rstrip(\"\\r\\n\"))\n            if line.split()[0] == \"end\":\n                break\n        s = Structure()\n        s.setElementMap(self._element_map)\n        s.readFromLines(lines)\n        return s\n"
  },
  {
    "path": "src/pynnp/pynnp_dec.pxd",
    "content": "# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\nfrom libcpp.string cimport string\nfrom libcpp.vector cimport vector\nfrom libcpp cimport bool\nfrom libc.stdint cimport int64_t\n\n###############################################################################\n# CutoffFunction\n###############################################################################\ncdef extern from \"CutoffFunction.h\" namespace \"nnp::CutoffFunction\":\n    cdef enum CutoffType:\n        CT_HARD,\n        CT_COS,\n        CT_TANHU,\n        CT_TANH,\n        CT_EXP,\n        CT_POLY1,\n        CT_POLY2,\n        CT_POLY3,\n        CT_POLY4\n\ncdef extern from \"CutoffFunction.h\" namespace \"nnp\":\n    cdef cppclass CutoffFunction:\n        CutoffFunction() except +\n        void   setCutoffType(const CutoffType cutoffType) except +\n        void   setCutoffRadius(const double cutoffRadius) except +\n        void   setCutoffParameter(const double alpha) except +\n        double f(double r) except +\n        double df(double r) except +\n        void   fdf(double r, double& fc, double& dfc) except +\n\n###############################################################################\n# ElementMap\n###############################################################################\ncdef extern from \"ElementMap.h\" namespace \"nnp\":\n    cdef cppclass ElementMap:\n        string         operator[](size_t index) except +\n        size_t         operator[](string symbol) except +\n        size_t         size() except +\n        size_t         index(string symbol) except +\n        string         symbol(size_t index) except +\n        size_t         atomicNumber(size_t index) except +\n        size_t         registerElements(string elementLine) except +\n        void           deregisterElements() except +\n        string         symbolFromAtomicNumber(size_t atomicNumber) except +\n        size_t         atomicNumber(string symbol) except +\n        vector[string] info() except +\n\n###############################################################################\n# Log\n###############################################################################\ncdef extern from \"Log.h\" namespace \"nnp\":\n    cdef cppclass Log:\n        bool writeToStdout\n        Log() except +\n        #Log&                     operator<<(std::string const& entry);\n        #Log&                     operator<<(\n        #                                  std::vector<std::string> const& entries);\n        void           addLogEntry(const string& entry) except +\n        #void                     addMultipleLogEntries(\n        #                                  std::vector<std::string> const& entries);\n        #void                     registerCFilePointer(FILE** const& filePointer);\n        #void                     registerStreamPointer(\n        #                                      std::ofstream* const& streamPointer);\n        vector[string] getLog() except +\n\n###############################################################################\n# Settings\n###############################################################################\ncdef extern from \"Settings.h\" namespace \"nnp::settings\":\n    #typedef std::multimap<std::string,\n    #                      std::pair<std::string, std::size_t> > KeyMap;\n    #typedef std::pair<KeyMap::const_iterator,\n    #                  KeyMap::const_iterator>                   KeyRange;\n    cdef cppclass Settings:\n        string         operator[](const string& keyword) except +\n        void           loadFile(const string& fileName) except +\n        bool           keywordExists(const string& keyword) except +\n        string         getValue(const string& keyword) except +\n        #KeyRange                 getValues(std::string const& keyword) const;\n        vector[string] info() except +\n        vector[string] getSettingsLines() except +\n        #void                     writeSettingsFile(\n        #                                         std::ofstream* const& file) const;\n\n###############################################################################\n# Vec3D\n###############################################################################\ncdef extern from \"Vec3D.h\" namespace \"nnp\":\n    cdef cppclass Vec3D:\n        double r[3]\n        Vec3D() except +\n        Vec3D(double x, double y, double z) except +\n        Vec3D(const Vec3D& source) except +\n        #Vec3D operator=(Vec3D rhs) except +\n        Vec3D& iadd      \"operator+=\"(const Vec3D& v) except +\n        Vec3D& isub      \"operator-=\"(const Vec3D& v) except +\n        Vec3D& imul      \"operator*=\"(const double a) except +\n        Vec3D& itruediv  \"operator/=\"(const double a) except +\n        double mul_vec3d \"operator*\"(const Vec3D& v) except +\n        #double&       operator[](std::size_t const index);\n        #double const& operator[](std::size_t const index) const;\n        bool   eq        \"operator==\"(const Vec3D& rhs) except +\n        bool   ne        \"operator!=\"(const Vec3D& rhs) except +\n        double norm() except +\n        double norm2() except +\n        Vec3D& normalize() except +\n        Vec3D  cross(const Vec3D& v) except +\n\n    Vec3D add   \"operator+\"(Vec3D lhs, const Vec3D& rhs) except +\n    Vec3D sub   \"operator-\"(Vec3D lhs, const Vec3D& rhs) except +\n    Vec3D neg   \"operator-\"(Vec3D v) except +\n    Vec3D mul_d \"operator*\"(Vec3D v, const double a) except +\n    Vec3D div_d \"operator/\"(Vec3D v, const double a) except +\n    Vec3D d_mul \"operator*\"(const double a, Vec3D v) except +\n\n###############################################################################\n# Atom\n###############################################################################\ncdef extern from \"Atom.h\" namespace \"nnp\":\n    cdef cppclass Atom:\n        cppclass Neighbor:\n            size_t         index\n            int64_t        tag\n            size_t         element\n            double         d\n            Vec3D          dr\n            vector[double] cache\n            vector[Vec3D]  dGdr\n            Neighbor() except +\n            bool eq \"operator==\"(const Neighbor& rhs) except +\n            bool ne \"operator!=\"(const Neighbor& rhs) except +\n            bool lt \"operator<\" (const Neighbor& rhs) except +\n            bool gt \"operator>\" (const Neighbor& rhs) except +\n            bool le \"operator<=\"(const Neighbor& rhs) except +\n            bool ge \"operator>=\"(const Neighbor& rhs) except +\n        bool             hasNeighborList\n        bool             hasSymmetryFunctions\n        bool             hasSymmetryFunctionDerivatives\n        bool             useChargeNeuron\n        size_t           index\n        size_t           indexStructure\n        int64_t          tag\n        size_t           element\n        size_t           numNeighbors\n        size_t           numNeighborsUnique\n        size_t           numSymmetryFunctions\n        double           energy\n        double           charge\n        double           chargeRef\n        Vec3D            r\n        Vec3D            f\n        Vec3D            fRef\n        vector[size_t]   neighborsUnique\n        vector[size_t]   numNeighborsPerElement\n        vector[size_t]   numSymmetryFunctionDerivatives;\n        vector[size_t]   cacheSizePerElement;\n        vector[double]   G\n        vector[double]   dEdG\n        vector[double]   dQdG\n        #vector[double]   dGdxia\n        vector[Vec3D]    dGdr\n        vector[Neighbor] neighbors\n        Atom() except +\n        vector[string] info() except +\n\n###############################################################################\n# Structure\n###############################################################################\ncdef extern from \"Structure.h\" namespace \"nnp::Structure\":\n    cdef enum SampleType:\n        ST_UNKNOWN,\n        ST_TRAINING,\n        ST_VALIDATION,\n        ST_TEST\n\ncdef extern from \"Structure.h\" namespace \"nnp\":\n    cdef cppclass Structure:\n        ElementMap     elementMap\n        bool           isPeriodic;\n        bool           isTriclinic;\n        bool           hasNeighborList;\n        bool           hasSymmetryFunctions;\n        bool           hasSymmetryFunctionDerivatives;\n        size_t         index;\n        size_t         numAtoms;\n        size_t         numElements;\n        size_t         numElementsPresent;\n        int            pbc[3];\n        double         energy;\n        double         energyRef;\n        double         chargeRef;\n        double         volume;\n        SampleType     sampleType;\n        string         comment;\n        Vec3D          box[3];\n        Vec3D          invbox[3];\n        vector[size_t] numAtomsPerElement;\n        vector[Atom]   atoms;\n        Structure() except +\n        void           setElementMap(ElementMap elementMap) except +\n        void           addAtom(Atom atom, string element) except +\n        void           readFromFile(string fileName) except +\n        #void                     readFromFile(std::ifstream& file);\n        void           readFromLines(vector[string] lines) except +\n        void           calculateNeighborList(double cutoffRadius) except +\n        #void                     calculatePbcCopies(double cutoffRadius);\n        #void                     calculateInverseBox();\n        #void                     calculateVolume();\n        void           remap() except +\n        #void                     remap(Atom& atom);\n        void           toNormalizedUnits(double meanEnergy,\n                                         double convEnergy,\n                                         double convLength,\n                                         double convCharge) except +\n        void           toPhysicalUnits(double meanEnergy,\n                                       double convEnergy,\n                                       double convLength,\n                                       double convCharge) except +\n        size_t         getMaxNumNeighbors() except +\n        #void                     freeAtoms(bool all);\n        void           reset() except +\n        void           clearNeighborList() except +\n        #void                     updateRmseEnergy(double&      rmse,\n        #                                          std::size_t& count) const;\n        #void                     updateRmseForces(double&      rmse,\n        #                                          std::size_t& count) const;\n        #std::string              getEnergyLine() const;\n        #std::vector<std::string> getForcesLines() const;\n        void           writeToFile(string fileName,\n                                   bool ref,\n                                   bool append) except +\n        void           writeToFile(string fileName, bool ref) except +\n        void           writeToFile(string fileName) except +\n        void           writeToFile() except +\n        #void                     writeToFile(\n        #                                   std::ofstream* const& file,\n        #                                   bool                  ref = true) const;\n        #void                     writeToFileXyz(std::ofstream* const& file) const;\n        #void                     writeToFilePoscar(\n        #                                         std::ofstream* const& file) const;\n        vector[string] info() except +\n\n###############################################################################\n# Mode\n###############################################################################\ncdef extern from \"Mode.h\" namespace \"nnp\":\n    cdef cppclass Mode:\n        ElementMap elementMap\n        Log        log\n        Mode() except +\n        void           initialize() except +\n        void           loadSettingsFile(string fileName) except +\n        void           setupGeneric() except +\n        void           setupNormalization() except +\n        void           setupElementMap() except +\n        void           setupElements() except +\n        void           setupCutoff() except +\n        void           setupSymmetryFunctions() except +\n        void           setupSymmetryFunctionScalingNone() except +\n        void           setupSymmetryFunctionScaling(string fileName) except +\n        void           setupSymmetryFunctionGroups() except +\n        void           setupSymmetryFunctionCache(bool verbose) except +\n        void           setupSymmetryFunctionMemory(bool verbose) except +\n        void           setupSymmetryFunctionStatistics(\n                                     bool collectStatistics,\n                                     bool collectExtrapolationWarnings,\n                                     bool writeExtrapolationWarnings,\n                                     bool stopOnExtrapolationWarnings) except +\n        void           setupNeuralNetwork()\n        void           setupNeuralNetworkWeights() except +\n        void           calculateSymmetryFunctions(\n                                                Structure structure,\n                                                bool      derivatives) except +\n        void           calculateSymmetryFunctionGroups(\n                                                Structure structure,\n                                                bool      derivatives) except +\n        void           calculateAtomicNeuralNetworks(\n                                                Structure structure,\n                                                bool      derivatives) except +\n        void           calculateEnergy(Structure structure) except +\n        void           calculateForces(Structure structure) except +\n        void           addEnergyOffset(Structure structure, bool ref) except +\n        void           removeEnergyOffset(Structure structure,\n                                          bool      ref) except +\n        #double                   getEnergyOffset(Structure const& structure) const;\n        #double                   getEnergyWithOffset(\n        #                                        Structure const& structure,\n        #                                        bool             ref = true) const;\n        #double                   normalizedEnergy(double energy) const;\n        #double                   normalizedEnergy(Structure const& structure,\n        #                                          bool             ref) const;\n        #double                   normalizedForce(double force) const;\n        #double                   physicalEnergy(double energy) const;\n        #double                   physicalEnergy(Structure const& structure,\n        #                                        bool             ref) const;\n        #double                   physicalForce(double force) const;\n        #void                     convertToNormalizedUnits(\n        #                                               Structure& structure) const;\n        #void                     convertToPhysicalUnits(\n        #                                               Structure& structure) const;\n        #std::size_t              getNumExtrapolationWarnings() const;\n        #void                     resetExtrapolationWarnings();\n        double         getMeanEnergy() except +\n        double         getConvEnergy() except +\n        double         getConvLength() except +\n        double         getMaxCutoffRadius() except +\n        #std::size_t              getNumElements() const;\n        #std::vector<std::size_t> getNumSymmetryFunctions() const;\n        bool           useNormalization() except +\n        bool           settingsKeywordExists(string keyword) except +\n        string         settingsGetValue(string keyword) except +\n        #std::vector<std::size_t> pruneSymmetryFunctionsRange(double threshold);\n        #std::vector<std::size_t> pruneSymmetryFunctionsSensitivity(\n        #                                        double threshold,\n        #                                        std::vector<\n        #                                        std::vector<double> > sensitivity);\n        #void                     writePrunedSettingsFile(\n        #                                          std::vector<std::size_t> prune,\n        #                                          std::string              fileName\n        #                                                      = \"output.nn\") const;\n        #void                     writeSettingsFile(\n        #                                 std::ofstream* const& file) const;\n        \n###############################################################################\n# Prediction\n###############################################################################\ncdef extern from \"Prediction.h\" namespace \"nnp\":\n    cdef cppclass Prediction(Mode):\n        string    fileNameSettings\n        string    fileNameScaling\n        string    formatWeightsFilesShort\n        string    formatWeightsFilesCharge\n        Structure structure\n        Prediction() except +\n        void readStructureFromFile(string fileName) except +\n        void setup() except +\n        void predict() except +\n"
  },
  {
    "path": "src/pynnp/setup-test.py",
    "content": "from distutils.core import setup\nfrom distutils.extension import Extension\nfrom Cython.Build import cythonize\nimport glob\n\nsources_dir = \"../libnnp/\"\nincludes = []\nsources = [\"pynnp.pyx\"]\nsources += glob.glob(sources_dir + \"*.cpp\")\ncompile_options = [\"-std=c++11\"] #, \"-fopenmp\"]\nlink_options = [] #\"-fopenmp\"]\n\nextension = [Extension(\"*\",\n                       sources,\n                       extra_compile_args=compile_options,\n                       extra_link_args=link_options,\n                       include_dirs=[sources_dir]+includes,\n                       language=\"c++\")]\n\nsetup(\n    ext_modules=cythonize(extension,\n                          annotate=True,\n                          compiler_directives={'language_level' : \"3\",\n                                               'c_string_type' : 'unicode',\n                                               'c_string_encoding' : 'utf8',\n                                               'linetrace' : True})\n)\n"
  },
  {
    "path": "src/pynnp/setup.py",
    "content": "from setuptools import setup, Extension\nfrom Cython.Build import cythonize\nimport glob\n\nsources_dir = \"../libnnp/\"\nincludes = []\nsources = [\"pynnp.pyx\"]\nsources += glob.glob(sources_dir + \"*.cpp\")\ncompile_options = [\"-std=c++11\"] #, \"-fopenmp\"]\nlink_options = [] #\"-fopenmp\"]\n\nextension = [Extension(\"*\",\n                       sources,\n                       extra_compile_args=compile_options,\n                       extra_link_args=link_options,\n                       include_dirs=[sources_dir]+includes,\n                       language=\"c++\")]\n\nsetup(\n    ext_modules=cythonize(extension,\n                          compiler_directives={'language_level' : \"3\",\n                                               'c_string_type' : 'unicode',\n                                               'c_string_encoding' : 'utf8'})\n)\n"
  },
  {
    "path": "test/cpp/BoostDataContainer.h",
    "content": "#ifndef BOOSTDATACONTAINER_H\n#define BOOSTDATACONTAINER_H\n\n#include <vector> // std::vector\n\ntemplate <class T> struct BoostDataContainer\n{\n    BoostDataContainer()\n    {\n        setup();\n    }\n\n    void setup()\n    {\n        return;\n    }\n\n    std::vector<T> examples;\n};\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example.h",
    "content": "#ifndef EXAMPLE_H\n#define EXAMPLE_H\n\n#include <ostream> // std::ostream\n#include <string>  // std::string\n\nstruct Example\n{\n    std::string name;\n    std::string description;\n};\n\nstd::ostream& operator<<(std::ostream& os, Example const& example)\n{\n    os << \"Example name       : \\\"\" << example.name << \"\\\"\\n\";\n    os << \"Example description: \\\"\" << example.description << \"\\\"\\n\";\n\n    return os;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/ExamplePrediction.h",
    "content": "#ifndef EXAMPLEPREDICTION_H\n#define EXAMPLEPREDICTION_H\n\n#include <vector>\n#include \"Example.h\"\n#include \"BoostDataContainer.h\"\n#include \"Vec3D.h\"\n\nstruct ExamplePrediction : public Example\n{\n    std::string pathData;\n\n    double                  energy;\n    std::vector<nnp::Vec3D> forces;\n\n    ExamplePrediction();\n\n    ExamplePrediction(std::string name) : \n        pathData(\"../../examples/nnp-predict\")\n    {\n        this->name = name;\n        this->description = std::string(\"Prediction example \\\"\")\n                          + this->name\n                          + \"\\\"\";\n        this->pathData += \"/\" + this->name;\n    }\n};\n\ntemplate<>\nvoid BoostDataContainer<ExamplePrediction>::setup()\n{\n    ExamplePrediction* e = nullptr;\n\n    examples.push_back(ExamplePrediction(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->energy = -2.7564547347815904E+04;\n    e->forces.push_back(nnp::Vec3D( -2.8966030062366754E-02,   2.7209599774412423E-03,   3.9737021445979048E-03));\n    e->forces.push_back(nnp::Vec3D(  7.9877423752479741E-03,   3.3297604748884998E-03,  -1.0163833042173850E-02));\n    e->forces.push_back(nnp::Vec3D(  1.1806902826331738E-02,  -9.4962509650420874E-03,   6.6334365831265344E-03));\n    e->forces.push_back(nnp::Vec3D(  1.5811460277845243E-03,   1.5010841412183408E-03,  -1.9125345585991289E-02));\n    e->forces.push_back(nnp::Vec3D( -5.5904666061025688E-03,   8.9440761861618728E-03,  -2.2307010253202861E-03));\n    e->forces.push_back(nnp::Vec3D(  3.0173737498853648E-04,  -1.0125957462634337E-02,   1.3857355934526888E-02));\n    e->forces.push_back(nnp::Vec3D( -7.8096712558967877E-04,  -1.6708813976931509E-03,  -4.6967806593604996E-03));\n    e->forces.push_back(nnp::Vec3D(  2.2427460962975566E-03,  -5.0824240654465643E-03,   2.8314700994836470E-03));\n    e->forces.push_back(nnp::Vec3D(  1.4370209345337737E-03,   6.0023390484798614E-03,   6.1252679756137313E-04));\n    e->forces.push_back(nnp::Vec3D( -2.3470427905371407E-03,  -3.6377522521246264E-02,  -2.5116071793401799E-02));\n    e->forces.push_back(nnp::Vec3D( -5.4041601211747463E-03,   2.6031776120279834E-02,   1.3699383192364398E-02));\n    e->forces.push_back(nnp::Vec3D(  2.2318059210811127E-02,   1.1576413172309447E-02,   1.1881649814830980E-02));\n    e->forces.push_back(nnp::Vec3D( -3.7211047627944138E-03,  -3.0535038018364696E-02,  -6.9418304222511381E-03));\n    e->forces.push_back(nnp::Vec3D( -1.3953553121442766E-03,   3.0014416067258683E-02,   2.7480041531564594E-03));\n    e->forces.push_back(nnp::Vec3D( -1.0411398826098380E-03,   2.7882151104234788E-04,   4.4191031441445693E-03));\n    e->forces.push_back(nnp::Vec3D( -3.3665987871872539E-03,  -6.8577288740309704E-03,  -2.8876784186482082E-02));\n    e->forces.push_back(nnp::Vec3D( -3.9991664005394507E-03,   2.4098585882656939E-03,   1.9900867578244705E-02));\n    e->forces.push_back(nnp::Vec3D(  9.5984017107607154E-03,   3.9723373179982435E-03,   1.6757485584924729E-02));\n    e->forces.push_back(nnp::Vec3D(  3.2219750123846966E-02,  -2.5232964368515010E-02,   1.1869876000272327E-02));\n    e->forces.push_back(nnp::Vec3D( -3.2139503170264018E-02,   1.5163248721495982E-02,  -5.8178449476993487E-03));\n    e->forces.push_back(nnp::Vec3D(  2.4854739876094311E-03,   1.2171976609879748E-02,  -1.3594761635027736E-02));\n    e->forces.push_back(nnp::Vec3D( -2.4366984114817341E-02,   4.0565735907979964E-03,  -1.8630608770253708E-02));\n    e->forces.push_back(nnp::Vec3D(  3.2145429403138272E-03,  -4.6021390788914453E-03,   1.6444433411725641E-02));\n    e->forces.push_back(nnp::Vec3D(  1.7672749227715126E-02,  -5.4774642137957862E-03,   6.2134679695512538E-03));\n    e->forces.push_back(nnp::Vec3D( -8.5670070269519803E-03,  -1.6322015049421015E-02,   1.5305810533427144E-02));\n    e->forces.push_back(nnp::Vec3D(  1.5623918606992360E-02,   1.2907452028740343E-02,  -8.9209921928810401E-03));\n    e->forces.push_back(nnp::Vec3D(  2.5244839795231819E-03,   2.4442415972083594E-03,  -1.0719182793553324E-02));\n    e->forces.push_back(nnp::Vec3D( -2.2891817600688102E-02,   2.5787240147435258E-02,   3.8524086274509504E-02));\n    e->forces.push_back(nnp::Vec3D(  1.9217837385631605E-02,   3.2269207224853561E-03,  -2.2793479210423406E-02));\n    e->forces.push_back(nnp::Vec3D( -1.1030583846457984E-03,  -3.1710952401599594E-02,  -1.1400678629961180E-02));\n    e->forces.push_back(nnp::Vec3D( -1.9716380198621618E-02,  -2.8374406181889433E-03,   1.1055440948111410E-02));\n    e->forces.push_back(nnp::Vec3D( -5.6175370688723606E-03,   4.3597476714221763E-03,   9.1269257814505008E-03));\n    e->forces.push_back(nnp::Vec3D(  2.3360267204542068E-02,  -3.0934051191527784E-03,  -1.8122620227859890E-02));\n    e->forces.push_back(nnp::Vec3D(  1.2679921090770185E-02,   1.5581390888057332E-03,  -2.7633020507912508E-02));\n    e->forces.push_back(nnp::Vec3D( -6.2061581015624189E-03,  -8.0051696813360895E-03,  -9.6006017186329694E-03));\n    e->forces.push_back(nnp::Vec3D( -6.5091617379989348E-03,   4.6328213267968158E-03,   3.6544684670864865E-02));\n    e->forces.push_back(nnp::Vec3D( -3.4555309289341350E-03,  -1.6583912379098047E-02,   2.4679525126150455E-02));\n    e->forces.push_back(nnp::Vec3D( -1.7677000842540444E-03,  -6.1042096360707551E-04,  -5.6590389500863238E-03));\n    e->forces.push_back(nnp::Vec3D(  6.0034635891685270E-03,   1.9380785153974397E-02,  -1.1277765663547379E-02));\n    e->forces.push_back(nnp::Vec3D( -6.7148057925522063E-04,   3.0152567310153373E-03,  -2.4082803307522847E-02));\n    e->forces.push_back(nnp::Vec3D(  3.5386176797931003E-03,   7.6533010428282726E-03,   1.1232739799243793E-02));\n    e->forces.push_back(nnp::Vec3D(  2.6682342751926953E-03,  -8.4385940568728647E-03,   6.2721569092616192E-03));\n    e->forces.push_back(nnp::Vec3D( -2.7681629775160848E-03,   3.1378320682778488E-02,  -3.6782644500318117E-02));\n    e->forces.push_back(nnp::Vec3D(  5.7198933874009891E-03,  -3.4183493487981095E-02,   8.6111398733362560E-03));\n    e->forces.push_back(nnp::Vec3D(  3.7422675183335146E-03,  -1.3246518934634795E-03,   2.4902561884752764E-02));\n    e->forces.push_back(nnp::Vec3D(  1.1165308825245017E-02,   7.6696438749757484E-03,  -6.0811050467589535E-02));\n    e->forces.push_back(nnp::Vec3D(  7.0506325792730985E-03,  -1.7059873339893169E-02,   1.8589313080370200E-02));\n    e->forces.push_back(nnp::Vec3D( -1.4680373323693797E-02,   1.2473915385042189E-02,   4.0820406744700888E-02));\n    e->forces.push_back(nnp::Vec3D( -2.2135890029494718E-02,  -2.7171684714111161E-02,  -8.5594001968856744E-03));\n    e->forces.push_back(nnp::Vec3D(  1.2537824032253534E-03,  -1.9989086221817013E-03,  -6.4080875630334730E-03));\n    e->forces.push_back(nnp::Vec3D(  1.8794114475506361E-02,   3.5240983887509583E-02,   5.8335014065085773E-03));\n    e->forces.push_back(nnp::Vec3D( -4.1753223452311340E-02,  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e->forces.push_back(nnp::Vec3D( -1.3914728175318856E-02,   9.5777398530114757E-03,   4.6891083077933151E-03));\n    e->forces.push_back(nnp::Vec3D(  1.1111224710843583E-03,  -5.0439866745527614E-04,   5.5309288773205808E-03));\n    e->forces.push_back(nnp::Vec3D(  6.3302845336084450E-03,   4.3777289942809229E-04,  -7.2696276857287878E-03));\n    e->forces.push_back(nnp::Vec3D( -1.1406959151858947E-02,  -6.0743416294743507E-04,   2.0172301319453185E-03));\n    e->forces.push_back(nnp::Vec3D(  1.0700599364636573E-02,  -1.4369638666558247E-02,   2.4033453943569615E-03));\n    e->forces.push_back(nnp::Vec3D( -6.2165894105018181E-03,   1.6406032472576687E-02,  -7.1556971304862146E-03));\n    e->forces.push_back(nnp::Vec3D( -3.1866150130920652E-02,  -2.5215815989929748E-02,  -5.4746353589679988E-03));\n    e->forces.push_back(nnp::Vec3D(  2.1048445962434041E-02,   3.1156308122411134E-02,   1.5089550526160521E-03));\n    e->forces.push_back(nnp::Vec3D(  1.2638305779184043E-02,  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e->forces.push_back(nnp::Vec3D( -7.6699658553634658E-03,   1.3725131782264538E-02,   1.1487447285539706E-02));\n    e->forces.push_back(nnp::Vec3D(  1.7609932633036375E-02,  -1.5887131264905301E-02,   1.4622841483880763E-02));\n    e->forces.push_back(nnp::Vec3D( -1.8333847220712993E-02,   2.0003925706629146E-02,  -1.8637854270344274E-02));\n    e->forces.push_back(nnp::Vec3D(  5.6513609533778569E-03,  -2.7099249395208112E-04,  -9.8613820141165071E-04));\n    e->forces.push_back(nnp::Vec3D( -2.7495163234804783E-02,  -2.5157315869776254E-02,  -3.4731381966392444E-02));\n    e->forces.push_back(nnp::Vec3D(  3.2825680861041123E-02,   2.2761219285549830E-02,   1.5319574303640964E-02));\n    e->forces.push_back(nnp::Vec3D( -4.2623690785706181E-03,   6.8709311944608843E-03,   1.5081234356966750E-02));\n    e->forces.push_back(nnp::Vec3D( -2.4520592494397453E-03,   1.1884988341343227E-02,   1.6745104733699844E-02));\n    e->forces.push_back(nnp::Vec3D(  1.1751990433135495E-02,  -1.1088127747995452E-02,  -1.0472000130292872E-02));\n    e->forces.push_back(nnp::Vec3D( -1.0687138300398901E-02,   7.8367569369407664E-04,  -6.6966079339768917E-03));\n    e->forces.push_back(nnp::Vec3D( -1.8752798963094907E-02,  -2.8619414290839338E-02,  -1.2052722296070991E-02));\n    e->forces.push_back(nnp::Vec3D(  2.3563466538919281E-03,   2.5876819076531100E-02,  -1.8887363752629997E-02));\n    e->forces.push_back(nnp::Vec3D(  1.5853373589812331E-02,   4.5785478137375987E-03,   2.9728302250457111E-02));\n    e->forces.push_back(nnp::Vec3D( -7.6377439183297220E-03,   1.1934177439733915E-02,  -7.9498454705595311E-03));\n    e->forces.push_back(nnp::Vec3D(  3.0498791658440079E-03,  -3.8861601594224206E-03,   6.5037922459422366E-03));\n    e->forces.push_back(nnp::Vec3D(  5.8072096343061647E-03,  -5.4532525508910338E-03,  -8.3415347793880596E-05));\n    e->forces.push_back(nnp::Vec3D(  2.7009624827833570E-03,   3.4485750600549966E-02,  -1.0248678679979707E-02));\n    e->forces.push_back(nnp::Vec3D( -4.3020619260568660E-03,  -2.0911565932890040E-02,   8.1750377141119764E-04));\n    e->forces.push_back(nnp::Vec3D(  9.1661816051461543E-03,  -2.0068455103795527E-04,   1.2643533440680907E-02));\n    e->forces.push_back(nnp::Vec3D(  2.9505637624168222E-02,   2.4764991781906710E-02,   2.8101116206828876E-03));\n    e->forces.push_back(nnp::Vec3D( -4.2059293159073838E-04,  -1.8110909814389300E-02,   6.7316802505894011E-03));\n    e->forces.push_back(nnp::Vec3D( -2.9717609972325903E-02,  -5.4063475686431280E-03,  -1.1228372790941687E-02));\n    e->forces.push_back(nnp::Vec3D( -1.3976930488603941E-02,  -4.3137992581493900E-03,   8.7338044041644657E-04));\n    e->forces.push_back(nnp::Vec3D( -6.2702158485852758E-03,  -1.3363731350867391E-02,   1.3221643233116958E-03));\n    e->forces.push_back(nnp::Vec3D(  1.5837499917906610E-02,   1.1063043327955898E-02,  -7.3266870738582948E-05));\n    e->forces.push_back(nnp::Vec3D(  5.7537632620636905E-03,  -4.2577093282010668E-02,   4.5027173200969383E-04));\n    e->forces.push_back(nnp::Vec3D( -1.8786536983521066E-02,   2.0216378474898874E-02,   2.7263103609520146E-02));\n    e->forces.push_back(nnp::Vec3D(  1.4406282844241470E-03,   2.3022881983054501E-02,  -2.0595466583864425E-02));\n    e->forces.push_back(nnp::Vec3D(  4.6260015775899735E-03,   6.4222599789955639E-03,   3.9807763579678490E-03));\n    e->forces.push_back(nnp::Vec3D( -5.4074475296588551E-03,  -5.4691884936129836E-03,   5.9862405081472154E-04));\n    e->forces.push_back(nnp::Vec3D(  8.6913651541384238E-03,   2.1966272192811497E-03,  -7.5680890820667007E-03));\n    e->forces.push_back(nnp::Vec3D(  1.0685739234565049E-02,   1.3132922579845868E-02,  -2.9726016526666469E-03));\n    e->forces.push_back(nnp::Vec3D( -3.2419249734497147E-03,   3.6476457292250079E-04,   3.1820678008295310E-05));\n    e->forces.push_back(nnp::Vec3D( -5.1399276336163563E-03,  -1.5775889889284529E-02,   3.7529936173136724E-03));\n\n    examples.push_back(ExamplePrediction(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->energy = -5.7365603183874578E+02;\n    e->forces.push_back(nnp::Vec3D( -1.4000786109479491E-01,   2.7403261309129619E-02,  -5.9615047913556280E-03));\n    e->forces.push_back(nnp::Vec3D(  1.3997290539679894E-01,   2.7389428456545951E-02,   5.9380897409333994E-03));\n    e->forces.push_back(nnp::Vec3D(  1.3998854099790886E-01,  -2.7396901091974960E-02,   6.0233784765652875E-03));\n    e->forces.push_back(nnp::Vec3D( -1.3998531485383750E-01,  -2.7397674146490955E-02,  -6.0145476333750289E-03));\n    e->forces.push_back(nnp::Vec3D( -1.3419464058370537E-01,  -3.0953981174232686E-02,   3.9300642958937725E-02));\n    e->forces.push_back(nnp::Vec3D(  1.3420252174401293E-01,  -3.0958700911860516E-02,  -3.9280059776477999E-02));\n    e->forces.push_back(nnp::Vec3D(  1.3419043778235407E-01,   3.0936661937571316E-02,  -3.9340452227574367E-02));\n    e->forces.push_back(nnp::Vec3D( -1.3428167355133661E-01,   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e->forces.push_back(nnp::Vec3D( -1.0180705189937705E-01,  -5.4316518403869460E-02,   4.3353116373059913E-02));\n    e->forces.push_back(nnp::Vec3D(  1.0176913346689458E-01,  -5.4321301536456000E-02,  -4.3371425135190073E-02));\n    e->forces.push_back(nnp::Vec3D(  1.0176525579273157E-01,   5.4343121065153148E-02,  -4.3302662596016936E-02));\n    e->forces.push_back(nnp::Vec3D( -1.0173858770142637E-01,   5.4323357963728301E-02,   4.3375935971984379E-02));\n    e->forces.push_back(nnp::Vec3D(  1.2683312490908236E-01,  -6.4432392846215422E-02,  -9.4422434924665496E-02));\n    e->forces.push_back(nnp::Vec3D( -1.2682480554849002E-01,  -6.4424337913938354E-02,   9.4428644563142178E-02));\n    e->forces.push_back(nnp::Vec3D( -1.2681286546886680E-01,   6.4405076808745909E-02,   9.4444471003031827E-02));\n    e->forces.push_back(nnp::Vec3D(  1.2687870965257547E-01,   6.4412102144057681E-02,  -9.4338566872525051E-02));\n    e->forces.push_back(nnp::Vec3D(  1.7409832568024819E-01,  -2.1336093828428906E-01,   5.4955787675547006E-02));\n    e->forces.push_back(nnp::Vec3D( -1.7414151294432784E-01,  -2.1337947679043753E-01,  -5.5000920753706932E-02));\n    e->forces.push_back(nnp::Vec3D( -1.7407567069606703E-01,   2.1337626565415838E-01,  -5.5024615585112811E-02));\n    e->forces.push_back(nnp::Vec3D(  1.7409051907382234E-01,   2.1337807311096152E-01,   5.4943484713384359E-02));\n    e->forces.push_back(nnp::Vec3D( -3.9781146599296741E-01,  -4.5785147277299813E-02,  -4.5737459873604211E-02));\n    e->forces.push_back(nnp::Vec3D(  3.9784022328445851E-01,  -4.5748942749148820E-02,   4.5738652707527624E-02));\n    e->forces.push_back(nnp::Vec3D(  3.9784691442422176E-01,   4.5749090208484028E-02,   4.5747367603166431E-02));\n    e->forces.push_back(nnp::Vec3D( -3.9780621287642876E-01,   4.5765304166508092E-02,  -4.5776334553898977E-02));\n    e->forces.push_back(nnp::Vec3D( -1.1200627831524600E-01,  -2.5987110404236489E-02,   1.2496014497896790E-01));\n    e->forces.push_back(nnp::Vec3D(  1.1202981380141384E-01,  -2.5980858949154490E-02,  -1.2495116856212819E-01));\n    e->forces.push_back(nnp::Vec3D(  1.1202519165653103E-01,   2.5968604244122232E-02,  -1.2503407654753435E-01));\n    e->forces.push_back(nnp::Vec3D( -1.1202856820078004E-01,   2.5962014875572315E-02,   1.2493814988034063E-01));\n    e->forces.push_back(nnp::Vec3D( -1.0904748183924062E-01,  -1.8755162592876801E-01,   1.2337072991670674E-01));\n    e->forces.push_back(nnp::Vec3D(  1.0903993371589932E-01,  -1.8753057124460096E-01,  -1.2331593240363552E-01));\n    e->forces.push_back(nnp::Vec3D(  1.0904673951463084E-01,   1.8754895077761155E-01,  -1.2330784724100977E-01));\n    e->forces.push_back(nnp::Vec3D( -1.0902522616579713E-01,   1.8753613312932496E-01,   1.2329301269434512E-01));\n    e->forces.push_back(nnp::Vec3D( -7.5140578729087165E-02,   4.8274012711602685E-02,  -1.8964751152126899E-01));\n    e->forces.push_back(nnp::Vec3D(  7.5159530519396389E-02,   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e->forces.push_back(nnp::Vec3D(  3.0581675851040421E-02,   1.5866233169638380E-02,   2.8417753981101138E-02));\n    e->forces.push_back(nnp::Vec3D( -3.0566144111126094E-02,   1.5861077638596652E-02,  -2.8415382982831479E-02));\n    e->forces.push_back(nnp::Vec3D( -2.9658977210693441E-02,  -3.5450087584560204E-02,   7.2898164580843833E-02));\n    e->forces.push_back(nnp::Vec3D(  2.9655572705746387E-02,  -3.5452652176107644E-02,  -7.2887821512318901E-02));\n    e->forces.push_back(nnp::Vec3D(  2.9644110461717575E-02,   3.5463484715387628E-02,  -7.2901174022813736E-02));\n    e->forces.push_back(nnp::Vec3D( -2.9687685471112779E-02,   3.5439931897246389E-02,   7.2893052228722569E-02));\n    e->forces.push_back(nnp::Vec3D( -1.3721034557414873E-02,  -8.5825992138123738E-02,  -2.2383029546918998E-02));\n    e->forces.push_back(nnp::Vec3D(  1.3746060993840846E-02,  -8.5829938349093332E-02,   2.2389196613982833E-02));\n    e->forces.push_back(nnp::Vec3D(  1.3745223693723238E-02,   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e->forces.push_back(nnp::Vec3D(  8.2789242337892893E-02,  -5.7459046001311284E-02,   5.6292322177404965E-02));\n    e->forces.push_back(nnp::Vec3D(  5.8979066518662596E-02,  -6.4010839275154635E-02,  -1.9008764783307711E-02));\n    e->forces.push_back(nnp::Vec3D( -5.8971185454284876E-02,  -6.3992645123648551E-02,   1.9013324563609196E-02));\n    e->forces.push_back(nnp::Vec3D( -5.8950418054058047E-02,   6.3990185830848950E-02,   1.9029722904771229E-02));\n    e->forces.push_back(nnp::Vec3D(  5.9015812898270639E-02,   6.3988192773871397E-02,  -1.8984753713879813E-02));\n    e->forces.push_back(nnp::Vec3D( -1.3539908000194192E-01,   1.1869048178129991E-01,  -6.5139890470952866E-02));\n    e->forces.push_back(nnp::Vec3D(  1.3537795910816888E-01,   1.1870156231469094E-01,   6.5122844035966285E-02));\n    e->forces.push_back(nnp::Vec3D(  1.3542165343203558E-01,  -1.1869309570520430E-01,   6.5108527814278241E-02));\n    e->forces.push_back(nnp::Vec3D( -1.3542368939410954E-01,  -1.1869455428085704E-01,  -6.5099475965825729E-02));\n    e->forces.push_back(nnp::Vec3D(  1.1238999943164421E-02,   1.4165163605429068E-01,  -4.4495168237055863E-02));\n    e->forces.push_back(nnp::Vec3D( -1.1213725805728167E-02,   1.4164723968603166E-01,   4.4488588119077813E-02));\n    e->forces.push_back(nnp::Vec3D( -1.1220240590027391E-02,  -1.4163620119424294E-01,   4.4520831724435279E-02));\n    e->forces.push_back(nnp::Vec3D(  1.1239342333100845E-02,  -1.4164491142357713E-01,  -4.4515908062602645E-02));\n    e->forces.push_back(nnp::Vec3D(  1.7274939997301714E-01,   9.4743828141788347E-02,   7.7856600004532969E-02));\n    e->forces.push_back(nnp::Vec3D( -1.7275552905230679E-01,   9.4759477791050248E-02,  -7.7818801138987495E-02));\n    e->forces.push_back(nnp::Vec3D( -1.7274520913840744E-01,  -9.4752227740979328E-02,  -7.7867715405995741E-02));\n    e->forces.push_back(nnp::Vec3D(  1.7274905600735449E-01,  -9.4742024533081004E-02,   7.7865346085569900E-02));\n    e->forces.push_back(nnp::Vec3D( -3.6002535937693411E-02,   1.5389282255331579E-01,   3.3020461858381471E-02));\n    e->forces.push_back(nnp::Vec3D(  3.6025446201175725E-02,   1.5388847707845146E-01,  -3.3024774268077435E-02));\n    e->forces.push_back(nnp::Vec3D(  3.6018230979757683E-02,  -1.5388479467900629E-01,  -3.3038840967927439E-02));\n    e->forces.push_back(nnp::Vec3D( -3.6000714073681474E-02,  -1.5389919202021499E-01,   3.3016358274407458E-02));\n    e->forces.push_back(nnp::Vec3D(  2.5263167184084685E-02,   1.5334817330815878E-01,  -4.6879010219804999E-02));\n    e->forces.push_back(nnp::Vec3D( -2.5268561191266817E-02,   1.5335159151176714E-01,   4.6885425721636426E-02));\n    e->forces.push_back(nnp::Vec3D( -2.5263151416447777E-02,  -1.5335041726858009E-01,   4.6866142620331896E-02));\n    e->forces.push_back(nnp::Vec3D(  2.5270494798888037E-02,  -1.5334726387521161E-01,  -4.6888507678491058E-02));\n    e->forces.push_back(nnp::Vec3D(  1.0710871731977081E-01,   2.9090511771972864E-02,   7.9856564559777701E-02));\n    e->forces.push_back(nnp::Vec3D( -1.0706843123312258E-01,   2.9119980409550269E-02,  -7.9908172184522147E-02));\n    e->forces.push_back(nnp::Vec3D( -1.0707489825726359E-01,  -2.9101674849580456E-02,  -7.9904630433936363E-02));\n    e->forces.push_back(nnp::Vec3D(  1.0706782605329966E-01,  -2.9110272399536855E-02,   7.9921205798818978E-02));\n    e->forces.push_back(nnp::Vec3D(  1.9365600975073526E-02,  -1.8289615432367852E-02,  -3.7764988691823451E-03));\n    e->forces.push_back(nnp::Vec3D( -1.9356927547397339E-02,  -1.8293454561606894E-02,   3.7761208663251553E-03));\n    e->forces.push_back(nnp::Vec3D( -1.9376514383964732E-02,   1.8285818824013238E-02,   3.7933295247501884E-03));\n    e->forces.push_back(nnp::Vec3D(  1.9366568034867040E-02,   1.8289132500623580E-02,  -3.7759751498303864E-03));\n    e->forces.push_back(nnp::Vec3D(  4.9048796488297068E-02,   1.5662932116107559E-02,  -2.5377257986905166E-02));\n    e->forces.push_back(nnp::Vec3D( -4.9060358968155714E-02,   1.5668067449307356E-02,   2.5353907086253308E-02));\n    e->forces.push_back(nnp::Vec3D( -4.9057385662366372E-02,  -1.5666792155093357E-02,   2.5355463706925332E-02));\n    e->forces.push_back(nnp::Vec3D(  4.9072410910339030E-02,  -1.5674245379036840E-02,  -2.5381896344836084E-02));\n    e->forces.push_back(nnp::Vec3D( -6.1912354811961764E-02,  -1.9867202177344098E-02,   1.2644092998275641E-01));\n    e->forces.push_back(nnp::Vec3D(  6.1881005112728676E-02,  -1.9856662825781784E-02,  -1.2641101260433146E-01));\n    e->forces.push_back(nnp::Vec3D(  6.1956554334560855E-02,   1.9899488035608065E-02,  -1.2648951581479848E-01));\n    e->forces.push_back(nnp::Vec3D( -6.1956369041609338E-02,   1.9899509959562359E-02,   1.2649132206068581E-01));\n    e->forces.push_back(nnp::Vec3D( -2.9160596774721770E-02,   4.8043253961742853E-02,   3.1916835256527054E-02));\n    e->forces.push_back(nnp::Vec3D(  2.9151197313091983E-02,   4.8044857470697457E-02,  -3.1909066740362486E-02));\n    e->forces.push_back(nnp::Vec3D(  2.9148868987902522E-02,  -4.8046055463763920E-02,  -3.1907239466793219E-02));\n    e->forces.push_back(nnp::Vec3D( -2.9148553934119283E-02,  -4.8046268806943786E-02,   3.1875481944545335E-02));\n    e->forces.push_back(nnp::Vec3D(  2.1405155110730396E-02,   3.5969304130269560E-02,   7.5891144110438846E-02));\n    e->forces.push_back(nnp::Vec3D( -2.1384044472319595E-02,   3.5925197835553056E-02,  -7.5836115878409383E-02));\n    e->forces.push_back(nnp::Vec3D( -2.1391242320127572E-02,  -3.5932276974083570E-02,  -7.5833979647411592E-02));\n    e->forces.push_back(nnp::Vec3D(  2.1379696126303069E-02,  -3.5951659713941743E-02,   7.5877842254100381E-02));\n    e->forces.push_back(nnp::Vec3D(  7.8325128329082533E-02,   3.3640873102989521E-02,   6.5304324855515836E-02));\n    e->forces.push_back(nnp::Vec3D( -7.8365906323433820E-02,   3.3633029681018778E-02,  -6.5293464571588147E-02));\n    e->forces.push_back(nnp::Vec3D( -7.8355542916841783E-02,  -3.3636382920138243E-02,  -6.5282900027072779E-02));\n    e->forces.push_back(nnp::Vec3D(  7.8332413251601771E-02,  -3.3638496039943615E-02,   6.5288273979366443E-02));\n    e->forces.push_back(nnp::Vec3D(  3.7915322336999228E-02,  -3.8663484092225309E-02,  -7.5828959972827695E-02));\n    e->forces.push_back(nnp::Vec3D( -3.7916523632527024E-02,  -3.8673315354541986E-02,   7.5843790472396921E-02));\n    e->forces.push_back(nnp::Vec3D( -3.7922504283561788E-02,   3.8653236127949075E-02,   7.5800452346171221E-02));\n    e->forces.push_back(nnp::Vec3D(  3.7936473894491805E-02,   3.8704762165063022E-02,  -7.5896893253279321E-02));\n    e->forces.push_back(nnp::Vec3D(  4.3810723328028718E-02,   7.7301824777861045E-02,   5.2478935688184326E-02));\n    e->forces.push_back(nnp::Vec3D( -4.3809894921678180E-02,   7.7303699496442960E-02,  -5.2475138307086978E-02));\n    e->forces.push_back(nnp::Vec3D( -4.3811294886706473E-02,  -7.7313682915489026E-02,  -5.2489132782773201E-02));\n    e->forces.push_back(nnp::Vec3D(  4.3830597350904194E-02,  -7.7308143375471081E-02,   5.2455959275626365E-02));\n    e->forces.push_back(nnp::Vec3D( -9.0757633164481405E-02,   1.0402341515843659E-01,   3.4669488850530332E-02));\n    e->forces.push_back(nnp::Vec3D(  9.0727111469917854E-02,   1.0402449358908034E-01,  -3.4677960819044104E-02));\n    e->forces.push_back(nnp::Vec3D(  9.0763984501207803E-02,  -1.0403914866048729E-01,  -3.4665245588695624E-02));\n    e->forces.push_back(nnp::Vec3D( -9.0768737531128962E-02,  -1.0402965655460100E-01,   3.4667794680385472E-02));\n    e->forces.push_back(nnp::Vec3D(  3.5815293991104044E-02,   2.5405011659585225E-02,   7.9027816506308420E-03));\n    e->forces.push_back(nnp::Vec3D( -3.5789754818209257E-02,   2.5415219586880824E-02,  -7.9208484803731799E-03));\n    e->forces.push_back(nnp::Vec3D( -3.5827689149422984E-02,  -2.5398042280458933E-02,  -7.8828217115014566E-03));\n    e->forces.push_back(nnp::Vec3D(  3.5817145339627279E-02,  -2.5405030958075364E-02,   7.9056734815332094E-03));\n    e->forces.push_back(nnp::Vec3D(  4.2309207707589669E-02,   1.7749489524669027E-02,   3.6316724727893594E-02));\n    e->forces.push_back(nnp::Vec3D( -4.2276734127241720E-02,   1.7731145615572732E-02,  -3.6405151742905623E-02));\n    e->forces.push_back(nnp::Vec3D( -4.2320530483244627E-02,  -1.7723352983969355E-02,  -3.6377130654700204E-02));\n    e->forces.push_back(nnp::Vec3D(  4.2298643837139528E-02,  -1.7729562120778242E-02,   3.6370642426159290E-02));\n    e->forces.push_back(nnp::Vec3D( -3.5716985048350580E-02,   7.5736241656861880E-02,   1.6847267974531754E-03));\n    e->forces.push_back(nnp::Vec3D(  3.5760644436382806E-02,   7.5732819102776808E-02,  -1.6580809789149560E-03));\n    e->forces.push_back(nnp::Vec3D(  3.5729461768210888E-02,  -7.5735222172770539E-02,  -1.6717372841554578E-03));\n    e->forces.push_back(nnp::Vec3D( -3.5715859744803936E-02,  -7.5724430665978185E-02,   1.6826591445618581E-03));\n\n    examples.push_back(ExamplePrediction(\"Anisole_SCAN\"));\n    e = &(examples.back());\n    e->energy = -9.6749614724733078E+02;\n    e->forces.push_back(nnp::Vec3D(  1.5196301089137254E-02,  3.0665350849063806E-02,  4.8767024815039930E-03));\n    e->forces.push_back(nnp::Vec3D(  3.3989124383321807E-02, -4.4332090623369534E-02, -3.4199154828114817E-03));\n    e->forces.push_back(nnp::Vec3D( -2.1848293705516433E-03, -9.1117827774268665E-03,  1.4651931038459647E-02));\n    e->forces.push_back(nnp::Vec3D(  4.2848864433426261E-02,  1.7283850962270291E-02,  4.0989847690277983E-02));\n    e->forces.push_back(nnp::Vec3D( -1.7059519566715801E-02, -8.8440060529208584E-03,  3.5338503129278574E-02));\n    e->forces.push_back(nnp::Vec3D(  3.4241853582971202E-02,  8.2322455580476177E-03,  1.3766089563839668E-02));\n    e->forces.push_back(nnp::Vec3D(  9.6715244403881330E-03, -1.2532781558762453E-02,  8.1181153246097869E-04));\n    e->forces.push_back(nnp::Vec3D( -8.3127275809967219E-03,  3.7333050272268624E-02,  7.2633766802396573E-03));\n    e->forces.push_back(nnp::Vec3D(  1.0501156041990055E-02, -2.2006661439781432E-03, -1.9370913488027167E-03));\n    e->forces.push_back(nnp::Vec3D( -2.0207470089681573E-02, -1.4672354923657032E-03, -4.5826078943988879E-02));\n    e->forces.push_back(nnp::Vec3D( -2.9459110664677435E-02,  3.1654549002911384E-02, -1.4945822202946461E-02));\n    e->forces.push_back(nnp::Vec3D(  5.3499073655845801E-03,  1.8650525150976087E-02,  3.4936395768049376E-02));\n    e->forces.push_back(nnp::Vec3D(  2.1112033607150065E-02, -3.9975312019352232E-04,  3.9952139827201825E-02));\n    e->forces.push_back(nnp::Vec3D( -2.8467311023293591E-02, -2.7413816941030678E-02,  3.2448510600543948E-02));\n    e->forces.push_back(nnp::Vec3D( -3.6463981348435000E-03, -4.8914841624307821E-03, -1.6395539674391352E-02));\n    e->forces.push_back(nnp::Vec3D(  7.2525678773452396E-03, -1.9461631664758176E-02, -9.9241501443663015E-03));\n    e->forces.push_back(nnp::Vec3D(  2.5330477943938452E-02, -1.0994907996754332E-02, -1.0863974437857972E-02));\n    e->forces.push_back(nnp::Vec3D( -2.5993179427378832E-02,  1.6430943857457653E-02, -1.2968616739768776E-02));\n    e->forces.push_back(nnp::Vec3D( -7.6027030358704209E-03,  9.5277969757469692E-03, -6.5379900556408732E-04));\n    e->forces.push_back(nnp::Vec3D( -1.4833643010451935E-02, -1.6415104724747467E-02, -3.8967743074708287E-02));\n    e->forces.push_back(nnp::Vec3D(  2.0092172682501262E-02, -1.4040926507049559E-02,  2.8772552540150154E-02));\n    e->forces.push_back(nnp::Vec3D(  2.3123058300002775E-02, -2.7340460873349785E-02,  1.4790315916741304E-02));\n    e->forces.push_back(nnp::Vec3D( -8.7125690855572799E-03,  3.5367846353247225E-02, -1.9869629557993852E-02));\n    e->forces.push_back(nnp::Vec3D(  2.1258215070708488E-02, -5.9450636694879091E-03,  6.3109862867066525E-03));\n    e->forces.push_back(nnp::Vec3D( -1.8148494872456060E-02, 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e->forces.push_back(nnp::Vec3D(  1.9340746265565614E-02,  2.1967918591003721E-02,  6.9112417010186991E-03));\n    e->forces.push_back(nnp::Vec3D(  4.6581464488447515E-03, -7.3936182856011159E-03, -2.3613879280654959E-03));\n    e->forces.push_back(nnp::Vec3D( -9.3882539723421049E-04,  9.5554618446233256E-03, -2.9545574278088947E-03));\n    e->forces.push_back(nnp::Vec3D(  2.6770762419808070E-04,  6.1912982963834512E-03,  3.3180688176485070E-03));\n    e->forces.push_back(nnp::Vec3D(  2.2178328758629046E-03,  6.2712516419776310E-03, -8.7387608713680894E-04));\n    e->forces.push_back(nnp::Vec3D(  1.6253875646711092E-02,  4.2788072755123125E-03,  1.0236589289519439E-02));\n    e->forces.push_back(nnp::Vec3D(  1.2860454921772395E-03, -2.4445868002777879E-03, -6.8991417687468944E-03));\n    e->forces.push_back(nnp::Vec3D(  9.3769421000692681E-03,  2.3933800403130390E-03, -5.1779102951218089E-03));\n    e->forces.push_back(nnp::Vec3D( -4.5176229779104304E-03,  1.6308558720807897E-02,  8.3377906217181382E-03));\n    e->forces.push_back(nnp::Vec3D( -1.1763272257125830E-03, -1.2135410015942061E-04, -1.3762964793020244E-03));\n    e->forces.push_back(nnp::Vec3D( -5.2808661273245029E-03, -2.4459478685394734E-03, -2.4389970109293742E-03));\n    e->forces.push_back(nnp::Vec3D( -4.6278666944600802E-03,  6.1221950114286484E-03, -4.6774516906711800E-03));\n    e->forces.push_back(nnp::Vec3D( -4.5813954828676732E-03,  1.0942773952752205E-04, -7.0664622086764059E-03));\n    e->forces.push_back(nnp::Vec3D( -1.1338565657951225E-02, -7.5009070734012280E-03, -7.9404248986404500E-03));\n    e->forces.push_back(nnp::Vec3D( -2.2622846906735479E-04, -1.7611161359398981E-03, -8.6655072723089053E-04));\n    e->forces.push_back(nnp::Vec3D(  2.9030975495135001E-03, -9.7205945299357228E-03,  6.7845258257109211E-03));\n    e->forces.push_back(nnp::Vec3D( -5.8698295357239808E-03,  1.7867800033149497E-02, -6.7395512572759383E-03));\n    e->forces.push_back(nnp::Vec3D(  1.7055160509118546E-03,  1.9030528236032435E-03, -4.7466742487395526E-03));\n    e->forces.push_back(nnp::Vec3D(  6.9829331864827426E-03, -4.9329913165048036E-03, -3.9484351054436800E-03));\n    e->forces.push_back(nnp::Vec3D(  3.9221251926019355E-03, -4.4268450454301523E-03, -5.3884791270289107E-03));\n    e->forces.push_back(nnp::Vec3D( -1.2366133046166265E-02, -2.1219138882544800E-03,  1.8523617503254704E-02));\n    e->forces.push_back(nnp::Vec3D( -7.6585637862560162E-03, -2.1520417239818013E-02,  4.8808504530101356E-05));\n    e->forces.push_back(nnp::Vec3D( -1.0051713486323657E-02,  3.9477194190462627E-03, -1.4685712509092912E-02));\n    e->forces.push_back(nnp::Vec3D(  2.2574196108603355E-03, -4.7776156396476489E-03,  1.2961600930188875E-04));\n    e->forces.push_back(nnp::Vec3D(  5.6551211665550986E-03, -5.7764799439152421E-03,  2.2250349621589639E-03));\n    e->forces.push_back(nnp::Vec3D(  9.0240702053783900E-03, -5.1831727488008833E-04, -2.1754719121969408E-03));\n    e->forces.push_back(nnp::Vec3D( -1.7378964745623322E-03,  2.3544180966111610E-03,  4.8831010467762044E-03));\n    e->forces.push_back(nnp::Vec3D( -7.7318797686209539E-03,  1.4422495014830103E-03,  1.2872286210997578E-03));\n    e->forces.push_back(nnp::Vec3D( -9.5978076956153568E-03,  2.8960411338709324E-03,  6.6635634533953065E-03));\n    e->forces.push_back(nnp::Vec3D(  1.1061837651919957E-02, -2.1008670050507029E-02, -7.8555680240218542E-03));\n    e->forces.push_back(nnp::Vec3D(  1.7476032420743630E-02, -3.3310313044562120E-05, -2.3081250011299879E-02));\n    e->forces.push_back(nnp::Vec3D(  1.4735792784262736E-03, -1.5012687150118408E-02,  6.9033396805225538E-03));\n    e->forces.push_back(nnp::Vec3D(  7.8990538751488567E-04, -8.5550432504280585E-03, -8.2442198496416675E-04));\n    e->forces.push_back(nnp::Vec3D( -3.4137066055389487E-03,  6.2343566576338605E-03,  5.2182970251789191E-03));\n    e->forces.push_back(nnp::Vec3D( -4.4697007328202447E-03, -7.2743518201324716E-04,  1.1997803573354792E-02));\n    e->forces.push_back(nnp::Vec3D( -2.0597646351336297E-03,  5.0064548042089447E-03,  8.6675709111427054E-04));\n    e->forces.push_back(nnp::Vec3D( -4.4199281270570550E-03,  1.5760998922325327E-03,  1.1461670475398523E-02));\n    e->forces.push_back(nnp::Vec3D(  1.2960156818485336E-03,  3.2221671310762715E-03,  3.1046779203761972E-04));\n    e->forces.push_back(nnp::Vec3D( -2.5752693165770378E-03,  3.1339291344596497E-03,  1.0053068139569176E-02));\n    e->forces.push_back(nnp::Vec3D(  4.7441056706408954E-03,  9.2223894208813325E-03, -2.0708562501410536E-04));\n    e->forces.push_back(nnp::Vec3D( -5.6286062792075086E-04,  2.7422369518731110E-03,  1.0730491593149458E-02));\n    e->forces.push_back(nnp::Vec3D(  5.7686660255924739E-03,  1.1362714888600262E-02, -8.7931759762433573E-03));\n    e->forces.push_back(nnp::Vec3D(  3.8325734091491466E-03,  5.9371557151924707E-03,  6.4467049749534523E-03));\n    e->forces.push_back(nnp::Vec3D(  2.0493271222988513E-03, -6.6447188962010005E-03, -5.5563402782090937E-03));\n    e->forces.push_back(nnp::Vec3D(  1.1557751133721476E-02, -8.0710877802923197E-03, -4.1543578988990706E-03));\n    e->forces.push_back(nnp::Vec3D( -9.5588335244531069E-03, -6.1082578143245815E-03,  1.5830010407835930E-02));\n    e->forces.push_back(nnp::Vec3D(  4.7071964884788756E-04, -6.0319100500921697E-03,  9.7462357433379481E-04));\n    e->forces.push_back(nnp::Vec3D( -3.4784094113932702E-03,  7.7530924845168004E-03,  7.1121940976594299E-04));\n    e->forces.push_back(nnp::Vec3D( -1.4182285158031575E-03, -5.5209368170377018E-04,  1.2755079064094474E-03));\n    e->forces.push_back(nnp::Vec3D( -2.7986824205194403E-03,  2.8120529389906623E-03,  2.4150003808863906E-03));\n    e->forces.push_back(nnp::Vec3D( -1.9201022615323142E-03,  8.2611548545258387E-03, -2.7294607183969573E-03));\n    e->forces.push_back(nnp::Vec3D(  1.9996272444267730E-03,  5.7386689766271131E-03,  8.4151632867246581E-04));\n    e->forces.push_back(nnp::Vec3D( -2.3126271064598529E-03,  2.2956443476331166E-03,  4.0939085575100670E-03));\n    e->forces.push_back(nnp::Vec3D( -3.0385665425810134E-04, -4.4382331632762968E-03, -3.2805522172438747E-03));\n    e->forces.push_back(nnp::Vec3D( -4.3259664258002827E-03,  1.0778205191351474E-03, -3.1307436468552868E-03));\n    e->forces.push_back(nnp::Vec3D( -4.6888567098048124E-04,  6.8066492057675902E-03,  7.6355836726437545E-03));\n    e->forces.push_back(nnp::Vec3D(  4.4443782990079951E-03,  1.0670169349116396E-02,  1.2349149362748928E-02));\n    e->forces.push_back(nnp::Vec3D(  4.0207272584431748E-03,  8.3228627527311399E-03, -1.2518330409142379E-03));\n    e->forces.push_back(nnp::Vec3D( -6.9039393933767899E-03, -8.3213429275377625E-03, -4.2620029038415060E-03));\n    e->forces.push_back(nnp::Vec3D( -4.8554177780133602E-03,  3.0880698248276725E-03,  1.3026911159880703E-02));\n    e->forces.push_back(nnp::Vec3D( -8.1076361368819707E-03, -1.7113461689777043E-03, -2.3477198812317246E-03));\n    e->forces.push_back(nnp::Vec3D(  4.1308595046648730E-03,  1.4016848520867528E-03, -7.5131846619706458E-03));\n    e->forces.push_back(nnp::Vec3D( -1.7457626512081838E-03,  7.4037343311573233E-03, -4.4832875519041802E-03));\n    e->forces.push_back(nnp::Vec3D(  5.4854649759633183E-05,  3.9396929506273605E-03, -1.9114329088612270E-03));\n    e->forces.push_back(nnp::Vec3D( -3.8414857506503856E-03, -3.2228081945508613E-04, -3.3231486237808249E-03));\n    e->forces.push_back(nnp::Vec3D( -1.0459242061217429E-02, -5.9891387044235618E-03, -3.8935862069978386E-04));\n    e->forces.push_back(nnp::Vec3D( -2.8214407681169409E-03,  9.7340413900251221E-03, -1.8405784193905738E-03));\n    e->forces.push_back(nnp::Vec3D(  1.1557471297333833E-02,  2.8293328554429436E-02,  2.8947019091391062E-02));\n    e->forces.push_back(nnp::Vec3D( -4.8171988912205715E-04,  2.1731691281420232E-04,  2.7221056313057081E-03));\n    e->forces.push_back(nnp::Vec3D( -1.9369943651792309E-03, -1.8169905488278629E-02,  1.1974940261467145E-02));\n    e->forces.push_back(nnp::Vec3D( -7.8404472618969559E-03,  3.2983885849258494E-02, -1.0346888600547076E-02));\n    e->forces.push_back(nnp::Vec3D( -5.2333906882355624E-03, -1.3090141329017025E-03, -3.5801537977236731E-03));\n    e->forces.push_back(nnp::Vec3D(  8.0630959748656077E-03, -1.3534470046563548E-03, -3.0829682324968314E-03));\n    e->forces.push_back(nnp::Vec3D(  2.3856825938129498E-03, -4.1768323632284240E-03,  3.5208720037624018E-03));\n    e->forces.push_back(nnp::Vec3D( -1.2105159232926131E-02, -1.1517100798499661E-02, -5.2184814175990722E-03));\n    e->forces.push_back(nnp::Vec3D(  7.1587639470904584E-03,  1.4983746705942423E-02,  1.7722272224086932E-03));\n    e->forces.push_back(nnp::Vec3D( -2.3840352694528941E-03, -4.3624013570524580E-03, -5.6682197202424756E-04));\n    e->forces.push_back(nnp::Vec3D( -7.1450858907636874E-03, -4.1961422273390130E-03, -5.5897140332344872E-03));\n    e->forces.push_back(nnp::Vec3D( -2.0367272578093679E-02, -1.8971488400265750E-03, -4.6366642548711836E-03));\n    e->forces.push_back(nnp::Vec3D( -8.0861850402677614E-04, -6.6276501507212988E-03,  2.2752550911348821E-03));\n    e->forces.push_back(nnp::Vec3D( -1.4406519044915696E-03, -1.3472106651715332E-02, -1.3156437019999257E-02));\n    e->forces.push_back(nnp::Vec3D( -9.2158959893874071E-03, -5.4994811039608439E-03,  4.0263884679154795E-03));\n    e->forces.push_back(nnp::Vec3D( -1.1204118000038212E-03, -1.7290656526068012E-03, -1.0473554229123203E-02));\n    e->forces.push_back(nnp::Vec3D( -2.2355166357362712E-03,  2.5305481768246518E-03, -9.4223343390518435E-04));\n    e->forces.push_back(nnp::Vec3D(  9.1378981806122615E-03,  3.1257899519103165E-03, -2.6269673542481126E-03));\n    e->forces.push_back(nnp::Vec3D( -2.1833758434736624E-04, -1.0435023341725139E-02, -2.7178049736653032E-03));\n    e->forces.push_back(nnp::Vec3D(  3.3885881440829766E-03,  2.8280505837422220E-03, -3.0611790148404117E-03));\n    e->forces.push_back(nnp::Vec3D(  1.0174050529379027E-02,  8.1060178445054379E-03, -1.2271263690762728E-02));\n    e->forces.push_back(nnp::Vec3D(  2.4499330850007776E-02, -1.2420723572231962E-03, -1.1453679778562759E-02));\n    e->forces.push_back(nnp::Vec3D(  8.0419529795655348E-04, -9.3984622128277656E-03, -7.4170417060564270E-03));\n    e->forces.push_back(nnp::Vec3D( -2.7041396412643181E-03,  2.2301937675214714E-03, -5.2399697267638684E-03));\n    e->forces.push_back(nnp::Vec3D( -1.0240115434584951E-02,  1.4059744387906596E-02,  1.7069462368240050E-02));\n    e->forces.push_back(nnp::Vec3D(  1.1389097581242969E-02,  1.8184250196123616E-02, -7.0302708503332421E-03));\n    e->forces.push_back(nnp::Vec3D(  6.7281447789706633E-03, -3.7593299330965523E-03, -1.0563316963166044E-04));\n    e->forces.push_back(nnp::Vec3D(  9.0865060878714406E-04,  3.3260013844267169E-03, -9.7691163453574297E-04));\n    e->forces.push_back(nnp::Vec3D(  7.1392705276847107E-03, -7.7424337393005530E-03,  9.4750151959719416E-03));\n    e->forces.push_back(nnp::Vec3D(  1.4848435242949832E-02, -5.7243347490378979E-03, -3.0280380389319165E-03));\n    e->forces.push_back(nnp::Vec3D(  5.3041975685308645E-05,  1.5599604534469388E-03, -3.8931999751634794E-03));\n    e->forces.push_back(nnp::Vec3D( -2.3896391472220551E-03, -2.5132601053769692E-04,  8.1204242243029766E-03));\n    e->forces.push_back(nnp::Vec3D(  6.3378245454390270E-03, -1.2025078198785077E-02, -1.2521612619389198E-02));\n    e->forces.push_back(nnp::Vec3D(  1.3097847315653049E-03, -2.6813531867674657E-03,  5.5853886120673659E-04));\n    e->forces.push_back(nnp::Vec3D(  1.5427753363248583E-03, -1.8770733429100080E-02, -5.5037215510248365E-03));\n    e->forces.push_back(nnp::Vec3D(  7.8514038493656211E-03, -5.1916396834196486E-03, -1.6120998137419101E-03));\n    e->forces.push_back(nnp::Vec3D( -6.6530602117571237E-03,  2.1640788594312524E-02, -7.1578697539409252E-03));\n    e->forces.push_back(nnp::Vec3D( -6.3680612307640064E-03,  3.5999086514426786E-03, -6.3621368203534093E-03));\n    e->forces.push_back(nnp::Vec3D(  3.7631369106316342E-03, -1.3614675169361077E-03,  1.8581512364969011E-02));\n    e->forces.push_back(nnp::Vec3D( -9.7928535738327493E-03,  3.3350703518997332E-03,  1.3391350046851179E-02));\n    e->forces.push_back(nnp::Vec3D(  2.9151088511663380E-03,  9.1582796363972787E-03, -3.7077144268094810E-03));\n    e->forces.push_back(nnp::Vec3D( -1.7934472393582581E-03, -1.1582401989932197E-03, -8.1005000781906428E-04));\n\n    examples.push_back(ExamplePrediction(\"DMABN_SCAN\"));\n    e = &(examples.back());\n    e->energy = -7.6864264790108564E+01;\n    e->forces.push_back(nnp::Vec3D(  4.8626838255106473E-03,  8.2178516307662555E-02, -3.8153852327335862E-02));\n    e->forces.push_back(nnp::Vec3D( -7.4813363454420870E-02,  2.1696615967792817E-02,  9.3763449210535078E-03));\n    e->forces.push_back(nnp::Vec3D(  3.0847005785849518E-02,  1.3849178112076442E-02, -1.6193350966869486E-02));\n    e->forces.push_back(nnp::Vec3D(  3.0468026915942713E-02, -6.0470192752535385E-03,  1.0070208727645000E-02));\n    e->forces.push_back(nnp::Vec3D(  7.2515867125728427E-03, -4.2238034089629041E-02,  1.0137430571185102E-02));\n    e->forces.push_back(nnp::Vec3D(  4.3391745293011652E-02, -1.0339540348525874E-02, -2.0187575399179668E-02));\n    e->forces.push_back(nnp::Vec3D(  1.2766261436442250E-02, -3.1032527930701648E-02,  4.0281020252906412E-02));\n    e->forces.push_back(nnp::Vec3D( -8.4164648824093628E-03, -1.2186615027276826E-02, -4.3152186996498181E-03));\n    e->forces.push_back(nnp::Vec3D( -7.4584482326976731E-02, -1.5599257440586927E-03,  1.2537279168497754E-03));\n    e->forces.push_back(nnp::Vec3D( -4.3172248113596767E-02, -7.3658908621706515E-02,  4.9630626730081881E-03));\n    e->forces.push_back(nnp::Vec3D(  3.8107711998244330E-02,  1.0349989223334729E-03,  7.0823117425412461E-04));\n    e->forces.push_back(nnp::Vec3D(  2.4670665807061117E-02, -4.0119753861182876E-03,  6.2431287040283995E-03));\n    e->forces.push_back(nnp::Vec3D( -2.0136708138830336E-04, -3.5204045295926578E-02,  1.7350361833194442E-02));\n    e->forces.push_back(nnp::Vec3D(  1.7858686061212393E-03,  6.3440542730957639E-03,  2.3341207955141312E-02));\n    e->forces.push_back(nnp::Vec3D(  4.5626389785463434E-02,  6.5614809325281040E-03, -1.2768316863561256E-03));\n    e->forces.push_back(nnp::Vec3D(  6.4851119330906776E-03,  6.1779127054392207E-03, -1.3329866718998312E-02));\n    e->forces.push_back(nnp::Vec3D(  8.9394222230467623E-03, -9.3391671411356368E-03, -1.1134022970414406E-03));\n    e->forces.push_back(nnp::Vec3D( -1.3843095043066607E-02, -1.1885477239927148E-02, -8.6626836683056357E-03));\n    e->forces.push_back(nnp::Vec3D( -2.2211797049418208E-02,  3.6413374214933403E-02, -1.0602627990020909E-04));\n    e->forces.push_back(nnp::Vec3D(  4.6024322712594507E-03,  4.1613859176409071E-02, -2.0211603039830741E-02));\n    e->forces.push_back(nnp::Vec3D( -2.2562094642339537E-02,  2.1633245487988666E-02, -1.7431364579897961E-04));\n\n    examples.push_back(ExamplePrediction(\"Ethylbenzene_SCAN\"));\n    e = &(examples.back());\n    e->energy = -8.2198742206281679E+02;\n    e->forces.push_back(nnp::Vec3D( -3.1326793716000771E-02, -1.3170042580312860E-02, -1.7617970880197914E-03));\n    e->forces.push_back(nnp::Vec3D( -1.0109140439021648E-02, -4.1716634902053658E-03,  4.4383811058265861E-03));\n    e->forces.push_back(nnp::Vec3D( -4.6140625035785109E-03,  3.9001411126122934E-03,  1.0574320133520708E-02));\n    e->forces.push_back(nnp::Vec3D( -2.3294923752790390E-03, -7.8115074182173640E-03, -5.4321426226202462E-03));\n    e->forces.push_back(nnp::Vec3D( -3.5718055320056153E-03, -9.2829315257007272E-03, -1.1671847853441329E-02));\n    e->forces.push_back(nnp::Vec3D(  2.8990811771526903E-02, -3.8976812787363197E-03, -1.4481548210616070E-02));\n    e->forces.push_back(nnp::Vec3D(  6.3852741649019834E-03, -9.9663054602775712E-03,  2.0022145156496928E-02));\n    e->forces.push_back(nnp::Vec3D(  2.1811153061691438E-03,  1.1707314202767688E-02,  1.3692112770560864E-02));\n    e->forces.push_back(nnp::Vec3D( -8.8392492168364954E-03, -2.9553650464435800E-03, -2.6424594978341358E-02));\n    e->forces.push_back(nnp::Vec3D(  5.8414379491082621E-03,  2.2909049117723471E-02,  2.1289376485187222E-02));\n    e->forces.push_back(nnp::Vec3D(  1.5552105684534067E-02,  4.2087682266339164E-03,  2.5591175465482095E-02));\n    e->forces.push_back(nnp::Vec3D( -3.7237320954061981E-03,  3.1282607370138868E-02, -6.0920747777617301E-02));\n    e->forces.push_back(nnp::Vec3D( -7.1629224989023035E-03, -7.3812931933879243E-03,  9.4020224153978024E-03));\n    e->forces.push_back(nnp::Vec3D( -8.4688605833859350E-03, -6.1694738614856783E-04, -4.1253637905290588E-02));\n    e->forces.push_back(nnp::Vec3D( -1.5974862524969918E-02,  7.6413723772174999E-03,  3.0302602813354457E-03));\n    e->forces.push_back(nnp::Vec3D(  1.4836158059570892E-02,  6.2151605921048842E-03,  2.5914303124149954E-02));\n    e->forces.push_back(nnp::Vec3D(  1.1406308870842903E-02,  2.3832249499746178E-02,  2.9016165360976768E-03));\n    e->forces.push_back(nnp::Vec3D( -1.1439114890902199E-02,  1.3018851305766749E-03,  2.0665510474144961E-02));\n    e->forces.push_back(nnp::Vec3D(  6.8670110809501556E-03,  2.3266736571616618E-02, -2.3706437186963591E-02));\n    e->forces.push_back(nnp::Vec3D( -3.2515324153520465E-02,  8.4829026297554341E-03,  1.9589698330506684E-02));\n    e->forces.push_back(nnp::Vec3D( -2.2375549210554829E-02,  2.5020867228878182E-02, -1.0459355378705279E-02));\n    e->forces.push_back(nnp::Vec3D( -3.4711786699339754E-02,  1.3669674915979788E-02,  2.8741767282208168E-02));\n    e->forces.push_back(nnp::Vec3D(  1.4957534674160257E-02, -1.1106517222884145E-03,  4.6081158928415238E-02));\n    e->forces.push_back(nnp::Vec3D(  1.0873907650969275E-02, -2.0178111163659702E-03, -6.3577819822917348E-03));\n    e->forces.push_back(nnp::Vec3D( -1.4204305762123073E-02,  5.7436783627511003E-03,  1.5928729655583333E-02));\n    e->forces.push_back(nnp::Vec3D( -9.7408871620191188E-03, -2.1540314296798192E-02,  3.3502040717501833E-03));\n    e->forces.push_back(nnp::Vec3D(  3.6013439385513494E-03,  6.3780174560385053E-03,  4.8884307631615826E-03));\n    e->forces.push_back(nnp::Vec3D(  4.3757669088420020E-02,  3.9976699547705823E-02,  2.1679446261595067E-02));\n    e->forces.push_back(nnp::Vec3D(  2.5501884337214408E-02,  1.7097258320128497E-02,  1.3439439447451192E-02));\n    e->forces.push_back(nnp::Vec3D( -3.7750786997872519E-03,  3.7354026862712751E-03, -3.6896964730147204E-02));\n    e->forces.push_back(nnp::Vec3D(  1.7777871495221746E-02,  2.0605403129124320E-02, -1.4160825201564670E-02));\n    e->forces.push_back(nnp::Vec3D(  3.4073970791496317E-03,  3.2611001251263128E-03, -2.4501793625691486E-02));\n    e->forces.push_back(nnp::Vec3D( -1.4921555711597957E-02,  1.1848292772968309E-02,  4.4048585763266203E-03));\n    e->forces.push_back(nnp::Vec3D(  3.9709176036333213E-03, -2.4921900328852234E-02, -3.8347739904269732E-03));\n    e->forces.push_back(nnp::Vec3D( -2.4360059992985073E-02, -5.8239379933207507E-03,  1.2366886594733190E-02));\n    e->forces.push_back(nnp::Vec3D(  2.8993502229084790E-02,  7.6515114590836684E-03,  9.5956845645098453E-03));\n    e->forces.push_back(nnp::Vec3D( -1.5046906409220380E-02, -3.9492001476203577E-03, -1.0842057962479310E-02));\n    e->forces.push_back(nnp::Vec3D( -1.5378658254934698E-02,  6.2436161555013666E-03, -4.2099986789991325E-03));\n    e->forces.push_back(nnp::Vec3D( -1.3361789127851699E-04, -1.6211463107775704E-02,  3.8312498923227543E-02));\n    e->forces.push_back(nnp::Vec3D(  2.8558262548831776E-02,  1.1076209002733001E-02,  7.1611260132349568E-03));\n    e->forces.push_back(nnp::Vec3D(  3.1911013378181446E-02,  8.8314461079023812E-03, -3.1034975265068496E-04));\n    e->forces.push_back(nnp::Vec3D(  1.0578081595825463E-02,  1.8225941237959679E-02, -2.3135541854024621E-02));\n    e->forces.push_back(nnp::Vec3D( -1.2012549255572708E-02, -6.9593414057787916E-03,  1.0844440106863088E-02));\n    e->forces.push_back(nnp::Vec3D( -5.3017231445205539E-03,  2.0851378486622052E-02,  1.1641080133825385E-02));\n    e->forces.push_back(nnp::Vec3D(  1.2258687986347759E-02, -9.8795128555179273E-03, -2.5651060955679171E-02));\n    e->forces.push_back(nnp::Vec3D( -2.6407642546722912E-02, -2.7733517313901227E-02, -7.2344958905847911E-04));\n    e->forces.push_back(nnp::Vec3D(  6.7570936418337689E-03,  2.4191090485936175E-02,  5.0604923764055315E-02));\n    e->forces.push_back(nnp::Vec3D( -1.6083142820508271E-02, -6.1141407498004393E-03,  1.3286269681182926E-02));\n    e->forces.push_back(nnp::Vec3D( -1.1354778243651754E-02, -1.1664504843099411E-02, -1.0706086426558480E-02));\n    e->forces.push_back(nnp::Vec3D( -1.4164959441590783E-02, -1.7236800332300854E-02,  2.2099839917759660E-02));\n    e->forces.push_back(nnp::Vec3D(  2.5955005699462019E-02, -7.7953430360518227E-03, -1.7316028835307886E-02));\n    e->forces.push_back(nnp::Vec3D( -3.8409728752714767E-04, -7.1871709215080189E-03,  2.4793099439475219E-02));\n    e->forces.push_back(nnp::Vec3D( -2.0139620462421209E-02, -2.3446129166273876E-02,  1.7511720126502862E-02));\n    e->forces.push_back(nnp::Vec3D(  1.5077939316150427E-02, -1.5451483139032673E-02, -1.8605061616847269E-03));\n    e->forces.push_back(nnp::Vec3D( -1.5258899892367360E-02,  4.3850898121453779E-03, -3.0740279205576800E-03));\n    e->forces.push_back(nnp::Vec3D(  2.3378496132104463E-03,  3.3954619300435959E-02,  7.8141632976951592E-03));\n    e->forces.push_back(nnp::Vec3D( -1.7845228349972191E-02,  3.4466935879122369E-02, -3.2956466513293876E-02));\n    e->forces.push_back(nnp::Vec3D(  1.5624547582211469E-02, -2.3899035662300151E-02, -2.1982412882615172E-02));\n    e->forces.push_back(nnp::Vec3D(  1.6823705452098180E-02, -1.8091862434702451E-02,  1.1095214976793479E-02));\n    e->forces.push_back(nnp::Vec3D(  1.5727187753047519E-03, -2.3189637239978147E-03,  1.2612578130822609E-02));\n    e->forces.push_back(nnp::Vec3D( -2.3666377504220584E-02,  1.6171057659681277E-02,  3.3191610197202813E-02));\n    e->forces.push_back(nnp::Vec3D( -2.4472973051202773E-03,  9.3147725725712463E-03, -1.2109597036509566E-02));\n    e->forces.push_back(nnp::Vec3D( -1.2625654414802361E-02,  3.0710557928563590E-02, -2.3788450117104763E-02));\n    e->forces.push_back(nnp::Vec3D( -1.8988279285503586E-02,  1.0697664633896835E-02,  1.6528080346788255E-02));\n    e->forces.push_back(nnp::Vec3D(  1.1646862748846682E-04, -1.3190591738461254E-02, -2.0633482993707757E-02));\n    e->forces.push_back(nnp::Vec3D( -1.4540377634038594E-02, -2.3349272174409120E-02,  1.2064866171145444E-02));\n    e->forces.push_back(nnp::Vec3D( -1.2742589148947731E-02,  7.1120562252603662E-03, -1.3136401679584219E-03));\n    e->forces.push_back(nnp::Vec3D( -3.5588414408979349E-02, -1.9742814344892355E-02, -2.2749022576574594E-02));\n    e->forces.push_back(nnp::Vec3D( -5.9042294097101352E-03,  1.5149181745981868E-02,  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3.0781670876435407E-02,  5.0820719326212472E-03));\n    e->forces.push_back(nnp::Vec3D(  2.3535176577779544E-02,  5.2922146053419120E-03, -2.2742905492197339E-03));\n    e->forces.push_back(nnp::Vec3D( -1.7681222989087890E-03,  5.7928963397461508E-04,  3.4660057397990617E-03));\n    e->forces.push_back(nnp::Vec3D(  3.7740628605457179E-03,  1.2003453609304611E-03, -3.2830480908393592E-02));\n    e->forces.push_back(nnp::Vec3D(  1.8727364347328800E-03, -1.7090026052045716E-02,  7.0150933746873168E-03));\n    e->forces.push_back(nnp::Vec3D(  3.7229078138817074E-03, -1.6192330450746098E-02, -3.4711803550697341E-02));\n    e->forces.push_back(nnp::Vec3D( -1.8411562284732126E-02, -3.5060811645125749E-02,  9.8768016958184889E-04));\n    e->forces.push_back(nnp::Vec3D( -3.1462626859183780E-03,  1.4342239909441829E-02,  4.3199191855711798E-02));\n    e->forces.push_back(nnp::Vec3D(  1.9597032126157415E-02,  4.4711843358852157E-02,  4.0999810937063251E-02));\n    e->forces.push_back(nnp::Vec3D(  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e->forces.push_back(nnp::Vec3D(  1.4588784276669113E-02,  2.1077194626944878E-02, -7.3097921036186881E-03));\n    e->forces.push_back(nnp::Vec3D(  5.4024817336361247E-03, -2.3408875465133895E-03,  4.8642501832850864E-03));\n    e->forces.push_back(nnp::Vec3D(  1.2629789509538598E-02, -2.0066179085219183E-03, -5.4316346582045372E-03));\n    e->forces.push_back(nnp::Vec3D(  5.4454146894422433E-04,  1.9798978892012845E-04,  7.6927455306268887E-03));\n    e->forces.push_back(nnp::Vec3D(  4.3296797897336634E-03, -4.1613794348871243E-03,  1.6293144745505816E-02));\n    e->forces.push_back(nnp::Vec3D(  1.6831803514603044E-02,  9.3198807279893433E-03, -2.7633282723161037E-02));\n    e->forces.push_back(nnp::Vec3D( -4.6105248242943701E-03,  3.8507021087744787E-03, -4.8594264141292110E-03));\n    e->forces.push_back(nnp::Vec3D( -1.1511344704394424E-02,  2.4638076238558682E-03, -1.2628278303704084E-02));\n    e->forces.push_back(nnp::Vec3D(  3.1640767286082554E-03,  3.2141171667319371E-03,  3.9050861122044683E-03));\n    e->forces.push_back(nnp::Vec3D(  1.2811258330148418E-02, -4.4689732863184154E-03, -6.6879619833609891E-03));\n    e->forces.push_back(nnp::Vec3D( -6.0876525510639744E-06, -3.6323599973631049E-02, -2.8018922334189570E-02));\n    e->forces.push_back(nnp::Vec3D( -1.6184881350645781E-02, -2.9483093256810061E-02,  1.5791566025144196E-02));\n    e->forces.push_back(nnp::Vec3D( -9.8324223588641072E-03, -7.8602362730982450E-03,  4.4919530222845491E-03));\n    e->forces.push_back(nnp::Vec3D(  1.0119636837391231E-03, -1.2972300537734172E-02,  1.5174595867937336E-04));\n    e->forces.push_back(nnp::Vec3D(  1.0203497305385638E-02, -1.6852111194225500E-02,  1.7478844307169793E-02));\n    e->forces.push_back(nnp::Vec3D(  5.4011871532361642E-03, -8.1700602081354878E-03, -8.0316935589987044E-03));\n    e->forces.push_back(nnp::Vec3D(  1.1568431621845822E-03, -1.0279132409758491E-02, -7.9050056956105996E-04));\n    e->forces.push_back(nnp::Vec3D(  5.2658324208805255E-03, -5.5280382311249689E-03, -2.4962340764173967E-03));\n    e->forces.push_back(nnp::Vec3D( -5.5927837939849338E-03,  9.0237442501118498E-03,  1.6486252895583371E-03));\n    e->forces.push_back(nnp::Vec3D( -7.1045435752922249E-03, -4.9960931626351411E-04,  1.0301674646098548E-02));\n    e->forces.push_back(nnp::Vec3D( -2.5681389118031401E-03, -1.2251782540703645E-03,  4.3914270621537556E-02));\n    e->forces.push_back(nnp::Vec3D( -2.1852763577357562E-02, -1.0389679676958228E-02, -1.9960787026074137E-02));\n    e->forces.push_back(nnp::Vec3D(  1.4716067181866769E-02,  7.4337124028601527E-03,  1.0083428149107249E-02));\n    e->forces.push_back(nnp::Vec3D(  2.5826837774328456E-03, -6.6722311472670994E-03, -1.5522225786543144E-02));\n    e->forces.push_back(nnp::Vec3D(  2.6349667971270772E-02, -2.5281963452956389E-02, -4.5661790345243791E-03));\n    e->forces.push_back(nnp::Vec3D(  1.2226889713978594E-02,  1.7105116391167872E-02, -4.8954931840448255E-05));\n    e->forces.push_back(nnp::Vec3D(  1.7382282743849665E-02, -9.2545373944752270E-03, -2.9727017410110496E-02));\n    e->forces.push_back(nnp::Vec3D( -9.2158569179213740E-03, -6.4830041038317614E-03,  3.0506953506698182E-03));\n    e->forces.push_back(nnp::Vec3D(  1.7966471186135057E-02, -4.9963454696210917E-04, -3.3519631194653147E-03));\n    e->forces.push_back(nnp::Vec3D(  2.2298818196425270E-02,  1.0389728770926823E-02, -7.2376962603359620E-03));\n    e->forces.push_back(nnp::Vec3D(  2.0491354094888042E-02,  5.9924357750703533E-03, -1.8063268772333069E-02));\n    e->forces.push_back(nnp::Vec3D( -5.9732238611338124E-03, -6.1431473978552304E-03, -1.7676442244663141E-03));\n    e->forces.push_back(nnp::Vec3D(  1.0717695457015286E-02,  1.6510638759147777E-02,  1.1507676802264406E-02));\n    e->forces.push_back(nnp::Vec3D( -1.6584299967407194E-03, -3.7419090641636820E-03,  4.8923504558683953E-03));\n    e->forces.push_back(nnp::Vec3D( -1.2726879314679822E-02, -5.9646127271104884E-03,  3.1941503799362931E-03));\n    e->forces.push_back(nnp::Vec3D( -7.2714735198775244E-03, -1.5210570091819342E-02, -1.4898835889997965E-02));\n    e->forces.push_back(nnp::Vec3D(  1.1329366432837275E-02,  1.2356113630470365E-02, -6.2630111258791896E-03));\n    e->forces.push_back(nnp::Vec3D(  5.8141788604463744E-03,  9.8568567125357338E-04,  7.8869450485235058E-03));\n    e->forces.push_back(nnp::Vec3D( -3.8618405473709915E-03,  2.4149825410788870E-03,  9.5567267987710612E-03));\n    e->forces.push_back(nnp::Vec3D( -2.4328290268836859E-03, -4.0491267992584653E-04,  3.1656493199821597E-03));\n    e->forces.push_back(nnp::Vec3D(  1.8485303393385637E-03, -2.3351128505762014E-03,  5.1479035928314173E-03));\n    e->forces.push_back(nnp::Vec3D(  5.2161473671328683E-04, -6.6542893828756998E-03,  3.3564749428621281E-03));\n    e->forces.push_back(nnp::Vec3D(  2.1240356740773476E-02,  2.8616983095602583E-02, -1.5357075566902509E-02));\n    e->forces.push_back(nnp::Vec3D( -1.5469662544688212E-02, -2.7467212433434198E-03,  4.7570558380814780E-03));\n    e->forces.push_back(nnp::Vec3D( -2.1714461018323330E-03,  1.6855392133189966E-02,  2.1042889047887439E-02));\n    e->forces.push_back(nnp::Vec3D( -7.5181694814496812E-03, -2.9665461369772985E-03, -9.1017624667947342E-03));\n    e->forces.push_back(nnp::Vec3D(  4.1655635331801378E-03, -1.4978396634405335E-02, -3.0214506338990506E-03));\n    e->forces.push_back(nnp::Vec3D(  1.2359854101127625E-03,  2.2199619927810992E-02,  7.7902990012139366E-03));\n    e->forces.push_back(nnp::Vec3D(  1.5316325873564695E-02,  3.0973979639290672E-03, -5.2450074356845686E-03));\n    e->forces.push_back(nnp::Vec3D(  1.3025333809043048E-02, -1.8660022167836861E-03, -7.6147343244483490E-03));\n    e->forces.push_back(nnp::Vec3D( -6.9444504154228398E-03, -6.4123564463277683E-03, -5.8091494093953436E-03));\n    e->forces.push_back(nnp::Vec3D( -5.5028163599383341E-03,  6.6070264946364891E-03, -5.6369655842955519E-03));\n    e->forces.push_back(nnp::Vec3D(  9.7502494957671885E-03, -1.6651822052838265E-02,  5.4856140546144022E-03));\n    e->forces.push_back(nnp::Vec3D(  1.0788894855242935E-03, -9.1434571814460238E-03,  6.5586033988592630E-03));\n    e->forces.push_back(nnp::Vec3D(  8.1807365825944632E-03, -8.7867241010995828E-03,  1.0456230791574872E-02));\n    e->forces.push_back(nnp::Vec3D(  3.3870431454436738E-03, -5.9615917643709168E-04, -1.1035224459592071E-02));\n    e->forces.push_back(nnp::Vec3D( -1.0927953738342659E-02, -9.6790342570279766E-03, -4.5953305751015852E-03));\n    e->forces.push_back(nnp::Vec3D(  1.5199780363761605E-02, -4.1973785669286790E-05, -1.5619873588471545E-02));\n    e->forces.push_back(nnp::Vec3D(  3.6542198967157982E-03, -1.6687159162134643E-03, -1.0420282107274737E-02));\n    e->forces.push_back(nnp::Vec3D( -3.7922652507531166E-03, -3.3675089661922633E-02,  5.4954816065430068E-03));\n    e->forces.push_back(nnp::Vec3D( -6.6834998375641550E-03, -3.2951642919293324E-03, -1.0878149495034109E-02));\n    e->forces.push_back(nnp::Vec3D( -4.3891870200234016E-04, -4.1652049632060987E-03, -6.8216217355209739E-03));\n    e->forces.push_back(nnp::Vec3D( -1.1797555701444855E-02,  9.5138962156206697E-03, -9.9094286541992881E-03));\n    e->forces.push_back(nnp::Vec3D( -4.0801804868116241E-03,  1.9525928185017908E-03,  3.1833817676042019E-03));\n    e->forces.push_back(nnp::Vec3D(  7.0148340774325701E-03,  9.9828872038024447E-03,  8.9001842309826729E-05));\n    e->forces.push_back(nnp::Vec3D( -1.2383625983817434E-02, -5.0667809410078349E-03,  1.3293212485518910E-02));\n    e->forces.push_back(nnp::Vec3D( -1.9671052231297208E-02, -5.9935671765716592E-03, -2.7299329475672755E-03));\n    e->forces.push_back(nnp::Vec3D(  2.0978098146188975E-02,  4.1809954671831858E-04,  5.3590218010518562E-03));\n    e->forces.push_back(nnp::Vec3D( -3.7533620864920367E-03, -5.2026372363296722E-04,  1.2392546612402544E-03));\n    e->forces.push_back(nnp::Vec3D( -9.6705082975955554E-03,  4.5240105739386190E-03,  5.7821207858049888E-03));\n    e->forces.push_back(nnp::Vec3D(  7.7142947055271714E-03, -1.1361051388691900E-02, -9.1902791839345351E-03));\n    e->forces.push_back(nnp::Vec3D( -2.0975030858652325E-02,  3.3062540955107678E-04,  2.4678187155939928E-02));\n    e->forces.push_back(nnp::Vec3D( -1.3437982209496567E-02,  1.1159231015158513E-03, -5.5022034210186980E-03));\n    e->forces.push_back(nnp::Vec3D( -2.9347084764982548E-03, -6.5216668566338383E-03, -1.6703925088377092E-02));\n    e->forces.push_back(nnp::Vec3D( -4.3801929648068149E-03, -5.5323071836863875E-03,  4.9014657009306068E-03));\n    e->forces.push_back(nnp::Vec3D( -1.4033839561424590E-02, -1.5691992622600876E-03, -7.2210134939627970E-03));\n    e->forces.push_back(nnp::Vec3D( -2.8571564691094280E-03, -1.6066809778975153E-02,  1.1316410334331676E-02));\n    e->forces.push_back(nnp::Vec3D( -5.8916043623124994E-03,  3.2240109691863152E-03,  1.1748372405408814E-02));\n    e->forces.push_back(nnp::Vec3D(  1.2914049035837394E-02,  1.6182413510179339E-02, -3.7379105598865411E-02));\n    e->forces.push_back(nnp::Vec3D( -5.0404904032028347E-03, -5.9293598540896605E-03, -9.9902967705286245E-03));\n    e->forces.push_back(nnp::Vec3D(  5.1056173057021821E-03,  1.4270417838853430E-02,  1.7506347679668622E-02));\n    e->forces.push_back(nnp::Vec3D(  6.9274241023844943E-04, -1.4630832524440760E-02, -1.6278469908022199E-03));\n    e->forces.push_back(nnp::Vec3D( -3.8997192795223000E-04,  1.3148011113507730E-02, -5.1469262013868269E-03));\n    e->forces.push_back(nnp::Vec3D(  2.5270346780235176E-03,  8.4851270660284729E-03, -9.6909182503258414E-03));\n    e->forces.push_back(nnp::Vec3D(  9.3003676153253414E-03, -2.4671354409701416E-03,  2.5551747032578724E-03));\n    e->forces.push_back(nnp::Vec3D(  7.9148375445665161E-03, -2.6163083762413830E-03,  1.3236216760648557E-02));\n    e->forces.push_back(nnp::Vec3D( -2.4949999720047639E-03,  1.7569262227404496E-03,  2.4243143935810121E-04));\n    e->forces.push_back(nnp::Vec3D(  9.8779045954541290E-04,  1.1455776807989429E-03,  1.6734916013697611E-02));\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/ExampleScreeningFunction.h",
    "content": "#ifndef EXAMPLESCREENINGFUNCTION_H\n#define EXAMPLESCREENINGFUNCTION_H\n\n#include <vector>\n#include \"Example.h\"\n#include \"BoostDataContainer.h\"\n#include \"ScreeningFunction.h\"\n\ndouble const radiusInner = 4.8;      // Inner limit of transition region.\ndouble const radiusOuter = 8.0;      // Outer limit of transition region.\ndouble const testRadius = 7.0;       // Inside transition region.\ndouble const testRadiusBelow = 2.0;  // Below transition region.\ndouble const testRadiusAbove = 10.0; // Above transition region.\n\nstruct ExampleScreeningFunction : public Example\n{\n    std::string            type;\n    double                 inner;\n    double                 outer;\n    double                 rt;\n    double                 rtbelow;\n    double                 rtabove;\n    double                 f;\n    double                 df;\n    nnp::ScreeningFunction fs;\n\n    ExampleScreeningFunction();\n\n    ExampleScreeningFunction(std::string name) : \n        inner  (radiusInner    ),\n        outer  (radiusOuter    ),\n        rt     (testRadius     ),\n        rtbelow(testRadiusBelow),\n        rtabove(testRadiusAbove)\n    {\n        this->name = name;\n        this->description = std::string(\"ScreeningFunction example \\\"\")\n                          + this->name\n                          + \"\\\"\";\n    }\n};\n\ntemplate<>\nvoid BoostDataContainer<ExampleScreeningFunction>::setup()\n{\n    ExampleScreeningFunction* e = nullptr;\n\n    examples.push_back(ExampleScreeningFunction(\"Cosine\"));\n    e = &(examples.back());\n    e->type = \"c\";\n    e->f = 7.7778511650980120E-01;\n    e->df = 4.0814669151450456E-01;\n    e->fs.setInnerOuter(e->inner, e->outer);\n    e->fs.setCoreFunction(e->type);\n\n    examples.push_back(ExampleScreeningFunction(\"Polynomial 1\"));\n    e = &(examples.back());\n    e->type = \"p1\";\n    e->f = 7.6806640625000011E-01;\n    e->df = 4.0283203124999994E-01;\n    e->fs.setInnerOuter(e->inner, e->outer);\n    e->fs.setCoreFunction(e->type);\n\n    examples.push_back(ExampleScreeningFunction(\"Polynomial 2\"));\n    e = &(examples.back());\n    e->type = \"p2\";\n    e->f = 8.1999397277832031E-01;\n    e->df = 4.3272972106933594E-01;\n    e->fs.setInnerOuter(e->inner, e->outer);\n    e->fs.setCoreFunction(e->type);\n\n    examples.push_back(ExampleScreeningFunction(\"Polynomial 3\"));\n    e = &(examples.back());\n    e->type = \"p3\";\n    e->f = 8.5718168318271637E-01;\n    e->df = 4.3385662138462061E-01;\n    e->fs.setInnerOuter(e->inner, e->outer);\n    e->fs.setCoreFunction(e->type);\n\n    examples.push_back(ExampleScreeningFunction(\"Polynomial 4\"));\n    e = &(examples.back());\n    e->type = \"p4\";\n    e->f = 8.8514509823289700E-01;\n    e->df = 4.1945122575270932E-01;\n    e->fs.setInnerOuter(e->inner, e->outer);\n    e->fs.setCoreFunction(e->type);\n\n    examples.push_back(ExampleScreeningFunction(\"Exponential window\"));\n    e = &(examples.back());\n    e->type = \"e\";\n    e->f = 5.9192173471535003E-01;\n    e->df = 6.3053409878824362E-01;\n    e->fs.setInnerOuter(e->inner, e->outer);\n    e->fs.setCoreFunction(e->type);\n\n    return;\n}\n\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_lammps_hdnnp.h",
    "content": "#ifndef EXAMPLE_LAMMPS_HDNNP_H\n#define EXAMPLE_LAMMPS_HDNNP_H\n\n#include \"Example.h\"\n#include \"BoostDataContainer.h\"\n\nstruct Example_lammps_hdnnp : public Example\n{\n    std::string tool;\n    std::string command;\n    std::string args;\n    std::string pathBin;\n    std::string pathData;\n\n    std::size_t lastTimeStep;\n    double      potentialEnergy;\n    double      totalEnergy;\n\n    Example_lammps_hdnnp(std::string name) :\n        pathBin(\"../../../bin\"),\n        pathData(\"../../examples/interface-LAMMPS/\")\n    {\n        this->name = name;\n        this->tool = \"lmp_mpi\";\n        this->description = std::string(\"Test example \\\"\")\n                          + this->name\n                          + \"\\\" with tool \\\"\"\n                          + this->tool + \"\\\"\";\n        this->command = pathBin + \"/\" + this->tool;\n        this->pathData += \"/\" + this->name;\n    }\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_lammps_hdnnp>::setup()\n{\n    Example_lammps_hdnnp* e = nullptr;\n\n    examples.push_back(Example_lammps_hdnnp(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"-in md.lmp \";\n    e->lastTimeStep = 5;\n    e->potentialEnergy = -6000559.4;\n    e->totalEnergy = -6000220.2;\n\n    examples.push_back(Example_lammps_hdnnp(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->args = \"-in md.lmp \";\n    e->lastTimeStep = 100;\n    e->potentialEnergy = -574.21185;\n    e->totalEnergy = -573.6561;\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp.h",
    "content": "#ifndef EXAMPLE_NNP_H\n#define EXAMPLE_NNP_H\n\n#include \"Example.h\"\n\nstruct Example_nnp : public Example\n{\n    std::string tool;\n    std::string command;\n    std::string args;\n    std::string pathBin;\n    std::string pathData;\n\n    Example_nnp();\n\n    Example_nnp(std::string tool, std::string name) : \n        pathBin(\"../../../bin\"),\n        pathData(\"../../examples\")\n    {\n        this->name = name;\n        this->tool = tool; \n        this->description = std::string(\"Test example \\\"\")\n                          + this->name\n                          + \"\\\" with tool \\\"\"\n                          + this->tool + \"\\\"\";\n        this->command = pathBin + \"/\" + this->tool;\n        this->pathData += \"/\" + this->tool + \"/\" + this->name;\n    }\n};\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_atomenv.h",
    "content": "#ifndef EXAMPLE_NNP_ATOMENV_H\n#define EXAMPLE_NNP_ATOMENV_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n#include <map>\n#include <string>\n#include <utility>\n\nstruct Example_nnp_atomenv : public Example_nnp\n{\n    std::vector<std::string>                 elements;\n    std::map<std::string, std::size_t>       numSF;\n    std::map<\n        std::pair<std::string, std::string>,\n        std::pair<std::size_t, std::size_t>> neighCut;\n\n    Example_nnp_atomenv(std::string name)\n        : Example_nnp(\"nnp-atomenv\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_atomenv>::setup()\n{\n    Example_nnp_atomenv* e = nullptr;\n\n    examples.push_back(Example_nnp_atomenv(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"100 6 2 4 4 \";\n    e->elements.push_back(\"H\");\n    e->elements.push_back(\"O\");\n    e->numSF[\"H\"] = 27;\n    e->numSF[\"O\"] = 30;\n    e->neighCut[std::make_pair(\"H\", \"H\")] = std::make_pair(6, 15);\n    e->neighCut[std::make_pair(\"H\", \"O\")] = std::make_pair(2, 19);\n    e->neighCut[std::make_pair(\"O\", \"H\")] = std::make_pair(4, 18);\n    e->neighCut[std::make_pair(\"O\", \"O\")] = std::make_pair(4, 16);\n\n    examples.push_back(Example_nnp_atomenv(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->args = \"100 12 6 3 6 \";\n    e->elements.push_back(\"S\");\n    e->elements.push_back(\"Cu\");\n    e->numSF[\"S\"]  = 72;\n    e->numSF[\"Cu\"] = 66;\n    e->neighCut[std::make_pair(\"S\" , \"S\" )] = std::make_pair(12, 48);\n    e->neighCut[std::make_pair(\"S\" , \"Cu\")] = std::make_pair( 6, 47);\n    e->neighCut[std::make_pair(\"Cu\", \"S\" )] = std::make_pair( 3, 45);\n    e->neighCut[std::make_pair(\"Cu\", \"Cu\")] = std::make_pair( 6, 38);\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_checkdw.h",
    "content": "#ifndef EXAMPLE_NNP_CHECKDW_H\n#define EXAMPLE_NNP_CHECKDW_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n\nstruct Example_nnp_checkdw : public Example_nnp\n{\n    Example_nnp_checkdw(std::string name)\n        : Example_nnp(\"nnp-checkdw\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_checkdw>::setup()\n{\n    Example_nnp_checkdw* e = nullptr;\n\n    // Way too slow for CI test.\n    //examples.push_back(Example_nnp_checkdw(\"H2O_RPBE-D3\"));\n    //e = &(examples.back());\n    //e->args = \"0 \";\n\n    examples.push_back(Example_nnp_checkdw(\"LJ\"));\n    e = &(examples.back());\n    e->args = \"0 \";\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_checkf.h",
    "content": "#ifndef EXAMPLE_NNP_CHECKF_H\n#define EXAMPLE_NNP_CHECKF_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n\nstruct Example_nnp_checkf : public Example_nnp\n{\n    Example_nnp_checkf(std::string name)\n        : Example_nnp(\"nnp-checkf\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_checkf>::setup()\n{\n    Example_nnp_checkf* e = nullptr;\n\n    examples.push_back(Example_nnp_checkf(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"\";\n\n    examples.push_back(Example_nnp_checkf(\"LJ\"));\n    e = &(examples.back());\n    e->args = \"\";\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_convert.h",
    "content": "#ifndef EXAMPLE_NNP_CONVERT_H\n#define EXAMPLE_NNP_CONVERT_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n#include <vector>\n\nstruct Example_nnp_convert : public Example_nnp\n{\n    std::vector<std::string> createdFiles;\n\n    Example_nnp_convert(std::string name)\n        : Example_nnp(\"nnp-convert\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_convert>::setup()\n{\n    Example_nnp_convert* e = nullptr;\n\n    examples.push_back(Example_nnp_convert(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->args = \"xyz S Cu \";\n    e->createdFiles.push_back(\"input.xyz\");\n\n    examples.push_back(Example_nnp_convert(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->args = \"poscar S Cu \";\n    e->createdFiles.push_back(\"POSCAR_1\");\n    e->createdFiles.push_back(\"POSCAR_20\");\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_dataset.h",
    "content": "#ifndef EXAMPLE_NNP_DATASET_H\n#define EXAMPLE_NNP_DATASET_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n\nstruct Example_nnp_dataset : public Example_nnp\n{\n    Example_nnp_dataset(std::string name)\n        : Example_nnp(\"nnp-dataset\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_dataset>::setup()\n{\n    Example_nnp_dataset* e = nullptr;\n\n    examples.push_back(Example_nnp_dataset(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"0 \";\n\n    examples.push_back(Example_nnp_dataset(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->args = \"0 \";\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_dist.h",
    "content": "#ifndef EXAMPLE_NNP_DIST_H\n#define EXAMPLE_NNP_DIST_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n#include <vector>\n\nstruct Example_nnp_dist : public Example_nnp\n{\n    std::vector<std::string> createdFiles;\n\n    Example_nnp_dist(std::string name)\n        : Example_nnp(\"nnp-dist\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_dist>::setup()\n{\n    Example_nnp_dist* e = nullptr;\n\n    examples.push_back(Example_nnp_dist(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"12.0 200 1 H O \";\n    e->createdFiles.push_back(\"rdf_H_H.out\");\n    e->createdFiles.push_back(\"rdf_H_O.out\");\n    e->createdFiles.push_back(\"rdf_O_O.out\");\n    e->createdFiles.push_back(\"adf_H_H_H.out\");\n    e->createdFiles.push_back(\"adf_H_H_O.out\");\n    e->createdFiles.push_back(\"adf_H_O_O.out\");\n    e->createdFiles.push_back(\"adf_O_H_H.out\");\n    e->createdFiles.push_back(\"adf_O_H_O.out\");\n    e->createdFiles.push_back(\"adf_O_O_O.out\");\n\n    examples.push_back(Example_nnp_dist(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->args = \"6.0 200 1 S Cu \";\n    e->createdFiles.push_back(\"rdf_S_S.out\");\n    e->createdFiles.push_back(\"rdf_S_Cu.out\");\n    e->createdFiles.push_back(\"rdf_Cu_Cu.out\");\n    e->createdFiles.push_back(\"adf_S_S_S.out\");\n    e->createdFiles.push_back(\"adf_S_S_Cu.out\");\n    e->createdFiles.push_back(\"adf_S_Cu_Cu.out\");\n    e->createdFiles.push_back(\"adf_Cu_S_S.out\");\n    e->createdFiles.push_back(\"adf_Cu_S_Cu.out\");\n    e->createdFiles.push_back(\"adf_Cu_Cu_Cu.out\");\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_norm.h",
    "content": "#ifndef EXAMPLE_NNP_DIST_H\n#define EXAMPLE_NNP_DIST_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n#include <vector>\n\nstruct Example_nnp_norm : public Example_nnp\n{\n    std::vector<std::string> createdFiles;\n\n    Example_nnp_norm(std::string name)\n        : Example_nnp(\"nnp-norm\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_norm>::setup()\n{\n    Example_nnp_norm* e = nullptr;\n\n    examples.push_back(Example_nnp_norm(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->createdFiles.push_back(\"evsv.dat\");\n    e->createdFiles.push_back(\"input.nn.bak\");\n    e->createdFiles.push_back(\"output.data\");\n\n    examples.push_back(Example_nnp_norm(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->createdFiles.push_back(\"evsv.dat\");\n    e->createdFiles.push_back(\"input.nn.bak\");\n    e->createdFiles.push_back(\"output.data\");\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_predict.h",
    "content": "#ifndef EXAMPLE_NNP_DIST_H\n#define EXAMPLE_NNP_DIST_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n#include <vector>\n\nstruct Example_nnp_predict : public Example_nnp\n{\n    double                   energy;\n    std::vector<std::string> createdFiles;\n\n    Example_nnp_predict(std::string name)\n        : Example_nnp(\"nnp-predict\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_predict>::setup()\n{\n    Example_nnp_predict* e = nullptr;\n\n    examples.push_back(Example_nnp_predict(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"0 \";\n    e->energy = -2.7564547347815904E+04;\n    e->createdFiles.push_back(\"energy.out\");\n    e->createdFiles.push_back(\"nnatoms.out\");\n    e->createdFiles.push_back(\"nnforces.out\");\n    e->createdFiles.push_back(\"output.data\");\n\n    examples.push_back(Example_nnp_predict(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->args = \"0 \";\n    e->energy = -5.7365603183874578E+02;\n    e->createdFiles.push_back(\"energy.out\");\n    e->createdFiles.push_back(\"nnatoms.out\");\n    e->createdFiles.push_back(\"nnforces.out\");\n    e->createdFiles.push_back(\"output.data\");\n\n    examples.push_back(Example_nnp_predict(\"Anisole_SCAN\"));\n    e = &(examples.back());\n    e->args = \"0 \";\n    e->energy = -9.6749614724733078E+02;\n    e->createdFiles.push_back(\"energy.out\");\n    e->createdFiles.push_back(\"nnatoms.out\");\n    e->createdFiles.push_back(\"nnforces.out\");\n    e->createdFiles.push_back(\"output.data\");\n\n    examples.push_back(Example_nnp_predict(\"DMABN_SCAN\"));\n    e = &(examples.back());\n    e->args = \"0 \";\n    e->energy = -7.6864264790108564E+01;\n    e->createdFiles.push_back(\"energy.out\");\n    e->createdFiles.push_back(\"nnatoms.out\");\n    e->createdFiles.push_back(\"nnforces.out\");\n    e->createdFiles.push_back(\"output.data\");\n\n    examples.push_back(Example_nnp_predict(\"Ethylbenzene_SCAN\"));\n    e = &(examples.back());\n    e->args = \"0 \";\n    e->energy = -8.2198742206281679E+02;\n    e->createdFiles.push_back(\"energy.out\");\n    e->createdFiles.push_back(\"nnatoms.out\");\n    e->createdFiles.push_back(\"nnforces.out\");\n    e->createdFiles.push_back(\"output.data\");\n\n    examples.push_back(Example_nnp_predict(\"H2O_RPBE-D3_4G\"));\n    e = &(examples.back());\n    e->args = \"0 \";\n    e->energy = -9.8016327504792771E+03;\n    e->createdFiles.push_back(\"energy.out\");\n    e->createdFiles.push_back(\"nnatoms.out\");\n    e->createdFiles.push_back(\"nnforces.out\");\n    e->createdFiles.push_back(\"output.data\");\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_prune.h",
    "content": "#ifndef EXAMPLE_NNP_DIST_H\n#define EXAMPLE_NNP_DIST_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n#include <vector>\n\nstruct Example_nnp_prune : public Example_nnp\n{\n    std::vector<std::string> createdFiles;\n\n    Example_nnp_prune(std::string name)\n        : Example_nnp(\"nnp-prune\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_prune>::setup()\n{\n    Example_nnp_prune* e = nullptr;\n\n    examples.push_back(Example_nnp_prune(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"range 1.0E-1 \";\n    e->createdFiles.push_back(\"output-prune-range.nn\");\n\n    examples.push_back(Example_nnp_prune(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"sensitivity 0.5 max \";\n    e->createdFiles.push_back(\"output-prune-sensitivity.nn\");\n\n    examples.push_back(Example_nnp_prune(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->args = \"range 1.0E-1 \";\n    e->createdFiles.push_back(\"output-prune-range.nn\");\n\n    examples.push_back(Example_nnp_prune(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->args = \"sensitivity 0.5 max \";\n    e->createdFiles.push_back(\"output-prune-sensitivity.nn\");\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_scaling.h",
    "content": "#ifndef EXAMPLE_NNP_SCALING_H\n#define EXAMPLE_NNP_SCALING_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n\nstruct Example_nnp_scaling : public Example_nnp\n{\n    Example_nnp_scaling(std::string name)\n        : Example_nnp(\"nnp-scaling\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_scaling>::setup()\n{\n    Example_nnp_scaling* e = nullptr;\n\n    examples.push_back(Example_nnp_scaling(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"100 \";\n\n    examples.push_back(Example_nnp_scaling(\"Cu2S_PBE\"));\n    e = &(examples.back());\n    e->args = \"100 \";\n\n    examples.push_back(Example_nnp_scaling(\"LJ\"));\n    e = &(examples.back());\n    e->args = \"100 \";\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_select.h",
    "content": "#ifndef EXAMPLE_NNP_DIST_H\n#define EXAMPLE_NNP_DIST_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n#include <vector>\n\nstruct Example_nnp_select : public Example_nnp\n{\n    std::vector<std::string> createdFiles;\n\n    Example_nnp_select(std::string name)\n        : Example_nnp(\"nnp-select\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_select>::setup()\n{\n    Example_nnp_select* e = nullptr;\n\n    examples.push_back(Example_nnp_select(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"interval 5 \";\n    e->createdFiles.push_back(\"output.data\");\n    e->createdFiles.push_back(\"reject.data\");\n\n    examples.push_back(Example_nnp_select(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"random 0.5 123 \";\n    e->createdFiles.push_back(\"output.data\");\n    e->createdFiles.push_back(\"reject.data\");\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_symfunc.h",
    "content": "#ifndef EXAMPLE_NNP_DIST_H\n#define EXAMPLE_NNP_DIST_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n#include <vector>\n\nstruct Example_nnp_symfunc : public Example_nnp\n{\n    std::vector<std::string> createdFiles;\n\n    Example_nnp_symfunc(std::string name)\n        : Example_nnp(\"nnp-symfunc\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_symfunc>::setup()\n{\n    Example_nnp_symfunc* e = nullptr;\n\n    examples.push_back(Example_nnp_symfunc(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->args = \"200 \";\n    e->createdFiles.push_back(\"sf.001.0001.out\");\n    e->createdFiles.push_back(\"sf.001.0027.out\");\n    e->createdFiles.push_back(\"sf.008.0001.out\");\n    e->createdFiles.push_back(\"sf.008.0030.out\");\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/Example_nnp_train.h",
    "content": "#ifndef EXAMPLE_NNP_TRAIN_H\n#define EXAMPLE_NNP_TRAIN_H\n\n#include \"Example_nnp.h\"\n#include \"BoostDataContainer.h\"\n\n#include <limits>  // std::numeric_limits\n\nstruct Example_nnp_train : public Example_nnp\n{\n    std::size_t lastEpoch;\n    double      rmseChargesTrain;\n    double      rmseChargesTest;\n    double      rmseEnergyTrain;\n    double      rmseEnergyTest;\n    double      rmseForcesTrain;\n    double      rmseForcesTest;\n    double      accuracy;\n\n    Example_nnp_train(std::string name) : Example_nnp(\"nnp-train\", name) {};\n};\n\ntemplate<>\nvoid BoostDataContainer<Example_nnp_train>::setup()\n{\n    Example_nnp_train* e = nullptr;\n\n    examples.push_back(Example_nnp_train(\"LJ\"));\n    e = &(examples.back());\n    e->lastEpoch = 10;\n    e->rmseEnergyTrain = 1.70594742E-03;\n    e->rmseEnergyTest  = 1.22642208E-03;\n    e->rmseForcesTrain = 3.77302629E-02;\n    e->rmseForcesTest  = 2.25135617E-01;\n    e->accuracy        = 10.0 * std::numeric_limits<double>::epsilon();\n\n    examples.push_back(Example_nnp_train(\"H2O_RPBE-D3\"));\n    e = &(examples.back());\n    e->lastEpoch = 2;\n    e->rmseEnergyTrain = 7.19539183E-04;\n    e->rmseEnergyTest  = 3.57910403E-04;\n    e->rmseForcesTrain = 2.46334310E-02;\n    e->rmseForcesTest  = 1.22544569E-02;\n    e->accuracy        = 1.0E-8;\n\n    examples.push_back(Example_nnp_train(\"H2O_RPBE-D3_norm-force\"));\n    e = &(examples.back());\n    e->lastEpoch = 2;\n    e->rmseEnergyTrain = 3.02402814E-04;\n    e->rmseEnergyTest  = 1.01753064E-04;\n    e->rmseForcesTrain = 6.08971134E-03;\n    e->rmseForcesTest  = 4.60947053E-03;\n    e->accuracy        = 100.0 * std::numeric_limits<double>::epsilon();\n\n    examples.push_back(Example_nnp_train(\"H2O_RPBE-D3_4G\"));\n    e = &(examples.back());\n    e->args = \"1\";\n    e->lastEpoch = 10;\n    e->rmseChargesTrain = 3.60544679E-04;\n    e->rmseChargesTest  = 4.60549641E-04;\n    e->accuracy        = 100.0 * std::numeric_limits<double>::epsilon();\n\n    examples.push_back(Example_nnp_train(\"H2O_RPBE-D3_4G\"));\n    e = &(examples.back());\n    e->args = \"2\";\n    e->lastEpoch = 10;\n    e->rmseEnergyTrain = 2.15640267E-05;\n    e->rmseEnergyTest  = 1.30155783E-05;\n    e->rmseForcesTrain = 2.07286126E-04;\n    e->rmseForcesTest  = 2.20371908E-04;\n    e->accuracy        = 1E-13;\n\n    return;\n}\n\n#endif\n"
  },
  {
    "path": "test/cpp/fileHelpers.h",
    "content": "#ifndef FILEHELPERS_H\n#define FILEHELPERS_H\n\n#include <iostream>\n#include <boost/filesystem.hpp>\n#include <string>\n\nnamespace bfs = boost::filesystem;\n\nbool copy_directory_recursively(bfs::path const& src, bfs::path const& dest)\n{\n    try\n    {\n        if(!bfs::exists(src) || !bfs::is_directory(src))\n        {\n            std::cerr << \"Source directory \" << src.string()\n                      << \" does not exist or is not a directory.\\n\";\n            return false;\n        }\n        if(bfs::exists(dest))\n        {\n            std::cerr << \"Destination directory \" << dest.string()\n                      << \" already exists.\\n\";\n            return false;\n        }\n        if(!bfs::create_directory(dest))\n        {\n            std::cerr << \"Unable to create destination directory\"\n                      << dest.string() << '\\n';\n            return false;\n        }\n    }\n    catch(bfs::filesystem_error const & e)\n    {\n        std::cerr << e.what() << '\\n';\n        return false;\n    }\n    for(bfs::directory_iterator file(src);\n        file != bfs::directory_iterator(); ++file)\n    {\n        try\n        {\n            bfs::path current(file->path());\n            if(bfs::is_directory(current))\n            {\n                if(!copy_directory_recursively(current,\n                                               dest / current.filename()))\n                {\n                    return false;\n                }\n            }\n            else\n            {\n                bfs::copy_file(current, dest / current.filename());\n            }\n        }\n        catch(bfs::filesystem_error const & e)\n        {\n            std::cerr << e.what() << '\\n';\n        }\n    }\n    return true;\n}\n\nstruct FixtureRepairDir\n{\n    FixtureRepairDir()\n    {\n        std::string p = bfs::current_path().string();\n        if (p.substr(p.size() - 4) == \"test\")\n        {\n            bfs::current_path(\"..\");\n            bfs::remove_all(\"test\");\n        }\n        else if (bfs::exists(\"test\"))\n        {\n            bfs::remove_all(\"test\");\n        }\n    }\n\n};\n\n#endif\n"
  },
  {
    "path": "test/cpp/fixtures.h",
    "content": "#ifndef FIXTURES_H\n#define FIXTURES_H\n\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"Structure.h\"\n\nusing namespace std;\nusing namespace nnp;\n\nstruct FixtureThreeAtomsMono\n{\n    FixtureThreeAtomsMono()\n    {\n        em.registerElements(\"H\");\n        s.setElementMap(em);\n\n        // Atom 1.\n        s.atoms.push_back(Atom());\n        s.atoms.back().numNeighborsPerElement.resize(em.size());\n        s.numAtoms++;\n        s.numAtomsPerElement[0]++;\n\n        // Atom 2.\n        s.atoms.push_back(Atom());\n        s.atoms.back().r[0] = 1.0;\n        s.atoms.back().r[1] = 2.0;\n        s.atoms.back().r[2] = 1.0;\n        s.atoms.back().index = 1;\n        s.atoms.back().numNeighborsPerElement.resize(em.size());\n        s.numAtoms++;\n        s.numAtomsPerElement[0]++;\n\n        // Atom 3.\n        s.atoms.push_back(Atom());\n        s.atoms.back().r[0] = 0.0;\n        s.atoms.back().r[1] = 3.0;\n        s.atoms.back().r[2] = -1.0;\n        s.atoms.back().index = 2;\n        s.atoms.back().numNeighborsPerElement.resize(em.size());\n        s.numAtoms++;\n        s.numAtomsPerElement[0]++;\n\n        // Calculate neighbor list.\n        s.calculateNeighborList(10.0);\n    }\n    ~FixtureThreeAtomsMono() {};\n\n    ElementMap em;\n    Structure s;\n};\n\nstruct FixtureThreeAtomsDual\n{\n    FixtureThreeAtomsDual()\n    {\n        em.registerElements(\"H He\");\n        s.setElementMap(em);\n\n        // Atom 1.\n        s.atoms.push_back(Atom());\n        s.atoms.back().numNeighborsPerElement.resize(em.size());\n        s.numAtoms++;\n        s.numAtomsPerElement[0]++;\n\n        // Atom 2.\n        s.atoms.push_back(Atom());\n        s.atoms.back().r[0] = 1.0;\n        s.atoms.back().r[1] = 2.0;\n        s.atoms.back().r[2] = 1.0;\n        s.atoms.back().index = 1;\n        s.atoms.back().element = 1;\n        s.atoms.back().numNeighborsPerElement.resize(em.size());\n        s.numAtoms++;\n        s.numAtomsPerElement[0]++;\n\n        // Atom 3.\n        s.atoms.push_back(Atom());\n        s.atoms.back().r[0] = 0.0;\n        s.atoms.back().r[1] = 3.0;\n        s.atoms.back().r[2] = -1.0;\n        s.atoms.back().index = 2;\n        s.atoms.back().element = 1;\n        s.atoms.back().numNeighborsPerElement.resize(em.size());\n        s.numAtoms++;\n        s.numAtomsPerElement[0]++;\n\n        // Calculate neighbor list.\n        s.calculateNeighborList(10.0);\n    }\n    ~FixtureThreeAtomsDual() {};\n\n    ElementMap em;\n    Structure s;\n};\n\nstruct FixtureFourAtomsMixed\n{\n    FixtureFourAtomsMixed()\n    {\n        em.registerElements(\"S Cu U\");\n        s.setElementMap(em);\n\n        // Atom 1.\n        s.atoms.push_back(Atom());\n        s.atoms.back().numNeighborsPerElement.resize(em.size());\n        s.numAtoms++;\n        s.numAtomsPerElement[0]++;\n\n        // Atom 2.\n        s.atoms.push_back(Atom());\n        s.atoms.back().r[0] = 1.0;\n        s.atoms.back().r[1] = 2.0;\n        s.atoms.back().r[2] = 1.0;\n        s.atoms.back().index = 1;\n        s.atoms.back().numNeighborsPerElement.resize(em.size());\n        s.numAtoms++;\n        s.numAtomsPerElement[0]++;\n\n        // Atom 3.\n        s.atoms.push_back(Atom());\n        s.atoms.back().r[0] = 0.0;\n        s.atoms.back().r[1] = 3.0;\n        s.atoms.back().r[2] = -1.0;\n        s.atoms.back().index = 2;\n        s.atoms.back().element = 1;\n        s.atoms.back().numNeighborsPerElement.resize(em.size());\n        s.numAtoms++;\n        s.numAtomsPerElement[1]++;\n\n        // Atom 4.\n        s.atoms.push_back(Atom());\n        s.atoms.back().r[0] = -2.0;\n        s.atoms.back().r[1] = 1.0;\n        s.atoms.back().r[2] = -0.5;\n        s.atoms.back().index = 3;\n        s.atoms.back().element = 2;\n        s.atoms.back().numNeighborsPerElement.resize(em.size());\n        s.numAtoms++;\n        s.numAtomsPerElement[2]++;\n\n        // Calculate neighbor list.\n        s.calculateNeighborList(10.0);\n    };\n    ~FixtureFourAtomsMixed() {};\n\n    ElementMap em;\n    Structure s;\n};\n\nvector<size_t> const typesMono = {2, 2, 3, 3, 9, 9, 12, 12, 13, 13,\n                                  20, 20, 20, 21, 21, 21, 22, 22, 22,\n                                  23, 23, 23, 24, 24, 24, 25, 25, 25};\nvector<string> const setupLinesMono = {\"H 2 H 0.001 0.0 10.0\",\n                                       \"H 2 H 0.030 1.0 10.0\",\n                                       \"H 3 H H 0.001  1.0 1.0 10.0 0.0\",\n                                       \"H 3 H H 0.030 -1.0 4.0 10.0 2.0\",\n                                       \"H 9 H H 0.001  1.0 1.0 10.0 0.0\",\n                                       \"H 9 H H 0.031 -1.0 4.0 10.0 2.0\",\n                                       \"H 12 0.001 0.0 10.0\",\n                                       \"H 12 0.030 1.0 10.0\",\n                                       \"H 13 0.001 0.0  1.0 1.0 10.0\",\n                                       \"H 13 0.030 2.0 -1.0 4.0 10.0\",\n                                       \"H 20 H    -10.0 10.0 p2\",\n                                       \"H 20 H      0.0  8.0 p2\",\n                                       \"H 20 H      1.0  3.0 p2\",\n                                       \"H 21 H H  -10.0 10.0  0.0 180.0 p2\",\n                                       \"H 21 H H    0.0 10.0 10.0  60.0 p2\",\n                                       \"H 21 H H    1.0 10.0 40.0 120.0 p2\",\n                                       \"H 22 H H  -10.0 10.0  0.0 180.0 p2\",\n                                       \"H 22 H H    0.0 10.0 10.0  60.0 p2\",\n                                       \"H 22 H H    1.0 10.0 40.0 120.0 p2\",\n                                       \"H 23 -10.0 10.0 p2\",\n                                       \"H 23   0.0  8.0 p2\",\n                                       \"H 23   1.0  3.0 p2\",\n                                       \"H 24 -10.0 10.0  0.0 180.0 p2\",\n                                       \"H 24   0.0 10.0 10.0  60.0 p2\",\n                                       \"H 24   1.0 10.0 40.0 120.0 p2\",\n                                       \"H 25 -10.0 10.0  0.0 180.0 p2\",\n                                       \"H 25   0.0 10.0 10.0  60.0 p2\",\n                                       \"H 25   1.0 10.0 40.0 120.0 p2\"};\nvector<double> const valuesMono = {4.6578975865793892E-01,\n                                   4.2613074319879601E-01,\n                                   2.2781144245150042E-02,\n                                   2.6506732726623567E-05,\n                                   8.8187604914213763E-02,\n                                   1.0245670290254523E-04, \n                                   4.6578975865793892E-01,\n                                   4.2613074319879601E-01,\n                                   2.2781144245150042E-02,\n                                   2.6506732726623567E-05,\n                                   1.71653828561074920,\n                                   1.63829178699555840,\n                                   0.59406437434580717, \n                                   0.39698365829232357,\n                                   0.056548996092037257,\n                                   0.0017053618495084467,\n                                   0.440241957350979370,\n                                   0.117549886737894540,\n                                   0.008811770360680239,\n                                   1.71653828561074920,\n                                   1.63829178699555840,\n                                   0.59406437434580717,\n                                   0.39698365829232357,\n                                   0.056548996092037257,\n                                   0.0017053618495084467,\n                                   0.440241957350979370,\n                                   0.117549886737894540,\n                                   0.008811770360680239};\n\nvector<size_t> const typesDual = {12, 12, 13, 13,\n                                  23, 23, 23, 24, 24, 24, 25, 25, 25};\nvector<string> const setupLinesDual = {\"H 12 0.001 0.0 10.0\",\n                                       \"H 12 0.030 1.0 10.0\",\n                                       \"H 13 0.001 0.0  1.0 1.0 10.0\",\n                                       \"H 13 0.030 2.0 -1.0 4.0 10.0\",\n                                       \"H 23 -10.0 10.0 p2\",\n                                       \"H 23   0.0  8.0 p2\",\n                                       \"H 23   1.0  3.0 p2\",\n                                       \"H 24 -10.0 10.0  0.0 180.0 p2\",\n                                       \"H 24   0.0 10.0 10.0  60.0 p2\",\n                                       \"H 24   1.0 10.0 40.0 120.0 p2\",\n                                       \"H 25 -10.0 10.0  0.0 180.0 p2\",\n                                       \"H 25   0.0 10.0 10.0  60.0 p2\",\n                                       \"H 25   1.0 10.0 40.0 120.0 p2\"};\nvector<double> const valuesDual = {9.3157951731587740E-01,\n                                   8.5226148639759169E-01,\n                                   9.1124576980600058E-02,\n                                   1.0602693090649413E-04,\n                                   3.4330765712215,\n                                   3.27658357399112,\n                                   1.18812874869161,\n                                   1.58793463316929,\n                                   0.226195984368149,\n                                   0.00682144739803379,\n                                   1.76096782940392,\n                                   0.470199546951578,\n                                   0.035247081442721};\n\nvector<size_t> const typesMixed = {2, 2, 3, 3, 3, 12, 12, 13, 13}; \nvector<string> const setupLinesMixed = {\"S 2 Cu 0.030 1.0 10.0\",\n                                        \"S 2  U 0.030 1.0 10.0\",\n                                        \"S 3  S Cu 0.001  1.0 1.0 10.0 0.0\",\n                                        \"S 3  S  U 0.001  1.0 1.0 10.0 0.0\",\n                                        \"S 3  Cu U 0.001  1.0 1.0 10.0 0.0\",\n                                        \"S 12 0.001 0.0 10.0\",\n                                        \"S 12 0.030 1.0 10.0\",\n                                        \"S 13 0.001 0.0  1.0 1.0 10.0\",\n                                        \"S 13 0.001 1.0 -1.0 4.0 10.0\"};\nvector<double> const valuesMixed = {1.8212508087363616E-01,\n                                    2.5814603379946083E-01,\n                                    2.2781144245150042E-02,\n                                    1.1723866787654575E-02,\n                                    1.8921487310992163E-02,\n                                    3.4986591461381153E+01,\n                                    3.2935153052088403E+01,\n                                    7.8310510986904234E+01,\n                                    3.6978004634143264E+00};\n\n#endif\n"
  },
  {
    "path": "test/cpp/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=../..\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# GENERAL SETTINGS\n###############################################################################\n# Default compiler, may be overridden by command line.\nCOMP=gnu # WARNING: Testing so far only works with \"gnu\" compiler.\n# Get from main makefile in src directory:\n#COMP=$(shell grep \"^COMP=\" ${PROJECT_DIR}/src/makefile | cut -d\"=\" -f2)\n\n# Log level for boost tests, may be overriden by command line.\nLOG_LEVEL=error\n\n# Include global (project-wide) settings.\ninclude $(PROJECT_DIR)/src/makefile.$(COMP)\n\n\n###############################################################################\n# PROJECT COMPILER AND FLAGS\n###############################################################################\nCC=$(PROJECT_CC)\nMPICC=$(PROJECT_MPICC)\nCFLAGS=$(PROJECT_CFLAGS)\nOPTIONS+=$(PROJECT_OPTIONS)\nDEBUG=$(PROJECT_DEBUG) $(PROJECT_TEST)\n\n# Extra include paths for compiling.\nINCLUDES=-I./ -I$(PROJECT_DIR)/src/libnnp -I$(PROJECT_DIR)/src/libnnptrain -I$(PROJECT_EIGEN) -I$(PROJECT_BOOST)/include\n\n# Extra flags for linking.\nLDFLAGS=$(PROJECT_LIB)/libnnp.a $(PROJECT_LIB)/libnnptrain.a $(PROJECT_LDFLAGS_BLAS) -L$(PROJECT_BOOST)/lib -lboost_system -lboost_unit_test_framework -lboost_filesystem -lpthread\n\n\n###############################################################################\n# DEFINE SOURCES\n###############################################################################\nSRC=$(wildcard test_*.cpp)\nSRC_NOIF=$(filter-out test_lammps_hdnnp.cpp, $(SRC))\nEXE=$(SRC:%.cpp=%)\nEXE_NOIF=$(SRC_NOIF:%.cpp=%)\n\n\n###############################################################################\n# RULES\n###############################################################################\n.PHONY: all no-interface coverage clean clean-coverage\n.NOTPARALLEL:\n\nall: $(EXE)\n\nno-interface: $(EXE_NOIF)\n\n%: %.cpp\n\t$(CC) $(CFLAGS) $(DEBUG) $(INCLUDES) $(OPTIONS) -o $@ $< $(LDFLAGS)\n\t./$@ --color_output=yes --log_level=$(LOG_LEVEL)\n\ncoverage:\n\tlcov -c -i --no-external        -d $(PROJECT_DIR)/src/libnnp -d $(PROJECT_DIR)/src/libnnptrain -d $(PROJECT_DIR)/src/libnnpif -d $(PROJECT_DIR)/src/application -o tests.base\n\tlcov -c    --no-external        -d $(PROJECT_DIR)/src/libnnp -d $(PROJECT_DIR)/src/libnnptrain -d $(PROJECT_DIR)/src/libnnpif -d $(PROJECT_DIR)/src/application -o tests.run\n\tlcov -a tests.base -a tests.run -d $(PROJECT_DIR)/src/libnnp -d $(PROJECT_DIR)/src/libnnptrain -d $(PROJECT_DIR)/src/libnnpif -d $(PROJECT_DIR)/src/application -o tests.info\n\tgenhtml -o htmlcov tests.info\n\nclean: clean-coverage\n\t$(RM) *.o *.gcno $(EXE)\n\nclean-coverage:\n\t$(RM) $(PROJECT_DIR)/src/libnnp/*.gcda\n\t$(RM) $(PROJECT_DIR)/src/libnnptrain/*.gcda\n\t$(RM) $(PROJECT_DIR)/src/libnnpif/LAMMPS/*.gcda\n\t$(RM) $(PROJECT_DIR)/src/application/*.gcda\n\t$(RM) *.gcda *.base *.run *.info\n\t$(RM) -r htmlcov\n\n# Grep for \"CI-CHECK\" for code changes if you want to review output files from non-interactive CI run.\n#test_nnp-train: test_nnp-train.cpp\n#\t$(CC) $(CFLAGS) $(DEBUG) $(INCLUDES) $(OPTIONS) -o $@ $< $(LDFLAGS)\n#\t-./$@ --color_output=yes --log_level=$(LOG_LEVEL)\n#\tcat nnp-train.log.0000.*\n#\tcat learning-curve.out.*\n"
  },
  {
    "path": "test/cpp/nnp_test.h",
    "content": "#ifndef NNP_TEST_H\n#define NNP_TEST_H\n\n#include <boost/test/unit_test.hpp>\n#include <boost/test/data/test_case.hpp>\n#include <boost/test/data/monomorphic.hpp>\n#include <boost/process.hpp>\n#include <boost/filesystem.hpp>\n#include <boost/asio.hpp>\n#include <iostream>\n#include \"fileHelpers.h\"\n\nnamespace bdata = boost::unit_test::data;\nnamespace bproc = boost::process;\nnamespace bfs = boost::filesystem;\n\n#define NNP_TOOL_TEST_CASE()\\\n\\\nBOOST_AUTO_TEST_SUITE(RegressionTests)\\\n\\\nBOOST_DATA_TEST_CASE_F(FixtureRepairDir,\\\n                       Execute_CorrectOutputFiles,\\\n                       bdata::make(container.examples),\\\n                       example)\\\n{\\\n    BOOST_REQUIRE(copy_directory_recursively(example.pathData, \"test\"));\\\n    bfs::current_path(\"test\");\\\n\\\n    boost::asio::io_service svc;\\\n    std::future<std::vector<char> > outStream;\\\n    bproc::child c(example.command + \" \" + example.args,\\\n                   bproc::std_out > outStream,\\\n                   svc);\\\n    svc.run();\\\n\\\n    BOOST_TEST_INFO(example.description);\\\n\\\n    nnpToolTestBody(example);\\\n\\\n    bfs::current_path(\"..\");\\\n    bfs::remove_all(\"test\");\\\n}\\\n\\\nBOOST_AUTO_TEST_SUITE_END()\n\n#endif\n    //BOOST_REQUIRE_EQUAL(result, 0);\n    //int result = bproc::system(example.command + \" \" + example.args,\n    //                           bproc::std_out > outStream);\n    //bproc::ipstream outStream;\n"
  },
  {
    "path": "test/cpp/test_CutoffFunction.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE CutoffFunction\n#include <boost/test/unit_test.hpp>\n#include <boost/test/data/test_case.hpp>\n#include <boost/test/data/monomorphic.hpp>\n\n#include \"CutoffFunction.h\"\n#include <limits> // std::numeric_limits\n#include <vector> // std::vector\n#include <stdexcept> // std::invalid_argument\n\nusing namespace std;\nusing namespace nnp;\n\nnamespace bdata = boost::unit_test::data;\n\ndouble const accuracy = 100.0 * numeric_limits<double>::epsilon(); \n\ndouble const cutoffRadius = 3.0;\ndouble const cutoffParameter = 0.2;\ndouble const testRadius = 0.8 * cutoffRadius;\ndouble const innerTestRadius = 0.1 * cutoffRadius;\nvector<CutoffFunction::CutoffType> const types = {CutoffFunction::CT_HARD ,\n                                                  CutoffFunction::CT_COS  ,\n                                                  CutoffFunction::CT_TANHU,\n                                                  CutoffFunction::CT_TANH ,\n                                                  CutoffFunction::CT_EXP  ,\n                                                  CutoffFunction::CT_POLY1,\n                                                  CutoffFunction::CT_POLY2,\n                                                  CutoffFunction::CT_POLY3,\n                                                  CutoffFunction::CT_POLY4};\nvector<double> const f = {1.0000000000000000E+00,\n                          1.4644660940672610E-01,\n                          7.6891537120697719E-03,\n                          1.7406350897769041E-02,\n                          2.7645304662956399E-01,\n                          1.5624999999999989E-01,\n                          1.0351562500000000E-01,\n                          7.0556640624999223E-02,\n                          4.8927307128898589E-02};\nvector<double> const df = { 0.0000000000000000E+00,\n                           -4.6280030605816297E-01,\n                           -3.7439367857705103E-02,\n                           -8.4753511078717925E-02,\n                           -9.0270382572918972E-01,\n                           -4.6874999999999978E-01,\n                           -4.3945312499999933E-01,\n                           -3.8452148437500017E-01,\n                           -3.2444000244142152E-01};\n\nBOOST_AUTO_TEST_SUITE(UnitTests)\n\nBOOST_AUTO_TEST_CASE(CheckCutoffTypeNumbers_CorrectNumbering)\n{\n    BOOST_REQUIRE_EQUAL(CutoffFunction::CT_HARD , 0);\n    BOOST_REQUIRE_EQUAL(CutoffFunction::CT_COS  , 1);\n    BOOST_REQUIRE_EQUAL(CutoffFunction::CT_TANHU, 2);\n    BOOST_REQUIRE_EQUAL(CutoffFunction::CT_TANH , 3);\n    BOOST_REQUIRE_EQUAL(CutoffFunction::CT_EXP  , 4);\n    BOOST_REQUIRE_EQUAL(CutoffFunction::CT_POLY1, 5);\n    BOOST_REQUIRE_EQUAL(CutoffFunction::CT_POLY2, 6);\n    BOOST_REQUIRE_EQUAL(CutoffFunction::CT_POLY3, 7);\n    BOOST_REQUIRE_EQUAL(CutoffFunction::CT_POLY4, 8);\n}\n\nBOOST_AUTO_TEST_CASE(CheckUnknownCutoffType_ThrowsError)\n{\n    CutoffFunction fc;\n\n    BOOST_REQUIRE_THROW(fc.setCutoffType(\n                            static_cast<CutoffFunction::CutoffType>(\n                                types.size())),\n                        invalid_argument);\n}\n\nBOOST_AUTO_TEST_CASE(CheckDefaultInitialization_AllZeroOutput)\n{\n    CutoffFunction fc;\n\n    BOOST_REQUIRE_EQUAL(fc.getCutoffType(), CutoffFunction::CT_HARD);\n    BOOST_REQUIRE_SMALL(fc.getCutoffRadius(), accuracy);\n    BOOST_REQUIRE_SMALL(fc.getCutoffParameter(), accuracy);\n}\n\nBOOST_AUTO_TEST_CASE(CheckInvalidCutoffParameter_ThrowsError)\n{\n    CutoffFunction fc;\n    fc.setCutoffType(CutoffFunction::CT_COS);\n\n    BOOST_REQUIRE_THROW(fc.setCutoffParameter(-0.001), invalid_argument);\n    BOOST_REQUIRE_THROW(fc.setCutoffParameter(1.0), invalid_argument);\n    BOOST_REQUIRE_THROW(fc.setCutoffParameter(1.1), invalid_argument);\n}\n\nBOOST_DATA_TEST_CASE(CalculateFunctions_CorrectResults,\n                     bdata::make(types) ^ bdata::make(f),\n                     type,\n                     f)\n{\n    CutoffFunction fc;\n    fc.setCutoffType(type);\n    fc.setCutoffRadius(cutoffRadius);\n    fc.setCutoffParameter(cutoffParameter);\n    BOOST_REQUIRE_SMALL(fc.f(testRadius) - f, accuracy);\n}\n\nBOOST_DATA_TEST_CASE(CalculateDerivatives_CorrectResults,\n                     bdata::make(types) ^ bdata::make(df),\n                     type,\n                     df)\n{\n    CutoffFunction fc;\n    fc.setCutoffType(type);\n    fc.setCutoffRadius(cutoffRadius);\n    fc.setCutoffParameter(cutoffParameter);\n    BOOST_REQUIRE_SMALL(fc.df(testRadius) - df, accuracy);\n}\n\nBOOST_DATA_TEST_CASE(CalculateFunctionsAndDerivatives_CorrectResults,\n                     bdata::make(types) ^ bdata::make(f) ^ bdata::make(df),\n                     type,\n                     f,\n                     df)\n{\n    CutoffFunction fc;\n    fc.setCutoffType(type);\n    fc.setCutoffRadius(cutoffRadius);\n    fc.setCutoffParameter(cutoffParameter);\n    double resf;\n    double resdf;\n    fc.fdf(testRadius, resf, resdf);\n    BOOST_REQUIRE_SMALL(resf - f, accuracy);\n    BOOST_REQUIRE_SMALL(resdf - df, accuracy);\n}\n\nBOOST_DATA_TEST_CASE(CalculateFunctionsOutOfCutoff_ZeroResult,\n                     bdata::make(types),\n                     type)\n{\n    CutoffFunction fc;\n    fc.setCutoffType(type);\n    fc.setCutoffRadius(cutoffRadius);\n    fc.setCutoffParameter(cutoffParameter);\n    BOOST_REQUIRE_SMALL(fc.f(1.5 * cutoffRadius), accuracy);\n}\n\nBOOST_DATA_TEST_CASE(CalculateDerivativesOutOfCutoff_ZeroResult,\n                     bdata::make(types),\n                     type)\n{\n    CutoffFunction fc;\n    fc.setCutoffType(type);\n    fc.setCutoffRadius(cutoffRadius);\n    fc.setCutoffParameter(cutoffParameter);\n    BOOST_REQUIRE_SMALL(fc.df(1.5 * cutoffRadius), accuracy);\n}\n\nBOOST_DATA_TEST_CASE(CalculateFunctionsAndDerivativesOutOfCutoff_ZeroResult,\n                     bdata::make(types),\n                     type)\n{\n    CutoffFunction fc;\n    fc.setCutoffType(type);\n    fc.setCutoffRadius(cutoffRadius);\n    fc.setCutoffParameter(cutoffParameter);\n    double resf;\n    double resdf;\n    fc.fdf(1.5 * cutoffRadius, resf, resdf);\n    BOOST_REQUIRE_SMALL(resf, accuracy);\n    BOOST_REQUIRE_SMALL(resdf, accuracy);\n}\n\nBOOST_DATA_TEST_CASE(CalculateFunctionsInsideInnerCutoff_OneResult,\n                     bdata::make(types),\n                     type)\n{\n    CutoffFunction fc;\n    fc.setCutoffType(type);\n    fc.setCutoffRadius(cutoffRadius);\n    fc.setCutoffParameter(cutoffParameter);\n    double resf = fc.f(innerTestRadius);\n    if (type == CutoffFunction::CT_TANHU)\n    {\n        BOOST_REQUIRE_SMALL(resf - 3.6752000144553820E-01, accuracy);\n    }\n    else if (type == CutoffFunction::CT_TANH)\n    {\n        BOOST_REQUIRE_SMALL(resf - 8.3197479809356334E-01, accuracy);\n    }\n    else\n    {\n        BOOST_REQUIRE_SMALL(resf - 1.0, accuracy);\n    }\n}\n\nBOOST_DATA_TEST_CASE(CalculateDerivativesInsideInnerCutoff_ZeroResult,\n                     bdata::make(types),\n                     type)\n{\n    CutoffFunction fc;\n    fc.setCutoffType(type);\n    fc.setCutoffRadius(cutoffRadius);\n    fc.setCutoffParameter(cutoffParameter);\n    double resdf = fc.df(innerTestRadius);\n    if (type == CutoffFunction::CT_TANHU)\n    {\n        BOOST_REQUIRE_SMALL(resdf - -2.4982884456067705E-01, accuracy);\n    }\n    else if (type == CutoffFunction::CT_TANH)\n    {\n        BOOST_REQUIRE_SMALL(resdf - -5.6555099503099682E-01, accuracy);\n    }\n    else\n    {\n        BOOST_REQUIRE_SMALL(resdf, accuracy);\n    }\n}\n\nBOOST_DATA_TEST_CASE(\n              CalculateFunctionsAndDerivativesInsideInnerCutoff_OneZeroResults,\n              bdata::make(types),\n              type)\n{\n    CutoffFunction fc;\n    fc.setCutoffType(type);\n    fc.setCutoffRadius(cutoffRadius);\n    fc.setCutoffParameter(cutoffParameter);\n    double resf;\n    double resdf;\n    fc.fdf(innerTestRadius, resf, resdf);\n    if (type == CutoffFunction::CT_TANHU)\n    {\n        BOOST_REQUIRE_SMALL(resf - 3.6752000144553820E-01, accuracy);\n        BOOST_REQUIRE_SMALL(resdf - -2.4982884456067705E-01, accuracy);\n    }\n    else if (type == CutoffFunction::CT_TANH)\n    {\n        BOOST_REQUIRE_SMALL(resf - 8.3197479809356334E-01, accuracy);\n        BOOST_REQUIRE_SMALL(resdf - -5.6555099503099682E-01, accuracy);\n    }\n    else\n    {\n        BOOST_REQUIRE_SMALL(resf - 1.0, accuracy);\n        BOOST_REQUIRE_SMALL(resdf, accuracy);\n    }\n}\n\nBOOST_AUTO_TEST_SUITE_END()\n"
  },
  {
    "path": "test/cpp/test_Prediction.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE Prediction\n#include <boost/test/unit_test.hpp>\n#include <boost/test/data/test_case.hpp>\n#include <boost/test/data/monomorphic.hpp>\n#include <boost/filesystem.hpp>\n#include \"fileHelpers.h\"\n#include \"ExamplePrediction.h\"\n\n#include \"Atom.h\"\n#include \"Structure.h\"\n#include \"Prediction.h\"\n#include \"utility.h\"\n#include <cstddef> // std::size_t\n#include <limits> // std::numeric_limits\n#include <string> // std::string, std::string::find_last_of\n#include <vector> // std::vector\n\nusing namespace std;\nusing namespace nnp;\n\nnamespace bdata = boost::unit_test::data;\nnamespace bfs = boost::filesystem;\n\ndouble const accuracy = 1000.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<ExamplePrediction> container;\n\nBOOST_AUTO_TEST_SUITE(RegressionTests)\n\nBOOST_DATA_TEST_CASE_F(FixtureRepairDir,\n                       PredictStructure_CorrectEnergiesForces,\n                       bdata::make(container.examples),\n                       example)\n{\n    BOOST_REQUIRE(copy_directory_recursively(example.pathData, \"test\"));\n    bfs::current_path(\"test\");\n\n    Prediction p;\n    p.log.writeToStdout = false;\n    p.setup();\n    p.readStructureFromFile();\n    p.predict();\n    BOOST_TEST_INFO(example.name + \" Potential energy\");\n    BOOST_REQUIRE_SMALL(p.structure.energy - example.energy, accuracy);\n\n    for (size_t i = 0; i < p.structure.atoms.size(); ++i)\n    {\n        Vec3D d = p.structure.atoms.at(i).f - example.forces.at(i);\n        BOOST_TEST_INFO(example.name + \" Atom \" << i << \" fx\");\n        BOOST_REQUIRE_SMALL(d[0], accuracy);\n        BOOST_TEST_INFO(example.name + \" Atom \" << i << \" fy\");\n        BOOST_REQUIRE_SMALL(d[1], accuracy);\n        BOOST_TEST_INFO(example.name + \" Atom \" << i << \" fz\");\n        BOOST_REQUIRE_SMALL(d[2], accuracy);\n    }\n\n    bfs::current_path(\"..\");\n    bfs::remove_all(\"test\");\n}\n\nBOOST_AUTO_TEST_SUITE_END()\n"
  },
  {
    "path": "test/cpp/test_ScreeningFunction.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE ScreeningFunction\n#include <boost/test/unit_test.hpp>\n#include <boost/test/data/test_case.hpp>\n#include <boost/test/data/monomorphic.hpp>\n#include \"ExampleScreeningFunction.h\"\n\n#include \"ScreeningFunction.h\"\n#include \"utility.h\"\n//#include <iostream>\n//#include <fstream>\n#include <limits> // std::numeric_limits\n#include <vector> // std::vector\n#include <stdexcept> // std::invalid_argument\n#include <string> // std::string\n\nusing namespace std;\nusing namespace nnp;\n\nnamespace bdata = boost::unit_test::data;\n\ndouble const accuracy = 100.0 * numeric_limits<double>::epsilon(); \n\nBoostDataContainer<ExampleScreeningFunction> container;\n\nBOOST_AUTO_TEST_SUITE(UnitTests)\n\nBOOST_AUTO_TEST_CASE(CheckUnknownCoreFunctionType_ThrowsError)\n{\n    ScreeningFunction fs;\n\n    BOOST_REQUIRE_THROW(fs.setCoreFunction(\"bla\"),\n                        invalid_argument);\n}\n\nBOOST_AUTO_TEST_CASE(CheckDefaultInitialization_AllZeroOutput)\n{\n    ScreeningFunction fs;\n\n    BOOST_REQUIRE_SMALL(fs.getInner(), accuracy);\n    BOOST_REQUIRE_SMALL(fs.getOuter(), accuracy);\n}\n\nBOOST_AUTO_TEST_CASE(CheckInvalidCutoffParameter_ThrowsError)\n{\n    ScreeningFunction fs;\n\n    BOOST_REQUIRE_THROW(fs.setInnerOuter(10.0, 5.0), invalid_argument);\n}\n\nBOOST_DATA_TEST_CASE(CombinedAndSeparateCall_SameResults,\n                     bdata::make(container.examples),\n                     e)\n{\n    double const rmin = 0.9 * e.inner;\n    double const rmax = 1.1 * e.outer;\n    size_t const n = 100;\n    double const dr = (rmax - rmin) / n;\n\n    BOOST_TEST_INFO(e.name + \" \\\"\" + e.type + \"\\\"\");\n    //ofstream file;\n    //file.open(\"fs.\" + e.type);\n    //double f;\n    //double df;\n    //e.fs.fdf(e.rt, f, df);\n    //file << strpr(\"# %f %24.16E %24.16E\\n\", e.rt, f, df);\n    for (size_t i = 0; i < n; ++i)\n    {\n        double const r = rmin + i * dr;\n        double f;\n        double df;\n        e.fs.fdf(r, f, df);\n        //file << r << \" \" << f << \" \" << df << endl;\n        BOOST_REQUIRE_SMALL(f - e.fs.f(r), accuracy);\n        BOOST_REQUIRE_SMALL(df - e.fs.df(r), accuracy);\n    }\n    //file.close();\n\n}\n\nBOOST_DATA_TEST_CASE(CompareAnalyticNumericDerivatives_ComparableResults,\n                     bdata::make(container.examples),\n                     e)\n{\n    double const accuracyNumeric = 1.0E-7; \n    double const delta = 1.0E-6;\n    double const rmin = e.inner + 10 * delta;\n    double const rmax = e.outer - 10 * delta;\n    size_t const n = 100;\n    double const dr = (rmax - rmin) / n;\n\n    BOOST_TEST_INFO(e.name + \" \\\"\" + e.type + \"\\\"\");\n    for (size_t i = 0; i < n; ++i)\n    {\n        double const r = rmin + i * dr;\n        double df = e.fs.df(r);\n        double flow = e.fs.f(r - delta);\n        double fhigh = e.fs.f(r + delta);\n        //cout << r << \" \" << (fhigh - flow) / (2.0 * delta) << \" \" << df << endl;\n        BOOST_REQUIRE_SMALL((fhigh - flow) / (2.0 * delta) - df,\n                            accuracyNumeric);\n    }\n\n}\n\nBOOST_DATA_TEST_CASE(CalculateFunctions_CorrectResults,\n                     bdata::make(container.examples),\n                     e)\n{\n    BOOST_TEST_INFO(e.name + \" \\\"\" + e.type + \"\\\"\");\n    BOOST_REQUIRE_SMALL(e.fs.f(e.rt) - e.f, accuracy);\n    BOOST_REQUIRE_SMALL(e.fs.f(e.rtbelow), accuracy);\n    BOOST_REQUIRE_SMALL(e.fs.f(e.rtabove) - 1.0, accuracy);\n}\n\nBOOST_DATA_TEST_CASE(CalculateDerivatives_CorrectResults,\n                     bdata::make(container.examples),\n                     e)\n{\n    BOOST_TEST_INFO(e.name + \" \\\"\" + e.type + \"\\\"\");\n    BOOST_REQUIRE_SMALL(e.fs.df(e.rt) - e.df, accuracy);\n    BOOST_REQUIRE_SMALL(e.fs.df(e.rtbelow), accuracy);\n    BOOST_REQUIRE_SMALL(e.fs.df(e.rtabove), accuracy);\n}\n\nBOOST_DATA_TEST_CASE(CalculateFunctionsAndDerivatives_CorrectResults,\n                     bdata::make(container.examples),\n                     e)\n{\n    BOOST_TEST_INFO(e.name + \" \\\"\" + e.type + \"\\\"\");\n    double f;\n    double df;\n    e.fs.fdf(e.rt, f, df);\n    BOOST_REQUIRE_SMALL(f - e.f, accuracy);\n    BOOST_REQUIRE_SMALL(df - e.df, accuracy);\n\n    e.fs.fdf(e.rtbelow, f, df);\n    BOOST_REQUIRE_SMALL(f, accuracy);\n    BOOST_REQUIRE_SMALL(df, accuracy);\n\n    e.fs.fdf(e.rtabove, f, df);\n    BOOST_REQUIRE_SMALL(f - 1.0, accuracy);\n    BOOST_REQUIRE_SMALL(df, accuracy);\n}\n\n}\n"
  },
  {
    "path": "test/cpp/test_Settings.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE Settings\n#include <boost/test/unit_test.hpp>\n#include <boost/test/data/test_case.hpp>\n#include <boost/test/data/monomorphic.hpp>\n#include <boost/filesystem.hpp>\n#include \"fileHelpers.h\"\n\n#include <cstdlib>\n#include <fstream>\n#include \"Settings.h\"\n\nusing namespace std;\nusing namespace nnp;\n\nnamespace bdata = boost::unit_test::data;\nnamespace bfs = boost::filesystem;\n\nBOOST_AUTO_TEST_SUITE(RegressionTests)\n\nBOOST_FIXTURE_TEST_CASE(ReadRecommendedSettings_NoCriticalErrors,\n                        FixtureRepairDir)\n{\n    BOOST_REQUIRE(bfs::create_directory(\"test\"));\n    bfs::copy_file(\"../../examples/input.nn.recommended\", \"test/input.nn\");\n    bfs::current_path(\"test\");\n\n    settings::Settings s;\n    size_t numCriticalProblems = s.loadFile();\n    BOOST_REQUIRE_EQUAL(numCriticalProblems, 0);\n\n    size_t numProblems = 0;\n    for (auto line : s.info())\n    {\n        if (line.find(\"WARNING\") != line.npos) numProblems++;\n    }\n    BOOST_REQUIRE_EQUAL(numProblems, 0);\n\n    bfs::current_path(\"..\");\n    bfs::remove_all(\"test\");\n}\n\nBOOST_FIXTURE_TEST_CASE(UnknownKeyword_NoCriticalErrors,\n                        FixtureRepairDir)\n{\n    BOOST_REQUIRE(bfs::create_directory(\"test\"));\n    bfs::copy_file(\"../../examples/input.nn.recommended\", \"test/input.nn\");\n    bfs::current_path(\"test\");\n\n    ofstream f;\n    f.open(\"input.nn\", ios_base::app);\n    f << \"abcdefghijk\";\n    f.flush();\n    f.close();\n\n    settings::Settings s;\n    size_t numCriticalProblems = s.loadFile();\n    BOOST_REQUIRE_EQUAL(numCriticalProblems, 0);\n\n    size_t numProblems = 0;\n    for (auto line : s.info())\n    {\n        if (line.find(\"WARNING\") != line.npos) numProblems++;\n    }\n    BOOST_REQUIRE_EQUAL(numProblems, 2);\n\n    BOOST_TEST_INFO(\"Forbidden to parse file for unknown keywords.\\n\");\n    BOOST_REQUIRE_THROW(s.keywordExists(\"abcdefghijk\"), runtime_error);\n\n    bfs::current_path(\"..\");\n    bfs::remove_all(\"test\");\n}\n\nBOOST_FIXTURE_TEST_CASE(DuplicatedKeyword_CriticalError,\n                        FixtureRepairDir)\n{\n    BOOST_REQUIRE(bfs::create_directory(\"test\"));\n    bfs::copy_file(\"../../examples/input.nn.recommended\", \"test/input.nn\");\n    bfs::current_path(\"test\");\n\n    ofstream f;\n    f.open(\"input.nn\", ios_base::app);\n    f << \"use_short_forces\";\n    f.flush();\n    f.close();\n\n    settings::Settings s;\n    size_t numCriticalProblems = s.loadFile();\n    BOOST_REQUIRE_EQUAL(numCriticalProblems, 1);\n\n    size_t numProblems = 0;\n    for (auto line : s.info())\n    {\n        if (line.find(\"WARNING\") != line.npos) numProblems++;\n    }\n    BOOST_REQUIRE_EQUAL(numProblems, 2);\n\n    bfs::current_path(\"..\");\n    bfs::remove_all(\"test\");\n}\n\nBOOST_FIXTURE_TEST_CASE(DuplicatedAlternativeKeyword_CriticalError,\n                        FixtureRepairDir)\n{\n    BOOST_REQUIRE(bfs::create_directory(\"test\"));\n    bfs::copy_file(\"../../examples/input.nn.recommended\", \"test/input.nn\");\n    bfs::current_path(\"test\");\n\n    ofstream f;\n    f.open(\"input.nn\", ios_base::app);\n    f << \"rmse_threshold_energy 0.5\";\n    f.flush();\n    f.close();\n\n    settings::Settings s;\n    size_t numCriticalProblems = s.loadFile();\n    BOOST_REQUIRE_EQUAL(numCriticalProblems, 2);\n\n    size_t numProblems = 0;\n    for (auto line : s.info())\n    {\n        if (line.find(\"WARNING\") != line.npos) numProblems++;\n    }\n    BOOST_REQUIRE_EQUAL(numProblems, 3);\n\n    bfs::current_path(\"..\");\n    bfs::remove_all(\"test\");\n}\n\nBOOST_FIXTURE_TEST_CASE(UseAlternativeKeyword_CorrectValue,\n                        FixtureRepairDir)\n{\n    BOOST_REQUIRE(bfs::create_directory(\"test\"));\n    bfs::copy_file(\"../../examples/input.nn.recommended\", \"test/input.nn\");\n    bfs::current_path(\"test\");\n\n    settings::Settings s;\n    s.loadFile();\n\n    double value = atof(s[\"short_force_error_threshold\"].c_str());\n    BOOST_REQUIRE_EQUAL(value, 1.0);\n    value = atof(s[\"rmse_threshold_force\"].c_str());\n    BOOST_REQUIRE_EQUAL(value, 1.0);\n\n    bfs::current_path(\"..\");\n    bfs::remove_all(\"test\");\n}\n\nBOOST_AUTO_TEST_SUITE_END()\n"
  },
  {
    "path": "test/cpp/test_SymmetryFunctionGroups.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE SymGrps\n#include <boost/test/unit_test.hpp>\n#include <boost/test/data/test_case.hpp>\n#include <boost/test/data/monomorphic.hpp>\n#include \"fixtures.h\"\n\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"Structure.h\"\n#include \"SymFnc.h\"\n#include \"SymFncBaseCutoff.h\"\n#include \"SymFncExpRad.h\"\n#include \"SymFncExpAngn.h\"\n#include \"SymFncExpAngw.h\"\n#include \"SymFncExpRadWeighted.h\"\n#include \"SymFncExpAngnWeighted.h\"\n#include \"SymFncCompRad.h\"\n#include \"SymFncCompAngw.h\"\n#include \"SymFncCompAngn.h\"\n#include \"SymFncCompRadWeighted.h\"\n#include \"SymFncCompAngnWeighted.h\"\n#include \"SymFncCompAngwWeighted.h\"\n#include \"SymGrp.h\"\n#include \"SymGrpExpRad.h\"\n#include \"SymGrpExpAngn.h\"\n#include \"SymGrpExpAngw.h\"\n#include \"SymGrpExpRadWeighted.h\"\n#include \"SymGrpExpAngnWeighted.h\"\n#include \"SymGrpCompRad.h\"\n#include \"SymGrpCompAngw.h\"\n#include \"SymGrpCompAngn.h\"\n#include \"SymGrpCompRadWeighted.h\"\n#include \"SymGrpCompAngnWeighted.h\"\n#include \"SymGrpCompAngwWeighted.h\"\n#include \"utility.h\"\n#include <cstddef> // std::size_t\n#include <limits> // std::numeric_limits\n#include <string> // std::string\n#include <vector> // std::vector\n\nusing namespace std;\nusing namespace nnp;\n\nnamespace bdata = boost::unit_test::data;\n\ndouble const accuracy = 1000.0 * numeric_limits<double>::epsilon();\ndouble const accuracyNumeric = 1E-6;\nsize_t const maxElements = 3;\nsize_t const maxCacheSize = 2;\n\nSymFnc* setupSymmetryFunction(ElementMap   em,\n                                        size_t const type,\n                                        string const setupLine)\n{\n    SymFnc* sf;\n    if      (type ==  2)  sf = new SymFncExpRad(em);\n    else if (type ==  3)  sf = new SymFncExpAngn(em);\n    else if (type ==  9)  sf = new SymFncExpAngw(em);\n    else if (type == 12)  sf = new SymFncExpRadWeighted(em);\n    else if (type == 13)  sf = new SymFncExpAngnWeighted(em);\n    else if (type == 20)  sf = new SymFncCompRad(em);\n    else if (type == 21)  sf = new SymFncCompAngn(em);\n    else if (type == 22)  sf = new SymFncCompAngw(em);\n    else if (type == 23)  sf = new SymFncCompRadWeighted(em);\n    else if (type == 24)  sf = new SymFncCompAngnWeighted(em);\n    else if (type == 25)  sf = new SymFncCompAngwWeighted(em);\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown symmetry function type.\\n\");\n    }\n\n    sf->setIndex(0);\n    for (size_t i = 0; i < em.size(); ++i)\n    {\n        sf->setIndexPerElement(i, 0);\n    }\n    sf->setParameters(setupLine);\n    SymFncBaseCutoff* sfcb = dynamic_cast<SymFncBaseCutoff*>(sf);\n    if (sfcb != nullptr)\n    {\n        sfcb->setCutoffFunction(CutoffFunction::CT_TANHU, 0.0);\n    }\n    string scalingLine = \"1 1 0.0 0.0 0.0 0.0\";\n    sf->setScalingType(SymFnc::ST_NONE, scalingLine, 0.0, 0.0);\n#ifndef NOSFCACHE\n    auto ci = sf->getCacheIdentifiers();\n    vector<size_t> count(em.size());\n    for (size_t i = 0; i < ci.size(); ++i)\n    {\n        size_t ne = atoi(split(ci.at(i))[0].c_str());\n        sf->addCacheIndex(ne, count.at(ne), ci.at(i));\n        count.at(ne)++;\n    }\n#endif\n\n    return sf;\n}\n\nSymGrp* setupSymmetryFunctionGroup(ElementMap em, SymFnc const& sf)\n{\n    SymGrp* sfg;\n    size_t const type = sf.getType();\n    if      (type ==  2)  sfg = new SymGrpExpRad(em);\n    else if (type ==  3)  sfg = new SymGrpExpAngn(em);\n    else if (type ==  9)  sfg = new SymGrpExpAngw(em);\n    else if (type == 12)  sfg = new SymGrpExpRadWeighted(em);\n    else if (type == 13)  sfg = new SymGrpExpAngnWeighted(em);\n    else if (type == 20)  sfg = new SymGrpCompRad(em);\n    else if (type == 21)  sfg = new SymGrpCompAngn(em);\n    else if (type == 22)  sfg = new SymGrpCompAngw(em);\n    else if (type == 23)  sfg = new SymGrpCompRadWeighted(em);\n    else if (type == 24)  sfg = new SymGrpCompAngnWeighted(em);\n    else if (type == 25)  sfg = new SymGrpCompAngwWeighted(em);\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown symmetry function type.\\n\");\n    }\n\n    sfg->addMember(&sf);\n    sfg->sortMembers();\n    sfg->setScalingFactors();\n\n    return sfg;\n}\n\nvoid recalculateSymmetryFunctionGroup(Structure&    s,\n                                      Atom&         a,\n                                      SymGrp const& sfg)\n{\n    s.clearNeighborList();\n    s.calculateNeighborList(10.0);\n    a.allocate(true);\n    sfg.calculate(a, true);\n\n    return;\n}\n\nvoid compareAnalyticNumericDerivGroup(Structure&   s,\n                                      ElementMap&  em,\n                                      size_t const type,\n                                      string const setupLine)\n{\n    SymFnc* sf = setupSymmetryFunction(em, type, setupLine);\n\n    SymGrp* sfg = setupSymmetryFunctionGroup(em, *sf);\n\n    // Allocate symmetry function arrays.\n    s.atoms.at(0).numSymmetryFunctions = 1;\n    s.atoms.at(0).numSymmetryFunctionDerivatives = vector<size_t>(em.size(), 1);\n#ifndef NOSFCACHE\n    s.atoms.at(0).cacheSizePerElement = vector<size_t>(maxElements,\n                                                       maxCacheSize);\n#endif\n    s.atoms.at(0).allocate(true);\n\n    double h = 1.0E-7;\n\n    vector<vector<double> > results;\n    for (size_t ia = 0; ia < s.numAtoms; ++ia)\n    {\n        results.push_back(vector<double>());\n        for (size_t ic = 0; ic < 3; ++ic)\n        {\n            s.atoms.at(ia).r[ic] += h;\n            recalculateSymmetryFunctionGroup(s, s.atoms.at(0), *sfg);\n            double Gh = s.atoms.at(0).G.at(0);\n            s.atoms.at(ia).r[ic] -= 2 * h;\n            recalculateSymmetryFunctionGroup(s, s.atoms.at(0), *sfg);\n            double Gl = s.atoms.at(0).G.at(0);\n            s.atoms.at(ia).r[ic] += h;\n            results.back().push_back((Gh - Gl)/(2 * h));\n        }\n    }\n\n    // Calculate symmetry function for atom 0.\n    recalculateSymmetryFunctionGroup(s, s.atoms.at(0), *sfg);\n\n    BOOST_TEST_INFO(string(\"Symmetry function derivatives, type \")\n                    << type << \"\\n\");\n    for (size_t ic = 0; ic < 3; ++ic)\n    {\n        BOOST_REQUIRE_SMALL(s.atoms.at(0).dGdr.at(0)[ic]\n                            - results.at(0).at(ic),\n                            accuracyNumeric);\n    }\n    for (size_t ia = 1; ia < s.numAtoms; ++ia)\n    {\n        for (size_t ic = 0; ic < 3; ++ic)\n        {\n            BOOST_REQUIRE_SMALL(s.atoms.at(0).neighbors.at(ia-1).dGdr.at(0)[ic]\n                                - results.at(ia).at(ic),\n                                accuracyNumeric);\n        }\n    }\n\n    delete sfg;\n    delete sf;\n\n    return;\n}\n\nvoid checkAbsoluteValueGroup(Structure&   s,\n                             ElementMap&  em,\n                             size_t const type,\n                             string const setupLine,\n                             double const value)\n{\n    SymFnc* sf = setupSymmetryFunction(em, type, setupLine);\n\n    SymGrp* sfg = setupSymmetryFunctionGroup(em, *sf);\n\n    // Allocate symmetry function arrays.\n    s.atoms.at(0).numSymmetryFunctions = 1;\n    s.atoms.at(0).numSymmetryFunctionDerivatives = vector<size_t>(em.size(), 1);\n#ifndef NOSFCACHE\n    s.atoms.at(0).cacheSizePerElement = vector<size_t>(maxElements,\n                                                       maxCacheSize);\n#endif\n    s.atoms.at(0).allocate(true);\n\n    // Calculate symmetry function for atom 0.\n    recalculateSymmetryFunctionGroup(s, s.atoms.at(0), *sfg);\n\n    BOOST_TEST_INFO(string(\"Symmetry function values, type \")\n                    << type << \"\\n\");\n    BOOST_REQUIRE_SMALL(s.atoms.at(0).G.at(0) - value, accuracy);\n\n    delete sf;\n\n    return;\n}\n\nBOOST_AUTO_TEST_SUITE(IntegrationTests)\n\nBOOST_DATA_TEST_CASE_F(FixtureThreeAtomsMono,\n                       CompareAnalyticNumericDerivMono_EqualResults,\n                       bdata::make(typesMono) ^ bdata::make(setupLinesMono),\n                       type,\n                       setupLine)\n{\n    compareAnalyticNumericDerivGroup(s, em, type, setupLine);\n}\n\nBOOST_DATA_TEST_CASE_F(FixtureThreeAtomsDual,\n                       CompareAnalyticNumericDerivDual_EqualResults,\n                       bdata::make(typesDual) ^ bdata::make(setupLinesDual),\n                       type,\n                       setupLine)\n{\n    compareAnalyticNumericDerivGroup(s, em, type, setupLine);\n}\n\nBOOST_DATA_TEST_CASE_F(FixtureFourAtomsMixed,\n                       CompareAnalyticNumericDerivMixed_EqualResults,\n                       bdata::make(typesMixed) ^ bdata::make(setupLinesMixed),\n                       type,\n                       setupLine)\n{\n    compareAnalyticNumericDerivGroup(s, em, type, setupLine);\n}\n\nBOOST_DATA_TEST_CASE_F(FixtureThreeAtomsMono,\n                       CheckAbsoluteValuesMono_CorrectResults,\n                       bdata::make(typesMono)\n                       ^ bdata::make(setupLinesMono)\n                       ^ bdata::make(valuesMono),\n                       type,\n                       setupLine,\n                       value)\n{\n    checkAbsoluteValueGroup(s, em, type, setupLine, value);\n}\n\nBOOST_DATA_TEST_CASE_F(FixtureThreeAtomsDual,\n                       CheckAbsoluteValuesDual_CorrectResults,\n                       bdata::make(typesDual)\n                       ^ bdata::make(setupLinesDual)\n                       ^ bdata::make(valuesDual),\n                       type,\n                       setupLine,\n                       value)\n{\n    checkAbsoluteValueGroup(s, em, type, setupLine, value);\n}\n\nBOOST_DATA_TEST_CASE_F(FixtureFourAtomsMixed,\n                       CheckAbsoluteValuesMixed_CorrectResults,\n                       bdata::make(typesMixed)\n                       ^ bdata::make(setupLinesMixed)\n                       ^ bdata::make(valuesMixed),\n                       type,\n                       setupLine,\n                       value)\n{\n    checkAbsoluteValueGroup(s, em, type, setupLine, value);\n}\n\nBOOST_AUTO_TEST_SUITE_END()\n"
  },
  {
    "path": "test/cpp/test_SymmetryFunctions.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE SymFncs\n#include <boost/test/unit_test.hpp>\n#include <boost/test/data/test_case.hpp>\n#include <boost/test/data/monomorphic.hpp>\n#include \"fixtures.h\"\n\n#include \"Atom.h\"\n#include \"ElementMap.h\"\n#include \"Structure.h\"\n#include \"SymFnc.h\"\n#include \"SymFncBaseCutoff.h\"\n#include \"SymFncExpRad.h\"\n#include \"SymFncCompRad.h\"\n#include \"SymFncExpAngn.h\"\n#include \"SymFncExpAngw.h\"\n#include \"SymFncCompAngw.h\"\n#include \"SymFncCompAngn.h\"\n#include \"SymFncExpRadWeighted.h\"\n#include \"SymFncExpAngnWeighted.h\"\n#include \"SymFncCompRadWeighted.h\"\n#include \"SymFncCompAngnWeighted.h\"\n#include \"SymFncCompAngwWeighted.h\"\n#include \"utility.h\"\n#include <cstddef> // std::size_t\n//#include <iostream> // std::cerr\n#include <limits> // std::numeric_limits\n#include <string> // std::string\n#include <vector> // std::vector\n\nusing namespace std;\nusing namespace nnp;\n\nnamespace bdata = boost::unit_test::data;\n\ndouble const accuracy = 1000.0 * numeric_limits<double>::epsilon();\ndouble const accuracyNumeric = 1E-6;\nsize_t const maxElements = 3;\nsize_t const maxCacheSize = 2;\n\nSymFnc* setupSymmetryFunction(ElementMap   em,\n                              size_t const type,\n                              string const setupLine)\n{\n    SymFnc* sf;\n    if      (type ==  2)  sf = new SymFncExpRad(em);\n    else if (type ==  3)  sf = new SymFncExpAngn(em);\n    else if (type ==  9)  sf = new SymFncExpAngw(em);\n    else if (type == 12)  sf = new SymFncExpRadWeighted(em);\n    else if (type == 13)  sf = new SymFncExpAngnWeighted(em);\n    else if (type == 20)  sf = new SymFncCompRad(em);\n    else if (type == 21)  sf = new SymFncCompAngn(em);\n    else if (type == 22)  sf = new SymFncCompAngw(em);\n    else if (type == 23)  sf = new SymFncCompRadWeighted(em);\n    else if (type == 24)  sf = new SymFncCompAngnWeighted(em);\n    else if (type == 25)  sf = new SymFncCompAngwWeighted(em);\n    else\n    {\n        throw runtime_error(\"ERROR: Unknown symmetry function type.\\n\");\n    }\n\n    sf->setIndex(0);\n    for (size_t i = 0; i < em.size(); ++i)\n    {\n        sf->setIndexPerElement(i, 0);\n    }\n    sf->setParameters(setupLine);\n    SymFncBaseCutoff* sfcb = dynamic_cast<SymFncBaseCutoff*>(sf);\n    if (sfcb != nullptr)\n    {\n        sfcb->setCutoffFunction(CutoffFunction::CT_TANHU, 0.0);\n    }\n    string scalingLine = \"1 1 0.0 0.0 0.0 0.0\";\n    sf->setScalingType(SymFnc::ST_NONE, scalingLine, 0.0, 0.0);\n#ifndef NOSFCACHE\n    auto ci = sf->getCacheIdentifiers();\n    vector<size_t> count(em.size());\n    for (size_t i = 0; i < ci.size(); ++i)\n    {\n        size_t ne = atoi(split(ci.at(i))[0].c_str());\n        sf->addCacheIndex(ne, count.at(ne), ci.at(i));\n        count.at(ne)++;\n    }\n#endif\n\n    return sf;\n}\n\nvoid recalculateSymmetryFunction(Structure&    s,\n                                 Atom&         a,\n                                 SymFnc const& sf)\n{\n    s.clearNeighborList();\n    s.calculateNeighborList(10.0);\n    a.allocate(true);\n    sf.calculate(a, true);\n\n    return;\n}\n\nvoid compareAnalyticNumericDeriv(Structure&   s,\n                                 ElementMap&  em,\n                                 size_t const type,\n                                 string const setupLine)\n{\n    SymFnc* sf = setupSymmetryFunction(em, type, setupLine);\n\n    // Allocate symmetry function arrays.\n    s.atoms.at(0).numSymmetryFunctions = 1;\n    s.atoms.at(0).numSymmetryFunctionDerivatives = vector<size_t>(em.size(), 1);\n#ifndef NOSFCACHE\n    s.atoms.at(0).cacheSizePerElement = vector<size_t>(maxElements,\n                                                       maxCacheSize);\n#endif\n    s.atoms.at(0).allocate(true);\n\n    double h = 1.0E-7;\n\n    vector<vector<double> > results;\n    for (size_t ia = 0; ia < s.numAtoms; ++ia)\n    {\n        results.push_back(vector<double>());\n        for (size_t ic = 0; ic < 3; ++ic)\n        {\n            s.atoms.at(ia).r[ic] += h;\n            recalculateSymmetryFunction(s, s.atoms.at(0), *sf);\n            double Gh = s.atoms.at(0).G.at(0);\n            s.atoms.at(ia).r[ic] -= 2 * h;\n            recalculateSymmetryFunction(s, s.atoms.at(0), *sf);\n            double Gl = s.atoms.at(0).G.at(0);\n            s.atoms.at(ia).r[ic] += h;\n            results.back().push_back((Gh - Gl)/(2 * h));\n        }\n    }\n\n    // Calculate symmetry function for atom 0.\n    recalculateSymmetryFunction(s, s.atoms.at(0), *sf);\n\n    BOOST_TEST_INFO(string(\"Symmetry function derivatives, type \")\n                    << type << \"\\n\");\n    for (size_t ic = 0; ic < 3; ++ic)\n    {\n        BOOST_REQUIRE_SMALL(s.atoms.at(0).dGdr.at(0)[ic]\n                            - results.at(0).at(ic),\n                            accuracyNumeric);\n    }\n    for (size_t ia = 1; ia < s.numAtoms; ++ia)\n    {\n        for (size_t ic = 0; ic < 3; ++ic)\n        {\n            BOOST_REQUIRE_SMALL(s.atoms.at(0).neighbors.at(ia-1).dGdr.at(0)[ic]\n                                - results.at(ia).at(ic),\n                                accuracyNumeric);\n        }\n    }\n\n    delete sf;\n\n    return;\n}\n\nvoid checkAbsoluteValue(Structure&   s,\n                        ElementMap&  em,\n                        size_t const type,\n                        string const setupLine,\n                        double const value)\n{\n    SymFnc* sf = setupSymmetryFunction(em, type, setupLine);\n\n    // Allocate symmetry function arrays.\n    s.atoms.at(0).numSymmetryFunctions = 1;\n    s.atoms.at(0).numSymmetryFunctionDerivatives = vector<size_t>(em.size(), 1);\n#ifndef NOSFCACHE\n    s.atoms.at(0).cacheSizePerElement = vector<size_t>(maxElements,\n                                                       maxCacheSize);\n#endif\n    s.atoms.at(0).allocate(true);\n\n    // Calculate symmetry function for atom 0.\n    recalculateSymmetryFunction(s, s.atoms.at(0), *sf);\n\n    BOOST_TEST_INFO(string(\"Symmetry function values, type \")\n                    << type << \"\\n\");\n//    cerr << strpr(\"%24.16E\\n\", s.atoms.at(0).G.at(0));\n    BOOST_REQUIRE_SMALL(s.atoms.at(0).G.at(0) - value, accuracy);\n\n    delete sf;\n\n    return;\n}\n\nBOOST_AUTO_TEST_SUITE(IntegrationTests)\n\nBOOST_DATA_TEST_CASE_F(FixtureThreeAtomsMono,\n                       CompareAnalyticNumericDerivMono_EqualResults,\n                       bdata::make(typesMono) ^ bdata::make(setupLinesMono),\n                       type,\n                       setupLine)\n{\n    compareAnalyticNumericDeriv(s, em, type, setupLine);\n}\n\nBOOST_DATA_TEST_CASE_F(FixtureThreeAtomsDual,\n                       CompareAnalyticNumericDerivDual_EqualResults,\n                       bdata::make(typesDual) ^ bdata::make(setupLinesDual),\n                       type,\n                       setupLine)\n{\n    compareAnalyticNumericDeriv(s, em, type, setupLine);\n}\n\nBOOST_DATA_TEST_CASE_F(FixtureFourAtomsMixed,\n                       CompareAnalyticNumericDerivMixed_EqualResults,\n                       bdata::make(typesMixed) ^ bdata::make(setupLinesMixed),\n                       type,\n                       setupLine)\n{\n    compareAnalyticNumericDeriv(s, em, type, setupLine);\n}\n\nBOOST_DATA_TEST_CASE_F(FixtureThreeAtomsMono,\n                       CheckAbsoluteValuesMono_CorrectResults,\n                       bdata::make(typesMono)\n                       ^ bdata::make(setupLinesMono)\n                       ^ bdata::make(valuesMono),\n                       type,\n                       setupLine,\n                       value)\n{\n    checkAbsoluteValue(s, em, type, setupLine, value);\n}\n\nBOOST_DATA_TEST_CASE_F(FixtureThreeAtomsDual,\n                       CheckAbsoluteValuesDual_CorrectResults,\n                       bdata::make(typesDual)\n                       ^ bdata::make(setupLinesDual)\n                       ^ bdata::make(valuesDual),\n                       type,\n                       setupLine,\n                       value)\n{\n    checkAbsoluteValue(s, em, type, setupLine, value);\n}\n\nBOOST_DATA_TEST_CASE_F(FixtureFourAtomsMixed,\n                       CheckAbsoluteValuesMixed_CorrectResults,\n                       bdata::make(typesMixed)\n                       ^ bdata::make(setupLinesMixed)\n                       ^ bdata::make(valuesMixed),\n                       type,\n                       setupLine,\n                       value)\n{\n    checkAbsoluteValue(s, em, type, setupLine, value);\n}\n\nBOOST_AUTO_TEST_SUITE_END()\n"
  },
  {
    "path": "test/cpp/test_lammps_hdnnp.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE lammps-hdnnp\n#include \"Example_lammps_hdnnp.h\"\n#include \"nnp_test.h\"\n#include \"utility.h\"\n\n#include <fstream> // std::ifstream\n#include <limits>  // std::numeric_limits\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nusing namespace std;\nusing namespace nnp;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_lammps_hdnnp> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_lammps_hdnnp const example)\n{\n    bool timeStepFound = false;\n    bool startReading = false;\n    string line;\n    ifstream file;\n    file.open(\"log.lammps\");\n    BOOST_REQUIRE(file.is_open());\n    while (getline(file, line))\n    {\n        vector<string> columns = split(reduce(line));\n        if (columns.size() > 0 && columns.at(0) == \"Step\")\n        {\n            startReading = true;\n        }\n        if (startReading == true &&\n            columns.size() >= 5 &&\n            columns.at(0) == to_string(example.lastTimeStep))\n        {\n            timeStepFound = true;\n            BOOST_REQUIRE_SMALL(example.potentialEnergy - stod(columns.at(2)),\n                                accuracy);\n            BOOST_REQUIRE_SMALL(example.totalEnergy - stod(columns.at(4)),\n                                accuracy);\n            break;\n        }\n    }\n    BOOST_REQUIRE_MESSAGE(timeStepFound,\n                          string(\"ERROR: Epoch information was not \"\n                                 \"found in file.\"));\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-atomenv.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-atomenv\n#include \"Example_nnp_atomenv.h\"\n#include \"nnp_test.h\"\n#include \"utility.h\"\n\n#include <limits> // std::numeric_limits\n#include <map> // std::map\n\nusing namespace std;\nusing namespace nnp;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_atomenv> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_atomenv const example)\n{\n    Example_nnp_atomenv const& ex = example;\n\n    BOOST_REQUIRE(bfs::exists(\"nnp-atomenv.log.0000\"));\n    BOOST_REQUIRE(bfs::exists(\"atomic-env.G\"));\n    BOOST_REQUIRE(bfs::exists(\"atomic-env.dGdx\"));\n    BOOST_REQUIRE(bfs::exists(\"atomic-env.dGdy\"));\n    BOOST_REQUIRE(bfs::exists(\"atomic-env.dGdz\"));\n    BOOST_REQUIRE(bfs::exists(\"neighbors.histo\"));\n\n    map<string, size_t> nexpected;\n    map<string, size_t> nexpectedFull;\n    for (auto e1 : ex.elements)\n    {\n        nexpected    [e1] = 1 + ex.numSF.at(e1);\n        nexpectedFull[e1] = 1 + ex.numSF.at(e1);\n        for (auto e2 : ex.elements)\n        {\n            nexpected.at(e1)     += ex.neighCut.at(make_pair(e1, e2)).first\n                                  * ex.neighCut.at(make_pair(e2, e1)).second;\n            nexpectedFull.at(e1) += ex.neighCut.at(make_pair(e1, e2)).first\n                                  * ex.numSF.at(e2);\n        }\n    }\n\n    string line;\n    ifstream file;\n    file.open(\"atomic-env.G\");\n    BOOST_REQUIRE(file.is_open());\n    while (getline(file, line))\n    {\n        vector<string> columns = split(reduce(line));;\n        string element = columns.at(0);\n        BOOST_REQUIRE_EQUAL(columns.size(), nexpectedFull.at(element));\n    }\n    file.close();\n\n    file.open(\"atomic-env.dGdx\");\n    BOOST_REQUIRE(file.is_open());\n    while (getline(file, line))\n    {\n        vector<string> columns = split(reduce(line));;\n        string element = columns.at(0);\n#ifndef NNP_FULL_SFD_MEMORY\n        BOOST_REQUIRE_EQUAL(columns.size(), nexpected.at(element));\n#else\n        BOOST_REQUIRE_EQUAL(columns.size(), nexpectedFull.at(element));\n#endif\n    }\n    file.close();\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-checkdw.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-checkdw\n#include \"Example_nnp_checkdw.h\"\n#include \"nnp_test.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_checkdw> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_checkdw const /*example*/)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-checkdw.log.0000\"));\n    BOOST_REQUIRE(bfs::exists(\"checkdw-summary.out\"));\n    BOOST_REQUIRE(bfs::exists(\"checkdw-weights.energy.out\"));\n    BOOST_REQUIRE(bfs::exists(\"checkdw-weights.force.out\"));\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-checkf.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-checkf\n#include \"Example_nnp_checkf.h\"\n#include \"nnp_test.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_checkf> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_checkf const /*example*/)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-checkf.log.0000\"));\n    BOOST_REQUIRE(bfs::exists(\"checkf-forces.out\"));\n    BOOST_REQUIRE(bfs::exists(\"checkf-summary.out\"));\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-convert.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-convert\n#include \"Example_nnp_convert.h\"\n#include \"nnp_test.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_convert> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_convert const example)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-convert.log\"));\n    for (auto f : example.createdFiles)\n    {\n        BOOST_REQUIRE(bfs::exists(f));\n    }\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-dataset.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-dataset\n#include \"Example_nnp_dataset.h\"\n#include \"nnp_test.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_dataset> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_dataset const /*example*/)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-dataset.log.0000\"));\n    BOOST_REQUIRE(bfs::exists(\"energy.comp\"));\n    BOOST_REQUIRE(bfs::exists(\"forces.comp\"));\n    BOOST_REQUIRE(bfs::exists(\"output.data\"));\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-dist.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-dist\n#include \"Example_nnp_dist.h\"\n#include \"nnp_test.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_dist> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_dist const example)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-dist.log\"));\n    for (auto f : example.createdFiles)\n    {\n        BOOST_REQUIRE(bfs::exists(f));\n    }\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-norm.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-norm\n#include \"Example_nnp_norm.h\"\n#include \"nnp_test.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_norm> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_norm const example)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-norm.log.0000\"));\n    for (auto f : example.createdFiles)\n    {\n        BOOST_REQUIRE(bfs::exists(f));\n    }\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-predict.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-predict\n#include \"Example_nnp_predict.h\"\n#include \"nnp_test.h\"\n#include \"utility.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\nusing namespace nnp;\n\n//double const accuracy = 10.0 * numeric_limits<double>::epsilon();\ndouble const accuracy = 1E-5; // Output\n\nBoostDataContainer<Example_nnp_predict> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_predict const example)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-predict.log\"));\n    for (auto f : example.createdFiles)\n    {\n        BOOST_REQUIRE(bfs::exists(f));\n    }\n    ifstream file;\n    file.open(\"output.data\");\n    string line;\n    while (getline(file, line))\n    {\n        vector<string> columns = split(reduce(line));\n        if (columns.at(0) != \"energy\") continue;\n        else\n        {\n            BOOST_REQUIRE_SMALL(example.energy - stod(columns.at(1)),\n                                accuracy);\n            break;\n        }\n    }\n    file.close();\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-prune.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-prune\n#include \"Example_nnp_prune.h\"\n#include \"nnp_test.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_prune> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_prune const example)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-prune.log\"));\n    for (auto f : example.createdFiles)\n    {\n        BOOST_REQUIRE(bfs::exists(f));\n    }\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-scaling.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-scaling\n#include \"Example_nnp_scaling.h\"\n#include \"nnp_test.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_scaling> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_scaling const /*example*/)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-scaling.log.0000\"));\n    BOOST_REQUIRE(bfs::exists(\"scaling.data\"));\n    BOOST_REQUIRE(bfs::exists(\"neighbors.histo\"));\n    BOOST_REQUIRE(bfs::exists(\"neighbors.out\"));\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-select.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-select\n#include \"Example_nnp_select.h\"\n#include \"nnp_test.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_select> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_select const example)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-select.log\"));\n    for (auto f : example.createdFiles)\n    {\n        BOOST_REQUIRE(bfs::exists(f));\n    }\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-symfunc.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-symfunc\n#include \"Example_nnp_symfunc.h\"\n#include \"nnp_test.h\"\n\n#include <limits> // std::numeric_limits\n\nusing namespace std;\n\ndouble const accuracy = 10.0 * numeric_limits<double>::epsilon();\n\nBoostDataContainer<Example_nnp_symfunc> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_symfunc const example)\n{\n    BOOST_REQUIRE(bfs::exists(\"nnp-symfunc.log\"));\n    for (auto f : example.createdFiles)\n    {\n        BOOST_REQUIRE(bfs::exists(f));\n    }\n\n    return;\n}\n"
  },
  {
    "path": "test/cpp/test_nnp-train.cpp",
    "content": "#define BOOST_TEST_DYN_LINK\n#define BOOST_TEST_MODULE nnp-train\n#include \"Example_nnp_train.h\"\n#include \"nnp_test.h\"\n#include \"utility.h\"\n\n#include <fstream> // std::ifstream\n#include <string>  // std::string\n#include <vector>  // std::vector\n\nusing namespace std;\nusing namespace nnp;\n\nBoostDataContainer<Example_nnp_train> container;\n\nNNP_TOOL_TEST_CASE()\n\nvoid nnpToolTestBody(Example_nnp_train const example)\n{\n    bool epochFound = false;\n    string line;\n    ifstream file;\n\n    // Grep for \"CI-CHECK\" for code changes if you want to review output files\n    // from non-interactive CI run.\n    //ifstream source(\"nnp-train.log.0000\", ios::binary);\n    //ofstream dest(\"../nnp-train.log.0000.\" + example.name, ios::binary);\n    //dest << source.rdbuf();\n    //source.close();\n    //dest.close();\n    //ifstream source2(\"learning-curve.out\", ios::binary);\n    //ofstream dest2(\"../learning-curve.out.\" + example.name, ios::binary);\n    //dest2 << source2.rdbuf();\n    //source2.close();\n    //dest2.close();\n\n    string filename{\"learning-curve.out\"};\n    if (example.args != \"\")\n        filename += \".stage-\" + example.args;\n\n    file.open(filename);\n    BOOST_REQUIRE(file.is_open());\n    while (getline(file, line))\n    {\n        vector<string> columns = split(reduce(line));\n        if (columns.at(0) == to_string(example.lastEpoch))\n        {\n            epochFound = true;\n            if (example.args == \"1\")\n            {\n                BOOST_REQUIRE_SMALL(example.rmseChargesTrain - stod(columns.at(1)),\n                                    example.accuracy);\n                BOOST_REQUIRE_SMALL(example.rmseChargesTest - stod(columns.at(2)),\n                                    example.accuracy);\n            }\n            else\n            {\n                BOOST_REQUIRE_SMALL(example.rmseEnergyTrain - stod(columns.at(1)),\n                                example.accuracy);\n                BOOST_REQUIRE_SMALL(example.rmseEnergyTest - stod(columns.at(2)),\n                                example.accuracy);\n                BOOST_REQUIRE_SMALL(example.rmseForcesTrain - stod(columns.at(9)),\n                                example.accuracy);\n                BOOST_REQUIRE_SMALL(example.rmseForcesTest - stod(columns.at(10)),\n                                example.accuracy);\n            }\n        }\n    }\n    file.close();\n    BOOST_REQUIRE_MESSAGE(epochFound,\n                          string(\"ERROR: Epoch information was not \"\n                                 \"found in file.\"));\n\n    return;\n}\n"
  },
  {
    "path": "test/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=..\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# PHONY TARGETS\n###############################################################################\n.PHONY: all clean cpp python clean-cpp clean-python\n\n\n###############################################################################\n# RULES\n###############################################################################\n\nall: cpp cpp-coverage python\n\nclean: clean-cpp clean-python\n\ncpp:\n\tcd cpp && $(MAKE)\n\ncpp-coverage:\n\tcd cpp && $(MAKE) coverage\n\nclean-cpp:\n\tcd cpp && $(MAKE) clean\n\npython:\n\tcd python && $(MAKE)\n\nclean-python:\n\tcd python && $(MAKE) clean\n"
  },
  {
    "path": "test/python/.coveragerc",
    "content": "[run]\nplugins = Cython.Coverage\nsource = ../../src/pynnp\n"
  },
  {
    "path": "test/python/makefile",
    "content": "#!/bin/make -f\n\n###############################################################################\n# PROJECT PATHS\n###############################################################################\nPROJECT_DIR=../..\nPROJECT_BIN=$(PROJECT_DIR)/bin\nPROJECT_INCLUDE=$(PROJECT_DIR)/include\nPROJECT_LIB=$(PROJECT_DIR)/lib\n\n\n###############################################################################\n# RULES\n###############################################################################\n.PHONY: all clean\n\nall:\n\texport PYTHONPATH=$(PYTHONPATH):$(PROJECT_DIR)/src/pynnp/ && pytest --cov=pynnp --cov-report html --cov-report term --cov-report=xml -v\n\nclean:\n\t$(RM) -r ./htmlcov\n\t$(RM) .coverage\n\t$(RM) -r .pytest_cache\n\t$(RM) -r __pycache__\n\t$(RM) coverage.xml\n"
  },
  {
    "path": "test/python/setups/Settings/input.nn",
    "content": "###############################################################################\n# GENERAL NNP SETTINGS\n###############################################################################\n# These keywords are (almost) always required.\nnumber_of_elements              2              # Number of elements.\nelements                        S Cu           # Specification of elements.\n#atom_energy                     S  0.0         # Free atom reference energy (S).\n#atom_energy                     Cu 0.0         # Free atom reference energy (Cu).\ncutoff_type                     6 0.0          # Cutoff type (optional argument: shift parameter alpha).\n#scale_symmetry_functions                       # Scale all symmetry functions with min/max values.\nscale_symmetry_functions_sigma                 # Scale all symmetry functions with sigma.\nscale_min_short                 0.0            # Minimum value for scaling.\nscale_max_short                 1.0            # Maximum value for scaling.\n#center_symmetry_functions                      # Center all symmetry functions, i.e. subtract mean value.\nglobal_hidden_layers_short      2              # Number of hidden layers.\nglobal_nodes_short              15 15          # Number of nodes in each hidden layer.\nglobal_activation_short         p p l          # Activation function for each hidden layer and output layer.\n#normalize_nodes                                # Normalize input of nodes.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR DATASET TOOLS\n###############################################################################\n# These keywords are used only by some tools handling data sets:\n# nnp-comp2, nnp-scaling, nnp-dataset, nnp-train.\nuse_short_forces                               # Use forces.\nrandom_seed                     1234567        # Random number generator seed.\n\n###############################################################################\n# ADDITIONAL SETTINGS FOR TRAINING\n###############################################################################\n# These keywords are solely used for training with nnp-train.\nepochs                          10             # Number of training epochs.\nupdater_type                    1              # Weight update method (0 = Gradient Descent, 1 = Kalman filter).\nparallel_mode                   0              # Training parallelization used (0 = Parallel (rank 0 update), 1 = Parallel (all update)).\njacobian_mode                   1              # Jacobian computation mode (0 = Summation to single gradient, 1 = Per-task summed gradient, 2 = Full Jacobian).\nupdate_strategy                 0              # Update strategy (0 = Combined, 1 = Per-element).\nselection_mode                  2              # Update candidate selection mode (0 = Random, 1 = Sort, 2 = Threshold).\ntask_batch_size_energy          1              # Number of energy update candidates prepared per task for each update (0 = Entire training set).\ntask_batch_size_force           1              # Number of force update candidates prepared per task for each update (0 = Entire training set).\nmemorize_symfunc_results                       # Keep symmetry function results in memory.\ntest_fraction                   0.1            # Fraction of structures kept for testing.\nforce_weight                    10.0           # Weight of force updates relative to energy updates.\nshort_energy_fraction           1.000          # Fraction of energy updates per epoch.\nshort_force_fraction            0.02315        # Fraction of force updates per epoch.\nshort_energy_error_threshold    0.00           # RMSE threshold for energy update candidates.\nshort_force_error_threshold     1.00           # RMSE threshold for force update candidates.\nrmse_threshold_trials           3              # Maximum number of RMSE threshold trials.\n#use_old_weights_short                          # Restart fitting with old weight parameters.\nweights_min                     -1.0           # Minimum value for initial random weights.\nweights_max                     1.0            # Maximum value for initial random weights.\n#precondition_weights                           # Precondition weights with initial energies.\n#nguyen_widrow_weights_short                    # Initialize neural network weights according to Nguyen-Widrow scheme.\nwrite_trainpoints               1              # Write energy comparison every this many epochs.\nwrite_trainforces               1              # Write force comparison every this many epochs.\nwrite_weights_epoch             1              # Write weights every this many epochs.\nwrite_neuronstats               1              # Write neuron statistics every this many epochs.\nwrite_trainlog                                 # Write training log file.\n####################\n# GRADIENT DESCENT #\n####################\n# This section is only used if \"updater_type\" is \"0\".\ngradient_type                   1              # Gradient descent type (0 = Fixed step size, 1 = Adam).\ngradient_eta                    1.0E-5         # Fixed step size gradient descent parameter eta.\ngradient_adam_eta               1.0E-3         # Adam parameter eta.\ngradient_adam_beta1             0.9            # Adam parameter beta1.\ngradient_adam_beta2             0.999          # Adam parameter beta2.\ngradient_adam_epsilon           1.0E-8         # Adam parameter epsilon.\n############################\n# KALMAN FILTER (STANDARD) #\n############################\n# This section is only used if \"updater_type\" is \"1\".\nkalman_type                     0              # Kalman filter type (0 = Standard, 1 = Fading memory).\nkalman_epsilon                  1.0E-2         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\nkalman_q0                       0.01           # General Kalman filter parameter q0 (\"large\").\nkalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\nkalman_qmin                     1.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\nkalman_eta                      0.01           # Standard Kalman filter parameter eta (0.001-1.0).\nkalman_etatau                   2.302          # Standard Kalman filter parameter etatau (2.302 => 1 order of magnitude per epoch).\nkalman_etamax                   1.0            # Standard Kalman filter parameter etamax (1.0+).\n#################################\n# KALMAN FILTER (FADING MEMORY) #\n#################################\n# This section is only used if \"updater_type\" is \"1\".\n# The settings here enable an alternative Kalman filter variant and are NOT RECOMMENDED!\n#kalman_type                     1              # Kalman filter type (0 = Standard, 1 = Fading memory).\n#kalman_epsilon                  1.0E-1         # General Kalman filter parameter epsilon (sigmoidal: 0.01, linear: 0.001).\n#kalman_q0                       0.00           # General Kalman filter parameter q0 (\"large\").\n#kalman_qtau                     2.302          # General Kalman filter parameter qtau (2.302 => 1 order of magnitude per epoch).\n#kalman_qmin                     0.0E-6         # General Kalman filter parameter qmin (typ. 1.0E-6).\n#kalman_lambda_short             0.96000        # Fading memory Kalman filter parameter lambda (forgetting factor 0.95-0.99).\n#kalman_nue_short                0.99950        # Fading memory Kalman filter parameter nu (0.99-0.9995).\n\n###############################################################################\n# SYMMETRY FUNCTIONS\n###############################################################################\n\n# Radial symmetry function (type 2):\n#symfunction_short <element-central> 2 <element-neighbor> <eta> <rshift> <rcutoff>\n\n# Narrow Angular symmetry function (type 3):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 3 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Wide Angular symmetry function (type 9):\n# NOTE: <<rshift>> is optional!\n#symfunction_short <element-central> 9 <element-neighbor1> <element-neighbor2> <eta> <lambda> <zeta> <rcutoff> <<rshift>\n\n# Generating radial symmetry function set:\n# mode  = shift    \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         9\n# grid  = 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5\n# Radial symmetry functions for element S \nsymfunction_short S  2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 S  2.000E+00 5.500E+00 6.000E+00\n\nsymfunction_short S  2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short S  2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Radial symmetry functions for element Cu\nsymfunction_short Cu 2 S  2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 S  2.000E+00 5.500E+00 6.000E+00\n\n# symfunction_short Cu 2 Cu 2.000E+00 1.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 2.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 3.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 4.500E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.000E+00 6.000E+00\nsymfunction_short Cu 2 Cu 2.000E+00 5.500E+00 6.000E+00\n\n# Generating narrow angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Narrow angular symmetry functions for element S \nsymfunction_short S  3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Narrow angular symmetry functions for element Cu\nsymfunction_short Cu 3 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 3 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Generating wide angular symmetry function set:\n# mode  = center   \n# r_0   = 1.500E+00\n# r_c   = 6.000E+00\n# r_N   = 5.500E+00\n# N     =         3\n# grid  = 1.5 3.5 5.5\n# zetas = 1.0 6.0\n# Wide angular symmetry functions for element S \nsymfunction_short S  9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short S  9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\n# Wide angular symmetry functions for element Cu\nsymfunction_short Cu 9 S  S  2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  S  1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 S  Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 2.222E-01  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 4.082E-02  1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 1.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02 -1 6.000E+00 6.000E+00 0.000E+00\nsymfunction_short Cu 9 Cu Cu 1.653E-02  1 6.000E+00 6.000E+00 0.000E+00\n"
  },
  {
    "path": "test/python/test_Atom.py",
    "content": "import pytest\nfrom pynnp import Atom, Vec3D\n\na = 13\nb = \"b\"\nc = 13.25323\nd = True\n\n@pytest.fixture\ndef a1():\n    global a1x, a1y, a1z\n    a1x, a1y, a1z = 1.0, 2.0, 3.0\n    a = Atom()\n    a.r = Vec3D(a1x, a1y, a1z)\n    return a\n\n@pytest.fixture\ndef v1():\n    global v1x, v1y, v1z\n    v1x, v1y, v1z = 1.0, 2.0, 3.0\n    v = Vec3D(v1x, v1y, v1z)\n    return v\n\nclass Test___cinit__:\n    def test_skeleton_initialization(self):\n        a = Atom(True)\n        assert isinstance(a, Atom), \"Can not create skeleton Atom instance.\"\n    def test_empty_initialization(self):\n        a = Atom()\n        assert isinstance(a, Atom), \"Can not create empty Atom instance.\"\n        assert isinstance(a.r, Vec3D), \"Member Vec3D not initialized.\"\n        assert isinstance(a.f, Vec3D), \"Member Vec3D not initialized.\"\n        assert isinstance(a.fRef, Vec3D), \"Member Vec3D not initialized.\"\n\nclass Test_hasNeighborList:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.hasNeighborList, bool), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1):\n        a1.hasNeighborList = not d\n        a1.hasNeighborList = d\n        assert a1.hasNeighborList == d, \"Wrong attribute setter or getter.\"\n\nclass Test_hasSymmetryFunctions:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.hasSymmetryFunctions, bool), (\n               \"Wrong attribute type.\")\n    def test_set_and_get(self, a1):\n        a1.hasSymmetryFunctions = not d\n        a1.hasSymmetryFunctions = d\n        assert a1.hasSymmetryFunctions == d, (\n               \"Wrong attribute setter or getter.\")\n\nclass Test_hasSymmetryFunctionDerivatives:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.hasSymmetryFunctionDerivatives, bool), (\n               \"Wrong attribute type.\")\n    def test_set_and_get(self, a1):\n        a1.hasSymmetryFunctionDerivatives = not d\n        a1.hasSymmetryFunctionDerivatives = d\n        assert a1.hasSymmetryFunctionDerivatives == d, (\n               \"Wrong attribute setter or getter.\")\n\nclass Test_index:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.index, int), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1):\n        with pytest.raises(TypeError):\n            a1.index = b\n        a1.index = a\n        assert a1.index == a, \"Wrong attribute setter or getter.\"\n\nclass Test_indexStructure:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.indexStructure, int), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1):\n        with pytest.raises(TypeError):\n            a1.indexStructure = b\n        a1.indexStructure = a\n        assert a1.indexStructure == a, \"Wrong attribute setter or getter.\"\n\nclass Test_tag:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.tag, int), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1):\n        with pytest.raises(TypeError):\n            a1.tag = b\n        a1.tag = a\n        assert a1.tag == a, \"Wrong attribute setter or getter.\"\n\nclass Test_element:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.element, int), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1):\n        with pytest.raises(TypeError):\n            a1.element = b\n        a1.element = a\n        assert a1.element == a, \"Wrong attribute setter or getter.\"\n\nclass Test_numNeighbors:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.numNeighbors, int), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1):\n        with pytest.raises(TypeError):\n            a1.numNeighbors = b\n        a1.numNeighbors = a\n        assert a1.numNeighbors == a, \"Wrong attribute setter or getter.\"\n\nclass Test_numNeighborsUnique:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.numNeighborsUnique, int), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1):\n        with pytest.raises(TypeError):\n            a1.numNeighborsUnique = b\n        a1.numNeighborsUnique = a\n        assert a1.numNeighborsUnique == a, \"Wrong attribute setter or getter.\"\n\nclass Test_numSymmetryFunctions:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.numSymmetryFunctions, int), (\n               \"Wrong attribute type.\")\n    def test_set_and_get(self, a1):\n        with pytest.raises(TypeError):\n            a1.numSymmetryFunctions = b\n        a1.numSymmetryFunctions = a\n        assert a1.numSymmetryFunctions == a, (\n               \"Wrong attribute setter or getter.\")\n\nclass Test_energy:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.energy, float), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1):\n        with pytest.raises(TypeError):\n            a1.energy = b\n        a1.energy = c\n        assert a1.energy == c, \"Wrong attribute setter or getter.\"\n\nclass Test_charge:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.charge, float), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1):\n        with pytest.raises(TypeError):\n            a1.charge = b\n        a1.charge = c\n        assert a1.charge == c, \"Wrong attribute setter or getter.\"\n\nclass Test_r:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.r, Vec3D), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1, v1):\n        with pytest.raises(TypeError):\n            a1.r = b\n        a1.r = v1\n        assert a1.r.r == [v1x, v1y, v1z], (\n               \"Wrong attribute setter or getter.\")\n\nclass Test_f:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.f, Vec3D), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1, v1):\n        with pytest.raises(TypeError):\n            a1.f = b\n        a1.f = v1\n        assert a1.f.r == [v1x, v1y, v1z], (\n               \"Wrong attribute setter or getter.\")\n\nclass Test_fRef:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.fRef, Vec3D), \"Wrong attribute type.\"\n    def test_set_and_get(self, a1, v1):\n        with pytest.raises(TypeError):\n            a1.fRef = b\n        a1.fRef = v1\n        assert a1.fRef.r == [v1x, v1y, v1z], (\n               \"Wrong attribute setter or getter.\")\n\nclass Test_neighborsUnique:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.neighborsUnique, list), \"Wrong attribute type.\"\n    # TODO: Test content.\n\nclass Test_numNeighborsPerElement:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.numNeighborsPerElement, list), (\n               \"Wrong attribute type.\")\n    # TODO: Test content.\n\nclass Test_G:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.G, list), (\n               \"Wrong attribute type.\")\n    # TODO: Test content.\n\nclass Test_dEdG:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.dEdG, list), (\n               \"Wrong attribute type.\")\n    # TODO: Test content.\n\n#class Test_dGdxia:\n#    def test_correct_type(self, a1):\n#        assert isinstance(a1.dGdxia, list), (\n#               \"Wrong attribute type.\")\n#    # TODO: Test content.\n\nclass Test_dGdr:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.dGdr, list), (\n               \"Wrong attribute type.\")\n    # TODO: Test content.\n\nclass Test_neighbors:\n    def test_correct_type(self, a1):\n        assert isinstance(a1.neighbors, list), (\n               \"Wrong attribute type.\")\n    # TODO: Test content.\n\nclass Test_info():\n    def test_return_list(self, a1):\n        info = a1.info()\n        assert isinstance(info, list), \"Wrong return type.\"\n        assert all(isinstance(i, str) for i in info), (\n               \"Wrong type of list elements.\")\n"
  },
  {
    "path": "test/python/test_CutoffFunction.py",
    "content": "import pytest\nfrom pynnp import CutoffFunction\n\ncutoff_radius = 3.0\ncutoff_parameter = 0.2\ncutoff_function_types = [CutoffFunction.CT_HARD,\n                         CutoffFunction.CT_COS,\n                         CutoffFunction.CT_TANHU,\n                         CutoffFunction.CT_TANH,\n                         CutoffFunction.CT_EXP,\n                         CutoffFunction.CT_POLY1,\n                         CutoffFunction.CT_POLY2,\n                         CutoffFunction.CT_POLY3,\n                         CutoffFunction.CT_POLY4]\n\ntest_radius = 0.8 * cutoff_radius\n\ncutoff_function_values = [1.0000000000000000E+00,\n                          1.4644660940672610E-01,\n                          7.6891537120697701E-03,\n                          1.7406350897769030E-02,\n                          2.7645304662956416E-01,\n                          1.5624999999999989E-01,\n                          1.0351562500000003E-01,\n                          7.0556640624999140E-02,\n                          4.8927307128909442E-02]\n\ncutoff_function_dvalues = [ 0.0000000000000000E+00,\n                           -4.6280030605816297E-01,\n                           -3.7439367857705103E-02,\n                           -8.4753511078717925E-02,\n                           -9.0270382572918983E-01,\n                           -4.6874999999999989E-01,\n                           -4.3945312499999917E-01,\n                           -3.8452148437500033E-01,\n                           -3.2444000244141674E-01]\n\n@pytest.fixture\ndef c1():\n    c = CutoffFunction()\n    c.setCutoffRadius(cutoff_radius)\n    c.setCutoffParameter(cutoff_parameter)\n    return c\n\nclass Test___cinit__:\n    def test_skeleton_initialization(self):\n        l = CutoffFunction(True)\n        assert isinstance(l, CutoffFunction), (\n               \"Can not create skeleton CutoffFunction instance.\")\n    def test_empty_initialization(self):\n        l = CutoffFunction()\n        assert isinstance(l, CutoffFunction), (\n               \"Can not create empty CutoffFunction instance.\")\n\nclass Test_setCutoffType:\n    @pytest.mark.parametrize(\"cf_type\", cutoff_function_types)\n    def test_set_correct_type(self, c1, cf_type):\n        c1.setCutoffType(cf_type)\n    def test_set_unknown_type(self, c1):\n        with pytest.raises(ValueError):\n            c1.setCutoffType(len(cutoff_function_types))\n\nclass Test_setCutoffRadius:\n    def test_set_float_value(self, c1):\n        c1.setCutoffRadius(12.0)\n    def test_set_wrong_argument(self, c1):\n        with pytest.raises(TypeError):\n            c1.setCutoffRadius(\"a\")\n\nclass Test_setCutoffParameter:\n    def test_set_float_value(self, c1):\n        c1.setCutoffParameter(0.3)\n    def test_set_wrong_float_value(self, c1):\n        with pytest.raises(ValueError):\n            c1.setCutoffParameter(-0.000001)\n        with pytest.raises(ValueError):\n            c1.setCutoffParameter(1.0)\n        with pytest.raises(ValueError):\n            c1.setCutoffParameter(1.000001)\n    def test_set_wrong_argument(self, c1):\n        with pytest.raises(TypeError):\n            c1.setCutoffParameter(\"a\")\n\nclass Test_f:\n    @pytest.mark.parametrize(\"cf_type\", cutoff_function_types)\n    def test_boundaries(self, c1, cf_type):\n        c1.setCutoffType(cf_type)\n        if cf_type not in [CutoffFunction.CT_TANHU]:\n            assert c1.f(0.0) == pytest.approx(1.0), (\n                   \"Wrong cutoff function value.\")\n        if cf_type not in [CutoffFunction.CT_TANHU, CutoffFunction.CT_TANH]:\n            assert c1.f(cutoff_radius * cutoff_parameter) == pytest.approx(1.0), (\n                   \"Wrong cutoff function value.\")\n        assert c1.f(cutoff_radius) == pytest.approx(0.0), (\n               \"Wrong cutoff function value.\")\n    @pytest.mark.parametrize(\"cf_type, cf_value\",\n                             zip(cutoff_function_types, cutoff_function_values))\n    def test_nonzero_radius(self, c1, cf_type, cf_value):\n        c1.setCutoffType(cf_type)\n        assert c1.f(test_radius) == pytest.approx(cf_value), (\n               \"Wrong cutoff function value.\")\n    def test_nonfloat_argument(self, c1):\n        with pytest.raises(TypeError):\n            c1.f(\"a\")\n\nclass Test_df:\n    @pytest.mark.parametrize(\"cf_type\", cutoff_function_types)\n    def test_boundaries(self, c1, cf_type):\n        c1.setCutoffType(cf_type)\n        if cf_type not in [CutoffFunction.CT_TANHU, CutoffFunction.CT_TANH]:\n            assert c1.df(0.0) == pytest.approx(0.0), (\n                   \"Wrong cutoff derivative value.\")\n        assert c1.df(cutoff_radius) == pytest.approx(0.0), (\n               \"Wrong cutoff derivative value.\")\n    @pytest.mark.parametrize(\"cf_type, cf_dvalue\",\n                             zip(cutoff_function_types,\n                                 cutoff_function_dvalues))\n    def test_nonzero_radius(self, c1, cf_type, cf_dvalue):\n        c1.setCutoffType(cf_type)\n        assert c1.df(test_radius) == pytest.approx(cf_dvalue), (\n               \"Wrong cutoff derivative value.\")\n    def test_nonfloat_argument(self, c1):\n        with pytest.raises(TypeError):\n            c1.df(\"a\")\n\nclass Test_fdf:\n    @pytest.mark.parametrize(\"cf_type\", cutoff_function_types)\n    def test_boundaries(self, c1, cf_type):\n        c1.setCutoffType(cf_type)\n\n        f, df = c1.fdf(0.0)\n        if cf_type not in [CutoffFunction.CT_TANHU]:\n            assert f == pytest.approx(1.0), (\n                   \"Wrong cutoff function value.\")\n        if cf_type not in [CutoffFunction.CT_TANHU, CutoffFunction.CT_TANH]:\n            assert df == pytest.approx(0.0), (\n                   \"Wrong cutoff derivative value.\")\n\n        f, df = c1.fdf(cutoff_radius * cutoff_parameter)\n        if cf_type not in [CutoffFunction.CT_TANHU, CutoffFunction.CT_TANH]:\n            assert f == pytest.approx(1.0), (\n                   \"Wrong cutoff function value.\")\n\n        f, df = c1.fdf(cutoff_radius)\n        assert f == pytest.approx(0.0), (\n               \"Wrong cutoff function value.\")\n        assert df == pytest.approx(0.0), (\n               \"Wrong cutoff derivative value.\")\n    @pytest.mark.parametrize(\"cf_type, cf_value, cf_dvalue\",\n                             zip(cutoff_function_types,\n                                 cutoff_function_values,\n                                 cutoff_function_dvalues))\n    def test_nonzero_radius(self, c1, cf_type, cf_value, cf_dvalue):\n        c1.setCutoffType(cf_type)\n        f, df = c1.fdf(test_radius)\n        assert f == pytest.approx(cf_value), (\n               \"Wrong cutoff function value.\")\n        assert df == pytest.approx(cf_dvalue), (\n               \"Wrong cutoff derivative value.\")\n    def test_nonfloat_argument(self, c1):\n        with pytest.raises(TypeError):\n            c1.fdf(\"a\")\n"
  },
  {
    "path": "test/python/test_ElementMap.py",
    "content": "import pytest\nfrom pynnp import ElementMap\n\n@pytest.fixture\ndef em1():\n    global elements\n    elements = [\"H\", \"O\", \"S\", \"Cu\"]\n    em = ElementMap()\n    em.registerElements(elements[3] + \" \" + elements[1] + \" \" +\n                        elements[2] + \" \" + elements[0])\n    return em\n\nclass Test___cinit__:\n    def test_skeleton_initialization(self):\n        em = ElementMap(True)\n        assert isinstance(em, ElementMap), (\n               \"Can not create skeleton ElementMap instance.\")\n    def test_empty_initialization(self):\n        em = ElementMap()\n        assert isinstance(em, ElementMap), (\n               \"Can not create empty ElementMap instance.\")\n\nclass Test_registerElements:\n    def test_nonstring_argument(self):\n        em = ElementMap()\n        with pytest.raises(TypeError):\n            em.registerElements(123)\n    def test_correct_elements_registered(self):\n        em = ElementMap()\n        em.registerElements(\"Cu O S H\")\n        assert em[0] == \"H\", \"Wrong element registration.\"\n        assert em[1] == \"O\", \"Wrong element registration.\"\n        assert em[2] == \"S\", \"Wrong element registration.\"\n        assert em[3] == \"Cu\", \"Wrong element registration.\"\n\nclass Test___getitem__:\n    def test_correct_element_index(self, em1):\n        for i, e in enumerate(elements):\n            assert em1[e] == i, \"Wrong element index returned.\"\n    def test_correct_element_symbol(self, em1):\n        for i, e in enumerate(elements):\n            assert em1[i] == e, \"Wrong element symbol returned.\"\n    def test_out_of_bounds_index(self, em1):\n        with pytest.raises(IndexError):\n            em1[4]\n    def test_unknown_symbol(self, em1):\n        with pytest.raises(ArithmeticError):\n            em1[\"XY\"]\n    def test_wrong_argument_type(self, em1):\n        with pytest.raises(NotImplementedError):\n            em1[1.23]\n\nclass Test_size:\n    def test_correct_empty_size_returned(self):\n        em = ElementMap()\n        assert em.size() == 0, \"Wrong size returned.\"\n    def test_correct_size_returned(self, em1):\n        assert em1.size() == 4, \"Wrong size returned.\"\n\nclass Test_index:\n    def test_correct_element_index(self, em1):\n        for i, e in enumerate(elements):\n            assert em1.index(e) == i, \"Wrong element order.\"\n    def test_wrong_argument_type(self, em1):\n        with pytest.raises(TypeError):\n            em1.index(1)\n\nclass Test_symbol:\n    def test_correct_element_index(self, em1):\n        for i, e in enumerate(elements):\n            assert em1.symbol(i) == e, \"Wrong element order.\"\n    def test_wrong_argument_type(self, em1):\n        with pytest.raises(TypeError):\n            em1.symbol(\"H\")\n\nclass Test_deregisterElements:\n    def test_empty_map(self, em1):\n        em1.deregisterElements()\n        assert em1.size() == 0, \"ElementMap not empty.\"\n\nclass Test_symbolFromAtomicNumber:\n    def test_some_elements(self, em1):\n        assert em1.symbolFromAtomicNumber(1) == \"H\", \"Wrong element symbol.\"\n        assert em1.symbolFromAtomicNumber(2) == \"He\", \"Wrong element symbol.\"\n        assert em1.symbolFromAtomicNumber(8) == \"O\", \"Wrong element symbol.\"\n        assert em1.symbolFromAtomicNumber(16) == \"S\", \"Wrong element symbol.\"\n        assert em1.symbolFromAtomicNumber(29) == \"Cu\", \"Wrong element symbol.\"\n        with pytest.raises(RuntimeError):\n            em1.symbolFromAtomicNumber(0)\n            em1.symbolFromAtomicNumber(300)\n\nclass Test_info():\n    def test_return_list(self, em1):\n        info = em1.info()\n        assert isinstance(info, list), \"Wrong return type.\"\n        assert all(isinstance(i, str) for i in info), (\n               \"Wrong type of list elements.\")\n"
  },
  {
    "path": "test/python/test_Log.py",
    "content": "import pytest\nfrom pynnp import Log\n\nd = True\n\n@pytest.fixture\ndef l1():\n    l = Log()\n    return l\n\nclass Test___cinit__:\n    def test_skeleton_initialization(self):\n        l = Log(True)\n        assert isinstance(l, Log), (\n               \"Can not create skeleton Log instance.\")\n    def test_empty_initialization(self):\n        l = Log()\n        assert isinstance(l, Log), (\n               \"Can not create empty Log instance.\")\n\nclass Test_addLogEntry:\n    def test_add_string_entry(self):\n        l = Log()\n        l.addLogEntry(\"Testing...\")\n    def test_add_nonstring_entry(self):\n        l = Log()\n        with pytest.raises(TypeError):\n            l.addLogEntry(123)\n\nclass Test_getLog:\n    def test_read_two_entries(self):\n        l = Log()\n        l.addLogEntry(\"First entry.\")\n        l.addLogEntry(\"Second entry.\")\n        log = l.getLog()\n        assert log[0] == \"First entry.\", \"Incorrect log entry returned.\"\n        assert log[1] == \"Second entry.\", \"Incorrect log entry returned.\"\n\nclass Test_writeToStdout:\n    def test_correct_type(self, l1):\n        assert isinstance(l1.writeToStdout, bool), \"Wrong attribute type.\"\n    def test_set_and_get(self, l1):\n        l1.writeToStdout = not d\n        l1.writeToStdout = d\n        assert l1.writeToStdout == d, \"Wrong attribute setter or getter.\"\n"
  },
  {
    "path": "test/python/test_Neighbor.py",
    "content": "import pytest\nfrom pynnp import Neighbor, Vec3D\n\na = 13\nb = \"b\"\nc = 13.25323\n\n@pytest.fixture\ndef n1():\n    global d1x, d1y, d1z\n    d1x, d1y, d1z = 1.0, 2.0, 3.0\n    n = Neighbor()\n    n.dr = Vec3D(d1x, d1y, d1z)\n    n.d = n.dr.norm()\n    n.element = 0\n    return n\n\n@pytest.fixture\ndef n2():\n    global d2x, d2y, d2z\n    d2x, d2y, d2z = 4.0, 5.0, 6.0\n    n = Neighbor()\n    n.dr = Vec3D(d2x, d2y, d2z)\n    n.d = n.dr.norm()\n    n.element = 1\n    return n\n\nclass Test___cinit__:\n    def test_skeleton_initialization(self):\n        n = Neighbor(True)\n        assert isinstance(n, Neighbor), (\n               \"Can not create skeleton Neighbor instance.\")\n    def test_empty_initialization(self):\n        n = Neighbor()\n        assert isinstance(n, Neighbor), (\n               \"Can not create empty Neighbor instance.\")\n        assert isinstance(n.dr, Vec3D), \"Member Vec3D not initialized.\"\n\nclass Test_index:\n    def test_correct_type(self, n1):\n        assert isinstance(n1.index, int), \"Wrong attribute type.\"\n    def test_set_and_get(self, n1):\n        with pytest.raises(TypeError):\n            n1.index = b\n        n1.index = a\n        assert n1.index == a, \"Wrong attribute setter or getter.\"\n\nclass Test_tag:\n    def test_correct_type(self, n1):\n        assert isinstance(n1.tag, int), \"Wrong attribute type.\"\n    def test_set_and_get(self, n1):\n        with pytest.raises(TypeError):\n            n1.tag = b\n        n1.tag = a\n        assert n1.tag == a, \"Wrong attribute setter or getter.\"\n\nclass Test_element:\n    def test_correct_type(self, n1):\n        assert isinstance(n1.element, int), \"Wrong attribute type.\"\n    def test_set_and_get(self, n1):\n        with pytest.raises(TypeError):\n            n1.element = b\n        n1.element = a\n        assert n1.element == a, \"Wrong attribute setter or getter.\"\n\nclass Test_d:\n    def test_correct_type(self, n1):\n        assert isinstance(n1.d, float), \"Wrong attribute type.\"\n    def test_set_and_get(self, n1):\n        with pytest.raises(TypeError):\n            n1.d = b\n        n1.d = c\n        assert n1.d == c, \"Wrong attribute setter or getter.\"\n\nclass Test_dr:\n    def test_correct_type(self, n1):\n        assert isinstance(n1.dr, Vec3D), \"Wrong attribute type.\"\n    def test_set_and_get(self, n1):\n        with pytest.raises(TypeError):\n            n1.dr = b\n        n1.dr = Vec3D(1.0, 2.0, 3.0)\n        assert n1.dr[0] == 1.0, \"Wrong attribute setter or getter.\"\n        assert n1.dr[1] == 2.0, \"Wrong attribute setter or getter.\"\n        assert n1.dr[2] == 3.0, \"Wrong attribute setter or getter.\"\n\nclass Test_dGdr:\n    def test_correct_type(self, n1):\n        assert isinstance(n1.dGdr, list), \"Wrong attribute type.\"\n    # TODO: Test content.\n\nclass Test___eq__:\n    def test_not_equal(self, n1, n2):\n        assert (n1 == n2) is False, \"Different neighbors are equal.\"\n    def test_element_different(self, n1, n2):\n        n1.d = n2.d\n        assert (n1 == n2) is False, \"Different neighbors are equal.\"\n    def test_distance_different(self, n1, n2):\n        n1.element = n2.element\n        assert (n1 == n2) is False, \"Different neighbors are equal.\"\n    def test_equal(self, n1, n2):\n        n1.d = n2.d\n        n1.element = n2.element\n        assert n1 == n2, \"Equal neighbors are not equal.\"\n\nclass Test___ne__:\n    def test_equal(self, n1, n2):\n        assert (n1 != n2) is False, \"Different neighbors are not different.\"\n    def test_element_different(self, n1, n2):\n        n1.d = n2.d\n        assert n1 != n2, \"Different neighbors are not different.\"\n    def test_distance_different(self, n1, n2):\n        n1.element = n2.element\n        assert n1 != n2, \"Different neighbors are not different.\"\n    def test_equal(self, n1, n2):\n        n1.d = n2.d\n        n1.element = n2.element\n        assert (n1 != n2) is False, \"Equal neighbors are not not different.\"\n\n#class Test___lt__:\n#    def test_less_than(self, n1, n2):\n#        assert n1 < n2, \"Wrong ordering of neighbors.\"\n#    def test_greater_than(self, n1, n2):\n#        assert (n2 < n1) is False, \"Wrong ordering of neighbors.\"\n#    def test_equal_distance(self, n1, n2):\n#        n1.d = n2.d\n#        assert n1 < n2, \"Wrong ordering of neighbors.\"\n#    def test_equal_element(self, n1, n2):\n#        n1.element = n2.element\n#        assert n1 < n2, \"Wrong ordering of neighbors.\"\n#    def test_equal(self, n1, n2):\n#        n1.d = n2.d\n#        n1.element = n2.element\n#        assert (n1 < n2) is False, \"Wrong ordering of neighbors.\"\n#\n#class Test___gt__:\n#    def test_less_than(self, n1, n2):\n#        assert (n1 > n2) is False, \"Wrong ordering of neighbors.\"\n#    def test_greater_than(self, n1, n2):\n#        assert n2 > n1, \"Wrong ordering of neighbors.\"\n#    def test_equal_distance(self, n1, n2):\n#        n1.d = n2.d\n#        assert n2 > n1, \"Wrong ordering of neighbors.\"\n#    def test_equal_element(self, n1, n2):\n#        n1.element = n2.element\n#        assert n2 > n1, \"Wrong ordering of neighbors.\"\n#    def test_equal(self, n1, n2):\n#        n1.d = n2.d\n#        n1.element = n2.element\n#        assert (n2 > n1) is False, \"Wrong ordering of neighbors.\"\n#\nclass Test___le__:\n    def test_less_than(self, n1, n2):\n        assert n1 <= n2, \"Wrong ordering of neighbors.\"\n    def test_greater_than(self, n1, n2):\n        assert (n2 <= n1) is False, \"Wrong ordering of neighbors.\"\n    def test_equal_distance(self, n1, n2):\n        n1.d = n2.d\n        assert n1 <= n2, \"Wrong ordering of neighbors.\"\n    def test_equal_element(self, n1, n2):\n        n1.element = n2.element\n        assert n1 <= n2, \"Wrong ordering of neighbors.\"\n    def test_equal(self, n1, n2):\n        n1.d = n2.d\n        n1.element = n2.element\n        assert n1 <= n2, \"Wrong ordering of neighbors.\"\n\nclass Test___ge__:\n    def test_less_than(self, n1, n2):\n        assert n2 >= n1, \"Wrong ordering of neighbors.\"\n    def test_greater_than(self, n1, n2):\n        assert (n1 >= n2) is False, \"Wrong ordering of neighbors.\"\n    def test_equal_distance(self, n1, n2):\n        n1.d = n2.d\n        assert n2 >= n1, \"Wrong ordering of neighbors.\"\n    def test_equal_element(self, n1, n2):\n        n1.element = n2.element\n        assert n2 >= n1, \"Wrong ordering of neighbors.\"\n    def test_equal(self, n1, n2):\n        n1.d = n2.d\n        n1.element = n2.element\n        assert n2 >= n1, \"Wrong ordering of neighbors.\"\n"
  },
  {
    "path": "test/python/test_Settings.py",
    "content": "import pytest\nimport os, shutil\nfrom pynnp import Settings\n\n@pytest.fixture\ndef prepare_dir(request):\n    dirname = \"workdir\"\n    if os.path.exists(dirname):\n        shutil.rmtree(dirname)\n    shutil.copytree(request.param, dirname)\n    olddir = os.getcwd()\n    os.chdir(dirname)\n    yield\n    os.chdir(olddir)\n    shutil.rmtree(dirname)\n\nprepare_default_dir = pytest.mark.parametrize('prepare_dir',\n                                              [\"setups/Settings\"],\n                                              indirect=True)\n\n@pytest.fixture\ndef s1():\n    s = Settings()\n    s.loadFile(\"input.nn\")\n    return s\n\nclass Test___cinit__:\n    def test_skeleton_initialization(self):\n        s = Settings(True)\n        assert isinstance(s, Settings), (\n               \"Can not create skeleton Settings instance.\")\n    def test_empty_initialization(self):\n        s = Settings()\n        assert isinstance(s, Settings), (\n               \"Can not create empty Settings instance.\")\n\n@prepare_default_dir\nclass Test_loadFile:\n    def test_file_read(self, prepare_dir):\n        s = Settings()\n        assert len(s.getSettingsLines()) == 0, \"Settings not empty.\"\n        s.loadFile(\"input.nn\")\n        assert len(s.getSettingsLines()) > 0, \"No lines were read.\"\n\n@prepare_default_dir\nclass Test___getitem__:\n    def test_existing_key(self, prepare_dir, s1):\n        assert isinstance(s1[\"number_of_elements\"], str), (\n               \"Did not get a value.\")\n        assert int(s1[\"number_of_elements\"]) == 2, (\n               \"Incorrect result returned.\")\n    def test_nonexisting_key(self, prepare_dir, s1):\n        with pytest.raises(RuntimeError):\n            s1[\"asdf\"]\n    def test_nonstring_key(self, prepare_dir, s1):\n        with pytest.raises(TypeError):\n            s1[3]\n\n@prepare_default_dir\nclass Test_keywordExists:\n    def test_existing_key(self, prepare_dir, s1):\n        assert s1.keywordExists(\"number_of_elements\") is True, (\n               \"Keyword exists but return value is False.\")\n    def test_nonexisting_key(self, prepare_dir, s1):\n        with pytest.raises(RuntimeError):\n            s1.keywordExists(\"asdf\")\n    def test_nonstring_key(self, prepare_dir, s1):\n        with pytest.raises(TypeError):\n            s1.keywordExists(3)\n\n@prepare_default_dir\nclass Test_getValue:\n    def test_existing_key(self, prepare_dir, s1):\n        assert isinstance(s1.getValue(\"number_of_elements\"), str), (\n               \"Did not get a value.\")\n        assert int(s1.getValue(\"number_of_elements\")) == 2, (\n               \"Incorrect result returned.\")\n    def test_nonexisting_key(self, prepare_dir, s1):\n        with pytest.raises(RuntimeError):\n            s1.getValue(\"asdf\")\n    def test_nonstring_key(self, prepare_dir, s1):\n        with pytest.raises(TypeError):\n            s1.getValue(3)\n\n@prepare_default_dir\nclass Test_info():\n    def test_return_list(self, prepare_dir, s1):\n        info = s1.info()\n        assert isinstance(info, list), \"Wrong return type.\"\n        assert all(isinstance(i, str) for i in info), (\n               \"Wrong type of list elements.\")\n\n@prepare_default_dir\nclass Test_getSettingsLines():\n    def test_return_list(self, prepare_dir, s1):\n        lines = s1.getSettingsLines()\n        assert isinstance(lines, list), \"Wrong return type.\"\n        assert all(isinstance(i, str) for i in lines), (\n               \"Wrong type of list elements.\")\n        f = open(\"input.nn\")\n        for i, fline in enumerate(f):\n            assert fline.rstrip(\"\\r\\n\") == lines[i], \"Different line content.\"\n"
  },
  {
    "path": "test/python/test_Vec3D.py",
    "content": "import pytest\nfrom pynnp import Vec3D\n\na = 2.5\n\n@pytest.fixture\ndef v1():\n    global v1x, v1y, v1z\n    v1x, v1y, v1z = 1.0, 2.0, 3.0\n    v = Vec3D(v1x, v1y, v1z)\n    return v\n\n@pytest.fixture\ndef v2():\n    global v2x, v2y, v2z\n    v2x, v2y, v2z = -5.0, -2.0, 3.0\n    v = Vec3D(v2x, v2y, v2z)\n    return v\n\nclass Test___cinit__:\n    def test_skeleton_initialization(self):\n        v = Vec3D(True)\n        assert isinstance(v, Vec3D), \"Can not create skeleton Vec3D instance.\"\n    def test_empty_initialization(self):\n        v = Vec3D()\n        assert isinstance(v, Vec3D), \"Can not create empty Vec3D instance.\"\n        assert v.r == [0.0, 0.0, 0.0], (\"Empty Vec3D is not initialized \"\n               \"correctly.\")\n    def test_float_initialization(self):\n        v = Vec3D(1.0, 2.0, 3.0)\n        assert isinstance(v, Vec3D), \"Can not create Vec3D instance.\"\n        assert v.r == [1.0, 2.0, 3.0], \"Vec3D is not initialized correctly.\"\n        with pytest.raises(ValueError):\n            Vec3D(1.0)\n        with pytest.raises(ValueError):\n            Vec3D(1.0, 2.0)\n        with pytest.raises(TypeError):\n            Vec3D(\"a\", \"b\", \"c\")\n    def test_Vec3D_initialization(self):\n        v = Vec3D(1.0, 2.0, 3.0)\n        w = Vec3D(v)\n        assert isinstance(w, Vec3D), \"Can not create Vec3D instance.\"\n        assert w.r == [1.0, 2.0, 3.0], \"Vec3D is not initialized correctly.\"\n        assert id(v) != id(w), \"Copy constructor did not return new object.\"\n\nclass Test___getitem__():\n    def test_no_integer_index(self, v1):\n        with pytest.raises(TypeError):\n            v1[\"a\"]\n    def test_negative_index(self, v1):\n        with pytest.raises(IndexError):\n            v1[-10]\n    def test_large_index(self, v1):\n        with pytest.raises(IndexError):\n            v1[3]\n    def test_components(self, v1):\n        assert v1[0] == v1x, \"Wrong x component.\"\n        assert v1[1] == v1y, \"Wrong y component.\"\n        assert v1[2] == v1z, \"Wrong z component.\"\n\nclass Test___setitem__():\n    def test_no_integer_index(self, v1):\n        with pytest.raises(TypeError):\n            v1[\"a\"] = 1.0\n    def test_negative_index(self, v1):\n        with pytest.raises(IndexError):\n            v1[-10] = 1.0\n    def test_large_index(self, v1):\n        with pytest.raises(IndexError):\n            v1[3] = 1.0\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1[0] = \"a\"\n    def test_components(self, v1):\n        v1[0] = -v1x\n        assert v1[0] == -v1x, \"Wrong x component.\"\n        v1[1] = -v1y\n        assert v1[1] == -v1y, \"Wrong x component.\"\n        v1[2] = -v1z\n        assert v1[2] == -v1z, \"Wrong x component.\"\n\nclass Test___str__():\n    def test_return_string(self, v1):\n        assert isinstance(v1.__str__(), str), \"No string returned.\"\n    def test_string_content(self, v1):\n        assert v1.__str__() == \"x: {0:f} y: {1:f} z: {2:f}\".format(v1x,\n                                                                   v1y,\n                                                                   v1z), (\n               \"Wrong string format.\")\n\nclass Test___iadd__():\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1 += \"a\"\n    def test_correct_addition(self, v1, v2):\n        v1 += v2\n        assert v1[0] == pytest.approx(v1x + v2x), \"Wrong x component.\"\n        assert v1[1] == pytest.approx(v1y + v2y), \"Wrong y component.\"\n        assert v1[2] == pytest.approx(v1z + v2z), \"Wrong z component.\"\n    def test_added_Vec3D_unchanged(self, v1, v2):\n        v1 += v2\n        assert v2[0] == v2x, \"Wrong x component.\"\n        assert v2[1] == v2y, \"Wrong y component.\"\n        assert v2[2] == v2z, \"Wrong z component.\"\n\nclass Test___isub__():\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1 -= \"a\"\n    def test_correct_subtraction(self, v1, v2):\n        v1 -= v2\n        assert v1[0] == pytest.approx(v1x - v2x), \"Wrong x component.\"\n        assert v1[1] == pytest.approx(v1y - v2y), \"Wrong y component.\"\n        assert v1[2] == pytest.approx(v1z - v2z), \"Wrong z component.\"\n    def test_subtracted_Vec3D_unchanged(self, v1, v2):\n        v1 -= v2\n        assert v2[0] == v2x, \"Wrong x component.\"\n        assert v2[1] == v2y, \"Wrong y component.\"\n        assert v2[2] == v2z, \"Wrong z component.\"\n\nclass Test___imul__():\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1 *= \"a\"\n    def test_correct_float_multiplication(self, v1):\n        v1 *= a\n        assert v1[0] == pytest.approx(a * v1x), \"Wrong x component.\"\n        assert v1[1] == pytest.approx(a * v1y), \"Wrong y component.\"\n        assert v1[2] == pytest.approx(a * v1z), \"Wrong z component.\"\n\nclass Test___itruediv__():\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1 /= \"a\"\n    def test_correct_float_division(self, v1):\n        v1 /= a\n        assert v1[0] == pytest.approx(v1x / a), \"Wrong x component.\"\n        assert v1[1] == pytest.approx(v1y / a), \"Wrong y component.\"\n        assert v1[2] == pytest.approx(v1z / a), \"Wrong z component.\"\n\nclass Test___mul__():\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            res = v1 * \"a\"\n        with pytest.raises(TypeError):\n            res = \"a\" * v1\n    def test_scalar_product(self, v1, v2):\n        sp = v1 * v2\n        assert isinstance(sp, float), \"Wrong type returned.\"\n        assert sp == pytest.approx(v1x * v2x + v1y * v2y + v1z * v2z), (\n               \"Wrong scalar product.\")\n    def test_right_float_multiplication(self, v1):\n        res = v1 * a\n        assert isinstance(res, Vec3D), \"Wrong type returned.\"\n        assert res[0] == pytest.approx(v1x * a), \"Wrong x component.\"\n        assert res[1] == pytest.approx(v1y * a), \"Wrong y component.\"\n        assert res[2] == pytest.approx(v1z * a), \"Wrong z component.\"\n    def test_left_float_multiplication(self, v1):\n        res = a * v1\n        assert isinstance(res, Vec3D), \"Wrong type returned.\"\n        assert res[0] == pytest.approx(v1x * a), \"Wrong x component.\"\n        assert res[1] == pytest.approx(v1y * a), \"Wrong y component.\"\n        assert res[2] == pytest.approx(v1z * a), \"Wrong z component.\"\n\nclass Test___eq__():\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1 == \"a\"\n    def test_equal_components(self, v1):\n        ve = Vec3D(v1x, v1y, v1z)\n        assert id(v1) != id(ve), \"Test Vec3Ds are identical.\"\n        assert (v1 == ve) == (\n               v1[0] == ve[0] and v1[1] == ve[1] and v1[2] == ve[2]), (\n               \"Wrong comparison.\")\n\nclass Test___ne__():\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1 != \"a\"\n    def test_one_different_component(self, v1):\n        ve = Vec3D(v1x + 1.0, v1y, v1z)\n        assert (v1 != ve) == (\n               v1[0] != ve[0] or v1[1] != ve[1] or v1[2] != ve[2]), (\n               \"Wrong comparison (x).\")\n        ve = Vec3D(v1x, v1y + 1.0, v1z)\n        assert (v1 != ve) == (\n               v1[0] != ve[0] or v1[1] != ve[1] or v1[2] != ve[2]), (\n               \"Wrong comparison (y).\")\n        ve = Vec3D(v1x, v1y, v1z + 1.0)\n        assert (v1 != ve) == (\n               v1[0] != ve[0] or v1[1] != ve[1] or v1[2] != ve[2]), (\n               \"Wrong comparison (z).\")\n\nclass Test_norm():\n    def test_correct_result(self, v1):\n        from math import sqrt\n        assert v1.norm() == pytest.approx(sqrt(v1x * v1x +\n                                               v1y * v1y +\n                                               v1z * v1z)), \"Norm incorrect.\"\n\nclass Test_norm2():\n    def test_correct_result(self, v1):\n        assert v1.norm2() == pytest.approx(v1x * v1x +\n                                           v1y * v1y +\n                                           v1z * v1z), \"Norm incorrect.\"\n\nclass Test_normalize():\n    def test_correct_result(self, v1):\n        v1.normalize()\n        assert v1.norm() == pytest.approx(1.0), \"Norm not equal to 1.0.\"\n\nclass Test_cross():\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1.cross(\"a\")\n    def test_correct_return_type(self, v1, v2):\n        v3 = v1.cross(v2)\n        assert isinstance(v3, Vec3D), \"Wrong type returned.\"\n    def test_correct_result(self, v1, v2):\n        v3 = v1.cross(v2)\n        assert v3[0] == pytest.approx(v1y * v2z - v2y * v1z), \"Wrong x result.\"\n        assert v3[1] == pytest.approx(v1z * v2x - v2z * v1x), \"Wrong y result.\"\n        assert v3[2] == pytest.approx(v1x * v2y - v2x * v1y), \"Wrong z result.\"\n\nclass Test___add__():\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1 + \"a\"\n        with pytest.raises(TypeError):\n            \"a\" + v1\n    def test_correct_return_type(self, v1, v2):\n        v3 = v1 + v2\n        assert isinstance(v3, Vec3D), \"Wrong type returned.\"\n    def test_new_object_returned(self, v1, v2):\n        v3 = v1 + v2\n        assert id(v1) != id(v3), \"No new Vec3D generated.\"\n        assert id(v2) != id(v3), \"No new Vec3D generated.\"\n    def test_correct_result(self, v1, v2):\n        v3 = v1 + v2\n        assert v3[0] == pytest.approx(v1x + v2x), \"Wrong x result.\"\n        assert v3[1] == pytest.approx(v1y + v2y), \"Wrong y result.\"\n        assert v3[2] == pytest.approx(v1z + v2z), \"Wrong z result.\"\n\nclass Test___sub__():\n    def test_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1 - \"a\"\n        with pytest.raises(TypeError):\n            \"a\" - v1\n    def test_correct_return_type(self, v1, v2):\n        v3 = v1 - v2\n        assert isinstance(v3, Vec3D), \"Wrong type returned.\"\n    def test_new_object_returned(self, v1, v2):\n        v3 = v1 - v2\n        assert id(v1) != id(v3), \"No new Vec3D generated.\"\n        assert id(v2) != id(v3), \"No new Vec3D generated.\"\n    def test_correct_result(self, v1, v2):\n        v3 = v1 - v2\n        assert v3[0] == pytest.approx(v1x - v2x), \"Wrong x result.\"\n        assert v3[1] == pytest.approx(v1y - v2y), \"Wrong y result.\"\n        assert v3[2] == pytest.approx(v1z - v2z), \"Wrong z result.\"\n\nclass Test___neg__():\n    def test_correct_return_type(self, v1):\n        assert isinstance(-v1, Vec3D), \"Wrong type returned.\"\n    def test_new_object_returned(self, v1):\n        assert id(v1) != id(-v1), \"No new Vec3D generated.\"\n    def test_correct_result(self, v1):\n        v2 = -v1\n        assert v2[0] == pytest.approx(-v1x), \"Wrong x result.\"\n        assert v2[1] == pytest.approx(-v1y), \"Wrong y result.\"\n        assert v2[2] == pytest.approx(-v1z), \"Wrong z result.\"\n\nclass Test___truediv__():\n    def test_wrong_type(self, v1, v2):\n        with pytest.raises(TypeError):\n            v1 / \"a\"\n        with pytest.raises(TypeError):\n            \"a\" / v1\n        with pytest.raises(TypeError):\n            v1 / v2\n    def test_correct_return_type(self, v1):\n        v2 = v1 / a\n        assert isinstance(v2, Vec3D), \"Wrong type returned.\"\n    def test_new_object_returned(self, v1):\n        v2 = v1 / a\n        assert id(v1) != id(v2), \"No new Vec3D generated.\"\n    def test_correct_result(self, v1):\n        v2 = v1 / a\n        assert v2[0] == pytest.approx(v1x / a), \"Wrong x result.\"\n        assert v2[1] == pytest.approx(v1y / a), \"Wrong y result.\"\n        assert v2[2] == pytest.approx(v1z / a), \"Wrong z result.\"\n\nclass Test_r():\n    def test_getter_correct_type(self, v1):\n        assert isinstance(v1.r, list), \"r is not a list.\"\n    def test_getter_correct_size(self, v1):\n        assert len(v1.r) == 3, \"Wrong size of r.\"\n    def test_getter_correct_content(self, v1):\n        assert v1.r == [v1x, v1y, v1z], \"Wrong content of r.\"\n    def test_setter_wrong_size(self, v1):\n        with pytest.raises(IndexError):\n            v1.r = \"a\"\n    def test_setter_wrong_type(self, v1):\n        with pytest.raises(TypeError):\n            v1.r = [\"a\", \"b\", \"c\"]\n    def test_setter_wrong_list_size(self, v1):\n        with pytest.raises(IndexError):\n            v1.r = [1.0, 2.0]\n    def test_setter_correct_assignment(self, v1, v2):\n        v1.r = [v2x, v2y, v2z]\n        assert v1.r == v2.r, \"Content not correctly assigned.\"\n    def test_setter_correct_assignment_to_Vec3D(self, v1, v2):\n        v1.r = [v2x, v2y, v2z]\n        assert v1 == v2, \"Content not correctly assigned.\"\n    # Assignment of individual components does NOT work!\n    def test_setter_index_assignment_not_possible(self, v1, v2):\n        v1.r[0] = v2x\n        v1.r[1] = v2y\n        v1.r[2] = v2z\n        assert v1.r[0] == v1x, \"Assignment did something unexpected.\"\n        assert v1.r[1] == v1y, \"Assignment did something unexpected.\"\n        assert v1.r[2] == v1z, \"Assignment did something unexpected.\"\n"
  },
  {
    "path": "tools/converter/convert-VASP_OUTCAR.py",
    "content": "#!/usr/bin/env python\n\n# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n###############################################################################\n# File converter from VASP OUTCAR to input.data format.\n# Works also if OUTCAR contains trajectories.\n# Tested with VASP 5.2.12\n###############################################################################\n\nimport numpy as np\nimport sys\n\ndef print_usage():\n    sys.stderr.write(\"USAGE: {0:s} <in_file> <<out_file>>\\n\".format(sys.argv[0]))\n    sys.stderr.write(\"       <in_file> .... OUTCAR file name.\\n\")\n    sys.stderr.write(\"       <out_file> ... Output file name (optional).\\n\")\n    return\n\nif len(sys.argv) < 2 or sys.argv[1] in [\"-?\", \"-h\", \"--help\"]:\n    print_usage()\n    sys.exit(1)\n\nfile_name = sys.argv[1]\nif len(sys.argv) > 2:\n    outfile_name = sys.argv[2]\nelse:\n    outfile_name = None\n\n# Read in the whole file first.\nf = open(file_name, \"r\")\nlines = [line for line in f]\nf.close()\n\n# If OUTCAR contains ionic movement run (e.g. from an MD simulation) multiple\n# configurations may be present. Thus, need to prepare empty lists.\nlattices   = []\nenergies   = []\natom_lists = []\n\n# Loop over all lines.\nelements = []\nfor i in range(len(lines)):\n    line = lines[i]\n    # Collect element type information, expecting VRHFIN lines like this:\n    #\n    # VRHFIN =Cu: d10 p1\n    #\n    if \"VRHFIN\" in line:\n        elements.append(line.split()[1].replace(\"=\", \"\").replace(\":\", \"\"))\n    # VASP specifies how many atoms of each element are present, e.g.\n    #\n    # ions per type =              48  96\n    #\n    if \"ions per type\" in line:\n        atoms_per_element = [int(it) for it in line.split()[4:]]\n    # Simulation box may be specified multiple times, I guess this line\n    # introduces the final lattice vectors.\n    if \"VOLUME and BASIS-vectors are now\" in line:\n        lattices.append([lines[i+j].split()[0:3] for j in range(5, 8)])\n    # Total energy is found in the line with \"energy  without\" (2 spaces) in\n    # the column with sigma->0:\n    #\n    # energy  without entropy=     -526.738461  energy(sigma->0) =     -526.738365\n    #\n    if \"energy  without entropy\" in line:\n        energies.append(line.split()[6])\n    # Atomic coordinates and forces are found in the lines following\n    # \"POSITION\" and \"TOTAL-FORCE\".\n    if \"POSITION\" in line and \"TOTAL-FORCE\" in line:\n        atom_lists.append([])\n        count = 0\n        for ei in range(len(atoms_per_element)):\n            for j in range(atoms_per_element[ei]):\n                atom_line = lines[i+2+count]\n                atom_lists[-1].append(atom_line.split()[0:6])\n                atom_lists[-1][-1].extend([elements[ei]])\n                count += 1\n\n# Sanity check: do all lists have the same length. \nif not (len(lattices) == len(energies) and len(energies) == len(atom_lists)):\n    raise RuntimeError(\"ERROR: Inconsistent OUTCAR file.\")\n\n# Open output file or write to stdout.\nif outfile_name is not None:\n    f = open(outfile_name, \"w\")\nelse:\n    f = sys.stdout\n\n# Write configurations in \"input.data\" format.\nfor i, (lattice, energy, atoms) in enumerate(zip(lattices, energies, atom_lists)):\n    f.write(\"begin\\n\")\n    f.write(\"comment source_file_name={0:s} structure_number={1:d}\\n\".format(file_name, i + 1))\n    f.write(\"lattice {0:s} {1:s} {2:s}\\n\".format(lattice[0][0], lattice[0][1], lattice[0][2]))\n    f.write(\"lattice {0:s} {1:s} {2:s}\\n\".format(lattice[1][0], lattice[1][1], lattice[1][2]))\n    f.write(\"lattice {0:s} {1:s} {2:s}\\n\".format(lattice[2][0], lattice[2][1], lattice[2][2]))\n    for a in atoms:\n        f.write(\"atom {0:s} {1:s} {2:s} {3:s} {4:s} {5:s} {6:s} {7:s} {8:s}\\n\".format(a[0], a[1], a[2], a[6], \"0.0\", \"0.0\", a[3], a[4], a[5]))\n    f.write(\"energy {0:s}\\n\".format(energy))\n    f.write(\"charge {0:s}\\n\".format(\"0.0\"))\n    f.write(\"end\\n\")\n"
  },
  {
    "path": "tools/misc/convert_nnp.py",
    "content": "#!/usr/bin/env python3\n\n# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n###############################################################################\n#\n# NNP converter between n2p2 versions.\n# \n# This converter is helpful when symmetry function ordering and definition\n# strings (keyword symfunction_short in input.nn) change between versions (e.g.\n# during development). It requires the \"old\" NNP (input.nn, scaling.data,\n# weights.???.data) and a small, representative data set (input.data).\n# Furthermore, it requires the binary nnp-scaling for each n2p2 version. It\n# will first apply changes to the input.nn file (adapt convert_input_nn). Then\n# it computes the scaling data for both versions and tries to find matches (see\n# ScalingData.__eq__ for a matching criterion). Finally, the script will output\n# converted versions of scaling.data and weights.???.data.\n# \n###############################################################################\n\nimport sys\nimport os\nimport glob\nimport shutil\nimport numpy as np\nimport re\nfrom typing import List, Dict\nfrom collections import OrderedDict\n\n# Settings: edit path to data and two different n2p2 bin directories here:\ndirs = [\"PSF_for_DMABN\", \"PSF_for_ethyl_benzene\", \"PSF_for_anisole\",\n        \"PAS_for_DMABN\", \"PAS_for_ethyl_benzene\", \"PAS_for_anisole\"]\nold_bin = \"~/local/src/n2p2-singraber_oldpsf/bin/\"      # branch: polynomial_symmetry_functions commit: 0b17662fdd9870818ac8060f3342991daa36b7ca\nnew_bin = \"~/local/src/n2p2-singraber_alternative/bin/\" # branch: polynomial_symmetry_functions commit: b514172eb4816e8791b5a488e671de7a3e1ba292\n\n# Store one scaling data line, allow comparison via equal operator.\nclass ScalingData:\n    def __init__(self, line):\n        self.line = line\n        split = line.split()\n        self.element = int(split[0])\n        self.index = int(split[1])\n        self.minimum = float(split[2])\n        self.maximum = float(split[3])\n        self.mean = float(split[4])\n        self.sigma = float(split[5])\n    # Define here how to find \"equal\" scaling data.\n    def __eq__(self, other):\n        if isinstance(other, self.__class__):\n            if self.element != other.element: return False\n            if np.abs(self.mean - other.mean) > 1.0E-10: return False\n            if np.abs(self.sigma - other.sigma) > 1.0E-10: return False\n            if np.abs(self.minimum - other.minimum) > 1.0E-10: return False\n            if np.abs(self.maximum - other.maximum) > 1.0E-10: return False\n            return True\n        else:\n            return False\n\n# Split string into columns but keep (multiple) separators in.\ndef split_columns(line, delimiter=' '):\n    r = [\"\"]\n    content = False\n    for c in line:\n        if c != delimiter:\n            content = True\n        elif c == delimiter and content:\n            r.append(\"\")\n            content = False\n        r[-1] += c\n    return r\n\n# Read in one scaling data file and return dictionary with scaling data for each element.\ndef read_scaling_data(file_name):\n    data = {}\n    f = open(file_name, \"r\")\n    for line in f:\n        ls = line.split()\n        if len(ls) > 0 and ls[0][0] != \"#\":\n            sd = ScalingData(line)\n            if sd.element not in data:\n                data[sd.element] = []\n            data[sd.element].append(sd)\n    return data\n\ndef convert_scaling_data(old_file, new_file, data: Dict[int, List[ScalingData]]):\n    fi = open(old_file, \"r\")\n    fo = open(new_file, \"w\")\n    for line in fi:\n        ls = line.split()\n        if len(ls) > 0 and ls[0][0] == \"#\":\n            fo.write(line)\n    fi.close()\n    for e, element_data in data.items():\n        count = 1\n        for d in element_data:\n            ls = split_columns(d.line)\n            ls[1] = \"{0:{1}d}\".format(count, len(ls[1]))\n            fo.write(\"\".join(ls))\n            count += 1\n    fo.close()\n\ndef convert_input_nn(old_file, new_file):\n    fi = open(old_file, \"r\")\n    fo = open(new_file, \"w\")\n    for line in fi:\n        ls = line.split()\n        if len(ls) > 0 and ls[0] == \"symfunction_short\":\n            sftype = int(ls[2])\n            if sftype > 100:\n                subtype = \"p2a\"\n            else:\n                subtype = \"p2\"\n            if sftype in [28, 280]:\n                ls[2] = \"20\"\n                ls.append(subtype)\n            if sftype in [89, 890]:\n                ls[2] = \"22\"\n                rc = ls[-1]\n                ls[-1] = ls[-2]\n                ls[-2] = ls[-3]\n                ls[-3] = rc\n                ls.append(subtype)\n            if sftype in [99, 990]:\n                ls[2] = \"21\"\n                rc = ls[-1]\n                ls[-1] = ls[-2]\n                ls[-2] = ls[-3]\n                ls[-3] = rc\n                ls.append(subtype)\n            line = \" \".join(ls) + \"\\n\"\n        fo.write(line)\n    fi.close()\n    fo.close()\n\ndef convert_weights_file(old_file, new_file, order):\n    fi = open(old_file, \"r\")\n    fo = open(new_file, \"w\")\n    for line in iter(fi.readline, ''): # Need this construction because of tell()\n        ls = line.split()\n        if len(ls) > 0 and ls[0][0] == \"#\":\n            fo.write(line)\n            pos = fi.tell()\n        else:\n            break # Break out of loop if header is copied.\n    # Continue reading old file to check how many neurons are in second layer.\n    fi.seek(pos)\n    neurons = 0\n    for line in iter(fi.readline, ''):\n        ls = line.split()\n        if int(ls[4]) > 1:\n            break\n        neurons += 1\n    fi.seek(pos)\n    # Now store first-to-second layer weights to rearrange afterwards.\n    weights = {i : [] for i in range(len(order))}\n    for line in iter(fi.readline, ''):\n        ls = line.split()\n        # Stop when biases are reached.\n        if ls[1] == \"b\":\n            break\n        input_neuron = int(ls[4]) - 1\n        weights[input_neuron].append(line)\n        pos = fi.tell()\n    # Print first-to-second layer weights in new order.\n    countw = 0\n    countn = 0\n    for i in order:\n        for line in weights[i]:\n            if countw % neurons == 0:\n                countn += 1\n            countw += 1\n            ls = split_columns(line)\n            ls[2] = \"{0:{1}d}\".format(countw, len(ls[2]))\n            ls[4] = \"{0:{1}d}\".format(countn, len(ls[4]))\n            fo.write(\"\".join(ls))\n    # Copy rest of weights file.\n    fi.seek(pos)\n    for line in iter(fi.readline, ''):\n        fo.write(line)\n\n    fi.close()\n    fo.close()\n\n\ndef main():\n    # Do not create data again if requested.\n    create_data = True\n    if len(sys.argv) > 1 and sys.argv[1] == \"-o\":\n        create_data = False\n\n    for d in dirs:\n        print(\"Processing dir: \" + d)\n\n        # Create temporary working dir for old version.\n        old_dir = \"old_\" + d\n        if create_data:\n            if os.path.exists(old_dir):\n                shutil.rmtree(old_dir)\n            shutil.copytree(d, old_dir)\n        os.chdir(old_dir)\n        # Check for weight files and create element -> weight file dictionary.\n        weight_files = sorted(glob.glob(\"weights.*.data\"))\n        weight_dict = {}\n        for i, wf in enumerate(weight_files):\n            weight_dict[i + 1] = wf\n            print(\"Found element \" + str(i + 1) + \": \" + wf)\n        # Get scaling of old symmetry functions.\n        if create_data: os.system(old_bin + \"nnp-scaling 100 > /dev/null && rm sf.* function.data\")\n        scaling_old = read_scaling_data(\"scaling.data\")\n        os.chdir(\"..\")\n\n        # Create working dir for new version.\n        new_dir = \"new_\" + d\n        if create_data:\n            if os.path.exists(new_dir):\n                shutil.rmtree(new_dir)\n            os.mkdir(new_dir)\n            shutil.copy2(old_dir + \"/input.data\", new_dir)\n            shutil.copy2(old_dir + \"/input.nn\", new_dir + \"/input.nn.old\")\n        os.chdir(new_dir)\n        # Convert symmetry function lines in input.nn.\n        convert_input_nn(\"input.nn.old\", \"input.nn\")\n        # Get scaling of new symmetry functions.\n        if create_data: os.system(new_bin + \"nnp-scaling 100 > /dev/null && rm sf.* function.data\")\n        scaling_new = read_scaling_data(\"scaling.data\")\n        os.chdir(\"..\")\n\n        # Now process the scaling data to find matches.\n        if len(scaling_old) != len(scaling_new):\n            raise RuntimeError(\"Different number of elements in symmetry function scaling data.\")\n        elements = sorted(scaling_new.keys())\n        index_in_new = {}\n        index_in_old = {}\n        for e in elements:\n            if len(scaling_old[e]) != len(scaling_new[e]):\n                raise RuntimeError(\"Different number of symmetry functions in scaling data.\")\n            nsf = len(scaling_new[e])\n            print(\"Searching matches for \" + str(nsf) + \" symmetry functions of element \" + str(e) + \"...\", end=\"\")\n            index_in_new[e] = [None] * nsf # Index of old SF in scaling_new.\n            index_in_old[e] = [None] * nsf # Index of new SF in scaling_old.\n            for ind_n, n in enumerate(scaling_new[e]):\n                for ind_o, o in enumerate(scaling_old[e]):\n                    if n == o:\n                        index_in_new[e][ind_o] = ind_n\n                        index_in_old[e][ind_n] = ind_o\n                        break\n            for o, n in enumerate(index_in_new[e]):\n                if n is None:\n                    raise RuntimeError(\"No match found for index in old settings: \" + str(o) + \"\\nLine: \" + scaling_old[o].line)\n            print(\"completed!\")\n\n        # Create dir for final converted version.\n        conv_dir = \"converted_\" + d\n        print(\"Writing converted NNP in \" + conv_dir + \".\")\n        if os.path.exists(conv_dir):\n            shutil.rmtree(conv_dir)\n        os.mkdir(conv_dir)\n        shutil.copy2(old_dir + \"/input.data\", conv_dir)\n        shutil.copy2(new_dir + \"/input.nn\", conv_dir + \"/input.nn\")\n        # Read original scaling data (not scaling_old which is only for a subset).\n        scaling_orig = read_scaling_data(d + \"/scaling.data\")\n        # Reorder scaling data according to new SF list.\n        scaling_conv = {}\n        for e in elements:\n            scaling_conv[e] = [scaling_orig[e][i] for i in index_in_old[e]]\n        os.chdir(conv_dir)\n        convert_scaling_data(\"../\" + d + \"/scaling.data\", \"scaling.data\", scaling_conv)\n        for e, wf in weight_dict.items():\n            shutil.copy2(\"../\" + d + \"/\" + wf, wf + \".old\")\n            convert_weights_file(wf + \".old\", wf, index_in_old[e])\n            os.remove(wf + \".old\")\n        os.system(new_bin + \"nnp-dataset 0 > /dev/null\")\n        os.chdir(\"..\")\n\n        print(\"-------------------------------------------------------------------------------\")\n\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "tools/misc/generate-acsf-angular_narrow.py",
    "content": "#!/usr/bin/env python\n\nimport numpy as np\nimport sys\n\n# Settings\nelements = [\"S\", \"Cu\"]\nmode     = \"center\"\nr_0      = 1.5\nr_c      = 6.0\nr_N      = r_c - 0.5\nN        = 3\nzetas    = [1.0, 6.0]\n\ngrid = np.linspace(r_0, r_N, N)\ndr = (r_N - r_0) / (N - 1)\n\nsys.stdout.write(\"# Generating narrow angular symmetry function set:\\n\")\nsys.stdout.write(\"# mode  = {0:9s}\\n\".format(mode))\nsys.stdout.write(\"# r_0   = {0:9.3E}\\n\".format(r_0))\nsys.stdout.write(\"# r_c   = {0:9.3E}\\n\".format(r_c))\nsys.stdout.write(\"# r_N   = {0:9.3E}\\n\".format(r_N))\nsys.stdout.write(\"# N     = {0:9d}\\n\".format(N))\nsys.stdout.write(\"# grid  = \" + \" \".join(str(r) for r in grid) + \"\\n\")\nsys.stdout.write(\"# zetas = \" + \" \".join(str(z) for z in zetas) + \"\\n\")\n\nif mode == \"center\":\n    eta_grid = 1.0 / (2.0 * grid**2)\n    rs_grid = [0.0] * N\nelif mode == \"shift\":\n    eta_grid = [1.0 / (2.0 * dr * dr)] * N\n    rs_grid = grid\n\nfor e in elements:\n    sys.stdout.write(\"# Narrow angular symmetry functions for element {0:2s}\\n\".format(e))\n    for e1 in elements:\n        elements_reduced = elements[elements.index(e1):]\n        for e2 in elements_reduced:\n            for (eta, rs) in zip(eta_grid, rs_grid):\n                for zeta in zetas:\n                    for lambd in [-1.0, 1.0]:\n                        sys.stdout.write(\"symfunction_short {0:2s} 3 {1:2s} {2:2s} {3:9.3E} {4:2.0f} {5:9.3E} {6:9.3E} {7:9.3E}\\n\".format(e, e1, e2, eta, lambd, zeta, r_c, rs))\n            sys.stdout.write(\"\\n\")\n"
  },
  {
    "path": "tools/misc/generate-acsf-angular_wide.py",
    "content": "#!/usr/bin/env python\n\nimport numpy as np\nimport sys\n\n# Settings\nelements = [\"S\", \"Cu\"]\nmode     = \"center\"\nr_0      = 1.5\nr_c      = 6.0\nr_N      = r_c - 0.5\nN        = 3\nzetas    = [1.0, 6.0]\n\ngrid = np.linspace(r_0, r_N, N)\ndr = (r_N - r_0) / (N - 1)\n\nsys.stdout.write(\"# Generating wide angular symmetry function set:\\n\")\nsys.stdout.write(\"# mode  = {0:9s}\\n\".format(mode))\nsys.stdout.write(\"# r_0   = {0:9.3E}\\n\".format(r_0))\nsys.stdout.write(\"# r_c   = {0:9.3E}\\n\".format(r_c))\nsys.stdout.write(\"# r_N   = {0:9.3E}\\n\".format(r_N))\nsys.stdout.write(\"# N     = {0:9d}\\n\".format(N))\nsys.stdout.write(\"# grid  = \" + \" \".join(str(r) for r in grid) + \"\\n\")\nsys.stdout.write(\"# zetas = \" + \" \".join(str(z) for z in zetas) + \"\\n\")\n\nif mode == \"center\":\n    eta_grid = 1.0 / (2.0 * grid**2)\n    rs_grid = [0.0] * N\nelif mode == \"shift\":\n    eta_grid = [1.0 / (2.0 * dr * dr)] * N\n    rs_grid = grid\n\nfor e in elements:\n    sys.stdout.write(\"# Wide angular symmetry functions for element {0:2s}\\n\".format(e))\n    for e1 in elements:\n        elements_reduced = elements[elements.index(e1):]\n        for e2 in elements_reduced:\n            for (eta, rs) in zip(eta_grid, rs_grid):\n                for zeta in zetas:\n                    for lambd in [-1.0, 1.0]:\n                        sys.stdout.write(\"symfunction_short {0:2s} 9 {1:2s} {2:2s} {3:9.3E} {4:2.0f} {5:9.3E} {6:9.3E} {7:9.3E}\\n\".format(e, e1, e2, eta, lambd, zeta, r_c, rs))\n            sys.stdout.write(\"\\n\")\n"
  },
  {
    "path": "tools/misc/generate-acsf-radial.py",
    "content": "#!/usr/bin/env python\n\nimport numpy as np\nimport sys\n\n# Settings\nelements = [\"S\", \"Cu\"]\nmode     = \"shift\"\nr_0      = 1.5\nr_c      = 6.0\nr_N      = r_c - 0.5\nN        = 9\n\ngrid = np.linspace(r_0, r_N, N)\ndr = (r_N - r_0) / (N - 1)\n\nsys.stdout.write(\"# Generating radial symmetry function set:\\n\")\nsys.stdout.write(\"# mode  = {0:9s}\\n\".format(mode))\nsys.stdout.write(\"# r_0   = {0:9.3E}\\n\".format(r_0))\nsys.stdout.write(\"# r_c   = {0:9.3E}\\n\".format(r_c))\nsys.stdout.write(\"# r_N   = {0:9.3E}\\n\".format(r_N))\nsys.stdout.write(\"# N     = {0:9d}\\n\".format(N))\nsys.stdout.write(\"# grid  = \" + \" \".join(str(r) for r in grid) + \"\\n\")\n\nif mode == \"center\":\n    eta_grid = 1.0 / (2.0 * grid**2)\n    rs_grid = [0.0] * N\nelif mode == \"shift\":\n    eta_grid = [1.0 / (2.0 * dr * dr)] * N\n    rs_grid = grid\n\nfor e in elements:\n    sys.stdout.write(\"# Radial symmetry functions for element {0:2s}\\n\".format(e))\n    for e1 in elements:\n        for (eta, rs) in zip(eta_grid, rs_grid):\n            sys.stdout.write(\"symfunction_short {0:2s} 2 {1:2s} {2:9.3E} {3:9.3E} {4:9.3E}\\n\".format(e, e1, eta, rs, r_c))\n        sys.stdout.write(\"\\n\")\n"
  },
  {
    "path": "tools/misc/nnp-archive.sh",
    "content": "#!/bin/bash\n\n# n2p2 - A neural network potential package\n# Copyright (C) 2018 Andreas Singraber (University of Vienna)\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at your option) any later version.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\n###############################################################################\n# nnp-archive.sh - Archiving of training directories\n#\n# Cleans up a training directory,\n# removes:\n#   - train-/testpoints.???.out for all but the first and last epoch.\n#   - train-/testforces.???.out for all but the first and last epoch.\n#   - function.data\n# compresses to nnp-archive.tar.gz:\n#   - weights.???.out\n#   - neuron-stats.???.out\n#   - train-log.out\n#   - train/test.data\n#   - nnp-train.log.N (where N > 0)\n# \n###############################################################################\n\nlast_epoch=$(grep -E \"TIMING +[0-9]{1,}\" nnp-train.log.0000 | tail -n 1 | awk '{print $2}')\n\nkeep_dir=\"nnp-archive_TMP\"\nzip_dir=\"nnp-archive\"\n\necho \"Keeping output from epoch 0 and ${last_epoch}...\"\n\nif [ -e $keep_dir ]\nthen\n    rm -r $keep_dir\nfi\nmkdir $keep_dir\n\nif [ -e $zip_dir ]\nthen\n    rm -r $zip_dir\nfi\nmkdir $zip_dir\n\nepoch_string=$(printf \"%06d\" 0)\n\nmv trainpoints.${epoch_string}.out $keep_dir\nmv testpoints.${epoch_string}.out $keep_dir\nmv trainforces.${epoch_string}.out $keep_dir\nmv testforces.${epoch_string}.out $keep_dir\nmv weights*.${epoch_string}.out $keep_dir\nmv neuron-stats.${epoch_string}.out $keep_dir\nmv nnp-train.log.0000 $keep_dir\n\nepoch_string=$(printf \"%06d\" $last_epoch)\n\nmv trainpoints.${epoch_string}.out $keep_dir\nmv testpoints.${epoch_string}.out $keep_dir\nmv trainforces.${epoch_string}.out $keep_dir\nmv testforces.${epoch_string}.out $keep_dir\nmv weights*.${epoch_string}.out $keep_dir\nmv neuron-stats.${epoch_string}.out $keep_dir\n\nmv weights*.out $zip_dir\nmv neuron-stats*.out $zip_dir\nmv train-log.out $zip_dir\nmv train.data $zip_dir\nmv test.data $zip_dir\nmv nnp-train.log.* $zip_dir\n\nif [ -e ${zip_dir}.tar.gz ]\nthen\n    echo \"ERROR: Archive directory already exists, aborting.\"\n    exit 1\nfi\ntar -czvf ${zip_dir}.tar.gz ${zip_dir}/*\nrm -r ${zip_dir}\n\nrm trainforces.*\nrm testforces.*\nrm trainpoints.*\nrm testpoints.*\nrm function.data\n\nmv ${keep_dir}/* .\n\nrm -r ${keep_dir}\n"
  },
  {
    "path": "tools/plot/plot-symfunc-histograms.ipynb",
    "content": "{\n \"cells\": [\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": null,\n   \"metadata\": {\n    \"collapsed\": true\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"%matplotlib nbagg\\n\",\n    \"import numpy as np\\n\",\n    \"import matplotlib\\n\",\n    \"import matplotlib.pyplot as plt\\n\",\n    \"import glob\\n\",\n    \"import math\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": null,\n   \"metadata\": {\n    \"collapsed\": true\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"class SymmetryFunctionData:\\n\",\n    \"    def __init__(self):\\n\",\n    \"        self.parameters = {}\\n\",\n    \"        self.histogram = []\\n\",\n    \"\\n\",\n    \"def readSymmetryFunctionHistogram(file_name):\\n\",\n    \"    sfd = SymmetryFunctionData()\\n\",\n    \"    f = open(file_name, \\\"r\\\")\\n\",\n    \"    for line in f:\\n\",\n    \"        split_line = line.split()\\n\",\n    \"        if split_line[0] == \\\"#SFINFO\\\":\\n\",\n    \"            sfd.parameters[split_line[1]] = split_line[2]\\n\",\n    \"        elif split_line[0][0] == \\\"#\\\":\\n\",\n    \"            continue\\n\",\n    \"        else:\\n\",\n    \"            sfd.histogram.append([float(split_line[0]),\\n\",\n    \"                                  float(split_line[1]),\\n\",\n    \"                                  float(split_line[2])])\\n\",\n    \"    f.close()\\n\",\n    \"    sfd.histogram = np.array(sfd.histogram).T\\n\",\n    \"    return sfd\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": null,\n   \"metadata\": {\n    \"collapsed\": true\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"sf_histograms = []\\n\",\n    \"for file_name in sorted(glob.glob(\\\"sf.*.histo\\\")):\\n\",\n    \"    sf_histograms.append(readSymmetryFunctionHistogram(file_name))\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": null,\n   \"metadata\": {\n    \"collapsed\": true,\n    \"scrolled\": false\n   },\n   \"outputs\": [],\n   \"source\": [\n    \"for sfh in sf_histograms:\\n\",\n    \"    print sfh.parameters[\\\"type\\\"], sfh.parameters[\\\"index\\\"]\\n\",\n    \"    fig = plt.figure()\\n\",\n    \"    ax = fig.add_subplot(111)\\n\",\n    \"    X = (sfh.histogram[0] + sfh.histogram[1]) / 2.\\n\",\n    \"    ax.plot(X, sfh.histogram[2])\\n\",\n    \"    mean = float(sfh.parameters[\\\"mean\\\"])\\n\",\n    \"    sigma = float(sfh.parameters[\\\"sigma\\\"])\\n\",\n    \"    ax.plot([mean - sigma, mean + sigma], [0, 0], \\\"-\\\", lw=3)\\n\",\n    \"    ax.plot(mean, 0, \\\"o\\\")\\n\",\n    \"    ax.plot(float(sfh.parameters[\\\"min\\\"]), 0, \\\"o\\\")\\n\",\n    \"    ax.plot(float(sfh.parameters[\\\"max\\\"]), 0, \\\"o\\\")\"\n   ]\n  }\n ],\n \"metadata\": {\n  \"anaconda-cloud\": {},\n  \"kernelspec\": {\n   \"display_name\": \"Python 2\",\n   \"language\": \"python\",\n   \"name\": \"python2\"\n  },\n  \"language_info\": {\n   \"codemirror_mode\": {\n    \"name\": \"ipython\",\n    \"version\": 2\n   },\n   \"file_extension\": \".py\",\n   \"mimetype\": \"text/x-python\",\n   \"name\": \"python\",\n   \"nbconvert_exporter\": \"python\",\n   \"pygments_lexer\": \"ipython2\",\n   \"version\": \"2.7.14\"\n  }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 2\n}\n"
  },
  {
    "path": "tools/plot/plot-symfunc-shape-rdf.ipynb",
    "content": "{\n \"cells\": [\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 1,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"%matplotlib nbagg\\n\",\n    \"import numpy as np\\n\",\n    \"import matplotlib\\n\",\n    \"import matplotlib.pyplot as plt\\n\",\n    \"import glob\\n\",\n    \"import math\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 2,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"class SymmetryFunctionData:\\n\",\n    \"    def __init__(self):\\n\",\n    \"        self.parameters = {}\\n\",\n    \"        self.radial = []\\n\",\n    \"        self.angular = []\\n\",\n    \"\\n\",\n    \"def readSymmetryFunction(file_name):\\n\",\n    \"    sfd = SymmetryFunctionData()\\n\",\n    \"    f = open(file_name, \\\"r\\\")\\n\",\n    \"    for line in f:\\n\",\n    \"        split_line = line.split()\\n\",\n    \"        if split_line[0] == \\\"#SFINFO\\\":\\n\",\n    \"            sfd.parameters[split_line[1]] = split_line[2]\\n\",\n    \"        elif split_line[0][0] == \\\"#\\\":\\n\",\n    \"            continue\\n\",\n    \"        else:\\n\",\n    \"            sfd.radial.append([float(split_line[0]),\\n\",\n    \"                               float(split_line[1])])\\n\",\n    \"            sfd.angular.append([float(split_line[2]),\\n\",\n    \"                                float(split_line[3])])\\n\",\n    \"    f.close()\\n\",\n    \"    sfd.radial = np.array(sfd.radial).T\\n\",\n    \"    return sfd\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 3,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"symmetry_functions = []\\n\",\n    \"for file_name in sorted(glob.glob(\\\"sf.*.out\\\")):\\n\",\n    \"    symmetry_functions.append(readSymmetryFunction(file_name))\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 4,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"text/plain\": [\n       \"[['H', 'H'], ['H', 'O'], ['O', 'O']]\"\n      ]\n     },\n     \"execution_count\": 4,\n     \"metadata\": {},\n     \"output_type\": \"execute_result\"\n    }\n   ],\n   \"source\": [\n    \"elements = [\\\"H\\\", \\\"O\\\"]\\n\",\n    \"element_combinations = [[elements[i], elements[j]] for i in range(len(elements)) for j in range(len(elements)) if i <= j]\\n\",\n    \"element_combinations\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 5,\n   \"metadata\": {\n    \"scrolled\": false\n   },\n   \"outputs\": [\n    {\n     \"data\": {\n      \"application/javascript\": [\n       \"/* Put everything inside the global mpl namespace */\\n\",\n       \"window.mpl = {};\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.get_websocket_type = function() {\\n\",\n       \"    if (typeof(WebSocket) !== 'undefined') {\\n\",\n       \"        return WebSocket;\\n\",\n       \"    } else if (typeof(MozWebSocket) !== 'undefined') {\\n\",\n       \"        return MozWebSocket;\\n\",\n       \"    } else {\\n\",\n       \"        alert('Your browser does not have WebSocket support.' +\\n\",\n       \"              'Please try Chrome, Safari or Firefox ≥ 6. ' +\\n\",\n       \"              'Firefox 4 and 5 are also supported but you ' +\\n\",\n       \"              'have to enable WebSockets in about:config.');\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\\n\",\n       \"    this.id = figure_id;\\n\",\n       \"\\n\",\n       \"    this.ws = websocket;\\n\",\n       \"\\n\",\n       \"    this.supports_binary = (this.ws.binaryType != undefined);\\n\",\n       \"\\n\",\n       \"    if (!this.supports_binary) {\\n\",\n       \"        var warnings = document.getElementById(\\\"mpl-warnings\\\");\\n\",\n       \"        if (warnings) {\\n\",\n       \"            warnings.style.display = 'block';\\n\",\n       \"            warnings.textContent = (\\n\",\n       \"                \\\"This browser does not support binary websocket messages. \\\" +\\n\",\n       \"                    \\\"Performance may be slow.\\\");\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.imageObj = new Image();\\n\",\n       \"\\n\",\n       \"    this.context = undefined;\\n\",\n       \"    this.message = undefined;\\n\",\n       \"    this.canvas = undefined;\\n\",\n       \"    this.rubberband_canvas = undefined;\\n\",\n       \"    this.rubberband_context = undefined;\\n\",\n       \"    this.format_dropdown = undefined;\\n\",\n       \"\\n\",\n       \"    this.image_mode = 'full';\\n\",\n       \"\\n\",\n       \"    this.root = $('<div/>');\\n\",\n       \"    this._root_extra_style(this.root)\\n\",\n       \"    this.root.attr('style', 'display: inline-block');\\n\",\n       \"\\n\",\n       \"    $(parent_element).append(this.root);\\n\",\n       \"\\n\",\n       \"    this._init_header(this);\\n\",\n       \"    this._init_canvas(this);\\n\",\n       \"    this._init_toolbar(this);\\n\",\n       \"\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    this.waiting = false;\\n\",\n       \"\\n\",\n       \"    this.ws.onopen =  function () {\\n\",\n       \"            fig.send_message(\\\"supports_binary\\\", {value: fig.supports_binary});\\n\",\n       \"            fig.send_message(\\\"send_image_mode\\\", {});\\n\",\n       \"            if (mpl.ratio != 1) {\\n\",\n       \"                fig.send_message(\\\"set_dpi_ratio\\\", {'dpi_ratio': mpl.ratio});\\n\",\n       \"            }\\n\",\n       \"            fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"    this.imageObj.onload = function() {\\n\",\n       \"            if (fig.image_mode == 'full') {\\n\",\n       \"                // Full images could contain transparency (where diff images\\n\",\n       \"                // almost always do), so we need to clear the canvas so that\\n\",\n       \"                // there is no ghosting.\\n\",\n       \"                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\\n\",\n       \"            }\\n\",\n       \"            fig.context.drawImage(fig.imageObj, 0, 0);\\n\",\n       \"        };\\n\",\n       \"\\n\",\n       \"    this.imageObj.onunload = function() {\\n\",\n       \"        fig.ws.close();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.ws.onmessage = this._make_on_message_function(this);\\n\",\n       \"\\n\",\n       \"    this.ondownload = ondownload;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_header = function() {\\n\",\n       \"    var titlebar = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\\n\",\n       \"        'ui-helper-clearfix\\\"/>');\\n\",\n       \"    var titletext = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-title\\\" style=\\\"width: 100%; ' +\\n\",\n       \"        'text-align: center; padding: 3px;\\\"/>');\\n\",\n       \"    titlebar.append(titletext)\\n\",\n       \"    this.root.append(titlebar);\\n\",\n       \"    this.header = titletext[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_canvas = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var canvas_div = $('<div/>');\\n\",\n       \"\\n\",\n       \"    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\\n\",\n       \"\\n\",\n       \"    function canvas_keyboard_event(event) {\\n\",\n       \"        return fig.key_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    canvas_div.keydown('key_press', canvas_keyboard_event);\\n\",\n       \"    canvas_div.keyup('key_release', canvas_keyboard_event);\\n\",\n       \"    this.canvas_div = canvas_div\\n\",\n       \"    this._canvas_extra_style(canvas_div)\\n\",\n       \"    this.root.append(canvas_div);\\n\",\n       \"\\n\",\n       \"    var canvas = $('<canvas/>');\\n\",\n       \"    canvas.addClass('mpl-canvas');\\n\",\n       \"    canvas.attr('style', \\\"left: 0; top: 0; z-index: 0; outline: 0\\\")\\n\",\n       \"\\n\",\n       \"    this.canvas = canvas[0];\\n\",\n       \"    this.context = canvas[0].getContext(\\\"2d\\\");\\n\",\n       \"\\n\",\n       \"    var backingStore = this.context.backingStorePixelRatio ||\\n\",\n       \"\\tthis.context.webkitBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.mozBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.msBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.oBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.backingStorePixelRatio || 1;\\n\",\n       \"\\n\",\n       \"    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\\n\",\n       \"\\n\",\n       \"    var rubberband = $('<canvas/>');\\n\",\n       \"    rubberband.attr('style', \\\"position: absolute; left: 0; top: 0; z-index: 1;\\\")\\n\",\n       \"\\n\",\n       \"    var pass_mouse_events = true;\\n\",\n       \"\\n\",\n       \"    canvas_div.resizable({\\n\",\n       \"        start: function(event, ui) {\\n\",\n       \"            pass_mouse_events = false;\\n\",\n       \"        },\\n\",\n       \"        resize: function(event, ui) {\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"        stop: function(event, ui) {\\n\",\n       \"            pass_mouse_events = true;\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function mouse_event_fn(event) {\\n\",\n       \"        if (pass_mouse_events)\\n\",\n       \"            return fig.mouse_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    rubberband.mousedown('button_press', mouse_event_fn);\\n\",\n       \"    rubberband.mouseup('button_release', mouse_event_fn);\\n\",\n       \"    // Throttle sequential mouse events to 1 every 20ms.\\n\",\n       \"    rubberband.mousemove('motion_notify', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    rubberband.mouseenter('figure_enter', mouse_event_fn);\\n\",\n       \"    rubberband.mouseleave('figure_leave', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    canvas_div.on(\\\"wheel\\\", function (event) {\\n\",\n       \"        event = event.originalEvent;\\n\",\n       \"        event['data'] = 'scroll'\\n\",\n       \"        if (event.deltaY < 0) {\\n\",\n       \"            event.step = 1;\\n\",\n       \"        } else {\\n\",\n       \"            event.step = -1;\\n\",\n       \"        }\\n\",\n       \"        mouse_event_fn(event);\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    canvas_div.append(canvas);\\n\",\n       \"    canvas_div.append(rubberband);\\n\",\n       \"\\n\",\n       \"    this.rubberband = rubberband;\\n\",\n       \"    this.rubberband_canvas = rubberband[0];\\n\",\n       \"    this.rubberband_context = rubberband[0].getContext(\\\"2d\\\");\\n\",\n       \"    this.rubberband_context.strokeStyle = \\\"#000000\\\";\\n\",\n       \"\\n\",\n       \"    this._resize_canvas = function(width, height) {\\n\",\n       \"        // Keep the size of the canvas, canvas container, and rubber band\\n\",\n       \"        // canvas in synch.\\n\",\n       \"        canvas_div.css('width', width)\\n\",\n       \"        canvas_div.css('height', height)\\n\",\n       \"\\n\",\n       \"        canvas.attr('width', width * mpl.ratio);\\n\",\n       \"        canvas.attr('height', height * mpl.ratio);\\n\",\n       \"        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\\n\",\n       \"\\n\",\n       \"        rubberband.attr('width', width);\\n\",\n       \"        rubberband.attr('height', height);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Set the figure to an initial 600x600px, this will subsequently be updated\\n\",\n       \"    // upon first draw.\\n\",\n       \"    this._resize_canvas(600, 600);\\n\",\n       \"\\n\",\n       \"    // Disable right mouse context menu.\\n\",\n       \"    $(this.rubberband_canvas).bind(\\\"contextmenu\\\",function(e){\\n\",\n       \"        return false;\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function set_focus () {\\n\",\n       \"        canvas.focus();\\n\",\n       \"        canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    window.setTimeout(set_focus, 100);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>')\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items) {\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) {\\n\",\n       \"            // put a spacer in here.\\n\",\n       \"            continue;\\n\",\n       \"        }\\n\",\n       \"        var button = $('<button/>');\\n\",\n       \"        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\\n\",\n       \"                        'ui-button-icon-only');\\n\",\n       \"        button.attr('role', 'button');\\n\",\n       \"        button.attr('aria-disabled', 'false');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"\\n\",\n       \"        var icon_img = $('<span/>');\\n\",\n       \"        icon_img.addClass('ui-button-icon-primary ui-icon');\\n\",\n       \"        icon_img.addClass(image);\\n\",\n       \"        icon_img.addClass('ui-corner-all');\\n\",\n       \"\\n\",\n       \"        var tooltip_span = $('<span/>');\\n\",\n       \"        tooltip_span.addClass('ui-button-text');\\n\",\n       \"        tooltip_span.html(tooltip);\\n\",\n       \"\\n\",\n       \"        button.append(icon_img);\\n\",\n       \"        button.append(tooltip_span);\\n\",\n       \"\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fmt_picker_span = $('<span/>');\\n\",\n       \"\\n\",\n       \"    var fmt_picker = $('<select/>');\\n\",\n       \"    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\\n\",\n       \"    fmt_picker_span.append(fmt_picker);\\n\",\n       \"    nav_element.append(fmt_picker_span);\\n\",\n       \"    this.format_dropdown = fmt_picker[0];\\n\",\n       \"\\n\",\n       \"    for (var ind in mpl.extensions) {\\n\",\n       \"        var fmt = mpl.extensions[ind];\\n\",\n       \"        var option = $(\\n\",\n       \"            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\\n\",\n       \"        fmt_picker.append(option)\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add hover states to the ui-buttons\\n\",\n       \"    $( \\\".ui-button\\\" ).hover(\\n\",\n       \"        function() { $(this).addClass(\\\"ui-state-hover\\\");},\\n\",\n       \"        function() { $(this).removeClass(\\\"ui-state-hover\\\");}\\n\",\n       \"    );\\n\",\n       \"\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\\n\",\n       \"    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\\n\",\n       \"    // which will in turn request a refresh of the image.\\n\",\n       \"    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_message = function(type, properties) {\\n\",\n       \"    properties['type'] = type;\\n\",\n       \"    properties['figure_id'] = this.id;\\n\",\n       \"    this.ws.send(JSON.stringify(properties));\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_draw_message = function() {\\n\",\n       \"    if (!this.waiting) {\\n\",\n       \"        this.waiting = true;\\n\",\n       \"        this.ws.send(JSON.stringify({type: \\\"draw\\\", figure_id: this.id}));\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    var format_dropdown = fig.format_dropdown;\\n\",\n       \"    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\\n\",\n       \"    fig.ondownload(fig, format);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_resize = function(fig, msg) {\\n\",\n       \"    var size = msg['size'];\\n\",\n       \"    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\\n\",\n       \"        fig._resize_canvas(size[0], size[1]);\\n\",\n       \"        fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\\n\",\n       \"    var x0 = msg['x0'] / mpl.ratio;\\n\",\n       \"    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\\n\",\n       \"    var x1 = msg['x1'] / mpl.ratio;\\n\",\n       \"    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\\n\",\n       \"    x0 = Math.floor(x0) + 0.5;\\n\",\n       \"    y0 = Math.floor(y0) + 0.5;\\n\",\n       \"    x1 = Math.floor(x1) + 0.5;\\n\",\n       \"    y1 = Math.floor(y1) + 0.5;\\n\",\n       \"    var min_x = Math.min(x0, x1);\\n\",\n       \"    var min_y = Math.min(y0, y1);\\n\",\n       \"    var width = Math.abs(x1 - x0);\\n\",\n       \"    var height = Math.abs(y1 - y0);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.clearRect(\\n\",\n       \"        0, 0, fig.canvas.width, fig.canvas.height);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\\n\",\n       \"    // Updates the figure title.\\n\",\n       \"    fig.header.textContent = msg['label'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_cursor = function(fig, msg) {\\n\",\n       \"    var cursor = msg['cursor'];\\n\",\n       \"    switch(cursor)\\n\",\n       \"    {\\n\",\n       \"    case 0:\\n\",\n       \"        cursor = 'pointer';\\n\",\n       \"        break;\\n\",\n       \"    case 1:\\n\",\n       \"        cursor = 'default';\\n\",\n       \"        break;\\n\",\n       \"    case 2:\\n\",\n       \"        cursor = 'crosshair';\\n\",\n       \"        break;\\n\",\n       \"    case 3:\\n\",\n       \"        cursor = 'move';\\n\",\n       \"        break;\\n\",\n       \"    }\\n\",\n       \"    fig.rubberband_canvas.style.cursor = cursor;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_message = function(fig, msg) {\\n\",\n       \"    fig.message.textContent = msg['message'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_draw = function(fig, msg) {\\n\",\n       \"    // Request the server to send over a new figure.\\n\",\n       \"    fig.send_draw_message();\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\\n\",\n       \"    fig.image_mode = msg['mode'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Called whenever the canvas gets updated.\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// A function to construct a web socket function for onmessage handling.\\n\",\n       \"// Called in the figure constructor.\\n\",\n       \"mpl.figure.prototype._make_on_message_function = function(fig) {\\n\",\n       \"    return function socket_on_message(evt) {\\n\",\n       \"        if (evt.data instanceof Blob) {\\n\",\n       \"            /* FIXME: We get \\\"Resource interpreted as Image but\\n\",\n       \"             * transferred with MIME type text/plain:\\\" errors on\\n\",\n       \"             * Chrome.  But how to set the MIME type?  It doesn't seem\\n\",\n       \"             * to be part of the websocket stream */\\n\",\n       \"            evt.data.type = \\\"image/png\\\";\\n\",\n       \"\\n\",\n       \"            /* Free the memory for the previous frames */\\n\",\n       \"            if (fig.imageObj.src) {\\n\",\n       \"                (window.URL || window.webkitURL).revokeObjectURL(\\n\",\n       \"                    fig.imageObj.src);\\n\",\n       \"            }\\n\",\n       \"\\n\",\n       \"            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\\n\",\n       \"                evt.data);\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \\\"data:image/png;base64\\\") {\\n\",\n       \"            fig.imageObj.src = evt.data;\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        var msg = JSON.parse(evt.data);\\n\",\n       \"        var msg_type = msg['type'];\\n\",\n       \"\\n\",\n       \"        // Call the  \\\"handle_{type}\\\" callback, which takes\\n\",\n       \"        // the figure and JSON message as its only arguments.\\n\",\n       \"        try {\\n\",\n       \"            var callback = fig[\\\"handle_\\\" + msg_type];\\n\",\n       \"        } catch (e) {\\n\",\n       \"            console.log(\\\"No handler for the '\\\" + msg_type + \\\"' message type: \\\", msg);\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        if (callback) {\\n\",\n       \"            try {\\n\",\n       \"                // console.log(\\\"Handling '\\\" + msg_type + \\\"' message: \\\", msg);\\n\",\n       \"                callback(fig, msg);\\n\",\n       \"            } catch (e) {\\n\",\n       \"                console.log(\\\"Exception inside the 'handler_\\\" + msg_type + \\\"' callback:\\\", e, e.stack, msg);\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\\n\",\n       \"mpl.findpos = function(e) {\\n\",\n       \"    //this section is from http://www.quirksmode.org/js/events_properties.html\\n\",\n       \"    var targ;\\n\",\n       \"    if (!e)\\n\",\n       \"        e = window.event;\\n\",\n       \"    if (e.target)\\n\",\n       \"        targ = e.target;\\n\",\n       \"    else if (e.srcElement)\\n\",\n       \"        targ = e.srcElement;\\n\",\n       \"    if (targ.nodeType == 3) // defeat Safari bug\\n\",\n       \"        targ = targ.parentNode;\\n\",\n       \"\\n\",\n       \"    // jQuery normalizes the pageX and pageY\\n\",\n       \"    // pageX,Y are the mouse positions relative to the document\\n\",\n       \"    // offset() returns the position of the element relative to the document\\n\",\n       \"    var x = e.pageX - $(targ).offset().left;\\n\",\n       \"    var y = e.pageY - $(targ).offset().top;\\n\",\n       \"\\n\",\n       \"    return {\\\"x\\\": x, \\\"y\\\": y};\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"/*\\n\",\n       \" * return a copy of an object with only non-object keys\\n\",\n       \" * we need this to avoid circular references\\n\",\n       \" * http://stackoverflow.com/a/24161582/3208463\\n\",\n       \" */\\n\",\n       \"function simpleKeys (original) {\\n\",\n       \"  return Object.keys(original).reduce(function (obj, key) {\\n\",\n       \"    if (typeof original[key] !== 'object')\\n\",\n       \"        obj[key] = original[key]\\n\",\n       \"    return obj;\\n\",\n       \"  }, {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.mouse_event = function(event, name) {\\n\",\n       \"    var canvas_pos = mpl.findpos(event)\\n\",\n       \"\\n\",\n       \"    if (name === 'button_press')\\n\",\n       \"    {\\n\",\n       \"        this.canvas.focus();\\n\",\n       \"        this.canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var x = canvas_pos.x * mpl.ratio;\\n\",\n       \"    var y = canvas_pos.y * mpl.ratio;\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {x: x, y: y, button: event.button,\\n\",\n       \"                             step: event.step,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"\\n\",\n       \"    /* This prevents the web browser from automatically changing to\\n\",\n       \"     * the text insertion cursor when the button is pressed.  We want\\n\",\n       \"     * to control all of the cursor setting manually through the\\n\",\n       \"     * 'cursor' event from matplotlib */\\n\",\n       \"    event.preventDefault();\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    // Handle any extra behaviour associated with a key event\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.key_event = function(event, name) {\\n\",\n       \"\\n\",\n       \"    // Prevent repeat events\\n\",\n       \"    if (name == 'key_press')\\n\",\n       \"    {\\n\",\n       \"        if (event.which === this._key)\\n\",\n       \"            return;\\n\",\n       \"        else\\n\",\n       \"            this._key = event.which;\\n\",\n       \"    }\\n\",\n       \"    if (name == 'key_release')\\n\",\n       \"        this._key = null;\\n\",\n       \"\\n\",\n       \"    var value = '';\\n\",\n       \"    if (event.ctrlKey && event.which != 17)\\n\",\n       \"        value += \\\"ctrl+\\\";\\n\",\n       \"    if (event.altKey && event.which != 18)\\n\",\n       \"        value += \\\"alt+\\\";\\n\",\n       \"    if (event.shiftKey && event.which != 16)\\n\",\n       \"        value += \\\"shift+\\\";\\n\",\n       \"\\n\",\n       \"    value += 'k';\\n\",\n       \"    value += event.which.toString();\\n\",\n       \"\\n\",\n       \"    this._key_event_extra(event, name);\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {key: value,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onclick = function(name) {\\n\",\n       \"    if (name == 'download') {\\n\",\n       \"        this.handle_save(this, null);\\n\",\n       \"    } else {\\n\",\n       \"        this.send_message(\\\"toolbar_button\\\", {name: name});\\n\",\n       \"    }\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\\n\",\n       \"    this.message.textContent = tooltip;\\n\",\n       \"};\\n\",\n       \"mpl.toolbar_items = [[\\\"Home\\\", \\\"Reset original view\\\", \\\"fa fa-home icon-home\\\", \\\"home\\\"], [\\\"Back\\\", \\\"Back to  previous view\\\", \\\"fa fa-arrow-left icon-arrow-left\\\", \\\"back\\\"], [\\\"Forward\\\", \\\"Forward to next view\\\", \\\"fa fa-arrow-right icon-arrow-right\\\", \\\"forward\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Pan\\\", \\\"Pan axes with left mouse, zoom with right\\\", \\\"fa fa-arrows icon-move\\\", \\\"pan\\\"], [\\\"Zoom\\\", \\\"Zoom to rectangle\\\", \\\"fa fa-square-o icon-check-empty\\\", \\\"zoom\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Download\\\", \\\"Download plot\\\", \\\"fa fa-floppy-o icon-save\\\", \\\"download\\\"]];\\n\",\n       \"\\n\",\n       \"mpl.extensions = [\\\"eps\\\", \\\"jpeg\\\", \\\"pdf\\\", \\\"png\\\", \\\"ps\\\", \\\"raw\\\", \\\"svg\\\", \\\"tif\\\"];\\n\",\n       \"\\n\",\n       \"mpl.default_extension = \\\"png\\\";var comm_websocket_adapter = function(comm) {\\n\",\n       \"    // Create a \\\"websocket\\\"-like object which calls the given IPython comm\\n\",\n       \"    // object with the appropriate methods. Currently this is a non binary\\n\",\n       \"    // socket, so there is still some room for performance tuning.\\n\",\n       \"    var ws = {};\\n\",\n       \"\\n\",\n       \"    ws.close = function() {\\n\",\n       \"        comm.close()\\n\",\n       \"    };\\n\",\n       \"    ws.send = function(m) {\\n\",\n       \"        //console.log('sending', m);\\n\",\n       \"        comm.send(m);\\n\",\n       \"    };\\n\",\n       \"    // Register the callback with on_msg.\\n\",\n       \"    comm.on_msg(function(msg) {\\n\",\n       \"        //console.log('receiving', msg['content']['data'], msg);\\n\",\n       \"        // Pass the mpl event to the overridden (by mpl) onmessage function.\\n\",\n       \"        ws.onmessage(msg['content']['data'])\\n\",\n       \"    });\\n\",\n       \"    return ws;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.mpl_figure_comm = function(comm, msg) {\\n\",\n       \"    // This is the function which gets called when the mpl process\\n\",\n       \"    // starts-up an IPython Comm through the \\\"matplotlib\\\" channel.\\n\",\n       \"\\n\",\n       \"    var id = msg.content.data.id;\\n\",\n       \"    // Get hold of the div created by the display call when the Comm\\n\",\n       \"    // socket was opened in Python.\\n\",\n       \"    var element = $(\\\"#\\\" + id);\\n\",\n       \"    var ws_proxy = comm_websocket_adapter(comm)\\n\",\n       \"\\n\",\n       \"    function ondownload(figure, format) {\\n\",\n       \"        window.open(figure.imageObj.src);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fig = new mpl.figure(id, ws_proxy,\\n\",\n       \"                           ondownload,\\n\",\n       \"                           element.get(0));\\n\",\n       \"\\n\",\n       \"    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\\n\",\n       \"    // web socket which is closed, not our websocket->open comm proxy.\\n\",\n       \"    ws_proxy.onopen();\\n\",\n       \"\\n\",\n       \"    fig.parent_element = element.get(0);\\n\",\n       \"    fig.cell_info = mpl.find_output_cell(\\\"<div id='\\\" + id + \\\"'></div>\\\");\\n\",\n       \"    if (!fig.cell_info) {\\n\",\n       \"        console.error(\\\"Failed to find cell for figure\\\", id, fig);\\n\",\n       \"        return;\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var output_index = fig.cell_info[2]\\n\",\n       \"    var cell = fig.cell_info[0];\\n\",\n       \"\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_close = function(fig, msg) {\\n\",\n       \"    var width = fig.canvas.width/mpl.ratio\\n\",\n       \"    fig.root.unbind('remove')\\n\",\n       \"\\n\",\n       \"    // Update the output cell to use the data from the current canvas.\\n\",\n       \"    fig.push_to_output();\\n\",\n       \"    var dataURL = fig.canvas.toDataURL();\\n\",\n       \"    // Re-enable the keyboard manager in IPython - without this line, in FF,\\n\",\n       \"    // the notebook keyboard shortcuts fail.\\n\",\n       \"    IPython.keyboard_manager.enable()\\n\",\n       \"    $(fig.parent_element).html('<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">');\\n\",\n       \"    fig.close_ws(fig, msg);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.close_ws = function(fig, msg){\\n\",\n       \"    fig.send_message('closing', msg);\\n\",\n       \"    // fig.ws.close()\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.push_to_output = function(remove_interactive) {\\n\",\n       \"    // Turn the data on the canvas into data in the output cell.\\n\",\n       \"    var width = this.canvas.width/mpl.ratio\\n\",\n       \"    var dataURL = this.canvas.toDataURL();\\n\",\n       \"    this.cell_info[1]['text/html'] = '<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">';\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Tell IPython that the notebook contents must change.\\n\",\n       \"    IPython.notebook.set_dirty(true);\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"    var fig = this;\\n\",\n       \"    // Wait a second, then push the new image to the DOM so\\n\",\n       \"    // that it is saved nicely (might be nice to debounce this).\\n\",\n       \"    setTimeout(function () { fig.push_to_output() }, 1000);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>')\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items){\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) { continue; };\\n\",\n       \"\\n\",\n       \"        var button = $('<button class=\\\"btn btn-default\\\" href=\\\"#\\\" title=\\\"' + name + '\\\"><i class=\\\"fa ' + image + ' fa-lg\\\"></i></button>');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add the status bar.\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\" style=\\\"text-align:right; float: right;\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"\\n\",\n       \"    // Add the close button to the window.\\n\",\n       \"    var buttongrp = $('<div class=\\\"btn-group inline pull-right\\\"></div>');\\n\",\n       \"    var button = $('<button class=\\\"btn btn-mini btn-primary\\\" href=\\\"#\\\" title=\\\"Stop Interaction\\\"><i class=\\\"fa fa-power-off icon-remove icon-large\\\"></i></button>');\\n\",\n       \"    button.click(function (evt) { fig.handle_close(fig, {}); } );\\n\",\n       \"    button.mouseover('Stop Interaction', toolbar_mouse_event);\\n\",\n       \"    buttongrp.append(button);\\n\",\n       \"    var titlebar = this.root.find($('.ui-dialog-titlebar'));\\n\",\n       \"    titlebar.prepend(buttongrp);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(el){\\n\",\n       \"    var fig = this\\n\",\n       \"    el.on(\\\"remove\\\", function(){\\n\",\n       \"\\tfig.close_ws(fig, {});\\n\",\n       \"    });\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(el){\\n\",\n       \"    // this is important to make the div 'focusable\\n\",\n       \"    el.attr('tabindex', 0)\\n\",\n       \"    // reach out to IPython and tell the keyboard manager to turn it's self\\n\",\n       \"    // off when our div gets focus\\n\",\n       \"\\n\",\n       \"    // location in version 3\\n\",\n       \"    if (IPython.notebook.keyboard_manager) {\\n\",\n       \"        IPython.notebook.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"    else {\\n\",\n       \"        // location in version 2\\n\",\n       \"        IPython.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    var manager = IPython.notebook.keyboard_manager;\\n\",\n       \"    if (!manager)\\n\",\n       \"        manager = IPython.keyboard_manager;\\n\",\n       \"\\n\",\n       \"    // Check for shift+enter\\n\",\n       \"    if (event.shiftKey && event.which == 13) {\\n\",\n       \"        this.canvas_div.blur();\\n\",\n       \"        event.shiftKey = false;\\n\",\n       \"        // Send a \\\"J\\\" for go to next cell\\n\",\n       \"        event.which = 74;\\n\",\n       \"        event.keyCode = 74;\\n\",\n       \"        manager.command_mode();\\n\",\n       \"        manager.handle_keydown(event);\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    fig.ondownload(fig, null);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.find_output_cell = function(html_output) {\\n\",\n       \"    // Return the cell and output element which can be found *uniquely* in the notebook.\\n\",\n       \"    // Note - this is a bit hacky, but it is done because the \\\"notebook_saving.Notebook\\\"\\n\",\n       \"    // IPython event is triggered only after the cells have been serialised, which for\\n\",\n       \"    // our purposes (turning an active figure into a static one), is too late.\\n\",\n       \"    var cells = IPython.notebook.get_cells();\\n\",\n       \"    var ncells = cells.length;\\n\",\n       \"    for (var i=0; i<ncells; i++) {\\n\",\n       \"        var cell = cells[i];\\n\",\n       \"        if (cell.cell_type === 'code'){\\n\",\n       \"            for (var j=0; j<cell.output_area.outputs.length; j++) {\\n\",\n       \"                var data = cell.output_area.outputs[j];\\n\",\n       \"                if (data.data) {\\n\",\n       \"                    // IPython >= 3 moved mimebundle to data attribute of output\\n\",\n       \"                    data = data.data;\\n\",\n       \"                }\\n\",\n       \"                if (data['text/html'] == html_output) {\\n\",\n       \"                    return [cell, data, j];\\n\",\n       \"                }\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// Register the function which deals with the matplotlib target/channel.\\n\",\n       \"// The kernel may be null if the page has been refreshed.\\n\",\n       \"if (IPython.notebook.kernel != null) {\\n\",\n       \"    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\\n\",\n       \"}\\n\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.Javascript object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"text/html\": [\n       \"<img src=\\\"data:image/png;base64,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\\\" width=\\\"639.8333333333334\\\">\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.HTML object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"application/javascript\": [\n       \"/* Put everything inside the global mpl namespace */\\n\",\n       \"window.mpl = {};\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.get_websocket_type = function() {\\n\",\n       \"    if (typeof(WebSocket) !== 'undefined') {\\n\",\n       \"        return WebSocket;\\n\",\n       \"    } else if (typeof(MozWebSocket) !== 'undefined') {\\n\",\n       \"        return MozWebSocket;\\n\",\n       \"    } else {\\n\",\n       \"        alert('Your browser does not have WebSocket support.' +\\n\",\n       \"              'Please try Chrome, Safari or Firefox ≥ 6. ' +\\n\",\n       \"              'Firefox 4 and 5 are also supported but you ' +\\n\",\n       \"              'have to enable WebSockets in about:config.');\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\\n\",\n       \"    this.id = figure_id;\\n\",\n       \"\\n\",\n       \"    this.ws = websocket;\\n\",\n       \"\\n\",\n       \"    this.supports_binary = (this.ws.binaryType != undefined);\\n\",\n       \"\\n\",\n       \"    if (!this.supports_binary) {\\n\",\n       \"        var warnings = document.getElementById(\\\"mpl-warnings\\\");\\n\",\n       \"        if (warnings) {\\n\",\n       \"            warnings.style.display = 'block';\\n\",\n       \"            warnings.textContent = (\\n\",\n       \"                \\\"This browser does not support binary websocket messages. \\\" +\\n\",\n       \"                    \\\"Performance may be slow.\\\");\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.imageObj = new Image();\\n\",\n       \"\\n\",\n       \"    this.context = undefined;\\n\",\n       \"    this.message = undefined;\\n\",\n       \"    this.canvas = undefined;\\n\",\n       \"    this.rubberband_canvas = undefined;\\n\",\n       \"    this.rubberband_context = undefined;\\n\",\n       \"    this.format_dropdown = undefined;\\n\",\n       \"\\n\",\n       \"    this.image_mode = 'full';\\n\",\n       \"\\n\",\n       \"    this.root = $('<div/>');\\n\",\n       \"    this._root_extra_style(this.root)\\n\",\n       \"    this.root.attr('style', 'display: inline-block');\\n\",\n       \"\\n\",\n       \"    $(parent_element).append(this.root);\\n\",\n       \"\\n\",\n       \"    this._init_header(this);\\n\",\n       \"    this._init_canvas(this);\\n\",\n       \"    this._init_toolbar(this);\\n\",\n       \"\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    this.waiting = false;\\n\",\n       \"\\n\",\n       \"    this.ws.onopen =  function () {\\n\",\n       \"            fig.send_message(\\\"supports_binary\\\", {value: fig.supports_binary});\\n\",\n       \"            fig.send_message(\\\"send_image_mode\\\", {});\\n\",\n       \"            if (mpl.ratio != 1) {\\n\",\n       \"                fig.send_message(\\\"set_dpi_ratio\\\", {'dpi_ratio': mpl.ratio});\\n\",\n       \"            }\\n\",\n       \"            fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"    this.imageObj.onload = function() {\\n\",\n       \"            if (fig.image_mode == 'full') {\\n\",\n       \"                // Full images could contain transparency (where diff images\\n\",\n       \"                // almost always do), so we need to clear the canvas so that\\n\",\n       \"                // there is no ghosting.\\n\",\n       \"                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\\n\",\n       \"            }\\n\",\n       \"            fig.context.drawImage(fig.imageObj, 0, 0);\\n\",\n       \"        };\\n\",\n       \"\\n\",\n       \"    this.imageObj.onunload = function() {\\n\",\n       \"        fig.ws.close();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.ws.onmessage = this._make_on_message_function(this);\\n\",\n       \"\\n\",\n       \"    this.ondownload = ondownload;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_header = function() {\\n\",\n       \"    var titlebar = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\\n\",\n       \"        'ui-helper-clearfix\\\"/>');\\n\",\n       \"    var titletext = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-title\\\" style=\\\"width: 100%; ' +\\n\",\n       \"        'text-align: center; padding: 3px;\\\"/>');\\n\",\n       \"    titlebar.append(titletext)\\n\",\n       \"    this.root.append(titlebar);\\n\",\n       \"    this.header = titletext[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_canvas = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var canvas_div = $('<div/>');\\n\",\n       \"\\n\",\n       \"    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\\n\",\n       \"\\n\",\n       \"    function canvas_keyboard_event(event) {\\n\",\n       \"        return fig.key_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    canvas_div.keydown('key_press', canvas_keyboard_event);\\n\",\n       \"    canvas_div.keyup('key_release', canvas_keyboard_event);\\n\",\n       \"    this.canvas_div = canvas_div\\n\",\n       \"    this._canvas_extra_style(canvas_div)\\n\",\n       \"    this.root.append(canvas_div);\\n\",\n       \"\\n\",\n       \"    var canvas = $('<canvas/>');\\n\",\n       \"    canvas.addClass('mpl-canvas');\\n\",\n       \"    canvas.attr('style', \\\"left: 0; top: 0; z-index: 0; outline: 0\\\")\\n\",\n       \"\\n\",\n       \"    this.canvas = canvas[0];\\n\",\n       \"    this.context = canvas[0].getContext(\\\"2d\\\");\\n\",\n       \"\\n\",\n       \"    var backingStore = this.context.backingStorePixelRatio ||\\n\",\n       \"\\tthis.context.webkitBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.mozBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.msBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.oBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.backingStorePixelRatio || 1;\\n\",\n       \"\\n\",\n       \"    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\\n\",\n       \"\\n\",\n       \"    var rubberband = $('<canvas/>');\\n\",\n       \"    rubberband.attr('style', \\\"position: absolute; left: 0; top: 0; z-index: 1;\\\")\\n\",\n       \"\\n\",\n       \"    var pass_mouse_events = true;\\n\",\n       \"\\n\",\n       \"    canvas_div.resizable({\\n\",\n       \"        start: function(event, ui) {\\n\",\n       \"            pass_mouse_events = false;\\n\",\n       \"        },\\n\",\n       \"        resize: function(event, ui) {\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"        stop: function(event, ui) {\\n\",\n       \"            pass_mouse_events = true;\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function mouse_event_fn(event) {\\n\",\n       \"        if (pass_mouse_events)\\n\",\n       \"            return fig.mouse_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    rubberband.mousedown('button_press', mouse_event_fn);\\n\",\n       \"    rubberband.mouseup('button_release', mouse_event_fn);\\n\",\n       \"    // Throttle sequential mouse events to 1 every 20ms.\\n\",\n       \"    rubberband.mousemove('motion_notify', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    rubberband.mouseenter('figure_enter', mouse_event_fn);\\n\",\n       \"    rubberband.mouseleave('figure_leave', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    canvas_div.on(\\\"wheel\\\", function (event) {\\n\",\n       \"        event = event.originalEvent;\\n\",\n       \"        event['data'] = 'scroll'\\n\",\n       \"        if (event.deltaY < 0) {\\n\",\n       \"            event.step = 1;\\n\",\n       \"        } else {\\n\",\n       \"            event.step = -1;\\n\",\n       \"        }\\n\",\n       \"        mouse_event_fn(event);\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    canvas_div.append(canvas);\\n\",\n       \"    canvas_div.append(rubberband);\\n\",\n       \"\\n\",\n       \"    this.rubberband = rubberband;\\n\",\n       \"    this.rubberband_canvas = rubberband[0];\\n\",\n       \"    this.rubberband_context = rubberband[0].getContext(\\\"2d\\\");\\n\",\n       \"    this.rubberband_context.strokeStyle = \\\"#000000\\\";\\n\",\n       \"\\n\",\n       \"    this._resize_canvas = function(width, height) {\\n\",\n       \"        // Keep the size of the canvas, canvas container, and rubber band\\n\",\n       \"        // canvas in synch.\\n\",\n       \"        canvas_div.css('width', width)\\n\",\n       \"        canvas_div.css('height', height)\\n\",\n       \"\\n\",\n       \"        canvas.attr('width', width * mpl.ratio);\\n\",\n       \"        canvas.attr('height', height * mpl.ratio);\\n\",\n       \"        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\\n\",\n       \"\\n\",\n       \"        rubberband.attr('width', width);\\n\",\n       \"        rubberband.attr('height', height);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Set the figure to an initial 600x600px, this will subsequently be updated\\n\",\n       \"    // upon first draw.\\n\",\n       \"    this._resize_canvas(600, 600);\\n\",\n       \"\\n\",\n       \"    // Disable right mouse context menu.\\n\",\n       \"    $(this.rubberband_canvas).bind(\\\"contextmenu\\\",function(e){\\n\",\n       \"        return false;\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function set_focus () {\\n\",\n       \"        canvas.focus();\\n\",\n       \"        canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    window.setTimeout(set_focus, 100);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>')\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items) {\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) {\\n\",\n       \"            // put a spacer in here.\\n\",\n       \"            continue;\\n\",\n       \"        }\\n\",\n       \"        var button = $('<button/>');\\n\",\n       \"        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\\n\",\n       \"                        'ui-button-icon-only');\\n\",\n       \"        button.attr('role', 'button');\\n\",\n       \"        button.attr('aria-disabled', 'false');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"\\n\",\n       \"        var icon_img = $('<span/>');\\n\",\n       \"        icon_img.addClass('ui-button-icon-primary ui-icon');\\n\",\n       \"        icon_img.addClass(image);\\n\",\n       \"        icon_img.addClass('ui-corner-all');\\n\",\n       \"\\n\",\n       \"        var tooltip_span = $('<span/>');\\n\",\n       \"        tooltip_span.addClass('ui-button-text');\\n\",\n       \"        tooltip_span.html(tooltip);\\n\",\n       \"\\n\",\n       \"        button.append(icon_img);\\n\",\n       \"        button.append(tooltip_span);\\n\",\n       \"\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fmt_picker_span = $('<span/>');\\n\",\n       \"\\n\",\n       \"    var fmt_picker = $('<select/>');\\n\",\n       \"    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\\n\",\n       \"    fmt_picker_span.append(fmt_picker);\\n\",\n       \"    nav_element.append(fmt_picker_span);\\n\",\n       \"    this.format_dropdown = fmt_picker[0];\\n\",\n       \"\\n\",\n       \"    for (var ind in mpl.extensions) {\\n\",\n       \"        var fmt = mpl.extensions[ind];\\n\",\n       \"        var option = $(\\n\",\n       \"            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\\n\",\n       \"        fmt_picker.append(option)\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add hover states to the ui-buttons\\n\",\n       \"    $( \\\".ui-button\\\" ).hover(\\n\",\n       \"        function() { $(this).addClass(\\\"ui-state-hover\\\");},\\n\",\n       \"        function() { $(this).removeClass(\\\"ui-state-hover\\\");}\\n\",\n       \"    );\\n\",\n       \"\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\\n\",\n       \"    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\\n\",\n       \"    // which will in turn request a refresh of the image.\\n\",\n       \"    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_message = function(type, properties) {\\n\",\n       \"    properties['type'] = type;\\n\",\n       \"    properties['figure_id'] = this.id;\\n\",\n       \"    this.ws.send(JSON.stringify(properties));\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_draw_message = function() {\\n\",\n       \"    if (!this.waiting) {\\n\",\n       \"        this.waiting = true;\\n\",\n       \"        this.ws.send(JSON.stringify({type: \\\"draw\\\", figure_id: this.id}));\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    var format_dropdown = fig.format_dropdown;\\n\",\n       \"    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\\n\",\n       \"    fig.ondownload(fig, format);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_resize = function(fig, msg) {\\n\",\n       \"    var size = msg['size'];\\n\",\n       \"    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\\n\",\n       \"        fig._resize_canvas(size[0], size[1]);\\n\",\n       \"        fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\\n\",\n       \"    var x0 = msg['x0'] / mpl.ratio;\\n\",\n       \"    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\\n\",\n       \"    var x1 = msg['x1'] / mpl.ratio;\\n\",\n       \"    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\\n\",\n       \"    x0 = Math.floor(x0) + 0.5;\\n\",\n       \"    y0 = Math.floor(y0) + 0.5;\\n\",\n       \"    x1 = Math.floor(x1) + 0.5;\\n\",\n       \"    y1 = Math.floor(y1) + 0.5;\\n\",\n       \"    var min_x = Math.min(x0, x1);\\n\",\n       \"    var min_y = Math.min(y0, y1);\\n\",\n       \"    var width = Math.abs(x1 - x0);\\n\",\n       \"    var height = Math.abs(y1 - y0);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.clearRect(\\n\",\n       \"        0, 0, fig.canvas.width, fig.canvas.height);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\\n\",\n       \"    // Updates the figure title.\\n\",\n       \"    fig.header.textContent = msg['label'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_cursor = function(fig, msg) {\\n\",\n       \"    var cursor = msg['cursor'];\\n\",\n       \"    switch(cursor)\\n\",\n       \"    {\\n\",\n       \"    case 0:\\n\",\n       \"        cursor = 'pointer';\\n\",\n       \"        break;\\n\",\n       \"    case 1:\\n\",\n       \"        cursor = 'default';\\n\",\n       \"        break;\\n\",\n       \"    case 2:\\n\",\n       \"        cursor = 'crosshair';\\n\",\n       \"        break;\\n\",\n       \"    case 3:\\n\",\n       \"        cursor = 'move';\\n\",\n       \"        break;\\n\",\n       \"    }\\n\",\n       \"    fig.rubberband_canvas.style.cursor = cursor;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_message = function(fig, msg) {\\n\",\n       \"    fig.message.textContent = msg['message'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_draw = function(fig, msg) {\\n\",\n       \"    // Request the server to send over a new figure.\\n\",\n       \"    fig.send_draw_message();\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\\n\",\n       \"    fig.image_mode = msg['mode'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Called whenever the canvas gets updated.\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// A function to construct a web socket function for onmessage handling.\\n\",\n       \"// Called in the figure constructor.\\n\",\n       \"mpl.figure.prototype._make_on_message_function = function(fig) {\\n\",\n       \"    return function socket_on_message(evt) {\\n\",\n       \"        if (evt.data instanceof Blob) {\\n\",\n       \"            /* FIXME: We get \\\"Resource interpreted as Image but\\n\",\n       \"             * transferred with MIME type text/plain:\\\" errors on\\n\",\n       \"             * Chrome.  But how to set the MIME type?  It doesn't seem\\n\",\n       \"             * to be part of the websocket stream */\\n\",\n       \"            evt.data.type = \\\"image/png\\\";\\n\",\n       \"\\n\",\n       \"            /* Free the memory for the previous frames */\\n\",\n       \"            if (fig.imageObj.src) {\\n\",\n       \"                (window.URL || window.webkitURL).revokeObjectURL(\\n\",\n       \"                    fig.imageObj.src);\\n\",\n       \"            }\\n\",\n       \"\\n\",\n       \"            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\\n\",\n       \"                evt.data);\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \\\"data:image/png;base64\\\") {\\n\",\n       \"            fig.imageObj.src = evt.data;\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        var msg = JSON.parse(evt.data);\\n\",\n       \"        var msg_type = msg['type'];\\n\",\n       \"\\n\",\n       \"        // Call the  \\\"handle_{type}\\\" callback, which takes\\n\",\n       \"        // the figure and JSON message as its only arguments.\\n\",\n       \"        try {\\n\",\n       \"            var callback = fig[\\\"handle_\\\" + msg_type];\\n\",\n       \"        } catch (e) {\\n\",\n       \"            console.log(\\\"No handler for the '\\\" + msg_type + \\\"' message type: \\\", msg);\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        if (callback) {\\n\",\n       \"            try {\\n\",\n       \"                // console.log(\\\"Handling '\\\" + msg_type + \\\"' message: \\\", msg);\\n\",\n       \"                callback(fig, msg);\\n\",\n       \"            } catch (e) {\\n\",\n       \"                console.log(\\\"Exception inside the 'handler_\\\" + msg_type + \\\"' callback:\\\", e, e.stack, msg);\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\\n\",\n       \"mpl.findpos = function(e) {\\n\",\n       \"    //this section is from http://www.quirksmode.org/js/events_properties.html\\n\",\n       \"    var targ;\\n\",\n       \"    if (!e)\\n\",\n       \"        e = window.event;\\n\",\n       \"    if (e.target)\\n\",\n       \"        targ = e.target;\\n\",\n       \"    else if (e.srcElement)\\n\",\n       \"        targ = e.srcElement;\\n\",\n       \"    if (targ.nodeType == 3) // defeat Safari bug\\n\",\n       \"        targ = targ.parentNode;\\n\",\n       \"\\n\",\n       \"    // jQuery normalizes the pageX and pageY\\n\",\n       \"    // pageX,Y are the mouse positions relative to the document\\n\",\n       \"    // offset() returns the position of the element relative to the document\\n\",\n       \"    var x = e.pageX - $(targ).offset().left;\\n\",\n       \"    var y = e.pageY - $(targ).offset().top;\\n\",\n       \"\\n\",\n       \"    return {\\\"x\\\": x, \\\"y\\\": y};\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"/*\\n\",\n       \" * return a copy of an object with only non-object keys\\n\",\n       \" * we need this to avoid circular references\\n\",\n       \" * http://stackoverflow.com/a/24161582/3208463\\n\",\n       \" */\\n\",\n       \"function simpleKeys (original) {\\n\",\n       \"  return Object.keys(original).reduce(function (obj, key) {\\n\",\n       \"    if (typeof original[key] !== 'object')\\n\",\n       \"        obj[key] = original[key]\\n\",\n       \"    return obj;\\n\",\n       \"  }, {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.mouse_event = function(event, name) {\\n\",\n       \"    var canvas_pos = mpl.findpos(event)\\n\",\n       \"\\n\",\n       \"    if (name === 'button_press')\\n\",\n       \"    {\\n\",\n       \"        this.canvas.focus();\\n\",\n       \"        this.canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var x = canvas_pos.x * mpl.ratio;\\n\",\n       \"    var y = canvas_pos.y * mpl.ratio;\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {x: x, y: y, button: event.button,\\n\",\n       \"                             step: event.step,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"\\n\",\n       \"    /* This prevents the web browser from automatically changing to\\n\",\n       \"     * the text insertion cursor when the button is pressed.  We want\\n\",\n       \"     * to control all of the cursor setting manually through the\\n\",\n       \"     * 'cursor' event from matplotlib */\\n\",\n       \"    event.preventDefault();\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    // Handle any extra behaviour associated with a key event\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.key_event = function(event, name) {\\n\",\n       \"\\n\",\n       \"    // Prevent repeat events\\n\",\n       \"    if (name == 'key_press')\\n\",\n       \"    {\\n\",\n       \"        if (event.which === this._key)\\n\",\n       \"            return;\\n\",\n       \"        else\\n\",\n       \"            this._key = event.which;\\n\",\n       \"    }\\n\",\n       \"    if (name == 'key_release')\\n\",\n       \"        this._key = null;\\n\",\n       \"\\n\",\n       \"    var value = '';\\n\",\n       \"    if (event.ctrlKey && event.which != 17)\\n\",\n       \"        value += \\\"ctrl+\\\";\\n\",\n       \"    if (event.altKey && event.which != 18)\\n\",\n       \"        value += \\\"alt+\\\";\\n\",\n       \"    if (event.shiftKey && event.which != 16)\\n\",\n       \"        value += \\\"shift+\\\";\\n\",\n       \"\\n\",\n       \"    value += 'k';\\n\",\n       \"    value += event.which.toString();\\n\",\n       \"\\n\",\n       \"    this._key_event_extra(event, name);\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {key: value,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onclick = function(name) {\\n\",\n       \"    if (name == 'download') {\\n\",\n       \"        this.handle_save(this, null);\\n\",\n       \"    } else {\\n\",\n       \"        this.send_message(\\\"toolbar_button\\\", {name: name});\\n\",\n       \"    }\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\\n\",\n       \"    this.message.textContent = tooltip;\\n\",\n       \"};\\n\",\n       \"mpl.toolbar_items = [[\\\"Home\\\", \\\"Reset original view\\\", \\\"fa fa-home icon-home\\\", \\\"home\\\"], [\\\"Back\\\", \\\"Back to  previous view\\\", \\\"fa fa-arrow-left icon-arrow-left\\\", \\\"back\\\"], [\\\"Forward\\\", \\\"Forward to next view\\\", \\\"fa fa-arrow-right icon-arrow-right\\\", \\\"forward\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Pan\\\", \\\"Pan axes with left mouse, zoom with right\\\", \\\"fa fa-arrows icon-move\\\", \\\"pan\\\"], [\\\"Zoom\\\", \\\"Zoom to rectangle\\\", \\\"fa fa-square-o icon-check-empty\\\", \\\"zoom\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Download\\\", \\\"Download plot\\\", \\\"fa fa-floppy-o icon-save\\\", \\\"download\\\"]];\\n\",\n       \"\\n\",\n       \"mpl.extensions = [\\\"eps\\\", \\\"jpeg\\\", \\\"pdf\\\", \\\"png\\\", \\\"ps\\\", \\\"raw\\\", \\\"svg\\\", \\\"tif\\\"];\\n\",\n       \"\\n\",\n       \"mpl.default_extension = \\\"png\\\";var comm_websocket_adapter = function(comm) {\\n\",\n       \"    // Create a \\\"websocket\\\"-like object which calls the given IPython comm\\n\",\n       \"    // object with the appropriate methods. Currently this is a non binary\\n\",\n       \"    // socket, so there is still some room for performance tuning.\\n\",\n       \"    var ws = {};\\n\",\n       \"\\n\",\n       \"    ws.close = function() {\\n\",\n       \"        comm.close()\\n\",\n       \"    };\\n\",\n       \"    ws.send = function(m) {\\n\",\n       \"        //console.log('sending', m);\\n\",\n       \"        comm.send(m);\\n\",\n       \"    };\\n\",\n       \"    // Register the callback with on_msg.\\n\",\n       \"    comm.on_msg(function(msg) {\\n\",\n       \"        //console.log('receiving', msg['content']['data'], msg);\\n\",\n       \"        // Pass the mpl event to the overridden (by mpl) onmessage function.\\n\",\n       \"        ws.onmessage(msg['content']['data'])\\n\",\n       \"    });\\n\",\n       \"    return ws;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.mpl_figure_comm = function(comm, msg) {\\n\",\n       \"    // This is the function which gets called when the mpl process\\n\",\n       \"    // starts-up an IPython Comm through the \\\"matplotlib\\\" channel.\\n\",\n       \"\\n\",\n       \"    var id = msg.content.data.id;\\n\",\n       \"    // Get hold of the div created by the display call when the Comm\\n\",\n       \"    // socket was opened in Python.\\n\",\n       \"    var element = $(\\\"#\\\" + id);\\n\",\n       \"    var ws_proxy = comm_websocket_adapter(comm)\\n\",\n       \"\\n\",\n       \"    function ondownload(figure, format) {\\n\",\n       \"        window.open(figure.imageObj.src);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fig = new mpl.figure(id, ws_proxy,\\n\",\n       \"                           ondownload,\\n\",\n       \"                           element.get(0));\\n\",\n       \"\\n\",\n       \"    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\\n\",\n       \"    // web socket which is closed, not our websocket->open comm proxy.\\n\",\n       \"    ws_proxy.onopen();\\n\",\n       \"\\n\",\n       \"    fig.parent_element = element.get(0);\\n\",\n       \"    fig.cell_info = mpl.find_output_cell(\\\"<div id='\\\" + id + \\\"'></div>\\\");\\n\",\n       \"    if (!fig.cell_info) {\\n\",\n       \"        console.error(\\\"Failed to find cell for figure\\\", id, fig);\\n\",\n       \"        return;\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var output_index = fig.cell_info[2]\\n\",\n       \"    var cell = fig.cell_info[0];\\n\",\n       \"\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_close = function(fig, msg) {\\n\",\n       \"    var width = fig.canvas.width/mpl.ratio\\n\",\n       \"    fig.root.unbind('remove')\\n\",\n       \"\\n\",\n       \"    // Update the output cell to use the data from the current canvas.\\n\",\n       \"    fig.push_to_output();\\n\",\n       \"    var dataURL = fig.canvas.toDataURL();\\n\",\n       \"    // Re-enable the keyboard manager in IPython - without this line, in FF,\\n\",\n       \"    // the notebook keyboard shortcuts fail.\\n\",\n       \"    IPython.keyboard_manager.enable()\\n\",\n       \"    $(fig.parent_element).html('<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">');\\n\",\n       \"    fig.close_ws(fig, msg);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.close_ws = function(fig, msg){\\n\",\n       \"    fig.send_message('closing', msg);\\n\",\n       \"    // fig.ws.close()\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.push_to_output = function(remove_interactive) {\\n\",\n       \"    // Turn the data on the canvas into data in the output cell.\\n\",\n       \"    var width = this.canvas.width/mpl.ratio\\n\",\n       \"    var dataURL = this.canvas.toDataURL();\\n\",\n       \"    this.cell_info[1]['text/html'] = '<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">';\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Tell IPython that the notebook contents must change.\\n\",\n       \"    IPython.notebook.set_dirty(true);\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"    var fig = this;\\n\",\n       \"    // Wait a second, then push the new image to the DOM so\\n\",\n       \"    // that it is saved nicely (might be nice to debounce this).\\n\",\n       \"    setTimeout(function () { fig.push_to_output() }, 1000);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>')\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items){\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) { continue; };\\n\",\n       \"\\n\",\n       \"        var button = $('<button class=\\\"btn btn-default\\\" href=\\\"#\\\" title=\\\"' + name + '\\\"><i class=\\\"fa ' + image + ' fa-lg\\\"></i></button>');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add the status bar.\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\" style=\\\"text-align:right; float: right;\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"\\n\",\n       \"    // Add the close button to the window.\\n\",\n       \"    var buttongrp = $('<div class=\\\"btn-group inline pull-right\\\"></div>');\\n\",\n       \"    var button = $('<button class=\\\"btn btn-mini btn-primary\\\" href=\\\"#\\\" title=\\\"Stop Interaction\\\"><i class=\\\"fa fa-power-off icon-remove icon-large\\\"></i></button>');\\n\",\n       \"    button.click(function (evt) { fig.handle_close(fig, {}); } );\\n\",\n       \"    button.mouseover('Stop Interaction', toolbar_mouse_event);\\n\",\n       \"    buttongrp.append(button);\\n\",\n       \"    var titlebar = this.root.find($('.ui-dialog-titlebar'));\\n\",\n       \"    titlebar.prepend(buttongrp);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(el){\\n\",\n       \"    var fig = this\\n\",\n       \"    el.on(\\\"remove\\\", function(){\\n\",\n       \"\\tfig.close_ws(fig, {});\\n\",\n       \"    });\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(el){\\n\",\n       \"    // this is important to make the div 'focusable\\n\",\n       \"    el.attr('tabindex', 0)\\n\",\n       \"    // reach out to IPython and tell the keyboard manager to turn it's self\\n\",\n       \"    // off when our div gets focus\\n\",\n       \"\\n\",\n       \"    // location in version 3\\n\",\n       \"    if (IPython.notebook.keyboard_manager) {\\n\",\n       \"        IPython.notebook.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"    else {\\n\",\n       \"        // location in version 2\\n\",\n       \"        IPython.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    var manager = IPython.notebook.keyboard_manager;\\n\",\n       \"    if (!manager)\\n\",\n       \"        manager = IPython.keyboard_manager;\\n\",\n       \"\\n\",\n       \"    // Check for shift+enter\\n\",\n       \"    if (event.shiftKey && event.which == 13) {\\n\",\n       \"        this.canvas_div.blur();\\n\",\n       \"        event.shiftKey = false;\\n\",\n       \"        // Send a \\\"J\\\" for go to next cell\\n\",\n       \"        event.which = 74;\\n\",\n       \"        event.keyCode = 74;\\n\",\n       \"        manager.command_mode();\\n\",\n       \"        manager.handle_keydown(event);\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    fig.ondownload(fig, null);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.find_output_cell = function(html_output) {\\n\",\n       \"    // Return the cell and output element which can be found *uniquely* in the notebook.\\n\",\n       \"    // Note - this is a bit hacky, but it is done because the \\\"notebook_saving.Notebook\\\"\\n\",\n       \"    // IPython event is triggered only after the cells have been serialised, which for\\n\",\n       \"    // our purposes (turning an active figure into a static one), is too late.\\n\",\n       \"    var cells = IPython.notebook.get_cells();\\n\",\n       \"    var ncells = cells.length;\\n\",\n       \"    for (var i=0; i<ncells; i++) {\\n\",\n       \"        var cell = cells[i];\\n\",\n       \"        if (cell.cell_type === 'code'){\\n\",\n       \"            for (var j=0; j<cell.output_area.outputs.length; j++) {\\n\",\n       \"                var data = cell.output_area.outputs[j];\\n\",\n       \"                if (data.data) {\\n\",\n       \"                    // IPython >= 3 moved mimebundle to data attribute of output\\n\",\n       \"                    data = data.data;\\n\",\n       \"                }\\n\",\n       \"                if (data['text/html'] == html_output) {\\n\",\n       \"                    return [cell, data, j];\\n\",\n       \"                }\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// Register the function which deals with the matplotlib target/channel.\\n\",\n       \"// The kernel may be null if the page has been refreshed.\\n\",\n       \"if (IPython.notebook.kernel != null) {\\n\",\n       \"    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\\n\",\n       \"}\\n\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.Javascript object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"text/html\": [\n       \"<img src=\\\"data:image/png;base64,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\\\" width=\\\"639.8333333333334\\\">\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.HTML object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"application/javascript\": [\n       \"/* Put everything inside the global mpl namespace */\\n\",\n       \"window.mpl = {};\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.get_websocket_type = function() {\\n\",\n       \"    if (typeof(WebSocket) !== 'undefined') {\\n\",\n       \"        return WebSocket;\\n\",\n       \"    } else if (typeof(MozWebSocket) !== 'undefined') {\\n\",\n       \"        return MozWebSocket;\\n\",\n       \"    } else {\\n\",\n       \"        alert('Your browser does not have WebSocket support.' +\\n\",\n       \"              'Please try Chrome, Safari or Firefox ≥ 6. ' +\\n\",\n       \"              'Firefox 4 and 5 are also supported but you ' +\\n\",\n       \"              'have to enable WebSockets in about:config.');\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\\n\",\n       \"    this.id = figure_id;\\n\",\n       \"\\n\",\n       \"    this.ws = websocket;\\n\",\n       \"\\n\",\n       \"    this.supports_binary = (this.ws.binaryType != undefined);\\n\",\n       \"\\n\",\n       \"    if (!this.supports_binary) {\\n\",\n       \"        var warnings = document.getElementById(\\\"mpl-warnings\\\");\\n\",\n       \"        if (warnings) {\\n\",\n       \"            warnings.style.display = 'block';\\n\",\n       \"            warnings.textContent = (\\n\",\n       \"                \\\"This browser does not support binary websocket messages. \\\" +\\n\",\n       \"                    \\\"Performance may be slow.\\\");\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.imageObj = new Image();\\n\",\n       \"\\n\",\n       \"    this.context = undefined;\\n\",\n       \"    this.message = undefined;\\n\",\n       \"    this.canvas = undefined;\\n\",\n       \"    this.rubberband_canvas = undefined;\\n\",\n       \"    this.rubberband_context = undefined;\\n\",\n       \"    this.format_dropdown = undefined;\\n\",\n       \"\\n\",\n       \"    this.image_mode = 'full';\\n\",\n       \"\\n\",\n       \"    this.root = $('<div/>');\\n\",\n       \"    this._root_extra_style(this.root)\\n\",\n       \"    this.root.attr('style', 'display: inline-block');\\n\",\n       \"\\n\",\n       \"    $(parent_element).append(this.root);\\n\",\n       \"\\n\",\n       \"    this._init_header(this);\\n\",\n       \"    this._init_canvas(this);\\n\",\n       \"    this._init_toolbar(this);\\n\",\n       \"\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    this.waiting = false;\\n\",\n       \"\\n\",\n       \"    this.ws.onopen =  function () {\\n\",\n       \"            fig.send_message(\\\"supports_binary\\\", {value: fig.supports_binary});\\n\",\n       \"            fig.send_message(\\\"send_image_mode\\\", {});\\n\",\n       \"            if (mpl.ratio != 1) {\\n\",\n       \"                fig.send_message(\\\"set_dpi_ratio\\\", {'dpi_ratio': mpl.ratio});\\n\",\n       \"            }\\n\",\n       \"            fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"    this.imageObj.onload = function() {\\n\",\n       \"            if (fig.image_mode == 'full') {\\n\",\n       \"                // Full images could contain transparency (where diff images\\n\",\n       \"                // almost always do), so we need to clear the canvas so that\\n\",\n       \"                // there is no ghosting.\\n\",\n       \"                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\\n\",\n       \"            }\\n\",\n       \"            fig.context.drawImage(fig.imageObj, 0, 0);\\n\",\n       \"        };\\n\",\n       \"\\n\",\n       \"    this.imageObj.onunload = function() {\\n\",\n       \"        fig.ws.close();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    this.ws.onmessage = this._make_on_message_function(this);\\n\",\n       \"\\n\",\n       \"    this.ondownload = ondownload;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_header = function() {\\n\",\n       \"    var titlebar = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\\n\",\n       \"        'ui-helper-clearfix\\\"/>');\\n\",\n       \"    var titletext = $(\\n\",\n       \"        '<div class=\\\"ui-dialog-title\\\" style=\\\"width: 100%; ' +\\n\",\n       \"        'text-align: center; padding: 3px;\\\"/>');\\n\",\n       \"    titlebar.append(titletext)\\n\",\n       \"    this.root.append(titlebar);\\n\",\n       \"    this.header = titletext[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(canvas_div) {\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_canvas = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var canvas_div = $('<div/>');\\n\",\n       \"\\n\",\n       \"    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\\n\",\n       \"\\n\",\n       \"    function canvas_keyboard_event(event) {\\n\",\n       \"        return fig.key_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    canvas_div.keydown('key_press', canvas_keyboard_event);\\n\",\n       \"    canvas_div.keyup('key_release', canvas_keyboard_event);\\n\",\n       \"    this.canvas_div = canvas_div\\n\",\n       \"    this._canvas_extra_style(canvas_div)\\n\",\n       \"    this.root.append(canvas_div);\\n\",\n       \"\\n\",\n       \"    var canvas = $('<canvas/>');\\n\",\n       \"    canvas.addClass('mpl-canvas');\\n\",\n       \"    canvas.attr('style', \\\"left: 0; top: 0; z-index: 0; outline: 0\\\")\\n\",\n       \"\\n\",\n       \"    this.canvas = canvas[0];\\n\",\n       \"    this.context = canvas[0].getContext(\\\"2d\\\");\\n\",\n       \"\\n\",\n       \"    var backingStore = this.context.backingStorePixelRatio ||\\n\",\n       \"\\tthis.context.webkitBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.mozBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.msBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.oBackingStorePixelRatio ||\\n\",\n       \"\\tthis.context.backingStorePixelRatio || 1;\\n\",\n       \"\\n\",\n       \"    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\\n\",\n       \"\\n\",\n       \"    var rubberband = $('<canvas/>');\\n\",\n       \"    rubberband.attr('style', \\\"position: absolute; left: 0; top: 0; z-index: 1;\\\")\\n\",\n       \"\\n\",\n       \"    var pass_mouse_events = true;\\n\",\n       \"\\n\",\n       \"    canvas_div.resizable({\\n\",\n       \"        start: function(event, ui) {\\n\",\n       \"            pass_mouse_events = false;\\n\",\n       \"        },\\n\",\n       \"        resize: function(event, ui) {\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"        stop: function(event, ui) {\\n\",\n       \"            pass_mouse_events = true;\\n\",\n       \"            fig.request_resize(ui.size.width, ui.size.height);\\n\",\n       \"        },\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function mouse_event_fn(event) {\\n\",\n       \"        if (pass_mouse_events)\\n\",\n       \"            return fig.mouse_event(event, event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    rubberband.mousedown('button_press', mouse_event_fn);\\n\",\n       \"    rubberband.mouseup('button_release', mouse_event_fn);\\n\",\n       \"    // Throttle sequential mouse events to 1 every 20ms.\\n\",\n       \"    rubberband.mousemove('motion_notify', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    rubberband.mouseenter('figure_enter', mouse_event_fn);\\n\",\n       \"    rubberband.mouseleave('figure_leave', mouse_event_fn);\\n\",\n       \"\\n\",\n       \"    canvas_div.on(\\\"wheel\\\", function (event) {\\n\",\n       \"        event = event.originalEvent;\\n\",\n       \"        event['data'] = 'scroll'\\n\",\n       \"        if (event.deltaY < 0) {\\n\",\n       \"            event.step = 1;\\n\",\n       \"        } else {\\n\",\n       \"            event.step = -1;\\n\",\n       \"        }\\n\",\n       \"        mouse_event_fn(event);\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    canvas_div.append(canvas);\\n\",\n       \"    canvas_div.append(rubberband);\\n\",\n       \"\\n\",\n       \"    this.rubberband = rubberband;\\n\",\n       \"    this.rubberband_canvas = rubberband[0];\\n\",\n       \"    this.rubberband_context = rubberband[0].getContext(\\\"2d\\\");\\n\",\n       \"    this.rubberband_context.strokeStyle = \\\"#000000\\\";\\n\",\n       \"\\n\",\n       \"    this._resize_canvas = function(width, height) {\\n\",\n       \"        // Keep the size of the canvas, canvas container, and rubber band\\n\",\n       \"        // canvas in synch.\\n\",\n       \"        canvas_div.css('width', width)\\n\",\n       \"        canvas_div.css('height', height)\\n\",\n       \"\\n\",\n       \"        canvas.attr('width', width * mpl.ratio);\\n\",\n       \"        canvas.attr('height', height * mpl.ratio);\\n\",\n       \"        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\\n\",\n       \"\\n\",\n       \"        rubberband.attr('width', width);\\n\",\n       \"        rubberband.attr('height', height);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Set the figure to an initial 600x600px, this will subsequently be updated\\n\",\n       \"    // upon first draw.\\n\",\n       \"    this._resize_canvas(600, 600);\\n\",\n       \"\\n\",\n       \"    // Disable right mouse context menu.\\n\",\n       \"    $(this.rubberband_canvas).bind(\\\"contextmenu\\\",function(e){\\n\",\n       \"        return false;\\n\",\n       \"    });\\n\",\n       \"\\n\",\n       \"    function set_focus () {\\n\",\n       \"        canvas.focus();\\n\",\n       \"        canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    window.setTimeout(set_focus, 100);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>')\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items) {\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) {\\n\",\n       \"            // put a spacer in here.\\n\",\n       \"            continue;\\n\",\n       \"        }\\n\",\n       \"        var button = $('<button/>');\\n\",\n       \"        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\\n\",\n       \"                        'ui-button-icon-only');\\n\",\n       \"        button.attr('role', 'button');\\n\",\n       \"        button.attr('aria-disabled', 'false');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"\\n\",\n       \"        var icon_img = $('<span/>');\\n\",\n       \"        icon_img.addClass('ui-button-icon-primary ui-icon');\\n\",\n       \"        icon_img.addClass(image);\\n\",\n       \"        icon_img.addClass('ui-corner-all');\\n\",\n       \"\\n\",\n       \"        var tooltip_span = $('<span/>');\\n\",\n       \"        tooltip_span.addClass('ui-button-text');\\n\",\n       \"        tooltip_span.html(tooltip);\\n\",\n       \"\\n\",\n       \"        button.append(icon_img);\\n\",\n       \"        button.append(tooltip_span);\\n\",\n       \"\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fmt_picker_span = $('<span/>');\\n\",\n       \"\\n\",\n       \"    var fmt_picker = $('<select/>');\\n\",\n       \"    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\\n\",\n       \"    fmt_picker_span.append(fmt_picker);\\n\",\n       \"    nav_element.append(fmt_picker_span);\\n\",\n       \"    this.format_dropdown = fmt_picker[0];\\n\",\n       \"\\n\",\n       \"    for (var ind in mpl.extensions) {\\n\",\n       \"        var fmt = mpl.extensions[ind];\\n\",\n       \"        var option = $(\\n\",\n       \"            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\\n\",\n       \"        fmt_picker.append(option)\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add hover states to the ui-buttons\\n\",\n       \"    $( \\\".ui-button\\\" ).hover(\\n\",\n       \"        function() { $(this).addClass(\\\"ui-state-hover\\\");},\\n\",\n       \"        function() { $(this).removeClass(\\\"ui-state-hover\\\");}\\n\",\n       \"    );\\n\",\n       \"\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\\n\",\n       \"    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\\n\",\n       \"    // which will in turn request a refresh of the image.\\n\",\n       \"    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_message = function(type, properties) {\\n\",\n       \"    properties['type'] = type;\\n\",\n       \"    properties['figure_id'] = this.id;\\n\",\n       \"    this.ws.send(JSON.stringify(properties));\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.send_draw_message = function() {\\n\",\n       \"    if (!this.waiting) {\\n\",\n       \"        this.waiting = true;\\n\",\n       \"        this.ws.send(JSON.stringify({type: \\\"draw\\\", figure_id: this.id}));\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    var format_dropdown = fig.format_dropdown;\\n\",\n       \"    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\\n\",\n       \"    fig.ondownload(fig, format);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_resize = function(fig, msg) {\\n\",\n       \"    var size = msg['size'];\\n\",\n       \"    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\\n\",\n       \"        fig._resize_canvas(size[0], size[1]);\\n\",\n       \"        fig.send_message(\\\"refresh\\\", {});\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\\n\",\n       \"    var x0 = msg['x0'] / mpl.ratio;\\n\",\n       \"    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\\n\",\n       \"    var x1 = msg['x1'] / mpl.ratio;\\n\",\n       \"    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\\n\",\n       \"    x0 = Math.floor(x0) + 0.5;\\n\",\n       \"    y0 = Math.floor(y0) + 0.5;\\n\",\n       \"    x1 = Math.floor(x1) + 0.5;\\n\",\n       \"    y1 = Math.floor(y1) + 0.5;\\n\",\n       \"    var min_x = Math.min(x0, x1);\\n\",\n       \"    var min_y = Math.min(y0, y1);\\n\",\n       \"    var width = Math.abs(x1 - x0);\\n\",\n       \"    var height = Math.abs(y1 - y0);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.clearRect(\\n\",\n       \"        0, 0, fig.canvas.width, fig.canvas.height);\\n\",\n       \"\\n\",\n       \"    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\\n\",\n       \"    // Updates the figure title.\\n\",\n       \"    fig.header.textContent = msg['label'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_cursor = function(fig, msg) {\\n\",\n       \"    var cursor = msg['cursor'];\\n\",\n       \"    switch(cursor)\\n\",\n       \"    {\\n\",\n       \"    case 0:\\n\",\n       \"        cursor = 'pointer';\\n\",\n       \"        break;\\n\",\n       \"    case 1:\\n\",\n       \"        cursor = 'default';\\n\",\n       \"        break;\\n\",\n       \"    case 2:\\n\",\n       \"        cursor = 'crosshair';\\n\",\n       \"        break;\\n\",\n       \"    case 3:\\n\",\n       \"        cursor = 'move';\\n\",\n       \"        break;\\n\",\n       \"    }\\n\",\n       \"    fig.rubberband_canvas.style.cursor = cursor;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_message = function(fig, msg) {\\n\",\n       \"    fig.message.textContent = msg['message'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_draw = function(fig, msg) {\\n\",\n       \"    // Request the server to send over a new figure.\\n\",\n       \"    fig.send_draw_message();\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\\n\",\n       \"    fig.image_mode = msg['mode'];\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Called whenever the canvas gets updated.\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// A function to construct a web socket function for onmessage handling.\\n\",\n       \"// Called in the figure constructor.\\n\",\n       \"mpl.figure.prototype._make_on_message_function = function(fig) {\\n\",\n       \"    return function socket_on_message(evt) {\\n\",\n       \"        if (evt.data instanceof Blob) {\\n\",\n       \"            /* FIXME: We get \\\"Resource interpreted as Image but\\n\",\n       \"             * transferred with MIME type text/plain:\\\" errors on\\n\",\n       \"             * Chrome.  But how to set the MIME type?  It doesn't seem\\n\",\n       \"             * to be part of the websocket stream */\\n\",\n       \"            evt.data.type = \\\"image/png\\\";\\n\",\n       \"\\n\",\n       \"            /* Free the memory for the previous frames */\\n\",\n       \"            if (fig.imageObj.src) {\\n\",\n       \"                (window.URL || window.webkitURL).revokeObjectURL(\\n\",\n       \"                    fig.imageObj.src);\\n\",\n       \"            }\\n\",\n       \"\\n\",\n       \"            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\\n\",\n       \"                evt.data);\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \\\"data:image/png;base64\\\") {\\n\",\n       \"            fig.imageObj.src = evt.data;\\n\",\n       \"            fig.updated_canvas_event();\\n\",\n       \"            fig.waiting = false;\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        var msg = JSON.parse(evt.data);\\n\",\n       \"        var msg_type = msg['type'];\\n\",\n       \"\\n\",\n       \"        // Call the  \\\"handle_{type}\\\" callback, which takes\\n\",\n       \"        // the figure and JSON message as its only arguments.\\n\",\n       \"        try {\\n\",\n       \"            var callback = fig[\\\"handle_\\\" + msg_type];\\n\",\n       \"        } catch (e) {\\n\",\n       \"            console.log(\\\"No handler for the '\\\" + msg_type + \\\"' message type: \\\", msg);\\n\",\n       \"            return;\\n\",\n       \"        }\\n\",\n       \"\\n\",\n       \"        if (callback) {\\n\",\n       \"            try {\\n\",\n       \"                // console.log(\\\"Handling '\\\" + msg_type + \\\"' message: \\\", msg);\\n\",\n       \"                callback(fig, msg);\\n\",\n       \"            } catch (e) {\\n\",\n       \"                console.log(\\\"Exception inside the 'handler_\\\" + msg_type + \\\"' callback:\\\", e, e.stack, msg);\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    };\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\\n\",\n       \"mpl.findpos = function(e) {\\n\",\n       \"    //this section is from http://www.quirksmode.org/js/events_properties.html\\n\",\n       \"    var targ;\\n\",\n       \"    if (!e)\\n\",\n       \"        e = window.event;\\n\",\n       \"    if (e.target)\\n\",\n       \"        targ = e.target;\\n\",\n       \"    else if (e.srcElement)\\n\",\n       \"        targ = e.srcElement;\\n\",\n       \"    if (targ.nodeType == 3) // defeat Safari bug\\n\",\n       \"        targ = targ.parentNode;\\n\",\n       \"\\n\",\n       \"    // jQuery normalizes the pageX and pageY\\n\",\n       \"    // pageX,Y are the mouse positions relative to the document\\n\",\n       \"    // offset() returns the position of the element relative to the document\\n\",\n       \"    var x = e.pageX - $(targ).offset().left;\\n\",\n       \"    var y = e.pageY - $(targ).offset().top;\\n\",\n       \"\\n\",\n       \"    return {\\\"x\\\": x, \\\"y\\\": y};\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"/*\\n\",\n       \" * return a copy of an object with only non-object keys\\n\",\n       \" * we need this to avoid circular references\\n\",\n       \" * http://stackoverflow.com/a/24161582/3208463\\n\",\n       \" */\\n\",\n       \"function simpleKeys (original) {\\n\",\n       \"  return Object.keys(original).reduce(function (obj, key) {\\n\",\n       \"    if (typeof original[key] !== 'object')\\n\",\n       \"        obj[key] = original[key]\\n\",\n       \"    return obj;\\n\",\n       \"  }, {});\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.mouse_event = function(event, name) {\\n\",\n       \"    var canvas_pos = mpl.findpos(event)\\n\",\n       \"\\n\",\n       \"    if (name === 'button_press')\\n\",\n       \"    {\\n\",\n       \"        this.canvas.focus();\\n\",\n       \"        this.canvas_div.focus();\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var x = canvas_pos.x * mpl.ratio;\\n\",\n       \"    var y = canvas_pos.y * mpl.ratio;\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {x: x, y: y, button: event.button,\\n\",\n       \"                             step: event.step,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"\\n\",\n       \"    /* This prevents the web browser from automatically changing to\\n\",\n       \"     * the text insertion cursor when the button is pressed.  We want\\n\",\n       \"     * to control all of the cursor setting manually through the\\n\",\n       \"     * 'cursor' event from matplotlib */\\n\",\n       \"    event.preventDefault();\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    // Handle any extra behaviour associated with a key event\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.key_event = function(event, name) {\\n\",\n       \"\\n\",\n       \"    // Prevent repeat events\\n\",\n       \"    if (name == 'key_press')\\n\",\n       \"    {\\n\",\n       \"        if (event.which === this._key)\\n\",\n       \"            return;\\n\",\n       \"        else\\n\",\n       \"            this._key = event.which;\\n\",\n       \"    }\\n\",\n       \"    if (name == 'key_release')\\n\",\n       \"        this._key = null;\\n\",\n       \"\\n\",\n       \"    var value = '';\\n\",\n       \"    if (event.ctrlKey && event.which != 17)\\n\",\n       \"        value += \\\"ctrl+\\\";\\n\",\n       \"    if (event.altKey && event.which != 18)\\n\",\n       \"        value += \\\"alt+\\\";\\n\",\n       \"    if (event.shiftKey && event.which != 16)\\n\",\n       \"        value += \\\"shift+\\\";\\n\",\n       \"\\n\",\n       \"    value += 'k';\\n\",\n       \"    value += event.which.toString();\\n\",\n       \"\\n\",\n       \"    this._key_event_extra(event, name);\\n\",\n       \"\\n\",\n       \"    this.send_message(name, {key: value,\\n\",\n       \"                             guiEvent: simpleKeys(event)});\\n\",\n       \"    return false;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onclick = function(name) {\\n\",\n       \"    if (name == 'download') {\\n\",\n       \"        this.handle_save(this, null);\\n\",\n       \"    } else {\\n\",\n       \"        this.send_message(\\\"toolbar_button\\\", {name: name});\\n\",\n       \"    }\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\\n\",\n       \"    this.message.textContent = tooltip;\\n\",\n       \"};\\n\",\n       \"mpl.toolbar_items = [[\\\"Home\\\", \\\"Reset original view\\\", \\\"fa fa-home icon-home\\\", \\\"home\\\"], [\\\"Back\\\", \\\"Back to  previous view\\\", \\\"fa fa-arrow-left icon-arrow-left\\\", \\\"back\\\"], [\\\"Forward\\\", \\\"Forward to next view\\\", \\\"fa fa-arrow-right icon-arrow-right\\\", \\\"forward\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Pan\\\", \\\"Pan axes with left mouse, zoom with right\\\", \\\"fa fa-arrows icon-move\\\", \\\"pan\\\"], [\\\"Zoom\\\", \\\"Zoom to rectangle\\\", \\\"fa fa-square-o icon-check-empty\\\", \\\"zoom\\\"], [\\\"\\\", \\\"\\\", \\\"\\\", \\\"\\\"], [\\\"Download\\\", \\\"Download plot\\\", \\\"fa fa-floppy-o icon-save\\\", \\\"download\\\"]];\\n\",\n       \"\\n\",\n       \"mpl.extensions = [\\\"eps\\\", \\\"jpeg\\\", \\\"pdf\\\", \\\"png\\\", \\\"ps\\\", \\\"raw\\\", \\\"svg\\\", \\\"tif\\\"];\\n\",\n       \"\\n\",\n       \"mpl.default_extension = \\\"png\\\";var comm_websocket_adapter = function(comm) {\\n\",\n       \"    // Create a \\\"websocket\\\"-like object which calls the given IPython comm\\n\",\n       \"    // object with the appropriate methods. Currently this is a non binary\\n\",\n       \"    // socket, so there is still some room for performance tuning.\\n\",\n       \"    var ws = {};\\n\",\n       \"\\n\",\n       \"    ws.close = function() {\\n\",\n       \"        comm.close()\\n\",\n       \"    };\\n\",\n       \"    ws.send = function(m) {\\n\",\n       \"        //console.log('sending', m);\\n\",\n       \"        comm.send(m);\\n\",\n       \"    };\\n\",\n       \"    // Register the callback with on_msg.\\n\",\n       \"    comm.on_msg(function(msg) {\\n\",\n       \"        //console.log('receiving', msg['content']['data'], msg);\\n\",\n       \"        // Pass the mpl event to the overridden (by mpl) onmessage function.\\n\",\n       \"        ws.onmessage(msg['content']['data'])\\n\",\n       \"    });\\n\",\n       \"    return ws;\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.mpl_figure_comm = function(comm, msg) {\\n\",\n       \"    // This is the function which gets called when the mpl process\\n\",\n       \"    // starts-up an IPython Comm through the \\\"matplotlib\\\" channel.\\n\",\n       \"\\n\",\n       \"    var id = msg.content.data.id;\\n\",\n       \"    // Get hold of the div created by the display call when the Comm\\n\",\n       \"    // socket was opened in Python.\\n\",\n       \"    var element = $(\\\"#\\\" + id);\\n\",\n       \"    var ws_proxy = comm_websocket_adapter(comm)\\n\",\n       \"\\n\",\n       \"    function ondownload(figure, format) {\\n\",\n       \"        window.open(figure.imageObj.src);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var fig = new mpl.figure(id, ws_proxy,\\n\",\n       \"                           ondownload,\\n\",\n       \"                           element.get(0));\\n\",\n       \"\\n\",\n       \"    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\\n\",\n       \"    // web socket which is closed, not our websocket->open comm proxy.\\n\",\n       \"    ws_proxy.onopen();\\n\",\n       \"\\n\",\n       \"    fig.parent_element = element.get(0);\\n\",\n       \"    fig.cell_info = mpl.find_output_cell(\\\"<div id='\\\" + id + \\\"'></div>\\\");\\n\",\n       \"    if (!fig.cell_info) {\\n\",\n       \"        console.error(\\\"Failed to find cell for figure\\\", id, fig);\\n\",\n       \"        return;\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    var output_index = fig.cell_info[2]\\n\",\n       \"    var cell = fig.cell_info[0];\\n\",\n       \"\\n\",\n       \"};\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_close = function(fig, msg) {\\n\",\n       \"    var width = fig.canvas.width/mpl.ratio\\n\",\n       \"    fig.root.unbind('remove')\\n\",\n       \"\\n\",\n       \"    // Update the output cell to use the data from the current canvas.\\n\",\n       \"    fig.push_to_output();\\n\",\n       \"    var dataURL = fig.canvas.toDataURL();\\n\",\n       \"    // Re-enable the keyboard manager in IPython - without this line, in FF,\\n\",\n       \"    // the notebook keyboard shortcuts fail.\\n\",\n       \"    IPython.keyboard_manager.enable()\\n\",\n       \"    $(fig.parent_element).html('<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">');\\n\",\n       \"    fig.close_ws(fig, msg);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.close_ws = function(fig, msg){\\n\",\n       \"    fig.send_message('closing', msg);\\n\",\n       \"    // fig.ws.close()\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.push_to_output = function(remove_interactive) {\\n\",\n       \"    // Turn the data on the canvas into data in the output cell.\\n\",\n       \"    var width = this.canvas.width/mpl.ratio\\n\",\n       \"    var dataURL = this.canvas.toDataURL();\\n\",\n       \"    this.cell_info[1]['text/html'] = '<img src=\\\"' + dataURL + '\\\" width=\\\"' + width + '\\\">';\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.updated_canvas_event = function() {\\n\",\n       \"    // Tell IPython that the notebook contents must change.\\n\",\n       \"    IPython.notebook.set_dirty(true);\\n\",\n       \"    this.send_message(\\\"ack\\\", {});\\n\",\n       \"    var fig = this;\\n\",\n       \"    // Wait a second, then push the new image to the DOM so\\n\",\n       \"    // that it is saved nicely (might be nice to debounce this).\\n\",\n       \"    setTimeout(function () { fig.push_to_output() }, 1000);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._init_toolbar = function() {\\n\",\n       \"    var fig = this;\\n\",\n       \"\\n\",\n       \"    var nav_element = $('<div/>')\\n\",\n       \"    nav_element.attr('style', 'width: 100%');\\n\",\n       \"    this.root.append(nav_element);\\n\",\n       \"\\n\",\n       \"    // Define a callback function for later on.\\n\",\n       \"    function toolbar_event(event) {\\n\",\n       \"        return fig.toolbar_button_onclick(event['data']);\\n\",\n       \"    }\\n\",\n       \"    function toolbar_mouse_event(event) {\\n\",\n       \"        return fig.toolbar_button_onmouseover(event['data']);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    for(var toolbar_ind in mpl.toolbar_items){\\n\",\n       \"        var name = mpl.toolbar_items[toolbar_ind][0];\\n\",\n       \"        var tooltip = mpl.toolbar_items[toolbar_ind][1];\\n\",\n       \"        var image = mpl.toolbar_items[toolbar_ind][2];\\n\",\n       \"        var method_name = mpl.toolbar_items[toolbar_ind][3];\\n\",\n       \"\\n\",\n       \"        if (!name) { continue; };\\n\",\n       \"\\n\",\n       \"        var button = $('<button class=\\\"btn btn-default\\\" href=\\\"#\\\" title=\\\"' + name + '\\\"><i class=\\\"fa ' + image + ' fa-lg\\\"></i></button>');\\n\",\n       \"        button.click(method_name, toolbar_event);\\n\",\n       \"        button.mouseover(tooltip, toolbar_mouse_event);\\n\",\n       \"        nav_element.append(button);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"    // Add the status bar.\\n\",\n       \"    var status_bar = $('<span class=\\\"mpl-message\\\" style=\\\"text-align:right; float: right;\\\"/>');\\n\",\n       \"    nav_element.append(status_bar);\\n\",\n       \"    this.message = status_bar[0];\\n\",\n       \"\\n\",\n       \"    // Add the close button to the window.\\n\",\n       \"    var buttongrp = $('<div class=\\\"btn-group inline pull-right\\\"></div>');\\n\",\n       \"    var button = $('<button class=\\\"btn btn-mini btn-primary\\\" href=\\\"#\\\" title=\\\"Stop Interaction\\\"><i class=\\\"fa fa-power-off icon-remove icon-large\\\"></i></button>');\\n\",\n       \"    button.click(function (evt) { fig.handle_close(fig, {}); } );\\n\",\n       \"    button.mouseover('Stop Interaction', toolbar_mouse_event);\\n\",\n       \"    buttongrp.append(button);\\n\",\n       \"    var titlebar = this.root.find($('.ui-dialog-titlebar'));\\n\",\n       \"    titlebar.prepend(buttongrp);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._root_extra_style = function(el){\\n\",\n       \"    var fig = this\\n\",\n       \"    el.on(\\\"remove\\\", function(){\\n\",\n       \"\\tfig.close_ws(fig, {});\\n\",\n       \"    });\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._canvas_extra_style = function(el){\\n\",\n       \"    // this is important to make the div 'focusable\\n\",\n       \"    el.attr('tabindex', 0)\\n\",\n       \"    // reach out to IPython and tell the keyboard manager to turn it's self\\n\",\n       \"    // off when our div gets focus\\n\",\n       \"\\n\",\n       \"    // location in version 3\\n\",\n       \"    if (IPython.notebook.keyboard_manager) {\\n\",\n       \"        IPython.notebook.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"    else {\\n\",\n       \"        // location in version 2\\n\",\n       \"        IPython.keyboard_manager.register_events(el);\\n\",\n       \"    }\\n\",\n       \"\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype._key_event_extra = function(event, name) {\\n\",\n       \"    var manager = IPython.notebook.keyboard_manager;\\n\",\n       \"    if (!manager)\\n\",\n       \"        manager = IPython.keyboard_manager;\\n\",\n       \"\\n\",\n       \"    // Check for shift+enter\\n\",\n       \"    if (event.shiftKey && event.which == 13) {\\n\",\n       \"        this.canvas_div.blur();\\n\",\n       \"        event.shiftKey = false;\\n\",\n       \"        // Send a \\\"J\\\" for go to next cell\\n\",\n       \"        event.which = 74;\\n\",\n       \"        event.keyCode = 74;\\n\",\n       \"        manager.command_mode();\\n\",\n       \"        manager.handle_keydown(event);\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"mpl.figure.prototype.handle_save = function(fig, msg) {\\n\",\n       \"    fig.ondownload(fig, null);\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"\\n\",\n       \"mpl.find_output_cell = function(html_output) {\\n\",\n       \"    // Return the cell and output element which can be found *uniquely* in the notebook.\\n\",\n       \"    // Note - this is a bit hacky, but it is done because the \\\"notebook_saving.Notebook\\\"\\n\",\n       \"    // IPython event is triggered only after the cells have been serialised, which for\\n\",\n       \"    // our purposes (turning an active figure into a static one), is too late.\\n\",\n       \"    var cells = IPython.notebook.get_cells();\\n\",\n       \"    var ncells = cells.length;\\n\",\n       \"    for (var i=0; i<ncells; i++) {\\n\",\n       \"        var cell = cells[i];\\n\",\n       \"        if (cell.cell_type === 'code'){\\n\",\n       \"            for (var j=0; j<cell.output_area.outputs.length; j++) {\\n\",\n       \"                var data = cell.output_area.outputs[j];\\n\",\n       \"                if (data.data) {\\n\",\n       \"                    // IPython >= 3 moved mimebundle to data attribute of output\\n\",\n       \"                    data = data.data;\\n\",\n       \"                }\\n\",\n       \"                if (data['text/html'] == html_output) {\\n\",\n       \"                    return [cell, data, j];\\n\",\n       \"                }\\n\",\n       \"            }\\n\",\n       \"        }\\n\",\n       \"    }\\n\",\n       \"}\\n\",\n       \"\\n\",\n       \"// Register the function which deals with the matplotlib target/channel.\\n\",\n       \"// The kernel may be null if the page has been refreshed.\\n\",\n       \"if (IPython.notebook.kernel != null) {\\n\",\n       \"    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\\n\",\n       \"}\\n\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.Javascript object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"text/html\": [\n       \"<img src=\\\"data:image/png;base64,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\\\" width=\\\"639.8333333333334\\\">\"\n      ],\n      \"text/plain\": [\n       \"<IPython.core.display.HTML object>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"for c in element_combinations:\\n\",\n    \"    fig, ax = plt.subplots()  \\n\",\n    \"    rdf_file_name = \\\"rdf_{0:s}_{1:s}.out\\\".format(*c)\\n\",\n    \"    rdf_data = np.loadtxt(rdf_file_name).T\\n\",\n    \"    #ax.semilogy()\\n\",\n    \"    #ax.set_ylim(1.E-4, 1.E0)\\n\",\n    \"    ax.plot(0.rdf_data[0], rdf_data[1], 'k-')\\n\",\n    \"    ec = c[0]\\n\",\n    \"    e1 = c[1]  \\n\",\n    \"    for sf in symmetry_functions:\\n\",\n    \"        if sf.parameters[\\\"type\\\"] == \\\"2\\\" and sf.parameters[\\\"ec\\\"] == ec and sf.parameters[\\\"e1\\\"] == e1:\\n\",\n    \"            ax.plot(sf.radial[0], 10*sf.radial[1], '-', label=sf.parameters[\\\"index\\\"])\\n\",\n    \"    ax.legend()\\n\",\n    \"    ax.set_title(c)\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": null,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": []\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": null,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": []\n  }\n ],\n \"metadata\": {\n  \"anaconda-cloud\": {},\n  \"kernelspec\": {\n   \"display_name\": \"Python 2\",\n   \"language\": \"python\",\n   \"name\": \"python2\"\n  },\n  \"language_info\": {\n   \"codemirror_mode\": {\n    \"name\": \"ipython\",\n    \"version\": 2\n   },\n   \"file_extension\": \".py\",\n   \"mimetype\": \"text/x-python\",\n   \"name\": \"python\",\n   \"nbconvert_exporter\": \"python\",\n   \"pygments_lexer\": \"ipython2\",\n   \"version\": \"2.7.14\"\n  }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 2\n}\n"
  }
]